{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# User Guide\n",
    "\n",
    "This notebook walks through how to use the Datawaza functions for data exploration, cleaning and modeling. It doesn't cover everything you need to do in a typical project. It just shows how you might incorporate the Datawaza functions into your existing workflow. \n",
    "\n",
    "## Table of Contents\n",
    "\n",
    "* **[Getting Started](#Getting-Started)**\n",
    "    * [Intall Datawaza](#Install-Datawaza) \n",
    "    * [Import Libraries](#Import-Libraries)\n",
    "* **[Explore](#Explore)**\n",
    "    * [Load Data](#Load-Data)\n",
    "    * [Get Unique Values](#Get-Unique-Values) - *get_unique()*\n",
    "    * [Plot Charts](#Plot-Charts) - *plot_charts()*\n",
    "        * [Categorical Distributions](#Categorical-Distributions)\n",
    "        * [Continuous Distributions](#Continuous-Distributions)\n",
    "    * [Get Outliers](#Get-Outliers) - *get_outliers()*\n",
    "    * [Load Encoded Data](#Load-Encoded-Data)\n",
    "    * [Get Correlations](#Get-Correlations) - *get_corr()*\n",
    "        * [Top Correlations](#Top-Correlations)\n",
    "        * [Top Correlations with Target](#Top-Correlations-with-Target)\n",
    "        * [Create DataFrame of Top Correlated Features](#Create-DataFrame-of-Top-Correlated-Features)\n",
    "    * [Plot Correlations](#Plot-Correlations) - *plot_corr()*\n",
    "    * [Plot 3D Chart](#Plot-3D-Chart) - *plot_3d()*\n",
    "    * [Plot Map of California](#Plot-Map-of-California) - *plot_map_ca()*\n",
    "    * [Plot Scatterplot](#Plot-Scatterplot) - *plot_scatt()*\n",
    "    * [Print ASCII Image](#Print-ASCII-Image) - *print_ascii_image()*\n",
    "* **[Clean](#Clean)**\n",
    "    * [Convert Data Types](#Convert-Data-Types) - *convert_dtypes()*\n",
    "    * [Load Data Units and Time Data](#Load-Data-Units-and-Time-Data)\n",
    "    * [Convert Data Values](#Convert-Data-Values) - *convert_data_values()*\n",
    "    * [Convert Time Values](#Convert-Time-Values) - *convert_time_values()*\n",
    "    * [Split Outliers](#Split-Outliers) - *split_outliers()*\n",
    "    * [Reduce Multicollinearity](#Reduce-Multicollinearity) - *reduce_multicollinearity()*\n",
    "* **[Model](#Model)**\n",
    "    * [Create Pipeline](#Create-Pipeline) - *create_pipeline()*\n",
    "    * [Iterate Model](#Iterate-Model) - *iterate_model()*\n",
    "        * [Create Results DataFrame](#Create-Results-DataFrame) - *create_results_df()*\n",
    "        * [Separate X and Y](#Separate-X-and-Y)\n",
    "        * [Split Train and Test](#Split-Train-and-Test)\n",
    "        * [Create Custom Configuration](#Create-Custom-Configuration)\n",
    "        * [Run Multiple Iterations](#Run-Multiple-Iterations) - *iterate_model()*\n",
    "        * [Review the Results](#Review-the-Results)\n",
    "        * [Plot the Results](#Plot-the-Results) - *plot_results()*\n",
    "        * [Examine the Final Model](#Examine-the-Final-Model)\n",
    "    * [Plot ACF Residuals](#Plot-ACF-Residuals) - *plot_acf_residuals()*\n",
    "    * [Evaluate Classification Model](#Evaluate-Classification-Model) - *eval_model()*\n",
    "        * [Separate X and Y Data](#Separate-X-and-Y-Data)\n",
    "        * [Split Train and Test Data](#Split-Train-and-Test-Data)\n",
    "        * [Build a Pipeline](#Build-a-Pipeline)\n",
    "        * [Fit the Data](#Fit-the-Data)\n",
    "        * [Make Predictions](#Make-Predictions)\n",
    "        * [Evaluate Model Performance](#Evaluate-Model-Performance) - *eval_model()*\n",
    "        * [Multi-Class Example](#Multi-Class-Example)\n",
    "    * [Compare Models](#Compare-Models) - *compare_models()*\n",
    "        * [Load and Prepare Data](#Load-and-Prepare-Data)\n",
    "        * [Identify Class Labels](#Identify-Class-Labels)\n",
    "        * [Define Configuration](#Define-Configuration)\n",
    "        * [Compare Binary Classification Models](#Compare-Binary-Classification-Models) - *compare_models()*\n",
    "        * [Review the Best Models](#Review-the-Best-Models)\n",
    "        * [Plot the Best Models](#Plot-the-Best-Models) - *plot_results()*\n",
    "        * [Compare Multi-Class Classification Models](#Compare-Multi-Class-Classification-Models) - *compare_models()*\n",
    "    * [Create Binary Classification Neural Network](#Create-Binary-Classification-Neural-Network) - *create_nn_binary*\n",
    "    * [Create Multi-Class Classification Neural Network](#Create-Multi-Class-Classification-Neural-Network) - *create_nn_multi()*\n",
    "    * [Plot Training History](#Plot-Training-History) - *plot_train_history()*\n",
    "* **[Tools](#Tools)**\n",
    "    * [Log Transform](#Log-Transform) - *log_transform()*\n",
    "    * [Check for Duplicates](#Check-for-Duplicates) - *check_for_duplicates()*\n",
    "    * [Split Dataframe](#Split-Dataframe) - *split_dataframe()*\n",
    "    * [Format Dataframe](#Format-Dataframe) - *format_df()*\n",
    "    * [Format Chart Axis as Dollars](#Format-Chart-Axis-as-Dollars) - *dollars()*\n",
    "    * [Format Chart Axis as Thousands](#Format-Chart-Axis-as-Thousands) - *thousands()*\n",
    "    * [Calculate VIF](#Calculate-VIF) - *calc_vif()*\n",
    "    * [Calculate PFI](#Calculate-PFI) - *calc_pfi()*\n",
    "    * [Extract Coefficients](#Extract-Coefficients) - *extract_coef()*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "## Getting Started\n",
    "\n",
    "### Install Datawaza\n",
    "\n",
    "Install Datawaza with pip:\n",
    "\n",
    "```pip install datawaza```\n",
    "\n",
    "Because Datawaza's functions cover a broad set of use cases, it requires a number of packages to be installed. But most of these should already be in your environment if you're doing Data Science or Machine Learning."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import Libraries\n",
    "\n",
    "You can import the entire library as follows:\n",
    "\n",
    "```import datawaza as dw```\n",
    "\n",
    "Alternatively, you can import select modules. For instance, if you only want to use the model pipeline and iteration tools:\n",
    "\n",
    "```from datawaza import model```\n",
    "\n",
    "In this guide, we'll import the complete Datawaza library and use the `dw` prefix before any of it's functions:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Data processing libraries\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "# Charting libraries\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import plotly.express as px\n",
    "from matplotlib.ticker import FuncFormatter\n",
    "\n",
    "# Modeling workflow \n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.model_selection import train_test_split, KFold, StratifiedKFold\n",
    "from sklearn.impute import SimpleImputer, KNNImputer\n",
    "from sklearn.preprocessing import (OneHotEncoder, OrdinalEncoder, PolynomialFeatures, StandardScaler,\n",
    "                                   MinMaxScaler, RobustScaler, FunctionTransformer)\n",
    "from sklearn.feature_selection import RFE, SequentialFeatureSelector\n",
    "\n",
    "# Models used in some examples\n",
    "from sklearn.linear_model import LinearRegression, LogisticRegression, Ridge\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from xgboost import XGBClassifier\n",
    "from statsmodels.tsa.seasonal import STL\n",
    "\n",
    "# Sample datasets\n",
    "from sklearn.datasets import load_iris, load_wine, load_breast_cancer, make_classification\n",
    "\n",
    "# Set environment flag to avoid TensorFlow warning\n",
    "import os\n",
    "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'\n",
    "\n",
    "# Import TensorFlow and Keras\n",
    "from keras.callbacks import EarlyStopping\n",
    "from scikeras.wrappers import KerasClassifier\n",
    "from keras.utils import to_categorical\n",
    "from keras.models import Sequential\n",
    "from keras.layers import Input, Dense\n",
    "\n",
    "# Import PyTorch\n",
    "import torch\n",
    "\n",
    "# Import Datawaza\n",
    "import datawaza as dw\n",
    "from datawaza.tools import LogTransformer"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "## Explore\n",
    "\n",
    "The `dw.explore` module provides tools to streamline exploratory data analysis.\n",
    "It contains functions to find unique values, plot distributions, detect outliers,\n",
    "extract the top correlations, and plot correlations.\n",
    "\n",
    "* [Load Data](#Load-Data)\n",
    "* [Get Unique Values](#Get-Unique-Values) - *get_unique()*\n",
    "* [Plot Charts](#Plot-Charts) - *plot_charts()*\n",
    "    * [Categorical Distributions](#Categorical-Distributions)\n",
    "    * [Continuous Distributions](#Continuous-Distributions)\n",
    "* [Get Outliers](#Get-Outliers) - *get_outliers()*\n",
    "* [Load Encoded Data](#Load-Encoded-Data)\n",
    "* [Get Correlations](#Get-Correlations) - *get_corr()*\n",
    "    * [Top Correlations](#Top-Correlations)\n",
    "    * [Top Correlations with Target](#Top-Correlations-with-Target)\n",
    "    * [Create DataFrame of Top Correlated Features](#Create-DataFrame-of-Top-Correlated-Features)\n",
    "* [Plot Correlations](#Plot-Correlations) - *plot_corr()*\n",
    "* [Plot 3D Chart](#Plot-3D-Chart) - *plot_3d()*\n",
    "* [Plot Map of California](#Plot-Map-of-California) - *plot_map_ca()*\n",
    "* [Plot Scatterplot](#Plot-Scatterplot) - *plot_scatt()*\n",
    "* [Print ASCII Image](#Print-ASCII-Image) - *print_ascii_image()*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load Data\n",
    "\n",
    "Let's load some initial data and set some display preferences."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Read in the data in CSV format\n",
    "df = pd.read_csv('data/bank-additional-full.csv', sep=';')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Set some display preferences\n",
    "pd.set_option('display.max_columns', None)\n",
    "pd.set_option('display.max_colwidth', None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>job</th>\n",
       "      <th>marital</th>\n",
       "      <th>education</th>\n",
       "      <th>default</th>\n",
       "      <th>housing</th>\n",
       "      <th>loan</th>\n",
       "      <th>contact</th>\n",
       "      <th>month</th>\n",
       "      <th>day_of_week</th>\n",
       "      <th>duration</th>\n",
       "      <th>campaign</th>\n",
       "      <th>pdays</th>\n",
       "      <th>previous</th>\n",
       "      <th>poutcome</th>\n",
       "      <th>emp.var.rate</th>\n",
       "      <th>cons.price.idx</th>\n",
       "      <th>cons.conf.idx</th>\n",
       "      <th>euribor3m</th>\n",
       "      <th>nr.employed</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>56</td>\n",
       "      <td>housemaid</td>\n",
       "      <td>married</td>\n",
       "      <td>basic.4y</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>261</td>\n",
       "      <td>1</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>1.1</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "      <td>5191.0</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>57</td>\n",
       "      <td>services</td>\n",
       "      <td>married</td>\n",
       "      <td>high.school</td>\n",
       "      <td>unknown</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>149</td>\n",
       "      <td>1</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>1.1</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "      <td>5191.0</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>37</td>\n",
       "      <td>services</td>\n",
       "      <td>married</td>\n",
       "      <td>high.school</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>226</td>\n",
       "      <td>1</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>1.1</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "      <td>5191.0</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>40</td>\n",
       "      <td>admin.</td>\n",
       "      <td>married</td>\n",
       "      <td>basic.6y</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>151</td>\n",
       "      <td>1</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>1.1</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "      <td>5191.0</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>56</td>\n",
       "      <td>services</td>\n",
       "      <td>married</td>\n",
       "      <td>high.school</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>307</td>\n",
       "      <td>1</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>1.1</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "      <td>5191.0</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age        job  marital    education  default housing loan    contact  \\\n",
       "0   56  housemaid  married     basic.4y       no      no   no  telephone   \n",
       "1   57   services  married  high.school  unknown      no   no  telephone   \n",
       "2   37   services  married  high.school       no     yes   no  telephone   \n",
       "3   40     admin.  married     basic.6y       no      no   no  telephone   \n",
       "4   56   services  married  high.school       no      no  yes  telephone   \n",
       "\n",
       "  month day_of_week  duration  campaign  pdays  previous     poutcome  \\\n",
       "0   may         mon       261         1    999         0  nonexistent   \n",
       "1   may         mon       149         1    999         0  nonexistent   \n",
       "2   may         mon       226         1    999         0  nonexistent   \n",
       "3   may         mon       151         1    999         0  nonexistent   \n",
       "4   may         mon       307         1    999         0  nonexistent   \n",
       "\n",
       "   emp.var.rate  cons.price.idx  cons.conf.idx  euribor3m  nr.employed   y  \n",
       "0           1.1          93.994          -36.4      4.857       5191.0  no  \n",
       "1           1.1          93.994          -36.4      4.857       5191.0  no  \n",
       "2           1.1          93.994          -36.4      4.857       5191.0  no  \n",
       "3           1.1          93.994          -36.4      4.857       5191.0  no  \n",
       "4           1.1          93.994          -36.4      4.857       5191.0  no  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Show the first few records of data\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 41188 entries, 0 to 41187\n",
      "Data columns (total 21 columns):\n",
      " #   Column          Non-Null Count  Dtype  \n",
      "---  ------          --------------  -----  \n",
      " 0   age             41188 non-null  int64  \n",
      " 1   job             41188 non-null  object \n",
      " 2   marital         41188 non-null  object \n",
      " 3   education       41188 non-null  object \n",
      " 4   default         41188 non-null  object \n",
      " 5   housing         41188 non-null  object \n",
      " 6   loan            41188 non-null  object \n",
      " 7   contact         41188 non-null  object \n",
      " 8   month           41188 non-null  object \n",
      " 9   day_of_week     41188 non-null  object \n",
      " 10  duration        41188 non-null  int64  \n",
      " 11  campaign        41188 non-null  int64  \n",
      " 12  pdays           41188 non-null  int64  \n",
      " 13  previous        41188 non-null  int64  \n",
      " 14  poutcome        41188 non-null  object \n",
      " 15  emp.var.rate    41188 non-null  float64\n",
      " 16  cons.price.idx  41188 non-null  float64\n",
      " 17  cons.conf.idx   41188 non-null  float64\n",
      " 18  euribor3m       41188 non-null  float64\n",
      " 19  nr.employed     41188 non-null  float64\n",
      " 20  y               41188 non-null  object \n",
      "dtypes: float64(5), int64(5), object(11)\n",
      "memory usage: 6.6+ MB\n"
     ]
    }
   ],
   "source": [
    "# Examine the data types and null counts\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create some column lists we can use to target the right kind of variables\n",
    "all_columns = list(df.columns)\n",
    "num_columns = [col for col in all_columns if df[col].dtype in ['int64', 'float64']]\n",
    "cat_columns = [col for col in all_columns if df[col].dtype in ['object', 'category', 'string']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Get Unique Values\n",
    "\n",
    "`dw.get_unique()` prints the unique values of all variables below a threshold `n`, including\n",
    "    counts and percentages.\n",
    "\n",
    "This function examines the unique values of all the variables in a DataFrame. If the number is below\n",
    "a threshold `n`, it will list their unique values. For each value, it prints out the count and percentage\n",
    "of the dataset with that value. You can change the sort, and there are options to strip single quotes\n",
    "from the variable names, or exclude NaN values. You can optionally show descriptive statistics for the\n",
    "continuous variables able the `n` threshold, or display simple plots.\n",
    "\n",
    "Use this to quickly examine the features of your dataset at the beginning of\n",
    "    exploratory data analysis. Use `df.nunique()` to first determine how many unique\n",
    "    values each variable has, and identify a number that likely separates the\n",
    "    categorical from continuous numeric variables. Then run get_unique using that\n",
    "    number as `n` (this avoids iterating over continuous data)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "duration          1544\n",
       "euribor3m          316\n",
       "age                 78\n",
       "campaign            42\n",
       "pdays               27\n",
       "cons.conf.idx       26\n",
       "cons.price.idx      26\n",
       "job                 12\n",
       "nr.employed         11\n",
       "month               10\n",
       "emp.var.rate        10\n",
       "previous             8\n",
       "education            8\n",
       "day_of_week          5\n",
       "marital              4\n",
       "default              3\n",
       "poutcome             3\n",
       "loan                 3\n",
       "housing              3\n",
       "contact              2\n",
       "y                    2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Look at unique value counts to choose an 'n' threshold between categorical and continuous\n",
    "df.nunique().sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "CATEGORICAL: Variables with unique values equal to or below: 12\n",
      "\n",
      "job has 12 unique values:\n",
      "\n",
      "    admin.              10422   25.3%\n",
      "    blue-collar         9254    22.47%\n",
      "    technician          6743    16.37%\n",
      "    services            3969    9.64%\n",
      "    management          2924    7.1%\n",
      "    retired             1720    4.18%\n",
      "    entrepreneur        1456    3.54%\n",
      "    self-employed       1421    3.45%\n",
      "    housemaid           1060    2.57%\n",
      "    unemployed          1014    2.46%\n",
      "    student             875     2.12%\n",
      "    unknown             330     0.8%\n",
      "\n",
      "marital has 4 unique values:\n",
      "\n",
      "    married        24928   60.52%\n",
      "    single         11568   28.09%\n",
      "    divorced       4612    11.2%\n",
      "    unknown        80      0.19%\n",
      "\n",
      "education has 8 unique values:\n",
      "\n",
      "    university.degree         12168   29.54%\n",
      "    high.school               9515    23.1%\n",
      "    basic.9y                  6045    14.68%\n",
      "    professional.course       5243    12.73%\n",
      "    basic.4y                  4176    10.14%\n",
      "    basic.6y                  2292    5.56%\n",
      "    unknown                   1731    4.2%\n",
      "    illiterate                18      0.04%\n",
      "\n",
      "default has 3 unique values:\n",
      "\n",
      "    no            32588   79.12%\n",
      "    unknown       8597    20.87%\n",
      "    yes           3       0.01%\n",
      "\n",
      "housing has 3 unique values:\n",
      "\n",
      "    yes           21576   52.38%\n",
      "    no            18622   45.21%\n",
      "    unknown       990     2.4%\n",
      "\n",
      "loan has 3 unique values:\n",
      "\n",
      "    no            33950   82.43%\n",
      "    yes           6248    15.17%\n",
      "    unknown       990     2.4%\n",
      "\n",
      "contact has 2 unique values:\n",
      "\n",
      "    cellular        26144   63.47%\n",
      "    telephone       15044   36.53%\n",
      "\n",
      "month has 10 unique values:\n",
      "\n",
      "    may       13769   33.43%\n",
      "    jul       7174    17.42%\n",
      "    aug       6178    15.0%\n",
      "    jun       5318    12.91%\n",
      "    nov       4101    9.96%\n",
      "    apr       2632    6.39%\n",
      "    oct       718     1.74%\n",
      "    sep       570     1.38%\n",
      "    mar       546     1.33%\n",
      "    dec       182     0.44%\n",
      "\n",
      "day_of_week has 5 unique values:\n",
      "\n",
      "    thu       8623   20.94%\n",
      "    mon       8514   20.67%\n",
      "    wed       8134   19.75%\n",
      "    tue       8090   19.64%\n",
      "    fri       7827   19.0%\n",
      "\n",
      "previous has 8 unique values:\n",
      "\n",
      "    0       35563   86.34%\n",
      "    1       4561    11.07%\n",
      "    2       754     1.83%\n",
      "    3       216     0.52%\n",
      "    4       70      0.17%\n",
      "    5       18      0.04%\n",
      "    6       5       0.01%\n",
      "    7       1       0.0%\n",
      "\n",
      "poutcome has 3 unique values:\n",
      "\n",
      "    nonexistent       35563   86.34%\n",
      "    failure           4252    10.32%\n",
      "    success           1373    3.33%\n",
      "\n",
      "emp.var.rate has 10 unique values:\n",
      "\n",
      "    1.4        16234   39.41%\n",
      "    -1.8       9184    22.3%\n",
      "    1.1        7763    18.85%\n",
      "    -0.1       3683    8.94%\n",
      "    -2.9       1663    4.04%\n",
      "    -3.4       1071    2.6%\n",
      "    -1.7       773     1.88%\n",
      "    -1.1       635     1.54%\n",
      "    -3.0       172     0.42%\n",
      "    -0.2       10      0.02%\n",
      "\n",
      "nr.employed has 11 unique values:\n",
      "\n",
      "    5228.1       16234   39.41%\n",
      "    5099.1       8534    20.72%\n",
      "    5191.0       7763    18.85%\n",
      "    5195.8       3683    8.94%\n",
      "    5076.2       1663    4.04%\n",
      "    5017.5       1071    2.6%\n",
      "    4991.6       773     1.88%\n",
      "    5008.7       650     1.58%\n",
      "    4963.6       635     1.54%\n",
      "    5023.5       172     0.42%\n",
      "    5176.3       10      0.02%\n",
      "\n",
      "y has 2 unique values:\n",
      "\n",
      "    no        36548   88.73%\n",
      "    yes       4640    11.27%\n"
     ]
    }
   ],
   "source": [
    "# Show the unique values of each variable below the threshold of n = 12\n",
    "dw.get_unique(df, 12, count=True, percent=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Plot Charts\n",
    "\n",
    "`dw.plot_charts` displays multiple bar plots and histograms for categorical and/or continuous\n",
    "    variables in a DataFrame, with an option to dimension by the specified `hue`.\n",
    "\n",
    "This function allows you to plot a large number of distributions with one line of code. You choose which type of plots to create by setting `plot_type` to `cat`, `cont`, or `both`. Categorical variables are plotted with `sns.countplot` ordered by descending value counts for a clean appearance. Continuous variables are plotted with `sns.histplot`. There are two approaches to identifying categorical vs. continuous variables: (a) you can specify `cat_cols` and `cont_cols` as lists of the respective column names, or (b) you can specify `n` as the dividing line, and any variable with `n` or lower unique values will be treated as categorical. In addition, you can enable `dtype_check` on the continuous columns to only include columns of data type `int64` or `float64`.\n",
    "\n",
    "For each type of variable, it creates a subplot layout that has `ncols`\n",
    "    columns, and is `fig_width` wide. It calculates how many rows are required to\n",
    "    display all the plots, and each row is `subplot_height` high. Specify `hue` if\n",
    "    you want to dimension the plots by another variable. You can set\n",
    "    `color_discrete_map` to a color mapping dictionary for the values of the `hue`\n",
    "    variable. You can also customize some parameters of the plots, such as\n",
    "    `rotation` of the X axis tick labels. For categorical variables, you can\n",
    "    normalize the plots to show proportions instead of counts by setting\n",
    "    `normalize` to True.\n",
    "\n",
    "For histograms, you can display KDE lines with `kde`, and change how the `hue`\n",
    "    variable appears by setting `multiple`. If you have a large amount of data that\n",
    "    is taking too long to process, you can take a random sample of your data by\n",
    "    setting `sample_size` to either a count or proportion. To handle skewed data,\n",
    "    you have two options: (a) you can enable log scale on the X axis with\n",
    "    `log_scale`, and (b) you can ignore zero values with `ignore_zero` (these can\n",
    "    sometimes dominate the left end of a chart).\n",
    "\n",
    "Use this function to quickly visualize the distributions of your data during\n",
    "    exploratory data analysis. With one line, you can produce a comprehensive\n",
    "    series of plots that can help you spot issues that will require handling during\n",
    "    data cleaning. By setting `hue` to your target y variable, you might be able to\n",
    "    catch glimpses of potential correlations or relationships.\n",
    "\n",
    "#### Categorical Distributions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
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",
      "text/plain": [
       "<Figure size 1500x2400 with 11 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot bar charts of categorical variables\n",
    "dw.plot_charts(df, plot_type='cat', cat_cols=cat_columns, rotation=90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load another dataset with a column that has a large number of categorical values\n",
    "df_telco = pd.read_csv('data/df_telco.csv', index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot a single chart for the larger value sets\n",
    "dw.plot_charts(df_telco, plot_type='cat', n=25, cat_cols=['Churn Reason'], ncols=1, fig_width=10, subplot_height=8, rotation=90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x2400 with 11 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot bar charts of categorical variables, dimensioned by the target variable\n",
    "dw.plot_charts(df, plot_type='cat', cat_cols=cat_columns, hue='y', rotation=90)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Continuous Distributions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x2000 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot histograms of continuous variables, dimensioned by the target variable\n",
    "dw.plot_charts(df, plot_type='cont', cont_cols=num_columns, hue='y', multiple='stack')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Get Outliers\n",
    "\n",
    "`dw.get_outliers()` detects and summarizes outliers for the specified numeric columns in a\n",
    "    DataFrame, based on an IQR ratio.\n",
    "\n",
    "This function identifies outliers using Tukey's method, where outliers are considered to be those data points\n",
    "that fall below Q1 - `ratio` * IQR or above Q3 + `ratio` * IQR. You can exclude zeros from the calculations,\n",
    "as they can appear as outliers and skew your results. You can also change the default IQR `ratio` of  1.5.\n",
    "If outliers are found, they will be summarized in the returned DataFrame. In addition, the distributions of\n",
    "the variables with outliers can be plotted as boxplots.\n",
    "\n",
    "Use this function to identify outliers during the early stages of exploratory\n",
    "    data analysis. With one line, you can see: total non-null, total zero values,\n",
    "    zero percent, outlier count, outlier percent, skewness, and kurtosis. You can\n",
    "    also visually spot outliers outside of the whiskers in the boxplots. Then you\n",
    "    can decide how you want to handle the outliers (ex: log transform, drop, etc.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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yZs2qa9eu3fF1zp8/L0lJjtpOa926dVP9+vVVp06dO8b16tVLJ0+e1IYNG3Ty5Ek1a9ZMp06d0rBhw/TFF1/o1q1b6tq1qwoXLqwqVaokmK5H+r9jPXfuXJocCwAASJ7Y2FjNnz9fDRo0UKVKlRKU20fV/vbbb6pSpYo11Z4kZcuWTe3bt9fRo0e1e/duh+3atGnj8IB5+wjow4cPS5I1wnzJkiXWFA+u2LZtm44cOaIePXokmHbOXtfTp09r+/btat26tfXLQUkqW7asnnnmGadTocTviz7++OM6f/78XfejY2JitGTJEjVq1EiFCxe21pcsWVJ169ZNEB8UFKSvvvpKy5Yt0+OPP67t27frm2++kZ+fX7Jf25X7hbjl9/qeYc6cOSpZsqRCQ0Md7pHsD5uPf49Us2ZNlSpVymFdQECAS9N9HD161KXR5zdv3tTbb7+tDh06JHit+Fy9t4hv5syZkuTS9C3S7XuGtLhfuHbtmtNfTtunbLTfyyTnnqdMmTI6cOCANm/erAMHDmju3Llyc3PTO++8o8aNG+uxxx7Tzz//rEcffVQhISH68MMPnU7tmCNHDu4XgHREAh2AS65du6YPPvhAhQoVkqenp3Lnzq08efIoIiLCYU7GY8eOOX2ievx1Bw4ckCQ9/fTTypMnj8O/pUuX6uzZs8muo72ja+8YO+Nqpzm12Y+3VatWCY538uTJunHjRoK5LeM/hd3T01MjRozQokWLFBgYqCeeeEIjR45UeHh4iuoUFRWlfv366d1331WhQoXuGGv/AqVZs2YO61977TVJt39GaffTTz/p0UcfVdu2bRUSEqIGDRrolVdeUfny5e84t19czjqN98qPP/6oP/74Q59++qlL8YGBgXrsscesTnyfPn1Uq1Yt1apVS0OGDNGKFSv0448/qlGjRnruuecUERHhsL39WFM6VyMAAEhd//33n6KiopKcWu3YsWMqUaJEgvX26R+OHTvmsD5uslj6vy/R7QMjQkJC1LNnT02ePFm5c+dW3bp19dVXXyU5/7l9Hus71ddel8Tqax/YkZz6ptR///2na9euqVixYgnKnNVPuj239HPPPadNmzbpzTfftKYfSS5X7hfilqfHPcOuXbsS3C8UL15ckhLcI8W/X5CkTp06qXjx4qpfv74KFiyotm3bWnOjp8Tnn3+uc+fOJflcn+TcW8RljNH333+vRx55RGXLlk3WdqnN29s7wVzzknT9+nWr3C459zxeXl6qVKmSdU+8cuVKLV26VMOHD9e+ffvUtGlT9ejRQ998843GjRvn9PlcxhjuF4B0xBzoAFzStWtXTZ06VT169FBYWJj8/f1ls9nUtGnTBCOnXWHfZsaMGQoKCkpQntSDaZyx36zs2LHDYQR8XDt27JAka/REYp0QZw/IvBv24x01alSidYvf0XL2wMsePXqoQYMGmj9/vpYsWaIBAwZo2LBhWrlyZbLnAPzkk0908+ZNvfrqq9boE/vDVS9evKijR48qf/788vDwUP78+SUpwbyUefPmteLtChQooHXr1unAgQMKDw9XsWLFFBQUpPz581ud/8TkypUrwf7utXfffVdNmjSRh4eH1S72pPeJEyd08+ZNqz3i27hxo+bOnat//vlH0u2HIQ0YMEBhYWEKCwvT119/rYULFzo8UMl+rPZ59QEAQObk7u7udH3cROCnn36q1q1ba8GCBVq6dKm6deumYcOGaePGjSpYsOC9qqok1+p7r5w/f15btmyRJO3evVuxsbFyc0v+eEB/f3/ly5fPuidIzI4dO1SgQAFrlPu9vGcoU6aMPvvsM6fl8RPTzu4X8ubNq+3bt2vJkiVatGiRFi1apKlTp6ply5aaPn16suoTGRmpjz76SJ06dVJUVJQ1Iv/y5csyxujo0aPy8fFR3rx5k3VvEdf69et17Ngxax59V+TKlStN7hfy5cunVatWJUhWnz59WpIc7gFSes8TExOj7t27q2/fvipQoICGDBmiatWqqU2bNpKkt956SzNnzrSW7S5evOj0SycA9wYJdAAumTt3rlq1auUwKvf69esJRtMGBwfr4MGDCbaPv87+MJ28efM6fXp6StSvX1/u7u6aMWNGog8S/fbbb5UlSxbVq1dP0v+NpIl/HPFHDEl3N0LYfrx+fn53fbwPPfSQ3nnnHb3zzjs6cOCAypUrp08//VTfffddsvZz/PhxXbx4UaVLl05QNnToUA0dOlTbtm1TuXLlVLFiRU2aNEknT550iDt16pQk5w9TLVasmNXJ2717t06fPp3ktDKFCxeWt7e3jhw5kqxjSU0nTpzQ999/r++//z5BWYUKFfToo49q+/btCcqMMerWrZu6d+9une9Tp045dLTz58+foA3tx+rqQ7cAAEDaypMnj/z8/KwvxBMTHBysffv2JVi/d+9eqzwlypQpozJlyuj999/XH3/8oerVq2vChAn66KOPnMbb+x3//PNPov1Me10Sq2/u3Lnl6+ubovomV548eeTt7W39QjMuZ/WTpM6dO+vSpUsaNmyY+vXrpy+++EI9e/ZM0es///zzmjRpktatW+cw/Y7d77//rqNHj+qtt96y1uXIkSPB/YKUNvcMf//9t2rVqnVX+/Hw8FCDBg3UoEEDxcbGqlOnTvr66681YMAAp78WTszFixd1+fJljRw5UiNHjkxQHhISooYNG2r+/PnJureIa+bMmbLZbNYvW10RGhqqmTNnKjIy8o4P102ucuXKafLkydqzZ4/DdDX2B/06GwiV3Hue8ePH69KlS+rVq5ck1+4Xbt26pRMnTuiFF15I6aEBuEtM4QLAJe7u7glGm4wZMybBqIu6detqw4YNDgnGCxcuWPPaxY3z8/PT0KFDFR0dneD1/vvvv2TXsVChQmrTpo2WL1+u8ePHJyifMGGCVq5cqXbt2lkjePz8/JQ7d26tXbvWIXbcuHEJtrffVDjrPCelYsWKeuihh/TJJ59Y84nH5crxXr161fr5oN1DDz2k7NmzO/zUMDIyUnv37k3y577dunXTvHnzHP59/fXXkm7Poz5v3jzrZ6ENGzaUp6enpk6d6vCLg8mTJ0uSnnnmmURfJzY2Vr1795aPj0+CuTTjy5o1qypVqmSNMEqpQ4cOWT9nTq74bTJv3jy9+uqrkm5/AfP555873W7atGk6ceKE+vfvb60LDAy0bqKjo6N18ODBBL+42Lp1q/z9/Z3ebAAAgHvPzc1NjRo10q+//uq0T2LvEz/77LPatGmTNmzYYJVduXJFEydOVJEiRZKcLzq+qKgo3bp1y2FdmTJl5Obm5tDXO378uNW/kG5/wR8SEqIvvvgi0ani8uXLp3Llymn69OkOMf/884+WLl2qZ599Nll1TUx0dLT27t1rjdh1xt3dXXXr1rWSrnZ79uzRkiVLEsTPnTtXP/74o4YPH66+ffuqadOmev/997V///4U1fHdd9+Vt7e33nrrLev5O3YXLlxQhw4d5OPjo3fffdda/9BDDykyMtJh5Prp06c1b968BPv39fVN0f2CJL3yyis6efKkJk2alKDs2rVrCabZcSb+Mbm5uVlTo8S9jlzpL+fNm9dp3/ipp56Sl5eX5s2bp379+klK3r2FXXR0tObMmaMaNWokmDLoTsLCwmSM0datW13eJj5n90wNGzZU1qxZHe4FjTGaMGGCChQooGrVqiW6P1fueS5cuKCBAwdq1KhR1rzqce8XpNvvg/j3C7t379b169fv+PoA0hYj0AG45Pnnn9eMGTPk7++vUqVKacOGDVq+fLk15YZd79699d133+mZZ55R165d5evrq8mTJ6tw4cK6cOGCNZLCz89P48ePV4sWLVShQgU1bdpUefLk0fHjx/W///1P1atX19ixYyXdfsBNSEiIWrVq5XQ+uLg+//xz7d27V506ddLixYutkeZLlizRggULVLNmzQRzW7/xxhsaPny43njjDVWqVElr16512iGvWLGiJKl///5q2rSpsmbNqgYNGrg0WsfNzU2TJ09W/fr1Vbp0abVp00YFChTQyZMntWrVKvn5+enXX3+94z7279+vWrVq6ZVXXlGpUqWUJUsWzZs3T2fOnFHTpk2tuHnz5qlNmzaaOnXqHUc/VKhQQRUqVHBYZ/+5ZenSpdWoUSNrfVBQkPr3768PPvhA9erVU6NGjfT3339r0qRJatasmSpXrmzFdu/eXdevX1e5cuUUHR2t77//Xps2bdL06dNd6hg3bNhQ/fv3V1RUlMPDoSIjIzVmzBhJsh7GOXbsWAUEBCggIEBdunSxYu3zYsZ9MNKxY8c0Y8YMSbJuhu0juYKDg9WiRQtJcjhuO/sXQvXr13c61cqlS5f03nvvaejQoQ5zZb788sv68MMPFRsbq/Xr1+v69esJblCXLVumBg0aMKchAAD3kaFDh2rp0qWqWbOm2rdvr5IlS+r06dOaM2eO1q1bp4CAAPXt21c//PCD6tevr27duilnzpyaPn26jhw5op9++inZU4ysXLlSXbp0UZMmTVS8eHHdunVLM2bMkLu7uxo3bmzFtWzZUmvWrLGS425ubho/frwaNGigcuXKqU2bNsqXL5/27t2rXbt2WUnpUaNGqX79+goLC1O7du107do1jRkzRv7+/ho0aFCqtNvJkydVsmTJJPvtgwcP1uLFi/X444+rU6dOunXrlsaMGaPSpUs7JKnPnj2rjh076qmnnrL6emPHjtWqVavUunVrrVu3zmrn1q1bW+1fpEiRRF+7WLFimj59upo3b64yZcqoXbt2CgkJ0dGjRzVlyhSdO3dOP/zwgzWyX7o9B3ufPn304osvqlu3brp69arGjx+v4sWL66+//nLYf8WKFbV8+XJ99tlnyp8/v0JCQlS1alWX2q9FixaaPXu2OnTooFWrVql69eqKiYnR3r17NXv2bC1ZssTpg23jeuONN3ThwgU9/fTTKliwoI4dO6YxY8aoXLlyDr94dNZfjs/Hx8dp33j+/PnatGmTQ1l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      "text/plain": [
       "<Figure size 1500x600 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Identify outliers, store in dataframe, and plot boxplots\n",
    "outliers_df = dw.get_outliers(df, num_columns, plot=True, width=15, height=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Column</th>\n",
       "      <th>Total Non-Null</th>\n",
       "      <th>Total Zero</th>\n",
       "      <th>Zero Percent</th>\n",
       "      <th>Outlier Count</th>\n",
       "      <th>Outlier Percent</th>\n",
       "      <th>Skewness</th>\n",
       "      <th>Kurtosis</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>previous</td>\n",
       "      <td>41188</td>\n",
       "      <td>35563</td>\n",
       "      <td>86.34</td>\n",
       "      <td>5625</td>\n",
       "      <td>13.66</td>\n",
       "      <td>3.83</td>\n",
       "      <td>20.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>duration</td>\n",
       "      <td>41188</td>\n",
       "      <td>4</td>\n",
       "      <td>0.01</td>\n",
       "      <td>2963</td>\n",
       "      <td>7.19</td>\n",
       "      <td>3.26</td>\n",
       "      <td>20.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>campaign</td>\n",
       "      <td>41188</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2406</td>\n",
       "      <td>5.84</td>\n",
       "      <td>4.76</td>\n",
       "      <td>36.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>pdays</td>\n",
       "      <td>41188</td>\n",
       "      <td>15</td>\n",
       "      <td>0.04</td>\n",
       "      <td>1515</td>\n",
       "      <td>3.68</td>\n",
       "      <td>-4.92</td>\n",
       "      <td>22.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>age</td>\n",
       "      <td>41188</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>469</td>\n",
       "      <td>1.14</td>\n",
       "      <td>0.78</td>\n",
       "      <td>0.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>cons.conf.idx</td>\n",
       "      <td>41188</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>447</td>\n",
       "      <td>1.09</td>\n",
       "      <td>0.30</td>\n",
       "      <td>-0.36</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Column  Total Non-Null  Total Zero  Zero Percent  Outlier Count  \\\n",
       "4       previous           41188       35563         86.34           5625   \n",
       "1       duration           41188           4          0.01           2963   \n",
       "2       campaign           41188           0          0.00           2406   \n",
       "3          pdays           41188          15          0.04           1515   \n",
       "0            age           41188           0          0.00            469   \n",
       "5  cons.conf.idx           41188           0          0.00            447   \n",
       "\n",
       "   Outlier Percent  Skewness  Kurtosis  \n",
       "4            13.66      3.83     20.11  \n",
       "1             7.19      3.26     20.25  \n",
       "2             5.84      4.76     36.98  \n",
       "3             3.68     -4.92     22.23  \n",
       "0             1.14      0.78      0.79  \n",
       "5             1.09      0.30     -0.36  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Display the dataframe with the output from detect_outliers\n",
    "outliers_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Store the outlier columns in a list for easy reference\n",
    "outlier_columns = list(outliers_df['Column'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['previous', 'duration', 'campaign', 'pdays', 'age', 'cons.conf.idx']"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Show the outlier column list values\n",
    "outlier_columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load Encoded Data\n",
    "\n",
    "Let's now load some encoded data, where everything is numeric, so we can demonstrate the correlation functions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load a previously cleaned and encoded dataset (processing not shown here)\n",
    "df_enc = pd.read_csv('data/df_enc.csv')\n",
    "df_enc.drop(['subscribed'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>duration</th>\n",
       "      <th>campaign</th>\n",
       "      <th>pdays</th>\n",
       "      <th>previous</th>\n",
       "      <th>emp.var.rate</th>\n",
       "      <th>cons.price.idx</th>\n",
       "      <th>cons.conf.idx</th>\n",
       "      <th>euribor3m</th>\n",
       "      <th>nr.employed</th>\n",
       "      <th>previously_contacted</th>\n",
       "      <th>subscribed_enc</th>\n",
       "      <th>job_admin.</th>\n",
       "      <th>job_blue-collar</th>\n",
       "      <th>job_entrepreneur</th>\n",
       "      <th>job_housemaid</th>\n",
       "      <th>job_management</th>\n",
       "      <th>job_retired</th>\n",
       "      <th>job_self-employed</th>\n",
       "      <th>job_services</th>\n",
       "      <th>job_student</th>\n",
       "      <th>job_technician</th>\n",
       "      <th>job_unemployed</th>\n",
       "      <th>job_unknown</th>\n",
       "      <th>marital_divorced</th>\n",
       "      <th>marital_married</th>\n",
       "      <th>marital_single</th>\n",
       "      <th>marital_unknown</th>\n",
       "      <th>education_basic.4y</th>\n",
       "      <th>education_basic.6y</th>\n",
       "      <th>education_basic.9y</th>\n",
       "      <th>education_high.school</th>\n",
       "      <th>education_illiterate</th>\n",
       "      <th>education_professional.course</th>\n",
       "      <th>education_university.degree</th>\n",
       "      <th>education_unknown</th>\n",
       "      <th>month_apr</th>\n",
       "      <th>month_aug</th>\n",
       "      <th>month_dec</th>\n",
       "      <th>month_jul</th>\n",
       "      <th>month_jun</th>\n",
       "      <th>month_mar</th>\n",
       "      <th>month_may</th>\n",
       "      <th>month_nov</th>\n",
       "      <th>month_oct</th>\n",
       "      <th>month_sep</th>\n",
       "      <th>day_of_week_fri</th>\n",
       "      <th>day_of_week_mon</th>\n",
       "      <th>day_of_week_thu</th>\n",
       "      <th>day_of_week_tue</th>\n",
       "      <th>day_of_week_wed</th>\n",
       "      <th>poutcome_failure</th>\n",
       "      <th>poutcome_nonexistent</th>\n",
       "      <th>poutcome_success</th>\n",
       "      <th>no_default_1</th>\n",
       "      <th>housing_yes</th>\n",
       "      <th>loan_yes</th>\n",
       "      <th>contact_telephone</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>56</td>\n",
       "      <td>261</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.1</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "      <td>5191.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>57</td>\n",
       "      <td>149</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.1</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "      <td>5191.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>37</td>\n",
       "      <td>226</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.1</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "      <td>5191.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>40</td>\n",
       "      <td>151</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.1</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "      <td>5191.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>56</td>\n",
       "      <td>307</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.1</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "      <td>5191.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age  duration  campaign  pdays  previous  emp.var.rate  cons.price.idx  \\\n",
       "0   56       261         1      0         0           1.1          93.994   \n",
       "1   57       149         1      0         0           1.1          93.994   \n",
       "2   37       226         1      0         0           1.1          93.994   \n",
       "3   40       151         1      0         0           1.1          93.994   \n",
       "4   56       307         1      0         0           1.1          93.994   \n",
       "\n",
       "   cons.conf.idx  euribor3m  nr.employed  previously_contacted  \\\n",
       "0          -36.4      4.857       5191.0                     0   \n",
       "1          -36.4      4.857       5191.0                     0   \n",
       "2          -36.4      4.857       5191.0                     0   \n",
       "3          -36.4      4.857       5191.0                     0   \n",
       "4          -36.4      4.857       5191.0                     0   \n",
       "\n",
       "   subscribed_enc  job_admin.  job_blue-collar  job_entrepreneur  \\\n",
       "0               0           0                0                 0   \n",
       "1               0           0                0                 0   \n",
       "2               0           0                0                 0   \n",
       "3               0           1                0                 0   \n",
       "4               0           0                0                 0   \n",
       "\n",
       "   job_housemaid  job_management  job_retired  job_self-employed  \\\n",
       "0              1               0            0                  0   \n",
       "1              0               0            0                  0   \n",
       "2              0               0            0                  0   \n",
       "3              0               0            0                  0   \n",
       "4              0               0            0                  0   \n",
       "\n",
       "   job_services  job_student  job_technician  job_unemployed  job_unknown  \\\n",
       "0             0            0               0               0            0   \n",
       "1             1            0               0               0            0   \n",
       "2             1            0               0               0            0   \n",
       "3             0            0               0               0            0   \n",
       "4             1            0               0               0            0   \n",
       "\n",
       "   marital_divorced  marital_married  marital_single  marital_unknown  \\\n",
       "0                 0                1               0                0   \n",
       "1                 0                1               0                0   \n",
       "2                 0                1               0                0   \n",
       "3                 0                1               0                0   \n",
       "4                 0                1               0                0   \n",
       "\n",
       "   education_basic.4y  education_basic.6y  education_basic.9y  \\\n",
       "0                   1                   0                   0   \n",
       "1                   0                   0                   0   \n",
       "2                   0                   0                   0   \n",
       "3                   0                   1                   0   \n",
       "4                   0                   0                   0   \n",
       "\n",
       "   education_high.school  education_illiterate  education_professional.course  \\\n",
       "0                      0                     0                              0   \n",
       "1                      1                     0                              0   \n",
       "2                      1                     0                              0   \n",
       "3                      0                     0                              0   \n",
       "4                      1                     0                              0   \n",
       "\n",
       "   education_university.degree  education_unknown  month_apr  month_aug  \\\n",
       "0                            0                  0          0          0   \n",
       "1                            0                  0          0          0   \n",
       "2                            0                  0          0          0   \n",
       "3                            0                  0          0          0   \n",
       "4                            0                  0          0          0   \n",
       "\n",
       "   month_dec  month_jul  month_jun  month_mar  month_may  month_nov  \\\n",
       "0          0          0          0          0          1          0   \n",
       "1          0          0          0          0          1          0   \n",
       "2          0          0          0          0          1          0   \n",
       "3          0          0          0          0          1          0   \n",
       "4          0          0          0          0          1          0   \n",
       "\n",
       "   month_oct  month_sep  day_of_week_fri  day_of_week_mon  day_of_week_thu  \\\n",
       "0          0          0                0                1                0   \n",
       "1          0          0                0                1                0   \n",
       "2          0          0                0                1                0   \n",
       "3          0          0                0                1                0   \n",
       "4          0          0                0                1                0   \n",
       "\n",
       "   day_of_week_tue  day_of_week_wed  poutcome_failure  poutcome_nonexistent  \\\n",
       "0                0                0                 0                     1   \n",
       "1                0                0                 0                     1   \n",
       "2                0                0                 0                     1   \n",
       "3                0                0                 0                     1   \n",
       "4                0                0                 0                     1   \n",
       "\n",
       "   poutcome_success  no_default_1  housing_yes  loan_yes  contact_telephone  \n",
       "0                 0             1            0         0                  1  \n",
       "1                 0             0            0         0                  1  \n",
       "2                 0             1            1         0                  1  \n",
       "3                 0             1            0         0                  1  \n",
       "4                 0             1            0         1                  1  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_enc.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Get Correlations\n",
    "\n",
    "`dw.get_corr()` displays the top `n` positive and negative correlations with a target variable\n",
    "    in a DataFrame.\n",
    "\n",
    "This function computes the correlation matrix for the provided DataFrame, and\n",
    "    identifies the top `n` positively and negatively correlated pairs of variables.\n",
    "    By default, it prints a summary of these correlations. Optionally, it can\n",
    "    return arrays of the variable names involved in these top correlations,\n",
    "    avoiding duplicates.\n",
    "\n",
    "Use this to quickly identify the strongest correlations with a target variable.\n",
    "    You can also use this to reduce a DataFrame with a large number of features\n",
    "    down to just the top `n` correlated features. Extract the names of the top\n",
    "    correlated features into 2 separate arrays (one for positive, one for\n",
    "    negative). Concatenate those variable lists and append the target variable. Use\n",
    "    this concatenated array to create a new DataFrame."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Top Correlations\n",
    "\n",
    "We can start by just listing the top correlations between all variables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Top 20 positive correlations:\n",
      "                       Variable 1            Variable 2  Correlation\n",
      "0                    emp.var.rate             euribor3m         0.97\n",
      "1                       euribor3m           nr.employed         0.95\n",
      "2                poutcome_success  previously_contacted         0.95\n",
      "3                    emp.var.rate           nr.employed         0.91\n",
      "4                           pdays  previously_contacted         0.84\n",
      "5                  cons.price.idx          emp.var.rate         0.78\n",
      "6                           pdays      poutcome_success         0.74\n",
      "7                  cons.price.idx             euribor3m         0.69\n",
      "8                poutcome_failure              previous         0.68\n",
      "9                        previous  previously_contacted         0.59\n",
      "10                 cons.price.idx     contact_telephone         0.59\n",
      "11               poutcome_success              previous         0.52\n",
      "12                 cons.price.idx           nr.employed         0.52\n",
      "13                    nr.employed  poutcome_nonexistent         0.49\n",
      "14                      euribor3m  poutcome_nonexistent         0.49\n",
      "15                          pdays              previous         0.48\n",
      "16  education_professional.course        job_technician         0.48\n",
      "17                   emp.var.rate  poutcome_nonexistent         0.47\n",
      "18                  cons.conf.idx             month_aug         0.45\n",
      "19                            age           job_retired         0.44\n",
      "\n",
      "Top 20 negative correlations:\n",
      "                     Variable 1                   Variable 2  Correlation\n",
      "0          poutcome_nonexistent                     previous        -0.88\n",
      "1              poutcome_failure         poutcome_nonexistent        -0.85\n",
      "2               marital_married               marital_single        -0.77\n",
      "3                   nr.employed                     previous        -0.50\n",
      "4          poutcome_nonexistent         previously_contacted        -0.49\n",
      "5          poutcome_nonexistent             poutcome_success        -0.47\n",
      "6                     euribor3m                     previous        -0.45\n",
      "7              marital_divorced              marital_married        -0.44\n",
      "8                  emp.var.rate                     previous        -0.42\n",
      "9                           age               marital_single        -0.41\n",
      "10                        pdays         poutcome_nonexistent        -0.41\n",
      "11                 emp.var.rate             poutcome_failure        -0.38\n",
      "12                    euribor3m             poutcome_failure        -0.38\n",
      "13                  nr.employed         previously_contacted        -0.37\n",
      "14        education_high.school  education_university.degree        -0.36\n",
      "15                  nr.employed             poutcome_failure        -0.35\n",
      "16                  nr.employed               subscribed_enc        -0.35\n",
      "17                  nr.employed             poutcome_success        -0.35\n",
      "18                    euribor3m                    month_apr        -0.34\n",
      "19  education_university.degree              job_blue-collar        -0.34\n"
     ]
    }
   ],
   "source": [
    "# Show the top positive and negative correlations\n",
    "dw.get_corr(df_enc, n=20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div style=\"background-color: #e8f3ff; border: 1px solid #aecae8; padding: 10px; border-radius: 3px;\">\n",
    "    <b>Observation:</b> Many of these features are strongly correlated with each other. We'll later use <i>reduce_multicollinearity()</i> to remove one of each pair that's least correlated with the target variable.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Top Correlations with Target\n",
    "\n",
    "Now let's list and extract the top positive and negative correlations with our target variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Top 15 positive correlations:\n",
      "              Variable 1      Variable 2  Correlation\n",
      "0               duration  subscribed_enc         0.41\n",
      "1       poutcome_success  subscribed_enc         0.32\n",
      "2   previously_contacted  subscribed_enc         0.32\n",
      "3                  pdays  subscribed_enc         0.27\n",
      "4               previous  subscribed_enc         0.23\n",
      "5              month_mar  subscribed_enc         0.14\n",
      "6              month_oct  subscribed_enc         0.14\n",
      "7              month_sep  subscribed_enc         0.12\n",
      "8           no_default_1  subscribed_enc         0.10\n",
      "9            job_student  subscribed_enc         0.09\n",
      "10           job_retired  subscribed_enc         0.09\n",
      "11             month_dec  subscribed_enc         0.08\n",
      "12             month_apr  subscribed_enc         0.08\n",
      "13         cons.conf.idx  subscribed_enc         0.06\n",
      "14        marital_single  subscribed_enc         0.05\n",
      "\n",
      "Top 15 negative correlations:\n",
      "              Variable 1      Variable 2  Correlation\n",
      "0            nr.employed  subscribed_enc        -0.35\n",
      "1              euribor3m  subscribed_enc        -0.31\n",
      "2           emp.var.rate  subscribed_enc        -0.30\n",
      "3   poutcome_nonexistent  subscribed_enc        -0.19\n",
      "4      contact_telephone  subscribed_enc        -0.14\n",
      "5         cons.price.idx  subscribed_enc        -0.14\n",
      "6              month_may  subscribed_enc        -0.11\n",
      "7               campaign  subscribed_enc        -0.07\n",
      "8        job_blue-collar  subscribed_enc        -0.07\n",
      "9     education_basic.9y  subscribed_enc        -0.05\n",
      "10       marital_married  subscribed_enc        -0.04\n",
      "11             month_jul  subscribed_enc        -0.03\n",
      "12          job_services  subscribed_enc        -0.03\n",
      "13      job_entrepreneur  subscribed_enc        -0.02\n",
      "14       day_of_week_mon  subscribed_enc        -0.02\n"
     ]
    }
   ],
   "source": [
    "# Get the top positive and negative correlations with the target variable, and save to lists\n",
    "pos_features, neg_features = dw.get_corr(df_enc, n=15, var='subscribed_enc', return_arrays=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Create DataFrame of Top Correlated Features\n",
    "\n",
    "We can now create a new DataFrame that consists only of our top positive and negative features. However, it would be better to reduce multicollinearity first. See [Reduce Multicollinearity](#Reduce-Multicollinearity)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Top positive correlation features:\n",
      " ['duration' 'poutcome_success' 'previously_contacted' 'pdays' 'previous'\n",
      " 'month_mar' 'month_oct' 'month_sep' 'no_default_1' 'job_student'\n",
      " 'job_retired' 'month_dec' 'month_apr' 'cons.conf.idx' 'marital_single']\n",
      "\n",
      "Top negative correlation features:\n",
      " ['nr.employed' 'euribor3m' 'emp.var.rate' 'poutcome_nonexistent'\n",
      " 'contact_telephone' 'cons.price.idx' 'month_may' 'campaign'\n",
      " 'job_blue-collar' 'education_basic.9y' 'marital_married' 'month_jul'\n",
      " 'job_services' 'job_entrepreneur' 'day_of_week_mon']\n"
     ]
    }
   ],
   "source": [
    "print(\"Top positive correlation features:\\n\", pos_features)\n",
    "print(\"\\nTop negative correlation features:\\n\", neg_features)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Combine them together and add the target variable\n",
    "top_features = np.concatenate((pos_features, neg_features))\n",
    "top_features = np.concatenate((top_features, ['subscribed_enc']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a dataframe with just these columns\n",
    "df_top_features = pd.DataFrame.copy(df_enc[top_features])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-50.8</td>\n",
       "      <td>0</td>\n",
       "      <td>4963.6</td>\n",
       "      <td>1.028</td>\n",
       "      <td>-1.1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>94.767</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>40195 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       duration  poutcome_success  previously_contacted  pdays  previous  month_mar  month_oct  month_sep  no_default_1  job_student  job_retired  month_dec  month_apr  cons.conf.idx  marital_single  nr.employed  euribor3m  emp.var.rate  poutcome_nonexistent  contact_telephone  cons.price.idx  month_may  campaign  job_blue-collar  education_basic.9y  marital_married  month_jul  job_services  job_entrepreneur  day_of_week_mon  subscribed_enc\n",
       "0           261                 0                     0      0         0          0          0          0             1            0            0          0          0          -36.4               0       5191.0      4.857           1.1                     1                  1          93.994          1         1                0                   0                1          0             0                 0                1               0\n",
       "1           149                 0                     0      0         0          0          0          0             0            0            0          0          0          -36.4               0       5191.0      4.857           1.1                     1                  1          93.994          1         1                0                   0                1          0             1                 0                1               0\n",
       "2           226                 0                     0      0         0          0          0          0             1            0            0          0          0          -36.4               0       5191.0      4.857           1.1                     1                  1          93.994          1         1                0                   0                1          0             1                 0                1               0\n",
       "3           151                 0                     0      0         0          0          0          0             1            0            0          0          0          -36.4               0       5191.0      4.857           1.1                     1                  1          93.994          1         1                0                   0                1          0             0                 0                1               0\n",
       "4           307                 0                     0      0         0          0          0          0             1            0            0          0          0          -36.4               0       5191.0      4.857           1.1                     1                  1          93.994          1         1                0                   0                1          0             1                 0                1               0\n",
       "...         ...               ...                   ...    ...       ...        ...        ...        ...           ...          ...          ...        ...        ...            ...             ...          ...        ...           ...                   ...                ...             ...        ...       ...              ...                 ...              ...        ...           ...               ...              ...             ...\n",
       "40190       334                 0                     0      0         0          0          0          0             1            0            1          0          0          -50.8               0       4963.6      1.028          -1.1                     1                  0          94.767          0         1                0                   0                1          0             0                 0                0               1\n",
       "40191       383                 0                     0      0         0          0          0          0             1            0            0          0          0          -50.8               0       4963.6      1.028          -1.1                     1                  0          94.767          0         1                1                   0                1          0             0                 0                0               0\n",
       "40192       189                 0                     0      0         0          0          0          0             1            0            1          0          0          -50.8               0       4963.6      1.028          -1.1                     1                  0          94.767          0         2                0                   0                1          0             0                 0                0               0\n",
       "40193       442                 0                     0      0         0          0          0          0             1            0            0          0          0          -50.8               0       4963.6      1.028          -1.1                     1                  0          94.767          0         1                0                   0                1          0             0                 0                0               1\n",
       "40194       239                 0                     0      0         1          0          0          0             1            0            1          0          0          -50.8               0       4963.6      1.028          -1.1                     0                  0          94.767          0         3                0                   0                1          0             0                 0                0               0\n",
       "\n",
       "[40195 rows x 31 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the top features dataframe\n",
    "df_top_features"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot Correlations\n",
    "\n",
    "`dw.plot_corr()` plots the top `n` correlations of one variable against others in a DataFrame.\n",
    "\n",
    "This function generates a barplot that visually represents the correlations of\n",
    "    a specified column with other numeric columns in a DataFrame. It displays both\n",
    "    the strength (height of the bars) and the nature (color) of the correlations\n",
    "    (positive or negative). The function computes correlations using the specified\n",
    "    method and presents the strongest positive and negative correlations up to the\n",
    "    number specified by `n`. Correlations are ordered from strongest to lowest,\n",
    "    from the outside in.\n",
    "\n",
    "Use this to communicate the correlations of one particular variable (ex: target\n",
    "    y) in relation to others with a very clean design. It's much easier to scan\n",
    "    this correlation chart vs. trying to find the variable of interest in a\n",
    "    heatmap. The fixed Y axis scales, and Red-Yellow-Green color palette, ensure\n",
    "    the actual magnitudes of the positive or negative correlations are clear and\n",
    "    not misinterpreted."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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oe+65x6L3L6innnoqx2HHzZs3Nz+35PPw9fWVJB08eDDPifSKQ1hYWI7runbtai743fr9Se/HqlWrzJcg5UdUVJR58snw8PB8X+qRnYLsQ/ISGBiY6Wd7q/QCZ0pKSqZilTX2PzExMeaJRnv27JljwdHV1VU9e/bMsy8F9e2330q6+buefilNTtKLRjt27Mhx4sDAwEA1adIk23Umk0nNmjWTlPX3Jy0tTT/++KOkm/uE9DgAyIhCAADkIeOcAImJiYVq68aNGzp69Kgk5VoEkG6eiU4/IN6/f3+OcTn9oVjQ2N27d5tHKjz55JPZzsaf8ZF+0HLrWb38uHDhgsaPH6/69eurYsWKCggIUOPGjRUYGKjAwEB17NgxU2xRSf9c77rrrhyv05Vunl1Mny09t59FXneTSL+WPmNxqSDSD/LT5wlIl34A1b59e9WoUUMBAQHmeQJujWnWrFm2ZxiLQm6fR8Yz3JZ8Hk8++aScnJx048YNtW3bVo8++qjmz5+v/fv3Z7lLQFErW7ZsrvN4ODk5mQ/Gbp3Tol+/fpJuXlt+xx13aMCAAfrkk0/yvMPE7t27zc/vvfdeS1OXVLB9SF7+85//5Lq+ZcuW5ucZPwtr7H8ytleQPKzljz/+kHRzlv+88k+/HW1ycnKO8xXktT9J/x269ffnxIkT5rtEFPa7AaD0ohAAAHmoVKmS+fnZs2cL1dbly5fNz/O6zMDJycn83rlNbJXTRG0FjT137ly+28kofWh9fu3cuVMNGjTQq6++qj///DPPg7Z///3XorzyI/1zzc8lHz4+Ppm2yU5ulzxIMg9RT01NzW+KmWQc0p9+YH/mzBn99ddfMplM5vXpBYP0mNTUVP3++++Z1hWH3D6PjMP1Lfk8GjRooE8++USenp5KSUnRd999p6FDhyowMFBVq1bV008/bdElGJbw8vLK84x6+uULt35/BgwYoPHjx6tMmTKKi4vTokWL9NRTT8nf31933HGHRo0ale2IiYwFsvRRBZYqyD4kL3n9LmW8jCPjZ2GN/U/G9gqSh7VYex9q6f7Emt8NAKUXdw0AgDxkPNO3a9cuq7VrrZmaCzKkN7fYjH9Mvv/++2rTpk2+2izIQURSUpJ69uypixcvysnJSSNHjtRjjz2mevXqydPT0zys/q+//lKdOnUkqVjO7paUWbN9fHxUv359HTlyRBs3btSQIUPMQ/4bNWpkvu65Xbt2WrRokbkQEBUVZZ4BvrjmBygO3bt3V3BwsD777DP99NNP+u2333T+/HlduHBBH3/8sT7++GP169dPCxcuLNJ5Agr7/Zk+fboGDx6sZcuWaf369dq6dauuXbum48eP66233tI777yjOXPmaMiQIVbKODNrXRYgWf5ZWHv/Y4vf6fQ+NG3aVB9//HG+tyvIXU4AwFooBABAHu68805VrlxZFy5c0G+//ab4+HiLh1Zn/KM1r9EFKSkp5onybp0orChkHPng4uKixo0bW/09fv75Z/PZzXnz5mW69j6jorq11628vLwUExOTr5Ee6UOQi+NnkZt27drpyJEj5gJAxssC0t06T0B6jIODQ6kbKuzu7q7Bgwdr8ODBkqRDhw7pm2++0TvvvKN//vlHS5YsUbNmzTLdti9jUSB9OHp28nsp0MWLF5WamprrAXX6dyyn70/NmjU1fvx4jR8/XsnJydqxY4c+//xzvf/++7p+/bqGDRumVq1amS8xyDgRXUxMTJ7DyItLXr9LGddn/Cyssf8pyP61sKO7spPeh4SEhCLZf+bXrd8NAMgOlwYAQB5MJpP5Ot7ExER9+OGHFrfl7OysunXrSpK2bduWa+zu3buVnJwsScXyR2VQUJD5LNqmTZuK5D0OHDhgfv7EE0/kGJd+rW1OrHW2L/1z3bVrV44Tdkk3h/yeOnUq0za2cus8ARknCkxXs2ZN1apVyzxPQHpMUFCQ3N3dizvlYtWwYUO9+OKL2rp1q3lyz88//zxTTMZ5PzJernOrP//8M1/vmZSUlOuklikpKYqKipKUv++Pk5OT2rRpo1mzZmn58uWSbo6M+fLLL80xd911l/l5xrkgbC23O5zcuj7jZ2GN/U/GCfoKkoe1ZJy8z5K5U6wlICDAPDnl7fTdAHB7oRAAAPnw/PPPm6/XnDRpUqaJ2nKTlpamZcuWZVoWHBws6eZBcW6znWcsOKRvU5SqVKmiu+++W5K0fPlynT9/3urvkfFgO6ezrWlpafrggw9ybadcuXLm5zdu3LA4n/TP9cqVK/r6669zjIuMjDRfolAcP4vcZBzav3z5ch09ejTT/ADp0gsDP//8s/la+cLMD5D+mRfm8y5O/v7+qlevnqSsE04GBASYn+dWdPrkk0/y/X633hYwoxUrVpgLDgX9/jz44IPm5xn70bRpU/Nt3z788EMlJCQUqN2ism/fvkwTGd5q4cKFkm5ejpDx+2iN/Y+fn5/5FptffPFFjvOLJCYmZikOWUPnzp0l3SzazJ492+rt55eDg4N5wtVffvkl158HAPtFIQAA8qFatWrme1cnJiaqXbt2WW7hdquDBw8qNDTUfK/vdEOHDjUPTR48eLD52u2M1qxZo8jISEk3Z7fOawZsa5kwYYKkm7fyevzxx80zT2fnxo0bmjt3rq5fv57v9tNHQ0g53z973Lhxec7FkHECrOPHj+f7/W8VFhZmLvCMGjVKf//9d5aYPXv2aMaMGZJufg+6dOli8ftZg5+fn/lznDNnjqTM8wOkSy8MLF261PxzLMz8AOmfeWE+b2tauXJlrt/P06dPmwt2GQ/8pZtnotOHpb/77rvZFjc+//xzffHFF/nO57333jNPyJhRbGysRo8eLenmkPf00UXpPv7441xHo6xZs8b8PGM/HBwc9MILL0i6OWFk3759lZSUlG0baWlp+ueff/Ldl8IaPHhwtoW+5cuX64cffpAkdenSJctEdtbY/wwdOlTSzc991KhR2W77/PPPWzyxX246dOhgvhvBzJkz8yw27Nu3T6tWrbJ6HpI0evRoOTg4yDAM9erVK9e7UOR1hwoApRNzBABAPoWFhenMmTOaNGmSzp07p/bt26tDhw567LHH1LBhQ3l4eOjSpUv6888/9f3332v16tVKTU3NcluxwMBAjRo1SjNnztSePXt01113aezYsWrWrJkSExO1atUqzZkzR6mpqSpbtqzef//9YuvjI488omeffVazZ8/Wr7/+qoYNG2rIkCG65557VKlSJSUmJurYsWP67bff9PXXX+vy5ctZDmxyExISoqpVq+rcuXOaMGGCTp48qa5du6py5co6duyYPvjgA61fv15t27bNdXhwxonEnn/+eb300kvy9fU1Dy2uVauWypTJ+7+4KlWqaObMmRo+fLjOnDmj5s2b68UXX1SbNm2UkpKidevWaebMmUpISJDJZNKCBQtyvc1gcWnXrp2OHj2quLg4Sdmf6U9flh7j4OBgvne5Jdq0aaMTJ07o22+/1fvvv6+2bduaRwm4ubnl684L1jRr1iz17t1bHTt21AMPPKCGDRvK3d1dly9f1h9//KF33nnHfEb41kn2ypQpo//+97969dVXtX//fj3wwAMaM2aMatSoobNnz+qLL77Q4sWL1aZNG23evDnPXKpUqSIXFxc99NBDev755/XII4/I2dlZ27dv14wZM8wH4a+88kqWz+npp5/W6NGj1a1bN7Vp00Z16tRRuXLldPbsWa1du1bvvfeeJMnV1VW9e/fOtO3w4cO1atUqrV27VitWrFBgYKCGDRumFi1ayMXFRbGxsdq6das++eQTPfXUU5oyZYqlH3e+tWjRQn/88YdatGihsWPHKjAwUHFxcfryyy/N+7KKFSvqzTffzLKtNfY/Q4cO1aJFi7R792699957OnHihIYMGSJ/f3+dPn1a8+bN05o1a8x5Wtvy5cvVsmVLXbp0SU888YQ+/vhjPfHEE6pbt64cHR117tw57d69W6tWrdLWrVs1atQoPfroo1bPIygoSC+//LImTpyoP//8U4GBgRo+fLjuv/9+VapUSVeuXFFUVJS+/vprOTo6asOGDVbPAcBtzgAAFMhXX31l1KpVy5CU5+POO+80fvrppyxtpKamGsOGDct1W3d392y3NQzD2LBhgzluw4YNueZbkFjDMIy0tDTj5ZdfNsqUKZNn/ypUqGBcu3atQO+3evVqo1y5cjm22b59e2P//v3m14sWLco2z549e+bYxokTJ8xx/fr1MyQZNWvWzLHP06dPNxwcHHJsz9nZ2ViyZEm22544cSLPXNPVrFnTkGT069cv17i8fPzxx5ny++KLL3J9P0lGUFBQrm22a9fOkGS0a9cu2/W7d+82nJ2ds/18MvanIN+39LjJkyfnGpdbvrk9HBwcjFdeeSXb7RMTE4277767UN/DjN+tHTt2GJUrV86xvWeeeSbXzyCvfcGPP/6YYz8ef/zxPNu49TMu6H4hr9+jjO8zefLkHPNwc3MzNm7cmOP7FHb/YxiG8ffffxv169fPcbsOHToYP/30U4H6XxBHjhwxGjdunK+f7csvv5xl+/zuJ/K7b8vrs8zpdx5A6calAQBQQN26ddORI0e0bNky9enTR/Xr15enp6fKlCkjLy8v3XXXXRo2bJh+/vln7du3Tx06dMjShoODg+bOnatff/1VvXv3Vo0aNeTs7Cw3NzcFBQVp/PjxOnr0aLbbFjWTyaRJkybpzz//1JgxY9SiRQvzfdIrVqyoRo0aqXfv3lqyZIliYmJUvnz5ArUfEhKiP/74Q3369JGfn5+cnJxUpUoVtWvXTgsWLND69evNk7zl5uOPP9Ybb7yhli1byt3dvVC3hxs/frx2796t8PBw1alTR+XLl1eFChXUsGFDPfvsszp8+LD69u1rcfvWlnGIf3bzA6TL7k4ClgoKCtKWLVv05JNPmr+vtvTJJ59owYIFeuqppxQUFCQfHx+VKVNGrq6uuvPOOzV06FDt3r3bPNz8Vi4uLvr55581ffp0BQYGqnz58nJzc9N//vMfvfvuu1q3bl2+vofpWrRooV27dumZZ54xn9WvVKmSQkND9cMPP+R4zfj+/fv1+uuv69FHH1WjRo1UqVIlOTo6ysPDQ3fffbcmT56sI0eOKDQ0NMd+fPHFF/r555/19NNPKyAgQOXLl1fZsmXl7++vRx99VO+//36Ow+SLwpQpU7R69Wp17NhR3t7eKlu2rGrVqqVhw4bpwIEDuV6iYo39j5+fn3bv3q1p06apcePGKl++vPnznDdvnn788UeVLVu2yPpfr149RUVFafny5erevbtq1Khh/pn4+vqqffv2mjBhgnbu3KlJkyYVWR7SzX3bwYMH9dxzz6lx48Zyc3NTmTJlzPvcadOm6aOPPirSHADcnkyGUQw3aAYAAAAAALcFRgQAAAAAAGBHKAQAAAAAAGBHKAQAAAAAAGBHSnwh4Ndff9Wjjz4qPz8/mUwmrVy5Ms9tNm7cqLvuukvOzs664447sr2X9dy5c1WrVi2VK1dOrVq10vbt262fPAAAAG4L586d0/79+wv8+PPPP22dOgAUWN43Wb7NJSYmqmnTphowYIC6deuWZ/yJEyfUsWNHDRkyRMuWLdP69es1aNAg+fr6KiQkRJL02WefKSIiQvPnz1erVq00a9YshYSE6MiRI8V+n2QAAAAUvXnz5unll18u8HY1a9bUyZMnrZ8QABShUnXXAJPJpBUrVqhLly45xowdO1bff/+99u/fb17Wq1cvXblyRatXr5YktWrVynz7IElKS0uTv7+/Ro4cqRdffLFI+wAAAIDiN2XKFAoBAOxGiR8RUFBbtmxRcHBwpmUhISF67rnnJElJSUnauXOnxo0bZ17v4OCg4OBgbdmyJcd2b9y4oRs3bphfp6Wl6dKlS6pUqZJMJpN1OwEAAACrioiIUEREhEXbxsfHWzkbALCMYRi6evWq/Pz85OCQ80wAdlcIiI2Nlbe3d6Zl3t7eio+P17///qvLly8rNTU125jDhw/n2O6rr75qURUZAAAAAABrOn36tKpXr57jersrBBSVcePGZaoix8XFqUaNGjp9+rTc3NxsmBkAAAAAwB7Ex8fL399fFStWzDXO7goBPj4+Onv2bKZlZ8+elZubm8qXLy9HR0c5OjpmG+Pj45Nju87OznJ2ds6y3M3NjUIAAAAAAKDY5HV5eom/fWBBtW7dWuvXr8+0bO3atWrdurUkqWzZsmrevHmmmLS0NK1fv94cAwAAAABASVXiCwEJCQmKiopSVFSUpJu3B4yKilJ0dLSkm0P2+/bta44fMmSI/vrrL40ZM0aHDx/WvHnz9Pnnn+v55583x0REROiDDz7QkiVLdOjQIQ0dOlSJiYkKCwsr1r4BAAAAAGBtJf7SgD/++EP333+/+XX6dfr9+vXT4sWLFRMTYy4KSFJAQIC+//57Pf/885o9e7aqV6+uDz/8UCEhIeaYJ554QufPn9ekSZMUGxuroKAgrV69OssEggAAAAAAlDQmwzAMWydRGsXHx8vd3V1xcXHMEQAAAAAAKHL5PQ4t8ZcGAAAAAACA/KMQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHaEQAAAAAACAHSkVhYC5c+eqVq1aKleunFq1aqXt27fnGNu+fXuZTKYsj44dO5pj+vfvn2V9aGhocXQFAAAAAIAiVcbWCRTWZ599poiICM2fP1+tWrXSrFmzFBISoiNHjqhq1apZ4r/++mslJSWZX1+8eFFNmzZVjx49MsWFhoZq0aJF5tfOzs5F1wkAAAAAAIpJiR8R8NZbbyk8PFxhYWFq1KiR5s+fLxcXFy1cuDDbeC8vL/n4+Jgfa9eulYuLS5ZCgLOzc6Y4T0/P4ugOAAAAAABFqkQXApKSkrRz504FBweblzk4OCg4OFhbtmzJVxuRkZHq1auXKlSokGn5xo0bVbVqVdWvX19Dhw7VxYsXc23nxo0bio+Pz/QAAAAAAOB2U6ILARcuXFBqaqq8vb0zLff29lZsbGye22/fvl379+/XoEGDMi0PDQ3V0qVLtX79er3++uv65Zdf9PDDDys1NTXHtl599VW5u7ubH/7+/pZ1CgAAAACAIlTi5wgojMjISAUGBqply5aZlvfq1cv8PDAwUE2aNFGdOnW0ceNGPfjgg9m2NW7cOEVERJhfx8fHUwwAAAAAANx2SvSIgMqVK8vR0VFnz57NtPzs2bPy8fHJddvExER9+umnGjhwYJ7vU7t2bVWuXFnHjh3LMcbZ2Vlubm6ZHgAAAAAA3G5KdCGgbNmyat68udavX29elpaWpvXr16t169a5bvvFF1/oxo0b6tOnT57vc+bMGV28eFG+vr6FzhkAAAAAAFsq0YUASYqIiNAHH3ygJUuW6NChQxo6dKgSExMVFhYmSerbt6/GjRuXZbvIyEh16dJFlSpVyrQ8ISFBL7zwgrZu3aqTJ09q/fr1euyxx3THHXcoJCSkWPoEAAAAAEBRKfFzBDzxxBM6f/68Jk2apNjYWAUFBWn16tXmCQSjo6Pl4JC53nHkyBH9/vvvWrNmTZb2HB0dtXfvXi1ZskRXrlyRn5+fOnTooFdeeUXOzs7F0icAAAAAAIqKyTAMw9ZJlEbx8fFyd3dXXFwc8wUAAAAAAIpcfo9DS/ylAQAAAAAAIP8oBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEdKRSFg7ty5qlWrlsqVK6dWrVpp+/btOcYuXrxYJpMp06NcuXKZYgzD0KRJk+Tr66vy5csrODhYR48eLepuAAAAAABQ5Ep8IeCzzz5TRESEJk+erF27dqlp06YKCQnRuXPnctzGzc1NMTEx5sepU6cyrX/jjTc0Z84czZ8/X9u2bVOFChUUEhKi69evF3V3AAAAAAAoUiW+EPDWW28pPDxcYWFhatSokebPny8XFxctXLgwx21MJpN8fHzMD29vb/M6wzA0a9YsTZgwQY899piaNGmipUuX6p9//tHKlSuLoUcAAAAAgPxITk7WiBEj5OnpKS8vL40cOVIpKSm5bvPvv//qjjvukIeHR6blEydOVGBgoMqUKaPnnnuu6JK+DZToQkBSUpJ27typ4OBg8zIHBwcFBwdry5YtOW6XkJCgmjVryt/fX4899pgOHDhgXnfixAnFxsZmatPd3V2tWrXKtU0AAAAAQPGaNm2afv/9dx08eFAHDhzQb7/9phkzZuS6zaRJk1SzZs0sy++44w698cYb6ty5c1Gle9so0YWACxcuKDU1NdMZfUny9vZWbGxsttvUr19fCxcu1DfffKOPP/5YaWlpatOmjc6cOSNJ5u0K0qYk3bhxQ/Hx8ZkeAAAAAICis3DhQk2YMEG+vr7y9fXVSy+9pMjIyBzjd+7cqdWrV2vs2LFZ1vXr108PP/yw3NzcijLl20KJLgRYonXr1urbt6+CgoLUrl07ff3116pSpYref//9QrX76quvyt3d3fzw9/e3UsYAAAAAgFtdvnxZZ86cUVBQkHlZUFCQoqOjFRcXlyU+JSVF4eHhmjt3rsqWLVuMmd5+SnQhoHLlynJ0dNTZs2czLT979qx8fHzy1YaTk5OaNWumY8eOSZJ5u4K2OW7cOMXFxZkfp0+fLkhXAAAAAAAFkJCQIEmZrvVPf3716tUs8TNnzlSzZs103333FUd6t7USXQgoW7asmjdvrvXr15uXpaWlaf369WrdunW+2khNTdW+ffvk6+srSQoICJCPj0+mNuPj47Vt27Zc23R2dpabm1umBwAAAACgaLi6ukpSprP/6c8rVqyYKfbYsWOaP3++Zs6cWXwJ3sbK2DqBwoqIiFC/fv3UokULtWzZUrNmzVJiYqLCwsIkSX379lW1atX06quvSpKmTp2qu+++W3fccYeuXLmimTNn6tSpUxo0aJCkm3cUeO655zRt2jTVrVtXAQEBmjhxovz8/NSlSxdbdRMAAAAAkIGnp6eqV6+uqKgo1alTR5IUFRUlf39/ubu7Z4r9/fffdfbsWdWrV0/SzbsNXL16VZUrV9b333+vVq1aFXv+tlTiCwFPPPGEzp8/r0mTJik2NlZBQUFavXq1ebK/6OhoOTj838CHy5cvKzw8XLGxsfL09FTz5s21efNmNWrUyBwzZswYJSYmavDgwbpy5YruuecerV69WuXKlSv2/gEAAAAAshcWFqbp06erbdu2kqQZM2aYT/Jm1LNnz0x3htuyZYsGDRqkqKgoVa1aVdLN4kBqaqr5cf36dTk6OsrJyal4OlOMTIZhGLZOojSKj4+Xu7u74uLiuEwAAAAAAIpAcnKynnvuOS1fvlyS1KdPH7399tsqU6aMhgwZIkmaP39+lu02btyoLl266MqVK+Zl/fv315IlSzLF9evXT4sXLy6y/K0tv8ehFAKKCIUAAAAAAEBxyu9xaImeLBAAAAAAABQMhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAyCA5OVkjRoyQp6envLy8NHLkSKWkpGQbO3LkSPn7+8vNzU3VqlXTc889p6SkJEnSuXPn1Lt3b1WvXl1ubm5q1qyZvv322+Lsillp7BMsRyEAAAAAADKYNm2afv/9dx08eFAHDhzQb7/9phkzZmQbO2zYMB0+fFjx8fHas2eP9uzZozfeeEOSlJCQoGbNmmnr1q26cuWKpk6dqieffFIHDx4szu5IKp19guUoBAAAAABABgsXLtSECRPk6+srX19fvfTSS4qMjMw2tmHDhqpQoYIkyTAMOTg46OjRo5Kk2rVra/To0apevbocHBz06KOPqn79+tq6dWux9SVdaewTLFfG1gkAAAAAwO3i8uXLOnPmjIKCgszLgoKCFB0drbi4OLm7u2fZ5rXXXtO0adOUmJioSpUq6fXXX8+27XPnzunQoUNq0qRJUaWfrdu5Tx8dHm7RdsXt6QZzbZ2CVTEiAAAAAAD+v4SEBEmSh4eHeVn686tXr2a7zYsvvqiEhAQdPHhQQ4YMkY+PT5aYpKQk9erVSz179lSLFi2snnduSmOfUDgUAgAAAADg/3N1dZUkxcXFmZelP69YsWKu2zZs2FBNmzZV//79My1PSkrS448/LhcXF33wwQfWTTgfSmOfUDgUAgAAAADg//P09FT16tUVFRVlXhYVFSV/f/9sh9DfKjk52Xw9vXTzgLlHjx5KSkrSV199pbJlyxZF2rkqjX1C4VAIAAAAAIAMwsLCNH36dMXGxio2NlYzZszQoEGDssQlJCRo0aJFunLligzD0L59+zRt2jSFhIRIunkA3bNnTyUmJmrlypVydnYu7q6YlcY+wXIUAgAAAAAgg4kTJ6p169Zq2LChGjZsqLZt22r8+PGSpCFDhmjIkCGSJJPJpOXLl6tOnTqqWLGiHnvsMXXs2FGzZs2SJG3evFnffPONNm3apMqVK8vV1VWurq453raPPqG4mAzDMGydRGkUHx8vd3d3xcXFyc3NzdbpAAAAAMBth7sGWFd+j0MZEQAAAAAAgB2hEAAAAADAIsnJyRoxYoQ8PT3l5eWlkSNHKiUlJUvcjRs3FB4eroCAAFWsWFENGjTQwoULzeujo6PNQ8zTH2XKlFHnzp2LszuA3aAQAAAAAMAi06ZN0++//66DBw/qwIED+u2337K9VjwlJUW+vr5at26d4uPjtXjxYo0aNUpr1qyRJNWoUUMJCQnmx6VLl+Th4aFevXoVd5cAu0AhAAAAAIBFFi5cqAkTJsjX11e+vr566aWXFBkZmSWuQoUKmjp1qurUqSOTyaS7775b999/v37//fds2125cqXS0tLUrVu3ou4CYJcoBAAAAAAosMuXL+vMmTMKCgoyLwsKClJ0dLTi4uJy3fb69evavn27mjRpku36yMhI9e7dW+XKlbNmygD+PwoBAAAAAAosISFBkuTh4WFelv786tWrOW5nGIYGDRqkunXrZnvG/9SpU1q3bl2297gHYB0UAgAAAAAUmKurqyRlOvuf/rxixYrZbmMYhoYNG6YjR45o5cqVcnDIejiyaNEiNWvWTE2bNi2CrAFIFAIAAAAAWMDT01PVq1dXVFSUeVlUVJT8/f3l7u6eJd4wDA0fPlzbtm3TmjVrso1JS0vTokWLGA0AFDEKAQAAAAAsEhYWpunTpys2NlaxsbGaMWNGjgfxI0aM0KZNm7R27Vp5enpmG7N27VpduHBBTz75ZFGmDdi9MrZOAAAAAEDJNHHiRF28eFENGzaUJPXp00fjx4+XJA0ZMkSSNH/+fJ06dUrz5s2Ts7Ozatasad6+T58+mj9/vvl1ZGSkHn/88WxHCwCwHpNhGIatkyiN4uPj5e7urri4OLm5udk6HQAAAAC47Xx0eLitU8iXpxvMtXUK+ZLf41AuDQAAAACKQXJyskaMGCFPT095eXlp5MiRSklJyRJ348YNhYeHKyAgQBUrVlSDBg20cOHCTDGPP/64fH195ebmpoCAAE2bNq24ugGgFKAQAAAAABSDadOm6ffff9fBgwd14MAB/fbbb5oxY0aWuJSUFPn6+mrdunWKj4/X4sWLNWrUKK1Zs8YcM3nyZJ08eVLx8fH65ZdftHz5cn388cfF2R0AJRhzBAAAAADFYOHChXr77bfl6+srSXrppZc0evRoTZo0KVNchQoVNHXqVPPru+++W/fff79+//13dejQQZIUGBhoXm8ymeTg4KCjR48WQy9KhnWnx9k6hXwJ9n8137ElpU9SwfoF22BEAAAAAFDELl++rDNnzigoKMi8LCgoSNHR0YqLi8t12+vXr2v79u1q0qRJpuXDhg2Ti4uLatSooYSEBPXv378IMgdQGlEIAAAAAIpYQkKCJMnDw8O8LP351atXc9zOMAwNGjRIdevWVbdu3TKtmzdvnhISErRjxw717ds3x1vyAcCtKAQAAAAARczV1VWSMp39T39esWLFbLcxDEPDhg3TkSNHtHLlSjk4ZP3T3cHBQS1atFDFihU1evToIsgcQGlEIQAAAAAoYp6enqpevbqioqLMy6KiouTv7y93d/cs8YZhaPjw4dq2bZvWrFmTbUxGycnJzBEAIN8oBAAAAADFICwsTNOnT1dsbKxiY2M1Y8YMDRo0KNvYESNGaNOmTVq7dm2WIf+nTp3SV199pYSEBKWlpWnz5s2aM2eOQkJCiqMbAEoB7hoAAAAAFIOJEyfq4sWLatiwoSSpT58+Gj9+vCRpyJAhkqT58+fr1KlTmjdvnpydnVWzZk3z9n369NH8+fMlSbNmzdLAgQOVlpYmPz8/jRw5Ui+++GIx9whASUUhAAAAACgGTk5Omjt3rubOnZtlXfoBviTVrFlThmHk2E7NmjX122+/FUmOAOwDlwYAAAAAAGBHKAQAAAAAAGBHKAQAAAAAAGBHKAQAAAAAAGBHSsVkgXPnztXMmTMVGxurpk2b6p133lHLli2zjf3ggw+0dOlS7d+/X5LUvHlzzZgxI1N8//79tWTJkkzbhYSEaPXq1UXXCQAAAKCYbY2dYusU8u1unym2TgEoNUr8iIDPPvtMERERmjx5snbt2qWmTZsqJCRE586dyzZ+48aNevLJJ7VhwwZt2bJF/v7+6tChg/7+++9McaGhoYqJiTE/Pvnkk+LoDgAAAAAARarEFwLeeusthYeHKywsTI0aNdL8+fPl4uKihQsXZhu/bNkyDRs2TEFBQWrQoIE+/PBDpaWlaf369ZninJ2d5ePjY354enoWR3cAAAAAAChSJboQkJSUpJ07dyo4ONi8zMHBQcHBwdqyZUu+2rh27ZqSk5Pl5eWVafnGjRtVtWpV1a9fX0OHDtXFixdzbefGjRuKj4/P9AAAAAAA4HZTogsBFy5cUGpqqry9vTMt9/b2VmxsbL7aGDt2rPz8/DIVE0JDQ7V06VKtX79er7/+un755Rc9/PDDSk1NzbGdV199Ve7u7uaHv7+/ZZ0CAAAAAKAIlYrJAi312muv6dNPP9XGjRtVrlw58/JevXqZnwcGBqpJkyaqU6eONm7cqAcffDDbtsaNG6eIiAjz6/j4eIoBAAAAAIDbTokeEVC5cmU5Ojrq7NmzmZafPXtWPj4+uW775ptv6rXXXtOaNWvUpEmTXGNr166typUr69ixYznGODs7y83NLdMDAACgqCUnJ2vEiBHy9PSUl5eXRo4cqZSUlGxj3333XbVo0ULOzs7q0qVLjm2ePXtWXl5eCgoKKpqk81Aa+wQAt5MSXQgoW7asmjdvnmmiv/SJ/1q3bp3jdm+88YZeeeUVrV69Wi1atMjzfc6cOaOLFy/K19fXKnkDAABYy7Rp0/T777/r4MGDOnDggH777TfNmDEj21g/Pz9NmDBB4eHhubY5YsQINWvWrCjSzZfS2CcAuJ2U6EKAJEVEROiDDz7QkiVLdOjQIQ0dOlSJiYkKCwuTJPXt21fjxo0zx7/++uuaOHGiFi5cqFq1aik2NlaxsbFKSEiQJCUkJOiFF17Q1q1bdfLkSa1fv16PPfaY7rjjDoWEhNikjwAAADlZuHChJkyYIF9fX/n6+uqll15SZGRktrHdunVTly5dVLly5Rzb++abb3Tp0iU9/fTTRZVynkpjnwDgdlLi5wh44okndP78eU2aNEmxsbEKCgrS6tWrzRMIRkdHy8Hh/+od7733npKSkvT4449namfy5MmaMmWKHB0dtXfvXi1ZskRXrlyRn5+fOnTooFdeeUXOzs7F2jcAAIDcXL58WWfOnMk03D0oKEjR0dGKi4uTu7t7gdqLi4tTRESEVq9erU2bNlk52/y5nfu09+Krhdq+uDSpNC7vIAB2rcQXAqSbQ71GjBiR7bqNGzdmen3y5Mlc2ypfvrx++uknK2UGAABQdNJHNHp4eJiXpT+/evVqgQ+ax4wZo/79+6tu3bo2KwSUxj4BwO2mxF8aAAAAkB/WmoDu3Llz6t27t6pXry43Nzc1a9ZM3377bTH0ICtXV1dJN896p0t/XrFixQK19dtvv2nTpk0aO3as9RK0QGnsEwDcbgo9IiAlJUVHjhzRlStXlJqamm3MfffdV9i3AQAAKJSME9BJ0sMPP6wZM2Zo0qRJWWLTJ6Bbt26dzpw5k2ldQkKCmjVrptdff11+fn76/vvv1atXL+3YsUONGjUqlr6k8/T0VPXq1RUVFaU6depIkqKiouTv71/gM+fr16/XX3/9JT8/P0nSjRs39O+//6py5crat29fsU2aXBr7BAC3G4sLAYZhaNKkSXrnnXd09erVXGNzKhAAAAAUl4ULF+rtt982H/y99NJLGj16dLaFgG7dukm6eQB6ayGgdu3aGj16tPn1o48+qvr162vr1q3FXgiQpLCwME2fPl1t27aVJM2YMUODBg3KNjYlJcX8SEtL0/Xr1+Xg4KCyZcsqIiIi03ZffPGFPvzwQ/3000+qWrVqsfQlXWnsEwDcTiwuBLzyyiuaPn26PDw81LdvX1WvXl1lypSKKQcAAEApY+0J6DI6d+6cDh06pCZNmlgh04KbOHGiLl68qIYNG0qS+vTpo/Hjx0uShgwZIkmaP3++pJujIl5++WXztuXLl1e7du20ceNGubm5yc3NzbzO09NTTk5Oql69enF1xaw09gkAbicmwzAMSzasVauWTCaT/vjjD1WqVMnaeZV48fHxcnd3V1xcXKb/gAAAQPE7ffq0atSoofPnz5tvM3f+/HlVrVpVp0+fzvHAcMqUKYqKitLKlSuzXZ+UlKTQ0FD5+/tryZIlRZU+bhOl8a4BW2OnFF0iVna3z5R8x647XTLunBDsn//vVEnpk1Swfn10eHgRZmI9TzeYa+sU8iW/x6EWTxYYGxurLl26UAQAAAC3PWtOQJcu/XbELi4u+uCDDwqfJAAAxcTiQkBAQIDi4+OtmQsAAECRyDgBXTpLJ6CTbhYBevTooaSkJH311VcqW7asFbMFAKBoWVwIGDp0qL777judO3fOmvkAAAAUifQJ6GJjYxUbG5vnBHTXr1/PNAFdUlKSpJu3IezZs6cSExO1cuVKOTs7F2c3AAAoNItn93vsscf022+/qU2bNpo0aZLuuuuuHK9BqFGjhsUJAgAAWIO1JqDbvHmzvvnmG5UrV84834AkjR8/3tweAAC3M4sLAQEBATKZTDIMQ2FhYTnGmUwmpaSkWPo2AAAAVuHk5KS5c+dq7tysEz6lFwDSTZkyRVOmTMm2nXbt2snCuZYBALgtWFwI6Nu3r0wmkzVzAQAAAAAARcziQsDixYutmAYAAAAAACgOFk8WCAAAAAAASh6LRwRktGnTJkVFRSk+Pl5ubm4KCgpS27ZtrdE0AAAAAACwokIVAjZv3qywsDAdO3ZMkmQYhnnegLp162rRokVq3bp14bMEAAAAAABWYXEh4MCBA+rQoYOuXbumhx56SPfff798fX0VGxurDRs2aM2aNQoJCdHWrVvVqFEja+YMAAAAAAAsZHEhYOrUqUpKStIPP/yg0NDQTOvGjh2r1atXq3Pnzpo6dao+/fTTQicKAAAAAAAKz+LJAjdu3KjHH388SxEgXWhoqB5//HFt2LDB4uQAAAAAAIB1WVwIiIuLU0BAQK4xAQEBiouLs/QtAAAAAACAlVl8aYCfn5+2bt2aa8y2bdvk5+dn6VsAAACUev8kfmjrFPLFr8KgfMeWlD5JBesXAJQWFo8I6Ny5szZu3KiJEyfq+vXrmdZdv35dkydP1oYNG/TYY48VOkkAAAAAAGAdFo8ImDhxor777jvNmDFD77//vlq2bClvb2+dPXtWO3bs0Pnz51W7dm1NnDjRmvkCAAAAAIBCsLgQUKlSJW3dulVjxozRp59+qh9++MG8rly5cgoLC9Prr78uLy8vqyQKAAAAAAAKz+JCgCRVrlxZCxcu1Pvvv6/Dhw8rPj5ebm5uatCggZycnKyVIwAAAAAAsJJCFQLSOTk5KTAw0BpNAQAAZOvstcW2TiHfvF362zoFAAByZPFkgQAAAAAAoOTJ94iABx54QCaTSUuWLFH16tX1wAMP5Gs7k8mk9evXW5wgAAAAAACwnnwXAjZu3CiTyaRr166ZX+eHyWSyKDEAAAAAAGB9+S4EpKWl5foaAAAAAADc/pgjAAAAAAAAO2JxIWDAgAH69ttvc4357rvvNGDAAEvfAgAAAAAAWJnFhYDFixcrKioq15g9e/ZoyZIllr4FAAAAAACwsiK9NOD69esqUybf0xAAAAAAAIAiVqij9JzuCGAYhk6fPq0ff/xRfn5+hXkLAAAAAABgRQUaEeDg4CBHR0c5OjpKkqZMmWJ+nfFRpkwZBQQEaNeuXerVq1eRJA4AAAAAAAquQCMC7rvvPvMogF9//VU1atRQrVq1ssQ5OjrKy8tLDzzwgMLDw62SKAAAAAAAKLwCFQI2btxofu7g4KCwsDBNmjTJ2jkBAAAAAIAiYvEcAWlpadbMAwAAAAAAFIMivWsAAAAAAAC4vRTqrgGpqan6/PPPtW7dOv3zzz+6ceNGlhiTyaT169cX5m0AAAAAAICVWFwISExMVIcOHbR161YZhiGTySTDMMzr01/ndItBAAAAAABQ/Cy+NGDatGnasmWLXn75ZV24cEGGYWjKlCmKiYnRZ599ptq1a6tHjx7ZjhIAAAAAAAC2YXEh4Ouvv9bdd9+tCRMmyMvLy7zc29tbPXr00IYNG7Ru3TrNnDnTKokCAAAAAIDCs7gQEB0drbvvvvv/GnJwyHT2v3r16urYsaOWLFlSuAwBAAAAAIDVWFwIqFChghwc/m9zd3d3xcTEZIrx8fFRdHS05dkBAAAAAACrsrgQULNmzUwH+Y0bN9bPP/9sHhVgGIbWr18vX1/fwmcJAAAAAACswuJCwIMPPqgNGzYoJSVFktSvXz9FR0erdevWeuGFF3TPPfcoKipK3bt3t1qyAAAAAACgcCwuBISHh2v06NE6f/68JGnAgAEaPny49uzZo//973/asmWLunXrpilTplgr1xzNnTtXtWrVUrly5dSqVStt37491/gvvvhCDRo0ULly5RQYGKgffvgh03rDMDRp0iT5+vqqfPnyCg4O1tGjR4uyCwAAAAAAFAuLCwF169bV2LFjMw39f+eddxQbG6stW7bon3/+0RdffCEXFxerJJqTzz77TBEREZo8ebJ27dqlpk2bKiQkROfOncs2fvPmzXryySc1cOBA7d69W126dFGXLl20f/9+c8wbb7yhOXPmaP78+dq2bZsqVKigkJAQXb9+vUj7AgAAAABAUStj7QarVKmiKlWqWLvZHL311lsKDw9XWFiYJGn+/Pn6/vvvtXDhQr344otZ4mfPnq3Q0FC98MILkqRXXnlFa9eu1bvvvqv58+fLMAzNmjVLEyZM0GOPPSZJWrp0qby9vbVy5Ur16tWrQPmlpaUpLS2tkL0EAABGmsnWKeRbQf7vLyn9Ko19kgrWLxkWn0MrVqWxT1JB++VYdIlYUWnsk1SwfplKSL9KyjFdfvO0eiGgOCUlJWnnzp0aN26ceZmDg4OCg4O1ZcuWbLfZsmWLIiIiMi0LCQnRypUrJUknTpxQbGysgoODzevd3d3VqlUrbdmyJcdCwI0bNzLdPjE+Pt7cXsWKFS3qHwAA+D8paQ1snUK+JTj8le/Y5LQ7izAT6/m3FPZJKli/TKltizAT6/nrSv77VD6lfdElYmV/Jea/X5WSHyrCTKznr79KX5+kgvWrXmqXokvEigrSJ1u6evVqvuLyXQh44IEHLErEZDJp/fr1Fm2blwsXLig1NVXe3t6Zlnt7e+vw4cPZbhMbG5ttfGxsrHl9+rKcYrLz6quv6uWXXy5wH24LV0/bOoP8q+ifv7jEM0WbhzVVqJ7/2MS/iy4Pa6tQLX9xSWeLNg9rKuudd0y6lAtFl4e1lamcv7jS2CdJSr1YdHlYm2Ol/MWlXSnSNKzKwSPfoWUc8tn/EsbJoQDf1xKiNPZJkso7+tg6BaurUMbP1ikUiYpO+fw7pAQpjX2SJK9yNWydgl3KdyFg48aNFr2ByVRyhoYVxrhx4zKNNIiPj5e/v78CAgLk5uZmw8zylvbzu7ZOId8cmr6Vr7i0rR8WcSbW4xA4I9+xadsXFmEm1uUQOC1fccbp74o4E+sx+T+T71jjwi9FmIl1mSqH5SuuNPZJkozL2Y8gux2ZPHvnL/Dat0WbiDW53GXrDAAAKDXSR6bnJd+FgNvxmojKlSvL0dFRZ89mPqN49uxZ+fhkX7H18fHJNT7937Nnz2aaCPHs2bMKCgrKMRdnZ2c5OztnWe7g4CAHh9v92qtUWyeQb/n/LEtjn6TS2C/DdPvtW3JiKsDPyjAZRZiJdeW3X6WxT1Ip7ZdDyemTbvv/IwEAKDny+zd4if7ft2zZsmrevHmmSw/S0tK0fv16tW7dOtttWrduneVShbVr15rjAwIC5OPjkykmPj5e27Zty7FNAAAAAABKCqtNFnjp0iUlJibK3z+f13BbSUREhPr166cWLVqoZcuWmjVrlhITE813Eejbt6+qVaumV199VZL07LPPql27dvrf//6njh076tNPP9Uff/yhBQsWSLp5KcNzzz2nadOmqW7dugoICNDEiRPl5+enLl26FGvfAAAAAACwtkKNCIiLi9Ozzz4rb29vValSRQEBAeZ127Zt0yOPPKKdO3cWOsncPPHEE3rzzTc1adIkBQUFKSoqSqtXrzZP9hcdHa2YmBhzfJs2bbR8+XItWLBATZs21ZdffqmVK1eqcePG5pgxY8Zo5MiRGjx4sP7zn/8oISFBq1evVrly5Yq0LwAAAAAAFDWLRwRcunRJbdq00Z9//qm77rpLVapU0aFDh8zrmzRpok2bNmnZsmVq3ry5VZLNyYgRIzRixIhs12U3yWGPHj3Uo0ePHNszmUyaOnWqpk6daq0UAQAAAAC4LVg8ImDKlCn6888/zUPrbz2wLl++vNq1a6eff/650EkCAAAAAADrsLgQ8O2336pTp07q2bNnjjG1atXSmTMl6H7uAAAAAACUchYXAmJiYtSoUaNcY5ydnZWYmGjpWwAAAAAAACuzuBBQqVIlnT59OteYw4cPy9fX19K3AAAAAAAAVmZxIeC+++7TN998k+PQ/4MHD2r16tUKDg62ODkAAAAAAGBdFhcCXnrpJaWmpqpt27ZatmyZLly4IEk6dOiQIiMj9cADD8jZ2VkvvPCC1ZIFAAAAAACFY/HtAwMDA/XZZ5/p6aefVt++fSVJhmGocePGMgxDFStW1Oeff666detaLVkAAAAAAFA4FhcCJKlz5846ceKElixZom3btunSpUtyc3NTq1atFBYWpsqVK1srTwAAAAAAYAUWFwKWLl0qb29vhYSE6Pnnn7dmTgAAAAAAoIhYXAgYOHCgRowYoZCQEGvmAwAACsulq60zAAAAtzGLJwv09fVVSkqKNXMBAAAAAABFzOJCQOfOnbV27VrduHHDmvkAAAAAAIAiZHEhYPr06apQoYK6deumAwcOWDMnAAAAAABQRCyeI6BZs2a6ceOGoqKitHr1apUrV05Vq1aVyWTKFGcymXT8+PFCJwoAAAAAAArP4kJAWlqaypYtqxo1amRabhhGrq8BAAAAAIDtWFwIOHnypBXTAAAAAAAAxcHiOQIGDBigt99+25q5AAAAAACAImZxIWD58uU6d+6cNXMBAAAAAABFzOJCQJ06dRQTE2PNXAAAAAAAQBGzeI6AAQMG6LXXXtPff/+tatWqWTMnAACKjcmrr61TAAAAKFYWFwK6d++uDRs2qE2bNhozZoz+85//yNvbO8vtAyVlubMAAAAAAACwDYsLAbVr15bJZJJhGHrmmWdyjDOZTEpJSbH0bQAAAAAAgBVZXAjo27dvtmf/AQBA6bJp0yYNGzZMR48eVb169fTee++pdevWFsXPmDFDM2bMMMcahqFr167pq6++Urdu3Yq8LwAAoBCFgMWLF1sxDQAAcDu6dOmSOnXqpDfeeEN9+/bV0qVL1alTJx0/flweHh4Fjh8/frzGjx9vjv/qq680cOBAPfzww8XYKwAA7JvFdw0AAACl34oVK1StWjWFh4fL2dlZ4eHh8vHx0YoVK6wSHxkZqSeffFLly5cvym4AAIAMLB4RkNGmTZsUFRWl+Ph4ubm5KSgoSG3btrVG0wAAwIb27t2roKCgTMuCgoK0d+/eQsefOXNGP/30k7Zv326tdAEAQD4UqhCwefNmhYWF6dixY5JuXueXPm9A3bp1tWjRolyvIQSA0spUZZCtU7C60tgn5C0hISHLJQAeHh66evVqoeMXLVqkJk2aqHnz5tZKFwAA5IPFhYADBw6oQ4cOunbtmh566CHdf//98vX1VWxsrDZs2KA1a9YoJCREW7duVaNGjayZMwAAKCLLli3Tf//7X0lSzZo1FRwcrEuXLmWKiYuLU5UqVbLd3tXVNV/xhmFo0aJFioiIsGL2AAAgPyyeI2Dq1KlKSkrSDz/8oJ9++kkvvvii+vXrp7Fjx2r16tX64YcfdP36dU2dOtWa+QIAgCLUu3dvJSQkKCEhQQcOHFCTJk0UFRWVKSYqKkqBgYHZbp/f+PXr1ysmJkZ9+vSxZvoAACAfLC4EbNy4UY8//rhCQ0OzXR8aGqrHH39cGzZssDg5AABgW127dtWZM2cUGRmppKQkRUZGKiYmRl27di1UfGRkpLp165btnQcAAEDRsrgQEBcXp4CAgFxjAgICFBcXZ+lbAAAAG/Py8tKqVas0e/Zsubu7a86cOVq1apU8PT0lSdHR0XJ1dVV0dHS+4qWbtxhcsWKFBg1i3gkAAGzB4kKAn5+ftm7dmmvMtm3b5OfnZ+lbAABQ4mzatElNmzaVi4uLgoKCtGXLlhxjY2Ji1LlzZ/n5+clkMmUZUr9//36FhISocuXKMplMunLlStEmn4N77rlHe/fu1b///qs9e/aoTZs25nU1atRQQkKCatSoka946Wax4Pr167r//vuLrQ8AAOD/WFwI6Ny5szZu3KiJEyfq+vXrmdZdv35dkydP1oYNG/TYY48VOkkAAEqCS5cuqVOnThoxYoQuX76s4cOHq1OnTjkewDs4OCg0NFQrV67Mdr2Tk5N69uypxYsXF1nOAADA/lh814CJEyfqu+++04wZM/T++++rZcuW8vb21tmzZ7Vjxw6dP39etWvX1sSJE62ZLwAAt60VK1aoWrVqCg8PlySFh4dr1qxZWrFihcLCwrLEe3t7a9iwYTm2V79+fdWvX18nT54sqpQBAIAdsrgQUKlSJW3dulVjxozRp59+qh9++MG8rly5cgoLC9Prr78uLy8vqyQKAMDtbu/evQoKCsq0LCgoSHv37rVNQgAAANmwuBAgSZUrV9bChQv1/vvv6/Dhw4qPj5ebm5saNGggJycna+UIAECJkJCQkGUWfA8PD129etU2CQEAAGSjwHMETJ8+XePHj1dycrJ5mZOTkwIDA9W2bVsFBgbKMAy99NJLeu2116yaLAAAt5Nly5bJ1dVVrq6uuvPOO+Xq6prlbjlxcXGqWLGijTIEAADIqkAjAtatW6dJkybpjTfeyPWMf9myZVWpUiW98MILatWqFbMCA8iRqUaErVMALNa7d2/17t3b/DoyMlKzZs3KFBMVFaWICL7nAADg9lGgEQFLly6Vp6enRowYkWfs8OHD5eXlpUWLFlmcHADgJmveki6j8ePHy2Qy5ThrfVEqjX3q2rWrzpw5o8jISCUlJSkyMlIxMTHq2rVrjttcv37dfPedpKQkXb9+XWlpaZIkwzB0/fp13bhxQ5J048YNXb9+XYZhFH1nAABAqVWgQsDmzZsVHBwsZ2fnPGOdnZ0VHBysTZs2WZwcAMD6t6RLt2fPHq1atUq+vr7WTzoPpbFPkuTl5aVVq1Zp9uzZcnd315w5c7Rq1Sp5enpKkqKjo+Xq6qro6GjzNuXLl1f58uUlSa1atVL58uX166+/SpJOnTql8uXLq0GDBpIkHx8flS9fXqdOnSrmngEAgNKkQIWAf/75R7Vr1853fEBAgGJiYgqcFADg/2S8JZ2zs7PCw8Pl4+OjFStWZBuffku6li1b5thmamqqBg0apHfffVdly5YtqtRzVBr7lO6ee+7R3r179e+//2rPnj1q06aNeV2NGjWUkJCgGjVqmJcZhpHl0b59e0lSrVq1sl1fq1atYu4VAAAoTQpUCHBwcMg0SWBekpOT5eBQ4PkIAQAZFMUt6d5++201adJE7dq1K2R2limNfQIAACgpCjRZoJ+fn/bv35/v+P3796tatWoFTgoA8H+sfUu6v/76S++++6527dplhewsUxr7BAAAUFIU6HT9vffeq59//lknT57MM/bkyZP6+eefdd9991maGwDYpaK+Jd3gwYM1bdo0eXl5WSPdfCmNfQIAACipClQIGD58uJKTk/X444/rwoULOcZdvHhRPXr0UEpKioYOHVroJAHAnvTu3VsJCQlKSEjQgQMH1KRJkyyz5EdFRSkwMNCi9tevX6/nnntOlStXVuXKlXX69Gn17dtXzz//vBWyz15p7BMAAEBJVaBLA+666y4999xzmjVrlho1aqQhQ4bo/vvvV/Xq1SVJf//9t9avX68FCxbo/PnzioiI0F133VUkiQOAvejatatGjx6tyMhIPf300/roo4/ydUu6dOm3pCtbtqwcHBx0+vTpTLGtW7fWlClT1K1btyLrw61KY58AAABKigIVAiTpf//7n8qVK6eZM2dq+vTpmj59eqb1hmHI0dFR48aN07Rp06yWKADYq/Rb0g0bNkwjRoxQvXr1stySrlGjRjp48KB5Nvr029FJN29JJ0kbNmxQ+/btzcXbdI6OjqpUqZK5veJQGvsEAABQUpgMwzAs2fD48eNatGiRNm/erNjYWEk372/ctm1b9e/fX3Xq1LFqotm5dOmSRo4cqVWrVsnBwUHdu3fX7Nmz5erqmmP85MmTtWbNGkVHR6tKlSrq0qWLXnnlFbm7u5vjTCZTlm0/+eQT9erVK9+5xcfHy93dXXFxcXJzcyt454pR2rqRtk4h3xyC38lXXNrmF4o4E+txaDMz37FpW8cWYSbW5XD367ZOAQAAALAr+T0OLfCIgHR16tSx+Rn/3r17KyYmRmvXrlVycrLCwsI0ePBgLV++PNv4f/75R//884/efPNNNWrUSKdOndKQIUP0zz//6Msvv8wUu2jRIoWGhppf3zq7NQAAAAAAJZHFhQBbO3TokFavXq0dO3aoRYsWkqR33nlHjzzyiN588035+fll2aZx48b66quvzK/r1Kmj6dOnq0+fPkpJSVGZMv/3cXh4eMjHx6foOwIAAAAAQDEq0F0DbidbtmyRh4eHuQggScHBwXJwcNC2bdvy3U76kImMRQDp5h0SKleurJYtW2rhwoXK6wqKGzduKD4+PtMDQPHbtGmTmjZtKhcXFwUFBWnLli05xsbExKhz587y8/OTyWTKMot9SkqKXnrpJfn7+8vNzU1du3bVuXPnirgHAAAAQNEqsYWA2NhYVa1aNdOyMmXKyMvLyzxnQV4uXLigV155RYMHD860fOrUqfr888+1du1ade/eXcOGDdM77+R+bfqrr74qd3d388Pf379gHQJQaJcuXVKnTp00YsQIXb58WcOHD1enTp105cqVbOMdHBwUGhqqlStXZrt+5syZ+v7777V161adPXtW7u7u6tOnT9F1AAAAACgGt10h4MUXX5TJZMr1cfjw4UK/T3x8vDp27KhGjRppypQpmdZNnDhRbdu2VbNmzTR27FiNGTNGM2fmPqHbuHHjFBcXZ37ceisrAEVvxYoVqlatmsLDw+Xs7Kzw8HD5+PhoxYoV2cZ7e3tr2LBhatmyZY7tPfPMM6pWrZrKly+vl19+WWvXrtXJkyeLsBcAAABA0brt5ggYNWqU+vfvn2tM7dq15ePjk2WIbkpKii5dupTntf1Xr15VaGioKlasqBUrVsjJySnX+FatWumVV17RjRs35OzsnG2Ms7NzjusAFI+9e/cqKCgo07KgoCDt3bvXovbS0tIyXRaUlpZmfp9atWpZmiYAAABgU7ddIaBKlSqqUqVKnnGtW7fWlStXtHPnTjVv3lyS9PPPPystLc18f+nsxMfHKyQkRM7Ozvr2229Vrly5PN8rKipKnp6eHOgDt7mEhIQsd/jw8PDQ1atXLWqvY8eOmj17th566CF5eXlp0qRJMplMzAECAACAEu22uzQgvxo2bKjQ0FCFh4dr+/bt2rRpk0aMGKFevXqZ7xjw999/q0GDBtq+fbukm0WADh06KDExUZGRkYqPj1dsbKxiY2OVmpoqSVq1apU+/PBD7d+/X8eOHdN7772nGTNmaOTIkTbrK4DsLVu2TK6urnJ1ddWdd94pV1dXxcXFZYqJi4tTxYoVLWp/3LhxCg4O1r333qt69eopKChIrq6uqlSpkjXSBwAAAGyixBYCpJsHAQ0aNNCDDz6oRx55RPfcc48WLFhgXp+cnKwjR47o2rVrkqRdu3Zp27Zt2rdvn+644w75+vqaH+nX9Ds5OWnu3Llq3bq1goKC9P777+utt97S5MmTbdJHADnr3bu3EhISlJCQoAMHDqhJkyZZZv6PiopSYGCgRe2XK1dOb731lk6dOqV//vlHjzzyiJKSknIddQQAAADc7m67SwMKwsvLS8uXL89xfa1atTJd39u+ffs8bwMYGhqq0NBQq+UIoPh07dpVo0ePVmRkpJ5++ml99NFHiomJUdeuXXPc5vr16+bnSUlJun79usqWLSsHBwfFxMQoKSlJNWrU0LFjxzRw4EBFRETIy8urOLoDAAAAFIkSPSIAADLy8vLSqlWrNHv2bLm7u2vOnDlatWqVPD09JUnR0dFydXVVdHS0eZvy5curfPnykm5ODFq+fHn9+uuv5vgHHnhAFSpUUHBwsDp16qTp06cXf8cAAAAAKyrRIwIA4Fb33HNPjncJqFGjhhISEjIty22UUKtWrXT8+HGr5gcAAADYGiMCAAAAAACwIxQCAAAAAACwIxQCAAAAAACwI8wRAJQgDne/busUAAAAAJRwjAgAAAAAAMCOMCIApZJDm5m2TgEAAAAAbkuMCAAAAAAAwI5QCAAAAAAAwI5QCAAAAAAAwI5QCAAAAAAAwI5QCAAAAAAAwI5QCAAAAAAAwI5QCAAAAAAAwI5QCAAAAAAAwI6UsXUCsD2H4HdsnQIAAAAAoJgwIgCwY5s2bVLTpk3l4uKioKAgbdmyJcfYXbt2qXnz5vLy8pKHh4fatGmjX3/9tRizBQAAAGANFAIAO3Xp0iV16tRJI0aM0OXLlzV8+HB16tRJV65cyTa+Zs2a+vrrr3Xx4kVdvnxZo0ePVseOHfXvv/8Wb+IAAAAACoVCAJAP1jxzvn//foWEhKhy5coymUw5HngXtRUrVqhatWoKDw+Xs7OzwsPD5ePjoxUrVmQbX6lSJdWsWVMmk0mGYcjR0VEJCQmKjY0t5swBAAAAFAaFACAP1j5z7uTkpJ49e2rx4sXF14ls7N27V0FBQZmWBQUFae/evblu5+HhobJly6pLly7q27evAgICijBLAAAAANZGIQDIg7XPnNevX18DBw5U48aNi7MbWSQkJMjDwyPTMg8PD129ejXX7a5cuaKrV6/qo48+0r333luEGQIAAAAoChQCgDyUljPny5Ytk6urq1xdXXXnnXfK1dVVcXFxmWLi4uJUsWLFPNsqX768+vTpo7ffflu///57UaUMAAAAoAhQCADyUFrOnPfu3VsJCQlKSEjQgQMH1KRJE0VFRWWKiYqKUmBgYL7bTE5O1tGjR62cKQAAAICiRCEAuIW9nDnv2rWrzpw5o8jISCUlJSkyMlIxMTHq2rVrtvHfffed9u7dq5SUFF27dk0zZszQmTNndN999xVz5gAAAAAKg0IAcAt7OXPu5eWlVatWafbs2XJ3d9ecOXO0atUqeXp6SpKio6Pl6uqq6OhoSdKFCxfUo0cPeXh4qEaNGlq7dq2+//571alTx5bdAAAAAFBAJsMwDFsnURrFx8fL3d1dcXFxcnNzs3U6KIRLly6pTp06evPNN/X000/ro48+0pgxY3Ts2DHzQXNG3333nWrUqKFGjRopKSlJs2bN0rRp07Rv3z7VqVNHhmHoxo0bOnXqlBo0aKDY2Fi5u7vL2dlZJpPJBj0EAAAAUBrk9ziUEQFAHqx95vzUqVMqX768GjRoIEny8fFR+fLlderUKdt0EAAAAIBdYURAEWFEAAAAAACgODEiADazadMmNW3aVC4uLgoKCtKWLVtyjN21a5eaN28uLy8veXh4qE2bNvr111/N6zdu3CiTyWSevM/V1VUjRowojm4AAAAAQKlUxtYJoHS5dOmSOnXqpDfeeEN9+/bV0qVL1alTJx0/fjzLLfgkqWbNmvr6669Vo0YNSdKKFSvUsWNHnTt3TuXLl5ckubu768qVK8XYCwAAAAAovRgRAKtasWKFqlWrpvDwcDk7Oys8PFw+Pj5asWJFtvGVKlVSzZo1ZTKZZBiGHB0dlZCQoNjY2GLOHAAAAADsAyMCYFV79+5VUFBQpmVBQUHau3dvrtt5eHgoISFBqamp6tu3rwICAszrEhIS5OfnJwcHB7Vr105vvPGGqlWrVhTpAwAAAECpx4gAWFVCQkKWSwA8PDx09erVXLe7cuWKrl69qo8++kj33nuveXmDBg0UFRWl06dP648//pBhGHr00UeVlpZWFOkDAAAAQKlHIQCFsmzZMvMkfnfeeadcXV0VFxeXKSYuLk4VK1bMs63y5curT58+evvtt/X7779LunlrvcaNG8vR0VE+Pj5asGCB9uzZoz///LNI+gMAAAAApR2FABRK7969lZCQoISEBB04cEBNmjRRVFRUppioqCgFBgbmu83k5GQdPXo023Umk6kw6QIAAACA3aMQAKvq2rWrzpw5o8jISCUlJSkyMlIxMTHq2rVrtvHfffed9u7dq5SUFF27dk0zZszQmTNndN9990mSNmzYoBMnTsgwDF28eFFDhw7VnXfeqbp16xZntwAAAACg1KAQAKvy8vLSqlWrNHv2bLm7u2vOnDlatWqVPD09JUnR0dFydXVVdHS0JOnChQvq0aOHPDw8VKNGDa1du1bff/+96tSpI0navXu37rvvPrm6uqpx48ZKSUnRd999J0dHR5v1EQAAAABKMpNhGIatkyiN4uPj5e7urri4OLm5udk6HQAAAABAKZff41BGBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEcoBAAAAAAAYEdKdCHg0qVL6t27t9zc3OTh4aGBAwcqISEh123at28vk8mU6TFkyJBMMdHR0erYsaNcXFxUtWpVvfDCC0pJSSnKrgAAAAAAUCzK2DqBwujdu7diYmK0du1aJScnKywsTIMHD9by5ctz3S48PFxTp041v3ZxcTE/T01NVceOHeXj46PNmzcrJiZGffv2lZOTk2bMmFFkfQEAAAAAoDiYDMMwbJ2EJQ4dOqRGjRppx44datGihSRp9erVeuSRR3TmzBn5+fllu1379u0VFBSkWbNmZbv+xx9/VKdOnfTPP//I29tbkjR//nyNHTtW58+fV9myZfOVX3x8vNzd3RUXFyc3N7eCdxAAAAAAgALI73Foib00YMuWLfLw8DAXASQpODhYDg4O2rZtW67bLlu2TJUrV1bjxo01btw4Xbt2LVO7gYGB5iKAJIWEhCg+Pl4HDhywfkcAAAAAAChGJfbSgNjYWFWtWjXTsjJlysjLy0uxsbE5bvfUU0+pZs2a8vPz0969ezV27FgdOXJEX3/9tbndjEUASebXubV748YN3bhxw/w6Pj6+wH0CAAAAAKCo3XaFgBdffFGvv/56rjGHDh2yuP3BgwebnwcGBsrX11cPPvigjh8/rjp16ljc7quvvqqXX37Z4u0BAAAAACgOt10hYNSoUerfv3+uMbVr15aPj4/OnTuXaXlKSoouXbokHx+ffL9fq1atJEnHjh1TnTp15OPjo+3bt2eKOXv2rCTl2u64ceMUERFhfh0fHy9/f/985wEAAAAAQHG47QoBVapUUZUqVfKMa926ta5cuaKdO3eqefPmkqSff/5ZaWlp5oP7/IiKipIk+fr6mtudPn26zp07Z770YO3atXJzc1OjRo1ybMfZ2VnOzs75fl8AAAAAAGyhxE4W2LBhQ4WGhio8PFzbt2/Xpk2bNGLECPXq1ct8x4C///5bDRo0MJ/hP378uF555RXt3LlTJ0+e1Lfffqu+ffvqvvvuU5MmTSRJHTp0UKNGjfT0009rz549+umnnzRhwgQNHz6cA30AAAAAQIlXYgsB0s3Z/xs0aKAHH3xQjzzyiO655x4tWLDAvD45OVlHjhwx3xWgbNmyWrdunTp06KAGDRpo1KhR6t69u1atWmXextHRUd99950cHR3VunVr9enTR3379tXUqVOLvX8AAAAAAFibyTAMw9ZJlEb5vX8jAAAAAADWkN/j0BI9IgAAAAAAABQMhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOwIhQAAAAAAAOxIiS4EXLp0Sb1795abm5s8PDw0cOBAJSQk5Bh/8uRJmUymbB9ffPGFOS679Z9++mlxdAkAAAAAgCJVxtYJFEbv3r0VExOjtWvXKjk5WWFhYRo8eLCWL1+ebby/v79iYmIyLVuwYIFmzpyphx9+ONPyRYsWKTQ01Pzaw8PD6vkDAAAAAFDcSmwh4NChQ1q9erV27NihFi1aSJLeeecdPfLII3rzzTfl5+eXZRtHR0f5+PhkWrZixQr17NlTrq6umZZ7eHhkiQUAAAAAoKQrsZcGbNmyRR4eHuYigCQFBwfLwcFB27Zty1cbO3fuVFRUlAYOHJhl3fDhw1W5cmW1bNlSCxculGEYubZ148YNxcfHZ3oAAAAAAHC7KbEjAmJjY1W1atVMy8qUKSMvLy/Fxsbmq43IyEg1bNhQbdq0ybR86tSpeuCBB+Ti4qI1a9Zo2LBhSkhI0DPPPJNjW6+++qpefvnlgncEAAAAAIBidNuNCHjxxRdznNAv/XH48OFCv8+///6r5cuXZzsaYOLEiWrbtq2aNWumsWPHasyYMZo5c2au7Y0bN05xcXHmx+nTpwudIwAAAAAA1nbbjQgYNWqU+vfvn2tM7dq15ePjo3PnzmVanpKSokuXLuXr2v4vv/xS165dU9++ffOMbdWqlV555RXduHFDzs7O2cY4OzvnuA4AAAAAgNvFbVcIqFKliqpUqZJnXOvWrXXlyhXt3LlTzZs3lyT9/PPPSktLU6tWrfLcPjIyUp07d87Xe0VFRcnT05MDfQAAAABAiXfbFQLyq2HDhgoNDVV4eLjmz5+v5ORkjRgxQr169TLfMeDvv//Wgw8+qKVLl6ply5bmbY8dO6Zff/1VP/zwQ5Z2V61apbNnz+ruu+9WuXLltHbtWs2YMUOjR48utr4BAAAAAFBUSmwhQJKWLVumESNG6MEHH5SDg4O6d++uOXPmmNcnJyfryJEjunbtWqbtFi5cqOrVq6tDhw5Z2nRyctLcuXP1/PPPyzAM3XHHHXrrrbcUHh5e5P0BAAAAAKComYy87osHi8THx8vd3V1xcXFyc3OzdToAAAAAgFIuv8eht91dAwAAAAAAQNGhEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB2hEAAAAAAAgB0p0YWA6dOnq02bNnJxcZGHh0e+tjEMQ5MmTZKvr6/Kly+v4OBgHT16NFPMpUuX1Lt3b7m5ucnDw0MDBw5UQkJCEfQAAAAAAIDiVaILAUlJSerRo4eGDh2a723eeOMNzZkzR/Pnz9e2bdtUoUIFhYSE6Pr16+aY3r1768CBA1q7dq2+++47/frrrxo8eHBRdAEAAAAAgGJlMgzDsHUShbV48WI999xzunLlSq5xhmHIz89Po0aN0ujRoyVJcXFx8vb21uLFi9WrVy8dOnRIjRo10o4dO9SiRQtJ0urVq/XII4/ozJkz8vPzy1dO8fHxcnd3V1xcnNzc3ArVPwAAAAAA8pLf49AyxZiTzZ04cUKxsbEKDg42L3N3d1erVq20ZcsW9erVS1u2bJGHh4e5CCBJwcHBcnBw0LZt29S1a9ds275x44Zu3Lhhfh0XFyfp5g8CAAAAAICiln78mdf5frsqBMTGxkqSvL29My339vY2r4uNjVXVqlUzrS9Tpoy8vLzMMdl59dVX9fLLL2dZ7u/vX9i0AQAAAADIt6tXr8rd3T3H9bddIeDFF1/U66+/nmvMoUOH1KBBg2LKKH/GjRuniIgI8+u0tDRdunRJlSpVkslksmFmxS8+Pl7+/v46ffp0qbosojT2qzT2SSqd/SqNfZJKZ79KY5+k0tmv0tgnqXT2qzT2SSqd/SqNfZJKZ79KY5+k0tuv/DIMQ1evXs3zkvbbrhAwatQo9e/fP9eY2rVrW9S2j4+PJOns2bPy9fU1Lz979qyCgoLMMefOncu0XUpKii5dumTePjvOzs5ydnbOtCy/dzIordzc3ErlL19p7Fdp7JNUOvtVGvsklc5+lcY+SaWzX6WxT1Lp7Fdp7JNUOvtVGvsklc5+lcY+SaW3X/mR20iAdLddIaBKlSqqUqVKkbQdEBAgHx8frV+/3nzgHx8fr23btpnvPNC6dWtduXJFO3fuVPPmzSVJP//8s9LS0tSqVasiyQsAAAAAgOJSom8fGB0draioKEVHRys1NVVRUVGKiopSQkKCOaZBgwZasWKFJMlkMum5557TtGnT9O2332rfvn3q27ev/Pz81KVLF0lSw4YNFRoaqvDwcG3fvl2bNm3SiBEj1KtXr3zfMQAAAAAAgNvVbTcioCAmTZqkJUuWmF83a9ZMkrRhwwa1b99eknTkyBHzDP6SNGbMGCUmJmrw4MG6cuWK7rnnHq1evVrlypUzxyxbtkwjRozQgw8+KAcHB3Xv3l1z5swpnk6VAs7Ozpo8eXKWSyVKutLYr9LYJ6l09qs09kkqnf0qjX2SSme/SmOfpNLZr9LYJ6l09qs09kkqnf0qjX2SSm+/rM1k5HVfAQAAAAAAUGqU6EsDAAAAAABAwVAIAAAAAADAjlAIAAAAAADAjlAIAAAAAADAjlAIAAAAmaSkpGjq1Kk6c+aMrVMBAABFgEIAkE8JCQmKj4/P9Cipjh8/rgkTJujJJ5/UuXPnJEk//vijDhw4YOPMkJ2kpCQdOXJEKSkptk7FKhYvXpzt8pSUFI0bN654k0G2ypQpo5kzZ5aa7xwAAMiMQgCQixMnTqhjx46qUKGC3N3d5enpKU9PT3l4eMjT09PW6Vnkl19+UWBgoLZt26avv/5aCQkJkqQ9e/Zo8uTJNs7OctHR0crubqiGYSg6OtoGGRXetWvXNHDgQLm4uOjOO+8092PkyJF67bXXbJyd5Z555hn16NFDly9fNi87cuSIWrVqpU8++cSGmRVOu3bttHTpUv3777+2TsUqHnjgAf3yyy+2TgP59Ouvv2ZbuElJSdGvv/5qg4wKLzk5WXXq1NGhQ4dsnYpV7dq1S/v27TO//uabb9SlSxeNHz9eSUlJNszM+q5cuWLrFGBHjh49qgULFmjatGmaOnVqpgeyMhnZ/eUM5NPevXvzHdukSZMizKRotG3bVoZh6Nlnn5W3t7dMJlOm9e3atbNRZpZr3bq1evTooYiICFWsWFF79uxR7dq1tX37dnXr1q3EDgV2dHRUTEyMqlatmmn5xYsXVbVqVaWmptooM8s9++yz2rRpk2bNmqXQ0FDt3btXtWvX1jfffKMpU6Zo9+7dtk7RIsePH1efPn10+vRpLVq0SH/++afGjBmjLl26aN68eXJ3d7d1ihZ57rnntHz5ct24cUM9e/bUwIEDdffdd9s6LYvNnz9fL7/8snr37q3mzZurQoUKmdZ37tzZRplZx+XLlxUZGWk+yGzYsKEGDBggLy8vG2dmmdK4D5SkatWqad26dWrYsKGtU7Ga//znP3rxxRfVvXt3/fXXX7rzzjvVtWtX7dixQx07dtSsWbNsnaJFXn/9ddWqVUtPPPGEJKlnz5766quv5OPjox9++EFNmza1cYb5061bt3zHfv3110WYSdFZsmSJKleurI4dO0qSxowZowULFqhRo0b65JNPVLNmTRtnWHAffPCBhg4dqsqVK8vHxyfT3+wmk0m7du2yYXa3KQMoBJPJZDg4OJj/ze1RElWoUME4fPiwrdOwqgoVKhh//fWXYRiG4erqahw/ftwwDMM4ceKE4ezsbMvUCsVkMhnnzp3LsvzkyZOGi4uLDTIqvBo1ahhbtmwxDCPzz+ro0aNGxYoVbZlaoaWmphojR440HBwcDCcnJ2P58uW2TskqkpOTja+++sro3Lmz4eTkZDRs2NCYOXOmERsba+vUCsxkMuX4KKn79HS//PKL4e7ubvj7+xtdu3Y1unbtatSoUcNwc3MzfvnlF1unZ5Gc9oFHjhwp0fuL6dOnG/369TOSk5NtnYrVuLm5GceOHTMMwzBee+01o0OHDoZhGMbvv/9uVK9e3ZapFUqtWrWMTZs2GYZhGGvWrDE8PDyMn376yRg4cKDx0EMP2Ti7/Ovfv7/50a9fP8PNzS3bfUX//v1tnarF6tWrZ6xfv94wDMPYvHmz4eLiYrz//vvGo48+anTt2tXG2VmmRo0axmuvvWbrNEqUMrYuRKBkO3HihPn57t27NXr0aL3wwgtq3bq1JGnLli363//+pzfeeMNWKRbKf/7zH50+fVr169e3dSpW4+HhoZiYGAUEBGRavnv3blWrVs1GWVkuIiJC0s1q78SJE+Xi4mJel5qaqm3btikoKMhG2RXO+fPns5zdk6TExMQso1NKmu+//16ffvqpWrdurT///FORkZFq166d/Pz8bJ1aoZQpU0bdunVTt27ddO7cOS1YsEATJ07U+PHj9cgjj+iZZ57RAw88YOs08yUtLc3WKRSZ4cOHq2fPnnrvvffk6Ogo6eb+YtiwYRo+fHimYdu3u/SzlyaTSf3795ezs7N5XWpqqvbu3as2bdrYKr1C27Fjh9avX681a9YoMDAwy8iUknhG1jAM8+/XunXr1KlTJ0mSv7+/Lly4YMvUCiU2Nlb+/v6SpO+++049e/ZUhw4dVKtWLbVq1crG2eXfokWLzM/Hjh2rnj17av78+Vn2FW5ubrZKsdBOnz6tO+64Q5K0cuVKde/eXYMHD1bbtm3Vvn172yZnocuXL6tHjx62TqNEoRCAQsk4dKhHjx6aM2eOHnnkEfOyJk2ayN/fXxMnTlSXLl1skGHhfPjhhxoyZIj+/vtvNW7cWE5OTpnWl8TLHXr16qWxY8fqiy++kMlkUlpamjZt2qTRo0erb9++tk6vwNKHxxuGoX379qls2bLmdWXLllXTpk01evRoW6VXKC1atND333+vkSNHSpL54P/DDz80F9tKov/+979asmSJpk+froiICJ09e1YDBgxQYGCg3nvvPfXs2dPWKRba9u3btWjRIn366aeqWrWq+vfvr7///ludOnXSsGHD9Oabb9o6Rbt27Ngxffnll+Y/7KWbQ+sjIiK0dOlSG2ZWcOmX0hiGoYoVK6p8+fLmdWXLltXdd9+t8PBwW6VXaB4eHurevbut07CqFi1aaNq0aQoODtYvv/yi9957T9LNkyve3t42zs5ynp6eOn36tPz9/bV69WpNmzZN0s3vZkm9NGXhwoX6/fffs91XtGnTRjNnzrRhdpZzdXXVxYsXVaNGDa1Zs8Z8UqVcuXIldp6bHj16aM2aNRoyZIitUykxKATAavbt25flLLMkBQQE6ODBgzbIqPDOnz+v48ePKywszLzMZDLJMAyZTKYS+R/bjBkzNHz4cPn7+ys1NVWNGjVSamqqnnrqKU2YMMHW6RXYhg0bJElhYWGaPXt2ia7Q32rGjBl6+OGHdfDgQaWkpGj27Nk6ePCgNm/eXKIncdu0aZO2bdtmvl40/frRuXPnasCAASW2EHDu3Dl99NFHWrRokY4ePapHH31Un3zyiUJCQsxFnP79+ys0NLTEFAISExP1yy+/KDo6OsskZs8884yNsiq8u+66S4cOHcoy2uvQoUMl5jrmdOlnL2vVqqUXXngh06io0iDj2dnSYtasWerdu7dWrlypl156yXxm9ssvvyzRoze6deump556SnXr1tXFixf18MMPS7pZsE/vY0mTkpKiw4cPZ9lXHD58uESPmnrooYc0aNAgNWvWTH/++af5JN6BAwdUq1Yt2yZnoTvuuEMTJ07U1q1bFRgYmOXkXUn+P6uoMFkgrOauu+5S48aN9eGHH5rPyiYlJWnQoEHav39/iZyko1GjRmrYsKHGjBmT7WSBJXEylXSnT5/Wvn37lJCQoGbNmqlu3bq2TgnZOH78uF577TXt2bNHCQkJuuuuuzR27FgFBgbaOjWL3bhxI9Pw5YyOHDlSYi/FKVu2rOrUqaMBAwaof//+qlKlSpaY+Ph4PfbYY+YC1u1s9+7deuSRR3Tt2jUlJibKy8tLFy5ckIuLi6pWraq//vrL1ila7LPPPtOYMWM0cuRI84SOW7du1dy5c/Xaa69lmpiupIz8OnHihFJSUrLsy48ePSonJ6cS+8e9Pbl+/bocHR2zHMCUFMnJyZo9e7ZOnz6t/v37q1mzZpKkt99+WxUrVtSgQYNsnGHBpY8SGj9+vFq2bClJ2rZtm1577TU9/fTTeuutt2ycoWWuXLmiCRMm6PTp0xo6dKhCQ0MlSZMnT1bZsmX10ksv2TjDgsvuZGQ6k8lUov/PKioUAmA127dv16OPPirDMMx/OO3du1cmk0mrVq0y70BLkgoVKmjPnj0ltpKdnalTp2r06NFZzhr9+++/mjlzpiZNmmSjzAonMTFRr732mtavX69z585lqdTzHwCK2m+//aZ7773X1mlYTfv27VWvXj3Nnz9f7u7u2rNnj5ycnNSnTx89++yzBZpZ+3bj4JD73ZNL4sivdu3aacCAAerXr1+m5R9//LE+/PBDbdy40TaJWcGXX36pzz//PNuRKSXxJENplZiYmGUOh5IuLS1Nb775pmbPnq2YmBhJkq+vr5599lmNGjUq0yUDQElDIQBWlZiYqGXLlunw4cOSbt6O6amnniqx/zE8+uij6t+/f6m6PrG03mLqySef1C+//KKnn35avr6+WUZvPPvsszbKrHDS0tJ07NixbIsb9913n42yKrhmzZrle4JD/rC/PXh4eGjbtm2qX7++PDw8tGXLFjVs2FDbtm1Tv379zPv5kujUqVP5ji0pI7/c3Ny0a9euLIXrY8eOqUWLFiX2fu5z5szRSy+9pP79+2vBggUKCwvT8ePHtWPHDg0fPlzTp0+3dYoF5uDgkOv+sKT+P+zq6qqePXtqwIABuueee2ydjtXFx8dLUqm4BHH16tVydXU1/5zmzp2rDz74QI0aNdLcuXPl6elp4wwLJ/3wtqRPrFzUmCMAVlWhQgUNHjzY1mlYzaOPPqrnn39e+/bty/Z6o5J4H+30s1y32rNnT4m9f7Yk/fjjj/r+++/Vtm1bW6diNVu3btVTTz2lU6dO6daabUk6Uykp02Sh169f17x589SoUSPzpIdbt27VgQMHNGzYMBtlaB2l6cylk5OT+cx51apVFR0drYYNG8rd3V2nT5+2cXaFU1IO7gvCZDLp6tWrWZbHxcWVqH3FrebNm6cFCxboySef1OLFizVmzBjVrl1bkyZN0qVLl2ydnkVWrFiR6XVycrJ2796tJUuW6OWXX7ZRVoX38ccfa/HixXrggQdUq1YtDRgwQH379i3xd4NJSUnRxo0bdfz4cT311FOSpH/++Udubm5ydXW1cXaWeeGFF/T6669LujnH16hRoxQREaENGzYoIiKixM7NsXTpUs2cOVNHjx6VJNWrV08vvPCCnn76aRtndpsq/jsWojRbunSp0bZtW8PX19c4efKkYRiG8dZbbxkrV660cWaWKU330fbw8DA8PT0NBwcH8/P0h5ubm+Hg4GAMGzbM1mlarFatWsbBgwdtnYZVNW3a1OjRo4dx8OBB4/Lly8aVK1cyPUqqgQMHGhMmTMiyfNKkSUZYWJgNMrKO2bNnG66ursaIESOMsmXLGv/973+N4OBgw93d3Rg/fryt0yuwhx56yFi2bJlhGIYxaNAgo2XLlsbHH39shISEGC1btrRxdoW3dOlSo02bNpn+v3r77bdL7P9XnTp1Mnr06GGkpKSYl6WkpBjdu3c3QkNDbZhZ4ZQvX97886lSpYoRFRVlGIZh/Pnnn4aXl5ctU7O6ZcuWGZ07d7Z1GoV27tw543//+58RGBholClTxujYsaPx1VdfGcnJybZOrcBOnjxpNGjQwHBxcTEcHR2N48ePG4ZhGM8884zx3//+18bZWa5ChQrGiRMnDMMwjMmTJxvdu3c3DMMwdu7caXh7e9swM8v973//M1xcXIwxY8YY3/y/9u48rsb0/x/465RKaUWFpMUSJYkQRsi+m+xbtNgmSTOyfIylBmHsk7GmhGyNZSxD9qWUQsVEaSFShghJ2u7fH307v46T7XR0dd+9n4+Hx0PXOeqVOOe+39d1va9jx7hjx45xXl5enJqaGrd27VrW8aokKgQQufnzzz+5unXrckuXLuVq1qwpfrEMCAjgunXrxjgdCQwM5AICAjiRSMRt2LCBCwwMFP8KDg7mwsPDWUeskN27d3PDhw/n3r17xzqK3KipqXEPHjxgHUPuNDU1ucTERKnxxMRETlNTk0Ei+TAzM+OCg4M5juM4dXV18WvgwoULOTc3N5bRZBIVFcVduHCB4ziOe/bsGdenTx9OQ0ODa9OmjfhmjK/Kvl+pqqoK4v3q33//5erUqcM1btyYmzRpEjdp0iSucePGnK6uLnfnzh3W8WRmYmLC3bp1i+M4jmvbti23ZcsWjuM47syZM5yOjg7LaHKXnJzM1apVi3UMudq4cSOnoqLCiUQiTldXl1u4cCGv3qeHDBnCjR8/nvvw4YPE6/rFixe5Jk2aME4nOx0dHe7ff//lOI7jOnfuzG3dupXjOI5LTU3lVFVVWUaTmbGxMbdr1y6p8cDAQM7Y2JhBoqqPCgFEblq0aMEdOXKE4zjJi+A7d+5wderUYZiMlHXp0iUuPz+fdQy5a926NaehocGpq6tzLVu25KytrSV+8VH37t25f/75h3UMudPX1+cCAgKkxgMCAjg9Pb3KDyQn1Wnmku+E+n6Vnp7OzZ8/n+vfvz83bNgwztvbm8vKymIdq0JcXFy4JUuWcBzHcX5+fpyqqirXs2dPTltbm3N2dmacTn5yc3M5Dw8PrlmzZqyjVFhmZia3cuVKrkWLFpyamho3btw47sKFC1xQUBBnYWHB9erVi3XEr1a7dm3u/v37HMdJvlbw+YaZ4zhu0KBBXJ8+fTgfHx9OSUmJe/LkCcdxJQW2pk2bMk4nGxUVlXInTxITEzkVFRUGiao+6hFA5CY1NVV8VExZKioqePfuHYNEFXPv3j1ERESgY8eOaN68Oe7fv48NGzbgw4cPGD9+POzt7VlHlEnXrl3Fv8/Ly5Pax8zXJjhl96ALhbu7O3755RdkZmaW26OCL8eafWzWrFmYPn06bt26JXEc086dO7Fw4ULG6WRXr149vHz5EkZGRmjUqBEiIiJgZWWF1NRUqR4PhC2hvV+VatCgAZYvX846hlxt27ZN3CjVzc0NderUQXh4OAYPHoypU6cyTicbHR0diV49HMfh7du3UFNTw549exgmq5jDhw8jICAAZ86cgbm5OX766SeMHz8e2tra4ud06tRJ4njOqq64uLjcHhtPnjyBhoYGg0Ty4efnh59++gkhISHYvHkzDAwMAJT0Wyo9SpBvmjRpgoMHD+J///ufxPiBAwfoiOxPoEIAkRsTExPExMRINWE6ffo0r170gZLMQ4YMgbq6OnJzc3HkyBE4OjrCysoKxcXF6N27N0JDQ3lZDMjNzcWcOXNw8OBBZGVlST3O16ZSixcvZh1B7kpPq3B2dhaP8fFYs4/NmzcPpqam2LBhg/iit0WLFggICMDIkSMZp5Odvb09/v77b1hbW8PJyQmenp4ICQlBdHQ0b47aqy6nOwjp/aqs7Oxs+Pv74969ewAACwsLODs7Q0tLi3Ey2SkoKEgc9zh69GiMHj2aYaKKW79+vcTHCgoK0NXVRYcOHXjdrd3JyQmjR49GWFgY2rVrV+5zGjRowKsz6nv37o3169dj27ZtAEreg3NycrB48WL079+fcTrZNWrUCCdOnJAaX7duHYM08uHt7Y1Ro0bhypUr4sbRYWFhOH/+PA4ePMg4XdVExwcSudmxYweWLFmCNWvWwMXFBTt27EBycjJ8fX2xY8cOXr1xd+rUCfb29li6dCn279+Pn376CdOnTxcfUzR//nzcvHkToaGhjJN+Ozc3N1y8eBG//fYbJkyYgE2bNiE9PR1bt27FihUrMG7cONYRZZadnY2QkBAkJyfDy8sLtWvXxq1bt6Cvry+udvPJl444E2Lncz4rLi5GcXExatQoqbHv378f4eHhaNq0KaZOnQplZWXGCb/sWzqW87n4JqT3q1LR0dHo06cPVFVVxSttoqKi8P79e4SGhqJNmzaME8ouLy8PcXFx5R6jysfTe4QqNzcXampqrGPI1ZMnT9CnTx9wHIcHDx7AxsYGDx48QN26dXHlyhWpo5j5JDk5GQEBAUhOTsaGDRugp6eHf/75B40aNYKFhQXreDK5efMm1q1bJy6GtmjRAr/88ku5K8AIFQKInO3duxdLlixBcnIygJLKr7e3N1xcXBgn+zZaWlq4efMmmjRpguLiYqioqODGjRviF5K7d++iZ8+eyMzMZJz02zVq1AhBQUHo1q2bxLnTu3fvxr59+3Dq1CnWEWUSFxeHnj17QktLCw8fPkRCQgJMTU3x66+/Ii0tDUFBQawjEkKqEKG8X5Xq0qULmjRpgu3bt4uLUYWFhXB1dUVKSgquXLnCOKFsTp8+DUdHR7x48ULqMT6vjBLi6o2yhLT1sLCwEAcOHEBsbCxycnLQpk0bjBs3Dqqqqqyjyezy5cvo168fOnfujCtXruDevXswNTXFihUrEB0djZCQENYRSSWgQgD5LnJzc5GTk8PbSqmWlhZu3bqFxo0bAwA0NDQQGxsLU1NTACUztc2bN8f79+9ZxpSJuro64uPj0ahRIzRs2BCHDx9G+/btkZqaCktLS+Tk5LCOKJOePXuiTZs2WLVqlcTPKzw8HGPHjsXDhw9ZR5RJcnIy1q9fL75YNDc3h4eHh/jfJl/Url0biYmJqFu3rtT+2I/x9WxwgGYu+Yjv71elVFVVcfv2bTRv3lxiPD4+HjY2NsjNzWWUrGKaNm2K3r17Y9GiRdDX12cdRy6Eunrj3bt3mDt3rqC2Hl65cgWdOnUSF9dKFRYWIjw8HHZ2doySVUzHjh0xYsQI/PzzzxLXTDdu3ICDgwOePHnCOuJXefPmjbjA9ObNm88+l6+FqO+JegQQuVm8eDGcnZ1hZGQENTU1Xi8PMzY2xoMHD8Q3W9evX0ejRo3Ej6elpaF+/fqs4lWIqakpUlNT0ahRIzRv3hwHDx5E+/btcfz4cYmGPnwTFRWFrVu3So0bGBjwcuUGAJw5cwaDBw9G69atJfa7WVhY4Pjx4+jVqxfjhF9v3bp14sZKH++PFQohzFx+qUhTFp8LNu/fvwfHceL3qufPn2P9+vUwNzdH7969WceTiaamJtLS0qQKAY8fP+Z1U7Nnz57h559/FkwRAAA8PT0xePDgcldvzJo1i7erN+bMmYOLFy9i8+bN5W495KPu3bsjIyNDqlD4+vVrdO/enRev6+W5c+cOgoODpcb19PTKfQ+rqnR0dMQ/H21t7XLfv/jeV+l7okIAkZtjx45h2bJl6Nq1K1xcXDBs2DCoqKiwjiWT6dOnS7xgtGzZUuLxf/75h5eNAoGSZj6xsbHo2rUr5s2bh0GDBsHPzw8FBQVYu3Yt63gyU1FRKbcanJiYCF1dXQaJKm7evHnw9PSUuoCaN28e5s6dy6tCwMSJE8v9vZC4u7tjxIgRvJ65FGqR5mNDhgyBg4MDpk2bhuzsbLRv3x7Kysp48eIF1q5di+nTp7OO+M1GjRoFFxcXrF69Gp06dQJQUjj08vLCmDFjGKeT3fDhw3Hp0iXerYL6nOjoaIkiAADUqFEDc+bMgY2NDcNkFXP8+HHx1kMnJyfxdhUjIyPs3buXlz2ISm8iP5aVlYVatWoxSCQf2trayMjIgImJicT47du3edVT6cKFC6hduzYA4OLFi4zT8A9tDSBydfv2bQQEBGDfvn0oLCzE6NGj4ezs/MnusYS9R48eifsh8PU4OgBwdXVFVlYWDh48iNq1ayMuLg6KiooYOnQo7OzseHmDU7NmTdy5c0fq2JvExES0atUKeXl5jJKR8mhqauL27duCumERqrp16+Ly5cuwsLDAjh078Mcff+D27dv466+/sGjRIvFWHD7Jz8+Hl5cXtmzZgsLCQgCAkpISpk+fjhUrVvC2MJ+bm4sRI0ZAV1e33GNUZ86cySiZ7PT19bF7926p1SdnzpyBo6Mjnj17xihZxQhp62HpSS/Hjh1D3759Jf7/FBUVIS4uDmZmZjh9+jSriBUye/ZsREZG4tChQ2jWrBlu3bqFZ8+ewdHREY6OjrxsBpuWlgZDQ0Opwg3HcXj8+LHEyl5SglYEELmytraGtbU11qxZg+PHjyMgIACdO3dG8+bN4eLigkmTJvGmEU5BQQFUVVURExMjtSKArwoKCtC3b19s2bJFfHNpZGQkiO7za9aswfDhw6Gnp4f379+ja9euyMzMRMeOHcWnPfCNrq4uYmJipAoBMTExvN/PXJ6ePXsiJSUFKSkprKPIRIgzl0VFRTh69KhEQ7PBgwdDUVGRcbKKyc3NFS+XDw0NhYODAxQUFGBra/vF0zqqKmVlZWzYsAG+vr7iBoiNGzeW2qb35MkTNGjQQOJIvqps3759CA0NRc2aNXHp0iWJi3yRSMTLQoBQV28Iaeth6bUqx3HQ0NCQaAyorKwMW1tbTJ48mVW8Clu+fDnc3NxgaGiIoqIimJubo6ioCGPHjsWvv/7KOp5MTExMyt3G8fLlS5iYmNDWgHJQIYB8FxzHoaCgAPn5+eA4Djo6OvDz88PChQuxfft2jBo1inXEL1JSUkKjRo0E9cKhpKSEuLg41jG+Cy0tLZw9exZhYWESnX179uzJOprMJk+ejClTpiAlJUXiYnHlypX4+eefGaeTvx9//JFXexM/5ufnhxEjRuDq1auCmLlMSkpC//79kZ6eDjMzMwCAr68vDA0NcfLkSV4XPJo0aYKjR4/ixx9/xJkzZ+Dp6QkA+O+//3jfUEpNTQ2WlpaffNzc3BwxMTHi5rdV3YIFC+Dt7Y158+bxpnjxJatXr4ZIJIKjo2O5qzf4SkhbDwMCAgCU9Izy8vLidd+r8igrK2P79u1YtGgR7ty5g5ycHFhbW0tNPPDJp7Zx5OTkoGbNmgwSVX20NYDI1c2bN8VbA1RUVODo6AhXV1c0adIEAPDHH39g6dKlvFn25u/vj8OHD2P37t3iPUh85+npCRUVFV5fbJQnKCgIo0aNklr+mp+fj/3798PR0ZFRMtlxHIf169djzZo1ePr0KYCSI868vLwwc+bMr27qRiqHv78/pk2bhpo1a6JOnTpSM5d8W+nQv39/cByHvXv3il//srKyMH78eCgoKODkyZOME8ouJCQEY8eORVFREXr06IHQ0FAAJYWOK1eu4J9//mGc8Pv5+BScqq527dqIiorideHpU3Jzcz+7eoPvhLD1MDU1FYWFhVI3yA8ePICSkhKMjY3ZBCNipRMjGzZswOTJkyX+HxUVFSEyMhKKiooICwtjFbHKokIAkRtLS0vcv38fvXv3xuTJkzFo0CCp5aMvXryAnp6e1LFaVZW1tTWSkpJQUFAAIyMjqcYwt27dYpRMdu7u7ggKCkLTpk3Rtm1bqe+Jb1X7UoqKiuUuCcvKyoKenh7vV3a8ffsWAHjd/ftjSUlJSE5Ohp2dHVRVVT9ZzeeLevXqYebMmYKZuaxVqxYiIiKkZpdjY2PRuXNnXu33LU9mZiYyMjJgZWUl/nnduHEDmpqa4s77fFtG/zX4Vgjw9PSErq4u/ve//7GOQqqhrl27wtnZWarJ7Z49e7Bjxw5cunSJTbAKGjZsGNq3b4+5c+dKjK9atQpRUVE4dOgQo2Tfrnv37gCAy5cvo2PHjlBWVhY/pqysDGNjY8yePZvXqx2+F9oaQORm5MiRcHZ2/my30bp16/KmCAAAQ4cOZR1B7u7evSs+ozgxMVHiMT7fhH3qJvLJkye86UvxOUIqAGRlZWHUqFG4cOECRCIRHjx4AFNTU7i4uEBHRwdr1qxhHVEm+fn5GDVqlGBuGlVUVMQFqLJycnIkLrT4ql69eqhXr57EWOmZ7qX4toxeiIqKirBq1SqcOXMGrVq1ktpyw5fitYODAwIDA6GpqSluRPcphw8frqRUFbdx48avfi7ftkcBJU2wS4/vLcvW1hYzZsxgkEg+rly5giVLlkiN9+vXj3fvwaWnBTg5OWHDhg28395VmagQQORm4cKF4t+XLjTh840lAF52Tf0SoR2vYm1tDZFIBJFIhB49ekgcx1RUVITU1FT07duXYULZPXv2DLNnz8b58+fx33//4eMFXHxd5eDp6YkaNWogLS0NLVq0EI+PGjUKP//8M+8uQkpNnDgRBw4cEMzM5cCBAzFlyhT4+/uLb5AjIyMxbdo0DB48mHG6ykGLJtm7c+cOrK2tAZQUssvi0zWGlpaWOK8QitOl1q1bJ/Hx8+fPkZubK24OmJ2dDTU1Nejp6fGyECASicotiL5+/Zq378HApwu6SkpK5R7FzAelfR3I16NCAJGroKAg/P7773jw4AEAoFmzZvDy8sKECRMYJ6uYmzdvSnTNLr0oIeyVrtqIiYlBnz59oK6uLn6sdEnYsGHDGKWrmEmTJiEtLQ0LFy5E/fr1eXXR+zmhoaE4c+YMGjZsKDHetGlT3nZsB4Qzc1lq48aNmDhxIjp27Cj+XgoLCzF48GBs2LCBcToiK769jnxt8bqqb+Moe5MipBuW1NRU8e+Dg4Px559/wt/fX9xgNCEhAZMnT8bUqVNZRawQOzs7+Pr6Yt++feLtrkVFRfD19cUPP/zAOJ3sLC0tceDAASxatEhifP/+/TA3N2eUquKio6Nx8OBBpKWlIT8/X+IxPq20qSxUCCBys3btWixcuBAzZswQL6O6du0apk2bhhcvXoi7MvPJf//9h9GjR+PSpUsS1e3u3btj//790NXVZRtQjv7880+8ePFC6k2hqitdtWFsbIzRo0fz9qzs8ly7dg1Xr15F69atWUeRq3fv3pXbFOvly5e8/vkJZeaylLa2No4dO4akpCRxIbRFixbi5q+En4S6yoFP2ziWLl2KcePGwcTEhHUUuVq4cCFCQkLERQAAMDMzw7p16zB8+HCMGzeOYTrZrFy5EnZ2djAzM0OXLl0AAFevXsWbN29w4cIFxulkt3DhQjg4OCA5ORn29vYAgPPnz2Pfvn286g9QVmlj6D59+iA0NBS9e/dGYmIinj17hh9//JF1vKqJI0ROjI2NuV27dkmNBwYGcsbGxgwSVdzIkSM5GxsbLj4+Xjz277//cjY2Ntzo0aMZJpM/e3t7zsTEhHUMmaWlpXGPHz8WfxwZGcl5eHhwW7duZZiqYlq0aMHdunWLdQy569evH/frr79yHMdx6urqXEpKCldUVMSNGDGCGzZsGON039/jx4+5oqIi1jHIV1BXV+eSk5NZx5CrtLQ0rrCwkHUMuePTz6pVq1acgoIC17FjR27Tpk3c8+fPWUeSC1VVVe7GjRtS45GRkZyqqiqDRPKRnp7OzZ8/n+vfvz83bNgwztvbm8vKymIdq8JOnDjBderUiVNTU+Pq1KnDde/enbt06RLrWDKztLTk/Pz8OI77/68HxcXF3OTJk7lFixYxTlc1USGAyI2Kigr34MEDqfHExERORUWFQaKK09TU/OSbmpaWVuUHqqD8/HzO1NRUorAhFD/88AMXFBTEcRzHZWRkcBoaGlzHjh25unXrct7e3ozTyebMmTNc7969udTUVNZR5OrOnTucnp4e17dvX05ZWZkbPnw416JFC05fX59LSkpiHe+709DQ4MUNi4ODA7dixQqp8ZUrV3LDhw9nkKjy8eVnxXEcl5OTw/36669cx44ducaNG3MmJiYSv4SOT4UAjuO4u3fvcvPnz+dMTEw4JSUlrn///tzevXu5d+/esY4ms4EDB3LW1tbczZs3xWPR0dFcmzZtuEGDBjFMRqoDNTU18fVS7dq1ubi4OI7jOC4+Pp6rV68ew2RVF20NIHLTpEkTHDx4UKpR1oEDB3h7ZEdxcbHUPl+gpJkKn04/KKWkpIS8vDzWMb6Lu3fvihuaHTx4EJaWlggLC0NoaCimTZvGmy0POjo6EsvI3717Jz5f+uN/iy9fvqzseHLRsmVLJCYmws/PDxoaGsjJyYGDgwPc3NxQv3591vG+O44nS7OF1FVaVnz5WQGAq6srLl++jAkTJgiqp4hQWVhYYPny5Vi+fDnCwsIQHByMWbNmYdq0abxt1rZz505MnDgRNjY24vergoIC9O3bFzt27GCcrmJyc3PL3XfeqlUrRokqJioqCsXFxejQoYPEeGRkJBQVFWFjY8Momex0dHTEjR0NDAxw9+5dWFpaIjs7G7m5uYzTVU1UCCBy4+3tjVGjRuHKlSviHgFhYWE4f/48Dh48yDidbOzt7eHh4YF9+/ahQYMGAID09HR4enqiR48ejNPJxs3NDStXrsSOHTskOuzzXUFBgXh/+blz58RdzZs3b46MjAyW0b7J+vXrWUeoFFpaWliwYAHrGOQzhNhV+lvFx8eLX/urun/++QcnT54s96gzUrXVqlULqqqqUFZWLrdDPV/o6uri1KlTePDggbivSPPmzdGsWTPGyWT3/PlzODk54Z9//in3cb6eHODm5oY5c+ZIFQLS09OxcuVKREZGMkomOzs7O5w9exaWlpYYMWIEPDw8cOHCBZw9e5a31+zfm3DuAghzw4YNQ2RkJNatW4ejR48CKGksdePGDd522ffz88PgwYNhbGwMQ0NDAMDjx4/RsmVL7Nmzh3E62URFReH8+fMIDQ2FpaUlatWqJfE4X7uqWlhYYMuWLRgwYADOnj2L3377DQDw9OlT1KlTh3G6rzdx4kTWEb67gIAAqKurY8SIERLjhw4dQm5ubrX4O+ADoXaVBkpW2qxYsUJ8NOfHK7xSUlIAQPy6zwc6OjqoXbs26xjM8G0FRGpqKoKDgxEcHIyEhAR07doV3t7eGD58OOtoFeLv749169aJT49q2rQpZs2aBVdXV8bJZDNr1ixkZ2cjMjIS3bp1w5EjR/Ds2TMsXbqU1yuj4uPj0aZNG6lxa2trxMfHM0hUcX5+fuJVrwsWLICSkhLCw8MxbNgw/Prrr4zTVU1UCCBy1bZtW97eIJfH0NAQt27dwrlz53D//n0AJcWNnj17Mk4mO21tbd4ep/c5K1euxI8//ojff/8dEydOhJWVFQDg77//Fm8Z4KOioiIcOXJEPLtibm6OIUOG8Ho1h6+vL7Zu3So1rqenhylTplAhoIoQYlfpUkJcRv/bb79h0aJF2LVrV7mncggdn7Zx2NraIioqCq1atYKTkxPGjBkDAwMD1rEqbNGiRVi7di3c3d3RsWNHAMD169fh6emJtLQ0+Pj4ME747S5cuIBjx47BxsYGCgoKMDIyQq9evaCpqQlfX18MGDCAdUSZqKio4NmzZ1KnbGRkZPDy+qKwsBAnTpxAnz59AAAKCgqYN28e41RVn4jj0ysnqXK+ZXmopqbmd0xCSMlN85s3b6CjoyMee/jwIdTU1KCnp8cwmWz+/fdfDB48GJmZmeLjmBITE6Grq4vjx4+jZcuWjBPKpmbNmrh//z6MjY0lxh8+fIgWLVrg/fv3bIJVEk1NTd4cc3by5EksX74cMTExUFVVRatWrbB48WJ07dqVdbQK0dbWFsQyemtra4kiRlJSEjiOg7GxsVRPkVu3blV2vEr1+PFjNGjQQHzWe1W2YMECjBs3jvcraz6mq6uLjRs3YsyYMRLj+/btg7u7O168eMEomew0NTURFxcHY2NjGBkZITg4GJ07d0ZqaiosLCx4u/d8zJgxyMjIwLFjx6ClpQWg5HjsoUOHQk9Pj5dbetXU1HDv3j0YGRmxjsIb/Cv5kCpFW1v7izMpHMdBJBLxdh/V+fPnsW7dOolztGfNmsXrVQFCpaioKFEEACB1s8knrq6usLCwQHR0tPj7evXqFSZNmoQpU6YgPDyccULZ6OnpiS+syoqNjeXVNg5Z8an+PmDAAN7OeH2OUJbRDx06lHWE706I2ziWLVsGAMjPz0dqaioaN27My1nYjxUUFJTbZK5t27YoLCxkkKjizMzMkJCQAGNjY1hZWWHr1q0wNjbGli1beN3cdvXq1bCzs4ORkZF4+25MTAz09fWxe/duxulk0759e8TExFAh4BvQigBSIZcvX/7q5/JxBunPP/+Eh4cHhg8fLl7mFhERgZCQEKxbtw5ubm6ME8omJCQEBw8eLLcDLp9mjdq0aYPz589DR0dHambsY3z6vkqpqqoiOjoaFhYWEuN3795Fu3bteDtzPnfuXBw4cAABAQGws7MDUPJa4uzsjOHDh2P16tWME35ffJq5LPXTTz/Bx8cHdevWZR1FLvbs2YNjx45V22X0fDJmzJjPbuPw8PBglEx279+/x4wZM7Br1y4AJSu9TE1N4e7uDgMDA94uaXZ3d4eSkhLWrl0rMT579my8f/8emzZtYpRMdnv27EFhYSEmTZqEmzdvom/fvnj58iWUlZURGBiIUaNGsY4os3fv3mHv3r2IjY0Vr/gaM2ZMuadl8cHBgwcxf/58eHp6om3btlI9sPh6wsP3RIUAQj6jYcOGmDdvHmbMmCExvmnTJixfvhzp6emMkslu48aNWLBgASZNmoRt27bByckJycnJiIqKgpubm3imgg+8vb3h5eUFNTU1eHt7f/a5ixcvrqRU8mNlZYV169aJ92eXunDhAjw8PHDnzh1GySomPz8fEyZMwKFDh8SzYMXFxXB0dMSWLVvK7VTPB187c8lHfNrO8ClCX0ZvamqKqKgoqVU12dnZaNOmDW///QllG0dZHh4eCAsLw/r169G3b1/ExcXB1NQUx44dw5IlS3D79m3WEWXi7u6OoKAgGBoawtbWFkDJcXRpaWlwdHSU+H/2cbGAL3Jzc3H//n00atRIMIVRoVBQUJAaE4lEvF+Z/D1RIYDI1atXr+Dv7y/R2MzJyYm3SzDV1dURExODJk2aSIw/ePAA1tbWyMnJYZRMds2bN8fixYsxZswYaGhoIDY2Fqampli0aBFevnwJPz8/1hHJ/zl16hTmzJmDJUuWiC+qIiIi4OPjgxUrVuCHH34QP5ePPTgSExPFMxGWlpa8X84nxJnLUmVfK/jqS8XCsvhYOFRQUEBmZqZUP5Rnz57B0NBQavUXX5iYmODUqVNo0aIF6yhyY2RkhAMHDsDW1lbi/1ZSUhLatGnD2+M5u3fv/lXPE4lEuHDhwndOIx8+Pj6YPXu21Mqh9+/f4/fff5c6VYUvgoKCPvu4o6NjJSWRn0ePHn32cb5fY3wPVAggcnPlyhUMGjQIWlpa4j1iN2/eRHZ2No4fPy5eAswnY8eOhbW1Nby8vCTGV69ejejoaOzfv59RMtmVbaaip6eHs2fPwsrKCg8ePICtrS2ysrJYR5TJxYsXP3kRsnXrVkydOrWSE1Vc2ep26U1l6Ut22Y+p0l01CHHmspQQCgFC9ffffwMo6Rewa9cuceMvoKSB6vnz53H27FkkJCSwilghQtzGoaamhrt378LU1FTi/1ZsbCzs7Ozw+vVr1hHJ/1FUVERGRoZUgS0rKwt6enq8fe/9uJ9SQUEBcnNzoaysDDU1Nbx8+ZJRMlKZ+N+ZhFQZbm5uGDVqFDZv3ize+1pUVISffvoJbm5uvFnGvHHjRvHvzc3NsWzZMly6dEmiR0BYWBh++eUXVhErpF69enj58iWMjIzQqFEjREREwMrKCqmpqbxqYvaxvn37YubMmVi+fLl4+eGLFy/g5OSEa9eu8bIQcPHiRdYR5Obnn3/Gb7/9hlq1auHnn3/+7HP5umRUKA3oyvP27VvWEeRKSMvoSxsGikQiqaM3lZSUYGxszLvzzsvbxqGvry+YbRw2NjY4efIk3N3dAfz/wu6OHTvE1xqkaigttn8sNjaW16/3r169khp78OABpk+fLjX5xRdCXOXwvdGKACI3qqqqiImJER9zViohIQGtW7fmTWMzExOTr3qeSCTi1cViKVdXVxgaGmLx4sXYtGkTvLy80LlzZ0RHR8PBwQH+/v6sI8okPDwcjo6OUFdXR3BwMFJTU+Hi4gIzMzMEBQXRkjDGunfvjiNHjkBbWxvdunX7ZGNHPi0Z/ZgQZy6Tk5MREBCAlJQUrF+/Hnp6evjnn3/QqFEjqSaWfCLEZfQmJiaIiooSxL5loW/juHbtGvr164fx48cjMDAQU6dORXx8PMLDw3H58mW0bduWdcRqT0dHByKRCK9fv4ampqbEe1ZRURFycnIwbdo0XjZA/Jzo6GiMHz8e9+/fZx3lm9Eqh29HhQAiN507d4aXl5fUcUZHjx7FihUrEBERwSYYkVBcXIzi4mJxk7b9+/cjPDwcTZs2xdSpU3nbqA2A+I05JCQExcXF+O233zBnzpwvHnFZlV29ehVbt25FSkoKDh06BAMDA+zevRsmJiYSPQIIG0JuQHf58mX069cPnTt3xpUrV3Dv3j2YmppixYoViI6ORkhICOuI30zoy+gJf6SkpMDX1xexsbHIyclBmzZtMHfuXFhaWrKORgDs2rULHMfB2dkZ69evl3itUFZWhrGxsSBXb8TExMDOzo63fSo+VnaVQ58+fVjHqXJoawCRm5kzZ8LDwwNJSUkSjc02bdqEFStWIC4uTvxcOsKDHQUFBYm956NHj8bo0aMZJpKfxMREREdHo2HDhnj69CkSEhKQm5srdYQMX/z111+YMGECxo0bh1u3buHDhw8AgNevX2P58uU4deoU44TfrqCgQLx6qGXLlqzjVJiQz3GfN28eli5dip9//hkaGhricXt7e942FRXiMvqyzp8//8lTK3bu3MkoVcUIaRsHUPIaOHXqVCxcuBDbt29nHYd8Qunrg4mJCTp16sTbI/U+pbQoWorjOGRkZMDPz09QfW6aNm2KFStW8HaVw/dGKwKI3JR3bEdZfDnCQ+h7mZs0aYLx48dj7NixaNasGes4crNixQosXrwYU6ZMwe+//46kpCRMmDABb968wZ49e3hZube2toanpyccHR0lGkrdvn0b/fr1Q2ZmJuuIMjE1NcWRI0dgZWXFOgr5DHV1ddy5cwcmJiYS//4ePnyI5s2bIy8vj3VEmQlpGX0pb29v+Pj4wMbGptxTK44cOcIoWcUIcRuHlpYWYmJivnorImGruLgYSUlJ5RbY+NgIG5C+ZheJRNDV1YW9vT3WrFmD+vXrM0omf0Jb5SBPtCKAyE1qairrCHJx+/ZtFBQUAChZyvu5vcx85ObmhuDgYPz2229o06YNxo8fj1GjRqFevXqso1XIhg0bcPToUfTr1w8A0LJlS9y4cQP/+9//0K1bN/FsOp8kJCSUe5GhpaWF7Ozsyg8kJwsWLMD//vc/7N69m9fNlj4mtJlLbW1tZGRkSN2s3L59GwYGBoxSyYdQ3q/K2rJlCwIDAzFhwgTWUeSi7IzlmTNnyt3Gwdcb6aFDh+Lo0aPw9PRkHYV8QUREBMaOHYtHjx5JNVSu6hNbn/NxQUMIqssqB3miFQGEVFOJiYnYu3cv9u3bh9TUVHTv3h3jx4/nbVfVFy9efHJ27/Lly+jatWslJ6o4U1NTbNu2DT179pSYkQ0KCsKKFSsQHx/POqJMrK2tkZSUhIKCAhgZGUlt3eDbXvpSQpu5nD17NiIjI3Ho0CE0a9YMt27dwrNnz+Do6AhHR0deNmkrS2jL6OvUqYMbN26gcePGrKPIRemMZelqwrLKbuMYOHAgi3gVsnTpUqxZswY9evRA27ZtpV4DZ86cySgZ+Vjr1q3RrFkzeHt7l7vSpmyBis+Kiopw584dGBkZSTXd44vqtMpBXqgQQOTq6dOnuHbtWrkXVnx7YxPaXubPiYiIwPTp0xEXF8fb6jZQMvMaEhKC5ORkeHl5oXbt2rh16xb09fV5OYPp6+uLPXv2YOfOnejVqxdOnTqFR48ewdPTEwsXLhQfPcU3X+oIzrcbTKE2oMvPz4ebmxsCAwNRVFSEGjVqoKioCGPHjkVgYKD4mFg+EuIy+rlz50JdXR0LFy5kHUWuhLiN43MrGfh6IpFQ1apVC7GxsWjSpAnrKHI1a9YsWFpawsXFBUVFRbCzs8P169ehpqaGEydOoFu3bqwjkkpAhQAiN6VH4CgrK6NOnToSF1Z8fWMT+l7mGzduIDg4GAcOHMCbN28waNAg7N+/n3UsmcTFxaFnz57Q0tLCw4cPkZCQAFNTU/z6669IS0v74vmyVRHHcVi+fDl8fX2Rm5sLAFBRUcHs2bPx22+/MU5HSgl55hIA0tLScPfuXeTk5MDa2hpNmzZlHanC6tevj1WrVglmGT0AeHh4ICgoCK1atUKrVq2kmpvxsadNdVD6msHX7YZCZ29vjzlz5qBv376so8hVw4YNcfToUdjY2ODo0aNwc3PDxYsXsXv3bly4cAFhYWGsI36VL/XyKoteA6VRIYDIjaGhIaZNm4b58+d/sXEgX/j7++Pw4cOC2sv88ZYAe3t7jBs3Dg4ODlBXV2cdT2alSyxXrVolsYw+PDwcY8eOxcOHD1lHlFl+fj6SkpKQk5MDc3NzXv+cyoqOjsa9e/cAAObm5rw/O1uIM5dCJbRl9ADQvXv3Tz4mEolw4cKFSkwjX0LbxgGUXF+sW7cODx48AFDS3XzWrFlwdXVlnIyUdeTIEfz666/w8vKCpaWlVIGNr6dg1axZE0lJSWjYsCGmTJkCNTU1rF+/HqmpqbCysuJNY72PX/du3bqFwsJCmJmZASi55lVUVETbtm15/Rr4vVCzQCI3ubm5GD16tGCKAADg5+eHpKQkNGjQQDB7mZs3b4527drBzc0No0ePhr6+PutIchEdHY1t27ZJjRsYGPC2u34pZWVlmJubs44hN0+ePMGYMWMQFhYGbW1tACXbOjp16oT9+/ejYcOGbAPKSGgN6JydnT/7OF9vwADA1dUVwcHBglpGf/HiRdYRvosvbePgo0WLFmHt2rVwd3cXn2hz/fp1eHp6Ii0tDT4+PowTklLDhg0DIPl6yJdTsD5HX18f8fHxqF+/Pk6fPo3NmzcDKLmW59O2r7Kve2vXroWGhgZ27dol7nPw6tUrODk5oUuXLqwiVmlUCCBy4+LigkOHDmHevHmso8iNEM8IT0hIEMTS3o+pqKiUW8FOTEyErq4ug0SycXBw+OrnHj58+Dsm+X5cXV1RUFCAe/fuiav2CQkJcHJygqurK06fPs04oeyENHP56tUriY8LCgpw9+5dZGdnw97enlEq+cjLy8O2bdtw7tw5QS6jf/LkCQDwtqhWltBOQwCAzZs3Y/v27RgzZox4bPDgwWjVqhXc3d2pEFCFCK3AW8rJyQkjR44UF9d69uwJAIiMjETz5s0Zp5PNmjVrEBoaKtHsUEdHB0uXLkXv3r3xyy+/MExXNVEhgMiNr68vBg4ciNOnT5e7fIqPF1Z8a1r2NYRYBABKLqJ8fHxw8OBBACUV+7S0NMydO1dc0ecDoXQg/pzLly8jPDxcXAQAADMzM/zxxx+8rtoLbeayvIZ5xcXFmD59Ou+X1MfFxaF169YAgLt370o8xtefW3FxsbgbfU5ODgBAQ0MDv/zyCxYsWMDb1Xr5+fno1KkT6xhyVVBQABsbG6nxtm3borCwkEEi8ilGRkasI3wXS5YsQcuWLfH48WOMGDECKioqAABFRUXeTui9efMGz58/lxp//vw53r59yyBR1Uc9AojcLF26FIsWLYKZmRn09fWlmgXS3pyqbeLEiXj8+DFvf06vX7/G8OHDER0djbdv36JBgwbIzMxEx44dcerUKaltHYSdZs2aYc+ePWjfvr3E+I0bNzB27FgkJSUxSlYxQmxAV56EhAR069YNGRkZrKOQMubPnw9/f394e3uLz8y+du0alixZgsmTJ2PZsmWME8pGiKchuLu7Q0lJSWqCZPbs2Xj//j02bdrEKBkpT3JyMtavXy/R08bDw4P3BdGvYWlpiVOnTsHQ0JB1lC9ydHTE1atXsWbNGvH1RWRkJLy8vNClSxfs2rWLccKqh1YEELlZs2YNdu7ciUmTJrGOIjcKCgqfnR3i696w8hgYGPB2xggomUk/e/Ysrl27hri4OOTk5KBNmzbi5W58VVhYiEuXLiE5ORljx46FhoYGnj59Ck1NTd42Dfz999/h7u6OTZs2iWfFoqOj4eHhgdWrVzNOJzshzlyWJzk5WVCzlkJZRr9r1y7s2LEDgwcPFo+1atUKBgYG+Omnn3hbCBDqNg5/f3+EhobC1tYWQMkNS1paGhwdHSU6ofP1+xOKM2fOYPDgwWjdurW4wBYWFgYLCwscP34cvXr1Ypzw+3r48CEKCgpYx/gqW7ZswezZszF27Fhx5ho1asDFxQW///4743RVE60IIHJTr149XL16VVBLz48dOybxcUFBAW7fvo1du3bB29sbLi4ujJKR6uDRo0fo27cv0tLS8OHDByQmJsLU1BQeHh748OEDtmzZwjqiTHR0dJCbm4vCwkLUqFFSjy79/ccrN16+fMkiokyENnP58bFMHMchIyMDJ0+exMSJE+Hn58coWcUJcRl9zZo1ERcXh2bNmkmMJyQkoHXr1nj//j2jZBUjxNMQPvc9lcXX709IrK2t0adPH6xYsUJifN68eQgNDeVl0+hvUfYUJr549+4dkpOTAQCNGzemFaGfQYUAIje+vr7IyMjAxo0bWUf57oKDg3HgwAGpQgHfCO38YiE1agNKmlVqaGjA398fderUEb8ZX7p0CZMnTxYfO8U337I8b+LEid8xiXwJ7Rz3j29WFBQUoKurC3t7ezg7O4uLOHwkxGX0HTp0QIcOHaTeg93d3REVFYWIiAhGyQjhr5o1a+LOnTtSk1yJiYlo1aoV8vLyGCWrHHwsBJCvx993cVLl3LhxAxcuXMCJEydgYWEhdRHM1w7n5bG1tcWUKVNYx5CZEM8vFlqjNgC4evUqwsPDoaysLDFubGyM9PR0Rqkqjk83999CaA3ohHocHSDMZfSrVq3CgAEDcO7cOYkj6dLS0vDPP/8wTicfQtnGQfhDV1cXMTExUoWAmJgY6OnpMUpFiHxQIYDIjba29jcdfcZX79+/x8aNG2FgYMA6ikyEen6xEI+YKi4uLrcPxZMnT6ChocEgEfkcId84C83Lly/LPSKrefPmvNqOUlbXrl2RkJCAzZs3i5uaOTg44KeffkKDBg0Yp5OdELdxEP6YPHkypkyZgpSUFHEPmLCwMKxcuVJq+xQhfENbAwj5DB0dHYmZPI7j8PbtW6iqqmLv3r0Ss0l8oauri40bN0qcXwwA+/btg7u7O168eMEoWcXUqVMHN27cEFQX31GjRkFLSwvbtm2DhoYG4uLioKuriyFDhqBRo0YICAhgHVGuevbsiZSUFKSkpLCOUmF8nbm0trb+6tULfN4bK9Rl9Hl5eYiLiyt3exQf368AYW7jIPzBcRzWr1+PNWvW4OnTpwCABg0awMvLCzNnzuTlaq9vQVsDhI0KAUSuhNbhPDAwUOJFvnSPbIcOHaCjo8Mwmey0tbURFRVV7n639u3bIzs7m02wChJaozag5GayT58+4DgODx48gI2NDR48eIC6deviypUrgluW6Ofnh6ysLCxevJh1FJkIYebS29v7q5/L158TAFy+fBkDBgxAo0aNyl1G36VLF8YJv93p06fh6OiIrKwsfHxpJxKJeHvKTYMGDbBlyxapQsaxY8fw008/8XqbFOGX0rPohbYiLy8vDzVr1iz3seDgYAwZMoQa7gkUFQKI3Ai1w/nVq1exZcsWpKSkICQkBAYGBti9ezdMTEzwww8/sI73zYR6frHQGrWVKiwsxIEDBxAbGys+EnHcuHFQVVVlHY18hGYu+SU9PV1iGX2LFi14vYy+adOm6N27NxYtWgR9fX3WceRGqKchEH5ITU1FYWGh1OTJgwcPoKSkBGNjYzbBKqi4uBjLli3Dli1b8OzZM/E1+8KFC2FsbEynYlUTVAggciPEDud//fUXJkyYgHHjxmH37t2Ij4+Hqakp/Pz8cOrUKZw6dYp1xG/m7u6OoKAgGBoalnt+cdkbaD7dPAvxiKkrV66gU6dOUt3ZCwsLER4eDjs7O0bJ5OvNmze4cOECzMzM0KJFC9ZxZCbUmcvo6GjxzbK5uTnatm3LOJF8CG0ZvaamJm7fvi2o7VGAcLdxEH7o2rUrnJ2dpZrc7tmzBzt27MClS5fYBKsgHx8f7Nq1Cz4+Ppg8eTLu3r0LU1NTHDhwAOvXr8f169dZRySVgAoBRG7q1KmD8PBwmJmZSewpevjwIczNzZGbm8s64jeztraGp6cnHB0dJb6n27dvo1+/fsjMzGQd8ZvR+cX8oaioiIyMDKktAFlZWdDT0+PtUt+RI0fCzs4OM2bMwPv372FlZYWHDx+C4zjs378fw4YNYx1RJkKbuXzy5AnGjBmDsLAwaGtrAwCys7PRqVMn7N+/n3f9D8oS4jJ6Z2dndO7cWXAzeULcxkH4Q1NTE7du3UKTJk0kxpOSkmBjY8Pb7ZRNmjTB1q1b0aNHD4nr2/v376Njx4549eoV64ikEtCpAURuhNjhPCEhodxZVy0tLd6++FeHzuZ8bdT2MY7jym1ElJWVxev9eleuXMGCBQsAAEeOHAHHccjOzsauXbuwdOlS3hYCrKys4OfnJzVz6efnBysrK0apZOfq6oqCggLcu3cPZmZmAEpeE52cnODq6orTp08zTig7d3d3jBgxQlDL6P38/DBixAhcvXoVlpaWUtujZs6cyShZxQj1NATCDyKRSNwboKzXr1/zsmBYKj09Xaq4AZRcyxcUFDBIRFigQgCRm969e2P9+vXYtm0bgJIXz5ycHCxevBj9+/dnnE429erVQ1JSktQesGvXrlEH1SpGCI3aSpUewykSiTBp0iSoqKiIHysqKkJcXJz4GCM+ev36NWrXrg2gZGZ22LBhUFNTw4ABA+Dl5cU4neyEdo775cuXxau8SpmZmeGPP/7g/Szss2fP8PPPPwumCACUnPwSGhqKmjVr4tKlSxJFRJFIxNtCAFCy4nDw4MGwtbUVb+OIjo4GwM9tHIQ/7Ozs4Ovri3379kFRURFAyfuwr68vL/tElTI3N8fVq1dhZGQkMR4SEgJra2tGqUhlo0IAkZs1a9agT58+MDc3R15eHsaOHSvucL5v3z7W8WQyefJkeHh4YOfOnRCJRHj69CmuX7+O2bNn87Y7fV5eHv744w9cvHix3L2xfD0SbMGCBfD398eKFSukGrXl5eXxqlGblpYWgJIVARoaGhKNAZWVlWFra4vJkyezildhhoaGuH79OmrXro3Tp09j//79AIBXr159snMxHwht5tLQ0LDcmaGioiJefj9lDR8+HJcuXRLUfvoFCxbA29sb8+bN41Xh80uEuI2D8MfKlSthZ2cHMzMzcQH06tWr4t42fLVo0SJMnDgR6enpKC4uxuHDh5GQkICgoCCcOHGCdTxSSahHAJEroXU45zgOy5cvh6+vr7jHgYqKCmbPno3ffvuNcTrZjBs3DqGhoRg+fDj09fWllp7z9UgwITZq8/b2xuzZs7+4DSAsLAw2NjYSKweqsj///BMeHh5QV1eHkZERbt26BQUFBfzxxx84fPgwr7evCKkB3bFjx7B8+XJs2rQJNjY2AEpmYd3d3TF37lwMHTqUbcAKyM3NxYgRI6CrqyuYZfS1a9dGVFSUoIobgHBPQyD88fTpU/j5+SE2Nhaqqqpo1aoVZsyYIV7ZxldXr16Fj4+PxDX7okWL0Lt3b9bRSCWhQgAhXyE/Px9JSUnIycmBubk51NXVWUeSmZaWFk6dOiWeNRcKoTVq+xaampqIiYnh1XaV6OhoPH78GL169RL/fzp58iS0tbV5+29TCDOXOjo6EsXBd+/eobCwUHxyRenva9WqhZcvX7KKWWH+/v6YNm0aatasiTp16kgto09JSWGYTjaenp7Q1dXF//73P9ZR5EqopyEQYfnpp5/g4+ODunXrso5CyFejQgD57jIyMlBQUIBGjRqxjkJQsi9s//79aNWqFesoclWdj5gq2/GXsCOEmctdu3Z99XM/Pk6LT+rVq4eZM2cKahn9zJkzERQUBCsrK7Rq1UpqlQOfjoMtS6inIRBh4WNBvlROTo7UCjZNTU1GaUhlokIA+e5atGiBxMREXsyGVQf//PMPNm7ciC1btkg1ieGzTx0x9fjxY5w6dYr3zc0+h2+FgKKiIgQGBuL8+fPlLqHn677L6jpzuWLFCkybNk18xCAfCHEZ/eeOhuXzcbBC3MZBhIdv78OpqamYMWMGLl26hLy8PPF46WlFdM1ePVCzQCIXhYWFWL58OZydnaWObAsKChLvryfs2djYIC8vD6amplBTU5O6qOLrct+uXbsiMTERmzZtwv379wHwu1GbkHl4eCAwMBADBgxAy5Ytyz0ikY+E2IDuayxfvhwjR47kVSFg4sSJOHDggKCW0fO5t8bnCPk0BEJYGT9+PDiOw86dO8vtF0WqB1oRQORGQ0MDd+7ckTpqj1QtPXv2RFpaGlxcXMp98efzct/qim8zEXXr1kVQUBBvjxX9lOo6c8m3f3+AcJfRC5EQt3EQ4eHb66C6ujpu3rwpcTwsqX5oRQCRG3t7e1y+fJkKAVVceHg4rl+/DisrK9ZR5C47Oxs3btwod7m5o6Mjo1TfH98q+crKymjSpAnrGHJHM5f8cefOHfFZ2Xfv3pV4jG//n4QuPz8fo0aNoiIAIXLUrl07PH78mAoB1RwVAojc9OvXD/PmzcOdO3fQtm1bqSPP+HZ0llA1b95ckB30jx8/jnHjxiEnJweamppSN2FCLgTwbWHXL7/8gg0bNsDPz09QN11CPcddiIS6jF6IhLiNgxDWduzYgWnTpiE9PR0tW7aUWhUltIbSpHy0NYDIzecufKnxSNURGhoKb29vLFu2rNzly3ztFNusWTP0798fy5cvh5qaGus4cmFvb4/Dhw9L7b1+8+YNhg4dytvmXz/++CMuXryI2rVrw8LCQurf4OHDhxklqxghNqD7GnxbEkv4hbZxED6YPn06fvvtN94cHxgREYGxY8fi4cOH4jGRSETNAqsZKgQQUs2ULdiUnY3l+4t/rVq1cOfOHUHdjCgoKCAzMxN6enoS4//99x8MDAxQUFDAKFnFODk5ffbxgICASkoiX0I9x/1LqBBAviehnoZA+MHY2BjOzs6YNGmSoI7BNjc3R4sWLTBnzpxy+0UJ6VQp8mm0NYDI1fnz58s9EkwkEsHf359hMlJKqEti+/Tpg+joaEHcjMTFxYl/Hx8fj8zMTPHHRUVFOH36NAwMDFhEkwu+3uh/SVFREVatWoUzZ85Uq5nLLl26QFVVlXUMIlBCfc8i/DBr1iwEBgbCx8cH3bt3h4uLC3788UeoqKiwjlYhjx49wt9//y3Ifj3k69GKACI33t7e8PHxgY2NDerXry9VXTxy5AijZORjV69exdatW5GcnIyQkBAYGBhg9+7dMDExwQ8//MA6nkz8/f3h4+MDJyencrc88KlHhYKCgvj/T3kv0aqqqvjjjz/g7Oxc2dHk6vnz50hISAAAmJmZQVdXl3GiihHizGVRURGOHDmCe/fuAQBatGiBoUOHokYNmkcghFQft27dQmBgIPbt24eioiKMHTsWzs7OaNOmDetoMhk0aBAmTZqEYcOGsY5CGKJCAJGb+vXrY9WqVZgwYQLrKOQz/vrrL0yYMAHjxo3D7t27ER8fD1NTU/j5+eHUqVM4deoU64gyEVKPikePHoHjOJiamuLGjRsSN8jKysrQ09ODoqIiw4QV8+7dO7i7uyMoKEi8ckhRURGOjo74448/BNPjge/+/fdfDB48GJmZmeLO0omJidDV1cXx48fRsmVLxgkJIaRyFRQU4M8//8TcuXNRUFAAS0tLzJw5E05OTrxqfrtt2zYsXboUzs7OvJ88IbKjQgCRmzp16uDGjRvVrlEW31hbW8PT0xOOjo4Se3tv376Nfv36SSxDJ+R7mDp1Ks6dOwc/Pz907twZAHDt2jXMnDkTvXr1wubNmxknJADQsWNH6OrqYteuXdDR0QEAvHr1CpMmTcLz588RHh7OOCEhhFSOgoICHDlyBAEBATh79ixsbW3h4uKCJ0+eYNOmTbC3t0dwcDDrmF9NSJMnRHZUCCByM3fuXKirq2PhwoWso5DPUFNTQ3x8PIyNjSUKASkpKTA3N0deXh7riN+VpaUlTp06BUNDQ9ZRvsjX1xf6+vpSWwB27tyJ58+fY+7cuYySVUzdunUREhKCbt26SYxfvHgRI0eOxPPnz9kEIxJUVVURHR0NCwsLifG7d++iXbt2gjyGlBBCyrp16xYCAgKwb98+KCgowNHREa6urmjevLn4OfSaSPiKNvkRucnLy8O2bdtw7ty5atUoi2/q1auHpKQkGBsbS4xfu3ZNEI32vuThw4e86ba/devWcmcYLCwsMHr0aN4WAnJzc6Gvry81rqenh9zcXAaJSHmaNWuGZ8+eSRUC/vvvP2owRQipFtq1aydeqTZ06FCpa1sAMDExwejRoxmkI6RiqBBA5CYuLg6tW7cGUFIdLYtP+6aEbvLkyfDw8MDOnTshEonw9OlTXL9+HbNnz6bVHFVMZmYm6tevLzWuq6uLjIwMBonko2PHjli8eDGCgoJQs2ZNAMD79+/h7e2Njh07Mk5Xvb1580b8e19fX8ycORNLliyBra0tgJKzp318fLBy5UpWEQkhpNKkpKR88Si9WrVq8fI0nMuXL2P16tXiZrDm5ubw8vJCly5dGCcjlYUKAURu6Igffpg3bx6Ki4vRo0cP5Obmws7ODioqKpg9ezbc3d1ZxyNlGBoaIiwsDCYmJhLjYWFhaNCgAaNUFbd+/Xr07dsXDRs2hJWVFQAgNjYWKioqCA0NZZyuetPW1pYo3HIch5EjR0qdYjFo0CDaQ0oIEbwvFQH4as+ePXBycoKDgwNmzpwJoOTaokePHggMDMTYsWMZJySVgXoEEFJN5efnIykpCTk5OTA3N4e6ujrrSJWibF+Eqm7VqlVYtWoVfv/9d9jb2wMAzp8/jzlz5uCXX37B/PnzGSeUXW5uLvbu3Yv79+8DKDmWbty4cXQePWOXL1/+6ud27dr1OyYhhBA2dHR0vnol68uXL79zmu+jRYsWmDJlCjw9PSXG165di+3bt4tXCRBho0IAIaRa4VMhgOM4zJs3Dxs3bkR+fj4AoGbNmpg7dy4WLVrEOJ3shNoEkRBCCP/t2rXrq587ceLE75jk+1FRUcG///4r1e8lKSkJLVu2FHzjaFKCCgGEkGqFT4WAUjk5Obh37x5UVVXRtGlTqKiosI5UIcbGxggODkanTp0kxiMjIzF69GikpqYySkY+lp2dDX9/f/HskIWFBZydnaGlpcU4GSGEEFk1adIEXl5emDp1qsT4li1bsGbNGjx48IBRMlKZqEcAIURw8vLyxE3oPrZ169ZyO9ZXZerq6mjXrh3rGHIj1CaIQhMdHY0+ffpAVVUV7du3B1CybHTZsmUIDQ1FmzZtGCckhJDv69atW1BSUoKlpSUA4NixYwgICIC5uTmWLFkCZWVlxgll88svv2DmzJmIiYkRF+XDwsIQGBiIDRs2ME5HKgutCCCECEJxcTGWLVuGLVu24NmzZ0hMTISpqSkWLlwIY2NjuLi4sI4ok+joaBw8eBBpaWni7QGlDh8+zChVxTRt2hSLFy/G+PHjJcZ3796NxYsXIyUlhVEyUlaXLl3QpEkTbN++HTVqlMwbFBYWwtXVFSkpKbhy5QrjhIQQ8n21a9cO8+bNw7Bhw5CSkgJzc3M4ODggKioKAwYMwPr161lHlNmRI0ewZs0a8YqvFi1awMvLC0OGDGGcjFQWBdYBCCFEHpYuXYrAwECsWrVKokLfsmVL7Nixg2Ey2e3fvx+dOnXCvXv3cOTIERQUFODff//FhQsXeL00e/LkyZg1axYCAgLw6NEjPHr0CDt37oSnpycmT57MOh75P9HR0Zg7d664CAAANWrUwJw5cxAdHc0wGSGEVI7ExETx0diHDh1C165dERwcjMDAQPz1119sw1XQjz/+iGvXriErKwtZWVm4du0aFQGqGdoaQAgRhKCgIGzbtg09evTAtGnTxONWVlbizvR8s3z5cqxbtw5ubm7Q0NDAhg0bYGJigqlTp5a7tJ4vvLy8kJWVhZ9++kmqCSKfT0IQGk1NTaSlpaF58+YS448fP4aGhgajVIQQUnk4jkNxcTEA4Ny5cxg4cCCAkuN9X7x4wTJahURFRaG4uBgdOnSQGI+MjISioiJsbGwYJSOViVYEEEIEIT09Xar7LVCyZaCgoIBBoopLTk7GgAEDAADKysp49+4dRCIRPD09sW3bNsbpZCcSibBy5Uo8f/4cERERiI2NxcuXL3l9EoIQjRo1Ci4uLjhw4AAeP36Mx48fY//+/XB1dcWYMWNYxyOEkO/OxsYGS5cuxe7du3H58mXxe3Jqairv+g2V5ebmhsePH0uNp6enw83NjUEiwgKtCCCECIK5uTmuXr0KIyMjifGQkBBYW1szSlUxOjo6ePv2LQDAwMAAd+/ehaWlJbKzs5Gbm8s4XcUJrQmi0KxevRoikQiOjo4oLCwEx3FQVlbG9OnTsWLFCtbxCCHku1u/fj3GjRuHo0ePYsGCBeIJh5CQEKmTb/gkPj6+3Iav1tbWiI+PZ5CIsECFAEKIICxatAgTJ05Eeno6iouLcfjwYSQkJCAoKAgnTpxgHU8mdnZ2OHv2LCwtLTFixAh4eHjgwoULOHv2LHr06ME6HhE4ZWVlbNiwAb6+vkhOTgYANG7cGGpqaoyTEUJI5WjVqhXu3LkjNf77779DUVGRQSL5UFFRwbNnz6SOUs7IyJDoC0OEjU4NIIQIxtWrV+Hj44PY2Fjk5OSgTZs2WLRoEXr37s06mkxevnyJvLw8NGjQAMXFxVi1ahXCw8PRtGlT/Prrr9DR0WEdkQiMg4MDAgMDoampCQcHh88+V11dHRYWFpg2bRqvm1cSQkh1M2bMGGRkZODYsWPi1+/s7GwMHToUenp6OHjwIOOEpDJQIYAQQgghAAAnJyds3LgRGhoacHJy+uxzP3z4gOvXr8PS0hJ///13JSUkhJDKo6CgAJFI9MnHi4qKKjGN/KSnp8POzg5ZWVni7ZMxMTHQ19fH2bNnYWhoyDghqQxUCCCECE5OTo64y28pTU1NRmlkp6ioiIyMDOjp6UmMZ2VlQU9Pj7cXIEQ44uPj0a5dO7x79451FEIIkbtjx45JfFxQUIDbt29j165d8Pb2houLC6NkFffu3Tvs3bsXsbGxUFVVRatWrTBmzBgoKSmxjkYqCRUCCCGCkJqaihkzZuDSpUvIy8sTj3McB5FIxMubZgUFBWRmZkoVAp4+fYrGjRvj/fv3jJIRUqKoqAh3796FlZUV6yiEEFJpgoODceDAAalCAV9cuXIFnTp1kuoHUFhYiPDwcNjZ2TFKRioTdYMghAjC+PHjwXEcdu7cCX19/c8u5avqNm7cCKDkmL0dO3ZAXV1d/FhRURGuXLkidbY7ISwoKipSEYAQUu3Y2tpiypQprGPIrHv37uWuOHz9+jW6d+/Oy8kT8u2oEEAIEYTY2FjcvHkTZmZmrKNU2Lp16wCUrGbYsmWLRGdiZWVlGBsbY8uWLaziEUIIIdXW+/fvsXHjRhgYGLCOIrPS1ZIfy8rKQq1atRgkIixQIYAQIgjt2rXD48ePBVEISE1NBVBSsT98+DCdDkAIIYQwoKOjI3HDzHEc3r59CzU1NezZs4dhMtmUngYjEokwadIkqKioiB8rKipCXFwcOnXqxCoeqWRUCCCECMKOHTswbdo0pKeno2XLllLNblq1asUomewuXrzIOgIhhBBSba1fv17iYwUFBejq6qJDhw68LNKXHhXIcRw0NDSgqqoqfkxZWRm2traYPHkyq3ikklGzQEKIIERERGDs2LF4+PCheEwkEvG6WWBRURECAwNx/vx5/Pfff1InIVy4cIFRMkIIIYTwlbe3N2bPnk3bAKo5KgQQQgTB3NwcLVq0wJw5c8ptFmhkZMQomexmzJiBwMBADBgwAPXr15f6nkp7CRBCCCHk+8jOzoa/vz/u3bsHALCwsICzs7N4dp0QvqJCACFEEGrVqoXY2Fg0adKEdRS5qVu3LoKCgtC/f3/WUQghhJBqJzo6Gn369IGqqirat28PAIiKisL79+8RGhqKNm3aME4oGxMTk8+erpSSklKJaQgr1COAECII9vb2gisEKCsrC+r7IYQQQvjE09MTgwcPxvbt21GjRsltU2FhIVxdXTFr1ixcuXKFcULZzJo1S+LjgoIC3L59G6dPn4aXlxebUKTS0YoAQoggbNu2DUuXLoWzszMsLS2lmgUOHjyYUTLZrVmzBikpKfDz8/ts5Z4QQggh8qeqqorbt2+jefPmEuPx8fGwsbFBbm4uo2Tfx6ZNmxAdHY2AgADWUUgloEIAIUQQFBQUPvkYX5sF/vjjj7h48SJq164NCwsLqeLG4cOHGSUjhBBChE9fXx+7d+9G7969JcbPnDkDR0dHPHv2jFGy7yMlJQWtW7fGmzdvWEchlYC2BhBCBOHjjvpCoK2tjR9//JF1DEIIIaRaGjVqFFxcXLB69Wp06tQJABAWFgYvLy+MGTOGcTr5CwkJQe3atVnHIJWECgGEEFJF0dI8QgghhJ3Vq1dDJBLB0dERhYWFAAAlJSVMnz4dK1asYJxOdtbW1hJbDjmOQ2ZmJp4/f44///yTYTJSmWhrACFEMC5fvozVq1eLj/gxNzeHl5cXunTpwjhZxTx//hwJCQkAADMzM+jq6jJORAghhFQfubm5SE5OBgA0btwYampqjBNVjLe3t8THCgoK0NXVRbdu3aT6IRDhokIAIUQQ9uzZAycnJzg4OKBz584ASpbvHTlyBIGBgRg7dizjhN/u3bt3cHd3R1BQkHjrg6KiIhwdHfHHH3/w/kKEEEIIIYSwQYUAQoggtGjRAlOmTIGnp6fE+Nq1a7F9+3bxKgE+mTp1Ks6dOwc/Pz9xcePatWuYOXMmevXqhc2bNzNOSAghhAiLg4MDAgMDoampCQcHh88+l89Ne4uKinD06FHx9ZGFhQUGDx4MRUVFxslIZaEeAYQQQUhJScGgQYOkxgcPHoz//e9/DBJV3F9//YWQkBB069ZNPNa/f3+oqqpi5MiRVAgghBBC5ExLS0u8f15LS4txmu8jKSkJ/fv3R3p6OszMzAAAvr6+MDQ0xMmTJ9G4cWPGCUlloEIAIUQQDA0Ncf78eTRp0kRi/Ny5czA0NGSUqmJyc3Ohr68vNa6npye4s4sJIYSQqqBso16hNu2dOXMmGjdujIiICPEpAVlZWRg/fjxmzpyJkydPMk5IKgNtDSCECMLmzZsxa9YsODs7SxzxExgYiA0bNmDq1KmME367Hj16oE6dOggKCkLNmjUBAO/fv8fEiRPx8uVLnDt3jnFCQgghRLiWLl2KcePGwcTEhHUUuapVqxYiIiJgaWkpMR4bG4vOnTsjJyeHUTJSmWhFACFEEKZPn4569ephzZo1OHjwIICSvgEHDhzAkCFDGKeTzfr169G3b180bNgQVlZWAErepFVUVBAaGso4HSGEECJshw4dwuLFi9GhQweMHz8eI0eORN26dVnHqjAVFRW8fftWajwnJwfKysoMEhEWaEUAIYRUYbm5udi7dy/u378PoKS4MW7cOKiqqjJORgghhAjfv//+i71792L//v148uQJevXqhXHjxmHo0KG8Pb3H0dERt27dgr+/P9q3bw8AiIyMxOTJk9G2bVsEBgayDUgqBRUCCCGCEBUVheLiYnTo0EFiPDIyEoqKirCxsWGUTHa+vr7Q19eHs7OzxPjOnTvx/PlzzJ07l1EyQgghpPoJCwtDcHAwDh06hLy8PLx584Z1JJlkZ2dj4sSJOH78OJSUlAAABQUFGDJkCAIDAwXbJJFIUmAdgBBC5MHNzQ2PHz+WGk9PT4ebmxuDRBW3detWNG/eXGrcwsICW7ZsYZCIEEIIqb5q1aoFVVVVKCsro6CggHUcmWlra+PYsWNITEzEoUOHcOjQISQmJuLIkSNUBKhGqBBACBGE+Ph4tGnTRmrc2toa8fHxDBJVXGZmJurXry81rquri4yMDAaJCCGEkOolNTUVy5Ytg4WFBWxsbHD79m14e3sjMzOTdbQK8ff3x9ChQzFixAiMGDECQ4cOxY4dO1jHIpWImgUSQgRBRUUFz549g6mpqcR4RkYGatTg50udoaEhwsLCpLoVh4WFoUGDBoxSEUIIIdWDra0toqKi0KpVKzg5OWHMmDEwMDBgHavCFi1ahLVr18Ld3R0dO3YEAFy/fh2enp5IS0uDj48P44SkMvDz6pgQQj7Su3dvzJ8/H8eOHRMva8vOzsb//vc/9OrVi3E62UyePBmzZs1CQUEB7O3tAQDnz5/HnDlz8MsvvzBORwghhAhbjx49sHPnTpibm7OOIlebN2/G9u3bMWbMGPHY4MGD0apVK7i7u1MhoJqgZoGEEEFIT0+HnZ0dsrKyYG1tDQCIiYmBvr4+zp49C0NDQ8YJvx3HcZg3bx42btyI/Px8AEDNmjUxd+5cLFq0iHE6QgghpHrIz89HamoqGjduzNtVhmVpa2sjKioKTZs2lRhPTExE+/btkZ2dzSYYqVRUCCCECMa7d++wd+9exMbGQlVVFa1atcKYMWPEHXH5KicnB/fu3YOqqiqaNm0KFRUV1pEIIYQQwXv//j1mzJiBXbt2ASi5UTY1NYW7uzsMDAwwb948xgll4+7uDiUlJaxdu1ZifPbs2Xj//j02bdrEKBmpTFQIIIQIwpUrV9CpUyepSn1hYSHCw8NhZ2fHKBkhhBBC+MjDwwNhYWFYv349+vbti7i4OJiamuLYsWNYsmQJbt++zTqiTNzd3REUFARDQ0PY2toCKDluOS0tDY6OjhITKB8XC4hwUCGAECIIioqKyMjIgJ6ensR4VlYW9PT0UFRUxCgZIYQQQvjIyMgIBw4cgK2tLTQ0NBAbGwtTU1MkJSWhTZs2ePPmDeuIMunevftXPU8kEuHChQvfOQ1hhf+bXAghBCX76UUikdR4VlYWatWqxSARIYQQQvjs+fPnUhMMQMlWxPKuOfji4sWLrCOQKoAKAYQQXnNwcABQUrWeNGmSxP75oqIixMXFoVOnTqziEUIIIYSnbGxscPLkSbi7uwOA+OZ/x44d4mP3COErKgQQQnit9KhAjuOgoaEBVVVV8WPKysqwtbXF5MmTWcUjhBBCCE8tX74c/fr1Q3x8PAoLC7FhwwbEx8cjPDwcly9fZh2PkAqhHgGEEEHw9vbG7NmzaRsAIYQQQuQmJSUFvr6+iI2NRU5ODtq0aYO5c+fC0tKSdTRCKoQKAYQQQgghhBBSRkFBAaZOnYqFCxfCxMSEdRxC5I4KAYQQQTAxMfls456UlJRKTEMIIYQQvtPS0kJMTAwVAoggUY8AQoggzJo1S+LjgoIC3L59G6dPn4aXlxebUIQQQgjhraFDh+Lo0aPw9PRkHYUQuaNCACFEEDw8PMod37RpE6Kjoys5DSGEEEL4rmnTpvDx8UFYWBjatm0r1Ydo5syZjJIRUnG0NYAQImgpKSlo3bo13rx5wzoKIYQQQnjkc1sCRCIRbTskvEYrAgghghYSEoLatWuzjkEIIYQQnklNTRX/vnTu9HP9iAjhEyoEEEIEwdraWuLNmeM4ZGZm4vnz5/jzzz8ZJiOEEEIIX/n7+2PdunV48OABgJLtArNmzYKrqyvjZIRUDBUCCCGCMHToUImPFRQUoKuri27duqF58+ZsQhFCCCGEtxYtWoS1a9fC3d0dHTt2BABcv34dnp6eSEtLg4+PD+OEhMiOegQQQgghhBBCyEd0dXWxceNGjBkzRmJ83759cHd3x4sXLxglI6TiaEUAIUQwioqKcPToUdy7dw8AYGFhgcGDB0NRUZFxMkIIIYTwTUFBAWxsbKTG27Zti8LCQgaJCJEfWhFACBGEpKQk9O/fH+np6TAzMwMAJCQkwNDQECdPnkTjxo0ZJySEEEIIn7i7u0NJSQlr166VGJ89ezbev3+PTZs2MUpGSMVRIYAQIgj9+/cHx3HYu3ev+JSArKwsjB8/HgoKCjh58iTjhIQQQgjhE3d3dwQFBcHQ0BC2trYAgMjISKSlpcHR0RFKSkri535cLCCkqqNCACFEEGrVqoWIiAhYWlpKjMfGxqJz587IyclhlIwQQgghfNS9e/evep5IJMKFCxe+cxpC5It6BBBCBEFFRQVv376VGs/JyYGysjKDRIQQQgjhs4sXL7KOQMh3o8A6ACGEyMPAgQMxZcoUREZGguM4cByHiIgITJs2DYMHD2YdjxBCCCGEkCqDtgYQQgQhOzsbEydOxPHjx8V79goKCjBkyBAEBgZCS0uLcUJCCCGEEEKqBioEEEIEJSkpCfHx8QAAc3NzNGnShHEiQgghhBBCqhbqEUAIEQx/f3+sW7cODx48AAA0bdoUs2bNgqurK+NkhBBCCCGEVB1UCCCECMKiRYuwdu1auLu7o2PHjgCA69evw9PTE2lpafDx8WGckBBCCCGEkKqBtgYQQgRBV1cXGzduxJgxYyTG9+3bB3d3d7x48YJRMkIIIYQQQqoWOjWAECIIBQUFsLGxkRpv27YtCgsLGSQihBBCCCGkaqJCACFEECZMmIDNmzdLjW/btg3jxo1jkIgQQgghhJCqibYGEEIEwd3dHUFBQTA0NIStrS0AIDIyEmlpaXB0dBQfKQgAa9euZRWTEEIIIYQQ5qgQQAgRhO7du3/V80QiES5cuPCd0xBCCCGEEFJ1USGAEEIIIYQQQgipRqhHACGEEEIIIYQQUo1QIYAQQgghhBBCCKlGqBBACCGEEEIIIYRUI1QIIIQQQgTg0qVLEIlEWLJkCesoVc6kSZMgEonw8OFDmT9HYGAgRCIRAgMDv/rPGBsbw9jYWOavSQghhHwvVAgghBBCGLh48SJGjRoFQ0NDqKiooHbt2vjhhx+wbt065OXllftn+HZj+fr1a6ipqUFHR+eT31Op7du3QyQSYcqUKZWUjhBCCKm+qBBACCGEVKLCwkJMnToV9vb2OHnyJGxtbfHzzz9j9OjRyMzMxM8//wwrKyskJSWxjlphWlpaGDZsGLKzs/HXX3999rk7d+4EALi4uMg9h6+vL+7duwcDAwO5f25CCCGEj6gQQAghhFSi+fPnY9u2bWjXrh0SEhJw6NAh+Pr64s8//0RCQgIWLVqExMRE9O3bF2/evGEdt8JKb+xLb/TLc+/ePURERMDCwgIdOnSQe4b69eujefPmUFJSkvvnJoQQQviICgGEEEJIJUlMTMTatWtRu3ZtHD9+XGqGWlFREd7e3hg7diySk5OxevVqAMDDhw8hEonw6NEjPHr0CCKRSPyrvJ4A0dHR6NWrFzQ0NKClpYUff/zxk/v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      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot a chart showing the top correlations with target variable\n",
    "dw.plot_corr(df_enc, 'subscribed_enc', n=16, size=(12,6), rotation=90)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot 3D Chart\n",
    "\n",
    "`dw.plot_3d()` creates a 3D scatter plot using Plotly Express.\n",
    "\n",
    "This function generates an interactive 3D scatter plot using the\n",
    "Plotly Express library. It allows for customization of the `x`, `y`, and `z`\n",
    "axes, as well as color coding of the points based on the column specified\n",
    "for `color` (similar to the `hue` parameter in Seaborn). A `color_discrete_map`\n",
    "dictionary can be passed to map specific values of the `color` column to\n",
    "colors. Alternatively, you can just pass a `color_discrete_map` or\n",
    "`color_continuous_scale` depending on the type of values in the `color`\n",
    "column. Onlye 1 of these 3 coloring methods should be used at a time. The plot\n",
    "can also be displayed with either a linear or logarithmic scale on each axis\n",
    "by setting `x_scale`, `y_scale`, or `z_scale` from 'linear' to 'log'.\n",
    "\n",
    "Use this function to visualize and explore relationships between three\n",
    "variables in a dataset, with the option to color code the points based\n",
    "on a fourth variable. It is a great way to visualize the top 3 principal\n",
    "components, dimensioned by the target variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load some PCA data that has good clustering\n",
    "df_X_scaled_pca_7_XY = pd.read_csv('data/df_X_scaled_pca_7_XY.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Map colors for consistent display of the 'Churn' values\n",
    "color_map_churn = {'Customer Stayed': px.colors.qualitative.D3[0], 'Customer Left': px.colors.qualitative.D3[1]}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
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F=e.borderwidth,B=e.borderpad,N=F+B,j=R.append(\"rect\").attr(\"class\",\"bg\").style(\"stroke-width\",F+\"px\").call(u.stroke,e.bordercolor).call(u.fill,e.bgcolor),U=e.width||e.height,V=w._topclips.selectAll(\"#\"+L).data(U?[0]:[]);V.enter().append(\"clipPath\").classed(\"annclip\",!0).attr(\"id\",L).append(\"rect\"),V.exit().remove();var q=e.font,H=w._meta?o.templateString(e.text,w._meta):e.text,G=R.append(\"text\").classed(\"annotation-text\",!0).text(H);k.annotationText?G.call(h.makeEditable,{delegate:R,gd:t}).call(Y).on(\"edit\",(function(r){e.text=r,this.call(Y),S(\"text\",r),y&&y.autorange&&M(y._name+\".autorange\",!0),x&&x.autorange&&M(x._name+\".autorange\",!0),i.call(\"_guiRelayout\",t,E())})):G.call(Y)}else n.selectAll(\"#\"+L).remove();function W(t){var n={index:r,annotation:e._input,fullAnnotation:e,event:t};return a&&(n.subplotId=a),n}function Y(r){return 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kt,At=function(r,n){O.selectAll(\".annotation-arrow-g\").remove();var l=C.x.head,f=C.y.head,h=C.x.tail+r,p=C.y.tail+n,v=C.x.text+r,b=C.y.text+n,_=o.rotationXYMatrix(P,v,b),w=o.apply2DTransform(_),A=o.apply2DTransform2(_),L=+j.attr(\"width\"),D=+j.attr(\"height\"),z=v-.5*L,F=z+L,B=b-.5*D,N=B+D,U=[[z,B,z,N],[z,N,F,N],[F,N,F,B],[F,B,z,B]].map(A);if(!U.reduce((function(t,e){return t^!!o.segmentsIntersect(l,f,l+1e6,f+1e6,e[0],e[1],e[2],e[3])}),!1)){U.forEach((function(t){var e=o.segmentsIntersect(h,p,l,f,t[0],t[1],t[2],t[3]);e&&(h=e.x,p=e.y)}));var V=e.arrowwidth,q=e.arrowcolor,H=e.arrowside,G=O.append(\"g\").style({opacity:u.opacity(q)}).classed(\"annotation-arrow-g\",!0),W=G.append(\"path\").attr(\"d\",\"M\"+h+\",\"+p+\"L\"+l+\",\"+f).style(\"stroke-width\",V+\"px\").call(u.stroke,u.rgb(q));if(g(W,H,e),k.annotationPosition&&W.node().parentNode&&!a){var Y=l,X=f;if(e.standoff){var Z=Math.sqrt(Math.pow(l-h,2)+Math.pow(f-p,2));Y+=e.standoff*(h-l)/Z,X+=e.standoff*(p-f)/Z}var K,J,$=G.append(\"path\").classed(\"annotation-arrow\",!0).classed(\"anndrag\",!0).classed(\"cursor-move\",!0).attr({d:\"M3,3H-3V-3H3ZM0,0L\"+(h-Y)+\",\"+(p-X),transform:s(Y,X)}).style(\"stroke-width\",V+6+\"px\").call(u.stroke,\"rgba(0,0,0,0)\").call(u.fill,\"rgba(0,0,0,0)\");d.init({element:$.node(),gd:t,prepFn:function(){var t=c.getTranslate(R);K=t.x,J=t.y,y&&y.autorange&&M(y._name+\".autorange\",!0),x&&x.autorange&&M(x._name+\".autorange\",!0)},moveFn:function(t,r){var n=w(K,J),i=n[0]+t,a=n[1]+r;R.call(c.setTranslate,i,a),S(\"x\",m(y,t,\"x\",T,e)),S(\"y\",m(x,r,\"y\",T,e)),e.axref===e.xref&&S(\"ax\",m(y,t,\"ax\",T,e)),e.ayref===e.yref&&S(\"ay\",m(x,r,\"ay\",T,e)),G.attr(\"transform\",s(t,r)),I.attr({transform:\"rotate(\"+P+\",\"+i+\",\"+a+\")\"})},doneFn:function(){i.call(\"_guiRelayout\",t,E());var 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e=t._fullLayout;e._infolayer.selectAll(\".annotation\").remove();for(var r=0;r<e.annotations.length;r++)e.annotations[r].visible&&y(t,r);return a.previousPromises(t)},drawOne:y,drawRaw:x}},33652:function(t,e,r){\"use strict\";var n=r(33428),i=r(76308),a=r(72196),o=r(3400),s=o.strScale,l=o.strRotate,u=o.strTranslate;t.exports=function(t,e,r){var o,c,f,h,p=t.node(),d=a[r.arrowhead||0],v=a[r.startarrowhead||0],g=(r.arrowwidth||1)*(r.arrowsize||1),y=(r.arrowwidth||1)*(r.startarrowsize||1),m=e.indexOf(\"start\")>=0,x=e.indexOf(\"end\")>=0,b=d.backoff*g+r.standoff,_=v.backoff*y+r.startstandoff;if(\"line\"===p.nodeName){o={x:+t.attr(\"x1\"),y:+t.attr(\"y1\")},c={x:+t.attr(\"x2\"),y:+t.attr(\"y2\")};var w=o.x-c.x,T=o.y-c.y;if(h=(f=Math.atan2(T,w))+Math.PI,b&&_&&b+_>Math.sqrt(w*w+T*T))return void D();if(b){if(b*b>w*w+T*T)return void D();var k=b*Math.cos(f),A=b*Math.sin(f);c.x+=k,c.y+=A,t.attr({x2:c.x,y2:c.y})}if(_){if(_*_>w*w+T*T)return void D();var 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n=r(23816),i=r(42300);t.exports={moduleType:\"component\",name:\"annotations\",layoutAttributes:r(13916),supplyLayoutDefaults:r(45216),includeBasePlot:r(36632)(\"annotations\"),calcAutorange:r(90272),draw:n.draw,drawOne:n.drawOne,drawRaw:n.drawRaw,hasClickToShow:i.hasClickToShow,onClick:i.onClick,convertCoords:r(26828)}},45899:function(t,e,r){\"use strict\";var n=r(13916),i=r(67824).overrideAll,a=r(31780).templatedArray;t.exports=i(a(\"annotation\",{visible:n.visible,x:{valType:\"any\"},y:{valType:\"any\"},z:{valType:\"any\"},ax:{valType:\"number\"},ay:{valType:\"number\"},xanchor:n.xanchor,xshift:n.xshift,yanchor:n.yanchor,yshift:n.yshift,text:n.text,textangle:n.textangle,font:n.font,width:n.width,height:n.height,opacity:n.opacity,align:n.align,valign:n.valign,bgcolor:n.bgcolor,bordercolor:n.bordercolor,borderpad:n.borderpad,borderwidth:n.borderwidth,showarrow:n.showarrow,arrowcolor:n.arrowcolor,arrowhead:n.arrowhead,startarrowhead:n.startarrowhead,arrowside:n.arrowside,arrowsize:n.arrowsize,startarrowsize:n.startarrowsize,arrowwidth:n.arrowwidth,standoff:n.standoff,startstandoff:n.startstandoff,hovertext:n.hovertext,hoverlabel:n.hoverlabel,captureevents:n.captureevents}),\"calc\",\"from-root\")},42456:function(t,e,r){\"use strict\";var n=r(3400),i=r(54460);function a(t,e){var r=e.fullSceneLayout.domain,a=e.fullLayout._size,o={pdata:null,type:\"linear\",autorange:!1,range:[-1/0,1/0]};t._xa={},n.extendFlat(t._xa,o),i.setConvert(t._xa),t._xa._offset=a.l+r.x[0]*a.w,t._xa.l2p=function(){return.5*(1+t._pdata[0]/t._pdata[3])*a.w*(r.x[1]-r.x[0])},t._ya={},n.extendFlat(t._ya,o),i.setConvert(t._ya),t._ya._offset=a.t+(1-r.y[1])*a.h,t._ya.l2p=function(){return.5*(1-t._pdata[1]/t._pdata[3])*a.h*(r.y[1]-r.y[0])}}t.exports=function(t){for(var e=t.fullSceneLayout.annotations,r=0;r<e.length;r++)a(e[r],t);t.fullLayout._infolayer.selectAll(\".annotation-\"+t.id).remove()}},52808:function(t,e,r){\"use strict\";var n=r(3400),i=r(54460),a=r(51272),o=r(87192),s=r(45899);function l(t,e,r,a){function l(r,i){return n.coerce(t,e,s,r,i)}function u(t){var n=t+\"axis\",a={_fullLayout:{}};return a._fullLayout[n]=r[n],i.coercePosition(e,a,l,t,t,.5)}l(\"visible\")&&(o(t,e,a.fullLayout,l),u(\"x\"),u(\"y\"),u(\"z\"),n.noneOrAll(t,e,[\"x\",\"y\",\"z\"]),e.xref=\"x\",e.yref=\"y\",e.zref=\"z\",l(\"xanchor\"),l(\"yanchor\"),l(\"xshift\"),l(\"yshift\"),e.showarrow&&(e.axref=\"pixel\",e.ayref=\"pixel\",l(\"ax\",-10),l(\"ay\",-30),n.noneOrAll(t,e,[\"ax\",\"ay\"])))}t.exports=function(t,e,r){a(t,e,{name:\"annotations\",handleItemDefaults:l,fullLayout:r.fullLayout})}},71836:function(t,e,r){\"use strict\";var n=r(23816).drawRaw,i=r(94424),a=[\"x\",\"y\",\"z\"];t.exports=function(t){for(var e=t.fullSceneLayout,r=t.dataScale,o=e.annotations,s=0;s<o.length;s++){for(var l=o[s],u=!1,c=0;c<3;c++){var f=a[c],h=l[f],p=e[f+\"axis\"].r2fraction(h);if(p<0||p>1){u=!0;break}}u?t.fullLayout._infolayer.select(\".annotation-\"+t.id+'[data-index=\"'+s+'\"]').remove():(l._pdata=i(t.glplot.cameraParams,[e.xaxis.r2l(l.x)*r[0],e.yaxis.r2l(l.y)*r[1],e.zaxis.r2l(l.z)*r[2]]),n(t.graphDiv,l,s,t.id,l._xa,l._ya))}}},56864:function(t,e,r){\"use strict\";var n=r(24040),i=r(3400);t.exports={moduleType:\"component\",name:\"annotations3d\",schema:{subplots:{scene:{annotations:r(45899)}}},layoutAttributes:r(45899),handleDefaults:r(52808),includeBasePlot:function(t,e){var r=n.subplotsRegistry.gl3d;if(r)for(var a=r.attrRegex,o=Object.keys(t),s=0;s<o.length;s++){var l=o[s];a.test(l)&&(t[l].annotations||[]).length&&(i.pushUnique(e._basePlotModules,r),i.pushUnique(e._subplots.gl3d,l))}},convert:r(42456),draw:r(71836)}},54976:function(t,e,r){\"use 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y=n.select(this).selectAll(\"g.errorbar\").data(e,h);if(y.exit().remove(),e.length){d.visible||y.selectAll(\"path.xerror\").remove(),v.visible||y.selectAll(\"path.yerror\").remove(),y.style(\"opacity\",1);var m=y.enter().append(\"g\").classed(\"errorbar\",!0);c&&m.style(\"opacity\",0).transition().duration(s.duration).style(\"opacity\",1),a.setClipUrl(y,r.layerClipId,t),y.each((function(t){var e=n.select(this),r=function(t,e,r){var n={x:e.c2p(t.x),y:r.c2p(t.y)};return void 0!==t.yh&&(n.yh=r.c2p(t.yh),n.ys=r.c2p(t.ys),i(n.ys)||(n.noYS=!0,n.ys=r.c2p(t.ys,!0))),void 0!==t.xh&&(n.xh=e.c2p(t.xh),n.xs=e.c2p(t.xs),i(n.xs)||(n.noXS=!0,n.xs=e.c2p(t.xs,!0))),n}(t,l,u);if(!g||t.vis){var a,o=e.select(\"path.yerror\");if(v.visible&&i(r.x)&&i(r.yh)&&i(r.ys)){var 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n=r(3400),i=r(55756),a=r(16132);t.exports=function(t,e,r,o){var s=n.extendFlat({},o.hoverlabel);e.hovertemplate&&(s.namelength=-1),a(t,e,(function(r,a){return n.coerce(t,e,i,r,a)}),s)}},10624:function(t,e,r){\"use strict\";var n=r(3400);e.getSubplot=function(t){return t.subplot||t.xaxis+t.yaxis||t.geo},e.isTraceInSubplots=function(t,r){if(\"splom\"===t.type){for(var n=t.xaxes||[],i=t.yaxes||[],a=0;a<n.length;a++)for(var o=0;o<i.length;o++)if(-1!==r.indexOf(n[a]+i[o]))return!0;return!1}return-1!==r.indexOf(e.getSubplot(t))},e.flat=function(t,e){for(var r=new Array(t.length),n=0;n<t.length;n++)r[n]=e;return r},e.p2c=function(t,e){for(var r=new Array(t.length),n=0;n<t.length;n++)r[n]=t[n].p2c(e);return r},e.getDistanceFunction=function(t,r,n,i){return\"closest\"===t?i||e.quadrature(r,n):\"x\"===t.charAt(0)?r:n},e.getClosest=function(t,e,r){if(!1!==r.index)r.index>=0&&r.index<t.length?r.distance=0:r.index=!1;else for(var n=0;n<t.length;n++){var 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n,i,o=r.container,s=r.fullLayout,l=s._size,u=r.event,c=!!e.hLinePoint,f=!!e.vLinePoint;if(o.selectAll(\".spikeline\").remove(),f||c){var d=p.combine(s.plot_bgcolor,s.paper_bgcolor);if(c){var g,y,m=e.hLinePoint;n=m&&m.xa,\"cursor\"===(i=m&&m.ya).spikesnap?(g=u.pointerX,y=u.pointerY):(g=n._offset+m.x,y=i._offset+m.y);var x,b,_=a.readability(m.color,d)<1.5?p.contrast(d):m.color,w=i.spikemode,T=i.spikethickness,k=i.spikecolor||_,A=v.getPxPosition(t,i);if(-1!==w.indexOf(\"toaxis\")||-1!==w.indexOf(\"across\")){if(-1!==w.indexOf(\"toaxis\")&&(x=A,b=g),-1!==w.indexOf(\"across\")){var 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n=r(33816),i=r(31780).templatedArray;r(36208),t.exports=i(\"image\",{visible:{valType:\"boolean\",dflt:!0,editType:\"arraydraw\"},source:{valType:\"string\",editType:\"arraydraw\"},layer:{valType:\"enumerated\",values:[\"below\",\"above\"],dflt:\"above\",editType:\"arraydraw\"},sizex:{valType:\"number\",dflt:0,editType:\"arraydraw\"},sizey:{valType:\"number\",dflt:0,editType:\"arraydraw\"},sizing:{valType:\"enumerated\",values:[\"fill\",\"contain\",\"stretch\"],dflt:\"contain\",editType:\"arraydraw\"},opacity:{valType:\"number\",min:0,max:1,dflt:1,editType:\"arraydraw\"},x:{valType:\"any\",dflt:0,editType:\"arraydraw\"},y:{valType:\"any\",dflt:0,editType:\"arraydraw\"},xanchor:{valType:\"enumerated\",values:[\"left\",\"center\",\"right\"],dflt:\"left\",editType:\"arraydraw\"},yanchor:{valType:\"enumerated\",values:[\"top\",\"middle\",\"bottom\"],dflt:\"top\",editType:\"arraydraw\"},xref:{valType:\"enumerated\",values:[\"paper\",n.idRegex.x.toString()],dflt:\"paper\",editType:\"arraydraw\"},yref:{valType:\"enumerated\",values:[\"paper\",n.idRegex.y.toString()],dflt:\"paper\",editType:\"arraydraw\"},editType:\"arraydraw\"})},63556:function(t,e,r){\"use 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b=Object.keys(l._plots);for(r=0;r<b.length;r++){e=b[r];var _=l._plots[e];if(_.imagelayer){var w=_.imagelayer.selectAll(\"image\").data(c[e]||[]);w.enter().append(\"image\"),w.exit().remove(),w.each((function(t){g.bind(this)(t),y.bind(this)(t)}))}}}},7402:function(t,e,r){\"use strict\";t.exports={moduleType:\"component\",name:\"images\",layoutAttributes:r(65760),supplyLayoutDefaults:r(25024),includeBasePlot:r(36632)(\"images\"),draw:r(60963),convertCoords:r(63556)}},3800:function(t,e,r){\"use strict\";var n=r(25376),i=r(22548);t.exports={_isSubplotObj:!0,visible:{valType:\"boolean\",dflt:!0,editType:\"legend\"},bgcolor:{valType:\"color\",editType:\"legend\"},bordercolor:{valType:\"color\",dflt:i.defaultLine,editType:\"legend\"},borderwidth:{valType:\"number\",min:0,dflt:0,editType:\"legend\"},font:n({editType:\"legend\"}),grouptitlefont:n({editType:\"legend\"}),orientation:{valType:\"enumerated\",values:[\"v\",\"h\"],dflt:\"v\",editType:\"legend\"},traceorder:{valType:\"flaglist\",flags:[\"reversed\",\"grouped\"],extras:[\"normal\"],editType:\"legend\"},tracegroupgap:{valType:\"number\",min:0,dflt:10,editType:\"legend\"},entrywidth:{valType:\"number\",min:0,editType:\"legend\"},entrywidthmode:{valType:\"enumerated\",values:[\"fraction\",\"pixels\"],dflt:\"pixels\",editType:\"legend\"},indentation:{valType:\"number\",min:-15,dflt:0,editType:\"legend\"},itemsizing:{valType:\"enumerated\",values:[\"trace\",\"constant\"],dflt:\"trace\",editType:\"legend\"},itemwidth:{valType:\"number\",min:30,dflt:30,editType:\"legend\"},itemclick:{valType:\"enumerated\",values:[\"toggle\",\"toggleothers\",!1],dflt:\"toggle\",editType:\"legend\"},itemdoubleclick:{valType:\"enumerated\",values:[\"toggle\",\"toggleothers\",!1],dflt:\"toggleothers\",editType:\"legend\"},groupclick:{valType:\"enumerated\",values:[\"toggleitem\",\"togglegroup\"],dflt:\"togglegroup\",editType:\"legend\"},x:{valType:\"number\",editType:\"legend\"},xref:{valType:\"enumerated\",dflt:\"paper\",values:[\"container\",\"paper\"],editType:\"layoutstyle\"},xanchor:{valType:\"enumerated\",values:[\"auto\",\"left\",\"center\",\"right\"],dflt:\"left\",editType:\"legend\"},y:{valType:\"number\",editType:\"legend\"},yref:{valType:\"enumerated\",dflt:\"paper\",values:[\"container\",\"paper\"],editType:\"layoutstyle\"},yanchor:{valType:\"enumerated\",values:[\"auto\",\"top\",\"middle\",\"bottom\"],editType:\"legend\"},uirevision:{valType:\"any\",editType:\"none\"},valign:{valType:\"enumerated\",values:[\"top\",\"middle\",\"bottom\"],dflt:\"middle\",editType:\"legend\"},title:{text:{valType:\"string\",dflt:\"\",editType:\"legend\"},font:n({editType:\"legend\"}),side:{valType:\"enumerated\",values:[\"top\",\"left\",\"top 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r=t._fullLayout,i=r._legends;r._infolayer.selectAll('[class^=\"legend\"]').each((function(){var t=n.select(this),e=t.attr(\"class\").split(\" \")[0];e.match(w)&&-1===i.indexOf(e)&&t.remove()}));for(var a=0;a<i.length;a++){var o=i[a];T(t,t._fullLayout[o])}}}},35456:function(t,e,r){\"use strict\";var n=r(24040),i=r(42451);t.exports=function(t,e,r){var a,o,s=e._inHover,l=i.isGrouped(e),u=i.isReversed(e),c={},f=[],h=!1,p={},d=0,v=0;function g(t,n,a){if(!1!==e.visible&&(!r||t===e._id))if(\"\"!==n&&i.isGrouped(e))-1===f.indexOf(n)?(f.push(n),h=!0,c[n]=[a]):c[n].push(a);else{var o=\"~~i\"+d;f.push(o),c[o]=[a],d++}}for(a=0;a<t.length;a++){var y=t[a],m=y[0],x=m.trace,b=x.legend,_=x.legendgroup;if(s||x.visible&&x.showlegend)if(n.traceIs(x,\"pie-like\"))for(p[_]||(p[_]={}),o=0;o<y.length;o++){var w=y[o].label;p[_][w]||(g(b,_,{label:w,color:y[o].color,i:y[o].i,trace:x,pts:y[o].pts}),p[_][w]=!0,v=Math.max(v,(w||\"\").length))}else 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d=o[p],v=c+\".\"+d+\".showspikes\";l[v]=!1,s[v]=f[d].showspikes}}r._previousVal=s}return l}function v(t,e){for(var r=e.currentTarget,i=r.getAttribute(\"data-attr\"),a=r.getAttribute(\"data-val\")||!0,o=t._fullLayout,s=o._subplots.geo||[],l=0;l<s.length;l++){var u=s[l],c=o[u];if(\"zoom\"===i){var f=c.projection.scale,h=\"in\"===a?2*f:.5*f;n.call(\"_guiRelayout\",t,u+\".projection.scale\",h)}}\"reset\"===i&&x(t,\"geo\")}function g(t){var e=t._fullLayout;return!e.hovermode&&(e._has(\"cartesian\")?e._isHoriz?\"y\":\"x\":\"closest\")}function y(t){var e=g(t);n.call(\"_guiRelayout\",t,\"hovermode\",e)}function m(t,e){for(var r=e.currentTarget.getAttribute(\"data-val\"),i=t._fullLayout,a=i._subplots.mapbox||[],o={},s=0;s<a.length;s++){var l=a[s],u=i[l].zoom,c=\"in\"===r?1.05*u:u/1.05;o[l+\".zoom\"]=c}n.call(\"_guiRelayout\",t,o)}function x(t,e){for(var r=t._fullLayout,i=r._subplots[e]||[],a={},o=0;o<i.length;o++)for(var s=i[o],l=r[s]._subplot.viewInitial,u=Object.keys(l),c=0;c<u.length;c++){var f=u[c];a[s+\".\"+f]=l[f]}n.call(\"_guiRelayout\",t,a)}c.toImage={name:\"toImage\",title:function(t){var e=(t._context.toImageButtonOptions||{}).format||\"png\";return u(t,\"png\"===e?\"Download plot as a png\":\"Download plot\")},icon:o.camera,click:function(t){var e=t._context.toImageButtonOptions,r={format:e.format||\"png\"};l.notifier(u(t,\"Taking snapshot - this may take a few seconds\"),\"long\"),\"svg\"!==r.format&&l.isIE()&&(l.notifier(u(t,\"IE only supports svg.  Changing format to svg.\"),\"long\"),r.format=\"svg\"),[\"filename\",\"width\",\"height\",\"scale\"].forEach((function(t){t in e&&(r[t]=e[t])})),n.call(\"downloadImage\",t,r).then((function(e){l.notifier(u(t,\"Snapshot succeeded\")+\" - \"+e,\"long\")})).catch((function(){l.notifier(u(t,\"Sorry, there was a problem downloading your snapshot!\"),\"long\")}))}},c.sendDataToCloud={name:\"sendDataToCloud\",title:function(t){return u(t,\"Edit in Chart Studio\")},icon:o.disk,click:function(t){i.sendDataToCloud(t)}},c.editInChartStudio={name:\"editInChartStudio\",title:function(t){return u(t,\"Edit in Chart Studio\")},icon:o.pencil,click:function(t){i.sendDataToCloud(t)}},c.zoom2d={name:\"zoom2d\",_cat:\"zoom\",title:function(t){return u(t,\"Zoom\")},attr:\"dragmode\",val:\"zoom\",icon:o.zoombox,click:f},c.pan2d={name:\"pan2d\",_cat:\"pan\",title:function(t){return u(t,\"Pan\")},attr:\"dragmode\",val:\"pan\",icon:o.pan,click:f},c.select2d={name:\"select2d\",_cat:\"select\",title:function(t){return u(t,\"Box Select\")},attr:\"dragmode\",val:\"select\",icon:o.selectbox,click:f},c.lasso2d={name:\"lasso2d\",_cat:\"lasso\",title:function(t){return u(t,\"Lasso Select\")},attr:\"dragmode\",val:\"lasso\",icon:o.lasso,click:f},c.drawclosedpath={name:\"drawclosedpath\",title:function(t){return u(t,\"Draw closed freeform\")},attr:\"dragmode\",val:\"drawclosedpath\",icon:o.drawclosedpath,click:f},c.drawopenpath={name:\"drawopenpath\",title:function(t){return u(t,\"Draw open freeform\")},attr:\"dragmode\",val:\"drawopenpath\",icon:o.drawopenpath,click:f},c.drawline={name:\"drawline\",title:function(t){return u(t,\"Draw line\")},attr:\"dragmode\",val:\"drawline\",icon:o.drawline,click:f},c.drawrect={name:\"drawrect\",title:function(t){return u(t,\"Draw 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axes\")},attr:\"zoom\",val:\"reset\",icon:o.home,click:f},c.hoverClosestCartesian={name:\"hoverClosestCartesian\",_cat:\"hoverclosest\",title:function(t){return u(t,\"Show closest data on hover\")},attr:\"hovermode\",val:\"closest\",icon:o.tooltip_basic,gravity:\"ne\",click:f},c.hoverCompareCartesian={name:\"hoverCompareCartesian\",_cat:\"hoverCompare\",title:function(t){return u(t,\"Compare data on hover\")},attr:\"hovermode\",val:function(t){return t._fullLayout._isHoriz?\"y\":\"x\"},icon:o.tooltip_compare,gravity:\"ne\",click:f},c.zoom3d={name:\"zoom3d\",_cat:\"zoom\",title:function(t){return u(t,\"Zoom\")},attr:\"scene.dragmode\",val:\"zoom\",icon:o.zoombox,click:h},c.pan3d={name:\"pan3d\",_cat:\"pan\",title:function(t){return u(t,\"Pan\")},attr:\"scene.dragmode\",val:\"pan\",icon:o.pan,click:h},c.orbitRotation={name:\"orbitRotation\",title:function(t){return u(t,\"Orbital rotation\")},attr:\"scene.dragmode\",val:\"orbit\",icon:o[\"3d_rotate\"],click:h},c.tableRotation={name:\"tableRotation\",title:function(t){return u(t,\"Turntable rotation\")},attr:\"scene.dragmode\",val:\"turntable\",icon:o[\"z-axis\"],click:h},c.resetCameraDefault3d={name:\"resetCameraDefault3d\",_cat:\"resetCameraDefault\",title:function(t){return u(t,\"Reset camera to default\")},attr:\"resetDefault\",icon:o.home,click:p},c.resetCameraLastSave3d={name:\"resetCameraLastSave3d\",_cat:\"resetCameraLastSave\",title:function(t){return u(t,\"Reset camera to last save\")},attr:\"resetLastSave\",icon:o.movie,click:p},c.hoverClosest3d={name:\"hoverClosest3d\",_cat:\"hoverclosest\",title:function(t){return u(t,\"Toggle show closest data on hover\")},attr:\"hovermode\",val:null,toggle:!0,icon:o.tooltip_basic,gravity:\"ne\",click:function(t,e){var r=d(t,e);n.call(\"_guiRelayout\",t,r)}},c.zoomInGeo={name:\"zoomInGeo\",_cat:\"zoomin\",title:function(t){return u(t,\"Zoom in\")},attr:\"zoom\",val:\"in\",icon:o.zoom_plus,click:v},c.zoomOutGeo={name:\"zoomOutGeo\",_cat:\"zoomout\",title:function(t){return u(t,\"Zoom out\")},attr:\"zoom\",val:\"out\",icon:o.zoom_minus,click:v},c.resetGeo={name:\"resetGeo\",_cat:\"reset\",title:function(t){return u(t,\"Reset\")},attr:\"reset\",val:null,icon:o.autoscale,click:v},c.hoverClosestGeo={name:\"hoverClosestGeo\",_cat:\"hoverclosest\",title:function(t){return u(t,\"Toggle show closest data on hover\")},attr:\"hovermode\",val:null,toggle:!0,icon:o.tooltip_basic,gravity:\"ne\",click:y},c.hoverClosestGl2d={name:\"hoverClosestGl2d\",_cat:\"hoverclosest\",title:function(t){return u(t,\"Toggle show closest data on hover\")},attr:\"hovermode\",val:null,toggle:!0,icon:o.tooltip_basic,gravity:\"ne\",click:y},c.hoverClosestPie={name:\"hoverClosestPie\",_cat:\"hoverclosest\",title:function(t){return u(t,\"Toggle show closest data on hover\")},attr:\"hovermode\",val:\"closest\",icon:o.tooltip_basic,gravity:\"ne\",click:y},c.resetViewSankey={name:\"resetSankeyGroup\",title:function(t){return u(t,\"Reset view\")},icon:o.home,click:function(t){for(var e={\"node.groups\":[],\"node.x\":[],\"node.y\":[]},r=0;r<t._fullData.length;r++){var i=t._fullData[r]._viewInitial;e[\"node.groups\"].push(i.node.groups.slice()),e[\"node.x\"].push(i.node.x.slice()),e[\"node.y\"].push(i.node.y.slice())}n.call(\"restyle\",t,e)}},c.toggleHover={name:\"toggleHover\",title:function(t){return u(t,\"Toggle show closest data on hover\")},attr:\"hovermode\",val:null,toggle:!0,icon:o.tooltip_basic,gravity:\"ne\",click:function(t,e){var r=d(t,e);r.hovermode=g(t),n.call(\"_guiRelayout\",t,r)}},c.resetViews={name:\"resetViews\",title:function(t){return u(t,\"Reset views\")},icon:o.home,click:function(t,e){var r=e.currentTarget;r.setAttribute(\"data-attr\",\"zoom\"),r.setAttribute(\"data-val\",\"reset\"),f(t,e),r.setAttribute(\"data-attr\",\"resetLastSave\"),p(t,e),x(t,\"geo\"),x(t,\"mapbox\")}},c.toggleSpikelines={name:\"toggleSpikelines\",title:function(t){return u(t,\"Toggle Spike Lines\")},icon:o.spikeline,attr:\"_cartesianSpikesEnabled\",val:\"on\",click:function(t){var e=t._fullLayout,r=e._cartesianSpikesEnabled;e._cartesianSpikesEnabled=\"on\"===r?\"off\":\"on\",n.call(\"_guiRelayout\",t,function(t){for(var e=\"on\"===t._fullLayout._cartesianSpikesEnabled,r=a.list(t,null,!0),n={},i=0;i<r.length;i++){var o=r[i];n[o._name+\".showspikes\"]=!!e||o._showSpikeInitial}return n}(t))}},c.resetViewMapbox={name:\"resetViewMapbox\",_cat:\"resetView\",title:function(t){return u(t,\"Reset view\")},attr:\"reset\",icon:o.home,click:function(t){x(t,\"mapbox\")}},c.zoomInMapbox={name:\"zoomInMapbox\",_cat:\"zoomin\",title:function(t){return u(t,\"Zoom in\")},attr:\"zoom\",val:\"in\",icon:o.zoom_plus,click:m},c.zoomOutMapbox={name:\"zoomOutMapbox\",_cat:\"zoomout\",title:function(t){return u(t,\"Zoom out\")},attr:\"zoom\",val:\"out\",icon:o.zoom_minus,click:m}},76052:function(t,e,r){\"use strict\";var n=r(44248),i=Object.keys(n),a=[\"drawline\",\"drawopenpath\",\"drawclosedpath\",\"drawcircle\",\"drawrect\",\"eraseshape\"],o=[\"v1hovermode\",\"hoverclosest\",\"hovercompare\",\"togglehover\",\"togglespikelines\"].concat(a),s=[];i.forEach((function(t){!function(t){if(-1===o.indexOf(t._cat||t.name)){var e=t.name,r=(t._cat||t.name).toLowerCase();-1===s.indexOf(e)&&s.push(e),-1===s.indexOf(r)&&s.push(r)}}(n[t])})),s.sort(),t.exports={DRAW_MODES:a,backButtons:o,foreButtons:s}},90824:function(t,e,r){\"use strict\";var n=r(3400),i=r(76308),a=r(31780),o=r(66540);t.exports=function(t,e){var r=t.modebar||{},s=a.newContainer(e,\"modebar\");function l(t,e){return n.coerce(r,s,o,t,e)}l(\"orientation\"),l(\"bgcolor\",i.addOpacity(e.paper_bgcolor,.5));var u=i.contrast(i.rgb(e.modebar.bgcolor));l(\"color\",i.addOpacity(u,.3)),l(\"activecolor\",i.addOpacity(u,.7)),l(\"uirevision\",e.uirevision),l(\"add\"),l(\"remove\")}},45460:function(t,e,r){\"use strict\";t.exports={moduleType:\"component\",name:\"modebar\",layoutAttributes:r(66540),supplyLayoutDefaults:r(90824),manage:r(18816)}},18816:function(t,e,r){\"use strict\";var n=r(79811),i=r(43028),a=r(24040),o=r(10624).isUnifiedHover,s=r(66400),l=r(44248),u=r(76052).DRAW_MODES,c=r(3400).extendDeep;t.exports=function(t){var e=t._fullLayout,r=t._context,f=e._modeBar;if(r.displayModeBar||r.watermark){if(!Array.isArray(r.modeBarButtonsToRemove))throw new Error([\"*modeBarButtonsToRemove* configuration options\",\"must be an array.\"].join(\" \"));if(!Array.isArray(r.modeBarButtonsToAdd))throw new Error([\"*modeBarButtonsToAdd* configuration options\",\"must be an array.\"].join(\" \"));var h,p=r.modeBarButtons;h=Array.isArray(p)&&p.length?function(t){for(var e=c([],t),r=0;r<e.length;r++)for(var n=e[r],i=0;i<n.length;i++){var a=n[i];if(\"string\"==typeof a){if(void 0===l[a])throw new Error([\"*modeBarButtons* configuration options\",\"invalid button name\"].join(\" \"));e[r][i]=l[a]}}return e}(p):!r.displayModeBar&&r.watermark?[]:function(t){var e=t._fullLayout,r=t._fullData,s=t._context;function c(t,e){if(\"string\"==typeof e){if(e.toLowerCase()===t.toLowerCase())return!0}else{var r=e.name,n=e._cat||e.name;if(r===t||n===t.toLowerCase())return!0}return!1}var f=e.modebar.add;\"string\"==typeof f&&(f=[f]);var h=e.modebar.remove;\"string\"==typeof h&&(h=[h]);var p=s.modeBarButtonsToAdd.concat(f.filter((function(t){for(var e=0;e<s.modeBarButtonsToRemove.length;e++)if(c(t,s.modeBarButtonsToRemove[e]))return!1;return!0}))),d=s.modeBarButtonsToRemove.concat(h.filter((function(t){for(var e=0;e<s.modeBarButtonsToAdd.length;e++)if(c(t,s.modeBarButtonsToAdd[e]))return!1;return!0}))),v=e._has(\"cartesian\"),g=e._has(\"gl3d\"),y=e._has(\"geo\"),m=e._has(\"pie\"),x=e._has(\"funnelarea\"),b=e._has(\"gl2d\"),_=e._has(\"ternary\"),w=e._has(\"mapbox\"),T=e._has(\"polar\"),k=e._has(\"smith\"),A=e._has(\"sankey\"),M=function(t){for(var e=n.list({_fullLayout:t},null,!0),r=0;r<e.length;r++)if(!e[r].fixedrange)return!1;return!0}(e),S=o(e.hovermode),E=[];function L(t){if(t.length){for(var e=[],r=0;r<t.length;r++){for(var n=t[r],i=l[n],a=i.name.toLowerCase(),o=(i._cat||i.name).toLowerCase(),s=!1,u=0;u<d.length;u++){var c=d[u].toLowerCase();if(c===a||c===o){s=!0;break}}s||e.push(l[n])}E.push(e)}}var C=[\"toImage\"];s.showEditInChartStudio?C.push(\"editInChartStudio\"):s.showSendToCloud&&C.push(\"sendDataToCloud\"),L(C);var P=[],O=[],I=[],D=[];(v||b||m||x||_)+y+g+w+T+k>1?(O=[\"toggleHover\"],I=[\"resetViews\"]):y?(P=[\"zoomInGeo\",\"zoomOutGeo\"],O=[\"hoverClosestGeo\"],I=[\"resetGeo\"]):g?(O=[\"hoverClosest3d\"],I=[\"resetCameraDefault3d\",\"resetCameraLastSave3d\"]):w?(P=[\"zoomInMapbox\",\"zoomOutMapbox\"],O=[\"toggleHover\"],I=[\"resetViewMapbox\"]):b?O=[\"hoverClosestGl2d\"]:m?O=[\"hoverClosestPie\"]:A?(O=[\"hoverClosestCartesian\",\"hoverCompareCartesian\"],I=[\"resetViewSankey\"]):O=[\"toggleHover\"],v&&(O=[\"toggleSpikelines\",\"hoverClosestCartesian\",\"hoverCompareCartesian\"]),(function(t){for(var e=0;e<t.length;e++)if(!a.traceIs(t[e],\"noHover\"))return!1;return!0}(r)||S)&&(O=[]),!v&&!b||M||(P=[\"zoomIn2d\",\"zoomOut2d\",\"autoScale2d\"],\"resetViews\"!==I[0]&&(I=[\"resetScale2d\"])),g?D=[\"zoom3d\",\"pan3d\",\"orbitRotation\",\"tableRotation\"]:(v||b)&&!M||_?D=[\"zoom2d\",\"pan2d\"]:w||y?D=[\"pan2d\"]:T&&(D=[\"zoom2d\"]),function(t){for(var e=!1,r=0;r<t.length&&!e;r++){var n=t[r];n._module&&n._module.selectPoints&&(a.traceIs(n,\"scatter-like\")?(i.hasMarkers(n)||i.hasText(n))&&(e=!0):a.traceIs(n,\"box-violin\")&&\"all\"!==n.boxpoints&&\"all\"!==n.points||(e=!0))}return e}(r)&&D.push(\"select2d\",\"lasso2d\");var z=[],R=function(t){-1===z.indexOf(t)&&-1!==O.indexOf(t)&&z.push(t)};if(Array.isArray(p)){for(var F=[],B=0;B<p.length;B++){var N=p[B];\"string\"==typeof N?(N=N.toLowerCase(),-1!==u.indexOf(N)?(e._has(\"mapbox\")||e._has(\"cartesian\"))&&D.push(N):\"togglespikelines\"===N?R(\"toggleSpikelines\"):\"togglehover\"===N?R(\"toggleHover\"):\"hovercompare\"===N?R(\"hoverCompareCartesian\"):\"hoverclosest\"===N?(R(\"hoverClosestCartesian\"),R(\"hoverClosestGeo\"),R(\"hoverClosest3d\"),R(\"hoverClosestGl2d\"),R(\"hoverClosestPie\")):\"v1hovermode\"===N&&(R(\"toggleHover\"),R(\"hoverClosestCartesian\"),R(\"hoverCompareCartesian\"),R(\"hoverClosestGeo\"),R(\"hoverClosest3d\"),R(\"hoverClosestGl2d\"),R(\"hoverClosestPie\"))):F.push(N)}p=F}return L(D),L(P.concat(I)),L(z),function(t,e){if(e.length)if(Array.isArray(e[0]))for(var r=0;r<e.length;r++)t.push(e[r]);else t.push(e);return t}(E,p)}(t),f?f.update(t,h):e._modeBar=s(t,h)}else f&&(f.destroy(),delete e._modeBar)}},66400:function(t,e,r){\"use strict\";var n=r(33428),i=r(38248),a=r(3400),o=r(9224),s=r(25788).version,l=new DOMParser;function u(t){this.container=t.container,this.element=document.createElement(\"div\"),this.update(t.graphInfo,t.buttons),this.container.appendChild(this.element)}var c=u.prototype;c.update=function(t,e){this.graphInfo=t;var r=this.graphInfo._context,n=this.graphInfo._fullLayout,i=\"modebar-\"+n._uid;this.element.setAttribute(\"id\",i),this._uid=i,this.element.className=\"modebar\",\"hover\"===r.displayModeBar&&(this.element.className+=\" modebar--hover ease-bg\"),\"v\"===n.modebar.orientation&&(this.element.className+=\" vertical\",e=e.reverse());var o=n.modebar,s=\"hover\"===r.displayModeBar?\".js-plotly-plot .plotly:hover \":\"\";a.deleteRelatedStyleRule(i),a.addRelatedStyleRule(i,s+\"#\"+i+\" .modebar-group\",\"background-color: \"+o.bgcolor),a.addRelatedStyleRule(i,\"#\"+i+\" .modebar-btn .icon path\",\"fill: \"+o.color),a.addRelatedStyleRule(i,\"#\"+i+\" .modebar-btn:hover .icon path\",\"fill: \"+o.activecolor),a.addRelatedStyleRule(i,\"#\"+i+\" .modebar-btn.active .icon path\",\"fill: \"+o.activecolor);var l=!this.hasButtons(e),u=this.hasLogo!==r.displaylogo,c=this.locale!==r.locale;if(this.locale=r.locale,(l||u||c)&&(this.removeAllButtons(),this.updateButtons(e),r.watermark||r.displaylogo)){var f=this.getLogo();r.watermark&&(f.className=f.className+\" watermark\"),\"v\"===n.modebar.orientation?this.element.insertBefore(f,this.element.childNodes[0]):this.element.appendChild(f),this.hasLogo=!0}this.updateActiveButton()},c.updateButtons=function(t){var e=this;this.buttons=t,this.buttonElements=[],this.buttonsNames=[],this.buttons.forEach((function(t){var r=e.createGroup();t.forEach((function(t){var n=t.name;if(!n)throw new Error(\"must provide button 'name' in button config\");if(-1!==e.buttonsNames.indexOf(n))throw new Error(\"button name '\"+n+\"' is taken\");e.buttonsNames.push(n);var i=e.createButton(t);e.buttonElements.push(i),r.appendChild(i)})),e.element.appendChild(r)}))},c.createGroup=function(){var t=document.createElement(\"div\");return t.className=\"modebar-group\",t},c.createButton=function(t){var e=this,r=document.createElement(\"a\");r.setAttribute(\"rel\",\"tooltip\"),r.className=\"modebar-btn\";var i=t.title;void 0===i?i=t.name:\"function\"==typeof i&&(i=i(this.graphInfo)),(i||0===i)&&r.setAttribute(\"data-title\",i),void 0!==t.attr&&r.setAttribute(\"data-attr\",t.attr);var a=t.val;if(void 0!==a&&(\"function\"==typeof a&&(a=a(this.graphInfo)),r.setAttribute(\"data-val\",a)),\"function\"!=typeof t.click)throw new Error(\"must provide button 'click' function in button 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n=r(25376),i=r(22548),a=(0,r(31780).templatedArray)(\"button\",{visible:{valType:\"boolean\",dflt:!0,editType:\"plot\"},step:{valType:\"enumerated\",values:[\"month\",\"year\",\"day\",\"hour\",\"minute\",\"second\",\"all\"],dflt:\"month\",editType:\"plot\"},stepmode:{valType:\"enumerated\",values:[\"backward\",\"todate\"],dflt:\"backward\",editType:\"plot\"},count:{valType:\"number\",min:0,dflt:1,editType:\"plot\"},label:{valType:\"string\",editType:\"plot\"},editType:\"plot\"});t.exports={visible:{valType:\"boolean\",editType:\"plot\"},buttons:a,x:{valType:\"number\",min:-2,max:3,editType:\"plot\"},xanchor:{valType:\"enumerated\",values:[\"auto\",\"left\",\"center\",\"right\"],dflt:\"left\",editType:\"plot\"},y:{valType:\"number\",min:-2,max:3,editType:\"plot\"},yanchor:{valType:\"enumerated\",values:[\"auto\",\"top\",\"middle\",\"bottom\"],dflt:\"bottom\",editType:\"plot\"},font:n({editType:\"plot\"}),bgcolor:{valType:\"color\",dflt:i.lightLine,editType:\"plot\"},activecolor:{valType:\"color\",editType:\"plot\"},bordercolor:{valType:\"color\",dflt:i.defaultLine,editType:\"plot\"},borderwidth:{valType:\"number\",min:0,dflt:0,editType:\"plot\"},editType:\"plot\"}},85984:function(t){\"use 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i,a;l.ensureSingle(t,\"text\",\"selector-text\",(function(t){t.attr(\"text-anchor\",\"middle\")})).call(s.font,e.font).text((i=r,a=n._fullLayout._meta,i.label?a?l.templateString(i.label,a):i.label:\"all\"===i.step?\"all\":i.count+i.step.charAt(0))).call((function(t){c.convertToTspans(t,n)}))}t.exports=function(t){var e=t._fullLayout._infolayer.selectAll(\".rangeselector\").data(function(t){for(var e=f.list(t,\"x\",!0),r=[],n=0;n<e.length;n++){var i=e[n];i.rangeselector&&i.rangeselector.visible&&r.push(i)}return r}(t),m);e.enter().append(\"g\").classed(\"rangeselector\",!0),e.exit().remove(),e.style({cursor:\"pointer\",\"pointer-events\":\"all\"}),e.each((function(e){var r=n.select(this),o=e,f=o.rangeselector,h=r.selectAll(\"g.button\").data(l.filterVisible(f.buttons));h.enter().append(\"g\").classed(\"button\",!0),h.exit().remove(),h.each((function(e){var r=n.select(this),a=y(o,e);e._isActive=function(t,e,r){if(\"all\"===e.step)return!0===t.autorange;var n=Object.keys(r);return 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w=\"top\";l.isBottomAnchor(r)&&(b-=h,w=\"bottom\"),l.isMiddleAnchor(r)&&(b-=h/2,w=\"middle\"),f=Math.ceil(f),h=Math.ceil(h),x=Math.round(x),b=Math.round(b),a.autoMargin(t,i+\"-range-selector\",{x:r.x,y:r.y,l:f*d[_],r:f*v[_],b:h*v[w],t:h*d[w]}),o.attr(\"transform\",u(x,b))}(t,h,f,o._name,r)}))}},48040:function(t,e,r){\"use strict\";var n=r(73220),i=r(3400).titleCase;t.exports=function(t,e){var r=t._name,a={};if(\"all\"===e.step)a[r+\".autorange\"]=!0;else{var o=function(t,e){var r,a=t.range,o=new Date(t.r2l(a[1])),s=e.step,l=n[\"utc\"+i(s)],u=e.count;switch(e.stepmode){case\"backward\":r=t.l2r(+l.offset(o,-u));break;case\"todate\":var c=l.offset(o,-u);r=t.l2r(+l.ceil(c))}return[r,a[1]]}(t,e);a[r+\".range[0]\"]=o[0],a[r+\".range[1]\"]=o[1]}return a}},41152:function(t,e,r){\"use strict\";t.exports={moduleType:\"component\",name:\"rangeselector\",schema:{subplots:{xaxis:{rangeselector:r(26680)}}},layoutAttributes:r(26680),handleDefaults:r(22148),draw:r(50216)}},11200:function(t,e,r){\"use 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n=r(3400),i=r(31780),a=r(79811),o=r(11200),s=r(10936);t.exports=function(t,e,r){var l=t[r],u=e[r];if(l.rangeslider||e._requestRangeslider[u._id]){n.isPlainObject(l.rangeslider)||(l.rangeslider={});var c,f,h=l.rangeslider,p=i.newContainer(u,\"rangeslider\");if(_(\"visible\")){_(\"bgcolor\",e.plot_bgcolor),_(\"bordercolor\"),_(\"borderwidth\"),_(\"thickness\"),_(\"autorange\",!u.isValidRange(h.range)),_(\"range\");var d=e._subplots;if(d)for(var v=d.cartesian.filter((function(t){return t.substr(0,t.indexOf(\"y\"))===a.name2id(r)})).map((function(t){return t.substr(t.indexOf(\"y\"),t.length)})),g=n.simpleMap(v,a.id2name),y=0;y<g.length;y++){var m=g[y];c=h[m]||{},f=i.newContainer(p,m,\"yaxis\");var x,b=e[m];c.range&&b.isValidRange(c.range)&&(x=\"fixed\"),\"match\"!==w(\"rangemode\",x)&&w(\"range\",b.range.slice())}p._input=h}}function _(t,e){return n.coerce(h,p,o,t,e)}function w(t,e){return n.coerce(c,f,s,t,e)}}},20060:function(t,e,r){\"use strict\";var n=r(33428),i=r(24040),a=r(7316),o=r(3400),s=o.strTranslate,l=r(43616),u=r(76308),c=r(81668),f=r(57952),h=r(79811),p=r(86476),d=r(93972),v=r(74636);function g(t){return\"number\"==typeof t.clientX?t.clientX:t.touches&&t.touches.length>0?t.touches[0].clientX:0}function y(t,e,r,n){var i=o.ensureSingle(t,\"rect\",v.bgClassName,(function(t){t.attr({x:0,y:0,\"shape-rendering\":\"crispEdges\"})})),a=n.borderwidth%2==0?n.borderwidth:n.borderwidth-1,c=-n._offsetShift,f=l.crispRound(e,n.borderwidth);i.attr({width:n._width+a,height:n._height+a,transform:s(c,c),\"stroke-width\":f}).call(u.stroke,n.bordercolor).call(u.fill,n.bgcolor)}function m(t,e,r,n){var i=e._fullLayout;o.ensureSingleById(i._topdefs,\"clipPath\",n._clipId,(function(t){t.append(\"rect\").attr({x:0,y:0})})).select(\"rect\").attr({width:n._width,height:n._height})}function x(t,e,r,i){var 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T,k=o.simpleMap(l.range,r.r2l),A=o.simpleMap(r.range,r.r2l);T=A[0]<A[1]?[Math.min(k[0],A[0]),Math.max(k[1],A[1])]:[Math.max(k[0],A[0]),Math.min(k[1],A[1])],l.range=l._input.range=o.simpleMap(T,r.l2r)}r.cleanRange(\"rangeslider.range\");var M=e._size,S=r.domain;l._width=M.w*(S[1]-S[0]);var E=Math.round(M.l+M.w*S[0]),L=Math.round(M.t+M.h*(1-r._counterDomainMin)+(\"bottom\"===r.side?r._depth:0)+l._offsetShift+v.extraPad);a.attr(\"transform\",s(E,L)),l._rl=o.simpleMap(l.range,r.r2l);var C=l._rl[0],P=l._rl[1],O=P-C;if(l.p2d=function(t){return t/l._width*O+C},l.d2p=function(t){return(t-C)/O*l._width},r.rangebreaks){var I=r.locateBreaks(C,P);if(I.length){var D,z,R=0;for(D=0;D<I.length;D++)R+=(z=I[D]).max-z.min;var F=l._width/(P-C-R),B=[-F*C];for(D=0;D<I.length;D++)z=I[D],B.push(B[B.length-1]-F*(z.max-z.min));for(l.d2p=function(t){for(var e=B[0],r=0;r<I.length;r++){var n=I[r];if(t>=n.max)e=B[r+1];else if(t<n.min)break}return 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r=t._fullLayout,n=e[s],l=e._id.charAt(0),u=0,c=0;return\"bottom\"===e.side&&(u=e._depth,e.title.text!==r._dfltTitle[l]&&(c=1.5*e.title.font.size+10+n._offsetShift,c+=(e.title.text.match(i.BR_TAG_ALL)||[]).length*e.title.font.size*o)),{x:0,y:e._counterDomainMin,l:0,r:0,t:0,b:n._height+u+Math.max(r.margin.b,c),pad:a.extraPad+2*n._offsetShift}}},49692:function(t,e,r){\"use strict\";var n=r(3400),i=r(11200),a=r(10936),o=r(97944);t.exports={moduleType:\"component\",name:\"rangeslider\",schema:{subplots:{xaxis:{rangeslider:n.extendFlat({},i,{yaxis:a})}}},layoutAttributes:r(11200),handleDefaults:r(94040),calcAutorange:r(26652),draw:r(20060),isVisible:o.isVisible,makeData:o.makeData,autoMarginOpts:o.autoMarginOpts}},10936:function(t){\"use 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0===i.path&&(void 0!==i.x0&&void 0!==i.x1&&void 0!==i.y0&&void 0!==i.y1||(e.selections[n]=null))}}},23640:function(t,e,r){\"use strict\";var n=r(9856).readPaths,i=r(55496),a=r(1936).clearOutlineControllers,o=r(76308),s=r(43616),l=r(31780).arrayEditor,u=r(65152),c=u.getPathString;function f(t){var e=t._fullLayout;for(var r in a(t),e._selectionLayer.selectAll(\"path\").remove(),e._plots){var n=e._plots[r].selectionLayer;n&&n.selectAll(\"path\").remove()}for(var i=0;i<e.selections.length;i++)p(t,i)}function h(t){return t._context.editSelection}function p(t,e){t._fullLayout._paperdiv.selectAll('.selectionlayer [data-index=\"'+e+'\"]').remove();var r=u.makeSelectionsOptionsAndPlotinfo(t,e),a=r.options,p=r.plotinfo;a._input&&function(r){var u=c(t,a),g={\"data-index\":e,\"fill-rule\":\"evenodd\",d:u},y=a.opacity,m=\"rgba(0,0,0,0)\",x=a.line.color||o.contrast(t._fullLayout.plot_bgcolor),b=a.line.width,_=a.line.dash;b||(b=5,_=\"solid\");var w=h(t)&&t._fullLayout._activeSelectionIndex===e;w&&(m=t._fullLayout.activeselection.fillcolor,y=t._fullLayout.activeselection.opacity);for(var T=[],k=1;k>=0;k--){var A=r.append(\"path\").attr(g).style(\"opacity\",k?.1:y).call(o.stroke,x).call(o.fill,m).call(s.dashLine,k?\"solid\":_,k?4+b:b);if(d(A,t,a),w){var M=l(t.layout,\"selections\",a);A.style({cursor:\"move\"});var S={element:A.node(),plotinfo:p,gd:t,editHelpers:M,isActiveSelection:!0},E=n(u,t);i(E,A,S)}else A.style(\"pointer-events\",k?\"all\":\"none\");T[k]=A}var L=T[0];T[1].node().addEventListener(\"click\",(function(){return function(t,e){if(h(t)){var r=+e.node().getAttribute(\"data-index\");if(r>=0){if(r===t._fullLayout._activeSelectionIndex)return void v(t);t._fullLayout._activeSelectionIndex=r,t._fullLayout._deactivateSelection=v,f(t)}}}(t,L)}))}(t._fullLayout._selectionLayer)}function d(t,e,r){var n=r.xref+r.yref;s.setClipUrl(t,\"clip\"+e._fullLayout._uid+n,e)}function v(t){h(t)&&t._fullLayout._activeSelectionIndex>=0&&(a(t),delete t._fullLayout._activeSelectionIndex,f(t))}t.exports={draw:f,drawOne:p,activateLastSelection:function(t){if(h(t)){var e=t._fullLayout.selections.length-1;t._fullLayout._activeSelectionIndex=e,t._fullLayout._deactivateSelection=v,f(t)}}}},34200:function(t,e,r){\"use strict\";var n=r(98192).u,i=r(92880).extendFlat;t.exports={newselection:{mode:{valType:\"enumerated\",values:[\"immediate\",\"gradual\"],dflt:\"immediate\",editType:\"none\"},line:{color:{valType:\"color\",editType:\"none\"},width:{valType:\"number\",min:1,dflt:1,editType:\"none\"},dash:i({},n,{dflt:\"dot\",editType:\"none\"}),editType:\"none\"},editType:\"none\"},activeselection:{fillcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\",editType:\"none\"},opacity:{valType:\"number\",min:0,max:1,dflt:.5,editType:\"none\"},editType:\"none\"}}},81004:function(t){\"use 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m,x=o(a,u,f,d),b={xref:h._id,yref:p._id,opacity:c.opacity,line:{color:c.line.color,width:c.line.width,dash:c.line.dash}};1===x.length&&(m=x[0]),m&&5===m.length&&\"select\"===v?(b.type=\"rect\",b.x0=m[0][1],b.y0=m[0][2],b.x1=m[2][1],b.y1=m[2][2]):(b.type=\"path\",h&&p&&l(x,h,p),b.path=s(x),m=null),i(u);for(var _=e.editHelpers,w=(_||{}).modifyItem,T=[],k=0;k<g.length;k++){var A=u._fullLayout.selections[k];if(A){if(T[k]=A._input,void 0!==d&&k===u._fullLayout._activeSelectionIndex){var M=b;switch(A.type){case\"rect\":w(\"x0\",M.x0),w(\"x1\",M.x1),w(\"y0\",M.y0),w(\"y1\",M.y1);break;case\"path\":w(\"path\",M.path)}}}else T[k]=A}return void 0===d?(T.push(b),T):_?_.getUpdateObj():{}}}}},5840:function(t,e,r){\"use strict\";var n=r(3400).strTranslate;function i(t,e){switch(t.type){case\"log\":return t.p2d(e);case\"date\":return t.p2r(e,0,t.calendar);default:return t.p2r(e)}}t.exports={p2r:i,r2p:function(t,e){switch(t.type){case\"log\":return t.d2p(e);case\"date\":return t.r2p(e,0,t.calendar);default:return t.r2p(e)}},axValue:function(t){var e=\"y\"===t._id.charAt(0)?1:0;return function(r){return i(t,r[e])}},getTransform:function(t){return n(t.xaxis._offset,t.yaxis._offset)}}},22676:function(t,e,r){\"use strict\";var n=r(23640),i=r(43156);t.exports={moduleType:\"component\",name:\"selections\",layoutAttributes:r(93956),supplyLayoutDefaults:r(74224),supplyDrawNewSelectionDefaults:r(81004),includeBasePlot:r(36632)(\"selections\"),draw:n.draw,drawOne:n.drawOne,reselect:i.reselect,prepSelect:i.prepSelect,clearOutline:i.clearOutline,clearSelectionsCache:i.clearSelectionsCache,selectOnClick:i.selectOnClick}},43156:function(t,e,r){\"use strict\";var n=r(14756),i=r(61456),a=r(24040),o=r(43616).dashStyle,s=r(76308),l=r(93024),u=r(10624).makeEventData,c=r(72760),f=c.freeMode,h=c.rectMode,p=c.drawMode,d=c.openMode,v=c.selectMode,g=r(65152),y=r(85448),m=r(55496),x=r(1936).clearOutline,b=r(9856),_=b.handleEllipse,w=b.readPaths,T=r(93940).newShapes,k=r(5968),A=r(23640).activateLastSelection,M=r(3400),S=M.sorterAsc,E=r(92065),L=r(91200),C=r(79811).getFromId,P=r(73696),O=r(39172).redrawReglTraces,I=r(83280),D=I.MINSELECT,z=E.filter,R=E.tester,F=r(5840),B=F.p2r,N=F.axValue,j=F.getTransform;function U(t){return void 0!==t.subplot}function V(t,e,r,n,i,a,o){var s,l,u,c,f,h,p,v,g,y=e._hoverdata,x=e._fullLayout.clickmode.indexOf(\"event\")>-1,b=[];if(function(t){return t&&Array.isArray(t)&&!0!==t[0].hoverOnBox}(y)){W(t,e,a);var _=function(t,e){var r,n,i=t[0],a=-1,o=[];for(n=0;n<e.length;n++)if(r=e[n],i.fullData._expandedIndex===r.cd[0].trace._expandedIndex){if(!0===i.hoverOnBox)break;void 0!==i.pointNumber?a=i.pointNumber:void 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u,c,f=o.selectAll(\".select-outline-\"+n.id);f&&i._fullLayout._outlining&&(s&&(u=T(f,t)),u&&a.call(\"_guiRelayout\",i,{shapes:u}),l&&!U(t)&&(c=k(f,t)),c&&(i._fullLayout._noEmitSelectedAtStart=!0,a.call(\"_guiRelayout\",i,{selections:c}).then((function(){e&&A(i)}))),i._fullLayout._outlining=!1)}n.selection={},n.selection.selectionDefs=t.selectionDefs=[],n.selection.mergedPolygons=t.mergedPolygons=[]}function X(t){return t._id}function Z(t,e,r,n){if(!t.calcdata)return[];var i,a,o,s=[],l=e.map(X),u=r.map(X);for(o=0;o<t.calcdata.length;o++)if(!0===(a=(i=t.calcdata[o])[0].trace).visible&&a._module&&a._module.selectPoints)if(!U({subplot:n})||a.subplot!==n&&a.geo!==n)if(\"splom\"===a.type){if(a._xaxes[l[0]]&&a._yaxes[u[0]]){var c=K(a._module,i,e[0],r[0]);c.scene=t._fullLayout._splomScenes[a.uid],s.push(c)}}else if(\"sankey\"===a.type){var 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c=l[u],f=c.data,h=c.fullData,p=c.pointIndex,d=c.pointIndices;d?([].push.apply(f.selectedpoints,d),i._fullInput!==i&&[].push.apply(h.selectedpoints,d)):(f.selectedpoints.push(p),i._fullInput!==i&&h.selectedpoints.push(p))}}else for(n=0;n<e.length;n++)delete(i=e[n].cd[0].trace).selectedpoints,delete i._input.selectedpoints,i._fullInput!==i&&delete i._fullInput.selectedpoints;!function(t,e){for(var r=!1,n=0;n<e.length;n++){var i=e[n],o=i.cd;a.traceIs(o[0].trace,\"regl\")&&(r=!0);var s=i._module,l=s.styleOnSelect||s.style;l&&(l(t,o,o[0].node3),o[0].nodeRangePlot3&&l(t,o,o[0].nodeRangePlot3))}r&&(P(t),O(t))}(t,e)}function Q(t,e,r){for(var i=(r?n.difference:n.union)({regions:t},{regions:[e]}).regions.reverse(),a=0;a<i.length;a++){var o=i[a];o.subtract=st(o,i.slice(0,a))}return i}function tt(t,e){if(Array.isArray(t))for(var r=e.cd,n=e.cd[0].trace,i=0;i<t.length;i++)t[i]=u(t[i],n,r);return t}function et(t,e){for(var r=[],n=0;n<t.length;n++){r[n]=[];for(var 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n=e[r][0].trace,i=t._fullLayout._splomScenes;if(i){var a=i[n.uid];a&&(a.selectBatch=[])}}}(t);for(var O={},I=0;I<P.length;I++){var D=P[I],z=D.indexOf(\"y\"),R=D.slice(0,z),F=D.slice(z),B=o&&s?r:void 0;if(B=at(f,R,F,B)){var N=n;if(!l){var j=C(t,R,\"x\"),U=C(t,F,\"y\");N=Z(t,[j],[U],D);for(var V=0;V<N.length;V++){var q=N[V],H=q.cd[0],G=H.trace;if(\"scattergl\"===q._module.name&&!H.t.xpx){var W=G.x,Y=G.y,X=G._length;H.t.xpx=[],H.t.ypx=[];for(var K=0;K<X;K++)H.t.xpx[K]=j.c2p(W[K]),H.t.ypx[K]=U.c2p(Y[K])}\"splom\"===q._module.name&&(O[G.uid]||(O[G.uid]=!0))}}var J=rt(B,N);u=u.concat(J),c=c.concat(N)}}var Q={points:u};$(t,c,Q);var tt=h.clickmode.indexOf(\"event\")>-1&&e;if(!a&&e){var et=ot(t,!0);if(et.length){var nt=et[0].xref,pt=et[0].yref;if(nt&&pt){var dt=ut(et);ct([C(t,nt,\"x\"),C(t,pt,\"y\")])(Q,dt)}}t._fullLayout._noEmitSelectedAtStart?t._fullLayout._noEmitSelectedAtStart=!1:tt&&ft(t,Q),h._reselect=!1}if(!a&&h._deselect){var vt=h._deselect;(function(t,e,r){for(var n=0;n<r.length;n++){var i=r[n];if(i.xaxis&&i.xaxis._id===t&&i.yaxis&&i.yaxis._id===e)return!0}return!1})(o=vt.xref,s=vt.yref,c)||it(t,o,s,n),tt&&(Q.points.length?ft(t,Q):ht(t)),h._deselect=!1}return{eventData:Q,selectionTesters:r}}function it(t,e,r,n){n=Z(t,[C(t,e,\"x\")],[C(t,r,\"y\")],e+r);for(var i=0;i<n.length;i++){var a=n[i];a._module.selectPoints(a,!1)}$(t,n)}function at(t,e,r,n){for(var i,a=0;a<t.length;a++){var o=t[a];e===o.xref&&r===o.yref&&(i?n=G(i=Q(i,o,!!o.subtract)):(i=[o],n=R(o)))}return n}function ot(t,e){for(var r=[],n=t._fullLayout,i=n.selections,a=i.length,o=0;o<a;o++)if(!e||o===n._activeSelectionIndex){var s=i[o];if(s){var l,u,c,f,h,p=s.xref,d=s.yref,v=C(t,p,\"x\"),m=C(t,d,\"y\");if(\"rect\"===s.type){h=[];var x=lt(v,s.x0),b=lt(v,s.x1),_=lt(m,s.y0),w=lt(m,s.y1);h=[[x,_],[x,w],[b,w],[b,_]],l=Math.min(x,b),u=Math.max(x,b),c=Math.min(_,w),f=Math.max(_,w),h.xmin=l,h.xmax=u,h.ymin=c,h.ymax=f,h.xref=p,h.yref=d,h.subtract=!1,h.isRect=!0,r.push(h)}else if(\"path\"===s.type)for(var T=s.path.split(\"Z\"),k=[],A=0;A<T.length;A++){var M=T[A];if(M){M+=\"Z\";var S=g.extractPathCoords(M,y.paramIsX,\"raw\"),E=g.extractPathCoords(M,y.paramIsY,\"raw\");l=1/0,u=-1/0,c=1/0,f=-1/0,h=[];for(var L=0;L<S.length;L++){var P=lt(v,S[L]),O=lt(m,E[L]);h.push([P,O]),l=Math.min(P,l),u=Math.max(P,u),c=Math.min(O,c),f=Math.max(O,f)}h.xmin=l,h.xmax=u,h.ymin=c,h.ymax=f,h.xref=p,h.yref=d,h.subtract=st(h,k),k.push(h),r.push(h)}}}}return r}function st(t,e){for(var r=!1,n=0;n<e.length;n++)for(var a=e[n],o=0;o<t.length;o++)if(i(t[o],a)){r=!r;break}return r}function lt(t,e){return\"date\"===t.type&&(e=e.replace(\"_\",\" \")),\"log\"===t.type?t.c2p(e):t.r2p(e,null,t.calendar)}function ut(t){for(var e=t.length,r=[],n=0;n<e;n++){var i=t[n];r=(r=r.concat(i)).concat([i[0]])}return(a=r).isRect=5===a.length&&a[0][0]===a[4][0]&&a[0][1]===a[4][1]&&a[0][0]===a[1][0]&&a[2][0]===a[3][0]&&a[0][1]===a[3][1]&&a[1][1]===a[2][1]||a[0][1]===a[1][1]&&a[2][1]===a[3][1]&&a[0][0]===a[3][0]&&a[1][0]===a[2][0],a.isRect&&(a.xmin=Math.min(a[0][0],a[2][0]),a.xmax=Math.max(a[0][0],a[2][0]),a.ymin=Math.min(a[0][1],a[2][1]),a.ymax=Math.max(a[0][1],a[2][1])),a;var a}function ct(t){return function(e,r){for(var n,i,a=0;a<t.length;a++){var o=t[a],s=o._id,l=s.charAt(0);if(r.isRect){n||(n={});var u=r[l+\"min\"],c=r[l+\"max\"];void 0!==u&&void 0!==c&&(n[s]=[B(o,u),B(o,c)].sort(S))}else i||(i={}),i[s]=r.map(N(o))}n&&(e.range=n),i&&(e.lassoPoints=i)}}function ft(t,e){e&&(e.selections=(t.layout||{}).selections||[]),t.emit(\"plotly_selected\",e)}function ht(t){t.emit(\"plotly_deselect\",null)}t.exports={reselect:nt,prepSelect:function(t,e,r,n,i){var u=!U(n),c=f(i),g=h(i),y=d(i),x=p(i),b=v(i),w=\"drawcircle\"===i,T=\"drawline\"===i||w,k=n.gd,A=k._fullLayout,S=b&&\"immediate\"===A.newselection.mode&&u,E=A._zoomlayer,C=n.element.getBoundingClientRect(),P=n.plotinfo,O=j(P),F=e-C.left,B=r-C.top;A._calcInverseTransform(k);var N=M.apply3DTransform(A._invTransform)(F,B);F=N[0],B=N[1];var q,H,X,K,J,tt,at,ot=A._invScaleX,st=A._invScaleY,lt=F,pt=B,dt=\"M\"+F+\",\"+B,vt=n.xaxes[0],gt=n.yaxes[0],yt=vt._length,mt=gt._length,xt=t.altKey&&!(p(i)&&y);W(t,k,n),c&&(q=z([[F,B]],I.BENDPX));var bt=E.selectAll(\"path.select-outline-\"+P.id).data([1]),_t=x?A.newshape:A.newselection;x&&(n.hasText=_t.label.text||_t.label.texttemplate);var wt=x&&!y?_t.fillcolor:\"rgba(0,0,0,0)\",Tt=_t.line.color||(u?s.contrast(k._fullLayout.plot_bgcolor):\"#7f7f7f\");bt.enter().append(\"path\").attr(\"class\",\"select-outline 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s=A.selections[o];s.xref!==t||s.yref!==e?n.push(r[o]):i=!0}i&&(k._fullLayout._noEmitSelectedAtStart=!0,a.call(\"_guiRelayout\",k,{selections:n}))}});var Lt=function(t){return t.plotinfo.fillRangeItems||ct(t.xaxes.concat(t.yaxes))}(n);n.moveFn=function(t,e){n._clearSubplotSelections&&(n._clearSubplotSelections(),n._clearSubplotSelections=void 0),lt=Math.max(0,Math.min(yt,ot*t+F)),pt=Math.max(0,Math.min(mt,st*e+B));var r=Math.abs(lt-F),i=Math.abs(pt-B);if(g){var a,o,s;if(b){var l=A.selectdirection;switch(a=\"any\"===l?i<Math.min(.6*r,D)?\"h\":r<Math.min(.6*i,D)?\"v\":\"d\":l){case\"h\":o=w?mt/2:0,s=mt;break;case\"v\":o=w?yt/2:0,s=yt}}if(x)switch(A.newshape.drawdirection){case\"vertical\":a=\"h\",o=w?mt/2:0,s=mt;break;case\"horizontal\":a=\"v\",o=w?yt/2:0,s=yt;break;case\"ortho\":r<i?(a=\"h\",o=B,s=pt):(a=\"v\",o=F,s=lt);break;default:a=\"d\"}\"h\"===a?((K=T?_(w,[lt,o],[lt,s]):[[F,o],[F,s],[lt,s],[lt,o]]).xmin=T?lt:Math.min(F,lt),K.xmax=T?lt:Math.max(F,lt),K.ymin=Math.min(o,s),K.ymax=Math.max(o,s),kt.attr(\"d\",\"M\"+K.xmin+\",\"+(B-D)+\"h-4v\"+2*D+\"h4ZM\"+(K.xmax-1)+\",\"+(B-D)+\"h4v\"+2*D+\"h-4Z\")):\"v\"===a?((K=T?_(w,[o,pt],[s,pt]):[[o,B],[o,pt],[s,pt],[s,B]]).xmin=Math.min(o,s),K.xmax=Math.max(o,s),K.ymin=T?pt:Math.min(B,pt),K.ymax=T?pt:Math.max(B,pt),kt.attr(\"d\",\"M\"+(F-D)+\",\"+K.ymin+\"v-4h\"+2*D+\"v4ZM\"+(F-D)+\",\"+(K.ymax-1)+\"v4h\"+2*D+\"v-4Z\")):\"d\"===a&&((K=T?_(w,[F,B],[lt,pt]):[[F,B],[F,pt],[lt,pt],[lt,B]]).xmin=Math.min(F,lt),K.xmax=Math.max(F,lt),K.ymin=Math.min(B,pt),K.ymax=Math.max(B,pt),kt.attr(\"d\",\"M0,0Z\"))}else 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s=[],u=k._fullLayout.selections,c=0;c<u.length;c++){var f=u[c];f&&(f.xref===i._id&&f.yref===o._id||s.push(f))}s.length<u.length&&(k._fullLayout._noEmitSelectedAtStart=!0,a.call(\"_guiRelayout\",k,{selections:s}))}}}else r.indexOf(\"select\")>-1&&V(e,k,n.xaxes,n.yaxes,n.subplot,n,bt),\"event\"===r&&ft(k,void 0);l.click(k,e,P.id)})).catch(M.error)}},n.doneFn=function(){kt.remove(),L.done(Mt).then((function(){L.clear(Mt),!S&&K&&n.selectionDefs&&(K.subtract=xt,n.selectionDefs.push(K),n.mergedPolygons.length=0,[].push.apply(n.mergedPolygons,X)),(S||x)&&Y(n,S),n.doneFnCompleted&&n.doneFnCompleted(St),b&&ft(k,at)})).catch(M.error)}},clearOutline:x,clearSelectionsCache:Y,selectOnClick:V}},46056:function(t,e,r){\"use strict\";var 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n=r(3400),i=r(54460),a=r(72736),o=r(43616),s=r(9856).readPaths,l=r(65152),u=l.getPathString,c=r(97728),f=r(84284).FROM_TL;t.exports=function(t,e,r,h){if(h.selectAll(\".shape-label\").remove(),r.label.text||r.label.texttemplate){var p;if(r.label.texttemplate){var d={};if(\"path\"!==r.type){var v=i.getFromId(t,r.xref),g=i.getFromId(t,r.yref);for(var y in c){var m=c[y](r,v,g);void 0!==m&&(d[y]=m)}}p=n.texttemplateStringForShapes(r.label.texttemplate,{},t._fullLayout._d3locale,d)}else p=r.label.text;var x,b,_,w,T={\"data-index\":e},k=r.label.font,A=h.append(\"g\").attr(T).classed(\"shape-label\",!0).append(\"text\").attr({\"data-notex\":1}).classed(\"shape-label-text\",!0).text(p);if(r.path){var M=u(t,r),S=s(M,t);x=1/0,_=1/0,b=-1/0,w=-1/0;for(var E=0;E<S.length;E++)for(var L=0;L<S[E].length;L++)for(var C=S[E][L],P=1;P<C.length;P+=2){var O=C[P],I=C[P+1];x=Math.min(x,O),b=Math.max(b,O),_=Math.min(_,I),w=Math.max(w,I)}}else{var 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n,i=t[0][0],o=e.gd,p=i.getAttribute(\"d\"),g=o._fullLayout.newshape,y=e.plotinfo,w=e.isActiveShape,T=y.xaxis,k=y.yaxis,A=!!y.domain||!y.xaxis,M=!!y.domain||!y.yaxis,S=a(r),E=m(p,o,y,w),L={editable:!0,visible:g.visible,name:g.name,showlegend:g.showlegend,legend:g.legend,legendwidth:g.legendwidth,legendgroup:g.legendgroup,legendgrouptitle:{text:g.legendgrouptitle.text,font:g.legendgrouptitle.font},legendrank:g.legendrank,label:g.label,xref:A?\"paper\":T._id,yref:M?\"paper\":k._id,layer:g.layer,opacity:g.opacity,line:{color:g.line.color,width:g.line.width,dash:g.line.dash}};if(S||(L.fillcolor=g.fillcolor,L.fillrule=g.fillrule),1===E.length&&(n=E[0]),n&&5===n.length&&\"drawrect\"===r)L.type=\"rect\",L.x0=n[0][1],L.y0=n[0][2],L.x1=n[2][1],L.y1=n[2][2];else if(n&&\"drawline\"===r)L.type=\"line\",L.x0=n[0][1],L.y0=n[0][2],L.x1=n[1][1],L.y1=n[1][2];else if(n&&\"drawcircle\"===r){L.type=\"circle\";var C=n[s][1],P=n[l][1],O=n[u][1],I=n[c][1],D=n[s][2],z=n[l][2],R=n[u][2],F=n[c][2],B=y.xaxis&&(\"date\"===y.xaxis.type||\"log\"===y.xaxis.type),N=y.yaxis&&(\"date\"===y.yaxis.type||\"log\"===y.yaxis.type);B&&(C=v(y.xaxis,C),P=v(y.xaxis,P),O=v(y.xaxis,O),I=v(y.xaxis,I)),N&&(D=v(y.yaxis,D),z=v(y.yaxis,z),R=v(y.yaxis,R),F=v(y.yaxis,F));var j=(P+I)/2,U=(D+R)/2,V=b({x0:j,y0:U,x1:j+(I-P+O-C)/2*f,y1:U+(F-z+R-D)/2*h});B&&(V.x0=d(y.xaxis,V.x0),V.x1=d(y.xaxis,V.x1)),N&&(V.y0=d(y.yaxis,V.y0),V.y1=d(y.yaxis,V.y1)),L.x0=V.x0,L.y0=V.y0,L.x1=V.x1,L.y1=V.y1}else L.type=\"path\",T&&k&&_(E,T,k),L.path=x(E),n=null;return L}t.exports={newShapes:function(t,e){if(t.length&&t[0][0]){var r=e.gd,n=e.isActiveShape,a=e.dragmode,o=(r.layout||{}).shapes||[];if(!i(a)&&void 0!==n){var s=r._fullLayout._activeShapeIndex;if(s<o.length)switch(r._fullLayout.shapes[s].type){case\"rect\":a=\"drawrect\";break;case\"circle\":a=\"drawcircle\";break;case\"line\":a=\"drawline\";break;case\"path\":var l=o[s].path||\"\";a=\"Z\"===l[l.length-1]?\"drawclosedpath\":\"drawopenpath\"}}var u=w(t,e,a);g(r);for(var c=e.editHelpers,f=(c||{}).modifyItem,h=[],p=0;p<o.length;p++){var d=r._fullLayout.shapes[p];if(h[p]=d._input,void 0!==n&&p===r._fullLayout._activeShapeIndex){var v=u;switch(d.type){case\"line\":case\"rect\":case\"circle\":f(\"x0\",v.x0),f(\"x1\",v.x1),f(\"y0\",v.y0),f(\"y1\",v.y1);break;case\"path\":f(\"path\",v.path)}}}return void 0===n?(h.push(u),h):c?c.getUpdateObj():{}}},createShapeObj:w}},1936:function(t){\"use strict\";t.exports={clearOutlineControllers:function(t){var e=t._fullLayout._zoomlayer;e&&e.selectAll(\".outline-controllers\").remove()},clearOutline:function(t){var e=t._fullLayout._zoomlayer;e&&e.selectAll(\".select-outline\").remove(),t._fullLayout._outlining=!1}}},65152:function(t,e,r){\"use strict\";var n=r(85448),i=r(3400),a=r(54460);e.rangeToShapePosition=function(t){return\"log\"===t.type?t.r2d:function(t){return t}},e.shapePositionToRange=function(t){return\"log\"===t.type?t.d2r:function(t){return t}},e.decodeDate=function(t){return function(e){return e.replace&&(e=e.replace(\"_\",\" \")),t(e)}},e.encodeDate=function(t){return function(e){return t(e).replace(\" \",\"_\")}},e.extractPathCoords=function(t,e,r){var a=[];return t.match(n.segmentRE).forEach((function(t){var o=e[t.charAt(0)].drawn;if(void 0!==o){var s=t.substr(1).match(n.paramRE);if(s&&!(s.length<o)){var l=s[o],u=r?l:i.cleanNumber(l);a.push(u)}}})),a},e.getDataToPixel=function(t,r,n,i){var a,o=t._fullLayout._size;if(r)if(\"domain\"===i)a=function(t){return r._length*(n?1-t:t)+r._offset};else{var s=e.shapePositionToRange(r);a=function(t){return r._offset+r.r2p(s(t,!0))},\"date\"===r.type&&(a=e.decodeDate(a))}else a=n?function(t){return o.t+o.h*(1-t)}:function(t){return o.l+o.w*t};return a},e.getPixelToData=function(t,r,n,i){var a,o=t._fullLayout._size;if(r)if(\"domain\"===i)a=function(t){var e=(t-r._offset)/r._length;return n?1-e:e};else{var s=e.rangeToShapePosition(r);a=function(t){return s(r.p2r(t-r._offset))}}else a=n?function(t){return 1-(t-o.t)/o.h}:function(t){return(t-o.l)/o.w};return a},e.roundPositionForSharpStrokeRendering=function(t,e){var r=1===Math.round(e%2),n=Math.round(t);return r?n+.5:n},e.makeShapesOptionsAndPlotinfo=function(t,e){var r=t._fullLayout.shapes[e]||{},n=t._fullLayout._plots[r.xref+r.yref];return n?n._hadPlotinfo=!0:(n={},r.xref&&\"paper\"!==r.xref&&(n.xaxis=t._fullLayout[r.xref+\"axis\"]),r.yref&&\"paper\"!==r.yref&&(n.yaxis=t._fullLayout[r.yref+\"axis\"])),n.xsizemode=r.xsizemode,n.ysizemode=r.ysizemode,n.xanchor=r.xanchor,n.yanchor=r.yanchor,{options:r,plotinfo:n}},e.makeSelectionsOptionsAndPlotinfo=function(t,e){var r=t._fullLayout.selections[e]||{},n=t._fullLayout._plots[r.xref+r.yref];return n?n._hadPlotinfo=!0:(n={},r.xref&&(n.xaxis=t._fullLayout[r.xref+\"axis\"]),r.yref&&(n.yaxis=t._fullLayout[r.yref+\"axis\"])),{options:r,plotinfo:n}},e.getPathString=function(t,r){var o,s,l,u,c,f,h,p,d=r.type,v=a.getRefType(r.xref),g=a.getRefType(r.yref),y=a.getFromId(t,r.xref),m=a.getFromId(t,r.yref),x=t._fullLayout._size;if(y?\"domain\"===v?s=function(t){return y._offset+y._length*t}:(o=e.shapePositionToRange(y),s=function(t){return y._offset+y.r2p(o(t,!0))}):s=function(t){return x.l+x.w*t},m?\"domain\"===g?u=function(t){return m._offset+m._length*(1-t)}:(l=e.shapePositionToRange(m),u=function(t){return m._offset+m.r2p(l(t,!0))}):u=function(t){return x.t+x.h*(1-t)},\"path\"===d)return y&&\"date\"===y.type&&(s=e.decodeDate(s)),m&&\"date\"===m.type&&(u=e.decodeDate(u)),function(t,e,r){var a=t.path,o=t.xsizemode,s=t.ysizemode,l=t.xanchor,u=t.yanchor;return a.replace(n.segmentRE,(function(t){var a=0,c=t.charAt(0),f=n.paramIsX[c],h=n.paramIsY[c],p=n.numParams[c],d=t.substr(1).replace(n.paramRE,(function(t){return f[a]?t=\"pixel\"===o?e(l)+Number(t):e(t):h[a]&&(t=\"pixel\"===s?r(u)-Number(t):r(t)),++a>p&&(t=\"X\"),t}));return a>p&&(d=d.replace(/[\\s,]*X.*/,\"\"),i.log(\"Ignoring extra params in segment \"+t)),c+d}))}(r,s,u);if(\"pixel\"===r.xsizemode){var b=s(r.xanchor);c=b+r.x0,f=b+r.x1}else c=s(r.x0),f=s(r.x1);if(\"pixel\"===r.ysizemode){var _=u(r.yanchor);h=_-r.y0,p=_-r.y1}else h=u(r.y0),p=u(r.y1);if(\"line\"===d)return\"M\"+c+\",\"+h+\"L\"+f+\",\"+p;if(\"rect\"===d)return\"M\"+c+\",\"+h+\"H\"+f+\"V\"+p+\"H\"+c+\"Z\";var w=(c+f)/2,T=(h+p)/2,k=Math.abs(w-c),A=Math.abs(T-h),M=\"A\"+k+\",\"+A,S=w+k+\",\"+T;return\"M\"+S+M+\" 0 1,1 \"+w+\",\"+(T-A)+M+\" 0 0,1 \"+S+\"Z\"}},41592:function(t,e,r){\"use strict\";var n=r(4016);t.exports={moduleType:\"component\",name:\"shapes\",layoutAttributes:r(46056),supplyLayoutDefaults:r(43712),supplyDrawNewShapeDefaults:r(65144),includeBasePlot:r(36632)(\"shapes\"),calcAutorange:r(96084),draw:n.draw,drawOne:n.drawOne}},97728:function(t){\"use strict\";function e(t,e){return e?e.d2l(t):t}function r(t,e){return e?e.l2d(t):t}function n(t,r){return e(t.x1,r)-e(t.x0,r)}function i(t,r,n){return e(t.y1,n)-e(t.y0,n)}t.exports={x0:function(t){return t.x0},x1:function(t){return t.x1},y0:function(t){return t.y0},y1:function(t){return t.y1},slope:function(t,e,r){return\"line\"!==t.type?void 0:i(t,0,r)/n(t,e)},dx:n,dy:i,width:function(t,e){return Math.abs(n(t,e))},height:function(t,e,r){return Math.abs(i(t,0,r))},length:function(t,e,r){return\"line\"!==t.type?void 0:Math.sqrt(Math.pow(n(t,e),2)+Math.pow(i(t,0,r),2))},xcenter:function(t,n){return r((e(t.x1,n)+e(t.x0,n))/2,n)},ycenter:function(t,n,i){return r((e(t.y1,i)+e(t.y0,i))/2,i)}}},89861:function(t,e,r){\"use 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n=r(25376),i=r(66741),a=r(92880).extendDeepAll,o=r(67824).overrideAll,s=r(85656),l=r(31780).templatedArray,u=r(60876),c=l(\"step\",{visible:{valType:\"boolean\",dflt:!0},method:{valType:\"enumerated\",values:[\"restyle\",\"relayout\",\"animate\",\"update\",\"skip\"],dflt:\"restyle\"},args:{valType:\"info_array\",freeLength:!0,items:[{valType:\"any\"},{valType:\"any\"},{valType:\"any\"}]},label:{valType:\"string\"},value:{valType:\"string\"},execute:{valType:\"boolean\",dflt:!0}});t.exports=o(l(\"slider\",{visible:{valType:\"boolean\",dflt:!0},active:{valType:\"number\",min:0,dflt:0},steps:c,lenmode:{valType:\"enumerated\",values:[\"fraction\",\"pixels\"],dflt:\"fraction\"},len:{valType:\"number\",min:0,dflt:1},x:{valType:\"number\",min:-2,max:3,dflt:0},pad:a(i({editType:\"arraydraw\"}),{},{t:{dflt:20}}),xanchor:{valType:\"enumerated\",values:[\"auto\",\"left\",\"center\",\"right\"],dflt:\"left\"},y:{valType:\"number\",min:-2,max:3,dflt:0},yanchor:{valType:\"enumerated\",values:[\"auto\",\"top\",\"middle\",\"bottom\"],dflt:\"top\"},transition:{duration:{valType:\"number\",min:0,dflt:150},easing:{valType:\"enumerated\",values:s.transition.easing.values,dflt:\"cubic-in-out\"}},currentvalue:{visible:{valType:\"boolean\",dflt:!0},xanchor:{valType:\"enumerated\",values:[\"left\",\"center\",\"right\"],dflt:\"left\"},offset:{valType:\"number\",dflt:10},prefix:{valType:\"string\"},suffix:{valType:\"string\"},font:n({})},font:n({}),activebgcolor:{valType:\"color\",dflt:u.gripBgActiveColor},bgcolor:{valType:\"color\",dflt:u.railBgColor},bordercolor:{valType:\"color\",dflt:u.railBorderColor},borderwidth:{valType:\"number\",min:0,dflt:u.railBorderWidth},ticklen:{valType:\"number\",min:0,dflt:u.tickLength},tickcolor:{valType:\"color\",dflt:u.tickColor},tickwidth:{valType:\"number\",min:0,dflt:1},minorticklen:{valType:\"number\",min:0,dflt:u.minorTickLength}}),\"arraydraw\",\"from-root\")},60876:function(t){\"use strict\";t.exports={name:\"sliders\",containerClassName:\"slider-container\",groupClassName:\"slider-group\",inputAreaClass:\"slider-input-area\",railRectClass:\"slider-rail-rect\",railTouchRectClass:\"slider-rail-touch-rect\",gripRectClass:\"slider-grip-rect\",tickRectClass:\"slider-tick-rect\",inputProxyClass:\"slider-input-proxy\",labelsClass:\"slider-labels\",labelGroupClass:\"slider-label-group\",labelClass:\"slider-label\",currentValueClass:\"slider-current-value\",railHeight:5,menuIndexAttrName:\"slider-active-index\",autoMarginIdRoot:\"slider-\",minWidth:30,minHeight:30,textPadX:40,arrowOffsetX:4,railRadius:2,railWidth:5,railBorder:4,railBorderWidth:1,railBorderColor:\"#bec8d9\",railBgColor:\"#f8fafc\",railInset:8,stepInset:10,gripRadius:10,gripWidth:20,gripHeight:20,gripBorder:20,gripBorderWidth:1,gripBorderColor:\"#bec8d9\",gripBgColor:\"#f6f8fa\",gripBgActiveColor:\"#dbdde0\",labelPadding:8,labelOffset:0,tickWidth:1,tickColor:\"#333\",tickOffset:25,tickLength:7,minorTickOffset:25,minorTickColor:\"#333\",minorTickLength:4,currentValuePadding:8,currentValueInset:0}},8132:function(t,e,r){\"use 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n.coerce(t,e,s,r,i)}if(\"skip\"===t.method||Array.isArray(t.args)?r(\"visible\"):e.visible=!1){r(\"method\"),r(\"args\");var i=r(\"label\",\"step-\"+e._index);r(\"value\",i),r(\"execute\")}}t.exports=function(t,e){i(t,e,{name:o,handleItemDefaults:l})}},79664:function(t,e,r){\"use strict\";var n=r(33428),i=r(7316),a=r(76308),o=r(43616),s=r(3400),l=s.strTranslate,u=r(72736),c=r(31780).arrayEditor,f=r(60876),h=r(84284),p=h.LINE_SPACING,d=h.FROM_TL,v=h.FROM_BR;function g(t){return f.autoMarginIdRoot+t._index}function y(t){return t._index}function m(t,e){var r=o.tester.selectAll(\"g.\"+f.labelGroupClass).data(e._visibleSteps);r.enter().append(\"g\").classed(f.labelGroupClass,!0);var a=0,l=0;r.each((function(t){var r=_(n.select(this),{step:t},e).node();if(r){var i=o.bBox(r);l=Math.max(l,i.height),a=Math.max(a,i.width)}})),r.remove();var c=e._dims={};c.inputAreaWidth=Math.max(f.railWidth,f.gripHeight);var h=t._fullLayout._size;c.lx=h.l+h.w*e.x,c.ly=h.t+h.h*(1-e.y),\"fraction\"===e.lenmode?c.outerLength=Math.round(h.w*e.len):c.outerLength=e.len,c.inputAreaStart=0,c.inputAreaLength=Math.round(c.outerLength-e.pad.l-e.pad.r);var p=(c.inputAreaLength-2*f.stepInset)/(e._stepCount-1),y=a+f.labelPadding;if(c.labelStride=Math.max(1,Math.ceil(y/p)),c.labelHeight=l,c.currentValueMaxWidth=0,c.currentValueHeight=0,c.currentValueTotalHeight=0,c.currentValueMaxLines=1,e.currentvalue.visible){var m=o.tester.append(\"g\");r.each((function(t){var r=x(m,e,t.label),n=r.node()&&o.bBox(r.node())||{width:0,height:0},i=u.lineCount(r);c.currentValueMaxWidth=Math.max(c.currentValueMaxWidth,Math.ceil(n.width)),c.currentValueHeight=Math.max(c.currentValueHeight,Math.ceil(n.height)),c.currentValueMaxLines=Math.max(c.currentValueMaxLines,i)})),c.currentValueTotalHeight=c.currentValueHeight+e.currentvalue.offset,m.remove()}c.height=c.currentValueTotalHeight+f.tickOffset+e.ticklen+f.labelOffset+c.labelHeight+e.pad.t+e.pad.b;var b=\"left\";s.isRightAnchor(e)&&(c.lx-=c.outerLength,b=\"right\"),s.isCenterAnchor(e)&&(c.lx-=c.outerLength/2,b=\"center\");var w=\"top\";s.isBottomAnchor(e)&&(c.ly-=c.height,w=\"bottom\"),s.isMiddleAnchor(e)&&(c.ly-=c.height/2,w=\"middle\"),c.outerLength=Math.ceil(c.outerLength),c.height=Math.ceil(c.height),c.lx=Math.round(c.lx),c.ly=Math.round(c.ly);var T={y:e.y,b:c.height*v[w],t:c.height*d[w]};\"fraction\"===e.lenmode?(T.l=0,T.xl=e.x-e.len*d[b],T.r=0,T.xr=e.x+e.len*v[b]):(T.x=e.x,T.l=c.outerLength*d[b],T.r=c.outerLength*v[b]),i.autoMargin(t,g(e),T)}function x(t,e,r){if(e.currentvalue.visible){var n,i,a=e._dims;switch(e.currentvalue.xanchor){case\"right\":n=a.inputAreaLength-f.currentValueInset-a.currentValueMaxWidth,i=\"left\";break;case\"center\":n=.5*a.inputAreaLength,i=\"middle\";break;default:n=f.currentValueInset,i=\"left\"}var l=s.ensureSingle(t,\"text\",f.labelClass,(function(t){t.attr({\"text-anchor\":i,\"data-notex\":1})})),c=e.currentvalue.prefix?e.currentvalue.prefix:\"\";if(\"string\"==typeof r)c+=r;else{var h=e.steps[e.active].label,d=e._gd._fullLayout._meta;d&&(h=s.templateString(h,d)),c+=h}e.currentvalue.suffix&&(c+=e.currentvalue.suffix),l.call(o.font,e.currentvalue.font).text(c).call(u.convertToTspans,e._gd);var v=u.lineCount(l),g=(a.currentValueMaxLines+1-v)*e.currentvalue.font.size*p;return u.positionText(l,n,g),l}}function b(t,e,r){s.ensureSingle(t,\"rect\",f.gripRectClass,(function(n){n.call(A,e,t,r).style(\"pointer-events\",\"all\")})).attr({width:f.gripWidth,height:f.gripHeight,rx:f.gripRadius,ry:f.gripRadius}).call(a.stroke,r.bordercolor).call(a.fill,r.bgcolor).style(\"stroke-width\",r.borderwidth+\"px\")}function _(t,e,r){var n=s.ensureSingle(t,\"text\",f.labelClass,(function(t){t.attr({\"text-anchor\":\"middle\",\"data-notex\":1})})),i=e.step.label,a=r._gd._fullLayout._meta;return a&&(i=s.templateString(i,a)),n.call(o.font,r.font).text(i).call(u.convertToTspans,r._gd),n}function w(t,e){var r=s.ensureSingle(t,\"g\",f.labelsClass),i=e._dims,a=r.selectAll(\"g.\"+f.labelGroupClass).data(i.labelSteps);a.enter().append(\"g\").classed(f.labelGroupClass,!0),a.exit().remove(),a.each((function(t){var r=n.select(this);r.call(_,t,e),o.setTranslate(r,E(e,t.fraction),f.tickOffset+e.ticklen+e.font.size*p+f.labelOffset+i.currentValueTotalHeight)}))}function T(t,e,r,n,i){var a=Math.round(n*(r._stepCount-1)),o=r._visibleSteps[a]._index;o!==r.active&&k(t,e,r,o,!0,i)}function k(t,e,r,n,a,o){var s=r.active;r.active=n,c(t.layout,f.name,r).applyUpdate(\"active\",n);var l=r.steps[r.active];e.call(S,r,o),e.call(x,r),t.emit(\"plotly_sliderchange\",{slider:r,step:r.steps[r.active],interaction:a,previousActive:s}),l&&l.method&&a&&(e._nextMethod?(e._nextMethod.step=l,e._nextMethod.doCallback=a,e._nextMethod.doTransition=o):(e._nextMethod={step:l,doCallback:a,doTransition:o},e._nextMethodRaf=window.requestAnimationFrame((function(){var r=e._nextMethod.step;r.method&&(r.execute&&i.executeAPICommand(t,r.method,r.args),e._nextMethod=null,e._nextMethodRaf=null)}))))}function A(t,e,r){if(!e._context.staticPlot){var i=r.node(),o=n.select(e);t.on(\"mousedown\",l),t.on(\"touchstart\",l)}function s(){return r.data()[0]}function l(){var t=s();e.emit(\"plotly_sliderstart\",{slider:t});var 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q=n.behavior.drag().on(\"dragstart\",(function(){n.event.sourceEvent.preventDefault(),n.event.sourceEvent.stopPropagation()})).on(\"drag\",this._onBarDrag.bind(this));k&&this.hbar.on(\".drag\",null).call(q),C&&this.vbar.on(\".drag\",null).call(q)}this.setTranslate(e,r)},s.prototype.disable=function(){(this.hbar||this.vbar)&&(this.bg.attr({width:0,height:0}),this.container.on(\"wheel\",null).on(\".drag\",null).call(a.setClipUrl,null),delete this._clipRect),this.hbar&&(this.hbar.on(\".drag\",null),this.hbar.remove(),delete this.hbar,delete this._hbarXMin,delete this._hbarTranslateMax),this.vbar&&(this.vbar.on(\".drag\",null),this.vbar.remove(),delete this.vbar,delete this._vbarYMin,delete this._vbarTranslateMax)},s.prototype._onBoxDrag=function(){var t=this.translateX,e=this.translateY;this.hbar&&(t-=n.event.dx),this.vbar&&(e-=n.event.dy),this.setTranslate(t,e)},s.prototype._onBoxWheel=function(){var 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e=n.select(t),r=t._fullLayout;if(r._calcInverseTransform=lt,r._calcInverseTransform(t),r._container=e.selectAll(\".plot-container\").data([0]),r._container.enter().insert(\"div\",\":first-child\").classed(\"plot-container\",!0).classed(\"plotly\",!0),r._paperdiv=r._container.selectAll(\".svg-container\").data([0]),r._paperdiv.enter().append(\"div\").classed(\"user-select-none\",!0).classed(\"svg-container\",!0).style(\"position\",\"relative\"),r._glcontainer=r._paperdiv.selectAll(\".gl-container\").data([{}]),r._glcontainer.enter().append(\"div\").classed(\"gl-container\",!0),r._paperdiv.selectAll(\".main-svg\").remove(),r._paperdiv.select(\".modebar-container\").remove(),r._paper=r._paperdiv.insert(\"svg\",\":first-child\").classed(\"main-svg\",!0),r._toppaper=r._paperdiv.append(\"svg\").classed(\"main-svg\",!0),r._modebardiv=r._paperdiv.append(\"div\"),delete r._modeBar,r._hoverpaper=r._paperdiv.append(\"svg\").classed(\"main-svg\",!0),!r._uid){var 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s=r._toppaper.append(\"g\").classed(\"layer-above\",!0);r._imageUpperLayer=s.append(\"g\").classed(\"imagelayer\",!0),r._shapeUpperLayer=s.append(\"g\").classed(\"shapelayer\",!0),r._selectionLayer=r._toppaper.append(\"g\").classed(\"selectionlayer\",!0),r._infolayer=r._toppaper.append(\"g\").classed(\"infolayer\",!0),r._menulayer=r._toppaper.append(\"g\").classed(\"menulayer\",!0),r._zoomlayer=r._toppaper.append(\"g\").classed(\"zoomlayer\",!0),r._hoverlayer=r._hoverpaper.append(\"g\").classed(\"hoverlayer\",!0),r._modebardiv.classed(\"modebar-container\",!0).style(\"position\",\"absolute\").style(\"top\",\"0px\").style(\"right\",\"0px\"),t.emit(\"plotly_framework\")}(t),d._shouldCreateBgLayer&&delete d._shouldCreateBgLayer),g.initGradients(t),g.initPatterns(t),f&&p.saveShowSpikeInitial(t);var y=!t.calcdata||t.calcdata.length!==(t._fullData||[]).length;y&&h.doCalcdata(t);for(var 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0!==t.onwheel?\"wheel\":\"mousewheel\";t._onwheel&&t.removeEventListener(r,t._onwheel),t._onwheel=e,t.addEventListener(r,e,{passive:!1})}else void 0!==t.onwheel?t.onwheel=e:void 0!==t.onmousewheel?t.onmousewheel=e:t.isAddedWheelEvent||(t.isAddedWheelEvent=!0,t.addEventListener(\"wheel\",e,{passive:!1}))}function X(t){var e=[];for(var r in t)e.push(t[r]);return e}t.exports={makeDragBox:function(t,e,r,s,u,f,v,y){var O,I,V,Z,K,J,$,Q,tt,et,rt,nt,it,at,ot,st,lt,ut,ct,ft,ht,pt,dt,vt=t._fullLayout._zoomlayer,gt=v+y===\"nsew\",yt=1===(v+y).length;function mt(){if(O=e.xaxis,I=e.yaxis,tt=O._length,et=I._length,$=O._offset,Q=I._offset,(V={})[O._id]=O,(Z={})[I._id]=I,v&&y)for(var r=e.overlays,n=0;n<r.length;n++){var i=r[n].xaxis;V[i._id]=i;var a=r[n].yaxis;Z[a._id]=a}K=X(V),J=X(Z),it=z(K,y),at=z(J,v),ot=!at&&!it,nt=W(t,t._fullLayout._axisMatchGroups,V,Z);var o=(rt=W(t,t._fullLayout._axisConstraintGroups,V,Z,nt)).isSubplotConstrained||nt.isSubplotConstrained;st=y||o,lt=v||o;var s=t._fullLayout;ut=s._has(\"scattergl\"),ct=s._has(\"splom\"),ft=s._has(\"svg\")}r+=e.yaxis._shift,mt();var xt=function(t,e,r){return t?\"nsew\"===t?r?\"\":\"pan\"===e?\"move\":\"crosshair\":t.toLowerCase()+\"-resize\":\"pointer\"}(at+it,t._fullLayout.dragmode,gt),bt=D(e,v+y+\"drag\",xt,r,s,u,f);if(ot&&!gt)return bt.onmousedown=null,bt.style.pointerEvents=\"none\",bt;var _t,wt,Tt,kt,At,Mt,St,Et,Lt,Ct,Pt={element:bt,gd:t,plotinfo:e};function Ot(){Pt.plotinfo.selection=!1,M(t)}function It(t,r){var i=Pt.gd;if(i._fullLayout._activeShapeIndex>=0)i._fullLayout._deactivateShape(i);else{var o=i._fullLayout.clickmode;if(q(i),2!==t||yt||Ht(),gt)o.indexOf(\"select\")>-1&&S(r,i,K,J,e.id,Pt),o.indexOf(\"event\")>-1&&p.click(i,r,e.id);else if(1===t&&yt){var s=v?I:O,u=\"s\"===v||\"w\"===y?0:1,f=s._name+\".range[\"+u+\"]\",h=function(t,e){var r,n=t.range[e],i=Math.abs(n-t.range[1-e]);return\"date\"===t.type?n:\"log\"===t.type?(r=Math.ceil(Math.max(0,-Math.log(i)/Math.LN10))+3,a(\".\"+r+\"g\")(Math.pow(10,n))):(r=Math.floor(Math.log(Math.abs(n))/Math.LN10)-Math.floor(Math.log(i)/Math.LN10)+4,a(\".\"+String(r)+\"g\")(n))}(s,u),d=\"left\",g=\"middle\";if(s.fixedrange)return;v?(g=\"n\"===v?\"top\":\"bottom\",\"right\"===s.side&&(d=\"right\")):\"e\"===y&&(d=\"right\"),i._context.showAxisRangeEntryBoxes&&n.select(bt).call(c.makeEditable,{gd:i,immediate:!0,background:i._fullLayout.paper_bgcolor,text:String(h),fill:s.tickfont?s.tickfont.color:\"#444\",horizontalAlign:d,verticalAlign:g}).on(\"edit\",(function(t){var e=s.d2r(t);void 0!==e&&l.call(\"_guiRelayout\",i,f,e)}))}}}function Dt(e,r){if(t._transitioningWithDuration)return!1;var n=Math.max(0,Math.min(tt,pt*e+_t)),i=Math.max(0,Math.min(et,dt*r+wt)),a=Math.abs(n-_t),o=Math.abs(i-wt);function s(){St=\"\",Tt.r=Tt.l,Tt.t=Tt.b,Lt.attr(\"d\",\"M0,0Z\")}if(Tt.l=Math.min(_t,n),Tt.r=Math.max(_t,n),Tt.t=Math.min(wt,i),Tt.b=Math.max(wt,i),rt.isSubplotConstrained)a>P||o>P?(St=\"xy\",a/tt>o/et?(o=a*et/tt,wt>i?Tt.t=wt-o:Tt.b=wt+o):(a=o*tt/et,_t>n?Tt.l=_t-a:Tt.r=_t+a),Lt.attr(\"d\",G(Tt))):s();else if(nt.isSubplotConstrained)if(a>P||o>P){St=\"xy\";var l=Math.min(Tt.l/tt,(et-Tt.b)/et),u=Math.max(Tt.r/tt,(et-Tt.t)/et);Tt.l=l*tt,Tt.r=u*tt,Tt.b=(1-l)*et,Tt.t=(1-u)*et,Lt.attr(\"d\",G(Tt))}else s();else!at||o<Math.min(Math.max(.6*a,C),P)?a<C||!it?s():(Tt.t=0,Tt.b=et,St=\"x\",Lt.attr(\"d\",function(t,e){return\"M\"+(t.l-.5)+\",\"+(e-P-.5)+\"h-3v\"+(2*P+1)+\"h3ZM\"+(t.r+.5)+\",\"+(e-P-.5)+\"h3v\"+(2*P+1)+\"h-3Z\"}(Tt,wt))):!it||a<Math.min(.6*o,P)?(Tt.l=0,Tt.r=tt,St=\"y\",Lt.attr(\"d\",function(t,e){return\"M\"+(e-P-.5)+\",\"+(t.t-.5)+\"v-3h\"+(2*P+1)+\"v3ZM\"+(e-P-.5)+\",\"+(t.b+.5)+\"v3h\"+(2*P+1)+\"v-3Z\"}(Tt,_t))):(St=\"xy\",Lt.attr(\"d\",G(Tt)));Tt.w=Tt.r-Tt.l,Tt.h=Tt.b-Tt.t,St&&(Ct=!0),t._dragged=Ct,U(Et,Lt,Tt,At,Mt,kt),zt(),t.emit(\"plotly_relayouting\",ht),Mt=!0}function zt(){ht={},\"xy\"!==St&&\"x\"!==St||(R(K,Tt.l/tt,Tt.r/tt,ht,rt.xaxes),Vt(\"x\",ht)),\"xy\"!==St&&\"y\"!==St||(R(J,(et-Tt.b)/et,(et-Tt.t)/et,ht,rt.yaxes),Vt(\"y\",ht))}function Rt(){zt(),q(t),Gt(),H(t)}Pt.prepFn=function(e,r,n){var a=Pt.dragmode,s=t._fullLayout.dragmode;s!==a&&(Pt.dragmode=s),mt(),pt=t._fullLayout._invScaleX,dt=t._fullLayout._invScaleY,ot||(gt?e.shiftKey?\"pan\"===s?s=\"zoom\":m(s)||(s=\"pan\"):e.ctrlKey&&(s=\"pan\"):s=\"pan\"),x(s)?Pt.minDrag=1:Pt.minDrag=void 0,m(s)?(Pt.xaxes=K,Pt.yaxes=J,A(e,r,n,Pt,s)):(Pt.clickFn=It,m(a)&&Ot(),ot||(\"zoom\"===s?(Pt.moveFn=Dt,Pt.doneFn=Rt,Pt.minDrag=1,function(e,r,n){var a=bt.getBoundingClientRect();_t=r-a.left,wt=n-a.top,t._fullLayout._calcInverseTransform(t);var s=i.apply3DTransform(t._fullLayout._invTransform)(_t,wt);_t=s[0],wt=s[1],Tt={l:_t,r:_t,w:0,t:wt,b:wt,h:0},kt=t._hmpixcount?t._hmlumcount/t._hmpixcount:o(t._fullLayout.plot_bgcolor).getLuminance(),Mt=!1,St=\"xy\",Ct=!1,Et=N(vt,kt,$,Q,At=\"M0,0H\"+tt+\"V\"+et+\"H0V0\"),Lt=j(vt,$,Q)}(0,r,n)):\"pan\"===s&&(Pt.moveFn=Ut,Pt.doneFn=Gt))),t._fullLayout._redrag=function(){var e=t._dragdata;if(e&&e.element===bt){var r=t._fullLayout.dragmode;m(r)||(mt(),Wt([0,0,tt,et]),Pt.moveFn(e.dx,e.dy))}}},g.init(Pt);var Ft=[0,0,tt,et],Bt=null,Nt=L.REDRAWDELAY,jt=e.mainplot?t._fullLayout._plots[e.mainplot]:e;function Ut(e,r){if(e*=pt,r*=dt,!t._transitioningWithDuration){if(t._fullLayout._replotting=!0,\"ew\"===it||\"ns\"===at){var n=it?-e:0,i=at?-r:0;if(nt.isSubplotConstrained){if(it&&at){var a=(e/tt-r/et)/2;n=-(e=a*tt),i=-(r=-a*et)}at?n=-i*tt/et:i=-n*et/tt}return it&&(F(K,e),Vt(\"x\")),at&&(F(J,r),Vt(\"y\")),Wt([n,i,tt,et]),qt(),void t.emit(\"plotly_relayouting\",ht)}var o,s,l=\"w\"===it==(\"n\"===at)?1:-1;if(it&&at&&(rt.isSubplotConstrained||nt.isSubplotConstrained)){var u=(e/tt+l*r/et)/2;e=u*tt,r=l*u*et}if(\"w\"===it?e=p(K,0,e):\"e\"===it?e=p(K,1,-e):it||(e=0),\"n\"===at?r=p(J,1,r):\"s\"===at?r=p(J,0,-r):at||(r=0),o=\"w\"===it?e:0,s=\"n\"===at?r:0,rt.isSubplotConstrained&&!nt.isSubplotConstrained||nt.isSubplotConstrained&&it&&at&&l>0){var c;if(nt.isSubplotConstrained||!it&&1===at.length){for(c=0;c<K.length;c++)K[c].range=K[c]._r.slice(),E(K[c],1-r/et);o=(e=r*tt/et)/2}if(nt.isSubplotConstrained||!at&&1===it.length){for(c=0;c<J.length;c++)J[c].range=J[c]._r.slice(),E(J[c],1-e/tt);s=(r=e*et/tt)/2}}nt.isSubplotConstrained&&at||Vt(\"x\"),nt.isSubplotConstrained&&it||Vt(\"y\");var f=tt-e,h=et-r;!nt.isSubplotConstrained||it&&at||(it?(s=o?0:e*et/tt,h=f*et/tt):(o=s?0:r*tt/et,f=h*tt/et)),Wt([o,s,f,h]),qt(),t.emit(\"plotly_relayouting\",ht)}function p(t,e,r){for(var n,i,a=1-e,o=0;o<t.length;o++){var s=t[o];if(!s.fixedrange){n=s,i=s._rl[a]+(s._rl[e]-s._rl[a])/B(r/s._length);var l=s.l2r(i);!1!==l&&void 0!==l&&(s.range[e]=l)}}return n._length*(n._rl[e]-i)/(n._rl[e]-n._rl[a])}}function Vt(t,e){for(var r=nt.isSubplotConstrained?{x:J,y:K}[t]:nt[t+\"axes\"],n=nt.isSubplotConstrained?{x:K,y:J}[t]:[],i=0;i<r.length;i++){var a=r[i],o=a._id,s=nt.xLinks[o]||nt.yLinks[o],l=n[0]||V[s]||Z[s];l&&(e?(e[a._name+\".range[0]\"]=e[l._name+\".range[0]\"],e[a._name+\".range[1]\"]=e[l._name+\".range[1]\"]):a.range=l.range.slice())}}function qt(){var r,n=[];function i(t){for(r=0;r<t.length;r++)t[r].fixedrange||n.push(t[r]._id)}function a(t,e){for(r=0;r<t.length;r++){var i=t[r],a=i[e];i.fixedrange||\"sync\"!==a.tickmode||n.push(a._id)}}for(st&&(i(K),i(rt.xaxes),i(nt.xaxes),a(e.overlays,\"xaxis\")),lt&&(i(J),i(rt.yaxes),i(nt.yaxes),a(e.overlays,\"yaxis\")),ht={},r=0;r<n.length;r++){var o=n[r],s=k(t,o);d.drawOne(t,s,{skipTitle:!0}),ht[s._name+\".range[0]\"]=s.range[0],ht[s._name+\".range[1]\"]=s.range[1]}d.redrawComponents(t,n)}function Ht(){if(!t._transitioningWithDuration){var e=t._context.doubleClick,r=[];it&&(r=r.concat(K)),at&&(r=r.concat(J)),nt.xaxes&&(r=r.concat(nt.xaxes)),nt.yaxes&&(r=r.concat(nt.yaxes));var n,i,a={};if(\"reset+autosize\"===e)for(e=\"autosize\",i=0;i<r.length;i++){var o=(n=r[i])._rangeInitial0,s=n._rangeInitial1,u=void 0!==o||void 0!==s;if(u&&(void 0!==o&&o!==n.range[0]||void 0!==s&&s!==n.range[1])||!u&&!0!==n.autorange){e=\"reset\";break}}if(\"autosize\"===e)for(i=0;i<r.length;i++)(n=r[i]).fixedrange||(a[n._name+\".autorange\"]=!0);else if(\"reset\"===e)for((it||rt.isSubplotConstrained)&&(r=r.concat(rt.xaxes)),at&&!rt.isSubplotConstrained&&(r=r.concat(rt.yaxes)),rt.isSubplotConstrained&&(it?at||(r=r.concat(J)):r=r.concat(K)),i=0;i<r.length;i++)if(!(n=r[i]).fixedrange){var c=n._name,f=n._autorangeInitial;void 0===n._rangeInitial0&&void 0===n._rangeInitial1?a[c+\".autorange\"]=!0:void 0===n._rangeInitial0?(a[c+\".autorange\"]=f,a[c+\".range\"]=[null,n._rangeInitial1]):void 0===n._rangeInitial1?(a[c+\".range\"]=[n._rangeInitial0,null],a[c+\".autorange\"]=f):a[c+\".range\"]=[n._rangeInitial0,n._rangeInitial1]}t.emit(\"plotly_doubleclick\",null),l.call(\"_guiRelayout\",t,a)}}function Gt(){Wt([0,0,tt,et]),i.syncOrAsync([T.previousPromises,function(){t._fullLayout._replotting=!1,l.call(\"_guiRelayout\",t,ht)}],t)}function Wt(e){var r,n,a,o,s=t._fullLayout,u=s._plots,c=s._subplots.cartesian;if(ct&&l.subplotsRegistry.splom.drag(t),ut)for(r=0;r<c.length;r++)if(a=(n=u[c[r]]).xaxis,o=n.yaxis,n._scene){var f=i.simpleMap(a.range,a.r2l),p=i.simpleMap(o.range,o.r2l);a.limitRange&&a.limitRange(),o.limitRange&&o.limitRange(),f=a.range,p=o.range,n._scene.update({range:[f[0],p[0],f[1],p[1]]})}if((ct||ut)&&(_(t),w(t)),ft){var d=e[2]/O._length,g=e[3]/I._length;for(r=0;r<c.length;r++){a=(n=u[c[r]]).xaxis,o=n.yaxis;var m,x,b,T,k=(st||nt.isSubplotConstrained)&&!a.fixedrange&&V[a._id],A=(lt||nt.isSubplotConstrained)&&!o.fixedrange&&Z[o._id];if(k?(m=d,b=y||nt.isSubplotConstrained?e[0]:Zt(a,m)):nt.xaHash[a._id]?(m=d,b=e[0]*a._length/O._length):nt.yaHash[a._id]?(m=g,b=\"ns\"===at?-e[1]*a._length/I._length:Zt(a,m,{n:\"top\",s:\"bottom\"}[at])):b=Xt(a,m=Yt(a,d,g)),m>1&&(void 0!==a.maxallowed&&st===(a.range[0]<a.range[1]?\"e\":\"w\")||void 0!==a.minallowed&&st===(a.range[0]<a.range[1]?\"w\":\"e\"))&&(m=1,b=0),A?(x=g,T=v||nt.isSubplotConstrained?e[1]:Zt(o,x)):nt.yaHash[o._id]?(x=g,T=e[1]*o._length/I._length):nt.xaHash[o._id]?(x=d,T=\"ew\"===it?-e[0]*o._length/O._length:Zt(o,x,{e:\"right\",w:\"left\"}[it])):T=Xt(o,x=Yt(o,d,g)),x>1&&(void 0!==o.maxallowed&&lt===(o.range[0]<o.range[1]?\"n\":\"s\")||void 0!==o.minallowed&&lt===(o.range[0]<o.range[1]?\"s\":\"n\"))&&(x=1,T=0),m||x){m||(m=1),x||(x=1);var M=a._offset-b/m,S=o._offset-T/x;n.clipRect.call(h.setTranslate,b,T).call(h.setScale,m,x),n.plot.call(h.setTranslate,M,S).call(h.setScale,1/m,1/x),m===n.xScaleFactor&&x===n.yScaleFactor||(h.setPointGroupScale(n.zoomScalePts,m,x),h.setTextPointsScale(n.zoomScaleTxt,m,x)),h.hideOutsideRangePoints(n.clipOnAxisFalseTraces,n),n.xScaleFactor=m,n.yScaleFactor=x}}}}function Yt(t,e,r){return t.fixedrange?0:st&&rt.xaHash[t._id]?e:lt&&(rt.isSubplotConstrained?rt.xaHash:rt.yaHash)[t._id]?r:0}function Xt(t,e){return e?(t.range=t._r.slice(),E(t,e),Zt(t,e)):0}function Zt(t,e,r){return t._length*(1-e)*b[r||t.constraintoward||\"middle\"]}return v.length*y.length!=1&&Y(bt,(function(e){if(t._context._scrollZoom.cartesian||t._fullLayout._enablescrollzoom){if(Ot(),t._transitioningWithDuration)return e.preventDefault(),void e.stopPropagation();mt(),clearTimeout(Bt);var r=-e.deltaY;if(isFinite(r)||(r=e.wheelDelta/10),isFinite(r)){var n,a=Math.exp(-Math.min(Math.max(r,-20),20)/200),o=jt.draglayer.select(\".nsewdrag\").node().getBoundingClientRect(),s=(e.clientX-o.left)/o.width,l=(o.bottom-e.clientY)/o.height;if(st){for(y||(s=.5),n=0;n<K.length;n++)u(K[n],s,a);Vt(\"x\"),Ft[2]*=a,Ft[0]+=Ft[2]*s*(1/a-1)}if(lt){for(v||(l=.5),n=0;n<J.length;n++)u(J[n],l,a);Vt(\"y\"),Ft[3]*=a,Ft[1]+=Ft[3]*(1-l)*(1/a-1)}Wt(Ft),qt(),t.emit(\"plotly_relayouting\",ht),Bt=setTimeout((function(){t._fullLayout&&(Ft=[0,0,tt,et],Gt())}),Nt),e.preventDefault()}else i.log(\"Did not find wheel motion attributes: \",e)}function u(t,e,r){if(!t.fixedrange){var n=i.simpleMap(t.range,t.r2l),a=n[0]+(n[1]-n[0])*e;t.range=n.map((function(e){return t.l2r(a+(e-a)*r)}))}}})),bt},makeDragger:I,makeRectDragger:D,makeZoombox:N,makeCorners:j,updateZoombox:U,xyCorners:G,transitionZoombox:V,removeZoombox:q,showDoubleClickNotifier:H,attachWheelEventHandler:Y}},42464:function(t,e,r){\"use strict\";var 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n=r*o,i=t.slice(),a=0===e?1:0,s=2===e?1:2,l=Math.cos(n),u=Math.sin(n);return i[a]=t[a]*l-t[s]*u,i[s]=t[s]*l+t[a]*u,i}function x(t,e){for(var r=0,n=0,i=t.length;n<i;++n)r+=t[n]*e[n];return r}t.exports=function(t,e){var r=t.projection;return(e._isScoped?h:e._isClipped?d:p)(t,r)}},84888:function(t,e,r){\"use strict\";var n=r(24040),i=r(33816).SUBPLOT_PATTERN;e.KY=function(t,e,r){var i=n.subplotsRegistry[e];if(!i)return[];for(var a=i.attr,o=[],s=0;s<t.length;s++){var l=t[s];l[0].trace[a]===r&&o.push(l)}return o},e._M=function(t,e){var r,i=[],a=[];if(!(r=\"string\"==typeof e?n.getModule(e).plot:\"function\"==typeof e?e:e.plot))return[i,t];for(var o=0;o<t.length;o++){var s=t[o],l=s[0].trace;!0===l.visible&&0!==l._length&&(l._module&&l._module.plot===r?i.push(s):a.push(s))}return[i,a]},e.op=function(t,e,r){if(!n.subplotsRegistry[e])return[];var a,o,s,l=n.subplotsRegistry[e].attr,u=[];if(\"gl2d\"===e){var c=r.match(i);o=\"x\"+c[1],s=\"y\"+c[2]}for(var f=0;f<t.length;f++)a=t[f],\"gl2d\"===e&&n.traceIs(a,\"gl2d\")?a[l[0]]===o&&a[l[1]]===s&&u.push(a):a[l]===r&&u.push(a);return u}},2428:function(t,e,r){\"use strict\";var n=r(62644),i=r(97264),a=r(29128),o=r(33816),s=r(89184);function l(t,e){this.element=t,this.plot=e,this.mouseListener=null,this.wheelListener=null,this.lastInputTime=Date.now(),this.lastPos=[0,0],this.boxEnabled=!1,this.boxInited=!1,this.boxStart=[0,0],this.boxEnd=[0,0],this.dragStart=[0,0]}t.exports=function(t){var e=t.mouseContainer,r=t.glplot,u=new l(e,r);function c(){t.xaxis.autorange=!1,t.yaxis.autorange=!1}function f(e,n,i){var a,s,l=t.calcDataBox(),f=r.viewBox,h=u.lastPos[0],p=u.lastPos[1],d=o.MINDRAG*r.pixelRatio,v=o.MINZOOM*r.pixelRatio;function g(e,r,n){var i=Math.min(r,n),a=Math.max(r,n);i!==a?(l[e]=i,l[e+2]=a,u.dataBox=l,t.setRanges(l)):(t.selectBox.selectBox=[0,0,1,1],t.glplot.setDirty())}switch(n*=r.pixelRatio,i*=r.pixelRatio,i=f[3]-f[1]-i,t.fullLayout.dragmode){case\"zoom\":if(e){var y=n/(f[2]-f[0])*(l[2]-l[0])+l[0],m=i/(f[3]-f[1])*(l[3]-l[1])+l[1];u.boxInited||(u.boxStart[0]=y,u.boxStart[1]=m,u.dragStart[0]=n,u.dragStart[1]=i),u.boxEnd[0]=y,u.boxEnd[1]=m,u.boxInited=!0,u.boxEnabled||u.boxStart[0]===u.boxEnd[0]&&u.boxStart[1]===u.boxEnd[1]||(u.boxEnabled=!0);var x=Math.abs(u.dragStart[0]-n)<v,b=Math.abs(u.dragStart[1]-i)<v;if(!function(){for(var e=t.graphDiv._fullLayout._axisConstraintGroups,r=t.xaxis._id,n=t.yaxis._id,i=0;i<e.length;i++)if(-1!==e[i][r]){if(-1!==e[i][n])return!0;break}return!1}()||x&&b)x&&(u.boxEnd[0]=u.boxStart[0]),b&&(u.boxEnd[1]=u.boxStart[1]);else{a=u.boxEnd[0]-u.boxStart[0],s=u.boxEnd[1]-u.boxStart[1];var _=(l[3]-l[1])/(l[2]-l[0]);Math.abs(a*_)>Math.abs(s)?(u.boxEnd[1]=u.boxStart[1]+Math.abs(a)*_*(s>=0?1:-1),u.boxEnd[1]<l[1]?(u.boxEnd[1]=l[1],u.boxEnd[0]=u.boxStart[0]+(l[1]-u.boxStart[1])/Math.abs(_)):u.boxEnd[1]>l[3]&&(u.boxEnd[1]=l[3],u.boxEnd[0]=u.boxStart[0]+(l[3]-u.boxStart[1])/Math.abs(_))):(u.boxEnd[0]=u.boxStart[0]+Math.abs(s)/_*(a>=0?1:-1),u.boxEnd[0]<l[0]?(u.boxEnd[0]=l[0],u.boxEnd[1]=u.boxStart[1]+(l[0]-u.boxStart[0])*Math.abs(_)):u.boxEnd[0]>l[2]&&(u.boxEnd[0]=l[2],u.boxEnd[1]=u.boxStart[1]+(l[2]-u.boxStart[0])*Math.abs(_)))}}else u.boxEnabled?(a=u.boxStart[0]!==u.boxEnd[0],s=u.boxStart[1]!==u.boxEnd[1],a||s?(a&&(g(0,u.boxStart[0],u.boxEnd[0]),t.xaxis.autorange=!1),s&&(g(1,u.boxStart[1],u.boxEnd[1]),t.yaxis.autorange=!1),t.relayoutCallback()):t.glplot.setDirty(),u.boxEnabled=!1,u.boxInited=!1):u.boxInited&&(u.boxInited=!1);break;case\"pan\":u.boxEnabled=!1,u.boxInited=!1,e?(u.panning||(u.dragStart[0]=n,u.dragStart[1]=i),Math.abs(u.dragStart[0]-n)<d&&(n=u.dragStart[0]),Math.abs(u.dragStart[1]-i)<d&&(i=u.dragStart[1]),a=(h-n)*(l[2]-l[0])/(r.viewBox[2]-r.viewBox[0]),s=(p-i)*(l[3]-l[1])/(r.viewBox[3]-r.viewBox[1]),l[0]+=a,l[2]+=a,l[1]+=s,l[3]+=s,t.setRanges(l),u.panning=!0,u.lastInputTime=Date.now(),c(),t.cameraChanged(),t.handleAnnotations()):u.panning&&(u.panning=!1,t.relayoutCallback())}u.lastPos[0]=n,u.lastPos[1]=i}return u.mouseListener=n(e,f),e.addEventListener(\"touchstart\",(function(t){var r=a(t.changedTouches[0],e);f(0,r[0],r[1]),f(1,r[0],r[1]),t.preventDefault()}),!!s&&{passive:!1}),e.addEventListener(\"touchmove\",(function(t){t.preventDefault();var r=a(t.changedTouches[0],e);f(1,r[0],r[1]),t.preventDefault()}),!!s&&{passive:!1}),e.addEventListener(\"touchend\",(function(t){f(0,u.lastPos[0],u.lastPos[1]),t.preventDefault()}),!!s&&{passive:!1}),u.wheelListener=i(e,(function(e,n){if(!t.scrollZoom)return!1;var i=t.calcDataBox(),a=r.viewBox,o=u.lastPos[0],s=u.lastPos[1],l=Math.exp(5*n/(a[3]-a[1])),f=o/(a[2]-a[0])*(i[2]-i[0])+i[0],h=s/(a[3]-a[1])*(i[3]-i[1])+i[1];return i[0]=(i[0]-f)*l+f,i[2]=(i[2]-f)*l+f,i[1]=(i[1]-h)*l+h,i[3]=(i[3]-h)*l+h,t.setRanges(i),u.lastInputTime=Date.now(),c(),t.cameraChanged(),t.handleAnnotations(),t.relayoutCallback(),!0}),!0),u}},92568:function(t,e,r){\"use strict\";var n=r(54460),i=r(43080);function a(t){this.scene=t,this.gl=t.gl,this.pixelRatio=t.pixelRatio,this.screenBox=[0,0,1,1],this.viewBox=[0,0,1,1],this.dataBox=[-1,-1,1,1],this.borderLineEnable=[!1,!1,!1,!1],this.borderLineWidth=[1,1,1,1],this.borderLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.ticks=[[],[]],this.tickEnable=[!0,!0,!1,!1],this.tickPad=[15,15,15,15],this.tickAngle=[0,0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickMarkLength=[0,0,0,0],this.tickMarkWidth=[0,0,0,0],this.tickMarkColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labels=[\"x\",\"y\"],this.labelEnable=[!0,!0,!1,!1],this.labelAngle=[0,Math.PI/2,0,3*Math.PI/2],this.labelPad=[15,15,15,15],this.labelSize=[12,12],this.labelFont=[\"sans-serif\",\"sans-serif\"],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.title=\"\",this.titleEnable=!0,this.titleCenter=[0,0,0,0],this.titleAngle=0,this.titleColor=[0,0,0,1],this.titleFont=\"sans-serif\",this.titleSize=18,this.gridLineEnable=[!0,!0],this.gridLineColor=[[0,0,0,.5],[0,0,0,.5]],this.gridLineWidth=[1,1],this.zeroLineEnable=[!0,!0],this.zeroLineWidth=[1,1],this.zeroLineColor=[[0,0,0,1],[0,0,0,1]],this.borderColor=[0,0,0,0],this.backgroundColor=[0,0,0,0],this.static=this.scene.staticPlot}var o=a.prototype,s=[\"xaxis\",\"yaxis\"];o.merge=function(t){var e,r,n,a,o,l,u,c,f,h,p;for(this.titleEnable=!1,this.backgroundColor=i(t.plot_bgcolor),h=0;h<2;++h){var d=(e=s[h]).charAt(0);for(n=(r=t[this.scene[e]._name]).title.text===this.scene.fullLayout._dfltTitle[d]?\"\":r.title.text,p=0;p<=2;p+=2)this.labelEnable[h+p]=!1,this.labels[h+p]=n,this.labelColor[h+p]=i(r.title.font.color),this.labelFont[h+p]=r.title.font.family,this.labelSize[h+p]=r.title.font.size,this.labelPad[h+p]=this.getLabelPad(e,r),this.tickEnable[h+p]=!1,this.tickColor[h+p]=i((r.tickfont||{}).color),this.tickAngle[h+p]=\"auto\"===r.tickangle?0:Math.PI*-r.tickangle/180,this.tickPad[h+p]=this.getTickPad(r),this.tickMarkLength[h+p]=0,this.tickMarkWidth[h+p]=r.tickwidth||0,this.tickMarkColor[h+p]=i(r.tickcolor),this.borderLineEnable[h+p]=!1,this.borderLineColor[h+p]=i(r.linecolor),this.borderLineWidth[h+p]=r.linewidth||0;u=this.hasSharedAxis(r),o=this.hasAxisInDfltPos(e,r)&&!u,l=this.hasAxisInAltrPos(e,r)&&!u,a=r.mirror||!1,c=u?-1!==String(a).indexOf(\"all\"):!!a,f=u?\"allticks\"===a:-1!==String(a).indexOf(\"ticks\"),o?this.labelEnable[h]=!0:l&&(this.labelEnable[h+2]=!0),o?this.tickEnable[h]=r.showticklabels:l&&(this.tickEnable[h+2]=r.showticklabels),(o||c)&&(this.borderLineEnable[h]=r.showline),(l||c)&&(this.borderLineEnable[h+2]=r.showline),(o||f)&&(this.tickMarkLength[h]=this.getTickMarkLength(r)),(l||f)&&(this.tickMarkLength[h+2]=this.getTickMarkLength(r)),this.gridLineEnable[h]=r.showgrid,this.gridLineColor[h]=i(r.gridcolor),this.gridLineWidth[h]=r.gridwidth,this.zeroLineEnable[h]=r.zeroline,this.zeroLineColor[h]=i(r.zerolinecolor),this.zeroLineWidth[h]=r.zerolinewidth}},o.hasSharedAxis=function(t){var e=this.scene,r=e.fullLayout._subplots.gl2d;return 0!==n.findSubplotsWithAxis(r,t).indexOf(e.id)},o.hasAxisInDfltPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"bottom\"===r:\"yaxis\"===t?\"left\"===r:void 0},o.hasAxisInAltrPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"top\"===r:\"yaxis\"===t?\"right\"===r:void 0},o.getLabelPad=function(t,e){var r=1.5,n=e.title.font.size,i=e.showticklabels;return\"xaxis\"===t?\"top\"===e.side?n*(r+(i?1:0))-10:n*(r+(i?.5:0))-10:\"yaxis\"===t?\"right\"===e.side?10+n*(r+(i?1:.5)):10+n*(r+(i?.5:0)):void 0},o.getTickPad=function(t){return\"outside\"===t.ticks?10+t.ticklen:15},o.getTickMarkLength=function(t){if(!t.ticks)return 0;var e=t.ticklen;return\"inside\"===t.ticks?-e:e},t.exports=function(t){return new a(t)}},39952:function(t,e,r){\"use strict\";var n=r(67824).overrideAll,i=r(17188),a=r(64859),o=r(9616),s=r(33816),l=r(57952),u=r(65460),c=r(84888).op;e.name=\"gl2d\",e.attr=[\"xaxis\",\"yaxis\"],e.idRoot=[\"x\",\"y\"],e.idRegex=s.idRegex,e.attrRegex=s.attrRegex,e.attributes=r(26720),e.supplyLayoutDefaults=function(t,e,r){e._has(\"cartesian\")||l.supplyLayoutDefaults(t,e,r)},e.layoutAttrOverrides=n(l.layoutAttributes,\"plot\",\"from-root\"),e.baseLayoutAttrOverrides=n({plot_bgcolor:a.plot_bgcolor,hoverlabel:u.hoverlabel},\"plot\",\"nested\"),e.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=e._subplots.gl2d,a=0;a<n.length;a++){var o=n[a],s=e._plots[o],l=c(r,\"gl2d\",o),u=s._scene2d;void 0===u&&(u=new i({id:o,graphDiv:t,container:t.querySelector(\".gl-container\"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio},e),s._scene2d=u),u.plot(l,t.calcdata,e,t.layout)}},e.clean=function(t,e,r,n){for(var i=n._subplots.gl2d||[],a=0;a<i.length;a++){var o=i[a],s=n._plots[o];s._scene2d&&0===c(t,\"gl2d\",o).length&&(s._scene2d.destroy(),delete n._plots[o])}l.clean.apply(this,arguments)},e.drawFramework=function(t){t._context.staticPlot||l.drawFramework(t)},e.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots.gl2d,n=0;n<r.length;n++){var i=e._plots[r[n]]._scene2d,a=i.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:o.svg,\"xlink:href\":a,x:0,y:0,width:\"100%\",height:\"100%\",preserveAspectRatio:\"none\"}),i.destroy()}},e.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots.gl2d,n=0;n<r.length;n++)e._plots[r[n]]._scene2d.updateFx(e.dragmode)}},17188:function(t,e,r){\"use strict\";var n,i,a=r(24040),o=r(54460),s=r(93024),l=r(67792).gl_plot2d,u=r(67792).gl_spikes2d,c=r(67792).gl_select_box,f=r(5408),h=r(92568),p=r(2428),d=r(16576),v=r(71888),g=v.enforce,y=v.clean,m=r(19280).doAutoRange,x=r(72760),b=x.drawMode,_=x.selectMode,w=[\"xaxis\",\"yaxis\"],T=r(33816).SUBPLOT_PATTERN;function k(t,e){this.container=t.container,this.graphDiv=t.graphDiv,this.pixelRatio=t.plotGlPixelRatio||window.devicePixelRatio,this.id=t.id,this.staticPlot=!!t.staticPlot,this.scrollZoom=this.graphDiv._context._scrollZoom.cartesian,this.fullData=null,this.updateRefs(e),this.makeFramework(),this.stopped||(this.glplotOptions=h(this),this.glplotOptions.merge(e),this.glplot=l(this.glplotOptions),this.camera=p(this),this.traces={},this.spikes=u(this.glplot),this.selectBox=c(this.glplot,{innerFill:!1,outerFill:!0}),this.lastButtonState=0,this.pickResult=null,this.isMouseOver=!0,this.stopped=!1,this.redraw=this.draw.bind(this),this.redraw())}t.exports=k;var A=k.prototype;A.makeFramework=function(){if(this.staticPlot){if(!(i||(n=document.createElement(\"canvas\"),i=f({canvas:n,preserveDrawingBuffer:!1,premultipliedAlpha:!0,antialias:!0}))))throw new Error(\"Error creating static canvas/context for image server\");this.canvas=n,this.gl=i}else{var t=this.container.querySelector(\".gl-canvas-focus\"),e=f({canvas:t,preserveDrawingBuffer:!0,premultipliedAlpha:!0});if(!e)return d(this),void(this.stopped=!0);this.canvas=t,this.gl=e}var r=this.canvas;r.style.width=\"100%\",r.style.height=\"100%\",r.style.position=\"absolute\",r.style.top=\"0px\",r.style.left=\"0px\",r.style[\"pointer-events\"]=\"none\",this.updateSize(r);var a=this.svgContainer=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");a.style.position=\"absolute\",a.style.top=a.style.left=\"0px\",a.style.width=a.style.height=\"100%\",a.style[\"z-index\"]=20,a.style[\"pointer-events\"]=\"none\";var o=this.mouseContainer=document.createElement(\"div\");o.style.position=\"absolute\",o.style[\"pointer-events\"]=\"auto\",this.pickCanvas=this.container.querySelector(\".gl-canvas-pick\");var s=this.container;s.appendChild(a),s.appendChild(o);var l=this;o.addEventListener(\"mouseout\",(function(){l.isMouseOver=!1,l.unhover()})),o.addEventListener(\"mouseover\",(function(){l.isMouseOver=!0}))},A.toImage=function(t){t||(t=\"png\"),this.stopped=!0,this.staticPlot&&this.container.appendChild(n),this.updateSize(this.canvas);var e=this.glplot.gl,r=e.drawingBufferWidth,i=e.drawingBufferHeight;e.clearColor(1,1,1,0),e.clear(e.COLOR_BUFFER_BIT|e.DEPTH_BUFFER_BIT),this.glplot.setDirty(),this.glplot.draw(),e.bindFramebuffer(e.FRAMEBUFFER,null);var a=new Uint8Array(r*i*4);e.readPixels(0,0,r,i,e.RGBA,e.UNSIGNED_BYTE,a);for(var o=0,s=i-1;o<s;++o,--s)for(var l=0;l<r;++l)for(var u=0;u<4;++u){var c=a[4*(r*o+l)+u];a[4*(r*o+l)+u]=a[4*(r*s+l)+u],a[4*(r*s+l)+u]=c}var f=document.createElement(\"canvas\");f.width=r,f.height=i;var h,p=f.getContext(\"2d\",{willReadFrequently:!0}),d=p.createImageData(r,i);switch(d.data.set(a),p.putImageData(d,0,0),t){case\"jpeg\":h=f.toDataURL(\"image/jpeg\");break;case\"webp\":h=f.toDataURL(\"image/webp\");break;default:h=f.toDataURL(\"image/png\")}return this.staticPlot&&this.container.removeChild(n),h},A.updateSize=function(t){t||(t=this.canvas);var e=this.pixelRatio,r=this.fullLayout,n=r.width,i=r.height,a=0|Math.ceil(e*n),o=0|Math.ceil(e*i);return t.width===a&&t.height===o||(t.width=a,t.height=o),t},A.computeTickMarks=function(){this.xaxis.setScale(),this.yaxis.setScale();for(var t=[o.calcTicks(this.xaxis),o.calcTicks(this.yaxis)],e=0;e<2;++e)for(var r=0;r<t[e].length;++r)t[e][r].text=t[e][r].text+\"\";return t},A.updateRefs=function(t){this.fullLayout=t;var e=this.id.match(T),r=\"xaxis\"+e[1],n=\"yaxis\"+e[2];this.xaxis=this.fullLayout[r],this.yaxis=this.fullLayout[n]},A.relayoutCallback=function(){var t=this.graphDiv,e=this.xaxis,r=this.yaxis,n=t.layout,i={},o=i[e._name+\".range\"]=e.range.slice(),s=i[r._name+\".range\"]=r.range.slice();i[e._name+\".autorange\"]=e.autorange,i[r._name+\".autorange\"]=r.autorange,a.call(\"_storeDirectGUIEdit\",t.layout,t._fullLayout._preGUI,i);var l=n[e._name];l.range=o,l.autorange=e.autorange;var u=n[r._name];u.range=s,u.autorange=r.autorange,i.lastInputTime=this.camera.lastInputTime,t.emit(\"plotly_relayout\",i)},A.cameraChanged=function(){var t=this.camera;this.glplot.setDataBox(this.calcDataBox());var e=this.computeTickMarks();(function(t,e){for(var r=0;r<2;++r){var n=t[r],i=e[r];if(n.length!==i.length)return!0;for(var a=0;a<n.length;++a)if(n[a].x!==i[a].x)return!0}return!1})(e,this.glplotOptions.ticks)&&(this.glplotOptions.ticks=e,this.glplotOptions.dataBox=t.dataBox,this.glplot.update(this.glplotOptions),this.handleAnnotations())},A.handleAnnotations=function(){for(var t=this.graphDiv,e=this.fullLayout.annotations,r=0;r<e.length;r++){var n=e[r];n.xref===this.xaxis._id&&n.yref===this.yaxis._id&&a.getComponentMethod(\"annotations\",\"drawOne\")(t,r)}},A.destroy=function(){if(this.glplot){var t=this.traces;t&&Object.keys(t).map((function(e){t[e].dispose(),delete t[e]})),this.glplot.dispose(),this.container.removeChild(this.svgContainer),this.container.removeChild(this.mouseContainer),this.fullData=null,this.glplot=null,this.stopped=!0,this.camera.mouseListener.enabled=!1,this.mouseContainer.removeEventListener(\"wheel\",this.camera.wheelListener),this.camera=null}},A.plot=function(t,e,r){var n=this.glplot;this.updateRefs(r),this.xaxis.clearCalc(),this.yaxis.clearCalc(),this.updateTraces(t,e),this.updateFx(r.dragmode);var i=r.width,a=r.height;this.updateSize(this.canvas);var o=this.glplotOptions;o.merge(r),o.screenBox=[0,0,i,a];var s={_fullLayout:{_axisConstraintGroups:r._axisConstraintGroups,xaxis:this.xaxis,yaxis:this.yaxis,_size:r._size}};y(s,this.xaxis),y(s,this.yaxis);var l,u,c=r._size,f=this.xaxis.domain,h=this.yaxis.domain;for(o.viewBox=[c.l+f[0]*c.w,c.b+h[0]*c.h,i-c.r-(1-f[1])*c.w,a-c.t-(1-h[1])*c.h],this.mouseContainer.style.width=c.w*(f[1]-f[0])+\"px\",this.mouseContainer.style.height=c.h*(h[1]-h[0])+\"px\",this.mouseContainer.height=c.h*(h[1]-h[0]),this.mouseContainer.style.left=c.l+f[0]*c.w+\"px\",this.mouseContainer.style.top=c.t+(1-h[1])*c.h+\"px\",u=0;u<2;++u)(l=this[w[u]])._length=o.viewBox[u+2]-o.viewBox[u],m(this.graphDiv,l),l.setScale();g(s),o.ticks=this.computeTickMarks(),o.dataBox=this.calcDataBox(),o.merge(r),n.update(o),this.glplot.draw()},A.calcDataBox=function(){var t=this.xaxis,e=this.yaxis,r=t.range,n=e.range,i=t.r2l,a=e.r2l;return[i(r[0]),a(n[0]),i(r[1]),a(n[1])]},A.setRanges=function(t){var e=this.xaxis,r=this.yaxis,n=e.l2r,i=r.l2r;e.range=[n(t[0]),n(t[2])],r.range=[i(t[1]),i(t[3])]},A.updateTraces=function(t,e){var r,n,i,a=Object.keys(this.traces);this.fullData=t;t:for(r=0;r<a.length;r++){var o=a[r],s=this.traces[o];for(n=0;n<t.length;n++)if((i=t[n]).uid===o&&i.type===s.type)continue t;s.dispose(),delete this.traces[o]}for(r=0;r<t.length;r++){i=t[r];var l=e[r],u=this.traces[i.uid];u?u.update(i,l):(u=i._module.plot(this,i,l),this.traces[i.uid]=u)}this.glplot.objects.sort((function(t,e){return t._trace.index-e._trace.index}))},A.updateFx=function(t){_(t)||b(t)?(this.pickCanvas.style[\"pointer-events\"]=\"none\",this.mouseContainer.style[\"pointer-events\"]=\"none\"):(this.pickCanvas.style[\"pointer-events\"]=\"auto\",this.mouseContainer.style[\"pointer-events\"]=\"auto\"),this.mouseContainer.style.cursor=\"pan\"===t?\"move\":\"zoom\"===t?\"crosshair\":null},A.emitPointAction=function(t,e){for(var r,n=t.trace.uid,i=t.pointIndex,a=0;a<this.fullData.length;a++)this.fullData[a].uid===n&&(r=this.fullData[a]);var o={x:t.traceCoord[0],y:t.traceCoord[1],curveNumber:r.index,pointNumber:i,data:r._input,fullData:this.fullData,xaxis:this.xaxis,yaxis:this.yaxis};s.appendArrayPointValue(o,r,i),this.graphDiv.emit(e,{points:[o]})},A.draw=function(){if(!this.stopped){requestAnimationFrame(this.redraw);var t=this.glplot,e=this.camera,r=e.mouseListener,n=1===this.lastButtonState&&0===r.buttons,i=this.fullLayout;this.lastButtonState=r.buttons,this.cameraChanged();var a,o=r.x*t.pixelRatio,l=this.canvas.height-t.pixelRatio*r.y;if(e.boxEnabled&&\"zoom\"===i.dragmode){this.selectBox.enabled=!0;for(var u=this.selectBox.selectBox=[Math.min(e.boxStart[0],e.boxEnd[0]),Math.min(e.boxStart[1],e.boxEnd[1]),Math.max(e.boxStart[0],e.boxEnd[0]),Math.max(e.boxStart[1],e.boxEnd[1])],c=0;c<2;c++)e.boxStart[c]===e.boxEnd[c]&&(u[c]=t.dataBox[c],u[c+2]=t.dataBox[c+2]);t.setDirty()}else if(!e.panning&&this.isMouseOver){this.selectBox.enabled=!1;var f=i._size,h=this.xaxis.domain,p=this.yaxis.domain,d=(a=t.pick(o/t.pixelRatio+f.l+h[0]*f.w,l/t.pixelRatio-(f.t+(1-p[1])*f.h)))&&a.object._trace.handlePick(a);if(d&&n&&this.emitPointAction(d,\"plotly_click\"),a&&\"skip\"!==a.object._trace.hoverinfo&&i.hovermode&&d&&(!this.lastPickResult||this.lastPickResult.traceUid!==d.trace.uid||this.lastPickResult.dataCoord[0]!==d.dataCoord[0]||this.lastPickResult.dataCoord[1]!==d.dataCoord[1])){var v=d;this.lastPickResult={traceUid:d.trace?d.trace.uid:null,dataCoord:d.dataCoord.slice()},this.spikes.update({center:a.dataCoord}),v.screenCoord=[((t.viewBox[2]-t.viewBox[0])*(a.dataCoord[0]-t.dataBox[0])/(t.dataBox[2]-t.dataBox[0])+t.viewBox[0])/t.pixelRatio,(this.canvas.height-(t.viewBox[3]-t.viewBox[1])*(a.dataCoord[1]-t.dataBox[1])/(t.dataBox[3]-t.dataBox[1])-t.viewBox[1])/t.pixelRatio],this.emitPointAction(d,\"plotly_hover\");var g=this.fullData[v.trace.index]||{},y=v.pointIndex,m=s.castHoverinfo(g,i,y);if(m&&\"all\"!==m){var x=m.split(\"+\");-1===x.indexOf(\"x\")&&(v.traceCoord[0]=void 0),-1===x.indexOf(\"y\")&&(v.traceCoord[1]=void 0),-1===x.indexOf(\"z\")&&(v.traceCoord[2]=void 0),-1===x.indexOf(\"text\")&&(v.textLabel=void 0),-1===x.indexOf(\"name\")&&(v.name=void 0)}s.loneHover({x:v.screenCoord[0],y:v.screenCoord[1],xLabel:this.hoverFormatter(\"xaxis\",v.traceCoord[0]),yLabel:this.hoverFormatter(\"yaxis\",v.traceCoord[1]),zLabel:v.traceCoord[2],text:v.textLabel,name:v.name,color:s.castHoverOption(g,y,\"bgcolor\")||v.color,borderColor:s.castHoverOption(g,y,\"bordercolor\"),fontFamily:s.castHoverOption(g,y,\"font.family\"),fontSize:s.castHoverOption(g,y,\"font.size\"),fontColor:s.castHoverOption(g,y,\"font.color\"),nameLength:s.castHoverOption(g,y,\"namelength\"),textAlign:s.castHoverOption(g,y,\"align\")},{container:this.svgContainer,gd:this.graphDiv})}}a||this.unhover(),t.draw()}},A.unhover=function(){this.lastPickResult&&(this.spikes.update({}),this.lastPickResult=null,this.graphDiv.emit(\"plotly_unhover\"),s.loneUnhover(this.svgContainer))},A.hoverFormatter=function(t,e){if(void 0!==e){var r=this[t];return o.tickText(r,r.c2l(e),\"hover\").text}}},12536:function(t,e,r){\"use strict\";var n=r(67824).overrideAll,i=r(65460),a=r(98432),o=r(84888).op,s=r(3400),l=r(9616),u=\"gl3d\",c=\"scene\";e.name=u,e.attr=c,e.idRoot=c,e.idRegex=e.attrRegex=s.counterRegex(\"scene\"),e.attributes=r(6636),e.layoutAttributes=r(346),e.baseLayoutAttrOverrides=n({hoverlabel:i.hoverlabel},\"plot\",\"nested\"),e.supplyLayoutDefaults=r(5208),e.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=e._subplots[u],i=0;i<n.length;i++){var s=n[i],l=o(r,u,s),c=e[s],f=c.camera,h=c._scene;h||(h=new a({id:s,graphDiv:t,container:t.querySelector(\".gl-container\"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio,camera:f},e),c._scene=h),h.viewInitial||(h.viewInitial={up:{x:f.up.x,y:f.up.y,z:f.up.z},eye:{x:f.eye.x,y:f.eye.y,z:f.eye.z},center:{x:f.center.x,y:f.center.y,z:f.center.z}}),h.plot(l,e,t.layout)}},e.clean=function(t,e,r,n){for(var i=n._subplots[u]||[],a=0;a<i.length;a++){var o=i[a];!e[o]&&n[o]._scene&&(n[o]._scene.destroy(),n._infolayer&&n._infolayer.selectAll(\".annotation-\"+o).remove())}},e.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots[u],n=e._size,i=0;i<r.length;i++){var a=e[r[i]],o=a.domain,s=a._scene,c=s.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:l.svg,\"xlink:href\":c,x:n.l+n.w*o.x[0],y:n.t+n.h*(1-o.y[1]),width:n.w*(o.x[1]-o.x[0]),height:n.h*(o.y[1]-o.y[0]),preserveAspectRatio:\"none\"}),s.destroy()}},e.cleanId=function(t){if(t.match(/^scene[0-9]*$/)){var e=t.substr(5);return\"1\"===e&&(e=\"\"),c+e}},e.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots[u],n=0;n<r.length;n++)e[r[n]]._scene.updateFx(e.dragmode,e.hovermode)}},6636:function(t){\"use strict\";t.exports={scene:{valType:\"subplotid\",dflt:\"scene\",editType:\"calc+clearAxisTypes\"}}},86140:function(t,e,r){\"use strict\";var n=r(76308),i=r(94724),a=r(92880).extendFlat,o=r(67824).overrideAll;t.exports=o({visible:i.visible,showspikes:{valType:\"boolean\",dflt:!0},spikesides:{valType:\"boolean\",dflt:!0},spikethickness:{valType:\"number\",min:0,dflt:2},spikecolor:{valType:\"color\",dflt:n.defaultLine},showbackground:{valType:\"boolean\",dflt:!1},backgroundcolor:{valType:\"color\",dflt:\"rgba(204, 204, 204, 0.5)\"},showaxeslabels:{valType:\"boolean\",dflt:!0},color:i.color,categoryorder:i.categoryorder,categoryarray:i.categoryarray,title:{text:i.title.text,font:i.title.font},type:a({},i.type,{values:[\"-\",\"linear\",\"log\",\"date\",\"category\"]}),autotypenumbers:i.autotypenumbers,autorange:i.autorange,autorangeoptions:{minallowed:i.autorangeoptions.minallowed,maxallowed:i.autorangeoptions.maxallowed,clipmin:i.autorangeoptions.clipmin,clipmax:i.autorangeoptions.clipmax,include:i.autorangeoptions.include,editType:\"plot\"},rangemode:i.rangemode,minallowed:i.minallowed,maxallowed:i.maxallowed,range:a({},i.range,{items:[{valType:\"any\",editType:\"plot\",impliedEdits:{\"^autorange\":!1}},{valType:\"any\",editType:\"plot\",impliedEdits:{\"^autorange\":!1}}],anim:!1}),tickmode:i.minor.tickmode,nticks:i.nticks,tick0:i.tick0,dtick:i.dtick,tickvals:i.tickvals,ticktext:i.ticktext,ticks:i.ticks,mirror:i.mirror,ticklen:i.ticklen,tickwidth:i.tickwidth,tickcolor:i.tickcolor,showticklabels:i.showticklabels,labelalias:i.labelalias,tickfont:i.tickfont,tickangle:i.tickangle,tickprefix:i.tickprefix,showtickprefix:i.showtickprefix,ticksuffix:i.ticksuffix,showticksuffix:i.showticksuffix,showexponent:i.showexponent,exponentformat:i.exponentformat,minexponent:i.minexponent,separatethousands:i.separatethousands,tickformat:i.tickformat,tickformatstops:i.tickformatstops,hoverformat:i.hoverformat,showline:i.showline,linecolor:i.linecolor,linewidth:i.linewidth,showgrid:i.showgrid,gridcolor:a({},i.gridcolor,{dflt:\"rgb(204, 204, 204)\"}),gridwidth:i.gridwidth,zeroline:i.zeroline,zerolinecolor:i.zerolinecolor,zerolinewidth:i.zerolinewidth,_deprecated:{title:i._deprecated.title,titlefont:i._deprecated.titlefont}},\"plot\",\"from-root\")},64380:function(t,e,r){\"use strict\";var n=r(49760).mix,i=r(3400),a=r(31780),o=r(86140),s=r(14944),l=r(28336),u=[\"xaxis\",\"yaxis\",\"zaxis\"];t.exports=function(t,e,r){var c,f;function h(t,e){return i.coerce(c,f,o,t,e)}for(var p=0;p<u.length;p++){var d=u[p];c=t[d]||{},(f=a.newContainer(e,d))._id=d[0]+r.scene,f._name=d,s(c,f,h,r),l(c,f,h,{font:r.font,letter:d[0],data:r.data,showGrid:!0,noAutotickangles:!0,noTickson:!0,noTicklabelmode:!0,noTicklabelstep:!0,noTicklabelposition:!0,noTicklabeloverflow:!0,noInsiderange:!0,bgColor:r.bgColor,calendar:r.calendar},r.fullLayout),h(\"gridcolor\",n(f.color,r.bgColor,72.72727272727273).toRgbString()),h(\"title.text\",d[0]),f.setScale=i.noop,h(\"showspikes\")&&(h(\"spikesides\"),h(\"spikethickness\"),h(\"spikecolor\",f.color)),h(\"showaxeslabels\"),h(\"showbackground\")&&h(\"backgroundcolor\")}}},44728:function(t,e,r){\"use strict\";var n=r(43080),i=r(3400),a=[\"xaxis\",\"yaxis\",\"zaxis\"];function o(){this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[18,18,18],this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=[\"Open Sans\",\"Open Sans\",\"Open Sans\"],this.labelSize=[20,20,20],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[30,30,30],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[10,10,10],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!0,!0,!0],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._defaultTickPad=this.tickPad.slice(),this._defaultLabelPad=this.labelPad.slice(),this._defaultLineTickLength=this.lineTickLength.slice()}o.prototype.merge=function(t,e){for(var r=this,o=0;o<3;++o){var s=e[a[o]];s.visible?(r.labels[o]=t._meta?i.templateString(s.title.text,t._meta):s.title.text,\"font\"in s.title&&(s.title.font.color&&(r.labelColor[o]=n(s.title.font.color)),s.title.font.family&&(r.labelFont[o]=s.title.font.family),s.title.font.size&&(r.labelSize[o]=s.title.font.size)),\"showline\"in s&&(r.lineEnable[o]=s.showline),\"linecolor\"in s&&(r.lineColor[o]=n(s.linecolor)),\"linewidth\"in s&&(r.lineWidth[o]=s.linewidth),\"showgrid\"in s&&(r.gridEnable[o]=s.showgrid),\"gridcolor\"in s&&(r.gridColor[o]=n(s.gridcolor)),\"gridwidth\"in s&&(r.gridWidth[o]=s.gridwidth),\"log\"===s.type?r.zeroEnable[o]=!1:\"zeroline\"in s&&(r.zeroEnable[o]=s.zeroline),\"zerolinecolor\"in s&&(r.zeroLineColor[o]=n(s.zerolinecolor)),\"zerolinewidth\"in s&&(r.zeroLineWidth[o]=s.zerolinewidth),\"ticks\"in s&&s.ticks?r.lineTickEnable[o]=!0:r.lineTickEnable[o]=!1,\"ticklen\"in s&&(r.lineTickLength[o]=r._defaultLineTickLength[o]=s.ticklen),\"tickcolor\"in s&&(r.lineTickColor[o]=n(s.tickcolor)),\"tickwidth\"in s&&(r.lineTickWidth[o]=s.tickwidth),\"tickangle\"in s&&(r.tickAngle[o]=\"auto\"===s.tickangle?-3600:Math.PI*-s.tickangle/180),\"showticklabels\"in s&&(r.tickEnable[o]=s.showticklabels),\"tickfont\"in s&&(s.tickfont.color&&(r.tickColor[o]=n(s.tickfont.color)),s.tickfont.family&&(r.tickFont[o]=s.tickfont.family),s.tickfont.size&&(r.tickSize[o]=s.tickfont.size)),\"mirror\"in s?-1!==[\"ticks\",\"all\",\"allticks\"].indexOf(s.mirror)?(r.lineTickMirror[o]=!0,r.lineMirror[o]=!0):!0===s.mirror?(r.lineTickMirror[o]=!1,r.lineMirror[o]=!0):(r.lineTickMirror[o]=!1,r.lineMirror[o]=!1):r.lineMirror[o]=!1,\"showbackground\"in s&&!1!==s.showbackground?(r.backgroundEnable[o]=!0,r.backgroundColor[o]=n(s.backgroundcolor)):r.backgroundEnable[o]=!1):(r.tickEnable[o]=!1,r.labelEnable[o]=!1,r.lineEnable[o]=!1,r.lineTickEnable[o]=!1,r.gridEnable[o]=!1,r.zeroEnable[o]=!1,r.backgroundEnable[o]=!1)}},t.exports=function(t,e){var r=new o;return r.merge(t,e),r}},5208:function(t,e,r){\"use strict\";var n=r(3400),i=r(76308),a=r(24040),o=r(168),s=r(64380),l=r(346),u=r(84888).op,c=\"gl3d\";function f(t,e,r,n){for(var o=r(\"bgcolor\"),l=i.combine(o,n.paper_bgcolor),f=[\"up\",\"center\",\"eye\"],h=0;h<f.length;h++)r(\"camera.\"+f[h]+\".x\"),r(\"camera.\"+f[h]+\".y\"),r(\"camera.\"+f[h]+\".z\");r(\"camera.projection.type\");var p=!!r(\"aspectratio.x\")&&!!r(\"aspectratio.y\")&&!!r(\"aspectratio.z\"),d=r(\"aspectmode\",p?\"manual\":\"auto\");p||(t.aspectratio=e.aspectratio={x:1,y:1,z:1},\"manual\"===d&&(e.aspectmode=\"auto\"),t.aspectmode=e.aspectmode);var v=u(n.fullData,c,n.id);s(t,e,{font:n.font,scene:n.id,data:v,bgColor:l,calendar:n.calendar,autotypenumbersDflt:n.autotypenumbersDflt,fullLayout:n.fullLayout}),a.getComponentMethod(\"annotations3d\",\"handleDefaults\")(t,e,n);var g=n.getDfltFromLayout(\"dragmode\");if(!1!==g&&!g)if(g=\"orbit\",t.camera&&t.camera.up){var y=t.camera.up.x,m=t.camera.up.y,x=t.camera.up.z;0!==x&&(y&&m&&x?x/Math.sqrt(y*y+m*m+x*x)>.999&&(g=\"turntable\"):g=\"turntable\")}else g=\"turntable\";r(\"dragmode\",g),r(\"hovermode\",n.getDfltFromLayout(\"hovermode\"))}t.exports=function(t,e,r){var i=e._basePlotModules.length>1;o(t,e,r,{type:c,attributes:l,handleDefaults:f,fullLayout:e,font:e.font,fullData:r,getDfltFromLayout:function(e){if(!i)return n.validate(t[e],l[e])?t[e]:void 0},autotypenumbersDflt:e.autotypenumbers,paper_bgcolor:e.paper_bgcolor,calendar:e.calendar})}},346:function(t,e,r){\"use strict\";var n=r(86140),i=r(86968).u,a=r(92880).extendFlat,o=r(3400).counterRegex;function s(t,e,r){return{x:{valType:\"number\",dflt:t,editType:\"camera\"},y:{valType:\"number\",dflt:e,editType:\"camera\"},z:{valType:\"number\",dflt:r,editType:\"camera\"},editType:\"camera\"}}t.exports={_arrayAttrRegexps:[o(\"scene\",\".annotations\",!0)],bgcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\",editType:\"plot\"},camera:{up:a(s(0,0,1),{}),center:a(s(0,0,0),{}),eye:a(s(1.25,1.25,1.25),{}),projection:{type:{valType:\"enumerated\",values:[\"perspective\",\"orthographic\"],dflt:\"perspective\",editType:\"calc\"},editType:\"calc\"},editType:\"camera\"},domain:i({name:\"scene\",editType:\"plot\"}),aspectmode:{valType:\"enumerated\",values:[\"auto\",\"cube\",\"data\",\"manual\"],dflt:\"auto\",editType:\"plot\",impliedEdits:{\"aspectratio.x\":void 0,\"aspectratio.y\":void 0,\"aspectratio.z\":void 0}},aspectratio:{x:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},y:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},z:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},editType:\"plot\",impliedEdits:{aspectmode:\"manual\"}},xaxis:n,yaxis:n,zaxis:n,dragmode:{valType:\"enumerated\",values:[\"orbit\",\"turntable\",\"zoom\",\"pan\",!1],editType:\"plot\"},hovermode:{valType:\"enumerated\",values:[\"closest\",!1],dflt:\"closest\",editType:\"modebar\"},uirevision:{valType:\"any\",editType:\"none\"},editType:\"plot\",_deprecated:{cameraposition:{valType:\"info_array\",editType:\"camera\"}}}},9020:function(t,e,r){\"use strict\";var n=r(43080),i=[\"xaxis\",\"yaxis\",\"zaxis\"];function a(){this.enabled=[!0,!0,!0],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.drawSides=[!0,!0,!0],this.lineWidth=[1,1,1]}a.prototype.merge=function(t){for(var e=0;e<3;++e){var r=t[i[e]];r.visible?(this.enabled[e]=r.showspikes,this.colors[e]=n(r.spikecolor),this.drawSides[e]=r.spikesides,this.lineWidth[e]=r.spikethickness):(this.enabled[e]=!1,this.drawSides[e]=!1)}},t.exports=function(t){var e=new a;return e.merge(t),e}},87152:function(t,e,r){\"use strict\";t.exports=function(t){for(var e=t.axesOptions,r=t.glplot.axesPixels,s=t.fullSceneLayout,l=[[],[],[]],u=0;u<3;++u){var c=s[a[u]];if(c._length=(r[u].hi-r[u].lo)*r[u].pixelsPerDataUnit/t.dataScale[u],Math.abs(c._length)===1/0||isNaN(c._length))l[u]=[];else{c._input_range=c.range.slice(),c.range[0]=r[u].lo/t.dataScale[u],c.range[1]=r[u].hi/t.dataScale[u],c._m=1/(t.dataScale[u]*r[u].pixelsPerDataUnit),c.range[0]===c.range[1]&&(c.range[0]-=1,c.range[1]+=1);var f=c.tickmode;if(\"auto\"===c.tickmode){c.tickmode=\"linear\";var h=c.nticks||i.constrain(c._length/40,4,9);n.autoTicks(c,Math.abs(c.range[1]-c.range[0])/h)}for(var p=n.calcTicks(c,{msUTC:!0}),d=0;d<p.length;++d)p[d].x=p[d].x*t.dataScale[u],\"date\"===c.type&&(p[d].text=p[d].text.replace(/\\<br\\>/g,\" \"));l[u]=p,c.tickmode=f}}for(e.ticks=l,u=0;u<3;++u)for(o[u]=.5*(t.glplot.bounds[0][u]+t.glplot.bounds[1][u]),d=0;d<2;++d)e.bounds[d][u]=t.glplot.bounds[d][u];t.contourLevels=function(t){for(var e=new Array(3),r=0;r<3;++r){for(var n=t[r],i=new Array(n.length),a=0;a<n.length;++a)i[a]=n[a].x;e[r]=i}return e}(l)};var n=r(54460),i=r(3400),a=[\"xaxis\",\"yaxis\",\"zaxis\"],o=[0,0,0]},94424:function(t){\"use strict\";function e(t,e){var r,n,i=[0,0,0,0];for(r=0;r<4;++r)for(n=0;n<4;++n)i[n]+=t[4*r+n]*e[r];return i}t.exports=function(t,r){return e(t.projection,e(t.view,e(t.model,[r[0],r[1],r[2],1])))}},98432:function(t,e,r){\"use strict\";var n,i,a=r(67792).gl_plot3d,o=a.createCamera,s=a.createScene,l=r(5408),u=r(89184),c=r(24040),f=r(3400),h=f.preserveDrawingBuffer(),p=r(54460),d=r(93024),v=r(43080),g=r(16576),y=r(94424),m=r(44728),x=r(9020),b=r(87152),_=r(19280).applyAutorangeOptions,w=!1;function T(t,e){var r=document.createElement(\"div\"),n=t.container;this.graphDiv=t.graphDiv;var i=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");i.style.position=\"absolute\",i.style.top=i.style.left=\"0px\",i.style.width=i.style.height=\"100%\",i.style[\"z-index\"]=20,i.style[\"pointer-events\"]=\"none\",r.appendChild(i),this.svgContainer=i,r.id=t.id,r.style.position=\"absolute\",r.style.top=r.style.left=\"0px\",r.style.width=r.style.height=\"100%\",n.appendChild(r),this.fullLayout=e,this.id=t.id||\"scene\",this.fullSceneLayout=e[this.id],this.plotArgs=[[],{},{}],this.axesOptions=m(e,e[this.id]),this.spikeOptions=x(e[this.id]),this.container=r,this.staticMode=!!t.staticPlot,this.pixelRatio=this.pixelRatio||t.plotGlPixelRatio||2,this.dataScale=[1,1,1],this.contourLevels=[[],[],[]],this.convertAnnotations=c.getComponentMethod(\"annotations3d\",\"convert\"),this.drawAnnotations=c.getComponentMethod(\"annotations3d\",\"draw\"),this.initializeGLPlot()}var k=T.prototype;k.prepareOptions=function(){var t=this,e={canvas:t.canvas,gl:t.gl,glOptions:{preserveDrawingBuffer:h,premultipliedAlpha:!0,antialias:!0},container:t.container,axes:t.axesOptions,spikes:t.spikeOptions,pickRadius:10,snapToData:!0,autoScale:!0,autoBounds:!1,cameraObject:t.camera,pixelRatio:t.pixelRatio};if(t.staticMode){if(!(i||(n=document.createElement(\"canvas\"),i=l({canvas:n,preserveDrawingBuffer:!0,premultipliedAlpha:!0,antialias:!0}))))throw new Error(\"error creating static canvas/context for image server\");e.gl=i,e.canvas=n}return e};var A=!0;k.tryCreatePlot=function(){var t=this,e=t.prepareOptions(),r=!0;try{t.glplot=s(e)}catch(n){if(t.staticMode||!A||h)r=!1;else{f.warn([\"webgl setup failed possibly due to\",\"false preserveDrawingBuffer config.\",\"The mobile/tablet device may not be detected by is-mobile module.\",\"Enabling preserveDrawingBuffer in second attempt to create webgl scene...\"].join(\" \"));try{h=e.glOptions.preserveDrawingBuffer=!0,t.glplot=s(e)}catch(t){h=e.glOptions.preserveDrawingBuffer=!1,r=!1}}}return A=!1,r},k.initializeGLCamera=function(){var t=this,e=t.fullSceneLayout.camera,r=\"orthographic\"===e.projection.type;t.camera=o(t.container,{center:[e.center.x,e.center.y,e.center.z],eye:[e.eye.x,e.eye.y,e.eye.z],up:[e.up.x,e.up.y,e.up.z],_ortho:r,zoomMin:.01,zoomMax:100,mode:\"orbit\"})},k.initializeGLPlot=function(){var t=this;if(t.initializeGLCamera(),!t.tryCreatePlot())return g(t);t.traces={},t.make4thDimension();var e=t.graphDiv,r=e.layout,n=function(){var e={};return t.isCameraChanged(r)&&(e[t.id+\".camera\"]=t.getCamera()),t.isAspectChanged(r)&&(e[t.id+\".aspectratio\"]=t.glplot.getAspectratio(),\"manual\"!==r[t.id].aspectmode&&(t.fullSceneLayout.aspectmode=r[t.id].aspectmode=e[t.id+\".aspectmode\"]=\"manual\")),e},i=function(t){if(!1!==t.fullSceneLayout.dragmode){var e=n();t.saveLayout(r),t.graphDiv.emit(\"plotly_relayout\",e)}};return t.glplot.canvas&&(t.glplot.canvas.addEventListener(\"mouseup\",(function(){i(t)})),t.glplot.canvas.addEventListener(\"touchstart\",(function(){w=!0})),t.glplot.canvas.addEventListener(\"wheel\",(function(r){if(e._context._scrollZoom.gl3d){if(t.camera._ortho){var n=r.deltaX>r.deltaY?1.1:1/1.1,a=t.glplot.getAspectratio();t.glplot.setAspectratio({x:n*a.x,y:n*a.y,z:n*a.z})}i(t)}}),!!u&&{passive:!1}),t.glplot.canvas.addEventListener(\"mousemove\",(function(){if(!1!==t.fullSceneLayout.dragmode&&0!==t.camera.mouseListener.buttons){var e=n();t.graphDiv.emit(\"plotly_relayouting\",e)}})),t.staticMode||t.glplot.canvas.addEventListener(\"webglcontextlost\",(function(r){e&&e.emit&&e.emit(\"plotly_webglcontextlost\",{event:r,layer:t.id})}),!1)),t.glplot.oncontextloss=function(){t.recoverContext()},t.glplot.onrender=function(){t.render()},!0},k.render=function(){var t,e=this,r=e.graphDiv,n=e.svgContainer,i=e.container.getBoundingClientRect();r._fullLayout._calcInverseTransform(r);var a=r._fullLayout._invScaleX,o=r._fullLayout._invScaleY,s=i.width*a,l=i.height*o;n.setAttributeNS(null,\"viewBox\",\"0 0 \"+s+\" \"+l),n.setAttributeNS(null,\"width\",s),n.setAttributeNS(null,\"height\",l),b(e),e.glplot.axes.update(e.axesOptions);for(var u=Object.keys(e.traces),c=null,h=e.glplot.selection,v=0;v<u.length;++v)\"skip\"!==(t=e.traces[u[v]]).data.hoverinfo&&t.handlePick(h)&&(c=t),t.setContourLevels&&t.setContourLevels();function g(t,r,n){var i=e.fullSceneLayout[t+\"axis\"];return\"log\"!==i.type&&(r=i.d2l(r)),p.hoverLabelText(i,r,n)}if(null!==c){var m=y(e.glplot.cameraParams,h.dataCoordinate);t=c.data;var x,_=r._fullData[t.index],T=h.index,k={xLabel:g(\"x\",h.traceCoordinate[0],t.xhoverformat),yLabel:g(\"y\",h.traceCoordinate[1],t.yhoverformat),zLabel:g(\"z\",h.traceCoordinate[2],t.zhoverformat)},A=d.castHoverinfo(_,e.fullLayout,T),M=(A||\"\").split(\"+\"),S=A&&\"all\"===A;_.hovertemplate||S||(-1===M.indexOf(\"x\")&&(k.xLabel=void 0),-1===M.indexOf(\"y\")&&(k.yLabel=void 0),-1===M.indexOf(\"z\")&&(k.zLabel=void 0),-1===M.indexOf(\"text\")&&(h.textLabel=void 0),-1===M.indexOf(\"name\")&&(c.name=void 0));var E=[];\"cone\"===t.type||\"streamtube\"===t.type?(k.uLabel=g(\"x\",h.traceCoordinate[3],t.uhoverformat),(S||-1!==M.indexOf(\"u\"))&&E.push(\"u: \"+k.uLabel),k.vLabel=g(\"y\",h.traceCoordinate[4],t.vhoverformat),(S||-1!==M.indexOf(\"v\"))&&E.push(\"v: \"+k.vLabel),k.wLabel=g(\"z\",h.traceCoordinate[5],t.whoverformat),(S||-1!==M.indexOf(\"w\"))&&E.push(\"w: \"+k.wLabel),k.normLabel=h.traceCoordinate[6].toPrecision(3),(S||-1!==M.indexOf(\"norm\"))&&E.push(\"norm: \"+k.normLabel),\"streamtube\"===t.type&&(k.divergenceLabel=h.traceCoordinate[7].toPrecision(3),(S||-1!==M.indexOf(\"divergence\"))&&E.push(\"divergence: \"+k.divergenceLabel)),h.textLabel&&E.push(h.textLabel),x=E.join(\"<br>\")):\"isosurface\"===t.type||\"volume\"===t.type?(k.valueLabel=p.hoverLabelText(e._mockAxis,e._mockAxis.d2l(h.traceCoordinate[3]),t.valuehoverformat),E.push(\"value: \"+k.valueLabel),h.textLabel&&E.push(h.textLabel),x=E.join(\"<br>\")):x=h.textLabel;var L={x:h.traceCoordinate[0],y:h.traceCoordinate[1],z:h.traceCoordinate[2],data:_._input,fullData:_,curveNumber:_.index,pointNumber:T};d.appendArrayPointValue(L,_,T),t._module.eventData&&(L=_._module.eventData(L,h,_,{},T));var C={points:[L]};if(e.fullSceneLayout.hovermode){var P=[];d.loneHover({trace:_,x:(.5+.5*m[0]/m[3])*s,y:(.5-.5*m[1]/m[3])*l,xLabel:k.xLabel,yLabel:k.yLabel,zLabel:k.zLabel,text:x,name:c.name,color:d.castHoverOption(_,T,\"bgcolor\")||c.color,borderColor:d.castHoverOption(_,T,\"bordercolor\"),fontFamily:d.castHoverOption(_,T,\"font.family\"),fontSize:d.castHoverOption(_,T,\"font.size\"),fontColor:d.castHoverOption(_,T,\"font.color\"),nameLength:d.castHoverOption(_,T,\"namelength\"),textAlign:d.castHoverOption(_,T,\"align\"),hovertemplate:f.castOption(_,T,\"hovertemplate\"),hovertemplateLabels:f.extendFlat({},L,k),eventData:[L]},{container:n,gd:r,inOut_bbox:P}),L.bbox=P[0]}h.distance<5&&(h.buttons||w)?r.emit(\"plotly_click\",C):r.emit(\"plotly_hover\",C),this.oldEventData=C}else d.loneUnhover(n),this.oldEventData&&r.emit(\"plotly_unhover\",this.oldEventData),this.oldEventData=void 0;e.drawAnnotations(e)},k.recoverContext=function(){var t=this;t.glplot.dispose();var e=function(){t.glplot.gl.isContextLost()?requestAnimationFrame(e):t.initializeGLPlot()?t.plot.apply(t,t.plotArgs):f.error(\"Catastrophic and unrecoverable WebGL error. Context lost.\")};requestAnimationFrame(e)};var M=[\"xaxis\",\"yaxis\",\"zaxis\"];function S(t,e,r){for(var n=t.fullSceneLayout,i=0;i<3;i++){var a=M[i],o=a.charAt(0),s=n[a],l=e[o],u=e[o+\"calendar\"],c=e[\"_\"+o+\"length\"];if(f.isArrayOrTypedArray(l))for(var h,p=0;p<(c||l.length);p++)if(f.isArrayOrTypedArray(l[p]))for(var d=0;d<l[p].length;++d)h=s.d2l(l[p][d],0,u),!isNaN(h)&&isFinite(h)&&(r[0][i]=Math.min(r[0][i],h),r[1][i]=Math.max(r[1][i],h));else h=s.d2l(l[p],0,u),!isNaN(h)&&isFinite(h)&&(r[0][i]=Math.min(r[0][i],h),r[1][i]=Math.max(r[1][i],h));else r[0][i]=Math.min(r[0][i],0),r[1][i]=Math.max(r[1][i],c-1)}}k.plot=function(t,e,r){var n=this;if(n.plotArgs=[t,e,r],!n.glplot.contextLost){var i,a,o,s,l,u,c=e[n.id],f=r[n.id];n.fullLayout=e,n.fullSceneLayout=c,n.axesOptions.merge(e,c),n.spikeOptions.merge(c),n.setViewport(c),n.updateFx(c.dragmode,c.hovermode),n.camera.enableWheel=n.graphDiv._context._scrollZoom.gl3d,n.glplot.setClearColor(v(c.bgcolor)),n.setConvert(l),t?Array.isArray(t)||(t=[t]):t=[];var h=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(o=0;o<t.length;++o)!0===(i=t[o]).visible&&0!==i._length&&S(this,i,h);!function(t,e){for(var r=t.fullSceneLayout,n=r.annotations||[],i=0;i<3;i++)for(var a=M[i],o=a.charAt(0),s=r[a],l=0;l<n.length;l++){var u=n[l];if(u.visible){var c=s.r2l(u[o]);!isNaN(c)&&isFinite(c)&&(e[0][i]=Math.min(e[0][i],c),e[1][i]=Math.max(e[1][i],c))}}}(this,h);var p=[1,1,1];for(s=0;s<3;++s)h[1][s]===h[0][s]?p[s]=1:p[s]=1/(h[1][s]-h[0][s]);for(n.dataScale=p,n.convertAnnotations(this),o=0;o<t.length;++o)!0===(i=t[o]).visible&&0!==i._length&&((a=n.traces[i.uid])?a.data.type===i.type?a.update(i):(a.dispose(),a=i._module.plot(this,i),n.traces[i.uid]=a):(a=i._module.plot(this,i),n.traces[i.uid]=a),a.name=i.name);var d=Object.keys(n.traces);t:for(o=0;o<d.length;++o){for(s=0;s<t.length;++s)if(t[s].uid===d[o]&&!0===t[s].visible&&0!==t[s]._length)continue t;(a=n.traces[d[o]]).dispose(),delete n.traces[d[o]]}n.glplot.objects.sort((function(t,e){return t._trace.data.index-e._trace.data.index}));var g,y=[[0,0,0],[0,0,0]],m=[],x={};for(o=0;o<3;++o){var b;if((u=(l=c[M[o]]).type)in x?(x[u].acc*=p[o],x[u].count+=1):x[u]={acc:p[o],count:1},l.autorange){y[0][o]=1/0,y[1][o]=-1/0;var w=n.glplot.objects,T=n.fullSceneLayout.annotations||[],k=l._name.charAt(0);for(s=0;s<w.length;s++){var A=w[s],E=A.bounds,L=A._trace.data._pad||0;\"ErrorBars\"===A.constructor.name&&l._lowerLogErrorBound?y[0][o]=Math.min(y[0][o],l._lowerLogErrorBound):y[0][o]=Math.min(y[0][o],E[0][o]/p[o]-L),y[1][o]=Math.max(y[1][o],E[1][o]/p[o]+L)}for(s=0;s<T.length;s++){var C=T[s];if(C.visible){var P=l.r2l(C[k]);y[0][o]=Math.min(y[0][o],P),y[1][o]=Math.max(y[1][o],P)}}if(\"rangemode\"in l&&\"tozero\"===l.rangemode&&(y[0][o]=Math.min(y[0][o],0),y[1][o]=Math.max(y[1][o],0)),y[0][o]>y[1][o])y[0][o]=-1,y[1][o]=1;else{var O=y[1][o]-y[0][o];y[0][o]-=O/32,y[1][o]+=O/32}if(b=[y[0][o],y[1][o]],b=_(b,l),y[0][o]=b[0],y[1][o]=b[1],l.isReversed()){var I=y[0][o];y[0][o]=y[1][o],y[1][o]=I}}else b=l.range,y[0][o]=l.r2l(b[0]),y[1][o]=l.r2l(b[1]);y[0][o]===y[1][o]&&(y[0][o]-=1,y[1][o]+=1),m[o]=y[1][o]-y[0][o],l.range=[y[0][o],y[1][o]],l.limitRange(),n.glplot.setBounds(o,{min:l.range[0]*p[o],max:l.range[1]*p[o]})}var D=c.aspectmode;if(\"cube\"===D)g=[1,1,1];else if(\"manual\"===D){var z=c.aspectratio;g=[z.x,z.y,z.z]}else{if(\"auto\"!==D&&\"data\"!==D)throw new Error(\"scene.js aspectRatio was not one of the enumerated types\");var R=[1,1,1];for(o=0;o<3;++o){var F=x[u=(l=c[M[o]]).type];R[o]=Math.pow(F.acc,1/F.count)/p[o]}g=\"data\"===D||Math.max.apply(null,R)/Math.min.apply(null,R)<=4?R:[1,1,1]}c.aspectratio.x=f.aspectratio.x=g[0],c.aspectratio.y=f.aspectratio.y=g[1],c.aspectratio.z=f.aspectratio.z=g[2],n.glplot.setAspectratio(c.aspectratio),n.viewInitial.aspectratio||(n.viewInitial.aspectratio={x:c.aspectratio.x,y:c.aspectratio.y,z:c.aspectratio.z}),n.viewInitial.aspectmode||(n.viewInitial.aspectmode=c.aspectmode);var B=c.domain||null,N=e._size||null;if(B&&N){var j=n.container.style;j.position=\"absolute\",j.left=N.l+B.x[0]*N.w+\"px\",j.top=N.t+(1-B.y[1])*N.h+\"px\",j.width=N.w*(B.x[1]-B.x[0])+\"px\",j.height=N.h*(B.y[1]-B.y[0])+\"px\"}n.glplot.redraw()}},k.destroy=function(){var t=this;t.glplot&&(t.camera.mouseListener.enabled=!1,t.container.removeEventListener(\"wheel\",t.camera.wheelListener),t.camera=null,t.glplot.dispose(),t.container.parentNode.removeChild(t.container),t.glplot=null)},k.getCamera=function(){var t,e=this;return e.camera.view.recalcMatrix(e.camera.view.lastT()),{up:{x:(t=e.camera).up[0],y:t.up[1],z:t.up[2]},center:{x:t.center[0],y:t.center[1],z:t.center[2]},eye:{x:t.eye[0],y:t.eye[1],z:t.eye[2]},projection:{type:!0===t._ortho?\"orthographic\":\"perspective\"}}},k.setViewport=function(t){var e,r=this,n=t.camera;r.camera.lookAt.apply(this,[[(e=n).eye.x,e.eye.y,e.eye.z],[e.center.x,e.center.y,e.center.z],[e.up.x,e.up.y,e.up.z]]),r.glplot.setAspectratio(t.aspectratio),\"orthographic\"===n.projection.type!==r.camera._ortho&&(r.glplot.redraw(),r.glplot.clearRGBA(),r.glplot.dispose(),r.initializeGLPlot())},k.isCameraChanged=function(t){var e=this.getCamera(),r=f.nestedProperty(t,this.id+\".camera\").get();function n(t,e,r,n){var 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n=0;n<r;++n)for(var i=0;i<e;++i){var a=4*(e*n+i),o=t[a+3];if(o>0)for(var s=255/o,l=0;l<3;++l)t[a+l]=Math.min(s*t[a+l],255)}}(o,i,a);var s=document.createElement(\"canvas\");s.width=i,s.height=a;var l,u=s.getContext(\"2d\",{willReadFrequently:!0}),c=u.createImageData(i,a);switch(c.data.set(o),u.putImageData(c,0,0),t){case\"jpeg\":l=s.toDataURL(\"image/jpeg\");break;case\"webp\":l=s.toDataURL(\"image/webp\");break;default:l=s.toDataURL(\"image/png\")}return e.staticMode&&e.container.removeChild(n),l},k.setConvert=function(){for(var t=0;t<3;t++){var e=this.fullSceneLayout[M[t]];p.setConvert(e,this.fullLayout),e.setScale=f.noop}},k.make4thDimension=function(){var t=this,e=t.graphDiv._fullLayout;t._mockAxis={type:\"linear\",showexponent:\"all\",exponentformat:\"B\"},p.setConvert(t._mockAxis,e)},t.exports=T},52094:function(t){\"use strict\";t.exports=function(t,e,r,n){n=n||t.length;for(var i=new Array(n),a=0;a<n;a++)i[a]=[t[a],e[a],r[a]];return i}},64859:function(t,e,r){\"use strict\";var 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n=this,i=n.gd,a=n.radius,o=n.cx,s=n.cy,l=n.getRadial(e),u=n.id+\"title\",f=0;if(l.title){var h=c.bBox(n.layers[\"radial-axis\"].node()).height,p=l.title.font.size,d=l.side;f=\"top\"===d?p:\"counterclockwise\"===d?-(h+.4*p):h+.8*p}var v=void 0!==r?r:n.radialAxisAngle,g=R(v),y=Math.cos(g),m=Math.sin(g),b=o+a/2*y+f*m,_=s-a/2*m+f*y;n.layers[\"radial-axis-title\"]=x.draw(i,u,{propContainer:l,propName:n.id+\".radialaxis.title\",placeholder:D(i,\"Click to enter radial axis title\"),attributes:{x:b,y:_,\"text-anchor\":\"middle\"},transform:{rotate:-v}})}},N.updateAngularAxis=function(t,e){var r=this,n=r.gd,i=r.layers,a=r.radius,c=r.innerRadius,f=r.cx,p=r.cy,d=r.getAngular(e),v=r.angularAxis,g=r.isSmith;g||(r.fillViewInitialKey(\"angularaxis.rotation\",d.rotation),v.setGeometry(),v.setScale());var y=g?function(t){var e=I(r,C([0,t.x]));return Math.atan2(e[0]-f,e[1]-p)-Math.PI/2}:function(t){return 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e,r,s=this,u=s.isSmith,c=s.gd,f=s.layers,h=t._zoomlayer,p=S.MINZOOM,d=S.OFFEDGE,v=s.radius,x=s.innerRadius,T=s.cx,k=s.cy,A=s.cxx,M=s.cyy,L=s.sectorInRad,C=s.vangles,P=s.radialAxis,O=E.clampTiny,I=E.findXYatLength,D=E.findEnclosingVertexAngles,z=S.cornerHalfWidth,R=S.cornerLen/2,F=g.makeDragger(f,\"path\",\"maindrag\",!1===t.dragmode?\"none\":\"crosshair\");n.select(F).attr(\"d\",s.pathSubplot()).attr(\"transform\",l(T,k)),F.onmousemove=function(t){m.hover(c,t,s.id),c._fullLayout._lasthover=F,c._fullLayout._hoversubplot=s.id},F.onmouseout=function(t){c._dragging||y.unhover(c,t)};var B,N,j,U,V,q,H,G,W,Y={element:F,gd:c,subplot:s.id,plotinfo:{id:s.id,xaxis:s.xaxis,yaxis:s.yaxis},xaxes:[s.xaxis],yaxes:[s.yaxis]};function X(t,e){return Math.sqrt(t*t+e*e)}function Z(t,e){return X(t-A,e-M)}function K(t,e){return Math.atan2(M-e,t-A)}function J(t,e){return[t*Math.cos(e),t*Math.sin(-e)]}function $(t,e){if(0===t)return s.pathSector(2*z);var 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I,D,z,B=g.makeRectDragger(c,T,\"crosshair\",-x,-x,m,m),N={element:B,gd:u};!1===t.dragmode&&(N.dragmode=!1),V(n.select(B),v.visible&&h<f,{transform:l(b,_)}),N.prepFn=function(){I=null,D=null,z=null,N.moveFn=j,N.doneFn=q,w(u)},N.clampFn=function(t,e){return Math.sqrt(t*t+e*e)<S.MINDRAG&&(t=0,e=0),[t,e]},y.init(N)}function j(t,e){if(I)I(t,e);else{var n=[t,-e],a=[Math.cos(M),Math.sin(M)],s=Math.abs(o.dot(n,a)/Math.sqrt(o.dot(n,n)));isNaN(s)||(I=s<.5?H:G)}var l={};!function(t){null!==D?t[i.id+\".radialaxis.angle\"]=D:null!==z&&(t[i.id+\".radialaxis.range[\"+r+\"]\"]=z)}(l),u.emit(\"plotly_relayouting\",l)}function q(){null!==D?a.call(\"_guiRelayout\",u,i.id+\".radialaxis.angle\",D):null!==z&&a.call(\"_guiRelayout\",u,i.id+\".radialaxis.range[\"+r+\"]\",z)}function H(t,e){if(0!==r){var n=b+t,a=_+e;D=Math.atan2(d-a,n-p),i.vangles&&(D=U(D,i.vangles)),D=F(D);var o=l(p,d)+s(-D);c[\"radial-axis\"].attr(\"transform\",o),c[\"radial-line\"].select(\"line\").attr(\"transform\",o);var 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B=o?A(t,e):A(r,n);o?f?(I=t+B*w,z=-B*F):(I=e-B*w,z=B*F):f?(D=r+B*w,R=-B*F):(D=n-B*w,R=B*F)}return{textX:P,textY:O,targetX:I,targetY:D,anchorX:z,anchorY:R,scale:k,rotate:T}}t.exports={plot:function(t,e,r,f,g,y){var w=e.xaxis,O=e.yaxis,I=t._fullLayout,D=t._context.staticPlot;g||(g={mode:I.barmode,norm:I.barmode,gap:I.bargap,groupgap:I.bargroupgap},p(\"bar\",I));var z=a.makeTraceGroups(f,r,\"trace bars\").each((function(r){var u=n.select(this),f=r[0].trace,p=r[0].t,z=\"waterfall\"===f.type,R=\"funnel\"===f.type,F=\"histogram\"===f.type,B=\"bar\"===f.type,N=B||R,j=0;z&&f.connector.visible&&\"between\"===f.connector.mode&&(j=f.connector.line.width/2);var U=\"h\"===f.orientation,V=S(g),q=a.ensureSingle(u,\"g\",\"points\"),H=T(f),G=q.selectAll(\"g.point\").data(a.identity,H);G.enter().append(\"g\").classed(\"point\",!0),G.exit().remove(),G.each((function(u,T){var S,z,R=n.select(this),q=function(t,e,r,n){var i=[],a=[],o=n?e:r,s=n?r:e;return 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v.coerceEnumerated(x,r)}(z,i);var B=\"stack\"===w.mode||\"relative\"===w.mode,N=n[i],j=!B||N._outmost,U=N.hasB,V=g&&g-y>_;if(F&&\"none\"!==k&&(!N.isBlank&&s!==u&&f!==p||\"auto\"!==k&&\"inside\"!==k)){var q=I.font,H=d.getBarColor(n[i],z),G=d.getInsideTextFont(z,i,q,H),W=d.getOutsideTextFont(z,i,q),Y=z.insidetextanchor||\"end\",X=r.datum();R?\"log\"===S.type&&X.s0<=0&&(s=S.range[0]<S.range[1]?0:S._length):\"log\"===O.type&&X.s0<=0&&(f=O.range[0]<O.range[1]?O._length:0);var Z,K,J,$,Q,tt=Math.abs(u-s),et=Math.abs(p-f),rt=tt-2*_,nt=et-2*_;if(\"outside\"===k&&(j||N.hasB||(k=\"inside\")),\"auto\"===k)if(j){k=\"inside\",Z=D(r,F,Q=a.ensureUniformFontSize(t,G)),J=(K=l.bBox(Z.node())).width,$=K.height;var it,at=J>0&&$>0;it=V?U?E(rt-2*g,nt,J,$,R)||E(rt,nt-2*g,J,$,R):R?E(rt-(g-y),nt,J,$,R)||E(rt,nt-2*(g-y),J,$,R):E(rt,nt-(g-y),J,$,R)||E(rt-2*(g-y),nt,J,$,R):E(rt,nt,J,$,R),at&&it?k=\"inside\":(k=\"outside\",Z.remove(),Z=null)}else k=\"inside\";if(!Z){var ot=(Z=D(r,F,Q=a.ensureUniformFontSize(t,\"outside\"===k?W:G))).attr(\"transform\");if(Z.attr(\"transform\",\"\"),J=(K=l.bBox(Z.node())).width,$=K.height,Z.attr(\"transform\",ot),J<=0||$<=0)return void Z.remove()}var st,lt=z.textangle;st=\"outside\"===k?function(t,e,r,n,i,a){var o,s=!!a.isHorizontal,l=!!a.constrained,u=a.angle||0,c=i.width,f=i.height,h=Math.abs(e-t),p=Math.abs(n-r);o=s?p>2*_?_:0:h>2*_?_:0;var d=1;l&&(d=s?Math.min(1,p/f):Math.min(1,h/c));var v=L(u),g=C(i,v),y=(s?g.x:g.y)/2,m=(i.left+i.right)/2,x=(i.top+i.bottom)/2,b=(t+e)/2,w=(r+n)/2,T=0,k=0,M=s?A(e,t):A(r,n);return s?(b=e-M*o,T=M*y):(w=n+M*o,k=-M*y),{textX:m,textY:x,targetX:b,targetY:w,anchorX:T,anchorY:k,scale:d,rotate:v}}(s,u,f,p,K,{isHorizontal:R,constrained:\"both\"===z.constraintext||\"outside\"===z.constraintext,angle:lt}):P(s,u,f,p,K,{isHorizontal:R,constrained:\"both\"===z.constraintext||\"inside\"===z.constraintext,angle:lt,anchor:Y,hasB:U,r:g,overhead:y}),st.fontSize=Q.size,h(\"histogram\"===z.type?\"bar\":z.type,st,I),N.transform=st;var ut=M(Z,I,w,T);a.setTransormAndDisplay(ut,st)}else r.select(\"text\").remove()}(t,e,R,r,T,H,G,W,Y,rt,it,g,y),e.layerClipId&&l.hideOutsideRangePoint(u,R.select(\"text\"),w,O,f.xcalendar,f.ycalendar)}));var W=!1===f.cliponaxis;l.setClipUrl(u,W?null:e.layerClipId,t)}));u.getComponentMethod(\"errorbars\",\"plot\")(t,z,e,g)},toMoveInsideBar:P}},45784:function(t){\"use strict\";function e(t,e,r,n,i){var a=e.c2p(n?t.s0:t.p0,!0),o=e.c2p(n?t.s1:t.p1,!0),s=r.c2p(n?t.p0:t.s0,!0),l=r.c2p(n?t.p1:t.s1,!0);return i?[(a+o)/2,(s+l)/2]:n?[o,(s+l)/2]:[(a+o)/2,l]}t.exports=function(t,r){var n,i=t.cd,a=t.xaxis,o=t.yaxis,s=i[0].trace,l=\"funnel\"===s.type,u=\"h\"===s.orientation,c=[];if(!1===r)for(n=0;n<i.length;n++)i[n].selected=0;else for(n=0;n<i.length;n++){var f=i[n],h=\"ct\"in f?f.ct:e(f,a,o,u,l);r.contains(h,!1,n,t)?(c.push({pointNumber:n,x:a.c2d(f.x),y:o.c2d(f.y)}),f.selected=1):f.selected=0}return c}},72592:function(t,e,r){\"use strict\";t.exports=i;var n=r(3400).distinctVals;function i(t,e){this.traces=t,this.sepNegVal=e.sepNegVal,this.overlapNoMerge=e.overlapNoMerge;for(var r=1/0,i=e.posAxis._id.charAt(0),a=[],o=0;o<t.length;o++){for(var s=t[o],l=0;l<s.length;l++){var u=s[l],c=u.p;void 0===c&&(c=u[i]),void 0!==c&&a.push(c)}s[0]&&s[0].width1&&(r=Math.min(s[0].width1,r))}this.positions=a;var f=n(a);this.distinctPositions=f.vals,1===f.vals.length&&r!==1/0?this.minDiff=r:this.minDiff=Math.min(f.minDiff,r);var h=(e.posAxis||{}).type;\"category\"!==h&&\"multicategory\"!==h||(this.minDiff=1),this.binWidth=this.minDiff,this.bins={}}i.prototype.put=function(t,e){var r=this.getLabel(t,e),n=this.bins[r]||0;return this.bins[r]=n+e,n},i.prototype.get=function(t,e){var r=this.getLabel(t,e);return this.bins[r]||0},i.prototype.getLabel=function(t,e){return(e<0&&this.sepNegVal?\"v\":\"^\")+(this.overlapNoMerge?t:Math.round(t/this.binWidth))}},60100:function(t,e,r){\"use strict\";var n=r(33428),i=r(76308),a=r(43616),o=r(3400),s=r(24040),l=r(82744).resizeText,u=r(20832),c=u.textfont,f=u.insidetextfont,h=u.outsidetextfont,p=r(60444);function d(t,e,r){a.pointStyle(t.selectAll(\"path\"),e,r),v(t,e,r)}function v(t,e,r){t.selectAll(\"text\").each((function(t){var i=n.select(this),s=o.ensureUniformFontSize(r,g(i,t,e,r));a.font(i,s)}))}function g(t,e,r,n){var i=n._fullLayout.font,a=r.textfont;if(t.classed(\"bartext-inside\")){var o=_(e,r);a=m(r,e.i,i,o)}else t.classed(\"bartext-outside\")&&(a=x(r,e.i,i));return 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i,a=t.cd[0].trace.hoveron,o=[];return-1!==a.indexOf(\"boxes\")&&(o=o.concat(l(t,e,r,n))),-1!==a.indexOf(\"points\")&&(i=u(t,e,r)),\"closest\"===n?i?[i]:o:i?(o.push(i),o):o},hoverOnBoxes:l,hoverOnPoints:u}},67244:function(t,e,r){\"use strict\";t.exports={attributes:r(63188),layoutAttributes:r(16560),supplyDefaults:r(90624).supplyDefaults,crossTraceDefaults:r(90624).crossTraceDefaults,supplyLayoutDefaults:r(68832).supplyLayoutDefaults,calc:r(62555),crossTraceCalc:r(96404).crossTraceCalc,plot:r(18728).plot,style:r(25776).style,styleOnSelect:r(25776).styleOnSelect,hoverPoints:r(27576).hoverPoints,eventData:r(10392),selectPoints:r(8264),moduleType:\"trace\",name:\"box\",basePlotModule:r(57952),categories:[\"cartesian\",\"svg\",\"symbols\",\"oriented\",\"box-violin\",\"showLegend\",\"boxLayout\",\"zoomScale\"],meta:{}}},16560:function(t){\"use 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b=t.selectAll(\"path.box\").data(\"violin\"!==r.type||r.box.visible?i.identity:[]);b.enter().append(\"path\").style(\"vector-effect\",o?\"none\":\"non-scaling-stroke\").attr(\"class\",\"box\"),b.exit().remove(),b.each((function(t){if(t.empty)return n.select(this).attr(\"d\",\"M0,0Z\");var e=f.c2l(t.pos+p,!0),a=f.l2p(e-s)+v,o=f.l2p(e+l)+v,b=h?(a+o)/2:f.l2p(e)+v,_=r.whiskerwidth,w=h?a*_+(1-_)*b:f.l2p(e-d)+v,T=h?o*_+(1-_)*b:f.l2p(e+d)+v,k=f.l2p(e-s*x)+v,A=f.l2p(e+l*x)+v,M=\"sd\"===r.sizemode,S=c.c2p(M?t.mean-t.sd:t.q1,!0),E=M?c.c2p(t.mean+t.sd,!0):c.c2p(t.q3,!0),L=i.constrain(M?c.c2p(t.mean,!0):c.c2p(t.med,!0),Math.min(S,E)+1,Math.max(S,E)-1),C=void 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n=r(49084),i=r(29736).axisHoverFormat,a=r(21776).Ks,o=r(52948),s=r(45464),l=r(92880).extendFlat,u={x:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},y:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},z:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},u:{valType:\"data_array\",editType:\"calc\"},v:{valType:\"data_array\",editType:\"calc\"},w:{valType:\"data_array\",editType:\"calc\"},sizemode:{valType:\"enumerated\",values:[\"scaled\",\"absolute\"],editType:\"calc\",dflt:\"scaled\"},sizeref:{valType:\"number\",editType:\"calc\",min:0},anchor:{valType:\"enumerated\",editType:\"calc\",values:[\"tip\",\"tail\",\"cm\",\"center\"],dflt:\"cm\"},text:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertemplate:a({editType:\"calc\"},{keys:[\"norm\"]}),uhoverformat:i(\"u\",1),vhoverformat:i(\"v\",1),whoverformat:i(\"w\",1),xhoverformat:i(\"x\"),yhoverformat:i(\"y\"),zhoverformat:i(\"z\"),showlegend:l({},s.showlegend,{dflt:!1})};l(u,n(\"\",{colorAttr:\"u/v/w 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U,V,q,H=j.select(\"path\");w(M)?(H.transition().duration(M.duration).ease(M.easing).each(\"end\",(function(){S&&S()})).each(\"interrupt\",(function(){S&&S()})).attrTween(\"d\",(U=N,V=L(r[0].lastY),q=L(r[0].y),function(){var t=i(V,q);return function(e){return U.endAngle(t(e))()}})),p._lastValue=r[0].y):H.attr(\"d\",\"number\"==typeof r[0].y?N.endAngle(L(r[0].y)):\"M0,0Z\"),H.call(T),j.exit().remove(),F=[];var G=p.gauge.threshold.value;(G||0===G)&&F.push({range:[G,G],color:p.gauge.threshold.color,line:{color:p.gauge.threshold.line.color,width:p.gauge.threshold.line.width},thickness:p.gauge.threshold.thickness});var W=_.selectAll(\"g.threshold-arc\").data(F);W.enter().append(\"g\").classed(\"threshold-arc\",!0).append(\"path\"),W.select(\"path\").call(P).call(T),W.exit().remove();var Y=_.selectAll(\"g.gauge-outline\").data([x]);Y.enter().append(\"g\").classed(\"gauge-outline\",!0).append(\"path\"),Y.select(\"path\").call(P).call(T),Y.exit().remove()}(t,0,e,{radius:U,innerRadius:V,gauge:W,layer:Y,size:B,gaugeBg:C,gaugeOutline:P,transitionOpts:r,onComplete:g});var X=I.selectAll(\"g.bullet\").data(R?e:[]);X.exit().remove();var Z=I.selectAll(\"g.bulletaxis\").data(R?e:[]);Z.exit().remove(),R&&function(t,e,r,n){var i,a,o,s,u,c=r[0].trace,f=n.gauge,p=n.layer,v=n.gaugeBg,g=n.gaugeOutline,y=n.size,x=c.domain,b=n.transitionOpts,_=n.onComplete;f.enter().append(\"g\").classed(\"bullet\",!0),f.attr(\"transform\",l(y.l,y.t)),p.enter().append(\"g\").classed(\"bulletaxis\",!0).classed(\"crisp\",!0),p.selectAll(\"g.xbulletaxistick,path,text\").remove();var A=y.h,M=c.gauge.bar.thickness*A,S=x.x[0],E=x.x[0]+(x.x[1]-x.x[0])*(c._hasNumber||c._hasDelta?1-h.bulletNumberDomainSize:1);function L(t){t.attr(\"width\",(function(t){return 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r=\"slices.\"+t;a(r+\".show\")&&(a(r+\".fill\"),a(r+\".locations\"))})),a(\"spaceframe.show\")&&a(\"spaceframe.fill\"),a(\"surface.show\")&&(a(\"surface.count\"),a(\"surface.fill\"),a(\"surface.pattern\")),a(\"contour.show\")&&(a(\"contour.color\"),a(\"contour.width\")),[\"text\",\"hovertext\",\"hovertemplate\",\"lighting.ambient\",\"lighting.diffuse\",\"lighting.specular\",\"lighting.roughness\",\"lighting.fresnel\",\"lighting.vertexnormalsepsilon\",\"lighting.facenormalsepsilon\",\"lightposition.x\",\"lightposition.y\",\"lightposition.z\",\"flatshading\",\"opacity\"].forEach((function(t){a(t)})),o(t,e,n,a,{prefix:\"\",cLetter:\"c\"}),e._length=null):e.visible=!1}t.exports={supplyDefaults:function(t,e,r,i){s(t,e,0,i,(function(r,i){return n.coerce(t,e,a,r,i)}))},supplyIsoDefaults:s}},6296:function(t,e,r){\"use 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n=r(49084),i=r(29736).axisHoverFormat,a=r(21776).Ks,o=r(16716),s=r(45464),l=r(92880).extendFlat;t.exports=l({x:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},y:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},z:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},i:{valType:\"data_array\",editType:\"calc\"},j:{valType:\"data_array\",editType:\"calc\"},k:{valType:\"data_array\",editType:\"calc\"},text:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertemplate:a({editType:\"calc\"}),xhoverformat:i(\"x\"),yhoverformat:i(\"y\"),zhoverformat:i(\"z\"),delaunayaxis:{valType:\"enumerated\",values:[\"x\",\"y\",\"z\"],dflt:\"z\",editType:\"calc\"},alphahull:{valType:\"number\",dflt:-1,editType:\"calc\"},intensity:{valType:\"data_array\",editType:\"calc\"},intensitymode:{valType:\"enumerated\",values:[\"vertex\",\"cell\"],dflt:\"vertex\",editType:\"calc\"},color:{valType:\"color\",editType:\"calc\"},vertexcolor:{valType:\"data_array\",editType:\"calc\"},facecolor:{valType:\"data_array\",editType:\"calc\"},transforms:void 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n=r(67792).gl_mesh3d,i=r(67792).delaunay_triangulate,a=r(67792).alpha_shape,o=r(67792).convex_hull,s=r(33040).parseColorScale,l=r(3400).isArrayOrTypedArray,u=r(43080),c=r(8932).extractOpts,f=r(52094);function h(t,e,r){this.scene=t,this.uid=r,this.mesh=e,this.name=\"\",this.color=\"#fff\",this.data=null,this.showContour=!1}var p=h.prototype;function d(t){for(var e=[],r=t.length,n=0;n<r;n++)e[n]=u(t[n]);return e}function v(t,e,r,n){for(var i=[],a=e.length,o=0;o<a;o++)i[o]=t.d2l(e[o],0,n)*r;return i}function g(t){for(var e=[],r=t.length,n=0;n<r;n++)e[n]=Math.round(t[n]);return e}function y(t,e){for(var r=t.length,n=0;n<r;n++)if(t[n]<=-.5||t[n]>=e-.5)return!1;return!0}p.handlePick=function(t){if(t.object===this.mesh){var e=t.index=t.data.index;t.data._cellCenter?t.traceCoordinate=t.data.dataCoordinate:t.traceCoordinate=[this.data.x[e],this.data.y[e],this.data.z[e]];var r=this.data.hovertext||this.data.text;return l(r)&&void 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p={positions:h,cells:n,lightPosition:[t.lightposition.x,t.lightposition.y,t.lightposition.z],ambient:t.lighting.ambient,diffuse:t.lighting.diffuse,specular:t.lighting.specular,roughness:t.lighting.roughness,fresnel:t.lighting.fresnel,vertexNormalsEpsilon:t.lighting.vertexnormalsepsilon,faceNormalsEpsilon:t.lighting.facenormalsepsilon,opacity:t.opacity,contourEnable:t.contour.show,contourColor:u(t.contour.color).slice(0,3),contourWidth:t.contour.width,useFacetNormals:t.flatshading};if(t.intensity){var m=c(t);this.color=\"#fff\";var x=t.intensitymode;p[x+\"Intensity\"]=t.intensity,p[x+\"IntensityBounds\"]=[m.min,m.max],p.colormap=s(t)}else t.vertexcolor?(this.color=t.vertexcolor[0],p.vertexColors=d(t.vertexcolor)):t.facecolor?(this.color=t.facecolor[0],p.cellColors=d(t.facecolor)):(this.color=t.color,p.meshColor=u(t.color));this.mesh.update(p)},p.dispose=function(){this.scene.glplot.remove(this.mesh),this.mesh.dispose()},t.exports=function(t,e){var r=t.glplot.gl,i=n({gl:r}),a=new 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r,n=t.cd,i=t.xaxis,a=t.yaxis,o=[],s=n[0].t.bPos||0;if(!1===e)for(r=0;r<n.length;r++)n[r].selected=0;else for(r=0;r<n.length;r++){var l=n[r];e.contains([i.c2p(l.pos+s),a.c2p(l.yc)],null,l.i,t)?(o.push({pointNumber:l.i,x:i.c2d(l.pos),y:a.c2d(l.yc)}),l.selected=1):l.selected=0}return o}},14008:function(t,e,r){\"use strict\";var n=r(33428),i=r(43616),a=r(76308);t.exports=function(t,e,r){var o=r||n.select(t).selectAll(\"g.ohlclayer\").selectAll(\"g.trace\");o.style(\"opacity\",(function(t){return t[0].trace.opacity})),o.each((function(t){var e=t[0].trace;n.select(this).selectAll(\"path\").each((function(t){if(!t.empty){var r=e[t.dir].line;n.select(this).style(\"fill\",\"none\").call(a.stroke,r.color).call(i.dashLine,r.dash,r.width).style(\"opacity\",e.selectedpoints&&!t.selected?.3:1)}}))}))}},72140:function(t,e,r){\"use strict\";var 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n=r(71688).wrap,i=r(94288).hasColorscale,a=r(47128),o=r(68944),s=r(43616),l=r(3400),u=r(38248);function c(t,e,r){t.valueInds.push(e),t.count+=r}function f(t,e,r){return{categoryInds:t,color:e,rawColor:r,valueInds:[],count:0}}function h(t,e,r){t.valueInds.push(e),t.count+=r}t.exports=function(t,e){var r=l.filterVisible(e.dimensions);if(0===r.length)return[];var p,d,v,g=r.map((function(t){var e;if(\"trace\"===t.categoryorder)e=null;else if(\"array\"===t.categoryorder)e=t.categoryarray;else{e=o(t.values);for(var r=!0,n=0;n<e.length;n++)if(!u(e[n])){r=!1;break}e.sort(r?l.sorterAsc:void 0),\"category descending\"===t.categoryorder&&(e=e.reverse())}return function(t,e){e=null==e?[]:e.map((function(t){return t}));var r={},n={},i=[];e.forEach((function(t,e){r[t]=0,n[t]=e}));for(var a=0;a<t.length;a++){var o,s=t[a];void 0===r[s]?(r[s]=1,o=e.push(s)-1,n[s]=o):(r[s]++,o=n[s]),i.push(o)}var l=e.map((function(t){return 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t.width})).attr(\"height\",(function(t){return t.height})).attr(\"y\",(function(t){return t.y})).attr(\"cursor\",(function(t){return\"fixed\"===t.parcatsViewModel.arrangement?\"default\":\"perpendicular\"===t.parcatsViewModel.arrangement?\"ns-resize\":\"move\"})),k(D),E.exit().remove(),S.append(\"text\").attr(\"class\",\"catlabel\").attr(\"pointer-events\",\"none\");var z=e._fullLayout.paper_bgcolor;M.select(\"text.catlabel\").attr(\"text-anchor\",(function(t){return d(t)?\"start\":\"end\"})).attr(\"alignment-baseline\",\"middle\").style(\"text-shadow\",f.makeTextShadow(z)).style(\"fill\",\"rgb(0, 0, 0)\").attr(\"x\",(function(t){return d(t)?t.width+5:-5})).attr(\"y\",(function(t){return t.height/2})).text((function(t){return t.model.categoryLabel})).each((function(t){u.font(n.select(this),t.parcatsViewModel.categorylabelfont),f.convertToTspans(n.select(this),e)})),S.append(\"text\").attr(\"class\",\"dimlabel\"),M.select(\"text.dimlabel\").attr(\"text-anchor\",\"middle\").attr(\"alignment-baseline\",\"baseline\").attr(\"cursor\",(function(t){return\"fixed\"===t.parcatsViewModel.arrangement?\"default\":\"ew-resize\"})).attr(\"x\",(function(t){return t.width/2})).attr(\"y\",-5).text((function(t,e){return 0===e?t.parcatsViewModel.model.dimensions[t.model.dimensionInd].dimensionLabel:null})).each((function(t){u.font(n.select(this),t.parcatsViewModel.labelfont)})),M.selectAll(\"rect.bandrect\").on(\"mouseover\",L).on(\"mouseout\",C),M.exit().remove(),A.call(n.behavior.drag().origin((function(t){return{x:t.x,y:0}})).on(\"dragstart\",P).on(\"drag\",O).on(\"dragend\",I)),h.each((function(t){t.traceSelection=n.select(this),t.pathSelection=n.select(this).selectAll(\"g.paths\").selectAll(\"path.path\"),t.dimensionSelection=n.select(this).selectAll(\"g.dimensions\").selectAll(\"g.dimension\")})),h.exit().remove()}function p(t){return t.key}function d(t){var e=t.parcatsViewModel.dimensions.length,r=t.parcatsViewModel.dimensions[e-1].model.dimensionInd;return t.model.dimensionInd===r}function v(t,e){return t.model.rawColor>e.model.rawColor?1:t.model.rawColor<e.model.rawColor?-1:0}function 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k(t){t.on(\"mousemove\",(function(t){i.event.preventDefault(),t.parent.inBrushDrag||T(this,t)})).on(\"mouseleave\",(function(t){t.parent.inBrushDrag||m()})).call(i.behavior.drag().on(\"dragstart\",(function(t){!function(t,e){i.event.sourceEvent.stopPropagation();var r=e.height-i.mouse(t)[1]-2*n.verticalPadding,a=e.unitToPaddedPx.invert(r),o=e.brush,s=_(e,r),l=s.interval,u=o.svgBrush;if(u.wasDragged=!1,u.grabbingBar=\"ns\"===s.region,u.grabbingBar){var c=l.map(e.unitToPaddedPx);u.grabPoint=r-c[0]-n.verticalPadding,u.barLength=c[1]-c[0]}u.clickableOrdinalRange=s.clickableOrdinalRange,u.stayingIntervals=e.multiselect&&o.filterSpecified?o.filter.getConsolidated():[],l&&(u.stayingIntervals=u.stayingIntervals.filter((function(t){return t[0]!==l[0]&&t[1]!==l[1]}))),u.startExtent=s.region?l[\"s\"===s.region?1:0]:a,e.parent.inBrushDrag=!0,u.brushStartCallback()}(this,t)})).on(\"drag\",(function(t){w(this,t)})).on(\"dragend\",(function(t){!function(t,e){var r=e.brush,n=r.filter,a=r.svgBrush;a._dragging||(T(t,e),w(t,e),e.brush.svgBrush.wasDragged=!1),a._dragging=!1,i.event.sourceEvent.stopPropagation();var o=a.grabbingBar;if(a.grabbingBar=!1,a.grabLocation=void 0,e.parent.inBrushDrag=!1,m(),!a.wasDragged)return a.wasDragged=void 0,a.clickableOrdinalRange?r.filterSpecified&&e.multiselect?a.extent.push(a.clickableOrdinalRange):(a.extent=[a.clickableOrdinalRange],r.filterSpecified=!0):o?(a.extent=a.stayingIntervals,0===a.extent.length&&M(r)):M(r),a.brushCallback(e),b(t.parentNode),void a.brushEndCallback(r.filterSpecified?n.getConsolidated():[]);var s=function(){n.set(n.getConsolidated())};if(e.ordinal){var l=e.unitTickvals;l[l.length-1]<l[0]&&l.reverse(),a.newExtent=[p(0,l,a.newExtent[0],a.stayingIntervals),p(1,l,a.newExtent[1],a.stayingIntervals)];var u=a.newExtent[1]>a.newExtent[0];a.extent=a.stayingIntervals.concat(u?[a.newExtent]:[]),a.extent.length||M(r),a.brushCallback(e),u?b(t.parentNode,s):(s(),b(t.parentNode))}else s();a.brushEndCallback(r.filterSpecified?n.getConsolidated():[])}(this,t)})))}function A(t,e){return t[0]-e[0]}function M(t){t.filterSpecified=!1,t.svgBrush.extent=[[-1/0,1/0]]}function S(t){for(var e,r=t.slice(),n=[],i=r.shift();i;){for(e=i.slice();(i=r.shift())&&i[0]<=e[1];)e[1]=Math.max(e[1],i[1]);n.push(e)}return 1===n.length&&n[0][0]>n[0][1]&&(n=[]),n}t.exports={makeBrush:function(t,e,r,n,i,a){var o,l=function(){var t,e,r=[];return{set:function(n){1===(r=n.map((function(t){return t.slice().sort(s)})).sort(A)).length&&r[0][0]===-1/0&&r[0][1]===1/0&&(r=[[0,-1]]),t=S(r),e=r.reduce((function(t,e){return[Math.min(t[0],e[0]),Math.max(t[1],e[1])]}),[1/0,-1/0])},get:function(){return r.slice()},getConsolidated:function(){return t},getBounds:function(){return e}}}();return l.set(r),{filter:l,filterSpecified:e,svgBrush:{extent:[],brushStartCallback:n,brushCallback:(o=i,function(t){var e=t.brush,r=function(t){return t.svgBrush.extent.map((function(t){return t.slice()}))}(e),n=r.slice();e.filter.set(n),o()}),brushEndCallback:a}}},ensureAxisBrush:function(t,e,r){var i=t.selectAll(\".\"+n.cn.axisBrush).data(o,a);i.enter().append(\"g\").classed(n.cn.axisBrush,!0),function(t,e,r){var i=r._context.staticPlot,a=t.selectAll(\".background\").data(o);a.enter().append(\"rect\").classed(\"background\",!0).call(d).call(v).style(\"pointer-events\",i?\"none\":\"auto\").attr(\"transform\",l(0,n.verticalPadding)),a.call(k).attr(\"height\",(function(t){return t.height-n.verticalPadding}));var s=t.selectAll(\".highlight-shadow\").data(o);s.enter().append(\"line\").classed(\"highlight-shadow\",!0).attr(\"x\",-n.bar.width/2).attr(\"stroke-width\",n.bar.width+n.bar.strokeWidth).attr(\"stroke\",e).attr(\"opacity\",n.bar.strokeOpacity).attr(\"stroke-linecap\",\"butt\"),s.attr(\"y1\",(function(t){return t.height})).call(x);var u=t.selectAll(\".highlight\").data(o);u.enter().append(\"line\").classed(\"highlight\",!0).attr(\"x\",-n.bar.width/2).attr(\"stroke-width\",n.bar.width-n.bar.strokeWidth).attr(\"stroke\",n.bar.fillColor).attr(\"opacity\",n.bar.fillOpacity).attr(\"stroke-linecap\",\"butt\"),u.attr(\"y1\",(function(t){return t.height})).call(x)}(i,e,r)},cleanRanges:function(t,e){if(Array.isArray(t[0])?(t=t.map((function(t){return t.sort(s)})),t=e.multiselect?S(t.sort(A)):[t[0]]):t=[t.sort(s)],e.tickvals){var r=e.tickvals.slice().sort(s);if(!(t=t.map((function(t){var e=[p(0,r,t[0],[]),p(1,r,t[1],[])];if(e[1]>e[0])return e})).filter((function(t){return t}))).length)return}return t.length>1?t:t[0]}}},61664:function(t,e,r){\"use strict\";t.exports={attributes:r(82296),supplyDefaults:r(60664),calc:r(95044),colorbar:{container:\"line\",min:\"cmin\",max:\"cmax\"},moduleType:\"trace\",name:\"parcoords\",basePlotModule:r(19976),categories:[\"gl\",\"regl\",\"noOpacity\",\"noHover\"],meta:{}}},19976:function(t,e,r){\"use strict\";var n=r(33428),i=r(84888)._M,a=r(24196),o=r(9616);e.name=\"parcoords\",e.plot=function(t){var e=i(t.calcdata,\"parcoords\")[0];e.length&&a(t,e)},e.clean=function(t,e,r,n){var i=n._has&&n._has(\"parcoords\"),a=e._has&&e._has(\"parcoords\");i&&!a&&(n._paperdiv.selectAll(\".parcoords\").remove(),n._glimages.selectAll(\"*\").remove())},e.toSVG=function(t){var e=t._fullLayout._glimages,r=n.select(t).selectAll(\".svg-container\");r.filter((function(t,e){return e===r.size()-1})).selectAll(\".gl-canvas-context, .gl-canvas-focus\").each((function(){var t=this,r=t.toDataURL(\"image/png\");e.append(\"svg:image\").attr({xmlns:o.svg,\"xlink:href\":r,preserveAspectRatio:\"none\",x:0,y:0,width:t.style.width,height:t.style.height})})),window.setTimeout((function(){n.selectAll(\"#filterBarPattern\").attr(\"id\",\"filterBarPattern\")}),60)}},95044:function(t,e,r){\"use strict\";var n=r(3400).isArrayOrTypedArray,i=r(8932),a=r(71688).wrap;t.exports=function(t,e){var r,o;return i.hasColorscale(e,\"line\")&&n(e.line.color)?(r=e.line.color,o=i.extractOpts(e.line).colorscale,i.calc(t,e,{vals:r,containerStr:\"line\",cLetter:\"c\"})):(r=function(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=.5;return e}(e._length),o=[[0,e.line.color],[1,e.line.color]]),a({lineColor:r,cscale:o})}},30140:function(t){\"use strict\";t.exports={maxDimensionCount:60,overdrag:45,verticalPadding:2,tickDistance:50,canvasPixelRatio:1,blockLineCount:5e3,layers:[\"contextLineLayer\",\"focusLineLayer\",\"pickLineLayer\"],axisTitleOffset:28,axisExtentOffset:10,bar:{width:4,captureWidth:10,fillColor:\"magenta\",fillOpacity:1,snapDuration:150,snapRatio:.25,snapClose:.01,strokeOpacity:1,strokeWidth:1,handleHeight:8,handleOpacity:1,handleOverlap:0},cn:{axisExtentText:\"axis-extent-text\",parcoordsLineLayers:\"parcoords-line-layers\",parcoordsLineLayer:\"parcoords-lines\",parcoords:\"parcoords\",parcoordsControlView:\"parcoords-control-view\",yAxis:\"y-axis\",axisOverlays:\"axis-overlays\",axis:\"axis\",axisHeading:\"axis-heading\",axisTitle:\"axis-title\",axisExtent:\"axis-extent\",axisExtentTop:\"axis-extent-top\",axisExtentTopText:\"axis-extent-top-text\",axisExtentBottom:\"axis-extent-bottom\",axisExtentBottomText:\"axis-extent-bottom-text\",axisBrush:\"axis-brush\"},id:{filterBarPattern:\"filter-bar-pattern\"}}},60664:function(t,e,r){\"use strict\";var n=r(3400),i=r(94288).hasColorscale,a=r(27260),o=r(86968).Q,s=r(51272),l=r(54460),u=r(82296),c=r(71864),f=r(30140).maxDimensionCount,h=r(26284);function p(t,e,r,i){function a(r,i){return n.coerce(t,e,u.dimensions,r,i)}var o=a(\"values\"),s=a(\"visible\");if(o&&o.length||(s=e.visible=!1),s){a(\"label\"),a(\"tickvals\"),a(\"ticktext\"),a(\"tickformat\");var f=a(\"range\");e._ax={_id:\"y\",type:\"linear\",showexponent:\"all\",exponentformat:\"B\",range:f},l.setConvert(e._ax,i.layout),a(\"multiselect\");var h=a(\"constraintrange\");h&&(e.constraintrange=c.cleanRanges(h,e))}}t.exports=function(t,e,r,l){function c(r,i){return n.coerce(t,e,u,r,i)}var d=t.dimensions;Array.isArray(d)&&d.length>f&&(n.log(\"parcoords traces support up to \"+f+\" dimensions at the moment\"),d.splice(f));var v=s(t,e,{name:\"dimensions\",layout:l,handleItemDefaults:p}),g=function(t,e,r,o,s){var l=s(\"line.color\",r);if(i(t,\"line\")&&n.isArrayOrTypedArray(l)){if(l.length)return s(\"line.colorscale\"),a(t,e,o,s,{prefix:\"line.\",cLetter:\"c\"}),l.length;e.line.color=r}return 1/0}(t,e,r,l,c);o(e,l,c),Array.isArray(v)&&v.length||(e.visible=!1),h(e,v,\"values\",g);var y={family:l.font.family,size:Math.round(l.font.size/1.2),color:l.font.color};n.coerceFont(c,\"labelfont\",y),n.coerceFont(c,\"tickfont\",y),n.coerceFont(c,\"rangefont\",y),c(\"labelangle\"),c(\"labelside\"),c(\"unselected.line.color\"),c(\"unselected.line.opacity\")}},95724:function(t,e,r){\"use strict\";var n=r(3400).isTypedArray;e.convertTypedArray=function(t){return n(t)?Array.prototype.slice.call(t):t},e.isOrdinal=function(t){return!!t.tickvals},e.isVisible=function(t){return t.visible||!(\"visible\"in t)}},29928:function(t,e,r){\"use strict\";var n=r(61664);n.plot=r(24196),t.exports=n},51352:function(t,e,r){\"use strict\";var n=[\"precision highp float;\",\"\",\"varying vec4 fragColor;\",\"\",\"attribute vec4 p01_04, p05_08, p09_12, p13_16,\",\"               p17_20, p21_24, p25_28, p29_32,\",\"               p33_36, p37_40, p41_44, p45_48,\",\"               p49_52, p53_56, p57_60, colors;\",\"\",\"uniform mat4 dim0A, dim1A, dim0B, dim1B, dim0C, dim1C, dim0D, dim1D,\",\"             loA, hiA, loB, hiB, loC, hiC, loD, hiD;\",\"\",\"uniform vec2 resolution, viewBoxPos, viewBoxSize;\",\"uniform float maskHeight;\",\"uniform float drwLayer; // 0: context, 1: focus, 2: pick\",\"uniform vec4 contextColor;\",\"uniform sampler2D maskTexture, palette;\",\"\",\"bool isPick    = (drwLayer > 1.5);\",\"bool isContext = (drwLayer < 0.5);\",\"\",\"const vec4 ZEROS = vec4(0.0, 0.0, 0.0, 0.0);\",\"const vec4 UNITS = vec4(1.0, 1.0, 1.0, 1.0);\",\"\",\"float val(mat4 p, mat4 v) {\",\"    return dot(matrixCompMult(p, v) * UNITS, UNITS);\",\"}\",\"\",\"float axisY(float ratio, mat4 A, mat4 B, mat4 C, mat4 D) {\",\"    float y1 = val(A, dim0A) + val(B, dim0B) + val(C, dim0C) + val(D, dim0D);\",\"    float y2 = val(A, dim1A) + val(B, dim1B) + val(C, dim1C) + val(D, dim1D);\",\"    return y1 * (1.0 - ratio) + y2 * ratio;\",\"}\",\"\",\"int iMod(int a, int b) {\",\"    return a - b * (a / b);\",\"}\",\"\",\"bool fOutside(float p, float lo, float hi) {\",\"    return (lo < hi) && (lo > p || p > hi);\",\"}\",\"\",\"bool vOutside(vec4 p, vec4 lo, vec4 hi) {\",\"    return (\",\"        fOutside(p[0], lo[0], hi[0]) ||\",\"        fOutside(p[1], lo[1], hi[1]) ||\",\"        fOutside(p[2], lo[2], hi[2]) ||\",\"        fOutside(p[3], lo[3], hi[3])\",\"    );\",\"}\",\"\",\"bool mOutside(mat4 p, mat4 lo, mat4 hi) {\",\"    return (\",\"        vOutside(p[0], lo[0], hi[0]) ||\",\"        vOutside(p[1], lo[1], hi[1]) ||\",\"        vOutside(p[2], lo[2], hi[2]) ||\",\"        vOutside(p[3], lo[3], hi[3])\",\"    );\",\"}\",\"\",\"bool outsideBoundingBox(mat4 A, mat4 B, mat4 C, mat4 D) {\",\"    return mOutside(A, loA, hiA) ||\",\"           mOutside(B, loB, hiB) ||\",\"           mOutside(C, loC, hiC) ||\",\"           mOutside(D, loD, hiD);\",\"}\",\"\",\"bool outsideRasterMask(mat4 A, mat4 B, mat4 C, mat4 D) {\",\"    mat4 pnts[4];\",\"    pnts[0] = A;\",\"    pnts[1] = B;\",\"    pnts[2] = C;\",\"    pnts[3] = D;\",\"\",\"    for(int i = 0; i < 4; ++i) {\",\"        for(int j = 0; j < 4; ++j) {\",\"            for(int k = 0; k < 4; ++k) {\",\"                if(0 == iMod(\",\"                    int(255.0 * texture2D(maskTexture,\",\"                        vec2(\",\"                            (float(i * 2 + j / 2) + 0.5) / 8.0,\",\"                            (pnts[i][j][k] * (maskHeight - 1.0) + 1.0) / maskHeight\",\"                        ))[3]\",\"                    ) / int(pow(2.0, float(iMod(j * 4 + k, 8)))),\",\"                    2\",\"                )) return true;\",\"            }\",\"        }\",\"    }\",\"    return false;\",\"}\",\"\",\"vec4 position(bool isContext, float v, mat4 A, mat4 B, mat4 C, mat4 D) {\",\"    float x = 0.5 * sign(v) + 0.5;\",\"    float y = axisY(x, A, B, C, D);\",\"    float z = 1.0 - abs(v);\",\"\",\"    z += isContext ? 0.0 : 2.0 * float(\",\"        outsideBoundingBox(A, B, C, D) ||\",\"        outsideRasterMask(A, B, C, D)\",\"    );\",\"\",\"    return vec4(\",\"        2.0 * (vec2(x, y) * viewBoxSize + viewBoxPos) / resolution - 1.0,\",\"        z,\",\"        1.0\",\"    );\",\"}\",\"\",\"void main() {\",\"    mat4 A = mat4(p01_04, p05_08, p09_12, p13_16);\",\"    mat4 B = mat4(p17_20, p21_24, p25_28, p29_32);\",\"    mat4 C = mat4(p33_36, p37_40, p41_44, p45_48);\",\"    mat4 D = mat4(p49_52, p53_56, p57_60, ZEROS);\",\"\",\"    float v = colors[3];\",\"\",\"    gl_Position = position(isContext, v, A, B, C, D);\",\"\",\"    fragColor =\",\"        isContext ? vec4(contextColor) :\",\"        isPick ? vec4(colors.rgb, 1.0) : texture2D(palette, vec2(abs(v), 0.5));\",\"}\"].join(\"\\n\"),i=[\"precision highp float;\",\"\",\"varying vec4 fragColor;\",\"\",\"void main() {\",\"    gl_FragColor = fragColor;\",\"}\"].join(\"\\n\"),a=r(30140).maxDimensionCount,o=r(3400),s=1e-6,l=new Uint8Array(4),u=new Uint8Array(4),c={shape:[256,1],format:\"rgba\",type:\"uint8\",mag:\"nearest\",min:\"nearest\"};function f(t,e,r,n,i){var a=t._gl;a.enable(a.SCISSOR_TEST),a.scissor(e,r,n,i),t.clear({color:[0,0,0,0],depth:1})}function h(t,e,r,n,i,a){var o=a.key;r.drawCompleted||(function(t){t.read({x:0,y:0,width:1,height:1,data:l})}(t),r.drawCompleted=!0),function s(l){var u=Math.min(n,i-l*n);0===l&&(window.cancelAnimationFrame(r.currentRafs[o]),delete r.currentRafs[o],f(t,a.scissorX,a.scissorY,a.scissorWidth,a.viewBoxSize[1])),r.clearOnly||(a.count=2*u,a.offset=2*l*n,e(a),l*n+u<i&&(r.currentRafs[o]=window.requestAnimationFrame((function(){s(l+1)}))),r.drawCompleted=!1)}(0)}function p(t,e){for(var r=new Array(256),n=0;n<256;n++)r[n]=t(n/255).concat(e);return r}function d(t,e){return(t>>>8*e)%256/255}function v(t,e,r){for(var n=new Array(8*e),i=0,a=0;a<e;a++)for(var o=0;o<2;o++)for(var s=0;s<4;s++){var l=4*t+s,u=r[64*a+l];63===l&&0===o&&(u*=-1),n[i++]=u}return n}function g(t){var e=\"0\"+t;return e.substr(e.length-2)}function y(t){return t<a?\"p\"+g(t+1)+\"_\"+g(t+4):\"colors\"}function m(t,e,r,n,i,a,s,l,u,c,f,h,p,d){for(var v=[[],[]],g=0;g<64;g++)v[0][g]=g===i?1:0,v[1][g]=g===a?1:0;s*=d,l*=d,u*=d,c*=d;var y=t.lines.canvasOverdrag*d,m=t.domain,x=t.canvasWidth*d,b=t.canvasHeight*d,_=t.pad.l*d,w=t.pad.b*d,T=t.layoutHeight*d,k=t.layoutWidth*d,A=t.deselectedLines.color,M=t.deselectedLines.opacity;return o.extendFlat({key:f,resolution:[x,b],viewBoxPos:[s+y,l],viewBoxSize:[u,c],i0:i,i1:a,dim0A:v[0].slice(0,16),dim0B:v[0].slice(16,32),dim0C:v[0].slice(32,48),dim0D:v[0].slice(48,64),dim1A:v[1].slice(0,16),dim1B:v[1].slice(16,32),dim1C:v[1].slice(32,48),dim1D:v[1].slice(48,64),drwLayer:h,contextColor:[A[0]/255,A[1]/255,A[2]/255,\"auto\"!==M?A[3]*M:Math.max(1/255,Math.pow(1/t.lines.color.length,1/3))],scissorX:(n===e?0:s+y)+(_-y)+k*m.x[0],scissorWidth:(n===r?x-s+y:u+.5)+(n===e?s+y:0),scissorY:l+w+T*m.y[0],scissorHeight:c,viewportX:_-y+k*m.x[0],viewportY:w+T*m.y[0],viewportWidth:x,viewportHeight:b},p)}function x(t){var e=2047,r=Math.max(0,Math.floor(t[0]*e),0),n=Math.min(e,Math.ceil(t[1]*e),e);return[Math.min(r,n),Math.max(r,n)]}t.exports=function(t,e){var r,l,g,b,_,w=e.context,T=e.pick,k=e.regl,A=k._gl,M=A.getParameter(A.ALIASED_LINE_WIDTH_RANGE),S=Math.max(M[0],Math.min(M[1],e.viewModel.plotGlPixelRatio)),E={currentRafs:{},drawCompleted:!0,clearOnly:!1},L=function(t){for(var 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a=u[e][n],o=i.map((function(t){return t.slice()})),s=\"dimensions[\"+n+\"].constraintrange\",l=r._tracePreGUI[t._fullData[c[e]]._fullInput.uid];if(void 0===l[s]){var h=a.constraintrange;l[s]=h||null}var p=t._fullData[c[e]].dimensions[n];o.length?(1===o.length&&(o=o[0]),a.constraintrange=o,p.constraintrange=o.slice(),o=[o]):(delete a.constraintrange,delete p.constraintrange,o=null);var d={};d[s]=o,t.emit(\"plotly_restyle\",[d,[f[e]]])},hover:function(e){t.emit(\"plotly_hover\",e)},unhover:function(e){t.emit(\"plotly_unhover\",e)},axesMoved:function(e,r){var n=function(t,e){return function(r,n){return s(t,e,r)-s(t,e,n)}}(r,u[e].filter(a));l[e].sort(n),u[e].filter((function(t){return!a(t)})).sort((function(t){return u[e].indexOf(t)})).forEach((function(t){l[e].splice(l[e].indexOf(t),1),l[e].splice(u[e].indexOf(t),0,t)})),t.emit(\"plotly_restyle\",[{dimensions:[l[e]]},[f[e]]])}})}}).reglPrecompiled=o},74996:function(t,e,r){\"use strict\";var n=r(45464),i=r(86968).u,a=r(25376),o=r(22548),s=r(21776).Ks,l=r(21776).Gw,u=r(92880).extendFlat,c=r(98192).c,f=a({editType:\"plot\",arrayOk:!0,colorEditType:\"plot\"});t.exports={labels:{valType:\"data_array\",editType:\"calc\"},label0:{valType:\"number\",dflt:0,editType:\"calc\"},dlabel:{valType:\"number\",dflt:1,editType:\"calc\"},values:{valType:\"data_array\",editType:\"calc\"},marker:{colors:{valType:\"data_array\",editType:\"calc\"},line:{color:{valType:\"color\",dflt:o.defaultLine,arrayOk:!0,editType:\"style\"},width:{valType:\"number\",min:0,dflt:0,arrayOk:!0,editType:\"style\"},editType:\"calc\"},pattern:c,editType:\"calc\"},text:{valType:\"data_array\",editType:\"plot\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"style\"},scalegroup:{valType:\"string\",dflt:\"\",editType:\"calc\"},textinfo:{valType:\"flaglist\",flags:[\"label\",\"text\",\"value\",\"percent\"],extras:[\"none\"],editType:\"calc\"},hoverinfo:u({},n.hoverinfo,{flags:[\"label\",\"text\",\"value\",\"percent\",\"name\"]}),hovertemplate:s({},{keys:[\"label\",\"color\",\"value\",\"percent\",\"text\"]}),texttemplate:l({editType:\"plot\"},{keys:[\"label\",\"color\",\"value\",\"percent\",\"text\"]}),textposition:{valType:\"enumerated\",values:[\"inside\",\"outside\",\"auto\",\"none\"],dflt:\"auto\",arrayOk:!0,editType:\"plot\"},textfont:u({},f,{}),insidetextorientation:{valType:\"enumerated\",values:[\"horizontal\",\"radial\",\"tangential\",\"auto\"],dflt:\"auto\",editType:\"plot\"},insidetextfont:u({},f,{}),outsidetextfont:u({},f,{}),automargin:{valType:\"boolean\",dflt:!1,editType:\"plot\"},title:{text:{valType:\"string\",dflt:\"\",editType:\"plot\"},font:u({},f,{}),position:{valType:\"enumerated\",values:[\"top 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n=r(7316);e.name=\"pie\",e.plot=function(t,r,i,a){n.plotBasePlot(e.name,t,r,i,a)},e.clean=function(t,r,i,a){n.cleanBasePlot(e.name,t,r,i,a)}},45768:function(t,e,r){\"use strict\";var n=r(38248),i=r(49760),a=r(76308),o={};function s(t){return function(e,r){return!!e&&!!(e=i(e)).isValid()&&(e=a.addOpacity(e,e.getAlpha()),t[r]||(t[r]=e),e)}}function l(t,e){var r,n=JSON.stringify(t),a=e[n];if(!a){for(a=t.slice(),r=0;r<t.length;r++)a.push(i(t[r]).lighten(20).toHexString());for(r=0;r<t.length;r++)a.push(i(t[r]).darken(20).toHexString());e[n]=a}return a}t.exports={calc:function(t,e){var r,i,a=[],o=t._fullLayout,l=o.hiddenlabels||[],u=e.labels,c=e.marker.colors||[],f=e.values,h=e._length,p=e._hasValues&&h;if(e.dlabel)for(u=new Array(h),r=0;r<h;r++)u[r]=String(e.label0+r*e.dlabel);var d={},v=s(o[\"_\"+e.type+\"colormap\"]),g=0,y=!1;for(r=0;r<h;r++){var m,x,b;if(p){if(m=f[r],!n(m))continue;m=+m}else m=1;void 0!==(x=u[r])&&\"\"!==x||(x=r);var _=d[x=String(x)];void 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p,d=l(\"text\"),v=l(\"texttemplate\");if(v||(p=l(\"textinfo\",i.isArrayOrTypedArray(d)?\"text+percent\":\"percent\")),l(\"hovertext\"),l(\"hovertemplate\"),v||p&&\"none\"!==p){var g=l(\"textposition\");s(t,e,n,l,g,{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!1,moduleHasCliponaxis:!1,moduleHasTextangle:!1,moduleHasInsideanchor:!1}),(Array.isArray(g)||\"auto\"===g||\"outside\"===g)&&l(\"automargin\"),(\"inside\"===g||\"auto\"===g||Array.isArray(g))&&l(\"insidetextorientation\")}else\"none\"===p&&l(\"textposition\",\"none\");o(e,n,l);var y=l(\"hole\");if(l(\"title.text\")){var m=l(\"title.position\",y?\"middle center\":\"top center\");y||\"middle center\"!==m||(e.title.position=\"top center\"),i.coerceFont(l,\"title.font\",n.font)}l(\"sort\"),l(\"direction\"),l(\"rotation\"),l(\"pull\")}else e.visible=!1}}},53644:function(t,e,r){\"use strict\";var n=r(10624).appendArrayMultiPointValues;t.exports=function(t,e){var r={curveNumber:e.index,pointNumbers:t.pts,data:e._input,fullData:e,label:t.label,color:t.color,value:t.v,percent:t.percent,text:t.text,bbox:t.bbox,v:t.v};return 1===t.pts.length&&(r.pointNumber=r.i=t.pts[0]),n(r,e,t.pts),\"funnelarea\"===e.type&&(delete r.v,delete r.i),r}},21552:function(t,e,r){\"use strict\";var n=r(43616),i=r(76308);t.exports=function(t,e,r,a){var o=r.marker.pattern;o&&o.shape?n.pointStyle(t,r,a,e):i.fill(t,e.color)}},69656:function(t,e,r){\"use strict\";var n=r(3400);function i(t){return-1!==t.indexOf(\"e\")?t.replace(/[.]?0+e/,\"e\"):-1!==t.indexOf(\".\")?t.replace(/[.]?0+$/,\"\"):t}e.formatPiePercent=function(t,e){var r=i((100*t).toPrecision(3));return n.numSeparate(r,e)+\"%\"},e.formatPieValue=function(t,e){var r=i(t.toPrecision(10));return n.numSeparate(r,e)},e.getFirstFilled=function(t,e){if(n.isArrayOrTypedArray(t))for(var r=0;r<e.length;r++){var i=t[e[r]];if(i||0===i||\"\"===i)return i}},e.castOption=function(t,r){return n.isArrayOrTypedArray(t)?e.getFirstFilled(t,r):t||void 0},e.getRotationAngle=function(t){return(\"auto\"===t?0:t)*Math.PI/180}},75792:function(t,e,r){\"use strict\";t.exports={attributes:r(74996),supplyDefaults:r(74174).supplyDefaults,supplyLayoutDefaults:r(90248),layoutAttributes:r(85204),calc:r(45768).calc,crossTraceCalc:r(45768).crossTraceCalc,plot:r(37820).plot,style:r(22152),styleOne:r(10528),moduleType:\"trace\",name:\"pie\",basePlotModule:r(80036),categories:[\"pie-like\",\"pie\",\"showLegend\"],meta:{}}},85204:function(t){\"use strict\";t.exports={hiddenlabels:{valType:\"data_array\",editType:\"calc\"},piecolorway:{valType:\"colorlist\",editType:\"calc\"},extendpiecolors:{valType:\"boolean\",dflt:!0,editType:\"calc\"}}},90248:function(t,e,r){\"use strict\";var n=r(3400),i=r(85204);t.exports=function(t,e){function r(r,a){return n.coerce(t,e,i,r,a)}r(\"hiddenlabels\"),r(\"piecolorway\",e.colorway),r(\"extendpiecolors\")}},37820:function(t,e,r){\"use strict\";var n=r(33428),i=r(7316),a=r(93024),o=r(76308),s=r(43616),l=r(3400),u=l.strScale,c=l.strTranslate,f=r(72736),h=r(82744),p=h.recordMinTextSize,d=h.clearMinTextSize,v=r(78048).TEXTPAD,g=r(69656),y=r(53644),m=r(3400).isValidTextValue;function x(t,e,r){var i=r[0],o=i.cx,s=i.cy,u=i.trace,c=\"funnelarea\"===u.type;\"_hasHoverLabel\"in u||(u._hasHoverLabel=!1),\"_hasHoverEvent\"in u||(u._hasHoverEvent=!1),t.on(\"mouseover\",(function(t){var r=e._fullLayout,f=e._fullData[u.index];if(!e._dragging&&!1!==r.hovermode){var h=f.hoverinfo;if(Array.isArray(h)&&(h=a.castHoverinfo({hoverinfo:[g.castOption(h,t.pts)],_module:u._module},r,0)),\"all\"===h&&(h=\"label+text+value+percent+name\"),f.hovertemplate||\"none\"!==h&&\"skip\"!==h&&h){var p=t.rInscribed||0,d=o+t.pxmid[0]*(1-p),v=s+t.pxmid[1]*(1-p),m=r.separators,x=[];if(h&&-1!==h.indexOf(\"label\")&&x.push(t.label),t.text=g.castOption(f.hovertext||f.text,t.pts),h&&-1!==h.indexOf(\"text\")){var b=t.text;l.isValidTextValue(b)&&x.push(b)}t.value=t.v,t.valueLabel=g.formatPieValue(t.v,m),h&&-1!==h.indexOf(\"value\")&&x.push(t.valueLabel),t.percent=t.v/i.vTotal,t.percentLabel=g.formatPiePercent(t.percent,m),h&&-1!==h.indexOf(\"percent\")&&x.push(t.percentLabel);var _=f.hoverlabel,w=_.font,T=[];a.loneHover({trace:u,x0:d-p*i.r,x1:d+p*i.r,y:v,_x0:c?o+t.TL[0]:d-p*i.r,_x1:c?o+t.TR[0]:d+p*i.r,_y0:c?s+t.TL[1]:v-p*i.r,_y1:c?s+t.BL[1]:v+p*i.r,text:x.join(\"<br>\"),name:f.hovertemplate||-1!==h.indexOf(\"name\")?f.name:void 0,idealAlign:t.pxmid[0]<0?\"left\":\"right\",color:g.castOption(_.bgcolor,t.pts)||t.color,borderColor:g.castOption(_.bordercolor,t.pts),fontFamily:g.castOption(w.family,t.pts),fontSize:g.castOption(w.size,t.pts),fontColor:g.castOption(w.color,t.pts),nameLength:g.castOption(_.namelength,t.pts),textAlign:g.castOption(_.align,t.pts),hovertemplate:g.castOption(f.hovertemplate,t.pts),hovertemplateLabels:t,eventData:[y(t,f)]},{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:e,inOut_bbox:T}),t.bbox=T[0],u._hasHoverLabel=!0}u._hasHoverEvent=!0,e.emit(\"plotly_hover\",{points:[y(t,f)],event:n.event})}})),t.on(\"mouseout\",(function(t){var r=e._fullLayout,i=e._fullData[u.index],o=n.select(this).datum();u._hasHoverEvent&&(t.originalEvent=n.event,e.emit(\"plotly_unhover\",{points:[y(o,i)],event:n.event}),u._hasHoverEvent=!1),u._hasHoverLabel&&(a.loneUnhover(r._hoverlayer.node()),u._hasHoverLabel=!1)})),t.on(\"click\",(function(t){var r=e._fullLayout,i=e._fullData[u.index];e._dragging||!1===r.hovermode||(e._hoverdata=[y(t,i)],a.click(e,n.event))}))}function b(t,e,r){var n=g.castOption(t.insidetextfont.color,e.pts);!n&&t._input.textfont&&(n=g.castOption(t._input.textfont.color,e.pts));var i=g.castOption(t.insidetextfont.family,e.pts)||g.castOption(t.textfont.family,e.pts)||r.family,a=g.castOption(t.insidetextfont.size,e.pts)||g.castOption(t.textfont.size,e.pts)||r.size;return{color:n||o.contrast(e.color),family:i,size:a}}function _(t,e){for(var r,n,i=0;i<t.length;i++)if((n=(r=t[i][0]).trace).title.text){var a=n.title.text;n._meta&&(a=l.templateString(a,n._meta));var o=s.tester.append(\"text\").attr(\"data-notex\",1).text(a).call(s.font,n.title.font).call(f.convertToTspans,e),u=s.bBox(o.node(),!0);r.titleBox={width:u.width,height:u.height},o.remove()}}function w(t,e,r){var n=r.r||e.rpx1,i=e.rInscribed;if(e.startangle===e.stopangle)return{rCenter:1-i,scale:0,rotate:0,textPosAngle:0};var 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r,n,i,a=t.trace,o={x:t.cx,y:t.cy},s={tx:0,ty:0};s.ty+=a.title.font.size,i=O(a),-1!==a.title.position.indexOf(\"top\")?(o.y-=(1+i)*t.r,s.ty-=t.titleBox.height):-1!==a.title.position.indexOf(\"bottom\")&&(o.y+=(1+i)*t.r);var l,u=t.r/(void 0===(l=t.trace.aspectratio)?1:l),c=e.w*(a.domain.x[1]-a.domain.x[0])/2;return-1!==a.title.position.indexOf(\"left\")?(c+=u,o.x-=(1+i)*u,s.tx+=t.titleBox.width/2):-1!==a.title.position.indexOf(\"center\")?c*=2:-1!==a.title.position.indexOf(\"right\")&&(c+=u,o.x+=(1+i)*u,s.tx-=t.titleBox.width/2),r=c/t.titleBox.width,n=P(t,e)/t.titleBox.height,{x:o.x,y:o.y,scale:Math.min(r,n),tx:s.tx,ty:s.ty}}function P(t,e){var r=t.trace,n=e.h*(r.domain.y[1]-r.domain.y[0]);return Math.min(t.titleBox.height,n/2)}function O(t){var e,r=t.pull;if(!r)return 0;if(l.isArrayOrTypedArray(r))for(r=0,e=0;e<t.pull.length;e++)t.pull[e]>r&&(r=t.pull[e]);return r}function I(t,e){for(var r=[],n=0;n<t.length;n++){var i=t[n][0],a=i.trace,o=a.domain,s=e.w*(o.x[1]-o.x[0]),l=e.h*(o.y[1]-o.y[0]);a.title.text&&\"middle center\"!==a.title.position&&(l-=P(i,e));var u=s/2,c=l/2;\"funnelarea\"!==a.type||a.scalegroup||(c/=a.aspectratio),i.r=Math.min(u,c)/(1+O(a)),i.cx=e.l+e.w*(a.domain.x[1]+a.domain.x[0])/2,i.cy=e.t+e.h*(1-a.domain.y[0])-l/2,a.title.text&&-1!==a.title.position.indexOf(\"bottom\")&&(i.cy-=P(i,e)),a.scalegroup&&-1===r.indexOf(a.scalegroup)&&r.push(a.scalegroup)}!function(t,e){for(var r,n,i,a=0;a<e.length;a++){var o=1/0,s=e[a];for(n=0;n<t.length;n++)if((i=(r=t[n][0]).trace).scalegroup===s){var l;if(\"pie\"===i.type)l=r.r*r.r;else if(\"funnelarea\"===i.type){var u,c;i.aspectratio>1?c=(u=r.r)/i.aspectratio:u=(c=r.r)*i.aspectratio,l=(u*=(1+i.baseratio)/2)*c}o=Math.min(o,l/r.vTotal)}for(n=0;n<t.length;n++)if((i=(r=t[n][0]).trace).scalegroup===s){var f=o*r.vTotal;\"funnelarea\"===i.type&&(f/=(1+i.baseratio)/2,f/=i.aspectratio),r.r=Math.sqrt(f)}}}(t,r)}function D(t,e){return[t*Math.sin(e),-t*Math.cos(e)]}function z(t,e,r){var n=t._fullLayout,i=r.trace,a=i.texttemplate,o=i.textinfo;if(!a&&o&&\"none\"!==o){var s,u=o.split(\"+\"),c=function(t){return-1!==u.indexOf(t)},f=c(\"label\"),h=c(\"text\"),p=c(\"value\"),d=c(\"percent\"),v=n.separators;if(s=f?[e.label]:[],h){var y=g.getFirstFilled(i.text,e.pts);m(y)&&s.push(y)}p&&s.push(g.formatPieValue(e.v,v)),d&&s.push(g.formatPiePercent(e.v/r.vTotal,v)),e.text=s.join(\"<br>\")}if(a){var x=l.castOption(i,e.i,\"texttemplate\");if(x){var b=function(t){return{label:t.label,value:t.v,valueLabel:g.formatPieValue(t.v,n.separators),percent:t.v/r.vTotal,percentLabel:g.formatPiePercent(t.v/r.vTotal,n.separators),color:t.color,text:t.text,customdata:l.castOption(i,t.i,\"customdata\")}}(e),_=g.getFirstFilled(i.text,e.pts);(m(_)||\"\"===_)&&(b.text=_),e.text=l.texttemplateString(x,b,t._fullLayout._d3locale,b,i._meta||{})}else e.text=\"\"}}function R(t,e){var r=t.rotate*Math.PI/180,n=Math.cos(r),i=Math.sin(r),a=(e.left+e.right)/2,o=(e.top+e.bottom)/2;t.textX=a*n-o*i,t.textY=a*i+o*n,t.noCenter=!0}t.exports={plot:function(t,e){var r=t._context.staticPlot,a=t._fullLayout,h=a._size;d(\"pie\",a),_(e,t),I(e,h);var v=l.makeTraceGroups(a._pielayer,e,\"trace\").each((function(e){var d=n.select(this),v=e[0],y=v.trace;!function(t){var e,r,n,i=t[0],a=i.r,o=i.trace,s=g.getRotationAngle(o.rotation),l=2*Math.PI/i.vTotal,u=\"px0\",c=\"px1\";if(\"counterclockwise\"===o.direction){for(e=0;e<t.length&&t[e].hidden;e++);if(e===t.length)return;s+=l*t[e].v,l*=-1,u=\"px1\",c=\"px0\"}for(n=D(a,s),e=0;e<t.length;e++)(r=t[e]).hidden||(r[u]=n,r.startangle=s,s+=l*r.v/2,r.pxmid=D(a,s),r.midangle=s,n=D(a,s+=l*r.v/2),r.stopangle=s,r[c]=n,r.largeArc=r.v>i.vTotal/2?1:0,r.halfangle=Math.PI*Math.min(r.v/i.vTotal,.5),r.ring=1-o.hole,r.rInscribed=E(r,i))}(e),d.attr(\"stroke-linejoin\",\"round\"),d.each((function(){var m=n.select(this).selectAll(\"g.slice\").data(e);m.enter().append(\"g\").classed(\"slice\",!0),m.exit().remove();var _=[[[],[]],[[],[]]],T=!1;m.each((function(i,o){if(i.hidden)n.select(this).selectAll(\"path,g\").remove();else{i.pointNumber=i.i,i.curveNumber=y.index,_[i.pxmid[1]<0?0:1][i.pxmid[0]<0?0:1].push(i);var u=v.cx,c=v.cy,h=n.select(this),d=h.selectAll(\"path.surface\").data([i]);if(d.enter().append(\"path\").classed(\"surface\",!0).style({\"pointer-events\":r?\"none\":\"all\"}),h.call(x,t,e),y.pull){var m=+g.castOption(y.pull,i.pts)||0;m>0&&(u+=m*i.pxmid[0],c+=m*i.pxmid[1])}i.cxFinal=u,i.cyFinal=c;var k=y.hole;if(i.v===v.vTotal){var A=\"M\"+(u+i.px0[0])+\",\"+(c+i.px0[1])+P(i.px0,i.pxmid,!0,1)+P(i.pxmid,i.px0,!0,1)+\"Z\";k?d.attr(\"d\",\"M\"+(u+k*i.px0[0])+\",\"+(c+k*i.px0[1])+P(i.px0,i.pxmid,!1,k)+P(i.pxmid,i.px0,!1,k)+\"Z\"+A):d.attr(\"d\",A)}else{var M=P(i.px0,i.px1,!0,1);if(k){var S=1-k;d.attr(\"d\",\"M\"+(u+k*i.px1[0])+\",\"+(c+k*i.px1[1])+P(i.px1,i.px0,!1,k)+\"l\"+S*i.px0[0]+\",\"+S*i.px0[1]+M+\"Z\")}else d.attr(\"d\",\"M\"+u+\",\"+c+\"l\"+i.px0[0]+\",\"+i.px0[1]+M+\"Z\")}z(t,i,v);var E=g.castOption(y.textposition,i.pts),C=h.selectAll(\"g.slicetext\").data(i.text&&\"none\"!==E?[0]:[]);C.enter().append(\"g\").classed(\"slicetext\",!0),C.exit().remove(),C.each((function(){var r=l.ensureSingle(n.select(this),\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),h=l.ensureUniformFontSize(t,\"outside\"===E?function(t,e,r){return{color:g.castOption(t.outsidetextfont.color,e.pts)||g.castOption(t.textfont.color,e.pts)||r.color,family:g.castOption(t.outsidetextfont.family,e.pts)||g.castOption(t.textfont.family,e.pts)||r.family,size:g.castOption(t.outsidetextfont.size,e.pts)||g.castOption(t.textfont.size,e.pts)||r.size}}(y,i,a.font):b(y,i,a.font));r.text(i.text).attr({class:\"slicetext\",transform:\"\",\"text-anchor\":\"middle\"}).call(s.font,h).call(f.convertToTspans,t);var d,m=s.bBox(r.node());if(\"outside\"===E)d=L(m,i);else if(d=w(m,i,v),\"auto\"===E&&d.scale<1){var x=l.ensureUniformFontSize(t,y.outsidetextfont);r.call(s.font,x),d=L(m=s.bBox(r.node()),i)}var _=d.textPosAngle,k=void 0===_?i.pxmid:D(v.r,_);if(d.targetX=u+k[0]*d.rCenter+(d.x||0),d.targetY=c+k[1]*d.rCenter+(d.y||0),R(d,m),d.outside){var A=d.targetY;i.yLabelMin=A-m.height/2,i.yLabelMid=A,i.yLabelMax=A+m.height/2,i.labelExtraX=0,i.labelExtraY=0,T=!0}d.fontSize=h.size,p(y.type,d,a),e[o].transform=d,l.setTransormAndDisplay(r,d)}))}function P(t,e,r,n){var a=n*(e[0]-t[0]),o=n*(e[1]-t[1]);return\"a\"+n*v.r+\",\"+n*v.r+\" 0 \"+i.largeArc+(r?\" 1 \":\" 0 \")+a+\",\"+o}}));var k=n.select(this).selectAll(\"g.titletext\").data(y.title.text?[0]:[]);if(k.enter().append(\"g\").classed(\"titletext\",!0),k.exit().remove(),k.each((function(){var e,r=l.ensureSingle(n.select(this),\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),i=y.title.text;y._meta&&(i=l.templateString(i,y._meta)),r.text(i).attr({class:\"titletext\",transform:\"\",\"text-anchor\":\"middle\"}).call(s.font,y.title.font).call(f.convertToTspans,t),e=\"middle center\"===y.title.position?function(t){var e=Math.sqrt(t.titleBox.width*t.titleBox.width+t.titleBox.height*t.titleBox.height);return{x:t.cx,y:t.cy,scale:t.trace.hole*t.r*2/e,tx:0,ty:-t.titleBox.height/2+t.trace.title.font.size}}(v):C(v,h),r.attr(\"transform\",c(e.x,e.y)+u(Math.min(1,e.scale))+c(e.tx,e.ty))})),T&&function(t,e){var r,n,i,a,o,s,u,c,f,h,p,d,v;function y(t,e){return t.pxmid[1]-e.pxmid[1]}function m(t,e){return e.pxmid[1]-t.pxmid[1]}function x(t,r){r||(r={});var i,c,f,p,d=r.labelExtraY+(n?r.yLabelMax:r.yLabelMin),v=n?t.yLabelMin:t.yLabelMax,y=n?t.yLabelMax:t.yLabelMin,m=t.cyFinal+o(t.px0[1],t.px1[1]),x=d-v;if(x*u>0&&(t.labelExtraY=x),l.isArrayOrTypedArray(e.pull))for(c=0;c<h.length;c++)(f=h[c])===t||(g.castOption(e.pull,t.pts)||0)>=(g.castOption(e.pull,f.pts)||0)||((t.pxmid[1]-f.pxmid[1])*u>0?(x=f.cyFinal+o(f.px0[1],f.px1[1])-v-t.labelExtraY)*u>0&&(t.labelExtraY+=x):(y+t.labelExtraY-m)*u>0&&(i=3*s*Math.abs(c-h.indexOf(t)),(p=f.cxFinal+a(f.px0[0],f.px1[0])+i-(t.cxFinal+t.pxmid[0])-t.labelExtraX)*s>0&&(t.labelExtraX+=p)))}for(n=0;n<2;n++)for(i=n?y:m,o=n?Math.max:Math.min,u=n?1:-1,r=0;r<2;r++){for(a=r?Math.max:Math.min,s=r?1:-1,(c=t[n][r]).sort(i),f=t[1-n][r],h=f.concat(c),d=[],p=0;p<c.length;p++)void 0!==c[p].yLabelMid&&d.push(c[p]);for(v=!1,p=0;n&&p<f.length;p++)if(void 0!==f[p].yLabelMid){v=f[p];break}for(p=0;p<d.length;p++){var b=p&&d[p-1];v&&!p&&(b=v),x(d[p],b)}}}(_,y),function(t,e){t.each((function(t){var r=n.select(this);if(t.labelExtraX||t.labelExtraY){var i=r.select(\"g.slicetext text\");t.transform.targetX+=t.labelExtraX,t.transform.targetY+=t.labelExtraY,l.setTransormAndDisplay(i,t.transform);var a=t.cxFinal+t.pxmid[0],s=\"M\"+a+\",\"+(t.cyFinal+t.pxmid[1]),u=(t.yLabelMax-t.yLabelMin)*(t.pxmid[0]<0?-1:1)/4;if(t.labelExtraX){var c=t.labelExtraX*t.pxmid[1]/t.pxmid[0],f=t.yLabelMid+t.labelExtraY-(t.cyFinal+t.pxmid[1]);Math.abs(c)>Math.abs(f)?s+=\"l\"+f*t.pxmid[0]/t.pxmid[1]+\",\"+f+\"H\"+(a+t.labelExtraX+u):s+=\"l\"+t.labelExtraX+\",\"+c+\"v\"+(f-c)+\"h\"+u}else s+=\"V\"+(t.yLabelMid+t.labelExtraY)+\"h\"+u;l.ensureSingle(r,\"path\",\"textline\").call(o.stroke,e.outsidetextfont.color).attr({\"stroke-width\":Math.min(2,e.outsidetextfont.size/8),d:s,fill:\"none\"})}else r.select(\"path.textline\").remove()}))}(m,y),T&&y.automargin){var A=s.bBox(d.node()),M=y.domain,S=h.w*(M.x[1]-M.x[0]),E=h.h*(M.y[1]-M.y[0]),P=(.5*S-v.r)/h.w,O=(.5*E-v.r)/h.h;i.autoMargin(t,\"pie.\"+y.uid+\".automargin\",{xl:M.x[0]-P,xr:M.x[1]+P,yb:M.y[0]-O,yt:M.y[1]+O,l:Math.max(v.cx-v.r-A.left,0),r:Math.max(A.right-(v.cx+v.r),0),b:Math.max(A.bottom-(v.cy+v.r),0),t:Math.max(v.cy-v.r-A.top,0),pad:5})}}))}));setTimeout((function(){v.selectAll(\"tspan\").each((function(){var t=n.select(this);t.attr(\"dy\")&&t.attr(\"dy\",t.attr(\"dy\"))}))}),0)},formatSliceLabel:z,transformInsideText:w,determineInsideTextFont:b,positionTitleOutside:C,prerenderTitles:_,layoutAreas:I,attachFxHandlers:x,computeTransform:R}},22152:function(t,e,r){\"use strict\";var n=r(33428),i=r(10528),a=r(82744).resizeText;t.exports=function(t){var e=t._fullLayout._pielayer.selectAll(\".trace\");a(t,e,\"pie\"),e.each((function(e){var r=e[0].trace,a=n.select(this);a.style({opacity:r.opacity}),a.selectAll(\"path.surface\").each((function(e){n.select(this).call(i,e,r,t)}))}))}},10528:function(t,e,r){\"use strict\";var n=r(76308),i=r(69656).castOption,a=r(21552);t.exports=function(t,e,r,o){var s=r.marker.line,l=i(s.color,e.pts)||n.defaultLine,u=i(s.width,e.pts)||0;t.call(a,e,r,o).style(\"stroke-width\",u).call(n.stroke,l)}},35484:function(t,e,r){\"use strict\";var n=r(52904);t.exports={x:n.x,y:n.y,xy:{valType:\"data_array\",editType:\"calc\"},indices:{valType:\"data_array\",editType:\"calc\"},xbounds:{valType:\"data_array\",editType:\"calc\"},ybounds:{valType:\"data_array\",editType:\"calc\"},text:n.text,marker:{color:{valType:\"color\",arrayOk:!1,editType:\"calc\"},opacity:{valType:\"number\",min:0,max:1,dflt:1,arrayOk:!1,editType:\"calc\"},blend:{valType:\"boolean\",dflt:null,editType:\"calc\"},sizemin:{valType:\"number\",min:.1,max:2,dflt:.5,editType:\"calc\"},sizemax:{valType:\"number\",min:.1,dflt:20,editType:\"calc\"},border:{color:{valType:\"color\",arrayOk:!1,editType:\"calc\"},arearatio:{valType:\"number\",min:0,max:1,dflt:0,editType:\"calc\"},editType:\"calc\"},editType:\"calc\"},transforms:void 0}},11072:function(t,e,r){\"use strict\";var n=r(67792).gl_pointcloud2d,i=r(3400).isArrayOrTypedArray,a=r(43080),o=r(19280).findExtremes,s=r(44928);function l(t,e){this.scene=t,this.uid=e,this.type=\"pointcloud\",this.pickXData=[],this.pickYData=[],this.xData=[],this.yData=[],this.textLabels=[],this.color=\"rgb(0, 0, 0)\",this.name=\"\",this.hoverinfo=\"all\",this.idToIndex=new Int32Array(0),this.bounds=[0,0,0,0],this.pointcloudOptions={positions:new Float32Array(0),idToIndex:this.idToIndex,sizemin:.5,sizemax:12,color:[0,0,0,1],areaRatio:1,borderColor:[0,0,0,1]},this.pointcloud=n(t.glplot,this.pointcloudOptions),this.pointcloud._trace=this}var u=l.prototype;u.handlePick=function(t){var e=this.idToIndex[t.pointId];return{trace:this,dataCoord:t.dataCoord,traceCoord:this.pickXYData?[this.pickXYData[2*e],this.pickXYData[2*e+1]]:[this.pickXData[e],this.pickYData[e]],textLabel:i(this.textLabels)?this.textLabels[e]:this.textLabels,color:this.color,name:this.name,pointIndex:e,hoverinfo:this.hoverinfo}},u.update=function(t){this.index=t.index,this.textLabels=t.text,this.name=t.name,this.hoverinfo=t.hoverinfo,this.bounds=[1/0,1/0,-1/0,-1/0],this.updateFast(t),this.color=s(t,{})},u.updateFast=function(t){var e,r,n,i,s,l,u=this.xData=this.pickXData=t.x,c=this.yData=this.pickYData=t.y,f=this.pickXYData=t.xy,h=t.xbounds&&t.ybounds,p=t.indices,d=this.bounds;if(f){if(n=f,e=f.length>>>1,h)d[0]=t.xbounds[0],d[2]=t.xbounds[1],d[1]=t.ybounds[0],d[3]=t.ybounds[1];else for(l=0;l<e;l++)i=n[2*l],s=n[2*l+1],i<d[0]&&(d[0]=i),i>d[2]&&(d[2]=i),s<d[1]&&(d[1]=s),s>d[3]&&(d[3]=s);if(p)r=p;else for(r=new Int32Array(e),l=0;l<e;l++)r[l]=l}else for(e=u.length,n=new Float32Array(2*e),r=new Int32Array(e),l=0;l<e;l++)i=u[l],s=c[l],r[l]=l,n[2*l]=i,n[2*l+1]=s,i<d[0]&&(d[0]=i),i>d[2]&&(d[2]=i),s<d[1]&&(d[1]=s),s>d[3]&&(d[3]=s);this.idToIndex=r,this.pointcloudOptions.idToIndex=r,this.pointcloudOptions.positions=n;var v=a(t.marker.color),g=a(t.marker.border.color),y=t.opacity*t.marker.opacity;v[3]*=y,this.pointcloudOptions.color=v;var m=t.marker.blend;null===m&&(m=u.length<100||c.length<100),this.pointcloudOptions.blend=m,g[3]*=y,this.pointcloudOptions.borderColor=g;var x=t.marker.sizemin,b=Math.max(t.marker.sizemax,t.marker.sizemin);this.pointcloudOptions.sizeMin=x,this.pointcloudOptions.sizeMax=b,this.pointcloudOptions.areaRatio=t.marker.border.arearatio,this.pointcloud.update(this.pointcloudOptions);var _=this.scene.xaxis,w=this.scene.yaxis,T=b/2||.5;t._extremes[_._id]=o(_,[d[0],d[2]],{ppad:T}),t._extremes[w._id]=o(w,[d[1],d[3]],{ppad:T})},u.dispose=function(){this.pointcloud.dispose()},t.exports=function(t,e){var r=new l(t,e.uid);return 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e.trace=t.trace,e.curveNumber=t.trace.index,{circular:t.circular,key:a,traceId:t.key,pointNumber:e.pointNumber,link:e,tinyColorHue:c.tinyRGB(n),tinyColorAlpha:n.getAlpha(),tinyColorHoverHue:c.tinyRGB(i),tinyColorHoverAlpha:i.getAlpha(),linkPath:M,linkLineColor:t.linkLineColor,linkLineWidth:t.linkLineWidth,linkArrowLength:t.linkArrowLength,valueFormat:t.valueFormat,valueSuffix:t.valueSuffix,sankey:t.sankey,parent:t,interactionState:t.interactionState,flow:e.flow}}function M(){return function(t){var e=t.linkArrowLength;if(t.link.circular)return function(t,e){var r=t.width/2,n=t.circularPathData;return\"top\"===t.circularLinkType?\"M \"+(n.targetX-e)+\" \"+(n.targetY+r)+\" L\"+(n.rightInnerExtent-e)+\" \"+(n.targetY+r)+\"A\"+(n.rightLargeArcRadius+r)+\" \"+(n.rightSmallArcRadius+r)+\" 0 0 1 \"+(n.rightFullExtent-r-e)+\" \"+(n.targetY-n.rightSmallArcRadius)+\"L\"+(n.rightFullExtent-r-e)+\" \"+n.verticalRightInnerExtent+\"A\"+(n.rightLargeArcRadius+r)+\" \"+(n.rightLargeArcRadius+r)+\" 0 0 1 \"+(n.rightInnerExtent-e)+\" \"+(n.verticalFullExtent-r)+\"L\"+n.leftInnerExtent+\" \"+(n.verticalFullExtent-r)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftLargeArcRadius+r)+\" 0 0 1 \"+(n.leftFullExtent+r)+\" \"+n.verticalLeftInnerExtent+\"L\"+(n.leftFullExtent+r)+\" \"+(n.sourceY-n.leftSmallArcRadius)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftSmallArcRadius+r)+\" 0 0 1 \"+n.leftInnerExtent+\" \"+(n.sourceY+r)+\"L\"+n.sourceX+\" \"+(n.sourceY+r)+\"L\"+n.sourceX+\" \"+(n.sourceY-r)+\"L\"+n.leftInnerExtent+\" \"+(n.sourceY-r)+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftSmallArcRadius-r)+\" 0 0 0 \"+(n.leftFullExtent-r)+\" \"+(n.sourceY-n.leftSmallArcRadius)+\"L\"+(n.leftFullExtent-r)+\" \"+n.verticalLeftInnerExtent+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftLargeArcRadius-r)+\" 0 0 0 \"+n.leftInnerExtent+\" \"+(n.verticalFullExtent+r)+\"L\"+(n.rightInnerExtent-e)+\" \"+(n.verticalFullExtent+r)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightLargeArcRadius-r)+\" 0 0 0 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\"+(n.sourceY+n.leftSmallArcRadius)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftSmallArcRadius+r)+\" 0 0 0 \"+n.leftInnerExtent+\" \"+(n.sourceY-r)+\"L\"+n.sourceX+\" \"+(n.sourceY-r)+\"L\"+n.sourceX+\" \"+(n.sourceY+r)+\"L\"+n.leftInnerExtent+\" \"+(n.sourceY+r)+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftSmallArcRadius-r)+\" 0 0 1 \"+(n.leftFullExtent-r)+\" \"+(n.sourceY+n.leftSmallArcRadius)+\"L\"+(n.leftFullExtent-r)+\" \"+n.verticalLeftInnerExtent+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftLargeArcRadius-r)+\" 0 0 1 \"+n.leftInnerExtent+\" \"+(n.verticalFullExtent-r)+\"L\"+(n.rightInnerExtent-e)+\" \"+(n.verticalFullExtent-r)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightLargeArcRadius-r)+\" 0 0 1 \"+(n.rightFullExtent+r-e)+\" \"+n.verticalRightInnerExtent+\"L\"+(n.rightFullExtent+r-e)+\" \"+(n.targetY+n.rightSmallArcRadius)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightSmallArcRadius-r)+\" 0 0 1 \"+(n.rightInnerExtent-e)+\" \"+(n.targetY+r)+\"L\"+(n.targetX-e)+\" \"+(n.targetY+r)+(e>0?\"L\"+n.targetX+\" \"+n.targetY:\"\")+\"Z\"}(t.link,e);var r=Math.abs((t.link.target.x0-t.link.source.x1)/2);e>r&&(e=r);var n=t.link.source.x1,a=t.link.target.x0-e,o=i(n,a),s=o(.5),l=o(.5),u=t.link.y0-t.link.width/2,c=t.link.y0+t.link.width/2,f=t.link.y1-t.link.width/2,h=t.link.y1+t.link.width/2,p=\"M\"+n+\",\"+u,d=\"C\"+s+\",\"+u+\" \"+l+\",\"+f+\" \"+a+\",\"+f,v=\"C\"+l+\",\"+h+\" \"+s+\",\"+c+\" \"+n+\",\"+c,g=e>0?\"L\"+(a+e)+\",\"+(f+t.link.width/2):\"\";return p+d+(g+=\"L\"+a+\",\"+h)+v+\"Z\"}}function S(t,e){var r=u(e.color),n=l.nodePadAcross,i=t.nodePad/2;e.dx=e.x1-e.x0,e.dy=e.y1-e.y0;var a=e.dx,o=Math.max(.5,e.dy),s=\"node_\"+e.pointNumber;return e.group&&(s=h.randstr()),e.trace=t.trace,e.curveNumber=t.trace.index,{index:e.pointNumber,key:s,partOfGroup:e.partOfGroup||!1,group:e.group,traceId:t.key,trace:t.trace,node:e,nodePad:t.nodePad,nodeLineColor:t.nodeLineColor,nodeLineWidth:t.nodeLineWidth,textFont:t.textFont,size:t.horizontal?t.height:t.width,visibleWidth:Math.ceil(a),visibleHeight:o,zoneX:-n,zoneY:-i,zoneWidth:a+2*n,zoneHeight:o+2*i,labelY:t.horizontal?e.dy/2+1:e.dx/2+1,left:1===e.originalLayer,sizeAcross:t.width,forceLayouts:t.forceLayouts,horizontal:t.horizontal,darkBackground:r.getBrightness()<=128,tinyColorHue:c.tinyRGB(r),tinyColorAlpha:r.getAlpha(),valueFormat:t.valueFormat,valueSuffix:t.valueSuffix,sankey:t.sankey,graph:t.graph,arrangement:t.arrangement,uniqueNodeLabelPathId:[t.guid,t.key,s].join(\"_\"),interactionState:t.interactionState,figure:t}}function E(t){t.attr(\"transform\",(function(t){return p(t.node.x0.toFixed(3),t.node.y0.toFixed(3))}))}function L(t){t.call(E)}function C(t,e){t.call(L),e.attr(\"d\",M())}function P(t){t.attr(\"width\",(function(t){return t.node.x1-t.node.x0})).attr(\"height\",(function(t){return t.visibleHeight}))}function O(t){return t.link.width>1||t.linkLineWidth>0}function I(t){return p(t.translateX,t.translateY)+(t.horizontal?\"matrix(1 0 0 1 0 0)\":\"matrix(0 1 1 0 0 0)\")}function D(t,e,r){t.on(\".basic\",null).on(\"mouseover.basic\",(function(t){t.interactionState.dragInProgress||t.partOfGroup||(r.hover(this,t,e),t.interactionState.hovered=[this,t])})).on(\"mousemove.basic\",(function(t){t.interactionState.dragInProgress||t.partOfGroup||(r.follow(this,t),t.interactionState.hovered=[this,t])})).on(\"mouseout.basic\",(function(t){t.interactionState.dragInProgress||t.partOfGroup||(r.unhover(this,t,e),t.interactionState.hovered=!1)})).on(\"click.basic\",(function(t){t.interactionState.hovered&&(r.unhover(this,t,e),t.interactionState.hovered=!1),t.interactionState.dragInProgress||t.partOfGroup||r.select(this,t,e)}))}function z(t,e,r,i){var o=a.behavior.drag().origin((function(t){return{x:t.node.x0+t.visibleWidth/2,y:t.node.y0+t.visibleHeight/2}})).on(\"dragstart\",(function(a){if(\"fixed\"!==a.arrangement&&(h.ensureSingle(i._fullLayout._infolayer,\"g\",\"dragcover\",(function(t){i._fullLayout._dragCover=t})),h.raiseToTop(this),a.interactionState.dragInProgress=a.node,F(a.node),a.interactionState.hovered&&(r.nodeEvents.unhover.apply(0,a.interactionState.hovered),a.interactionState.hovered=!1),\"snap\"===a.arrangement)){var o=a.traceId+\"|\"+a.key;a.forceLayouts[o]?a.forceLayouts[o].alpha(1):function(t,e,r,i){!function(t){for(var e=0;e<t.length;e++)t[e].y=(t[e].y0+t[e].y1)/2,t[e].x=(t[e].x0+t[e].x1)/2}(r.graph.nodes);var a=r.graph.nodes.filter((function(t){return t.originalX===r.node.originalX})).filter((function(t){return!t.partOfGroup}));r.forceLayouts[e]=n.forceSimulation(a).alphaDecay(0).force(\"collide\",n.forceCollide().radius((function(t){return t.dy/2+r.nodePad/2})).strength(1).iterations(l.forceIterations)).force(\"constrain\",function(t,e,r,n){return function(){for(var t=0,i=0;i<r.length;i++){var a=r[i];a===n.interactionState.dragInProgress?(a.x=a.lastDraggedX,a.y=a.lastDraggedY):(a.vx=(a.originalX-a.x)/l.forceTicksPerFrame,a.y=Math.min(n.size-a.dy/2,Math.max(a.dy/2,a.y))),t=Math.max(t,Math.abs(a.vx),Math.abs(a.vy))}!n.interactionState.dragInProgress&&t<.1&&n.forceLayouts[e].alpha()>0&&n.forceLayouts[e].alpha(0)}}(0,e,a,r)).stop()}(0,o,a),function(t,e,r,n,i){window.requestAnimationFrame((function a(){var o;for(o=0;o<l.forceTicksPerFrame;o++)r.forceLayouts[n].tick();if(function(t){for(var e=0;e<t.length;e++)t[e].y0=t[e].y-t[e].dy/2,t[e].y1=t[e].y0+t[e].dy,t[e].x0=t[e].x-t[e].dx/2,t[e].x1=t[e].x0+t[e].dx}(r.graph.nodes),r.sankey.update(r.graph),C(t.filter(B(r)),e),r.forceLayouts[n].alpha()>0)window.requestAnimationFrame(a);else{var 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a=(t.graph.nodes[i].x0+t.graph.nodes[i].x1)/2,o=(t.graph.nodes[i].y0+t.graph.nodes[i].y1)/2;r.push(a/t.figure.width),n.push(o/t.figure.height)}b.call(\"_guiRestyle\",e,{\"node.x\":[r],\"node.y\":[n]},t.trace.index).then((function(){e._fullLayout._dragCover&&e._fullLayout._dragCover.remove()}))}function F(t){t.lastDraggedX=t.x0+t.dx/2,t.lastDraggedY=t.y0+t.dy/2}function B(t){return function(e){return e.node.originalX===t.node.originalX}}t.exports=function(t,e,r,n,i){var o=t._context.staticPlot,s=!1;h.ensureSingle(t._fullLayout._infolayer,\"g\",\"first-render\",(function(){s=!0}));var v=t._fullLayout._dragCover,b=r.filter((function(t){return m(t).trace.visible})).map(k.bind(null,n)),_=e.selectAll(\".\"+l.cn.sankey).data(b,g);_.exit().remove(),_.enter().append(\"g\").classed(l.cn.sankey,!0).style(\"box-sizing\",\"content-box\").style(\"position\",\"absolute\").style(\"left\",0).style(\"shape-rendering\",\"geometricPrecision\").style(\"pointer-events\",o?\"none\":\"auto\").attr(\"transform\",I),_.each((function(e,r){t._fullData[r]._sankey=e;var n=\"bgsankey-\"+e.trace.uid+\"-\"+r;h.ensureSingle(t._fullLayout._draggers,\"rect\",n),t._fullData[r]._bgRect=a.select(\".\"+n),t._fullData[r]._bgRect.style(\"pointer-events\",o?\"none\":\"all\").attr(\"width\",e.width).attr(\"height\",e.height).attr(\"x\",e.translateX).attr(\"y\",e.translateY).classed(\"bgsankey\",!0).style({fill:\"transparent\",\"stroke-width\":0})})),_.transition().ease(l.ease).duration(l.duration).attr(\"transform\",I);var L=_.selectAll(\".\"+l.cn.sankeyLinks).data(y,g);L.enter().append(\"g\").classed(l.cn.sankeyLinks,!0).style(\"fill\",\"none\");var C=L.selectAll(\".\"+l.cn.sankeyLink).data((function(t){return t.graph.links.filter((function(t){return t.value})).map(A.bind(null,t))}),g);C.enter().append(\"path\").classed(l.cn.sankeyLink,!0).call(D,_,i.linkEvents),C.style(\"stroke\",(function(t){return O(t)?c.tinyRGB(u(t.linkLineColor)):t.tinyColorHue})).style(\"stroke-opacity\",(function(t){return O(t)?c.opacity(t.linkLineColor):t.tinyColorAlpha})).style(\"fill\",(function(t){return t.tinyColorHue})).style(\"fill-opacity\",(function(t){return t.tinyColorAlpha})).style(\"stroke-width\",(function(t){return O(t)?t.linkLineWidth:1})).attr(\"d\",M()),C.style(\"opacity\",(function(){return t._context.staticPlot||s||v?1:0})).transition().ease(l.ease).duration(l.duration).style(\"opacity\",1),C.exit().transition().ease(l.ease).duration(l.duration).style(\"opacity\",0).remove();var R=_.selectAll(\".\"+l.cn.sankeyNodeSet).data(y,g);R.enter().append(\"g\").classed(l.cn.sankeyNodeSet,!0),R.style(\"cursor\",(function(t){switch(t.arrangement){case\"fixed\":return\"default\";case\"perpendicular\":return\"ns-resize\";default:return\"move\"}}));var F=R.selectAll(\".\"+l.cn.sankeyNode).data((function(t){var e=t.graph.nodes;return function(t){var e,r=[];for(e=0;e<t.length;e++)t[e].originalX=(t[e].x0+t[e].x1)/2,t[e].originalY=(t[e].y0+t[e].y1)/2,-1===r.indexOf(t[e].originalX)&&r.push(t[e].originalX);for(r.sort((function(t,e){return t-e})),e=0;e<t.length;e++)t[e].originalLayerIndex=r.indexOf(t[e].originalX),t[e].originalLayer=t[e].originalLayerIndex/(r.length-1)}(e),e.map(S.bind(null,t))}),g);F.enter().append(\"g\").classed(l.cn.sankeyNode,!0).call(E).style(\"opacity\",(function(e){return!t._context.staticPlot&&!s||e.partOfGroup?0:1})),F.call(D,_,i.nodeEvents).call(z,C,i,t),F.transition().ease(l.ease).duration(l.duration).call(E).style(\"opacity\",(function(t){return t.partOfGroup?0:1})),F.exit().transition().ease(l.ease).duration(l.duration).style(\"opacity\",0).remove();var B=F.selectAll(\".\"+l.cn.nodeRect).data(y);B.enter().append(\"rect\").classed(l.cn.nodeRect,!0).call(P),B.style(\"stroke-width\",(function(t){return t.nodeLineWidth})).style(\"stroke\",(function(t){return c.tinyRGB(u(t.nodeLineColor))})).style(\"stroke-opacity\",(function(t){return c.opacity(t.nodeLineColor)})).style(\"fill\",(function(t){return t.tinyColorHue})).style(\"fill-opacity\",(function(t){return t.tinyColorAlpha})),B.transition().ease(l.ease).duration(l.duration).call(P);var N=F.selectAll(\".\"+l.cn.nodeLabel).data(y);N.enter().append(\"text\").classed(l.cn.nodeLabel,!0).style(\"cursor\",\"default\"),N.attr(\"data-notex\",1).text((function(t){return t.node.label})).each((function(e){var r=a.select(this);f.font(r,e.textFont),x.convertToTspans(r,t)})).style(\"text-shadow\",x.makeTextShadow(t._fullLayout.paper_bgcolor)).attr(\"text-anchor\",(function(t){return 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n=r(94288).hasColorscale,i=r(47128),a=r(43028);t.exports=function(t,e){a.hasLines(e)&&n(e,\"line\")&&i(t,e,{vals:e.line.color,containerStr:\"line\",cLetter:\"c\"}),a.hasMarkers(e)&&(n(e,\"marker\")&&i(t,e,{vals:e.marker.color,containerStr:\"marker\",cLetter:\"c\"}),n(e,\"marker.line\")&&i(t,e,{vals:e.marker.line.color,containerStr:\"marker.line\",cLetter:\"c\"}))}},88200:function(t){\"use strict\";t.exports={PTS_LINESONLY:20,minTolerance:.2,toleranceGrowth:10,maxScreensAway:20,eventDataKeys:[]}},96664:function(t,e,r){\"use strict\";var n=r(16356),i=r(96376).setGroupPositions;function a(t,e,r,n,i,a,o){i[n]=!0;var s={i:null,gap:!0,s:0};if(s[o]=r,t.splice(e,0,s),e&&r===t[e-1][o]){var l=t[e-1];s.s=l.s,s.i=l.i,s.gap=l.gap}else a&&(s.s=function(t,e,r,n){var i=t[e-1],a=t[e+1];return a?i?i.s+(a.s-i.s)*(r-i[n])/(a[n]-i[n]):a.s:i.s}(t,e,r,o));e||(t[0].t=t[1].t,t[0].trace=t[1].trace,delete t[1].t,delete 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n=r(21776).Ks,i=r(21776).Gw,a=r(98304),o=r(52904),s=r(45464),l=r(49084),u=r(98192).u,c=r(92880).extendFlat,f=r(67824).overrideAll,h=o.marker,p=o.line,d=h.line;t.exports=f({lon:{valType:\"data_array\"},lat:{valType:\"data_array\"},locations:{valType:\"data_array\"},locationmode:{valType:\"enumerated\",values:[\"ISO-3\",\"USA-states\",\"country 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if(\"vh\"===e.line.shape){for(n=[],i=0;i<o-1;i++)isNaN(r[2*i])||isNaN(r[2*i+1])?n.push(NaN,NaN,NaN,NaN):(n.push(r[2*i],r[2*i+1]),isNaN(r[2*i+2])||isNaN(r[2*i+3])?n.push(NaN,NaN):n.push(r[2*i],r[2*i+3]));n.push(r[a-2],r[a-1])}else n=r;var u=!1;for(i=0;i<n.length;i++)if(isNaN(n[i])){u=!0;break}var c=u||n.length>v.TOO_MANY_POINTS||h.hasMarkers(e)?\"rect\":\"round\";if(u&&e.connectgaps){var f=n[0],p=n[1];for(i=0;i<n.length;i+=2)isNaN(n[i])||isNaN(n[i+1])?(n[i]=f,n[i+1]=p):(f=n[i],p=n[i+1])}return{join:c,positions:n}},errorBarPositions:function(t,e,r,i,a){var s=o.getComponentMethod(\"errorbars\",\"makeComputeError\"),l=c.getFromId(t,e.xaxis,\"x\"),u=c.getFromId(t,e.yaxis,\"y\"),f=r.length/2,h={};function p(t,i){var a=i._id.charAt(0),o=e[\"error_\"+a];if(o&&o.visible&&(\"linear\"===i.type||\"log\"===i.type)){for(var l=s(o),u={x:0,y:1}[a],c={x:[0,1,2,3],y:[2,3,0,1]}[a],p=new Float64Array(4*f),d=1/0,v=-1/0,g=0,y=0;g<f;g++,y+=4){var m=t[g];if(n(m)){var x=r[2*g+u],b=l(m,g),_=b[0],w=b[1];if(n(_)&&n(w)){var T=m-_,k=m+w;p[y+c[0]]=x-i.c2l(T),p[y+c[1]]=i.c2l(k)-x,p[y+c[2]]=0,p[y+c[3]]=0,d=Math.min(d,m-_),v=Math.max(v,m+w)}}}h[a]={positions:r,errors:p,_bnds:[d,v]}}}return p(i,l),p(a,u),h},textPosition:function(t,e,r,n){var i,a=e._length,o={};if(h.hasMarkers(e)){var s=r.font,u=r.align,c=r.baseline;for(o.offset=new Array(a),i=0;i<a;i++){var f=n.sizes?n.sizes[i]:n.size,p=l(s)?s[i].size:s.size,d=l(u)?u.length>1?u[i]:u[0]:u,v=l(c)?c.length>1?c[i]:c[0]:c,g=y[d],m=y[v],x=f?f/.8+1:0,b=-m*x-.5*m;o.offset[i]=[g*x/p,b/p]}}return o}}},80220:function(t,e,r){\"use strict\";var n=r(3400),i=r(24040),a=r(80088),o=r(2876),s=r(88200),l=r(43028),u=r(43980),c=r(31147),f=r(74428),h=r(66828),p=r(70840),d=r(124);t.exports=function(t,e,r,v){function g(r,i){return n.coerce(t,e,o,r,i)}var y=!!t.marker&&a.isOpenSymbol(t.marker.symbol),m=l.isBubble(t),x=u(t,e,v,g);if(x){c(t,e,v,g),g(\"xhoverformat\"),g(\"yhoverformat\");var b=x<s.PTS_LINESONLY?\"lines+markers\":\"lines\";g(\"text\"),g(\"hovertext\"),g(\"hovertemplate\"),g(\"mode\",b),l.hasMarkers(e)&&(f(t,e,r,v,g,{noAngleRef:!0,noStandOff:!0}),g(\"marker.line.width\",y||m?1:0)),l.hasLines(e)&&(g(\"connectgaps\"),h(t,e,r,v,g),g(\"line.shape\")),l.hasText(e)&&(g(\"texttemplate\"),d(t,e,v,g));var _=(e.line||{}).color,w=(e.marker||{}).color;g(\"fill\"),\"none\"!==e.fill&&p(t,e,r,g);var T=i.getComponentMethod(\"errorbars\",\"supplyDefaults\");T(t,e,_||w||r,{axis:\"y\"}),T(t,e,_||w||r,{axis:\"x\",inherit:\"y\"}),n.coerceSelectionMarkerOpacity(e,g)}else e.visible=!1}},26768:function(t,e,r){\"use strict\";var n=r(3400),i=r(76308),a=r(13448).DESELECTDIM;t.exports={styleTextSelection:function(t){var e,r,o=t[0],s=o.trace,l=o.t,u=l._scene,c=l.index,f=u.selectBatch[c],h=u.unselectBatch[c],p=u.textOptions[c],d=u.textSelectedOptions[c]||{},v=u.textUnselectedOptions[c]||{},g=n.extendFlat({},p);if(f.length||h.length){var y=d.color,m=v.color,x=p.color,b=n.isArrayOrTypedArray(x);for(g.color=new Array(s._length),e=0;e<f.length;e++)r=f[e],g.color[r]=y||(b?x[r]:x);for(e=0;e<h.length;e++){r=h[e];var _=b?x[r]:x;g.color[r]=m||(y?_:i.addOpacity(_,a))}}u.glText[c].update(g)}}},99396:function(t,e,r){\"use strict\";var n=r(76688);t.exports=function(t,e,r){var i=t.i;return\"x\"in t||(t.x=e._x[i]),\"y\"in t||(t.y=e._y[i]),n(t,e,r)}},80088:function(t,e,r){\"use strict\";var n=r(67072);e.isOpenSymbol=function(t){return\"string\"==typeof t?n.OPEN_RE.test(t):t%200>100},e.isDotSymbol=function(t){return\"string\"==typeof t?n.DOT_RE.test(t):t>200}},41272:function(t,e,r){\"use strict\";var n=r(24040),i=r(3400),a=r(44928);function o(t,e,r,o){var s=t.xa,l=t.ya,u=t.distance,c=t.dxy,f=t.index,h={pointNumber:f,x:e[f],y:r[f]};h.tx=i.isArrayOrTypedArray(o.text)?o.text[f]:o.text,h.htx=Array.isArray(o.hovertext)?o.hovertext[f]:o.hovertext,h.data=Array.isArray(o.customdata)?o.customdata[f]:o.customdata,h.tp=Array.isArray(o.textposition)?o.textposition[f]:o.textposition;var p=o.textfont;p&&(h.ts=i.isArrayOrTypedArray(p.size)?p.size[f]:p.size,h.tc=Array.isArray(p.color)?p.color[f]:p.color,h.tf=Array.isArray(p.family)?p.family[f]:p.family);var d=o.marker;d&&(h.ms=i.isArrayOrTypedArray(d.size)?d.size[f]:d.size,h.mo=i.isArrayOrTypedArray(d.opacity)?d.opacity[f]:d.opacity,h.mx=i.isArrayOrTypedArray(d.symbol)?d.symbol[f]:d.symbol,h.ma=i.isArrayOrTypedArray(d.angle)?d.angle[f]:d.angle,h.mc=i.isArrayOrTypedArray(d.color)?d.color[f]:d.color);var v=d&&d.line;v&&(h.mlc=Array.isArray(v.color)?v.color[f]:v.color,h.mlw=i.isArrayOrTypedArray(v.width)?v.width[f]:v.width);var g=d&&d.gradient;g&&\"none\"!==g.type&&(h.mgt=Array.isArray(g.type)?g.type[f]:g.type,h.mgc=Array.isArray(g.color)?g.color[f]:g.color);var y=s.c2p(h.x,!0),m=l.c2p(h.y,!0),x=h.mrc||1,b=o.hoverlabel;b&&(h.hbg=Array.isArray(b.bgcolor)?b.bgcolor[f]:b.bgcolor,h.hbc=Array.isArray(b.bordercolor)?b.bordercolor[f]:b.bordercolor,h.hts=i.isArrayOrTypedArray(b.font.size)?b.font.size[f]:b.font.size,h.htc=Array.isArray(b.font.color)?b.font.color[f]:b.font.color,h.htf=Array.isArray(b.font.family)?b.font.family[f]:b.font.family,h.hnl=i.isArrayOrTypedArray(b.namelength)?b.namelength[f]:b.namelength);var _=o.hoverinfo;_&&(h.hi=Array.isArray(_)?_[f]:_);var w=o.hovertemplate;w&&(h.ht=Array.isArray(w)?w[f]:w);var T={};T[t.index]=h;var k=o._origX,A=o._origY,M=i.extendFlat({},t,{color:a(o,h),x0:y-x,x1:y+x,xLabelVal:k?k[f]:h.x,y0:m-x,y1:m+x,yLabelVal:A?A[f]:h.y,cd:T,distance:u,spikeDistance:c,hovertemplate:h.ht});return h.htx?M.text=h.htx:h.tx?M.text=h.tx:o.text&&(M.text=o.text),i.fillText(h,o,M),n.getComponentMethod(\"errorbars\",\"hoverInfo\")(h,o,M),M}t.exports={hoverPoints:function(t,e,r,n){var i,a,s,l,u,c,f,h,p,d,v=t.cd,g=v[0].t,y=v[0].trace,m=t.xa,x=t.ya,b=g.x,_=g.y,w=m.c2p(e),T=x.c2p(r),k=t.distance;if(g.tree){var A=m.p2c(w-k),M=m.p2c(w+k),S=x.p2c(T-k),E=x.p2c(T+k);i=\"x\"===n?g.tree.range(Math.min(A,M),Math.min(x._rl[0],x._rl[1]),Math.max(A,M),Math.max(x._rl[0],x._rl[1])):g.tree.range(Math.min(A,M),Math.min(S,E),Math.max(A,M),Math.max(S,E))}else i=g.ids;var L=k;if(\"x\"===n){var C=!!y.xperiodalignment,P=!!y.yperiodalignment;for(c=0;c<i.length;c++){if(l=b[a=i[c]],f=Math.abs(m.c2p(l)-w),C){var O=m.c2p(y._xStarts[a]),I=m.c2p(y._xEnds[a]);f=w>=Math.min(O,I)&&w<=Math.max(O,I)?0:1/0}if(f<L){if(L=f,u=_[a],h=x.c2p(u)-T,P){var D=x.c2p(y._yStarts[a]),z=x.c2p(y._yEnds[a]);h=T>=Math.min(D,z)&&T<=Math.max(D,z)?0:1/0}d=Math.sqrt(f*f+h*h),s=i[c]}}}else for(c=i.length-1;c>-1;c--)l=b[a=i[c]],u=_[a],f=m.c2p(l)-w,h=x.c2p(u)-T,(p=Math.sqrt(f*f+h*h))<L&&(L=d=p,s=a);return t.index=s,t.distance=L,t.dxy=d,void 0===s?[t]:[o(t,b,_,y)]},calcHover:o}},38983:function(t,e,r){\"use strict\";var n=r(64628);n.plot=r(89876),t.exports=n},89876:function(t,e,r){\"use strict\";var n=r(38540),i=r(13472),a=r(24544),o=r(23352),s=r(3400),l=r(72760).selectMode,u=r(5048),c=r(43028),f=r(14328),h=r(26768).styleTextSelection,p={};function d(t,e,r,n){var i=t._size,a=t.width*n,o=t.height*n,s=i.l*n,l=i.b*n,u=i.r*n,c=i.t*n,f=i.w*n,h=i.h*n;return[s+e.domain[0]*f,l+r.domain[0]*h,a-u-(1-e.domain[1])*f,o-c-(1-r.domain[1])*h]}(t.exports=function(t,e,r){if(r.length){var v,g,y=t._fullLayout,m=e._scene,x=e.xaxis,b=e.yaxis;if(m)if(u(t,[\"ANGLE_instanced_arrays\",\"OES_element_index_uint\"],p)){var _=m.count,w=y._glcanvas.data()[0].regl;if(f(t,e,r),m.dirty){if(!m.line2d&&!m.error2d||m.scatter2d||m.fill2d||m.glText||w.clear({}),!0===m.error2d&&(m.error2d=a(w)),!0===m.line2d&&(m.line2d=i(w)),!0===m.scatter2d&&(m.scatter2d=n(w)),!0===m.fill2d&&(m.fill2d=i(w)),!0===m.glText)for(m.glText=new Array(_),v=0;v<_;v++)m.glText[v]=new o(w);if(m.glText){if(_>m.glText.length){var T=_-m.glText.length;for(v=0;v<T;v++)m.glText.push(new o(w))}else if(_<m.glText.length){var k=m.glText.length-_;m.glText.splice(_,k).forEach((function(t){t.destroy()}))}for(v=0;v<_;v++)m.glText[v].update(m.textOptions[v])}if(m.line2d&&(m.line2d.update(m.lineOptions),m.lineOptions=m.lineOptions.map((function(t){if(t&&t.positions){for(var e=t.positions,r=0;r<e.length&&(isNaN(e[r])||isNaN(e[r+1]));)r+=2;for(var n=e.length-2;n>r&&(isNaN(e[n])||isNaN(e[n+1]));)n-=2;t.positions=e.slice(r,n+2)}return t})),m.line2d.update(m.lineOptions)),m.error2d){var A=(m.errorXOptions||[]).concat(m.errorYOptions||[]);m.error2d.update(A)}m.scatter2d&&m.scatter2d.update(m.markerOptions),m.fillOrder=s.repeat(null,_),m.fill2d&&(m.fillOptions=m.fillOptions.map((function(t,e){var n=r[e];if(t&&n&&n[0]&&n[0].trace){var i,a,o=n[0],s=o.trace,l=o.t,u=m.lineOptions[e],c=[];s._ownfill&&c.push(e),s._nexttrace&&c.push(e+1),c.length&&(m.fillOrder[e]=c);var f,h,p=[],d=u&&u.positions||l.positions;if(\"tozeroy\"===s.fill){for(f=0;f<d.length&&isNaN(d[f+1]);)f+=2;for(h=d.length-2;h>f&&isNaN(d[h+1]);)h-=2;0!==d[f+1]&&(p=[d[f],0]),p=p.concat(d.slice(f,h+2)),0!==d[h+1]&&(p=p.concat([d[h],0]))}else if(\"tozerox\"===s.fill){for(f=0;f<d.length&&isNaN(d[f]);)f+=2;for(h=d.length-2;h>f&&isNaN(d[h]);)h-=2;0!==d[f]&&(p=[0,d[f+1]]),p=p.concat(d.slice(f,h+2)),0!==d[h]&&(p=p.concat([0,d[h+1]]))}else if(\"toself\"===s.fill||\"tonext\"===s.fill){for(p=[],i=0,t.splitNull=!0,a=0;a<d.length;a+=2)(isNaN(d[a])||isNaN(d[a+1]))&&((p=p.concat(d.slice(i,a))).push(d[i],d[i+1]),p.push(null,null),i=a+2);p=p.concat(d.slice(i)),i&&p.push(d[i],d[i+1])}else{var v=s._nexttrace;if(v){var g=m.lineOptions[e+1];if(g){var y=g.positions;if(\"tonexty\"===s.fill){for(p=d.slice(),e=Math.floor(y.length/2);e--;){var x=y[2*e],b=y[2*e+1];isNaN(x)||isNaN(b)||p.push(x,b)}t.fill=v.fillcolor}}}}if(s._prevtrace&&\"tonext\"===s._prevtrace.fill){var _=m.lineOptions[e-1].positions,w=p.length/2,T=[i=w];for(a=0;a<_.length;a+=2)(isNaN(_[a])||isNaN(_[a+1]))&&(T.push(a/2+w+1),i=a+2);p=p.concat(_),t.hole=T}return t.fillmode=s.fill,t.opacity=s.opacity,t.positions=p,t}})),m.fill2d.update(m.fillOptions))}var M=y.dragmode,S=l(M),E=y.clickmode.indexOf(\"select\")>-1;for(v=0;v<_;v++){var L=r[v][0],C=L.trace,P=L.t,O=P.index,I=C._length,D=P.x,z=P.y;if(C.selectedpoints||S||E){if(S||(S=!0),C.selectedpoints){var R=m.selectBatch[O]=s.selIndices2selPoints(C),F={};for(g=0;g<R.length;g++)F[R[g]]=1;var B=[];for(g=0;g<I;g++)F[g]||B.push(g);m.unselectBatch[O]=B}var N=P.xpx=new Array(I),j=P.ypx=new Array(I);for(g=0;g<I;g++)N[g]=x.c2p(D[g]),j[g]=b.c2p(z[g])}else P.xpx=P.ypx=null}if(S){if(m.select2d||(m.select2d=n(y._glcanvas.data()[1].regl)),m.scatter2d){var U=new Array(_);for(v=0;v<_;v++)U[v]=m.selectBatch[v].length||m.unselectBatch[v].length?m.markerUnselectedOptions[v]:{};m.scatter2d.update(U)}m.select2d&&(m.select2d.update(m.markerOptions),m.select2d.update(m.markerSelectedOptions)),m.glText&&r.forEach((function(t){var e=((t||[])[0]||{}).trace||{};c.hasText(e)&&h(t)}))}else m.scatter2d&&m.scatter2d.update(m.markerOptions);var V={viewport:d(y,x,b,t._context.plotGlPixelRatio),range:[(x._rl||x.range)[0],(b._rl||b.range)[0],(x._rl||x.range)[1],(b._rl||b.range)[1]]},q=s.repeat(V,m.count);m.fill2d&&m.fill2d.update(q),m.line2d&&m.line2d.update(q),m.error2d&&m.error2d.update(q.concat(q)),m.scatter2d&&m.scatter2d.update(q),m.select2d&&m.select2d.update(q),m.glText&&m.glText.forEach((function(t){t.update(V)}))}else m.init()}}).reglPrecompiled=p},74588:function(t,e,r){\"use strict\";var n=r(3400);t.exports=function(t,e){var r=e._scene,i={count:0,dirty:!0,lineOptions:[],fillOptions:[],markerOptions:[],markerSelectedOptions:[],markerUnselectedOptions:[],errorXOptions:[],errorYOptions:[],textOptions:[],textSelectedOptions:[],textUnselectedOptions:[],selectBatch:[],unselectBatch:[]},a={fill2d:!1,scatter2d:!1,error2d:!1,line2d:!1,glText:!1,select2d:!1};return e._scene||((r=e._scene={}).init=function(){n.extendFlat(r,a,i)},r.init(),r.update=function(t){var e=n.repeat(t,r.count);if(r.fill2d&&r.fill2d.update(e),r.scatter2d&&r.scatter2d.update(e),r.line2d&&r.line2d.update(e),r.error2d&&r.error2d.update(e.concat(e)),r.select2d&&r.select2d.update(e),r.glText)for(var i=0;i<r.count;i++)r.glText[i].update(t)},r.draw=function(){for(var t=r.count,e=r.fill2d,i=r.error2d,a=r.line2d,o=r.scatter2d,s=r.glText,l=r.select2d,u=r.selectBatch,c=r.unselectBatch,f=0;f<t;f++){if(e&&r.fillOrder[f]&&e.draw(r.fillOrder[f]),a&&r.lineOptions[f]&&a.draw(f),i&&(r.errorXOptions[f]&&i.draw(f),r.errorYOptions[f]&&i.draw(f+t)),o&&r.markerOptions[f])if(c[f].length){var h=n.repeat([],r.count);h[f]=c[f],o.draw(h)}else 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n=r(3400),i=n.pushUnique,a=r(43028),o=r(50328);t.exports=function(t,e){var r=t.cd,s=r[0].trace,l=r[0].t,u=t.scene,c=u.matrixOptions.cdata,f=t.xaxis,h=t.yaxis,p=[];if(!u)return p;var d=!a.hasMarkers(s)&&!a.hasText(s);if(!0!==s.visible||d)return p;var v=o.getDimIndex(s,f),g=o.getDimIndex(s,h);if(!1===v||!1===g)return p;var y=l.xpx[v],m=l.ypx[g],x=c[v],b=c[g],_=(t.scene.selectBatch||[]).slice(),w=[];if(!1!==e&&!e.degenerate)for(var T=0;T<x.length;T++)e.contains([y[T],m[T]],null,T,t)?(p.push({pointNumber:T,x:x[T],y:b[T]}),i(_,T)):-1!==_.indexOf(T)?i(_,T):w.push(T);var k=u.matrixOptions;return _.length||w.length?u.selectBatch.length||u.unselectBatch.length||u.matrix.update(u.unselectedOptions,n.extendFlat({},k,u.selectedOptions,u.viewOpts)):u.matrix.update(k,null),u.selectBatch=_,u.unselectBatch=w,p}},90167:function(t,e,r){\"use strict\";var n=r(49084),i=r(29736).axisHoverFormat,a=r(21776).Ks,o=r(52948),s=r(45464),l=r(92880).extendFlat,u={x:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},y:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},z:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},u:{valType:\"data_array\",editType:\"calc\"},v:{valType:\"data_array\",editType:\"calc\"},w:{valType:\"data_array\",editType:\"calc\"},starts:{x:{valType:\"data_array\",editType:\"calc\"},y:{valType:\"data_array\",editType:\"calc\"},z:{valType:\"data_array\",editType:\"calc\"},editType:\"calc\"},maxdisplayed:{valType:\"integer\",min:0,dflt:1e3,editType:\"calc\"},sizeref:{valType:\"number\",editType:\"calc\",min:0,dflt:1},text:{valType:\"string\",dflt:\"\",editType:\"calc\"},hovertext:{valType:\"string\",dflt:\"\",editType:\"calc\"},hovertemplate:a({editType:\"calc\"},{keys:[\"tubex\",\"tubey\",\"tubez\",\"tubeu\",\"tubev\",\"tubew\",\"norm\",\"divergence\"]}),uhoverformat:i(\"u\",1),vhoverformat:i(\"v\",1),whoverformat:i(\"w\",1),xhoverformat:i(\"x\"),yhoverformat:i(\"y\"),zhoverformat:i(\"z\"),showlegend:l({},s.showlegend,{dflt:!1})};l(u,n(\"\",{colorAttr:\"u/v/w 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L=function(){m=0,M=[],S=[],E=[]};(!m||m<M.length*S.length*E.length)&&L();var C=function(t){return\"x\"===t?v:\"y\"===t?g:y},P=function(t){return\"x\"===t?M:\"y\"===t?S:E},O=function(t){return t[m-1]<t[0]?-1:1},I=C(A[1]),D=C(A[3]),z=C(A[5]),R=P(A[1]).length,F=P(A[3]).length,B=P(A[5]).length,N=!1,j=function(t,e,r){return R*(F*t+e)+r},U=O(C(A[1])),V=O(C(A[3])),q=O(C(A[5]));for(e=0;e<B-1;e++){for(r=0;r<F-1;r++){for(i=0;i<R-1;i++){var H=j(e,r,i),G=j(e,r,i+1),W=j(e,r+1,i),Y=j(e+1,r,i);if(I[H]*U<I[G]*U&&D[H]*V<D[W]*V&&z[H]*q<z[Y]*q||(N=!0),N)break}if(N)break}if(N)break}return N&&(n.warn(\"Encountered arbitrary coordinates! 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y=n[c];r.xMax=Math.max(r.xMax,y),r.xMin=Math.min(r.xMin,y);var m=o[c];r.yMax=Math.max(r.yMax,m),r.yMin=Math.min(r.yMin,m);var x=l[c];r.zMax=Math.max(r.zMax,x),r.zMin=Math.min(r.zMin,x)}e._slen=u,e._normMax=f,e._xbnds=[r.xMin,r.xMax],e._ybnds=[r.yMin,r.yMax],e._zbnds=[r.zMin,r.zMax]},filter:s,processGrid:a}},25668:function(t,e,r){\"use strict\";var n=r(67792).gl_streamtube3d,i=n.createTubeMesh,a=r(3400),o=r(33040).parseColorScale,s=r(8932).extractOpts,l=r(52094),u={xaxis:0,yaxis:1,zaxis:2};function c(t,e){this.scene=t,this.uid=e,this.mesh=null,this.data=null}var f=c.prototype;function h(t){var e=t.length;return e>2?t.slice(1,e-1):2===e?[(t[0]+t[1])/2]:t}function p(t){var e=t.length;return 1===e?[.5,.5]:[t[1]-t[0],t[e-1]-t[e-2]]}function d(t,e){var r=t.fullSceneLayout,i=t.dataScale,c=e._len,f={};function d(t,e){var n=r[e],o=i[u[e]];return a.simpleMap(t,(function(t){return 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O.lightPosition=[D.x,D.y,D.z],O.ambient=e.lighting.ambient,O.diffuse=e.lighting.diffuse,O.specular=e.lighting.specular,O.roughness=e.lighting.roughness,O.fresnel=e.lighting.fresnel,O.opacity=e.opacity,e._pad=O.tubeScale*e.sizeref*2,O}f.handlePick=function(t){var e=this.scene.fullSceneLayout,r=this.scene.dataScale;function n(t,n){var i=e[n],a=r[u[n]];return i.l2c(t)/a}if(t.object===this.mesh){var i=t.data.position,a=t.data.velocity;return t.traceCoordinate=[n(i[0],\"xaxis\"),n(i[1],\"yaxis\"),n(i[2],\"zaxis\"),n(a[0],\"xaxis\"),n(a[1],\"yaxis\"),n(a[2],\"zaxis\"),t.data.intensity*this.data._normMax,t.data.divergence],t.textLabel=this.data.hovertext||this.data.text,!0}},f.update=function(t){this.data=t;var e=d(this.scene,t);this.mesh.update(e)},f.dispose=function(){this.scene.glplot.remove(this.mesh),this.mesh.dispose()},t.exports=function(t,e){var r=t.glplot.gl,n=d(t,e),a=i(r,n),o=new c(t,e.uid);return o.mesh=a,o.data=e,a._trace=o,t.glplot.add(a),o}},54304:function(t,e,r){\"use 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n=r(45464),i=r(21776).Ks,a=r(21776).Gw,o=r(49084),s=r(86968).u,l=r(74996),u=r(27328),c=r(92880).extendFlat,f=r(98192).c;t.exports={labels:{valType:\"data_array\",editType:\"calc\"},parents:{valType:\"data_array\",editType:\"calc\"},values:{valType:\"data_array\",editType:\"calc\"},branchvalues:{valType:\"enumerated\",values:[\"remainder\",\"total\"],dflt:\"remainder\",editType:\"calc\"},count:{valType:\"flaglist\",flags:[\"branches\",\"leaves\"],dflt:\"leaves\",editType:\"calc\"},level:{valType:\"any\",editType:\"plot\",anim:!0},maxdepth:{valType:\"integer\",editType:\"plot\",dflt:-1},marker:c({colors:{valType:\"data_array\",editType:\"calc\"},line:{color:c({},l.marker.line.color,{dflt:null}),width:c({},l.marker.line.width,{dflt:1}),editType:\"calc\"},pattern:f,editType:\"calc\"},o(\"marker\",{colorAttr:\"colors\",anim:!1})),leaf:{opacity:{valType:\"number\",editType:\"style\",min:0,max:1},editType:\"plot\"},text:l.text,textinfo:{valType:\"flaglist\",flags:[\"label\",\"text\",\"value\",\"current 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n=r(7316);e.name=\"sunburst\",e.plot=function(t,r,i,a){n.plotBasePlot(e.name,t,r,i,a)},e.clean=function(t,r,i,a){n.cleanBasePlot(e.name,t,r,i,a)}},3776:function(t,e,r){\"use strict\";var n=r(74148),i=r(38248),a=r(3400),o=r(8932).makeColorScaleFuncFromTrace,s=r(45768).makePullColorFn,l=r(45768).generateExtendedColors,u=r(8932).calc,c=r(39032).ALMOST_EQUAL,f={},h={},p={};function d(t,e,r){var n=0,i=t.children;if(i){for(var a=i.length,o=0;o<a;o++)n+=d(i[o],e,r);r.branches&&n++}else r.leaves&&n++;return t.value=t.data.data.value=n,e._values||(e._values=[]),e._values[t.data.data.i]=n,n}e.calc=function(t,e){var r,l,f,h,p,v,g=t._fullLayout,y=e.ids,m=a.isArrayOrTypedArray(y),x=e.labels,b=e.parents,_=e.values,w=a.isArrayOrTypedArray(_),T=[],k={},A={},M=function(t){return t||\"number\"==typeof t},S=function(t){return!w||i(_[t])&&_[t]>=0};m?(r=Math.min(y.length,b.length),l=function(t){return M(y[t])&&S(t)},f=function(t){return String(y[t])}):(r=Math.min(x.length,b.length),l=function(t){return 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if(e={rpx1:t.rpx1,transform:{textPosAngle:n.textPosAngle,scale:0,rotate:n.rotate,rCenter:n.rCenter,x:n.x,y:n.y}},R)if(t.parent)if(Z){var i=t.x1>Z?2*Math.PI:0;e.x0=e.x1=i}else s.extendFlat(e,$(t));else e.x0=e.x1=V;else e.x0=e.x1=V;var o=a(e.transform.textPosAngle,t.transform.textPosAngle),l=a(e.rpx1,t.rpx1),u=a(e.x0,t.x0),f=a(e.x1,t.x1),h=a(e.transform.scale,n.scale),p=a(e.transform.rotate,n.rotate),d=0===n.rCenter?3:0===e.transform.rCenter?1/3:1,v=a(e.transform.rCenter,n.rCenter);return function(t){var e=l(t),r=u(t),i=f(t),a=function(t){return v(Math.pow(t,d))}(t),s={pxmid:G(e,(r+i)/2),rpx1:e,transform:{textPosAngle:o(t),rCenter:a,x:n.x,y:n.y}};return c(A.type,n,y),{transform:{targetX:Y(s),targetY:X(s),scale:h(t),rotate:p(t),rCenter:a}}}}(t);return function(t){return E(e(t),M)}})):w.attr(\"transform\",E(i,M))}))}function w(t){return e=t.rpx1,r=t.transform.textPosAngle,[e*Math.sin(r),-e*Math.cos(r)];var e,r}e.plot=function(t,e,r,i){var a,o,s=t._fullLayout,l=s._sunburstlayer,u=!r,c=!s.uniformtext.mode&&b.hasTransition(r);f(\"sunburst\",s),(a=l.selectAll(\"g.trace.sunburst\").data(e,(function(t){return t[0].trace.uid}))).enter().append(\"g\").classed(\"trace\",!0).classed(\"sunburst\",!0).attr(\"stroke-linejoin\",\"round\"),a.order(),c?(i&&(o=i()),n.transition().duration(r.duration).ease(r.easing).each(\"end\",(function(){o&&o()})).each(\"interrupt\",(function(){o&&o()})).each((function(){l.selectAll(\"g.trace\").each((function(e){_(t,e,this,r)}))}))):(a.each((function(e){_(t,e,this,r)})),s.uniformtext.mode&&y(t,s._sunburstlayer.selectAll(\".trace\"),\"sunburst\")),u&&a.exit().remove()},e.formatSliceLabel=function(t,e,r,n,i){var a=r.texttemplate,o=r.textinfo;if(!(a||o&&\"none\"!==o))return\"\";var l=i.separators,u=n[0],c=t.data.data,f=u.hierarchy,h=b.isHierarchyRoot(t),p=b.getParent(f,t),d=b.getValue(t);if(!a){var v,g=o.split(\"+\"),y=function(t){return-1!==g.indexOf(t)},m=[];if(y(\"label\")&&c.label&&m.push(c.label),c.hasOwnProperty(\"v\")&&y(\"value\")&&m.push(b.formatValue(c.v,l)),!h){y(\"current path\")&&m.push(b.getPath(t.data));var x=0;y(\"percent parent\")&&x++,y(\"percent entry\")&&x++,y(\"percent root\")&&x++;var _=x>1;if(x){var w,T=function(t){v=b.formatPercent(w,l),_&&(v+=\" of \"+t),m.push(v)};y(\"percent parent\")&&!h&&(w=d/b.getValue(p),T(\"parent\")),y(\"percent entry\")&&(w=d/b.getValue(e),T(\"entry\")),y(\"percent root\")&&(w=d/b.getValue(f),T(\"root\"))}}return y(\"text\")&&(v=s.castOption(r,c.i,\"text\"),s.isValidTextValue(v)&&m.push(v)),m.join(\"<br>\")}var k=s.castOption(r,c.i,\"texttemplate\");if(!k)return\"\";var A={};c.label&&(A.label=c.label),c.hasOwnProperty(\"v\")&&(A.value=c.v,A.valueLabel=b.formatValue(c.v,l)),A.currentPath=b.getPath(t.data),h||(A.percentParent=d/b.getValue(p),A.percentParentLabel=b.formatPercent(A.percentParent,l),A.parent=b.getPtLabel(p)),A.percentEntry=d/b.getValue(e),A.percentEntryLabel=b.formatPercent(A.percentEntry,l),A.entry=b.getPtLabel(e),A.percentRoot=d/b.getValue(f),A.percentRootLabel=b.formatPercent(A.percentRoot,l),A.root=b.getPtLabel(f),c.hasOwnProperty(\"color\")&&(A.color=c.color);var M=s.castOption(r,c.i,\"text\");return(s.isValidTextValue(M)||\"\"===M)&&(A.text=M),A.customdata=s.castOption(r,c.i,\"customdata\"),s.texttemplateString(k,A,i._d3locale,A,r._meta||{})}},85676:function(t,e,r){\"use strict\";var n=r(33428),i=r(76308),a=r(3400),o=r(82744).resizeText,s=r(60404);function l(t,e,r,n){var o=e.data.data,l=!e.children,u=o.i,c=a.castOption(r,u,\"marker.line.color\")||i.defaultLine,f=a.castOption(r,u,\"marker.line.width\")||0;t.call(s,e,r,n).style(\"stroke-width\",f).call(i.stroke,c).style(\"opacity\",l?r.leaf.opacity:null)}t.exports={style:function(t){var e=t._fullLayout._sunburstlayer.selectAll(\".trace\");o(t,e,\"sunburst\"),e.each((function(e){var r=n.select(this),i=e[0].trace;r.style(\"opacity\",i.opacity),r.selectAll(\"path.surface\").each((function(e){n.select(this).call(l,e,i,t)}))}))},styleOne:l}},16716:function(t,e,r){\"use strict\";var n=r(76308),i=r(49084),a=r(29736).axisHoverFormat,o=r(21776).Ks,s=r(45464),l=r(92880).extendFlat,u=r(67824).overrideAll;function c(t){return{show:{valType:\"boolean\",dflt:!1},start:{valType:\"number\",dflt:null,editType:\"plot\"},end:{valType:\"number\",dflt:null,editType:\"plot\"},size:{valType:\"number\",dflt:null,min:0,editType:\"plot\"},project:{x:{valType:\"boolean\",dflt:!1},y:{valType:\"boolean\",dflt:!1},z:{valType:\"boolean\",dflt:!1}},color:{valType:\"color\",dflt:n.defaultLine},usecolormap:{valType:\"boolean\",dflt:!1},width:{valType:\"number\",min:1,max:16,dflt:2},highlight:{valType:\"boolean\",dflt:!0},highlightcolor:{valType:\"color\",dflt:n.defaultLine},highlightwidth:{valType:\"number\",min:1,max:16,dflt:2}}}var f=t.exports=u(l({z:{valType:\"data_array\"},x:{valType:\"data_array\"},y:{valType:\"data_array\"},text:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertemplate:o(),xhoverformat:a(\"x\"),yhoverformat:a(\"y\"),zhoverformat:a(\"z\"),connectgaps:{valType:\"boolean\",dflt:!1,editType:\"calc\"},surfacecolor:{valType:\"data_array\"}},i(\"\",{colorAttr:\"z or surfacecolor\",showScaleDflt:!0,autoColorDflt:!1,editTypeOverride:\"calc\"}),{contours:{x:c(),y:c(),z:c()},hidesurface:{valType:\"boolean\",dflt:!1},lightposition:{x:{valType:\"number\",min:-1e5,max:1e5,dflt:10},y:{valType:\"number\",min:-1e5,max:1e5,dflt:1e4},z:{valType:\"number\",min:-1e5,max:1e5,dflt:0}},lighting:{ambient:{valType:\"number\",min:0,max:1,dflt:.8},diffuse:{valType:\"number\",min:0,max:1,dflt:.8},specular:{valType:\"number\",min:0,max:2,dflt:.05},roughness:{valType:\"number\",min:0,max:1,dflt:.5},fresnel:{valType:\"number\",min:0,max:5,dflt:.2}},opacity:{valType:\"number\",min:0,max:1,dflt:1},opacityscale:{valType:\"any\",editType:\"calc\"},_deprecated:{zauto:l({},i.zauto,{}),zmin:l({},i.zmin,{}),zmax:l({},i.zmax,{})},hoverinfo:l({},s.hoverinfo),showlegend:l({},s.showlegend,{dflt:!1})}),\"calc\",\"nested\");f.x.editType=f.y.editType=f.z.editType=\"calc+clearAxisTypes\",f.transforms=void 0},56576:function(t,e,r){\"use strict\";var n=r(47128);t.exports=function(t,e){e.surfacecolor?n(t,e,{vals:e.surfacecolor,containerStr:\"\",cLetter:\"c\"}):n(t,e,{vals:e.z,containerStr:\"\",cLetter:\"c\"})}},79164:function(t,e,r){\"use strict\";var n=r(67792).gl_surface3d,i=r(67792).ndarray,a=r(67792).ndarray_linear_interpolate.d2,o=r(70448),s=r(11240),l=r(3400).isArrayOrTypedArray,u=r(33040).parseColorScale,c=r(43080),f=r(8932).extractOpts;function h(t,e,r){this.scene=t,this.uid=r,this.surface=e,this.data=null,this.showContour=[!1,!1,!1],this.contourStart=[null,null,null],this.contourEnd=[null,null,null],this.contourSize=[0,0,0],this.minValues=[1/0,1/0,1/0],this.maxValues=[-1/0,-1/0,-1/0],this.dataScaleX=1,this.dataScaleY=1,this.refineData=!0,this.objectOffset=[0,0,0]}var p=h.prototype;p.getXat=function(t,e,r,n){var i=l(this.data.x)?l(this.data.x[0])?this.data.x[e][t]:this.data.x[t]:t;return void 0===r?i:n.d2l(i,0,r)},p.getYat=function(t,e,r,n){var i=l(this.data.y)?l(this.data.y[0])?this.data.y[e][t]:this.data.y[e]:e;return void 0===r?i:n.d2l(i,0,r)},p.getZat=function(t,e,r,n){var i=this.data.z[e][t];return null===i&&this.data.connectgaps&&this.data._interpolatedZ&&(i=this.data._interpolatedZ[e][t]),void 0===r?i:n.d2l(i,0,r)},p.handlePick=function(t){if(t.object===this.surface){var e=(t.data.index[0]-1)/this.dataScaleX-1,r=(t.data.index[1]-1)/this.dataScaleY-1,n=Math.max(Math.min(Math.round(e),this.data.z[0].length-1),0),i=Math.max(Math.min(Math.round(r),this.data._ylength-1),0);t.index=[n,i],t.traceCoordinate=[this.getXat(n,i),this.getYat(n,i),this.getZat(n,i)],t.dataCoordinate=[this.getXat(n,i,this.data.xcalendar,this.scene.fullSceneLayout.xaxis),this.getYat(n,i,this.data.ycalendar,this.scene.fullSceneLayout.yaxis),this.getZat(n,i,this.data.zcalendar,this.scene.fullSceneLayout.zaxis)];for(var a=0;a<3;a++){null!=t.dataCoordinate[a]&&(t.dataCoordinate[a]*=this.scene.dataScale[a])}var o=this.data.hovertext||this.data.text;return l(o)&&o[i]&&void 0!==o[i][n]?t.textLabel=o[i][n]:t.textLabel=o||\"\",t.data.dataCoordinate=t.dataCoordinate.slice(),this.surface.highlight(t.data),this.scene.glplot.spikes.position=t.dataCoordinate,!0}};var d=[2,3,5,7,11,13,17,19,23,29,31,37,41,43,47,53,59,61,67,71,73,79,83,89,97,101,103,107,109,113,127,131,137,139,149,151,157,163,167,173,179,181,191,193,197,199,211,223,227,229,233,239,241,251,257,263,269,271,277,281,283,293,307,311,313,317,331,337,347,349,353,359,367,373,379,383,389,397,401,409,419,421,431,433,439,443,449,457,461,463,467,479,487,491,499,503,509,521,523,541,547,557,563,569,571,577,587,593,599,601,607,613,617,619,631,641,643,647,653,659,661,673,677,683,691,701,709,719,727,733,739,743,751,757,761,769,773,787,797,809,811,821,823,827,829,839,853,857,859,863,877,881,883,887,907,911,919,929,937,941,947,953,967,971,977,983,991,997,1009,1013,1019,1021,1031,1033,1039,1049,1051,1061,1063,1069,1087,1091,1093,1097,1103,1109,1117,1123,1129,1151,1153,1163,1171,1181,1187,1193,1201,1213,1217,1223,1229,1231,1237,1249,1259,1277,1279,1283,1289,1291,1297,1301,1303,1307,1319,1321,1327,1361,1367,1373,1381,1399,1409,1423,1427,1429,1433,1439,1447,1451,1453,1459,1471,1481,1483,1487,1489,1493,1499,1511,1523,1531,1543,1549,1553,1559,1567,1571,1579,1583,1597,1601,1607,1609,1613,1619,1621,1627,1637,1657,1663,1667,1669,1693,1697,1699,1709,1721,1723,1733,1741,1747,1753,1759,1777,1783,1787,1789,1801,1811,1823,1831,1847,1861,1867,1871,1873,1877,1879,1889,1901,1907,1913,1931,1933,1949,1951,1973,1979,1987,1993,1997,1999,2003,2011,2017,2027,2029,2039,2053,2063,2069,2081,2083,2087,2089,2099,2111,2113,2129,2131,2137,2141,2143,2153,2161,2179,2203,2207,2213,2221,2237,2239,2243,2251,2267,2269,2273,2281,2287,2293,2297,2309,2311,2333,2339,2341,2347,2351,2357,2371,2377,2381,2383,2389,2393,2399,2411,2417,2423,2437,2441,2447,2459,2467,2473,2477,2503,2521,2531,2539,2543,2549,2551,2557,2579,2591,2593,2609,2617,2621,2633,2647,2657,2659,2663,2671,2677,2683,2687,2689,2693,2699,2707,2711,2713,2719,2729,2731,2741,2749,2753,2767,2777,2789,2791,2797,2801,2803,2819,2833,2837,2843,2851,2857,2861,2879,2887,2897,2903,2909,2917,2927,2939,2953,2957,2963,2969,2971,2999];function v(t,e){if(t<e)return 0;for(var r=0;0===Math.floor(t%e);)t/=e,r++;return r}function g(t){for(var e=[],r=0;r<d.length;r++){var n=d[r];e.push(v(t,n))}return e}function y(t){for(var e=g(t),r=t,n=0;n<d.length;n++)if(e[n]>0){r=d[n];break}return r}function m(t,e){if(!(t<1||e<1)){for(var r=g(t),n=g(e),i=1,a=0;a<d.length;a++)i*=Math.pow(d[a],Math.max(r[a],n[a]));return i}}p.calcXnums=function(t){var e,r=[];for(e=1;e<t;e++){var n=this.getXat(e-1,0),i=this.getXat(e,0);r[e-1]=i!==n&&null!=n&&null!=i?Math.abs(i-n):0}var a=0;for(e=1;e<t;e++)a+=r[e-1];for(e=1;e<t;e++)0===r[e-1]?r[e-1]=1:r[e-1]=Math.round(a/r[e-1]);return r},p.calcYnums=function(t){var e,r=[];for(e=1;e<t;e++){var n=this.getYat(0,e-1),i=this.getYat(0,e);r[e-1]=i!==n&&null!=n&&null!=i?Math.abs(i-n):0}var a=0;for(e=1;e<t;e++)a+=r[e-1];for(e=1;e<t;e++)0===r[e-1]?r[e-1]=1:r[e-1]=Math.round(a/r[e-1]);return r};var x=[1,2,4,6,12,24,36,48,60,120,180,240,360,720,840,1260],b=x[9],_=x[13];function w(t,e,r){var n=r[8]+r[2]*e[0]+r[5]*e[1];return t[0]=(r[6]+r[0]*e[0]+r[3]*e[1])/n,t[1]=(r[7]+r[1]*e[0]+r[4]*e[1])/n,t}function T(t,e,r){return function(t,e,r,n){for(var i=[0,0],o=t.shape[0],s=t.shape[1],l=0;l<o;l++)for(var u=0;u<s;u++)r(i,[l,u],n),t.set(l,u,a(e,i[0],i[1]))}(t,e,w,r),t}function k(t,e){for(var r=!1,n=0;n<t.length;n++)if(e===t[n]){r=!0;break}!1===r&&t.push(e)}p.estimateScale=function(t,e){for(var r=1+function(t){if(0!==t.length){for(var e=1,r=0;r<t.length;r++)e=m(e,t[r]);return e}}(0===e?this.calcXnums(t):this.calcYnums(t));r<b;)r*=2;for(;r>_;)r--,r/=y(r),++r<b&&(r=_);var n=Math.round(r/t);return n>1?n:1},p.refineCoords=function(t){for(var e=this.dataScaleX,r=this.dataScaleY,n=t[0].shape[0],a=t[0].shape[1],o=0|Math.floor(t[0].shape[0]*e+1),s=0|Math.floor(t[0].shape[1]*r+1),l=1+n+1,u=1+a+1,c=i(new Float32Array(l*u),[l,u]),f=[1/e,0,0,0,1/r,0,0,0,1],h=0;h<t.length;++h){this.surface.padField(c,t[h]);var p=i(new Float32Array(o*s),[o,s]);T(p,c,f),t[h]=p}},p.setContourLevels=function(){var t,e,r,n=[[],[],[]],i=[!1,!1,!1],a=!1;for(t=0;t<3;++t)if(this.showContour[t]&&(a=!0,this.contourSize[t]>0&&null!==this.contourStart[t]&&null!==this.contourEnd[t]&&this.contourEnd[t]>this.contourStart[t]))for(i[t]=!0,e=this.contourStart[t];e<this.contourEnd[t];e+=this.contourSize[t])r=e*this.scene.dataScale[t],k(n[t],r);if(a){var o=[[],[],[]];for(t=0;t<3;++t)this.showContour[t]&&(o[t]=i[t]?n[t]:this.scene.contourLevels[t]);this.surface.update({levels:o})}},p.update=function(t){var e,r,n,a,l=this.scene,h=l.fullSceneLayout,p=this.surface,d=u(t),v=l.dataScale,g=t.z[0].length,y=t._ylength,m=l.contourLevels;this.data=t;var x=[];for(e=0;e<3;e++)for(x[e]=[],r=0;r<g;r++)x[e][r]=[];for(r=0;r<g;r++)for(n=0;n<y;n++)x[0][r][n]=this.getXat(r,n,t.xcalendar,h.xaxis),x[1][r][n]=this.getYat(r,n,t.ycalendar,h.yaxis),x[2][r][n]=this.getZat(r,n,t.zcalendar,h.zaxis);if(t.connectgaps)for(t._emptypoints=s(x[2]),o(x[2],t._emptypoints),t._interpolatedZ=[],r=0;r<g;r++)for(t._interpolatedZ[r]=[],n=0;n<y;n++)t._interpolatedZ[r][n]=x[2][r][n];for(e=0;e<3;e++)for(r=0;r<g;r++)for(n=0;n<y;n++)null==(a=x[e][r][n])?x[e][r][n]=NaN:a=x[e][r][n]*=v[e];for(e=0;e<3;e++)for(r=0;r<g;r++)for(n=0;n<y;n++)null!=(a=x[e][r][n])&&(this.minValues[e]>a&&(this.minValues[e]=a),this.maxValues[e]<a&&(this.maxValues[e]=a));for(e=0;e<3;e++)this.objectOffset[e]=.5*(this.minValues[e]+this.maxValues[e]);for(e=0;e<3;e++)for(r=0;r<g;r++)for(n=0;n<y;n++)null!=(a=x[e][r][n])&&(x[e][r][n]-=this.objectOffset[e]);var b=[i(new Float32Array(g*y),[g,y]),i(new Float32Array(g*y),[g,y]),i(new 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A=[!0,!0,!0],M=[\"x\",\"y\",\"z\"];for(e=0;e<3;++e){var S=t.contours[M[e]];A[e]=S.highlight,w.showContour[e]=S.show||S.highlight,w.showContour[e]&&(w.contourProject[e]=[S.project.x,S.project.y,S.project.z],S.show?(this.showContour[e]=!0,w.levels[e]=m[e],p.highlightColor[e]=w.contourColor[e]=c(S.color),S.usecolormap?p.highlightTint[e]=w.contourTint[e]=0:p.highlightTint[e]=w.contourTint[e]=1,w.contourWidth[e]=S.width,this.contourStart[e]=S.start,this.contourEnd[e]=S.end,this.contourSize[e]=S.size):(this.showContour[e]=!1,this.contourStart[e]=null,this.contourEnd[e]=null,this.contourSize[e]=0),S.highlight&&(w.dynamicColor[e]=c(S.highlightcolor),w.dynamicWidth[e]=S.highlightwidth))}(function(t){var e=t[0].rgb,r=t[t.length-1].rgb;return e[0]===r[0]&&e[1]===r[1]&&e[2]===r[2]&&e[3]===r[3]})(d)&&(w.vertexColor=!0),w.objectOffset=this.objectOffset,w.coords=b,p.update(w),p.visible=t.visible,p.enableDynamic=A,p.enableHighlight=A,p.snapToData=!0,\"lighting\"in 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m(t,e){return\"clip\"+t._fullLayout._uid+\"_columnBoundaryClippath_\"+e.calcdata.key+\"_\"+e.specIndex}function x(t){return[].concat.apply([],t.map((function(t){return t}))).map((function(t){return t.__data__}))}function b(t,e,r){var a=t.selectAll(\".\"+n.cn.scrollbarKit).data(s.repeat,s.keyFun);a.enter().append(\"g\").classed(n.cn.scrollbarKit,!0).style(\"shape-rendering\",\"geometricPrecision\"),a.each((function(t){var e=t.scrollbarState;e.totalHeight=function(t){var e=t.rowBlocks;return 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u=l.selectAll(\".\"+n.cn.scrollbarGlyph).data(s.repeat,s.keyFun);u.enter().append(\"line\").classed(n.cn.scrollbarGlyph,!0).attr(\"stroke\",\"black\").attr(\"stroke-width\",n.scrollbarWidth).attr(\"stroke-linecap\",\"round\").attr(\"y1\",n.scrollbarWidth/2),u.attr(\"y2\",(function(t){return t.scrollbarState.barLength-n.scrollbarWidth/2})).attr(\"stroke-opacity\",(function(t){return t.columnDragInProgress||!t.scrollbarState.barWiggleRoom||r?0:.4})),u.transition().delay(0).duration(0),u.transition().delay(n.scrollbarHideDelay).duration(n.scrollbarHideDuration).attr(\"stroke-opacity\",0);var c=o.selectAll(\".\"+n.cn.scrollbarCaptureZone).data(s.repeat,s.keyFun);c.enter().append(\"line\").classed(n.cn.scrollbarCaptureZone,!0).attr(\"stroke\",\"white\").attr(\"stroke-opacity\",.01).attr(\"stroke-width\",n.scrollbarCaptureWidth).attr(\"stroke-linecap\",\"butt\").attr(\"y1\",0).on(\"mousedown\",(function(r){var 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32-Math.clz32(t)}:a.prototype._countBits=function(t){var e=t,r=0;return e>=4096&&(r+=13,e>>>=13),e>=64&&(r+=7,e>>>=7),e>=8&&(r+=4,e>>>=4),e>=2&&(r+=2,e>>>=2),r+e},a.prototype._zeroBits=function(t){if(0===t)return 26;var e=t,r=0;return 0==(8191&e)&&(r+=13,e>>>=13),0==(127&e)&&(r+=7,e>>>=7),0==(15&e)&&(r+=4,e>>>=4),0==(3&e)&&(r+=2,e>>>=2),0==(1&e)&&r++,r},a.prototype.bitLength=function(){var t=this.words[this.length-1],e=this._countBits(t);return 26*(this.length-1)+e},a.prototype.zeroBits=function(){if(this.isZero())return 0;for(var t=0,e=0;e<this.length;e++){var r=this._zeroBits(this.words[e]);if(t+=r,26!==r)break}return t},a.prototype.byteLength=function(){return Math.ceil(this.bitLength()/8)},a.prototype.toTwos=function(t){return 0!==this.negative?this.abs().inotn(t).iaddn(1):this.clone()},a.prototype.fromTwos=function(t){return this.testn(t-1)?this.notn(t).iaddn(1).ineg():this.clone()},a.prototype.isNeg=function(){return 0!==this.negative},a.prototype.neg=function(){return this.clone().ineg()},a.prototype.ineg=function(){return this.isZero()||(this.negative^=1),this},a.prototype.iuor=function(t){for(;this.length<t.length;)this.words[this.length++]=0;for(var e=0;e<t.length;e++)this.words[e]=this.words[e]|t.words[e];return this.strip()},a.prototype.ior=function(t){return n(0==(this.negative|t.negative)),this.iuor(t)},a.prototype.or=function(t){return this.length>t.length?this.clone().ior(t):t.clone().ior(this)},a.prototype.uor=function(t){return this.length>t.length?this.clone().iuor(t):t.clone().iuor(this)},a.prototype.iuand=function(t){var e;e=this.length>t.length?t:this;for(var r=0;r<e.length;r++)this.words[r]=this.words[r]&t.words[r];return this.length=e.length,this.strip()},a.prototype.iand=function(t){return n(0==(this.negative|t.negative)),this.iuand(t)},a.prototype.and=function(t){return this.length>t.length?this.clone().iand(t):t.clone().iand(this)},a.prototype.uand=function(t){return this.length>t.length?this.clone().iuand(t):t.clone().iuand(this)},a.prototype.iuxor=function(t){var e,r;this.length>t.length?(e=this,r=t):(e=t,r=this);for(var n=0;n<r.length;n++)this.words[n]=e.words[n]^r.words[n];if(this!==e)for(;n<e.length;n++)this.words[n]=e.words[n];return this.length=e.length,this.strip()},a.prototype.ixor=function(t){return n(0==(this.negative|t.negative)),this.iuxor(t)},a.prototype.xor=function(t){return this.length>t.length?this.clone().ixor(t):t.clone().ixor(this)},a.prototype.uxor=function(t){return this.length>t.length?this.clone().iuxor(t):t.clone().iuxor(this)},a.prototype.inotn=function(t){n(\"number\"==typeof t&&t>=0);var e=0|Math.ceil(t/26),r=t%26;this._expand(e),r>0&&e--;for(var i=0;i<e;i++)this.words[i]=67108863&~this.words[i];return r>0&&(this.words[i]=~this.words[i]&67108863>>26-r),this.strip()},a.prototype.notn=function(t){return this.clone().inotn(t)},a.prototype.setn=function(t,e){n(\"number\"==typeof t&&t>=0);var r=t/26|0,i=t%26;return this._expand(r+1),this.words[r]=e?this.words[r]|1<<i:this.words[r]&~(1<<i),this.strip()},a.prototype.iadd=function(t){var e,r,n;if(0!==this.negative&&0===t.negative)return this.negative=0,e=this.isub(t),this.negative^=1,this._normSign();if(0===this.negative&&0!==t.negative)return t.negative=0,e=this.isub(t),t.negative=1,e._normSign();this.length>t.length?(r=this,n=t):(r=t,n=this);for(var i=0,a=0;a<n.length;a++)e=(0|r.words[a])+(0|n.words[a])+i,this.words[a]=67108863&e,i=e>>>26;for(;0!==i&&a<r.length;a++)e=(0|r.words[a])+i,this.words[a]=67108863&e,i=e>>>26;if(this.length=r.length,0!==i)this.words[this.length]=i,this.length++;else if(r!==this)for(;a<r.length;a++)this.words[a]=r.words[a];return this},a.prototype.add=function(t){var e;return 0!==t.negative&&0===this.negative?(t.negative=0,e=this.sub(t),t.negative^=1,e):0===t.negative&&0!==this.negative?(this.negative=0,e=t.sub(this),this.negative=1,e):this.length>t.length?this.clone().iadd(t):t.clone().iadd(this)},a.prototype.isub=function(t){if(0!==t.negative){t.negative=0;var e=this.iadd(t);return t.negative=1,e._normSign()}if(0!==this.negative)return this.negative=0,this.iadd(t),this.negative=1,this._normSign();var r,n,i=this.cmp(t);if(0===i)return this.negative=0,this.length=1,this.words[0]=0,this;i>0?(r=this,n=t):(r=t,n=this);for(var a=0,o=0;o<n.length;o++)a=(e=(0|r.words[o])-(0|n.words[o])+a)>>26,this.words[o]=67108863&e;for(;0!==a&&o<r.length;o++)a=(e=(0|r.words[o])+a)>>26,this.words[o]=67108863&e;if(0===a&&o<r.length&&r!==this)for(;o<r.length;o++)this.words[o]=r.words[o];return this.length=Math.max(this.length,o),r!==this&&(this.negative=1),this.strip()},a.prototype.sub=function(t){return this.clone().isub(t)};var d=function(t,e,r){var n,i,a,o=t.words,s=e.words,l=r.words,u=0,c=0|o[0],f=8191&c,h=c>>>13,p=0|o[1],d=8191&p,v=p>>>13,g=0|o[2],y=8191&g,m=g>>>13,x=0|o[3],b=8191&x,_=x>>>13,w=0|o[4],T=8191&w,k=w>>>13,A=0|o[5],M=8191&A,S=A>>>13,E=0|o[6],L=8191&E,C=E>>>13,P=0|o[7],O=8191&P,I=P>>>13,D=0|o[8],z=8191&D,R=D>>>13,F=0|o[9],B=8191&F,N=F>>>13,j=0|s[0],U=8191&j,V=j>>>13,q=0|s[1],H=8191&q,G=q>>>13,W=0|s[2],Y=8191&W,X=W>>>13,Z=0|s[3],K=8191&Z,J=Z>>>13,$=0|s[4],Q=8191&$,tt=$>>>13,et=0|s[5],rt=8191&et,nt=et>>>13,it=0|s[6],at=8191&it,ot=it>>>13,st=0|s[7],lt=8191&st,ut=st>>>13,ct=0|s[8],ft=8191&ct,ht=ct>>>13,pt=0|s[9],dt=8191&pt,vt=pt>>>13;r.negative=t.negative^e.negative,r.length=19;var gt=(u+(n=Math.imul(f,U))|0)+((8191&(i=(i=Math.imul(f,V))+Math.imul(h,U)|0))<<13)|0;u=((a=Math.imul(h,V))+(i>>>13)|0)+(gt>>>26)|0,gt&=67108863,n=Math.imul(d,U),i=(i=Math.imul(d,V))+Math.imul(v,U)|0,a=Math.imul(v,V);var yt=(u+(n=n+Math.imul(f,H)|0)|0)+((8191&(i=(i=i+Math.imul(f,G)|0)+Math.imul(h,H)|0))<<13)|0;u=((a=a+Math.imul(h,G)|0)+(i>>>13)|0)+(yt>>>26)|0,yt&=67108863,n=Math.imul(y,U),i=(i=Math.imul(y,V))+Math.imul(m,U)|0,a=Math.imul(m,V),n=n+Math.imul(d,H)|0,i=(i=i+Math.imul(d,G)|0)+Math.imul(v,H)|0,a=a+Math.imul(v,G)|0;var mt=(u+(n=n+Math.imul(f,Y)|0)|0)+((8191&(i=(i=i+Math.imul(f,X)|0)+Math.imul(h,Y)|0))<<13)|0;u=((a=a+Math.imul(h,X)|0)+(i>>>13)|0)+(mt>>>26)|0,mt&=67108863,n=Math.imul(b,U),i=(i=Math.imul(b,V))+Math.imul(_,U)|0,a=Math.imul(_,V),n=n+Math.imul(y,H)|0,i=(i=i+Math.imul(y,G)|0)+Math.imul(m,H)|0,a=a+Math.imul(m,G)|0,n=n+Math.imul(d,Y)|0,i=(i=i+Math.imul(d,X)|0)+Math.imul(v,Y)|0,a=a+Math.imul(v,X)|0;var xt=(u+(n=n+Math.imul(f,K)|0)|0)+((8191&(i=(i=i+Math.imul(f,J)|0)+Math.imul(h,K)|0))<<13)|0;u=((a=a+Math.imul(h,J)|0)+(i>>>13)|0)+(xt>>>26)|0,xt&=67108863,n=Math.imul(T,U),i=(i=Math.imul(T,V))+Math.imul(k,U)|0,a=Math.imul(k,V),n=n+Math.imul(b,H)|0,i=(i=i+Math.imul(b,G)|0)+Math.imul(_,H)|0,a=a+Math.imul(_,G)|0,n=n+Math.imul(y,Y)|0,i=(i=i+Math.imul(y,X)|0)+Math.imul(m,Y)|0,a=a+Math.imul(m,X)|0,n=n+Math.imul(d,K)|0,i=(i=i+Math.imul(d,J)|0)+Math.imul(v,K)|0,a=a+Math.imul(v,J)|0;var bt=(u+(n=n+Math.imul(f,Q)|0)|0)+((8191&(i=(i=i+Math.imul(f,tt)|0)+Math.imul(h,Q)|0))<<13)|0;u=((a=a+Math.imul(h,tt)|0)+(i>>>13)|0)+(bt>>>26)|0,bt&=67108863,n=Math.imul(M,U),i=(i=Math.imul(M,V))+Math.imul(S,U)|0,a=Math.imul(S,V),n=n+Math.imul(T,H)|0,i=(i=i+Math.imul(T,G)|0)+Math.imul(k,H)|0,a=a+Math.imul(k,G)|0,n=n+Math.imul(b,Y)|0,i=(i=i+Math.imul(b,X)|0)+Math.imul(_,Y)|0,a=a+Math.imul(_,X)|0,n=n+Math.imul(y,K)|0,i=(i=i+Math.imul(y,J)|0)+Math.imul(m,K)|0,a=a+Math.imul(m,J)|0,n=n+Math.imul(d,Q)|0,i=(i=i+Math.imul(d,tt)|0)+Math.imul(v,Q)|0,a=a+Math.imul(v,tt)|0;var _t=(u+(n=n+Math.imul(f,rt)|0)|0)+((8191&(i=(i=i+Math.imul(f,nt)|0)+Math.imul(h,rt)|0))<<13)|0;u=((a=a+Math.imul(h,nt)|0)+(i>>>13)|0)+(_t>>>26)|0,_t&=67108863,n=Math.imul(L,U),i=(i=Math.imul(L,V))+Math.imul(C,U)|0,a=Math.imul(C,V),n=n+Math.imul(M,H)|0,i=(i=i+Math.imul(M,G)|0)+Math.imul(S,H)|0,a=a+Math.imul(S,G)|0,n=n+Math.imul(T,Y)|0,i=(i=i+Math.imul(T,X)|0)+Math.imul(k,Y)|0,a=a+Math.imul(k,X)|0,n=n+Math.imul(b,K)|0,i=(i=i+Math.imul(b,J)|0)+Math.imul(_,K)|0,a=a+Math.imul(_,J)|0,n=n+Math.imul(y,Q)|0,i=(i=i+Math.imul(y,tt)|0)+Math.imul(m,Q)|0,a=a+Math.imul(m,tt)|0,n=n+Math.imul(d,rt)|0,i=(i=i+Math.imul(d,nt)|0)+Math.imul(v,rt)|0,a=a+Math.imul(v,nt)|0;var wt=(u+(n=n+Math.imul(f,at)|0)|0)+((8191&(i=(i=i+Math.imul(f,ot)|0)+Math.imul(h,at)|0))<<13)|0;u=((a=a+Math.imul(h,ot)|0)+(i>>>13)|0)+(wt>>>26)|0,wt&=67108863,n=Math.imul(O,U),i=(i=Math.imul(O,V))+Math.imul(I,U)|0,a=Math.imul(I,V),n=n+Math.imul(L,H)|0,i=(i=i+Math.imul(L,G)|0)+Math.imul(C,H)|0,a=a+Math.imul(C,G)|0,n=n+Math.imul(M,Y)|0,i=(i=i+Math.imul(M,X)|0)+Math.imul(S,Y)|0,a=a+Math.imul(S,X)|0,n=n+Math.imul(T,K)|0,i=(i=i+Math.imul(T,J)|0)+Math.imul(k,K)|0,a=a+Math.imul(k,J)|0,n=n+Math.imul(b,Q)|0,i=(i=i+Math.imul(b,tt)|0)+Math.imul(_,Q)|0,a=a+Math.imul(_,tt)|0,n=n+Math.imul(y,rt)|0,i=(i=i+Math.imul(y,nt)|0)+Math.imul(m,rt)|0,a=a+Math.imul(m,nt)|0,n=n+Math.imul(d,at)|0,i=(i=i+Math.imul(d,ot)|0)+Math.imul(v,at)|0,a=a+Math.imul(v,ot)|0;var Tt=(u+(n=n+Math.imul(f,lt)|0)|0)+((8191&(i=(i=i+Math.imul(f,ut)|0)+Math.imul(h,lt)|0))<<13)|0;u=((a=a+Math.imul(h,ut)|0)+(i>>>13)|0)+(Tt>>>26)|0,Tt&=67108863,n=Math.imul(z,U),i=(i=Math.imul(z,V))+Math.imul(R,U)|0,a=Math.imul(R,V),n=n+Math.imul(O,H)|0,i=(i=i+Math.imul(O,G)|0)+Math.imul(I,H)|0,a=a+Math.imul(I,G)|0,n=n+Math.imul(L,Y)|0,i=(i=i+Math.imul(L,X)|0)+Math.imul(C,Y)|0,a=a+Math.imul(C,X)|0,n=n+Math.imul(M,K)|0,i=(i=i+Math.imul(M,J)|0)+Math.imul(S,K)|0,a=a+Math.imul(S,J)|0,n=n+Math.imul(T,Q)|0,i=(i=i+Math.imul(T,tt)|0)+Math.imul(k,Q)|0,a=a+Math.imul(k,tt)|0,n=n+Math.imul(b,rt)|0,i=(i=i+Math.imul(b,nt)|0)+Math.imul(_,rt)|0,a=a+Math.imul(_,nt)|0,n=n+Math.imul(y,at)|0,i=(i=i+Math.imul(y,ot)|0)+Math.imul(m,at)|0,a=a+Math.imul(m,ot)|0,n=n+Math.imul(d,lt)|0,i=(i=i+Math.imul(d,ut)|0)+Math.imul(v,lt)|0,a=a+Math.imul(v,ut)|0;var kt=(u+(n=n+Math.imul(f,ft)|0)|0)+((8191&(i=(i=i+Math.imul(f,ht)|0)+Math.imul(h,ft)|0))<<13)|0;u=((a=a+Math.imul(h,ht)|0)+(i>>>13)|0)+(kt>>>26)|0,kt&=67108863,n=Math.imul(B,U),i=(i=Math.imul(B,V))+Math.imul(N,U)|0,a=Math.imul(N,V),n=n+Math.imul(z,H)|0,i=(i=i+Math.imul(z,G)|0)+Math.imul(R,H)|0,a=a+Math.imul(R,G)|0,n=n+Math.imul(O,Y)|0,i=(i=i+Math.imul(O,X)|0)+Math.imul(I,Y)|0,a=a+Math.imul(I,X)|0,n=n+Math.imul(L,K)|0,i=(i=i+Math.imul(L,J)|0)+Math.imul(C,K)|0,a=a+Math.imul(C,J)|0,n=n+Math.imul(M,Q)|0,i=(i=i+Math.imul(M,tt)|0)+Math.imul(S,Q)|0,a=a+Math.imul(S,tt)|0,n=n+Math.imul(T,rt)|0,i=(i=i+Math.imul(T,nt)|0)+Math.imul(k,rt)|0,a=a+Math.imul(k,nt)|0,n=n+Math.imul(b,at)|0,i=(i=i+Math.imul(b,ot)|0)+Math.imul(_,at)|0,a=a+Math.imul(_,ot)|0,n=n+Math.imul(y,lt)|0,i=(i=i+Math.imul(y,ut)|0)+Math.imul(m,lt)|0,a=a+Math.imul(m,ut)|0,n=n+Math.imul(d,ft)|0,i=(i=i+Math.imul(d,ht)|0)+Math.imul(v,ft)|0,a=a+Math.imul(v,ht)|0;var At=(u+(n=n+Math.imul(f,dt)|0)|0)+((8191&(i=(i=i+Math.imul(f,vt)|0)+Math.imul(h,dt)|0))<<13)|0;u=((a=a+Math.imul(h,vt)|0)+(i>>>13)|0)+(At>>>26)|0,At&=67108863,n=Math.imul(B,H),i=(i=Math.imul(B,G))+Math.imul(N,H)|0,a=Math.imul(N,G),n=n+Math.imul(z,Y)|0,i=(i=i+Math.imul(z,X)|0)+Math.imul(R,Y)|0,a=a+Math.imul(R,X)|0,n=n+Math.imul(O,K)|0,i=(i=i+Math.imul(O,J)|0)+Math.imul(I,K)|0,a=a+Math.imul(I,J)|0,n=n+Math.imul(L,Q)|0,i=(i=i+Math.imul(L,tt)|0)+Math.imul(C,Q)|0,a=a+Math.imul(C,tt)|0,n=n+Math.imul(M,rt)|0,i=(i=i+Math.imul(M,nt)|0)+Math.imul(S,rt)|0,a=a+Math.imul(S,nt)|0,n=n+Math.imul(T,at)|0,i=(i=i+Math.imul(T,ot)|0)+Math.imul(k,at)|0,a=a+Math.imul(k,ot)|0,n=n+Math.imul(b,lt)|0,i=(i=i+Math.imul(b,ut)|0)+Math.imul(_,lt)|0,a=a+Math.imul(_,ut)|0,n=n+Math.imul(y,ft)|0,i=(i=i+Math.imul(y,ht)|0)+Math.imul(m,ft)|0,a=a+Math.imul(m,ht)|0;var Mt=(u+(n=n+Math.imul(d,dt)|0)|0)+((8191&(i=(i=i+Math.imul(d,vt)|0)+Math.imul(v,dt)|0))<<13)|0;u=((a=a+Math.imul(v,vt)|0)+(i>>>13)|0)+(Mt>>>26)|0,Mt&=67108863,n=Math.imul(B,Y),i=(i=Math.imul(B,X))+Math.imul(N,Y)|0,a=Math.imul(N,X),n=n+Math.imul(z,K)|0,i=(i=i+Math.imul(z,J)|0)+Math.imul(R,K)|0,a=a+Math.imul(R,J)|0,n=n+Math.imul(O,Q)|0,i=(i=i+Math.imul(O,tt)|0)+Math.imul(I,Q)|0,a=a+Math.imul(I,tt)|0,n=n+Math.imul(L,rt)|0,i=(i=i+Math.imul(L,nt)|0)+Math.imul(C,rt)|0,a=a+Math.imul(C,nt)|0,n=n+Math.imul(M,at)|0,i=(i=i+Math.imul(M,ot)|0)+Math.imul(S,at)|0,a=a+Math.imul(S,ot)|0,n=n+Math.imul(T,lt)|0,i=(i=i+Math.imul(T,ut)|0)+Math.imul(k,lt)|0,a=a+Math.imul(k,ut)|0,n=n+Math.imul(b,ft)|0,i=(i=i+Math.imul(b,ht)|0)+Math.imul(_,ft)|0,a=a+Math.imul(_,ht)|0;var St=(u+(n=n+Math.imul(y,dt)|0)|0)+((8191&(i=(i=i+Math.imul(y,vt)|0)+Math.imul(m,dt)|0))<<13)|0;u=((a=a+Math.imul(m,vt)|0)+(i>>>13)|0)+(St>>>26)|0,St&=67108863,n=Math.imul(B,K),i=(i=Math.imul(B,J))+Math.imul(N,K)|0,a=Math.imul(N,J),n=n+Math.imul(z,Q)|0,i=(i=i+Math.imul(z,tt)|0)+Math.imul(R,Q)|0,a=a+Math.imul(R,tt)|0,n=n+Math.imul(O,rt)|0,i=(i=i+Math.imul(O,nt)|0)+Math.imul(I,rt)|0,a=a+Math.imul(I,nt)|0,n=n+Math.imul(L,at)|0,i=(i=i+Math.imul(L,ot)|0)+Math.imul(C,at)|0,a=a+Math.imul(C,ot)|0,n=n+Math.imul(M,lt)|0,i=(i=i+Math.imul(M,ut)|0)+Math.imul(S,lt)|0,a=a+Math.imul(S,ut)|0,n=n+Math.imul(T,ft)|0,i=(i=i+Math.imul(T,ht)|0)+Math.imul(k,ft)|0,a=a+Math.imul(k,ht)|0;var Et=(u+(n=n+Math.imul(b,dt)|0)|0)+((8191&(i=(i=i+Math.imul(b,vt)|0)+Math.imul(_,dt)|0))<<13)|0;u=((a=a+Math.imul(_,vt)|0)+(i>>>13)|0)+(Et>>>26)|0,Et&=67108863,n=Math.imul(B,Q),i=(i=Math.imul(B,tt))+Math.imul(N,Q)|0,a=Math.imul(N,tt),n=n+Math.imul(z,rt)|0,i=(i=i+Math.imul(z,nt)|0)+Math.imul(R,rt)|0,a=a+Math.imul(R,nt)|0,n=n+Math.imul(O,at)|0,i=(i=i+Math.imul(O,ot)|0)+Math.imul(I,at)|0,a=a+Math.imul(I,ot)|0,n=n+Math.imul(L,lt)|0,i=(i=i+Math.imul(L,ut)|0)+Math.imul(C,lt)|0,a=a+Math.imul(C,ut)|0,n=n+Math.imul(M,ft)|0,i=(i=i+Math.imul(M,ht)|0)+Math.imul(S,ft)|0,a=a+Math.imul(S,ht)|0;var Lt=(u+(n=n+Math.imul(T,dt)|0)|0)+((8191&(i=(i=i+Math.imul(T,vt)|0)+Math.imul(k,dt)|0))<<13)|0;u=((a=a+Math.imul(k,vt)|0)+(i>>>13)|0)+(Lt>>>26)|0,Lt&=67108863,n=Math.imul(B,rt),i=(i=Math.imul(B,nt))+Math.imul(N,rt)|0,a=Math.imul(N,nt),n=n+Math.imul(z,at)|0,i=(i=i+Math.imul(z,ot)|0)+Math.imul(R,at)|0,a=a+Math.imul(R,ot)|0,n=n+Math.imul(O,lt)|0,i=(i=i+Math.imul(O,ut)|0)+Math.imul(I,lt)|0,a=a+Math.imul(I,ut)|0,n=n+Math.imul(L,ft)|0,i=(i=i+Math.imul(L,ht)|0)+Math.imul(C,ft)|0,a=a+Math.imul(C,ht)|0;var Ct=(u+(n=n+Math.imul(M,dt)|0)|0)+((8191&(i=(i=i+Math.imul(M,vt)|0)+Math.imul(S,dt)|0))<<13)|0;u=((a=a+Math.imul(S,vt)|0)+(i>>>13)|0)+(Ct>>>26)|0,Ct&=67108863,n=Math.imul(B,at),i=(i=Math.imul(B,ot))+Math.imul(N,at)|0,a=Math.imul(N,ot),n=n+Math.imul(z,lt)|0,i=(i=i+Math.imul(z,ut)|0)+Math.imul(R,lt)|0,a=a+Math.imul(R,ut)|0,n=n+Math.imul(O,ft)|0,i=(i=i+Math.imul(O,ht)|0)+Math.imul(I,ft)|0,a=a+Math.imul(I,ht)|0;var Pt=(u+(n=n+Math.imul(L,dt)|0)|0)+((8191&(i=(i=i+Math.imul(L,vt)|0)+Math.imul(C,dt)|0))<<13)|0;u=((a=a+Math.imul(C,vt)|0)+(i>>>13)|0)+(Pt>>>26)|0,Pt&=67108863,n=Math.imul(B,lt),i=(i=Math.imul(B,ut))+Math.imul(N,lt)|0,a=Math.imul(N,ut),n=n+Math.imul(z,ft)|0,i=(i=i+Math.imul(z,ht)|0)+Math.imul(R,ft)|0,a=a+Math.imul(R,ht)|0;var Ot=(u+(n=n+Math.imul(O,dt)|0)|0)+((8191&(i=(i=i+Math.imul(O,vt)|0)+Math.imul(I,dt)|0))<<13)|0;u=((a=a+Math.imul(I,vt)|0)+(i>>>13)|0)+(Ot>>>26)|0,Ot&=67108863,n=Math.imul(B,ft),i=(i=Math.imul(B,ht))+Math.imul(N,ft)|0,a=Math.imul(N,ht);var It=(u+(n=n+Math.imul(z,dt)|0)|0)+((8191&(i=(i=i+Math.imul(z,vt)|0)+Math.imul(R,dt)|0))<<13)|0;u=((a=a+Math.imul(R,vt)|0)+(i>>>13)|0)+(It>>>26)|0,It&=67108863;var Dt=(u+(n=Math.imul(B,dt))|0)+((8191&(i=(i=Math.imul(B,vt))+Math.imul(N,dt)|0))<<13)|0;return u=((a=Math.imul(N,vt))+(i>>>13)|0)+(Dt>>>26)|0,Dt&=67108863,l[0]=gt,l[1]=yt,l[2]=mt,l[3]=xt,l[4]=bt,l[5]=_t,l[6]=wt,l[7]=Tt,l[8]=kt,l[9]=At,l[10]=Mt,l[11]=St,l[12]=Et,l[13]=Lt,l[14]=Ct,l[15]=Pt,l[16]=Ot,l[17]=It,l[18]=Dt,0!==u&&(l[19]=u,r.length++),r};function v(t,e,r){return(new g).mulp(t,e,r)}function g(t,e){this.x=t,this.y=e}Math.imul||(d=p),a.prototype.mulTo=function(t,e){var r,n=this.length+t.length;return r=10===this.length&&10===t.length?d(this,t,e):n<63?p(this,t,e):n<1024?function(t,e,r){r.negative=e.negative^t.negative,r.length=t.length+e.length;for(var n=0,i=0,a=0;a<r.length-1;a++){var o=i;i=0;for(var s=67108863&n,l=Math.min(a,e.length-1),u=Math.max(0,a-t.length+1);u<=l;u++){var c=a-u,f=(0|t.words[c])*(0|e.words[u]),h=67108863&f;s=67108863&(h=h+s|0),i+=(o=(o=o+(f/67108864|0)|0)+(h>>>26)|0)>>>26,o&=67108863}r.words[a]=s,n=o,o=i}return 0!==n?r.words[a]=n:r.length--,r.strip()}(this,t,e):v(this,t,e),r},g.prototype.makeRBT=function(t){for(var e=new Array(t),r=a.prototype._countBits(t)-1,n=0;n<t;n++)e[n]=this.revBin(n,r,t);return e},g.prototype.revBin=function(t,e,r){if(0===t||t===r-1)return t;for(var n=0,i=0;i<e;i++)n|=(1&t)<<e-i-1,t>>=1;return n},g.prototype.permute=function(t,e,r,n,i,a){for(var o=0;o<a;o++)n[o]=e[t[o]],i[o]=r[t[o]]},g.prototype.transform=function(t,e,r,n,i,a){this.permute(a,t,e,r,n,i);for(var o=1;o<i;o<<=1)for(var s=o<<1,l=Math.cos(2*Math.PI/s),u=Math.sin(2*Math.PI/s),c=0;c<i;c+=s)for(var f=l,h=u,p=0;p<o;p++){var d=r[c+p],v=n[c+p],g=r[c+p+o],y=n[c+p+o],m=f*g-h*y;y=f*y+h*g,g=m,r[c+p]=d+g,n[c+p]=v+y,r[c+p+o]=d-g,n[c+p+o]=v-y,p!==s&&(m=l*f-u*h,h=l*h+u*f,f=m)}},g.prototype.guessLen13b=function(t,e){var r=1|Math.max(e,t),n=1&r,i=0;for(r=r/2|0;r;r>>>=1)i++;return 1<<i+1+n},g.prototype.conjugate=function(t,e,r){if(!(r<=1))for(var n=0;n<r/2;n++){var i=t[n];t[n]=t[r-n-1],t[r-n-1]=i,i=e[n],e[n]=-e[r-n-1],e[r-n-1]=-i}},g.prototype.normalize13b=function(t,e){for(var r=0,n=0;n<e/2;n++){var i=8192*Math.round(t[2*n+1]/e)+Math.round(t[2*n]/e)+r;t[n]=67108863&i,r=i<67108864?0:i/67108864|0}return t},g.prototype.convert13b=function(t,e,r,i){for(var a=0,o=0;o<e;o++)a+=0|t[o],r[2*o]=8191&a,a>>>=13,r[2*o+1]=8191&a,a>>>=13;for(o=2*e;o<i;++o)r[o]=0;n(0===a),n(0==(-8192&a))},g.prototype.stub=function(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=0;return e},g.prototype.mulp=function(t,e,r){var n=2*this.guessLen13b(t.length,e.length),i=this.makeRBT(n),a=this.stub(n),o=new Array(n),s=new Array(n),l=new Array(n),u=new Array(n),c=new Array(n),f=new Array(n),h=r.words;h.length=n,this.convert13b(t.words,t.length,o,n),this.convert13b(e.words,e.length,u,n),this.transform(o,a,s,l,n,i),this.transform(u,a,c,f,n,i);for(var p=0;p<n;p++){var d=s[p]*c[p]-l[p]*f[p];l[p]=s[p]*f[p]+l[p]*c[p],s[p]=d}return this.conjugate(s,l,n),this.transform(s,l,h,a,n,i),this.conjugate(h,a,n),this.normalize13b(h,n),r.negative=t.negative^e.negative,r.length=t.length+e.length,r.strip()},a.prototype.mul=function(t){var e=new a(null);return e.words=new Array(this.length+t.length),this.mulTo(t,e)},a.prototype.mulf=function(t){var e=new a(null);return e.words=new Array(this.length+t.length),v(this,t,e)},a.prototype.imul=function(t){return this.clone().mulTo(t,this)},a.prototype.imuln=function(t){n(\"number\"==typeof t),n(t<67108864);for(var e=0,r=0;r<this.length;r++){var i=(0|this.words[r])*t,a=(67108863&i)+(67108863&e);e>>=26,e+=i/67108864|0,e+=a>>>26,this.words[r]=67108863&a}return 0!==e&&(this.words[r]=e,this.length++),this},a.prototype.muln=function(t){return this.clone().imuln(t)},a.prototype.sqr=function(){return this.mul(this)},a.prototype.isqr=function(){return this.imul(this.clone())},a.prototype.pow=function(t){var e=function(t){for(var e=new Array(t.bitLength()),r=0;r<e.length;r++){var n=r/26|0,i=r%26;e[r]=(t.words[n]&1<<i)>>>i}return e}(t);if(0===e.length)return new a(1);for(var r=this,n=0;n<e.length&&0===e[n];n++,r=r.sqr());if(++n<e.length)for(var i=r.sqr();n<e.length;n++,i=i.sqr())0!==e[n]&&(r=r.mul(i));return r},a.prototype.iushln=function(t){n(\"number\"==typeof t&&t>=0);var e,r=t%26,i=(t-r)/26,a=67108863>>>26-r<<26-r;if(0!==r){var o=0;for(e=0;e<this.length;e++){var s=this.words[e]&a,l=(0|this.words[e])-s<<r;this.words[e]=l|o,o=s>>>26-r}o&&(this.words[e]=o,this.length++)}if(0!==i){for(e=this.length-1;e>=0;e--)this.words[e+i]=this.words[e];for(e=0;e<i;e++)this.words[e]=0;this.length+=i}return this.strip()},a.prototype.ishln=function(t){return n(0===this.negative),this.iushln(t)},a.prototype.iushrn=function(t,e,r){var i;n(\"number\"==typeof t&&t>=0),i=e?(e-e%26)/26:0;var a=t%26,o=Math.min((t-a)/26,this.length),s=67108863^67108863>>>a<<a,l=r;if(i-=o,i=Math.max(0,i),l){for(var u=0;u<o;u++)l.words[u]=this.words[u];l.length=o}if(0===o);else if(this.length>o)for(this.length-=o,u=0;u<this.length;u++)this.words[u]=this.words[u+o];else this.words[0]=0,this.length=1;var c=0;for(u=this.length-1;u>=0&&(0!==c||u>=i);u--){var f=0|this.words[u];this.words[u]=c<<26-a|f>>>a,c=f&s}return l&&0!==c&&(l.words[l.length++]=c),0===this.length&&(this.words[0]=0,this.length=1),this.strip()},a.prototype.ishrn=function(t,e,r){return n(0===this.negative),this.iushrn(t,e,r)},a.prototype.shln=function(t){return this.clone().ishln(t)},a.prototype.ushln=function(t){return this.clone().iushln(t)},a.prototype.shrn=function(t){return this.clone().ishrn(t)},a.prototype.ushrn=function(t){return this.clone().iushrn(t)},a.prototype.testn=function(t){n(\"number\"==typeof t&&t>=0);var e=t%26,r=(t-e)/26,i=1<<e;return!(this.length<=r||!(this.words[r]&i))},a.prototype.imaskn=function(t){n(\"number\"==typeof t&&t>=0);var e=t%26,r=(t-e)/26;if(n(0===this.negative,\"imaskn works only with positive numbers\"),this.length<=r)return this;if(0!==e&&r++,this.length=Math.min(r,this.length),0!==e){var i=67108863^67108863>>>e<<e;this.words[this.length-1]&=i}return this.strip()},a.prototype.maskn=function(t){return this.clone().imaskn(t)},a.prototype.iaddn=function(t){return n(\"number\"==typeof t),n(t<67108864),t<0?this.isubn(-t):0!==this.negative?1===this.length&&(0|this.words[0])<t?(this.words[0]=t-(0|this.words[0]),this.negative=0,this):(this.negative=0,this.isubn(t),this.negative=1,this):this._iaddn(t)},a.prototype._iaddn=function(t){this.words[0]+=t;for(var e=0;e<this.length&&this.words[e]>=67108864;e++)this.words[e]-=67108864,e===this.length-1?this.words[e+1]=1:this.words[e+1]++;return this.length=Math.max(this.length,e+1),this},a.prototype.isubn=function(t){if(n(\"number\"==typeof t),n(t<67108864),t<0)return this.iaddn(-t);if(0!==this.negative)return this.negative=0,this.iaddn(t),this.negative=1,this;if(this.words[0]-=t,1===this.length&&this.words[0]<0)this.words[0]=-this.words[0],this.negative=1;else for(var e=0;e<this.length&&this.words[e]<0;e++)this.words[e]+=67108864,this.words[e+1]-=1;return this.strip()},a.prototype.addn=function(t){return this.clone().iaddn(t)},a.prototype.subn=function(t){return this.clone().isubn(t)},a.prototype.iabs=function(){return this.negative=0,this},a.prototype.abs=function(){return this.clone().iabs()},a.prototype._ishlnsubmul=function(t,e,r){var i,a,o=t.length+r;this._expand(o);var s=0;for(i=0;i<t.length;i++){a=(0|this.words[i+r])+s;var l=(0|t.words[i])*e;s=((a-=67108863&l)>>26)-(l/67108864|0),this.words[i+r]=67108863&a}for(;i<this.length-r;i++)s=(a=(0|this.words[i+r])+s)>>26,this.words[i+r]=67108863&a;if(0===s)return this.strip();for(n(-1===s),s=0,i=0;i<this.length;i++)s=(a=-(0|this.words[i])+s)>>26,this.words[i]=67108863&a;return this.negative=1,this.strip()},a.prototype._wordDiv=function(t,e){var r=(this.length,t.length),n=this.clone(),i=t,o=0|i.words[i.length-1];0!=(r=26-this._countBits(o))&&(i=i.ushln(r),n.iushln(r),o=0|i.words[i.length-1]);var s,l=n.length-i.length;if(\"mod\"!==e){(s=new a(null)).length=l+1,s.words=new Array(s.length);for(var u=0;u<s.length;u++)s.words[u]=0}var c=n.clone()._ishlnsubmul(i,1,l);0===c.negative&&(n=c,s&&(s.words[l]=1));for(var f=l-1;f>=0;f--){var h=67108864*(0|n.words[i.length+f])+(0|n.words[i.length+f-1]);for(h=Math.min(h/o|0,67108863),n._ishlnsubmul(i,h,f);0!==n.negative;)h--,n.negative=0,n._ishlnsubmul(i,1,f),n.isZero()||(n.negative^=1);s&&(s.words[f]=h)}return s&&s.strip(),n.strip(),\"div\"!==e&&0!==r&&n.iushrn(r),{div:s||null,mod:n}},a.prototype.divmod=function(t,e,r){return n(!t.isZero()),this.isZero()?{div:new a(0),mod:new a(0)}:0!==this.negative&&0===t.negative?(s=this.neg().divmod(t,e),\"mod\"!==e&&(i=s.div.neg()),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.iadd(t)),{div:i,mod:o}):0===this.negative&&0!==t.negative?(s=this.divmod(t.neg(),e),\"mod\"!==e&&(i=s.div.neg()),{div:i,mod:s.mod}):0!=(this.negative&t.negative)?(s=this.neg().divmod(t.neg(),e),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.isub(t)),{div:s.div,mod:o}):t.length>this.length||this.cmp(t)<0?{div:new a(0),mod:this}:1===t.length?\"div\"===e?{div:this.divn(t.words[0]),mod:null}:\"mod\"===e?{div:null,mod:new a(this.modn(t.words[0]))}:{div:this.divn(t.words[0]),mod:new a(this.modn(t.words[0]))}:this._wordDiv(t,e);var i,o,s},a.prototype.div=function(t){return this.divmod(t,\"div\",!1).div},a.prototype.mod=function(t){return this.divmod(t,\"mod\",!1).mod},a.prototype.umod=function(t){return this.divmod(t,\"mod\",!0).mod},a.prototype.divRound=function(t){var e=this.divmod(t);if(e.mod.isZero())return e.div;var r=0!==e.div.negative?e.mod.isub(t):e.mod,n=t.ushrn(1),i=t.andln(1),a=r.cmp(n);return a<0||1===i&&0===a?e.div:0!==e.div.negative?e.div.isubn(1):e.div.iaddn(1)},a.prototype.modn=function(t){n(t<=67108863);for(var e=(1<<26)%t,r=0,i=this.length-1;i>=0;i--)r=(e*r+(0|this.words[i]))%t;return r},a.prototype.idivn=function(t){n(t<=67108863);for(var e=0,r=this.length-1;r>=0;r--){var i=(0|this.words[r])+67108864*e;this.words[r]=i/t|0,e=i%t}return this.strip()},a.prototype.divn=function(t){return this.clone().idivn(t)},a.prototype.egcd=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i=new a(1),o=new a(0),s=new a(0),l=new a(1),u=0;e.isEven()&&r.isEven();)e.iushrn(1),r.iushrn(1),++u;for(var c=r.clone(),f=e.clone();!e.isZero();){for(var h=0,p=1;0==(e.words[0]&p)&&h<26;++h,p<<=1);if(h>0)for(e.iushrn(h);h-- >0;)(i.isOdd()||o.isOdd())&&(i.iadd(c),o.isub(f)),i.iushrn(1),o.iushrn(1);for(var d=0,v=1;0==(r.words[0]&v)&&d<26;++d,v<<=1);if(d>0)for(r.iushrn(d);d-- >0;)(s.isOdd()||l.isOdd())&&(s.iadd(c),l.isub(f)),s.iushrn(1),l.iushrn(1);e.cmp(r)>=0?(e.isub(r),i.isub(s),o.isub(l)):(r.isub(e),s.isub(i),l.isub(o))}return{a:s,b:l,gcd:r.iushln(u)}},a.prototype._invmp=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i,o=new a(1),s=new a(0),l=r.clone();e.cmpn(1)>0&&r.cmpn(1)>0;){for(var u=0,c=1;0==(e.words[0]&c)&&u<26;++u,c<<=1);if(u>0)for(e.iushrn(u);u-- >0;)o.isOdd()&&o.iadd(l),o.iushrn(1);for(var f=0,h=1;0==(r.words[0]&h)&&f<26;++f,h<<=1);if(f>0)for(r.iushrn(f);f-- >0;)s.isOdd()&&s.iadd(l),s.iushrn(1);e.cmp(r)>=0?(e.isub(r),o.isub(s)):(r.isub(e),s.isub(o))}return(i=0===e.cmpn(1)?o:s).cmpn(0)<0&&i.iadd(t),i},a.prototype.gcd=function(t){if(this.isZero())return t.abs();if(t.isZero())return this.abs();var e=this.clone(),r=t.clone();e.negative=0,r.negative=0;for(var n=0;e.isEven()&&r.isEven();n++)e.iushrn(1),r.iushrn(1);for(;;){for(;e.isEven();)e.iushrn(1);for(;r.isEven();)r.iushrn(1);var i=e.cmp(r);if(i<0){var a=e;e=r,r=a}else if(0===i||0===r.cmpn(1))break;e.isub(r)}return r.iushln(n)},a.prototype.invm=function(t){return this.egcd(t).a.umod(t)},a.prototype.isEven=function(){return 0==(1&this.words[0])},a.prototype.isOdd=function(){return 1==(1&this.words[0])},a.prototype.andln=function(t){return this.words[0]&t},a.prototype.bincn=function(t){n(\"number\"==typeof t);var e=t%26,r=(t-e)/26,i=1<<e;if(this.length<=r)return this._expand(r+1),this.words[r]|=i,this;for(var a=i,o=r;0!==a&&o<this.length;o++){var s=0|this.words[o];a=(s+=a)>>>26,s&=67108863,this.words[o]=s}return 0!==a&&(this.words[o]=a,this.length++),this},a.prototype.isZero=function(){return 1===this.length&&0===this.words[0]},a.prototype.cmpn=function(t){var e,r=t<0;if(0!==this.negative&&!r)return-1;if(0===this.negative&&r)return 1;if(this.strip(),this.length>1)e=1;else{r&&(t=-t),n(t<=67108863,\"Number is too big\");var i=0|this.words[0];e=i===t?0:i<t?-1:1}return 0!==this.negative?0|-e:e},a.prototype.cmp=function(t){if(0!==this.negative&&0===t.negative)return-1;if(0===this.negative&&0!==t.negative)return 1;var e=this.ucmp(t);return 0!==this.negative?0|-e:e},a.prototype.ucmp=function(t){if(this.length>t.length)return 1;if(this.length<t.length)return-1;for(var e=0,r=this.length-1;r>=0;r--){var n=0|this.words[r],i=0|t.words[r];if(n!==i){n<i?e=-1:n>i&&(e=1);break}}return e},a.prototype.gtn=function(t){return 1===this.cmpn(t)},a.prototype.gt=function(t){return 1===this.cmp(t)},a.prototype.gten=function(t){return this.cmpn(t)>=0},a.prototype.gte=function(t){return this.cmp(t)>=0},a.prototype.ltn=function(t){return-1===this.cmpn(t)},a.prototype.lt=function(t){return-1===this.cmp(t)},a.prototype.lten=function(t){return this.cmpn(t)<=0},a.prototype.lte=function(t){return this.cmp(t)<=0},a.prototype.eqn=function(t){return 0===this.cmpn(t)},a.prototype.eq=function(t){return 0===this.cmp(t)},a.red=function(t){return new T(t)},a.prototype.toRed=function(t){return n(!this.red,\"Already a number in reduction context\"),n(0===this.negative,\"red works only with positives\"),t.convertTo(this)._forceRed(t)},a.prototype.fromRed=function(){return n(this.red,\"fromRed works only with numbers in reduction context\"),this.red.convertFrom(this)},a.prototype._forceRed=function(t){return this.red=t,this},a.prototype.forceRed=function(t){return n(!this.red,\"Already a number in reduction context\"),this._forceRed(t)},a.prototype.redAdd=function(t){return n(this.red,\"redAdd works only with red numbers\"),this.red.add(this,t)},a.prototype.redIAdd=function(t){return n(this.red,\"redIAdd works only with red numbers\"),this.red.iadd(this,t)},a.prototype.redSub=function(t){return n(this.red,\"redSub works only with red numbers\"),this.red.sub(this,t)},a.prototype.redISub=function(t){return n(this.red,\"redISub works only with red numbers\"),this.red.isub(this,t)},a.prototype.redShl=function(t){return n(this.red,\"redShl works only with red numbers\"),this.red.shl(this,t)},a.prototype.redMul=function(t){return n(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.mul(this,t)},a.prototype.redIMul=function(t){return n(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.imul(this,t)},a.prototype.redSqr=function(){return n(this.red,\"redSqr works only with red numbers\"),this.red._verify1(this),this.red.sqr(this)},a.prototype.redISqr=function(){return n(this.red,\"redISqr works only with red numbers\"),this.red._verify1(this),this.red.isqr(this)},a.prototype.redSqrt=function(){return n(this.red,\"redSqrt works only with red numbers\"),this.red._verify1(this),this.red.sqrt(this)},a.prototype.redInvm=function(){return n(this.red,\"redInvm works only with red numbers\"),this.red._verify1(this),this.red.invm(this)},a.prototype.redNeg=function(){return n(this.red,\"redNeg works only with red numbers\"),this.red._verify1(this),this.red.neg(this)},a.prototype.redPow=function(t){return n(this.red&&!t.red,\"redPow(normalNum)\"),this.red._verify1(this),this.red.pow(this,t)};var y={k256:null,p224:null,p192:null,p25519:null};function m(t,e){this.name=t,this.p=new a(e,16),this.n=this.p.bitLength(),this.k=new a(1).iushln(this.n).isub(this.p),this.tmp=this._tmp()}function x(){m.call(this,\"k256\",\"ffffffff ffffffff ffffffff ffffffff ffffffff ffffffff fffffffe fffffc2f\")}function b(){m.call(this,\"p224\",\"ffffffff ffffffff ffffffff ffffffff 00000000 00000000 00000001\")}function _(){m.call(this,\"p192\",\"ffffffff ffffffff ffffffff fffffffe ffffffff ffffffff\")}function w(){m.call(this,\"25519\",\"7fffffffffffffff ffffffffffffffff ffffffffffffffff ffffffffffffffed\")}function T(t){if(\"string\"==typeof t){var e=a._prime(t);this.m=e.p,this.prime=e}else n(t.gtn(1),\"modulus must be greater than 1\"),this.m=t,this.prime=null}function k(t){T.call(this,t),this.shift=this.m.bitLength(),this.shift%26!=0&&(this.shift+=26-this.shift%26),this.r=new a(1).iushln(this.shift),this.r2=this.imod(this.r.sqr()),this.rinv=this.r._invmp(this.m),this.minv=this.rinv.mul(this.r).isubn(1).div(this.m),this.minv=this.minv.umod(this.r),this.minv=this.r.sub(this.minv)}m.prototype._tmp=function(){var t=new a(null);return t.words=new Array(Math.ceil(this.n/13)),t},m.prototype.ireduce=function(t){var e,r=t;do{this.split(r,this.tmp),e=(r=(r=this.imulK(r)).iadd(this.tmp)).bitLength()}while(e>this.n);var n=e<this.n?-1:r.ucmp(this.p);return 0===n?(r.words[0]=0,r.length=1):n>0?r.isub(this.p):void 0!==r.strip?r.strip():r._strip(),r},m.prototype.split=function(t,e){t.iushrn(this.n,0,e)},m.prototype.imulK=function(t){return t.imul(this.k)},i(x,m),x.prototype.split=function(t,e){for(var r=4194303,n=Math.min(t.length,9),i=0;i<n;i++)e.words[i]=t.words[i];if(e.length=n,t.length<=9)return t.words[0]=0,void(t.length=1);var a=t.words[9];for(e.words[e.length++]=a&r,i=10;i<t.length;i++){var o=0|t.words[i];t.words[i-10]=(o&r)<<4|a>>>22,a=o}a>>>=22,t.words[i-10]=a,0===a&&t.length>10?t.length-=10:t.length-=9},x.prototype.imulK=function(t){t.words[t.length]=0,t.words[t.length+1]=0,t.length+=2;for(var e=0,r=0;r<t.length;r++){var n=0|t.words[r];e+=977*n,t.words[r]=67108863&e,e=64*n+(e/67108864|0)}return 0===t.words[t.length-1]&&(t.length--,0===t.words[t.length-1]&&t.length--),t},i(b,m),i(_,m),i(w,m),w.prototype.imulK=function(t){for(var e=0,r=0;r<t.length;r++){var n=19*(0|t.words[r])+e,i=67108863&n;n>>>=26,t.words[r]=i,e=n}return 0!==e&&(t.words[t.length++]=e),t},a._prime=function(t){if(y[t])return y[t];var e;if(\"k256\"===t)e=new x;else if(\"p224\"===t)e=new b;else if(\"p192\"===t)e=new _;else{if(\"p25519\"!==t)throw new Error(\"Unknown prime \"+t);e=new w}return y[t]=e,e},T.prototype._verify1=function(t){n(0===t.negative,\"red works only with positives\"),n(t.red,\"red works only with red numbers\")},T.prototype._verify2=function(t,e){n(0==(t.negative|e.negative),\"red works only with positives\"),n(t.red&&t.red===e.red,\"red works only with red numbers\")},T.prototype.imod=function(t){return this.prime?this.prime.ireduce(t)._forceRed(this):t.umod(this.m)._forceRed(this)},T.prototype.neg=function(t){return t.isZero()?t.clone():this.m.sub(t)._forceRed(this)},T.prototype.add=function(t,e){this._verify2(t,e);var r=t.add(e);return r.cmp(this.m)>=0&&r.isub(this.m),r._forceRed(this)},T.prototype.iadd=function(t,e){this._verify2(t,e);var r=t.iadd(e);return r.cmp(this.m)>=0&&r.isub(this.m),r},T.prototype.sub=function(t,e){this._verify2(t,e);var r=t.sub(e);return r.cmpn(0)<0&&r.iadd(this.m),r._forceRed(this)},T.prototype.isub=function(t,e){this._verify2(t,e);var r=t.isub(e);return r.cmpn(0)<0&&r.iadd(this.m),r},T.prototype.shl=function(t,e){return this._verify1(t),this.imod(t.ushln(e))},T.prototype.imul=function(t,e){return this._verify2(t,e),this.imod(t.imul(e))},T.prototype.mul=function(t,e){return this._verify2(t,e),this.imod(t.mul(e))},T.prototype.isqr=function(t){return this.imul(t,t.clone())},T.prototype.sqr=function(t){return this.mul(t,t)},T.prototype.sqrt=function(t){if(t.isZero())return t.clone();var e=this.m.andln(3);if(n(e%2==1),3===e){var r=this.m.add(new a(1)).iushrn(2);return this.pow(t,r)}for(var i=this.m.subn(1),o=0;!i.isZero()&&0===i.andln(1);)o++,i.iushrn(1);n(!i.isZero());var s=new a(1).toRed(this),l=s.redNeg(),u=this.m.subn(1).iushrn(1),c=this.m.bitLength();for(c=new a(2*c*c).toRed(this);0!==this.pow(c,u).cmp(l);)c.redIAdd(l);for(var f=this.pow(c,i),h=this.pow(t,i.addn(1).iushrn(1)),p=this.pow(t,i),d=o;0!==p.cmp(s);){for(var v=p,g=0;0!==v.cmp(s);g++)v=v.redSqr();n(g<d);var y=this.pow(f,new a(1).iushln(d-g-1));h=h.redMul(y),f=y.redSqr(),p=p.redMul(f),d=g}return h},T.prototype.invm=function(t){var e=t._invmp(this.m);return 0!==e.negative?(e.negative=0,this.imod(e).redNeg()):this.imod(e)},T.prototype.pow=function(t,e){if(e.isZero())return new a(1).toRed(this);if(0===e.cmpn(1))return t.clone();var r=new Array(16);r[0]=new a(1).toRed(this),r[1]=t;for(var n=2;n<r.length;n++)r[n]=this.mul(r[n-1],t);var i=r[0],o=0,s=0,l=e.bitLength()%26;for(0===l&&(l=26),n=e.length-1;n>=0;n--){for(var u=e.words[n],c=l-1;c>=0;c--){var f=u>>c&1;i!==r[0]&&(i=this.sqr(i)),0!==f||0!==o?(o<<=1,o|=f,(4==++s||0===n&&0===c)&&(i=this.mul(i,r[o]),s=0,o=0)):s=0}l=26}return i},T.prototype.convertTo=function(t){var e=t.umod(this.m);return e===t?e.clone():e},T.prototype.convertFrom=function(t){var e=t.clone();return e.red=null,e},a.mont=function(t){return new k(t)},i(k,T),k.prototype.convertTo=function(t){return this.imod(t.ushln(this.shift))},k.prototype.convertFrom=function(t){var e=this.imod(t.mul(this.rinv));return e.red=null,e},k.prototype.imul=function(t,e){if(t.isZero()||e.isZero())return t.words[0]=0,t.length=1,t;var r=t.imul(e),n=r.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),i=r.isub(n).iushrn(this.shift),a=i;return i.cmp(this.m)>=0?a=i.isub(this.m):i.cmpn(0)<0&&(a=i.iadd(this.m)),a._forceRed(this)},k.prototype.mul=function(t,e){if(t.isZero()||e.isZero())return new a(0)._forceRed(this);var 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if(h.right===s){if(!(d=p.left)||0!==d._color){p._color=0,p.right=h.left,h._color=1,h.left=p,l[f-2]=h,l[f-1]=s,i(p),i(h),f>=3&&((v=l[f-3]).right===p?v.right=h:v.left=h);break}h._color=1,p.left=n(1,d),p._color=0,f-=1}else{var d;if(!(d=p.left)||0!==d._color){var v;h.left=s.right,p._color=0,p.right=s.left,s._color=1,s.right=h,s.left=p,l[f-2]=s,l[f-1]=h,i(p),i(h),i(s),f>=3&&((v=l[f-3]).right===p?v.right=s:v.left=s);break}h._color=1,p.left=n(1,d),p._color=0,f-=1}}return l[0]._color=1,new a(o,l[0])},o.forEach=function(t,e,r){if(this.root)switch(arguments.length){case 1:return s(t,this.root);case 2:return l(e,this._compare,t,this.root);case 3:if(this._compare(e,r)>=0)return;return u(e,r,this._compare,t,this.root)}},Object.defineProperty(o,\"begin\",{get:function(){for(var t=[],e=this.root;e;)t.push(e),e=e.left;return new c(this,t)}}),Object.defineProperty(o,\"end\",{get:function(){for(var t=[],e=this.root;e;)t.push(e),e=e.right;return new c(this,t)}}),o.at=function(t){if(t<0)return new c(this,[]);for(var e=this.root,r=[];;){if(r.push(e),e.left){if(t<e.left._count){e=e.left;continue}t-=e.left._count}if(!t)return new c(this,r);if(t-=1,!e.right)break;if(t>=e.right._count)break;e=e.right}return new c(this,[])},o.ge=function(t){for(var e=this._compare,r=this.root,n=[],i=0;r;){var a=e(t,r.key);n.push(r),a<=0&&(i=n.length),r=a<=0?r.left:r.right}return n.length=i,new c(this,n)},o.gt=function(t){for(var e=this._compare,r=this.root,n=[],i=0;r;){var a=e(t,r.key);n.push(r),a<0&&(i=n.length),r=a<0?r.left:r.right}return n.length=i,new c(this,n)},o.lt=function(t){for(var e=this._compare,r=this.root,n=[],i=0;r;){var a=e(t,r.key);n.push(r),a>0&&(i=n.length),r=a<=0?r.left:r.right}return n.length=i,new c(this,n)},o.le=function(t){for(var e=this._compare,r=this.root,n=[],i=0;r;){var a=e(t,r.key);n.push(r),a>=0&&(i=n.length),r=a<0?r.left:r.right}return n.length=i,new c(this,n)},o.find=function(t){for(var e=this._compare,r=this.root,n=[];r;){var i=e(t,r.key);if(n.push(r),0===i)return new c(this,n);r=i<=0?r.left:r.right}return new c(this,[])},o.remove=function(t){var e=this.find(t);return e?e.remove():this},o.get=function(t){for(var e=this._compare,r=this.root;r;){var n=e(t,r.key);if(0===n)return r.value;r=n<=0?r.left:r.right}};var f=c.prototype;function h(t,e){t.key=e.key,t.value=e.value,t.left=e.left,t.right=e.right,t._color=e._color,t._count=e._count}function p(t,e){return t<e?-1:t>e?1:0}Object.defineProperty(f,\"valid\",{get:function(){return this._stack.length>0}}),Object.defineProperty(f,\"node\",{get:function(){return this._stack.length>0?this._stack[this._stack.length-1]:null},enumerable:!0}),f.clone=function(){return new c(this.tree,this._stack.slice())},f.remove=function(){var t=this._stack;if(0===t.length)return this.tree;var o=new Array(t.length),s=t[t.length-1];o[o.length-1]=new e(s._color,s.key,s.value,s.left,s.right,s._count);for(var l=t.length-2;l>=0;--l)(s=t[l]).left===t[l+1]?o[l]=new e(s._color,s.key,s.value,o[l+1],s.right,s._count):o[l]=new e(s._color,s.key,s.value,s.left,o[l+1],s._count);if((s=o[o.length-1]).left&&s.right){var u=o.length;for(s=s.left;s.right;)o.push(s),s=s.right;var c=o[u-1];for(o.push(new e(s._color,c.key,c.value,s.left,s.right,s._count)),o[u-1].key=s.key,o[u-1].value=s.value,l=o.length-2;l>=u;--l)s=o[l],o[l]=new e(s._color,s.key,s.value,s.left,o[l+1],s._count);o[u-1].left=o[u]}if(0===(s=o[o.length-1])._color){var f=o[o.length-2];for(f.left===s?f.left=null:f.right===s&&(f.right=null),o.pop(),l=0;l<o.length;++l)o[l]._count--;return new a(this.tree._compare,o[0])}if(s.left||s.right){for(s.left?h(s,s.left):s.right&&h(s,s.right),s._color=1,l=0;l<o.length-1;++l)o[l]._count--;return new a(this.tree._compare,o[0])}if(1===o.length)return new a(this.tree._compare,null);for(l=0;l<o.length;++l)o[l]._count--;var p=o[o.length-2];return function(t){for(var e,a,o,s,l=t.length-1;l>=0;--l){if(e=t[l],0===l)return void(e._color=1);if((a=t[l-1]).left===e){if((o=a.right).right&&0===o.right._color)return s=(o=a.right=r(o)).right=r(o.right),a.right=o.left,o.left=a,o.right=s,o._color=a._color,e._color=1,a._color=1,s._color=1,i(a),i(o),l>1&&((u=t[l-2]).left===a?u.left=o:u.right=o),void(t[l-1]=o);if(o.left&&0===o.left._color)return s=(o=a.right=r(o)).left=r(o.left),a.right=s.left,o.left=s.right,s.left=a,s.right=o,s._color=a._color,a._color=1,o._color=1,e._color=1,i(a),i(o),i(s),l>1&&((u=t[l-2]).left===a?u.left=s:u.right=s),void(t[l-1]=s);if(1===o._color){if(0===a._color)return a._color=1,void(a.right=n(0,o));a.right=n(0,o);continue}o=r(o),a.right=o.left,o.left=a,o._color=a._color,a._color=0,i(a),i(o),l>1&&((u=t[l-2]).left===a?u.left=o:u.right=o),t[l-1]=o,t[l]=a,l+1<t.length?t[l+1]=e:t.push(e),l+=2}else{if((o=a.left).left&&0===o.left._color)return s=(o=a.left=r(o)).left=r(o.left),a.left=o.right,o.right=a,o.left=s,o._color=a._color,e._color=1,a._color=1,s._color=1,i(a),i(o),l>1&&((u=t[l-2]).right===a?u.right=o:u.left=o),void(t[l-1]=o);if(o.right&&0===o.right._color)return s=(o=a.left=r(o)).right=r(o.right),a.left=s.right,o.right=s.left,s.right=a,s.left=o,s._color=a._color,a._color=1,o._color=1,e._color=1,i(a),i(o),i(s),l>1&&((u=t[l-2]).right===a?u.right=s:u.left=s),void(t[l-1]=s);if(1===o._color){if(0===a._color)return a._color=1,void(a.left=n(0,o));a.left=n(0,o);continue}var u;o=r(o),a.left=o.right,o.right=a,o._color=a._color,a._color=0,i(a),i(o),l>1&&((u=t[l-2]).right===a?u.right=o:u.left=o),t[l-1]=o,t[l]=a,l+1<t.length?t[l+1]=e:t.push(e),l+=2}}}(o),p.left===s?p.left=null:p.right=null,new a(this.tree._compare,o[0])},Object.defineProperty(f,\"key\",{get:function(){if(this._stack.length>0)return this._stack[this._stack.length-1].key},enumerable:!0}),Object.defineProperty(f,\"value\",{get:function(){if(this._stack.length>0)return this._stack[this._stack.length-1].value},enumerable:!0}),Object.defineProperty(f,\"index\",{get:function(){var t=0,e=this._stack;if(0===e.length){var r=this.tree.root;return r?r._count:0}e[e.length-1].left&&(t=e[e.length-1].left._count);for(var n=e.length-2;n>=0;--n)e[n+1]===e[n].right&&(++t,e[n].left&&(t+=e[n].left._count));return t},enumerable:!0}),f.next=function(){var t=this._stack;if(0!==t.length){var e=t[t.length-1];if(e.right)for(e=e.right;e;)t.push(e),e=e.left;else for(t.pop();t.length>0&&t[t.length-1].right===e;)e=t[t.length-1],t.pop()}},Object.defineProperty(f,\"hasNext\",{get:function(){var t=this._stack;if(0===t.length)return!1;if(t[t.length-1].right)return!0;for(var e=t.length-1;e>0;--e)if(t[e-1].left===t[e])return!0;return!1}}),f.update=function(t){var r=this._stack;if(0===r.length)throw new Error(\"Can't update empty node!\");var n=new Array(r.length),i=r[r.length-1];n[n.length-1]=new e(i._color,i.key,t,i.left,i.right,i._count);for(var o=r.length-2;o>=0;--o)(i=r[o]).left===r[o+1]?n[o]=new e(i._color,i.key,i.value,n[o+1],i.right,i._count):n[o]=new e(i._color,i.key,i.value,i.left,n[o+1],i._count);return new a(this.tree._compare,n[0])},f.prev=function(){var t=this._stack;if(0!==t.length){var e=t[t.length-1];if(e.left)for(e=e.left;e;)t.push(e),e=e.right;else for(t.pop();t.length>0&&t[t.length-1].left===e;)e=t[t.length-1],t.pop()}},Object.defineProperty(f,\"hasPrev\",{get:function(){var t=this._stack;if(0===t.length)return!1;if(t[t.length-1].left)return!0;for(var e=t.length-1;e>0;--e)if(t[e-1].right===t[e])return!0;return!1}})},7453:function(t,e,r){\"use strict\";t.exports=function(t,e){var r=new c(t);return r.update(e),r};var n=r(9557),i=r(1681),a=r(1011),o=r(2864),s=r(8468),l=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]);function u(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function c(t){this.gl=t,this.pixelRatio=1,this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.autoTicks=!0,this.tickSpacing=[1,1,1],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickAlign=[\"auto\",\"auto\",\"auto\"],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[10,10,10],this.lastCubeProps={cubeEdges:[0,0,0],axis:[0,0,0]},this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=\"sans-serif\",this.labelSize=[20,20,20],this.labelAngle=[0,0,0],this.labelAlign=[\"auto\",\"auto\",\"auto\"],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[10,10,10],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[0,0,0],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!1,!1,!1],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._firstInit=!0,this._text=null,this._lines=null,this._background=a(t)}var f=c.prototype;function h(){this.primalOffset=[0,0,0],this.primalMinor=[0,0,0],this.mirrorOffset=[0,0,0],this.mirrorMinor=[0,0,0]}f.update=function(t){function e(e,r,n){if(n in t){var i,a=t[n],o=this[n];(e?Array.isArray(a)&&Array.isArray(a[0]):Array.isArray(a))?this[n]=i=[r(a[0]),r(a[1]),r(a[2])]:this[n]=i=[r(a),r(a),r(a)];for(var s=0;s<3;++s)if(i[s]!==o[s])return!0}return!1}t=t||{};var r,a=e.bind(this,!1,Number),o=e.bind(this,!1,Boolean),l=e.bind(this,!1,String),u=e.bind(this,!0,(function(t){if(Array.isArray(t)){if(3===t.length)return[+t[0],+t[1],+t[2],1];if(4===t.length)return[+t[0],+t[1],+t[2],+t[3]]}return[0,0,0,1]})),c=!1,f=!1;if(\"bounds\"in t)for(var h=t.bounds,p=0;p<2;++p)for(var d=0;d<3;++d)h[p][d]!==this.bounds[p][d]&&(f=!0),this.bounds[p][d]=h[p][d];if(\"ticks\"in t)for(r=t.ticks,c=!0,this.autoTicks=!1,p=0;p<3;++p)this.tickSpacing[p]=0;else a(\"tickSpacing\")&&(this.autoTicks=!0,f=!0);if(this._firstInit&&(\"ticks\"in t||\"tickSpacing\"in t||(this.autoTicks=!0),f=!0,c=!0,this._firstInit=!1),f&&this.autoTicks&&(r=s.create(this.bounds,this.tickSpacing),c=!0),c){for(p=0;p<3;++p)r[p].sort((function(t,e){return t.x-e.x}));s.equal(r,this.ticks)?c=!1:this.ticks=r}o(\"tickEnable\"),l(\"tickFont\")&&(c=!0),a(\"tickSize\"),a(\"tickAngle\"),a(\"tickPad\"),u(\"tickColor\");var v=l(\"labels\");l(\"labelFont\")&&(v=!0),o(\"labelEnable\"),a(\"labelSize\"),a(\"labelPad\"),u(\"labelColor\"),o(\"lineEnable\"),o(\"lineMirror\"),a(\"lineWidth\"),u(\"lineColor\"),o(\"lineTickEnable\"),o(\"lineTickMirror\"),a(\"lineTickLength\"),a(\"lineTickWidth\"),u(\"lineTickColor\"),o(\"gridEnable\"),a(\"gridWidth\"),u(\"gridColor\"),o(\"zeroEnable\"),u(\"zeroLineColor\"),a(\"zeroLineWidth\"),o(\"backgroundEnable\"),u(\"backgroundColor\"),this._text?this._text&&(v||c)&&this._text.update(this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont):this._text=n(this.gl,this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont),this._lines&&c&&(this._lines.dispose(),this._lines=null),this._lines||(this._lines=i(this.gl,this.bounds,this.ticks))};var p=[new h,new h,new h];function d(t,e,r,n,i){for(var a=t.primalOffset,o=t.primalMinor,s=t.mirrorOffset,l=t.mirrorMinor,u=n[e],c=0;c<3;++c)if(e!==c){var f=a,h=s,p=o,d=l;u&1<<c&&(f=s,h=a,p=l,d=o),f[c]=r[0][c],h[c]=r[1][c],i[c]>0?(p[c]=-1,d[c]=0):(p[c]=0,d[c]=1)}}var v=[0,0,0],g={model:l,view:l,projection:l,_ortho:!1};f.isOpaque=function(){return!0},f.isTransparent=function(){return!1},f.drawTransparent=function(t){};var y=[0,0,0],m=[0,0,0],x=[0,0,0];f.draw=function(t){t=t||g;for(var e=this.gl,r=t.model||l,n=t.view||l,i=t.projection||l,a=this.bounds,s=t._ortho||!1,c=o(r,n,i,a,s),f=c.cubeEdges,h=c.axis,b=n[12],_=n[13],w=n[14],T=n[15],k=(s?2:1)*this.pixelRatio*(i[3]*b+i[7]*_+i[11]*w+i[15]*T)/e.drawingBufferHeight,A=0;A<3;++A)this.lastCubeProps.cubeEdges[A]=f[A],this.lastCubeProps.axis[A]=h[A];var M=p;for(A=0;A<3;++A)d(p[A],A,this.bounds,f,h);e=this.gl;var S,E,L,C=v;for(A=0;A<3;++A)this.backgroundEnable[A]?C[A]=h[A]:C[A]=0;for(this._background.draw(r,n,i,a,C,this.backgroundColor),this._lines.bind(r,n,i,this),A=0;A<3;++A){var P=[0,0,0];h[A]>0?P[A]=a[1][A]:P[A]=a[0][A];for(var O=0;O<2;++O){var I=(A+1+O)%3,D=(A+1+(1^O))%3;this.gridEnable[I]&&this._lines.drawGrid(I,D,this.bounds,P,this.gridColor[I],this.gridWidth[I]*this.pixelRatio)}for(O=0;O<2;++O)I=(A+1+O)%3,D=(A+1+(1^O))%3,this.zeroEnable[D]&&Math.min(a[0][D],a[1][D])<=0&&Math.max(a[0][D],a[1][D])>=0&&this._lines.drawZero(I,D,this.bounds,P,this.zeroLineColor[D],this.zeroLineWidth[D]*this.pixelRatio)}for(A=0;A<3;++A){this.lineEnable[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].primalOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio),this.lineMirror[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].mirrorOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio);var z=u(y,M[A].primalMinor),R=u(m,M[A].mirrorMinor),F=this.lineTickLength;for(O=0;O<3;++O){var B=k/r[5*O];z[O]*=F[O]*B,R[O]*=F[O]*B}this.lineTickEnable[A]&&this._lines.drawAxisTicks(A,M[A].primalOffset,z,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio),this.lineTickMirror[A]&&this._lines.drawAxisTicks(A,M[A].mirrorOffset,R,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio)}function N(t){(L=[0,0,0])[t]=1}function j(t,e,r){var n=(t+1)%3,i=(t+2)%3,a=e[n],o=e[i],s=r[n],l=r[i];a>0&&l>0||a>0&&l<0||a<0&&l>0||a<0&&l<0?N(n):(o>0&&s>0||o>0&&s<0||o<0&&s>0||o<0&&s<0)&&N(i)}for(this._lines.unbind(),this._text.bind(r,n,i,this.pixelRatio),A=0;A<3;++A){var U=M[A].primalMinor,V=M[A].mirrorMinor,q=u(x,M[A].primalOffset);for(O=0;O<3;++O)this.lineTickEnable[A]&&(q[O]+=k*U[O]*Math.max(this.lineTickLength[O],0)/r[5*O]);var H=[0,0,0];if(H[A]=1,this.tickEnable[A]){for(-3600===this.tickAngle[A]?(this.tickAngle[A]=0,this.tickAlign[A]=\"auto\"):this.tickAlign[A]=-1,E=1,\"auto\"===(S=[this.tickAlign[A],.5,E])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]),L=[0,0,0],j(A,U,V),O=0;O<3;++O)q[O]+=k*U[O]*this.tickPad[O]/r[5*O];this._text.drawTicks(A,this.tickSize[A],this.tickAngle[A],q,this.tickColor[A],H,L,S)}if(this.labelEnable[A]){for(E=0,L=[0,0,0],this.labels[A].length>4&&(N(A),E=1),\"auto\"===(S=[this.labelAlign[A],.5,E])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]),O=0;O<3;++O)q[O]+=k*U[O]*this.labelPad[O]/r[5*O];q[A]+=.5*(a[0][A]+a[1][A]),this._text.drawLabel(A,this.labelSize[A],this.labelAngle[A],q,this.labelColor[A],[0,0,0],L,S)}}this._text.unbind()},f.dispose=function(){this._text.dispose(),this._lines.dispose(),this._background.dispose(),this._lines=null,this._text=null,this._background=null,this.gl=null}},1011:function(t,e,r){\"use strict\";t.exports=function(t){for(var e=[],r=[],s=0,l=0;l<3;++l)for(var u=(l+1)%3,c=(l+2)%3,f=[0,0,0],h=[0,0,0],p=-1;p<=1;p+=2){r.push(s,s+2,s+1,s+1,s+2,s+3),f[l]=p,h[l]=p;for(var d=-1;d<=1;d+=2){f[u]=d;for(var v=-1;v<=1;v+=2)f[c]=v,e.push(f[0],f[1],f[2],h[0],h[1],h[2]),s+=1}var g=u;u=c,c=g}var y=n(t,new Float32Array(e)),m=n(t,new Uint16Array(r),t.ELEMENT_ARRAY_BUFFER),x=i(t,[{buffer:y,type:t.FLOAT,size:3,offset:0,stride:24},{buffer:y,type:t.FLOAT,size:3,offset:12,stride:24}],m),b=a(t);return b.attributes.position.location=0,b.attributes.normal.location=1,new o(t,y,x,b)};var n=r(5827),i=r(2944),a=r(1943).bg;function o(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n}var s=o.prototype;s.draw=function(t,e,r,n,i,a){for(var o=!1,s=0;s<3;++s)o=o||i[s];if(o){var l=this.gl;l.enable(l.POLYGON_OFFSET_FILL),l.polygonOffset(1,2),this.shader.bind(),this.shader.uniforms={model:t,view:e,projection:r,bounds:n,enable:i,colors:a},this.vao.bind(),this.vao.draw(this.gl.TRIANGLES,36),this.vao.unbind(),l.disable(l.POLYGON_OFFSET_FILL)}},s.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},2864:function(t,e,r){\"use strict\";t.exports=function(t,e,r,a,p){i(s,e,t),i(s,r,s);for(var m=0,x=0;x<2;++x){c[2]=a[x][2];for(var b=0;b<2;++b){c[1]=a[b][1];for(var _=0;_<2;++_)c[0]=a[_][0],h(l[m],c,s),m+=1}}var w=-1;for(x=0;x<8;++x){for(var T=l[x][3],k=0;k<3;++k)u[x][k]=l[x][k]/T;p&&(u[x][2]*=-1),T<0&&(w<0||u[x][2]<u[w][2])&&(w=x)}if(w<0){w=0;for(var A=0;A<3;++A){for(var M=(A+2)%3,S=(A+1)%3,E=-1,L=-1,C=0;C<2;++C){var P=(I=C<<A)+(C<<M)+(1-C<<S),O=I+(1-C<<M)+(C<<S);o(u[I],u[P],u[O],f)<0||(C?E=1:L=1)}if(E<0||L<0)L>E&&(w|=1<<A);else{for(C=0;C<2;++C){P=(I=C<<A)+(C<<M)+(1-C<<S),O=I+(1-C<<M)+(C<<S);var I,D=d([l[I],l[P],l[O],l[I+(1<<M)+(1<<S)]]);C?E=D:L=D}L>E&&(w|=1<<A)}}}var z=7^w,R=-1;for(x=0;x<8;++x)x!==w&&x!==z&&(R<0||u[R][1]>u[x][1])&&(R=x);var F=-1;for(x=0;x<3;++x)(N=R^1<<x)!==w&&N!==z&&(F<0&&(F=N),(S=u[N])[0]<u[F][0]&&(F=N));var B=-1;for(x=0;x<3;++x){var N;(N=R^1<<x)!==w&&N!==z&&N!==F&&(B<0&&(B=N),(S=u[N])[0]>u[B][0]&&(B=N))}var j=v;j[0]=j[1]=j[2]=0,j[n.log2(F^R)]=R&F,j[n.log2(R^B)]=R&B;var U=7^B;U===w||U===z?(U=7^F,j[n.log2(B^U)]=U&B):j[n.log2(F^U)]=U&F;var V=g,q=w;for(A=0;A<3;++A)V[A]=q&1<<A?-1:1;return y};var n=r(2288),i=r(104),a=r(4670),o=r(417),s=new Array(16),l=new Array(8),u=new Array(8),c=new Array(3),f=[0,0,0];function h(t,e,r){for(var n=0;n<4;++n){t[n]=r[12+n];for(var i=0;i<3;++i)t[n]+=e[i]*r[4*i+n]}}!function(){for(var t=0;t<8;++t)l[t]=[1,1,1,1],u[t]=[1,1,1]}();var p=[[0,0,1,0,0],[0,0,-1,1,0],[0,-1,0,1,0],[0,1,0,1,0],[-1,0,0,1,0],[1,0,0,1,0]];function d(t){for(var e=0;e<p.length;++e)if((t=a.positive(t,p[e])).length<3)return 0;var r=t[0],n=r[0]/r[3],i=r[1]/r[3],o=0;for(e=1;e+1<t.length;++e){var s=t[e],l=t[e+1],u=s[0]/s[3]-n,c=s[1]/s[3]-i,f=l[0]/l[3]-n,h=l[1]/l[3]-i;o+=Math.abs(u*h-c*f)}return o}var v=[1,1,1],g=[0,0,0],y={cubeEdges:v,axis:g}},1681:function(t,e,r){\"use strict\";t.exports=function(t,e,r){var o=[],s=[0,0,0],l=[0,0,0],u=[0,0,0],c=[0,0,0];o.push(0,0,1,0,1,1,0,0,-1,0,0,-1,0,1,1,0,1,-1);for(var f=0;f<3;++f){for(var h=o.length/3|0,d=0;d<r[f].length;++d){var v=+r[f][d].x;o.push(v,0,1,v,1,1,v,0,-1,v,0,-1,v,1,1,v,1,-1)}var g=o.length/3|0;s[f]=h,l[f]=g-h,h=o.length/3|0;for(var y=0;y<r[f].length;++y)v=+r[f][y].x,o.push(v,0,1,v,1,1,v,0,-1,v,0,-1,v,1,1,v,1,-1);g=o.length/3|0,u[f]=h,c[f]=g-h}var m=n(t,new Float32Array(o)),x=i(t,[{buffer:m,type:t.FLOAT,size:3,stride:0,offset:0}]),b=a(t);return b.attributes.position.location=0,new p(t,m,x,b,l,s,c,u)};var n=r(5827),i=r(2944),a=r(1943).j,o=[0,0,0],s=[0,0,0],l=[0,0,0],u=[0,0,0],c=[1,1];function f(t){return t[0]=t[1]=t[2]=0,t}function h(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function p(t,e,r,n,i,a,o,s){this.gl=t,this.vertBuffer=e,this.vao=r,this.shader=n,this.tickCount=i,this.tickOffset=a,this.gridCount=o,this.gridOffset=s}var d=p.prototype;d.bind=function(t,e,r){this.shader.bind(),this.shader.uniforms.model=t,this.shader.uniforms.view=e,this.shader.uniforms.projection=r,c[0]=this.gl.drawingBufferWidth,c[1]=this.gl.drawingBufferHeight,this.shader.uniforms.screenShape=c,this.vao.bind()},d.unbind=function(){this.vao.unbind()},d.drawAxisLine=function(t,e,r,n,i){var a=f(s);this.shader.uniforms.majorAxis=s,a[t]=e[1][t]-e[0][t],this.shader.uniforms.minorAxis=a;var o,c=h(u,r);c[t]+=e[0][t],this.shader.uniforms.offset=c,this.shader.uniforms.lineWidth=i,this.shader.uniforms.color=n,(o=f(l))[(t+2)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6),(o=f(l))[(t+1)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6)},d.drawAxisTicks=function(t,e,r,n,i){if(this.tickCount[t]){var a=f(o);a[t]=1,this.shader.uniforms.majorAxis=a,this.shader.uniforms.offset=e,this.shader.uniforms.minorAxis=r,this.shader.uniforms.color=n,this.shader.uniforms.lineWidth=i;var s=f(l);s[t]=1,this.shader.uniforms.screenAxis=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t])}},d.drawGrid=function(t,e,r,n,i,a){if(this.gridCount[t]){var c=f(s);c[e]=r[1][e]-r[0][e],this.shader.uniforms.minorAxis=c;var p=h(u,n);p[e]+=r[0][e],this.shader.uniforms.offset=p;var d=f(o);d[t]=1,this.shader.uniforms.majorAxis=d;var v=f(l);v[t]=1,this.shader.uniforms.screenAxis=v,this.shader.uniforms.lineWidth=a,this.shader.uniforms.color=i,this.vao.draw(this.gl.TRIANGLES,this.gridCount[t],this.gridOffset[t])}},d.drawZero=function(t,e,r,n,i,a){var o=f(s);this.shader.uniforms.majorAxis=o,o[t]=r[1][t]-r[0][t],this.shader.uniforms.minorAxis=o;var c=h(u,n);c[t]+=r[0][t],this.shader.uniforms.offset=c;var p=f(l);p[e]=1,this.shader.uniforms.screenAxis=p,this.shader.uniforms.lineWidth=a,this.shader.uniforms.color=i,this.vao.draw(this.gl.TRIANGLES,6)},d.dispose=function(){this.vao.dispose(),this.vertBuffer.dispose(),this.shader.dispose()}},1943:function(t,e,r){\"use strict\";var n=r(6832),i=r(5158),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, majorAxis, minorAxis, screenAxis;\\nuniform float lineWidth;\\nuniform vec2 screenShape;\\n\\nvec3 project(vec3 p) {\\n  vec4 pp = projection * view * model * vec4(p, 1.0);\\n  return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nvoid main() {\\n  vec3 major = position.x * majorAxis;\\n  vec3 minor = position.y * minorAxis;\\n\\n  vec3 vPosition = major + minor + offset;\\n  vec3 pPosition = project(vPosition);\\n  vec3 offset = project(vPosition + screenAxis * position.z);\\n\\n  vec2 screen = normalize((offset - pPosition).xy * screenShape) / screenShape;\\n\\n  gl_Position = vec4(pPosition + vec3(0.5 * screen * lineWidth, 0), 1.0);\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = color;\\n}\"]);e.j=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec3\"}])};var s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, axis, alignDir, alignOpt;\\nuniform float scale, angle, pixelScale;\\nuniform vec2 resolution;\\n\\nvec3 project(vec3 p) {\\n  vec4 pp = projection * view * model * vec4(p, 1.0);\\n  return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nfloat computeViewAngle(vec3 a, vec3 b) {\\n  vec3 A = project(a);\\n  vec3 B = project(b);\\n\\n  return atan(\\n    (B.y - A.y) * resolution.y,\\n    (B.x - A.x) * resolution.x\\n  );\\n}\\n\\nconst float PI = 3.141592;\\nconst float TWO_PI = 2.0 * PI;\\nconst float HALF_PI = 0.5 * PI;\\nconst float ONE_AND_HALF_PI = 1.5 * PI;\\n\\nint option = int(floor(alignOpt.x + 0.001));\\nfloat hv_ratio =       alignOpt.y;\\nbool enableAlign =    (alignOpt.z != 0.0);\\n\\nfloat mod_angle(float a) {\\n  return mod(a, PI);\\n}\\n\\nfloat positive_angle(float a) {\\n  return mod_angle((a < 0.0) ?\\n    a + TWO_PI :\\n    a\\n  );\\n}\\n\\nfloat look_upwards(float a) {\\n  float b = positive_angle(a);\\n  return ((b > HALF_PI) && (b <= ONE_AND_HALF_PI)) ?\\n    b - PI :\\n    b;\\n}\\n\\nfloat look_horizontal_or_vertical(float a, float ratio) {\\n  // ratio controls the ratio between being horizontal to (vertical + horizontal)\\n  // if ratio is set to 0.5 then it is 50%, 50%.\\n  // when using a higher ratio e.g. 0.75 the result would\\n  // likely be more horizontal than vertical.\\n\\n  float b = positive_angle(a);\\n\\n  return\\n    (b < (      ratio) * HALF_PI) ? 0.0 :\\n    (b < (2.0 - ratio) * HALF_PI) ? -HALF_PI :\\n    (b < (2.0 + ratio) * HALF_PI) ? 0.0 :\\n    (b < (4.0 - ratio) * HALF_PI) ? HALF_PI :\\n                                    0.0;\\n}\\n\\nfloat roundTo(float a, float b) {\\n  return float(b * floor((a + 0.5 * b) / b));\\n}\\n\\nfloat look_round_n_directions(float a, int n) {\\n  float b = positive_angle(a);\\n  float div = TWO_PI / float(n);\\n  float c = roundTo(b, div);\\n  return look_upwards(c);\\n}\\n\\nfloat applyAlignOption(float rawAngle, float delta) {\\n  return\\n    (option >  2) ? look_round_n_directions(rawAngle + delta, option) :       // option 3-n: round to n directions\\n    (option == 2) ? look_horizontal_or_vertical(rawAngle + delta, hv_ratio) : // horizontal or vertical\\n    (option == 1) ? rawAngle + delta :       // use free angle, and flip to align with one direction of the axis\\n    (option == 0) ? look_upwards(rawAngle) : // use free angle, and stay upwards\\n    (option ==-1) ? 0.0 :                    // useful for backward compatibility, all texts remains horizontal\\n                    rawAngle;                // otherwise return back raw input angle\\n}\\n\\nbool isAxisTitle = (axis.x == 0.0) &&\\n                   (axis.y == 0.0) &&\\n                   (axis.z == 0.0);\\n\\nvoid main() {\\n  //Compute world offset\\n  float axisDistance = position.z;\\n  vec3 dataPosition = axisDistance * axis + offset;\\n\\n  float beta = angle; // i.e. user defined attributes for each tick\\n\\n  float axisAngle;\\n  float clipAngle;\\n  float flip;\\n\\n  if (enableAlign) {\\n    axisAngle = (isAxisTitle) ? HALF_PI :\\n                      computeViewAngle(dataPosition, dataPosition + axis);\\n    clipAngle = computeViewAngle(dataPosition, dataPosition + alignDir);\\n\\n    axisAngle += (sin(axisAngle) < 0.0) ? PI : 0.0;\\n    clipAngle += (sin(clipAngle) < 0.0) ? PI : 0.0;\\n\\n    flip = (dot(vec2(cos(axisAngle), sin(axisAngle)),\\n                vec2(sin(clipAngle),-cos(clipAngle))) > 0.0) ? 1.0 : 0.0;\\n\\n    beta += applyAlignOption(clipAngle, flip * PI);\\n  }\\n\\n  //Compute plane offset\\n  vec2 planeCoord = position.xy * pixelScale;\\n\\n  mat2 planeXform = scale * mat2(\\n     cos(beta), sin(beta),\\n    -sin(beta), cos(beta)\\n  );\\n\\n  vec2 viewOffset = 2.0 * planeXform * planeCoord / resolution;\\n\\n  //Compute clip position\\n  vec3 clipPosition = project(dataPosition);\\n\\n  //Apply text offset in clip coordinates\\n  clipPosition += vec3(viewOffset, 0.0);\\n\\n  //Done\\n  gl_Position = vec4(clipPosition, 1.0);\\n}\"]),l=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = color;\\n}\"]);e.f=function(t){return i(t,s,l,null,[{name:\"position\",type:\"vec3\"}])};var u=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec3 normal;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 enable;\\nuniform vec3 bounds[2];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n\\n  vec3 signAxis = sign(bounds[1] - bounds[0]);\\n\\n  vec3 realNormal = signAxis * normal;\\n\\n  if(dot(realNormal, enable) > 0.0) {\\n    vec3 minRange = min(bounds[0], bounds[1]);\\n    vec3 maxRange = max(bounds[0], bounds[1]);\\n    vec3 nPosition = mix(minRange, maxRange, 0.5 * (position + 1.0));\\n    gl_Position = projection * view * model * vec4(nPosition, 1.0);\\n  } else {\\n    gl_Position = vec4(0,0,0,0);\\n  }\\n\\n  colorChannel = abs(realNormal);\\n}\"]),c=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 colors[3];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n  gl_FragColor = colorChannel.x * colors[0] +\\n                 colorChannel.y * colors[1] +\\n                 colorChannel.z * colors[2];\\n}\"]);e.bg=function(t){return i(t,u,c,null,[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}])}},9557:function(t,e,r){\"use strict\";t.exports=function(t,e,r,i,o,l){var u=n(t),f=a(t,[{buffer:u,size:3}]),h=s(t);h.attributes.position.location=0;var p=new c(t,h,u,f);return p.update(e,r,i,o,l),p};var n=r(5827),a=r(2944),o=r(875),s=r(1943).f,l=window||i.global||{},u=l.__TEXT_CACHE||{};function c(t,e,r,n){this.gl=t,this.shader=e,this.buffer=r,this.vao=n,this.tickOffset=this.tickCount=this.labelOffset=this.labelCount=null}l.__TEXT_CACHE={};var f=c.prototype,h=[0,0];f.bind=function(t,e,r,n){this.vao.bind(),this.shader.bind();var i=this.shader.uniforms;i.model=t,i.view=e,i.projection=r,i.pixelScale=n,h[0]=this.gl.drawingBufferWidth,h[1]=this.gl.drawingBufferHeight,this.shader.uniforms.resolution=h},f.unbind=function(){this.vao.unbind()},f.update=function(t,e,r,n,i){var a=[];function s(t,e,r,n,i,s){var l=u[r];l||(l=u[r]={});var c=l[e];c||(c=l[e]=function(t,e){try{return o(t,e)}catch(e){return console.warn('error vectorizing text:\"'+t+'\" error:',e),{cells:[],positions:[]}}}(e,{triangles:!0,font:r,textAlign:\"center\",textBaseline:\"middle\",lineSpacing:i,styletags:s}));for(var f=(n||12)/12,h=c.positions,p=c.cells,d=0,v=p.length;d<v;++d)for(var g=p[d],y=2;y>=0;--y){var m=h[g[y]];a.push(f*m[0],-f*m[1],t)}}for(var l=[0,0,0],c=[0,0,0],f=[0,0,0],h=[0,0,0],p={breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0},d=0;d<3;++d){f[d]=a.length/3|0,s(.5*(t[0][d]+t[1][d]),e[d],r[d],12,1.25,p),h[d]=(a.length/3|0)-f[d],l[d]=a.length/3|0;for(var v=0;v<n[d].length;++v)n[d][v].text&&s(n[d][v].x,n[d][v].text,n[d][v].font||i,n[d][v].fontSize||12,1.25,p);c[d]=(a.length/3|0)-l[d]}this.buffer.update(a),this.tickOffset=l,this.tickCount=c,this.labelOffset=f,this.labelCount=h},f.drawTicks=function(t,e,r,n,i,a,o,s){this.tickCount[t]&&(this.shader.uniforms.axis=a,this.shader.uniforms.color=i,this.shader.uniforms.angle=r,this.shader.uniforms.scale=e,this.shader.uniforms.offset=n,this.shader.uniforms.alignDir=o,this.shader.uniforms.alignOpt=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t]))},f.drawLabel=function(t,e,r,n,i,a,o,s){this.labelCount[t]&&(this.shader.uniforms.axis=a,this.shader.uniforms.color=i,this.shader.uniforms.angle=r,this.shader.uniforms.scale=e,this.shader.uniforms.offset=n,this.shader.uniforms.alignDir=o,this.shader.uniforms.alignOpt=s,this.vao.draw(this.gl.TRIANGLES,this.labelCount[t],this.labelOffset[t]))},f.dispose=function(){this.shader.dispose(),this.vao.dispose(),this.buffer.dispose()}},8468:function(t,e){\"use strict\";function r(t,e){var r=t+\"\",n=r.indexOf(\".\"),i=0;n>=0&&(i=r.length-n-1);var a=Math.pow(10,i),o=Math.round(t*e*a),s=o+\"\";if(s.indexOf(\"e\")>=0)return s;var l=o/a,u=o%a;o<0?(l=0|-Math.ceil(l),u=0|-u):(l=0|Math.floor(l),u|=0);var c=\"\"+l;if(o<0&&(c=\"-\"+c),i){for(var f=\"\"+u;f.length<i;)f=\"0\"+f;return c+\".\"+f}return c}e.create=function(t,e){for(var n=[],i=0;i<3;++i){for(var a=[],o=(t[0][i],t[1][i],0);o*e[i]<=t[1][i];++o)a.push({x:o*e[i],text:r(e[i],o)});for(o=-1;o*e[i]>=t[0][i];--o)a.push({x:o*e[i],text:r(e[i],o)});n.push(a)}return n},e.equal=function(t,e){for(var r=0;r<3;++r){if(t[r].length!==e[r].length)return!1;for(var n=0;n<t[r].length;++n){var i=t[r][n],a=e[r][n];if(i.x!==a.x||i.text!==a.text||i.font!==a.font||i.fontColor!==a.fontColor||i.fontSize!==a.fontSize||i.dx!==a.dx||i.dy!==a.dy)return!1}}return!0}},2771:function(t,e,r){\"use strict\";t.exports=function(t,e,r,l,f){var h=e.model||u,p=e.view||u,y=e.projection||u,m=e._ortho||!1,x=t.bounds,b=(f=f||a(h,p,y,x,m)).axis;o(c,p,h),o(c,y,c);for(var _=v,w=0;w<3;++w)_[w].lo=1/0,_[w].hi=-1/0,_[w].pixelsPerDataUnit=1/0;var T=n(s(c,c));s(c,c);for(var k=0;k<3;++k){var A=(k+1)%3,M=(k+2)%3,S=g;t:for(w=0;w<2;++w){var E=[];if(b[k]<0!=!!w){S[k]=x[w][k];for(var L=0;L<2;++L){S[A]=x[L^w][A];for(var C=0;C<2;++C)S[M]=x[C^L^w][M],E.push(S.slice())}var P=m?5:4;for(L=P;L===P;++L){if(0===E.length)continue t;E=i.positive(E,T[L])}for(L=0;L<E.length;++L){M=E[L];var O=d(g,c,M,r,l);for(C=0;C<3;++C)_[C].lo=Math.min(_[C].lo,M[C]),_[C].hi=Math.max(_[C].hi,M[C]),C!==k&&(_[C].pixelsPerDataUnit=Math.min(_[C].pixelsPerDataUnit,Math.abs(O[C])))}}}}return _};var n=r(5795),i=r(4670),a=r(2864),o=r(104),s=r(2142),l=r(6342),u=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]),c=new Float32Array(16);function f(t,e,r){this.lo=t,this.hi=e,this.pixelsPerDataUnit=r}var h=[0,0,0,1],p=[0,0,0,1];function d(t,e,r,n,i){for(var a=0;a<3;++a){for(var o=h,s=p,u=0;u<3;++u)s[u]=o[u]=r[u];s[3]=o[3]=1,s[a]+=1,l(s,s,e),s[3]<0&&(t[a]=1/0),o[a]-=1,l(o,o,e),o[3]<0&&(t[a]=1/0);var c=(o[0]/o[3]-s[0]/s[3])*n,f=(o[1]/o[3]-s[1]/s[3])*i;t[a]=.25*Math.sqrt(c*c+f*f)}return t}var v=[new f(1/0,-1/0,1/0),new f(1/0,-1/0,1/0),new f(1/0,-1/0,1/0)],g=[0,0,0]},5827:function(t,e,r){\"use strict\";var n=r(5306),i=r(7498),a=r(5050),o=[\"uint8\",\"uint8_clamped\",\"uint16\",\"uint32\",\"int8\",\"int16\",\"int32\",\"float32\"];function s(t,e,r,n,i){this.gl=t,this.type=e,this.handle=r,this.length=n,this.usage=i}var l=s.prototype;function u(t,e,r,n,i,a){var o=i.length*i.BYTES_PER_ELEMENT;if(a<0)return t.bufferData(e,i,n),o;if(o+a>r)throw new Error(\"gl-buffer: If resizing buffer, must not specify offset\");return t.bufferSubData(e,a,i),r}function c(t,e){for(var r=n.malloc(t.length,e),i=t.length,a=0;a<i;++a)r[a]=t[a];return r}l.bind=function(){this.gl.bindBuffer(this.type,this.handle)},l.unbind=function(){this.gl.bindBuffer(this.type,null)},l.dispose=function(){this.gl.deleteBuffer(this.handle)},l.update=function(t,e){if(\"number\"!=typeof e&&(e=-1),this.bind(),\"object\"==typeof t&&void 0!==t.shape){var r=t.dtype;if(o.indexOf(r)<0&&(r=\"float32\"),this.type===this.gl.ELEMENT_ARRAY_BUFFER&&(r=gl.getExtension(\"OES_element_index_uint\")&&\"uint16\"!==r?\"uint32\":\"uint16\"),r===t.dtype&&function(t,e){for(var r=1,n=e.length-1;n>=0;--n){if(e[n]!==r)return!1;r*=t[n]}return!0}(t.shape,t.stride))0===t.offset&&t.data.length===t.shape[0]?this.length=u(this.gl,this.type,this.length,this.usage,t.data,e):this.length=u(this.gl,this.type,this.length,this.usage,t.data.subarray(t.offset,t.shape[0]),e);else{var s=n.malloc(t.size,r),l=a(s,t.shape);i.assign(l,t),this.length=u(this.gl,this.type,this.length,this.usage,e<0?s:s.subarray(0,t.size),e),n.free(s)}}else if(Array.isArray(t)){var f;f=this.type===this.gl.ELEMENT_ARRAY_BUFFER?c(t,\"uint16\"):c(t,\"float32\"),this.length=u(this.gl,this.type,this.length,this.usage,e<0?f:f.subarray(0,t.length),e),n.free(f)}else if(\"object\"==typeof t&&\"number\"==typeof t.length)this.length=u(this.gl,this.type,this.length,this.usage,t,e);else{if(\"number\"!=typeof t&&void 0!==t)throw new Error(\"gl-buffer: Invalid data type\");if(e>=0)throw new Error(\"gl-buffer: Cannot specify offset when resizing buffer\");(t|=0)<=0&&(t=1),this.gl.bufferData(this.type,0|t,this.usage),this.length=t}},t.exports=function(t,e,r,n){if(r=r||t.ARRAY_BUFFER,n=n||t.DYNAMIC_DRAW,r!==t.ARRAY_BUFFER&&r!==t.ELEMENT_ARRAY_BUFFER)throw new Error(\"gl-buffer: Invalid type for webgl buffer, must be either gl.ARRAY_BUFFER or gl.ELEMENT_ARRAY_BUFFER\");if(n!==t.DYNAMIC_DRAW&&n!==t.STATIC_DRAW&&n!==t.STREAM_DRAW)throw new Error(\"gl-buffer: Invalid usage for buffer, must be either gl.DYNAMIC_DRAW, gl.STATIC_DRAW or gl.STREAM_DRAW\");var i=t.createBuffer(),a=new s(t,r,i,0,n);return a.update(e),a}},1140:function(t,e,r){\"use strict\";var n=r(2858);t.exports=function(t,e){var r=t.positions,i=t.vectors,a={positions:[],vertexIntensity:[],vertexIntensityBounds:t.vertexIntensityBounds,vectors:[],cells:[],coneOffset:t.coneOffset,colormap:t.colormap};if(0===t.positions.length)return e&&(e[0]=[0,0,0],e[1]=[0,0,0]),a;for(var o=0,s=1/0,l=-1/0,u=1/0,c=-1/0,f=1/0,h=-1/0,p=null,d=null,v=[],g=1/0,y=!1,m=0;m<r.length;m++){var x=r[m];s=Math.min(x[0],s),l=Math.max(x[0],l),u=Math.min(x[1],u),c=Math.max(x[1],c),f=Math.min(x[2],f),h=Math.max(x[2],h);var b=i[m];if(n.length(b)>o&&(o=n.length(b)),m){var _=2*n.distance(p,x)/(n.length(d)+n.length(b));_?(g=Math.min(g,_),y=!1):y=!0}y||(p=x,d=b),v.push(b)}var w=[s,u,f],T=[l,c,h];e&&(e[0]=w,e[1]=T),0===o&&(o=1);var k=1/o;isFinite(g)||(g=1),a.vectorScale=g;var A=t.coneSize||.5;t.absoluteConeSize&&(A=t.absoluteConeSize*k),a.coneScale=A,m=0;for(var M=0;m<r.length;m++)for(var S=(x=r[m])[0],E=x[1],L=x[2],C=v[m],P=n.length(C)*k,O=0;O<8;O++){a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vertexIntensity.push(P,P,P),a.vertexIntensity.push(P,P,P);var I=a.positions.length;a.cells.push([I-6,I-5,I-4],[I-3,I-2,I-1])}return a};var i=r(7234);t.exports.createMesh=r(5028),t.exports.createConeMesh=function(e,r){return t.exports.createMesh(e,r,{shaders:i,traceType:\"cone\"})}},5028:function(t,e,r){\"use strict\";var n=r(5158),i=r(5827),a=r(2944),o=r(8931),s=r(104),l=r(7437),u=r(5050),c=r(9156),f=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function h(t,e,r,n,i,a,o,s,l,u,c){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.pickShader=n,this.trianglePositions=i,this.triangleVectors=a,this.triangleColors=s,this.triangleUVs=l,this.triangleIds=o,this.triangleVAO=u,this.triangleCount=0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.traceType=c,this.tubeScale=1,this.coneScale=2,this.vectorScale=1,this.coneOffset=.25,this._model=f,this._view=f,this._projection=f,this._resolution=[1,1]}var p=h.prototype;p.isOpaque=function(){return this.opacity>=1},p.isTransparent=function(){return this.opacity<1},p.pickSlots=1,p.setPickBase=function(t){this.pickId=t},p.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),\"opacity\"in t&&(this.opacity=t.opacity),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),void 0!==t.tubeScale&&(this.tubeScale=t.tubeScale),void 0!==t.vectorScale&&(this.vectorScale=t.vectorScale),void 0!==t.coneScale&&(this.coneScale=t.coneScale),void 0!==t.coneOffset&&(this.coneOffset=t.coneOffset),t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t){for(var e=c({colormap:t,nshades:256,format:\"rgba\"}),r=new Uint8Array(1024),n=0;n<256;++n){for(var i=e[n],a=0;a<3;++a)r[4*n+a]=i[a];r[4*n+3]=255*i[3]}return u(r,[256,256,4],[4,0,1])}(t.colormap)),this.texture.generateMipmap());var r=t.cells,n=t.positions,i=t.vectors;if(n&&r&&i){var a=[],o=[],s=[],l=[],f=[];this.cells=r,this.positions=n,this.vectors=i;var h=t.meshColor||[1,1,1,1],p=t.vertexIntensity,d=1/0,v=-1/0;if(p)if(t.vertexIntensityBounds)d=+t.vertexIntensityBounds[0],v=+t.vertexIntensityBounds[1];else for(var g=0;g<p.length;++g){var y=p[g];d=Math.min(d,y),v=Math.max(v,y)}else for(g=0;g<n.length;++g)y=n[g][2],d=Math.min(d,y),v=Math.max(v,y);for(this.intensity=p||function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n),this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],g=0;g<n.length;++g)for(var m=n[g],x=0;x<3;++x)!isNaN(m[x])&&isFinite(m[x])&&(this.bounds[0][x]=Math.min(this.bounds[0][x],m[x]),this.bounds[1][x]=Math.max(this.bounds[1][x],m[x]));var b=0;t:for(g=0;g<r.length;++g){var _=r[g];if(3===_.length){for(x=0;x<3;++x){m=n[T=_[x]];for(var w=0;w<3;++w)if(isNaN(m[w])||!isFinite(m[w]))continue t}for(x=0;x<3;++x){var T;m=n[T=_[2-x]],a.push(m[0],m[1],m[2],m[3]);var k=i[T];o.push(k[0],k[1],k[2],k[3]||0);var A,M=h;3===M.length?s.push(M[0],M[1],M[2],1):s.push(M[0],M[1],M[2],M[3]),A=p?[(p[T]-d)/(v-d),0]:[(m[2]-d)/(v-d),0],l.push(A[0],A[1]),f.push(g)}b+=1}}this.triangleCount=b,this.trianglePositions.update(a),this.triangleVectors.update(o),this.triangleColors.update(s),this.triangleUVs.update(l),this.triangleIds.update(new Uint32Array(f))}},p.drawTransparent=p.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||f,n=t.view||f,i=t.projection||f,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var u={model:r,view:n,projection:i,inverseModel:f.slice(),clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],opacity:this.opacity,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,texture:0};u.inverseModel=l(u.inverseModel,u.model),e.disable(e.CULL_FACE),this.texture.bind(0);var c=new Array(16);for(s(c,u.view,u.model),s(c,u.projection,c),l(c,c),o=0;o<3;++o)u.eyePosition[o]=c[12+o]/c[15];var h=c[15];for(o=0;o<3;++o)h+=this.lightPosition[o]*c[4*o+3];for(o=0;o<3;++o){for(var p=c[12+o],d=0;d<3;++d)p+=c[4*d+o]*this.lightPosition[d];u.lightPosition[o]=p/h}if(this.triangleCount>0){var v=this.triShader;v.bind(),v.uniforms=u,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()}},p.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||f,n=t.view||f,i=t.projection||f,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s={model:r,view:n,projection:i,clipBounds:a,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,pickId:this.pickId/255},l=this.pickShader;l.bind(),l.uniforms=s,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind())},p.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions[r[1]].slice(0,3),i={position:n,dataCoordinate:n,index:Math.floor(r[1]/48)};return\"cone\"===this.traceType?i.index=Math.floor(r[1]/48):\"streamtube\"===this.traceType&&(i.intensity=this.intensity[r[1]],i.velocity=this.vectors[r[1]].slice(0,3),i.divergence=this.vectors[r[1]][3],i.index=e),i},p.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.pickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleVectors.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleIds.dispose()},t.exports=function(t,e,r){var s=r.shaders;1===arguments.length&&(t=(e=t).gl);var l=function(t,e){var r=n(t,e.meshShader.vertex,e.meshShader.fragment,null,e.meshShader.attributes);return r.attributes.position.location=0,r.attributes.color.location=2,r.attributes.uv.location=3,r.attributes.vector.location=4,r}(t,s),c=function(t,e){var r=n(t,e.pickShader.vertex,e.pickShader.fragment,null,e.pickShader.attributes);return r.attributes.position.location=0,r.attributes.id.location=1,r.attributes.vector.location=4,r}(t,s),f=o(t,u(new Uint8Array([255,255,255,255]),[1,1,4]));f.generateMipmap(),f.minFilter=t.LINEAR_MIPMAP_LINEAR,f.magFilter=t.LINEAR;var p=i(t),d=i(t),v=i(t),g=i(t),y=i(t),m=new h(t,f,l,c,p,d,y,v,g,a(t,[{buffer:p,type:t.FLOAT,size:4},{buffer:y,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:v,type:t.FLOAT,size:4},{buffer:g,type:t.FLOAT,size:2},{buffer:d,type:t.FLOAT,size:4}]),r.traceType||\"cone\");return m.update(e),m}},7234:function(t,e,r){var n=r(6832),i=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n//   segment + 0 top vertex\\n//   segment + 1 perimeter vertex a+1\\n//   segment + 2 perimeter vertex a\\n//   segment + 3 center base vertex\\n//   segment + 4 perimeter vertex a\\n//   segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n  const float segmentCount = 8.0;\\n\\n  float index = rawIndex - floor(rawIndex /\\n    (segmentCount * 6.0)) *\\n    (segmentCount * 6.0);\\n\\n  float segment = floor(0.001 + index/6.0);\\n  float segmentIndex = index - (segment*6.0);\\n\\n  normal = -normalize(d);\\n\\n  if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n    return mix(vec3(0.0), -d, coneOffset);\\n  }\\n\\n  float nextAngle = (\\n    (segmentIndex > 0.99 &&  segmentIndex < 1.01) ||\\n    (segmentIndex > 4.99 &&  segmentIndex < 5.01)\\n  ) ? 1.0 : 0.0;\\n  float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n  vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n  vec3 v2 = v1 - d;\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d)*0.25;\\n  vec3 y = v * sin(angle) * length(d)*0.25;\\n  vec3 v3 = v2 + x + y;\\n  if (segmentIndex < 3.0) {\\n    vec3 tx = u * sin(angle);\\n    vec3 ty = v * -cos(angle);\\n    vec3 tangent = tx + ty;\\n    normal = normalize(cross(v3 - v1, tangent));\\n  }\\n\\n  if (segmentIndex == 0.0) {\\n    return mix(d, vec3(0.0), coneOffset);\\n  }\\n  return v3;\\n}\\n\\nattribute vec3 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\n\\nuniform float vectorScale, coneScale, coneOffset;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 eyePosition, lightPosition;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  // Scale the vector magnitude to stay constant with\\n  // model & view changes.\\n  vec3 normal;\\n  vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector), position.w, coneOffset, normal);\\n  vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * conePosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n  // vec4 m_position  = model * vec4(conePosition, 1.0);\\n  vec4 t_position  = view * conePosition;\\n  gl_Position      = projection * t_position;\\n\\n  f_color          = color;\\n  f_data           = conePosition.xyz;\\n  f_position       = position.xyz;\\n  f_uv             = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * opacity;\\n}\\n\"]),o=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n//   segment + 0 top vertex\\n//   segment + 1 perimeter vertex a+1\\n//   segment + 2 perimeter vertex a\\n//   segment + 3 center base vertex\\n//   segment + 4 perimeter vertex a\\n//   segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n  const float segmentCount = 8.0;\\n\\n  float index = rawIndex - floor(rawIndex /\\n    (segmentCount * 6.0)) *\\n    (segmentCount * 6.0);\\n\\n  float segment = floor(0.001 + index/6.0);\\n  float segmentIndex = index - (segment*6.0);\\n\\n  normal = -normalize(d);\\n\\n  if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n    return mix(vec3(0.0), -d, coneOffset);\\n  }\\n\\n  float nextAngle = (\\n    (segmentIndex > 0.99 &&  segmentIndex < 1.01) ||\\n    (segmentIndex > 4.99 &&  segmentIndex < 5.01)\\n  ) ? 1.0 : 0.0;\\n  float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n  vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n  vec3 v2 = v1 - d;\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d)*0.25;\\n  vec3 y = v * sin(angle) * length(d)*0.25;\\n  vec3 v3 = v2 + x + y;\\n  if (segmentIndex < 3.0) {\\n    vec3 tx = u * sin(angle);\\n    vec3 ty = v * -cos(angle);\\n    vec3 tangent = tx + ty;\\n    normal = normalize(cross(v3 - v1, tangent));\\n  }\\n\\n  if (segmentIndex == 0.0) {\\n    return mix(d, vec3(0.0), coneOffset);\\n  }\\n  return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform float vectorScale, coneScale, coneOffset;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  vec3 normal;\\n  vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector.xyz), position.w, coneOffset, normal);\\n  vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n  gl_Position = projection * view * conePosition;\\n  f_id        = id;\\n  f_position  = position.xyz;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]);e.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec4\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"vector\",type:\"vec3\"}]},e.pickShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec4\"},{name:\"id\",type:\"vec4\"},{name:\"vector\",type:\"vec3\"}]}},1950:function(t){t.exports={0:\"NONE\",1:\"ONE\",2:\"LINE_LOOP\",3:\"LINE_STRIP\",4:\"TRIANGLES\",5:\"TRIANGLE_STRIP\",6:\"TRIANGLE_FAN\",256:\"DEPTH_BUFFER_BIT\",512:\"NEVER\",513:\"LESS\",514:\"EQUAL\",515:\"LEQUAL\",516:\"GREATER\",517:\"NOTEQUAL\",518:\"GEQUAL\",519:\"ALWAYS\",768:\"SRC_COLOR\",769:\"ONE_MINUS_SRC_COLOR\",770:\"SRC_ALPHA\",771:\"ONE_MINUS_SRC_ALPHA\",772:\"DST_ALPHA\",773:\"ONE_MINUS_DST_ALPHA\",774:\"DST_COLOR\",775:\"ONE_MINUS_DST_COLOR\",776:\"SRC_ALPHA_SATURATE\",1024:\"STENCIL_BUFFER_BIT\",1028:\"FRONT\",1029:\"BACK\",1032:\"FRONT_AND_BACK\",1280:\"INVALID_ENUM\",1281:\"INVALID_VALUE\",1282:\"INVALID_OPERATION\",1285:\"OUT_OF_MEMORY\",1286:\"INVALID_FRAMEBUFFER_OPERATION\",2304:\"CW\",2305:\"CCW\",2849:\"LINE_WIDTH\",2884:\"CULL_FACE\",2885:\"CULL_FACE_MODE\",2886:\"FRONT_FACE\",2928:\"DEPTH_RANGE\",2929:\"DEPTH_TEST\",2930:\"DEPTH_WRITEMASK\",2931:\"DEPTH_CLEAR_VALUE\",2932:\"DEPTH_FUNC\",2960:\"STENCIL_TEST\",2961:\"STENCIL_CLEAR_VALUE\",2962:\"STENCIL_FUNC\",2963:\"STENCIL_VALUE_MASK\",2964:\"STENCIL_FAIL\",2965:\"STENCIL_PASS_DEPTH_FAIL\",2966:\"STENCIL_PASS_DEPTH_PASS\",2967:\"STENCIL_REF\",2968:\"STENCIL_WRITEMASK\",2978:\"VIEWPORT\",3024:\"DITHER\",3042:\"BLEND\",3088:\"SCISSOR_BOX\",3089:\"SCISSOR_TEST\",3106:\"COLOR_CLEAR_VALUE\",3107:\"COLOR_WRITEMASK\",3317:\"UNPACK_ALIGNMENT\",3333:\"PACK_ALIGNMENT\",3379:\"MAX_TEXTURE_SIZE\",3386:\"MAX_VIEWPORT_DIMS\",3408:\"SUBPIXEL_BITS\",3410:\"RED_BITS\",3411:\"GREEN_BITS\",3412:\"BLUE_BITS\",3413:\"ALPHA_BITS\",3414:\"DEPTH_BITS\",3415:\"STENCIL_BITS\",3553:\"TEXTURE_2D\",4352:\"DONT_CARE\",4353:\"FASTEST\",4354:\"NICEST\",5120:\"BYTE\",5121:\"UNSIGNED_BYTE\",5122:\"SHORT\",5123:\"UNSIGNED_SHORT\",5124:\"INT\",5125:\"UNSIGNED_INT\",5126:\"FLOAT\",5386:\"INVERT\",5890:\"TEXTURE\",6401:\"STENCIL_INDEX\",6402:\"DEPTH_COMPONENT\",6406:\"ALPHA\",6407:\"RGB\",6408:\"RGBA\",6409:\"LUMINANCE\",6410:\"LUMINANCE_ALPHA\",7680:\"KEEP\",7681:\"REPLACE\",7682:\"INCR\",7683:\"DECR\",7936:\"VENDOR\",7937:\"RENDERER\",7938:\"VERSION\",9728:\"NEAREST\",9729:\"LINEAR\",9984:\"NEAREST_MIPMAP_NEAREST\",9985:\"LINEAR_MIPMAP_NEAREST\",9986:\"NEAREST_MIPMAP_LINEAR\",9987:\"LINEAR_MIPMAP_LINEAR\",10240:\"TEXTURE_MAG_FILTER\",10241:\"TEXTURE_MIN_FILTER\",10242:\"TEXTURE_WRAP_S\",10243:\"TEXTURE_WRAP_T\",10497:\"REPEAT\",10752:\"POLYGON_OFFSET_UNITS\",16384:\"COLOR_BUFFER_BIT\",32769:\"CONSTANT_COLOR\",32770:\"ONE_MINUS_CONSTANT_COLOR\",32771:\"CONSTANT_ALPHA\",32772:\"ONE_MINUS_CONSTANT_ALPHA\",32773:\"BLEND_COLOR\",32774:\"FUNC_ADD\",32777:\"BLEND_EQUATION_RGB\",32778:\"FUNC_SUBTRACT\",32779:\"FUNC_REVERSE_SUBTRACT\",32819:\"UNSIGNED_SHORT_4_4_4_4\",32820:\"UNSIGNED_SHORT_5_5_5_1\",32823:\"POLYGON_OFFSET_FILL\",32824:\"POLYGON_OFFSET_FACTOR\",32854:\"RGBA4\",32855:\"RGB5_A1\",32873:\"TEXTURE_BINDING_2D\",32926:\"SAMPLE_ALPHA_TO_COVERAGE\",32928:\"SAMPLE_COVERAGE\",32936:\"SAMPLE_BUFFERS\",32937:\"SAMPLES\",32938:\"SAMPLE_COVERAGE_VALUE\",32939:\"SAMPLE_COVERAGE_INVERT\",32968:\"BLEND_DST_RGB\",32969:\"BLEND_SRC_RGB\",32970:\"BLEND_DST_ALPHA\",32971:\"BLEND_SRC_ALPHA\",33071:\"CLAMP_TO_EDGE\",33170:\"GENERATE_MIPMAP_HINT\",33189:\"DEPTH_COMPONENT16\",33306:\"DEPTH_STENCIL_ATTACHMENT\",33635:\"UNSIGNED_SHORT_5_6_5\",33648:\"MIRRORED_REPEAT\",33901:\"ALIASED_POINT_SIZE_RANGE\",33902:\"ALIASED_LINE_WIDTH_RANGE\",33984:\"TEXTURE0\",33985:\"TEXTURE1\",33986:\"TEXTURE2\",33987:\"TEXTURE3\",33988:\"TEXTURE4\",33989:\"TEXTURE5\",33990:\"TEXTURE6\",33991:\"TEXTURE7\",33992:\"TEXTURE8\",33993:\"TEXTURE9\",33994:\"TEXTURE10\",33995:\"TEXTURE11\",33996:\"TEXTURE12\",33997:\"TEXTURE13\",33998:\"TEXTURE14\",33999:\"TEXTURE15\",34e3:\"TEXTURE16\",34001:\"TEXTURE17\",34002:\"TEXTURE18\",34003:\"TEXTURE19\",34004:\"TEXTURE20\",34005:\"TEXTURE21\",34006:\"TEXTURE22\",34007:\"TEXTURE23\",34008:\"TEXTURE24\",34009:\"TEXTURE25\",34010:\"TEXTURE26\",34011:\"TEXTURE27\",34012:\"TEXTURE28\",34013:\"TEXTURE29\",34014:\"TEXTURE30\",34015:\"TEXTURE31\",34016:\"ACTIVE_TEXTURE\",34024:\"MAX_RENDERBUFFER_SIZE\",34041:\"DEPTH_STENCIL\",34055:\"INCR_WRAP\",34056:\"DECR_WRAP\",34067:\"TEXTURE_CUBE_MAP\",34068:\"TEXTURE_BINDING_CUBE_MAP\",34069:\"TEXTURE_CUBE_MAP_POSITIVE_X\",34070:\"TEXTURE_CUBE_MAP_NEGATIVE_X\",34071:\"TEXTURE_CUBE_MAP_POSITIVE_Y\",34072:\"TEXTURE_CUBE_MAP_NEGATIVE_Y\",34073:\"TEXTURE_CUBE_MAP_POSITIVE_Z\",34074:\"TEXTURE_CUBE_MAP_NEGATIVE_Z\",34076:\"MAX_CUBE_MAP_TEXTURE_SIZE\",34338:\"VERTEX_ATTRIB_ARRAY_ENABLED\",34339:\"VERTEX_ATTRIB_ARRAY_SIZE\",34340:\"VERTEX_ATTRIB_ARRAY_STRIDE\",34341:\"VERTEX_ATTRIB_ARRAY_TYPE\",34342:\"CURRENT_VERTEX_ATTRIB\",34373:\"VERTEX_ATTRIB_ARRAY_POINTER\",34466:\"NUM_COMPRESSED_TEXTURE_FORMATS\",34467:\"COMPRESSED_TEXTURE_FORMATS\",34660:\"BUFFER_SIZE\",34661:\"BUFFER_USAGE\",34816:\"STENCIL_BACK_FUNC\",34817:\"STENCIL_BACK_FAIL\",34818:\"STENCIL_BACK_PASS_DEPTH_FAIL\",34819:\"STENCIL_BACK_PASS_DEPTH_PASS\",34877:\"BLEND_EQUATION_ALPHA\",34921:\"MAX_VERTEX_ATTRIBS\",34922:\"VERTEX_ATTRIB_ARRAY_NORMALIZED\",34930:\"MAX_TEXTURE_IMAGE_UNITS\",34962:\"ARRAY_BUFFER\",34963:\"ELEMENT_ARRAY_BUFFER\",34964:\"ARRAY_BUFFER_BINDING\",34965:\"ELEMENT_ARRAY_BUFFER_BINDING\",34975:\"VERTEX_ATTRIB_ARRAY_BUFFER_BINDING\",35040:\"STREAM_DRAW\",35044:\"STATIC_DRAW\",35048:\"DYNAMIC_DRAW\",35632:\"FRAGMENT_SHADER\",35633:\"VERTEX_SHADER\",35660:\"MAX_VERTEX_TEXTURE_IMAGE_UNITS\",35661:\"MAX_COMBINED_TEXTURE_IMAGE_UNITS\",35663:\"SHADER_TYPE\",35664:\"FLOAT_VEC2\",35665:\"FLOAT_VEC3\",35666:\"FLOAT_VEC4\",35667:\"INT_VEC2\",35668:\"INT_VEC3\",35669:\"INT_VEC4\",35670:\"BOOL\",35671:\"BOOL_VEC2\",35672:\"BOOL_VEC3\",35673:\"BOOL_VEC4\",35674:\"FLOAT_MAT2\",35675:\"FLOAT_MAT3\",35676:\"FLOAT_MAT4\",35678:\"SAMPLER_2D\",35680:\"SAMPLER_CUBE\",35712:\"DELETE_STATUS\",35713:\"COMPILE_STATUS\",35714:\"LINK_STATUS\",35715:\"VALIDATE_STATUS\",35716:\"INFO_LOG_LENGTH\",35717:\"ATTACHED_SHADERS\",35718:\"ACTIVE_UNIFORMS\",35719:\"ACTIVE_UNIFORM_MAX_LENGTH\",35720:\"SHADER_SOURCE_LENGTH\",35721:\"ACTIVE_ATTRIBUTES\",35722:\"ACTIVE_ATTRIBUTE_MAX_LENGTH\",35724:\"SHADING_LANGUAGE_VERSION\",35725:\"CURRENT_PROGRAM\",36003:\"STENCIL_BACK_REF\",36004:\"STENCIL_BACK_VALUE_MASK\",36005:\"STENCIL_BACK_WRITEMASK\",36006:\"FRAMEBUFFER_BINDING\",36007:\"RENDERBUFFER_BINDING\",36048:\"FRAMEBUFFER_ATTACHMENT_OBJECT_TYPE\",36049:\"FRAMEBUFFER_ATTACHMENT_OBJECT_NAME\",36050:\"FRAMEBUFFER_ATTACHMENT_TEXTURE_LEVEL\",36051:\"FRAMEBUFFER_ATTACHMENT_TEXTURE_CUBE_MAP_FACE\",36053:\"FRAMEBUFFER_COMPLETE\",36054:\"FRAMEBUFFER_INCOMPLETE_ATTACHMENT\",36055:\"FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT\",36057:\"FRAMEBUFFER_INCOMPLETE_DIMENSIONS\",36061:\"FRAMEBUFFER_UNSUPPORTED\",36064:\"COLOR_ATTACHMENT0\",36096:\"DEPTH_ATTACHMENT\",36128:\"STENCIL_ATTACHMENT\",36160:\"FRAMEBUFFER\",36161:\"RENDERBUFFER\",36162:\"RENDERBUFFER_WIDTH\",36163:\"RENDERBUFFER_HEIGHT\",36164:\"RENDERBUFFER_INTERNAL_FORMAT\",36168:\"STENCIL_INDEX8\",36176:\"RENDERBUFFER_RED_SIZE\",36177:\"RENDERBUFFER_GREEN_SIZE\",36178:\"RENDERBUFFER_BLUE_SIZE\",36179:\"RENDERBUFFER_ALPHA_SIZE\",36180:\"RENDERBUFFER_DEPTH_SIZE\",36181:\"RENDERBUFFER_STENCIL_SIZE\",36194:\"RGB565\",36336:\"LOW_FLOAT\",36337:\"MEDIUM_FLOAT\",36338:\"HIGH_FLOAT\",36339:\"LOW_INT\",36340:\"MEDIUM_INT\",36341:\"HIGH_INT\",36346:\"SHADER_COMPILER\",36347:\"MAX_VERTEX_UNIFORM_VECTORS\",36348:\"MAX_VARYING_VECTORS\",36349:\"MAX_FRAGMENT_UNIFORM_VECTORS\",37440:\"UNPACK_FLIP_Y_WEBGL\",37441:\"UNPACK_PREMULTIPLY_ALPHA_WEBGL\",37442:\"CONTEXT_LOST_WEBGL\",37443:\"UNPACK_COLORSPACE_CONVERSION_WEBGL\",37444:\"BROWSER_DEFAULT_WEBGL\"}},6603:function(t,e,r){var 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outOfRange(clipBounds[0], clipBounds[1], fragPosition) ||\\n    fragColor.a * opacity == 0.\\n  ) discard;\\n\\n  gl_FragColor = opacity * fragColor;\\n}\"]);t.exports=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"offset\",type:\"vec3\"}])}},4234:function(t,e,r){\"use strict\";var n=r(8931);t.exports=function(t,e,r,n){i||(i=t.FRAMEBUFFER_UNSUPPORTED,a=t.FRAMEBUFFER_INCOMPLETE_ATTACHMENT,o=t.FRAMEBUFFER_INCOMPLETE_DIMENSIONS,s=t.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT);var u=t.getExtension(\"WEBGL_draw_buffers\");if(!l&&u&&function(t,e){var r=t.getParameter(e.MAX_COLOR_ATTACHMENTS_WEBGL);l=new Array(r+1);for(var n=0;n<=r;++n){for(var i=new Array(r),a=0;a<n;++a)i[a]=t.COLOR_ATTACHMENT0+a;for(a=n;a<r;++a)i[a]=t.NONE;l[n]=i}}(t,u),Array.isArray(e)&&(n=r,r=0|e[1],e=0|e[0]),\"number\"!=typeof e)throw new Error(\"gl-fbo: Missing shape parameter\");var c=t.getParameter(t.MAX_RENDERBUFFER_SIZE);if(e<0||e>c||r<0||r>c)throw new 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c(t,e){t.bindFramebuffer(t.FRAMEBUFFER,e[0]),t.bindRenderbuffer(t.RENDERBUFFER,e[1]),t.bindTexture(t.TEXTURE_2D,e[2])}function f(t){switch(t){case i:throw new Error(\"gl-fbo: Framebuffer unsupported\");case a:throw new Error(\"gl-fbo: Framebuffer incomplete attachment\");case o:throw new Error(\"gl-fbo: Framebuffer incomplete dimensions\");case s:throw new Error(\"gl-fbo: Framebuffer incomplete missing attachment\");default:throw new Error(\"gl-fbo: Framebuffer failed for unspecified reason\")}}function h(t,e,r,i,a,o){if(!i)return null;var s=n(t,e,r,a,i);return s.magFilter=t.NEAREST,s.minFilter=t.NEAREST,s.mipSamples=1,s.bind(),t.framebufferTexture2D(t.FRAMEBUFFER,o,t.TEXTURE_2D,s.handle,0),s}function p(t,e,r,n,i){var a=t.createRenderbuffer();return t.bindRenderbuffer(t.RENDERBUFFER,a),t.renderbufferStorage(t.RENDERBUFFER,n,e,r),t.framebufferRenderbuffer(t.FRAMEBUFFER,i,t.RENDERBUFFER,a),a}function 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m=r.getExtension(\"WEBGL_depth_texture\");m?d?t.depth=h(r,i,a,m.UNSIGNED_INT_24_8_WEBGL,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):v&&(t.depth=h(r,i,a,r.UNSIGNED_SHORT,r.DEPTH_COMPONENT,r.DEPTH_ATTACHMENT)):v&&d?t._depth_rb=p(r,i,a,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):v?t._depth_rb=p(r,i,a,r.DEPTH_COMPONENT16,r.DEPTH_ATTACHMENT):d&&(t._depth_rb=p(r,i,a,r.STENCIL_INDEX,r.STENCIL_ATTACHMENT));var x=r.checkFramebufferStatus(r.FRAMEBUFFER);if(x!==r.FRAMEBUFFER_COMPLETE){for(t._destroyed=!0,r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteFramebuffer(t.handle),t.handle=null,t.depth&&(t.depth.dispose(),t.depth=null),t._depth_rb&&(r.deleteRenderbuffer(t._depth_rb),t._depth_rb=null),y=0;y<t.color.length;++y)t.color[y].dispose(),t.color[y]=null;t._color_rb&&(r.deleteRenderbuffer(t._color_rb),t._color_rb=null),c(r,e),f(x)}c(r,e)}(this)}var v=d.prototype;function g(t,e,r){if(t._destroyed)throw new Error(\"gl-fbo: Can't resize destroyed FBO\");if(t._shape[0]!==e||t._shape[1]!==r){var n=t.gl,i=n.getParameter(n.MAX_RENDERBUFFER_SIZE);if(e<0||e>i||r<0||r>i)throw new Error(\"gl-fbo: Can't resize FBO, invalid dimensions\");t._shape[0]=e,t._shape[1]=r;for(var a=u(n),o=0;o<t.color.length;++o)t.color[o].shape=t._shape;t._color_rb&&(n.bindRenderbuffer(n.RENDERBUFFER,t._color_rb),n.renderbufferStorage(n.RENDERBUFFER,n.RGBA4,t._shape[0],t._shape[1])),t.depth&&(t.depth.shape=t._shape),t._depth_rb&&(n.bindRenderbuffer(n.RENDERBUFFER,t._depth_rb),t._useDepth&&t._useStencil?n.renderbufferStorage(n.RENDERBUFFER,n.DEPTH_STENCIL,t._shape[0],t._shape[1]):t._useDepth?n.renderbufferStorage(n.RENDERBUFFER,n.DEPTH_COMPONENT16,t._shape[0],t._shape[1]):t._useStencil&&n.renderbufferStorage(n.RENDERBUFFER,n.STENCIL_INDEX,t._shape[0],t._shape[1])),n.bindFramebuffer(n.FRAMEBUFFER,t.handle);var s=n.checkFramebufferStatus(n.FRAMEBUFFER);s!==n.FRAMEBUFFER_COMPLETE&&(t.dispose(),c(n,a),f(s)),c(n,a)}}Object.defineProperties(v,{shape:{get:function(){return this._destroyed?[0,0]:this._shapeVector},set:function(t){if(Array.isArray(t)||(t=[0|t,0|t]),2!==t.length)throw new Error(\"gl-fbo: Shape vector must be length 2\");var e=0|t[0],r=0|t[1];return g(this,e,r),[e,r]},enumerable:!1},width:{get:function(){return this._destroyed?0:this._shape[0]},set:function(t){return g(this,t|=0,this._shape[1]),t},enumerable:!1},height:{get:function(){return this._destroyed?0:this._shape[1]},set:function(t){return t|=0,g(this,this._shape[0],t),t},enumerable:!1}}),v.bind=function(){if(!this._destroyed){var t=this.gl;t.bindFramebuffer(t.FRAMEBUFFER,this.handle),t.viewport(0,0,this._shape[0],this._shape[1])}},v.dispose=function(){if(!this._destroyed){this._destroyed=!0;var t=this.gl;t.deleteFramebuffer(this.handle),this.handle=null,this.depth&&(this.depth.dispose(),this.depth=null),this._depth_rb&&(t.deleteRenderbuffer(this._depth_rb),this._depth_rb=null);for(var e=0;e<this.color.length;++e)this.color[e].dispose(),this.color[e]=null;this._color_rb&&(t.deleteRenderbuffer(this._color_rb),this._color_rb=null)}}},3530:function(t,e,r){var n=r(8974).sprintf,i=r(6603),a=r(9365),o=r(8008);t.exports=function(t,e,r){\"use strict\";var s=a(e)||\"of unknown name (see npm glsl-shader-name)\",l=\"unknown type\";void 0!==r&&(l=r===i.FRAGMENT_SHADER?\"fragment\":\"vertex\");for(var u=n(\"Error compiling %s shader %s:\\n\",l,s),c=n(\"%s%s\",u,t),f=t.split(\"\\n\"),h={},p=0;p<f.length;p++){var d=f[p];if(\"\"!==d&&\"\\0\"!==d){var v=parseInt(d.split(\":\")[2]);if(isNaN(v))throw new Error(n(\"Could not parse error: %s\",d));h[v]=d}}var g=o(e).split(\"\\n\");for(p=0;p<g.length;p++)if((h[p+3]||h[p+2]||h[p+1])&&(u+=g[p]+\"\\n\",h[p+1])){var y=h[p+1];y=y.substr(y.split(\":\",3).join(\":\").length+1).trim(),u+=n(\"^^^ %s\\n\\n\",y)}return{long:u.trim(),short:c.trim()}}},6386:function(t,e,r){\"use strict\";t.exports=function(t,e){var r=t.gl,n=new u(t,o(r,l.vertex,l.fragment),o(r,l.pickVertex,l.pickFragment),s(r),s(r),s(r),s(r));return n.update(e),t.addObject(n),n};var n=r(5070),i=r(9560),a=r(5306),o=r(5158),s=r(5827),l=r(1292);function u(t,e,r,n,i,a,o){this.plot=t,this.shader=e,this.pickShader=r,this.positionBuffer=n,this.weightBuffer=i,this.colorBuffer=a,this.idBuffer=o,this.xData=[],this.yData=[],this.shape=[0,0],this.bounds=[1/0,1/0,-1/0,-1/0],this.pickOffset=0}var c,f=u.prototype,h=[0,0,1,0,0,1,1,0,1,1,0,1];f.draw=(c=[1,0,0,0,1,0,0,0,1],function(){var t=this.plot,e=this.shader,r=this.bounds,n=this.numVertices;if(!(n<=0)){var i=t.gl,a=t.dataBox,o=r[2]-r[0],s=r[3]-r[1],l=a[2]-a[0],u=a[3]-a[1];c[0]=2*o/l,c[4]=2*s/u,c[6]=2*(r[0]-a[0])/l-1,c[7]=2*(r[1]-a[1])/u-1,e.bind();var f=e.uniforms;f.viewTransform=c,f.shape=this.shape;var h=e.attributes;this.positionBuffer.bind(),h.position.pointer(),this.weightBuffer.bind(),h.weight.pointer(i.UNSIGNED_BYTE,!1),this.colorBuffer.bind(),h.color.pointer(i.UNSIGNED_BYTE,!0),i.drawArrays(i.TRIANGLES,0,n)}}),f.drawPick=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0,0,0];return function(r){var n=this.plot,i=this.pickShader,a=this.bounds,o=this.numVertices;if(!(o<=0)){var s=n.gl,l=n.dataBox,u=a[2]-a[0],c=a[3]-a[1],f=l[2]-l[0],h=l[3]-l[1];t[0]=2*u/f,t[4]=2*c/h,t[6]=2*(a[0]-l[0])/f-1,t[7]=2*(a[1]-l[1])/h-1;for(var p=0;p<4;++p)e[p]=r>>8*p&255;this.pickOffset=r,i.bind();var d=i.uniforms;d.viewTransform=t,d.pickOffset=e,d.shape=this.shape;var v=i.attributes;return this.positionBuffer.bind(),v.position.pointer(),this.weightBuffer.bind(),v.weight.pointer(s.UNSIGNED_BYTE,!1),this.idBuffer.bind(),v.pickId.pointer(s.UNSIGNED_BYTE,!1),s.drawArrays(s.TRIANGLES,0,o),r+this.shape[0]*this.shape[1]}}}(),f.pick=function(t,e,r){var n=this.pickOffset,i=this.shape[0]*this.shape[1];if(r<n||r>=n+i)return null;var a=r-n,o=this.xData,s=this.yData;return{object:this,pointId:a,dataCoord:[o[a%this.shape[0]],s[a/this.shape[0]|0]]}},f.update=function(t){var e=(t=t||{}).shape||[0,0],r=t.x||i(e[0]),o=t.y||i(e[1]),s=t.z||new Float32Array(e[0]*e[1]),l=!1!==t.zsmooth;this.xData=r,this.yData=o;var u,c,f,p,d=t.colorLevels||[0],v=t.colorValues||[0,0,0,1],g=d.length,y=this.bounds;l?(u=y[0]=r[0],c=y[1]=o[0],f=y[2]=r[r.length-1],p=y[3]=o[o.length-1]):(u=y[0]=r[0]+(r[1]-r[0])/2,c=y[1]=o[0]+(o[1]-o[0])/2,f=y[2]=r[r.length-1]+(r[r.length-1]-r[r.length-2])/2,p=y[3]=o[o.length-1]+(o[o.length-1]-o[o.length-2])/2);var m=1/(f-u),x=1/(p-c),b=e[0],_=e[1];this.shape=[b,_];var w=(l?(b-1)*(_-1):b*_)*(h.length>>>1);this.numVertices=w;for(var T=a.mallocUint8(4*w),k=a.mallocFloat32(2*w),A=a.mallocUint8(2*w),M=a.mallocUint32(w),S=0,E=l?b-1:b,L=l?_-1:_,C=0;C<L;++C){var P,O;l?(P=x*(o[C]-c),O=x*(o[C+1]-c)):(P=C<_-1?x*(o[C]-(o[C+1]-o[C])/2-c):x*(o[C]-(o[C]-o[C-1])/2-c),O=C<_-1?x*(o[C]+(o[C+1]-o[C])/2-c):x*(o[C]+(o[C]-o[C-1])/2-c));for(var I=0;I<E;++I){var D,z;l?(D=m*(r[I]-u),z=m*(r[I+1]-u)):(D=I<b-1?m*(r[I]-(r[I+1]-r[I])/2-u):m*(r[I]-(r[I]-r[I-1])/2-u),z=I<b-1?m*(r[I]+(r[I+1]-r[I])/2-u):m*(r[I]+(r[I]-r[I-1])/2-u));for(var R=0;R<h.length;R+=2){var F,B,N,j,U=h[R],V=h[R+1],q=s[l?(C+V)*b+(I+U):C*b+I],H=n.le(d,q);if(H<0)F=v[0],B=v[1],N=v[2],j=v[3];else if(H===g-1)F=v[4*g-4],B=v[4*g-3],N=v[4*g-2],j=v[4*g-1];else{var G=(q-d[H])/(d[H+1]-d[H]),W=1-G,Y=4*H,X=4*(H+1);F=W*v[Y]+G*v[X],B=W*v[Y+1]+G*v[X+1],N=W*v[Y+2]+G*v[X+2],j=W*v[Y+3]+G*v[X+3]}T[4*S]=255*F,T[4*S+1]=255*B,T[4*S+2]=255*N,T[4*S+3]=255*j,k[2*S]=.5*D+.5*z,k[2*S+1]=.5*P+.5*O,A[2*S]=U,A[2*S+1]=V,M[S]=C*b+I,S+=1}}}this.positionBuffer.update(k),this.weightBuffer.update(A),this.colorBuffer.update(T),this.idBuffer.update(M),a.free(k),a.free(T),a.free(A),a.free(M)},f.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.positionBuffer.dispose(),this.weightBuffer.dispose(),this.colorBuffer.dispose(),this.idBuffer.dispose(),this.plot.removeObject(this)}},1292:function(t,e,r){\"use strict\";var n=r(6832);t.exports={fragment:n([\"precision lowp float;\\n#define GLSLIFY 1\\nvarying vec4 fragColor;\\nvoid main() {\\n  gl_FragColor = vec4(fragColor.rgb * fragColor.a, fragColor.a);\\n}\\n\"]),vertex:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 color;\\nattribute vec2 weight;\\n\\nuniform vec2 shape;\\nuniform mat3 viewTransform;\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  vec3 vPosition = viewTransform * vec3( position + (weight-.5)/(shape-1.) , 1.0);\\n  fragColor = color;\\n  gl_Position = vec4(vPosition.xy, 0, vPosition.z);\\n}\\n\"]),pickFragment:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\nvarying vec2 vWeight;\\n\\nuniform vec2 shape;\\nuniform vec4 pickOffset;\\n\\nvoid main() {\\n  vec2 d = step(.5, vWeight);\\n  vec4 id = fragId + pickOffset;\\n  id.x += d.x + d.y*shape.x;\\n\\n  id.y += floor(id.x / 256.0);\\n  id.x -= floor(id.x / 256.0) * 256.0;\\n\\n  id.z += floor(id.y / 256.0);\\n  id.y -= floor(id.y / 256.0) * 256.0;\\n\\n  id.w += floor(id.z / 256.0);\\n  id.z -= floor(id.z / 256.0) * 256.0;\\n\\n  gl_FragColor = id/255.;\\n}\\n\"]),pickVertex:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\nattribute vec2 weight;\\n\\nuniform vec2 shape;\\nuniform mat3 viewTransform;\\n\\nvarying vec4 fragId;\\nvarying vec2 vWeight;\\n\\nvoid main() {\\n  vWeight = weight;\\n\\n  fragId = pickId;\\n\\n  vec3 vPosition = viewTransform * vec3( position + (weight-.5)/(shape-1.) , 1.0);\\n  gl_Position = vec4(vPosition.xy, 0, vPosition.z);\\n}\\n\"])}},248:function(t,e,r){var n=r(6832),i=r(5158),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, nextPosition;\\nattribute float arcLength, lineWidth;\\nattribute vec4 color;\\n\\nuniform vec2 screenShape;\\nuniform float pixelRatio;\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 fragColor;\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\n\\nvec4 project(vec3 p) {\\n  return projection * view * model * vec4(p, 1.0);\\n}\\n\\nvoid main() {\\n  vec4 startPoint = project(position);\\n  vec4 endPoint   = project(nextPosition);\\n\\n  vec2 A = startPoint.xy / startPoint.w;\\n  vec2 B =   endPoint.xy /   endPoint.w;\\n\\n  float clipAngle = atan(\\n    (B.y - A.y) * screenShape.y,\\n    (B.x - A.x) * screenShape.x\\n  );\\n\\n  vec2 offset = 0.5 * pixelRatio * lineWidth * vec2(\\n    sin(clipAngle),\\n    -cos(clipAngle)\\n  ) / screenShape;\\n\\n  gl_Position = vec4(startPoint.xy + startPoint.w * offset, startPoint.zw);\\n\\n  worldPosition = position;\\n  pixelArcLength = arcLength;\\n  fragColor = color;\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3      clipBounds[2];\\nuniform sampler2D dashTexture;\\nuniform float     dashScale;\\nuniform float     opacity;\\n\\nvarying vec3    worldPosition;\\nvarying float   pixelArcLength;\\nvarying vec4    fragColor;\\n\\nvoid main() {\\n  if (\\n    outOfRange(clipBounds[0], clipBounds[1], worldPosition) ||\\n    fragColor.a * opacity == 0.\\n  ) discard;\\n\\n  float dashWeight = texture2D(dashTexture, vec2(dashScale * pixelArcLength, 0)).r;\\n  if(dashWeight < 0.5) {\\n    discard;\\n  }\\n  gl_FragColor = fragColor * opacity;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\n#define FLOAT_MAX  1.70141184e38\\n#define FLOAT_MIN  1.17549435e-38\\n\\n// https://github.com/mikolalysenko/glsl-read-float/blob/master/index.glsl\\nvec4 packFloat(float v) {\\n  float av = abs(v);\\n\\n  //Handle special cases\\n  if(av < FLOAT_MIN) {\\n    return vec4(0.0, 0.0, 0.0, 0.0);\\n  } else if(v > FLOAT_MAX) {\\n    return vec4(127.0, 128.0, 0.0, 0.0) / 255.0;\\n  } else if(v < -FLOAT_MAX) {\\n    return vec4(255.0, 128.0, 0.0, 0.0) / 255.0;\\n  }\\n\\n  vec4 c = vec4(0,0,0,0);\\n\\n  //Compute exponent and mantissa\\n  float e = floor(log2(av));\\n  float m = av * pow(2.0, -e) - 1.0;\\n\\n  //Unpack mantissa\\n  c[1] = floor(128.0 * m);\\n  m -= c[1] / 128.0;\\n  c[2] = floor(32768.0 * m);\\n  m -= c[2] / 32768.0;\\n  c[3] = floor(8388608.0 * m);\\n\\n  //Unpack exponent\\n  float ebias = e + 127.0;\\n  c[0] = floor(ebias / 2.0);\\n  ebias -= c[0] * 2.0;\\n  c[1] += floor(ebias) * 128.0;\\n\\n  //Unpack sign bit\\n  c[0] += 128.0 * step(0.0, -v);\\n\\n  //Scale back to range\\n  return c / 255.0;\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform float pickId;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], worldPosition)) discard;\\n\\n  gl_FragColor = vec4(pickId/255.0, packFloat(pixelArcLength).xyz);\\n}\"]),l=[{name:\"position\",type:\"vec3\"},{name:\"nextPosition\",type:\"vec3\"},{name:\"arcLength\",type:\"float\"},{name:\"lineWidth\",type:\"float\"},{name:\"color\",type:\"vec4\"}];e.createShader=function(t){return i(t,a,o,null,l)},e.createPickShader=function(t){return i(t,a,s,null,l)}},6086:function(t,e,r){\"use strict\";t.exports=function(t){var e=t.gl||t.scene&&t.scene.gl,r=f(e);r.attributes.position.location=0,r.attributes.nextPosition.location=1,r.attributes.arcLength.location=2,r.attributes.lineWidth.location=3,r.attributes.color.location=4;var o=h(e);o.attributes.position.location=0,o.attributes.nextPosition.location=1,o.attributes.arcLength.location=2,o.attributes.lineWidth.location=3,o.attributes.color.location=4;for(var s=n(e),l=i(e,[{buffer:s,size:3,offset:0,stride:48},{buffer:s,size:3,offset:12,stride:48},{buffer:s,size:1,offset:24,stride:48},{buffer:s,size:1,offset:28,stride:48},{buffer:s,size:4,offset:32,stride:48}]),c=u(new Array(1024),[256,1,4]),p=0;p<1024;++p)c.data[p]=255;var d=a(e,c);d.wrap=e.REPEAT;var v=new y(e,r,o,s,l,d);return v.update(t),v};var n=r(5827),i=r(2944),a=r(8931),o=new Uint8Array(4),s=new Float32Array(o.buffer),l=r(5070),u=r(5050),c=r(248),f=c.createShader,h=c.createPickShader,p=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function d(t,e){for(var r=0,n=0;n<3;++n){var i=t[n]-e[n];r+=i*i}return Math.sqrt(r)}function v(t){for(var e=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],r=0;r<3;++r)e[0][r]=Math.max(t[0][r],e[0][r]),e[1][r]=Math.min(t[1][r],e[1][r]);return e}function g(t,e,r,n){this.arcLength=t,this.position=e,this.index=r,this.dataCoordinate=n}function y(t,e,r,n,i,a){this.gl=t,this.shader=e,this.pickShader=r,this.buffer=n,this.vao=i,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.points=[],this.arcLength=[],this.vertexCount=0,this.bounds=[[0,0,0],[0,0,0]],this.pickId=0,this.lineWidth=1,this.texture=a,this.dashScale=1,this.opacity=1,this.hasAlpha=!1,this.dirty=!0,this.pixelRatio=1}var m=y.prototype;m.isTransparent=function(){return this.hasAlpha},m.isOpaque=function(){return!this.hasAlpha},m.pickSlots=1,m.setPickBase=function(t){this.pickId=t},m.drawTransparent=m.draw=function(t){if(this.vertexCount){var e=this.gl,r=this.shader,n=this.vao;r.bind(),r.uniforms={model:t.model||p,view:t.view||p,projection:t.projection||p,clipBounds:v(this.clipBounds),dashTexture:this.texture.bind(),dashScale:this.dashScale/this.arcLength[this.arcLength.length-1],opacity:this.opacity,screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},m.drawPick=function(t){if(this.vertexCount){var e=this.gl,r=this.pickShader,n=this.vao;r.bind(),r.uniforms={model:t.model||p,view:t.view||p,projection:t.projection||p,pickId:this.pickId,clipBounds:v(this.clipBounds),screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},m.update=function(t){var e,r;this.dirty=!0;var n=!!t.connectGaps;\"dashScale\"in t&&(this.dashScale=t.dashScale),this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=+t.opacity,this.opacity<1&&(this.hasAlpha=!0));var 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t[0]=x*n+b*s+_*f+w*v,t[1]=x*i+b*l+_*h+w*g,t[2]=x*a+b*u+_*p+w*y,t[3]=x*o+b*c+_*d+w*m,x=r[4],b=r[5],_=r[6],w=r[7],t[4]=x*n+b*s+_*f+w*v,t[5]=x*i+b*l+_*h+w*g,t[6]=x*a+b*u+_*p+w*y,t[7]=x*o+b*c+_*d+w*m,x=r[8],b=r[9],_=r[10],w=r[11],t[8]=x*n+b*s+_*f+w*v,t[9]=x*i+b*l+_*h+w*g,t[10]=x*a+b*u+_*p+w*y,t[11]=x*o+b*c+_*d+w*m,x=r[12],b=r[13],_=r[14],w=r[15],t[12]=x*n+b*s+_*f+w*v,t[13]=x*i+b*l+_*h+w*g,t[14]=x*a+b*u+_*p+w*y,t[15]=x*o+b*c+_*d+w*m,t}},5268:function(t){t.exports=function(t,e,r,n,i,a,o){var s=1/(e-r),l=1/(n-i),u=1/(a-o);return t[0]=-2*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=-2*l,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=2*u,t[11]=0,t[12]=(e+r)*s,t[13]=(i+n)*l,t[14]=(o+a)*u,t[15]=1,t}},1120:function(t){t.exports=function(t,e,r,n,i){var a=1/Math.tan(e/2),o=1/(n-i);return t[0]=a/r,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=a,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=(i+n)*o,t[11]=-1,t[12]=0,t[13]=0,t[14]=2*i*n*o,t[15]=0,t}},4422:function(t){t.exports=function(t,e,r,n){var 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t[0]=e[0],t[1]=e[4],t[2]=e[8],t[3]=e[12],t[4]=e[1],t[5]=e[5],t[6]=e[9],t[7]=e[13],t[8]=e[2],t[9]=e[6],t[10]=e[10],t[11]=e[14],t[12]=e[3],t[13]=e[7],t[14]=e[11],t[15]=e[15];return t}},4340:function(t,e,r){\"use strict\";var n=r(957),i=r(7309);function a(t,e){for(var r=[0,0,0,0],n=0;n<4;++n)for(var i=0;i<4;++i)r[i]+=t[4*n+i]*e[n];return r}function o(t,e,r,n,i){for(var o=a(n,a(r,a(e,[t[0],t[1],t[2],1]))),s=0;s<3;++s)o[s]/=o[3];return[.5*i[0]*(1+o[0]),.5*i[1]*(1-o[1])]}function s(t,e){for(var r=[0,0,0],n=0;n<t.length;++n)for(var i=t[n],a=e[n],o=0;o<3;++o)r[o]+=a*i[o];return r}t.exports=function(t,e,r,a,l,u){if(1===t.length)return[0,t[0].slice()];for(var c=new Array(t.length),f=0;f<t.length;++f)c[f]=o(t[f],r,a,l,u);var h=0,p=1/0;for(f=0;f<c.length;++f){for(var d=0,v=0;v<2;++v)d+=Math.pow(c[f][v]-e[v],2);d<p&&(p=d,h=f)}var g=function(t,e){if(2===t.length){for(var r=0,a=0,o=0;o<2;++o)r+=Math.pow(e[o]-t[0][o],2),a+=Math.pow(e[o]-t[1][o],2);return(r=Math.sqrt(r))+(a=Math.sqrt(a))<1e-6?[1,0]:[a/(r+a),r/(a+r)]}if(3===t.length){var s=[0,0];return i(t[0],t[1],t[2],e,s),n(t,s)}return[]}(c,e),y=0;for(f=0;f<3;++f){if(g[f]<-.001||g[f]>1.0001)return null;y+=g[f]}return Math.abs(y-1)>.001?null:[h,s(t,g),g]}},2056:function(t,e,r){var n=r(6832),i=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, normal;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model\\n           , view\\n           , projection\\n           , inverseModel;\\nuniform vec3 eyePosition\\n           , lightPosition;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvec4 project(vec3 p) {\\n  return projection * view * model * vec4(p, 1.0);\\n}\\n\\nvoid main() {\\n  gl_Position      = project(position);\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * vec4(position , 1.0);\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  f_normal  = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n  f_color          = color;\\n  f_data           = position;\\n  f_uv             = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\n//#pragma glslify: beckmann = require(glsl-specular-beckmann) // used in gl-surface3d\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness\\n            , fresnel\\n            , kambient\\n            , kdiffuse\\n            , kspecular;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (f_color.a == 0.0 ||\\n    outOfRange(clipBounds[0], clipBounds[1], f_data)\\n  ) discard;\\n\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n  //float specular = max(0.0, beckmann(L, V, N, roughness)); // used in gl-surface3d\\n\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = vec4(f_color.rgb, 1.0) * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * f_color.a;\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n  f_color = color;\\n  f_data  = position;\\n  f_uv    = uv;\\n}\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_data)) discard;\\n\\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),l=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\nattribute float pointSize;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0.0, 0.0 ,0.0 ,0.0);\\n  } else {\\n    gl_Position = projection * view * model * vec4(position, 1.0);\\n  }\\n  gl_PointSize = pointSize;\\n  f_color = color;\\n  f_uv = uv;\\n}\"]),u=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  vec2 pointR = gl_PointCoord.xy - vec2(0.5, 0.5);\\n  if(dot(pointR, pointR) > 0.25) {\\n    discard;\\n  }\\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),c=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n  f_id        = id;\\n  f_position  = position;\\n}\"]),f=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]),h=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3  position;\\nattribute float pointSize;\\nattribute vec4  id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0.0, 0.0, 0.0, 0.0);\\n  } else {\\n    gl_Position  = projection * view * model * vec4(position, 1.0);\\n    gl_PointSize = pointSize;\\n  }\\n  f_id         = id;\\n  f_position   = position;\\n}\"]),p=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n}\"]),d=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec3 contourColor;\\n\\nvoid main() {\\n  gl_FragColor = vec4(contourColor, 1.0);\\n}\\n\"]);e.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},e.wireShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},e.pointShader={vertex:l,fragment:u,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"pointSize\",type:\"float\"}]},e.pickShader={vertex:c,fragment:f,attributes:[{name:\"position\",type:\"vec3\"},{name:\"id\",type:\"vec4\"}]},e.pointPickShader={vertex:h,fragment:f,attributes:[{name:\"position\",type:\"vec3\"},{name:\"pointSize\",type:\"float\"},{name:\"id\",type:\"vec4\"}]},e.contourShader={vertex:p,fragment:d,attributes:[{name:\"position\",type:\"vec3\"}]}},8116:function(t,e,r){\"use strict\";var n=r(5158),i=r(5827),a=r(2944),o=r(8931),s=r(115),l=r(104),u=r(7437),c=r(5050),f=r(9156),h=r(7212),p=r(5306),d=r(2056),v=r(4340),g=d.meshShader,y=d.wireShader,m=d.pointShader,x=d.pickShader,b=d.pointPickShader,_=d.contourShader,w=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function T(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v,g,y,m,x,b,_,T,k,A,M,S){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.lineShader=n,this.pointShader=i,this.pickShader=a,this.pointPickShader=o,this.contourShader=s,this.trianglePositions=l,this.triangleColors=c,this.triangleNormals=h,this.triangleUVs=f,this.triangleIds=u,this.triangleVAO=p,this.triangleCount=0,this.lineWidth=1,this.edgePositions=d,this.edgeColors=g,this.edgeUVs=y,this.edgeIds=v,this.edgeVAO=m,this.edgeCount=0,this.pointPositions=x,this.pointColors=_,this.pointUVs=T,this.pointSizes=k,this.pointIds=b,this.pointVAO=A,this.pointCount=0,this.contourLineWidth=1,this.contourPositions=M,this.contourVAO=S,this.contourCount=0,this.contourColor=[0,0,0],this.contourEnable=!0,this.pickVertex=!0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.hasAlpha=!1,this.opacityscale=!1,this._model=w,this._view=w,this._projection=w,this._resolution=[1,1]}var k=T.prototype;function A(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;r<e.length;++r){if(e.length<2)return 1;if(e[r][0]===t)return e[r][1];if(e[r][0]>t&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}function M(t){var e=n(t,m.vertex,m.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.pointSize.location=4,e}function S(t){var e=n(t,x.vertex,x.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e}function E(t){var e=n(t,b.vertex,b.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e.attributes.pointSize.location=4,e}function L(t){var e=n(t,_.vertex,_.fragment);return e.attributes.position.location=0,e}k.isOpaque=function(){return!this.hasAlpha},k.isTransparent=function(){return this.hasAlpha},k.pickSlots=1,k.setPickBase=function(t){this.pickId=t},k.highlight=function(t){if(t&&this.contourEnable){for(var e=h(this.cells,this.intensity,t.intensity),r=e.cells,n=e.vertexIds,i=e.vertexWeights,a=r.length,o=p.mallocFloat32(6*a),s=0,l=0;l<a;++l)for(var u=r[l],c=0;c<2;++c){var f=u[0];2===u.length&&(f=u[c]);for(var d=n[f][0],v=n[f][1],g=i[f],y=1-g,m=this.positions[d],x=this.positions[v],b=0;b<3;++b)o[s++]=g*m[b]+y*x[b]}this.contourCount=s/3|0,this.contourPositions.update(o.subarray(0,s)),p.free(o)}else this.contourCount=0},k.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"contourEnable\"in t&&(this.contourEnable=t.contourEnable),\"contourColor\"in t&&(this.contourColor=t.contourColor),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=t.opacity,this.opacity<1&&(this.hasAlpha=!0)),\"opacityscale\"in t&&(this.opacityscale=t.opacityscale,this.hasAlpha=!0),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),t.texture?(this.texture.dispose(),this.texture=o(e,t.texture)):t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t,e){for(var r=f({colormap:t,nshades:256,format:\"rgba\"}),n=new Uint8Array(1024),i=0;i<256;++i){for(var a=r[i],o=0;o<3;++o)n[4*i+o]=a[o];n[4*i+3]=e?255*A(i/255,e):255*a[3]}return c(n,[256,256,4],[4,0,1])}(t.colormap,this.opacityscale)),this.texture.generateMipmap());var r=t.cells,n=t.positions;if(n&&r){var i=[],a=[],l=[],u=[],h=[],p=[],d=[],v=[],g=[],y=[],m=[],x=[],b=[],_=[];this.cells=r,this.positions=n;var w=t.vertexNormals,T=t.cellNormals,k=void 0===t.vertexNormalsEpsilon?1e-6:t.vertexNormalsEpsilon,M=void 0===t.faceNormalsEpsilon?1e-6:t.faceNormalsEpsilon;t.useFacetNormals&&!T&&(T=s.faceNormals(r,n,M)),T||w||(w=s.vertexNormals(r,n,k));var S=t.vertexColors,E=t.cellColors,L=t.meshColor||[1,1,1,1],C=t.vertexUVs,P=t.vertexIntensity,O=t.cellUVs,I=t.cellIntensity,D=1/0,z=-1/0;if(!C&&!O)if(P)if(t.vertexIntensityBounds)D=+t.vertexIntensityBounds[0],z=+t.vertexIntensityBounds[1];else for(var R=0;R<P.length;++R){var F=P[R];D=Math.min(D,F),z=Math.max(z,F)}else if(I)if(t.cellIntensityBounds)D=+t.cellIntensityBounds[0],z=+t.cellIntensityBounds[1];else for(R=0;R<I.length;++R)F=I[R],D=Math.min(D,F),z=Math.max(z,F);else for(R=0;R<n.length;++R)F=n[R][2],D=Math.min(D,F),z=Math.max(z,F);this.intensity=P||I||function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n),this.pickVertex=!(I||E);var B=t.pointSizes,N=t.pointSize||1;for(this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],R=0;R<n.length;++R)for(var j=n[R],U=0;U<3;++U)!isNaN(j[U])&&isFinite(j[U])&&(this.bounds[0][U]=Math.min(this.bounds[0][U],j[U]),this.bounds[1][U]=Math.max(this.bounds[1][U],j[U]));var V=0,q=0,H=0;t:for(R=0;R<r.length;++R){var G=r[R];switch(G.length){case 1:for(j=n[Y=G[0]],U=0;U<3;++U)if(isNaN(j[U])||!isFinite(j[U]))continue t;y.push(j[0],j[1],j[2]),X=S?S[Y]:E?E[R]:L,this.opacityscale&&P?a.push(X[0],X[1],X[2],this.opacity*A((P[Y]-D)/(z-D),this.opacityscale)):3===X.length?m.push(X[0],X[1],X[2],this.opacity):(m.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)),Z=C?C[Y]:P?[(P[Y]-D)/(z-D),0]:O?O[R]:I?[(I[R]-D)/(z-D),0]:[(j[2]-D)/(z-D),0],x.push(Z[0],Z[1]),B?b.push(B[Y]):b.push(N),_.push(R),H+=1;break;case 2:for(U=0;U<2;++U){j=n[Y=G[U]];for(var W=0;W<3;++W)if(isNaN(j[W])||!isFinite(j[W]))continue t}for(U=0;U<2;++U)j=n[Y=G[U]],p.push(j[0],j[1],j[2]),X=S?S[Y]:E?E[R]:L,this.opacityscale&&P?a.push(X[0],X[1],X[2],this.opacity*A((P[Y]-D)/(z-D),this.opacityscale)):3===X.length?d.push(X[0],X[1],X[2],this.opacity):(d.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)),Z=C?C[Y]:P?[(P[Y]-D)/(z-D),0]:O?O[R]:I?[(I[R]-D)/(z-D),0]:[(j[2]-D)/(z-D),0],v.push(Z[0],Z[1]),g.push(R);q+=1;break;case 3:for(U=0;U<3;++U)for(j=n[Y=G[U]],W=0;W<3;++W)if(isNaN(j[W])||!isFinite(j[W]))continue t;for(U=0;U<3;++U){var Y,X,Z,K;j=n[Y=G[2-U]],i.push(j[0],j[1],j[2]),(X=S?S[Y]:E?E[R]:L)?this.opacityscale&&P?a.push(X[0],X[1],X[2],this.opacity*A((P[Y]-D)/(z-D),this.opacityscale)):3===X.length?a.push(X[0],X[1],X[2],this.opacity):(a.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)):a.push(.5,.5,.5,1),Z=C?C[Y]:P?[(P[Y]-D)/(z-D),0]:O?O[R]:I?[(I[R]-D)/(z-D),0]:[(j[2]-D)/(z-D),0],u.push(Z[0],Z[1]),K=w?w[Y]:T[R],l.push(K[0],K[1],K[2]),h.push(R)}V+=1}}this.pointCount=H,this.edgeCount=q,this.triangleCount=V,this.pointPositions.update(y),this.pointColors.update(m),this.pointUVs.update(x),this.pointSizes.update(b),this.pointIds.update(new Uint32Array(_)),this.edgePositions.update(p),this.edgeColors.update(d),this.edgeUVs.update(v),this.edgeIds.update(new Uint32Array(g)),this.trianglePositions.update(i),this.triangleColors.update(a),this.triangleUVs.update(u),this.triangleNormals.update(l),this.triangleIds.update(new Uint32Array(h))}},k.drawTransparent=k.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,i=t.projection||w,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var s={model:r,view:n,projection:i,inverseModel:w.slice(),clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],contourColor:this.contourColor,texture:0};s.inverseModel=u(s.inverseModel,s.model),e.disable(e.CULL_FACE),this.texture.bind(0);var c=new Array(16);for(l(c,s.view,s.model),l(c,s.projection,c),u(c,c),o=0;o<3;++o)s.eyePosition[o]=c[12+o]/c[15];var f,h=c[15];for(o=0;o<3;++o)h+=this.lightPosition[o]*c[4*o+3];for(o=0;o<3;++o){for(var p=c[12+o],d=0;d<3;++d)p+=c[4*d+o]*this.lightPosition[d];s.lightPosition[o]=p/h}this.triangleCount>0&&((f=this.triShader).bind(),f.uniforms=s,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&this.lineWidth>0&&((f=this.lineShader).bind(),f.uniforms=s,this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0&&((f=this.pointShader).bind(),f.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind()),this.contourEnable&&this.contourCount>0&&this.contourLineWidth>0&&((f=this.contourShader).bind(),f.uniforms=s,this.contourVAO.bind(),e.drawArrays(e.LINES,0,this.contourCount),this.contourVAO.unbind())},k.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,i=t.projection||w,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s,l={model:r,view:n,projection:i,clipBounds:a,pickId:this.pickId/255};(s=this.pickShader).bind(),s.uniforms=l,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0&&((s=this.pointPickShader).bind(),s.uniforms=l,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind())},k.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;for(var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions,i=new Array(r.length),a=0;a<r.length;++a)i[a]=n[r[a]];var o=t.coord[0],s=t.coord[1];if(!this.pickVertex){var l=this.positions[r[0]],u=this.positions[r[1]],c=this.positions[r[2]],f=[(l[0]+u[0]+c[0])/3,(l[1]+u[1]+c[1])/3,(l[2]+u[2]+c[2])/3];return{_cellCenter:!0,position:[o,s],index:e,cell:r,cellId:e,intensity:this.intensity[e],dataCoordinate:f}}var h=v(i,[o*this.pixelRatio,this._resolution[1]-s*this.pixelRatio],this._model,this._view,this._projection,this._resolution);if(!h)return null;var p=h[2],d=0;for(a=0;a<r.length;++a)d+=p[a]*this.intensity[r[a]];return{position:h[1],index:r[h[0]],cell:r,cellId:e,intensity:d,dataCoordinate:this.positions[r[h[0]]]}},k.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.lineShader.dispose(),this.pointShader.dispose(),this.pickShader.dispose(),this.pointPickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleNormals.dispose(),this.triangleIds.dispose(),this.edgeVAO.dispose(),this.edgePositions.dispose(),this.edgeColors.dispose(),this.edgeUVs.dispose(),this.edgeIds.dispose(),this.pointVAO.dispose(),this.pointPositions.dispose(),this.pointColors.dispose(),this.pointUVs.dispose(),this.pointSizes.dispose(),this.pointIds.dispose(),this.contourVAO.dispose(),this.contourPositions.dispose(),this.contourShader.dispose()},t.exports=function(t,e){if(1===arguments.length&&(t=(e=t).gl),!(t.getExtension(\"OES_standard_derivatives\")||t.getExtension(\"MOZ_OES_standard_derivatives\")||t.getExtension(\"WEBKIT_OES_standard_derivatives\")))throw new Error(\"derivatives not supported\");var r=function(t){var e=n(t,g.vertex,g.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.normal.location=4,e}(t),s=function(t){var e=n(t,y.vertex,y.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e}(t),l=M(t),u=S(t),f=E(t),h=L(t),p=o(t,c(new Uint8Array([255,255,255,255]),[1,1,4]));p.generateMipmap(),p.minFilter=t.LINEAR_MIPMAP_LINEAR,p.magFilter=t.LINEAR;var d=i(t),v=i(t),m=i(t),x=i(t),b=i(t),_=a(t,[{buffer:d,type:t.FLOAT,size:3},{buffer:b,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:v,type:t.FLOAT,size:4},{buffer:m,type:t.FLOAT,size:2},{buffer:x,type:t.FLOAT,size:3}]),w=i(t),k=i(t),A=i(t),C=i(t),P=a(t,[{buffer:w,type:t.FLOAT,size:3},{buffer:C,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:k,type:t.FLOAT,size:4},{buffer:A,type:t.FLOAT,size:2}]),O=i(t),I=i(t),D=i(t),z=i(t),R=i(t),F=a(t,[{buffer:O,type:t.FLOAT,size:3},{buffer:R,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:I,type:t.FLOAT,size:4},{buffer:D,type:t.FLOAT,size:2},{buffer:z,type:t.FLOAT,size:1}]),B=i(t),N=new T(t,p,r,s,l,u,f,h,d,b,v,m,x,_,w,C,k,A,P,O,R,I,D,z,F,B,a(t,[{buffer:B,type:t.FLOAT,size:3}]));return N.update(e),N}},4554:function(t,e,r){\"use strict\";t.exports=function(t){var e=t.gl;return new o(t,n(e,[0,0,0,1,1,0,1,1]),i(e,a.boxVert,a.lineFrag))};var n=r(5827),i=r(5158),a=r(2709);function o(t,e,r){this.plot=t,this.vbo=e,this.shader=r}var s,l,u=o.prototype;u.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},u.drawBox=(s=[0,0],l=[0,0],function(t,e,r,n,i){var a=this.plot,o=this.shader,u=a.gl;s[0]=t,s[1]=e,l[0]=r,l[1]=n,o.uniforms.lo=s,o.uniforms.hi=l,o.uniforms.color=i,u.drawArrays(u.TRIANGLE_STRIP,0,4)}),u.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},3016:function(t,e,r){\"use strict\";t.exports=function(t){var e=t.gl;return new s(t,n(e),i(e,o.gridVert,o.gridFrag),i(e,o.tickVert,o.gridFrag))};var n=r(5827),i=r(5158),a=r(5070),o=r(2709);function s(t,e,r,n){this.plot=t,this.vbo=e,this.shader=r,this.tickShader=n,this.ticks=[[],[]]}function l(t,e){return t-e}var u,c,f,h,p,d=s.prototype;d.draw=(u=[0,0],c=[0,0],f=[0,0],function(){for(var t=this.plot,e=this.vbo,r=this.shader,n=this.ticks,i=t.gl,a=t._tickBounds,o=t.dataBox,s=t.viewBox,l=t.gridLineWidth,h=t.gridLineColor,p=t.gridLineEnable,d=t.pixelRatio,v=0;v<2;++v){var g=a[v],y=a[v+2]-g,m=.5*(o[v+2]+o[v]),x=o[v+2]-o[v];c[v]=2*y/x,u[v]=2*(g-m)/x}r.bind(),e.bind(),r.attributes.dataCoord.pointer(),r.uniforms.dataShift=u,r.uniforms.dataScale=c;var b=0;for(v=0;v<2;++v){f[0]=f[1]=0,f[v]=1,r.uniforms.dataAxis=f,r.uniforms.lineWidth=l[v]/(s[v+2]-s[v])*d,r.uniforms.color=h[v];var _=6*n[v].length;p[v]&&_&&i.drawArrays(i.TRIANGLES,b,_),b+=_}}),d.drawTickMarks=function(){var t=[0,0],e=[0,0],r=[1,0],n=[0,1],i=[0,0],o=[0,0];return function(){for(var s=this.plot,u=this.vbo,c=this.tickShader,f=this.ticks,h=s.gl,p=s._tickBounds,d=s.dataBox,v=s.viewBox,g=s.pixelRatio,y=s.screenBox,m=y[2]-y[0],x=y[3]-y[1],b=v[2]-v[0],_=v[3]-v[1],w=0;w<2;++w){var T=p[w],k=p[w+2]-T,A=.5*(d[w+2]+d[w]),M=d[w+2]-d[w];e[w]=2*k/M,t[w]=2*(T-A)/M}e[0]*=b/m,t[0]*=b/m,e[1]*=_/x,t[1]*=_/x,c.bind(),u.bind(),c.attributes.dataCoord.pointer();var S=c.uniforms;S.dataShift=t,S.dataScale=e;var E=s.tickMarkLength,L=s.tickMarkWidth,C=s.tickMarkColor,P=6*f[0].length,O=Math.min(a.ge(f[0],(d[0]-p[0])/(p[2]-p[0]),l),f[0].length),I=Math.min(a.gt(f[0],(d[2]-p[0])/(p[2]-p[0]),l),f[0].length),D=0+6*O,z=6*Math.max(0,I-O),R=Math.min(a.ge(f[1],(d[1]-p[1])/(p[3]-p[1]),l),f[1].length),F=Math.min(a.gt(f[1],(d[3]-p[1])/(p[3]-p[1]),l),f[1].length),B=P+6*R,N=6*Math.max(0,F-R);i[0]=2*(v[0]-E[1])/m-1,i[1]=(v[3]+v[1])/x-1,o[0]=E[1]*g/m,o[1]=L[1]*g/x,N&&(S.color=C[1],S.tickScale=o,S.dataAxis=n,S.screenOffset=i,h.drawArrays(h.TRIANGLES,B,N)),i[0]=(v[2]+v[0])/m-1,i[1]=2*(v[1]-E[0])/x-1,o[0]=L[0]*g/m,o[1]=E[0]*g/x,z&&(S.color=C[0],S.tickScale=o,S.dataAxis=r,S.screenOffset=i,h.drawArrays(h.TRIANGLES,D,z)),i[0]=2*(v[2]+E[3])/m-1,i[1]=(v[3]+v[1])/x-1,o[0]=E[3]*g/m,o[1]=L[3]*g/x,N&&(S.color=C[3],S.tickScale=o,S.dataAxis=n,S.screenOffset=i,h.drawArrays(h.TRIANGLES,B,N)),i[0]=(v[2]+v[0])/m-1,i[1]=2*(v[3]+E[2])/x-1,o[0]=L[2]*g/m,o[1]=E[2]*g/x,z&&(S.color=C[2],S.tickScale=o,S.dataAxis=r,S.screenOffset=i,h.drawArrays(h.TRIANGLES,D,z))}}(),d.update=(h=[1,1,-1,-1,1,-1],p=[1,-1,1,1,-1,-1],function(t){for(var e=t.ticks,r=t.bounds,n=new Float32Array(18*(e[0].length+e[1].length)),i=(this.plot.zeroLineEnable,0),a=[[],[]],o=0;o<2;++o)for(var s=a[o],l=e[o],u=r[o],c=r[o+2],f=0;f<l.length;++f){var d=(l[f].x-u)/(c-u);s.push(d);for(var v=0;v<6;++v)n[i++]=d,n[i++]=h[v],n[i++]=p[v]}this.ticks=a,this.vbo.update(n)}),d.dispose=function(){this.vbo.dispose(),this.shader.dispose(),this.tickShader.dispose()}},1154:function(t,e,r){\"use strict\";t.exports=function(t){var e=t.gl;return new o(t,n(e,[-1,-1,-1,1,1,-1,1,1]),i(e,a.lineVert,a.lineFrag))};var n=r(5827),i=r(5158),a=r(2709);function o(t,e,r){this.plot=t,this.vbo=e,this.shader=r}var s,l,u=o.prototype;u.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},u.drawLine=(s=[0,0],l=[0,0],function(t,e,r,n,i,a){var o=this.plot,u=this.shader,c=o.gl;s[0]=t,s[1]=e,l[0]=r,l[1]=n,u.uniforms.start=s,u.uniforms.end=l,u.uniforms.width=i*o.pixelRatio,u.uniforms.color=a,c.drawArrays(c.TRIANGLE_STRIP,0,4)}),u.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},2709:function(t,e,r){\"use strict\";var n=r(6832),i=n([\"precision lowp float;\\n#define GLSLIFY 1\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = vec4(color.xyz * color.w, color.w);\\n}\\n\"]);t.exports={lineVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 start, end;\\nuniform float width;\\n\\nvec2 perp(vec2 v) {\\n  return vec2(v.y, -v.x);\\n}\\n\\nvec2 screen(vec2 v) {\\n  return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n  vec2 delta = normalize(perp(start - end));\\n  vec2 offset = mix(start, end, 0.5 * (coord.y+1.0));\\n  gl_Position = vec4(screen(offset + 0.5 * width * delta * coord.x), 0, 1);\\n}\\n\"]),lineFrag:i,textVert:n([\"#define GLSLIFY 1\\nattribute vec3 textCoordinate;\\n\\nuniform vec2 dataScale, dataShift, dataAxis, screenOffset, textScale;\\nuniform float angle;\\n\\nvoid main() {\\n  float dataOffset  = textCoordinate.z;\\n  vec2 glyphOffset  = textCoordinate.xy;\\n  mat2 glyphMatrix = mat2(cos(angle), sin(angle), -sin(angle), cos(angle));\\n  vec2 screenCoordinate = dataAxis * (dataScale * dataOffset + dataShift) +\\n    glyphMatrix * glyphOffset * textScale + screenOffset;\\n  gl_Position = vec4(screenCoordinate, 0, 1);\\n}\\n\"]),textFrag:i,gridVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale;\\nuniform float lineWidth;\\n\\nvoid main() {\\n  vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n  pos += 10.0 * dataCoord.y * vec2(dataAxis.y, -dataAxis.x) + dataCoord.z * lineWidth;\\n  gl_Position = vec4(pos, 0, 1);\\n}\\n\"]),gridFrag:i,boxVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 lo, hi;\\n\\nvec2 screen(vec2 v) {\\n  return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n  gl_Position = vec4(screen(mix(lo, hi, coord)), 0, 1);\\n}\\n\"]),tickVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale, screenOffset, tickScale;\\n\\nvoid main() {\\n  vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n  gl_Position = vec4(pos + tickScale*dataCoord.yz + screenOffset, 0, 1);\\n}\\n\"])}},5613:function(t,e,r){\"use strict\";t.exports=function(t){var e=t.gl;return new l(t,n(e),i(e,s.textVert,s.textFrag))};var n=r(5827),i=r(5158),a=r(6946),o=r(5070),s=r(2709);function l(t,e,r){this.plot=t,this.vbo=e,this.shader=r,this.tickOffset=[[],[]],this.tickX=[[],[]],this.labelOffset=[0,0],this.labelCount=[0,0]}var u,c,f,h,p,d,v=l.prototype;v.drawTicks=(u=[0,0],c=[0,0],f=[0,0],function(t){var e=this.plot,r=this.shader,n=this.tickX[t],i=this.tickOffset[t],a=e.gl,s=e.viewBox,l=e.dataBox,h=e.screenBox,p=e.pixelRatio,d=e.tickEnable,v=e.tickPad,g=e.tickColor,y=e.tickAngle,m=e.labelEnable,x=e.labelPad,b=e.labelColor,_=e.labelAngle,w=this.labelOffset[t],T=this.labelCount[t],k=o.lt(n,l[t]),A=o.le(n,l[t+2]);u[0]=u[1]=0,u[t]=1,c[t]=(s[2+t]+s[t])/(h[2+t]-h[t])-1;var M=2/h[2+(1^t)]-h[1^t];c[1^t]=M*s[1^t]-1,d[t]&&(c[1^t]-=M*p*v[t],k<A&&i[A]>i[k]&&(r.uniforms.dataAxis=u,r.uniforms.screenOffset=c,r.uniforms.color=g[t],r.uniforms.angle=y[t],a.drawArrays(a.TRIANGLES,i[k],i[A]-i[k]))),m[t]&&T&&(c[1^t]-=M*p*x[t],r.uniforms.dataAxis=f,r.uniforms.screenOffset=c,r.uniforms.color=b[t],r.uniforms.angle=_[t],a.drawArrays(a.TRIANGLES,w,T)),c[1^t]=M*s[2+(1^t)]-1,d[t+2]&&(c[1^t]+=M*p*v[t+2],k<A&&i[A]>i[k]&&(r.uniforms.dataAxis=u,r.uniforms.screenOffset=c,r.uniforms.color=g[t+2],r.uniforms.angle=y[t+2],a.drawArrays(a.TRIANGLES,i[k],i[A]-i[k]))),m[t+2]&&T&&(c[1^t]+=M*p*x[t+2],r.uniforms.dataAxis=f,r.uniforms.screenOffset=c,r.uniforms.color=b[t+2],r.uniforms.angle=_[t+2],a.drawArrays(a.TRIANGLES,w,T))}),v.drawTitle=function(){var t=[0,0],e=[0,0];return function(){var r=this.plot,n=this.shader,i=r.gl,a=r.screenBox,o=r.titleCenter,s=r.titleAngle,l=r.titleColor,u=r.pixelRatio;if(this.titleCount){for(var c=0;c<2;++c)e[c]=2*(o[c]*u-a[c])/(a[2+c]-a[c])-1;n.bind(),n.uniforms.dataAxis=t,n.uniforms.screenOffset=e,n.uniforms.angle=s,n.uniforms.color=l,i.drawArrays(i.TRIANGLES,this.titleOffset,this.titleCount)}}}(),v.bind=(h=[0,0],p=[0,0],d=[0,0],function(){var t=this.plot,e=this.shader,r=t._tickBounds,n=t.dataBox,i=t.screenBox,a=t.viewBox;e.bind();for(var o=0;o<2;++o){var s=r[o],l=r[o+2]-s,u=.5*(n[o+2]+n[o]),c=n[o+2]-n[o],f=a[o],v=a[o+2]-f,g=i[o],y=i[o+2]-g;p[o]=2*l/c*v/y,h[o]=2*(s-u)/c*v/y}d[1]=2*t.pixelRatio/(i[3]-i[1]),d[0]=d[1]*(i[3]-i[1])/(i[2]-i[0]),e.uniforms.dataScale=p,e.uniforms.dataShift=h,e.uniforms.textScale=d,this.vbo.bind(),e.attributes.textCoordinate.pointer()}),v.update=function(t){var e,r,n,i,o,s=[],l=t.ticks,u=t.bounds;for(o=0;o<2;++o){var c=[Math.floor(s.length/3)],f=[-1/0],h=l[o];for(e=0;e<h.length;++e){var p=h[e],d=p.x,v=p.text,g=p.font||\"sans-serif\";i=p.fontSize||12;for(var y=1/(u[o+2]-u[o]),m=u[o],x=v.split(\"\\n\"),b=0;b<x.length;b++)for(n=a(g,x[b]).data,r=0;r<n.length;r+=2)s.push(n[r]*i,-n[r+1]*i-b*i*1.2,(d-m)*y);c.push(Math.floor(s.length/3)),f.push(d)}this.tickOffset[o]=c,this.tickX[o]=f}for(o=0;o<2;++o){for(this.labelOffset[o]=Math.floor(s.length/3),n=a(t.labelFont[o],t.labels[o],{textAlign:\"center\"}).data,i=t.labelSize[o],e=0;e<n.length;e+=2)s.push(n[e]*i,-n[e+1]*i,0);this.labelCount[o]=Math.floor(s.length/3)-this.labelOffset[o]}for(this.titleOffset=Math.floor(s.length/3),n=a(t.titleFont,t.title).data,i=t.titleSize,e=0;e<n.length;e+=2)s.push(n[e]*i,-n[e+1]*i,0);this.titleCount=Math.floor(s.length/3)-this.titleOffset,this.vbo.update(s)},v.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},2117:function(t,e,r){\"use strict\";t.exports=function(t){var e=t.gl,r=new l(e,n(e,[e.drawingBufferWidth,e.drawingBufferHeight]));return r.grid=i(r),r.text=a(r),r.line=o(r),r.box=s(r),r.update(t),r};var n=r(2611),i=r(3016),a=r(5613),o=r(1154),s=r(4554);function l(t,e){this.gl=t,this.pickBuffer=e,this.screenBox=[0,0,t.drawingBufferWidth,t.drawingBufferHeight],this.viewBox=[0,0,0,0],this.dataBox=[-10,-10,10,10],this.gridLineEnable=[!0,!0],this.gridLineWidth=[1,1],this.gridLineColor=[[0,0,0,1],[0,0,0,1]],this.pixelRatio=1,this.tickMarkLength=[0,0,0,0],this.tickMarkWidth=[0,0,0,0],this.tickMarkColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[15,15,15,15],this.tickAngle=[0,0,0,0],this.tickEnable=[!0,!0,!0,!0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[15,15,15,15],this.labelAngle=[0,Math.PI/2,0,3*Math.PI/2],this.labelEnable=[!0,!0,!0,!0],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.titleCenter=[0,0],this.titleEnable=!0,this.titleAngle=0,this.titleColor=[0,0,0,1],this.borderColor=[0,0,0,0],this.backgroundColor=[0,0,0,0],this.zeroLineEnable=[!0,!0],this.zeroLineWidth=[4,4],this.zeroLineColor=[[0,0,0,1],[0,0,0,1]],this.borderLineEnable=[!0,!0,!0,!0],this.borderLineWidth=[2,2,2,2],this.borderLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.grid=null,this.text=null,this.line=null,this.box=null,this.objects=[],this.overlays=[],this._tickBounds=[1/0,1/0,-1/0,-1/0],this.static=!1,this.dirty=!1,this.pickDirty=!1,this.pickDelay=120,this.pickRadius=10,this._pickTimeout=null,this._drawPick=this.drawPick.bind(this),this._depthCounter=0}var u=l.prototype;function c(t){for(var e=t.slice(),r=0;r<e.length;++r)e[r]=e[r].slice();return e}function f(t,e){return t.x-e.x}u.setDirty=function(){this.dirty=this.pickDirty=!0},u.setOverlayDirty=function(){this.dirty=!0},u.nextDepthValue=function(){return this._depthCounter++/65536},u.draw=function(){var t=this.gl,e=this.screenBox,r=this.viewBox,n=this.dataBox,i=this.pixelRatio,a=this.grid,o=this.line,s=this.text,l=this.objects;if(this._depthCounter=0,this.pickDirty&&(this._pickTimeout&&clearTimeout(this._pickTimeout),this.pickDirty=!1,this._pickTimeout=setTimeout(this._drawPick,this.pickDelay)),this.dirty){if(this.dirty=!1,t.bindFramebuffer(t.FRAMEBUFFER,null),t.enable(t.SCISSOR_TEST),t.disable(t.DEPTH_TEST),t.depthFunc(t.LESS),t.depthMask(!1),t.enable(t.BLEND),t.blendEquation(t.FUNC_ADD,t.FUNC_ADD),t.blendFunc(t.ONE,t.ONE_MINUS_SRC_ALPHA),this.borderColor){t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]);var u=this.borderColor;t.clearColor(u[0]*u[3],u[1]*u[3],u[2]*u[3],u[3]),t.clear(t.COLOR_BUFFER_BIT|t.DEPTH_BUFFER_BIT)}t.scissor(r[0],r[1],r[2]-r[0],r[3]-r[1]),t.viewport(r[0],r[1],r[2]-r[0],r[3]-r[1]);var c=this.backgroundColor;t.clearColor(c[0]*c[3],c[1]*c[3],c[2]*c[3],c[3]),t.clear(t.COLOR_BUFFER_BIT),a.draw();var f=this.zeroLineEnable,h=this.zeroLineColor,p=this.zeroLineWidth;if(f[0]||f[1]){o.bind();for(var d=0;d<2;++d)if(f[d]&&n[d]<=0&&n[d+2]>=0){var v=e[d]-n[d]*(e[d+2]-e[d])/(n[d+2]-n[d]);0===d?o.drawLine(v,e[1],v,e[3],p[d],h[d]):o.drawLine(e[0],v,e[2],v,p[d],h[d])}}for(d=0;d<l.length;++d)l[d].draw();t.viewport(e[0],e[1],e[2]-e[0],e[3]-e[1]),t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]),this.grid.drawTickMarks(),o.bind();var g=this.borderLineEnable,y=this.borderLineWidth,m=this.borderLineColor;for(g[1]&&o.drawLine(r[0],r[1]-.5*y[1]*i,r[0],r[3]+.5*y[3]*i,y[1],m[1]),g[0]&&o.drawLine(r[0]-.5*y[0]*i,r[1],r[2]+.5*y[2]*i,r[1],y[0],m[0]),g[3]&&o.drawLine(r[2],r[1]-.5*y[1]*i,r[2],r[3]+.5*y[3]*i,y[3],m[3]),g[2]&&o.drawLine(r[0]-.5*y[0]*i,r[3],r[2]+.5*y[2]*i,r[3],y[2],m[2]),s.bind(),d=0;d<2;++d)s.drawTicks(d);this.titleEnable&&s.drawTitle();var x=this.overlays;for(d=0;d<x.length;++d)x[d].draw();t.disable(t.SCISSOR_TEST),t.disable(t.BLEND),t.depthMask(!0)}},u.drawPick=function(){if(!this.static){var t=this.pickBuffer;this.gl,this._pickTimeout=null,t.begin();for(var e=1,r=this.objects,n=0;n<r.length;++n)e=r[n].drawPick(e);t.end()}},u.pick=function(t,e){if(!this.static){var r=this.pixelRatio,n=this.pickPixelRatio,i=this.viewBox,a=0|Math.round((t-i[0]/r)*n),o=0|Math.round((e-i[1]/r)*n),s=this.pickBuffer.query(a,o,this.pickRadius);if(!s)return null;for(var l=s.id+(s.value[0]<<8)+(s.value[1]<<16)+(s.value[2]<<24),u=this.objects,c=0;c<u.length;++c){var f=u[c].pick(a,o,l);if(f)return f}return null}},u.setScreenBox=function(t){var e=this.screenBox,r=this.pixelRatio;e[0]=0|Math.round(t[0]*r),e[1]=0|Math.round(t[1]*r),e[2]=0|Math.round(t[2]*r),e[3]=0|Math.round(t[3]*r),this.setDirty()},u.setDataBox=function(t){var e=this.dataBox;(e[0]!==t[0]||e[1]!==t[1]||e[2]!==t[2]||e[3]!==t[3])&&(e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],this.setDirty())},u.setViewBox=function(t){var e=this.pixelRatio,r=this.viewBox;r[0]=0|Math.round(t[0]*e),r[1]=0|Math.round(t[1]*e),r[2]=0|Math.round(t[2]*e),r[3]=0|Math.round(t[3]*e);var n=this.pickPixelRatio;this.pickBuffer.shape=[0|Math.round((t[2]-t[0])*n),0|Math.round((t[3]-t[1])*n)],this.setDirty()},u.update=function(t){t=t||{};var e=this.gl;this.pixelRatio=t.pixelRatio||1;var r=this.pixelRatio;this.pickPixelRatio=Math.max(r,1),this.setScreenBox(t.screenBox||[0,0,e.drawingBufferWidth/r,e.drawingBufferHeight/r]),this.screenBox,this.setViewBox(t.viewBox||[.125*(this.screenBox[2]-this.screenBox[0])/r,.125*(this.screenBox[3]-this.screenBox[1])/r,.875*(this.screenBox[2]-this.screenBox[0])/r,.875*(this.screenBox[3]-this.screenBox[1])/r]);var n=this.viewBox,i=(n[2]-n[0])/(n[3]-n[1]);this.setDataBox(t.dataBox||[-10,-10/i,10,10/i]),this.borderColor=!1!==t.borderColor&&(t.borderColor||[0,0,0,0]).slice(),this.backgroundColor=(t.backgroundColor||[0,0,0,0]).slice(),this.gridLineEnable=(t.gridLineEnable||[!0,!0]).slice(),this.gridLineWidth=(t.gridLineWidth||[1,1]).slice(),this.gridLineColor=c(t.gridLineColor||[[.5,.5,.5,1],[.5,.5,.5,1]]),this.zeroLineEnable=(t.zeroLineEnable||[!0,!0]).slice(),this.zeroLineWidth=(t.zeroLineWidth||[4,4]).slice(),this.zeroLineColor=c(t.zeroLineColor||[[0,0,0,1],[0,0,0,1]]),this.tickMarkLength=(t.tickMarkLength||[0,0,0,0]).slice(),this.tickMarkWidth=(t.tickMarkWidth||[0,0,0,0]).slice(),this.tickMarkColor=c(t.tickMarkColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.titleCenter=(t.titleCenter||[.5*(n[0]+n[2])/r,(n[3]+120)/r]).slice(),this.titleEnable=!(\"titleEnable\"in t)||!!t.titleEnable,this.titleAngle=t.titleAngle||0,this.titleColor=(t.titleColor||[0,0,0,1]).slice(),this.labelPad=(t.labelPad||[15,15,15,15]).slice(),this.labelAngle=(t.labelAngle||[0,Math.PI/2,0,3*Math.PI/2]).slice(),this.labelEnable=(t.labelEnable||[!0,!0,!0,!0]).slice(),this.labelColor=c(t.labelColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.tickPad=(t.tickPad||[15,15,15,15]).slice(),this.tickAngle=(t.tickAngle||[0,0,0,0]).slice(),this.tickEnable=(t.tickEnable||[!0,!0,!0,!0]).slice(),this.tickColor=c(t.tickColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.borderLineEnable=(t.borderLineEnable||[!0,!0,!0,!0]).slice(),this.borderLineWidth=(t.borderLineWidth||[2,2,2,2]).slice(),this.borderLineColor=c(t.borderLineColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);var a=t.ticks||[[],[]],o=this._tickBounds;o[0]=o[1]=1/0,o[2]=o[3]=-1/0;for(var s=0;s<2;++s){var l=a[s].slice(0);0!==l.length&&(l.sort(f),o[s]=Math.min(o[s],l[0].x),o[s+2]=Math.max(o[s+2],l[l.length-1].x))}this.grid.update({bounds:o,ticks:a}),this.text.update({bounds:o,ticks:a,labels:t.labels||[\"x\",\"y\"],labelSize:t.labelSize||[12,12],labelFont:t.labelFont||[\"sans-serif\",\"sans-serif\"],title:t.title||\"\",titleSize:t.titleSize||18,titleFont:t.titleFont||\"sans-serif\"}),this.static=!!t.static,this.setDirty()},u.dispose=function(){this.box.dispose(),this.grid.dispose(),this.text.dispose(),this.line.dispose();for(var t=this.objects.length-1;t>=0;--t)this.objects[t].dispose();for(this.objects.length=0,t=this.overlays.length-1;t>=0;--t)this.overlays[t].dispose();this.overlays.length=0,this.gl=null},u.addObject=function(t){this.objects.indexOf(t)<0&&(this.objects.push(t),this.setDirty())},u.removeObject=function(t){for(var e=this.objects,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setDirty();break}},u.addOverlay=function(t){this.overlays.indexOf(t)<0&&(this.overlays.push(t),this.setOverlayDirty())},u.removeOverlay=function(t){for(var e=this.overlays,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setOverlayDirty();break}}},4296:function(t,e,r){\"use strict\";t.exports=function(t,e){t=t||document.body;var r=[.01,1/0];\"distanceLimits\"in(e=e||{})&&(r[0]=e.distanceLimits[0],r[1]=e.distanceLimits[1]),\"zoomMin\"in e&&(r[0]=e.zoomMin),\"zoomMax\"in e&&(r[1]=e.zoomMax);var u=i({center:e.center||[0,0,0],up:e.up||[0,1,0],eye:e.eye||[0,0,10],mode:e.mode||\"orbit\",distanceLimits:r}),c=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],f=0,h=t.clientWidth,p=t.clientHeight,d={keyBindingMode:\"rotate\",enableWheel:!0,view:u,element:t,delay:e.delay||16,rotateSpeed:e.rotateSpeed||1,zoomSpeed:e.zoomSpeed||1,translateSpeed:e.translateSpeed||1,flipX:!!e.flipX,flipY:!!e.flipY,modes:u.modes,_ortho:e._ortho||e.projection&&\"orthographic\"===e.projection.type||!1,tick:function(){var e=n(),r=this.delay,i=e-2*r;u.idle(e-r),u.recalcMatrix(i),u.flush(e-(100+2*r));for(var a=!0,o=u.computedMatrix,s=0;s<16;++s)a=a&&c[s]===o[s],c[s]=o[s];var l=t.clientWidth===h&&t.clientHeight===p;return h=t.clientWidth,p=t.clientHeight,a?!l:(f=Math.exp(u.computedRadius[0]),!0)},lookAt:function(t,e,r){u.lookAt(u.lastT(),t,e,r)},rotate:function(t,e,r){u.rotate(u.lastT(),t,e,r)},pan:function(t,e,r){u.pan(u.lastT(),t,e,r)},translate:function(t,e,r){u.translate(u.lastT(),t,e,r)}};return Object.defineProperties(d,{matrix:{get:function(){return u.computedMatrix},set:function(t){return u.setMatrix(u.lastT(),t),u.computedMatrix},enumerable:!0},mode:{get:function(){return u.getMode()},set:function(t){var e=u.computedUp.slice(),r=u.computedEye.slice(),i=u.computedCenter.slice();if(u.setMode(t),\"turntable\"===t){var a=n();u._active.lookAt(a,r,i,e),u._active.lookAt(a+500,r,i,[0,0,1]),u._active.flush(a)}return u.getMode()},enumerable:!0},center:{get:function(){return u.computedCenter},set:function(t){return u.lookAt(u.lastT(),null,t),u.computedCenter},enumerable:!0},eye:{get:function(){return u.computedEye},set:function(t){return u.lookAt(u.lastT(),t),u.computedEye},enumerable:!0},up:{get:function(){return u.computedUp},set:function(t){return u.lookAt(u.lastT(),null,null,t),u.computedUp},enumerable:!0},distance:{get:function(){return f},set:function(t){return u.setDistance(u.lastT(),t),t},enumerable:!0},distanceLimits:{get:function(){return u.getDistanceLimits(r)},set:function(t){return u.setDistanceLimits(t),t},enumerable:!0}}),t.addEventListener(\"contextmenu\",(function(t){return t.preventDefault(),!1})),d._lastX=-1,d._lastY=-1,d._lastMods={shift:!1,control:!1,alt:!1,meta:!1},d.enableMouseListeners=function(){function e(e,r,i,a){var o=d.keyBindingMode;if(!1!==o){var s=\"rotate\"===o,l=\"pan\"===o,c=\"zoom\"===o,h=!!a.control,p=!!a.alt,v=!!a.shift,g=!!(1&e),y=!!(2&e),m=!!(4&e),x=1/t.clientHeight,b=x*(r-d._lastX),_=x*(i-d._lastY),w=d.flipX?1:-1,T=d.flipY?1:-1,k=Math.PI*d.rotateSpeed,A=n();if(-1!==d._lastX&&-1!==d._lastY&&((s&&g&&!h&&!p&&!v||g&&!h&&!p&&v)&&u.rotate(A,w*k*b,-T*k*_,0),(l&&g&&!h&&!p&&!v||y||g&&h&&!p&&!v)&&u.pan(A,-d.translateSpeed*b*f,d.translateSpeed*_*f,0),c&&g&&!h&&!p&&!v||m||g&&!h&&p&&!v)){var M=-d.zoomSpeed*_/window.innerHeight*(A-u.lastT())*100;u.pan(A,0,0,f*(Math.exp(M)-1))}return d._lastX=r,d._lastY=i,d._lastMods=a,!0}}d.mouseListener=a(t,e),t.addEventListener(\"touchstart\",(function(r){var n=s(r.changedTouches[0],t);e(0,n[0],n[1],d._lastMods),e(1,n[0],n[1],d._lastMods)}),!!l&&{passive:!0}),t.addEventListener(\"touchmove\",(function(r){var n=s(r.changedTouches[0],t);e(1,n[0],n[1],d._lastMods),r.preventDefault()}),!!l&&{passive:!1}),t.addEventListener(\"touchend\",(function(t){e(0,d._lastX,d._lastY,d._lastMods)}),!!l&&{passive:!0}),d.wheelListener=o(t,(function(t,e){if(!1!==d.keyBindingMode&&d.enableWheel){var r=d.flipX?1:-1,i=d.flipY?1:-1,a=n();if(Math.abs(t)>Math.abs(e))u.rotate(a,0,0,-t*r*Math.PI*d.rotateSpeed/window.innerWidth);else if(!d._ortho){var o=-d.zoomSpeed*i*e/window.innerHeight*(a-u.lastT())/20;u.pan(a,0,0,f*(Math.exp(o)-1))}}}),!0)},d.enableMouseListeners(),d};var n=r(8161),i=r(1152),a=r(6145),o=r(6475),s=r(2565),l=r(5233)},8245:function(t,e,r){var n=r(6832),i=r(5158),a=n([\"precision mediump float;\\n#define GLSLIFY 1\\nattribute vec2 position;\\nvarying vec2 uv;\\nvoid main() {\\n  uv = position;\\n  gl_Position = vec4(position, 0, 1);\\n}\"]),o=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D accumBuffer;\\nvarying vec2 uv;\\n\\nvoid main() {\\n  vec4 accum = texture2D(accumBuffer, 0.5 * (uv + 1.0));\\n  gl_FragColor = min(vec4(1,1,1,1), accum);\\n}\"]);t.exports=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec2\"}])}},1059:function(t,e,r){\"use strict\";var n=r(4296),i=r(7453),a=r(2771),o=r(6496),s=r(2611),l=r(4234),u=r(8126),c=r(6145),f=r(1120),h=r(5268),p=r(8245),d=r(2321)({tablet:!0,featureDetect:!0});function v(){this.mouse=[-1,-1],this.screen=null,this.distance=1/0,this.index=null,this.dataCoordinate=null,this.dataPosition=null,this.object=null,this.data=null}function g(t){var e=Math.round(Math.log(Math.abs(t))/Math.log(10));if(e<0){var r=Math.round(Math.pow(10,-e));return Math.ceil(t*r)/r}return e>0?(r=Math.round(Math.pow(10,e)),Math.ceil(t/r)*r):Math.ceil(t)}function y(t){return\"boolean\"!=typeof t||t}t.exports={createScene:function(t){(t=t||{}).camera=t.camera||{};var e=t.canvas;e||(e=document.createElement(\"canvas\"),t.container?t.container.appendChild(e):document.body.appendChild(e));var r=t.gl;if(r||(t.glOptions&&(d=!!t.glOptions.preserveDrawingBuffer),r=function(t,e){var r=null;try{(r=t.getContext(\"webgl\",e))||(r=t.getContext(\"experimental-webgl\",e))}catch(t){return null}return r}(e,t.glOptions||{premultipliedAlpha:!0,antialias:!0,preserveDrawingBuffer:d})),!r)throw new Error(\"webgl not supported\");var m=t.bounds||[[-10,-10,-10],[10,10,10]],x=new v,b=l(r,r.drawingBufferWidth,r.drawingBufferHeight,{preferFloat:!d}),_=p(r),w=t.cameraObject&&!0===t.cameraObject._ortho||t.camera.projection&&\"orthographic\"===t.camera.projection.type||!1,T={eye:t.camera.eye||[2,0,0],center:t.camera.center||[0,0,0],up:t.camera.up||[0,1,0],zoomMin:t.camera.zoomMax||.1,zoomMax:t.camera.zoomMin||100,mode:t.camera.mode||\"turntable\",_ortho:w},k=t.axes||{},A=i(r,k);A.enable=!k.disable;var M=t.spikes||{},S=o(r,M),E=[],L=[],C=[],P=[],O=!0,I=!0,D={view:null,projection:new Array(16),model:new Array(16),_ortho:!1},z=(I=!0,[r.drawingBufferWidth,r.drawingBufferHeight]),R=t.cameraObject||n(e,T),F={gl:r,contextLost:!1,pixelRatio:t.pixelRatio||1,canvas:e,selection:x,camera:R,axes:A,axesPixels:null,spikes:S,bounds:m,objects:E,shape:z,aspect:t.aspectRatio||[1,1,1],pickRadius:t.pickRadius||10,zNear:t.zNear||.01,zFar:t.zFar||1e3,fovy:t.fovy||Math.PI/4,clearColor:t.clearColor||[0,0,0,0],autoResize:y(t.autoResize),autoBounds:y(t.autoBounds),autoScale:!!t.autoScale,autoCenter:y(t.autoCenter),clipToBounds:y(t.clipToBounds),snapToData:!!t.snapToData,onselect:t.onselect||null,onrender:t.onrender||null,onclick:t.onclick||null,cameraParams:D,oncontextloss:null,mouseListener:null,_stopped:!1,getAspectratio:function(){return{x:this.aspect[0],y:this.aspect[1],z:this.aspect[2]}},setAspectratio:function(t){this.aspect[0]=t.x,this.aspect[1]=t.y,this.aspect[2]=t.z,I=!0},setBounds:function(t,e){this.bounds[0][t]=e.min,this.bounds[1][t]=e.max},setClearColor:function(t){this.clearColor=t},clearRGBA:function(){this.gl.clearColor(this.clearColor[0],this.clearColor[1],this.clearColor[2],this.clearColor[3]),this.gl.clear(this.gl.COLOR_BUFFER_BIT|this.gl.DEPTH_BUFFER_BIT)}},B=[r.drawingBufferWidth/F.pixelRatio|0,r.drawingBufferHeight/F.pixelRatio|0];function N(){if(!F._stopped&&F.autoResize){var t=e.parentNode,r=1,n=1;t&&t!==document.body?(r=t.clientWidth,n=t.clientHeight):(r=window.innerWidth,n=window.innerHeight);var i=0|Math.ceil(r*F.pixelRatio),a=0|Math.ceil(n*F.pixelRatio);if(i!==e.width||a!==e.height){e.width=i,e.height=a;var o=e.style;o.position=o.position||\"absolute\",o.left=\"0px\",o.top=\"0px\",o.width=r+\"px\",o.height=n+\"px\",O=!0}}}function j(){for(var t=E.length,e=P.length,n=0;n<e;++n)C[n]=0;t:for(n=0;n<t;++n){var i=E[n],a=i.pickSlots;if(a){for(var o=0;o<e;++o)if(C[o]+a<255){L[n]=o,i.setPickBase(C[o]+1),C[o]+=a;continue t}var l=s(r,z);L[n]=e,P.push(l),C.push(a),i.setPickBase(1),e+=1}else L[n]=-1}for(;e>0&&0===C[e-1];)C.pop(),P.pop().dispose()}function U(){if(F.contextLost)return!0;r.isContextLost()&&(F.contextLost=!0,F.mouseListener.enabled=!1,F.selection.object=null,F.oncontextloss&&F.oncontextloss())}F.autoResize&&N(),window.addEventListener(\"resize\",N),F.update=function(t){F._stopped||(t=t||{},O=!0,I=!0)},F.add=function(t){F._stopped||(t.axes=A,E.push(t),L.push(-1),O=!0,I=!0,j())},F.remove=function(t){if(!F._stopped){var e=E.indexOf(t);e<0||(E.splice(e,1),L.pop(),O=!0,I=!0,j())}},F.dispose=function(){if(!F._stopped&&(F._stopped=!0,window.removeEventListener(\"resize\",N),e.removeEventListener(\"webglcontextlost\",U),F.mouseListener.enabled=!1,!F.contextLost)){A.dispose(),S.dispose();for(var t=0;t<E.length;++t)E[t].dispose();for(b.dispose(),t=0;t<P.length;++t)P[t].dispose();_.dispose(),r=null,A=null,S=null,E=[]}},F._mouseRotating=!1,F._prevButtons=0,F.enableMouseListeners=function(){F.mouseListener=c(e,(function(t,e,r){if(!F._stopped){var n=P.length,i=E.length,a=x.object;x.distance=1/0,x.mouse[0]=e,x.mouse[1]=r,x.object=null,x.screen=null,x.dataCoordinate=x.dataPosition=null;var o=!1;if(t&&F._prevButtons)F._mouseRotating=!0;else{F._mouseRotating&&(I=!0),F._mouseRotating=!1;for(var s=0;s<n;++s){var l=P[s].query(e,B[1]-r-1,F.pickRadius);if(l){if(l.distance>x.distance)continue;for(var u=0;u<i;++u){var c=E[u];if(L[u]===s){var f=c.pick(l);f&&(x.buttons=t,x.screen=l.coord,x.distance=l.distance,x.object=c,x.index=f.distance,x.dataPosition=f.position,x.dataCoordinate=f.dataCoordinate,x.data=f,o=!0)}}}}}a&&a!==x.object&&(a.highlight&&a.highlight(null),O=!0),x.object&&(x.object.highlight&&x.object.highlight(x.data),O=!0),(o=o||x.object!==a)&&F.onselect&&F.onselect(x),1&t&&!(1&F._prevButtons)&&F.onclick&&F.onclick(x),F._prevButtons=t}}))},e.addEventListener(\"webglcontextlost\",U);var V=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],q=[V[0].slice(),V[1].slice()];function H(){if(!U()){N();var t=F.camera.tick();D.view=F.camera.matrix,O=O||t,I=I||t,A.pixelRatio=F.pixelRatio,S.pixelRatio=F.pixelRatio;var e=E.length,n=V[0],i=V[1];n[0]=n[1]=n[2]=1/0,i[0]=i[1]=i[2]=-1/0;for(var o=0;o<e;++o){(C=E[o]).pixelRatio=F.pixelRatio,C.axes=F.axes,O=O||!!C.dirty,I=I||!!C.dirty;var s=C.bounds;if(s)for(var l=s[0],c=s[1],p=0;p<3;++p)n[p]=Math.min(n[p],l[p]),i[p]=Math.max(i[p],c[p])}var d=F.bounds;if(F.autoBounds)for(p=0;p<3;++p){if(i[p]<n[p])n[p]=-1,i[p]=1;else{n[p]===i[p]&&(n[p]-=1,i[p]+=1);var v=.05*(i[p]-n[p]);n[p]=n[p]-v,i[p]=i[p]+v}d[0][p]=n[p],d[1][p]=i[p]}var y=!1;for(p=0;p<3;++p)y=y||q[0][p]!==d[0][p]||q[1][p]!==d[1][p],q[0][p]=d[0][p],q[1][p]=d[1][p];if(I=I||y,O=O||y){if(y){var m=[0,0,0];for(o=0;o<3;++o)m[o]=g((d[1][o]-d[0][o])/10);A.autoTicks?A.update({bounds:d,tickSpacing:m}):A.update({bounds:d})}var T=r.drawingBufferWidth,k=r.drawingBufferHeight;for(z[0]=T,z[1]=k,B[0]=0|Math.max(T/F.pixelRatio,1),B[1]=0|Math.max(k/F.pixelRatio,1),function(t,e){var r=t.bounds,n=t.cameraParams,i=n.projection,a=n.model,o=t.gl.drawingBufferWidth,s=t.gl.drawingBufferHeight,l=t.zNear,u=t.zFar,c=t.fovy,p=o/s;e?(h(i,-p,p,-1,1,l,u),n._ortho=!0):(f(i,c,p,l,u),n._ortho=!1);for(var d=0;d<16;++d)a[d]=0;a[15]=1;var v=0;for(d=0;d<3;++d)v=Math.max(v,r[1][d]-r[0][d]);for(d=0;d<3;++d)t.autoScale?a[5*d]=t.aspect[d]/(r[1][d]-r[0][d]):a[5*d]=1/v,t.autoCenter&&(a[12+d]=.5*-a[5*d]*(r[0][d]+r[1][d]))}(F,w),o=0;o<e;++o)(C=E[o]).axesBounds=d,F.clipToBounds&&(C.clipBounds=d);x.object&&(F.snapToData?S.position=x.dataCoordinate:S.position=x.dataPosition,S.bounds=d),I&&(I=!1,function(){if(!U()){r.colorMask(!0,!0,!0,!0),r.depthMask(!0),r.disable(r.BLEND),r.enable(r.DEPTH_TEST),r.depthFunc(r.LEQUAL);for(var t=E.length,e=P.length,n=0;n<e;++n){var i=P[n];i.shape=B,i.begin();for(var a=0;a<t;++a)if(L[a]===n){var o=E[a];o.drawPick&&(o.pixelRatio=1,o.drawPick(D))}i.end()}}}()),F.axesPixels=a(F.axes,D,T,k),F.onrender&&F.onrender(),r.bindFramebuffer(r.FRAMEBUFFER,null),r.viewport(0,0,T,k),F.clearRGBA(),r.depthMask(!0),r.colorMask(!0,!0,!0,!0),r.enable(r.DEPTH_TEST),r.depthFunc(r.LEQUAL),r.disable(r.BLEND),r.disable(r.CULL_FACE);var M=!1;for(A.enable&&(M=M||A.isTransparent(),A.draw(D)),S.axes=A,x.object&&S.draw(D),r.disable(r.CULL_FACE),o=0;o<e;++o)(C=E[o]).axes=A,C.pixelRatio=F.pixelRatio,C.isOpaque&&C.isOpaque()&&C.draw(D),C.isTransparent&&C.isTransparent()&&(M=!0);if(M){for(b.shape=z,b.bind(),r.clear(r.DEPTH_BUFFER_BIT),r.colorMask(!1,!1,!1,!1),r.depthMask(!0),r.depthFunc(r.LESS),A.enable&&A.isTransparent()&&A.drawTransparent(D),o=0;o<e;++o)(C=E[o]).isOpaque&&C.isOpaque()&&C.draw(D);for(r.enable(r.BLEND),r.blendEquation(r.FUNC_ADD),r.blendFunc(r.ONE,r.ONE_MINUS_SRC_ALPHA),r.colorMask(!0,!0,!0,!0),r.depthMask(!1),r.clearColor(0,0,0,0),r.clear(r.COLOR_BUFFER_BIT),A.isTransparent()&&A.drawTransparent(D),o=0;o<e;++o){var C;(C=E[o]).isTransparent&&C.isTransparent()&&C.drawTransparent(D)}r.bindFramebuffer(r.FRAMEBUFFER,null),r.blendFunc(r.ONE,r.ONE_MINUS_SRC_ALPHA),r.disable(r.DEPTH_TEST),_.bind(),b.color[0].bind(0),_.uniforms.accumBuffer=0,u(r),r.disable(r.BLEND)}for(O=!1,o=0;o<e;++o)E[o].dirty=!1}}}return F.enableMouseListeners(),function t(){F._stopped||F.contextLost||(H(),requestAnimationFrame(t))}(),F.redraw=function(){F._stopped||(O=!0,H())},F},createCamera:n}},8023:function(t,e,r){var n=r(6832);e.pointVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform float pointCloud;\\n\\nhighp float rand(vec2 co) {\\n  highp float a = 12.9898;\\n  highp float b = 78.233;\\n  highp float c = 43758.5453;\\n  highp float d = dot(co.xy, vec2(a, b));\\n  highp float e = mod(d, 3.14);\\n  return fract(sin(e) * c);\\n}\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n    // if we don't jitter the point size a bit, overall point cloud\\n    // saturation 'jumps' on zooming, which is disturbing and confusing\\n  gl_PointSize = pointSize * ((19.5 + rand(position)) / 20.0);\\n  if(pointCloud != 0.0) { // pointCloud is truthy\\n    // get the same square surface as circle would be\\n    gl_PointSize *= 0.886;\\n  }\\n}\"]),e.pointFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color, borderColor;\\nuniform float centerFraction;\\nuniform float pointCloud;\\n\\nvoid main() {\\n  float radius;\\n  vec4 baseColor;\\n  if(pointCloud != 0.0) { // pointCloud is truthy\\n    if(centerFraction == 1.0) {\\n      gl_FragColor = color;\\n    } else {\\n      gl_FragColor = mix(borderColor, color, centerFraction);\\n    }\\n  } else {\\n    radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n    if(radius > 1.0) {\\n      discard;\\n    }\\n    baseColor = mix(borderColor, color, step(radius, centerFraction));\\n    gl_FragColor = vec4(baseColor.rgb * baseColor.a, baseColor.a);\\n  }\\n}\\n\"]),e.pickVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n  gl_PointSize = pointSize;\\n\\n  vec4 id = pickId + pickOffset;\\n  id.y += floor(id.x / 256.0);\\n  id.x -= floor(id.x / 256.0) * 256.0;\\n\\n  id.z += floor(id.y / 256.0);\\n  id.y -= floor(id.y / 256.0) * 256.0;\\n\\n  id.w += floor(id.z / 256.0);\\n  id.z -= floor(id.z / 256.0) * 256.0;\\n\\n  fragId = id;\\n}\\n\"]),e.pickFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  float radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n  if(radius > 1.0) {\\n    discard;\\n  }\\n  gl_FragColor = fragId / 255.0;\\n}\\n\"])},8271:function(t,e,r){\"use strict\";var n=r(5158),i=r(5827),a=r(5306),o=r(8023);function s(t,e,r,n,i){this.plot=t,this.offsetBuffer=e,this.pickBuffer=r,this.shader=n,this.pickShader=i,this.sizeMin=.5,this.sizeMinCap=2,this.sizeMax=20,this.areaRatio=1,this.pointCount=0,this.color=[1,0,0,1],this.borderColor=[0,0,0,1],this.blend=!1,this.pickOffset=0,this.points=null}t.exports=function(t,e){var r=t.gl,a=new s(t,i(r),i(r),n(r,o.pointVertex,o.pointFragment),n(r,o.pickVertex,o.pickFragment));return a.update(e),t.addObject(a),a};var l,u,c=s.prototype;c.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.offsetBuffer.dispose(),this.pickBuffer.dispose(),this.plot.removeObject(this)},c.update=function(t){var e;function r(e,r){return e in t?t[e]:r}t=t||{},this.sizeMin=r(\"sizeMin\",.5),this.sizeMax=r(\"sizeMax\",20),this.color=r(\"color\",[1,0,0,1]).slice(),this.areaRatio=r(\"areaRatio\",1),this.borderColor=r(\"borderColor\",[0,0,0,1]).slice(),this.blend=r(\"blend\",!1);var n=t.positions.length>>>1,i=t.positions instanceof Float32Array,o=t.idToIndex instanceof Int32Array&&t.idToIndex.length>=n,s=t.positions,l=i?s:a.mallocFloat32(s.length),u=o?t.idToIndex:a.mallocInt32(n);if(i||l.set(s),!o)for(l.set(s),e=0;e<n;e++)u[e]=e;this.points=s,this.offsetBuffer.update(l),this.pickBuffer.update(u),i||a.free(l),o||a.free(u),this.pointCount=n,this.pickOffset=0},c.unifiedDraw=(l=[1,0,0,0,1,0,0,0,1],u=[0,0,0,0],function(t){var e=void 0!==t,r=e?this.pickShader:this.shader,n=this.plot.gl,i=this.plot.dataBox;if(0===this.pointCount)return t;var a=i[2]-i[0],o=i[3]-i[1],s=function(t,e){var r,n=0,i=t.length>>>1;for(r=0;r<i;r++){var a=t[2*r],o=t[2*r+1];a>=e[0]&&a<=e[2]&&o>=e[1]&&o<=e[3]&&n++}return n}(this.points,i),c=this.plot.pickPixelRatio*Math.max(Math.min(this.sizeMinCap,this.sizeMin),Math.min(this.sizeMax,this.sizeMax/Math.pow(s,.33333)));l[0]=2/a,l[4]=2/o,l[6]=-2*i[0]/a-1,l[7]=-2*i[1]/o-1,this.offsetBuffer.bind(),r.bind(),r.attributes.position.pointer(),r.uniforms.matrix=l,r.uniforms.color=this.color,r.uniforms.borderColor=this.borderColor,r.uniforms.pointCloud=c<5,r.uniforms.pointSize=c,r.uniforms.centerFraction=Math.min(1,Math.max(0,Math.sqrt(1-this.areaRatio))),e&&(u[0]=255&t,u[1]=t>>8&255,u[2]=t>>16&255,u[3]=t>>24&255,this.pickBuffer.bind(),r.attributes.pickId.pointer(n.UNSIGNED_BYTE),r.uniforms.pickOffset=u,this.pickOffset=t);var f=n.getParameter(n.BLEND),h=n.getParameter(n.DITHER);return f&&!this.blend&&n.disable(n.BLEND),h&&n.disable(n.DITHER),n.drawArrays(n.POINTS,0,this.pointCount),f&&!this.blend&&n.enable(n.BLEND),h&&n.enable(n.DITHER),t+this.pointCount}),c.draw=c.unifiedDraw,c.drawPick=c.unifiedDraw,c.pick=function(t,e,r){var n=this.pickOffset,i=this.pointCount;if(r<n||r>=n+i)return null;var a=r-n,o=this.points;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}}},6093:function(t){t.exports=function(t,e,r,n){var i,a,o,s,l,u=e[0],c=e[1],f=e[2],h=e[3],p=r[0],d=r[1],v=r[2],g=r[3];return(a=u*p+c*d+f*v+h*g)<0&&(a=-a,p=-p,d=-d,v=-v,g=-g),1-a>1e-6?(i=Math.acos(a),o=Math.sin(i),s=Math.sin((1-n)*i)/o,l=Math.sin(n*i)/o):(s=1-n,l=n),t[0]=s*u+l*p,t[1]=s*c+l*d,t[2]=s*f+l*v,t[3]=s*h+l*g,t}},8240:function(t){\"use strict\";t.exports=function(t){return t||0===t?t.toString():\"\"}},4123:function(t,e,r){\"use strict\";var n=r(875);t.exports=function(t,e,r){var a=i[e];if(a||(a=i[e]={}),t in a)return a[t];var o={textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e,lineSpacing:1.25,styletags:{breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0},triangles:!0},s=n(t,o);o.triangles=!1;var l,u,c=n(t,o);if(r&&1!==r){for(l=0;l<s.positions.length;++l)for(u=0;u<s.positions[l].length;++u)s.positions[l][u]/=r;for(l=0;l<c.positions.length;++l)for(u=0;u<c.positions[l].length;++u)c.positions[l][u]/=r}var f=[[1/0,1/0],[-1/0,-1/0]],h=c.positions.length;for(l=0;l<h;++l){var p=c.positions[l];for(u=0;u<2;++u)f[0][u]=Math.min(f[0][u],p[u]),f[1][u]=Math.max(f[1][u],p[u])}return a[t]=[s,c,f]};var i={}},9282:function(t,e,r){var n=r(5158),i=r(6832),a=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform vec4 highlightId;\\nuniform float highlightScale;\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = 1.0;\\n    if(distance(highlightId, id) < 0.0001) {\\n      scale = highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1);\\n    vec4 viewPosition = view * worldPosition;\\n    viewPosition = viewPosition / viewPosition.w;\\n    vec4 clipPosition = projection * (viewPosition + scale * vec4(glyph.x, -glyph.y, 0, 0));\\n\\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\"]),o=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float highlightScale, pixelRatio;\\nuniform vec4 highlightId;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = pixelRatio;\\n    if(distance(highlightId.bgr, id.bgr) < 0.001) {\\n      scale *= highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1.0);\\n    vec4 viewPosition = view * worldPosition;\\n    vec4 clipPosition = projection * viewPosition;\\n    clipPosition /= clipPosition.w;\\n\\n    gl_Position = clipPosition + vec4(screenSize * scale * vec2(glyph.x, -glyph.y), 0.0, 0.0);\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\"]),s=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform float highlightScale;\\nuniform vec4 highlightId;\\nuniform vec3 axes[2];\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float scale, pixelRatio;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float lscale = pixelRatio * scale;\\n    if(distance(highlightId, id) < 0.0001) {\\n      lscale *= highlightScale;\\n    }\\n\\n    vec4 clipCenter   = projection * view * model * vec4(position, 1);\\n    vec3 dataPosition = position + 0.5*lscale*(axes[0] * glyph.x + axes[1] * glyph.y) * clipCenter.w * screenSize.y;\\n    vec4 clipPosition = projection * view * model * vec4(dataPosition, 1);\\n\\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = dataPosition;\\n  }\\n}\\n\"]),l=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float opacity;\\n\\nvarying vec4 interpColor;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (\\n    outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate) ||\\n    interpColor.a * opacity == 0.\\n  ) discard;\\n  gl_FragColor = interpColor * opacity;\\n}\\n\"]),u=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float pickGroup;\\n\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate)) discard;\\n\\n  gl_FragColor = vec4(pickGroup, pickId.bgr);\\n}\"]),c=[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"glyph\",type:\"vec2\"},{name:\"id\",type:\"vec4\"}],f={vertex:a,fragment:l,attributes:c},h={vertex:o,fragment:l,attributes:c},p={vertex:s,fragment:l,attributes:c},d={vertex:a,fragment:u,attributes:c},v={vertex:o,fragment:u,attributes:c},g={vertex:s,fragment:u,attributes:c};function y(t,e){var r=n(t,e),i=r.attributes;return i.position.location=0,i.color.location=1,i.glyph.location=2,i.id.location=3,r}e.createPerspective=function(t){return y(t,f)},e.createOrtho=function(t){return y(t,h)},e.createProject=function(t){return y(t,p)},e.createPickPerspective=function(t){return y(t,d)},e.createPickOrtho=function(t){return y(t,v)},e.createPickProject=function(t){return y(t,g)}},2182:function(t,e,r){\"use strict\";var n=r(3596),i=r(5827),a=r(2944),o=r(5306),s=r(104),l=r(9282),u=r(4123),c=r(8240),f=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function h(t,e){var r=t[0],n=t[1],i=t[2],a=t[3];return t[0]=e[0]*r+e[4]*n+e[8]*i+e[12]*a,t[1]=e[1]*r+e[5]*n+e[9]*i+e[13]*a,t[2]=e[2]*r+e[6]*n+e[10]*i+e[14]*a,t[3]=e[3]*r+e[7]*n+e[11]*i+e[15]*a,t}function p(t,e,r,n){return h(n,n),h(n,n),h(n,n)}function d(t,e){this.index=t,this.dataCoordinate=this.position=e}function v(t){return!0===t||t>1?1:t}function g(t,e,r,n,i,a,o,s,l,u,c,f){this.gl=t,this.pixelRatio=1,this.shader=e,this.orthoShader=r,this.projectShader=n,this.pointBuffer=i,this.colorBuffer=a,this.glyphBuffer=o,this.idBuffer=s,this.vao=l,this.vertexCount=0,this.lineVertexCount=0,this.opacity=1,this.hasAlpha=!1,this.lineWidth=0,this.projectScale=[2/3,2/3,2/3],this.projectOpacity=[1,1,1],this.projectHasAlpha=!1,this.pickId=0,this.pickPerspectiveShader=u,this.pickOrthoShader=c,this.pickProjectShader=f,this.points=[],this._selectResult=new d(0,[0,0,0]),this.useOrtho=!0,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.axesProject=[!0,!0,!0],this.axesBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.highlightId=[1,1,1,1],this.highlightScale=2,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.dirty=!0}t.exports=function(t){var e=t.gl,r=l.createPerspective(e),n=l.createOrtho(e),o=l.createProject(e),s=l.createPickPerspective(e),u=l.createPickOrtho(e),c=l.createPickProject(e),f=i(e),h=i(e),p=i(e),d=i(e),v=new g(e,r,n,o,f,h,p,d,a(e,[{buffer:f,size:3,type:e.FLOAT},{buffer:h,size:4,type:e.FLOAT},{buffer:p,size:2,type:e.FLOAT},{buffer:d,size:4,type:e.UNSIGNED_BYTE,normalized:!0}]),s,u,c);return v.update(t),v};var y=g.prototype;y.pickSlots=1,y.setPickBase=function(t){this.pickId=t},y.isTransparent=function(){if(this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&this.projectHasAlpha)return!0;return!1},y.isOpaque=function(){if(!this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&!this.projectHasAlpha)return!0;return!1};var m=[0,0],x=[0,0,0],b=[0,0,0],_=[0,0,0,1],w=[0,0,0,1],T=f.slice(),k=[0,0,0],A=[[0,0,0],[0,0,0]];function M(t){return t[0]=t[1]=t[2]=0,t}function S(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=1,t}function E(t,e,r,n){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[r]=n,t}var L=[[-1e8,-1e8,-1e8],[1e8,1e8,1e8]];function C(t,e,r,n,i,a,o){var l=r.gl;if((a===r.projectHasAlpha||o)&&function(t,e,r,n){var i,a=e.axesProject,o=e.gl,l=t.uniforms,u=r.model||f,c=r.view||f,h=r.projection||f,d=e.axesBounds,v=function(t){for(var e=A,r=0;r<2;++r)for(var n=0;n<3;++n)e[r][n]=Math.max(Math.min(t[r][n],1e8),-1e8);return e}(e.clipBounds);i=e.axes&&e.axes.lastCubeProps?e.axes.lastCubeProps.axis:[1,1,1],m[0]=2/o.drawingBufferWidth,m[1]=2/o.drawingBufferHeight,t.bind(),l.view=c,l.projection=h,l.screenSize=m,l.highlightId=e.highlightId,l.highlightScale=e.highlightScale,l.clipBounds=v,l.pickGroup=e.pickId/255,l.pixelRatio=n;for(var g=0;g<3;++g)if(a[g]){l.scale=e.projectScale[g],l.opacity=e.projectOpacity[g];for(var y=T,L=0;L<16;++L)y[L]=0;for(L=0;L<4;++L)y[5*L]=1;y[5*g]=0,i[g]<0?y[12+g]=d[0][g]:y[12+g]=d[1][g],s(y,u,y),l.model=y;var C=(g+1)%3,P=(g+2)%3,O=M(x),I=M(b);O[C]=1,I[P]=1;var D=p(0,0,0,S(_,O)),z=p(0,0,0,S(w,I));if(Math.abs(D[1])>Math.abs(z[1])){var R=D;D=z,z=R,R=O,O=I,I=R;var F=C;C=P,P=F}D[0]<0&&(O[C]=-1),z[1]>0&&(I[P]=-1);var B=0,N=0;for(L=0;L<4;++L)B+=Math.pow(u[4*C+L],2),N+=Math.pow(u[4*P+L],2);O[C]/=Math.sqrt(B),I[P]/=Math.sqrt(N),l.axes[0]=O,l.axes[1]=I,l.fragClipBounds[0]=E(k,v[0],g,-1e8),l.fragClipBounds[1]=E(k,v[1],g,1e8),e.vao.bind(),e.vao.draw(o.TRIANGLES,e.vertexCount),e.lineWidth>0&&(o.lineWidth(e.lineWidth*n),e.vao.draw(o.LINES,e.lineVertexCount,e.vertexCount)),e.vao.unbind()}}(e,r,n,i),a===r.hasAlpha||o){t.bind();var u=t.uniforms;u.model=n.model||f,u.view=n.view||f,u.projection=n.projection||f,m[0]=2/l.drawingBufferWidth,m[1]=2/l.drawingBufferHeight,u.screenSize=m,u.highlightId=r.highlightId,u.highlightScale=r.highlightScale,u.fragClipBounds=L,u.clipBounds=r.axes.bounds,u.opacity=r.opacity,u.pickGroup=r.pickId/255,u.pixelRatio=i,r.vao.bind(),r.vao.draw(l.TRIANGLES,r.vertexCount),r.lineWidth>0&&(l.lineWidth(r.lineWidth*i),r.vao.draw(l.LINES,r.lineVertexCount,r.vertexCount)),r.vao.unbind()}}function P(t,e,r,i){var a;a=Array.isArray(t)?e<t.length?t[e]:void 0:t,a=c(a);var o=!0;n(a)&&(a=\"▼\",o=!1);var s=u(a,r,i);return{mesh:s[0],lines:s[1],bounds:s[2],visible:o}}y.draw=function(t){C(this.useOrtho?this.orthoShader:this.shader,this.projectShader,this,t,this.pixelRatio,!1,!1)},y.drawTransparent=function(t){C(this.useOrtho?this.orthoShader:this.shader,this.projectShader,this,t,this.pixelRatio,!0,!1)},y.drawPick=function(t){C(this.useOrtho?this.pickOrthoShader:this.pickPerspectiveShader,this.pickProjectShader,this,t,1,!0,!0)},y.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[2]+(t.value[1]<<8)+(t.value[0]<<16);if(e>=this.pointCount||e<0)return null;var r=this.points[e],n=this._selectResult;n.index=e;for(var i=0;i<3;++i)n.position[i]=n.dataCoordinate[i]=r[i];return n},y.highlight=function(t){if(t){var e=t.index,r=255&e,n=e>>8&255,i=e>>16&255;this.highlightId=[r/255,n/255,i/255,0]}else this.highlightId=[1,1,1,1]},y.update=function(t){if(\"perspective\"in(t=t||{})&&(this.useOrtho=!t.perspective),\"orthographic\"in t&&(this.useOrtho=!!t.orthographic),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"project\"in t)if(Array.isArray(t.project))this.axesProject=t.project;else{var e=!!t.project;this.axesProject=[e,e,e]}if(\"projectScale\"in t)if(Array.isArray(t.projectScale))this.projectScale=t.projectScale.slice();else{var r=+t.projectScale;this.projectScale=[r,r,r]}if(this.projectHasAlpha=!1,\"projectOpacity\"in t){Array.isArray(t.projectOpacity)?this.projectOpacity=t.projectOpacity.slice():(r=+t.projectOpacity,this.projectOpacity=[r,r,r]);for(var n=0;n<3;++n)this.projectOpacity[n]=v(this.projectOpacity[n]),this.projectOpacity[n]<1&&(this.projectHasAlpha=!0)}this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=v(t.opacity),this.opacity<1&&(this.hasAlpha=!0)),this.dirty=!0;var i,a,s=t.position,l=t.font||\"normal\",u=t.alignment||[0,0];if(2===u.length)i=u[0],a=u[1];else for(i=[],a=[],n=0;n<u.length;++n)i[n]=u[n][0],a[n]=u[n][1];var 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float segmentCount = 8.0;\\n\\n  float angle = 2.0 * 3.14159 * (index / segmentCount);\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d);\\n  vec3 y = v * sin(angle) * length(d);\\n  vec3 v3 = x + y;\\n\\n  normal = normalize(v3);\\n\\n  return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\n\\nuniform float vectorScale, tubeScale;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 eyePosition, lightPosition;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  // Scale the vector magnitude to stay constant with\\n  // model & view changes.\\n  vec3 normal;\\n  vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\\n  vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * tubePosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n  // vec4 m_position  = model * vec4(tubePosition, 1.0);\\n  vec4 t_position  = view * tubePosition;\\n  gl_Position      = projection * t_position;\\n\\n  f_color          = color;\\n  f_data           = tubePosition.xyz;\\n  f_position       = position.xyz;\\n  f_uv             = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha 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outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * opacity;\\n}\\n\"]),o=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the tube vertex and normal at the given index.\\n//\\n// The returned vertex is for a tube ring with its center at origin, radius of length(d), pointing in the direction of d.\\n//\\n// Each tube segment is made up of a ring of vertices.\\n// These vertices are used to make up the triangles of the tube by connecting them together in the vertex array.\\n// The indexes of tube segments run from 0 to 8.\\n//\\nvec3 getTubePosition(vec3 d, float index, out vec3 normal) {\\n  float segmentCount = 8.0;\\n\\n  float angle = 2.0 * 3.14159 * (index / segmentCount);\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d);\\n  vec3 y = v * sin(angle) * length(d);\\n  vec3 v3 = x + y;\\n\\n  normal = normalize(v3);\\n\\n  return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform float tubeScale;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  vec3 normal;\\n  vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\\n  vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n  gl_Position = projection * view * tubePosition;\\n  f_id        = id;\\n  f_position  = position.xyz;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]);e.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec4\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"vector\",type:\"vec4\"}]},e.pickShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec4\"},{name:\"id\",type:\"vec4\"},{name:\"vector\",type:\"vec4\"}]}},7307:function(t,e,r){\"use strict\";var n=r(2858),i=r(4020),a=[\"xyz\",\"xzy\",\"yxz\",\"yzx\",\"zxy\",\"zyx\"],o=function(t,e){var r,n=t.length;for(r=0;r<n;r++){var i=t[r];if(i===e)return r;if(i>e)return r-1}return r},s=function(t,e,r){return t<e?e:t>r?r:t},l=function(t){var e=1/0;t.sort((function(t,e){return t-e}));for(var r=t.length,n=1;n<r;n++){var i=Math.abs(t[n]-t[n-1]);i<e&&(e=i)}return e};t.exports=function(t,e){var r=t.startingPositions,u=t.maxLength||1e3,c=t.tubeSize||1,f=t.absoluteTubeSize,h=t.gridFill||\"+x+y+z\",p={};-1!==h.indexOf(\"-x\")&&(p.reversedX=!0),-1!==h.indexOf(\"-y\")&&(p.reversedY=!0),-1!==h.indexOf(\"-z\")&&(p.reversedZ=!0),p.filled=a.indexOf(h.replace(/-/g,\"\").replace(/\\+/g,\"\"));var d=t.getVelocity||function(e){return function(t,e,r){var i=e.vectors,a=e.meshgrid,l=t[0],u=t[1],c=t[2],f=a[0].length,h=a[1].length,p=a[2].length,d=o(a[0],l),v=o(a[1],u),g=o(a[2],c),y=d+1,m=v+1,x=g+1;if(d=s(d,0,f-1),y=s(y,0,f-1),v=s(v,0,h-1),m=s(m,0,h-1),g=s(g,0,p-1),x=s(x,0,p-1),d<0||v<0||g<0||y>f-1||m>h-1||x>p-1)return n.create();var b,_,w,T,k,A,M=a[0][d],S=a[0][y],E=a[1][v],L=a[1][m],C=a[2][g],P=(l-M)/(S-M),O=(u-E)/(L-E),I=(c-C)/(a[2][x]-C);switch(isFinite(P)||(P=.5),isFinite(O)||(O=.5),isFinite(I)||(I=.5),r.reversedX&&(d=f-1-d,y=f-1-y),r.reversedY&&(v=h-1-v,m=h-1-m),r.reversedZ&&(g=p-1-g,x=p-1-x),r.filled){case 5:k=g,A=x,w=v*p,T=m*p,b=d*p*h,_=y*p*h;break;case 4:k=g,A=x,b=d*p,_=y*p,w=v*p*f,T=m*p*f;break;case 3:w=v,T=m,k=g*h,A=x*h,b=d*h*p,_=y*h*p;break;case 2:w=v,T=m,b=d*h,_=y*h,k=g*h*f,A=x*h*f;break;case 1:b=d,_=y,k=g*f,A=x*f,w=v*f*p,T=m*f*p;break;default:b=d,_=y,w=v*f,T=m*f,k=g*f*h,A=x*f*h}var D=i[b+w+k],z=i[b+w+A],R=i[b+T+k],F=i[b+T+A],B=i[_+w+k],N=i[_+w+A],j=i[_+T+k],U=i[_+T+A],V=n.create(),q=n.create(),H=n.create(),G=n.create();n.lerp(V,D,B,P),n.lerp(q,z,N,P),n.lerp(H,R,j,P),n.lerp(G,F,U,P);var W=n.create(),Y=n.create();n.lerp(W,V,H,O),n.lerp(Y,q,G,O);var X=n.create();return n.lerp(X,W,Y,I),X}(e,t,p)},v=t.getDivergence||function(t,e){var r=n.create(),i=1e-4;n.add(r,t,[i,0,0]);var a=d(r);n.subtract(a,a,e),n.scale(a,a,1/i),n.add(r,t,[0,i,0]);var o=d(r);n.subtract(o,o,e),n.scale(o,o,1/i),n.add(r,t,[0,0,i]);var s=d(r);return n.subtract(s,s,e),n.scale(s,s,1/i),n.add(r,a,o),n.add(r,r,s),r},g=[],y=e[0][0],m=e[0][1],x=e[0][2],b=e[1][0],_=e[1][1],w=e[1][2],T=function(t){var e=t[0],r=t[1],n=t[2];return!(e<y||e>b||r<m||r>_||n<x||n>w)},k=10*n.distance(e[0],e[1])/u,A=k*k,M=1,S=0,E=r.length;E>1&&(M=function(t){for(var e=[],r=[],n=[],i={},a={},o={},s=t.length,u=0;u<s;u++){var c=t[u],f=c[0],h=c[1],p=c[2];i[f]||(e.push(f),i[f]=!0),a[h]||(r.push(h),a[h]=!0),o[p]||(n.push(p),o[p]=!0)}var d=l(e),v=l(r),g=l(n),y=Math.min(d,v,g);return isFinite(y)?y:1}(r));for(var L=0;L<E;L++){var C=n.create();n.copy(C,r[L]);var P=[C],O=[],I=d(C),D=C;O.push(I);var z=[],R=v(C,I),F=n.length(R);isFinite(F)&&F>S&&(S=F),z.push(F),g.push({points:P,velocities:O,divergences:z});for(var B=0;B<100*u&&P.length<u&&T(C);){B++;var N=n.clone(I),j=n.squaredLength(N);if(0===j)break;j>A&&n.scale(N,N,k/Math.sqrt(j)),n.add(N,N,C),I=d(N),n.squaredDistance(D,N)-A>-1e-4*A&&(P.push(N),D=N,O.push(I),R=v(N,I),F=n.length(R),isFinite(F)&&F>S&&(S=F),z.push(F)),C=N}}var U=function(t,e,r,a){for(var o=0,s=0;s<t.length;s++)for(var l=t[s].velocities,u=0;u<l.length;u++)o=Math.max(o,n.length(l[u]));var c=t.map((function(t){return function(t,e,r,a){for(var o=t.points,s=t.velocities,l=t.divergences,u=[],c=[],f=[],h=[],p=[],d=[],v=0,g=0,y=i.create(),m=i.create(),x=0;x<o.length;x++){var b=o[x],_=s[x],w=l[x];0===e&&(w=.05*r),g=n.length(_)/a,y=i.create(),n.copy(y,_),y[3]=w;for(var T=0;T<8;T++)p[T]=[b[0],b[1],b[2],T];if(h.length>0)for(T=0;T<8;T++){var k=(T+1)%8;u.push(h[T],p[T],p[k],p[k],h[k],h[T]),f.push(m,y,y,y,m,m),d.push(v,g,g,g,v,v);var A=u.length;c.push([A-6,A-5,A-4],[A-3,A-2,A-1])}var M=h;h=p,p=M;var S=m;m=y,y=S;var E=v;v=g,g=E}return{positions:u,cells:c,vectors:f,vertexIntensity:d}}(t,r,a,o)})),f=[],h=[],p=[],d=[];for(s=0;s<c.length;s++){var v=c[s],g=f.length;for(f=f.concat(v.positions),p=p.concat(v.vectors),d=d.concat(v.vertexIntensity),u=0;u<v.cells.length;u++){var y=v.cells[u],m=[];h.push(m);for(var x=0;x<y.length;x++)m.push(y[x]+g)}}return{positions:f,cells:h,vectors:p,vertexIntensity:d,colormap:e}}(g,t.colormap,S,M);return f?U.tubeScale=f:(0===S&&(S=1),U.tubeScale=.5*c*M/S),U};var u=r(9578),c=r(1140).createMesh;t.exports.createTubeMesh=function(t,e){return c(t,e,{shaders:u,traceType:\"streamtube\"})}},9054:function(t,e,r){var n=r(5158),i=r(6832),a=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute vec3 f;\\nattribute vec3 normal;\\n\\nuniform vec3 objectOffset;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 lightPosition, eyePosition;\\nuniform sampler2D colormap;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  vec3 localCoordinate = vec3(uv.zw, f.x);\\n  worldCoordinate = objectOffset + localCoordinate;\\n  vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n  vec4 clipPosition = projection * view * worldPosition;\\n  gl_Position = clipPosition;\\n  kill = f.y;\\n  value = f.z;\\n  planeCoordinate = uv.xy;\\n\\n  vColor = texture2D(colormap, vec2(value, value));\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * worldPosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  lightDirection = lightPosition - cameraCoordinate.xyz;\\n  eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  surfaceNormal  = normalize((vec4(normal,0) * inverseModel).xyz);\\n}\\n\"]),o=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat beckmannSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness) {\\n  return beckmannDistribution(dot(surfaceNormal, normalize(lightDirection + viewDirection)), roughness);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 lowerBound, upperBound;\\nuniform float contourTint;\\nuniform vec4 contourColor;\\nuniform sampler2D colormap;\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform float vertexColor;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  if (\\n    kill > 0.0 ||\\n    vColor.a == 0.0 ||\\n    outOfRange(clipBounds[0], clipBounds[1], worldCoordinate)\\n  ) discard;\\n\\n  vec3 N = normalize(surfaceNormal);\\n  vec3 V = normalize(eyeDirection);\\n  vec3 L = normalize(lightDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = max(beckmannSpecular(L, V, N, roughness), 0.);\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  //decide how to interpolate color — in vertex or in fragment\\n  vec4 surfaceColor =\\n    step(vertexColor, .5) * texture2D(colormap, vec2(value, value)) +\\n    step(.5, vertexColor) * vColor;\\n\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = mix(litColor, contourColor, contourTint) * opacity;\\n}\\n\"]),s=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute float f;\\n\\nuniform vec3 objectOffset;\\nuniform mat3 permutation;\\nuniform mat4 model, view, projection;\\nuniform float height, zOffset;\\nuniform sampler2D colormap;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  vec3 dataCoordinate = permutation * vec3(uv.xy, height);\\n  worldCoordinate = objectOffset + dataCoordinate;\\n  vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n\\n  vec4 clipPosition = projection * view * worldPosition;\\n  clipPosition.z += zOffset;\\n\\n  gl_Position = clipPosition;\\n  value = f + objectOffset.z;\\n  kill = -1.0;\\n  planeCoordinate = uv.zw;\\n\\n  vColor = texture2D(colormap, vec2(value, value));\\n\\n  //Don't do lighting for contours\\n  surfaceNormal   = vec3(1,0,0);\\n  eyeDirection    = vec3(0,1,0);\\n  lightDirection  = vec3(0,0,1);\\n}\\n\"]),l=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec2 shape;\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 surfaceNormal;\\n\\nvec2 splitFloat(float v) {\\n  float vh = 255.0 * v;\\n  float upper = floor(vh);\\n  float lower = fract(vh);\\n  return vec2(upper / 255.0, floor(lower * 16.0) / 16.0);\\n}\\n\\nvoid main() {\\n  if ((kill > 0.0) ||\\n      (outOfRange(clipBounds[0], clipBounds[1], worldCoordinate))) discard;\\n\\n  vec2 ux = splitFloat(planeCoordinate.x / shape.x);\\n  vec2 uy = splitFloat(planeCoordinate.y / shape.y);\\n  gl_FragColor = vec4(pickId, ux.x, uy.x, ux.y + (uy.y/16.0));\\n}\\n\"]);e.createShader=function(t){var e=n(t,a,o,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},e.createPickShader=function(t){var e=n(t,a,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},e.createContourShader=function(t){var e=n(t,s,o,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e},e.createPickContourShader=function(t){var e=n(t,s,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e}},3754:function(t,e,r){\"use strict\";t.exports=function(t){var e=t.gl,r=m(e),n=b(e),s=x(e),l=_(e),u=i(e),c=a(e,[{buffer:u,size:4,stride:w,offset:0},{buffer:u,size:3,stride:w,offset:16},{buffer:u,size:3,stride:w,offset:28}]),f=i(e),h=a(e,[{buffer:f,size:4,stride:20,offset:0},{buffer:f,size:1,stride:20,offset:16}]),p=i(e),d=a(e,[{buffer:p,size:2,type:e.FLOAT}]),v=o(e,1,S,e.RGBA,e.UNSIGNED_BYTE);v.minFilter=e.LINEAR,v.magFilter=e.LINEAR;var g=new E(e,[0,0],[[0,0,0],[0,0,0]],r,n,u,c,v,s,l,f,h,p,d,[0,0,0]),y={levels:[[],[],[]]};for(var T in t)y[T]=t[T];return y.colormap=y.colormap||\"jet\",g.update(y),g};var n=r(2288),i=r(5827),a=r(2944),o=r(8931),s=r(5306),l=r(9156),u=r(7498),c=r(7382),f=r(5050),h=r(4162),p=r(104),d=r(7437),v=r(5070),g=r(9144),y=r(9054),m=y.createShader,x=y.createContourShader,b=y.createPickShader,_=y.createPickContourShader,w=40,T=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],k=[[0,0],[0,1],[1,0],[1,1],[1,0],[0,1]],A=[[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0]];function M(t,e,r,n,i){this.position=t,this.index=e,this.uv=r,this.level=n,this.dataCoordinate=i}!function(){for(var t=0;t<3;++t){var e=A[t],r=(t+2)%3;e[(t+1)%3+0]=1,e[r+3]=1,e[t+6]=1}}();var S=256;function E(t,e,r,n,i,a,o,l,u,c,h,p,d,v,g){this.gl=t,this.shape=e,this.bounds=r,this.objectOffset=g,this.intensityBounds=[],this._shader=n,this._pickShader=i,this._coordinateBuffer=a,this._vao=o,this._colorMap=l,this._contourShader=u,this._contourPickShader=c,this._contourBuffer=h,this._contourVAO=p,this._contourOffsets=[[],[],[]],this._contourCounts=[[],[],[]],this._vertexCount=0,this._pickResult=new M([0,0,0],[0,0],[0,0],[0,0,0],[0,0,0]),this._dynamicBuffer=d,this._dynamicVAO=v,this._dynamicOffsets=[0,0,0],this._dynamicCounts=[0,0,0],this.contourWidth=[1,1,1],this.contourLevels=[[1],[1],[1]],this.contourTint=[0,0,0],this.contourColor=[[.5,.5,.5,1],[.5,.5,.5,1],[.5,.5,.5,1]],this.showContour=!0,this.showSurface=!0,this.enableHighlight=[!0,!0,!0],this.highlightColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.highlightTint=[1,1,1],this.highlightLevel=[-1,-1,-1],this.enableDynamic=[!0,!0,!0],this.dynamicLevel=[NaN,NaN,NaN],this.dynamicColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.dynamicTint=[1,1,1],this.dynamicWidth=[1,1,1],this.axesBounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.surfaceProject=[!1,!1,!1],this.contourProject=[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],this.colorBounds=[!1,!1],this._field=[f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0])],this.pickId=1,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.snapToData=!1,this.pixelRatio=1,this.opacity=1,this.lightPosition=[10,1e4,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.vertexColor=0,this.dirty=!0}var L=E.prototype;L.genColormap=function(t,e){var r=!1,n=c([l({colormap:t,nshades:S,format:\"rgba\"}).map((function(t,n){var i=e?function(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;r<e.length;++r){if(e.length<2)return 1;if(e[r][0]===t)return e[r][1];if(e[r][0]>t&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}(n/255,e):t[3];return i<1&&(r=!0),[t[0],t[1],t[2],255*i]}))]);return u.divseq(n,255),this.hasAlphaScale=r,n},L.isTransparent=function(){return this.opacity<1||this.hasAlphaScale},L.isOpaque=function(){return!this.isTransparent()},L.pickSlots=1,L.setPickBase=function(t){this.pickId=t};var C=[0,0,0],P={showSurface:!1,showContour:!1,projections:[T.slice(),T.slice(),T.slice()],clipBounds:[[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]};function O(t,e){var r,n,i,a=e.axes&&e.axes.lastCubeProps.axis||C,o=e.showSurface,s=e.showContour;for(r=0;r<3;++r)for(o=o||e.surfaceProject[r],n=0;n<3;++n)s=s||e.contourProject[r][n];for(r=0;r<3;++r){var l=P.projections[r];for(n=0;n<16;++n)l[n]=0;for(n=0;n<4;++n)l[5*n]=1;l[5*r]=0,l[12+r]=e.axesBounds[+(a[r]>0)][r],p(l,t.model,l);var u=P.clipBounds[r];for(i=0;i<2;++i)for(n=0;n<3;++n)u[i][n]=t.clipBounds[i][n];u[0][r]=-1e8,u[1][r]=1e8}return P.showSurface=o,P.showContour=s,P}var I={model:T,view:T,projection:T,inverseModel:T.slice(),lowerBound:[0,0,0],upperBound:[0,0,0],colorMap:0,clipBounds:[[0,0,0],[0,0,0]],height:0,contourTint:0,contourColor:[0,0,0,1],permutation:[1,0,0,0,1,0,0,0,1],zOffset:-1e-4,objectOffset:[0,0,0],kambient:1,kdiffuse:1,kspecular:1,lightPosition:[1e3,1e3,1e3],eyePosition:[0,0,0],roughness:1,fresnel:1,opacity:1,vertexColor:0},D=T.slice(),z=[1,0,0,0,1,0,0,0,1];function R(t,e){t=t||{};var r=this.gl;r.disable(r.CULL_FACE),this._colorMap.bind(0);var n=I;n.model=t.model||T,n.view=t.view||T,n.projection=t.projection||T,n.lowerBound=[this.bounds[0][0],this.bounds[0][1],this.colorBounds[0]||this.bounds[0][2]],n.upperBound=[this.bounds[1][0],this.bounds[1][1],this.colorBounds[1]||this.bounds[1][2]],n.objectOffset=this.objectOffset,n.contourColor=this.contourColor[0],n.inverseModel=d(n.inverseModel,n.model);for(var i=0;i<2;++i)for(var a=n.clipBounds[i],o=0;o<3;++o)a[o]=Math.min(Math.max(this.clipBounds[i][o],-1e8),1e8);n.kambient=this.ambientLight,n.kdiffuse=this.diffuseLight,n.kspecular=this.specularLight,n.roughness=this.roughness,n.fresnel=this.fresnel,n.opacity=this.opacity,n.height=0,n.permutation=z,n.vertexColor=this.vertexColor;var s=D;for(p(s,n.view,n.model),p(s,n.projection,s),d(s,s),i=0;i<3;++i)n.eyePosition[i]=s[12+i]/s[15];var l=s[15];for(i=0;i<3;++i)l+=this.lightPosition[i]*s[4*i+3];for(i=0;i<3;++i){var u=s[12+i];for(o=0;o<3;++o)u+=s[4*o+i]*this.lightPosition[o];n.lightPosition[i]=u/l}var c=O(n,this);if(c.showSurface){for(this._shader.bind(),this._shader.uniforms=n,this._vao.bind(),this.showSurface&&this._vertexCount&&this._vao.draw(r.TRIANGLES,this._vertexCount),i=0;i<3;++i)this.surfaceProject[i]&&this.vertexCount&&(this._shader.uniforms.model=c.projections[i],this._shader.uniforms.clipBounds=c.clipBounds[i],this._vao.draw(r.TRIANGLES,this._vertexCount));this._vao.unbind()}if(c.showContour){var f=this._contourShader;n.kambient=1,n.kdiffuse=0,n.kspecular=0,n.opacity=1,f.bind(),f.uniforms=n;var h=this._contourVAO;for(h.bind(),i=0;i<3;++i)for(f.uniforms.permutation=A[i],r.lineWidth(this.contourWidth[i]*this.pixelRatio),o=0;o<this.contourLevels[i].length;++o)o===this.highlightLevel[i]?(f.uniforms.contourColor=this.highlightColor[i],f.uniforms.contourTint=this.highlightTint[i]):0!==o&&o-1!==this.highlightLevel[i]||(f.uniforms.contourColor=this.contourColor[i],f.uniforms.contourTint=this.contourTint[i]),this._contourCounts[i][o]&&(f.uniforms.height=this.contourLevels[i][o],h.draw(r.LINES,this._contourCounts[i][o],this._contourOffsets[i][o]));for(i=0;i<3;++i)for(f.uniforms.model=c.projections[i],f.uniforms.clipBounds=c.clipBounds[i],o=0;o<3;++o)if(this.contourProject[i][o]){f.uniforms.permutation=A[o],r.lineWidth(this.contourWidth[o]*this.pixelRatio);for(var v=0;v<this.contourLevels[o].length;++v)v===this.highlightLevel[o]?(f.uniforms.contourColor=this.highlightColor[o],f.uniforms.contourTint=this.highlightTint[o]):0!==v&&v-1!==this.highlightLevel[o]||(f.uniforms.contourColor=this.contourColor[o],f.uniforms.contourTint=this.contourTint[o]),this._contourCounts[o][v]&&(f.uniforms.height=this.contourLevels[o][v],h.draw(r.LINES,this._contourCounts[o][v],this._contourOffsets[o][v]))}for(h.unbind(),(h=this._dynamicVAO).bind(),i=0;i<3;++i)if(0!==this._dynamicCounts[i])for(f.uniforms.model=n.model,f.uniforms.clipBounds=n.clipBounds,f.uniforms.permutation=A[i],r.lineWidth(this.dynamicWidth[i]*this.pixelRatio),f.uniforms.contourColor=this.dynamicColor[i],f.uniforms.contourTint=this.dynamicTint[i],f.uniforms.height=this.dynamicLevel[i],h.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]),o=0;o<3;++o)this.contourProject[o][i]&&(f.uniforms.model=c.projections[o],f.uniforms.clipBounds=c.clipBounds[o],h.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]));h.unbind()}}L.draw=function(t){return R.call(this,t,!1)},L.drawTransparent=function(t){return R.call(this,t,!0)};var F={model:T,view:T,projection:T,inverseModel:T,clipBounds:[[0,0,0],[0,0,0]],height:0,shape:[0,0],pickId:0,lowerBound:[0,0,0],upperBound:[0,0,0],zOffset:0,objectOffset:[0,0,0],permutation:[1,0,0,0,1,0,0,0,1],lightPosition:[0,0,0],eyePosition:[0,0,0]};function B(t,e){return Array.isArray(t)?[e(t[0]),e(t[1]),e(t[2])]:[e(t),e(t),e(t)]}function N(t){return Array.isArray(t)?3===t.length?[t[0],t[1],t[2],1]:[t[0],t[1],t[2],t[3]]:[0,0,0,1]}function j(t){if(Array.isArray(t)){if(Array.isArray(t))return[N(t[0]),N(t[1]),N(t[2])];var e=N(t);return[e.slice(),e.slice(),e.slice()]}}L.drawPick=function(t){t=t||{};var e=this.gl;e.disable(e.CULL_FACE);var r=F;r.model=t.model||T,r.view=t.view||T,r.projection=t.projection||T,r.shape=this._field[2].shape,r.pickId=this.pickId/255,r.lowerBound=this.bounds[0],r.upperBound=this.bounds[1],r.objectOffset=this.objectOffset,r.permutation=z;for(var n=0;n<2;++n)for(var i=r.clipBounds[n],a=0;a<3;++a)i[a]=Math.min(Math.max(this.clipBounds[n][a],-1e8),1e8);var o=O(r,this);if(o.showSurface){for(this._pickShader.bind(),this._pickShader.uniforms=r,this._vao.bind(),this._vao.draw(e.TRIANGLES,this._vertexCount),n=0;n<3;++n)this.surfaceProject[n]&&(this._pickShader.uniforms.model=o.projections[n],this._pickShader.uniforms.clipBounds=o.clipBounds[n],this._vao.draw(e.TRIANGLES,this._vertexCount));this._vao.unbind()}if(o.showContour){var s=this._contourPickShader;s.bind(),s.uniforms=r;var l=this._contourVAO;for(l.bind(),a=0;a<3;++a)for(e.lineWidth(this.contourWidth[a]*this.pixelRatio),s.uniforms.permutation=A[a],n=0;n<this.contourLevels[a].length;++n)this._contourCounts[a][n]&&(s.uniforms.height=this.contourLevels[a][n],l.draw(e.LINES,this._contourCounts[a][n],this._contourOffsets[a][n]));for(n=0;n<3;++n)for(s.uniforms.model=o.projections[n],s.uniforms.clipBounds=o.clipBounds[n],a=0;a<3;++a)if(this.contourProject[n][a]){s.uniforms.permutation=A[a],e.lineWidth(this.contourWidth[a]*this.pixelRatio);for(var u=0;u<this.contourLevels[a].length;++u)this._contourCounts[a][u]&&(s.uniforms.height=this.contourLevels[a][u],l.draw(e.LINES,this._contourCounts[a][u],this._contourOffsets[a][u]))}l.unbind()}},L.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=this._field[2].shape,r=this._pickResult,n=e[0]*(t.value[0]+(t.value[2]>>4)/16)/255,i=Math.floor(n),a=n-i,o=e[1]*(t.value[1]+(15&t.value[2])/16)/255,s=Math.floor(o),l=o-s;i+=1,s+=1;var u=r.position;u[0]=u[1]=u[2]=0;for(var c=0;c<2;++c)for(var f=c?a:1-a,h=0;h<2;++h)for(var p=i+c,d=s+h,g=f*(h?l:1-l),y=0;y<3;++y)u[y]+=this._field[y].get(p,d)*g;for(var m=this._pickResult.level,x=0;x<3;++x)if(m[x]=v.le(this.contourLevels[x],u[x]),m[x]<0)this.contourLevels[x].length>0&&(m[x]=0);else if(m[x]<this.contourLevels[x].length-1){var b=this.contourLevels[x][m[x]],_=this.contourLevels[x][m[x]+1];Math.abs(b-u[x])>Math.abs(_-u[x])&&(m[x]+=1)}for(r.index[0]=a<.5?i:i+1,r.index[1]=l<.5?s:s+1,r.uv[0]=n/e[0],r.uv[1]=o/e[1],y=0;y<3;++y)r.dataCoordinate[y]=this._field[y].get(r.index[0],r.index[1]);return r},L.padField=function(t,e){var r=e.shape.slice(),n=t.shape.slice();u.assign(t.lo(1,1).hi(r[0],r[1]),e),u.assign(t.lo(1).hi(r[0],1),e.hi(r[0],1)),u.assign(t.lo(1,n[1]-1).hi(r[0],1),e.lo(0,r[1]-1).hi(r[0],1)),u.assign(t.lo(0,1).hi(1,r[1]),e.hi(1)),u.assign(t.lo(n[0]-1,1).hi(1,r[1]),e.lo(r[0]-1)),t.set(0,0,e.get(0,0)),t.set(0,n[1]-1,e.get(0,r[1]-1)),t.set(n[0]-1,0,e.get(r[0]-1,0)),t.set(n[0]-1,n[1]-1,e.get(r[0]-1,r[1]-1))},L.update=function(t){t=t||{},this.objectOffset=t.objectOffset||this.objectOffset,this.dirty=!0,\"contourWidth\"in t&&(this.contourWidth=B(t.contourWidth,Number)),\"showContour\"in t&&(this.showContour=B(t.showContour,Boolean)),\"showSurface\"in t&&(this.showSurface=!!t.showSurface),\"contourTint\"in t&&(this.contourTint=B(t.contourTint,Boolean)),\"contourColor\"in t&&(this.contourColor=j(t.contourColor)),\"contourProject\"in t&&(this.contourProject=B(t.contourProject,(function(t){return B(t,Boolean)}))),\"surfaceProject\"in t&&(this.surfaceProject=t.surfaceProject),\"dynamicColor\"in t&&(this.dynamicColor=j(t.dynamicColor)),\"dynamicTint\"in t&&(this.dynamicTint=B(t.dynamicTint,Number)),\"dynamicWidth\"in t&&(this.dynamicWidth=B(t.dynamicWidth,Number)),\"opacity\"in t&&(this.opacity=t.opacity),\"opacityscale\"in t&&(this.opacityscale=t.opacityscale),\"colorBounds\"in t&&(this.colorBounds=t.colorBounds),\"vertexColor\"in t&&(this.vertexColor=t.vertexColor?1:0),\"colormap\"in t&&this._colorMap.setPixels(this.genColormap(t.colormap,this.opacityscale));var e=t.field||t.coords&&t.coords[2]||null,r=!1;if(e||(e=this._field[2].shape[0]||this._field[2].shape[2]?this._field[2].lo(1,1).hi(this._field[2].shape[0]-2,this._field[2].shape[1]-2):this._field[2].hi(0,0)),\"field\"in t||\"coords\"in t){var i=(e.shape[0]+2)*(e.shape[1]+2);i>this._field[2].data.length&&(s.freeFloat(this._field[2].data),this._field[2].data=s.mallocFloat(n.nextPow2(i))),this._field[2]=f(this._field[2].data,[e.shape[0]+2,e.shape[1]+2]),this.padField(this._field[2],e),this.shape=e.shape.slice();for(var a=this.shape,o=0;o<2;++o)this._field[2].size>this._field[o].data.length&&(s.freeFloat(this._field[o].data),this._field[o].data=s.mallocFloat(this._field[2].size)),this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2]);if(t.coords){var l=t.coords;if(!Array.isArray(l)||3!==l.length)throw new Error(\"gl-surface: invalid coordinates for x/y\");for(o=0;o<2;++o){var u=l[o];for(y=0;y<2;++y)if(u.shape[y]!==a[y])throw new Error(\"gl-surface: coords have incorrect shape\");this.padField(this._field[o],u)}}else if(t.ticks){var c=t.ticks;if(!Array.isArray(c)||2!==c.length)throw new Error(\"gl-surface: invalid ticks\");for(o=0;o<2;++o){var p=c[o];if((Array.isArray(p)||p.length)&&(p=f(p)),p.shape[0]!==a[o])throw new Error(\"gl-surface: invalid tick length\");var d=f(p.data,a);d.stride[o]=p.stride[0],d.stride[1^o]=0,this.padField(this._field[o],d)}}else{for(o=0;o<2;++o){var v=[0,0];v[o]=1,this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2],v,0)}this._field[0].set(0,0,0);for(var y=0;y<a[0];++y)this._field[0].set(y+1,0,y);for(this._field[0].set(a[0]+1,0,a[0]-1),this._field[1].set(0,0,0),y=0;y<a[1];++y)this._field[1].set(0,y+1,y);this._field[1].set(0,a[1]+1,a[1]-1)}var m=this._field,x=f(s.mallocFloat(3*m[2].size*2),[3,a[0]+2,a[1]+2,2]);for(o=0;o<3;++o)g(x.pick(o),m[o],\"mirror\");var b=f(s.mallocFloat(3*m[2].size),[a[0]+2,a[1]+2,3]);for(o=0;o<a[0]+2;++o)for(y=0;y<a[1]+2;++y){var _=x.get(0,o,y,0),w=x.get(0,o,y,1),T=x.get(1,o,y,0),A=x.get(1,o,y,1),M=x.get(2,o,y,0),S=x.get(2,o,y,1),E=T*S-A*M,L=M*w-S*_,C=_*A-w*T,P=Math.sqrt(E*E+L*L+C*C);P<1e-8?(P=Math.max(Math.abs(E),Math.abs(L),Math.abs(C)))<1e-8?(C=1,L=E=0,P=1):P=1/P:P=1/Math.sqrt(P),b.set(o,y,0,E*P),b.set(o,y,1,L*P),b.set(o,y,2,C*P)}s.free(x.data);var O=[1/0,1/0,1/0],I=[-1/0,-1/0,-1/0],D=1/0,z=-1/0,R=(a[0]-1)*(a[1]-1)*6,F=s.mallocFloat(n.nextPow2(10*R)),N=0,U=0;for(o=0;o<a[0]-1;++o)t:for(y=0;y<a[1]-1;++y){for(var V=0;V<2;++V)for(var q=0;q<2;++q)for(var H=0;H<3;++H){var G=this._field[H].get(1+o+V,1+y+q);if(isNaN(G)||!isFinite(G))continue t}for(H=0;H<6;++H){var W=o+k[H][0],Y=y+k[H][1],X=this._field[0].get(W+1,Y+1),Z=this._field[1].get(W+1,Y+1);G=this._field[2].get(W+1,Y+1),E=b.get(W+1,Y+1,0),L=b.get(W+1,Y+1,1),C=b.get(W+1,Y+1,2),t.intensity&&(K=t.intensity.get(W,Y));var K=t.intensity?t.intensity.get(W,Y):G+this.objectOffset[2];F[N++]=W,F[N++]=Y,F[N++]=X,F[N++]=Z,F[N++]=G,F[N++]=0,F[N++]=K,F[N++]=E,F[N++]=L,F[N++]=C,O[0]=Math.min(O[0],X+this.objectOffset[0]),O[1]=Math.min(O[1],Z+this.objectOffset[1]),O[2]=Math.min(O[2],G+this.objectOffset[2]),D=Math.min(D,K),I[0]=Math.max(I[0],X+this.objectOffset[0]),I[1]=Math.max(I[1],Z+this.objectOffset[1]),I[2]=Math.max(I[2],G+this.objectOffset[2]),z=Math.max(z,K),U+=1}}for(t.intensityBounds&&(D=+t.intensityBounds[0],z=+t.intensityBounds[1]),o=6;o<N;o+=10)F[o]=(F[o]-D)/(z-D);this._vertexCount=U,this._coordinateBuffer.update(F.subarray(0,N)),s.freeFloat(F),s.free(b.data),this.bounds=[O,I],this.intensity=t.intensity||this._field[2],this.intensityBounds[0]===D&&this.intensityBounds[1]===z||(r=!0),this.intensityBounds=[D,z]}if(\"levels\"in t){var J=t.levels;for(J=Array.isArray(J[0])?J.slice():[[],[],J],o=0;o<3;++o)J[o]=J[o].slice(),J[o].sort((function(t,e){return t-e}));for(o=0;o<3;++o)for(y=0;y<J[o].length;++y)J[o][y]-=this.objectOffset[o];t:for(o=0;o<3;++o){if(J[o].length!==this.contourLevels[o].length){r=!0;break}for(y=0;y<J[o].length;++y)if(J[o][y]!==this.contourLevels[o][y]){r=!0;break t}}this.contourLevels=J}if(r){m=this._field,a=this.shape;for(var $=[],Q=0;Q<3;++Q){var tt=this.contourLevels[Q],et=[],rt=[],nt=[0,0,0];for(o=0;o<tt.length;++o){var it=h(this._field[Q],tt[o]);et.push($.length/5|0),U=0;t:for(y=0;y<it.cells.length;++y){var at=it.cells[y];for(H=0;H<2;++H){var ot=it.positions[at[H]],st=ot[0],lt=0|Math.floor(st),ut=st-lt,ct=ot[1],ft=0|Math.floor(ct),ht=ct-ft,pt=!1;e:for(var dt=0;dt<3;++dt){nt[dt]=0;var vt=(Q+dt+1)%3;for(V=0;V<2;++V){var gt=V?ut:1-ut;for(W=0|Math.min(Math.max(lt+V,0),a[0]),q=0;q<2;++q){var yt=q?ht:1-ht;if(Y=0|Math.min(Math.max(ft+q,0),a[1]),G=dt<2?this._field[vt].get(W,Y):(this.intensity.get(W,Y)-this.intensityBounds[0])/(this.intensityBounds[1]-this.intensityBounds[0]),!isFinite(G)||isNaN(G)){pt=!0;break e}var mt=gt*yt;nt[dt]+=mt*G}}}if(pt){if(H>0){for(var xt=0;xt<5;++xt)$.pop();U-=1}continue t}$.push(nt[0],nt[1],ot[0],ot[1],nt[2]),U+=1}}rt.push(U)}this._contourOffsets[Q]=et,this._contourCounts[Q]=rt}var bt=s.mallocFloat($.length);for(o=0;o<$.length;++o)bt[o]=$[o];this._contourBuffer.update(bt),s.freeFloat(bt)}},L.dispose=function(){this._shader.dispose(),this._vao.dispose(),this._coordinateBuffer.dispose(),this._colorMap.dispose(),this._contourBuffer.dispose(),this._contourVAO.dispose(),this._contourShader.dispose(),this._contourPickShader.dispose(),this._dynamicBuffer.dispose(),this._dynamicVAO.dispose();for(var t=0;t<3;++t)s.freeFloat(this._field[t].data)},L.highlight=function(t){var e,r;if(!t)return this._dynamicCounts=[0,0,0],this.dyanamicLevel=[NaN,NaN,NaN],void(this.highlightLevel=[-1,-1,-1]);for(e=0;e<3;++e)this.enableHighlight[e]?this.highlightLevel[e]=t.level[e]:this.highlightLevel[e]=-1;for(r=this.snapToData?t.dataCoordinate:t.position,e=0;e<3;++e)r[e]-=this.objectOffset[e];if(this.enableDynamic[0]&&r[0]!==this.dynamicLevel[0]||this.enableDynamic[1]&&r[1]!==this.dynamicLevel[1]||this.enableDynamic[2]&&r[2]!==this.dynamicLevel[2]){for(var n=0,i=this.shape,a=s.mallocFloat(12*i[0]*i[1]),o=0;o<3;++o)if(this.enableDynamic[o]){this.dynamicLevel[o]=r[o];var l=(o+1)%3,u=(o+2)%3,c=this._field[o],f=this._field[l],p=this._field[u],d=h(c,r[o]),v=d.cells,g=d.positions;for(this._dynamicOffsets[o]=n,e=0;e<v.length;++e)for(var y=v[e],m=0;m<2;++m){var x=g[y[m]],b=+x[0],_=0|b,w=0|Math.min(_+1,i[0]),T=b-_,k=1-T,A=+x[1],M=0|A,S=0|Math.min(M+1,i[1]),E=A-M,L=1-E,C=k*L,P=k*E,O=T*L,I=T*E,D=C*f.get(_,M)+P*f.get(_,S)+O*f.get(w,M)+I*f.get(w,S),z=C*p.get(_,M)+P*p.get(_,S)+O*p.get(w,M)+I*p.get(w,S);if(isNaN(D)||isNaN(z)){m&&(n-=1);break}a[2*n+0]=D,a[2*n+1]=z,n+=1}this._dynamicCounts[o]=n-this._dynamicOffsets[o]}else this.dynamicLevel[o]=NaN,this._dynamicCounts[o]=0;this._dynamicBuffer.update(a.subarray(0,2*n)),s.freeFloat(a)}}},8931:function(t,e,r){\"use strict\";var n=r(5050),i=r(7498),a=r(5306);t.exports=function(t){if(arguments.length<=1)throw new Error(\"gl-texture2d: Missing arguments for texture2d constructor\");if(o||function(t){o=[t.LINEAR,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_NEAREST],s=[t.NEAREST,t.LINEAR,t.NEAREST_MIPMAP_NEAREST,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_LINEAR],l=[t.REPEAT,t.CLAMP_TO_EDGE,t.MIRRORED_REPEAT]}(t),\"number\"==typeof arguments[1])return g(t,arguments[1],arguments[2],arguments[3]||t.RGBA,arguments[4]||t.UNSIGNED_BYTE);if(Array.isArray(arguments[1]))return g(t,0|arguments[1][0],0|arguments[1][1],arguments[2]||t.RGBA,arguments[3]||t.UNSIGNED_BYTE);if(\"object\"==typeof arguments[1]){var e=arguments[1],r=u(e)?e:e.raw;if(r)return function(t,e,r,n,i,a){var o=v(t);return t.texImage2D(t.TEXTURE_2D,0,i,i,a,e),new h(t,o,r,n,i,a)}(t,r,0|e.width,0|e.height,arguments[2]||t.RGBA,arguments[3]||t.UNSIGNED_BYTE);if(e.shape&&e.data&&e.stride)return function(t,e){var r=e.dtype,o=e.shape.slice(),s=t.getParameter(t.MAX_TEXTURE_SIZE);if(o[0]<0||o[0]>s||o[1]<0||o[1]>s)throw new Error(\"gl-texture2d: Invalid texture size\");var l=d(o,e.stride.slice()),u=0;\"float32\"===r?u=t.FLOAT:\"float64\"===r?(u=t.FLOAT,l=!1,r=\"float32\"):\"uint8\"===r?u=t.UNSIGNED_BYTE:(u=t.UNSIGNED_BYTE,l=!1,r=\"uint8\");var f,p,g=0;if(2===o.length)g=t.LUMINANCE,o=[o[0],o[1],1],e=n(e.data,o,[e.stride[0],e.stride[1],1],e.offset);else{if(3!==o.length)throw new Error(\"gl-texture2d: Invalid shape for texture\");if(1===o[2])g=t.ALPHA;else if(2===o[2])g=t.LUMINANCE_ALPHA;else if(3===o[2])g=t.RGB;else{if(4!==o[2])throw new Error(\"gl-texture2d: Invalid shape for pixel coords\");g=t.RGBA}}u!==t.FLOAT||t.getExtension(\"OES_texture_float\")||(u=t.UNSIGNED_BYTE,l=!1);var y=e.size;if(l)f=0===e.offset&&e.data.length===y?e.data:e.data.subarray(e.offset,e.offset+y);else{var m=[o[2],o[2]*o[0],1];p=a.malloc(y,r);var x=n(p,o,m,0);\"float32\"!==r&&\"float64\"!==r||u!==t.UNSIGNED_BYTE?i.assign(x,e):c(x,e),f=p.subarray(0,y)}var b=v(t);return t.texImage2D(t.TEXTURE_2D,0,g,o[0],o[1],0,g,u,f),l||a.free(p),new h(t,b,o[0],o[1],g,u)}(t,e)}throw new Error(\"gl-texture2d: Invalid arguments for texture2d constructor\")};var o=null,s=null,l=null;function u(t){return\"undefined\"!=typeof HTMLCanvasElement&&t instanceof HTMLCanvasElement||\"undefined\"!=typeof HTMLImageElement&&t instanceof HTMLImageElement||\"undefined\"!=typeof HTMLVideoElement&&t instanceof HTMLVideoElement||\"undefined\"!=typeof ImageData&&t instanceof ImageData}var c=function(t,e){i.muls(t,e,255)};function f(t,e,r){var n=t.gl,i=n.getParameter(n.MAX_TEXTURE_SIZE);if(e<0||e>i||r<0||r>i)throw new Error(\"gl-texture2d: Invalid texture size\");return t._shape=[e,r],t.bind(),n.texImage2D(n.TEXTURE_2D,0,t.format,e,r,0,t.format,t.type,null),t._mipLevels=[0],t}function h(t,e,r,n,i,a){this.gl=t,this.handle=e,this.format=i,this.type=a,this._shape=[r,n],this._mipLevels=[0],this._magFilter=t.NEAREST,this._minFilter=t.NEAREST,this._wrapS=t.CLAMP_TO_EDGE,this._wrapT=t.CLAMP_TO_EDGE,this._anisoSamples=1;var o=this,s=[this._wrapS,this._wrapT];Object.defineProperties(s,[{get:function(){return o._wrapS},set:function(t){return o.wrapS=t}},{get:function(){return o._wrapT},set:function(t){return o.wrapT=t}}]),this._wrapVector=s;var l=[this._shape[0],this._shape[1]];Object.defineProperties(l,[{get:function(){return o._shape[0]},set:function(t){return o.width=t}},{get:function(){return o._shape[1]},set:function(t){return o.height=t}}]),this._shapeVector=l}var p=h.prototype;function d(t,e){return 3===t.length?1===e[2]&&e[1]===t[0]*t[2]&&e[0]===t[2]:1===e[0]&&e[1]===t[0]}function v(t){var e=t.createTexture();return t.bindTexture(t.TEXTURE_2D,e),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE),e}function g(t,e,r,n,i){var a=t.getParameter(t.MAX_TEXTURE_SIZE);if(e<0||e>a||r<0||r>a)throw new Error(\"gl-texture2d: Invalid texture shape\");if(i===t.FLOAT&&!t.getExtension(\"OES_texture_float\"))throw new Error(\"gl-texture2d: Floating point textures not supported on this platform\");var o=v(t);return t.texImage2D(t.TEXTURE_2D,0,n,e,r,0,n,i,null),new h(t,o,e,r,n,i)}Object.defineProperties(p,{minFilter:{get:function(){return this._minFilter},set:function(t){this.bind();var e=this.gl;if(this.type===e.FLOAT&&o.indexOf(t)>=0&&(e.getExtension(\"OES_texture_float_linear\")||(t=e.NEAREST)),s.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown filter mode \"+t);return e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MIN_FILTER,t),this._minFilter=t}},magFilter:{get:function(){return this._magFilter},set:function(t){this.bind();var e=this.gl;if(this.type===e.FLOAT&&o.indexOf(t)>=0&&(e.getExtension(\"OES_texture_float_linear\")||(t=e.NEAREST)),s.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown filter mode \"+t);return e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MAG_FILTER,t),this._magFilter=t}},mipSamples:{get:function(){return this._anisoSamples},set:function(t){var e=this._anisoSamples;if(this._anisoSamples=0|Math.max(t,1),e!==this._anisoSamples){var r=this.gl.getExtension(\"EXT_texture_filter_anisotropic\");r&&this.gl.texParameterf(this.gl.TEXTURE_2D,r.TEXTURE_MAX_ANISOTROPY_EXT,this._anisoSamples)}return this._anisoSamples}},wrapS:{get:function(){return this._wrapS},set:function(t){if(this.bind(),l.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_S,t),this._wrapS=t}},wrapT:{get:function(){return this._wrapT},set:function(t){if(this.bind(),l.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_T,t),this._wrapT=t}},wrap:{get:function(){return this._wrapVector},set:function(t){if(Array.isArray(t)||(t=[t,t]),2!==t.length)throw new Error(\"gl-texture2d: Must specify wrap mode for rows and columns\");for(var e=0;e<2;++e)if(l.indexOf(t[e])<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);this._wrapS=t[0],this._wrapT=t[1];var r=this.gl;return this.bind(),r.texParameteri(r.TEXTURE_2D,r.TEXTURE_WRAP_S,this._wrapS),r.texParameteri(r.TEXTURE_2D,r.TEXTURE_WRAP_T,this._wrapT),t}},shape:{get:function(){return this._shapeVector},set:function(t){if(Array.isArray(t)){if(2!==t.length)throw new Error(\"gl-texture2d: Invalid texture shape\")}else t=[0|t,0|t];return f(this,0|t[0],0|t[1]),[0|t[0],0|t[1]]}},width:{get:function(){return this._shape[0]},set:function(t){return f(this,t|=0,this._shape[1]),t}},height:{get:function(){return this._shape[1]},set:function(t){return t|=0,f(this,this._shape[0],t),t}}}),p.bind=function(t){var e=this.gl;return void 0!==t&&e.activeTexture(e.TEXTURE0+(0|t)),e.bindTexture(e.TEXTURE_2D,this.handle),void 0!==t?0|t:e.getParameter(e.ACTIVE_TEXTURE)-e.TEXTURE0},p.dispose=function(){this.gl.deleteTexture(this.handle)},p.generateMipmap=function(){this.bind(),this.gl.generateMipmap(this.gl.TEXTURE_2D);for(var t=Math.min(this._shape[0],this._shape[1]),e=0;t>0;++e,t>>>=1)this._mipLevels.indexOf(e)<0&&this._mipLevels.push(e)},p.setPixels=function(t,e,r,o){var s=this.gl;this.bind(),Array.isArray(e)?(o=r,r=0|e[1],e=0|e[0]):(e=e||0,r=r||0),o=o||0;var l=u(t)?t:t.raw;if(l)this._mipLevels.indexOf(o)<0?(s.texImage2D(s.TEXTURE_2D,0,this.format,this.format,this.type,l),this._mipLevels.push(o)):s.texSubImage2D(s.TEXTURE_2D,o,e,r,this.format,this.type,l);else{if(!(t.shape&&t.stride&&t.data))throw new Error(\"gl-texture2d: Unsupported data type\");if(t.shape.length<2||e+t.shape[1]>this._shape[1]>>>o||r+t.shape[0]>this._shape[0]>>>o||e<0||r<0)throw new Error(\"gl-texture2d: Texture dimensions are out of bounds\");!function(t,e,r,o,s,l,u,f){var h=f.dtype,p=f.shape.slice();if(p.length<2||p.length>3)throw new Error(\"gl-texture2d: Invalid ndarray, must be 2d or 3d\");var v=0,g=0,y=d(p,f.stride.slice());if(\"float32\"===h?v=t.FLOAT:\"float64\"===h?(v=t.FLOAT,y=!1,h=\"float32\"):\"uint8\"===h?v=t.UNSIGNED_BYTE:(v=t.UNSIGNED_BYTE,y=!1,h=\"uint8\"),2===p.length)g=t.LUMINANCE,p=[p[0],p[1],1],f=n(f.data,p,[f.stride[0],f.stride[1],1],f.offset);else{if(3!==p.length)throw new Error(\"gl-texture2d: Invalid shape for texture\");if(1===p[2])g=t.ALPHA;else if(2===p[2])g=t.LUMINANCE_ALPHA;else if(3===p[2])g=t.RGB;else{if(4!==p[2])throw new Error(\"gl-texture2d: Invalid shape for pixel coords\");g=t.RGBA}p[2]}if(g!==t.LUMINANCE&&g!==t.ALPHA||s!==t.LUMINANCE&&s!==t.ALPHA||(g=s),g!==s)throw new Error(\"gl-texture2d: Incompatible texture format for setPixels\");var m=f.size,x=u.indexOf(o)<0;if(x&&u.push(o),v===l&&y)0===f.offset&&f.data.length===m?x?t.texImage2D(t.TEXTURE_2D,o,s,p[0],p[1],0,s,l,f.data):t.texSubImage2D(t.TEXTURE_2D,o,e,r,p[0],p[1],s,l,f.data):x?t.texImage2D(t.TEXTURE_2D,o,s,p[0],p[1],0,s,l,f.data.subarray(f.offset,f.offset+m)):t.texSubImage2D(t.TEXTURE_2D,o,e,r,p[0],p[1],s,l,f.data.subarray(f.offset,f.offset+m));else{var b;b=l===t.FLOAT?a.mallocFloat32(m):a.mallocUint8(m);var _=n(b,p,[p[2],p[2]*p[0],1]);v===t.FLOAT&&l===t.UNSIGNED_BYTE?c(_,f):i.assign(_,f),x?t.texImage2D(t.TEXTURE_2D,o,s,p[0],p[1],0,s,l,b.subarray(0,m)):t.texSubImage2D(t.TEXTURE_2D,o,e,r,p[0],p[1],s,l,b.subarray(0,m)),l===t.FLOAT?a.freeFloat32(b):a.freeUint8(b)}}(s,e,r,o,this.format,this.type,this._mipLevels,t)}}},3056:function(t){\"use strict\";t.exports=function(t,e,r){e?e.bind():t.bindBuffer(t.ELEMENT_ARRAY_BUFFER,null);var n=0|t.getParameter(t.MAX_VERTEX_ATTRIBS);if(r){if(r.length>n)throw new Error(\"gl-vao: Too many vertex attributes\");for(var i=0;i<r.length;++i){var a=r[i];if(a.buffer){var o=a.buffer,s=a.size||4,l=a.type||t.FLOAT,u=!!a.normalized,c=a.stride||0,f=a.offset||0;o.bind(),t.enableVertexAttribArray(i),t.vertexAttribPointer(i,s,l,u,c,f)}else{if(\"number\"==typeof a)t.vertexAttrib1f(i,a);else if(1===a.length)t.vertexAttrib1f(i,a[0]);else if(2===a.length)t.vertexAttrib2f(i,a[0],a[1]);else if(3===a.length)t.vertexAttrib3f(i,a[0],a[1],a[2]);else{if(4!==a.length)throw new Error(\"gl-vao: Invalid vertex attribute\");t.vertexAttrib4f(i,a[0],a[1],a[2],a[3])}t.disableVertexAttribArray(i)}}for(;i<n;++i)t.disableVertexAttribArray(i)}else for(t.bindBuffer(t.ARRAY_BUFFER,null),i=0;i<n;++i)t.disableVertexAttribArray(i)}},7220:function(t,e,r){\"use strict\";var n=r(3056);function i(t){this.gl=t,this._elements=null,this._attributes=null,this._elementsType=t.UNSIGNED_SHORT}i.prototype.bind=function(){n(this.gl,this._elements,this._attributes)},i.prototype.update=function(t,e,r){this._elements=e,this._attributes=t,this._elementsType=r||this.gl.UNSIGNED_SHORT},i.prototype.dispose=function(){},i.prototype.unbind=function(){},i.prototype.draw=function(t,e,r){r=r||0;var n=this.gl;this._elements?n.drawElements(t,e,this._elementsType,r):n.drawArrays(t,r,e)},t.exports=function(t){return new i(t)}},3778:function(t,e,r){\"use strict\";var n=r(3056);function i(t,e,r,n,i,a){this.location=t,this.dimension=e,this.a=r,this.b=n,this.c=i,this.d=a}function 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strict\";t.exports=function(t,e,r,n,i,a,o,s,l,u){var c=e+a+u;if(f>0){var f=Math.sqrt(c+1);t[0]=.5*(o-l)/f,t[1]=.5*(s-n)/f,t[2]=.5*(r-a)/f,t[3]=.5*f}else{var h=Math.max(e,a,u);f=Math.sqrt(2*h-c+1),e>=h?(t[0]=.5*f,t[1]=.5*(i+r)/f,t[2]=.5*(s+n)/f,t[3]=.5*(o-l)/f):a>=h?(t[0]=.5*(r+i)/f,t[1]=.5*f,t[2]=.5*(l+o)/f,t[3]=.5*(s-n)/f):(t[0]=.5*(n+s)/f,t[1]=.5*(o+l)/f,t[2]=.5*f,t[3]=.5*(r-i)/f)}return t}},7774:function(t,e,r){\"use strict\";t.exports=function(t){var e=(t=t||{}).center||[0,0,0],r=t.rotation||[0,0,0,1],n=t.radius||1;e=[].slice.call(e,0,3),c(r=[].slice.call(r,0,4),r);var i=new f(r,e,Math.log(n));return i.setDistanceLimits(t.zoomMin,t.zoomMax),(\"eye\"in t||\"up\"in t)&&i.lookAt(0,t.eye,t.center,t.up),i};var n=r(8444),i=r(3012),a=r(5950),o=r(7437),s=r(567);function l(t,e,r){return Math.sqrt(Math.pow(t,2)+Math.pow(e,2)+Math.pow(r,2))}function u(t,e,r,n){return Math.sqrt(Math.pow(t,2)+Math.pow(e,2)+Math.pow(r,2)+Math.pow(n,2))}function c(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=u(r,n,i,a);o>1e-6?(t[0]=r/o,t[1]=n/o,t[2]=i/o,t[3]=a/o):(t[0]=t[1]=t[2]=0,t[3]=1)}function f(t,e,r){this.radius=n([r]),this.center=n(e),this.rotation=n(t),this.computedRadius=this.radius.curve(0),this.computedCenter=this.center.curve(0),this.computedRotation=this.rotation.curve(0),this.computedUp=[.1,0,0],this.computedEye=[.1,0,0],this.computedMatrix=[.1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],this.recalcMatrix(0)}var h=f.prototype;h.lastT=function(){return Math.max(this.radius.lastT(),this.center.lastT(),this.rotation.lastT())},h.recalcMatrix=function(t){this.radius.curve(t),this.center.curve(t),this.rotation.curve(t);var e=this.computedRotation;c(e,e);var r=this.computedMatrix;a(r,e);var n=this.computedCenter,i=this.computedEye,o=this.computedUp,s=Math.exp(this.computedRadius[0]);i[0]=n[0]+s*r[2],i[1]=n[1]+s*r[6],i[2]=n[2]+s*r[10],o[0]=r[1],o[1]=r[5],o[2]=r[9];for(var l=0;l<3;++l){for(var 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Sr=function(t,e){this.type=Xt,this.needle=t,this.haystack=e};Sr.parse=function(t,e){if(3!==t.length)return e.error(\"Expected 2 arguments, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1,Jt),n=e.parse(t[2],2,Jt);return r&&n?ae(r.type,[Xt,Yt,Wt,Gt,Jt])?new Sr(r,n):e.error(\"Expected first argument to be of type boolean, string, number or null, but found \"+re(r.type)+\" instead\"):null},Sr.prototype.evaluate=function(t){var e=this.needle.evaluate(t),r=this.haystack.evaluate(t);if(!r)return!1;if(!oe(e,[\"boolean\",\"string\",\"number\",\"null\"]))throw new xe(\"Expected first argument to be of type boolean, string, number or null, but found \"+re(ge(e))+\" instead.\");if(!oe(r,[\"string\",\"array\"]))throw new xe(\"Expected second argument to be of type array or string, but found \"+re(ge(r))+\" instead.\");return r.indexOf(e)>=0},Sr.prototype.eachChild=function(t){t(this.needle),t(this.haystack)},Sr.prototype.outputDefined=function(){return!0},Sr.prototype.serialize=function(){return[\"in\",this.needle.serialize(),this.haystack.serialize()]};var Er=function(t,e,r){this.type=Wt,this.needle=t,this.haystack=e,this.fromIndex=r};Er.parse=function(t,e){if(t.length<=2||t.length>=5)return e.error(\"Expected 3 or 4 arguments, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1,Jt),n=e.parse(t[2],2,Jt);if(!r||!n)return null;if(!ae(r.type,[Xt,Yt,Wt,Gt,Jt]))return e.error(\"Expected first argument to be of type boolean, string, number or null, but found \"+re(r.type)+\" instead\");if(4===t.length){var i=e.parse(t[3],3,Wt);return i?new Er(r,n,i):null}return new Er(r,n)},Er.prototype.evaluate=function(t){var e=this.needle.evaluate(t),r=this.haystack.evaluate(t);if(!oe(e,[\"boolean\",\"string\",\"number\",\"null\"]))throw new xe(\"Expected first argument to be of type boolean, string, number or 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e={color:Zt,string:Yt,number:Wt,enum:Yt,boolean:Xt,formatted:Qt,resolvedImage:te};return\"array\"===t.type?ee(e[t.value]||Jt,t.length):e[t.type]}(e):void 0),n=r.parse(t,void 0,void 0,void 0,e&&\"string\"===e.type?{typeAnnotation:\"coerce\"}:void 0);return n?Xr(new un(n,e)):Zr(r.errors)}un.prototype.evaluateWithoutErrorHandling=function(t,e,r,n,i,a){return this._evaluator.globals=t,this._evaluator.feature=e,this._evaluator.featureState=r,this._evaluator.canonical=n,this._evaluator.availableImages=i||null,this._evaluator.formattedSection=a,this.expression.evaluate(this._evaluator)},un.prototype.evaluate=function(t,e,r,n,i,a){this._evaluator.globals=t,this._evaluator.feature=e||null,this._evaluator.featureState=r||null,this._evaluator.canonical=n,this._evaluator.availableImages=i||null,this._evaluator.formattedSection=a||null;try{var o=this.expression.evaluate(this._evaluator);if(null==o||\"number\"==typeof o&&o!=o)return this._defaultValue;if(this._enumValues&&!(o in this._enumValues))throw new xe(\"Expected value to be one of \"+Object.keys(this._enumValues).map((function(t){return JSON.stringify(t)})).join(\", \")+\", but found \"+JSON.stringify(o)+\" instead.\");return o}catch(t){return this._warningHistory[t.message]||(this._warningHistory[t.message]=!0,\"undefined\"!=typeof console&&console.warn(t.message)),this._defaultValue}};var hn=function(t,e){this.kind=t,this._styleExpression=e,this.isStateDependent=\"constant\"!==t&&!Xe(e.expression)};hn.prototype.evaluateWithoutErrorHandling=function(t,e,r,n,i,a){return this._styleExpression.evaluateWithoutErrorHandling(t,e,r,n,i,a)},hn.prototype.evaluate=function(t,e,r,n,i,a){return this._styleExpression.evaluate(t,e,r,n,i,a)};var pn=function(t,e,r,n){this.kind=t,this.zoomStops=r,this._styleExpression=e,this.isStateDependent=\"camera\"!==t&&!Xe(e.expression),this.interpolationType=n};function dn(t,e){if(\"error\"===(t=fn(t,e)).result)return t;var r=t.value.expression,n=Ye(r);if(!n&&!Kr(e))return Zr([new qt(\"\",\"data expressions not supported\")]);var i=Ze(r,[\"zoom\"]);if(!i&&!Jr(e))return Zr([new qt(\"\",\"zoom expressions not supported\")]);var a=gn(r);if(!a&&!i)return Zr([new qt(\"\",'\"zoom\" expression may only be used as input to a top-level \"step\" or \"interpolate\" expression.')]);if(a instanceof qt)return Zr([a]);if(a instanceof wr&&!$r(e))return Zr([new qt(\"\",'\"interpolate\" expressions cannot be used with this property')]);if(!a)return Xr(new hn(n?\"constant\":\"source\",t.value));var o=a instanceof wr?a.interpolation:void 0;return Xr(new pn(n?\"camera\":\"composite\",t.value,a.labels,o))}pn.prototype.evaluateWithoutErrorHandling=function(t,e,r,n,i,a){return this._styleExpression.evaluateWithoutErrorHandling(t,e,r,n,i,a)},pn.prototype.evaluate=function(t,e,r,n,i,a){return this._styleExpression.evaluate(t,e,r,n,i,a)},pn.prototype.interpolationFactor=function(t,e,r){return this.interpolationType?wr.interpolationFactor(this.interpolationType,t,e,r):0};var vn=function(t,e){this._parameters=t,this._specification=e,jt(this,rn(this._parameters,this._specification))};function gn(t){var e=null;if(t instanceof Ar)e=gn(t.result);else if(t instanceof kr)for(var r=0,n=t.args;r<n.length;r+=1){var i=n[r];if(e=gn(i))break}else(t instanceof tr||t instanceof wr)&&t.input instanceof Ee&&\"zoom\"===t.input.name&&(e=t);return e instanceof qt||t.eachChild((function(t){var r=gn(t);r instanceof qt?e=r:!e&&r?e=new qt(\"\",'\"zoom\" expression may only be used as input to a top-level \"step\" or \"interpolate\" expression.'):e&&r&&e!==r&&(e=new qt(\"\",'Only one zoom-based \"step\" or \"interpolate\" subexpression may be used in an expression.'))})),e}function yn(t){var e=t.key,r=t.value,n=t.valueSpec||{},i=t.objectElementValidators||{},a=t.style,o=t.styleSpec,s=[],l=Qr(r);if(\"object\"!==l)return[new Bt(e,r,\"object expected, \"+l+\" found\")];for(var u in r){var c=u.split(\".\")[0],f=n[c]||n[\"*\"],h=void 0;if(i[c])h=i[c];else if(n[c])h=Hn;else if(i[\"*\"])h=i[\"*\"];else{if(!n[\"*\"]){s.push(new Bt(e,r[u],'unknown property \"'+u+'\"'));continue}h=Hn}s=s.concat(h({key:(e?e+\".\":e)+u,value:r[u],valueSpec:f,style:a,styleSpec:o,object:r,objectKey:u},r))}for(var p in n)i[p]||n[p].required&&void 0===n[p].default&&void 0===r[p]&&s.push(new Bt(e,r,'missing required property \"'+p+'\"'));return s}function mn(t){var e=t.value,r=t.valueSpec,n=t.style,i=t.styleSpec,a=t.key,o=t.arrayElementValidator||Hn;if(\"array\"!==Qr(e))return[new Bt(a,e,\"array expected, \"+Qr(e)+\" found\")];if(r.length&&e.length!==r.length)return[new Bt(a,e,\"array length \"+r.length+\" expected, length \"+e.length+\" found\")];if(r[\"min-length\"]&&e.length<r[\"min-length\"])return[new Bt(a,e,\"array length at least \"+r[\"min-length\"]+\" expected, length \"+e.length+\" found\")];var s={type:r.value,values:r.values};i.$version<7&&(s.function=r.function),\"object\"===Qr(r.value)&&(s=r.value);for(var l=[],u=0;u<e.length;u++)l=l.concat(o({array:e,arrayIndex:u,value:e[u],valueSpec:s,style:n,styleSpec:i,key:a+\"[\"+u+\"]\"}));return l}function xn(t){var e=t.key,r=t.value,n=t.valueSpec,i=Qr(r);return\"number\"===i&&r!=r&&(i=\"NaN\"),\"number\"!==i?[new Bt(e,r,\"number expected, \"+i+\" found\")]:\"minimum\"in n&&r<n.minimum?[new Bt(e,r,r+\" is less than the minimum value \"+n.minimum)]:\"maximum\"in n&&r>n.maximum?[new Bt(e,r,r+\" is greater than the maximum value \"+n.maximum)]:[]}function bn(t){var e,r,n,i=t.valueSpec,a=Ut(t.value.type),o={},s=\"categorical\"!==a&&void 0===t.value.property,l=!s,u=\"array\"===Qr(t.value.stops)&&\"array\"===Qr(t.value.stops[0])&&\"object\"===Qr(t.value.stops[0][0]),c=yn({key:t.key,value:t.value,valueSpec:t.styleSpec.function,style:t.style,styleSpec:t.styleSpec,objectElementValidators:{stops:function(t){if(\"identity\"===a)return[new Bt(t.key,t.value,'identity function may not have a \"stops\" property')];var e=[],r=t.value;return e=e.concat(mn({key:t.key,value:r,valueSpec:t.valueSpec,style:t.style,styleSpec:t.styleSpec,arrayElementValidator:f})),\"array\"===Qr(r)&&0===r.length&&e.push(new Bt(t.key,r,\"array must have at least one stop\")),e},default:function(t){return Hn({key:t.key,value:t.value,valueSpec:i,style:t.style,styleSpec:t.styleSpec})}}});return\"identity\"===a&&s&&c.push(new Bt(t.key,t.value,'missing required property \"property\"')),\"identity\"===a||t.value.stops||c.push(new Bt(t.key,t.value,'missing required property \"stops\"')),\"exponential\"===a&&t.valueSpec.expression&&!$r(t.valueSpec)&&c.push(new Bt(t.key,t.value,\"exponential functions not supported\")),t.styleSpec.$version>=8&&(l&&!Kr(t.valueSpec)?c.push(new Bt(t.key,t.value,\"property functions not supported\")):s&&!Jr(t.valueSpec)&&c.push(new Bt(t.key,t.value,\"zoom functions not supported\"))),\"categorical\"!==a&&!u||void 0!==t.value.property||c.push(new Bt(t.key,t.value,'\"property\" property is required')),c;function f(t){var e=[],a=t.value,s=t.key;if(\"array\"!==Qr(a))return[new Bt(s,a,\"array expected, \"+Qr(a)+\" found\")];if(2!==a.length)return[new Bt(s,a,\"array length 2 expected, length \"+a.length+\" found\")];if(u){if(\"object\"!==Qr(a[0]))return[new Bt(s,a,\"object expected, \"+Qr(a[0])+\" found\")];if(void 0===a[0].zoom)return[new Bt(s,a,\"object stop key must have zoom\")];if(void 0===a[0].value)return[new Bt(s,a,\"object stop key must have value\")];if(n&&n>Ut(a[0].zoom))return[new Bt(s,a[0].zoom,\"stop zoom values must appear in ascending order\")];Ut(a[0].zoom)!==n&&(n=Ut(a[0].zoom),r=void 0,o={}),e=e.concat(yn({key:s+\"[0]\",value:a[0],valueSpec:{zoom:{}},style:t.style,styleSpec:t.styleSpec,objectElementValidators:{zoom:xn,value:h}}))}else e=e.concat(h({key:s+\"[0]\",value:a[0],valueSpec:{},style:t.style,styleSpec:t.styleSpec},a));return cn(Vt(a[1]))?e.concat([new Bt(s+\"[1]\",a[1],\"expressions are not allowed in function stops.\")]):e.concat(Hn({key:s+\"[1]\",value:a[1],valueSpec:i,style:t.style,styleSpec:t.styleSpec}))}function h(t,n){var s=Qr(t.value),l=Ut(t.value),u=null!==t.value?t.value:n;if(e){if(s!==e)return[new Bt(t.key,u,s+\" stop domain type must match previous stop domain type \"+e)]}else e=s;if(\"number\"!==s&&\"string\"!==s&&\"boolean\"!==s)return[new Bt(t.key,u,\"stop domain value must be a number, string, or boolean\")];if(\"number\"!==s&&\"categorical\"!==a){var c=\"number expected, \"+s+\" found\";return Kr(i)&&void 0===a&&(c+='\\nIf you intended to use a categorical function, specify `\"type\": \"categorical\"`.'),[new Bt(t.key,u,c)]}return\"categorical\"!==a||\"number\"!==s||isFinite(l)&&Math.floor(l)===l?\"categorical\"!==a&&\"number\"===s&&void 0!==r&&l<r?[new Bt(t.key,u,\"stop domain values must appear in ascending order\")]:(r=l,\"categorical\"===a&&l in o?[new Bt(t.key,u,\"stop domain values must be unique\")]:(o[l]=!0,[])):[new Bt(t.key,u,\"integer expected, found \"+l)]}}function _n(t){var e=(\"property\"===t.expressionContext?dn:fn)(Vt(t.value),t.valueSpec);if(\"error\"===e.result)return e.value.map((function(e){return new Bt(\"\"+t.key+e.key,t.value,e.message)}));var r=e.value.expression||e.value._styleExpression.expression;if(\"property\"===t.expressionContext&&\"text-font\"===t.propertyKey&&!r.outputDefined())return[new Bt(t.key,t.value,'Invalid data expression for \"'+t.propertyKey+'\". Output values must be contained as literals within the expression.')];if(\"property\"===t.expressionContext&&\"layout\"===t.propertyType&&!Xe(r))return[new Bt(t.key,t.value,'\"feature-state\" data expressions are not supported with layout properties.')];if(\"filter\"===t.expressionContext&&!Xe(r))return[new Bt(t.key,t.value,'\"feature-state\" data expressions are not supported with filters.')];if(t.expressionContext&&0===t.expressionContext.indexOf(\"cluster\")){if(!Ze(r,[\"zoom\",\"feature-state\"]))return[new Bt(t.key,t.value,'\"zoom\" and \"feature-state\" expressions are not supported with cluster properties.')];if(\"cluster-initial\"===t.expressionContext&&!Ye(r))return[new Bt(t.key,t.value,\"Feature data expressions are not supported with initial expression part of cluster properties.\")]}return[]}function wn(t){var e=t.key,r=t.value,n=t.valueSpec,i=[];return Array.isArray(n.values)?-1===n.values.indexOf(Ut(r))&&i.push(new Bt(e,r,\"expected one of [\"+n.values.join(\", \")+\"], \"+JSON.stringify(r)+\" found\")):-1===Object.keys(n.values).indexOf(Ut(r))&&i.push(new Bt(e,r,\"expected one of [\"+Object.keys(n.values).join(\", \")+\"], \"+JSON.stringify(r)+\" found\")),i}function Tn(t){if(!0===t||!1===t)return!0;if(!Array.isArray(t)||0===t.length)return!1;switch(t[0]){case\"has\":return t.length>=2&&\"$id\"!==t[1]&&\"$type\"!==t[1];case\"in\":return t.length>=3&&(\"string\"!=typeof t[1]||Array.isArray(t[2]));case\"!in\":case\"!has\":case\"none\":return!1;case\"==\":case\"!=\":case\">\":case\">=\":case\"<\":case\"<=\":return 3!==t.length||Array.isArray(t[1])||Array.isArray(t[2]);case\"any\":case\"all\":for(var e=0,r=t.slice(1);e<r.length;e+=1){var n=r[e];if(!Tn(n)&&\"boolean\"!=typeof n)return!1}return!0;default:return!0}}vn.deserialize=function(t){return new vn(t._parameters,t._specification)},vn.serialize=function(t){return{_parameters:t._parameters,_specification:t._specification}};var kn={type:\"boolean\",default:!1,transition:!1,\"property-type\":\"data-driven\",expression:{interpolated:!1,parameters:[\"zoom\",\"feature\"]}};function An(t){if(null==t)return{filter:function(){return!0},needGeometry:!1};Tn(t)||(t=En(t));var e=fn(t,kn);if(\"error\"===e.result)throw new Error(e.value.map((function(t){return t.key+\": \"+t.message})).join(\", \"));return{filter:function(t,r,n){return e.value.evaluate(t,r,{},n)},needGeometry:Sn(t)}}function Mn(t,e){return t<e?-1:t>e?1:0}function Sn(t){if(!Array.isArray(t))return!1;if(\"within\"===t[0])return!0;for(var e=1;e<t.length;e++)if(Sn(t[e]))return!0;return!1}function En(t){if(!t)return!0;var e,r=t[0];return t.length<=1?\"any\"!==r:\"==\"===r?Ln(t[1],t[2],\"==\"):\"!=\"===r?On(Ln(t[1],t[2],\"==\")):\"<\"===r||\">\"===r||\"<=\"===r||\">=\"===r?Ln(t[1],t[2],r):\"any\"===r?(e=t.slice(1),[\"any\"].concat(e.map(En))):\"all\"===r?[\"all\"].concat(t.slice(1).map(En)):\"none\"===r?[\"all\"].concat(t.slice(1).map(En).map(On)):\"in\"===r?Cn(t[1],t.slice(2)):\"!in\"===r?On(Cn(t[1],t.slice(2))):\"has\"===r?Pn(t[1]):\"!has\"===r?On(Pn(t[1])):\"within\"!==r||t}function Ln(t,e,r){switch(t){case\"$type\":return[\"filter-type-\"+r,e];case\"$id\":return[\"filter-id-\"+r,e];default:return[\"filter-\"+r,t,e]}}function Cn(t,e){if(0===e.length)return!1;switch(t){case\"$type\":return[\"filter-type-in\",[\"literal\",e]];case\"$id\":return[\"filter-id-in\",[\"literal\",e]];default:return e.length>200&&!e.some((function(t){return typeof t!=typeof e[0]}))?[\"filter-in-large\",t,[\"literal\",e.sort(Mn)]]:[\"filter-in-small\",t,[\"literal\",e]]}}function Pn(t){switch(t){case\"$type\":return!0;case\"$id\":return[\"filter-has-id\"];default:return[\"filter-has\",t]}}function On(t){return[\"!\",t]}function In(t){return Tn(Vt(t.value))?_n(jt({},t,{expressionContext:\"filter\",valueSpec:{value:\"boolean\"}})):Dn(t)}function Dn(t){var e=t.value,r=t.key;if(\"array\"!==Qr(e))return[new Bt(r,e,\"array expected, \"+Qr(e)+\" found\")];var n,i=t.styleSpec,a=[];if(e.length<1)return[new Bt(r,e,\"filter array must have at least 1 element\")];switch(a=a.concat(wn({key:r+\"[0]\",value:e[0],valueSpec:i.filter_operator,style:t.style,styleSpec:t.styleSpec})),Ut(e[0])){case\"<\":case\"<=\":case\">\":case\">=\":e.length>=2&&\"$type\"===Ut(e[1])&&a.push(new Bt(r,e,'\"$type\" cannot be use with operator \"'+e[0]+'\"'));case\"==\":case\"!=\":3!==e.length&&a.push(new Bt(r,e,'filter array for operator \"'+e[0]+'\" must have 3 elements'));case\"in\":case\"!in\":e.length>=2&&\"string\"!==(n=Qr(e[1]))&&a.push(new Bt(r+\"[1]\",e[1],\"string expected, \"+n+\" found\"));for(var o=2;o<e.length;o++)n=Qr(e[o]),\"$type\"===Ut(e[1])?a=a.concat(wn({key:r+\"[\"+o+\"]\",value:e[o],valueSpec:i.geometry_type,style:t.style,styleSpec:t.styleSpec})):\"string\"!==n&&\"number\"!==n&&\"boolean\"!==n&&a.push(new Bt(r+\"[\"+o+\"]\",e[o],\"string, number, or boolean expected, \"+n+\" found\"));break;case\"any\":case\"all\":case\"none\":for(var s=1;s<e.length;s++)a=a.concat(Dn({key:r+\"[\"+s+\"]\",value:e[s],style:t.style,styleSpec:t.styleSpec}));break;case\"has\":case\"!has\":n=Qr(e[1]),2!==e.length?a.push(new Bt(r,e,'filter array for \"'+e[0]+'\" operator must have 2 elements')):\"string\"!==n&&a.push(new Bt(r+\"[1]\",e[1],\"string expected, \"+n+\" found\"));break;case\"within\":n=Qr(e[1]),2!==e.length?a.push(new Bt(r,e,'filter array for \"'+e[0]+'\" operator must have 2 elements')):\"object\"!==n&&a.push(new Bt(r+\"[1]\",e[1],\"object expected, \"+n+\" found\"))}return a}function zn(t,e){var r=t.key,n=t.style,i=t.styleSpec,a=t.value,o=t.objectKey,s=i[e+\"_\"+t.layerType];if(!s)return[];var l=o.match(/^(.*)-transition$/);if(\"paint\"===e&&l&&s[l[1]]&&s[l[1]].transition)return Hn({key:r,value:a,valueSpec:i.transition,style:n,styleSpec:i});var u,c=t.valueSpec||s[o];if(!c)return[new Bt(r,a,'unknown property \"'+o+'\"')];if(\"string\"===Qr(a)&&Kr(c)&&!c.tokens&&(u=/^{([^}]+)}$/.exec(a)))return[new Bt(r,a,'\"'+o+'\" does not support interpolation syntax\\nUse an identity property function instead: `{ \"type\": \"identity\", \"property\": '+JSON.stringify(u[1])+\" }`.\")];var f=[];return\"symbol\"===t.layerType&&(\"text-field\"===o&&n&&!n.glyphs&&f.push(new Bt(r,a,'use of \"text-field\" requires a style \"glyphs\" property')),\"text-font\"===o&&tn(Vt(a))&&\"identity\"===Ut(a.type)&&f.push(new Bt(r,a,'\"text-font\" does not support identity 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h=i.sources&&i.sources[r.source],p=h&&Ut(h.type);h?\"vector\"===p&&\"raster\"===s?e.push(new Bt(n,r.source,'layer \"'+r.id+'\" requires a raster source')):\"raster\"===p&&\"raster\"!==s?e.push(new Bt(n,r.source,'layer \"'+r.id+'\" requires a vector source')):\"vector\"!==p||r[\"source-layer\"]?\"raster-dem\"===p&&\"hillshade\"!==s?e.push(new Bt(n,r.source,\"raster-dem source can only be used with layer type 'hillshade'.\")):\"line\"!==s||!r.paint||!r.paint[\"line-gradient\"]||\"geojson\"===p&&h.lineMetrics||e.push(new Bt(n,r,'layer \"'+r.id+'\" specifies a line-gradient, which requires a GeoJSON source with `lineMetrics` enabled.')):e.push(new Bt(n,r,'layer \"'+r.id+'\" must specify a \"source-layer\"')):e.push(new Bt(n,r.source,'source \"'+r.source+'\" not found'))}else e.push(new Bt(n,r,'missing required property \"source\"'));return 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Arrows\"](t)&&(t>=11026&&t<=11055||t>=11088&&t<=11097||t>=11192&&t<=11243)||pi[\"CJK Symbols and Punctuation\"](t)||pi.Katakana(t)||pi[\"Private Use Area\"](t)||pi[\"CJK Compatibility Forms\"](t)||pi[\"Small Form Variants\"](t)||pi[\"Halfwidth and Fullwidth Forms\"](t)||8734===t||8756===t||8757===t||t>=9984&&t<=10087||t>=10102&&t<=10131||65532===t||65533===t)}(t))}function yi(t){return pi.Arabic(t)||pi[\"Arabic Supplement\"](t)||pi[\"Arabic Extended-A\"](t)||pi[\"Arabic Presentation Forms-A\"](t)||pi[\"Arabic Presentation Forms-B\"](t)}function mi(t){return t>=1424&&t<=2303||pi[\"Arabic Presentation Forms-A\"](t)||pi[\"Arabic Presentation Forms-B\"](t)}function xi(t,e){return!(!e&&mi(t)||t>=2304&&t<=3583||t>=3840&&t<=4255||pi.Khmer(t))}function bi(t){for(var e=0,r=t;e<r.length;e+=1)if(mi(r[e].charCodeAt(0)))return!0;return!1}var _i=\"deferred\",wi=\"loading\",Ti=\"loaded\",ki=\"error\",Ai=null,Mi=\"unavailable\",Si=null,Ei=function(t){t&&\"string\"==typeof t&&t.indexOf(\"NetworkError\")>-1&&(Mi=ki),Ai&&Ai(t)};function Li(){Ci.fire(new Dt(\"pluginStateChange\",{pluginStatus:Mi,pluginURL:Si}))}var Ci=new Rt,Pi=function(){return Mi},Oi=function(){if(Mi!==_i||!Si)throw new Error(\"rtl-text-plugin cannot be downloaded unless a pluginURL is specified\");Mi=wi,Li(),Si&&Mt({url:Si},(function(t){t?Ei(t):(Mi=Ti,Li())}))},Ii={applyArabicShaping:null,processBidirectionalText:null,processStyledBidirectionalText:null,isLoaded:function(){return Mi===Ti||null!=Ii.applyArabicShaping},isLoading:function(){return Mi===wi},setState:function(t){Mi=t.pluginStatus,Si=t.pluginURL},isParsed:function(){return null!=Ii.applyArabicShaping&&null!=Ii.processBidirectionalText&&null!=Ii.processStyledBidirectionalText},getPluginURL:function(){return Si}},Di=function(t,e){this.zoom=t,e?(this.now=e.now,this.fadeDuration=e.fadeDuration,this.zoomHistory=e.zoomHistory,this.transition=e.transition):(this.now=0,this.fadeDuration=0,this.zoomHistory=new hi,this.transition={})};Di.prototype.isSupportedScript=function(t){return function(t,e){for(var r=0,n=t;r<n.length;r+=1)if(!xi(n[r].charCodeAt(0),e))return!1;return!0}(t,Ii.isLoaded())},Di.prototype.crossFadingFactor=function(){return 0===this.fadeDuration?1:Math.min((this.now-this.zoomHistory.lastIntegerZoomTime)/this.fadeDuration,1)},Di.prototype.getCrossfadeParameters=function(){var t=this.zoom,e=t-Math.floor(t),r=this.crossFadingFactor();return t>this.zoomHistory.lastIntegerZoom?{fromScale:2,toScale:1,t:e+(1-e)*r}:{fromScale:.5,toScale:1,t:1-(1-r)*e}};var zi=function(t,e){this.property=t,this.value=e,this.expression=function(t,e){if(tn(t))return new vn(t,e);if(cn(t)){var r=dn(t,e);if(\"error\"===r.result)throw new Error(r.value.map((function(t){return t.key+\": \"+t.message})).join(\", \"));return r.value}var n=t;return\"string\"==typeof t&&\"color\"===e.type&&(n=ue.parse(t)),{kind:\"constant\",evaluate:function(){return n}}}(void 0===e?t.specification.default:e,t.specification)};zi.prototype.isDataDriven=function(){return\"source\"===this.expression.kind||\"composite\"===this.expression.kind},zi.prototype.possiblyEvaluate=function(t,e,r){return this.property.possiblyEvaluate(this,t,e,r)};var Ri=function(t){this.property=t,this.value=new zi(t,void 0)};Ri.prototype.transitioned=function(t,e){return new Bi(this.property,this.value,e,p({},t.transition,this.transition),t.now)},Ri.prototype.untransitioned=function(){return new Bi(this.property,this.value,null,{},0)};var Fi=function(t){this._properties=t,this._values=Object.create(t.defaultTransitionablePropertyValues)};Fi.prototype.getValue=function(t){return w(this._values[t].value.value)},Fi.prototype.setValue=function(t,e){this._values.hasOwnProperty(t)||(this._values[t]=new Ri(this._values[t].property)),this._values[t].value=new zi(this._values[t].property,null===e?void 0:w(e))},Fi.prototype.getTransition=function(t){return w(this._values[t].transition)},Fi.prototype.setTransition=function(t,e){this._values.hasOwnProperty(t)||(this._values[t]=new Ri(this._values[t].property)),this._values[t].transition=w(e)||void 0},Fi.prototype.serialize=function(){for(var t={},e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e],i=this.getValue(n);void 0!==i&&(t[n]=i);var a=this.getTransition(n);void 0!==a&&(t[n+\"-transition\"]=a)}return t},Fi.prototype.transitioned=function(t,e){for(var r=new Ni(this._properties),n=0,i=Object.keys(this._values);n<i.length;n+=1){var a=i[n];r._values[a]=this._values[a].transitioned(t,e._values[a])}return r},Fi.prototype.untransitioned=function(){for(var t=new Ni(this._properties),e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e];t._values[n]=this._values[n].untransitioned()}return t};var Bi=function(t,e,r,n,i){this.property=t,this.value=e,this.begin=i+n.delay||0,this.end=this.begin+n.duration||0,t.specification.transition&&(n.delay||n.duration)&&(this.prior=r)};Bi.prototype.possiblyEvaluate=function(t,e,r){var n=t.now||0,i=this.value.possiblyEvaluate(t,e,r),a=this.prior;if(a){if(n>this.end)return this.prior=null,i;if(this.value.isDataDriven())return this.prior=null,i;if(n<this.begin)return a.possiblyEvaluate(t,e,r);var o=(n-this.begin)/(this.end-this.begin);return this.property.interpolate(a.possiblyEvaluate(t,e,r),i,function(t){if(t<=0)return 0;if(t>=1)return 1;var e=t*t,r=e*t;return 4*(t<.5?r:3*(t-e)+r-.75)}(o))}return i};var Ni=function(t){this._properties=t,this._values=Object.create(t.defaultTransitioningPropertyValues)};Ni.prototype.possiblyEvaluate=function(t,e,r){for(var n=new Vi(this._properties),i=0,a=Object.keys(this._values);i<a.length;i+=1){var o=a[i];n._values[o]=this._values[o].possiblyEvaluate(t,e,r)}return n},Ni.prototype.hasTransition=function(){for(var t=0,e=Object.keys(this._values);t<e.length;t+=1){var r=e[t];if(this._values[r].prior)return!0}return!1};var ji=function(t){this._properties=t,this._values=Object.create(t.defaultPropertyValues)};ji.prototype.getValue=function(t){return w(this._values[t].value)},ji.prototype.setValue=function(t,e){this._values[t]=new zi(this._values[t].property,null===e?void 0:w(e))},ji.prototype.serialize=function(){for(var t={},e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e],i=this.getValue(n);void 0!==i&&(t[n]=i)}return t},ji.prototype.possiblyEvaluate=function(t,e,r){for(var n=new Vi(this._properties),i=0,a=Object.keys(this._values);i<a.length;i+=1){var o=a[i];n._values[o]=this._values[o].possiblyEvaluate(t,e,r)}return n};var Ui=function(t,e,r){this.property=t,this.value=e,this.parameters=r};Ui.prototype.isConstant=function(){return\"constant\"===this.value.kind},Ui.prototype.constantOr=function(t){return\"constant\"===this.value.kind?this.value.value:t},Ui.prototype.evaluate=function(t,e,r,n){return this.property.evaluate(this.value,this.parameters,t,e,r,n)};var Vi=function(t){this._properties=t,this._values=Object.create(t.defaultPossiblyEvaluatedValues)};Vi.prototype.get=function(t){return this._values[t]};var qi=function(t){this.specification=t};qi.prototype.possiblyEvaluate=function(t,e){return t.expression.evaluate(e)},qi.prototype.interpolate=function(t,e,r){var n=rr[this.specification.type];return n?n(t,e,r):t};var Hi=function(t,e){this.specification=t,this.overrides=e};Hi.prototype.possiblyEvaluate=function(t,e,r,n){return\"constant\"===t.expression.kind||\"camera\"===t.expression.kind?new Ui(this,{kind:\"constant\",value:t.expression.evaluate(e,null,{},r,n)},e):new Ui(this,t.expression,e)},Hi.prototype.interpolate=function(t,e,r){if(\"constant\"!==t.value.kind||\"constant\"!==e.value.kind)return t;if(void 0===t.value.value||void 0===e.value.value)return new Ui(this,{kind:\"constant\",value:void 0},t.parameters);var n=rr[this.specification.type];return n?new Ui(this,{kind:\"constant\",value:n(t.value.value,e.value.value,r)},t.parameters):t},Hi.prototype.evaluate=function(t,e,r,n,i,a){return\"constant\"===t.kind?t.value:t.evaluate(e,r,n,i,a)};var Gi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.possiblyEvaluate=function(t,e,r,n){if(void 0===t.value)return new Ui(this,{kind:\"constant\",value:void 0},e);if(\"constant\"===t.expression.kind){var i=t.expression.evaluate(e,null,{},r,n),a=\"resolvedImage\"===t.property.specification.type&&\"string\"!=typeof i?i.name:i,o=this._calculate(a,a,a,e);return new Ui(this,{kind:\"constant\",value:o},e)}if(\"camera\"===t.expression.kind){var s=this._calculate(t.expression.evaluate({zoom:e.zoom-1}),t.expression.evaluate({zoom:e.zoom}),t.expression.evaluate({zoom:e.zoom+1}),e);return new Ui(this,{kind:\"constant\",value:s},e)}return new Ui(this,t.expression,e)},e.prototype.evaluate=function(t,e,r,n,i,a){if(\"source\"===t.kind){var o=t.evaluate(e,r,n,i,a);return this._calculate(o,o,o,e)}return\"composite\"===t.kind?this._calculate(t.evaluate({zoom:Math.floor(e.zoom)-1},r,n),t.evaluate({zoom:Math.floor(e.zoom)},r,n),t.evaluate({zoom:Math.floor(e.zoom)+1},r,n),e):t.value},e.prototype._calculate=function(t,e,r,n){return n.zoom>n.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}},e.prototype.interpolate=function(t){return t},e}(Hi),Wi=function(t){this.specification=t};Wi.prototype.possiblyEvaluate=function(t,e,r,n){if(void 0!==t.value){if(\"constant\"===t.expression.kind){var i=t.expression.evaluate(e,null,{},r,n);return 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Vi(r.paint)}}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getCrossfadeParameters=function(){return this._crossfadeParameters},e.prototype.getLayoutProperty=function(t){return\"visibility\"===t?this.visibility:this._unevaluatedLayout.getValue(t)},e.prototype.setLayoutProperty=function(t,e,r){if(void 0===r&&(r={}),null!=e){var n=\"layers.\"+this.id+\".layout.\"+t;if(this._validate($n,n,t,e,r))return}\"visibility\"!==t?this._unevaluatedLayout.setValue(t,e):this.visibility=e},e.prototype.getPaintProperty=function(t){return x(t,Zi)?this._transitionablePaint.getTransition(t.slice(0,-11)):this._transitionablePaint.getValue(t)},e.prototype.setPaintProperty=function(t,e,r){if(void 0===r&&(r={}),null!=e){var n=\"layers.\"+this.id+\".paint.\"+t;if(this._validate(Jn,n,t,e,r))return!1}if(x(t,Zi))return this._transitionablePaint.setTransition(t.slice(0,-11),e||void 0),!1;var i=this._transitionablePaint._values[t],a=\"cross-faded-data-driven\"===i.property.specification[\"property-type\"],o=i.value.isDataDriven(),s=i.value;this._transitionablePaint.setValue(t,e),this._handleSpecialPaintPropertyUpdate(t);var l=this._transitionablePaint._values[t].value;return l.isDataDriven()||o||a||this._handleOverridablePaintPropertyUpdate(t,s,l)},e.prototype._handleSpecialPaintPropertyUpdate=function(t){},e.prototype._handleOverridablePaintPropertyUpdate=function(t,e,r){return!1},e.prototype.isHidden=function(t){return!!(this.minzoom&&t<this.minzoom)||!!(this.maxzoom&&t>=this.maxzoom)||\"none\"===this.visibility},e.prototype.updateTransitions=function(t){this._transitioningPaint=this._transitionablePaint.transitioned(t,this._transitioningPaint)},e.prototype.hasTransition=function(){return this._transitioningPaint.hasTransition()},e.prototype.recalculate=function(t,e){t.getCrossfadeParameters&&(this._crossfadeParameters=t.getCrossfadeParameters()),this._unevaluatedLayout&&(this.layout=this._unevaluatedLayout.possiblyEvaluate(t,void 0,e)),this.paint=this._transitioningPaint.possiblyEvaluate(t,void 0,e)},e.prototype.serialize=function(){var t={id:this.id,type:this.type,source:this.source,\"source-layer\":this.sourceLayer,metadata:this.metadata,minzoom:this.minzoom,maxzoom:this.maxzoom,filter:this.filter,layout:this._unevaluatedLayout&&this._unevaluatedLayout.serialize(),paint:this._transitionablePaint&&this._transitionablePaint.serialize()};return this.visibility&&(t.layout=t.layout||{},t.layout.visibility=this.visibility),_(t,(function(t,e){return!(void 0===t||\"layout\"===e&&!Object.keys(t).length||\"paint\"===e&&!Object.keys(t).length)}))},e.prototype._validate=function(t,e,r,n,i){return void 0===i&&(i={}),(!i||!1!==i.validate)&&Qn(this,t.call(Zn,{key:e,layerType:this.type,objectKey:r,value:n,styleSpec:Ft,style:{glyphs:!0,sprite:!0}}))},e.prototype.is3D=function(){return!1},e.prototype.isTileClipped=function(){return!1},e.prototype.hasOffscreenPass=function(){return!1},e.prototype.resize=function(){},e.prototype.isStateDependent=function(){for(var t in this.paint._values){var e=this.paint.get(t);if(e instanceof Ui&&Kr(e.property.specification)&&(\"source\"===e.value.kind||\"composite\"===e.value.kind)&&e.value.isStateDependent)return!0}return!1},e}(Rt),Ji={Int8:Int8Array,Uint8:Uint8Array,Int16:Int16Array,Uint16:Uint16Array,Int32:Int32Array,Uint32:Uint32Array,Float32:Float32Array},$i=function(t,e){this._structArray=t,this._pos1=e*this.size,this._pos2=this._pos1/2,this._pos4=this._pos1/4,this._pos8=this._pos1/8},Qi=function(){this.isTransferred=!1,this.capacity=-1,this.resize(0)};function ta(t,e){void 0===e&&(e=1);var r=0,n=0;return{members:t.map((function(t){var i,a=(i=t.type,Ji[i].BYTES_PER_ELEMENT),o=r=ea(r,Math.max(e,a)),s=t.components||1;return n=Math.max(n,a),r+=a*s,{name:t.name,type:t.type,components:s,offset:o}})),size:ea(r,Math.max(n,e)),alignment:e}}function ea(t,e){return Math.ceil(t/e)*e}Qi.serialize=function(t,e){return t._trim(),e&&(t.isTransferred=!0,e.push(t.arrayBuffer)),{length:t.length,arrayBuffer:t.arrayBuffer}},Qi.deserialize=function(t){var e=Object.create(this.prototype);return e.arrayBuffer=t.arrayBuffer,e.length=t.length,e.capacity=t.arrayBuffer.byteLength/e.bytesPerElement,e._refreshViews(),e},Qi.prototype._trim=function(){this.length!==this.capacity&&(this.capacity=this.length,this.arrayBuffer=this.arrayBuffer.slice(0,this.length*this.bytesPerElement),this._refreshViews())},Qi.prototype.clear=function(){this.length=0},Qi.prototype.resize=function(t){this.reserve(t),this.length=t},Qi.prototype.reserve=function(t){if(t>this.capacity){this.capacity=Math.max(t,Math.floor(5*this.capacity),128),this.arrayBuffer=new 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this.int16[s+0]=e,this.int16[s+1]=r,this.int16[s+2]=n,this.int16[s+3]=i,this.int16[s+4]=a,this.int16[s+5]=o,t},e}(Qi);ia.prototype.bytesPerElement=12,oi(\"StructArrayLayout2i4i12\",ia);var aa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)},e.prototype.emplace=function(t,e,r,n,i,a,o){var s=4*t,l=8*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.uint8[l+4]=n,this.uint8[l+5]=i,this.uint8[l+6]=a,this.uint8[l+7]=o,t},e}(Qi);aa.prototype.bytesPerElement=8,oi(\"StructArrayLayout2i4ub8\",aa);var oa=function(t){function e(){t.apply(this,arguments)}return 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this._structArray.uint8[this._pos1+38]},r.hidden.set=function(t){this._structArray.uint8[this._pos1+38]=t},r.crossTileID.get=function(){return this._structArray.uint32[this._pos4+10]},r.crossTileID.set=function(t){this._structArray.uint32[this._pos4+10]=t},r.associatedIconIndex.get=function(){return this._structArray.int16[this._pos2+22]},Object.defineProperties(e.prototype,r),e}($i);Ma.prototype.size=48;var Sa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new Ma(this,t)},e}(ga);oi(\"PlacedSymbolArray\",Sa);var Ea=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var 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r.anchorX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorY.get=function(){return this._structArray.int16[this._pos2+1]},r.rightJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+2]},r.centerJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+3]},r.leftJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+4]},r.verticalPlacedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+5]},r.placedIconSymbolIndex.get=function(){return this._structArray.int16[this._pos2+6]},r.verticalPlacedIconSymbolIndex.get=function(){return this._structArray.int16[this._pos2+7]},r.key.get=function(){return this._structArray.uint16[this._pos2+8]},r.textBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+9]},r.textBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+10]},r.verticalTextBoxStartIndex.get=function(){return 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s=t;s<e;s++)this.paintVertexArray.emplace(s,r,n);this.maxValue=Math.max(this.maxValue,Math.abs(r),Math.abs(n))}},so.prototype.upload=function(t){this.paintVertexArray&&this.paintVertexArray.arrayBuffer&&(this.paintVertexBuffer&&this.paintVertexBuffer.buffer?this.paintVertexBuffer.updateData(this.paintVertexArray):this.paintVertexBuffer=t.createVertexBuffer(this.paintVertexArray,this.paintVertexAttributes,this.expression.isStateDependent))},so.prototype.destroy=function(){this.paintVertexBuffer&&this.paintVertexBuffer.destroy()},so.prototype.setUniform=function(t,e){var r=this.useIntegerZoom?Math.floor(e.zoom):e.zoom,n=f(this.expression.interpolationFactor(r,this.zoom,this.zoom+1),0,1);t.set(n)},so.prototype.getBinding=function(t,e,r){return new Ka(t,e)};var lo=function(t,e,r,n,i,a){this.expression=t,this.type=e,this.useIntegerZoom=r,this.zoom=n,this.layerId=a,this.zoomInPaintVertexArray=new i,this.zoomOutPaintVertexArray=new i};lo.prototype.populatePaintArray=function(t,e,r){var n=this.zoomInPaintVertexArray.length;this.zoomInPaintVertexArray.resize(t),this.zoomOutPaintVertexArray.resize(t),this._setPaintValues(n,t,e.patterns&&e.patterns[this.layerId],r)},lo.prototype.updatePaintArray=function(t,e,r,n,i){this._setPaintValues(t,e,r.patterns&&r.patterns[this.layerId],i)},lo.prototype._setPaintValues=function(t,e,r,n){if(n&&r){var i=r.min,a=r.mid,o=r.max,s=n[i],l=n[a],u=n[o];if(s&&l&&u)for(var c=t;c<e;c++)this.zoomInPaintVertexArray.emplace(c,l.tl[0],l.tl[1],l.br[0],l.br[1],s.tl[0],s.tl[1],s.br[0],s.br[1],l.pixelRatio,s.pixelRatio),this.zoomOutPaintVertexArray.emplace(c,l.tl[0],l.tl[1],l.br[0],l.br[1],u.tl[0],u.tl[1],u.br[0],u.br[1],l.pixelRatio,u.pixelRatio)}},lo.prototype.upload=function(t){this.zoomInPaintVertexArray&&this.zoomInPaintVertexArray.arrayBuffer&&this.zoomOutPaintVertexArray&&this.zoomOutPaintVertexArray.arrayBuffer&&(this.zoomInPaintVertexBuffer=t.createVertexBuffer(this.zoomInPaintVertexArray,Fa.members,this.expression.isStateDependent),this.zoomOutPaintVertexBuffer=t.createVertexBuffer(this.zoomOutPaintVertexArray,Fa.members,this.expression.isStateDependent))},lo.prototype.destroy=function(){this.zoomOutPaintVertexBuffer&&this.zoomOutPaintVertexBuffer.destroy(),this.zoomInPaintVertexBuffer&&this.zoomInPaintVertexBuffer.destroy()};var uo=function(t,e,r){this.binders={},this._buffers=[];var n=[];for(var i in t.paint._values)if(r(i)){var a=t.paint.get(i);if(a 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instanceof ao&&n.setConstantPatternPositions(t,e)}},uo.prototype.updatePaintArrays=function(t,e,r,n,i){var a=!1;for(var o in t)for(var s=0,l=e.getPositions(o);s<l.length;s+=1){var u=l[s],c=r.feature(u.index);for(var f in this.binders){var h=this.binders[f];if((h instanceof oo||h instanceof so||h instanceof lo)&&!0===h.expression.isStateDependent){var p=n.paint.get(f);h.expression=p.value,h.updatePaintArray(u.start,u.end,c,t[o],i),a=!0}}}return a},uo.prototype.defines=function(){var t=[];for(var e in this.binders){var r=this.binders[e];(r instanceof io||r instanceof ao)&&t.push.apply(t,r.uniformNames.map((function(t){return\"#define HAS_UNIFORM_\"+t})))}return t},uo.prototype.getBinderAttributes=function(){var t=[];for(var e in this.binders){var r=this.binders[e];if(r instanceof oo||r instanceof so)for(var n=0;n<r.paintVertexAttributes.length;n++)t.push(r.paintVertexAttributes[n].name);else if(r instanceof lo)for(var i=0;i<Fa.members.length;i++)t.push(Fa.members[i].name)}return t},uo.prototype.getBinderUniforms=function(){var t=[];for(var e in this.binders){var r=this.binders[e];if(r instanceof io||r instanceof ao||r instanceof so)for(var n=0,i=r.uniformNames;n<i.length;n+=1){var a=i[n];t.push(a)}}return t},uo.prototype.getPaintVertexBuffers=function(){return this._buffers},uo.prototype.getUniforms=function(t,e){var r=[];for(var n in this.binders){var i=this.binders[n];if(i instanceof io||i instanceof ao||i instanceof so)for(var a=0,o=i.uniformNames;a<o.length;a+=1){var s=o[a];if(e[s]){var l=i.getBinding(t,e[s],s);r.push({name:s,property:n,binding:l})}}}return r},uo.prototype.setUniforms=function(t,e,r,n){for(var i=0,a=e;i<a.length;i+=1){var o=a[i],s=o.name,l=o.property,u=o.binding;this.binders[l].setUniform(u,n,r.get(l),s)}},uo.prototype.updatePaintBuffers=function(t){for(var e in this._buffers=[],this.binders){var r=this.binders[e];if(t&&r instanceof lo){var 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u=t.readVarint();n=7&u,i=u>>3}if(i--,1===n||2===n)o+=t.readSVarint(),s+=t.readSVarint(),1===n&&(e&&l.push(e),e=[]),e.push(new a(o,s));else{if(7!==n)throw new Error(\"unknown command \"+n);e&&e.push(e[0].clone())}}return e&&l.push(e),l},Ys.prototype.bbox=function(){var t=this._pbf;t.pos=this._geometry;for(var e=t.readVarint()+t.pos,r=1,n=0,i=0,a=0,o=1/0,s=-1/0,l=1/0,u=-1/0;t.pos<e;){if(n<=0){var c=t.readVarint();r=7&c,n=c>>3}if(n--,1===r||2===r)(i+=t.readSVarint())<o&&(o=i),i>s&&(s=i),(a+=t.readSVarint())<l&&(l=a),a>u&&(u=a);else if(7!==r)throw new Error(\"unknown command \"+r)}return[o,l,s,u]},Ys.prototype.toGeoJSON=function(t,e,r){var n,i,a=this.extent*Math.pow(2,r),o=this.extent*t,s=this.extent*e,l=this.loadGeometry(),u=Ys.types[this.type];function c(t){for(var e=0;e<t.length;e++){var r=t[e],n=180-360*(r.y+s)/a;t[e]=[360*(r.x+o)/a-180,360/Math.PI*Math.atan(Math.exp(n*Math.PI/180))-90]}}switch(this.type){case 1:var f=[];for(n=0;n<l.length;n++)f[n]=l[n][0];c(l=f);break;case 2:for(n=0;n<l.length;n++)c(l[n]);break;case 3:for(l=function(t){var e=t.length;if(e<=1)return[t];for(var r,n,i=[],a=0;a<e;a++){var o=Zs(t[a]);0!==o&&(void 0===n&&(n=o<0),n===o<0?(r&&i.push(r),r=[t[a]]):r.push(t[a]))}return r&&i.push(r),i}(l),n=0;n<l.length;n++)for(i=0;i<l[n].length;i++)c(l[n][i])}1===l.length?l=l[0]:u=\"Multi\"+u;var h={type:\"Feature\",geometry:{type:u,coordinates:l},properties:this.properties};return\"id\"in this&&(h.id=this.id),h};var Ks=Js;function Js(t,e){this.version=1,this.name=null,this.extent=4096,this.length=0,this._pbf=t,this._keys=[],this._values=[],this._features=[],t.readFields($s,this,e),this.length=this._features.length}function $s(t,e,r){15===t?e.version=r.readVarint():1===t?e.name=r.readString():5===t?e.extent=r.readVarint():2===t?e._features.push(r.pos):3===t?e._keys.push(r.readString()):4===t&&e._values.push(function(t){for(var e=null,r=t.readVarint()+t.pos;t.pos<r;){var n=t.readVarint()>>3;e=1===n?t.readString():2===n?t.readFloat():3===n?t.readDouble():4===n?t.readVarint64():5===n?t.readVarint():6===n?t.readSVarint():7===n?t.readBoolean():null}return e}(r))}function Qs(t,e,r){if(3===t){var n=new Ks(r,r.readVarint()+r.pos);n.length&&(e[n.name]=n)}}Js.prototype.feature=function(t){if(t<0||t>=this._features.length)throw new Error(\"feature index out of bounds\");this._pbf.pos=this._features[t];var e=this._pbf.readVarint()+this._pbf.pos;return new Ws(this._pbf,e,this.extent,this._keys,this._values)};var tl={VectorTile:function(t,e){this.layers=t.readFields(Qs,{},e)},VectorTileFeature:Ws,VectorTileLayer:Ks},el=tl.VectorTileFeature.types,rl=Math.pow(2,13);function nl(t,e,r,n,i,a,o,s){t.emplaceBack(e,r,2*Math.floor(n*rl)+o,i*rl*2,a*rl*2,Math.round(s))}var il=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.hasPattern=!1,this.layoutVertexArray=new ia,this.indexArray=new va,this.programConfigurations=new co(t.layers,t.zoom),this.segments=new za,this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id}))};function al(t,e){return t.x===e.x&&(t.x<0||t.x>po)||t.y===e.y&&(t.y<0||t.y>po)}il.prototype.populate=function(t,e,r){this.features=[],this.hasPattern=Ns(\"fill-extrusion\",this.layers,e);for(var n=0,i=t;n<i.length;n+=1){var a=i[n],o=a.feature,s=a.id,l=a.index,u=a.sourceLayerIndex,c=this.layers[0]._featureFilter.needGeometry,f=mo(o,c);if(this.layers[0]._featureFilter.filter(new Di(this.zoom),f,r)){var h={id:s,sourceLayerIndex:u,index:l,geometry:c?f.geometry:yo(o),properties:o.properties,type:o.type,patterns:{}};this.hasPattern?this.features.push(js(\"fill-extrusion\",this.layers,h,this.zoom,e)):this.addFeature(h,h.geometry,l,r,{}),e.featureIndex.insert(o,h.geometry,l,u,this.index,!0)}}},il.prototype.addFeatures=function(t,e,r){for(var n=0,i=this.features;n<i.length;n+=1){var a=i[n],o=a.geometry;this.addFeature(a,o,a.index,e,r)}},il.prototype.update=function(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)},il.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length},il.prototype.uploadPending=function(){return!this.uploaded||this.programConfigurations.needsUpload},il.prototype.upload=function(t){this.uploaded||(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,Gs),this.indexBuffer=t.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(t),this.uploaded=!0},il.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())},il.prototype.addFeature=function(t,e,r,n,i){for(var a=0,o=Fs(e,500);a<o.length;a+=1){for(var s=o[a],l=0,u=0,c=s;u<c.length;u+=1)l+=c[u].length;for(var f=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray),h=0,p=s;h<p.length;h+=1){var d=p[h];if(0!==d.length&&!((O=d).every((function(t){return t.x<0}))||O.every((function(t){return t.x>po}))||O.every((function(t){return t.y<0}))||O.every((function(t){return t.y>po}))))for(var v=0,g=0;g<d.length;g++){var y=d[g];if(g>=1){var m=d[g-1];if(!al(y,m)){f.vertexLength+4>za.MAX_VERTEX_ARRAY_LENGTH&&(f=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray));var x=y.sub(m)._perp()._unit(),b=m.dist(y);v+b>32768&&(v=0),nl(this.layoutVertexArray,y.x,y.y,x.x,x.y,0,0,v),nl(this.layoutVertexArray,y.x,y.y,x.x,x.y,0,1,v),v+=b,nl(this.layoutVertexArray,m.x,m.y,x.x,x.y,0,0,v),nl(this.layoutVertexArray,m.x,m.y,x.x,x.y,0,1,v);var _=f.vertexLength;this.indexArray.emplaceBack(_,_+2,_+1),this.indexArray.emplaceBack(_+1,_+2,_+3),f.vertexLength+=4,f.primitiveLength+=2}}}}if(f.vertexLength+l>za.MAX_VERTEX_ARRAY_LENGTH&&(f=this.segments.prepareSegment(l,this.layoutVertexArray,this.indexArray)),\"Polygon\"===el[t.type]){for(var w=[],T=[],k=f.vertexLength,A=0,M=s;A<M.length;A+=1){var S=M[A];if(0!==S.length){S!==s[0]&&T.push(w.length/2);for(var E=0;E<S.length;E++){var L=S[E];nl(this.layoutVertexArray,L.x,L.y,0,0,1,1,0),w.push(L.x),w.push(L.y)}}}for(var C=as(w,T),P=0;P<C.length;P+=3)this.indexArray.emplaceBack(k+C[P],k+C[P+2],k+C[P+1]);f.primitiveLength+=C.length/3,f.vertexLength+=l}}var O;this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,t,r,i,n)},oi(\"FillExtrusionBucket\",il,{omit:[\"layers\",\"features\"]});var ol={paint:new Xi({\"fill-extrusion-opacity\":new qi(Ft[\"paint_fill-extrusion\"][\"fill-extrusion-opacity\"]),\"fill-extrusion-color\":new Hi(Ft[\"paint_fill-extrusion\"][\"fill-extrusion-color\"]),\"fill-extrusion-translate\":new qi(Ft[\"paint_fill-extrusion\"][\"fill-extrusion-translate\"]),\"fill-extrusion-translate-anchor\":new qi(Ft[\"paint_fill-extrusion\"][\"fill-extrusion-translate-anchor\"]),\"fill-extrusion-pattern\":new Gi(Ft[\"paint_fill-extrusion\"][\"fill-extrusion-pattern\"]),\"fill-extrusion-height\":new Hi(Ft[\"paint_fill-extrusion\"][\"fill-extrusion-height\"]),\"fill-extrusion-base\":new Hi(Ft[\"paint_fill-extrusion\"][\"fill-extrusion-base\"]),\"fill-extrusion-vertical-gradient\":new qi(Ft[\"paint_fill-extrusion\"][\"fill-extrusion-vertical-gradient\"])})},sl=function(t){function e(e){t.call(this,e,ol)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.createBucket=function(t){return new il(t)},e.prototype.queryRadius=function(){return Io(this.paint.get(\"fill-extrusion-translate\"))},e.prototype.is3D=function(){return!0},e.prototype.queryIntersectsFeature=function(t,e,r,n,i,o,s,l){var u=Do(t,this.paint.get(\"fill-extrusion-translate\"),this.paint.get(\"fill-extrusion-translate-anchor\"),o.angle,s),c=this.paint.get(\"fill-extrusion-height\").evaluate(e,r),f=this.paint.get(\"fill-extrusion-base\").evaluate(e,r),h=function(t,e,r,n){for(var i=[],o=0,s=t;o<s.length;o+=1){var l=s[o],u=[l.x,l.y,n,1];qo(u,u,e),i.push(new a(u[0]/u[3],u[1]/u[3]))}return i}(u,l,0,0),p=function(t,e,r,n){for(var i=[],o=[],s=n[8]*e,l=n[9]*e,u=n[10]*e,c=n[11]*e,f=n[8]*r,h=n[9]*r,p=n[10]*r,d=n[11]*r,v=0,g=t;v<g.length;v+=1){for(var y=[],m=[],x=0,b=g[v];x<b.length;x+=1){var _=b[x],w=_.x,T=_.y,k=n[0]*w+n[4]*T+n[12],A=n[1]*w+n[5]*T+n[13],M=n[2]*w+n[6]*T+n[14],S=n[3]*w+n[7]*T+n[15],E=M+u,L=S+c,C=k+f,P=A+h,O=M+p,I=S+d,D=new a((k+s)/L,(A+l)/L);D.z=E/L,y.push(D);var z=new a(C/I,P/I);z.z=O/I,m.push(z)}i.push(y),o.push(m)}return[i,o]}(n,f,c,l);return function(t,e,r){var n=1/0;To(r,e)&&(n=ul(r,e[0]));for(var i=0;i<e.length;i++)for(var a=e[i],o=t[i],s=0;s<a.length-1;s++){var l=a[s],u=a[s+1],c=o[s],f=[l,u,o[s+1],c,l];_o(r,f)&&(n=Math.min(n,ul(r,f)))}return n!==1/0&&n}(p[0],p[1],h)},e}(Ki);function ll(t,e){return t.x*e.x+t.y*e.y}function ul(t,e){if(1===t.length){for(var r,n=0,i=e[n++];!r||i.equals(r);)if(!(r=e[n++]))return 1/0;for(;n<e.length;n++){var a=e[n],o=t[0],s=r.sub(i),l=a.sub(i),u=o.sub(i),c=ll(s,s),f=ll(s,l),h=ll(l,l),p=ll(u,s),d=ll(u,l),v=c*h-f*f,g=(h*p-f*d)/v,y=(c*d-f*p)/v,m=1-g-y,x=i.z*m+r.z*g+a.z*y;if(isFinite(x))return x}return 1/0}for(var b=1/0,_=0,w=e;_<w.length;_+=1){var T=w[_];b=Math.min(b,T.z)}return b}var cl=ta([{name:\"a_pos_normal\",components:2,type:\"Int16\"},{name:\"a_data\",components:4,type:\"Uint8\"}],4).members,fl=ta([{name:\"a_uv_x\",components:1,type:\"Float32\"},{name:\"a_split_index\",components:1,type:\"Float32\"}]).members,hl=tl.VectorTileFeature.types,pl=Math.cos(Math.PI/180*37.5),dl=Math.pow(2,14)/.5,vl=function(t){var e=this;this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.hasPattern=!1,this.patternFeatures=[],this.lineClipsArray=[],this.gradients={},this.layers.forEach((function(t){e.gradients[t.id]={}})),this.layoutVertexArray=new aa,this.layoutVertexArray2=new oa,this.indexArray=new va,this.programConfigurations=new co(t.layers,t.zoom),this.segments=new za,this.maxLineLength=0,this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id}))};vl.prototype.populate=function(t,e,r){this.hasPattern=Ns(\"line\",this.layers,e);for(var n=this.layers[0].layout.get(\"line-sort-key\"),i=[],a=0,o=t;a<o.length;a+=1){var s=o[a],l=s.feature,u=s.id,c=s.index,f=s.sourceLayerIndex,h=this.layers[0]._featureFilter.needGeometry,p=mo(l,h);if(this.layers[0]._featureFilter.filter(new Di(this.zoom),p,r)){var d=n?n.evaluate(p,{},r):void 0,v={id:u,properties:l.properties,type:l.type,sourceLayerIndex:f,index:c,geometry:h?p.geometry:yo(l),patterns:{},sortKey:d};i.push(v)}}n&&i.sort((function(t,e){return t.sortKey-e.sortKey}));for(var g=0,y=i;g<y.length;g+=1){var m=y[g],x=m,b=x.geometry,_=x.index,w=x.sourceLayerIndex;if(this.hasPattern){var T=js(\"line\",this.layers,m,this.zoom,e);this.patternFeatures.push(T)}else this.addFeature(m,b,_,r,{});var k=t[_].feature;e.featureIndex.insert(k,b,_,w,this.index)}},vl.prototype.update=function(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)},vl.prototype.addFeatures=function(t,e,r){for(var n=0,i=this.patternFeatures;n<i.length;n+=1){var a=i[n];this.addFeature(a,a.geometry,a.index,e,r)}},vl.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length},vl.prototype.uploadPending=function(){return!this.uploaded||this.programConfigurations.needsUpload},vl.prototype.upload=function(t){this.uploaded||(0!==this.layoutVertexArray2.length&&(this.layoutVertexBuffer2=t.createVertexBuffer(this.layoutVertexArray2,fl)),this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,cl),this.indexBuffer=t.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(t),this.uploaded=!0},vl.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())},vl.prototype.lineFeatureClips=function(t){if(t.properties&&t.properties.hasOwnProperty(\"mapbox_clip_start\")&&t.properties.hasOwnProperty(\"mapbox_clip_end\"))return{start:+t.properties.mapbox_clip_start,end:+t.properties.mapbox_clip_end}},vl.prototype.addFeature=function(t,e,r,n,i){var a=this.layers[0].layout,o=a.get(\"line-join\").evaluate(t,{}),s=a.get(\"line-cap\"),l=a.get(\"line-miter-limit\"),u=a.get(\"line-round-limit\");this.lineClips=this.lineFeatureClips(t);for(var c=0,f=e;c<f.length;c+=1){var h=f[c];this.addLine(h,t,o,s,l,u)}this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,t,r,i,n)},vl.prototype.addLine=function(t,e,r,n,i,a){if(this.distance=0,this.scaledDistance=0,this.totalDistance=0,this.lineClips){this.lineClipsArray.push(this.lineClips);for(var o=0;o<t.length-1;o++)this.totalDistance+=t[o].dist(t[o+1]);this.updateScaledDistance(),this.maxLineLength=Math.max(this.maxLineLength,this.totalDistance)}for(var s=\"Polygon\"===hl[e.type],l=t.length;l>=2&&t[l-1].equals(t[l-2]);)l--;for(var u=0;u<l-1&&t[u].equals(t[u+1]);)u++;if(!(l<(s?3:2))){\"bevel\"===r&&(i=1.05);var c,f=this.overscaling<=16?15*po/(512*this.overscaling):0,h=this.segments.prepareSegment(10*l,this.layoutVertexArray,this.indexArray),p=void 0,d=void 0,v=void 0,g=void 0;this.e1=this.e2=-1,s&&(c=t[l-2],g=t[u].sub(c)._unit()._perp());for(var y=u;y<l;y++)if(!(d=y===l-1?s?t[u+1]:void 0:t[y+1])||!t[y].equals(d)){g&&(v=g),c&&(p=c),c=t[y],g=d?d.sub(c)._unit()._perp():v;var m=(v=v||g).add(g);0===m.x&&0===m.y||m._unit();var x=v.x*g.x+v.y*g.y,b=m.x*g.x+m.y*g.y,_=0!==b?1/b:1/0,w=2*Math.sqrt(2-2*b),T=b<pl&&p&&d,k=v.x*g.y-v.y*g.x>0;if(T&&y>u){var A=c.dist(p);if(A>2*f){var M=c.sub(c.sub(p)._mult(f/A)._round());this.updateDistance(p,M),this.addCurrentVertex(M,v,0,0,h),p=M}}var S=p&&d,E=S?r:s?\"butt\":n;if(S&&\"round\"===E&&(_<a?E=\"miter\":_<=2&&(E=\"fakeround\")),\"miter\"===E&&_>i&&(E=\"bevel\"),\"bevel\"===E&&(_>2&&(E=\"flipbevel\"),_<i&&(E=\"miter\")),p&&this.updateDistance(p,c),\"miter\"===E)m._mult(_),this.addCurrentVertex(c,m,0,0,h);else if(\"flipbevel\"===E){if(_>100)m=g.mult(-1);else{var L=_*v.add(g).mag()/v.sub(g).mag();m._perp()._mult(L*(k?-1:1))}this.addCurrentVertex(c,m,0,0,h),this.addCurrentVertex(c,m.mult(-1),0,0,h)}else if(\"bevel\"===E||\"fakeround\"===E){var C=-Math.sqrt(_*_-1),P=k?C:0,O=k?0:C;if(p&&this.addCurrentVertex(c,v,P,O,h),\"fakeround\"===E)for(var I=Math.round(180*w/Math.PI/20),D=1;D<I;D++){var z=D/I;if(.5!==z){var R=z-.5;z+=z*R*(z-1)*((1.0904+x*(x*(3.55645-1.43519*x)-3.2452))*R*R+(.848013+x*(.215638*x-1.06021)))}var F=g.sub(v)._mult(z)._add(v)._unit()._mult(k?-1:1);this.addHalfVertex(c,F.x,F.y,!1,k,0,h)}d&&this.addCurrentVertex(c,g,-P,-O,h)}else if(\"butt\"===E)this.addCurrentVertex(c,m,0,0,h);else if(\"square\"===E){var B=p?1:-1;this.addCurrentVertex(c,m,B,B,h)}else\"round\"===E&&(p&&(this.addCurrentVertex(c,v,0,0,h),this.addCurrentVertex(c,v,1,1,h,!0)),d&&(this.addCurrentVertex(c,g,-1,-1,h,!0),this.addCurrentVertex(c,g,0,0,h)));if(T&&y<l-1){var N=c.dist(d);if(N>2*f){var j=c.add(d.sub(c)._mult(f/N)._round());this.updateDistance(c,j),this.addCurrentVertex(j,g,0,0,h),c=j}}}}},vl.prototype.addCurrentVertex=function(t,e,r,n,i,a){void 0===a&&(a=!1);var 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e=Fl(this);for(t=t||[];this.pos<e;)t.push(this.readSFixed32());return t},readPackedFixed64:function(t){if(this.type!==Il.Bytes)return t.push(this.readFixed64());var e=Fl(this);for(t=t||[];this.pos<e;)t.push(this.readFixed64());return t},readPackedSFixed64:function(t){if(this.type!==Il.Bytes)return t.push(this.readSFixed64());var e=Fl(this);for(t=t||[];this.pos<e;)t.push(this.readSFixed64());return t},skip:function(t){var e=7&t;if(e===Il.Varint)for(;this.buf[this.pos++]>127;);else if(e===Il.Bytes)this.pos=this.readVarint()+this.pos;else if(e===Il.Fixed32)this.pos+=4;else{if(e!==Il.Fixed64)throw new Error(\"Unimplemented type: \"+e);this.pos+=8}},writeTag:function(t,e){this.writeVarint(t<<3|e)},realloc:function(t){for(var e=this.length||16;e<this.pos+t;)e*=2;if(e!==this.length){var r=new Uint8Array(e);r.set(this.buf),this.buf=r,this.length=e}},finish:function(){return this.length=this.pos,this.pos=0,this.buf.subarray(0,this.length)},writeFixed32:function(t){this.realloc(4),Kl(this.buf,t,this.pos),this.pos+=4},writeSFixed32:function(t){this.realloc(4),Kl(this.buf,t,this.pos),this.pos+=4},writeFixed64:function(t){this.realloc(8),Kl(this.buf,-1&t,this.pos),Kl(this.buf,Math.floor(t*zl),this.pos+4),this.pos+=8},writeSFixed64:function(t){this.realloc(8),Kl(this.buf,-1&t,this.pos),Kl(this.buf,Math.floor(t*zl),this.pos+4),this.pos+=8},writeVarint:function(t){(t=+t||0)>268435455||t<0?function(t,e){var r,n;if(t>=0?(r=t%4294967296|0,n=t/4294967296|0):(n=~(-t/4294967296),4294967295^(r=~(-t%4294967296))?r=r+1|0:(r=0,n=n+1|0)),t>=0x10000000000000000||t<-0x10000000000000000)throw new Error(\"Given varint doesn't fit into 10 bytes\");e.realloc(10),function(t,e,r){r.buf[r.pos++]=127&t|128,t>>>=7,r.buf[r.pos++]=127&t|128,t>>>=7,r.buf[r.pos++]=127&t|128,t>>>=7,r.buf[r.pos++]=127&t|128,t>>>=7,r.buf[r.pos]=127&t}(r,0,e),function(t,e){var r=(7&t)<<4;e.buf[e.pos++]|=r|((t>>>=3)?128:0),t&&(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),t&&(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),t&&(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),t&&(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),t&&(e.buf[e.pos++]=127&t)))))}(n,e)}(t,this):(this.realloc(4),this.buf[this.pos++]=127&t|(t>127?128:0),t<=127||(this.buf[this.pos++]=127&(t>>>=7)|(t>127?128:0),t<=127||(this.buf[this.pos++]=127&(t>>>=7)|(t>127?128:0),t<=127||(this.buf[this.pos++]=t>>>7&127))))},writeSVarint:function(t){this.writeVarint(t<0?2*-t-1:2*t)},writeBoolean:function(t){this.writeVarint(Boolean(t))},writeString:function(t){t=String(t),this.realloc(4*t.length),this.pos++;var e=this.pos;this.pos=function(t,e,r){for(var n,i,a=0;a<e.length;a++){if((n=e.charCodeAt(a))>55295&&n<57344){if(!i){n>56319||a+1===e.length?(t[r++]=239,t[r++]=191,t[r++]=189):i=n;continue}if(n<56320){t[r++]=239,t[r++]=191,t[r++]=189,i=n;continue}n=i-55296<<10|n-56320|65536,i=null}else i&&(t[r++]=239,t[r++]=191,t[r++]=189,i=null);n<128?t[r++]=n:(n<2048?t[r++]=n>>6|192:(n<65536?t[r++]=n>>12|224:(t[r++]=n>>18|240,t[r++]=n>>12&63|128),t[r++]=n>>6&63|128),t[r++]=63&n|128)}return r}(this.buf,t,this.pos);var r=this.pos-e;r>=128&&Nl(e,r,this),this.pos=e-1,this.writeVarint(r),this.pos+=r},writeFloat:function(t){this.realloc(4),Pl(this.buf,t,this.pos,!0,23,4),this.pos+=4},writeDouble:function(t){this.realloc(8),Pl(this.buf,t,this.pos,!0,52,8),this.pos+=8},writeBytes:function(t){var e=t.length;this.writeVarint(e),this.realloc(e);for(var r=0;r<e;r++)this.buf[this.pos++]=t[r]},writeRawMessage:function(t,e){this.pos++;var r=this.pos;t(e,this);var n=this.pos-r;n>=128&&Nl(r,n,this),this.pos=r-1,this.writeVarint(n),this.pos+=n},writeMessage:function(t,e,r){this.writeTag(t,Il.Bytes),this.writeRawMessage(e,r)},writePackedVarint:function(t,e){e.length&&this.writeMessage(t,jl,e)},writePackedSVarint:function(t,e){e.length&&this.writeMessage(t,Ul,e)},writePackedBoolean:function(t,e){e.length&&this.writeMessage(t,Hl,e)},writePackedFloat:function(t,e){e.length&&this.writeMessage(t,Vl,e)},writePackedDouble:function(t,e){e.length&&this.writeMessage(t,ql,e)},writePackedFixed32:function(t,e){e.length&&this.writeMessage(t,Gl,e)},writePackedSFixed32:function(t,e){e.length&&this.writeMessage(t,Wl,e)},writePackedFixed64:function(t,e){e.length&&this.writeMessage(t,Yl,e)},writePackedSFixed64:function(t,e){e.length&&this.writeMessage(t,Xl,e)},writeBytesField:function(t,e){this.writeTag(t,Il.Bytes),this.writeBytes(e)},writeFixed32Field:function(t,e){this.writeTag(t,Il.Fixed32),this.writeFixed32(e)},writeSFixed32Field:function(t,e){this.writeTag(t,Il.Fixed32),this.writeSFixed32(e)},writeFixed64Field:function(t,e){this.writeTag(t,Il.Fixed64),this.writeFixed64(e)},writeSFixed64Field:function(t,e){this.writeTag(t,Il.Fixed64),this.writeSFixed64(e)},writeVarintField:function(t,e){this.writeTag(t,Il.Varint),this.writeVarint(e)},writeSVarintField:function(t,e){this.writeTag(t,Il.Varint),this.writeSVarint(e)},writeStringField:function(t,e){this.writeTag(t,Il.Bytes),this.writeString(e)},writeFloatField:function(t,e){this.writeTag(t,Il.Fixed32),this.writeFloat(e)},writeDoubleField:function(t,e){this.writeTag(t,Il.Fixed64),this.writeDouble(e)},writeBooleanField:function(t,e){this.writeVarintField(t,Boolean(e))}};var $l=3;function Ql(t,e,r){1===t&&r.readMessage(tu,e)}function tu(t,e,r){if(3===t){var n=r.readMessage(eu,{}),i=n.id,a=n.bitmap,o=n.width,s=n.height,l=n.left,u=n.top,c=n.advance;e.push({id:i,bitmap:new Jo({width:o+2*$l,height:s+2*$l},a),metrics:{width:o,height:s,left:l,top:u,advance:c}})}}function eu(t,e,r){1===t?e.id=r.readVarint():2===t?e.bitmap=r.readBytes():3===t?e.width=r.readVarint():4===t?e.height=r.readVarint():5===t?e.left=r.readSVarint():6===t?e.top=r.readSVarint():7===t&&(e.advance=r.readVarint())}var ru=$l;function nu(t){for(var e=0,r=0,n=0,i=t;n<i.length;n+=1){var a=i[n];e+=a.w*a.h,r=Math.max(r,a.w)}t.sort((function(t,e){return e.h-t.h}));for(var o=[{x:0,y:0,w:Math.max(Math.ceil(Math.sqrt(e/.95)),r),h:1/0}],s=0,l=0,u=0,c=t;u<c.length;u+=1)for(var f=c[u],h=o.length-1;h>=0;h--){var p=o[h];if(!(f.w>p.w||f.h>p.h)){if(f.x=p.x,f.y=p.y,l=Math.max(l,f.y+f.h),s=Math.max(s,f.x+f.w),f.w===p.w&&f.h===p.h){var d=o.pop();h<o.length&&(o[h]=d)}else f.h===p.h?(p.x+=f.w,p.w-=f.w):f.w===p.w?(p.y+=f.h,p.h-=f.h):(o.push({x:p.x+f.w,y:p.y,w:p.w-f.w,h:f.h}),p.y+=f.h,p.h-=f.h);break}}return{w:s,h:l,fill:e/(s*l)||0}}var iu=1,au=function(t,e){var r=e.pixelRatio,n=e.version,i=e.stretchX,a=e.stretchY,o=e.content;this.paddedRect=t,this.pixelRatio=r,this.stretchX=i,this.stretchY=a,this.content=o,this.version=n},ou={tl:{configurable:!0},br:{configurable:!0},tlbr:{configurable:!0},displaySize:{configurable:!0}};ou.tl.get=function(){return[this.paddedRect.x+iu,this.paddedRect.y+iu]},ou.br.get=function(){return[this.paddedRect.x+this.paddedRect.w-iu,this.paddedRect.y+this.paddedRect.h-iu]},ou.tlbr.get=function(){return this.tl.concat(this.br)},ou.displaySize.get=function(){return[(this.paddedRect.w-2*iu)/this.pixelRatio,(this.paddedRect.h-2*iu)/this.pixelRatio]},Object.defineProperties(au.prototype,ou);var su=function(t,e){var r={},n={};this.haveRenderCallbacks=[];var i=[];this.addImages(t,r,i),this.addImages(e,n,i);var a=nu(i),o=a.w,s=a.h,l=new $o({width:o||1,height:s||1});for(var u in t){var c=t[u],f=r[u].paddedRect;$o.copy(c.data,l,{x:0,y:0},{x:f.x+iu,y:f.y+iu},c.data)}for(var h in e){var p=e[h],d=n[h].paddedRect,v=d.x+iu,g=d.y+iu,y=p.data.width,m=p.data.height;$o.copy(p.data,l,{x:0,y:0},{x:v,y:g},p.data),$o.copy(p.data,l,{x:0,y:m-1},{x:v,y:g-1},{width:y,height:1}),$o.copy(p.data,l,{x:0,y:0},{x:v,y:g+m},{width:y,height:1}),$o.copy(p.data,l,{x:y-1,y:0},{x:v-1,y:g},{width:1,height:m}),$o.copy(p.data,l,{x:0,y:0},{x:v+y,y:g},{width:1,height:m})}this.image=l,this.iconPositions=r,this.patternPositions=n};su.prototype.addImages=function(t,e,r){for(var n in t){var i=t[n],a={x:0,y:0,w:i.data.width+2*iu,h:i.data.height+2*iu};r.push(a),e[n]=new au(a,i),i.hasRenderCallback&&this.haveRenderCallbacks.push(n)}},su.prototype.patchUpdatedImages=function(t,e){for(var r in t.dispatchRenderCallbacks(this.haveRenderCallbacks),t.updatedImages)this.patchUpdatedImage(this.iconPositions[r],t.getImage(r),e),this.patchUpdatedImage(this.patternPositions[r],t.getImage(r),e)},su.prototype.patchUpdatedImage=function(t,e,r){if(t&&e&&t.version!==e.version){t.version=e.version;var n=t.tl,i=n[0],a=n[1];r.update(e.data,void 0,{x:i,y:a})}},oi(\"ImagePosition\",au),oi(\"ImageAtlas\",su);var lu={horizontal:1,vertical:2,horizontalOnly:3},uu=-17;var cu=function(){this.scale=1,this.fontStack=\"\",this.imageName=null};cu.forText=function(t,e){var r=new cu;return r.scale=t||1,r.fontStack=e,r},cu.forImage=function(t){var e=new cu;return e.imageName=t,e};var fu=function(){this.text=\"\",this.sectionIndex=[],this.sections=[],this.imageSectionID=null};function hu(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v){var g,y=fu.fromFeature(t,i);f===lu.vertical&&y.verticalizePunctuation();var m=Ii.processBidirectionalText,x=Ii.processStyledBidirectionalText;if(m&&1===y.sections.length){g=[];for(var b=0,_=m(y.toString(),bu(y,u,a,e,n,p,d));b<_.length;b+=1){var w=_[b],T=new fu;T.text=w,T.sections=y.sections;for(var k=0;k<w.length;k++)T.sectionIndex.push(0);g.push(T)}}else if(x){g=[];for(var A=0,M=x(y.text,y.sectionIndex,bu(y,u,a,e,n,p,d));A<M.length;A+=1){var S=M[A],E=new fu;E.text=S[0],E.sectionIndex=S[1],E.sections=y.sections,g.push(E)}}else g=function(t,e){for(var r=[],n=t.text,i=0,a=0,o=e;a<o.length;a+=1){var s=o[a];r.push(t.substring(i,s)),i=s}return i<n.length&&r.push(t.substring(i,n.length)),r}(y,bu(y,u,a,e,n,p,d));var L=[],C={positionedLines:L,text:y.toString(),top:c[1],bottom:c[1],left:c[0],right:c[0],writingMode:f,iconsInText:!1,verticalizable:!1};return function(t,e,r,n,i,a,o,s,l,u,c,f){for(var h=0,p=uu,d=0,v=0,g=\"right\"===s?1:\"left\"===s?0:.5,y=0,m=0,x=i;m<x.length;m+=1){var b=x[m];b.trim();var _=b.getMaxScale(),w=(_-1)*Ll,T={positionedGlyphs:[],lineOffset:0};t.positionedLines[y]=T;var k=T.positionedGlyphs,A=0;if(b.length()){for(var M=0;M<b.length();M++){var S=b.getSection(M),E=b.getSectionIndex(M),L=b.getCharCode(M),C=0,P=null,O=null,I=null,D=Ll,z=!(l===lu.horizontal||!c&&!vi(L)||c&&(pu[L]||yi(L)));if(S.imageName){var R=n[S.imageName];if(!R)continue;I=S.imageName,t.iconsInText=t.iconsInText||!0,O=R.paddedRect;var F=R.displaySize;S.scale=S.scale*Ll/f,P={width:F[0],height:F[1],left:iu,top:-ru,advance:z?F[1]:F[0]},C=w+(Ll-F[1]*S.scale),D=P.advance;var B=z?F[0]*S.scale-Ll*_:F[1]*S.scale-Ll*_;B>0&&B>A&&(A=B)}else{var N=r[S.fontStack],j=N&&N[L];if(j&&j.rect)O=j.rect,P=j.metrics;else{var U=e[S.fontStack],V=U&&U[L];if(!V)continue;P=V.metrics}C=(_-S.scale)*Ll}z?(t.verticalizable=!0,k.push({glyph:L,imageName:I,x:h,y:p+C,vertical:z,scale:S.scale,fontStack:S.fontStack,sectionIndex:E,metrics:P,rect:O}),h+=D*S.scale+u):(k.push({glyph:L,imageName:I,x:h,y:p+C,vertical:z,scale:S.scale,fontStack:S.fontStack,sectionIndex:E,metrics:P,rect:O}),h+=P.advance*S.scale+u)}if(0!==k.length){var q=h-u;d=Math.max(q,d),wu(k,0,k.length-1,g,A)}h=0;var H=a*_+A;T.lineOffset=Math.max(A,w),p+=H,v=Math.max(H,v),++y}else p+=a,++y}var G=p-uu,W=_u(o),Y=W.horizontalAlign,X=W.verticalAlign;(function(t,e,r,n,i,a,o,s,l){var u=(e-r)*i,c=0;c=a!==o?-s*n-uu:(-n*l+.5)*o;for(var f=0,h=t;f<h.length;f+=1)for(var p=0,d=h[f].positionedGlyphs;p<d.length;p+=1){var v=d[p];v.x+=u,v.y+=c}})(t.positionedLines,g,Y,X,d,v,a,G,i.length),t.top+=-X*G,t.bottom=t.top+G,t.left+=-Y*d,t.right=t.left+d}(C,e,r,n,g,o,s,l,f,u,h,v),!function(t){for(var e=0,r=t;e<r.length;e+=1)if(0!==r[e].positionedGlyphs.length)return!1;return!0}(L)&&C}fu.fromFeature=function(t,e){for(var r=new fu,n=0;n<t.sections.length;n++){var i=t.sections[n];i.image?r.addImageSection(i):r.addTextSection(i,e)}return r},fu.prototype.length=function(){return this.text.length},fu.prototype.getSection=function(t){return this.sections[this.sectionIndex[t]]},fu.prototype.getSectionIndex=function(t){return this.sectionIndex[t]},fu.prototype.getCharCode=function(t){return this.text.charCodeAt(t)},fu.prototype.verticalizePunctuation=function(){this.text=function(t){for(var e=\"\",r=0;r<t.length;r++){var n=t.charCodeAt(r+1)||null,i=t.charCodeAt(r-1)||null;n&&gi(n)&&!El[t[r+1]]||i&&gi(i)&&!El[t[r-1]]||!El[t[r]]?e+=t[r]:e+=El[t[r]]}return e}(this.text)},fu.prototype.trim=function(){for(var t=0,e=0;e<this.text.length&&pu[this.text.charCodeAt(e)];e++)t++;for(var r=this.text.length,n=this.text.length-1;n>=0&&n>=t&&pu[this.text.charCodeAt(n)];n--)r--;this.text=this.text.substring(t,r),this.sectionIndex=this.sectionIndex.slice(t,r)},fu.prototype.substring=function(t,e){var r=new fu;return r.text=this.text.substring(t,e),r.sectionIndex=this.sectionIndex.slice(t,e),r.sections=this.sections,r},fu.prototype.toString=function(){return this.text},fu.prototype.getMaxScale=function(){var t=this;return this.sectionIndex.reduce((function(e,r){return 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wu(t,e,r,n,i){if(n||i)for(var a=t[r],o=a.metrics.advance*a.scale,s=(t[r].x+o)*n,l=e;l<=r;l++)t[l].x-=s,t[l].y+=i}function Tu(t,e,r,n,i,a){var o,s=t.image;if(s.content){var l=s.content,u=s.pixelRatio||1;o=[l[0]/u,l[1]/u,s.displaySize[0]-l[2]/u,s.displaySize[1]-l[3]/u]}var c,f,h,p,d=e.left*a,v=e.right*a;\"width\"===r||\"both\"===r?(p=i[0]+d-n[3],f=i[0]+v+n[1]):f=(p=i[0]+(d+v-s.displaySize[0])/2)+s.displaySize[0];var g=e.top*a,y=e.bottom*a;return\"height\"===r||\"both\"===r?(c=i[1]+g-n[0],h=i[1]+y+n[2]):h=(c=i[1]+(g+y-s.displaySize[1])/2)+s.displaySize[1],{image:s,top:c,right:f,bottom:h,left:p,collisionPadding:o}}du[10]=!0,du[32]=!0,du[38]=!0,du[40]=!0,du[41]=!0,du[43]=!0,du[45]=!0,du[47]=!0,du[173]=!0,du[183]=!0,du[8203]=!0,du[8208]=!0,du[8211]=!0,du[8231]=!0;var ku=function(t){function e(e,r,n,i){t.call(this,e,r),this.angle=n,void 0!==i&&(this.segment=i)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.clone=function(){return new 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i=t.interpolationType,a=t.minZoom,o=t.maxZoom,s=i?f(wr.interpolationFactor(i,e,a,o),0,1):0;\"camera\"===t.kind?n=er(t.minSize,t.maxSize,s):r=s}return{uSizeT:r,uSize:n}}var Lu=Object.freeze({__proto__:null,getSizeData:Mu,evaluateSizeForFeature:Su,evaluateSizeForZoom:Eu,SIZE_PACK_FACTOR:Au});function Cu(t,e,r,n,i){if(void 0===e.segment)return!0;for(var a=e,o=e.segment+1,s=0;s>-r/2;){if(--o<0)return!1;s-=t[o].dist(a),a=t[o]}s+=t[o].dist(t[o+1]),o++;for(var l=[],u=0;s<r/2;){var c=t[o-1],f=t[o],h=t[o+1];if(!h)return!1;var p=c.angleTo(f)-f.angleTo(h);for(p=Math.abs((p+3*Math.PI)%(2*Math.PI)-Math.PI),l.push({distance:s,angleDelta:p}),u+=p;s-l[0].distance>n;)u-=l.shift().angleDelta;if(u>i)return!1;o++,s+=f.dist(h)}return!0}function Pu(t){for(var e=0,r=0;r<t.length-1;r++)e+=t[r].dist(t[r+1]);return e}function Ou(t,e,r){return t?.6*e*r:0}function Iu(t,e){return Math.max(t?t.right-t.left:0,e?e.right-e.left:0)}function Du(t,e,r,n,i,a){for(var 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a(0,0);c.push({tl:D,tr:z,bl:R,br:F,tex:y,writingMode:e.writingMode,glyphOffset:S,sectionIndex:g.sectionIndex,isSDF:x,pixelOffsetTL:Y,pixelOffsetBR:X,minFontScaleX:0,minFontScaleY:0})}}return c}(0,r,l,i,o,s,n,t.allowVerticalPlacement),y=t.textSizeData,m=null;\"source\"===y.kind?(m=[Au*i.layout.get(\"text-size\").evaluate(s,{})])[0]>ec&&k(t.layerIds[0]+': Value for \"text-size\" is >= '+tc+'. Reduce your \"text-size\".'):\"composite\"===y.kind&&((m=[Au*d.compositeTextSizes[0].evaluate(s,{},v),Au*d.compositeTextSizes[1].evaluate(s,{},v)])[0]>ec||m[1]>ec)&&k(t.layerIds[0]+': Value for \"text-size\" is >= '+tc+'. Reduce your \"text-size\".'),t.addSymbols(t.text,g,m,l,o,s,c,e,u.lineStartIndex,u.lineLength,p,v);for(var x=0,b=f;x<b.length;x+=1)h[b[x]]=t.text.placedSymbolArray.length-1;return 4*g.length}function nc(t){for(var e in t)return t[e];return null}function ic(t,e,r,n){var i=t.compareText;if(e in i){for(var a=i[e],o=a.length-1;o>=0;o--)if(n.dist(a[o])<r)return!0}else i[e]=[];return i[e].push(n),!1}var ac=tl.VectorTileFeature.types,oc=[{name:\"a_fade_opacity\",components:1,type:\"Uint8\",offset:0}];function sc(t,e,r,n,i,a,o,s,l,u,c,f,h){var p=s?Math.min(ec,Math.round(s[0])):0,d=s?Math.min(ec,Math.round(s[1])):0;t.emplaceBack(e,r,Math.round(32*n),Math.round(32*i),a,o,(p<<1)+(l?1:0),d,16*u,16*c,256*f,256*h)}function lc(t,e,r){t.emplaceBack(e.x,e.y,r),t.emplaceBack(e.x,e.y,r),t.emplaceBack(e.x,e.y,r),t.emplaceBack(e.x,e.y,r)}function uc(t){for(var e=0,r=t.sections;e<r.length;e+=1)if(bi(r[e].text))return!0;return!1}var cc=function(t){this.layoutVertexArray=new la,this.indexArray=new va,this.programConfigurations=t,this.segments=new za,this.dynamicLayoutVertexArray=new ua,this.opacityVertexArray=new ca,this.placedSymbolArray=new Sa};cc.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length&&0===this.indexArray.length&&0===this.dynamicLayoutVertexArray.length&&0===this.opacityVertexArray.length},cc.prototype.upload=function(t,e,r,n){this.isEmpty()||(r&&(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,wl.members),this.indexBuffer=t.createIndexBuffer(this.indexArray,e),this.dynamicLayoutVertexBuffer=t.createVertexBuffer(this.dynamicLayoutVertexArray,Tl.members,!0),this.opacityVertexBuffer=t.createVertexBuffer(this.opacityVertexArray,oc,!0),this.opacityVertexBuffer.itemSize=1),(r||n)&&this.programConfigurations.upload(t))},cc.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy(),this.dynamicLayoutVertexBuffer.destroy(),this.opacityVertexBuffer.destroy())},oi(\"SymbolBuffers\",cc);var fc=function(t,e,r){this.layoutVertexArray=new t,this.layoutAttributes=e,this.indexArray=new r,this.segments=new za,this.collisionVertexArray=new da};fc.prototype.upload=function(t){this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,this.layoutAttributes),this.indexBuffer=t.createIndexBuffer(this.indexArray),this.collisionVertexBuffer=t.createVertexBuffer(this.collisionVertexArray,kl.members,!0)},fc.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.segments.destroy(),this.collisionVertexBuffer.destroy())},oi(\"CollisionBuffers\",fc);var hc=function(t){this.collisionBoxArray=t.collisionBoxArray,this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.pixelRatio=t.pixelRatio,this.sourceLayerIndex=t.sourceLayerIndex,this.hasPattern=!1,this.hasRTLText=!1,this.sortKeyRanges=[],this.collisionCircleArray=[],this.placementInvProjMatrix=Bo([]),this.placementViewportMatrix=Bo([]);var e=this.layers[0]._unevaluatedLayout._values;this.textSizeData=Mu(this.zoom,e[\"text-size\"]),this.iconSizeData=Mu(this.zoom,e[\"icon-size\"]);var r=this.layers[0].layout,n=r.get(\"symbol-sort-key\"),i=r.get(\"symbol-z-order\");this.canOverlap=r.get(\"text-allow-overlap\")||r.get(\"icon-allow-overlap\")||r.get(\"text-ignore-placement\")||r.get(\"icon-ignore-placement\"),this.sortFeaturesByKey=\"viewport-y\"!==i&&void 0!==n.constantOr(1);var a=\"viewport-y\"===i||\"auto\"===i&&!this.sortFeaturesByKey;this.sortFeaturesByY=a&&this.canOverlap,\"point\"===r.get(\"symbol-placement\")&&(this.writingModes=r.get(\"text-writing-mode\").map((function(t){return lu[t]}))),this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id})),this.sourceID=t.sourceID};hc.prototype.createArrays=function(){this.text=new cc(new co(this.layers,this.zoom,(function(t){return/^text/.test(t)}))),this.icon=new cc(new co(this.layers,this.zoom,(function(t){return/^icon/.test(t)}))),this.glyphOffsetArray=new Ca,this.lineVertexArray=new Pa,this.symbolInstances=new La},hc.prototype.calculateGlyphDependencies=function(t,e,r,n,i){for(var a=0;a<t.length;a++)if(e[t.charCodeAt(a)]=!0,(r||n)&&i){var o=El[t.charAt(a)];o&&(e[o.charCodeAt(0)]=!0)}},hc.prototype.populate=function(t,e,r){var n=this.layers[0],i=n.layout,a=i.get(\"text-font\"),o=i.get(\"text-field\"),s=i.get(\"icon-image\"),l=(\"constant\"!==o.value.kind||o.value.value instanceof he&&!o.value.value.isEmpty()||o.value.value.toString().length>0)&&(\"constant\"!==a.value.kind||a.value.value.length>0),u=\"constant\"!==s.value.kind||!!s.value.value||Object.keys(s.parameters).length>0,c=i.get(\"symbol-sort-key\");if(this.features=[],l||u){for(var f=e.iconDependencies,h=e.glyphDependencies,p=e.availableImages,d=new Di(this.zoom),v=0,g=t;v<g.length;v+=1){var y=g[v],m=y.feature,x=y.id,b=y.index,_=y.sourceLayerIndex,w=n._featureFilter.needGeometry,T=mo(m,w);if(n._featureFilter.filter(d,T,r)){w||(T.geometry=yo(m));var k=void 0;if(l){var A=n.getValueAndResolveTokens(\"text-field\",T,r,p),M=he.factory(A);uc(M)&&(this.hasRTLText=!0),(!this.hasRTLText||\"unavailable\"===Pi()||this.hasRTLText&&Ii.isParsed())&&(k=Sl(M,n,T))}var S=void 0;if(u){var E=n.getValueAndResolveTokens(\"icon-image\",T,r,p);S=E instanceof pe?E:pe.fromString(E)}if(k||S){var L=this.sortFeaturesByKey?c.evaluate(T,{},r):void 0,C={id:x,text:k,icon:S,index:b,sourceLayerIndex:_,geometry:T.geometry,properties:m.properties,type:ac[m.type],sortKey:L};if(this.features.push(C),S&&(f[S.name]=!0),k){var P=a.evaluate(T,{},r).join(\",\"),O=\"map\"===i.get(\"text-rotation-alignment\")&&\"point\"!==i.get(\"symbol-placement\");this.allowVerticalPlacement=this.writingModes&&this.writingModes.indexOf(lu.vertical)>=0;for(var I=0,D=k.sections;I<D.length;I+=1){var z=D[I];if(z.image)f[z.image.name]=!0;else{var R=di(k.toString()),F=z.fontStack||P,B=h[F]=h[F]||{};this.calculateGlyphDependencies(z.text,B,O,this.allowVerticalPlacement,R)}}}}}}\"line\"===i.get(\"symbol-placement\")&&(this.features=function(t){var e={},r={},n=[],i=0;function a(e){n.push(t[e]),i++}function o(t,e,i){var a=r[t];return delete r[t],r[e]=a,n[a].geometry[0].pop(),n[a].geometry[0]=n[a].geometry[0].concat(i[0]),a}function s(t,r,i){var a=e[r];return delete e[r],e[t]=a,n[a].geometry[0].shift(),n[a].geometry[0]=i[0].concat(n[a].geometry[0]),a}function l(t,e,r){var n=r?e[0][e[0].length-1]:e[0][0];return t+\":\"+n.x+\":\"+n.y}for(var u=0;u<t.length;u++){var c=t[u],f=c.geometry,h=c.text?c.text.toString():null;if(h){var p=l(h,f),d=l(h,f,!0);if(p in r&&d in e&&r[p]!==e[d]){var v=s(p,d,f),g=o(p,d,n[v].geometry);delete e[p],delete r[d],r[l(h,n[g].geometry,!0)]=g,n[v].geometry=null}else p in r?o(p,d,f):d in e?s(p,d,f):(a(u),e[p]=i-1,r[d]=i-1)}else a(u)}return n.filter((function(t){return t.geometry}))}(this.features)),this.sortFeaturesByKey&&this.features.sort((function(t,e){return t.sortKey-e.sortKey}))}},hc.prototype.update=function(t,e,r){this.stateDependentLayers.length&&(this.text.programConfigurations.updatePaintArrays(t,e,this.layers,r),this.icon.programConfigurations.updatePaintArrays(t,e,this.layers,r))},hc.prototype.isEmpty=function(){return 0===this.symbolInstances.length&&!this.hasRTLText},hc.prototype.uploadPending=function(){return!this.uploaded||this.text.programConfigurations.needsUpload||this.icon.programConfigurations.needsUpload},hc.prototype.upload=function(t){!this.uploaded&&this.hasDebugData()&&(this.textCollisionBox.upload(t),this.iconCollisionBox.upload(t)),this.text.upload(t,this.sortFeaturesByY,!this.uploaded,this.text.programConfigurations.needsUpload),this.icon.upload(t,this.sortFeaturesByY,!this.uploaded,this.icon.programConfigurations.needsUpload),this.uploaded=!0},hc.prototype.destroyDebugData=function(){this.textCollisionBox.destroy(),this.iconCollisionBox.destroy()},hc.prototype.destroy=function(){this.text.destroy(),this.icon.destroy(),this.hasDebugData()&&this.destroyDebugData()},hc.prototype.addToLineVertexArray=function(t,e){var r=this.lineVertexArray.length;if(void 0!==t.segment){for(var n=t.dist(e[t.segment+1]),i=t.dist(e[t.segment]),a={},o=t.segment+1;o<e.length;o++)a[o]={x:e[o].x,y:e[o].y,tileUnitDistanceFromAnchor:n},o<e.length-1&&(n+=e[o+1].dist(e[o]));for(var s=t.segment||0;s>=0;s--)a[s]={x:e[s].x,y:e[s].y,tileUnitDistanceFromAnchor:i},s>0&&(i+=e[s-1].dist(e[s]));for(var l=0;l<e.length;l++){var u=a[l];this.lineVertexArray.emplaceBack(u.x,u.y,u.tileUnitDistanceFromAnchor)}}return{lineStartIndex:r,lineLength:this.lineVertexArray.length-r}},hc.prototype.addSymbols=function(t,e,r,n,i,a,o,s,l,u,c,f){for(var h=t.indexArray,p=t.layoutVertexArray,d=t.segments.prepareSegment(4*e.length,p,h,this.canOverlap?a.sortKey:void 0),v=this.glyphOffsetArray.length,g=d.vertexLength,y=this.allowVerticalPlacement&&o===lu.vertical?Math.PI/2:0,m=a.text&&a.text.sections,x=0;x<e.length;x++){var b=e[x],_=b.tl,w=b.tr,T=b.bl,k=b.br,A=b.tex,M=b.pixelOffsetTL,S=b.pixelOffsetBR,E=b.minFontScaleX,L=b.minFontScaleY,C=b.glyphOffset,P=b.isSDF,O=b.sectionIndex,I=d.vertexLength,D=C[1];sc(p,s.x,s.y,_.x,D+_.y,A.x,A.y,r,P,M.x,M.y,E,L),sc(p,s.x,s.y,w.x,D+w.y,A.x+A.w,A.y,r,P,S.x,M.y,E,L),sc(p,s.x,s.y,T.x,D+T.y,A.x,A.y+A.h,r,P,M.x,S.y,E,L),sc(p,s.x,s.y,k.x,D+k.y,A.x+A.w,A.y+A.h,r,P,S.x,S.y,E,L),lc(t.dynamicLayoutVertexArray,s,y),h.emplaceBack(I,I+1,I+2),h.emplaceBack(I+1,I+2,I+3),d.vertexLength+=4,d.primitiveLength+=2,this.glyphOffsetArray.emplaceBack(C[0]),x!==e.length-1&&O===e[x+1].sectionIndex||t.programConfigurations.populatePaintArrays(p.length,a,a.index,{},f,m&&m[O])}t.placedSymbolArray.emplaceBack(s.x,s.y,v,this.glyphOffsetArray.length-v,g,l,u,s.segment,r?r[0]:0,r?r[1]:0,n[0],n[1],o,0,!1,0,c)},hc.prototype._addCollisionDebugVertex=function(t,e,r,n,i,a){return e.emplaceBack(0,0),t.emplaceBack(r.x,r.y,n,i,Math.round(a.x),Math.round(a.y))},hc.prototype.addCollisionDebugVertices=function(t,e,r,n,i,o,s){var l=i.segments.prepareSegment(4,i.layoutVertexArray,i.indexArray),u=l.vertexLength,c=i.layoutVertexArray,f=i.collisionVertexArray,h=s.anchorX,p=s.anchorY;this._addCollisionDebugVertex(c,f,o,h,p,new a(t,e)),this._addCollisionDebugVertex(c,f,o,h,p,new a(r,e)),this._addCollisionDebugVertex(c,f,o,h,p,new a(r,n)),this._addCollisionDebugVertex(c,f,o,h,p,new a(t,n)),l.vertexLength+=4;var d=i.indexArray;d.emplaceBack(u,u+1),d.emplaceBack(u+1,u+2),d.emplaceBack(u+2,u+3),d.emplaceBack(u+3,u),l.primitiveLength+=4},hc.prototype.addDebugCollisionBoxes=function(t,e,r,n){for(var i=t;i<e;i++){var a=this.collisionBoxArray.get(i),o=a.x1,s=a.y1,l=a.x2,u=a.y2;this.addCollisionDebugVertices(o,s,l,u,n?this.textCollisionBox:this.iconCollisionBox,a.anchorPoint,r)}},hc.prototype.generateCollisionDebugBuffers=function(){this.hasDebugData()&&this.destroyDebugData(),this.textCollisionBox=new fc(ha,Al.members,_a),this.iconCollisionBox=new fc(ha,Al.members,_a);for(var t=0;t<this.symbolInstances.length;t++){var e=this.symbolInstances.get(t);this.addDebugCollisionBoxes(e.textBoxStartIndex,e.textBoxEndIndex,e,!0),this.addDebugCollisionBoxes(e.verticalTextBoxStartIndex,e.verticalTextBoxEndIndex,e,!0),this.addDebugCollisionBoxes(e.iconBoxStartIndex,e.iconBoxEndIndex,e,!1),this.addDebugCollisionBoxes(e.verticalIconBoxStartIndex,e.verticalIconBoxEndIndex,e,!1)}},hc.prototype._deserializeCollisionBoxesForSymbol=function(t,e,r,n,i,a,o,s,l){for(var u={},c=e;c<r;c++){var f=t.get(c);u.textBox={x1:f.x1,y1:f.y1,x2:f.x2,y2:f.y2,anchorPointX:f.anchorPointX,anchorPointY:f.anchorPointY},u.textFeatureIndex=f.featureIndex;break}for(var h=n;h<i;h++){var p=t.get(h);u.verticalTextBox={x1:p.x1,y1:p.y1,x2:p.x2,y2:p.y2,anchorPointX:p.anchorPointX,anchorPointY:p.anchorPointY},u.verticalTextFeatureIndex=p.featureIndex;break}for(var d=a;d<o;d++){var v=t.get(d);u.iconBox={x1:v.x1,y1:v.y1,x2:v.x2,y2:v.y2,anchorPointX:v.anchorPointX,anchorPointY:v.anchorPointY},u.iconFeatureIndex=v.featureIndex;break}for(var g=s;g<l;g++){var y=t.get(g);u.verticalIconBox={x1:y.x1,y1:y.y1,x2:y.x2,y2:y.y2,anchorPointX:y.anchorPointX,anchorPointY:y.anchorPointY},u.verticalIconFeatureIndex=y.featureIndex;break}return u},hc.prototype.deserializeCollisionBoxes=function(t){this.collisionArrays=[];for(var e=0;e<this.symbolInstances.length;e++){var r=this.symbolInstances.get(e);this.collisionArrays.push(this._deserializeCollisionBoxesForSymbol(t,r.textBoxStartIndex,r.textBoxEndIndex,r.verticalTextBoxStartIndex,r.verticalTextBoxEndIndex,r.iconBoxStartIndex,r.iconBoxEndIndex,r.verticalIconBoxStartIndex,r.verticalIconBoxEndIndex))}},hc.prototype.hasTextData=function(){return this.text.segments.get().length>0},hc.prototype.hasIconData=function(){return this.icon.segments.get().length>0},hc.prototype.hasDebugData=function(){return this.textCollisionBox&&this.iconCollisionBox},hc.prototype.hasTextCollisionBoxData=function(){return this.hasDebugData()&&this.textCollisionBox.segments.get().length>0},hc.prototype.hasIconCollisionBoxData=function(){return this.hasDebugData()&&this.iconCollisionBox.segments.get().length>0},hc.prototype.addIndicesForPlacedSymbol=function(t,e){for(var r=t.placedSymbolArray.get(e),n=r.vertexStartIndex+4*r.numGlyphs,i=r.vertexStartIndex;i<n;i+=4)t.indexArray.emplaceBack(i,i+1,i+2),t.indexArray.emplaceBack(i+1,i+2,i+3)},hc.prototype.getSortedSymbolIndexes=function(t){if(this.sortedAngle===t&&void 0!==this.symbolInstanceIndexes)return this.symbolInstanceIndexes;for(var e=Math.sin(t),r=Math.cos(t),n=[],i=[],a=[],o=0;o<this.symbolInstances.length;++o){a.push(o);var s=this.symbolInstances.get(o);n.push(0|Math.round(e*s.anchorX+r*s.anchorY)),i.push(s.featureIndex)}return a.sort((function(t,e){return n[t]-n[e]||i[e]-i[t]})),a},hc.prototype.addToSortKeyRanges=function(t,e){var r=this.sortKeyRanges[this.sortKeyRanges.length-1];r&&r.sortKey===e?r.symbolInstanceEnd=t+1:this.sortKeyRanges.push({sortKey:e,symbolInstanceStart:t,symbolInstanceEnd:t+1})},hc.prototype.sortFeatures=function(t){var e=this;if(this.sortFeaturesByY&&this.sortedAngle!==t&&!(this.text.segments.get().length>1||this.icon.segments.get().length>1)){this.symbolInstanceIndexes=this.getSortedSymbolIndexes(t),this.sortedAngle=t,this.text.indexArray.clear(),this.icon.indexArray.clear(),this.featureSortOrder=[];for(var r=0,n=this.symbolInstanceIndexes;r<n.length;r+=1){var i=n[r],a=this.symbolInstances.get(i);this.featureSortOrder.push(a.featureIndex),[a.rightJustifiedTextSymbolIndex,a.centerJustifiedTextSymbolIndex,a.leftJustifiedTextSymbolIndex].forEach((function(t,r,n){t>=0&&n.indexOf(t)===r&&e.addIndicesForPlacedSymbol(e.text,t)})),a.verticalPlacedTextSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.text,a.verticalPlacedTextSymbolIndex),a.placedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,a.placedIconSymbolIndex),a.verticalPlacedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,a.verticalPlacedIconSymbolIndex)}this.text.indexBuffer&&this.text.indexBuffer.updateData(this.text.indexArray),this.icon.indexBuffer&&this.icon.indexBuffer.updateData(this.icon.indexArray)}},oi(\"SymbolBucket\",hc,{omit:[\"layers\",\"collisionBoxArray\",\"features\",\"compareText\"]}),hc.MAX_GLYPHS=65535,hc.addDynamicAttributes=lc;var pc=new Xi({\"symbol-placement\":new qi(Ft.layout_symbol[\"symbol-placement\"]),\"symbol-spacing\":new qi(Ft.layout_symbol[\"symbol-spacing\"]),\"symbol-avoid-edges\":new qi(Ft.layout_symbol[\"symbol-avoid-edges\"]),\"symbol-sort-key\":new Hi(Ft.layout_symbol[\"symbol-sort-key\"]),\"symbol-z-order\":new qi(Ft.layout_symbol[\"symbol-z-order\"]),\"icon-allow-overlap\":new qi(Ft.layout_symbol[\"icon-allow-overlap\"]),\"icon-ignore-placement\":new qi(Ft.layout_symbol[\"icon-ignore-placement\"]),\"icon-optional\":new qi(Ft.layout_symbol[\"icon-optional\"]),\"icon-rotation-alignment\":new qi(Ft.layout_symbol[\"icon-rotation-alignment\"]),\"icon-size\":new Hi(Ft.layout_symbol[\"icon-size\"]),\"icon-text-fit\":new qi(Ft.layout_symbol[\"icon-text-fit\"]),\"icon-text-fit-padding\":new qi(Ft.layout_symbol[\"icon-text-fit-padding\"]),\"icon-image\":new Hi(Ft.layout_symbol[\"icon-image\"]),\"icon-rotate\":new Hi(Ft.layout_symbol[\"icon-rotate\"]),\"icon-padding\":new qi(Ft.layout_symbol[\"icon-padding\"]),\"icon-keep-upright\":new qi(Ft.layout_symbol[\"icon-keep-upright\"]),\"icon-offset\":new Hi(Ft.layout_symbol[\"icon-offset\"]),\"icon-anchor\":new Hi(Ft.layout_symbol[\"icon-anchor\"]),\"icon-pitch-alignment\":new qi(Ft.layout_symbol[\"icon-pitch-alignment\"]),\"text-pitch-alignment\":new qi(Ft.layout_symbol[\"text-pitch-alignment\"]),\"text-rotation-alignment\":new qi(Ft.layout_symbol[\"text-rotation-alignment\"]),\"text-field\":new Hi(Ft.layout_symbol[\"text-field\"]),\"text-font\":new Hi(Ft.layout_symbol[\"text-font\"]),\"text-size\":new Hi(Ft.layout_symbol[\"text-size\"]),\"text-max-width\":new Hi(Ft.layout_symbol[\"text-max-width\"]),\"text-line-height\":new qi(Ft.layout_symbol[\"text-line-height\"]),\"text-letter-spacing\":new Hi(Ft.layout_symbol[\"text-letter-spacing\"]),\"text-justify\":new Hi(Ft.layout_symbol[\"text-justify\"]),\"text-radial-offset\":new Hi(Ft.layout_symbol[\"text-radial-offset\"]),\"text-variable-anchor\":new qi(Ft.layout_symbol[\"text-variable-anchor\"]),\"text-anchor\":new Hi(Ft.layout_symbol[\"text-anchor\"]),\"text-max-angle\":new qi(Ft.layout_symbol[\"text-max-angle\"]),\"text-writing-mode\":new qi(Ft.layout_symbol[\"text-writing-mode\"]),\"text-rotate\":new Hi(Ft.layout_symbol[\"text-rotate\"]),\"text-padding\":new qi(Ft.layout_symbol[\"text-padding\"]),\"text-keep-upright\":new qi(Ft.layout_symbol[\"text-keep-upright\"]),\"text-transform\":new Hi(Ft.layout_symbol[\"text-transform\"]),\"text-offset\":new Hi(Ft.layout_symbol[\"text-offset\"]),\"text-allow-overlap\":new qi(Ft.layout_symbol[\"text-allow-overlap\"]),\"text-ignore-placement\":new qi(Ft.layout_symbol[\"text-ignore-placement\"]),\"text-optional\":new qi(Ft.layout_symbol[\"text-optional\"])}),dc={paint:new Xi({\"icon-opacity\":new Hi(Ft.paint_symbol[\"icon-opacity\"]),\"icon-color\":new Hi(Ft.paint_symbol[\"icon-color\"]),\"icon-halo-color\":new Hi(Ft.paint_symbol[\"icon-halo-color\"]),\"icon-halo-width\":new Hi(Ft.paint_symbol[\"icon-halo-width\"]),\"icon-halo-blur\":new Hi(Ft.paint_symbol[\"icon-halo-blur\"]),\"icon-translate\":new qi(Ft.paint_symbol[\"icon-translate\"]),\"icon-translate-anchor\":new qi(Ft.paint_symbol[\"icon-translate-anchor\"]),\"text-opacity\":new Hi(Ft.paint_symbol[\"text-opacity\"]),\"text-color\":new Hi(Ft.paint_symbol[\"text-color\"],{runtimeType:Zt,getOverride:function(t){return t.textColor},hasOverride:function(t){return!!t.textColor}}),\"text-halo-color\":new Hi(Ft.paint_symbol[\"text-halo-color\"]),\"text-halo-width\":new Hi(Ft.paint_symbol[\"text-halo-width\"]),\"text-halo-blur\":new Hi(Ft.paint_symbol[\"text-halo-blur\"]),\"text-translate\":new qi(Ft.paint_symbol[\"text-translate\"]),\"text-translate-anchor\":new qi(Ft.paint_symbol[\"text-translate-anchor\"])}),layout:pc},vc=function(t){this.type=t.property.overrides?t.property.overrides.runtimeType:Gt,this.defaultValue=t};vc.prototype.evaluate=function(t){if(t.formattedSection){var e=this.defaultValue.property.overrides;if(e&&e.hasOverride(t.formattedSection))return e.getOverride(t.formattedSection)}return t.feature&&t.featureState?this.defaultValue.evaluate(t.feature,t.featureState):this.defaultValue.property.specification.default},vc.prototype.eachChild=function(t){this.defaultValue.isConstant()||t(this.defaultValue.value._styleExpression.expression)},vc.prototype.outputDefined=function(){return!1},vc.prototype.serialize=function(){return null},oi(\"FormatSectionOverride\",vc,{omit:[\"defaultValue\"]});var gc=function(t){function e(e){t.call(this,e,dc)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.recalculate=function(e,r){if(t.prototype.recalculate.call(this,e,r),\"auto\"===this.layout.get(\"icon-rotation-alignment\")&&(\"point\"!==this.layout.get(\"symbol-placement\")?this.layout._values[\"icon-rotation-alignment\"]=\"map\":this.layout._values[\"icon-rotation-alignment\"]=\"viewport\"),\"auto\"===this.layout.get(\"text-rotation-alignment\")&&(\"point\"!==this.layout.get(\"symbol-placement\")?this.layout._values[\"text-rotation-alignment\"]=\"map\":this.layout._values[\"text-rotation-alignment\"]=\"viewport\"),\"auto\"===this.layout.get(\"text-pitch-alignment\")&&(this.layout._values[\"text-pitch-alignment\"]=this.layout.get(\"text-rotation-alignment\")),\"auto\"===this.layout.get(\"icon-pitch-alignment\")&&(this.layout._values[\"icon-pitch-alignment\"]=this.layout.get(\"icon-rotation-alignment\")),\"point\"===this.layout.get(\"symbol-placement\")){var n=this.layout.get(\"text-writing-mode\");if(n){for(var i=[],a=0,o=n;a<o.length;a+=1){var s=o[a];i.indexOf(s)<0&&i.push(s)}this.layout._values[\"text-writing-mode\"]=i}else this.layout._values[\"text-writing-mode\"]=[\"horizontal\"]}this._setPaintOverrides()},e.prototype.getValueAndResolveTokens=function(t,e,r,n){var i=this.layout.get(t).evaluate(e,{},r,n),a=this._unevaluatedLayout._values[t];return a.isDataDriven()||cn(a.value)||!i?i:function(t,e){return e.replace(/{([^{}]+)}/g,(function(e,r){return r in t?String(t[r]):\"\"}))}(e.properties,i)},e.prototype.createBucket=function(t){return new hc(t)},e.prototype.queryRadius=function(){return 0},e.prototype.queryIntersectsFeature=function(){return!1},e.prototype._setPaintOverrides=function(){for(var t=0,r=dc.paint.overridableProperties;t<r.length;t+=1){var n=r[t];if(e.hasPaintOverride(this.layout,n)){var i,a=this.paint.get(n),o=new vc(a),s=new un(o,a.property.specification);i=\"constant\"===a.value.kind||\"source\"===a.value.kind?new hn(\"source\",s):new pn(\"composite\",s,a.value.zoomStops,a.value._interpolationType),this.paint._values[n]=new Ui(a.property,i,a.parameters)}}},e.prototype._handleOverridablePaintPropertyUpdate=function(t,r,n){return!(!this.layout||r.isDataDriven()||n.isDataDriven())&&e.hasPaintOverride(this.layout,t)},e.hasPaintOverride=function(t,e){var r=t.get(\"text-field\"),n=dc.paint.properties[e],i=!1,a=function(t){for(var e=0,r=t;e<r.length;e+=1){var a=r[e];if(n.overrides&&n.overrides.hasOverride(a))return void(i=!0)}};if(\"constant\"===r.value.kind&&r.value.value instanceof he)a(r.value.value.sections);else if(\"source\"===r.value.kind){var o=function(t){if(!i)if(t instanceof me&&ge(t.value)===Qt){var e=t.value;a(e.sections)}else t instanceof we?a(t.sections):t.eachChild(o)},s=r.value;s._styleExpression&&o(s._styleExpression.expression)}return i},e}(Ki),yc={paint:new Xi({\"background-color\":new qi(Ft.paint_background[\"background-color\"]),\"background-pattern\":new Wi(Ft.paint_background[\"background-pattern\"]),\"background-opacity\":new qi(Ft.paint_background[\"background-opacity\"])})},mc=function(t){function e(e){t.call(this,e,yc)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(Ki),xc={paint:new Xi({\"raster-opacity\":new qi(Ft.paint_raster[\"raster-opacity\"]),\"raster-hue-rotate\":new qi(Ft.paint_raster[\"raster-hue-rotate\"]),\"raster-brightness-min\":new qi(Ft.paint_raster[\"raster-brightness-min\"]),\"raster-brightness-max\":new qi(Ft.paint_raster[\"raster-brightness-max\"]),\"raster-saturation\":new qi(Ft.paint_raster[\"raster-saturation\"]),\"raster-contrast\":new qi(Ft.paint_raster[\"raster-contrast\"]),\"raster-resampling\":new qi(Ft.paint_raster[\"raster-resampling\"]),\"raster-fade-duration\":new qi(Ft.paint_raster[\"raster-fade-duration\"])})},bc=function(t){function e(e){t.call(this,e,xc)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(Ki);var _c=function(t){function e(e){t.call(this,e,{}),this.implementation=e}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.is3D=function(){return\"3d\"===this.implementation.renderingMode},e.prototype.hasOffscreenPass=function(){return void 0!==this.implementation.prerender},e.prototype.recalculate=function(){},e.prototype.updateTransitions=function(){},e.prototype.hasTransition=function(){},e.prototype.serialize=function(){},e.prototype.onAdd=function(t){this.implementation.onAdd&&this.implementation.onAdd(t,t.painter.context.gl)},e.prototype.onRemove=function(t){this.implementation.onRemove&&this.implementation.onRemove(t,t.painter.context.gl)},e}(Ki),wc={circle:Go,heatmap:es,hillshade:ns,fill:Hs,\"fill-extrusion\":sl,line:bl,symbol:gc,background:mc,raster:bc};var Tc=s.HTMLImageElement,kc=s.HTMLCanvasElement,Ac=s.HTMLVideoElement,Mc=s.ImageData,Sc=s.ImageBitmap,Ec=function(t,e,r,n){this.context=t,this.format=r,this.texture=t.gl.createTexture(),this.update(e,n)};Ec.prototype.update=function(t,e,r){var n=t.width,i=t.height,a=!(this.size&&this.size[0]===n&&this.size[1]===i||r),o=this.context,s=o.gl;if(this.useMipmap=Boolean(e&&e.useMipmap),s.bindTexture(s.TEXTURE_2D,this.texture),o.pixelStoreUnpackFlipY.set(!1),o.pixelStoreUnpack.set(1),o.pixelStoreUnpackPremultiplyAlpha.set(this.format===s.RGBA&&(!e||!1!==e.premultiply)),a)this.size=[n,i],t instanceof Tc||t instanceof kc||t instanceof Ac||t instanceof Mc||Sc&&t instanceof Sc?s.texImage2D(s.TEXTURE_2D,0,this.format,this.format,s.UNSIGNED_BYTE,t):s.texImage2D(s.TEXTURE_2D,0,this.format,n,i,0,this.format,s.UNSIGNED_BYTE,t.data);else{var l=r||{x:0,y:0},u=l.x,c=l.y;t instanceof Tc||t instanceof kc||t instanceof Ac||t instanceof Mc||Sc&&t instanceof Sc?s.texSubImage2D(s.TEXTURE_2D,0,u,c,s.RGBA,s.UNSIGNED_BYTE,t):s.texSubImage2D(s.TEXTURE_2D,0,u,c,n,i,s.RGBA,s.UNSIGNED_BYTE,t.data)}this.useMipmap&&this.isSizePowerOfTwo()&&s.generateMipmap(s.TEXTURE_2D)},Ec.prototype.bind=function(t,e,r){var n=this.context.gl;n.bindTexture(n.TEXTURE_2D,this.texture),r!==n.LINEAR_MIPMAP_NEAREST||this.isSizePowerOfTwo()||(r=n.LINEAR),t!==this.filter&&(n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MAG_FILTER,t),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MIN_FILTER,r||t),this.filter=t),e!==this.wrap&&(n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_S,e),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_T,e),this.wrap=e)},Ec.prototype.isSizePowerOfTwo=function(){return this.size[0]===this.size[1]&&Math.log(this.size[0])/Math.LN2%1==0},Ec.prototype.destroy=function(){this.context.gl.deleteTexture(this.texture),this.texture=null};var Lc=function(t){var e=this;this._callback=t,this._triggered=!1,\"undefined\"!=typeof MessageChannel&&(this._channel=new MessageChannel,this._channel.port2.onmessage=function(){e._triggered=!1,e._callback()})};Lc.prototype.trigger=function(){var t=this;this._triggered||(this._triggered=!0,this._channel?this._channel.port1.postMessage(!0):setTimeout((function(){t._triggered=!1,t._callback()}),0))},Lc.prototype.remove=function(){delete this._channel,this._callback=function(){}};var Cc=function(t,e,r){this.target=t,this.parent=e,this.mapId=r,this.callbacks={},this.tasks={},this.taskQueue=[],this.cancelCallbacks={},m([\"receive\",\"process\"],this),this.invoker=new Lc(this.process),this.target.addEventListener(\"message\",this.receive,!1),this.globalScope=S()?t:s};function Pc(t,e,r){var n=2*Math.PI*6378137/256/Math.pow(2,r);return[t*n-2*Math.PI*6378137/2,e*n-2*Math.PI*6378137/2]}Cc.prototype.send=function(t,e,r,n,i){var a=this;void 0===i&&(i=!1);var o=Math.round(1e18*Math.random()).toString(36).substring(0,10);r&&(this.callbacks[o]=r);var s=C(this.globalScope)?void 0:[];return this.target.postMessage({id:o,type:t,hasCallback:!!r,targetMapId:n,mustQueue:i,sourceMapId:this.mapId,data:ci(e,s)},s),{cancel:function(){r&&delete a.callbacks[o],a.target.postMessage({id:o,type:\"<cancel>\",targetMapId:n,sourceMapId:a.mapId})}}},Cc.prototype.receive=function(t){var e=t.data,r=e.id;if(r&&(!e.targetMapId||this.mapId===e.targetMapId))if(\"<cancel>\"===e.type){delete this.tasks[r];var n=this.cancelCallbacks[r];delete this.cancelCallbacks[r],n&&n()}else S()||e.mustQueue?(this.tasks[r]=e,this.taskQueue.push(r),this.invoker.trigger()):this.processTask(r,e)},Cc.prototype.process=function(){if(this.taskQueue.length){var t=this.taskQueue.shift(),e=this.tasks[t];delete this.tasks[t],this.taskQueue.length&&this.invoker.trigger(),e&&this.processTask(t,e)}},Cc.prototype.processTask=function(t,e){var r=this;if(\"<response>\"===e.type){var n=this.callbacks[t];delete this.callbacks[t],n&&(e.error?n(fi(e.error)):n(null,fi(e.data)))}else{var i=!1,a=C(this.globalScope)?void 0:[],o=e.hasCallback?function(e,n){i=!0,delete r.cancelCallbacks[t],r.target.postMessage({id:t,type:\"<response>\",sourceMapId:r.mapId,error:e?ci(e):null,data:ci(n,a)},a)}:function(t){i=!0},s=null,l=fi(e.data);if(this.parent[e.type])s=this.parent[e.type](e.sourceMapId,l,o);else if(this.parent.getWorkerSource){var u=e.type.split(\".\");s=this.parent.getWorkerSource(e.sourceMapId,u[0],l.source)[u[1]](l,o)}else o(new Error(\"Could not find function \"+e.type));!i&&s&&s.cancel&&(this.cancelCallbacks[t]=s.cancel)}},Cc.prototype.remove=function(){this.invoker.remove(),this.target.removeEventListener(\"message\",this.receive,!1)};var Oc=function(t,e){t&&(e?this.setSouthWest(t).setNorthEast(e):4===t.length?this.setSouthWest([t[0],t[1]]).setNorthEast([t[2],t[3]]):this.setSouthWest(t[0]).setNorthEast(t[1]))};Oc.prototype.setNorthEast=function(t){return this._ne=t instanceof Dc?new Dc(t.lng,t.lat):Dc.convert(t),this},Oc.prototype.setSouthWest=function(t){return this._sw=t instanceof Dc?new Dc(t.lng,t.lat):Dc.convert(t),this},Oc.prototype.extend=function(t){var e,r,n=this._sw,i=this._ne;if(t instanceof Dc)e=t,r=t;else{if(!(t instanceof Oc)){if(Array.isArray(t)){if(4===t.length||t.every(Array.isArray)){var a=t;return this.extend(Oc.convert(a))}var o=t;return this.extend(Dc.convert(o))}return this}if(e=t._sw,r=t._ne,!e||!r)return this}return n||i?(n.lng=Math.min(e.lng,n.lng),n.lat=Math.min(e.lat,n.lat),i.lng=Math.max(r.lng,i.lng),i.lat=Math.max(r.lat,i.lat)):(this._sw=new Dc(e.lng,e.lat),this._ne=new Dc(r.lng,r.lat)),this},Oc.prototype.getCenter=function(){return new Dc((this._sw.lng+this._ne.lng)/2,(this._sw.lat+this._ne.lat)/2)},Oc.prototype.getSouthWest=function(){return this._sw},Oc.prototype.getNorthEast=function(){return this._ne},Oc.prototype.getNorthWest=function(){return new Dc(this.getWest(),this.getNorth())},Oc.prototype.getSouthEast=function(){return new Dc(this.getEast(),this.getSouth())},Oc.prototype.getWest=function(){return this._sw.lng},Oc.prototype.getSouth=function(){return this._sw.lat},Oc.prototype.getEast=function(){return this._ne.lng},Oc.prototype.getNorth=function(){return this._ne.lat},Oc.prototype.toArray=function(){return[this._sw.toArray(),this._ne.toArray()]},Oc.prototype.toString=function(){return\"LngLatBounds(\"+this._sw.toString()+\", \"+this._ne.toString()+\")\"},Oc.prototype.isEmpty=function(){return!(this._sw&&this._ne)},Oc.prototype.contains=function(t){var e=Dc.convert(t),r=e.lng,n=e.lat,i=this._sw.lat<=n&&n<=this._ne.lat,a=this._sw.lng<=r&&r<=this._ne.lng;return this._sw.lng>this._ne.lng&&(a=this._sw.lng>=r&&r>=this._ne.lng),i&&a},Oc.convert=function(t){return!t||t instanceof Oc?t:new Oc(t)};var Ic=6371008.8,Dc=function(t,e){if(isNaN(t)||isNaN(e))throw new Error(\"Invalid LngLat object: (\"+t+\", \"+e+\")\");if(this.lng=+t,this.lat=+e,this.lat>90||this.lat<-90)throw new Error(\"Invalid LngLat latitude value: must be between -90 and 90\")};Dc.prototype.wrap=function(){return new Dc(h(this.lng,-180,180),this.lat)},Dc.prototype.toArray=function(){return[this.lng,this.lat]},Dc.prototype.toString=function(){return\"LngLat(\"+this.lng+\", \"+this.lat+\")\"},Dc.prototype.distanceTo=function(t){var e=Math.PI/180,r=this.lat*e,n=t.lat*e,i=Math.sin(r)*Math.sin(n)+Math.cos(r)*Math.cos(n)*Math.cos((t.lng-this.lng)*e);return Ic*Math.acos(Math.min(i,1))},Dc.prototype.toBounds=function(t){void 0===t&&(t=0);var e=360*t/40075017,r=e/Math.cos(Math.PI/180*this.lat);return new Oc(new Dc(this.lng-r,this.lat-e),new Dc(this.lng+r,this.lat+e))},Dc.convert=function(t){if(t instanceof Dc)return t;if(Array.isArray(t)&&(2===t.length||3===t.length))return new Dc(Number(t[0]),Number(t[1]));if(!Array.isArray(t)&&\"object\"==typeof t&&null!==t)return new Dc(Number(\"lng\"in t?t.lng:t.lon),Number(t.lat));throw new Error(\"`LngLatLike` argument must be specified as a LngLat instance, an object {lng: <lng>, lat: <lat>}, an object {lon: <lng>, lat: <lat>}, or an array of [<lng>, <lat>]\")};var zc=2*Math.PI*Ic;function Rc(t){return zc*Math.cos(t*Math.PI/180)}function Fc(t){return(180+t)/360}function Bc(t){return(180-180/Math.PI*Math.log(Math.tan(Math.PI/4+t*Math.PI/360)))/360}function Nc(t,e){return t/Rc(e)}function jc(t){var e=180-360*t;return 360/Math.PI*Math.atan(Math.exp(e*Math.PI/180))-90}var Uc=function(t,e,r){void 0===r&&(r=0),this.x=+t,this.y=+e,this.z=+r};Uc.fromLngLat=function(t,e){void 0===e&&(e=0);var r=Dc.convert(t);return new Uc(Fc(r.lng),Bc(r.lat),Nc(e,r.lat))},Uc.prototype.toLngLat=function(){return new Dc(360*this.x-180,jc(this.y))},Uc.prototype.toAltitude=function(){return t=this.z,e=this.y,t*Rc(jc(e));var t,e},Uc.prototype.meterInMercatorCoordinateUnits=function(){return 1/zc*(t=jc(this.y),1/Math.cos(t*Math.PI/180));var t};var Vc=function(t,e,r){this.z=t,this.x=e,this.y=r,this.key=Gc(0,t,t,e,r)};Vc.prototype.equals=function(t){return this.z===t.z&&this.x===t.x&&this.y===t.y},Vc.prototype.url=function(t,e){var r,n,i,a,o,s=(r=this.x,n=this.y,i=this.z,a=Pc(256*r,256*(n=Math.pow(2,i)-n-1),i),o=Pc(256*(r+1),256*(n+1),i),a[0]+\",\"+a[1]+\",\"+o[0]+\",\"+o[1]),l=function(t,e,r){for(var n,i=\"\",a=t;a>0;a--)i+=(e&(n=1<<a-1)?1:0)+(r&n?2:0);return i}(this.z,this.x,this.y);return t[(this.x+this.y)%t.length].replace(\"{prefix}\",(this.x%16).toString(16)+(this.y%16).toString(16)).replace(\"{z}\",String(this.z)).replace(\"{x}\",String(this.x)).replace(\"{y}\",String(\"tms\"===e?Math.pow(2,this.z)-this.y-1:this.y)).replace(\"{quadkey}\",l).replace(\"{bbox-epsg-3857}\",s)},Vc.prototype.getTilePoint=function(t){var e=Math.pow(2,this.z);return new a((t.x*e-this.x)*po,(t.y*e-this.y)*po)},Vc.prototype.toString=function(){return this.z+\"/\"+this.x+\"/\"+this.y};var qc=function(t,e){this.wrap=t,this.canonical=e,this.key=Gc(t,e.z,e.z,e.x,e.y)},Hc=function(t,e,r,n,i){this.overscaledZ=t,this.wrap=e,this.canonical=new Vc(r,+n,+i),this.key=Gc(e,t,r,n,i)};function Gc(t,e,r,n,i){(t*=2)<0&&(t=-1*t-1);var a=1<<r;return(a*a*t+a*i+n).toString(36)+r.toString(36)+e.toString(36)}Hc.prototype.equals=function(t){return this.overscaledZ===t.overscaledZ&&this.wrap===t.wrap&&this.canonical.equals(t.canonical)},Hc.prototype.scaledTo=function(t){var e=this.canonical.z-t;return t>this.canonical.z?new Hc(t,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y):new Hc(t,this.wrap,t,this.canonical.x>>e,this.canonical.y>>e)},Hc.prototype.calculateScaledKey=function(t,e){var r=this.canonical.z-t;return t>this.canonical.z?Gc(this.wrap*+e,t,this.canonical.z,this.canonical.x,this.canonical.y):Gc(this.wrap*+e,t,t,this.canonical.x>>r,this.canonical.y>>r)},Hc.prototype.isChildOf=function(t){if(t.wrap!==this.wrap)return!1;var e=this.canonical.z-t.canonical.z;return 0===t.overscaledZ||t.overscaledZ<this.overscaledZ&&t.canonical.x===this.canonical.x>>e&&t.canonical.y===this.canonical.y>>e},Hc.prototype.children=function(t){if(this.overscaledZ>=t)return[new Hc(this.overscaledZ+1,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y)];var e=this.canonical.z+1,r=2*this.canonical.x,n=2*this.canonical.y;return[new Hc(e,this.wrap,e,r,n),new Hc(e,this.wrap,e,r+1,n),new Hc(e,this.wrap,e,r,n+1),new Hc(e,this.wrap,e,r+1,n+1)]},Hc.prototype.isLessThan=function(t){return this.wrap<t.wrap||!(this.wrap>t.wrap)&&(this.overscaledZ<t.overscaledZ||!(this.overscaledZ>t.overscaledZ)&&(this.canonical.x<t.canonical.x||!(this.canonical.x>t.canonical.x)&&this.canonical.y<t.canonical.y))},Hc.prototype.wrapped=function(){return new Hc(this.overscaledZ,0,this.canonical.z,this.canonical.x,this.canonical.y)},Hc.prototype.unwrapTo=function(t){return new Hc(this.overscaledZ,t,this.canonical.z,this.canonical.x,this.canonical.y)},Hc.prototype.overscaleFactor=function(){return Math.pow(2,this.overscaledZ-this.canonical.z)},Hc.prototype.toUnwrapped=function(){return new qc(this.wrap,this.canonical)},Hc.prototype.toString=function(){return this.overscaledZ+\"/\"+this.canonical.x+\"/\"+this.canonical.y},Hc.prototype.getTilePoint=function(t){return this.canonical.getTilePoint(new Uc(t.x-this.wrap,t.y))},oi(\"CanonicalTileID\",Vc),oi(\"OverscaledTileID\",Hc,{omit:[\"posMatrix\"]});var Wc=function(t,e,r){if(this.uid=t,e.height!==e.width)throw new RangeError(\"DEM tiles must be square\");if(r&&\"mapbox\"!==r&&\"terrarium\"!==r)return k('\"'+r+'\" is not a valid encoding type. Valid types include \"mapbox\" and \"terrarium\".');this.stride=e.height;var n=this.dim=e.height-2;this.data=new Uint32Array(e.data.buffer),this.encoding=r||\"mapbox\";for(var i=0;i<n;i++)this.data[this._idx(-1,i)]=this.data[this._idx(0,i)],this.data[this._idx(n,i)]=this.data[this._idx(n-1,i)],this.data[this._idx(i,-1)]=this.data[this._idx(i,0)],this.data[this._idx(i,n)]=this.data[this._idx(i,n-1)];this.data[this._idx(-1,-1)]=this.data[this._idx(0,0)],this.data[this._idx(n,-1)]=this.data[this._idx(n-1,0)],this.data[this._idx(-1,n)]=this.data[this._idx(0,n-1)],this.data[this._idx(n,n)]=this.data[this._idx(n-1,n-1)]};Wc.prototype.get=function(t,e){var r=new Uint8Array(this.data.buffer),n=4*this._idx(t,e);return(\"terrarium\"===this.encoding?this._unpackTerrarium:this._unpackMapbox)(r[n],r[n+1],r[n+2])},Wc.prototype.getUnpackVector=function(){return\"terrarium\"===this.encoding?[256,1,1/256,32768]:[6553.6,25.6,.1,1e4]},Wc.prototype._idx=function(t,e){if(t<-1||t>=this.dim+1||e<-1||e>=this.dim+1)throw new RangeError(\"out of range source coordinates for DEM data\");return(e+1)*this.stride+(t+1)},Wc.prototype._unpackMapbox=function(t,e,r){return(256*t*256+256*e+r)/10-1e4},Wc.prototype._unpackTerrarium=function(t,e,r){return 256*t+e+r/256-32768},Wc.prototype.getPixels=function(){return new $o({width:this.stride,height:this.stride},new Uint8Array(this.data.buffer))},Wc.prototype.backfillBorder=function(t,e,r){if(this.dim!==t.dim)throw new Error(\"dem dimension mismatch\");var n=e*this.dim,i=e*this.dim+this.dim,a=r*this.dim,o=r*this.dim+this.dim;switch(e){case-1:n=i-1;break;case 1:i=n+1}switch(r){case-1:a=o-1;break;case 1:o=a+1}for(var s=-e*this.dim,l=-r*this.dim,u=a;u<o;u++)for(var c=n;c<i;c++)this.data[this._idx(c,u)]=t.data[this._idx(c+s,u+l)]},oi(\"DEMData\",Wc);var Yc=function(t){this._stringToNumber={},this._numberToString=[];for(var e=0;e<t.length;e++){var r=t[e];this._stringToNumber[r]=e,this._numberToString[e]=r}};Yc.prototype.encode=function(t){return this._stringToNumber[t]},Yc.prototype.decode=function(t){return this._numberToString[t]};var Xc=function(t,e,r,n,i){this.type=\"Feature\",this._vectorTileFeature=t,t._z=e,t._x=r,t._y=n,this.properties=t.properties,this.id=i},Zc={geometry:{configurable:!0}};Zc.geometry.get=function(){return void 0===this._geometry&&(this._geometry=this._vectorTileFeature.toGeoJSON(this._vectorTileFeature._x,this._vectorTileFeature._y,this._vectorTileFeature._z).geometry),this._geometry},Zc.geometry.set=function(t){this._geometry=t},Xc.prototype.toJSON=function(){var t={geometry:this.geometry};for(var e in this)\"_geometry\"!==e&&\"_vectorTileFeature\"!==e&&(t[e]=this[e]);return t},Object.defineProperties(Xc.prototype,Zc);var Kc=function(){this.state={},this.stateChanges={},this.deletedStates={}};Kc.prototype.updateState=function(t,e,r){var n=String(e);if(this.stateChanges[t]=this.stateChanges[t]||{},this.stateChanges[t][n]=this.stateChanges[t][n]||{},p(this.stateChanges[t][n],r),null===this.deletedStates[t])for(var i in this.deletedStates[t]={},this.state[t])i!==n&&(this.deletedStates[t][i]=null);else if(this.deletedStates[t]&&null===this.deletedStates[t][n])for(var a in this.deletedStates[t][n]={},this.state[t][n])r[a]||(this.deletedStates[t][n][a]=null);else for(var o in r)this.deletedStates[t]&&this.deletedStates[t][n]&&null===this.deletedStates[t][n][o]&&delete this.deletedStates[t][n][o]},Kc.prototype.removeFeatureState=function(t,e,r){if(null!==this.deletedStates[t]){var n=String(e);if(this.deletedStates[t]=this.deletedStates[t]||{},r&&void 0!==e)null!==this.deletedStates[t][n]&&(this.deletedStates[t][n]=this.deletedStates[t][n]||{},this.deletedStates[t][n][r]=null);else if(void 0!==e)if(this.stateChanges[t]&&this.stateChanges[t][n])for(r in this.deletedStates[t][n]={},this.stateChanges[t][n])this.deletedStates[t][n][r]=null;else this.deletedStates[t][n]=null;else this.deletedStates[t]=null}},Kc.prototype.getState=function(t,e){var r=String(e),n=this.state[t]||{},i=this.stateChanges[t]||{},a=p({},n[r],i[r]);if(null===this.deletedStates[t])return{};if(this.deletedStates[t]){var o=this.deletedStates[t][e];if(null===o)return{};for(var s in o)delete a[s]}return a},Kc.prototype.initializeTileState=function(t,e){t.setFeatureState(this.state,e)},Kc.prototype.coalesceChanges=function(t,e){var r={};for(var n in this.stateChanges){this.state[n]=this.state[n]||{};var i={};for(var a in this.stateChanges[n])this.state[n][a]||(this.state[n][a]={}),p(this.state[n][a],this.stateChanges[n][a]),i[a]=this.state[n][a];r[n]=i}for(var o in this.deletedStates){this.state[o]=this.state[o]||{};var s={};if(null===this.deletedStates[o])for(var l in this.state[o])s[l]={},this.state[o][l]={};else for(var u in this.deletedStates[o]){if(null===this.deletedStates[o][u])this.state[o][u]={};else for(var c=0,f=Object.keys(this.deletedStates[o][u]);c<f.length;c+=1){var h=f[c];delete this.state[o][u][h]}s[u]=this.state[o][u]}r[o]=r[o]||{},p(r[o],s)}if(this.stateChanges={},this.deletedStates={},0!==Object.keys(r).length)for(var d in t)t[d].setFeatureState(r,e)};var Jc=function(t,e){this.tileID=t,this.x=t.canonical.x,this.y=t.canonical.y,this.z=t.canonical.z,this.grid=new ti(po,16,0),this.grid3D=new ti(po,16,0),this.featureIndexArray=new Ia,this.promoteId=e};function $c(t,e,r,n,i){return b(t,(function(t,a){var o=e instanceof Vi?e.get(a):null;return o&&o.evaluate?o.evaluate(r,n,i):o}))}function Qc(t){for(var e=1/0,r=1/0,n=-1/0,i=-1/0,a=0,o=t;a<o.length;a+=1){var s=o[a];e=Math.min(e,s.x),r=Math.min(r,s.y),n=Math.max(n,s.x),i=Math.max(i,s.y)}return{minX:e,minY:r,maxX:n,maxY:i}}function tf(t,e){return e-t}Jc.prototype.insert=function(t,e,r,n,i,a){var o=this.featureIndexArray.length;this.featureIndexArray.emplaceBack(r,n,i);for(var s=a?this.grid3D:this.grid,l=0;l<e.length;l++){for(var u=e[l],c=[1/0,1/0,-1/0,-1/0],f=0;f<u.length;f++){var h=u[f];c[0]=Math.min(c[0],h.x),c[1]=Math.min(c[1],h.y),c[2]=Math.max(c[2],h.x),c[3]=Math.max(c[3],h.y)}c[0]<po&&c[1]<po&&c[2]>=0&&c[3]>=0&&s.insert(o,c[0],c[1],c[2],c[3])}},Jc.prototype.loadVTLayers=function(){return this.vtLayers||(this.vtLayers=new tl.VectorTile(new Ol(this.rawTileData)).layers,this.sourceLayerCoder=new Yc(this.vtLayers?Object.keys(this.vtLayers).sort():[\"_geojsonTileLayer\"])),this.vtLayers},Jc.prototype.query=function(t,e,r,n){var i=this;this.loadVTLayers();for(var o=t.params||{},s=po/t.tileSize/t.scale,l=An(o.filter),u=t.queryGeometry,c=t.queryPadding*s,f=Qc(u),h=this.grid.query(f.minX-c,f.minY-c,f.maxX+c,f.maxY+c),p=Qc(t.cameraQueryGeometry),d=0,v=this.grid3D.query(p.minX-c,p.minY-c,p.maxX+c,p.maxY+c,(function(e,r,n,i){return function(t,e,r,n,i){for(var o=0,s=t;o<s.length;o+=1){var l=s[o];if(e<=l.x&&r<=l.y&&n>=l.x&&i>=l.y)return!0}var u=[new a(e,r),new a(e,i),new a(n,i),new a(n,r)];if(t.length>2)for(var c=0,f=u;c<f.length;c+=1)if(Co(t,f[c]))return!0;for(var h=0;h<t.length-1;h++)if(Po(t[h],t[h+1],u))return!0;return!1}(t.cameraQueryGeometry,e-c,r-c,n+c,i+c)}));d<v.length;d+=1){var g=v[d];h.push(g)}h.sort(tf);for(var y,m={},x=function(a){var c=h[a];if(c!==y){y=c;var f=i.featureIndexArray.get(c),p=null;i.loadMatchingFeature(m,f.bucketIndex,f.sourceLayerIndex,f.featureIndex,l,o.layers,o.availableImages,e,r,n,(function(e,r,n){return p||(p=yo(e)),r.queryIntersectsFeature(u,e,n,p,i.z,t.transform,s,t.pixelPosMatrix)}))}},b=0;b<h.length;b++)x(b);return m},Jc.prototype.loadMatchingFeature=function(t,e,r,n,i,a,o,s,l,u,c){var f=this.bucketLayerIDs[e];if(!a||function(t,e){for(var r=0;r<t.length;r++)if(e.indexOf(t[r])>=0)return!0;return!1}(a,f)){var h=this.sourceLayerCoder.decode(r),d=this.vtLayers[h].feature(n);if(i.needGeometry){var v=mo(d,!0);if(!i.filter(new Di(this.tileID.overscaledZ),v,this.tileID.canonical))return}else if(!i.filter(new Di(this.tileID.overscaledZ),d))return;for(var g=this.getId(d,h),y=0;y<f.length;y++){var m=f[y];if(!(a&&a.indexOf(m)<0)){var x=s[m];if(x){var b={};void 0!==g&&u&&(b=u.getState(x.sourceLayer||\"_geojsonTileLayer\",g));var _=p({},l[m]);_.paint=$c(_.paint,x.paint,d,b,o),_.layout=$c(_.layout,x.layout,d,b,o);var w=!c||c(d,x,b);if(w){var T=new Xc(d,this.z,this.x,this.y,g);T.layer=_;var k=t[m];void 0===k&&(k=t[m]=[]),k.push({featureIndex:n,feature:T,intersectionZ:w})}}}}}},Jc.prototype.lookupSymbolFeatures=function(t,e,r,n,i,a,o,s){var l={};this.loadVTLayers();for(var u=An(i),c=0,f=t;c<f.length;c+=1){var h=f[c];this.loadMatchingFeature(l,r,n,h,u,a,o,s,e)}return l},Jc.prototype.hasLayer=function(t){for(var e=0,r=this.bucketLayerIDs;e<r.length;e+=1)for(var n=0,i=r[e];n<i.length;n+=1)if(t===i[n])return!0;return!1},Jc.prototype.getId=function(t,e){var r=t.id;if(this.promoteId){var n=\"string\"==typeof this.promoteId?this.promoteId:this.promoteId[e];\"boolean\"==typeof(r=t.properties[n])&&(r=Number(r))}return r},oi(\"FeatureIndex\",Jc,{omit:[\"rawTileData\",\"sourceLayerCoder\"]});var ef=function(t,e){this.tileID=t,this.uid=v(),this.uses=0,this.tileSize=e,this.buckets={},this.expirationTime=null,this.queryPadding=0,this.hasSymbolBuckets=!1,this.hasRTLText=!1,this.dependencies={},this.expiredRequestCount=0,this.state=\"loading\"};ef.prototype.registerFadeDuration=function(t){var e=t+this.timeAdded;e<N.now()||this.fadeEndTime&&e<this.fadeEndTime||(this.fadeEndTime=e)},ef.prototype.wasRequested=function(){return\"errored\"===this.state||\"loaded\"===this.state||\"reloading\"===this.state},ef.prototype.loadVectorData=function(t,e,r){if(this.hasData()&&this.unloadVectorData(),this.state=\"loaded\",t){for(var n in t.featureIndex&&(this.latestFeatureIndex=t.featureIndex,t.rawTileData?(this.latestRawTileData=t.rawTileData,this.latestFeatureIndex.rawTileData=t.rawTileData):this.latestRawTileData&&(this.latestFeatureIndex.rawTileData=this.latestRawTileData)),this.collisionBoxArray=t.collisionBoxArray,this.buckets=function(t,e){var r={};if(!e)return r;for(var n=function(){var t=a[i],n=t.layerIds.map((function(t){return e.getLayer(t)})).filter(Boolean);if(0!==n.length){t.layers=n,t.stateDependentLayerIds&&(t.stateDependentLayers=t.stateDependentLayerIds.map((function(t){return n.filter((function(e){return e.id===t}))[0]})));for(var o=0,s=n;o<s.length;o+=1){var l=s[o];r[l.id]=t}}},i=0,a=t;i<a.length;i+=1)n();return r}(t.buckets,e.style),this.hasSymbolBuckets=!1,this.buckets){var i=this.buckets[n];if(i instanceof hc){if(this.hasSymbolBuckets=!0,!r)break;i.justReloaded=!0}}if(this.hasRTLText=!1,this.hasSymbolBuckets)for(var a in this.buckets){var o=this.buckets[a];if(o instanceof hc&&o.hasRTLText){this.hasRTLText=!0,Ii.isLoading()||Ii.isLoaded()||\"deferred\"!==Pi()||Oi();break}}for(var s in this.queryPadding=0,this.buckets){var l=this.buckets[s];this.queryPadding=Math.max(this.queryPadding,e.style.getLayer(s).queryRadius(l))}t.imageAtlas&&(this.imageAtlas=t.imageAtlas),t.glyphAtlasImage&&(this.glyphAtlasImage=t.glyphAtlasImage)}else this.collisionBoxArray=new Aa},ef.prototype.unloadVectorData=function(){for(var t in this.buckets)this.buckets[t].destroy();this.buckets={},this.imageAtlasTexture&&this.imageAtlasTexture.destroy(),this.imageAtlas&&(this.imageAtlas=null),this.glyphAtlasTexture&&this.glyphAtlasTexture.destroy(),this.latestFeatureIndex=null,this.state=\"unloaded\"},ef.prototype.getBucket=function(t){return this.buckets[t.id]},ef.prototype.upload=function(t){for(var e in this.buckets){var r=this.buckets[e];r.uploadPending()&&r.upload(t)}var n=t.gl;this.imageAtlas&&!this.imageAtlas.uploaded&&(this.imageAtlasTexture=new Ec(t,this.imageAtlas.image,n.RGBA),this.imageAtlas.uploaded=!0),this.glyphAtlasImage&&(this.glyphAtlasTexture=new Ec(t,this.glyphAtlasImage,n.ALPHA),this.glyphAtlasImage=null)},ef.prototype.prepare=function(t){this.imageAtlas&&this.imageAtlas.patchUpdatedImages(t,this.imageAtlasTexture)},ef.prototype.queryRenderedFeatures=function(t,e,r,n,i,a,o,s,l,u){return this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData?this.latestFeatureIndex.query({queryGeometry:n,cameraQueryGeometry:i,scale:a,tileSize:this.tileSize,pixelPosMatrix:u,transform:s,params:o,queryPadding:this.queryPadding*l},t,e,r):{}},ef.prototype.querySourceFeatures=function(t,e){var r=this.latestFeatureIndex;if(r&&r.rawTileData){var n=r.loadVTLayers(),i=e?e.sourceLayer:\"\",a=n._geojsonTileLayer||n[i];if(a)for(var o=An(e&&e.filter),s=this.tileID.canonical,l=s.z,u=s.x,c=s.y,f={z:l,x:u,y:c},h=0;h<a.length;h++){var p=a.feature(h);if(o.needGeometry){var d=mo(p,!0);if(!o.filter(new Di(this.tileID.overscaledZ),d,this.tileID.canonical))continue}else if(!o.filter(new Di(this.tileID.overscaledZ),p))continue;var v=r.getId(p,i),g=new Xc(p,l,u,c,v);g.tile=f,t.push(g)}}},ef.prototype.hasData=function(){return\"loaded\"===this.state||\"reloading\"===this.state||\"expired\"===this.state},ef.prototype.patternsLoaded=function(){return this.imageAtlas&&!!Object.keys(this.imageAtlas.patternPositions).length},ef.prototype.setExpiryData=function(t){var e=this.expirationTime;if(t.cacheControl){var r=E(t.cacheControl);r[\"max-age\"]&&(this.expirationTime=Date.now()+1e3*r[\"max-age\"])}else t.expires&&(this.expirationTime=new Date(t.expires).getTime());if(this.expirationTime){var n=Date.now(),i=!1;if(this.expirationTime>n)i=!1;else if(e)if(this.expirationTime<e)i=!0;else{var a=this.expirationTime-e;a?this.expirationTime=n+Math.max(a,3e4):i=!0}else i=!0;i?(this.expiredRequestCount++,this.state=\"expired\"):this.expiredRequestCount=0}},ef.prototype.getExpiryTimeout=function(){if(this.expirationTime)return this.expiredRequestCount?1e3*(1<<Math.min(this.expiredRequestCount-1,31)):Math.min(this.expirationTime-(new Date).getTime(),Math.pow(2,31)-1)},ef.prototype.setFeatureState=function(t,e){if(this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData&&0!==Object.keys(t).length){var r=this.latestFeatureIndex.loadVTLayers();for(var n in this.buckets)if(e.style.hasLayer(n)){var i=this.buckets[n],a=i.layers[0].sourceLayer||\"_geojsonTileLayer\",o=r[a],s=t[a];if(o&&s&&0!==Object.keys(s).length){i.update(s,o,this.imageAtlas&&this.imageAtlas.patternPositions||{});var l=e&&e.style&&e.style.getLayer(n);l&&(this.queryPadding=Math.max(this.queryPadding,l.queryRadius(i)))}}}},ef.prototype.holdingForFade=function(){return void 0!==this.symbolFadeHoldUntil},ef.prototype.symbolFadeFinished=function(){return!this.symbolFadeHoldUntil||this.symbolFadeHoldUntil<N.now()},ef.prototype.clearFadeHold=function(){this.symbolFadeHoldUntil=void 0},ef.prototype.setHoldDuration=function(t){this.symbolFadeHoldUntil=N.now()+t},ef.prototype.setDependencies=function(t,e){for(var r={},n=0,i=e;n<i.length;n+=1)r[i[n]]=!0;this.dependencies[t]=r},ef.prototype.hasDependency=function(t,e){for(var r=0,n=t;r<n.length;r+=1){var i=n[r],a=this.dependencies[i];if(a)for(var o=0,s=e;o<s.length;o+=1)if(a[s[o]])return!0}return!1};var rf=s.performance,nf=function(t){this._marks={start:[t.url,\"start\"].join(\"#\"),end:[t.url,\"end\"].join(\"#\"),measure:t.url.toString()},rf.mark(this._marks.start)};nf.prototype.finish=function(){rf.mark(this._marks.end);var t=rf.getEntriesByName(this._marks.measure);return 0===t.length&&(rf.measure(this._marks.measure,this._marks.start,this._marks.end),t=rf.getEntriesByName(this._marks.measure),rf.clearMarks(this._marks.start),rf.clearMarks(this._marks.end),rf.clearMeasures(this._marks.measure)),t},t.Actor=Cc,t.AlphaImage=Jo,t.CanonicalTileID=Vc,t.CollisionBoxArray=Aa,t.Color=ue,t.DEMData=Wc,t.DataConstantProperty=qi,t.DictionaryCoder=Yc,t.EXTENT=po,t.ErrorEvent=zt,t.EvaluationParameters=Di,t.Event=Dt,t.Evented=Rt,t.FeatureIndex=Jc,t.FillBucket=Us,t.FillExtrusionBucket=il,t.ImageAtlas=su,t.ImagePosition=au,t.LineBucket=vl,t.LngLat=Dc,t.LngLatBounds=Oc,t.MercatorCoordinate=Uc,t.ONE_EM=Ll,t.OverscaledTileID=Hc,t.Point=a,t.Point$1=a,t.Properties=Xi,t.Protobuf=Ol,t.RGBAImage=$o,t.RequestManager=W,t.RequestPerformance=nf,t.ResourceType=_t,t.SegmentVector=za,t.SourceFeatureState=Kc,t.StructArrayLayout1ui2=wa,t.StructArrayLayout2f1f2i16=pa,t.StructArrayLayout2i4=ra,t.StructArrayLayout3ui6=va,t.StructArrayLayout4i8=na,t.SymbolBucket=hc,t.Texture=Ec,t.Tile=ef,t.Transitionable=Fi,t.Uniform1f=Ka,t.Uniform1i=Za,t.Uniform2f=Ja,t.Uniform3f=$a,t.Uniform4f=Qa,t.UniformColor=to,t.UniformMatrix4f=ro,t.UnwrappedTileID=qc,t.ValidationError=Bt,t.WritingMode=lu,t.ZoomHistory=hi,t.add=function(t,e,r){return t[0]=e[0]+r[0],t[1]=e[1]+r[1],t[2]=e[2]+r[2],t},t.addDynamicAttributes=lc,t.asyncAll=function(t,e,r){if(!t.length)return r(null,[]);var n=t.length,i=new Array(t.length),a=null;t.forEach((function(t,o){e(t,(function(t,e){t&&(a=t),i[o]=e,0==--n&&r(a,i)}))}))},t.bezier=u,t.bindAll=m,t.browser=N,t.cacheEntryPossiblyAdded=function(t){++xt>ht&&(t.getActor().send(\"enforceCacheSizeLimit\",ft),xt=0)},t.clamp=f,t.clearTileCache=function(t){var e=s.caches.delete(ct);t&&e.catch(t).then((function(){return t()}))},t.clipLine=Fu,t.clone=function(t){var e=new Fo(16);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],e[4]=t[4],e[5]=t[5],e[6]=t[6],e[7]=t[7],e[8]=t[8],e[9]=t[9],e[10]=t[10],e[11]=t[11],e[12]=t[12],e[13]=t[13],e[14]=t[14],e[15]=t[15],e},t.clone$1=w,t.clone$2=function(t){var e=new Fo(3);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e},t.collisionCircleLayout=Ml,t.config=j,t.create=function(){var t=new Fo(16);return 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generateId cannot be used together.\");var n=function(t,e){var r=[];if(\"FeatureCollection\"===t.type)for(var n=0;n<t.features.length;n++)rt(r,t.features[n],e,n);else\"Feature\"===t.type?rt(r,t,e):rt(r,{geometry:t},e);return r}(t,e);this.tiles={},this.tileCoords=[],r&&(console.timeEnd(\"preprocess data\"),console.log(\"index: maxZoom: %d, maxPoints: %d\",e.indexMaxZoom,e.indexMaxPoints),console.time(\"generate tiles\"),this.stats={},this.total=0),(n=function(t,e){var r=e.buffer/e.extent,n=t,i=lt(t,1,-1-r,r,0,-1,2,e),a=lt(t,1,1-r,2+r,0,-1,2,e);return(i||a)&&(n=lt(t,1,-r,1+r,0,-1,2,e)||[],i&&(n=gt(i,1).concat(n)),a&&(n=n.concat(gt(a,-1)))),n}(n,e)).length&&this.splitTile(n,0,0,0),r&&(n.length&&console.log(\"features: %d, points: %d\",this.tiles[0].numFeatures,this.tiles[0].numPoints),console.timeEnd(\"generate tiles\"),console.log(\"tiles generated:\",this.total,JSON.stringify(this.stats)))}function kt(t,e,r){return 32*((1<<t)*r+e)+t}function At(t,e){var r=t.tileID.canonical;if(!this._geoJSONIndex)return e(null,null);var n=this._geoJSONIndex.getTile(r.z,r.x,r.y);if(!n)return e(null,null);var i=new g(n.features),a=_(i);0===a.byteOffset&&a.byteLength===a.buffer.byteLength||(a=new Uint8Array(a)),e(null,{vectorTile:i,rawData:a.buffer})}V.prototype.load=function(t){var e=this.options,r=e.log,n=e.minZoom,i=e.maxZoom,a=e.nodeSize;r&&console.time(\"total time\");var o=\"prepare \"+t.length+\" points\";r&&console.time(o),this.points=t;for(var s=[],l=0;l<t.length;l++)t[l].geometry&&s.push(H(t[l],l));this.trees[i+1]=new j(s,K,J,a,Float32Array),r&&console.timeEnd(o);for(var u=i;u>=n;u--){var c=+Date.now();s=this._cluster(s,u),this.trees[u]=new j(s,K,J,a,Float32Array),r&&console.log(\"z%d: %d clusters in %dms\",u,s.length,+Date.now()-c)}return r&&console.timeEnd(\"total time\"),this},V.prototype.getClusters=function(t,e){var r=((t[0]+180)%360+360)%360-180,n=Math.max(-90,Math.min(90,t[1])),i=180===t[2]?180:((t[2]+180)%360+360)%360-180,a=Math.max(-90,Math.min(90,t[3]));if(t[2]-t[0]>=360)r=-180,i=180;else if(r>i){var o=this.getClusters([r,n,180,a],e),s=this.getClusters([-180,n,i,a],e);return o.concat(s)}for(var l=this.trees[this._limitZoom(e)],u=[],c=0,f=l.range(Y(r),X(a),Y(i),X(n));c<f.length;c+=1){var h=f[c],p=l.points[h];u.push(p.numPoints?G(p):this.points[p.index])}return u},V.prototype.getChildren=function(t){var e=this._getOriginId(t),r=this._getOriginZoom(t),n=\"No cluster with the specified id.\",i=this.trees[r];if(!i)throw new Error(n);var a=i.points[e];if(!a)throw new Error(n);for(var o=this.options.radius/(this.options.extent*Math.pow(2,r-1)),s=[],l=0,u=i.within(a.x,a.y,o);l<u.length;l+=1){var c=u[l],f=i.points[c];f.parentId===t&&s.push(f.numPoints?G(f):this.points[f.index])}if(0===s.length)throw new Error(n);return s},V.prototype.getLeaves=function(t,e,r){e=e||10,r=r||0;var n=[];return this._appendLeaves(n,t,e,r,0),n},V.prototype.getTile=function(t,e,r){var n=this.trees[this._limitZoom(t)],i=Math.pow(2,t),a=this.options,o=a.extent,s=a.radius/o,l=(r-s)/i,u=(r+1+s)/i,c={features:[]};return this._addTileFeatures(n.range((e-s)/i,l,(e+1+s)/i,u),n.points,e,r,i,c),0===e&&this._addTileFeatures(n.range(1-s/i,l,1,u),n.points,i,r,i,c),e===i-1&&this._addTileFeatures(n.range(0,l,s/i,u),n.points,-1,r,i,c),c.features.length?c:null},V.prototype.getClusterExpansionZoom=function(t){for(var e=this._getOriginZoom(t)-1;e<=this.options.maxZoom;){var r=this.getChildren(t);if(e++,1!==r.length)break;t=r[0].properties.cluster_id}return e},V.prototype._appendLeaves=function(t,e,r,n,i){for(var a=0,o=this.getChildren(e);a<o.length;a+=1){var s=o[a],l=s.properties;if(l&&l.cluster?i+l.point_count<=n?i+=l.point_count:i=this._appendLeaves(t,l.cluster_id,r,n,i):i<n?i++:t.push(s),t.length===r)break}return i},V.prototype._addTileFeatures=function(t,e,r,n,i,a){for(var o=0,s=t;o<s.length;o+=1){var l=e[s[o]],u=l.numPoints,c={type:1,geometry:[[Math.round(this.options.extent*(l.x*i-r)),Math.round(this.options.extent*(l.y*i-n))]],tags:u?W(l):this.points[l.index].properties},f=void 0;u?f=l.id:this.options.generateId?f=l.index:this.points[l.index].id&&(f=this.points[l.index].id),void 0!==f&&(c.id=f),a.features.push(c)}},V.prototype._limitZoom=function(t){return Math.max(this.options.minZoom,Math.min(+t,this.options.maxZoom+1))},V.prototype._cluster=function(t,e){for(var r=[],n=this.options,i=n.radius,a=n.extent,o=n.reduce,s=n.minPoints,l=i/(a*Math.pow(2,e)),u=0;u<t.length;u++){var c=t[u];if(!(c.zoom<=e)){c.zoom=e;for(var f=this.trees[e+1],h=f.within(c.x,c.y,l),p=c.numPoints||1,d=p,v=0,g=h;v<g.length;v+=1){var y=g[v],m=f.points[y];m.zoom>e&&(d+=m.numPoints||1)}if(d>=s){for(var x=c.x*p,b=c.y*p,_=o&&p>1?this._map(c,!0):null,w=(u<<5)+(e+1)+this.points.length,T=0,k=h;T<k.length;T+=1){var A=k[T],M=f.points[A];if(!(M.zoom<=e)){M.zoom=e;var S=M.numPoints||1;x+=M.x*S,b+=M.y*S,M.parentId=w,o&&(_||(_=this._map(c,!0)),o(_,this._map(M)))}}c.parentId=w,r.push(q(x/d,b/d,w,d,_))}else if(r.push(c),d>1)for(var E=0,L=h;E<L.length;E+=1){var C=L[E],P=f.points[C];P.zoom<=e||(P.zoom=e,r.push(P))}}}return r},V.prototype._getOriginId=function(t){return t-this.points.length>>5},V.prototype._getOriginZoom=function(t){return(t-this.points.length)%32},V.prototype._map=function(t,e){if(t.numPoints)return e?Z({},t.properties):t.properties;var r=this.points[t.index].properties,n=this.options.map(r);return e&&n===r?Z({},n):n},Tt.prototype.options={maxZoom:14,indexMaxZoom:5,indexMaxPoints:1e5,tolerance:3,extent:4096,buffer:64,lineMetrics:!1,promoteId:null,generateId:!1,debug:0},Tt.prototype.splitTile=function(t,e,r,n,i,a,o){for(var s=[t,e,r,n],l=this.options,u=l.debug;s.length;){n=s.pop(),r=s.pop(),e=s.pop(),t=s.pop();var c=1<<e,f=kt(e,r,n),h=this.tiles[f];if(!h&&(u>1&&console.time(\"creation\"),h=this.tiles[f]=bt(t,e,r,n,l),this.tileCoords.push({z:e,x:r,y:n}),u)){u>1&&(console.log(\"tile z%d-%d-%d (features: %d, points: %d, simplified: %d)\",e,r,n,h.numFeatures,h.numPoints,h.numSimplified),console.timeEnd(\"creation\"));var p=\"z\"+e;this.stats[p]=(this.stats[p]||0)+1,this.total++}if(h.source=t,i){if(e===l.maxZoom||e===i)continue;var d=1<<i-e;if(r!==Math.floor(a/d)||n!==Math.floor(o/d))continue}else if(e===l.indexMaxZoom||h.numPoints<=l.indexMaxPoints)continue;if(h.source=null,0!==t.length){u>1&&console.time(\"clipping\");var v,g,y,m,x,b,_=.5*l.buffer/l.extent,w=.5-_,T=.5+_,k=1+_;v=g=y=m=null,x=lt(t,c,r-_,r+T,0,h.minX,h.maxX,l),b=lt(t,c,r+w,r+k,0,h.minX,h.maxX,l),t=null,x&&(v=lt(x,c,n-_,n+T,1,h.minY,h.maxY,l),g=lt(x,c,n+w,n+k,1,h.minY,h.maxY,l),x=null),b&&(y=lt(b,c,n-_,n+T,1,h.minY,h.maxY,l),m=lt(b,c,n+w,n+k,1,h.minY,h.maxY,l),b=null),u>1&&console.timeEnd(\"clipping\"),s.push(v||[],e+1,2*r,2*n),s.push(g||[],e+1,2*r,2*n+1),s.push(y||[],e+1,2*r+1,2*n),s.push(m||[],e+1,2*r+1,2*n+1)}}},Tt.prototype.getTile=function(t,e,r){var n=this.options,i=n.extent,a=n.debug;if(t<0||t>24)return null;var o=1<<t,s=kt(t,e=(e%o+o)%o,r);if(this.tiles[s])return mt(this.tiles[s],i);a>1&&console.log(\"drilling down to z%d-%d-%d\",t,e,r);for(var l,u=t,c=e,f=r;!l&&u>0;)u--,c=Math.floor(c/2),f=Math.floor(f/2),l=this.tiles[kt(u,c,f)];return l&&l.source?(a>1&&console.log(\"found parent tile z%d-%d-%d\",u,c,f),a>1&&console.time(\"drilling down\"),this.splitTile(l.source,u,c,f,t,e,r),a>1&&console.timeEnd(\"drilling 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i=n[r];o.accumulated=t[i],t[i]=a[i].evaluate(o,s)}},r}(n)).load(o.features):function(t,e){return new Tt(t,e)}(o,n.geojsonVtOptions)}catch(a){return r(a)}e.loaded={};var u={};if(i){var c=i.finish();c&&(u.resourceTiming={},u.resourceTiming[n.source]=JSON.parse(JSON.stringify(c)))}r(null,u)}))}},r.prototype.coalesce=function(){\"Coalescing\"===this._state?this._state=\"Idle\":\"NeedsLoadData\"===this._state&&(this._state=\"Coalescing\",this._loadData())},r.prototype.reloadTile=function(t,r){var n=this.loaded,i=t.uid;return n&&n[i]?e.prototype.reloadTile.call(this,t,r):this.loadTile(t,r)},r.prototype.loadGeoJSON=function(e,r){if(e.request)t.getJSON(e.request,r);else{if(\"string\"!=typeof e.data)return r(new Error(\"Input data given to '\"+e.source+\"' is not a valid GeoJSON object.\"));try{return r(null,JSON.parse(e.data))}catch(t){return r(new Error(\"Input data given to '\"+e.source+\"' is not a valid GeoJSON object.\"))}}},r.prototype.removeSource=function(t,e){this._pendingCallback&&this._pendingCallback(null,{abandoned:!0}),e()},r.prototype.getClusterExpansionZoom=function(t,e){try{e(null,this._geoJSONIndex.getClusterExpansionZoom(t.clusterId))}catch(t){e(t)}},r.prototype.getClusterChildren=function(t,e){try{e(null,this._geoJSONIndex.getChildren(t.clusterId))}catch(t){e(t)}},r.prototype.getClusterLeaves=function(t,e){try{e(null,this._geoJSONIndex.getLeaves(t.clusterId,t.limit,t.offset))}catch(t){e(t)}},r}(l);var St=function(e){var r=this;this.self=e,this.actor=new t.Actor(e,this),this.layerIndexes={},this.availableImages={},this.workerSourceTypes={vector:l,geojson:Mt},this.workerSources={},this.demWorkerSources={},this.self.registerWorkerSource=function(t,e){if(r.workerSourceTypes[t])throw new Error('Worker source with name \"'+t+'\" already registered.');r.workerSourceTypes[t]=e},this.self.registerRTLTextPlugin=function(e){if(t.plugin.isParsed())throw new Error(\"RTL text plugin already 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s=i([\"transform\",\"WebkitTransform\"]);r.setTransform=function(t,e){t.style[s]=e};var l=!1;try{var u=Object.defineProperty({},\"passive\",{get:function(){l=!0}});t.window.addEventListener(\"test\",u,u),t.window.removeEventListener(\"test\",u,u)}catch(t){l=!1}r.addEventListener=function(t,e,r,n){void 0===n&&(n={}),\"passive\"in n&&l?t.addEventListener(e,r,n):t.addEventListener(e,r,n.capture)},r.removeEventListener=function(t,e,r,n){void 0===n&&(n={}),\"passive\"in n&&l?t.removeEventListener(e,r,n):t.removeEventListener(e,r,n.capture)};var c=function(e){e.preventDefault(),e.stopPropagation(),t.window.removeEventListener(\"click\",c,!0)};function f(t){var e=t.userImage;return!!(e&&e.render&&e.render())&&(t.data.replace(new Uint8Array(e.data.buffer)),!0)}r.suppressClick=function(){t.window.addEventListener(\"click\",c,!0),t.window.setTimeout((function(){t.window.removeEventListener(\"click\",c,!0)}),0)},r.mousePos=function(e,r){var n=e.getBoundingClientRect();return new t.Point(r.clientX-n.left-e.clientLeft,r.clientY-n.top-e.clientTop)},r.touchPos=function(e,r){for(var n=e.getBoundingClientRect(),i=[],a=0;a<r.length;a++)i.push(new t.Point(r[a].clientX-n.left-e.clientLeft,r[a].clientY-n.top-e.clientTop));return i},r.mouseButton=function(e){return void 0!==t.window.InstallTrigger&&2===e.button&&e.ctrlKey&&t.window.navigator.platform.toUpperCase().indexOf(\"MAC\")>=0?0:e.button},r.remove=function(t){t.parentNode&&t.parentNode.removeChild(t)};var h=function(e){function r(){e.call(this),this.images={},this.updatedImages={},this.callbackDispatchedThisFrame={},this.loaded=!1,this.requestors=[],this.patterns={},this.atlasImage=new t.RGBAImage({width:1,height:1}),this.dirty=!0}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.isLoaded=function(){return this.loaded},r.prototype.setLoaded=function(t){if(this.loaded!==t&&(this.loaded=t,t)){for(var e=0,r=this.requestors;e<r.length;e+=1){var n=r[e],i=n.ids,a=n.callback;this._notify(i,a)}this.requestors=[]}},r.prototype.getImage=function(t){return this.images[t]},r.prototype.addImage=function(t,e){this._validate(t,e)&&(this.images[t]=e)},r.prototype._validate=function(e,r){var n=!0;return this._validateStretch(r.stretchX,r.data&&r.data.width)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"stretchX\" value'))),n=!1),this._validateStretch(r.stretchY,r.data&&r.data.height)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"stretchY\" value'))),n=!1),this._validateContent(r.content,r)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"content\" value'))),n=!1),n},r.prototype._validateStretch=function(t,e){if(!t)return!0;for(var r=0,n=0,i=t;n<i.length;n+=1){var a=i[n];if(a[0]<r||a[1]<a[0]||e<a[1])return!1;r=a[1]}return!0},r.prototype._validateContent=function(t,e){return!(t&&(4!==t.length||t[0]<0||e.data.width<t[0]||t[1]<0||e.data.height<t[1]||t[2]<0||e.data.width<t[2]||t[3]<0||e.data.height<t[3]||t[2]<t[0]||t[3]<t[1]))},r.prototype.updateImage=function(t,e){var r=this.images[t];e.version=r.version+1,this.images[t]=e,this.updatedImages[t]=!0},r.prototype.removeImage=function(t){var e=this.images[t];delete this.images[t],delete this.patterns[t],e.userImage&&e.userImage.onRemove&&e.userImage.onRemove()},r.prototype.listImages=function(){return Object.keys(this.images)},r.prototype.getImages=function(t,e){var r=!0;if(!this.isLoaded())for(var n=0,i=t;n<i.length;n+=1){var a=i[n];this.images[a]||(r=!1)}this.isLoaded()||r?this._notify(t,e):this.requestors.push({ids:t,callback:e})},r.prototype._notify=function(e,r){for(var n={},i=0,a=e;i<a.length;i+=1){var o=a[i];this.images[o]||this.fire(new t.Event(\"styleimagemissing\",{id:o}));var s=this.images[o];s?n[o]={data:s.data.clone(),pixelRatio:s.pixelRatio,sdf:s.sdf,version:s.version,stretchX:s.stretchX,stretchY:s.stretchY,content:s.content,hasRenderCallback:Boolean(s.userImage&&s.userImage.render)}:t.warnOnce('Image \"'+o+'\" could not be loaded. Please make sure you have added the image with map.addImage() or a \"sprite\" property in your style. You can provide missing images by listening for the \"styleimagemissing\" map event.')}r(null,n)},r.prototype.getPixelSize=function(){var t=this.atlasImage;return{width:t.width,height:t.height}},r.prototype.getPattern=function(e){var r=this.patterns[e],n=this.getImage(e);if(!n)return null;if(r&&r.position.version===n.version)return r.position;if(r)r.position.version=n.version;else{var i={w:n.data.width+2,h:n.data.height+2,x:0,y:0},a=new t.ImagePosition(i,n);this.patterns[e]={bin:i,position:a}}return this._updatePatternAtlas(),this.patterns[e].position},r.prototype.bind=function(e){var r=e.gl;this.atlasTexture?this.dirty&&(this.atlasTexture.update(this.atlasImage),this.dirty=!1):this.atlasTexture=new t.Texture(e,this.atlasImage,r.RGBA),this.atlasTexture.bind(r.LINEAR,r.CLAMP_TO_EDGE)},r.prototype._updatePatternAtlas=function(){var e=[];for(var r in this.patterns)e.push(this.patterns[r].bin);var n=t.potpack(e),i=n.w,a=n.h,o=this.atlasImage;for(var s in o.resize({width:i||1,height:a||1}),this.patterns){var l=this.patterns[s].bin,u=l.x+1,c=l.y+1,f=this.images[s].data,h=f.width,p=f.height;t.RGBAImage.copy(f,o,{x:0,y:0},{x:u,y:c},{width:h,height:p}),t.RGBAImage.copy(f,o,{x:0,y:p-1},{x:u,y:c-1},{width:h,height:1}),t.RGBAImage.copy(f,o,{x:0,y:0},{x:u,y:c+p},{width:h,height:1}),t.RGBAImage.copy(f,o,{x:h-1,y:0},{x:u-1,y:c},{width:1,height:p}),t.RGBAImage.copy(f,o,{x:0,y:0},{x:u+h,y:c},{width:1,height:p})}this.dirty=!0},r.prototype.beginFrame=function(){this.callbackDispatchedThisFrame={}},r.prototype.dispatchRenderCallbacks=function(t){for(var e=0,r=t;e<r.length;e+=1){var n=r[e];if(!this.callbackDispatchedThisFrame[n]){this.callbackDispatchedThisFrame[n]=!0;var i=this.images[n];f(i)&&this.updateImage(n,i)}}},r}(t.Evented);var p=g,d=g,v=1e20;function g(t,e,r,n,i,a){this.fontSize=t||24,this.buffer=void 0===e?3:e,this.cutoff=n||.25,this.fontFamily=i||\"sans-serif\",this.fontWeight=a||\"normal\",this.radius=r||8;var o=this.size=this.fontSize+2*this.buffer;this.canvas=document.createElement(\"canvas\"),this.canvas.width=this.canvas.height=o,this.ctx=this.canvas.getContext(\"2d\"),this.ctx.font=this.fontWeight+\" \"+this.fontSize+\"px \"+this.fontFamily,this.ctx.textBaseline=\"middle\",this.ctx.fillStyle=\"black\",this.gridOuter=new Float64Array(o*o),this.gridInner=new Float64Array(o*o),this.f=new Float64Array(o),this.d=new Float64Array(o),this.z=new Float64Array(o+1),this.v=new Int16Array(o),this.middle=Math.round(o/2*(navigator.userAgent.indexOf(\"Gecko/\")>=0?1.2:1))}function y(t,e,r,n,i,a,o){for(var s=0;s<e;s++){for(var l=0;l<r;l++)n[l]=t[l*e+s];for(m(n,i,a,o,r),l=0;l<r;l++)t[l*e+s]=i[l]}for(l=0;l<r;l++){for(s=0;s<e;s++)n[s]=t[l*e+s];for(m(n,i,a,o,e),s=0;s<e;s++)t[l*e+s]=Math.sqrt(i[s])}}function m(t,e,r,n,i){r[0]=0,n[0]=-v,n[1]=+v;for(var a=1,o=0;a<i;a++){for(var s=(t[a]+a*a-(t[r[o]]+r[o]*r[o]))/(2*a-2*r[o]);s<=n[o];)o--,s=(t[a]+a*a-(t[r[o]]+r[o]*r[o]))/(2*a-2*r[o]);r[++o]=a,n[o]=s,n[o+1]=+v}for(a=0,o=0;a<i;a++){for(;n[o+1]<a;)o++;e[a]=(a-r[o])*(a-r[o])+t[r[o]]}}g.prototype.draw=function(t){this.ctx.clearRect(0,0,this.size,this.size),this.ctx.fillText(t,this.buffer,this.middle);for(var e=this.ctx.getImageData(0,0,this.size,this.size),r=new Uint8ClampedArray(this.size*this.size),n=0;n<this.size*this.size;n++){var i=e.data[4*n+3]/255;this.gridOuter[n]=1===i?0:0===i?v:Math.pow(Math.max(0,.5-i),2),this.gridInner[n]=1===i?v:0===i?0:Math.pow(Math.max(0,i-.5),2)}for(y(this.gridOuter,this.size,this.size,this.f,this.d,this.v,this.z),y(this.gridInner,this.size,this.size,this.f,this.d,this.v,this.z),n=0;n<this.size*this.size;n++){var a=this.gridOuter[n]-this.gridInner[n];r[n]=Math.max(0,Math.min(255,Math.round(255-255*(a/this.radius+this.cutoff))))}return r},p.default=d;var x=function(t,e){this.requestManager=t,this.localIdeographFontFamily=e,this.entries={}};x.prototype.setURL=function(t){this.url=t},x.prototype.getGlyphs=function(e,r){var n=this,i=[];for(var a in e)for(var o=0,s=e[a];o<s.length;o+=1){var l=s[o];i.push({stack:a,id:l})}t.asyncAll(i,(function(t,e){var r=t.stack,i=t.id,a=n.entries[r];a||(a=n.entries[r]={glyphs:{},requests:{},ranges:{}});var o=a.glyphs[i];if(void 0===o){if(o=n._tinySDF(a,r,i))return a.glyphs[i]=o,void e(null,{stack:r,id:i,glyph:o});var s=Math.floor(i/256);if(256*s>65535)e(new Error(\"glyphs > 65535 not supported\"));else if(a.ranges[s])e(null,{stack:r,id:i,glyph:o});else{var l=a.requests[s];l||(l=a.requests[s]=[],x.loadGlyphRange(r,s,n.url,n.requestManager,(function(t,e){if(e){for(var r in e)n._doesCharSupportLocalGlyph(+r)||(a.glyphs[+r]=e[+r]);a.ranges[s]=!0}for(var i=0,o=l;i<o.length;i+=1)(0,o[i])(t,e);delete a.requests[s]}))),l.push((function(t,n){t?e(t):n&&e(null,{stack:r,id:i,glyph:n[i]||null})}))}}else e(null,{stack:r,id:i,glyph:o})}),(function(t,e){if(t)r(t);else if(e){for(var n={},i=0,a=e;i<a.length;i+=1){var o=a[i],s=o.stack,l=o.id,u=o.glyph;(n[s]||(n[s]={}))[l]=u&&{id:u.id,bitmap:u.bitmap.clone(),metrics:u.metrics}}r(null,n)}}))},x.prototype._doesCharSupportLocalGlyph=function(e){return!!this.localIdeographFontFamily&&(t.isChar[\"CJK Unified Ideographs\"](e)||t.isChar[\"Hangul Syllables\"](e)||t.isChar.Hiragana(e)||t.isChar.Katakana(e))},x.prototype._tinySDF=function(e,r,n){var i=this.localIdeographFontFamily;if(i&&this._doesCharSupportLocalGlyph(n)){var a=e.tinySDF;if(!a){var o=\"400\";/bold/i.test(r)?o=\"900\":/medium/i.test(r)?o=\"500\":/light/i.test(r)&&(o=\"200\"),a=e.tinySDF=new x.TinySDF(24,3,8,.25,i,o)}return{id:n,bitmap:new t.AlphaImage({width:30,height:30},a.draw(String.fromCharCode(n))),metrics:{width:24,height:24,left:0,top:-8,advance:24}}}},x.loadGlyphRange=function(e,r,n,i,a){var o=256*r,s=o+255,l=i.transformRequest(i.normalizeGlyphsURL(n).replace(\"{fontstack}\",e).replace(\"{range}\",o+\"-\"+s),t.ResourceType.Glyphs);t.getArrayBuffer(l,(function(e,r){if(e)a(e);else if(r){for(var n={},i=0,o=t.parseGlyphPBF(r);i<o.length;i+=1){var s=o[i];n[s.id]=s}a(null,n)}}))},x.TinySDF=p;var b=function(){this.specification=t.styleSpec.light.position};b.prototype.possiblyEvaluate=function(e,r){return t.sphericalToCartesian(e.expression.evaluate(r))},b.prototype.interpolate=function(e,r,n){return{x:t.number(e.x,r.x,n),y:t.number(e.y,r.y,n),z:t.number(e.z,r.z,n)}};var _=new t.Properties({anchor:new t.DataConstantProperty(t.styleSpec.light.anchor),position:new b,color:new t.DataConstantProperty(t.styleSpec.light.color),intensity:new t.DataConstantProperty(t.styleSpec.light.intensity)}),w=\"-transition\",T=function(e){function r(r){e.call(this),this._transitionable=new t.Transitionable(_),this.setLight(r),this._transitioning=this._transitionable.untransitioned()}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.getLight=function(){return this._transitionable.serialize()},r.prototype.setLight=function(e,r){if(void 0===r&&(r={}),!this._validate(t.validateLight,e,r))for(var n in e){var i=e[n];t.endsWith(n,w)?this._transitionable.setTransition(n.slice(0,-11),i):this._transitionable.setValue(n,i)}},r.prototype.updateTransitions=function(t){this._transitioning=this._transitionable.transitioned(t,this._transitioning)},r.prototype.hasTransition=function(){return this._transitioning.hasTransition()},r.prototype.recalculate=function(t){this.properties=this._transitioning.possiblyEvaluate(t)},r.prototype._validate=function(e,r,n){return(!n||!1!==n.validate)&&t.emitValidationErrors(this,e.call(t.validateStyle,t.extend({value:r,style:{glyphs:!0,sprite:!0},styleSpec:t.styleSpec})))},r}(t.Evented),k=function(t,e){this.width=t,this.height=e,this.nextRow=0,this.data=new Uint8Array(this.width*this.height),this.dashEntry={}};k.prototype.getDash=function(t,e){var r=t.join(\",\")+String(e);return this.dashEntry[r]||(this.dashEntry[r]=this.addDash(t,e)),this.dashEntry[r]},k.prototype.getDashRanges=function(t,e,r){var n=[],i=t.length%2==1?-t[t.length-1]*r:0,a=t[0]*r,o=!0;n.push({left:i,right:a,isDash:o,zeroLength:0===t[0]});for(var s=t[0],l=1;l<t.length;l++){o=!o;var u=t[l];i=s*r,a=(s+=u)*r,n.push({left:i,right:a,isDash:o,zeroLength:0===u})}return n},k.prototype.addRoundDash=function(t,e,r){for(var n=e/2,i=-r;i<=r;i++)for(var a=this.nextRow+r+i,o=this.width*a,s=0,l=t[s],u=0;u<this.width;u++){u/l.right>1&&(l=t[++s]);var c=Math.abs(u-l.left),f=Math.abs(u-l.right),h=Math.min(c,f),p=void 0,d=i/r*(n+1);if(l.isDash){var v=n-Math.abs(d);p=Math.sqrt(h*h+v*v)}else p=n-Math.sqrt(h*h+d*d);this.data[o+u]=Math.max(0,Math.min(255,p+128))}},k.prototype.addRegularDash=function(t){for(var e=t.length-1;e>=0;--e){var r=t[e],n=t[e+1];r.zeroLength?t.splice(e,1):n&&n.isDash===r.isDash&&(n.left=r.left,t.splice(e,1))}var i=t[0],a=t[t.length-1];i.isDash===a.isDash&&(i.left=a.left-this.width,a.right=i.right+this.width);for(var o=this.width*this.nextRow,s=0,l=t[s],u=0;u<this.width;u++){u/l.right>1&&(l=t[++s]);var c=Math.abs(u-l.left),f=Math.abs(u-l.right),h=Math.min(c,f),p=l.isDash?h:-h;this.data[o+u]=Math.max(0,Math.min(255,p+128))}},k.prototype.addDash=function(e,r){var n=r?7:0,i=2*n+1;if(this.nextRow+i>this.height)return t.warnOnce(\"LineAtlas out of space\"),null;for(var a=0,o=0;o<e.length;o++)a+=e[o];if(0!==a){var s=this.width/a,l=this.getDashRanges(e,this.width,s);r?this.addRoundDash(l,s,n):this.addRegularDash(l)}var u={y:(this.nextRow+n+.5)/this.height,height:2*n/this.height,width:a};return this.nextRow+=i,this.dirty=!0,u},k.prototype.bind=function(t){var e=t.gl;this.texture?(e.bindTexture(e.TEXTURE_2D,this.texture),this.dirty&&(this.dirty=!1,e.texSubImage2D(e.TEXTURE_2D,0,0,0,this.width,this.height,e.ALPHA,e.UNSIGNED_BYTE,this.data))):(this.texture=e.createTexture(),e.bindTexture(e.TEXTURE_2D,this.texture),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_S,e.REPEAT),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_T,e.REPEAT),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MIN_FILTER,e.LINEAR),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MAG_FILTER,e.LINEAR),e.texImage2D(e.TEXTURE_2D,0,e.ALPHA,this.width,this.height,0,e.ALPHA,e.UNSIGNED_BYTE,this.data))};var A=function e(r,n){this.workerPool=r,this.actors=[],this.currentActor=0,this.id=t.uniqueId();for(var i=this.workerPool.acquire(this.id),a=0;a<i.length;a++){var o=i[a],s=new e.Actor(o,n,this.id);s.name=\"Worker \"+a,this.actors.push(s)}};function M(e,r,n){var i=function(i,a){if(i)return n(i);if(a){var o=t.pick(t.extend(a,e),[\"tiles\",\"minzoom\",\"maxzoom\",\"attribution\",\"mapbox_logo\",\"bounds\",\"scheme\",\"tileSize\",\"encoding\"]);a.vector_layers&&(o.vectorLayers=a.vector_layers,o.vectorLayerIds=o.vectorLayers.map((function(t){return t.id}))),o.tiles=r.canonicalizeTileset(o,e.url),n(null,o)}};return e.url?t.getJSON(r.transformRequest(r.normalizeSourceURL(e.url),t.ResourceType.Source),i):t.browser.frame((function(){return i(null,e)}))}A.prototype.broadcast=function(e,r,n){n=n||function(){},t.asyncAll(this.actors,(function(t,n){t.send(e,r,n)}),n)},A.prototype.getActor=function(){return this.currentActor=(this.currentActor+1)%this.actors.length,this.actors[this.currentActor]},A.prototype.remove=function(){this.actors.forEach((function(t){t.remove()})),this.actors=[],this.workerPool.release(this.id)},A.Actor=t.Actor;var S=function(e,r,n){this.bounds=t.LngLatBounds.convert(this.validateBounds(e)),this.minzoom=r||0,this.maxzoom=n||24};S.prototype.validateBounds=function(t){return Array.isArray(t)&&4===t.length?[Math.max(-180,t[0]),Math.max(-90,t[1]),Math.min(180,t[2]),Math.min(90,t[3])]:[-180,-90,180,90]},S.prototype.contains=function(e){var r=Math.pow(2,e.z),n=Math.floor(t.mercatorXfromLng(this.bounds.getWest())*r),i=Math.floor(t.mercatorYfromLat(this.bounds.getNorth())*r),a=Math.ceil(t.mercatorXfromLng(this.bounds.getEast())*r),o=Math.ceil(t.mercatorYfromLat(this.bounds.getSouth())*r);return e.x>=n&&e.x<a&&e.y>=i&&e.y<o};var E=function(e){function r(r,n,i,a){if(e.call(this),this.id=r,this.dispatcher=i,this.type=\"vector\",this.minzoom=0,this.maxzoom=22,this.scheme=\"xyz\",this.tileSize=512,this.reparseOverscaled=!0,this.isTileClipped=!0,this._loaded=!1,t.extend(this,t.pick(n,[\"url\",\"scheme\",\"tileSize\",\"promoteId\"])),this._options=t.extend({type:\"vector\"},n),this._collectResourceTiming=n.collectResourceTiming,512!==this.tileSize)throw new Error(\"vector tile sources must have a tileSize of 512\");this.setEventedParent(a)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._tileJSONRequest=M(this._options,this.map._requestManager,(function(r,n){e._tileJSONRequest=null,e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(t.extend(e,n),n.bounds&&(e.tileBounds=new S(n.bounds,e.minzoom,e.maxzoom)),t.postTurnstileEvent(n.tiles,e.map._requestManager._customAccessToken),t.postMapLoadEvent(n.tiles,e.map._getMapId(),e.map._requestManager._skuToken,e.map._requestManager._customAccessToken),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.hasTile=function(t){return!this.tileBounds||this.tileBounds.contains(t.canonical)},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setSourceProperty=function(t){this._tileJSONRequest&&this._tileJSONRequest.cancel(),t(),this.map.style.sourceCaches[this.id].clearTiles(),this.load()},r.prototype.setTiles=function(t){var e=this;return this.setSourceProperty((function(){e._options.tiles=t})),this},r.prototype.setUrl=function(t){var e=this;return this.setSourceProperty((function(){e.url=t,e._options.url=t})),this},r.prototype.onRemove=function(){this._tileJSONRequest&&(this._tileJSONRequest.cancel(),this._tileJSONRequest=null)},r.prototype.serialize=function(){return t.extend({},this._options)},r.prototype.loadTile=function(e,r){var n=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme)),i={request:this.map._requestManager.transformRequest(n,t.ResourceType.Tile),uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,tileSize:this.tileSize*e.tileID.overscaleFactor(),type:this.type,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};function a(n,i){return delete e.request,e.aborted?r(null):n&&404!==n.status?r(n):(i&&i.resourceTiming&&(e.resourceTiming=i.resourceTiming),this.map._refreshExpiredTiles&&i&&e.setExpiryData(i),e.loadVectorData(i,this.map.painter),t.cacheEntryPossiblyAdded(this.dispatcher),r(null),void(e.reloadCallback&&(this.loadTile(e,e.reloadCallback),e.reloadCallback=null)))}i.request.collectResourceTiming=this._collectResourceTiming,e.actor&&\"expired\"!==e.state?\"loading\"===e.state?e.reloadCallback=r:e.request=e.actor.send(\"reloadTile\",i,a.bind(this)):(e.actor=this.dispatcher.getActor(),e.request=e.actor.send(\"loadTile\",i,a.bind(this)))},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.actor&&t.actor.send(\"abortTile\",{uid:t.uid,type:this.type,source:this.id},void 0)},r.prototype.unloadTile=function(t){t.unloadVectorData(),t.actor&&t.actor.send(\"removeTile\",{uid:t.uid,type:this.type,source:this.id},void 0)},r.prototype.hasTransition=function(){return!1},r}(t.Evented),L=function(e){function r(r,n,i,a){e.call(this),this.id=r,this.dispatcher=i,this.setEventedParent(a),this.type=\"raster\",this.minzoom=0,this.maxzoom=22,this.roundZoom=!0,this.scheme=\"xyz\",this.tileSize=512,this._loaded=!1,this._options=t.extend({type:\"raster\"},n),t.extend(this,t.pick(n,[\"url\",\"scheme\",\"tileSize\"]))}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._tileJSONRequest=M(this._options,this.map._requestManager,(function(r,n){e._tileJSONRequest=null,e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(t.extend(e,n),n.bounds&&(e.tileBounds=new S(n.bounds,e.minzoom,e.maxzoom)),t.postTurnstileEvent(n.tiles),t.postMapLoadEvent(n.tiles,e.map._getMapId(),e.map._requestManager._skuToken),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.onRemove=function(){this._tileJSONRequest&&(this._tileJSONRequest.cancel(),this._tileJSONRequest=null)},r.prototype.serialize=function(){return t.extend({},this._options)},r.prototype.hasTile=function(t){return!this.tileBounds||this.tileBounds.contains(t.canonical)},r.prototype.loadTile=function(e,r){var n=this,i=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme),this.tileSize);e.request=t.getImage(this.map._requestManager.transformRequest(i,t.ResourceType.Tile),(function(i,a){if(delete e.request,e.aborted)e.state=\"unloaded\",r(null);else if(i)e.state=\"errored\",r(i);else if(a){n.map._refreshExpiredTiles&&e.setExpiryData(a),delete a.cacheControl,delete a.expires;var o=n.map.painter.context,s=o.gl;e.texture=n.map.painter.getTileTexture(a.width),e.texture?e.texture.update(a,{useMipmap:!0}):(e.texture=new t.Texture(o,a,s.RGBA,{useMipmap:!0}),e.texture.bind(s.LINEAR,s.CLAMP_TO_EDGE,s.LINEAR_MIPMAP_NEAREST),o.extTextureFilterAnisotropic&&s.texParameterf(s.TEXTURE_2D,o.extTextureFilterAnisotropic.TEXTURE_MAX_ANISOTROPY_EXT,o.extTextureFilterAnisotropicMax)),e.state=\"loaded\",t.cacheEntryPossiblyAdded(n.dispatcher),r(null)}}))},r.prototype.abortTile=function(t,e){t.request&&(t.request.cancel(),delete t.request),e()},r.prototype.unloadTile=function(t,e){t.texture&&this.map.painter.saveTileTexture(t.texture),e()},r.prototype.hasTransition=function(){return!1},r}(t.Evented),C=function(e){function r(r,n,i,a){e.call(this,r,n,i,a),this.type=\"raster-dem\",this.maxzoom=22,this._options=t.extend({type:\"raster-dem\"},n),this.encoding=n.encoding||\"mapbox\"}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.serialize=function(){return{type:\"raster-dem\",url:this.url,tileSize:this.tileSize,tiles:this.tiles,bounds:this.bounds,encoding:this.encoding}},r.prototype.loadTile=function(e,r){var n=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme),this.tileSize);function i(t,n){t&&(e.state=\"errored\",r(t)),n&&(e.dem=n,e.needsHillshadePrepare=!0,e.state=\"loaded\",r(null))}e.request=t.getImage(this.map._requestManager.transformRequest(n,t.ResourceType.Tile),function(n,a){if(delete e.request,e.aborted)e.state=\"unloaded\",r(null);else if(n)e.state=\"errored\",r(n);else if(a){this.map._refreshExpiredTiles&&e.setExpiryData(a),delete a.cacheControl,delete a.expires;var o=t.window.ImageBitmap&&a instanceof t.window.ImageBitmap&&t.offscreenCanvasSupported()?a:t.browser.getImageData(a,1),s={uid:e.uid,coord:e.tileID,source:this.id,rawImageData:o,encoding:this.encoding};e.actor&&\"expired\"!==e.state||(e.actor=this.dispatcher.getActor(),e.actor.send(\"loadDEMTile\",s,i.bind(this)))}}.bind(this)),e.neighboringTiles=this._getNeighboringTiles(e.tileID)},r.prototype._getNeighboringTiles=function(e){var r=e.canonical,n=Math.pow(2,r.z),i=(r.x-1+n)%n,a=0===r.x?e.wrap-1:e.wrap,o=(r.x+1+n)%n,s=r.x+1===n?e.wrap+1:e.wrap,l={};return l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y).key]={backfilled:!1},r.y>0&&(l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y-1).key]={backfilled:!1}),r.y+1<n&&(l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y+1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y+1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y+1).key]={backfilled:!1}),l},r.prototype.unloadTile=function(t){t.demTexture&&this.map.painter.saveTileTexture(t.demTexture),t.fbo&&(t.fbo.destroy(),delete t.fbo),t.dem&&delete t.dem,delete t.neighboringTiles,t.state=\"unloaded\",t.actor&&t.actor.send(\"removeDEMTile\",{uid:t.uid,source:this.id})},r}(L),P=function(e){function r(r,n,i,a){e.call(this),this.id=r,this.type=\"geojson\",this.minzoom=0,this.maxzoom=18,this.tileSize=512,this.isTileClipped=!0,this.reparseOverscaled=!0,this._removed=!1,this._loaded=!1,this.actor=i.getActor(),this.setEventedParent(a),this._data=n.data,this._options=t.extend({},n),this._collectResourceTiming=n.collectResourceTiming,this._resourceTiming=[],void 0!==n.maxzoom&&(this.maxzoom=n.maxzoom),n.type&&(this.type=n.type),n.attribution&&(this.attribution=n.attribution),this.promoteId=n.promoteId;var o=t.EXTENT/this.tileSize;this.workerOptions=t.extend({source:this.id,cluster:n.cluster||!1,geojsonVtOptions:{buffer:(void 0!==n.buffer?n.buffer:128)*o,tolerance:(void 0!==n.tolerance?n.tolerance:.375)*o,extent:t.EXTENT,maxZoom:this.maxzoom,lineMetrics:n.lineMetrics||!1,generateId:n.generateId||!1},superclusterOptions:{maxZoom:void 0!==n.clusterMaxZoom?Math.min(n.clusterMaxZoom,this.maxzoom-1):this.maxzoom-1,minPoints:Math.max(2,n.clusterMinPoints||2),extent:t.EXTENT,radius:(n.clusterRadius||50)*o,log:!1,generateId:n.generateId||!1},clusterProperties:n.clusterProperties,filter:n.filter},n.workerOptions)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._updateWorkerData((function(r){if(r)e.fire(new t.ErrorEvent(r));else{var n={dataType:\"source\",sourceDataType:\"metadata\"};e._collectResourceTiming&&e._resourceTiming&&e._resourceTiming.length>0&&(n.resourceTiming=e._resourceTiming,e._resourceTiming=[]),e.fire(new t.Event(\"data\",n))}}))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setData=function(e){var r=this;return this._data=e,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._updateWorkerData((function(e){if(e)r.fire(new t.ErrorEvent(e));else{var n={dataType:\"source\",sourceDataType:\"content\"};r._collectResourceTiming&&r._resourceTiming&&r._resourceTiming.length>0&&(n.resourceTiming=r._resourceTiming,r._resourceTiming=[]),r.fire(new t.Event(\"data\",n))}})),this},r.prototype.getClusterExpansionZoom=function(t,e){return this.actor.send(\"geojson.getClusterExpansionZoom\",{clusterId:t,source:this.id},e),this},r.prototype.getClusterChildren=function(t,e){return this.actor.send(\"geojson.getClusterChildren\",{clusterId:t,source:this.id},e),this},r.prototype.getClusterLeaves=function(t,e,r,n){return this.actor.send(\"geojson.getClusterLeaves\",{source:this.id,clusterId:t,limit:e,offset:r},n),this},r.prototype._updateWorkerData=function(e){var r=this;this._loaded=!1;var n=t.extend({},this.workerOptions),i=this._data;\"string\"==typeof i?(n.request=this.map._requestManager.transformRequest(t.browser.resolveURL(i),t.ResourceType.Source),n.request.collectResourceTiming=this._collectResourceTiming):n.data=JSON.stringify(i),this.actor.send(this.type+\".loadData\",n,(function(t,i){r._removed||i&&i.abandoned||(r._loaded=!0,i&&i.resourceTiming&&i.resourceTiming[r.id]&&(r._resourceTiming=i.resourceTiming[r.id].slice(0)),r.actor.send(r.type+\".coalesce\",{source:n.source},null),e(t))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.loadTile=function(e,r){var n=this,i=e.actor?\"reloadTile\":\"loadTile\";e.actor=this.actor;var a={type:this.type,uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,maxZoom:this.maxzoom,tileSize:this.tileSize,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};e.request=this.actor.send(i,a,(function(t,a){return delete e.request,e.unloadVectorData(),e.aborted?r(null):t?r(t):(e.loadVectorData(a,n.map.painter,\"reloadTile\"===i),r(null))}))},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.aborted=!0},r.prototype.unloadTile=function(t){t.unloadVectorData(),this.actor.send(\"removeTile\",{uid:t.uid,type:this.type,source:this.id})},r.prototype.onRemove=function(){this._removed=!0,this.actor.send(\"removeSource\",{type:this.type,source:this.id})},r.prototype.serialize=function(){return t.extend({},this._options,{type:this.type,data:this._data})},r.prototype.hasTransition=function(){return!1},r}(t.Evented),O=t.createLayout([{name:\"a_pos\",type:\"Int16\",components:2},{name:\"a_texture_pos\",type:\"Int16\",components:2}]),I=function(e){function r(t,r,n,i){e.call(this),this.id=t,this.dispatcher=n,this.coordinates=r.coordinates,this.type=\"image\",this.minzoom=0,this.maxzoom=22,this.tileSize=512,this.tiles={},this._loaded=!1,this.setEventedParent(i),this.options=r}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(e,r){var n=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this.url=this.options.url,t.getImage(this.map._requestManager.transformRequest(this.url,t.ResourceType.Image),(function(i,a){n._loaded=!0,i?n.fire(new t.ErrorEvent(i)):a&&(n.image=a,e&&(n.coordinates=e),r&&r(),n._finishLoading())}))},r.prototype.loaded=function(){return this._loaded},r.prototype.updateImage=function(t){var e=this;return this.image&&t.url?(this.options.url=t.url,this.load(t.coordinates,(function(){e.texture=null})),this):this},r.prototype._finishLoading=function(){this.map&&(this.setCoordinates(this.coordinates),this.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setCoordinates=function(e){var r=this;this.coordinates=e;var n=e.map(t.MercatorCoordinate.fromLngLat);this.tileID=function(e){for(var r=1/0,n=1/0,i=-1/0,a=-1/0,o=0,s=e;o<s.length;o+=1){var l=s[o];r=Math.min(r,l.x),n=Math.min(n,l.y),i=Math.max(i,l.x),a=Math.max(a,l.y)}var u=i-r,c=a-n,f=Math.max(u,c),h=Math.max(0,Math.floor(-Math.log(f)/Math.LN2)),p=Math.pow(2,h);return new t.CanonicalTileID(h,Math.floor((r+i)/2*p),Math.floor((n+a)/2*p))}(n),this.minzoom=this.maxzoom=this.tileID.z;var i=n.map((function(t){return r.tileID.getTilePoint(t)._round()}));return this._boundsArray=new t.StructArrayLayout4i8,this._boundsArray.emplaceBack(i[0].x,i[0].y,0,0),this._boundsArray.emplaceBack(i[1].x,i[1].y,t.EXTENT,0),this._boundsArray.emplaceBack(i[3].x,i[3].y,0,t.EXTENT),this._boundsArray.emplaceBack(i[2].x,i[2].y,t.EXTENT,t.EXTENT),this.boundsBuffer&&(this.boundsBuffer.destroy(),delete this.boundsBuffer),this.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})),this},r.prototype.prepare=function(){if(0!==Object.keys(this.tiles).length&&this.image){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,O.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture||(this.texture=new t.Texture(e,this.image,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var i=this.tiles[n];\"loaded\"!==i.state&&(i.state=\"loaded\",i.texture=this.texture)}}},r.prototype.loadTile=function(t,e){this.tileID&&this.tileID.equals(t.tileID.canonical)?(this.tiles[String(t.tileID.wrap)]=t,t.buckets={},e(null)):(t.state=\"errored\",e(null))},r.prototype.serialize=function(){return{type:\"image\",url:this.options.url,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return!1},r}(t.Evented);var D=function(e){function r(t,r,n,i){e.call(this,t,r,n,i),this.roundZoom=!0,this.type=\"video\",this.options=r}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1;var r=this.options;this.urls=[];for(var n=0,i=r.urls;n<i.length;n+=1){var a=i[n];this.urls.push(this.map._requestManager.transformRequest(a,t.ResourceType.Source).url)}t.getVideo(this.urls,(function(r,n){e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(e.video=n,e.video.loop=!0,e.video.addEventListener(\"playing\",(function(){e.map.triggerRepaint()})),e.map&&e.video.play(),e._finishLoading())}))},r.prototype.pause=function(){this.video&&this.video.pause()},r.prototype.play=function(){this.video&&this.video.play()},r.prototype.seek=function(e){if(this.video){var r=this.video.seekable;e<r.start(0)||e>r.end(0)?this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+this.id,null,\"Playback for this video can be set only between the \"+r.start(0)+\" and \"+r.end(0)+\"-second mark.\"))):this.video.currentTime=e}},r.prototype.getVideo=function(){return this.video},r.prototype.onAdd=function(t){this.map||(this.map=t,this.load(),this.video&&(this.video.play(),this.setCoordinates(this.coordinates)))},r.prototype.prepare=function(){if(!(0===Object.keys(this.tiles).length||this.video.readyState<2)){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,O.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?this.video.paused||(this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE),r.texSubImage2D(r.TEXTURE_2D,0,0,0,r.RGBA,r.UNSIGNED_BYTE,this.video)):(this.texture=new t.Texture(e,this.video,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var i=this.tiles[n];\"loaded\"!==i.state&&(i.state=\"loaded\",i.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"video\",urls:this.urls,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this.video&&!this.video.paused},r}(I),z=function(e){function r(r,n,i,a){e.call(this,r,n,i,a),n.coordinates?Array.isArray(n.coordinates)&&4===n.coordinates.length&&!n.coordinates.some((function(t){return!Array.isArray(t)||2!==t.length||t.some((function(t){return\"number\"!=typeof t}))}))||this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'\"coordinates\" property must be an array of 4 longitude/latitude array pairs'))):this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'missing required property \"coordinates\"'))),n.animate&&\"boolean\"!=typeof n.animate&&this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'optional \"animate\" property must be a boolean value'))),n.canvas?\"string\"==typeof n.canvas||n.canvas instanceof t.window.HTMLCanvasElement||this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'\"canvas\" must be either a string representing the ID of the canvas element from which to read, or an HTMLCanvasElement instance'))):this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'missing required property \"canvas\"'))),this.options=n,this.animate=void 0===n.animate||n.animate}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){this._loaded=!0,this.canvas||(this.canvas=this.options.canvas instanceof t.window.HTMLCanvasElement?this.options.canvas:t.window.document.getElementById(this.options.canvas)),this.width=this.canvas.width,this.height=this.canvas.height,this._hasInvalidDimensions()?this.fire(new t.ErrorEvent(new Error(\"Canvas dimensions cannot be less than or equal to zero.\"))):(this.play=function(){this._playing=!0,this.map.triggerRepaint()},this.pause=function(){this._playing&&(this.prepare(),this._playing=!1)},this._finishLoading())},r.prototype.getCanvas=function(){return this.canvas},r.prototype.onAdd=function(t){this.map=t,this.load(),this.canvas&&this.animate&&this.play()},r.prototype.onRemove=function(){this.pause()},r.prototype.prepare=function(){var e=!1;if(this.canvas.width!==this.width&&(this.width=this.canvas.width,e=!0),this.canvas.height!==this.height&&(this.height=this.canvas.height,e=!0),!this._hasInvalidDimensions()&&0!==Object.keys(this.tiles).length){var r=this.map.painter.context,n=r.gl;for(var i in this.boundsBuffer||(this.boundsBuffer=r.createVertexBuffer(this._boundsArray,O.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?(e||this._playing)&&this.texture.update(this.canvas,{premultiply:!0}):this.texture=new t.Texture(r,this.canvas,n.RGBA,{premultiply:!0}),this.tiles){var a=this.tiles[i];\"loaded\"!==a.state&&(a.state=\"loaded\",a.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"canvas\",coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this._playing},r.prototype._hasInvalidDimensions=function(){for(var t=0,e=[this.canvas.width,this.canvas.height];t<e.length;t+=1){var r=e[t];if(isNaN(r)||r<=0)return!0}return!1},r}(I),R={vector:E,raster:L,\"raster-dem\":C,geojson:P,video:D,image:I,canvas:z};function F(e,r){var n=t.identity([]);return t.translate(n,n,[1,1,0]),t.scale(n,n,[.5*e.width,.5*e.height,1]),t.multiply(n,n,e.calculatePosMatrix(r.toUnwrapped()))}function B(t,e,r,n,i,a){var o=function(t,e,r){if(t)for(var n=0,i=t;n<i.length;n+=1){var a=e[i[n]];if(a&&a.source===r&&\"fill-extrusion\"===a.type)return!0}else for(var o in e){var s=e[o];if(s.source===r&&\"fill-extrusion\"===s.type)return!0}return!1}(i&&i.layers,e,t.id),s=a.maxPitchScaleFactor(),l=t.tilesIn(n,s,o);l.sort(N);for(var u=[],c=0,f=l;c<f.length;c+=1){var h=f[c];u.push({wrappedTileID:h.tileID.wrapped().key,queryResults:h.tile.queryRenderedFeatures(e,r,t._state,h.queryGeometry,h.cameraQueryGeometry,h.scale,i,a,s,F(t.transform,h.tileID))})}var p=function(t){for(var e={},r={},n=0,i=t;n<i.length;n+=1){var a=i[n],o=a.queryResults,s=a.wrappedTileID,l=r[s]=r[s]||{};for(var u in o)for(var 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Mt=function(t,e,r){this.func=t,this.mask=e,this.range=r};Mt.ReadOnly=!1,Mt.ReadWrite=!0,Mt.disabled=new Mt(519,Mt.ReadOnly,[0,1]);var St=7680,Et=function(t,e,r,n,i,a){this.test=t,this.ref=e,this.mask=r,this.fail=n,this.depthFail=i,this.pass=a};Et.disabled=new Et({func:519,mask:0},0,0,St,St,St);var Lt=function(t,e,r){this.blendFunction=t,this.blendColor=e,this.mask=r};Lt.Replace=[1,0],Lt.disabled=new Lt(Lt.Replace,t.Color.transparent,[!1,!1,!1,!1]),Lt.unblended=new Lt(Lt.Replace,t.Color.transparent,[!0,!0,!0,!0]),Lt.alphaBlended=new Lt([1,771],t.Color.transparent,[!0,!0,!0,!0]);var Ct=function(t,e,r){this.enable=t,this.mode=e,this.frontFace=r};Ct.disabled=new Ct(!1,1029,2305),Ct.backCCW=new Ct(!0,1029,2305);var Pt=function(t){this.gl=t,this.extVertexArrayObject=this.gl.getExtension(\"OES_vertex_array_object\"),this.clearColor=new G(this),this.clearDepth=new W(this),this.clearStencil=new Y(this),this.colorMask=new X(this),this.depthMask=new Z(this),this.stencilMask=new K(this),this.stencilFunc=new J(this),this.stencilOp=new $(this),this.stencilTest=new Q(this),this.depthRange=new tt(this),this.depthTest=new et(this),this.depthFunc=new rt(this),this.blend=new nt(this),this.blendFunc=new it(this),this.blendColor=new at(this),this.blendEquation=new ot(this),this.cullFace=new st(this),this.cullFaceSide=new lt(this),this.frontFace=new ut(this),this.program=new ct(this),this.activeTexture=new ft(this),this.viewport=new ht(this),this.bindFramebuffer=new pt(this),this.bindRenderbuffer=new dt(this),this.bindTexture=new vt(this),this.bindVertexBuffer=new gt(this),this.bindElementBuffer=new yt(this),this.bindVertexArrayOES=this.extVertexArrayObject&&new mt(this),this.pixelStoreUnpack=new xt(this),this.pixelStoreUnpackPremultiplyAlpha=new bt(this),this.pixelStoreUnpackFlipY=new _t(this),this.extTextureFilterAnisotropic=t.getExtension(\"EXT_texture_filter_anisotropic\")||t.getExtension(\"MOZ_EXT_texture_filter_anisotropic\")||t.getExtension(\"WEBKIT_EXT_texture_filter_anisotropic\"),this.extTextureFilterAnisotropic&&(this.extTextureFilterAnisotropicMax=t.getParameter(this.extTextureFilterAnisotropic.MAX_TEXTURE_MAX_ANISOTROPY_EXT)),this.extTextureHalfFloat=t.getExtension(\"OES_texture_half_float\"),this.extTextureHalfFloat&&(t.getExtension(\"OES_texture_half_float_linear\"),this.extRenderToTextureHalfFloat=t.getExtension(\"EXT_color_buffer_half_float\")),this.extTimerQuery=t.getExtension(\"EXT_disjoint_timer_query\"),this.maxTextureSize=t.getParameter(t.MAX_TEXTURE_SIZE)};Pt.prototype.setDefault=function(){this.unbindVAO(),this.clearColor.setDefault(),this.clearDepth.setDefault(),this.clearStencil.setDefault(),this.colorMask.setDefault(),this.depthMask.setDefault(),this.stencilMask.setDefault(),this.stencilFunc.setDefault(),this.stencilOp.setDefault(),this.stencilTest.setDefault(),this.depthRange.setDefault(),this.depthTest.setDefault(),this.depthFunc.setDefault(),this.blend.setDefault(),this.blendFunc.setDefault(),this.blendColor.setDefault(),this.blendEquation.setDefault(),this.cullFace.setDefault(),this.cullFaceSide.setDefault(),this.frontFace.setDefault(),this.program.setDefault(),this.activeTexture.setDefault(),this.bindFramebuffer.setDefault(),this.pixelStoreUnpack.setDefault(),this.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.pixelStoreUnpackFlipY.setDefault()},Pt.prototype.setDirty=function(){this.clearColor.dirty=!0,this.clearDepth.dirty=!0,this.clearStencil.dirty=!0,this.colorMask.dirty=!0,this.depthMask.dirty=!0,this.stencilMask.dirty=!0,this.stencilFunc.dirty=!0,this.stencilOp.dirty=!0,this.stencilTest.dirty=!0,this.depthRange.dirty=!0,this.depthTest.dirty=!0,this.depthFunc.dirty=!0,this.blend.dirty=!0,this.blendFunc.dirty=!0,this.blendColor.dirty=!0,this.blendEquation.dirty=!0,this.cullFace.dirty=!0,this.cullFaceSide.dirty=!0,this.frontFace.dirty=!0,this.program.dirty=!0,this.activeTexture.dirty=!0,this.viewport.dirty=!0,this.bindFramebuffer.dirty=!0,this.bindRenderbuffer.dirty=!0,this.bindTexture.dirty=!0,this.bindVertexBuffer.dirty=!0,this.bindElementBuffer.dirty=!0,this.extVertexArrayObject&&(this.bindVertexArrayOES.dirty=!0),this.pixelStoreUnpack.dirty=!0,this.pixelStoreUnpackPremultiplyAlpha.dirty=!0,this.pixelStoreUnpackFlipY.dirty=!0},Pt.prototype.createIndexBuffer=function(t,e){return new U(this,t,e)},Pt.prototype.createVertexBuffer=function(t,e,r){return new q(this,t,e,r)},Pt.prototype.createRenderbuffer=function(t,e,r){var n=this.gl,i=n.createRenderbuffer();return this.bindRenderbuffer.set(i),n.renderbufferStorage(n.RENDERBUFFER,t,e,r),this.bindRenderbuffer.set(null),i},Pt.prototype.createFramebuffer=function(t,e,r){return new At(this,t,e,r)},Pt.prototype.clear=function(t){var e=t.color,r=t.depth,n=this.gl,i=0;e&&(i|=n.COLOR_BUFFER_BIT,this.clearColor.set(e),this.colorMask.set([!0,!0,!0,!0])),void 0!==r&&(i|=n.DEPTH_BUFFER_BIT,this.depthRange.set([0,1]),this.clearDepth.set(r),this.depthMask.set(!0)),n.clear(i)},Pt.prototype.setCullFace=function(t){!1===t.enable?this.cullFace.set(!1):(this.cullFace.set(!0),this.cullFaceSide.set(t.mode),this.frontFace.set(t.frontFace))},Pt.prototype.setDepthMode=function(t){t.func!==this.gl.ALWAYS||t.mask?(this.depthTest.set(!0),this.depthFunc.set(t.func),this.depthMask.set(t.mask),this.depthRange.set(t.range)):this.depthTest.set(!1)},Pt.prototype.setStencilMode=function(t){t.test.func!==this.gl.ALWAYS||t.mask?(this.stencilTest.set(!0),this.stencilMask.set(t.mask),this.stencilOp.set([t.fail,t.depthFail,t.pass]),this.stencilFunc.set({func:t.test.func,ref:t.ref,mask:t.test.mask})):this.stencilTest.set(!1)},Pt.prototype.setColorMode=function(e){t.deepEqual(e.blendFunction,Lt.Replace)?this.blend.set(!1):(this.blend.set(!0),this.blendFunc.set(e.blendFunction),this.blendColor.set(e.blendColor)),this.colorMask.set(e.mask)},Pt.prototype.unbindVAO=function(){this.extVertexArrayObject&&this.bindVertexArrayOES.set(null)};var Ot=function(e){function r(r,n,i){var a=this;e.call(this),this.id=r,this.dispatcher=i,this.on(\"data\",(function(t){\"source\"===t.dataType&&\"metadata\"===t.sourceDataType&&(a._sourceLoaded=!0),a._sourceLoaded&&!a._paused&&\"source\"===t.dataType&&\"content\"===t.sourceDataType&&(a.reload(),a.transform&&a.update(a.transform))})),this.on(\"error\",(function(){a._sourceErrored=!0})),this._source=function(e,r,n,i){var a=new R[r.type](e,r,n,i);if(a.id!==e)throw new Error(\"Expected Source id to be \"+e+\" instead of \"+a.id);return t.bindAll([\"load\",\"abort\",\"unload\",\"serialize\",\"prepare\"],a),a}(r,n,i,this),this._tiles={},this._cache=new j(0,this._unloadTile.bind(this)),this._timers={},this._cacheTimers={},this._maxTileCacheSize=null,this._loadedParentTiles={},this._coveredTiles={},this._state=new t.SourceFeatureState}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.onAdd=function(t){this.map=t,this._maxTileCacheSize=t?t._maxTileCacheSize:null,this._source&&this._source.onAdd&&this._source.onAdd(t)},r.prototype.onRemove=function(t){this._source&&this._source.onRemove&&this._source.onRemove(t)},r.prototype.loaded=function(){if(this._sourceErrored)return!0;if(!this._sourceLoaded)return!1;if(!this._source.loaded())return!1;for(var t in this._tiles){var e=this._tiles[t];if(\"loaded\"!==e.state&&\"errored\"!==e.state)return!1}return!0},r.prototype.getSource=function(){return this._source},r.prototype.pause=function(){this._paused=!0},r.prototype.resume=function(){if(this._paused){var t=this._shouldReloadOnResume;this._paused=!1,this._shouldReloadOnResume=!1,t&&this.reload(),this.transform&&this.update(this.transform)}},r.prototype._loadTile=function(t,e){return this._source.loadTile(t,e)},r.prototype._unloadTile=function(t){if(this._source.unloadTile)return this._source.unloadTile(t,(function(){}))},r.prototype._abortTile=function(t){if(this._source.abortTile)return this._source.abortTile(t,(function(){}))},r.prototype.serialize=function(){return this._source.serialize()},r.prototype.prepare=function(t){for(var e in this._source.prepare&&this._source.prepare(),this._state.coalesceChanges(this._tiles,this.map?this.map.painter:null),this._tiles){var r=this._tiles[e];r.upload(t),r.prepare(this.map.style.imageManager)}},r.prototype.getIds=function(){return t.values(this._tiles).map((function(t){return t.tileID})).sort(It).map((function(t){return t.key}))},r.prototype.getRenderableIds=function(e){var r=this,n=[];for(var i in this._tiles)this._isIdRenderable(i,e)&&n.push(this._tiles[i]);return e?n.sort((function(e,n){var i=e.tileID,a=n.tileID,o=new t.Point(i.canonical.x,i.canonical.y)._rotate(r.transform.angle),s=new t.Point(a.canonical.x,a.canonical.y)._rotate(r.transform.angle);return i.overscaledZ-a.overscaledZ||s.y-o.y||s.x-o.x})).map((function(t){return t.tileID.key})):n.map((function(t){return t.tileID})).sort(It).map((function(t){return t.key}))},r.prototype.hasRenderableParent=function(t){var e=this.findLoadedParent(t,0);return!!e&&this._isIdRenderable(e.tileID.key)},r.prototype._isIdRenderable=function(t,e){return this._tiles[t]&&this._tiles[t].hasData()&&!this._coveredTiles[t]&&(e||!this._tiles[t].holdingForFade())},r.prototype.reload=function(){if(this._paused)this._shouldReloadOnResume=!0;else for(var t in this._cache.reset(),this._tiles)\"errored\"!==this._tiles[t].state&&this._reloadTile(t,\"reloading\")},r.prototype._reloadTile=function(t,e){var r=this._tiles[t];r&&(\"loading\"!==r.state&&(r.state=e),this._loadTile(r,this._tileLoaded.bind(this,r,t,e)))},r.prototype._tileLoaded=function(e,r,n,i){if(i)return e.state=\"errored\",void(404!==i.status?this._source.fire(new t.ErrorEvent(i,{tile:e})):this.update(this.transform));e.timeAdded=t.browser.now(),\"expired\"===n&&(e.refreshedUponExpiration=!0),this._setTileReloadTimer(r,e),\"raster-dem\"===this.getSource().type&&e.dem&&this._backfillDEM(e),this._state.initializeTileState(e,this.map?this.map.painter:null),this._source.fire(new t.Event(\"data\",{dataType:\"source\",tile:e,coord:e.tileID}))},r.prototype._backfillDEM=function(t){for(var e=this.getRenderableIds(),r=0;r<e.length;r++){var n=e[r];if(t.neighboringTiles&&t.neighboringTiles[n]){var i=this.getTileByID(n);a(t,i),a(i,t)}}function a(t,e){t.needsHillshadePrepare=!0;var r=e.tileID.canonical.x-t.tileID.canonical.x,n=e.tileID.canonical.y-t.tileID.canonical.y,i=Math.pow(2,t.tileID.canonical.z),a=e.tileID.key;0===r&&0===n||Math.abs(n)>1||(Math.abs(r)>1&&(1===Math.abs(r+i)?r+=i:1===Math.abs(r-i)&&(r-=i)),e.dem&&t.dem&&(t.dem.backfillBorder(e.dem,r,n),t.neighboringTiles&&t.neighboringTiles[a]&&(t.neighboringTiles[a].backfilled=!0)))}},r.prototype.getTile=function(t){return this.getTileByID(t.key)},r.prototype.getTileByID=function(t){return this._tiles[t]},r.prototype._retainLoadedChildren=function(t,e,r,n){for(var i in this._tiles){var a=this._tiles[i];if(!(n[i]||!a.hasData()||a.tileID.overscaledZ<=e||a.tileID.overscaledZ>r)){for(var o=a.tileID;a&&a.tileID.overscaledZ>e+1;){var s=a.tileID.scaledTo(a.tileID.overscaledZ-1);(a=this._tiles[s.key])&&a.hasData()&&(o=s)}for(var l=o;l.overscaledZ>e;)if(t[(l=l.scaledTo(l.overscaledZ-1)).key]){n[o.key]=o;break}}}},r.prototype.findLoadedParent=function(t,e){if(t.key in this._loadedParentTiles){var r=this._loadedParentTiles[t.key];return r&&r.tileID.overscaledZ>=e?r:null}for(var n=t.overscaledZ-1;n>=e;n--){var i=t.scaledTo(n),a=this._getLoadedTile(i);if(a)return a}},r.prototype._getLoadedTile=function(t){var e=this._tiles[t.key];return e&&e.hasData()?e:this._cache.getByKey(t.wrapped().key)},r.prototype.updateCacheSize=function(t){var e=(Math.ceil(t.width/this._source.tileSize)+1)*(Math.ceil(t.height/this._source.tileSize)+1),r=Math.floor(5*e),n=\"number\"==typeof this._maxTileCacheSize?Math.min(this._maxTileCacheSize,r):r;this._cache.setMaxSize(n)},r.prototype.handleWrapJump=function(t){var e=(t-(void 0===this._prevLng?t:this._prevLng))/360,r=Math.round(e);if(this._prevLng=t,r){var n={};for(var i in this._tiles){var a=this._tiles[i];a.tileID=a.tileID.unwrapTo(a.tileID.wrap+r),n[a.tileID.key]=a}for(var o in this._tiles=n,this._timers)clearTimeout(this._timers[o]),delete this._timers[o];for(var s in this._tiles){var l=this._tiles[s];this._setTileReloadTimer(s,l)}}},r.prototype.update=function(e){var n=this;if(this.transform=e,this._sourceLoaded&&!this._paused){var i;this.updateCacheSize(e),this.handleWrapJump(this.transform.center.lng),this._coveredTiles={},this.used?this._source.tileID?i=e.getVisibleUnwrappedCoordinates(this._source.tileID).map((function(e){return new t.OverscaledTileID(e.canonical.z,e.wrap,e.canonical.z,e.canonical.x,e.canonical.y)})):(i=e.coveringTiles({tileSize:this._source.tileSize,minzoom:this._source.minzoom,maxzoom:this._source.maxzoom,roundZoom:this._source.roundZoom,reparseOverscaled:this._source.reparseOverscaled}),this._source.hasTile&&(i=i.filter((function(t){return n._source.hasTile(t)})))):i=[];var a=e.coveringZoomLevel(this._source),o=Math.max(a-r.maxOverzooming,this._source.minzoom),s=Math.max(a+r.maxUnderzooming,this._source.minzoom),l=this._updateRetainedTiles(i,a);if(Dt(this._source.type)){for(var u={},c={},f=0,h=Object.keys(l);f<h.length;f+=1){var p=h[f],d=l[p],v=this._tiles[p];if(v&&!(v.fadeEndTime&&v.fadeEndTime<=t.browser.now())){var g=this.findLoadedParent(d,o);g&&(this._addTile(g.tileID),u[g.tileID.key]=g.tileID),c[p]=d}}for(var y in this._retainLoadedChildren(c,a,s,l),u)l[y]||(this._coveredTiles[y]=!0,l[y]=u[y])}for(var m in l)this._tiles[m].clearFadeHold();for(var x=0,b=t.keysDifference(this._tiles,l);x<b.length;x+=1){var _=b[x],w=this._tiles[_];w.hasSymbolBuckets&&!w.holdingForFade()?w.setHoldDuration(this.map._fadeDuration):w.hasSymbolBuckets&&!w.symbolFadeFinished()||this._removeTile(_)}this._updateLoadedParentTileCache()}},r.prototype.releaseSymbolFadeTiles=function(){for(var t in this._tiles)this._tiles[t].holdingForFade()&&this._removeTile(t)},r.prototype._updateRetainedTiles=function(t,e){for(var n={},i={},a=Math.max(e-r.maxOverzooming,this._source.minzoom),o=Math.max(e+r.maxUnderzooming,this._source.minzoom),s={},l=0,u=t;l<u.length;l+=1){var c=u[l],f=this._addTile(c);n[c.key]=c,f.hasData()||e<this._source.maxzoom&&(s[c.key]=c)}this._retainLoadedChildren(s,e,o,n);for(var h=0,p=t;h<p.length;h+=1){var d=p[h],v=this._tiles[d.key];if(!v.hasData()){if(e+1>this._source.maxzoom){var g=d.children(this._source.maxzoom)[0],y=this.getTile(g);if(y&&y.hasData()){n[g.key]=g;continue}}else{var m=d.children(this._source.maxzoom);if(n[m[0].key]&&n[m[1].key]&&n[m[2].key]&&n[m[3].key])continue}for(var x=v.wasRequested(),b=d.overscaledZ-1;b>=a;--b){var _=d.scaledTo(b);if(i[_.key])break;if(i[_.key]=!0,!(v=this.getTile(_))&&x&&(v=this._addTile(_)),v&&(n[_.key]=_,x=v.wasRequested(),v.hasData()))break}}}return n},r.prototype._updateLoadedParentTileCache=function(){for(var t in this._loadedParentTiles={},this._tiles){for(var e=[],r=void 0,n=this._tiles[t].tileID;n.overscaledZ>0;){if(n.key in this._loadedParentTiles){r=this._loadedParentTiles[n.key];break}e.push(n.key);var i=n.scaledTo(n.overscaledZ-1);if(r=this._getLoadedTile(i))break;n=i}for(var a=0,o=e;a<o.length;a+=1){var s=o[a];this._loadedParentTiles[s]=r}}},r.prototype._addTile=function(e){var r=this._tiles[e.key];if(r)return r;(r=this._cache.getAndRemove(e))&&(this._setTileReloadTimer(e.key,r),r.tileID=e,this._state.initializeTileState(r,this.map?this.map.painter:null),this._cacheTimers[e.key]&&(clearTimeout(this._cacheTimers[e.key]),delete this._cacheTimers[e.key],this._setTileReloadTimer(e.key,r)));var n=Boolean(r);return n||(r=new t.Tile(e,this._source.tileSize*e.overscaleFactor()),this._loadTile(r,this._tileLoaded.bind(this,r,e.key,r.state))),r?(r.uses++,this._tiles[e.key]=r,n||this._source.fire(new t.Event(\"dataloading\",{tile:r,coord:r.tileID,dataType:\"source\"})),r):null},r.prototype._setTileReloadTimer=function(t,e){var r=this;t in this._timers&&(clearTimeout(this._timers[t]),delete this._timers[t]);var n=e.getExpiryTimeout();n&&(this._timers[t]=setTimeout((function(){r._reloadTile(t,\"expired\"),delete r._timers[t]}),n))},r.prototype._removeTile=function(t){var e=this._tiles[t];e&&(e.uses--,delete this._tiles[t],this._timers[t]&&(clearTimeout(this._timers[t]),delete this._timers[t]),e.uses>0||(e.hasData()&&\"reloading\"!==e.state?this._cache.add(e.tileID,e,e.getExpiryTimeout()):(e.aborted=!0,this._abortTile(e),this._unloadTile(e))))},r.prototype.clearTiles=function(){for(var t in this._shouldReloadOnResume=!1,this._paused=!1,this._tiles)this._removeTile(t);this._cache.reset()},r.prototype.tilesIn=function(e,r,n){var i=this,a=[],o=this.transform;if(!o)return a;for(var s=n?o.getCameraQueryGeometry(e):e,l=e.map((function(t){return o.pointCoordinate(t)})),u=s.map((function(t){return o.pointCoordinate(t)})),c=this.getIds(),f=1/0,h=1/0,p=-1/0,d=-1/0,v=0,g=u;v<g.length;v+=1){var y=g[v];f=Math.min(f,y.x),h=Math.min(h,y.y),p=Math.max(p,y.x),d=Math.max(d,y.y)}for(var m=function(e){var n=i._tiles[c[e]];if(!n.holdingForFade()){var s=n.tileID,v=Math.pow(2,o.zoom-n.tileID.overscaledZ),g=r*n.queryPadding*t.EXTENT/n.tileSize/v,y=[s.getTilePoint(new t.MercatorCoordinate(f,h)),s.getTilePoint(new t.MercatorCoordinate(p,d))];if(y[0].x-g<t.EXTENT&&y[0].y-g<t.EXTENT&&y[1].x+g>=0&&y[1].y+g>=0){var m=l.map((function(t){return s.getTilePoint(t)})),x=u.map((function(t){return s.getTilePoint(t)}));a.push({tile:n,tileID:s,queryGeometry:m,cameraQueryGeometry:x,scale:v})}}},x=0;x<c.length;x++)m(x);return a},r.prototype.getVisibleCoordinates=function(t){for(var e=this,r=this.getRenderableIds(t).map((function(t){return e._tiles[t].tileID})),n=0,i=r;n<i.length;n+=1){var a=i[n];a.posMatrix=this.transform.calculatePosMatrix(a.toUnwrapped())}return r},r.prototype.hasTransition=function(){if(this._source.hasTransition())return!0;if(Dt(this._source.type))for(var e in this._tiles){var r=this._tiles[e];if(void 0!==r.fadeEndTime&&r.fadeEndTime>=t.browser.now())return!0}return!1},r.prototype.setFeatureState=function(t,e,r){t=t||\"_geojsonTileLayer\",this._state.updateState(t,e,r)},r.prototype.removeFeatureState=function(t,e,r){t=t||\"_geojsonTileLayer\",this._state.removeFeatureState(t,e,r)},r.prototype.getFeatureState=function(t,e){return t=t||\"_geojsonTileLayer\",this._state.getState(t,e)},r.prototype.setDependencies=function(t,e,r){var n=this._tiles[t];n&&n.setDependencies(e,r)},r.prototype.reloadTilesForDependencies=function(t,e){for(var r in this._tiles)this._tiles[r].hasDependency(t,e)&&this._reloadTile(r,\"reloading\");this._cache.filter((function(r){return!r.hasDependency(t,e)}))},r}(t.Evented);function It(t,e){var r=Math.abs(2*t.wrap)-+(t.wrap<0),n=Math.abs(2*e.wrap)-+(e.wrap<0);return t.overscaledZ-e.overscaledZ||n-r||e.canonical.y-t.canonical.y||e.canonical.x-t.canonical.x}function Dt(t){return\"raster\"===t||\"image\"===t||\"video\"===t}function zt(){return new t.window.Worker(oa.workerUrl)}Ot.maxOverzooming=10,Ot.maxUnderzooming=3;var Rt=\"mapboxgl_preloaded_worker_pool\",Ft=function(){this.active={}};Ft.prototype.acquire=function(t){if(!this.workers)for(this.workers=[];this.workers.length<Ft.workerCount;)this.workers.push(new zt);return this.active[t]=!0,this.workers.slice()},Ft.prototype.release=function(t){delete this.active[t],0===this.numActive()&&(this.workers.forEach((function(t){t.terminate()})),this.workers=null)},Ft.prototype.isPreloaded=function(){return!!this.active[Rt]},Ft.prototype.numActive=function(){return Object.keys(this.active).length};var Bt,Nt=Math.floor(t.browser.hardwareConcurrency/2);function jt(){return Bt||(Bt=new Ft),Bt}function Ut(e,r){var n={};for(var i in e)\"ref\"!==i&&(n[i]=e[i]);return t.refProperties.forEach((function(t){t in r&&(n[t]=r[t])})),n}function Vt(t){t=t.slice();for(var e=Object.create(null),r=0;r<t.length;r++)e[t[r].id]=t[r];for(var n=0;n<t.length;n++)\"ref\"in t[n]&&(t[n]=Ut(t[n],e[t[n].ref]));return t}Ft.workerCount=Math.max(Math.min(Nt,6),1);var qt={setStyle:\"setStyle\",addLayer:\"addLayer\",removeLayer:\"removeLayer\",setPaintProperty:\"setPaintProperty\",setLayoutProperty:\"setLayoutProperty\",setFilter:\"setFilter\",addSource:\"addSource\",removeSource:\"removeSource\",setGeoJSONSourceData:\"setGeoJSONSourceData\",setLayerZoomRange:\"setLayerZoomRange\",setLayerProperty:\"setLayerProperty\",setCenter:\"setCenter\",setZoom:\"setZoom\",setBearing:\"setBearing\",setPitch:\"setPitch\",setSprite:\"setSprite\",setGlyphs:\"setGlyphs\",setTransition:\"setTransition\",setLight:\"setLight\"};function Ht(t,e,r){r.push({command:qt.addSource,args:[t,e[t]]})}function Gt(t,e,r){e.push({command:qt.removeSource,args:[t]}),r[t]=!0}function Wt(t,e,r,n){Gt(t,r,n),Ht(t,e,r)}function Yt(e,r,n){var i;for(i in e[n])if(e[n].hasOwnProperty(i)&&\"data\"!==i&&!t.deepEqual(e[n][i],r[n][i]))return!1;for(i in r[n])if(r[n].hasOwnProperty(i)&&\"data\"!==i&&!t.deepEqual(e[n][i],r[n][i]))return!1;return!0}function Xt(e,r,n,i,a,o){var s;for(s in r=r||{},e=e||{})e.hasOwnProperty(s)&&(t.deepEqual(e[s],r[s])||n.push({command:o,args:[i,s,r[s],a]}));for(s in r)r.hasOwnProperty(s)&&!e.hasOwnProperty(s)&&(t.deepEqual(e[s],r[s])||n.push({command:o,args:[i,s,r[s],a]}))}function Zt(t){return t.id}function Kt(t,e){return t[e.id]=e,t}function Jt(e,r){if(!e)return[{command:qt.setStyle,args:[r]}];var n=[];try{if(!t.deepEqual(e.version,r.version))return[{command:qt.setStyle,args:[r]}];t.deepEqual(e.center,r.center)||n.push({command:qt.setCenter,args:[r.center]}),t.deepEqual(e.zoom,r.zoom)||n.push({command:qt.setZoom,args:[r.zoom]}),t.deepEqual(e.bearing,r.bearing)||n.push({command:qt.setBearing,args:[r.bearing]}),t.deepEqual(e.pitch,r.pitch)||n.push({command:qt.setPitch,args:[r.pitch]}),t.deepEqual(e.sprite,r.sprite)||n.push({command:qt.setSprite,args:[r.sprite]}),t.deepEqual(e.glyphs,r.glyphs)||n.push({command:qt.setGlyphs,args:[r.glyphs]}),t.deepEqual(e.transition,r.transition)||n.push({command:qt.setTransition,args:[r.transition]}),t.deepEqual(e.light,r.light)||n.push({command:qt.setLight,args:[r.light]});var i={},a=[];!function(e,r,n,i){var a;for(a in r=r||{},e=e||{})e.hasOwnProperty(a)&&(r.hasOwnProperty(a)||Gt(a,n,i));for(a in r)r.hasOwnProperty(a)&&(e.hasOwnProperty(a)?t.deepEqual(e[a],r[a])||(\"geojson\"===e[a].type&&\"geojson\"===r[a].type&&Yt(e,r,a)?n.push({command:qt.setGeoJSONSourceData,args:[a,r[a].data]}):Wt(a,r,n,i)):Ht(a,r,n))}(e.sources,r.sources,a,i);var o=[];e.layers&&e.layers.forEach((function(t){i[t.source]?n.push({command:qt.removeLayer,args:[t.id]}):o.push(t)})),n=n.concat(a),function(e,r,n){r=r||[];var i,a,o,s,l,u,c,f=(e=e||[]).map(Zt),h=r.map(Zt),p=e.reduce(Kt,{}),d=r.reduce(Kt,{}),v=f.slice(),g=Object.create(null);for(i=0,a=0;i<f.length;i++)o=f[i],d.hasOwnProperty(o)?a++:(n.push({command:qt.removeLayer,args:[o]}),v.splice(v.indexOf(o,a),1));for(i=0,a=0;i<h.length;i++)o=h[h.length-1-i],v[v.length-1-i]!==o&&(p.hasOwnProperty(o)?(n.push({command:qt.removeLayer,args:[o]}),v.splice(v.lastIndexOf(o,v.length-a),1)):a++,u=v[v.length-i],n.push({command:qt.addLayer,args:[d[o],u]}),v.splice(v.length-i,0,o),g[o]=!0);for(i=0;i<h.length;i++)if(s=p[o=h[i]],l=d[o],!g[o]&&!t.deepEqual(s,l))if(t.deepEqual(s.source,l.source)&&t.deepEqual(s[\"source-layer\"],l[\"source-layer\"])&&t.deepEqual(s.type,l.type)){for(c in Xt(s.layout,l.layout,n,o,null,qt.setLayoutProperty),Xt(s.paint,l.paint,n,o,null,qt.setPaintProperty),t.deepEqual(s.filter,l.filter)||n.push({command:qt.setFilter,args:[o,l.filter]}),t.deepEqual(s.minzoom,l.minzoom)&&t.deepEqual(s.maxzoom,l.maxzoom)||n.push({command:qt.setLayerZoomRange,args:[o,l.minzoom,l.maxzoom]}),s)s.hasOwnProperty(c)&&\"layout\"!==c&&\"paint\"!==c&&\"filter\"!==c&&\"metadata\"!==c&&\"minzoom\"!==c&&\"maxzoom\"!==c&&(0===c.indexOf(\"paint.\")?Xt(s[c],l[c],n,o,c.slice(6),qt.setPaintProperty):t.deepEqual(s[c],l[c])||n.push({command:qt.setLayerProperty,args:[o,c,l[c]]}));for(c in l)l.hasOwnProperty(c)&&!s.hasOwnProperty(c)&&\"layout\"!==c&&\"paint\"!==c&&\"filter\"!==c&&\"metadata\"!==c&&\"minzoom\"!==c&&\"maxzoom\"!==c&&(0===c.indexOf(\"paint.\")?Xt(s[c],l[c],n,o,c.slice(6),qt.setPaintProperty):t.deepEqual(s[c],l[c])||n.push({command:qt.setLayerProperty,args:[o,c,l[c]]}))}else n.push({command:qt.removeLayer,args:[o]}),u=v[v.lastIndexOf(o)+1],n.push({command:qt.addLayer,args:[l,u]})}(o,r.layers,n)}catch(t){console.warn(\"Unable to compute style diff:\",t),n=[{command:qt.setStyle,args:[r]}]}return n}var $t=function(t,e){this.reset(t,e)};$t.prototype.reset=function(t,e){this.points=t||[],this._distances=[0];for(var r=1;r<this.points.length;r++)this._distances[r]=this._distances[r-1]+this.points[r].dist(this.points[r-1]);this.length=this._distances[this._distances.length-1],this.padding=Math.min(e||0,.5*this.length),this.paddedLength=this.length-2*this.padding},$t.prototype.lerp=function(e){if(1===this.points.length)return this.points[0];e=t.clamp(e,0,1);for(var r=1,n=this._distances[r],i=e*this.paddedLength+this.padding;n<i&&r<this._distances.length;)n=this._distances[++r];var a=r-1,o=this._distances[a],s=n-o,l=s>0?(i-o)/s:0;return this.points[a].mult(1-l).add(this.points[r].mult(l))};var Qt=function(t,e,r){var n=this.boxCells=[],i=this.circleCells=[];this.xCellCount=Math.ceil(t/r),this.yCellCount=Math.ceil(e/r);for(var a=0;a<this.xCellCount*this.yCellCount;a++)n.push([]),i.push([]);this.circleKeys=[],this.boxKeys=[],this.bboxes=[],this.circles=[],this.width=t,this.height=e,this.xScale=this.xCellCount/t,this.yScale=this.yCellCount/e,this.boxUid=0,this.circleUid=0};function te(e,r,n,i,a){var o=t.create();return r?(t.scale(o,o,[1/a,1/a,1]),n||t.rotateZ(o,o,i.angle)):t.multiply(o,i.labelPlaneMatrix,e),o}function ee(e,r,n,i,a){if(r){var o=t.clone(e);return t.scale(o,o,[a,a,1]),n||t.rotateZ(o,o,-i.angle),o}return i.glCoordMatrix}function re(e,r){var n=[e.x,e.y,0,1];pe(n,n,r);var i=n[3];return{point:new t.Point(n[0]/i,n[1]/i),signedDistanceFromCamera:i}}function ne(t,e){return.5+t/e*.5}function ie(t,e){var r=t[0]/t[3],n=t[1]/t[3];return r>=-e[0]&&r<=e[0]&&n>=-e[1]&&n<=e[1]}function ae(e,r,n,i,a,o,s,l){var u=i?e.textSizeData:e.iconSizeData,c=t.evaluateSizeForZoom(u,n.transform.zoom),f=[256/n.width*2+1,256/n.height*2+1],h=i?e.text.dynamicLayoutVertexArray:e.icon.dynamicLayoutVertexArray;h.clear();for(var p=e.lineVertexArray,d=i?e.text.placedSymbolArray:e.icon.placedSymbolArray,v=n.transform.width/n.transform.height,g=!1,y=0;y<d.length;y++){var m=d.get(y);if(m.hidden||m.writingMode===t.WritingMode.vertical&&!g)he(m.numGlyphs,h);else{g=!1;var x=[m.anchorX,m.anchorY,0,1];if(t.transformMat4(x,x,r),ie(x,f)){var b=x[3],_=ne(n.transform.cameraToCenterDistance,b),w=t.evaluateSizeForFeature(u,c,m),T=s?w/_:w*_,k=new t.Point(m.anchorX,m.anchorY),A=re(k,a).point,M={},S=le(m,T,!1,l,r,a,o,e.glyphOffsetArray,p,h,A,k,M,v);g=S.useVertical,(S.notEnoughRoom||g||S.needsFlipping&&le(m,T,!0,l,r,a,o,e.glyphOffsetArray,p,h,A,k,M,v).notEnoughRoom)&&he(m.numGlyphs,h)}else he(m.numGlyphs,h)}}i?e.text.dynamicLayoutVertexBuffer.updateData(h):e.icon.dynamicLayoutVertexBuffer.updateData(h)}function oe(t,e,r,n,i,a,o,s,l,u,c){var f=s.glyphStartIndex+s.numGlyphs,h=s.lineStartIndex,p=s.lineStartIndex+s.lineLength,d=e.getoffsetX(s.glyphStartIndex),v=e.getoffsetX(f-1),g=ce(t*d,r,n,i,a,o,s.segment,h,p,l,u,c);if(!g)return null;var y=ce(t*v,r,n,i,a,o,s.segment,h,p,l,u,c);return y?{first:g,last:y}:null}function se(e,r,n,i){return e===t.WritingMode.horizontal&&Math.abs(n.y-r.y)>Math.abs(n.x-r.x)*i?{useVertical:!0}:(e===t.WritingMode.vertical?r.y<n.y:r.x>n.x)?{needsFlipping:!0}:null}function le(e,r,n,i,a,o,s,l,u,c,f,h,p,d){var v,g=r/24,y=e.lineOffsetX*g,m=e.lineOffsetY*g;if(e.numGlyphs>1){var x=e.glyphStartIndex+e.numGlyphs,b=e.lineStartIndex,_=e.lineStartIndex+e.lineLength,w=oe(g,l,y,m,n,f,h,e,u,o,p);if(!w)return{notEnoughRoom:!0};var T=re(w.first.point,s).point,k=re(w.last.point,s).point;if(i&&!n){var A=se(e.writingMode,T,k,d);if(A)return A}v=[w.first];for(var M=e.glyphStartIndex+1;M<x-1;M++)v.push(ce(g*l.getoffsetX(M),y,m,n,f,h,e.segment,b,_,u,o,p));v.push(w.last)}else{if(i&&!n){var S=re(h,a).point,E=e.lineStartIndex+e.segment+1,L=new t.Point(u.getx(E),u.gety(E)),C=re(L,a),P=C.signedDistanceFromCamera>0?C.point:ue(h,L,S,1,a),O=se(e.writingMode,S,P,d);if(O)return O}var I=ce(g*l.getoffsetX(e.glyphStartIndex),y,m,n,f,h,e.segment,e.lineStartIndex,e.lineStartIndex+e.lineLength,u,o,p);if(!I)return{notEnoughRoom:!0};v=[I]}for(var D=0,z=v;D<z.length;D+=1){var R=z[D];t.addDynamicAttributes(c,R.point,R.angle)}return{}}function ue(t,e,r,n,i){var a=re(t.add(t.sub(e)._unit()),i).point,o=r.sub(a);return r.add(o._mult(n/o.mag()))}function ce(e,r,n,i,a,o,s,l,u,c,f,h){var p=i?e-r:e+r,d=p>0?1:-1,v=0;i&&(d*=-1,v=Math.PI),d<0&&(v+=Math.PI);for(var g=d>0?l+s:l+s+1,y=a,m=a,x=0,b=0,_=Math.abs(p),w=[];x+b<=_;){if((g+=d)<l||g>=u)return null;if(m=y,w.push(y),void 0===(y=h[g])){var T=new t.Point(c.getx(g),c.gety(g)),k=re(T,f);if(k.signedDistanceFromCamera>0)y=h[g]=k.point;else{var A=g-d;y=ue(0===x?o:new t.Point(c.getx(A),c.gety(A)),T,m,_-x+1,f)}}x+=b,b=m.dist(y)}var M=(_-x)/b,S=y.sub(m),E=S.mult(M)._add(m);E._add(S._unit()._perp()._mult(n*d));var L=v+Math.atan2(y.y-m.y,y.x-m.x);return w.push(E),{point:E,angle:L,path:w}}Qt.prototype.keysLength=function(){return this.boxKeys.length+this.circleKeys.length},Qt.prototype.insert=function(t,e,r,n,i){this._forEachCell(e,r,n,i,this._insertBoxCell,this.boxUid++),this.boxKeys.push(t),this.bboxes.push(e),this.bboxes.push(r),this.bboxes.push(n),this.bboxes.push(i)},Qt.prototype.insertCircle=function(t,e,r,n){this._forEachCell(e-n,r-n,e+n,r+n,this._insertCircleCell,this.circleUid++),this.circleKeys.push(t),this.circles.push(e),this.circles.push(r),this.circles.push(n)},Qt.prototype._insertBoxCell=function(t,e,r,n,i,a){this.boxCells[i].push(a)},Qt.prototype._insertCircleCell=function(t,e,r,n,i,a){this.circleCells[i].push(a)},Qt.prototype._query=function(t,e,r,n,i,a){if(r<0||t>this.width||n<0||e>this.height)return!i&&[];var o=[];if(t<=0&&e<=0&&this.width<=r&&this.height<=n){if(i)return!0;for(var s=0;s<this.boxKeys.length;s++)o.push({key:this.boxKeys[s],x1:this.bboxes[4*s],y1:this.bboxes[4*s+1],x2:this.bboxes[4*s+2],y2:this.bboxes[4*s+3]});for(var l=0;l<this.circleKeys.length;l++){var u=this.circles[3*l],c=this.circles[3*l+1],f=this.circles[3*l+2];o.push({key:this.circleKeys[l],x1:u-f,y1:c-f,x2:u+f,y2:c+f})}return a?o.filter(a):o}var h={hitTest:i,seenUids:{box:{},circle:{}}};return this._forEachCell(t,e,r,n,this._queryCell,o,h,a),i?o.length>0:o},Qt.prototype._queryCircle=function(t,e,r,n,i){var a=t-r,o=t+r,s=e-r,l=e+r;if(o<0||a>this.width||l<0||s>this.height)return!n&&[];var u=[],c={hitTest:n,circle:{x:t,y:e,radius:r},seenUids:{box:{},circle:{}}};return this._forEachCell(a,s,o,l,this._queryCellCircle,u,c,i),n?u.length>0:u},Qt.prototype.query=function(t,e,r,n,i){return this._query(t,e,r,n,!1,i)},Qt.prototype.hitTest=function(t,e,r,n,i){return this._query(t,e,r,n,!0,i)},Qt.prototype.hitTestCircle=function(t,e,r,n){return this._queryCircle(t,e,r,!0,n)},Qt.prototype._queryCell=function(t,e,r,n,i,a,o,s){var l=o.seenUids,u=this.boxCells[i];if(null!==u)for(var c=this.bboxes,f=0,h=u;f<h.length;f+=1){var p=h[f];if(!l.box[p]){l.box[p]=!0;var d=4*p;if(t<=c[d+2]&&e<=c[d+3]&&r>=c[d+0]&&n>=c[d+1]&&(!s||s(this.boxKeys[p]))){if(o.hitTest)return a.push(!0),!0;a.push({key:this.boxKeys[p],x1:c[d],y1:c[d+1],x2:c[d+2],y2:c[d+3]})}}}var v=this.circleCells[i];if(null!==v)for(var g=this.circles,y=0,m=v;y<m.length;y+=1){var x=m[y];if(!l.circle[x]){l.circle[x]=!0;var b=3*x;if(this._circleAndRectCollide(g[b],g[b+1],g[b+2],t,e,r,n)&&(!s||s(this.circleKeys[x]))){if(o.hitTest)return a.push(!0),!0;var _=g[b],w=g[b+1],T=g[b+2];a.push({key:this.circleKeys[x],x1:_-T,y1:w-T,x2:_+T,y2:w+T})}}}},Qt.prototype._queryCellCircle=function(t,e,r,n,i,a,o,s){var l=o.circle,u=o.seenUids,c=this.boxCells[i];if(null!==c)for(var f=this.bboxes,h=0,p=c;h<p.length;h+=1){var d=p[h];if(!u.box[d]){u.box[d]=!0;var v=4*d;if(this._circleAndRectCollide(l.x,l.y,l.radius,f[v+0],f[v+1],f[v+2],f[v+3])&&(!s||s(this.boxKeys[d])))return a.push(!0),!0}}var g=this.circleCells[i];if(null!==g)for(var y=this.circles,m=0,x=g;m<x.length;m+=1){var b=x[m];if(!u.circle[b]){u.circle[b]=!0;var _=3*b;if(this._circlesCollide(y[_],y[_+1],y[_+2],l.x,l.y,l.radius)&&(!s||s(this.circleKeys[b])))return a.push(!0),!0}}},Qt.prototype._forEachCell=function(t,e,r,n,i,a,o,s){for(var l=this._convertToXCellCoord(t),u=this._convertToYCellCoord(e),c=this._convertToXCellCoord(r),f=this._convertToYCellCoord(n),h=l;h<=c;h++)for(var p=u;p<=f;p++){var d=this.xCellCount*p+h;if(i.call(this,t,e,r,n,d,a,o,s))return}},Qt.prototype._convertToXCellCoord=function(t){return Math.max(0,Math.min(this.xCellCount-1,Math.floor(t*this.xScale)))},Qt.prototype._convertToYCellCoord=function(t){return Math.max(0,Math.min(this.yCellCount-1,Math.floor(t*this.yScale)))},Qt.prototype._circlesCollide=function(t,e,r,n,i,a){var o=n-t,s=i-e,l=r+a;return l*l>o*o+s*s},Qt.prototype._circleAndRectCollide=function(t,e,r,n,i,a,o){var s=(a-n)/2,l=Math.abs(t-(n+s));if(l>s+r)return!1;var u=(o-i)/2,c=Math.abs(e-(i+u));if(c>u+r)return!1;if(l<=s||c<=u)return!0;var f=l-s,h=c-u;return f*f+h*h<=r*r};var fe=new Float32Array([-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0]);function he(t,e){for(var r=0;r<t;r++){var n=e.length;e.resize(n+4),e.float32.set(fe,3*n)}}function pe(t,e,r){var n=e[0],i=e[1];return t[0]=r[0]*n+r[4]*i+r[12],t[1]=r[1]*n+r[5]*i+r[13],t[3]=r[3]*n+r[7]*i+r[15],t}var de=100,ve=function(t,e,r){void 0===e&&(e=new Qt(t.width+200,t.height+200,25)),void 0===r&&(r=new Qt(t.width+200,t.height+200,25)),this.transform=t,this.grid=e,this.ignoredGrid=r,this.pitchfactor=Math.cos(t._pitch)*t.cameraToCenterDistance,this.screenRightBoundary=t.width+de,this.screenBottomBoundary=t.height+de,this.gridRightBoundary=t.width+200,this.gridBottomBoundary=t.height+200};function ge(e,r,n){return r*(t.EXTENT/(e.tileSize*Math.pow(2,n-e.tileID.overscaledZ)))}ve.prototype.placeCollisionBox=function(t,e,r,n,i){var a=this.projectAndGetPerspectiveRatio(n,t.anchorPointX,t.anchorPointY),o=r*a.perspectiveRatio,s=t.x1*o+a.point.x,l=t.y1*o+a.point.y,u=t.x2*o+a.point.x,c=t.y2*o+a.point.y;return!this.isInsideGrid(s,l,u,c)||!e&&this.grid.hitTest(s,l,u,c,i)?{box:[],offscreen:!1}:{box:[s,l,u,c],offscreen:this.isOffscreen(s,l,u,c)}},ve.prototype.placeCollisionCircles=function(e,r,n,i,a,o,s,l,u,c,f,h,p){var d=[],v=new t.Point(r.anchorX,r.anchorY),g=re(v,o),y=ne(this.transform.cameraToCenterDistance,g.signedDistanceFromCamera),m=(c?a/y:a*y)/t.ONE_EM,x=re(v,s).point,b=oe(m,i,r.lineOffsetX*m,r.lineOffsetY*m,!1,x,v,r,n,s,{}),_=!1,w=!1,T=!0;if(b){for(var k=.5*h*y+p,A=new t.Point(-100,-100),M=new t.Point(this.screenRightBoundary,this.screenBottomBoundary),S=new $t,E=b.first,L=b.last,C=[],P=E.path.length-1;P>=1;P--)C.push(E.path[P]);for(var O=1;O<L.path.length;O++)C.push(L.path[O]);var I=2.5*k;if(l){var D=C.map((function(t){return re(t,l)}));C=D.some((function(t){return t.signedDistanceFromCamera<=0}))?[]:D.map((function(t){return t.point}))}var z=[];if(C.length>0){for(var R=C[0].clone(),F=C[0].clone(),B=1;B<C.length;B++)R.x=Math.min(R.x,C[B].x),R.y=Math.min(R.y,C[B].y),F.x=Math.max(F.x,C[B].x),F.y=Math.max(F.y,C[B].y);z=R.x>=A.x&&F.x<=M.x&&R.y>=A.y&&F.y<=M.y?[C]:F.x<A.x||R.x>M.x||F.y<A.y||R.y>M.y?[]:t.clipLine([C],A.x,A.y,M.x,M.y)}for(var N=0,j=z;N<j.length;N+=1){var U=j[N];S.reset(U,.25*k);var V;V=S.length<=.5*k?1:Math.ceil(S.paddedLength/I)+1;for(var q=0;q<V;q++){var H=q/Math.max(V-1,1),G=S.lerp(H),W=G.x+de,Y=G.y+de;d.push(W,Y,k,0);var X=W-k,Z=Y-k,K=W+k,J=Y+k;if(T=T&&this.isOffscreen(X,Z,K,J),w=w||this.isInsideGrid(X,Z,K,J),!e&&this.grid.hitTestCircle(W,Y,k,f)&&(_=!0,!u))return{circles:[],offscreen:!1,collisionDetected:_}}}}return{circles:!u&&_||!w?[]:d,offscreen:T,collisionDetected:_}},ve.prototype.queryRenderedSymbols=function(e){if(0===e.length||0===this.grid.keysLength()&&0===this.ignoredGrid.keysLength())return{};for(var r=[],n=1/0,i=1/0,a=-1/0,o=-1/0,s=0,l=e;s<l.length;s+=1){var u=l[s],c=new t.Point(u.x+de,u.y+de);n=Math.min(n,c.x),i=Math.min(i,c.y),a=Math.max(a,c.x),o=Math.max(o,c.y),r.push(c)}for(var f={},h={},p=0,d=this.grid.query(n,i,a,o).concat(this.ignoredGrid.query(n,i,a,o));p<d.length;p+=1){var v=d[p],g=v.key;if(void 0===f[g.bucketInstanceId]&&(f[g.bucketInstanceId]={}),!f[g.bucketInstanceId][g.featureIndex]){var y=[new t.Point(v.x1,v.y1),new t.Point(v.x2,v.y1),new t.Point(v.x2,v.y2),new t.Point(v.x1,v.y2)];t.polygonIntersectsPolygon(r,y)&&(f[g.bucketInstanceId][g.featureIndex]=!0,void 0===h[g.bucketInstanceId]&&(h[g.bucketInstanceId]=[]),h[g.bucketInstanceId].push(g.featureIndex))}}return h},ve.prototype.insertCollisionBox=function(t,e,r,n,i){var a={bucketInstanceId:r,featureIndex:n,collisionGroupID:i};(e?this.ignoredGrid:this.grid).insert(a,t[0],t[1],t[2],t[3])},ve.prototype.insertCollisionCircles=function(t,e,r,n,i){for(var a=e?this.ignoredGrid:this.grid,o={bucketInstanceId:r,featureIndex:n,collisionGroupID:i},s=0;s<t.length;s+=4)a.insertCircle(o,t[s],t[s+1],t[s+2])},ve.prototype.projectAndGetPerspectiveRatio=function(e,r,n){var i=[r,n,0,1];return pe(i,i,e),{point:new t.Point((i[0]/i[3]+1)/2*this.transform.width+de,(-i[1]/i[3]+1)/2*this.transform.height+de),perspectiveRatio:.5+this.transform.cameraToCenterDistance/i[3]*.5}},ve.prototype.isOffscreen=function(t,e,r,n){return r<de||t>=this.screenRightBoundary||n<de||e>this.screenBottomBoundary},ve.prototype.isInsideGrid=function(t,e,r,n){return r>=0&&t<this.gridRightBoundary&&n>=0&&e<this.gridBottomBoundary},ve.prototype.getViewportMatrix=function(){var e=t.identity([]);return t.translate(e,e,[-100,-100,0]),e};var ye=function(t,e,r,n){this.opacity=t?Math.max(0,Math.min(1,t.opacity+(t.placed?e:-e))):n&&r?1:0,this.placed=r};ye.prototype.isHidden=function(){return 0===this.opacity&&!this.placed};var me=function(t,e,r,n,i){this.text=new ye(t?t.text:null,e,r,i),this.icon=new ye(t?t.icon:null,e,n,i)};me.prototype.isHidden=function(){return this.text.isHidden()&&this.icon.isHidden()};var xe=function(t,e,r){this.text=t,this.icon=e,this.skipFade=r},be=function(){this.invProjMatrix=t.create(),this.viewportMatrix=t.create(),this.circles=[]},_e=function(t,e,r,n,i){this.bucketInstanceId=t,this.featureIndex=e,this.sourceLayerIndex=r,this.bucketIndex=n,this.tileID=i},we=function(t){this.crossSourceCollisions=t,this.maxGroupID=0,this.collisionGroups={}};function Te(e,r,n,i,a){var o=t.getAnchorAlignment(e),s=-(o.horizontalAlign-.5)*r,l=-(o.verticalAlign-.5)*n,u=t.evaluateVariableOffset(e,i);return new t.Point(s+u[0]*a,l+u[1]*a)}function ke(e,r,n,i,a,o){var s=e.x1,l=e.x2,u=e.y1,c=e.y2,f=e.anchorPointX,h=e.anchorPointY,p=new t.Point(r,n);return i&&p._rotate(a?o:-o),{x1:s+p.x,y1:u+p.y,x2:l+p.x,y2:c+p.y,anchorPointX:f,anchorPointY:h}}we.prototype.get=function(t){if(this.crossSourceCollisions)return{ID:0,predicate:null};if(!this.collisionGroups[t]){var e=++this.maxGroupID;this.collisionGroups[t]={ID:e,predicate:function(t){return t.collisionGroupID===e}}}return this.collisionGroups[t]};var Ae=function(t,e,r,n){this.transform=t.clone(),this.collisionIndex=new ve(this.transform),this.placements={},this.opacities={},this.variableOffsets={},this.stale=!1,this.commitTime=0,this.fadeDuration=e,this.retainedQueryData={},this.collisionGroups=new we(r),this.collisionCircleArrays={},this.prevPlacement=n,n&&(n.prevPlacement=void 0),this.placedOrientations={}};function Me(t,e,r,n,i){t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0)}Ae.prototype.getBucketParts=function(e,r,n,i){var a=n.getBucket(r),o=n.latestFeatureIndex;if(a&&o&&r.id===a.layerIds[0]){var s=n.collisionBoxArray,l=a.layers[0].layout,u=Math.pow(2,this.transform.zoom-n.tileID.overscaledZ),c=n.tileSize/t.EXTENT,f=this.transform.calculatePosMatrix(n.tileID.toUnwrapped()),h=\"map\"===l.get(\"text-pitch-alignment\"),p=\"map\"===l.get(\"text-rotation-alignment\"),d=ge(n,1,this.transform.zoom),v=te(f,h,p,this.transform,d),g=null;if(h){var y=ee(f,h,p,this.transform,d);g=t.multiply([],this.transform.labelPlaneMatrix,y)}this.retainedQueryData[a.bucketInstanceId]=new _e(a.bucketInstanceId,o,a.sourceLayerIndex,a.index,n.tileID);var m={bucket:a,layout:l,posMatrix:f,textLabelPlaneMatrix:v,labelToScreenMatrix:g,scale:u,textPixelRatio:c,holdingForFade:n.holdingForFade(),collisionBoxArray:s,partiallyEvaluatedTextSize:t.evaluateSizeForZoom(a.textSizeData,this.transform.zoom),collisionGroup:this.collisionGroups.get(a.sourceID)};if(i)for(var x=0,b=a.sortKeyRanges;x<b.length;x+=1){var _=b[x],w=_.sortKey,T=_.symbolInstanceStart,k=_.symbolInstanceEnd;e.push({sortKey:w,symbolInstanceStart:T,symbolInstanceEnd:k,parameters:m})}else e.push({symbolInstanceStart:0,symbolInstanceEnd:a.symbolInstances.length,parameters:m})}},Ae.prototype.attemptAnchorPlacement=function(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d){var v,g=[f.textOffset0,f.textOffset1],y=Te(t,r,n,g,i),m=this.collisionIndex.placeCollisionBox(ke(e,y.x,y.y,a,o,this.transform.angle),c,s,l,u.predicate);if(!d||0!==this.collisionIndex.placeCollisionBox(ke(d,y.x,y.y,a,o,this.transform.angle),c,s,l,u.predicate).box.length)return m.box.length>0?(this.prevPlacement&&this.prevPlacement.variableOffsets[f.crossTileID]&&this.prevPlacement.placements[f.crossTileID]&&this.prevPlacement.placements[f.crossTileID].text&&(v=this.prevPlacement.variableOffsets[f.crossTileID].anchor),this.variableOffsets[f.crossTileID]={textOffset:g,width:r,height:n,anchor:t,textBoxScale:i,prevAnchor:v},this.markUsedJustification(h,t,f,p),h.allowVerticalPlacement&&(this.markUsedOrientation(h,p,f),this.placedOrientations[f.crossTileID]=p),{shift:y,placedGlyphBoxes:m}):void 0},Ae.prototype.placeLayerBucketPart=function(e,r,n){var i=this,a=e.parameters,o=a.bucket,s=a.layout,l=a.posMatrix,u=a.textLabelPlaneMatrix,c=a.labelToScreenMatrix,f=a.textPixelRatio,h=a.holdingForFade,p=a.collisionBoxArray,d=a.partiallyEvaluatedTextSize,v=a.collisionGroup,g=s.get(\"text-optional\"),y=s.get(\"icon-optional\"),m=s.get(\"text-allow-overlap\"),x=s.get(\"icon-allow-overlap\"),b=\"map\"===s.get(\"text-rotation-alignment\"),_=\"map\"===s.get(\"text-pitch-alignment\"),w=\"none\"!==s.get(\"icon-text-fit\"),T=\"viewport-y\"===s.get(\"symbol-z-order\"),k=m&&(x||!o.hasIconData()||y),A=x&&(m||!o.hasTextData()||g);!o.collisionArrays&&p&&o.deserializeCollisionBoxes(p);var M=function(e,a){if(!r[e.crossTileID])if(h)i.placements[e.crossTileID]=new xe(!1,!1,!1);else{var p,T=!1,M=!1,S=!0,E=null,L={box:null,offscreen:null},C={box:null,offscreen:null},P=null,O=null,I=0,D=0,z=0;a.textFeatureIndex?I=a.textFeatureIndex:e.useRuntimeCollisionCircles&&(I=e.featureIndex),a.verticalTextFeatureIndex&&(D=a.verticalTextFeatureIndex);var R=a.textBox;if(R){var F=function(r){var n=t.WritingMode.horizontal;if(o.allowVerticalPlacement&&!r&&i.prevPlacement){var a=i.prevPlacement.placedOrientations[e.crossTileID];a&&(i.placedOrientations[e.crossTileID]=a,n=a,i.markUsedOrientation(o,n,e))}return n},B=function(r,n){if(o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&a.verticalTextBox)for(var i=0,s=o.writingModes;i<s.length&&(s[i]===t.WritingMode.vertical?(L=n(),C=L):L=r(),!(L&&L.box&&L.box.length));i+=1);else L=r()};if(s.get(\"text-variable-anchor\")){var N=s.get(\"text-variable-anchor\");if(i.prevPlacement&&i.prevPlacement.variableOffsets[e.crossTileID]){var j=i.prevPlacement.variableOffsets[e.crossTileID];N.indexOf(j.anchor)>0&&(N=N.filter((function(t){return t!==j.anchor}))).unshift(j.anchor)}var U=function(t,r,n){for(var a=t.x2-t.x1,s=t.y2-t.y1,u=e.textBoxScale,c=w&&!x?r:null,h={box:[],offscreen:!1},p=m?2*N.length:N.length,d=0;d<p;++d){var g=N[d%N.length],y=d>=N.length,k=i.attemptAnchorPlacement(g,t,a,s,u,b,_,f,l,v,y,e,o,n,c);if(k&&(h=k.placedGlyphBoxes)&&h.box&&h.box.length){T=!0,E=k.shift;break}}return h};B((function(){return U(R,a.iconBox,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox,n=L&&L.box&&L.box.length;return o.allowVerticalPlacement&&!n&&e.numVerticalGlyphVertices>0&&r?U(r,a.verticalIconBox,t.WritingMode.vertical):{box:null,offscreen:null}})),L&&(T=L.box,S=L.offscreen);var V=F(L&&L.box);if(!T&&i.prevPlacement){var q=i.prevPlacement.variableOffsets[e.crossTileID];q&&(i.variableOffsets[e.crossTileID]=q,i.markUsedJustification(o,q.anchor,e,V))}}else{var H=function(t,r){var n=i.collisionIndex.placeCollisionBox(t,m,f,l,v.predicate);return n&&n.box&&n.box.length&&(i.markUsedOrientation(o,r,e),i.placedOrientations[e.crossTileID]=r),n};B((function(){return H(R,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox;return o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&r?H(r,t.WritingMode.vertical):{box:null,offscreen:null}})),F(L&&L.box&&L.box.length)}}if(T=(p=L)&&p.box&&p.box.length>0,S=p&&p.offscreen,e.useRuntimeCollisionCircles){var G=o.text.placedSymbolArray.get(e.centerJustifiedTextSymbolIndex),W=t.evaluateSizeForFeature(o.textSizeData,d,G),Y=s.get(\"text-padding\"),X=e.collisionCircleDiameter;P=i.collisionIndex.placeCollisionCircles(m,G,o.lineVertexArray,o.glyphOffsetArray,W,l,u,c,n,_,v.predicate,X,Y),T=m||P.circles.length>0&&!P.collisionDetected,S=S&&P.offscreen}if(a.iconFeatureIndex&&(z=a.iconFeatureIndex),a.iconBox){var Z=function(t){var e=w&&E?ke(t,E.x,E.y,b,_,i.transform.angle):t;return i.collisionIndex.placeCollisionBox(e,x,f,l,v.predicate)};M=C&&C.box&&C.box.length&&a.verticalIconBox?(O=Z(a.verticalIconBox)).box.length>0:(O=Z(a.iconBox)).box.length>0,S=S&&O.offscreen}var K=g||0===e.numHorizontalGlyphVertices&&0===e.numVerticalGlyphVertices,J=y||0===e.numIconVertices;if(K||J?J?K||(M=M&&T):T=M&&T:M=T=M&&T,T&&p&&p.box&&(C&&C.box&&D?i.collisionIndex.insertCollisionBox(p.box,s.get(\"text-ignore-placement\"),o.bucketInstanceId,D,v.ID):i.collisionIndex.insertCollisionBox(p.box,s.get(\"text-ignore-placement\"),o.bucketInstanceId,I,v.ID)),M&&O&&i.collisionIndex.insertCollisionBox(O.box,s.get(\"icon-ignore-placement\"),o.bucketInstanceId,z,v.ID),P&&(T&&i.collisionIndex.insertCollisionCircles(P.circles,s.get(\"text-ignore-placement\"),o.bucketInstanceId,I,v.ID),n)){var $=o.bucketInstanceId,Q=i.collisionCircleArrays[$];void 0===Q&&(Q=i.collisionCircleArrays[$]=new be);for(var tt=0;tt<P.circles.length;tt+=4)Q.circles.push(P.circles[tt+0]),Q.circles.push(P.circles[tt+1]),Q.circles.push(P.circles[tt+2]),Q.circles.push(P.collisionDetected?1:0)}i.placements[e.crossTileID]=new xe(T||k,M||A,S||o.justReloaded),r[e.crossTileID]=!0}};if(T)for(var S=o.getSortedSymbolIndexes(this.transform.angle),E=S.length-1;E>=0;--E){var L=S[E];M(o.symbolInstances.get(L),o.collisionArrays[L])}else for(var C=e.symbolInstanceStart;C<e.symbolInstanceEnd;C++)M(o.symbolInstances.get(C),o.collisionArrays[C]);if(n&&o.bucketInstanceId in this.collisionCircleArrays){var P=this.collisionCircleArrays[o.bucketInstanceId];t.invert(P.invProjMatrix,l),P.viewportMatrix=this.collisionIndex.getViewportMatrix()}o.justReloaded=!1},Ae.prototype.markUsedJustification=function(e,r,n,i){var a,o={left:n.leftJustifiedTextSymbolIndex,center:n.centerJustifiedTextSymbolIndex,right:n.rightJustifiedTextSymbolIndex};a=i===t.WritingMode.vertical?n.verticalPlacedTextSymbolIndex:o[t.getAnchorJustification(r)];for(var s=0,l=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex,n.verticalPlacedTextSymbolIndex];s<l.length;s+=1){var u=l[s];u>=0&&(e.text.placedSymbolArray.get(u).crossTileID=a>=0&&u!==a?0:n.crossTileID)}},Ae.prototype.markUsedOrientation=function(e,r,n){for(var i=r===t.WritingMode.horizontal||r===t.WritingMode.horizontalOnly?r:0,a=r===t.WritingMode.vertical?r:0,o=0,s=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex];o<s.length;o+=1){var l=s[o];e.text.placedSymbolArray.get(l).placedOrientation=i}n.verticalPlacedTextSymbolIndex&&(e.text.placedSymbolArray.get(n.verticalPlacedTextSymbolIndex).placedOrientation=a)},Ae.prototype.commit=function(t){this.commitTime=t,this.zoomAtLastRecencyCheck=this.transform.zoom;var e=this.prevPlacement,r=!1;this.prevZoomAdjustment=e?e.zoomAdjustment(this.transform.zoom):0;var n=e?e.symbolFadeChange(t):1,i=e?e.opacities:{},a=e?e.variableOffsets:{},o=e?e.placedOrientations:{};for(var s in this.placements){var l=this.placements[s],u=i[s];u?(this.opacities[s]=new me(u,n,l.text,l.icon),r=r||l.text!==u.text.placed||l.icon!==u.icon.placed):(this.opacities[s]=new me(null,n,l.text,l.icon,l.skipFade),r=r||l.text||l.icon)}for(var c in i){var f=i[c];if(!this.opacities[c]){var h=new me(f,n,!1,!1);h.isHidden()||(this.opacities[c]=h,r=r||f.text.placed||f.icon.placed)}}for(var p in a)this.variableOffsets[p]||!this.opacities[p]||this.opacities[p].isHidden()||(this.variableOffsets[p]=a[p]);for(var d in o)this.placedOrientations[d]||!this.opacities[d]||this.opacities[d].isHidden()||(this.placedOrientations[d]=o[d]);r?this.lastPlacementChangeTime=t:\"number\"!=typeof this.lastPlacementChangeTime&&(this.lastPlacementChangeTime=e?e.lastPlacementChangeTime:t)},Ae.prototype.updateLayerOpacities=function(t,e){for(var r={},n=0,i=e;n<i.length;n+=1){var a=i[n],o=a.getBucket(t);o&&a.latestFeatureIndex&&t.id===o.layerIds[0]&&this.updateBucketOpacities(o,r,a.collisionBoxArray)}},Ae.prototype.updateBucketOpacities=function(e,r,n){var i=this;e.hasTextData()&&e.text.opacityVertexArray.clear(),e.hasIconData()&&e.icon.opacityVertexArray.clear(),e.hasIconCollisionBoxData()&&e.iconCollisionBox.collisionVertexArray.clear(),e.hasTextCollisionBoxData()&&e.textCollisionBox.collisionVertexArray.clear();var a=e.layers[0].layout,o=new me(null,0,!1,!1,!0),s=a.get(\"text-allow-overlap\"),l=a.get(\"icon-allow-overlap\"),u=a.get(\"text-variable-anchor\"),c=\"map\"===a.get(\"text-rotation-alignment\"),f=\"map\"===a.get(\"text-pitch-alignment\"),h=\"none\"!==a.get(\"icon-text-fit\"),p=new me(null,0,s&&(l||!e.hasIconData()||a.get(\"icon-optional\")),l&&(s||!e.hasTextData()||a.get(\"text-optional\")),!0);!e.collisionArrays&&n&&(e.hasIconCollisionBoxData()||e.hasTextCollisionBoxData())&&e.deserializeCollisionBoxes(n);for(var d=function(t,e,r){for(var n=0;n<e/4;n++)t.opacityVertexArray.emplaceBack(r)},v=function(n){var a=e.symbolInstances.get(n),s=a.numHorizontalGlyphVertices,l=a.numVerticalGlyphVertices,v=a.crossTileID,g=r[v],y=i.opacities[v];g?y=o:y||(y=p,i.opacities[v]=y),r[v]=!0;var m=s>0||l>0,x=a.numIconVertices>0,b=i.placedOrientations[a.crossTileID],_=b===t.WritingMode.vertical,w=b===t.WritingMode.horizontal||b===t.WritingMode.horizontalOnly;if(m){var T=De(y.text),k=_?ze:T;d(e.text,s,k);var A=w?ze:T;d(e.text,l,A);var M=y.text.isHidden();[a.rightJustifiedTextSymbolIndex,a.centerJustifiedTextSymbolIndex,a.leftJustifiedTextSymbolIndex].forEach((function(t){t>=0&&(e.text.placedSymbolArray.get(t).hidden=M||_?1:0)})),a.verticalPlacedTextSymbolIndex>=0&&(e.text.placedSymbolArray.get(a.verticalPlacedTextSymbolIndex).hidden=M||w?1:0);var S=i.variableOffsets[a.crossTileID];S&&i.markUsedJustification(e,S.anchor,a,b);var E=i.placedOrientations[a.crossTileID];E&&(i.markUsedJustification(e,\"left\",a,E),i.markUsedOrientation(e,E,a))}if(x){var L=De(y.icon),C=!(h&&a.verticalPlacedIconSymbolIndex&&_);if(a.placedIconSymbolIndex>=0){var P=C?L:ze;d(e.icon,a.numIconVertices,P),e.icon.placedSymbolArray.get(a.placedIconSymbolIndex).hidden=y.icon.isHidden()}if(a.verticalPlacedIconSymbolIndex>=0){var O=C?ze:L;d(e.icon,a.numVerticalIconVertices,O),e.icon.placedSymbolArray.get(a.verticalPlacedIconSymbolIndex).hidden=y.icon.isHidden()}}if(e.hasIconCollisionBoxData()||e.hasTextCollisionBoxData()){var I=e.collisionArrays[n];if(I){var D=new t.Point(0,0);if(I.textBox||I.verticalTextBox){var z=!0;if(u){var R=i.variableOffsets[v];R?(D=Te(R.anchor,R.width,R.height,R.textOffset,R.textBoxScale),c&&D._rotate(f?i.transform.angle:-i.transform.angle)):z=!1}I.textBox&&Me(e.textCollisionBox.collisionVertexArray,y.text.placed,!z||_,D.x,D.y),I.verticalTextBox&&Me(e.textCollisionBox.collisionVertexArray,y.text.placed,!z||w,D.x,D.y)}var F=Boolean(!w&&I.verticalIconBox);I.iconBox&&Me(e.iconCollisionBox.collisionVertexArray,y.icon.placed,F,h?D.x:0,h?D.y:0),I.verticalIconBox&&Me(e.iconCollisionBox.collisionVertexArray,y.icon.placed,!F,h?D.x:0,h?D.y:0)}}},g=0;g<e.symbolInstances.length;g++)v(g);if(e.sortFeatures(this.transform.angle),this.retainedQueryData[e.bucketInstanceId]&&(this.retainedQueryData[e.bucketInstanceId].featureSortOrder=e.featureSortOrder),e.hasTextData()&&e.text.opacityVertexBuffer&&e.text.opacityVertexBuffer.updateData(e.text.opacityVertexArray),e.hasIconData()&&e.icon.opacityVertexBuffer&&e.icon.opacityVertexBuffer.updateData(e.icon.opacityVertexArray),e.hasIconCollisionBoxData()&&e.iconCollisionBox.collisionVertexBuffer&&e.iconCollisionBox.collisionVertexBuffer.updateData(e.iconCollisionBox.collisionVertexArray),e.hasTextCollisionBoxData()&&e.textCollisionBox.collisionVertexBuffer&&e.textCollisionBox.collisionVertexBuffer.updateData(e.textCollisionBox.collisionVertexArray),e.bucketInstanceId in this.collisionCircleArrays){var y=this.collisionCircleArrays[e.bucketInstanceId];e.placementInvProjMatrix=y.invProjMatrix,e.placementViewportMatrix=y.viewportMatrix,e.collisionCircleArray=y.circles,delete this.collisionCircleArrays[e.bucketInstanceId]}},Ae.prototype.symbolFadeChange=function(t){return 0===this.fadeDuration?1:(t-this.commitTime)/this.fadeDuration+this.prevZoomAdjustment},Ae.prototype.zoomAdjustment=function(t){return Math.max(0,(this.transform.zoom-t)/1.5)},Ae.prototype.hasTransitions=function(t){return this.stale||t-this.lastPlacementChangeTime<this.fadeDuration},Ae.prototype.stillRecent=function(t,e){var r=this.zoomAtLastRecencyCheck===e?1-this.zoomAdjustment(e):1;return this.zoomAtLastRecencyCheck=e,this.commitTime+this.fadeDuration*r>t},Ae.prototype.setStale=function(){this.stale=!0};var Se=Math.pow(2,25),Ee=Math.pow(2,24),Le=Math.pow(2,17),Ce=Math.pow(2,16),Pe=Math.pow(2,9),Oe=Math.pow(2,8),Ie=Math.pow(2,1);function De(t){if(0===t.opacity&&!t.placed)return 0;if(1===t.opacity&&t.placed)return 4294967295;var e=t.placed?1:0,r=Math.floor(127*t.opacity);return r*Se+e*Ee+r*Le+e*Ce+r*Pe+e*Oe+r*Ie+e}var ze=0,Re=function(t){this._sortAcrossTiles=\"viewport-y\"!==t.layout.get(\"symbol-z-order\")&&void 0!==t.layout.get(\"symbol-sort-key\").constantOr(1),this._currentTileIndex=0,this._currentPartIndex=0,this._seenCrossTileIDs={},this._bucketParts=[]};Re.prototype.continuePlacement=function(t,e,r,n,i){for(var a=this._bucketParts;this._currentTileIndex<t.length;){var o=t[this._currentTileIndex];if(e.getBucketParts(a,n,o,this._sortAcrossTiles),this._currentTileIndex++,i())return!0}for(this._sortAcrossTiles&&(this._sortAcrossTiles=!1,a.sort((function(t,e){return t.sortKey-e.sortKey})));this._currentPartIndex<a.length;){var s=a[this._currentPartIndex];if(e.placeLayerBucketPart(s,this._seenCrossTileIDs,r),this._currentPartIndex++,i())return!0}return!1};var Fe=function(t,e,r,n,i,a,o){this.placement=new Ae(t,i,a,o),this._currentPlacementIndex=e.length-1,this._forceFullPlacement=r,this._showCollisionBoxes=n,this._done=!1};Fe.prototype.isDone=function(){return this._done},Fe.prototype.continuePlacement=function(e,r,n){for(var i=this,a=t.browser.now(),o=function(){var e=t.browser.now()-a;return!i._forceFullPlacement&&e>2};this._currentPlacementIndex>=0;){var s=r[e[this._currentPlacementIndex]],l=this.placement.collisionIndex.transform.zoom;if(\"symbol\"===s.type&&(!s.minzoom||s.minzoom<=l)&&(!s.maxzoom||s.maxzoom>l)){if(this._inProgressLayer||(this._inProgressLayer=new Re(s)),this._inProgressLayer.continuePlacement(n[s.source],this.placement,this._showCollisionBoxes,s,o))return;delete this._inProgressLayer}this._currentPlacementIndex--}this._done=!0},Fe.prototype.commit=function(t){return this.placement.commit(t),this.placement};var Be=512/t.EXTENT/2,Ne=function(t,e,r){this.tileID=t,this.indexedSymbolInstances={},this.bucketInstanceId=r;for(var n=0;n<e.length;n++){var i=e.get(n),a=i.key;this.indexedSymbolInstances[a]||(this.indexedSymbolInstances[a]=[]),this.indexedSymbolInstances[a].push({crossTileID:i.crossTileID,coord:this.getScaledCoordinates(i,t)})}};Ne.prototype.getScaledCoordinates=function(e,r){var n=r.canonical.z-this.tileID.canonical.z,i=Be/Math.pow(2,n);return{x:Math.floor((r.canonical.x*t.EXTENT+e.anchorX)*i),y:Math.floor((r.canonical.y*t.EXTENT+e.anchorY)*i)}},Ne.prototype.findMatches=function(t,e,r){for(var n=this.tileID.canonical.z<e.canonical.z?1:Math.pow(2,this.tileID.canonical.z-e.canonical.z),i=0;i<t.length;i++){var a=t.get(i);if(!a.crossTileID){var o=this.indexedSymbolInstances[a.key];if(o)for(var s=this.getScaledCoordinates(a,e),l=0,u=o;l<u.length;l+=1){var c=u[l];if(Math.abs(c.coord.x-s.x)<=n&&Math.abs(c.coord.y-s.y)<=n&&!r[c.crossTileID]){r[c.crossTileID]=!0,a.crossTileID=c.crossTileID;break}}}}};var je=function(){this.maxCrossTileID=0};je.prototype.generate=function(){return++this.maxCrossTileID};var Ue=function(){this.indexes={},this.usedCrossTileIDs={},this.lng=0};Ue.prototype.handleWrapJump=function(t){var e=Math.round((t-this.lng)/360);if(0!==e)for(var r in this.indexes){var n=this.indexes[r],i={};for(var a in n){var o=n[a];o.tileID=o.tileID.unwrapTo(o.tileID.wrap+e),i[o.tileID.key]=o}this.indexes[r]=i}this.lng=t},Ue.prototype.addBucket=function(t,e,r){if(this.indexes[t.overscaledZ]&&this.indexes[t.overscaledZ][t.key]){if(this.indexes[t.overscaledZ][t.key].bucketInstanceId===e.bucketInstanceId)return!1;this.removeBucketCrossTileIDs(t.overscaledZ,this.indexes[t.overscaledZ][t.key])}for(var n=0;n<e.symbolInstances.length;n++)e.symbolInstances.get(n).crossTileID=0;this.usedCrossTileIDs[t.overscaledZ]||(this.usedCrossTileIDs[t.overscaledZ]={});var i=this.usedCrossTileIDs[t.overscaledZ];for(var a in this.indexes){var o=this.indexes[a];if(Number(a)>t.overscaledZ)for(var s in o){var l=o[s];l.tileID.isChildOf(t)&&l.findMatches(e.symbolInstances,t,i)}else{var u=o[t.scaledTo(Number(a)).key];u&&u.findMatches(e.symbolInstances,t,i)}}for(var c=0;c<e.symbolInstances.length;c++){var f=e.symbolInstances.get(c);f.crossTileID||(f.crossTileID=r.generate(),i[f.crossTileID]=!0)}return void 0===this.indexes[t.overscaledZ]&&(this.indexes[t.overscaledZ]={}),this.indexes[t.overscaledZ][t.key]=new Ne(t,e.symbolInstances,e.bucketInstanceId),!0},Ue.prototype.removeBucketCrossTileIDs=function(t,e){for(var r in e.indexedSymbolInstances)for(var n=0,i=e.indexedSymbolInstances[r];n<i.length;n+=1){var a=i[n];delete this.usedCrossTileIDs[t][a.crossTileID]}},Ue.prototype.removeStaleBuckets=function(t){var e=!1;for(var r in this.indexes){var n=this.indexes[r];for(var i in n)t[n[i].bucketInstanceId]||(this.removeBucketCrossTileIDs(r,n[i]),delete n[i],e=!0)}return e};var Ve=function(){this.layerIndexes={},this.crossTileIDs=new je,this.maxBucketInstanceId=0,this.bucketsInCurrentPlacement={}};Ve.prototype.addLayer=function(t,e,r){var n=this.layerIndexes[t.id];void 0===n&&(n=this.layerIndexes[t.id]=new Ue);var i=!1,a={};n.handleWrapJump(r);for(var o=0,s=e;o<s.length;o+=1){var l=s[o],u=l.getBucket(t);u&&t.id===u.layerIds[0]&&(u.bucketInstanceId||(u.bucketInstanceId=++this.maxBucketInstanceId),n.addBucket(l.tileID,u,this.crossTileIDs)&&(i=!0),a[u.bucketInstanceId]=!0)}return n.removeStaleBuckets(a)&&(i=!0),i},Ve.prototype.pruneUnusedLayers=function(t){var e={};for(var r in t.forEach((function(t){e[t]=!0})),this.layerIndexes)e[r]||delete this.layerIndexes[r]};var qe=function(e,r){return t.emitValidationErrors(e,r&&r.filter((function(t){return\"source.canvas\"!==t.identifier})))},He=t.pick(qt,[\"addLayer\",\"removeLayer\",\"setPaintProperty\",\"setLayoutProperty\",\"setFilter\",\"addSource\",\"removeSource\",\"setLayerZoomRange\",\"setLight\",\"setTransition\",\"setGeoJSONSourceData\"]),Ge=t.pick(qt,[\"setCenter\",\"setZoom\",\"setBearing\",\"setPitch\"]),We=function(){var e={},r=t.styleSpec.$version;for(var n in t.styleSpec.$root){var i=t.styleSpec.$root[n];if(i.required){var a;null!=(a=\"version\"===n?r:\"array\"===i.type?[]:{})&&(e[n]=a)}}return e}(),Ye=function(e){function r(n,i){var a=this;void 0===i&&(i={}),e.call(this),this.map=n,this.dispatcher=new A(jt(),this),this.imageManager=new h,this.imageManager.setEventedParent(this),this.glyphManager=new x(n._requestManager,i.localIdeographFontFamily),this.lineAtlas=new k(256,512),this.crossTileSymbolIndex=new Ve,this._layers={},this._serializedLayers={},this._order=[],this.sourceCaches={},this.zoomHistory=new t.ZoomHistory,this._loaded=!1,this._availableImages=[],this._resetUpdates(),this.dispatcher.broadcast(\"setReferrer\",t.getReferrer());var o=this;this._rtlTextPluginCallback=r.registerForPluginStateChange((function(e){var r={pluginStatus:e.pluginStatus,pluginURL:e.pluginURL};o.dispatcher.broadcast(\"syncRTLPluginState\",r,(function(e,r){if(t.triggerPluginCompletionEvent(e),r&&r.every((function(t){return t})))for(var n in o.sourceCaches)o.sourceCaches[n].reload()}))})),this.on(\"data\",(function(t){if(\"source\"===t.dataType&&\"metadata\"===t.sourceDataType){var e=a.sourceCaches[t.sourceId];if(e){var r=e.getSource();if(r&&r.vectorLayerIds)for(var n in a._layers){var i=a._layers[n];i.source===r.id&&a._validateLayer(i)}}}}))}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.loadURL=function(e,r){var n=this;void 0===r&&(r={}),this.fire(new t.Event(\"dataloading\",{dataType:\"style\"}));var i=\"boolean\"==typeof r.validate?r.validate:!t.isMapboxURL(e);e=this.map._requestManager.normalizeStyleURL(e,r.accessToken);var a=this.map._requestManager.transformRequest(e,t.ResourceType.Style);this._request=t.getJSON(a,(function(e,r){n._request=null,e?n.fire(new t.ErrorEvent(e)):r&&n._load(r,i)}))},r.prototype.loadJSON=function(e,r){var n=this;void 0===r&&(r={}),this.fire(new t.Event(\"dataloading\",{dataType:\"style\"})),this._request=t.browser.frame((function(){n._request=null,n._load(e,!1!==r.validate)}))},r.prototype.loadEmpty=function(){this.fire(new t.Event(\"dataloading\",{dataType:\"style\"})),this._load(We,!1)},r.prototype._load=function(e,r){if(!r||!qe(this,t.validateStyle(e))){for(var n in this._loaded=!0,this.stylesheet=e,e.sources)this.addSource(n,e.sources[n],{validate:!1});e.sprite?this._loadSprite(e.sprite):this.imageManager.setLoaded(!0),this.glyphManager.setURL(e.glyphs);var i=Vt(this.stylesheet.layers);this._order=i.map((function(t){return t.id})),this._layers={},this._serializedLayers={};for(var a=0,o=i;a<o.length;a+=1){var s=o[a];(s=t.createStyleLayer(s)).setEventedParent(this,{layer:{id:s.id}}),this._layers[s.id]=s,this._serializedLayers[s.id]=s.serialize()}this.dispatcher.broadcast(\"setLayers\",this._serializeLayers(this._order)),this.light=new T(this.stylesheet.light),this.fire(new t.Event(\"data\",{dataType:\"style\"})),this.fire(new t.Event(\"style.load\"))}},r.prototype._loadSprite=function(e){var r=this;this._spriteRequest=function(e,r,n){var i,a,o,s=t.browser.devicePixelRatio>1?\"@2x\":\"\",l=t.getJSON(r.transformRequest(r.normalizeSpriteURL(e,s,\".json\"),t.ResourceType.SpriteJSON),(function(t,e){l=null,o||(o=t,i=e,c())})),u=t.getImage(r.transformRequest(r.normalizeSpriteURL(e,s,\".png\"),t.ResourceType.SpriteImage),(function(t,e){u=null,o||(o=t,a=e,c())}));function c(){if(o)n(o);else if(i&&a){var e=t.browser.getImageData(a),r={};for(var s in i){var l=i[s],u=l.width,c=l.height,f=l.x,h=l.y,p=l.sdf,d=l.pixelRatio,v=l.stretchX,g=l.stretchY,y=l.content,m=new t.RGBAImage({width:u,height:c});t.RGBAImage.copy(e,m,{x:f,y:h},{x:0,y:0},{width:u,height:c}),r[s]={data:m,pixelRatio:d,sdf:p,stretchX:v,stretchY:g,content:y}}n(null,r)}}return{cancel:function(){l&&(l.cancel(),l=null),u&&(u.cancel(),u=null)}}}(e,this.map._requestManager,(function(e,n){if(r._spriteRequest=null,e)r.fire(new t.ErrorEvent(e));else if(n)for(var i in n)r.imageManager.addImage(i,n[i]);r.imageManager.setLoaded(!0),r._availableImages=r.imageManager.listImages(),r.dispatcher.broadcast(\"setImages\",r._availableImages),r.fire(new t.Event(\"data\",{dataType:\"style\"}))}))},r.prototype._validateLayer=function(e){var r=this.sourceCaches[e.source];if(r){var n=e.sourceLayer;if(n){var i=r.getSource();(\"geojson\"===i.type||i.vectorLayerIds&&-1===i.vectorLayerIds.indexOf(n))&&this.fire(new t.ErrorEvent(new Error('Source layer \"'+n+'\" does not exist on source \"'+i.id+'\" as specified by style layer \"'+e.id+'\"')))}}},r.prototype.loaded=function(){if(!this._loaded)return!1;if(Object.keys(this._updatedSources).length)return!1;for(var t in this.sourceCaches)if(!this.sourceCaches[t].loaded())return!1;return!!this.imageManager.isLoaded()},r.prototype._serializeLayers=function(t){for(var e=[],r=0,n=t;r<n.length;r+=1){var i=n[r],a=this._layers[i];\"custom\"!==a.type&&e.push(a.serialize())}return e},r.prototype.hasTransitions=function(){if(this.light&&this.light.hasTransition())return!0;for(var t in this.sourceCaches)if(this.sourceCaches[t].hasTransition())return!0;for(var e in this._layers)if(this._layers[e].hasTransition())return!0;return!1},r.prototype._checkLoaded=function(){if(!this._loaded)throw new Error(\"Style is not done loading\")},r.prototype.update=function(e){if(this._loaded){var r=this._changed;if(this._changed){var n=Object.keys(this._updatedLayers),i=Object.keys(this._removedLayers);for(var a in(n.length||i.length)&&this._updateWorkerLayers(n,i),this._updatedSources){var o=this._updatedSources[a];\"reload\"===o?this._reloadSource(a):\"clear\"===o&&this._clearSource(a)}for(var s in this._updateTilesForChangedImages(),this._updatedPaintProps)this._layers[s].updateTransitions(e);this.light.updateTransitions(e),this._resetUpdates()}var l={};for(var u in this.sourceCaches){var c=this.sourceCaches[u];l[u]=c.used,c.used=!1}for(var f=0,h=this._order;f<h.length;f+=1){var p=h[f],d=this._layers[p];d.recalculate(e,this._availableImages),!d.isHidden(e.zoom)&&d.source&&(this.sourceCaches[d.source].used=!0)}for(var v in l){var g=this.sourceCaches[v];l[v]!==g.used&&g.fire(new t.Event(\"data\",{sourceDataType:\"visibility\",dataType:\"source\",sourceId:v}))}this.light.recalculate(e),this.z=e.zoom,r&&this.fire(new t.Event(\"data\",{dataType:\"style\"}))}},r.prototype._updateTilesForChangedImages=function(){var t=Object.keys(this._changedImages);if(t.length){for(var e in this.sourceCaches)this.sourceCaches[e].reloadTilesForDependencies([\"icons\",\"patterns\"],t);this._changedImages={}}},r.prototype._updateWorkerLayers=function(t,e){this.dispatcher.broadcast(\"updateLayers\",{layers:this._serializeLayers(t),removedIds:e})},r.prototype._resetUpdates=function(){this._changed=!1,this._updatedLayers={},this._removedLayers={},this._updatedSources={},this._updatedPaintProps={},this._changedImages={}},r.prototype.setState=function(e){var r=this;if(this._checkLoaded(),qe(this,t.validateStyle(e)))return!1;(e=t.clone$1(e)).layers=Vt(e.layers);var n=Jt(this.serialize(),e).filter((function(t){return!(t.command in Ge)}));if(0===n.length)return!1;var i=n.filter((function(t){return!(t.command in He)}));if(i.length>0)throw new Error(\"Unimplemented: \"+i.map((function(t){return t.command})).join(\", \")+\".\");return n.forEach((function(t){\"setTransition\"!==t.command&&r[t.command].apply(r,t.args)})),this.stylesheet=e,!0},r.prototype.addImage=function(e,r){if(this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"An image with this name already exists.\")));this.imageManager.addImage(e,r),this._afterImageUpdated(e)},r.prototype.updateImage=function(t,e){this.imageManager.updateImage(t,e)},r.prototype.getImage=function(t){return this.imageManager.getImage(t)},r.prototype.removeImage=function(e){if(!this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"No image with this name exists.\")));this.imageManager.removeImage(e),this._afterImageUpdated(e)},r.prototype._afterImageUpdated=function(e){this._availableImages=this.imageManager.listImages(),this._changedImages[e]=!0,this._changed=!0,this.dispatcher.broadcast(\"setImages\",this._availableImages),this.fire(new t.Event(\"data\",{dataType:\"style\"}))},r.prototype.listImages=function(){return this._checkLoaded(),this.imageManager.listImages()},r.prototype.addSource=function(e,r,n){var i=this;if(void 0===n&&(n={}),this._checkLoaded(),void 0!==this.sourceCaches[e])throw new Error(\"There is already a source with this ID\");if(!r.type)throw new Error(\"The type property must be defined, but only the following properties were given: \"+Object.keys(r).join(\", \")+\".\");if(!([\"vector\",\"raster\",\"geojson\",\"video\",\"image\"].indexOf(r.type)>=0&&this._validate(t.validateStyle.source,\"sources.\"+e,r,null,n))){this.map&&this.map._collectResourceTiming&&(r.collectResourceTiming=!0);var a=this.sourceCaches[e]=new Ot(e,r,this.dispatcher);a.style=this,a.setEventedParent(this,(function(){return{isSourceLoaded:i.loaded(),source:a.serialize(),sourceId:e}})),a.onAdd(this.map),this._changed=!0}},r.prototype.removeSource=function(e){if(this._checkLoaded(),void 0===this.sourceCaches[e])throw new Error(\"There is no source with this ID\");for(var r in this._layers)if(this._layers[r].source===e)return this.fire(new t.ErrorEvent(new Error('Source \"'+e+'\" cannot be removed while layer \"'+r+'\" is using it.')));var n=this.sourceCaches[e];delete this.sourceCaches[e],delete this._updatedSources[e],n.fire(new t.Event(\"data\",{sourceDataType:\"metadata\",dataType:\"source\",sourceId:e})),n.setEventedParent(null),n.clearTiles(),n.onRemove&&n.onRemove(this.map),this._changed=!0},r.prototype.setGeoJSONSourceData=function(t,e){this._checkLoaded(),this.sourceCaches[t].getSource().setData(e),this._changed=!0},r.prototype.getSource=function(t){return this.sourceCaches[t]&&this.sourceCaches[t].getSource()},r.prototype.addLayer=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=e.id;if(this.getLayer(i))this.fire(new t.ErrorEvent(new Error('Layer with id \"'+i+'\" already exists on this map')));else{var a;if(\"custom\"===e.type){if(qe(this,t.validateCustomStyleLayer(e)))return;a=t.createStyleLayer(e)}else{if(\"object\"==typeof e.source&&(this.addSource(i,e.source),e=t.clone$1(e),e=t.extend(e,{source:i})),this._validate(t.validateStyle.layer,\"layers.\"+i,e,{arrayIndex:-1},n))return;a=t.createStyleLayer(e),this._validateLayer(a),a.setEventedParent(this,{layer:{id:i}}),this._serializedLayers[a.id]=a.serialize()}var o=r?this._order.indexOf(r):this._order.length;if(r&&-1===o)this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.')));else{if(this._order.splice(o,0,i),this._layerOrderChanged=!0,this._layers[i]=a,this._removedLayers[i]&&a.source&&\"custom\"!==a.type){var s=this._removedLayers[i];delete this._removedLayers[i],s.type!==a.type?this._updatedSources[a.source]=\"clear\":(this._updatedSources[a.source]=\"reload\",this.sourceCaches[a.source].pause())}this._updateLayer(a),a.onAdd&&a.onAdd(this.map)}}},r.prototype.moveLayer=function(e,r){if(this._checkLoaded(),this._changed=!0,this._layers[e]){if(e!==r){var n=this._order.indexOf(e);this._order.splice(n,1);var i=r?this._order.indexOf(r):this._order.length;r&&-1===i?this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.'))):(this._order.splice(i,0,e),this._layerOrderChanged=!0)}}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be moved.\")))},r.prototype.removeLayer=function(e){this._checkLoaded();var r=this._layers[e];if(r){r.setEventedParent(null);var n=this._order.indexOf(e);this._order.splice(n,1),this._layerOrderChanged=!0,this._changed=!0,this._removedLayers[e]=r,delete this._layers[e],delete this._serializedLayers[e],delete this._updatedLayers[e],delete this._updatedPaintProps[e],r.onRemove&&r.onRemove(this.map)}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be removed.\")))},r.prototype.getLayer=function(t){return this._layers[t]},r.prototype.hasLayer=function(t){return t in this._layers},r.prototype.setLayerZoomRange=function(e,r,n){this._checkLoaded();var i=this.getLayer(e);i?i.minzoom===r&&i.maxzoom===n||(null!=r&&(i.minzoom=r),null!=n&&(i.maxzoom=n),this._updateLayer(i)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot have zoom extent.\")))},r.prototype.setFilter=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=this.getLayer(e);if(i){if(!t.deepEqual(i.filter,r))return null==r?(i.filter=void 0,void this._updateLayer(i)):void(this._validate(t.validateStyle.filter,\"layers.\"+i.id+\".filter\",r,null,n)||(i.filter=t.clone$1(r),this._updateLayer(i)))}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be filtered.\")))},r.prototype.getFilter=function(e){return t.clone$1(this.getLayer(e).filter)},r.prototype.setLayoutProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getLayoutProperty(r),n)||(a.setLayoutProperty(r,n,i),this._updateLayer(a)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getLayoutProperty=function(e,r){var n=this.getLayer(e);if(n)return n.getLayoutProperty(r);this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style.\")))},r.prototype.setPaintProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getPaintProperty(r),n)||(a.setPaintProperty(r,n,i)&&this._updateLayer(a),this._changed=!0,this._updatedPaintProps[e]=!0):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getPaintProperty=function(t,e){return this.getLayer(t).getPaintProperty(e)},r.prototype.setFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=e.sourceLayer,a=this.sourceCaches[n];if(void 0!==a){var o=a.getSource().type;\"geojson\"===o&&i?this.fire(new t.ErrorEvent(new Error(\"GeoJSON sources cannot have a sourceLayer parameter.\"))):\"vector\"!==o||i?(void 0===e.id&&this.fire(new t.ErrorEvent(new Error(\"The feature id parameter must be provided.\"))),a.setFeatureState(i,e.id,r)):this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+n+\"' does not exist in the map's style.\")))},r.prototype.removeFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=this.sourceCaches[n];if(void 0!==i){var a=i.getSource().type,o=\"vector\"===a?e.sourceLayer:void 0;\"vector\"!==a||o?r&&\"string\"!=typeof e.id&&\"number\"!=typeof e.id?this.fire(new t.ErrorEvent(new Error(\"A feature id is required to remove its specific state property.\"))):i.removeFeatureState(o,e.id,r):this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+n+\"' does not exist in the map's style.\")))},r.prototype.getFeatureState=function(e){this._checkLoaded();var r=e.source,n=e.sourceLayer,i=this.sourceCaches[r];if(void 0!==i){if(\"vector\"!==i.getSource().type||n)return void 0===e.id&&this.fire(new t.ErrorEvent(new Error(\"The feature id parameter must be provided.\"))),i.getFeatureState(n,e.id);this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+r+\"' does not exist in the map's style.\")))},r.prototype.getTransition=function(){return t.extend({duration:300,delay:0},this.stylesheet&&this.stylesheet.transition)},r.prototype.serialize=function(){return t.filterObject({version:this.stylesheet.version,name:this.stylesheet.name,metadata:this.stylesheet.metadata,light:this.stylesheet.light,center:this.stylesheet.center,zoom:this.stylesheet.zoom,bearing:this.stylesheet.bearing,pitch:this.stylesheet.pitch,sprite:this.stylesheet.sprite,glyphs:this.stylesheet.glyphs,transition:this.stylesheet.transition,sources:t.mapObject(this.sourceCaches,(function(t){return t.serialize()})),layers:this._serializeLayers(this._order)},(function(t){return void 0!==t}))},r.prototype._updateLayer=function(t){this._updatedLayers[t.id]=!0,t.source&&!this._updatedSources[t.source]&&\"raster\"!==this.sourceCaches[t.source].getSource().type&&(this._updatedSources[t.source]=\"reload\",this.sourceCaches[t.source].pause()),this._changed=!0},r.prototype._flattenAndSortRenderedFeatures=function(t){for(var e=this,r=function(t){return\"fill-extrusion\"===e._layers[t].type},n={},i=[],a=this._order.length-1;a>=0;a--){var o=this._order[a];if(r(o)){n[o]=a;for(var s=0,l=t;s<l.length;s+=1){var u=l[s][o];if(u)for(var c=0,f=u;c<f.length;c+=1){var h=f[c];i.push(h)}}}}i.sort((function(t,e){return e.intersectionZ-t.intersectionZ}));for(var p=[],d=this._order.length-1;d>=0;d--){var v=this._order[d];if(r(v))for(var g=i.length-1;g>=0;g--){var y=i[g].feature;if(n[y.layer.id]<d)break;p.push(y),i.pop()}else for(var m=0,x=t;m<x.length;m+=1){var b=x[m][v];if(b)for(var _=0,w=b;_<w.length;_+=1){var T=w[_];p.push(T.feature)}}}return p},r.prototype.queryRenderedFeatures=function(e,r,n){r&&r.filter&&this._validate(t.validateStyle.filter,\"queryRenderedFeatures.filter\",r.filter,null,r);var i={};if(r&&r.layers){if(!Array.isArray(r.layers))return this.fire(new t.ErrorEvent(new Error(\"parameters.layers must be an Array.\"))),[];for(var a=0,o=r.layers;a<o.length;a+=1){var s=o[a],l=this._layers[s];if(!l)return this.fire(new t.ErrorEvent(new Error(\"The layer '\"+s+\"' does not exist in the map's style and cannot be queried for features.\"))),[];i[l.source]=!0}}var u=[];for(var c in r.availableImages=this._availableImages,this.sourceCaches)r.layers&&!i[c]||u.push(B(this.sourceCaches[c],this._layers,this._serializedLayers,e,r,n));return this.placement&&u.push(function(t,e,r,n,i,a,o){for(var s={},l=a.queryRenderedSymbols(n),u=[],c=0,f=Object.keys(l).map(Number);c<f.length;c+=1){var h=f[c];u.push(o[h])}u.sort(N);for(var p=function(){var r=v[d],n=r.featureIndex.lookupSymbolFeatures(l[r.bucketInstanceId],e,r.bucketIndex,r.sourceLayerIndex,i.filter,i.layers,i.availableImages,t);for(var a in n){var o=s[a]=s[a]||[],u=n[a];u.sort((function(t,e){var n=r.featureSortOrder;if(n){var i=n.indexOf(t.featureIndex);return n.indexOf(e.featureIndex)-i}return e.featureIndex-t.featureIndex}));for(var c=0,f=u;c<f.length;c+=1){var h=f[c];o.push(h)}}},d=0,v=u;d<v.length;d+=1)p();var g=function(e){s[e].forEach((function(n){var i=n.feature,a=t[e],o=r[a.source].getFeatureState(i.layer[\"source-layer\"],i.id);i.source=i.layer.source,i.layer[\"source-layer\"]&&(i.sourceLayer=i.layer[\"source-layer\"]),i.state=o}))};for(var y in s)g(y);return s}(this._layers,this._serializedLayers,this.sourceCaches,e,r,this.placement.collisionIndex,this.placement.retainedQueryData)),this._flattenAndSortRenderedFeatures(u)},r.prototype.querySourceFeatures=function(e,r){r&&r.filter&&this._validate(t.validateStyle.filter,\"querySourceFeatures.filter\",r.filter,null,r);var n=this.sourceCaches[e];return n?function(t,e){for(var r=t.getRenderableIds().map((function(e){return t.getTileByID(e)})),n=[],i={},a=0;a<r.length;a++){var o=r[a],s=o.tileID.canonical.key;i[s]||(i[s]=!0,o.querySourceFeatures(n,e))}return n}(n,r):[]},r.prototype.addSourceType=function(t,e,n){return r.getSourceType(t)?n(new Error('A source type called \"'+t+'\" already exists.')):(r.setSourceType(t,e),e.workerSourceURL?void this.dispatcher.broadcast(\"loadWorkerSource\",{name:t,url:e.workerSourceURL},n):n(null,null))},r.prototype.getLight=function(){return this.light.getLight()},r.prototype.setLight=function(e,r){void 0===r&&(r={}),this._checkLoaded();var n=this.light.getLight(),i=!1;for(var a in e)if(!t.deepEqual(e[a],n[a])){i=!0;break}if(i){var o={now:t.browser.now(),transition:t.extend({duration:300,delay:0},this.stylesheet.transition)};this.light.setLight(e,r),this.light.updateTransitions(o)}},r.prototype._validate=function(e,r,n,i,a){return void 0===a&&(a={}),(!a||!1!==a.validate)&&qe(this,e.call(t.validateStyle,t.extend({key:r,style:this.serialize(),value:n,styleSpec:t.styleSpec},i)))},r.prototype._remove=function(){for(var e in this._request&&(this._request.cancel(),this._request=null),this._spriteRequest&&(this._spriteRequest.cancel(),this._spriteRequest=null),t.evented.off(\"pluginStateChange\",this._rtlTextPluginCallback),this._layers)this._layers[e].setEventedParent(null);for(var r in this.sourceCaches)this.sourceCaches[r].clearTiles(),this.sourceCaches[r].setEventedParent(null);this.imageManager.setEventedParent(null),this.setEventedParent(null),this.dispatcher.remove()},r.prototype._clearSource=function(t){this.sourceCaches[t].clearTiles()},r.prototype._reloadSource=function(t){this.sourceCaches[t].resume(),this.sourceCaches[t].reload()},r.prototype._updateSources=function(t){for(var e in this.sourceCaches)this.sourceCaches[e].update(t)},r.prototype._generateCollisionBoxes=function(){for(var t in this.sourceCaches)this._reloadSource(t)},r.prototype._updatePlacement=function(e,r,n,i,a){void 0===a&&(a=!1);for(var o=!1,s=!1,l={},u=0,c=this._order;u<c.length;u+=1){var f=c[u],h=this._layers[f];if(\"symbol\"===h.type){if(!l[h.source]){var p=this.sourceCaches[h.source];l[h.source]=p.getRenderableIds(!0).map((function(t){return p.getTileByID(t)})).sort((function(t,e){return e.tileID.overscaledZ-t.tileID.overscaledZ||(t.tileID.isLessThan(e.tileID)?-1:1)}))}var d=this.crossTileSymbolIndex.addLayer(h,l[h.source],e.center.lng);o=o||d}}if(this.crossTileSymbolIndex.pruneUnusedLayers(this._order),((a=a||this._layerOrderChanged||0===n)||!this.pauseablePlacement||this.pauseablePlacement.isDone()&&!this.placement.stillRecent(t.browser.now(),e.zoom))&&(this.pauseablePlacement=new Fe(e,this._order,a,r,n,i,this.placement),this._layerOrderChanged=!1),this.pauseablePlacement.isDone()?this.placement.setStale():(this.pauseablePlacement.continuePlacement(this._order,this._layers,l),this.pauseablePlacement.isDone()&&(this.placement=this.pauseablePlacement.commit(t.browser.now()),s=!0),o&&this.pauseablePlacement.placement.setStale()),s||o)for(var v=0,g=this._order;v<g.length;v+=1){var y=g[v],m=this._layers[y];\"symbol\"===m.type&&this.placement.updateLayerOpacities(m,l[m.source])}return!this.pauseablePlacement.isDone()||this.placement.hasTransitions(t.browser.now())},r.prototype._releaseSymbolFadeTiles=function(){for(var t in this.sourceCaches)this.sourceCaches[t].releaseSymbolFadeTiles()},r.prototype.getImages=function(t,e,r){this.imageManager.getImages(e.icons,r),this._updateTilesForChangedImages();var n=this.sourceCaches[e.source];n&&n.setDependencies(e.tileID.key,e.type,e.icons)},r.prototype.getGlyphs=function(t,e,r){this.glyphManager.getGlyphs(e.stacks,r)},r.prototype.getResource=function(e,r,n){return t.makeRequest(r,n)},r}(t.Evented);Ye.getSourceType=function(t){return R[t]},Ye.setSourceType=function(t,e){R[t]=e},Ye.registerForPluginStateChange=t.registerForPluginStateChange;var Xe=t.createLayout([{name:\"a_pos\",type:\"Int16\",components:2}]),Ze=_r(\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#if !defined(lowp)\\n#define lowp\\n#endif\\n#if !defined(mediump)\\n#define mediump\\n#endif\\n#if !defined(highp)\\n#define highp\\n#endif\\n#endif\",\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#if !defined(lowp)\\n#define lowp\\n#endif\\n#if !defined(mediump)\\n#define mediump\\n#endif\\n#if !defined(highp)\\n#define highp\\n#endif\\n#endif\\nvec2 unpack_float(const float packedValue) {int packedIntValue=int(packedValue);int v0=packedIntValue/256;return vec2(v0,packedIntValue-v0*256);}vec2 unpack_opacity(const float packedOpacity) {int intOpacity=int(packedOpacity)/2;return vec2(float(intOpacity)/127.0,mod(packedOpacity,2.0));}vec4 decode_color(const vec2 encodedColor) {return vec4(unpack_float(encodedColor[0])/255.0,unpack_float(encodedColor[1])/255.0\\n);}float unpack_mix_vec2(const vec2 packedValue,const float t) {return mix(packedValue[0],packedValue[1],t);}vec4 unpack_mix_color(const vec4 packedColors,const float t) {vec4 minColor=decode_color(vec2(packedColors[0],packedColors[1]));vec4 maxColor=decode_color(vec2(packedColors[2],packedColors[3]));return mix(minColor,maxColor,t);}vec2 get_pattern_pos(const vec2 pixel_coord_upper,const vec2 pixel_coord_lower,const vec2 pattern_size,const float tile_units_to_pixels,const vec2 pos) {vec2 offset=mod(mod(mod(pixel_coord_upper,pattern_size)*256.0,pattern_size)*256.0+pixel_coord_lower,pattern_size);return (tile_units_to_pixels*pos+offset)/pattern_size;}\"),Ke=_r(\"uniform vec4 u_color;uniform float u_opacity;void main() {gl_FragColor=u_color*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}\"),Je=_r(\"uniform vec2 u_pattern_tl_a;uniform vec2 u_pattern_br_a;uniform vec2 u_pattern_tl_b;uniform vec2 u_pattern_br_b;uniform vec2 u_texsize;uniform float u_mix;uniform float u_opacity;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(u_pattern_tl_a/u_texsize,u_pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(u_pattern_tl_b/u_texsize,u_pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_mix)*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pattern_size_a;uniform vec2 u_pattern_size_b;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_scale_a;uniform float u_scale_b;uniform float u_tile_units_to_pixels;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_a*u_pattern_size_a,u_tile_units_to_pixels,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_b*u_pattern_size_b,u_tile_units_to_pixels,a_pos);}\"),$e=_r(\"varying vec3 v_data;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define mediump float radius\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define highp vec4 stroke_color\\n#pragma mapbox: define mediump float stroke_width\\n#pragma mapbox: define lowp float stroke_opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize mediump float radius\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize highp vec4 stroke_color\\n#pragma mapbox: initialize mediump float stroke_width\\n#pragma mapbox: initialize lowp float stroke_opacity\\nvec2 extrude=v_data.xy;float extrude_length=length(extrude);lowp float antialiasblur=v_data.z;float antialiased_blur=-max(blur,antialiasblur);float opacity_t=smoothstep(0.0,antialiased_blur,extrude_length-1.0);float color_t=stroke_width < 0.01 ? 0.0 : smoothstep(antialiased_blur,0.0,extrude_length-radius/(radius+stroke_width));gl_FragColor=opacity_t*mix(color*opacity,stroke_color*stroke_opacity,color_t);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform bool u_scale_with_map;uniform bool u_pitch_with_map;uniform vec2 u_extrude_scale;uniform lowp float u_device_pixel_ratio;uniform highp float u_camera_to_center_distance;attribute vec2 a_pos;varying vec3 v_data;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define mediump float radius\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define highp vec4 stroke_color\\n#pragma mapbox: define mediump float stroke_width\\n#pragma mapbox: define lowp float stroke_opacity\\nvoid main(void) {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize mediump float radius\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize highp vec4 stroke_color\\n#pragma mapbox: initialize mediump float stroke_width\\n#pragma mapbox: initialize lowp float stroke_opacity\\nvec2 extrude=vec2(mod(a_pos,2.0)*2.0-1.0);vec2 circle_center=floor(a_pos*0.5);if (u_pitch_with_map) {vec2 corner_position=circle_center;if (u_scale_with_map) {corner_position+=extrude*(radius+stroke_width)*u_extrude_scale;} else {vec4 projected_center=u_matrix*vec4(circle_center,0,1);corner_position+=extrude*(radius+stroke_width)*u_extrude_scale*(projected_center.w/u_camera_to_center_distance);}gl_Position=u_matrix*vec4(corner_position,0,1);} else {gl_Position=u_matrix*vec4(circle_center,0,1);if (u_scale_with_map) {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*u_camera_to_center_distance;} else {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*gl_Position.w;}}lowp float antialiasblur=1.0/u_device_pixel_ratio/(radius+stroke_width);v_data=vec3(extrude.x,extrude.y,antialiasblur);}\"),Qe=_r(\"void main() {gl_FragColor=vec4(1.0);}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}\"),tr=_r(\"uniform highp float u_intensity;varying vec2 v_extrude;\\n#pragma mapbox: define highp float weight\\n#define GAUSS_COEF 0.3989422804014327\\nvoid main() {\\n#pragma mapbox: initialize highp float weight\\nfloat d=-0.5*3.0*3.0*dot(v_extrude,v_extrude);float val=weight*u_intensity*GAUSS_COEF*exp(d);gl_FragColor=vec4(val,1.0,1.0,1.0);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform float u_extrude_scale;uniform float u_opacity;uniform float u_intensity;attribute vec2 a_pos;varying vec2 v_extrude;\\n#pragma mapbox: define highp float weight\\n#pragma mapbox: define mediump float radius\\nconst highp float ZERO=1.0/255.0/16.0;\\n#define GAUSS_COEF 0.3989422804014327\\nvoid main(void) {\\n#pragma mapbox: initialize highp float weight\\n#pragma mapbox: initialize mediump float radius\\nvec2 unscaled_extrude=vec2(mod(a_pos,2.0)*2.0-1.0);float S=sqrt(-2.0*log(ZERO/weight/u_intensity/GAUSS_COEF))/3.0;v_extrude=S*unscaled_extrude;vec2 extrude=v_extrude*radius*u_extrude_scale;vec4 pos=vec4(floor(a_pos*0.5)+extrude,0,1);gl_Position=u_matrix*pos;}\"),er=_r(\"uniform sampler2D u_image;uniform sampler2D u_color_ramp;uniform float u_opacity;varying vec2 v_pos;void main() {float t=texture2D(u_image,v_pos).r;vec4 color=texture2D(u_color_ramp,vec2(t,0.5));gl_FragColor=color*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(0.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_world;attribute vec2 a_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos*u_world,0,1);v_pos.x=a_pos.x;v_pos.y=1.0-a_pos.y;}\"),rr=_r(\"varying float v_placed;varying float v_notUsed;void main() {float alpha=0.5;gl_FragColor=vec4(1.0,0.0,0.0,1.0)*alpha;if (v_placed > 0.5) {gl_FragColor=vec4(0.0,0.0,1.0,0.5)*alpha;}if (v_notUsed > 0.5) {gl_FragColor*=.1;}}\",\"attribute vec2 a_pos;attribute vec2 a_anchor_pos;attribute vec2 a_extrude;attribute vec2 a_placed;attribute vec2 a_shift;uniform mat4 u_matrix;uniform vec2 u_extrude_scale;uniform float u_camera_to_center_distance;varying float v_placed;varying float v_notUsed;void main() {vec4 projectedPoint=u_matrix*vec4(a_anchor_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);gl_Position=u_matrix*vec4(a_pos,0.0,1.0);gl_Position.xy+=(a_extrude+a_shift)*u_extrude_scale*gl_Position.w*collision_perspective_ratio;v_placed=a_placed.x;v_notUsed=a_placed.y;}\"),nr=_r(\"varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;void main() {float alpha=0.5*min(v_perspective_ratio,1.0);float stroke_radius=0.9*max(v_perspective_ratio,1.0);float distance_to_center=length(v_extrude);float distance_to_edge=abs(distance_to_center-v_radius);float opacity_t=smoothstep(-stroke_radius,0.0,-distance_to_edge);vec4 color=mix(vec4(0.0,0.0,1.0,0.5),vec4(1.0,0.0,0.0,1.0),v_collision);gl_FragColor=color*alpha*opacity_t;}\",\"attribute vec2 a_pos;attribute float a_radius;attribute vec2 a_flags;uniform mat4 u_matrix;uniform mat4 u_inv_matrix;uniform vec2 u_viewport_size;uniform float u_camera_to_center_distance;varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;vec3 toTilePosition(vec2 screenPos) {vec4 rayStart=u_inv_matrix*vec4(screenPos,-1.0,1.0);vec4 rayEnd  =u_inv_matrix*vec4(screenPos, 1.0,1.0);rayStart.xyz/=rayStart.w;rayEnd.xyz  /=rayEnd.w;highp float t=(0.0-rayStart.z)/(rayEnd.z-rayStart.z);return mix(rayStart.xyz,rayEnd.xyz,t);}void main() {vec2 quadCenterPos=a_pos;float radius=a_radius;float collision=a_flags.x;float vertexIdx=a_flags.y;vec2 quadVertexOffset=vec2(mix(-1.0,1.0,float(vertexIdx >=2.0)),mix(-1.0,1.0,float(vertexIdx >=1.0 && vertexIdx <=2.0)));vec2 quadVertexExtent=quadVertexOffset*radius;vec3 tilePos=toTilePosition(quadCenterPos);vec4 clipPos=u_matrix*vec4(tilePos,1.0);highp float camera_to_anchor_distance=clipPos.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);float padding_factor=1.2;v_radius=radius;v_extrude=quadVertexExtent*padding_factor;v_perspective_ratio=collision_perspective_ratio;v_collision=collision;gl_Position=vec4(clipPos.xyz/clipPos.w,1.0)+vec4(quadVertexExtent*padding_factor/u_viewport_size*2.0,0.0,0.0);}\"),ir=_r(\"uniform highp vec4 u_color;uniform sampler2D u_overlay;varying vec2 v_uv;void main() {vec4 overlay_color=texture2D(u_overlay,v_uv);gl_FragColor=mix(u_color,overlay_color,overlay_color.a);}\",\"attribute vec2 a_pos;varying vec2 v_uv;uniform mat4 u_matrix;uniform float u_overlay_scale;void main() {v_uv=a_pos/8192.0;gl_Position=u_matrix*vec4(a_pos*u_overlay_scale,0,1);}\"),ar=_r(\"#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float opacity\\ngl_FragColor=color*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float opacity\\ngl_Position=u_matrix*vec4(a_pos,0,1);}\"),or=_r(\"varying vec2 v_pos;\\n#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 outline_color\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=outline_color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;uniform vec2 u_world;varying vec2 v_pos;\\n#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 outline_color\\n#pragma mapbox: initialize lowp float opacity\\ngl_Position=u_matrix*vec4(a_pos,0,1);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}\"),sr=_r(\"uniform vec2 u_texsize;uniform sampler2D u_image;uniform float u_fade;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);float dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=mix(color1,color2,u_fade)*alpha*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_world;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;gl_Position=u_matrix*vec4(a_pos,0,1);vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,a_pos);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}\"),lr=_r(\"uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_fade)*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileZoomRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileZoomRatio,a_pos);}\"),ur=_r(\"varying vec4 v_color;void main() {gl_FragColor=v_color;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;uniform float u_vertical_gradient;uniform lowp float u_opacity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec4 v_color;\\n#pragma mapbox: define highp float base\\n#pragma mapbox: define highp float height\\n#pragma mapbox: define highp vec4 color\\nvoid main() {\\n#pragma mapbox: initialize highp float base\\n#pragma mapbox: initialize highp float height\\n#pragma mapbox: initialize highp vec4 color\\nvec3 normal=a_normal_ed.xyz;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);gl_Position=u_matrix*vec4(a_pos,t > 0.0 ? height : base,1);float colorvalue=color.r*0.2126+color.g*0.7152+color.b*0.0722;v_color=vec4(0.0,0.0,0.0,1.0);vec4 ambientlight=vec4(0.03,0.03,0.03,1.0);color+=ambientlight;float directional=clamp(dot(normal/16384.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((1.0-colorvalue+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_color.r+=clamp(color.r*directional*u_lightcolor.r,mix(0.0,0.3,1.0-u_lightcolor.r),1.0);v_color.g+=clamp(color.g*directional*u_lightcolor.g,mix(0.0,0.3,1.0-u_lightcolor.g),1.0);v_color.b+=clamp(color.b*directional*u_lightcolor.b,mix(0.0,0.3,1.0-u_lightcolor.b),1.0);v_color*=u_opacity;}\"),cr=_r(\"uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float base\\n#pragma mapbox: initialize lowp float height\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);vec4 mixedColor=mix(color1,color2,u_fade);gl_FragColor=mixedColor*v_lighting;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_height_factor;uniform vec3 u_scale;uniform float u_vertical_gradient;uniform lowp float u_opacity;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float base\\n#pragma mapbox: initialize lowp float height\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec3 normal=a_normal_ed.xyz;float edgedistance=a_normal_ed.w;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);float z=t > 0.0 ? height : base;gl_Position=u_matrix*vec4(a_pos,z,1);vec2 pos=normal.x==1.0 && normal.y==0.0 && normal.z==16384.0\\n? a_pos\\n: vec2(edgedistance,z*u_height_factor);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,pos);v_lighting=vec4(0.0,0.0,0.0,1.0);float directional=clamp(dot(normal/16383.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((0.5+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_lighting.rgb+=clamp(directional*u_lightcolor,mix(vec3(0.0),vec3(0.3),1.0-u_lightcolor),vec3(1.0));v_lighting*=u_opacity;}\"),fr=_r(\"#ifdef GL_ES\\nprecision highp float;\\n#endif\\nuniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_dimension;uniform float u_zoom;uniform vec4 u_unpack;float getElevation(vec2 coord,float bias) {vec4 data=texture2D(u_image,coord)*255.0;data.a=-1.0;return dot(data,u_unpack)/4.0;}void main() {vec2 epsilon=1.0/u_dimension;float a=getElevation(v_pos+vec2(-epsilon.x,-epsilon.y),0.0);float b=getElevation(v_pos+vec2(0,-epsilon.y),0.0);float c=getElevation(v_pos+vec2(epsilon.x,-epsilon.y),0.0);float d=getElevation(v_pos+vec2(-epsilon.x,0),0.0);float e=getElevation(v_pos,0.0);float f=getElevation(v_pos+vec2(epsilon.x,0),0.0);float g=getElevation(v_pos+vec2(-epsilon.x,epsilon.y),0.0);float h=getElevation(v_pos+vec2(0,epsilon.y),0.0);float i=getElevation(v_pos+vec2(epsilon.x,epsilon.y),0.0);float exaggerationFactor=u_zoom < 2.0 ? 0.4 : u_zoom < 4.5 ? 0.35 : 0.3;float exaggeration=u_zoom < 15.0 ? (u_zoom-15.0)*exaggerationFactor : 0.0;vec2 deriv=vec2((c+f+f+i)-(a+d+d+g),(g+h+h+i)-(a+b+b+c))/pow(2.0,exaggeration+(19.2562-u_zoom));gl_FragColor=clamp(vec4(deriv.x/2.0+0.5,deriv.y/2.0+0.5,1.0,1.0),0.0,1.0);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_dimension;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);highp vec2 epsilon=1.0/u_dimension;float scale=(u_dimension.x-2.0)/u_dimension.x;v_pos=(a_texture_pos/8192.0)*scale+epsilon;}\"),hr=_r(\"uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_latrange;uniform vec2 u_light;uniform vec4 u_shadow;uniform vec4 u_highlight;uniform vec4 u_accent;\\n#define PI 3.141592653589793\\nvoid main() {vec4 pixel=texture2D(u_image,v_pos);vec2 deriv=((pixel.rg*2.0)-1.0);float scaleFactor=cos(radians((u_latrange[0]-u_latrange[1])*(1.0-v_pos.y)+u_latrange[1]));float slope=atan(1.25*length(deriv)/scaleFactor);float aspect=deriv.x !=0.0 ? atan(deriv.y,-deriv.x) : PI/2.0*(deriv.y > 0.0 ? 1.0 :-1.0);float intensity=u_light.x;float azimuth=u_light.y+PI;float base=1.875-intensity*1.75;float maxValue=0.5*PI;float scaledSlope=intensity !=0.5 ? ((pow(base,slope)-1.0)/(pow(base,maxValue)-1.0))*maxValue : slope;float accent=cos(scaledSlope);vec4 accent_color=(1.0-accent)*u_accent*clamp(intensity*2.0,0.0,1.0);float shade=abs(mod((aspect+azimuth)/PI+0.5,2.0)-1.0);vec4 shade_color=mix(u_shadow,u_highlight,shade)*sin(scaledSlope)*clamp(intensity*2.0,0.0,1.0);gl_FragColor=accent_color*(1.0-shade_color.a)+shade_color;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos=a_texture_pos/8192.0;}\"),pr=_r(\"uniform lowp float u_device_pixel_ratio;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform vec2 u_units_to_pixels;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_linesofar;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}\"),dr=_r(\"uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;varying highp vec2 v_uv;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);vec4 color=texture2D(u_image,v_uv);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\nattribute vec2 a_pos_normal;attribute vec4 a_data;attribute float a_uv_x;attribute float a_split_index;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_units_to_pixels;uniform float u_image_height;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp vec2 v_uv;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;highp float texel_height=1.0/u_image_height;highp float half_texel_height=0.5*texel_height;v_uv=vec2(a_uv_x,a_split_index*texel_height-half_texel_height);vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}\"),vr=_r(\"uniform lowp float u_device_pixel_ratio;uniform vec2 u_texsize;uniform float u_fade;uniform mediump vec3 u_scale;uniform sampler2D u_image;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;vec2 pattern_size_a=vec2(display_size_a.x*fromScale/tileZoomRatio,display_size_a.y);vec2 pattern_size_b=vec2(display_size_b.x*toScale/tileZoomRatio,display_size_b.y);float aspect_a=display_size_a.y/v_width;float aspect_b=display_size_b.y/v_width;float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float x_a=mod(v_linesofar/pattern_size_a.x*aspect_a,1.0);float x_b=mod(v_linesofar/pattern_size_b.x*aspect_b,1.0);float y=0.5*v_normal.y+0.5;vec2 texel_size=1.0/u_texsize;vec2 pos_a=mix(pattern_tl_a*texel_size-texel_size,pattern_br_a*texel_size+texel_size,vec2(x_a,y));vec2 pos_b=mix(pattern_tl_b*texel_size-texel_size,pattern_br_b*texel_size+texel_size,vec2(x_b,y));vec4 color=mix(texture2D(u_image,pos_a),texture2D(u_image,pos_b),u_fade);gl_FragColor=color*alpha*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\n#define LINE_DISTANCE_SCALE 2.0\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform vec2 u_units_to_pixels;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_linesofar=a_linesofar;v_width2=vec2(outset,inset);v_width=floorwidth;}\"),gr=_r(\"uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;uniform float u_sdfgamma;uniform float u_mix;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float sdfdist_a=texture2D(u_image,v_tex_a).a;float sdfdist_b=texture2D(u_image,v_tex_b).a;float sdfdist=mix(sdfdist_a,sdfdist_b,u_mix);alpha*=smoothstep(0.5-u_sdfgamma/floorwidth,0.5+u_sdfgamma/floorwidth,sdfdist);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\n#define LINE_DISTANCE_SCALE 2.0\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_patternscale_a;uniform float u_tex_y_a;uniform vec2 u_patternscale_b;uniform float u_tex_y_b;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_tex_a=vec2(a_linesofar*u_patternscale_a.x/floorwidth,normal.y*u_patternscale_a.y+u_tex_y_a);v_tex_b=vec2(a_linesofar*u_patternscale_b.x/floorwidth,normal.y*u_patternscale_b.y+u_tex_y_b);v_width2=vec2(outset,inset);}\"),yr=_r(\"uniform float u_fade_t;uniform float u_opacity;uniform sampler2D u_image0;uniform sampler2D u_image1;varying vec2 v_pos0;varying vec2 v_pos1;uniform float u_brightness_low;uniform float u_brightness_high;uniform float u_saturation_factor;uniform float u_contrast_factor;uniform vec3 u_spin_weights;void main() {vec4 color0=texture2D(u_image0,v_pos0);vec4 color1=texture2D(u_image1,v_pos1);if (color0.a > 0.0) {color0.rgb=color0.rgb/color0.a;}if (color1.a > 0.0) {color1.rgb=color1.rgb/color1.a;}vec4 color=mix(color0,color1,u_fade_t);color.a*=u_opacity;vec3 rgb=color.rgb;rgb=vec3(dot(rgb,u_spin_weights.xyz),dot(rgb,u_spin_weights.zxy),dot(rgb,u_spin_weights.yzx));float average=(color.r+color.g+color.b)/3.0;rgb+=(average-rgb)*u_saturation_factor;rgb=(rgb-0.5)*u_contrast_factor+0.5;vec3 u_high_vec=vec3(u_brightness_low,u_brightness_low,u_brightness_low);vec3 u_low_vec=vec3(u_brightness_high,u_brightness_high,u_brightness_high);gl_FragColor=vec4(mix(u_high_vec,u_low_vec,rgb)*color.a,color.a);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_tl_parent;uniform float u_scale_parent;uniform float u_buffer_scale;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos0;varying vec2 v_pos1;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos0=(((a_texture_pos/8192.0)-0.5)/u_buffer_scale )+0.5;v_pos1=(v_pos0*u_scale_parent)+u_tl_parent;}\"),mr=_r(\"uniform sampler2D u_texture;varying vec2 v_tex;varying float v_fade_opacity;\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\nlowp float alpha=opacity*v_fade_opacity;gl_FragColor=texture2D(u_texture,v_tex)*alpha;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform highp float u_camera_to_center_distance;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform float u_fade_change;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform vec2 u_texsize;varying vec2 v_tex;varying float v_fade_opacity;\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;vec2 a_minFontScale=a_pixeloffset.zw/256.0;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*max(a_minFontScale,fontScale)+a_pxoffset/16.0),0.0,1.0);v_tex=a_tex/u_texsize;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;v_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));}\"),xr=_r(\"#define SDF_PX 8.0\\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;uniform bool u_is_text;varying vec2 v_data0;varying vec3 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nfloat EDGE_GAMMA=0.105/u_device_pixel_ratio;vec2 tex=v_data0.xy;float gamma_scale=v_data1.x;float size=v_data1.y;float fade_opacity=v_data1[2];float fontScale=u_is_text ? size/24.0 : size;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;varying vec2 v_data0;varying vec3 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale+a_pxoffset),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0=a_tex/u_texsize;v_data1=vec3(gamma_scale,size,interpolated_fade_opacity);}\"),br=_r(\"#define SDF_PX 8.0\\n#define SDF 1.0\\n#define ICON 0.0\\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform sampler2D u_texture_icon;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;varying vec4 v_data0;varying vec4 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nfloat fade_opacity=v_data1[2];if (v_data1.w==ICON) {vec2 tex_icon=v_data0.zw;lowp float alpha=opacity*fade_opacity;gl_FragColor=texture2D(u_texture_icon,tex_icon)*alpha;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\nreturn;}vec2 tex=v_data0.xy;float EDGE_GAMMA=0.105/u_device_pixel_ratio;float gamma_scale=v_data1.x;float size=v_data1.y;float fontScale=size/24.0;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;uniform vec2 u_texsize_icon;varying vec4 v_data0;varying vec4 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);float is_sdf=a_size[0]-2.0*a_size_min;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=size/24.0;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0.xy=a_tex/u_texsize;v_data0.zw=a_tex/u_texsize_icon;v_data1=vec4(gamma_scale,size,interpolated_fade_opacity,is_sdf);}\");function _r(t,e){var r=/#pragma mapbox: ([\\w]+) ([\\w]+) ([\\w]+) ([\\w]+)/g,n=e.match(/attribute ([\\w]+) ([\\w]+)/g),i=t.match(/uniform ([\\w]+) ([\\w]+)([\\s]*)([\\w]*)/g),a=e.match(/uniform ([\\w]+) ([\\w]+)([\\s]*)([\\w]*)/g),o=a?a.concat(i):i,s={};return{fragmentSource:t=t.replace(r,(function(t,e,r,n,i){return s[i]=!0,\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+i+\"\\nvarying \"+r+\" \"+n+\" \"+i+\";\\n#else\\nuniform \"+r+\" \"+n+\" u_\"+i+\";\\n#endif\\n\":\"\\n#ifdef HAS_UNIFORM_u_\"+i+\"\\n    \"+r+\" \"+n+\" \"+i+\" = u_\"+i+\";\\n#endif\\n\"})),vertexSource:e=e.replace(r,(function(t,e,r,n,i){var a=\"float\"===n?\"vec2\":\"vec4\",o=i.match(/color/)?\"color\":a;return s[i]?\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+i+\"\\nuniform lowp float u_\"+i+\"_t;\\nattribute \"+r+\" \"+a+\" a_\"+i+\";\\nvarying \"+r+\" \"+n+\" \"+i+\";\\n#else\\nuniform \"+r+\" \"+n+\" u_\"+i+\";\\n#endif\\n\":\"vec4\"===o?\"\\n#ifndef HAS_UNIFORM_u_\"+i+\"\\n    \"+i+\" = a_\"+i+\";\\n#else\\n    \"+r+\" \"+n+\" \"+i+\" = u_\"+i+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+i+\"\\n    \"+i+\" = unpack_mix_\"+o+\"(a_\"+i+\", u_\"+i+\"_t);\\n#else\\n    \"+r+\" \"+n+\" \"+i+\" = u_\"+i+\";\\n#endif\\n\":\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+i+\"\\nuniform lowp float u_\"+i+\"_t;\\nattribute \"+r+\" \"+a+\" a_\"+i+\";\\n#else\\nuniform \"+r+\" \"+n+\" u_\"+i+\";\\n#endif\\n\":\"vec4\"===o?\"\\n#ifndef HAS_UNIFORM_u_\"+i+\"\\n    \"+r+\" \"+n+\" \"+i+\" = a_\"+i+\";\\n#else\\n    \"+r+\" \"+n+\" \"+i+\" = u_\"+i+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+i+\"\\n    \"+r+\" \"+n+\" \"+i+\" = unpack_mix_\"+o+\"(a_\"+i+\", u_\"+i+\"_t);\\n#else\\n    \"+r+\" \"+n+\" \"+i+\" = u_\"+i+\";\\n#endif\\n\"})),staticAttributes:n,staticUniforms:o}}var wr=Object.freeze({__proto__:null,prelude:Ze,background:Ke,backgroundPattern:Je,circle:$e,clippingMask:Qe,heatmap:tr,heatmapTexture:er,collisionBox:rr,collisionCircle:nr,debug:ir,fill:ar,fillOutline:or,fillOutlinePattern:sr,fillPattern:lr,fillExtrusion:ur,fillExtrusionPattern:cr,hillshadePrepare:fr,hillshade:hr,line:pr,lineGradient:dr,linePattern:vr,lineSDF:gr,raster:yr,symbolIcon:mr,symbolSDF:xr,symbolTextAndIcon:br}),Tr=function(){this.boundProgram=null,this.boundLayoutVertexBuffer=null,this.boundPaintVertexBuffers=[],this.boundIndexBuffer=null,this.boundVertexOffset=null,this.boundDynamicVertexBuffer=null,this.vao=null};function kr(t){for(var e=[],r=0;r<t.length;r++)if(null!==t[r]){var n=t[r].split(\" \");e.push(n.pop())}return e}Tr.prototype.bind=function(t,e,r,n,i,a,o,s){this.context=t;for(var l=this.boundPaintVertexBuffers.length!==n.length,u=0;!l&&u<n.length;u++)this.boundPaintVertexBuffers[u]!==n[u]&&(l=!0);var c=!this.vao||this.boundProgram!==e||this.boundLayoutVertexBuffer!==r||l||this.boundIndexBuffer!==i||this.boundVertexOffset!==a||this.boundDynamicVertexBuffer!==o||this.boundDynamicVertexBuffer2!==s;!t.extVertexArrayObject||c?this.freshBind(e,r,n,i,a,o,s):(t.bindVertexArrayOES.set(this.vao),o&&o.bind(),i&&i.dynamicDraw&&i.bind(),s&&s.bind())},Tr.prototype.freshBind=function(t,e,r,n,i,a,o){var s,l=t.numAttributes,u=this.context,c=u.gl;if(u.extVertexArrayObject)this.vao&&this.destroy(),this.vao=u.extVertexArrayObject.createVertexArrayOES(),u.bindVertexArrayOES.set(this.vao),s=0,this.boundProgram=t,this.boundLayoutVertexBuffer=e,this.boundPaintVertexBuffers=r,this.boundIndexBuffer=n,this.boundVertexOffset=i,this.boundDynamicVertexBuffer=a,this.boundDynamicVertexBuffer2=o;else{s=u.currentNumAttributes||0;for(var f=l;f<s;f++)c.disableVertexAttribArray(f)}e.enableAttributes(c,t);for(var h=0,p=r;h<p.length;h+=1)p[h].enableAttributes(c,t);a&&a.enableAttributes(c,t),o&&o.enableAttributes(c,t),e.bind(),e.setVertexAttribPointers(c,t,i);for(var d=0,v=r;d<v.length;d+=1){var g=v[d];g.bind(),g.setVertexAttribPointers(c,t,i)}a&&(a.bind(),a.setVertexAttribPointers(c,t,i)),n&&n.bind(),o&&(o.bind(),o.setVertexAttribPointers(c,t,i)),u.currentNumAttributes=l},Tr.prototype.destroy=function(){this.vao&&(this.context.extVertexArrayObject.deleteVertexArrayOES(this.vao),this.vao=null)};var Ar=function(t,e,r,n,i,a){var o=t.gl;this.program=o.createProgram();for(var s=kr(r.staticAttributes),l=n?n.getBinderAttributes():[],u=s.concat(l),c=r.staticUniforms?kr(r.staticUniforms):[],f=n?n.getBinderUniforms():[],h=[],p=0,d=c.concat(f);p<d.length;p+=1){var v=d[p];h.indexOf(v)<0&&h.push(v)}var g=n?n.defines():[];a&&g.push(\"#define OVERDRAW_INSPECTOR;\");var y=g.concat(Ze.fragmentSource,r.fragmentSource).join(\"\\n\"),m=g.concat(Ze.vertexSource,r.vertexSource).join(\"\\n\"),x=o.createShader(o.FRAGMENT_SHADER);if(o.isContextLost())this.failedToCreate=!0;else{o.shaderSource(x,y),o.compileShader(x),o.attachShader(this.program,x);var b=o.createShader(o.VERTEX_SHADER);if(o.isContextLost())this.failedToCreate=!0;else{o.shaderSource(b,m),o.compileShader(b),o.attachShader(this.program,b),this.attributes={};var _={};this.numAttributes=u.length;for(var w=0;w<this.numAttributes;w++)u[w]&&(o.bindAttribLocation(this.program,w,u[w]),this.attributes[u[w]]=w);o.linkProgram(this.program),o.deleteShader(b),o.deleteShader(x);for(var T=0;T<h.length;T++){var k=h[T];if(k&&!_[k]){var A=o.getUniformLocation(this.program,k);A&&(_[k]=A)}}this.fixedUniforms=i(t,_),this.binderUniforms=n?n.getUniforms(t,_):[]}}};function Mr(t,e,r){var n=1/ge(r,1,e.transform.tileZoom),i=Math.pow(2,r.tileID.overscaledZ),a=r.tileSize*Math.pow(2,e.transform.tileZoom)/i,o=a*(r.tileID.canonical.x+r.tileID.wrap*i),s=a*r.tileID.canonical.y;return{u_image:0,u_texsize:r.imageAtlasTexture.size,u_scale:[n,t.fromScale,t.toScale],u_fade:t.t,u_pixel_coord_upper:[o>>16,s>>16],u_pixel_coord_lower:[65535&o,65535&s]}}Ar.prototype.draw=function(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v){var g,y=t.gl;if(!this.failedToCreate){for(var m in t.program.set(this.program),t.setDepthMode(r),t.setStencilMode(n),t.setColorMode(i),t.setCullFace(a),this.fixedUniforms)this.fixedUniforms[m].set(o[m]);p&&p.setUniforms(t,this.binderUniforms,f,{zoom:h});for(var x=(g={},g[y.LINES]=2,g[y.TRIANGLES]=3,g[y.LINE_STRIP]=1,g)[e],b=0,_=c.get();b<_.length;b+=1){var w=_[b],T=w.vaos||(w.vaos={});(T[s]||(T[s]=new Tr)).bind(t,this,l,p?p.getPaintVertexBuffers():[],u,w.vertexOffset,d,v),y.drawElements(e,w.primitiveLength*x,y.UNSIGNED_SHORT,w.primitiveOffset*x*2)}}};var Sr=function(e,r,n,i){var a=r.style.light,o=a.properties.get(\"position\"),s=[o.x,o.y,o.z],l=t.create$1();\"viewport\"===a.properties.get(\"anchor\")&&t.fromRotation(l,-r.transform.angle),t.transformMat3(s,s,l);var u=a.properties.get(\"color\");return{u_matrix:e,u_lightpos:s,u_lightintensity:a.properties.get(\"intensity\"),u_lightcolor:[u.r,u.g,u.b],u_vertical_gradient:+n,u_opacity:i}},Er=function(e,r,n,i,a,o,s){return t.extend(Sr(e,r,n,i),Mr(o,r,s),{u_height_factor:-Math.pow(2,a.overscaledZ)/s.tileSize/8})},Lr=function(t){return{u_matrix:t}},Cr=function(e,r,n,i){return t.extend(Lr(e),Mr(n,r,i))},Pr=function(t,e){return{u_matrix:t,u_world:e}},Or=function(e,r,n,i,a){return t.extend(Cr(e,r,n,i),{u_world:a})},Ir=function(e,r,n,i){var a,o,s=e.transform;if(\"map\"===i.paint.get(\"circle-pitch-alignment\")){var l=ge(n,1,s.zoom);a=!0,o=[l,l]}else a=!1,o=s.pixelsToGLUnits;return{u_camera_to_center_distance:s.cameraToCenterDistance,u_scale_with_map:+(\"map\"===i.paint.get(\"circle-pitch-scale\")),u_matrix:e.translatePosMatrix(r.posMatrix,n,i.paint.get(\"circle-translate\"),i.paint.get(\"circle-translate-anchor\")),u_pitch_with_map:+a,u_device_pixel_ratio:t.browser.devicePixelRatio,u_extrude_scale:o}},Dr=function(t,e,r){var n=ge(r,1,e.zoom),i=Math.pow(2,e.zoom-r.tileID.overscaledZ),a=r.tileID.overscaleFactor();return{u_matrix:t,u_camera_to_center_distance:e.cameraToCenterDistance,u_pixels_to_tile_units:n,u_extrude_scale:[e.pixelsToGLUnits[0]/(n*i),e.pixelsToGLUnits[1]/(n*i)],u_overscale_factor:a}},zr=function(t,e,r){return{u_matrix:t,u_inv_matrix:e,u_camera_to_center_distance:r.cameraToCenterDistance,u_viewport_size:[r.width,r.height]}},Rr=function(t,e,r){return void 0===r&&(r=1),{u_matrix:t,u_color:e,u_overlay:0,u_overlay_scale:r}},Fr=function(t){return{u_matrix:t}},Br=function(t,e,r,n){return{u_matrix:t,u_extrude_scale:ge(e,1,r),u_intensity:n}},Nr=function(e,r,n,i){var a=t.create();t.ortho(a,0,e.width,e.height,0,0,1);var o=e.context.gl;return{u_matrix:a,u_world:[o.drawingBufferWidth,o.drawingBufferHeight],u_image:n,u_color_ramp:i,u_opacity:r.paint.get(\"heatmap-opacity\")}},jr=function(e,r,n){var i=n.paint.get(\"hillshade-shadow-color\"),a=n.paint.get(\"hillshade-highlight-color\"),o=n.paint.get(\"hillshade-accent-color\"),s=n.paint.get(\"hillshade-illumination-direction\")*(Math.PI/180);\"viewport\"===n.paint.get(\"hillshade-illumination-anchor\")&&(s-=e.transform.angle);var l,u,c,f=!e.options.moving;return{u_matrix:e.transform.calculatePosMatrix(r.tileID.toUnwrapped(),f),u_image:0,u_latrange:(l=r.tileID,u=Math.pow(2,l.canonical.z),c=l.canonical.y,[new t.MercatorCoordinate(0,c/u).toLngLat().lat,new t.MercatorCoordinate(0,(c+1)/u).toLngLat().lat]),u_light:[n.paint.get(\"hillshade-exaggeration\"),s],u_shadow:i,u_highlight:a,u_accent:o}},Ur=function(e,r){var n=r.stride,i=t.create();return t.ortho(i,0,t.EXTENT,-t.EXTENT,0,0,1),t.translate(i,i,[0,-t.EXTENT,0]),{u_matrix:i,u_image:1,u_dimension:[n,n],u_zoom:e.overscaledZ,u_unpack:r.getUnpackVector()}};var Vr=function(e,r,n){var i=e.transform;return{u_matrix:Yr(e,r,n),u_ratio:1/ge(r,1,i.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_units_to_pixels:[1/i.pixelsToGLUnits[0],1/i.pixelsToGLUnits[1]]}},qr=function(e,r,n,i){return t.extend(Vr(e,r,n),{u_image:0,u_image_height:i})},Hr=function(e,r,n,i){var a=e.transform,o=Wr(r,a);return{u_matrix:Yr(e,r,n),u_texsize:r.imageAtlasTexture.size,u_ratio:1/ge(r,1,a.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_image:0,u_scale:[o,i.fromScale,i.toScale],u_fade:i.t,u_units_to_pixels:[1/a.pixelsToGLUnits[0],1/a.pixelsToGLUnits[1]]}},Gr=function(e,r,n,i,a){var o=e.transform,s=e.lineAtlas,l=Wr(r,o),u=\"round\"===n.layout.get(\"line-cap\"),c=s.getDash(i.from,u),f=s.getDash(i.to,u),h=c.width*a.fromScale,p=f.width*a.toScale;return t.extend(Vr(e,r,n),{u_patternscale_a:[l/h,-c.height/2],u_patternscale_b:[l/p,-f.height/2],u_sdfgamma:s.width/(256*Math.min(h,p)*t.browser.devicePixelRatio)/2,u_image:0,u_tex_y_a:c.y,u_tex_y_b:f.y,u_mix:a.t})};function Wr(t,e){return 1/ge(t,1,e.tileZoom)}function Yr(t,e,r){return t.translatePosMatrix(e.tileID.posMatrix,e,r.paint.get(\"line-translate\"),r.paint.get(\"line-translate-anchor\"))}var Xr=function(t,e,r,n,i){return{u_matrix:t,u_tl_parent:e,u_scale_parent:r,u_buffer_scale:1,u_fade_t:n.mix,u_opacity:n.opacity*i.paint.get(\"raster-opacity\"),u_image0:0,u_image1:1,u_brightness_low:i.paint.get(\"raster-brightness-min\"),u_brightness_high:i.paint.get(\"raster-brightness-max\"),u_saturation_factor:(o=i.paint.get(\"raster-saturation\"),o>0?1-1/(1.001-o):-o),u_contrast_factor:(a=i.paint.get(\"raster-contrast\"),a>0?1/(1-a):1+a),u_spin_weights:Zr(i.paint.get(\"raster-hue-rotate\"))};var a,o};function Zr(t){t*=Math.PI/180;var e=Math.sin(t),r=Math.cos(t);return[(2*r+1)/3,(-Math.sqrt(3)*e-r+1)/3,(Math.sqrt(3)*e-r+1)/3]}var Kr,Jr=function(t,e,r,n,i,a,o,s,l,u){var c=i.transform;return{u_is_size_zoom_constant:+(\"constant\"===t||\"source\"===t),u_is_size_feature_constant:+(\"constant\"===t||\"camera\"===t),u_size_t:e?e.uSizeT:0,u_size:e?e.uSize:0,u_camera_to_center_distance:c.cameraToCenterDistance,u_pitch:c.pitch/360*2*Math.PI,u_rotate_symbol:+r,u_aspect_ratio:c.width/c.height,u_fade_change:i.options.fadeDuration?i.symbolFadeChange:1,u_matrix:a,u_label_plane_matrix:o,u_coord_matrix:s,u_is_text:+l,u_pitch_with_map:+n,u_texsize:u,u_texture:0}},$r=function(e,r,n,i,a,o,s,l,u,c,f){var h=a.transform;return t.extend(Jr(e,r,n,i,a,o,s,l,u,c),{u_gamma_scale:i?Math.cos(h._pitch)*h.cameraToCenterDistance:1,u_device_pixel_ratio:t.browser.devicePixelRatio,u_is_halo:+f})},Qr=function(e,r,n,i,a,o,s,l,u,c){return t.extend($r(e,r,n,i,a,o,s,l,!0,u,!0),{u_texsize_icon:c,u_texture_icon:1})},tn=function(t,e,r){return{u_matrix:t,u_opacity:e,u_color:r}},en=function(e,r,n,i,a,o){return t.extend(function(t,e,r,n){var i=r.imageManager.getPattern(t.from.toString()),a=r.imageManager.getPattern(t.to.toString()),o=r.imageManager.getPixelSize(),s=o.width,l=o.height,u=Math.pow(2,n.tileID.overscaledZ),c=n.tileSize*Math.pow(2,r.transform.tileZoom)/u,f=c*(n.tileID.canonical.x+n.tileID.wrap*u),h=c*n.tileID.canonical.y;return{u_image:0,u_pattern_tl_a:i.tl,u_pattern_br_a:i.br,u_pattern_tl_b:a.tl,u_pattern_br_b:a.br,u_texsize:[s,l],u_mix:e.t,u_pattern_size_a:i.displaySize,u_pattern_size_b:a.displaySize,u_scale_a:e.fromScale,u_scale_b:e.toScale,u_tile_units_to_pixels:1/ge(n,1,r.transform.tileZoom),u_pixel_coord_upper:[f>>16,h>>16],u_pixel_coord_lower:[65535&f,65535&h]}}(i,o,n,a),{u_matrix:e,u_opacity:r})},rn={fillExtrusion:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fillExtrusionPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_height_factor:new t.Uniform1f(e,r.u_height_factor),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fill:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},fillPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},fillOutline:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world)}},fillOutlinePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},circle:function(e,r){return{u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_scale_with_map:new t.Uniform1i(e,r.u_scale_with_map),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},collisionBox:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pixels_to_tile_units:new t.Uniform1f(e,r.u_pixels_to_tile_units),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_overscale_factor:new t.Uniform1f(e,r.u_overscale_factor)}},collisionCircle:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_inv_matrix:new t.UniformMatrix4f(e,r.u_inv_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_viewport_size:new t.Uniform2f(e,r.u_viewport_size)}},debug:function(e,r){return{u_color:new t.UniformColor(e,r.u_color),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_overlay:new t.Uniform1i(e,r.u_overlay),u_overlay_scale:new t.Uniform1f(e,r.u_overlay_scale)}},clippingMask:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmap:function(e,r){return{u_extrude_scale:new t.Uniform1f(e,r.u_extrude_scale),u_intensity:new t.Uniform1f(e,r.u_intensity),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmapTexture:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_color_ramp:new t.Uniform1i(e,r.u_color_ramp),u_opacity:new t.Uniform1f(e,r.u_opacity)}},hillshade:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_latrange:new t.Uniform2f(e,r.u_latrange),u_light:new t.Uniform2f(e,r.u_light),u_shadow:new t.UniformColor(e,r.u_shadow),u_highlight:new t.UniformColor(e,r.u_highlight),u_accent:new t.UniformColor(e,r.u_accent)}},hillshadePrepare:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_dimension:new t.Uniform2f(e,r.u_dimension),u_zoom:new t.Uniform1f(e,r.u_zoom),u_unpack:new t.Uniform4f(e,r.u_unpack)}},line:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels)}},lineGradient:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_image:new t.Uniform1i(e,r.u_image),u_image_height:new t.Uniform1f(e,r.u_image_height)}},linePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_texsize:new t.Uniform2f(e,r.u_texsize),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_image:new t.Uniform1i(e,r.u_image),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},lineSDF:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_patternscale_a:new t.Uniform2f(e,r.u_patternscale_a),u_patternscale_b:new t.Uniform2f(e,r.u_patternscale_b),u_sdfgamma:new t.Uniform1f(e,r.u_sdfgamma),u_image:new t.Uniform1i(e,r.u_image),u_tex_y_a:new t.Uniform1f(e,r.u_tex_y_a),u_tex_y_b:new t.Uniform1f(e,r.u_tex_y_b),u_mix:new t.Uniform1f(e,r.u_mix)}},raster:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_tl_parent:new t.Uniform2f(e,r.u_tl_parent),u_scale_parent:new t.Uniform1f(e,r.u_scale_parent),u_buffer_scale:new t.Uniform1f(e,r.u_buffer_scale),u_fade_t:new t.Uniform1f(e,r.u_fade_t),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image0:new t.Uniform1i(e,r.u_image0),u_image1:new t.Uniform1i(e,r.u_image1),u_brightness_low:new t.Uniform1f(e,r.u_brightness_low),u_brightness_high:new t.Uniform1f(e,r.u_brightness_high),u_saturation_factor:new t.Uniform1f(e,r.u_saturation_factor),u_contrast_factor:new t.Uniform1f(e,r.u_contrast_factor),u_spin_weights:new t.Uniform3f(e,r.u_spin_weights)}},symbolIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture)}},symbolSDF:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},symbolTextAndIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texsize_icon:new t.Uniform2f(e,r.u_texsize_icon),u_texture:new t.Uniform1i(e,r.u_texture),u_texture_icon:new t.Uniform1i(e,r.u_texture_icon),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},background:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_color:new t.UniformColor(e,r.u_color)}},backgroundPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image:new t.Uniform1i(e,r.u_image),u_pattern_tl_a:new t.Uniform2f(e,r.u_pattern_tl_a),u_pattern_br_a:new t.Uniform2f(e,r.u_pattern_br_a),u_pattern_tl_b:new t.Uniform2f(e,r.u_pattern_tl_b),u_pattern_br_b:new t.Uniform2f(e,r.u_pattern_br_b),u_texsize:new t.Uniform2f(e,r.u_texsize),u_mix:new t.Uniform1f(e,r.u_mix),u_pattern_size_a:new t.Uniform2f(e,r.u_pattern_size_a),u_pattern_size_b:new t.Uniform2f(e,r.u_pattern_size_b),u_scale_a:new t.Uniform1f(e,r.u_scale_a),u_scale_b:new t.Uniform1f(e,r.u_scale_b),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_tile_units_to_pixels:new t.Uniform1f(e,r.u_tile_units_to_pixels)}}};function nn(e,r,n,i,a,o,s){for(var l=e.context,u=l.gl,c=e.useProgram(\"collisionBox\"),f=[],h=0,p=0,d=0;d<i.length;d++){var v=i[d],g=r.getTile(v),y=g.getBucket(n);if(y){var m=v.posMatrix;0===a[0]&&0===a[1]||(m=e.translatePosMatrix(v.posMatrix,g,a,o));var x=s?y.textCollisionBox:y.iconCollisionBox,b=y.collisionCircleArray;if(b.length>0){var _=t.create(),w=m;t.mul(_,y.placementInvProjMatrix,e.transform.glCoordMatrix),t.mul(_,_,y.placementViewportMatrix),f.push({circleArray:b,circleOffset:p,transform:w,invTransform:_}),p=h+=b.length/4}x&&c.draw(l,u.LINES,Mt.disabled,Et.disabled,e.colorModeForRenderPass(),Ct.disabled,Dr(m,e.transform,g),n.id,x.layoutVertexBuffer,x.indexBuffer,x.segments,null,e.transform.zoom,null,null,x.collisionVertexBuffer)}}if(s&&f.length){var T=e.useProgram(\"collisionCircle\"),k=new t.StructArrayLayout2f1f2i16;k.resize(4*h),k._trim();for(var A=0,M=0,S=f;M<S.length;M+=1)for(var E=S[M],L=0;L<E.circleArray.length/4;L++){var C=4*L,P=E.circleArray[C+0],O=E.circleArray[C+1],I=E.circleArray[C+2],D=E.circleArray[C+3];k.emplace(A++,P,O,I,D,0),k.emplace(A++,P,O,I,D,1),k.emplace(A++,P,O,I,D,2),k.emplace(A++,P,O,I,D,3)}(!Kr||Kr.length<2*h)&&(Kr=function(e){var r=2*e,n=new t.StructArrayLayout3ui6;n.resize(r),n._trim();for(var i=0;i<r;i++){var a=6*i;n.uint16[a+0]=4*i+0,n.uint16[a+1]=4*i+1,n.uint16[a+2]=4*i+2,n.uint16[a+3]=4*i+2,n.uint16[a+4]=4*i+3,n.uint16[a+5]=4*i+0}return n}(h));for(var z=l.createIndexBuffer(Kr,!0),R=l.createVertexBuffer(k,t.collisionCircleLayout.members,!0),F=0,B=f;F<B.length;F+=1){var N=B[F],j=zr(N.transform,N.invTransform,e.transform);T.draw(l,u.TRIANGLES,Mt.disabled,Et.disabled,e.colorModeForRenderPass(),Ct.disabled,j,n.id,R,z,t.SegmentVector.simpleSegment(0,2*N.circleOffset,N.circleArray.length,N.circleArray.length/2),null,e.transform.zoom,null,null,null)}R.destroy(),z.destroy()}}var an=t.identity(new Float32Array(16));function on(e,r,n,i,a,o){var s=t.getAnchorAlignment(e),l=-(s.horizontalAlign-.5)*r,u=-(s.verticalAlign-.5)*n,c=t.evaluateVariableOffset(e,i);return new t.Point((l/a+c[0])*o,(u/a+c[1])*o)}function sn(e,r,n,i,a,o,s,l,u,c,f){var h=e.text.placedSymbolArray,p=e.text.dynamicLayoutVertexArray,d=e.icon.dynamicLayoutVertexArray,v={};p.clear();for(var g=0;g<h.length;g++){var y=h.get(g),m=e.allowVerticalPlacement&&!y.placedOrientation,x=y.hidden||!y.crossTileID||m?null:i[y.crossTileID];if(x){var b=new t.Point(y.anchorX,y.anchorY),_=re(b,n?l:s),w=ne(o.cameraToCenterDistance,_.signedDistanceFromCamera),T=a.evaluateSizeForFeature(e.textSizeData,c,y)*w/t.ONE_EM;n&&(T*=e.tilePixelRatio/u);for(var k=x.width,A=x.height,M=on(x.anchor,k,A,x.textOffset,x.textBoxScale,T),S=n?re(b.add(M),s).point:_.point.add(r?M.rotate(-o.angle):M),E=e.allowVerticalPlacement&&y.placedOrientation===t.WritingMode.vertical?Math.PI/2:0,L=0;L<y.numGlyphs;L++)t.addDynamicAttributes(p,S,E);f&&y.associatedIconIndex>=0&&(v[y.associatedIconIndex]={shiftedAnchor:S,angle:E})}else he(y.numGlyphs,p)}if(f){d.clear();for(var C=e.icon.placedSymbolArray,P=0;P<C.length;P++){var O=C.get(P);if(O.hidden)he(O.numGlyphs,d);else{var I=v[P];if(I)for(var D=0;D<O.numGlyphs;D++)t.addDynamicAttributes(d,I.shiftedAnchor,I.angle);else he(O.numGlyphs,d)}}e.icon.dynamicLayoutVertexBuffer.updateData(d)}e.text.dynamicLayoutVertexBuffer.updateData(p)}function ln(t,e,r){return r.iconsInText&&e?\"symbolTextAndIcon\":t?\"symbolSDF\":\"symbolIcon\"}function un(e,r,n,i,a,o,s,l,u,c,f,h){for(var p=e.context,d=p.gl,v=e.transform,g=\"map\"===l,y=\"map\"===u,m=g&&\"point\"!==n.layout.get(\"symbol-placement\"),x=g&&!y&&!m,b=void 0!==n.layout.get(\"symbol-sort-key\").constantOr(1),_=!1,w=e.depthModeForSublayer(0,Mt.ReadOnly),T=n.layout.get(\"text-variable-anchor\"),k=[],A=0,M=i;A<M.length;A+=1){var S=M[A],E=r.getTile(S),L=E.getBucket(n);if(L){var C=a?L.text:L.icon;if(C&&C.segments.get().length){var P=C.programConfigurations.get(n.id),O=a||L.sdfIcons,I=a?L.textSizeData:L.iconSizeData,D=y||0!==v.pitch,z=e.useProgram(ln(O,a,L),P),R=t.evaluateSizeForZoom(I,v.zoom),F=void 0,B=[0,0],N=void 0,j=void 0,U=null,V=void 0;if(a){if(N=E.glyphAtlasTexture,j=d.LINEAR,F=E.glyphAtlasTexture.size,L.iconsInText){B=E.imageAtlasTexture.size,U=E.imageAtlasTexture;var q=\"composite\"===I.kind||\"camera\"===I.kind;V=D||e.options.rotating||e.options.zooming||q?d.LINEAR:d.NEAREST}}else{var H=1!==n.layout.get(\"icon-size\").constantOr(0)||L.iconsNeedLinear;N=E.imageAtlasTexture,j=O||e.options.rotating||e.options.zooming||H||D?d.LINEAR:d.NEAREST,F=E.imageAtlasTexture.size}var G=ge(E,1,e.transform.zoom),W=te(S.posMatrix,y,g,e.transform,G),Y=ee(S.posMatrix,y,g,e.transform,G),X=T&&L.hasTextData(),Z=\"none\"!==n.layout.get(\"icon-text-fit\")&&X&&L.hasIconData();m&&ae(L,S.posMatrix,e,a,W,Y,y,c);var K=e.translatePosMatrix(S.posMatrix,E,o,s),J=m||a&&T||Z?an:W,$=e.translatePosMatrix(Y,E,o,s,!0),Q=O&&0!==n.paint.get(a?\"text-halo-width\":\"icon-halo-width\").constantOr(1),tt={program:z,buffers:C,uniformValues:O?L.iconsInText?Qr(I.kind,R,x,y,e,K,J,$,F,B):$r(I.kind,R,x,y,e,K,J,$,a,F,!0):Jr(I.kind,R,x,y,e,K,J,$,a,F),atlasTexture:N,atlasTextureIcon:U,atlasInterpolation:j,atlasInterpolationIcon:V,isSDF:O,hasHalo:Q};if(b&&L.canOverlap){_=!0;for(var et=0,rt=C.segments.get();et<rt.length;et+=1){var nt=rt[et];k.push({segments:new t.SegmentVector([nt]),sortKey:nt.sortKey,state:tt})}}else k.push({segments:C.segments,sortKey:0,state:tt})}}}_&&k.sort((function(t,e){return t.sortKey-e.sortKey}));for(var it=0,at=k;it<at.length;it+=1){var ot=at[it],st=ot.state;if(p.activeTexture.set(d.TEXTURE0),st.atlasTexture.bind(st.atlasInterpolation,d.CLAMP_TO_EDGE),st.atlasTextureIcon&&(p.activeTexture.set(d.TEXTURE1),st.atlasTextureIcon&&st.atlasTextureIcon.bind(st.atlasInterpolationIcon,d.CLAMP_TO_EDGE)),st.isSDF){var lt=st.uniformValues;st.hasHalo&&(lt.u_is_halo=1,cn(st.buffers,ot.segments,n,e,st.program,w,f,h,lt)),lt.u_is_halo=0}cn(st.buffers,ot.segments,n,e,st.program,w,f,h,st.uniformValues)}}function cn(t,e,r,n,i,a,o,s,l){var u=n.context,c=u.gl;i.draw(u,c.TRIANGLES,a,o,s,Ct.disabled,l,r.id,t.layoutVertexBuffer,t.indexBuffer,e,r.paint,n.transform.zoom,t.programConfigurations.get(r.id),t.dynamicLayoutVertexBuffer,t.opacityVertexBuffer)}function fn(t,e,r,n,i,a,o){var s,l,u,c,f,h=t.context.gl,p=r.paint.get(\"fill-pattern\"),d=p&&p.constantOr(1),v=r.getCrossfadeParameters();o?(l=d&&!r.getPaintProperty(\"fill-outline-color\")?\"fillOutlinePattern\":\"fillOutline\",s=h.LINES):(l=d?\"fillPattern\":\"fill\",s=h.TRIANGLES);for(var g=0,y=n;g<y.length;g+=1){var m=y[g],x=e.getTile(m);if(!d||x.patternsLoaded()){var b=x.getBucket(r);if(b){var _=b.programConfigurations.get(r.id),w=t.useProgram(l,_);d&&(t.context.activeTexture.set(h.TEXTURE0),x.imageAtlasTexture.bind(h.LINEAR,h.CLAMP_TO_EDGE),_.updatePaintBuffers(v));var T=p.constantOr(null);if(T&&x.imageAtlas){var k=x.imageAtlas,A=k.patternPositions[T.to.toString()],M=k.patternPositions[T.from.toString()];A&&M&&_.setConstantPatternPositions(A,M)}var S=t.translatePosMatrix(m.posMatrix,x,r.paint.get(\"fill-translate\"),r.paint.get(\"fill-translate-anchor\"));if(o){c=b.indexBuffer2,f=b.segments2;var E=[h.drawingBufferWidth,h.drawingBufferHeight];u=\"fillOutlinePattern\"===l&&d?Or(S,t,v,x,E):Pr(S,E)}else c=b.indexBuffer,f=b.segments,u=d?Cr(S,t,v,x):Lr(S);w.draw(t.context,s,i,t.stencilModeForClipping(m),a,Ct.disabled,u,r.id,b.layoutVertexBuffer,c,f,r.paint,t.transform.zoom,_)}}}}function hn(t,e,r,n,i,a,o){for(var s=t.context,l=s.gl,u=r.paint.get(\"fill-extrusion-pattern\"),c=u.constantOr(1),f=r.getCrossfadeParameters(),h=r.paint.get(\"fill-extrusion-opacity\"),p=0,d=n;p<d.length;p+=1){var v=d[p],g=e.getTile(v),y=g.getBucket(r);if(y){var m=y.programConfigurations.get(r.id),x=t.useProgram(c?\"fillExtrusionPattern\":\"fillExtrusion\",m);c&&(t.context.activeTexture.set(l.TEXTURE0),g.imageAtlasTexture.bind(l.LINEAR,l.CLAMP_TO_EDGE),m.updatePaintBuffers(f));var b=u.constantOr(null);if(b&&g.imageAtlas){var _=g.imageAtlas,w=_.patternPositions[b.to.toString()],T=_.patternPositions[b.from.toString()];w&&T&&m.setConstantPatternPositions(w,T)}var k=t.translatePosMatrix(v.posMatrix,g,r.paint.get(\"fill-extrusion-translate\"),r.paint.get(\"fill-extrusion-translate-anchor\")),A=r.paint.get(\"fill-extrusion-vertical-gradient\"),M=c?Er(k,t,A,h,v,f,g):Sr(k,t,A,h);x.draw(s,s.gl.TRIANGLES,i,a,o,Ct.backCCW,M,r.id,y.layoutVertexBuffer,y.indexBuffer,y.segments,r.paint,t.transform.zoom,m)}}}function pn(t,e,r,n,i,a){var o=t.context,s=o.gl,l=e.fbo;if(l){var u=t.useProgram(\"hillshade\");o.activeTexture.set(s.TEXTURE0),s.bindTexture(s.TEXTURE_2D,l.colorAttachment.get());var c=jr(t,e,r);u.draw(o,s.TRIANGLES,n,i,a,Ct.disabled,c,r.id,t.rasterBoundsBuffer,t.quadTriangleIndexBuffer,t.rasterBoundsSegments)}}function dn(e,r,n,i,a,o){var s=e.context,l=s.gl,u=r.dem;if(u&&u.data){var c=u.dim,f=u.stride,h=u.getPixels();if(s.activeTexture.set(l.TEXTURE1),s.pixelStoreUnpackPremultiplyAlpha.set(!1),r.demTexture=r.demTexture||e.getTileTexture(f),r.demTexture){var p=r.demTexture;p.update(h,{premultiply:!1}),p.bind(l.NEAREST,l.CLAMP_TO_EDGE)}else r.demTexture=new t.Texture(s,h,l.RGBA,{premultiply:!1}),r.demTexture.bind(l.NEAREST,l.CLAMP_TO_EDGE);s.activeTexture.set(l.TEXTURE0);var d=r.fbo;if(!d){var v=new t.Texture(s,{width:c,height:c,data:null},l.RGBA);v.bind(l.LINEAR,l.CLAMP_TO_EDGE),(d=r.fbo=s.createFramebuffer(c,c,!0)).colorAttachment.set(v.texture)}s.bindFramebuffer.set(d.framebuffer),s.viewport.set([0,0,c,c]),e.useProgram(\"hillshadePrepare\").draw(s,l.TRIANGLES,i,a,o,Ct.disabled,Ur(r.tileID,u),n.id,e.rasterBoundsBuffer,e.quadTriangleIndexBuffer,e.rasterBoundsSegments),r.needsHillshadePrepare=!1}}function vn(e,r,n,i,a){var o=i.paint.get(\"raster-fade-duration\");if(o>0){var s=t.browser.now(),l=(s-e.timeAdded)/o,u=r?(s-r.timeAdded)/o:-1,c=n.getSource(),f=a.coveringZoomLevel({tileSize:c.tileSize,roundZoom:c.roundZoom}),h=!r||Math.abs(r.tileID.overscaledZ-f)>Math.abs(e.tileID.overscaledZ-f),p=h&&e.refreshedUponExpiration?1:t.clamp(h?l:1-u,0,1);return e.refreshedUponExpiration&&l>=1&&(e.refreshedUponExpiration=!1),r?{opacity:1,mix:1-p}:{opacity:p,mix:0}}return{opacity:1,mix:0}}var gn=new t.Color(1,0,0,1),yn=new t.Color(0,1,0,1),mn=new t.Color(0,0,1,1),xn=new t.Color(1,0,1,1),bn=new t.Color(0,1,1,1);function _n(t){var e=t.transform.padding;wn(t,t.transform.height-(e.top||0),3,gn),wn(t,e.bottom||0,3,yn),Tn(t,e.left||0,3,mn),Tn(t,t.transform.width-(e.right||0),3,xn);var r=t.transform.centerPoint;!function(t,e,r,n){var i=20,a=2;kn(t,e-a/2,r-i/2,a,i,n),kn(t,e-i/2,r-a/2,i,a,n)}(t,r.x,t.transform.height-r.y,bn)}function wn(t,e,r,n){kn(t,0,e+r/2,t.transform.width,r,n)}function Tn(t,e,r,n){kn(t,e-r/2,0,r,t.transform.height,n)}function kn(e,r,n,i,a,o){var s=e.context,l=s.gl;l.enable(l.SCISSOR_TEST),l.scissor(r*t.browser.devicePixelRatio,n*t.browser.devicePixelRatio,i*t.browser.devicePixelRatio,a*t.browser.devicePixelRatio),s.clear({color:o}),l.disable(l.SCISSOR_TEST)}function An(e,r,n){var i=e.context,a=i.gl,o=n.posMatrix,s=e.useProgram(\"debug\"),l=Mt.disabled,u=Et.disabled,c=e.colorModeForRenderPass(),f=\"$debug\";i.activeTexture.set(a.TEXTURE0),e.emptyTexture.bind(a.LINEAR,a.CLAMP_TO_EDGE),s.draw(i,a.LINE_STRIP,l,u,c,Ct.disabled,Rr(o,t.Color.red),f,e.debugBuffer,e.tileBorderIndexBuffer,e.debugSegments);var h=r.getTileByID(n.key).latestRawTileData,p=h&&h.byteLength||0,d=Math.floor(p/1024),v=r.getTile(n).tileSize,g=512/Math.min(v,512)*(n.overscaledZ/e.transform.zoom)*.5,y=n.canonical.toString();n.overscaledZ!==n.canonical.z&&(y+=\" => \"+n.overscaledZ),function(t,e){t.initDebugOverlayCanvas();var r=t.debugOverlayCanvas,n=t.context.gl,i=t.debugOverlayCanvas.getContext(\"2d\");i.clearRect(0,0,r.width,r.height),i.shadowColor=\"white\",i.shadowBlur=2,i.lineWidth=1.5,i.strokeStyle=\"white\",i.textBaseline=\"top\",i.font=\"bold 36px Open Sans, sans-serif\",i.fillText(e,5,5),i.strokeText(e,5,5),t.debugOverlayTexture.update(r),t.debugOverlayTexture.bind(n.LINEAR,n.CLAMP_TO_EDGE)}(e,y+\" \"+d+\"kb\"),s.draw(i,a.TRIANGLES,l,u,Lt.alphaBlended,Ct.disabled,Rr(o,t.Color.transparent,g),f,e.debugBuffer,e.quadTriangleIndexBuffer,e.debugSegments)}var Mn={symbol:function(e,r,n,i,a){if(\"translucent\"===e.renderPass){var o=Et.disabled,s=e.colorModeForRenderPass();n.layout.get(\"text-variable-anchor\")&&function(e,r,n,i,a,o,s){for(var l=r.transform,u=\"map\"===a,c=\"map\"===o,f=0,h=e;f<h.length;f+=1){var p=h[f],d=i.getTile(p),v=d.getBucket(n);if(v&&v.text&&v.text.segments.get().length){var g=v.textSizeData,y=t.evaluateSizeForZoom(g,l.zoom),m=ge(d,1,r.transform.zoom),x=te(p.posMatrix,c,u,r.transform,m),b=\"none\"!==n.layout.get(\"icon-text-fit\")&&v.hasIconData();if(y){var _=Math.pow(2,l.zoom-d.tileID.overscaledZ);sn(v,u,c,s,t.symbolSize,l,x,p.posMatrix,_,y,b)}}}}(i,e,n,r,n.layout.get(\"text-rotation-alignment\"),n.layout.get(\"text-pitch-alignment\"),a),0!==n.paint.get(\"icon-opacity\").constantOr(1)&&un(e,r,n,i,!1,n.paint.get(\"icon-translate\"),n.paint.get(\"icon-translate-anchor\"),n.layout.get(\"icon-rotation-alignment\"),n.layout.get(\"icon-pitch-alignment\"),n.layout.get(\"icon-keep-upright\"),o,s),0!==n.paint.get(\"text-opacity\").constantOr(1)&&un(e,r,n,i,!0,n.paint.get(\"text-translate\"),n.paint.get(\"text-translate-anchor\"),n.layout.get(\"text-rotation-alignment\"),n.layout.get(\"text-pitch-alignment\"),n.layout.get(\"text-keep-upright\"),o,s),r.map.showCollisionBoxes&&(nn(e,r,n,i,n.paint.get(\"text-translate\"),n.paint.get(\"text-translate-anchor\"),!0),nn(e,r,n,i,n.paint.get(\"icon-translate\"),n.paint.get(\"icon-translate-anchor\"),!1))}},circle:function(e,r,n,i){if(\"translucent\"===e.renderPass){var a=n.paint.get(\"circle-opacity\"),o=n.paint.get(\"circle-stroke-width\"),s=n.paint.get(\"circle-stroke-opacity\"),l=void 0!==n.layout.get(\"circle-sort-key\").constantOr(1);if(0!==a.constantOr(1)||0!==o.constantOr(1)&&0!==s.constantOr(1)){for(var u=e.context,c=u.gl,f=e.depthModeForSublayer(0,Mt.ReadOnly),h=Et.disabled,p=e.colorModeForRenderPass(),d=[],v=0;v<i.length;v++){var g=i[v],y=r.getTile(g),m=y.getBucket(n);if(m){var x=m.programConfigurations.get(n.id),b={programConfiguration:x,program:e.useProgram(\"circle\",x),layoutVertexBuffer:m.layoutVertexBuffer,indexBuffer:m.indexBuffer,uniformValues:Ir(e,g,y,n)};if(l)for(var _=0,w=m.segments.get();_<w.length;_+=1){var T=w[_];d.push({segments:new t.SegmentVector([T]),sortKey:T.sortKey,state:b})}else d.push({segments:m.segments,sortKey:0,state:b})}}l&&d.sort((function(t,e){return t.sortKey-e.sortKey}));for(var k=0,A=d;k<A.length;k+=1){var M=A[k],S=M.state,E=S.programConfiguration,L=S.program,C=S.layoutVertexBuffer,P=S.indexBuffer,O=S.uniformValues,I=M.segments;L.draw(u,c.TRIANGLES,f,h,p,Ct.disabled,O,n.id,C,P,I,n.paint,e.transform.zoom,E)}}}},heatmap:function(e,r,n,i){if(0!==n.paint.get(\"heatmap-opacity\"))if(\"offscreen\"===e.renderPass){var a=e.context,o=a.gl,s=Et.disabled,l=new Lt([o.ONE,o.ONE],t.Color.transparent,[!0,!0,!0,!0]);(function(t,e,r){var n=t.gl;t.activeTexture.set(n.TEXTURE1),t.viewport.set([0,0,e.width/4,e.height/4]);var i=r.heatmapFbo;if(i)n.bindTexture(n.TEXTURE_2D,i.colorAttachment.get()),t.bindFramebuffer.set(i.framebuffer);else{var a=n.createTexture();n.bindTexture(n.TEXTURE_2D,a),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_S,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_T,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MIN_FILTER,n.LINEAR),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MAG_FILTER,n.LINEAR),i=r.heatmapFbo=t.createFramebuffer(e.width/4,e.height/4,!1),function(t,e,r,n){var i=t.gl,a=t.extRenderToTextureHalfFloat?t.extTextureHalfFloat.HALF_FLOAT_OES:i.UNSIGNED_BYTE;i.texImage2D(i.TEXTURE_2D,0,i.RGBA,e.width/4,e.height/4,0,i.RGBA,a,null),n.colorAttachment.set(r)}(t,e,a,i)}})(a,e,n),a.clear({color:t.Color.transparent});for(var u=0;u<i.length;u++){var c=i[u];if(!r.hasRenderableParent(c)){var f=r.getTile(c),h=f.getBucket(n);if(h){var p=h.programConfigurations.get(n.id),d=e.useProgram(\"heatmap\",p),v=e.transform.zoom;d.draw(a,o.TRIANGLES,Mt.disabled,s,l,Ct.disabled,Br(c.posMatrix,f,v,n.paint.get(\"heatmap-intensity\")),n.id,h.layoutVertexBuffer,h.indexBuffer,h.segments,n.paint,e.transform.zoom,p)}}}a.viewport.set([0,0,e.width,e.height])}else\"translucent\"===e.renderPass&&(e.context.setColorMode(e.colorModeForRenderPass()),function(e,r){var n=e.context,i=n.gl,a=r.heatmapFbo;if(a){n.activeTexture.set(i.TEXTURE0),i.bindTexture(i.TEXTURE_2D,a.colorAttachment.get()),n.activeTexture.set(i.TEXTURE1);var o=r.colorRampTexture;o||(o=r.colorRampTexture=new t.Texture(n,r.colorRamp,i.RGBA)),o.bind(i.LINEAR,i.CLAMP_TO_EDGE),e.useProgram(\"heatmapTexture\").draw(n,i.TRIANGLES,Mt.disabled,Et.disabled,e.colorModeForRenderPass(),Ct.disabled,Nr(e,r,0,1),r.id,e.viewportBuffer,e.quadTriangleIndexBuffer,e.viewportSegments,r.paint,e.transform.zoom)}}(e,n))},line:function(e,r,n,i){if(\"translucent\"===e.renderPass){var a=n.paint.get(\"line-opacity\"),o=n.paint.get(\"line-width\");if(0!==a.constantOr(1)&&0!==o.constantOr(1))for(var s=e.depthModeForSublayer(0,Mt.ReadOnly),l=e.colorModeForRenderPass(),u=n.paint.get(\"line-dasharray\"),c=n.paint.get(\"line-pattern\"),f=c.constantOr(1),h=n.paint.get(\"line-gradient\"),p=n.getCrossfadeParameters(),d=f?\"linePattern\":u?\"lineSDF\":h?\"lineGradient\":\"line\",v=e.context,g=v.gl,y=!0,m=0,x=i;m<x.length;m+=1){var b=x[m],_=r.getTile(b);if(!f||_.patternsLoaded()){var w=_.getBucket(n);if(w){var T=w.programConfigurations.get(n.id),k=e.context.program.get(),A=e.useProgram(d,T),M=y||A.program!==k,S=c.constantOr(null);if(S&&_.imageAtlas){var E=_.imageAtlas,L=E.patternPositions[S.to.toString()],C=E.patternPositions[S.from.toString()];L&&C&&T.setConstantPatternPositions(L,C)}var P=f?Hr(e,_,n,p):u?Gr(e,_,n,u,p):h?qr(e,_,n,w.lineClipsArray.length):Vr(e,_,n);if(f)v.activeTexture.set(g.TEXTURE0),_.imageAtlasTexture.bind(g.LINEAR,g.CLAMP_TO_EDGE),T.updatePaintBuffers(p);else if(u&&(M||e.lineAtlas.dirty))v.activeTexture.set(g.TEXTURE0),e.lineAtlas.bind(v);else if(h){var O=w.gradients[n.id],I=O.texture;if(n.gradientVersion!==O.version){var D=256;if(n.stepInterpolant){var z=r.getSource().maxzoom,R=b.canonical.z===z?Math.ceil(1<<e.transform.maxZoom-b.canonical.z):1,F=w.maxLineLength/t.EXTENT*1024*R;D=t.clamp(t.nextPowerOfTwo(F),256,v.maxTextureSize)}O.gradient=t.renderColorRamp({expression:n.gradientExpression(),evaluationKey:\"lineProgress\",resolution:D,image:O.gradient||void 0,clips:w.lineClipsArray}),O.texture?O.texture.update(O.gradient):O.texture=new t.Texture(v,O.gradient,g.RGBA),O.version=n.gradientVersion,I=O.texture}v.activeTexture.set(g.TEXTURE0),I.bind(n.stepInterpolant?g.NEAREST:g.LINEAR,g.CLAMP_TO_EDGE)}A.draw(v,g.TRIANGLES,s,e.stencilModeForClipping(b),l,Ct.disabled,P,n.id,w.layoutVertexBuffer,w.indexBuffer,w.segments,n.paint,e.transform.zoom,T,w.layoutVertexBuffer2),y=!1}}}}},fill:function(e,r,n,i){var a=n.paint.get(\"fill-color\"),o=n.paint.get(\"fill-opacity\");if(0!==o.constantOr(1)){var s=e.colorModeForRenderPass(),l=n.paint.get(\"fill-pattern\"),u=e.opaquePassEnabledForLayer()&&!l.constantOr(1)&&1===a.constantOr(t.Color.transparent).a&&1===o.constantOr(0)?\"opaque\":\"translucent\";if(e.renderPass===u){var c=e.depthModeForSublayer(1,\"opaque\"===e.renderPass?Mt.ReadWrite:Mt.ReadOnly);fn(e,r,n,i,c,s,!1)}if(\"translucent\"===e.renderPass&&n.paint.get(\"fill-antialias\")){var f=e.depthModeForSublayer(n.getPaintProperty(\"fill-outline-color\")?2:0,Mt.ReadOnly);fn(e,r,n,i,f,s,!0)}}},\"fill-extrusion\":function(t,e,r,n){var i=r.paint.get(\"fill-extrusion-opacity\");if(0!==i&&\"translucent\"===t.renderPass){var a=new Mt(t.context.gl.LEQUAL,Mt.ReadWrite,t.depthRangeFor3D);if(1!==i||r.paint.get(\"fill-extrusion-pattern\").constantOr(1))hn(t,e,r,n,a,Et.disabled,Lt.disabled),hn(t,e,r,n,a,t.stencilModeFor3D(),t.colorModeForRenderPass());else{var o=t.colorModeForRenderPass();hn(t,e,r,n,a,Et.disabled,o)}}},hillshade:function(t,e,r,n){if(\"offscreen\"===t.renderPass||\"translucent\"===t.renderPass){for(var i=t.context,a=t.depthModeForSublayer(0,Mt.ReadOnly),o=t.colorModeForRenderPass(),s=\"translucent\"===t.renderPass?t.stencilConfigForOverlap(n):[{},n],l=s[0],u=0,c=s[1];u<c.length;u+=1){var f=c[u],h=e.getTile(f);h.needsHillshadePrepare&&\"offscreen\"===t.renderPass?dn(t,h,r,a,Et.disabled,o):\"translucent\"===t.renderPass&&pn(t,h,r,a,l[f.overscaledZ],o)}i.viewport.set([0,0,t.width,t.height])}},raster:function(t,e,r,n){if(\"translucent\"===t.renderPass&&0!==r.paint.get(\"raster-opacity\")&&n.length)for(var i=t.context,a=i.gl,o=e.getSource(),s=t.useProgram(\"raster\"),l=t.colorModeForRenderPass(),u=o instanceof I?[{},n]:t.stencilConfigForOverlap(n),c=u[0],f=u[1],h=f[f.length-1].overscaledZ,p=!t.options.moving,d=0,v=f;d<v.length;d+=1){var g=v[d],y=t.depthModeForSublayer(g.overscaledZ-h,1===r.paint.get(\"raster-opacity\")?Mt.ReadWrite:Mt.ReadOnly,a.LESS),m=e.getTile(g),x=t.transform.calculatePosMatrix(g.toUnwrapped(),p);m.registerFadeDuration(r.paint.get(\"raster-fade-duration\"));var b=e.findLoadedParent(g,0),_=vn(m,b,e,r,t.transform),w=void 0,T=void 0,k=\"nearest\"===r.paint.get(\"raster-resampling\")?a.NEAREST:a.LINEAR;i.activeTexture.set(a.TEXTURE0),m.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST),i.activeTexture.set(a.TEXTURE1),b?(b.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST),w=Math.pow(2,b.tileID.overscaledZ-m.tileID.overscaledZ),T=[m.tileID.canonical.x*w%1,m.tileID.canonical.y*w%1]):m.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST);var A=Xr(x,T||[0,0],w||1,_,r);o instanceof I?s.draw(i,a.TRIANGLES,y,Et.disabled,l,Ct.disabled,A,r.id,o.boundsBuffer,t.quadTriangleIndexBuffer,o.boundsSegments):s.draw(i,a.TRIANGLES,y,c[g.overscaledZ],l,Ct.disabled,A,r.id,t.rasterBoundsBuffer,t.quadTriangleIndexBuffer,t.rasterBoundsSegments)}},background:function(t,e,r){var n=r.paint.get(\"background-color\"),i=r.paint.get(\"background-opacity\");if(0!==i){var a=t.context,o=a.gl,s=t.transform,l=s.tileSize,u=r.paint.get(\"background-pattern\");if(!t.isPatternMissing(u)){var c=!u&&1===n.a&&1===i&&t.opaquePassEnabledForLayer()?\"opaque\":\"translucent\";if(t.renderPass===c){var f=Et.disabled,h=t.depthModeForSublayer(0,\"opaque\"===c?Mt.ReadWrite:Mt.ReadOnly),p=t.colorModeForRenderPass(),d=t.useProgram(u?\"backgroundPattern\":\"background\"),v=s.coveringTiles({tileSize:l});u&&(a.activeTexture.set(o.TEXTURE0),t.imageManager.bind(t.context));for(var g=r.getCrossfadeParameters(),y=0,m=v;y<m.length;y+=1){var x=m[y],b=t.transform.calculatePosMatrix(x.toUnwrapped()),_=u?en(b,i,t,u,{tileID:x,tileSize:l},g):tn(b,i,n);d.draw(a,o.TRIANGLES,h,f,p,Ct.disabled,_,r.id,t.tileExtentBuffer,t.quadTriangleIndexBuffer,t.tileExtentSegments)}}}}},debug:function(t,e,r){for(var n=0;n<r.length;n++)An(t,e,r[n])},custom:function(t,e,r){var n=t.context,i=r.implementation;if(\"offscreen\"===t.renderPass){var a=i.prerender;a&&(t.setCustomLayerDefaults(),n.setColorMode(t.colorModeForRenderPass()),a.call(i,n.gl,t.transform.customLayerMatrix()),n.setDirty(),t.setBaseState())}else if(\"translucent\"===t.renderPass){t.setCustomLayerDefaults(),n.setColorMode(t.colorModeForRenderPass()),n.setStencilMode(Et.disabled);var o=\"3d\"===i.renderingMode?new Mt(t.context.gl.LEQUAL,Mt.ReadWrite,t.depthRangeFor3D):t.depthModeForSublayer(0,Mt.ReadOnly);n.setDepthMode(o),i.render(n.gl,t.transform.customLayerMatrix()),n.setDirty(),t.setBaseState(),n.bindFramebuffer.set(null)}}},Sn=function(t,e){this.context=new Pt(t),this.transform=e,this._tileTextures={},this.setup(),this.numSublayers=Ot.maxUnderzooming+Ot.maxOverzooming+1,this.depthEpsilon=1/Math.pow(2,16),this.crossTileSymbolIndex=new Ve,this.gpuTimers={}};Sn.prototype.resize=function(e,r){if(this.width=e*t.browser.devicePixelRatio,this.height=r*t.browser.devicePixelRatio,this.context.viewport.set([0,0,this.width,this.height]),this.style)for(var n=0,i=this.style._order;n<i.length;n+=1){var a=i[n];this.style._layers[a].resize()}},Sn.prototype.setup=function(){var e=this.context,r=new t.StructArrayLayout2i4;r.emplaceBack(0,0),r.emplaceBack(t.EXTENT,0),r.emplaceBack(0,t.EXTENT),r.emplaceBack(t.EXTENT,t.EXTENT),this.tileExtentBuffer=e.createVertexBuffer(r,Xe.members),this.tileExtentSegments=t.SegmentVector.simpleSegment(0,0,4,2);var n=new t.StructArrayLayout2i4;n.emplaceBack(0,0),n.emplaceBack(t.EXTENT,0),n.emplaceBack(0,t.EXTENT),n.emplaceBack(t.EXTENT,t.EXTENT),this.debugBuffer=e.createVertexBuffer(n,Xe.members),this.debugSegments=t.SegmentVector.simpleSegment(0,0,4,5);var i=new t.StructArrayLayout4i8;i.emplaceBack(0,0,0,0),i.emplaceBack(t.EXTENT,0,t.EXTENT,0),i.emplaceBack(0,t.EXTENT,0,t.EXTENT),i.emplaceBack(t.EXTENT,t.EXTENT,t.EXTENT,t.EXTENT),this.rasterBoundsBuffer=e.createVertexBuffer(i,O.members),this.rasterBoundsSegments=t.SegmentVector.simpleSegment(0,0,4,2);var a=new t.StructArrayLayout2i4;a.emplaceBack(0,0),a.emplaceBack(1,0),a.emplaceBack(0,1),a.emplaceBack(1,1),this.viewportBuffer=e.createVertexBuffer(a,Xe.members),this.viewportSegments=t.SegmentVector.simpleSegment(0,0,4,2);var o=new t.StructArrayLayout1ui2;o.emplaceBack(0),o.emplaceBack(1),o.emplaceBack(3),o.emplaceBack(2),o.emplaceBack(0),this.tileBorderIndexBuffer=e.createIndexBuffer(o);var s=new t.StructArrayLayout3ui6;s.emplaceBack(0,1,2),s.emplaceBack(2,1,3),this.quadTriangleIndexBuffer=e.createIndexBuffer(s),this.emptyTexture=new t.Texture(e,{width:1,height:1,data:new Uint8Array([0,0,0,0])},e.gl.RGBA);var l=this.context.gl;this.stencilClearMode=new Et({func:l.ALWAYS,mask:0},0,255,l.ZERO,l.ZERO,l.ZERO)},Sn.prototype.clearStencil=function(){var e=this.context,r=e.gl;this.nextStencilID=1,this.currentStencilSource=void 0;var n=t.create();t.ortho(n,0,this.width,this.height,0,0,1),t.scale(n,n,[r.drawingBufferWidth,r.drawingBufferHeight,0]),this.useProgram(\"clippingMask\").draw(e,r.TRIANGLES,Mt.disabled,this.stencilClearMode,Lt.disabled,Ct.disabled,Fr(n),\"$clipping\",this.viewportBuffer,this.quadTriangleIndexBuffer,this.viewportSegments)},Sn.prototype._renderTileClippingMasks=function(t,e){if(this.currentStencilSource!==t.source&&t.isTileClipped()&&e&&e.length){this.currentStencilSource=t.source;var r=this.context,n=r.gl;this.nextStencilID+e.length>256&&this.clearStencil(),r.setColorMode(Lt.disabled),r.setDepthMode(Mt.disabled);var i=this.useProgram(\"clippingMask\");this._tileClippingMaskIDs={};for(var a=0,o=e;a<o.length;a+=1){var s=o[a],l=this._tileClippingMaskIDs[s.key]=this.nextStencilID++;i.draw(r,n.TRIANGLES,Mt.disabled,new Et({func:n.ALWAYS,mask:0},l,255,n.KEEP,n.KEEP,n.REPLACE),Lt.disabled,Ct.disabled,Fr(s.posMatrix),\"$clipping\",this.tileExtentBuffer,this.quadTriangleIndexBuffer,this.tileExtentSegments)}}},Sn.prototype.stencilModeFor3D=function(){this.currentStencilSource=void 0,this.nextStencilID+1>256&&this.clearStencil();var t=this.nextStencilID++,e=this.context.gl;return new Et({func:e.NOTEQUAL,mask:255},t,255,e.KEEP,e.KEEP,e.REPLACE)},Sn.prototype.stencilModeForClipping=function(t){var e=this.context.gl;return new Et({func:e.EQUAL,mask:255},this._tileClippingMaskIDs[t.key],0,e.KEEP,e.KEEP,e.REPLACE)},Sn.prototype.stencilConfigForOverlap=function(t){var e,r=this.context.gl,n=t.sort((function(t,e){return e.overscaledZ-t.overscaledZ})),i=n[n.length-1].overscaledZ,a=n[0].overscaledZ-i+1;if(a>1){this.currentStencilSource=void 0,this.nextStencilID+a>256&&this.clearStencil();for(var o={},s=0;s<a;s++)o[s+i]=new Et({func:r.GEQUAL,mask:255},s+this.nextStencilID,255,r.KEEP,r.KEEP,r.REPLACE);return this.nextStencilID+=a,[o,n]}return[(e={},e[i]=Et.disabled,e),n]},Sn.prototype.colorModeForRenderPass=function(){var e=this.context.gl;if(this._showOverdrawInspector){var r=1/8;return new Lt([e.CONSTANT_COLOR,e.ONE],new t.Color(r,r,r,0),[!0,!0,!0,!0])}return\"opaque\"===this.renderPass?Lt.unblended:Lt.alphaBlended},Sn.prototype.depthModeForSublayer=function(t,e,r){if(!this.opaquePassEnabledForLayer())return Mt.disabled;var n=1-((1+this.currentLayer)*this.numSublayers+t)*this.depthEpsilon;return new Mt(r||this.context.gl.LEQUAL,e,[n,n])},Sn.prototype.opaquePassEnabledForLayer=function(){return this.currentLayer<this.opaquePassCutoff},Sn.prototype.render=function(e,r){var n=this;this.style=e,this.options=r,this.lineAtlas=e.lineAtlas,this.imageManager=e.imageManager,this.glyphManager=e.glyphManager,this.symbolFadeChange=e.placement.symbolFadeChange(t.browser.now()),this.imageManager.beginFrame();var i=this.style._order,a=this.style.sourceCaches;for(var o in a){var s=a[o];s.used&&s.prepare(this.context)}var l,u,c={},f={},h={};for(var p in a){var d=a[p];c[p]=d.getVisibleCoordinates(),f[p]=c[p].slice().reverse(),h[p]=d.getVisibleCoordinates(!0).reverse()}this.opaquePassCutoff=1/0;for(var v=0;v<i.length;v++){var g=i[v];if(this.style._layers[g].is3D()){this.opaquePassCutoff=v;break}}this.renderPass=\"offscreen\";for(var y=0,m=i;y<m.length;y+=1){var x=m[y],b=this.style._layers[x];if(b.hasOffscreenPass()&&!b.isHidden(this.transform.zoom)){var _=f[b.source];(\"custom\"===b.type||_.length)&&this.renderLayer(this,a[b.source],b,_)}}for(this.context.bindFramebuffer.set(null),this.context.clear({color:r.showOverdrawInspector?t.Color.black:t.Color.transparent,depth:1}),this.clearStencil(),this._showOverdrawInspector=r.showOverdrawInspector,this.depthRangeFor3D=[0,1-(e._order.length+2)*this.numSublayers*this.depthEpsilon],this.renderPass=\"opaque\",this.currentLayer=i.length-1;this.currentLayer>=0;this.currentLayer--){var w=this.style._layers[i[this.currentLayer]],T=a[w.source],k=c[w.source];this._renderTileClippingMasks(w,k),this.renderLayer(this,T,w,k)}for(this.renderPass=\"translucent\",this.currentLayer=0;this.currentLayer<i.length;this.currentLayer++){var A=this.style._layers[i[this.currentLayer]],M=a[A.source],S=(\"symbol\"===A.type?h:f)[A.source];this._renderTileClippingMasks(A,c[A.source]),this.renderLayer(this,M,A,S)}this.options.showTileBoundaries&&(t.values(this.style._layers).forEach((function(t){t.source&&!t.isHidden(n.transform.zoom)&&(t.source!==(u&&u.id)&&(u=n.style.sourceCaches[t.source]),(!l||l.getSource().maxzoom<u.getSource().maxzoom)&&(l=u))})),l&&Mn.debug(this,l,l.getVisibleCoordinates())),this.options.showPadding&&_n(this),this.context.setDefault()},Sn.prototype.renderLayer=function(t,e,r,n){r.isHidden(this.transform.zoom)||(\"background\"===r.type||\"custom\"===r.type||n.length)&&(this.id=r.id,this.gpuTimingStart(r),Mn[r.type](t,e,r,n,this.style.placement.variableOffsets),this.gpuTimingEnd())},Sn.prototype.gpuTimingStart=function(t){if(this.options.gpuTiming){var e=this.context.extTimerQuery,r=this.gpuTimers[t.id];r||(r=this.gpuTimers[t.id]={calls:0,cpuTime:0,query:e.createQueryEXT()}),r.calls++,e.beginQueryEXT(e.TIME_ELAPSED_EXT,r.query)}},Sn.prototype.gpuTimingEnd=function(){if(this.options.gpuTiming){var t=this.context.extTimerQuery;t.endQueryEXT(t.TIME_ELAPSED_EXT)}},Sn.prototype.collectGpuTimers=function(){var t=this.gpuTimers;return this.gpuTimers={},t},Sn.prototype.queryGpuTimers=function(t){var e={};for(var r in t){var n=t[r],i=this.context.extTimerQuery,a=i.getQueryObjectEXT(n.query,i.QUERY_RESULT_EXT)/1e6;i.deleteQueryEXT(n.query),e[r]=a}return e},Sn.prototype.translatePosMatrix=function(e,r,n,i,a){if(!n[0]&&!n[1])return e;var o=a?\"map\"===i?this.transform.angle:0:\"viewport\"===i?-this.transform.angle:0;if(o){var s=Math.sin(o),l=Math.cos(o);n=[n[0]*l-n[1]*s,n[0]*s+n[1]*l]}var u=[a?n[0]:ge(r,n[0],this.transform.zoom),a?n[1]:ge(r,n[1],this.transform.zoom),0],c=new Float32Array(16);return t.translate(c,e,u),c},Sn.prototype.saveTileTexture=function(t){var e=this._tileTextures[t.size[0]];e?e.push(t):this._tileTextures[t.size[0]]=[t]},Sn.prototype.getTileTexture=function(t){var e=this._tileTextures[t];return e&&e.length>0?e.pop():null},Sn.prototype.isPatternMissing=function(t){if(!t)return!1;if(!t.from||!t.to)return!0;var e=this.imageManager.getPattern(t.from.toString()),r=this.imageManager.getPattern(t.to.toString());return!e||!r},Sn.prototype.useProgram=function(t,e){this.cache=this.cache||{};var r=\"\"+t+(e?e.cacheKey:\"\")+(this._showOverdrawInspector?\"/overdraw\":\"\");return this.cache[r]||(this.cache[r]=new Ar(this.context,t,wr[t],e,rn[t],this._showOverdrawInspector)),this.cache[r]},Sn.prototype.setCustomLayerDefaults=function(){this.context.unbindVAO(),this.context.cullFace.setDefault(),this.context.activeTexture.setDefault(),this.context.pixelStoreUnpack.setDefault(),this.context.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.context.pixelStoreUnpackFlipY.setDefault()},Sn.prototype.setBaseState=function(){var t=this.context.gl;this.context.cullFace.set(!1),this.context.viewport.set([0,0,this.width,this.height]),this.context.blendEquation.set(t.FUNC_ADD)},Sn.prototype.initDebugOverlayCanvas=function(){if(null==this.debugOverlayCanvas){this.debugOverlayCanvas=t.window.document.createElement(\"canvas\"),this.debugOverlayCanvas.width=512,this.debugOverlayCanvas.height=512;var e=this.context.gl;this.debugOverlayTexture=new t.Texture(this.context,this.debugOverlayCanvas,e.RGBA)}},Sn.prototype.destroy=function(){this.emptyTexture.destroy(),this.debugOverlayTexture&&this.debugOverlayTexture.destroy()};var En=function(t,e){this.points=t,this.planes=e};En.fromInvProjectionMatrix=function(e,r,n){var i=Math.pow(2,n),a=[[-1,1,-1,1],[1,1,-1,1],[1,-1,-1,1],[-1,-1,-1,1],[-1,1,1,1],[1,1,1,1],[1,-1,1,1],[-1,-1,1,1]].map((function(r){return t.transformMat4([],r,e)})).map((function(e){return t.scale$1([],e,1/e[3]/r*i)})),o=[[0,1,2],[6,5,4],[0,3,7],[2,1,5],[3,2,6],[0,4,5]].map((function(e){var r=t.sub([],a[e[0]],a[e[1]]),n=t.sub([],a[e[2]],a[e[1]]),i=t.normalize([],t.cross([],r,n)),o=-t.dot(i,a[e[1]]);return i.concat(o)}));return new En(a,o)};var Ln=function(e,r){this.min=e,this.max=r,this.center=t.scale$2([],t.add([],this.min,this.max),.5)};Ln.prototype.quadrant=function(e){for(var r=[e%2==0,e<2],n=t.clone$2(this.min),i=t.clone$2(this.max),a=0;a<r.length;a++)n[a]=r[a]?this.min[a]:this.center[a],i[a]=r[a]?this.center[a]:this.max[a];return i[2]=this.max[2],new Ln(n,i)},Ln.prototype.distanceX=function(t){return Math.max(Math.min(this.max[0],t[0]),this.min[0])-t[0]},Ln.prototype.distanceY=function(t){return Math.max(Math.min(this.max[1],t[1]),this.min[1])-t[1]},Ln.prototype.intersects=function(e){for(var r=[[this.min[0],this.min[1],0,1],[this.max[0],this.min[1],0,1],[this.max[0],this.max[1],0,1],[this.min[0],this.max[1],0,1]],n=!0,i=0;i<e.planes.length;i++){for(var a=e.planes[i],o=0,s=0;s<r.length;s++)o+=t.dot$1(a,r[s])>=0;if(0===o)return 0;o!==r.length&&(n=!1)}if(n)return 2;for(var l=0;l<3;l++){for(var u=Number.MAX_VALUE,c=-Number.MAX_VALUE,f=0;f<e.points.length;f++){var h=e.points[f][l]-this.min[l];u=Math.min(u,h),c=Math.max(c,h)}if(c<0||u>this.max[l]-this.min[l])return 0}return 1};var Cn=function(t,e,r,n){if(void 0===t&&(t=0),void 0===e&&(e=0),void 0===r&&(r=0),void 0===n&&(n=0),isNaN(t)||t<0||isNaN(e)||e<0||isNaN(r)||r<0||isNaN(n)||n<0)throw new Error(\"Invalid value for edge-insets, top, bottom, left and right must all be numbers\");this.top=t,this.bottom=e,this.left=r,this.right=n};Cn.prototype.interpolate=function(e,r,n){return null!=r.top&&null!=e.top&&(this.top=t.number(e.top,r.top,n)),null!=r.bottom&&null!=e.bottom&&(this.bottom=t.number(e.bottom,r.bottom,n)),null!=r.left&&null!=e.left&&(this.left=t.number(e.left,r.left,n)),null!=r.right&&null!=e.right&&(this.right=t.number(e.right,r.right,n)),this},Cn.prototype.getCenter=function(e,r){var n=t.clamp((this.left+e-this.right)/2,0,e),i=t.clamp((this.top+r-this.bottom)/2,0,r);return new t.Point(n,i)},Cn.prototype.equals=function(t){return this.top===t.top&&this.bottom===t.bottom&&this.left===t.left&&this.right===t.right},Cn.prototype.clone=function(){return new Cn(this.top,this.bottom,this.left,this.right)},Cn.prototype.toJSON=function(){return{top:this.top,bottom:this.bottom,left:this.left,right:this.right}};var Pn=function(e,r,n,i,a){this.tileSize=512,this.maxValidLatitude=85.051129,this._renderWorldCopies=void 0===a||a,this._minZoom=e||0,this._maxZoom=r||22,this._minPitch=null==n?0:n,this._maxPitch=null==i?60:i,this.setMaxBounds(),this.width=0,this.height=0,this._center=new t.LngLat(0,0),this.zoom=0,this.angle=0,this._fov=.6435011087932844,this._pitch=0,this._unmodified=!0,this._edgeInsets=new Cn,this._posMatrixCache={},this._alignedPosMatrixCache={}},On={minZoom:{configurable:!0},maxZoom:{configurable:!0},minPitch:{configurable:!0},maxPitch:{configurable:!0},renderWorldCopies:{configurable:!0},worldSize:{configurable:!0},centerOffset:{configurable:!0},size:{configurable:!0},bearing:{configurable:!0},pitch:{configurable:!0},fov:{configurable:!0},zoom:{configurable:!0},center:{configurable:!0},padding:{configurable:!0},centerPoint:{configurable:!0},unmodified:{configurable:!0},point:{configurable:!0}};Pn.prototype.clone=function(){var t=new Pn(this._minZoom,this._maxZoom,this._minPitch,this.maxPitch,this._renderWorldCopies);return t.tileSize=this.tileSize,t.latRange=this.latRange,t.width=this.width,t.height=this.height,t._center=this._center,t.zoom=this.zoom,t.angle=this.angle,t._fov=this._fov,t._pitch=this._pitch,t._unmodified=this._unmodified,t._edgeInsets=this._edgeInsets.clone(),t._calcMatrices(),t},On.minZoom.get=function(){return this._minZoom},On.minZoom.set=function(t){this._minZoom!==t&&(this._minZoom=t,this.zoom=Math.max(this.zoom,t))},On.maxZoom.get=function(){return this._maxZoom},On.maxZoom.set=function(t){this._maxZoom!==t&&(this._maxZoom=t,this.zoom=Math.min(this.zoom,t))},On.minPitch.get=function(){return this._minPitch},On.minPitch.set=function(t){this._minPitch!==t&&(this._minPitch=t,this.pitch=Math.max(this.pitch,t))},On.maxPitch.get=function(){return this._maxPitch},On.maxPitch.set=function(t){this._maxPitch!==t&&(this._maxPitch=t,this.pitch=Math.min(this.pitch,t))},On.renderWorldCopies.get=function(){return this._renderWorldCopies},On.renderWorldCopies.set=function(t){void 0===t?t=!0:null===t&&(t=!1),this._renderWorldCopies=t},On.worldSize.get=function(){return this.tileSize*this.scale},On.centerOffset.get=function(){return this.centerPoint._sub(this.size._div(2))},On.size.get=function(){return new t.Point(this.width,this.height)},On.bearing.get=function(){return-this.angle/Math.PI*180},On.bearing.set=function(e){var r=-t.wrap(e,-180,180)*Math.PI/180;this.angle!==r&&(this._unmodified=!1,this.angle=r,this._calcMatrices(),this.rotationMatrix=t.create$2(),t.rotate(this.rotationMatrix,this.rotationMatrix,this.angle))},On.pitch.get=function(){return this._pitch/Math.PI*180},On.pitch.set=function(e){var r=t.clamp(e,this.minPitch,this.maxPitch)/180*Math.PI;this._pitch!==r&&(this._unmodified=!1,this._pitch=r,this._calcMatrices())},On.fov.get=function(){return this._fov/Math.PI*180},On.fov.set=function(t){t=Math.max(.01,Math.min(60,t)),this._fov!==t&&(this._unmodified=!1,this._fov=t/180*Math.PI,this._calcMatrices())},On.zoom.get=function(){return this._zoom},On.zoom.set=function(t){var e=Math.min(Math.max(t,this.minZoom),this.maxZoom);this._zoom!==e&&(this._unmodified=!1,this._zoom=e,this.scale=this.zoomScale(e),this.tileZoom=Math.floor(e),this.zoomFraction=e-this.tileZoom,this._constrain(),this._calcMatrices())},On.center.get=function(){return this._center},On.center.set=function(t){t.lat===this._center.lat&&t.lng===this._center.lng||(this._unmodified=!1,this._center=t,this._constrain(),this._calcMatrices())},On.padding.get=function(){return this._edgeInsets.toJSON()},On.padding.set=function(t){this._edgeInsets.equals(t)||(this._unmodified=!1,this._edgeInsets.interpolate(this._edgeInsets,t,1),this._calcMatrices())},On.centerPoint.get=function(){return this._edgeInsets.getCenter(this.width,this.height)},Pn.prototype.isPaddingEqual=function(t){return this._edgeInsets.equals(t)},Pn.prototype.interpolatePadding=function(t,e,r){this._unmodified=!1,this._edgeInsets.interpolate(t,e,r),this._constrain(),this._calcMatrices()},Pn.prototype.coveringZoomLevel=function(t){var e=(t.roundZoom?Math.round:Math.floor)(this.zoom+this.scaleZoom(this.tileSize/t.tileSize));return Math.max(0,e)},Pn.prototype.getVisibleUnwrappedCoordinates=function(e){var r=[new t.UnwrappedTileID(0,e)];if(this._renderWorldCopies)for(var n=this.pointCoordinate(new t.Point(0,0)),i=this.pointCoordinate(new t.Point(this.width,0)),a=this.pointCoordinate(new t.Point(this.width,this.height)),o=this.pointCoordinate(new t.Point(0,this.height)),s=Math.floor(Math.min(n.x,i.x,a.x,o.x)),l=Math.floor(Math.max(n.x,i.x,a.x,o.x)),u=s-1;u<=l+1;u++)0!==u&&r.push(new t.UnwrappedTileID(u,e));return r},Pn.prototype.coveringTiles=function(e){var r=this.coveringZoomLevel(e),n=r;if(void 0!==e.minzoom&&r<e.minzoom)return[];void 0!==e.maxzoom&&r>e.maxzoom&&(r=e.maxzoom);var i=t.MercatorCoordinate.fromLngLat(this.center),a=Math.pow(2,r),o=[a*i.x,a*i.y,0],s=En.fromInvProjectionMatrix(this.invProjMatrix,this.worldSize,r),l=e.minzoom||0;this.pitch<=60&&this._edgeInsets.top<.1&&(l=r);var u=function(t){return{aabb:new Ln([t*a,0,0],[(t+1)*a,a,0]),zoom:0,x:0,y:0,wrap:t,fullyVisible:!1}},c=[],f=[],h=r,p=e.reparseOverscaled?n:r;if(this._renderWorldCopies)for(var d=1;d<=3;d++)c.push(u(-d)),c.push(u(d));for(c.push(u(0));c.length>0;){var v=c.pop(),g=v.x,y=v.y,m=v.fullyVisible;if(!m){var x=v.aabb.intersects(s);if(0===x)continue;m=2===x}var b=v.aabb.distanceX(o),_=v.aabb.distanceY(o),w=Math.max(Math.abs(b),Math.abs(_)),T=3+(1<<h-v.zoom)-2;if(v.zoom===h||w>T&&v.zoom>=l)f.push({tileID:new t.OverscaledTileID(v.zoom===h?p:v.zoom,v.wrap,v.zoom,g,y),distanceSq:t.sqrLen([o[0]-.5-g,o[1]-.5-y])});else for(var k=0;k<4;k++){var A=(g<<1)+k%2,M=(y<<1)+(k>>1);c.push({aabb:v.aabb.quadrant(k),zoom:v.zoom+1,x:A,y:M,wrap:v.wrap,fullyVisible:m})}}return f.sort((function(t,e){return t.distanceSq-e.distanceSq})).map((function(t){return t.tileID}))},Pn.prototype.resize=function(t,e){this.width=t,this.height=e,this.pixelsToGLUnits=[2/t,-2/e],this._constrain(),this._calcMatrices()},On.unmodified.get=function(){return this._unmodified},Pn.prototype.zoomScale=function(t){return Math.pow(2,t)},Pn.prototype.scaleZoom=function(t){return Math.log(t)/Math.LN2},Pn.prototype.project=function(e){var r=t.clamp(e.lat,-this.maxValidLatitude,this.maxValidLatitude);return new t.Point(t.mercatorXfromLng(e.lng)*this.worldSize,t.mercatorYfromLat(r)*this.worldSize)},Pn.prototype.unproject=function(e){return new t.MercatorCoordinate(e.x/this.worldSize,e.y/this.worldSize).toLngLat()},On.point.get=function(){return this.project(this.center)},Pn.prototype.setLocationAtPoint=function(e,r){var n=this.pointCoordinate(r),i=this.pointCoordinate(this.centerPoint),a=this.locationCoordinate(e),o=new t.MercatorCoordinate(a.x-(n.x-i.x),a.y-(n.y-i.y));this.center=this.coordinateLocation(o),this._renderWorldCopies&&(this.center=this.center.wrap())},Pn.prototype.locationPoint=function(t){return this.coordinatePoint(this.locationCoordinate(t))},Pn.prototype.pointLocation=function(t){return this.coordinateLocation(this.pointCoordinate(t))},Pn.prototype.locationCoordinate=function(e){return t.MercatorCoordinate.fromLngLat(e)},Pn.prototype.coordinateLocation=function(t){return t.toLngLat()},Pn.prototype.pointCoordinate=function(e){var r=[e.x,e.y,0,1],n=[e.x,e.y,1,1];t.transformMat4(r,r,this.pixelMatrixInverse),t.transformMat4(n,n,this.pixelMatrixInverse);var i=r[3],a=n[3],o=r[0]/i,s=n[0]/a,l=r[1]/i,u=n[1]/a,c=r[2]/i,f=n[2]/a,h=c===f?0:(0-c)/(f-c);return new t.MercatorCoordinate(t.number(o,s,h)/this.worldSize,t.number(l,u,h)/this.worldSize)},Pn.prototype.coordinatePoint=function(e){var r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix),new t.Point(r[0]/r[3],r[1]/r[3])},Pn.prototype.getBounds=function(){return(new t.LngLatBounds).extend(this.pointLocation(new t.Point(0,0))).extend(this.pointLocation(new t.Point(this.width,0))).extend(this.pointLocation(new t.Point(this.width,this.height))).extend(this.pointLocation(new t.Point(0,this.height)))},Pn.prototype.getMaxBounds=function(){return this.latRange&&2===this.latRange.length&&this.lngRange&&2===this.lngRange.length?new t.LngLatBounds([this.lngRange[0],this.latRange[0]],[this.lngRange[1],this.latRange[1]]):null},Pn.prototype.setMaxBounds=function(t){t?(this.lngRange=[t.getWest(),t.getEast()],this.latRange=[t.getSouth(),t.getNorth()],this._constrain()):(this.lngRange=null,this.latRange=[-this.maxValidLatitude,this.maxValidLatitude])},Pn.prototype.calculatePosMatrix=function(e,r){void 0===r&&(r=!1);var n=e.key,i=r?this._alignedPosMatrixCache:this._posMatrixCache;if(i[n])return i[n];var a=e.canonical,o=this.worldSize/this.zoomScale(a.z),s=a.x+Math.pow(2,a.z)*e.wrap,l=t.identity(new Float64Array(16));return t.translate(l,l,[s*o,a.y*o,0]),t.scale(l,l,[o/t.EXTENT,o/t.EXTENT,1]),t.multiply(l,r?this.alignedProjMatrix:this.projMatrix,l),i[n]=new Float32Array(l),i[n]},Pn.prototype.customLayerMatrix=function(){return this.mercatorMatrix.slice()},Pn.prototype._constrain=function(){if(this.center&&this.width&&this.height&&!this._constraining){this._constraining=!0;var e,r,n,i,a=-90,o=90,s=-180,l=180,u=this.size,c=this._unmodified;if(this.latRange){var f=this.latRange;a=t.mercatorYfromLat(f[1])*this.worldSize,e=(o=t.mercatorYfromLat(f[0])*this.worldSize)-a<u.y?u.y/(o-a):0}if(this.lngRange){var h=this.lngRange;s=t.mercatorXfromLng(h[0])*this.worldSize,r=(l=t.mercatorXfromLng(h[1])*this.worldSize)-s<u.x?u.x/(l-s):0}var p=this.point,d=Math.max(r||0,e||0);if(d)return this.center=this.unproject(new t.Point(r?(l+s)/2:p.x,e?(o+a)/2:p.y)),this.zoom+=this.scaleZoom(d),this._unmodified=c,void(this._constraining=!1);if(this.latRange){var v=p.y,g=u.y/2;v-g<a&&(i=a+g),v+g>o&&(i=o-g)}if(this.lngRange){var y=p.x,m=u.x/2;y-m<s&&(n=s+m),y+m>l&&(n=l-m)}void 0===n&&void 0===i||(this.center=this.unproject(new t.Point(void 0!==n?n:p.x,void 0!==i?i:p.y))),this._unmodified=c,this._constraining=!1}},Pn.prototype._calcMatrices=function(){if(this.height){var e=this._fov/2,r=this.centerOffset;this.cameraToCenterDistance=.5/Math.tan(e)*this.height;var n=Math.PI/2+this._pitch,i=this._fov*(.5+r.y/this.height),a=Math.sin(i)*this.cameraToCenterDistance/Math.sin(t.clamp(Math.PI-n-i,.01,Math.PI-.01)),o=this.point,s=o.x,l=o.y,u=1.01*(Math.cos(Math.PI/2-this._pitch)*a+this.cameraToCenterDistance),c=this.height/50,f=new Float64Array(16);t.perspective(f,this._fov,this.width/this.height,c,u),f[8]=2*-r.x/this.width,f[9]=2*r.y/this.height,t.scale(f,f,[1,-1,1]),t.translate(f,f,[0,0,-this.cameraToCenterDistance]),t.rotateX(f,f,this._pitch),t.rotateZ(f,f,this.angle),t.translate(f,f,[-s,-l,0]),this.mercatorMatrix=t.scale([],f,[this.worldSize,this.worldSize,this.worldSize]),t.scale(f,f,[1,1,t.mercatorZfromAltitude(1,this.center.lat)*this.worldSize,1]),this.projMatrix=f,this.invProjMatrix=t.invert([],this.projMatrix);var h=this.width%2/2,p=this.height%2/2,d=Math.cos(this.angle),v=Math.sin(this.angle),g=s-Math.round(s)+d*h+v*p,y=l-Math.round(l)+d*p+v*h,m=new Float64Array(f);if(t.translate(m,m,[g>.5?g-1:g,y>.5?y-1:y,0]),this.alignedProjMatrix=m,f=t.create(),t.scale(f,f,[this.width/2,-this.height/2,1]),t.translate(f,f,[1,-1,0]),this.labelPlaneMatrix=f,f=t.create(),t.scale(f,f,[1,-1,1]),t.translate(f,f,[-1,-1,0]),t.scale(f,f,[2/this.width,2/this.height,1]),this.glCoordMatrix=f,this.pixelMatrix=t.multiply(new Float64Array(16),this.labelPlaneMatrix,this.projMatrix),!(f=t.invert(new Float64Array(16),this.pixelMatrix)))throw new Error(\"failed to invert matrix\");this.pixelMatrixInverse=f,this._posMatrixCache={},this._alignedPosMatrixCache={}}},Pn.prototype.maxPitchScaleFactor=function(){if(!this.pixelMatrixInverse)return 1;var e=this.pointCoordinate(new t.Point(0,0)),r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix)[3]/this.cameraToCenterDistance},Pn.prototype.getCameraPoint=function(){var e=this._pitch,r=Math.tan(e)*(this.cameraToCenterDistance||1);return this.centerPoint.add(new t.Point(0,r))},Pn.prototype.getCameraQueryGeometry=function(e){var r=this.getCameraPoint();if(1===e.length)return[e[0],r];for(var n=r.x,i=r.y,a=r.x,o=r.y,s=0,l=e;s<l.length;s+=1){var u=l[s];n=Math.min(n,u.x),i=Math.min(i,u.y),a=Math.max(a,u.x),o=Math.max(o,u.y)}return[new t.Point(n,i),new t.Point(a,i),new t.Point(a,o),new t.Point(n,o),new t.Point(n,i)]},Object.defineProperties(Pn.prototype,On);var In=function(e){var r,n,i,a,o;this._hashName=e&&encodeURIComponent(e),t.bindAll([\"_getCurrentHash\",\"_onHashChange\",\"_updateHash\"],this),this._updateHash=(r=this._updateHashUnthrottled.bind(this),n=300,i=!1,a=null,o=function(){a=null,i&&(r(),a=setTimeout(o,n),i=!1)},function(){return i=!0,a||o(),a})};In.prototype.addTo=function(e){return this._map=e,t.window.addEventListener(\"hashchange\",this._onHashChange,!1),this._map.on(\"moveend\",this._updateHash),this},In.prototype.remove=function(){return t.window.removeEventListener(\"hashchange\",this._onHashChange,!1),this._map.off(\"moveend\",this._updateHash),clearTimeout(this._updateHash()),delete this._map,this},In.prototype.getHashString=function(e){var r=this._map.getCenter(),n=Math.round(100*this._map.getZoom())/100,i=Math.ceil((n*Math.LN2+Math.log(512/360/.5))/Math.LN10),a=Math.pow(10,i),o=Math.round(r.lng*a)/a,s=Math.round(r.lat*a)/a,l=this._map.getBearing(),u=this._map.getPitch(),c=\"\";if(c+=e?\"/\"+o+\"/\"+s+\"/\"+n:n+\"/\"+s+\"/\"+o,(l||u)&&(c+=\"/\"+Math.round(10*l)/10),u&&(c+=\"/\"+Math.round(u)),this._hashName){var f=this._hashName,h=!1,p=t.window.location.hash.slice(1).split(\"&\").map((function(t){var e=t.split(\"=\")[0];return e===f?(h=!0,e+\"=\"+c):t})).filter((function(t){return t}));return h||p.push(f+\"=\"+c),\"#\"+p.join(\"&\")}return\"#\"+c},In.prototype._getCurrentHash=function(){var e,r=this,n=t.window.location.hash.replace(\"#\",\"\");return this._hashName?(n.split(\"&\").map((function(t){return t.split(\"=\")})).forEach((function(t){t[0]===r._hashName&&(e=t)})),(e&&e[1]||\"\").split(\"/\")):n.split(\"/\")},In.prototype._onHashChange=function(){var t=this._getCurrentHash();if(t.length>=3&&!t.some((function(t){return isNaN(t)}))){var e=this._map.dragRotate.isEnabled()&&this._map.touchZoomRotate.isEnabled()?+(t[3]||0):this._map.getBearing();return this._map.jumpTo({center:[+t[2],+t[1]],zoom:+t[0],bearing:e,pitch:+(t[4]||0)}),!0}return!1},In.prototype._updateHashUnthrottled=function(){var e=t.window.location.href.replace(/(#.+)?$/,this.getHashString());try{t.window.history.replaceState(t.window.history.state,null,e)}catch(t){}};var Dn={linearity:.3,easing:t.bezier(0,0,.3,1)},zn=t.extend({deceleration:2500,maxSpeed:1400},Dn),Rn=t.extend({deceleration:20,maxSpeed:1400},Dn),Fn=t.extend({deceleration:1e3,maxSpeed:360},Dn),Bn=t.extend({deceleration:1e3,maxSpeed:90},Dn),Nn=function(t){this._map=t,this.clear()};function jn(t,e){(!t.duration||t.duration<e.duration)&&(t.duration=e.duration,t.easing=e.easing)}function Un(e,r,n){var i=n.maxSpeed,a=n.linearity,o=n.deceleration,s=t.clamp(e*a/(r/1e3),-i,i),l=Math.abs(s)/(o*a);return{easing:n.easing,duration:1e3*l,amount:s*(l/2)}}Nn.prototype.clear=function(){this._inertiaBuffer=[]},Nn.prototype.record=function(e){this._drainInertiaBuffer(),this._inertiaBuffer.push({time:t.browser.now(),settings:e})},Nn.prototype._drainInertiaBuffer=function(){for(var e=this._inertiaBuffer,r=t.browser.now();e.length>0&&r-e[0].time>160;)e.shift()},Nn.prototype._onMoveEnd=function(e){if(this._drainInertiaBuffer(),!(this._inertiaBuffer.length<2)){for(var r={zoom:0,bearing:0,pitch:0,pan:new t.Point(0,0),pinchAround:void 0,around:void 0},n=0,i=this._inertiaBuffer;n<i.length;n+=1){var a=i[n].settings;r.zoom+=a.zoomDelta||0,r.bearing+=a.bearingDelta||0,r.pitch+=a.pitchDelta||0,a.panDelta&&r.pan._add(a.panDelta),a.around&&(r.around=a.around),a.pinchAround&&(r.pinchAround=a.pinchAround)}var o=this._inertiaBuffer[this._inertiaBuffer.length-1].time-this._inertiaBuffer[0].time,s={};if(r.pan.mag()){var l=Un(r.pan.mag(),o,t.extend({},zn,e||{}));s.offset=r.pan.mult(l.amount/r.pan.mag()),s.center=this._map.transform.center,jn(s,l)}if(r.zoom){var u=Un(r.zoom,o,Rn);s.zoom=this._map.transform.zoom+u.amount,jn(s,u)}if(r.bearing){var c=Un(r.bearing,o,Fn);s.bearing=this._map.transform.bearing+t.clamp(c.amount,-179,179),jn(s,c)}if(r.pitch){var f=Un(r.pitch,o,Bn);s.pitch=this._map.transform.pitch+f.amount,jn(s,f)}if(s.zoom||s.bearing){var h=void 0===r.pinchAround?r.around:r.pinchAround;s.around=h?this._map.unproject(h):this._map.getCenter()}return this.clear(),t.extend(s,{noMoveStart:!0})}};var Vn=function(e){function n(n,i,a,o){void 0===o&&(o={});var s=r.mousePos(i.getCanvasContainer(),a),l=i.unproject(s);e.call(this,n,t.extend({point:s,lngLat:l,originalEvent:a},o)),this._defaultPrevented=!1,this.target=i}e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n;var i={defaultPrevented:{configurable:!0}};return n.prototype.preventDefault=function(){this._defaultPrevented=!0},i.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(n.prototype,i),n}(t.Event),qn=function(e){function n(n,i,a){var o=\"touchend\"===n?a.changedTouches:a.touches,s=r.touchPos(i.getCanvasContainer(),o),l=s.map((function(t){return i.unproject(t)})),u=s.reduce((function(t,e,r,n){return t.add(e.div(n.length))}),new t.Point(0,0)),c=i.unproject(u);e.call(this,n,{points:s,point:u,lngLats:l,lngLat:c,originalEvent:a}),this._defaultPrevented=!1}e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n;var i={defaultPrevented:{configurable:!0}};return n.prototype.preventDefault=function(){this._defaultPrevented=!0},i.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(n.prototype,i),n}(t.Event),Hn=function(t){function e(e,r,n){t.call(this,e,{originalEvent:n}),this._defaultPrevented=!1}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={defaultPrevented:{configurable:!0}};return e.prototype.preventDefault=function(){this._defaultPrevented=!0},r.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(e.prototype,r),e}(t.Event),Gn=function(t,e){this._map=t,this._clickTolerance=e.clickTolerance};Gn.prototype.reset=function(){delete this._mousedownPos},Gn.prototype.wheel=function(t){return this._firePreventable(new Hn(t.type,this._map,t))},Gn.prototype.mousedown=function(t,e){return this._mousedownPos=e,this._firePreventable(new Vn(t.type,this._map,t))},Gn.prototype.mouseup=function(t){this._map.fire(new Vn(t.type,this._map,t))},Gn.prototype.click=function(t,e){this._mousedownPos&&this._mousedownPos.dist(e)>=this._clickTolerance||this._map.fire(new Vn(t.type,this._map,t))},Gn.prototype.dblclick=function(t){return this._firePreventable(new Vn(t.type,this._map,t))},Gn.prototype.mouseover=function(t){this._map.fire(new Vn(t.type,this._map,t))},Gn.prototype.mouseout=function(t){this._map.fire(new Vn(t.type,this._map,t))},Gn.prototype.touchstart=function(t){return this._firePreventable(new qn(t.type,this._map,t))},Gn.prototype.touchmove=function(t){this._map.fire(new qn(t.type,this._map,t))},Gn.prototype.touchend=function(t){this._map.fire(new qn(t.type,this._map,t))},Gn.prototype.touchcancel=function(t){this._map.fire(new qn(t.type,this._map,t))},Gn.prototype._firePreventable=function(t){if(this._map.fire(t),t.defaultPrevented)return{}},Gn.prototype.isEnabled=function(){return!0},Gn.prototype.isActive=function(){return!1},Gn.prototype.enable=function(){},Gn.prototype.disable=function(){};var Wn=function(t){this._map=t};Wn.prototype.reset=function(){this._delayContextMenu=!1,delete this._contextMenuEvent},Wn.prototype.mousemove=function(t){this._map.fire(new Vn(t.type,this._map,t))},Wn.prototype.mousedown=function(){this._delayContextMenu=!0},Wn.prototype.mouseup=function(){this._delayContextMenu=!1,this._contextMenuEvent&&(this._map.fire(new Vn(\"contextmenu\",this._map,this._contextMenuEvent)),delete this._contextMenuEvent)},Wn.prototype.contextmenu=function(t){this._delayContextMenu?this._contextMenuEvent=t:this._map.fire(new Vn(t.type,this._map,t)),this._map.listens(\"contextmenu\")&&t.preventDefault()},Wn.prototype.isEnabled=function(){return!0},Wn.prototype.isActive=function(){return!1},Wn.prototype.enable=function(){},Wn.prototype.disable=function(){};var Yn=function(t,e){this._map=t,this._el=t.getCanvasContainer(),this._container=t.getContainer(),this._clickTolerance=e.clickTolerance||1};function Xn(t,e){for(var r={},n=0;n<t.length;n++)r[t[n].identifier]=e[n];return r}Yn.prototype.isEnabled=function(){return!!this._enabled},Yn.prototype.isActive=function(){return!!this._active},Yn.prototype.enable=function(){this.isEnabled()||(this._enabled=!0)},Yn.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},Yn.prototype.mousedown=function(t,e){this.isEnabled()&&t.shiftKey&&0===t.button&&(r.disableDrag(),this._startPos=this._lastPos=e,this._active=!0)},Yn.prototype.mousemoveWindow=function(t,e){if(this._active){var n=e;if(!(this._lastPos.equals(n)||!this._box&&n.dist(this._startPos)<this._clickTolerance)){var i=this._startPos;this._lastPos=n,this._box||(this._box=r.create(\"div\",\"mapboxgl-boxzoom\",this._container),this._container.classList.add(\"mapboxgl-crosshair\"),this._fireEvent(\"boxzoomstart\",t));var a=Math.min(i.x,n.x),o=Math.max(i.x,n.x),s=Math.min(i.y,n.y),l=Math.max(i.y,n.y);r.setTransform(this._box,\"translate(\"+a+\"px,\"+s+\"px)\"),this._box.style.width=o-a+\"px\",this._box.style.height=l-s+\"px\"}}},Yn.prototype.mouseupWindow=function(e,n){var i=this;if(this._active&&0===e.button){var a=this._startPos,o=n;if(this.reset(),r.suppressClick(),a.x!==o.x||a.y!==o.y)return this._map.fire(new t.Event(\"boxzoomend\",{originalEvent:e})),{cameraAnimation:function(t){return t.fitScreenCoordinates(a,o,i._map.getBearing(),{linear:!0})}};this._fireEvent(\"boxzoomcancel\",e)}},Yn.prototype.keydown=function(t){this._active&&27===t.keyCode&&(this.reset(),this._fireEvent(\"boxzoomcancel\",t))},Yn.prototype.reset=function(){this._active=!1,this._container.classList.remove(\"mapboxgl-crosshair\"),this._box&&(r.remove(this._box),this._box=null),r.enableDrag(),delete this._startPos,delete this._lastPos},Yn.prototype._fireEvent=function(e,r){return this._map.fire(new t.Event(e,{originalEvent:r}))};var Zn=function(t){this.reset(),this.numTouches=t.numTouches};Zn.prototype.reset=function(){delete this.centroid,delete this.startTime,delete this.touches,this.aborted=!1},Zn.prototype.touchstart=function(e,r,n){(this.centroid||n.length>this.numTouches)&&(this.aborted=!0),this.aborted||(void 0===this.startTime&&(this.startTime=e.timeStamp),n.length===this.numTouches&&(this.centroid=function(e){for(var r=new t.Point(0,0),n=0,i=e;n<i.length;n+=1){var a=i[n];r._add(a)}return r.div(e.length)}(r),this.touches=Xn(n,r)))},Zn.prototype.touchmove=function(t,e,r){if(!this.aborted&&this.centroid){var n=Xn(r,e);for(var i in this.touches){var a=this.touches[i],o=n[i];(!o||o.dist(a)>30)&&(this.aborted=!0)}}},Zn.prototype.touchend=function(t,e,r){if((!this.centroid||t.timeStamp-this.startTime>500)&&(this.aborted=!0),0===r.length){var n=!this.aborted&&this.centroid;if(this.reset(),n)return n}};var Kn=function(t){this.singleTap=new Zn(t),this.numTaps=t.numTaps,this.reset()};Kn.prototype.reset=function(){this.lastTime=1/0,delete this.lastTap,this.count=0,this.singleTap.reset()},Kn.prototype.touchstart=function(t,e,r){this.singleTap.touchstart(t,e,r)},Kn.prototype.touchmove=function(t,e,r){this.singleTap.touchmove(t,e,r)},Kn.prototype.touchend=function(t,e,r){var n=this.singleTap.touchend(t,e,r);if(n){var i=t.timeStamp-this.lastTime<500,a=!this.lastTap||this.lastTap.dist(n)<30;if(i&&a||this.reset(),this.count++,this.lastTime=t.timeStamp,this.lastTap=n,this.count===this.numTaps)return this.reset(),n}};var Jn=function(){this._zoomIn=new Kn({numTouches:1,numTaps:2}),this._zoomOut=new Kn({numTouches:2,numTaps:1}),this.reset()};Jn.prototype.reset=function(){this._active=!1,this._zoomIn.reset(),this._zoomOut.reset()},Jn.prototype.touchstart=function(t,e,r){this._zoomIn.touchstart(t,e,r),this._zoomOut.touchstart(t,e,r)},Jn.prototype.touchmove=function(t,e,r){this._zoomIn.touchmove(t,e,r),this._zoomOut.touchmove(t,e,r)},Jn.prototype.touchend=function(t,e,r){var n=this,i=this._zoomIn.touchend(t,e,r),a=this._zoomOut.touchend(t,e,r);return i?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()+1,around:e.unproject(i)},{originalEvent:t})}}):a?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()-1,around:e.unproject(a)},{originalEvent:t})}}):void 0},Jn.prototype.touchcancel=function(){this.reset()},Jn.prototype.enable=function(){this._enabled=!0},Jn.prototype.disable=function(){this._enabled=!1,this.reset()},Jn.prototype.isEnabled=function(){return this._enabled},Jn.prototype.isActive=function(){return this._active};var $n={};$n[0]=1,$n[2]=2;var Qn=function(t){this.reset(),this._clickTolerance=t.clickTolerance||1};Qn.prototype.reset=function(){this._active=!1,this._moved=!1,delete this._lastPoint,delete this._eventButton},Qn.prototype._correctButton=function(t,e){return!1},Qn.prototype._move=function(t,e){return{}},Qn.prototype.mousedown=function(t,e){if(!this._lastPoint){var n=r.mouseButton(t);this._correctButton(t,n)&&(this._lastPoint=e,this._eventButton=n)}},Qn.prototype.mousemoveWindow=function(t,e){var r=this._lastPoint;if(r)if(t.preventDefault(),function(t,e){var r=$n[e];return void 0===t.buttons||(t.buttons&r)!==r}(t,this._eventButton))this.reset();else if(this._moved||!(e.dist(r)<this._clickTolerance))return this._moved=!0,this._lastPoint=e,this._move(r,e)},Qn.prototype.mouseupWindow=function(t){this._lastPoint&&r.mouseButton(t)===this._eventButton&&(this._moved&&r.suppressClick(),this.reset())},Qn.prototype.enable=function(){this._enabled=!0},Qn.prototype.disable=function(){this._enabled=!1,this.reset()},Qn.prototype.isEnabled=function(){return this._enabled},Qn.prototype.isActive=function(){return this._active};var ti=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.mousedown=function(e,r){t.prototype.mousedown.call(this,e,r),this._lastPoint&&(this._active=!0)},e.prototype._correctButton=function(t,e){return 0===e&&!t.ctrlKey},e.prototype._move=function(t,e){return{around:e,panDelta:e.sub(t)}},e}(Qn),ei=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._correctButton=function(t,e){return 0===e&&t.ctrlKey||2===e},e.prototype._move=function(t,e){var r=.8*(e.x-t.x);if(r)return this._active=!0,{bearingDelta:r}},e.prototype.contextmenu=function(t){t.preventDefault()},e}(Qn),ri=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._correctButton=function(t,e){return 0===e&&t.ctrlKey||2===e},e.prototype._move=function(t,e){var r=-.5*(e.y-t.y);if(r)return this._active=!0,{pitchDelta:r}},e.prototype.contextmenu=function(t){t.preventDefault()},e}(Qn),ni=function(t){this._minTouches=1,this._clickTolerance=t.clickTolerance||1,this.reset()};ni.prototype.reset=function(){this._active=!1,this._touches={},this._sum=new t.Point(0,0)},ni.prototype.touchstart=function(t,e,r){return this._calculateTransform(t,e,r)},ni.prototype.touchmove=function(t,e,r){if(this._active&&!(r.length<this._minTouches))return t.preventDefault(),this._calculateTransform(t,e,r)},ni.prototype.touchend=function(t,e,r){this._calculateTransform(t,e,r),this._active&&r.length<this._minTouches&&this.reset()},ni.prototype.touchcancel=function(){this.reset()},ni.prototype._calculateTransform=function(e,r,n){n.length>0&&(this._active=!0);var i=Xn(n,r),a=new t.Point(0,0),o=new t.Point(0,0),s=0;for(var l in i){var u=i[l],c=this._touches[l];c&&(a._add(u),o._add(u.sub(c)),s++,i[l]=u)}if(this._touches=i,!(s<this._minTouches)&&o.mag()){var f=o.div(s);if(this._sum._add(f),!(this._sum.mag()<this._clickTolerance))return{around:a.div(s),panDelta:f}}},ni.prototype.enable=function(){this._enabled=!0},ni.prototype.disable=function(){this._enabled=!1,this.reset()},ni.prototype.isEnabled=function(){return this._enabled},ni.prototype.isActive=function(){return this._active};var ii=function(){this.reset()};function ai(t,e,r){for(var n=0;n<t.length;n++)if(t[n].identifier===r)return e[n]}ii.prototype.reset=function(){this._active=!1,delete this._firstTwoTouches},ii.prototype._start=function(t){},ii.prototype._move=function(t,e,r){return{}},ii.prototype.touchstart=function(t,e,r){this._firstTwoTouches||r.length<2||(this._firstTwoTouches=[r[0].identifier,r[1].identifier],this._start([e[0],e[1]]))},ii.prototype.touchmove=function(t,e,r){if(this._firstTwoTouches){t.preventDefault();var n=this._firstTwoTouches,i=n[0],a=n[1],o=ai(r,e,i),s=ai(r,e,a);if(o&&s){var l=this._aroundCenter?null:o.add(s).div(2);return this._move([o,s],l,t)}}},ii.prototype.touchend=function(t,e,n){if(this._firstTwoTouches){var i=this._firstTwoTouches,a=i[0],o=i[1],s=ai(n,e,a),l=ai(n,e,o);s&&l||(this._active&&r.suppressClick(),this.reset())}},ii.prototype.touchcancel=function(){this.reset()},ii.prototype.enable=function(t){this._enabled=!0,this._aroundCenter=!!t&&\"center\"===t.around},ii.prototype.disable=function(){this._enabled=!1,this.reset()},ii.prototype.isEnabled=function(){return this._enabled},ii.prototype.isActive=function(){return this._active};function oi(t,e){return Math.log(t/e)/Math.LN2}var si=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),delete this._distance,delete this._startDistance},e.prototype._start=function(t){this._startDistance=this._distance=t[0].dist(t[1])},e.prototype._move=function(t,e){var r=this._distance;if(this._distance=t[0].dist(t[1]),this._active||!(Math.abs(oi(this._distance,this._startDistance))<.1))return this._active=!0,{zoomDelta:oi(this._distance,r),pinchAround:e}},e}(ii);function li(t,e){return 180*t.angleWith(e)/Math.PI}var ui=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),delete this._minDiameter,delete this._startVector,delete this._vector},e.prototype._start=function(t){this._startVector=this._vector=t[0].sub(t[1]),this._minDiameter=t[0].dist(t[1])},e.prototype._move=function(t,e){var r=this._vector;if(this._vector=t[0].sub(t[1]),this._active||!this._isBelowThreshold(this._vector))return this._active=!0,{bearingDelta:li(this._vector,r),pinchAround:e}},e.prototype._isBelowThreshold=function(t){this._minDiameter=Math.min(this._minDiameter,t.mag());var e=25/(Math.PI*this._minDiameter)*360,r=li(t,this._startVector);return Math.abs(r)<e},e}(ii);function ci(t){return Math.abs(t.y)>Math.abs(t.x)}var fi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),this._valid=void 0,delete this._firstMove,delete this._lastPoints},e.prototype._start=function(t){this._lastPoints=t,ci(t[0].sub(t[1]))&&(this._valid=!1)},e.prototype._move=function(t,e,r){var n=t[0].sub(this._lastPoints[0]),i=t[1].sub(this._lastPoints[1]);if(this._valid=this.gestureBeginsVertically(n,i,r.timeStamp),this._valid)return this._lastPoints=t,this._active=!0,{pitchDelta:(n.y+i.y)/2*-.5}},e.prototype.gestureBeginsVertically=function(t,e,r){if(void 0!==this._valid)return this._valid;var n=t.mag()>=2,i=e.mag()>=2;if(n||i){if(!n||!i)return void 0===this._firstMove&&(this._firstMove=r),r-this._firstMove<100&&void 0;var a=t.y>0==e.y>0;return ci(t)&&ci(e)&&a}},e}(ii),hi={panStep:100,bearingStep:15,pitchStep:10},pi=function(){var t=hi;this._panStep=t.panStep,this._bearingStep=t.bearingStep,this._pitchStep=t.pitchStep,this._rotationDisabled=!1};function di(t){return t*(2-t)}pi.prototype.reset=function(){this._active=!1},pi.prototype.keydown=function(t){var e=this;if(!(t.altKey||t.ctrlKey||t.metaKey)){var r=0,n=0,i=0,a=0,o=0;switch(t.keyCode){case 61:case 107:case 171:case 187:r=1;break;case 189:case 109:case 173:r=-1;break;case 37:t.shiftKey?n=-1:(t.preventDefault(),a=-1);break;case 39:t.shiftKey?n=1:(t.preventDefault(),a=1);break;case 38:t.shiftKey?i=1:(t.preventDefault(),o=-1);break;case 40:t.shiftKey?i=-1:(t.preventDefault(),o=1);break;default:return}return this._rotationDisabled&&(n=0,i=0),{cameraAnimation:function(s){var l=s.getZoom();s.easeTo({duration:300,easeId:\"keyboardHandler\",easing:di,zoom:r?Math.round(l)+r*(t.shiftKey?2:1):l,bearing:s.getBearing()+n*e._bearingStep,pitch:s.getPitch()+i*e._pitchStep,offset:[-a*e._panStep,-o*e._panStep],center:s.getCenter()},{originalEvent:t})}}}},pi.prototype.enable=function(){this._enabled=!0},pi.prototype.disable=function(){this._enabled=!1,this.reset()},pi.prototype.isEnabled=function(){return this._enabled},pi.prototype.isActive=function(){return this._active},pi.prototype.disableRotation=function(){this._rotationDisabled=!0},pi.prototype.enableRotation=function(){this._rotationDisabled=!1};var vi=4.000244140625,gi=function(e,r){this._map=e,this._el=e.getCanvasContainer(),this._handler=r,this._delta=0,this._defaultZoomRate=.01,this._wheelZoomRate=.0022222222222222222,t.bindAll([\"_onTimeout\"],this)};gi.prototype.setZoomRate=function(t){this._defaultZoomRate=t},gi.prototype.setWheelZoomRate=function(t){this._wheelZoomRate=t},gi.prototype.isEnabled=function(){return!!this._enabled},gi.prototype.isActive=function(){return!!this._active||void 0!==this._finishTimeout},gi.prototype.isZooming=function(){return!!this._zooming},gi.prototype.enable=function(t){this.isEnabled()||(this._enabled=!0,this._aroundCenter=t&&\"center\"===t.around)},gi.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},gi.prototype.wheel=function(e){if(this.isEnabled()){var r=e.deltaMode===t.window.WheelEvent.DOM_DELTA_LINE?40*e.deltaY:e.deltaY,n=t.browser.now(),i=n-(this._lastWheelEventTime||0);this._lastWheelEventTime=n,0!==r&&r%vi==0?this._type=\"wheel\":0!==r&&Math.abs(r)<4?this._type=\"trackpad\":i>400?(this._type=null,this._lastValue=r,this._timeout=setTimeout(this._onTimeout,40,e)):this._type||(this._type=Math.abs(i*r)<200?\"trackpad\":\"wheel\",this._timeout&&(clearTimeout(this._timeout),this._timeout=null,r+=this._lastValue)),e.shiftKey&&r&&(r/=4),this._type&&(this._lastWheelEvent=e,this._delta-=r,this._active||this._start(e)),e.preventDefault()}},gi.prototype._onTimeout=function(t){this._type=\"wheel\",this._delta-=this._lastValue,this._active||this._start(t)},gi.prototype._start=function(e){if(this._delta){this._frameId&&(this._frameId=null),this._active=!0,this.isZooming()||(this._zooming=!0),this._finishTimeout&&(clearTimeout(this._finishTimeout),delete this._finishTimeout);var n=r.mousePos(this._el,e);this._around=t.LngLat.convert(this._aroundCenter?this._map.getCenter():this._map.unproject(n)),this._aroundPoint=this._map.transform.locationPoint(this._around),this._frameId||(this._frameId=!0,this._handler._triggerRenderFrame())}},gi.prototype.renderFrame=function(){var e=this;if(this._frameId&&(this._frameId=null,this.isActive())){var r=this._map.transform;if(0!==this._delta){var n=\"wheel\"===this._type&&Math.abs(this._delta)>vi?this._wheelZoomRate:this._defaultZoomRate,i=2/(1+Math.exp(-Math.abs(this._delta*n)));this._delta<0&&0!==i&&(i=1/i);var a=\"number\"==typeof this._targetZoom?r.zoomScale(this._targetZoom):r.scale;this._targetZoom=Math.min(r.maxZoom,Math.max(r.minZoom,r.scaleZoom(a*i))),\"wheel\"===this._type&&(this._startZoom=r.zoom,this._easing=this._smoothOutEasing(200)),this._delta=0}var o,s=\"number\"==typeof this._targetZoom?this._targetZoom:r.zoom,l=this._startZoom,u=this._easing,c=!1;if(\"wheel\"===this._type&&l&&u){var f=Math.min((t.browser.now()-this._lastWheelEventTime)/200,1),h=u(f);o=t.number(l,s,h),f<1?this._frameId||(this._frameId=!0):c=!0}else o=s,c=!0;return this._active=!0,c&&(this._active=!1,this._finishTimeout=setTimeout((function(){e._zooming=!1,e._handler._triggerRenderFrame(),delete e._targetZoom,delete e._finishTimeout}),200)),{noInertia:!0,needsRenderFrame:!c,zoomDelta:o-r.zoom,around:this._aroundPoint,originalEvent:this._lastWheelEvent}}},gi.prototype._smoothOutEasing=function(e){var r=t.ease;if(this._prevEase){var n=this._prevEase,i=(t.browser.now()-n.start)/n.duration,a=n.easing(i+.01)-n.easing(i),o=.27/Math.sqrt(a*a+1e-4)*.01,s=Math.sqrt(.0729-o*o);r=t.bezier(o,s,.25,1)}return this._prevEase={start:t.browser.now(),duration:e,easing:r},r},gi.prototype.reset=function(){this._active=!1};var yi=function(t,e){this._clickZoom=t,this._tapZoom=e};yi.prototype.enable=function(){this._clickZoom.enable(),this._tapZoom.enable()},yi.prototype.disable=function(){this._clickZoom.disable(),this._tapZoom.disable()},yi.prototype.isEnabled=function(){return this._clickZoom.isEnabled()&&this._tapZoom.isEnabled()},yi.prototype.isActive=function(){return this._clickZoom.isActive()||this._tapZoom.isActive()};var mi=function(){this.reset()};mi.prototype.reset=function(){this._active=!1},mi.prototype.dblclick=function(t,e){return t.preventDefault(),{cameraAnimation:function(r){r.easeTo({duration:300,zoom:r.getZoom()+(t.shiftKey?-1:1),around:r.unproject(e)},{originalEvent:t})}}},mi.prototype.enable=function(){this._enabled=!0},mi.prototype.disable=function(){this._enabled=!1,this.reset()},mi.prototype.isEnabled=function(){return this._enabled},mi.prototype.isActive=function(){return this._active};var xi=function(){this._tap=new Kn({numTouches:1,numTaps:1}),this.reset()};xi.prototype.reset=function(){this._active=!1,delete this._swipePoint,delete this._swipeTouch,delete this._tapTime,this._tap.reset()},xi.prototype.touchstart=function(t,e,r){this._swipePoint||(this._tapTime&&t.timeStamp-this._tapTime>500&&this.reset(),this._tapTime?r.length>0&&(this._swipePoint=e[0],this._swipeTouch=r[0].identifier):this._tap.touchstart(t,e,r))},xi.prototype.touchmove=function(t,e,r){if(this._tapTime){if(this._swipePoint){if(r[0].identifier!==this._swipeTouch)return;var n=e[0],i=n.y-this._swipePoint.y;return this._swipePoint=n,t.preventDefault(),this._active=!0,{zoomDelta:i/128}}}else this._tap.touchmove(t,e,r)},xi.prototype.touchend=function(t,e,r){this._tapTime?this._swipePoint&&0===r.length&&this.reset():this._tap.touchend(t,e,r)&&(this._tapTime=t.timeStamp)},xi.prototype.touchcancel=function(){this.reset()},xi.prototype.enable=function(){this._enabled=!0},xi.prototype.disable=function(){this._enabled=!1,this.reset()},xi.prototype.isEnabled=function(){return this._enabled},xi.prototype.isActive=function(){return this._active};var bi=function(t,e,r){this._el=t,this._mousePan=e,this._touchPan=r};bi.prototype.enable=function(t){this._inertiaOptions=t||{},this._mousePan.enable(),this._touchPan.enable(),this._el.classList.add(\"mapboxgl-touch-drag-pan\")},bi.prototype.disable=function(){this._mousePan.disable(),this._touchPan.disable(),this._el.classList.remove(\"mapboxgl-touch-drag-pan\")},bi.prototype.isEnabled=function(){return this._mousePan.isEnabled()&&this._touchPan.isEnabled()},bi.prototype.isActive=function(){return this._mousePan.isActive()||this._touchPan.isActive()};var _i=function(t,e,r){this._pitchWithRotate=t.pitchWithRotate,this._mouseRotate=e,this._mousePitch=r};_i.prototype.enable=function(){this._mouseRotate.enable(),this._pitchWithRotate&&this._mousePitch.enable()},_i.prototype.disable=function(){this._mouseRotate.disable(),this._mousePitch.disable()},_i.prototype.isEnabled=function(){return this._mouseRotate.isEnabled()&&(!this._pitchWithRotate||this._mousePitch.isEnabled())},_i.prototype.isActive=function(){return this._mouseRotate.isActive()||this._mousePitch.isActive()};var wi=function(t,e,r,n){this._el=t,this._touchZoom=e,this._touchRotate=r,this._tapDragZoom=n,this._rotationDisabled=!1,this._enabled=!0};wi.prototype.enable=function(t){this._touchZoom.enable(t),this._rotationDisabled||this._touchRotate.enable(t),this._tapDragZoom.enable(),this._el.classList.add(\"mapboxgl-touch-zoom-rotate\")},wi.prototype.disable=function(){this._touchZoom.disable(),this._touchRotate.disable(),this._tapDragZoom.disable(),this._el.classList.remove(\"mapboxgl-touch-zoom-rotate\")},wi.prototype.isEnabled=function(){return this._touchZoom.isEnabled()&&(this._rotationDisabled||this._touchRotate.isEnabled())&&this._tapDragZoom.isEnabled()},wi.prototype.isActive=function(){return this._touchZoom.isActive()||this._touchRotate.isActive()||this._tapDragZoom.isActive()},wi.prototype.disableRotation=function(){this._rotationDisabled=!0,this._touchRotate.disable()},wi.prototype.enableRotation=function(){this._rotationDisabled=!1,this._touchZoom.isEnabled()&&this._touchRotate.enable()};var Ti=function(t){return t.zoom||t.drag||t.pitch||t.rotate},ki=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(t.Event);function Ai(t){return t.panDelta&&t.panDelta.mag()||t.zoomDelta||t.bearingDelta||t.pitchDelta}var Mi=function(e,n){this._map=e,this._el=this._map.getCanvasContainer(),this._handlers=[],this._handlersById={},this._changes=[],this._inertia=new Nn(e),this._bearingSnap=n.bearingSnap,this._previousActiveHandlers={},this._eventsInProgress={},this._addDefaultHandlers(n),t.bindAll([\"handleEvent\",\"handleWindowEvent\"],this);var i=this._el;this._listeners=[[i,\"touchstart\",{passive:!0}],[i,\"touchmove\",{passive:!1}],[i,\"touchend\",void 0],[i,\"touchcancel\",void 0],[i,\"mousedown\",void 0],[i,\"mousemove\",void 0],[i,\"mouseup\",void 0],[t.window.document,\"mousemove\",{capture:!0}],[t.window.document,\"mouseup\",void 0],[i,\"mouseover\",void 0],[i,\"mouseout\",void 0],[i,\"dblclick\",void 0],[i,\"click\",void 0],[i,\"keydown\",{capture:!1}],[i,\"keyup\",void 0],[i,\"wheel\",{passive:!1}],[i,\"contextmenu\",void 0],[t.window,\"blur\",void 0]];for(var a=0,o=this._listeners;a<o.length;a+=1){var s=o[a],l=s[0],u=s[1],c=s[2];r.addEventListener(l,u,l===t.window.document?this.handleWindowEvent:this.handleEvent,c)}};Mi.prototype.destroy=function(){for(var e=0,n=this._listeners;e<n.length;e+=1){var i=n[e],a=i[0],o=i[1],s=i[2];r.removeEventListener(a,o,a===t.window.document?this.handleWindowEvent:this.handleEvent,s)}},Mi.prototype._addDefaultHandlers=function(t){var e=this._map,r=e.getCanvasContainer();this._add(\"mapEvent\",new Gn(e,t));var n=e.boxZoom=new Yn(e,t);this._add(\"boxZoom\",n);var i=new Jn,a=new mi;e.doubleClickZoom=new yi(a,i),this._add(\"tapZoom\",i),this._add(\"clickZoom\",a);var o=new xi;this._add(\"tapDragZoom\",o);var s=e.touchPitch=new fi;this._add(\"touchPitch\",s);var l=new ei(t),u=new ri(t);e.dragRotate=new _i(t,l,u),this._add(\"mouseRotate\",l,[\"mousePitch\"]),this._add(\"mousePitch\",u,[\"mouseRotate\"]);var c=new ti(t),f=new ni(t);e.dragPan=new bi(r,c,f),this._add(\"mousePan\",c),this._add(\"touchPan\",f,[\"touchZoom\",\"touchRotate\"]);var h=new ui,p=new si;e.touchZoomRotate=new wi(r,p,h,o),this._add(\"touchRotate\",h,[\"touchPan\",\"touchZoom\"]),this._add(\"touchZoom\",p,[\"touchPan\",\"touchRotate\"]);var d=e.scrollZoom=new gi(e,this);this._add(\"scrollZoom\",d,[\"mousePan\"]);var v=e.keyboard=new pi;this._add(\"keyboard\",v),this._add(\"blockableMapEvent\",new Wn(e));for(var g=0,y=[\"boxZoom\",\"doubleClickZoom\",\"tapDragZoom\",\"touchPitch\",\"dragRotate\",\"dragPan\",\"touchZoomRotate\",\"scrollZoom\",\"keyboard\"];g<y.length;g+=1){var m=y[g];t.interactive&&t[m]&&e[m].enable(t[m])}},Mi.prototype._add=function(t,e,r){this._handlers.push({handlerName:t,handler:e,allowed:r}),this._handlersById[t]=e},Mi.prototype.stop=function(t){if(!this._updatingCamera){for(var e=0,r=this._handlers;e<r.length;e+=1)r[e].handler.reset();this._inertia.clear(),this._fireEvents({},{},t),this._changes=[]}},Mi.prototype.isActive=function(){for(var t=0,e=this._handlers;t<e.length;t+=1)if(e[t].handler.isActive())return!0;return!1},Mi.prototype.isZooming=function(){return!!this._eventsInProgress.zoom||this._map.scrollZoom.isZooming()},Mi.prototype.isRotating=function(){return!!this._eventsInProgress.rotate},Mi.prototype.isMoving=function(){return Boolean(Ti(this._eventsInProgress))||this.isZooming()},Mi.prototype._blockedByActive=function(t,e,r){for(var n in t)if(n!==r&&(!e||e.indexOf(n)<0))return!0;return!1},Mi.prototype.handleWindowEvent=function(t){this.handleEvent(t,t.type+\"Window\")},Mi.prototype._getMapTouches=function(t){for(var e=[],r=0,n=t;r<n.length;r+=1){var i=n[r],a=i.target;this._el.contains(a)&&e.push(i)}return e},Mi.prototype.handleEvent=function(t,e){if(\"blur\"!==t.type){this._updatingCamera=!0;for(var n=\"renderFrame\"===t.type?void 0:t,i={needsRenderFrame:!1},a={},o={},s=t.touches?this._getMapTouches(t.touches):void 0,l=s?r.touchPos(this._el,s):r.mousePos(this._el,t),u=0,c=this._handlers;u<c.length;u+=1){var f=c[u],h=f.handlerName,p=f.handler,d=f.allowed;if(p.isEnabled()){var v=void 0;this._blockedByActive(o,d,h)?p.reset():p[e||t.type]&&(v=p[e||t.type](t,l,s),this.mergeHandlerResult(i,a,v,h,n),v&&v.needsRenderFrame&&this._triggerRenderFrame()),(v||p.isActive())&&(o[h]=p)}}var g={};for(var y in this._previousActiveHandlers)o[y]||(g[y]=n);this._previousActiveHandlers=o,(Object.keys(g).length||Ai(i))&&(this._changes.push([i,a,g]),this._triggerRenderFrame()),(Object.keys(o).length||Ai(i))&&this._map._stop(!0),this._updatingCamera=!1;var m=i.cameraAnimation;m&&(this._inertia.clear(),this._fireEvents({},{},!0),this._changes=[],m(this._map))}else this.stop(!0)},Mi.prototype.mergeHandlerResult=function(e,r,n,i,a){if(n){t.extend(e,n);var o={handlerName:i,originalEvent:n.originalEvent||a};void 0!==n.zoomDelta&&(r.zoom=o),void 0!==n.panDelta&&(r.drag=o),void 0!==n.pitchDelta&&(r.pitch=o),void 0!==n.bearingDelta&&(r.rotate=o)}},Mi.prototype._applyChanges=function(){for(var e={},r={},n={},i=0,a=this._changes;i<a.length;i+=1){var o=a[i],s=o[0],l=o[1],u=o[2];s.panDelta&&(e.panDelta=(e.panDelta||new t.Point(0,0))._add(s.panDelta)),s.zoomDelta&&(e.zoomDelta=(e.zoomDelta||0)+s.zoomDelta),s.bearingDelta&&(e.bearingDelta=(e.bearingDelta||0)+s.bearingDelta),s.pitchDelta&&(e.pitchDelta=(e.pitchDelta||0)+s.pitchDelta),void 0!==s.around&&(e.around=s.around),void 0!==s.pinchAround&&(e.pinchAround=s.pinchAround),s.noInertia&&(e.noInertia=s.noInertia),t.extend(r,l),t.extend(n,u)}this._updateMapTransform(e,r,n),this._changes=[]},Mi.prototype._updateMapTransform=function(t,e,r){var n=this._map,i=n.transform;if(!Ai(t))return this._fireEvents(e,r,!0);var a=t.panDelta,o=t.zoomDelta,s=t.bearingDelta,l=t.pitchDelta,u=t.around,c=t.pinchAround;void 0!==c&&(u=c),n._stop(!0),u=u||n.transform.centerPoint;var f=i.pointLocation(a?u.sub(a):u);s&&(i.bearing+=s),l&&(i.pitch+=l),o&&(i.zoom+=o),i.setLocationAtPoint(f,u),this._map._update(),t.noInertia||this._inertia.record(t),this._fireEvents(e,r,!0)},Mi.prototype._fireEvents=function(e,r,n){var i=this,a=Ti(this._eventsInProgress),o=Ti(e),s={};for(var l in e){var u=e[l].originalEvent;this._eventsInProgress[l]||(s[l+\"start\"]=u),this._eventsInProgress[l]=e[l]}for(var c in!a&&o&&this._fireEvent(\"movestart\",o.originalEvent),s)this._fireEvent(c,s[c]);for(var f in o&&this._fireEvent(\"move\",o.originalEvent),e){var h=e[f].originalEvent;this._fireEvent(f,h)}var p,d={};for(var v in this._eventsInProgress){var g=this._eventsInProgress[v],y=g.handlerName,m=g.originalEvent;this._handlersById[y].isActive()||(delete this._eventsInProgress[v],p=r[y]||m,d[v+\"end\"]=p)}for(var x in d)this._fireEvent(x,d[x]);var b=Ti(this._eventsInProgress);if(n&&(a||o)&&!b){this._updatingCamera=!0;var _=this._inertia._onMoveEnd(this._map.dragPan._inertiaOptions),w=function(t){return 0!==t&&-i._bearingSnap<t&&t<i._bearingSnap};_?(w(_.bearing||this._map.getBearing())&&(_.bearing=0),this._map.easeTo(_,{originalEvent:p})):(this._map.fire(new t.Event(\"moveend\",{originalEvent:p})),w(this._map.getBearing())&&this._map.resetNorth()),this._updatingCamera=!1}},Mi.prototype._fireEvent=function(e,r){this._map.fire(new t.Event(e,r?{originalEvent:r}:{}))},Mi.prototype._requestFrame=function(){var t=this;return this._map.triggerRepaint(),this._map._renderTaskQueue.add((function(e){delete t._frameId,t.handleEvent(new ki(\"renderFrame\",{timeStamp:e})),t._applyChanges()}))},Mi.prototype._triggerRenderFrame=function(){void 0===this._frameId&&(this._frameId=this._requestFrame())};var Si=function(e){function r(r,n){e.call(this),this._moving=!1,this._zooming=!1,this.transform=r,this._bearingSnap=n.bearingSnap,t.bindAll([\"_renderFrameCallback\"],this)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.getCenter=function(){return new t.LngLat(this.transform.center.lng,this.transform.center.lat)},r.prototype.setCenter=function(t,e){return this.jumpTo({center:t},e)},r.prototype.panBy=function(e,r,n){return e=t.Point.convert(e).mult(-1),this.panTo(this.transform.center,t.extend({offset:e},r),n)},r.prototype.panTo=function(e,r,n){return this.easeTo(t.extend({center:e},r),n)},r.prototype.getZoom=function(){return this.transform.zoom},r.prototype.setZoom=function(t,e){return this.jumpTo({zoom:t},e),this},r.prototype.zoomTo=function(e,r,n){return this.easeTo(t.extend({zoom:e},r),n)},r.prototype.zoomIn=function(t,e){return this.zoomTo(this.getZoom()+1,t,e),this},r.prototype.zoomOut=function(t,e){return this.zoomTo(this.getZoom()-1,t,e),this},r.prototype.getBearing=function(){return this.transform.bearing},r.prototype.setBearing=function(t,e){return this.jumpTo({bearing:t},e),this},r.prototype.getPadding=function(){return this.transform.padding},r.prototype.setPadding=function(t,e){return this.jumpTo({padding:t},e),this},r.prototype.rotateTo=function(e,r,n){return this.easeTo(t.extend({bearing:e},r),n)},r.prototype.resetNorth=function(e,r){return this.rotateTo(0,t.extend({duration:1e3},e),r),this},r.prototype.resetNorthPitch=function(e,r){return this.easeTo(t.extend({bearing:0,pitch:0,duration:1e3},e),r),this},r.prototype.snapToNorth=function(t,e){return Math.abs(this.getBearing())<this._bearingSnap?this.resetNorth(t,e):this},r.prototype.getPitch=function(){return this.transform.pitch},r.prototype.setPitch=function(t,e){return this.jumpTo({pitch:t},e),this},r.prototype.cameraForBounds=function(e,r){e=t.LngLatBounds.convert(e);var n=r&&r.bearing||0;return this._cameraForBoxAndBearing(e.getNorthWest(),e.getSouthEast(),n,r)},r.prototype._cameraForBoxAndBearing=function(e,r,n,i){var a={top:0,bottom:0,right:0,left:0};if(\"number\"==typeof(i=t.extend({padding:a,offset:[0,0],maxZoom:this.transform.maxZoom},i)).padding){var o=i.padding;i.padding={top:o,bottom:o,right:o,left:o}}i.padding=t.extend(a,i.padding);var s=this.transform,l=s.padding,u=s.project(t.LngLat.convert(e)),c=s.project(t.LngLat.convert(r)),f=u.rotate(-n*Math.PI/180),h=c.rotate(-n*Math.PI/180),p=new t.Point(Math.max(f.x,h.x),Math.max(f.y,h.y)),d=new t.Point(Math.min(f.x,h.x),Math.min(f.y,h.y)),v=p.sub(d),g=(s.width-(l.left+l.right+i.padding.left+i.padding.right))/v.x,y=(s.height-(l.top+l.bottom+i.padding.top+i.padding.bottom))/v.y;if(!(y<0||g<0)){var m=Math.min(s.scaleZoom(s.scale*Math.min(g,y)),i.maxZoom),x=\"number\"==typeof i.offset.x?new t.Point(i.offset.x,i.offset.y):t.Point.convert(i.offset),b=(i.padding.left-i.padding.right)/2,_=(i.padding.top-i.padding.bottom)/2,w=new t.Point(b,_).rotate(n*Math.PI/180),T=x.add(w).mult(s.scale/s.zoomScale(m));return{center:s.unproject(u.add(c).div(2).sub(T)),zoom:m,bearing:n}}t.warnOnce(\"Map cannot fit within canvas with the given bounds, padding, and/or offset.\")},r.prototype.fitBounds=function(t,e,r){return this._fitInternal(this.cameraForBounds(t,e),e,r)},r.prototype.fitScreenCoordinates=function(e,r,n,i,a){return this._fitInternal(this._cameraForBoxAndBearing(this.transform.pointLocation(t.Point.convert(e)),this.transform.pointLocation(t.Point.convert(r)),n,i),i,a)},r.prototype._fitInternal=function(e,r,n){return e?(delete(r=t.extend(e,r)).padding,r.linear?this.easeTo(r,n):this.flyTo(r,n)):this},r.prototype.jumpTo=function(e,r){this.stop();var n=this.transform,i=!1,a=!1,o=!1;return\"zoom\"in e&&n.zoom!==+e.zoom&&(i=!0,n.zoom=+e.zoom),void 0!==e.center&&(n.center=t.LngLat.convert(e.center)),\"bearing\"in e&&n.bearing!==+e.bearing&&(a=!0,n.bearing=+e.bearing),\"pitch\"in e&&n.pitch!==+e.pitch&&(o=!0,n.pitch=+e.pitch),null==e.padding||n.isPaddingEqual(e.padding)||(n.padding=e.padding),this.fire(new t.Event(\"movestart\",r)).fire(new t.Event(\"move\",r)),i&&this.fire(new t.Event(\"zoomstart\",r)).fire(new t.Event(\"zoom\",r)).fire(new t.Event(\"zoomend\",r)),a&&this.fire(new t.Event(\"rotatestart\",r)).fire(new t.Event(\"rotate\",r)).fire(new t.Event(\"rotateend\",r)),o&&this.fire(new t.Event(\"pitchstart\",r)).fire(new t.Event(\"pitch\",r)).fire(new t.Event(\"pitchend\",r)),this.fire(new t.Event(\"moveend\",r))},r.prototype.easeTo=function(e,r){var n=this;this._stop(!1,e.easeId),(!1===(e=t.extend({offset:[0,0],duration:500,easing:t.ease},e)).animate||!e.essential&&t.browser.prefersReducedMotion)&&(e.duration=0);var i=this.transform,a=this.getZoom(),o=this.getBearing(),s=this.getPitch(),l=this.getPadding(),u=\"zoom\"in e?+e.zoom:a,c=\"bearing\"in e?this._normalizeBearing(e.bearing,o):o,f=\"pitch\"in e?+e.pitch:s,h=\"padding\"in e?e.padding:i.padding,p=t.Point.convert(e.offset),d=i.centerPoint.add(p),v=i.pointLocation(d),g=t.LngLat.convert(e.center||v);this._normalizeCenter(g);var y,m,x=i.project(v),b=i.project(g).sub(x),_=i.zoomScale(u-a);e.around&&(y=t.LngLat.convert(e.around),m=i.locationPoint(y));var w={moving:this._moving,zooming:this._zooming,rotating:this._rotating,pitching:this._pitching};return this._zooming=this._zooming||u!==a,this._rotating=this._rotating||o!==c,this._pitching=this._pitching||f!==s,this._padding=!i.isPaddingEqual(h),this._easeId=e.easeId,this._prepareEase(r,e.noMoveStart,w),this._ease((function(e){if(n._zooming&&(i.zoom=t.number(a,u,e)),n._rotating&&(i.bearing=t.number(o,c,e)),n._pitching&&(i.pitch=t.number(s,f,e)),n._padding&&(i.interpolatePadding(l,h,e),d=i.centerPoint.add(p)),y)i.setLocationAtPoint(y,m);else{var v=i.zoomScale(i.zoom-a),g=u>a?Math.min(2,_):Math.max(.5,_),w=Math.pow(g,1-e),T=i.unproject(x.add(b.mult(e*w)).mult(v));i.setLocationAtPoint(i.renderWorldCopies?T.wrap():T,d)}n._fireMoveEvents(r)}),(function(t){n._afterEase(r,t)}),e),this},r.prototype._prepareEase=function(e,r,n){void 0===n&&(n={}),this._moving=!0,r||n.moving||this.fire(new t.Event(\"movestart\",e)),this._zooming&&!n.zooming&&this.fire(new t.Event(\"zoomstart\",e)),this._rotating&&!n.rotating&&this.fire(new t.Event(\"rotatestart\",e)),this._pitching&&!n.pitching&&this.fire(new t.Event(\"pitchstart\",e))},r.prototype._fireMoveEvents=function(e){this.fire(new t.Event(\"move\",e)),this._zooming&&this.fire(new t.Event(\"zoom\",e)),this._rotating&&this.fire(new t.Event(\"rotate\",e)),this._pitching&&this.fire(new t.Event(\"pitch\",e))},r.prototype._afterEase=function(e,r){if(!this._easeId||!r||this._easeId!==r){delete this._easeId;var n=this._zooming,i=this._rotating,a=this._pitching;this._moving=!1,this._zooming=!1,this._rotating=!1,this._pitching=!1,this._padding=!1,n&&this.fire(new t.Event(\"zoomend\",e)),i&&this.fire(new t.Event(\"rotateend\",e)),a&&this.fire(new t.Event(\"pitchend\",e)),this.fire(new t.Event(\"moveend\",e))}},r.prototype.flyTo=function(e,r){var n=this;if(!e.essential&&t.browser.prefersReducedMotion){var i=t.pick(e,[\"center\",\"zoom\",\"bearing\",\"pitch\",\"around\"]);return this.jumpTo(i,r)}this.stop(),e=t.extend({offset:[0,0],speed:1.2,curve:1.42,easing:t.ease},e);var a=this.transform,o=this.getZoom(),s=this.getBearing(),l=this.getPitch(),u=this.getPadding(),c=\"zoom\"in e?t.clamp(+e.zoom,a.minZoom,a.maxZoom):o,f=\"bearing\"in e?this._normalizeBearing(e.bearing,s):s,h=\"pitch\"in e?+e.pitch:l,p=\"padding\"in e?e.padding:a.padding,d=a.zoomScale(c-o),v=t.Point.convert(e.offset),g=a.centerPoint.add(v),y=a.pointLocation(g),m=t.LngLat.convert(e.center||y);this._normalizeCenter(m);var x=a.project(y),b=a.project(m).sub(x),_=e.curve,w=Math.max(a.width,a.height),T=w/d,k=b.mag();if(\"minZoom\"in e){var A=t.clamp(Math.min(e.minZoom,o,c),a.minZoom,a.maxZoom),M=w/a.zoomScale(A-o);_=Math.sqrt(M/k*2)}var S=_*_;function E(t){var e=(T*T-w*w+(t?-1:1)*S*S*k*k)/(2*(t?T:w)*S*k);return Math.log(Math.sqrt(e*e+1)-e)}function L(t){return(Math.exp(t)-Math.exp(-t))/2}function C(t){return(Math.exp(t)+Math.exp(-t))/2}var P=E(0),O=function(t){return C(P)/C(P+_*t)},I=function(t){return w*((C(P)*(L(e=P+_*t)/C(e))-L(P))/S)/k;var e},D=(E(1)-P)/_;if(Math.abs(k)<1e-6||!isFinite(D)){if(Math.abs(w-T)<1e-6)return this.easeTo(e,r);var z=T<w?-1:1;D=Math.abs(Math.log(T/w))/_,I=function(){return 0},O=function(t){return Math.exp(z*_*t)}}if(\"duration\"in e)e.duration=+e.duration;else{var R=\"screenSpeed\"in e?+e.screenSpeed/_:+e.speed;e.duration=1e3*D/R}return e.maxDuration&&e.duration>e.maxDuration&&(e.duration=0),this._zooming=!0,this._rotating=s!==f,this._pitching=h!==l,this._padding=!a.isPaddingEqual(p),this._prepareEase(r,!1),this._ease((function(e){var i=e*D,d=1/O(i);a.zoom=1===e?c:o+a.scaleZoom(d),n._rotating&&(a.bearing=t.number(s,f,e)),n._pitching&&(a.pitch=t.number(l,h,e)),n._padding&&(a.interpolatePadding(u,p,e),g=a.centerPoint.add(v));var y=1===e?m:a.unproject(x.add(b.mult(I(i))).mult(d));a.setLocationAtPoint(a.renderWorldCopies?y.wrap():y,g),n._fireMoveEvents(r)}),(function(){return n._afterEase(r)}),e),this},r.prototype.isEasing=function(){return!!this._easeFrameId},r.prototype.stop=function(){return this._stop()},r.prototype._stop=function(t,e){if(this._easeFrameId&&(this._cancelRenderFrame(this._easeFrameId),delete this._easeFrameId,delete this._onEaseFrame),this._onEaseEnd){var r=this._onEaseEnd;delete this._onEaseEnd,r.call(this,e)}if(!t){var n=this.handlers;n&&n.stop(!1)}return this},r.prototype._ease=function(e,r,n){!1===n.animate||0===n.duration?(e(1),r()):(this._easeStart=t.browser.now(),this._easeOptions=n,this._onEaseFrame=e,this._onEaseEnd=r,this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback))},r.prototype._renderFrameCallback=function(){var e=Math.min((t.browser.now()-this._easeStart)/this._easeOptions.duration,1);this._onEaseFrame(this._easeOptions.easing(e)),e<1?this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback):this.stop()},r.prototype._normalizeBearing=function(e,r){e=t.wrap(e,-180,180);var n=Math.abs(e-r);return Math.abs(e-360-r)<n&&(e-=360),Math.abs(e+360-r)<n&&(e+=360),e},r.prototype._normalizeCenter=function(t){var e=this.transform;if(e.renderWorldCopies&&!e.lngRange){var r=t.lng-e.center.lng;t.lng+=r>180?-360:r<-180?360:0}},r}(t.Evented),Ei=function(e){void 0===e&&(e={}),this.options=e,t.bindAll([\"_toggleAttribution\",\"_updateEditLink\",\"_updateData\",\"_updateCompact\"],this)};Ei.prototype.getDefaultPosition=function(){return\"bottom-right\"},Ei.prototype.onAdd=function(t){var e=this.options&&this.options.compact;return this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-attrib\"),this._compactButton=r.create(\"button\",\"mapboxgl-ctrl-attrib-button\",this._container),this._compactButton.addEventListener(\"click\",this._toggleAttribution),this._setElementTitle(this._compactButton,\"ToggleAttribution\"),this._innerContainer=r.create(\"div\",\"mapboxgl-ctrl-attrib-inner\",this._container),this._innerContainer.setAttribute(\"role\",\"list\"),e&&this._container.classList.add(\"mapboxgl-compact\"),this._updateAttributions(),this._updateEditLink(),this._map.on(\"styledata\",this._updateData),this._map.on(\"sourcedata\",this._updateData),this._map.on(\"moveend\",this._updateEditLink),void 0===e&&(this._map.on(\"resize\",this._updateCompact),this._updateCompact()),this._container},Ei.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"styledata\",this._updateData),this._map.off(\"sourcedata\",this._updateData),this._map.off(\"moveend\",this._updateEditLink),this._map.off(\"resize\",this._updateCompact),this._map=void 0,this._attribHTML=void 0},Ei.prototype._setElementTitle=function(t,e){var r=this._map._getUIString(\"AttributionControl.\"+e);t.title=r,t.setAttribute(\"aria-label\",r)},Ei.prototype._toggleAttribution=function(){this._container.classList.contains(\"mapboxgl-compact-show\")?(this._container.classList.remove(\"mapboxgl-compact-show\"),this._compactButton.setAttribute(\"aria-pressed\",\"false\")):(this._container.classList.add(\"mapboxgl-compact-show\"),this._compactButton.setAttribute(\"aria-pressed\",\"true\"))},Ei.prototype._updateEditLink=function(){var e=this._editLink;e||(e=this._editLink=this._container.querySelector(\".mapbox-improve-map\"));var r=[{key:\"owner\",value:this.styleOwner},{key:\"id\",value:this.styleId},{key:\"access_token\",value:this._map._requestManager._customAccessToken||t.config.ACCESS_TOKEN}];if(e){var n=r.reduce((function(t,e,n){return e.value&&(t+=e.key+\"=\"+e.value+(n<r.length-1?\"&\":\"\")),t}),\"?\");e.href=t.config.FEEDBACK_URL+\"/\"+n+(this._map._hash?this._map._hash.getHashString(!0):\"\"),e.rel=\"noopener nofollow\",this._setElementTitle(e,\"MapFeedback\")}},Ei.prototype._updateData=function(t){!t||\"metadata\"!==t.sourceDataType&&\"visibility\"!==t.sourceDataType&&\"style\"!==t.dataType||(this._updateAttributions(),this._updateEditLink())},Ei.prototype._updateAttributions=function(){if(this._map.style){var t=[];if(this.options.customAttribution&&(Array.isArray(this.options.customAttribution)?t=t.concat(this.options.customAttribution.map((function(t){return\"string\"!=typeof t?\"\":t}))):\"string\"==typeof this.options.customAttribution&&t.push(this.options.customAttribution)),this._map.style.stylesheet){var e=this._map.style.stylesheet;this.styleOwner=e.owner,this.styleId=e.id}var r=this._map.style.sourceCaches;for(var n in r){var i=r[n];if(i.used){var a=i.getSource();a.attribution&&t.indexOf(a.attribution)<0&&t.push(a.attribution)}}t.sort((function(t,e){return t.length-e.length}));var o=(t=t.filter((function(e,r){for(var n=r+1;n<t.length;n++)if(t[n].indexOf(e)>=0)return!1;return!0}))).join(\" | \");o!==this._attribHTML&&(this._attribHTML=o,t.length?(this._innerContainer.innerHTML=o,this._container.classList.remove(\"mapboxgl-attrib-empty\")):this._container.classList.add(\"mapboxgl-attrib-empty\"),this._editLink=null)}},Ei.prototype._updateCompact=function(){this._map.getCanvasContainer().offsetWidth<=640?this._container.classList.add(\"mapboxgl-compact\"):this._container.classList.remove(\"mapboxgl-compact\",\"mapboxgl-compact-show\")};var Li=function(){t.bindAll([\"_updateLogo\"],this),t.bindAll([\"_updateCompact\"],this)};Li.prototype.onAdd=function(t){this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl\");var e=r.create(\"a\",\"mapboxgl-ctrl-logo\");return e.target=\"_blank\",e.rel=\"noopener nofollow\",e.href=\"https://www.mapbox.com/\",e.setAttribute(\"aria-label\",this._map._getUIString(\"LogoControl.Title\")),e.setAttribute(\"rel\",\"noopener nofollow\"),this._container.appendChild(e),this._container.style.display=\"none\",this._map.on(\"sourcedata\",this._updateLogo),this._updateLogo(),this._map.on(\"resize\",this._updateCompact),this._updateCompact(),this._container},Li.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"sourcedata\",this._updateLogo),this._map.off(\"resize\",this._updateCompact)},Li.prototype.getDefaultPosition=function(){return\"bottom-left\"},Li.prototype._updateLogo=function(t){t&&\"metadata\"!==t.sourceDataType||(this._container.style.display=this._logoRequired()?\"block\":\"none\")},Li.prototype._logoRequired=function(){if(this._map.style){var t=this._map.style.sourceCaches;for(var e in t)if(t[e].getSource().mapbox_logo)return!0;return!1}},Li.prototype._updateCompact=function(){var t=this._container.children;if(t.length){var e=t[0];this._map.getCanvasContainer().offsetWidth<250?e.classList.add(\"mapboxgl-compact\"):e.classList.remove(\"mapboxgl-compact\")}};var Ci=function(){this._queue=[],this._id=0,this._cleared=!1,this._currentlyRunning=!1};Ci.prototype.add=function(t){var e=++this._id;return this._queue.push({callback:t,id:e,cancelled:!1}),e},Ci.prototype.remove=function(t){for(var e=this._currentlyRunning,r=0,n=e?this._queue.concat(e):this._queue;r<n.length;r+=1){var i=n[r];if(i.id===t)return void(i.cancelled=!0)}},Ci.prototype.run=function(t){void 0===t&&(t=0);var e=this._currentlyRunning=this._queue;this._queue=[];for(var r=0,n=e;r<n.length;r+=1){var i=n[r];if(!i.cancelled&&(i.callback(t),this._cleared))break}this._cleared=!1,this._currentlyRunning=!1},Ci.prototype.clear=function(){this._currentlyRunning&&(this._cleared=!0),this._queue=[]};var Pi={\"AttributionControl.ToggleAttribution\":\"Toggle attribution\",\"AttributionControl.MapFeedback\":\"Map feedback\",\"FullscreenControl.Enter\":\"Enter fullscreen\",\"FullscreenControl.Exit\":\"Exit fullscreen\",\"GeolocateControl.FindMyLocation\":\"Find my location\",\"GeolocateControl.LocationNotAvailable\":\"Location not available\",\"LogoControl.Title\":\"Mapbox logo\",\"NavigationControl.ResetBearing\":\"Reset bearing to north\",\"NavigationControl.ZoomIn\":\"Zoom in\",\"NavigationControl.ZoomOut\":\"Zoom out\",\"ScaleControl.Feet\":\"ft\",\"ScaleControl.Meters\":\"m\",\"ScaleControl.Kilometers\":\"km\",\"ScaleControl.Miles\":\"mi\",\"ScaleControl.NauticalMiles\":\"nm\"},Oi=t.window.HTMLImageElement,Ii=t.window.HTMLElement,Di=t.window.ImageBitmap,zi=60,Ri={center:[0,0],zoom:0,bearing:0,pitch:0,minZoom:-2,maxZoom:22,minPitch:0,maxPitch:zi,interactive:!0,scrollZoom:!0,boxZoom:!0,dragRotate:!0,dragPan:!0,keyboard:!0,doubleClickZoom:!0,touchZoomRotate:!0,touchPitch:!0,bearingSnap:7,clickTolerance:3,pitchWithRotate:!0,hash:!1,attributionControl:!0,failIfMajorPerformanceCaveat:!1,preserveDrawingBuffer:!1,trackResize:!0,renderWorldCopies:!0,refreshExpiredTiles:!0,maxTileCacheSize:null,localIdeographFontFamily:\"sans-serif\",transformRequest:null,accessToken:null,fadeDuration:300,crossSourceCollisions:!0},Fi=function(n){function i(e){var r=this;if(null!=(e=t.extend({},Ri,e)).minZoom&&null!=e.maxZoom&&e.minZoom>e.maxZoom)throw new Error(\"maxZoom must be greater than or equal to minZoom\");if(null!=e.minPitch&&null!=e.maxPitch&&e.minPitch>e.maxPitch)throw new Error(\"maxPitch must be greater than or equal to minPitch\");if(null!=e.minPitch&&e.minPitch<0)throw new Error(\"minPitch must be greater than or equal to 0\");if(null!=e.maxPitch&&e.maxPitch>zi)throw new Error(\"maxPitch must be less than or equal to 60\");var i=new Pn(e.minZoom,e.maxZoom,e.minPitch,e.maxPitch,e.renderWorldCopies);if(n.call(this,i,e),this._interactive=e.interactive,this._maxTileCacheSize=e.maxTileCacheSize,this._failIfMajorPerformanceCaveat=e.failIfMajorPerformanceCaveat,this._preserveDrawingBuffer=e.preserveDrawingBuffer,this._antialias=e.antialias,this._trackResize=e.trackResize,this._bearingSnap=e.bearingSnap,this._refreshExpiredTiles=e.refreshExpiredTiles,this._fadeDuration=e.fadeDuration,this._crossSourceCollisions=e.crossSourceCollisions,this._crossFadingFactor=1,this._collectResourceTiming=e.collectResourceTiming,this._renderTaskQueue=new Ci,this._controls=[],this._mapId=t.uniqueId(),this._locale=t.extend({},Pi,e.locale),this._clickTolerance=e.clickTolerance,this._requestManager=new t.RequestManager(e.transformRequest,e.accessToken),\"string\"==typeof e.container){if(this._container=t.window.document.getElementById(e.container),!this._container)throw new Error(\"Container '\"+e.container+\"' not found.\")}else{if(!(e.container instanceof Ii))throw new Error(\"Invalid type: 'container' must be a String or HTMLElement.\");this._container=e.container}if(e.maxBounds&&this.setMaxBounds(e.maxBounds),t.bindAll([\"_onWindowOnline\",\"_onWindowResize\",\"_onMapScroll\",\"_contextLost\",\"_contextRestored\"],this),this._setupContainer(),this._setupPainter(),void 0===this.painter)throw new Error(\"Failed to initialize WebGL.\");this.on(\"move\",(function(){return r._update(!1)})),this.on(\"moveend\",(function(){return r._update(!1)})),this.on(\"zoom\",(function(){return r._update(!0)})),void 0!==t.window&&(t.window.addEventListener(\"online\",this._onWindowOnline,!1),t.window.addEventListener(\"resize\",this._onWindowResize,!1),t.window.addEventListener(\"orientationchange\",this._onWindowResize,!1)),this.handlers=new Mi(this,e);var a=\"string\"==typeof e.hash&&e.hash||void 0;this._hash=e.hash&&new In(a).addTo(this),this._hash&&this._hash._onHashChange()||(this.jumpTo({center:e.center,zoom:e.zoom,bearing:e.bearing,pitch:e.pitch}),e.bounds&&(this.resize(),this.fitBounds(e.bounds,t.extend({},e.fitBoundsOptions,{duration:0})))),this.resize(),this._localIdeographFontFamily=e.localIdeographFontFamily,e.style&&this.setStyle(e.style,{localIdeographFontFamily:e.localIdeographFontFamily}),e.attributionControl&&this.addControl(new Ei({customAttribution:e.customAttribution})),this.addControl(new Li,e.logoPosition),this.on(\"style.load\",(function(){r.transform.unmodified&&r.jumpTo(r.style.stylesheet)})),this.on(\"data\",(function(e){r._update(\"style\"===e.dataType),r.fire(new t.Event(e.dataType+\"data\",e))})),this.on(\"dataloading\",(function(e){r.fire(new t.Event(e.dataType+\"dataloading\",e))}))}n&&(i.__proto__=n),i.prototype=Object.create(n&&n.prototype),i.prototype.constructor=i;var a={showTileBoundaries:{configurable:!0},showPadding:{configurable:!0},showCollisionBoxes:{configurable:!0},showOverdrawInspector:{configurable:!0},repaint:{configurable:!0},vertices:{configurable:!0},version:{configurable:!0}};return i.prototype._getMapId=function(){return this._mapId},i.prototype.addControl=function(e,r){if(void 0===r&&(r=e.getDefaultPosition?e.getDefaultPosition():\"top-right\"),!e||!e.onAdd)return this.fire(new t.ErrorEvent(new Error(\"Invalid argument to map.addControl(). Argument must be a control with onAdd and onRemove methods.\")));var n=e.onAdd(this);this._controls.push(e);var i=this._controlPositions[r];return-1!==r.indexOf(\"bottom\")?i.insertBefore(n,i.firstChild):i.appendChild(n),this},i.prototype.removeControl=function(e){if(!e||!e.onRemove)return this.fire(new t.ErrorEvent(new Error(\"Invalid argument to map.removeControl(). Argument must be a control with onAdd and onRemove methods.\")));var r=this._controls.indexOf(e);return r>-1&&this._controls.splice(r,1),e.onRemove(this),this},i.prototype.hasControl=function(t){return this._controls.indexOf(t)>-1},i.prototype.resize=function(e){var r=this._containerDimensions(),n=r[0],i=r[1];this._resizeCanvas(n,i),this.transform.resize(n,i),this.painter.resize(n,i);var a=!this._moving;return a&&(this.stop(),this.fire(new t.Event(\"movestart\",e)).fire(new t.Event(\"move\",e))),this.fire(new t.Event(\"resize\",e)),a&&this.fire(new t.Event(\"moveend\",e)),this},i.prototype.getBounds=function(){return this.transform.getBounds()},i.prototype.getMaxBounds=function(){return this.transform.getMaxBounds()},i.prototype.setMaxBounds=function(e){return this.transform.setMaxBounds(t.LngLatBounds.convert(e)),this._update()},i.prototype.setMinZoom=function(t){if((t=null==t?-2:t)>=-2&&t<=this.transform.maxZoom)return this.transform.minZoom=t,this._update(),this.getZoom()<t&&this.setZoom(t),this;throw new Error(\"minZoom must be between -2 and the current maxZoom, inclusive\")},i.prototype.getMinZoom=function(){return this.transform.minZoom},i.prototype.setMaxZoom=function(t){if((t=null==t?22:t)>=this.transform.minZoom)return this.transform.maxZoom=t,this._update(),this.getZoom()>t&&this.setZoom(t),this;throw new Error(\"maxZoom must be greater than the current minZoom\")},i.prototype.getMaxZoom=function(){return this.transform.maxZoom},i.prototype.setMinPitch=function(t){if((t=null==t?0:t)<0)throw new Error(\"minPitch must be greater than or equal to 0\");if(t>=0&&t<=this.transform.maxPitch)return this.transform.minPitch=t,this._update(),this.getPitch()<t&&this.setPitch(t),this;throw new Error(\"minPitch must be between 0 and the current maxPitch, inclusive\")},i.prototype.getMinPitch=function(){return this.transform.minPitch},i.prototype.setMaxPitch=function(t){if((t=null==t?zi:t)>zi)throw new Error(\"maxPitch must be less than or equal to 60\");if(t>=this.transform.minPitch)return this.transform.maxPitch=t,this._update(),this.getPitch()>t&&this.setPitch(t),this;throw new Error(\"maxPitch must be greater than the current minPitch\")},i.prototype.getMaxPitch=function(){return this.transform.maxPitch},i.prototype.getRenderWorldCopies=function(){return this.transform.renderWorldCopies},i.prototype.setRenderWorldCopies=function(t){return this.transform.renderWorldCopies=t,this._update()},i.prototype.project=function(e){return this.transform.locationPoint(t.LngLat.convert(e))},i.prototype.unproject=function(e){return this.transform.pointLocation(t.Point.convert(e))},i.prototype.isMoving=function(){return this._moving||this.handlers.isMoving()},i.prototype.isZooming=function(){return this._zooming||this.handlers.isZooming()},i.prototype.isRotating=function(){return this._rotating||this.handlers.isRotating()},i.prototype._createDelegatedListener=function(t,e,r){var n,i=this;if(\"mouseenter\"===t||\"mouseover\"===t){var a=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){var o=i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[];o.length?a||(a=!0,r.call(i,new Vn(t,i,n.originalEvent,{features:o}))):a=!1},mouseout:function(){a=!1}}}}if(\"mouseleave\"===t||\"mouseout\"===t){var o=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){(i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[]).length?o=!0:o&&(o=!1,r.call(i,new Vn(t,i,n.originalEvent)))},mouseout:function(e){o&&(o=!1,r.call(i,new Vn(t,i,e.originalEvent)))}}}}return{layer:e,listener:r,delegates:(n={},n[t]=function(t){var n=i.getLayer(e)?i.queryRenderedFeatures(t.point,{layers:[e]}):[];n.length&&(t.features=n,r.call(i,t),delete t.features)},n)}},i.prototype.on=function(t,e,r){if(void 0===r)return n.prototype.on.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in this._delegatedListeners=this._delegatedListeners||{},this._delegatedListeners[t]=this._delegatedListeners[t]||[],this._delegatedListeners[t].push(i),i.delegates)this.on(a,i.delegates[a]);return this},i.prototype.once=function(t,e,r){if(void 0===r)return n.prototype.once.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in i.delegates)this.once(a,i.delegates[a]);return this},i.prototype.off=function(t,e,r){var i=this;if(void 0===r)return n.prototype.off.call(this,t,e);return this._delegatedListeners&&this._delegatedListeners[t]&&function(n){for(var a=n[t],o=0;o<a.length;o++){var s=a[o];if(s.layer===e&&s.listener===r){for(var l in s.delegates)i.off(l,s.delegates[l]);return a.splice(o,1),i}}}(this._delegatedListeners),this},i.prototype.queryRenderedFeatures=function(e,r){if(!this.style)return[];var n;if(void 0!==r||void 0===e||e instanceof t.Point||Array.isArray(e)||(r=e,e=void 0),r=r||{},(e=e||[[0,0],[this.transform.width,this.transform.height]])instanceof t.Point||\"number\"==typeof e[0])n=[t.Point.convert(e)];else{var i=t.Point.convert(e[0]),a=t.Point.convert(e[1]);n=[i,new t.Point(a.x,i.y),a,new t.Point(i.x,a.y),i]}return this.style.queryRenderedFeatures(n,r,this.transform)},i.prototype.querySourceFeatures=function(t,e){return this.style.querySourceFeatures(t,e)},i.prototype.setStyle=function(e,r){return!1!==(r=t.extend({},{localIdeographFontFamily:this._localIdeographFontFamily},r)).diff&&r.localIdeographFontFamily===this._localIdeographFontFamily&&this.style&&e?(this._diffStyle(e,r),this):(this._localIdeographFontFamily=r.localIdeographFontFamily,this._updateStyle(e,r))},i.prototype._getUIString=function(t){var e=this._locale[t];if(null==e)throw new Error(\"Missing UI string '\"+t+\"'\");return e},i.prototype._updateStyle=function(t,e){return this.style&&(this.style.setEventedParent(null),this.style._remove()),t?(this.style=new Ye(this,e||{}),this.style.setEventedParent(this,{style:this.style}),\"string\"==typeof t?this.style.loadURL(t):this.style.loadJSON(t),this):(delete this.style,this)},i.prototype._lazyInitEmptyStyle=function(){this.style||(this.style=new Ye(this,{}),this.style.setEventedParent(this,{style:this.style}),this.style.loadEmpty())},i.prototype._diffStyle=function(e,r){var n=this;if(\"string\"==typeof e){var i=this._requestManager.normalizeStyleURL(e),a=this._requestManager.transformRequest(i,t.ResourceType.Style);t.getJSON(a,(function(e,i){e?n.fire(new t.ErrorEvent(e)):i&&n._updateDiff(i,r)}))}else\"object\"==typeof e&&this._updateDiff(e,r)},i.prototype._updateDiff=function(e,r){try{this.style.setState(e)&&this._update(!0)}catch(n){t.warnOnce(\"Unable to perform style diff: \"+(n.message||n.error||n)+\".  Rebuilding the style from scratch.\"),this._updateStyle(e,r)}},i.prototype.getStyle=function(){if(this.style)return this.style.serialize()},i.prototype.isStyleLoaded=function(){return this.style?this.style.loaded():t.warnOnce(\"There is no style added to the map.\")},i.prototype.addSource=function(t,e){return this._lazyInitEmptyStyle(),this.style.addSource(t,e),this._update(!0)},i.prototype.isSourceLoaded=function(e){var r=this.style&&this.style.sourceCaches[e];if(void 0!==r)return r.loaded();this.fire(new t.ErrorEvent(new Error(\"There is no source with ID '\"+e+\"'\")))},i.prototype.areTilesLoaded=function(){var t=this.style&&this.style.sourceCaches;for(var e in t){var r=t[e]._tiles;for(var n in r){var i=r[n];if(\"loaded\"!==i.state&&\"errored\"!==i.state)return!1}}return!0},i.prototype.addSourceType=function(t,e,r){return this._lazyInitEmptyStyle(),this.style.addSourceType(t,e,r)},i.prototype.removeSource=function(t){return this.style.removeSource(t),this._update(!0)},i.prototype.getSource=function(t){return this.style.getSource(t)},i.prototype.addImage=function(e,r,n){void 0===n&&(n={});var i=n.pixelRatio;void 0===i&&(i=1);var a=n.sdf;void 0===a&&(a=!1);var o=n.stretchX,s=n.stretchY,l=n.content;this._lazyInitEmptyStyle();if(r instanceof Oi||Di&&r instanceof Di){var u=t.browser.getImageData(r),c=u.width,f=u.height,h=u.data;this.style.addImage(e,{data:new t.RGBAImage({width:c,height:f},h),pixelRatio:i,stretchX:o,stretchY:s,content:l,sdf:a,version:0})}else{if(void 0===r.width||void 0===r.height)return this.fire(new t.ErrorEvent(new Error(\"Invalid arguments to map.addImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`\")));var p=r.width,d=r.height,v=r.data,g=r;this.style.addImage(e,{data:new t.RGBAImage({width:p,height:d},new Uint8Array(v)),pixelRatio:i,stretchX:o,stretchY:s,content:l,sdf:a,version:0,userImage:g}),g.onAdd&&g.onAdd(this,e)}},i.prototype.updateImage=function(e,r){var n=this.style.getImage(e);if(!n)return this.fire(new t.ErrorEvent(new Error(\"The map has no image with that id. If you are adding a new image use `map.addImage(...)` instead.\")));var i=r instanceof Oi||Di&&r instanceof Di?t.browser.getImageData(r):r,a=i.width,o=i.height,s=i.data;if(void 0===a||void 0===o)return this.fire(new t.ErrorEvent(new Error(\"Invalid arguments to map.updateImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`\")));if(a!==n.data.width||o!==n.data.height)return this.fire(new t.ErrorEvent(new Error(\"The width and height of the updated image must be that same as the previous version of the image\")));var l=!(r instanceof Oi||Di&&r instanceof Di);n.data.replace(s,l),this.style.updateImage(e,n)},i.prototype.hasImage=function(e){return e?!!this.style.getImage(e):(this.fire(new t.ErrorEvent(new Error(\"Missing required image id\"))),!1)},i.prototype.removeImage=function(t){this.style.removeImage(t)},i.prototype.loadImage=function(e,r){t.getImage(this._requestManager.transformRequest(e,t.ResourceType.Image),r)},i.prototype.listImages=function(){return this.style.listImages()},i.prototype.addLayer=function(t,e){return this._lazyInitEmptyStyle(),this.style.addLayer(t,e),this._update(!0)},i.prototype.moveLayer=function(t,e){return this.style.moveLayer(t,e),this._update(!0)},i.prototype.removeLayer=function(t){return this.style.removeLayer(t),this._update(!0)},i.prototype.getLayer=function(t){return this.style.getLayer(t)},i.prototype.setLayerZoomRange=function(t,e,r){return this.style.setLayerZoomRange(t,e,r),this._update(!0)},i.prototype.setFilter=function(t,e,r){return void 0===r&&(r={}),this.style.setFilter(t,e,r),this._update(!0)},i.prototype.getFilter=function(t){return this.style.getFilter(t)},i.prototype.setPaintProperty=function(t,e,r,n){return void 0===n&&(n={}),this.style.setPaintProperty(t,e,r,n),this._update(!0)},i.prototype.getPaintProperty=function(t,e){return this.style.getPaintProperty(t,e)},i.prototype.setLayoutProperty=function(t,e,r,n){return void 0===n&&(n={}),this.style.setLayoutProperty(t,e,r,n),this._update(!0)},i.prototype.getLayoutProperty=function(t,e){return this.style.getLayoutProperty(t,e)},i.prototype.setLight=function(t,e){return void 0===e&&(e={}),this._lazyInitEmptyStyle(),this.style.setLight(t,e),this._update(!0)},i.prototype.getLight=function(){return this.style.getLight()},i.prototype.setFeatureState=function(t,e){return this.style.setFeatureState(t,e),this._update()},i.prototype.removeFeatureState=function(t,e){return this.style.removeFeatureState(t,e),this._update()},i.prototype.getFeatureState=function(t){return this.style.getFeatureState(t)},i.prototype.getContainer=function(){return this._container},i.prototype.getCanvasContainer=function(){return this._canvasContainer},i.prototype.getCanvas=function(){return this._canvas},i.prototype._containerDimensions=function(){var t=0,e=0;return this._container&&(t=this._container.clientWidth||400,e=this._container.clientHeight||300),[t,e]},i.prototype._detectMissingCSS=function(){\"rgb(250, 128, 114)\"!==t.window.getComputedStyle(this._missingCSSCanary).getPropertyValue(\"background-color\")&&t.warnOnce(\"This page appears to be missing CSS declarations for Mapbox GL JS, which may cause the map to display incorrectly. Please ensure your page includes mapbox-gl.css, as described in https://www.mapbox.com/mapbox-gl-js/api/.\")},i.prototype._setupContainer=function(){var t=this._container;t.classList.add(\"mapboxgl-map\"),(this._missingCSSCanary=r.create(\"div\",\"mapboxgl-canary\",t)).style.visibility=\"hidden\",this._detectMissingCSS();var e=this._canvasContainer=r.create(\"div\",\"mapboxgl-canvas-container\",t);this._interactive&&e.classList.add(\"mapboxgl-interactive\"),this._canvas=r.create(\"canvas\",\"mapboxgl-canvas\",e),this._canvas.addEventListener(\"webglcontextlost\",this._contextLost,!1),this._canvas.addEventListener(\"webglcontextrestored\",this._contextRestored,!1),this._canvas.setAttribute(\"tabindex\",\"0\"),this._canvas.setAttribute(\"aria-label\",\"Map\"),this._canvas.setAttribute(\"role\",\"region\");var n=this._containerDimensions();this._resizeCanvas(n[0],n[1]);var i=this._controlContainer=r.create(\"div\",\"mapboxgl-control-container\",t),a=this._controlPositions={};[\"top-left\",\"top-right\",\"bottom-left\",\"bottom-right\"].forEach((function(t){a[t]=r.create(\"div\",\"mapboxgl-ctrl-\"+t,i)})),this._container.addEventListener(\"scroll\",this._onMapScroll,!1)},i.prototype._resizeCanvas=function(e,r){var n=t.browser.devicePixelRatio||1;this._canvas.width=n*e,this._canvas.height=n*r,this._canvas.style.width=e+\"px\",this._canvas.style.height=r+\"px\"},i.prototype._setupPainter=function(){var r=t.extend({},e.webGLContextAttributes,{failIfMajorPerformanceCaveat:this._failIfMajorPerformanceCaveat,preserveDrawingBuffer:this._preserveDrawingBuffer,antialias:this._antialias||!1}),n=this._canvas.getContext(\"webgl\",r)||this._canvas.getContext(\"experimental-webgl\",r);n?(this.painter=new Sn(n,this.transform),t.webpSupported.testSupport(n)):this.fire(new t.ErrorEvent(new Error(\"Failed to initialize WebGL\")))},i.prototype._contextLost=function(e){e.preventDefault(),this._frame&&(this._frame.cancel(),this._frame=null),this.fire(new t.Event(\"webglcontextlost\",{originalEvent:e}))},i.prototype._contextRestored=function(e){this._setupPainter(),this.resize(),this._update(),this.fire(new t.Event(\"webglcontextrestored\",{originalEvent:e}))},i.prototype._onMapScroll=function(t){if(t.target===this._container)return this._container.scrollTop=0,this._container.scrollLeft=0,!1},i.prototype.loaded=function(){return!this._styleDirty&&!this._sourcesDirty&&!!this.style&&this.style.loaded()},i.prototype._update=function(t){return this.style?(this._styleDirty=this._styleDirty||t,this._sourcesDirty=!0,this.triggerRepaint(),this):this},i.prototype._requestRenderFrame=function(t){return this._update(),this._renderTaskQueue.add(t)},i.prototype._cancelRenderFrame=function(t){this._renderTaskQueue.remove(t)},i.prototype._render=function(e){var r,n=this,i=0,a=this.painter.context.extTimerQuery;if(this.listens(\"gpu-timing-frame\")&&(r=a.createQueryEXT(),a.beginQueryEXT(a.TIME_ELAPSED_EXT,r),i=t.browser.now()),this.painter.context.setDirty(),this.painter.setBaseState(),this._renderTaskQueue.run(e),!this._removed){var o=!1;if(this.style&&this._styleDirty){this._styleDirty=!1;var s=this.transform.zoom,l=t.browser.now();this.style.zoomHistory.update(s,l);var u=new t.EvaluationParameters(s,{now:l,fadeDuration:this._fadeDuration,zoomHistory:this.style.zoomHistory,transition:this.style.getTransition()}),c=u.crossFadingFactor();1===c&&c===this._crossFadingFactor||(o=!0,this._crossFadingFactor=c),this.style.update(u)}if(this.style&&this._sourcesDirty&&(this._sourcesDirty=!1,this.style._updateSources(this.transform)),this._placementDirty=this.style&&this.style._updatePlacement(this.painter.transform,this.showCollisionBoxes,this._fadeDuration,this._crossSourceCollisions),this.painter.render(this.style,{showTileBoundaries:this.showTileBoundaries,showOverdrawInspector:this._showOverdrawInspector,rotating:this.isRotating(),zooming:this.isZooming(),moving:this.isMoving(),fadeDuration:this._fadeDuration,showPadding:this.showPadding,gpuTiming:!!this.listens(\"gpu-timing-layer\")}),this.fire(new t.Event(\"render\")),this.loaded()&&!this._loaded&&(this._loaded=!0,this.fire(new t.Event(\"load\"))),this.style&&(this.style.hasTransitions()||o)&&(this._styleDirty=!0),this.style&&!this._placementDirty&&this.style._releaseSymbolFadeTiles(),this.listens(\"gpu-timing-frame\")){var f=t.browser.now()-i;a.endQueryEXT(a.TIME_ELAPSED_EXT,r),setTimeout((function(){var e=a.getQueryObjectEXT(r,a.QUERY_RESULT_EXT)/1e6;a.deleteQueryEXT(r),n.fire(new t.Event(\"gpu-timing-frame\",{cpuTime:f,gpuTime:e}))}),50)}if(this.listens(\"gpu-timing-layer\")){var h=this.painter.collectGpuTimers();setTimeout((function(){var e=n.painter.queryGpuTimers(h);n.fire(new t.Event(\"gpu-timing-layer\",{layerTimes:e}))}),50)}var p=this._sourcesDirty||this._styleDirty||this._placementDirty;return p||this._repaint?this.triggerRepaint():!this.isMoving()&&this.loaded()&&this.fire(new t.Event(\"idle\")),!this._loaded||this._fullyLoaded||p||(this._fullyLoaded=!0),this}},i.prototype.remove=function(){this._hash&&this._hash.remove();for(var e=0,r=this._controls;e<r.length;e+=1)r[e].onRemove(this);this._controls=[],this._frame&&(this._frame.cancel(),this._frame=null),this._renderTaskQueue.clear(),this.painter.destroy(),this.handlers.destroy(),delete this.handlers,this.setStyle(null),void 0!==t.window&&(t.window.removeEventListener(\"resize\",this._onWindowResize,!1),t.window.removeEventListener(\"orientationchange\",this._onWindowResize,!1),t.window.removeEventListener(\"online\",this._onWindowOnline,!1));var n=this.painter.context.gl.getExtension(\"WEBGL_lose_context\");n&&n.loseContext&&n.loseContext(),Bi(this._canvasContainer),Bi(this._controlContainer),Bi(this._missingCSSCanary),this._container.classList.remove(\"mapboxgl-map\"),this._removed=!0,this.fire(new t.Event(\"remove\"))},i.prototype.triggerRepaint=function(){var e=this;this.style&&!this._frame&&(this._frame=t.browser.frame((function(t){e._frame=null,e._render(t)})))},i.prototype._onWindowOnline=function(){this._update()},i.prototype._onWindowResize=function(t){this._trackResize&&this.resize({originalEvent:t})._update()},a.showTileBoundaries.get=function(){return!!this._showTileBoundaries},a.showTileBoundaries.set=function(t){this._showTileBoundaries!==t&&(this._showTileBoundaries=t,this._update())},a.showPadding.get=function(){return!!this._showPadding},a.showPadding.set=function(t){this._showPadding!==t&&(this._showPadding=t,this._update())},a.showCollisionBoxes.get=function(){return!!this._showCollisionBoxes},a.showCollisionBoxes.set=function(t){this._showCollisionBoxes!==t&&(this._showCollisionBoxes=t,t?this.style._generateCollisionBoxes():this._update())},a.showOverdrawInspector.get=function(){return!!this._showOverdrawInspector},a.showOverdrawInspector.set=function(t){this._showOverdrawInspector!==t&&(this._showOverdrawInspector=t,this._update())},a.repaint.get=function(){return!!this._repaint},a.repaint.set=function(t){this._repaint!==t&&(this._repaint=t,this.triggerRepaint())},a.vertices.get=function(){return!!this._vertices},a.vertices.set=function(t){this._vertices=t,this._update()},i.prototype._setCacheLimits=function(e,r){t.setCacheLimits(e,r)},a.version.get=function(){return t.version},Object.defineProperties(i.prototype,a),i}(Si);function Bi(t){t.parentNode&&t.parentNode.removeChild(t)}var Ni={showCompass:!0,showZoom:!0,visualizePitch:!1},ji=function(e){var n=this;this.options=t.extend({},Ni,e),this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),this._container.addEventListener(\"contextmenu\",(function(t){return t.preventDefault()})),this.options.showZoom&&(t.bindAll([\"_setButtonTitle\",\"_updateZoomButtons\"],this),this._zoomInButton=this._createButton(\"mapboxgl-ctrl-zoom-in\",(function(t){return n._map.zoomIn({},{originalEvent:t})})),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._zoomInButton).setAttribute(\"aria-hidden\",!0),this._zoomOutButton=this._createButton(\"mapboxgl-ctrl-zoom-out\",(function(t){return n._map.zoomOut({},{originalEvent:t})})),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._zoomOutButton).setAttribute(\"aria-hidden\",!0)),this.options.showCompass&&(t.bindAll([\"_rotateCompassArrow\"],this),this._compass=this._createButton(\"mapboxgl-ctrl-compass\",(function(t){n.options.visualizePitch?n._map.resetNorthPitch({},{originalEvent:t}):n._map.resetNorth({},{originalEvent:t})})),this._compassIcon=r.create(\"span\",\"mapboxgl-ctrl-icon\",this._compass),this._compassIcon.setAttribute(\"aria-hidden\",!0))};ji.prototype._updateZoomButtons=function(){var t=this._map.getZoom(),e=t===this._map.getMaxZoom(),r=t===this._map.getMinZoom();this._zoomInButton.disabled=e,this._zoomOutButton.disabled=r,this._zoomInButton.setAttribute(\"aria-disabled\",e.toString()),this._zoomOutButton.setAttribute(\"aria-disabled\",r.toString())},ji.prototype._rotateCompassArrow=function(){var t=this.options.visualizePitch?\"scale(\"+1/Math.pow(Math.cos(this._map.transform.pitch*(Math.PI/180)),.5)+\") rotateX(\"+this._map.transform.pitch+\"deg) rotateZ(\"+this._map.transform.angle*(180/Math.PI)+\"deg)\":\"rotate(\"+this._map.transform.angle*(180/Math.PI)+\"deg)\";this._compassIcon.style.transform=t},ji.prototype.onAdd=function(t){return this._map=t,this.options.showZoom&&(this._setButtonTitle(this._zoomInButton,\"ZoomIn\"),this._setButtonTitle(this._zoomOutButton,\"ZoomOut\"),this._map.on(\"zoom\",this._updateZoomButtons),this._updateZoomButtons()),this.options.showCompass&&(this._setButtonTitle(this._compass,\"ResetBearing\"),this.options.visualizePitch&&this._map.on(\"pitch\",this._rotateCompassArrow),this._map.on(\"rotate\",this._rotateCompassArrow),this._rotateCompassArrow(),this._handler=new Ui(this._map,this._compass,this.options.visualizePitch)),this._container},ji.prototype.onRemove=function(){r.remove(this._container),this.options.showZoom&&this._map.off(\"zoom\",this._updateZoomButtons),this.options.showCompass&&(this.options.visualizePitch&&this._map.off(\"pitch\",this._rotateCompassArrow),this._map.off(\"rotate\",this._rotateCompassArrow),this._handler.off(),delete this._handler),delete this._map},ji.prototype._createButton=function(t,e){var n=r.create(\"button\",t,this._container);return n.type=\"button\",n.addEventListener(\"click\",e),n},ji.prototype._setButtonTitle=function(t,e){var r=this._map._getUIString(\"NavigationControl.\"+e);t.title=r,t.setAttribute(\"aria-label\",r)};var Ui=function(e,n,i){void 0===i&&(i=!1),this._clickTolerance=10,this.element=n,this.mouseRotate=new ei({clickTolerance:e.dragRotate._mouseRotate._clickTolerance}),this.map=e,i&&(this.mousePitch=new ri({clickTolerance:e.dragRotate._mousePitch._clickTolerance})),t.bindAll([\"mousedown\",\"mousemove\",\"mouseup\",\"touchstart\",\"touchmove\",\"touchend\",\"reset\"],this),r.addEventListener(n,\"mousedown\",this.mousedown),r.addEventListener(n,\"touchstart\",this.touchstart,{passive:!1}),r.addEventListener(n,\"touchmove\",this.touchmove),r.addEventListener(n,\"touchend\",this.touchend),r.addEventListener(n,\"touchcancel\",this.reset)};function Vi(e,r,n){if(e=new t.LngLat(e.lng,e.lat),r){var i=new t.LngLat(e.lng-360,e.lat),a=new t.LngLat(e.lng+360,e.lat),o=n.locationPoint(e).distSqr(r);n.locationPoint(i).distSqr(r)<o?e=i:n.locationPoint(a).distSqr(r)<o&&(e=a)}for(;Math.abs(e.lng-n.center.lng)>180;){var s=n.locationPoint(e);if(s.x>=0&&s.y>=0&&s.x<=n.width&&s.y<=n.height)break;e.lng>n.center.lng?e.lng-=360:e.lng+=360}return e}Ui.prototype.down=function(t,e){this.mouseRotate.mousedown(t,e),this.mousePitch&&this.mousePitch.mousedown(t,e),r.disableDrag()},Ui.prototype.move=function(t,e){var r=this.map,n=this.mouseRotate.mousemoveWindow(t,e);if(n&&n.bearingDelta&&r.setBearing(r.getBearing()+n.bearingDelta),this.mousePitch){var i=this.mousePitch.mousemoveWindow(t,e);i&&i.pitchDelta&&r.setPitch(r.getPitch()+i.pitchDelta)}},Ui.prototype.off=function(){var t=this.element;r.removeEventListener(t,\"mousedown\",this.mousedown),r.removeEventListener(t,\"touchstart\",this.touchstart,{passive:!1}),r.removeEventListener(t,\"touchmove\",this.touchmove),r.removeEventListener(t,\"touchend\",this.touchend),r.removeEventListener(t,\"touchcancel\",this.reset),this.offTemp()},Ui.prototype.offTemp=function(){r.enableDrag(),r.removeEventListener(t.window,\"mousemove\",this.mousemove),r.removeEventListener(t.window,\"mouseup\",this.mouseup)},Ui.prototype.mousedown=function(e){this.down(t.extend({},e,{ctrlKey:!0,preventDefault:function(){return e.preventDefault()}}),r.mousePos(this.element,e)),r.addEventListener(t.window,\"mousemove\",this.mousemove),r.addEventListener(t.window,\"mouseup\",this.mouseup)},Ui.prototype.mousemove=function(t){this.move(t,r.mousePos(this.element,t))},Ui.prototype.mouseup=function(t){this.mouseRotate.mouseupWindow(t),this.mousePitch&&this.mousePitch.mouseupWindow(t),this.offTemp()},Ui.prototype.touchstart=function(t){1!==t.targetTouches.length?this.reset():(this._startPos=this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.down({type:\"mousedown\",button:0,ctrlKey:!0,preventDefault:function(){return t.preventDefault()}},this._startPos))},Ui.prototype.touchmove=function(t){1!==t.targetTouches.length?this.reset():(this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.move({preventDefault:function(){return t.preventDefault()}},this._lastPos))},Ui.prototype.touchend=function(t){0===t.targetTouches.length&&this._startPos&&this._lastPos&&this._startPos.dist(this._lastPos)<this._clickTolerance&&this.element.click(),this.reset()},Ui.prototype.reset=function(){this.mouseRotate.reset(),this.mousePitch&&this.mousePitch.reset(),delete this._startPos,delete this._lastPos,this.offTemp()};var qi={center:\"translate(-50%,-50%)\",top:\"translate(-50%,0)\",\"top-left\":\"translate(0,0)\",\"top-right\":\"translate(-100%,0)\",bottom:\"translate(-50%,-100%)\",\"bottom-left\":\"translate(0,-100%)\",\"bottom-right\":\"translate(-100%,-100%)\",left:\"translate(0,-50%)\",right:\"translate(-100%,-50%)\"};function Hi(t,e,r){var n=t.classList;for(var i in qi)n.remove(\"mapboxgl-\"+r+\"-anchor-\"+i);n.add(\"mapboxgl-\"+r+\"-anchor-\"+e)}var Gi,Wi=function(e){function n(n,i){if(e.call(this),(n instanceof t.window.HTMLElement||i)&&(n=t.extend({element:n},i)),t.bindAll([\"_update\",\"_onMove\",\"_onUp\",\"_addDragHandler\",\"_onMapClick\",\"_onKeyPress\"],this),this._anchor=n&&n.anchor||\"center\",this._color=n&&n.color||\"#3FB1CE\",this._scale=n&&n.scale||1,this._draggable=n&&n.draggable||!1,this._clickTolerance=n&&n.clickTolerance||0,this._isDragging=!1,this._state=\"inactive\",this._rotation=n&&n.rotation||0,this._rotationAlignment=n&&n.rotationAlignment||\"auto\",this._pitchAlignment=n&&n.pitchAlignment&&\"auto\"!==n.pitchAlignment?n.pitchAlignment:this._rotationAlignment,n&&n.element)this._element=n.element,this._offset=t.Point.convert(n&&n.offset||[0,0]);else{this._defaultMarker=!0,this._element=r.create(\"div\"),this._element.setAttribute(\"aria-label\",\"Map marker\");var a=r.createNS(\"http://www.w3.org/2000/svg\",\"svg\");a.setAttributeNS(null,\"display\",\"block\"),a.setAttributeNS(null,\"height\",\"41px\"),a.setAttributeNS(null,\"width\",\"27px\"),a.setAttributeNS(null,\"viewBox\",\"0 0 27 41\");var o=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");o.setAttributeNS(null,\"stroke\",\"none\"),o.setAttributeNS(null,\"stroke-width\",\"1\"),o.setAttributeNS(null,\"fill\",\"none\"),o.setAttributeNS(null,\"fill-rule\",\"evenodd\");var s=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");s.setAttributeNS(null,\"fill-rule\",\"nonzero\");var l=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");l.setAttributeNS(null,\"transform\",\"translate(3.0, 29.0)\"),l.setAttributeNS(null,\"fill\",\"#000000\");for(var u=0,c=[{rx:\"10.5\",ry:\"5.25002273\"},{rx:\"10.5\",ry:\"5.25002273\"},{rx:\"9.5\",ry:\"4.77275007\"},{rx:\"8.5\",ry:\"4.29549936\"},{rx:\"7.5\",ry:\"3.81822308\"},{rx:\"6.5\",ry:\"3.34094679\"},{rx:\"5.5\",ry:\"2.86367051\"},{rx:\"4.5\",ry:\"2.38636864\"}];u<c.length;u+=1){var f=c[u],h=r.createNS(\"http://www.w3.org/2000/svg\",\"ellipse\");h.setAttributeNS(null,\"opacity\",\"0.04\"),h.setAttributeNS(null,\"cx\",\"10.5\"),h.setAttributeNS(null,\"cy\",\"5.80029008\"),h.setAttributeNS(null,\"rx\",f.rx),h.setAttributeNS(null,\"ry\",f.ry),l.appendChild(h)}var p=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");p.setAttributeNS(null,\"fill\",this._color);var d=r.createNS(\"http://www.w3.org/2000/svg\",\"path\");d.setAttributeNS(null,\"d\",\"M27,13.5 C27,19.074644 20.250001,27.000002 14.75,34.500002 C14.016665,35.500004 12.983335,35.500004 12.25,34.500002 C6.7499993,27.000002 0,19.222562 0,13.5 C0,6.0441559 6.0441559,0 13.5,0 C20.955844,0 27,6.0441559 27,13.5 Z\"),p.appendChild(d);var v=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");v.setAttributeNS(null,\"opacity\",\"0.25\"),v.setAttributeNS(null,\"fill\",\"#000000\");var g=r.createNS(\"http://www.w3.org/2000/svg\",\"path\");g.setAttributeNS(null,\"d\",\"M13.5,0 C6.0441559,0 0,6.0441559 0,13.5 C0,19.222562 6.7499993,27 12.25,34.5 C13,35.522727 14.016664,35.500004 14.75,34.5 C20.250001,27 27,19.074644 27,13.5 C27,6.0441559 20.955844,0 13.5,0 Z M13.5,1 C20.415404,1 26,6.584596 26,13.5 C26,15.898657 24.495584,19.181431 22.220703,22.738281 C19.945823,26.295132 16.705119,30.142167 13.943359,33.908203 C13.743445,34.180814 13.612715,34.322738 13.5,34.441406 C13.387285,34.322738 13.256555,34.180814 13.056641,33.908203 C10.284481,30.127985 7.4148684,26.314159 5.015625,22.773438 C2.6163816,19.232715 1,15.953538 1,13.5 C1,6.584596 6.584596,1 13.5,1 Z\"),v.appendChild(g);var y=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");y.setAttributeNS(null,\"transform\",\"translate(6.0, 7.0)\"),y.setAttributeNS(null,\"fill\",\"#FFFFFF\");var m=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");m.setAttributeNS(null,\"transform\",\"translate(8.0, 8.0)\");var x=r.createNS(\"http://www.w3.org/2000/svg\",\"circle\");x.setAttributeNS(null,\"fill\",\"#000000\"),x.setAttributeNS(null,\"opacity\",\"0.25\"),x.setAttributeNS(null,\"cx\",\"5.5\"),x.setAttributeNS(null,\"cy\",\"5.5\"),x.setAttributeNS(null,\"r\",\"5.4999962\");var b=r.createNS(\"http://www.w3.org/2000/svg\",\"circle\");b.setAttributeNS(null,\"fill\",\"#FFFFFF\"),b.setAttributeNS(null,\"cx\",\"5.5\"),b.setAttributeNS(null,\"cy\",\"5.5\"),b.setAttributeNS(null,\"r\",\"5.4999962\"),m.appendChild(x),m.appendChild(b),s.appendChild(l),s.appendChild(p),s.appendChild(v),s.appendChild(y),s.appendChild(m),a.appendChild(s),a.setAttributeNS(null,\"height\",41*this._scale+\"px\"),a.setAttributeNS(null,\"width\",27*this._scale+\"px\"),this._element.appendChild(a),this._offset=t.Point.convert(n&&n.offset||[0,-14])}this._element.classList.add(\"mapboxgl-marker\"),this._element.addEventListener(\"dragstart\",(function(t){t.preventDefault()})),this._element.addEventListener(\"mousedown\",(function(t){t.preventDefault()})),Hi(this._element,this._anchor,\"marker\"),this._popup=null}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.addTo=function(t){return this.remove(),this._map=t,t.getCanvasContainer().appendChild(this._element),t.on(\"move\",this._update),t.on(\"moveend\",this._update),this.setDraggable(this._draggable),this._update(),this._map.on(\"click\",this._onMapClick),this},n.prototype.remove=function(){return this._map&&(this._map.off(\"click\",this._onMapClick),this._map.off(\"move\",this._update),this._map.off(\"moveend\",this._update),this._map.off(\"mousedown\",this._addDragHandler),this._map.off(\"touchstart\",this._addDragHandler),this._map.off(\"mouseup\",this._onUp),this._map.off(\"touchend\",this._onUp),this._map.off(\"mousemove\",this._onMove),this._map.off(\"touchmove\",this._onMove),delete this._map),r.remove(this._element),this._popup&&this._popup.remove(),this},n.prototype.getLngLat=function(){return this._lngLat},n.prototype.setLngLat=function(e){return this._lngLat=t.LngLat.convert(e),this._pos=null,this._popup&&this._popup.setLngLat(this._lngLat),this._update(),this},n.prototype.getElement=function(){return this._element},n.prototype.setPopup=function(t){if(this._popup&&(this._popup.remove(),this._popup=null,this._element.removeEventListener(\"keypress\",this._onKeyPress),this._originalTabIndex||this._element.removeAttribute(\"tabindex\")),t){if(!(\"offset\"in t.options)){var e=13.5,r=Math.sqrt(Math.pow(e,2)/2);t.options.offset=this._defaultMarker?{top:[0,0],\"top-left\":[0,0],\"top-right\":[0,0],bottom:[0,-38.1],\"bottom-left\":[r,-1*(24.6+r)],\"bottom-right\":[-r,-1*(24.6+r)],left:[e,-24.6],right:[-13.5,-24.6]}:this._offset}this._popup=t,this._lngLat&&this._popup.setLngLat(this._lngLat),this._originalTabIndex=this._element.getAttribute(\"tabindex\"),this._originalTabIndex||this._element.setAttribute(\"tabindex\",\"0\"),this._element.addEventListener(\"keypress\",this._onKeyPress)}return this},n.prototype._onKeyPress=function(t){var e=t.code,r=t.charCode||t.keyCode;\"Space\"!==e&&\"Enter\"!==e&&32!==r&&13!==r||this.togglePopup()},n.prototype._onMapClick=function(t){var e=t.originalEvent.target,r=this._element;this._popup&&(e===r||r.contains(e))&&this.togglePopup()},n.prototype.getPopup=function(){return this._popup},n.prototype.togglePopup=function(){var t=this._popup;return t?(t.isOpen()?t.remove():t.addTo(this._map),this):this},n.prototype._update=function(t){if(this._map){this._map.transform.renderWorldCopies&&(this._lngLat=Vi(this._lngLat,this._pos,this._map.transform)),this._pos=this._map.project(this._lngLat)._add(this._offset);var e=\"\";\"viewport\"===this._rotationAlignment||\"auto\"===this._rotationAlignment?e=\"rotateZ(\"+this._rotation+\"deg)\":\"map\"===this._rotationAlignment&&(e=\"rotateZ(\"+(this._rotation-this._map.getBearing())+\"deg)\");var n=\"\";\"viewport\"===this._pitchAlignment||\"auto\"===this._pitchAlignment?n=\"rotateX(0deg)\":\"map\"===this._pitchAlignment&&(n=\"rotateX(\"+this._map.getPitch()+\"deg)\"),t&&\"moveend\"!==t.type||(this._pos=this._pos.round()),r.setTransform(this._element,qi[this._anchor]+\" translate(\"+this._pos.x+\"px, \"+this._pos.y+\"px) \"+n+\" \"+e)}},n.prototype.getOffset=function(){return this._offset},n.prototype.setOffset=function(e){return this._offset=t.Point.convert(e),this._update(),this},n.prototype._onMove=function(e){if(!this._isDragging){var r=this._clickTolerance||this._map._clickTolerance;this._isDragging=e.point.dist(this._pointerdownPos)>=r}this._isDragging&&(this._pos=e.point.sub(this._positionDelta),this._lngLat=this._map.unproject(this._pos),this.setLngLat(this._lngLat),this._element.style.pointerEvents=\"none\",\"pending\"===this._state&&(this._state=\"active\",this.fire(new t.Event(\"dragstart\"))),this.fire(new t.Event(\"drag\")))},n.prototype._onUp=function(){this._element.style.pointerEvents=\"auto\",this._positionDelta=null,this._pointerdownPos=null,this._isDragging=!1,this._map.off(\"mousemove\",this._onMove),this._map.off(\"touchmove\",this._onMove),\"active\"===this._state&&this.fire(new t.Event(\"dragend\")),this._state=\"inactive\"},n.prototype._addDragHandler=function(t){this._element.contains(t.originalEvent.target)&&(t.preventDefault(),this._positionDelta=t.point.sub(this._pos).add(this._offset),this._pointerdownPos=t.point,this._state=\"pending\",this._map.on(\"mousemove\",this._onMove),this._map.on(\"touchmove\",this._onMove),this._map.once(\"mouseup\",this._onUp),this._map.once(\"touchend\",this._onUp))},n.prototype.setDraggable=function(t){return this._draggable=!!t,this._map&&(t?(this._map.on(\"mousedown\",this._addDragHandler),this._map.on(\"touchstart\",this._addDragHandler)):(this._map.off(\"mousedown\",this._addDragHandler),this._map.off(\"touchstart\",this._addDragHandler))),this},n.prototype.isDraggable=function(){return this._draggable},n.prototype.setRotation=function(t){return this._rotation=t||0,this._update(),this},n.prototype.getRotation=function(){return this._rotation},n.prototype.setRotationAlignment=function(t){return this._rotationAlignment=t||\"auto\",this._update(),this},n.prototype.getRotationAlignment=function(){return this._rotationAlignment},n.prototype.setPitchAlignment=function(t){return this._pitchAlignment=t&&\"auto\"!==t?t:this._rotationAlignment,this._update(),this},n.prototype.getPitchAlignment=function(){return this._pitchAlignment},n}(t.Evented),Yi={positionOptions:{enableHighAccuracy:!1,maximumAge:0,timeout:6e3},fitBoundsOptions:{maxZoom:15},trackUserLocation:!1,showAccuracyCircle:!0,showUserLocation:!0};var Xi=0,Zi=!1,Ki=function(e){function n(r){e.call(this),this.options=t.extend({},Yi,r),t.bindAll([\"_onSuccess\",\"_onError\",\"_onZoom\",\"_finish\",\"_setupUI\",\"_updateCamera\",\"_updateMarker\"],this)}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.onAdd=function(e){return this._map=e,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),n=this._setupUI,void 0!==Gi?n(Gi):void 0!==t.window.navigator.permissions?t.window.navigator.permissions.query({name:\"geolocation\"}).then((function(t){Gi=\"denied\"!==t.state,n(Gi)})):(Gi=!!t.window.navigator.geolocation,n(Gi)),this._container;var n},n.prototype.onRemove=function(){void 0!==this._geolocationWatchID&&(t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0),this.options.showUserLocation&&this._userLocationDotMarker&&this._userLocationDotMarker.remove(),this.options.showAccuracyCircle&&this._accuracyCircleMarker&&this._accuracyCircleMarker.remove(),r.remove(this._container),this._map.off(\"zoom\",this._onZoom),this._map=void 0,Xi=0,Zi=!1},n.prototype._isOutOfMapMaxBounds=function(t){var e=this._map.getMaxBounds(),r=t.coords;return e&&(r.longitude<e.getWest()||r.longitude>e.getEast()||r.latitude<e.getSouth()||r.latitude>e.getNorth())},n.prototype._setErrorState=function(){switch(this._watchState){case\"WAITING_ACTIVE\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"ACTIVE_LOCK\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\");break;case\"BACKGROUND\":this._watchState=\"BACKGROUND_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\")}},n.prototype._onSuccess=function(e){if(this._map){if(this._isOutOfMapMaxBounds(e))return this._setErrorState(),this.fire(new t.Event(\"outofmaxbounds\",e)),this._updateMarker(),void this._finish();if(this.options.trackUserLocation)switch(this._lastKnownPosition=e,this._watchState){case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"BACKGROUND\":case\"BACKGROUND_ERROR\":this._watchState=\"BACKGROUND\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\")}this.options.showUserLocation&&\"OFF\"!==this._watchState&&this._updateMarker(e),this.options.trackUserLocation&&\"ACTIVE_LOCK\"!==this._watchState||this._updateCamera(e),this.options.showUserLocation&&this._dotElement.classList.remove(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"geolocate\",e)),this._finish()}},n.prototype._updateCamera=function(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude),n=e.coords.accuracy,i=this._map.getBearing(),a=t.extend({bearing:i},this.options.fitBoundsOptions);this._map.fitBounds(r.toBounds(n),a,{geolocateSource:!0})},n.prototype._updateMarker=function(e){if(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude);this._accuracyCircleMarker.setLngLat(r).addTo(this._map),this._userLocationDotMarker.setLngLat(r).addTo(this._map),this._accuracy=e.coords.accuracy,this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()}else this._userLocationDotMarker.remove(),this._accuracyCircleMarker.remove()},n.prototype._updateCircleRadius=function(){var t=this._map._container.clientHeight/2,e=this._map.unproject([0,t]),r=this._map.unproject([1,t]),n=e.distanceTo(r),i=Math.ceil(2*this._accuracy/n);this._circleElement.style.width=i+\"px\",this._circleElement.style.height=i+\"px\"},n.prototype._onZoom=function(){this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()},n.prototype._onError=function(e){if(this._map){if(this.options.trackUserLocation)if(1===e.code){this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.disabled=!0;var r=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.title=r,this._geolocateButton.setAttribute(\"aria-label\",r),void 0!==this._geolocationWatchID&&this._clearWatch()}else{if(3===e.code&&Zi)return;this._setErrorState()}\"OFF\"!==this._watchState&&this.options.showUserLocation&&this._dotElement.classList.add(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"error\",e)),this._finish()}},n.prototype._finish=function(){this._timeoutId&&clearTimeout(this._timeoutId),this._timeoutId=void 0},n.prototype._setupUI=function(e){var n=this;if(this._container.addEventListener(\"contextmenu\",(function(t){return t.preventDefault()})),this._geolocateButton=r.create(\"button\",\"mapboxgl-ctrl-geolocate\",this._container),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._geolocateButton).setAttribute(\"aria-hidden\",!0),this._geolocateButton.type=\"button\",!1===e){t.warnOnce(\"Geolocation support is not available so the GeolocateControl will be disabled.\");var i=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.disabled=!0,this._geolocateButton.title=i,this._geolocateButton.setAttribute(\"aria-label\",i)}else{var a=this._map._getUIString(\"GeolocateControl.FindMyLocation\");this._geolocateButton.title=a,this._geolocateButton.setAttribute(\"aria-label\",a)}this.options.trackUserLocation&&(this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this._watchState=\"OFF\"),this.options.showUserLocation&&(this._dotElement=r.create(\"div\",\"mapboxgl-user-location-dot\"),this._userLocationDotMarker=new Wi(this._dotElement),this._circleElement=r.create(\"div\",\"mapboxgl-user-location-accuracy-circle\"),this._accuracyCircleMarker=new Wi({element:this._circleElement,pitchAlignment:\"map\"}),this.options.trackUserLocation&&(this._watchState=\"OFF\"),this._map.on(\"zoom\",this._onZoom)),this._geolocateButton.addEventListener(\"click\",this.trigger.bind(this)),this._setup=!0,this.options.trackUserLocation&&this._map.on(\"movestart\",(function(e){var r=e.originalEvent&&\"resize\"===e.originalEvent.type;e.geolocateSource||\"ACTIVE_LOCK\"!==n._watchState||r||(n._watchState=\"BACKGROUND\",n._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\"),n._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),n.fire(new t.Event(\"trackuserlocationend\")))}))},n.prototype.trigger=function(){if(!this._setup)return t.warnOnce(\"Geolocate control triggered before added to a map\"),!1;if(this.options.trackUserLocation){switch(this._watchState){case\"OFF\":this._watchState=\"WAITING_ACTIVE\",this.fire(new t.Event(\"trackuserlocationstart\"));break;case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":case\"BACKGROUND_ERROR\":Xi--,Zi=!1,this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this.fire(new t.Event(\"trackuserlocationend\"));break;case\"BACKGROUND\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._lastKnownPosition&&this._updateCamera(this._lastKnownPosition),this.fire(new t.Event(\"trackuserlocationstart\"))}switch(this._watchState){case\"WAITING_ACTIVE\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_LOCK\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"BACKGROUND\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\");break;case\"BACKGROUND_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\")}if(\"OFF\"===this._watchState&&void 0!==this._geolocationWatchID)this._clearWatch();else if(void 0===this._geolocationWatchID){var e;this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"true\"),++Xi>1?(e={maximumAge:6e5,timeout:0},Zi=!0):(e=this.options.positionOptions,Zi=!1),this._geolocationWatchID=t.window.navigator.geolocation.watchPosition(this._onSuccess,this._onError,e)}}else t.window.navigator.geolocation.getCurrentPosition(this._onSuccess,this._onError,this.options.positionOptions),this._timeoutId=setTimeout(this._finish,1e4);return!0},n.prototype._clearWatch=function(){t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0,this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this.options.showUserLocation&&this._updateMarker(null)},n}(t.Evented),Ji={maxWidth:100,unit:\"metric\"},$i=function(e){this.options=t.extend({},Ji,e),t.bindAll([\"_onMove\",\"setUnit\"],this)};function Qi(t,e,r){var n=r&&r.maxWidth||100,i=t._container.clientHeight/2,a=t.unproject([0,i]),o=t.unproject([n,i]),s=a.distanceTo(o);if(r&&\"imperial\"===r.unit){var l=3.2808*s;l>5280?ta(e,n,l/5280,t._getUIString(\"ScaleControl.Miles\")):ta(e,n,l,t._getUIString(\"ScaleControl.Feet\"))}else r&&\"nautical\"===r.unit?ta(e,n,s/1852,t._getUIString(\"ScaleControl.NauticalMiles\")):s>=1e3?ta(e,n,s/1e3,t._getUIString(\"ScaleControl.Kilometers\")):ta(e,n,s,t._getUIString(\"ScaleControl.Meters\"))}function ta(t,e,r,n){var i,a,o,s=(i=r,(a=Math.pow(10,(\"\"+Math.floor(i)).length-1))*((o=i/a)>=10?10:o>=5?5:o>=3?3:o>=2?2:o>=1?1:function(t){var e=Math.pow(10,Math.ceil(-Math.log(t)/Math.LN10));return Math.round(t*e)/e}(o))),l=s/r;t.style.width=e*l+\"px\",t.innerHTML=s+\"&nbsp;\"+n}$i.prototype.getDefaultPosition=function(){return\"bottom-left\"},$i.prototype._onMove=function(){Qi(this._map,this._container,this.options)},$i.prototype.onAdd=function(t){return this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-scale\",t.getContainer()),this._map.on(\"move\",this._onMove),this._onMove(),this._container},$i.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"move\",this._onMove),this._map=void 0},$i.prototype.setUnit=function(t){this.options.unit=t,Qi(this._map,this._container,this.options)};var ea=function(e){this._fullscreen=!1,e&&e.container&&(e.container instanceof t.window.HTMLElement?this._container=e.container:t.warnOnce(\"Full screen control 'container' must be a DOM element.\")),t.bindAll([\"_onClickFullscreen\",\"_changeIcon\"],this),\"onfullscreenchange\"in t.window.document?this._fullscreenchange=\"fullscreenchange\":\"onmozfullscreenchange\"in t.window.document?this._fullscreenchange=\"mozfullscreenchange\":\"onwebkitfullscreenchange\"in t.window.document?this._fullscreenchange=\"webkitfullscreenchange\":\"onmsfullscreenchange\"in t.window.document&&(this._fullscreenchange=\"MSFullscreenChange\")};ea.prototype.onAdd=function(e){return this._map=e,this._container||(this._container=this._map.getContainer()),this._controlContainer=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),this._checkFullscreenSupport()?this._setupUI():(this._controlContainer.style.display=\"none\",t.warnOnce(\"This device does not support fullscreen mode.\")),this._controlContainer},ea.prototype.onRemove=function(){r.remove(this._controlContainer),this._map=null,t.window.document.removeEventListener(this._fullscreenchange,this._changeIcon)},ea.prototype._checkFullscreenSupport=function(){return!!(t.window.document.fullscreenEnabled||t.window.document.mozFullScreenEnabled||t.window.document.msFullscreenEnabled||t.window.document.webkitFullscreenEnabled)},ea.prototype._setupUI=function(){var e=this._fullscreenButton=r.create(\"button\",\"mapboxgl-ctrl-fullscreen\",this._controlContainer);r.create(\"span\",\"mapboxgl-ctrl-icon\",e).setAttribute(\"aria-hidden\",!0),e.type=\"button\",this._updateTitle(),this._fullscreenButton.addEventListener(\"click\",this._onClickFullscreen),t.window.document.addEventListener(this._fullscreenchange,this._changeIcon)},ea.prototype._updateTitle=function(){var t=this._getTitle();this._fullscreenButton.setAttribute(\"aria-label\",t),this._fullscreenButton.title=t},ea.prototype._getTitle=function(){return this._map._getUIString(this._isFullscreen()?\"FullscreenControl.Exit\":\"FullscreenControl.Enter\")},ea.prototype._isFullscreen=function(){return this._fullscreen},ea.prototype._changeIcon=function(){(t.window.document.fullscreenElement||t.window.document.mozFullScreenElement||t.window.document.webkitFullscreenElement||t.window.document.msFullscreenElement)===this._container!==this._fullscreen&&(this._fullscreen=!this._fullscreen,this._fullscreenButton.classList.toggle(\"mapboxgl-ctrl-shrink\"),this._fullscreenButton.classList.toggle(\"mapboxgl-ctrl-fullscreen\"),this._updateTitle())},ea.prototype._onClickFullscreen=function(){this._isFullscreen()?t.window.document.exitFullscreen?t.window.document.exitFullscreen():t.window.document.mozCancelFullScreen?t.window.document.mozCancelFullScreen():t.window.document.msExitFullscreen?t.window.document.msExitFullscreen():t.window.document.webkitCancelFullScreen&&t.window.document.webkitCancelFullScreen():this._container.requestFullscreen?this._container.requestFullscreen():this._container.mozRequestFullScreen?this._container.mozRequestFullScreen():this._container.msRequestFullscreen?this._container.msRequestFullscreen():this._container.webkitRequestFullscreen&&this._container.webkitRequestFullscreen()};var ra={closeButton:!0,closeOnClick:!0,focusAfterOpen:!0,className:\"\",maxWidth:\"240px\"},na=[\"a[href]\",\"[tabindex]:not([tabindex='-1'])\",\"[contenteditable]:not([contenteditable='false'])\",\"button:not([disabled])\",\"input:not([disabled])\",\"select:not([disabled])\",\"textarea:not([disabled])\"].join(\", \"),ia=function(e){function n(r){e.call(this),this.options=t.extend(Object.create(ra),r),t.bindAll([\"_update\",\"_onClose\",\"remove\",\"_onMouseMove\",\"_onMouseUp\",\"_onDrag\"],this)}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.addTo=function(e){return this._map&&this.remove(),this._map=e,this.options.closeOnClick&&this._map.on(\"click\",this._onClose),this.options.closeOnMove&&this._map.on(\"move\",this._onClose),this._map.on(\"remove\",this.remove),this._update(),this._focusFirstElement(),this._trackPointer?(this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"mouseup\",this._onMouseUp),this._container&&this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")):this._map.on(\"move\",this._update),this.fire(new t.Event(\"open\")),this},n.prototype.isOpen=function(){return!!this._map},n.prototype.remove=function(){return this._content&&r.remove(this._content),this._container&&(r.remove(this._container),delete this._container),this._map&&(this._map.off(\"move\",this._update),this._map.off(\"move\",this._onClose),this._map.off(\"click\",this._onClose),this._map.off(\"remove\",this.remove),this._map.off(\"mousemove\",this._onMouseMove),this._map.off(\"mouseup\",this._onMouseUp),this._map.off(\"drag\",this._onDrag),delete this._map),this.fire(new t.Event(\"close\")),this},n.prototype.getLngLat=function(){return this._lngLat},n.prototype.setLngLat=function(e){return this._lngLat=t.LngLat.convert(e),this._pos=null,this._trackPointer=!1,this._update(),this._map&&(this._map.on(\"move\",this._update),this._map.off(\"mousemove\",this._onMouseMove),this._container&&this._container.classList.remove(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.remove(\"mapboxgl-track-pointer\")),this},n.prototype.trackPointer=function(){return this._trackPointer=!0,this._pos=null,this._update(),this._map&&(this._map.off(\"move\",this._update),this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"drag\",this._onDrag),this._container&&this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")),this},n.prototype.getElement=function(){return this._container},n.prototype.setText=function(e){return this.setDOMContent(t.window.document.createTextNode(e))},n.prototype.setHTML=function(e){var r,n=t.window.document.createDocumentFragment(),i=t.window.document.createElement(\"body\");for(i.innerHTML=e;r=i.firstChild;)n.appendChild(r);return this.setDOMContent(n)},n.prototype.getMaxWidth=function(){return this._container&&this._container.style.maxWidth},n.prototype.setMaxWidth=function(t){return this.options.maxWidth=t,this._update(),this},n.prototype.setDOMContent=function(t){if(this._content)for(;this._content.hasChildNodes();)this._content.firstChild&&this._content.removeChild(this._content.firstChild);else this._content=r.create(\"div\",\"mapboxgl-popup-content\",this._container);return this._content.appendChild(t),this._createCloseButton(),this._update(),this._focusFirstElement(),this},n.prototype.addClassName=function(t){this._container&&this._container.classList.add(t)},n.prototype.removeClassName=function(t){this._container&&this._container.classList.remove(t)},n.prototype.setOffset=function(t){return this.options.offset=t,this._update(),this},n.prototype.toggleClassName=function(t){if(this._container)return this._container.classList.toggle(t)},n.prototype._createCloseButton=function(){this.options.closeButton&&(this._closeButton=r.create(\"button\",\"mapboxgl-popup-close-button\",this._content),this._closeButton.type=\"button\",this._closeButton.setAttribute(\"aria-label\",\"Close popup\"),this._closeButton.innerHTML=\"&#215;\",this._closeButton.addEventListener(\"click\",this._onClose))},n.prototype._onMouseUp=function(t){this._update(t.point)},n.prototype._onMouseMove=function(t){this._update(t.point)},n.prototype._onDrag=function(t){this._update(t.point)},n.prototype._update=function(t){var e=this,n=this._lngLat||this._trackPointer;if(this._map&&n&&this._content&&(this._container||(this._container=r.create(\"div\",\"mapboxgl-popup\",this._map.getContainer()),this._tip=r.create(\"div\",\"mapboxgl-popup-tip\",this._container),this._container.appendChild(this._content),this.options.className&&this.options.className.split(\" \").forEach((function(t){return e._container.classList.add(t)})),this._trackPointer&&this._container.classList.add(\"mapboxgl-popup-track-pointer\")),this.options.maxWidth&&this._container.style.maxWidth!==this.options.maxWidth&&(this._container.style.maxWidth=this.options.maxWidth),this._map.transform.renderWorldCopies&&!this._trackPointer&&(this._lngLat=Vi(this._lngLat,this._pos,this._map.transform)),!this._trackPointer||t)){var i=this._pos=this._trackPointer&&t?t:this._map.project(this._lngLat),a=this.options.anchor,o=aa(this.options.offset);if(!a){var s,l=this._container.offsetWidth,u=this._container.offsetHeight;s=i.y+o.bottom.y<u?[\"top\"]:i.y>this._map.transform.height-u?[\"bottom\"]:[],i.x<l/2?s.push(\"left\"):i.x>this._map.transform.width-l/2&&s.push(\"right\"),a=0===s.length?\"bottom\":s.join(\"-\")}var c=i.add(o[a]).round();r.setTransform(this._container,qi[a]+\" translate(\"+c.x+\"px,\"+c.y+\"px)\"),Hi(this._container,a,\"popup\")}},n.prototype._focusFirstElement=function(){if(this.options.focusAfterOpen&&this._container){var t=this._container.querySelector(na);t&&t.focus()}},n.prototype._onClose=function(){this.remove()},n}(t.Evented);function aa(e){if(e){if(\"number\"==typeof e){var r=Math.round(Math.sqrt(.5*Math.pow(e,2)));return{center:new t.Point(0,0),top:new t.Point(0,e),\"top-left\":new t.Point(r,r),\"top-right\":new t.Point(-r,r),bottom:new t.Point(0,-e),\"bottom-left\":new t.Point(r,-r),\"bottom-right\":new t.Point(-r,-r),left:new t.Point(e,0),right:new t.Point(-e,0)}}if(e instanceof t.Point||Array.isArray(e)){var n=t.Point.convert(e);return{center:n,top:n,\"top-left\":n,\"top-right\":n,bottom:n,\"bottom-left\":n,\"bottom-right\":n,left:n,right:n}}return{center:t.Point.convert(e.center||[0,0]),top:t.Point.convert(e.top||[0,0]),\"top-left\":t.Point.convert(e[\"top-left\"]||[0,0]),\"top-right\":t.Point.convert(e[\"top-right\"]||[0,0]),bottom:t.Point.convert(e.bottom||[0,0]),\"bottom-left\":t.Point.convert(e[\"bottom-left\"]||[0,0]),\"bottom-right\":t.Point.convert(e[\"bottom-right\"]||[0,0]),left:t.Point.convert(e.left||[0,0]),right:t.Point.convert(e.right||[0,0])}}return aa(new t.Point(0,0))}var oa={version:t.version,supported:e,setRTLTextPlugin:t.setRTLTextPlugin,getRTLTextPluginStatus:t.getRTLTextPluginStatus,Map:Fi,NavigationControl:ji,GeolocateControl:Ki,AttributionControl:Ei,ScaleControl:$i,FullscreenControl:ea,Popup:ia,Marker:Wi,Style:Ye,LngLat:t.LngLat,LngLatBounds:t.LngLatBounds,Point:t.Point,MercatorCoordinate:t.MercatorCoordinate,Evented:t.Evented,config:t.config,prewarm:function(){jt().acquire(Rt)},clearPrewarmedResources:function(){var t=Bt;t&&(t.isPreloaded()&&1===t.numActive()?(t.release(Rt),Bt=null):console.warn(\"Could not clear WebWorkers since there are active Map instances that still reference it. The pre-warmed WebWorker pool can only be cleared when all map instances have been removed with map.remove()\"))},get accessToken(){return t.config.ACCESS_TOKEN},set accessToken(e){t.config.ACCESS_TOKEN=e},get baseApiUrl(){return t.config.API_URL},set baseApiUrl(e){t.config.API_URL=e},get workerCount(){return Ft.workerCount},set workerCount(t){Ft.workerCount=t},get maxParallelImageRequests(){return t.config.MAX_PARALLEL_IMAGE_REQUESTS},set maxParallelImageRequests(e){t.config.MAX_PARALLEL_IMAGE_REQUESTS=e},clearStorage:function(e){t.clearTileCache(e)},workerUrl:\"\"};return oa})),r}()},3108:function(t,e,r){\"use strict\";t.exports=r(26099)},26099:function(t,e,r){\"use strict\";var n=r(64928),i=r(32420),a=r(51160),o=r(76752),s=r(55616),l=r(31264),u=r(47520),c=r(18400),f=r(72512),h=r(76244);function p(t,e){for(var r=e[0],n=e[1],a=1/(e[2]-r),o=1/(e[3]-n),s=new Array(t.length),l=0,u=t.length/2;l<u;l++)s[2*l]=i((t[2*l]-r)*a,0,1),s[2*l+1]=i((t[2*l+1]-n)*o,0,1);return 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t&&t._gl&&t.prop&&t.texture&&t.buffer}(t)?this.gl=o(t):(t={regl:t},this.gl=t.regl._gl),this.shader=b.get(this.gl),this.shader?this.regl=this.shader.regl:this.regl=t.regl||a({gl:this.gl}),this.charBuffer=this.regl.buffer({type:\"uint8\",usage:\"stream\"}),this.sizeBuffer=this.regl.buffer({type:\"float\",usage:\"stream\"}),this.shader||(this.shader=this.createShader(),b.set(this.gl,this.shader)),this.batch=[],this.fontSize=[],this.font=[],this.fontAtlas=[],this.draw=this.shader.draw.bind(this),this.render=function(){this.regl._refresh(),this.draw(this.batch)},this.canvas=this.gl.canvas,this.update(h(t)?t:{})};T.prototype.createShader=function(){var t=this.regl,e=t({blend:{enable:!0,color:[0,0,0,1],func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst 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float fontSize, charStep, em, align, baseline;\\n\\t\\t\\tuniform vec4 viewport;\\n\\t\\t\\tuniform vec4 color;\\n\\t\\t\\tuniform vec2 atlasSize, atlasDim, scale, translate, positionOffset;\\n\\t\\t\\tvarying vec2 charCoord, charId;\\n\\t\\t\\tvarying float charWidth;\\n\\t\\t\\tvarying vec4 fontColor;\\n\\t\\t\\tvoid main () {\\n\\t\\t\\t\\tvec2 offset = floor(em * (vec2(align + charOffset, baseline)\\n\\t\\t\\t\\t\\t+ vec2(positionOffset.x, -positionOffset.y)))\\n\\t\\t\\t\\t\\t/ (viewport.zw * scale.xy);\\n\\n\\t\\t\\t\\tvec2 position = (position + translate) * scale;\\n\\t\\t\\t\\tposition += offset * scale;\\n\\n\\t\\t\\t\\tcharCoord = position * viewport.zw + viewport.xy;\\n\\n\\t\\t\\t\\tgl_Position = vec4(position * 2. - 1., 0, 1);\\n\\n\\t\\t\\t\\tgl_PointSize = charStep;\\n\\n\\t\\t\\t\\tcharId.x = mod(char, atlasDim.x);\\n\\t\\t\\t\\tcharId.y = floor(char / atlasDim.x);\\n\\n\\t\\t\\t\\tcharWidth = width * em;\\n\\n\\t\\t\\t\\tfontColor = color / 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return;\\n\\n\\t\\t\\t\\tuv += charId * charStep;\\n\\t\\t\\t\\tuv = uv / atlasSize;\\n\\n\\t\\t\\t\\tvec4 color = fontColor;\\n\\t\\t\\t\\tvec4 mask = texture2D(atlas, uv);\\n\\n\\t\\t\\t\\tfloat maskY = lightness(mask);\\n\\t\\t\\t\\t// float colorY = lightness(color);\\n\\t\\t\\t\\tcolor.a *= maskY;\\n\\t\\t\\t\\tcolor.a *= opacity;\\n\\n\\t\\t\\t\\t// color.a += .1;\\n\\n\\t\\t\\t\\t// antialiasing, see yiq color space y-channel formula\\n\\t\\t\\t\\t// color.rgb += (1. - color.rgb) * (1. - mask.rgb);\\n\\n\\t\\t\\t\\tgl_FragColor = color;\\n\\t\\t\\t}\"});return{regl:t,draw:e,atlas:{}}},T.prototype.update=function(t){var e=this;if(\"string\"==typeof t)t={text:t};else if(!t)return;null!=(t=i(t,{position:\"position positions coord coords coordinates\",font:\"font fontFace fontface typeface cssFont css-font family fontFamily\",fontSize:\"fontSize fontsize size font-size\",text:\"text texts chars characters value values symbols\",align:\"align alignment textAlign 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t.offset&&(t.offset=[t.offset,0]),this.positionOffset=m(t.offset)),t.direction&&(this.direction=t.direction),t.range&&(this.range=t.range,this.scale=[1/(t.range[2]-t.range[0]),1/(t.range[3]-t.range[1])],this.translate=[-t.range[0],-t.range[1]]),t.scale&&(this.scale=t.scale),t.translate&&(this.translate=t.translate),this.scale||(this.scale=[1/this.viewport.width,1/this.viewport.height]),this.translate||(this.translate=[0,0]),this.font.length||t.font||(t.font=T.baseFontSize+\"px sans-serif\");var r,a=!1,o=!1;if(t.font&&(Array.isArray(t.font)?t.font:[t.font]).forEach((function(t,r){if(\"string\"==typeof t)try{t=n.parse(t)}catch(e){t=n.parse(T.baseFontSize+\"px \"+t)}else t=n.parse(n.stringify(t));var i=n.stringify({size:T.baseFontSize,family:t.family,stretch:_?t.stretch:void 0,variant:t.variant,weight:t.weight,style:t.style}),s=p(t.size),l=Math.round(s[0]*d(s[1]));if(l!==e.fontSize[r]&&(o=!0,e.fontSize[r]=l),!(e.font[r]&&i==e.font[r].baseString||(a=!0,e.font[r]=T.fonts[i],e.font[r]))){var u=t.family.join(\", \"),c=[t.style];t.style!=t.variant&&c.push(t.variant),t.variant!=t.weight&&c.push(t.weight),_&&t.weight!=t.stretch&&c.push(t.stretch),e.font[r]={baseString:i,family:u,weight:t.weight,stretch:t.stretch,style:t.style,variant:t.variant,width:{},kerning:{},metrics:y(u,{origin:\"top\",fontSize:T.baseFontSize,fontStyle:c.join(\" \")})},T.fonts[i]=e.font[r]}})),(a||o)&&this.font.forEach((function(r,i){var a=n.stringify({size:e.fontSize[i],family:r.family,stretch:_?r.stretch:void 0,variant:r.variant,weight:r.weight,style:r.style});if(e.fontAtlas[i]=e.shader.atlas[a],!e.fontAtlas[i]){var o=r.metrics;e.shader.atlas[a]=e.fontAtlas[i]={fontString:a,step:2*Math.ceil(e.fontSize[i]*o.bottom*.5),em:e.fontSize[i],cols:0,rows:0,height:0,width:0,chars:[],ids:{},texture:e.regl.texture()}}null==t.text&&(t.text=e.text)})),\"string\"==typeof t.text&&t.position&&t.position.length>2){for(var s=Array(.5*t.position.length),h=0;h<s.length;h++)s[h]=t.text;t.text=s}if(null!=t.text||a){if(this.textOffsets=[0],Array.isArray(t.text)){this.count=t.text[0].length,this.counts=[this.count];for(var b=1;b<t.text.length;b++)this.textOffsets[b]=this.textOffsets[b-1]+t.text[b-1].length,this.count+=t.text[b].length,this.counts.push(t.text[b].length);this.text=t.text.join(\"\")}else this.text=t.text,this.count=this.text.length,this.counts=[this.count];r=[],this.font.forEach((function(t,n){T.atlasContext.font=t.baseString;for(var i=e.fontAtlas[n],a=0;a<e.text.length;a++){var o=e.text.charAt(a);if(null==i.ids[o]&&(i.ids[o]=i.chars.length,i.chars.push(o),r.push(o)),null==t.width[o]&&(t.width[o]=T.atlasContext.measureText(o).width/T.baseFontSize,e.kerning)){var s=[];for(var l in t.width)s.push(l+o,o+l);g(t.kerning,v(t.family,{pairs:s}))}}}))}if(t.position)if(t.position.length>2){for(var w=!t.position[0].length,k=c.mallocFloat(2*this.count),A=0,M=0;A<this.counts.length;A++){var S=this.counts[A];if(w)for(var E=0;E<S;E++)k[M++]=t.position[2*A],k[M++]=t.position[2*A+1];else for(var L=0;L<S;L++)k[M++]=t.position[A][0],k[M++]=t.position[A][1]}this.position.call?this.position({type:\"float\",data:k}):this.position=this.regl.buffer({type:\"float\",data:k}),c.freeFloat(k)}else this.position.destroy&&this.position.destroy(),this.position={constant:t.position};if(t.text||a){var C=c.mallocUint8(this.count),P=c.mallocFloat(2*this.count);this.textWidth=[];for(var O=0,I=0;O<this.counts.length;O++){for(var D=this.counts[O],z=this.font[O]||this.font[0],R=this.fontAtlas[O]||this.fontAtlas[0],F=0;F<D;F++){var B=this.text.charAt(I),N=this.text.charAt(I-1);if(C[I]=R.ids[B],P[2*I]=z.width[B],F){var j=P[2*I-2],U=P[2*I],V=P[2*I-1]+.5*j+.5*U;if(this.kerning){var q=z.kerning[N+B];q&&(V+=.001*q)}P[2*I+1]=V}else P[2*I+1]=.5*P[2*I];I++}this.textWidth.push(P.length?.5*P[2*I-2]+P[2*I-1]:0)}t.align||(t.align=this.align),this.charBuffer({data:C,type:\"uint8\",usage:\"stream\"}),this.sizeBuffer({data:P,type:\"float\",usage:\"stream\"}),c.freeUint8(C),c.freeFloat(P),r.length&&this.font.forEach((function(t,r){var n=e.fontAtlas[r],i=n.step,a=Math.floor(T.maxAtlasSize/i),o=Math.min(a,n.chars.length),s=Math.ceil(n.chars.length/o),l=x(o*i),c=x(s*i);n.width=l,n.height=c,n.rows=s,n.cols=o,n.em&&n.texture({data:u({canvas:T.atlasCanvas,font:n.fontString,chars:n.chars,shape:[l,c],step:[i,i]})})}))}if(t.align&&(this.align=t.align,this.alignOffset=this.textWidth.map((function(t,r){var n=Array.isArray(e.align)?e.align.length>1?e.align[r]:e.align[0]:e.align;if(\"number\"==typeof n)return n;switch(n){case\"right\":case\"end\":return-t;case\"center\":case\"centre\":case\"middle\":return.5*-t}return 0}))),null==this.baseline&&null==t.baseline&&(t.baseline=0),null!=t.baseline&&(this.baseline=t.baseline,Array.isArray(this.baseline)||(this.baseline=[this.baseline]),this.baselineOffset=this.baseline.map((function(t,r){var n=(e.font[r]||e.font[0]).metrics,i=0;return i+=.5*n.bottom,-1*(i+=\"number\"==typeof t?t-n.baseline:-n[t])}))),null!=t.color)if(t.color||(t.color=\"transparent\"),\"string\"!=typeof t.color&&isNaN(t.color)){var H;if(\"number\"==typeof t.color[0]&&t.color.length>this.counts.length){var G=t.color.length;H=c.mallocUint8(G);for(var W=(t.color.subarray||t.color.slice).bind(t.color),Y=0;Y<G;Y+=4)H.set(l(W(Y,Y+4),\"uint8\"),Y)}else{var X=t.color.length;H=c.mallocUint8(4*X);for(var Z=0;Z<X;Z++)H.set(l(t.color[Z]||0,\"uint8\"),4*Z)}this.color=H}else this.color=l(t.color,\"uint8\");if(t.position||t.text||t.color||t.baseline||t.align||t.font||t.offset||t.opacity)if(this.color.length>4||this.baselineOffset.length>1||this.align&&this.align.length>1||this.fontAtlas.length>1||this.positionOffset.length>2){var K=Math.max(.5*this.position.length||0,.25*this.color.length||0,this.baselineOffset.length||0,this.alignOffset.length||0,this.font.length||0,this.opacity.length||0,.5*this.positionOffset.length||0);this.batch=Array(K);for(var J=0;J<this.batch.length;J++)this.batch[J]={count:this.counts.length>1?this.counts[J]:this.counts[0],offset:this.textOffsets.length>1?this.textOffsets[J]:this.textOffsets[0],color:this.color?this.color.length<=4?this.color:this.color.subarray(4*J,4*J+4):[0,0,0,255],opacity:Array.isArray(this.opacity)?this.opacity[J]:this.opacity,baseline:null!=this.baselineOffset[J]?this.baselineOffset[J]:this.baselineOffset[0],align:this.align?null!=this.alignOffset[J]?this.alignOffset[J]:this.alignOffset[0]:0,atlas:this.fontAtlas[J]||this.fontAtlas[0],positionOffset:this.positionOffset.length>2?this.positionOffset.subarray(2*J,2*J+2):this.positionOffset}}else this.count?this.batch=[{count:this.count,offset:0,color:this.color||[0,0,0,255],opacity:Array.isArray(this.opacity)?this.opacity[0]:this.opacity,baseline:this.baselineOffset[0],align:this.alignOffset?this.alignOffset[0]:0,atlas:this.fontAtlas[0],positionOffset:this.positionOffset}]:this.batch=[]},T.prototype.destroy=function(){},T.prototype.kerning=!0,T.prototype.position={constant:new Float32Array(2)},T.prototype.translate=null,T.prototype.scale=null,T.prototype.font=null,T.prototype.text=\"\",T.prototype.positionOffset=[0,0],T.prototype.opacity=1,T.prototype.color=new Uint8Array([0,0,0,255]),T.prototype.alignOffset=[0,0],T.maxAtlasSize=1024,T.atlasCanvas=document.createElement(\"canvas\"),T.atlasContext=T.atlasCanvas.getContext(\"2d\",{alpha:!1}),T.baseFontSize=64,T.fonts={},t.exports=T},55212:function(t,e,r){\"use strict\";var n=r(55616);function 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n=t.segments({inverted:!1,regions:[]}),i=0;i<e.coordinates.length;i++)n=t.selectUnion(t.combine(n,r(e.coordinates[i])));return t.polygon(n)}throw new Error(\"PolyBool: Cannot convert GeoJSON object to PolyBool polygon\")},fromPolygon:function(t,e,r){function n(t,r){return e.pointInsideRegion([.5*(t[0][0]+t[1][0]),.5*(t[0][1]+t[1][1])],r)}function i(t){return{region:t,children:[]}}r=t.polygon(t.segments(r));var a=i(null);function o(t,e){for(var r=0;r<t.children.length;r++)if(n(e,(s=t.children[r]).region))return void o(s,e);var a=i(e);for(r=0;r<t.children.length;r++){var s;n((s=t.children[r]).region,e)&&(a.children.push(s),t.children.splice(r,1),r--)}t.children.push(a)}for(var s=0;s<r.regions.length;s++){var l=r.regions[s];l.length<3||o(a,l)}function u(t,e){for(var r=0,n=t[t.length-1][0],i=t[t.length-1][1],a=[],o=0;o<t.length;o++){var s=t[o][0],l=t[o][1];a.push([s,l]),r+=l*n-s*i,n=s,i=l}return r<0!==e&&a.reverse(),a.push([a[0][0],a[0][1]]),a}var c=[];function f(t){var e=[u(t.region,!1)];c.push(e);for(var r=0;r<t.children.length;r++)e.push(h(t.children[r]))}function h(t){for(var e=0;e<t.children.length;e++)f(t.children[e]);return u(t.region,!0)}for(s=0;s<a.children.length;s++)f(a.children[s]);return c.length<=0?{type:\"Polygon\",coordinates:[]}:1==c.length?{type:\"Polygon\",coordinates:c[0]}:{type:\"MultiPolygon\",coordinates:c}}};t.exports=e},72200:function(t,e,r){var n=r(48088);t.exports=function(t,e,r){function i(t,e,n){return{id:r?r.segmentId():-1,start:t,end:e,myFill:{above:n.myFill.above,below:n.myFill.below},otherFill:null}}var a=n.create();function o(t,r){a.insertBefore(t,(function(n){return i=t.isStart,a=t.pt,o=r,s=n.isStart,l=n.pt,u=n.other.pt,(0!==(c=e.pointsCompare(a,l))?c:e.pointsSame(o,u)?0:i!==s?i?1:-1:e.pointAboveOrOnLine(o,s?l:u,s?u:l)?1:-1)<0;var i,a,o,s,l,u,c}))}function s(t,e){var r=function(t,e){var r=n.node({isStart:!0,pt:t.start,seg:t,primary:e,other:null,status:null});return o(r,t.end),r}(t,e);return function(t,e,r){var 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y,m,x=g();if(x)t?(m=null===h.seg.myFill.below||h.seg.myFill.above!==h.seg.myFill.below)&&(x.seg.myFill.above=!x.seg.myFill.above):x.seg.otherFill=h.seg.myFill,r&&r.segmentUpdate(x.seg),h.other.remove(),h.remove();if(a.getHead()!==h){r&&r.rewind(h.seg);continue}t?(m=null===h.seg.myFill.below||h.seg.myFill.above!==h.seg.myFill.below,h.seg.myFill.below=v?v.seg.myFill.above:i,h.seg.myFill.above=m?!h.seg.myFill.below:h.seg.myFill.below):null===h.seg.otherFill&&(y=v?h.primary===v.primary?v.seg.otherFill.above:v.seg.myFill.above:h.primary?o:i,h.seg.otherFill={above:y,below:y}),r&&r.status(h.seg,!!d&&d.seg,!!v&&v.seg),h.other.status=p.insert(n.node({ev:h}))}else{var b=h.status;if(null===b)throw new Error(\"PolyBool: Zero-length segment detected; your epsilon is probably too small or too large\");if(s.exists(b.prev)&&s.exists(b.next)&&c(b.prev.ev,b.next.ev),r&&r.statusRemove(b.ev.seg),b.remove(),!h.primary){var 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r=t.root,n=t.root.next;null!==n&&!e(n);)r=n,n=n.next;return{before:r===t.root?null:r,after:n,insert:function(t){return t.prev=r,t.next=n,r.next=t,null!==n&&(n.prev=t),t}}}};return t},node:function(t){return t.prev=null,t.next=null,t.remove=function(){t.prev.next=t.next,t.next&&(t.next.prev=t.prev),t.prev=null,t.next=null},t}}},11403:function(t){t.exports=function(t,e,r){var n=[],i=[];return t.forEach((function(t){var a=t.start,o=t.end;if(e.pointsSame(a,o))console.warn(\"PolyBool: Warning: Zero-length segment detected; your epsilon is probably too small or too large\");else{r&&r.chainStart(t);for(var s={index:0,matches_head:!1,matches_pt1:!1},l={index:0,matches_head:!1,matches_pt1:!1},u=s,c=0;c<n.length;c++){var f=(g=n[c])[0],h=(g[1],g[g.length-1]);if(g[g.length-2],e.pointsSame(f,a)){if(k(c,!0,!0))break}else if(e.pointsSame(f,o)){if(k(c,!0,!1))break}else if(e.pointsSame(h,a)){if(k(c,!1,!0))break}else if(e.pointsSame(h,o)&&k(c,!1,!1))break}if(u===s)return 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a=n[t],o=n[i],s=a[a.length-1],l=a[a.length-2],u=o[0],c=o[1];e.pointsCollinear(l,s,u)&&(r&&r.chainRemoveTail(t,s),a.pop(),s=l),e.pointsCollinear(s,u,c)&&(r&&r.chainRemoveHead(i,u),o.shift()),r&&r.chainJoin(t,i),n[t]=a.concat(o),n.splice(i,1)}})),i}},82368:function(t){function e(t,e,r){var n=[];return t.forEach((function(t){var i=(t.myFill.above?8:0)+(t.myFill.below?4:0)+(t.otherFill&&t.otherFill.above?2:0)+(t.otherFill&&t.otherFill.below?1:0);0!==e[i]&&n.push({id:r?r.segmentId():-1,start:t.start,end:t.end,myFill:{above:1===e[i],below:2===e[i]},otherFill:null})})),r&&r.selected(n),n}var r={union:function(t,r){return e(t,[0,2,1,0,2,2,0,0,1,0,1,0,0,0,0,0],r)},intersect:function(t,r){return e(t,[0,0,0,0,0,2,0,2,0,0,1,1,0,2,1,0],r)},difference:function(t,r){return e(t,[0,0,0,0,2,0,2,0,1,1,0,0,0,1,2,0],r)},differenceRev:function(t,r){return e(t,[0,2,1,0,0,0,1,1,0,2,0,2,0,0,0,0],r)},xor:function(t,r){return e(t,[0,2,1,0,2,0,0,1,1,0,0,2,0,1,2,0],r)}};t.exports=r},9696:function(t,e,r){\"use 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this.big_endian?16777216*r[t]+65536*r[t+1]+256*r[t+2]+r[t+3]:r[t]+256*r[t+1]+65536*r[t+2]+16777216*r[t+3]},n.prototype.is_subifd_link=function(t,e){return 0===t&&34665===e||0===t&&34853===e||34665===t&&40965===e},n.prototype.exif_format_length=function(t){switch(t){case 1:case 2:case 6:case 7:return 1;case 3:case 8:return 2;case 4:case 9:case 11:return 4;case 5:case 10:case 12:return 8;default:return 0}},n.prototype.exif_format_read=function(t,e){var r;switch(t){case 1:case 2:return this.input[e];case 6:return(r=this.input[e])|33554430*(128&r);case 3:return this.read_uint16(e);case 8:return(r=this.read_uint16(e))|131070*(32768&r);case 4:return this.read_uint32(e);case 9:return 0|this.read_uint32(e);default:return null}},n.prototype.scan_ifd=function(t,n,i){var a=this.read_uint16(n);n+=2;for(var o=0;o<a;o++){var s=this.read_uint16(n),l=this.read_uint16(n+2),u=this.read_uint32(n+4),c=this.exif_format_length(l),f=u*c,h=f<=4?n+8:this.read_uint32(n+8),p=!1;if(h+f>this.input.length)throw e(\"unexpected EOF\",\"EBADDATA\");for(var d=[],v=h,g=0;g<u;g++,v+=c){var y=this.exif_format_read(l,v);if(null===y){d=null;break}d.push(y)}if(Array.isArray(d)&&2===l&&(d=r(String.fromCharCode.apply(null,d)))&&\"\\0\"===d[d.length-1]&&(d=d.slice(0,-1)),this.is_subifd_link(t,s)&&Array.isArray(d)&&Number.isInteger(d[0])&&d[0]>0&&(this.ifds_to_read.push({id:s,offset:d[0]}),p=!0),!1===i({is_big_endian:this.big_endian,ifd:t,tag:s,format:l,count:u,entry_offset:n+this.start,data_length:f,data_offset:h+this.start,value:d,is_subifd_link:p}))return void(this.aborted=!0);n+=12}0===t&&this.ifds_to_read.push({id:1,offset:this.read_uint32(n)})},t.exports.ExifParser=n,t.exports.get_orientation=function(t){var e=0;try{return new n(t,0,t.length).each((function(t){if(0===t.ifd&&274===t.tag&&Array.isArray(t.value))return e=t.value[0],!1})),e}catch(t){return-1}}},44600:function(t,e,r){\"use strict\";var n=r(9696).eW,i=r(9696).eI;function a(t,e){if(t.length<4+e)return null;var r=i(t,e);return 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t=l(t,\"float64\"),r.count=Math.floor(t.length/2),r.bounds=n(t,2),r.offset=e,e+=r.count,t}},{color:function(t,e){var r=e.count;if(t||(t=\"transparent\"),!Array.isArray(t)||\"number\"==typeof t[0]){var n=t;t=Array(r);for(var a=0;a<r;a++)t[a]=n}if(t.length<r)throw Error(\"Not enough colors\");for(var o=new Uint8Array(4*r),s=0;s<r;s++){var l=i(t[s],\"uint8\");o.set(l,4*s)}return o},range:function(t,e,r){var n=e.bounds;return t||(t=n),e.scale=[1/(t[2]-t[0]),1/(t[3]-t[1])],e.translate=[-t[0],-t[1]],e.scaleFract=f(e.scale),e.translateFract=f(e.translate),t},viewport:function(t){var e;return Array.isArray(t)?e={x:t[0],y:t[1],width:t[2]-t[0],height:t[3]-t[1]}:t?(e={x:t.x||t.left||0,y:t.y||t.top||0},t.right?e.width=t.right-e.x:e.width=t.w||t.width||0,t.bottom?e.height=t.bottom-e.y:e.height=t.h||t.height||0):e={x:0,y:0,width:y.drawingBufferWidth,height:y.drawingBufferHeight},e}}]),c):c})),e||r){var h=x.reduce((function(t,e,r){return t+(e?e.count:0)}),0),g=new Float64Array(2*h),_=new Uint8Array(4*h),w=new Float32Array(4*h);x.forEach((function(t,e){if(t){var r=t.positions,n=t.count,i=t.offset,a=t.color,o=t.errors;n&&(_.set(a,4*i),w.set(o,4*i),g.set(r,2*i))}}));var T=c(g);u(T);var k=f(g,T);p(k),d(_),v(w)}}}function k(){u.destroy(),p.destroy(),d.destroy(),v.destroy(),g.destroy()}};var h=[[1,0,0,1,0,0],[1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,1,0,0],[1,0,0,1,0,0],[1,0,-1,0,0,1],[1,0,-1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,1],[1,0,-1,0,0,1],[-1,0,-1,0,0,1],[-1,0,-1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,1],[-1,0,-1,0,0,1],[0,1,1,0,0,0],[0,1,-1,0,0,0],[0,-1,-1,0,0,0],[0,-1,-1,0,0,0],[0,1,1,0,0,0],[0,-1,1,0,0,0],[0,1,0,-1,1,0],[0,1,0,-1,-1,0],[0,1,0,1,-1,0],[0,1,0,1,1,0],[0,1,0,-1,1,0],[0,1,0,1,-1,0],[0,-1,0,-1,1,0],[0,-1,0,-1,-1,0],[0,-1,0,1,-1,0],[0,-1,0,1,1,0],[0,-1,0,-1,1,0],[0,-1,0,1,-1,0]]},13472:function(t,e,r){\"use strict\";var n=r(72160),i=r(76752),a=r(50896),o=r(55616),s=r(47520),l=r(28912),u=r(71152),c=r(37816),f=c.float32,h=c.fract32,p=r(60463),d=r(51160),v=r(10272);function g(t,e){if(!(this instanceof g))return new g(t,e);if(\"function\"==typeof t?(e||(e={}),e.regl=t):e=t,e.length&&(e.positions=e),!(t=e.regl).hasExtension(\"ANGLE_instanced_arrays\"))throw Error(\"regl-error2d: `ANGLE_instanced_arrays` extension should be enabled\");this.gl=t._gl,this.regl=t,this.passes=[],this.shaders=g.shaders.has(t)?g.shaders.get(t):g.shaders.set(t,g.createShaders(t)).get(t),this.update(e)}t.exports=g,g.dashMult=2,g.maxPatternLength=256,g.precisionThreshold=3e6,g.maxPoints=1e4,g.maxLines=2048,g.shaders=new p,g.createShaders=function(t){var e,r=t.buffer({usage:\"static\",type:\"float\",data:[0,1,0,0,1,1,1,0]}),n={primitive:\"triangle strip\",instances:t.prop(\"count\"),count:4,offset:0,uniforms:{miterMode:function(t,e){return\"round\"===e.join?2:1},miterLimit:t.prop(\"miterLimit\"),scale:t.prop(\"scale\"),scaleFract:t.prop(\"scaleFract\"),translateFract:t.prop(\"translateFract\"),translate:t.prop(\"translate\"),thickness:t.prop(\"thickness\"),dashTexture:t.prop(\"dashTexture\"),opacity:t.prop(\"opacity\"),pixelRatio:t.context(\"pixelRatio\"),id:t.prop(\"id\"),dashLength:t.prop(\"dashLength\"),viewport:function(t,e){return[e.viewport.x,e.viewport.y,t.viewportWidth,t.viewportHeight]},depth:t.prop(\"depth\")},blend:{enable:!0,color:[0,0,0,0],equation:{rgb:\"add\",alpha:\"add\"},func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst alpha\",dstAlpha:\"one\"}},depth:{enable:function(t,e){return!e.overlay}},stencil:{enable:!1},scissor:{enable:!0,box:t.prop(\"viewport\")},viewport:t.prop(\"viewport\")},i=t(a({vert:\"\\nprecision highp float;\\n\\nattribute vec2 aCoord, bCoord, aCoordFract, bCoordFract;\\nattribute vec4 color;\\nattribute float lineEnd, lineTop;\\n\\nuniform vec2 scale, scaleFract, translate, translateFract;\\nuniform float thickness, pixelRatio, id, depth;\\nuniform vec4 viewport;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\n\\nvec2 project(vec2 position, vec2 positionFract, vec2 scale, vec2 scaleFract, vec2 translate, vec2 translateFract) {\\n\\t// the order is important\\n\\treturn position * scale + translate\\n       + positionFract * scale + translateFract\\n       + position * scaleFract\\n       + positionFract * scaleFract;\\n}\\n\\nvoid main() {\\n\\tfloat lineStart = 1. - lineEnd;\\n\\tfloat lineOffset = lineTop * 2. - 1.;\\n\\n\\tvec2 diff = (bCoord + bCoordFract - aCoord - aCoordFract);\\n\\ttangent = normalize(diff * scale * viewport.zw);\\n\\tvec2 normal = vec2(-tangent.y, tangent.x);\\n\\n\\tvec2 position = project(aCoord, aCoordFract, scale, scaleFract, translate, translateFract) * lineStart\\n\\t\\t+ project(bCoord, bCoordFract, scale, scaleFract, translate, translateFract) * lineEnd\\n\\n\\t\\t+ thickness * normal * .5 * lineOffset / viewport.zw;\\n\\n\\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\\n\\n\\tfragColor = color / 255.;\\n}\\n\",frag:\"\\nprecision highp float;\\n\\nuniform float dashLength, pixelRatio, thickness, opacity, id;\\nuniform sampler2D dashTexture;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\n\\nvoid main() {\\n\\tfloat alpha = 1.;\\n\\n\\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashLength) * .5 + .25;\\n\\tfloat dash = texture2D(dashTexture, vec2(t, .5)).r;\\n\\n\\tgl_FragColor = fragColor;\\n\\tgl_FragColor.a *= alpha * opacity * dash;\\n}\\n\",attributes:{lineEnd:{buffer:r,divisor:0,stride:8,offset:0},lineTop:{buffer:r,divisor:0,stride:8,offset:4},aCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:8,divisor:1},bCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:16,divisor:1},aCoordFract:{buffer:t.prop(\"positionFractBuffer\"),stride:8,offset:8,divisor:1},bCoordFract:{buffer:t.prop(\"positionFractBuffer\"),stride:8,offset:16,divisor:1},color:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:0,divisor:1}}},n));try{e=t(a({cull:{enable:!0,face:\"back\"},vert:\"\\nprecision highp float;\\n\\nattribute vec2 aCoord, bCoord, nextCoord, prevCoord;\\nattribute vec4 aColor, bColor;\\nattribute float lineEnd, lineTop;\\n\\nuniform vec2 scale, translate;\\nuniform float thickness, pixelRatio, id, depth;\\nuniform vec4 viewport;\\nuniform float miterLimit, miterMode;\\n\\nvarying vec4 fragColor;\\nvarying vec4 startCutoff, endCutoff;\\nvarying vec2 tangent;\\nvarying vec2 startCoord, endCoord;\\nvarying float enableStartMiter, enableEndMiter;\\n\\nconst float REVERSE_THRESHOLD = -.875;\\nconst float MIN_DIFF = 1e-6;\\n\\n// TODO: possible optimizations: avoid overcalculating all for vertices and calc just one instead\\n// TODO: precalculate dot products, normalize things beforehead etc.\\n// TODO: refactor to rectangular algorithm\\n\\nfloat distToLine(vec2 p, vec2 a, vec2 b) {\\n\\tvec2 diff = b - a;\\n\\tvec2 perp = normalize(vec2(-diff.y, diff.x));\\n\\treturn dot(p - a, perp);\\n}\\n\\nbool isNaN( float val ){\\n  return ( val < 0.0 || 0.0 < val || val == 0.0 ) ? false : true;\\n}\\n\\nvoid main() {\\n\\tvec2 aCoord = aCoord, bCoord = bCoord, prevCoord = prevCoord, nextCoord = nextCoord;\\n\\n  vec2 adjustedScale;\\n  adjustedScale.x = (abs(scale.x) < MIN_DIFF) ? MIN_DIFF : scale.x;\\n  adjustedScale.y = (abs(scale.y) < MIN_DIFF) ? MIN_DIFF : scale.y;\\n\\n  vec2 scaleRatio = adjustedScale * viewport.zw;\\n\\tvec2 normalWidth = thickness / scaleRatio;\\n\\n\\tfloat lineStart = 1. - lineEnd;\\n\\tfloat lineBot = 1. - lineTop;\\n\\n\\tfragColor = (lineStart * aColor + lineEnd * bColor) / 255.;\\n\\n\\tif (isNaN(aCoord.x) || isNaN(aCoord.y) || isNaN(bCoord.x) || isNaN(bCoord.y)) return;\\n\\n\\tif (aCoord == prevCoord) prevCoord = aCoord + normalize(bCoord - aCoord);\\n\\tif (bCoord == nextCoord) nextCoord = bCoord - normalize(bCoord - aCoord);\\n\\n\\n\\tvec2 prevDiff = aCoord - prevCoord;\\n\\tvec2 currDiff = bCoord - aCoord;\\n\\tvec2 nextDiff = nextCoord - bCoord;\\n\\n\\tvec2 prevTangent = normalize(prevDiff * scaleRatio);\\n\\tvec2 currTangent = normalize(currDiff * scaleRatio);\\n\\tvec2 nextTangent = normalize(nextDiff * scaleRatio);\\n\\n\\tvec2 prevNormal = vec2(-prevTangent.y, prevTangent.x);\\n\\tvec2 currNormal = vec2(-currTangent.y, currTangent.x);\\n\\tvec2 nextNormal = vec2(-nextTangent.y, nextTangent.x);\\n\\n\\tvec2 startJoinDirection = normalize(prevTangent - currTangent);\\n\\tvec2 endJoinDirection = normalize(currTangent - nextTangent);\\n\\n\\t// collapsed/unidirectional segment cases\\n\\t// FIXME: there should be more elegant solution\\n\\tvec2 prevTanDiff = abs(prevTangent - currTangent);\\n\\tvec2 nextTanDiff = abs(nextTangent - currTangent);\\n\\tif (max(prevTanDiff.x, prevTanDiff.y) < MIN_DIFF) {\\n\\t\\tstartJoinDirection = currNormal;\\n\\t}\\n\\tif (max(nextTanDiff.x, nextTanDiff.y) < MIN_DIFF) {\\n\\t\\tendJoinDirection = currNormal;\\n\\t}\\n\\tif (aCoord == bCoord) {\\n\\t\\tendJoinDirection = startJoinDirection;\\n\\t\\tcurrNormal = prevNormal;\\n\\t\\tcurrTangent = prevTangent;\\n\\t}\\n\\n\\ttangent = currTangent;\\n\\n\\t//calculate join shifts relative to normals\\n\\tfloat startJoinShift = dot(currNormal, startJoinDirection);\\n\\tfloat endJoinShift = dot(currNormal, endJoinDirection);\\n\\n\\tfloat startMiterRatio = abs(1. / startJoinShift);\\n\\tfloat endMiterRatio = abs(1. / endJoinShift);\\n\\n\\tvec2 startJoin = startJoinDirection * startMiterRatio;\\n\\tvec2 endJoin = endJoinDirection * endMiterRatio;\\n\\n\\tvec2 startTopJoin, startBotJoin, endTopJoin, endBotJoin;\\n\\tstartTopJoin = sign(startJoinShift) * startJoin * .5;\\n\\tstartBotJoin = -startTopJoin;\\n\\n\\tendTopJoin = sign(endJoinShift) * endJoin * .5;\\n\\tendBotJoin = -endTopJoin;\\n\\n\\tvec2 aTopCoord = aCoord + normalWidth * startTopJoin;\\n\\tvec2 bTopCoord = bCoord + normalWidth * endTopJoin;\\n\\tvec2 aBotCoord = aCoord + normalWidth * startBotJoin;\\n\\tvec2 bBotCoord = bCoord + normalWidth * endBotJoin;\\n\\n\\t//miter anti-clipping\\n\\tfloat baClipping = distToLine(bCoord, aCoord, aBotCoord) / dot(normalize(normalWidth * endBotJoin), normalize(normalWidth.yx * vec2(-startBotJoin.y, startBotJoin.x)));\\n\\tfloat abClipping = distToLine(aCoord, bCoord, bTopCoord) / dot(normalize(normalWidth * startBotJoin), normalize(normalWidth.yx * vec2(-endBotJoin.y, endBotJoin.x)));\\n\\n\\t//prevent close to reverse direction switch\\n\\tbool prevReverse = dot(currTangent, prevTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, prevNormal)) * min(length(prevDiff), length(currDiff)) <  length(normalWidth * currNormal);\\n\\tbool nextReverse = dot(currTangent, nextTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, nextNormal)) * min(length(nextDiff), length(currDiff)) <  length(normalWidth * currNormal);\\n\\n\\tif (prevReverse) {\\n\\t\\t//make join rectangular\\n\\t\\tvec2 miterShift = normalWidth * startJoinDirection * miterLimit * .5;\\n\\t\\tfloat normalAdjust = 1. - min(miterLimit / startMiterRatio, 1.);\\n\\t\\taBotCoord = aCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\\n\\t\\taTopCoord = aCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\\n\\t}\\n\\telse if (!nextReverse && baClipping > 0. && baClipping < length(normalWidth * endBotJoin)) {\\n\\t\\t//handle miter clipping\\n\\t\\tbTopCoord -= normalWidth * endTopJoin;\\n\\t\\tbTopCoord += normalize(endTopJoin * normalWidth) * baClipping;\\n\\t}\\n\\n\\tif (nextReverse) {\\n\\t\\t//make join rectangular\\n\\t\\tvec2 miterShift = normalWidth * endJoinDirection * miterLimit * .5;\\n\\t\\tfloat normalAdjust = 1. - min(miterLimit / endMiterRatio, 1.);\\n\\t\\tbBotCoord = bCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\\n\\t\\tbTopCoord = bCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\\n\\t}\\n\\telse if (!prevReverse && abClipping > 0. && abClipping < length(normalWidth * startBotJoin)) {\\n\\t\\t//handle miter clipping\\n\\t\\taBotCoord -= normalWidth * startBotJoin;\\n\\t\\taBotCoord += normalize(startBotJoin * normalWidth) * abClipping;\\n\\t}\\n\\n\\tvec2 aTopPosition = (aTopCoord) * adjustedScale + translate;\\n\\tvec2 aBotPosition = (aBotCoord) * adjustedScale + translate;\\n\\n\\tvec2 bTopPosition = (bTopCoord) * adjustedScale + translate;\\n\\tvec2 bBotPosition = (bBotCoord) * adjustedScale + translate;\\n\\n\\t//position is normalized 0..1 coord on the screen\\n\\tvec2 position = (aTopPosition * lineTop + aBotPosition * lineBot) * lineStart + (bTopPosition * lineTop + bBotPosition * lineBot) * lineEnd;\\n\\n\\tstartCoord = aCoord * scaleRatio + translate * viewport.zw + viewport.xy;\\n\\tendCoord = bCoord * scaleRatio + translate * viewport.zw + viewport.xy;\\n\\n\\tgl_Position = vec4(position  * 2.0 - 1.0, depth, 1);\\n\\n\\tenableStartMiter = step(dot(currTangent, prevTangent), .5);\\n\\tenableEndMiter = step(dot(currTangent, nextTangent), .5);\\n\\n\\t//bevel miter cutoffs\\n\\tif (miterMode == 1.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * miterLimit * .5;\\n\\t\\t\\tstartCutoff = vec4(aCoord, aCoord);\\n\\t\\t\\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\\n\\t\\t\\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tstartCutoff += viewport.xyxy;\\n\\t\\t\\tstartCutoff += startMiterWidth.xyxy;\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * miterLimit * .5;\\n\\t\\t\\tendCutoff = vec4(bCoord, bCoord);\\n\\t\\t\\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x)  / scaleRatio;\\n\\t\\t\\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tendCutoff += viewport.xyxy;\\n\\t\\t\\tendCutoff += endMiterWidth.xyxy;\\n\\t\\t}\\n\\t}\\n\\n\\t//round miter cutoffs\\n\\telse if (miterMode == 2.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * abs(dot(startJoinDirection, currNormal)) * .5;\\n\\t\\t\\tstartCutoff = vec4(aCoord, aCoord);\\n\\t\\t\\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\\n\\t\\t\\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tstartCutoff += viewport.xyxy;\\n\\t\\t\\tstartCutoff += startMiterWidth.xyxy;\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * abs(dot(endJoinDirection, currNormal)) * .5;\\n\\t\\t\\tendCutoff = vec4(bCoord, bCoord);\\n\\t\\t\\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x)  / scaleRatio;\\n\\t\\t\\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tendCutoff += viewport.xyxy;\\n\\t\\t\\tendCutoff += endMiterWidth.xyxy;\\n\\t\\t}\\n\\t}\\n}\\n\",frag:\"\\nprecision highp float;\\n\\nuniform float dashLength, pixelRatio, thickness, opacity, id, miterMode;\\nuniform sampler2D dashTexture;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\nvarying vec4 startCutoff, endCutoff;\\nvarying vec2 startCoord, endCoord;\\nvarying float enableStartMiter, enableEndMiter;\\n\\nfloat distToLine(vec2 p, vec2 a, vec2 b) {\\n\\tvec2 diff = b - a;\\n\\tvec2 perp = normalize(vec2(-diff.y, diff.x));\\n\\treturn dot(p - a, perp);\\n}\\n\\nvoid main() {\\n\\tfloat alpha = 1., distToStart, distToEnd;\\n\\tfloat cutoff = thickness * .5;\\n\\n\\t//bevel miter\\n\\tif (miterMode == 1.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\\n\\t\\t\\tif (distToStart < -1.) {\\n\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\treturn;\\n\\t\\t\\t}\\n\\t\\t\\talpha *= min(max(distToStart + 1., 0.), 1.);\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\\n\\t\\t\\tif (distToEnd < -1.) {\\n\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\treturn;\\n\\t\\t\\t}\\n\\t\\t\\talpha *= min(max(distToEnd + 1., 0.), 1.);\\n\\t\\t}\\n\\t}\\n\\n\\t// round miter\\n\\telse if (miterMode == 2.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\\n\\t\\t\\tif (distToStart < 0.) {\\n\\t\\t\\t\\tfloat radius = length(gl_FragCoord.xy - startCoord);\\n\\n\\t\\t\\t\\tif(radius > cutoff + .5) {\\n\\t\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\t\\treturn;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\\n\\t\\t\\tif (distToEnd < 0.) {\\n\\t\\t\\t\\tfloat radius = length(gl_FragCoord.xy - endCoord);\\n\\n\\t\\t\\t\\tif(radius > cutoff + .5) {\\n\\t\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\t\\treturn;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\\n\\n\\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashLength) * .5 + .25;\\n\\tfloat dash = texture2D(dashTexture, vec2(t, .5)).r;\\n\\n\\tgl_FragColor = fragColor;\\n\\tgl_FragColor.a *= alpha * opacity * dash;\\n}\\n\",attributes:{lineEnd:{buffer:r,divisor:0,stride:8,offset:0},lineTop:{buffer:r,divisor:0,stride:8,offset:4},aColor:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:0,divisor:1},bColor:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:4,divisor:1},prevCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:0,divisor:1},aCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:8,divisor:1},bCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:16,divisor:1},nextCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:24,divisor:1}}},n))}catch(t){e=i}return{fill:t({primitive:\"triangle\",elements:function(t,e){return e.triangles},offset:0,vert:\"\\nprecision highp float;\\n\\nattribute vec2 position, positionFract;\\n\\nuniform vec4 color;\\nuniform vec2 scale, scaleFract, translate, translateFract;\\nuniform float pixelRatio, id;\\nuniform vec4 viewport;\\nuniform float opacity;\\n\\nvarying vec4 fragColor;\\n\\nconst float MAX_LINES = 256.;\\n\\nvoid main() {\\n\\tfloat 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at=0;at<t.dashes.length;++at){for(var ot=0,st=t.dashes[at]*g.dashMult*.5;ot<st;++ot)Q[rt++]=nt;nt^=255}}y.dashLength=tt,y.dashTexture({channels:1,data:Q,width:Q.length,height:1,mag:\"linear\",min:\"linear\"},0,0)}if(t.color){var lt=y.count,ut=t.color;ut||(ut=\"transparent\");var ct=new Uint8Array(4*lt+4);if(Array.isArray(ut)&&\"number\"!=typeof ut[0]){for(var ft=0;ft<lt;ft++){var ht=n(ut[ft],\"uint8\");ct.set(ht,4*ft)}ct.set(n(ut[0],\"uint8\"),4*lt)}else for(var pt=n(ut,\"uint8\"),dt=0;dt<lt+1;dt++)ct.set(pt,4*dt);y.colorBuffer({usage:\"dynamic\",type:\"uint8\",data:ct})}}else e.passes[p]=null})),t.length<this.passes.length){for(var p=t.length;p<this.passes.length;p++){var y=this.passes[p];y&&(y.colorBuffer.destroy(),y.positionBuffer.destroy(),y.dashTexture.destroy())}this.passes.length=t.length}for(var m=[],x=0;x<this.passes.length;x++)null!==this.passes[x]&&m.push(this.passes[x]);return this.passes=m,this}},g.prototype.destroy=function(){return 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Uint8Array(1020),width:255,height:1,type:\"uint8\",format:\"rgba\",wrapS:\"clamp\",wrapT:\"clamp\",mag:\"nearest\",min:\"nearest\"}),c(this,{regl:t,gl:i,groups:[],markerCache:[null],markerTextures:[null],palette:a,paletteIds:{},paletteTexture:n,maxColors:255,maxSize:100,canvas:i.canvas}),this.update(e);var o={uniforms:{constPointSize:!!e.constPointSize,opacity:t.prop(\"opacity\"),paletteSize:function(t,e){return[r.tooManyColors?0:255,n.height]},pixelRatio:t.context(\"pixelRatio\"),scale:t.prop(\"scale\"),scaleFract:t.prop(\"scaleFract\"),translate:t.prop(\"translate\"),translateFract:t.prop(\"translateFract\"),markerTexture:t.prop(\"markerTexture\"),paletteTexture:n},attributes:{x:function(t,e){return e.xAttr||{buffer:e.positionBuffer,stride:8,offset:0}},y:function(t,e){return e.yAttr||{buffer:e.positionBuffer,stride:8,offset:4}},xFract:function(t,e){return e.xAttr?{constant:[0,0]}:{buffer:e.positionFractBuffer,stride:8,offset:0}},yFract:function(t,e){return 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vec2 pos = (position + translate) * scale\\n      + (positionFract + translateFract) * scale\\n      + (position + translate) * scaleFract\\n      + (positionFract + translateFract) * scaleFract;\\n\\n  gl_Position = vec4(pos * 2. - 1., 0., 1.);\\n\\n  fragColor = color;\\n  fragBorderColor = borderColor;\\n  fragWidth = 1. / gl_PointSize;\\n\\n  fragBorderColorLevel = clamp(borderLevel - borderLevel * borderSize / size, 0., 1.);\\n  fragColorLevel = clamp(borderLevel + (1. - borderLevel) * borderSize / size, 0., 1.);\\n}\\n\"]),this.drawMarker=t(s);var l=c({},o);l.frag=f([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor, fragBorderColor;\\nvarying float fragBorderRadius, fragWidth;\\n\\nuniform float opacity;\\n\\nfloat smoothStep(float edge0, float edge1, float x) {\\n\\tfloat t;\\n\\tt = clamp((x - edge0) / (edge1 - edge0), 0.0, 1.0);\\n\\treturn t * t * (3.0 - 2.0 * t);\\n}\\n\\nvoid main() {\\n\\tfloat radius, alpha = 1.0, delta = fragWidth;\\n\\n\\tradius 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paletteSize, scale, scaleFract, translate, translateFract;\\nuniform sampler2D paletteTexture;\\n\\nconst float maxSize = 100.;\\n\\nvarying vec4 fragColor, fragBorderColor;\\nvarying float fragBorderRadius, fragWidth;\\n\\nfloat pointSizeScale = (constPointSize) ? 2. : pixelRatio;\\n\\nbool isDirect = (paletteSize.x < 1.);\\n\\nvec4 getColor(vec4 id) {\\n  return isDirect ? id / 255. : texture2D(paletteTexture,\\n    vec2(\\n      (id.x + .5) / paletteSize.x,\\n      (id.y + .5) / paletteSize.y\\n    )\\n  );\\n}\\n\\nvoid main() {\\n  // ignore inactive points\\n  if (isActive == 0.) return;\\n\\n  vec2 position = vec2(x, y);\\n  vec2 positionFract = vec2(xFract, yFract);\\n\\n  vec4 color = getColor(colorId);\\n  vec4 borderColor = getColor(borderColorId);\\n\\n  float size = size * maxSize / 255.;\\n  float borderSize = borderSize * maxSize / 255.;\\n\\n  gl_PointSize = (size + borderSize) * pointSizeScale;\\n\\n  vec2 pos = (position + translate) * scale\\n      + (positionFract + translateFract) * scale\\n      + (position + translate) * scaleFract\\n      + (positionFract + translateFract) * scaleFract;\\n\\n  gl_Position = vec4(pos * 2. - 1., 0., 1.);\\n\\n  fragBorderRadius = 1. - 2. * borderSize / (size + borderSize);\\n  fragColor = color;\\n  fragBorderColor = borderColor.a == 0. || borderSize == 0. ? vec4(color.rgb, 0.) : borderColor;\\n  fragWidth = 1. / gl_PointSize;\\n}\\n\"]),v&&(l.frag=l.frag.replace(\"smoothstep\",\"smoothStep\"),s.frag=s.frag.replace(\"smoothstep\",\"smoothStep\")),this.drawCircle=t(l)}x.defaults={color:\"black\",borderColor:\"transparent\",borderSize:0,size:12,opacity:1,marker:void 0,viewport:null,range:null,pixelSize:null,count:0,offset:0,bounds:null,positions:[],snap:1e4},x.prototype.render=function(){return arguments.length&&this.update.apply(this,arguments),this.draw(),this},x.prototype.draw=function(){for(var t=this,e=arguments.length,r=new Array(e),n=0;n<e;n++)r[n]=arguments[n];var i=this.groups;if(1===r.length&&Array.isArray(r[0])&&(null===r[0][0]||Array.isArray(r[0][0]))&&(r=r[0]),this.regl._refresh(),r.length)for(var a=0;a<r.length;a++)this.drawItem(a,r[a]);else i.forEach((function(e,r){t.drawItem(r)}));return this},x.prototype.drawItem=function(t,e){var r,n=this.groups,o=n[t];if(\"number\"==typeof e&&(t=e,o=n[e],e=null),o&&o.count&&o.opacity){o.activation[0]&&this.drawCircle(this.getMarkerDrawOptions(0,o,e));for(var s=[],l=1;l<o.activation.length;l++)o.activation[l]&&(!0===o.activation[l]||o.activation[l].data.length)&&s.push.apply(s,function(t){if(Array.isArray(t))return a(t)}(r=this.getMarkerDrawOptions(l,o,e))||function(t){if(\"undefined\"!=typeof Symbol&&null!=t[Symbol.iterator]||null!=t[\"@@iterator\"])return Array.from(t)}(r)||i(r)||function(){throw new TypeError(\"Invalid attempt to spread non-iterable instance.\\nIn order to be iterable, non-array objects must have a [Symbol.iterator]() method.\")}());s.length&&this.drawMarker(s)}},x.prototype.getMarkerDrawOptions=function(t,e,r){var i=e.range,a=e.tree,o=e.viewport,s=e.activation,l=e.selectionBuffer,u=e.count;if(this.regl,!a)return r?[c({},e,{markerTexture:this.markerTextures[t],activation:s[t],count:r.length,elements:r,offset:0})]:[c({},e,{markerTexture:this.markerTextures[t],activation:s[t],offset:0})];var f=[],h=a.range(i,{lod:!0,px:[(i[2]-i[0])/o.width,(i[3]-i[1])/o.height]});if(r){for(var p=s[t].data,d=new Uint8Array(u),v=0;v<r.length;v++){var g=r[v];d[g]=p?p[g]:1}l.subdata(d)}for(var y=h.length;y--;){var m=n(h[y],2),x=m[0],b=m[1];f.push(c({},e,{markerTexture:this.markerTextures[t],activation:r?l:s[t],offset:x,count:b-x}))}return f},x.prototype.update=function(){for(var t=this,e=arguments.length,r=new Array(e),n=0;n<e;n++)r[n]=arguments[n];if(r.length){1===r.length&&Array.isArray(r[0])&&(r=r[0]);var i=this.groups,a=this.gl,o=this.regl,l=this.maxSize,f=this.maxColors,v=this.palette;this.groups=i=r.map((function(e,r){var n=i[r];if(void 0===e)return n;null===e?e={positions:null}:\"function\"==typeof e?e={ondraw:e}:\"number\"==typeof e[0]&&(e={positions:e}),null===(e=h(e,{positions:\"positions data points\",snap:\"snap cluster lod tree\",size:\"sizes size radius\",borderSize:\"borderSizes borderSize border-size bordersize borderWidth borderWidths border-width borderwidth stroke-width strokeWidth strokewidth outline\",color:\"colors color fill fill-color fillColor\",borderColor:\"borderColors borderColor stroke stroke-color strokeColor\",marker:\"markers marker shape\",range:\"range dataBox databox\",viewport:\"viewport viewPort viewBox viewbox\",opacity:\"opacity alpha transparency\",bounds:\"bound bounds boundaries limits\",tooManyColors:\"tooManyColors palette paletteMode optimizePalette enablePalette\"})).positions&&(e.positions=[]),null!=e.tooManyColors&&(t.tooManyColors=e.tooManyColors),n||(i[r]=n={id:r,scale:null,translate:null,scaleFract:null,translateFract:null,activation:[],selectionBuffer:o.buffer({data:new Uint8Array(0),usage:\"stream\",type:\"uint8\"}),sizeBuffer:o.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"uint8\"}),colorBuffer:o.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"uint8\"}),positionBuffer:o.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"float\"}),positionFractBuffer:o.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"float\"})},e=c({},x.defaults,e)),e.positions&&!(\"marker\"in e)&&(e.marker=n.marker,delete n.marker),e.marker&&!(\"positions\"in e)&&(e.positions=n.positions,delete n.positions);var m=0,b=0;if(p(n,e,[{snap:!0,size:function(t,e){return null==t&&(t=x.defaults.size),m+=t&&t.length?1:0,t},borderSize:function(t,e){return null==t&&(t=x.defaults.borderSize),m+=t&&t.length?1:0,t},opacity:parseFloat,color:function(e,r){return null==e&&(e=x.defaults.color),e=t.updateColor(e),b++,e},borderColor:function(e,r){return null==e&&(e=x.defaults.borderColor),e=t.updateColor(e),b++,e},bounds:function(t,e,r){return\"range\"in r||(r.range=null),t},positions:function(t,e,r){var n=e.snap,i=e.positionBuffer,a=e.positionFractBuffer,l=e.selectionBuffer;if(t.x||t.y)return t.x.length?e.xAttr={buffer:o.buffer(t.x),offset:0,stride:4,count:t.x.length}:e.xAttr={buffer:t.x.buffer,offset:4*t.x.offset||0,stride:4*(t.x.stride||1),count:t.x.count},t.y.length?e.yAttr={buffer:o.buffer(t.y),offset:0,stride:4,count:t.y.length}:e.yAttr={buffer:t.y.buffer,offset:4*t.y.offset||0,stride:4*(t.y.stride||1),count:t.y.count},e.count=Math.max(e.xAttr.count,e.yAttr.count),t;t=d(t,\"float64\");var c=e.count=Math.floor(t.length/2),f=e.bounds=c?s(t,2):null;if(r.range||e.range||(delete e.range,r.range=f),r.marker||e.marker||(delete e.marker,r.marker=null),n&&(!0===n||c>n)?e.tree=u(t,{bounds:f}):n&&n.length&&(e.tree=n),e.tree){var h={primitive:\"points\",usage:\"static\",data:e.tree,type:\"uint32\"};e.elements?e.elements(h):e.elements=o.elements(h)}var p=g.float32(t);return i({data:p,usage:\"dynamic\"}),a({data:g.fract32(t,p),usage:\"dynamic\"}),l({data:new Uint8Array(c),type:\"uint8\",usage:\"stream\"}),t}},{marker:function(e,r,n){var i=r.activation;if(i.forEach((function(t){return t&&t.destroy&&t.destroy()})),i.length=0,e&&\"number\"!=typeof e[0]){for(var a=[],s=0,l=Math.min(e.length,r.count);s<l;s++){var u=t.addMarker(e[s]);a[u]||(a[u]=new Uint8Array(r.count)),a[u][s]=1}for(var c=0;c<a.length;c++)if(a[c]){var f={data:a[c],type:\"uint8\",usage:\"static\"};i[c]?i[c](f):i[c]=o.buffer(f),i[c].data=a[c]}}else i[t.addMarker(e)]=!0;return e},range:function(t,e,r){var n=e.bounds;if(n)return t||(t=n),e.scale=[1/(t[2]-t[0]),1/(t[3]-t[1])],e.translate=[-t[0],-t[1]],e.scaleFract=g.fract(e.scale),e.translateFract=g.fract(e.translate),t},viewport:function(t){return y(t||[a.drawingBufferWidth,a.drawingBufferHeight])}}]),m){var _=n,w=_.count,T=_.size,k=_.borderSize,A=_.sizeBuffer,M=new Uint8Array(2*w);if(T.length||k.length)for(var S=0;S<w;S++)M[2*S]=Math.round(255*(null==T[S]?T:T[S])/l),M[2*S+1]=Math.round(255*(null==k[S]?k:k[S])/l);A({data:M,usage:\"dynamic\"})}if(b){var E,L=n,C=L.count,P=L.color,O=L.borderColor,I=L.colorBuffer;if(t.tooManyColors){if(P.length||O.length){E=new Uint8Array(8*C);for(var D=0;D<C;D++){var z=P[D];E[8*D]=v[4*z],E[8*D+1]=v[4*z+1],E[8*D+2]=v[4*z+2],E[8*D+3]=v[4*z+3];var R=O[D];E[8*D+4]=v[4*R],E[8*D+5]=v[4*R+1],E[8*D+6]=v[4*R+2],E[8*D+7]=v[4*R+3]}}}else if(P.length||O.length){E=new Uint8Array(4*C+2);for(var F=0;F<C;F++)null!=P[F]&&(E[4*F]=P[F]%f,E[4*F+1]=Math.floor(P[F]/f)),null!=O[F]&&(E[4*F+2]=O[F]%f,E[4*F+3]=Math.floor(O[F]/f))}I({data:E||new Uint8Array(0),type:\"uint8\",usage:\"dynamic\"})}return n}))}},x.prototype.addMarker=function(t){var e,r=this.markerTextures,n=this.regl,i=this.markerCache,a=null==t?0:i.indexOf(t);if(a>=0)return a;if(t instanceof Uint8Array||t instanceof Uint8ClampedArray)e=t;else{e=new Uint8Array(t.length);for(var o=0,s=t.length;o<s;o++)e[o]=255*t[o]}var l=Math.floor(Math.sqrt(e.length));return a=r.length,i.push(t),r.push(n.texture({channels:1,data:e,radius:l,mag:\"linear\",min:\"linear\"})),a},x.prototype.updateColor=function(t){var e=this.paletteIds,r=this.palette,n=this.maxColors;Array.isArray(t)||(t=[t]);var i=[];if(\"number\"==typeof t[0]){var a=[];if(Array.isArray(t))for(var s=0;s<t.length;s+=4)a.push(t.slice(s,s+4));else for(var u=0;u<t.length;u+=4)a.push(t.subarray(u,u+4));t=a}for(var c=0;c<t.length;c++){var f=t[c];f=o(f,\"uint8\");var h=l(f,!1);if(null==e[h]){var p=r.length;e[h]=Math.floor(p/4),r[p]=f[0],r[p+1]=f[1],r[p+2]=f[2],r[p+3]=f[3]}i[c]=e[h]}return!this.tooManyColors&&r.length>4*n&&(this.tooManyColors=!0),this.updatePalette(r),1===i.length?i[0]:i},x.prototype.updatePalette=function(t){if(!this.tooManyColors){var e=this.maxColors,r=this.paletteTexture,n=Math.ceil(.25*t.length/e);if(n>1)for(var i=.25*(t=t.slice()).length%e;i<n*e;i++)t.push(0,0,0,0);r.height<n&&r.resize(e,n),r.subimage({width:Math.min(.25*t.length,e),height:n,data:t},0,0)}},x.prototype.destroy=function(){return this.groups.forEach((function(t){t.sizeBuffer.destroy(),t.positionBuffer.destroy(),t.positionFractBuffer.destroy(),t.colorBuffer.destroy(),t.activation.forEach((function(t){return t&&t.destroy&&t.destroy()})),t.selectionBuffer.destroy(),t.elements&&t.elements.destroy()})),this.groups.length=0,this.paletteTexture.destroy(),this.markerTextures.forEach((function(t){return t&&t.destroy&&t.destroy()})),this};var b=r(50896);t.exports=function(t,e){var r=new m(t,e),n=r.render.bind(r);return b(n,{render:n,update:r.update.bind(r),draw:r.draw.bind(r),destroy:r.destroy.bind(r),regl:r.regl,gl:r.gl,canvas:r.gl.canvas,groups:r.groups,markers:r.markerCache,palette:r.palette}),n}},55795:function(t,e,r){\"use strict\";var n=r(38540),i=r(55616),a=r(76752),o=r(3951),s=r(67752),l=r(51160),u=r(47520);function c(t,e){if(!(this instanceof c))return new c(t,e);this.traces=[],this.passes={},this.regl=t,this.scatter=n(t),this.canvas=this.scatter.canvas}function f(t,e,r){return(null!=t.id?t.id:t)<<16|(255&e)<<8|255&r}function h(t,e,r){var n,i,a,o,s=t[e],l=t[r];return s.length>2?(s[0],s[2],n=s[1],i=s[3]):s.length?(n=s[0],i=s[1]):(s.x,n=s.y,s.x,s.width,i=s.y+s.height),l.length>2?(a=l[0],o=l[2],l[1],l[3]):l.length?(a=l[0],o=l[1]):(a=l.x,l.y,o=l.x+l.width,l.y,l.height),[a,n,o,i]}function p(t){if(\"number\"==typeof t)return[t,t,t,t];if(2===t.length)return[t[0],t[1],t[0],t[1]];var e=l(t);return[e.x,e.y,e.x+e.width,e.y+e.height]}t.exports=c,c.prototype.render=function(){for(var t,e=this,r=[],n=arguments.length;n--;)r[n]=arguments[n];return r.length&&(t=this).update.apply(t,r),this.regl.attributes.preserveDrawingBuffer?this.draw():(this.dirty?null==this.planned&&(this.planned=o((function(){e.draw(),e.dirty=!0,e.planned=null}))):(this.draw(),this.dirty=!0,o((function(){e.dirty=!1}))),this)},c.prototype.update=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];if(e.length){for(var n=0;n<e.length;n++)this.updateItem(n,e[n]);this.traces=this.traces.filter(Boolean);for(var i=[],a=0,o=0;o<this.traces.length;o++){for(var s=this.traces[o],l=this.traces[o].passes,u=0;u<l.length;u++)i.push(this.passes[l[u]]);s.passOffset=a,a+=s.passes.length}return(t=this.scatter).update.apply(t,i),this}},c.prototype.updateItem=function(t,e){var r=this.regl;if(null===e)return this.traces[t]=null,this;if(!e)return this;var n,o=i(e,{data:\"data items columns rows values 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Uint8Array}),color:\"black\",marker:null,size:12,borderColor:\"transparent\",borderSize:1,viewport:l([r._gl.drawingBufferWidth,r._gl.drawingBufferHeight]),padding:[0,0,0,0],opacity:1,diagonal:!0,upper:!0,lower:!0});if(null!=o.color&&(s.color=o.color),null!=o.size&&(s.size=o.size),null!=o.marker&&(s.marker=o.marker),null!=o.borderColor&&(s.borderColor=o.borderColor),null!=o.borderSize&&(s.borderSize=o.borderSize),null!=o.opacity&&(s.opacity=o.opacity),o.viewport&&(s.viewport=l(o.viewport)),null!=o.diagonal&&(s.diagonal=o.diagonal),null!=o.upper&&(s.upper=o.upper),null!=o.lower&&(s.lower=o.lower),o.data){s.buffer(u(o.data)),s.columns=o.data.length,s.count=o.data[0].length,s.bounds=[];for(var c=0;c<s.columns;c++)s.bounds[c]=a(o.data[c],1)}o.range&&(s.range=o.range,n=s.range&&\"number\"!=typeof s.range[0]),o.domain&&(s.domain=o.domain);var d=!1;null!=o.padding&&(Array.isArray(o.padding)&&o.padding.length===s.columns&&\"number\"==typeof o.padding[o.padding.length-1]?(s.padding=o.padding.map(p),d=!0):s.padding=p(o.padding));var v=s.columns,g=s.count,y=s.viewport.width,m=s.viewport.height,x=s.viewport.x,b=s.viewport.y,_=y/v,w=m/v;s.passes=[];for(var T=0;T<v;T++)for(var k=0;k<v;k++)if((s.diagonal||k!==T)&&(s.upper||!(T>k))&&(s.lower||!(T<k))){var A=f(s.id,T,k),M=this.passes[A]||(this.passes[A]={});if(o.data&&(o.transpose?M.positions={x:{buffer:s.buffer,offset:k,count:g,stride:v},y:{buffer:s.buffer,offset:T,count:g,stride:v}}:M.positions={x:{buffer:s.buffer,offset:k*g,count:g},y:{buffer:s.buffer,offset:T*g,count:g}},M.bounds=h(s.bounds,T,k)),o.domain||o.viewport||o.data){var S=d?h(s.padding,T,k):s.padding;if(s.domain){var E=h(s.domain,T,k),L=E[0],C=E[1],P=E[2],O=E[3];M.viewport=[x+L*y+S[0],b+C*m+S[1],x+P*y-S[2],b+O*m-S[3]]}else M.viewport=[x+k*_+_*S[0],b+T*w+w*S[1],x+(k+1)*_-_*S[2],b+(T+1)*w-w*S[3]]}o.color&&(M.color=s.color),o.size&&(M.size=s.size),o.marker&&(M.marker=s.marker),o.borderSize&&(M.borderSize=s.borderSize),o.borderColor&&(M.borderColor=s.borderColor),o.opacity&&(M.opacity=s.opacity),o.range&&(M.range=n?h(s.range,T,k):s.range||M.bounds),s.passes.push(A)}return this},c.prototype.draw=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];if(e.length){for(var n=[],i=0;i<e.length;i++)if(\"number\"==typeof e[i]){var a=this.traces[e[i]],o=a.passes,l=a.passOffset;n.push.apply(n,s(l,l+o.length))}else if(e[i].length){var u=e[i],c=this.traces[i],f=c.passes,h=c.passOffset;f=f.map((function(t,e){n[h+e]=u}))}(t=this.scatter).draw.apply(t,n)}else this.scatter.draw();return this},c.prototype.destroy=function(){return this.traces.forEach((function(t){t.buffer&&t.buffer.destroy&&t.buffer.destroy()})),this.traces=null,this.passes=null,this.scatter.destroy(),this}},28624:function(t){t.exports=function(){function t(t,e){this.id=W++,this.type=t,this.data=e}function e(t){if(0===t.length)return[];var r=t.charAt(0),n=t.charAt(t.length-1);if(1<t.length&&r===n&&('\"'===r||\"'\"===r))return['\"'+t.substr(1,t.length-2).replace(/\\\\/g,\"\\\\\\\\\").replace(/\"/g,'\\\\\"')+'\"'];if(r=/\\[(false|true|null|\\d+|'[^']*'|\"[^\"]*\")\\]/.exec(t))return e(t.substr(0,r.index)).concat(e(r[1])).concat(e(t.substr(r.index+r[0].length)));if(1===(r=t.split(\".\")).length)return['\"'+t.replace(/\\\\/g,\"\\\\\\\\\").replace(/\"/g,'\\\\\"')+'\"'];for(t=[],n=0;n<r.length;++n)t=t.concat(e(r[n]));return t}function r(t){return\"[\"+e(t).join(\"][\")+\"]\"}function n(t){return\"string\"==typeof t?t.split():t}function i(t){return\"string\"==typeof t?document.querySelector(t):t}function a(t){var e,r,a,o,s=t||{};t={};var 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e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return(t=e.year()+(e.year()<0?1:0))%4==3||t%4==-1},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear||n.regionalOptions[\"\"].invalidYear),13},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(13===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return(t=i.year())<0&&t++,i.day()+30*(i.month()-1)+365*(t-1)+Math.floor(t/4)+this.jdEpoch-1},fromJD:function(t){var e=Math.floor(t)+.5-this.jdEpoch,r=Math.floor((e-Math.floor((e+366)/1461))/365)+1;r<=0&&r--,e=Math.floor(t)+.5-this.newDate(r,1,1).toJD();var n=Math.floor(e/30)+1,i=e-30*(n-1)+1;return 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this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),13},daysInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),400},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/8)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]},daysInWeek:function(){return 8},dayOfWeek:function(t,e,r){return(this._validate(t,e,r,n.local.invalidDate).day()+1)%8},weekDay:function(t,e,r){var n=this.dayOfWeek(t,e,r);return n>=2&&n<=6},extraInfo:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return{century:o[Math.floor((i.year()-1)/100)+1]||\"\"}},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return t=i.year()+(i.year()<0?1:0),e=i.month(),(r=i.day())+(e>1?16:0)+(e>2?32*(e-2):0)+400*(t-1)+this.jdEpoch-1},fromJD:function(t){t=Math.floor(t+.5)-Math.floor(this.jdEpoch)-1;var e=Math.floor(t/400)+1;t-=400*(e-1),t+=t>15?16:0;var r=Math.floor(t/32)+1,n=t-32*(r-1)+1;return this.newDate(e<=0?e-1:e,r,n)}});var o={20:\"Fruitbat\",21:\"Anchovy\"};n.calendars.discworld=a},65168:function(t,e,r){var n=r(38700),i=r(50896);function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new 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this._validate(t,this.minMonth,this.minDay,n.local.invalidYear||n.regionalOptions[\"\"].invalidYear),13},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(13===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return(t=i.year())<0&&t++,i.day()+30*(i.month()-1)+365*(t-1)+Math.floor(t/4)+this.jdEpoch-1},fromJD:function(t){var e=Math.floor(t)+.5-this.jdEpoch,r=Math.floor((e-Math.floor((e+366)/1461))/365)+1;r<=0&&r--,e=Math.floor(t)+.5-this.newDate(r,1,1).toJD();var n=Math.floor(e/30)+1,i=e-30*(n-1)+1;return this.newDate(r,n,i)}}),n.calendars.ethiopian=a},2084:function(t,e,r){var n=r(38700),i=r(50896);function 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e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return this._leapYear(e.year())},_leapYear:function(t){return o(7*(t=t<0?t+1:t)+1,19)<7},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),this._leapYear(t.year?t.year():t)?13:12},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){return t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year(),this.toJD(-1===t?1:t+1,7,1)-this.toJD(t,7,1)},daysInMonth:function(t,e){return t.year&&(e=t.month(),t=t.year()),this._validate(t,e,this.minDay,n.local.invalidMonth),12===e&&this.leapYear(t)||8===e&&5===o(this.daysInYear(t),10)?30:9===e&&3===o(this.daysInYear(t),10)?29:this.daysPerMonth[e-1]},weekDay:function(t,e,r){return 6!==this.dayOfWeek(t,e,r)},extraInfo:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return{yearType:(this.leapYear(i)?\"embolismic\":\"common\")+\" \"+[\"deficient\",\"regular\",\"complete\"][this.daysInYear(i)%10-3]}},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=i.year(),e=i.month(),r=i.day();var a=t<=0?t+1:t,o=this.jdEpoch+this._delay1(a)+this._delay2(a)+r+1;if(e<7){for(var s=7;s<=this.monthsInYear(t);s++)o+=this.daysInMonth(t,s);for(s=1;s<e;s++)o+=this.daysInMonth(t,s)}else for(s=7;s<e;s++)o+=this.daysInMonth(t,s);return o},_delay1:function(t){var e=Math.floor((235*t-234)/19),r=12084+13753*e,n=29*e+Math.floor(r/25920);return o(3*(n+1),7)<3&&n++,n},_delay2:function(t){var e=this._delay1(t-1),r=this._delay1(t);return this._delay1(t+1)-r==356?2:r-e==382?1:0},fromJD:function(t){t=Math.floor(t)+.5;for(var e=Math.floor(98496*(t-this.jdEpoch)/35975351)-1;t>=this.toJD(-1===e?1:e+1,7,1);)e++;for(var r=t<this.toJD(e,1,1)?7:1;t>this.toJD(e,r,this.daysInMonth(e,r));)r++;var n=t-this.toJD(e,r,1)+1;return 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e=Math.floor((30*(t-this.jdEpoch)+10646)/10631);e=e<=0?e-1:e;var r=Math.min(12,Math.ceil((t-29-this.toJD(e,1,1))/29.5)+1),n=t-this.toJD(e,r,1)+1;return this.newDate(e,r,n)}}),n.calendars.islamic=a},24747:function(t,e,r){var n=r(38700),i=r(50896);function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new 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n.add(4-(n.dayOfWeek()||7),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return t=i.year(),e=i.month(),r=i.day(),t<0&&t++,e<=2&&(t--,e+=12),Math.floor(365.25*(t+4716))+Math.floor(30.6001*(e+1))+r-1524.5},fromJD:function(t){var e=Math.floor(t+.5)+1524,r=Math.floor((e-122.1)/365.25),n=Math.floor(365.25*r),i=Math.floor((e-n)/30.6001),a=i-Math.floor(i<14?1:13),o=r-Math.floor(a>2?4716:4715),s=e-n-Math.floor(30.6001*i);return o<=0&&o--,this.newDate(o,a,s)}}),n.calendars.julian=a},65616:function(t,e,r){var n=r(38700),i=r(50896);function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}function o(t,e){return t-e*Math.floor(t/e)}function s(t,e){return o(t-1,e)+1}a.prototype=new 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this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),!1},formatYear:function(t){t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year();var e=Math.floor(t/400);return t%=400,t+=t<0?400:0,e+\".\"+Math.floor(t/20)+\".\"+t%20},forYear:function(t){if((t=t.split(\".\")).length<3)throw\"Invalid Mayan year\";for(var e=0,r=0;r<t.length;r++){var n=parseInt(t[r],10);if(Math.abs(n)>19||r>0&&n<0)throw\"Invalid Mayan year\";e=20*e+n}return e},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),18},weekOfYear:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate),0},daysInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),360},daysInMonth:function(t,e){return this._validate(t,e,this.minDay,n.local.invalidMonth),20},daysInWeek:function(){return 5},dayOfWeek:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate).day()},weekDay:function(t,e,r){return 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o=n.instance(\"gregorian\");i(a.prototype,{name:\"Nanakshahi\",jdEpoch:2257673.5,daysPerMonth:[31,31,31,31,31,30,30,30,30,30,30,30],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Nanakshahi\",epochs:[\"BN\",\"AN\"],monthNames:[\"Chet\",\"Vaisakh\",\"Jeth\",\"Harh\",\"Sawan\",\"Bhadon\",\"Assu\",\"Katak\",\"Maghar\",\"Poh\",\"Magh\",\"Phagun\"],monthNamesShort:[\"Che\",\"Vai\",\"Jet\",\"Har\",\"Saw\",\"Bha\",\"Ass\",\"Kat\",\"Mgr\",\"Poh\",\"Mgh\",\"Pha\"],dayNames:[\"Somvaar\",\"Mangalvar\",\"Budhvaar\",\"Veervaar\",\"Shukarvaar\",\"Sanicharvaar\",\"Etvaar\"],dayNamesShort:[\"Som\",\"Mangal\",\"Budh\",\"Veer\",\"Shukar\",\"Sanichar\",\"Et\"],dayNamesMin:[\"So\",\"Ma\",\"Bu\",\"Ve\",\"Sh\",\"Sa\",\"Et\"],digits:null,dateFormat:\"dd-mm-yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear||n.regionalOptions[\"\"].invalidYear);return o.leapYear(e.year()+(e.year()<1?1:0)+1469)},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(1-(n.dayOfWeek()||7),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidMonth);(t=i.year())<0&&t++;for(var a=i.day(),s=1;s<i.month();s++)a+=this.daysPerMonth[s-1];return a+o.toJD(t+1468,3,13)},fromJD:function(t){t=Math.floor(t+.5);for(var e=Math.floor((t-(this.jdEpoch-1))/366);t>=this.toJD(e+1,1,1);)e++;for(var r=t-Math.floor(this.toJD(e,1,1)+.5)+1,n=1;r>this.daysInMonth(e,n);)r-=this.daysInMonth(e,n),n++;return this.newDate(e,n,r)}}),n.calendars.nanakshahi=a},73040:function(t,e,r){var n=r(38700),i=r(50896);function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Nepali\",jdEpoch:1700709.5,daysPerMonth:[31,31,32,32,31,30,30,29,30,29,30,30],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,daysPerYear:365,regionalOptions:{\"\":{name:\"Nepali\",epochs:[\"BBS\",\"ABS\"],monthNames:[\"Baisakh\",\"Jestha\",\"Ashadh\",\"Shrawan\",\"Bhadra\",\"Ashwin\",\"Kartik\",\"Mangsir\",\"Paush\",\"Mangh\",\"Falgun\",\"Chaitra\"],monthNamesShort:[\"Bai\",\"Je\",\"As\",\"Shra\",\"Bha\",\"Ash\",\"Kar\",\"Mang\",\"Pau\",\"Ma\",\"Fal\",\"Chai\"],dayNames:[\"Aaitabaar\",\"Sombaar\",\"Manglbaar\",\"Budhabaar\",\"Bihibaar\",\"Shukrabaar\",\"Shanibaar\"],dayNamesShort:[\"Aaita\",\"Som\",\"Mangl\",\"Budha\",\"Bihi\",\"Shukra\",\"Shani\"],dayNamesMin:[\"Aai\",\"So\",\"Man\",\"Bu\",\"Bi\",\"Shu\",\"Sha\"],digits:null,dateFormat:\"dd/mm/yyyy\",firstDay:1,isRTL:!1}},leapYear:function(t){return this.daysInYear(t)!==this.daysPerYear},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){if(t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year(),void 0===this.NEPALI_CALENDAR_DATA[t])return this.daysPerYear;for(var e=0,r=this.minMonth;r<=12;r++)e+=this.NEPALI_CALENDAR_DATA[t][r];return e},daysInMonth:function(t,e){return t.year&&(e=t.month(),t=t.year()),this._validate(t,e,this.minDay,n.local.invalidMonth),void 0===this.NEPALI_CALENDAR_DATA[t]?this.daysPerMonth[e-1]:this.NEPALI_CALENDAR_DATA[t][e]},weekDay:function(t,e,r){return 6!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=i.year(),e=i.month(),r=i.day();var a=n.instance(),o=0,s=e,l=t;this._createMissingCalendarData(t);var u=t-(s>9||9===s&&r>=this.NEPALI_CALENDAR_DATA[l][0]?56:57);for(9!==e&&(o=r,s--);9!==s;)s<=0&&(s=12,l--),o+=this.NEPALI_CALENDAR_DATA[l][s],s--;return 9===e?(o+=r-this.NEPALI_CALENDAR_DATA[l][0])<0&&(o+=a.daysInYear(u)):o+=this.NEPALI_CALENDAR_DATA[l][9]-this.NEPALI_CALENDAR_DATA[l][0],a.newDate(u,1,1).add(o,\"d\").toJD()},fromJD:function(t){var e=n.instance().fromJD(t),r=e.year(),i=e.dayOfYear(),a=r+56;this._createMissingCalendarData(a);for(var o=9,s=this.NEPALI_CALENDAR_DATA[a][0],l=this.NEPALI_CALENDAR_DATA[a][o]-s+1;i>l;)++o>12&&(o=1,a++),l+=this.NEPALI_CALENDAR_DATA[a][o];var u=this.NEPALI_CALENDAR_DATA[a][o]-(l-i);return this.newDate(a,o,u)},_createMissingCalendarData:function(t){var e=this.daysPerMonth.slice(0);e.unshift(17);for(var r=t-1;r<t+2;r++)void 0===this.NEPALI_CALENDAR_DATA[r]&&(this.NEPALI_CALENDAR_DATA[r]=e)},NEPALI_CALENDAR_DATA:{1970:[18,31,31,32,31,31,31,30,29,30,29,30,30],1971:[18,31,31,32,31,32,30,30,29,30,29,30,30],1972:[17,31,32,31,32,31,30,30,30,29,29,30,30],1973:[19,30,32,31,32,31,30,30,30,29,30,29,31],1974:[19,31,31,32,30,31,31,30,29,30,29,30,30],1975:[18,31,31,32,32,30,31,30,29,30,29,30,30],1976:[17,31,32,31,32,31,30,30,30,29,29,30,31],1977:[18,31,32,31,32,31,31,29,30,29,30,29,31],1978:[18,31,31,32,31,31,31,30,29,30,29,30,30],1979:[18,31,31,32,32,31,30,30,29,30,29,30,30],1980:[17,31,32,31,32,31,30,30,30,29,29,30,31],1981:[18,31,31,31,32,31,31,29,30,30,29,30,30],1982:[18,31,31,32,31,31,31,30,29,30,29,30,30],1983:[18,31,31,32,32,31,30,30,29,30,29,30,30],1984:[17,31,32,31,32,31,30,30,30,29,29,30,31],1985:[18,31,31,31,32,31,31,29,30,30,29,30,30],1986:[18,31,31,32,31,31,31,30,29,30,29,30,30],1987:[18,31,32,31,32,31,30,30,29,30,29,30,30],1988:[17,31,32,31,32,31,30,30,30,29,29,30,31],1989:[18,31,31,31,32,31,31,30,29,30,29,30,30],1990:[18,31,31,32,31,31,31,30,29,30,29,30,30],1991:[18,31,32,31,32,31,30,30,29,30,29,30,30],1992:[17,31,32,31,32,31,30,30,30,29,30,29,31],1993:[18,31,31,31,32,31,31,30,29,30,29,30,30],1994:[18,31,31,32,31,31,31,30,29,30,29,30,30],1995:[17,31,32,31,32,31,30,30,30,29,29,30,30],1996:[17,31,32,31,32,31,30,30,30,29,30,29,31],1997:[18,31,31,32,31,31,31,30,29,30,29,30,30],1998:[18,31,31,32,31,31,31,30,29,30,29,30,30],1999:[17,31,32,31,32,31,30,30,30,29,29,30,31],2e3:[17,30,32,31,32,31,30,30,30,29,30,29,31],2001:[18,31,31,32,31,31,31,30,29,30,29,30,30],2002:[18,31,31,32,32,31,30,30,29,30,29,30,30],2003:[17,31,32,31,32,31,30,30,30,29,29,30,31],2004:[17,30,32,31,32,31,30,30,30,29,30,29,31],2005:[18,31,31,32,31,31,31,30,29,30,29,30,30],2006:[18,31,31,32,32,31,30,30,29,30,29,30,30],2007:[17,31,32,31,32,31,30,30,30,29,29,30,31],2008:[17,31,31,31,32,31,31,29,30,30,29,29,31],2009:[18,31,31,32,31,31,31,30,29,30,29,30,30],2010:[18,31,31,32,32,31,30,30,29,30,29,30,30],2011:[17,31,32,31,32,31,30,30,30,29,29,30,31],2012:[17,31,31,31,32,31,31,29,30,30,29,30,30],2013:[18,31,31,32,31,31,31,30,29,30,29,30,30],2014:[18,31,31,32,32,31,30,30,29,30,29,30,30],2015:[17,31,32,31,32,31,30,30,30,29,29,30,31],2016:[17,31,31,31,32,31,31,29,30,30,29,30,30],2017:[18,31,31,32,31,31,31,30,29,30,29,30,30],2018:[18,31,32,31,32,31,30,30,29,30,29,30,30],2019:[17,31,32,31,32,31,30,30,30,29,30,29,31],2020:[17,31,31,31,32,31,31,30,29,30,29,30,30],2021:[18,31,31,32,31,31,31,30,29,30,29,30,30],2022:[17,31,32,31,32,31,30,30,30,29,29,30,30],2023:[17,31,32,31,32,31,30,30,30,29,30,29,31],2024:[17,31,31,31,32,31,31,30,29,30,29,30,30],2025:[18,31,31,32,31,31,31,30,29,30,29,30,30],2026:[17,31,32,31,32,31,30,30,30,29,29,30,31],2027:[17,30,32,31,32,31,30,30,30,29,30,29,31],2028:[17,31,31,32,31,31,31,30,29,30,29,30,30],2029:[18,31,31,32,31,32,30,30,29,30,29,30,30],2030:[17,31,32,31,32,31,30,30,30,30,30,30,31],2031:[17,31,32,31,32,31,31,31,31,31,31,31,31],2032:[17,32,32,32,32,32,32,32,32,32,32,32,32],2033:[18,31,31,32,32,31,30,30,29,30,29,30,30],2034:[17,31,32,31,32,31,30,30,30,29,29,30,31],2035:[17,30,32,31,32,31,31,29,30,30,29,29,31],2036:[17,31,31,32,31,31,31,30,29,30,29,30,30],2037:[18,31,31,32,32,31,30,30,29,30,29,30,30],2038:[17,31,32,31,32,31,30,30,30,29,29,30,31],2039:[17,31,31,31,32,31,31,29,30,30,29,30,30],2040:[17,31,31,32,31,31,31,30,29,30,29,30,30],2041:[18,31,31,32,32,31,30,30,29,30,29,30,30],2042:[17,31,32,31,32,31,30,30,30,29,29,30,31],2043:[17,31,31,31,32,31,31,29,30,30,29,30,30],2044:[17,31,31,32,31,31,31,30,29,30,29,30,30],2045:[18,31,32,31,32,31,30,30,29,30,29,30,30],2046:[17,31,32,31,32,31,30,30,30,29,29,30,31],2047:[17,31,31,31,32,31,31,30,29,30,29,30,30],2048:[17,31,31,32,31,31,31,30,29,30,29,30,30],2049:[17,31,32,31,32,31,30,30,30,29,29,30,30],2050:[17,31,32,31,32,31,30,30,30,29,30,29,31],2051:[17,31,31,31,32,31,31,30,29,30,29,30,30],2052:[17,31,31,32,31,31,31,30,29,30,29,30,30],2053:[17,31,32,31,32,31,30,30,30,29,29,30,30],2054:[17,31,32,31,32,31,30,30,30,29,30,29,31],2055:[17,31,31,32,31,31,31,30,29,30,30,29,30],2056:[17,31,31,32,31,32,30,30,29,30,29,30,30],2057:[17,31,32,31,32,31,30,30,30,29,29,30,31],2058:[17,30,32,31,32,31,30,30,30,29,30,29,31],2059:[17,31,31,32,31,31,31,30,29,30,29,30,30],2060:[17,31,31,32,32,31,30,30,29,30,29,30,30],2061:[17,31,32,31,32,31,30,30,30,29,29,30,31],2062:[17,30,32,31,32,31,31,29,30,29,30,29,31],2063:[17,31,31,32,31,31,31,30,29,30,29,30,30],2064:[17,31,31,32,32,31,30,30,29,30,29,30,30],2065:[17,31,32,31,32,31,30,30,30,29,29,30,31],2066:[17,31,31,31,32,31,31,29,30,30,29,29,31],2067:[17,31,31,32,31,31,31,30,29,30,29,30,30],2068:[17,31,31,32,32,31,30,30,29,30,29,30,30],2069:[17,31,32,31,32,31,30,30,30,29,29,30,31],2070:[17,31,31,31,32,31,31,29,30,30,29,30,30],2071:[17,31,31,32,31,31,31,30,29,30,29,30,30],2072:[17,31,32,31,32,31,30,30,29,30,29,30,30],2073:[17,31,32,31,32,31,30,30,30,29,29,30,31],2074:[17,31,31,31,32,31,31,30,29,30,29,30,30],2075:[17,31,31,32,31,31,31,30,29,30,29,30,30],2076:[16,31,32,31,32,31,30,30,30,29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e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return 682*((e.year()-(e.year()>0?474:473))%2820+474+38)%2816<682},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-(n.dayOfWeek()+1)%7,\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=i.year(),e=i.month(),r=i.day();var a=t-(t>=0?474:473),s=474+o(a,2820);return r+(e<=7?31*(e-1):30*(e-1)+6)+Math.floor((682*s-110)/2816)+365*(s-1)+1029983*Math.floor(a/2820)+this.jdEpoch-1},fromJD:function(t){var e=(t=Math.floor(t)+.5)-this.toJD(475,1,1),r=Math.floor(e/1029983),n=o(e,1029983),i=2820;if(1029982!==n){var a=Math.floor(n/366),s=o(n,366);i=Math.floor((2134*a+2816*s+2815)/1028522)+a+1}var l=i+2820*r+474;l=l<=0?l-1:l;var 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i=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return t=this._t2gYear(i.year()),a.weekOfYear(t,i.month(),i.day())},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return t=this._t2gYear(i.year()),a.toJD(t,i.month(),i.day())},fromJD:function(t){var e=a.fromJD(t),r=this._g2tYear(e.year());return this.newDate(r,e.month(),e.day())},_t2gYear:function(t){return t+this.yearsOffset+(t>=-this.yearsOffset&&t<=-1?1:0)},_g2tYear:function(t){return t-this.yearsOffset-(t>=1&&t<=this.yearsOffset?1:0)}}),n.calendars.taiwan=o},4592:function(t,e,r){var n=r(38700),i=r(50896),a=n.instance();function o(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}o.prototype=new 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i=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return t=this._t2gYear(i.year()),a.weekOfYear(t,i.month(),i.day())},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return t=this._t2gYear(i.year()),a.toJD(t,i.month(),i.day())},fromJD:function(t){var e=a.fromJD(t),r=this._g2tYear(e.year());return this.newDate(r,e.month(),e.day())},_t2gYear:function(t){return t-this.yearsOffset-(t>=1&&t<=this.yearsOffset?1:0)},_g2tYear:function(t){return t+this.yearsOffset+(t>=-this.yearsOffset&&t<=-1?1:0)}}),n.calendars.thai=o},45348:function(t,e,r){var n=r(38700),i=r(50896);function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new 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n=r(50896);function i(){this.regionalOptions=[],this.regionalOptions[\"\"]={invalidCalendar:\"Calendar {0} not found\",invalidDate:\"Invalid {0} date\",invalidMonth:\"Invalid {0} month\",invalidYear:\"Invalid {0} year\",differentCalendars:\"Cannot mix {0} and {1} dates\"},this.local=this.regionalOptions[\"\"],this.calendars={},this._localCals={}}function a(t,e,r,n){if(this._calendar=t,this._year=e,this._month=r,this._day=n,0===this._calendar._validateLevel&&!this._calendar.isValid(this._year,this._month,this._day))throw(u.local.invalidDate||u.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name)}function o(t,e){return\"000000\".substring(0,e-(t=\"\"+t).length)+t}function s(){this.shortYearCutoff=\"+10\"}function l(t){this.local=this.regionalOptions[t]||this.regionalOptions[\"\"]}n(i.prototype,{instance:function(t,e){t=(t||\"gregorian\").toLowerCase(),e=e||\"\";var r=this._localCals[t+\"-\"+e];if(!r&&this.calendars[t]&&(r=new this.calendars[t](e),this._localCals[t+\"-\"+e]=r),!r)throw(this.local.invalidCalendar||this.regionalOptions[\"\"].invalidCalendar).replace(/\\{0\\}/,t);return r},newDate:function(t,e,r,n,i){return(n=(null!=t&&t.year?t.calendar():\"string\"==typeof n?this.instance(n,i):n)||this.instance()).newDate(t,e,r)},substituteDigits:function(t){return function(e){return(e+\"\").replace(/[0-9]/g,(function(e){return t[e]}))}},substituteChineseDigits:function(t,e){return function(r){for(var n=\"\",i=0;r>0;){var a=r%10;n=(0===a?\"\":t[a]+e[i])+n,i++,r=Math.floor(r/10)}return 0===n.indexOf(t[1]+e[1])&&(n=n.substr(1)),n||t[0]}}}),n(a.prototype,{newDate:function(t,e,r){return this._calendar.newDate(null==t?this:t,e,r)},year:function(t){return 0===arguments.length?this._year:this.set(t,\"y\")},month:function(t){return 0===arguments.length?this._month:this.set(t,\"m\")},day:function(t){return 0===arguments.length?this._day:this.set(t,\"d\")},date:function(t,e,r){if(!this._calendar.isValid(t,e,r))throw(u.local.invalidDate||u.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name);return this._year=t,this._month=e,this._day=r,this},leapYear:function(){return this._calendar.leapYear(this)},epoch:function(){return this._calendar.epoch(this)},formatYear:function(){return this._calendar.formatYear(this)},monthOfYear:function(){return this._calendar.monthOfYear(this)},weekOfYear:function(){return this._calendar.weekOfYear(this)},daysInYear:function(){return this._calendar.daysInYear(this)},dayOfYear:function(){return this._calendar.dayOfYear(this)},daysInMonth:function(){return this._calendar.daysInMonth(this)},dayOfWeek:function(){return this._calendar.dayOfWeek(this)},weekDay:function(){return this._calendar.weekDay(this)},extraInfo:function(){return this._calendar.extraInfo(this)},add:function(t,e){return this._calendar.add(this,t,e)},set:function(t,e){return this._calendar.set(this,t,e)},compareTo:function(t){if(this._calendar.name!==t._calendar.name)throw(u.local.differentCalendars||u.regionalOptions[\"\"].differentCalendars).replace(/\\{0\\}/,this._calendar.local.name).replace(/\\{1\\}/,t._calendar.local.name);var e=this._year!==t._year?this._year-t._year:this._month!==t._month?this.monthOfYear()-t.monthOfYear():this._day-t._day;return 0===e?0:e<0?-1:1},calendar:function(){return this._calendar},toJD:function(){return this._calendar.toJD(this)},fromJD:function(t){return this._calendar.fromJD(t)},toJSDate:function(){return this._calendar.toJSDate(this)},fromJSDate:function(t){return this._calendar.fromJSDate(t)},toString:function(){return(this.year()<0?\"-\":\"\")+o(Math.abs(this.year()),4)+\"-\"+o(this.month(),2)+\"-\"+o(this.day(),2)}}),n(s.prototype,{_validateLevel:0,newDate:function(t,e,r){return null==t?this.today():(t.year&&(this._validate(t,e,r,u.local.invalidDate||u.regionalOptions[\"\"].invalidDate),r=t.day(),e=t.month(),t=t.year()),new a(this,t,e,r))},today:function(){return this.fromJSDate(new Date)},epoch:function(t){return this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[\"\"].invalidYear).year()<0?this.local.epochs[0]:this.local.epochs[1]},formatYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[\"\"].invalidYear);return(e.year()<0?\"-\":\"\")+o(Math.abs(e.year()),4)},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[\"\"].invalidYear),12},monthOfYear:function(t,e){var r=this._validate(t,e,this.minDay,u.local.invalidMonth||u.regionalOptions[\"\"].invalidMonth);return(r.month()+this.monthsInYear(r)-this.firstMonth)%this.monthsInYear(r)+this.minMonth},fromMonthOfYear:function(t,e){var r=(e+this.firstMonth-2*this.minMonth)%this.monthsInYear(t)+this.minMonth;return this._validate(t,r,this.minDay,u.local.invalidMonth||u.regionalOptions[\"\"].invalidMonth),r},daysInYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[\"\"].invalidYear);return this.leapYear(e)?366:365},dayOfYear:function(t,e,r){var n=this._validate(t,e,r,u.local.invalidDate||u.regionalOptions[\"\"].invalidDate);return n.toJD()-this.newDate(n.year(),this.fromMonthOfYear(n.year(),this.minMonth),this.minDay).toJD()+1},daysInWeek:function(){return 7},dayOfWeek:function(t,e,r){var n=this._validate(t,e,r,u.local.invalidDate||u.regionalOptions[\"\"].invalidDate);return(Math.floor(this.toJD(n))+2)%this.daysInWeek()},extraInfo:function(t,e,r){return this._validate(t,e,r,u.local.invalidDate||u.regionalOptions[\"\"].invalidDate),{}},add:function(t,e,r){return this._validate(t,this.minMonth,this.minDay,u.local.invalidDate||u.regionalOptions[\"\"].invalidDate),this._correctAdd(t,this._add(t,e,r),e,r)},_add:function(t,e,r){if(this._validateLevel++,\"d\"===r||\"w\"===r){var n=t.toJD()+e*(\"w\"===r?this.daysInWeek():1),i=t.calendar().fromJD(n);return this._validateLevel--,[i.year(),i.month(),i.day()]}try{var a=t.year()+(\"y\"===r?e:0),o=t.monthOfYear()+(\"m\"===r?e:0);i=t.day(),\"y\"===r?(t.month()!==this.fromMonthOfYear(a,o)&&(o=this.newDate(a,t.month(),this.minDay).monthOfYear()),o=Math.min(o,this.monthsInYear(a)),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o)))):\"m\"===r&&(function(t){for(;o<t.minMonth;)a--,o+=t.monthsInYear(a);for(var e=t.monthsInYear(a);o>e-1+t.minMonth;)a++,o-=e,e=t.monthsInYear(a)}(this),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o))));var s=[a,this.fromMonthOfYear(a,o),i];return this._validateLevel--,s}catch(t){throw 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n=this._validate(t,e,r,u.local.invalidDate||u.regionalOptions[\"\"].invalidDate),i=new Date(n.year(),n.month()-1,n.day());return i.setHours(0),i.setMinutes(0),i.setSeconds(0),i.setMilliseconds(0),i.setHours(i.getHours()>12?i.getHours()+2:0),i},fromJSDate:function(t){return this.newDate(t.getFullYear(),t.getMonth()+1,t.getDate())}});var u=t.exports=new i;u.cdate=a,u.baseCalendar=s,u.calendars.gregorian=l},15168:function(t,e,r){var n=r(50896),i=r(38700);n(i.regionalOptions[\"\"],{invalidArguments:\"Invalid arguments\",invalidFormat:\"Cannot format a date from another calendar\",missingNumberAt:\"Missing number at position {0}\",unknownNameAt:\"Unknown name at position {0}\",unexpectedLiteralAt:\"Unexpected literal at position {0}\",unexpectedText:\"Additional text found at end\"}),i.local=i.regionalOptions[\"\"],n(i.cdate.prototype,{formatDate:function(t,e){return\"string\"!=typeof 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   "source": [
    "# Plot a 3-dimensional chart\n",
    "dw.plot_3d(df=df_X_scaled_pca_7_XY, x='PCA1', y='PCA2', z='PCA3', color='Churn', color_discrete_map=color_map_churn)"
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot Map of California\n",
    "\n",
    "`dw.plot_map_ca()` plots longitude and latitude data on a geographic map of California.\n",
    "\n",
    "This function creates a geographic map of California using Cartopy and\n",
    "overlays data points from a DataFrame. The map includes major cities, county\n",
    "boundaries, and geographic terrain features. Specify the columns in the\n",
    "dataframe that map to the longitude (`lon`) and the latitude (`lat`). Then\n",
    "specify an optional `hue` column to see changes in this variable by color,\n",
    "and/or a `size` column to see changes in this varible by dot size. So two\n",
    "variables can be visualized at once.\n",
    "\n",
    "A few parameters can be customized, such as the range of the dot sizes\n",
    "(`size_range`) if you're using `size`. You can also just use `dot_size` to\n",
    "specify a fixed size for all the dots on the map. The `alpha` transparency\n",
    "can be adjusted, to make sure you at least have a chance of seeing dots of\n",
    "a different color that may be covered up by the top-most layer. You can also\n",
    "customize the `color_map` for the `hue` parameter.\n",
    "\n",
    "Use this function to visualize geospatial data related to\n",
    "California on a clean map."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load some data with latitude and longitude for California\n",
    "df_housing = pd.read_csv('data/housing_no_outliers.csv', index_col=0)"
   ]
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   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1200x1200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Use custom function plot data on California map\n",
    "dw.plot_map_ca(df_housing, lon='longitude', lat='latitude', hue='ocean_proximity', size='median_house_value', size_range=(5, 150), alpha=0.8, title='Housing Blocks by Ocean Proximity and Median House Value')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot Scatterplot\n",
    "\n",
    "`dw.plot_scatt()` creates a scatter plot using Seaborn's scatterplot function.\n",
    "\n",
    "This function generates a scatter plot using the Seaborn library. It allows\n",
    "for customization of the `x` and `y` axes, as well as the `hue` and `size`\n",
    "dimensions. The `hue` parameter is used to color the points based on a\n",
    "categorical column, while the `size` parameter is used to vary the size of\n",
    "the points based on a numerical column or a fixed value. You can also set\n",
    "the range of sizes with `size_range`, and the title of the plot with `title`.\n",
    "The `alpha` parameter controls the transparency of the points. You can also\n",
    "specify a color map with `color_map` to change the color scheme of the plot.\n",
    "The `fig_size` parameter allows you to set the size of the figure.\n",
    "\n",
    "Use this function to visualize relationships between two variables in a\n",
    "dataset, with the option to color and size the points based on additional\n",
    "variables. It is a great way to explore correlations between variables and\n",
    "identify patterns in the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a scatterplot of the housing data\n",
    "dw.plot_scatt(df=df_housing, x='median_income', y='median_house_value', hue='ocean_proximity', x_format='large_dollars', y_format='large_dollars',\n",
    "          title='Median Income vs. Median House Value by Ocean Proximity', x_label='Median Income', y_label='Median House Value',\n",
    "          legend_title='Ocean Proximity')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Print ASCII Image\n",
    "\n",
    "`dw.print_ascii_image()` prints an ASCII representation of one or two PyTorch images.\n",
    "\n",
    "This function takes one or two PyTorch tensors representing images and prints\n",
    "their ASCII representation. It supports various options to customize the\n",
    "output, such as the number of channels, orientation, and value representation\n",
    "(binary or continuous). The function can also merge multiple channels into a\n",
    "single grayscale representation using either the mean or a weighted sum of the\n",
    "channels.\n",
    "\n",
    "The tensor data should be concatenated into one long vector. For example, for\n",
    "a single-channel image of size 28x28, the tensor should have a size of [784].\n",
    "For a three-channel image of size 32x32, the tensor should have a size of\n",
    "[3072]. Please process the tensors before passing them to this function.\n",
    "\n",
    "Use this function when you want to visualize PyTorch images in the console\n",
    "using ASCII characters, perhaps for debugging during your modeling workflow.\n",
    "For example, you can compare two images side by side (a source image from the\n",
    "x dataset, and the corresponding generated image x_hat)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Load Tensor Images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load sample tensor images\n",
    "image1 = torch.load('data/mnist_28x28_ch1_x0.pt')\n",
    "image2 = torch.load('data/svhn_32x32_ch3_x0.pt')\n",
    "image3 = torch.load('data/svhn_32x32_ch3_xhat0.pt')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Review Tensor Data\n",
    "\n",
    "This function was designed to work with a single dimension tensor, with no separate channel dimensions. So if you had multiple channels as a 2nd dimension, they would have been already concatenated together. If you have a batch of let's say [100, 784] to represent 100 images with length 784 (for a 28x28 MNIST image), and that's your `x` dataset, you would pass `x[0]` or `x[i]` into this function. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "image1 size: [784]\n",
      "image2 size: [3072]\n",
      "image3 size: [3072]\n"
     ]
    }
   ],
   "source": [
    "# Review the dimensions, note there is no batch nor channel dimension, everything is concatenated\n",
    "print(f\"image1 size: {list(image1.size())}\")\n",
    "print(f\"image2 size: {list(image2.size())}\")\n",
    "print(f\"image3 size: {list(image3.size())}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 1., 1., 0.,\n",
       "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1.,\n",
       "        1., 0., 0., 0., 0., 0., 0., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.,\n",
       "        1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "        1., 1., 1., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 0., 0., 0., 0., 0., 0.,\n",
       "        1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 1., 1., 0., 0., 0., 0.,\n",
       "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0.,\n",
       "        0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 0., 0., 0., 1., 1., 0., 0., 0.,\n",
       "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1.,\n",
       "        1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 1., 1., 1., 1., 0., 0.,\n",
       "        1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1.,\n",
       "        1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 1., 1., 0., 0.,\n",
       "        0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1.,\n",
       "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1.,\n",
       "        1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Sample 28x28 1-channel tensor of '4' from MNIST data\n",
    "image1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([0.4549, 0.4510, 0.4667,  ..., 0.2784, 0.2902, 0.3020])"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Sample 32x32 3-channel tensor of '8' from SVHN data\n",
    "image2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([0.3091, 0.2603, 0.3264,  ..., 0.3444, 0.3897, 0.3819])"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Sample 32x32 3-channel tensor of '8' from SVHN data (generated)\n",
    "image3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Print Binary Image\n",
    "\n",
    "This converts 0 and 1 to an empty space and a solid block ('█') to make it easier to scan. A space is added to roughly approximate a square aspect ratio of 28x28 in this example."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                                       \n",
      "                                                       \n",
      "                                                       \n",
      "                                                       \n",
      "                                        █              \n",
      "                      █ █             █ █              \n",
      "                      █ █             █ █ █            \n",
      "                      █ █               █              \n",
      "                    █ █ █             █                \n",
      "                  █ █ █             █ █                \n",
      "                    █               █ █                \n",
      "                    █               █                  \n",
      "                    █ █           █ █ █                \n",
      "                    █ █           █ █                  \n",
      "                █ █ █ █ █         █ █                  \n",
      "                █ █ █ █ █ █ █   █ █                    \n",
      "                  █ █ █ █ █ █ █ █ █     █ █            \n",
      "                  █ █ █ █ █ █ █ █ █ █ █ █ █            \n",
      "                      █ █   █ █         █              \n",
      "                            █ █                        \n",
      "                            █ █                        \n",
      "                          █ █                          \n",
      "                          █ █ █                        \n",
      "                        █ █ █                          \n",
      "                                                       \n",
      "                                                       \n",
      "                                                       \n",
      "                                                       \n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Print a single binary image with a space between characters\n",
    "dw.print_ascii_image(image1, width=28, height=28, add_space=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Print Continuous Image with 3 Channels\n",
    "\n",
    "For continuous data (floats between 0.00 and 1.00) we need to convert those intensities (or probabilities) into a visual representation. By default, the `ascii_chars` are '@%#*+=-:. ', but they can be changed. The characters should be ordered from dark to light, with the last character representing the lightest value."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "++++*#%@@%#*++======+*#%%@@@@%%%   ===++*#%@%#+========+*#%%@@%%%%%   ----=+*###*+=-------==**#%######\n",
      "---=+*%@@#*=----::-==+*%%@@@@@%%   :-:-=*#%%#+=-:::::--=+*%%@@@@%%%   ::::-=*##*+-::....::-=+*#%%#####\n",
      "::-=+*%@%#+=-----::--=+#%@@@@@%%   :::-+*#%%*+-:::-::::-=+#%@@@@%%%   ...:-=*##+=::.::....:-=*##%#####\n",
      ":--=*#%%%*=----==-:::-+*%@@@%%%%   ::-=*##%#+=:::-==-:::-+*%@@@%%%#   ..:-=+*#*+-:.::--:...:=+*####***\n",
      ":-=+#%%%%+=::-=++=:::-=*%%@%%%##   :--+#%%%#+-:::=++=:::-=*%%@%%%##   .::=+**#*=:..:-==-...:-+*###****\n",
      ":-=*%@@%#=-::-+**=:::-=*%%@%%###   :-=*#%%%*=:.:-=**=:.:-=*%@@%%###   .:-+*##*+-:..:=++=...:-+*###****\n",
      "--+#%@@%*=:::-+##+::::=*%@@%####   :-+#%@@%*-:.:-+**+::::=*%@@%####   ::=+###*+:...-=**=:...-=*##*****\n",
      ":-+#@@@%#=:::=+##+::::=*%%%%####   :-+#%@@%*-:::-+##+::::=*%%%%####   .:=*#%##+:...-+**=:...-=*##**+*+\n",
      ":-+#@@@%*=:::=*##+:.:-=*%%%%####   :-+#%@%#*-:.:-+##+:::-=*%%%%####   .:=*#%#*+:..:-+##=...:-+*##**+*+\n",
      ":-+#%@@%#=-:-=+##=:::-+*%%%%%###   :-+#%@%#*=:::-+##=:::-+#%%%%%###   .:=*###*+-:.:-=**-...:=+*##*****\n",
      ":-*#%@%%#+=--=+#*=:::-+#%@%%%%%#   :-+#%@%#*=-::-+#*=::--+#%@@%%%##   :-=*###*+=:::-=*+-..::=+###*****\n",
      ":-*#%@%%#+=-:-=*+=::-=+#%@%%%%%%   :-*#%%%#*+-::-=++=::-=*#%@@%%%%%   :-+*###*+=-:.:-==-..::=*###*#***\n",
      ":=*#@@@@%*=-::-=--:--=*#%%%%%%%%   :=*#%@%%#+=-::-=-----=*#%@%%%%%%   :-+*#%##*+-:..:-::..:-=**##*#***\n",
      ":-+#%@@@%*=-::-------=*#%%%%%%%%   :-+#%%%%#+=-.:-------=*#%%%%%%%%   .:+*#####+-: .::::::::=+****#**#\n",
      "-=++*%%%#+--:-===+=---=*%%%%%%%%   -=++*#%%*=-:::=+++=---+*%%%%%%%#   :-==+*##*=::.:-----:.:-+********\n",
      "--==+*##*-:::=+***=-:-=*#%%%%%%%   --==+*#*+-:::=+***=-:-=*#%%%%%##   :---=+**=:...-=++=-:..:=********\n",
      ":--==***+-::-+*##*=-::=*#%%%%%%%   :---=+*+=:.:-+*##*=-::=*#%%%%%##   ::---+++=:..:=+**+-:..:=+*******\n",
      ":---=+*+=::-=*#%#*=-:-=*#%%%%%%%   ::--=+++-:.:-+#%#*=-:-=*#%%%%%##   .:::-=+=-:.:-+***+-:..:=+*******\n",
      ":::-=++=-::-=*#%#*=-:-=*#%%%%%%%   :::--=+=-:::=*###*=-:-=*#%%%%%%#   ...:-==-::.:-+***=-:..-=********\n",
      ":::-=++=-::-=*#%#*=-:-=*#%%%%%%%   .::-=++=-:.:=*###+--:-=*#%%%%%%%   ...:-==-:..:-+*#*=::.:-=********\n",
      ":::-=++=-:::=*%%#+-::-=*#%%%%%%%   .::-=++-::.:=*###+-::-=*#%%%%%%%   ...:-==-:..:-+*#*=:..:-+********\n",
      ":::-=+=-::::=*##*=-:-=+*#%%%%%%%   ..:-=+=-::::=*##*=:::-+*#%%%%%%%   ...:-=-:...:-+**+-:..:=+********\n",
      "::-=++=-:::-=###*=---=+#%%%%%%%%   :::=++=-::::=*##+-::-=+#%%%%%%%%   ..:-==-:...:-***+-:.:-=+*#*****#\n",
      "--=+**+-:::-=*##*=:--=*#%@%%%%%%   :-=+**+-:.:-=***+-::-=*#%%%%%%%%   .:-=++=:...:=+**=-..:-+*###**#*#\n",
      "-=++*#+-:::-=+**+----=*%%@@%%%%%   -==+*#+-:::-=+*+=-::-=*#%@@%%%%#   :-==++=:...:-=++-::::-+*######**\n",
      "==+*##*=::::-=+=----=+*%%@@%%%%%   -=+*##*=:.::-===-:--=+*%%@%%%%%#   -==+**+-:...:-=-::::-=+*######*#\n",
      "-=+*##*=-:::-==-:-===*#%@@%%%%%%   -=+*##*=:...:-=-::-==+#%%%%%%%%%   :-=+**+-:...:--:.::--=*#########\n",
      "--=+##*+-::::-=---=++*#%@@%%%%%%   --=*##*=-::.:-----==+*#%%%%%%%##   :-=+**+=:....:-:::--=+*####*####\n",
      ":--+*##+=--::-====++*##%%%%%%%%#   :-=+*#*+=-:::----=++*##%%%%##%##   .:-=+*+=-::..:--:-==++*####**##*\n",
      "::-+*%##+==--==++***##%%%%%%%%%%   ::-+*##*+-----=+++**##%%%%%#%%##   .:-=+**+=::::--===+++*#####*####\n",
      "--=*#%%%#+++++*#####%%%@@%%%%@%%   --=*#%%#*+++++**#####%%%%%%#%%%%   ::-+*##*+=====++*****######*#%##\n",
      "+++*#%%%##****#######%%%%%%#%%%#   +++*#%%%#*****########%%%%######   ===+*###*+++++********####**####\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Print a single continuous image with 3 channels\n",
    "dw.print_ascii_image(image2, values='continuous', channels=3, width=32, height=32, orientation='horizontal')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Print Continuous Image with Merged Channels\n",
    "\n",
    "This averages the channels together, using perceptual weights by default, which is typical for greyscale conversion. But other `channel_weights` can be specified."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+ + + + * # % @ @ % # * + + = = = = = = + * # % % @ @ @ @ % % %\n",
      "- - - = + * % @ @ # * = - - - - : : - = = + * % % @ @ @ @ @ % %\n",
      ": : - = + * % @ % # + = - - - - - : : - - = + # % @ @ @ @ @ % %\n",
      ": - - = * # % % % * = - - - - = = - : : : - + * % @ @ @ % % % %\n",
      ": - = + # % % % % + = : : - = + + = : : : - = * % % @ % % % # #\n",
      ": - = * % @ @ % # = - : : - + * * = : : : - = * % % @ % % # # #\n",
      "- - + # % @ @ % * = : : : - + # # + : : : : = * % @ @ % # # # #\n",
      ": - + # @ @ @ % # = : : : = + # # + : : : : = * % % % % # # # #\n",
      ": - + # @ @ @ % * = : : : = * # # + : . : - = * % % % % # # # #\n",
      ": - + # % @ @ % # = - : - = + # # = : : : - + * % % % % % # # #\n",
      ": - * # % @ % % # + = - - = + # * = : : : - + # % @ % % % % % #\n",
      ": - * # % @ % % # + = - : - = * + = : : - = + # % @ % % % % % %\n",
      ": = * # @ @ @ @ % * = - : : - = - - : - - = * # % % % % % % % %\n",
      ": - + # % @ @ @ % * = - : : - - - - - - - = * # % % % % % % % %\n",
      "- = + + * % % % # + - - : - = = = + = - - - = * % % % % % % % %\n",
      "- - = = + * # # * - : : : = + * * * = - : - = * # % % % % % % %\n",
      ": - - = = * * * + - : : - + * # # * = - : : = * # % % % % % % %\n",
      ": - - - = + * + = : : - = * # % # * = - : - = * # % % % % % % %\n",
      ": : : - = + + = - : : - = * # % # * = - : - = * # % % % % % % %\n",
      ": : : - = + + = - : : - = * # % # * = - : - = * # % % % % % % %\n",
      ": : : - = + + = - : : : = * % % # + - : : - = * # % % % % % % %\n",
      ": : : - = + = - : : : : = * # # * = - : - = + * # % % % % % % %\n",
      ": : - = + + = - : : : - = # # # * = - - - = + # % % % % % % % %\n",
      "- - = + * * + - : : : - = * # # * = : - - = * # % @ % % % % % %\n",
      "- = + + * # + - : : : - = + * * + - - - - = * % % @ @ % % % % %\n",
      "= = + * # # * = : : : : - = + = - - - - = + * % % @ @ % % % % %\n",
      "- = + * # # * = - : : : - = = - : - = = = * # % @ @ % % % % % %\n",
      "- - = + # # * + - : : : : - = - - - = + + * # % @ @ % % % % % %\n",
      ": - - + * # # + = - - : : - = = = = + + * # # % % % % % % % % #\n",
      ": : - + * % # # + = = - - = = + + * * * # # % % % % % % % % % %\n",
      "- - = * # % % % # + + + + + * # # # # # % % % @ @ % % % % @ % %\n",
      "+ + + * # % % % # # * * * * # # # # # # # % % % % % % # % % % #\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Print a single continuous image but merge the channels into one:\n",
    "dw.print_ascii_image(image2, values='continuous', channels=3, width=32, height=32, merge_channels=True, add_space=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Print 2 Image Comparison\n",
    "\n",
    "This comes in handy when you are evaluating the input image into an Encoder, in comparison with the output image from a Decoder."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "++++*#%@@%#*++======+*#%%@@@@%%%   #%##%##%###%######*###%%###%%%#%\n",
      "---=+*%@@#*=----::-==+*%%@@@@@%%   ***##%%%%#####******##%%%%%%%%##\n",
      "::-=+*%@%#+=-----::--=+#%@@@@@%%   ***###%#%%#**+++++++**##%%%%%%%%\n",
      ":--=*#%%%*=----==-:::-+*%@@@%%%%   +****##%#**+=======+++*%%%@@%%%%\n",
      ":-=+#%%%%+=::-=++=:::-=*%%@%%%##   +++*######+=+====-===**#%@%@%%%#\n",
      ":-=*%@@%#=-::-+**=:::-=*%%@%%###   +++*#####*==-===-=--=++%@@@%@%%%\n",
      "--+#%@@%*=:::-+##+::::=*%@@%####   =++*####*+--=-===+=--=*#@@@%%%#%\n",
      ":-+#@@@%#=:::=+##+::::=*%%%%####   ==++*#%#++==-==+++=--=*#%@@@%%%%\n",
      ":-+#@@@%*=:::=*##+:.:-=*%%%%####   ++++**##*+=-==*+*+=--=*#%@@@@%#%\n",
      ":-+#%@@%#=-:-=+##=:::-+*%%%%%###   ++++*#%#*+--=++**+=-=+*#%@@@@%%%\n",
      ":-*#%@%%#+=--=+#*=:::-+#%@%%%%%#   ==+*+###+==-=+****=-==#%%@%@@%%%\n",
      ":-*#%@%%#+=-:-=*+=::-=+#%@%%%%%%   *++**###*====+****====*#@@@@@@%%\n",
      ":=*#@@@@%*=-::-=--:--=*#%%%%%%%%   +=++*##**+===+***+====+#%@@@@%%#\n",
      ":-+#%@@@%*=-::-------=*#%%%%%%%%   ++++*###*+====+=*+=-==+#%@@@@%%#\n",
      "-=++*%%%#+--:-===+=---=*%%%%%%%%   ==+=*###*+=====+++=--=**%@@@@@%%\n",
      "--==+*##*-:::=+***=-:-=*#%%%%%%%   ==++####*++===+++==--=+#%@@@@%%%\n",
      ":--==***+-::-+*##*=-::=*#%%%%%%%   ===+*###*++--=+++==--=+#%@@@@%%%\n",
      ":---=+*+=::-=*#%#*=-:-=*#%%%%%%%   ==++**#**=+=-=++*+=---+*%%@@@@%#\n",
      ":::-=++=-::-=*#%#*=-:-=*#%%%%%%%   =+=+*###*+-=+++*#+==--+*%%@@@%%%\n",
      ":::-=++=-::-=*#%#*=-:-=*#%%%%%%%   +++++*##*+=--=+***+---+#%%@@%%%%\n",
      ":::-=++=-:::=*%%#+-::-=*#%%%%%%%   ++=++*#**+===+*#**+===+#%@@@@%#%\n",
      ":::-=+=-::::=*##*=-:-=+*#%%%%%%%   ++++**##*+=-=++##*+---=*%@@%%%##\n",
      "::-=++=-:::-=###*=---=+#%%%%%%%%   +++++*#**=--=+*##*==--++%@@@%%%#\n",
      "--=+**+-:::-=*##*=:--=*#%@%%%%%%   +++++*#**=---=**#*+---+*#%@@@%##\n",
      "-=++*#+-:::-=+**+----=*%%@@%%%%%   +==++*#**=---=+***==:=+##@@@%%%#\n",
      "==+*##*=::::-=+=----=+*%%@@%%%%%   +=++**#**+---=+*++==-=*#%@@@%#%#\n",
      "-=+*##*=-:::-==-:-===*#%@@%%%%%%   =+++*###*+==--=++==-=+*#%%%@@%#*\n",
      "--=+##*+-::::-=---=++*#%@@%%%%%%   ++++#*###++--==+=====**%%@%@%@%#\n",
      ":--+*##+=--::-====++*##%%%%%%%%#   ++**###%#*++==+==+=++#%%@@%@@@##\n",
      "::-+*%##+==--==++***##%%%%%%%%%%   ***#*#%%##**++++=++**#%%%@@%%%#%\n",
      "--=*#%%%#+++++*#####%%%@@%%%%@%%   *####%%%###**+++**#*##%%%%%%%%%%\n",
      "+++*#%%%##****#######%%%%%%#%%%#   ##*###%%%%%#*##**#####%%%@%%%##%\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Print 2 images side by side with continuous values merged channels\n",
    "dw.print_ascii_image(image2, image3, values='continuous', channels=3, width=32, height=32,\n",
    "                  merge_channels=True, orientation='vertical', add_space=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "## Clean\n",
    "\n",
    "The `dw.clean` module provides tools to clean data in preparation for modeling.\n",
    "It contains functions to convert data types, convert unites of measurement,\n",
    "convert time values, and reduce multicollinearity.\n",
    "\n",
    "* [Convert Data Types](#Convert-Data-Types) - *convert_dtypes()*\n",
    "* [Load Data Units and Time Data](#Load-Data-Units-and-Time-Data)\n",
    "* [Convert Data Values](#Convert-Data-Values) - *convert_data_values()*\n",
    "* [Convert Time Values](#Convert-Time-Values) - *convert_time_values()*\n",
    "* [Split Outliers](#Split-Outliers) - *split_outliers()*\n",
    "* [Reduce Multicollinearity](#Reduce-Multicollinearity) - *reduce_multicollinearity()*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Convert Data Types\n",
    "\n",
    "`dw.convert_dtypes()` converts specified columns in a DataFrame to the desired data type.\n",
    "\n",
    "This function converts the data type of the specified columns in the input\n",
    "DataFrame to the desired target data type. It supports both base Python data\n",
    "types (e.g., int, float, str) and Pandas-specific data types (e.g., 'int64',\n",
    "'float64', 'object', 'bool', 'datetime64', 'timedelta[ns]', 'category'). If\n",
    "`inplace` is set to True (default), the conversion is done in place, modifying\n",
    "the original DataFrame. If `inplace` is False, a new DataFrame with the\n",
    "converted columns is returned. If `show_results` is set to True, it will print\n",
    "the results of each successful conversion and any error messages for columns\n",
    "that could not be converted.\n",
    "\n",
    "Use this function when you need to convert the data types of specific columns\n",
    "in a DataFrame to a consistent target data type, especially when dealing with\n",
    "multiple columns at once and identifying columns that require further data\n",
    "cleaning."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 41188 entries, 0 to 41187\n",
      "Data columns (total 11 columns):\n",
      " #   Column       Non-Null Count  Dtype \n",
      "---  ------       --------------  ----- \n",
      " 0   job          41188 non-null  object\n",
      " 1   marital      41188 non-null  object\n",
      " 2   education    41188 non-null  object\n",
      " 3   default      41188 non-null  object\n",
      " 4   housing      41188 non-null  object\n",
      " 5   loan         41188 non-null  object\n",
      " 6   contact      41188 non-null  object\n",
      " 7   month        41188 non-null  object\n",
      " 8   day_of_week  41188 non-null  object\n",
      " 9   poutcome     41188 non-null  object\n",
      " 10  y            41188 non-null  object\n",
      "dtypes: object(11)\n",
      "memory usage: 3.5+ MB\n"
     ]
    }
   ],
   "source": [
    "# Review data types of our previously identified categorical features\n",
    "df[cat_columns].info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 41188 entries, 0 to 41187\n",
      "Data columns (total 10 columns):\n",
      " #   Column          Non-Null Count  Dtype  \n",
      "---  ------          --------------  -----  \n",
      " 0   age             41188 non-null  int64  \n",
      " 1   duration        41188 non-null  int64  \n",
      " 2   campaign        41188 non-null  int64  \n",
      " 3   pdays           41188 non-null  int64  \n",
      " 4   previous        41188 non-null  int64  \n",
      " 5   emp.var.rate    41188 non-null  float64\n",
      " 6   cons.price.idx  41188 non-null  float64\n",
      " 7   cons.conf.idx   41188 non-null  float64\n",
      " 8   euribor3m       41188 non-null  float64\n",
      " 9   nr.employed     41188 non-null  float64\n",
      "dtypes: float64(5), int64(5)\n",
      "memory usage: 3.1 MB\n"
     ]
    }
   ],
   "source": [
    "# Review data types of our previously identified numeric features\n",
    "df[num_columns].info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Change all the categorical features to 'category' data type\n",
    "dw.convert_dtypes(df, cat_columns, 'category')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 41188 entries, 0 to 41187\n",
      "Data columns (total 11 columns):\n",
      " #   Column       Non-Null Count  Dtype   \n",
      "---  ------       --------------  -----   \n",
      " 0   job          41188 non-null  category\n",
      " 1   marital      41188 non-null  category\n",
      " 2   education    41188 non-null  category\n",
      " 3   default      41188 non-null  category\n",
      " 4   housing      41188 non-null  category\n",
      " 5   loan         41188 non-null  category\n",
      " 6   contact      41188 non-null  category\n",
      " 7   month        41188 non-null  category\n",
      " 8   day_of_week  41188 non-null  category\n",
      " 9   poutcome     41188 non-null  category\n",
      " 10  y            41188 non-null  category\n",
      "dtypes: category(11)\n",
      "memory usage: 444.9 KB\n"
     ]
    }
   ],
   "source": [
    "# Review the updated data types for our categorical features\n",
    "df[cat_columns].info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Change all the numeric features to 'float' data type\n",
    "dw.convert_dtypes(df, num_columns, 'float')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 41188 entries, 0 to 41187\n",
      "Data columns (total 10 columns):\n",
      " #   Column          Non-Null Count  Dtype  \n",
      "---  ------          --------------  -----  \n",
      " 0   age             41188 non-null  float64\n",
      " 1   duration        41188 non-null  float64\n",
      " 2   campaign        41188 non-null  float64\n",
      " 3   pdays           41188 non-null  float64\n",
      " 4   previous        41188 non-null  float64\n",
      " 5   emp.var.rate    41188 non-null  float64\n",
      " 6   cons.price.idx  41188 non-null  float64\n",
      " 7   cons.conf.idx   41188 non-null  float64\n",
      " 8   euribor3m       41188 non-null  float64\n",
      " 9   nr.employed     41188 non-null  float64\n",
      "dtypes: float64(10)\n",
      "memory usage: 3.1 MB\n"
     ]
    }
   ],
   "source": [
    "# Review the updated data types for our numeric features\n",
    "df[num_columns].info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load Data Units and Time Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load data with mixed data units of measurement, and different date/time formats\n",
    "df_data_time = pd.read_csv('data/df_data_time.csv', index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>67.12 mB</td>\n",
       "      <td>5.19 GB</td>\n",
       "      <td>45161.23615</td>\n",
       "      <td>2019-09-11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>117.02mB</td>\n",
       "      <td>2.34 GB</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>2019-07-13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>39.61 MB</td>\n",
       "      <td>52.94 MB</td>\n",
       "      <td>45161.23608</td>\n",
       "      <td>2021-02-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>56.11 giga</td>\n",
       "      <td>7.97 GB</td>\n",
       "      <td>45161.21538</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9.84 Gigabytes</td>\n",
       "      <td>26.23 GB</td>\n",
       "      <td>45160.48826</td>\n",
       "      <td>2019-12-23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.35 GB</td>\n",
       "      <td>45160.78181</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>14.37 Gb</td>\n",
       "      <td>1.31 TB</td>\n",
       "      <td>45161.23658</td>\n",
       "      <td>2020-09-25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>63.37mb</td>\n",
       "      <td>2.65 MB</td>\n",
       "      <td>45139.22113</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>27.64gb</td>\n",
       "      <td>25.84 GB</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019-05-18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0 B</td>\n",
       "      <td>39.38 GB</td>\n",
       "      <td>45160.64827</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                A         B            C           D\n",
       "0        67.12 mB   5.19 GB  45161.23615  2019-09-11\n",
       "1        117.02mB   2.34 GB      0.00000  2019-07-13\n",
       "2        39.61 MB  52.94 MB  45161.23608  2021-02-02\n",
       "3      56.11 giga   7.97 GB  45161.21538         NaN\n",
       "4  9.84 Gigabytes  26.23 GB  45160.48826  2019-12-23\n",
       "5             NaN   2.35 GB  45160.78181         NaN\n",
       "6        14.37 Gb   1.31 TB  45161.23658  2020-09-25\n",
       "7         63.37mb   2.65 MB  45139.22113           0\n",
       "8         27.64gb  25.84 GB          NaN  2019-05-18\n",
       "9             0 B  39.38 GB  45160.64827         NaN"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the messy data that mixes numbers and strings, mixes units of measurement, the incconsistent syntax, NaNs, and 0's\n",
    "df_data_time[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 19 entries, 0 to 18\n",
      "Data columns (total 4 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   A       18 non-null     object \n",
      " 1   B       19 non-null     object \n",
      " 2   C       18 non-null     float64\n",
      " 3   D       16 non-null     object \n",
      "dtypes: float64(1), object(3)\n",
      "memory usage: 760.0+ bytes\n"
     ]
    }
   ],
   "source": [
    "# Review the data types, note the objects and lack of datetime formats\n",
    "df_data_time.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Crate lists of columns we want to convert\n",
    "data_columns = ['A', 'B']\n",
    "time_columns = ['C', 'D']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Convert Data Values\n",
    "\n",
    "`dw.convert_data_values()` converts mixed data values (ex: GB, MB, KB) to a common unit of measurement.\n",
    "\n",
    "This function converts values in the specified columns of the input DataFrame\n",
    "to the desired target unit. If `inplace` is set to True, the conversion is done\n",
    "in place, modifying the original DataFrame. If `inplace` is False (default), a\n",
    "new DataFrame with the converted values is returned. The string suffix is\n",
    "dropped and the column is converted to a float. It handles inconsistent suffix\n",
    "strings, with or without spaces after the numbers (ex: '10GB', '10 Gb'). A\n",
    "variety of spelling options are supported (ex: 'GB', 'Gigabytes'), but you\n",
    "can pass a custom dictionary as `conversion_dict` if desired. To display a\n",
    "summary of the changes made, set `show_results` to True.\n",
    "\n",
    "Use this to clean up messy data that has a variety of units of measurement\n",
    "appended as text strings to the numeric values. The result will be columns\n",
    "with a common unit of measurement as floats (with no text suffixes)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert values in specified columns to GB and assign to a new df\n",
    "df_data = dw.convert_data_values(df_data_time, data_columns, target_unit='GB')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.065547</td>\n",
       "      <td>5.190000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.114277</td>\n",
       "      <td>2.340000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.038682</td>\n",
       "      <td>0.051699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>56.110000</td>\n",
       "      <td>7.970000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9.840000</td>\n",
       "      <td>26.230000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.350000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>14.370000</td>\n",
       "      <td>1341.440000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.061885</td>\n",
       "      <td>0.002588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>27.640000</td>\n",
       "      <td>25.840000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>39.380000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           A            B\n",
       "0   0.065547     5.190000\n",
       "1   0.114277     2.340000\n",
       "2   0.038682     0.051699\n",
       "3  56.110000     7.970000\n",
       "4   9.840000    26.230000\n",
       "5        NaN     2.350000\n",
       "6  14.370000  1341.440000\n",
       "7   0.061885     0.002588\n",
       "8  27.640000    25.840000\n",
       "9   0.000000    39.380000"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the converted data in the new dataframe\n",
    "df_data[['A','B']][:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 19 entries, 0 to 18\n",
      "Data columns (total 2 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   A       18 non-null     float64\n",
      " 1   B       19 non-null     float64\n",
      "dtypes: float64(2)\n",
      "memory usage: 456.0 bytes\n"
     ]
    }
   ],
   "source": [
    "# Review the converted data, note the dtype is now float\n",
    "df_data[['A','B']].info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original: 67.12 mB -> Converted: 67.12000000 MB\n",
      "Original: 117.02mB -> Converted: 117.02000000 MB\n",
      "Original: 39.61 MB -> Converted: 39.61000000 MB\n",
      "Original: 56.11 giga -> Converted: 57456.64000000 MB\n",
      "Original: 9.84 Gigabytes -> Converted: 10076.16000000 MB\n",
      "Original: NaN -> Converted: NaN\n",
      "Original: 14.37 Gb -> Converted: 14714.88000000 MB\n",
      "Original: 63.37mb -> Converted: 63.37000000 MB\n",
      "Original: 27.64gb -> Converted: 28303.36000000 MB\n",
      "Original: 0 B -> Converted: 0.00000000 MB\n",
      "Original: 1.2 GB -> Converted: 1228.80000000 MB\n",
      "Original: 696.27 Mega -> Converted: 696.27000000 MB\n",
      "Original: 766.18 Megabytes -> Converted: 766.18000000 MB\n",
      "Original: 868.81 mega -> Converted: 868.81000000 MB\n",
      "Original: 0B -> Converted: 0.00000000 MB\n",
      "Original: 150.35 megabyte -> Converted: 150.35000000 MB\n",
      "Original: 8.88gigabyte -> Converted: 9093.12000000 MB\n",
      "Original: 0b -> Converted: 0.00000000 MB\n",
      "Original: 198.58giga -> Converted: 203345.92000000 MB\n",
      "Original: 5.19 GB -> Converted: 5314.56000000 MB\n",
      "Original: 2.34 GB -> Converted: 2396.16000000 MB\n",
      "Original: 52.94 MB -> Converted: 52.94000000 MB\n",
      "Original: 7.97 GB -> Converted: 8161.28000000 MB\n",
      "Original: 26.23 GB -> Converted: 26859.52000000 MB\n",
      "Original: 2.35 GB -> Converted: 2406.40000000 MB\n",
      "Original: 1.31 TB -> Converted: 1373634.56000000 MB\n",
      "Original: 2.65 MB -> Converted: 2.65000000 MB\n",
      "Original: 25.84 GB -> Converted: 26460.16000000 MB\n",
      "Original: 39.38 GB -> Converted: 40325.12000000 MB\n",
      "Original: 0 B -> Converted: 0.00000000 MB\n",
      "Original: 755.21 MB -> Converted: 755.21000000 MB\n",
      "Original: 10.67 GB -> Converted: 10926.08000000 MB\n",
      "Original: 354.73 MB -> Converted: 354.73000000 MB\n",
      "Original: 0 B -> Converted: 0.00000000 MB\n",
      "Original: 3.27 GB -> Converted: 3348.48000000 MB\n",
      "Original: 1.57 GB -> Converted: 1607.68000000 MB\n",
      "Original: 0 B -> Converted: 0.00000000 MB\n",
      "Original: 312.59 KB -> Converted: 0.30526367 MB\n"
     ]
    }
   ],
   "source": [
    "# Convert data values to MB in place, modifying the existing df, and show a summary of the changes\n",
    "dw.convert_data_values(df_data_time, data_columns, target_unit='MB', inplace=True, show_results=True, decimal=8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Convert Time Values\n",
    "\n",
    "`dw.convert_time_values()` converts time values in specified columns of a DataFrame to a target format.\n",
    "\n",
    "This function converts time values in the specified columns of the input\n",
    "DataFrame to the desired target format. If `inplace` is set to True, the\n",
    "conversion is done in place, modifying the original DataFrame. If `inplace`\n",
    "is False (default), a new DataFrame with the converted values is returned.\n",
    "\n",
    "The function can handle time values in various formats, including:\n",
    "1. Excel serial format (e.g., '45161.23458')\n",
    "2. String format (e.g., 'YYYY-MM-DD')\n",
    "3. UNIX epoch in milliseconds (e.g., '1640304000000.0')\n",
    "\n",
    "If your format is not supported, you can define `pattern_list` as a list of\n",
    "custom datetime patterns.\n",
    "\n",
    "If `zero_to_nan` is set to True, values of '0', '0.0', '0.00', 0, 0.0, or 0.00\n",
    "will be replaced with NaN. Otherwise, zero values will be detected as a\n",
    "Unix Epoch format with value 1970-01-01 00:00:00.\n",
    "\n",
    "You can use the default `target_format` of '%Y-%m-%d %H:%M:%S', or specify\n",
    "a different format. To display a summary of the changes made, set\n",
    "`show_results` to True."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original: 45161.23615 (Excel Serial) -> Converted: 2023-08-25 05:40:03\n",
      "Original: 0.0 (Zero) -> Converted: NaT\n",
      "Original: 45161.23608 (Excel Serial) -> Converted: 2023-08-25 05:39:57\n",
      "Original: 45161.21538 (Excel Serial) -> Converted: 2023-08-25 05:10:08\n",
      "Original: 45160.48826 (Excel Serial) -> Converted: 2023-08-24 11:43:05\n",
      "Original: 45160.78181 (Excel Serial) -> Converted: 2023-08-24 18:45:48\n",
      "Original: 45161.23658 (Excel Serial) -> Converted: 2023-08-25 05:40:40\n",
      "Original: 45139.22113 (Excel Serial) -> Converted: 2023-08-03 05:18:25\n",
      "Original: nan -> Converted: NaT\n",
      "Original: 45160.64827 (Excel Serial) -> Converted: 2023-08-24 15:33:30\n",
      "Original: 45161.2346 (Excel Serial) -> Converted: 2023-08-25 05:37:49\n",
      "Original: 45160.88611 (Excel Serial) -> Converted: 2023-08-24 21:15:59\n",
      "Original: 45161.23702 (Excel Serial) -> Converted: 2023-08-25 05:41:18\n",
      "Original: 45161.23482 (Excel Serial) -> Converted: 2023-08-25 05:38:08\n",
      "Original: 45155.64277 (Excel Serial) -> Converted: 2023-08-19 15:25:35\n",
      "Original: 45161.23592 (Excel Serial) -> Converted: 2023-08-25 05:39:43\n",
      "Original: 45155.85252 (Excel Serial) -> Converted: 2023-08-19 20:27:37\n",
      "Original: 45160.83184 (Excel Serial) -> Converted: 2023-08-24 19:57:50\n",
      "Original: 45161.13627 (Excel Serial) -> Converted: 2023-08-25 03:16:13\n",
      "Original: 2019-09-11 (Standard Datetime String) -> Converted: 2019-09-11 00:00:00\n",
      "Original: 2019-07-13 (Standard Datetime String) -> Converted: 2019-07-13 00:00:00\n",
      "Original: 2021-02-02 (Standard Datetime String) -> Converted: 2021-02-02 00:00:00\n",
      "Original: nan -> Converted: NaT\n",
      "Original: 2019-12-23 (Standard Datetime String) -> Converted: 2019-12-23 00:00:00\n",
      "Original: nan -> Converted: NaT\n",
      "Original: 2020-09-25 (Standard Datetime String) -> Converted: 2020-09-25 00:00:00\n",
      "Original: 0 (Zero) -> Converted: NaT\n",
      "Original: 2019-05-18 (Standard Datetime String) -> Converted: 2019-05-18 00:00:00\n",
      "Original: nan -> Converted: NaT\n",
      "Original: 2020-12-15 (Standard Datetime String) -> Converted: 2020-12-15 00:00:00\n",
      "Original: 2021-05-11 (Standard Datetime String) -> Converted: 2021-05-11 00:00:00\n",
      "Original: 2020-04-30 (Standard Datetime String) -> Converted: 2020-04-30 00:00:00\n",
      "Original: 2019-04-17 (Standard Datetime String) -> Converted: 2019-04-17 00:00:00\n",
      "Original: 2019-12-20 (Standard Datetime String) -> Converted: 2019-12-20 00:00:00\n",
      "Original: 2020-08-19 (Standard Datetime String) -> Converted: 2020-08-19 00:00:00\n",
      "Original: 2017-11-27 (Standard Datetime String) -> Converted: 2017-11-27 00:00:00\n",
      "Original: 2020-11-20 (Standard Datetime String) -> Converted: 2020-11-20 00:00:00\n",
      "Original: 2019-07-18 (Standard Datetime String) -> Converted: 2019-07-18 00:00:00\n"
     ]
    }
   ],
   "source": [
    "# Convert time values in specified columns to the default format\n",
    "df_time = dw.convert_time_values(df_data_time, time_columns, show_results=True,\n",
    "                                zero_to_nan=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2023-08-25 05:40:03</td>\n",
       "      <td>2019-09-11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaT</td>\n",
       "      <td>2019-07-13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2023-08-25 05:39:57</td>\n",
       "      <td>2021-02-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2023-08-25 05:10:08</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2023-08-24 11:43:05</td>\n",
       "      <td>2019-12-23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2023-08-24 18:45:48</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2023-08-25 05:40:40</td>\n",
       "      <td>2020-09-25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2023-08-03 05:18:25</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>NaT</td>\n",
       "      <td>2019-05-18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2023-08-24 15:33:30</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    C          D\n",
       "0 2023-08-25 05:40:03 2019-09-11\n",
       "1                 NaT 2019-07-13\n",
       "2 2023-08-25 05:39:57 2021-02-02\n",
       "3 2023-08-25 05:10:08        NaT\n",
       "4 2023-08-24 11:43:05 2019-12-23\n",
       "5 2023-08-24 18:45:48        NaT\n",
       "6 2023-08-25 05:40:40 2020-09-25\n",
       "7 2023-08-03 05:18:25        NaT\n",
       "8                 NaT 2019-05-18\n",
       "9 2023-08-24 15:33:30        NaT"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the converted data in the new dataframe, notice the consistent date/time format\n",
    "df_time[['C','D']][:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 19 entries, 0 to 18\n",
      "Data columns (total 2 columns):\n",
      " #   Column  Non-Null Count  Dtype         \n",
      "---  ------  --------------  -----         \n",
      " 0   C       17 non-null     datetime64[ns]\n",
      " 1   D       15 non-null     datetime64[ns]\n",
      "dtypes: datetime64[ns](2)\n",
      "memory usage: 456.0 bytes\n"
     ]
    }
   ],
   "source": [
    "# Review the converted data, note the dtype is now a pandas datetime object\n",
    "df_time[['C','D']].info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Split Outliers\n",
    "\n",
    "`dw.split_outliers()` splits a DataFrame into two based on the presence of outliers.\n",
    "\n",
    "This function identifies outliers in the specified columns of the\n",
    "input DataFrame using the Interquartile Range (IQR) method. It then\n",
    "splits the DataFrame into two: one containing rows without outliers\n",
    "and another containing only the rows with outliers.\n",
    "\n",
    "Use this function when you need to separate outliers from the main\n",
    "data for further analysis or processing."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Specify columns we want to evaluate for outliers, this can be any set of numeric columns\n",
    "skew_columns = ['duration', 'campaign']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot histograms of skewed variables, dimensioned by the target variable\n",
    "dw.plot_charts(df, plot_type='cont', cont_cols=skew_columns, hue='y', multiple='stack')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Split the dataframe based on the default IQR multiplier of 1.5, looking across the specified columns\n",
    "df_no_outliers, df_outliers = dw.split_outliers(df, columns=skew_columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "df_no_outliers: 35,963\n",
      "df_outliers: 5,225\n"
     ]
    }
   ],
   "source": [
    "# Compare the size of the 2 dataframes\n",
    "print(f'df_no_outliers: {len(df_no_outliers):,.0f}')\n",
    "print(f'df_outliers: {len(df_outliers):,.0f}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot histogram of skewed variables, but now in df with no outliers, dimensioned by the target variable\n",
    "dw.plot_charts(df_no_outliers, plot_type='cont', cont_cols=skew_columns, hue='y', multiple='stack')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Reduce Multicollinearity\n",
    "\n",
    "`dw.reduce_multicollinearity()` reduces multicollinearity in a DataFrame by removing highly correlated features.\n",
    "\n",
    "This function iteratively evaluates pairs of features in a DataFrame based on\n",
    "their correlation to each other and to a specified target column. If two\n",
    "features are highly correlated (above `corr_threshold`), the one with the lower\n",
    "correlation to the target column is removed. The number of NaN and/or zero\n",
    "values can also be considered (prefering removal of features with more) by\n",
    "setting `consider_nan` or `consider_zero` to True. The threshold for\n",
    "significant differences (`diff_threshold`) can also be adjusted. Sometimes it\n",
    "might appear as if the correlations are the same, but it says one is greater.\n",
    "Adjust `decimal` to a larger number to see more precision in the correlation.\n",
    "\n",
    "Use this function to remove redundant features, and reduce a large feature set\n",
    "to a smaller one that contains the features most correlated with the target.\n",
    "This should improve the model's ability to learn from the dataset, improve\n",
    "performance, and increase interpretability of results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Evaluating pair: 'nr.employed' and 'emp.var.rate' (0.91) - 58 kept features\n",
      " - Correlation with target: 0.3530, 0.2974\n",
      " - NaN/0 counts: 0, 0\n",
      " - Keeping 'nr.employed' (higher correlation, lower or equal count)\n",
      "\n",
      "Evaluating pair: 'nr.employed' and 'euribor3m' (0.95) - 57 kept features\n",
      " - Correlation with target: 0.3530, 0.3063\n",
      " - NaN/0 counts: 0, 0\n",
      " - Keeping 'nr.employed' (higher correlation, lower or equal count)\n",
      "\n",
      "Evaluating pair: 'previously_contacted' and 'pdays' (0.84) - 56 kept features\n",
      " - Correlation with target: 0.3236, 0.2657\n",
      " - NaN/0 counts: 38714, 38729\n",
      " - Keeping 'previously_contacted' (higher correlation, lower or equal count)\n",
      "\n",
      "Evaluating pair: 'previously_contacted' and 'poutcome_success' (0.95) - 55 kept features\n",
      " - Correlation with target: 0.3236, 0.3155\n",
      " - NaN/0 counts: 38714, 38850\n",
      " - Keeping 'previously_contacted' (higher correlation, lower or equal count)\n",
      "\n",
      "Evaluating pair: 'previous' and 'poutcome_nonexistent' (-0.88) - 54 kept features\n",
      " - Correlation with target: 0.2287, 0.1916\n",
      " - NaN/0 counts: 34710, 5485\n",
      " - Keeping 'poutcome_nonexistent' (higher correlation, significant diff: 0.8420 > 0.1000)\n",
      "\n",
      "Evaluating pair: 'poutcome_nonexistent' and 'poutcome_failure' (-0.85) - 53 kept features\n",
      " - Correlation with target: 0.1916, 0.0298\n",
      " - NaN/0 counts: 5485, 36055\n",
      " - Keeping 'poutcome_nonexistent' (higher correlation, lower or equal count)\n",
      "\n",
      "Evaluating pair: 'marital_single' and 'marital_married' (-0.77) - 52 kept features\n",
      " - Correlation with target: 0.0539, 0.0439\n",
      " - NaN/0 counts: 28907, 15858\n",
      " - Keeping 'marital_married' (higher correlation, significant diff: 0.4514 > 0.1000)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Remove redundant features, keeping the ones with the strongest correlation to target\n",
    "df_reduced = dw.reduce_multicollinearity(df_enc, 'subscribed_enc', corr_threshold=0.70,\n",
    "                                         decimal=4, consider_nan=True, consider_zero=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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T5uxia9SoocqVK2vixImaOnWqTp06pSVLlthlEOWi2K60g+pVrVpVUt4G1QMApGf1GAEAAACFRW6mbssu1sXFRd9884327dun8uXLq0ePHurXr59dplQuqu2y1aB6AICMWd0jIK2tW7cqMjJScXFx8vT0VGhoqJo3b26LXQMAAORZbq4y5yT2/vvv108//WTeZvTo0WrZsmUBtSZ3ueYm9l5p14QJE3TlyhXVqlVLktSzZ0+LQfUkaeHChZLuDKo3ZcoU87Zubm5q2bKlXcZrAIDCIk+FgG3btqlfv346deqUJFkMHHjfffdp6dKlatq0ad6zBAAAyKPUq8ypFyuyusqcXeyBAwdUtWpVubi46Ntvv9WSJUsUERGR/42wItfcxN4r7XJxcdGCBQu0YEH6wblSCwCpJk+erMmTJxdQZgBQNFhdCDh8+LBat26tGzdu6LHHHtPDDz+sgIAARUdHa9OmTfrpp5/Upk0b7dixQ7Vr17ZlzgAAALmWm6vMWcVK0qpVq/T+++/r5s2bqlevnr7++mvVrVu3IJtjVlTbBQDIP1ZPH/jMM89ozZo1Wrt2rdq2bZtu/fr169WxY0c9+eST+vzzz/OcaGHD9IEAAAAAbIXpA+2rqE0faPVggZs3b9bTTz+dYRFAktq2baunn35amzZtsvYlAAAAAACAjVldCIiNjVVwcHCWMcHBwRYj0wIAAAAAAPuyeoyAwMBA7dixI8uYnTt3KjAw0NqXAAAAAJCP/kr4yN4p5FhgyYwHwcxIYWlXbtoE2JLVPQI6duyozZs3a8KECbp586bFups3b2rSpEnatGmTOnXqlOckAQAAAACAbVjdI2DChAn69ttvNWPGDH3wwQdq3Lix/Pz8FBMTo927d+vy5cuqUqWKJkyYYMt8AQAAAABAHlhdCChTpox27NihUaNG6fPPP9f3339vXleiRAn169dPb775pnx8fGySKAAAAAAAyDurCwGS5OvrqyVLluiDDz7QsWPHFBcXJ09PT9WsWVMuLi62yhEAAAAAANhIngoBqVxcXBQSEmKLXQEAAAD3pJgby+ydQo74ufe1dwoA7nFWDxYIAAAAAAAKnxz3CHjkkUdkMpm0fPlyVahQQY888kiOtjOZTIqIiLA6QQAAAAAAYDs5LgRs3rxZJpNJN27cMP+cEyaTyarEAAAAAACA7eW4EJCSkpLlzwAAAIAkXbn5mb1TyLEyJZ61dwoAUOAYIwAAAAAAAAdi9awB/fv3V+fOndWxY8dMY7799lutXr1aS5YssfZlAAAAJEn/3PrC3inkWGnXZ3IcW1jalZs2AQDubVb3CFi2bJkiIyOzjNm/f7+WL19u7UsAAAAAAAAby9dbA27evKlixazudAAAAAAAAGwsT2fpmc0IYBiGzp8/rx9++EGBgYF5eQkAAAAAAGBDueoR4OTkJGdnZzk7O0uSJk+ebP457aNYsWIKDg7W3r171b1793xJHAAAAAAA5F6uegQ89NBD5l4AW7ZsUcWKFVW5cuV0cc7OzvLx8dEjjzyi8PBwmyQKAAAAAADyLleFgM2bN5ufOzk5qV+/fpo4caKtcwIAAAAAAPnE6jECUlJSbJkHAAAAAAAoAPk6awAAAAAAALi35GnWgOTkZK1atUo///yz/vrrL926dStdjMlkUkRERF5eBgAAAAAA2IjVhYCEhAS1bt1aO3bskGEYMplMMgzDvD7158ymGAQAAAAAAAXP6lsDpk2bpu3bt2vKlCn6+++/ZRiGJk+erKioKH3xxReqUqWKunbtmmEvAQAAAAAAYB9WFwJWr16tBx54QOPHj5ePj495uZ+fn7p27apNmzbp559/1uzZs22SKAAAAAAAyDurCwHnzp3TAw888P935ORkcfW/QoUKat++vZYvX563DAEAAAAAgM1YXQgoWbKknJz+/+ZeXl6KioqyiPH399e5c+eszw4AAAAAANiU1YWASpUqWZzk16lTRxs3bjT3CjAMQxEREQoICMh7lgAAAAAAwCasLgQ8+uij2rRpk5KSkiRJffr00blz59S0aVO9+uqratGihSIjI/XUU0/ZLFkAAAAAAJA3VhcCwsPDNXLkSF2+fFmS1L9/fw0dOlT79+/X//73P23fvl1PPvmkJk+ebKtcM7VgwQJVrlxZJUqUUJMmTbRr164s47/88kvVrFlTJUqUUEhIiL7//nuL9YZhaOLEiQoICJCbm5vCwsJ08uTJ/GwCAAAAAAAFwupCwH333afRo0dbdP1/5513FB0dre3bt+uvv/7Sl19+KXd3d5skmpkvvvhCI0aM0KRJk7R3717Vq1dPbdq00aVLlzKM37Ztm5599lkNGDBA+/btU+fOndW5c2cdOnTIHDNr1izNnz9fCxcu1M6dO1WyZEm1adNGN2/ezNe2AAAAAACQ34rZeodly5ZV2bJlbb3bTM2ZM0fh4eHq16+fJGnhwoX67rvvtGTJEo0ZMyZd/Lx589S2bVu9+uqrkqTXX39dGzZs0LvvvquFCxfKMAzNnTtX48ePV6dOnSRJK1askJ+fn77++mt17949V/mlpKQoJSUlj60EAABGisneKeRYbv7vLyztKoptkopmu4pim6Si2a5cnScYzvmXiI3lpl2mQtKuwnJOl9M8bV4IKEiJiYnas2ePxo4da17m5OSksLAwbd++PcNttm/frhEjRlgsa9Omjb7++mtJ0unTpxUdHa2wsDDzei8vLzVp0kTbt2/PtBBw69Yti+kT4+LizPsrVaqUVe0DAAD/X7IRbO8Ucuyq6c8cxxaWduWuTVXyMRPbupaLdiWl1MzHTGwn3innbbqdcn8+ZmJb/xbBduWmTWVuP5aPmdjWn3/mvF3VkzvnXyI2lJs22dP169dzFJfjQsAjjzxiVSImk0kRERFWbZudv//+W8nJyfLz87NY7ufnp2PHjmW4TXR0dIbx0dHR5vWpyzKLycjMmTM1ZcqUXLfhnnD9vL0zyLlSQTmLS4zJ3zxsqbhf9jGpkv7OvzxsrZhvzuKKYpskKflK/uVha85lchaXci1f07ApJ++cxxbFdhmx+ZqGTZm8chzqbCqdj4nYT1Fsl7PJx94p5ItiTjk8XhYiLk65+L+tECmK7SrlUt7eKeQLnxIV7Z2CQ8pxIWDz5s1WvYDJVDi65eTV2LFjLXoaxMXFKSgoSMHBwfL09LRjZtlL2fiuvVPIMad6c3IUZ5z/Np8zsR1T0As5jjX+/iUfM7Etk2+/HMUVxTZJkvFPxr2S7kWm0j1yFnhjbf4mYkvuDXIeWxTbdfP77GPuFSXq2zsDAACKjNSe6dnJcSHgXrwnwtfXV87OzoqJsbz6GxMTI39//wy38ff3zzI+9d+YmBiLgRBjYmIUGhqaaS6urq5ydXVNt9zJyUlOTlaPyVhAku2dQI7l9L00TPfe5zUzplx8PgyTkY+Z2FZO21UU2yQV0XY5FZ42KTfH3aLYrqLYJgAAkK2cni8V6v99ixcvroYNG1rcepCSkqKIiAg1bdo0w22aNm2a7laFDRs2mOODg4Pl7+9vERMXF6edO3dmuk8AAAAAAAoLmw0WePXqVSUkJCgoKIf3cNvIiBEj1KdPHzVq1EiNGzfW3LlzlZCQYJ5FoHfv3ipfvrxmzpwpSXrxxRfVsmVL/e9//1P79u31+eef6/fff9eiRYsk3bmV4aWXXtK0adN03333KTg4WBMmTFBgYKA6d+5coG0DAAAAAMDW8tQjIDY2Vi+++KL8/PxUtmxZBQf//1Fvd+7cqXbt2mnPnj15TjIrzzzzjN566y1NnDhRoaGhioyM1Pr1682D/Z07d05RUVHm+GbNmmnlypVatGiR6tWrp6+++kpff/216tSpY44ZNWqUhg8froEDB+o///mP4uPjtX79epUoUSJf2wIAAAAAQH6zukfA1atX1axZM504cUINGjRQ2bJldfToUfP6unXrauvWrfr000/VsGFDmySbmWHDhmnYsGEZrstokMOuXbuqa9eume7PZDJp6tSpmjp1qq1SBAAAAADgnmB1j4DJkyfrxIkT5q71d59Yu7m5qWXLltq4cWOekwQAAAAAALZhdSFg7dq16tChg7p165ZpTOXKlXXhwgVrXwIAAAAAANiY1YWAqKgo1a5dO8sYV1dXJSQkWPsSAAAAAADAxqwuBJQpU0bnz5/PMubYsWMKCAiw9iUAAAAAAICNWV0IeOihh/TNN99k2vX/yJEjWr9+vcLCwqxODgAAAAAA2JbVswa89tpr+uabb9S8eXPNmDFDf//9tyTp6NGj2rZtm1577TW5urrq1VdftVmyAAAgB0o8Ye8MAADAPczqQkBISIi++OIL9erVS71795YkGYahOnXqyDAMlSpVSqtWrdJ9991ns2QBAAAAAEDeWF0IkKSOHTvq9OnTWr58uXbu3KmrV6/K09NTTZo0Ub9+/eTr62urPAEAAAAAgA1YXQhYsWKF/Pz81KZNG7388su2zAkAAAAAAOQTqwsBAwYM0LBhw9SmTRtb5gMAuFe5d7F3BvmjqLYLAAAgE1bPGhAQEKCkpCRb5gIAAAAAAPKZ1YWAjh07asOGDbp165Yt8wEAAAAAAPnI6kLA9OnTVbJkST355JM6fPiwLXMCAAAAAAD5xOoxAurXr69bt24pMjJS69evV4kSJVSuXDmZTCaLOJPJpD/++CPPiQIAAAAAgLyzuhCQkpKi4sWLq2LFihbLDcPI8mcAAAAAAGA/VhcCzpw5Y8M0AAAAAABAQbB6jID+/fvr7bfftmUuAAAAAAAgn1ldCFi5cqUuXbpky1wAAMA9aOvWrapXr57c3d0VGhqq7du3Wx1/5swZmUwmeXh4mB9PPPFEfjcBAACkYXUhoGrVqoqKirJlLgAA4B5z9epVdejQQcOGDdM///yjoUOHqkOHDrp27Vqe4i9cuKD4+HjFx8dr3bp1+d8QAABgZvUYAf3799cbb7yhixcvqnz58rbMCQAKPZNPb3unANjEmjVrVL58eYWHh0uSwsPDNXfuXK1Zs0b9+vXLczwAACh4VhcCnnrqKW3atEnNmjXTqFGj9J///Ed+fn7ppg+UlG5mAQAAUDgcOHBAoaGhFstCQ0N14MCBPMXXqVNHSUlJaty4sWbNmqWaNWvaMm0AAJAFqwsBVapUkclkkmEYeuGFFzKNM5lMSkpKsvZlAACAHcXHx8vb29timbe3t65fv25VvK+vr3bu3Kn69esrISFBr7/+uh577DEdPnxYnp6e+dEEAABwF6vHCOjdu7d69+6tPn36mJ9n9OjVq5ct8wUAFBG2HIBuxowZFoPPlSxZUiaTSatXr87vZuQqz9zG26Ndn376qfn17r//fnl4eCg2NtYiJjY2VqVKlcpw++ziPTw81LhxY7m4uMjb21tvvfWWbt++rW3btuVPgwAAQDpWFwKWLVumpUuX5ugBAEBath6Abty4ceaB5+Lj47VixQp5eXnp8ccfL7hG5SDP3Mbbo109evQwv97hw4dVt25dRUZGWsRERkYqJCQkw+1zG28ymTK8rRAAAOQfqwsBAABYK+2Acq6urgoPD5e/v7/WrFljk/jFixfr2WeflZubW342I895FoZ2denSRRcuXNDixYuVmJioxYsXKyoqSl26dLEqfufOnTp69KiSk5MVHx+v0aNHy2QyqWnTpgXWJgAAHJ3VYwSktXXrVkVGRiouLk6enp4KDQ1V8+bNbbFrAEARlF8D0El3pqX78ccftWvXLlulm2NFsV0+Pj5at26dhgwZomHDhql69epat26dSpcuLUk6d+6cateurSNHjqhixYrZxv/5558aP368oqOj5e7uriZNmuinn36Sl5dXgbYLAABHlqdCwLZt29SvXz+dOnVKkmQYhrl733333aelS5dS4QdsyFT2eXunYHNFsU3Inq0HoEtr6dKlqlu3rho2bGirdHOsqLarRYsWmRYzKlasqPj4+BzHP/vss3r22WdtniMAAMg5q28NOHz4sFq3bq2TJ08qLCxM06dP19KlSzVjxgw99thjOnHihNq0aaMjR47YMl8AQCGU3wPQpTIMQ0uXLtWAAQNs24BMFNV2AQCAos3qQsDUqVOVmJio77//Xj/++KPGjBmjPn36aPTo0Vq/fr2+//573bx5U1OnTrVlvgCAQqigBqCLiIhQVFSUevbsacv0M1VU2wUAAIo2qwsBmzdv1tNPP622bdtmuL5t27Z6+umntWnTJquTAwAUTbYegC7V4sWL9eSTT6brbl9Qimq7AABA0WJ1ISA2NlbBwcFZxgQHB6fr8ggAQOqAcvPmzZOXl5fmz5+fbgA6Dw8PnTt3Lkfx0p2p+NasWaPnn7ffuBNFtV0AAKBoMRmGYVizYZUqVRQcHKyIiIhMY8LCwvTnn3/qzz//tDrBwiouLk5eXl6KjY2Vp6envdPJUsrPw+2dQo45hb2Tozjj3Jx8zsR2TBVH2DsFFAJbt27VkCFDdPLkSVWvXl3vv/9+poOxRkVF6b///a9+//13RUVFad++fRYj0x86dEivvPKK9uzZoytXruiff/7hSjMAAEARkNPzUKt7BHTs2FGbN2/WhAkTdPPmTYt1N2/e1KRJk7Rp0yZ16tTJ2pcAAOjOFeEOHTpo2LBh+ueffzR06FB16NBB165dyzDeyclJbdu21ddff53hehcXF3Xr1k3Lli3Lt5wBAABw77K6R8CVK1fUpEkTnT59WmXKlFHjxo3l5+enmJgY7d69W5cvX1aVKlW0a9cu+fj42Drvex49AvIHPQLgiBYvXqy3335bhw4dMi+7//77NXLkSPXr1y/LbU0mU7oeAanOnDmj4OBgegQAAAAUETk9Dy1m7QuUKVNGO3bs0KhRo/T555/r+++/N68rUaKE+vXrpzfffNMhiwAAYEsHDhxIdyIfGhqa6TztAAAAQFasLgRIkq+vr5YsWaIPPvhAx44dU1xcnDw9PVWzZk25uLjYKkcAcGjx8fHprth7e3vr+vXr9kkIAAAAhVquxwiYPn26xo0bp9u3b5uXubi4KCQkRM2bN1dISIgMw9Brr72mN954w6bJAoAj+PTTT+Xh4SEPDw/df//98vDwSDcDS2xsrEqVKmWnDAEAAFCY5apHwM8//6yJEydq1qxZWV7xL168uMqUKaNXX31VTZo00cMPP5znRIHc4L57FGY9evRQjx49zD8vXrxYc+fOtYiJjIzUiBF8zgEAAJB7ueoRsGLFCpUuXVrDhg3LNnbo0KHy8fHR0qVLrU4OQP7aunWr6tWrJ3d3d4WGhmr79u2ZxkZFRaljx44KDAyUyWRSZGRkprHjxo2TyWTKdNT6/FQU29SlSxdduHBBixcvVmJiohYvXqyoqCh16dIl021u3rxpntElMTFRN2/eVEpKiiTJMAzdvHlTt27dkiTdunVLN2/elJVjxwIAAKCQyVUhYNu2bQoLC5Orq2u2sa6urgoLC9PWrVutTg5A/rH1lHSp9u/fr3Xr1ikgIMD2SWejKLZJknx8fLRu3TrNmzdPXl5emj9/vtatW6fSpUtLks6dOycPDw+dO3fOvI2bm5vc3NwkSU2aNJGbm5u2bNkiSTp79qzc3NxUs2ZNSZK/v7/c3Nx09uzZAm4ZAAAA7CFXhYC//vpLVapUyXF8cHCwoqKicp0UgPy3Zs0alS9fXuHh4XJ1dVV4eLj8/f21Zs2aDOP9/Pw0ZMgQNW7cONN9Jicn6/nnn9e7776r4sWL51fqmSqKbUrVokULHThwQP/++6/279+vZs2amddVrFhR8fHxqlixonmZYRjpHq1atZIkVa5cOcP1lStXLuBWAQAAwB5yVQhwcnKyGCQwO7dv35aTU67HIwRQAPJjSrq3335bdevWVcuWLfOYnXWKYpsAAAAAW8vVYIGBgYE6dOhQjuMPHTqk8uXL5zopAPnP1lPS/fnnn3r33Xe1d+9eG2RnnaLYJgAAAMDWcnW5/sEHH9TGjRt15syZbGPPnDmjjRs36qGHHrI2NwA2lN9T0g0cOFDTpk2Tj4+PLdLNkaLYJgAAACC/5aoQMHToUN2+fVtPP/20/v7770zjrly5oq5duyopKUmDBw/Oc5IA8q5Hjx6Kj49XfHy8Dh8+rLp166YbJT8yMlIhISFW7T8iIkIvvfSSfH195evrq/Pnz6t37956+eWXbZB9xopimwAAAID8lqtbAxo0aKCXXnpJc+fOVe3atTVo0CA9/PDDqlChgiTp4sWLioiI0KJFi3T58mWNGDFCDRo0yJfEAeRNly5dNHLkSC1evFi9evXSxx9/nKMp6VKlTklXvHhxOTk56fz58xaxTZs21eTJk/Xkk0/mWxvuVhTbBAAAANhargoBkvS///1PJUqU0OzZszV9+nRNnz7dYr1hGHJ2dtbYsWM1bdo0myUKwLZSp6QbMmSIhg0bpurVq6ebkq527do6cuSIeTT61OnopDtT0knSpk2b1KpVK3NBMJWzs7PKlClj3l9BKIptAgAAAGzNZBiGYc2Gf/zxh5YuXapt27YpOjpa0p25qJs3b66+ffuqatWqNk00I1evXtXw4cO1bt06OTk56amnntK8efPk4eGRafykSZP0008/6dy5cypbtqw6d+6s119/XV5eXuY4k8mUbtvPPvtM3bt3z3FucXFx8vLyUmxsrDw9PXPfuAKU8vNwe6eQY05h79g7BQAAAAC4J+X0PDTXPQJSVa1a1e5X/Hv06KGoqCht2LBBt2/fVr9+/TRw4ECtXLkyw/i//vpLf/31l9566y3Vrl1bZ8+e1aBBg/TXX3/pq6++sohdunSp2rZta/757pHIAQAAAAAojKwuBNjb0aNHtX79eu3evVuNGjWSJL3zzjtq166d3nrrLQUGBqbbpk6dOvq///s/889Vq1bV9OnT1bNnTyUlJalYsf//dnh7e8vf3z//GwIAAAAAQAHK1awB95Lt27fL29vbXASQpLCwMDk5OWnnzp053k9ql4m0RQDpzgwJvr6+aty4sZYsWaLs7qC4deuW4uLiLB4oOrZu3ap69erJ3d1doaGh2r59e6axUVFR6tixowIDA2UymdKNYp+UlKTXXntNQUFB8vT0VJcuXXTp0qV8bgEAAAAA3FFoCwHR0dEqV66cxbJixYrJx8fHPGZBdv7++2+9/vrrGjhwoMXyqVOnatWqVdqwYYOeeuopDRkyRO+8k/W96TNnzpSXl5f5ERQUlLsG4Z519epVdejQQcOGDdM///yjoUOHqkOHDrp27VqG8U5OTmrbtq2+/vrrDNfPnj1b3333nXbs2KGYmBh5eXmpZ8+e+dcAAAAAAEjjnisEjBkzRiaTKcvHsWPH8vw6cXFxat++vWrXrq3JkydbrJswYYKaN2+u+vXra/To0Ro1apRmz56d5f7Gjh2r2NhY8+PuacdQeK1Zs0bly5dXeHi4XF1dFR4eLn9/f61ZsybDeD8/Pw0ZMkSNGzfOdH8vvPCCypcvLzc3N02ZMkUbNmzQmTNn8rEVAAAAAHDHPTdGwCuvvKK+fftmGVOlShX5+/un606dlJSkq1evZntv//Xr19W2bVuVKlVKa9askYuLS5bxTZo00euvv65bt27J1dU1wxhXV9dM16FwO3DggEJDQy2WhYaG6sCBA1btLyUlxeJWk5SUFPPrVK5c2do0AQAAACBH7rlCQNmyZVW2bNls45o2bapr165pz549atiwoSRp48aNSklJMc8FnpG4uDi1adNGrq6uWrt2rUqUKJHta0VGRqp06dKc6Duo+Pj4dLNGeHt76/r161btr3379po3b54ee+wx+fj4aOLEiTKZTIwrAQAAAKBA3HO3BuRUrVq11LZtW4WHh2vXrl3aunWrhg0bpu7du5tnDLh48aJq1qypXbt2SbpTBGjdurUSEhK0ePFixcXFKTo6WtHR0UpOTpYkrVu3Th999JEOHTqkU6dO6f3339eMGTM0fPhwu7UVBevTTz+Vh4eHPDw8dP/998vDw0OxsbEWMbGxsSpVqpR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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot a chart showing the top correlations with target variable, but with redundant features removed\n",
    "dw.plot_corr(df_reduced, 'subscribed_enc', n=16, size=(12,6), rotation=90)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "## Model\n",
    "\n",
    "The `dw.model` module provides tools to streamline data modeling workflows.\n",
    "It contains functions to set up pipelines, iterate over models, and evaluate results.\n",
    "\n",
    "* [Create Pipeline](#Create-Pipeline) - *create_pipeline()*\n",
    "* [Iterate Model](#Iterate-Model) - *iterate_model()*\n",
    "    * [Create Results DataFrame](#Create-Results-DataFrame) - *create_results_df()*\n",
    "    * [Separate X and Y](#Separate-X-and-Y)\n",
    "    * [Split Train and Test](#Split-Train-and-Test)\n",
    "    * [Create Custom Configuration](#Create-Custom-Configuration)\n",
    "    * [Run Multiple Iterations](#Run-Multiple-Iterations) - *iterate_model()*\n",
    "    * [Review the Results](#Review-the-Results)\n",
    "    * [Plot the Results](#Plot-the-Results) - *plot_results()*\n",
    "    * [Examine the Final Model](#Examine-the-Final-Model)\n",
    "* [Plot ACF Residuals](#Plot-ACF-Residuals) - *plot_acf_residuals()*\n",
    "* [Evaluate Classification Model](#Evaluate-Classification-Model) - *eval_model()*\n",
    "    * [Separate X and Y Data](#Separate-X-and-Y-Data)\n",
    "    * [Split Train and Test Data](#Split-Train-and-Test-Data)\n",
    "    * [Build a Pipeline](#Build-a-Pipeline)\n",
    "    * [Fit the Data](#Fit-the-Data)\n",
    "    * [Make Predictions](#Make-Predictions)\n",
    "    * [Evaluate Model Performance](#Evaluate-Model-Performance) - *eval_model()*\n",
    "    * [Multi-Class Example](#Multi-Class-Example)\n",
    "* [Compare Models](#Compare-Models) - *compare_models()*\n",
    "    * [Load and Prepare Data](#Load-and-Prepare-Data)\n",
    "    * [Identify Class Labels](#Identify-Class-Labels)\n",
    "    * [Define Configuration](#Define-Configuration)\n",
    "    * [Compare Binary Classification Models](#Compare-Binary-Classification-Models) - *compare_models()*\n",
    "    * [Review the Best Models](#Review-the-Best-Models)\n",
    "    * [Plot the Best Models](#Plot-the-Best-Models) - *plot_results()*\n",
    "    * [Compare Multi-Class Classification Models](#Compare-Multi-Class-Classification-Models) - *compare_models()*\n",
    "* [Create Binary Classification Neural Network](#Create-Binary-Classification-Neural-Network) - *create_nn_binary*\n",
    "* [Create Multi-Class Classification Neural Network](#Create-Multi-Class-Classification-Neural-Network) - *create_nn_multi()*\n",
    "* [Plot Training History](#Plot-Training-History) - *plot_train_history()*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create Pipeline\n",
    "\n",
    "`dw.create_pipeline()` creates a custom pipeline for data preprocessing and modeling.\n",
    "\n",
    "This function allows you to define a custom pipeline by specifying the\n",
    "desired preprocessing steps (imputation, transformation, scaling, feature\n",
    "selection) and the model to use for predictions. Provide the keys\n",
    "for the steps you want to include in the pipeline. If a step is not\n",
    "specified, it will be skipped. The definition of the keys are defined in\n",
    "a configuration dictionary that is passed to the function. If no external\n",
    "configuration is provided, a default one will be used.\n",
    "\n",
    "* `imputer_key` (str) is selected from `config['imputers']`\n",
    "* `transformer_keys` (list or str) are selected from `config['transformers']`\n",
    "* `scaler_key` (str) is selected from `config['scalers']`\n",
    "* `selector_key` (str) is selected from `config['selectors']`\n",
    "* `model_key` (str) is selected from `config['models']`\n",
    "* `config['no_scale']` lists model keys that should not be scaled.\n",
    "* `config['no_poly']` lists models that should not be polynomial transformed.\n",
    "\n",
    "By default, the sequence of the Pipeline steps are: Imputer > Column\n",
    "Transformer > Scaler > Selector > Model. However, if `impute_first` is False,\n",
    "the data will be imputed after the column transformations. Scaling will not\n",
    "be done for any Model that is listed in `config['no_scale']` (ex: for decision\n",
    "trees, which don't require scaling).\n",
    "\n",
    "A column transformer will be created based on the specified\n",
    "`transformer_keys`. Any number of column transformations can be defined here.\n",
    "For example, you can define `transformer_keys = ['ohe', 'poly2', 'log']` to\n",
    "One-Hot Encode some columns, Polynomial transform some columns, and Log\n",
    "transform others. Just define each of these in your config file to\n",
    "reference the appropriate column lists. By default, these will transform the\n",
    "columns passed in as `cat_columns` or `num_columns`. But you may want to\n",
    "apply different transformations to your categorical features. For example,\n",
    "if you One-Hot Encode some, but Ordinal Encode others, you could define\n",
    "separate column lists for these as 'ohe_columns' and 'ord_columns', and then\n",
    "define `transformer_keys` in your config dictionary that reference them:\n",
    "\n",
    "```\n",
    "'ohe': (OneHotEncoder(drop='if_binary', handle_unknown='ignore'), ohe_columns),\n",
    "'ord': (OrdinalEncoder(), ord_columns),\n",
    "```\n",
    "\n",
    "Here is an example of the configuration dictionary structure:\n",
    "\n",
    "```\n",
    "config = {\n",
    "    'imputers': {\n",
    "        'knn_imputer': KNNImputer().set_output(transform='pandas'),\n",
    "        'simple_imputer': SimpleImputer()\n",
    "    },\n",
    "    'transformers': {\n",
    "        'ohe': (OneHotEncoder(drop='if_binary', handle_unknown='ignore'),\n",
    "                cat_columns),\n",
    "        'ord': (OrdinalEncoder(), cat_columns),\n",
    "        'poly2': (PolynomialFeatures(degree=2, include_bias=False),\n",
    "                  num_columns),\n",
    "        'log': (FunctionTransformer(np.log1p, validate=True),\n",
    "                num_columns)\n",
    "    },\n",
    "    'scalers': {\n",
    "        'stand': StandardScaler(),\n",
    "        'minmax': MinMaxScaler()\n",
    "    },\n",
    "    'selectors': {\n",
    "        'rfe_logreg': RFE(LogisticRegression(max_iter=max_iter,\n",
    "                                        random_state=random_state,\n",
    "                                        class_weight=class_weight)),\n",
    "        'sfs_linreg': SequentialFeatureSelector(LinearRegression())\n",
    "    },\n",
    "    'models': {\n",
    "        'linreg': LinearRegression(),\n",
    "        'logreg': LogisticRegression(max_iter=max_iter,\n",
    "                                     random_state=random_state,\n",
    "                                     class_weight=class_weight),\n",
    "        'tree_class': DecisionTreeClassifier(random_state=random_state),\n",
    "        'tree_reg': DecisionTreeRegressor(random_state=random_state)\n",
    "    },\n",
    "    'no_scale': ['tree_class', 'tree_reg'],\n",
    "    'no_poly': ['tree_class', 'tree_reg']\n",
    "}\n",
    "```\n",
    "\n",
    "Use this function to quickly create a pipeline during model iteration and\n",
    "evaluation. You can easily experiment with different combinations of\n",
    "preprocessing steps and models to find the best performing pipeline. This\n",
    "function is utilized by `iterate_model`, `compare_models`, and\n",
    "`compare_reg_models` to dynamically build pipelines as part of that\n",
    "larger modeling workflow."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define column lists\n",
    "cat_columns = ['ocean_proximity']\n",
    "num_columns = ['longitude', 'latitude', 'housing_median_age','total_rooms', 'total_bedrooms', 'population',\n",
    "               'households', 'median_income']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a pipeline with Standard Scaler and Linear Regression\n",
    "pipeline = dw.create_pipeline(scaler_key='stand', model_key='linreg', cat_columns=cat_columns, num_columns=num_columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-1 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-1 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-1 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-1 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-1 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;stand&#x27;, StandardScaler()), (&#x27;linreg&#x27;, LinearRegression())])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" ><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link \">i<span>Not fitted</span></span></label><div class=\"sk-toggleable__content \"><pre>Pipeline(steps=[(&#x27;stand&#x27;, StandardScaler()), (&#x27;linreg&#x27;, LinearRegression())])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" ><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;StandardScaler<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.StandardScaler.html\">?<span>Documentation for StandardScaler</span></a></label><div class=\"sk-toggleable__content \"><pre>StandardScaler()</pre></div> </div></div><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" ><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;LinearRegression<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.linear_model.LinearRegression.html\">?<span>Documentation for LinearRegression</span></a></label><div class=\"sk-toggleable__content \"><pre>LinearRegression()</pre></div> </div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('stand', StandardScaler()), ('linreg', LinearRegression())])"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the pipeline\n",
    "pipeline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a pipeline with One-Hot Encoding, Standard Scaler, and a Logistic Regression model\n",
    "pipeline = dw.create_pipeline(transformer_keys=['ohe'],\n",
    "                           scaler_key='stand',\n",
    "                           model_key='logreg',\n",
    "                           cat_columns=cat_columns, num_columns=num_columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-2 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-2 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-2 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-2 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-2 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-2 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-2 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-2 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-2 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;ohe&#x27;,\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;ohe&#x27;,\n",
       "                                                  OneHotEncoder(drop=&#x27;if_binary&#x27;,\n",
       "                                                                handle_unknown=&#x27;ignore&#x27;),\n",
       "                                                  [&#x27;ocean_proximity&#x27;])])),\n",
       "                (&#x27;stand&#x27;, StandardScaler()),\n",
       "                (&#x27;logreg&#x27;,\n",
       "                 LogisticRegression(max_iter=10000, random_state=42))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" ><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link \">i<span>Not fitted</span></span></label><div class=\"sk-toggleable__content \"><pre>Pipeline(steps=[(&#x27;ohe&#x27;,\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;ohe&#x27;,\n",
       "                                                  OneHotEncoder(drop=&#x27;if_binary&#x27;,\n",
       "                                                                handle_unknown=&#x27;ignore&#x27;),\n",
       "                                                  [&#x27;ocean_proximity&#x27;])])),\n",
       "                (&#x27;stand&#x27;, StandardScaler()),\n",
       "                (&#x27;logreg&#x27;,\n",
       "                 LogisticRegression(max_iter=10000, random_state=42))])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-5\" type=\"checkbox\" ><label for=\"sk-estimator-id-5\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;ohe: ColumnTransformer<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.compose.ColumnTransformer.html\">?<span>Documentation for ohe: ColumnTransformer</span></a></label><div class=\"sk-toggleable__content \"><pre>ColumnTransformer(force_int_remainder_cols=False, remainder=&#x27;passthrough&#x27;,\n",
       "                  transformers=[(&#x27;ohe&#x27;,\n",
       "                                 OneHotEncoder(drop=&#x27;if_binary&#x27;,\n",
       "                                               handle_unknown=&#x27;ignore&#x27;),\n",
       "                                 [&#x27;ocean_proximity&#x27;])])</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-6\" type=\"checkbox\" ><label for=\"sk-estimator-id-6\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">ohe</label><div class=\"sk-toggleable__content \"><pre>[&#x27;ocean_proximity&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-7\" type=\"checkbox\" ><label for=\"sk-estimator-id-7\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;OneHotEncoder<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.OneHotEncoder.html\">?<span>Documentation for OneHotEncoder</span></a></label><div class=\"sk-toggleable__content \"><pre>OneHotEncoder(drop=&#x27;if_binary&#x27;, handle_unknown=&#x27;ignore&#x27;)</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-8\" type=\"checkbox\" ><label for=\"sk-estimator-id-8\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">remainder</label><div class=\"sk-toggleable__content \"><pre></pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-9\" type=\"checkbox\" ><label for=\"sk-estimator-id-9\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">passthrough</label><div class=\"sk-toggleable__content \"><pre>passthrough</pre></div> </div></div></div></div></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-10\" type=\"checkbox\" ><label for=\"sk-estimator-id-10\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;StandardScaler<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.StandardScaler.html\">?<span>Documentation for StandardScaler</span></a></label><div class=\"sk-toggleable__content \"><pre>StandardScaler()</pre></div> </div></div><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-11\" type=\"checkbox\" ><label for=\"sk-estimator-id-11\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;LogisticRegression<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.linear_model.LogisticRegression.html\">?<span>Documentation for LogisticRegression</span></a></label><div class=\"sk-toggleable__content \"><pre>LogisticRegression(max_iter=10000, random_state=42)</pre></div> </div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('ohe',\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder='passthrough',\n",
       "                                   transformers=[('ohe',\n",
       "                                                  OneHotEncoder(drop='if_binary',\n",
       "                                                                handle_unknown='ignore'),\n",
       "                                                  ['ocean_proximity'])])),\n",
       "                ('stand', StandardScaler()),\n",
       "                ('logreg',\n",
       "                 LogisticRegression(max_iter=10000, random_state=42))])"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the pipeline\n",
    "pipeline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a pipeline with KNN Imputer, One-Hot Encoding, Polynomial Transformation, Log Transformation, Standard Scaler,\n",
    "# and Gradient Boost Regressor for the model\n",
    "pipeline = dw.create_pipeline(imputer_key='knn_imputer',\n",
    "                           transformer_keys=['ohe', 'poly2', 'log'],\n",
    "                           scaler_key='stand',\n",
    "                           model_key='boost_reg',\n",
    "                           cat_columns=cat_columns, num_columns=num_columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-3 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-3 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-3 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-3 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-3 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-3 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-3 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-3 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-3 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-3 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-3 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;knn_imputer&#x27;, KNNImputer()),\n",
       "                (&#x27;ohe_poly2_log&#x27;,\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;ohe&#x27;,\n",
       "                                                  OneHotEncoder(drop=&#x27;if_binary&#x27;,\n",
       "                                                                handle_unknown=&#x27;ignore&#x27;),\n",
       "                                                  [&#x27;ocean_proximity&#x27;]),\n",
       "                                                 (&#x27;poly2&#x27;,\n",
       "                                                  PolynomialFeatures(include_bias=False),\n",
       "                                                  [&#x27;longitude&#x27;, &#x27;latitude&#x27;,\n",
       "                                                   &#x27;housing_median_age&#x27;,\n",
       "                                                   &#x27;total_rooms&#x27;,\n",
       "                                                   &#x27;total_bedrooms&#x27;,\n",
       "                                                   &#x27;population&#x27;, &#x27;households&#x27;,\n",
       "                                                   &#x27;median_income&#x27;]),\n",
       "                                                 (&#x27;log&#x27;,\n",
       "                                                  FunctionTransformer(func=&lt;ufunc &#x27;log1p&#x27;&gt;,\n",
       "                                                                      validate=True),\n",
       "                                                  [&#x27;longitude&#x27;, &#x27;latitude&#x27;,\n",
       "                                                   &#x27;housing_median_age&#x27;,\n",
       "                                                   &#x27;total_rooms&#x27;,\n",
       "                                                   &#x27;total_bedrooms&#x27;,\n",
       "                                                   &#x27;population&#x27;, &#x27;households&#x27;,\n",
       "                                                   &#x27;median_income&#x27;])])),\n",
       "                (&#x27;stand&#x27;, StandardScaler()),\n",
       "                (&#x27;boost_reg&#x27;, GradientBoostingRegressor(random_state=42))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-12\" type=\"checkbox\" ><label for=\"sk-estimator-id-12\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link \">i<span>Not fitted</span></span></label><div class=\"sk-toggleable__content \"><pre>Pipeline(steps=[(&#x27;knn_imputer&#x27;, KNNImputer()),\n",
       "                (&#x27;ohe_poly2_log&#x27;,\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;ohe&#x27;,\n",
       "                                                  OneHotEncoder(drop=&#x27;if_binary&#x27;,\n",
       "                                                                handle_unknown=&#x27;ignore&#x27;),\n",
       "                                                  [&#x27;ocean_proximity&#x27;]),\n",
       "                                                 (&#x27;poly2&#x27;,\n",
       "                                                  PolynomialFeatures(include_bias=False),\n",
       "                                                  [&#x27;longitude&#x27;, &#x27;latitude&#x27;,\n",
       "                                                   &#x27;housing_median_age&#x27;,\n",
       "                                                   &#x27;total_rooms&#x27;,\n",
       "                                                   &#x27;total_bedrooms&#x27;,\n",
       "                                                   &#x27;population&#x27;, &#x27;households&#x27;,\n",
       "                                                   &#x27;median_income&#x27;]),\n",
       "                                                 (&#x27;log&#x27;,\n",
       "                                                  FunctionTransformer(func=&lt;ufunc &#x27;log1p&#x27;&gt;,\n",
       "                                                                      validate=True),\n",
       "                                                  [&#x27;longitude&#x27;, &#x27;latitude&#x27;,\n",
       "                                                   &#x27;housing_median_age&#x27;,\n",
       "                                                   &#x27;total_rooms&#x27;,\n",
       "                                                   &#x27;total_bedrooms&#x27;,\n",
       "                                                   &#x27;population&#x27;, &#x27;households&#x27;,\n",
       "                                                   &#x27;median_income&#x27;])])),\n",
       "                (&#x27;stand&#x27;, StandardScaler()),\n",
       "                (&#x27;boost_reg&#x27;, GradientBoostingRegressor(random_state=42))])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-13\" type=\"checkbox\" ><label for=\"sk-estimator-id-13\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;KNNImputer<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.impute.KNNImputer.html\">?<span>Documentation for KNNImputer</span></a></label><div class=\"sk-toggleable__content \"><pre>KNNImputer()</pre></div> </div></div><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-14\" type=\"checkbox\" ><label for=\"sk-estimator-id-14\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;ohe_poly2_log: ColumnTransformer<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.compose.ColumnTransformer.html\">?<span>Documentation for ohe_poly2_log: ColumnTransformer</span></a></label><div class=\"sk-toggleable__content \"><pre>ColumnTransformer(force_int_remainder_cols=False, remainder=&#x27;passthrough&#x27;,\n",
       "                  transformers=[(&#x27;ohe&#x27;,\n",
       "                                 OneHotEncoder(drop=&#x27;if_binary&#x27;,\n",
       "                                               handle_unknown=&#x27;ignore&#x27;),\n",
       "                                 [&#x27;ocean_proximity&#x27;]),\n",
       "                                (&#x27;poly2&#x27;,\n",
       "                                 PolynomialFeatures(include_bias=False),\n",
       "                                 [&#x27;longitude&#x27;, &#x27;latitude&#x27;, &#x27;housing_median_age&#x27;,\n",
       "                                  &#x27;total_rooms&#x27;, &#x27;total_bedrooms&#x27;, &#x27;population&#x27;,\n",
       "                                  &#x27;households&#x27;, &#x27;median_income&#x27;]),\n",
       "                                (&#x27;log&#x27;,\n",
       "                                 FunctionTransformer(func=&lt;ufunc &#x27;log1p&#x27;&gt;,\n",
       "                                                     validate=True),\n",
       "                                 [&#x27;longitude&#x27;, &#x27;latitude&#x27;, &#x27;housing_median_age&#x27;,\n",
       "                                  &#x27;total_rooms&#x27;, &#x27;total_bedrooms&#x27;, &#x27;population&#x27;,\n",
       "                                  &#x27;households&#x27;, &#x27;median_income&#x27;])])</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-15\" type=\"checkbox\" ><label for=\"sk-estimator-id-15\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">ohe</label><div class=\"sk-toggleable__content \"><pre>[&#x27;ocean_proximity&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-16\" type=\"checkbox\" ><label for=\"sk-estimator-id-16\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;OneHotEncoder<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.OneHotEncoder.html\">?<span>Documentation for OneHotEncoder</span></a></label><div class=\"sk-toggleable__content \"><pre>OneHotEncoder(drop=&#x27;if_binary&#x27;, handle_unknown=&#x27;ignore&#x27;)</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-17\" type=\"checkbox\" ><label for=\"sk-estimator-id-17\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">poly2</label><div class=\"sk-toggleable__content \"><pre>[&#x27;longitude&#x27;, &#x27;latitude&#x27;, &#x27;housing_median_age&#x27;, &#x27;total_rooms&#x27;, &#x27;total_bedrooms&#x27;, &#x27;population&#x27;, &#x27;households&#x27;, &#x27;median_income&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-18\" type=\"checkbox\" ><label for=\"sk-estimator-id-18\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;PolynomialFeatures<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.PolynomialFeatures.html\">?<span>Documentation for PolynomialFeatures</span></a></label><div class=\"sk-toggleable__content \"><pre>PolynomialFeatures(include_bias=False)</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-19\" type=\"checkbox\" ><label for=\"sk-estimator-id-19\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">log</label><div class=\"sk-toggleable__content \"><pre>[&#x27;longitude&#x27;, &#x27;latitude&#x27;, &#x27;housing_median_age&#x27;, &#x27;total_rooms&#x27;, &#x27;total_bedrooms&#x27;, &#x27;population&#x27;, &#x27;households&#x27;, &#x27;median_income&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-20\" type=\"checkbox\" ><label for=\"sk-estimator-id-20\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;FunctionTransformer<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.FunctionTransformer.html\">?<span>Documentation for FunctionTransformer</span></a></label><div class=\"sk-toggleable__content \"><pre>FunctionTransformer(func=&lt;ufunc &#x27;log1p&#x27;&gt;, validate=True)</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-21\" type=\"checkbox\" ><label for=\"sk-estimator-id-21\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">remainder</label><div class=\"sk-toggleable__content \"><pre></pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-22\" type=\"checkbox\" ><label for=\"sk-estimator-id-22\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">passthrough</label><div class=\"sk-toggleable__content \"><pre>passthrough</pre></div> </div></div></div></div></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-23\" type=\"checkbox\" ><label for=\"sk-estimator-id-23\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;StandardScaler<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.StandardScaler.html\">?<span>Documentation for StandardScaler</span></a></label><div class=\"sk-toggleable__content \"><pre>StandardScaler()</pre></div> </div></div><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-24\" type=\"checkbox\" ><label for=\"sk-estimator-id-24\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;GradientBoostingRegressor<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.ensemble.GradientBoostingRegressor.html\">?<span>Documentation for GradientBoostingRegressor</span></a></label><div class=\"sk-toggleable__content \"><pre>GradientBoostingRegressor(random_state=42)</pre></div> </div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('knn_imputer', KNNImputer()),\n",
       "                ('ohe_poly2_log',\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder='passthrough',\n",
       "                                   transformers=[('ohe',\n",
       "                                                  OneHotEncoder(drop='if_binary',\n",
       "                                                                handle_unknown='ignore'),\n",
       "                                                  ['ocean_proximity']),\n",
       "                                                 ('poly2',\n",
       "                                                  PolynomialFeatures(include_bias=False),\n",
       "                                                  ['longitude', 'latitude',\n",
       "                                                   'housing_median_age',\n",
       "                                                   'total_rooms',\n",
       "                                                   'total_bedrooms',\n",
       "                                                   'population', 'households',\n",
       "                                                   'median_income']),\n",
       "                                                 ('log',\n",
       "                                                  FunctionTransformer(func=<ufunc 'log1p'>,\n",
       "                                                                      validate=True),\n",
       "                                                  ['longitude', 'latitude',\n",
       "                                                   'housing_median_age',\n",
       "                                                   'total_rooms',\n",
       "                                                   'total_bedrooms',\n",
       "                                                   'population', 'households',\n",
       "                                                   'median_income'])])),\n",
       "                ('stand', StandardScaler()),\n",
       "                ('boost_reg', GradientBoostingRegressor(random_state=42))])"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the pipeline\n",
    "pipeline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Iterate Model\n",
    "\n",
    "`dw.iterate_model()` creates and evaluates a model pipeline with specified parameters.\n",
    "\n",
    "This function creates a pipeline from specified parameters for imputers,\n",
    "    column transformers, scalers, feature selectors, and models. Parameters must\n",
    "    be defined in a configuration dictionary containing the sections described\n",
    "    below. If `config` is not defined, the `create_pipeline` function will revert\n",
    "    to the default config embedded in its code. After creating the pipeline, it\n",
    "    fits the pipeline to the passed training data, and evaluates performance with\n",
    "    both test and training data. There are options to see plots of residuals and\n",
    "    actuals vs. predicted, save results to a results_df with user-defined note,\n",
    "    display coefficients, calculate permutation feature importance, variance\n",
    "    inflation factor (VIF), and perform cross-validation.\n",
    "\n",
    "`create_pipeline` is called to create a pipeline from the specified parameters:\n",
    "\n",
    "* `imputer_key` (str) is selected from `config['imputers']`\n",
    "* `transformer_keys` (list or str) are selected from `config['transformers']`\n",
    "* `scaler_key` (str) is selected from `config['scalers']`\n",
    "* `selector_key` (str) is selected from `config['selectors']`\n",
    "* `model_key` (str) is selected from `config['models']`\n",
    "* `config['no_scale']` lists model keys that should not be scaled.\n",
    "* `config['no_poly']` lists models that should not be polynomial transformed.\n",
    "\n",
    "Here is an example of the configuration dictionary structure. It is based on\n",
    "what `create_pipeline` requires to assemble the pipeline. But it adds some\n",
    "additional configuration parameters only required by `iterate_model`, which\n",
    "are `params` (grid search parameters) and `cv` (cross-validation parameters):\n",
    "\n",
    "```\n",
    "config = {\n",
    "    'imputers': {\n",
    "        'knn_imputer': KNNImputer().set_output(transform='pandas'),\n",
    "        'simple_imputer': SimpleImputer()\n",
    "    },\n",
    "    'transformers': {\n",
    "        'ohe': (OneHotEncoder(drop='if_binary', handle_unknown='ignore'),\n",
    "                cat_columns),\n",
    "        'ord': (OrdinalEncoder(), cat_columns),\n",
    "        'poly2': (PolynomialFeatures(degree=2, include_bias=False),\n",
    "                  num_columns),\n",
    "        'log': (FunctionTransformer(np.log1p, validate=True),\n",
    "                num_columns)\n",
    "    },\n",
    "    'scalers': {\n",
    "        'stand': StandardScaler(),\n",
    "        'minmax': MinMaxScaler()\n",
    "    },\n",
    "    'selectors': {\n",
    "        'rfe_logreg': RFE(LogisticRegression(max_iter=max_iter,\n",
    "                                        random_state=random_state,\n",
    "                                        class_weight=class_weight)),\n",
    "        'sfs_linreg': SequentialFeatureSelector(LinearRegression())\n",
    "    },\n",
    "    'models': {\n",
    "        'linreg': LinearRegression(),\n",
    "        'logreg': LogisticRegression(max_iter=max_iter,\n",
    "                                     random_state=random_state,\n",
    "                                     class_weight=class_weight),\n",
    "        'tree_class': DecisionTreeClassifier(random_state=random_state),\n",
    "        'tree_reg': DecisionTreeRegressor(random_state=random_state)\n",
    "    },\n",
    "    'no_scale': ['tree_class', 'tree_reg'],\n",
    "    'no_poly': ['tree_class', 'tree_reg'],\n",
    "    'params': {\n",
    "        'sfs': {\n",
    "            'Selector: sfs__n_features_to_select': np.arange(3, 13, 1),\n",
    "        },\n",
    "        'linreg': {\n",
    "            'Model: linreg__fit_intercept': [True],\n",
    "        },\n",
    "        'ridge': {\n",
    "            'Model: ridge__alpha': np.array([0.001, 0.1, 1, 10, 100, 1000, 10000, 100000]),\n",
    "        }\n",
    "    },\n",
    "    'cv': {\n",
    "        'kfold_5': KFold(n_splits=5, shuffle=True, random_state=42),\n",
    "        'kfold_10': KFold(n_splits=10, shuffle=True, random_state=42),\n",
    "        'skf_5': StratifiedKFold(n_splits=5, shuffle=True, random_state=42),\n",
    "        'skf_10': StratifiedKFold(n_splits=10, shuffle=True, random_state=42)\n",
    "    }\n",
    "}\n",
    "```\n",
    "\n",
    "In addition to the configuration file, you will need to define any column\n",
    "lists if you want to target certain transformations to a subset of columns.\n",
    "For example, you might define a 'ohe' transformer for One-Hot Encoding, and\n",
    "reference 'ohe_columns' or 'cat_columns' in its definition in the config.\n",
    "\n",
    "When `iterate_model` completes, it will print out the results and performance\n",
    "metrics, as well as any requested charts. It will return the best model, and\n",
    "also the grid search results (if a grid search was ran). In addition, if\n",
    "`save = True` it will append the results to a global variable `results_df`.\n",
    "This should be created using `create_results_df` beforehand. If `export=True`\n",
    "it will save the best model to disk using joblib dump with a timestamp.\n",
    "\n",
    "Use this function to iterate and evaluate different model pipeline\n",
    "configurations, analyze their performance, and select the best model. With one\n",
    "line of code, you can quickly explore a change to the model pipeline, or\n",
    "grid search parameters, and see how it impacts performance. You can also\n",
    "track the results of these iterations in a `results_df` DataFrame that can\n",
    "be used to evaluate the best model, or to plot the progress you made from\n",
    "each iteration."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Create Results DataFrame\n",
    "\n",
    "`dw.create_results_df` initializes the results_df DataFrame with the columns required for `iterate_model`.\n",
    "\n",
    "This function creates a new DataFrame with the following columns:\n",
    "'Iteration', 'Train MSE', 'Test MSE', 'Train RMSE', 'Test RMSE',\n",
    "'Train MAE', 'Test MAE', 'Train R^2 Score', 'Test R^2 Score',\n",
    "'Pipeline', 'Best Grid Params', 'Note', 'Date'.\n",
    "\n",
    "Create a `results_df` with this function, and then pass it as a parameter\n",
    "to `iterate_model`. The results of each model iteration will be appended\n",
    "to `results_df`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create the dw.results_df required for saving the results of each iteration\n",
    "results_df = dw.create_results_df()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Iteration</th>\n",
       "      <th>Train MSE</th>\n",
       "      <th>Test MSE</th>\n",
       "      <th>Train RMSE</th>\n",
       "      <th>Test RMSE</th>\n",
       "      <th>Train MAE</th>\n",
       "      <th>Test MAE</th>\n",
       "      <th>Train R^2 Score</th>\n",
       "      <th>Test R^2 Score</th>\n",
       "      <th>Pipeline</th>\n",
       "      <th>Best Grid Params</th>\n",
       "      <th>Note</th>\n",
       "      <th>Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [Iteration, Train MSE, Test MSE, Train RMSE, Test RMSE, Train MAE, Test MAE, Train R^2 Score, Test R^2 Score, Pipeline, Best Grid Params, Note, Date]\n",
       "Index: []"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Show the empty results_df that will store the results of each iteration\n",
    "results_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Separate X and Y Data\n",
    "\n",
    "Let's prepare the X and y datasets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load the California housing dataset\n",
    "df_housing = pd.read_csv('data/housing_no_outliers.csv', index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define the X and y columns\n",
    "x_num_columns = ['longitude', 'latitude', 'housing_median_age','total_rooms', 'total_bedrooms', 'population',\n",
    "               'households', 'median_income']\n",
    "x_cat_columns = ['ocean_proximity']\n",
    "y_column = ['median_house_value']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create X and y, with some different combinations of X features\n",
    "X1 = df_housing[x_num_columns]\n",
    "X2 = df_housing[x_num_columns + x_cat_columns]\n",
    "y = df_housing[y_column]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X1: (18568, 8), y: (18568, 1)\n",
      "X2: (18568, 9), y: (18568, 1)\n"
     ]
    }
   ],
   "source": [
    "# Verify X/Y split\n",
    "print(f'X1: {X1.shape}, y: {y.shape}')\n",
    "print(f'X2: {X2.shape}, y: {y.shape}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X1: (8) ['longitude', 'latitude', 'housing_median_age', 'total_rooms', 'total_bedrooms', 'population', 'households', 'median_income']\n",
      "X2: (9) ['longitude', 'latitude', 'housing_median_age', 'total_rooms', 'total_bedrooms', 'population', 'households', 'median_income', 'ocean_proximity']\n",
      "y: (1) ['median_house_value']\n"
     ]
    }
   ],
   "source": [
    "# Verify X/Y columns\n",
    "print(f'X1: ({len(X1.columns)})', list(X1.columns))\n",
    "print(f'X2: ({len(X2.columns)})', list(X2.columns))\n",
    "print(f'y: ({len(y.columns)})', list(y.columns))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Split Train and Test Data\n",
    "\n",
    "Now we'll separate the train set from the test set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create training and test datasets\n",
    "X1_train, X1_test, y1_train, y1_test = train_test_split(X1, y, test_size=0.25, random_state=42)\n",
    "X2_train, X2_test, y2_train, y2_test = train_test_split(X2, y, test_size=0.25, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X1: (13926, 8) (4642, 8) (13926, 1) (4642, 1)\n",
      "X2: (13926, 9) (4642, 9) (13926, 1) (4642, 1)\n"
     ]
    }
   ],
   "source": [
    "# Verify train/test split\n",
    "print('X1:', X1_train.shape, X1_test.shape, y1_train.shape, y1_test.shape)\n",
    "print('X2:', X2_train.shape, X2_test.shape, y2_train.shape, y2_test.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Create Custom Configuration\n",
    "\n",
    "You need to define a configuration dictionary that is structured with names that `iterate_model` and `create_pipeline` expect. The format is documented in the docstrings for both of those functions. In addition, you have to import any libraries referenced in the configuration. And some column lists and variables referenced in the configurations need to be defined."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Any column lists referenced in the configuration file need to be defined\n",
    "cat_columns = ['ocean_proximity']\n",
    "num_columns = ['longitude', 'latitude', 'housing_median_age','total_rooms', 'total_bedrooms', 'population',\n",
    "               'households', 'median_income']\n",
    "ohe_columns = cat_columns\n",
    "ord_columns = cat_columns\n",
    "poly2_columns = ['median_income']\n",
    "poly3_columns = ['median_income']\n",
    "log_columns = ['total_rooms','total_bedrooms','population','households']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "# If you are doing one-hot encoding, you might want to specify a value to drop\n",
    "ohe_drop_categories = ['ISLAND']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "# If you are doing ordinal encoding, the ordering needs to be specified\n",
    "# Island > Near Bay > Near Ocean > 1 Hour to Ocean > Inland\n",
    "ocean_proximity_order = [['INLAND', '<1H OCEAN', 'NEAR OCEAN', 'NEAR BAY', 'ISLAND']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "# If you want to set any variables in the configurations globally, set them here\n",
    "max_iter = 1000\n",
    "random_state = 42\n",
    "class_weight = 'balanced'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a custom configuration file\n",
    "my_config = {\n",
    "    'imputers': {\n",
    "        'knn_imputer': KNNImputer().set_output(transform='pandas'),\n",
    "        'simple_imputer': SimpleImputer()\n",
    "    },\n",
    "    'transformers': {\n",
    "        'ohe': (OneHotEncoder(drop='if_binary', handle_unknown='ignore'),\n",
    "                ohe_columns),\n",
    "        'ohe_drop': (OneHotEncoder(drop=ohe_drop_categories, handle_unknown='ignore'), ohe_columns),\n",
    "        'ord': (OrdinalEncoder(categories=ocean_proximity_order), ord_columns),\n",
    "        'poly2': (PolynomialFeatures(degree=2, include_bias=False),\n",
    "                  poly2_columns),\n",
    "        'poly3': (PolynomialFeatures(degree=3, include_bias=False),\n",
    "                  poly3_columns),\n",
    "        'log': (LogTransformer(),\n",
    "                log_columns)\n",
    "    },\n",
    "    'scalers': {\n",
    "        'stand': StandardScaler(),\n",
    "        'minmax': MinMaxScaler()\n",
    "    },\n",
    "    'selectors': {\n",
    "        'rfe_logreg': RFE(LogisticRegression(max_iter=max_iter,\n",
    "                                        random_state=random_state,\n",
    "                                        class_weight=class_weight)),\n",
    "        'rfe_linreg': RFE(LinearRegression()),\n",
    "        'sfs_linreg': SequentialFeatureSelector(LinearRegression())\n",
    "    },\n",
    "    'models': {\n",
    "        'linreg': LinearRegression(),\n",
    "        'ridge': Ridge(),\n",
    "        'logreg': LogisticRegression(max_iter=max_iter,\n",
    "                                     random_state=random_state,\n",
    "                                     class_weight=class_weight),\n",
    "        'tree_class': DecisionTreeClassifier(random_state=random_state),\n",
    "        'tree_reg': DecisionTreeRegressor(random_state=random_state)\n",
    "    },\n",
    "    'no_scale': ['tree_class', 'tree_reg'],\n",
    "    'no_poly': ['tree_class', 'tree_reg'],\n",
    "    'params': {\n",
    "        'sfs_linreg': {\n",
    "            'sfs_linreg__n_features_to_select': np.arange(5, 10, 1),\n",
    "        },\n",
    "        'rfe_linreg': {\n",
    "            'rfe_linreg__n_features_to_select': np.arange(5, 10, 1),\n",
    "        },\n",
    "        'linreg': {\n",
    "            'linreg__fit_intercept': [True],\n",
    "        },\n",
    "        'ridge': {\n",
    "            'ridge__alpha': np.array([0.001, 0.1, 1, 10, 100, 1000, 10000, 100000]),\n",
    "        },\n",
    "        'tree_reg': {\n",
    "            'tree_reg__max_depth': [3, 5, 7],\n",
    "            'tree_reg__min_samples_split': [5, 10, 15],\n",
    "            'tree_reg__criterion': ['poisson', 'friedman_mse', 'squared_error', 'absolute_error'],\n",
    "            'tree_reg__min_samples_leaf': [2, 4, 6]\n",
    "        }\n",
    "    },\n",
    "    'cv': {\n",
    "        'kfold_5': KFold(n_splits=5, shuffle=True, random_state=42),\n",
    "        'kfold_10': KFold(n_splits=10, shuffle=True, random_state=42),\n",
    "        'skf_5': StratifiedKFold(n_splits=5, shuffle=True, random_state=42),\n",
    "        'skf_10': StratifiedKFold(n_splits=10, shuffle=True, random_state=42)\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'imputers': {'knn_imputer': KNNImputer(), 'simple_imputer': SimpleImputer()},\n",
       " 'transformers': {'ohe': (OneHotEncoder(drop='if_binary', handle_unknown='ignore'),\n",
       "   ['ocean_proximity']),\n",
       "  'ohe_drop': (OneHotEncoder(drop=['ISLAND'], handle_unknown='ignore'),\n",
       "   ['ocean_proximity']),\n",
       "  'ord': (OrdinalEncoder(categories=[['INLAND', '<1H OCEAN', 'NEAR OCEAN', 'NEAR BAY',\n",
       "                               'ISLAND']]),\n",
       "   ['ocean_proximity']),\n",
       "  'poly2': (PolynomialFeatures(include_bias=False), ['median_income']),\n",
       "  'poly3': (PolynomialFeatures(degree=3, include_bias=False),\n",
       "   ['median_income']),\n",
       "  'log': (LogTransformer(),\n",
       "   ['total_rooms', 'total_bedrooms', 'population', 'households'])},\n",
       " 'scalers': {'stand': StandardScaler(), 'minmax': MinMaxScaler()},\n",
       " 'selectors': {'rfe_logreg': RFE(estimator=LogisticRegression(class_weight='balanced', max_iter=1000,\n",
       "                                   random_state=42)),\n",
       "  'rfe_linreg': RFE(estimator=LinearRegression()),\n",
       "  'sfs_linreg': SequentialFeatureSelector(estimator=LinearRegression())},\n",
       " 'models': {'linreg': LinearRegression(),\n",
       "  'ridge': Ridge(),\n",
       "  'logreg': LogisticRegression(class_weight='balanced', max_iter=1000, random_state=42),\n",
       "  'tree_class': DecisionTreeClassifier(random_state=42),\n",
       "  'tree_reg': DecisionTreeRegressor(random_state=42)},\n",
       " 'no_scale': ['tree_class', 'tree_reg'],\n",
       " 'no_poly': ['tree_class', 'tree_reg'],\n",
       " 'params': {'sfs_linreg': {'sfs_linreg__n_features_to_select': array([5, 6, 7, 8, 9])},\n",
       "  'rfe_linreg': {'rfe_linreg__n_features_to_select': array([5, 6, 7, 8, 9])},\n",
       "  'linreg': {'linreg__fit_intercept': [True]},\n",
       "  'ridge': {'ridge__alpha': array([1.e-03, 1.e-01, 1.e+00, 1.e+01, 1.e+02, 1.e+03, 1.e+04, 1.e+05])},\n",
       "  'tree_reg': {'tree_reg__max_depth': [3, 5, 7],\n",
       "   'tree_reg__min_samples_split': [5, 10, 15],\n",
       "   'tree_reg__criterion': ['poisson',\n",
       "    'friedman_mse',\n",
       "    'squared_error',\n",
       "    'absolute_error'],\n",
       "   'tree_reg__min_samples_leaf': [2, 4, 6]}},\n",
       " 'cv': {'kfold_5': KFold(n_splits=5, random_state=42, shuffle=True),\n",
       "  'kfold_10': KFold(n_splits=10, random_state=42, shuffle=True),\n",
       "  'skf_5': StratifiedKFold(n_splits=5, random_state=42, shuffle=True),\n",
       "  'skf_10': StratifiedKFold(n_splits=10, random_state=42, shuffle=True)}}"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the configuration, notice the names of the columns and categories have been embedded\n",
    "my_config"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Run Multiple Iterations\n",
    "\n",
    "Now that we have our `results_df` ready to store results, and our configuration is complete, let's start with a simple model, and then progressively get more complex."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Iteration 1: Linear Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "ITERATION 1 RESULTS\n",
      "\n",
      "Pipeline: linreg\n",
      "Note: X1. Baseline. Test size: 0.25, Pipeline: LinReg\n",
      "May 30, 2024 09:17 AM UTC\n",
      "\n",
      "Predictions:\n",
      "                          Train            Test\n",
      "MSE:            3,568,722,086.53 3,614,822,636.93\n",
      "RMSE:                 59,738.78       60,123.40\n",
      "MAE:                  44,353.86       44,484.81\n",
      "R^2 Score:                 0.61            0.62\n",
      "\n",
      "Permutation Feature Importance:\n",
      "           Feature Importance Mean Importance Std\n",
      "          latitude            1.50           0.01\n",
      "         longitude            1.29           0.01\n",
      "     median_income            0.83           0.01\n",
      "        population            0.29           0.01\n",
      "    total_bedrooms            0.29           0.00\n",
      "        households            0.12           0.00\n",
      "       total_rooms            0.08           0.00\n",
      "housing_median_age            0.02           0.00\n",
      "\n",
      "Variance Inflation Factor:\n",
      "          Features   VIF Multicollinearity\n",
      "    total_bedrooms 32.40              High\n",
      "        households 30.01              High\n",
      "       total_rooms 13.80              High\n",
      "          latitude  8.74          Moderate\n",
      "         longitude  8.43          Moderate\n",
      "        population  6.75          Moderate\n",
      "     median_income  1.83               Low\n",
      "housing_median_age  1.30               Low\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Coefficients:\n",
      "              Feature Coefficient\n",
      "1           longitude  -38,839.33\n",
      "2            latitude  -38,580.35\n",
      "3  housing_median_age      738.05\n",
      "4         total_rooms       -8.95\n",
      "5      total_bedrooms       86.41\n",
      "6          population      -33.20\n",
      "7          households       62.66\n",
      "8       median_income        3.91\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Start with a simple Linear Regression baseline\n",
    "results_df, iteration_1 = dw.iterate_model(X1_train, X1_test, y1_train, y1_test,\n",
    "        model='linreg',\n",
    "        iteration='1', note='X1. Baseline. Test size: 0.25, Pipeline: LinReg',\n",
    "        plot=True, lowess=True, coef=True, perm=True, vif=True, decimal=2,\n",
    "        save=True, save_df=results_df, config=my_config)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-4 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-4 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-4 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-4 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-4 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-4 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-4 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-4 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-4 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-4 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-4 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-4 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-4 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-4 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-4\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;linreg&#x27;, LinearRegression())])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-25\" type=\"checkbox\" ><label for=\"sk-estimator-id-25\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;linreg&#x27;, LinearRegression())])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-26\" type=\"checkbox\" ><label for=\"sk-estimator-id-26\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;LinearRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.linear_model.LinearRegression.html\">?<span>Documentation for LinearRegression</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>LinearRegression()</pre></div> </div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('linreg', LinearRegression())])"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the pipeline\n",
    "iteration_1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Iteration 2: Linear Regression with Log"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "ITERATION 2 RESULTS\n",
      "\n",
      "Pipeline: log -> linreg\n",
      "Note: X1. Test size: 0.25, Pipeline: Log > LinReg\n",
      "May 30, 2024 09:17 AM UTC\n",
      "\n",
      "Predictions:\n",
      "                          Train            Test\n",
      "MSE:            3,333,110,642.12 3,356,136,122.95\n",
      "RMSE:                 57,733.10       57,932.17\n",
      "MAE:                  42,497.76       42,620.51\n",
      "R^2 Score:                 0.63            0.64\n",
      "\n",
      "Permutation Feature Importance:\n",
      "           Feature Importance Mean Importance Std\n",
      "          latitude            1.37           0.01\n",
      "         longitude            1.17           0.01\n",
      "    total_bedrooms            1.10           0.01\n",
      "     median_income            1.04           0.01\n",
      "        population            0.61           0.01\n",
      "       total_rooms            0.48           0.01\n",
      "        households            0.20           0.00\n",
      "housing_median_age            0.02           0.00\n",
      "\n",
      "Variance Inflation Factor:\n",
      "          Features   VIF Multicollinearity\n",
      "    total_bedrooms 32.40              High\n",
      "        households 30.01              High\n",
      "       total_rooms 13.80              High\n",
      "          latitude  8.74          Moderate\n",
      "         longitude  8.43          Moderate\n",
      "        population  6.75          Moderate\n",
      "     median_income  1.83               Low\n",
      "housing_median_age  1.30               Low\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Coefficients:\n",
      "              Feature Coefficient\n",
      "1     total_rooms_log  -63,173.70\n",
      "2  total_bedrooms_log   99,367.25\n",
      "3      population_log  -72,634.41\n",
      "4      households_log   42,917.09\n",
      "5           longitude  -36,985.09\n",
      "6            latitude  -36,881.30\n",
      "7  housing_median_age      810.44\n",
      "8       median_income        4.37\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Now let's add some log transformation\n",
    "results_df, iteration_2 = dw.iterate_model(X1_train, X1_test, y1_train, y1_test,\n",
    "        transformers=['log'], model='linreg',\n",
    "        iteration='2', note='X1. Test size: 0.25, Pipeline: Log > LinReg',\n",
    "        plot=True, lowess=True, coef=True, perm=True, vif=True, decimal=2,\n",
    "        save=True, save_df=results_df, config=my_config)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-5 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-5 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-5 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-5 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-5 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-5 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-5 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-5 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-5 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-5 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-5 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-5 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-5 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-5 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-5 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-5 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-5\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;log&#x27;,\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;log&#x27;, LogTransformer(),\n",
       "                                                  [&#x27;total_rooms&#x27;,\n",
       "                                                   &#x27;total_bedrooms&#x27;,\n",
       "                                                   &#x27;population&#x27;,\n",
       "                                                   &#x27;households&#x27;])])),\n",
       "                (&#x27;linreg&#x27;, LinearRegression())])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-27\" type=\"checkbox\" ><label for=\"sk-estimator-id-27\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;log&#x27;,\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;log&#x27;, LogTransformer(),\n",
       "                                                  [&#x27;total_rooms&#x27;,\n",
       "                                                   &#x27;total_bedrooms&#x27;,\n",
       "                                                   &#x27;population&#x27;,\n",
       "                                                   &#x27;households&#x27;])])),\n",
       "                (&#x27;linreg&#x27;, LinearRegression())])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-28\" type=\"checkbox\" ><label for=\"sk-estimator-id-28\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;log: ColumnTransformer<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.compose.ColumnTransformer.html\">?<span>Documentation for log: ColumnTransformer</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>ColumnTransformer(force_int_remainder_cols=False, remainder=&#x27;passthrough&#x27;,\n",
       "                  transformers=[(&#x27;log&#x27;, LogTransformer(),\n",
       "                                 [&#x27;total_rooms&#x27;, &#x27;total_bedrooms&#x27;, &#x27;population&#x27;,\n",
       "                                  &#x27;households&#x27;])])</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-29\" type=\"checkbox\" ><label for=\"sk-estimator-id-29\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">log</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;total_rooms&#x27;, &#x27;total_bedrooms&#x27;, &#x27;population&#x27;, &#x27;households&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-30\" type=\"checkbox\" ><label for=\"sk-estimator-id-30\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">LogTransformer</label><div class=\"sk-toggleable__content fitted\"><pre>LogTransformer()</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-31\" type=\"checkbox\" ><label for=\"sk-estimator-id-31\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">remainder</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;longitude&#x27;, &#x27;latitude&#x27;, &#x27;housing_median_age&#x27;, &#x27;median_income&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-32\" type=\"checkbox\" ><label for=\"sk-estimator-id-32\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">passthrough</label><div class=\"sk-toggleable__content fitted\"><pre>passthrough</pre></div> </div></div></div></div></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-33\" type=\"checkbox\" ><label for=\"sk-estimator-id-33\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;LinearRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.linear_model.LinearRegression.html\">?<span>Documentation for LinearRegression</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>LinearRegression()</pre></div> </div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('log',\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder='passthrough',\n",
       "                                   transformers=[('log', LogTransformer(),\n",
       "                                                  ['total_rooms',\n",
       "                                                   'total_bedrooms',\n",
       "                                                   'population',\n",
       "                                                   'households'])])),\n",
       "                ('linreg', LinearRegression())])"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the pipeline\n",
    "iteration_2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Iteration 3: Linear Regression with Log, Poly2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "ITERATION 3 RESULTS\n",
      "\n",
      "Pipeline: log_poly2 -> linreg\n",
      "Note: X1. Test size: 0.25, Pipeline: Log > Poly2 > LinReg\n",
      "May 30, 2024 09:17 AM UTC\n",
      "\n",
      "Predictions:\n",
      "                          Train            Test\n",
      "MSE:            3,329,236,889.32 3,350,722,399.55\n",
      "RMSE:                 57,699.54       57,885.42\n",
      "MAE:                  42,383.21       42,493.32\n",
      "R^2 Score:                 0.63            0.64\n",
      "\n",
      "Permutation Feature Importance:\n",
      "           Feature Importance Mean Importance Std\n",
      "          latitude            1.40           0.01\n",
      "         longitude            1.20           0.01\n",
      "    total_bedrooms            1.04           0.01\n",
      "     median_income            1.02           0.01\n",
      "        population            0.62           0.01\n",
      "       total_rooms            0.43           0.01\n",
      "        households            0.21           0.00\n",
      "housing_median_age            0.02           0.00\n",
      "\n",
      "Variance Inflation Factor:\n",
      "          Features   VIF Multicollinearity\n",
      "    total_bedrooms 32.40              High\n",
      "        households 30.01              High\n",
      "       total_rooms 13.80              High\n",
      "          latitude  8.74          Moderate\n",
      "         longitude  8.43          Moderate\n",
      "        population  6.75          Moderate\n",
      "     median_income  1.83               Low\n",
      "housing_median_age  1.30               Low\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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sGfvYnTt31F5HpT9b2bX4ww8/KLxuyJAhDIfDUfheKO93hSb79+9nALD/+fr6Mo8ePSrXewkhpLxKx2DXrl1jADB79+5VeN25c+cUHj927BgDgLlz547abaempjIAmO+++65cbZF9r2/fvp1JTU1lXr9+zZw+fZpxcnJiOBwOuy/ZPW7kyJEK74+NjWW0tbWZ5cuXKzz++PFjRkdHh31cLBYzVlZWjI+PDyMSidjXbdmyhQGgcA+UxY7y94mAgADGyMiIefnypcJ+5O/ba9asYQAwMTEx1d5GVSIiIlTec2bMmMEYGhqy981PP/2UEQgETHFxscbtVcSsWbMYBwcH9vO4cOECA4AJDQ1lX1NcXMw4Ozszjo6OTGZmpsL75T9HVb8RGObttXL58mWFx1WdL1Xxj+wee/XqVfaxHTt2qDxn70K2Tfm/E3XHVN6/PYZR/xuAYcof76mL0Ut/trJr0dvbmykoKGBfd+rUKQYAs3jxYvaxcePGMQAUYi2GYZhWrVoxbdq0UdqXOjwej41/zM3NmV9//bXc7yW1g5bpkQaHx+NhwoQJSo/Lr4fOzc1FWloaOnfujPz8fISHh5e53eHDh8PU1JT9t2xGRHkqtXTv3l1hVkqLFi0gEAjY90okEly8eBEDBw5UyOvUpEkT9O7du8ztywiFQlhaWsLS0hJNmjTB119/jQ4dOuDYsWMKr3N2dmZn98gcOnQInTt3hqmpKdLS0tj/unfvDolEgqtXrwKQJlDU0dFRGKXQ1tbG7Nmzy2zf8ePHUVJSgsWLFyvl5ynPCFNNtBGQnuuioiJ2pBYALly4gKysLAwfPpx9zMTEBLdv38br16/Ltd2ynD17Funp6Rg5ciT72MiRI/Hw4UM8ffqUfezIkSPgcDj47rvvlLZR1SN18n832dnZSEtLQ2BgIKKjo5GdnV2l+6oshmFw5MgR9O/fHwzDKFwbPXv2RHZ2ttLSyXHjxinlSODxeOx1KZFIkJ6eDkNDQzRr1qzSSy/PnDkDbW1tzJkzR+Hxzz//HAzD4OzZswqPl/VdUZYuXbogODgYhw4dwrRp06CrqwuhUFipthNCSHkdOnQIxsbG6NGjh8J3cJs2bWBoaIjLly8DADsT4tSpU1Ve6XPixImwtLSEnZ0d+vbtyy7r9vX1VXjdtGnTFP599OhRlJSUYNiwYQptt7GxQdOmTdm23717FykpKZg2bZpCkmZZSgBNUlNTcfXqVUycOBGNGzdWeK489+2aaCMAuLm5wcfHBwcPHmQfk0gkOHz4MPr378/eN01MTCAUChEcHFzmNsujuLgYBw8exPDhw9nPQ7ZkbO/evezrQkNDERMTg7lz5yoleK/O+KewsBBpaWlo3749ALxTOoaqVt6/PRlVvwGAqo/3ZNfijBkzFHJJ9e3bF+7u7jh9+rTSe0r/bXbu3LlCFTHPnj2LM2fOYN26dWjcuDHFP/UALdMjDY69vb3KSg5Pnz7FN998g0uXLiEnJ0fhufJ8yZYOHmQdU6XXY5fnvbL3y96bkpKCgoIClUtpKrK8Rk9PDydPngQAtrRpo0aNlF7n7Oys9FhUVBQePXqkdllgSkoKAODly5ewtbWFoaGhwvOyab6avHjxAlpaWvD09CzztarURBsBoGXLlnB3d8fBgwcxadIkANIlehYWFmwOCgBYvXo1xo0bBwcHB7Rp0wZ9+vTB2LFj4eLiUpnDw549e+Ds7Awej4fnz58DkC5DMzAwwN69e7FixQoA0s/Rzs4OZmZmldpPRVy/fh3fffcdbt68ifz8fIXnsrOzyxXcymRkZEAsFrP/1tfXr9D71UlNTUVWVha2bNmCLVu2qHyN7NqQUfU3IMvDtXHjRsTExCjkKSjPEjlVXr58CTs7OxgZGSk8Lqs49fLlS4XHy/quKIu1tTU7ZX7IkCFYsWIFevTogaioKEpgTgipNlFRUcjOzoaVlZXK52XfwYGBgRg8eDCWLl2Kn3/+GR988AEGDhyIjz/+GDwe753asHjxYnTu3Bna2tqwsLCAh4eHyiIqpb//o6KiwDAMmjZtqnK7siVOsu/r0q/T1dUt874v+0Ht7e1dvoMppSbaKDN8+HB8/fXXSEhIgL29Pf7991+kpKQoDMbNmDEDf/31F3r37g17e3sEBQVh2LBh6NWrV2UODxcuXEBqairatWvHxj+AdIBl//79WLVqFbS0tNill5X9HCsiIyMDS5cuxYEDB5RiiIp2zhQUFCi9p6ruyeX925NRFf8AVRvvAW+vRVWxt7u7O0JCQhQek+U/lVeR+AcAm++sd+/e+PDDD+Ht7Q1DQ0PMmjWrQm0nNYc6o0iDo6oiRFZWFgIDAyEQCLBs2TK4urpCT08P9+/fx1dffVWuUuza2toqH2dKJSGu6vdWhLa2Nrp3717m61R9RiUlJejRowe+/PJLle9xc3N75/a9q5ps4/Dhw7F8+XKkpaXByMgIJ06cwMiRIxUC22HDhqFz5844duwYLly4gDVr1mDVqlU4evRohWa0AUBOTg5OnjyJwsJClcHmvn37sHz58ioZ+VO3jdJJIl+8eIFu3brB3d0dP/30ExwcHMDlcnHmzBn8/PPP5fq7kTdo0CBcuXKF/fe4ceOUkrtWhqwdo0ePVpsXrHS+EVV/AytWrMC3336LiRMn4vvvv4eZmRm0tLQwd+7cCh9rZVX1d8WQIUOwaNEi/P3335g6deq7NI0QQtQqKSlRmsUiT/Yjk8Ph4PDhw7h16xZOnjyJ8+fPY+LEiVi3bh1u3bqlNIhUEc2bN69UDFRSUgIOh4OzZ8+q/A5+lzZVlZps4/Dhw7Fw4UIcOnQIc+fOxV9//QVjY2OFjiYrKys8ePAA58+fx9mzZ3H27Fns2LEDY8eOVVkApiyy62bYsGEqn79y5YrKxOoVVd74R9aWGzdu4IsvvoCPjw8MDQ1RUlKCXr16VTgmOHjwoNKqjar6DVDevz0ZVfFPVcd7laEu/qksV1dXtGrVCnv37qXOqDqMOqPIe+Hff/9Feno6jh49ioCAAPZxWYWV2mZlZQU9PT2F0SAZVY9VB1dXV+Tl5ZUZyDk6OuKff/5BXl6eQvATERFRrn2UlJQgLCwMPj4+al+nLlioiTbKDB8+HEuXLsWRI0dgbW2NnJwcNnGnPFtbW8yYMQMzZsxASkoKWrdujeXLl1e4M+ro0aMoLCzEpk2b2KSl8u3+5ptvcP36dfj7+8PV1RXnz59HRkaGxtlR6j5HU1NTldVFSs/SOXnyJEQiEU6cOKEwY6f0lO/yWrduncIIl/yS1PJSdUyWlpYwMjKCRCIp1w8RdQ4fPowuXbrgjz/+UHg8KytL4ZxUpEPQ0dERFy9eRG5ursLsKNnSYEdHx0q3tzwKCgoAVHwUlxBCKsLV1RUXL15Ep06dylUmvn379mjfvj2WL1+Offv2YdSoUThw4AAmT55co4mhAWnbGYaBs7OzxkEt2fd1VFSUwizpoqIixMTEoGXLlmrfK5uV9OTJE41t0RT/VHcbZZydndGuXTscPHgQs2bNwtGjRzFw4EClmWtcLhf9+/dH//79UVJSghkzZuD333/Ht99+W6FZ/UKhEH///TeGDx+uUK1PZs6cOdi7dy+6dOnCLmN/8uSJxvu9pvgHUK6wVjr+yczMxD///IOlS5di8eLF7ONRUVHlOqbSevbs+c5LGjVdGxX521OlIvFeef8+ZddiRESEwrUoe6y64x9AGgOJRKJq3w+pPMoZRd4Lst52+VEIsViMjRs31laTFMhmNB0/flwh/9Dz58+VcspUl2HDhuHmzZs4f/680nNZWVkoLi4GAPTp0wfFxcUK5V4lEgk2bNhQ5j4GDhwILS0tLFu2TGmURf7c8Pl8lZ0lNdFGGQ8PDzRv3hwHDx7EwYMHYWtrq9CRKZFIlH7gW1lZwc7OTuHGl5aWhvDwcKUpz6Xt2bMHLi4umDZtGoYMGaLw3/z582FoaMiOeg0ePBgMw2Dp0qVK2ynP5+jq6ors7Gw8evSIfSwxMVEpt5iqv5vs7Gzs2LFD47Go06ZNG3Tv3p39rzLLNVUdk7a2NgYPHowjR46oDPRTU1PLtW1tbW2lkcpDhw4plSDm8/kAylcuuE+fPpBIJPjtt98UHv/555/B4XAq3GmpTlpamspR1m3btgGAUs4UQgipSsOGDYNEIsH333+v9FxxcTH7fZmZman0XSUbnJLdOw0MDADUXEn2QYMGQVtbG0uXLlVqG8MwSE9PByD9HrW0tMTmzZsVlpzv3LmzzLZaWloiICAA27dvR1xcnNI+ZNTdX2qijfKGDx+OW7duYfv27UhLS1NYogeA3Z+MlpYWOwNZdh6LiooQHh6OxMREjfs6duwYhEIhZs6cqRT/DBkyBP369cORI0cgEonQunVrODs7Y/369UrHU57P0dHREdra2myOUZnSvwdUxT8A2KrNFWVra6sQ/1Rm4EzdMZX3b0+TisR76mLL0nx9fWFlZYXNmzcrxMVnz57Fs2fP0Ldv3zK3UR7FxcUql/L9999/ePz4McU/dRzNjCLvhY4dO8LU1BTjxo3DnDlzwOFwsHv37ipfJvculixZggsXLqBTp06YPn06+wPW29sbDx48qPb9f/HFFzhx4gT69euH8ePHo02bNhAKhXj8+DEOHz6M2NhYWFhYoH///ujUqRMWLFiA2NhYeHp64ujRo+WaedGkSRMsWrQI33//PTp37oxBgwaBx+Phzp07sLOzw8qVKwFIOy02bdqEH374AU2aNIGVlRW6du1aI22UN3z4cCxevBh6enqYNGmSQtL13NxcNGrUCEOGDEHLli1haGiIixcv4s6dO1i3bh37ut9++w1Lly7F5cuX8cEHH6jcz+vXr3H58mWlJNcyPB4PPXv2xKFDh/Drr7+iS5cuGDNmDH799VdERUWxU8avXbuGLl26sNOR27Rpg4sXL+Knn36CnZ0dnJ2d4efnhxEjRuCrr77CRx99hDlz5iA/Px+bNm2Cm5ubQlLOoKAgduRz6tSpyMvLw9atW2FlZVVmcFld1B3Tjz/+iMuXL8PPzw+ffPIJPD09kZGRgfv37+PixYvIyMgoc9v9+vXDsmXLMGHCBHTs2BGPHz/G3r17lfJsuLq6wsTEBJs3b4aRkRH4fD78/PxU5mHo378/unTpgkWLFiE2NhYtW7bEhQsX8Pfff2Pu3LkKycrfxZ49e7B582YMHDgQLi4uyM3Nxfnz5xEcHIz+/fsrjUoSQkhVCgwMxNSpU7Fy5Uo8ePAAQUFB0NXVRVRUFA4dOoRffvkFQ4YMwa5du7Bx40Z89NFHcHV1RW5uLrZu3QqBQIA+ffoAkC4j8vT0xMGDB+Hm5gYzMzN4e3tXW54gV1dX/PDDD1i4cCFiY2MxcOBAGBkZISYmBseOHcOUKVMwf/586Orq4ocffsDUqVPRtWtXDB8+HDExMdixY0e58jH9+uuv8Pf3R+vWrTFlyhQ4OzsjNjYWp0+fZuO8Nm3aAAAWLVqEESNGQFdXF/3796+xNsoMGzYM8+fPx/z582FmZqbUeTJ58mRkZGSga9euaNSoEV6+fIkNGzbAx8eHzYmYkJAADw+PMpfk7927F+bm5ujYsaPK5wcMGICtW7fi9OnTGDRoEDZt2oT+/fvDx8cHEyZMgK2tLcLDw/H06VN2sFL2Oc6ZMwc9e/aEtrY2RowYAWNjYwwdOhQbNmwAh8OBq6srTp06pZRXSSAQICAgAKtXr0ZRURHs7e1x4cKFWl1Roe6Yyvu3p0lF4j11MXppurq6WLVqFSZMmIDAwECMHDkSycnJ+OWXX+Dk5IR58+ZVyeeSl5cHBwcHDB8+HF5eXuDz+Xj8+DF27NgBY2NjfPvtt1WyH1JNaqZoHyFVT1WJU1Wl4GWuX7/OtG/fntHX12fs7OyYL7/8kjl//rxSidfSpdll5V7XrFmjtE2UKj0sKxtc+jUzZ85Ueq+jo6NSifp//vmHadWqFcPlchlXV1dm27ZtzOeff87o6emp+RTeGjduHMPn88t8naOjI9O3b1+Vz+Xm5jILFy5kmjRpwnC5XMbCwoLp2LEjs3btWkYsFrOvS09PZ8aMGcMIBALG2NiYGTNmDBMaGqpUFlfV58EwDLN9+3amVatWDI/HY0xNTZnAwEAmODiYfT4pKYnp27cvY2RkpFSKuKrbqElUVBRbIjYkJEThOZFIxHzxxRdMy5YtGSMjI4bP5zMtW7ZkNm7cqPA62WdQuoywvHXr1jEAmH/++Ufta3bu3MkAYP7++2+GYaTljdesWcO4u7szXC6XsbS0ZHr37s3cu3ePfU94eDgTEBDA6OvrMwAUrrcLFy4w3t7eDJfLZZo1a8bs2bNH5fk6ceIE06JFC0ZPT49xcnJiVq1axWzfvl2pjHFgYGCZJaMrStXfs6ZjSk5OZmbOnMk4ODgwurq6jI2NDdOtWzdmy5Yt7GtkpYcPHTqktL/CwkLm888/Z2xtbRl9fX2mU6dOzM2bN1Ue299//814enoyOjo6CtdU6e8PhpFes/PmzWPs7OwYXV1dpmnTpsyaNWsUylAzTMW+K0q7c+cOM3ToUKZx48YMj8dj+Hw+07p1a+ann35iioqKNL6XEEIqSl2Z+S1btjBt2rRh9PX1GSMjI6Z58+bMl19+ybx+/ZphGIa5f/8+M3LkSPa7ysrKiunXrx9z9+5dhe3cuHGDadOmDcPlcpVirdI0fa/Lk93jUlNTVT5/5MgRxt/fn+Hz+Qyfz2fc3d2ZmTNnMhEREQqv27hxI+Ps7MzweDzG19eXuXr1qtJ9QhY7lo43njx5wnz00UeMiYkJo6enxzRr1oz59ttvFV7z/fffM/b29oyWlpbSvbYq21iWTp06MQCYyZMnKz13+PBhJigoiLGysmK4XC7TuHFjZurUqUxiYqLSZ6Dp/pWcnMzo6OgwY8aMUfua/Px8xsDAgPnoo4/Yx0JCQpgePXqw8VeLFi2YDRs2sM8XFxczs2fPZiwtLRkOh6NwraampjKDBw9mDAwMGFNTU2bq1KnMkydPlM5XfHw8e66MjY2ZoUOHMq9fv1a6Hnfs2KF0nt6VbJt37twp1zExTNl/ewyj+TdAeeM9dTG67O+wdLx78OBBNuY3MzNjRo0axcTHxyu8Rt1vGHW/I+SJRCLm008/ZVq0aMEIBAJGV1eXcXR0ZCZNmlSl54RUDw7D1KGpIYQQJQMHDsTTp08rvU6dEEIIIYQQQgipSyhnFCF1iCzZsExUVBTOnDmjdnkXIYQQQgghhBBS39DMKELqEFtbW4wfPx4uLi54+fIlNm3aBJFIhNDQUDRt2rS2m0cIIYQQQgghhLwzSmBOSB3Sq1cv7N+/H0lJSeDxeOjQoQNWrFhBHVGEEEIIIYQQQhoMmhlFCCGEEEIIIYQQQmoM5YwihBBCCCGEEEIIITWGOqMIIYQQQgghhBBCSI2hnFF1TElJCV6/fg0jIyNwOJzabg4hhBDSYDEMg9zcXNjZ2UFLi8bn6juKoQghhJCaURUxFHVG1TGvX7+Gg4NDbTeDEEIIeW+8evUKjRo1qu1mkHdEMRQhhBBSs94lhqLOqDrGyMgIgPSkCgSCWm4NIYQQ0nDl5OTAwcGBvfeS+o1iKEIIIaRmVEUMRZ1RdYxsWrlAIKBAihBCCKkBtKSrYaAYihBCCKlZ7xJDUYIEQgghhBBCCCGEEFJjqDOKEEIIIYQQQgghhNQY6owihBBCCCGEEEIIITWGOqMIIYQQQgghhBBCSI2hzihCCCGEEEIIIYQQUmOoM4oQQgghhBBCCCGE1BjqjCKEEEIIIYQQQgghNUanthtACCGE1GcZQjEKxBLoc7VhxufWdnMIIYQQ8h6ieITUN9QZRQghhFSCUFSM0FdZWHH6GSKSc9HM2ghf9/VAKwcT8Hl0eyWEEEJI9aN4hNRXtEyPEEIIqYTQV1kYve02whJzIClhEJaYg9HbbuPBq6zabhohhBBC3hMUj5D6ijqjCCGEkArKEIqx4vQzlc8tP/MMGUJxDbeIEEIIIe8bikdIfUadUYQQQkgFFYgliEjOVflcZFIuCookNdwiQgghhLxvKB4h9Rl1RhFCCCEVpM/VRjNrI5XPudkYQV9Xu4ZbRAghhJD3DcUjpD6jzihCCCGkgsz4XHzd10Plc4v6eFAVG0IIIYRUO4pHSH1GnVGEEEJIJbRyMMHeyX7wtBNAR4sDTzsB9k72g4+DSW03jRBCCCHvCYpHSH1FtR4JIYSQSuDzdNCpiQX2TPJDQZEE+rraNAJJCCGEkBpF8Qipr6gzihBCCHkHFPARQgghpLZRPELqG1qmRwghhBBCCCGEEEJqDHVGEUIIIYQQQgghhJAaQ51RhBBCCCGEEEIIIaTGUGcUIYQQQgghhBBCCKkx1BlFCCGEEEIIIYQQQmoMdUYRQgghhBBCCCGEkBpDnVGEEEIIIYQQQgghpMZQZxQhhBBCCCGEEEIIqTHUGUUIIYQQQgghhBBCagx1RhFCCCGEEEIIIYSQGkOdUYQQQgghhBBCCCGkxlBnFCGEEEIIIYQQQgipMdQZRQghhBBCCCGEEEJqjE5tN4AQQohqGUIxCsQS6HO1Ycbn1nZzCCGEEEIIIaRKUGcUIYTUMUJRMUJfZWHF6WeISM5FM2sjfN3XA60cTMDn0dc2IYQQQgghpH6jZXqEEFLHhL7KwuhttxGWmANJCYOwxByM3nYbD15l1XbTCCGEEEIIIeSdUWcUIYTUIRlCMVacfqbyueVnniFDKK7hFhFCCCGEEEJI1aLOKEIIqUMKxBJEJOeqfC4yKRcFRZIabhEhpL5ISEjA6NGjYW5uDn19fTRv3hx3795ln2cYBosXL4atrS309fXRvXt3REVFKWwjIyMDo0aNgkAggImJCSZNmoS8vDyN+y0sLMTMmTNhbm4OQ0NDDB48GMnJyQqviYuLQ9++fWFgYAArKyt88cUXKC4uVnjNv//+i9atW4PH46FJkybYuXPnu30ghBBCCKmzqDOKEELqEH2uNppZG6l8zs3GCPq62jXcIkJIfZCZmYlOnTpBV1cXZ8+eRVhYGNatWwdTU1P2NatXr8avv/6KzZs34/bt2+Dz+ejZsycKCwvZ14waNQpPnz5FcHAwTp06hatXr2LKlCka9z1v3jycPHkShw4dwpUrV/D69WsMGjSIfV4ikaBv374Qi8W4ceMGdu3ahZ07d2Lx4sXsa2JiYtC3b1906dIFDx48wNy5czF58mScP3++Cj8lQgghhNQZTB0THx/PjBo1ijEzM2P09PQYb29v5s6dO+zzJSUlzLfffsvY2Ngwenp6TLdu3ZjIyEiFbaSnpzMff/wxY2RkxBgbGzMTJ05kcnNzNe63oKCAmTFjBmNmZsbw+Xxm0KBBTFJSksJrXr58yfTp04fR19dnLC0tmfnz5zNFRUUKr7l8+TLTqlUrhsvlMq6ursyOHTsqdPzZ2dkMACY7O7tC7yOENBzXolIZx69OKf0XEpVa200jpEFpSPfcr776ivH391f7fElJCWNjY8OsWbOGfSwrK4vh8XjM/v37GYZhmLCwMAaAQtx19uxZhsPhMAkJCSq3m5WVxejq6jKHDh1iH3v27BkDgLl58ybDMAxz5swZRktLSyGu2rRpEyMQCBiRSMQwDMN8+eWXjJeXl8K2hw8fzvTs2bO8H0GDOp+EEEJIXVYV99w6NTOKRvUIIQRo5WCCvZP94GkngI4WB552Auyd7AcfB5PabhohpI46ceIEfH19MXToUFhZWaFVq1bYunUr+3xMTAySkpLQvXt39jFjY2P4+fnh5s2bAICbN2/CxMQEvr6+7Gu6d+8OLS0t3L59W+V+7927h6KiIoXturu7o3Hjxgrbbd68OaytrdnX9OzZEzk5OXj69Cn7GvltyF4j24YqIpEIOTk5Cv8RQgghpH6oUzXCV61aBQcHB+zYsYN9zNnZmf3/DMNg/fr1+Oabb/Dhhx8CAP78809YW1vj+PHjGDFiBJ49e4Zz587hzp07bDC1YcMG9OnTB2vXroWdnZ3SfrOzs/HHH39g37596Nq1KwBgx44d8PDwwK1bt9C+fXtcuHABYWFhuHjxIqytreHj44Pvv/8eX331FZYsWQIul4vNmzfD2dkZ69atAwB4eHggJCQEP//8M3r27FltnxshpGHh83TQqYkF9kzyQ0GRBPq62jDjc2u7WYSQOiw6OhqbNm3CZ599hq+//hp37tzBnDlzwOVyMW7cOCQlJQGAQoeQ7N+y55KSkmBlZaXwvI6ODszMzNjXlJaUlAQulwsTExON21W1X9lzml6Tk5ODgoIC6OvrK+175cqVWLp0qdrPhBBCCCF1V52aGUWjejSqRwh5y4zPhb2JPnVEEULKVFJSgtatW2PFihVo1aoVpkyZgk8++QSbN2+u7aZVm4ULFyI7O5v979WrV7XdJEIIIaRaZQjFSMgsaBAVtutUZ5RsVK9p06Y4f/48pk+fjjlz5mDXrl0AUO9H9VRZuXIljI2N2f8cHBxUvo4QQgghRB1bW1t4enoqPObh4YG4uDgAgI2NDQAoVblLTk5mn7OxsUFKSorC88XFxcjIyGBfU5qNjQ3EYjGysrI0blfVfuXbpe41AoFA5awoAODxeBAIBAr/EUIIIQ2RUFSMkOdpGL3tNgLWXMbobbcR8jwNQlFx2W+uo+pUZxSN6tGoHiGEEEIqrlOnToiIiFB4LDIyEo6OjgCkaQ9sbGzwzz//sM/n5OTg9u3b6NChAwCgQ4cOyMrKwr1799jXXLp0CSUlJfDz81O53zZt2kBXV1dhuxEREYiLi1PY7uPHjxU6uoKDgyEQCNgOtA4dOihsQ/Ya2TYIIYSQ91noqyyM3nYbYYk5kJQwCEvMwehtt/HgVVZtN63S6lRnFI3q0ageIYQQQipu3rx5uHXrFlasWIHnz59j37592LJlC2bOnAkA4HA4mDt3Ln744QecOHECjx8/xtixY2FnZ4eBAwcCkMZcvXr1wieffIL//vsP169fx6xZszBixAiVOTcBabqESZMm4bPPPsPly5dx7949TJgwAR06dED79u0BAEFBQfD09MSYMWPw8OFDnD9/Ht988w1mzpwJHo8HAJg2bRqio6Px5ZdfIjw8HBs3bsRff/2FefPmVf+HRwghhNRhGUIxVpx+pvK55Wee1dsle3WqM4pG9QghhJC6ryHlK2go2rZti2PHjmH//v3w9vbG999/j/Xr12PUqFHsa7788kvMnj0bU6ZMQdu2bZGXl4dz585BT0+Pfc3evXvh7u6Obt26oU+fPvD398eWLVsU9sXhcLBz50723z///DP69euHwYMHIyAgADY2Njh69Cj7vLa2Nk6dOgVtbW106NABo0ePxtixY7Fs2TL2Nc7Ozjh9+jSCg4PRsmVLrFu3Dtu2baMCMIQQQt57BWIJIpJzVT4XmZSLgiJJDbeoanAYhmFquxEyd+7cQceOHbF06VIMGzYM//33Hz755BNs2bKFDaZWrVqFH3/8Ebt27YKzszO+/fZbPHr0CGFhYWww1bt3byQnJ2Pz5s0oKirChAkT4Ovri3379qnd9/Tp03HmzBns3LkTAoEAs2fPBgDcuHEDACCRSODj4wM7OzusXr0aSUlJGDNmDCZPnowVK1YAkCZY9/b2xsyZMzFx4kRcunQJc+bMwenTp8sdTOXk5MDY2BjZ2dk0S6qeyBCKUSCWQJ9LFc8IIQ2bUFSM0FdZWHH6GSKSc9HM2ghf9/VAKwcT8Hl1qkBvudA9t+JiYmLg5uaGsLAwNG3atLabo4DOJyGEkIYoQyhml+iV5mknwJ5JfjX+O7Qq7rl1amYUjeqR+qQhJpEjhBBNGmK+AlIxZ86cwZQpU+pcRxQhhBDSUJnxufi6r4fK5xb18ai3EyLq1MyomkKjeqQqyDqiSts72Q+dmljUQosIIfVNfZpZWRdH5d4V3XMbFjqfhBBCGiqhqBgPXmVh+ZlniEzKhZuNERb18YBPLc1Or4p7bv2bU18FaFSPvKuyksjVxx9lhJCaUx+XuzXUfAWEEEIIIXUdn6eDTk0ssGeSHwqKJNDXrfsDmWWpmxFvNZNVliGksuhHGSHkXciWu8nIlrvV5ZmV+lxtNLM2Ujkzys3GCPq62rXQKkIIIYSQ90d974CSV6dyRhFSX8h+lKlCP8oIIZrU1/K8DTVfASGEEEIIqXnUGUVIJdCPMkJIZdXnmZWtHEywd7IfPO0E0NHiwNNOgL2T/eDjYFLbTSOEEEIIIfXIe7lMj5CqIPtRpiqJHCGEqFOfl7s1xHwFhBBCCCGk5lFnFCGVRD/KCCGVIZtZqaoaZ3lnVtZ2FT76riOEEEIIIe+COqMIeUf0o4wQUlGVnVlZH6vwEUIIIYQQUhpFroQQQkgNq+zMyvpYhY8QQgghhJDSKIE5IYQQUg4ZQjESMguqtNqdGZ8LexP9ci/Nq49V+AghhBBCCCmNZkYRQgghGtSVpXH1uQofIYQQQggh8mhmFCGEEKKBbGlcWGIOJCUMuzTuwausGm2HrAqfKnW9Ch8hhBBCCCHyqDOKEEIIUaMuLY2TVeFTpbxV+AghhBBCCKkLqDOKEEIIUaO2l8aVzlMlq8LnaSeAjhYHnnYC7J3sV2YVPkIIIYQQQuoSyhlFCCGEqCFbGheWmKP0XHUujdOUp6oyVfgIIYQQQgipS2hmFCGEEKJGbS2NKytPVUWq8BFCCCGEEFLXUGcUIYQQokFZS+NKL6V7V3UpTxUhhBBCCCHVgZbpEUIIIRrweToql8YJRcUIeZ6mcikdn1f522tV5anKEIpRIJZAn0tL+QghhBBCSN1CM6MIIYSQcii9NK6spXSVJctTpUp58lTJOslGb7uNgDWXMXrbbYQ8T4NQVPxO7SKEEEIIIaSqUGcUIYQQUkHVuZTuXfNUVVcnWU2o6iWPhBBCCCGkbqLOKEIIIaSCqmopnTpl5alSp77mm6LZXIQQQgghVaygADh+HNi9u7ZbohLljCKEEEIqSLaULiwxR+m58iylK4u6PFVlqe5OsvKoTK4q2WwuGdlsrr2T/dCpiUV1NZUQQgghpM6rUGyVmwucPg0cPQqcOQMIhUBQEDBmTM00tgJoZhQhhBBSQe+6lK4i+5HPU1WWd8039S4qO7upvs7mIoQQQsi7oyX66pU7tsrIAHbuBAYMACwtgZEjgehoYNEiIDwcOH++VtpfFuqMIoQQQiqhokvpaiLYqqlOMlUqm6uq3LO5cnMBSfXP7CKEEEJI9aMl+mXTGFslJQG//y6d9WRtDUycKO2UWrkSiI0F7t4FFi4EmjWr7cNQi8MwDFPbjSBv5eTkwNjYGNnZ2RAIBLXdHEIIIWXIEIo1LqUTiooR+ioLK04/Q0RyLppZG+Hrvh5o5WACPq/qV8sLRcV48CoLy888Q2RSLtxsjLCojwd8qml/gPQzkAVLpXnaCbBnkp/SZyObcs7hAPMPPcSNF+lK7/Wx4GG3TRqM/j4CnDoFnD0LfPBBlbWb7rkNC51PQgipP2QdUaXREn0pVbGVXU4KekXcxKCXt+EV/RgcLS1pXDR4MDBwIGBrW2Ptq4p7LuWMIoQQ8l6rTI4jeeWtbidT3fmQKptv6l1UJFeVqs65+UFu4PN0EByWDG5xETrH3ke/Z9cw4OUdaAuFQKtWwNKldXp0jxBCCCHlU9YSfVWDWO8bWWzllJGAXpE30SvyOnwSoyDS1sF1p1aw37AJpiOGAObmtd3USqPOKEIIIe+lmpixVJvBVk0GcRVJ6K6qc+6THbdxxK0Ao67tRqv7/8K4UIj8Js0g+fwLaI8aCbi51chxEEIIIaT61YWCK3UWwwBPnsD0wCFc3LkXzonRyNfl4V/nNtjuOxCXXNuisbMN9oz3A+p5hx11RhFCCKkz3nWWUkXUxIyl9yXYkuWqUjXdXj5XlXznnFaJBG3jw9D/2VX0jrgO84IcFLu4omDWLKR8NARFHl41ch0QQgghpGZVd1XieodhpDmejh4FjhwBoqJgIBCA/0EQpmqPwBXn1ijU1WNfXt15QGsKdUYRQgipdTWdV6mmZiy9T8GWLKG7qlxVMgWiYujfv4PFT6+gb0QIrPMyEC+wxKHm3XHWMwAb1k5CXGah9Do4dbnarwNCCCGE1LzyDmI1aBIJcOOGtAPq6FEgLk665G7gQOCXX4CuXcGHNsa+ysIrDbFVfUaRHSGEkFpX03mVamrG0vsUbKnNVcUwwP37KNizD9aHD+HIqzik8E1x2t0fJ90DEGrfDAxHC552AmQVFCt8Vim5hQiJSoWJvi7sTPQb1OdFCCGEvM/KM4jV4BQVAVeuSGc/HTsGJCdLk44PGiRNQt65M6DztouGD9R4HtCaRJ1RhBBCalVt5FWqyRlL71uwxZ6rp0+BAwdQcuAgtJ5HQcw3xllPf1h9uxZjo3go0VL8jBf2dsePZ8PZfwd5WiPIyxrbQ2Kx9VoMzZIihBBCGpDqLrhSk6kfNCosBC5elHZAnTgBZGQATk7A6NHSDig/P0BLS+MmGlIHlDyK5gghhNSq2sirVJMzlmqjul2tiYoCDh4EDhyQdkYZGyO1ex980Wo0bji2RLG2DnrwrLF6uLSTKTL5bedcYzMD3I7JAABYGHIR5GWN+YcesZuu7tlyhBBCCKl5VR0T1XTqB5Xy8oBz56QdUKdPA7m5gLs7MH26dBZUq1YAh1MzbanDqDOKEEJIraqtvEo1PWOpwXZAvXwJ/PWXtAPq/n2Azwc+/BC5i5ci078Lph16qnBug8OSERqXiSkBrgjytIZAXxdmfC4yhGL2OhjSphG2h8Sq3B2VfCaEEEKIOjWd+oGVlQWcOiXtgDp3DigsRHGLlsifPQ8lgwbBpE3L6tt3PaV5PhghhLzHMoRiJGQWIEMoru2mNGiyWUqqVGdeJfkZS1e+7II9k6RBSl1dAlbT16PG/SUmAr/+CnTsKJ1qvngx4OwM/PUXhK9eI2TpLxieaIWQV7kqZ72l5Ymx+lw4dHW02PMrfx04mBq8F1UICSGEEFJ1ykr9UOUxVGoqsG0b0Ls3YGUFjBkDJCVB9N1S3PnnDgZM3IBWjB8+DslByPM0CEXFFd5FQ/49UjcjbkIIqUV1Ynrve6Y8s5Sqa+1/6W3VmRwDb9T09ah2f3pF4J/6W7oM78oVaYLNnj2BPXuAAQMAIyMAQOjzNHZEMi4jv0Kz3mTXQVhizntThZAQQghpqGo6pqqR1A8JCdLk40eOAFevSh8LCAB++klaCa9RI9yRi4WAys3Oeh9+j3AYhmFquxHkrZycHBgbGyM7OxsCgaC2m0PIeymk1A1EhnLVVL8MoVgpr1J13IxlwZEBVxsMpMGLjjYQm56PpSfC6tRNv6avR/n9CQrz0DPyJvqFX0NA3ENwAKBrV2DECOCjjwBTU4X3ZgjFGL3tNtuJZGHIxYLe7gq5n8rT/kyhGI8SsjFu+38Vel9F0T23YaHzSQghdUNtdaSUjkPkedoJKr/MPzoaOHpU2gF16xagqwt06yZNQD5ggHRWVBW1QRajZgjFmLDzP6TlKc6Iqiu/R6rinkudUXUMBVKkPqtrM0oqo9puYqTSqrIzRj44cjDTR29vW2y5Gs0GShP9nXD+aTKCw5LfaT9VpaavxwyhGJP/dxmNQi6i/7OrCIi5D12JBP85eOFu+yCMWjUPps6N1L4/IbMAAWsuQ1LyNrTo4WmNnl7KCct9yghIhaJiPHiVpXK2XFUFsnTPbVjofBJCSN1QmwO7VbbvZ8+knU9HjgAPHgB6ekCvXtIOqH79ABMTlW9TFQvJ6GhxcOXLLrA30Vd6TlUHnqq4tK78HqmKe27DmN9FCKlVDWkaaW1UdiPqlbX2v6I3Y1lSSwtDLib6O2HuwQcApDN4AtwsICoqwSR/J7xMFyIyOa/S+6kqNXE9ZgjFKMjOg+ByMPT/Ooi9Z85Av1iE+3bN8FvQZPBGDodpU2cIM/NRaGaucVuqktGrS1helveqCiEhhBDSQJQ3dquuQexKF6hhGGmnk6wDKjwcMDSUdjx9/bU0L5ShYZn7r2xhHlWJ1+cfeoS1Q1sgNC6TnSHVkH6P1K9fiYSQOqnWqlZUg9qq7EZUq8rOGPngSL5aW5CnNYLezNyRdabO6+6Go6EJCA5LrtWbfnVej8IcIV7uP46krbvQ7nEIDMUFKPBugf29J2C7fVt4dmjx9nM58RTNrI3QwdUCAj1d8Hk6KoNIWRLy0iOSaXlieNkJ4GTBr3A7qQOKEEIIqT/Kit3yREUIS8yp8CB2hlAMUZEEDKT9Ruo6sSo0mFVSAty+Le18OnoUiImRpiD48ENg9WqgRw/pjKgKUBcLAcqFeWSxFIcDtR1420NiMbh1I/x+NRpAw/o9Qp1RhJB3UtUzV2qbuhuIhSEXqwa1kK7hhrheHVN9VpWdMfLBkaxam4UhF0Fe1go5jcISczB97312JMpKoFclN/3KjABWJKApl+Ji4NIl4OBB8A4fgWdONnTMG+P3doNwyiMAuY2dsXpwCxQeeaTycxm7/T/sntQOXB0ttbm1WjmY4K+p7fEwPht8rjaEYglaNjKGl51xxdpKCCGEkHqnrNgtK7+oQoPYshUYF8OS4W0vUBg81NSJpTZGKi4Grl2TdkAdOwa8fg1YW0tzYQ4aBHzwgTQn1Dsoa3ZW6VUl64a2VN+Bl5yLUX6N2X9XZ6XpmkadUYSQd9IQl7WVvoGM7uCIgCYW+OrIo3q/DLG+qcrOGPng6FWmtMpbgJsFO0OqNNlIVICb5Tvd9N91GaunjRG2j/PF2guR0pxL1kb4omczeNgYla8BEgkQEgIcOCANvFJTIXF1xWG/Adju4IdIS6e3r80T42pUGnaMb4uvjjxWubmVZ8LRuakFG2SqCiLFEgbH7iewx+thS/l7CCGEkKpUV3O1aordFvZ2x49nw1W+T90gduirLMw9EKpUEKVCKzHEYuCff6Rx0N9/A2lpgIMDMGyYtAOqY0dAu+pmG5U1O6v0qpLwJA1VhK2NEJ+ZD087QfmWG9YjlMC8jqHkm6S+acgJvzOEYoiKJYhKzsPYaq7qRdSrykTWsqSWsipvoqISLD7xVG2SyeMzO8HZgv9OnY7vmkgz5Hka5h4IxZj2jvB1NIWEAULjMtHB1RztnNXkcGIY6bTzAweAQ4eko34ODsDw4cCIEUhw9kDA2n8hKWFgYcjFkDaN4GBqgFeZ+TgWmoB9n7RH0M9X1X4uSwd4YdHxJwDAvt/dVoD2zmZ4niqsN9Uo6Z7bsND5JIS8D+pDrlZ1sVtjMwN88Cb+KE1Vcu9MoRiH78XD09YIy8+EV+z3Rn4+cP68tAPq5EkgJwdo2lSagHzQIMDXF+BwyjyW0p1+79oJKDsmA642XmXm4/C9eABQW31496R2aGJlCJ5O3ep0pATmhJBaV+XLiOoQ2Q2noiM4pPJU3eCrMpG1/Ky34KfJmOTvrHEkys5E/50Cu3ddxip7f+vGprA31cfyM+Fs4OlozkdyTiGsBW9yGTAMEBoKHDwo/e/lS8DGRjrqN3w40L49oKUFANAXitHM2giNTPXZvFBpQhE+8XfB76PboFhSovFzicvIB6CYb2vrtRgs6OWOY6EJao9321hfjXkeCCGEEKJZfcjVqi52y3gTf5Qn/YJQVIxHCdk4FpoAPq9x+VZi5OQAp09LO6DOnpV2SDVvDsybJ+2E8vYuVweUbP/ynX5j2jsioKkF1l6IrHQnoPwxybaxoLc7zj9NxvmnyVg7tEWFqw/XZw3zqAghNarSVSvqgYa4DLEuKs8oX1V0XpQOjvi62ljQ213lzLdFfd+9M1XT9ZOeJ0KeqEjj6FqBWII0oQgT/Z2UpqbPPfgAuya2g/WrF8DBg5Ds3w/t589RYmYOraFDgBEjgM6dVU47N+Nz8d0AT7zKyMf8Q48wuLU9hvp6IClbhPNPkxCTno95PZrikz/vKb13bvem+PrYY5X5tgy42hr/Xv6LycDnhx6WK4Crq8sPCCGEkNpS33K1lm5LRQaxQ19lYdyb+CwuI19tJ1YboxIYH9gDnPobCA6WLslr2xb49lvpDCg3t0q1Xb7Tz8KQC297ASbuuss+X5lOQPljkm1DVjHvx7PhEIqKsW2cLxjgvagiTJ1RhJB31pBLsFN1vZpR06N88tdnG0fTautMlb9+5JfDaWtxYKyvi2m772scXdPnauMTfxelvFZOGQnoF34Njn/OBhJjUCwQ4Lp3ZySP+xK8oB5wsTOFiyUffA35D5zMDbD0RBgGtbZDL28bLDv5tiNwor8TwhJzsHVsG/wcHMXmqprk7wxHMwOk5YkxLVC5XbJcXOpmVMWmCyEpYTSe3/qw/IAQQoii+jqAUN/a3RAGSVUNYi/p7wlHcwMkZBZAn6sNDhSryx2+F6+wjM0yLxM9o26iV8R1dIp/Iq2K5+8PrFol7YBq3FjN3sundKeffBXm0srbCaipI1E+T6md3DLFho6iOkJIlakPN/GKasjLEOuK2h7lq87OVNn18+eNWHY5m3yHj72pPsISc9R2zpjxuejgao4fz4XDPjsFfcOvoV/4NbRIeg6hrh7+aeqH2HlfAz2DkFGshZ3XYhBxPAzNrI0wP8gNzWyMoM/VUXk8xRIgTShCD48mCjOg5EfpjtxPwKyuTZApFCMuIx9H7sfDv2lL7J3sh9Q8EbZei1HYZulgUd7UQBfEpgkVHlN1fuvD8gNCCCFS9XUAob62uyEMkpaOu3S1OIhMycOEHXfZc/FVb3c0ehMjAUBanhh3rjzA3+K70P77ODyjH4PR0kJ6u07Y+8EXOOvqh+kj/avs/JXu9JNVYValvJ2AGjsSk3OxekgLOFvwK9fgekqrthtACCF1nWwEx9NOAB0tDjztBNg72a9BLEOsCyoyypchFCMhswAZQnGVt8OMz4W9ib7Kjpt32W8rBxOMaOuA+YceISwxB5ISBim5hXiekodpgS5Y1Mcd87o3xfKB3ghLzEGm/D4SE9F47zac3P8lrm+eiM9C9iJeYIUZHy5Am9l7sHnK93jYKgBZEm189tdDdvthiTmYuOsuHsVnY9a++wh5ngahqFihXTrawCf+Lthw6bnKdm8PicWHLe1gacjDq0xpR9TMLk1gLdCHj4MJPGyM0MxasaJfWp4Y558mY/1wH3javvl7sRVg3dCWuBaZCl9HUywf6I1pgS6wMOSqPL+aOiar47w3VD/++CM4HA7mzp3LPlZYWIiZM2fC3NwchoaGGDx4MJKTkxXeFxcXh759+8LAwABWVlb44osvUFxcDE0yMjIwatQoCAQCmJiYYNKkScjLy1N4zaNHj9C5c2fo6enBwcEBq1evVtrOoUOH4O7uDj09PTRv3hxnzpyp/AdACKkRsgEE+fvP6G238eBVVm03TaP62m7ZIJcq9W2QVBZ3RabkKZ2Lcdv/Q5/mtmhdmIIZN//CiV1zserzAfD4dSWMbS2QsO43/LrvGvr0/Qbf2PjjulC3Ss+frNNPRjbzWxU3ayOk54mU4qyytll6G++ap7Q+os4oQggpg/wIzpUvu2DPJOkMjffthlFdNN6c34zyCUXFbFW6gDWXMXrbbZUdLFVNKCrG7Zh0HLkXjyuRKThyLx63Y9IrtF9RcQnWXohk/x3kaY0Fvd1xNTINW65Gw9JID+efJmPxiac4dj8BYY+jIfptI9ClC2BvD8E3C2HjbI9P+32ONrP2YMZHX+OMuz8KdfUwyd8ZALDlarTKfW+49BzN7Y1VBmix6flo7WiicZROVFyCEVtv4WpkGlYPbgEPG+l5Cn2VhVHbbmOiv5PS+4LDkqGjxUGQlzWWDvBC56YWuP4iFf5NLbH8TDgWn3iKq5FpWNDbHaPbOyqM4jaE5Qd1wZ07d/D777+jRYsWCo/PmzcPJ0+exKFDh3DlyhW8fv0agwYNYp+XSCTo27cvxGIxbty4gV27dmHnzp1YvHixxv2NGjUKT58+RXBwME6dOoWrV69iypQp7PM5OTkICgqCo6Mj7t27hzVr1mDJkiXYsmUL+5obN25g5MiRmDRpEkJDQzFw4EAMHDgQT548qaJPhRBS1errAEJ9bbdMXR4k1TR4p+o5pXPBMHBPicG8a3vh07czjv4yEbNuHsQrY2vM7v8FWs/ei6wDRzFVuzl+Cc1AWp7ifqrq/JXu9Dt8L15lzAMAk/ydMXHnHdx/mVmhbcorK09pRT/X8jxXF3AYhlGuq0hqDZUlJoS8j2QdTaXJlmaV9fy70JQvIjQuEy9S85SW17laGqJVY9NybT8hswABay5DUsLAwpDLLmOT//+Cwjz0jLyJfuHX0Cn2AbS1OOB07Yq8j4Ygp1c/6JibITwpFz+eDVfI33TuaRI+cLPE4hNP1ZZJXjrAC4uOP1EofZwhFGP0ttsY08ERu2++VF0q2VaAzk0t8LtcR9feyX7wtBVg1JsRzB6e1uj5ZvmhrF3zezbD/v/iEBwmnXEjf5ylbR/ni64e1grnQjY6qtQedaWb30FDvOfm5eWhdevW2LhxI3744Qf4+Phg/fr1yM7OhqWlJfbt24chQ4YAAMLDw+Hh4YGbN2+iffv2OHv2LPr164fXr1/D2lp6XjZv3oyvvvoKqamp4HKVP/tnz57B09MTd+7cga+vLwDg3Llz6NOnD+Lj42FnZ4dNmzZh0aJFSEpKYrexYMECHD9+HOHh0mqlw4cPh1AoxKlTp9htt2/fHj4+Pti8eXO5jr0hnk9C6jL5+1tpOlocXPmyC+zrYP6b+tru0jKE4ipJL1AVebM0LXsEoPa5rPwiBKy+BO+ECPSOvIGekTfgnJmIHB4fl5q0Q6t5k/BppjWeZIjZnJ4Opvrosu5KtZ8/oagYD15lsbmtRrd3xAfNLLH6XAQb88z4wBW5omKUlDDIF0vQqYk5HM35agesS2+zdMW80ueisp+rpueqajC9Ku65NKxPCCGkSlUmqFFKZvmm1G0TK0NkvkNOKfm2cADkl/MGz+fpIFMoxsv0fKUqdvMPPcL64T5wMufDtBzHJ5/fQT4B5khPU0T/shVbb15AQMw96EokuOPghSU9puFFQE8sHBeABUcewyHkNXp7M/jr7isEuFlgSoALbIx5+OtuPILDkuFqydeYNDwuIx+A4swi2QykdRci8HUfD3z210Ol907yd8bKs4qf+/Izz7B5VGt29lJwWDJC4zIxuHUjjPJrjPjMfDSzMcT4jk5IyCpAZFIupga6qk36uTY4Ej6NTdnzRzna3t3MmTPRt29fdO/eHT/88AP7+L1791BUVITu3buzj7m7u6Nx48ZsZ9TNmzfRvHlztiMKAHr27Inp06fj6dOnaNWqldL+bt68CRMTE7YjCgC6d+8OLS0t3L59Gx999BFu3ryJgIAAhc6snj17YtWqVcjMzISpqSlu3ryJzz77TGHbPXv2xPHjx9Ueq0gkgkgkYv+dk6P8N0AIqT71NX9RfWq3ppiqMvdE+e3xdLSqrMNCXb7Hv6a2h1jCKD03dssN/O0DNL0ejJv7/oJVVgrS9QW40LQ9lnSfhhuOLdDUwRx7RvhhO6DQ6ZYhFL/z+StPrKoqp6ioSIIANwuM8msMbQ4glpRg982X7OfnaG4AUXGJ2gFLdXlKZSsA5M/FdwM8IS4uwZg/FKvvafpcZTk2dbQ59SL/JnVGEULIe6qqK8gIRcWIThXiRWoeIpJy8DA+GzO6NClXUCO7Oe8Y74vUXDFuvEjH/MMPYcHnKSWxlCffwVJWgDUlwAVnHiciPrNA4w1edqMWioqQmivC8oHeeJWZj8P34tnp4FuuRqO1o0m5OqPkO1ic9LUQd+UcZoZdQc/196AjKsR9u2ZYFTgBp907IdlIGiDoCDl4HJ+NlNxCTPR3wtyDDwAAN16ks9tdO7QFkrILEehmifYu5hi/447Svmd0ccWSE08BKAZo8oH42SdJWDu0hcLsJtmsq9LT3yOTclHCQCEITMsTs7OnPO0EmBLgCk9bATaPag3ZoOWPZ8NVfjaqlt6pqrJTVdUNG7oDBw7g/v37uHNH+VqQzUoyMTFReNza2hpJSUnsa+Q7omTPy55TJSkpCVZWVgqP6ejowMzMTGG7zs7Oardramqqdt/q9gsAK1euxNKlS9U+TwipXvV1AKE+tLuqE6yr2t78IDfsv/OKvZ9XtsNC07LHh/HZOHY/AQCgIylGh7hH6B1xAz2ibsEyPwsltnYo7t8fI4pdcaeRFyRabzuS1J2Ldzl/KTmFeJaUi1Vnw8v9ucq2JxQVIyGzAFcj05CSW4gFvd0VBvPCEnMwZfe9cg1YKs3EV9GZdzk8BVcj01S+X/a5yldqlsWqy08/w8BW9irfVxOFgSqiTueMouSbhBBS9aoj/5JQVIzb0en46sgjfH7oIa5EpmFQa3vsuhFboWSSUSlC9NsQghVnniElR6SQxNLCUPnG6WZjBB0tKOR1OvMoEbdj0pWSYc49+ABBXtZIyS3E5fAUrDyjuoNk+ZlnSMkpxItUIY6FJijkOOrhKf2xHJmci5KSch6UWAzfx9fx37OdGNSnDTYeWwHHrCRc+3gmxn97EIPGrMP2th+yHVHA2xlNmkoJbw+JxSedXbD0VBi0OdLOqdJJw/lc1UGdGZ+L+UFuAKSzm348G47OTS2wdIAXfhrWEkfux7PL7Ep/3gJ9XbU5D5YP9MbTxByM2nYbXdZdwYy995FbWFxmTjB5lKOtcl69eoVPP/0Ue/fuhZ6eXm03p0YsXLgQ2dnZ7H+vXr2q7SYR8t6pq/mLysqVU1fbLVPVCdZVbW/irrvo6WWtFF9VNO+SpnyPRkwRGoUEY93pn3Bvwyjs/msxAuIeILr3Rzi/7SjiH4XDeOtmzF72CZo1Mi33uVB1/v6a2h5NrPgqz7ssB+iNF+kYt/2/Sn2uoa+y8PmhB1jc3wM/DfNBprBIZWy65Wo0ckVFZW5P5nVWAdJyRWxxFxlNFfz4XG04mOmzOUjlY1UHU30Y8lTPDqtr+TfrbGSnKfnm6dOncejQIRgbG2PWrFkYNGgQrl+/DuBt8k0bGxvcuHEDiYmJGDt2LHR1dbFixQq1+xs1ahQSExMRHByMoqIiTJgwAVOmTMG+ffsAvE2+2b17d2zevBmPHz/GxIkTYWJiwibplCXfXLlyJfr164d9+/Zh4MCBuH//Pry9vavpkyKEEKnyznRSN5X6Xabu3nuZiYm77ipsc/6hR1g7tAX+d/k5PGwFZY7CZAjF2Hj5OaYFuiiM8KTlibHlajQGt26kkL8IkHawpOSI8CojH8dCExCRnIsFvdyx9nykyn1sD4nF4NaNNN7g0/NEeJaUi3FyM43kjyc0LhNWRnoQ6OuqP5jiYuDyZeDAAeDoUehlZUHPwwMFn8/Hf/69MOxyOptL6V8VuZRkS+TmdXfTmGD8dVYBPnCzxMqzEUjJLWSXy8Vl5GPl2WewMtLDlABXeNkJFIK611kF0NLi4MAUP/z6z3O8SM2DhSEP7rZGiE0XYnbXJgqzsOQ/bzM+V+XspSX9PZEnKlaabTZh539YPbiFwvVRenuq1JVRu/ri3r17SElJQevWrdnHJBIJrl69it9++w3nz5+HWCxGVlaWwuyo5ORk2NjYAABsbGzw33//KWxXNuAne01pNjY2SElJUXisuLgYGRkZCtstPXBYervqXqNuvwDA4/HA4/HUPk8IqX7qlh3VlvLOKKpr7ZZXVoL1is5skd9e6Zk0R+8nKMVXFe2wKL3s0UBcgC4v7qJX5A30/PU+RhQIEWXugF2t+yGrd3949u6M7ddfIuJFLprtfcCen4qci9LnT1eLg8iUPEzYcVfleQ99lYWQqFS1M42Wn36GPZM1p324GJaMKQEuWHby7bW1oLc7zj9NVhjAK++ApaprVX57sgp+qlYGlDBAb29bduY8oJhKIrdQ9QBzXVuGWicTmFPyTUq+SQgpv4pM5a6OBNEat2krQKCbBUZ3cCozmWRCZj4exWdjw6XnCsnCzz9NxuXwFByf2QlfHnmksHSrqZUhbrxIV7gZLx/oXWZC71eZ+bgamaayzYv6ekir2mlI6t25qSX8m5bquCspAa5dQ+GefdA9fgzaaamAqyswYgQwfDjg7Q1wOGzyyv9dfo4BLe3gZm2Eey8zsS0kGuaGPCzs7Y5bL9IhYRh0dLVARFIufr/6QmnJnKwtjc0MNB7vxc8C4WTBB6D6WvmmrwcKiiRYdyGSfeyr3u4Q6Olg0fEnCp1NjuYGKJYAHA7AAcBA+v95OtLARt11ML6jE7q5W2HluXCVCTtrS0O65+bm5uLly5cKj02YMAHu7u746quv4ODgAEtLS+zfvx+DBw8GAERERMDd3V0phkpMTGSX3m3ZsgVffPEFUlJSVHb8yGKou3fvok2bNgCACxcuoFevXkoxVHJyMnR1pZ24X3/9NY4ePaoQQ+Xn5+PkyZPstjt27IgWLVpQDEUIKbfqLHhSU8pKsC5/XwfeDkbK7s08XcU8mQViCQLWXEY3dysEvSk6Ih9nmRpwcSc2g+2gehSfjd8+bl2hePDmvec49N1G9Iq8iYCY+9ArFuOJtSuMRw9HSve+GPxvpsaCJpU5P7LjNuBq4+mbgVVV2/WwFWD0ttsY5ddYY7x0fGYnOFuoTj6emFWA6y/SVLZ97dAW+PFsOBunedoKNHZsyai7VmXbA4Bv+noqxLgyZ+b4Y/6hR2pj1TVDW6DvryFKz1Xl30GDTWBOyTcJIaT8KjLTSdNU6spO3dW4zeRc/PCRNzhlbEMoKkZ4Ui6m773PPiY/G0koKoadiT62jfVlZ3/ZmegjLl2ILXKjeRaGXJgZcstM6H3kfjy+6euJH06HKa217+Birj7HUXIuVg9pAWcLPjKEYojExdC5ewf6Rw5B/8RRaCcmIsfECn8364zH43pj2NQP0aqxqdJorI+DCaYFuuLHNzkL/JzNsHVMG+hzdaDP1UaxpARbr8WAA6CZjQC/j2mD46EJ2H0rjt2ObPbUkDaNNCbylJ/BVfpaScktxOvsAqUk7eO2/4e/praXft5FEvC0tZCQXaAw4ji3e1OIi0tgKeDB284Y6XkijG4vnZUln18LAPbceompgS4VGvXUlHyeKDMyMlKahc3n82Fubs4+PmnSJHz22WcwMzODQCDA7Nmz0aFDB7Rv3x4AEBQUBE9PT4wZMwarV69GUlISvvnmG8ycOVPtDCQPDw/06tULn3zyCTZv3oyioiLMmjULI0aMgJ2dHQDg448/xtKlSzFp0iR89dVXePLkCX755Rf8/PPP7HY+/fRTBAYGYt26dejbty8OHDiAu3fvYsuWLdXxcRFCGqCqnlFUWzQmWLc2woWwZHjaCeBpa4SwxFyFAaaJ/k54Ep8Dn8YmuBaVCncb6cDVd/09YWqgi9n7H7DbksVZ28f74lF8NrZei0EzayN82asZiiTlmNqTkgIcPw4cPYr2//yDDsXFCHPyws8BYxDp3wOTx3SDs4MJzADsbZKFsMQctakHlp9+hs2jW8NQT7fMojS62hxEJOVi5ZsYakEvdxwLTVC93TPPsPFjaeEVTTON3KyNcPLhawS4WbKxs3wcwgBs28uaXfZ1OfKOya5VVTmfZLP4f78aDUdzA5V5NA15OkgTilSuJohMzoWRnk69yL9Z5zqjKPkmIaShqOoE4er2UZHAqzoqyJQZND1NwtXINI0JIqNThVh3Qf3Suh8HN0dUSi6WnghTmP3VyESP7Qgb3NoeQ30bIVNYhNldmyh0bMnIOnDS8sRwszLE6sEtsFZuRtDqwS1gZqCr8XjMDHQQee4qhH/uRaubF8BPjEcK3xT/tOkKwQ+jsF/LHhfCUwEAJ/74T6lTMFMoxqOEbIzbLl0OFeRpjSAvayw4+gRpQhG+7u2BM48TMai1PbaHxGLLm+Dw8yA3NDY1wLEHrzE10AX/RqRgSJtGaGpliJaNTFQer/wyOFXXirqcVEGe1nidVYglcp/3RH8n2L9JJC9L0rltrC+4WlqISMrBN8efqp227mZjBJ5O+f4OVM3ekk8+X9Wlid8nP//8M7S0tDB48GCIRCL07NkTGzduZJ/X1tbGqVOnMH36dHTo0AF8Ph/jxo3DsmXL2NfExsbC2dkZly9fxgcffAAA2Lt3L2bNmoVu3bqx2//111/Z9xgbG+PChQuYOXMm2rRpAwsLCyxevJhNcwBIZ0Ht27cP33zzDb7++ms0bdoUx48fpzQHhJByq44Bt9qgKUG3fKVb+SXwFoZc9PSyhpWRHoa3EyA6JQ+9vW3xU3AkfjwXzt5Le3haK+WEXHs+Ep2bWuDGi3SEJeZg/I47WD/cB9YCHlo0KnW/jY8Hjh6V/nftmvSxwEBw1q8HPvoINsYWGFuq8l2BWAIPWwHsTfQ1DvaFPE/DnltxSvd5+bhAFifJzxYy4GprPO9aWtLCK4fvxaudmTW5szNWnHmGa8/TsGO8L6JShApxyJqhLRCRnMvGbKVnlxnr6eKarQCL+pavw6dALIGDmT4m+jspbGtBb3cEP01GB1dzBLhZws3aCHyejtJgXkpOIb7u7YEtV6OVYq+ErAIY8nTRqQm/Ti5DlVenIjlZ8s3g4OD3Kvmm/GyqnJwcODg41GKLCCHvqqoroGhS0cCrOirIlCdoSssTq52tlSEUSyvwaZhdpauthQG/XWcfk83+2j2xHfyczWBjzEMvbxt2Hf+0ABccm9EBL9ML2Mp+w9s64MyjRFgJ9LBxVGuk54uV8lxN3HUXf01tr/J4mqTFYUN2FMzbTIBdzAuIjE1x2NkPpwJn4LaDF0q0tIFIYO1QW9yPz2ZnBsnyEMgq/D17ncOO4FkYchHkZc0GRtMCXfDX3VcY1NpeabbSpF13sXNCW+yb7IdXmfkokljg6P0EcAC0dzXH9vG+WHs+UloRT8UIWE5BESKScxVG4RzMDLD1WozCccrapCoPgSxnluzYfgqOxMBW9nC2MEAzG0O2o+rHs+H47eNW6OFpjejUPHR1tyr3taVqpt/cgw/Yaet1sTRxXfXvv/8q/FtPTw//+9//8L///U/texwdHTUWX4mJiYGJiQlatmzJPmZmZsbm2FSnRYsWuCb74aLG0KFDMXToUI2vIaQhqInBqvdRdQy4VTd11wKbm/H0M5WVbqcFumDtm0G8IE9r9G9ph03/vsCvl56jmbUR5vVww8G7ipXy5h58gE2jWqOXlzWiUvIUZtKM8mus0K4tV6PRuakFCsQStGeyYHDqb2kH1O3bgK4u0L07sGULMGAAYGnJvs/szf/KiuXIx8KrBrfQONhnasBFSm6hwn0+QyjG66wC3H+ZgZ5e1mjV2BQRSdJYRhaLaJzxZGMEI54uG9edf5qsVEF4+geuMNLTRqvGprgcnoLUXLFSHHLy4Wv4OZspxGyy5+YfeoRdE9pi+3hf2BhrTkkhY8DV1pjzycqIB08747efa6nviciUPLVxmr2JPrsioa5/v9SpanryyTd1dHSgo6ODK1eu4Ndff4WOjg6sra3Z5JvySiffLCtJZmm1nXxTIBAo/EcIqZvKqswiU5UVUMrapyzwUkVd4FXVFWQyhGI0NtXHyVmd0NHVXKGamyxokll++hni0oUKx1MgliAiKUf9cVgb4VqUcsJJC0MuwpNzsXSAF/o0t8Mnf95DWGIOurlbwdmSj0XHnrKV/aYGuKB1Y2N82dsd28b6oomVkdpqektOhsHJ3ADrh/ugm04OZt88iH//nI2Lf8yA/Z9bcdLQGWdXb8eQxUewqOcs3HRsIe2IekM2vVpGlmg8IjkXo7fdVhjBKz0zycHUAC0bGaudxr76XARyREUAh4NiCYOR7RxwJTINE3fexbZrMVjxkTcuzQ9UqEAnCwiDw5Ixpr2jQuWViKRcpc+9rAp+pY+Nz9XGJ3/eQ5CnjbQjy9MaC3q7Y9nJZ1h49DGuRqZBVFwCoai4zOtZ00w/+X1XtNIPqTpnzpzB119/DVNT09puCiH1TnVUs22oyhtzyZMNjqlS2QG36lLWtSBL0L15dGss+9ALnZtaYOXZZ+ysJlkhFgtDLnp522D2/lCFuPOTP1VXyttw6TmiUvIUqgTLUhiwGAbMkyfoc3wbHLv7w8DLHViyBLCzA/bskS7PO3MGmDRJoSNKnqpYeMLO/9hKvqVN8nfG7lsv2TYtP/MMj+Kl29hwKQqNzfg4/zQZE3bewbHQBIUKx4fvxWOiv5PK7S7q4wFTPpeN6xIyC7DmfAQGtrLHwantMaZDYyw9+RTjd9zFoFb22DCyFVLzREqf2+F78Zjbrana+GjVuQiceJhY7r9nBlBIMyFvy9Vo3InNrHSsFJsuxKh68t1SpzqjunXrhsePH+PBgwfsf76+vhg1ahT7/3V1dfHPP/+w74mIiEBcXBw6dOgAAOjQoQMeP36s0LkUHBwMgUAAT09Plfvt0KEDsrKycO/ePfaxS5cuoaSkBH5+fuxrrl69iqKit2Uag4OD0axZMzYg69Chg0LbZK+RtY0QUj9VJHgsa9mcqhuLqoCrvPusTOAlX4HkypddFDouVFEXEMq3scu6K/jqyGOMae+IP8b7YnF/D1x/kaY0FVw2DVv+ePS52ngYn602kFjQ2x3bQhRv2INb2+O3j1vB0pCHF6l52B4ind0jP9NIPgAat+MO7r3MxsittzB5110k5xQi0M0Cywd6K5XSzYt4Af31P6FZvy74Y/nHmHPnCAx9W+Gzj5eixfTdmN9nLjI6d0VYWoHK9kYm56KxmQH7bzdrI1x8lozi4hKsHtICZoZc+DlLxw6bWhkqtCNdKEIzG4HGWWIZeWIM/N91/HnzJUTFJbA31YekhMGNF+kYuPEGXqblK5x3WUB46N4rdGpijvmHHiEltxCfdHaGlYCHz0oFhpoqDao6NlkAu+HSc6wc1Bz9W9oqff5j/vgPt6PTMWvffY3Xc1n5x2T7rk/LLRqaNWvW4IsvvqjtZhBSL1XlYFVD9a4ddqoG3P6a2h5NrPgV7tyqLhlCMWLShAiJSkVKbqHGa8FQTxd7bsXh96vRCoN7stlAQ9o0wrZSM5xlSg8gAdJ7qYOpATuTpqeXNWZ84Ioj917BO+k55l/9E/9sm46z22bAfe/veGpij/s/bUViVBwS/tiLjIFDgVIpc1Qdn6pYOC1PjKuRadg0qjU8bQVKg5c3XqSzbUrPE+FxfDZScgvRw1M6W1v+70b2OtkMqfNPk7F+uM/b7ZYaaBUVlWDF2WeY3bUJFvb2QHqeCFN338PCo0/Yz3XDped4GJ+FNeciFDq7ZG3PzC/SGKPwudrl/nsuK97R1eaojXPKem9JCerNd0udWqZHyTcJIbWhrOny1ZUgXNNyvorsk53KXcEkhaWPNVMoRm5hEUoYQKCvyy4rU7fcUFUbp++9zy6nks7ASVUIntysjfAyPZ89nmMzOkJPRxvDfB1w+nGi0tTpz4Lc4GrJhwWfh5QcabGHQa3tFJbkydbr83k6cLXkqx212nI1Gh/52CM1rxCpuSKY8XngcABzPg8r2psjfec+NP33DHwTnoHh8fDCswOOjZsOmxGD8P3lOIXp32UlwZQfYZzXww3iYgmWnHybf2lej6Zo72IGA64OrkSmsY9P7uwsXfKmYds62hx0dbdCcFiy0nK4w/fisfJsOLzsjdlcDRsvP8e0QBe2Mt/g1vbo4GqO7SGx2HotBmP8HLF1bBv8HByFyORc5Isl5T42+dwVkcm5EIqk17fKnBQXFHNSqLqey8o/Jtt3XV1uQQgh6jSU5NrVrSLxjyryA24FRRLoanEQmZKnUICjqlMnlHfZpaq4r3SOxdLXgrpUCJfCU7B6cAsUSRil5fYyqpbfyd9LOUwJbv15EpPTQnHs9Ek4ZCcjU88IwU39kLpkOXI7dYaZkSG09XRx6kUGtoY8gAWfh+8GeMLpTXVdVccsHwuXTtB9LDQBfi5mmN21CUTFJXiWmMOmc5DZHhKLSf4uiMvIL9ds7d+vRiM4LBmT/Z2wZ7LqHEn6XG1Y8HnIEIrVVtSLTM7F+E5OAKSdV5P8nfAyXYjI5DwAQNyb2C8lt1Ap6biVkR77uZbn77mseKdIwqiNc8obK5W3LbWJwzCM8pmoQz744AP4+Phg/fr1AIDCwkJ8/vnn2L9/v0LyTfmlcC9fvsT06dPx77//ssk3f/zxR+joSL9wVCXfzMjIwKxZs3Dy5EmF5JuGhobsdh89eoSZM2fizp07sLCwwOzZs/HVV18ptPfQoUP45ptvEBsbi6ZNm2L16tXo06dPuY+XyhITUnPKk9spQyjGrH330aKRsVK1Ck87gdIXfIZQrLa8fenXqyvpenKWP746oqZcq4p9yu+7MkkKhaJiRCbn4mV6vkIixPlBbth/55VSp4J8mVx1JWU7N7XA44RsjGnviAyhGOlCERgGCGxmiSsRqdh9S1qC/pu+npCUlKBIUgIzPg87b8SiZSNjNLMRwMZYD4fvvsK8oGaISRNi9LbbsDDk4vsPvVUm6147tAVKGGDh0cdqy/b+PqYNDHnaeJVZgMPnHqBJyAUMfX4dLV48AKOjgxCX1rCaPBYO40bgdloR1l6IxOj2jfHt34qBi6byxL+M8MGKM89gzufhkwBnmPG5GLddsSiHhSEXqwa3wCS5nFUyG0e1Bp+rjXE7lAt5bBvriy3XXuCzHm7IF0sgKirBhkvPFTrlbr1Ix5zuTaHN0UKxRIKYtHysPh+h0BF29kkSrIx47DV9KTwFyz70QlxGAVwtDfAqo1BlKWH5Y5PlrpBdH7Lz/vvVaKUyx7LPf+kALyw6/oR9rPT1XDq5u3wQ62pliMV/P0Fkcl6V5Yyie27DQueT1GUJmQUIWHNZ7f3pypddYG9SvnwzDVVFYqjyUhdrVcV9pKI5QtW1Rf6eqaPFwfm5ATDlc9ljFYqK8eBVFjvoOLqDIwKaWGDthUgEulngSmSaxnjsd7nlYD995IULv/+Fjg+uomfUTVjnZaDI0hrn3TrgbLMOaDXqQ7RytUSmsAh5omKFuHCivxNeZxXAzkRfKel2YzN9MAB0tTjQ0tLC5F130chUXynZ95QAFzhb8JGUXYgZ++6r/Xs4OLU9pu6+h3nd3dR2HulocbDsQy/suRWHqYEuaO9iDmuB+rzTl54l47/YDFzV8HmtG9YCIVHp2BoSDQs+D7O7NsHR0AQEhyVjz6R24PN03szIV0xgbs7n4ovDj9hzWNbfc6ZQjCuRqWpjLTcrQ3jI5YwqTd21tG5oS4XOver8bqmKe26d74yqDpcvX8agQYMQHR1d53IeUCBFSM0pT4DyKiMft2PSlW46558m43J4isov+PJsV1PAtX6EDz7/62G5A9Z3TYR6OyYdrzLyVXasqOpU8LQTYOPHrdHtpytq2/i/j1sjV1SE7SGxcDDTR29vW6WAplhSgvCkPPg5m2HDpedIE4ow2d8FbRxNEJmci3UXImEl0MPeSX4QSyRIzRUjLU+ELVejceNFutJ+PW0FmN21CTZceq42yPi5Z2MIDx5F7q496BT7ABwA1x1b4pR7Z/T6dhqsHW1hpKeD7AIJTj9+jcP34jGkTSOVgUsPT2v0bS49LtlMrq96N4OJPhdPErIRl5EPPk8b554kK713WqCLxmBo/fCWeJ1diNXnIt7OEuvhhvyiYuhqaWH3rZdKSc4BaRLTYb4O+Ck4Uul6lXUaBXlaY6hvI/wcHKVUCpqnq4VrUWkY074xdHW0FGapLeztDltjHvKLSnD6USKO3I9XuC7kAyBVAbCnrQA9vaxRUCRRGCE9OqMTTPR12YC+kak++jS3xYNXWfC2F2B7SCzShCJ84u+CNo6mMOBqw8HMoEpGtOme27DQ+SR1WXV0tDQ0Vd1hV92feUU6ujS2Re6e6WkrQICbhcoqxBlCMUTFEkQl52Gs3KCNusGxbWN9sf16DB5EJWNIdgQmJN2HxaVzMMrLRrzAEufcOiK8Yw/0nDwQpob60NHhYPW5CDxPzVOqWCfb18pBzfHJn/eU9rV2aAscvZ+AYb4OsBFwIWGAxOxCle3aOaEtzPm6+OrIE7Wfx/RAV8w+EFpmvPR1H3dci0rD8QfSeELT9ZGRJ8LT1zlIF4rVdgItP/MMFnyeQuy0frgPdLQ4eJaUAz9nc/azl7dhZCssPflU42C1fKyekFmApSefsp118knqLzxNwqJ+Hmhsxld7LKU7KOUT3MsPIlfnd0tV3HPr1DK9mkLJNwkh5Z0uH5MmVFk1Y+3QFtJ8RxoShGtaNqdpOV9EYk65qsGUHpHzczbDwt4eMNbXgaGersaboPzjj15ls9XdSpOfAi0jXyZX3RRhYwMdTN1zDxaGXEz0d1JZ8WPn+LbQ09VRmOW04oz0nKwd2gIAsLS/F568zsbKM+FKS/JU5aMCgIn+TgrnzEBcgO7Pb2PR7Uew/PJfoKgIdxp5YUmPaTjr1hHpfBMAwJM7aVjeyAbT9oQqjPZdf56mtE0ACA5Lxmg/R8zr0RSZ+UV4kZIHAU8HC48+Zj+X5QO9VZ7nsvIy5YklEBdLMLtrE1gY8pCaJ8L9uAy0amyKT/68h2mBLkrT1mX5sib/qVghUL4KHgAEeVkrBJLyr+EA+CMkBiUM8OPZcAxu3QjjOznBiKcDGxM9HL4XD4Zh4OdijmtRacjKL1Kq8CM7htJLA77s2QwZ+WJsuxbDfr4Le3tAV4ujsCwjLDEHselCzOvuhul77yPI05otfSwrT11d1SkJIaS6VEc124amqqvhlZU6IU9UVOnPvaLLLkVFEgS6WWCUX2OFWfaA4j1zXg83LDz6SGUVYtny+x/Pvi3AIsuXVDrNwYx2Nmhy/QL+CD4N3rmz0MrNwUvzRvjTOwjn3DrisU0TgMNhO6xux2SwMVaRhFGZXHtIG+lAlirbQ2LRuakFW/22mbURlp9WXShm9bkIzOnaRGVsBQBzuzeFqFi67P/wvXi1nW2T/J0x9+ADtgOorOvDzJCHzm6WiM/Mx64JbbFKbsBvkr8zTj1KREqOCCk5IoXYacvVaHzTzwPN7Y0VPnt5m/59wcbLsr/nDKEYQlExYtKE+PFsuMLsuaZWfMRnFrCx1ii/xojLyMfKs89gJdCDIU9X47GUXo6anifCxJ13FAYJgbr/3fJeRnFr1qyp7SYQQmpZeXI7lb7hy9seEotVg5uXmSBc3bI5TQHXw/hsLOjtrnLkRf6mIv8DPsjTGkFe1vjqyCOFm52njRHCknLVTiEvEEvA52lr7BhRlW9AvkxuaZ8HuSFTWIRpgS7Q19VWu9Y/KiVPYyfY9vFtkZorUljKVrpzRf6m287ZDK5WhhAVSXByUitcXLcLza6cQdcXd6BXJEJ2i9ZIXPAdhmY0wmu+ucpjDXudo1AGWbavGy/SlQK9Sf7O2HP7JYLDkuFmbYh5Pdygp6uDOd2a4KfgSEQm56nNLVVWzqns/CJYGenhTmwmvv1buqztt49bYdlJaeCrqjOrPHkVOBxofM2srk3gZm0ELS1pgBuTJkRTa0OFpYCL+3vg13+ea8z34GZtBKFYAh0tjnRWVR93ZOUX4bO/Hiqcy7kHH2D3xHbYdOWFQlu6ulthw6XnCgnp5d9XkfwhhBBSV1Q2x+P7oqo77MrKrZNXWPlKY3mFRRjdXtqBIN+xBEjjyJyCIoVldlEpeQo5IuVzRcnumb+M8EFabqFiFeJSHVs5BcpJtIPDkhEal4lR7sbYzo2E0enfYbAwGJyCAhR7N0fezDkQfzgQ8eaNcfpMOCKTc+H5Zsb1wbuvcONFOiwMuQhws4CoqAQ+jU0qNZAmy7e0PSQWi/t5KrxWftl9fGY+bE30sPNGrMrYCgBOPHybRzT4TXJy+Znok/ydEfI8ld1mi0Ym5b4+GpkaoJGpAZo3MkFOQREuhCUrxTGy4xjcuhH+CIlBbJoQBlwdjcc/JdBFmsrCxgghz9Ow8fJzpVnsshjmr6nt2Wv991Idf7+MaFXuY5G9zkRfF7+MaFXvvlvey84oQmrLuy6nIlWnPKNvmjqs0oUiCPR1kJBZoPZ8ajrHZnwuvhvgicvhKUq5qGZ2aQKfMgJW+RE5TT/Yt4/zxZdHHrE32NI/5A242rAz0ce6oS0RnpSjFFAplfuFtLqdKZ+LplaG+HNiO/x4NlxhKdm1yDTsvv0SzayN8P1AL/x66bnKz0BdJ5iFIReBbhbQ1uIgOlXIVkqRV3rGVpCnNUa0tMa+bzfC58Y5BD2/jeaiAuR6Nkf6ZwtQ+NFHyLVzRG5hEUzOhON1OZI+yu+rc1ML/Hg2HFMCXNGpiTlOPnzNBi6f9WgKD1uBwrK3L3o2Q1hiDnbffKlyRO/wvXisGdISE3Yq54X6rIcbtl6LZkcpF/R2R7GkBEnZIvbzUtWZVVaQKOtU1DgjS1SMSf7O4Opw4GZtqPK6epEixO2YDEQm52JBb3elIAoAJnd2xquMfCwd4CVdrsjVxsozqjt2V54NR4CbhcLSS9mxfNLZWW3nWV1PykkIIaWVZ7DqfVeVHXYcAFMCXFQuyZoa6IJ7L7NgY6xf4Tyb6pKQh8ZlYkibRnC3ESAmXYjk3EJ42xkj9FWWwgBj6YG1eT3cEPY6G9ocPawLjlTYX3qeCHmiIhSIJTDgaiOrQKxw/zfNz0b357fRO+IGOr98CF1JETK8fBA+fg7EAwbi+whp51Wz2/n4boAWNo9pjfsvs8DT0cL26zG48SKdHdCUpaRY0Mu9UgNpjc300cPTGpfDUyBhStjXlt5+M2sjtHMyx5A2jZCQVYjZXZsgX1yMyOQ8HLkfj+b2xmwH25QAV3RwMcOl8BQEeVnjsx5NYWLAxeWIFHRqYqGwTXWzpjOEYoiKJGAAMMzbpOtmfC4KxBKsOheuNqH5KL/GbPEdDkfzqoB2TmawM9Fnl2+qmsUus+RkGHaMb8te6+l5Ikzu7IIOLuawNKr4d0J9/W6hzihCakBFExwS1aqyM688o28ZEKu86QR5WqNPc1tMl1vOVdHzKRQVQ1xcgqtyo2Tf9PWEo7kB3KyNyrypyHeUaZoRs/ZCpNIyOwtDLsISc2BnrIf8IgniMwqgpSWtKvddf0+ceJjILoH7rIcbtl+PYWe4TA10QRMrQ4Q8T8OK08+QJhRh5gdN0M7JFKLiEkz+865Cx1dwWLLaG7dQJIGfs5lCcviU3EJ0dJUGF1uuxSiNHspG1hqbGaCJpSFO3otDv4wIjP97L/hTTqCrSIgocwdsbjsIp9w7Y96s/gAYbPo3GhHJN9DD0xqfB7mpTBwuXxlOniwYScsTw8WCj5dpQpjzeZjXXZrDycmcr7Ts7ZM/72Hr2DYw43NVTp+fGugCEwMdpZE++VFK2bbmH3qEbWN98Swxm/0sVU1bL0+Fv7ICKU9bAeIzC/AqIx8Lerlj7YVI9pqRjT5aC3hY2t8LHA5QJGGwYaQPNv379hjmdGuCI/cTFJZRetgKNI8mBrgo7MPMkItm1kaaO9hKVackhJD6oj78SKyIqozPqvJHdb5YgjMqKvVO8nfGmUeJCGxmWeH7iKpqf/MPPcKGka0woKUtNv0bja1v4peJ/k4w1tNVu5xve0gsfvu4Nc49TkIrRxP8/fC1wuCbLN6ctvs+20l0OSIFM9z1cev0fvSOvA6/uCfQYhjccfBC2NxF+JrTBE+1TbBtrC8WHFUcjBz++y3sGN8W2lrSc3Y7JkPlgObvV1+oHEhLzRVpjKFm7QvFgt7uEIqKEZ2ajy96NsMXhx8qbb+RqT7S80VK+Vij04QY3LoRG4ul5YlhzuciKjkXP1+MQpCnNRqZ6uPw/QR82NKOTfMgm9X1Mk0IAU8Hjc0MYMLnsr+/LoYlszkoS8ft5alMJx8fqlsyuKivB+xM9BWqGHdzt1Zf6TApF8UlDDo1scDO8W3xLCkXq86G48ez75aOoL59t7yXCczrMkq+2TBVZyWP90F1deYpJf+TG32Tbbf0udOUKLIi51PdNbF7Yjs0sTIEr4zgSz4R5vKB3horjchXMFM1OjUlwAVnHiciPrOArQiy9VoMBrduhJDnqbAy0kNjMwPEZeSjp5c18otKlJYHZgqLcCw0QelmbmHIxTd9PfHD6TClMrjrh/ugoEjCzijyczbDhE5OCh07sg6KHp7WeJmWD10dDjZfeg7BvVsYFXsLQc+ugZuRjtcW9jjS1B+nPDojwsIR4HAAKFeSmRbogkJxCfxcpEnT5TtQbr3IwM6bsUqfoaetAANb2cOcz0VCVj48bY3ZBOF/jPPF6nMRahNryhKqz/jAFbmiIpSUAHEZ+Whub4xfL0VhdtcmeJKQg8ZmBjDjc7H71ku1ydmHt3UAn6fNXns9PK3RUy7xZTtnM0zs5KyQM0pGVgXP1dJQ7Wu2j/PFtpC3eSO+7NUM+27HSc+zhmtmcmdniIokKGGgUPFO3vRAF43VftYP98GjhCx2H7Jr4d7LTPWJS6sgKSfdcxsWOp+E1Ky6PtianFOACTvuIiW3EINbN2JjmSP342FlpIeBrewxpE2jct9HMoViHL4XDwOutlLeJ1VFOg7fi8eWMb4Y+vtNtTHahXkBMDXg4nV2AR7EZbHvAxQ7PhplJ+MXbgxw5AhavQ4HtLQR2qQVjjn7IbpTdwzu3UZthVt5nrYCzOvRFEZ6Olh28hmbLL2sIi3t3tyX/7obrxB7yAbSTj9+jWOhr+FpK8Di/p5IyxXBwUwfoqISLDkZxm5fUxz9xzhf3H+Zid+vRrOdho/js2Fnqo8tbzrIfjwbju8HemPDP8/Vzrr6tFtT2BrzkF1YjHkHH5QZt6uLyX8ZIU1cnltYBEmJdFWEvYk+BPq6+Dk4Snr8pX47yBc+0ljpUC6GUbf/v6a2RxMrozq7qoaq6TVAFEg1PFQ95d1Vd2eerDoJwyhO3wWUO6y+6u2OY/eVO12A8p9PTddER1dzjOngCFFRCVwtDeFiyVcb0Mk+l3ndm+L8U+WKbYBiMKIpAJCvmrd+uA/aOZkgPqsQS06GKXTUNbHiY8KOuwhLzFHYnroOMQtDLn4c1AI62tIKLbJA4ctezWCgq41hW26xry1dMUUhwEjKwYDCV5iRfBcWZ0/ANCsVCUaWOOXRGQHfzkS/6wWQqLible6Mk7XT1ZKPZR964UWKEHEZ+bgckYIpAS5qq9FwOECBuBjaWlr49u8nCjkKBm68rjbIPPNpZ+QWFmHdhUj8F5OhkOw7NC4T84PcYGWkh7UXIjG6fWN8+7f6TsXD0zrgf/++QG9vG2y7FsMGh3O6NUV2fhHux2XCv6k5UnPF7PNu1kb4PMgNKTmFKGGA1DwR2jiaIDlHpBRIHrz7Sikp/KZRrVFQJFHI9aTumhHo6eBqZJpSh56FIRff9vOAIU9X5WjqtrG+MORpY9b+UIUR4R6e1hjj54iMfNVVb6ri75/uuQ0LnU9CalZNDrZWZvbVs9fZiM8qUFn9bd3Qlmhkqg8/F+UckqoIRcW4+zITq84qFlSRzdzu5WWNQa0bYf1FxUq1etra2Hjlhdq4ccd4X0SlCBU69Ob1aApTAy727w6G9cUz6B1xHc2TX6BYl4s7zdricON2CG3ZCWumdkFEUi5Sc0UAAAtDHtuZlZVfpBD/yOhocXB4ekf873IUBrduhPQ8sdoBTWsBDzvGt0Vkch54OlpstWILQ65C597jhGw0tzfG71ejoaPFwek5/ohKykNiTgF8ncwwZPPbzriyquPN6toEmUIx22n4y4hW0NHm4HJ4CgqLSuBtL4COlhY+P/QQpga6auPaA1P8NHa2yfa3Y4IvErIKEZeerzBTfUHvZuBwOMjKF2PTv9EKlaFl1Z87ukqX1FkL3lbwuxqZWq5Kh7K/EXW/CWSz4uQrUdeljl6AqukRUi+UJ1E2Ua+i1UoqGqxoqnQh+8KXny5eVFyiNql56YSV6qi7JmSdLxv+eZssen6QG/xczBVuPLJjbGrFx8lZnRCfWQBHc77KH+yyKdJA+RJc/341GluuRqO1Y2u0czZXmiafkFmgcnmgqiViQZ7W6N/SFmJJCSb/+bZiXlhiDsbvuIP1w30U8kHJL8myMOQiyNMKO347hgHPrqJveAgcspORwjdFWr8P8bmgJS6buoLhaEFL4IRmNqo7CEvngZJv5x8hsejpZY1rUWnILiiCno42dk5oi9Vy1VVmdHGFthaw5nwkAt0sUFBUggW93bE9JBZpQhG2jmmjcXp3YZEEulpaWNzPE2JJCc48TsTKs8/QurGpwnYm+7ugVWMTjdt6lVEgnZkmkmBgK3vwudqIy8jHrH332c/wWlQaenpZY2Are7jbGEEoKsYfITHsbKtpgS5YeSaCHSUe5dcYZnwumzeitPjMgnJVWtxyNRoDfOzg3UgxGJFeA3ZIyi5EaGa2yqUSIVFpsDPVV1pOGhyWDKGoGDO7uGLLmDZYf1F5FJIQQkjtqGh8VlmVmX0lFBXj/stMrDwbjkam+kpL4qcGukCgpwMdLQ4yhWKYlqOdoa+yME5N3qeX6UL08rbFlN3KlWr/GOeLr3o1w7gdyjkiF/XxQEya8G2HHsOAefgAYX9txMTk+1j3IhIinj6i2wUiZNZcPGrREQ6O1rhyMgxjOzhCi8NBZHKe0hK0Bb3d8SQ+R2UeTDdrI/wXk4F53dyQni+GmQFXbexhzufheUoeiktKIBQWszFaWp5Y4X6to8VB3+a27PaPhSbgamQaJnd2Rl5hscL2y8pvKZaU4LsTT+FmY4RfRrRi7/UCPV08fZ2N+YceYVqgC5pZGyHAzUJtXCvLsznKr7HG/SXniDBo4w22g01W1U5XWwtGPB3MexNbl64MLav+vHtiO7YzqjyVDtvJVb6WxfOl2ydbOlm6EnVDLN5CnVGEVLOqLlP7vilvZ15FgxXZ6zVVuihdTheQ3mg0dRhcCEuGp51AYb+lO8i4OsCCXu4K07wBqEwWPXHXXeye2A6d3SxVHuP8IDccfdNZUPqH/qK+HvB4czNffuYZGpuVL8F1ZHIuSkqgcNwyJUwJm+y8mY0Ruxa+dA4j2Y00OlWI808VZ9vIbLkardABIesoEj9+gqVxj+H46ykMSX2FDH0Bzrl1xEmPANx28IK7vSk6N7XApTfv2xYSjRUfNVc562ZqoAu+PxXG/lu+nbLkmPN7uMHMkIf1F6PYjqF2TqZIyi5EUUkJJuyUbneSvxMYAPMPPUKQpzUm+jth1bkItaWJ5/d0w8Z/X7B5s77o6YZCcYnKc73izDNYGHKxclBzlSO4c7o1wfbrMejkaoGu7tY48/g1tlyNV0rsLjuP3514iqUDvAAAt2My2OdlQaCkhGE/9+UDvRVeI6+8lRYjk3Mh0NNBvliCP8b5Yt2FSKQLRejXwhaz94di+UBv7L79EqaPdZVKGGflF2HZh17gcw2U9vFfTAb6NrfFzxcjMSXAFUGe1hDo69JsUkIIUaE6CuWo22ZNDbY+eZ2NkKhUjPJrzMZMZf0ovx+XiTFvOo7CEnNwPy4Tg1s3wqrBzaHNAa6/SMf3p6LZpXql47bSNHW8bQ+JxbzubtigpljLuguRGNuhsVKH2ILe7nA0N8DUnXfg8zoCvSKuo1fkTThlJSKbx8ftFv4wmP4lCrp0xbpr8dK4L0aIT121sWtCO+QWFuNFSh46NTFXylsp6wRbde5tx4h82oP7LzORkS/GmD/+k1YD7u7G5l+SNzXQBfamevjnWQq6eViXmVsJeJt/My1PjM/+eog9k9phaqALPj3wAEDZ+S1bNzbBlS+7sIOgmUIxcguLwNXmIF8sgYUhl43lREUlagvh6OlqoZm1UZn7uxUtjX9Kd7Bdi0rDwFb2WNDbHUUSRm2n18qz4TA20IWrpaHKvwlZrDm0TSP872MfvMosVKh8vWpwC6X2aRo8bmjFW6gzipBqVtVlat835e3MU5VQUlOwInu9pkoXqr7wNZ1P+Rvw3sl+8HEwUeo8Wv6RN7ILpPmVZI99/6E3rIx4uB+XpbJy3Mqz4fCyN2aPSSYltxD/xWZgWqALQqLSsOVqNLo0s8Iov8YQiiXwtBXAlM9FpyY87JnkhzxRUbkCCWmJ4WIIRcUQFZegQCwBh8PgRYoQK+Vmj/XwfBuYlB79CXwzWrWgt7tSNT35JOSOZgY4cj8e/FexEKw7jP2xN2H8IgJivhFOuPjh5AeTcd2xJYq1396u5DtBAOnInZURj+0EkQV60z9whUBfR+HzlLVTvsNEj6ujMJopG+3aPt4Xf157yT5uYsBFdKoQ64a2gAFXhw3c+DwdpY7AL3s1Q0RSLs49SQIgvR4n7LyLP8b5wpSvq/KaS8sT43pUOjaNaq2Qz+qTAGfcepGBTzq74HpUOgZuvK6U2L30eVSXsPxVZr5S0vh0oUhjkvnyXjMulnxkCovw1ZFHGNy6EQKaWmD5mwp6qvZ75L60M83TVoA8kQTpeSK1+0jLE8PLTgAnC77Sawgh5H1XHbmb1FWNa+NoCj5Pp9KDreo6t1Q9npJTiMSsQoViL7J7nyxGA6BQKY3DATb9+0Jhn7KOBlkHg5M5H/OD3PDzxSjwudqYeyAUO8a3gxmfq7JdmUIxAt0skJJbqHIQyNmSr3HgRlIC/HA6DINbN8KPg5vjQUw69q75E1/mPcW20ydgm5uONANjXGjaAYt7TMNNxxZgdLk4NrwjPv7tOrutsMQcTN19D+uH+2DF2Wf4xN8F26/HqtzvuguR+P5Dbyw9GYbGZvro5W2Lv+6+AgdAMxsBuNpaGNTaHkfvJ+BoaIJSHDO5szTJe+/mtujuYY0nCTn4omczlVWAJ/k748j9eKwb2hLnniYpfEYrzoTjE38nHJjih6RsEV5lCDHjA1fM2h+qcjsv0/LfDsDGZeLlm+VzsvO/YlBzgAHShWJ42glUzsoP8rLGnzdfYqK/E348G652qdy8Hm5YdPyx2vPG50rzdB6Z3kHj+X0cn43cwmJ42iq3B5Befw/js9HB1UKpquKEnf9h9eAWmCg3oFoVxVvqSwV36owipAZUZZna9025qt5VYimf7PWV+cJnz+fpZwrLjeRvwP+7/BzTAl0VbjopuYV4kZqnNPtp+t77WDu0BS5HpODrPh44+yRJoYMhMjkX2QWKxyhbApeULUJEUi4MuDqY3bUJLkekgsMBGpsZIFdUpDD1nKetha96uWPcjrdtkpGvFDKziysiknKQkiPCmvNv8zxN9HeCvak+whJz2IBIfiaPbPRncOtG6N/SDluuxUC7VGeIfB6onMgXGB//Hy5EhcDs2WMIdfXwpE0g9OZ9jbvN2uLIU9Vr/Ns5m8GMz8Xygd5IyxOhSzNLcHW0YGXEw8h2jaGtBeSJJDDR1wVXm4OfhrVUyKHUy8sGpga6mNzZGd72xpj7ZrSutLXnIxHgZsGWPS5hGBwLTWATUsoEhyVDoKeDxf09kJQtQnhSDrZcjcag1vbo4WmN0LhMTA10QXtnc2hxOHCy4GPvf3Eq97nn9ku0aCRNmN7G0QSRyblYflrawbnzZizWDm0B08e6SmWhZded7DyuHtIS1kY8hMZlYXJnZzbnU0puISZ0cmKTxjd7E3B+0dONnQEmz9ZYD5/1cFOZ8Fz+mvm6jweM9bhYdvIZG/TLz8RTtV/ZD4re3jawMuJh7sEXKvdx5H4827lLCCFE+YdmRQfkykPVNsdu/w/bx/nCz8W8QoOtmlIieNoaISwxV2VH2rOkXKWlSrJ735rzEXidVYDD9+LZZWppQhE+8XfB50Fu6J+chx3XY9DV3YodBDkWmgA+VxtT3nToLOnvhcZm+vj+Q2+F2Srq2vVNX08UFhVDUgJ2lpaVkR4EerplDtxkZwvxbOch+MTfxeCw6xibnYEcc2tc9vkA+xr54k4jT5Rove3A87Q2ws1o1bOWt1yNxkc+9jDgap69zNPRQk8va3jYCnD4XjwGtbZXqFY8r0dTMAyDY6Gv2fhtdPvGcLU0REpuIWyN9SEqKkZmfhEO3Hmlcsnjp92bwtncADbGTVAgLkYvL2u4WvLZ5O6NzfTB19PFspNvP8e1Q62VtiOLoxMyC+BqZYhXmfl4lZGvFDNP+fMe1g5tgZMPX8NE31Ghg6x0ZUA+T4ddsqgqTUB6XiEs+Dyk5IjY98tyguaLJUh7M0h2/2VWmed3739x2DPJT+3fxMLeHvjqiHKHWFqeGFej0rB7YjusPBeOyKRc5BdpGAgsY1VNXS8qUBolMK9jKPlmw5YhFL9zmdr3UVlV7xIyCxCw5rLaxM9XvuwCexN9dlsxaUJ8+D9p0mmNiRTLSEgely5EyPM0pOSKoMWRztCRBSdD2zRiK2jIbm6dm0hnipSVaHzDyFZYevKpQoWWDR+3QtDPVyEpYWBhyMWaIS2QLhQr5AiY/oErLI24Cjf8Bb2lywFPPUpEi0bGePQqG96NBAo35KmBLjjzKBGvMgswt3tTGHC1kZanOmm0fNJqABjfwUmpMt0kf2fwtLWw8coL9PK2RmMzaT4rC0MulrQ1xd01W9Ev/Bp8E55BpK2LS65tYTJxNH7ne2BIZzc4mOkjTySBvq4Wpuy+p1TmeKivA35+U81OVTVA+dlCW8e2wdZr0ejuYQN3GyNcf57GVtH5fUxrFBSVoPcv11QmXh/aphGCvGyQnieCpREPZ58k4fC9eMzr7qaQ7FNTgsoNI1uhkYke0oRFSm0+/ThRKWG4p60APw5ujlvRGdhy9YXSCGzp6jietgK2c0xWdSagmQWuRqRh9+2X0tl4A73B4QCJ2YUAoHIq/vZxvigqYfCLLC+TXBUbd1tDmBvy3laOkb9msgreJLY3hFBUjB5vrlHgbZLSlNxCjZVzGpsZwJzPxbOkXIW/8YW93eFkwYchVwcMUC0jfHTPbVjofJK6qCpnKKibrXTpWYrqarCVLJSjsfiOrQCrBjdH80YmZcZnmlIiANL758/DfHD9RZpCBbq0PDFOzvLHV0ceqW3DwFb2KBAXw95Un10+X7qq2rweTXE9Kh27b7+En7MZ5ge5QU9XGuPEpgshKpLAyYKvtDzewpCrNFtFRjYryYLPw+yuTeBiwYeVQA9PS81eBwBekQg77DKRufsA/MNvwlgkRKaNAwoHDMQF947YV2KNTz5oovL+uHWsLxYdf8x2lMi3bWwHJ3TzsIIOh4M7sZlY/0+kynhhTIfGcLbg49d/nmNIm0Yqi5FsGtUa3/79RCHmlMUZ0uWARQqzmGS5lXp62yA2VQh9rjY2XHquMHD5JD4H3o0EuPEiHQFNLZXiyeUDvfHLpSh85GOvUOEwLU8MHS0Ozs/tjEvhqSqrNJdu4+5J7VAsYbDmfITK6nWy9vo4mMDWWA+RKXl4kZKHI/cVKxaqun4md3bG2SdJeBSfhe8/9FaYRS9/nhYefYSs/CJc+bILTPR1Ff4mZDmi9LlaOHIvHofepOaQrzB9LDQBx2d2Ak9HGwVFEhjoaqu8noCyiwPIigrId6y9ysxHV3crtHMuX7L+8qJqeg0QBVKEqKeuM09d0GRhyMXUQFf08HibZybkeRpColLZDqjyVLrQ1J5f/4lSShw50d8JFoY8TNp1F93crdibW1nV0mRVTzxtBQjyssb6i1EAgG3jfJGUVYh9/8UhLDEHn/VoynbwlFa6swgAfhrWErraHMze/4D9XGRVUNxtjfDsdQ44HA7iMvLR0dUcD15laazON7trEzZw0dHiYM+kdiguYcAwwL24TOy59RI/DfVBrqgI3514ivXd7KF/8m/YnjsBmwe3UczRxjXnVjjpEYCLTfyQxzOQdriN9EF0Wr5Cp83nQW64FpmGPbdfop2zGSb5O6vMDSV/3PL/X1aZZc7+UIWqMr28rDHM1wEvUoVKwY6qgEQ+uCqSMNh98yVScgsxpE0jdHS1QERSLn5X0XnU0dUckzs7Y6KKWUcbRvogOlWoUP3mh4HeEBWX4LO/HpZ5ncj+fXxmJ+hoASUMUFAkQUhUGrvN1FwROrial11i+M01VyCWKASGC3t74Mj9eGkHo44WOBwObAR64OlwUFwC6HO1EJuej6UnwpS2b2HIxdd9PBCZnKuxks3mMa3R2Ey6/K7033h1j/DRPbdhofNJ6pLq+P5SV71O1b0fUB6QK6+yBvnWDmuJgKaWCvk0VcVnsvaqG/j7cZA39HR1FJZhyQaV+rawxeca7oWHp3XAlchUnH+arHHQY+3QFrj5Ih39Wtgiu6BYYV9f9mqGf8NTlTryyqr4Jj8otHZoCxy9n4B53d2QmifCH2cewf7mZQx9+R86RNyGTkE+Is0bI9K/B3jDh+LnZH1EpOSxx5qQVQB7E32lWTtFEgn+vBlX6p7qDlMDnsKs9WmBLjDS08G+/xQr4m4d64sj9+MxroMjeDpa+Ob403Idz7qhLdmUE4v6eKjtEOroao4pAS4YryIxu+x6/O3jVlh28pnS+8v6fP/3cSvcjE4vd8w84wPX/7P33fFNVf/7T0aTtknTlTbdu+mGLnZpFWhZopUhIlM2CipDxa34EVBBUPyIbAUXskSULUgpG1paumjp3iXdGc3+/ZHeS25ykyKiH/19+369fEmTm3vPOffec57zHs8DoQMHTnYcjN2UafE3Pz0/BI9tyqR8nhopwoyB/miWWQ7CHsyqxeN9Pcln1TgwJ1dq8NqhPDPHb4tMBZlKg/K71GzARY8Eg89l4eMT1ADloGBXiAS25HV7cvTSGbEf8nG2M8OxdNf4s/a3OqM6OswfFkvWCwAe3HqBVK/9/2R/Z72yKUCjcygQ0cNfbtVRQEtqpAgju481Vbrg21onSz5T2EgbOTv03GB8fOI2JRJIt/gSkYtwDwG4bCbeOpyHNrka38zpj1u1HRgQ5IL8ug7sulCO+clBWLEvF9/O6X9fGVbGn6XHeZNcSMY2ONgV7zwWCbVOj84uNUqbZBB78DFl2xXLIHRSX2h0OpzIb0RtqwLpcd7YnlmGeUlBSPB3BofNRGNVPYIvnIbg8EE4XcoAQ6+HfGgKNrjEYZ9vP7TbOZid98eFgzD+i4tm19w8NR5ylQb2HDYpK2yt38bOPDaTge/nDcQ7P+eT34tFfKwZHwOZUgsOmwGZUks6uKw5Jwlw9c64SAh5XNS2K8wcVqYcTotSgmgdQHSSvUtTQ1Hf1gWxB58WvJn2k/g7LUoEH2c7aLQ6M1C/NDUUP16vwamCRnyQHm1RvpnNZODgc4Ox8sAts5T5yYm+2HmhHHfuSjEvKQj9Al2g1+nQ2NmFICEfHV0aMBhAs1QJrY6aeZUaKcKSYSF48ouLFq97cmkygtz4Zt8Bf71s+N+15vZiqL/HejHUv8P+LVwmf9Ye5vzVIlNB2qXGwm+y7nvtB/66zKgUsRDTBgVYdXLVtSlwtbwFRQ0dCHXn45UDtyjrgJDPweonY/D6oVuUDA6CnLqurQvH8xostmH1k9EobpLitYO3MG9ooFXnxnuPR6LSpOSLsE+e6kviI6Idvi72ePara/cVFIr0FCDVwwY1u3/Ey7I8CC+eA1utgqJPLLITH8V6fhQq3fwsYovNU+PB57LhwuOAyQAO59SRwjYrR4dj7bEirEgTI9Sdj1a5hrZsftOUOLCZDLx7JB+uPC7eHBve7bBg4Gp5C1x5NnjZZPyN+7PqiSh8c7mKXPcJHLP6yWiLDiFL+IYYk6GhQkR4CrB8n7lD0RrW2j4jEb4udsgoltxXZhSbycC26YmQqjTIr2u3+BwMDnbFqieioFDrcLmsGdvPl8GVx8ULw0MAAJ/9Zhlfvp8ehQqJDDWtCugBBLjywGEzodPp8W53JYPpe90qUyG3tp2iwEgYnfPY0rzwR6pqalsVeHLzBbwyMox2bHfP7o9ksZvVc/wRexhr7n275Z2cnMBgMO7rWK22V6q+13rt/7L9L+qV43ydDPXWx4rQLFNiTIynGc/AjJ1XsW5SH/xyq45Ctn22qAkypQZrJ8TAyd4GFRK5GXcAXdtbZCqsO1lM256PT9zG8jQx3vopn/zMVHHO2GG2rbt+f+XocMhVWnRpdDiUXYu1x4vIiEZtmwLrJvUBi8m0yhHw2uhwMt2Z+IzPNa8vT4sU4fG+Xlj6Yw4lcsJkMDB9gD++ulQBIZ+D6QP9EefnDBYDKJfIUdksw4bTJVg3qQ9s2Sycud2IV0aG4bvfCpC//jdMLruIR25fA1OjRmvCAHzx5IvY7ZUAYZAv5icHodKoPM3YGdeuUNMSuG86cwdDQ4V/SA1wzfgYeAi4+DmnHnelSpLfyFDm54O3fson+7x4WAh+mD8Aq44UksTrdLYzswIbJ8eiQiIHn2tDUQ5MFguhVOswJykAlc0yFDdKARhIQrd2Kw4SZkmyd97uG9g0JQ5vH87HyyPDaFX1jHmaiL9r2+Q4mFWLWYMDzGSl53VzK2RXtVpXlPFwgEjAxdoJMSi7K8Pthg4cyKrB7CGB2Hu9GnwuG6+MDMPOzAqsPV6E6QP9MTRUiJf25lAcXwzosW1GAlnSV9umgL01kluRA9gsKraoa1NAoTI4Cv8O2fC/w3oxVK/12r+Py+TP2B/lsrRkxmM2baB1iXpjYQ/C/qhQTotMhU6FGrVtcsxPDqLNFHlxRCh0ej0szWhNHV0obOjEh0bZILG+TiSuIGxigg8uljZj5ehws8BhXk0Hgt35WDIshLa0fO7QQHzUjbPCRA7W+T+7CcQtre3bz5djeZoYNiwm2Y6Vo8J75AgSylqRVnIZY/ZexODqW2BqNSgIjEbXy2/iXVYYzmv4JK7qUmstXn/P5Uq8PFIMpcYQ5MmtaSfHx9PRDjtnJuKuVAW1DvjkFD3m3Px7KSb388VnT8eByWCgtk2Brb/eG/8lw0LMxt+4P8FufIyMEqGmVY5HxG4k55M1ERM6fGM85lMH+OF2Q4dFQu+8mg4zwZZlqWKU3pWioaMLUV4OcObRqxUbYyGxyAEiRy4+3nfbYoYcgf1e+P4mRcXOx8kWd+7K0CJTWX1+JJ0qLDc6JxFA3fJ7KdwFtvj06TjE+jqRTuN2hQbZ1a344Wo17Tl3ZlZQ1KQBy/PCH3l/7TgsA6m9hWdt7bEiRHs7/qOw033P/GfPniX/XVFRgZUrV2LWrFkYNGgQAODSpUv4+uuvsWbNmoffyl7rtX+w/f8Y4fsjfaI79mEQaRqflwFAbqU9BFjbfK4UyWIhhoW5490jBbTnNV4ACLJGQn3Oz9keed1Oq57aLlNqUNemsLh4XS1vAdvEaWSsOHcwq5ZCskhci5DjXbEvh3TKEJ9vnhqPXRfLMX9okFWQVNjQSVFaE4scIFVSN7hCPgejoj0oPAAF9R14ae9NrJvUB8PC3dGhVOHRMBE2/16Kz87cIUFVoJs9UiMNTrQF/TwwsfIaWt7eg29Lr8FOo0S2ZxiOTHkBwmenYtrxWvL8TUbnz65qRbyfs5kzbvWTMWiRKbHuZDHFmUZIOvcIDvkcLEgORrtCjSAhHy8MC4GtDQs/ZdeBxWTgsT6eZhLIz32bhU+e6ov30yOh1zOsgquqFjkUai0+PnEbgHkG3oBAF6wZH4O7nSrcrG5FsBvPrM0zBvmjVabGB+nRFH4MwAAox8R44kJJM3bN6oePT9ymgLTMEgna5GpEegrICOYjYjf09XEkyzpNjXjmTZ2hxvZyWhhEAjuIBHbwcbZHrK8T+gfKsO28IR3d+HdCPgfR3gJKuWRTZxduVLZidLQnsqtb8X56JJztuXC250Ch1mBpqhjzdl834zAYHCwEm8lAbavCTLFx/aS+f4ts+N9hvRiq13rt4WCDh2V/NXajk3gn7I/MX8ZjVtViPaDQx8cRkV6CBxLKkSk1yKpqxebfS8mM7tRIkRnp87I0MTKL73ESGjsTZUoN8uraUd/WZRZsWfhNFnbMTMTFMglJKB7mwUdVi4LCY2RMUC525+POXSm2Tk/ARiM+wxeGh+BAVi2ulregqUOJl0eG4Up5s1V8oNXprDobYn2ccDinDk2dXdDq9NiSUUq7Xnp23MUazXVoN+zHq5X50DEYyAuJReGrq1AxdARYPj5wc+AivKAReTdqSFz18+IhtNcnMMQbh+4FyJanicFkAB+fKCax0bvjIlHX3mW1D0FCHqpa5HC0szEb/0XfZmH7jET8cqvOLOC3YqQYaq0W3s52Zk5BD4EtXPmBtFxTXk62PWKyW7XteGVUGG0pX4yPIw7n1GH1k9HgsJlQaXSobpHDy8kWm38vg4+zHaYO9LNIdG4s3FIukeF2Yye0Oj0l2ExUO0zu50vBLAX1HZi16xo2To6FmwMHGq3eal+yqlrNPvMQ2OLtx6NgZ8MCl800c7S/nx71h5zHD0Mlz4XHwaBgV6w9XmTxuv807PRAnFHDhw/H3LlzMWXKFMrn3333HbZu3Yrff//9YbXv/5z1ppj/e+yvjvD9L5xcf6RPlo4Ndefj2V3X7psQnOinPYcFPUBGFNYcK8SV8hYMCHTBS8ND0SpXo6pFjnh/p+6SJJBjY5oK31M5knF6NbE5fqyPF1x4HKzYl4OLpc1W294iU6GuTYHqVjkO36xDgKs9fJ3tIZEqwegmMpertIjxEdCWWwn5HHw8qS+2ZZRRpO4Jp0SkpwAjo0RQqLWU79wdbPH2uAgcvdWAYeHutIu7ca0/kQb8+pgICmcU0HO9/pT+fvBxtqOV8F2fHo7wnMvgHNyPoAunwZJJke8ehCMRyfglPAldPn4WeQKI80/u5wsel0XrGNk4ORYsJvBzjiGDikjHPpBl2Zny+ZQ4qDRa8G1tsPF0CSUaaM9loapZgUFBLnjhh5tWyVBDRXx8fPy21bRwPxd7vP1zPpztbSxmuhlf35XPwVNbLpPHTEzwobTRuLyPzWRg56x+mP3VNWyaEoeb1W0kh9PZ2014NMwdEZ4CxPo6dm92pLC1YUKr0+OFH272+MyblqSSROW17XhheCjl3Sxu7MT1ihY48zjYc6mSfC9Mnx26fs9PDkK8vxPq27vQ2N6Fs7eb8HQ/X9S3KyllhIseCYaTHRvL9+dCyONSxuLPiAvcr/0v1txeDPXXWS+G+uea1bKvh/Q+349ZIgAPFPLA6y6VehhG118yE9hTgP4BLvDqgcfJ9Bz3w3H5oEI5lridCI7JYHc+/F3s8fx3WWbODOLappycphbpKcAH6dF446c8MvvIuAzLVMnskTA3vPjDTUhkSix5NBT9Apyh0elha8NEfVsXatsV8HW2h5DHgVylgUSmxjyaErYvp8VD0qkieTfp2pUsFiKjWEJZg1IjRRgb44kjBzIQduEknii7jLCqImhYbGT4x+JY2GCcDhmAjxcOR3ZVKwLdeBZL9+m4l+6HFoAY6w/So1HTKrdaFvfeE1GQdmnw8QnLGObtcRFYdYSqBO3vaofGDiWe/y7b7DebpsThTFEjhoQIcTCrFn19HBHmIYCHoy0Y0KO2rYvWUUVg0Y8m9gETgKO9DSqbFbjd0IGcmnZMiPfB8fwGTB/oB4lUhe3ny2nHjcjOHx3tCRYTuCs1cLVeLW+hOKZC3HiUsRGL+Fg6QgwhnwsbNgOvH8yziuv6BbhAodZQcDJhRBmntZK68yV3MX0HtRzvj/COAeb7DNM94P3s0QyZjSos+jb7b5lr/2cE5vb29sjJyUFoaCjl8+LiYsTGxkIulz9QY3qtF0j9m+yv4jL5X6ax/5E+WTp29+z+WLE/x0z9A6ASaRr309fFDqOjPc0ILOvaFPByokZqjJVRLKnI9LSJ/XB8DF49eAt+znYYRXNdU94fou1nX34Elc1yrP61EBKZEi88Gop+gc6Qq7TIKJHgSlkznu7nC61OB39XHjQ6HZqlatoU8+MvDkVeXTstcGExgPHx5g6LU/mNGB/vA3sOCzrocbdTaeZUMK71JzgVmjqVaJEp4WTPxWe/GaKL6yb1pa3jJ/r69ex++ODXe7xULJ0WgypzMa4wA2PuXIKDQopW/xCoJ03CsagUBA6OB4thIDDX6wF/V57V8+9fOAivH7IODkJFfKw9VoT3Ho/COz8bavJTIw3E47sulJOgKMjNHi1SNdoUatqSgo2TYxHixkNli9yqw2bVE1FI9Hc2qPLR8IAR4Gpigg8yiiUkeO2JCP/rZ/uByWBg87lSWjUh4B7wdHewxetjwrH6aBGSxUJ8ea7M7Fg2k4G9CwZSSg1Xj4/uEWwRoEfI5+DzZ+JR1SInFWXa5GqcWZECPxceZEoNblS2Ugg3jd8LY2evtX7vnJmIvLp2HM9rxKhoEQJceXjhB/r7Q5R+Go8FgAcWF7hf+1+sub0Y6q+zXgz1z7U/onr7V5o1AvCDWbV47tGQh4a3jK9F57TvCdvRjZlZQMEoA0qp0T1QENPY6WUpmGcJVxHZyMPC3VDdqoCjrQ1OFjRgX3dwzdjBVNMqR4g7nyx32jItAc99lwWtTk87Pi+PFKOxowtXK1rILO17WFCMCyUS1HcoSPzo42xHcjESuGh5mhiF9e0YEOgKJpOBUwWNlGxkwNzZsG5iDPZ9fRwDs8/hsdLLCG0og4Zri/pBj+Bu2lisZgTjZoce/QNd8PLIMDTLVOBzWVj8XbaZo45Yz1hMBj6c0IcSRPwjzoqFKUHIrWm3iCG2Tk+Ap4ALNouJxz6/YPE9Wz0+BqVNUopQyYLk4B65me5Ku5Aa4UFRzVs8LAR3mjrh58Izy1y6VdOOoWIhalrl4HHZZkG6W7VtGBQshEarpw16mjrjIr0E2D7DUDUQ4+1opsA3ONgVMwcFYME3N8yepfU94N33Ho/Ct1eqsPrJaNS1d+Fzo7LBBSlBEAm4OH6rEd9cqYSYxnltTUTpzbGRtLjUOHBM2LdzByDW18niHtA0s9TS7yQyJV4fHUF73Yedhfo/c0aFhYXhiSeewEcffUT5/JVXXsHhw4dx+/btB2pMr/UCqX+L/ZURvr+asNeS9URWuX1mIhnFs6pelxyMGG9H/F7cRBIwTkzwQZAbH+4OXAQJeXCwtSElSy1tZoV8DtaMj6HlzTFdpIz/Nkje+iPcQ0ArwUqMY0/EglszyshU8upWOSqa5ZjSzw8zd11FWqQIMwb5g8NiGtKmuyM9c5ICwWYCAjsOmAwGGtq7cKm0GX18HbH9fDm5uL2UGgo2g0Hr8Ng0JRZ6PSxu2n1dbHGqoAkZxRJodDp8+nQssqvaUNksp/BECfkcTErwweOx3qhsluGnm3WY2t8PthwWihs64cLjWCUDf/uxSEzbfgnxVfkYV5iB0bcvQChvR4WTJ36NTEbAc8/CLr4vtHpgw6kSSkZMiDsPv+bWW43gvTEmHDN2WSYH/XBCDFpkagwOcYVeD7y8PwcMMDAnKRDNMiVC3PlYZ6REsmRYCK6UtdBLW3sK8MlTfVHeLMOeS5UWs9EWPRIMrg0TF0uaEe0jsOjoI55ZpVpHgvaeQOXqJ6MhsLPB4u8sRKu6AV+0tyPsOSy4OXBxs7oNn/1WQqvQN32gP1pkKrIPACzKY2+fkYidF8rNIonGDtdITwHWTohBsBsfV8qaaZ9Nkkiey8ambqLPnvr9+phwzNx1Dbuf7WeVdP/1MeGY1h1VNGSpecHXxR4+TnZo6lRi/clis43Xv1VNrxdD/XXWi6H+ufZPyIxqlamw/0YN7DkssxJp483/n8VbRFYDmwVUNsux8XSJRScC3bWI3zMYoM3WFvI5mJ8cjLRIg1IwXYkQkamu0epJ55RptgXxt1anw8Qtl9DUocTa8THYfanS7D7ROal6Up6lCyguGRaCkwUNCBTykBQixJs/5dPy/BBOrFFRHtADmLf7utlauG1GApgMBqX8isjkGh3tgS6NFu58LipbFBT1ufnJQTh2qx7VrQosTRXj6K06HMqqRUzDHYwuvoDHS6/A5241Ojj2uBEzGI5Tn8aSVnfUqpgQ8jmYNtAfyaFCtCs0lPPSBTOJ5+p8iQQvjgiFuwMXlc1y3G7oQLS3431lNBP9en1MBI7lNZhlNy9LFcPZ3gbfXq3C6GgP7LpQQZ/hb4Hk3hpJOYHH9AB9sG12fwQL7cFkGsrstDo97nZ2obatC3xbFhQqHa1TZPNUQ0Ds8M06qwq/Xd0VAjWtcswYHIDSuzLaPdJ/n4mDn4sddHqgoV2JBd/cw//34/TbkVmOjU/Hws6GhavlLWbOLgL/3GmSoo+PExZ/n02+Z16OtkjdkEE7fiMjRZjQnQ1P3K/Xx0SAx2XhjZ/yzEpqjR1Oxo7cPj6O+O/vpTie12B2jcHBrliYEkyhGLHmtH6YiQ1/K4G5sW3YsAETJkzAsWPHMGDAAADA1atXUVJSggMHDjxQQ3qt1/6o/S+5mh4WF4CpPSzCywcxq31q7MTV8hYIHbiI83WiPdYYlBCk2+89HgV7DotS9z47KQC2LBa+OFcKwOCooiPam5jggw2nrHPgEAsq8Xe5REa2Ia+2w6zO/I2x9/gT9AA+PEZfU70zswKrnojCqiP3gN0HT0bjjUN53c4uPyjUWqw+Ss0c+eFaNab088V3V6swId4bEqkS4Z58cNlMpMd5g89lQasD/J3tsfTHHDP+nP03atDQrsSh7Fra77ZmlGFyP1+EuvPBADAoWIjGDiW+uUxNPTe+F1u7x31paiiyqlsxKNAVXk622Hu9BstSxZhryuPTIkNSSxkCV7+Jywf2Q9guQa2DGw5ED8cv4UNxyyMEkV6OmBHqD1swKCnxBDfC5qnxKG+WY3YSPfHkK6PC4MLjWKzPnzbQH/YcNnYYPUsvjwxDU0cXThU2YmK8D2Z/Rb3uom+zsG5SH1oC9OLGTmRVtaK2VYE5SYFYf7KYUp5xIr8RT/T1gq0Ni1SpIQDt1AF+CPd0QH2bAsFuPGR3n/9EfiPmJQWSfQhy42ObFa6p4iYpQtz4Vt+xD56MhlKjw6ojBWbtI8CtgYTTFxtOUfvQLFVCqdEho1hCfv7m2EgIHTg4cKMGj4S54/lHQ2Bnw8T8PTfMxmhOUiC++L0Uzz0SbJGUf9OZO0gWC5Fb046lqaGYt/tGj6Sxej0QJnKAVg+rxxljOD8XO4S680nZ4wGBLlg7IQZ8DhtsFgMOtjb/arLjXgzVa/8XzYXHwetjI2g3kn+UZPtBTKbUILe2HYeya2nnV2MOlwfFW5Yy2z+aGINjtxppeQL/e/YOgt14UGl00Oj0UGq0uFHRBiYTkCm1WJQSDB6XTXFwSKQqRHkJECDkATAPYhJcXBsnx2L1sUKMifZEcqgQ607em1NfHhmGdoUaV8qakVPTjtdHR+BccRN4XBbt2m3K2UgIcdDxXm6aEou6ti48GuaOmjYF5iQFoKRJijNFTcipacOswYHo7FJj6/lyzE4KwJ0mKQUHWhJ3MXX0bDhVgvQ4b0o7JVIVtmSU4XyJBKOiRfBz4ZnxJ7209ya+erYfmDodrnz3C54rvYQ3T/4K1+YGtNgJ8FvoAAhXrsLrHW7YMGMg6qVKrOdz8OP1Gki7NAh246GqRWF2XoLrKrubX2higg/8XOzh72KP5FAhGjuVeMMo431ktEePnEvG/cqtbsdTiT7YdaECKWIh5icHwcvJFiqNDl9mlGFklAi7LlTgheEhtM6oF4aH4HZDp9lzaI2kXCxyIJWM6ezDY0WYPsgPdiZKvvOTgyBTarHdAi7adOYOVo4Ox0cn6IMvxY2deD89CutPFoMBA1n63U4lAlztsHt2f6w9VkRi+3fGRaKjS41XD+QhRSzEuWIJ5VzW+DIJInSxyAHhHgK88D19wJAQ0jlfIoFOD2h1evI9+3nxEIvjV92qQGF9B4aGCvHRxD7wcrIj55Vv5gyglNQa7wEt0T5odXqzyo2+Po5kNjlhpwoakV3VSnFa/1N5jR8IzY0ZMwbFxcXYvHkziooMnR83bhwWLlwIX1/fh9rAXus1U/snqLHYWVOH8nCAnY25ctn92IM6uf6oY47ueKt9EjmgsL4DW/YaIoYRnoL7AiXPf5eNdZP6oKmzC872NqTiWISngOynpc1sT5tcY+K/4sZOzBoSgFARn2xDQX0HsroJyt9Pj0JebQdFtct0rE1TyWtbFWT/Cuo7UFDXgduNnXhxeAhkSh0l6mIMQm5UtWJkpAdWHbmXKkvU4ROLS2FDJ3xd7DA7KcCMLNLR1sbid6fyGxHjLYBMqUWLTI2aVjk0Oj1eGx2O6d0REUv3Yt7uG9g2IwE7L1Zg3tAALB0eiu+vVuObOf0h6VTi9Pcn4JR5HLOKM+HR0gC5sxB1o8ZhATsCWd7h0DOY5PkWpATBhcfBbwVNtPdn05k7eGdcJK6UN1OU1YiU5++uVEGq1JAODWMT8jkYEuJqRjI++6vr2Do9AZMSfLDegrOETp0EMDy/TZ1KBLrxzAgsV+zLxfYZifBw5OKV/bfI7whAC1D5JIwB8ZykAKxIE2P219fhYMu2+v54O9riRmWr1WNYTAae3nrZrH0bJ8cit6YNwW58WhLOtceKsOGpWGRVtWLl6HCyXPI/vxZg7fg+yK/rwJGcenw/byBsbVikchFxT5amitEs7UKkp8CgpNfDe/fluTLwuGzsmJmIsrsyq326UdWK2UkByK6y3neCHNRArO+JZ42cjXwuG8WNnX+ovOWfbL0Yqtf+r1qcrxO+nTsAHxwtfCCS7T9j2dVtlExoU+eBu4MtufkvbuhEh0JNi6us4S06gvbdFyswuZ8vxQn2zrhISJVauNhzIHLkIruqzaz86afsWjCZDAwOdsWKNDFmDPLH6qOFcLbn4LXREXC0Y6NFpgIDsBjE3JpRhqn9/eDtbIdXDuRiYoIPlo4IhUanxxuH8sjrrUgTw9HOBjMHGRxDfFsb/DB/AD777Q6ZURvr64R4P2cy49xSIDEtUgStDjh8sw4fnbhNBuu8nezw8sgwbDhVQjqYlgwLQVWLHKmRIjKYY83JRdyrnpSCie/eGBOOD45SN+lsrQYDqvMgm70NjxZdRHLLXbQ5CSFJHYM3+FE4JQxHmLczFj0SjFU2TEpw6NVRYehUapBX244ME4cHYTszK7AiVQw2m0lZs5alinEsr4GCK+d+fR0fTuhDWdMJM1XOBYA4fydUSGQYGeWBQCEPTAZwqbQZey5XQiJVobZVgRSxEF1qnRnx/DvjIiFTanAiv9HMGRvWTQq/8BtzSok5SYHQ6fVWcYFY5IAJmy9R7tdLe2/iyOIkq79jMWAVFxQ3dmJ8vLdZYLWooRPvPR4FWxsmbla3o7btHgn+1AHmipPG4kF0Ge8SqQprxvcBm8HoEf/Q3Ze1x4rw4vBQrD91G0tTxRDyuJDIlNhwqhhzkgJxIKsGk/v5ws2BS5kzTOcPYl9i6R1Y1C22Y/wOAJZVDSVSFT46XoSxfTz/sY4o4AGdUQDg6+uL1atXP8y29Fqv3Zf9E9RY/qoIX09OLnsbFgUIWUrNjrPAHWDNkWetT8aT7wdHC/HtnAGUYy2BEsCwMFuTzLWkkHY/ymmE9Q90QaK/M5o6lFg6IpRcmI0jZCOjRDhb1AQ+lw1HWza6NDqsHBWOLRmlFFU3Ylz6+DghNVJERiCI9iT4OZuBG+O+vj0uknQoLEwJwtaMMpKAMSlUiFMFjfBxMnBkEVE1IZ9DOupchRw8lWjucCCcEvY2bJRJZBRgu+iRYPwwfwBWHSlEilho8V5sOFWCJcNCUN3ShQhPGxSevYynf70FzwP7kd5SixY7AY6LB+NIWjImLJ2CixVtmB/lgU+N0ovnJAXil1wDsbi1TCSpUoMoL0e8eiAX0wb64/30KJzMb8T7vxSQz4xWB/z03GB8dOI2CXjfHheJVRaUEDeeLsHrY8L/sLT1slQxOrvU2Ha+3Czj7ExRE8olMng62SJFLERTZxdtf+YkBQAAlGod5iUFYvbgAOzIrACfy8K2GQnQaPWYO5RecWZOUiDUWj0OZtdgRVoYLfBcMVJsFtkibGtGGT6Z1BdO9hy8vD/XrA9iER+d3SDTWPXw44l9cO62BC+NEOPzM3dwsUyCEeEiHMyqxfRBfgZnUWUb3vjpFoQ8Lv6THo1TBQ339d6dKmiETKnB7KRAUinP1F4ZFYbVRwvh78rD4309sXhYCJ6j4U977tFgvPtzPgDDc7HVyJloCZRN234Fe+b0x9BQN9ox+6dbL4bqtf+LxuOyMSREaJYR8FebtaxzIoghFjlQpOJPFjTiw+7M3NfHRiDS0wEF9Z0WA6F01yDmL+M538fZDkqNDnsuVVIyq72d7QyBr26F1y3TE2DLZuLl/bnkca+MDIPA1gavHrj32aujw+HT/VtTIxwypwqbsHJ0OA5m1SLEnW82n87++jrJmTV7SCB+vF4NqVKD5Wli2LJZ6NJo0dDehQA3e/yyJAmXSpvhZG9jlg1M9Nc0Y2jtsSIz2gVic71tRgLq2xTkutMTnjQOONEpBRMmFjmAx2XjdmMnOBo1kiqyMfr2RYy4cwXOXZ2ocXRH5Zgn8AYzDM+8OAkHb9YjxtsR2owyLE8TA4AZDrtU1oyMYgmtw4OwZpkSLnwuhSaioL4Dc3dfN3OmSaQqnC+W4Ktn++Gj4/eUc597NBg8DgvuDrZok6tJ7qu916qRInazKNBT3NiJ+clBEPI5aFeo8dHEGBTUd6K+TUFx2BBtItSbbzd1GOg4ZiTik1PFFNVCJoMBfxd760Gnyjbasbjcg8Jhl0ZnET8seiQYgJ5CKE4EVjdPjceib29g5ehwtMiU+P7qvUwhS3sHArO8MTYctjYs3Khsw0cniuDK4+LTp2PRpdaCybLuHAt252NHZjktF5pYxMOro8IpmfevjgqHkMdBjLcjVh8txMHnhtCOE2HEHjDZCo7ffr4cy9PEeO1gHvmZh6N1VcMHTZD4u4zZ8yH0dv78eUybNg2DBw9Gba1BunvPnj3IzMx8aI3rtV4ztZ7K2FpkKtrv/gojInyRXgKwmQxEeglIErkHNcIhRGcfpEeTPEvJH5/FtO1XcKWsGV9frEBBfQeZMrr7YgWulDVTjsu8IyFlewnOBuMU0+uVrWiVqe71ydPQp8HBrjiwaBAc7diYmOADIZ+D4oZOyNVaSv/9XKxnMYlFDlixL5e87paMUszu3tzvv1FD/tvY9t+owdLUULPPAZCRBsAQhXt2SCAWf5eNqTuu4ER+Iz6c0Adrx0dDLOJjYUoQlqWGIsbbERnFEjz++QXM35OFm9VtqG1V4D/p0XhmgC+lfQRIGhklgpDPIduz6JEg8GzZVvva0N5F/h3n6wxfFzsy+vTUlsvIKJYgyltAbrjTIkVYOTocGcUSvP1zPt78KR8arR6pkSKz8/94vRpVrXKzti75PhtNHUosSxNjXF8vq+0L7WzAkL1fImDYYOz9dC5892xHtlc4Zk56D/2f343XRy3GJf8+2HmpGn4u9hDybZAe5433Ho/C0FAh1hwrJB10BDA0NbHIAUI+h1y0u9RavPVTPrZklCHez5ns7/PfZeH1Q3mYOzQQh58fjPQ4b1S3yO+r7IvO+ge6INbXCRsnx2JRShAGB7vik6f6Yu/1avi52pP3ghjrLrUOL48Mw6HsWjz++QWc6858Mh17omyQ+N27RwrQqdQAAA5l1yGj+C78Xe3BYTGxcXIs+f5EegqwflJfHM9vwEcnbuPJOB+0yQ0qh8bHfP1sP/g52+FKeYvFft+VqsBhMzFzkB9WPxlDtiW3ph2Odhw8920W5Zl4ae9NNMtUSAhwgqfAFs89GowgIQ+1bQpMH+gPGxYTEzZfwuqjhWjqUKKgvgMnCxqQU9NO+z4C1PcOAK6Wt6CxvQtspoEA1rTfvxfdxcpR4fB2ssN/fi2EVqfHV8/2oxy3Y2Yirpe3ok2uRqSnAKOjPSn339rGZM3Ror91zn+Y1ouheu3/srnwOPA2Kld52NYiM2SJtMhUkCk1qGtTWF1X0qJEZlLxWzNK782nP2TjZlUbLX66Wd0GAFCqtUgRC/FBejQWpgSRm1Xj+cvYuW58nhX7cil4AwA+PV2Ci6XNlOOe/eo6yptlaOrsIj+bufMqxsR4Un5LmFjkACaTgWhvAVbsy0UfH0erjp4Yb0fM3X0dTyX6YlFKMI7k1BsIoE8WI6+2HUUNUkiVGrTJVQh242FAoAsWpgSRfZ4+0P8P0y5sOFUCoYMtFj0SBKDnrHg/F3vy72WpYkR6GvCGcTuEfA4W9hOhbc/32HFiA25segY7D6xCfF0Rvo0bjcdmbsT8d/fhp2nLkOUTgZ0Xq9DXxxER3etxm0JNm4Ht62wPiUwJFz7HIg6ZmxSEjaetU0wY2zdXKqHXAR9NjMG6SX0xNFSId3/Ox8v7czE0VIj3Ho8iSxFrWhWks4XOxCIH+LrYYfXRIrz/SwFu1XYg2I2Hvr5O2N4djDMdp/Uni+FibygR0+r1+CA9Cusm9UWKWIjdlyrBZjHwc06dRVywNFWM7ZnmQisAsP18GV4dHU773bJUMXZklmPf9Woz3LR9RiJkSjU2/05/3k1n7mBCvOHdShG7UZ4XS3sKAJidFIgXf7iJ1w7egq+zHT6fEo8lw0JgZ8OCwNYGq48WYUW3I9LUVo4Ox1cXK3CqoNEMt5c3y1EmkePVA7lIFgux6vEoJIuFePVALpqkSpy93QRXPrdHpxCxB+zpHQjzEEAk4JJYq7pFRjpQTW1BShBKmjoh68as/0R7oMyoAwcOYPr06Zg6dSqysrKgVBpUs9rb27F69WocPXr0oTay13qNsL+Kq+lB7K+K8NGlsb87LhJSpYYiG2oczSIiLQTQmW0SzZm2/QqOLE7CGgsZPR8eK0J6nDcivQSI9HDAukl9oNHpoNMB1ypasS2zDEIeFytHhyOvtgP2NiwoNTr4Otvhs6fjoNXp/lDUhEiZJTidThn9m3BevTo6DP7O9tgzuz/WGNWGL0sVI7NEgja5GoODXTEp0ceMt2jO19excXIs3hxjKBVrU6gtpny/+VOegVuHJsNnZ2YFNk6OReYdCZo6u8BmMpFb0261r0UN90oXPRw5eDrRD1cqmjFrSAAcbNmQKzWQK7WQyJQWsz4WfHPDLIIGGOrCLYGcL8+V4e1xEVCozWv/vTqaMLYwE0+VXkDImtvo4tjiRMgAuH+yA8/Wu0DBtDE7X3FjJ14bHY7qli58eLzIYhSOLhNpTlIgPjx+G+PjvcHjssmF1VJ/Z391HTtnJiLB3xF8jo3V8c2v78CSYSFmCoUEl5JxFPml1FAcu2XI4koJdTPLRov2FphFak1LASyVDc7fY7hHAls2+vo64bMzd7AoJRjz9lzHk7HemDrAD1UtclIthc1kYGCQC2Z/dQ0pYje893gUatsUKGrowJaMMrw0PNRqv4Pc7NHY0QWuDZsSce3j42i1bDE9zhtRXo6w5bCQUXwXAUJ7eDnZUqJqhO2/UYM3x0bi11v1VtPZjdsV6SnA7ssVyK/rwKonolDaJKP0+6tLFdgzuz8WpASByzbMkUFuPGRVtqGwvgMfHi/Co2HueO/xKFS1yNHZpaaMQ0+grEOh/kenn9NZL4bqtV77a8w0+3tAoAvmJgXiakWL1fk1r7YDZ4uaEOkpwIKUIPySW0/JfhgaIrSYEf3Br4XYPC0OFRI5zhlx9q0cHQ4+l5o99Eeyfgj6gYUpQRTuSOK4s7ebyJIgmUqDBclBZm2ckxQImVJDXvN+6Q8+OVWMkVEiJPg740hOHab090VDuxJylQa3atoxKNgVKo0O84YGYdv5MjAAhHsIECri4zMabqGertvQ3gU3By4OLhqMDpM1wNjEIgfUtMoR6SnAnKRA7L1ejZmD/LF2fB98cqoYiuYWvK0rxcIbZyH44DcwuxRoE0dia//xOBY2BHdcfQGGga5h/dAgMhOOyCjispnYklGGFWlhJGYxzkK24zDx+ugI7LlUaZETc3CwK1pkSkwd4GfGD2Y8xsS5wz0E0Oh1kKu0ZopvxLNAqODNTgrA2mNFFvmPlqeJweOw4WDLJsvxbzd2YsfMRKv0D5FejsiqbEV1awfOFDXh0TB3iEV8pMd6o6ChA1q9HhfuSGhxQbO0C0Iel1ZB25XPRbiHA3VP043j916vJnmtjCk1zpdIUFDfDj8XXo/PanFjJ1Qa6v7DWklefl07Nk6OhUSqopTFrkgTQ63R4nheA7Q6PXbOTMS6U8VmpcRMJgNld6WYnRSA0iYZkruz6Z+I9cL5EgllzInxvVDSjJdGGMpg7werxPk6wbEH2ofrFa1YP6kvzpdIsCWjFCtHheP7a9VmfV6WKsavt+pwKLvub60e+qP2QGp6cXFxWLp0KWbMmAEHBwfk5OQgKCgI2dnZGD16NBoazJnee+3+rFcJxrr9GTWWP0t4/ncTprfIVKSTCwCl38YLpFylhVylwYbTJVYVIzZOju1R2vSNn/Kwb8FA1LZ1UYgIjRVCds3qB3suC+/9fK+OfnmaGEqNjrYEZ9uMRLzx0y3ahUok4GL9pL6QyFQYGOgCnV4PiVSFy2Ut2N7tAHttdDj8hfbk5vXsbcNCmRQihEavx8fHb1tUyBgZJcKICBFe3p9rVUXjfIkEQ0OFOJBVQ46rRKoEkwEMDBKisKED/i72mLnrGoR8Dv6THk1bW79jZiKyKlvx399LseGpPujj44g7TXJ8+lsJZSzzajoQ6+eELrUGuy9VWWzbkmEheOtwHglkerqH+xcOwkcnDE6gD3f9jjG3L2BcYQYSawuhZNmgOWUE6kY+jl3OUfi19P6U0C7ckVhVxSOI3elU5wCDMmFdmwLH8xpJ3iVL50qP80ag0B4MMEgicWPbOSsRXDYTF+5IkODvQiqs9Q90wbNDAmiVFz95qi9qWuXoH+iCVUcKyWv31HeCBJMoG7SoOjguAk9vNZSrrp/UBzsyKyweuyAlCJXNMkR4Cmi5siypR+6YmQitTo+sqlazNluS4QYMz8SqJ6Jgz2Fj+b4cg4NuRCj8XewxZlOmVeWXry5WoK+PI6K9HeHlZEerZPTltHj8dLMOzw4JQKtMhc9+s6DOSDM3nylqpJDQE7Z3/gDIlFrSod7Tffpyejz8XHhm392v/S/W3F4M9ddZL4b6v22mRN7E/EGn1kYYkQ0uV2uh1d5TlTMmEJ420M+q2tiB5wbjic8vmH1HlM8T81dP87WxehqxvhgLqcxOCsCp/EbMGhwAqUpDUbJdniaGnQ0TFc1y6HRAtJcAeoYedjZsnChoxJ5LFZiY4GN1Ph0ZJYJCrUWkpwBR3o6QKTVgMoDiRim2ny8nr/X8o8Fw43OxPbOcQnGwclQ4DmXXmp3/ftbbMA8Blu/LwYBAF8xJCqQtZ/9yWjxkSg2KG6Vklu6qwSKc+3g7ptXdQFTBNTA1amR7hSErcRh8Zj+DCicPBLs5UMrPTHGKYawjsfi7LEikKixMCUKXWodobwHZtwEmOMNMrUzkgHcfj4RMqbWosEfgOjaTAY1OT3WIjBQj47bEoiLw0FAhyiQyjIwSQa7SwtPRlsLH+fLIMDjZs6HT61Hd0oX//FqAiQk+CHXnI8Sdj3KJnFbVbuNkg4Lcc99lke2lU0GcnRSAi6XNcONz0cfHESKBLRZ2c6dae7cIBwixp9HqdFh54JZFtb8UsRA5Ne14eaQYbxzKt6q0dzK/ESOjRPB2tqNV5P5iajwqmuUobbr3vLw+JgKrjxaaCQQRn0ukKoyK9sDrY8Kh1hiUKAkl8aZ2BfLrO83ub4SHAIUNHbRjsG5SH/T1dYKrPQcufK7Z93R2o7IFbXI17TuwflJffHTCwFH1zeUqfDihD149YNjjEMI7hBLgrdp2xHg7YktG2V+mWPow1twHKtO7ffs2kpOTzT53dHREW1vbAzWk13rtfsxaGZslriaZUkMCFNOytfsxmVKDK+XNOHCjBueKm3DgRg2ulDf/PSmP3XhFqb6XEWaaHnoouxYRngKkRoqsRp9uN3RYTe2tapFDyOegtq0LL+29iabOLswbGoipA/xwp0mKx/sa0sA/PnEbZwqbKKnjc76+DheejVmq7c5ZiQhwtUOIG5/2uq48Ls6XSLDixxwwGEBThxK3atrRIlNC133u6TuvouyuDNUtMhzIqkFxoxRbMspQ1SJHvZXUez8XO0R4ClDSJO0x5bu4sRMjo0SU8qcT+Y3wdeFh2/ky/HC1Gu0KNdaOj8Yro8Lh7WSLPbP7m5Ul/XCtGrF+TpgxyB9hHgJUNCuw4JsbZun40T4C/OfXArh0kxxaaptSo6OUjRF14Zbu4e8XChFw4BtETx+Pq1/MxJtnd6DDlo+Pp72J47/l4J2ZqzCxxRePxgdAyOdYTWdekBKEwoZOq2VbL48Mw5aMMiwZFoJNU+IMSh96PYLdeGSJJJvJRISnAIseCeoxOsrjsDBv9w3wuCxsn5FoNr7fX61Gm1yNCE8B9t2owdvjIvDe41GYPtDfYgnA9vPlsLVhmxFz99SWsX288Pa4CFT1UDbY0H7v/q05VoTnHw22OFZhHg4YEW5QuzE1iVSFCyXN2DI9wayMTabSYOPpEto295SyL1VqUWj0/M3fcwO1bQoMCHSh/U11qwIVzTLEeDvCx9kernwuZEo1Vo4ON7sfJ/IbEOkpAI/Dhr8rz/Kz3J21SpTONHV0wcnOfL74dm5/+DrbI0DIw5HFQ/CfJ6IR7MbHu+MiaUtQFqQEwYFrntX3T7deDNVrvfbwjY7GgZgzjbMljOec3bP7I9bXCc7dZYN8WxsIeVyzcrqqFuvz7JUy+hLrz367g5dH3iufMZ6vTUum+ge6ULgwl6WJsfi7bDP8kB7njS6NFvN23zDDYXKVDrcbO+HnaoeKFjneOJSPsZsycSKvAe+Mi0JjR5fF9fyVkWHwdbFHl1oHlVaHJd9lY+7u67jTJMOyH3PIazV1duFWbTtsbVgYH+9tkYLB2PbfqLFYRjQnKRA5Ne3kOnWxtBk/XKvGzpnmGOBkQSNKmqQI03Rgdd05HDrwFkaOiMPqE/+FB1uH9x6ZjUGLduHJ6evxfsRYLLhkyLDZn1WDtCgR9i4YaEY3ABhKxn68Xk0GXM4UNWFIiBAr9uWSWPj5R4IpOONUQSPWHivC0FAh1k3qi2VpYrTIVHj2q2sWSzBXjBTjcE4d2rvUWGRSWj/7q+tIChXSrnXLUsW4K1XiVEEjtmaUwY3PxWsHb5FlfENDhXh5fw5K78rABAM3q9vIfcKdJilyatopXIzGtjWjDB4CLl4cHoKmzi6sPVaECE8BbSnp4GBXHMiqwYs/3IS6G5+6O9iS1Q3k/aKhLXHhceBkZ4MOhcYqJcGwcBEeCXNHbavCIlXHgpQgBLvx8PJIMfZcrsSFOxJsm0HFTmvG98H28+V4ZX8utmSUQSJVYWKCD3Jr2il7KEKYJre6HRPifZAWKcKICHcs3JOFtI0ZmPv1dXLPmFfXQXt/mUxYzXiUKtQobKDHkabWIlPhrZ/ycbezyyLtgyuPC38Xe6THeYPJvKdUTPDkvvFTHrZklOFqeQuSQoQkxcrfWT30R+yBnFEeHh64c8c8DTMzMxNBQUF/ulG91mvW7I9yNRGE55bq/Huy2w0dqG6R41B2Ld46bHD+VLfIcbvB3Fv/MIzOeVbSJMX0Af4W+Qbm77mBkVEiSKRKi4App6YdS4aF0H5HcMEQ5MGmDq+MYgm0OmB5qtisZp+wVUcKESy0x6JHgrF3wUCkx3lj5cFbePGHHMxJCqTlQHrukWDYc1jY9Ww/tMnUqG/vQk2rHLk17XhnXCTWjI/BB+nRKGmUwsmeS3HMVLfKSTlaUyMUuebvuYGiHpxwd6VK9A90gUSqwvw9VHD30t6bSIsSoamzCy/8cBP2HDZ2XijH5bJW8GzZeGNsOD6cEEMBN7suVOCxPh5QarQ9qr5tPF2CuUn0c6ZY5IBgNx7q2hQYH+eNrTMS8OP1arwwnHoPBV1STLx1Grt+fBuLpw3F+yc3465cg9+WvY/vfrqC+m/2wWbmdFRqWHhE7IaFKUE4mFWLCfE+FgH69pmJELs7YECAM55K9MWFOxJsnhpvdoyPsy1OFTSCzWRAptJg05k7eO3gLWQUS/DyyDB0qXRYvi8HG06VgAEGYnwEPTpEAeD9XwpR395FAVrE+P73bCnyajtwPK8BOzIrwLVhQqnRWXUYufJs4Myjcjz05MRpk6tw/FYjQtx4Vo8rMpoHJFIVfrpZZ8aftHNmIq5VNONwdi2Km6R4YXgIxsd7m53vmyuVkHWp8clTfbFuUl8ki4XYkVkObyc73G7spG3z/hs1mDs0kLZ9c5IC4eVoS+F5AoB1J4vx4nDLIE+p1uJ8iQS2NizsyCxH5p1mHMyqpdyPi6USDAsX4XheA5747wUs/zEHr4+OoH3PxR4OaJYqsfi7LOzPqkFNqwInCxrxxe93yHPOGOgHpVqHubtvIHVDBl49cAt8W4Oc+btHCrBmfB/MGhRAAWXO9v8+RxTQi6F6rdcIM+Z2+rNGR+NgPGcaOw8IHp4Yb0eKIicR8DQtp9t/owYvjaCfM61x5lwtbwGTySDX2EPZtZifHESLsZ4dEgiJTIlITwG2TE9AZrHELBsVMPAGfXyCHlt8cqoY4+O80dSpxEt7b5pxSw4NdUNOdRt2zaI6erZOTwCPy4ZGp8eoaBHWHitCQX2HAXsYOTGM230srx6f/UadxwhM8YUJXnjrsUi48Gywg8bBdDy/ARPifSjr1KmCRmzPLMf6p/rgyOIhWJUeBWlRMWZd3I/Hn5uE8U8MxLAta2HHs8O3s1biv9+ew8wZH+HrhHGoF1BFLTaduYMAV3tsPF2CL8+VIVTEh7uDLYWzUeTIRWqkCGKRIXA6LNwdG04VU/pbSROYIjb/K/blwI7NNBsPwnZmVmDb9ER8f7UaAa72Fh0Xn5wqxufPxJmN0d7r1Rgc7Aohn4Nh4e7Y1F0K2V1xSP5/Z2YFtHqQHGEF9R3wcbYHm2ldJa68WQ5bGzbefyIa26YnWAzuGZP9M5jA6cImvDwyDClhbujs0uDjSX1wZkUKvpljyIgyVbvNrm7DL7l1VjHV6cJGfHS8CO0KDY7eqseWaQlm4/FLbj2WfH+TJK8XCWyx60IFBaMU1rejplVBOX+oO58yNqZB4kgvAe0ea9r2K7hR2YrtmeaKdQB6VCGubJHfN68xMY+tO1kMFhO0OHhOUiBe3HsTq48W4kiO9fEsbOjEytHhmDbQ/x9LZP5AnFHz5s3Diy++iJ07d4LBYKCurg6XLl3CihUr8NZbbz3sNvZar1Hsj3A19UR43lPKYqtMhaoWBS3f0MbJsQgUqqAHHmr5Hp1a4IydV7FzZiKceTZWve9T+vuRUvOmNiHeBycLGsxqiucODcSxPAMXDEHOaFoLTzhmtk5PMIveEVbc2IniJin0AEXitalDiTlfX8euWf3AYjJwuqCRlJltlasoCmCzkwKgUOkwb2ggpEotRW1maWoomqVKLEwJQrSXAL/eqseSYSG0dfvGilz7b9TgnXGRyK/roKTkSqQqLEgJApvJQFqECCv2m6fXEuM6baA/CWQ+nBCD1w7kYW23ys785CCUSWQkaOzr4wi5Soc2ufK+6t0HBtFnqBgUDIvwVKIv7LksuNhzkFfbjnF9PPHpYyEo2vodEi6fQEpZFtg6DUrEsdg0fAGOhw2GhOeMD9KjsernfAwP15kpBS4ZFgJbGwM3AqEwsnhYSPfzLsfKA7l4fUwENDo9GtoVGBPjiV0XKpAsFmJ+chACXO3RodCgo0uNAYEu0Oj0Zs/LvN0GTiXnWzYoqO/A4u+zsXNmP7w4PBQLvjEvRTNWbCxu7ASLeY8vgW7sAANgza5qxftPRFusryfIx005HvbfqLGYWr5kWAhuVLYixscRa48X0XJUAYZsp23nqW0k2jQ/ORhDQ4XoUmnxzZVKDAp2NZMn1uv1OJRdR/5WLHKARKYGi8lAgJAHrg0TZ4qakFkiQZjIgbbNEqkKx/IasGNmIlm2KBY5YEFKEAS2bHx3tdpsQ1Pc2Ik2uZqWU+Fobj2Wp4VhYJAQVS0yBLvxcKaoCfOTg8jrCvkcvD4mAku+zybPScwRdFxnK9LC8PXFClKi+bPfSsh350R+Iw5kGfplynVHnG/tsSLM230dW6YnoI+PABKZGlw2E99ersJrY3hw/pdxRvViqF77v26GLIN25Fa3g8dlQabUoo+vI6K9HM02sPdrdGrEpnMm4TwADCVEdHNHnK8TnOyoXE8SqQotMqUZt+WcpEBIu1SYlxQEew7LjCNILHLApdJm7L9RQ5bP6HW6bq5LKg/hvN3XsXV6Avyc7SHtUmPPlUrafvK4LKvYQqnWWVXiWjIsBF1qHaYP8kOsjxOYDAa6NDpcLW+h8IOeyG+kZOOacj7SKcoJ+RxEewng6WiLJcNCIFcZSure/6UAEqkK387tj3cfj0RdWxduN3TgQJZhXAg+QlOFMkVOHs6u2YLx5Vcws7oYXWwOMgLjsW3sMvwW0h8dtnxsnBwLnk6H27duWRwTImOZWJ8nxPvgzbERsLNh4eOTt3Gl3MAp9vLIMEO5U3fWujFmILLjLPH4aPWwel/q2hU4VdCIR9KjrR5X1aJAepw3wj0ccOGOhORfrG1VYFKCD8I8BCiXyCzyP7FZDMr9r26Vw5XHtdr22w0GpxWhbmia5UzcFz8Xe/i72CPG2xGf/XYHLwwPJUsbiWMe6+MFPk3Gcl2bApJOJew5LKvKw2uOFZLBSZlSC6GDQUSHx2FR+CgBYPPvpZgQb3hetp0vp5T+CfkcM7xkz2VjkxWH4aonovD24Xza79ceK0KyWEhbXphXa51LtrC+874zk4znsZ9z6s1KQV8bHUHh7yS4PulKMInxlEhV2Dkz8R/Lr/lAnFF6vR6rV6/GmjVrIJcbNqVcLhcrVqzA+++//9Ab+X/JevkOHq7VtiqQ/PFZi/X55155FN7dtcB0Vi6R4vlvsy3WLG+YHIule2/Syvw+iPXEifXJpL4Ya8L1YrxI9A90gSuPg4L6TnzwayFtfbyQz8GkBB8MCxchu7oNno5c/JxjIHlemBIEVx6Xtuaf6PO7j0fiuW+zzDa4RC38pjMWeGM8BVj1RBRaZCoU1nfA18WedjHaNCUWaq2e9ruNk2PxZUYpJsT5YFi4O5gMQKPTo7NLjaoWBW43dCCnph3L08R4astlaHV6pEWKMK6vFzb/Xkrep/nJQXC0M2zUTxU04sjiIUj/4qLF52TvgoH48lwZzhY1Ye+CgViw5wal/5umxOG9I/kGwuZn+4HHYeNMUaNVriWCq2r6ID/YsJi0ZNHGvEsebD0E506jfdc36Jd/EbZqJSRRsbg5aCSqho/B/kYG5VrLUkPhYs+Fu4AqMUzYjpmJ+PVWPQ5m1WL9pL6UBZ5o4/I0MTq7NBZ5Blx5HDjas7HyQB7l2sbEnFw2k+S9ivQUYPpAP7jyudh4usRifwn+qNVHzR3JxNgZO6roQAfxuTEPkynHw7QB/hgSKsQGEy4JH2c7tCvU2HejBqcKGpEaKcLYGE/KJuTFEaHIqW5FkBuf1qH19bP9UN/RhZ9v1pGlDKa2eWo8hRNs/aS+cHPg4stzpbhzV4p5SYbSDS6bgXKJHIu+zaLlqZg7NBCZdyTwc7FHvwAXCPkc3O1U4ovfSy3yMkzu54tNZ0oo/AIHsmrg7mCLtCgRYrwdUVDXjktlLRgf743aNgW8uzkkCD4ta9xfHx0vIqWhc2vaLI7Tukl9UNuqwIn8RqvvypaMMkR6CrBuUh8cvllHtvXfyBnVi6H+OuvFUP8Oy65qReldqRknTbAbH3F+zg98XlPOKMAw7z+V6Htvnu8mJA5x50Oj1VMCiQQ3KIMBrNiXg+LGTgqPZB8fR3SpdXBz4ILBALpUWnQqNfjstzuUfhAcQbtn98eX56jzsDGPlSlvjbuDLYaGCsHjsmBnw6Z1cL0xJsIqRls5OhzPfnUNzvY2Zudvk6tx7MWhKL0rxa2advTxcTLjtCTabsz3WFBvzjFp+rcxxxbd+Yj2/Sc9ChklErjxuXDhcbDnciUuljYbfh/pjt/3nkL4xdNIL78Mn/oKaOx5aEoejn1+/bCFFw45x86szz1hzw+ejMYXv5eS7RCL+Hh5ZBgtR+O2GQmoaJYBegZlnAmcsfZYkdm4vjY6AjWtcqvrWLJYiC/PlfXInzU01JARbcwfBhiw6JHFQ1DX3mUVlwUK7TF+8yUSzwr5HLwzLhJsJpM2qLZ+Ul8cyKq5xy1kgr/o7uuiR4LxS04dxsf7YP2p23h3XBS6NFqsO1Fsth8CQBEVMDj9xJCrtPjv2VJaHLhrVj/svV6NERHuUKp1VnnWds3qh+zqVvI5NTZT7Pbp07F44YeblnlXFw3CBKOxM/1+3aS+tOM+ONgVc4cG0vJgbpuRiI9PFGFSoi9SI0TgsJlgAOBaSaQwnscIHqgRESL8VtRImQsIGxkpwtSB/lhrJPZkhqv/wZxRD+SMIkylUuHOnTuQSqWIjIwEn0/PC9Nr92+9QOrh2p8hPAeAO02dGLnxvMWJaeesfpix8yrl8z1z+mNoqJvZ8fdDgE7nPCM29mJ3PuL9nZFf14Fbte3Yf6MG8X7OZovEK6PCEOrOh0anQ3ZVO0n6PSzcnVw8c2vukdoBhg3hwaxazBjkDw9HW6uT8a8vJOF6RasZQFo/qS+0ej1eO3jLKjkn14ZpdfPZE9B6e1wE2uVqsFlMnC+RIMHfCQ3tSjK6GuLGR6tChe3ny6HR6bB0hJh2Af5yWgKUGi04bCbcHbh46yfLRIkfToiBrQ0LMqUGXWotZCot2uQqONrZwI7Dhg2TAZVOh4q7MgwMdoVSrcMHRwstOiHWT+qLLRml+CA9BuXNMtS3KRDt7YjOLg0K6w3RQolUBRutGkPLszGt8jKS8i+Ao5DhtmcwTkY/AvaUyRBEiFHdKjfLXEmLFGFUtAeapSqzsTR2FIW689EiU2H35UoKfwJ5r5ckYWk3VwTduAwNFWJUtAcmfnnvebEGSM8WNWHrjASotTq48gxg/mR3ZgzFufd0HJzsbTDd5N0CgE+fjsV/z96hPM/7b9TgsRgvDAhywaYzdyhkou/+XGDW/wnxPng0zB25te3Yf6Maj4a50zpkjJULRQIuds/uj5yadng72cHNgYtDWTVo6OjCkBChmTPRw5ELHoeNE/kNVh03hGNnQUoQPAS22J5ZDgZgNoaLhwUborgnitEsU2JOUhAGBrkgv64d608WQyJVkWN/MKsWU/r7QqnR0T5/nz8TB38Xe9S2deFmdSvlPf78mTi8+3M+3B1skR7nDU9HLqTd5bB2HCaEfA7aFRqr8+KuWf1ga8PC6cJGxPo5Ibe6zeoYEJunnkh9TefcT5+ORXKo25/KjPpfrrm9GOrhWy+G+udbq0yFc8V3aTd1m6fGo6+vE/R6PFC2eWNHFy6VNptlL92sbsWwCBF8ne1gy2ahtl1BEWH54MloSJUarDlaZLRhDoMLzwblEgMtA5PBQJyfMz45dW/DTaiCma6fGyfHwpXPQZDQHpfKWijz8Afp0cgouYvUSPN18lR+I6YO9INKo6dcx9ips2dOf6g0Olpy463TE9DQ0YWyuzIK+baxeEp6nBcu3JEg3FNAew4iG5VYB326yaFNydeNg0BiEd8i1iLOR6jKHnpuMMZ1k70L+RysHCnGr9t+wsquQtgeOQz/tgbIeALcfTQNX3vE4wfnCAR6u5o5tghjMxnYt3AQKpvpCbqJYNua8THYdaECV8tbsH1mIj6yIn7zyVN9oVBrKdgGMAT5IjwFFOL4pamhKKjvwJ5LlRazrXfN6odt58twsbTZYvDMuK1ikQOmD/RHi0xFcVSmx3lDodJYdXpteiYWS767Sfk+NVKEGYP8oFTraYncR0V5UJR/9y4YiAmbL1lt68bJsXCxt4EeQKtcTTv2384dADaLgclbLpt999WsfrDjsMBhM3GtohU7MsvgyueSynXtCjXmfn39voRvhHwOXPkczNx5zeyYPXP6w5bNRHGjFC48jlWn5ZfT47FwT5bV/cfi77LNnJFrxscgo/gu+vo6UbDgSyNC4eVki+oWBYWsnngXR0SJaBMYZEoNbla3URQIrYrpeAnw7ZwB6OxSI/OOBJXNcjNcfT8JGA9i/zNn1OzZs/Hpp5/CwYFaoyiTybBkyRLs3LnzgRrTa71A6q8wukgZgPuSuaxrU2Du19etqjkYb1iJz7+Ze8/JZSo1bC2DytR5Rmwu82o7zIDF3KGBcLa3wbNGnnjC0TAq2hM2TAZaZCrsuVxptrF9eaSBaHFNN0CI9BTg06djDe1VafD6wTyLfV6UEoyXfryJAYEueGG4Id3byd4GWo0OXRodPjha1GM20BtjIzBj51XazefqJ6OtqtZsfDoWjrY2yK5uRf8AF9S0KczGJdJTQPbFmpOJWOReHxOOLrWOVsHt06dj8cHRQgh5XMxPDoIzzwZsJgN6PbDaCLiuHB0GtVZvcAzIlHh9dAR+vWWeYjsnKRBylQYejnbYYAQ2XxoRiv03avBbXh0GVebisaLzGFV8EU5dUtxx9YV8/ERwp06BIjAEbBYDWVVtBq4mpRYejly0ytRwc+Biz+VK0glmCh7pHEUrRorx/VVzME1koYz7/AK0Or2ZxPGh7Fq8MCwUcpWWdHhZAy7rJvXB6cImPJXog9lfXUdqpAjP9PdFu0JD2Tg892gwDt+sw/BwNzjacVDTqiAdjQFCe3g72UGh1iKrso0sKZidZCBkX320CGNiPPFImBvUWj14HBbZ/j/6nK0eH4NXjEo3Cadkm1yN8mYZAl154LKZYLGAwzfrYWfDoiiYTBvoj5LGTvi78qwqIP76wlC0ypWQKbXYkVmO4sZOi2P4yVN9Ud0ih6eTHYLdePj2ShUGd5f/NcuUeG10BAkILY3viyNCwWEx8PGJYjNg1MfXEcfyGpBd1YpJ3fOIQm2I+hNlDK+NCYeQz8VyK07K9DhvNEuV2JJRhiOLk1B6V2p1DL5+tl+P8wYRsX3rsQjk1XbA09EWAjs2Yryd/nXOqF4M9ddZL4b631tPgbeqZhkWfmO+4UuLFGFMdxYDMTe9Ojoc4R4OEAls7+vata0KPLn5Aqb290OivzNYTAac7DlgsxjoUuvQKlfB0dYGR/PqSSc8UXZMl429ZXoCNpwuhos9x6Jiq7GzhbBITwE+mhgDNpOJho4uw5py1JC18O64KPBt2bSb98+ejoWzPYc2ELNxcizYTAYc7NhgMwGlRo91J+4pyr4yKgwSqQqu9jZolqlp8cyOmYn44VoV5iQFUlT+CBPyOViQHIwwDwdcKpUgxJ2P4/mNeLyvJxxsbdAmV6OqRQa9HhDyuWAyGfB1toMdh2UVaxnP4W+MCYdcrsRv2w4g8vJppFdcg6C5Ea18ZxwNGYCLfZMxbNFkLD9knhltaaxnJwVArdFBJLDFupP0qnmRngKSjqCPjxPSv6DHBmwmAz/MH4iSJin2XKo0y4yyhG8OZtXixeGhaOpUYvPv9zJ+lqeJ4Whrg7p2BV74wXDP6TKcibYyAExK9MGGUyWQyJSYlxSEeH8n2LJZWL4/B9MH+FvNFPrlhSTk1bbTZop//Wx/aHQ60sGaU9NOlkkaZ68RGfutMrXV4PAH6VE4UdDYo7PIUpY74UiK9BTAwc6GQrtCBOed7W16dN4RVQkypcYs28rDkYsLdyRI9HfB9sxyi0FiYk9oac/46dOxaOzoQqCQZ+KMFMPf2Q5pn54ng53xfs5wtGfjq4uVGBHhbvGZWXusCJ8+HWdxL0ooEDZLlVixL4cSdKZru6UEDCGfgwUpwUiNEEFgZ/NQs6P+Z84oFouF+vp6uLu7Uz6XSCTw8PCARvM3qIz9f2q9QOr+7H6yjAgz8zB3p2jH3mc53dmiJjz7lbm3ncggME2XZDMZOL0sBQFCQ+nIH3WGZRTfxYydVykpwdYiE//5tYCSFWHsaHhjTDjUOj1m7TJv/8bJsWAxgZ9z6nG2qAmrnojCN5ersOiRINiwWKRkq7Gtn9QXHDYD1ypaMSjIleLpJ2RlW2SW5UjXHCtEm1yN4y8OxQs/3KSdMNdN6os2uRpFDR1m6aiRngJ8/kwcSu9K0diuhCufg5yaNjMuqM1T46FQa6FQaXuUUd5wupjkRzAFB8tSxfj1Vh2F12fdpD7gsg3aD+8dKSDBrOk9IsDGwaxaDAhyQUqoG+rau6DT6cAySZdm6HXoV1OAteoCOB09DBdZOyqcPPFLxFAciUiG64B4zEsJhh2bhcpmKew4bHx5roziTPBxtkdmyV08Ge+DWzXtKGrogD2HRaYu9wSkTAHe17P7oaJZhr1Xa+DjbGf2bM1PDoJWp0NdmwJR3o6Y/dX1HtPPP5rYB6/sz6WAu+kD/ZHg7ww2kwmuDROvHshFcaMU4+O9MCbaixIdXpoqxoUSCfZcqTSLFu+YmYjSu4bIV08y00DPGXhvjA3H1O33NgSfT4mDox0bbQoNpeRzybAQ+LnYo75dgeuVrWTKPqBHbZsCAwNd8a6laFY3GHPh2UBga4NF32Zh3tDAHlP4GQyQxxDgJzlUaObQEfI5+HBCH/C5bCg1OhTUd8DbyRZLvr9pdu4t0xNgx2bC0Z4DjU6H9SeLSQeUaUTaWint+kl9wWUz8d3VKjz3SAgEdmx0qbRWx+DFEaFgMxlW5w2JVEVxDC9LFaOgvh0TEnz/VKTvf7Hm9mKov856MdTfY3QY7H4DbxUSGYZ/cs4sA9wazvF0sr0vPqkWmQqf/VaCPj6O2H6+HL4udhgdTXVwEc73aB8BTuQ3Yni4O3YbOR2MjciGKJfIKY4J02NMS8eJkp7l+3LIAKCHwBYKjQ4MAG8cshzws7Z5T4sSQa3RITHABdvOl6GPjyMGB7tCqwMpN29t3Yv0FGD9U32g0erNqAnoMOSSYSG4K1XCx8kO604W047n8jQxRAIunvivZaqD9x6PwrsHsrEnUAb+L4cRcuk32La1QC7yQtOIMWhKHYOphWyowbyvMjbjsSZw6XtHCvDa6HCUNEnh63wv05nANcZZtpunxWPTb5YzZBYPC8Hbh/MoTsqe2rV4WAhOFzZifJw3bFhM1Ld3oaihA7k17ZifHAQ3Pgd3pSp8dPw26UBcmiqGLZuJS2Ut2JFZhmA3PmYPCcTc3ddp78fClCDIVRrsvlRlsR1rxkfjUFYdon0EZs6uWzXtmDHIH+fvSBDtLaDNTCfWXAD4fEo8pu64YrVsTabUWMXZq56IwuuH8mi/IzD4rln94MLjmpXMEo4Va847YydaWpQICpXWLNN9+8xEeDnZoUWmgkylQcVdGdYcL6LdE9LtGVeOCsfhm7UYFOxKO0ftmJkIHoeFVb8Woll6LzB4P8/y+TuSHqt0iDadKmgkExOMS46N97Ome0665+jPUsoY29/ujOro6IBer4ezszNKSkrg5navFEmr1eLIkSNYuXIl6urqrJyl16zZvw1I/RGn0MOwP5JlRNvWHgjPaX8nVeJmTRsZgRKLHPDqqDCcLbqLry5VmB1PpHr6ufD+UJmgTKlBVlUrfitoQrSPgIxI9JSiOjRUSBIAG0+SaZEizE4KoI1+Gf82wd8ZTR1KNMuU2HO5EhMTfDA+3hsFdZ1mqe7H8xsgU2os1kZvnBwLexsWPJxscaWsBdszy+DK4+KF4SGwZbOg0GjBZDDg42QLlVaPgroO0olEV3JougnePiMR9lwmntl2FYcWDUJli8IMZJ7Ib0T/AJf7HjtiY9/U2YXpA/0R5+cMFgO4XtmKK+UtlHJG4nfpcQYltGapEgeyavB+ejQtsBHyOZifHIwhwa54udsJQy5Ode2IrS/GuMIMjCnKhKe0GU1O7ih/dAz+49AXtzxCAAYDaZEiSpTsdaPsF2PbOj0BdjYsrDlWREkf93S0xaxd1zAxwcfqWMwY5I/KZhnCPATwcLSFTq+DQqUjObnoFuBtMxKx60I5+Fw2xsR4AoDVDJj9iwZjwmbLgHXdpL7Q6HS4WNqMwRYWfVPHGfE3wZ002yRT0NIGZ/ez/aHS0mfDbZ+RCC8nWzz71TW48riYOzQQDAAsJoOMbAL0i/zS1FDUt3Whtk0BPxd7ZFW1YlS0hwVuikS8djCXdKDuuVyJsTGeVoHd7tn9oQfMMgtNs+DoPu8JGKXHeePDbmJ+03fPeNwJ7i8bNtMsJV3I50DkaAsGGGiVq3Akpw5ylRZDQ4W0Y/D1s/2hUGtwIKvWDGwuSAnC0dx6VLcqzIAnYJhvUsT/njK9Xgz119u/DUP928waBjMVXyHMNPBmiouEfA7eT4+GUq2zGIQaGirEkBAhYrwdyffdEv4kAojW5v/NU+Ox4XQxFqYEI1DIMyvHIozYMEd6CSjHmBJth7jzsdzoOnROky3T4lHUKMXQECEmbbF8PWub9y3TE6DT68m5lK6PltYC4hzrJvXF7YYOSum0tbHaMTMRrx4wfG5tPAnuJ2OzVXdhalsRnq6+joDLZ2DT2YFaoTeOhAxC0aARSHpmNC6UNuOZ/n54p7uk/n7av2JfDgWX1rYqkBYlQpdaa3WNez89Cm/9lA899FiWGoZ5FrLHPjxehOJGKZ57JAj9A13x0fHbmDbQz2o2NeFYsZRlt2NmIgKE9pB1aWDDYkKt00Or1UOm0sDJzgZgMKDR6fD6wTw0dXZZzZC2YTFog0rbZyRif1YNRkS4Y+2xIjNOyA8n9IGHwBaP//cChoW79+jgObBoUI/VBQAeODNqxkA/cGxY2H6+nHZPZ8qdtHFyLKpa5BbL0Ex5tojP6crTetoTGn/PgIEo3JqT98vp8eBzbSBVqslSv56e5fcej8I7P+ffd/lci0wFpUYLvR7QA7RtN3amGTvGTO1+qoPuxx7GmvuHXGJOTk5gMBhgMBgQi8Vm3zMYDLz33nsP1JBe+3fZn3EK/RmjU5qbtv3Kfb1UD+osc+FzMSxchHAPATkx8WxYaFeo8dUl8+MXpATBoVtJgk5qmDBTZYXs6jZM32HIxBDyOfjkqVjc7lYO60mVzVSGmFA9KW2yLjf64vBQbDxdgvQ4b4S48/HxxD74+EQx/FzssfG3EjwZ642pA/woChaLUoKwzoKs8NaMMixKCcaTX1xEmMgBq5+MgUjARW2rAmqdDpt+u0MbWXtnXCRYTCaeM8oWIlQL103qA5lSgwnxPth7vRpjYzwhFvHRYlKjThz/yVN9Ab0etxs7rS7oy1LFOJpXjwQ/Z/i62JHKJMbKfg51bPi52JuNG59rkEcNdHVGqIgPpVpHO84SqQofHS/C9/MG4nZjJ4Q8G6Qq6+H0w2ZsKTwP3/ZG3OU54ZfwofglfChyfSNwaPFQaPfngt0dOZuU6EsCpoUpQRSZZWPbeLoEQ0OF5EJJKNptnByLDU/FQqvXU9SBTPsU6SXA7kuVpNrb/OQgKFQaRHgJ8OlpepnfDaeKScCd1YOqnVjkgPo2RQ+KIx3YklGGH+YPwKoj9CqYhLQwAfKJv5kMmD2XhMy0qQLS3KGBYLGAzCIJraJcZokEKWFu+GRSX+TXd8KGxYCXkx3e+umeyoqpspDxmG+bkYhvrlRiWLg7Cus7odPrsXlqPIXPakFKECSdXSSY2nTmDt4eF4Hfb9+1OkYsJgO5NebKLYSEuenvjD83VkYyteLGTvA4LIrUsbEynvG4Fzd2QqcHCXanDvBDTasc4R4OcOVzzdaG2UkBKLsrNRuDOUmBqGtXkBkHhMrR1AF+uCtVokOhwaujw3G6sMmMYB8wzDfJYnN+vn+q9WKoXvu3myUMdmRx0n0rF7vwOHhtTDim77hKOvQ3GRGAE5nKxIaYwDlrjxUhPc4b/QKczfidXh8bgVB3PpRqLT4+cRsAMGOQP1planyQHm3GcbnpzB2seiIax281wJnHsTrnVrXIodXryWPoghB9fJyQGiki22ysDgsYAhcKtQ4n8hrQpdJYvR4hV0/3nZeTLZb/aFhzCCeeqTqYpbWAOAfBS2mMjUwxpLGtP1mMCfE+YDBg8Rhi/bpY2gy+Uo5HS69hVPFFPFp2HfZqJZThkaiZNg+LugJQ5BYAMBgAgJ/238LmqfHoUuswPzkIL+292WP7OWwm3ns8CsHuPLx9OB/FjVKwmQz858lo6PV6RHk5UpReCZuXHIht58ux+sloNHYowdDrsW1GIkXAZHmaGD5OdliaahBvifIUQKZSIz3OG/4u9j0+JxMTfLDdAs5af7IYi1KCwWAADnZsfHjsNiXjycPRFiwmA7cbOzFvaKBVRcRFKcEkdmmWKTE3KQj9g1xQUNeB6xUtsOew8PkzcWhoV+J2g4Fn9qOJfeBqz0Fut/JbdlUror0MGesqjRZ66LH+ZAmulrcg0lOAZalinClsolWsBoDlaeIeqQXmDg2EDYtB24/nHjGMxfPfUVV5p22/QnLvxvk64cjiISi9K8Pthg6USWT44Wq11Xtg9rmHA+xsWLRtgJV0HNM948AgV6w9XkR7bHFjJ3Q6w28UKi0kMoPyd4Brz8+M1fb10CY6M1acJxxjdHY/ivJ/lzH/yMFnz57Fb7/9Br1ej/379+PMmTPkf5mZmaiqqsIbb7zxV7W11/5BRgCSgvoOcvMybfsV3Kxu+8uu2SJTWQU7LTIV7XcPeq3aVgXlnF5Odgh248PLyQ5sNhMeAlt89nQsIj0FYDMZiPQU4L/PxMPPxZ6M3BESnXRmPAERfRPyOViYEoSlI8SQdQMWYmGmPUf3ZGa6ySSARU+/dbRno1mmBI/DwvPfZaNZpkJTZxeqWuQQ8rjYklGGN37Kw5aMMhLERXs7Wt3QejnbwtneBgX1HZjz9XU0diih0wPzdt9AU2cXUiNFeGnvTcqzk1/Xgc/PWJZbXZYqBqBHsBsPx/MbsGZ8DDq7NFiYEgQhnzqRbj9fjgAhDytHhWPpCDGYDEMGivF9Wj+pL/Zer0ZqhAhanR6joz2xYl8upU0r9uVidIwnJFKqxC0BFl3sOWAwGFixLxdFDR0IEzmQ9++D9GiybWKRA5hFBdhRdgRnty9CwpPD8UzuSZwPiMOUp1djwHNf470RC3DDJxKhHo6QKjWYkxSAnbP64bXR4dhw6p6DpSdngqnjDDBs2DPvSOBkb2P1Wfg1t57S/5f23oQrn4vOLs19XVMiVeGtw3mYnxxEe+xzjwSjqkWO99OjaO/b3KGBOJBVAwAGAHWf/ST+DvMQ0P7mVEEj1hwrxDvjInHgucGYPsgPq48WoratC3uuVGLtsSIMDRXivcejMDRUiDXHCvHNlUq0K9RgMhngcVjIr+uAnQ2L9h2jsw2nirF0hBih7nysGCnGoew6vHU4j3IdFoOB9Ub3trixE+1yDfr6OFkcw2WpYjz/XRa2ZJRidlIA5bv9N2rMPiM+f3VUOBamBMHXxR4rR4WbjT1AD+QIB5TxOBsfS8ikv/FTHs6VSMC3taFdG1bsy4Urn4sNp4sxfZAf9i4YiJdHhuFAVg10Oj05rsbn23i6BO8dyYdOr8eHx4vMHFFEm+5HKvmfYr0Yqtf+zWYNg5VKpPcdeAOAeD9n/LhgIMbE0K+9I6NE5DxFzDfNMiX6+Aig0+tx4Y4hm9kYf14pa4ZUaViv0iINAcRD2bV4++d8ZBRLsHJ0OFIjRYY2NXaitEmKxABn2LIYWJoaStv2OUmBuCvtgrO9DeYnB1GCEMZtXvRtFkZGiTA42BXrJ/WlSK+LRXzMTgqATKlBsliI34qaaOdqwLDB93c1X8cB4OWRYaiQyMn+rRwdTpk/CbO0FhD9ITJKTuQ3YvPUeER6CuDn0jO2sIY/msprwfvuW1y8uAHZm6Zi05GPESpvRv3i5Xjzw/04t/83vBE3EUXugaQjirBNZ+5AyOfi6K16rJvUB7k17Vbb//bhPLzxUx5WHSnEo2GGUmexyAEn8gwZUmeKDEqAxpjv06dj0aXS4nheA9K/uAidXo/8+g4o1RqseiIKB58bjI8mxqCyWYZWhQpKtQ7ld6X44Ggh2hUaXK9owYt7b1ps14KUIBzIqukRo3k52+LdI/m426mkPL8v/HATVS1y8DlshIkcejxPsDsPsT5O2DQlFmvH98Gh7FqM/+Ii9lyqxDvjojCujydWHSnE8n05OFcswfzkIBzJqUOpRIZdF8rx8kgx6fR94r8X8OZP+ahsVmBcH0/sXTAQb4+LwMqDufjv76U4kW8+nusn9cXvt5vw7JAA8lkyG/PJsTiW14AblW3YM7u/2e+VGh3+e7aUto9rjhahsUOB7Oo2vHrgFtkPbyc7PPdoMO1vlqWKSQxpbG+MiaA4XGRKDZlxlfzxWUzbfgWZdySQKa2Xx7sLOFYxtMDOkIRgw2Lg9dERyCiWYGk3zxOdEe+iafselrnwOGAxmH9oXv5f2R9yRqWkpOCRRx5BeXk50tPTkZKSQv43aNAgeHl5/VXt7LV/kP2dTiFj+yNZRg9q9ztJZVe3YXtmOVhMBtLjvLHqiSikx3lDYMuGv9FG2YXHwetjI2ivRUxALTIVWmUqzBjkj/cej0JGsQRv/5yPPZcqsTxNjP03arDoEfrJ9+WRYYj1dYJcpaVMksRCtv9GDZYMC6H97ZykQHz22x3MSQoiN6E7MysMpXYcFuYODTT7TVqkCF5OthYn5P6BLujo0uCTp2JJh8P6k8WoblUAsLyBN114jZ06KWIh7nYq8cqBW+hS6zAh3htv/ZSP5ftykFvTjs+ficOX0xLI6xU3doLNYuLs7Sa8/XM+mqVq7LpQjrQoEb6Z0x8fToiBh6Mtor0EOJxTh8EhrhazjbZmlJkFTuYkBcLL0Rbeznb4pNuZsP9GDbm4E/ev5MJNfFV3Cge+XIiEMUMx5NdvcUIQiCUzPsCpM9l4fdRiXPLvAx2TRTn34u+yoAew7MebyK1pp4zL/TgmTY0Akh8dv40VaebZGIABSJ293WTmSNt4ugQu9tYXYONrSqQqHLtVj6+e7UcBHl/N6gcwgMM36/DUlsvIKJbgzbGRGBkpIoGis70NksVuWJgSBFce576dJsTf/t0RKDpz5XHRLFPh3O0m7LlUBYlUhbK7UoSJHCgOEMLpKhY5wNPRFu//UkhuZBRq+neMzoobO6HU6PDKgVuoaVVgx8xEuDvYYkdmOb69UoV+AS4olUgpDhaxyAE8rkHGO9rLAbtmUcdw16x+yCyRQCJV0YI/dwdbuPI42DQlzsxBrlBrkFEswbNfXcOh7FrKpowwAhiZ9sPUAWXp2DfGRIABWFwbdmZWYEyMJ2xYTEzYfAkv78/B+HjvHp9pmVJj9XutTkf73T/RejFUr/2bzRoGu13fcV+BN8J4XDZC3B0srr3GjvA5SYGQdJebrDpSSK4hpvPYl+fKwGEzMSDQBWlRIszfc8Oik4uYz774vRQ8rg1+vF5DOmaMN8wXSiUYHCzEku9voqpFhm0zEi0GIYjA2anCRgS78fBBejTWjo/GslQxVh25t5bMTw5Cs1SFbTMSzK73w7VqcFgMfPJUX7PvmEwgt6aN7N+KfblgMhlm426cEWx8jg2T+0Kt1WLpCDEWpgQhu6oVcpXBQUZk/dDev+6xMp2r3aStmJp9FHt+eBNXNk1D9NtL0VjViHPPLsNPBzPx+ze/InPiPHzTYouNpw08XnRW3NiJFpkSNa0KrD1WhBhvRwhsbWjvh7GTz+CU4ZPPyIGsGnx5rgzuDraUIFNalAhVzTKEuBsykMbHe0Gp0eFEfiNe3JuDtw/no7GjCxdLm+HrYk9x4oyP98aP12tIGgI6p8uW6QkQ2LIhkap6XM9uVLZh+kBDxp4xTiaenzaFCu+OiyQzaiyd5+ecOrz9cz4qmuV49qtrlOd8yffZaJWrMSpahFWPRyFZLMSKfTkYFi7C/hs1GBvjCalSa+ZQXfZjDlz5XLCZDHz22x1ynE8VNJLjuW5SX6yb1AdbMkqx57KBt2rbjATUtirw8YnbSI/zxs+Lh+CDJ6Og1OoQ7MbDmBgPDBW74Zu5A/DT80PIoJ+Ho61VDNUmV5sFtuZ8fR08Dov2/ahrV+CjCX0Q6dX9uZcA384dgFhfJ8q5HzSZQiSww2tjwmm/e93IoVTcJCUD7k0dSvza7WQ1be+t2nZ8+nScWfsept1vQsT/2h6onurMmTPg8/mYNGkS5fN9+/ZBLpdj5syZD6VxvfbPtL/DKURnxEtFm+74EF6qVpkKubXtmGmkYkJXBtgiU+GLs3cwpb8fJb2UsN2z+1NKR+J8nfDt3AFmBOoRng7IvCMxK2fxdrZDQX0HLpY2QyTgYsNTsWAyQVtOxOOwYM9hIsiNhyA3HkkAbJzmzGIyaH97PL8BV8tbsDxNjAV7DPwDxY2dqGqR43heI94eF45Dzw1GZbNBdaO8WY5JCT549cAtrBwVjtkmZMMEt9HHx29T0u1P5TeSZW2WNvDG7bWUAv94X09EewtIrgTiuFVHCinXy6vpwOWyFkzp74s5SYHwc7GHn6s9PARcVDbL8eUv945fniZGTavC6oI4PzkIbCYDYpEDFj0SDD6Xhe+uGsoFjX8nVWrxyY7TGFuYiTVF59G3oQQKGy7aU0fj6KRF2C0IR47EkGXVdbvF4j0xLokyTVfff8OcG4ywBSlBeP+XArPPCSB5tbwFr40Ox86ZiRS1maWpYhTWGwg2jcecuHdVLXLMHRpIy4FgWopguJcKeDpy8fa4CHSpdXCwZaGpU4XFJqnYL+29iR0zE5FX2473fylAvJ8zyY21rbtU0LRcg+6aC1KCwGUz8c3lSjLNn66dbx828AgQ42dtLIkMJAKMFdR3YMGeG1gzPoZ8/u6nFMLZ3gb2HBZePZBLlp9Vtcix8mAuVo42ONsIAvy3x0WiqkWOFpkKb/9cgCfjvPHJU32g1wMNHUrIlWrsuVJJXuNUQSNZ1jZtoB8ChDy88H02XHgcrBkfg6L6TkikSrTKVVj4jXn568bJscitaYMrj4sFKUH4JbfeLPuIzgH1+TNx4HFYcHewRZtcTSHQ7FCokSIWYuoAP7OymOLGTrw2OhxrjhnS3IkN0+N9PRHuIbB43+rbuyyWCcxJCoT+3+OLIq0XQ/Xav9GsYbCcmnasHB2OGTQqcK+NDqeN/FvFkt1r7ydP9cX5krsYEiKkzBFNnV240yTFwpQg9A9whlylhZsDF4Ahu8i4pNrYiLVVLHIgBVXkKi1OFTSislmGD9JjSBy05lghGUAT8jmI8TY4U6y1mckAJiX4YEdmOXgcFsI9HSm8RMT8+8P8AfjstzsYGio0o0KobVVgZJQIQ0OFmJ8cBA6bibcP52FSgg9yatrxwvAQsoxdrtTQzo+nChrxRF8vvD0uAmV3ZUj0d0FVqxzbMsopa7xKq0dGsaTH9XDlQcPnq2L5uP7zYYwqvoDEmkLoGAxc8uuD3FdWYaUuCLcZ3RvfK23YPDUIGp0OqZEinC1qspghIhY54HplKxamBOGFH26SJfhCPgdfTk9ATYsChfUdZqXaYpED3PhcipOqTa7G1AF+ZJCJwIkHs2ohV2kR4+0ILycR5u2+QVnfXzt4Cx9N7EPhnDQuV//xejVZpm5cTh7szsfbh/Pg78ojFfVeGhGK+XvM+RHnJAXiUpkEaZEe2Hi6hHIfTuQ3gsUAOro0PfKDEhhoYoIP1p+kp8zYfr4c6XHeePvnfPIaNypaMSDIBYOCXPHuz+ZYEQBJ2zE+3hs8LpvEXsR4spkMfPp0LOYnB+FEfiM2nCqBWMTHa6Mj4OtiB0CPonopvjASeRkSIoRMqYELjwMum4lksRvO35FAYMu2iqE0Wvoauo9PFGNklAgpYiE2PRNn4HRiAFy2gT8p1s/ZIhdUT8kUPZWtxfs5G/ZzvxaSGPqNsRGkQ4nu/ARWm58cjNRId3DZhvY+Gu7+l5fIEQkRdFx+f1VG1oPYAzmj1qxZgy1btph97u7ujvnz5/cCqf/P7WE4hR6E+PzPvlSWrknwXxXWdeBQdi3tb40nKWmXGs8/GoKCug5yM2lsRGRHD5DXI+p3FWot7G1Y0AOoa1Mgs+QuJVV37bEifP5MHB7r4wkOmwlXHgd8Lhsr9uWiqbOLsqFdc6wQ7g62mDHIH2EeTAj5XBx+fjA+PH4b54rv4qXhYiz45gayqlqRW9NOC3oiPQUobuw0Sid3QFOnEuGefEiVOqw6kkcuKMtSxWiWKrF0hBgZxVSuHQO3kQ+FoNh409vZZcgsIzbwGp0OS1PFEPK4kMiU2HWhHPOTg/CfXwtoeXgWfZtFEmQClvl61h4rwrYZiWhXqOHuYHA+vfjDTdqFnYiy/DB/oNUF0dHOBvsWDoJGq4edjSHlNbuqFSFuPISJHHC3pBIfS28jfNpKXMzLgsaGg4zQ/ni+/3gEzZqE36rkmDrAD3k/3wPHpo4EPxd7vLT3JmXjPnWAH6n0R/TTOCPGlOjZU2BLW8pEABexyAHtcjUChTykx3mDx2GhqkWOimYp/Fx4tPxbGyfHQqvTQyTgmvEuLU8T44dr1WbXXJAShIZ2JX66WQt3B1ukRribcVoQtv5kMdKiDJHttCiRxeeHcJosSxMjs1iCNrkakZ4CvDIqDPVtCrz/SzEkUhXsOSwcWDQI1S0KUrZ4TlIgpZ3G43eKhk/qpRGhZAaSsUmkKlwoaSZ5jw5l11okhjQGizszK0ggZ2w7MyswKcEHCrUOQ0OFWHWkgHzXnnskGB6Otlj2Yy5uN3ZiQKCLgZ9hZiIulzWTTh7ivARZrkSqwsQEH5JwdGFKED6jGXshn4O7nUrsnt0fdW1dUGm1JOg0JuYNdufjq4sV2Do9Aa48w2bs3e7neFKCDzY9Ewdnew5ceBzIlBqUNElxrlhCapG8ZwABAABJREFUy/0iFjmAY0NNGSfeg+WpYmybkYANp0ooz/QvufUYH++NvJoOWuftrZp2JAQ40T5b/2TrxVC99r+2+8VgpsdZwmDPPxqCWJPAW//ueYvDYqK4oRPeznYkp2iLTAWtTmd17Q0Q2uN6RQsiPR0p2UjGAatyicyMg/KDJ6OtOozWjI9GQX0nlo4QQ67SgsnQk22SKtXg2jBxvsSwzoR7CLDtfDleHB6CdoWGVBi11Ga1Vo+916oxPt4brTI1pcze2BralbhS3mJG+E20ceoAP7zxUx7YTAZWj4/BxAQfRHs7YkSkCK0yFdm/kiYpulQ62vnxekUr2ZcgNx7mfm3uaNk0JRbL08SY8/V1WmyxPE0Mr7s12N10BuyffoK4uggjbTi4EZqA18a+iIrBwzH9sXhoOCy4ni/HIh9HhHkI4O9qj4NZNdhzuYrk/fRw5NKOBbFerkgTk+sxwYPkwGWDy2aarZ+AwUnmYm+Dl/fnUDAsEUAhcOLJ/EaMj/fGzswKkhPTNNA1McHHIhfqzswKpIiFSI3ywPkSCYobO3G+RIIVI8U4fqsBZXdlYDOZEDnYYlxfT7h1E22b8lQyoMfIKE9a5+QnT/WFnQ2LgoGIjBpLQcsH4YAMdOXBicfp8XemnJGEiUUO6OhS47WDeeT3xY1ScNhMhLgbAuyLv6cGHqfvuEoG9I35jNrlKquBps4utcU2Th3gh2+vVmFecrDZ/GVtPvuzyRRKjQ5BQh62z0ykJRC3dH6CP3ZsH0949UBU/rCFwSwlRPyVGVl/1B7IGVVVVYXAQPMSHn9/f1RVVf3pRvXaP9v+jFPozxKfP8hL1dM1iZTND9KtAJiGTshUGhTUd1DPMyYCKo0WWh3ITAA/Fzvk1rThQ6MMIeJ6XDbTrC3EosiAYUN+PM8g3Zld1YZobwF8nAwLjlanN1uQ2+Rq9PVxxO1GKbn5nj0kEAJbNo7easC6SX1wurAJLwwPQWmTDNWtVAWKuUMDsfpoIbkBTYvyAJsBSKSOlMyngvoOHMurx5gYTzL7SiziY+kIMYR8LpzsbfCikcqYsW3NKMOaJ6MBGDJ7Nk+NR5tCjQ2n7kWGlqaGwsfJHjtmJuK1g+YqMoCBVyBZLMTF0mbacj8CoL5x6J4Djcg0SxYLLZYDfPZbCZYMC8Gib81J/uYkBeKX3DoMCnalZA29O0gEm8M/Yv7VU3C8ehFgsXBd3A8fjVuOyiEjMGVEFFT5jfDwFOL2tXzaLBo6RwJhxpw8J/IbsX1GIj7pJtmsbVVA5GCLBSlB0OsBTndW0OzBAdg1KxEfG6k+GgOXtx6LRG27Aq0KFVx4NiQA+GRSX6tlimvHx+Dx/16AkM+hOEO5bCbGxniitlVBud4vufU4VdBIqq8NCRFaBT6rn4wGAyCjz4QjhHiftmaUYf2kvjhfIsFHx4vwaJg79i4YiBaZClszykgwvyw1FBGeArz1Uz55n14eKYZSrcPIKBFkSg36dgNlHxc7fDghBiqtDpklErz3eCRsWEwoNTro9HpKBpKxfXOlEjE+hvvl52IPPodlRoC6LFWM/Pr2+wKLH6RHo6Gji3ynAMO7tvj7bKyb1AdNnV0YHu6OtCgRpV/vPxENFpOBrKpW7L9RQ8kWM74m3fWNN3Jru5XzFj0SjF2zEnGuWELKBhs7oc+X3IVY5ECZf86VSChAMLu6jZIVYUqCvnJ0OC0BrESqwmuH8jA42JUEeFqtDhO3XEJThxKjokSI9hFQyNIJh/proyPA0NOTo/6TrRdD9dr/ymRKDcruylB69x5meO7REDMMRoebXh0djlB3Hn5cMBDvHimglUWP9BRg41OxUGm1aOpUkvPWgEAXvDwyDI52NpAptfjv73cQ4SnAf9KjkXnnLvR6QMjnkvP+nKRAfHT8NuYnB8HJzgYtMiWmDvBDs0wJH2d7LPsxB0I+B7OTAswCKSfyGyw6jKYN9Ed9exf2XKok+xUgtEdqpAjBbjx8fKKYEvjjspkIEzkgwc8ZHxwtsiqK8vLIMOy6WEEGyj5IjyaJjI3XNIlUha7usu+eiJjFIgf4udjhqwsVZMbwB0/eEwohMposzY9rjhXio4l9aIMSALD59zIsSw0lnR4fn7iNOUMCMaSrHowDB+H/xXHwiguhsbVD1YAUXJi3CNWDhiEizBvTGAxcKmvBuz/nI1ksxPSB/th05g7p8FkyLAQNHUrszKzA++lROFPYZJaZbYxRbG3YWH2sEMuGh8KFz8XG0yVYe7wIC5IDsWNmItab/G5vd7aS6T1gMRg4XyJBiliIg1m1GB/vbRa4NHW29LRWz08OQrtchfVP9cHdThWyqlrx5blSPDs4EGP7eMLJzgbrTxfjeF4DhHwO3hkXSQaAmUwDj1BDuwrbzlfQXoPIZDI244yaFLHQwJdqlB3WU3Y2HQfkpimGANL9/M5ULAYwYGIOmwEhn4OdmRWYnxyMKC8BYn2d/lDWEfF/a4EmqQUOJ6KND5LZ86DJFMbzoUSmxLykIAwKdgXbgXr9P5Os8VcJgxk7AB9EUf7vsAfqnbu7O3JzcxEQEED5PCcnB66urg+jXb32D7cH9bT+GTU84MFeKmvXjPAUkJOntYm9f6ALyu/KzDZby37MwcbJsVh9rBBCHpdUhZu565rZ9X5cMBAqrd6sLURUxIbFwHtHCkhgQfx/16x+VheO83eaKXLse69XY2SUCL/cqkOHUoUn+nrRlrINFQtxvliCRH9njOqOLG47X46Vo8LNMsSEfA4mJfqQqeGkAs4ZgwLO+kl9yYXc1KFwKLsWEpkKGyfH4nh+A9oVGrMMmHm7b2D7jERSSYTOCEAA0HNM0WVKEYCDAVhUkrta3oJZgwNoF8Sb1a2YlOiD0iYZUr25ePTKUYw/mYnAm5fA0OvRlZSCwvfW4RmJF9rtutPTW7Wo7M5w0+qAlaPCse9GNeYnB2HFvlyz8Yn2csS7R6glBQtSgrD6aCEGB7ti/tAgONrbdJNrynGrth2bz5VifLw3XHkcvLw/F289FomVh27hrcciMX2QH8lN8NGJIrjyDGnsR3PrMW2gP9YcK4K3sx2ZUu4vtA7CWuQG4GOa3XO+RILlaWKkx3nDyd4GDlw25CoNgt14yO4GKu8/EQ0bFsPq86vU6DAiUoSC+g5S0dC0VLCyWU5eu7hRivMlhsy8K+Ut3efhI8JTYPZcPfvVdWyfkYiyu1LMHBSAT38rIYHy8jQxzhdL8NWlCijUWoR7CLB8Xw7mDQ202t7iRim2ZJSRUtimmwDjEryewGJDRxc2WSHunzbQHz7OdrSZggTR65rxMSio76AFqKbXt/SeLPk+Gxsnx2JoqNDMMTZ3t2EMOxXUTDFjIGgNhO7MrMCuWf0Q5MYHj8u2mllBRAxbZCoIeVw0dSjJyP/K0eGU9/O10RG4VdOOQcH/PszRi6F67X9hMqUGV8tb8PGJ25SAzdcXK8AYHEDBYHS4aebOq9g4ORaeTrbYNasfNDo9icEIvs3VvxZCBz2Wp4aRGSB0gaKlqaG4UNKMLRmlZplNxJx2sbQZF0ubsWNmInJq2rG1G58QamWWOCj336jBm2MjzbJWhXwOhoQIzTJT5u2+gU1T4qDSaLHtfDkl8EcE3bR6kEFBugyiV0cZHG2BrvZkm+xsmHh9dASlb+8/EY2LpRI42tlYzAohgoSAIftn8XfZlJKyebuvY+34Ppi7+zoZsLI0P742OgIsJoNcK02tuLETUqUWa48WYrFDG/oVnYXnf4/Cpa4KKh4fV6OHgPnxUsyud0GXjS0gA3C6EjhdiZ8XD8GHx4vgbG+DwcFCSkDPeJ36+MRttMnVCBU5oK5dgQ/So1FQ30HJ0gcAf1d7hLjxwWYzKWVuOj2wI7PcYknjp5NjUVBvGF8PARclTZ1YMiwEno626OvrhC61DgtTgihl4wDV2dLTWu3vao/82g58fKKYpJN4KtGXxMDEu6TV6XGqoBE/59RjZHd54Ph4byz5/qb1gHfjPZVmYyMyatwd+sLfhYc4P2cym+tMUROWjhBbDKSaUigUN3aCybSeUGD8O1OaCsJxWNuqwIR4QylqWqQIAUIeAKBNboXygibryIXHwfBIdyzde9PMkbpxchxs2PSBpgUpQfB0tEWUFz0HmTWz1vd3x0UCAGpbFWZZScR8mBYpInEqEcwzdhj9mWSNP7s/7sn+aQ4oY/tDBOaETZkyBS+88ALOnj0LrVYLrVaLM2fO4MUXX8TTTz/9sNvYa/9AM3YKnXvlUXwz514KJmGminQPSnxOp2znwuPA28nuvkrzrF2zQ6EmJ09rCiSvjY7A2mPmkp5Eucu6iX2RLBaiXCKzqAqXU9NusS3bz5ejvl1JgquJCT7Iq+3Aym6OFWvKIlszSs0IOg9m1WL6QH8SIJiSeA4VC+HtxEWwOx/j430o6nb2HBbFsbQwJQifTo4lFc7o1GQINTlC4YUg8c4oluC10RHgcVmobJZhWaqYJP02tU9OFcOhu4aczsQiBzLN25Qk0pqy2c7MCthzrJ/3RmUrhaBx8bAQXCyVYKinHc69uwnuM57G4qeTsOKHD8FWKPDu8PmY+t5BFO05gJcF/e45ogByDFYdKcSMnVdxKLsW85ODUNumwK5ZiXhzbCRlfOw4LDwW40USG26aEgcvRzt8MTUe0wf6452f8zH60/N4Zf8tKNRalN6V4WJpM1bsy4VCrcOGybFkuWhhfQf2XKrCgj030CxV4oVhoSRZZHWrAgyGAVAThJTTB/ojq7LN6tjY2jBpicSLGzshsLXBjcoWMBmGzLVXDtwiiWV9ne2g1OjAZTMtckUsSAnCkh+ykV3Z9ocUDYsbO9EsVZHtXpoqxoZTJfT3/0I5+ge6YsE3VDLbOV9fRx9fRyxLDUWYhwPCPPgYEOhyX0pEAMxK8IwJ0AmQ29O5OpXWlQoT/JytPtcx3o6Yt/sGxO6GDKaNk2ORGinCKyPDAJjPadbek60ZZSi9K6P97pNTxfB2sYdIwEWkpzkpaE/cLy58Lrk2EIEMaySjxsIP+2/UkJlRpqqHKWFuPaa8/xOtF0P12t9tMqUGl8uazciOCczw37N3SIxV16awiFW2ZpThUmkz7jRJKRjMmBT4xeGhZHmaJfW5ebtvoI+vIx7r42mmrjtv9w14O9mR6876k8WI8XY0wyeWslkIIY2t06kE4dtnJlosm9v8eylEDrYUVdxt0xOwdIQYV8paYGfDJNcbY0Ln9x43iNc42tngrlSJAUGuuN3YiQnx3nC055j1bdG3WXg03B17LlfSK5A9HYsoTwE+nxKPI4uHmJVJEdal1mLnTINK8NmiJhzMqsWqJ6LwywtJ+GhiDAA9uDZMrDlWiEulzbRrPFOnxZPSMgz5/H0c/ngaZi2dDM/93+GkMByzJr6Lgpt3cOGdDfiPTbjBEWViV8oMJYs94a+14/vA18UOoe48hHsIcPhmHaUUkiB0Pl3QiOVpYrNz+Trb40p5C626c3FjJ+rau7qDnkp8d7UaCo0OEqkSLXIVPvvtDpbvy6ElvDcW6Nh/owbLLQi8LE8T48Kdu4j3d7KIgU0J8o0xFtGfnsjNpUr6EjGCg/KlvTfJ86dFijA/OQhXylponyFjonfj8zjaGd4pch22QhAvFjmAw2ZS1txTBY3kuBmCiVpS4InBgNX+0bmW4v2c8enTcThfIsE7P+fjfIkEnz4dhzg/J0R7OVKxgqcAu2f3x8AgV/QPdH3gbCE6DHLoucFQanS04lXGaud0992U/Px+MI6p/a+Ewf4p9kB38v3330dFRQWGDx8ONttwCp1OhxkzZmD16tUPtYG99s82OmeQpVRDP2e7P+Q1fxgpiz3VBzOZIKMhlvh43hgbAUc7ttVyl3tlQWFwd+BSyvaIiZ3HYVndsEV5CSCwtQEDQLinAGqtjoya8bhsWp4gOtLhnZkVeGNMOAR2NiRZsKmtP1mM1U9GI9jNHv/5lXoMsWD6ONuR/fNzsUd1i+HzZLHQDCzsv1GDd8ZFQqnRmWVdvLT3JnbOTIQrj4t2udrqGNiwGFZryM8XS7BtRiJ2XSinkGr3lGLtLuBaLMUjopCEU2HrxAgwfj2OlzOPw/G3k0jTKJHtGYa1KTPxa1gSVswZhqPHDFLzBXUd952htXlqPNoVGlreqp0zExHjI0BxoxQMAG//nIdlqWFmkUbT1PLPz9xBWpQI/QKcsXNWIrafLyfHz7Sk87XREciqaqU87y0yFbZlluG9cVEWo2uf/XbHLFUbuMcdMDra0yLfVGWzDP/5tQCbpybgk6f6Yvv5crOSvqYOJZplSnx3lb48aWtGGckrZXzt/O5MqrXHiqze/0FBLihplOKD9Gizd5JIjV+xL5fMlvrhWjXtPPD8o8Hg27JJ4m6CS8TUhHyOgV8i0gNMBlB+V0YpszROQx/Tx8NqNJZwHtIZwZuQ1g2u7WxYkKs0yKpsQ7iHA36cPxDv/lKAU/mN2DI9AZ+eLulRvpsuMkt8V9fWhT2zB8DRng2RgOoA+iOp6feb3WqcfXsqvxFvjo2kcHB8PLEv+lpQZ/qnWy+G6rW/28ruyiySHROcOAQVgaRTaXWeeD89Ckdu1iNQyIOXk53ZRkrI45K/t+aooCtNMm4Tse4Qcx1AzfxslimxclQ47Dkss7m9utVAek1k09S0ysFhWZE5b+yEg70N3n4sAnelSrTK1XDpdir8cqsOF8skeGNMBC6VNZuV3G2eGo+rFS3oUmsxJsYT388bCEdbNt6jERQBgHUnipEsFuLLc1Qy7KoWOVYfNZTXLd+XQ5ZQp0aKyGwYAnd+8XspJN28Sgn+TnC2t0FnlwbniyU4lF1LmYuNycnZWg0GVt3C6OILSCu5DDdZG9qd3dA5egxWusXhED8IwZ5OWDFSDHu+HcI8BNhqIat8e2YZ3n8iGnd7eF7aFWooNVqwmQwI+VzsuVIJ51s2ZtkwbXI1RkZ7mJ2rp6wlXxc7eDvbYdmPOVg3qQ+2ZpTh5ZFhFsnIs6taAQALkoPh52KPN8ZEwM/FHm58LskJSeHMcrSFo60NLtyRWMTAhBk/twTGMg54WyrxXJ4mhkZHT9htnK20M7MCLw4Xw47DJM9jTKEg9nCAXKmhiL4QZqz4Rq7DcwegtlWOX3LrzQjiF6QE4e3DeRaFTeYkBSKv1kBJMCRECAZgFb8zaLxRxu2gwwN/RXmZKQbh2bBQ3apAVbMcyWIhmjq7KFlJQUIebjd2Yt7QQIv33bgM8UEqeP5XwmD/FHsgZxSHw8HevXvx/vvvIycnB3Z2doiJiYG/v//Dbl+v/QvNUqrhkcVJf6iW9mGkLBKbpKbOLjMuGneBLRy4NpSUSmNi6XWT+sDJngMGAD1Aabslp8OzX12jlO0ZkyTKlOYcAUTJVriHADqdHnN2X0OImyFbyZiDiVB6eXVUOLyc7MBiMnAsr4FcVI2tuLETlS1yfHO5CrOTAiiKGMbH5Nd1IMJTYDYB0jmWqlrkyK1px+ykACjVOrPfSKQqSJVa7LlEz7Wz7mQx0uO8caao0Sqo0OmA2jaFmSPgheEhYDIY0Oj0+PiEgTcowsOBJIms6QGsnCpohJeTnRnvwIqRYtS0KCDrlGNm620833gNLinHwJbLUOodiq+GTMEv4UmocfIgz2cttdsa8K5pVVgkyF93shjvjIuEt7M9frxejfFxPhYjuHQg/YNfi5Ae54UXhoegQ6ExA1SE45Lg7iHua3WrHEIet0fFxbHdssbGJYbR3gIUNnRg90XrTiSJVIXGji6EuPGw/qm+kHQqUdjQSQE+Qj63R6eLsS1ICUKFRIa6NgXWjI8hI7+m9z8tUoRwT0dsOFVMS6ptSvI55+vr2DEzETsyyw3cGd1Av7ixE+/8nA8Wk4H1k/qisllOcokYX9PYQW3Mm8HnspAWJcKsIQFwtrcBn8tGpJcDrle0WlUqNHYemppY5ACJVIkp/X3RLFPhUHYtpVwg0JWHb+cMQG2bAl1qDZYMC4G/qzlnk/H5rEVmbzd0oF+gi5kjCngwHsGewJkpoLO3YaF/oAsJ7v6NGVGE/VUYas2aNTh48CCKiopgZ2eHwYMH48MPP0RYWBh5TFdXF5YvX44ffvgBSqUSI0eOxBdffAGR6J7Dt6qqCosWLcLZs2fB5/Mxc+ZMrFmzhnSc0VlLSwuWLFmCI0eOgMlkYsKECfj000/B5/PJY3Jzc/H888/j2rVrcHNzw5IlS/DKK69QzrNv3z689dZbqKioQGhoKD788EOMGTPmT43Lv9EeJolti0xl4IgyCZwQc3lNqxyJAS4oa5Ji5q5rWDoi1Do1QIkE0T4C5FS3oUwig7+Jk1siU5K/7ylQZM0BTsz7xjw2xIb+ZH4j/Fx4lBI447md2MATa0ykpwBPxHpZ7ZdCpYFObyAp/uFqNeW8tjZM6PRAhpFAw5tjI+HmwIENiwkHWxYkUjVe+P4mZR62hL+IbGHj8nchn4MF3Tx884YGYv+NGiz5PhvbZiQgxluAX3LrzXAnUc63Y2YimmUq8LjmQc/ONinqv9mH3+9cguuZE3CQd6LTwwfyZ6YiN3UsSgIiUdOuhCeAH8RuyCi5i+3ny/Hm2Ah4OHItjlmwGx9uDly4OVg+hsjq2ZJRhi+nJYDLvhe4MA1wRXYHYU3PZc2JM3doIBZ/l42Vo8ORXdWKnZkVWDrCSqZ0ZgVWpIrBZjNNAsliHMyqxS+36jAh3gcvDg+Foz0bn/12hyStnzs0EO+Oi0RJk9TqM21c2hYq4lMCgBfuSMzEOgiRlWf6+9JyYxlnKxU3dqKvryNWHrhFXtP4GYr0FGD6QD+z4N/yNDHsuSzIlBqzYP6xvHokBjiTmWoE4brAlk2blbcgJQgsBoMkyN9xoQLfzBkArg3LMgdUbTseDXenHTPAOh74q8rLiPJiojKCbh754Gghts9IRJjIwfpcZqEM8X7tr1aLBx4+MfrDtAcq0yNMLBZj0qRJeOyxx3odUb0GwHqq4ZpjhVg5Opz2O9MNy8NKWXThcfDhhBh8/kwcwj0EqGk1OFVWjg7HB+nRcOZxzFIq3QW2GBXtgWaZCnO/vo53j+Qjp7oNi4eFkOftqdzlyVhvs7RdT0dbvDLq3qbAuKRt+b4crDlWhFWPR2He0EDkm2TcpEWK8NrocHR2afD+LwU4lFUDfxd7fP5MHMbHUyOLYpEDKpvl5PXHx3nj8ymx2D4jAT8uGIgji4fgu3kDIRJwUVDXYZZWSziWjPu3/0YNxsd740R+I8Tdi6up6XT6HhU69vVQtjRvz3WI3R1wpbwFS1NDsX/hICwZFgKZUoOsqlYcyKpBi8ygmgYGA6uPFWJoqBAh7nwsMbo/puc9U9QEew4Lrx7IJVPrk4OcsP/DrzBs/RvI+XIm3tv2Knh5OfgsPh0///Ab0mZsxJcDJ1IcUURfjFO7jftjbbGiA4nG5yy9K8WqIwUYHOyKwcGuVo8lrk+A9OLGTrg72GJXZgXkKi32XK5EithQcvh+ehRsbVg4VdBIyf6L9BSQJYRZVa04mFVrVgZFqKAFu/Mwa3AApQTztYN58BDYwceZ3ilQ3NgJN76hrPL9Xwtga8PCjYpWcNlM8LksTEzwIcswekpfl6m0lFTyo7n18HG2g5eTHebtvoEtGaVmzxXhMJ63+7rFVHo6ks/1J4sxbaA/XhsdAR9nOyzYcwOvHTREB115XJwvkeCNn/Lw1uE8yjUtpXAv+jYLcpUWQh4XGq0OFRI5mqUqfHKqBG8dzsexvAazNPst0xPg7WyLy2UtVt8Xew4L7QoNbblAdasCSo0W+2/U4G6nCpvO3MGsr65ZLJmcOzQQwW48i9fKqWm3CogeJDX9fowoyXbmceDlZIdgN/6/2hFlbA8bQ507dw7PP/88Ll++jFOnTkGtViMtLQ0y2b3yy6VLl+LIkSPYt28fzp07h7q6OowfP578XqvVYuzYsVCpVLh48SK+/vprfPXVV3j77betXnvq1KnIz8/HqVOn8MsvvyAjIwPz588nv+/o6EBaWhr8/f1x48YNfPzxx3j33XexdetW8piLFy9iypQpmDNnDrKzs5Geno709HTk5dGLWvz/aAT3El25yIOaQqXF7YZ7a71pOf25YglYTAbOFt0FYCi3sVZaTQhO6AFM234F5RIZBgS6kMdsOFWMpamhAP5caRIxN88deq88WiJV4WJpMyb38zUrgVuxLxdjYzzx+ZQ4szKltx+LgEanx0sjQmmvtzRVDDYDaOpUms2nl0qbYWfDNitxfGnvTSjVOvA5LDR0KGnbQ6w1pn0zVZYj7smh7Fo8+9U1SlnZhlMlsLVhY9UTUaTQx8KUIHyQHo2FKUEQ8jlYf7IYDlw2GfS0VykwpigTmw5/iBubpmLJxuWwuX4N6vkLcP3gaUx+9VsMFo7Byjo+9EwmWmVqeDvb4XB2HeRKLS6WNuPnnDqcL5aQ99K0vYtSglHZLMerB3Kt4i/i3n32WwnUOh1WWCiHm5MUiJpWhdmaZyzkYrxOfv5MHI7lNVBK44sbO60Gt5plSrg62Jrd42e/uo5oHwHw/9g787Aoy/WPfwaGGWAGkB1kUUCGTVAB1xTLFFyyzKXVLU2trE5uldWprNOu2XbSzGyxrCy3rNwq9zV3QREEZN93Bphhmd8fw/s6wyyoacvveF/XuU4yM+/yvM/73Pdz39/7+wXWHc+jVtPEPSsOcyCjXPzO3LWnqNM00zPAxeqcNmxte25jMg/fHCJ+7u1sz6f7L5qNtd7aloa3kx7Fv3hCD6PPDI9f1UGHQatOn6Q0bCNNzq9m7IcHjNrJQL82fLQniy3JRSy6PZK1D/VnUKgHr/58jjVHck1ik48nx1OvaebFzSlE+7uw7niemIhxU8gYGuVttqV+WKT33y4BApeEVyy9t2lFteiAZ0ZFWF/L/mDCyJCaoL1dDVG7oV0Pn3KtTaLT6czjAtvZ3Llzefnll1EoFMydO9fqd99+++1rcnH/i1ZTU4OLiwvV1dU4Ozv/1ZdzxZZf2UDCWztpMQM3ldpI2LngZnLK680Snxtm64XjuDramSCaquqb2P3kLfhZ2JAYZn/lUhsOZ5azeHuaUbVqW0oxk/t3YVCop/Hv2irwKW0oLEOS4qV396CxqZWlO9KZ2C+Qf29KsXifi26PYukvaSLqKdRLySf7swjyUBDl68zKfVmMjfXj9S2pJvf39Ihw8isb2JZSzNnCGlGZQ9PcyvaUYpPWwDnDQvn5TCEbThQAsGRCD6OK4NQBXUkI9WBPuqlSlqBit+lUvhHE/ZUx3Xn+B+P7GxbpTVKUN606HTJbWxNy0IcGB7MnrcxsZl9QjPtoT6Z4HMPKydxhKn46U8CGEwVE+jrzypju6NBR09jMm4aqhCPDkUttya9qwN7Ohi8OZotqanf26kxipI8RIkioKoV4KtiTVsa5gip6553ltnN7GXl+Hx711RS6d0Z2/72cSxjBq7l2nC2qvex7AZjavys3h3vy5tbzDFZ5sNvC754dGWECn7d0zA2P9OfZDSkdfvfjyfEsXH8aLyd7FiSFUVDVQFmdBh3gqZTTxd2Rud+dood/J6Mx7xPkxuO3hlJd30SFWoOzgx1NLTqTZwqwcnI8284WMSTMy2wr3zt39+Q/P501qaBF+jozqX8gC9cnE+nrzNK7epBSWMPKvVkm72J7xJahvX1XD3Ir6vFQysmp0KtBejnZ89iQbrz/2wVxjNrPq6faiPitjWHvrm78nFzI+uOXEGvC+/vCDyksuj2KZzde2givmhKPWtvMsl16VNrEvl24KdSDpTvSGN7dh63JRRbPN6aXnyg08OCgILYkF4lBpodSxsyEEMJ9nDieU0mIp4JFm88yLtafuC6utLTqzM7rqf278MrPqRbP+cF9vTieU2k0rubev/lJYXx9JAel3JZR0Z2NWgqFa53ajuDYkgnr6N9RscWc/Vk+96+IoUpLS/Hy8mL37t0kJCRQXV2Np6cna9asYfz48QCkpqYSERHBwYMH6devH1u2bOG2226joKBAREstX76cp556itLSUmQy02d67tw5IiMj+f3334mPjwdg69atjBw5kry8PDp37syyZct49tlnKSoqEo/x9NNPs3HjRlJT9a3id999N2q1mh9//FE8dr9+/ejZsyfLly+/rHv+O8RQf6QCLWwa2tsfIbGtUGt5dM1xMeawtNYKCqhzhqrYnVYqxhqG6872lCJujfTmmfVneHVsNE9+f5pIX2deHxfN7R/sF4+1cnIcNjYSVu7N4r4+gUZy75e+E0+LrpVnNySbxEELR0Sw7nged/cOwEMp41/fnKSsTouHUsbrY6N5e0e6xXVv0R1RvLApRbzu52+LoLG5lTe3nsff1YGR0b5GLb+zBgdjI5EQ4ObAM+uTTdDrH9zXi5c2n7N4vlfHdufNreeJ8XcxaeFr79sBlk+M5UxeNUGeClbtu0i5WsPCERFm/a9AAP74EH1CaE96KcMijWPAaQO7siOlmFEBcroe2kXgzi0od/+GVKvhvE8Im0P7s0V1E3Meux1bG4lZPy48+2dGRqDT6ZjXJrby3KhIdqeVkBjpw+pD2fTwdyHGvxP2drYczioX4yRzfkXwU4Kfk9pI+HxaHyRtc/LDXRlmY7VGbSvd/Z2NjvVgm7BIVb2WFh0cz6nky0PZYtwh+O2vDufw7KgIXvnJ/PO6nDhMIsFq/HdHr850dVMw68tjJp+/e09PXv7xrAHqW8Zb42MoV2vbREms7x1WTolH09yCjcTGiGhfsPfv7UVWmdpqrNF+vhnuCSI7O/PV9L7o0CeiJBKY/90pDmSU46GUMW+YCvc2JUMhVnx6RDh2NhL2Xijnk32ZuCvkRs82srOz2KKm1jRzMreqwz3e38Eq1FqR5669CeO490KZHvUltSGloJqCqkaz7+m1IBm/XmO3N72USZ8cMfn76ul9jPbAV2vXwude9t2dOHGCpqYm8b8tmcRcU+gN+5+xjqCGCpm+9WLl5Hir7RYOMlsm9etikjx5ekQ4yfk1RhloIfCzs5WQVlJnxDElcMAI12OoXrdsVwbdO7uIi7KDzBa/dvwHhoTiqYV17DxfwqBQD7MS5eJ9ejthY4OobiLI8U4b2BVPpQyprQ0zEoLZfb5U/E57pTtXxSWllfFx/hRVa9h5vsSsRO3C9Wf4aFIcQyO8cVfKWXs0F9Anh4I9lQS6OfD8phRRzc3wtzO+OCaqcj03KpItZwrJrWxA5e1kcn9CC+MH98ayan+WCQy4e2cXojq78JiZoNOw5104zoQ4fxbdHsUv54pZtT+LaD89/0tacS1nC2vwcpazcP0Z0amH+yppaGrh1Z9TjZJpCrkUCfre8tWHsklQeTAzIRgfF3vWHs1lR0oR41TNeH31GSPO7cO3rpx8J0/WRw1hc0QC5zqHsn3uYHx0OiZmVZBTUc9vqSUm42XuXgD6hbhR19hEgkqP0Irx72Q22BMCKkstWYbHfGtbmkWOK6HS+O49PSmrbdSrrYyLQdvSYpQ4EeaAh0Ju1H666PYofk0t5tE1x8WxHRfrx+T+XcxyG/10pkBM8pmzFXsyzXJKGUoAP3JzCBfL643uvT2Hw7aUYrNtlGfyq1n6izHkfuGICBPyb+Ee9aimcLyd7Xl9q3nONIH3ZPnuTJKivNmTVmpE2plTUW+EyBI2LMU1jSzZkWbEdbHueB4rJsdRqW7i3V/Ntwa0bwcUuC0E7i9h0yKTSlDIpSzblWnSvjEu1p8nh4ehlEt5e0caR7IqmH5TkNUKaUurzgTBKbT8LhwRQedO9uh0sOZIDklR3iTn19Cq0zGmlx9KuS11Gv0a/cjNIagsVATb27VIQP2d4eRXa39FDFVdXQ2Am5setXLs2DGampoYOnSo+J3w8HACAwPFZNTBgweJjo42attLSkri4YcfJiUlhV69epmc5+DBg3Tq1ElMRAEMHToUGxsbDh8+zJ133snBgwdJSEgwSmYlJSXxxhtvUFlZiaurKwcPHjRJ1CUlJbFx48ZrMh7X2/4oz+WVSKNfibkpZDxySzc+P3BRTKyYMwFdkltZT15lg4lS6GtbzuHlZE+gmwMT+3Yho6QO0KNNlHIpPz0+kNJaDRV1+gLH2mO5LBwejlrbbLZ1Z196GcOivHhjXAxLDAqGb4yLQSGzJdrPReRQem5UJLkVagLcFDg72Fld97TNrXpExthokU9K4A86W1jD8TZf+Mqd3dmdVsqrP5/j8SGhZJS0MFil55gSEkpC/GXtfPZ2toyN9TOJ5balFHM6r4pbw73o4u6IWtOCr4s921KKGBndmYXrTzMu1p+EUA9e+dm8r1q17yLTBwaTU1GPQm5rwtFYlJHL0S1reanmDJ5H9mPT0sy5LlFsHHg/6QMSGTlmAHV5NTzi74KmuZVP9pnnfxKe/cq9WTw7Ut/BIBDBT4gP4EROJZP6dRHjgN1pZdzfN1AcF8H/vnxHdzTNrZwrrDHhIFJ5O+FoZ8NHe7OI9HViUv9AInycOXKxUlT+vbd3AI3NrTy/KdmES+uD+2ItFl8MeYzqNE3MHabiQTPJnL7Bblbjgvv7BmIntbGovpxWXIuro4zvj+eZKiqOCOOrQzlG9zw+zp+3tqVRUtvIuFh/63sHHyfcFDJ2ppZQqW7i/Xt7scwgYTdrcDAeChmBrg6EeinNxodzh6lYtT/LRAFPuKZAVwdO51fzhkFb2vxEldhOunBDshhvvDk+hs4GIgVNrToUMlsTFcRnzXFRXWOep+thHQmv3N830Oje+gS5U1zTyBfT+vD6llT9c7lMJfnLsesxdhVqLa9ZWFte+zmVqAdd/hbP57KTUTt37jT73zfshhlaR9whcqmNKP9rLVhzU8hICPXgyXX6ZIwQHLy+JZU3x8WIGXgh8CtTa3imXWVJ4IAx3PQJtnJvFk8mhXE6r4o3DJE3oyKM+A+Etqv7+wYikcDhrAoOZJSz7rjlHvZZCcEo7aUmEunzvzvNJ1Piqdc206Btprufs1mi68UTYpAAW9vaqaQ2NtRrm+nh72KysRQ4av69MUW8h9m3hDAu1o9XfkoVE2Ev3RElBqCGXBG5lfWsP55PtJ8LT3x7ko8nx1FUraGiXsPsW0KYvcZ401RWpwWJnv8or7KeMb38ROf04uYUegW6XhbRelmdlt1pZbTq4KM9mUhtJCIvkRBUfHU4R0xyeChlDIvwYcYXlypRQjJt5eR4mlpaRcd8IKMcdDoiS7J43+Y8T25ch09FERVObvygGsDmiASO+4Wjk+i7lKf270p2eb2R3LWgftf+XuYOU7Gvra9+QIg7j98aioOdLQXVDZzOq2b5bj3yyxznVWF1PamFdeaD8gulRs9kw4l8HOW2Jgk/gTurb5Abfi4OFNc2su7h/miaW3CU2Jokc2IDXYnv4iZKQH+0J1Os+hlW7vqHuHPHfw+IQYghX8KRrAoGq7ysOu3/3NmdvellJlXO/MoGPpoUR2Flo8VEzap9F5mZEEKwp4KfzhQayTc/+f1p3hgXw4AQd45kVYgJqj3ny3CQmXI2xQa64u/qwGtbUhms8uiQ92TH2WJRplhI/AiJwWdGRpBbUc/iCT2QSW1QyqX8d+cFo+e07nge/xnTncxSNQcyyqyer3074Kp9F5nUvwuOdlL6h7jj6STD29kBLyd7E+VO4dl9si+LL6f3oU+QG6OifWluNeXXMDxnXaMxnN9DKWN+ogo3hdxovj84KIgTOZUMCPEwktQW7KsH+/4pVc1rIVrxd7U/O4ZqbW3liSee4KabbqJ79+4AIiqpU6dORt/19vamqKhI/I5hIkr4XPjMnBUVFeHlZcwHIpVKcXNzMzpuUFCQxeO6urpaPLel8wJoNBo0mktqmzU1pu/Cn2V/lOfyepLY9grohGRAV8rrtB1uwJb+kibGN+aEMB5dc4IlE3qSWlTDx5PiaNXBo2tOUKbWMGNgMLFdOlGvbWF0tB/Z5fV8uDuD5tZWXrojiowStbiZBejubxoHCXHbuuN5qLydkEttqNU0MzDUky8PZYsoGUvrntRGQv8Q/cbR21nO4m3G/IvCero3vYzEKG9CPJUEeShobG5htwEn1NMjwlHK7TiVa527r0HbYjaW+3J6b+q1/ry4+ax4zIcGB3N3fABSWwnPjIzg+2N5JKg8rT6T+C6deHr9GZ5MCuPtHen41JSRlH6QEef30ztPT5KeGtqT8idf5IFqf4qd2uZaE/z23WlWTYkno7SOyM4uHT77tOJaHGS2okJvbmUDcqkNcV1dxYSekIRqz5lZVqfl35uSeXpEuMm8Ab1vfWt7GpP6dUHT3MoT355E5a3klTHdWTy+BxIJyGwl/JRcyMt3dDdCAy8cEcHao7kWCbIFHqNNpwrIr2xg7rBQs7GWvZ1p3GD4LEO8FDQ2WferyrbEzYmcSmYmhBDj50KLrpXOLg7kVTYYfV/YQ7S06vhoT6bVvcOzIyMI8VRiI5Ew7fPfievaySge+u/OCwwJ92JEd1/qtc1mRWGO51TwwuhIzhXWmiQEVd5Kpt0URHpJnRFR97Q2ER21ppkjWRV4OduToPIkyENh5HdDPJXUNjbz1ZEcvQpiZ2eLiZi/Q4KjI7MKnvB2IsbfhWBPpdHfvZ3t8Xa2p5uXUiyYXWvagGs5doaK8e0trbiWmoamv8Wz+mdHdzfsb2mGKkjtoYaXG6xVqLXsSS8zixzak1aGyltJvbaVgqoGElQeOMpsWWHG+YEx4bNg5Wp9K9PUT383uZbV0/rQN8iNAxnlorPNrazHXXGJpNGS8t4jt4QQ4OrAwvXmOS6WbNcjXtyUct7cet7i9T46pJtRpam0tsVE1cQSifrsNSdYPCGGktpGEYmRUaLmfHGtWQXAaQO74mxvB8DSHel6aGp6KbNvCTGLlFl7NJcHBwXRoG0xaeUzRD29fEcUey+UiXxF7c0QDdSeH+LVn/XKKgKB6fg4f4vInLd3pImKPN3Kchh9bi+3pe4hpCKfGkdnGm4fw3+7DcB7dBIvrk8x+q2HUsagUA8e+Mx4HghJwRV7MrklzIv/3NmdPWmlvLktlZHRvqyd1Y+q+iZeMggyBZSWIQpp6k1difR1JqO0juIaDYNVnixYd4pxsf4sHBHOuaJaDmSUcVM3D6NnsnBEBB4KGfPWnmJeogqVtxPHsqt44YcURnT3ZVCoB8//kGL0DJPzaugT7MZrY7uTnF9DTkU95wprqFQ3Gc3T03nVzBkWKib2DPnP2qNxZiaE8OyoCHLKrRPE700vNQqahABIaiOhrE6Lr6u9VYc4qJs7L/90Tmy5NLQl29N4dEg3RkX7UlqnoamlFbmdjQkKrf37UFLbaDHoM5x7acW1TOwXSKSvs6hyt3BEhNhGJ7WRsOGRAaSX1LIgKYylO9LFcX9tbDQS4PUtqZd9PsP7fn1cNE+vO8Prbe17z4yKINRLaXWsT+fX4O/qIFbdXx8bzQOfmVaAnx4Rzr4LlxJkiZHejO7hS0srRgknAan18eQ4Pt1/0ewz+iOoDGtWUNVgFNBdC9GKG6a32bNnk5yczL59+/7qS7mu9tprr7Fo0aK/+jKuCarpepLYClX37PK6DjfjXk727EgpFgVC2hcZYgNdqazXsjutFHeljPnfnSYx0ptpA7uyat9FcT17/NZudPFwZLDKA3s7W5NWt4cGB1tVJZuXqMJDKTdac+cMCyW1UE8Sba5dZm6iCpmtDVJbOJ5dh7O9dRTVS3dE0SugEyW1GrOqsN/M7MupNvEWc2v7U8PDeGubaSw3LtaPhiadyVr7+DcnefuuHpzMreK+PgEsHBFOuVpr9ZloW1qZE2yLz4oPeOW77+lVcB6tjZQDXXrwTNJsfunWl7tGxrI7rYziVtNjCAIyDh0kYgRE8NHsKib160JDUwvDu/sgs7XhPwZzW4iLzRGLC7Hxx5PjWbrDlIj7SFYF85PC0DbrE6td3RUU1WhYtivDqBh4IKOM50dHGCUvy+q01DY2s2pKPIsNim5zE1V4KmV8fjBb9NnFNRqW/mKKYvZ37WYVdf78Jn17vjVVuAZts3ivb25N5aU7ogj3daakttFkXppL2JnsHdq1Y3Xu5MCMgcEs25Up/i4x0puZCcFG3RYP3xzM23f1wMlBr8ItkcAt4V64KWSU1mn56NtLe57ESG/u7OVnlBg1JOpevCONlZPj0YFFRM4/CfV0OWYNPLFwZDjR/p1M/v5PK5jZSLD6ztv8Iebwa2eXPXKGBJcd2fr166/qYm7Y9bc/o/3B0oJ1JcGapqnFInLo06nxnCuqNQpQ5iWqSM6vMauaZ06N68GBwWYDCIDXtqTyzt09WX8iT2zXer3tb109Lm3iDZMOr4+LprS2EamNDcn5NSbBj4BGCvFUEuDmiJ2txGqAVKe55OyW/pLGkgk9kNpKLlu5rX0CLreynr5BbmaTV/O/O82y+2P1ZH3FtcxMCKK7nzPpJXXifedU1OurVlIJqYW1BLk7MijU0+wiJ6Cebg7zIqWghpSCGotBrVCxMWw9q9c0i21LORX1eChlDAjxsAibbkxNo0/qZras+46I0ovUyBzZrurPy0NmcCi4F/++swfedjZklapNkmuvju3OMxYSh/r2zAA8nWTUNjbxzi/pJEZ6E+KpIKeiwSRwnfHFMT4xqC5pmltxdbTjye9Pi/O0R0An3hofw1vb0th4Mp8XR0fhprAzeSZPfHuST6bE8/kDfTiQUc5zG5N5MimcF0dH6cfLDOpu8YQYnt+UzKLbo3B2kLI3vYyJ/QJ577cLJjLKP58pFIOhQDfzpOtCoLVySjzNra0Wg/95iSq+O5bH1mRT9IK+3VNJq07XgUO04XBWhdnnoG+7aBE52HQ6CbeGe/HOr+k4yaXi3BrcTm7ZUsK4/dxTeTvRu6sbvi4OVKg1yO1s2lUTndBBG4eDKTJv/cMDxMqnufPNTVTx7e+5ZuWRfzpdaNRCPHHlYVZNjbcaLAvXtnhCDGpNM3WaFpMK6bOjIujmpWT5bj2x++tbUkmM8ialoIY9aWVmx3npjnSSunubTQhea2nhCrWGkzlVRlx+8xJV5LerKgt2vZJhf6b9mTHUo48+KpKI+/v7i3/38fFBq9VSVVVlhI4qLi7Gx8dH/M6RI8b8EsXFxeJn5szHx4eSkhKjvzU3N1NRUWF0XOE4lo5r6TuWzguwcOFCo9a+mpoaAgICLH7/etm1QDVdrirlH4njZLa2VjfaW84U8fzoCIqqNXR2kZPU3duoyAD6RPcT354Uk0mWCmMPfXmcxRNiOJVXzbxEFe+1Kyh1pLTXvbMLP50pNGqbm/HFMd6/tyduCplZVbJvf8/l3t4BvL41lSn9u9Kis45ycbKX8su5Yovr4nu/XmDGoGDWHMkxWdvnJ6nwcbY38V0eShkT4v0ttkOu3JvFojuimLtWHxv0DXIzKhAJ1q0sh7eqMwj86BGcziXTJJPze1gfnoi9jd9CelNjfwm10b5YaWjlag1Rvk5klamZn6QSEU6GJviWhSMiOJhZRlKUL0t3pBnRTAjFNiEJ9fqWVJpadKx7uD/Hs6tY2cYndH/fQH7PqjBboIr0dcbRzpZfzxbz/r09aWnFiNpBiH8WT4hh7dE8BoS4iypvkb7OTOrbBR06o2M/ve606BP3pJXi5WRPTkW9UXEN9HxOj31zkpFRviZzZ26iin1pZWSWqknOryG/soH37+1JUbUGhdxWbLEUFOQM51CdpoWjFyuRSHR081RaLf7Bpb3Dp1N746aUmyR13BR6tLrQTmjp/Xrs65Osnt6HcF9Tnh5DUEB5nYaR0b5GMUV7mgSBqNsSF6+h/ZP9cHuzBp4wZ/+0gpmTvZ3F2H3W4GCc5HZ//kWZsctORrm4uIj/rdPp2LBhAy4uLiJHwLFjx6iqqrqigOuG/Xn2V2Rz2y9Y1oK18joNdZomMcCSSDCbaPFQyqhuaDbbjvfFtN4M7+5jRJAscDCV1Wl4aHCwmKTqE+Rq1DfeXuY4tUi/aXvk5m7kVKh5a3wPahqb2XAi38jReDnZ0zfYjU/3Z+HtbM+etDIS2rUHGaKRBMf+/OgIqwFSkLuCV+/sjrO9HQ4yW55ad8akFbGjQM4wAff9sTyrXBHv/3aBl+/ozupD2XRxV1Bc08jXR3IZH+dPqw7UmhY+2pMBwKR+XQjzcebJdaeZO0zFQ1+a3zTPXnOcp0eEcyCjDFsbGNPLjy5ujng561uEjmRVEOnrzL+GhiIBkR9CIOqcO0zFluRCnh4RzvmiWqPx6lxTwqhz+7gtdS89itJpsndgS1Bv3h40kT1BsWik+rknJLT2ppfxxvhoDmWUkxilD647d3KgtrHZ6hiG+zgxd+1JegW6ioGTtQ29gOKZMTAYnURnFPSdLaxh6qe/8949PduUOuQ4O0gtIr6WbE8jQeXBnrQy5gxVodY0EeShJL2kjocGBxsRzsOlBOR/d2Zwd+8AkQTekoxycY2GZ0eF46aQWZ2L9nY2zP/uLPOGqVgxKY53fkmnXK3hwbZ2jMLKRu7tHUBLq84EATdrcDAncip55Wd9e+20z02D4Mdv7YbUxnr1JsRTacLBNmdYKAGujrS0tX/IpbYmwbghUm/JXT3YeCLfhMdiXqKKJTvSGBrhZXaDtiApjJM5VXzze67Z53Qs+1ILh2GC+v6+gai1LXR2sTeLDJw1OJiXfzxr8vfF29KY1D+wwyTaqn0XeX1cNG4KO1pboV+wO9rmVmwk+gDE1QxPjCHHR3tLK67l+dsiAdN2ymslLSzYyZwqo7kgrOEfT45D5a0krbjO+NqucTLsr7A/I4bS6XQ89thjbNiwgV27dpm0xcXFxWFnZ8evv/7KuHHjADh//jw5OTn0798fgP79+/PKK69QUlIitt7t2LEDZ2dnIiMjzZ63f//+VFVVcezYMeLi4gD47bffaG1tpW/fvuJ3nn32WZqamrCzsxOPGxYWhqurq/idX3/9lSeeeEI89o4dO8RrM2dyuRy5XG7x8z/LrhWqydrm6EriOEsJK0vy64/cEoKrox22Nq7cs0K/2TIn5GGIZhJikBmDgqwWxgaFerDjbLHJ+LRHjRiNmbcT9doW9rRrm9uWUszXR3JZOCKcmoZmHhvSjVpNMxkldeLanl/ZwMt3RCGT2uJgZ2t1M3Ykq9JqLHUkq4KpA7qSFOXN+uP5DG7jpOzq7ohCLqWpxTTZdTk8U2lFteJvDmSUo5BL+XhSLD98+hMRB3dw24VDBJbk0GjvyKGI/lQsnM5S22D+NaYXG834KR8Xe7NjmRjpzchoX15p49qc1LeLSTu/gAh+ZmQE+y6UkRDqaUSe3T5xUVanpaCqgdfGRhsVhV8fG01Lq45Xfz7HU8PDjYpmgs1PUqFtbsHF0Q5PJ7lV/rIxvfx4a9t5pg8Mpl+wG9ll9ZzIq2KbBfJuIQaK9nfBxd7OhDrgx9OFlNRo+OzgRX48U8AH9/WivE5LD38XlHI7VN5Kpt7UFXs7G/KrGsgu11MmGLazDw7zYMH3l8Z/+sAg5FIbXv7pLAtHRLDmSC639/A14l1UyGz1PENbU43e6WBPpcX9l6fTpbjMWuH5tS2pRHU25f1RyKVE+jqz/P5YWnQ6Zn9lnqdQGLO9F8quqY//p9iVoL2uF6ff9TRXhYxAd0ez8WSgmyOuf5PrvewsxKeffir+91NPPcVdd93F8uXLsbXVT96WlhYeeeSRf6QC3P+C/R2yuZaCNcFZPrT6uLjoPzUiHH9XB5Pvjo/zN9uO56GUUaFuMkuQ/OnU3mibW3j31wvi8WO7uDKpbxc+O3jRbOtaXBc3/FwdeOLbk3wxrQ9d3Bx4+KsTnC2sIbtczZyhevh4WZ2GtUfz6OLmKAY0hu06Km8l0wZ2JaNEbdSj/eiaE7w+NsYswaIeBtxCvbYZpdyYe+onA0RLXgeBnCFHTVmdlsamVqvBkaa5lQduCsJBakNXd4VIyLn+RD4zBgbz0aQ40orrKK1tbFPaqGPd8XyWT4zjvV8vVZgE9a2yOi3rj+czpX9XUXUkMVKfCLo5zIvbYnyp07SgbW7hh1OFelUOX2fU2hZWTomnq5sDY3r6MWnVEb2iYG83jv74Fbed20vv/LNobO3YGRJP47/mUH7zUB7fmGZyX0K1z9ZGQk19E44yKeVqPdrsmRHhdHZ1sDqG+y/ouZV2nC2me2dntqUUd7ihr6rXkq9pYcOJfLPfWb47k0GhHjy7MZlXxnTvMKF4trCG74/lMSHenwUGKCtDiLXh99OKawnyULD3QimHMivEKnh7rrDunV341zcncVPImDNUxb83mSoazRmmYu3RPDERpEPH62NjKK7RzwGhHWPawK7MGBgkosIEZ/fz6UJGRPuycEQEZwqqzfKJrTuezyODQ6xW621sJGbJ9z+ZEs8n+7I4nFXB08PDrSL1RkT70CfITayyCpVtnU6ftGpp1ZnnmJDaEOXnzPkfzT+nlfsyefmO7mI7hmE1dvX0Prg42BkTXno7MWeYiu+OmqKlhOfY2gqvb7+ESswurzdJoqUV19LJ0Q5/V4XFTWqkjxNTDXhiOtr8uTiaDwn+qLSwoRVUNbB4u+m7Cnp01hNDVTzSDhV2rZNhf4X9GTHU7NmzWbNmDZs2bcLJyUnkWnJxccHBwQEXFxemT5/O3LlzcXNzw9nZmccee4z+/fvTr18/ABITE4mMjGTSpEm8+eabFBUV8dxzzzF79myLSZ+IiAiGDx/OjBkzWL58OU1NTTz66KPcc889dO7cGYD77ruPRYsWMX36dJ566imSk5N59913Wbp0qXicf/3rXwwePJglS5YwatQovvnmG44ePcqKFSuuekz+LLtcVFNHZm1z1F5pz1wc11HCSgLcEuHFvLUnjdCyL/6QwkeT4oziK3NtWEKc46GU4abUb5gvpzC29Jc0nhsVaZQUMnd8weYnqphtILIhxHPv39sL0PHUujNGbeqZZepLJM1uDtRpWliyWc8n+tb4GLNru18nB175+Thje/lZXRePZVey7nge42L98Xd15FxhDWuP5nJzmBfrT+Qx51aVkbJagKsj54tqLis+k+ha6ZV/nj6/raRH5mGGlReicXahaugI9g96kWl5nWiRyVl0exS5G5Mton3N8SkJiBrDMRcSMf+9Lxa51IamFh0yqQQbiY6cinrG9fKzSqY+Ltafdcfz9K1k7ZDCD3ym5/qqUGvZm1bGqqnxLN52Kek1L1FFenEti08W8uiQbiJ9hDlLK64lxs+Fz6f1oapey7TPfqesTtthzPSfO7sjAfxdHRjTy48+Qa4cyao08Z9ldVpe2nyO18dF4++mAKCTwTuaXlJnsp+Yu/YUH94fi62NhEhfZ2YNDsbZXsqaI7m4K+UEeyqMhFQifJyQSMDVUU5EZ2e6+7lcdnubt7ODuJ5Yfb/MFGrarwFLJvS4IqLu/0Xr6N4r1Foq1VoGt+3j2sduf+eCWZi3E80trUYJ0gA3h8sWpfkz7Kq6BVetWsX8+fPFIArA1taWuXPnsmrVqqu+mNdee43evXvj5OSEl5cXY8aM4fx541aqxsZGZs+ejbu7O0qlknHjxpnAunNychg1ahSOjo54eXmxYMECmpubrZ67oqKC+++/H2dnZzp16sT06dOpqzOuzp4+fZpBgwZhb29PQEAAb775pslxvvvuO8LDw7G3tyc6Opqff/75Kkfj2llH2dwKtemG6HqYEKwZmqGzPFtYI3IcTVl1hJHRvngojRcIS4uypSQVwFvbznM8p8ro+DO/OMYglQcqb6UIfzX8/MEvjrahV2S8vjWVZh0i59LMhGDe/+0Cs78+Tl5lAzMGBTG8uw+Bbo48PTycOUNVNLXo+HJ6b+YNC+Olzed4/ocU9qTpObCGRXq3JYdaeOfunkT6OiNtc25LJvRga0oRr29NJcTLieW7je9px9liXt+SyphefiSoPHlsSDez9zx9YBA7z5fw0OBgXhnTnYcGB6OUSQmzsPiovJ04V1jDjC+OklfVSGmdhvnfnSbcV8mi0VFsOJHPXR8dYvXBbCJ8nfF31UN5JYC91IYxvfx46Y4oxvTyw872khpUD38XkbjaQyljeHcfpnz6O6/+fI5nNiTz6s/neOzrk+JYPzU8DAc7W57ZcIbHvzlFbV4RLxXv572P5zNqRB9e2PkJOhcX5t82j/te+QH1mrWs7NybDWnVLLs/1uxYxga6snBEBK/8nGr0HALdFbz36wWmDexqdkwev7Ub647n4aGU8dDgYAaEeDBY5UFZncbqOEb7udAv2N2q8x8V40ukr7OYULR0LKFNMTHKmxlfHKOktpEZg4K4v28gF0rquL3HpXfEkPMhv6qeLw5mc2+fAJpbWvluVj+eGxXJnrQycQxsbCTEBboitbFpk8uOMfr8tbExSHQ61h/P5/U2QvB37+5JVpmamauPGb0v8787TUF1I9MGBrHo9ii9ktGWc+RWNhDiqcBRZsu25GI+2ZfFgqQwNj96E8+PjsTdUUaIpwI7qY1YrW//DDNKaymp1Yjz2HBNWLI9jWg/lzZy0AyLz3J+kormFh2f7MsiQeXB4gk9eGVMFPXaZhRyfZJceLcGhXqI97DueB670kpJKaix+JzcFXLK6zTG197ZmU+n9ubXsyUkvLULtaaZBNWl414sr6N3Vzez9yQ8x7I6LfsulPHloRw+2pNp2ubn44SyDWItFBsMn8nElYc5V1TLTd086BXoKnJ8WBqjWYODUcilrJ7Wh8jOl+7jqwf7XrVSTIVaj1Iw9DEdKdh4Kk0THv/fAuXrFUMtW7aM6upqbr75Znx9fcX/ffvtt+J3li5dym233ca4ceNISEjAx8fHqC3Q1taWH3/8EVtbW/r378/EiROZPHkyL730kvidixcvIpFI2LVrl/i3r776ivDwcG699VZGjhzJwIEDjZJILi4ubN++naysLOLi4pg3bx7PP/88M2fOFL8zYMAA1qxZw4oVK+jRowfff/89GzduFAnY/+4moJquxfvjppDhZ6BkdblxnKW1IK24ln0Xyrh/5WG+OpTNc6Mi2Ztexgs/pLA3vYx37u6JUi41ejcNW52Fta1e28Kkfl14YXQkpbUaXh4TJSalzJnherblTCGfTu0tHsvLyR53hYz37+1ltO5/9kBvI5ENQ1u2K4Pk/BoT/yPEEB5KGSOjfZn++VHOFtZQUqPhy0M5yNvFKXKpDfZ2Nngo5FbXRYFCAPScPML/Z5TWEeTuyIMDgziYUW4yRgLPlDl7sF8A2d9v5qXtyzj04VTWf7WAMWd3sSOwF7+++yXjX9jApn+9wh5VPzRSmVHyytBPLZ7Qg8eGdOO1LedYfzzf5FnNSggxi6gpq9OyaPNZtiQXUatpYm96GS062JZSTHZFvdX1OcLXmQmXQRHx5eFs6hqbeXRIN76e0Y9Hh3Tjja2pvLblvL5g5u5IvbbF6ryRSHTYSiQUVWsYH+ePh1ImFlQs/cbH2Z5ega54OtkT2dmZtOI63tiaarHw08nRtE3JmgLZB79d4PMH+vCfMVFcLFPz2pZUQjwVvDkuBm9nOWtn9eO2Hp1FIZUpn/7OvO9Ose9CGXKpjdE7bc0q1Fq6uDmyelof6pusjJOZQk37NSC1yHL8IhB1Xws1uP+PptY0i0WAxHf2sDutjBdGR/La2Gij+O3vXDBTyKX0CXJnfJw/g8O8GB/nT58g978Vx5VEp9PpOv6asbm6uvLZZ59xxx13GP1906ZNTJ06lcrKyqu6mOHDh3PPPffQu3dvmpubeeaZZ0hOTubs2bMoFPrM9cMPP8xPP/3EZ599houLC48++ig2Njbs378f0FcXe/bsiY+PD2+99RaFhYVMnjyZGTNm8Oqrr1o894gRIygsLOSjjz6iqamJBx54gN69e7NmzRpAz0OgUqkYOnQoCxcu5MyZM0ybNo133nlHDKYOHDhAQkICr732Grfddhtr1qzhjTfe4Pjx45cdTNXU1ODi4kJ1dfU1Q5nlVzaQ8NZOI6JpwaQ2EnY/ectl9QlfiVWotdQ0NBm1jID+xc4sVZNRVsf5whq6eCj44kC22epRpK8zg0I9jNqLBNh4e26oYE8lC9efsXiPi26PMpG9j/R1ZvH4GOZ/f9ri+ROjvPngtwvsXjCYBd+f4d4+AaQU1BDf1RVXRxlLtqdxOKuCMO9LSmurD2fTN8iNB24KMoI6C7Z4Qgyvb0ll7jAV7/yazp09/Qh0cxQJFgXi569n9OOejw9ZvaddaaUktaG6DFEXbo525FY2sGJPpqhw0y/YjdJajdlWqSUTehj19N/bJxCFzJYQLyW700rQ6cBDKRcRM8+NiuTDXReYmRBsFnUT1dmZRZvP8tyoSOZ9d4qWVp1ZyL/hWL94eyQZJXW8+s1hEtMOMfrcHm7KPokUHUeCerA+dCC/9xrMsIGRdHF3pF+wO89tTBY5blTeSiO1HiGAtFR5/eyB3jy57jQ9/DuZjOH0gUE42Uv5/lieiJoTxrFPkCvFtRpmtuN3APh0am8+3ptJD38Xdlu510W3R/LLuRJU3kocZVKz/EDCMxkf58+etDL8XR1MEHwzE4Jp0DazcEMyyyfG8vaONB4aHIKdrYSd50u4Jcybr4/kMD7O36jKJ9jHk+PwcpKTUao2+/nbd/Xg1Z8vzYv37+vFY2tOWLyvZ0aGM/GTS3wzyyfGsmp/FpP6dUHd2IybUs47vxhzve1NK+PQxXLmDQsTpa6F96GsjevAUPZ72sCuIiKs/bs9LNKbUdG+RvxkT48Ix15qw2/nS4xQXwLHxNqjuTwwIMjsM/jvfb144YcUVkyKo6q+yey7s3JyPG9uS6VCrWVCnD/j4wNQa5rFSi4Yt7skRnqbtBMb3pPhu+ihlFmcvwIaokKtFQNPk2fS2VmEjgsB1bBIb5P5/uCgIII8FPQK1LdLVai1f4ig1Bo6o7qhiQfbNoom1+vrzNK7ezBn7SmTFqXrFThdD5/bkV2vGOrPsp07dzJ27FgyMzPFFru/i/0Vz7O9/dH3x5x1FMf9MncwoE9WfLQnw2jzrfJWMi8xjFkGZNqCcuqI7j5IJFBY3UhuRQMbTuSbvJuCmEW4jxPni2roEdCJnIp60RdZi3faxxYvj4lke0qJUcwD8MF9sZTXaejqriC1qIYn1115PDco1ENUi7V2D/svlIlKfZP6deHhr46bXRfnDFOxP72MguoGE9/70OBg3JUy7l95xGg8A90c6RngQnqJmp/OFIrHvJhfwfjq8zxcfhKX7VtwrK0iz9mTbaoBbFX155hfBOF+rgwK9RAVBF/cnEJZnZbPHuhNeZ2G9JI6o/b85RNj+eJgthHPn4dSxsR+XUhQeVLX2MwDn/1udRx/OlPItJuCRJR+R3HagqQwlHJph7HpV4dzeHhwCI99Y9oeFunr3EZEX0OUn4tZDqvlE2NxsLM1UrueNrArBzLKGRDibtUnCibsN55aZyHGN/CPhtbRu7bo9igUcin7LpQysJsnK/ZkGvk5B6kN45Yf7PD6wLSdtr3v7BvkxnOjIiit1TDFQHDJ0jHNxQPW4ojV0/swKNTT5O83TG/t0aiWRKBCPJVi/PS/ZtfC515VMmru3Ll88cUXPPPMM/Tp0weAw4cP8/rrrzNp0iTefvvtq7qY9lZaWoqXlxe7d+8mISGB6upqPD09WbNmDePHjwcgNTWViIgIDh48SL9+/diyZQu33XYbBQUFokTw8uXLeeqppygtLUUmMw0Mzp07R2RkJL///rvI37B161ZGjhxJXl4enTt3ZtmyZTz77LOiNDLA008/zcaNG0lN1WfQ7777btRqNT/++KN47H79+tGzZ0+WL19+Wfd8PQKpy92sXAtTa5o5nlPJa2396cKGOdDdka7ujpwtrBUX2Un9ujA21o87PzxgcdFfO6sfz21MEYOD2beE4OkkNwqEBA6m9kot4j2aSWoJx9/82EBue3+fxfN/O6sfmaV1RHV2QWYrIbmg1sjxGG4i4VKiSUggWLueAFdHGppacJTZGm2Qhe+8MS6ap9adsXiMN8ZFU1nfxPmiGtwUcrp6OFJQ2YjS3paWVnjwi6OMje3MsAgf3v/tgsgXcFOouwnp59aUIvEehkd5My4ugKU70ghwc2BEd1/WHs2lh78LYT7O+LjI2ZtWRnc/F97/7YLFJElLaytRnV2Yu/YUZwtreGVMdxP1PcGcmxtZ4VqI3/Yf8Nq/E3lLM4f9o9gckUBZ0m3ckdiLCrVWHCcvJ3teGdOd7Ip6Iwh6+4DyqeHhZoNrYQzH9PLj1Z/PGQWSORX1nMmvpm+QvlVTUAoyvEf9OHoYqcXMTwpj86l8NpwosOr82weQ5oJgw2fyypjuvPtbOk8mhZk93srJ8TQ26Qk0B6k8SC6o5nBmhdge2VFw+eyoCF75qeN3Z8mEHoT7OnH7B/stvi9fTu/LxE8Oi5D8s4U1BLg6Eu7jREFVg9lkjvDOTOrfRZ+MaJubfYLcmD4wyCzvhPAbLyd7k3fb21nOmhn9sLfT84XUa5o4ml1l9r3Nr2xgsMqDBm2r0fPsE+TG47eG4iSXIpHo+Rv++1sm3f2dTZ7Tmbxq5HY2fLQnk8jOzqycHG+SbBHmw+tbUi3Oi3fu7omnk4zvj+Wx4USB+Pdhkd7cFR9gNNeeHXUpQXO5xQa1ppmTuVW88tM5ytUapg8MJq5LJwoqG3FV2BHp64ybGVTS1Vj7AE4wIXD+7Vyx2bnw6dTe3BLudV0285bsr0he/Fkx1PWyBQsWiKjzv5v9HZJR18Pax3GGBaB6bQv2dra8uDnFJC4RVO4sxUcDQtzFhIyh3xKOH+ypxMleSmcXe3adL8XVUYazg50JB9OwSG/u6R1gwkVkGFssmdCD/RllDAhxN0mGb0ku4r4+gXy8N5MYfxerPispypuGphaj4kJVfROLJ/QgwM2Buz6ynigREllSGwlfTO+NXGpDSws0terQ6XS4K2R6n5pdSYinkop6rcU1+z8/nTVB3UT6OvPwzSG01qnJ/HIdief3o/p9N3Z1tVT5daVo2EiebO3GaZ/QS3Ar9ATbcqkNjjJbvjqUQ25lg1GR01A5N9rfhX0XShms8jLLh/XtzH7Y2kh4flOK1XEM83GisamV1CI9HQBYLuB9PDmeZzeeYWwvvw7jW5W3E15OcuasPSkWVoT5GtnZmde2nKOusYXXxnanrE5rNG9mJQTj42LP3SsOmRx/8YQY9l+4pEBsWHSK6+JqtmixJ62UyauOmPzdEk2J1T1T2/2dya9mVkKw2QSRxXlhsN8yV7B54fZItM2tTPrE9Fo3PDKAem2LWS45w3surGrgi4MX8W9XeDOJM/+EQs8/3cytuTeSeqb2lyWjWltbWbx4Me+++y6FhYUA+Pr68q9//Yt58+YZQc//iF24cIHQ0FDOnDlD9+7d+e2337j11luprKw0UoLp0qULTzzxBHPmzOH555/nhx9+4OTJk+LnWVlZBAcHc/z4cXr16mVynlWrVjFv3jyjamRzczP29vZ899133HnnnUyePJmamho2btwofmfnzp0MGTKEiooKXF1dCQwMZO7cuUbkmy+88AIbN27k1ClT1IE5u16BVEebg+t9nvfv7YlCLhUrIMJLfaGkzqpTW3R7JCdyq8U+1y7uDkiQGMnlCsezxMH07j09RaJgQ/TO6bxqpt3Ulbd3pFs8/wujI6jTtPDJviymDuhqcl64tDEWKn+DQj0IdHO0mHiR2kj47336vvO3d5hHfLx7T0++/j2HB28KNntPq6bGs3JvlojKmpeo4pvfc9lxtpg5Q0PZllJMhK8Tw7v7mCi0eChlrJwcT35VA6fzqkU0lvCZwOsgPKPtKcUmyaY5w0IJ8lBw38rDFpMkn0yJ57tjeSIxdPukiLxJw82ZxxidupehGUewb9JQoIrmE/++/BQ2kCJnD4tViK7uCp7blMxTSWGUq7XGRKw3h9DF3ZGM0jrcFHKrlcFvZ/Vj3DLTCtYH9/XC20nOCz+cNeIAaz+O/70vFns7W+xsJfx0upD/7soQP7eUZHKy1yOhDK9JSIZ181IS4qlg5upjRqgad4XcalItMcqbd37Rt0Muuz+WvKoGNhzP7zAJKLWRsPah/kxYftDi54sn9MDezoZDGRUMDHW3+r7MGRZKaa2GLm6O/HdXBg/c1JWzhTUMCfO2XJ00SHipvJUsHBGBh1KOpqWF5zdaDqSFgLc9F0SkrzPLJ8US2MYDsft8idmAcfGEGN7adp5VU3uz/0I53x/L5ZYwL+K7uNLcqhMTuAKH3VeHsjneRk5uWNWvqm8SNzhfPdiXYA8FA9/cafJ85yWG0TPAhXlrTcfBQyljVkIIPQJcsLO14ZezxW3joZ8z+zPK8FTKifB1pmegC13dL6koXWmx4XReFalFtSjlUhq0zW3cb3m8e0+va+ILLud60Ok4mVtlJM/95PAwVN5KOndy/MPXcCX2VyQv/qwY6n/R/r8mowAxiWvOLwoJHSHxs+z+WD49kMVd8QFomlrN+gAPpYz/jOnOe79eEN/XYZHe3NcngOqGZpMEfnJeDff2CWBOW4GpvQ0IcWdivy50ddcX2pZsTxM5BBckhWFjA29sOS8mw+O7unK+qIbNpwqZ3L8LPs72jFt+kBBPBQuSwkxiF4AvpvWmrE5rgixNzquhT7AbuRX1bDpZcFmFyakDujIq2pf8qgaje50zLJT96eV8dvAi6x/uz3Md+CHDYohSU8+wzN95XnsO5c5fsNM0Uh8eydn+w6hKGsWsk1qGRJjGBvOTwvB3tae4RoO7QoadrQ2tOh2PfX3CRNBh2f2xLP0ljbTiOj57IJ7mFoxUgoUk4Pg4P3Q6zIrMfDa1NxX1puO4LUU/f9pf36zBehT2FwdzLMZEoI+3bSUSNp0qIL+ygVfu7M6mkwV093M2ieO8nOScyq3iYGYF0X4uol9VyG3ZmlxsdczXHc/jg/tiyamop6q+iQlx/hbJmMVCTAeJHEOztJcRkH4T4vytot8tFcCF4pC541stHHZ25qvpfdGBxUKNWtPM6bwqkvNrRAVAHxe5yMk6IMSdxRN6oIM/pdDzT7f2hb6Ons/fkcD8z7Br4XOvKh1qY2PDk08+yZNPPklNjf6hXGun39rayhNPPMFNN90ktrgJqCTDRBSAt7e3SNRZVFQkIqIMPxc+M2dFRUWiaoxgUqkUNzc3o+O2V6YxPK6rq6vFc1s6L4BGo0Gj0Yj/FsbzWtuVyldejVnjNCiq1rDhxKWFWVCHsObU5g5T8fBXx402msJi0N7K6rTsSy9j2f2xvP/bBaMNjkQCsYGuZhIqKhqami0SJz9ycwjVDc3MXK1Hlwib/fYm9Mh/1NYa9K9bQ6ms11olr/RylnPnhwfwUMr4163diAt0pUWnv78Jcf58dyyPMT06YyeViNL1hnLCXx/JFZE1ghLV23f14EROpZ5YXa1hQrweLda+he77Y3k8syGZF0ZHmjhLQ+6tyf27UK9tYdbgYHacLaaktlHkaJjxxTE+ndqbR2/pZpE7YMn2NAaFeog8BuuP5zOjnx8/LP6V0ef2MCz9EE7aBlK8gkmfNYeGMWN57nS9GHhZkrOd/91pVk2Jx81RZla5BOC93y6w42wxDw0OtvocGptaef/enizblWmEiKmqb6K5VUeZWmNRyUTgXXj7rh6U1GpYvseU30tQclt0exS/nCsW2+7aX5NAeh3p68ykfoG8emd0G0m8Xhr4qeHhRuqPhtZeOfH93y6w5K4evL4l1Yhk1tIYyGxtrH7ezUvJ3LUnmZUQwoq9mWYlqAEeuSWEhevPiGilAxnlHMgo5+PJcRRUN1yW8mOFWsuRrHKGhOsr39Z+8/q4aN7/7YJJ9XF+kkpMRFWotbyx9by5Q7Bq30WmDwxG29TK0YsVpBXXUaHWEuqtNJlzU1Yd4Z27e3I8p9LknRFI9wVuGE2zsbqS4cZRpzMlvzf8XCCEn5eo4uPJcRzKrDBKtr17T09c7I2DnSshTq5Qa3naAtryWqnBXI7EvV8nB4ZEeKPydqKyvomDmeU8ue40Hgr5dVd5/TvYnxFD3bD/X1ah1rInrUxUdW2vKDx37SkWT4ghu1zNkHAvNM2tvHy7Hj1s72TL08PDxfY9D6WM+YlhhPk4Ibe14cGBXUlrawE7kVPJiO4+ZsVgFk+IoaJea1V5blS0Lx/8doEpA7owZ5gKJ3spthIJZXUakvOrSYzyxlMp1xdxJOBgJ6VvsBtltVp8XOx5966eZJbXsT+93ISoe/YtITS16Mxe28eT47lYXkeMvwuhXkqzyEtB0AT08cUtYV5kV6jNimOsmhLPj2cKqNNY90P39w0kxKaReQ3n6HFkJ95H9iJtbqI2uhcVc5/mRO9beOiw/vcPOfsT5lNmorqaU1HPsewKWlo6sdSgjX1mQjALR4Sz5kiukSLr+79dYOGICNyUMhq0zXz2ezaDQj3EYxmqCr4+LtqESPyRm0Oo1TSL4+ihlJGg8kDT1Mr0gV15flMKr29JZWZCCDd1c+dCSR1KuZSXfzwrxuvmiNTnDlNRWtvIkh1pIt2EQmZLQqiHiXqqQEbfuZMDh7MqjFoNP5oYx5eHc4wUsAWET1pxLTMTgvnPmO58si+LHWeL+epBvWJnfmWDiXokXJlimmC9AjqxelofXjMQHjFUtA3zcTZR720/L9pbnyA3JMDFMjXnCmrwUMqM4peOiMrr23ynJUsrriW/qsFIAXDawK7c1yeAEzmVzL6lG52vMSXL/2drL7p1pUTyN+zy7aqjvebmZnbt2kVGRgb33XcfAAUFBTg7O6NUKjv4dcc2e/ZskpOT2bdv3x8+1t/ZXnvtNRYtWnTdz3M1i7FgliSC25u1TYhCbmv0mfBSt7TqzDq1J4eHsSu11GSjaW0x+PJwNr26dDJyyoFujvx35wUmxPubKH/M+OIoKybFsfN8qcn5H7+1G15Ocp7bmNLheQ0dj16Ryg4kOotJrvlJKt7adp7ESG/ubatAvmLQ1jhnWChKuS1uCjlTVv0uomaEe9I0tXIix5hTxEMpo7xOy/v39sLezoYP7o0FnY7Izk5MC+5qlIR7ekQ4O1KK22Dtxvc9LNKbj/dmkRjpTbiPsxG/z9MjwjmQUY6Xk5wAV0culNRxUzd3Fm02lac3HJeVu9Kx2/krTxb8TvcFv3JndRU5XoGs6jOWlEHDGXXXLTjbS9l9voxbwi7JuluTs128PY2ld/Xg/k8Oi0FdJ0clMf4KHl1zQpw31tR6pg8M4r87LzA+zp/J/QOJ6+pKbkUDL20+e6n/f0QEjjJbPrYSdJzOryaztM6qklurDjGJ0dE1vbblHJP7d2FMLz8UMltyKuq5UFJ72cqJacW1lNVqmNSvC939nFl9MNvqXETXysM3h/DY16bcDnOHqdhyppBZCSHkV9VzV3wAhdWNrJwcb1SJfXJ4GDqdjsn9u3BTNw/2pZeJgdbSHem8PCaqw+s3TMqs2JtlUR1P+I2muYV7egeQX9lglKiN8r20qe+ILDuuSydmrD7Kc6MiOZ5TaXXOrdiTKSadDe3pEeFE+7mIVVmFHDE51D6hmlNhrGZnKeE6/fOjrJoaz5n8aqrqm4j0dbYqxXu5xYbLSRT9UbsSifuLFfVGSbSSGo1VldfL9UX/BLveMdQN+2usoKpBnKPXcuPXoG1h9eFsXBV2Inqlva3ad5FXxnTnZG419dpm9qSXofJ2YtOpfM4V1PL0iHAKqhrwd3U0QcQ0alt5ekQ4TS06Vlrwd6v2XWTOsNAO1/K04lq6eSlZvjuTu+MDWLX/Eor74ZtD2Hm+hAEh7oz+7wFjlNfmSzHQd0fzOJBZxpyhKryc5WJCa4lFJc40xvTyY+InR5jUtwufTIkXW7/6BLmxICmM6oYmJvfvipujjLiuruxLL7Ooert4exof3BdLlYXComddBVOLT3DrY69y74lD0NrKUf9IfrxtFpGzp9DsH0AnRzve25Ai/sbQ9xuqrppD9p8trOGJb0+yeEIMt/fw5UROpRjXpBXX6rn3vjhqhGhq75vSimup1zTjaGfLpP6BhPk4c/RiJZllarYm64vk5lB2c4aqWH8iH3eFjCmrjvD0iHB+OlPI0yPCRaGRVfsu8ta280YIt6fXn27HVeZEQ1OLRfXUZbsyeGxINxOf6OMi55kREUZoNUE9OL+yQc+B9t0pJEhYNbU3Lg56fk8BDRQT4EJXdwXNLTojX3ElPkMhlzJI5YmLox1n8qqNknwAPi72lx2TCeN8T+8AHvz8qEVFZKtqtx0QZFeqtWSX15st3r5zd09WT+tDoLvisu//hpkW+v7I87lh1u2qklHZ2dkMHz6cnJwcNBoNw4YNw8nJiTfeeAONRnPZ/EiW7NFHH+XHH39kz549+Pv7i3/38fFBq9VSVVVlhI4qLi7Gx8dH/M6RI8b9toLanvCd9ubj40NJSYnR35qbm6moqDA6bnvVvvbHtfQdS+cFWLhwIXPnzhX/XVNTQ0BAgMXv/1G7ksXYGgmtprnVZFNgbROi1rQYfWb4UrevEqm1eh6l1YezTY4jKJlZcgA+zvb8fLqQvellLLo9ktrGJsJ99Dw05uydX9JJjPKmoKqBZ0eG46qQ0dyqY1tyEV09FOLGrSNJdMHxTB8YxHu/pnNzmBe/X6wwK2Uf6OrIhdI6/j0qgnK11mxVbvnEOD47cLHtnrVGQUakr7Morzs+zp+4QH1b0eGsClwVdibor7VHc8XrFpzTe/f0RGoroVUHC4aHYS+1Ydf5Uvall9E3yI3EKG+jlsSzhTVsTylmQrw/n+6/iINMSt+ubsikNvQNcjOqaoFernhs3UVuef97Tv+0CUV1BdmdfEgdcz+vOseQMHYIg4PdGSa1obC6kde2pJJZqmbtQ/3Zm15GWnEt4T7OVpNAhTWNLJ7QgyNZ5azYk9XWCqDixdFRfLgrg7TiWryc7OnirmD5xDje+9WUJ0tA7yy7P5ac8gYjfiIhGFx2f6zZexSefUaJvs3JUoLpkVtCsJXoVYKEa/J3deTTqb15a9t5s1W3Lw5mG8lgeyhlPDMywizJuGG1V7gmCTAo1EO8H4VcajbhuvlUAYNCPdmbXmqCwJuXqMJDIcPFUcZHezKYmRAsch49vf408xJVbbLXVSKqZWZCMB/tziSvskEMtHamluBgZ8u8RJVZ/qe5w1Ss2JvBXfEBRuOXWlRjEYU1N1HF0h3p6NDx6p3dcZDpg4CSGg0tBp0oVhMj3k76xF2dVkw0dZR0fnN8DHsvlHUI9ReSQ2cLa4ySW+0TkVYTrtvSeGxIN+YMVXEit8qqFO/lFhskEr3Mb3sBCIGHTWLm2Fdql4vU6kgdzBCl1ZFc/T/NrncMdcP+fKtQaziZo289Febo/EQVPQM6XRMuNmEt81DKra5RNjYSE2TE2F5+/Ov8SV7fksprY2OMiMYNUU+vb0nlkym9rR7fztaG+Ukqs6TTgi9SeTuxPaVY3+q1P4u+QW7E+LsQ4OpISkE1E/sG8tzGFLPJ+JLaRo5lV/LIzSHodDrOFNS0KfRKaGrRMVilLza259lMK65FIbOlpVXHZwcv8uOZApbdH4vU1oZKtZZnNyQbIY7y2trBrN2rg50NjXa2PDakGw9/dRz/6mKS0g4y/PwB4vLPIbG1oaLvQP596yy2h/anVNlGYPxLMcvu96OqvtmiOqGhL35+dCQvWSjqrdp3kTG9/IwKIYL6saGa4OIJMUYJK+F7Lo52Ymu4SFof7cu7v6ZbLIY8/NVxPp4cz5bkQsrqtOI12EttGRfnR1FNI3OGheIok2Jro0+ELFyfbHLtc4apyC63rs5XqzHuTpjcvwvZ5fUmyD/hHr2d7DlfWMPEvl1ERFn3zi5Gc95VYUdjUwsLvv/jaNsQTyW1jc18dSTHqDC09miuxSLfMyMjkEklYqzQJ8iNe3oHmEWHGT43QRzIHAdYR4qytY1NFhXFV+zJZPmk2H+kr/yrzbDQt+FEPgtHRFzV87lh1u2qOKPGjBmDk5MTn3zyCe7u7pw6dYrg4GB27drFjBkzSE83v/HvyHQ6HY899hgbNmxg165dhIaGGn0uEJh//fXXjBs3DoDz588THh5uQmBeWFgott6tWLGCBQsWUFJSglxuGhQIBOZHjx4lLi4OgO3btzN8+HATAvPi4mLs7PRSoM888wzr1683IjCvr69n8+bN4rEHDBhATEzMX0pgfrVmrqdZyO4bBlzCQg9wOLPcLDz6g3t70dyqM9pcW9q8L5nQg7zKeralFBttmmxt9Mp8TS06s4uB0Mv96p3RZJer8XVx4MXNKXw0Kc4qoeV3D/Xn6MVKox5rH2d7ZFIbFq5P5mxhDSpvJXOGqiyqnq07nse4WH+2phSxM7WEl+6I4pkNySbE2BtP5vP+Pb04lVcNYJUHKEHlwfLdps5FaiNh2f2x1Gqa+f5YHmNj/awSIxtyWhkef0wvP95oawt6Ymgo37VB9D+4r5cJ2akhf9ToHp1ZtivDSBHtm99z2ZFSRM/CNG47t4dRqfvwrSun2MWTfbFD6PTARL5p9aZPkDv5VQ1m+QOS82pwVdqRGOlNvbaFmsZm3tp63uL4PD86gkfXnOCNcTEEujlSUqvh6MUK8qoauKd3ABKJBJmtDTnlan44XcjjQ7qRVlzHucIaI54s0DsSa8/ihdGRZsk0V02N58nvT5sniGwbV/c2JbNbI7xo1cGhzApW7svk8VtCadHp6O7nzPaUYpNr+nRqPJX1Tazcm0VacS0TzZCmtyeIBfj0gd7IbCW88lOqyTMcF+tPhK8zKm8l5wprSC+p43ReNdF+LvQNcsPLWU5dYwu1miY+3a+/D0NutwSVB3vSymhubRWVC9tvCgznm9Ce+dIdUXx5MMciAXjfYDfe/+2CUXVUSGaZ49bYdb4Ed4WM+C6uyOxsQadj6S/pXCitY8bAYPqHuOPpJMPb2Tw3AxgrBUptJGx85CYOZpZbngcC3xGWORva28UyNbe+vdto7TGcJxP7BfLvTZb5vBZP6EFsl04o5XbXJNAprm7gYrma/KpGI2TEg4OC8OvkQFcPR7yd/xiaQ63Rb8ByyuuNkpvPjIygV+ClDcGVqLxeT87Dv8LnXq8Y6ob9dTGUJVL+VVPiGRLhbeYXV277LpSxL720Q/Lo9giZd+7uSXa5moamlg5/66G0zk/40h1RfLQnk/GxfuRUNIhxk6+LPZtOFRgpgno52fPwzcEoZFKjmHHuMBW1jVpCvJyo17RwOKuc1YeyjegUDMVTxsb6sT2lmLGxfrz36wWjuEFAlpi7d0Ny9va27P5Yyuu0rDmSY/FeHxvSjfVf/8aT6mTcd/yE27kzaGztOBHeG+n4cWTfNJRPzlZb/P2b42N40oxas6DsNyjUA01TC/lVDTz+zUmLa+FLd0Sh0yESrxsqFLZ/fob3/+49PenkYMdXh3PYbhAjCHQXgj/vaC5JbfQIpLlrT+LlZG8SD5kjx16QGEZxTQO1jS1W59OgUA8yy9Ti758dFW4Suxh+/9U7uzPmwwPiOArCIO2LK8+NiiS7XM3SNnqNP+orBFENCTD/u1McyCg3G/MtHBlObKCeSN3wN9YUZA2f2+USlbc3c7GGYILaZlePG8ioqzXhWUptJFwoqbvi5/P/2f4yzqi9e/dy4MABE2W6rl27kp9vHvJ6OTZ79mzWrFnDpk2bcHJyErmWXFxccHBwwMXFhenTpzN37lzc3Nxwdnbmscceo3///vTr1w+AxMREIiMjmTRpEm+++SZFRUU899xzzJ4922wiCiAiIoLhw4czY8YMli9fTlNTE48++ij33HMPnTt3BuC+++5j0aJFTJ8+naeeeork5GTeffddli5dKh7nX//6F4MHD2bJkiWMGjWKb775hqNHj7JixYqrHpO/ysxVrYUqSvvs/sSVh1k7qx/aFh1f/55rto/8pzMF9A1yM0JfJOfV8PHkeKPN9eO3dmNbShF708t4a3yMSE5dptbwzIgIZq85wbBIbxNuKENUyTu/pDNnWCgXy+qZM1RFY1OrVXSEtrnVqKoyMyEYFwcZrTodb02IIbWwBpnUhtI6DR9PjjNSopuXqEIhsyXaz8VIvljgLjKHajqVV8VN3Tw4mVtltWL05PAwvj+WZ+JkVd5O6CQwd+0pHhoczKp9F60iLAw5rQT+qEA3R7q4OeLqaMfZwhpmrj4mVmjaV/NAj+BYfzyf8XH+Ru1cZwuqWfLmWv5rm8YrG9fhVV5IhZMbFSNv5/XQgXzU5IVOYgMpsHiCDx4KOUEeChM4+vzvTvPJlHjqNE2U1WqZtOoIHkoZL9/R3WwgqUegXWBcrD9LtqfxwuhI5qw9iYdCzrxEFZtPForqMw8OCuLRm/WJqHnfnTLrrDuqkDrbS014F6YPDCKvooH/jInmvV/T2ZlaglrTzPOjI6mub+J4TiXa5lZmfalH9nRxVxglUd/5NY2nR4SzfHcmSVHeeDnZU1XfJCLo1hzJNUIMltZpqK7X8vq4aKrrmyip1SCTSsivbEBqIxF/9/XhHEZG+5rcjzAXBdLyJ9edEQP6qM4ufHskVxyzh28O5t4+gTz29Qm2pei5tz7em8X9fQMJcHNgbC9/Xtp8zizc3HC+rdp3kVfv7I6NRKJvMTljZ9Ry+tqWc1TVN3F37wDOF9fqk77DVAS4OnIwo5wTOZUm3Bor92Zyb59AmlpajdpbZ98SgouDHecKazmdVyXC9YM9FCaor+kD9WS/QjCv8nGis6sD4+P8Ufk4McWM8s7VVL6cHexM1h4BCTozIYTeXd2srk0hngqR/+pamA6obmg24VyZu/YUKybFceWlKVM7kVsltigaPjeZVGIUrAkoLUv3LqC0rgRB9U+x6xVD3bC/xgqqGiy2Ii3enka4r/M1adnrFdAJma2EXgGuol8xtPmJKlp1OoZG9KdMrWmLrepYsSeTZ0aGd4hSub9vIO/9ls7Ld3Q3K9by5PAwUgtr6dPVFVsbG3aeLxFVdj2c5Ki8lAyP8hFjMVsbCUq5HQ98pqcbmDEoiABXR45mVzAg2IPXt6RyOKuCvkFuLJ8Yh0xqw89nClHa2zKmpx8Pf3WchwYHs/54PmNj/YyIuNsjS9ojhAF6+OsVf83Z+79dYNHtkaboFp2OiNIslpRn0Pm9LYzITENr78DxqP4UPbkYTeJwMjU2rDuexxwnF84X51kcz+KaRmYmBJsUT8vqtLgrZEz65DBLJvSgq7vC6lpYp2mhUq0RUTnC+LY/38yEYDEWmD4wiB9P64mrBb5D4Te/pZYwZ6iKCrVl/q/29BNqTbP4d2cHO6O28PyqBgLdHPn0gXiaW/Xk2HKpDWfyqqisb7KIIBKeWVmdlhM5laya2ht7O+uxWE1js/jv8XH+JOfX8PSIcBMqipM5VQyNvMQF/Ed9heHvHrmlGwcyyk26OnoFdsLXxYGq+iY0za3ib/IrrXNmTuwXSKSvMwuSwlB5O6GQS6+YUsVcrCGYytsJZwe7q7rvG6Y3w2fg7Wx/VZQ3N8yyXVUyqrW1lZYWU26JvLw8nJzMtxFcji1btgyAm2++2ejvn376KVOnTgVg6dKl2NjYMG7cODQaDUlJSXz44Yfid21tbfnxxx95+OGH6d+/PwqFgilTpvDSSy+J37l48SJBQUHs3LlTPNdXX33Fo48+yq233ioe/7333hN/4+Liwvbt25k9ezZxcXF4eHjw/PPPM3PmTPE7AwYMYM2aNTz33HM888wzhIaGsnHjRpGA/Z9k5rhFrCU8TuVVi+pd7TePq/ZnEe3nQksrvLrlHHf29BM/25tewvOjIyiq1pBaVMMXB7O5Kz4AW4mEhqZWUWL45THd0TS18tDgYL4/lsfwKG8SVKaEjYDYCrV0h57vqG+QG3OGqYyg6YLNS1Qxe80lkvSzhTX8fKYQhVzKUgOlu4dvDsbVUcbC9WeY2K8LC0eEI5HA8ZxKgjwURqiWeYkqGptazBKHP5kURkW9lv0X9C1fVknOneQ8MzLCCMHw9IhwwnyceOr7M8AlLqv7+5oSIwsmBBXmuAHaJxEmxPmTW2Hakhjg6ogERC6JbmU5jD63l9tS9xJSkUeNozNVI0bzy82jcEq6lX//eE7P/WTQ97Nq30WW3BXDvLWmQQnoCc8XJIWhkEt5bWw0S7afx9ZGYpLcFIIxgSw1rbiWwupG7uzpx0d7Mpn++VEWT4jB9YyduNH+4dGbOF9Uc9ltpO2fxaZTBZzOq+bVO7tTXKNpI7LO4NZwL6L8nHl2VDhKuZTDWZX865sTuCvkTB8YxKZTBQAm87esTitC9kdF66u/Sd29+c+d3dmTVoqNBBHt9NGeTIuqgr+llpLU3ZvXx0Xz0+lCXv5RLycc7Gk9uC2qbjSC+C+fGMePZwrEvz329Uk+n9ZbTL7uv1BOmLcT5WoN42L9TVo4DTcFhkFsWnEtnRxlyKSXSNLNEYC36HS8ODoSH5dL763h/DT8jdRGwsIR4Yz+YL/RNWw6WcCEeH8TuL5UImH5ngyGR/nw8pgotqcUm1SVDRNN8V1cr5nYg6WWtbI6LYFuDizZkWYxUH9yeBjBnteWO6ippdWiEMM7v6SzfFLsHzq+YeKofSJ+74Uyo82ABKxuUgTF8z+D5+rPtusVQ92wv8Y64qa7VnNUIZcS5KHAxUFr4hffHB9NUbWGtw3WzwVJYZwtrOH9Xy/QquuY5iCnoh53hZzyOo1ZioE1h3Oo0zQzfWAQ3/6uRywJHH8C4ml3Wonoux4cGCzyY47u4UtRtQaJBNwVctTaZkbH+KKUS0mM8ub5TSmX2huTVBy9WMFDg4O5NdybngGdeO9X80mlVfsu8uH9sXy8N8skQdMRyXSFugl3hYx37urB7tU/EX5oB6MvHKJzWT71jkoy+w3hvZunsNU/hjm399CvVTsuisfoiL7B00lOQ1Mznz3Qmze3mm/Jf2PreZKivC22pE8fGISrox2VCjti/Dux+lC2RcqAru6OvDo2moySOiMfZ8h3KMQShzMrGB7tfdn0E6sPZYucUW4KOyJ8nS1uyIW26g93XuDxW7vhppCZpQHYm1amb33r7MyCxDDWH8uns6t1LqbjBnypoV5KdGCWJ2nxhBhsbS4FoNfSV7TnaNx7oYxXxnQXaTfad410RBcQ6ObIoFAPPt6bSY+ATijkV0apAvrvLxwZzqRPTAtpz9xoIbvmdmM8r61dVZve3XffjYuLCytWrMDJyYnTp0/j6enJHXfcQWBgIJ9++un1uNZrZjt37mTs2LFkZmbi6ur6V1+Okf1d2vTMyXObk4gXEi63hnvzW2ox3x3LMwkIpDYSFt0eRW5lvREk2Fqr3g+P3sTT687g7+pgdhPe3NLKFwctw6sF6VfDFj9PJ3uR0FLl7cS/hoZy8IJevle4nsn9uxDu42xSFRRgzeauZ2ZCMI1NesnbJ4aG4ukkB3SU1TUZJbSeGh5GQ1MLD315HJW3kmdHRlBapzF7/+/f0wuprcQsKuizB3pzJq8KN4UcN6WM1QezifF3sQq3Tozyxt/VwWobX1V9ExsfuYkTuVUo5LZG6ImHBgcT21TB6bdXMOrsHiJKL1Ijc2S7qj8/hg/iUHAv3p3Uh1lfHrMqa/v1jH7M/vo4Y3v5maikCG1J8747JSKaNM2tbD5VYCT7KyT+hPPsTS9jsMqDngbV4vbX8OzICHaeL2F8nL9Z3qVVU+Kp0zTz+DcnTT5rD4lfPCGGgxnl9A9xN5HWDnB1JL+qQWwFNKfiaNhaAODtLGfJhB5kl9djIwG5nS2nc6vFlrZytcZin/riCTE0altNWg2svVsrJ8fz5rZUI7loc88s0teZpXf1YHd6Ge4KOxxlUoprG1n7e57V925vepl4LEO5W0ttLCsnx1NU04Cvi4NZTqn2baZCi+mrP1+qglu733fu7kltYzP/3pTMnb06kxjpY4SqNITVG5oAy/6jlS8TWem2zYiHk4xpnx1lSLiXCdR/+sAg+gS7EeDqeEXn6ojgO6O0jsSleyxC+bfPSfhDCbDCqga+OHgR/3bvtnB8w9a7CrWW935JN9+6mV/N47eG4qaQmfVFgl0LOeW/wuf+02Oov7P9Fc+zoKrBahvOyinx14zMfHdaKQczysT26kA3R+q1zQR7Ks2unx9PjmPd8XzCfZywkUCgm8IqzcHCEREiwmhmQjD9gt356XSh6HcfGhzM6bxqxsb6may3HkoZH02KI6NUTWZpHSO6+zBj9THeGBstotwN/WBXNwU5lfXMXXvKpHjXP9idj/ZkcjirgiVtcYE1qoU721q3DG3dw/3598YUs8+lu7eCe7Q52G7cwO2Zh1GUFNLs7kFa/1tZ5hbDVq9IXFwUvDImmllfHmNsrB93xftT3ob40unAx9meMrXGbBJpyYQeZJbV0TPAFRsJaJtb9UrHdRqW/pIm+l+pjYRXx0YT5qWkTK01ilFnDQ7GXSnj8wPZ7DhbbNXPfTw5nmc3nqGkRmPymYCGXrztvNFzuxL6CSFesdZ2KvifCrWWBz47QlmdlrnDQgn1cmoTDHGlVacv4v58ppD/jOmOt5M91Y1NTPvsd1Hp8YXRUWYFVT57oDcr9mRyJKsClY8T79zVkye+PWnxvZufpOJIVgUBro7UN7UwPtbfrADI1ZoQIzja2ZLS1iXS3oT2QEut5obxZXsfeaUmxho/nRPn0LOj/rdbyG7Y9bdr4XOvKhmVm5vL8OHD0el0pKenEx8fT3p6Oh4eHuzZs0fkavq72oIFC/Dy8mLBggV/9aWY2N8lGQVwJq+a03lV4qZifJw/e9LKRB6nXgGuuDhKee/XC6JSSvuNNuidQlKUNxIJRHV2EQMmIcFjzpG8c3dPXt1yjqeHhxslD4SAZVikN62tOh7+6rhJ8uvde3qyJ63UJFnwnzFRHM2uEhXKbg7zZOInR2hp1YnVokp1k9n+9iUTYiioaiDMTKIK4NOpvUnOryLIQ4EO0DS3mgQMwv2W1Dby8pjuOMpskdpIKK3VGlWMHhvSDWcHqdW+eUO+pznDQtmSXMSAEHeLyYeqei2V9U04ymxNNokCr4KmuZUwHyUVai2fHcgmKcqbHzYfJmLvVu7KOEBI9jkaZfZsD+nD5ogE9gTFopHKxGsSOJyq6ptYdHuUyG9geN3PjYqguqGJvMoGI46uH04Vkl/ZYJIQMSdjfemZXAqe1x3P4/Fbu4lKekICVLgGb2c5/70vltrGJqobmo3Ge36Sis2nCpgQ50+9ttVIJc4cJ1OkrzMvj4lkx9kSk4Ta23f1wFMpF9sMDQNHYe4GeyqJ8nXmQqmev+p0XjU3h3nx5tZUPc/UsFC8lHIKqxsB8HSS8/wm8wF1pK8zS+6K4bb395sE6ub4DOYOU5FSWG1C6N9+vIS/ff9wfzJL1cxde4phkd7MTwxj5Ht7LW4KFt0ehb2drRhcGfI0VNRpOJmrJ/ht35Y7MyFYJFk1d4+G82LV1N48vf60UdBtbS2J9HXmnbt7snj7eRKjvFl/PJ8YfxfCfZzp6u6It7McuZ20w4TGH1VyM+SPkEhAp7vEI9GeW+5MfjUf3Bd72ee5XILvnHI1D3153OI4LZ8Ue9VtgWpNM8eyK3l9S6rZxKu5xNG+C2U88c0Jo3tfdzyPd+/pZcTv8f+NM+qfHkP9ne3vxhn16dTe3BJ+bZ6nkJgtqW3khdGRpBTUEODqSLivE0u2p5lFzET6OrN4Qgz/+ekcz42K4HRbIeudX4wFPc7kVRPt72Lk7wRET/uiZF5lPbvbrbfm0LsLksJoammlXtti1od/NCmOzw9cFNFR7Yt8DdpmFm5I7nB9nzMsFAkSI9+9ICmMXWklJIR6ijGntKWZAdmnGJ52kLG5R7GvKKPW3YuG225nT3QCGxVBjIoNYMn2NDExFtfFldrGJvKrGo3U3QSey5vDPahtbGFZm2iKMJ77LpRyUzcPtqcUc2cvP97/zTLX1ZK7YjhfVMd/fjrLxH5diA3UJ7COZVcS7Klg0eazYrw2tX9X+ndz5912z6+ppcVqgfblMVFmeTjNxQlPDQ8DCRy4UG7CZWluHTfnf4R7vFnlye60UvH5Gl7z9pQinr0tgodWHze5phHdfUS+TMOkiqa5VSwSNWhbrPIOfvdQfyPi+uslenE5BRO51MYkUdQ+vrwWxRXhem60kN2wP8v+smQU6NXmvv32W06dOkVdXR2xsbHcf//9ODhcOynb/0X7OySjLDmWzNI6bgnzIrui3iLSw0Mp44P7epFT0UBmaR3fH8tj2f1xFFY38M3vucwYFCRWyKyR9z48OJiozi58uCtDXODNBzsq1JoWXv7pLO4KOU8ND+OH0wX0DzZNzLRHdn01vQ+v/JxKSW2jmDQwh/5KjPTmzl5+5FU2WCViHNPLj2APR7LK6tlwIt9EsSrYU8mv54oZFnnpHvoGuTEvMRSQoNa0cDynkq+P5PDBvbHc87Fl0vX2iYNPpsRzrrCa+K5uFFVrOF9Uw6m8asbF+lNW10g3L32wKpzz8Vu7UVXfTFW9FoXclmW7LgVZC3t1IuC3n9F8uYawjNO0yuWkxw7i5E1JeN87lqlrjREpQnIwpaCGSrW+9cwcMmrF5Dg6OdjpWzfbzR93hQy1poUXN6eYkHJO6heI0t7OJNgzDJ6HR/mw7ngefYLcaGxqIdzHGbnUhn9vSqasTsuAEHdmJgQz9dPfTTb+vYPcaGnVsf5YHrWaZv59WwS2EhtKaxs5llPJFwezja5peJQ34+ICjFBvwjuQX9nA0rt7UFjVSHpJnThfLLXZJefVMEjlQb22mZqGZnEzDvDf+2Ipq9MQ5KFg9AemySZhLnwzs5/FZNWAEHcm9uuCn6sDra06PtqTKUo6t5+/jw3pxr836efU+Dh/wn2c6e7nzIe7MhgQ4k5yfg1jenXmmTZSf3PHePH2SD7Zm0Vum5peXBdTxFFBVQPldVp+PF0gBrrbnhjEyPf2WSVw/fJQTpsapQPPtqt2m3tvDX+/Y24CWaVqs5tFgWT9kVu6mQ1Ur6eS27VKslzucSrVWnanlZrdGL57T08SQj2vunJs6RoEZFv7BBOYQY1ZIAO93O9djf1VPvdGDHV97K96nuaS7QuSwujh73JN1PRAn0zed6EMGwko7e34cGeGRcStYFIbCVv+NYgKtQZHmZRytZam5ha8nO1xkElRNzYhtbXhRwP0k4dSxqR+XRjR3ZcNJ/KMEO8PDQ4m3MfZCKmkR7NcSo4ZFmg2zR4gCsG0t0hfZ5K6e+PXyTxqe8WkOJ7ZoKcksCZ446GU82tqMQ52toyM9qGmoRlPJzk1DU0cPV/AgIxjlH3xDb3P7MOlUY3aL5DzA4ZSO+oO3qxwIbVULY5h984unC2sEekR+ga5MX1gkFXU7gujI8ksU5MY6cPGE/kiKt8Sgszwt2+Mi6GTox3/3phiUeXUMJ5aMqEHK/dl8s7dPTlXWCvGevf3DcRBZmtW5fDTqb0JdHegXtPCmA8PmPhJD6WMCXH+3BrhzY6zxai8lTy57sxliUuA9bW/oKqBrcl6MaL2RQcvZ3s+vC/WLPG2cE3j4wNwdZSZTapYTQJZQOhfrm+9kuLTlYhxVKi1FFQ1sPlUgUmi71oUV27Yn2N/tDj5/8n+kmRUU1MT4eHh/Pjjj0RERFzVSW+YZfs7JKMsOZZvZvSlqVVntid58YQYDmSUMSDEw2jDPT9JRScHO8YuOyhWtwQlrpYWHa/8bB79M7y7Dw8PDmHsMr3j7KgNx0Mpw8XRDoVMyq/nSsRk0KR+XegV6IqtBBqbW/lkX5ZYPZw7LJRANwWpRTVi1a19Bc7wvB1teH96fCAtrTqq6ptYf0IfjBgmhuYlhpJb0Wix3UpoRRISA4bqYoYmIM0amlrEoMXWRkJsoKuYcBLGfmdqCT0COonjZikpsv/Qeew3b+K21D30y0lGYmtDzaCb0YybwCN1gRyr1PfafzIlnsp6fTIx0M2B4d19jaqFTwzVt9Y0aFt4bUuqUfLIRgISicTs/b9zd090ulbmtOOTktpI+HJ6X5T2tsiltkgk0NjUQm5FA6fzqsSEm6Bi+O2sfvx7Y4pJgD59YBAvbT5rVaGltFZDY3MrDna2vG0m0SQkWy1J7y6eEMNb287zxrgYahub8FTac/8nh3F1tOtQ6fCNcTF8si9LDz9vQwy52NshsYG04jq+OZJrtQUzxFNhdiPw7j09cZJL+fp3PRm6tYB+3fE87u0TiFJuy1vb0vTtBwOD6RvsRlmtBm1LK89tTLbSJhBHqKeSlMIabNoIf/xdHQn2VJhN8AjJhfI6Dd/M6MfsNScs3uMH9/VCaiNh/EcHmdg30KTVpKPK+cop8ZelZmMuGLyeqJxrkWS50ja24zmVZJbWmVSpgz0V9Aq8urb1jjYFb4yLJthTafGeLreSez0qvn+2z70RQ11f+6tjqIKqBnGO/tHWPGHDI7WFiromzhfXkluhpou7wmxLuSXl3BdGR7Jo81kjBdy9aWUGghUh4rof6ObA7T39+KANyWNYvDqZW0lGaR1PJoVT29hMcW0jS3ekMe2mrtjbSU2QQwInorUWuy+n9+WlHy37ZmFtNofgEZAlAqo6q0zNyGhfVm9Pxu/gTsZnH2HA+cNIG+pp6KYi5+YRHI2/BVlsLzyc5DxgJnFjqJALiG2JMf4uJv7VsDV9TC8/YgM78cyGMwwJ9xKpK9ojyAQbEOIuUjX4OtuzYl8m/YPdTWKzHSnFDA7z5MtDOUb3m9TdGwc7KXFdOpFWXMuS7WncFt1ZVKY1bEMP93Zif0Y5cjsb3v/Vclz56JBuPNJGGm/Rn7bzKR2t/dYoIr56sC8Rvs5/qA3bkn9+956eIofmlRzzaopPV+qDr2dx5YZdX7uexcl/qv1lyCg/Pz9++eWXG4HUdbA/O5Bqn921tqg+OypCJClvb9YkdN+5uyf/+eksC9sk4vuHeHC+qJbvjuUyMyHYrJP6ZmY/zuRVi8iSjjabg0I9iPB1JjagE5UNTXy46wK3xXRm2a4MMaB64tZQFPZSTudVs2T7eQDeGh+Ds4Mdd310yGzSy/C8hm125qpXY3r5cSy7gseHdKOgWq9kI2zoY7t0orlFxyIrCREh6Hr3np442NmiaW412zf/9YN9qdM2GxE9zxkWytqjeSZV0U+n9ubjvZkcyCg3uTcnjZrEtEOMPreHhJxT6FpbORAYw48Rg8galMTQgRGEeCr4ObkQT6WcAFdHkaOqb5AbEb6WWxZdHGzRtuiMknH/vi3CaivWMyPDmdgu0dm+JfHJpDB+v1hBc6vOIodU+0rYx5PjkUhg1upjZvnOBGVBgFpNs5Fij2BCkC+0qlpDx8X4O3PPisNXJJ+8N72MZ0eF4+YoY9OpAn5LLRHfDWuJ2CUTerA/o5RbwrzFuS60OPi42HOxrA47Wxvmtf12WKQ3d8cHWG1FNJdYfnp4uPgumtsULEgKw8VByqaTBUT7uxgnpBNV9A12N+uoS2oaOVdUS1W9BkeZnVmRgZVT4onwVuIgtxNbVAyVNtOKa+kT5Ma0m4KMVBoF+3J6X0I8Fdzx4X6LXGUC0vCKAu1rBKkXznO1SZYrqcqCHsGRUlDDuaJalHJb6jQtRPo6EenrfNUIjiu9hr+T/RXJixsx1PWzvzoZdS3M3IZnZkIwP58ppHdXN6sI7fY+8JMp8aQUVOOukIvrHujb9xubWjicVcHqQ9k8MzKC8joNXT0UIgdS++LVi6Mj6dzJwajoNXeYCmd7KXetOGR0LQJKXqeDl388d8Vt5mCKAheQvpVqrZHvl9pIeHtYAD57fqH6y29JyDqOvKWJM94hbFUNoN/8B/mqRkEXN0cC3RxxU8isFvsMx/DjSXFUNzaZ7QbYmVrCotujeOGHFNY/MoAPd2UwLtaP/enlOMhsCGuHIBOs/bj2DXLjgZuCzPq/d+7uia+LnN9SS8X7NcdjKfB+vjEumrTiOgLdHInxdyHav5PYnj19YFcTwm/BlkzoAeiY10HM0b4I09Ha/+rYaFpadai8lRzPrmLlvkzclXKj5MuVFnwM9y1i+5tBYufp4eF8eSib7e3iYeGarPmjqy0+Xc3vrlc73Q3UzvWz61mcFOyf9vyuhc+1uZofzZ49mzfeeIPm5uaOv3zD/pam1jSLL1XCWzuZuPIw+y6UUdfYZFEVRiGzLLlqTUJ3xZ5M5iWqcJRJ2Z1WxgOf/c6GE/nMTAgmv6qBxRNiiPR1RmojIdLXmY8n68mkP96XybSBXYFLqnHmLK24lkA3R1bsyaSyQYtCZsuoaF8e+1qPtLg13IuxsX68uPkst3+wn9UHs3n+tkjiAl3Zfb4Mma1e6QsQFc6Eawp0u3Te74/lsSBJxdMjwtmTVsbzP6SwJ62Mp0eEsyBJxffHcrktxpfcygZmfHEUf1cHnkwKY8OJfO766BCF1Y1W7yHC15lVU3tjI5HwzIYz/HCqwGRsVk/rQ2VDEzO+OMbZwhpR/WzGF8dIivLGQ2m8cL217Twx/i6AvvXqq1/PMfrsblas/w9H37+fJT8vxaGpkWV3PsYHq3cx6Z7/8G2PJI7XSVDIbJn++VFGRPlyOq+a539IYfXBbB64qSsNTS0WVbne2nYeJ7mM0loNJbUaAtwcuTnMCxuJxOr9m4llmD4wiBV7MsT7nPrZ7/QKdGXd8Tye3ZjMR3syxYBs1uBgscXN0JbuSKOpuVV8xqAPBoXn+O9NKbzycyp1mhYOZVSYvb5V+y4yMyGEYZHeVu+hX7CbqPrz/bE8pg3sellzN624Fns7W07mVbMnrYwh4V6icmX7OSnMhZWT49nfljQS5rowTk98e5KCqgZ+OFVIubpJ/M3wKB/s7WyYMyyUxRN6MCjUg9e2nDNKYq4/ns+wCB/mf3daPKajwbu/42wxr29JZVCoB4tuj2KwyoPGphYamlqI9ncx+t3ZwhqmfX6U49mV5m6ftJI6pqw6Ql1jC+cKq/l4cpzJPZ4tqKahTSb5mVERlNVpWXMkF7nUhjG9/HjpjihuDvPCy1nO6ul9jH7/1YN96RXYCVsbCc+MiDB5b4dFehupBrVX3PmzlNzcFDL8OjlcVeAhKPWYM5WPEw52tkZ/O1tUy5y1Jymv06DTQXmdhie+Pcm5IvP3eT2u4WqtQq0lv7KBCrW24y//je1GDHXDrNmJ3CoxCW64pidGeePiaNdhHGEYSznIbHCwk4oqdu/c3ZMXRkfxzIZk7v/kCNtSill0exQyWxv6BbuLfIIeShmJUd7ieh7iqcDHxZ7pbQhT4boe/OIoBdWNRrGH4F9f2nyOf317kpkJwWav96nhYTjaSS2vHQZrM8DdvQN4flOy6PspLubek1v5dv2L3JYYS58X5+JWX81bCZMYOGslo6e+y38H3M1rWRK6ujvy0Z5Mnt2YTIVa26FPFsaguVVn4tPmf3eapChv+gS5kVNRj8rbieKaRrYmFzHji2N093fm19QSfFzkJvfWflxbWnXE+LuwdEea2etZsSeT1KI6PtmXhZeTPW/f1YOtKfpW+4cGB/PKmO5UqpuY1K8LKm8n0orrxPt8av0Zca0crPLA08kee6ktb9/Vw8hPLpnQgzN51SKpelmdluS8GpbdH2viT9urylpd+72dCHRzYPXBbO766BAbTuTz5vgefDq1Nzd18xALVII6XWTntnN1Nn8uc/uWE7lV9AzoxJfT+7L7yVv4cnpfov1cyKtsMH9NVvyRoRpse3vl53NW/c7l3oOh/RG/b84s7evUmht+5lrYH5kfl2P/y8/vqjBlv//+O7/++ivbt28nOjoahcKY8HT9+vXX5OJu2PUzIdgR7GybEsTmRwdalCBVa1ssftaRhK7K24lxyw4anU+QX12xJ5Nbwry4v28gam0LZwuqifHvhIdCLm7CK9VNHUrQphXXklJQQ3Orjm+O5ALGjt/w3I9/c5IVk+JQa5poaW1lfpJK7LU/kVNJtJ8eqePtbCwzW6dpMSsj+9/7enFbjF66eMOJfLPnTS2qsXoPLg52LNt9gQcGBFFWp2XH2WJO5FQyLtafqTd1JdRLyZ60UralmFZ7QJ8wEeR7Dcf+ob6dSUo7wL1Hl/Gv3b/g0KzhpK+KNwdP5aewgRQ5e+grkCGBcCbZaEwBVu3PYlK/LoyK9iW3sp4tyUVM6d+Vj608b21LK50cZRRWXyKZtpVIrN5/J0c7In2djZRkfjxdaAKzfntHGssnxvH8phQDEvIwvjmSY/Jd4Xrqtc3MTAjmiW9PWpwTs748xuIJMXgoZSbHSSuuJdzHiX3pZVbvQSGz5XCWPqElJJGmD+za4dxVeTshl9oQ6ObIotsjyamoNxpfw7kwsV8gwZ4KCqsamNg3kOc2pph9Div3ZvHqnd05k1/DS3dEUadpwd7Ohs8PZnOzytNiy6m5xHJ7CeuyOq04zyJ99ZUQAUllzl7bkkqUn4tR0GXo2AWlzR9PF/LEUBWeSjmldRre3JaK1MaG23t0Bowllf/z0zmmDwwmxr8Tnk4yvJ31lc6oB11Mqo0ncquM2voM1x97qS0vbtaPYftA1aok8zVMsvwRE5J05qp1z7aTdBbG3PD5CfbKz+euGul1JddwNfb/DRp/I4a6YZbM2oZn1b6LPDakm1V/EuHrxEt3RFFSq8HVwY6LFWo2nMgX35uuHqH8cKpA/P3ZwhpmrznBO3f3JL24VkzSjI/zN1rP5wxTmQhfCLZiT6YYe5jzrz+dKWTxhBgjNO2jQ7qhlEs5W1gj+ub2NmtwMK/+fI5IX2ceHBSEs70Uu4J8pqYdZETaAeLzzgJQHtePk3NeYHZDFwoVbibHSSuuNUqItfdn7cdQiH3Gx/lbLLKu2neR50dH8uia4yye0IPTeVVi7LBq30VuCfNi7dE85gwLNVLbaz+u0HGxNczbiQ2PDCC5oJpXfz5HbKArT48IN0JrPTE0lBh/FxZ8f2nc04pqUWubuViuJ5xfsTerrS0zmEn9A2lthZyKehMVRYBofxeW/pLGLWFezBwcTJ+ubmbbTq2t/fOTwkRRGdDPtSmrjvDVg33xdrYXv6eQS7mpmwdfTu9rFSlkad9iDpVyNf7ojxSfLvcerqddyfjcsCu3612c/F9+fleFjOrUqRPjxo0jKSmJzp074+LiYvS/G/b3NmvBzmtbzvH0iHCzn/Xwd+GZUebbCnxc7K1WR45lV5n9THDaQiXHXSFj9aFsPJ1kTBvYlRM5lRRUNRDj78z8RJXZY0wfGMS643movJ3ILq/H3s7WYkBlaO/8kk5UZxfK1E18fSSX9+/txdQBXXl6RDhbk4uZ+90pDmaW89rYaB4aHMzk/l1YtivD7LH+uzOjTR5ef25z5xWQMuZszjAVP50p4K74AA5nVogomKr6JvamlxHmreTZDcl4KOWXVdGza2nilozf+WjHe4wa1pOPNryKfdYFvhk+hUGzVjJm8tt80nsMRc76Ba59BVIY08RIb8bG6pVgBETJgBB3CqsbrD7vhia9uoyAvqjXNlPb2MSjQ7qZ/c38JBV55WoGhXrw9Yx+PDsynFd+PmfSdijcZ3FNIwkqDxZP6MELoyPxcpJZroS1VQu7ujvyyZR4ZiWEWJwTQkLP3DH2Xyhj9aFsi89wRkIQDW0JW8F2nC3m+U0pPGbhvoVxnp+k4vOD2exLLyW/qpEQLyUPtasmCwmEtOI6KtVNfLz3IhmlaqvzwV5ma+QgW3U6nOyluCllLJnQg4cGB5ug6cJ8nE2O+f2xPKv3cCqvGpnUxuq1tHfUho5deDfSiut45KvjTPjoII98dZy04joeG9IN+7akj2HAt/6Rmxgf5093PxcxEQWm1caONne1miYxWG4fqAqBtjm7FkmWa2WXW5W9nsFUpI8Tq6bEG1XSP53amwgf8+vElZg5pMjElYc5mVv1h4/9V9iNGOp/26wh/Ky+o22FFUs+6MFBQeRVNvDloRxsJJBX1WCC6rGEol6xJ5NOCpnov9onSDwU1mOPEC8lYD7mEtC0Y3r5sWpqbxKjvLG1gaxyNQ9/dVxMVhmuHaum9qaru4LF43swwVVD3sJFdBl1KweXPcCzu1bRYGfP+3fPZ/uvJ/n3Y+9y7Lb7cO1mflxU3k74ulxKfliLxeYnqUSEdUdJosamFv59WyRrDuewNblYRNsKsdj64/n8fKbQCGEUbsa/CskxS9furpRxKrea1QdzAEyQVWcLa5i5+hh1GuP1u0+QG1mlaiavOmL03ce+PomDnZT3fktnb3oZb43vwZn8aqrqm0Sk1NaUIhFl5amUW+U/M+d/Vk/vw57zpWYLhJZQJNaQQleKSrkapNK1QPhea7TT5dr1Ru3csOuLAP9ff35XVFJsbW3lrbfeIi0tDa1Wy5AhQ3jxxRdvqL/8w8xasHMkq4I3xseI6ANDcr2ozvoguf1nC0eEE+DmwFMjwpmyypTc/OkR4cz//pTZ86UV1zKxXyCRvs7MviUEpb0ULyd7bCQSGrQtvD42hrd3pPHurxeY1LcLq6bEG6nVCHw3ZXVaXh8bw8/JhfQM7CRWvToKJppadby9PY3m1lb8OtnTxd2Pn88UEuHrRP+Qrqzad5FFm8+28TKpSM6vMVtNSyuuRacDtUafjDB3XsN2K8MK4WNDuuHrImdgN0+xOigovt3fN5BuXkoamvTPzFpFL9zDAZtff+H1LWsZnnaATo111AV345fhE7G99x5WlcsZG+tHrhkegPYVyC1timvmEETzvzvN23f1YOGIcCaZed5zh6koqm7gcFaFkdR0TkU99/UJZOXkeCPOogcHBfH1kVxGdNcr4inktiIyrqRGY3J8lbcTp/OqjZAdq6f14aHBwWZJXWcNDsbBzpZytZan1p3m7bt6Wp0T9/cNNPn79IFBIkfDtpRi3rm7Jyv2ZBrNw1M51ZTWakyqvGnFdaw/kc+qqfEs3mY8d8/kVbNwRAR7zpcxLtaPlzafE6uX8xJV3NmrMxtOFIjH8lDKuKmbu1hpzSits1rh3XA832icEiO9mRDvb8Q39vSIcCMVps6d7E2OWVanZfvZIpNnJ7x/s2/phoujndVrae+oDVFHlt6NBwcF4eQgpT1+60oCvZoGy63Hwnsb2dlZ5LBob4ZorPZko38Xu9yq7PVEep0tquXJdafFdSunop4F359qU9G7ejWxjoK0a8Xb9WfYjRjqf9suB+Fn7h0V+A0FldjcinqTtfiRW0JQyGz5eG8W0wZ2xa+TAy//aDkJbw5F7amU8/it3Xjoy+OmaFi1xur6HujmwLBIb4sxV1mdlje3prLo9igam1rIKderE4Mx8vf+voGoNc3UHTvFqY8+546MQwwqyEAjk7Ozayyrxj/FhOcfRmrvyE12ttRrmpkVLCWloJYHBwUxd61prDkjIYgWXauRf0nOq+HjyfEsNRjD+UkqHKW2PDMygpV7s8jrAEGllEspr9MQ7KngeE4l8787zbL7Y7G1kYjFvQ0nCiiu0fDokG7UaZoJ91GaHPP7Y3kWOZpmDQ6moKqB93em8+a4GA5mllsspi3blWH0XBeOiOCpdabHBH3y8bMHenOhWI2zg5SHbw5m2sCuVNc38dqWVI5kVVj1i4Zmzv/UNDSx+nC22e9fTeHjSgspV4NUut4I3+tpfxalwP+yXc/58b/+/K6IwPzll1/mxRdfZOjQoTg4OLBt2zbuvfdeVq1adT2v8X/K/gzyzcsl5bVGrmf4mVxqw4ncKn5JKaa7v7PRZvLpEeEEeyqY2cZxZHI+X2cW3R6JndQGudQWe6kNUlsJ2uZWajXNPPj5UaPKiodSxqqp8eiQcDizgk/2ZRLiqeTxW0Opqm+ik6OUmoYm6jQtzF17yizxuWFgF+qlZNWBLIaGe/N+m3qMNUJwgYzdRKHDQNVM09zKhZI6i6TVA0LcmX1LCPZ2tvx+sRK/TvYUVDWy6WSBxTGaMyyUpTvSKalt5NU7o0XicImulfi8s4w+t5e7cw4jLy8jp5MPB+OH4jZ9Mm59Yxn30SE8lDJevqM7jnJb6jUtRmorMxKCkNrY0MXdkZSCapZsT6OsTtshafyzI8MprGk0IbI+nV9Fg7bF7G+XTIhh3fF8ov1czBKQT+ofiFxqy/fH8ixKIrcn7xSu5517epBb0cASg2TlnGEqymobaWpr3bwcMvznR0fw0uZzFgm+AT64txcXSuvwVMrFe3htbAzNLa04O0hpboE3tqXqkxdtx/BxkbM3vYxgTyVKuZQGbTNpxXWsO55HVX2TEVGrYJ890JsVezJFlb3nR0caqQJaIxptryZj7buLJ8Sw/ng+42L923io3M1+b/OjN6EDMkvVIjH93b0D8OvkgI+znKPZVWbbLd69pycJoZ64tltH2pNBCknYxChvkvNr8HaScyirgsdvDb1iRy9s/M4V1Fgl/F0+KRal3K7D43e4Hv5DCCevBwHn9SR6v97k6H8m4fWNGOr629+ZwPxy3z3D75lTwJ0zLJQ9aaUkqDwJcHNEAtRrW9iTVoqjzJY+Qe442Nky4r29l0UMDpeIu28J96SoWsPao7lGPljlrWRBUphRy5lggk9+/rZIssvVbEkutkoOHujmiEQC/95k0Cqu0xFddIHhaQcYkXaA4Ip8amUO/BbShy1hA0iaN4XvzlUyfWAQ9nb6ePGhL49RVqdl7rBQXBxkxHXpRG5Fg1F88/it3ejqriCtpBZbiYT8qkZRuKGbp4Li2kYc7KR07mTPt7/ncq6wlieTwrCzlVCm1uJkLxUpHAxt5ZR4Vu3L4nBWhRGpeX5lA6+MieKLQ9liIckwZpl9cwi9Al1NxDaGRXpzV3yAUXJs+sAgtqcUcWukN5/tv8jySb2oaWjhjv9aJnx/6Y4ovjyUw7OjIghwdeCWJbutkos/2dbWZzgH/wixdoVaw8mcKjJK1Zb97lX4hD9LTOSfqnT3Z43P/7pdr/nxT35+f7qaXmhoKPPnz2fWrFkA/PLLL4waNYqGhgZsbK6q4++GtbM/K5C6lhuSw1nl7EwtIcDVkXK1Br9ODnT1UHCsTTmjm6eS6QODmP65qUP//IHeyKU2vPTjOQLcHBjT04+8ygYUclvUmhZ8XOT8cKrQKBHw7MgIdp4vIdrPhfgurjS36owSSQuSwnCQ2lCnbWHV/iyjgMqciomla7Mkk2xOse2zB3qTV9GAp5McXxd7CqsbaGhqNbsxXzKhBzKphK+P5BLt50JmmZrZt4QwbtlBi0HDkrt64CizZcYXx3j9zih80pKp/GQ1/Y//ik9tOfXevhyOH0rV6LG43zyA/RnlnMmv5pGbQ5j4yRFU3kqeTArDr5MjBdUNpJfU4aaQ4epoh5eTnJ/PFFFap2FAiLuYXFo8oYdVSeZXx0bz5tZUxsXqFemi/Jz56nAO3x3Ns5j4eGVMd4tcRd7Ocj57oDfHs6vIraynpNb4eiwlhoTrWTyhB66OdhRUN4hcCEKia9OjNzH2wwNmFRPbP5uP9mTwnzu6tykvVqGUS1m2K9OkAv2WAcppVkIwP54pZHiUHt319l09kEn1LXISoLmllYwyNW9tPX/ZKkjC31dOiUcHSG301eXbPzAORE3U7SyoyXSUhFuQFMaC709RVqc1q5j37Ci9w00uqOa3cyUmycSVk+PZklxIfzPPbHtKEc/fHmWSNGjv2PsEuTE/UYWtjQ0V9Vq0zS14OdnTK9DV5Jo7MmGNuxJloCu1fyKX0fUIpq5nwuh6B2l/ZvLiRgx1/e3vmoy6knksvKP/3XnBYlFm5eR4TuRUEuSpMEpUXa3qnpAw8XKy56nhYZwvriMh1IOsMrWY3Hn+tkgC3Bx5a9t5sz450teZ9+/rxYXiOmZ9aZq0Egok4+P8cVfI2XgsF/tjRxhxfj/D0w7iX1NCpb0Tp2ITUN53N+nRfclWt4iKxY8O6cbzm5Kpqm8ySqQIccWQcC9u7+FLYbVGTDh1drHn6MVKegZ2Yk96KZ5KOYFujpTWaXCU2RLf1Y1tyUWiHxNMiP8+mdKb0lqNEQptfqKKr3/PNYlDFk+I4a1t53l8SChyOxuxwGMYs0htJHw+rTc1Dc1GSbPpA4PYn1EmXl+Il4LnN6UgtbFhUKgHkZ2dSQj1RAeW55GvM4vu0PvZzp0crM+5tgKqIERzrTa8v50rZtrnR6+L3/0zlMwEu15Kd9fT/szx+V+36zE//qnP71r43CuKPHNychg5cqT476FDhyKRSCgoKMDf35Rn5Yb9fe1atZ6U1DRSWNXInrQyA4narkZk5SU1GhRyKR9PjmPpjnQj57sztZTu/s6E+zoxOsaXcrXWiGxz2sCu3NcngOxyNUPCvQhwdSTYU8HH+/TJgVBvpUkb2QOf/c4nU+L5/ngej9/aDZmNDaumxLNyX5bYduahlDFjUBCDunnwys+pZu/NEpT9tXHR7E0vM7oPRztbfk4uFKtkCxLDCPVWmm3N2ppSRH5lA4NVHvi7OpJVpqalVWcVDi6zkZCxbT9bi3/DffQsPEvzqevkTn7SbezoM5T3GjwprW9mSXwP5n6nTyismBTHsexK5g4LJcLXmbcNWrPmDFNxrrCa6vomlu5IF8+7J61UhMp31HZVVd8kclrNT1JRqdaSGOnNd0fzLLZdhXobQ9QFlFqvAFdcHe14+cdzRpXG/RfKGBTqwcyEYPxdHXh7R5pR65/h9ZwrrOGjPZl8PDmOT/dfFNFEr4+NobSmscOWMKFtbl5iGGptM6fyqtlwIp+S2kbGxfrzr1tDcXGU8t6vF8gorWP6wGD6BbuRXlzHt0dzxaBz9i0h+kRUO6RMYU0j0wZ2NRucCW2A7S2tuBYdiBt5O1vTFg6hxWFmQgiJkd44O9ghARMOrY5aVgurG8RgvD1h+sBQDwLdFFSotSz64azZOfH2jjTG9PLj9S2pRq1ar205h5ezvdkWMEMofWlNIyW1Gmoam1HIpEjavnMF9RIRoSSRwIc79cSzwvN++64erNybZZJc+yP2TyScvB5Eq9ez/c9NIWN+ooppZgoGCxLD/jEbBbgRQ/0v25W0YQjvaJCHggfNzHu4JCzy8FfHxb8JqnuCMMzMhGCz/mZ+koqVe7OQ2khM6A6q6pvwcpLTqtNxIreSzacKGRTqIa7nHk4yElQeRuu74DfSimvbFKFKTfzrUyPCkNpIqKxpIHvtZu5RpzDxty04lJdSonBlm6o/W1QDcEm8lbH9uvL8jnTOb70gtpLvSCmmUq0VUdRV9U3i9Yd46eOKHWeLyS5X89IdUWSUqCmv07BiT4b++g6aFhgfGhzMcxuSza5bq/Zd5IP7Yvn84EUm9g1kTC8/FG3+fOW+LLNxyKp9F5k+MJicinr2ppeJyTPDJFefIDe8nOzxUOp4956epBTUcK6wxiza+5YwL3oGdKKlVYefqwOuChmVaq1VwnelzFbkd5KA1e9eLFOL/74WrUAFVQ0s3q5XBbQUZ/0Rv3s9W+bbo5v/SX5FMHF8fjp3TeOcG2Zq12N+/BMoIa6XXREyytbWlqKiIjw9PcW/OTk5cfr0aYKCgq7LBf6v2Z9d1fuj2d3daaVGPFHW0BfDu/vw4MAgzhfVGiEqANY93J/cigazTvOLab2p17bw3q8XjKp/DU0trD6YbbXyJ5HAnrQySmobefmO7rz/2wX8XR1EdNQDN3Xl6fVnrgjKnhjlTb9gN3IqGsgoqWPn+RImxAUQ5uPEgYwyvj92CSmyeMd5Bod6mqBIBCRPUY1eEvn1Lalmq0ghZbkss00j4JfNOGReQOPSiZKho/itxxAUSUNYdTBXdDpzE1WcLajWk68PU2FvZ8N7v6UzY1CwWWj9J1PiCXBzZMS75qH83s5yXrsz2uwm8N27e5JToaZfsAcncqsIcHVgw4l8Ors4cFOou5h07BPkxuO3hqKUS6nTNHEmrxp3pZy5a0+ZbT8QoO5CFVEIHoVKqI2EDlv3In2deWxIN7xd7Glt1fHMhjN4KOU8ODDI6F6ElrCkKG8q1Fq6eihJL66lubWVx74+abYtQfjNqBhfDmSUsyetlBdvj2LD8TxO5VUzc1AwEgm8sfW8CVIG9MF6dnm9Ed/UgqQwdp8v5bODF03uK7KzM19N74sOxEApvaSWuz86ZPJda60e0DEyakwvP1792TQhZlgx7QgB8+2sfkaJaEvX1t4q1Voyy+qoUGuN+KzmDAvF1VFGiKfSpMXP0MwhlAznUmKkN6PbVcx7BLjQvbPLVaOB/smw6uth16uqV6HW8t4v6SYt4NMHBnEmv/qqWjgN7c/0uTdiqOtvf0dkVIVaS01DEzvOFvORkBwxsEhfZ14fF02Ip9JoPbK23j48OJjdVtbzQaEeZJapGRXta8JvKJHoKKtrQiGzNYnFIn2deXRIN1padXR1dyCjtN4oLrscPxLl68T6E/lMiPenqFpDem4Zuh2/MDH/KF47tyGtqqTc3YeG0XeQmTCcN6pcOV+qpk+QG9NuCjJpYQM9RUJ2uZqlv6Szamo8bo4yLpbXc76ohqzyesbF+jHji2OXdX1vbk1F5e3Ey2OiuOujQx22sY2P9WNEtC/TPz9qFd0t+MBZq4+Zbb0fF+vHxH5dyG677u5+Ljz+zUmrx2pu0WFnKyHMxxmFXEp+ZQOLNqeIsVN7BPKzt0UQ6KZX5+zou2Nj/UUE27XwWRkldSS+s8fofoSYqYu7I/2C3Qn2VF718QW7lqiUfyK62ZKpNc0kF1RzKrf6msU5N+zPt38aKu9PR0bpdDqmTp2KXH6JjLSxsZGHHnrISJr4hizxP8f+yESvUGt5Y4sxqqhXgKuRJL2hBbk78vaONGL89XxB4+P8xcRNS4uOFe1alEDvyCrUTSay7E98e5J1D/e3ivR4Y1wMdZomhkV6MWv1cWo1zZSpNSI6JTHSmwA3h8uS+BVMQLBsTylmUBuEfWZCsFFCRSCEfntHGmN7+Zvd4Ku8nejcyR5neymL2ziahCrSzxv3E7V3C3em7ye4IIMmpRO7IwaweeADDJl9H/9anwJq8NieLiJQBEj3k0nh3KzyxN5OyrGcSh4e3I23tp03O0ZLtqfx6p3dLd6/u0JOU4uOZffHGsHJH7klhE0nC8ivbKBO0yIix96/tyeZpWoq65t4a3wMF0rrOFtQw6NrjuPlZN8WBJ5nYt8ufP5AHyrrtSbPdf53p1k8IYYTOZWiRPK4WH/2ppeRUVJHZpnaLKJJqOoKz17T3MqOlCL8XR1JK65jVkIInk5yI+JxLyd7VN5OLNudSX5lA4NCPegT5EZydjUAQ8K92J9ebnQ+4Tfrj+Ujt7PhSFYFDU0t+Ls6Ym9nS01jkxGJenukTFd3Bcn5NTwzMhylXEpuRQOOMhtuCvUwm4x6ZUx3UgprjAKlhSPD2fDIAJ7dmGy1etK+ynI6r9oiwuTZURFIbSUmfwdjYkarCBhvp7b2zhijlsHLqew0aJuoUDcZJf4E5aeVk+NpaGrCFctrlTmEkjCXssvVJEZ589jXJ01+d7mJEnOcUH8Xwsm/C1/V9arqNWhbWH04G9czdiaIu6r6Jma0U538O9uNGOp/y8xtdNsLRoA+rpj22e9tZP+X1iNr622YjzMrLMRaghDHuuN5xPg5s3hCDOV1Wo7lVIoI3OdGRZot/s1LVPHG1lSkNja8fXcPfm5TuhPW9NN51Tw5PIypn/5u8tvpA4N4c1sqKyfHk+DnyGfz3mbE+QM8lHEEJ20DGW5+5E6YRN4tw9HFxiG3s8FVJuV5bQua5lZaWnUW45UVezK5u3cAq6bG83/t3XdYU2f7B/BvAiSMEFYgbGUFBBUElGId1ao4Wmu1Vvu6q7X61vZX7VBra9fbaqsddlmtq8O2zlpbRaUu1DoZKhsFWTJEdoCEJOf3B+aYkAEq2/tzXVzvCzk5OXlCObf3cz/3c7WgEoeSivDtf0IR4GyNeoUS0voGbJgRhjq50mAMmlFcjb5uNnh/fBByy2pxOrPU6P3sekkNACClsBqP+Tti6+z+uFZifNOQjOJqdlLMx8kKgS5CZBRX48Uh3gjtYYcVfySxvwtD/R3Zc6mrxD3sLJFXXosr+ZU4lVmKI8nF+GVehFaD+/zyOoMVyAK+GXs9Ro+1NoeNpSlEAh5Ka+St0qBb3++rehfgQBchHvN3uqfzGbq3teZ9ritWNxvS9L2odcX38jDrCgmo1nZPlVFz5sxp0XFbt2697wt62HXGWT1Dms7aiQQ8fPOfUJ0Gy+obbG83G2SWVOuthJn5SA/M3nZRZ4bI2CzXirG9jPZEGCIRITajFPOHeMPZhg9TLhcJuRXs0qtlYwIMViQBwJbZ4dh0Kptd7qXZG0E9a2aoUkfdO+C7aaF6K0U2zwpH9NVCzB/igzFfnUJAQzleq7iMkDOHYZ96BQpzC5QOi0L9xGewyzEIO67ewjNh7kZn/Ab7iXC1oBILh/ogr7wWUpkSQ/0dDVY+mXI5OPDKINysqMecbbqB5bbZ/VFWK8fuuHz0dbdBgLMQPewtsDehAD+fy9WqRhoVKMbYPi7YeSkPwe428HcWwsPeAtvP52JvfAFMuRxsmd0fHACpRdVgGMZow3Z1Pwt1dZqzjTkOXC3E3vgCthm7TKFCamGVTq+HxibkgfjqaCYe83eCWMiHs9AcOy7lYZi/I5IKqnQq1TT7Zax8shcW/ZqAxSMkWLk/GXaWZmxfLPVz1LOe28/nsn0XjM7I3pl1rJMr2f9m1D0VVkenYfmYANhZ8rR2inzniV5QqBjM2Ky7Y+H2eREIdBGitgWzJ003GzDUL0jWoERiXoXWNbwR5Y9gdxvYC+7+41ndE6KpTTPD8enhNIgEfKydHAwGaPHMTnZpDV7anmDw9+Hbaf3gJdI/o9pcX4yXh/vi62PX7quCydisqUyh6tDKqM46o9vas3rdqWcUxVBtrzPFUIaqBb+cEoJV0alwsOJr91xqUgnLN+Mgv6wOyTerkFdey07eAcDv8x/RirU0qTcDMTPhGqw8jgoU47kIT3x6KF2rulpszcfWf29gf+JNHF48BC//msAuVVffA8cHuyCzRKpTcXXy4jW4nzmKOUXxsD55FOYNMqQ69kS0/6OIlgxEpsgTga427D0WAGY80gPDApxw8Goh/J2t8fquKwbjlb9fHoTbNTLE5ZbD094KG2Oz2Pf26gg/SOsb0MtViCU7rxgcl4+f7o0J3/0LwPimHprxzbqpIfBysMLqQ2mI8LJHLxchu4mMps+fDcbHB1PZmGJD7HUM83eCRCyAg4Cvk8ATCXhYNbEPdl3K19uk/uDVQvx1uRD/LBmKnqK7yep7qUKNzbiFmXp2Pf5scjD2xOfjMX8nBLkK4eskgELJPPCkhqH4YOvs/hgW0LJk1P3c2+5nUqY7VTd3p/dCupZ2b2BO2l5nCqSMkcoUyLolxdI9d2/6qyf2wf7LN9mGm5rLsEqlMvzvqd5464+rWrM/u+Py8dbYXnCxMceHf6fq/CFtruH1qol99O90MjMcB5MakxdAY3LIWWgOK74pnvn+LF4Y7MUmDvQ1a37lcV+421ng3+tlBkvZP5oQhBX7ko2Wg1ubm7ABoeY/8I+lFSPr6nV8YXIN9b/8Cs/UBCh4PBRGDkPJ2AmoHD4Ka89o984S8M3w0q/xBgO19dNCUVnfoBXQLBklwemMUv1LwO7s0ne7RgZzM1OtwPKVx33RoGTw8m8JOs/bMCMMDQoV/rx8EzEpxWxAdyS52GBAlV5Ug6ESEfydhXht12WsmtgHy1uwPDLQRYj3xgdCKlMAAFZFp2F4gBO8HQXwtLfAol8TdJY8qD/7p4JdITA3wenM28gpq8VAHwck5VdpLSPUl2RcOzkYqYVV7BJPYwmzEA9bvPdXMhwEfHw6qa/OLjfqZKynvSUG+YlgzTfDNI2AQd3P64uYTNyWytg+VKZcDoTmppj/c3ybBBf6Eganr5Xi1d8TdBJvmrP1RpdM5VeCb8bFEImjTkDcXKB4raQaUV8aTpoeenUwfJ2s9b6X5pYO7lwQicnfG94cwFhz7eaC/o5sONlVm13ej7Z8r13lnktaprN8ns0lyd9+ohcqaxtQK1cgs6QGu+PyEd7DDs9F9MAn0Wno5WqN0UEu+CImQysOSMqvwhB/EXgmXFTXK7R6Rql9/mwwzEw4eqtB1UvfJWJrLBzqg/yKWkjE1uyGMyIrPhaP9ENCbjlcbBobYTfd4OWb50Jga8nDqcxS+HHrYRF9ALbR+9H/egJ4KgXKgkLwg1M/HPSLRI6dq9Zz1ffY+gYFG3eo39/aZ/ri9d2GE0kfPBWEBb/EYdXEPnpbD3z+bDAEfBNwOBy9j2+aGQ6RFQ+3a+XsrrvTI3pgsESktQvvi0O9cfBKIfLK67BiXAAcBXzIlAwm3Lm/64sZl4ySYNfFPOSV1+H1KH/Ept/CL+dz9O6Cq8nQ7nrqz2pvfAFWT+rDLr0D7m0TiryyWpzPvq23mvx4WglilgxBSbUM7+9PaZVJjbIaWYsmtYy5l7/3DzIp09Y7tban7vReSNdCyahuqLMEUs1R/8P146f7YP7PcRAJeNg8KxyHkooQ7GEHByszlNbI2UBp9cQ+SCuqRm83oVay4uXhvrDkm8CEw0F5rVwneGpu/f+8wT0hNOdp7XSivtFGBYmx+s4ywheH+KCPmw2EFqb434FUjOvjopXkUq9r97S3RH55LXydBNgTX6DTIFRty+xwiKz4eHr9vwb/+O9eEIlauQLfHL/OVgu5q2qRteEnuB3Zj4F5SQCXi8pBjyFj2Dh8wg9AntIUb43ppbd8/vf5EfjgL92EHQAM9HEweK2bZ4Vj6Z4rukmbWeHIvlWDDbFZePfJQLZiqIeDJeJyK3A4qahFu7AsGOqNK/mVBnf9WT8tFOZmJqhvUMLNzgJ74wswurfY4HvRrIz6fnronc+2Bj893x/1DSp8+c/dnkKvjZLgVEYpG/S98rgvruRXwN9ZCC6Hg6SCSnYZoXqMxEI+LuVUGEwyqhvLf/FPhsFZ03VTQ+BgxYO3o4CtAAK0d7nR1xPrrXG9YMkzwcTv/tWqjGqaAPrgqd4IdBHi8c8Nb8vc0uCiJTOGLZ1VUwc8hqrF9r30KLxEVmwQ2NJA8WZFHeb9eMng78OmWeFsU9Z7vfYN00Px4n0k9VoyJsYqzdqyOulhmwVty+22u8o9l7RMZ/k89VWOqyfi8strMbq3M5bvvbtka+Fj3jDhcvHf7fFs9a+++/n6aaH48/JNzIjwRHltA6z4puzudgO87PHqCD+YcDmIz6kw2J9qsJ8IwwKc8NXRTIP37W1z+iOzuBoutuawMDPVStZ8OtABFn/vh/DgX7CPOwcOwyDZpy+UT0/Er66h8AsLNFq1PlQiwtg+LnjymzNaj302uS8YGO4L2cfNBtdLa/Dz2RydBuIiAQ8vDvFBpI8DKmrlqGtQ4QuNuPC1URJYmHEhMDfD8bSSO8/hI7esFsfTS7Dmmb5QqhhcLahCVZ0cvk7W8HMSoK5BiXNZZahvUCA6qVir6l99D5TKlfB2tEJxZT2kciWG+YtwWypHblkdrPmmcBLyDfamaq731wdPBRnsmdiSKtQyqRyLfo1HHzcbnYrwQFchVk/sg/FNPgfgwRP9Nyvq2GszdO82dL33cm97kImK7nQffZAYipAH0e49owgBGv+Af3ygsRS5TCrDl1NCIBLwUFQpw8mMUmw8lc02GR8ZKEZCbjmCXIUwNeHo7Hy3cHs8O/vz3ABPbJ0djjUau8/1cbNBkKuN3gqduYO87sz6FGjt9qIurS4or8PrIyUwNW2sTFp9KI2t1rldI9Na215aI8ee+Hw8E+aOAGch+KZcXL9VAxMuR6dH0etR/uCAwcGkQqO9A1KLqhDWwx7PSawRlngCFp/shfD0CYSqVCjtPxA/D1+OAUueR1oDvzH5VKvEgqE99PbOAoCvjl7Dy8N99Qaorzzuhw/+StH7vM+OZOCHmeFY8UeSxnuQIKmgEg5WfJTWyLH/ciE706euYDLWj2tahCf7vYedJTgA9sYXYMFQb62qt9IaOb4+dg0zIj3BNzXB1fwKDPYTYdGvCQYTPXMHeWFPfP6dMvICZBTXGOwdNvfHS1g/LRT9etjCzIQLqUwBpQow4XDw4YEUvDLcjz1+4WM+8HUSwNy0sbGjvtJ19WsP9XeEk7U5YpKLtfpMSe7sRFhaXY8P/07R6fHx1rhemL7pPEQCHrtzo+b1vvp7ArbO7o8DrwzCrWoZPj2UzvZU0PTNsWvYNCv8gXYou5cZw5b2P9LsCdH0mgNdhHC1tdA6d0v7MbjaWhjeMS3K32gQZW/FY8e9qRVje8HD3sro44aCzZaMib0Vr9V3pmuJztKvqr20xQ6AhLQlzb+V+iYm+rrbws3OAimFVUgprELyzSrEZpQCAJ4Jc8fXx67pPe/Xx65hqESEnLJa/HIuFx9OCMSEfm7wdbICl8PBexoVLvr6U2UUV+N/E4JQUi1HsLsNtpy+ofd1Pj2Ujgn93FDfoMLV/NtYHSqAU8xJWP+0H1avXgRjaoryiEE48tJK1I4ZhwxYNSY5iuXY6iTA61ESvVXr6nusnZVulUxmSQ3q5SqDO91a8kzw9bFreH5QT1jxTdn3NSnUjW2WfuDKTVzOr8SsgT2wYlwA+KaNy9PLpHL870Cawc1Slu9NQlSQGLVyJcJ72EHJMHjl90T2+HmDvfBGlARz7rwnzfv2Z5ODsezOhJ8pl4MBPSNxIbuMrXoeKhHdd+8vS56Jwc07WvI30N6Kh/8O89V7/1t+ZzJMn48Opj5QMuZ+Ex/3cm9T/1tEn5Zcf3OxQ1e6x6hUKqM7J6oYVftfFCEtxO3oCyCdX5m0MbFTJm2cYdO8Waw9kgFnYWOj6xd/iUNJdT1eGOyFaRGeSCuqwvhgF7w1NgAmHI7BoGfL6Rvo49aYcCqvbUBUkBhrJwdj0XBfrDuaCQszLv586VGsGNsLYiEfgS5CfDY5GIeSiyAS8HE+uwwbYrOwYl8SNsRmsTOBt6Uy2Av4eH1XY9m3UsWwTZEdrc3x8nBf9hpGBYqxbEwAYjNK8dquy/j62DUsH9P4envjCzBUIsLaycFYO7kvbpbXYc3hDOyOy8fzg3rqfU8vhotR+sNPcJwxBWNHhsL11f8iM6sQGyYswvFjCVi15Cv8HhwFE0dHreSTh52lwRvxhewyNjkW6CKEKZfDjkV9g5EbeHE1FEoVFg33xW8vPIIlI/3gYmMBT3sr2FvxIBLwEJNSjNXRaRjsJ8L4YFd43mnsro9EbA1fJwF7DbVyJSJ9HDAx1A2xGaVYuT8ZsRmlWDYmACMDxWxAGZ1UhFq5Cp81adiu+V5+nNMfQnNT9HGzwaroVDZQfCbM3WCS7utj11BcJcMrvyVg8+kbkIit8eflm3Cw4iO/vBaBLo0zXKGednCxadweOayHHbbMCtcZx0PJRZgU6o6VfyZjsJ8IQySOyCtr3Cr6/fFBGOwnwvK9V7D8j8btmj86mMr+dwHcbeL84lAfnd939e/Y0j1XMf6bM6iobTD6mXE4jcktfVoSKKkTQZq/+9M3nUdiXoXOsep/OOmjmfhSB296r2mc9jU1FyhqjhsAhHjY6nwmW2f3R7C7jdH3Cdwd90DXO891FWL7vAi2eXZzj+vT0jEBGsfFzdai3YLXe7k2Q5r+Xe8K2nucCblf6r+VmhMTmn+LF26PR1SQGCJB4++y5r3fWByQUVwNf2chPO0t8XQ/V8gbVBjqJ4KDFR/nsm6jpLqefY3Xd13Reg2g8f6tYoCKWnmzk04uN7ORvXgFFr4+FX2HhMLxkw+hFImQ/dm3OBiTgCOf/wjMn4/NmXXYfDobTtbm2Dq7P06m38KBq4XYNFP/PXb+EG9sOt14PxcJeFgw1BsfTegNCzMThPW0ZWMR9T13VXQq+rjboFau0HlfE0NdMbq3Mz74KxWv7bqMkxmlmBjqht1xBaisU+C2VIbrt6SYtfWi1vg3HZuM4mqIBHzsic9HZX0DFvwSr3X8kp2XUSNT4uvnQvS+J3XcKRFbgwHgJRLghZ/ikFJYhV1GYsWeIkujsdbpa7cf+G+0oftfTwcrnM8u0//5d9Ckxr3c21pjUuZ+YoPOSKECu9lA09/Pg1cKoehe81Okm6Flep1MW5WY309zP0OVFX5OAsy5c2MH7i4fc7ez0Jn9e3m4L8zNuLhVI29xj6DBfiJsPp2N9dNCUS1TYNOpbPZ8b0RJUFxVz+5A9yANzr+aGoKCijpsiM0yWKr+5ZQQeNpboK5BhYs3yjBU4ojUwiq882eyTu+AGwW38dztZMwvvAC7o0fAk9ejrHcIvnUKxwH/QSgS3q0EWTu5L8xNTeAk5OO5H86z49KSbYldbcxRLWuACZcLa74p/MQCcDgcvPyr4QbQK58MxObT2eAAGHtnq2f1mM4f4o3oq4V3eh1I4GDJw0/ncjC6t7PevgtbZ/fHyYwSjO7tjKJKGW7V1MPHUaB3FlRd9Tbn0Z4oqZIh1NMWT3xzxuDyyAn93LB4x+V76h1myuXg9xceQXpxtVYJ+pbZ/SHgcXE2qwyRPg4Y4OWg9bzGvmc1uF4qRXphFS7nV2JSqDvbP0pz/IZIRPj+pG4yzNByuRulUq0ldvoapao/65Lqep0+ak5C8wdaBnY/5ectLXdv6ZKp++1hcL/l/er3baxy5l6ba3fmvkz3e22dtfF5R+ksy7pI6+hMn6e+3pqaNJeka977m4sD3hsfiJ2X8jA+2BUVtQ34/mSWwYofzdcA7jbm/uLZEAjMTbHij6S7r8MwCCzJxuj0M5iQdQ6exTmo51ugdMgI/OISipuPDsPw/r5a8cMrj/tCKlPAx1GAc9llSMyrwKRQN1jyTOFsw0dFbQPyyuqQXnT3HuvrZIXle5P0xoyLhvvCxsIUHx1I09uTUP0+Al2EiAoSN/a+0lMtro49ZjzSw/AGFhpjo/7/zfWKHBUkhqxBifHBrtiXeFNnA5XPJgejoKIWhzSW9AHQ22dq+dgAhHra4VJOOWYZaDL+6eE07P3vo63S76fp/a+zLlNr6b2tNa+/tTfeaG/qsWi62cCe+Hw4WZvjl3ldZ8kh6VqoZ1Q31NqB1IP8w8PQDWHL7HDIGlRsALDrxUi89Fs83ozy10noqIMq9c52xgKCPfH5mBzmjuEBYqQXVcPNzpwtidb05ZQQ/O9ACkpr5EZ3Q9m7MBKTDazTN+VysG5qCN7/OwWfTOqLNYfSje6+Mu+nS5jxSA9Y8hrHTJ3kMlM2YGxREubdvIiAc8dgVluDMr9ekE54BsWjn8TKq/VGd7u5VS3HIY3eTMbez6aZ4Ui+WYmfz+Vo9ThaONQHHx5MwXtPBuG/eoIydfD51theBpuabpwRhtTCKvx8LgefTOqLXXH5sDDjIirIBV8dvdvse+FjPujlLEDSzWq2HLi5wPmjp3tjzeF0nM8uw7LRAUYThK8M9wXPjKuT2Grpa6h3PnxxqDcOXClEfnldY9PXgiq88rif0QTF7RoZnt92UafHxs9zB2D9ies6PSoAwwFP0yBJ3/WLBDyseaYvbkvlOjse+TgK0M/TTucaWxoo3U8i6F778rQk8dMZA9170Za9ijrq2jpzgq0jdKbkBXlwHfV5Gprwy70txbDPDPf+U0/EiQQ8fDKpL+b+eKnZOOBkRgkGeNlDplAZ3M13dXQau2zsg6eC8Mu5XCweKcHOS3mNO/e5CLHmmT4oqqjDN6t/xeiMfzE641/0qChCJd8KFSPGYIs4BMHPP4slf2UYvaYfZoYhMbcCChWDzaez8f74IOSV17KTLU3/cSwRW+OFQd64XSszOAmYc1vK9nTaE5+P5WN6sS0Y1GP367wIvGdkR8GhEhGGB4gx9QfDcaB6/NdNDcHHB1PZz8DY8dvP52JGpCdsLXj4+tg1nX6lj0kc9U6eiQQ8TA5zx5T+nuCZcsEwjZVACqUK/16/rbM74aHkIhRU1LXpvbIz3g/u5d7WGa+/o5zKvKV39+Vf5kZgkN/DNRak/bTGPZeW6XVz97JUR5OxJTZrD2egok6OtZP7YqCPA7hc4IVB3nqX4Xk7CpBeXI1jaSVay+I0zR3khdIaGZaNCcDJjFJM/eEc6hqUWHM4Q+/xG2OzMCnUHQAMLvfaMjscQgszo+XPHA4HJVUy3CyvM1qqLpUrEepph0F+IvxwOgsuViZYZpaHVdFf4eI3M7Dul3dgkRiPb/qNx5HdxzFm9lc49+wLYLx8jJ5XpQLOZd3G4pF3+xoZej/rpobAhAsk3azSSpbMHeQFcBioVAz+SCjA99PDDJaQbzqVjcJKmd7r+fKfTNTKlY1bEh/JwKJhPpDKlGhQKjGhnxs+eCoIE/q5wdbCDPUKVYuXFmYUV6OkSoZ/r9+GUsVgQ+x1g+Xqb472h7+zNS7eKMPW2drl/YN8RXg9SqL3eXMHeWHN4XS8NTYAO158BFFBYtwolWKoxBFDJCKsjk5DbzchZAbqlNVLf3wcBVg3tZ9OuXaopx3+O0z/766h5XJNl7NpjpF6WcKbowMg4JthdXSazvKBmju7Bza9xpYGpPezjEuzL8/JN4fhl7mNwZyhxEZz12R0SV8H9WO416Vp9zom7el+ru1el04SQoyTyhTsP4iHrDmO6ZvO4/S1UnYH2Mo6hdE4pLRGhgVDvbF4hAQedhZYO7mvVr9CzfvgxhlhOHD1Jqz4piiqlBltfaCOkSRia3jaW2JCPzek3KxETEoxuCol7C6cgemrr2LwiDD88cvrmJJyDP/2DMHbL67F0RNX8L9nl8LimYnYdKkIQONSeUOv90VMJgZLRJCIBZCIrZFbVsve89S9lTTbKFzILoOtpanB822MzYIFzxTv7k/GqcxSLB/TS2spnPp98Uy5zS5nLL3TH9TQ+EvlSnz+bDBqZQq8GeUPa3NTvceLBDwsHR0AD3tLrHwyEFvP3ECtXIEhEu3lhDEpxcgrr9V7jtIaOeoUKuSW1WLej5fY35eMkhp4O1rpLE2MSSlu83tlZ1ymdi/3ts54/R0l1NOucSw0/mZsnxeBfp62HX1phBjV8RE1aTP329xPKlPgZoXxBI1KBVwprMBroyQok8oR4W2P1Ye0GyGOChTD094CMx7pgd5uQpzPKtPbmPL0tVt41FekNUNmyTMx+vqfTOoDkYAPK74JpDIlhOZmmBHpiSBXGyiVKljyTdGgUOH5QT0NNsmukzcGi+rAwVAjckszEzwd7ILUnQewMnovhnwSC2FVGaTuPfD3oAn4qccjYHr3wX+H+2JX4k04WNXB3NQElhoNTPWdN7esFv+J8ERCbjk2zwpnd6spKK+DWGiOGZGeUKmA3LJafPh3YyXYl1NCcCW/Ag5W/LszZ+V1mBTqjg2xWRgdJMYQiW4zd/W4Cfj6e8lkFFdj9qM92f9vwuFgSn8PnS2dgcaZ2VLp3aRWc+MXn1vOfq9OtjVtCj53kBdOpN3CsABHRHg5oE6uxMvDfVEtU+B6SQ0++DsFq57uo/f351ByES5klwHg4K/LhQjrYYuiShk4HMDBio93nwxE3I0KDPQxPjNkrEmyOuDRN1NniOZz8u+MkeayhB/uNPrX12R2VXQaglxt7jsIfZDGnK0Z+N7PuLWFB12a1pkruO7l2h62xueEtDVjmzQEugixKjrVYByybIw/O1GUXlyN958MggoMlo0JgJ2lGdKKqjEqSIxpEZ7o4WCJJbsuo6RKho8m9IbYxrxFm4zMHeSFV3ck4q0RPji+eTdWJZ7EyGvnIaqtRJXIGdGBj6Lh9Qko6B2GQQFi3Eguxsf/NO7C99iE3i3uY1VUKYMFzxT/HeYDAc8UmSU1RuMCmYIxer4AZ2t8PLEPPO0tsOjXBJ2K5ZeH+4IBjL6Gq6053t6XhPlDvPWO/5JRErjZmuP/fk9ERnENFgz1xp74Ap3PS18D+vlDvNGgVOmt2N4dl4+3xwXqNJMWCXgY4ivS2jxF/fvy89wBeLyXE977K4W9V66b2q/N75VN4x5LMxMwACpqGyBTqDr03teS16bNLe5ix2IejQXpWigZ1Y3d7z88EvIqcDrzltGbvLkZF4P9HPHOvmSkF1dj3bMhWserm3au/DMZb0T5s72H1D2CpkV4Nm67HpsFLwdLnRmy5hIcJlwOHK35bB+CZ8LccatahqxbUrafwbLRASgorzO4MwvfrLEwcHdcvv5tlBkGr9tWoHDefzHk8gkIbhWhVuyCX/yH4sqjUZjzf5Pg1sBgKQPE55bjvf3JjZVFk4Nha2mGL49mGN3dwt6KBztLM4gEPDQoGAz2E2H1pD4AgNXRafj3+m12O+jFIyTIK6/Fzkt5WDc1BOXSBlTLFPBxtMKV/Ap42lsCaNyNxtByNonYGjUy/Z+5RGwNwZ1/lEvE1jAx4eKzI/or0z6PycC8Qd74+GAqO37GdsZbFa2dEI1JKcaV/Ap8NjkYObdr2aRZeA87yJUqfBGTqbVkLatUioziGsSkFuNKfqXenRMDXRp3QBwqadxS+Y+EAq1zDPVv7AVhSHM91e4n4NF8jkyhxBCJIwoq6nR22Ht91xWsndwXCbnldxOHrZAY6AyJoM4SKLZ0V7/uzsJYgryFjc8JIY2am/D7floozmeXwYpvqhOHLBruA4YBluy8DKAx4WHJN8HuuHwEu9vA31kIXycrnM26jS//ycTiEX4QWfFRUiWDJY8LByue0RhJKlfiiyclkO3eiz2XT8Jx1RFMrK3BDVsX7O4zApKFs7A0h4fyeiXefzQIX+xLQlKxFFFBYjhZm6OitgG1ciX7Gs3FZOlFVRgV5Iyfzt7AE31dYW5mgsUj/fT2nZw7yAtmphyj5ztzrRQbYrMw8s7GH01juH0JBXgy2MXgDsNLRkkgV6iQUVzDVptrnmPeYC/supiHMX1cMMzfCRnFNfCws8QPp7K1Pq/bUhnG9nHR2cn39V1X8PmzwVj4mLdO64PSGjl6OFjq3H8/mdgXS/foxklA4wTUL3MjOuxeaW/F69L9BCnpcldbjcX99B4mpCWoZ1Qn05r9Du6nZ4tmEzxDCYZvnusHUxMOFvxyNwAQCXh4a2wvNrBqaa+oxhlAHiZ8d0Zrfb2x/gRbZodj06lsnM8u02rY+Wy4O5bvvcr+g159jtXRaTo9C5r2H9g4IwxV9Q3YciobJlcvY0bOeYxLOwWrglyUWtri9tinsIIfCPsRj2FUHxdsOX0DHnYWGHOnGfhtqQzzBnkjtIctMopr8NflmxjgZQ8TDhDoasNWPUnE1nhztD8UShW2nLmBd58MxB8JBSiuqsejviKczy7DjEd64Onv/sXjAU46s3HPD+qJPm42SC2sZhNxz4Z7oE6uwPI/GvtO6JuRAxormuoaFHp7Rn02ORgAg9d2XcGW2eHgcDiYZ6Rvwo4XH8Gk9WfZn+lrzvlGlD9Opt/CtrM39H72mk1VjV23uv8FAIPHfD89FCIBD/nl9Xof/3JKCB7xtoezjW6fpPYKvoqr6jBn66VmG6kCrdtTqas35nxQ3aF3VWuiHhvaqGdU99Ken2dzvfn+WTIU/93euCub5mYduWW1cLOzwO8X8tjHlo0JwJHkYowKEmNvfAGbkOrhYIkz126BYQCJWIgV+67im/+E4qujmXo3XrGS1WKnexk8TkTD6ugRmNTVocbXH3/6ROI3tzCo+vTF3MHe7EYd+u7Fk0LdMczfCZklNbDim2DJzstGY7LPJgdjT3w+JoW6gwGDvfEF+M8AT/x5+SbGB7ti/YnrbFygnoj7M6EAg/wc9d6vP382GPnltXCw4iOvvBbH0krweIAThgeI8U9qMduUebCfCFmlUp3YY+lof1wtqICDwBwSsQDxORXYm5CPp/u5I7ynHepkCvzfjkQ4WZtjqEQEdztLrNiXpNXbUT0OQ/xE+OhgmtGeonnldXffY5P+Rpr33zq58r429WgvbX1voGRG19SVk5Sk7bXGPZd+i7qx+1mqo66mUqoYvbNJb472R2FlPX4+m8M+R129Y8kzxc75j+DLo5nwtG8s6Z4W4Wm0FNuKb4LkwkqdGTJDy7mWjJLgtwt5bDNpzcqSrWdusMvVNM/x9rhArXOsntgXOy7laZV955y+BPu/9+HnxGNwyM9GnbUNov0HYtfgF1E9YCDGh3ni0sFUIO0W4u/sCONpb4nqegXefbIXKusU+PKfTKw+lMYmjXo5W6NUKsdrOy+z1WC5ZbV4fddlvPtkEK7fqkFcTjliM0oxf4g3TmfewguDvZFZUoMIL3t2O2g19XvdMCMMH0enQmTFx/ODeuLA1UKM6e0MkYCH0ho57K3MsGVWONZqJMDmDvJCfYMScTcqDFaKudpZYPOscGQWV6O8tsHorGVGcbXWeQrK6+AsNMfzg3pCxQCe9hZY+Wcy5g/x1vvZqyum1L87A31ESC+qZt+DJnX/iw2xWbCxMMXnzwZj06lsZBRXY4CXPd6I8sftGhms+WbYGJui9/U2xmYh2MNG5+ftWTGjUKJFyyqA1u2p9LAHfbQ0TVtnqJgjpDtortJQaGHGxmDq3klqexZGsn+Xnglzx974AkwMdcOR5GJMDHXDltM3sPHOUu7XRkngbmuBosp6/DhnAGQKlVbF1c7DV9Dz338w8cYF9M+Mg4lchhRXP/zdfzIOSQZi2atPwcfCDHPKayG0MIMlzxSzI3ugj5sQ/TzssHhnIntd6uscFSTGe38lY3iAE3uvjzGwxP5QchHmDfZiN7YRCXiw4psgKkiM3y7kIqq3GCufCIS9wAxcDgcNShWeDfdASU09Ns0Mx+cxd2MV9Q7Mm04Vay2JS8qvwj+pxewYrprYF6mFlUjILUdCbjkmh7njwwlBKK6SwdbSDL1cGicB1edYPEKC2zWNPULf+6uxin35mF7YE58PdW5od1w+O6mqHgd1LKtPRnE1btxurFj/ZFIf2FiaQcA3Y++5TZMvZZB32srU+23r0RKUzOjaqLKctDWqjOpk2mI3veSblbicXwkrngmkciWC3W0Q5GpjcIcszSoCzdk8qVyJp/u5oLhKjqe+baxk0reW/s3R/nC3s8ArvyUiKkiMw8nFBmeVZj7iCT9nAfLK9Fe0fPNcP1y7VQNHAR/2Vjz8fC5H/65md3ZOUc9waRIL+VpLwm7VyDDQxwEH951B0KloPJ15Bt43r0MhsMafPfvjr4AhON0zBAqTxvHZPCsccoVKbyn499NDUStXshVhmtZPCwUAvPNnkk6CJdBFiCn9PXCzoo4Nrn6YGQYvkQCphZVwtObjg79SW1RFo97C+DF/J/iLBSisrEO1TAGG4cDJmgdfJwHSi6qRX14HD3tLfHwwVadS7LPJwVCoGHxyKA0ZxTXNzoKuik6FRGyNGY/0gEyhQg8HS+yNz8fP53K1Zhf1VUwtHimBKRc4mVGK3m5Cncqvpv2TTLkcrH02GCIrPizNuFgbk4FgdxtE+jhAoWKw9nBjwLl9bgSmbT5vcNbx8KuD4eN0t6loe1fMGH29O7+/JzNLO81ubd0FVUbp97BXzKlRZVT30t6fZ3PVJDo7g91J4MiVKvx8NgcphVX4aEJv5JfX4nJ+pd5qJwDYvSAS5bVyfBGTiaESEa5cSkfP0zF48vo59L9xBVyVEvm9+uFk0CBwJ03Cyss1WsmiPm5CBLlqJ2jmD/GGkzUPMoUKaw5naFUv1cqV7PVpxoGWPC487K2QX16n1Sahl7M1Xtt1BSmFVWwMoLmTngkH4JmZYNOpbJRKZXhhkDcivO1RVFGPlKIqOAr4qJYp0MvZGrO2XtR5/5tmhuOzmHRwwNHZLfdwcjEKKurwycQ+WBWdZnAMN80Mx6GkQqQUVrPj8p8BnvjhVFbjTrzO1vh8cjDSiqrZhNvSZnYA/t+EIBRU1MNJyEfvO3G1seRL03/YN/196Sj3swNvS1E1btdF8RNpTmvccykZ1cm0RTLqXmckmrtxNLeUTyTgYdOscIABSmtkaFAyRhM5dXIlTmbcYpNaTWfc1ImJjyb01rtdLnAnYTE5GKmFVVqzj0BjwPDhhCC8sy8Z1ZlZmJl/Ac9eOwOb5MtQWlhCGjUGlU8+jSu9H4GSZ47vT96d9XttlAS/X8wDAL2l4HZWZli2J8lgoDKhnxtu18h0rsmUy8H+RY/in9RithT9Sn4lPnwqCC//lohXHvfDS7/GN7sdsfp1hkpEeDrUHTcr6lBR24Cc21IEuFgjIbcCIR52sLU0xVdHr8Gab8ouLdQcZ74pF9+duK71PkYGijGmtzNbhdT0M1EnpdSJts+fDcbHB1OxeIRE63PSDGTzy2vh6yTAhtgsvDbSHy/+ottPQnNbavX72zQrHK53AqEr+RXILK6GJc9U6/dq8Qg/o4nPzbPC4aIRTLVl8GWIof+2fp47AL5OAvBNH+7EQFuhYJgYQsmo7qW9P8+WbkN/s6IOF7LLkFpYhT3x+QCAVRP74IWf4rBgqDcCnIVIL6rCST1tDUQCHj54qjf+t/4QRqefxRPXz6JfbjKU4OCcZx8ckgzEYUkkbgnssWlmOAor6xHiYYsDV29id1zja2m2UdC0dnJfWPNNkVFcDQ97K3g5WKKoWoYVf1zF++OD8NKvCTrP+ea5fnC2MUd2qRTltQ2I9LbH9VtSvLbrMpQqBh9N6I11xzIxsZ8bPOwscVsqg7udJZbsvKx3AnPeYC9EJxXBx9HKaFuHz57ti30JN7EnPl9rgm/t5L7wtLfEAC8H3Kyow7wfDS+Hf3d8IE6kleByfiVeGuaLEA9byBQqraV0T68/g6dD3OBpb4nSGhk87C31jp06BlK3g1g3tR8e9RUZvd+EeNi26PelvbVV0oGSGV1bR8TJpGuhZFQ31NqB1P38I8xYcAUASTcrUVhRj7SiKp3AQV+g8dIwH7jbWSC7tJadSXthiDeKK+vx09kctq+UehbNx0mgdwcVzYqbpgJdhPj82WBcKahE1q0a7I67G6z8+kQP3NjwIwbHH4NHSjxUfD6KHx2GjwR9cdRnAKzshXgmzB0edpbo624DDoBrt6Tgm3K1KrGaVokN9nVAg4rB09/9a/AP9QdPBYFhoFOtFegixFfPhWDln8lava/6uNlg7Fen8cJgL6PvVbMyypTLwaZZ4VCqGK1ZzyUjJTidWYqfz+fAX2yN/3vcD54OlkgrrEROWR0cBXy2Muq9J4MgMDfF7CYzkiIBD5tmhoPL5eBcVhk2n87S2slPs4JJfV0cDpq99pYco35/6l2Jau+Uu/NNuci6JcXSPVe0ni8RC7B0dIDeHQC3zA5HqIcdbDWCno4Iklr6DxfSujrzuHdUHw3q39GIklHdS0d9ns1VGur7R932eQNwq1qOnZfy8MrjviiqlLEJHbWeZQX4SJUBUcwB+OemQc41xemeIcgdNgb2z03C90lVWpNFDgIzLN1zFZ9PDmZ7HTUXO03o54bBfg5gGOB2jRw/ncvB+GAX9LC3QlapVO+yvILyOqwYG4DYzFIEuFgjt6wOh5OKkFJYhdUTe8PczFRrM5k/EgqM9iJdO7kvOADe3HPV6ISjvgr6QBchts4Jh1ho0aI+XmamXIOfk764YGSgGBP7ueHrY9f0TsypY5ZT10qxaWa44WSYRlzR3pWpLfl73xaTNu2VzKD7WdugZCJpDvWMIkbd7xpwQztglUnluFlRh+NpJSiuqsf0R3rgh1PZ7PPUO+g17XP00q8J+HJKCNvn6PUoCcqlMpibmSC9uForQFEnIPTtoNLbtXF54cu/6c7UvR4lwQd/p7CJnZWRYmDvHxgU9w9s1/yLCA4XJ3uE4PNxS+AxZyqqTC3xmLsQooIqvUvFzlwrxTOh7niirwv6utuwya098fl4JswdPo4CyBQqxDaz62CNTInbNTKdx14c6o2z18swMdQNVnxTxKQU4/VdV7BnYST8xdb3tEOdRGwNGwszPP3dv1rjPu+nS1g7uS/srpohpbAKL/4Sh++nh8LUhIsL2WUIdrdBLxchvvlPKE5l3IK7nQW2zu6PNYfTtcr1ZQoVMkuq4XHn8ZyyWnwRk4GM4hqt68oorsb8Id5YFZ2K5WN66Q0a5w7ywp74xvem+bvT9DzTH2ncbfGtMb1gwTPBtE3ntSr7PO0sdPo4DA9wwqmMUq2eUupdc2LTS+HrJNBKRt1PT7UH1Vl2l3vYdMZx76g+GtS/g5DW19zfE339pYoq68Ez5aKPmw3MuBz0cLCEv5MAyqtXMSb9DKIyzqLXrRtQmlsgpkc/fPvk6zju0x/VfCsAgOhsCSaHuePTZ/oCYHD9lhSZxVIsGuaHSznleH5QT7y+6wo87Iz3Pephb4lauRJ/JRZioK8DpkV4ILesDkqVFB9Hp+LpEDedHWxNuRzcutNXacFQb7jbWmL+EG/870AKeKYmWvd/S15jrPfCYC+dnZPVtpy+gZeH+xqNp3LKpAbfg0JleJw1zyG0MDP6WemLC2JSijE6SIwhEt2dfNWvPy3Cs7EHYQt7FLbX/ede/t63RT/Btt7Ble5nbasj4mTy8KHKqE6mNWf1WmtGQt8f++cH9QQHHGw+nc3eZJqbfdOsdvn82WB42Fng3f0pBnsLLR0dABsLU9y4fbeiaslICarqGrSac6uX0p1LyMKojHN4Ii0Wg24kwhQMsnr3x2a3CEz/5P/w+rECtun1nEd7Ys3hdCweIdG7hPCHmWHYeuaGVtXSzYo6uNpa6JSX21maYc423WqczyYHw0nIR0WtHL9dyGN3x3G2MYdCqcKrOxJRWiPXWpY20McBLwz2xpxtF/WOib6KpG1z+mNjbJbBXlpau7S5CLHq6d64VSPH5zF3q6heGyXBrep6uNhY4sZtKbxFVuCZcmFqAsTlVMBLZIUvYjKN9nZSL6eTK1TgchnklNZh1aE0NqhZNjoA7nYWMDczgbmZidH+Sd/PCIWAb4bMkmpM2XBO55i/Fg3SqYxSL+O0szTT6YlVUduAf5YMRU+RldZ5OnPFDOneOmrpIC1Z1EaVUd1LW3yerVV10fS/vQVDvWHC4WB4gAiK85dQ89tOPJJ4ElY5WajiWeKYb39ESx7F7Pfn48PjuUaXr7228wp7f34jyh/7LxegRqZEVJAY5dIGo32P3n0yEDcraqFkgNXRaVj5RCB8nAT4+/JNvcsG1c97f3wgJm84B5GAhw0zwrDhZBaeH9RTp9+lOjacFuFptNXCqol9YGbC1TuRtW5qCKrqFHjnzySdxzQrNMqlcpzMuGXwHEP8HGHXzGeoLy74ZGJfnZhDcywG+4lwtaASn0zqg7icCqQVVWlV6De9zvZyP3/vW7tqqy3vOXQ/a3sUJxNjaJleN9SagVRrlVfq+2PfGHyEokzagBd+auz701xPp6Z9jhY+5g0LM1Ms23sFz4S5w9tRAGu+KWrlCvQUWeF2jQwmXC4seCZQKhnE55Wjp4MVSqrqEeHtABMuByZ1UsSs3gz/kwcxNOsS+EoFzrsH4e9eg3F9yGj0CZXgVGYp3hoTgJSialjxTJBbVouS6npM6e/R4ibhIgGP7e/Q1NfP9QPAYP0J7V3/LMy44JlwIVMoIZWpsO7o3WTOwsd8sP/yTcSkFGOgjwNmPNIDZVI58strMdBHhAalCmuPZOC2VIa5g7wR1sMWtTIlVAyDTw7drVx6I8ofzkJzPPHN6RaNuymXgz3/HYinvjmjc+zW2f3xxu7LWsGTsffdtLeTvpu/saCmpb3J9H0+A30csGCoD2ZuucD+rLlk6C/zDP++UzNn0p46qvSdSu51UTKqe2nNz7O1qy40/1F37WYF3hNVYtDVU7A7/Desi2+izEKIjIhhMJ8yGSulzki5LYNEbI0PJwQhr6zOYILlRqkUX/yTqfXzzbPCsfl0Nq7fqsGiYX7wsLfQWYYPNE6axaQW45XhvsgulYLL4eDnczl4e1wv/O9AqsFm4BtnhEEqa4CSaaxqmhnZAz+dzcHsR3ti+d6rWj0jZzzSA4P8RCipluHns4Y3ofnmP/1wIfs2eKYmOr0qjyQX4aXhvhivJ3bRjD0Kyuvw/l/JenuQHkkuwsrxQS1eFtY0LjAUs3w2ORj/Xi/FuD4uWKvRKqHppF17J0g6y9/7tkpmdJb397CgOJnoQ8mobqgz9IzSpO+PvWZfKHc7C4y90xB7qERkdBataZ+jHS8+gmsl1XCwMtep0mlQqlAjU2hVIc0f4o06uQLv7YrHY1mX8GTqKYzNiQO3rhaJLhL8FTAYBwMGoVDoyL7G++ODYG5mgg2x1zF/iLdWUPXpM321giZNTZM4zSU6RgWJUSdXsv2k/MUCvLbrMoZIHDG2twvm/aRbObV2cl/8e70UA31EWu/z5eG+MOECjgJzpBRWsdU9pTVyiAQ8/DAjHDllUqQWVmNPfD5+njsAr+00PmOnWRk1oZ8bPj6ou3yz6bEted/qz/ytsb3Qz/PeAovmApTmK/seQ1lNA66X1iC9sArZt2vxbJg7ntfTM+qXuREY5EezZKRz6KimoNSMVBclo7qX1vw8W73qoqEBOHEC9Tt2weyvP2FSUoJigT0qR43DB/xeOOseBCXXBJ9N7ovMkhp42DVW9x5PL8HyMQG4LZXrJFgcrXlYsvOy3h17v5oagtoGJc5llcHX0QpltbrPL6io1an4fn5QT7jYmEMqU2JXXL5OhfaSkRJEJxci1MMOX/yTgUmh7hjo7QAFw+DijTI2ZtDXQ3TxSAl2XsrTqqoGgJ+eH4A+bjaYdmdznKbVzU7W5tg6JxzXSqRGkxqaG+zonENo/kAJCkM7I16/VY3wHvZ6Yw/1bsfqZuntWUnS2f7et3Yyo7O9P0IeRtQzijTrQdeAN13/3rQvVEphFW7cluKDp4JQXCVDfy97PK9nyZq6z5FIwMMzYe4IcBaiXCqHJc9UK1GTUliFuT9ewg8zw7SqbjLzb2Pfx0fxYV0S4v+JhpWsFhWSQFydvQjrHEJxrEGg85oSsTV8nATYfDobZVI5FEoVNs0Mx+cxjUv8KmsbjPYWyC2rZb9vrufCtAhPNnH12eRgvLarMTh0subj85gMvc/bG1+AGY/00FommFJYhYXb47FhehjWHEnXmUEsrZFjxb4kraRR3I0KzB/ibbBHk2Z/qcUjJVix76rR96Gpuff91XMheGGIz30FFs318THWa2B6ZA9cL5FidXQaG+QuGxOA3q5C7HzxEVzOq4QV3wRSmRLBHo29xlqDseUa1ECTtFRb99HobK9LSFdzvz03ddTXAzExwN69wP79QFkZzHv0QN2U5/A2V4K9fA+8+JgvyjJKobzz32VmSY3OJNCvF/IwIcQVE/q5QcA3QY1MCZGAj1/O5egkooDG+3NlfQMmrT8LoHG32fPZZRjsd7fvkb5JupTCKry+6wrWTwtFfYMC4/q4YOelPAyViDB/iDecbcyx81Ie0gqrIbLio7RGjuPpJQjxsMXehAKMD3ZBgLMQ/zuQoreH6As/XcLmWeGQyhS4kF3G9qb0d7aGnUZ/mqY7EK+b2g9ioQXEQgujvf/smzlHSz4zQ/fypjELBwCHA0T6OGCenkQU0Fg1prkbcEtfqzV0tr/33f39EULuD7ejL4C0Lc2b58k3h+GXuY0zei2dnVH/sVd7JsxdpwHl8AAnfPBXKlILqxCbXoq1k/si0EUIUy6nsZ/B5GAcSi5CqKcdlo0JQGxGKV7bdRmfx2RCqWpsVt7UFzGZmNHfDauERfgn9Rdc+X4Wtu1+H8zFiyid/xI2fP83Rsz4EnNdR+C55x7Te+2vPO6LlX8mgQNg2ZgA/HQ2F2/tu4oJ/dzwx38HYliAI14bJdH73CUjJTieXsJ+n1deqzUOmiRia+SX12q9V3VwaCyZE+xug6+PXdP72Lqjmejrrj+BklFcDU97S/b7r49nwtmGrzPum2aF42p+JSpqG9hru11TD5EV3+D70EzANfu+na1hb8W/pwCjTCpHQXkdyqR3g2d7Kx7cbC0MBpVNiQQ8DPEVYeaWC0gprIJSxSClsAozt1xA8s0qyBQq/JFQgHf+TMYfCQWokSkgu9M09H5JZQp2lnzImuOYvuk8Tl8rhVSmMPoYIfoY+t0G2rYpaEe9LiFdTUsbUetVUwPs2gU89xzg6AiMHw+cPQssWADExQHZ2Sh7fxX2WfYEw+Fid1w+nh/Uk3160++Bxiba7+5PRqS3PXq5NM4+X8kvR355nd5LkIitEZdTAaCxmt3b0QrPhntgQ2wWVuxLwobYLAwPcDLYUPzrY9fgZmcJkYCHPm42cLezRGphFRb9Go+98QX47zAf9HYTYvbAnvjgqSB8fewaYlKK8f5fKaiTK7BxRpjBc392JAPTH+mB98cHYbCfCC425hALzQHcnUANdL0Ty7gKsX1ehNYEqqGYQa0l59Cnpfdy9eu72lrAxcYCDAOjk3b6lp+0R9zQ3f/ed/f3R8jDgpbpdTKdccmAZqm6vr5Q6p99MD5Ip4E0lwsI+Kb47UKewd4Dmr2HOIwK4fkpeCrtFKbkXoBZ6S3k2DrjXPgI2M+dgd0yO4zp64rXd12GRGyN/w7zwfVbNXC7U2auLiNf+JgPpLIGcLlceNpbYNGvCTqzh/sXDcTeuJvo7S7UKV2/ml8Jvhm3RT2jNswIg6uNOeRKFc5cK4WbrQUs+aaorlfA2tzUYI+EL6eE6GzjrNbcNsZvjQ3A6Wul2B3XWL6+8slekDcwSCuuhoBvAh9HAd79KxlD/Ry1ytQBGNylb9PMcCzbe0WnZ9Qnk/pirp5Zv+3zIhDoIkRtC2b17rf3xv02Em06I7plVjiG99JNeraUseUapiYcvU3WqYEmMaajmoJSM1JtnfGeS+5fa32e99yPpqIC+OuvxgqoQ4caK6KCg4FJkxq/AgONnr/phiXTIxr7LKkrudU7wzIMA18nAW5W1EOuVIFnwtW7CcvmWeFY/sdVqFQMe89v+hpr71RxG4pBPngqCBlFNRgsEeEzjU1j1Bup5NyW4rWR/iitkenEhc21QfjgqSD8cj7X4N+e1ljSda/nuN9lmffTu6i9Gm9397/33f39EdLZUc+obqgzBsZSmQJxOeVYHZ2mty+Uuq/QEIlIb38hkYCHNZODseZQuv6btbM1nmUKofj1N4xLOw2Xmtu4ZeuIrGFj8ZF1MK44+zXWQqMxgSMwN0VxZT1yy2rR202I9/9KAQDMH+KDAGdr3Kquh5O1OVZpLOFq2khSJOBh44xwTN5w1uDua2snB7NJr7mDvJBfUauT9HrlcV/siS9AHzchglxtcCqzFL3dhFo9EpaMlGCHnh4JexZG4p19yQaTKiuf7IWpG3WDlXVTQ/DRwVSIrPh4flBPOFjxYGFmgq+OXUMfNxt42lvC3oqHr49d03vu2ZE9MdTfEWsOp2sFl4beX85tKRwEfK2fLx8TACtzU7z9R1KLkkut0btMHVTWyZVG+wRo9vrSHE9jpfLNvbaxnf8M9uCiBpqkBTqqKSg1I23UGe+55P61a8+oW7eAP/8E9uwBjh5t7AkVEdGYfJo4EfDxuafziwQ8TAp1xxN9XSAS8FBdr4BMoQIDIOd2LdQbpWj20cwtk8LT3gobY7O0klY+jlZYvjdJJy5Tv4anvSVc7SwMx2UaEzsiAQ/f/KcfcsvqcL2khu1haSz2WzzCD4eTi5vdMbez/O150GbY9xLjdETj7e7+9767vz9COitKRnVDnTUwLpfKsSsuHw5WZrDim2LBL3dn4kQCHpaNCcDq6DSDVTd/vvQoJq7/924CgWHQ61Y2nkyNxRNpp+BZUYxblrY4GPAo/uo1BDOWPIcPD6bpbco5KkiML+/sHKMZMJlyOfhkUh/wTE3w8m8JOtegWYG1YKg3erva4LsT1w0GS+umhkDFAH8k5LNb9GoGcvnltfB1EmBDbBYWj5DgnT+TDL5/9c426h4JS0ZKkJBbDi9HK73HfzY5GGeul2Kgj4NO1dah5CKtxNZ300Lh62SFMetOa+1gY+ha1LvnTAn3wM2KOtyqkYHLARys+CitkcHeig9vRyuYcMFWlGm+777uNpArVWwvCk3tEXg1lxzSVxllyuXg8OIh8HHU7S3WnOaaZH7wVBDe+kN3u2lqoElI59dZ77nk/rT2bnpNqy7eD7VF30vHwP9zHxAb23jg4MGNCainnwbc3e/p/OezbmNtk6qjM9dLMWegF+yteOBwADMTIOVmNWbp2Q1vy6xw2FiaolzaAA97S9TIFEi9WY2DSYWYGOoGWYPK4C7HYiEfqyf2xZxt+nfZWxWdysZg+u6t6qp4O0szrXhjVKAYTwa7QKmC3uruzlg1/KDNsO+lQocabxNCuovWuOdSzyjSInZWPAS6CvHariuolSuwaWY425/Iydocrjbm+OCp3kjKr2J7F4mFfKwY2wt/LnoUNTIF/MXW8CnNw6unt+PopoWI3voKnks8jOReA/D35z9h0Ms/YcfMpVj0zmwcSCo22JTTUcDX+j7U0w5AY48EGwszrD9xXe972HL6BqY/0gMA4OckAANGpy+D2htR/kjKr8ChpELEZpSy11JaI2d7LpzMKIVcqWL7Jejrp6X22ZEMvDU2gO2R8OnhNChUDITmZtg6u79Wr6d1U0NwKLkIe+MLsDo6DYP9RNg6uz8m9HPDquhUnQqrb45dQ0F5nVZvp9IaOQ4nFxvs3zUqUIwaWQNOZtyCu50FDiUVY+X+ZBxOLoazDR+74/Kw+fQNLBsTgEAXISpqG3DqWil6iqzgJDTHO/uS9b7Pjw6mavWDksoUuFlRd/+9N/Qw1ifgxaHe7HJETRLx/TezbNo3rel5a2T6r58aaBJCSNel7rn560hnxFlcxv7tb6D/4L7gv/E6wOcD338PFBYCJ04AL798T4koAJApVNh0OhuD/URsbHDm+i0M9HHA0j1XMGTNccz78RKKKuX45FC63nOsPZKBI8kl+DwmExW1cvx7rRQhnrY4n12Gw8nF8HGyMnj/crDiw8mahw0zwvTGCZoxWNNelcDdnpKa8cZAHweMChLj5d8ScTKjBOunhWqduyW9mzqC0ft8C+7l99Kf9UFfixBCuhNaUEtaTN0U0syEgy//ycSoIDHWTu6L/ZdvorCyHp8cTsdHE3pDLDTH588GI6+8Fl/EZOLX345jQdFF7Eg5BeuMFFTzLHBEEokPh8/D6Z4h+PS5MOSV1WJlJB+5ZbUw4XBQY6CJY9Mm2xKxNWwsTSES8PDiUG9Y8EyNNpL8cEIQkm9WwZJviq+PXoObnQXWTu6rVX304lBv2Fqa4YWfLmGAlz1eGyXR2zPppWG+UDEqXC+RIv3OTnTGXruyTgG+GRenMkuRdUsKU24pJGJrJOaV490nAyFXqJBVKgWXAzbhpE5+edpb4pNDaXpn0jKKq6FigMUj/bR6WsWkFCMhtxw/zAzHzYo6JBVUYk98Pv4zwBPVMgVsLcwxdYCH1u6HjbvdxLFVZAm55Zg/xAejAsUQWjSW1BeUtzy5lJBXgdOZt4zuWsjReybjDO0Sacbl6E1ivhHlf19L9ADt3XmaWjGuF0xN9L8DaqBJCCH37ttvv8WaNWtQVFSE4OBgfP311xgwYECHXY/tn3uAjz8AoqKAn34CnngCsLN74PPWyZU4n13G9pTUV9GcUliFK/kVze7m+2aUP8prGxCdVIxauRL+YmvEpBQj57YUi0dI9PaVWjJSAi6HA2l9A4ZIRFg+JgCpRdVaFVFqjbsTWyHQRcjGSv087RDkaoOXf0tg440Pn+qNr49dw6hAMR71FeHnczkYcmcnPhcbc3g7WnXKXj5G7/P3cC9vyXGt9VqEENIdUGUUaTH1zI+DgA9rc1O421ngUk45YjNKkVlSA5EVH8v3XkVVXQNup13D+UUr8PEnc3H8+3l48sA2pNq5IfGrLZj+0X4sffI1lAwajk+mhiE6qQhf/JPJ7vCyKjoNi0fo3+Vu7iAvrcqXuYO88NXRa/hhZjhchOYAwxitYjmSXIxxfVzgbtu4y11MSjFbfaSemfz4YCpM7vQeejPKH6425vhhpvbM4aaZ4fAWWWH9iSx2drC5Hfd4Jhz8k1qClU8G4tv/hGKwnwirolPx87lccDkc2Fia4YO/U7D/cqFORZOPk8Doua34Jth5KV/neasn9gXPhINIHxGmR/bEyicCIVeq8PPZHFy8cRtrD2foPeeW0zcwKdQdpTVyBLkK0VNkxQZILZ3VU2+NrW9nIM3P7/Vdl+95FxlDs5C+TgJsmR2uNQZbZ/dHsIGdCVvK2O48vV1t7mvnHkIIIdp27NiBJUuW4N1330V8fDyCg4MRFRWFkpKS5p/cVhYubOwPtW8fMGNGqySigJbtVgwY39V2gJc9+nnawtbSDIl5FSiprscujXtuRnEN9iYU6K2S3nEpDzcr61ErVyE2oxSLdybC3spM74TOi0O98f5fKZjQzw37XnoU66eH4p0/k7D/8k323BW1DZApVCiVyjAqSIzXd13Bv9dv4/uTWXh1RyKmbDyH1EL9SbXO4H534evsr0UIIZ0Z9YzqZLpC/4pyqRwnM27h1R2JWDLSDz0drPDB3yn4OFIE7NmDgZeOQnDxHGQmZjjhHYa/eg3BUZ8BqOOZY6CPA5aNCQDDANFJhWwvJk2mXA62zumP+gYVvtDYSeb1KAli00vxy/kcrf5Jx9NKsPe/A2HG5aCuQYncsjq9fQrUPRCcrM3xxbPBWLzzssG+Q2+NDcD0zRcw0McBswf2xFt/XNVpcr56Yl+8ta9xt5oPn+pttGfUuqkhqKpTwN3OAk7WPLyx+yr7vpaMlCC5sBJgwDb81OzRlFtWi5yyWjwV7Kp3dnPL7HBsOpWNf6/f1nne1YJKfDElGGJhY1XQqcxbmLH5AgD9OyNqfgZrnw2Go4Cvt+dBS5p1avZFaLqLj77+V63RR0IqUyDpZiUu51VCwDdBjUyJYA8b9Ha1aZXZWGNNMqmBJiFdT1e45z5MIiIi0L9/f3zzzTcAAJVKBQ8PD7z88stYtmxZs8/vap9nc7sVA9oVUyIBD8+EucPDzhImXA7cbC30btYCQOueO8DLHq887ofK2gbE55azTcgDXYT45Jk+SC+q1rvjnkRsjRXjesHXSQCFimHvb5q9GzXjDnsrHvLL6/BHQoHB+OqXeZ17Y4/2vJdT3EAI6cqogXk31BUCKc0gZM0wN/Q4eQh+xw/A9sK/UIKD4keG4Av7frgYPBhjHvWHh50l8sprsTuucZe6H+f0R0phtdFgZdXE3iivacDlmxXoYW+FniJLnMksRVW9AhKxAJY8U1TLFMi6VYMr+ZV4MtgFKhXw19WbeHtsL9yqlmvtFjdvsBfkCiWUKiC/vBZBrkLUK1QGE0c3SqX44p9MrJ7YBz+dzWl2J7WNM8LA4QCFlfVwsTHHFzGZWsmmlMJKiO70ujIz4aK8tgGPeNuDb8LFF0cz8U9KMQZ42eOFwV6Ys013SeCW2eG4dKMM3o4CnYSOv7MAT337r8Gk0j9LhqKnyEqn8bd6JxxD783Y7nMtadbZ9PVEAh4+fKo3ZAoVUgur2GCYfc1W2EWmvbZLJoR0D13hnvuwkMvlsLS0xO7duzFhwgT257NmzUJFRQX+/PPPZs/R1T5PzXvpUL+7uxVrJp3yymvB5QAjeomRW1aHjbFZBncKBu5u1gIAk8Pc8VSIG/YlFhic/Dv2+lDcrpEj53YtNsZm4bZUhrmDvDHQxwGO1jx2MqspffdbkYCHLbP74+nvDMck1KCbEEK6h9a453a+hduk06svLUPgP/vwRspJDFl7GVxGhVvhA7Fs1Es4LInE1NEhEDSo8LKbEFtO32CDpmVjApCUX4Ws0lr0cROip8hSq8eR2pKREryx+wr++5gvwjztYGrCwccHU/HCYG/supQPP7EAXx+7xp538Ug/HLxaiAgve0wN98Sbu69iTG8xJvRzgxXPBFwuYGbCwaZTuexz+rrboqBCqtMv6pXHfWFuxsXP53IgEvAgEVsb7dXwiLc9Fgz1hrmZCczNOFCpzLF8b2MV1bQIT+SW1WLZ3it4e1wgqusVqGtQ4nZNLbsjzeZZ4VgxNgBvRPnDimeCm5X1Otc0d5AXuBxgbG8XcLkcvBHlj9IaGcprG8A35eJqQZXRnkxHUooR6CqEp52F1nvZHZdvsJJrxbheRnssaS6TMzSr17QvQmmNHGVSucFqrPtpZq5JvSxQn48OprbJdsldQZlUjjq5EhY8mnklhHRepaWlUCqVEIvFWj8Xi8VIS0vT+xyZTAaZTMZ+X1Wlex/szDTvpQ1KJR7xEWH7uRyMulOdpI5Zlo8JgFSu1Kr6Timswuu7rmDt5L5IyC1nE03qZfYbYrNwMqMUfd1ttTZi0SRxtoaAbwZPeyv0dLBCaA9bqFRge0QaY6h3o8iKZzgmoQbdhBBCNFDPKNIyUinw++/A00/DRdIDa//+HFbyOqwdswDXE9Ix+z8fY0dwFCoshDiWVoJHfR3w+q4rSCmsglLFsEHTYIkI9Q0KgAOcybytt4/B6cxSDPN3wsY7CRsTDgfzBnnjxm0pJoe765z3hZ/iMFTiBCdrc7y6IxEphVX48WwO7K3M8MU/GTAz4eLl3xK1nrNwezzcbC2wMTaL7Rc1VCKCm60Ftp/PQ2mNHM+EuSMup9xoryaZorHXwpxtF5FWVIN1RzO1dtzbEJuF0ho5NsZmIcDZGq425lo9rz47koHopGKM+iIWf10uxNt/JOn0sFoVnYpPD2XAhMvB5tPZOJd1G3KFCrdrZHjvr2R8diTdYE+mxSMlqG9Q4NXfE1BZp2h+x7177Ftgb8WDm62FwaC1aV+E2gZlm+0iUydXtuqufV2dVKZgZ66HrDmO6ZvO33NvLkII6cxWrVoFGxsb9svDw6OjL+m+NCiVuFUtR51cgWkRnjpxzpnrpVh1UH9CTp18UtPc+W7uIC988U+GwRhBs2G2nRWvMSml0SPSGEO9G13tLA3ueEsNugkhhGiiyihiWH09EB0N7NgB/PUXUFsL9O+Puvc/xKngYXjxZAlEAh5G2TogvfhuI+zhAU74IiZT7yk/O5KBwX4imJlw8fP5HNhdNdOqIloVnYqK2ga8Pz4IGcXVyC2rxS/ncrF4pB8EfDOD590Ym4UJ/dzY79WJlm/+0w8f/KW/WmbL6RsY5u/EVikFugjhbGOB42klCHQRYmwfF8z76RLejPLXWz305mh/LPwljp1tNOFwjFZRWZubQq7kYf20MJRKZWw/LCueCZQqBpY8E6QXV0OpYthrUquobYAFzxSphdVIKSzQOX9SQRV+fn4AVkWnsf0hXh3hh3JpAyzMTPHuk4E4lFSIZWMCMHPLBfZ56h1wts7uD3sBv9X7FjStoLI0M0EvF2Gb7CKjbgZLs7GNEvIqtMY5pbAK0zedpyWLhJBOSSQSwcTEBMXFxVo/Ly4uhrOzs97nLF++HEuWLGG/r6qq6lIJKalMgYS8Cnx8IJWtgpo/xBsjA8VaS+887Cyb3VFPTSK2hlSuxNbZ/XEy4xaybkmRVFCFLbPCsTYmQ2dp/YPSd982VDVFDboJIYRoomQU0SaXA//801gFtW8fUF0NBAcDb78NTJkCeHujvLwOe/5KxtrJfUvQp2QAADobSURBVFEubcClG+VaSYDmgqblYwIg4Juyz2maeAl0ESK3rBYSsTVybtey1U97/zvQ6HkFfO1kQ0xKMUYGilscwL04xBtW5qbYuSAS5qZcpBdVQ2TFZ6uHNJfOvTjUG9X1Cq2yd/WON4aWy9U3KFFV14Ar+RW4nF+JN6L8UVhRj9yy2uaf72wNoYWZwe2ARwaKEeJhi3VTQyBTKJFXVof39qdo9ZUI72kHZxu+3gDR21HQ4gbf97PsS/O4tgpSabvku2jJIiGkq+HxeAgLC8PRo0fZnlEqlQpHjx7FokWL9D6Hz+eDz+e341W2Ln2TBq/uSNRZetdcfKGOIwBg2ZgA9HGzgZ0VD8EetnhhiDc70RTiadcuDbNbspRfn+bii86w7LwzXAMhhHQXtEyPAAoFcPQo8MILgLMzMG4ccPEi8NprQGoqkJgILF8OeHsDaKxAyS+vw+roNPg7W+OH01laJeDGtiGWiK2RWlSN5IJKg2Xjcwd5YU98Pvu/anE3jC+Zq5HpLsPKulVj9Dn55bXs8sC/rxZi3o+X8Oz3Z2FmykUfdxvMH+KNmJRinaVzdpY8fHggRet8u+Py8fJwX4Pv6dPD6bicX4GTGaWYGOqGnZfy4WZngazSGiwY6g1vRwFWPtkLIoFucKNOphjbDjghrwK5ZbW4ViLFwu3xOkskK+sUKKmSNTYnnxmOw68OwaaZ4XjUV9SiRFRrLfsyVNrfGrvd0XbJjWjJIiGkK1qyZAl++OEH/Pjjj0hNTcXChQshlUoxZ86cjr60Vmds0qDp0rvdcfmYP8Rb77EvDvXGvsQC9n4X1sMOdneSJE2X0je3tL61tfT1mosvOsOy885wDYQQ0t3QbnqdTLvtBKNSAWfONC7B27ULKCkBvLyAqVMbK6D69gU4HINPV9+Q1TuyudlZYExvZ2w6lY3bUhmWj+ml1WhT7bPJwVgVnYpnwtxRL1eht7tQp1n31fxKPOJjjz3xBVpl6mIhHx8+1Rvzf9Ztev75s8EwM+Hg5d+0X1Mk4GHVxD56G6Vvnd0fbrbmiMstx2dHMtgZyEAXIYZIRIjNKMV7TwaiVCrHN8euae3MJxEL8ObuqzqzlBtnhKGqvkHnPR1KLsLxtBK8Pz4IK/YlAWjc8Sb7lhT9PO3weUyGRkN2Cc5kluKX8zl6d6kDdLcDVu9c984TvfDh36kGd8h754lesDY3w5u7r7Cv99a4XujX5Pz6dKWd6h727ZKb7mSoqTV2LSSku+hqu689DL755husWbMGRUVFCAkJwVdffYWIiIgWPbcrfZ4F5XUYsua4wV3nNOMFAPjjvwNRK1fqVBX7OgmgUDFG73edvZqnufiiM8QfneEaCCGkM2mNey4lozqZNg2kGKax4mnHjsavggLAza0x+TR1KhAebjQBpUm9HfG3x69hYqgbXt91BSIBD6+NkkAitoZKBZTXyvHlP5laS9v+vlKImJRiiAQ8LBsTgNXRaZgU6g4fJwEEfFPUyRXwsLfE2/uSkFFcw76eSMDDi0N8EOppi5JqGb7WSA6pzwsAUXd2oFE/tmSUBDfL62DJN9H6+etRElwrqYEVzxR8My5WR6exyaits/vDisfFuewy/HQ2B9881w+utuYolTbgcFIR9sTnY/mYADCATi+pBUO9cSW/En3cbOBpb4ncslrsiW/cTjnQRYjBfiJ2WeJAHwfMeKQHFm6P1xnfn58fAF+xAHzTlgWO6qB26+z+mLPtosHg9pe5ETieXqKzNLK5YKqrJTc6e+DdHihwJqR5XSl5QZrXlT5Po/dVFyEm9HPDp4fSdCal9E1GGbrf6etJ1dIJqPbSXHyxaWY45v14qUPjj64WAxFCSHtojXtu57gTkbZVWwt8+GFjAio7G3ByAiZPbkxADRwIcO99taZ6qVUvFyGkckVj8+xDaXhnXzIGeNnj9VESuNtZYIhEhGkRnujhYIkluy6jpKpxC2Z1g/FlYwKw5fQNbD6dDYnYGm9E+UOhVGklokYFitltjlcfSkOElz1WPtkLFmamOJFRAi4HbAVVQm45pj/SAx9OCMKR5GJ8eigNw/ydIBELsHikHzzsLNGgVCG1qAoWZqbILavFqcxSTA5zx8mMUix8zAe/XchFfnkd5g/xxppn+uJQUjFmDuyB709cx6ggMZyszXGtpAZ1cpVOL6lIbxHCe9hj3k+XdMZs7iAvrIq+W5If7G6Dr49d0zu+qw6l4fvpoaiVKVHfoISrrQUAw0kWdfPuhNxyo30lzEw5Wksf1ZrrI9RVln11hcC7vVADWUII6bzsrXh4c7Q/Zm+9qPPYwsd84GprjuhXB8PBis8mnSpq62DBM4GbrQW7bMzY/U5vT6rfE7B19gDYW/FaNGHT1pM7zcYXnSD+6AzXQAgh3RH1jGoD3377LXr27Alzc3NERETgwoULzT+pLZmbN+6KN2JEY3PyggLgm2+AQYPuKxGlyd6KBw87SwyWOOKXuRH447+Poo+bDeb/HIfL+ZWIzSjFin1JOH2tFCIr7Saj6l5ME/q5Ycvs/hjsJ8IPp7JgxTfFl1NCEOgihFjIx9g+LlrbHP97/TambjyPmxV1OJ9Vhv2XC7F2cl8EughRUdsAK54p3tmXjA2xWcgorsGG2CwcTi5GZV0Dluy8jAnf/YttZ3LgbmeOkup6ZBRXY3iAGBP6uSHrVg2OpBSzTURvS+UI62kLFcOwfbIG+4ng6yRAhLe9Ti+p13YlwoQL/DAzDIEud/oWuQjx+bPBaFAqsXiEBAuGekMk4MHfWWg0uInPqcCoL2Mx78dLOJ5WgvicMoO9CtTNu38+l4OFj/noPecbUf6I12iI2vT1jAVT6mSXPp1ppzp14K3ZL2v6pvNIzKvo6Etrd23Zm4sQQsiD83USsPGOOl74YWY4auob8NmRjMbqbVOuTq+i89m3EZ9bbvR+p68n1ahAMZaNCcDSPVea7XvUXj2Smo0vOkH80RmugRBCuiNKRrWyHTt2YMmSJXj33XcRHx+P4OBgREVFoaSkpOMuissFEhKAjRuBxx8HTO/vH6NlUjkKyutQJtVNZqgt3XMFG2KzUFojx2dH0jFvsBeAxuab6v+vqbRGDgcrHpbsTMSG2CxcyC5DenENcm5L8dbYAPwwMxwbmywpU/v62DW8MUqi02Dc39laK8kjEvAwKkisldBKKazCnG2X8KivCAO87HHmeik+PZQGkUA7Ybbl9A0UVspQVFmPZWMCUFojx4bYLLy26wr2JhRg2ZgAnMosxbv7k3EqsxTLx/TCrxfykFpYhQn93PDxxD74+OneMDPh4KezuVi5PxmxGaVYNiYAErHAeKN3rWu9iKxSKUqq6w0mWfp52GLd1H5ILazEppnhWsHthhlh2H+5AI4Cc70N0psLptTJLn06y051ze0gZ+z3tjtr74a1hBBCWsbdzhIOVjytSa3le69g+R9JeGGwN1xtLfROshxPK8Gqg2l6z6m+3zWt5jEUCxmasGmvyZ3m4gtXW4sOjz+6QgxECCFdESWjWtnnn3+OF154AXPmzEFgYCC+//57WFpaYsuWLR17YS3sBQXoJp1aOjtWJ1eiVCrDgqHe+GhCbzwT5o5TmbewdnJfPNHXFXaWZjozgJ9NDsah5CK2Wkcitsb1khp88U8mpm++gKv5lYarh4qrUVGnwNrJfeFkbY7Np7Ox/XwurM1NtZI8z4S5Y8vpG3rPseX0Dbw+SgIOdLdHVr+GgG+Cwsp6eDlaae3UVlBRB3c7C3w/PRR//PdRDPYTYVV0KmJSivHT2RzYW5nh00NpyCuvw8u/JersbldV32AwuGm6k6D6WjV31wG0kyzqSpjpj/TEljPZWsHtij+u4o+Em9gYm6VzDqBlwVRn36mOyugJIYR0NUGuQkR42WP7+VxsPp0NJ2tzbJ3dH8HuNgYnWTzsLJu93zWt5jEWCzWdsGnvyZ3m4ovOEH90hmsghJDuhtZrtCK5XI64uDgsX76c/RmXy8WIESNw9uzZDrwywzR7AfBNuTr9dt4dHwiGYXA68xamRXgir7wWu+PyMX3Tea1GyGVSOeQKJb6Z2g9fHs3ED6ey4S+2xvODeuJKfiUe9RFhzrZLEAl4Wj2dVkWnai0bWzJSgi1nsmHK5UAitobfneohQz2Q6hqUbBP0aRGekMqVuHSjDM8P6sk2FzcatBVXw4TLhUjA1+nppH6NGpkSgBJWvLvLnpru1CaVKfB4LyeIrPmw4plAKlfCX2yNrbP7Y+meq3pf+4O/U7F1dn/tvj4au+81XU6XUVyNaRGe2j/Tk2RhGOB8dhn+vX5b7/tdO7mv1nUGu9sgyNVG7zVq0lz21Rl3qlMH3np/V6iM3ihq+E4IIR3DXsDH8F5iBLgI2Xuruk9kQXmd3vglr7y22fuduppH3TOqJQkstfae3GkuvugM8UdnuAZCCOluKBnVikpLS6FUKiEWi7V+LhaLkZamv5xaJpNBJpOx31dV6QYWbUFfo+fXR0nw28U8NrhJKaxC9q0amJuZIjajlD1u2ZgAHE4uxkcHU7Ftdn9klNRonef5QT1hxTdFTEoxXt91Bb/Pj8AHfzUmeUprGnfYS75Zhag7zcArahvYJMyBqzfRx80G4/q4ILesFgolg3mDvbBk52Wd9zB3kBfq5Ap26RzQuBPeG7svo5+nHdtcPN9Y0Ca2RplUjkBXIb47cV0nATR3kBf4plw4Cfls0GEo+JArGfwRX8COQy8XIXrYGw/+FCpGK7hRqlRYtueq3kSSvsotfUmW5pIyCpXudd6Lzhp8NQ28NVEZvX7U8J0QQjoHdQJKk6H7+e64fLw9LhCv7kjUeY7m/a6fhy12vvgILudXwtPeEstGB2BDrG6s0zSW6KjJnebu053hPt4ZroEQQroLWqbXwVatWgUbGxv2y8PDo11eV18vgOd/vISoIDHbU0gk4MHeio9Xd+guMYsKEoNhGKQWVeucR/24+jxFlTKdhIy6z9NQiQg7F0Ti/fFBEAn4SC+qYZfbNSZfpLiSV8k2KNdc3nc1vxK3pQ1a5dLB7jZYN7UfCsrrsOZwOib0c2tsgB4l0TsOS0ZKYMrl4M+EAjwb7q71GuumhsDRmgc3O4tmK4cM9Va4USpFhJe93udoBnTqvj6e9laYN0i3txagf+meviSLsd4Gb4zyx/PbLnbbBt9URn9vqOE7IYR0Xobu56U1cvRwsGzR/U49UTZ720X8cafX5chA7UnTprEE9UgihBDSHjgMwzAdfRHdhVwuh6WlJXbv3o0JEyawP581axYqKirw559/6jxHX2WUh4cHKisrIRTeW8VKS5VJ5ew/QJsKdBFisJ8IG2KzsGCoN2IzSg0e98Zof6w5lN7seRYO9cZJI+cZKhEhKsgZDMPAzNQENfUKnMu+jV/O5QAAlo0JYJfiedpbIresFnvi87Fuaj8EughRq6dcOve2FKevlSLnduOxMyJ7oLerDT47koGM4sblcEtGSWBjboqNp7JRUF6HDycEwdGaD5UKYMDAzIQDK54Z7Fqw7bHB8XQVYvXEPhj/zRmdxzSXOWqdr0aGxLwKrNW41jdH+0Noboq3/0xuXM7nbI0VY3shxEAFi1SmQGJexd3lf87WWD4mAEdTSrDt7A291/nL3IhuE2CWSeVURt+M5n5vu9PvAyGGVFVVwcbGpk3vuaT9dJfPs2kLhab3c837v7H7nbrfZ1NfTgnBquhUOAj4BmMJfXGEsbiDEELIw6U17rl0N2lFPB4PYWFhOHr0KJuMUqlUOHr0KBYtWqT3OXw+H3w+X+9jbcVoLwCNvkTN9VpytTFv0Xku51fitVESzP3xks5xcwd5Iau0BoWV9fj62DWtpX79PO0Qk1KMw8nFWDYmAFtO32hMzjhbY93UfmxAZKfn9U1NuPjlXC77D+0vYjIxwKtx6Z7yTrLpfNbtuzv/TQ6GUsXA096queHT0VxvBVtLM+2+UBoBnT7G+ke0tFeBvt4GsgYlZp+/aPA6u1ODb0qiNI8avhNCSOdibOm0ofu/ofudsSbkG2OzsGtBJAR8M4PPpx5JhBBC2holo1rZkiVLMGvWLISHh2PAgAH48ssvIZVKMWfOnI6+NJbRXgAafYmMNsgUW8OqheeZFOqOE+kl+GFmGL6IyWSrfeYO8sLpa7cwto8rXvjpbqJKvdRv7eS+SMgtR0JuOXq7CrHyiUCIbfiwteA1W63EAbSamAPAhexyfPFPJp4N98AXMXerjt55IhCe9paQaOw6cy+a660g4JvhUV+rew7ozM1MwDCN/6t2r4Gg5vE3K+qMfl4t32+RdAfU8J0QQjoX9dJpNfXSaUOV1MY0N/FowuW2KKagBBQhhJC2Qj2jWtmUKVOwdu1arFy5EiEhIUhMTMShQ4d0mpp3JKM9haL8cbWgEqZcDq7kV+L1Ufp7La0Y1wvu9lYGzzN3kBeuFlTis8nBOJRchJ/P5SI6qQjvPhmItZODMVQiwp74fEzp74kvYjL0nmPL6Rt4bZSEbZg+bfN5vLQ9AcmFVZDKFEbfI9/MBEn5VTq9pkYHOSMxtxyLR/rhl7kR+HJKCAb62KOfp919l523tLeCui9Uc4GdVKZgS+uHrDmO6ZvO4/S10mbfc3PUCTp95g7yAoeyUQ8V6glCCCHtp0wqR0F5HcqkcoOPG6pk+uhgqsHnGaKecNCHJhwIIYR0BtQzqpNpr34HxnoByBQqtoKnuV4F7HkOpLKVRm9E+UOhVLEVFyIBH3nltdgdlw8TLge7FkQCACprG5BbVotXfk+EUqX7a2jK5WDHi49g0vqzOo+1ZJbw9LVSvPp7gk6vqS+mhMDXSQC+aeuVnLdmbwVDPR7uZ2ZUU5lUjq/+yURvd+HdJY93KtSuFlTilcf9KAHxkKGeIORh1116DJFGnfHzbOmupQXldRiy5rjBeOjkm8PgpmfHPWPaKp4ghBBCWuOeS8moTqa9A6mWNnpu7rj0omqkFlbhxm0pBvs54K/LRejt1pj00OwDlVRQpZX0yCuT4sWf4w02N5/Qzw0fH9SdKWxJg+WO+If2gzbObuum0oYSdOum9qPA9CFGDd/Jw6ozJi/I/euMn2dLE0Jtcf+nCQdCCCFthRqYkwfW0sCmuUTV+38lY2KoG778JxNlUjmGShy1Gpar+0BtmRWudS6G0e3tpLZ4pAQr9l3V+5otabDcEc03H/T8bd1Uup+HLdZN7acVmKqbwZOOo7lzUkckgygBRQghra+5pXeaCSb10ml9iav7XTpNTcgJIYR0ZpSMIg+sTq7E+ewyWPFNsXZyX5RLG/DZEf19oNbGZCDE004rGFL3dmq6dEzWoITIio+SKpnOee6l30FXCrzauqk0BaadS0uXbxBCCOl67nWCqZ+H7T3tvttSdJ8nhBDSGVEDc/LA1AmUmJRirI5Og7+zdYuDL2tzM4T2sMXq6DQM9hPh/fFBGOwnwqroxpnE16MMNFDvpg2W26updEubqZO2pd45KaWwCkoVw+6clJhX0dGXRggh5AHdaxNxzQmjk28Owy9zG5fy0eQEIYSQ7oiSUeSBqJcXfTKpL0QCHkpr5Pj3emmLgy87Kx7c7S3x7pNBOJVZinf3J+NUZineeSIQYqE5QtwbZwkDXe/siOcqxPZ5Ed16WZl6ZvRhes8Po9beOYkQQkjncr8TTDRhRAgh5GFAUy3kvuhbXvTppL6IzSzFHwkFWD6mF17dkajzPH3Bl7/YGgqlClP6e8BbZAWeGRdCvik8HazuzBLyH6plZbSU7uHQ1v3BCCGEdLy2WnpHCCGEdHW0m14n0xl3gtHH0O4wPz8/AL5iAUy5HBRVynC9tAbphVW4nF+Jl4b5Gt3BhXb0Ig+Ttt45kRDSvK5yzyUt05k/T4pxCCGEdCetcc+lZXrknhlbXrTqUBpMOBykF9dg6Z4reG3nZZzMKMWCoT7NbiVMZenkYdJe/cEIIYR0PIpxCCGEEG2UjCL3zNjyots1MqQWVes0ZZ655QI1ZSakCeoPRgghhBBCCHkYUc8ocs/Uu8PoW140b7A3PolO0/u8jw6m0tKjTkLdeN6CR8sFOhL1ByOEEEIIIYQ8jKgyitwzY8uLIr0dqClzJ1EmlaOgvE5rVzapTMH2+xqy5jimbzqP09dKIZUpOvBKCS3fIIQQQgghhDxMKBlF7ouh5UWO1jz4i631PkfibA0LMxMA+hMlpHUYSzgl5FXoLKGcvuk8LaEkhBBCCCGEENJuaDe9TqYz7wSjj77dYQzttKfuhZOQV4GPD6Qivbga/mJrvDWuF/o109yctJyh8f9r0SAs3XOFdm8jhJA7uto9lxhHnychhBDSPmg3PdLh9C0vMtaUmSpz2paxnQ6vl9bQEkpCCCGEEEIIIR2OSlFIqzPUlLlcKkfqzSp8NKE38sprsTsuH6U1jcv0qLl56zC202F6YZXBxvOaSygJIYQQQgghhJC2RJVRpM1oVk1JZQpcKajEHwkFWLk/GbEZpVg2JgAjA8UAqDKntah3OtTncn4llo0J0PvYirG9KBFICCGEEEIIIaRdUDKKtIuEvArM2nJBa3ne67uuICpIDJGAR5U5rcTYTocvDfNFWA87g0soCSGEEEIIIYSQ9kDL9EibM9bHaMvpG5gU6o4hEkeqzGkl6p5dHx1MRUZRNSTO1lgxthdC7jSJ17eEkhBCCCGEEEIIaS+UjCJtzlgfo4zianz6TF94iaza+aq6r5YknCgBRQghhBBCCCGko1AyirQ5dR8jvY2zxdZwtbWAFZ9+FVsbJZwIIYQQQgghhHRG1DOKtDljfYxWjKPG2YQQQgghhBBCyMOEklGkXaj7GFHjbEIIIYQQQggh5OFGa6NIu6DG2YQQQgghhBBCCAEoGUXaGSWgCCGEEEIIIYSQhxst0yOEEEIIIYQQQggh7YaSUYQQQgghhBBCCCGk3VAyihBCCCGEEEIIIYS0G0pGEUIIIYQQQgghhJB2Qw3MCSGEdBplUjnq5EpY8GjHTUIIIYQQQrorSkYRQgjpcFKZAgl5Ffj4QCrSi6vhL7bGW+N6oZ+HLaz4dKsihBBCCCGkO6FleoQQQjpcQl4Fpm86j5TCKihVDFIKqzB903kk5lV09KURQgghhBBCWhklowghhHSoMqkcHx9I1fvYRwdTUSaVt/MVEUIIIYQQQtoSJaMIIYR0qDq5EunF1XofyyiqRl2Dsp2viBBCCCGEENKWKBlFCCGkQ1nwTOAvttb7mMTZGhZmJu18RYQQQgghhJC2RMkoQgghHcreioe3xvXS+9iKsb1oVz1CCCGEEEK6GUpGEUII6XD9PGyxfV4EAl2FMOVyEOgqxPZ5EQjxsO3oSyOk02toaMDSpUvRp08fWFlZwdXVFTNnzsTNmze1jisrK8O0adMgFApha2uLuXPnoqamRuuYK1euYPDgwTA3N4eHhwc+/fTTZl8/NzcX48aNg6WlJZycnPDGG29AoVBoHXPixAmEhoaCz+fD19cX27Zt0znPt99+i549e8Lc3BwRERG4cOHCvQ8GIYQQQroESkYRQgjpcFZ8UzzqK8IvcyNw8s1h+GVuBB71FcGKb9rRl0ZIp1dbW4v4+Hi88847iI+Px969e5Geno7x48drHTdt2jQkJycjJiYGf//9N2JjYzF//nz28aqqKowaNQo9evRAXFwc1qxZg/feew8bN240+NpKpRLjxo2DXC7Hv//+ix9//BHbtm3DypUr2WOys7Mxbtw4DBs2DImJiXj11Vcxb948HD58mD1mx44dWLJkCd59913Ex8cjODgYUVFRKCkpacWRIoQQQkhnwWEYhunoiyB3VVVVwcbGBpWVlRAKhR19OYQQQki31Z3vuRcvXsSAAQOQk5MDT09PpKamIjAwEBcvXkR4eDgA4NChQxg7dizy8/Ph6uqK9evXY8WKFSgqKgKP17g8dtmyZdi3bx/S0tL0vk50dDSeeOIJ3Lx5E2KxGADw/fffY+nSpbh16xZ4PB6WLl2KAwcOICkpiX3e1KlTUVFRgUOHDgEAIiIi0L9/f3zzzTcAAJVKBQ8PD7z88stYtmxZi95zd/48CSGEkM6kNe65VBlFCCGEENLNVFZWgsPhwNbWFgBw9uxZ2NrasokoABgxYgS4XC7Onz/PHjNkyBA2EQUAUVFRSE9PR3l5ud7XOXv2LPr06cMmotTPqaqqQnJyMnvMiBEjtJ4XFRWFs2fPAgDkcjni4uK0juFyuRgxYgR7jD4ymQxVVVVaX4QQQgjpGigZRQghhBDSjdTX12Pp0qV47rnn2NnKoqIiODk5aR1namoKe3t7FBUVscdoJpUAsN+rj2mqJc8xdExVVRXq6upQWloKpVKp9xhDrwsAq1atgo2NDfvl4eFh8FhCCCGEdC6UjCKEEEII6UK2b98OgUDAfp06dYp9rKGhAc8++ywYhsH69es78Crb3vLly1FZWcl+5eXldfQlEUIIIaSFqDMsIYQQQkgXMn78eERERLDfu7m5AbibiMrJycGxY8e0ejg4OzvrNANXKBQoKyuDs7Mze0xxcbHWMerv1cc05ezsrLPrXdPnGDqvUCiEhYUFTExMYGJiovcYQ68LAHw+H3w+3+DjhBBCCOm8qDKKEEIIIaQLsba2hq+vL/tlYWHBJqIyMzPxzz//wMHBQes5kZGRqKioQFxcHPuzY8eOQaVSsYmtyMhIxMbGoqGhgT0mJiYG/v7+sLOz03stkZGRuHr1qlaiKyYmBkKhEIGBgewxR48e1XpeTEwMIiMjAQA8Hg9hYWFax6hUKhw9epQ9hhBCCCHdCyWjCCGEEEK6sIaGBjzzzDO4dOkStm/fDqVSiaKiIhQVFUEulwMAevXqhdGjR+OFF17AhQsXcObMGSxatAhTp06Fq6srAOA///kPeDwe5s6di+TkZOzYsQPr1q3DkiVLDL72qFGjEBgYiBkzZuDy5cs4fPgw3n77bbz00kts1dKCBQuQlZWFN998E2lpafjuu++wc+dOLF68mD3PkiVL8MMPP+DHH39EamoqFi5cCKlUijlz5rThyBFCCCGko9AyPUIIIYSQLqygoAD79+8HAISEhGg9dvz4cTz22GMAGntNLVq0CI8//ji4XC4mTZqEr776ij3WxsYGR44cwUsvvYSwsDCIRCKsXLkS8+fPZ485ceIEhg0bhuzsbPTs2RMmJib4+++/sXDhQkRGRsLKygqzZs3CBx98wD7Hy8sLBw4cwOLFi7Fu3Tq4u7tj06ZNiIqKYo+ZMmUKbt26hZUrV6KoqAghISE4dOiQTlNzQgghhHQPHIZhmI6+CHJXVVUVbGxsUFlZqdXrgRBCCCGti+65927r1q34+OOPkZKSAjMzs46+HC30eRJCCCHtozXuubRMjxBCCCGEtMjBgwfx8ccfd7pEFCGEEEK6FlqmRwghhBBCWmTXrl0dfQmEEEII6QaoMooQQgghhBBCCCGEtBtKRhFCCCGEEEIIIYSQdtNpklENDQ1YunQp+vTpAysrK7i6umLmzJm4efOm1nFlZWWYNm0ahEIhbG1tMXfuXNTU1Ggdc+XKFQwePBjm5ubw8PDAp59+2uzr5+bmYty4cbC0tISTkxPeeOMNKBQKrWNOnDiB0NBQ8Pl8+Pr6Ytu2bTrn+fbbb9GzZ0+Ym5sjIiICFy5cuPfBIIQQQgghhBBCCOmmOk0yqra2FvHx8XjnnXcQHx+PvXv3Ij09HePHj9c6btq0aUhOTkZMTAz+/vtvxMbGam05XFVVhVGjRqFHjx6Ii4vDmjVr8N5772Hjxo0GX1upVGLcuHGQy+X4999/8eOPP2Lbtm1YuXIle0x2djbGjRuHYcOGITExEa+++irmzZuHw4cPs8fs2LEDS5Yswbvvvov4+HgEBwcjKioKJSUlrThShBBCCCGEEEIIIV0Xh2EYpqMvwpCLFy9iwIAByMnJgaenJ1JTUxEYGIiLFy8iPDwcAHDo0CGMHTsW+fn5cHV1xfr167FixQoUFRWBx+MBAJYtW4Z9+/YhLS1N7+tER0fjiSeewM2bNyEWiwEA33//PZYuXYpbt26Bx+Nh6dKlOHDgAJKSktjnTZ06FRUVFTh06BAAICIiAv3798c333wDAFCpVPDw8MDLL7+MZcuWteg907bEhBBCSPuge273Qp8nIYQQ0j5a457baSqj9KmsrASHw4GtrS0A4OzZs7C1tWUTUQAwYsQIcLlcnD9/nj1myJAhbCIKAKKiopCeno7y8nK9r3P27Fn06dOHTUSpn1NVVYXk5GT2mBEjRmg9LyoqCmfPngUAyOVyxMXFaR3D5XIxYsQI9hhCCCGEEEIIIYSQh51pR1+AIfX19Vi6dCmee+45NtNWVFQEJycnreNMTU1hb2+PoqIi9hgvLy+tY9RJpqKiItjZ2em8VlFRkVYiqulzjB1TVVWFuro6lJeXQ6lU6j3GUEUWAMhkMshkMvb7qqoqg8cS0lrKpHLUyZWw4JnA3orX/BMIIYQQ0qXQvZ4QQkhn1mGVUdu3b4dAIGC/Tp06xT7W0NCAZ599FgzDYP369R11ie1i1apVsLGxYb88PDw6+pJINyaVKXD6WimmbzqPIWuOY/qm8zh9rRRSmaL5JxNCCCGk06N7PSGEkK6gw5JR48ePR2JiIvulXnqnTkTl5OQgJiZGa/2hs7OzTjNwhUKBsrIyODs7s8cUFxdrHaP+Xn1MUy15jqFjhEIhLCwsIBKJYGJiovcYQ68LAMuXL0dlZSX7lZeXZ/BYQh5UQl4Fpm86j5TCKihVDFIKqzB903kk5lV09KURQgghpBXQvZ4QQkhX0GHJKGtra/j6+rJfFhYWbCIqMzMT//zzDxwcHLSeExkZiYqKCsTFxbE/O3bsGFQqFSIiIthjYmNj0dDQwB4TExMDf39/vUv01M+5evWqVqJLnQgLDAxkjzl69KjW82JiYhAZGQkA4PF4CAsL0zpGpVLh6NGj7DH68Pl8CIVCrS9C2kKZVI6PD6Tqfeyjg6kok8rb+YoIIYQQ0proXk8IIaSr6DQNzBsaGvDMM8/g0qVL2L59O5RKJYqKilBUVAS5vPHG2atXL4wePRovvPACLly4gDNnzmDRokWYOnUqXF1dAQD/+c9/wOPxMHfuXCQnJ2PHjh1Yt24dlixZYvC1R40ahcDAQMyYMQOXL1/G4cOH8fbbb+Oll14Cn88HACxYsABZWVl48803kZaWhu+++w47d+7E4sWL2fMsWbIEP/zwA3788UekpqZi4cKFkEqlmDNnThuOHCEtUydXIr24Wu9jGUXVqGtQtvMVEUIIIaQ10b2eEEJIV9FpklEFBQXYv38/8vPzERISAhcXF/br33//ZY/bvn07AgIC8Pjjj2Ps2LEYNGgQNm7cyD5uY2ODI0eOIDs7G2FhYXjttdewcuVKzJ8/nz3mxIkT4HA4uHHjBgDAxMQEf//9N0xMTBAZGYnp06dj5syZ+OCDD9jneHl54cCBA4iJiUFwcDA+++wzbNq0CVFRUewxU6ZMwdq1a7Fy5UqEhIQgMTERhw4d0mlqTkhHsOCZwF9srfcxibM1LMxM2vmKCCGEENKa6F5PCCGkq+AwDMN09EW0t61bt+Ljjz9GSkoKzMzMOvpytFRVVcHGxgaVlZW0ZI+0OnVD06a2z4vAo76iDrgiQgjpOHTP7V7o82xE93pCCCFtrTXuuZ2mMqo9HTx4EB9//HGnS0QR0tb6edhi+7wIBLoKYcrlINBViO3zIhDiYdvRl0YIIYSQVkD3ekIIIV3BQ1kZ1ZnRrB5pD2VSOeoalLAwM4G9Fa+jL4cQQjoE3XO7F/o8tdG9nhBCSFtpjXuuaStfEyGkC6CglBBCCOne6F5PCCGkM3sol+kRQgghhBBCCCGEkI5ByShCCCGEEEIIIYQQ0m4oGUUIIYQQQgghhBBC2g0lowghhBBCCCGEEEJIu6FkFCGEEEIIIYQQQghpN5SMIoQQQgghhBBCCCHthpJRhBBCCCGEEEIIIaTdmHb0BRBtDMMAAKqqqjr4SgghhJDuTX2vVd97SddGMRQhhBDSPlojhqJkVCdTXV0NAPDw8OjgKyGEEEIeDtXV1bCxsenoyyAPiGIoQgghpH09SAzFYWg6sFNRqVS4efMmrK2tweFwdB6vqqqCh4cH8vLyIBQKO+AKHw40zm2Pxrh90Di3PRrj9tEW48wwDKqrq+Hq6goulzoXdHUUQ3U8GuP2QePc9miM2weNc9trqzFujRiKKqM6GS6XC3d392aPEwqF9B9sO6Bxbns0xu2Dxrnt0Ri3j9YeZ6qI6j4ohuo8aIzbB41z26Mxbh80zm2vLcb4QWMomgYkhBBCCCGEEEIIIe2GklGEEEIIIYQQQgghpN1QMqqL4fP5ePfdd8Hn8zv6Uro1Gue2R2PcPmic2x6NcfugcSYPin6H2h6NcfugcW57NMbtg8a57XXmMaYG5oQQQgghhBBCCCGk3VBlFCGEEEIIIYQQQghpN5SMIoQQQgghhBBCCCHthpJRhBBCCCGEEEIIIaTdUDKqi/n222/Rs2dPmJubIyIiAhcuXOjoS2pXsbGxePLJJ+Hq6goOh4N9+/ZpPc4wDFauXAkXFxdYWFhgxIgRyMzM1DqmrKwM06ZNg1AohK2tLebOnYuamhqjr1tfX4+XXnoJDg4OEAgEmDRpEoqLi7WOyc3Nxbhx42BpaQknJye88cYbUCgUWsecOHECoaGh4PP58PX1xbZt2+57LNrKqlWr0L9/f1hbW8PJyQkTJkxAenq61jGtNR5NteSzuXLlCgYPHgxzc3N4eHjg008/1TnPrl27EBAQAHNzc/Tp0wcHDx68z9FoG+vXr0ffvn0hFAohFAoRGRmJ6Oho9nEa39a3evVqcDgcvPrqq+zPaJwf3HvvvQcOh6P1FRAQwD5OY0w6C4qfKH5qaxQ/tQ+KodofxVBtg2IoAAzpMn7//XeGx+MxW7ZsYZKTk5kXXniBsbW1ZYqLizv60trNwYMHmRUrVjB79+5lADB//PGH1uOrV69mbGxsmH379jGXL19mxo8fz3h5eTF1dXXsMaNHj2aCg4OZc+fOMadOnWJ8fX2Z5557zujrLliwgPHw8GCOHj3KXLp0iXnkkUeYgQMHso8rFAqmd+/ezIgRI5iEhATm4MGDjEgkYpYvX84ek5WVxVhaWjJLlixhUlJSmK+//poxMTFhDh061DqD00qioqKYrVu3MklJSUxiYiIzduxYxtPTk6mpqWGPaY3x0Ke5z6ayspIRi8XMtGnTmKSkJOa3335jLCwsmA0bNrDHnDlzhjExMWE+/fRTJiUlhXn77bcZMzMz5urVq604Sg9m//79zIEDB5iMjAwmPT2deeuttxgzMzMmKSmJYRga39Z24cIFpmfPnkzfvn2Z//u//2N/TuP84N59910mKCiIKSwsZL9u3brFPk5jTDoDip8ofmoPFD+1D4qh2hfFUG2HYiiGoWRUFzJgwADmpZdeYr9XKpWMq6srs2rVqg68qo7TNJhSqVSMs7Mzs2bNGvZnFRUVDJ/PZ3777TeGYRgmJSWFAcBcvHiRPSY6OprhcDhMQUGB3tepqKhgzMzMmF27drE/S01NZQAwZ8+eZRimMcjjcrlMUVERe8z69esZoVDIyGQyhmEY5s0332SCgoK0zj1lyhQmKirqPkegfZSUlDAAmJMnTzIM03rj0VRLPpvvvvuOsbOz0zrH0qVLGX9/f/b7Z599lhk3bpzWuSMiIpgXX3zxfoegXdjZ2TGbNm2i8W1l1dXVjJ+fHxMTE8MMHTqUDaRonFvHu+++ywQHB+t9jMaYdBYUP2mj+Kl9UPzUfiiGahsUQ7UtiqEYhpbpdRFyuRxxcXEYMWIE+zMul4sRI0bg7NmzHXhlnUd2djaKioq0xsjGxgYRERHsGJ09exa2trYIDw9njxkxYgS4XC7Onz+v97xxcXFoaGjQOm9AQAA8PT21ztunTx+IxWL2mKioKFRVVSE5OZk9RvMc6mM6++dXWVkJALC3twfQeuPRVEs+m7Nnz2LIkCHg8Xha501PT0d5eTl7TFcaZ6VSid9//x1SqRSRkZE0vq3spZdewrhx43Sumca59WRmZsLV1RXe3t6YNm0acnNzAdAYk86B4qfmUfzUNih+ansUQ7UtiqHa3sMeQ1EyqosoLS2FUqnU+mUDALFYjKKiog66qs5FPQ7GxqioqAhOTk5aj5uamsLe3t7gOBYVFYHH48HW1tboefW9ruZ1GTqmqqoKdXV1LX2b7UqlUuHVV1/Fo48+it69ewNovfFoqiWfzYOMc2f77+Tq1asQCATg8/lYsGAB/vjjDwQGBtL4tqLff/8d8fHxWLVqlc5jNM6tIyIiAtu2bcOhQ4ewfv16ZGdnY/DgwaiurqYxJp0CxU/No/ip9VH81LYohmp7FEO1PYqhANN7OpoQ8lB56aWXkJSUhNOnT3f0pXQ7/v7+SExMRGVlJXbv3o1Zs2bh5MmTHX1Z3UZeXh7+7//+DzExMTA3N+/oy+m2xowZw/7/vn37IiIiAj169MDOnTthYWHRgVdGCCEdh+KntkUxVNuiGKp9UAxFlVFdhkgkgomJiU4H/eLiYjg7O3fQVXUu6nEwNkbOzs4oKSnRelyhUKCsrMzgODo7O0Mul6OiosLoefW9ruZ1GTpGKBR2yj84ixYtwt9//43jx4/D3d2d/XlrjUdTLflsHmScO9t/JzweD76+vggLC8OqVasQHByMdevW0fi2kri4OJSUlCA0NBSmpqYwNTXFyZMn8dVXX8HU1BRisZjGuQ3Y2tpCIpHg2rVr9LtMOgWKn5pH8VProvip7VEM1bYohuoYD2MMRcmoLoLH4yEsLAxHjx5lf6ZSqXD06FFERkZ24JV1Hl5eXnB2dtYao6qqKpw/f54do8jISFRUVCAuLo495tixY1CpVIiIiNB73rCwMJiZmWmdNz09Hbm5uVrnvXr1qtZ/3DExMRAKhQgMDGSP0TyH+pjO9vkxDINFixbhjz/+wLFjx+Dl5aX1eGuNR1Mt+WwiIyMRGxuLhoYGrfP6+/vDzs6OPaYrjHNTKpUKMpmMxreVPP7447h69SoSExPZr/DwcEybNo39/zTOra+mpgbXr1+Hi4sL/S6TToHip+ZR/NQ6KH7qOBRDtS6KoTrGQxlD3VO7c9Khfv/9d4bP5zPbtm1jUlJSmPnz5zO2trZaHfS7u+rqaiYhIYFJSEhgADCff/45k5CQwOTk5DAM07g1sa2tLfPnn38yV65cYZ566im9WxP369ePOX/+PHP69GnGz8+vRVsTe3p6MseOHWMuXbrEREZGMpGRkezj6q01R40axSQmJjKHDh1iHB0d9W5N/MYbbzCpqanMt99+2ym3Jl64cCFjY2PDnDhxQmur0draWvaY1hgPfZr7bCoqKhixWMzMmDGDSUpKYn7//XfG0tJSZ6tRU1NTZu3atUxqairz7rvvdrrtXJctW8acPHmSyc7OZq5cucIsW7aM4XA4zJEjRxiGofFtK5o7wTAMjXNreO2115gTJ04w2dnZzJkzZ5gRI0YwIpGIKSkpYRiGxph0DhQ/UfzUHih+ah8UQ3UMiqFaH8VQDEPJqC7m66+/Zjw9PRkej8cMGDCAOXfuXEdfUrs6fvw4A0Dna9asWQzDNG5P/M477zBisZjh8/nM448/zqSnp2ud4/bt28xzzz3HCAQCRigUMnPmzGGqq6u1jgHAbN26lf2+rq6O+e9//8vY2dkxlpaWzNNPP80UFhZqPefGjRvMmDFjGAsLC0YkEjGvvfYa09DQoHP9ISEhDI/HY7y9vbVeo7PQN75tMR7Z2dkMAOb48ePsz1ry2Vy+fJkZNGgQw+fzGTc3N2b16tU672Hnzp2MRCJheDweExQUxBw4cKB1BqeVPP/880yPHj0YHo/HODo6Mo8//jgbRDEMjW9baRpI0Tg/uClTpjAuLi4Mj8dj3NzcmClTpjDXrl1jH6cxJp0FxU8UP7U1ip/aB8VQHYNiqNZHMRTDcBiGYe6tloqQ7i07OxsSiQQpKSnw8/Pr6Mvpto4fP46JEyciKyuLLfkkrYfGt33QOLc9GmNCugaKn9oH/U1sezTG7YPGue119jGmnlGENHHw4EHMnz+fAqk2dvDgQbz11lud8g9jd0Dj2z5onNsejTEhXQPFT+2D/ia2PRrj9kHj3PY6+xhTZRQhhBBCCCGEEEIIaTdUGUUIIYQQQgghhBBC2g0lowghhBBCCCGEEEJIu6FkFCGEEEIIIYQQQghpN5SMIoQQQgghhBBCCCHthpJRhBBCCCGEEEIIIaTdUDKKEEIIIYQQQgghhLQbSkYRQkgnw+FwsG/fvo6+DEIIIYSQLoPiJ0K6FkpGEUIeamfPnoWJiQnGjRt3T8/r2bMnvvzyy7a5KEIIIYSQToziJ0LIg6JkFCHkobZ582a8/PLLiI2Nxc2bNzv6cgghhBBCOj2KnwghD4qSUYSQh1ZNTQ127NiBhQsXYty4cdi2bZvW43/99Rf69+8Pc3NziEQiPP300wCAxx57DDk5OVi8eDE4HA44HA4A4L333kNISIjWOb788kv07NmT/f7ixYsYOXIkRCIRbGxsMHToUMTHx7fl2ySEEEIIaTUUPxFCWgMlowghD62dO3ciICAA/v7+mD59OrZs2QKGYQAABw4cwNNPP42xY8ciISEBR48exYABAwAAe/fuhbu7Oz744AMUFhaisLCwxa9ZXV2NWbNm4fTp0zh37hz8/PwwduxYVFdXt8l7JIQQQghpTRQ/EUJag2lHXwAhhHSUzZs3Y/r06QCA0aNHo7KyEidPnsRjjz2Gjz76CFOnTsX777/PHh8cHAwAsLe3h4mJCaytreHs7HxPrzl8+HCt7zdu3AhbW1ucPHkSTzzxxAO+I0IIIYSQtkXxEyGkNVBlFCHkoZSeno4LFy7gueeeAwCYmppiypQp2Lx5MwAgMTERjz/+eKu/bnFxMV544QX4+fnBxsYGQqEQNTU1yM3NbfXXIoQQQghpTRQ/EUJaC1VGEUIeSps3b4ZCoYCrqyv7M4ZhwOfz8c0338DCwuKez8nlctkydbWGhgat72fNmoXbt29j3bp16NGjB/h8PiIjIyGXy+/vjRBCCCGEtBOKnwghrYUqowghDx2FQoGffvoJn332GRITE9mvy5cvw9XVFb/99hv69u2Lo0ePGjwHj8eDUqnU+pmjoyOKioq0AqrExEStY86cOYNXXnkFY8eORVBQEPh8PkpLS1v1/RFCCCGEtDaKnwghrYkqowghD52///4b5eXlmDt3LmxsbLQemzRpEjZv3ow1a9bg8ccfh4+PD6ZOnQqFQoGDBw9i6dKlAICePXsiNjYWU6dOBZ/Ph0gkwmOPPYZbt27h008/xTPPPINDhw4hOjoaQqGQPb+fnx9+/vlnhIeHo6qqCm+88cZ9zSISQgghhLQnip8IIa2JKqMIIQ+dzZs3Y8SIETqBFNAYTF26dAn29vbYtWsX9u/fj5CQEAwfPhwXLlxgj/vggw9w48YN+Pj4wNHREQDQq1cvfPfdd/j2228RHByMCxcu4PXXX9d57fLycoSGhmLGjBl45ZVX4OTk1LZvmBBCCCHkAVH8RAhpTRym6QJdQgghhBBCCCGEEELaCFVGEUIIIYQQQgghhJB2Q8koQgghhBBCCCGEENJuKBlFCCGEEEIIIYQQQtoNJaMIIYQQQgghhBBCSLuhZBQhhBBCCCGEEEIIaTeUjCKEEEIIIYQQQggh7YaSUYQQQgghhBBCCCGk3VAyihBCCCGEEEIIIYS0G0pGEUIIIYQQQgghhJB2Q8koQgghhBBCCCGEENJuKBlFCCGEEEIIIYQQQtoNJaMIIYQQQgghhBBCSLv5f3STlhCGJjrDAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Coefficients:\n",
      "              Feature Coefficient\n",
      "1     total_rooms_log  -60,286.63\n",
      "2  total_bedrooms_log   96,715.51\n",
      "3      population_log  -73,240.50\n",
      "4      households_log   43,616.79\n",
      "5       median_income        3.88\n",
      "6     median_income^2        0.00\n",
      "7           longitude  -37,366.74\n",
      "8            latitude  -37,286.13\n",
      "9  housing_median_age      812.71\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Let's now try adding a polynomial transformation\n",
    "results_df, iteration_3 = dw.iterate_model(X1_train, X1_test, y1_train, y1_test,\n",
    "        transformers=['log', 'poly2'], model='linreg',\n",
    "        iteration='3', note='X1. Test size: 0.25, Pipeline: Log > Poly2 > LinReg',\n",
    "        plot=True, lowess=True, coef=True, perm=True, vif=True, decimal=2,\n",
    "        save=True, save_df=results_df, config=my_config)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-6 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-6 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-6 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-6 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-6 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-6 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-6 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-6 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-6 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-6 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-6 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-6 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-6 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-6 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-6 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-6 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-6 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-6\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;log_poly2&#x27;,\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;log&#x27;, LogTransformer(),\n",
       "                                                  [&#x27;total_rooms&#x27;,\n",
       "                                                   &#x27;total_bedrooms&#x27;,\n",
       "                                                   &#x27;population&#x27;,\n",
       "                                                   &#x27;households&#x27;]),\n",
       "                                                 (&#x27;poly2&#x27;,\n",
       "                                                  PolynomialFeatures(include_bias=False),\n",
       "                                                  [&#x27;median_income&#x27;])])),\n",
       "                (&#x27;linreg&#x27;, LinearRegression())])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-34\" type=\"checkbox\" ><label for=\"sk-estimator-id-34\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;log_poly2&#x27;,\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;log&#x27;, LogTransformer(),\n",
       "                                                  [&#x27;total_rooms&#x27;,\n",
       "                                                   &#x27;total_bedrooms&#x27;,\n",
       "                                                   &#x27;population&#x27;,\n",
       "                                                   &#x27;households&#x27;]),\n",
       "                                                 (&#x27;poly2&#x27;,\n",
       "                                                  PolynomialFeatures(include_bias=False),\n",
       "                                                  [&#x27;median_income&#x27;])])),\n",
       "                (&#x27;linreg&#x27;, LinearRegression())])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-35\" type=\"checkbox\" ><label for=\"sk-estimator-id-35\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;log_poly2: ColumnTransformer<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.compose.ColumnTransformer.html\">?<span>Documentation for log_poly2: ColumnTransformer</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>ColumnTransformer(force_int_remainder_cols=False, remainder=&#x27;passthrough&#x27;,\n",
       "                  transformers=[(&#x27;log&#x27;, LogTransformer(),\n",
       "                                 [&#x27;total_rooms&#x27;, &#x27;total_bedrooms&#x27;, &#x27;population&#x27;,\n",
       "                                  &#x27;households&#x27;]),\n",
       "                                (&#x27;poly2&#x27;,\n",
       "                                 PolynomialFeatures(include_bias=False),\n",
       "                                 [&#x27;median_income&#x27;])])</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-36\" type=\"checkbox\" ><label for=\"sk-estimator-id-36\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">log</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;total_rooms&#x27;, &#x27;total_bedrooms&#x27;, &#x27;population&#x27;, &#x27;households&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-37\" type=\"checkbox\" ><label for=\"sk-estimator-id-37\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">LogTransformer</label><div class=\"sk-toggleable__content fitted\"><pre>LogTransformer()</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-38\" type=\"checkbox\" ><label for=\"sk-estimator-id-38\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">poly2</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;median_income&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-39\" type=\"checkbox\" ><label for=\"sk-estimator-id-39\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;PolynomialFeatures<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.PolynomialFeatures.html\">?<span>Documentation for PolynomialFeatures</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>PolynomialFeatures(include_bias=False)</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-40\" type=\"checkbox\" ><label for=\"sk-estimator-id-40\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">remainder</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;longitude&#x27;, &#x27;latitude&#x27;, &#x27;housing_median_age&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-41\" type=\"checkbox\" ><label for=\"sk-estimator-id-41\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">passthrough</label><div class=\"sk-toggleable__content fitted\"><pre>passthrough</pre></div> </div></div></div></div></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-42\" type=\"checkbox\" ><label for=\"sk-estimator-id-42\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;LinearRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.linear_model.LinearRegression.html\">?<span>Documentation for LinearRegression</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>LinearRegression()</pre></div> </div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('log_poly2',\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder='passthrough',\n",
       "                                   transformers=[('log', LogTransformer(),\n",
       "                                                  ['total_rooms',\n",
       "                                                   'total_bedrooms',\n",
       "                                                   'population',\n",
       "                                                   'households']),\n",
       "                                                 ('poly2',\n",
       "                                                  PolynomialFeatures(include_bias=False),\n",
       "                                                  ['median_income'])])),\n",
       "                ('linreg', LinearRegression())])"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the pipeline\n",
    "iteration_3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Iteration 4: Linear Regression with OHE, Log, Poly2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "ITERATION 4 RESULTS\n",
      "\n",
      "Pipeline: ohe_log_poly2 -> linreg\n",
      "Note: X2. Test size: 0.25, Pipeline: OHE > Log > Poly2 > LinReg\n",
      "May 30, 2024 09:17 AM UTC\n",
      "\n",
      "Predictions:\n",
      "                          Train            Test\n",
      "MSE:            3,231,250,156.15 3,242,416,485.65\n",
      "RMSE:                 56,844.09       56,942.22\n",
      "MAE:                  41,276.18       41,406.32\n",
      "R^2 Score:                 0.64            0.66\n",
      "\n",
      "Permutation Feature Importance:\n",
      "           Feature Importance Mean Importance Std\n",
      "     median_income            0.92           0.01\n",
      "    total_bedrooms            0.72           0.01\n",
      "        population            0.61           0.01\n",
      "          latitude            0.61           0.01\n",
      "         longitude            0.59           0.01\n",
      "       total_rooms            0.26           0.01\n",
      "        households            0.23           0.00\n",
      "   ocean_proximity            0.06           0.00\n",
      "housing_median_age            0.02           0.00\n",
      "\n",
      "Variance Inflation Factor:\n",
      "          Features   VIF Multicollinearity\n",
      "    total_bedrooms 32.40              High\n",
      "        households 30.01              High\n",
      "       total_rooms 13.80              High\n",
      "          latitude  8.74          Moderate\n",
      "         longitude  8.43          Moderate\n",
      "        population  6.75          Moderate\n",
      "     median_income  1.83               Low\n",
      "housing_median_age  1.30               Low\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Coefficients:\n",
      "                       Feature Coefficient\n",
      "1    ocean_proximity_<1H OCEAN   -4,421.89\n",
      "2       ocean_proximity_INLAND  -38,314.09\n",
      "3       ocean_proximity_ISLAND   69,133.27\n",
      "4     ocean_proximity_NEAR BAY  -23,189.14\n",
      "5   ocean_proximity_NEAR OCEAN   -3,208.17\n",
      "6              total_rooms_log  -46,665.44\n",
      "7           total_bedrooms_log   80,641.63\n",
      "8               population_log  -72,784.50\n",
      "9               households_log   45,310.14\n",
      "10               median_income        3.54\n",
      "11             median_income^2        0.00\n",
      "12                   longitude  -26,238.41\n",
      "13                    latitude  -24,484.78\n",
      "14          housing_median_age      730.23\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Let's see if one-hot encoding the categorical feature 'ocean_proximity' helps\n",
    "results_df, iteration_4 = dw.iterate_model(X2_train, X2_test, y2_train, y2_test,\n",
    "        transformers=['ohe', 'log', 'poly2'], model='linreg',\n",
    "        iteration='4', note='X2. Test size: 0.25, Pipeline: OHE > Log > Poly2 > LinReg',\n",
    "        plot=True, lowess=True, coef=True, perm=True, vif=True, decimal=2,\n",
    "        save=True, save_df=results_df, config=my_config)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-7 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-7 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-7 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-7 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-7 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-7 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-7 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-7 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-7 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-7 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-7 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-7 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-7 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-7 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-7 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-7 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-7 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-7\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;ohe_log_poly2&#x27;,\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;ohe&#x27;,\n",
       "                                                  OneHotEncoder(drop=&#x27;if_binary&#x27;,\n",
       "                                                                handle_unknown=&#x27;ignore&#x27;),\n",
       "                                                  [&#x27;ocean_proximity&#x27;]),\n",
       "                                                 (&#x27;log&#x27;, LogTransformer(),\n",
       "                                                  [&#x27;total_rooms&#x27;,\n",
       "                                                   &#x27;total_bedrooms&#x27;,\n",
       "                                                   &#x27;population&#x27;,\n",
       "                                                   &#x27;households&#x27;]),\n",
       "                                                 (&#x27;poly2&#x27;,\n",
       "                                                  PolynomialFeatures(include_bias=False),\n",
       "                                                  [&#x27;median_income&#x27;])])),\n",
       "                (&#x27;linreg&#x27;, LinearRegression())])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-43\" type=\"checkbox\" ><label for=\"sk-estimator-id-43\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;ohe_log_poly2&#x27;,\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;ohe&#x27;,\n",
       "                                                  OneHotEncoder(drop=&#x27;if_binary&#x27;,\n",
       "                                                                handle_unknown=&#x27;ignore&#x27;),\n",
       "                                                  [&#x27;ocean_proximity&#x27;]),\n",
       "                                                 (&#x27;log&#x27;, LogTransformer(),\n",
       "                                                  [&#x27;total_rooms&#x27;,\n",
       "                                                   &#x27;total_bedrooms&#x27;,\n",
       "                                                   &#x27;population&#x27;,\n",
       "                                                   &#x27;households&#x27;]),\n",
       "                                                 (&#x27;poly2&#x27;,\n",
       "                                                  PolynomialFeatures(include_bias=False),\n",
       "                                                  [&#x27;median_income&#x27;])])),\n",
       "                (&#x27;linreg&#x27;, LinearRegression())])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-44\" type=\"checkbox\" ><label for=\"sk-estimator-id-44\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;ohe_log_poly2: ColumnTransformer<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.compose.ColumnTransformer.html\">?<span>Documentation for ohe_log_poly2: ColumnTransformer</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>ColumnTransformer(force_int_remainder_cols=False, remainder=&#x27;passthrough&#x27;,\n",
       "                  transformers=[(&#x27;ohe&#x27;,\n",
       "                                 OneHotEncoder(drop=&#x27;if_binary&#x27;,\n",
       "                                               handle_unknown=&#x27;ignore&#x27;),\n",
       "                                 [&#x27;ocean_proximity&#x27;]),\n",
       "                                (&#x27;log&#x27;, LogTransformer(),\n",
       "                                 [&#x27;total_rooms&#x27;, &#x27;total_bedrooms&#x27;, &#x27;population&#x27;,\n",
       "                                  &#x27;households&#x27;]),\n",
       "                                (&#x27;poly2&#x27;,\n",
       "                                 PolynomialFeatures(include_bias=False),\n",
       "                                 [&#x27;median_income&#x27;])])</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-45\" type=\"checkbox\" ><label for=\"sk-estimator-id-45\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">ohe</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;ocean_proximity&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-46\" type=\"checkbox\" ><label for=\"sk-estimator-id-46\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;OneHotEncoder<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.OneHotEncoder.html\">?<span>Documentation for OneHotEncoder</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>OneHotEncoder(drop=&#x27;if_binary&#x27;, handle_unknown=&#x27;ignore&#x27;)</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-47\" type=\"checkbox\" ><label for=\"sk-estimator-id-47\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">log</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;total_rooms&#x27;, &#x27;total_bedrooms&#x27;, &#x27;population&#x27;, &#x27;households&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-48\" type=\"checkbox\" ><label for=\"sk-estimator-id-48\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">LogTransformer</label><div class=\"sk-toggleable__content fitted\"><pre>LogTransformer()</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-49\" type=\"checkbox\" ><label for=\"sk-estimator-id-49\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">poly2</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;median_income&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-50\" type=\"checkbox\" ><label for=\"sk-estimator-id-50\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;PolynomialFeatures<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.PolynomialFeatures.html\">?<span>Documentation for PolynomialFeatures</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>PolynomialFeatures(include_bias=False)</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-51\" type=\"checkbox\" ><label for=\"sk-estimator-id-51\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">remainder</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;longitude&#x27;, &#x27;latitude&#x27;, &#x27;housing_median_age&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-52\" type=\"checkbox\" ><label for=\"sk-estimator-id-52\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">passthrough</label><div class=\"sk-toggleable__content fitted\"><pre>passthrough</pre></div> </div></div></div></div></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-53\" type=\"checkbox\" ><label for=\"sk-estimator-id-53\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;LinearRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.linear_model.LinearRegression.html\">?<span>Documentation for LinearRegression</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>LinearRegression()</pre></div> </div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('ohe_log_poly2',\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder='passthrough',\n",
       "                                   transformers=[('ohe',\n",
       "                                                  OneHotEncoder(drop='if_binary',\n",
       "                                                                handle_unknown='ignore'),\n",
       "                                                  ['ocean_proximity']),\n",
       "                                                 ('log', LogTransformer(),\n",
       "                                                  ['total_rooms',\n",
       "                                                   'total_bedrooms',\n",
       "                                                   'population',\n",
       "                                                   'households']),\n",
       "                                                 ('poly2',\n",
       "                                                  PolynomialFeatures(include_bias=False),\n",
       "                                                  ['median_income'])])),\n",
       "                ('linreg', LinearRegression())])"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the pipeline\n",
    "iteration_4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Iteration 5: Linear Regression with Ordinal, Log, Poly2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "ITERATION 5 RESULTS\n",
      "\n",
      "Pipeline: ord_log_poly2 -> linreg\n",
      "Note: X2. Test size: 0.25, Pipeline: Ord > Log > Poly2 > LinReg\n",
      "May 30, 2024 09:17 AM UTC\n",
      "\n",
      "Predictions:\n",
      "                          Train            Test\n",
      "MSE:            3,323,311,153.49 3,339,547,363.35\n",
      "RMSE:                 57,648.17       57,788.82\n",
      "MAE:                  42,307.00       42,378.78\n",
      "R^2 Score:                 0.63            0.65\n",
      "\n",
      "Permutation Feature Importance:\n",
      "           Feature Importance Mean Importance Std\n",
      "          latitude            1.22           0.01\n",
      "         longitude            1.02           0.01\n",
      "     median_income            1.01           0.01\n",
      "    total_bedrooms            0.99           0.01\n",
      "        population            0.59           0.01\n",
      "       total_rooms            0.41           0.01\n",
      "        households            0.21           0.00\n",
      "housing_median_age            0.02           0.00\n",
      "   ocean_proximity            0.00           0.00\n",
      "\n",
      "Variance Inflation Factor:\n",
      "          Features   VIF Multicollinearity\n",
      "    total_bedrooms 32.40              High\n",
      "        households 30.01              High\n",
      "       total_rooms 13.80              High\n",
      "          latitude  8.74          Moderate\n",
      "         longitude  8.43          Moderate\n",
      "        population  6.75          Moderate\n",
      "     median_income  1.83               Low\n",
      "housing_median_age  1.30               Low\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Coefficients:\n",
      "               Feature Coefficient\n",
      "1      ocean_proximity    3,815.27\n",
      "2      total_rooms_log  -58,936.46\n",
      "3   total_bedrooms_log   94,196.95\n",
      "4       population_log  -72,001.58\n",
      "5       households_log   43,435.62\n",
      "6        median_income        3.86\n",
      "7      median_income^2        0.00\n",
      "8            longitude  -34,484.02\n",
      "9             latitude  -34,728.43\n",
      "10  housing_median_age      783.22\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# For one last try, let's see if ordinal encoding 'ocean_proximity' is better\n",
    "results_df, iteration_5 = dw.iterate_model(X2_train, X2_test, y2_train, y2_test,\n",
    "        transformers=['ord', 'log', 'poly2'], model='linreg',\n",
    "        iteration='5', note='X2. Test size: 0.25, Pipeline: Ord > Log > Poly2 > LinReg',\n",
    "        plot=True, lowess=True, coef=True, perm=True, vif=True, decimal=2,\n",
    "        save=True, save_df=results_df, config=my_config)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-8 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-8 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-8 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-8 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-8 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-8 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-8 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-8 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-8 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-8 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-8 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-8 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-8 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-8 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-8 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-8 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-8 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-8 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-8 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-8 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-8 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-8 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-8 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-8 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-8 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-8 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-8 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-8 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-8 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-8 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-8 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-8 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-8 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-8 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-8 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-8 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-8 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-8 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-8 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-8 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-8 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-8 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-8\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;ord_log_poly2&#x27;,\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;ord&#x27;,\n",
       "                                                  OrdinalEncoder(categories=[[&#x27;INLAND&#x27;,\n",
       "                                                                              &#x27;&lt;1H &#x27;\n",
       "                                                                              &#x27;OCEAN&#x27;,\n",
       "                                                                              &#x27;NEAR &#x27;\n",
       "                                                                              &#x27;OCEAN&#x27;,\n",
       "                                                                              &#x27;NEAR &#x27;\n",
       "                                                                              &#x27;BAY&#x27;,\n",
       "                                                                              &#x27;ISLAND&#x27;]]),\n",
       "                                                  [&#x27;ocean_proximity&#x27;]),\n",
       "                                                 (&#x27;log&#x27;, LogTransformer(),\n",
       "                                                  [&#x27;total_rooms&#x27;,\n",
       "                                                   &#x27;total_bedrooms&#x27;,\n",
       "                                                   &#x27;population&#x27;,\n",
       "                                                   &#x27;households&#x27;]),\n",
       "                                                 (&#x27;poly2&#x27;,\n",
       "                                                  PolynomialFeatures(include_bias=False),\n",
       "                                                  [&#x27;median_income&#x27;])])),\n",
       "                (&#x27;linreg&#x27;, LinearRegression())])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-54\" type=\"checkbox\" ><label for=\"sk-estimator-id-54\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;ord_log_poly2&#x27;,\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;ord&#x27;,\n",
       "                                                  OrdinalEncoder(categories=[[&#x27;INLAND&#x27;,\n",
       "                                                                              &#x27;&lt;1H &#x27;\n",
       "                                                                              &#x27;OCEAN&#x27;,\n",
       "                                                                              &#x27;NEAR &#x27;\n",
       "                                                                              &#x27;OCEAN&#x27;,\n",
       "                                                                              &#x27;NEAR &#x27;\n",
       "                                                                              &#x27;BAY&#x27;,\n",
       "                                                                              &#x27;ISLAND&#x27;]]),\n",
       "                                                  [&#x27;ocean_proximity&#x27;]),\n",
       "                                                 (&#x27;log&#x27;, LogTransformer(),\n",
       "                                                  [&#x27;total_rooms&#x27;,\n",
       "                                                   &#x27;total_bedrooms&#x27;,\n",
       "                                                   &#x27;population&#x27;,\n",
       "                                                   &#x27;households&#x27;]),\n",
       "                                                 (&#x27;poly2&#x27;,\n",
       "                                                  PolynomialFeatures(include_bias=False),\n",
       "                                                  [&#x27;median_income&#x27;])])),\n",
       "                (&#x27;linreg&#x27;, LinearRegression())])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-55\" type=\"checkbox\" ><label for=\"sk-estimator-id-55\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;ord_log_poly2: ColumnTransformer<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.compose.ColumnTransformer.html\">?<span>Documentation for ord_log_poly2: ColumnTransformer</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>ColumnTransformer(force_int_remainder_cols=False, remainder=&#x27;passthrough&#x27;,\n",
       "                  transformers=[(&#x27;ord&#x27;,\n",
       "                                 OrdinalEncoder(categories=[[&#x27;INLAND&#x27;,\n",
       "                                                             &#x27;&lt;1H OCEAN&#x27;,\n",
       "                                                             &#x27;NEAR OCEAN&#x27;,\n",
       "                                                             &#x27;NEAR BAY&#x27;,\n",
       "                                                             &#x27;ISLAND&#x27;]]),\n",
       "                                 [&#x27;ocean_proximity&#x27;]),\n",
       "                                (&#x27;log&#x27;, LogTransformer(),\n",
       "                                 [&#x27;total_rooms&#x27;, &#x27;total_bedrooms&#x27;, &#x27;population&#x27;,\n",
       "                                  &#x27;households&#x27;]),\n",
       "                                (&#x27;poly2&#x27;,\n",
       "                                 PolynomialFeatures(include_bias=False),\n",
       "                                 [&#x27;median_income&#x27;])])</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-56\" type=\"checkbox\" ><label for=\"sk-estimator-id-56\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">ord</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;ocean_proximity&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-57\" type=\"checkbox\" ><label for=\"sk-estimator-id-57\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;OrdinalEncoder<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.OrdinalEncoder.html\">?<span>Documentation for OrdinalEncoder</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>OrdinalEncoder(categories=[[&#x27;INLAND&#x27;, &#x27;&lt;1H OCEAN&#x27;, &#x27;NEAR OCEAN&#x27;, &#x27;NEAR BAY&#x27;,\n",
       "                            &#x27;ISLAND&#x27;]])</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-58\" type=\"checkbox\" ><label for=\"sk-estimator-id-58\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">log</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;total_rooms&#x27;, &#x27;total_bedrooms&#x27;, &#x27;population&#x27;, &#x27;households&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-59\" type=\"checkbox\" ><label for=\"sk-estimator-id-59\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">LogTransformer</label><div class=\"sk-toggleable__content fitted\"><pre>LogTransformer()</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-60\" type=\"checkbox\" ><label for=\"sk-estimator-id-60\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">poly2</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;median_income&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-61\" type=\"checkbox\" ><label for=\"sk-estimator-id-61\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;PolynomialFeatures<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.PolynomialFeatures.html\">?<span>Documentation for PolynomialFeatures</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>PolynomialFeatures(include_bias=False)</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-62\" type=\"checkbox\" ><label for=\"sk-estimator-id-62\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">remainder</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;longitude&#x27;, &#x27;latitude&#x27;, &#x27;housing_median_age&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-63\" type=\"checkbox\" ><label for=\"sk-estimator-id-63\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">passthrough</label><div class=\"sk-toggleable__content fitted\"><pre>passthrough</pre></div> </div></div></div></div></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-64\" type=\"checkbox\" ><label for=\"sk-estimator-id-64\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;LinearRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.linear_model.LinearRegression.html\">?<span>Documentation for LinearRegression</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>LinearRegression()</pre></div> </div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('ord_log_poly2',\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder='passthrough',\n",
       "                                   transformers=[('ord',\n",
       "                                                  OrdinalEncoder(categories=[['INLAND',\n",
       "                                                                              '<1H '\n",
       "                                                                              'OCEAN',\n",
       "                                                                              'NEAR '\n",
       "                                                                              'OCEAN',\n",
       "                                                                              'NEAR '\n",
       "                                                                              'BAY',\n",
       "                                                                              'ISLAND']]),\n",
       "                                                  ['ocean_proximity']),\n",
       "                                                 ('log', LogTransformer(),\n",
       "                                                  ['total_rooms',\n",
       "                                                   'total_bedrooms',\n",
       "                                                   'population',\n",
       "                                                   'households']),\n",
       "                                                 ('poly2',\n",
       "                                                  PolynomialFeatures(include_bias=False),\n",
       "                                                  ['median_income'])])),\n",
       "                ('linreg', LinearRegression())])"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the pipeline\n",
    "iteration_5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Iteration 6: Linear Regression with OHE, Log, Poly3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "ITERATION 6 RESULTS\n",
      "\n",
      "Pipeline: ohe_log_poly3 -> linreg\n",
      "Note: X2. Test size: 0.25, Pipeline: OHE > Log > Poly3 > LinReg\n",
      "May 30, 2024 09:17 AM UTC\n",
      "\n",
      "Predictions:\n",
      "                          Train            Test\n",
      "MSE:            3,191,564,996.57 3,179,359,775.40\n",
      "RMSE:                 56,493.94       56,385.81\n",
      "MAE:                  41,117.33       41,107.58\n",
      "R^2 Score:                 0.65            0.66\n",
      "\n",
      "Permutation Feature Importance:\n",
      "           Feature Importance Mean Importance Std\n",
      "     median_income            0.95           0.01\n",
      "    total_bedrooms            0.76           0.01\n",
      "        population            0.62           0.01\n",
      "          latitude            0.60           0.01\n",
      "         longitude            0.58           0.01\n",
      "       total_rooms            0.29           0.01\n",
      "        households            0.24           0.00\n",
      "   ocean_proximity            0.05           0.00\n",
      "housing_median_age            0.02           0.00\n",
      "\n",
      "Variance Inflation Factor:\n",
      "          Features   VIF Multicollinearity\n",
      "    total_bedrooms 32.40              High\n",
      "        households 30.01              High\n",
      "       total_rooms 13.80              High\n",
      "          latitude  8.74          Moderate\n",
      "         longitude  8.43          Moderate\n",
      "        population  6.75          Moderate\n",
      "     median_income  1.83               Low\n",
      "housing_median_age  1.30               Low\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Coefficients:\n",
      "                       Feature Coefficient\n",
      "1    ocean_proximity_<1H OCEAN   13,653.03\n",
      "2       ocean_proximity_INLAND  -19,527.72\n",
      "3       ocean_proximity_ISLAND      100.12\n",
      "4     ocean_proximity_NEAR BAY   -5,699.28\n",
      "5   ocean_proximity_NEAR OCEAN   15,294.44\n",
      "6              total_rooms_log  -49,206.07\n",
      "7           total_bedrooms_log   82,928.70\n",
      "8               population_log  -73,367.99\n",
      "9               households_log   46,297.94\n",
      "10               median_income        0.30\n",
      "11             median_income^2        0.00\n",
      "12             median_income^3        0.00\n",
      "13                   longitude  -26,119.29\n",
      "14                    latitude  -24,332.90\n",
      "15          housing_median_age      753.07\n"
     ]
    },
    {
     "data": {
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ERB+0d3L73suKFCmCsmXLIjQ0FLa2tkhNTUVcXJxWm4cPH+Y6BxUAZfurK/S9/BhbW1vExMRo7U9PT0dsbKxWm9x+xsu/Izfjxo3Ds2fPlK+oqKg3/MVERERERERERPS23slE5y9LTExEWFgYevTogWrVqsHAwACHDx9G+/btAQA3btxAZGQkateunevjXVxcYGtri8OHD6NKlSoAslbSO3v2LAYPHgwAqF27NuLi4nDhwgVUq1YNAHDkyBFkZmaiZs2aSpvx48cjLS0NBgYGAICDBw+iXLlysLKyem1+IyMjGBkZvZO+ICIiIlI7Z9+9siO8N7dntpIdgYiI6D/tX4+UGjNmDI4dO4bbt2/j1KlT+OKLL6Cvr48uXbrA0tIS3t7eGD16NI4ePYoLFy6gT58+qF27dq4r7wGARqPByJEj8f3332PXrl24cuUKevbsCXt7e7Rr1w4A4OHhgebNm6N///44d+4cTp48iWHDhqFz586wt7cHAHTt2hWGhobw9vbG1atXsWnTJixYsACjR4/+t38yERERERERERH9S/96pNTdu3fRpUsXPHnyBCVKlEC9evVw5swZlChRAgAwb9486OnpoX379khJSUGzZs3w888/a/0MZ2dn9O7dG5MnTwYAfPPNN3j+/DkGDBiAuLg41KtXDwEBATA2NlYes379egwbNgyNGzdWfv7ChQuV/ZaWljhw4ACGDh2KatWqoXjx4pg4cSIGDBjwb/9kIiIiIiIiIiL6lzRCCCEzQFJSEooVK4b9+/ejYcOGMqPkKj4+HpaWlnj27BksLCxkxyEiIipwPtTbs3hr1rvxoR4fAI8RIiKi18lvLeWdT3T+to4ePYpPP/20QBakiIiIiIiIiIjo/ZBelGrVqhX27v1wr6AREREREREREVFO0otSRERERERERESkPixKERERERERERGRzrEoRUREREREREREOseiFBERERERERER6RyLUkREREREREREpHMsShERERERERERkc6xKEVERERERERERDrHohQREREREREREekci1JERERERERERKRzLEoREREREREREZHOsShFREREREREREQ6x6IUERERERERERHpHItSRERERERERESkcyxKERERERERERGRzrEoRUREREREREREOseiFBERERERERER6RyLUkREREREREREpHOFZAcgIqKCz9l3r+wI78Xtma1kRyAiIiIiUi0WpVSEHyqJiIiIiIiIqKDg7XtERERERERERKRzLEoREREREREREZHOsShFREREREREREQ6x6IUERERERERERHpnCqKUkuWLIGzszOMjY1Rs2ZNnDt3TnYkIiIiIiIiIiJV++CLUps2bcLo0aMxadIkBAYGonLlymjWrBliYmJkRyMiIiIiIiIiUq0Pvig1d+5c9O/fH3369IGnpyeWLVsGU1NTrFq1SnY0IiIiIiIiIiLV+qCLUqmpqbhw4QKaNGmibNPT00OTJk1w+vRpicmIiIiIiIiIiNTtgy5KPX78GBkZGbCxsdHabmNjg+jo6Fwfk5KSgvj4eK0vALh69arS5tq1a4iKigIAJCcnIzAwEAkJCQCAhw8fIigoSGl748YN3LlzBwCQlpaGwMBAPHv2DADw6NEjXLx4UWl769YtREREAAAyMjIQGBiIp0+fAgCePHmCwMBACCEAAGFhYQgLCwMACCEQGBiIJ0+eAACePn2KwMBAZGRkAAAiIiJw69Yt5fekPgxDRlJWhsyU50iJDoXISAcApD+LQdqTu3+3jQlHxvOn/982KattempW2/hHSH0c+XfbR7eRnhib1TY1GSnRochMS8lqm/AYqY/uvNT2DtLjH2e1TUvJapv6IqttYixSYyKUtmmPo5Aen3W7pUhPy2qbkpTVT8+f4tKlS1r9ffv2ba3+jouLU/o7MDBQq7/Dw8O1+js2Nit/bGwsAgMDkZmZCQAIDw9HaGio8tjAwEA8fvxYq7/T09OV/r5586bS9tKlS8rtovHx8QgMDERqalYfRkZGIiQkRGl7+fJl5dhMTExEYGAgkpOTAQB3797FtWvXlLbBwcG4f/8+ACApKQmBgYFISsrql/v37yM4OFhpe+3aNdy9m/X/NfuYTUxMBABER0fj8uXLStuQkBBERmb9f01NTUVgYKDyPIiJidHq75s3byrHbHp6utYx+/jxY63+Dg0NVfo7MzMz1/7OPmbDw8O1jtnAwEA8evQIABAXF4fAwECkpaUBAG7fvo0bN25o9ffDhw+1+jslJUXp7+vXr2v194MHD7T6+8WLF0p/v/y8v3r1Ku7duwcAePHiBQIDA/H8+XMAwIMHD3DlyhWt/v4vnyMuXryo9PezZ8+yfu5/+ByR+jD877ZP7iL9WdbxITLSeY74f//2HPF3f8dp93fsPaTFZeUVmRlIiQ5FRnLWz81IeoaU6L/7LO3p/b/bisysti+ynjcZLxKyjq3MrGM2LS4aabH3lMemRIf+/bqWnPjK69pD7WP2YW7HbNb5JD0+BmmPo7T6m+eI/J0jss/Jd+7c0TonBwUF/afPESnRoch83TEbe4/nCPB9BM8R//4ckd3fCQkJWsdsVFSU1jF75coVpb+fP3+u1d/37t3L0d/Zx2x2f2cfsw8ePNA6Zq9fv64csykpKVrH7MOHD/lZAwX3HGHXewGcfffC2XcvSg78BSUH+cHZdy+cfHbDrvcCOHz1K5x998Lhq19h13sBnL7ZldV2kB9KDlihPNau9wI4jNgAZ9+9cBy5Kavt2J1w9t2LUoNXoWT/5Upb+z6L4DD8f1ltR/2W1XbMjqy2Q1ajZL9lf7ftuxilhq3Lajt6C+x6L4Dj19v+v+0a2Hv//Hdb759RauiarLZfb/ugzhFvJD5g9+7dEwDEqVOntLaPHTtW1KhRI9fHTJo0SQDI8WVnZ6e0qVixohg+fLgQQohbt24JAOLo0aNCCCFmzZolrKyslLa1atUS3t7eQggh7t+/LwCIPXv2CCGEWLx4sTA0NFTaNm7cWHTu3FkIIcSzZ88EALF582YhhBCrV68WAERaWpoQQojWrVuL1q1bCyGESEtLEwDE6tWrhRBCbN68WQAQz549E0II0blzZ9G4cWPl9xgaGorFixcLIYTYs2ePACDu378vhBDC29tb1KpVS2lrZWUlZs2aJYQQ4ujRowKAuHXrlhBCiOHDh4uKFSsqbUuWLCkmTZokhBDi3LlzAoAICgoSQgjh6+srXF1dlbZly5YVY8aMEUIIERwcrPX/adq0acLW1lZpW7VqVTFkyBAhhBARERECgDh48KAQQog5c+YIc3NzpW3dunVFr169hBBCxMTECABi586dQgghli1bJvT19ZW2xs5VhWm5usLJZ49wGLVFABDFW48VTj57RLHPvxYAhOPX24WTzx5hUra2MCldXTj57BFOPll9VrT5cOHks0eUaPetACBKjdgonHz2CDPPhsLIoYLSVmNgJKwaDxBOPnuE9ZdTBABRcrC/cPLZIwpXbi4MbcsobfVMLESRT3oKJ589wqbbjwKAsO+3TDj57BHm1dsKg2KOSlt9C2thUbuTcPLZI2x7zRcAhG2v+UIIIcaPHy+cnJyUv9XT01OMGjVKCCFESEiIACD+/PNPIYQQM2bMEMWLF1faVq9eXQwYMEAIIURUVJQAIAICAoQQQixYsECYmpoqbRs0aCC6desmhBDiyZMnAoDYunWrEEKIX375Rbx8imnZsqX44osvhBBCJCcnCwBi3bp1QgghNmzYIACIxMREIYQQHTp0EE2bNlUeq6+vL5YtWyaEEGLnzp0CgIiJiRFCCNGrVy9Rt25dpa25ubmYM2eOEEKIgwcPCgAiIiJCCCHEkCFDRNWqVZW2tra2Ytq0aUIIIU6dOiUAiODgYCGEEBY1vEShoiWV/i5UxE5Y1OognHz2CLs+i7L6u+dc4eSzR1jW7SL0CxdT2hqUcBbm1VoLJ589wn7ACgFA2HSZIZx89ogiDfsIPePCSltD+3KicKWmwslnjyg5dK0AIEp0mCScfPaIop8NEtAvpLQ1dqosTD0+yTpmR2Y9z4u39c06ZluOzDpmx+7MOmbdaggTtxrCyWePcByb1WfFWo4UQvAckd9zRNOmTUWHDh2EEEIkJiYKAGLDhg1CCPGfPkc4+ewRFrU7CX0L67+P2WKOwrx6WyEEzxH5PUeMGTNGlC1bVmnr6uoqfH19hRDiP32OcPLZI4q39RUAhMPIzcLJZ48w9fhEGDtVFk4+We9feI7Iktc5Yt26dQKASE5OFkII8cUXX4iWLVsqjwUgfvnlFyGEEFu3bhUAxJMnT4QQQnTr1k00aNBAaWtqaioWLFgghBAiICBAABBRUVFCCCEGDBggqlevrrQtXry4mDFjhhBCiD///FMAECEhIUIIIUaNGiU8PT2Vtk5OTmL8+PFCCCEuXLggAIgLFy4IIfg+4n2fI4KCggQAce7cOSFE1uePkiVLKm35WePvc4RBCee/X9cKFxOWdbtkva71nJv1Ga3PoqzXtVodRKEidn+/bytaUljU8Mp639Z3SdY5uftPWefk+t2FvpnV3+dZG1dRuGqrrPPsID8BQFh3+l44+ewRVo28hcbQRGlrVNJTmFVoLJx89ohSw9dnnZO9JmSdk5sNFdDo/X1Ozsdnjbc9RxT09xFOPnuEfb9lWa9r3X7Mel37pKfQM7H4u79ty4jClZtn9fdg/6z+/nKKEILniA/tHJH9GpB9rngdjRD/X+r6AKWmpsLU1BRbtmxBu3btlO29evVCXFwcdu7cmeMxKSkpytUQIKva7ODggFOnTqF27doAsiqT5ubmcHBwQHJyMq5du4YyZcrA3NwcDx8+RHR0NCpXrgwgqzJpbGwMJycnpKWl4cqVK3B1dYWlpSUePXqEu3fvomrVqgCyKpOFChWCi4sLMjIyEBQUBBcXF1hZWeHJkye4c+cOqlatCo1Go1QlXV1dIYTAxYsX4eTkhGLFiuHp06eIiIhA5cqVoa+vj4iICKSnp6NMmTIAsq5elCpVCiVKlMCzZ88QFhaGihUrwsDAAHfu3EFycjLKlSsHIOvqha2tLWxsbJCQkIBbt27B09MTxsbGiIqKQkJCAjw9PQFkXb0oXrw47Ozs8Pz5c9y4cQMeHh4wMTHBvXv3EBcXh/LlywPIunphaWmJUqVK4cWLF7h+/TrKli2LwoUL48GDB3j06BEqVaoEIOvqhZmZGRwdHZGSkoKrV6/Czc0NFhYWePjwIR48eIAqVaoo/W1kZARnZ2elv0uXLo0iRYrg0aNHiIqKwkcffQQAKDlgBaCnD4MithCZGUiNiUAhSxvom5gj40UC0p89hKFNaWg0ellX70UmDKzss46T6FAUsigBfVNLZCQnIj0uGobWLtDo6We1zcyAQdGSWcfhw3DoFy4KfbMiyExJQtrT+zAs4QSNvgHS42Mg0lJgUMwhq21MBPRNi0C/sBUyU18gLfYeDIs7QlPIEOnxj5GZmgTD4o5ZbR/dhp6xOQqZF0NmWjLSntyFQbFSiJzTHvfv30dsbCwqVKigHLMWFhYoVaqUcsxm93d0dDRiYmKU/g4JCYGpqSkcHR2RmpqK4OBgpb9jYmJw//59pb9v3rwJAwMDuLi4ID09HZcvX1aO2cePHyMyMlLp79DQUOjp6aF06dLIzMzEpUuX4OzsjKJFiyI2Nha3b99Wjtnw8HBkZGQox2xgYCAcHBxQokQJxMXFITw8XDlmb9++jZSUFOWYvXTpEuzs7GBjY4P4+HiEhoaifPnyMDIyQmRkJJ4/fw4PDw8AWVeLSpQoATs7OyQmJuLmzZvKMVtqyBpkpjyHYQmn/+/vO9AzNkMh8+LITEtB2pMoGBQtBT1DY6QnxiLzRTwMSzhntX0cCT1DExSyKAGRnorUx5EwsLKHnpEpMp4/RcbzpzC0Lg0g66q8ppAhCllaQ2SkI/XRbRhY2UHPyAwZSc+QkfAYhjauWW1j7+U8ZovYQt+4MDJexCP9WQwMbVyh0WiQ9jTrSqKBlR2EEEh9GIZCltaIWtCF54h8niNu3boFfX19lC5dWjknZx+zDl/9+p89R+gZGCM94QkykxNeOWZNcffnXjxH5PMccffuXTx79kzrmC1SpAhKliwJx6+3/WfPEfomFnkes7dntuI5Ih/niOxjtkqVKtDT00N4eDgyMzPh5uamHLOOjo4oXry4ck6uVKkSChUqhIiICKSlpaFs2bLKMWtvbw9ra2vlmK1QoQIMDQ0RGRmJpKQkuLu7K8estbU1bG1tlWM2u7/v3r2L+Ph4pb+Dg4NRtGhR2NvbIykpCSEhIXB3d4epqSnfR7znc0T2MVuuXDmYmZnhwYMHePz4MSpWrKj0Nz9rZJ0jak7Zo/26ZmKBQoWLIjM1GWmxd2FQzAF6BkZIT3iMzORX3rcZmaGQxcvv20pCz9Ak65yc9AyG1i5Z587HUdAYGqGQhTVEehpSH9/RPicnPoWhzcvnZAMUsrT5+5xcxBZ6xoWRkfQM6fGPYGTr9vpz8kufNXb2KvvW5wi3734v0O8jClkU//t17f/7OyPxKTKS4v7u7ydR0Bj8f39npCH1UVZ/R877kueID+wc4eLigqJFi+LZs2ewsLDA63zQRSkAqFmzJmrUqIFFixYByBru6+joiGHDhsHX1/eNj4+Pj4elpeUbO5L+e5x998qO8F7cntlKdoQPAo8PyguPD8rLh3p8ADxGiEi3eD7Vxv6g/5L81lIK6TCTFKNHj0avXr1QvXp11KhRA/Pnz8fz58/Rp08f2dGIiIiIiIiIiFTrgy9KderUCY8ePcLEiRMRHR2NKlWqICAgIMfk50REL+PVGiIiIiIiovfrgy9KAcCwYcMwbNgw2TGIiIiIiIiIiOj/6ckOQERERERERERE6sOiFBERERERERER6RyLUkREREREREREpHMsShERERERERERkc6xKEVERERERERERDrHohQREREREREREekci1JERERERERERKRzLEoREREREREREZHOFZIdgEiW2zNbyY5AREREREREpFocKUVERERERERERDrHohQREREREREREekci1JERERERERERKRznFOKiIiIiIiIqIDjnLj0IWJRioiIiIiIiAocFmGIPny8fY+IiIiIiIiIiHSORSkiIiIiIiIiItI5FqWIiIiIiIiIiEjnWJQiIiIiIiIiIiKdY1GKiIiIiIiIiIh0jkUpIiIiIiIiIiLSORaliIiIiIiIiIhI51iUIiIiIiIiIiIinWNRioiIiIiIiIiIdI5FKSIiIiIiIiIi0jkWpYiIiIiIiIiISOdYlCIiIiIiIiIiIp3710Wp3r17Q6PRaH01b95cq01sbCy6desGCwsLFClSBN7e3khMTMzz5yYnJ2Po0KEoVqwYChcujPbt2+Phw4dabSIjI9GqVSuYmprC2toaY8eORXp6ulabP/74Ax999BGMjIzg5uYGf3//f/snExERERERERHRv/RORko1b94cDx48UL42btyotb9bt264evUqDh48iD179uD48eMYMGBAnj9z1KhR2L17N3777TccO3YM9+/fh5eXl7I/IyMDrVq1QmpqKk6dOoU1a9bA398fEydOVNpERESgVatWaNSoES5duoSRI0eiX79++P3339/Fn01ERERERERERP9QoXfxQ4yMjGBra5vrvuvXryMgIAB//fUXqlevDgBYtGgRWrZsidmzZ8Pe3j7HY549ewY/Pz9s2LABn376KQBg9erV8PDwwJkzZ1CrVi0cOHAA165dw6FDh2BjY4MqVapg2rRp8PHxweTJk2FoaIhly5bBxcUFc+bMAQB4eHjgxIkTmDdvHpo1a/Yu/nQiIiIiIiIiIvoH3slIqT/++APW1tYoV64cBg8ejCdPnij7Tp8+jSJFiigFKQBo0qQJ9PT0cPbs2Vx/3oULF5CWloYmTZoo29zd3eHo6IjTp08rP7dixYqwsbFR2jRr1gzx8fG4evWq0ubln5HdJvtn5CYlJQXx8fFaX0RERERERERE9G7965FSzZs3h5eXF1xcXBAWFoZvv/0WLVq0wOnTp6Gvr4/o6GhYW1tr/9JChVC0aFFER0fn+jOjo6NhaGiIIkWKaG23sbFRHhMdHa1VkMren70vrzbx8fF48eIFTExMcvzuH374AVOmTMl/BxARkercntlKdgQiIiIiov+8txoptX79ehQuXFj5+vPPP9G5c2e0adMGFStWRLt27bBnzx789ddf+OOPP95T5Pdr3LhxePbsmfIVFRUlOxIRERERERER0QfnrUZKtWnTBjVr1lS+L1myZI42pUuXRvHixREaGorGjRvD1tYWMTExWm3S09MRGxv72nmobG1tkZqairi4OK3RUg8fPlQeY2tri3Pnzmk9Lnt1vpfbvLpi38OHD2FhYZHrKCkga34sIyOjXPcREREREREREdG78VYjpczNzeHm5qZ85VbYuXv3Lp48eQI7OzsAQO3atREXF4cLFy4obY4cOYLMzEytAtfLqlWrBgMDAxw+fFjZduPGDURGRqJ27drKz71y5YpWwevgwYOwsLCAp6en0ubln5HdJvtnEBERERERERGRHP9qovPExESMHTsWZ86cwe3bt3H48GG0bdsWbm5uyup2Hh4eaN68Ofr3749z587h5MmTGDZsGDp37pzrynsAYGlpCW9vb4wePRpHjx7FhQsX0KdPH9SuXRu1atUCADRt2hSenp7o0aMHgoKC8Pvvv+O7777D0KFDlZFOgwYNQnh4OL755huEhITg559/xubNmzFq1Kh/82cTEREREREREdG/9K+KUvr6+rh8+TLatGmDsmXLwtvbG9WqVcOff/6pdQvc+vXr4e7ujsaNG6Nly5aoV68eVqxYofWzNBoN/P39le/nzZuHzz//HO3bt8cnn3wCW1tbbNu2Tet379mzB/r6+qhduza6d++Onj17YurUqUobFxcX7N27FwcPHkTlypUxZ84crFy5UimYERERERERERGRHBohhJAdIiIiAmXLlsW1a9dQpkwZ2XG0xMfHw9LSEs+ePYOFhYXsOERERFTAOfvulR3hveHKk0RERJQf+a2l/KuRUu/Kvn37MGDAgAJXkCIiIiIiIiIiovfjrVbfe1+GDh0qOwIREREREREREelQgRgpRURERERERERE6sKiFBERERERERER6RyLUkREREREREREpHMsShERERERERERkc6xKEVERERERERERDrHohQREREREREREekci1JERERERERERKRzLEoREREREREREZHOFZIdgIiIiOhDcntmK9kRiIiIiP4TOFKKiIiIiIiIiIh0jkUpIiIiIiIiIiLSORaliIiIiIiIiIhI51iUIiIiIiIiIiIineNE528ghAAAxMfHS05CRERERERERFTwZddQsmsqr8Oi1BskJCQAABwcHCQnISIiIiIiIiL670hISIClpeVr92vEm8pWKpeZmYn79+/D3NwcGo1Gdpz/hPj4eDg4OCAqKgoWFhay40jH/tDG/tDG/tDG/tDG/tDG/tDG/tDG/tDG/tDG/tDG/tDG/tDG/tDG/vhnhBBISEiAvb099PReP3MUR0q9gZ6eHkqVKiU7xn+ShYUFn7QvYX9oY39oY39oY39oY39oY39oY39oY39oY39oY39oY39oY39oY39oY3+8vbxGSGXjROdERERERERERKRzLEoREREREREREZHOsShF75yRkREmTZoEIyMj2VEKBPaHNvaHNvaHNvaHNvaHNvaHNvaHNvaHNvaHNvaHNvaHNvaHNvaHNvbH+8WJzomIiIiIiIiISOc4UoqIiIiIiIiIiHSORSkiIiIiIiIiItI5FqWIiIiIiIiIiEjnWJQiInpHfv75Z9kRiIiIiIiI/jM40TkR0TtStGhRfPzxx1i9ejXs7e1lx5Hu+PHj+Wr3ySefvOckRERERERUELEoRXlycXGBRqPJs41Go0FYWJiOEhUMz58/x48//oht27bh9u3b0Gg0cHFxQYcOHTBmzBiYmprKjqhzQghcuHBBqz+qVq36xuPnQ3L//n30798fp0+fxsKFC9G9e3fZkaTS03v9YNzs40Kj0SA9PV1XkQqM+Pj4XLdrNBoYGRnB0NBQx4nk2rVrV67bNRoNjI2N4ebmBhcXFx2nIir4UlNTERERAVdXVxQqVEh2HCKi/7Tk5GQYGxvLjqE6LEpRnhYsWPDafbdv38by5cuRkpKCjIwMHaaSKzU1FXXq1EFwcDBatGgBd3d3CCFw/fp1BAQE4KOPPsLx48dhYGAgO6rOHD16FN7e3rhz5w6yTynZhalVq1apbiSMv78/Ro8ejUaNGmH8+PE5PihUqlRJUjLdevbsWa7bk5KSsGDBAixcuBClS5dGcHCwjpPJp6enl2fBtlSpUujduzcmTZqUZ3HvQ5HdH6++JcneptFoUK9ePezYsQNWVlaSUuoWC5favvjii1yfMy8XLrt27Ypy5cpJSKd7SUlJGD58ONasWQMAuHnzJkqXLo3hw4ejZMmS8PX1lZyQCpKHDx8iJSUFjo6OsqNI8+eff2L58uUICwvDli1bULJkSaxbtw4uLi6oV6+e7Hg6x/74W2ZmJqZPn45ly5bh4cOHyvl0woQJcHZ2hre3t+yIHz5B9JaePHkiRo4cKYyMjMQnn3wiTp8+LTuSTs2fP1/Y2NiIkJCQHPuuX78ubGxsxMKFCyUkk+PWrVvC1NRUNGrUSOzYsUOEhISI69evi61bt4oGDRoIMzMzERYWJjumzh08eFDo6+sLPT09odFotP6rVhkZGeKXX34RpUqVEo6OjmLVqlUiIyNDdiwp1qxZI0qVKiW+++47sWvXLrFr1y7x3XffCQcHB7F8+XLx/fffiyJFiojp06fLjqoThw4dEjVr1hSHDh0S8fHxIj4+Xhw6dEjUrl1b7N27V5w4cUKUL19e9O3bV3ZUnck+X7zuy9HRUUycOFE1z6FevXoJS0tL4eTkJLy8vISXl5dwdnYWRYoUER07dhTlypUTRkZG4sSJE7Kj6sSIESNEtWrVxJ9//qn1Ortjxw5RpUoVyel0a8mSJaJx48biyy+/FIcOHdLa9+jRI+Hi4iIpme7Fx8eLbt26CUdHR9GzZ0+RkpIihgwZopxPPvnkE/Hs2TPZMXVuy5YtwsTERPTr108YGRkpz5dFixaJFi1aSE6ne+wPbVOmTBGlS5cW//vf/4SJiYnSH7/++quoVauW5HTqwKIU5VtSUpLyQaly5cpi7969siNJ8cknn4jFixe/dv/ChQvFJ598osNEcg0dOlR8+umnue7LzMwUn376qRg2bJiOU8k1Z84cYWpqKnr16iVCQ0PF7du3tb7UaOvWraJcuXKiaNGi4qeffhLJycmyI0n16aefik2bNuXYvmnTJuX5tHbtWlGuXDldR5OifPny4uTJkzm2nzhxQnh6egohsgq9Dg4Ouo4mDQuX2nx8fMTgwYO1inAZGRli2LBhYty4cSIzM1MMGDBA1K1bV2JK3XF0dFQuChYuXFj5EHXr1i1hbm4uM5pOLViwQJiamoqhQ4eK7t27C0NDQzFjxgxlf3R0tKouBg0bNky4u7uLhQsXioYNG4q2bduKChUqiBMnTohjx44JT09P8e2338qOqXNVqlQRa9asEUJoP18CAwOFjY2NzGhSsD+0ubq6KgXtl/vj+vXrokiRIjKjqQaLUvRG6enpYunSpcLW1lY4OzuLtWvXiszMTNmxpClevLgIDg5+7f4rV66I4sWL6zCRXOXLlxe7du167f5du3aJ8uXL6zCRPGFhYaJevXrCxsZG7NixQ3acAuGPP/4QNWvWFKampmLcuHEiLi5OdqQCwdjYWNy8eTPH9ps3bwoTExMhhBDh4eHKvz90xsbG4sqVKzm2X758WRgbGwshhLh9+7Zq+kMIFi5fVbx4cXHjxo0c22/cuCGKFSsmhMg6XiwtLXWcTI6Xr+a//CHq0qVLwsLCQmY0nfL09BTr169Xvj958qQoUaKEmDBhghBCfUUpBwcHceTIESGEEPfu3RMajUbs3r1b2b9nzx7VnDNeZmJiIiIiIoQQ2s+XsLAwYWRkJDGZHOwPbcbGxspF45f74+rVq8LMzExmNNX48CeqoH9l8+bN8PDwwMSJE+Hr64sbN26gR48eqpq8+lVxcXEoVqzYa/cXK1bstXPpfIgiIyNRsWLF1+6vUKEC7ty5o8NE8lSqVAk2NjYIDg5G27Ztc22jpvmTWrZsic8++wxVqlRBWFgYZsyYAUtLS9mxCgQHBwf4+fnl2O7n5wcHBwcAwJMnT1Qzf1K1atUwduxYPHr0SNn26NEjfPPNN/j4448BALdu3VL6Rg1OnTqFqlWr5thetWpVnD59GgBQr149REZG6jqaFOnp6QgJCcmxPSQkRJnX0tjYWDXvT6pXr469e/cq32f/3StXrkTt2rVlxdK5iIgI1KlTR/m+Tp06OHLkCFasWIFx48ZJTCZHTEwM3NzcAAD29vYwMTFB2bJllf0VKlRAVFSUrHjS2NraIjQ0NMf2EydOoHTp0hISycX+0Obp6Yk///wzx/YtW7bk+jpM7x6X6aA8de7cGSYmJujSpQvu3Lnz2okz586dq+Nk8mRmZkJfX/+1+/X09FQ18XtiYmKeqw2ampoiKSlJh4nkWbZsWa4r7iUkJGDjxo1YuXIlLly4oJrjIyAgAIUKFcKmTZuwefPm17aLjY3VYaqCYfbs2fjyyy+xf/9+pehy/vx5hISEYMuWLQCAv/76C506dZIZU2f8/PzQtm1blCpVSik8RUVFoXTp0ti5cyeArHPNd999JzOmTmUXLmfOnKm1Xa2Fyx49esDb2xvffvut8pz566+/MGPGDPTs2RMAcOzYMZQvX15mTJ2ZMWMGWrRogWvXriE9PR0LFizAtWvXcOrUKRw7dkx2PJ0pXrw4oqKi4OzsrGyrUKECjhw5gk8//RT379+XF06CYsWK4dGjR8o5om3btihSpIiyPzExEUZGRpLSydO/f3989dVXWLVqFTQaDe7fv4/Tp09jzJgxmDBhgux4Osf+0DZx4kT06tUL9+7dQ2ZmJrZt24YbN25g7dq12LNnj+x4qsDV9yhPDRs2zNdVx6NHj+ogTcGgp6eHChUqvHbp5fT0dFy9elU1hQc9PT0cOXIERYsWzXX/48eP8dlnn6mmP152/Phx+Pn5YevWrbC3t4eXlxfat2+vfKD60GWvCvUmvXr1es9JCqaIiAgsX74cN2/eBACUK1cOAwcO1PpwpSaZmZk4cOCAVn989tlnqlh9MDe7du3Cl19+CXd391wLl59//jmWLl2KW7duqeLCUEZGBmbOnInFixfj4cOHAAAbGxsMHz4cPj4+0NfXR2RkJPT09FCqVCnJaXUjLCwMM2fORFBQEBITE/HRRx/Bx8cnz9HLH5quXbvCxsYG8+bNy7Hv6tWraNSoEZ48eaKa9yAtWrRAu3btMHDgwFz3+/v745dffsHJkyd1nEwuIQRmzJiBH374QblQamRkhDFjxmDatGmS0+ke+yOnP//8E1OnTtU6n06cOBFNmzaVHU0VWJQiektTpkzJV7tJkya95yQFw+uWcge0l3NXyxvC6Oho+Pv7w8/PD/Hx8ejYsSOWLVuGoKAgeHp6yo5X4GRkZOQ58pBIzVi4zF18fDwAwMLCQnISku3y5cu4cOEC+vTpk+v+4OBgbN26VTXvyWJjY6Gnp6c1Oupl+/fvh4mJCRo2bKjTXAVFamoqQkNDkZiYCE9PTxQuXFh2JKnYH1RQsChF/8r169fh5+eH2bNny45CkuR3vignJ6f3nES+1q1b4/jx42jVqhW6deuG5s2bQ19fHwYGBixKveLmzZvw8/PD2rVr8eDBA9lxpIiLi4Ofnx+uX78OAChfvjz69u2r2nm3jh07htmzZyv94enpibFjx6J+/fqSk1FB8ujRI9y4cQMA4O7ujuLFi0tOJFdMTAxiYmKQmZmptb1SpUqSEhEREb0dFqXorT1//hy//vor/Pz8cObMGXh6eqpq8mai1ylUqBBGjBiBwYMHo0yZMsp2FqWyJCUlYdOmTVi1ahVOnz6N6tWro3379hg7dqzsaDp3/vx5NGvWDCYmJqhRowaArPlxXrx4gQMHDuCjjz6SnFC3/ve//6FPnz7w8vJC3bp1AWRNuLpjxw74+/uja9eukhPKwcLl354/f47hw4dj7dq1SgFGX18fPXv2xKJFi/Kc2/BDdOHCBfTq1QvXr1/PMVJZTaOTiV7Hy8sr3223bdv2HpMUDOyP17Oyssp1uhqNRgNjY2O4ubmhd+/erx2RSf8ei1KUbydPnoSfnx82b96MFy9eYNSoUejXrx/c3d1lR9OpRo0avXGeLY1Gg8OHD+sokVz5XfnJ0dHxPSeR78yZM/Dz88OmTZvg4eGBHj16oHPnzrCzs1N1UerMmTNYuXIlfvvtNzg6OuL69es4evSoqkfA1K9fH25ubvjll1+U+enS09PRr18/hIeH4/jx45IT6paHhwcGDBiAUaNGaW2fO3cufvnlF6UooyYsXGobOHAgDh06hMWLF2sVLkeMGIHPPvsMS5culZxQtypXrgxXV1f4+PjAxsYmx/sSNYxOftnIkSMxf/582TEKDPYHtAoIQghs374dlpaWqF69OoCswm5cXBy8vLywevVqWTF1hv3xevPmzcP06dPRokUL5fX23LlzCAgIwKhRoxAREYF169Zh0aJF6N+/v+S0HyYWpShPMTEx8Pf3x6pVq/Ds2TN06dIFXbt2Re3atVX7IfvVD00vS0hIwIYNG5CSkqKaq5TZc0q9KnsuKSCrSJeenq7raNI8f/5cGRF07tw5ZGRkYO7cuejbty/Mzc1lx9OZOXPmaJ07unfvjsqVK3PkGAATExNcvHgxR1H/2rVrqF69umpWrMxmZGSEq1evKkuZZwsNDUWFChWQnJwsKZk8LFxqK168OLZs2ZJjLpyjR4+iY8eOePTokZxgkpibm+PixYs5njNqk5GRgd69eyM0NBSnT5+WHUc69kfufHx8EBsbi2XLlinzWGZkZGDIkCGwsLDATz/9JDmhbrE/tLVv3x6fffYZBg0apLV9+fLlOHDgALZu3YpFixZhxYoVuHLliqSUHzhBlAdjY2PRvXt3ERAQIDIyMpTthQoVElevXpWYrGBJS0sT8+fPFyVKlBBubm5i48aNsiPpzKVLl3L9unjxovDx8REmJiaiRIkSsmNKExISIsaOHStsbW2FsbGxaN26texIOqOvry++/fZbkZ6errWd5w8hrK2txe+//55je0BAgLC2tpaQSC5XV1exbNmyHNuXLl0q3NzcJCSSz9jYWFy/fj3H9qtXrwoTExMJieQyMTER165dy7E9ODhYmJqaSkgkV9u2bcWWLVtkx5DqxYsXokWLFqJKlSri6dOnsuNIx/54veLFi4uQkJAc20NCQkTRokUlJJKL/aHNzMxM3Lp1K8f2W7duCTMzMyGEEKGhoap8rdGV3Ne0J/p/Tk5OOHHiBBwdHeHk5KS6W/XyY/369Zg4cSJevHiByZMnY8CAAcpVbTWoXLlyjm2HDh2Cr68vbt68iW+++QZff/21hGQFQ7ly5TBr1iz88MMP2L17N1atWiU7ks5MmzYNq1evxrp169ClSxf06NEDFSpUkB2rQOjUqRO8vb0xe/Zs1KlTB0DWLdJjx45Fly5dJKfTva+//hojRozApUuXtPrD398fCxYskJxODgsLC0RGRuZ43Y2KilLViMtstWvXxqRJk7B27VoYGxsDAF68eIEpU6agdu3aktPp3sqVK9GrVy8EBwejQoUKMDAw0Nrfpk0bScl0p0mTJoiNjcWxY8deu9qcmrA/Xi89PR0hISEoV66c1vaQkJAciwSoAftDW9GiRbF79+4cd8Ps3r0bRYsWBZB1F4QaX3t1RT2fnOkfCQkJUeaS+vjjj1G2bFl0794dAN44r9KHLiAgAL6+voiIiMCYMWMwevRomJmZyY4lVWBgIHx8fPDnn3+iX79+2LdvH6ytrWXHKhD09fXRrl07tGvXTnYUnRk3bhzGjRuHY8eOYdWqVahZsybc3NwghMDTp09lx5Nq9uzZ0Gg06Nmzp3Jrq4GBAQYPHoyZM2dKTqd7gwcPhq2tLebMmYPNmzcDyJpnatOmTWjbtq3kdHKwcKltwYIFaNasGUqVKqVcDAkKCoKxsTF+//13yel07/Tp0zh58iT279+fY59aJjo/deoUFi1ahBIlSsiOUiCwP16vT58+8Pb2RlhYmDJn0NmzZzFz5kxVTl7N/tA2YcIEDB48GEePHtWaw3Hfvn1YtmwZAODgwYNo0KCBzJgfNtlDtei/IyEhQaxYsULUrl1baDQa0bBhQ7FixQoRExMjO5pOnT17VjRs2FAYGxuLkSNHikePHsmOJF1oaKjo2LGj0NfXF126dBFhYWGyI0lz5MgRMXv2bHHixAkhhBDLli0TDg4Oonjx4qJfv34iKSlJckJ54uPjxbJly0SNGjWEvr6+qF27tpgzZ47sWFI9f/5cXL58WVy+fFk8f/5cdhwqQFJSUsSIESOEoaGh0NPTE3p6esLIyEiMHDlSJCcny44nxfPnz8WKFSvE6NGjxejRo8Uvv/yi2nOqk5OTGDp0qIiOjpYdRZqFCxcKY2NjsWfPHtlRCgT2x+tlZGSIH3/8Udjb2wuNRiM0Go2wt7cXP/74Y44pBtSA/ZHTiRMnROfOnUXVqlVF1apVRefOncXJkydlx1INTnRO/8j169fh5+eHdevWITY2FmlpabIj6Yyenh5MTEwwYMAAuLi4vLbdiBEjdJhKniFDhsDPzw+NGjXCzJkzUaVKFdmRpPnll18wePBguLi4ICoqCpMmTcL06dPRo0cP6Onp4X//+59qR8K86sqVK/Dz88P69etVN0Ex0dtISkpCWFgYAMDV1RWmpqaSE1FBYG5ujkuXLsHV1VV2FKnWr1+PIUOGYPv27fj0009lx5GO/fFm8fHxALJukSb2BxUMLErRv5Keno5du3bBy8tLdhSdcXZ2fuOtixqNBuHh4TpKJJeenh6MjY3fON9YYGCgjhLJU6FCBQwcOBDDhw9HQEAAWrdurcz7AQC//fYbxo0bh9DQUMlJC460tLQcc6F8qN7mPLlt27b3mKRgsLKyyvdt4LGxse85DRVEu3btyndbNcyh9LJevXqhfv366Nevn+wo0u3btw99+vTBw4cPZUcpENgfRP9ccnIyUlNTtbaxYPf+cU4pytPmzZvRrl07GBoaAgDu3r0Le3t76OnpAQBSU1NV9wH79u3bsiMUKJMmTZIdocAIDw9XPhg1b94cGo1GuTcdAGrWrImoqChZ8XSuZcuW2LhxIywtLQEAM2fOxKBBg5QJWJ88eYL69evj2rVrElPqTnY/UJb58+fLjlDgsHCpLb9z8KllDqWXlS1bFuPGjcOJEydQsWLFHMV9tYzWBrJea7Zv3y47RoHB/sjJxcUlz4sgarmQnI39oS0pKQnffPMNNm/ejCdPnuTYr7bXFxk4UorypK+vjwcPHiiTVVtYWODSpUsoXbo0AODhw4ewt7fnk/UlcXFx+N///odhw4bJjkI6pqenh+joaOX5Ym5ujqCgINU+X3j++PdOnjyJ6tWrw8jISHaUAuHVwuaH5m0mmF29evV7TEIFXV7TB6hptDZRfry6imtaWhouXryIgIAAjB07Fr6+vpKSycH+0DZ06FAcPXoU06ZNQ48ePbBkyRLcu3cPy5cvx8yZM9GtWzfZET94HClFeXq1Zska5usdPnwYfn5+2L59O0xNTVmUQtZ96uvXr4efnx/Onz8vO857p9FokJCQAGNjYwghoNFokJiYqNyvn/1fteD5499r0aKFViFP7WbMmIGOHTt+sEWpf1JoYuFSW8WKFbFv3z44ODjIjvJeRUREyI5QIKWmpiIiIgKurq4oVIgfc9gfWb766qtcty9ZskQV709fxf7Qtnv3bqxduxYNGzZEnz59UL9+fbi5ucHJyQnr169nUUoH9GQHIPovi4qKwtSpU+Hi4oKmTZtCo9Fg+/btiI6Olh1NqqNHj6JHjx6ws7PDtGnTULNmTdmRdEIIgbJly8LKygpFixZFYmIiqlatCisrK1hZWaFcuXKyI9J/DAt52tgfObVo0QL37t2THaPAuH37tqoWXwGynhdqf24kJSXB29sbpqamKF++PCIjIwEAw4cPV+XiIuyP/GnRogW2bt0qO0aBodb+iI2NVS7+WVhYKPNY1qtXD8ePH5cZTTVYlCJ6S2lpafjtt9/QrFkzlCtXDpcuXcJPP/0EPT09jB8/Hs2bN1fNxM0vu3fvHqZPnw43Nzd8+eWX2LBhA1atWoV79+5hyZIlsuPpxNGjR3HkyBHl63Xfq4VGo8kxZ0F+J7YmovxRezFCzdauXYuKFSvCxMQEJiYmqFSpEtatWyc7lhTjxo1DUFAQ/vjjDxgbGyvbmzRpgk2bNklMJgf7I3+2bNmCokWLyo5RYKi1P0qXLq2MPnV3d8fmzZsBZI2g+lBHZhc06h3HSfn2+++/KxP0ZmZm4vDhwwgODgaQNX+S2pQsWRLu7u7o3r07fv31V1hZWQEAunTpIjmZHFu3boWfnx+OHz+OFi1aYM6cOWjRogXMzMxQsWJFVRUhGjRoIDtCgSKEQO/evZXbipKTkzFo0CCYmZkBAFJSUmTGIyL6z5o7dy4mTJiAYcOGoW7dugCAEydOYNCgQXj8+DFGjRolOaFu7dixA5s2bUKtWrW03neUL18eYWFhEpPJwf7QVrVqVa1+EEIgOjoajx49ws8//ywxmRzsD219+vRBUFAQGjRoAF9fX7Ru3RqLFy9GWloa5s6dKzueKrAoRW+UvZx9toEDB2p9r6aiAwCkp6crI0D09fVlx5GuU6dO8PHxwaZNm2Bubi47DhUgPXv21Do/dO/ePdc2RET0dhYtWoSlS5dqnUPbtGmD8uXLY/LkyaorSj169EhZVONlz58/V937VID98aq2bdtq/d16enooUaIEGjZsCHd3d4nJ5GB/aHv5fNmkSROEhITgwoULcHNzQ6VKlSQmUw8WpShPmZmZsiMUOPfv31dGB3311Vdo0aIFunfvrsoXeQDw9vbGkiVL8Mcff6BHjx7o1KmTMnqM1M3f3192hP88tZ5XiChvDx48QJ06dXJsr1OnDh48eCAhkVzVq1fH3r17MXz4cAB/nztXrlyJ2rVry4wmBftD2+TJk2VHKFDYH3lzcnKCk5NTju1qWUhDBs4pRfSWjI2N0a1bNxw5cgRXrlyBh4cHRowYgfT0dEyfPh0HDx5U1RL3y5cvx4MHDzBgwABs3LgRdnZ2aNu2LYQQLGqqXEZGBi5fvowXL17k2JeUlITLly/zGHkDzhekrX79+jAxMZEdo0Bh4VKd3NzclHlPXrZp0yaUKVNGQiK5ZsyYgW+//RaDBw9Geno6FixYgKZNm2L16tWYPn267Hg6x/7Qpq+vj5iYmBzbnzx5osq7Htgf/4waF9LQFRalKE8XLlxAo0aNcl3K/tmzZ2jUqBGCgoIkJCsYXF1d8f333+POnTvYu3cvUlJS8Pnnn+c6ZPpDZmJigl69euHYsWO4cuUKypcvDxsbG9StWxddu3bFtm3bZEckCdatW4e+ffvC0NAwxz5DQ0P07dsXGzZskJBMvhcvXiApKUn5/s6dO5g/fz4OHDig1S4hIUFZEeZDFhgYiCtXrijf79y5E+3atcO3336L1NRUZfu+fftgZ2cnI2KBpebCZW7zWi5fvhw2Nja6D6NjU6ZMwcSJE9G8eXNMmzYN06ZNQ/PmzTFlyhRMnTpVdjydq1evHi5duoT09HRUrFgRBw4cgLW1NU6fPo1q1arJjqdz7A9trztPpqSk5Poe5UPH/qCCRiPU/G6G3qhr167w8PDAhAkTct0/Y8YMXLt2Df/73/90nKzgevToEdatW4fRo0fLjiJVZmYm9u7dCz8/P+zfv5+TWv+/LVu2oEOHDrJj6ET9+vUxdOhQdO7cOdf9mzdvxuLFi1W53G7Tpk3h5eWFQYMGIS4uDu7u7jAwMMDjx48xd+5cDB48WHZEnfr444/h6+uL9u3bIzw8HOXLl8cXX3yBv/76C61atcL8+fNlRyTJfvzxRzg7O6NTp04AgI4dO2Lr1q2wtbXFvn37ULlyZckJde/ChQuYN28erl+/DgDw8PDA119/japVq0pORlQwLFy4EEDWnEHTpk1D4cKFlX0ZGRk4fvw4bt++jYsXL8qKqFPsj3/H3NwcQUFBqrhYqGssSlGeXF1dsX379tdO8nblyhW0bdsW4eHhOk5WcIWHh2PQoEE5RjyoVXp6Ou7fvw9HR0fZUXQiPT0dISEhMDQ0RNmyZZXtO3fuxMSJExESEqKaAp21tTXOnTsHZ2fnXPdHRESgRo0aePTokW6DFQDFixfHsWPHUL58eaxcuRKLFi3CxYsXsXXrVkycOFH5kKkWlpaWCAwMhKurK3788UccOXIEv//+O06ePInOnTsjKipKdkSde/jwIcaMGYPDhw8jJiYmx5VtNd0mDgAuLi5Yv3496tSpg4MHD6Jjx47YtGkTNm/ejMjISL7mEgAgJiYGMTExOW4NV+tkxWrvDxcXFwBZo5FLlSqldWuaoaEhnJ2dMXXqVNSsWVNWRJ1if/w7LEq9P5zonPJ07969PFdUK1y4sCon1MxLQkICDh8+LDtGgXH16lV89NFHqvgAFRwcjM8//1z5AN22bVssXboUHTt2RHBwMPr374+9e/dKTqk7z58/z/XW32wJCQlat7CpSVJSknJuPXDgALy8vKCnp4datWrhzp07ktPp3stz0B06dAiff/45AMDBwQGPHz+WGU2a3r17IzIyEhMmTICdnZ3q546Kjo5WJpfds2cPOnbsiKZNm8LZ2VmVH6D27dsHfX19NGvWTGv777//jszMTLRo0UJSMjkuXLiAXr164fr16zkKuBqNRhXvQV7G/sgSEREBAGjUqBG2bdum+oV42B9UULEoRXkqUaIEbty4oVTWXxUSEoLixYvrOBX916hlQKaPjw/c3NywePFibNy4ERs3bsT169fh7e2NgIAA1U3QXKZMGZw6deq1V2RPnDihygl5gaxJinfs2IEvvvgCv//+u7IccUxMDCwsLCSn073q1avj+++/R5MmTXDs2DEsXboUQNYbaDXMD5SbEydO4M8//0SVKlVkRykQrKysEBUVBQcHBwQEBOD7778HkPX6opYP2C/z9fXFzJkzc2wXQsDX11d1Ram+ffuibNmy8PPzg42NjeqLuOwPbUePHpUdoUBhf1BBw6IU5alJkyaYPn06mjdvnmOfEALTp09HkyZNJCSj/xK1vBn666+/cODAAVSpUgX169fHxo0b8e2336JHjx6yo0nRtWtXfPfdd6hTp06OwlRQUBAmTpyIb775RlI6uSZOnIiuXbti1KhRaNy4sbJE94EDB1Q5H8z8+fPRrVs37NixA+PHj4ebmxuArDnYclv2Xg0cHBxUU9DPDy8vL3Tt2hVlypTBkydPlKLLxYsXleNFTW7dugVPT88c293d3REaGiohkVzh4eHYunWrKo+F3LA/gNGjR2PatGkwMzN74zyvc+fO1VEqedgf/55aFtKQgUUpytN3332HatWqoWbNmvj6669Rrlw5AFkjpObMmYObN2/C399fbkiiAuLx48ewt7cHkDVHjpmZGWrVqiU5lTyjRo3C/v37Ua1aNTRp0gTu7u4Ass4fhw4dQt26dZURQmrToUMH1KtXDw8ePNCaoLlx48b44osvJCaTo1KlSlqr72X76aefVLs89fz58+Hr64vly5e/dl42NZk3bx6cnZ0RFRWFWbNmKRP0PnjwAEOGDJGcTvcsLS0RHh6e49gIDQ2FmZmZnFASNW7cGEFBQaouwryM/ZFVsE5LS1P+/TpquXD6cn8EBgaq5u/Or8OHDytzOL46B9uqVasAZF1spfeDE53TG50/fx69e/fGtWvXlBOYEAKenp5YvXo1Pv74Y8kJdatq1ap5nsiTkpJw69Yt1dxOcPny5Tz3h4SEoEuXLqroD319fdy8eRMlSpSAEAIODg44ceJEjg8Naro9Ky0tDfPmzcOGDRtw69YtCCFQtmxZdO3aFSNHjuTSw5RDYmJijjeEanrOZLOyskJSUhLS09NhamoKAwMDrf2xsbGSklFBMHDgQJw+fRrbt2+Hq6srgKyCVPv27fHxxx9j5cqVkhPq1uPHj9GrVy/UqFEDFSpUyPF8adOmjaRkcrA/iPJvypQpmDp1KqpXr57rHI7bt2+XlEw9WJSifLt48SJCQ0OVD5VqnediypQp+Wo3adKk95ykYNDT04NGo8n1NpPs7WqZVDO7L7Jl/+2vfq+GvqC8JScnY9GiRTh69GiuV+UCAwMlJZMjIiICw4YNwx9//IHk5GRlu5qfM2vWrMlzf69evXSURJ5du3blu63aPmQ/e/YMzZs3x/nz51GqVCkAwN27d1G/fn1s27YNRYoUkRtQx3bv3o0ePXrkuriGGs8h7A/KS9++fbFgwYIci1k9f/4cw4cPV0YGqYWdnR1mzZql2uk2CgIWpeitZK+CxMnNKVt+VwpzcnJ6z0nkO3bsWL7aNWjQ4D0nKVhevHiBgwcP4ubNmwCAcuXKoUmTJqqb+P1l3bp1w4EDB9ChQ4dcJ6FVS1E7W926dSGEwFdffZVrf6jtOUNZ9PT0tL5/9QLIy8eJGj9kCyFw8OBBBAUFwcTEBJUqVcInn3wiO5YUzs7O+PzzzzFhwgTO+QL2x6u++OKLXO9y0Gg0MDY2hpubG7p27apMU/Kh09fXx4MHD2Btba21/fHjx7C1tUV6erqkZHIUK1YM586dU0adku6xKEVvFBcXh/Hjx2PTpk14+vQpgKzbCjp37ozvv/9edVfjiP6N2NhYFC1aVHYMndm1axf69eunFLSzFS9eHH5+fmjdurWkZHJZWlpi3759qFu3ruwoBULhwoVx4cIF1XwgyK+MjAzs2LED169fBwCUL18ebdq0UeU8W4cOHYKPjw9mzJihLAxw+vRpfPfdd5gxYwY+++wzyQlJJnNzc1y6dIkfKv8f+0Nb7969sWPHDhQpUgTVqlUDkDUiOS4uDk2bNkVQUBBu376Nw4cPf9Cvy/Hx8RBCwMrKCrdu3UKJEiWUfRkZGdi9ezd8fX1x//59iSl1z8fHB4ULF8aECRNkR1EtTnROeYqNjUXt2rVx7949dOvWDR4eHgCAa9euwd/fH4cPH8apU6dgZWUlOanuNGrU6I2TA2o0Ghw+fFhHieR6/Pgxnj9/rjUS6urVq5g9ezaeP3+Odu3acWJAZK2qtnLlSuzevRsvXryQHUcnTp06hQ4dOqBNmzb4+uuvtc4fc+bMQYcOHXDs2DFVTgZfsmTJHMPm1ezjjz9GVFQUi1IvCQ0NRcuWLXHv3j2lX3744Qc4ODhg7969qvuwOXLkSCxbtgz16tVTtjVr1gympqYYMGCAUrhTk/xMzKsWXl5eOHr0qOqeF6/D/tBma2uLrl27YvHixcoIzMzMTHz11VcwNzfHr7/+ikGDBsHHxwcnTpyQnPb9KVKkCDQaDTQaDcqWLZtjv0ajyfc0JR+S5ORkrFixAocOHUKlSpVyzMHG1QjfP46UojyNHDkShw8fxqFDh3IM/42OjkbTpk3RuHFjzJs3T1JC3ctrtbCEhARs2LABKSkpqrmVoEuXLrC3t8ecOXMAADExMXB3d4e9vT1cXV2xf/9++Pn5qfI+7Tt37mDVqlVYs2YNnj59ihYtWqB9+/b48ssvZUfTiZYtW8LBwQHLly/Pdf/AgQMRFRWFffv26TiZfPv378fChQuxbNkyVdza+iZhYWEYNGgQunfvnuukvJUqVZKUTJ6WLVtCCIH169croyufPHmC7t27Q09PD3v37pWcULdMTEzw119/oUKFClrbL1++jJo1a6qm2J+NE/Nqmz59OubPn49WrVqhYsWKOc4hI0aMkJRMDvaHthIlSuDkyZM5CjE3b95EnTp18PjxY1y5cgX169dHXFycnJA6cOzYMQgh8Omnn2Lr1q1aI/cNDQ3h5OSkrCKtJo0aNXrtPo1GgyNHjugwjTqxKEV5cnZ2xvLly9GsWbNc9wcEBGDQoEG4ffu2boMVMOnp6ViyZAmmT58OS0tLTJs2DZ07d5YdSydcXFzg7++vzPkye/ZsLFu2DCEhIShUqBBmz56NLVu24MyZM5KT6kZqaiq2bduGlStX4uTJk2jSpAn279+PixcvomLFirLj6VTRokVx7Nix1/7dly9fRoMGDZTbgtXk0aNH6NixI44fP86V1QCcOXMGXbt21XotUdtCCa8yMzPDmTNncjx/goKCULduXSQmJkpKJscnn3wCY2NjrFu3TrlI9vDhQ/Ts2RPJycn5ntPvQ8GJebW5uLi8dp9Go0F4eLgO08jH/tBmZWWFNWvW5FgQYdeuXejVqxeePn2KW7duoUaNGqp4T3Lnzh04ODjkmLePSBbevkd5evDgAcqXL//a/RUqVEB0dLQOExU869evx8SJE/HixQtMnjwZAwYMQKFC6nlqRUdHw9nZWfn+yJEj8PLyUvqgTZs2+OGHHySl063hw4dj48aNKFOmDLp3745NmzahWLFiMDAwUOUcMC9evICFhcVr91taWmqttKYmXbp0wb179zBjxoxcJ/ZWm759+6Jq1arYuHEj++P/GRkZISEhIcf2xMREGBoaSkgk16pVq/DFF1/A0dERDg4OAICoqCiUKVMGO3bskBtOgtTUVNSpU0d2jAIjIiJCdoQChf2hrUePHvD29sa3336Ljz/+GADw119/YcaMGejZsyeArFFEeX3m+ZBkj9BOSkpCZGQkUlNTtfarcXQyyaWeT870jxQvXhy3b99Wlht+VUREhKombX5ZQEAAfH19ERERgTFjxmD06NEwMzOTHUvnLCwsEBcXp7zAnTt3Dt7e3sp+jUaDlJQUWfF0aunSpfDx8YGvry/nCwJQpkwZHDlyBH369Ml1/+HDh1GmTBkdpyoYTp06hdOnT6Ny5cqyoxQId+7cwa5du+Dm5iY7SoHx+eefY8CAAfDz80ONGjUAAGfPnsWgQYNyXO1XAzc3N1y+fBkHDx5ESEgIAMDDwwNNmjRRZRGzX79+2LBhAyfmzUX2TSBqPC5yw/4A5s2bBxsbG8yaNQsPHz4EANjY2GDUqFHw8fEBADRt2hTNmzeXGVNnHj16hD59+mD//v257lfj6OTz589j8+bNuRbptm3bJimVenDMHuWpWbNmGD9+fI4nJwCkpKRgwoQJqjmBZzt37hwaNWqEL774Ao0aNUJYWBgmTJigyoIUANSqVQsLFy5EZmYmtmzZgoSEBHz66afK/ps3bypXtT9069atw7lz52BnZ4dOnTphz549qnxhz9anTx+MGTMm1zmj9u7di2+++Qa9e/fWfbACwN3dXXVz4OTl008/RVBQkOwYBcrChQvh6uqK2rVrw9jYGMbGxqhbty7c3NywYMEC2fGk0Gg0aNq0KUaMGIERI0bgs88+U+0H7eTkZMydOxcNGjTA8OHDMXr0aK0vNVq7di0qVqwIExMTmJiYoFKlSli3bp3sWNKwP/6mr6+P8ePH48GDB4iLi0NcXBwePHiAb7/9VhnJ7ujo+NqL8B+akSNHIi4uDmfPnoWJiQkCAgKwZs0alClTBrt27ZIdT+d+/fVX1KlTB9evX8f27duRlpaGq1ev4siRI7C0tJQdTxU4pxTl6e7du6hevTqMjIwwdOhQuLu7QwiB69ev4+eff0ZKSgrOnz+vmqIDAOjp6cHExAQDBgzI8559tUwiefnyZTRu3Bjx8fFIT0/Ht99+i2nTpin7e/ToATMzMyxbtkxiSt2KiIiAv78//P39kZSUhNjYWGzatAkdOnSQHU2nMjMz0alTJ2zduhXlypWDh4eHcv64desW2rVrh99++02VcxocOHAAU6ZMwfTp03OdhDav2x4/RCtWrMD333+Pvn375tofahwZlO3WrVtaI4PUNJps4cKF+W6rltfcbJyYV9vcuXMxYcIEDBs2DHXr1gUAnDhxAkuWLMH333+f5yI1HyL2B+XFzs4OO3fuRI0aNWBhYYHz58+jbNmy2LVrF2bNmvVBr0CYm0qVKmHgwIEYOnQozM3NERQUBBcXFwwcOBB2dnaqXJFQ11iUojeKiIjAkCFDcODAAa0hwJ999hkWL16sqjfIQNbk72+6Mqu2SSQfP36MkydPwtbWFjVr1tTat3fvXnh6euZZwPtQCSFw4MAB+Pn5YdeuXShevDi8vLze6oPWh2DTpk3YuHEjbt68CQAoW7YsOnfurJrFAHKTXYh79Vyi1om98ypMqrE/KEt+XzfU9ppLObm4uGDKlCnK/EDZ1qxZg8mTJ6tujiX2h7aHDx9izJgxOHz4MGJiYvDqx1+1vcZYWFjg8uXLcHZ2hpOTEzZs2IC6desiIiIC5cuXR1JSkuyIOmVmZoarV6/C2dkZxYoVwx9//IGKFSvi+vXr+PTTT/HgwQPZET94nFOK3sjFxQX79+9XVqYAsuZ2UOtcUmpfaTA3xYsXR9u2bXPd16pVKx2nKTg0Gg2aNWuGZs2aITY2FmvXrsXq1atlx9K5Tp06oVOnTrJjFChHjx6VHaFAyczMlB2hQBg9ejSmTZsGMzOzN96CNXfuXB2lkkdtH5zpn3vw4EGuE7/XqVNHlR8o2R/aevfujcjISEyYMAF2dnaqve03W7ly5XDjxg04OzujcuXKWL58OZydnbFs2TLY2dnJjqdzVlZWysIiJUuWRHBwMCpWrIi4uDjVFehkYVGK8s3KykqZbJUoW35H/ajt1opXFS1aFCNHjsTIkSNlR6ECoEGDBrIjUAF08eJFpKWlKf+m3Kl14mYvLy/4+/vDwsICXl5eebZV28S8bm5u2Lx5M7799lut7Zs2bVLlghrsD20nTpzAn3/+iSpVqsiOUiB89dVXSnFy0qRJaN68Of73v//B0NAQa9askZxO9z755BMcPHgQFStWxJdffomvvvoKR44cwcGDB9G4cWPZ8VSBRSmit8QijLZ58+a9sY1Go1FFf3h6euLEiRPKKMIhQ4Zg6tSpKF68OAAgJiYGzs7OvOpCAIC4uDj4+fnh+vXrAIDy5cujb9++qp1U89ixY5g9e7bSH56enhg7dizq168vOZnuvDyCjqPpclq7di1++uknZdR22bJlMXbsWPTo0UNyMt2wtLRUCnFqPU+8zpQpU9CpUyccP35cmUPp5MmTOHz4MDZv3iw5ne6xP7Q5ODjkuGVPzbp37678u1q1arhz5w5CQkLg6OiovGdVk8WLFyM5ORkAMH78eBgYGODUqVNo3749vvvuO8np1IFzShG9pfzMccH5LdRJT08P0dHRsLa2BpB1z/6lS5dQunRpAFlzGtjZ2fFWJcL58+fRrFkzmJiYKCNQ//rrL7x48QIHDhzARx99JDmhbv3vf/9Dnz594OXlpfUBavv27fD390fXrl0lJ9S9vn37YsGCBTA3N9fa/vz5cwwfPhyrVq2SlEwOTtz8z5w8eVJZsOZDd+HCBcybN08pbHt4eODrr79G1apVJSeTg/3xtwMHDmDOnDnKbWpq9Darcqrh9nAqWFiUIiKdqlixIvbt2/dBrtj4alEqewWPl4tS9vb2qptQk3KqX78+3Nzc8Msvv6BQoaxBy+np6ejXrx/Cw8Nx/PhxyQl1y8PDAwMGDMhRWJg7dy5++eUX5UOVmujr6+PBgwfK+STb48ePYWtri/T0dEnJ5ODEzf/MqxdHiNTIysoKSUlJSE9Ph6mpaY4VXmNjYyUl0528Vux8mVpW74yPj1dWOo6Pj8+zrdpWRJaBt+8RvWcfchHmn7h9+7YyZwrRli1b0KFDB9kxdO78+fNaBSkAKFSoEL755htUr15dYjI5wsPD0bp16xzb27Rpk2NOlA9dfHw8hBAQQiAhIQHGxsbKvoyMDOzbty9HoUoNOHHzP6OWa8/79u2Dvr4+mjVrprX9999/R2ZmJlq0aCEpmRzsD23z58+XHUE63hKuzcrKSrnwU6RIkVznKFTrisgysChFedq1a1e+2rVp0+Y9J/nvYhFGPTQaTY4XNbVNxPuq9PR0hISEwNDQEGXLllW279y5ExMnTkRISIgqi1IWFhaIjIyEu7u71vaoqKgct2upgYODAw4fPgw3Nzet7YcOHVJdQT/7zbFGo9F6zmTTaDSYMmWKhGRyceJmyouvry9mzpyZY7sQAr6+vqorwrA/tPXq1Ut2BCpgjhw5oswBy4KdfCxKUZ7atWun9b1Go8lx1Y0VZKIsQgg0btxYGf3y4sULtG7dGoaGhgCgutttgoOD8fnnnyMqKgoA0LZtWyxduhQdO3ZEcHAw+vfvj71790pOKUenTp3g7e2N2bNnK6M/Tp48ibFjx6JLly6S0+ne119/jREjRuDSpUta/eHv748FCxZITqdbR48ehRACn376KbZu3aq8aQYAQ0NDODk5wd7eXmJCOThxM+Xl1q1b8PT0zLHd3d0doaGhEhLJxf7IKSMjAzt27NBaXKRNmzbQ19eXnIxkeHkVZK6ILB+LUpSnVydkfnWOHCL626RJk7S+b9u2bY427du311Uc6Xx8fODm5obFixdj48aN2LhxI65fvw5vb28EBATAxMREdkRpZs+eDY1Gg549eyrFSgMDAwwePDjXq9sfusGDB8PW1hZz5sxRCgweHh7YtGlTrs+jD1n2m+OIiAg4ODhAT09PcqKCoX379jh79izmzZuHHTt2AMg6Rs6dO6fKiZtJm6WlJcLDw3NMYh0aGgozMzM5oSRif2gLDQ1Fy5Ytce/ePZQrVw4A8MMPP8DBwQF79+6Fq6ur5ISka5cvX85320qVKr3HJARwonN6SyxKvT32mTb2h3pYW1vjwIEDqFKlCp49ewYrKyusWbNGNcu350dSUhLCwsIAAK6urjA1NZWciAqapKQkREZGIjU1VWs73yRTfqhlovOBAwfi9OnT2L59u1JgCA0NRfv27fHxxx9j5cqVkhPqFvtDW8uWLSGEwPr165XRp0+ePEH37t2hp6en2lHbaqanp6fcAfSmqTZ4R9D7x5FSRET0Xjx+/Fi5zcjS0hJmZmaoVauW5FQFi6mpKaysrJR/q92FCxe0bq1Q8wiYR48eoU+fPti/f3+u+9X4JjkzMxOhoaGIiYnJMZL7k08+kZSqYFPLtedZs2ahefPmcHd3R6lSpQAAd+/eRf369TF79mzJ6XSP/aHt2LFjOHPmjNbt0MWKFcPMmTOV24FJXV5esfXixYsYM2YMxo4di9q1awMATp8+jTlz5mDWrFmyIqoKi1JE9E6Eh4fn60rs8uXLYWNjo4NEuteoUaM3Xm3RaDQ4fPiwjhLJpdFolNXDsq9EvXjxIsfSu2pcajczMxPff/895syZg8TERABZowi//vprjB8/XnW3bMXExKBz5874448/UKRIEQBAXFwcGjVqhF9//RUlSpSQG1CCkSNHIi4uDmfPnkXDhg2xfft2PHz4UDlu1ObMmTPo2rUr7ty5w7kt30JCQoLsCDphaWmJU6dO4eDBgwgKCoKJiQkqVaqk2mIl+0ObkZFRrs+FxMREZd5PUhcnJyfl319++SUWLlyIli1bKtsqVaoEBwcHTJgwIcccy/Tu8fY9eisWFhYICgqCi4uL7CjS5bcIs2HDBrRt2/aDv4dfT08PDRo0gLe3Nzp06KC1jLlajBo16rX7EhISsGHDBqSkpKjmw1P20Ohsrw6RVvNSu+PGjYOfnx+mTJmiXKU9ceIEJk+ejP79+2P69OmSE+pWp06dEB4ejrVr18LDwwMAcO3aNfTq1Qtubm7YuHGj5IS6Z2dnh507d6JGjRqwsLDA+fPnUbZsWezatQuzZs3CiRMnZEfUqSpVqqBs2bKYMmUK7OzsclwAsLS0lJRMjocPH2LMmDE4fPgwYmJichTq1HheJXqdnj17IjAwEH5+fqhRowYA4OzZs+jfvz+qVasGf39/uQFJKhMTEwQGBirvP7Jdv34dH330EV68eCEpmXqwKEV5srKy0nrjFxcXBwsLixxX8WNjY3UdTToWYbRdunQJq1evxsaNG5GamqqsLpb94q9W6enpWLJkCaZPnw5LS0tMmzYNnTt3lh1LJ44dO5avdmpc9cTe3h7Lli1DmzZttLbv3LkTQ4YMwb179yQlk8PS0hKHDh3Cxx9/rLX93LlzaNq0KeLi4uQEk8jCwgKXL1+Gs7MznJycsGHDBtStWxcREREoX748kpKSZEfUKTMzMwQFBcHNzU12lAKhRYsWiIyMxLBhw3It0qltgQAAOHz4sFKke/X2zlWrVklKJQ/7429xcXHo1asXdu/eDQMDAwBAWloa2rZti9WrVysjdEmdPvroI1SoUAErV65URs6lpqaiX79+CA4ORmBgoOSEHz7evkd5mj9/vuwIBVZgYCBWr16N0aNHY9iwYaovwlSpUgULFizAnDlzsGvXLvj7+6NevXooW7Ys+vbtix49eqjuFpz169dj4sSJePHiBSZPnowBAwagUCH1nHbzU2xSY0EbyPq73d3dc2x3d3dXZZ9kZmYqHxReZmBgkOPDlFqUK1cON27cgLOzMypXrozly5fD2dkZy5Ytg52dnex4OlezZk2EhoayKPX/Tpw4gT///BNVqlSRHaVAmDJlCqZOnYrq1avnWqRTG/aHtiJFimDnzp0IDQ1V5i308PDg+YQAAMuWLUPr1q1RqlQpZRGRy5cvQ6PRYPfu3ZLTqQNHShH9S+np6UoRJiAgQNVFmJelpKTg559/xrhx45CamgpDQ0N07NgRP/744wf/gSogIAC+vr6IiIjAmDFjMHr06A/+9s23deDAAaxcuRK7d+9W5bDomjVrombNmli4cKHW9uHDh+Ovv/7CmTNnJCWTo23btoiLi8PGjRuVyfHv3buHbt26wcrKCtu3b5ecUPf+97//IT09Hb1798aFCxfQvHlzxMbGwtDQEP7+/ujUqZPsiO/dy0t2h4WF4bvvvsPYsWNRsWLFHEVMta1G6OnpifXr16t6MYCX2dnZYdasWVzd9f+xP4DRo0fnu+3cuXPfYxL6L3j+/DnWr1+PkJAQAFlFy65du/L9u46wKEX0jqi5CPOy8+fPY9WqVfj1119hZmaGXr16wdvbG3fv3sWUKVMQHx+Pc+fOyY75Xpw7dw4+Pj44c+YMBg0ahPHjx6N48eKyYxUYd+7cwapVq7BmzRo8ffoULVq0QPv27fHll1/KjqZzx44dQ6tWreDo6Ki10ktUVBT27duH+vXrS06oW1FRUWjTpg2uXr0KBwcHZVuFChWwa9cuZfUoNUtKSkJISAgcHR1Vc155ecnu3Ly8nLfa5lA6cOAA5syZo4ygU7tixYrh3LlzcHV1lR2lQGB/ZC0+kx8ajQZHjhx5z2mIKC8sStG/EhQUhI8++kh1bwZfpuYizMvmzp2L1atX48aNG2jZsiX69euHli1bas0/dvfuXTg7OyM9PV1i0vdHT08PJiYmGDBgQJ6LAYwYMUKHqeRKTU3Ftm3bsHLlSpw8eRJNmjTB/v37cfHiRVSsWFF2PKnu37+PJUuWaF2VGzJkiDJSSG2EEDh06JBWfzRp0kRyKpLpzp07+W778kpKamBlZYWkpCSkp6fD1NQ0x8gxtd0G7OPjg8KFC2PChAmyoxQI7A+it7Nu3TosX74c4eHhOH36NJycnDBv3jyULl1alXP06Zp6Jjeh90atdc1XizBr167VKsK4uLjA399fNVcwly5dir59+6J3796vHRlmbW0NPz8/HSfTHUdHR2g0GuzYseO1bTQajWqKUsOHD8fGjRtRpkwZdO/eHZs2bUKxYsVgYGAAfX192fGkSUtLQ/PmzbFs2TLVrbKXm7S0NJiYmODSpUv47LPP8Nlnn8mOJA1vN9GmtkLT2+Ccn9qSk5OxYsUKHDp0CJUqVcpRpFPD8+Vl7A+i/Fu6dCkmTpyIkSNH4vvvv1cGW1hZWWH+/PksSukAR0pRnry8vPLc/+zZM/zxxx+qHClVpkyZNxZhUlNTsXHjRvTq1UvH6XTv9u3bcHR0zLEyoxACUVFRcHR0lJSMZClUqBB8fHzg6+sLc3NzZbuBgQGCgoLg6ekpMZ1cJUqUwKlTp1CmTBnZUQqE0qVLY/v27ahcubLsKFLxdpO8rVu3DsuWLUNERIRyJXv+/PlwcXHhhwaVy+u5o8bnC/uDKP88PT0xY8YMtGvXDubm5ggKCkLp0qURHByMhg0b4vHjx7IjfvBYlKI8GRgY4LPPPoONjU2u+2NjY7Fnzx5VFqVYhNGmr6+PBw8ewNraWmv7kydPYG1trcpj5E0qVqyIffv2KXPofGg2btyIVatW4fTp02jVqhV69OiBFi1awNjYWPVFqVGjRsHIyAgzZ86UHaVA8PPzw7Zt27Bu3ToULVpUdhwqgF6+kj19+nQEBwejdOnS8Pf3x5o1a3D06FHZEaVJTk5Gamqq1jYLCwtJaYiI/ltMTEwQEhICJycnraLUrVu3UKlSJVUuyKNrvH2P8uTh4YH27dvD29s71/2XLl3Cnj17dJyqYHB1dc21CBMbGwsXFxfVFWFeV99OTEyEsbGxjtP8N9y+fRtpaWmyY7w3Xbp0QZcuXRAREQF/f38MHToUSUlJyMzMxLVr11RdlEpPT8eqVatw6NAhVKtWLcfqLmq7tWLx4sUIDQ2Fvb09nJyccvRHYGCgpGRUUCxatAi//PIL2rVrp1XMrV69OsaMGSMxmRzPnz+Hj48PNm/ejCdPnuTYr7b3IERE/5SLiwsuXbqU45bxgIAAeHh4SEqlLixKUZ6qVauGwMDA1xaljIyMVDciKBuLMFmy50DRaDSYOHEiTE1NlX0ZGRk4e/YsqlSpIikdFQQuLi6YMmUKJk+ejAMHDsDPzw/du3fHyJEj4eXlhYULF8qOqHPBwcH46KOPAAA3b97U2qfRaGREkqpdu3ayIxQ4jRo1yvNYUNvtNxEREahatWqO7UZGRnj+/LmERHJ98803OHr0KJYuXYoePXpgyZIluHfvHpYvX66aEZheXl7w9/eHhYXFG6eb2LZtm45SycP+IPpnRo8ejaFDhyI5ORlCCJw7dw4bN27EDz/8gJUrV8qOpwosSlGeli1blufVNg8PD0REROgwkXwswmi7ePEigKwi3ZUrV2BoaKjsMzQ0ROXKlVV5FZty0mg0aNasGZo1a4bY2FisXbsWq1evlh1LivzeanT37l3Y29vnuE34QzNp0iTZEQqcV19H0tLScOnSJQQHB6tinsJX8Uq2tt27d2Pt2rVo2LAh+vTpg/r168PNzQ1OTk5Yv349unXrJjvie2dpaakUbi0tLSWnkY/9QfTP9OvXDyYmJvjuu++QlJSErl27wt7eHgsWLEDnzp1lx1MFzilF9JayJ488duwYateunaMI4+zsjDFjxqhuAuM+ffpgwYIFnMfiLbx83zpRbiwsLHDp0iUeI6SYPHkyEhMTMXv2bNlRdGrlypWYPHky5syZA29vb6xcuRJhYWHKlWy1fXAoXLgwrl27BkdHR5QqVQrbtm1DjRo1EBERgYoVKyIxMVF2xALp5MmTqF69OoyMjGRHKRDYH0TakpKSkJiYmGN6Fnq/OFKK6C1lj3BgEUabWke80Ot5enrixIkTysTVQ4YMwdSpU1G8eHEAQExMDJydnZGUlCQzZoH2IV83srKyyvetirGxse85zX9H9+7dUaNGDdUVpXglW1vp0qUREREBR0dHuLu7Y/PmzahRowZ2796NIkWKyI5XYLVo0YKF/pewP4i0mZqaat0FQ7rBohS9UVRUFKpWrYrz58/D2dlZ2f7w4UNUqFABJ0+eRNmyZeUFlIRFGM5fQHkLCQlBenq68v3//vc/jBkzRilKCSGQnJwsKx5JNn/+fOXfT548wffff49mzZqhdu3aAIDTp0/j999/x4QJEyQlLJhOnz6tqnkLX9atWzd069aNV7KRdWEsKCgIDRo0gK+vL1q3bo3FixcjLS1NdQslvI0PudD/T7A/iLLeg0ycOBFHjx5FTEwMMjMztfbzwtj7x6IUvZGDgwPKly+PdevWaX042LhxIxwcHFRVkGIRRhvnL8hdeHh4vq46Ll++HDY2NjpIVDDk9uZXjZN6U5aX50Vq3749pk6dimHDhinbRowYgcWLF+PQoUMYNWqUjIhSvfoaI4TAgwcPcP78eVUW6l68eAEhhHIV+9GjR5g/fz48PT3RtGlT2fF07uXnRJMmTRASEoILFy7Azc0NlSpVkpiMiOi/pUePHggNDYW3tzdsbGz43lQCFqUoX3r27IlZs2ZpvRFet24devfuLS+UBCzCaHt5tBhHjv3Nzc0NDRo0gLe3Nzp06PDaUQ1du3bVcTKigun333/Hjz/+mGN78+bN4evrKyGRfK++xujp6aFcuXKYOnWqKoswbdu2hZeXFwYNGoS4uDjUqFEDhoaGePz4MebOnYvBgwfLjiiVk5NTjkngiYjozf7880+cOHEClStXlh1FtViUonzp2LEjRowYgbNnz6JmzZq4du0arl69qorVXV7GIgzlR2BgIFavXo3Ro0dj2LBh6NSpE7y9vVGjRg3Z0XRKo9HkuNrEq09vRy39VaxYMezcuRNff/211vadO3eiWLFiklLJxdcYbYGBgZg3bx4AYMuWLbC1tcXFixexdetWTJw4URVFqYULF2LAgAEwNjbGwoUL82w7YsQIHaUiIvpvc3d3x4sXL2THUDWuvkf51qNHD5ibm+Pnn3/GuHHjEBISgu3bt8uORQUE78fOKT09Hbt27YK/vz8CAgJQtmxZ9O3bFz169ECJEiVkx3vv9PT0UKFCBRQqlHX94/Lly3B3d1dWrExPT8fVq1eRkZEhM2aBppYVGv39/dGvXz+0aNECNWvWBACcPXsWAQEB+OWXX1Q3Kvdl58+fx/Xr1wFkLR5QrVo1yYnkMDU1RUhICBwdHdGxY0eUL18ekyZNQlRUFMqVK6eKBRNcXFxw/vx5FCtWDC4uLq9tp9FoEB4ersNk/x1c0VQb+4MI+Ouvv+Dr64uJEyeiQoUKMDAw0NrPRa3ePxalKN8OHjyILl264N69eyhTpgwWLlyIdu3ayY4lDYsw2lq2bJnn/dgvzx+jNikpKUoxNzU1FYaGhujYsSN+/PFH2NnZyY733kyZMiVf7SZNmvSek/x3RUVFwd7eHvr6+rKjvHdnz57FwoULlQKMh4cHRowYoRSp1Obu3bvo0qULTp48qaymFhcXhzp16uDXX39FqVKl5AbUsUqVKqFfv3744osvUKFCBQQEBKB27dq4cOECWrVqhejoaNkR6T9ALYX+/GJ/EAG3bt1C165dERgYqLVdCAGNRsOLpzrAohTlmxACTk5OaN26NX777Tfcv39fGQGhRizCaDM3N+f92K84f/48Vq1ahV9//RVmZmbo1asXvL29cffuXUyZMgXx8fE4d+6c7JikI29aHOFlalgogfLWvHlzxMXFYc2aNShXrhwA4MaNG+jTpw8sLCwQEBAgOaFubdmyBV27dkVGRgYaN26MAwcOAAB++OEHHD9+HPv375eckIiI/otq1KiBQoUK4auvvsr1M12DBg0kJVMP9VYU6K1pNBp0794dP/74I4YNG6bqghTASfFexfux/zZ37lysXr0aN27cQMuWLbF27Vq0bNkSenp6ALJuwfD394ezs7PcoKRTXBwhb2FhYVi9ejXCw8Mxf/58WFtbY//+/XB0dET58uVlx9O5Y8eO4dSpU0pBCgDKlSuHRYsWoX79+hKTydGhQwfUq1cPDx480Hrdbdy4Mb744guJyXRn9OjR+W47d+7c95ik4Hn48CHGjBmDw4cPIyYmJsdqr2ob6cD+IMq/4OBgXLx4Uev1lnRL3VUFemt9+vTB6dOn4e3tLTuKdCzCaPv55595P/b/W7p0Kfr27YvevXu/9vY8a2tr+Pn56TiZbjVq1OiNE3VrNBocPnxYR4nk4sTVr3fs2DG0aNECdevWxfHjx/H999/D2toaQUFB8PPzw5YtW2RH1DkHBwekpaXl2J6RkQF7e3sJieSztbWFra2t1jY1LSBx8eJFre8DAwORnp6ufJC6efMm9PX1VTnvWO/evREZGYkJEybAzs5ONYtEvA77gyj/qlevrsxPSHLw9j2if4iT4mnj/dh/u337NhwdHZWRUdmEEIiKioKjo6OkZLo1atSo1+5LSEjAhg0bkJKSoqpjg3JXu3ZtfPnllxg9erTWHCfnzp2Dl5cX7t69Kzuizu3cuRMzZszAkiVLUL16dQBZtwQPHz4cPj4+qpvT8U1F7iNHjugwjXxz587FH3/8gTVr1sDKygoA8PTpU/Tp0wf169fPsZLlh87c3Bx//vknqlSpIjtKgcD+IMq/3377DZMnT8bYsWNRsWLFHJ/pKlWqJCmZerAoRe9UxYoVsW/fPjg4OMiO8t6xCKON92P/TV9fHw8ePIC1tbXW9idPnsDa2lp1x8bL0tPTsWTJEkyfPh2WlpaYNm0aOnfuLDuWFFu2bMHmzZsRGRmJ1NRUrX2vnlc+dIULF8aVK1fg4uKiVZS6ffs23N3dkZycLDuizllZWSEpKQnp6enK7fLZ/zYzM9Nqq4aFNV4tcqelpeHSpUsIDg5Gr169sGDBAknJ5ChZsiQOHDiQ49bW4OBgNG3aFPfv35eUTA5PT0+sX78eVatWlR2lQGB/EOXfqxeRgayR/Gr9TCcDb9+jd+r27du53m7wIerWrRsMDAywYcOGXIswasP7sf/2ulp/YmIijI2NdZym4Fi/fj0mTpyIFy9eYPLkyRgwYIBq56ZbuHAhxo8fj969e2Pnzp3o06cPwsLC8Ndff2Ho0KGy4+lckSJF8ODBgxzL3F+8eBElS5aUlEqu+fPny45QoMybNy/X7ZMnT0ZiYqKO08gXHx+PR48e5dj+6NEjJCQkSEgk1/z58+Hr64vly5dzvkawP4jeRkREhOwIqseRUvROqWlpWVNTUxZhXvLJJ59g4sSJaNKkiewo0mRPQrtgwQL0798fpqamyr6MjAycPXsW+vr6OHnypKyIUgQEBMDX1xcREREYM2YMRo8enWOkh9q4u7tj0qRJ6NKli9Z5c+LEiYiNjcXixYtlR9SpMWPG4OzZs/jtt99QtmxZBAYG4uHDh+jZsyd69uyJSZMmyY5IBVRoaChq1KihitFiL+vZsyf+/PNPzJkzR5lX6+zZsxg7dizq16+PNWvWSE6oWy+PLDQ1Nc1x+43ajg/2B9G716pVK6xcufK188XSP6fOS9RE7wAnxdM2fPhwfPXVV6q+Hzt7ElohBK5cuQJDQ0Nln6GhISpXrowxY8bIiqdz586dg4+PD86cOYNBgwbh0KFDKF68uOxYBUJkZCTq1KkDADAxMVFGNvTo0QO1atVSXVFqxowZGDp0KBwcHJCRkQFPT09kZGSga9eu+O6772THkyYjIwM7duzA9evXAQDly5dHmzZtoK+vLzlZwXH69GlVjkBdtmwZxowZg65duyoj1AsVKgRvb2/89NNPktPpHkcWamN/EL17x48f5yJX7wlHStE7paaRUpwUTxvvx/5bnz59sGDBAtVNdv8qPT09mJiYYMCAATluy3rZiBEjdJiqYChdujS2bt2KqlWronr16ujfvz8GDhyIAwcOoHPnzqq9ih0ZGYng4GAkJiaiatWqKFOmjOxI0oSGhqJly5a4d++ecvHjxo0bcHBwwN69e+Hq6io5oW55eXlpfS+EwIMHD3D+/HlMmDBBtaPpnj9/jrCwMACAq6ur6kehEhG9L2r6nKtrLErRO6WmJyuLMNru3LmT534nJycdJaGCwtnZ+Y1zrWk0GoSHh+soUcHRr18/ODg4YNKkSViyZAnGjh2LunXr4vz58/Dy8oKfn5/siNJkvy1R+zx9LVu2hBAC69evR9GiRQFkLZbQvXt36OnpYe/evZIT6lafPn20vtfT00OJEiXw6aefomnTppJSyRcaGoqwsDB88sknMDExUd6DqFlycnKOxSPUfJGI/UH0bqjpc66usShF75SanqwswtDLvLy84O/vDwsLixxX9F+1bds2HaWigiozMxOZmZnKRO+//vorTp06hTJlymDgwIFat36qhZ+fH+bNm4dbt24BAMqUKYORI0eiX79+kpPJYWZmhjNnzqBixYpa24OCglC3bl1VTu5Nf3vy5Ak6duyIo0ePQqPR4NatWyhdujT69u0LKysrzJkzR3ZEnXr+/Dl8fHywefNmPHnyJMd+tV0oZH8QvXtq+pyra5xTivIlPDw8X0/A5cuXw8bGRgeJ5GPRCdi1axdatGgBAwMD7Nq1K8+2bdq00VEqOSwtLZWr05aWlpLT/DdVrFgR+/btg4ODg+wo793du3e1/s7OnTujc+fOEEIgKioKjo6OEtPp3sSJEzF37lwMHz4ctWvXBpA1V9CoUaMQGRmJqVOnSk6oe0ZGRrmuopaYmKjKomW2CxcuaM2xpdYl70eNGgUDAwNERkbCw8ND2d6pUyeMHj1adUWpb775BkePHsXSpUvRo0cPLFmyBPfu3cPy5csxc+ZM2fF0jv1BRP8lHClF+aKnp4cGDRrA29sbHTp0UOWkogCLMK/S09NDdHQ0rK2tc72dMZsab2ekt6emK1D6+vp48OABrK2ttbY/efIE1tbWqnu+lChRAgsXLkSXLl20tm/cuBHDhw/H48ePJSWTp2fPnggMDISfn5/W6mr9+/dHtWrV4O/vLzegjsXExKBz5874448/UKRIEQBAXFwcGjVqhF9//RUlSpSQG1DHbG1t8fvvv6Ny5cpa587w8HBUqlRJdSPpHB0dsXbtWjRs2BAWFhYIDAyEm5sb1q1bh40bN2Lfvn2yI+oU+4Po3VPT+1Rd40gpypfAwECsXr0ao0ePxrBhw9CpUyd4e3srb5TVol27dkoRpl27dq9tp5YiTGZmZq7/JqK8vW7el8TERFUW/dPS0lC9evUc26tVq4b09HQJieRbuHAhevXqhdq1aysLaaSlpaFt27ZYsGCB5HS6N3z4cCQkJODq1avKyKBr166hV69eGDFiBDZu3Cg5oW49f/4cpqamObbHxsbCyMhIQiK5YmNjlQ+KFhYWymIR9erVw+DBg2VGk4L9QfTuffvtt8ocj/RusShF+VKlShUsWLAAc+bMwa5du+Dv74969eqhbNmy6Nu3L3r06KGKq5QswvwzSUlJub55/lA9efIEEydOxNGjRxETE5PjWFHrymoEjB49GkBW4XrChAlaz4uMjAycPXsWVapUkZROnh49emDp0qWYO3eu1vYVK1agW7duklLJVaRIEezcuROhoaG4du0aAMDT0xNubm6Sk8kREBCAQ4cOad2q5unpiSVLlqhyovP69etj7dq1mDZtGoCsc0pmZiZmzZqFRo0aSU6ne6VLl0ZERAQcHR3h7u6OzZs3o0aNGti9e7cysk5N2B9E+fe6u180Gg2MjY3h5uYGFxcXjBs3TsfJ1INFKXorhQoVgpeXF1q1aoWff/4Z48aNw5gxY/Dtt9+iY8eO+PHHH2FnZyc7pnRqK8IAQOPGjbF27VqULFlSa/vZs2fRo0cP3Lx5U1Iy3evRowdCQ0Ph7e0NGxsb1a+ERH+7ePEigKyRUleuXNGaG8jQ0BCVK1fGmDFjZMXTqewCHZD1xm/lypU4cOAAatWqBSDr3BEZGYmePXvKiigdJ3//W2ZmpjJi7GUGBgaqvEg0a9YsNG7cGOfPn0dqaiq++eYbXL16FbGxsTh58qTseDrXp08fBAUFoUGDBvD19UXr1q2xePFipKWl5Sh2qwH7gyj/2rVrp6yg/rKXV1WvV68eduzYASsrK0kpP2ycU4reyvnz57Fq1Sr8+uuvMDMzQ69eveDt7Y27d+9iypQpiI+Px7lz52TH1AkWYbS1atUKZ86cwc8//4xOnTohMzMTU6dOxYwZMzBkyBDMnz9fdkSdMTc3x4kTJ1C5cmXZUf5T1HSvfp8+fbBgwQJVL8ud39EcGo0GR44cec9pCp7XTf6+ePFijBo1SnWTv7dt2xZxcXHYuHEj7O3tAQD37t1Dt27dYGVlhe3bt0tOqHtxcXFYsmQJgoKCkJiYiI8++ghDhw7lxUFkrZB84cIFuLm5oVKlSrLjSMf+IHq9w4cPY/z48Zg+fboyNc25c+cwYcIEfPfdd7C0tMTAgQNRs2ZN+Pn5SU77YWJRivJl7ty5WL16NW7cuIGWLVuiX79+aNmypdbk1nfv3oWzs7Nq5v9gESanJUuW4JtvvkHbtm1x+/Zt3LlzB6tXr1bdrRUff/wxFi1apIz4oPxRU1HqZXfv3gUAlCpVSnKSgu/u3buwt7fPc2GFDwUnf9cWFRWFNm3a4OrVq8rKlZGRkahYsSJ27dqlyudPcnIyLl++nOtt4mpYbIWI6F2oUKECVqxYgTp16mhtP3nyJAYMGICrV6/i0KFD6Nu3LyIjIyWl/LDx9j3Kl6VLl6Jv377o3bv3a6/AWVtbq6p6vHfvXixZsgR9+/bFzp07lSLMnj17VFeEyTZ06FDcvXsXP/74IwoVKoQ//vgjxwleDX7++Wf4+vpi4sSJqFChQo5bTtQ2OiY8PDxfhably5fDxsZGB4nky8zMxPfff485c+Yoq2SZm5vj66+/xvjx41VRdPknPD09cenSJVUULjn5uzYHBwcEBgbi8OHDuH79OgDAw8MDTZo0kZxMjoCAAPTo0QOxsbG53nKihsVWFi5ciAEDBsDY2BgLFy7Ms+2IESN0lEoe9gfRPxMWFpbre3MLCwuEh4cDyLp9Xm0Xg3SJI6UoX27fvg1HR8ccH5SEEIiKioKjo6OkZPKNGzdO9UUYAHj69Cn69euHw4cP46effsKxY8ewY8cOzJo1C0OGDJEdT6du3bqFrl27IjAwUGt79n3paviw8DI9PT00aNAA3t7e6NChgypXl3vVuHHj4OfnhylTpqBu3boAgBMnTmDy5Mno378/pk+fLjlhwaSm0XTDhw+HgYFBjvlfxowZgxcvXmDJkiWSkslz+PBhHD58ONeRQatWrZKUSo4yZcqgadOmmDhxomqK+a9ycXHB+fPnUaxYMbi4uLy2nUajUT5YfsjYH0T/TL169WBubo61a9cqC3c9evQIPXv2xPPnz3H8+HEcOnQIQ4cOxY0bNySn/TCxKEX5oq+vjwcPHsDa2lpr+5MnT2Btba26D9kAizCvKlmyJFxcXLBu3TrlzdCmTZswZMgQ1KpVC3v37pWcUHdq1KiBQoUK4auvvsp1ovMGDRpISibHpUuXsHr1amzcuBGpqano1KkTvL29lfv21cje3h7Lli3LcYvNzp07MWTIENy7d09SsoJNbUWptWvXwsHBIdfJ318egamGiYunTJmCqVOnonr16rCzs8txXlXbnFIWFha4ePEiXF1dZUchIvpPu3HjBtq2bYuIiAjl9vCoqCiULl0aO3fuRNmyZbFjxw4kJCSgR48ektN+mFiUonzR09NDdHR0jqLUnTt34OnpiefPn0tKJg+LMNqmTZuW621Hd+/eRZ8+fXDw4EFJyXTP1NQUF/+vvXuPirrc1wD+cBm5GIimmKjACOMVUJFMJNl19NhJ09C1dhOeAIVx5Q0VlJ3pZgQywdvgDXVtoMJLCDvPUVeUsjcqGiGCgErqDhEd3OFyK4Fy8SCX8wfb2Y2QTu2cd/T3fNZqpe/wx9MvFyPPvO/3LSnBkCFDREcxKS0tLTh8+DA+++wzHDlyBIMHD0ZoaCiCgoJ0n0xJhbW1Nc6fP4/Bgwfrrf/tb3/DqFGj0NTUJCiZaZNSKcVB8Pr69euH9evX8weCfwoNDYWfnx/CwsJERyEieua1tbUhOztbd1HVkCFD8J//+Z8cp2AkLKXosR5e2b1lyxbMnTsXtra2utdaW1tRUFAACwsLSV4/zBLm5z38tvLoJ9lS4e/vD7VaLdlZJ0/yf//3f9ixYwc+/PBDNDc3o1u3bnjnnXewbt06ydwa9corr+CVV17pNPcjPDwchYWFOH36tKBkpk1KpRTpe/HFF3HmzBnuDPqnxsZG/P73v0efPn3g6enZaXahFGYGPfw7qiGksJuQz4OInlUspeixHn5Sm5ubC19fX3Tr1k33Wrdu3eDq6orly5dDoVCIimgSpF7CPLR7925s2LAB5eXlAIDBgwcjKipKcp9s//nPf0ZMTAyioqK6/GFBqtcxFxUV4ZNPPsH+/fvRvXt3hISEICwsDDdu3EBsbCzu3r2LM2fOiI5pFLm5uZg6dSqcnZ3h6+sLAMjPz0dVVRW++uorTJgwQXBC02Rvby+ZQeek74MPPsALL7yA6Oho0VFMQmpqKubNmwdra2u8+OKLen//kMrMoEd3ExYXF6OlpUW3S/n777+HhYUFxowZI4ndhHweRL8eZxaKxVKKDDJnzhxs2bJFcreGPQlLmH/RaDSIjo7GokWL9AY3JyUlYc2aNYiIiBCc0Hi62uprZmYm2UHnGo0Gn376Kf72t79hypQpUKlUmDJlit5zunHjBlxdXSVzq5hWq4WlpSWSkpJw+fJlAB03iS1YsAAtLS2SvjzicbhTSlp+uvOjra0NaWlp8PLygpeXV6eyX2o7P1566SUsXrwYK1as4PESdPz/P3HiBNLS0tCzZ08AHbM/58yZgwkTJmDZsmWCExoXnweR4TizUDyWUkS/EksYfXK5HLGxsQgODtZbT0tLQ0xMDCorKwUlM77r168/9nUXFxcjJTENCoUCoaGhmD179s8ez2tubkZ6ejpCQkKMnE4MXh7x61RVVcHJyQkWFhaio5ARcK7Wz+vVqxcKCwt5nPGf+vfvj+zsbIwYMUJvvaysDJMnT8YPP/wgKJkYfB5EhuPMQvEsRQcg0zVz5kx89tlnsLe3x8yZMx/7tf/zP/9jpFSmY9u2bdi5c6deCTN9+nSMGDECMTExkiulqqurMX78+E7r48ePR3V1tYBE4kitdHqSv/zlL3B2du70aX57ezuqqqrg7OyMbt26SaaQAv515PdR9fX1sLa2NnIaMZ70vvJTD99jHt6KQ9Jw/Phx0RFMVkhICDIyMrBy5UrRUUzC3bt38Y9//KPT+j/+8Q/cu3dPQCKx+DyIDNfc3NzlzzBkPCyl6Gf16NFDt32xR48egtOYHpYw+tzd3ZGZmdnpL8gZGRmSmDl2+PBhvPnmm5DJZDh8+PBjv3b69OlGSmUa3NzcutwVVFNTA7lcLqldQQ+PI5mZmUGtVnd5ecSoUaMEpTMuvq8Q/Xqtra1Yv349jh49yuOMAGbMmIE5c+Zg06ZNGDt2LACgoKAAUVFRv6gAf17weRAZTqVS4fPPP+fMQoF4fI/oV/Lw8MCsWbM6lTBr1qxBRkYGLly4ICiZGAcOHIBSqcSkSZN0xxnz8vKQk5ODzMxMzJgxQ3DCp8vc3Bw3b96Eo6PjY+d7SHGm1E+fzU9dv34dw4cPR0NDg6BkxsfLI4jot/C4o41SPM7Y2NiI5cuX45NPPsGDBw8AAJaWlggLC8OGDRvQvXt3wQmNi8+DyHBLlizB7t27ObNQIJZSRL+S1EuYrhQXF0Oj0eDSpUsAOgY3L1u2DKNHjxacjER4uCtoy5YtmDt3bpe7giwsLJCXlycqojC8PIKI6LfX0NCAiooKAB27dKVevvB5ED0ZS37xWEqRQe7cuQO1Wo3jx493eVVmTU2NoGRisYTp8ODBA7z//vuIjo6GXC4XHcekNTY26pUzzzPuCqJf4osvvkBmZia0Wi2am5v1XisuLhaUioieJVeuXEFFRQX8/f1hY2Oju/VWqvg8iOhZwFKKDDJlyhRcuXIFYWFh6Nu3b6c3NCkNKAZYwnSlR48eKC0t5fMAMHHiROzevRv9+/fXWy8oKEBQUBC+//57QcnE4K4gepKtW7di1apVmD17Nv70pz9hzpw5qKioQGFhIRYuXIiPP/5YdEQiMmF37tzBO++8g+PHj8PMzAzl5eUYNGgQQkND0bNnT2zatEl0RKPi8yCiZwlLKTKInZ0dvvnmG4wcOVJ0FJPBEkZfSEgIRo0aJblbB7sydepUnD59Gjt27IBSqURbWxvi4uKwdu1aLFiwAJs3bxYdkcikDB06FKtXr0ZgYCDs7Oxw7tw5DBo0CGq1GjU1Ndi+fbvoiERkwoKDg3Hr1i2kpKRg2LBhuu8hR48eRWRkJL777jvREY2Kz4Po8XjLvGnh7XtkkKFDh6KpqUl0DJMSEBCAgwcPsoT5J4VCgbi4OOTl5WHMmDGd5hYsXrxYUDLjy8rKQlJSEkJDQ3Ho0CFcu3YN169fx5dffonJkyeLjmcUfLOnX0Kr1epuM7WxsdFdWR4UFIRx48axlCKix8rOzsbRo0cxYMAAvXWFQoHr168LSiUOnwfR4/GWedPCUooMsmPHDqxYsQJqtRoeHh6dbiWQ4rEcljD6UlNT4eDggLNnz+Ls2bN6r5mZmUnueSxcuBA3btzAunXrYGlpiRMnTuh+6JYCvtnTL/HSSy+hpqYGLi4ucHZ2xunTpzFy5EhUVlaCG7qJ6EkaGhq6nNdYU1MDKysrAYnE4vMgerxPP/20y1+TGDy+RwYpLy/HrFmzOg2bfTgwUWpX3AN47LE9MzMzXL161YhpyJT8+OOPUKlUyMnJwYYNG5Cbm4uDBw9i/fr1WLBggeh4RCZHpVJh4MCBWL16NZKSkhAVFQU/Pz8UFRVh5syZSE1NFR2RiEzYlClTMGbMGHz00Uews7PD+fPn4eLignfffRdtbW344osvREc0Kj4PIsM1NTWhvb1dV+Rev34d//u//4vhw4dL5oSDaCylyCBjx46FpaUllixZ0uWg89/97neCkpEpevhtRao3vPTv3x9yuRx79uzRlZcZGRlYsGABxo0bh6ysLMEJiUxLW1sb2traYGnZsYF7//79+Pbbb6FQKPD+++/r3dxIRPSosrIyTJw4Ed7e3jh27BimT5+O7777DjU1NcjLy4Obm5voiEbF50FkuMmTJ2PmzJmYN28eamtrMWTIEHTr1g23b9+GRqPB/PnzRUd87rGUIoPY2tqipKQEQ4YMER3FJEm9hHkoNTUViYmJKC8vB9BxxHHp0qVQqVSCkxnXRx99hFWrVsHc3Fxv/caNG5gzZw7+8pe/CEomxp07d6BWq3H8+HHcunULbW1teq/X1NQISkamQqvVYuDAgZ2+h7a3t6OqqgrOzs6CkhHRs6K2thZJSUk4d+4c6uvr4e3tjYULF6Jfv36iownB50FkmN69eyM3NxcjRoxASkoKtm3bhpKSEhw4cABqtRqXLl0SHfG5x1KKDOLv7w+1Wo1JkyaJjmJSWML8i1qthkajQXh4OHx9fQEA+fn52L59OyIiIhAXFyc4oRgsLDuOEVy5cgVhYWFd7rQMCQkRlIxMhYWFBaqrq+Ho6Ki3fufOHTg6OkryiDgR/TL379/H+fPnu/zwY/r06YJSicPnQWQYW1tbXL58Gc7OznjnnXcwYsQIrF69GlVVVRgyZAgaGxtFR3zucdA5GSQ8PBxLlixBVFQUPD09Ow069/LyEpRMnJ8rYSIiIqDVaiVXwuzcuRPJyckIDAzUrU2fPh1eXl4IDw+X3PPYvXs3NmzYoCssBw8ejKioKAQFBQlOZnynTp3CN998g5EjR4qOQibq4XzCR9XX18Pa2lpAIiJ6lhw5cgRBQUGoqanpdDmCFGef8nkQGc7d3R0HDx7EjBkzcPToUd3N6rdu3ZLkZV4icKcUGeTRY0hAx5ualAed9+nTB1u3btUrYQAgPT0d4eHhuH37tqBkYjg4OKCwsBAKhUJv/fvvv8fYsWNRW1srJpgAGo0G0dHRWLRoEfz8/AAA33zzDZKSkrBmzRrdm51UvPzyy9i2bRvGjRsnOgqZmMjISADAli1bMHfuXL3bolpbW1FQUAALCwvk5eWJikhEzwCFQoHJkydDrVajb9++ouMIx+dBZLgvvvgCs2bNQmtrKyZOnIjs7GwAQHx8PE6ePImvv/5acMLnH0spMsj169cf+7qLi4uRkpgOljD6wsPDIZPJoNFo9NaXL1+OpqYmJCUlCUpmfHK5HLGxsQgODtZbT0tLQ0xMDCorKwUlE6OwsBArVqyAWq2Gh4dHp52W/BRKul5//XUAQG5uLnx9ffUGmnfr1g2urq5Yvnx5p++zREQ/ZW9vj5KSEg7w/ic+D6Jf5ubNm6iursbIkSN1mzHOnDkDe3t7DB06VHC65x9LKaJfiSWMvvDwcOzevRsDBw7U7YgpKCiAVqtFcHCwXhHx6DN73lhbW6OsrAzu7u566+Xl5fD09MT9+/cFJROjvLwcs2bNQnFxsd66lHdakr45c+Zgy5YtLCiJ6FcJDQ2Fn58fwsLCREcxCXweRPQsYSlFP+vw4cN48803IZPJcPjw4cd+rRQHJrKE0fdwx8OTmJmZ4dixY085jVgeHh6YNWsWVq5cqbe+Zs0aZGRk4MKFC4KSiTF27FhYWlpiyZIlXQ46/93vficoGZmiGzduAAAGDBggOAkRPSsaGxvx+9//Hn369Oly9unixYsFJRODz4PIcK+//vpjLyR63n9uMQUspehnmZub4+bNm3B0dOxyptRDUt3pwBLm17lx4wacnJwe+2fqWXfgwAEolUpMmjRJN1MqLy8POTk5yMzMxIwZMwQnNC5bW1uUlJRgyJAhoqOQiWpra8OaNWuwadMm1NfXAwDs7OywbNkyrFq16rn+fkFE/77U1FTMmzcP1tbWePHFF/V+wDQzM8PVq1cFpjM+Pg8iwz066/XBgwcoLS1FWVkZQkJCsGXLFkHJpIOlFNFTJoUS5pewt7dHaWkpBg0aJDrKU1VcXAyNRoNLly4BAIYNG4Zly5Zh9OjRgpMZn7+/P9RqNSZNmiQ6CpmoDz/8EKmpqYiNjdW7HCAmJgZz587Fxx9/LDghEZmyl156CYsXL8aKFSv49y3weRD9FmJiYlBfX4+NGzeKjvLcYylF/7bGxka9G5NIn1RKGEPZ2dnh3Llzz+3zePDgAd5//31ER0dDLpeLjmMS/vznPyMmJgZRUVFdHiPw8vISlIxMhZOTE3bt2tXpKPihQ4ewYMEC/P3vfxeUjIieBb169UJhYSEHe/8TnwfRv+/KlSsYO3YsampqREd57rE6J4NMnDixyx8KCgoKMGrUKOMHeoaw95UWmUyGAwcOiI5hUpRKJS5duoTQ0FC8/PLLGDVqFEaPHq37N1FNTU2Xt9sMHTqUfxkkoicKCQlBRkaG6Bgmg8+D6N+Xn58Pa2tr0TEkwVJ0AHo2WFtbw8vLCzt27IBSqURbWxvi4uKwdu1aLFiwQHQ8IpMSEBCAgwcPdjqjLlWVlZWiI5CJGzlyJLZv346tW7fqrW/fvh0jR44UlIqInhWtra1Yv349jh49Ci8vr047cqVw4cxP8XkQGW7mzJl6v29vb0d1dTWKiooQHR0tKJW0sJQig2RlZSEpKQmhoaE4dOgQrl27huvXr+PLL7/E5MmTRccjMikKhQJxcXHIy8vDmDFj0L17d73XpXbrjYuLi+gIZOLWr1+PqVOn4q9//St8fX0BdHxCWVVVha+++kpwOiIydRcuXNDtvC0rK9N77XG3aj2v+DyIDNejRw+935ubm2PIkCGIi4vjz7lGwplS9It8+OGHWLduHSwtLXHixAmMHz9edCST97zPUPqlpDBj63GzpKRy683hw4fx5ptvQiaT4fDhw4/92kfnCJH0aLVaWFpaIikpCZcvXwbQcTnAggUL0NLSAmdnZ8EJiYiIiOhpYClFBvnxxx+hUqmQk5ODDRs2IDc3FwcPHsT69et5fO8JpFDC/BIs6aTB3NwcN2/ehKOj42Nv/jEzM0Nra6sRk5EpsrCwQHV1NRwdHfXW79y5A0dHR/4ZISIioqfq7NmzuluzR4wYwbmnRsTje2QQDw8PyOVylJSUQC6XY+7cucjIyMCCBQuQlZWFrKws0RFNFntffRcvXoSTk5PoGEbz8P+/1LbLt7W1dflroq783PfJ+vp6DhklIiKip+bWrVt49913ceLECTg4OAAAamtr8frrr2P//v3o06eP2IASwFKKDDJv3jysWrVKb8eDUqmEn58f5syZIzCZ6ZNKCdPQ0ICEhATk5OTg1q1bnYqIh0fWBg4cKCKe0aWmpiIxMRHl5eUAOuZMLV26FCqVSnAy09LY2AhbW1vRMUiQyMhIAB2lrVqt1vuz0NrayhteiYiI6KkKDw/HvXv38N1332HYsGEAOn5+CwkJweLFi5Geni444fOPx/foF5Pqzo9HGVrCSEVgYCByc3MRFBSEfv36dfrzsWTJEkHJjE+tVkOj0SA8PFxvaPP27dsRERGBuLg4wQmNa+LEidi9ezf69++vt15QUICgoCB8//33gpKRaK+//joAIDc3F76+vujWrZvutW7dusHV1RXLly+HQqEQFZGIiIieYz169MBf//pXvPzyy3rrZ86cweTJk1FbWysmmIRwpxQZbPfu3diwYYNu58fgwYMRFRWFoKAgwcnEUKlUjy1hpObrr79GVlYW/Pz8REcRbufOnUhOTkZgYKBubfr06fDy8kJ4eLjkSilra2t4eXlhx44dUCqVaGtrQ1xcHNauXcuZdBJ3/PhxAMCcOXOwZcsW2NvbC05EREREUtLW1gaZTNZpXSaTcQSFkbCUIoNoNBpER0dj0aJFutLhm2++wbx583D79m1EREQITmh8LGH09ezZE7169RIdwyQ8ePAAPj4+ndbHjBmDlpYWAYnEysrKQlJSEkJDQ3Ho0CFcu3YN169fx5dffsmrdgkA8Omnn4qOQERERBL0H//xH1iyZAnS09N1I1f+/ve/IyIiAhMnThScThp4fI8MIpfLERsbi+DgYL31tLQ0xMTEoLKyUlAyceRyOb766ivd2WOp27t3Lw4dOoS0tDTJzwgKDw+HTCaDRqPRW1++fDmampqQlJQkKJlYH374IdatWwdLS0ucOHEC48ePFx2JiIiIiCSsqqoK06dPx3fffaebfavVauHp6YnDhw9jwIABghM+/1hKkUGsra1RVlYGd3d3vfXy8nJ4enri/v37gpKJwxJG3+jRo1FRUYH29na4urp22gZbXFwsKJnxhYeHY/fu3Rg4cCDGjRsHoGN+klarRXBwsN6zebS4eh79+OOPUKlUyMnJwYYNG5Cbm4uDBw9i/fr1PL5HREREREK1t7cjJycHly5dAgAMGzYMkyZNEpxKOlhKkUE8PDwwa9YsrFy5Um99zZo1yMjIwIULFwQlE4cljL7Y2NjHvr569WojJRHv4fDmJzEzM8OxY8eechrx+vfvD7lcjj179kAulwMAMjIysGDBAowbNw5ZWVmCExIRERGRVOXk5Pzs5VWffPKJoFTSwZlSZJDY2FgolUqcPHlSN0MpLy8POTk5yMzMFJxOjICAANERTIqUSqcneTi8+Ulu3LiBtrY2mJubP+VEYs2bNw+rVq3S++9UKpXw8/PDnDlzBCYjIiIiIimLjY1FXFwcfHx8eHmVINwpRQYrLi6GRqPR29a4bNkyjB49WnAyomeTvb09SktLMWjQINFRjObhWw7f8ImIiIhItH79+mH9+vWSvVHeFDzfH8/Tb+LBgwcIDQ1Fz549sXfvXpw9exZnz57F3r17WUiRTmtrKzZu3IixY8fipZdeQq9evfT+oc6k9JnA7t274enpCRsbG9jY2MDLywt79uwRHYuIiIiIJKy5uZmX7wjGUoqeSCaT4cCBA6JjmByWMPpiY2Oh0WigVCpRV1eHyMhIzJw5E+bm5oiJiREdjwTSaDSYP38+pkyZgszMTGRmZuK//uu/MG/ePCQmJoqOR0REREQSpVKp8Pnnn4uOIWk8vkcGCQkJwahRoxARESE6islQq9VISUnBsmXL8Mc//hGrVq3CtWvXcPDgQajVaixevFh0RKNyc3PD1q1bMXXqVNjZ2aG0tFS3dvr0aX6z74KdnR3OnTv33B/fk8vliI2NRXBwsN56WloaYmJiUFlZKSgZEREREUlNZGSk7tdtbW1IS0uDl5cXvLy8Ol1eJYWbskXjoHMyiEKhQFxcHPLy8jBmzBh0795d73WpFTAAsG/fPiQnJ2Pq1KmIiYlBYGAg3Nzc4OXlhdOnT0vumdy8eROenp4AgBdeeAF1dXUAgLfeegvR0dEio5Fg1dXVXW6LHj9+PKqrqwUkIiIiIiKpKikp0fv9qFGjAABlZWV665yBahwspcggqampcHBw0M2T+ikzMzPJFTAAS5hHDRgwANXV1XB2doabmxuys7Ph7e2NwsJCWFlZiY5nkqTyRufu7o7MzEysXLlSbz0jIwMKhUJQKiIiIiKSIkNvyibjYClFBuHxms5YwuibMWMGcnJy8MorryA8PBzvvfceUlNTodVqeezzZ0jl9HRsbCyUSiVOnjwJPz8/AEBeXh5ycnKQmZkpOB0REREREYnCmVL0i/FK9w4rVqyAvb09Vq5ciYyMDLz33ntwdXXVlTAJCQmiIwqVn5+P/Px8KBQKTJs2TXQck1RVVQUnJydYWFiIjvLUFRcXQ6PR4NKlSwCAYcOGYdmyZbzBk4iIiIhIwlhKkcFSU1ORmJiI8vJyAB1zppYuXQqVSiU4mWlgCUMPNTQ0ICEhATk5Obh16xba2tr0Xr969aqgZMb34MEDvP/++4iOjoZcLhcdh4iIiIiITAhLKTKIWq2GRqNBeHg4fH19AXSUMNu3b0dERATi4uIEJyRTsGfPHuzatQuVlZXIz8+Hi4sLNm/eDLlcjrffflt0PKMJDAxEbm4ugoKC0K9fv067CpcsWSIomRg9evRAaWkpSykiIiIiItLDUooM0qdPH2zduhWBgYF66+np6QgPD8ft27cFJROLJcy/7Ny5E2q1GkuXLsXHH3+MsrIyDBo0CJ999hnS0tIkNVDQwcEBWVlZuvlJUhcSEoJRo0ZxthgREREREenhoHMyyIMHD+Dj49NpfcyYMWhpaRGQSLxHS5jW1lYAHYXE5s2bJVdKbdu2DcnJyQgICNCbp+Xj44Ply5cLTGZ8PXv2RK9evUTHMBkKhQJxcXHIy8vDmDFj0L17d73XpXh7JxERERERcacUGSg8PBwymQwajUZvffny5WhqakJSUpKgZOIMHz4ca9euRUBAAOzs7HDu3DkMGjQIZWVleO211yS3e8zGxgaXL1+Gi4uL3vMoLy+Hl5cXmpqaREc0mr179+LQoUNIS0uDra2t6DjCPe7YnpmZmaRmbBERERER0b9wpxQZLDU1FdnZ2Rg3bhwAoKCgAFqtFsHBwYiMjNR93aPF1fOqsrKyy5vDrKys0NDQICCRWHK5HKWlpXBxcdFbP3LkCIYNGyYolRibNm1CRUUF+vbtC1dXV8hkMr3Xi4uLBSUTo7KyUnQEIiIiIiIyQSylyCBlZWXw9vYGAFRUVAAAevfujd69e6OsrEz3dY8OdH6esYTRFxkZiYULF+L+/ftob2/HmTNnkJ6ejvj4eKSkpIiOZ1QBAQGiI5ish5tzpfS9goiIiIiIusZSigxi6JDqGzduoK2tDebm5k85kXgsYfSpVCrY2Njgj3/8IxobGzFr1iw4OTlhy5YtePfdd0XHM6rVq1eLjmByUlNTkZiYiPLycgAdc6aWLl0KlUolOBkREREREYnCmVL0m7K3t0dpaSkGDRokOopR7Nu3DzExMbrdY05OToiNjUVYWJjgZGI1Njaivr4ejo6OoqOQCVCr1dBoNAgPD4evry8AID8/H9u3b0dERATi4uIEJyQiIiIiIhFYStFv6qcDrqWEJUzH3KCWlhYoFAq99fLycshkMri6uooJJkBraysSExORmZkJrVaL5uZmvddramoEJROjT58+2Lp1KwIDA/XW09PTER4eLrlLAYiIiIiIqMPzf8aK6CmprKzUHUWytbXVFVLl5eW4du2awGRizJ49G99++22n9YKCAsyePdv4gQSKjY2FRqOBUqlEXV0dIiMjMXPmTJibmyMmJkZ0PKN78OABfHx8Oq2PGTMGLS0tAhIREREREZEpYClF9CuxhNFXUlICPz+/Tuvjxo1DaWmp8QMJtG/fPiQnJ2PZsmWwtLREYGAgUlJSoFarcfr0adHxjC4oKAg7d+7stP6nP/0J//3f/y0gERERERERmQIOOif6lR5XwixatEhAIrHMzMxw7969Tut1dXVobW0VkEicmzdvwtPTEwDwwgsvoK6uDgDw1ltvITo6WmQ0YVJTU5GdnY1x48YB6ChvtVotgoODERkZqfs6jUYjKiIRERERERkZSyn6TUnpmneWMPr8/f0RHx+P9PR0WFhYAOiYrRQfH49XX31VcDrjGjBgAKqrq+Hs7Aw3NzdkZ2fD29sbhYWFsLKyEh3P6MrKyuDt7Q0AuksBevfujd69e6OsrEz3dVL6/kFERERERBx0Tr8xKQ06nzZtGmxsbDqVMEqlEg0NDfj6668FJzSuixcvwt/fHw4ODpgwYQIA4NSpU7h79y6OHTsGDw8PwQmNZ8WKFbC3t8fKlSuRkZGB9957D66urtBqtYiIiEBCQoLoiCbpxo0bcHJygrk5T5YTEREREUkBSyn6TVVVVcHJyUlX0jzPWMJ09sMPPyApKQmlpaWwsbGBl5cXFi1ahF69eomOJlR+fj7y8/OhUCgwbdo00XFMlr29PUpLSyVRahMREREREY/vkYEaGhqQkJCAnJwc3Lp1C21tbXqvX716FQAwcOBAEfGEGD58OM6fP69XwgQHB0u6hLG1tUWvXr3Qr18/AB3zlKRQUD6Jr68vfH19RccwefyMhIiIiIhIWlhKkUFUKhVyc3MRFBSEfv36cfbLP7GE+ZeioiK88cYbsLGxwdixYwEAiYmJWLt2rW6mkpTs2bMHu3btQmVlJfLz8+Hi4oLNmzdDLpfj7bffFh2PiIiIiIhIOB7fI4M4ODggKyury9vmpKqrEqawsBBNTU2SLGEmTJgAd3d3JCcnw9Kyo+9uaWmBSqXC1atXcfLkScEJjWfnzp1Qq9VYunQpPv74Y5SVlWHQoEH47LPPkJaWhuPHj4uOaJKkNJOOiIiIiIhYSpGB5HI5vvrqKwwbNkx0FJPBEkafjY0NSkpKMHToUL31ixcvwsfHB42NjYKSGd/w4cOxdu1aBAQE6BUtZWVleO2113D79m3REU0SSykiIiIiImnhFUdkkI8++ghqtVpSxcKTFBUV4YMPPtAVUgBgaWmJP/zhDygqKhKYTAx7e3totdpO61VVVbCzsxOQSJzKykqMHj2607qVlRUaGhoEJHo28FgwEREREZG0cKYUGWTTpk2oqKhA37594erqCplMpvd6cXGxoGTiPCxhHt0ZJMUSBgCUSiXCwsKwceNGjB8/HgCQl5eHqKgoBAYGCk5nXHK5HKWlpXBxcdFbP3LkCHcbPgY37hIRERERSQtLKTJIQECA6AgmhyWMvo0bN8LMzAzBwcFoaWkBAMhkMsyfPx8JCQmC0xlXZGQkFi5ciPv376O9vR1nzpxBeno64uPjkZKSIjqeybp48SKcnJxExyAiIiIiIiPhTCmiX6m5uRlRUVHYtWtXlyWMlZWV4IRiNDY2oqKiAgDg5uYGW1tbwYnE2LdvH2JiYnTPwsnJCbGxsQgLCxOczPgaGhqQkJCAnJwc3Lp1C21tbXqvX716VVAyIiIiIiISiaUU0b+JJQw9TmNjI+rr6+Ho6Cg6ijCBgYHIzc1FUFAQ+vXr12l21JIlSwQlIyIiIiIikVhKkUFaW1uRmJiIzMxMaLVaNDc3671eU1MjKBmR6amsrERLSwsUCoXeenl5OWQyGVxdXcUEE8TBwQFZWVnw8/MTHYWIiIiIiEwIb98jg8TGxkKj0UCpVKKurg6RkZGYOXMmzM3NERMTIzoekUmZPXs2vv32207rBQUFmD17tvEDCdazZ0/06tVLdAwiIiIiIjIx3ClFBnFzc8PWrVsxdepU2NnZobS0VLd2+vRpfP7556IjEpkMe3t7FBcXw93dXW/9ypUr8PHxQW1trZhgguzduxeHDh1CWloaj7cSEREREZEOb98jg9y8eROenp4AgBdeeAF1dXUAgLfeegvR0dEioxGZHDMzM9y7d6/Tel1dHVpbWwUkEmvTpk2oqKhA37594erqCplMpvd6cXGxoGRERERERCQSSykyyIABA1BdXQ1nZ2e4ubkhOzsb3t7eKCwslOwtc0Q/x9/fH/Hx8UhPT4eFhQWAjrls8fHxePXVVwWnM76AgADREYiIiIiIyATx+B4ZZMWKFbC3t8fKlSuRkZGB9957D66urtBqtYiIiEBCQoLoiEQm4+LFi/D394eDgwMmTJgAADh16hTu3r2LY8eOwcPDQ3BCIiIiIiIi8VhK0a+Sn5+P/Px8KBQKTJs2TXQcIpPzww8/YPv27Th37hxsbGzg5eWFRYsWceA3ERERERHRP7GUIiKip6q1tRWJiYnIzMyEVqtFc3Oz3us1NTWCkhERERERkUjmogPQs2PPnj3w8/ODk5MTrl+/DgDYvHkzDh06JDgZkempra3Fpk2boFKpoFKpkJiYqLsgQGpiY2Oh0WigVCpRV1eHyMhIzJw5E+bm5oiJiREdj4iIiIiIBGEpRQbZuXMnIiMjMWXKFNTW1upuEHNwcMDmzZvFhiMyMUVFRXBzc0NiYiJqampQU1MDjUYDNzc3Sd40t2/fPiQnJ2PZsmWwtLREYGAgUlJSoFarcfr0adHxiIiIiIhIEB7fI4MMHz4ca9euRUBAAOzs7HDu3DkMGjQIZWVleO2113D79m3REYlMxoQJE+Du7o7k5GRYWnZcctrS0gKVSoWrV6/i5MmTghMaV/fu3XHp0iU4OzujX79+yMrKgre3N65evYrRo0dLdgcZEREREZHUcacUGaSyshKjR4/utG5lZYWGhgYBiYhMV1FRET744ANdIQUAlpaW+MMf/oCioiKBycQYMGAAqqurAQBubm7Izs4GABQWFsLKykpkNCIiIiIiEoilFBlELpejtLS00/qRI0cwbNgw4wciMmH29vbQarWd1quqqmBnZycgkVgzZsxATk4OACA8PBzR0dFQKBQIDg5GaGio4HRERERERCSK5ZO/hAiIjIzEwoULcf/+fbS3t+PMmTNIT09HfHw8UlJSRMcjMilKpRJhYWHYuHEjxo8fDwDIy8tDVFQUAgMDBaczvoSEBN2vlUolnJ2dkZ+fD4VCgWnTpglMRkREREREInGmFBls3759iImJQUVFBQDAyckJsbGxCAsLE5yMyLQ0NzcjKioKu3btQktLCwBAJpNh/vz5SEhI4JE1IiIiIiIisJSiX6GxsRH19fVwdHQUHYXIpDU2NupKXDc3N9ja2gpOJM6ePXuwa9cuVFZWIj8/Hy4uLti8eTPkcjnefvtt0fGIiIiIiEgAzpQig1RWVqK8vBwAYGtrqyukysvLce3aNYHJiEyXra0tPD094enpKelCaufOnYiMjMSUKVNQW1uL1tZWAICDgwM2b94sNhwREREREQnDUooMMnv2bHz77bed1gsKCjB79mzjByKiZ8a2bduQnJyMVatWwcLCQrfu4+ODCxcuCExGREREREQisZQig5SUlMDPz6/T+rhx47q8lY+I6KHKykqMHj2607qVlRUaGhoEJCIiIiIiIlPAUooMYmZmhnv37nVar6ur0x3FISLqilwu77K8PnLkCIYNG2b8QEREREREZBIsRQegZ4O/vz/i4+ORnp6uO37T2tqK+Ph4vPrqq4LTEZEpi4yMxMKFC3H//n20t7fjzJkzSE9PR3x8PFJSUkTHIyIiIiIiQXj7Hhnk4sWL8Pf3h4ODAyZMmAAAOHXqFO7evYtjx47Bw8NDcEIiMmX79u1DTEyM7jZCJycnxMbGIiwsTHAyIiIiIiIShaUUGeyHH37A9u3bce7cOdjY2MDLywuLFi1Cr169REcjomdEY2Mj6uvrdTd4EhERERGRdLGUIiKip6qyshItLS1QKBR66+Xl5ZDJZHB1dRUTjIiIiIiIhOJMKTJYbW0tUlNTcenSJQDAiBEjEBoaih49eghORkSmbPbs2QgNDe1UShUUFCAlJQUnTpwQE4yIiIiIiITiTikySFFREd544w3Y2Nhg7NixAIDCwkI0NTUhOzsb3t7eghMSkamyt7dHcXEx3N3d9davXLkCHx8f1NbWiglGRERERERCcacUGSQiIgLTp09HcnIyLC07/ti0tLRApVJh6dKlOHnypOCERGSqzMzMcO/evU7rdXV1aG1tFZCIiIiIiIhMAXdKkUFsbGxQUlKCoUOH6q1fvHgRPj4+aGxsFJSMiEzdtGnTYGNjg/T0dFhYWAAAWltboVQq0dDQgK+//lpwQiIiIiIiEoE7pcgg9vb20Gq1nUqpqqoq2NnZCUpFRM+CdevWwd/fH0OGDMGECRMAAKdOncLdu3dx7NgxwemIiIiIiEgUc9EB6NmgVCoRFhaGjIwMVFVVoaqqCvv374dKpUJgYKDoeERkwoYPH47z58/jnXfewa1bt3Dv3j0EBwfj8uXL8PDwEB2PiIiIiIgE4fE9MkhzczOioqKwa9cutLS0AABkMhnmz5+PhIQEWFlZCU5IRERERERERM8SllL0izQ2NqKiogIA4ObmBltbW8GJiOhZUFtbi9TUVFy6dAkAMGLECISGhqJHjx6CkxERERERkSgspYiI6KkqKirCG2+8ARsbG4wdOxYAUFhYiKamJmRnZ8Pb21twQiIiIiIiEoGlFBERPVUTJkyAu7s7kpOTYWnZcb9GS0sLVCoVrl69ipMnTwpOSEREREREIrCUIiKip8rGxgYlJSWdbu+8ePEifHx80NjYKCgZERERERGJxNv3iIjoqbK3t4dWq+20XlVVBTs7OwGJiIiIiIjIFLCUIiKip0qpVCIsLAwZGRmoqqpCVVUV9u/fD5VKhcDAQNHxiIiIiIhIEEvRAYiI6Pm2ceNGmJmZITg4GC0tLQAAmUyG+fPnIyEhQXA6IiIiIiIShTOliIjIKBobG1FRUQEAcHNzg62treBEREREREQkEkspIiIiIiIiIiIyOs6UIiIiIiIiIiIio2MpRURERERERERERsdSioiIiIiIiIiIjI6lFBERERERERERGR1LKSIiIiIiIiIiMjqWUkREREREREREZHQspYiIiIiIiIiIyOhYShERERERERERkdH9P0E+yDQvgiWeAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# One other idea is to see what a 3-degree polynomial does on 'median_income'\n",
    "results_df, iteration_6 = dw.iterate_model(X2_train, X2_test, y2_train, y2_test,\n",
    "        transformers=['ohe', 'log', 'poly3'], model='linreg',\n",
    "        iteration='6', note='X2. Test size: 0.25, Pipeline: OHE > Log > Poly3 > LinReg',\n",
    "        plot=True, lowess=True, coef=True, perm=True, vif=True, decimal=2,\n",
    "        save=True, save_df=results_df, config=my_config)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-9 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-9 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-9 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-9 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-9 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-9 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-9 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-9 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-9 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-9 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-9 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-9 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-9 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-9 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-9 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-9 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-9 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-9 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-9 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-9 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-9 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-9 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-9 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-9 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-9 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-9\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;ohe_log_poly3&#x27;,\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;ohe&#x27;,\n",
       "                                                  OneHotEncoder(drop=&#x27;if_binary&#x27;,\n",
       "                                                                handle_unknown=&#x27;ignore&#x27;),\n",
       "                                                  [&#x27;ocean_proximity&#x27;]),\n",
       "                                                 (&#x27;log&#x27;, LogTransformer(),\n",
       "                                                  [&#x27;total_rooms&#x27;,\n",
       "                                                   &#x27;total_bedrooms&#x27;,\n",
       "                                                   &#x27;population&#x27;,\n",
       "                                                   &#x27;households&#x27;]),\n",
       "                                                 (&#x27;poly3&#x27;,\n",
       "                                                  PolynomialFeatures(degree=3,\n",
       "                                                                     include_bias=False),\n",
       "                                                  [&#x27;median_income&#x27;])])),\n",
       "                (&#x27;linreg&#x27;, LinearRegression())])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-65\" type=\"checkbox\" ><label for=\"sk-estimator-id-65\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;ohe_log_poly3&#x27;,\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;ohe&#x27;,\n",
       "                                                  OneHotEncoder(drop=&#x27;if_binary&#x27;,\n",
       "                                                                handle_unknown=&#x27;ignore&#x27;),\n",
       "                                                  [&#x27;ocean_proximity&#x27;]),\n",
       "                                                 (&#x27;log&#x27;, LogTransformer(),\n",
       "                                                  [&#x27;total_rooms&#x27;,\n",
       "                                                   &#x27;total_bedrooms&#x27;,\n",
       "                                                   &#x27;population&#x27;,\n",
       "                                                   &#x27;households&#x27;]),\n",
       "                                                 (&#x27;poly3&#x27;,\n",
       "                                                  PolynomialFeatures(degree=3,\n",
       "                                                                     include_bias=False),\n",
       "                                                  [&#x27;median_income&#x27;])])),\n",
       "                (&#x27;linreg&#x27;, LinearRegression())])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-66\" type=\"checkbox\" ><label for=\"sk-estimator-id-66\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;ohe_log_poly3: ColumnTransformer<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.compose.ColumnTransformer.html\">?<span>Documentation for ohe_log_poly3: ColumnTransformer</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>ColumnTransformer(force_int_remainder_cols=False, remainder=&#x27;passthrough&#x27;,\n",
       "                  transformers=[(&#x27;ohe&#x27;,\n",
       "                                 OneHotEncoder(drop=&#x27;if_binary&#x27;,\n",
       "                                               handle_unknown=&#x27;ignore&#x27;),\n",
       "                                 [&#x27;ocean_proximity&#x27;]),\n",
       "                                (&#x27;log&#x27;, LogTransformer(),\n",
       "                                 [&#x27;total_rooms&#x27;, &#x27;total_bedrooms&#x27;, &#x27;population&#x27;,\n",
       "                                  &#x27;households&#x27;]),\n",
       "                                (&#x27;poly3&#x27;,\n",
       "                                 PolynomialFeatures(degree=3,\n",
       "                                                    include_bias=False),\n",
       "                                 [&#x27;median_income&#x27;])])</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-67\" type=\"checkbox\" ><label for=\"sk-estimator-id-67\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">ohe</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;ocean_proximity&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-68\" type=\"checkbox\" ><label for=\"sk-estimator-id-68\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;OneHotEncoder<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.OneHotEncoder.html\">?<span>Documentation for OneHotEncoder</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>OneHotEncoder(drop=&#x27;if_binary&#x27;, handle_unknown=&#x27;ignore&#x27;)</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-69\" type=\"checkbox\" ><label for=\"sk-estimator-id-69\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">log</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;total_rooms&#x27;, &#x27;total_bedrooms&#x27;, &#x27;population&#x27;, &#x27;households&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-70\" type=\"checkbox\" ><label for=\"sk-estimator-id-70\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">LogTransformer</label><div class=\"sk-toggleable__content fitted\"><pre>LogTransformer()</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-71\" type=\"checkbox\" ><label for=\"sk-estimator-id-71\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">poly3</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;median_income&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-72\" type=\"checkbox\" ><label for=\"sk-estimator-id-72\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;PolynomialFeatures<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.PolynomialFeatures.html\">?<span>Documentation for PolynomialFeatures</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>PolynomialFeatures(degree=3, include_bias=False)</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-73\" type=\"checkbox\" ><label for=\"sk-estimator-id-73\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">remainder</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;longitude&#x27;, &#x27;latitude&#x27;, &#x27;housing_median_age&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-74\" type=\"checkbox\" ><label for=\"sk-estimator-id-74\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">passthrough</label><div class=\"sk-toggleable__content fitted\"><pre>passthrough</pre></div> </div></div></div></div></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-75\" type=\"checkbox\" ><label for=\"sk-estimator-id-75\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;LinearRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.linear_model.LinearRegression.html\">?<span>Documentation for LinearRegression</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>LinearRegression()</pre></div> </div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('ohe_log_poly3',\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder='passthrough',\n",
       "                                   transformers=[('ohe',\n",
       "                                                  OneHotEncoder(drop='if_binary',\n",
       "                                                                handle_unknown='ignore'),\n",
       "                                                  ['ocean_proximity']),\n",
       "                                                 ('log', LogTransformer(),\n",
       "                                                  ['total_rooms',\n",
       "                                                   'total_bedrooms',\n",
       "                                                   'population',\n",
       "                                                   'households']),\n",
       "                                                 ('poly3',\n",
       "                                                  PolynomialFeatures(degree=3,\n",
       "                                                                     include_bias=False),\n",
       "                                                  ['median_income'])])),\n",
       "                ('linreg', LinearRegression())])"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the pipeline\n",
    "iteration_6"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Iteration 7: Linear Regression with OHE, Log"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "ITERATION 7 RESULTS\n",
      "\n",
      "Pipeline: ohe_log -> linreg\n",
      "Note: X2. Test size: 0.25, Pipeline: OHE > Log > LinReg\n",
      "May 30, 2024 09:17 AM UTC\n",
      "\n",
      "Predictions:\n",
      "                          Train            Test\n",
      "MSE:            3,237,365,967.08 3,249,712,162.27\n",
      "RMSE:                 56,897.86       57,006.25\n",
      "MAE:                  41,453.54       41,585.27\n",
      "R^2 Score:                 0.64            0.66\n",
      "\n",
      "Permutation Feature Importance:\n",
      "           Feature Importance Mean Importance Std\n",
      "     median_income            0.94           0.01\n",
      "    total_bedrooms            0.79           0.01\n",
      "        population            0.59           0.01\n",
      "          latitude            0.59           0.01\n",
      "         longitude            0.57           0.01\n",
      "       total_rooms            0.30           0.01\n",
      "        households            0.22           0.00\n",
      "   ocean_proximity            0.06           0.00\n",
      "housing_median_age            0.02           0.00\n",
      "\n",
      "Variance Inflation Factor:\n",
      "          Features   VIF Multicollinearity\n",
      "    total_bedrooms 32.40              High\n",
      "        households 30.01              High\n",
      "       total_rooms 13.80              High\n",
      "          latitude  8.74          Moderate\n",
      "         longitude  8.43          Moderate\n",
      "        population  6.75          Moderate\n",
      "     median_income  1.83               Low\n",
      "housing_median_age  1.30               Low\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Coefficients:\n",
      "                       Feature Coefficient\n",
      "1    ocean_proximity_<1H OCEAN   -4,563.40\n",
      "2       ocean_proximity_INLAND  -37,995.49\n",
      "3       ocean_proximity_ISLAND   68,751.51\n",
      "4     ocean_proximity_NEAR BAY  -23,027.74\n",
      "5   ocean_proximity_NEAR OCEAN   -3,164.88\n",
      "6              total_rooms_log  -50,498.18\n",
      "7           total_bedrooms_log   84,183.78\n",
      "8               population_log  -71,995.45\n",
      "9               households_log   44,404.94\n",
      "10                   longitude  -25,874.39\n",
      "11                    latitude  -24,114.88\n",
      "12          housing_median_age      728.72\n",
      "13               median_income        4.17\n"
     ]
    },
    {
     "data": {
      "image/png": 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yv/zyC6ZOnSp3DCIiIiIiIiKiT9oHuX3vTebm5qhYsSKCgoJgZWWFlJQUxMbGKrV58uRJjnNQAZC2v71C35uPsbKywtOnT5X2p6WlISYmRqlNTl/jze+RkwkTJuDly5fSR0RExDt+YiIiIiIiIiIiKqgPXpRKSEhAcHAwrK2tUbt2bejq6uLYsWPS/rt37yI8PBwNGjTI8fGOjo6wsrJSekxcXBwuXLggPaZBgwaIjY3FlStXpDbHjx9HRkYG6tWrJ7U5deoUUlNTpTZHjhxBpUqVYGFhkWt+fX19mJqaKn0QEREREREREdGH9d5FqbFjx+LkyZMICwvD2bNn8e2330JbWxs9evSAmZkZPD09MXr0aJw4cQJXrlyBh4cHGjRokOPKewCgUCgwcuRIzJgxA3v37sWNGzfQp08f2NjYoFOnTgAAZ2dntG7dGgMGDMDFixdx5swZDBs2DN27d4eNjQ0AoGfPntDT04Onpydu3bqFrVu3YuHChRg9evT7/shERERERERERPSe3ntOqYcPH6JHjx6Ijo5GqVKl0LhxY5w/fx6lSpUCAMyfPx9aWlro3LkzkpOT0apVKyxbtkzpazg4OKBv376YMmUKAODHH3/Eq1evMHDgQMTGxqJx48bw8/ODgYGB9JiNGzdi2LBhaN68ufT1Fy1aJO03MzPD4cOHMXToUNSuXRslS5aEt7c3Bg4c+L4/MhERERGRbBzGH5A7gmzCZreTOwIREX1ACiGEkDNAYmIiSpQogUOHDuHLL7+UM0qO4uLiYGZmhpcvX/JWPqIC4otmIioKeK4jVeMxR0RE6i6/tZQPPqdUQZ04cQJfffWVWhakiIiIiIiIiIjo45C9KNWuXTscOFB0r/YQERERERERERVFsheliIiIiIiIiIio6GFRioiIiIiIiIiIVI5FKSIiIiIiIiIiUjkWpYiIiIiIiIiISOVYlCIiIiIiIiIiIpVjUYqIiIiIiIiIiFSORSkiIiIiIiIiIlI5FqWIiIiIiIiIiEjlWJQiIiIiIiIiIiKVY1GKiIiIiIiIiIhUjkUpIiIiIiIiIiJSORaliIiIiIiIiIhI5ViUIiIiIiIiIiIilWNRioiIiIiIiIiIVI5FKSIiIiIiIiIiUjkWpYiIiIiIiIiISOVYlCIiIiIiIiIiIpVjUYqIiIiIiIiIiFSORSkiIiIiIiIiIlI5FqWIiIiIiIiIiEjlWJQiIiIiIiIiIiKVY1GKiIiIiIiIiIhUjkUpIiIiIiIiIiJSuSJRlFq6dCkcHBxgYGCAevXq4eLFi3JHIiIiIiIiIiIq0j75otTWrVsxevRoTJ48Gf7+/qhRowZatWqFp0+fyh2NiIiIiIiIiKjI+uSLUvPmzcOAAQPg4eEBFxcXrFixAkZGRlizZo3c0YiIiIiIiIiIiqxPuiiVkpKCK1euoEWLFtI2LS0ttGjRAufOnZMxGRERERERERFR0fZJF6WeP3+O9PR0WFpaKm23tLREVFRUjo9JTk5GXFyc0gcA3Lp1S2pz+/ZtREREAACSkpLg7++P+Ph4AMCTJ08QEBAgtb179y4ePHgAAEhNTYW/vz9evnwJAHj27BmuXr0qtb1//z5CQ0MBAOnp6fD398eLFy8AANHR0fD394cQAgAQHByM4OBgAIAQAv7+/oiOjgYAvHjxAv7+/khPTwcAhIaG4v79+9L3uXr1Kp49ewYAePnyJfz9/ZGamgoAePDgAe7evSu1DQgIwJMnTwAA8fHx8Pf3R1JSEgAgIiICt2/fltreuHEDkZGRAIBXr17B398fr1+/BgA8evRIqQ9v3bqFhw8fAgBev34Nf39/JCQkAAAiIyNx/fp1qe2dO3cQHh4u/X78/f2l38uTJ09w7do1pf4OCwtT6u/Y2Fipv/39/ZX6OyQkRKm/Y2JiAAAxMTHw9/dHRkYGACAkJARBQUHSY/39/fH8+XOl/k5LS5P6+969e1Lba9euSbeLxsXFwd/fHykpKQCA8PBwBAYGSm2vX78uHZsJCQlK/f3w4UOl/r558yYeP34MAEhMTIS/vz8SExMBAI8fP8bNmzeltrdv35b6O+uYzervqKgopf4ODAyU+jslJUWpv58+farU3/fu3ZOO2bS0NKVj9vnz50iO+q/PUl88Rmps5s8mRAaSo4KQ/jrz7yb9dTySo4IgMjKP2dTYKKTGPJIemxwVhPTEzL+bjKSEzLbpmf2d9vIJUqMfSm1TnoQg/VVmhozkxMy2aZnHd1rcU6Q+j/iv7dNQpCVk/s4zUl4jOSoIGanJ/2/7HCnPHvzX9tkDpMVn/s4zUpMz26Zk/m7SEmKQ8izsv7bPw3mOAM8RPEe8+xzxZn8HBQVJ/Z2RkZFjf2cdsyEhIUrHrL+/v3TMxsbGKh2zYWFhSsfstWvXpGM2q7+Tk5Ol/r5z545Sf2cds1n9nXXMPnz4UOmYLeg5Ii0uM69IS8lsm5z5u0l/9QIpT0OktqnRD5H2MvP4EOlp/2/7KrNt4kukPAn+r23Mo//OsxnpmefOpMzfY/rruMzz4f/PEakvIpH6IvNnE0L8/5yc+XtMzzrP5nJOTnkSLJ2TeY6Q5xwh0t94XotWfl5LT/j/c+D/n9dEWsr/2z5HyvPw/9o+C0NafObzQkZq0v+fA/9/zMZH53DMZuaVjtmUzN9NesILpDwNldqmRkcgLS7rmE196/iORcqTN47vvI7ZxJe5vo7QxHPErVu38OhR5t9R1jH76lXm33JkZCRu3LghteV7jU/rHOEw/gDsf9wL674LYfvDFjiMPwDbH7bAuu9C2Hvtg8P4Aygz2AdlBv0Bh/EH4DD+QGbbEZsy247cmtn2x73/tR24Smpr47EYtsM3wmH8AdiN+iuz7bjdcBh/AGWHrEWZASv+a9tvCWyH/ZnZdvT2zLZjd/2/7TrY9F/+X1vPpSg7dH1m2zE7YN13IezG7MhsO3Q9bDyX/te2/3KUHbIu82cduyuz7ejtAPg6gueIfBCfsEePHgkA4uzZs0rbx40bJ+rWrZvjYyZPniwAZPuwtraW2lSrVk0MHz5cCCHE/fv3BQBx4sQJIYQQc+bMERYWFlLb+vXrC09PTyGEEI8fPxYAxP79+4UQQixZskTo6elJbZs3by66d+8uhBDi5cuXAoDYtm2bEEKItWvXCgAiNTVVCCFE+/btRfv27YUQQqSmpgoAYu3atUIIIbZt2yYAiJcvXwohhOjevbto3ry5sPfaL+y99gto64jiXw8W9l77RakumT9vmaHrhb3XflGsekuhZ1NJaqtlUEyYf+kh7L32C8seswQAYTNwlbD32i9MarcXuqUcpLbaxUoIs0Y9hL3XfmHVZ15mv3ksFvZe+4Vp/S5Cx9xaaqtTvIwwresq7L32C+t+SwUAYdX7N2HvtV+YNekttI0tpLZ6luVFsVrthL3XflFmsI8AIEp3myHsvfYLi2aeQqFnKLXVL+MijKtm/qxlh28UAEQp10lCCCFWrFghtLW1pf5u2bKl6NKlixBCiISEBAFAbNq0SQghxIYNGwQAkZSUJIQQwrBiA2FYrs5/fQiI4q2HZ/Zhp58EAFF2xGZh77VfGLt8KfRtq0ptFbr6wqL5QGHvtV+U/m5qZn9/75vZ3zVaCz2rCv/1t6GpMP+iT2Z/9/o1s7/7r8js7zodhW4Ju//627S0MG3QLbO/3Rdk9qH7gsz+btBNaJuWltrqlrATJnU6Cnuv/cKm/woBQFj2+lXYe+0X5l/0EVqGpv/1t1UFUaxG68z+/t5XABB+fn5CCCEWLlwojIyMpD5s2rSp6NWrlxBCiOjoaAFA7NixQwghxB9//CHePMW0bdtWfPvtt0IIIZKSkgQAsWHDBiGEEJs2bRIAREJCghBCiC5duoiWLVtKj9XW1hYrVqwQQgixZ88eAUA8ffpUCCGEu7u7aNSokdTWxMREzJ07VwghxJEjRwQAERoaKoQQYsiQIaJWrVpSWysrKzF9+nQhhBBnz54VAMTNmzeFEEKMHTtWVKxYUWpbvnx5MX78eCGEEAEBAQKAuHjxohAi87xRpkwZqe2HOEfYe+0Xxb8eLKCtI/1uDOxrCCPnL4S9135hOzLz77xkx/HC3mu/KNF2pAAg7MbtEfZe+4WhU11h6FRX2HvtF3bjMvusRNuRwt5rvyjZcbwAIGxHbhP2XvuFkfMXwsC+htqcI4QQomLFimLs2LFCCCFu3rypdC6fPn26sLKykvqwVq1aYsiQIUIIIUJDQwt1jrD32i+KtxoqoND6r78dagmjSo0y+3vU9sz+bj8us7+/GZPZ32N2Zfa3GpwjRo0aJVxcXKR+sbe3FxMnThRCCHHlyhUBQFy5ckUIIcTEiROFvb291NbFxeW9zhGlv5ua2d/NBwqFrv5//W1bVRi7fJnZ3yM2Z/Z3p58y+7v1cAFAamtYro4wrNgg85gdsyvzmP1mTOYx235c5jE7anvmMVupkTBwqPVffyu0RPFWQzP723VSZn8P35jZ31WbC/0yLv/1t56hsGjmmdnf3WZo7DlCCNW/jsiip6cnlixZIoQQYv/+zOP98ePHQgghPD09Rf369aW2FhYWYs6cOUIIIU6cOCEAiPv37wshhEa9jvgY54g//vhDCCHEjh07BAARHR0thBCiV69eomnTplIfGhkZiYULFwohhPDz8xMAREREhBBCiIEDB4o6depIbUuWLClmzZolhBDi33//FQBEYGCgEEK89zli1KhRQgghAgMDBQDx77//CiGEmDVrlihZsqTUtk6dOmLgwIFCCCEiIiLU7nVEYc4RZQb7ZJ6Ta7UTepbl/ztmjS2EWZPemcds798yj9l+SzOP2bquQqd4mf+OWXNrYVq/S+Yx67E485jtMy/zmG3UQ2gXK/Hf67ZSDsKkdvvMc/LAVZnn5B6zMs/JX3oILYNi/x3fNpVEseotM4/voeszj9kuk3N8HfG+5whNeR3xoc8RJiYm0rHUqFEj4e7uLoQQ4unTpwKA2LNnjxDi/d5rfPvtt6Jt27bSY3mOyMT3Gpr9OiLr95v1eiI3CiH+X+r6BKWkpMDIyAjbt29Hp06dpO3u7u6IjY3Fnj17sj0mOTlZqnQCmdVPW1tbnD17Fg0aNACQWZk0MTGBra0tkpKScPv2bVSoUAEmJiZ48uQJoqKiUKNGDQCZlUkDAwPY29sjNTUVN27cQPny5WFmZoZnz57h4cOHqFWrFoDMyqSOjg4cHR2Rnp6OgIAAODo6wsLCAtHR0Xjw4AFq1aoFhUIhVSXLly8PIQSuXr0Ke3t7lChRAi9evEBoaChq1KgBbW1thIaGIi0tDV/7ZF51S3kSDG2TktA2MkNG8iukvoiEXikHKLR1kPbyKURaCnRLlM1s+zQE2sYW0Da2QEZyIlJfPIZeSTsodPSQFvcMGSmvoVfSLrPtszBoGZpCp1hxZKQkITXmIXRL2EJLVx9p8c+RkfQKeqXs/9/2AbT0jaFjWhIZqclIjY6AbvEy0NIzRFpCDDISX0KvtCMAIPV5BBR6+tAxLQ2RloqU5w+ga2EDLX0jpL96gfSEF9CzLJfZNvohFDq60DGzhEhPQ8qzMOiaWyF8QTc8e/YMERER+Oyzz6T+1tbWRrly5aT+dnBwQPHixRETE4OwsDDUrFkTWlpaKDPYBxAZ0LWwyTxOooKgY1oK2kZmSE9KQFpsFPRKO0KhpZ15FS8jHbrFy/y/v0OgXaw4tI3N/+vDUvZQaOsiLe4pRGoydEvY/r+/Q6FtZA7tYhbISHmN1JhHb/T3c2SkJCr3t4EJdExKICM1CanRD6Fboiy0dA2QFh+NjKR46JVyyGz7PBxaekbQMS0JkZaClOfhUn+nJ7xAemLsf/0dHQGF7v/7Oz0Vu3rYwcnJCaampnj69CkeP36MmjVrAsi8eqGrqwtHR0ekpaXh+vXr0jH7/PlzhIeHS/0dFBQELS0tlCtXDhkZGbh27Vq2/s46ZkNCQpCeno4KFSoAyLx6YWtri1KlSiE2NhYhISGoVq0adHV1ERYWhuTkZFSqVAlA5tULa2trWFpaIi4uDkFBQahSpQr09fURHh6OV69ewdnZGUDm1YtSpUrB2toaCQkJuHfvHpydnWFoaIiHDx/i5cuXqFKlCoDMqxfm5uYoU6YMXr9+jTt37qBSpUowNjZGZGQknj9/jmrVqn2wc0SNX04jPfEl0uOfQ8+yfObvJuYRoKUNXXMriIx0pDwNhY65FbQNiiH9dRzSXj6FnmV5KBQKaQSEroU1hBBIeRIMHbPS0DY0zccxK+85Imx2O9y6dQtmZmYoW7as1N8VK1ZEsWLFEBkZiWfPnqF69eoAMq9wGhsbw87ODsnJyXAYtKLA5wgtg2JIT3yJtLhn0Ldyyr2/zSyhbWiC9NfxSHv5BHqW5aBQaGX2oczniNPDaiAuLg4uLi4AMkdKFS9eHDY2NkhMTERgYCAqV64MIyMjPH78GDExMahatap0zLZccqlQ54iUZ2+ek2ORnhDzX3/ndcy+3d8vHgMKrcy2IgMpT0Ky93cuffhmf2ckJSA1NuqNY/YJRFrqf8fskxBoF1M+ZsNWDta4c4QcryOyzslXr15F2bJlUapUKbx8+RLBwcHSOfnBgwdISkqSzskBAQGwsrKCpaUl4uPjcf/+fbi4uMDAwABlh/hqzOuID32O2NnVGnZ2dihZsqTU39WrV4eOjg5CQ0ORmpqKihUrSs9rNjY2KF26tPS8VrVqVejp6SE8PByJiYmoXLmydMyWLl0aVlZW0jGb1d8PHz58r3OEqakpypYtKx2zWefkqKgoPH36VDonBwYGwsjICHZ2dkhJScHNmzfV6nWE3citBT5H6JW0h0Ln/+fklGTolvzvnKxlZPb/YzbznCwds3HPkZH81jFrYAwdkzeP2bLQ0jPIPGZfx731us0QOqal/jsnv3nMvnoBvdJvHrN60DEr/d8xa2ENLX3jbK8jjnhWLPQ5wsZjkca8jvjQ54h9nlWlY/bu3bvQ19eHg4ODdE4uV64czM3N3+u9RkhICDIyMuDk5CQdszxH8L2Gpr+OcHR0RPHixfHy5UuYmpoiN590UQoA6tWrh7p162Lx4sUAMofy2dnZYdiwYRg/fvw7Hx8XFwczM7N3dqQmcBh/QO4Isgmb3e69Hs++I1XjMUeqxmOOVI3HHMmBx13hsN+IqKDyW0vRUWEmWYwePRru7u6oU6cO6tatiwULFuDVq1fw8PCQO5rK8YRKREREREREROriky9KdeuWeduWt7c3oqKiULNmTfj5+WWb/JyIiIiIiIiIiFTnky9KAcCwYcMwbNgwuWMQEREREREREdH/ackdgIiIiIiIiIiIih4WpYiIiIiIiIiISOVYlCIiIiIiIiIiIpVjUYqIiIiIiIiIiFSORSkiIiIiIiIiIlI5FqWIiIiIiIiIiEjlWJQiIiIiIiIiIiKVY1GKiIiIiIiIiIhUjkUpIiIiIiIiIiJSORaliIiIiIiIiIhI5ViUIiIiIiIiIiIildOROwAREWUXNrud3BGIiIiIAPB1CRF9PBwpRUREREREREREKseRUkREREREVCRwxA8RkXrhSCkiIiIiIiIiIlI5FqWIiIiIiIiIiEjlWJQiIiIiIiIiIiKVY1GKiIiIiIiIiIhUjkUpIiIiIiIiIiJSORaliIiIiIiIiIhI5ViUIiIiIiIiIiIildOROwCRJgib3U7uCERERERERESfFI6UIiIiIiIiIiIilWNRioiIiIiIiIiIVI5FKSIiIiIiIiIiUjkWpYiIiIiIiIiISOXeuyjVt29fKBQKpY/WrVsrtYmJiUGvXr1gamoKc3NzeHp6IiEhIc+vm5SUhKFDh6JEiRIoVqwYOnfujCdPnii1CQ8PR7t27WBkZITSpUtj3LhxSEtLU2rzzz//4LPPPoO+vj6cnJzg6+v7vj8yERERERERERG9pw8yUqp169aIjIyUPjZv3qy0v1evXrh16xaOHDmC/fv349SpUxg4cGCeX3PUqFHYt28f/vrrL5w8eRKPHz+Gq6urtD89PR3t2rVDSkoKzp49i3Xr1sHX1xfe3t5Sm9DQULRr1w7NmjXDtWvXMHLkSPTv3x9///33h/ixiYiIiIiIiIiokHQ+xBfR19eHlZVVjvvu3LkDPz8/XLp0CXXq1AEALF68GG3btsXvv/8OGxubbI95+fIlfHx8sGnTJnz11VcAgLVr18LZ2Rnnz59H/fr1cfjwYdy+fRtHjx6FpaUlatasienTp8PLywtTpkyBnp4eVqxYAUdHR8ydOxcA4OzsjNOnT2P+/Plo1arVh/jRiYiIiIiIiIioED7ISKl//vkHpUuXRqVKlfD9998jOjpa2nfu3DmYm5tLBSkAaNGiBbS0tHDhwoUcv96VK1eQmpqKFi1aSNsqV64MOzs7nDt3Tvq61apVg6WlpdSmVatWiIuLw61bt6Q2b36NrDZZXyMnycnJiIuLU/ogIiIiIiIiIqIP671HSrVu3Rqurq5wdHREcHAwfvrpJ7Rp0wbnzp2DtrY2oqKiULp0aeVvqqOD4sWLIyoqKsevGRUVBT09PZibmyttt7S0lB4TFRWlVJDK2p+1L682cXFxeP36NQwNDbN9719++QVTp07NfwcQERF9AsJmt5M7AhEREREVMQUaKbVx40YUK1ZM+vj333/RvXt3dOjQAdWqVUOnTp2wf/9+XLp0Cf/8889HivxxTZgwAS9fvpQ+IiIi5I5ERERERERERPTJKdBIqQ4dOqBevXrS52XKlMnWply5cihZsiSCgoLQvHlzWFlZ4enTp0pt0tLSEBMTk+s8VFZWVkhJSUFsbKzSaKknT55Ij7GyssLFixeVHpe1Ot+bbd5ese/JkycwNTXNcZQUkDk/lr6+fo77iIiIiIiIiIjowyjQSCkTExM4OTlJHzkVdh4+fIjo6GhYW1sDABo0aIDY2FhcuXJFanP8+HFkZGQoFbjeVLt2bejq6uLYsWPStrt37yI8PBwNGjSQvu6NGzeUCl5HjhyBqakpXFxcpDZvfo2sNllfg4iIiIiIiIiI5PFeE50nJCRg3LhxOH/+PMLCwnDs2DF07NgRTk5O0up2zs7OaN26NQYMGICLFy/izJkzGDZsGLp3757jynsAYGZmBk9PT4wePRonTpzAlStX4OHhgQYNGqB+/foAgJYtW8LFxQVubm4ICAjA33//jZ9//hlDhw6VRjoNHjwYISEh+PHHHxEYGIhly5Zh27ZtGDVq1Pv82ERERERERERE9J7eqyilra2N69evo0OHDqhYsSI8PT1Ru3Zt/Pvvv0q3wG3cuBGVK1dG8+bN0bZtWzRu3BirVq1S+loKhQK+vr7S5/Pnz8c333yDzp0744svvoCVlRV27typ9L33798PbW1tNGjQAL1790afPn0wbdo0qY2joyMOHDiAI0eOoEaNGpg7dy5Wr14tFcyIiIiIiIiIiEgeCiGEkDtEaGgoKlasiNu3b6NChQpyx1ESFxcHMzMzvHz5EqampnLHISIiIvokOIw/IHcE2XC1SyIi+tTlt5byXiOlPpSDBw9i4MCBaleQIiIiIiIiIiKij6NAq+99LEOHDpU7AhERERERERERqZBajJQiIiIiIiIiIqKihUUpIiIiIiIiIiJSORaliIiIiIiIiIhI5ViUIiIiIiIiIiIilWNRioiIiIiIiIiIVI5FKSIiIiIiIiIiUjkWpYiIiIiIiIiISOV05A5AREREREVP2Ox2ckcgIiIimXGkFBERERERERERqRyLUkREREREREREpHIsShERERERERERkcqxKEVERERERERERCrHic7fQQgBAIiLi5M5CRERERERERGR+suqoWTVVHLDotQ7xMfHAwBsbW1lTkJEREREREREpDni4+NhZmaW636FeFfZqojLyMjA48ePYWJiAoVCIXccjRUXFwdbW1tERETA1NRU7jgag/1WeOy7wmG/FR77rvDYd4XDfis89l3hse8Kh/1WeOy7wmG/FR777sMQQiA+Ph42NjbQ0sp95iiOlHoHLS0tlC1bVu4YnwxTU1P+YRcC+63w2HeFw34rPPZd4bHvCof9Vnjsu8Jj3xUO+63w2HeFw34rPPbd+8trhFQWTnROREREREREREQqx6IUERERERERERGpHItSpBL6+vqYPHky9PX15Y6iUdhvhce+Kxz2W+Gx7wqPfVc47LfCY98VHvuucNhvhce+Kxz2W+Gx71SLE50TEREREREREZHKcaQUERERERERERGpHItSRERERERERESkcixKERERERERERGRyrEoRUT0iVq2bJncEYiIiIiIiHLFic6JiD5RxYsXx+eff461a9fCxsZG7jga5dSpU/lq98UXX3zkJEREREREny4WpajAHB0doVAo8myjUCgQHBysokSa5dWrV/j111+xc+dOhIWFQaFQwNHREV26dMHYsWNhZGQkd0S1JoTAlStXlPquVq1a7zwmi6LHjx9jwIABOHfuHBYtWoTevXvLHUljaGnlPpA461hTKBRIS0tTVSSNExcXl+N2hUIBfX196OnpqTiR5ti7d2+O2xUKBQwMDODk5ARHR0cVpyIiInWUlJQEAwMDuWNolJSUFISGhqJ8+fLQ0dGRO06Rx6IUFdjChQtz3RcWFoaVK1ciOTkZ6enpKkylGVJSUtCwYUPcvHkTbdq0QeXKlSGEwJ07d+Dn54fPPvsMp06dgq6urtxR1dKJEyfg6emJBw8eIOvUlVWYWrNmDUet5MLX1xejR49Gs2bNMHHixGxPvtWrV5cpmfp6+fJljtsTExOxcOFCLFq0COXKlcPNmzdVnExzaGlp5VksLlu2LPr27YvJkyfnWQQsirL67u2XaFnbFAoFGjdujN27d8PCwkKmlOqJxdDC+/bbb3P8m32zGNqzZ09UqlRJhnTq7d9//8XKlSsRHByM7du3o0yZMtiwYQMcHR3RuHFjueOpNfZd4WRkZGDmzJlYsWIFnjx5gnv37qFcuXKYNGkSHBwc4OnpKXdEtZSYmIjhw4dj3bp1ACD12/Dhw1GmTBmMHz9e5oRFlCD6AKKjo8XIkSOFvr6++OKLL8S5c+fkjqSWFixYICwtLUVgYGC2fXfu3BGWlpZi0aJFMiRTf/fv3xdGRkaiWbNmYvfu3SIwMFDcuXNH7NixQzRt2lQYGxuL4OBguWOqrSNHjghtbW2hpaUlFAqF0r/0bunp6eKPP/4QZcuWFXZ2dmLNmjUiPT1d7lhqbd26daJs2bLi559/Fnv37hV79+4VP//8s7C1tRUrV64UM2bMEObm5mLmzJlyR1U7R48eFfXq1RNHjx4VcXFxIi4uThw9elQ0aNBAHDhwQJw+fVpUqVJF9OvXT+6oaifrvJbbh52dnfD29ubfbw7c3d2FmZmZsLe3F66ursLV1VU4ODgIc3Nz0bVrV1GpUiWhr68vTp8+LXdUtbJ9+3ZhaGgo+vfvL/T19aXXIosXLxZt2rSROZ16Y98V3tSpU0W5cuXEn3/+KQwNDaW+27Jli6hfv77M6dTXiBEjRO3atcW///6r9N5h9+7dombNmjKnK7pYlKL3kpiYKL2xqFGjhjhw4IDckdTaF198IZYsWZLr/kWLFokvvvhChYk0x9ChQ8VXX32V476MjAzx1VdfiWHDhqk4lWaYO3euMDIyEu7u7iIoKEiEhYUpfVDeduzYISpVqiSKFy8ufvvtN5GUlCR3JI3w1Vdfia1bt2bbvnXrVulvef369aJSpUqqjqb2qlSpIs6cOZNt++nTp4WLi4sQIrPQbGtrq+poao/F0MLz8vIS33//vVLBLj09XQwbNkxMmDBBZGRkiIEDB4pGjRrJmFL91KxZU6xbt04IIUSxYsWkN7n+/v7C0tJSzmhqj31XeOXLlxdHjx4VQij33Z07d4S5ubmc0dSanZ2dNHjizX67f/++MDExkTNakcaiFBVKWlqaWL58ubCyshIODg5i/fr1IiMjQ+5Yaq9kyZLi5s2bue6/ceOGKFmypAoTaY4qVaqIvXv35rp/7969okqVKipMpP6Cg4NF48aNhaWlpdi9e7fccTTOP//8I+rVqyeMjIzEhAkTRGxsrNyRNIqBgYG4d+9etu337t0ThoaGQgghQkJCpP/TfwwMDMSNGzeybb9+/bowMDAQQggRFhbGvssBi6GFV7JkSXH37t1s2+/evStKlCghhMg8Bs3MzFScTL0ZGhqK0NBQIYTym9zg4GChr68vYzL1x74rPAMDA+nC4pt9d+vWLWFsbCxnNLX25qiyN/vt2rVrwtTUVM5oRRoncaAC27ZtG5ydneHt7Y3x48fj7t27cHNz40TT+RAbG4sSJUrkur9EiRK5zmVT1IWHh6NatWq57q9atSoePHigwkTqr3r16rC0tMTNmzfRsWPHHNtwTqSctW3bFl9//TVq1qyJ4OBgzJo1C2ZmZnLH0ii2trbw8fHJtt3Hxwe2trYAgOjoaM6JlIPatWtj3LhxePbsmbTt2bNn+PHHH/H5558DAO7fvy/1I/3n7NmzqFWrVrbttWrVwrlz5wAAjRs3Rnh4uKqjqb20tDQEBgZm2x4YGCjNE2pgYMDXe2+xsrJCUFBQtu2nT59GuXLlZEikOdh3hefi4oJ///032/bt27fneA6kTHXq1MGBAwekz7POZ6tXr0aDBg3kilXkcap5KrDu3bvD0NAQPXr0wIMHD3KdEG7evHkqTqb+MjIyoK2tnet+LS0tThCfi4SEhDxXJjQyMkJiYqIKE6m/FStW5LjiXnx8PDZv3ozVq1fjypUrPOZy4OfnBx0dHWzduhXbtm3LtV1MTIwKU2mW33//Hd999x0OHTokFVIuX76MwMBAbN++HQBw6dIldOvWTc6YasnHxwcdO3ZE2bJlpcJTREQEypUrhz179gDIPCf+/PPPcsZUS1nF0NmzZyttZzH03dzc3ODp6YmffvpJ+pu9dOkSZs2ahT59+gAATp48iSpVqsgZU+0MGDAAP/zwA9asWQOFQoHHjx/j3LlzGDt2LCZNmiR3PLXGvis8b29vuLu749GjR8jIyMDOnTtx9+5drF+/Hvv375c7ntqaNWsW2rRpg9u3byMtLQ0LFy7E7du3cfbsWZw8eVLueEUWV9+jAvvyyy/zdZXsxIkTKkijWbS0tFC1atVclx5NS0vDrVu3WCTIgZaWFo4fP47ixYvnuP/58+f4+uuv2Xd5OHXqFHx8fLBjxw7Y2NjA1dUVnTt3lt580H+yVmV5F3d394+cRLOFhoZi5cqVuHfvHgCgUqVKGDRoEBwcHOQNpgEyMjJw+PBhpb77+uuvuVLhO+zduxffffcdKleunGMx9JtvvsHy5ctx//59Xjx7S3p6OmbPno0lS5bgyZMnAABLS0sMHz4cXl5e0NbWRnh4OLS0tFC2bFmZ06oPIQRmzZqFX375Rbo4pq+vj7Fjx2L69Okyp1Nv7Lv38++//2LatGkICAhAQkICPvvsM3h7e6Nly5ZyR1NrwcHBmD17tlK/eXl55XlHBn1cLEoRqdDUqVPz1W7y5MkfOYnmyW2JdEB5mXQWpZRFRUXB19cXPj4+iIuLQ9euXbFixQoEBATAxcVF7ngaLT09Pc+Rj0QkDxZD319cXBwAwNTUVOYkmiMlJQVBQUFISEiAi4sLihUrJnckjcG+IyraWJSiD+7OnTvw8fHB77//LncU+oTkd74oe3v7j5xEc7Rv3x6nTp1Cu3bt0KtXL7Ru3Rra2trQ1dVlUeo93Lt3Dz4+Pli/fj0iIyPljqPWYmNj4ePjgzt37gAAqlSpgn79+nF+rnw4efIkfv/9d6nvXFxcMG7cODRp0kTmZPSpe/bsGe7evQsAqFy5MkqWLClzIiKiD+vp06d4+vQpMjIylLZXr15dpkRFG4tS9EG8evUKW7ZsgY+PD86fPw8XFxdOoEwkMx0dHYwYMQLff/89KlSoIG1nUargEhMTsXXrVqxZswbnzp1DnTp10LlzZ4wbN07uaGrr8uXLaNWqFQwNDVG3bl0AmfPTvH79GocPH8Znn30mc0L19eeff8LDwwOurq5o1KgRgMyJf3fv3g1fX1/07NlT5oTqjcXQwnn16hWGDx+O9evXS2/UtLW10adPHyxevDjPeR2LGldX13y33blz50dMonnYdx+GhYVFjtOpKBQKGBgYwMnJCX379oWHh4cM6dTXlStX4O7ujjt37mS7+4J3XMiHRSl6L2fOnIGPjw+2bduG169fY9SoUejfvz8qV64sdzS11KxZs3fOx6VQKHDs2DEVJdIc+V0pyc7O7iMn0Rznz5+Hj48Ptm7dCmdnZ7i5uaF79+6wtrZmUSqfzp8/j9WrV+Ovv/6CnZ0d7ty5gxMnTnC0Sj40adIETk5O+OOPP6R59NLS0tC/f3+EhITg1KlTMidUX87Ozhg4cCBGjRqltH3evHn4448/pGILZcdiaOENGjQIR48exZIlS5SKoSNGjMDXX3+N5cuXy5xQfbz5Rl8IgV27dsHMzAx16tQBkPnGNzY2Fq6urli7dq1cMdUS++7DmD9/PmbOnIk2bdpI57qLFy/Cz88Po0aNQmhoKDZs2IDFixdjwIABMqdVHzVq1ED58uXh5eUFS0vLbO/LeMeFPFiUogJ7+vQpfH19sWbNGrx8+RI9evRAz5490aBBA77RfYe332C8KT4+Hps2bUJycjKr9DnImlPqbVlzSQGZBb20tDRVR1N7r169kkb5XLx4Eenp6Zg3bx769esHExMTueOppblz5yqd43r37o0aNWpwlFkBGBoa4urVq9kuUty+fRt16tThapl50NfXx61bt+Dk5KS0PSgoCFWrVkVSUpJMydQfi6GFV7JkSWzfvh1ffvml0vYTJ06ga9euePbsmTzB1JyXlxdiYmKwYsUKaZ7B9PR0DBkyBKampvjtt99kTqi+2HeF17lzZ3z99dcYPHiw0vaVK1fi8OHD2LFjBxYvXoxVq1bhxo0bMqVUPyYmJrh69Wq251eSF4tSVGCGhobo0qULevfurbQSEN+sFU5aWhqWLl2KmTNnwszMDNOnT0f37t3ljqV2AgICctwuhMCWLVuwaNEiFCtWDE+fPlVxMs1y9+5d+Pj4YMOGDYiNjcXXX3+NvXv3yh1L7ejo6MDLywvTpk1Tmsyc57n8s7S0xIYNG7KtAvT333+jT58+0upelJ2TkxPGjRuHQYMGKW1fsWIF5s6di/v378uUTP2xGFp4RkZGuHLlCpydnZW237p1C3Xr1sWrV69kSqbeSpUqhdOnT6NSpUpK2+/evYuGDRsiOjpapmTqj31XeMWKFcO1a9dyvHhRs2ZNJCQkIDg4GNWrV+ff7hs6deoENzc3dO7cWe4o9Iac16UnyoO9vT1Onz4NOzs72Nvb81a997Bx40Z4e3vj9evXmDJlCgYOHChd2SVlNWrUyLbt6NGjGD9+PO7du4cff/wRY8aMkSGZZqlUqRLmzJmDX375Bfv27cOaNWvkjqSWpk+fjrVr12LDhg3o0aMH3NzcULVqVbljaZRu3brB09MTv//+Oxo2bAgg85bvcePGoUePHjKnU29jxozBiBEjcO3aNaW+8/X1xcKFC2VOp95MTU0RHh6e7bVJREQER4a+Q4MGDTB58mSsX78eBgYGAIDXr19j6tSpaNCggczp1FdaWhoCAwOzFVYCAwOzTaJMyth3hVe8eHHs27cv210Y+/btQ/HixQFkjpTneU/Z6tWr4e7ujps3b6Jq1arQ1dVV2t+hQweZkhVtfPdLBRYYGCjNJfX555+jYsWK6N27NwC8c74kyuTn54fx48cjNDQUY8eOxejRo2FsbCx3LI3h7+8PLy8v/Pvvv+jfvz8OHjyI0qVLyx1Lo2hra6NTp07o1KmT3FHU0oQJEzBhwgScPHkSa9asQb169eDk5AQhBF68eCF3PI3w+++/Q6FQoE+fPtJttbq6uvj+++8xe/ZsmdOpt++//x5WVlaYO3cutm3bBiBznqmtW7eiY8eOMqdTbyyGFt7ChQvRqlUrlC1bVroQFBAQAAMDA/z9998yp1NfHh4e8PT0RHBwsDS3z4ULFzB79mxOMv0O7LvCmzRpEr7//nucOHFCaf68gwcPYsWKFQCAI0eOoGnTpnLGVDvnzp3DmTNncOjQoWz7ONG5fHj7Hr2XhIQEbN68GWvXrsX58+fRtGlT9OzZE506dUKpUqXkjqd2Ll68CC8vL5w/fx6DBw/GxIkTudRyAQQHB+Onn37Cjh070LVrV8yYMQPlypWTO5ZaO3HiBPz9/VG/fn00atQIK1euxMyZM/H69Wt06tQJixYtgqGhodwx1V7WnG9r1qzBlStXULduXXTp0gWjR4+WO5raS0xMRHBwMACgfPnyXMGLPqqUlBSMGzcOK1asyLEYqq+vL3NC9ZaYmIiNGzciMDAQQGYxtFevXnyeyENGRgZ+//13LFy4EJGRkQAAa2tr/PDDDxgzZozSLeCkjH33fs6cOYMlS5bg7t27ADJHww8fPlwqyFN2Dg4O+OabbzBp0iRYWlrKHYf+j0Up+mDu3LkjzVUTExOD1NRUuSOpHS0tLRgaGmLgwIFwdHTMtd2IESNUmEozDBkyBD4+PmjWrBlmz56NmjVryh1J7f3xxx/4/vvv4ejoiIiICEyePBkzZ86Em5sbtLS08Oeff3LUSiHcuHEDPj4+2LhxIyf+JVJTLIaSHOLi4gBk3kZKBcO+I1UwMTHBtWvXUL58ebmj0BtYlKIPLi0tDXv37oWrq6vcUdSOg4PDO29xVCgUCAkJUVEizaGlpQUDA4N3zmHm7++vokTqr2rVqhg0aBCGDx8OPz8/tG/fXrqXHgD++usvTJgwAUFBQTIn1UypqanZ5iIo6gpy3t+5c+dHTKJ5LCws8n0LfExMzEdOQ0VFQRa64FwrROopKSkJKSkpSttY3MuZu7s7mjRpgv79+8sdhd7AOaWowLZt24ZOnTpBT08PAPDw4UPY2NhIq/ClpKTwTW4uwsLC5I6gsSZPnix3BI0TEhIivYlo3bo1FAqFNO8AANSrVw8RERFyxVNrbdu2xebNm2FmZgYAmD17NgYPHgxzc3MAQHR0NJo0aYLbt2/LmFL9ZPUXFdyCBQvkjqCxWAwtvPzOK8i5VnLn6OiYZ0GZFxpzx74rvMTERPz444/Ytm1bjqsU8u81ZxUrVsSECRNw+vRpVKtWLdvFRd6tIg+OlKIC09bWRmRkpDSxtKmpKa5duybN7fPkyRPY2NjwZFgIsbGx+PPPPzFs2DC5o9AnQEtLC1FRUdLfqomJCQICAvi3mg88z6nOmTNnUKdOHc71UwhvF0uLqoJMiLx27dqPmISKordXxExNTcXVq1fh5+eHcePGYfz48TIlU3/su8IbOnQoTpw4genTp8PNzQ1Lly7Fo0ePsHLlSsyePRu9evWSO6Jaymv6FN6tIh+OlKICe7uOybrm+zt27Bh8fHywa9cuGBkZsShVQHFxcdi4cSN8fHxw+fJlueOoDYVCgfj4eBgYGEAIAYVCgYSEBGnehqx/KTue51SnTZs2SgU/yr9Zs2aha9euRb4oVZhCE4uhhVetWjUcPHgQtra2ckdRCz/88EOO25cuXcrXJO/Aviu8ffv2Yf369fjyyy/h4eGBJk2awMnJCfb29ti4cSOLUrkIDQ2VOwLlQEvuAERFVUREBKZNmwZHR0e0bNkSCoUCu3btQlRUlNzRNMaJEyfg5uYGa2trTJ8+HfXq1ZM7kloRQqBixYqwsLBA8eLFkZCQgFq1asHCwgIWFhaoVKmS3BGJWPB7D+y7wmvTpg0ePXokdwyNFBYWxsVs8qFNmzbYsWOH3DE0Evvu3WJiYqSLOaamptJcg40bN8apU6fkjKYxhBB8HlUTHClFpEKpqanYvXs3Vq9ejX///RetW7fGb7/9hh49emDixIlwcXGRO6Lae/ToEXx9fbF27VrExsbixYsX2LRpE7p27ZrvSYKLihMnTsgdQWMpFIpsxxOPL6JPB9+I0Me2fft2FC9eXO4YGol9927lypVDaGgo7OzsULlyZWzbtg1169bFvn37ivzo2XdZv349fvvtN9y/fx9A5jxT48aNg5ubm8zJii4WpahQ/v77b2lC24yMDBw7dgw3b94EkDkvEuWsTJkyqFy5Mnr37o0tW7bAwsICANCjRw+Zk6m/HTt2wMfHB6dOnUKbNm0wd+5ctGnTBsbGxqhWrRoLBjlo2rSp3BE0lhACffv2lW7tSUpKwuDBg2FsbAwASE5OljMeERGpiVq1aim9BhFCICoqCs+ePcOyZctkTKb+2HeF5+HhgYCAADRt2hTjx49H+/btsWTJEqSmpmLevHlyx1Nb8+bNw6RJkzBs2DA0atQIAHD69GkMHjwYz58/x6hRo2ROWDSxKEWFkrWkfJZBgwYpfc4CQc7S0tKkERja2tpyx9Eo3bp1g5eXF7Zu3QoTExO549Anrk+fPkrnsd69e+fYhoiIiraOHTsqPV9oaWmhVKlS+PLLL1G5cmUZk6k/9l3hvVk8adGiBQIDA3HlyhU4OTmhevXqMiZTb4sXL8by5cuVXsN16NABVapUwZQpU1iUkgmLUlRgGRkZckfQWI8fP5ZG/Pzwww9o06YNevfuzSJePnh6emLp0qX4559/4Obmhm7dukkjzYg+NF9fX7kjFBk8/xGRJpsyZYrcETQW++7Dsbe3h729fbbtXJhAWWRkJBo2bJhte8OGDREZGSlDIgI40TmRShkYGKBXr144fvw4bty4AWdnZ4wYMQJpaWmYOXMmjhw5wiXmc7Fy5UpERkZi4MCB2Lx5M6ytrdGxY0cIIVgopQ8uPT0d169fx+vXr7PtS0xMxPXr13ncfSCc26fwmjRpAkNDQ7ljaCQWQ+lD0dbWxtOnT7Ntj46O5qj4d2DffXxcmECZk5MTtm3blm371q1bUaFCBRkSEcCiFBXClStX0KxZsxyXk3/58iWaNWuGgIAAGZJplvLly2PGjBl48OABDhw4gOTkZHzzzTcoXbq03NHUlqGhIdzd3XHy5EncuHEDVapUgaWlJRo1aoSePXti586dckekT8SGDRvQr18/6OnpZdunp6eHfv36YdOmTTIk0xyvX79GYmKi9PmDBw+wYMECHD58WKldfHy8tIIQZfL398eNGzekz/fs2YNOnTrhp59+QkpKirT94MGDsLa2liOixmMxNH9ymid05cqVsLS0VH0YNZXbsZScnJzjcwj9h31HqjZ16lR4e3ujdevWmD59OqZPn47WrVtj6tSpmDZtmtzxiiyF4LMyFVDPnj3h7OyMSZMm5bh/1qxZuH37Nv78808VJ9N8z549w4YNGzB69Gi5o2iMjIwMHDhwAD4+Pjh06BAnoC6g7du3o0uXLnLHUDtNmjTB0KFD0b179xz3b9u2DUuWLOGyy3lo2bIlXF1dMXjwYMTGxqJy5crQ1dXF8+fPMW/ePHz//fdyR1Rbn3/+OcaPH4/OnTsjJCQEVapUwbfffotLly6hXbt2WLBggdwR6RP066+/wsHBAd26dQMAdO3aFTt27ICVlRUOHjyIGjVqyJxQvSxatAhA5tw+06dPR7FixaR96enpOHXqFMLCwnD16lW5Iqot9p3qmJiYICAggBd/3nDlyhXMnz8fd+7cAQA4OztjzJgxqFWrlszJii4WpajAypcvj127duU6id6NGzfQsWNHhISEqDiZ5gsJCcHgwYOzjSSgd0tLS8Pjx49hZ2cndxS1kpaWhsDAQOjp6aFixYrS9j179sDb2xuBgYEs5OWgdOnSuHjxIhwcHHLcHxoairp16+LZs2eqDaZBSpYsiZMnT6JKlSpYvXo1Fi9ejKtXr2LHjh3w9vaWXgxSdmZmZvD390f58uXx66+/4vjx4/j7779x5swZdO/eHREREXJHVFtPnjzB2LFjcezYMTx9+jTbSAzeIp87R0dHbNy4EQ0bNsSRI0fQtWtXbN26Fdu2bUN4eDhfm7zF0dERQOYo0LJlyyrdbqanpwcHBwdMmzYN9erVkyui2mLfqQ6LUqQJONE5FdijR4/yXP2sWLFinCiukOLj43Hs2DG5Y2ikW7du4bPPPuMbjjfcvHkT33zzjfQGtmPHjli+fDm6du2KmzdvYsCAAThw4IDMKdXTq1evcrxFOUt8fLzSrWmUXWJiovRccfjwYbi6ukJLSwv169fHgwcPZE6n3t6cK+/o0aP45ptvAAC2trZ4/vy5nNHUXt++fREeHo5JkybB2tqac0cVQFRUlDQZ8v79+9G1a1e0bNkSDg4OLA7kIDQ0FADQrFkz7Ny5k4uvFAD7juRy8OBBaGtro1WrVkrb//77b2RkZKBNmzYyJSvaWJSiAitVqhTu3r0rXeV4W2BgIEqWLKniVEScI+RtXl5ecHJywpIlS7B582Zs3rwZd+7cgaenJ/z8/DhBch4qVKiAs2fP5joi9PTp05wQ8x2cnJywe/dufPvtt/j777+lZZafPn0KU1NTmdOptzp16mDGjBlo0aIFTp48ieXLlwPIfCPHuXzydvr0afz777+oWbOm3FE0joWFBSIiImBraws/Pz/MmDEDQOZzKy/45O7EiRNyR9BY7DtStfHjx2P27NnZtgshMH78eBalZMKiFBVYixYtMHPmTLRu3TrbPiEEZs6ciRYtWsiQjIo6XhFXdunSJRw+fBg1a9ZEkyZNsHnzZvz0009wc3OTO5ra69mzJ37++Wc0bNgwW2EqICAA3t7e+PHHH2VKpxm8vb3Rs2dPjBo1Cs2bN0eDBg0AZI6a4rwNeVuwYAF69eqF3bt3Y+LEiXBycgKQOQdcTktZ039sbW15gaKQXF1d0bNnT1SoUAHR0dHSm7OrV69KxyBlGj16NKZPnw5jY+N3zgM6b948FaXSDOw71eLCBMru378PFxeXbNsrV66MoKAgGRIRwKIUFcLPP/+M2rVro169ehgzZgwqVaoEIHOE1Ny5c3Hv3j34+vrKG5KI8Pz5c9jY2ADInKPG2NgY9evXlzmVZhg1ahQOHTqE2rVro0WLFqhcuTKAzPPc0aNH0ahRI2nkD+WsS5cuaNy4MSIjI5UmSG7evDm+/fZbGZOpv+rVqyutvpflt99+4zLp77BgwQKMHz8eK1euzHVOOMrZ/Pnz4eDggIiICMyZM0eafDoyMhJDhgyROZ16uXr1KlJTU6X/54YXy7J7s+/8/f3ZR+/h2LFj0vx5Wbd8Z1mzZg2AzIts9B8zMzOEhIRke34ICgqCsbGxPKGIE51T4Vy+fBl9+/bF7du3pScTIQRcXFywdu1afP755zInVE+1atXK88k3MTER9+/f5zD5HFy/fj3P/YGBgejRowf77g3a2tq4d+8eSpUqBSEEbG1tcfr06WxPxLyVKmepqamYP38+Nm3ahPv370MIgYoVK6Jnz54YOXIkl6smlUhISMj2ZoN/s7mzsLBAYmIi0tLSYGRkBF1dXaX9MTExMiUjIvpwpk6dimnTpqFOnTo5zp+3a9cumZKpt0GDBuHcuXPYtWsXypcvDyCzINW5c2d8/vnnWL16tcwJiyYWpei9XL16FUFBQdKbNc7hkLepU6fmq93kyZM/chLNo6WlBYVCkeNtGVnbFQoFi1JvyOqzLFl99Pbn7DP6GJKSkrB48WKcOHEix6u4/v7+MiVTf6GhoRg2bBj++ecfJCUlSdv5N/tu69aty3O/u7u7ipJohr179+a7bYcOHT5iEiqK+vXrh4ULF2ZbQOnVq1cYPny4NNqHsrO2tsacOXM4JUMBvXz5Eq1bt8bly5dRtmxZAMDDhw/RpEkT7Ny5E+bm5vIGLKJYlKL3lrUSECc3p48pv6t12dvbf+QkmuPkyZP5ate0adOPnERzvX79GkeOHMG9e/cAAJUqVUKLFi04SXw+9OrVC4cPH0aXLl1gaWmZ7Soui++5a9SoEYQQ+OGHH3LsO/7N0oeipaWl9PnbF3/ePPZYDM3Zt99+m+MoeIVCAQMDAzg5OaFnz57SdBf0H21tbURGRqJ06dJK258/fw4rKyukpaXJlEz9lShRAhcvXpRG+1D+CSFw5MgRBAQEwNDQENWrV8cXX3whd6wijUUpKpTY2FhMnDgRW7duxYsXLwBkDpnv3r07ZsyYwSozkYaIiYlB8eLF5Y6hlvbu3Yv+/ftLhfcsJUuWhI+PD9q3by9TMs1gZmaGgwcPolGjRnJH0TjFihXDlStX+Ca2kNLT07F7927cuXMHAFClShV06NCB83G9w9GjR+Hl5YVZs2ZJCxOcO3cOP//8M2bNmoWvv/5a5oTqqW/fvti9ezfMzc1Ru3ZtAJkjQWNjY9GyZUsEBAQgLCwMx44d4/nw/+Li4iCEgIWFBe7fv49SpUpJ+9LT07Fv3z6MHz8ejx8/ljGlevPy8kKxYsUwadIkuaMQvTdOdE4FFhMTgwYNGuDRo0fo1asXnJ2dAQC3b9+Gr68vjh07hrNnz8LCwkLmpOqnWbNm75zQUaFQ4NixYypKpDmeP3+OV69eKY2EunXrFn7//Xe8evUKnTp14mSOBXD48GGsXr0a+/btw+vXr+WOo3bOnj2LLl26oEOHDhgzZozSeW7u3Lno0qULTp48yYnj81CmTJlst2RQ/nz++eeIiIhgUaoQgoKC0LZtWzx69Ejqv19++QW2trY4cOAARxXkYeTIkVixYgUaN24sbWvVqhWMjIwwcOBAqchHyqysrNCzZ08sWbJEGnmWkZGBH374ASYmJtiyZQsGDx4MLy8vnD59Wua06sHc3BwKhQIKhQIVK1bMtl+hUOR7youiKikpCatWrcLRo0dRvXr1bPPnceXC3OVngnhSLY6UogIbOXIkjh07hqNHj2ZbYjQqKgotW7ZE8+bNMX/+fJkSqq+8VuuKj4/Hpk2bkJyczCHyOejRowdsbGwwd+5cAMDTp09RuXJl2NjYoHz58jh06BB8fHx4b30eHjx4gDVr1mDdunV48eIF2rRpg86dO+O7776TO5raadu2LWxtbbFy5coc9w8aNAgRERE4ePCgipNpjkOHDmHRokVYsWIFb6stoODgYAwePBi9e/dG1apVs73ZqF69ukzJ1F/btm0hhMDGjRulUaDR0dHo3bs3tLS0cODAAZkTqi9DQ0NcunQJVatWVdp+/fp11KtXjxcwclGqVCmcOXMmW3Hl3r17aNiwIZ4/f44bN26gSZMmiI2NlSekmjl58iSEEPjqq6+wY8cOpRHbenp6sLe3l1YPppw1a9Ys130KhQLHjx9XYRrNwQni1ZQgKiB7e3vh5+eX6/5Dhw4Je3t71QXScKmpqWLBggWiVKlSwsnJSWzevFnuSGrJwcFB/PPPP9Lnv/32myhfvrxITU2VPq9Xr55c8dRWcnKy2Lx5s2jevLkwMDAQ33zzjdDW1hbXr1+XO5pas7CwyLOPAgIChLm5uQoTaZ6nT5+KL7/8UmhpaYlixYoJCwsLpQ/K3blz54Sjo6NQKBTSh5aWlvQv5c7IyCjHv91r164JY2NjGRJpjiZNmoivv/5aREVFSduioqJEy5YtxRdffCFjMvVmbm4u9uzZk237nj17pOeJe/fu8TkjB2FhYSI9PV3uGFSEWFlZifXr18sdg97C2/eowCIjI1GlSpVc91etWhVRUVEqTKS5Nm7cCG9vb7x+/RpTpkzBwIEDoaPDP8ucREVFwcHBQfr8+PHjcHV1lfqrQ4cO+OWXX2RKp56GDx+OzZs3o0KFCujduze2bt2KEiVKQFdXl3OrvMPr169hamqa634zMzOlVdEoux49euDRo0eYNWtWjpN1U+769euHWrVqYfPmzey7AtLX10d8fHy27QkJCdDT05MhkeZYs2YNvv32W9jZ2cHW1hYAEBERgQoVKmD37t3yhlNjbm5u8PT0xE8//YTPP/8cAHDp0iXMmjULffr0AZA5Miiv185FVdYo2sTERISHhyMlJUVpP0eF0oeWkpKChg0byh2D3sJ3v1RgJUuWRFhYmLSM5ttCQ0M5cfI7+Pn5Yfz48QgNDcXYsWMxevRoGBsbyx1LrZmamiI2NlZ6AXPx4kV4enpK+xUKBZKTk+WKp5aWL18OLy8vjB8/nnP7FFCFChVw/PhxeHh45Lj/2LFjqFChgopTaZazZ8/i3LlzqFGjhtxRNM6DBw+wd+9eODk5yR1F43zzzTcYOHAgfHx8ULduXQDAhQsXMHjwYHTo0EHmdOrNyckJ169fx5EjRxAYGAgAcHZ2RosWLVgYzcP8+fNhaWmJOXPm4MmTJwAAS0tLjBo1Cl5eXgCAli1bonXr1nLGVEvPnj2Dh4cHDh06lON+TmeRt8uXL2Pbtm05FvR27twpUyr11r9/f2zatIkTxKsZFqWowFq1aoWJEyfiyJEj2a46JicnY9KkSXzizcXFixfh5eWF8+fPY/DgwTh69ChKliwpdyyNUL9+fSxatAh//PEHdu7cifj4eHz11VfS/nv37klXdinThg0bsGbNGlhbW6Ndu3Zwc3NDmzZt5I6lETw8PDB27FhYWlqibdu2SvsOHDiAH3/8ET/99JNM6TRD5cqVOQdNIX311VcICAhgUaoQFi1aBHd3dzRo0ECaiystLQ0dOnTAwoULZU6n/hQKBVq2bImWLVvKHUVjaGtrY+LEiZg4cSLi4uIAINtIWzs7Ozmiqb2RI0ciNjYWFy5cwJdffoldu3bhyZMnmDFjhjSHKOVsy5Yt6NOnD1q1aoXDhw+jZcuWuHfvHp48eYJvv/1W7nhqixPEqydOdE4F9vDhQ9SpUwf6+voYOnQoKleuDCEE7ty5g2XLliE5ORmXL19mgSAHWlpaMDQ0xMCBA+Ho6JhruxEjRqgwlWa4fv06mjdvjri4OKSlpeGnn37C9OnTpf1ubm4wNjbGihUrZEypnkJDQ+Hr6wtfX18kJiYiJiYGW7duRZcuXeSOprYyMjLQrVs37NixA5UqVYKzs7N0nrt//z46deqEv/76S1ppibI7fPgwpk6dipkzZ6JatWrZXvjldXtkUbdq1SrMmDED/fr1y7HvOOLn3e7fv6802ocFvpwtWrQo32352oQ+NGtra+zZswd169aFqakpLl++jIoVK2Lv3r2YM2cOVyvMQ/Xq1TFo0CAMHToUJiYmCAgIgKOjIwYNGgRra2uuXpgLThCvnliUokIJDQ3FkCFDcPjwYWQdQgqFAl9//TWWLFnCF3+5cHBweOcQeIVCgZCQEBUl0izPnz/HmTNnYGVlhXr16intO3DgAFxcXPIs9hV1QggcPnwYPj4+2Lt3L0qWLAlXV9cCvSkparZu3YrNmzfj3r17AICKFSuie/fu6N69u8zJ1F9Wwe7tc54QAgqFgrdl5CGvYif7jj6k/D5n8rVJ7p48eYKxY8dKS8y//daKf6+5MzU1xfXr1+Hg4AB7e3ts2rQJjRo1QmhoKKpUqYLExES5I6otY2Nj3Lp1Cw4ODihRogT++ecfVKtWDXfu3MFXX32FyMhIuSMS5Rtv36NCcXR0xKFDh/DixQvcv38fQOZcBJxLKm9hYWFyR9BoJUuWRMeOHXPc165dOxWn0TwKhQKtWrVCq1atEBMTg/Xr12Pt2rVyx1Jr3bp1Q7du3eSOoZFOnDghdwSNlZGRIXcEjTJ69GhMnz4dxsbGGD16dJ5teWuGstDQULkjaLy+ffsiPDwckyZNynGJecpdpUqVcPfuXTg4OKBGjRpYuXIlHBwcsGLFClhbW8sdT61ZWFhIizqUKVMGN2/eRLVq1RAbG8tiHmkcjpQiIo2Q39E8vL2AiKhoadasGXbt2gVzc/M8b80AWCzNrzdHwVPeTExM8O+//6JmzZpyR9E4f/75J9LS0tC3b19cuXIFrVu3RnR0NPT09LBu3TpeFMpDz549UadOHakov3jxYnTs2BFHjhzBZ599xonO3+Dq6gpfX1+YmprC1dU1z7bsN3mwKEWkQiysFF5+bjHg7QXKXFxccPr0aWkE45AhQzBt2jRpcv2nT5/CwcGBV9Too4mNjYWPjw/u3LkDAKhSpQr69esHMzMzmZOpv5MnT+L333+X+s7FxQXjxo1DkyZNZE5Gn7L169fjt99+k0bBV6xYEePGjYObm5vMydSXi4sLNm7ciFq1askdReMlJiYiMDAQdnZ2XAjoHWJiYpCUlAQbGxtkZGRgzpw5OHv2LCpUqICff/4ZFhYWckdUGx4eHli0aBFMTExyXVU5C+8gkAeLUkQqxMIKqZKWlhaioqJQunRpAJlzN1y7dg3lypUDkDkPhrW1NW8Voo/i8uXLaNWqFQwNDVG3bl0AwKVLl/D69WscPnwYn332mcwJ1deff/4JDw8PuLq6olGjRgCAM2fOYNeuXfD19UXPnj1lTqi++vXrh4ULF8LExERp+6tXrzB8+HCsWbNGpmTqb968eZg0aRKGDRsmHXenT5/G0qVLMWPGDIwaNUrmhOrp8OHDmDt3rnTrGeXtXbfYvom325Jczpw5Iy3sRR8fi1JE9EmqVq0aDh48WKRXgXy7KJW1OsubRSkbGxtOwkofRZMmTeDk5IQ//vgDOjqZU1impaWhf//+CAkJwalTp2ROqL6cnZ0xcODAbEWAefPm4Y8//pBGT1F22traiIyMlM57WZ4/fw4rKyukpaXJlEz9OTo6YurUqejTp4/S9nXr1mHKlCmcfyoXFhYWSExMRFpaGoyMjLKtlhkTEyNTMvX0rltss3AltOzi4uKklWvj4uLybMsVbt/P2xdy6ePiROdEaoyFlcILCwtDamqq3DHoE7Z9+3Z06dJF7hhq6/Lly0oFKQDQ0dHBjz/+iDp16siYTP2FhISgffv22bZ36NABP/30kwyJ1F9cXByEEBBCID4+HgYGBtK+9PR0HDx4MFuhipRFRkaiYcOG2bY3bNiQK3nlYcGCBXJH0Cic163wLCwspKK7ubl5jnO+cYXbD4PjdlSLRSkqsL179+arXYcOHT5ykk8fCyv0PhQKRbYXLJy0Nv/S0tIQGBgIPT09VKxYUdq+Z88eeHt7IzAwkEWpPJiamiI8PByVK1dW2h4REZHt1ipSZmtri2PHjsHJyUlp+9GjR3mRIhdZb9AUCoXS32sWhUKBqVOnypBMczg5OWHbtm3ZCp9bt25FhQoVZEql/tzd3eWOQEXE8ePHpXlCWdyjTwmLUlRgnTp1UvpcoVBkqyazQk8kPyEEmjdvLo1Uef36Ndq3bw89PT0A4G0sebh58ya++eYbREREAAA6duyI5cuXo2vXrrh58yYGDBiAAwcOyJxSvXXr1g2enp74/fffpdEXZ86cwbhx49CjRw+Z06m3MWPGYMSIEbh27ZpS3/n6+mLhwoUyp1NPJ06cgBACX331FXbs2CG9cQMAPT092Nvbw8bGRsaE6m/q1Kno1q0bTp06pTSX2bFjx7Bt2zaZ06m39PR07N69W2lRhw4dOkBbW1vmZPQpadq0aY7/J9J0nFOK3tvb89TQh8O+LTz2HfI9KmDy5MkfOYnmadeuHZKTkzFy5Ehs3rwZmzdvRqVKleDp6YmhQ4fC0NBQ7ohqLyUlBePGjcOKFSukAqiuri6+//57zJ49m5OHvsOuXbswd+5c6U2us7Mzxo0bh44dO8qcTL09ePAAtra20NLSkjuKRrpy5Qrmz5+vdNyNGTOGK8vlISgoCG3btsWjR49QqVIlAMDdu3dha2uLAwcOoHz58jInpE/F9evX8922evXqHzHJp4/vI1SLRSl6b/yj/XjYt4XHvqP3Ubp0aRw+fBg1a9bEy5cvYWFhgXXr1nFZ9EJITExEcHAwAKB8+fIwMjKSOREVBYmJiQgPD0dKSorSdr5Row+tbdu2EEJg48aN0gi96Oho9O7dG1paWhxVSx+MlpaWdIfKu6Zj4B0r74cTnasWb98jIiJ6y/Pnz6VbfczMzGBsbIz69evLnEozGRkZwcLCQvo/5d+VK1eUbgfiaJV3e/bsGTw8PHDo0KEc9/ONWt4yMjIQFBSEp0+fIiMjQ2nfF198IVMq9Xby5EmcP39e6ZbREiVKYPbs2dJtkEQfwpsrYF69ehVjx47FuHHj0KBBAwDAuXPnMHfuXMyZM0euiJ8MjttRLRaliEijhISE5OuqxcqVK2FpaamCROqrWbNm77ySplAocOzYMRUl0hwKhUJawSvriuTr16+zLcHMJZdzl5GRgRkzZmDu3LlISEgAkDmCccyYMZg4cSJvr8rD06dP0b17d/zzzz8wNzcHAMTGxqJZs2bYsmULSpUqJW9ANTZy5EjExsbiwoUL+PLLL7Fr1y48efJEOhYpd+fPn0fPnj3x4MEDzhVaAPr6+oiPj8+2PSEhQZrDkehDsLe3l/7/3XffYdGiRWjbtq20rXr16rC1tcWkSZOyzQFMBZPT3zR9PCxK0XvLaYUvyhsLK4Xn5OSEpk2bwtPTE126dFFa9vtNPXv2VHEy9VOzZs1c98XHx2PTpk1ITk5WXSANIoRQWsFLCKE0SoVLLr/bxIkT4ePjozRa4PTp05gyZQqSkpIwc+ZMmROqr+HDhyM+Ph63bt2Cs7MzAOD27dtwd3fHiBEjsHnzZpkTqq/jx49jz549qFOnDrS0tGBvb4+vv/4apqam+OWXX9CuXTu5I6qtwYMHo06dOjhw4ACsra352i6fvvnmGwwcOBA+Pj6oW7cuAODChQsYPHgwV6Kmj+bGjRtwdHTMtt3R0RG3b9+WIZFmePLkCcaOHYtjx47h6dOn2QrwfF0nD84pRQVmYWGh9EIlNjYWpqam2a56x8TEqDqaxtDS0spXYYWyu3btGtauXYvNmzcjJSVFWuEr64Ug5S0tLQ1Lly7FzJkzYWZmhunTp6N79+5yx1I7J0+ezFc7rn6TOxsbG6xYsSLbm7I9e/ZgyJAhePTokUzJ1J+ZmRmOHj2Kzz//XGn7xYsX0bJlS8TGxsoTTAOYmpri+vXrcHBwgL29PTZt2oRGjRohNDQUVapUQWJiotwR1ZaxsTECAgLg5OQkdxSNEhsbC3d3d+zbtw+6uroAgNTUVHTs2BFr166VRjsSfUifffYZqlatitWrV0sj8lJSUtC/f3/cvHkT/v7+MidUT23atEF4eDiGDRuWY/Gdi4nIgyOlqMAWLFggdwSN5+/vj7Vr12L06NEYNmwYCysFULNmTSxcuBBz587F3r174evri8aNG6NixYro168f3NzceGtLLjZu3Ahvb2+8fv0aU6ZMwcCBA6Gjw6eBnOSn2MTCe95iYmJQuXLlbNsrV67MvnuHjIwM6c3tm3R1dbPN80PKKlWqhLt378LBwQE1atTAypUr4eDggBUrVsDa2lrueGqtXr16CAoKYlGqgMzNzbFnzx4EBQUprVrIfqSPacWKFWjfvj3Kli0rLeBw/fp1KBQK7Nu3T+Z06uv06dP4999/87ybgFSPI6WIZJSWliYVVvz8/FhYKYTk5GQsW7YMEyZMQEpKCvT09NC1a1f8+uuvfAPyf35+fhg/fjxCQ0MxduxYjB49GsbGxnLH0liHDx/G6tWrsW/fPrx+/VruOGqrXr16qFevHhYtWqS0ffjw4bh06RLOnz8vUzL117FjR8TGxmLz5s3ShPuPHj1Cr169YGFhgV27dsmcUH39+eefSEtLQ9++fXHlyhW0bt0aMTEx0NPTg6+vL7p16yZ3RLXy5hLzwcHB+PnnnzFu3DhUq1YtW2GUKxf+Z/To0fluO2/evI+YhIqyV69eYePGjQgMDASQWQzt2bMnX+PlwcXFBRs3buTCIWqGRSkiNcDCSsFdvnwZa9aswZYtW2BsbAx3d3d4enri4cOHmDp1KuLi4nDx4kW5Y8rq4sWL8PLywvnz5zF48GBMnDgRJUuWlDuWRnrw4AHWrFmDdevW4cWLF2jTpg06d+6M7777Tu5oauvkyZNo164d7OzslFYGioiIwMGDB9GkSROZE6qviIgIdOjQAbdu3YKtra20rWrVqti7dy/Kli0rc0LNkZiYiMDAQNjZ2fH8l4M3l5jPyZvLz3Oulf80a9YsX+0UCgWOHz/+kdMQUX4dPnwYc+fOlUbRknpgUYo+uICAAHz22Wd88ZIPLKwU3Lx587B27VrcvXsXbdu2Rf/+/dG2bVulOc0ePnwIBwcHpKWlyZhUflpaWjA0NMTAgQNznAwzy4gRI1SYSnOkpKRg586dWL16Nc6cOYMWLVrg0KFDuHr1KqpVqyZ3PI3w+PFjLF26VOkq7pAhQ6TRP5Q7IQSOHj2q1HctWrSQORV9ah48eJDvtm+u/EVE8tuwYQNWrlyJkJAQnDt3Dvb29pg/fz7KlSvHuZFyYWFhgcTERKSlpcHIyCjbiFBOLyAPFqXogwsICECtWrU470UeWFgpvAoVKqBfv37o27dvrqPIUlJSsHnzZri7u6s4nXpxcHB45+pJCoUCISEhKkqkOYYPH47NmzejQoUK6N27N7p3744SJUpAV1cXAQEBcHFxkTuiWktNTUXr1q2xYsUKVKhQQe44GiU1NRWGhoa4du0aqlatKnccjcBbqYioqFm+fDm8vb0xcuRIzJgxA7du3UK5cuXg6+uLdevW4cSJE3JHVEvr1q3Lc39Rf+8gFxalqMBcXV3z3P/y5Uv8888/HCmVBxZWCi8sLAx2dnbZVnsUQiAiIgJ2dnYyJaNPiY6ODry8vDB+/HiYmJhI21mUyr9SpUrh7NmzLEoVQrly5bBr1y7UqFFD7igagbdSfTgbNmzAihUrEBoaKo28WLBgARwdHTnygkiNuLi4YNasWejUqRNMTEwQEBCAcuXK4ebNm/jyyy/x/PlzuSMS5RuXXaIC27dvH77++mtYWlrmuJ/FqHc7cuTIOwsrenp6LEjloHz58oiMjETp0qWVtsfExMDR0ZHH33uoVq0aDh48KM1hU5Rt2LABa9asgbW1Ndq1awc3Nze0adNG7lgapXfv3vDx8cHs2bPljqJxJk6ciJ9++gkbNmxA8eLF5Y6j9jgi4MN4c+TFzJkzpedTc3NzLFiwgEUpIjUSGhqa42Td+vr6ePXqlQyJNE9SUhJSUlKUtpmamsqUpmhjUYoKzNnZGZ07d4anp2eO+69du4b9+/erOJVmYWGl8HIb3JmQkAADAwMVp/m0hIWFITU1Ve4YaqFHjx7o0aMHQkND4evri6FDhyIxMREZGRm4ffs2R0rlQ1paGtasWYOjR4+idu3a2VYD4m1UuVuyZAmCgoJgY2MDe3v7bH3n7+8vUzL6lC1evBh//PEHOnXqpFRMrlOnDsaOHStjMiJ6m6OjI65du5Ztrjc/Pz84OzvLlEr9vXr1Cl5eXti2bRuio6Oz7ed7MHmwKEUFVrt2bfj7++dalNLX1+ctVO/AwkrBZc0ZolAo4O3tDSMjI2lfeno6Lly4gJo1a8qUjj5Vjo6OmDp1KqZMmYLDhw/Dx8cHvXv3xsiRI+Hq6opFixbJHVFt3bx5E5999hkA4N69e0r73jXXWVHXqVMnuSNorGbNmuV5fPH2vdxx5AWR5hg9ejSGDh2KpKQkCCFw8eJFbN68Gb/88gtWr14tdzy19eOPP+LEiRNYvnw53NzcsHTpUjx69AgrV67kyG4ZsShFBbZixYo8q8jOzs4IDQ1VYSLNwcJK4V29ehVAZkHvxo0b0NPTk/bp6emhRo0avJJLH41CoUCrVq3QqlUrxMTEYP369Vi7dq3csdRafm+pevjwIWxsbLLdzlyUTZ48We4IGuvt59DU1FRcu3YNN2/e5C3x78CRF0Sao3///jA0NMTPP/+MxMRE9OzZEzY2Nli4cCG6d+8udzy1tW/fPqxfvx5ffvklPDw80KRJEzg5OcHe3h4bN25Er1695I5YJLEoRQWmr68vdwSNxcJK4WW9wfXw8MDChQt5zzfJpnjx4hg5ciRGjhwpd5RPgouLC65du4Zy5crJHYU+AfPnz89x+5QpU5CQkKDiNJqFIy+INEuvXr3Qq1cvJCYmIiEhIdu0IJRdTEyM9HrD1NQUMTExAIDGjRvj+++/lzNakcaiFJEKsbDy/jg6hVTBxcUFp0+fliaZHjJkCKZNm4aSJUsCAJ4+fQoHBwckJibKGfOTwEWAM1lYWOT7tsasF9GUf71790bdunXx+++/yx1FbXHkBZFmMjIyUrr7gnJXrlw5hIaGws7ODpUrV8a2bdtQt25d7Nu3D+bm5nLHK7JYlKJCiYiIQK1atXD58mU4ODhI2588eYKqVavizJkzqFixonwB1RwLKwXj6uoKX19fmJqawtXVNc+2O3fuVFEq+pQFBgYiLS1N+vzPP//E2LFjpaKUEAJJSUlyxaNP0IIFC6T/R0dHY8aMGWjVqhUaNGgAADh37hz+/vtvTJo0SaaEmu3cuXOcszEfOPKCSDNER0fD29sbJ06cwNOnT5GRkaG0nxcvcubh4YGAgAA0bdoU48ePR/v27bFkyRKkpqZyARYZsShFhWJra4sqVapgw4YNSi+QN2/eDFtbWxakcsDCSuGZmZlJIwjMzMxkTqN5QkJC8nVr1MqVK2FpaamCRJonp9E8nKybPqQ35zvq3Lkzpk2bhmHDhknbRowYgSVLluDo0aMYNWqUHBE1wtvPr0IIREZG4vLlyyzovcPr168hhJBGXTx79gwLFiyAi4sLWrZsKXc8InqDm5sbgoKC4OnpCUtLS74myac3nz9btGiBwMBAXLlyBU5OTqhevbqMyYo2FqWo0Pr06YM5c+YovcjbsGED+vbtK18oNcbCSuG9ObKMo8wKzsnJCU2bNoWnpye6dOmS62iBnj17qjgZEeXk77//xq+//ppte+vWrTF+/HgZEmmOt59ftbS0UKlSJUybNo2FlXfo2LEjXF1dMXjwYMTGxqJu3brQ09PD8+fPMW/ePM63QqRG/v33X5w+fRo1atSQO4pGs7e3z7a4A6kei1JUaF27dsWIESNw4cIF1KtXD7dv38atW7e4akEuWFghufj7+2Pt2rUYPXo0hg0bhm7dusHT0xN169aVO5raUigU2a468irkx8F+za5EiRLYs2cPxowZo7R9z549KFGihEypNAOfXwvP399fmih++/btsLKywtWrV7Fjxw54e3uzKEWkRipXrozXr1/LHUMjLFq0CAMHDoSBgQEWLVqUZ9sRI0aoKBW9SSE4wyi9Bzc3N5iYmGDZsmWYMGECAgMDsWvXLrlj0SeM99AXXlpaGvbu3QtfX1/4+fmhYsWK6NevH9zc3FCqVCm546kVLS0tVK1aFTo6mddurl+/jsqVK0srZqalpeHWrVtIT0+XM+YnwcTEBAEBAVx97w2+vr7o378/2rRpg3r16gEALly4AD8/P/zxxx8ckZwPly9fxp07dwBkLlxQu3ZtmROpPyMjIwQGBsLOzg5du3ZFlSpVMHnyZERERKBSpUpc2IFIjVy6dAnjx4+Ht7c3qlatCl1dXaX9XEzpP46Ojrh8+TJKlCgBR0fHXNspFAqEhISoMBllYVGK3suRI0fQo0cPPHr0CBUqVMCiRYvQqVMnuWOpPRZWCq9t27Z53kP/5rwslLPk5GSpkJySkgI9PT107doVv/76K6ytreWOpxamTp2ar3aTJ0/+yEk+fREREbCxsYG2trbcUdTKhQsXsGjRIqmw4uzsjBEjRkhFKsrZw4cP0aNHD5w5c0ZaSSk2NhYNGzbEli1bULZsWXkDqrHq1aujf//++Pbbb1G1alX4+fmhQYMGuHLlCtq1a4eoqCi5IxLR/92/fx89e/aEv7+/0nYhBBQKBS+akUZhUYreixAC9vb2aN++Pf766y88fvxYGllAuWNhpfBMTEx4D30hXb58GWvWrMGWLVtgbGwMd3d3eHp64uHDh5g6dSri4uJw8eJFuWOSBnvXIg5v4oIO9DG0bt0asbGxWLduHSpVqgQAuHv3Ljw8PGBqago/Pz+ZE6qv7du3o2fPnkhPT0fz5s1x+PBhAMAvv/yCU6dO4dChQzInJKIsdevWhY6ODn744Ycc30s0bdpUpmREBcfqAb0XhUKB3r1749dff8WwYcNYkMonTk5YeLyHvuDmzZuHtWvX4u7du2jbti3Wr1+Ptm3bQktLC0DmsGZfX184ODjIG5Q0Hhdx+HCCg4Oxdu1ahISEYMGCBShdujQOHToEOzs7VKlSRe54auvkyZM4e/asVJACgEqVKmHx4sVo0qSJjMnUX5cuXdC4cWNERkYqvT5p3rw5vv32WxmTEdHbbt68iatXryqd6yhno0ePznfbefPmfcQklBtWEOi9eXh44Ny5c/D09JQ7isZgYaXwli1bxnvoC2j58uXo168f+vbtm+vteaVLl4aPj4+Kk6mvZs2avXMCboVCgWPHjqkokWbgJNMfxsmTJ9GmTRs0atQIp06dwowZM1C6dGkEBATAx8cH27dvlzui2rK1tUVqamq27enp6bCxsZEhkWaxsrKClZWV0jYuikGkfurUqSPN90Z5u3r1qtLn/v7+SEtLk/ru3r170NbW5tyDMuLte0Qy4OSEhcd76AsuLCwMdnZ20sioLEIIREREwM7OTqZk6mvUqFG57ouPj8emTZuQnJzM440+igYNGuC7777D6NGjlSaCv3jxIlxdXfHw4UO5I6qtPXv2YNasWVi6dCnq1KkDIPPW5eHDh8PLy4vzXubhXcX448ePqzANEeXlr7/+wpQpUzBu3DhUq1Yt23uJ6tWry5RMvc2bNw///PMP1q1bBwsLCwDAixcv4OHhgSZNmmRb9ZZUg0Up+uiqVauGgwcPwtbWVu4oaoOFlcLjPfQFp62tjcjISJQuXVppe3R0NEqXLs3jLZ/S0tKwdOlSzJw5E2ZmZpg+fTq6d+8udyy1tn37dmzbtg3h4eFISUlR2vf2+Y/+U6xYMdy4cQOOjo5KRamwsDBUrlwZSUlJckdUWxYWFkhMTERaWpo0pUDW/42NjZXaclERZW8X41NTU3Ht2jXcvHkT7u7uWLhwoUzJiOhtb19oBDJHcPO9RN7KlCmDw4cPZ7sN/ubNm2jZsiUeP34sU7Kijbfv0UcXFhaW41D6oqxXr17Q1dXFpk2bciysUO54D33B5XbtISEhAQYGBipOo5k2btwIb29vvH79GlOmTMHAgQM5h947LFq0CBMnTkTfvn2xZ88eeHh4IDg4GJcuXcLQoUPljqfWzM3NERkZmW3p6qtXr6JMmTIypdIMCxYskDuCxpo/f36O26dMmYKEhAQVpyGivISGhsodQSPFxcXh2bNn2bY/e/YM8fHxMiQigEUpIlmwsFJ4vIc+/7ImdlQoFPD29oaRkZG0Lz09HRcuXEDNmjVlSqcZ/Pz8MH78eISGhmLs2LEYPXp0ttEWlLNly5Zh1apV6NGjB3x9ffHjjz+iXLly8Pb25giVd+jevTu8vLzw119/QaFQICMjA2fOnMHYsWPRp08fueOpNa5e++H17t0bdevWxe+//y53FCL6P3t7+3y1a9euHVavXp3rnKJFzbfffgsPDw/MnTtXmi/vwoULGDduXIFWEKYPi0UpIhmwsFJ4w4cPxw8//MB76PMha2JHIQRu3LgBPT09aZ+enh5q1KiBsWPHyhVPrV28eBFeXl44f/48Bg8ejKNHj6JkyZJyx9Io4eHhaNiwIQDA0NBQugLp5uaG+vXrY8mSJXLGU2uzZs3C0KFDYWtri/T0dLi4uCA9PR09e/bEzz//LHc8tZeeno7du3fjzp07AIAqVaqgQ4cO0NbWljmZZjp37hxH1RJpqFOnTnFxpTesWLECY8eORc+ePaU7eXR0dODp6YnffvtN5nRFF+eUoo/uzfkwKBMnJyw83kNfcB4eHli4cCEn0C8ALS0tGBoaYuDAgdluoXrTiBEjVJhKs5QrVw47duxArVq1UKdOHQwYMACDBg3C4cOH0b17d46Wyofw8HDcvHkTCQkJqFWrFipUqCB3JLUXFBSEtm3b4tGjR9KFn7t378LW1hYHDhxA+fLlZU6ovt4eJSCEQGRkJC5fvoxJkyZh8uTJMiUjosLi+7CcvXr1CsHBwQCA8uXLcxS8zFiUoo+OJ8PsWFgpvAcPHuS5P7/DmYny4uDg8M653hQKBUJCQlSUSPP0798ftra2mDx5MpYuXYpx48ahUaNGuHz5MlxdXeHj4yN3RI2Q9TKNcw/mT9u2bSGEwMaNG1G8eHEAmYs69O7dG1paWjhw4IDMCdWXh4eH0udaWlooVaoUvvrqK7Rs2VKmVET0Pvg+LGdBQUEIDg7GF198AUNDQ+k9GMmDRSn66HgyzI6FFfrYXF1d4evrC1NT03feI79z504VpaKiJCMjAxkZGdKE8Fu2bMHZs2dRoUIFDBo0SOl2UsrOx8cH8+fPx/379wEAFSpUwMiRI9G/f3+Zk6k3Y2NjnD9/HtWqVVPaHhAQgEaNGnHCbiIqUvg+TFl0dDS6du2KEydOQKFQ4P79+yhXrhz69esHCwsLzJ07V+6IRRLnlKJCCwkJydcJbuXKlbC0tFRBIs3BolPB7N27F23atIGuri727t2bZ9sOHTqoKJV6MzMzk674mJmZyZzm01etWjUcPHgQtra2ckdRGw8fPlTqj+7du6N79+4QQiAiIgJ2dnYyplNv3t7emDdvHoYPH44GDRoAyJzXZ9SoUQgPD8e0adNkTqi+9PX1c1xBKSEhgYXQfLpy5YrSfFy1atWSORER0YcxatQo6OrqIjw8HM7OztL2bt26YfTo0SxKyYQjpajQtLS00LRpU3h6eqJLly6cBPMdWFgpPC0tLURFRaF06dI53vqYhbc+klx4JTI7bW1tREZGonTp0krbo6OjUbp0af6t5qFUqVJYtGgRevToobR98+bNGD58OJ4/fy5TMvXXp08f+Pv7w8fHR2llpQEDBqB27drw9fWVN6Aae/r0Kbp3745//vkH5ubmAIDY2Fg0a9YMW7ZsQalSpeQNSEQFxtcnyqysrPD333+jRo0aSn0TEhKC6tWrczStTDhSigrN398fa9euxejRozFs2DB069YNnp6e0otAUtapUyepsNKpU6dc27Gwkl1GRkaO/yci9ZXb/AwJCQm8iPEOqampqFOnTrbttWvXRlpamgyJNMeiRYvg7u6OBg0aSIuIpKamomPHjli4cKHM6dTb8OHDER8fj1u3bkkjCG7fvg13d3eMGDECmzdvljkhERXUTz/9JM2vR5kTnBsZGWXbHhMTA319fRkSEcCRUvQBpKWlYe/evfD19YWfnx8qVqyIfv36wc3NjVfVSKUSExNzfKIp6qKjo+Ht7Y0TJ07g6dOn2Qp7XAXt/fFK5H9Gjx4NAFi4cCEGDBig9DeZnp6OCxcuQFtbG2fOnJErotobPnw4dHV1MW/ePKXtY8eOxevXr7F06VKZkmmOoKAg3L59GwDg4uICJycnmROpPzMzMxw9ehSff/650vaLFy+iZcuWiI2NlScYEWWT210XCoUCBgYGcHJyynP14KKqbdu2qF27NqZPnw4TExNcv34d9vb26N69OzIyMrB9+3a5IxZJHClF701HRweurq5o164dli1bhgkTJmDs2LH46aef0LVrV/z666+wtraWO6bGYGElb82bN8f69etRpkwZpe0XLlyAm5sb7t27J1My9eXm5oagoCB4enrC0tKSq4vQR3X16lUAmSOlbty4oTSPj56eHmrUqIGxY8fKFU9tZRXzgMw3FatXr8bhw4dRv359AJnnuPDwcPTp00euiBqDk8QXTkZGhjS67E26urocpUykZjp16iSt3P2mN1fzbty4MXbv3g0LCwuZUqqfOXPmoHnz5rh8+TJSUlLw448/4tatW4iJieHFMhlxpBS9t8uXL2PNmjXYsmULjI2N4e7uDk9PTzx8+BBTp05FXFwcLl68KHdMtcLCSuG1a9cO58+fx7Jly9CtWzdkZGRg2rRpmDVrFoYMGYIFCxbIHVHtmJiY4PTp06hRo4bcUT5ZHCmVnYeHBxYuXAhTU1O5o2iEZs2a5audQqHA8ePHP3IazZXbJPFLlizBqFGjOEl8Hjp27IjY2Fhs3rwZNjY2AIBHjx6hV69esLCwwK5du2ROSERZjh07hokTJ2LmzJnS1CkXL17EpEmT8PPPP8PMzAyDBg1CvXr14OPjI3Na9RIbG4ulS5ciICAACQkJ+OyzzzB06FAOopARi1JUaPPmzcPatWtx9+5dtG3bFv3790fbtm2VJqJ++PAhHBwcOAfGW1hYeT9Lly7Fjz/+iI4dOyIsLAwPHjzA2rVr0bJlS7mjqaXPP/8cixcvlkZc0IfHolTeHj58CAAoW7aszEk+LQ8fPoSNjU2eC0AUNZwkvvAiIiLQoUMH3Lp1S1o5Mzw8HNWqVcPevXv590ukRqpWrYpVq1ahYcOGStvPnDmDgQMH4tatWzh69Cj69euH8PBwmVKqp6SkJFy/fj3HKS242JQ8ePseFdry5cvRr18/9O3bN9fKcunSpVmdz8GBAwewdOlS9OvXD3v27JEKK/v372dhJR+GDh2Khw8f4tdff4WOjg7++eefbE/K9J9ly5Zh/Pjx8Pb2RtWqVbPdnsGRLLkLCQnJV6Fp5cqVsLS0VEEizZGRkYEZM2Zg7ty50mo2JiYmGDNmDCZOnMhCygfg4uKCa9eusRj6Bk4SX3i2trbw9/fHsWPHcOfOHQCAs7MzWrRoIXMyInpbcHBwjq/fTE1NERISAiDz1mUW4pX5+fnBzc0NMTExOd76yMWm5MGRUlRoYWFhsLOzy/bGQgiBiIgI2NnZyZRMc0yYMIGFlQJ68eIF+vfvj2PHjuG3337DyZMnsXv3bsyZMwdDhgyRO55aun//Pnr27Al/f3+l7VlzDvAJOHdaWlpo2rQpPD090aVLF64aVwATJkyAj48Ppk6dikaNGgEATp8+jSlTpmDAgAGYOXOmzAk1H0foZcdJ4t/PsWPHcOzYsRxHEKxZs0amVET0tsaNG8PExATr16+XFpZ69uwZ+vTpg1evXuHUqVM4evQohg4dirt378qcVn1UqFABLVu2hLe3Ny8mqhEWpajQtLW1ERkZidKlSyttj46ORunSpflGNw8srBRemTJl4OjoiA0bNkirimzduhVDhgxB/fr1ceDAAZkTqp+6detCR0cHP/zwQ44TnTdt2lSmZOrv2rVrWLt2LTZv3oyUlBR069YNnp6e0vwNlDsbGxusWLEi21D4PXv2YMiQIXj06JFMyT4dLEplN3z4cKxfvx62trY5ThL/5kjRtwtXRd3UqVMxbdo01KlTB9bW1tmeKzinFJH6uHv3Ljp27IjQ0FDpdtuIiAiUK1cOe/bsQcWKFbF7927Ex8fDzc1N5rTqw9TUFFevXkX58uXljkJvYFGKCk1LSwtRUVHZilIPHjyAi4sLXr16JVMy9cfCSuFNnz49x1t/Hj58CA8PDxw5ckSmZOrLyMgIV69eRaVKleSOorHS0tKwd+9e+Pr6ws/PDxUrVkS/fv3g5uYmXaEkZQYGBrh+/ToqVqyotP3u3buoWbMmXr9+LVOyTweLUtlxwvjCs7a2xpw5c/gGlkhDZGRk4PDhw9ICSZUqVcLXX3/N2+Pz0K9fPzRq1Aienp5yR6E3sChFBZa1bPXChQsxYMAAGBkZSfvS09Nx4cIFaGtrc1nNPLCw8mFknb7evppLyr744gt4e3tzXpAPIDk5GcuWLcOECROQkpICPT09dO3aFb/++itXbXlLvXr1UK9ePSxatEhp+/Dhw3Hp0iWcP39epmSfDhal6EMqUaIELl68yBEERPTJSkxMxHfffYdSpUqhWrVq2eZZHTFihEzJijYWpajAsq5Cnjx5Eg0aNICenp60T09PDw4ODhg7diwqVKggV0SNwsJKwa1fvx6//fYb7t+/DwCoWLEixo0bx6u7ufjrr78wZcoUjBs3Lscn4OrVq8uUTHNcvnwZa9aswZYtW2BsbAx3d3d4enri4cOHmDp1KuLi4nDx4kW5Y6qVkydPol27drCzs0ODBg0AAOfOnUNERAQOHjyIJk2ayJxQ85mamnKic/pgvLy8UKxYMUyaNEnuKESUD5wDruB8fHwwePBgGBgYoESJEkrvvxQKhTRJPKkWi1JUaB4eHli4cCFX7iokFlYKZ968eZg0aRKGDRumNHny0qVLMWPGDIwaNUrmhOonp2HcCoWCE53nw7x587B27VrcvXsXbdu2Rf/+/dG2bVulPn348CEcHBy4stdbwsPDoaOjg6VLlyIwMBBA5kpeQ4YMQVpaGhfD+AA4UoreV9bodyDzVqB169ahevXqqF69erYLGJyDi0h9cA64wrGyssKIESMwfvx43uaoRliUIpIBCyuF5+joiKlTp6JPnz5K29etW4cpU6YgNDRUpmTq68GDB3nut7e3V1ESzVOhQgX069cPffv2zfX2vJSUFGzevBnu7u4qTqfeuBjGxxcREQEbGxtoa2vLHYU0FOfgItJMnAOucIoXL45Lly7xNmU1w6IUFYirqyt8fX1hamoKV1fXPNvu3LlTRak0DwsrhWdgYICbN2/CyclJafv9+/dRrVo1JCUlyZSMPkVhYWGws7PLdjVNCIGIiAiO9skDF8MomHc9p76Jz69EREUb54ArnFGjRqFUqVL46aef5I5Cb9CROwBpFjMzM2l4qJmZmcxpNFdkZCQaNmyYbXvDhg0RGRkpQyLN4eTkhG3btmV7Mtm6dSvnMXvD3r170aZNG+jq6mLv3r15tu3QoYOKUmme8uXL5zjaJyYmBo6Ojhztk4Os24EUCgW8vb1zXAyjZs2aMqVTX3xOJSKi/Orfvz82bdrEOeAKKD09HXPmzMHff//N25TVCItSVCBr167N8f9UMCysFN7UqVPRrVs3nDp1Srr18cyZMzh27Bi2bdsmczr10alTJ2mUSqdOnXJtxzml8pbbYOKEhAQYGBioOI1muHr1KoDMvrtx40a2xTBq1KiBsWPHyhVPbfE5lYiI8ispKQmrVq3C0aNHWVwpgBs3bqBWrVoAgJs3byrt46JT8uHte0Qy2LFjB7p164YWLVrkWFj59ttvZU6o3vz9/TFv3jzcuXMHQObkyWPGjJGeZIjeV9Zon4ULF2LAgAE5jvbR1tbGmTNn5Iqo9rgYBhER0ceR13xwnAOONA2LUlRo0dHR8Pb2xokTJ3JcijQmJkamZJqBhZWCS01NxaBBgzBp0iQ4OjrKHeeTkJiYqFRwoUxZL/ZOnjyJBg0aZBvt4+DggLFjx3JkI30027dvx7Zt2xAeHo6UlBSlff7+/jKlIiIiIvqwWJSiQmvbti2CgoLg6ekJS0vLbEMeuRJVzlhYeT9mZma4du0a+64AmjdvjvXr16NMmTJK2y9cuAA3Nzfcu3dPpmTqj6N9SA6LFi3CxIkT0bdvX6xatQoeHh4IDg7GpUuXMHToUMycOVPuiEREREQfBItSVGgmJiY4ffo0atSoIXcUjcPCSuG5u7ujZs2aGDVqlNxRNEa7du1w/vx5LFu2DN26dUNGRgamTZuGWbNmYciQIViwYIHcEYnoDZUrV8bkyZPRo0cPmJiY4H/t3X1Q1nW+//EXCCkYSI7ZSt5wiWxqgnesByPdOu3U2Uojz8y5Fk+Q4nUm70hB2XV1IWBLyJsLM03nIOesd0t4pjnqRHU4i4lmeIOCG6vNkqIXbjiOS5ACjnLz+8MTv65Q08ubz3Xh8zHThJ/v9cdrrmG4efH5vD9Hjx7V4MGDlZaWprq6Oq1Zs8Z0RADAPcYt6OiqGHQOlw0dOlTNzc2mY3ikmJgYbd++nWLFBWFhYcrMzNS+ffs0duxY9ezZ0+n566+/biiZ+yosLNTatWuVkJCgHTt26NSpUzp9+rQ+/PBDPfvss6bjuR1+6INpDoej44ZWPz8/XbhwQZIUFxenqKgoSikAuA9xCzq6KkopuOy9997TokWLlJaWphEjRnS69YHjLtdHseK6vLw8BQUF6fDhwzp8+LDTMy8vL96765gzZ47OnDmjt99+Wz4+Ptq9e3fHL71wxg99MO0nP/mJ6urqNGjQIA0cOFD79+/XyJEjVV1dfd0bIQEAXRu3oKOr4vgeXFZVVaWpU6d2Grja3t7ONfM/4kbH9ry8vHTy5Ml7mAZd3TfffCObzabi4mItX75cJSUl2r59u5YtW6bZs2ebjgfgB2w2mwYMGKA33nhDa9euVUpKiqKjo1VWVqYpU6YoLy/PdEQAgEHNzc1qb2/vuKzm9OnT+u///m8NHz6cXfDwOJRScNm4cePk4+OjefPmXXPQ+c9//nNDyXC/+O7L1w8/9+Ds0UcflcVi0ebNmzsK0YKCAs2ePVtRUVEqLCw0nBDA97W1tamtrU0+Plc3tL///vv6/PPPFRYWptdee83pNkgAwP3n2Wef1ZQpUzRz5kzV19frscce0wMPPKDz58/Lbrdr1qxZpiMCN41SCi7z9/dXeXm5HnvsMdNRPBrFyq3Ly8tTTk6OqqqqJF09Djl//nzZbDbDydzT73//ey1ZskTe3t5O62fOnNH06dP1v//7v4aSub+///3vSktL06effqpz586pra3N6XldXZ2hZOjKHA6HBgwY0On7Qnt7u2pqajRw4EBDyQAA7qBPnz4qKSnR448/rg0bNujdd99VeXm5PvjgA6Wlpen48eOmIwI3jZlScFlkZKRqamoopVxEseKatLQ02e12JSYmavz48ZKk0tJSJSUlyeFwKDMz03BC95Oamtrx8fdL0P79+1NI/Yi4uDh99dVXmjFjxjV3hAJ3g8ViUW1trfr27eu0XldXJ4vFwvF4ALjPNTU1KSAgQJJUVFSkKVOmyNvbW1FRUTp9+rThdMCtoZSCyxITEzVv3jylpKQoPDy806DziIgIQ8ncH8WK69atW6fc3FzFxsZ2rE2ePFkRERFKTEzkvbuOTZs2afny5R0l6E9/+lOlpKQoLi7OcDL3tnfvXn322WcaOXKk6Si4j3w3m/GHLl68qB49ehhIBABwJ0OGDNH27dv18ssv63/+5386bvQ+d+4cl03B41BKwWVWq1WSlJCQ0LHm5eXFoPObQLHiuitXrigyMrLT+tixY9XS0mIgkfuz2+1KTU3V3LlzFR0dLUn67LPPNHPmTJ0/f77jBxl0NnToUDU3N5uOgftEcnKypKvfS1NTUzsG2EpSa2urDhw4oFGjRhlKBwBwF2lpaZo6daqSkpL0zDPPdPyRu6ioSKNHjzacDrg1zJSCy35sa+igQYPuURLPExQUpEOHDiksLMxp/a9//avGjRun+vp6M8E8QGJionx9fWW3253WFy5cqObmZq1du9ZQMvdlsViUkZGh+Ph4p/WNGzcqPT1d1dXVhpK5v0OHDmnRokVKS0vTiBEjOu0I5a+RuJOefvppSVJJSYnGjx/vNND8gQceUEhIiBYuXNjpewcA4P5z9uxZ1dbWauTIkR1zQw8ePKjAwEANHTrUcDrg5lFKAQZQrLguMTFRmzZt0oABAxQVFSVJOnDggBwOh+Lj451Kgx++v/erHj16qLKyUkOGDHFar6qqUnh4uC5dumQomfurqqrS1KlTdeTIEad1doTibpo+fbreeecdSk8AANDlUUrhluzcuVO//OUv5evrq507d97wtZMnT75HqTwPxYrrvttJ8GO8vLy0a9euu5zGM4wYMUJTp07V4sWLndbffPNNFRQU6IsvvjCUzP2NGzdOPj4+mjdv3jUHnf/85z83lAz3izNnzkiS+vfvbzgJAMBdPP300ze8fIWfgeFJKKVwS7y9vXX27Fn17du30/Xy38cOghujWLn7zpw5o+Dg4Bt+nt4vPvjgA1mtVv3iF7/omCm1b98+FRcXa9u2bXr55ZcNJ3Rf/v7+Ki8v55ZR3FNtbW168803tXLlSl28eFGSFBAQoAULFmjJkiV8XQOA+9wP54FeuXJFFRUVqqys1Kuvvqp33nnHUDLg1jHoHLekra3tmh/j1nz66ac39bozZ86ora2NX0BcMHz4cFVUVGjw4MGmoxj3z//8zzp48KDsdru2b98uSRo2bJgOHjzIMMwfERkZqZqaGkop3FNLlixRXl6esrOznS4nSE9P16VLl/TWW28ZTggAMCknJ+ea6+np6R1/zAA8BTulcFc0NTU53RoE1wQGBlKsuCggIEBHjx6979+7K1eu6LXXXlNqaqosFovpOB7nv/7rv5Senq6UlBSFh4d3GnQeERFhKBm6suDgYK1fv77TMfgdO3Zo9uzZ+tvf/mYoGQDAnX311VcaN26c6urqTEcBbhrbL+CyZ5555po/GHNl9Z1DZ4zb5evrqw8++MB0DI9ltVp1/PhxJSQk6Gc/+5lGjRql0aNHd/wfuBvq6uqueXPS0KFD+UUDAHBdpaWl6tGjh+kYwC3h+B5c1qNHD0VEROi9996T1WpVW1ubMjMztXTpUs2ePdt0PAD/JyYmRtu3b+80fwA/rrq62nQE3IdGjhypNWvWaPXq1U7ra9as0ciRIw2lAgC4iylTpjj9u729XbW1tSorK1NqaqqhVIBrKKXgssLCQq1du1YJCQnasWOHTp06pdOnT+vDDz/Us88+azoegP8TFhamzMxM7du3T2PHjlXPnj2dnr/++uuGkrm/QYMGmY6A+9CyZcv0wgsv6E9/+pPGjx8v6epfv2tqavTRRx8ZTgcAMK1Xr15O//b29tZjjz2mzMxMfg+Dx2GmFG7bb3/7W7399tvy8fHR7t279cQTT5iO1GUwF8l1zOP6/240S8rLy0snT568h2nc386dO/XLX/5Svr6+2rlz5w1f+8OZP8Cd4HA45OPjo7Vr1+rLL7+UdPVygtmzZ6ulpUUDBw40nBAAAODOoJSCy7755hvZbDYVFxdr+fLlKikp0fbt27Vs2TKO790hFCuuo9CDq7y9vXX27Fn17dv3hjdfenl5qbW19R4mw/2iW7duqq2tVd++fZ3W//73v6tv37583gEAJEmHDx/W8ePHJUmPP/448y7hkTi+B5eNGDFCFotF5eXlslgs+rd/+zcVFBRo9uzZKiwsVGFhoemIHo/O2HXHjh1TcHCw6Rhu57vPKS8vL8NJ3FdbW9s1Pwbulet97b948SIDbAEAOnfunH71q19p9+7dCgoKkiTV19fr6aef1vvvv6+HH37YbEDgFlBKwWUzZ87UkiVLnHYSWK1WRUdHa/r06QaTdR0UK501NjYqOztbxcXFOnfuXKfS4LujaAMGDDARz23l5eUpJydHVVVVkq7OmZo/f75sNpvhZJ6rqalJ/v7+pmOgC0lOTpZ0tTROS0tz+vxqbW3ldlsAgCQpMTFRFy5c0F/+8hcNGzZM0tXfG1599VW9/vrrys/PN5wQuHkc38Mdwe6LW3OzxQo6i42NVUlJieLi4tSvX79On3Pz5s0zlMx9paWlyW63KzEx0Wlo8po1a5SUlKTMzEzDCd3XM888o02bNunRRx91Wj9w4IDi4uL017/+1VAydEVPP/20JKmkpETjx4/XAw880PHsgQceUEhIiBYuXKiwsDBTEQEAbqBXr17605/+pJ/97GdO6wcPHtSzzz6r+vp6M8EAF7BTCrdl06ZNWr58ecfui5/+9KdKSUlRXFyc4WTuzWaz3bBYwfV9/PHHKiwsVHR0tOkoHmPdunXKzc1VbGxsx9rkyZMVERGhxMRESqkb6NGjhyIiIvTee+/JarWqra1NmZmZWrp0KbPzcMd9+umnkqTp06frnXfeUWBgoOFEAAB31NbWJl9f307rvr6+jB6Ax6GUgsvsdrtSU1M1d+7cjoLgs88+08yZM3X+/HklJSUZTui+KFZc99BDD6l3796mY3iUK1euKDIystP62LFj1dLSYiCR5ygsLNTatWuVkJCgHTt26NSpUzp9+rQ+/PBDrlzGXfOf//mfpiMAANzYP/7jP2revHnKz8/vGPXxt7/9TUlJSXrmmWcMpwNuDcf34DKLxaKMjAzFx8c7rW/cuFHp6emqrq42lMz9WSwWffTRRx1nwHHztmzZoh07dmjjxo3M87lJiYmJ8vX1ld1ud1pfuHChmpubtXbtWkPJPMdvf/tbvf322/Lx8dHu3bv1xBNPmI4EAADuUzU1NZo8ebL+8pe/dMxRdTgcCg8P186dO9W/f3/DCYGbRykFl/Xo0UOVlZUaMmSI03pVVZXCw8N16dIlQ8ncH8WK60aPHq0TJ06ovb1dISEhnbYuHzlyxFAy95WYmKhNmzZpwIABioqKknR1JpLD4VB8fLzTe/jD4up+980338hms6m4uFjLly9XSUmJtm/frmXLlnF8DwAAGNPe3q7i4mIdP35ckjRs2DD94he/MJwKuHWUUnDZiBEjNHXqVC1evNhp/c0331RBQYG++OILQ8ncH8WK6zIyMm74/I033rhHSTzHd8OTf4yXl5d27dp1l9N4lkcffVQWi0WbN2+WxWKRJBUUFGj27NmKiopSYWGh4YQAAOB+VFxcfN1Lk/7jP/7DUCrg1jFTCi7LyMiQ1WrVnj17OmYj7du3T8XFxdq2bZvhdO4tJibGdASPRel0674bnvxjzpw5o7a2Nnl7e9/lRJ5j5syZWrJkidN7YrVaFR0drenTpxtMBgAA7lcZGRnKzMxUZGQklybB47FTCrflyJEjstvtTttGFyxYoNGjRxtOBuBWBQYGqqKiQoMHDzYdxS199+2SH/wAAIBJ/fr107Jly7jxHF0Cfw6HS65cuaKEhAQ99NBD2rJliw4fPqzDhw9ry5YtFFK4q1pbW7VixQqNGzdOP/nJT9S7d2+n/+A6/kZxbZs2bVJ4eLj8/Pzk5+eniIgIbd682XQsAABwn7p8+TKXrqDLoJSCS3x9ffXBBx+YjuGxKFZcl5GRIbvdLqvVqoaGBiUnJ2vKlCny9vZWenq66XjoYux2u2bNmqXnn39e27Zt07Zt2/RP//RPmjlzpnJyckzHAwAA9yGbzaY//vGPpmMAdwTH9+CyV199VaNGjVJSUpLpKB4nLS1NGzZs0IIFC/S73/1OS5Ys0alTp7R9+3alpaXp9ddfNx3RbYWGhmr16tV64YUXFBAQoIqKio61/fv38w36NgQEBOjo0aMc3/sei8WijIwMxcfHO61v3LhR6enpqq6uNpQMAADcT5KTkzs+bmtr08aNGxUREaGIiIhOlyZxmzI8CYPO4bKwsDBlZmZq3759Gjt2rHr27On0nGLl+rZu3arc3Fy98MILSk9PV2xsrEJDQxUREaH9+/fz3t3A2bNnFR4eLkl68MEH1dDQIEl68cUXlZqaajIauqDa2tprbo9/4oknVFtbayARAAC4H5WXlzv9e9SoUZKkyspKp3VmX8LTUErBZXl5eQoKCuqYJ/V9Xl5eFCs3QLHiuv79+6u2tlYDBw5UaGioioqKNGbMGB06dEjdu3c3Hc+j8UNMZ0OGDNG2bdu0ePFip/WCggKFhYUZSgUAAO43N3ubMuBpKKXgMo6tuI5ixXUvv/yyiouL9Q//8A9KTEzUK6+8ory8PDkcDo6S3iZOc3eWkZEhq9WqPXv2KDo6WpK0b98+FRcXa9u2bYbTAQAAAJ6NmVK4I7gq/dYsWrRIgYGBWrx4sQoKCvTKK68oJCSko1jJzs42HdFjlJaWqrS0VGFhYZo0aZLpOB6tpqZGwcHB6tatm+kobuXIkSOy2+06fvy4JGnYsGFasGABN40CAAAAt4lSCrclLy9POTk5qqqqknR1ztT8+fNls9kMJ/MsFCu4mxobG5Wdna3i4mKdO3dObW1tTs9PnjxpKJl7u3Llil577TWlpqbKYrGYjgMAAAB0OZRScFlaWprsdrsSExM1fvx4SVfLlTVr1igpKUmZmZmGE6Kr2rx5s9avX6/q6mqVlpZq0KBBWrVqlSwWi1566SXT8dxObGysSkpKFBcXp379+nXa0Thv3jxDydxfr169VFFRQSkFAAAA3AWUUnDZww8/rNWrVys2NtZpPT8/X4mJiTp//ryhZJ6BYsU169atU1pamubPn6+33npLlZWVGjx4sP7whz9o48aNDIG8hqCgIBUWFnbMRMLNe/XVVzVq1CjmlQEAAAB3AYPO4bIrV64oMjKy0/rYsWPV0tJiIJHn+GGx0traKulqebBq1SpKqRt49913lZubq5iYGKfZW5GRkVq4cKHBZO7roYceUu/evU3H8EhhYWHKzMzUvn37NHbsWPXs2dPpObeMAgAAAK5jpxRclpiYKF9fX9ntdqf1hQsXqrm5WWvXrjWUzP0NHz5cS5cuVUxMjAICAnT06FENHjxYlZWVeuqpp9hldgN+fn768ssvNWjQIKf3rqqqShEREWpubjYd0e1s2bJFO3bs0MaNG+Xv7286jke50bE9Ly8v5nEBAAAAt4GdUrgteXl5KioqUlRUlCTpwIEDcjgcio+PV3Jycsfrflhc3e+qq6uveXNX9+7d1djYaCCR57BYLKqoqNCgQYOc1j/55BMNGzbMUCr3tnLlSp04cUKPPPKIQkJC5Ovr6/T8yJEjhpK5v+rqatMRAAAAgC6LUgouq6ys1JgxYyRJJ06ckCT16dNHffr0UWVlZcfrfjhUGRQrtyM5OVlz5szRpUuX1N7eroMHDyo/P19ZWVnasGGD6XhuKSYmxnSELuG7jcV8TQMAAADuDEopuOxmB0qfOXNGbW1t8vb2vsuJPAfFiutsNpv8/Pz0u9/9Tk1NTZo6daqCg4P1zjvv6Fe/+pXpeG7pjTfeMB3Bo+Xl5SknJ0dVVVWSrs6Zmj9/vmw2m+FkAAAAgGdjphTuusDAQFVUVGjw4MGmo7iVrVu3Kj09vWOXWXBwsDIyMjRjxgzDyTxHU1OTLl68qL59+5qOgi4qLS1NdrtdiYmJGj9+vCSptLRUa9asUVJSkjIzMw0nBAAAADwXpRTuuu8Po0ZnFCu3prq6Wi0tLQoLC3Nar6qqkq+vr0JCQswEc2Otra3KycnRtm3b5HA4dPnyZafndXV1hpK5v4cfflirV69WbGys03p+fr4SExO5lAAAAAC4DZynAgyorq7uOArk7+/fUUhVVVXp1KlTBpO5v2nTpunzzz/vtH7gwAFNmzbt3gfyABkZGbLb7bJarWpoaFBycrKmTJkib29vpaenm47n1q5cuaLIyMhO62PHjlVLS4uBRAAAAEDXQSkFGECx4rry8nJFR0d3Wo+KilJFRcW9D+QBtm7dqtzcXC1YsEA+Pj6KjY3Vhg0blJaWpv3795uO59bi4uK0bt26Tuv//u//rn/91381kAgAAADoOhh0Dhhwo2Jl7ty5BhJ5Di8vL124cKHTekNDg1pbWw0kcn9nz55VeHi4JOnBBx9UQ0ODJOnFF19UamqqyWgeIS8vT0VFRYqKipJ0tTx2OByKj49XcnJyx+vsdrupiAAAAIBHopTCXcf16Z1RrLhu4sSJysrKUn5+vrp16ybp6sykrKwsPfnkk4bTuaf+/furtrZWAwcOVGhoqIqKijRmzBgdOnRI3bt3Nx3PrVVWVmrMmDGS1HEpQZ8+fdSnTx9VVlZ2vI6vcwAAAMCtY9A57joGnXc2adIk+fn5dSpWrFarGhsb9fHHHxtO6L6OHTumiRMnKigoSBMmTJAk7d27V99++6127dqlESNGGE7ofhYtWqTAwEAtXrxYBQUFeuWVVxQSEiKHw6GkpCRlZ2ebjujxzpw5o+DgYHl7cyoeAAAAuFmUUrjrampqFBwc3FG+gGLldn399ddau3atKioq5Ofnp4iICM2dO1e9e/c2Hc0jlJaWqrS0VGFhYZo0aZLpOF1CYGCgKioqKN8BAACAW8DxPbissbFR2dnZKi4u1rlz59TW1ub0/OTJk5KkAQMGmIjn1oYPH64///nPTsVKfHw8xcpN8vf3V+/evdWvXz9JV+ckUXrevPHjx2v8+PGmY3Qp/H0HAAAAuHWUUnCZzWZTSUmJ4uLi1K9fP2aq3CKKFdeUlZXpueeek5+fn8aNGydJysnJ0dKlSztmJaGzzZs3a/369aqurlZpaakGDRqkVatWyWKx6KWXXjIdDwAAAMB9iON7cFlQUJAKCwuveYscbuxaxcqhQ4fU3NxMsfIjJkyYoCFDhig3N1c+Pld79ZaWFtlsNp08eVJ79uwxnND9rFu3TmlpaZo/f77eeustVVZWavDgwfrDH/6gjRs36tNPPzUd0eMxOw8AAAC4dZRScJnFYtFHH32kYcOGmY7icShWXOfn56fy8nINHTrUaf3YsWOKjIxUU1OToWTua/jw4Vq6dKliYmKcypPKyko99dRTOn/+vOmIHo9SCgAAALh1XBMEl/3+979XWloaJYALysrK9Jvf/KajkJIkHx8f/frXv1ZZWZnBZO4vMDBQDoej03pNTY0CAgIMJHJ/1dXVGj16dKf17t27q7Gx0UCirofjywAAAMCtY6YUXLZy5UqdOHFCjzzyiEJCQuTr6+v0/MiRI4aSub/vipUf7vahWPlxVqtVM2bM0IoVK/TEE09Ikvbt26eUlBTFxsYaTueeLBaLKioqNGjQIKf1Tz75hJ2OdwibjgEAAIBbRykFl8XExJiO4LEoVly3YsUKeXl5KT4+Xi0tLZIkX19fzZo1S9nZ2YbTuafk5GTNmTNHly5dUnt7uw4ePKj8/HxlZWVpw4YNpuN1CceOHVNwcLDpGAAAAIBHYaYUYMDly5eVkpKi9evXX7NY6d69u+GE7q+pqUknTpyQJIWGhsrf399wIve2detWpaend7xnwcHBysjI0IwZMwwnc2+NjY3Kzs5WcXGxzp07p7a2NqfnJ0+eNJQMAAAA8HyUUoBBFCu415qamnTx4kX17dvXdBSPEBsbq5KSEsXFxalfv36dZkfNmzfPUDIAAADA81FKwWWtra3KycnRtm3b5HA4dPnyZafndXV1hpIB+L7q6mq1tLQoLCzMab2qqkq+vr4KCQkxE8wDBAUFqbCwUNHR0aajAAAAAF0Ot+/BZRkZGbLb7bJarWpoaFBycrKmTJkib29vpaenm44H4P9MmzZNn3/+eaf1AwcOaNq0afc+kAd56KGH1Lt3b9MxAAAAgC6JnVJwWWhoqFavXq0XXnhBAQEBqqio6Fjbv3+//vjHP5qOCEBXb3s8cuSIhgwZ4rT+1VdfKTIyUvX19WaCeYAtW7Zox44d2rhxI8drAQAAgDuM2/fgsrNnzyo8PFyS9OCDD6qhoUGS9OKLLyo1NdVkNADf4+XlpQsXLnRab2hoUGtrq4FEnmPlypU6ceKEHnnkEYWEhMjX19fp+ZEjRwwlAwAAADwfpRRc1r9/f9XW1mrgwIEKDQ1VUVGRxowZo0OHDnF7HOBGJk6cqKysLOXn56tbt26Srs6Ey8rK0pNPPmk4nXuLiYkxHQEAAADosji+B5ctWrRIgYGBWrx4sQoKCvTKK68oJCREDodDSUlJys7ONh0RgKRjx45p4sSJCgoK0oQJEyRJe/fu1bfffqtdu3ZpxIgRhhMCAAAAuB9RSuGOKS0tVWlpqcLCwjRp0iTTcQB8z9dff601a9bo6NGj8vPzU0REhObOncsQbwAAAADGUEoBAHAdra2tysnJ0bZt2+RwOHT58mWn53V1dYaSAQAAAJ7P23QAeLbNmzcrOjpawcHBOn36tCRp1apV2rFjh+FkAL6vvr5eK1eulM1mk81mU05OTsflBLi+jIwM2e12Wa1WNTQ0KDk5WVOmTJG3t7fS09NNxwMAAAA8GqUUXLZu3TolJyfr+eefV319fcctXkFBQVq1apXZcAA6lJWVKTQ0VDk5Oaqrq1NdXZ3sdrtCQ0O5Pe5HbN26Vbm5uVqwYIF8fHwUGxurDRs2KC0tTfv37zcdDwAAAPBoHN+Dy4YPH66lS5cqJiZGAQEBOnr0qAYPHqzKyko99dRTOn/+vOmIACRNmDBBQ4YMUW5urnx8rl662tLSIpvNppMnT2rPnj2GE7qvnj176vjx4xo4cKD69eunwsJCjRkzRidPntTo0aPZbQYAAADcBnZKwWXV1dUaPXp0p/Xu3bursbHRQCIA11JWVqbf/OY3HYWUJPn4+OjXv/61ysrKDCZzf/3791dtba0kKTQ0VEVFRZKkQ4cOqXv37iajAQAAAB6PUgous1gsqqio6LT+ySefaNiwYfc+EIBrCgwMlMPh6LReU1OjgIAAA4k8x8svv6zi4mJJUmJiolJTUxUWFqb4+HglJCQYTgcAAAB4Np8ffwlwbcnJyZozZ44uXbqk9vZ2HTx4UPn5+crKytKGDRtMxwPwf6xWq2bMmKEVK1boiSeekCTt27dPKSkpio2NNZzOvWVnZ3d8bLVaNXDgQJWWliosLEyTJk0ymAwAAADwfMyUwm3ZunWr0tPTdeLECUlScHCwMjIyNGPGDMPJAHzn8uXLSklJ0fr169XS0iJJ8vX11axZs5Sdnc0xNAAAAABGUErhjmhqatLFixfVt29f01EAXEdTU1NHgRwaGip/f3/DiTzD5s2btX79elVXV6u0tFSDBg3SqlWrZLFY9NJLL5mOBwAAAHgsZkrBZdXV1aqqqpIk+fv7dxRSVVVVOnXqlMFkAK7F399f4eHhCg8Pp5C6SevWrVNycrKef/551dfXq7W1VZIUFBSkVatWmQ0HAAAAeDhKKbhs2rRp+vzzzzutHzhwQNOmTbv3gQDgDnv33XeVm5urJUuWqFu3bh3rkZGR+uKLLwwmAwAAADwfpRRcVl5erujo6E7rUVFR17yVDwA8TXV1tUaPHt1pvXv37mpsbDSQCAAAAOg6KKXgMi8vL124cKHTekNDQ8cRFwDwZBaL5Zol+yeffKJhw4bd+0AAAABAF+JjOgA818SJE5WVlaX8/PyOYy2tra3KysrSk08+aTgdANy+5ORkzZkzR5cuXVJ7e7sOHjyo/Px8ZWVlacOGDabjAQAAAB6N2/fgsmPHjmnixIkKCgrShAkTJEl79+7Vt99+q127dmnEiBGGEwLA7du6davS09M7bi4MDg5WRkaGZsyYYTgZAAAA4NkopXBbvv76a61Zs0ZHjx6Vn5+fIiIiNHfuXPXu3dt0NAC4o5qamnTx4sWOm0YBAAAA3B5KKQAArqO6ulotLS0KCwtzWq+qqpKvr69CQkLMBAMAAAC6AGZK4bbU19crLy9Px48flyQ9/vjjSkhIUK9evQwnA4DbN23aNCUkJHQqpQ4cOKANGzZo9+7dZoIBAAAAXQA7peCysrIyPffcc/Lz89O4ceMkSYcOHVJzc7OKioo0ZswYwwkB4PYEBgbqyJEjGjJkiNP6V199pcjISNXX15sJBgAAAHQB7JSCy5KSkjR58mTl5ubKx+fqp1JLS4tsNpvmz5+vPXv2GE4IALfHy8tLFy5c6LTe0NCg1tZWA4kAAACAroOdUnCZn5+fysvLNXToUKf1Y8eOKTIyUk1NTYaSAcCdMWnSJPn5+Sk/P1/dunWTJLW2tspqtaqxsVEff/yx4YQAAACA52KnFFwWGBgoh8PRqZSqqalRQECAoVQAcOe8/fbbmjhxoh577DFNmDBBkrR37159++232rVrl+F0AAAAgGfzNh0AnstqtWrGjBkqKChQTU2Nampq9P7778tmsyk2NtZ0PAC4bcOHD9ef//xn/cu//IvOnTunCxcuKD4+Xl9++aVGjBhhOh4AAADg0Ti+B5ddvnxZKSkpWr9+vVpaWiRJvr6+mjVrlrKzs9W9e3fDCQEAAAAAgLuilMJta2pq0okTJyRJoaGh8vf3N5wIAO6c+vp65eXl6fjx45Kkxx9/XAkJCerVq5fhZAAAAIBno5QCAOA6ysrK9Nxzz8nPz0/jxo2TJB06dEjNzc0qKirSmDFjDCcEAAAAPBelFAAA1zFhwgQNGTJEubm58vG5ejdIS0uLbDabTp48qT179hhOCAAAAHguSikAAK7Dz89P5eXlnW4ZPXbsmCIjI9XU1GQoGQAAAOD5uH0PAIDrCAwMlMPh6LReU1OjgIAAA4kAAACAroNSCgCA67BarZoxY4YKCgpUU1Ojmpoavf/++7LZbIqNjTUdDwAAAPBoPqYDAADgrlasWCEvLy/Fx8erpaVFkuTr66tZs2YpOzvbcDoAAADAszFTCgCAH9HU1KQTJ05IkkJDQ+Xv7284EQAAAOD5KKUAAAAAAABwzzFTCgAAAAAAAPccpRQAAAAAAADuOUopAAAAAAAA3HOUUgAAAAAAALjnKKUAAAAAAABwz1FKAQAAAAAA4J6jlAIAAAAAAMA9RykFAAAAAACAe+7/AY5qoXRjjyCqAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# The Polynomials aren't having much of an effect, their coefficients are almost 0.\n",
    "# Let's try one-hot encoding without the polynomial, we didn't try this yet\n",
    "results_df, iteration_7 = dw.iterate_model(X2_train, X2_test, y2_train, y2_test,\n",
    "        transformers=['ohe', 'log'], model='linreg',\n",
    "        iteration='7', note='X2. Test size: 0.25, Pipeline: OHE > Log > LinReg',\n",
    "        plot=True, lowess=True, coef=True, perm=True, vif=True, decimal=2,\n",
    "        save=True, save_df=results_df, config=my_config)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-10 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-10 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-10 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-10 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-10 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-10 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-10 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-10 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-10 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-10 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-10 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-10 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-10 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-10 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-10 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-10 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-10 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-10 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-10 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-10 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-10 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-10 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-10 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-10 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-10 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-10 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-10 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-10 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-10 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-10 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-10 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-10 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-10 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-10 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-10 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-10 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-10 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-10 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-10 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-10 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-10 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-10 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-10\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;ohe_log&#x27;,\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;ohe&#x27;,\n",
       "                                                  OneHotEncoder(drop=&#x27;if_binary&#x27;,\n",
       "                                                                handle_unknown=&#x27;ignore&#x27;),\n",
       "                                                  [&#x27;ocean_proximity&#x27;]),\n",
       "                                                 (&#x27;log&#x27;, LogTransformer(),\n",
       "                                                  [&#x27;total_rooms&#x27;,\n",
       "                                                   &#x27;total_bedrooms&#x27;,\n",
       "                                                   &#x27;population&#x27;,\n",
       "                                                   &#x27;households&#x27;])])),\n",
       "                (&#x27;linreg&#x27;, LinearRegression())])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-76\" type=\"checkbox\" ><label for=\"sk-estimator-id-76\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;ohe_log&#x27;,\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;ohe&#x27;,\n",
       "                                                  OneHotEncoder(drop=&#x27;if_binary&#x27;,\n",
       "                                                                handle_unknown=&#x27;ignore&#x27;),\n",
       "                                                  [&#x27;ocean_proximity&#x27;]),\n",
       "                                                 (&#x27;log&#x27;, LogTransformer(),\n",
       "                                                  [&#x27;total_rooms&#x27;,\n",
       "                                                   &#x27;total_bedrooms&#x27;,\n",
       "                                                   &#x27;population&#x27;,\n",
       "                                                   &#x27;households&#x27;])])),\n",
       "                (&#x27;linreg&#x27;, LinearRegression())])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-77\" type=\"checkbox\" ><label for=\"sk-estimator-id-77\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;ohe_log: ColumnTransformer<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.compose.ColumnTransformer.html\">?<span>Documentation for ohe_log: ColumnTransformer</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>ColumnTransformer(force_int_remainder_cols=False, remainder=&#x27;passthrough&#x27;,\n",
       "                  transformers=[(&#x27;ohe&#x27;,\n",
       "                                 OneHotEncoder(drop=&#x27;if_binary&#x27;,\n",
       "                                               handle_unknown=&#x27;ignore&#x27;),\n",
       "                                 [&#x27;ocean_proximity&#x27;]),\n",
       "                                (&#x27;log&#x27;, LogTransformer(),\n",
       "                                 [&#x27;total_rooms&#x27;, &#x27;total_bedrooms&#x27;, &#x27;population&#x27;,\n",
       "                                  &#x27;households&#x27;])])</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-78\" type=\"checkbox\" ><label for=\"sk-estimator-id-78\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">ohe</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;ocean_proximity&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-79\" type=\"checkbox\" ><label for=\"sk-estimator-id-79\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;OneHotEncoder<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.OneHotEncoder.html\">?<span>Documentation for OneHotEncoder</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>OneHotEncoder(drop=&#x27;if_binary&#x27;, handle_unknown=&#x27;ignore&#x27;)</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-80\" type=\"checkbox\" ><label for=\"sk-estimator-id-80\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">log</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;total_rooms&#x27;, &#x27;total_bedrooms&#x27;, &#x27;population&#x27;, &#x27;households&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-81\" type=\"checkbox\" ><label for=\"sk-estimator-id-81\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">LogTransformer</label><div class=\"sk-toggleable__content fitted\"><pre>LogTransformer()</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-82\" type=\"checkbox\" ><label for=\"sk-estimator-id-82\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">remainder</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;longitude&#x27;, &#x27;latitude&#x27;, &#x27;housing_median_age&#x27;, &#x27;median_income&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-83\" type=\"checkbox\" ><label for=\"sk-estimator-id-83\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">passthrough</label><div class=\"sk-toggleable__content fitted\"><pre>passthrough</pre></div> </div></div></div></div></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-84\" type=\"checkbox\" ><label for=\"sk-estimator-id-84\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;LinearRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.linear_model.LinearRegression.html\">?<span>Documentation for LinearRegression</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>LinearRegression()</pre></div> </div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('ohe_log',\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder='passthrough',\n",
       "                                   transformers=[('ohe',\n",
       "                                                  OneHotEncoder(drop='if_binary',\n",
       "                                                                handle_unknown='ignore'),\n",
       "                                                  ['ocean_proximity']),\n",
       "                                                 ('log', LogTransformer(),\n",
       "                                                  ['total_rooms',\n",
       "                                                   'total_bedrooms',\n",
       "                                                   'population',\n",
       "                                                   'households'])])),\n",
       "                ('linreg', LinearRegression())])"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the pipeline\n",
    "iteration_7"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Iteration 8: Ridge with Log, Poly3, Standard and CV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "ITERATION 8 RESULTS\n",
      "\n",
      "Pipeline: log_poly3 -> stand -> ridge\n",
      "Note: X1. Test size: 0.25, Pipeline: Log > Poly3 > Stand > Ridge. CV: 5\n",
      "May 30, 2024 09:17 AM UTC\n",
      "\n",
      "Cross Validation:\n",
      "\n",
      "Cross-Validation (R^2) Scores for 5 Folds:\n",
      "Fold 1: 0.63\n",
      "Fold 2: 0.64\n",
      "Fold 3: 0.63\n",
      "Fold 4: 0.63\n",
      "Fold 5: 0.65\n",
      "Average: 0.64\n",
      "Standard Deviation: 0.00\n",
      "\n",
      "Predictions:\n",
      "                          Train            Test\n",
      "MSE:            3,288,332,850.84 3,283,356,079.58\n",
      "RMSE:                 57,343.99       57,300.58\n",
      "MAE:                  42,229.62       42,182.13\n",
      "R^2 Score:                 0.64            0.65\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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sbCxpaWltuiServO5tbKyMnbs2MGNN95IZGRkcHr//v25/PLLWb58eZtlfvvb37b4e9SoUVRXVwfT0zvSPDLk7Nmz+fDDD/nPf/7D0KFD+dWvfsXmzZtPeN8FQRCEs2vx4sWEhYVx+eWXt7i2DRkyhJCQkOC1rTkTeNmyZXg8ni7dh5tvvhmTyUR8fDxXXHEFVquV999/n2HDhgGBrnWffPIJ06ZNQ5KkFvs5adIkrFZrsE0RHh5OSUlJp7pkNfv6669xu93cfffdLbrmtR5o5ESd7PU+PDwcm83G6tWrT2n7XaWmpoY1a9ZwzTXXBN9HVVUV1dXVTJo0ifz8fI4cOdJimVtvvbVN3a6jj4fH46G6uprevXsTHh5+0qUZli9fTmxsLNdee21wmkql4p577qGxsZH169e3mP9U7gkSEhK46KKL+NOf/sRnn33GAw88wAcffHBWB0oSLmyi+54gnAYJCQntFjDcu3cvTz75JGvWrGlz02y1Wo+73qSkpBZ/N1+MOhOwab1s8/LNy1ZWVuJwOOjdu3eb+dqb1hGtVsvSpUuBQF2nl19+mcrKyhYX8Pz8fAAuu+yydtdhNBqBQODgpZde4ne/+x0xMTEMHz6cqVOncsMNNxxzFJvDhw/Tu3fvNrUSMjIyOv0+2vOvf/2LV199lZycnBYN2Z49ex5zuZdffpm5c+fSo0cPhgwZwuTJk7nhhhvo1atXh8u43W5qampaTDOZTF1S0DQ/Px9JkkhLS2v39dZp36frfG7t8OHDQPufU1ZWFitXrmxTZPRY34nm86g9d911F5s3b2bbtm3BUWauueYa+vTpw7333ssPP/xwwvsvCIIgnD35+flYrVbMZnO7r1dWVgIwZswYZs2axfz583nttdcYO3Ys06dP57rrrjvlUeyefvppRo0aRWNjI5999hkfffRRi5HMLBYLdXV1vPPOO7zzzjvH3M9HHnmEr7/+mosuuojevXszceJErrvuOkaOHNnh9puvo62v7yaTqUUA40Sd7PX+zjvv5OOPP+bKK68kISGBiRMncs0113DFFVccc3sWi6VFvaqQkJBjdv3vrAMHDiBJEk899RRPPfVUu/NUVlaSkJAQ/Lu9Np7D4WDBggW8++67HDlyBEmSgq+dTPsHAp9dWlpam5Hvmrv7NX+2zU72nuD7779n6tSpbN68maFDhwIwffp0jEYj8+fP5+abbyY7O/uk3oMgnCwRlBKE06C9IoF1dXWMGTMGo9HIs88+S2pqKlqtlm3btvHII4/g9/uPu96OAhJHXwxPx7InQqFQMGHChODfkyZNIjMzk9tvvz1YRLL5vb7//vvtBpeOHj3wvvvuY9q0aXz++eesXLmSp556igULFrBmzZouGR2kowLuPp+vxTH7z3/+w4033sj06dN56KGHMJvNKBQKFixY0KaAaWvXXHMNo0aN4rPPPmPVqlW88sorvPTSS3z66acdZqFt3LiRcePGtZhWWFjYYR2tE+H3+5HJZKxYsaLd86J1w+90nc9d4WTOa7fbzT/+8Q8efvjhFo0/lUrFlVdeyZtvvonb7RajOgqCIJxD/H4/ZrOZDz74oN3Xm2sqymQylixZwubNm1m6dCkrV67k5ptv5tVXX2Xz5s2nFPzo169fsA00ffp07HY7t956K5deeik9evQIXht/9atfMXfu3HbX0Vz7KCsri9zcXJYtW8ZXX33FJ598wltvvcXTTz/N/PnzT3ofmx2r/XO0U7nem81mduzYwcqVK1mxYgUrVqzg3Xff5YYbbmhTwPtow4YNaxGE+f3vf39SheZba97XBx98kEmTJrU7T+sHse21ge6++27effdd7rvvPkaMGEFYWBgymYw5c+Z06/YPwF//+ldiYmKCAalmv/jFL3jmmWfYuHGjCEoJZ5wISgnCGbJu3Tqqq6v59NNPGT16dHB6YWHhWdyrn5nNZrRaLQcOHGjzWnvTOisuLo7777+f+fPns3nzZoYPHx7sRmg2m1sEsDqSmprK7373O373u9+Rn5/PwIEDefXVV/nPf/7T7vzJycns2bMHSZJaNLpyc3PbzBsREUFdXV2b6YcPH26RybRkyRJ69erFp59+2mKdv//974+7/xA4DnfeeSd33nknlZWVDB48mOeff77DoNSAAQPapLsfKzusPR01OFNTU5EkiZ49e5Kenn5C62x2IudzZ0duTE5OBtr/nHJycoiOju6SoZirq6vxer3tjhrk8Xjw+/2dGlFIEARB6D5SU1P5+uuvGTlyZKdGEBs+fDjDhw/n+eefZ9GiRVx//fV89NFH/OY3vznpEYdbe/HFF/nss894/vnnWbhwISaTidDQUHw+X6faPwaDgV/+8pf88pe/xO12M3PmTJ5//nkee+wxtFptm/mbr6P5+fkt2jAWi6VNBk1zZk1dXV2LwU1aZ+ScavtVrVYzbdo0pk2bht/v58477+Svf/0rTz31VIeZ+B988AEOhyP497Eyy9vT0efXvB6VStWp49+RJUuWMHfuXF599dXgNKfT2aY9eSLnUXJyMrt27cLv97d4YNbcPbL5sz1VFRUVHbZ/ALxeb5dsRxBOhKgpJQhnSPMTjaOfYLjdbt56662ztUstNGc4ff755y1qHx04cIAVK1ac0rrvvvtu9Ho9L774IhDInjIajbzwwgvt1nOwWCwA2O12nE5ni9dSU1MJDQ3F5XJ1uL3JkydTWlrKkiVLgtPsdnu7qfKpqals3ry5xag0y5Yto7i4uMV87X1+P/zwA5s2bepwPyDwxLF1KrfZbCY+Pv6Y7yEiIoIJEya0+NdeA/RYmgM4rRtJM2fORKFQMH/+/DZP1CRJorq6+rjrPpHz2WAwdCqdPS4ujoEDB/Kvf/2rxT7v2bOHVatWMXny5OOuozPMZjPh4eF89tlnLT73xsZGli5dSmZmphgSWRAE4RxzzTXX4PP5eO6559q85vV6g9eV2traNte+5hF0m6/Ler0eaHv9PFGpqanMmjWL9957j/LychQKBbNmzeKTTz5hz549beZvbv8Aba7FarWa7OxsJEnqsBbWhAkTUKlUvPHGGy3e45/+9Kd29w1gw4YNwWk2m61NBtOptF9bvwe5XB7MBDtWG2jkyJEt2j8nGpTq6PMzm82MHTuWv/71r5SVlbVZ7ujjfywKhaLNOfTGG2+0CfZ01A5rz+TJkykvL+e///1vcJrX6+WNN94gJCSEMWPGdGrfjic9PZ2KigrWrVvXYvqHH34I0CW9EAThRIlMKUE4Qy655BIiIiKYO3cu99xzDzKZjPfff7/Lu8+dimeeeYZVq1YxcuRI7rjjDnw+H2+++SZ9+/Zlx44dJ73eqKgobrrpJt566y32799PVlYWb7/9Nr/+9a8ZPHgwc+bMwWQyUVRUxJdffsnIkSN58803ycvLY/z48VxzzTVkZ2ejVCr57LPPqKioYM6cOR1u79Zbb+XNN9/khhtuYOvWrcTFxfH+++8HGylH+81vfsOSJUu44ooruOaaaygoKOA///lPi6LwAFOnTuXTTz9lxowZTJkyhcLCQhYuXEh2djaNjY0d7ktDQwOJiYnMnj2bAQMGEBISwtdff81PP/3U4gnb6TBkyBAAnnjiCebMmYNKpWLatGmkpqbyhz/8gccee4xDhw4xffp0QkNDKSws5LPPPuO2227jwQcfPOa6T+R8HjJkCP/973954IEHGDZsGCEhIUybNq3d9b7yyitceeWVjBgxgltuuQWHw8Ebb7xBWFhYl6TuQ6Ax+eCDD/Lkk08yfPhwbrjhBnw+H//4xz8oKSnpMANPEARB6L7GjBnD7bffzoIFC9ixYwcTJ05EpVKRn5/P4sWLef3115k9ezb/+te/eOutt5gxYwapqak0NDTwt7/9DaPRGHz4odPpyM7O5r///S/p6elERkbSt29f+vbte8L79dBDD/Hxxx/zpz/9iRdffJEXX3yRtWvXcvHFF3PrrbeSnZ1NTU0N27Zt4+uvvw7Wk5w4cSKxsbGMHDmSmJgY9u/fz5tvvsmUKVMIDQ1td1smk4kHH3yQBQsWMHXqVCZPnsz27dtZsWIF0dHRLeadOHEiSUlJ3HLLLTz00EMoFAr++c9/BttjzU6l/fqb3/yGmpoaLrvsMhITEzl8+DBvvPEGAwcODNZKOh2O9fn95S9/4dJLL6Vfv37ceuut9OrVi4qKCjZt2kRJSQk7d+487vqnTp3K+++/T1hYGNnZ2WzatImvv/6aqKioFvMNHDgQhULBSy+9hNVqRaPRcNlll7Vb9+y2227jr3/9KzfeeCNbt24lJSWFJUuW8P333/OnP/2pw8/8RN111128++67TJs2jbvvvpvk5GTWr1/Phx9+yOWXX87FF1/cJdsRhBNy5gb6E4TzT+vhiCUpMMRrR0P4fv/999Lw4cMlnU4nxcfHSw8//LC0cuXKNsPFth5St3n411deeaXNOmk15G17Q/wC0rx589osm5yc3GJ4YEmSpG+++UYaNGiQpFarpdTUVOnvf/+79Lvf/U7SarUdHIWfzZ07VzIYDO2+VlBQICkUihbbW7t2rTRp0iQpLCxM0mq1UmpqqnTjjTdKW7ZskSRJkqqqqqR58+ZJmZmZksFgkMLCwqSLL75Y+vjjj1usu/WwupIkSYcPH5Z+8YtfSHq9XoqOjpbuvffe4LDQrYfmffXVV6WEhARJo9FII0eOlLZs2dJmnX6/X3rhhRek5ORkSaPRSIMGDZKWLVvW5rOSpJaficvlkh566CFpwIABUmhoqGQwGKQBAwZIb7311nGP54loHo568eLFLaY/99xzUkJCgiSXy9sM8fzJJ59Il156qWQwGCSDwSBlZmZK8+bNk3Jzc4PzdMX53NjYKF133XXB4Yebj1fzef3uu++2WO/XX38tjRw5UtLpdJLRaJSmTZsm7du3r8U8zee5xWJpMb29oaw78sEHH0gXXXSRFB4eLul0Ouniiy+WlixZctzlBEEQhLOvvTaYJEnSO++8Iw0ZMkTS6XRSaGio1K9fP+nhhx+WSktLJUmSpG3btknXXnutlJSUJGk0GslsNktTp04Ntj2abdy4URoyZIikVqvbtLVa6+ga3Gzs2LGS0WiU6urqJEmSpIqKCmnevHlSjx49JJVKJcXGxkrjx4+X3nnnneAyf/3rX6XRo0dLUVFRkkajkVJTU6WHHnpIslqtwXnau+b5fD5p/vz5UlxcnKTT6aSxY8dKe/bsabfNt3XrVuniiy+W1Gq1lJSUJP3f//1fu+s82fbrkiVLpIkTJ0pmszm4jdtvv10qKyvr8FiejOTkZGnKlCktph3r8ysoKJBuuOEGKTY2VlKpVFJCQoI0derUFm2A5uPw008/tdlebW2tdNNNN0nR0dFSSEiINGnSJCknJ6fdY/y3v/1N6tWrl6RQKFocr/barhUVFcH1qtVqqV+/fm3aSCdyT9CRnJwcafbs2cHzLzk5WXrwwQclm8123GUF4XSQSVI3StMQBKFbmj59Onv37g2OmicIgiAIgiAIgiAIp0rUlBIEoYWjC0tCoFjm8uXLGTt27NnZIUEQBEEQBEEQBOG8JDKlBEFoIS4ujhtvvJFevXpx+PBh3n77bVwuF9u3byctLe1s754gCIIgCIIgCIJwnhCFzgVBaOGKK67gww8/pLy8HI1Gw4gRI3jhhRdEQEoQBEEQBEEQBEHoUiJTShAEQRAEQRAEQRAEQTjjRE0pQRAEQRAEQRAEQRAE4YwTQSlBEARBEARBEARBEAThjBM1pboZv99PaWkpoaGhyGSys707giAIgtCtSJJEQ0MD8fHxyOXi2ZrwM9GGEgRBEISOddc2lAhKdTOlpaX06NHjbO+GIAiCIHRrxcXFJCYmnu3dELoR0YYSBEEQhOPrbm0oEZTqZkJDQ4HAiWI0Gs/y3giCIAhC91JfX0+PHj2C10tBaCbaUIIgCILQse7ahhJBqW6mOd3caDSKBpUgCIIgdEB0zxJaE20oQRAEQTi+7taG6j4dCQVBEARBEARBEARBEIQLhghKCYIgCIIgCIIgCIIgCGecCEoJgiAIgiAIgiAIgiAIZ5wISgmCIAiCIAiCIAiCIAhnnAhKCYIgCIIgCIIgCIIgCGecCEoJgiAIgiAIgiAIgiAIZ5wISgmCIAiCIAiCIAiCIAhnXLcLSr399tv0798fo9GI0WhkxIgRrFixIvi60+lk3rx5REVFERISwqxZs6ioqGixjqKiIqZMmYJer8dsNvPQQw/h9XqPud2amhquv/56jEYj4eHh3HLLLTQ2NraYZ9euXYwaNQqtVkuPHj14+eWX26xn8eLFZGZmotVq6devH8uXLz+FoyGcbk6PD5vLi9PjO9u7IgiCIAiC0K2JdpMgCILQ1bpdUCoxMZEXX3yRrVu3smXLFi677DKuuuoq9u7dC8D999/P0qVLWbx4MevXr6e0tJSZM2cGl/f5fEyZMgW3283GjRv517/+xXvvvcfTTz99zO1ef/317N27l9WrV7Ns2TI2bNjAbbfdFny9vr6eiRMnkpyczNatW3nllVd45plneOedd4LzbNy4kWuvvZZbbrmF7du3M336dKZPn86ePXu6+CgJp8rj81NcY2fxlhL+/E0+i7eUUFxjx+Pzn+1dEwRBEARB6FZEu0kQBEE4XWSSJElneyeOJzIykldeeYXZs2djMplYtGgRs2fPBiAnJ4esrCw2bdrE8OHDWbFiBVOnTqW0tJSYmBgAFi5cyCOPPILFYkGtVrdZ//79+8nOzuann35i6NChAHz11VdMnjyZkpIS4uPjefvtt3niiScoLy8PruPRRx/l888/JycnB4Bf/vKX2Gw2li1bFlz38OHDGThwIAsXLuzUe62vrycsLAyr1YrRaDz5gyYcU3GNnReW76ek1hGclhih4/HJWfSI1J/FPRMEQRCORVwnhY6Ic+P0Ee2mjjk9Pnx+CYVchlalONu7IwiC0KHuep3sdplSR/P5fHz00UfYbDZGjBjB1q1b8Xg8TJgwIThPZmYmSUlJbNq0CYBNmzbRr1+/YEAKYNKkSdTX1wezrVrbtGkT4eHhwYAUwIQJE5DL5fzwww/BeUaPHt0iqDVp0iRyc3Opra0NznP0vjXP07xvQvfg9PhYl2tp0bACKKl1sCHPIlLSBUEQBEEQmoh2U/tE9pggCELXUJ7tHWjP7t27GTFiBE6nk5CQED777DOys7PZsWMHarWa8PDwFvPHxMRQXl4OQHl5eYuAVPPrza+1p7y8HLPZ3GKaUqkkMjKyxXp79uzZ4XojIiI63HZH2wVwuVy4XK7g3/X19R3OK3QNn1+ipNbe7mtFNXZ8/m6fPCgIgiAIgnBGiHZT+8qtzlbZY9VsLKg677LHRCaYIAinW7fMlMrIyGDHjh388MMP3HHHHcydO5d9+/ad7d06LRYsWEBYWFjwX48ePc72Lp33FHIZiRHtNxaSIvUo5LIzvEeCIAiCIAjdk2g3tXUhZI+JTDBBEM6UbhmUUqvV9O7dmyFDhrBgwQIGDBjA66+/TmxsLG63m7q6uhbzV1RUEBsbC0BsbGyb0fia/26ep7XY2FgqKytbTPN6vdTU1JzQejuap6PtAjz22GNYrdbgv+Li4g7nFbqGVqVgbIaJxAhdi+mJETpGp5vEUyBBEARBEIQmot3U1oWQPdacCfbxlmI2FlTz8ZZiXli+n3Kr82zvmiAI55luGZRqze/343K5GDJkCCqVim+++Sb4Wm5uLkVFRYwYMQKAESNGsHv37hZBptWrV2M0GsnOzm53/SNGjKCuro6tW7cGp61Zswa/38/FF18cnGfDhg14PJ4W683IyCAiIiI4z9H71jxP8761R6PRYDQaW/wTTr/YMC2PT85izrAeXJIaxZxhPXh8chaxYdqzvWuCIAiCIAjdimg3tXS+Z49dCJlggiB0H92uptRjjz3GlVdeSVJSEg0NDSxatIh169axcuVKwsLCuOWWW3jggQeIjIzEaDRy9913M2LECIYPHw7AxIkTyc7O5te//jUvv/wy5eXlPPnkk8ybNw+NRtPuNrOysrjiiiu49dZbWbhwIR6Ph7vuuos5c+YQHx8PwHXXXcf8+fO55ZZbeOSRR9izZw+vv/46r732WnA99957L2PGjOHVV19lypQpfPTRR2zZsoV33nnn9B844YSoFHJ6ROqZNSRR9JMXBEEQBEE4BtFuaqk5e2xjQVWbEQnPh+yxCyETTBCE7qPbBaUqKyu54YYbKCsrIywsjP79+7Ny5Uouv/xyAF577TXkcjmzZs3C5XIxadIk3nrrreDyCoWCZcuWcccddzBixAgMBgNz587l2WefDc5z6NAhevbsydq1axk7diwAH3zwAXfddRfjx48Prv/Pf/5zcJmwsDBWrVrFvHnzGDJkCNHR0Tz99NPcdtttwXkuueQSFi1axJNPPsnjjz9OWloan3/+OX379j3NR004Wed6o0EQBEEQBOFMEe2mnzVnj23Is1BUYycpUs/odNN5kT32cyZYdZvXzodMMEEQuheZJEkXXKh77dq1zJw5k4MHDwa73nUX9fX1hIWFYbVaRVc+QRAEQWhFXCeFjohzQzgbztfR6Ypr7K1GFwxkgp1vowsKwoWku14nu12m1JmwfPlyHn/88W4XkBIEQRAEQRAE4dxxPgWijnY+Z4IJgtC9XJBBqVdeeeVs74IgdHvn65M/QRAEQRAE4dhEHTFBEM6UCzIoJQhCxzw+P+VWZ9OoK3YSI/SMzQg8GVMpzokBOwVBEARBEIQucD4EosSDVkHo3kRQShCEFsqtzlY1BKrZWFAlaggIgiAIgiAI5wzxoFUQzg0iKCUIQpDT42u6cDtaTC+pdbAhz8KsIYniCZMgCIIgCIJwVnUm+0k8aBWEc4MISgmCEOTzS5TU2tt9rajGjs9/wQ3WKQiCIAiCIHQTnc1+Eg9auz/RrVJoJoJSgiAEKeQyEiP0QHWb15Ii9SjksjO/U4IgCIIgCGeZuIHuHjqb/SQetHZfolul0JoISgmCEKRVKRibYWJjQVWLJ0uJETpGp5tEI0wQBEEQhAuKuIHuWqcS3DuR7CfxoLX7Et0qhdZEUEoQhBZiw7Q8PjmLDXkWimrsJEXqGZ0eaHwJgiAIgiB0B2cqc0ncQHeNrgjunUj2k3jQ2j2JbpVCe0RQShCEFlQKOT0i9cwakijS1AVBEARB6FbOZOaSuIHuOl0R3DvR7CfxoLX7Ed0qhfaIoJQgCO0SjSxBEARBELqbM5m5JG6gu0ZXBfdONPtJPGjtfkS3SqE9IiglCIIgCIIgCEK3d6Yzl8QNdNfoyuDeyWQ/iUBU9yG6VQrtEUEpQRCEs0CM4iMIgiAIJ+ZMZy6JG+iu0ZXBPZH9dO4T3SqF1kRQShAE4QwSo/gIgiAIwslRK+TMGdaDGYMSqLV72HKohvV5FhweH4kRutOyTXEDfepOR3BPBKLOXSKwKLQmglKCIAhnkBjFRxAEQRBOnMfnp7zeyfq8KnYfqSMpUs/YDDMZsaF8sPkwQ1Mi2VViJTFC16UPes7mDfTZzqruyu2L4J7QmghECc1EUEoQBOEMEaP4CIIgCMLJKbM6ef7LfZTUOvD6JDYdrObb/Cr+MKMvf5jRj9zyBhauL8AUqjktD3rO5PX5bGdVn47ti+wYQRA6IoJSgiAIZ4gYxUcQBEEQTozH58fm8vLV7jK2Hq5Fo1Rg1CmJ0KtpdHnZeKCaS9OiWbi+AJfX3+JBD3DSAZCzmaV0trOqT+f2RSBKEITWRAETQRCEM+TnQp9tiVF8BEEQzk1Ojw+by4vT4zvbu3JGnan3XW51UtXoZm9ZPTaXjxqbmyNN2VJ2t4+dJXX4/RIurz+4TFGNHafHx+ItJfz5m3wWbymhuMaOx+c/xpYCPD4/xTX2k1r2ZLQ+jsfLqj7dx/tsb18QhAuPyJQSBEE4Q8QoPoIgCOePs93F6mw5k++7OUDS2xxCr2jDUfsg0eDyEKJRkmoKodbuabFcQriOwiobH28pbprS+UyfM5Wl1NFxjA7RUG51tLvMmciqFlndZ8fZrh8mCGeTCEoJgiCcQaLQpyAIwvnhbHexOlsqrE7W51XS2xzKsJQIau0e1udVMjbdTGIXvO+jb86bAyR1djdjM8ys2lfBQYsNALfXT894PZdlmlmbUxlcPiFcy/BeUazcW95ivZYGF0dqHUQa1ADt3vyfydqPHZ0/j03O4tI0Exvyq9oscyayqn/O6q4+K9u/0JyPwW0RYBNOlAhKCYJwwTuTF09R6FMQBOHcd64OXHGs611nroVOjw+7x0e/hHDW5VZysMpGr2gDYzPMODw+nB7fSb/v9m7Opw2IIzFCxxc7SsmKM/LCjH6sz7NQYGmkb3wYk/rGEqZVYgrVcElqFEmRekalmaixu1mfZwmuW6OU89sxqYTpVXyyrYQjtY52b/5PJEvoVNoONpeXtbmVFNXYkct+DvKU1Dr4Ns/ClP6B9302sqrP1azuczUQcj4Ft8/HAJtwZoiglCCcgHP1gie072xePMX5IwiCcO4617o4Het6B3T6Wigj8N4f+3Q3hVW24PRV+yr449UDOJUcmvZuzmUyiVFpJjYWVLNwfQFj0k0MS4lkcr84okPUhOsDWU/TByUE22cKmYzvDlS1qDE1Jt2EKVTDs0v3Uu/0NgWC2t78Hy9LCMDh9mFpdLH+JNoOzZ+DXC5j7xErtTY3oVoVKoUMWVNwqqjGjlIuP6tZ1edSVve5HAg5V4PbHTmfAmzCmSWCUoLQCefyBU/omLh4CoIgXLhO5UHTudbFqaPr3fMz+mJz+Tp9LfT6Jb7Ns7QISAEctNj4Lr+KpEg9mpPYv9Y3534pENT7dNsRLu4ZxWOTs/i2KUBy0NJIYoQOg+bn25jWn9+otGi+zf95fUNTItmQb6HG5kGt/Lnd1vrmv6MsoZQoPZP6xOLyBop8V1gdVDW62HKoho0FJ16v6oYRKcSH66i1e2h0eYkL06FWBs6ZpEg9SoXstGZVH+/cP5eyupuPaVHNz0Hic6Utd64Ft4/ldAbYRFLA+U8EpQShE0Tw4vxzvj2dEgRBEDqnKx40nUtdnI51vbPaPXx7oOqEroUVDS5UChke3883zCqFjPJ650nvY/PNuSRJgSLmTg9unx+1Qs6SrSXcf3n6CQVIWmf6JEfp+Xp/BSpF22Bh65v/1sv2jDZwRd9YqhsDXQLzKhowhWoYl2GmT7yRdzYc7FTb4ejPYcuhmhY1shpcHiIU6mBGUvM6uvo8OvrcL661kxihY2yGmbgOzv3udB63J3BMKwPH8KhzxuuTWJ9nYXY3b8uda8HtYzkdXV9FUsCFQwSlBOE4RPDi/HQ+PZ0SBEEQOq+rHjSdyS5Op5IpcKzrnVwua9O+adbetVAhl5ESpScuTEeDy4Pb60etlBOqUdEz2nDSN9HNN+cen0SZ1REMeNnwYdQpcXp8wa56ndE60wcgJcrAj4U1beZtffPfelmlXEZJnYN7PtqO2+unssFFvdPDij3lvDK7P6PSo/l6X+Vx2w5Hfw7r8ywtamQdqbXTNyGMsRnm09pFrtzq5Pkv91FYZQ8GcVbsLmPBzP4kRupQys+tG32fX+JQtb3NOdPo8lJYZev2bblzKbh9PJ0JsJ1okEkkBVw4zq1fHkE4C0Tw4vz088WzrXPt6ZQgCMKGDRuYNm0a8fHxyGQyPv/88xavS5LE008/TVxcHDqdjgkTJpCfn99inpqaGq6//nqMRiPh4eHccsstNDY2HnO7TqeTefPmERUVRUhICLNmzaKioqLFPEVFRUyZMgW9Xo/ZbOahhx7C6/W2mGfdunUMHjwYjUZD7969ee+99076WBxzf4/zoMnp8XV6XUcHL+4Zn8asIYn0iNR36RN8u9tLnd1NWZ2D9bkWPt12hOIaOx6f//gLNznW9c7vl0iM0LX7WnvXwsBNtJleJgMRejUxRi2xRi2/HpHE1P5x+PzSCR3Do9c7JsNEpEHVIgOrl8nApb1N5JQ1nPR6DRolBo2SsRmmNu/1WDf/zct6/RKr9pZz0GLD65fQNHX/K7A0si7XwkUpkWiUcsZlmIFAEfPmfXV6fMG/1Qo5yVEGAFxePwvXF7Ahz8KwlEjunZDOzMFdf/4crfncL6wKBHFq7R5sLh87iq18ubuURqf3+CvphmJCNcFzRmr6z+3zE2vsfvWv2tMc3J4zrAeXpEYxZ1gPHp+c1S3rdx1Lc4DtWN+x5iDTx1uK2VhQzcdbinlh+X7KrW2zLLvyt1ro/kSmlCAcx/mUWiv87Hx6OiUIgmCz2RgwYAA333wzM2fObPP6yy+/zJ///Gf+9a9/0bNnT5566ikmTZrEvn370GoDNz/XX389ZWVlrF69Go/Hw0033cRtt93GokWLOtzu/fffz5dffsnixYsJCwvjrrvuYubMmXz//fcA+Hw+pkyZQmxsLBs3bqSsrIwbbrgBlUrFCy+8AEBhYSFTpkzht7/9LR988AHffPMNv/nNb4iLi2PSpEldepxOx4Om03G9ODqjQKOUMbBHOBf3isTp8bMhr5JRaSYSO5kpcKzrXZhexbgMM5sKqjt9LTw6Q6y0zsH0QQmoFHKW7iylpINR7TrDFKLh6Wl9WL2vggJLI6mmEMakm7A0uNheVEu/xLBOr6s1p8dHdIgmWJvqcI2dHhE6xnQiM8kvSZTUBI6N3eUlVKuk3ulBJoMYo4b0mFDe/tUQlHIZu0qsfJdvITZMy+h0E0atiganB59fIkyvYkq/WDYfrKKwyo7L62fVvgr2ldXz+OSsFjWyTkcNHZ9forg2kCF1dOAPIK+iEbvbh1Z18qMnng1KuYxR6SY+33mEgkobfklCkqC32cCladHnRBu9vfpdCpkMt9ePzy+dU5/HsbJHT7TniUgKuLDIJEnqVp/oggUL+PTTT8nJyUGn03HJJZfw0ksvkZGREZzH6XTyu9/9jo8++giXy8WkSZN46623iImJCc5TVFTEHXfcwdq1awkJCWHu3LksWLAApbLjOFxNTQ133303S5cuRS6XM2vWLF5//XVCQkKC8+zatYt58+bx008/YTKZuPvuu3n44YdbrGfx4sU89dRTHDp0iLS0NF566SUmT57cqfdfX19PWFgYVqsVo9HY2cMmnGbFNfZW6aOBBptIHz23NTf627t4ir7qgtA9ievk8clkMj777DOmT58OBLKk4uPj+d3vfseDDz4IgNVqJSYmhvfee485c+awf/9+srOz+emnnxg6dCgAX331FZMnT6akpIT4+Pg227FarZhMJhYtWsTs2bMByMnJISsri02bNjF8+HBWrFjB1KlTKS0tDbbTFi5cyCOPPILFYkGtVvPII4/w5ZdfsmfPnuC658yZQ11dHV999VWn33dnzg2nx8fiLSV8vKW4zWtzhvXoNl3yi2vsvPRVDlf2jSUuTMfa3ED3sAGJ4VzSOwqFLFAIu7P7eqzrHXBS10Knx4eMQI2pBa3aSAnhWh6fnB2oVaTs3PXU6fGxvagOgAi9ilq7hy2HalifZ2HGoIST+myODu5VNTi5dngyGoUch8eH1eGhzu6hR4SOmGO8V6fHx0c/FvN/q3Px+iVMoRoMagV3jutNb3MIPxysoajGRoRezYTsGMK0KqwODza3l/gwHd8eqKKszsH4rBh6ROjwSRIrdpe3e6xPZw0dp8fHx1uK+fM3+dhcLbNM7hibyuXZMSRF6lsEx7o7p8dHUY0dh9vHNzkVHKhspLc5hLHpZjQqOQnhuhPq9nk6dSbQeKzP3+eXuixQeboLh7e3fpvLy5+/yWdjQduH/JekRnHP+LQ2gdlz4bf6XNNd21Dd7ldn/fr1zJs3j2HDhuH1enn88ceZOHEi+/btw2AIpLx2xVO59hzvCWF9fT0TJ05kwoQJLFy4kN27d3PzzTcTHh7ObbfdBsDGjRu59tprWbBgAVOnTmXRokVMnz6dbdu20bdv39N89ITT5VwaGlfovHNpdBlBEISTVVhYSHl5ORMmTAhOCwsL4+KLL2bTpk3MmTOHTZs2ER4eHgxIAUyYMAG5XM4PP/zAjBkz2qx369ateDyeFuvNzMwkKSkpGJTatGkT/fr1a/HgcNKkSdxxxx3s3buXQYMGsWnTphbraJ7nvvvu68KjEHAuZMk2ZxSkxYQQH67jwSU7OWgJjHa3uaCa9XkWHr0yk45yQNq7ITze9e5kroValQKby4tCLuOGESlsOVTDutxKGl0+dpVYWb67jEl9YlAq5J0KqmhVChIjdO0+BDzZz+bomjQTs2OosDp56os9uDz+4Ch8rR8ytj5+WpWCy7LMfHfAwr6yeuwuH1P7x5MSZeCPX+VQVu+i1u5GpZCz9XAtj1yRyfaiOkqtDqb0i+OSXlFMe/M7Vu2r4LVfDqRnlKHDY306aug0vx+1Qs7YDDNf7SkPBv8g0EVyTLoJq92DIvrsZBadbJBEq1KgUylYl1PJwMRwJmTFUNXg4tsDFsZlmMkpa2BgUvhZ/V6fSKCxvc//+wMWHr0yizKrk3W5lacUqDxThcPbO94n2vPkXPitFrpOtwtKtX4i9t5772E2m9m6dSujR4/GarXyj3/8g0WLFnHZZZcB8O6775KVlcXmzZsZPnw4q1atYt++fXz99dfExMQwcOBAnnvuOR555BGeeeYZ1Oq2EfP9+/fz1VdftXhC+MYbbzB58mT++Mc/Eh8fzwcffIDb7eaf//wnarWaPn36sGPHDv7v//4vGJR6/fXXueKKK3jooYcAeO6551i9ejVvvvkmCxcuPJ2H7pxxLg7rKYIX55f2GpyCIAjnq/LycoAWgaHmv5tfKy8vx2w2t3hdqVQSGRkZnKe99arVasLDw4+53va2e/R+dTRPfX09DocDna79mkculwuXyxX8u76+vt35WuvuD5qau62MzTAFRxZr5vT6Ka1z8F1+FUmRejRHLdeZG85jXe9O5FrYvK21uZXsPWIlPjwwiltGbChPfr6bBqeP/eX1jM0w8fLK3E4HVU71szn6+q6Qyfg2/+cb2qEpkazLrSS/opEIg4oIhRq5LFDo/bsDFqYPTMTS4GRdXqCLUY+jjl9cmJbfT+vD+jwLh6vtzB6cwPo8C4dqHMgAGTKUchmbDlazfE8Z/RPCeeyz3WzIs/CnOQN5elo2YVoVepUCt8/fbjZSVw+s03qkveQoPVP6xfHizH4s3VVGXkVDsIukzeUl6QQy74537E80g+9UgiTRIRpGpZtadPscm26msv7Uu30e7WTen9Pjw+nxUdXoos7uZuvhWjYWtB9o7OjzL6yy8+XuUgYnRTZlGZ18oPJsFg4/mSBTd/+tFrpOtwtKtWa1WgGIjIwEuu6pXGudeUK4adMmRo8e3SKoNWnSJF566SVqa2uJiIhg06ZNPPDAAy3WPWnSpDYFRy9E58OwniJ4cW47H85BQRAEIWDBggXMnz//hJfr7g+amjMKIvRqCqvsyIDmWhtapRy/JFFe37Yw8Jm84WzeVlGNnVqbm1q7h5X7ynl+ej8m9YljydYSUk0h1No9FNXYWZdbyczBicftGnayn0171/cx6dFkxxvRKOW4vH4i9CoOVgUCfG5voFC8JEl4fBJapYKKeiePfLKLGpsbALlMxvcHLDwxJZsekXriwrVM6R+HzeVFp1IE1iVJyBVy9GoFVocHl9fPgcpGxmcG7kHKrE6+zaviir6xLN5awrcHqugZZWBspjnQtfGotkdX19A5eqQ9t9fHZVkxFFgayYo1cuMlKXj9fvx+8Pr9KOQyQrWqE1p/M6fHR2V9IJh35ARrinXFOSuTQa3dzbCUCC7PjqHO7mFDniXY7fNU60qdTNvx6KBtblkDZqOGsRlmsuKMLFxf0G6gsb3P3y9JNDg95FX8fE7BiQUqm4NpzctZGlwtXu+K0cQ7G7BrXY9uVJqJzLhQlHI5Tk/bemY+v0SkQc30QQko5TIkxL3Y+apbB6X8fj/33XcfI0eODHZ966qncq115glheXk5PXv27HC9ERERHW67o+2e7FO+c5EY1lM428Q5KAjChSg2NhaAiooK4uLigtMrKioYOHBgcJ7KysoWy3m9XmpqaoLLt7det9tNXV1di3ZZRUVFcJnY2Fh+/PHHFss1j8539DytR+yrqKjAaDR2mCUF8Nhjj7V4EFhfX0+PHj06nL+17npz05xRUNXoopfJgEoRCESpFHKMOhVKhYye0YbgzXbzDeHa3MoWGQh+SaKoxs76vEpmD+lxQu/3WDeZR2d0yGWBYEajy8tBi411uRbGZZjYVlTLmHQTa3IqqbW52XPEyvisGGps7hN6EKSQyTp1w9tRt6cHLs9gTLqJVfsqqLV76BUdKAWiVsqRAR6fRJnVQZ94I9/sr+DHQzVolIFaRDa3l8Iqe/CG3dLg4g9f7mPr4VpentWfMJ2KkjoHyZEGlIpAYWok6G0KoarRhUYpJ1yvorDaRp3Dw6fbSrC5fHj9flbsKWPBzP4kRupQygPH4njdm4Bgd8nOBCKaR9qrtbt4fHIWSZEG1uVVsmxXGcmRei5Jjcbu8bG31MroNNMJB6U8Pj8NTg9VDW4e+2wXZXVOQrUqVApZp9pWTo+PkloHN4xIaVNDrLNBEo/Pj93tJTpEw3NL91HR4EQplyGTyYJZNaf6PT+ZtuPRQduKeieNLi8r95WzYEb/4PnYOtDY0efv9vlJNYVgdXiYmB3D0JRIIvQqJGjRhbf196T587HaPcjlMnx+iZQoPXeOTeWtdQW4vD+P4HmyhcNPNGB3dNBZksDS6GLpzrI2yzYfw/bWey46F3sJnWndOig1b9489uzZw3fffXe2d+W0OdmnfOeark5JFoQTJc5BQRAuVD179iQ2NpZvvvkmGISqr6/nhx9+4I477gBgxIgR1NXVsXXrVoYMGQLAmjVr8Pv9XHzxxe2ud8iQIahUKr755htmzZoFQG5uLkVFRYwYMSK43ueff57Kysrgw7/Vq1djNBrJzs4OzrN8+fIW6169enVwHR3RaDRoNJpjznOuig3TYtAomNw3jh8La+iXEMaYdBMRBjVOj4/kqEANluIaO+tyLYxOjya3rAG3149SIcPrC2RYuH1+9pc24OzvQyGXHTcY5PH5g7VrWndha162dUaHSiEjLkxHg8tDaZ2D2UMSeWFGPyrqnXz442EanD4SIvQcrrbz702Hjnkz33yT+21+FdnxRvQqBRsLqimzdpyB09H1/Uidk80Hq5naP46hKZEkRujobU5GIZexam8FvqYslMRIHVEhGnIqGgBwef00Or3oNUoaXB4O19jx+PzBbagVctbmBrJwVuwpp87hJsqgRqdWEBeu5bIsM2tzLIEAmAziwrRUNbqQpECg0O72sbPEyup95cy5KAm5zB+8WR3XTvemhHAtI3tHs6vE2umaQkePtDepTxxJkQYe/mQndXYP4Xo1n9Q7+XhrMS/O7E+sUUNVo4tQrfKEShqUW51UNbrYkGdhX2ng2DW6vMSF6dq0rdq7KZckCNerWLW3nINVNnpFG4LZRNuLajsVJCmzOnn1qxzun5TB/Kv6sGpfoNh5ekwIE7NjMYee2u/DybQdWy+jUsjx+SXyyhtZm1vJRSmRrNxb3qaOUkfd29LMIYzNMKGQyRidbmJdXiXldU4yYkMxqBWYQrU4PF6+2lPB4WobiRF6pvSPRS6TUVrn5Jv9FRysstEz2sBlmWb6JoYxPtPM8j0/J0yc7GjiJ/uwV6tSUFxjbzVAws/LGjSK8+Ihsuih0XndNih11113sWzZMjZs2EBiYmJwelc9lWutM08IO3qSd/R6O5qno+2e6lO+c4UY1lM428Q5KAjC+ayxsZEDBw4E/y4sLGTHjh1ERkaSlJTEfffdxx/+8AfS0tLo2bMnTz31FPHx8cER+rKysrjiiiu49dZbWbhwIR6Ph7vuuos5c+a0O/IeBIql33LLLTzwwANERkZiNBq5++67GTFiBMOHDwdg4sSJZGdn8+tf/5qXX36Z8vJynnzySebNmxcMKP32t7/lzTff5OGHH+bmm29mzZo1fPzxx3z55Zen96B1YyqFnEiDBr1ayVvXD6ay3sU3ORWU1DhIiwklOkSDQibjlZU5FFbZ6W0OwRymocHlIUynQi4Doy6Q+ZIaE0KtzU2j00tiOzd0zQEDpUJGhdXJV3vKyYgNZXBSBPUOD+tyKxmXYQ4u2zqjQwKUChkRejX9E8PQquSsy6vk821HaHD6goW0NzTVajrWg6Dmm9zsOCMy4N7/budIrYO4MB0qRaA73eNTskmK1Af32y91fH0vqXMQYVCzen8Fn28/QmZcKFP7xzOpTywFlkZ6m0KIMKhRyGX0jDIgl8nwSxJOrx+jTkaD10+PCF1T7Sl7MDNs5d4yBieH8/Ks/mw6WE2dzU2PSD2DkiMoqraxZGsxkgR9E4yM6m1iydYSGl1eQrVKdGoFMqC0zonV4eHfmw4Hg3/mUA1PTM5i/VE1dEb2jqa0zsH/rc5rym5pe4Pu9Pjw+PzIZTLUCjlqhZzkKD1un59xGabA6I3VDhIitDQ6vbi8fopr7MhlkBIdwrKdpSzZWkJGbCjjMszHvGlu3pbX5yfWqKX4qGPv8Uk0uDxEKNSU1jmQJIKB06NvyuPCtVgaXTz7v73sKLEGl1+1r4IXZvRjVJrpuEESp8fHmv2VRISoqbW5WZNTSf/EcEb0isLq8PBtvqXFeXsyfH6J0enR9DaHBLO4mjOMOmo7Ht3e9EsSBo2SWrsbl9dPXkUDl2UGjm97WVzt1VAa2Tsar9+P3e3j8c920+jyolLIWZdnYdmuMl6Y0Q+DRkGsUYPV4aa3OQS5LJAZ9c3+Ct7beAinJ7DPK/eW89ovBzKxT2wwKHWyhcNP5WHvsZZdn1fJyNTo8+Ihsuih0XndLiglSRJ33303n332GevWrWvTXa6rnsq11pknhCNGjOCJJ57A4/GgUqmC683IyCAiIiI4zzfffNNixJhjPe07n5/yHe1ER1wQhK4mzkFBEM5nW7ZsYdy4ccG/mx94zZ07l/fee4+HH34Ym83GbbfdRl1dHZdeeilfffUVWu3P3SE++OAD7rrrLsaPH49cLmfWrFn8+c9/brEdmUzGu+++y4033gjAa6+9FpzX5XIxadIk3nrrreD8CoWCZcuWcccddzBixAgMBgNz587l2WefDc7Ts2dPvvzyS+6//35ef/11EhMT+fvf/86kSZNOx6E6p2hVCiwNLv64KoeiGgc+v8Smg9VsKqjidxMzSDWHUGCxsaO4lin94tlRVMf+sga8fj9KuZzseCPjMkyo5HIcTUWXm2/oWj/FnzOsB26fn4t6RfLN/spg0egJWTEtlm3O6Pj+QKB7WHNGVpo5hFFpJgxqJaYQDRf1jCQhQs+YdBOWBhfr8yxolHIi9Gp8fqlFV7TWXRBvGJHM2txKDlQ2IklQ7/QQaVBzuMbO+txKpg9KYM8RK9/lVzF7SCJxYTokSUIma3ktTwzXUVhl44sdpQDsKbWyvaiWZ6/qi0YlZ03T+7z2oiTmXNSDCdkxFFXb+aGwmm/zq0iLCWFMhhm1Qk5ihA63149fkog0aPjnd4WMyzQzfWACpqaMHKvDw9qcRgYlRZBmDmHqgHi8Xj9f7S3D0uii3ukhOdKAX5IIN6goqGzk+wNVyGUtu7w119QC2FViPSogBRqlnOw4I76mrmtVDS7W5lrIq2ggMULH+MwYYowapvSLY9WecqJDNRRW2ZDJQCmX4/F58fklpvRLAGT8Ydk+Nh2sJkSjZEdxHZsKqtu9aW5dOD1Cr2Jin1huvCSFb/ZXBgMfbq8fjVLOzMGJOL0+XF4/vc0h1NndfLHjCBsLqlgwsx/rcy3U2D2oFDI8vsB7PWix8d0BC9dfnNyJwIPE0OQIJveLpdbuxtLg4p6PtuH0+InQq4k1apHLZCcVxDheTSiX199h27G5vemXqqh3eFEqZCSE62h0eukTH4ZWpeDhKzKD58zR2qupplTIaHR6+XhLMQ1OL0atkiEpEYxJMxEdqgEkXF4ffRPDiI/QsXJPOWtyKogK0TAqzURylJ75S/fh9PgprLKxNqeS6y5K4pLUqFMqHN7Zh73tZckde1kHo9JaHleNUs6YdBODkyPw+ALnWWdraZ2tLnOih8aJ6XZBqXnz5rFo0SK++OILQkNDg7WYwsLC0Ol0XfZUrrXOPCG87rrrmD9/PrfccguPPPIIe/bs4fXXX+e1114Lrufee+9lzJgxvPrqq0yZMoWPPvqILVu28M4775zmI9e9iWE9hbNNnIOCIJzPxo4diyR1nPEpk8l49tlnWwSDWouMjGTRokUdvl5YWIhSqWTkyJHBaVqtlr/85S/85S9/6XC55OTkNt3z2tv/7du3H3OeC5HT4+Ob/ZVsPliDxychk4EpVENRrZ2vcyoYmBjOf38sxuuTMOqU3DchnTU5lRRW2UiO0jM+Kwa9WsmSrcVclhnTogbN0U/x/ZLEDSOSsbt9PPbJbvIrG/E1nU+r95Xz2i8HtajvZArV8NjkLJa1GsWttM6BUi5j1uBExmaYOVxtDxadBvjtmFSSIvV8sq2kqSi2jlFpJtw+P1qlnNzyhkDARq/GFKLmreuHYA7V0Oj08NOhWr7JqeBQtQ2PTyIxQs+Q5Ai+2lvOqDQT3x2wUFH/c53WhHAtw3tFsXJvOfKjglVp5lAq6128ujqXsjont4zqidPj59NtRyizOjCHapkxKIFZgxPQqZTBguSj0kx8su0IdXY3IMfq8LDxQDVT+wXuE5buLKWq0cXQ5EgmZMVS1ehiZ3EdfeKNpJpCKLU6cTUFtaJC1IzqbWLl3p+7ULV3s2pzeVmXW9kiIPXbMamYQjUcqrHj8PqZ/7+9VNnceHx+LA0ulu0q46VZ/YkP1/LqNQOpc7gZkBhOXkUDSrmMqBA1EjAhK4bv8qsobCr+rlbKO9wPj9dPmdXB88v3U1rnxC9J1NrcrMupZMGs/tw4MoWF6w4CEKpV8uDEDJQKGYt/KmZvWX2LrnkL1xdgd/sorrW36Prp9vpRK+XU2DzBOlvN55taIccnSS0CNZYGNz8drqG0LpBJ9+sRyQzvFcljn+1GrZAjk518JvzR3w1303tvzuIak25iX1l9h23Ho4O2FfVOau0+QjVKMuOMTO4Xi98PueUNJIR3XC+v9XpVCjlVjW6iQ9TccmlP4sJ1bCqopiIv0E30skwzSrmcV1fm8d2BKlKi9FTUO1mytYSXZ/Vnav94lmwtQUZgtEm5XMY949NOKWBzrIe9zTXv2suSiw3THudBsQ7/UZ/Z0ef8t/kWqhrd7XYrbtZdusyJHhonptsFpd5++20g0Dg5Wlc/lTt06BA9e/Zk7dq1wW0d7wlhWFgYq1atYt68eQwZMoTo6GiefvppbrvttuA8l1xyCYsWLeLJJ5/k8ccfJy0tjc8//zxYqP1C1h2H9TzbUXThzOqO5+CFTHz/BOHcsnz5cm677TbS0tLO9q6cM071d87j85Nf0RDMJAnVKFHKZTg9foqq7YxOM6FRKRicHMHHPxVTXu9kYnYsE/vEUFrn5KMfi4gP19I3Pozv8qtIitSjof2n+HKZjG/zq8ivbAwURm7aZoHFxo+F1cSGaVnWVJQ4KUrP+MwYpg9MoNHlocbWcsSz5kyPf286hKXBxZh0E5P6xhJlUHO42obV7mHr4VrW5VpYsrWEZ68KtJOTIvXsLbVi1KoYkhzJst1lFFbZAnV1Mk30jgnhSK2DygYnLo+fvolhHKq2IQOenJLNt/kWimsdJEfqGZVmosbuDgbEIHCDO7lfHH5J4r4J6SjkoFMpmffBVvY3BQr0aiVbD9fwxJRsEiN0KJpGBnP7/Lw4qx+bCqrZUVxHcpSeselm8i0NKOSypuNUw+p9lfj8EpUNTrx+Pwt/NZRnr+pDXmUjphAN5lAtWpWcoho7Ww/XolMpGJNuYmhKJPHh2jY3qwkROvyShFwmY0y6KRAQ/HQ3j16Zycq95Wwtqg3c5IfrMIVqsLt9bDlUw1UD4wnVKQnVKrk8O4ZvcirIq2hsylZTkRSl5/sDVTQ4vagVckI1qmDwrvmmufkG3+vz89XecnaXWIPFzEO1KnIqAnWSrrsoGRkyDlfbmDU4kYRwHetzLWTEhjI8NYqqBhfr8gLdQMekm7A6PCRG6JDJZKiVMiIUP49s3ivagFwe6PbXUW2xUWnRlNTa+dfGQzQ4A93Zvs238PjkLOYM68F3+dXIOLlM+LY1oQKBs1q7m00FgRpl0wclHLPtGBWi5sVZ/aludPPjoRpqbW5G9o6moNLGwvUFzBiUAHS+cL1CLqNHhB6DRkF8uI4/rsylvN5Jg9OLx+fn2wNVPDwpkz4JRr4vqMLrl9CoFBy0NDYd90AXUpVCRkZMaIv6cO2NetcZx3rYO7FPDJYG1zG7rnW07Jh0MwaNgsSIQG2y5nP+qS/24PIEApebjtENrrt0mRM9NE5MtwtKHespX7OueCpXWFhIeHg4AwYMCE473hNCgP79+/Ptt98ec56rr76aq6+++pjzXIi60xDM3SWKLpxZ3ekcvJCJ758gnJvmzZt3tnfhnNFVv3NymYzEyJ8zKvQaJQ3OQPerrLhQXF4fNlegS09OeQMb8iz8cLCGGpubGrsbgCv7xjI2w8z3BdU0N7Pbe4rv9vmpqHcGR/vTquRcNSCByf3iSIrSI0kS8eFa0mNCMOpUHK62ER+uY83+yhZFk5sDGrFhWp6YnIXD48Prl9h4oIq8ikbMRg3jMsxkxhl54ct9TSMEWpjaP45JfWLRqeQ0OD28+FUOmwuqkYCv91WwbGcZf7xmAH0Twli4roCfDtXyl+sHMWNQIsW1dg5V2xiaEsn4LBV6tYIQjRK/JPGH6X2ptXvYUVRLZpwRuRy+2l1BXkUD/RPDGZkaxU2X9mT+0r00urzo1UqO1Dn5Lr+KWUMSUcgDx+uL7UeYOTiRkalRDEmOoKrBxWfbj7Amp4I/Xj2AGKMmGDySyUCtkNPo8rKzuJb0oT1INYWwIc9CaZ2D2DAtQ5MjuXNcKkgQFaJhXW4llQ0uMmJDGZthJqzpMx2WEsmK3WXU2DwMTYloKkJvJzok0C1PkgK1nJDJ0Chl1Nk97D5Sz4SsGBqcXsJ0KsqsDh65IpO1uZUUWmxkxIZiClGTFKVHrZQTHaJBpfj5JjkpUo9aIQ/e4N87Po2c8gZq7Z5gMXOlQkZ8uJbCKht+v8S0/nFEGNSoFHKO1DkY0COcNTkV5FcGuoGOyzAjl8m4qGckVruHsekmNh6oorhpFEf4OXvd6fG1qC123393UFJrD273y92lPDwpk0vTovlk6xFCtTIOVdvZfLCau8alEa5Xc6CiMVCbSnZiN/+tvxtHB85q7G6iQzUdjlTY+nufEK5jVLoJrVLO59uP8E1OJdEh6hMuXH/0iJybD1ZTXu8MZHH5/KgVcg5X2/l6fwXDUiL58Ici7O7Ab0KjS0mhxcbE7FgiDCqy44yMzTRjd3v5clf5KbfBOnrYq1Upmtbfcde14z0obn5tcHIE3+ZbcHn8Lc7R9jL6ulOXOdFD48R0u6DUmbJ8+XIef/zxYC0o4czpDl/C7hJFF86O7nAOXsjE908QhPNdV/3OqRVyxmfG8OWuMiwNLrQqOSqFqqn7SuAmf85FPfD6JfrGh5FX0YAkgd3tQymXIUmQHhNKg9NLYoQOS6OLWrsbU6iG5CgDGwsCT/HlMhlldU7iw3UkRujw+Pw8cHk6PSL1rM+zBIufj0qLxu728o/vDpIQruPKfnFMHxzI+hiYFEGEXoVGGSi0rVLISYzUU1Rj549f7qO4JpDhZHP5WN3UFeqyrBgW/VBEgaURjUJOZIiaaQMS+HhLMUXVdnpE6rG5vDg9PuqdHrYX1XJZppkvdhzB6fGzZn8lvxqezKOf7KbO4SZCr0anUvDA5enEh+tYn2dhV0kdSZF6Zg5OxOX1M3/pPnLLG6i1u9lXWs/SnaU8PTWbaf0T+CanguYYxuGjutgo5DJiwwLHZeH6AjYfrMaoU6GQyzDqVPx4qIaJ2bFsO1xLSVOB7zC9iozYUH4xIIGKehf3fbSdUquTxAgdfj/8b0cpL83uT4haySfbSuifGE6MUdtUl6qCoSmRbCuqJc0cyqNXZvHdAQtx4ToqG1zEhemwOtz0jDYgk4GxKUjS4PSiUyvom2BEIZexdn8lw3tGsb2oDpfXz6AeEYzPiqHO5qaq0c1lmWY2F1RRag10e/RLEj2abpo9Pn+gQHqNnVq7h57RgVpYDo8fq8ODUadEhozM2FBCtErC9Cq0KgWupuzAxz7dTYGlEY/PjwSs2FPO63MG0jPagMPtQ6WQc++EdL7Lr6K83knPaEMwK+bTbUeaaoulsC63kjKrg6sGJnB5dgymUA0V9U6qbC4mZJn5Nr8KpVxGg9PLrhIrl2WaubJPHFEXqympc/DdgSpGpUV3OujSUYaLXCYjOVKPSiHH5vIGA5AGzc+3062/95IksSHfwsNXZJIcZWDGoIROFa5vT1SImjCdiuW7y/D6JSQp0K1RksDrCxSuH5NuIkyvQkagi2N8mI7+iWEo5DLuHJvKmHQzRq2Sp77YQ2FVc+Dt5NtgHT3stbm8x+26plUpjvmguPk1j89PVaM72L20vXU1625d5kQPjc67YINSr7zyytneBeEs6U5RdEG40IjvnyAI57uu/J1TKeXEGDW8fu0gNuRZyK9oJDFCx5X9YnF6/Hy5q5SBSeGYQjRcnh3DxoIqyqxOVAoZEjJ6mQyMzTDxQ0E1I3pHs2xnKfvK6nl8chZX9I3h2/yf9/PHQ9VclhnDj4XVZMeHkRxl4NFPd3Gk1kF8uI6fDtXw3y1F/OGqfuhUSt7beAiNUsG1FyVx7cVJVNY72VFch8srMTZDTmxYoCva+lwLpXXOYPaQDR8HLTbW5VUyJt3Eoh+KSDWFEKJVUVHvRKmQU2p1IpcHRvYL16vx+v24vH72ldUzNDkiWGOppNaBt+lGNC5Mh06l4I6xqaTFhFJjc5EeE0KNzc3nO44wvFcU+8rqsTS4MGqV1Ds9eHx+SuscrMut5LJMMz8UVmN3+2h0eok1avFLEo3OQLHqKf1jKa610zchjJzyhmCx9glZsQxJiiDGqGXBrP7sL63nq73lxIVpuSwzBoNGyYo95dQ5PMQYtcgAhUIW7GY3uW8co9NNrM+zUFhlo2d04DOTJBicFMErK3OD3fsidIFA164SK1sO1TIuw8zKveU43D4A9GoFUQY1w1Ii2VNqpX9iOB6/n34JYTy7bB9f7SmjweXF7fUztV8cD12RyZNT+wS3nRChY0KmmSiDGo/Pz6W9o0mJMtDo8nBZppkvd5VxwNKIw+NrGklQzqW9TS0CM16/xLdN65PJCGbeHaqy8f2BKq69KIkDlY28ufYAI3pFMTQlknGZJqIMGkK1Snx+iSNNgYUIvYriWju/n5ZNUqSBdXmVHK62kxylZ2J2LLFGDQa1goNVNlxeP/HhOopq7Lyz4SCPXJnJxgNVLN9dHuza15mgi1alYNqAOEakRmFpcAVH3TOFahiVbqLR6eXTbSXBgQAm9oklLkyLBG2+9zKZjIp6Fz8WVjNjUGA0+daF64/323B09tXQlAhMIRrUCjlxYTrK651ISNjdPjJiQ7G5vCjl8mDXsJ7ROib1iSXGqKW3KQSAxVtLjgpIBRTV2FmXW8nMwYktPsvOar3PJ9J17Vi/hc2v9YjQs6kT6+puXeZED43Ou2CDUsK5o6vrznS3KLogXEjE908QhPNdV//OGbRKPD6JvvFGLuoZSZ3dg0ou5y/f5rG9qI7//lSMhMQfpvfjwUkZbD1cS0mtg1ijhpG9o/FLMKJ3NBX1LtY2Fc3ekGdhxuCEFk/xzaFaekToeGpaH3xNNYRqbR5iw7TIZIGR5SyNgdpA47PMDE4Op2e0gcVbiim1OgnTKbksM1BL5pWVOTw0KRNzqCZ4LOQyGdEhGib2iWF0monkKAPhehXzxvXm8mwzCoWM9XlV9DaHBIIRTaMN9ow20OjyUtXoIiFcR73TS3KUAacncCPe6PQQF6bDoFFw+5hUUqINfLK1hD2lVnqbQ7gs00zfhDDC9KrgaH4en0SsUYvXL2HUqSiusXNF3zjcXj+VDS6GJkcwNsPEj4U1bCyoJiXKwJgME+nmUCJ0ajYeqGJrUS1PT+1DSrSB7w5YWJ9rITEyUO/onsvSyCmvZ8nWYq4Z2oMjdXaMWhVWhwelQoZOpaDR6SVCp6be6eXxT3dTWG0LROFksGpfOa9ePZC0mEAgYdW+Clbtq+COMamMTTex5VANSrkMU6iGt64fHCxYHqZTcWmaifyKBuYv20tcmI5Xrx5AqtkAgEIuJ0ynQpIgJdpAg9OLQaNg+sB4nB4/SoUMuUzGAUsjPxXWkF/ZiClUw4SsGIw6FS/N7s/anEosDS7SY0IZkhyB1+/H4/UHC5H7JQlLowu1Uo7L62vRnbGi3oXXJwWDMiv3lrNsVxkNTg83jEhhUp8YFAo5Vw1K4IfCGmrtHq7oE0ukQcNDn+ykqNqOoikDcHNBNQtm9mdk72j2lzfQ2xTCuExTMDC08UA147Ni+GZ/ZacDwj8HgCo5VG0nxqhhQnYMV/SNRadSEKJV8pt/b2HvkfrgMl/uLuP1OYMwHXWut1Zc83Og6ujC9Z35bTg6+6rO7mZ0uomlO0vxSxJhOhX1Tg/m0MBIeyFaJddd3IPiGgcJ4TqG94qixu7huwPVjEqLJjpEEwz4AUhI+P0SPgkKq2w43D5qbW5iTrGcQld2XTuRdZ2uLnOnei8qAlHHJ4JSF5hzqbDw6ao7092i6IJwIRHfP0EQuoPT2R7q6t85r09ixZ5yPvqpKDjticlZJITr+C6/mgiDGrkM3l5fwNgME1cNiCc6RIOsabS8A5UNbCyo4X87jtDgChS1Plhlw++n3af4YXo19Q4PVY0udGoFLq8ffdP/keBAZSMzBiVi1Kp47NPdVFhdRIWoKa61s3p/BQtm9CfVHKifNH1QQvBYHD2K1pqcClbvryQjJoSp/eOIDglsc2+plapGFxOyYli1t5yDVbamukhKTKEaxjTdkDvcPvokGBmXaaay3onb52dUUjTRIWr+sGwf24rqsLu9fL1fFuwqKJfJSIzQsb2oFo1SzrhMMyNTo4gM0aBRygnRKhmaHEGqOYQr+sZSXOPgtdV5uH1+fjgY6OL02OQszEYNT03L5kidg0i9mmeX7qPG7kYhk1Fjd/Phj4d5adYAfiis4Z/fFXJRzyhMIVrcvkC3N4NaiUGtpN7pJTPeyNrcSgosgawivyTh90NeeSPf5lu47qJk7hybylvrCnB5/YEAhFHLc1f1paLexdKdpUSHaJg+KAGrw0NeeQOfbith6a5SXB4/By02vjtQxVUDE7C7fUTo5QxJjuSKvrGkx4RSbXPzw8FqLs+Opc7hRiWX4fFJ/O7jHTg8fkI0gcylXSVWHr0yk5IaO5ekRtEvIQyn14/DHSiSXe/0sHJvBYerbfxyWA8SwnXEh2upswey0dTKQCH1nk2jwjUHZTw+iTKrA49PYn95PWMzTLy+MpdHrshk+qB4thyqYc5FSXz442FKahzB745GKafO4WF9noVpA+LRqRVclmmmst7F59uPUGv3kFfRwFUD4/ntmFQWri/oVEC4dfc7vySx7XAtj0/JJsao5d+bDrUISAHkVTSyel8F112c1Knv/Yn8NrTOulyfZyErzsgfZvRj88FqSq1OogxqxqSbqGpwEmkIZfaQHjg9PgqrbKzcW876PEtTILqSxydnMzItmg35VfglCa/PT73Ti8vjI8YYyPYqqgkErRJPsZxCV3Zd62hdplBNm2LxXbldUQP1zBFBqQvEufilOl11Z0ThOeFUnUvB3e7mfPr+ifNAEM49ze2htbmB7InECB3jMsxd2h7q6t+55swr+VEFm7ceruWyzBi+P1CN3e2lzu7B7XOx6UA1Vw2IxyeBHAmn149fCmREaFQK7G4fdQ4PkQYVXr8/uL9Hc3p8VDe6MGpVlFsD3e56ROrRqwO1YtLMoWiVcjbkB7pohevUTTVuIL+ikTU5lQxJjmB9ngUJgsciO84YHDmuubtdXnk9chlM7hePTqXgN5f25D8/HKa0zsGLM/uz8WA1VQ0ukqP0XJoWjc3lxerwMOeiHozPDNTHidCHBru8rc2tpLDKhlYlx+mRIUMW7Co4pV8cl2Wa2VlsZdqAOBIj9KzNraS4xk6/hHAuyzTxzC/64JdgV0kdT3y2m3qnF50qkF1UXGNnQ24lU/rHc7jKxoAeESzdWUq90xv4nCQJp8dPbnkj3+RUMLxXFP/ZfJhv9lfw6xHJbD1cg0ohRwbIZNDLZCBCr+JIrQONqrlOUeAz0CjllNUFRu9LiwllTLqJfWX1jOwdjValwNLg4tXVuRyqsuH2SQxNieC97w+xZGsJDk+gK59SLkOllFNR70SvVvDZvEtQK+TU2QPBnFX7KojQqxiTbkatkLH5YA1T+8Xx0ZYiHB5/IPDTFFRqcHr54WA1U/vH45MkyqxOlu4qpcLqJDPOyLCUSMyhGj76sQi/JDFrSCIbC6qC55RcJgsEBzLMlNU5mJgdw9CUCEK1KirrnazNtRAXpqXW7qGkNlAHamr/eFbvq0CtlGF1eIjQq3F5fWiUCsJ0ShRyOeX1TlKiDPx6eDI1Njc/Haqh2ubC5goEWQqrbPQ2G3jr+sH4pUCQqaPR5joakfJInZNv8yxcNSiBwqpGZg9JZFyGiehQDVUNLtbmWjhc3YhCTqe+9yfy29A669LlDdQ0G50ezYSsWBLCtZRanVjtHhIj9IRqVfj8Ekt3lvHxlmIgUNfK4wsEFlftK2fGoATijBoO1dgDxdK9ftJiQri4VyQf/niYMelmSmodRIdqTqlt07rrmlohxydJuL3+YE2pk12XTBb4vD7ddoTD1bY297Vd1WVO1EA9c0RQ6gJxrn2pTnfdGVF4TjhaZ4ML52Jwtzs6179/4jwQhHNXmdXJs//by76y+uDIVRvyLPx+Wp8ubQ81/86tz6ukqMZBUmRgqPOOfueOdR1qL/OqOWPihRn9+L6giu1FdaRE6xmXYUYhl1PT6GJDfhVFNYEuXWPTzaTHhPLW2gNNBctN5JQ1MDApvN0b4f1lDYzNMLNyXzkHLTasdjehWhWmUA2XZZqBQHcftUJOqFaJ1eHB65PwI5Ff2cD4LDORBjWSJBEVombBzH5IksQn245gdbiJC9MRolHw27G9iQ5Rs2RrCZUNThIj9Mwa3IPiahtKhYxZgxJQKuRU21zsK60n0qDi5kt7Um518t8txfSMNnD1kB48N70PepWStbmV6NUK9GolYToVHp+E3eWlpMZOpEGNVqXg+Rl9qW5089hnuyircxKiVbKrxMqyXaU8P6MfiRE6Vu2toNTqwC+B3R2o/xQXpuNwjZ1qm4tGtw+fJJFT3kCZ1YFKISfKoEavDmQNHahoZGJ2LOF6NVsO1XDTyJ48OTWbdbkWimsCNZFGp5tQyQM30LFNBc6dXh9apQKjTkXP6ECXO4NGwY0jU/D5JZRyeVMRaQeWBhcNTi+1dg+FVTbiI3TEhWtpdHqD53aoVkmPCD0Otw+/BBU2F49/tosjtU5CNAqQydh2uI75V/VhYrYZuVxGZb0LjVJOSa0Dl9ePUi5DIZex+4iVq4f2wO4OBAav6BNLncPD9weq+f0Xe3h6Wh9GpUWTGRtKhF7N7yZmsCHPQqRBw6CkcCIN6sBIfwY1IVolq/dVcKCykZ7RBmYPSSQuXMsnW0oAKK6xo1LImT4wAZvLS0yoFp1aQahWidcv0eDyEq5TkxCuo6rRxTsbChifFcOto3px86U9OVxtJz5cy+KfirmiXxwSMtbnVlJmdXZ4zT5et1tJkrj+4mQcHn9TdlugptSMQQno1Qp8/s61b06kDdT83fdLVUiBARZxef2s3ldJlEFDclRCIMMq+uffDbe3ZZHxo7PR9hyxMm1API9MzuKb/RXsKrHSM9rAuAwzFVYnS7aUADIuz47psnIKWpWiy9pNze+xuMZ+3PvaU31YKGqgnlkiKHUBOBe/VF1dj6H1KBlnqvCcyKTo3k70InmuBXe7q3O98OOZOg/E74cgdC2nx8ea/ZX8eKgGjy/QjrDh48fCGtbmVHLNsB5d+l0zaBSMTI1mVJoMv1/CoGm77s5ch9rLvHJ5/Xyx4whPTMlmZO8oLkqJpKLeyeFqOxLwp9V5VDR1a5PLZHyXX8XT0/rwwMR0ekWH4HD7+DbfQr/EsDb7JJNBtc2NXAavXj2QTQXVlNTag3WVPF4/dQ4P2XFG9pfVo5AHugkq5DIkv0Rvcwg2l5dJfWKxuXys2lfOkaaR1MqsDow6FS6Pn0vTYjGHanhoyU4q6l2YQzVIwOaCKp6Ymk2UQc0HPxQxJt3EG2sP8OWuMjRKOYkROursHmxuL9P6xyMh4fL4cXvdJITr8fiqaHQFMnyUcjmmUA23jk6lwenls21HmNBUEN7u9hFuUFPT6MLS4EICvtpTxpyLkkiJNhCmU1NndyOXBbq0Nbg8JEXqMYdqiTSoqbV7iDFqaHR58TadT+F6FVaHgt4xIVQ3uojQq5g+MCH43qb0j0MhA78UaJvuK6tnTLqJb/MtHKhsxKhVBgIRkXou6hnJuhwLF/WKpMHpZX2uhZK6QHbfsJRI7hzbmz9/k0+jy8uGPAvXXZzEjwerOVzzc/s5OVLPuEwzTo+PkloHmw5Ws+dIPT6/RKNLQXy4lsJqG8t3l3F5dgwapYLephC+2lMe7GLXXCeqV7QBkKi1efi2qYZVL5OBidkx9E8MY+OBKqb0j8fp8XHTez8yMjWam0b2DN6HlFkdJEUaGJUWTa3NzRc7jmC1e/mpsIY9R6w8MSUbmrowJkboAtuWJPaXN3Bxryi+2FlKgSVQE8ygURIXq2VwUjifbT/CZZkxRIdo+PDHIqwOD0mRBqIMasY1BVCfW7qXLYdriQvToVbK21yznR4ffklizrAehGiUwS5vzZIi9WiVCnRqJb9bvI395T934VuTU8lfrhscLBB+vPbNsdpAra/7CpmMUWnRfLmrlNyKBjRKBUadkl7RBkanm9otSn50ENsvSTQ4PYHaaVol/RPDUchlmEM1TOoTy6jeJkrqHHy8pZiNB6pQKOQUWBqZrUvs0nIKXdluOlP3tWeyBqpo74mg1AXhXCws3FX1GFweH2VWJ6v2lrcZJUOjUpy2L77IpDg3nMhF8lwM7nZ35+LxOhPngfj9EITTw+Pzk1/REAxI/TxdIreiAY/P32W/S22vL4EuOq2vL529DrWXXTEqzUR5vZMXV+ynT3wYI1OjGNk7mv/tPEJFUxZNtc1NmE6FX4Ith2qY1CeWfWX1hOuUzBwcGA2swelpMbS90+NjcHI45dZAt6+RvaNQyE34JYkQjRJdaKBI94SsGL7eX0Gt3U1sWCBDJz5cx9R+8UQa1MhkcPeH24NZVMN7RRGqVeH2+rG5vAzsER7sbhdpUCOXy/D6/OwurWf57nIuzzYzvFcURp2KjJgQviQQjGtwejHqVNjcXrLijPj98NJXOcwaksjYDBOLtxZTUe8MdJWTwa+GJ6FWyHnq8z18m1/F0J6R/FhYw6EqOz0iA0EKf1OB8QJLoNjzJalRrMut5IfCGmSyQPfH+DAdo9JNfJsXCA5d0TeWKf3jWLmvnPyKRqptbow6JSNSo5jcL46DlY28OKs/aoWcz3cc4VC1jZQoA6PSTDjcXvxIbCqoZljPCJ6Yks3KPYG2ana8kUFJ4eSU19PLHILT4+PRT3dx0BLITAvRKlmfa+Ge8WmMzzazfFc5Rq0Ko07F3ePTWJNTSV5FoPD3+KwYwnQq9hyxEmFQc7g6cD+glMvw+PzU2T3o1QpyyhsYm27m4y3FTO4Xx/92lmJ1eIBA7fVUk4FfDEygqinDrDmwJUmwYncZL88egNvrJyFcy6fbj+Bw+1Ar5VgaXDy0ZCeFVTZMoRoi9GqW7y7l0SuzmD4ogZVNwa99pfUs313G0OQINuRZGJoSya4SK1lxoWwuqOLyPjH8+dpBwVH9UqINjEiN4nCVDavDTYxRy6Of7OJglY0og5owvYoNeZX8/hd9KKq2c6jaHgwsRijUlNQ6+P5AFdMHJWBpcP3cnTc8MFpd34Qw/rL2AC6vP9i1zidJbMi34PX7iQnV4vIGugH6/RLf5QdG52sOKnTmd+Toedq77k/pH0uj00uBpZGHr8hkXV4lByobyYw18osB8R1mXR4dxC6qCbxvU6iGXtEGLkmNCo7WOCotGq/fj0IGcy5KYlKfWLYX1WLQKNCru+4eqavbTWfqvvZM1EAV7b2fiaDUBeBcLCzcVfUYyqxO7vloO/kVjcFpzaNkpDSlRZ8OIqOm+2t+anjDiBQi9Cpq7Z7gsL/tXSS7S3BXPE05u87EeSB+PwTh9JDLZCRG6tp9rUeEvkXNplNxrJuw7w9UMWtwIj5JwuPz4/X5yY4zYmlwBTMz2rtZay+7QiGTselgNbdc2ovoEDVrcipJjjKQX9GIJEno1ApkdqixualudLP1cC0X9Yxic2E1949Px9LoYvGWYg5XB7qTjcs0Yw7VUlDZSKg20H3socU7ya1oRKuUY9SpSDUZeGBiBit2l9EnPowFM/vzbb6FQ1W2QF2nTDPRBjUAn+8oxdIQGIWtwenhm5wKZg5KZOOBKvwSRIWoKbDY0KoUhOvU+PwSpXVO/JLE/rJ6Lu0dxaOf7uL/rhnI9EEJLN1ZxoHKRlxeP0adjDRTCOOzzOSU1we6EsplNLq8/GF6P9Y1BbvSYkL45bAklu0qpajGjkoho7rBRao5hBV7y6l3eAnXq1Ap5Hj8flJNBkpq7SjlcuZf1Yf/7SzloMVGr2gDk/rGolbIeXt9AUW1dr7YUcq7Nw3jHzcMw+b2opTLgyOiqZVykiL0WBpdPLd0H4XVgYLtLq+fFbvLgsGqi3tFMn/pXp6e2oeZgxMAqLG7ee/7Q4RqFYxKM/HBD0XsLLYCgSy25hpWmw9WMyw5ktX7Kri4VyRLthTj8PgZmhIZLPr935+K6JsQxsCkCOpsbnqZDEgS6DRyJveL4/KsWGKMWpQKUMrlZMSEEGVQ8/yMvizfXc5BSyO9zSGMyzQTolFSa3cz/xd9KbM6+Xp/BV/sOEJuRaCG1vSBCcjkMvYcqcfm8nFJajRrcys53DRintvrD9Qdq2xkfZ6Fi1KiWL23AqVcjkIh40itnRmDEnj0yiyO1DpYuL6AJ6dmMbl/PC6vj4OWRgYlRXBZlplwnZp1uZX8Ze0BHpyUyTc5FZRZHVw9JJHLs2MwG7VYGlwcqXUQHRoIeMpk4D4q+8nYVM/q2aX7gt15NUo53+VbeGJqNn/99RDqHR7C9KpgMPVIrQONUkFUiDzYnc7rC3R3HdXoYkNe1XGDCu2149q77vdNMLKjuI53vytkTIaZcRkmJmTFUNXgoqjGjilUg88vtdsmPLr7cH6ljZQoPYOTIthfXs+LK/ajVij4sbCax67Moszq5J31BfSOCeHyPrH0iNARou26EEFXt5vO1H1te/eiGqWc6YPimdI/Dp+/4/pknWVzBX4TeptDqLMHsgcv1PaeCEpdAM7VwsKnWnfG5vKyal8FFVYnsWFalHIZXr9EudUZHCWjvbTXU9XdMmou5CDGsd67JAXS7JtH9+kVbWBshpmsOCPbi2rbXCTPdnBXPE3pHk73edDdfj8E4XyiVsgZnxnDsl1lHLTYgtN7mQxclmVG3UW/pUffhGmUcsakmxiaEkmkQUWkQRMcqexQtY0IvYrR6Say4owsXF8QDEwdfbPm8fpx+/z4JQmFTIZaIUelDOzr5dlmSuucTcGjBgb2CMcUqqHc6iTGqEWvVlJjc6NVyZk2IJ5wvYo7x/TG0ujisU93U9ngRC6T8dVeL1/sLOWlmf1JjNAjAf/bWYql0Y05VIPXL+Hy+imqcfDN/goGJkXwXb6F9JgQsuONXNwzknKrk79tOMiO4jrevHYQSrkMZdNvYqhWyZZDtQzvGcXT0/qw5VANkgR9443klQe6ANbbPUgE3nOqyUCt3UNBZSOr9pUze3Aif7x6ABvyLMRH6BjUI5wIvRqVUs6+0nrcXj/hBg1///YgOrWSCVkxXJ4dQ6PLi8PjY19ZPQaNkmuG9iAuXEdKtIGdxXUcrAqMeieXQbo5hDEZJtbkVKJVypmQFcuwlEgmZsfS6AyMmvefzYdpdHnRKhUcrGqkqtFFiEbJ9weqW1ybo5RqHE2/50cXlJaAHw/VsnRnKddfnExSlJ4yq4u1OZVkxRmxu73849tCfiys5oNbh+P0+MiraMDrCxR3VshleP2BbLHmAvAjU6PpbQ5lTU4l3+ZXsXRnKXa3D6vDQ0KEDoNGyeg0Ex//VMRVAxNYl1vJ3BEpJEUZWJ9XSXGNg34JYYxON9E3MZz/bilmYnYsF/cKBLfq7G5kQJ3Dw8q95ewvayA5Ss81Q3twUUokT3y+m8PVdsL1avx+iYSIQH2sUK2SgxZboHwGMtTKQOZaVIiGapubxAgdRp2KEb2iGJoSQVKkgRCtkryKBv75fSEubyCTKzxKzYOLd5JX0YAE+P0S799yETU2N3a3D3OohpIaB7+f1if4ng5V2ellMjCpTyzxYVo0ChkhGiVKxc/X6Ky4UNblWoLdeWWyQLfAg9V2Vu4tZ1SaiZ8O1TAuw0yoVtXi+i+XyaApyFVmdRATFkdpnTPQDa6DoEJH7ThTqIZv86vaXPe1KgV5FY0oFHKWbC1hydYStCo5U/vHc83QQHC6st7J/rIG6hweRqVFB9uEzUHs2UN64Pb6Ka938v6mwyzbVYrbK2FQyzhcbefL3WX0Twxn48FqdhTXsa+0nt9P60O4PhBYPtl7iKOXa91u8kuB77gM6NH0kOBEgjtn8r726HvR0joH0wcloFLIWbqztGmgjJNri3t8fsqsTr7aXcbesvoW9yAL1xccs713vt7XiaDUBaI7FBY+0S/Rqdad8UsSZXUOQrTK4NMpjTJQ9LG0zhH8Uexq3SWj5lwIYpyuH9bOvHdLo4tn/7eXHSXW4HKrmoaNHpVmahNcONvB3ZPNnjmXL16nc99Pdt2n+zzoLr8fgnA+UinlxBg1vDSrP2tyfi5UfFmmmZhQTTDQc6qab8I0ylp+OyYVU6iGdbmVlFudpMeGBkcqW7K1mHKrk2W7ynhhRj/GpJtYta8CgJ7RBhRyGVa7m4p6F9/kVFBU4yA9JoSxGWYi9Sr0GiValYIth2qpd3pJiNCxs6SOCVkxfJNTQZ3NQ5RBTXSImqemZJMYqWf57jIuSY3i2/wqrA4PU/vF0z8xjKhQDZZ6F0U1gUBZSnQIhZZGSmrt6NUKpg2IZ2J2LKZQDV6fnzC9Gq/Pz8dbS1i6sxSH20dtU/0ln19iba6FMekm/vFdITaHB5fXT4hWyd+/PcjDV2QyY1ACXkliki6WbYdrKaq14/L48fokUk2BG7S1OZUo5DLyKxppcHn5Ns/CNcMScXr8rM+1kF/ZQEqUgUvTTPxuYgbVjS6Sogy8ueYA//2pGHOoBqNWyXPT+5IZE8r4pkywlXvLuSglkscnZ/FDYTUltU6u7BvLmHQz5VYHeeWNPHplJqV1DpbtKiMjNpRhKRHklNfzxY4jeHwSoVoll2fHoFLI+cOX+zho+TkT6stdpbw0uz8xRi0ltXYam6Yf3arIKW/A6fUhl8nQKOXEhmspszqIDdPSLyGMxAgdOpWC4loHKdEGfJIETaPHqRRyPD4/SVGB0dbuHNcbv18iOkRDmdUZbOuaQtSMz47hqgGB7pS/HZOKUiHnXzddBMjIq6wPFiv/8WANr63K5f6JGTQ4POSU1wfP2+hQDbFhWl5Yvo+9R+qpsgWCVKv2lvPirP68evUAMuOMKGSBrn6zhySyLqeSinoXKdF6ZLJAQCpEo8Tnl7i0dzTXXtQDo07FW9cPptHpZemuUr7eX0FyZKBu2d9uGIrD7QsWjn9ldn8qG1ysy61kTU4lGwuqmdo/jrW5FuocHq7sF0ukQcPDS3ZSUuvA21QHa/PBal6a1Z9pA+L5eEsJCrkMvyTRI0JHhEFNQZUt2J03VKNEKZdRUmtnd4mVUWkmFm8pYVNBdbCtdfT1v7leU2KkjjHpJjbkWYCOHyJ11I577MoswnWqNr8jdfZA4K45sKtVyfn9tGySIg1sLKjmfztKCdEqGZthRq2U88rKHB6alNmiTahVKfD6JP77UzHf5FSgkMuIClETplPhcPuINGjIjjfy4a3DqbO72XKols0Hq4kO0WBpcLIuz8KREwi+dNQNcUyGie8PWCissgeCuio5KVEGLkqJYn2uhWqb+4TuUVrf1/aMNjCxTwxaVWCE0K5qNx59LyoDKhpcLOiCTPZyq5Pnv9zH1sO12FyB0TKb70HGpJvabe+dC/d1p0IEpS4QZ7Ow8Kl+iU52PxUyGUlReo785GhRrLDe6SElWo+ii9L022y3m3SX7M5dgE73D+vx3rvT42N9roUauweVQhZskBy02PjugIXrL05u97w72eDuqQZXTiZ75ly+eJ3Ofe+KdZ/OIH93+f0QhPOVXqMkPlzLtP5xyOWBAuRhTQGertIcvJbJArVcHvt0d2B0tHAt6/IsLNlaErj5yDCxck85To+PzQeruahnJKv2VZAYoWNinxjsbm+LLCiJQObVhjwLj03OIlqS0CgVlFkdhOtVeH1+lu4oJc0cyvPT+/HDwRqqbS4uTYsmMVLHs0v3cqTOwcje0eRVNHDbqF6kRBv4JqeC/IpAN60r+sSSEKHDJ0lkx4exvbiOuy9LIyFcx4Z8CwctNvrEG5mQHcOAxDCqG128MKMfRq2SyqbaPMt2lXKo2sYMQ0LTKG4ezKEalPJAACbSoKa83kmkQYPZqOHxKVmsy61kf1kD5lANYzLMHLQ08vX+CpIi9fRPDMMvweDkCBxuP88v30dJjQNksOVwLT8UVnPP+HQKqxoZl2Fmxe5ySmrtwZHaDlQ28ouBCZTXO1i1t4L+ieGEaJVIwKg0E5GGQNfBHwtrqGhwcv/laYFC5g4Xd45NJVSrxNlU3P2qgQk4PT7GZQayGpbvKqO4xkFpnQOnJ9DW/PFQLf/bWcpNl/SkR6Qej8+PXBbI0JYRCNykxYRgdQSyr/olhDE6zURFg5PoEA2j001UNjipanRRUe8MvqeDTUW+/ZJEmjmEMekmtCo5BRYb63MrGZ4axeKtJU1dHH28MnsA8eFavD6JQ9U2vs2vosbmYtbgHqiUcnYWW9l9xEpKlJ6xGWbSYkL4sbCauZekkFfRSKRezdVDe6BTK/hs2xGO1DqDIy06vYFMD5VCRlackfVNtZ6SowyMSY/mb3OHsftIHZP6xPJTYU1T4XwZvx3Ti57RIWzIq+JwdaDL55DkSHqbQli1t4JNB2tYn2/h4UmZaJRyamxuvi+oCtYd+8XAeIb3iuKdDQWMTjcx/xd9KK2z0ycpgkU/HKak1oGMwD2ARimnutHNhjwLs4f2wKBRkl/RSEyYlin94lAp5MQaA9dtCQm95ueH2L1Mge5UfkmiqMYebGs1X//X5lRyuMZOlEHNiNQoKuqdrMutDP4GNAcVmtt/QLAdd/RD8eIaO+vzKpnaP44CS2OLAutbDtUyqU8sWw7VUFLrYGr/eJIiDTz5+R68fj8ur5/KelcwmJEVZ+RIrYPIpu6zzW1OpUJGSpSBiKbsJ5p+R+4c25u0mBC+2FHKrpI6ekUbGJdpJj5Mh9Pjw+HxkRJloLrRzefbSzp1D9Fe+/unQ9U8d1VfHpucxbJdpZTUOEiPDQ12J/zHt4VIcEL3KO3d11oaXHy5q7zTbbsTaZtrVYrgvcOpZrIf3aZXK+TYCASlDlpsrM+zMCwlkoOWxjbtve58X9cVRFDqAnOyAZ5Tuak+W18ilULOJanR9IjQc8Dyc02pHhF6RvSKPm035l2dSXEyx767dwE6nedEZ957czaKSiEjLkxHg8uD2+tHrZRTY/OglLd/bpxocLczAZDOfL4nkz1zLl+8Tue+d8W6T2eQ/2xn5AnC+U6lkBNp0KBXK0/rQ7rYMC1T+8fz8ZZiKhucRBhUaJRyrA4PBZZG1uVWMigpgvc3HUalkFNR76S3OYQbRiQzPsuMRqmgoj5Qt6eg6ueuhs1Fob/Lr2JchgmzUUFihB6vT6LM6sTjk3jqi91cPaQHcy5KIlynwuPz8/n2Un4orMGoDdQFuqJvLFGGwMh3h6rseHx+kMFPh2p4aVZ/HG4fF/WMxOnxkhSp59FPdwXqNink5JY3sLu4judm9mNwciTLdpVSUNlISrSBGYMSGZIUQb3Ti9cv8dz0vvxYWEO51Um4XsWodBM6tQK5TEat3Y3dLUetkAe7Ge0vr+fTbSV8ur2EUI2KQT3CmNQnNpj58+Wucg5X22lweoOj6/n8EtuLark0LZpam4e3rh/M5oPVFNcEamWNSotGqwps57JMM2tzK/nfDhup5hDGZphweX3EGrWMyTAFz4ldJbXU2rxIfhlf7CylqsFFdKiaG0emYLV7WLqzlPgwHbnlDfj8ElEhmqYs/MDnlFvWgNPjY2y6iRW7y9hWVBcoDA6kmQ2Mz4yh1u5Gr1Lw+1/0IdKgRpIk/vX9IcZnm0lr6o6XajZQWe/ildn9WZfbVOg6LlDoWqmQY3MFAprvbz7EyN7RfNjU5U+llBOiVlDv8KBSyPn35sO8t7GQmYMTcXh83P/xDpweH7V2D1/scPPlrnJent2f7DhjoN6XQY3HJ2H3eNCpFRTX2rG7vWhVChIjdNQ7vUzuG4dcJmPBiv3kVwRuor/cVcYn24p59eqB9AjXExum5aVZ/fl6fwV6tZLMOCMvrsihsMqGQiZj5d4KIkOKWTCjP5f0jmLl3go2FVSzNreSWYMSuOM/WymqsRMbFugSuHRnGS/P7k//xHD2llqZNTiRqBA1EmB1eIg0BLpNaptGqZPLZBRW2ZAkmDE4Eb9fCo7WqJTLGJ9p5n87j3CgMrD/Lq+f1OjAebE2t5KKeidqhZyDVTa8PgmtSoFeo6BvYhiT+8VRY3Px/uYiVu4tI0KvQd2UbdkjUo/b52fptkA3r7mXpHCo2obP78fq8OLy+lApAtljBy02HB5/MNDZ3I03v7KBG0Yk88wv+rBqbwXDe0WysaAarz+w76WNbuDnYMaswYnUOz18sq2kTXbTuKZ2haXBxZh0E5P6xhBl0FBYbaPcGmgfb8izkB1vxKhV8U1OBVsP1wYzSSc2dYVVyGXYXN52y5901P4urLKzfE8ZE7JiGJwUyS+HhgSP27JdpejUCiL06pO6R2mer7jG3um23ck+nGyvLd4cYDx8ApnszeuRy2SEalU0urzBh+MFlkYm94sjMULX4hh09/u6riCCUsIxnWpWwdn8Erl9fhweH3+8egBrmy7kvc0hjMswY/f4cPv8XZaq31pXZFKcyrHvzl2ATvc50Zn33pyNEkgplxGh+PnpUa9oQ4uaA+3p7P51FAB5YnIWMWHaTn++J5o9cy5fvE7nvp/Muo8VNDxdx7A7dLcWhPPd6f4NbK7rUtUYGBmsmVoRKJCcV9HAuExzU9cNX2D0OZmM6QMTKK934mjKuimobERGoAi11x+oSeT0+imvd2DUqVDKZYxJj2ZdXiV1djdevxeH209ueQMer5+F6wuYPiiB3aV1mEI0aFVyNh+s5tfDU/jgh8MctNgC3YNkoFMpqLG5WbGnnL7xRtxeP1cP7cHiLSVUWF2E6wIFn+Vy6GUOwVLv4pVVOWw+WIPb68fj87N8dzmvXjOAhHAt63MrKKp1cO2wJDx+P7nljRRV2UkM1wULZRdV20mO1jM+M4ZeJgORejVmo4bLs2LJigsNjGJXZeP+/27nszsv/X/23jM+rvO69v6f6b0BM4NBIQGQaAQB9iJRFEmJEimSalRxUezYjpM3zk1x7Fi2bMc1lmzZcew0O7k3Nze5iZt6p6jCJokSxQoSvRF9eu/lnPfDGYxIqpGynNi+3P75gwDwzMyZ5zzP3muvvRYToRTTkQwlURaKlySIZhSMB1NlzSwNArClzYlKqUCvViJKEpl8CVGCLz4is9ZECUpnvDxxao4ffnA5uaJIPFvkzHSMUCrPDV01JMxF/vA/jjEaSOKx6rl1RR3eWJYfPDfEWDDFuuYqnBYtM9EMHqsOq142TQFY5DIRSOZoqjby7dtkQGksmMJj1XNFcxXJXIGFdiNqtYIhb5zpsMCXH+0lmSvy06MT7PmzTWQKJQKJHG6rFn88xzUdbm5fXY9Ro0KpELjzx6/w93etwhvL8MWdSxAleOj4NMFEjnq7nisWVZHKlTg+EWFzm4vmaiM2g5p9g7I7n92gwayTNcdGA0mOTYT50LoFnA2mZTDUn6LJaeAj6xtprDJSEqXKSJ1Zp+KaDhcvDQeZiWTQa+QxMbNORb4ouwpe1VLFZCTNQoeR9c1VuCw6Hjsxw5mZGKlciXq7nnxJZNSf4oUBH1cuqubh4zOURIm5WIZMUWQ0IGt+JXNFzDo140EZ0N3a4caoVfHw8Wl2r6ynUBRxmnRoVAoMGiVFUSKaLmDVq1lYZUSlgLlYhlxBxKZXY9TKDCKXRcu3d3fL467pArU2PWsbHQQSOZ4945UZV2olCxwGECCdK/Lo8Rl+dGCU21bWs6PLw7HJMPFsEZVSgV2pocGh56rF1Tzw+hT/fGgMjVLB5jYnNoOafEmiWBIroGpEpWBBlYFkrsAPnh/i7u3tfGJDE5F0nqtbnRi0Kkw6FR9c24AkyTpvIIurV5k0BBI5JAnmohl0agV/8UAv8WyxbNrwBjDjscl5Raac07wyEmLIl8Rp0XLDUg+dtRZOTUepMmq556EeAskco8EUOrWCpXVWWlwmDg0Hefj4NJ11Vra0ud6Ur75T/j0eTJPOl7j36X6+e3s3Pzowyt5eeVT53Bz27WqUC3Oxc/8buKTcbq48OjcdybzpPr1Tc/LcXFySJNnNMVsgXxJxmrQUSvIe+G412rnXubA5vrTWSrVJ8ybQ79e5rnu/4jIodTneMX5ZVsF/50OkVAj0zcYJJXOsa3KwrbOGaFqm8TrNWtprzKRyRVmA8Rwr5Pcj3o1JcTHsmF/m3r8ViDGP5jc49G87AvRfoT/0XtbEpbyvc7U85sVl5931BN6gM5/LRpl3XGqqNnBDVw3ALz2T/k4AyHQkgwgXPZd+qeyZ3+TD61f53i/l2v+d44//nePWl+NyXI73L5QK4U2ufmadmlimwCKXiXAqz+2r6tnRVUOr21zWvhT57rMDfGjtQqqMahqrjZVCRyEIlCQJq07FbSvqSWSL7On10llr5e5tbbwyGqqMOd28rJa5eJbHT86yuc1Fp8fKqD9FoSTyyPEZPrx2AbF0gWqTlqIoYlMIWPRqBATmohnuXF1PMJlHqVAwF8viMGkoibLwdLpQZF2zg+f7fcxEZEAmmS2SL4mk80VOTUVpcdWzaqGDifAMgWSOfz44xt4+H4/9jw2EU3k+84uTjJWZV6Ik8fRpL3//4RU4jBrWlsXFtWWA4cuPnJYBD62KGqsOsawXJEmAILPH3BYd2UKJB49Ns2qhnXuf7ueqlmquaXex2GVGp1by6IkZGZAqKzqoFAJT4TQvjwS5eXkte8546fBY+OoTvSyplb+Pr93Yic2oRqNUYDdoSOVLfGxDEyemIpyairKlzcWeM3OEUwUsZVBqkVNugMYzBbKFEpOhNKsbHVzb7q4U1Aa1AqdFQzRdoKvOikKh4B/vWskL/T6CqRyRVJ6NLdV8d88gi1wmblzmwabXgCCfEaIocs+ODvJFkSsXVWMzaPjCwz2EknnMOhX+eA6PTcd3b1/GdDTDz16f4ju3d+Mya3n4+AwKQXbDM5dd1gQBaqx6gonydxOYF4CXhapvWlbHS8MBxoIp+byUJBxGDXOxrCxGblCjKH8X8WyRYX+SW1fWIZbd4V4/G2HVQjvHJyOEU/myYLuEVqUgkZUYD6S5YakHpULAY9Wx2GkikZWvG88UKIkSmvLoZzCZp91jIZjMsXGxk6Io0e+Ns7bJwYPHpxn1J5HKn2mR08iWNieiJOd1+wcDDPuTtLpM3LKiDpNWRZVRw67uWkxaFVqVgsdPzvLg8WkEQcCkk3+/ptHOyakIdTYDnXVWSqLEz49OsqTWwn23drNv0M9MJEN3vZVNrU4SuSI/OjBKtiCSosTh0RDXtLt4aShASZQIp/NIQL3dwBWLqlAKCnzxHEfGQ9y6ov68c3+eBfSxKxupMmopliTUKgVGpQpDlZJcQaTdYyaUyhNOFSpsLZBzzgNDAXZ1e8gXRdRKgfv3DDAbzeJPZElkizx7Zo77dnfTVmPh2V4vw4EkVUYtADcvq6PapOXzD/UQTObJFUqcmY1zeDTEPTs6cJu1SMh56js3UPWI5Rwrks7T4jLJwGabC5dFRyJb4OjZCE6z9rwa5dxczBvLcPOKOjRKBQeH5fy6wW7gxmWei8rtCiWRVK7IntNzHJuIoFEqMOvUqJXCRTU+z83FxwIp5mIZCiWJZqeRtU0yY3RTq+tda7QLc/r55niDXc+2pTUVkflz4/8FaYfLoNTlqMRbodC/LGPhv/Mh0qmVbGyp5t6n+yvCoSAX8ves6CCZLfLw8emK0On1nTV4rDq072Pxd6k6P281e35uXOy9P3fDmwqnK2i+3AGqIp2XAZf54vr9GjO7mLiUNfFegAGdWsmNyzzs7PYQSed5rtfHgDcuJ3XdtZXrv5VI4g1La4hli5c0k/528U4AiNWgZv+g/5K+30thz/wmH16/yvd+Kdd+P0cIfxlR9ctxOS7Hb268VUNBpRRY31zFjrKmzV3rF/DKSIhnznjxWPXs6KrhKzd2EknlqDJpuW6Jm2dOezkbSqFQCGgVCj6xsQmtWsl9z/QzG82iVk6zptHB5jYnNy2rxRfPkS2KHBkPl7VaQty+qo5jExFeGgmSL48Aui067AY1b2BmAvmSSK1Nz2QozbGJCLesqKPOpmcylMJm0GDSKbHqVdgNWmbKgtKZQgmLXo1CEJCQGAumCCZzHBgKcN0SN9UmLUtrLVh0Kupsev7j1QmmIhnUCtmNTYHAWCDJC/1+PrC6ga893ktTtZEv7ujgyLhcPH79pqVo1Qquaqnm0ZMzDPnekGVYVG3iqsXVlESJIV+SzW0uPrGhiQVVRvYN+nn4+Ayfua4NX0IexcpJojxKJ4JWrcCfyKJRKQgksty+qp7v39FNu8dCIJ7j0EiQpWoLCq3Akz1z9M7GqLHquLbdTTCZI5zK84MPrODwWIjZMmPqikXVRNN5aq16Hjo2zXefHcKiV2HWqWiqNvGlHR2YdGqyBZF4psgLAz6mwxla3CZuWlaLvay5ZdSq+PrNneSKIrGMPJblT2SptxlY2+zAZdbhtupYWGXgoWPTZAsiFr0M4uRKIuPBFPsG/Wxpd/F/XjnL/kE/H1yzgCanEUEAQ3mM0qJTYTdqWFpr4cUBP8O+JAggSGA2qHnmtJftnR7+clcnz/V76ZmO0VxtpNqooc6upyjKrBFvLFsRb6+xajlbBkgdRg27uj1EMwVa3Gae6/MjCJDJl7DqVSSyBRa7jETSefRqJTaDmg2Lq5kMy7pgsli3LBTvNGlZ4jHLAJVBg0opoFIqaLAbUCkE/vfvruaxk7MM+RIsdsm5vcOkYdiX5O6HepgMyXnZc70+Ts/E+Oz1bcxGMxg0KiRRQtCrWb+oiqIk4Y3JbMSNi2Xh6fue7qex2sQ9N7RXRnPvebiHu9YtZFOrk9tW1qNTKTBoZUH/eY0xgH0DflrdZr5yUyevj4c5Phml2WlkU6uTaLqAvSx0PhXOVPYOeKPBGUjkMOvUXN/pZv+Q/B2plYrymjKypc3F6RnZxVKS5j0s5ZgIpQgl8/gTMuj18kiIWpuuAnSfDaU5OBzgw2sXMhpIoVIoUAiy7tTWDjf7B/0M+ZKyLpxWhSTJGmX7B/zs7PYw5EvSYNdTY9O9bQN1U6sLg1aJ26LlpeEgv3tlY4UtORFKs8hp5NoONw3njK1lCyWyhRLBZI5oOo9RqyKTL/GZR06SK4oURQmNUsHSOgseq/4t9+BzcztvLEuuKNI7FyeVK5GiRDJXxGPVo1EJF9X4rLHquGdHB8+e8XJmNsYip6ztFkjkePTELALCRdXHl8qI/39B2uEyKPVrHP9VrllvV/jL872/HGPhv/sheruH3qxT8cl/P0rvTLzyt0+dnuOHH1xBY7XxV/Z+3qnQNWqVFTDko+XZc0mSEC4QZJ+NyiKO77Y+zhVjPDUdLYtPygfr3+8bPs+h453el8emYy76/jFGLmVNXCowML+WpyOyNfHXHu8lnJJn7vvnEvTOxPjSziU0OAxvYqNolAq88ez74qoB7wyAWPXqNwFS8/F2z9alsGf+u5+7XyZ+le/9Yq/9fo0Q/iaLzV+Oy3E53p+YP4vnhaAXOAxctbgam0FNMltg/0iIFpeJ1Y12oukC+wb8rGlyMBuVWbxN1Ub+7yfXkiyPB0mShNuiq7B+5CJUYN+gn/94dYI/uLqZFQvsPNvr5c7VDZyaivLo8Wn+cFMzf33nMkqizA5XKwUWuUy8PBJkNJDEbpTd9AxqJasbHfzs9SmOng2TKYjs6KrhldEgk+F0RQg6mSvQ4jZxfCqCViW/r4IoMRPNcP2SGqYjGR44Ns2hEXlk/UPrFjARSlMURaYiaaQyS71sKodaqZCZywq4aVktO7o9WPVqAsksNy+vY5HLSO9sDKNGxX27u9g3EGDIl6DFJbsRSkiMBZIschnRKAWanEY+92APw74kDqOGW5bXUW+XNY5i6QKZoqw7ZNapqLXpKYmwuc3FXCxDs9NMMJHnnodP0+6x0FVn5c9/dpJcSSSTLxFK5Xm+38e3d3ejUIBRq2JjSzUqpYJCUcSsU+Ox6vDGMjx2chaXRctcTNabGg8mmYtn6KixMBXJcPeDpxgLyJphFr2KVrcZETg0LDcVr+lwUW8z8IPnh5gMp4mmCwQTORqrjfzjXSvJ5EvkCiL9c3Ey+RJ2o7r8HYOEwKg/yfVL3GhVCkb8SfIlkWvaXewfCJArlpAAl1lLU7URm1HD2bJ+mQDU2vQVsfF/e2Wcz21v55bldezqrmXIl+DkdJQ1jQ4ODgUY9CXIl0QKJYkWl5HNrbJ2l16tZF2Tg9fPRrhlRS03L6+TR/6iGWx6NQqFDNLesNTDsD/B76xfwIbFTiTkBp5WpUAQJAwaJcFkjsYqI1e3Onl9PAQI1Nn0vDoeYnAugcuqZVtnDbetqieWyRNM5lErBURR1sj6/LZ2GaQ8MY0owtlQmkPDAbrqbPz13kE2tTpZ22Sn3m7gA2sayBVK9M7GeeTEDCcmIyRyJfrn4hweC7Gjq4afvT5JviDxi6PTjAVS/Om1Lewf8rNzqYeF1abz9oF0vsRf7x3kyzs72NZZw6qFDsLpPC8O+HGZtVzfWcM/f2QVOrU83pstlNCplZUG56ZWJ0VRZCKU5Qs3tFfAw3aPmZuW1VFl0uKNZciVQUFZp0hEo1RU9IkcRjVj5e+3UBS5Y1U9KxbYZU0uCTRKgTa3iYG5OEVRos6mp8aq45GTKfRqZcUFcH408tR0jC3tLgwaJZPh9Hn73VuBLelckU9vbSWQyJHIFfnh80P0exMUSiJHJ8Kcnonx1Rs7MepUzEWz7Bv0y9+rRcvmNhfVJg0/PzpF71wcl0mLQatiLpZh/2CAnV0eXh0LMhPNVu75ubndfF632GWi+Zw6r1CSSOQK2JWai2p8qpUK3GYtV7VUs7Glmki6wMGhQEWg/mLr4/fCiHeatdxzQwcHh/1MhTO/ddIOl0GpX9OYDqc5Nhf5Lylk3q7wv2931/vCWPjv1Ed5q4deAP7j1YnzACmAIV+S5/p8fHjdgvd1lG8+3qnQ3Tfgp6veyi+OTgFyYmQzqCmUJDSqN+6zVqXglhV1+BK5sgPEG+vDadaet7HNu4psbKlmbZPjTRvnfHENb2ZlaVUKlngsFEsi6dwbXYpjExFeGf3lRacvZk28F2Bgfi1/9IpG9vZ6OTUdRaNUlLsgCmai2Tf92/cbiJiPdwJADBolDXYDh9/Ds3Wx7+G/4rn7VQHnv8r3fjHXfr9GCH+TxeYvx+W4HO9PzOchu7o9BJM5REkeQxoLJNCpVaxosLFv0M9YIEmL28ymVidiGTj69M9P8q8fX0O+KHJ4NMRUJEO9Xc/mNictbpM8BqZRIQJGjYpPbmzi2nY3dQ49HqvMovnyzg729vpQKQSCyTx7e72MBpK0uc3sXlXPN29ZyjNn5gin8lSbtaxvqmI2muGJnhmcJh0/f32Sa9qdfO2mTh49McOgV2ag1Fh0VBm1HBoOMhvNIAHxdJ4Gu54t7U5e7PcjShK+WBZvLItSIfDD54f4i23ttLjMFVFpjVIWKteqFLTXmNGolGxqczHsS1Lv0LNhcTXxjAzWRdJ5fu+qZkqixEeuWIgoSvgSWQ4OBtjY6qRvLs7VLU4UCoH9gwEmQ2m0KgValYLDoyFuXF7L/kE/hZKEWa+mJIo4DBpWL3Qw7IuzrMFGsSQzMB58bZITU1F+/+pmXhjwM+BN4DRrserVpHJFhn1JfPEszU4T/+Mnx8kWSqgUCgolkQVVBr6yawlVJi13b2/n+ESE/UN+0vkS8UwBS3mE84V+H+PBFKXyOOLOLg8ui5avP95LvzdBOl9ic5uLJ3pmORtMVVhNVr3Mbjs8FmJ9kwN/IofHpieSzmPUKtGoFKRy8vpb7DIRSRdocBhYvsBWEQH/4QeXc2gkyEwkzYbF1XTV2VApZKDSadZWRuumIxkKJXk8sn8uzt++MMw9N3RwZDzMS8NBPrmxia/d1MmeM14GvAmanUY2t7nwxbMcGPRTa9ezvrmKb+8Z4MVBPz+6ayXfv3M5B4b8nA2lcFt0bO/0UGWSdZ4CyTzjwSRuiw6HQcO9u7s4Mh7GH89h1KrY2eXBrJN1ogRB4L6n+5iL5cgXReZiGZ7t9crjdAN+ljXYUCoUPHJihp7pKLU2PbtX1rNygZ2vPn6Gkijhi2e5tl3LH25ahNOsZf+gn4nwNMvqbWWgOM+TPbM4jJqKUcF4MMVNy2r5o82LGfYnWFZvY+sSN+OBFAcGAzQ5jNy0zMMSjxmjVkUwkePoRITxYAqnWcc/7h/l2V4vBo2SFpeJO1YtQaUQ8CZzvDQcxJ/IVRwRXWYtH9/QhF6tIJjK88pIkFa3mQ+vXYBGpSgDxEX8sQxXLq7mpZEgh8dC5VE9BYtcRlYssCOWm9zN1UZ0agWfub6Vxmoj+wcDjPqTdNZZqbXpuXFZLaeno4yH0hSKEvFsgfYaM8O+BEVRQhDkvDidL1Fn0zHsS3D/swPct7ubsWAKk06Fx6bjtlX1CMgAFkC+KDLgTXB8IsKtK+t55swc09EMJq2sj6ZUCPjiOQ4OBdjZ7eHep/uZDKfxxbNyziXAx69s4pbldXTV2Xh5JMjRs2G8JYnHT82wpd3FF3cs4dDwW+d283ldNJ1nc5uLvX2+ChicL4o0XELjU0J2Rpyv2bQqBRtbq1nb6GBh1aURGy6lwXloOIhNr2bDomrs3ZqyftpvD5Tz2/NJfsvir58bxJ+dX6i/ukLmnQrxgbkEm94HxsKvgz7Kua+XyBYY8iXe8u9G/InzrFp/2Ti3aBcAb0y+j1qVoqJ3ZDOoKZUFC7XlA+bo2TBXt8r3Pp4pVvQobllRi1qp4L7yZj0fB4b83L2tnRF/klAqXwEx8yWR/rkEdqMGu0HN6kZH+e8D5xXX5xbgWpWicjjv6fVW9Ak2t73hCnIxQM07iRLq1Mp3XROXCgycu5btBrkbJCCc1wVRCG9Pz/1VaBl5bDru291FOl8ilikQSxeot+sx6VS/cibTr/K5K4oiyWyRVDnBjqYLNNj1uN8n4Hz+vd+you5913y7mPvyfowQ/iaLzV+Oy3E53t9I54s8emKWfz44iiDAF3d0sKnVyUQ4zecfOFUBHJ7r8/Nkzxw/+MByWtxmOmutBBN57tszgL9cnE2G07zQ7+OLOzrY2eXhuX4/pVKJT21uY4HDwGtnw3h7sjTY9Gxqc2LRq/md9QvxxXP8yU+Oc2b2jYbck6dn+eePrOaO1Q2olQrGAykeOTHNsYkILrOOkijnT4+cmOEPNy9iaZ2Vze0uQokcj5yYYbHLxOe2tXF4LMR0JI3Hqmd1o53pSIZHT8ywfamHzW1O2j1mIukCrTVmDgz62bqkhkPDAXpn4xRKIjq1kvYaM1cuquK1sRCiBI+cmOHz29vRa5Q4DBoeTc2wrrmKfEnk0FCQEX+SerueaztcfGDNAgLJLNcvqWHIl0SlEnCbdfzDh1fitmrRq5VIEtRYdHztpk6ePeOjdzbGorL5jTee5dCQnwVlMW+zTsWwT84HnWZtRaMomi5g1qnwWHVE0gXcFh2HhoOk8yVUCoFwKodKqeBsMMWzvV6uaK7m+GSEze1OOmot3PNwD6lcCZtBgyhKDPsSSJI8Qriru5Y/uaaFJ07N8vrZCIUyOGY1qBmYi5PIFrHo1WX2jwKTTsV4MMXOLg/Zosj2pTUcn4jgi+cw62SHNI9Vx+Y2Fy/0+2isMrC9swaDRsWgN062UGLj4mpcFh3BZI4nemYxa1Wsb3ZwcNjKbDRDJJWnJEq01ZhlcOzULMFknkPDAa5YVMUL/T6+9VQ///57a9m+tIYtbS78yRyPnpjmxQGZJbWiwU44lUeSJF4dC/HU6TluW1nHzm4PgYQMJunUCu5+sIdXx8LEMoWKQ+F3bltGIJHjqsVO6uw6Gai065mLySDoc71ezszEMevUqJSyFlU0VeCV0SAfXNtAtiDyradlQetweXzt6dOyy+CtK+o5Mh6iqdqEyyI3de95pIe5WBazVs3AXIJnTs/x+RvauXN1AweHA6gUClK5ItUmLeFUnp1dHqpMC8suiEWG/Ql0aiUdtRbS+RL9cwmGfQnq7HpuXl6Hy6KlWBJZ5DKyU+GhxqpjY4sTpUIglinw7acHODYZQaWQxa9fHgnyhRs6mImmeXEggMusYffKeuLZIj97fapi4HT9Ejd2sxZtUeLz29t5+swcI/4krW4zW9pcTEcyvDQcZFtnDZvbXCDAAoeRLzx0mrOhFGqFgkFfglNTUf7qlqV8dls7r46GmClPZtzYXUvPVJSJcJpktkiuIMpja20uHjkxzXgwzYGhANe2uwgl8ySzxTeZ+dTZ9axpdNDiNhPP5BnyJiiUJFQK4TzB8omwLIg+nzuZtSr+bGsLCxxGHjo+LTMfTRpuXl7L+mYH9zx8mkS2SN9sjDtWNbxtbjef1z12coYOj4V7b+3iwFCA0UCSpbVWti2tuejG57lNZ388yx9c3YzTrOXgcIDn+nwsrDKypd2F533Kid/c4JTrhS/u6MDg+O2Bcn57PslvWcxEsqj1b6Ctv6pC5p0K8UPDAf74mpb3jbHw61KAKQSB1hoLNWfljb8oSqRzRRK5Iotd5vMESc+NS2GFvNXYzqY2JzevqOPEVJRPbGiqdGTGgimWeCxsXeLmDzct4scHRjkwFKDDY+Eruzo5ejbMdESmae7s9vD4qVnGAikS2QIqpdwBfG08zJ7eOdY0VvGjA6MVELPGomOxy8QzZ+YYC6ZorjZWwKVgMlc5BM4twDe1yqyrex4+TTSTx6pXUyxJnJiM8uVdS7j/9m7yRdkB6K3u1Js/u56NLU7yJZHHTsxQY9W/JbPrwrhUYKAkSkxF0oiSRCSdP4+emy+K7/hv38vrvVucex+myvdhc5sLt1WHSqG4ZDbQr4suUaEkMhPJ8ETPLCP+ZGVNzYOk9e8BOL/ws/1XjL1drCbbewUNf5PF5i/H5bgc728USxJTkRRatZJ0rshfPnaGvX++iZeGg0yG0ijLhVmhJDHqT/LySJCbltWyrbOGFwZ8+ONZFIJApljCbdHhjWd5/WyY21c38POjU9yw1EOdTc93nx2siBfniyLPlAWMLTo1e3u9DPuTCALM995OTMZ4+PgMH1q7AG8sw/4hPz95bYpqk+YNsV1BPgNnIxnufrAHtVKBUaukUJKIZfJ84YYOblxWS64oolcr+Ou9Q7zY7+XvP7yKBoeBbKGEN5bDF89yw1IPkiRh1Cr56o2db5x/VQZWL7TTPxdn/6CfT25cxBWLqqgyaYhnChSL8JErGrEbZFCm2WkklMqxt8/LqakoX9rZQa1VTzRToMampdaip7pdSyJbwGHQIgjQ743zdM8c27tq+PC6BUiSRCpf4sh4mH97ZZzrO2sYmEvws9cn+fZt3SyptfBsr49gIsdilwlBkA1jMoUSRo0Ko1ZJlUnLTCSNgCyqbdVrKEkS0+E0p6fjXLXYyY8PjPLsGS/37u7i+iU1HJuIoFcriaXzNDtNqIcCfOPmpWXmDwz6EmQKJZQKAZVSIJTI0ew0cXg0jNUA0XSekgT6jJLGMiujwW5Ao1LwlRs72dvrJZjMsbDKyPpmB7FMgWqzlj/uaOHo2QjfeLIXg0ZFm9vMN29ZymQ4zWd+fpJopkC1ScPvb2zmz65t4cRklBF/giqTli3lM/4XR6ewGzWEU3kaq4xsaHHiNGkwaOT18NkHT9I3Kzd9VQqBJbUWrml3MeJPsrDKSDJX5GwwRbYg8tiJWf72xWG+d8cyXh0LM1YeRS2KMlAxFkyzf9DP2iYHxyfCLKiqp6vOij+e5Tt7Bvj01jb65xKE0/myLpAOlVIhM5OSOQwaFXt6Z5gpm9lYDWoS5dc/OBRg+9IaAoksm1qd6FRKXh0PkS2I2A2aSh0QSRd4eSRYzgdCSILE2iYH25fWoFUryeZLPH5qlvFgiiqThs2tLq5b4kalUPBXT/Ux6pc/04mpKKenY3xuezslUeS2lfXkiyJi2cFNo1Swt89HMJnDadYSSOQolETGg2me7Jmls9bKiwN+tna4mI1l+cHzQ7KR0zlg3327u9CplJyYjLKs3sa17W4i6Tz7B/1yTVFroSSKBBI5Prx2oezSmMxh02swapXkiiL7BwP89Mgk1y+pYWe3LDofKb/GZ7e18dpYmLPBFFaDmo0tTiZDKR47OUOxJDHiT3LHqnpAYCaarpj5nNtAf6Hfz19c34rTrKPFbeaFAX9531Bi1atRKaHBrieWkR0sFYLATcvrWOAw8rmHTpHNlzBqVRVg/t5bu9jVXctIIMFVLU7UKgXqt9mDz83rfnxglE2tTtY0OtjR5Tl/v7vImM/hp8JprAY1X3+8l1AqXxltPDQc4Ks3dv5SZJJsoSSD0yWRJR4LgUSOXLme+W1scF4GpX6D4ldRyLxTIV5r0yMIvCfGwvs51nMp17qYv9WqFVzb7mJv7xwD3iRalSwU2O6xcN0S95s+33spkN9ubOfz29v502sWo9eouOdh2ZZYrZRdAl/o9/GlnUvY1Opkb5+PHx8Y5S+ub2P3yvrKdUVJKosgylRvVbm7ksoVGfGnuH6J7Bw3v1nt6PZw/55+jpyNUCjJa2dvn4/v3NbNyoW2yj06twBf3egoi3CnqbHKbjbxTBEJiZdHgly1uJp/OjhKV50No0aJ06xDEN4o8i/87PmiyIPHpvnGzUvRqZX8/PXJt2V2nXs/LwUYmLdhrTZq8MXl72pHl4dn+7yMB9IVJ5J3AhXe6fU2tjorOl4Xu57fqrNxeDRUYTxeLJPp102XaC6W5Z6Hejg5Hav8bG+fnBxMRzJUm7UXfY/e7rNZdCq+++wA48H5ZOa/fuztlx0h/E0Wm78cl+NyvD9RKInMxbLkiyXZuS1XxKxTURQlEtki3lgWtVJBsWwHJwAalQJvLFsZmXquz1dxmVMpFWV2ap7+uQS7ltXyb59YiyjC62fD+BNZZqKy7b1CEDg2EeXJnlk+dmUTI4FkWTdGdruz6tXYDBqCyRyCADaDhu2dNezt8zIXzWISZXHtrjorm1pdTEZSuCxaCiWJeKZAIluoiFv3zcY5OBTgf2xZzFgwxT99ZA0mnYqfHJlk2JeojCVG03ka7Ab6ZmN44znWNjvYtawWhQB/89wQj52a4eMbmsgUiqxtcvBcn49krsitK+oopSSe7JljMiSzLnZ117K8wc63nurjyZ45ru1wkcqVcBjUKBUCwVieQ0OyQLTVoGZTq5NbV9YTzeT53y+Py86DZg3rm6v502tbWeAw8M+HxhgPpuidjbGt08MTp2Z5YcDP7pX1PHPay1xMHjeKpgs4jGoMaiV1dgOxsjtclVFTdnWmItxdZ5PBssOjIT6+oZE7VzcwF8vgMGjY2uFGABqrjHzuwVP87A+uoM6mpyRJKCT5jHh+wMdtKxs4Mh4ikS3hsclMoZULbVzdWk3fbJxnznhprTGzpc3Jrm6PLDyvU2PRq1AIAptaZY2m6UiaazvcLKu3srapCoUAe3u9jAVTFEUJo0bJ/zo0xvpF1XxwTQM3Laulby7GM2fmeODYJDcuq+XaDhetbjMWvZpPX9tCvigSzxZI5op88+Yu9g/6K+Ohm9qcqJUKuuqs/N2HVhDLFFCUwb3ZWAanWYvHqufQcJBsvoRZpyKdlwtxUZIY8ifZvrSGmpZqktlCWfhaxB/PEc3I4KQoQrpUIpYpYjeoyRZKVJtk57iNi6tpcZl4bTzE830+6u16Etkic7EMTdVGvrRziTxVUBQr4NW5oVYKRNIFGquMfGrTIjo8ZuxGDZqyMdH9ewYYDSSJZQpk8yKHR0L86HdW8UTPLHOxLHqNsvJcT0dlqY47V9czE8nwQr+PbZ01KJWyrtrAXJxoRmbizTvQJbIFBrwJNrY4SeWKbG5z8kK/j77ZOAaNkmhaQKEQCCVlZ/FtnTX4E1m+//wQRo0SrUqJIMiv3+E2U23W8lTPHMsbbISSOVxmHYWSSDxTIJ4tkiuW6JuLs7O7Fm8sy/efG8Qbz6EQYEWDnZuW13Ljsloy+SKJbJFFLhPfv3MFz/f7WGDXo1HJUxG1Vj0vDvorDfR8WduqUBI5PhmhwWFg1UI7Fr2a8UCKXLFEKl9kbaODjS1OJkKpilOgzNyTR3GrjPJ9WeAwEE0XeGU0xEevWIhaqcBzEbnZG/p+fiZCGUb8Cert+vfExJ+XSDFplTx6cpZAMl8hOEgS9M3FOTDk5/ZVDZdcB1/Y1LYb1Fzd6qxMq8wDU79tDc7LoNRvUPwqCpl3KsQ3tcqU0qlw+qIL4vezgL7Ya2ULJSQJAsk36yy91et6o1lmoxm+uGMJ+wb9jPiTtNWYubG7Fo/tzZvaperCvNPYzktl2+GfHpnEn8hiN6oxa1UoFAK9c3H2DfpZ2+jg2V4vTrOWerushTQXy/Jiv5/VC2VBQlGigurnUzJrqdkpJ0BAxRkjlSsyG8vysSsbWd3owFHucMUzBZqdbzCJqkwa7tvdRSSVx6BR8WTPLDVWHbmiyFw0i82gRpLg+GSENY12emfj9M7Gea7Py1du7KyMbzlMGvYN+s/rjCSyBSbDBQ4MBVjTKCeZ9XY9CLC2SRZ6lCSJVK6ITq08b/O+WGDAG8tyYMjPuuYqHjs1yy+OTlVsel8aCRBOFWiuNr4rqHDh6zWUBWmzhRJ/+8JwheX1buv5Uka33u2w+nXSJZI/l5/hQPK8n48HU7w6FuL2VfUUSvJheTGH8Ft9tpdHAnzmujZaXOZzQKlfvit0qUD5Lzv++JssNn85Lsfl+OVifr8plET2l63it3XW8OjJWXmUxabHG02zdYmbrUvcWPVqgskcL48EeXkkSL1Dz3Q0g1Ih0OIycXIqSrEkMhfNkMqXAHBbtIz4EziMWqqMGp44NVtuUpVQCgIKhax9MuiVx9AWOU0URBGVQqDWqkerVpDIFmWnt1gWUZSos+v54QdW8OKAn5loBqtezXVL3NiNaiTJQJ1NT+9snFimQKEk0lxt4upWJw8fn6bWpketUvC3H1xOMlfi8w+d4vhEFKVC4IUBP3v7vNx7azejgSQKQeAbT/ShEGB9cxWf396OVq1ksdPMDZ0eDBol/kQWh0HDumYH4VSebz7Ry5nZOJmCiFal4OUR+Rzc0uak35tgc5uLf9g3wv23dxNK5rn7gVNki7IFvD+R49BwkO/e3s2L/X5+dGAUu0GDSafi0HCQ+3Z3U2XS8NjJGdwWHa+MBPmDqxfxnduWcXAoQKFY4v9+ci2ZfKnCarPoZBHuVQvtWHRqzoZS2I0a0vkSi1wyg/ixk7NE0wWcZi2hVB67QcO/Hx7mleEgX75xCV11Vn73ykYePDZNOJUnksqztcPNE6dmORtKUyiJPHJihk0tLr59WzcHhwKcDcqg3DXtLsYCKb7/3BCz0QxHxkM8cWqW+2+TmXHD/iSLncayPqmIXq3iE1c1oVYKFIoS/374LNd0uBkra1qVRIlAUgbRDg0FAPjU5kV8/7lhhnxxvnGTzOY6OBzgpeEgjVVGrmqpxqpXY9ap+JeXxlErFGxqc3LDUg+JbAFJkjWJjoyHeX08TFuNmZuX16FTK1ngMJDMFvEnsiysMhDNFKgyaqi1yUL02aJIV50Vu0HDqekobouOk5MRVjdWsbapihf6/ezq9vBsr5dRf4pMoYRZVNFeY2b70hp6pqM8fdqLy6Ll2nY3S2os/PVzQ5h1KrrqrFj16goYUSqv/Xn5jnlwShDk589m0LC0zsKhkSB2vYZ2jxmbQcM9N3TwyIlpnj49R0Ej4UvkSOWLjAdSFIqydpxUZkPlSyK+eBYR+OZTfXzrli4EAb75RC8fv6qJGpuecCpPKlesgFL5kkiz04g/kSOeLWAzaJgorwuNSk1VmaUmShKToTS5osiOLg8np6L0zcojnyqlwNJaK1e3OtGoFPzxNS3kSyINDgOCEEKlELDo1eg1SuLZIi0uM1qVgmfPBJksOwEWRYmXR4O8Oh7i7z60ArVSwZ5eb4Utf9e6BTTYDUyEk7wyEuau9bKpwVwsU2mIzzvdTYbl9z8ZTvPd27s5OBxg1J+isdrAji4PFr0au1GDTq2oMNfGg6kKm0ohCEgC2Axqouk8NVYdBo0SpeLiakyDVsmVi6rZsFigWBLRqhXkiyK5gohKeWl5Xr4kEs8WOTkVxRvLnv+7oshkOPOeQKNzc2NRkoik8jzZM8e9t3ZViAvw29fgvAxK/ZpGnV2H/5z1/assZN628C+7rl1KQfx+FtDvdq03nNYy2AxqvvF4L+F0AbVSQBCEt3zdbKHEvsEAj52cYVOrk3VNDrZ11hBN5/HGsm8CLN6LLsz82M652lTzB9xUGawJJvO4LTokSSKWkcfwaiw6fOX3cOfqBra0uyrfwTce7+XI2TA3La/l1hX1PHZyhnxRRKuSQZxqs5ZNrU4ODsuJRKEkUW83EE7l+YOrm1lYZaw4/zRVG9nWWVPWWxLfNPN9Y3ctbW4zL40EKxuiQaMkkS2y0GEgmMyjUijIFUuMBVI81+djXZODyXAao07F4FwCX1y2XbYZ1OTLIMVoQHaA+f82NeOx6tnb6yWaLlBr03Ploir8iRyDvgRXt7wB+lwMMDD/HT12cpYai74yJ35oOIDdoOHD6xaiVigu6rC58PUKJZEne2Z59MRspTNxMev5ndbApXQ2Llx/52qRKRWyZsT7pbV0MaCN/LkyaJQKUsiFkSDIjiDeWJZMocQ/HRyj4SLA6Ld7tqYiGV4c8LO60VE5eOfjvXSFflmg/JfZc/87TR4ux+W4HP/1cWGHu9amZ2NLNalskelwmvtv62bfoJ9oOk9rjYVEtsjjp2YY9qVY5DKyq7uWjS3VuMyyzk+Ly4THouPV8RA90zFKkiw+PS+C/EK/D4dRw60r6qi368kW5H1ZqRCQyu+nyWkkVyixrbOGx07NMBfNolYpmI3K+cb6pir+zytneW0szPc/sIw6u547VzcQTecZCaR4+Pg0LW4z2ztr+MquJewbDHCyzHbY3OZiIpSiby7GR9YvJJmVQbGXRoKM+mWdrPlzZSyQYv+gn83lhqfHquOm5bWsa6rCpFXxqU3NzG/vE6EUIHBqOkp3g5XHe2d57WyETL5UET0+PBripZEgt61q4Pl+H5F0jslwmlhGNnUZCcgjY7miiCBAMJnjxQE/25bW0FVvxWXRkcgWeHU0xCsjQXZ1e/jw2gVc2+GmscqIRiWPKV67xEWdVR4pemk4yFQZVNzc5iKcyiEg8U8fWcXB4QAzkQwem45VC+344lme6/PKekrIefxIIMnPX5/CYdTwg+eH+MCaBm5aXkcwmaPGqmNvn5c71zTwvTuW83y/T3YXdJvw2GRR+dWNDra0u7Dq1Lw2HuabT/ahUirQqZUolQqiadkVcH1zFSenIizxmEnnS7w44GeorMe0tcNNlUnDYpeJQCJHU1nqQEDOMQolsezwqEWlEPj6zZ0oAJdZRyiVY02jnaNnIzx8fJone2a5b3c3HquORU4TPzkyyStjQQpFkes6a9jW6eYbT/QRSsk6QyOBJP1zce7Z0cGWdhc/OTLJnjNePrmxmWdOzxFI5igUJQxaJZ11VrZ2uHlpJMjXHu/lE1c1lV38Qvz+1c2cmYlSFCW+dWsXh4YCeOPZCjtrJpLh/j0DZAoiM9EMe87M8Z3blrFrmYe+mTib2lyV3KlQEknni6xvquLxk7PMRjOYdWrUSoEGh4HrO90Ekzm+t3eQm5bV4TRrefyULDzfXW/j2g439XY9X3+ij2xBJJTMs6DKwLN9XhxKjcwmjGfRqxUsrDKgAP72gytQCPDz16c5cjZCo9PErm6PzFoLpEjlSnisan5/YzO7V9SRyBX5hw+vRCEILHYZef1sGKVCwKpXE07JDoMLq42olQJGjZo/v66VQ0MBHEYtKxfaqDZp0agUsph6XK6b1jQ6ePr0HKGkrBuWyZdYVm9lV7cHQQBfPIsgUGZFFqk2a7mxuxZRgm8/08/pmTj5osixiQi9c3G+tKODl4ZDRNJ5lArZoW4ekHpjf5SosehQCAL/+vI4m9qcrG10sLXdjS+e5cRklFUNNvzxHN+4eSlHxsNIQGethYG5BGqlnEdLkvy+qoxagglZx+1icjpvLMvXy/VUUZT14pqrjXz+hnaGfUmi6cIl5YdKhYAoSufJhcyHRqVggUN/yaDRhbmxQhAw69RMhdOV5v7ecnP/t63BeRmU+jWNz17Xxglv7r+kkHm7wv9SAZn3U9j33a515+oGvPHzndZOTsdQK4Wy05rwlq/7Zp0XoayLJBAuCzqeG+9FF0YQwGPVE0nlyZdEzFoVu1fWs6OrpkIp/sSGJmx6NQ8em6ZYktCqBdRKBUtqLbgtOm5cJruLFEsS+wb99M3FKZQknuyZZeUCO391SxdHz4YJJHI0OAysWGBjOpLhwGAAUZJwGNVsbKlGp1ZQY6kmmMzRWWvFn8jyf14Z57XxEPfftgyjVnke8CdKEtl8ies7a9jT660wnlQKgdpyEvZkzxxKBVzT7mJzm5M6m4Fqk4bpaIYRXxKnRUsqVyJFCb1GWd7YSyxymlAr5ev8xYOnSGVL2A1qxkMp6u0Gvnt7N8Fkjnuf7j8P9HkrsOStBORzRfG8OfHrl7iRAINaifYSN+359f/w8Tl+cXT6vN9duK7e6v1duAa0KmWFRl9v11/0+zh3/Z0rQL9/0M+jJ6bprLOypc31S43yXQpoo1QINNgNmHVqkrli5VDXqhRUmTRMhdMcHg1x+CLAaAFY3WhnTaOdSLrA0bNhDgwFyBRKTIXTbG5zvunfvJeu0H8n0+ydQNVflXPh5bgcl+O/L7yxLN96qo/xYJpEtkCmUOLpnlm+fVs3dQ4DD5+Y5qrFTpbVW0nliuwb8LNqoZ1r2t0EEjleHQuyrdODy6zFZlDzXJ+PnV0evrSjgydPz9E3G2dxWZzbF8/y+KlZVjc6uHF5LVvaXew54+W1s2EUApQkiWan/Ldj5QL6Hz68koNDQQbLTnKy2HqKp3pmyRREXhzwc9OyWhxGDfFcEZD3scmQ7FI1GUmze2UdNy6TnQSPnY0SSuX4yq5OLHo1T5+eY+sSN1PhN8bmpfL/BWDYn2T3ynpmImm+cEM7HquefYN+Hj85Q2etlU1tToolEQSBzz1wSm7ACAIDZSe6eVFkJMgWRQa9CXZ117Kp1cmLA36mwmkUgsB0NEOxJMlMCJUCnVrB7hV13Ly8lnS+xHgwxd5eLx6bnk1tLoqiiCAIfHjdQvacmePFAVmseGNLNYscJryxLN98UhbMLpU1jw6PhrhnRwd6jZIBb4IVC+xc1+HGoFXii+f454OjaFQKtGoF1UYNVy2uRqtW8M8fWUWNVYdVr8agUaESZPBDFCUeOjZNc7WJNU12dnV7UAi1lEQRvUbFyyNBfvjCMFc0V/Hp61orJjThVAG7QU1JkpiJZjg1FeXKxVUscBhI5Erc+3QfY4EU8WyRWLrAkz2zfOf2ZSyptdIzHWVLm4s9Z+Y4G0pj1qmIpvO015i5ps1FMltggV1PJF3goePT9M7GaXYa2dLmot1j4YfPD/FceQxtXZMs/TAVTlMUJVYtsHNgKEAknUerUqA2qsnmS4wGZBH4nV0e7r21i4NDct76ndtlJljPdJwFDlmL9Mx0jJ7pKN+/czlN1UasBjVzsSyJbIFjk1GuaXchiRIbFlezyGmiJEqEUnmUCoG/urWLWEZmaT16YoaXRoLc2F3Lzq5asoUS0+E0bqvcDL7/2QFuWlbHX+5awoGhALPRNDctq2NJrUXWuSoVuHm5DEh9/sGeCrvsldEQ+wf9fHprK7u6a3nwmKzTdHWrk6d65sgUZHaQzaCm3W3muiU15IoiapUCUZQw6ZTkSyL/8eoEnR4L9+3uYv9ggGAiy0evbEKjVPB4zyyD3gStbjOLnCY+vqEJm17Dg8emmI5myRdF1jU5uHJRNQaNisdOzhJK5rhzTQOFosiLg36GvAlaayxc2+5iJprhH/aN8LErG7l7WzuHRgJEUwXcVh0bFldTZdKiEKDOrkeSZCCpzq5nW2cNH1jTQEmS+NiGJo6Mh9k34CeRLXJ6OsaTPbMsb7DTOxtDADa2VvNM7xxLa21saXNSbdaSyhVprDKiVMgmRM/3+dnb68MXz5LKlfjU5kWE0oVKLr91iZumagNGrYcTk1GmI5mKy2KDw8AVi6p4smeOvrn4u+Z0MilBrqeUCoEPrGlgc5sTs06NALS5zXzh4Z6Lzg+zhRICYDGoubbDfZ6bn1opsMRjYVOr65Lzu7eqO+drW188S61NxwfXNPxWNjgvg1K/plHvMNBc5/wvLVp+Wfez91PY992ulS+Jb3JaA97VaU2pEMrij1V4bDpeHgkxE0lTVy7ELyx435MujASb2pzsG/QzHkjymetaWdtcRSSd5ydHJpkOZ2hxm9jWWUOL28QPnhsilS9x06padnR5KJRESuUugEallDfhMtsoV5D4xpO97Oyq5Y5V9SyskjsjmUKJMzMx1jQ6qC87XFjKs/lDvjhWvZo2t4ll9VbuWNXAt57q58CQnw2LqivFuiRJSJLE/3n5LJtanXzr1qU8cmKGEX+SVQvtbFhUTf9cnINDfv7i+jacFh37B/2Ekl5+b2MTr4zIHZKtHW6eK2/OybJbjKuc/JYkqTLKsMBhIF0okSuKjAaSHBgKsK7JwfN9fg4OBbh1ZR2hZL4CliysMrKzq4ZYtnjemOa8gPxr42FyRZG9fb4Kw+aDaxoqXcBLjXdag7PRDJLE2462ZgslVjfa+cUxNWeDaYxaFYWSRK1Vy9YON4lssUy/fmc713PX37kC9OPBFHajmjOz8fN0qt5LeGNZ/uqpvvO6Mu90KN+4zMPSOgv7BwO80O+jJElYdWo2LK5mzxlvRQfgncDoQknEl8jxykgQg1bFqgU2PrxuAbtX1vP4qRksOjWZcsd/Pt5LV+jtwO1AIsdMJIPDKI/A/lcCQ79uGmGX43JcjvcnUrkiCoUgN8r6vDx6coZUrsTrExGe6Jnlw2sXolUq+YsHTvHwp66gJMLyBTY5VwimWeQ0srnNSTpfZCSQBwT+9eWzSBLcuKyWre0uNrY4iWcKvDDg42dHJolnizQ49Ax5E9gNar59WzdP9swy7E/S7DSyudVFIlvAbZYbYtUmLbtX1hFO5TkblFlQT/TMksqVEAQYC8jCzMlskX85NMau7lr+4OpF5cJc5LWxMAogX5JQKwU662Tx3QePTfOhdQ1019vQq1XUWHUYtSpimQKCKANSkgTtNWbMWhW1Nj2tbjODvgT+eJZXx0KcmIpycDggA1w6+OYtS2l1mysso5IooRRkBoIoSYiSnIdpVQoCiRzPnvFW9CUXOAxo1Qri2SI1Fi337Ghn1ULZBe6LD59mKpLBrFORHwvxVM8cf/9hmbnynT39TIUzZbHtEC8PB7n/jm72DwaYi2UrUgO5oki2WOLAUIDOWgt/8tMTgNzmXNNo5+s3d/Lpra3s7fWx2GViY2s1Nr0GlVJgkcvEgcEAU5EMDQ49O7s8bGp18sDrU4wFU9zzSA8/+4MrUAqQK0lE0jmOTnh5vs/3xihgMsfKhXYcRjU/fGEYUaKcV8hOeXa9hg2Lq3n4+AzHzkZRKQUsOhUGtZLxYIoX+n3ctKyWtU0OJAl+8vtXEEnn6ZmOMh1Oc1WLE41agd2owRfP8a2n+jk+GSGRlYHK+VHMFQvs9ExF2bCoihF/kk9vbeXEZISpSIZWt4mXR4KVPDlfFFEpFaiVAr54Dr1GhUFT5Jp2F/lSCZfZwO6V9VzbUWAilOL5Ph/tHjM3Lqtj36CfA0N+rl9SU5EWWdfk4JWRINd1uDHpVJQkGf4siSKvjoUY8iVZ5DJxbbuLzloLxyYi2AwaIqk8X3nsDDu7POzqrsWoVXHXuoUcn4ww7EuwrsnBYtcCEtkiT5+ew6rX0Oo2sbrRQTCRY3WjndlYhmxBJF/WjDs4HOC6JW5OTEZwmrVk8yXu3d3Fa+X30eI2sX1pDfGMLGUx6k+xyGlkw+JqvnVLF1969DRffOQ0v7N+IZvbXCyptRDLFPja47344lmKJYkDQwGeOe3lvt1d7OjysK7ZwX++NsEip5mrWqoZ9iUolIwcGQ9h0qnxJ3LsG/CzvMHG6kYHyWyRvb1e1i+qYl2zg/ue7mdDSzVb2ly0uM2oFQL/+spZFjgM3Ly8lnVNjsr39+dbW3Cadezp9dI/F6fGqmNzq2ya9K0n+4hlCgx6E1y3pIb1zVWcDaUAiX/6yGrCqTzP9/mY6cvQ4jZTY9Vj0atpqjZUJBo0SgVup45NrU72D/nJFErs7ZNZoE3VRjznaEH1zyZwW+VnJpDIcWAoQK4oviv5YZ7pLwjw1RuX0Fht5MUBP8O+JEtqLezq8vCpzYv5pwOj79h4LpREElnZTVupEDDpVDRXG/nBB5bzQr+fqUiaNrdZnnZ5D6DRfN4vSsHKzxSCgEYl0OExU23Snvc5f5sanJdBqV/j+K9cXG+1qC8VkFEqBJqdJtY2OeistaJRCeSLEr2zMcLlzsXFxru9tii9ARhE0oWLdlrTqZVsX+omkirwzaf66JuNkyvb0b4yGuRrFzglXKrY9lwsy3O9XjrrrNxzQzvBVI7maiO+eJbPP9jDeLnbqFEqOFTWQ/jYhkY6PBYMGhUPH5/hzGyMZfU2rlpcTZ1dz8Iqw3njUrmCxJ4zXpqdRhZWG0nkiowHkuzo8lSKWm8sizeeJZouYNWreWHAz2hZO+umZbV87aYlPH3ai+Kce1MoSRRFkaIk8X9fneALN7SzvqmKa9vdKBRg0Cj5zyOT3NDlwW3V8RcPnKq4Av7O+oWcmo4y6k+yrN5WGaEbCyRZ1mBjS5uLQrljGUzkqbfL30u87LAhICfD2ztlofbJcJp8UTyP4WLSqpiKZPjBc0P4Ernyu35DQP6WFbX8/PU3WE1vB2Jc7Ab+TmtwY4uTQDLHfRcwcF4/G+KrN3VSLIk4zVr+7WNr6Z2L8/JIEJtezR2rG4hnizx1epbJUJquOhvXdrw90+nc9TcvQD8vjm/WyrP154I/wEV9tvl7MH+vh7wJErkiGqWiQhM+91C+EEjxWOVEekubk965OMsbbAz7Evzi6BQlUaqwFd8OjPbGsnzv2QF2dddSbdLyRM8ck+F0xTHGbdFSkiQ+uKbhbdmiFz9ueD6wOM84sxrUPHR8mplIpgJuOk3a80T7f9m48L5tbpMtgr/9TD8z0fn57F8Nc+u3KVG5HJfj1znmn/N9g356Z2LUWHXctKyO5Q02vvp4L4lskbFAEqUCPnFVI3esrqfGqieeKXD3g6fo9yaQkPerJ07N8cMPLqfObuD4RJSiKHI2lEIhgEal5P5n+5gIpUnmisQyRZqqDVzd4mTPGS/HJsL8/V2ruGvdQtL5ItF0QXbQNajJiyKJXIHJUJrGaiP7BwP8aP8o/oQstD6fJy1yGimJEtliiS1tLqpNWn7y2gTxbAGPVc+WNheiJOG2aLjn4R6OT0ZRlUcFP7GhEbVCyX++OsHVrXJjTpJkQXdRkmh1m7hpWS2Fksjz/X6GfQlcFi13rpHlCv7uxRH6y+LAN3TJTsNusw6tSsHWDjePnphltHwfVQqBFreRazvcJHNFvv/cEEqlwDXtLmx6NZvbnLw8HGAinOH6JTU0V5uYiWR5bTzEqekYJVEWa68rO329OhbmuiVuvLEs13e6uaK5CptBg0mrRKVQMBVJlTU2ZcBKACx6FQNzcdY02nGbdSgUAiqFwEw0w0vDQXZ2eVjsMstmNnPxMsvNzHf39DMbyyFKMpPr0FCQb9/Wxbdv72bPGS/jwRS+eJaFVUb++uk+pqNZiiWR2ViWBoeeDYureeLULD0zMT59bSsbFlezfzBAriDS6jZxS3ncK5FD1v/KFhBFWSqi3q7HrFMzFkhh1cuM5wNDAaqMWjo8Zja3uVAKAoIAkVSe2WiWZ3u9nA2mUCsVCECuJDLmT7FvwM/mNhc901GCyTw9M1HaPRZuWVGHojzWtLDKwOGxEAVRJJGV2dXa8lhTvijybK+XqxY7kUoSgUSWBQ55/f37KxN0eCzU2w187sFThFI5vrO7WxbPf22SSDqP06zjqhaZUa1QCGgUApGMvBZG/EnimQJ7e73sOePlO7d1s6bJwVQ4jU6l4As3dGDWqnjs1CwzkQy1Npkl5IvnOD4ZQadW8p09A3x8QxMus5Yne2blETaTlt0r61m5wM7Xn+zFUD5bZyIZ7ljdwD/ctRKNSsGh4QBbO9zsLrvs5Yolgokcn33gFIWSrBEkCPDSiJy/PvypDRRFUQY5tCpUCoEDgwHmohn5XkpSRTz7md45Ni52Um3S8vntHRRLIj0zMf5x3yj37GinxW2mu86KSiGwuc0lC8/7k7TWyGYDCkFgfZOD/3t4ggeOTvOT1ybZvrSGP9y0iH975Sw7umrKjnRavnZTJ7PRDBa9mq+V97JopoAvnuXp016+e3s3t6ys4z8OT9JVb6PKqOGV0SA90zE+dmUjkVSee58eqDw3B4YDvDIa5Ks3dvK1mzp55rQ8kVFn07NioZ3JUIpfvD6FJMGSWst5OXyNRcctK+rZ2JJjNprl4FCgAkjBu5Mf5JxeNkhY4DByz0OnGfIlKUkSxyYivD4e5rPXt7Gp1clkOC07pibObzzv7K5BIQjMRrO80O+TXc2dRm5Y6qHBbuAjVyxElCTU5ZHa9xIqpcDGlmqePi03F+bz8qZqA5tazx87/W1rcF4Gpf4fj3da1Jcq1KtTK7mx24MvnuXREzMM+5O0uExsKx/wlyoSvKXNiSBILHKasRvURNIFRgMJNrXKbh7zgMHRs2E2t7kq1Ml3clrLFkrywSrAAruBo2dldk22IPB6mYp655rznRLO1YWZjWbY2OKk3WNGpZDdN5SCLEY4L2j6v18eJ50vsau7lj++ZjGpXJEXB/yMBVOYdSr5wFEqmAqneaVs+xxM5rn7wR5OTcsJnsusJZ4t4CxquXFZLcWSyD/sGyGRLeEya2l2GtmwqJpDQwFmo1muWFRVGeXTqZVUmTQcm5Atau9+sIdhnyxMvafXy+GRIPfe1s3VLdWI5Q1clCQSWdk9xqpXU2PVEU7n0aqVvNDvYzaW4fc3NvO925chShJPn54jkS1WupeRdJ4FDgOvj4f5x/0jbGlzVUbodGol9XY9xbKQZpvHzPGpCKVycqJSCJU5+UhaBqkaHPLo23QkU9FRumN1A8+cmWMykkajVCCUNZrmBeR3ddciILzld/RWwMq7beDvtAbbPWaeODV33nOhVSm4aVkdoUSel0eDHJuI0OGxsLPbw/IGG95YllAqz188cKpC8T08FuLVsSBf2rnkbQGJ+fWnVAg8emK6LI6vrszWg3wYZwul8nt6+8/2Jg0xm55VjXb+bGsLX3+ij0iuULZW1p93wM+PwE2F0xXBzkPDAf7yxiXcsryWaLrAd54ZIFuQk4N5tuJbjSpmCyUODQe5eXkdjdVG/urJPsaDKZK5IkfGw7w2FuTLuzrfduzt3b7Hc8EYjVLBwiojr4y+ASxe2+Gi3qHnu3sGmIvlKjbfz5yZ4y93LSGalhP39+Ngv3B0cHObiyd6ZhkPvjHaAu+vte9vY6JyOS7Hr3PMP+eT4TSRVB5/IsdTp73cf1s3Ny6r5YlTs3xyYzOxdIGDw0EmwykWOoysa3bw0Ssb+cvHzsgiuwqByXCKl0eCfGjtAk5NRdjVXcvNy2vJFUUsejVf3rmEQ8MBTs/EqLHo2NTm4mwwxc+PTlIS4V9fGudPr11M/1yaxS4TKqXAT49M8vsbm4mk8rw0EmTAG2fD4moODgdIjRcr1vRNVUa2tLsw61To1UpyJbHSTHMYNGjVCn7x+hQ/+OBy6uw6/uGuVcSzBQRkIWSPVc9Dx6f5t8NnWVhl4LPXtfHqWAhfIsuiahOb211YdCq++FAPY6E0gUSOZE5mb9y3u5v1zVXsLxulhFN5frR/lGX1NiRJoqvexvc/sIx95Vyq2Wnk2nY3LouWvpkYVzRXUWOVmRaCABadms9ua+fFAR9XLXZyeDTIVS1OxoOpCgBXKEmyW59RHj3PF0X+x5bFuC06DgzJgEC7x8KmVie3r2zg2TM+UvlSxSFRqVBQ7zAQSRdkVlamQL4ooVUrZKaIAHPxDF986DQD3gT/63dX88yZOV4ZC1Nv16MQBOLZImPBJA8em2Jji4sVDTJrWCUIZIsif7a1ldfPRhj0Jthh0VY0vP7lpTFqrHpi2Tx/uGkRd61bSFGUpQLmHfWW1llpqjYynynkijIwZNAoWVJrAeAbT/Sxa5mHOruOx0/NMhWWm2Vb2p2MBVM4TRr6ZmVXOEsZxCqIEhIwEkiyrbOGKqMGkLixu46nT8/hj2fprLVyQ5eHze0uDo0EeX08XGH8uy1GViywkyuWiKTznJqOcMfqBkLJPA8cm2ZprZXPXt+GSinwbK+XVK7ER9c34rbqueehHkYCSewGDXqNkoeOTfPDDy3HbtCQyZd49oyXk1NRlIKA3ajBoFUxFkjy0kiAD69ZQN9cnDWNDnyJHPc81MNkOM2uZbW0us3o1UpWLbSxvtnBA0enWdvowGXW8vmHejhblplI5Yo82TPLvbu7uGNVA/sHAwiCrHmkUgiAwIg/wdrGKowaFVq1kkJJ3hOe75drlFqbfBbHMgVmohleGw+zYVEVPz86Q2OVgQ2L5Nx8IpQikZVZeRqVrNHqMGrwRrMYNEoODvu5dYWcMyysMlJn13NyKsr2pTXYDBpCiRx//tBJxvwpBAFeHPSz58wcf33HchY4jBUXTglY7DIRTORQCAKN1UZi6Twui8x2rDJpefDoFMFkHlGSHRq1SgUj/iT7BwNc0VxF72ycrR1uXhkN8fUn+gD42IZGXhkNMeJLyO57KgVmrRpvLFvJd+ZzvHl93UNDaVY3OljkNHFNeb8oirLh0v7BAKsb7RwaCvDQ8ZmKfvB8vJu8g5zTuwgk5AbCaFC+L1ql7MA+4E1UNJvGAkmKovgm6YdNrdVkCiJ3P9jDeHlCB2Bvr4+/+cBymqqMqFW/ZN5YNuP6wg0dMqsukKTVbWJnV+15jdm3k6a4Z0cHbrMWif9acsv7EZdBqf/H40KFf4CXRwKVIvndhHov7MYHEjn+7Ocn6Z+LI0myts7TZ+b42w+uoPESBZmdZi1XLXayt8/LqF+m4V6/pEbWsDkHMDswFKDDY+HeW7ve1mnt3EJtMpzGZlBzy4o6Viy08fUneskVZHeMQV+CQkk870E+Vxdm3uVvvvj3WGWR7nShxLGzYVY3Ovjijg6+/OgZHjw2zSeuakIhCIz4kxXtHfmQyaNXKzkbSiEBT52e5eRUFKNWyVdv7KSx7HDy0PFpOjwWNre62NZZQziVx6pXo1Ep8cez/MdrEwQTefYN+Pj6zUsryYdSIeCxyWLiE6E0giBT5wEGfEleGpZdAEVJot6ur4xEpvMluuut7Oz2MOJL4ovn2NXtocok05ETuSIeq45wKo+pPJKmUyl4/WyYrR1uDo+GKrTbeSG+L+7oQKVUoCrf0i1tLg6PhpgKp7Hq1aTzJRoccgfg4FBABhNbXJyZiZ2no5QviZyZiRPPyOwv9TnA1FQ4jVqpeMvvaL4ot+hUfPfZgXMc3d6dofJ2a1CpEJiOpM8THm+skscRv/pYL4FkjmFfgr29Po5NRPjMda0oBIE9vXOMlp3rBATyRZGptwAkLnyuGhxyMtRZZ+XMbPxNtsV1Nj3jwRS/ODr1jp/twud9Xsj9Czd0VPQQ5kdgG8oCjeeOwBVKUsVNZS6W4ZHjM2xYXEW1ScsH1y3gx/vHkJDIF0VqrTpWNzromY6dB/KURIkltRbqbHoeOjbN8ckoWpUCq14NwHQ0+44AzVsdxK+fDfHNm5cSzxbfBMbs7Krh1bEg48F0BTjc2+elb05+1tVKBUatiplohuf6fKxpdLxJ1+y9xFuNDtoNakb8yfNGjOfj/bL2/XVya7wcl+O3Id6JdXjucz4vSBvLFBgNJNk/5OeaNhdOsxajRsVXn+gjkMhSEiUOK8I8dmqWL+3o4MbuWn7++pRc8GlV+BNZxLJui1opu3cls0WG/HFaXBZuXVnPlnYX/XMJHjg6xVOnZ2Wmc0mi1qbDG8tx1/96jcf+eAM/3j+KzaAmV5QLqf65BHqNgm/erOaeGzp4eSTIgFe2Rb+23YXdqOHMTKyiAXn/7d24y8LEsYzsAHViKkqNVU80LYNcs9GMLIHQ6mSJR97bf/jCMJvbnGztcFNtkq9r0ir56WtTnJ6NY9ap0agUFNIiA94kLw74WdPo4GdHJllYZcCiU/HPH1lNY7UBo0bWY/RY9ezs9qAQZOaIVS+733XV26gyyUWYy6JFpZDdtExaZUXUezaWJZLO01gls+rfAKZkQK7WJrsRui067n6oh6lwmhqLjoPDQZ7qmeN7dyzjA2sa+N7eoQqrrc6mZ2uHrLPpjWUroEu6AHaDBgEBg1pJNJ3Hadbisep49MQMmXyJZNn10KxToVYq5HE2tYIXB/1YDTILzZ/I8oHVC/iDq5u5bokbRbmBEs8WuGVFHasXOrAbNDzZM8dkOMUChyxNYStLWnjjWe5c3cDePi+D3gSSJK/XpbUWrl/ipn8uzsIqI03VMmtkJJBEkmQB+UMjAf5ky2KUCgWN1UaePuNFr1ZSY9GRzMlA5rJ6K06zhplIBgSBzz/Yw9lQGodRw6npGEfGQ3zn9mV8fls7T5+ZK7sBymCDN5bl+GSET14li9vPRDLc98wAM5EMhZLItR1uPrV5EeFUniqThisWyYDlsF9mtuSKIhadirOhFK+Nhakt6+2cKTvOASRyRWptehocBqKpAggCTdVGCqLI4yflqYRv3rz0PCOgzloLd65uYDqSZmuHm32DfsYCSWqsepSCzNg/G0qzbyDA5jYXL4+EcJm1rG1y8OMDI9gMGtY2OvjOnoHKmatRKagyajkblM/4WKaI3aBGEOR1dGIywppGB4dHgzx8PEssU+CjVyzEZlCX3amhlJEqDbN2j0WeHAjLMhJatRKPVceXdnSQLZSwGTVolAoeGwkSTRVYWGVAVc69wqlCxQXcrFMRzRRYWKVnc6uLR07MVEZ+++cSuCw6+fkQJQZ9SWYiGRQKcJq01Nn1JLJFZqMZFlQZuXtbOwPeOF9/orfSnIylC5wNyo6U83Gh4Y9Rqyrrt8o6WKsbHVzT7iKSLrBvwI/TrGX70ppKThNN52W9rtNzZAsiGpV8vYuVd6ix6jDrVDx0bAazViWbGWiUFEQJQYBQStZTa/eYCSXzBCpTGXIYtSqe6JliNpbm9lX1Fa2sYCIn74NlB9L3Gheacc039yPpQsWMS6186/xSkiTGAimePePlqpZqjp6N/MY1JH/tQKmDBw/y3e9+l2PHjjE3N8cjjzzCLbfcUvm9JEl89atf5X/+z/9JNBplw4YN/OhHP6KlpaXyN+FwmD/5kz/hiSeeQKFQcNttt/HDH/4Qk8n0tq+bzWb57Gc/y89+9jNyuRzbtm3jH//xH3G73ZW/mZyc5FOf+hT79u3DZDLxu7/7u9x3332oVG/cxv379/OZz3yG3t5eGhoa+PKXv8zHPvax9/UevV8xv6jn2Q+JbIF8SSSSyrNvwM/tq+sxaFQ4zVpuWl4rz7QqFajL7hwX6ulsaq0mnS8yFU6fh1YP+5I81+fjw+sWnOcUdmGid+F/ZwoliqJEV52VTKHEnjNeTkxGKxv9uYDZickIG1uc3LVuIaq3cFq7sBgPJfO8OODnO7d18+Qfb2TIl2DfYIDmarl78FZJqE6tZCqcroxszYvtPXDMwL23djEXy3LvU33ce1s3T/zxVQz5Epi1KqKZPB0eC/1zcaYjsiC3AKTzJewGDZIk4TBqKIoSNyz10Fhl5AsP93A2mMakVTEwl6DBbqCp2sjRiQgToZRMo2938Q8fXsmAN8GR8TBHJ8I0OAz4QrIAo0WrYtSfRBBkYG2e/qtXK5mOpFEpZAHOe3Z0cGDQz9lQCpdZx/alNUgS1NsNdNXb0KoVFIoiInICp1QIVJk0lCTZ7jaRK/LA0SlaXCbuvbWLI+MhpspjfW8lxHch0Fln07N+URXpfIlqs4YvrujAadYSHSlwdWs1TrOWux88xee2tVNr0xFK5UnnS5URMXijQ3LhdyRHiJdHAnzmujZaXOZzQKl3Z6j4Ejnue0a+liRJnJiKcmgoyA8+tJwGh4E1jY6K8LhBo+TwaAhfXB6HMGiUFEWJqXCaoxNhdq+o55p22cXlqZ458mW7YHjjgH4nlotRq2Jzm4tXRoJMlQsggDqbjvXNVTzb6z3vvV/42c7VOzl6Nsy+QVmgMiTmOTQSYEubkwePyeOPtVYZGJz/d/NOgols4Tw3lfFgim2dbg4OBfjw2oUIyABsZ62FrUvcjAdS/PjAKE6z9o0ETanAoFYSTObomY7KmiNAPFugwW5A4O0Bmvk9K5DIcf0SN6sbHdgNMkAZTOW5f88As28xFjdPE5/vrp6eiRFJ5wEqTL86m565qKxRF8sUyJetxEVJQiEIl+xy+Fajg/Ojxi+PBN/09++Hte/7aTZxOS7H/+txMazDC59ztVKojITNRLLcscpMV72Nx07OMBeV9UxUCgVFUWQ2mufQcIAbujw8c8ZbAeebqoxIEjx5apZBX6IMfrjprLXRUxaxjmdkdupoMIlSEFApBZqrjWxqddEzE8VqkMGOP93agt2gIZktsrbJwZA/QSpX4iuPn+F3r2jkA2sWcMvyWgqiRCCR40f7RzgwGOD3rmpiZ3ctj5+aZSKUosaq4+pWJx9at4BUtkgsk+dPf3qCQV8CjVJBnV3PoaEAn9vexrUdLp7v82HWqVEoBMw6Fel8kXimwMnpKIFEDp1aiUmrIqKSbd9H/Em2drhZ5JJHYVK5ImPBFC8O+FnsMrG51UlBlCUSrHo1/niOU9NRtnW6qTJqSeWL1NsNBMqMlMlwhja3matbnWQLIha9iv2DfnbOO5yVhapVStm8Y56VcWYmxxe2t+M0a0lki7zY7+cXxyY5OBTgQ2sXkCvK77XFbWLHUg9Os45TU1HyJbHS+GusMrBhcTU9M1GW1lr5+s1L+Yd9I0TSBRa5TGjVCvQaJcWSSCpXIleUbe1NOjX/39WLeOj4NOPBFHq1ksOjQX73ykbimQJPn5njbDBNs9PI713VTL4o8sVHTuNP5PCXx/0ODgW4//Zuuuqs/N/DE2xudfLt3d0VQKerzsr1nTW4zFp+cmSSa9qd7B8MMOhLVJwPc0U5vz84HGD3inpuXl5H70yM8VAKUZKw6dUV4eve2ThalYLXxsOcDaVRlb9vSZI4PRsnls4z4I3TVWflmnYXgUSOB45N0TMVY11zFWadmnS+iDeWZUWDjY+sX0iVSdbMCiRyuC26CgA5FkhVmudalYKSJOflc7EMqVyRmWiGxmpDRVRfFCXSuSJWvZoGhwGVAtQqBfFMsSKQv6Ccb0+E0hRKIgeGZDZOvd2ApfyaNoMGtVJgMpzBadbgserwxeedsuu5qsWJWadieb1d1r3qqDlPAsGgUZEvirS4TXAaktkCZp0Km15m3y+sMhJJ5yusqKW1Vk5Px9jU6uKZMzKgKEpQFGVzoKtaqilJEuuaHRRFsbzvyKy9yXCarz3ey1d2LSGYzGE3aohnCuSKBbQqBRadimAyh1IhsKnNRb1Nz8ZWJ1a9mo9esZA/uLqZYV+CeFbWS0pkCwgItLnldZsruxk6jBosejXd9VasOjUmjYq/e2G4AkgBpHIlmqqNHJ+MVn4238jd1e2RjZXKYuEzkTQHh4Nvcly+olwbzOc08ySEeWe+QDLHwkswA5sfq2vzmDkxFa0w5RWiJO9jNh1zsSxHJ8KsaXTwh5sW8eMDo5URQVECXzzDV2/sZKHDKDOuAkkWOU3csLQG4ZdL4SrnyYX6uABXLqqiq94KyGfTVDkvn68F5pvFZ2ZjbGyp5hdHp37jGpK/dqBUKpVi2bJlfOITn2D37t1v+v3999/P3/7t3/Jv//ZvNDU18Zd/+Zds27aNvr4+dDp5Qd51113Mzc3x3HPPUSgU+PjHP84f/MEf8JOf/ORtX/fP//zPeeqpp3jggQewWq388R//Mbt37+bll18GoFQqsXPnTmpqanjllVeYm5vjox/9KGq1mnvvvReA8fFxdu7cyR/+4R/yn//5n7zwwgt88pOfxOPxsG3btl/B3frlYn7xn8t+AEhRom8uhiTVnwc8Lawysn2pGyMqfLEs33q6n9lotnJIvDQc4E+3tlQYF+fGiD8hMzOKIgVRJF+Uwa9BX6LckZNnsKcjGertsutGJl/kX14eL9vLu+j0WPnxBQJ0bzfic25cWKgJgN2orljnrmtycGIqyh2r62X9p0TuPCHt+SS0JEqV65xboI8FUuwf8rOl3cW+QT/P9/lY11zFqekoa5scGEpKti+t4cCgn7FACgGZQbbYZWJji6zJs6bRAcC15c7MRCiNhIROreDqVicWvZrPPXiq0qECeLbXy1dv7CSdl7UfFIKsp/W5B3tY1+zgI+sbWeQy8fRpL2qVgLIMKlr1ahqrjCgU4ItlmYlkyt0JNzq1DKacDaXIl0Ry8RICAi8NB/HFsyyokg/qD61dQN9MnAFfApNWRVGU+NmRSb59Wzc3r6hDIQjv6DQ2/70VSxIS8sGkUylY31SFUatEqRC4uqUafyIr2yL7kzzf7+PO1bL183gwVWGbzINf7+QYORXJ8OKAn9VlK9Vz460AkEJJBiT2nJ6jfy6BVqXAG89SKIlMhtOcmIywrdONN56TxxuCKba0uzg9E8Ubz1Jr1dFgN8jaEwIMe5NE0nlOTEa4a91C1jU5+NZT/RVdqHlA4p1YLgat/Pn+bGsrLw0H8cazNFUbubrFSTid58BQ4E1rf16QPZzKES2PRlYZZZbgkloL33qqn6IoEU0VaHGbub7TzSKnLMjpssjCuG9oayEn3sjgpihJNFUbCSbzTITSFeHR7Z1u7EYtPdPRymF+oe7VK6NBFjgMNLvkRoGEnAinckU0Kk3lfly4bkqihDeWOc+FcCyY4n9sXsTLo6EKW+Hc73b/oJ/bVr5BE/fFsyx0GBAQKp8lVxRJZou0uM0ksgW+c1s3RVHkP1+dqCQc13fW4LHqLtrJ8a00yeZHjV8dDxHPFCs/v9gu37vpRL2fZhOX43L8vx4Xwzq88DkXBKHMjNCwrN6KQaOkJMk5llIhm5IoNQKZfAmDRhadvm6JG5dZ1rNrrDJwVYuTx0/O8L29Q6RyRSTg0ROz/PWdy2ipMZPKlVAqFHzndhlsOBtMsdht4upycZzMFvnfv7sGp1lLrlAimMzhi2e5cVkt2zplseXqMujy0nCQrnoLd/2vI+X9V0G9Tc94KIU/keVvnhuSx250Kg4MBfj8tnYWVhl4+MQM42VJgp3dHrZ3enCatWiUCnavrKe52kS9w8Ch4QBGjYpXx0IsrbOy2GXiuT4fEhIlUWb5pnIyQ9usU/FPH1lNIlvkW0/1MR3NIIoSr42HeOb0LJ+/oYMj42EePzXLXDRDviS74H1w7QIa7AZmY5nzdGK0ZW2fe2/tYsdSD197oldmwu7u4uBwgMlQmu56G1e3VpPMFagyySPne854GQmkaHGZ2LXMQ2edhWMTYW5S1LK+uYprO9zEMgX29nn5nXULuWdHB8/2ehkLpGisMrCpzcVYIMUro0E8Vj1ui451zVW8OOBnV7eHV0aCRNIF5srsqsYqA2sbHTx5apYt7S5qbXqcJi3VJg1/cm0LuaLId58d4Mh4pMLGWtvkYHAuQbzMCqq16WXDm9kYA9441y9xc2Q8xL1PD3B12cXshi4PTpNWXpOixAK7gSqTllF/knOPBo1KITPOEzn0GiXhdJ7PXN/GSyNB/OW8Y8PiagwaJXajmmqjloePz2DVq7Hq5ZxmIpTGZdESSuUJJvP82c9OolEpUAiy2L5OrcRp1jARSnN8MsLOrhpq7XoePznLiD/JYpcJj1XHLctrOT4RIZYp0Ow0olbKkg8WvZpCUcRt0dLgMBBKyY3m21bW81yfj4G5BAqFQK4oi95f2+FiNpqlJMkyEs0uE8vqZZOBs8F0RThfq1LwQr/sQJnMFWmsNnB6JloGjEr4EzksOjWtbjNWvZqNrU6qjBr+89UJdi2rZXWjHbVSwRd3dBBNFypnrkmn4sbuWl4ZCTLkS5Ivihg1srTFNeXaIVsokS9/pp+9PsnmNhf33trFvgEZUFzskg2SzDoVDxyd4s7VCxiYS7B8ga2S/x4YDDARShPLFKiz6fHGsmQLJSQgnYdMvkS9XW4O/sk1iymWZN3fnx4J4Lbo2bC4CoNGyVWLq1EKAsFEnulImo2tTg4NB8tO4DLDvKnKyJWLqzlyNkRjlZG/unUpK4/PMOiVtdMWu0zU2vW8Nh5mMiwz1f+/TYvwWHUcGAoyF3tDz/Ncs6Jzo6EM8M/HuS7bW5e4qbfrL1m/aX6M7/A5OaMoiug1CtY1VfFCv489vV6eOT3HF27oYFOrs1I3RNJ5ru+swaBW8bmH3pDiEJDzu+/cvowFjvcOrbyTlm1TtexaOBVOUyyJsqRIKo9Zp0alFCo16SKnqSKF8pvWkPy1A6VuuOEGbrjhhrf8nSRJ/OAHP+DLX/4yN998MwD//u//jtvt5tFHH+WDH/wg/f397Nmzh9dff53Vq1cD8Hd/93fs2LGD733ve9TW1r7purFYjH/5l3/hJz/5Cddccw0A//qv/0pHRwevvvoq69evZ+/evfT19fH888/jdrtZvnw53/zmN/n85z/P1772NTQaDT/+8Y9pamrir//6rwHo6OjgpZde4m/+5m9+LUEppUIoUzDPZz8AXLekhkCZJTIbzaJVKVjT6GC2PMv8bK+X09MxTDoVkgTRdAFRknhpJFhhXMiTyvLYWGuNGQGZWfHKaJDxUBqHUc22zhqsBjV/9J/HSWTkhChfFHnw2DRfu6kTvVrFjw+MsbfPx723dlUE6M4trt7tQSuJUgVRBpk+qhZg7eJq1jc5KoyXeLZAKJnn23sG3jIJdRg15xV888kByCLd13XUMBvNcnpGRqmf7fWxuc2JUSM7zXztpk6e7fUxGpC1tja1OpmNZjg5FeX/27SIlQtseKw6njglj9vpVErMOhVrm+y8NhYiki6gUSrQqBSEU3nGg7Ktbne9jbsf7OEf71pJURSJpPMUyg5otyyv49WxEMO+JFq1PM/dVC2DOPOWygDP9/nYP+jHY9XxvTuXoVer2Ns3w1WLndz94EnGAqkymKTntbEQX9y5hK/dvJSHj08z5JPnna9b4kaUYM8ZLzcuq31XHSedWslUIn1B0g9N1Qa+dlMnTrMWm0FTBkNrePaMl1Ayy327uzkw6Gc2mmFpnZXNbW84XLxTUT4VTrO5zfmmn78VQ8Uby5IrivTOxVEpBBK5IoWiWKHtP9kzx9rGKo6eDRNN5zFqlUTTMrDzQtki12bQoBAkZmNZnBYtZ4Mp/vngGAeHAnxpZwcfWd/Is73eCiChFITKeOl8KASBqUiaFwf8LPGY+fTPT1bsr7e0y0KXJq2Kl0aC5x3m892oO9c0lOnXMBpI8szpOersBrZ2uOmqt3Lrijr+10vjlc7/pzYtIlMoUW3SnMcQ3Nzm5OWRAJFUvmwRLNLslNfwQ8enqbfr0SgFWZRfpSCTFxnyJc67p/PPrShJTIbThFJ5rm13sfeM3LVWlhPIept8P9L5Ik/1eM9bN06ztgLe3PPwaeZiGXZ112IzyJog810jSZIq7M8zMzGu7XBTEiWZMZArsmtZLT3TMcaCKRLZApF0AY9Nz5Z2uateKIn86U9PMBJIIpSHYp86PccPP7iCxot0c3wrTb4DQwFWLbRz363dvDwSfFsR9wvjYnWi3pNb6OW4HJfjTXGxrMO3es4F5L1wc7sLo1ZJtiDSYDcyEZrCZdEiSlAq71HLGmwoFQLrmx00O01sbnORK5b43y+flYs/lQIkmIqk2TfoZ2eXh6wAerWCJ3v8rGiwccNSD7FMnlPTUdwmLTcvr8WfyPPTI5OM+JM0VRvZ0uYinilQb9MTSef5p4NjtLjk7r5Zp0anUqBVaTBpVQiCgMusYyqcIVsssX1pDdctceMp7zcqpYK5WAanWcuXdnbgserLDoIp2mvM7OjycFVLNX/0n8eYKguNn5mJMxVJc8eqBp7t9ZLJl8gUSpi0KrrrLNyw1INCIVAoymyV6YgsjDwdyVBn19PvTbJvQP68T5+ew2bQEEjkGPGn0CgVRNJ59g0EGA+lUCigVJIL2N7ZOM/2edna4ebrNy3l2ESYbKHEjd212A0aVAqB07Mx/LEcJp2abzzex/GpKAAv9PnY2+flvlu7cZm15IsiBo2SA0N+oqmCrNckCIRSOVYvtLO1w81cLMsDR6d4bSzEN29ZSo1FR1GU+MNNzfzsyBShZI5v39bN8/0+Tk/HWOQysaXNhTee5T9fm0ClFNiwuBq3Rccnr25ieb2Nh07MMBZMU2PVkcoVyZdELDp5FFwpCCiQnffmBeX3nPFy9/Z2PretnZdGggz5EvTNxvBYdAgCJHNFTs/EWNVoJ5Mv0uR840zTquRxdpVSNi4a9CX4xP95nd0r67iuo4Zr211UmeR7H0jmcBi0WPUaOmstHJ2IVATSs4USKoVAICmPW3V4LCxvsLJtqQenSVMWXTfwH69OoFQIzMayfP+5IU5NRYmkCygEeGU0xPfvXMY3b1nKkC/B9UvcvDYWqhgnFUtgM2jYsKiasWCSJ07NcuWiKr69u5sXB2QGS3e9lW2dNRg0Sl4ZDZYZ4ApuWV5HSRR5+Pi0LG8hgq4Mvj5yfJqrFlfLbDidh97ZOCcmopWzttqkYeVCG/90YJREtsDntrfzoXULUCoUhJM5XhkN4Y1l2NbpqZy5KoXMJvz2bd2VZlpztZF1TbJT3Qv9vsr1Y5kCCxxG/v7FEVYssHF1i5Nrl7gJxHPMxTJE0nmCiTySJHFoOEBnnQUBOTe9fombVrcJq17NFYuqqLPpOFuW8ACod+hZ3+xAQmZuf+upPs4G0yRyMjv8+X55vdfYdMTTBVlQ3iJLj9yzo4OXR+Rn02PTs77JQd9MjK883kuHx8J3buvmrnULyJfECrs8Vyjx+e3tPNfnw25Qs8Ch5/49A3jjuXID8Z3Nija1ueTx0HNinkU078z3XsCWcyc2JsJpnCZ5BHPezU8hCOVRx8B5zexjZ8NsX+rhP16bYDKUrpgC6NRKwqkCh35JAOidtJyv73QTSOS49+l+lnhkEfgne+aYCqept+vJl0SanUY2tTo5eE6T+sKaOVsokcoV+XWMXztQ6p1ifHwcr9fL1q1bKz+zWq2sW7eOw4cP88EPfpDDhw9js9kqgBTA1q1bUSgUvPbaa9x6661vuu6xY8coFArnXbe9vZ0FCxZw+PBh1q9fz+HDh+nq6jpvnG/btm186lOfore3lxUrVnD48OHzrjH/N5/+9Kff9jPlcjlyuTdmVuPx+CXdk7eKi3Vd0qmVbG518vjJ2QqqCtDsNNJdppvPo8jzdvR3P9jD/bd3M+BNEErliaQL1Np0KAR5HM0fz7KpxXkeILXYJTuueOM5/uznJ5gMyYdrMlvkxESUe3a0V9BpUZJFlKciaQ4MyRarL40EyRdFjk1E2La0huMTkYsqrrKFEpIkg0fVJrkrqFPL88N/tKWFapOWV8fCPHJyFrtBzY3LakkXivji2fOuM5+E3rKi7ryC71xHvGankWAyh4REi0tGqYuixDOnfdy2qo5AQmaqrGt2sH2prA31XL+fx05M8zvrF6JSCPzNB5ZTFCXaa8wcPRvGpFNh0ChZ7DLzfJ9fTkbKY4kOo6aSlNVadXjjGV4dC3Hbqnoe+tSVBJM5Hjk+w8bWau7b3cVLw/LIV0N5k7cb1ZyYDGPSaaiz61nsWsC1HW4ODftJ5Uq80O9j9UKZijweTKFSypRsgMlwhgODfq7tcNPmNnHFoiqCiRxP9Myypc2FUaN6k0D2uUDLPMhXY9G9KenXquRkQZJgIpTmhQGZht/iMnHT8lomw2kODvpZscDO7SvrsRnViBLkCiKlMv12QZWBl8rjUfOsGYUg0FZjRquSO1gXCucrBTkZzpdESpKESatCqxLpqDEzMBenmJUBqXwZmGqwG8gWSoz4k9gMGhDgxKQ8v/3M6TmCSXk0LJ4t4jbr2Nji5KFjU0TSeY5ORHh5JMitK+qwGzVc3SI/W9liicmwTCHPlkVvb1xWy/pmh0zt16q5pt3NL45O8dMjk3isej56xUJuW1XPxpbqCtNwXoerxqqruOZY9GqubnGyscXJlx49zTNnvPz9h1ewo6uGU9NRtrS7OD4RIVKe1zfr1Oc9AzVWHV/auYR9A35OTEZoqDKwudXFZDjFaCDJn21twZfI8fJIkNFACodRzeZWFy0uc4UtVQFFRHCadfz0tQk6ay18945l7Bv0M+JP0lVv5YZODxadir987Exl1FKriiAIEru6a1lSa2EulmV9s4MVDTbq7AYi6TwOo4ZIqoDdqEYUqbA/6+wGJkJpfnpkgvt2d6NXKcnki3zm+jLjLJalzq7nqpZqdColVUYt/kSWb+3uIpTIsW8wwJM9swy9zRjyO8VbafItcBioseneleF5blysTtSlmlNcjstxOd463qrBMd/YmrggyX8n7c2SKDusXdVSzYsDdgJJuRgzaeXxurVNDowaFX+2tZUhn8zK/emRCaKZQoWRIJRx5/GgbORi1amRgJ1dHg6PhTg4HGSR08jmVicOswZfPMcXH+rh+FRUFhEG9pyZ4zu3LWMunqWrzkpnrVUegRIltColH12/kIdOzABQa9Nx1eJqfv76JN+6pYvGanlM5ZETKZaUzTtuW9mAUaPCbZGdeOcFxF8fD3NqKspnrmvjykXVPJv1Ec3kaao28D8PjXFFswwaHB4LEUhkqbcbWLnAzompCH/56Bme+JONFaZ2IlskUyhVnHtH/Emu7XCTyBYxalXEMgUWu4woFAIKhcBoIElJlBsTCkGqMHAngmnSuSJVRi03Lasjks6jUgp44xmMGhUCsKXDyWMnZwmm8vLoV1kUddiX5MBQgLvWLSBXLOE0a/mddQtRK2XWj0op4DBo+N6zgxydiJDIFWmuNvKNm5dSZ9fzs9enGA8maXOb2b60hkJJxG2R7+/65ip88RwPH5/mxGQUrVrJZDjNjUYNNy+vxWPRE0jm6JmKMhWWtZpMWhU2g5p4tkC9Q8+Rs2FmyyONNVZd2ZXQTDQlj83t6q5FoxJQCgo0KoFgPMcf/eQ4I4EkX795KZtbnezsUslOb7EsZp0MJDRWmblyUTUPH59Gr1aybyDAkfEIhaLIbavqWbnAxr++fJZ7dnSQL5VY31zFT49MIpabnRIyC67OqiOeyfOvH19DpMxm8sazXL/EjVGr5BNXNcmjfjMxxgJJrHp5fL7WJmuWPdvrZfvSGtwWHS6zlm/f1s2BQVn/yWZUs3Gxk3i2gMuipbHKyI8PjLK1w826Zgc3lvVQJSREEVY02Hn05DTRdIGbltdSZ9OzvMHGkfFwWVtSSaEkEcsWyBSKFRb7V3d18ny/j5NTUZqdMsA7G83w8PEp/s/H1xFNFXj69BzhVB63RceaJgdqpcAPnh/innPO6JIoMRvN0Oo2s3KhA61SQKdR8e+HJyiUJCx6+Xsd9iUrANzTp7385MgUSLIz5n23dfNcn48aq47xYIpam55iSWI6kuLQUABvPFuRN6mzG/jRXavY2++jdyYu60W1OctMS4EX+/2cmYm/4finF4hnirw6FuJmSx3BZJ5XRoMM++X1e+uKOm5ZLjs7ng2m+MmRSZ7qmUOtFFjT6KBYknPoc5lLgUSOl0YCLK2z0uo28ejJWfq9CcxadUV+40Kzogv3UAVyDnNh8/qGLtmtO5UrXrLL8LlawYWSzOZ/vs93npufWikDUwurDFy5qIoFDgMbW5yolALRdEHWui2+IeCuUgpMlHP495prZQuyrMt9u7sYmEtwaDhAre2N/E1u1GYIJHIVLeUDQwFiGXntrWuqqgBr8zGfe5/b3ByZ8b+n9/erjt8oUMrrlTVTzgWG5v97/nderxeXy3Xe71UqFQ6Ho/I3b3VdjUaDzWZ7x+u+1eue+77e7m/i8TiZTAa9/s1OVPfddx9f//rX3/YzX0q8F9cll0XHvbd2safXWxlT2dTqRJSk85wFzrWjDyVzNFUbKwBSMlvEoFURSORorDLitsiCe+duLGqlgqdPzzIeTCGKkCwnFd54lhcH/KxtcvCT1ybQq5UYtbKO1XgwxfVLakjl5DnrIV+CW1bUcsPSmnd84Ofvw3Qkg82g5vBIkGvaXbw6GmQ0mGJbZw0us67seFNCoRCQJOifjfHprW1sanPyfN/5D+xkOF22V32j4DPrZCeSeocsEvjEqVnaa+SNO1Mo8f07l1Vmty06FQqFnq8/0ceZmRi5opxkddZauLbDzXP9Xq5srgZEdnZ7ODYRYSSQrIh62sq6OeryZpgrd+zaa8zYDGpaXGamIhmKJZFkvshXH+vFG8/y8IlpvnFzJ9uXesgXReLZgkz9LOpocVt44OgUNqOGNY0OPDYdv7O+EZVCIJzK4zBqmQil0aqUOM1a1EqBeEYG2/rmEuzo8hDJFPj0L06SLYgI5f/d2O05RyBbHlmcZ+OZdComQin2D/rZvbKeKqMGrUpROQQ2tTppcZuZiWb4wkOnCSRzmLRKjp4N8+pokLtv6CCdL6JRCVgNavyJHM/1+vAnciysMrCp1cnNy+voqDHz8kgQhSCwcqEdp1lHlUnuir446GfIm6iIljuMGhLZArFsgb29PqbCKa5bUkN3vY271i/kzjUN5Aoi0Uyhst7r7Hr8iRwNdgOvnw2jUgj852sTLKwycN/ubl4/GyaYzGM3quVOWDDFkz1z8qhYQWTQm+TWFfXs7KpBpVQwEUyhVArYDWoS2SIOg5o/vbaFdo+FXEEGPuOZAp/c2MTaRjtfebyXRK5QKY7OLYrsBnn87f49A8zGs4STOXyJHE/2zHH/bd3cuqKeXxyd4sV+P3etW8BXb5RZaXU2/dse7Oce4LuW1RJM5jg5FcFp0vLj31mFJEEwkZNHFCcinA2l2Nv7Bruxby5eOVSLJZHtS2s4ejbMD54fZmNLNVcsqpKfS4sWi1bNA8emzwGk3hC7/8XRKQLJPA6DmjtWN1Bl1PDJf3udrnobt62s54lTs+SLsmB/oSSd1zVqcZnxxrN8Z88APTNRtnV62NLm5OpWmXGmUSmIpfNEyolw72ycRU4Tt66oY9VCG19/oq8yhnyxce59uxCAulgtzEvViXo3c4rLcTkux7vHuazDc5mX+ZKI06SlUHbclc/lt3/O1UoqANYXd3Swb9DPdCRDe42Zq1qcJLMFgqkcr/aEeeDYFN+4eSluix6tSkGcst4JsrB3c7URUZRQKhWoFaAA1jQ62NrhxmZQE0sXyORF9g8GGA4kz9M5GvQm2Tfo5xMbmgin8uw5433DIXlpDR+5spEGu4GOOgt2o4ZiSdasaao2cd8zA8xGM5REiSFfgp7pKPfs6ODjG5p4bVzWUZx3OzXrVEyGMzzf72N1o4M9vV6OjIfZWhbqNuvU2I0abllei0WnxhfP8tMjsli7UatCr1bgNusQBKGSFyQyBexGDW01ZoLJXNmJUGBR2YpdQG4YNVUbKZYk1Mo3dDT1almou7piNFPAoFESzRSosxn498NnmY5kaHGbORtMURQl6svGIul8Ca1KQSSVpyhK3PvUAJ/b3oaxrBcZSOQIpXJoVUq+uHMJz/f7GPUnuXVlLS0uM2dDadY1OWiuNnJoJMBrz4a5e3s7iWyBV8fC/PjAaAWkdJm16NSy9Xu2UOLm5XX84ugUS2strFxoZ6zsFCZJstPhq2MhdnZ5ODERqazZRDk3WddUhdWgob3Gwr8fPst4MMWqhXY2t7lIZgsMB5IUSxLffLKXK//0aupsen7wweW8OOBnYC5BrU3HLSvqiKYLHBkPVcDVaLpAPCuL+F/T7uLQcIAlJy1s65QNiL57xzKOno0w5EvgKgtU200aXjzmZ5NayfeeHSSSLvBHWxZh1qn5j1cniKQKLKw2snqhnc9ta+d/HhqjzqYva0VlOT0d56rF1XzsX1/HY9Xyj3et4qbltWQLsr7pqekIr46GuGN1A3/7oRW8MOBjOpxh2JfEYdAwFkySyhVpcBj43t5BXhkN4TBqeHkkyN3b29m+tIZjE2GmIhliadl9+G/uXEFTtYlHTswQSGS5clE1t6yoZWe3h/65OA8dm+boRJjf27gIo1bF3Q/1cHIyisOowahV8ciJae6/fRltnvR5Z/S8BMhLI0EiZdOiP722hc9vb+f4ZITZqCxfsqnVhUmr5O7t7RweC3FqKipLNbQ68UYzjPmT/P/svWeYVOeVrn3vyrkrV+ecgW5ykBBZAgkUULIcZNkzjuMwjrJly1nJksYeB43lPDOOyhGQhEAgEAIEIjR07gY6VurKOe3vx64uoTi2z5lzfL7Rui5dgqJq9+6qXftd71rPup8vbWrDE06yts2BJ5riiw+e4OxMHJdJjVIu49nTbr65pROAqxdUcdX8SvrdUR55dYIGu54Wl4GeyRCBeKZ0/SjlkpmASaPEF01xy2MnOTUpjevtOOXm6ZPT/OKDizh6Nsgv959hJpbGrJMME1wmDc+cdhNMZIvIFanZ+uKQv6R+uufaLk5OhAjGJRHE+WYv55sVvfEe6npDTtNg13Pp3HLCqTer6f9aqPfszzhyNvgmtIcgSJy+2c/pfP5xvU2PRfcawL0gSt8Pq06FvyhC+GvO5a3276vbHHx6XUtJiTXLd4XXjzEuqZfuMWqFjH53BKNGwW1XzX1d432Wtzvb3Mwm4//FGf3fif+nilL/f4xbbrmFL3zhC6W/RyIRampq/qZj/S2uSxqlHLtRxUUt9hLh/8VBHxe12mlxGjk5EQYk16jRYpHqwMgMl82rYEfPNIPeGKligjC30sjqVqmKvKLJxoXNdgqiiE4lfemHvPFSFytXEKUOIBL3ZnNXJfde143DqMYfS3NsLESZVkpYgkX3ifIyDWf9cRxGDWU6VUnZUhDF11XmZ9+HD66o57nTbsLJrGRDXLRSXlxn4aWRGZKZPAq5QL4gEk3lGA8KHD4b4P3L6lhab+XI2WCpal5rleCJsxu+F/olMHitVceKJgnw3uTU87HVjUSSWZ477cZuVLOu3YVOJUchF5DLZXz+4lZ29rolUKbTKDnTFB3eZALk8wI2o5pvXt7J3gEfixus9E6F2TinnOPjIV4emSmN3JWb1Cyqs5AXYUmDFbNWiT+WIZsvcOX8Ku7a0cd7l9YCAh/89SHCqSwWnYpEJk+9TcfnL25lWaMNmSDw5IkpJgMJumvMrG138rFVjfROR2iw64vuMAKTwSR5UVosnEY1A54o9TY9719Wx7OnPRKvJ5zColeVbqBnZxJMhyUZvtOoRiETCCakkap1HS6anYbXgQQX11tJZnLs6vcSz+QwaRTFWf4s0VSupDA6NRlmLJDgW0+eJhDPIlqObQABAABJREFUoFbIeXFIUrR8+4q5JLN5tnRXYlQreOL4FFNhD3VWPYvqLNRa9Ww7Oc2pqQhHzgb47lXzSGXy/NMfXiWUSPOnj16ASSuBWcOpHMF4BqdBjdOo5uxMnGFvDKdRjUwQuGSOi5eG/fhiaaKpPN95qpcPXVjP+5bWoVHKcIdT/PuBszx1cop0TtrEiCJUFaW2//T7o9x1TRc7TrnxxlJcu7CGp05OsbzRxoI6C9Mhial1biZBvV3H+nYXF7U6+P1HliGKoFfJJfOBN2yKHnl1Ak80DSJkctKuZNYNan27k0denSg6qQh/EQBxVn0JkjQ/nMiwvt1FKJnlsWOTDLijuEzS9T6vsozTUxG6a8zY9Co+sLwWEWkzks7m8URSZHJ5vnBJK/uG/HjCKc7447iMGhRFV6VzM68tmLMqzVse7cEbTeE0agglMhwcDXDLpe101ZjZdnKa5Q1WfvnBxeSK55krFNAqFQx5JJvfL17SxnOnPUxHUlh0anb1e9hxahqVQsYnVjXxniU1hIE7tvdxYjyMJyopJneckqzdt3RVUmvVvcn58C+Jt2Pdzar7ZjkXb1UU/Gs5Ue+0QX433o13453jfKX55q5yXjk7w4A7VlJeNjr0LG2w8vTJKVa3Ot+kVHyrY2VyBZ44PsVYMMG6Nidr2pxEi7DjeDpLjVnHo+FJgoksu/u8XLe4mv1DPl4enSGbF5EXGZRr252oFDKOjwWpseqIpnPctr2X71wxF51Kjlb12sZFIZPxxvq5P5YmL4p89s/H6JmUcjtEePrkFD9930JWtzt45NVJzs3EqbPp2bqgikdenWDAHSWVy6NXSW5VI74423um2TinnCqzltu3zuOeZ/tRK+TIZAIgMh5MsqbNSSiR5dlTbq5eUM0V86vY2ethZ6+HJoeete1OjFolZVoFTqOGeCZHriCyssXOgRE/kaQEW45n8syp1HJ5dyWj/hiXzaug1WXgwiY7lRYNpyYiVFkkGPyOHncR/g5alZy5VWWsarWTSOcl5cewnzP+uDTS2O7kgmY7iXSOmViaSrOWeDqHSavEoFaUzEoqzBrCySw3LK1BEATCqRwyAeKZHHajhnQmz9hMgmsWVIEgoFXKmAglJTv3Igvoiu4qpsNJ9g56WVRr4YImG3sHvUTPZNm6sIpL51ZQUabBppeYT5l8gTqrjgV1FqosOp7v8zDkiaEqwqrP+OJSA3hLJ3sGfJyYCEmNuRZJOZTK5fnhzkFOjoeIpnMMeWO8NOzncxta2dJVyePHJlHIZPzp8BgfWFGHUibjomY7q1udFArSdMGB4RmSRXC1L5oujdU12vVEUlkaHAbi6Rwuk5pUtkCdTU+dVVdq9MbTWfJ5kesX1/DkiSnGgknWtTuxGdR8+eETnCs69ZVplWw/OcUtl3Wwrs3Jc70egokMmVyBZqeembgEAY8kszx9cpotXZWs/8EerllYzdULq/j0uhZkgkAsneXahdUIgkCuUCAQz7B3wMeKJhvbT07TWWniHy5swKRVEohnOD4epMqs5dbNc3hx0MuZmTirWh3UWnV896le3GHJCe+xY1N0VZfxjS2dtJdLTdNam46rF1bxyNFJTk2GS2zKMq2kljk4OsN7Fkvqutk1+nw+p1EjKf1+snuIhXUWPriiDrtBA4joVXK8kTRHzwXZ0OHiiu5Kwsksp6fCeKNpPr2+mUwuT6VZh16j5LHjEt/NpJFcKieDScZmEuzs9TCvuozP/uk4d1/bxXOn3Rw9F+TDFzSQLLpenx+zzssdFUb2DPqYDqVeZ5R0xh/nhX4fq1rtKGQCLpOGS+a4cJk03PJoD6FkBotOKjQdGPFzy6UdmLWvqe5njV6AEht3Ns43K3pjnJ/TzGZfnshrXGMp/naXYYkx5UAQRFqcRirN2pISUlUcZ33j888XKMyaXtVYdaxosvH0yWl6pyN/1bl4win2DnppdhpZUm8hmMiwd8DLmjbn2/ILz4ehf3BFHZd3V1Jepn1Lx/q3a27+vcX/U0Wp8nJJqufxeKioqCg97vF4mD9/fuk5Xu/rVS65XI5AIFB6/VsdN5PJEAqFXqeW8ng8pdeUl5dz+PDh173O4/G87rzKy8tLj53/HJPJ9JYqKQC1Wo1arX6nX/svire64NQKGZ0VJnL5AtFU9m1hcEaNErtB/aYRE6tezaEzEghu9mailAu8PDLDknord13TxQv9XrzRNK0uA+s7XBi1Sm781SFOTIRRKaQbWbPTwB8+soyuqjKePjGFIEiuYzKZtOH6wPI6cvkCPZNhRnxxGuw6Lu50UW3R8dPdQ8hlQkkyu3fQi8Oo4YruSiaD0gJvN6jprjFj1atQymVMhSRp42wh7cruSk5OhGh2GWl1Gag0a5kKJfHH0mTzBSrNWnQqiX804I6yssXOoTMB1rY5aa8w8eTxSS46b/RFr5Yzr7qMZY1WBEECiJs0Sq7orsIbTXHXjgHes6SK7hoLgViGh454WN3q5PCZGSKpLMsbJVVIKJHhyROTlJs0XDG/EoVMhlIr48xMDIVQ7BiIIk8dn+TGFfV8ZZNkqzvsiZU4BFPhFC8MeFnT5kCnUvD48UleHPTxzcvncHHRnWzvoMRZMKgl/pdCJnB6KoI7kqLRbuDjvzvCiC+OXBA4dCbAvmE/39zSyeI6C5VmLacnw5ycCJdkuY12SQL88NEJnEY1yxps/PHQGCaNks1dFSjlMuLpHALw8VWNXLWgknAiSyKbRy2XYdap0ChlJNI5fvj8IJ9a28xFrXaeO+3BrFOikMvwhFMoZAKTIcmtEFGS6PZNh7lmURVt5UaePDGFL5pGBBRFV55zMwme63WzpN7Kbdv6+NyGVgLxDPuH/OxIubHoVdyxdR5r25w8c9rNqckI8XSOFwd9uCNJnvnnVSQyBX538ByD7hhNTj3r2114oimUCoH2ciONdj0jvhh1Nj0qhYzvXTWXfUM+hn1xKss0rGiycWI8RJNDUhMeGw+SyUnFUxFochjY0O4klxf57PoWVAoZ1y+p4ed7RxibSXDH1nlUlGkIxDPc/PCJEg8glxc5ei7IbVfNJRDL8OixCbqrLazvcJY6MrPFwNkZfEEAtVKGkJRg4rMORyq5jLZy43/ZxXmr7s1FLXYselVJzZbNF/DF0iQzefYN+bn/xkVUFmGx205OMaeyjDXtToxqJdPhFP/852Mks3k2zilnSb1V6qgZpC6xSiF1E89feKU5/xRfuqQVp0lT6jLv7vewq1+yXN92chpBJpDI5EtQzUqzBO0UikUki06JJ5LkkjkultZLttmhRIbDZwN4IilyBZG9g36mQilMWgXhpJxULl8q5m2eV1FyQfxfidn3dN+Qn85KEzqlnAMjMyXo5xu7fX8rJ+rdQtS78W785fF2nervXjmXR1+d5MREqKQk90XTPH5sCgHhLfkh5x9rPJjArlexrNGG3ajm8w8ex2XSEEpkuW5xNV1VZjyRNGVa6X60u9/Dhc02vl5sog16YtRaJXc4p1FNPC01Z87OJLh5Uzv/9r5FqJWyIp5Ajloho8aik8aYRRFfLF0qTrU6jczE0gy6o3BewWrQG+O5XjdXdFfx411DmHVKNs6RcqKeyTCRImg4k80QKiIbRv1xUtkC3326l1su7eDK+VX84eA5UjmpmNJebiSSzKKQCWzodBGIp7lrRz/RdI5cvsCuPg9Pn5zm9q1zuWJ+FW3lJn68a4gRbwyrXsUtl3Vw+MwMJ8bD1Fil+2IkmcOmV/GVTW0o5TLSuTwz0Qx/fuUca1pdrGi28dP3LWBXv5fxQIL2ciPrOlxFl7MM9zwrubNmcwVeGpnh5ZEZvnhJGxVFlMAFTTZeKrrbeiIpIqkcnRUmrpxfRTAurRWPHZtibpWJC5psWHQq/nx4jPcuq6NRKbE+q61afNEMX3n4ZKmpC7C9x82913UhAC6Thmgqx3evmEMkJY0e7R/y80K/l2qL5NxXa9WyqM7CRCDJeDDBVy9tZ++AjyFvjFaXkcu7K5HLBOx6Fata7CxtsBJMZNjV72VhrZmjYyF6pyISELwgIhOkJsZLw34u6XRxcGQGhVzgsWOTtLtMLKw3F0dFBfKC1DC+oNnGvx84W8r9ABrtBla1Otg74CsB80EqAj1xbJLxoOSovKLJTjSV5cR4kOsW1zIRTOCNpFjeYOWFfi+DnlhJ4QYQiGd5adjPwjoLO067yeYLNDklddBDR8YpFN2evdEUSrnA2janpExSKSiIoFJISr1AIsOzpz2cmgzT7JT2JdUWLXJBQKmQsXfQx6gvXtpTRFNZjGYFLS4ja9qcmHVKHj02yWRIMibQFpvqJyfCbDs5zca55VzQaENfLACdnAghiiCTSXuuXEEaz3QXIfa/eHGUtnIja9uk7++qFjvbeqbwRtLo1QrJaCqUQhQFXhr2E05mWd3qwGpQs6jewlMnJoscLql5nc7lOTUZ5pf7z6CSyfjuVXOw6qU9pE4928QtoJALjBYnQ9a2SwYIX9rYRi4volHJ2d3rZW2bk+d63UUDJimPqCzTSvndedMg2bxYYlKNeGNcvbCKGouWyVCKpfU29gx4mQgmqCiqsUVRYsG9OOTlwiZ76Tswa/QyW3Scjb8ULzBrBpTLF3imyDU2apQo5QKCIPwvQb0dRXHACwNenj3txmWS3EYlB8IcdoO6pFiC1wQKewe99E1FcZVVlNaGWTHDX3ouqWyeRDbPvCoJvD9a3AevaXMST+eK3FrFO+IZ1ndIzpbff6a/hEs5NRUpOdY7jeq3bW7+PcX/U0WphoYGysvL2bVrV6kIFYlEOHToEJ/85CcBWLFiBaFQiKNHj7Jo0SIAdu/eTaFQYNmyZW953EWLFqFUKtm1axfXXHMNAAMDA4yNjbFixYrScW+//Xa8Xm9pPHDnzp2YTCY6OztLz9m+ffvrjr1z587SMf47443d9PNHXt4oqXyjpPDtOutGTaEkmQzGM1w6t4KeyTDucIr7945wQbONFU022sqNkmpDreAPB89xairCbDlbJgj0T0c5NRlm60LJ8ctYVL8cORfAolWhVsi5bVsvPZNhMrkCR87KOT0V4VtbOrl0Xjk3LKnBZlCTyOQpFKBMo8AbTXPzwyf44AX11Nr0PFZcRLqqzKxssfGJ1U2SW0dRtp0viDx8dIL7XhjmVx9cjKloxSoXBGIpqTN2xh9nS1cF7nCKPx8eZ9+Qnzu2zuWbl3dK3YdAAotBxbaTbh4sLpKzoVXK+fkHF7F3wEejXU+by8R0KMUXHjzOiC/ORS0OXh0LlixP8wWR8UASuQx+9cElxNI5njg+Rbg4p3xxp6vEFiov0xJJZjk2FqK72sz6Dhf+aJpnTrl5adjPvOoy2lxGjp4LsndAminfM+BlXbsLq17FGX8cUZQYWAiUHEkcxULkSNE9QiaTOovjgQTPnHazusWBIAgSS2jAW5qnX9PqxBtNcWI8xMI6CzVWHWq5wK1bOqgo0/DIqxOSi2LRalanlCPXC1Qq5ezq83JqKkx3tZnljVaunF/J8fEQW7oqmQomUcqlC6fFZWR3v/d18G6tSsYHltfhi2ZQyQVOTUZIZPKYdRJXKldUzQ16YlzcUU7vVIRdfR4W1lp4ttdDKlsoFRiWFscKFHIZckFgIpjg1s1zSGUL3PzwCV45+5okfkePm3uv62YsICm+ZIKUqGiVEn+gTKvk0nkVFAoigiDgi6Z58JVxvnPlHOxGNX/8yHLyBbEof8+gUyko0ymZCCY5ci7I48en6KwwccX8KsYDUgf6M+taeOzYJOcCiVJnyKpX4Q6neOrENIvrLfRORRjyxDh0ZqbUkZm1162yaMkXChREMGuVxNMSm6PFaSSUyLK0wcraduffxDJ6acTHnVu7ODA8RTYvSei1RUlzR4WJQCzDHdv7eHl0BodBTc9khGdOu7nvfQt4YcBLJJVDIRN49rSbZ065EYEbl9eydUE1nnCKcrOmtPD6ommanQbc4RTPnHZzbkayw17X7qSruoxoKse8ajNPf2YlqWyBWx49yVgggbE4FvLIq1ru3NrF6lYHqVye9y6te22stAgaXdPmRKeSUxBfu4dK90QtkaTkuOOLZmivMKL9Xyj0zH42nmiaO4ugSgH43APHiwmdFpVC9qZu37ucqHfj3fjfG2/F3Xw7pfktl3Vw6dxyLmiylZTks5uOt3O0PJ+lKIrgjaZ4/MQkd27t4gPL63jy+BRGjYKJYJKNneU8emySLV0V7B30kcrm+fHuIS7uKGfjXBfXFh1Lk5k8B4b9eGNpLu+uZCqU4uURP5fOrcAfTZEpiOQKIlPBJEsarGw/NU2+IGLSKvDHMrQ6Daxpc3D4TAAR6R43u9EUBGmzqVPJuefaLl45F2RVi4OZWJpqixYRSiYS+YLEemovN+KLpvBF07w46GNZg5Wf7h5GIRew6JWsaXOgksv4h5UNLKi1cHBkhkgqR65QKKkL/MUxwmUNNhxGNes7nBwdC3Jxp4tQIsPWBdVs6ZLGxSVTkSyrWqWGTv90CKNWiUmjpM5m4FtPnWLrgkquX1zH9YtrEJDGkfIFkZlYmh2n3JyejGDQKFDIZeQLBcZDSQ6dmeHK+VU4TNKo19cu6+Dl0Rn6pqURtGsWVRFL5Xj2tJvuajOXdEpK3V19Xi6bV05ehH/8j1fYNLec5Q1WqkQdewa8TIdTUh5cvDxGfTH2DPi4Yn6lpP4HXCYtBSR17ogvTrgIll5QY+be67sRRXi6Z4qHXhnn2sU1LKgxs6bdiS+SZtgbJZRQYdOrUSllPHliihcGpJzp0rkVnPVPSiwupYqKMo20VgvSpn5tm4Mr5leyoMaMzSCpKCSDkjxmrYSKkMsgnMhy97VdHBydwRtJlxhOE0FpPLNMq2Bdm5NkJsc///l40V1bZDyQoM6m455ru4ml86SyeZxGDelcAZtRzYgvVsprZq9DpUIgmMjQ5NBzQZONijKJjzMVSvJCv7dYgJJTb5PA1v+0pglvNM3RsSDr2p2IoliCpb96LkgklUMQJJfqf3v/ImqsOm767eHSd3L23378ngWYiiOl8YxU2D03Ey/tkWSCxDhK56QC7YXNdm7f1sv3r+1GZ1SwqM5CvzuKICCxSQsiclHErFMy7I1y+EyAV8eCHBj289VLO0hk89y8sZ29gz6mwkk6K0ysb3fhMKql4plMKg/5IimiqSwfWF5PKJHhz4fHODUVod6uY22bk4+sbOD2bX280O9jZbMNEcmJMp0rlL7XTQ4DhqI75s5eD4G4hJTYOKeC9gojU6EEP//AYpLZHHJBUmybip9/tUWHUiFQbdFKxgzF+0truQGZIPDtK+eSSOew6lUY1RJHdmefh5lYpjRdMR1K4TJp+O6Vc9Aq5YSLReq7r+3i1XPB13Fu/xK8wOx99Z/Xt9DvjhIsjltKuZP0S/+tLsPeYkFn1BdnOpwkky/wRPGevaffy0WtDkKJLNUWbWkPXWPVsXVBNRe1pJkKpV63Nvw15zILqb/l0R5GfDFpogLY1uPmRzfMJ5MrEE29xgp7KzzD+byp89X8b8dE/nuNv7uiVCwWY3h4uPT3M2fOcPz4caxWK7W1tXzuc5/jtttuo6WlhYaGBr7xjW9QWVnJVVddBUiOd5s2beKjH/0o999/P9lslk9/+tPccMMNb+m8BxIs/R//8R/5whe+gNVqxWQy8ZnPfIYVK1awfPlyAC655BI6Ozu58cYbufvuu3G73dx666186lOfKimdPvGJT/DTn/6Um2++mX/4h39g9+7dPPjgg2zbtu2/903jzd3080de3iipPH/D83ZQ9NnHy02aEghOIZPxrcvnlNwKbHoVlWYtoggPHRnnPUtr6XdHkcsEFAhQnH83aRXoVAoS6RyDnihDnhjVFi2XzqmgwqzhgVfGeXUshFGjwKCWuh6TxS/S5q4KHn11kn5PlIoyDevandRadTx5Ypr2ChN1Nj03P3yCEV8chUzg4MgML4/4ufnSdjK5AmvbpUpzlVnLqDcGwO5+iWe0o8fNuSJQU0SSJK9qdbBnwIdeLSeRybF/2M9FLXZS2QInJ6TiyURQKhSsbLZzQZMdh1GNQiY5d/S7I1zcWU4ym2dnn4epUJIbltRgN6j5yqZ2ti6IcXIyxFPHpyiIIu9ZVEOdXcdkMMnaNifhZJZjY0F+sHOQL13Shs2gYnmjjWAiw3QkybefOg1IktLKMom70OIyMBVK8rXHejDrVNgMKiKpHAtqzWTyBTrKTbzQ78WgUVAodsw0Shk2g4qzxTEpuSB1SFQKGbm8lNjq1Aq+9NBxtsyr5IruSjZ0uCQAfTHx+dLGNpqdBkwaJTs+t6ro5NHHWDBRApQ+fXKK+96/kGgqx2f/dKy0YB49F+TPr4xx19VdpLIF7AYVn1rXgkkjLW7r2iVGly8mjaAJAvzjykZ0KgW3PtbDp9Y1U2HW4I2mSWbzlJs06FQKAvEMjXY9wUSaRCbPqC/Ohg4X+UIBpUKALAx7YqxvdxGMS92Hgigpc1Y02njutIcB9+td44a9Eotj45xyzFoVBVHEYVSTzYucnAix7eQUjQ4jF89xYdEqcZnU3HnNPKKpHDtfneRcII7TqGFVq12yni3ySb768En63FGsehWvnA2gPCRZfJ+eipDO5RkLJKXkCUpF32gqx5AnysWdLhRyGUIxYdo74GVLdyXeaBqzVuJYPXZskskiV63KosWsVbJpbjnhRIZvFjlS7xRvVF+qFTJWtdpZXGdFECQ3qFxBRCGXlIKxdI61bc7SdS+XCejUCvKiyKgvRiJbYCqYLDHi1EWnm0yuwKnJCJd3i9z9bD/fvmIONoMEekxlpULjXc/0c/hMoMTU2NEzzX3vX4RBreCpE1MsrJM2PTPxDFqV5BxUXqYhEMtyYMTPlq4KnCY1vmiGLz98giFPrPR77u738qMbFpQSMZhBJgioFXJsBmkEprPCKKkQ/oYC0PmqicX1FvYVO7UfXFFX4vQBRNNZLHLVW3b7yss03HJZB3sHvIwHk9S9y4l6N96NvzrejrtpM6jegdsmdfu//PDJNx3vrZSK57MUC6J0f1TIZAx5Yrw8MsP7ltZy6dwKQkUsgV4lLzme/fiGBewZ9KJWyFnWYMVWZDs9dWKKqXCSZQ02ltj1JLN5uqrLODZWwBtNYVAryKWy3LmtD280xafXtXDLpR28OOQjlMjQaJfccXVqBSuabPzs/Qt5vs/DEyemUMgEtnRV8uEL6xGRit3NLgNqhZzn+zysaXWys9cjbbwRS5uxDR0uaXN6xRypmGDXc9tVc1hSb8VuVKNSyBEQuXJ+JXKZjKdPTCEicVcSGalAnyuIDHslhuP+YR9r2pycngpTY9GV8srJUIo1bQ4W1klKoJ29bmwGNcsbrdy+rY/bt87j0rnlPHNqmv94eYz/ODCGw6jmk6ubWNvu5HtPn+ZLG9vpmQwTiGcoiGDRK4vubRKrNJbO0eQwMjYT5+mTU1y/uIbLuyo544+RyuRJ5wqsbHGwZ8BbaoysbpWcWi9qsfF8n4cHDo/zu5fPseOfL2IylCxBq2eV3ggSN8eiU/Hr/aP0T0e557ou9g36OT0Zkc4NqQjij0tqn2sWVjPqi6NSyvnzK+P8ZPcwiiLU/ZJOF59a28y2HjcXd0ojoXMqy/jpC0OEkxmanQZePRdEJsBMPEs0lcVp0tDiMlBl0bGlWKjwRtM0OQyUl2lQKeT0TITorCyTgOpaJWqlnK0LqkojXMfHQ7xyNsDVCyXYuUmr5NFXJ5gOp7AbVCTSOUQRRnxxiStWZyFXELmoxc4TJybxF38eSCpuY1FxlMsXqLHoMGqUfGZdCwLw+PFJHj82ibn4PbDopNxGLhN49NUJ/nh4nH9a24RGIZNGX/ul9VSjlBNJ5VArZCyoMSOKIhqlnK9e2s6uPi9PnZBwCt5IigISG8wbSWHRqZDLBWqteg6NSsXbeDqHiLTHanYaiKSyBBIZXhz08Z4l1axpc/LsaYnPppLLMGgUVFul62NXv5dMvoAnkkFA4NleN61OA7v6JYzCtYuqkQkCKoVQulfkik7oZXoVcoWMqXCSe57p59WxkNSYF0W2n3Rzz3VdXDG/kiFvlCvnV9Lo0JPMFNAoZaSyAvU2aeJEFOGrD/cQSGTQquScm5E4V3df0021VU8snePAsJ+JUJIai471HU7sBhWr2xzsHfTSOxUhky+gksvoqDSxutXBdCiJKMDBkRkmQynKy9RcMb+KD6yoo2cizAsD0uuuXFCFP5bmxHiYIW+U6uKIba1VR5VZSyKTJ5zMSigJJHbU26n3U1lJid9ZYcKsUzG/xszJiTDJTE7anxYb2tUWben5f2nDbjbXHQskSvxbAYERb5xd/R7mV5vZ2ethSb2VO7b3vWksT/E25/yXOh7nCqKUF/pjpYkKkJAb+4f8XDm/6nU54VuJSM7nTb0xZpVTb9Xc/HuLv7ui1JEjR1i7dm3p77O8pZtuuol///d/5+abbyYej/Oxj32MUCjEypUreeaZZ9BoXkvO//CHP/DpT3+a9evXI5PJuOaaa/jxj3/8up8jCAK//e1v+dCHPgTAD3/4w9Jz0+k0Gzdu5N/+7d9Kz5fL5Tz99NN88pOfZMWKFej1em666Sa++93vlp7T0NDAtm3b+PznP8+PfvQjqqur+dWvfsXGjRv/O96q18Ubu+mzYHJ/LMV7l9axvNFWchybtfL1RdNvSs6cxcdfGPDhDie5ckEVKrmMfUM+3OEUK1scbC6CrCPJLDKZwFce6eHcTJyrFlTR5DCU4J+IUCiIbJ5XIYHXtvWVNmCvjkmy1zuv7mLQEyUQz5SAe4IA9TY9Z2bi+GIZHjoqWbb2TIQ5MR7iu1fOxaCSs77DxQsD3pLSZ9ZpbyyY4PleD1cvrCaVzWPVqdCq5HTXmOmdjnBiPMRFzXbuva6LFwd9eCNpWlwGFtRamImlUckFvnflXCx6Fdl8AZ1SwfO9UyyotRCMZ2iw69nSVYFBpSCHWLIVLojwvSvnkswWyBUKhOJpbts6j3qbnsePT+CPZijTKVnf7qLFaeS7T5/iY6uaiCRzvDjkY9gTo9llYH27i44KEwdG/MypLGMqnGRuVRmXza3gxUE/3kgKg0YBgkCZVsH8Ggt/fmWcUEIa0TTrlFSZNUyFUszE02yc6+LVcwFGZySml0YpZ15VGTqlgsoyLU6jGqtehVgE9aWyeSrMWrRKOR9Z2chdO/oREZlXVcbdO/r50IX11Fr1vDjkY++Aj4oyDdctrmH/sJ+xYILpcIpUNk+uIPJK0dHt5ZEA3qgEfder5EyHkhSAPYNeblgiWemWaaSCpFwm4DCq+P4189jeIwH4W5wG3re0lsePTzHsi3F4NMD6dic7etxMFotgBo0Ci07FmjYnu/o8qBQyGux6QokMsZSkqIqn8zTY9XgjKYIJSXpu0krOi0q5jHOB1xIaQQCLTlWa/a8qusHs7PUwGZKKPataHWzoLOdfnx9k/7CP71/TVXIFunOHdL1PFq2tZ7suL4/MsLzRxtzqMkb8cSw6JbmCWEz4gly7qJpoKkeby1CCwAuCVBSSCVJnzqxTsr7dyf5hP6FEjlF/nFg6RzKT5+5nBrhqQSW3bu5k76CX8ZkE82strG1zYDOoyZu1HBjxsz+e5aIW+1vCGFNFx6Px4Guw8U+tbaaiTMNLw37MOiUOg8QIS2cLaFVy6qw6OiqMuExqqeiXSLN/2M+2k9OYtErCiQyVRUD87DIt2UJraa8wks0XuKK7Cn80w8EzM0wWrcCXN9i4cXkdA+4IkaLltS+WYd+Qj67qMh54ZZylDVZ6psIlJ71cXiSbL2DWSewIu1GNXCbdx9LZAhadUkq0FDJS2QL7h/28Z3HNmxZtmSBIRgZtb60q+0ucTs9XYCypt3B6OsJ0OEmZVlXi9MHrGQvnd9iy+QKecIrJ4n19fYcSrUpecrl84489/5zkgkCmqGb7axK0/x0sqv9dx3k33o3/XfF2aqg7r573tgn9eCCJpUv1Jvent1Mq5gsiZ2cki3WtUs5MTGJHqRRaaUw4L/LnV8ZpsOlY3+7EVabln9Y2I4oSX+7K7krCyRx7B6UiWZVZGiPRqxX86fAYA+4ozU4DW7oquaDJTiKbR6uU83yfl7Fggslgktu39bJ1YTVL6q3U23SYtEo8EUktNBaIY9IouXZRDcsbbSBCnV3P/iE/w74YFp2KDR0uGh0qUpkc7kiKn9+4iGQmj1wmo1AoYNKqUMoFbtvWS61Vz+auCix6NRe1OHhhwMdkSFJAXNxZjiBIpg61Nh0HRqTN96zrX64gUm/XEYinJaMcu55aq07CLTglds/LozMcHw+yssXOojorF3dKZkJVZi03rqhjR880W7oruftaycX1jD/OghozV86v4qkTUwx5YgQTGVpdBk5PRVDKBYLxLLmClKe2uoyYtEry+QJ2g4WOChO/P3iW9y6tw6pXY9IqmA6nuOUhiYE0q7J5rtfNvdd2U2czMBlMksoVmFtpRK2QU2NUYk1FqCjEEeMR5MkUBjHLZeMeCg+dRra7n+50Crl7L9X9U3zorI9COoWykEdZyGNRgnOHHGO5jk+7Q3hmYpDJ4NLKcWhkqMU88udyCPdkMYXiODQy8ukMcws5VmeyFL6VYUkux8dTGWT5LIIoUhCkJpZKpUBEoKYgchMCIgIFQUCQCeg1KspVKgSdlqxag15UEEKBQqdFYysDjYYFGg0XmY3EZEqGwzkUdXYaPEneF86RU2nw5mWERQVZpQrZQS81ijY8bhU6Sxl3bWrGky2waU45h0alJpIoisTSOXQqOataHcTSWQxqJdl8gavmV9JebmRnrweTVik5Jcula+jLG9v5+OomNEo5SrmMMi1MBBMkM3nJQTCX55tb5lBv1/PMKTcz8TRGjZJrF1WzvNHGPc/2c+X8KgqiyFgggV6tYGefB4dRzbJGKy8W9zypXB5RFGl1GdjQ4WJXnzTpYNEp8YTTjPhi3LypnRcHfYz647Q4DWzuqiCayvHEsUl8sQzpXB4QGfbEWN5g46kTUyyoseCNpnlx0EskmSs6vEnf51Q2R7lJSyCeZu+Q5GiskMvI5LKoFDLOzsR5od/LskYbI94YCPAv183n5ZEZJkMJzDoVFzbZMagVPPrqBJPhJBVlGmLpHE6jmlAiy1Q4SaVZy5ceOsGgJ4ZGKaE1Do3OcOvmTsltfVM7z5yScvAGuzTuaDWomQol+cIDJ0oKu4Io8uwpN9+8fA65gsjWBdV8YJnEO71jex+ToVSpoHliPMQtl3YwHU4iIpn7gLQXWNPqpPptGEz5gkhnpaQuPzUZkqYdTk0TTko/P1Nk/y5tsLK730sokWFNm/NN+e1b5SXnTxpl8lIeJiLl5LPIixGf5Ig4EUzy0rCfqxZUlfbQZ2fipf1AR4WJ+/eO4DCq/yoluyeaRiWXkcjnS4+pFRKXNpt/syr3jceVywTWFHmFs3v9I2cD7B30lYpj56usBie8PPsXndn/2fi7K0qtWbMG8R3cjQRB4Lvf/e7rikFvDKvVyh//+Me3/fczZ86gUCi48MILS49pNBruu+8+7rvvvrd9XV1d3ZvG897q/I8dO/aOz/nviDfaSFaaNQQTGW67ah4uk+Z14yqbuypIZfPc82x/yeFqNjn7yqZ29g/7ePDIBJd0ukhm8nzpiROks9IG7sUhP9UWLbdc1oFKLuOBV8Z4adgPwPHxEJfMcfHEiUmGPDHkxY7O5d2VvDwyQ787iieSQq2QUVGmZTwocZ3ayo0oimBEQZC+XLMQPV/RxSCdy6NWSCM2+wYlcGEqV+CpE4kSKFiSa0s3n9NTEda2pykUQKuQYdJo2DinnBf6vQx4oty5o5+rFlSyps1Jg11PKpvn4aMTtJUbuaDZzr4hHzaDmmUNVvQaBdcsqkYsSDfVK7or8UZSKOQyxHyBh49MSC42LgOb5pRLrJp4hk1zKzCoFXzxoROc9cepMEuOOodGZ/jGlk7+48PLyOYLfO3Rk/RMRRCAXf1edvZ6uOvqLmLpHFqVnHuf6edzF7eyps3Jbz+0hGAiw+niBnx98Wa549R0yfmjxqJlfYeLUV+M+/eM8PmLW7j96nmEElnpnEURo0aBRilj41wXR88FODuTYDIkSepbXAaWN1j54+FzrG51sLTByrA3xuXdldy8qY0ynYpvFwHjuYKIN5JidZuD8YBUHMrkCsgEQZrzBuSCjLFAAptBVYS2SiUJmQChRBa9WoE/ksJmVCNHQC6jCLbX8v5lteQKBUZ8cWKZPKemwhjUCrafmqa9wsjd13axf8jHVCjJnMoyLmi2Y9IqWN5oxWFQs7jews5eT5GJILCs0cpl8yo4Nh7ik2uaWNPmQAbE0lJRq8qsLY2X2gySM2AklaOyTEs2X+DbT55mKizB9z2RNM+d9vCzDyziB9fPp0ynlGTMoljq6Lx/WR1lOiW+SJrdAx72D/tYWGth35CPD11Qz+auCsxaFf6YtLidm4mzdUE1GoWMdR0u9g376Z2KlMbLpN/JSs9EmDVtTuZWlXHfC8O4TBpkgsDzfR7OzsT53lO9rOtwctm8CjbNKUelkIEg8LuDZ9k4pxy1Qk44EccfSxevBTkapcQQiaayhBNZynRKrl9cjVYpQ6dSUGPVcdu2Xk5PRZgMJbm8u5KnT06TyuVRyQU+tqqJTE6Ci5bpVNRYdXz4ggY2dpZzx/Y+fNE0q1ocNDsNDHsl+b4gwPWLq7l6QTVymcCiOjOPH5viqZNTZPNSUvDk8Sm+saWT9y6t46Ej46RyBWx6FUOeGEsbrISTGUKJDC1OA8/3eogkc8WRTslF0qJTEUvnMGuVrO9wcdm8CgoiBONpdvZ62D0g8Ucy+cLrFu1zgcRbSstT2TyiCL5Ymr1vKOo7iqPC57u0nK/AmGXzPZcX8RddTGf7Yqrz7PjO77C9cRRIRMRp1HDLpe0Ez5OTzz53ttFQUablgiYbiWye3qnI2xYgZ+NvcW/97zzOu/E/N+677z7uuece3G433d3d/OQnP2Hp0qX/S8d8JxfLYDxDleWtuZ+1Vh0qheyvcrSsNEsOVqIoolXJpQKxTMBmUHEukOC5024sOiXNTgM5EZ7v9TDqj3NFdwWVZi3fe/o0vdNRsvkCerWCfcN+Pre+BXc4xY5TktvzgZEZfvie+ZRpFCDAZEga25j9nv358Di/P3iOb2zpZH6Nme8+fZqpUBKVXE6uUODlkRm+d9VcjBoFX3+sh6lQimRWsoo/MR7iO1fO4fL5VQx5YsTTeV4a9heLTRLfaiqU5sjZICcnwvRPR/ja5g4mgwkePjqOKMJHVzXijaQ4ORlmVYudi1rs7B30ESiyZBRygdZyaaP/zOlpaqw68oUCNz90gsPngvzw+vno1QrkgsAnVjdhN6jZPeBlxBuju9qMTq2gu8ZcdNuTMRaIc3l3JVa9CgFIZvP0uSNoVHJeORPg0rkVnJwIc+hMoGS4s6TOxMpmO8fHg7zQ76PaomVtq4NPLnSR90ww3TeGXZlh6pUhlh8a5JJkFH0qgSmTwJhNon9AwCHLsmPcizGbwpRNIPtylA+mUnzwHa7FLxb/X3hKxwUqNYuVahRaDTK1iqxMTrwgIFOpEBNaquQKcvkMDqcRlVaDJ5knlgeTRYfDakCnUJLTqemdSRHNCZjLdNQ4yzCZdMTzcMqbwBvNYDco6ao0oVUInJoIcWosSItDT1WZBp1CIJ7K4i3kcagESKV4pXeSQiKBMptBSCQJJHx0lClRZlLkEkkS3hBN+QwWIc8lySSXplLIePu922yIgoCo1/NHnZ64UkNSpUEwGNDbzCh3G8hqdEzk5IynZVhdVtrqXcw1GRjPyNCcNaExmwno9eR0eg5600zl5ZRXOVjZUclNK+p5vs9DriDngyvqaXLo+d7TvUTTuaIjdIEDw35u3dzJ1QuqWVxvwRORHOS++KBUdNSr5Xz78jn88/oWjo2FGPHFMGuVrGlz4omk2D3gRSZIfNGdfR7ufW6AK+dXsXGOi0s6ywkmMozNJBBFEW8sTb4grfCiCM0uA/5Yms3zKqi36/naoycJJrKYdUoefjXFnw6Pcdc1XVh1ap46OcX6dhdn/XGiKSmniSSz0rUrExjySu7cNRZpnLXGosW1oBJRhIIIJ8aDmLUSx7PcpEEhk6FXKcgVCuRFMKgVvNDvxRdNF6c9pFHXExNhtvVMc3GnE61SzjULq4mms3jCKR4+OsEHV9Tx0vAMZ/xx6mw68gWRqXCSc0Ww+vwaM9/f0cfPb1zEUyenGX/DOJk3miaVzeMwaXj6xNTrMArJbP5tFU4quQydUs7nHjjOdDjJty7v5FuXz+HQmQBDHmn/tbDWQt90hDu292HRqTkwMsPXL+uguoi28EZS7Bn0MRl8Pb/zfAC9Si4jjlQYEkXJYMIfS5cUWvdc20WZVnL+vrPY4Jh1Zz0w4uebW+bwpUvaqDovL/uvQi6TlG0VZVqiRXWlSiHDoFZQbZUYyP+V6kouE6go0/DUySmGvbHSeyqZO+lK7+msyirYZOTtqyj/9+Lvrij1fyK2b9/Oxz72MVpaWv5vn8pfFW9V4X07OKfDoGbT3Aq0Sjm3PNpTUigBnJwM85WN7bQ4jecVpaTu/M5eD3OrygBKaqshTwyLXlmy75wIJtk36OPy7sqSLBDg1/vPcM913dz3voXs7PUw4ovRVm6ks7KM3f0+tEoZdTZdqYMvFs9lXZuTh49OMOqT2Ef5gkiDXcdFLQ7+eGgMT6Q4m0+WcFLOmZk4V8yvot8doc6mk2SvMgFVcRwoX5Dg6sF4loIo0lBrYTqcZDKU5JbLOkoFullVUSqbJ5LMYtAocBjVfO2xHv7xwkYa7HqePjnNWCBBV1UZq9skjk06VyCZK6AGPvWHV+l3R0tL8bYTU/zkfQuxGdTYjRoePjpBOJlFRNoE33RBA9csrMJmUCOTCfijaRbXWxnwRElmCshkMOqLs2fAy2XzKpiJp/na5k6cJjX/fuAs06EU7RVG1rU7Wd2qIprMUm7S8Km1zUwEkpSbNVzU7CCRyeEwqrlpRT3BeJZwMseBkZnXXSMapRyXScM3iu4tI/44FWUaVjTa8EZSPHfag1Gt5Esb2wjFM2TzIu0VJp46MY0/linBzJ0mDf5YhiqLjmy+IH1U57EU8oUC1WYt+YJY5HcpqLPpkcsEWpwGCgURo1bJTCxDKptHJhM4MOxnMpSi2qJlZbNdAkjm8nRXmzkxHkIAfr53lDVtDpY32mhxGRGAkxMhfvuSm1qrno1zynGZ1Nj1am5YWlNkQSmQywRqrFqiqTzBRBpvNM0Pdg5y/ZJq1rU7eXHQV1K+TQST1Fq1rOtwSlyA0RlqrToUMhlapYwPX9hAPJ3j8NkAcyvLCKvlmNQK2lwGVFVl7Or3MOyN0eQwcO3CGjI5Sb2zoNaCQi5w+EyAIU+URoeBLV0VqBQC44E4NVYdDoOab26RYLdn/HEsOhUXtTgY8kT52mM9VFl03HNtF9csrGZFkw2DWkGsyGsSBIFnT3s4fCbAZEhyvPn4qiZ+u/8sB0cC3Lqlk2angSePT3LWH6e7xlwCOSYzebb1TDMRTNLqMrKu3UWlWcvTJ6Z4eWSGTK7AI69OMLeqjG9fMYcj5wJUmbU0OfRMhyWGwP5hv7TwW3Vs6HDy8xsXIyKSL8BvPrSYJ45NMeqP8Q8rGzColTx1YoqzM3GcJg3LGqxUWbT8fO8IqZzIVCjJngEvyxqsPHfaTZk0GUy1VVIehJM5nj3t4dpF1ezomcYXTSMISskhxypJ2PUqBamcVHB7tNdT+t0umVNOW7kJf0xS8SnlMirMGjZ3VZDISPeFbK5AvJjUSnySDJl8ge8+eZpAIlvioO0d9HLzxnaGvTFm4hnWtDmwG9S4w69tgo+cDbC23QkC2A1qblxeV+z4uTk2HiyNz8x22FLZfFENGisVfBUygUyuwEsjfuZWlnHH9j5u3zqXeDpfUoHMusE8dFTHHVvnMRNLv6Xs/Pz4W9xb/zuP8278z4wHHniAL3zhC9x///0sW7aMf/3Xf2Xjxo0MDAyUeJ5/S7yTi2XfdJQ1rQ5eHpl5SzWUTqVAZ1X8RY6WSrmMde0Odva66XdHUcplJfj4RS0Onjoh8aOuXVSN3aAmULxXLGu0Ulmm5emeaV45K5ljIEibx56JMLv7vWyaW86fXxlHJkgq0xf6vaxospLLg02vIl8QKYjSZiqbLxBL5+goKk1OT0awG1TFJoKMSCrLoTMzXNhkxx1JkyuIJIqjatFUjr0DPt67tJZKs5abH5bUFDqVHINawZ5+L1/c2MZ1i6uJpfNc2CSNVM2tMvP9a7p55tQ01RYd337qNCub7czEM/hjab5+WQf7hvwcGwtSZ5MMUzyRFOMzCd67pJaZeIYPr2zgcxe3AfDepTWUm9Q4jGq+9JCEaVArZAx6ouzs83D7VXNZVGdBp5KxutVJKpvHHZYca+e69DTK03hnJpl8dgBnyMUdST/hvIeyVBRDPIJqJETmzzOkRib4p1wCYyKKMhxEKKoVFhY/04uBtYKMiNZAVK0nptKR0OhI62zQUIWjrR2ZyUSurAzRaEQwGQkptbwazDOVV2BzmGmudzGeLHD7C2fJKjVYbUa+trmDuVVmJoJJnjstuTJLjlkuaiw6Hu2Zxm5Q0VVtJpTKcfPDJ5gOpzBqFEWepYKfvHchg54oX3roBNctrmFDh5OQQY3coMagktEazzJPIUMmCGiUkvJ6z94RFtZZMBrUPNbvLTkEbpxTjsyq40+Hx3jwyHhpVDCVlcbt37e0lqsWVJHOFXjm1Qme7pnm3mu7KYgin/njqyRiSRzKAtlYgjaTgs9fWE0uEuVE3zjravSkQ1GGR6eJBcK06gWcQg5VLEYhHkOdSiJGozDtwRoIow2G0WVTaLNpNOkEnW8hVmg6789ZpQqZ0cBelRZ3XkFFlZ2IQsvn0gIxhZqoUktKrSWnNxA/XclllXYM43YyRhP7/DnSQwEMOiNpmZ5vPnmKaxbW8MEVdVy1oIrTU2EePDLOwdEZtEo5Nr0Kq0FNmVbJT967UHINj6Z5/PgkL4/OsKjWwvVLJBf12dOuNGvZ2FnOUyenWNfuYu+gl7MzUoE7msoRT+cY9MR4od/LjSvq6Z+O0F1tpsGuZ0ePG61KTrVFSyydI5cXmV/M2bL5Auv/ZQ9/+Ohyfr53hAMjfm5cXs/yBitlOiUtLiMHRmZQymXkCqLErTVpsOhUnJmRJhvKtEqMGgWToSS5vEifO8LKFjuf/fNx7tg6jz2DXh44PE4wkeVDF9Qzed59NJrKkUhLefuoL87GOS48UQmfMV7cH2aKuVcmX+CahZKB0z3b+zgwMlN6f57r9XDvdd28sexyvvOzL5bGH0uRzhX4wXOD/PpDS1jZZOPaRdVkcgUiqRxmnYqNcyrYP+zDE5EK7TPxNDPRDLc8dpLpUKoERz8/L5lVyefyknIvkxdpdkoM3WNFzt2pyRBPnZzmM+ua2T80w3gggSBI+bZKIRBJ5jhSHG39awxxNEo5q9uc7BvycXZGxFC8bupsOla3OnnlzMx/qbpyh1PctaOPM35JpfvSsJ+DZ2a4c2sX5ebXF8c0Svn/smHPf1f8fZ7Vf3N86lOf+r99Cn9VvF3nucKseccNwJxKE/9+4GypICUIYNYpmQ6leHl0husWSzfN88Fsw94oF7VIbgmz7nXwZvvOsUACmUxgXpWZl0eljWo8neNDvz7EZ9a3cu2iahRyAaHoymE3qJiJZ1DJizPkxY1cMiNVxW+7ah57BrwMe2O0VxjZOr+aeDordd1A4goh3aBcJg0ymUC9XU+ZVsWBEWnUx6RVoJAJmDQK1rQ5UMgkgOJkKMmOU24eOjLOFd2VLG+0cXFnOe5wkiFvjCqzFotOxZXdlTx0ZILlDXYaHXq+9mgPI744IiIHR6T39dYtc9AoZTiMah4+MkHfG/hDA0UXm2sXVRNJZBn2SnJ4p1HNZ9a3sKhOcuT7w6FzBOJZ7AYVl82roKPCyC2P9pDOFTDqlIQSWVwmjaSQMcNn/vhq6WdZh1QcHPFLxSqjGptRUqV4IylkxQ0rIiQyeVa12Qkmstz2dC/uSJpMrkA4mWXHqWnu/8AigvEM48EkC2olgKZWIWMqnOJne0fI5gsMeWOEk1n2D/tLxU53OIVGKUOrlBzTVrU6cBhUdFZWMqfCyGPHJ3ni2BTZgkiTU49aKeeiVgd7Bn2EEpHiCKHEpVjV6sAbTaFSyHjmlJsNHS5u397H6akImVwBvUrOviEf39jSiVYp54ImGwdG/IwFpMX03w+cLRXX7tzRx1l/HJlM4NhYmGNjQW65tAOLXkUgnuHFIS/nZuK4jBouanUgEwT0KgWJjNRB+dW+M9x9TTffvmJO0d0oLm0kWqXf++d7h0llpYTdoFawrr2ajkppwV/ZbMNmUDPgjlKmUWLUKvn8A8cZ9sbIFhkB23sk2LdVr0IQBL79ZC8HR2eKEHQ3u/o8/PR9C1HJZfijGV4550avknPl/CrCiSwDnig7Tk3z4qAPo0aJL5rm8JkA1y+uoSCKuMNJrAYVyWwek1a6tYsiVJslF5/ZTv2ZmTj7hnx0Vhipsmips+l57rSHmXiGSrOGhbUWqixa7t87gkWnYt+Qjx+8Zz5ni+OfEhC1wNcf7+GK7io+sKyWBruBU5NhHCY1t2/ro3cqQjpXQKuUS9+bzZ30T0eQywUW1Vq4cUUdCpnATDzD957u5dCZQEkZ+fDRCe6+pouVLQ529nrQqxWM+uOs73CRKcLsW5ySg2HvdJT73rcAp0mDRafklx9czM4+D5PBJBd3utg0R7LDjSQlDsRXHj5JvyeKKEpctX1DNr56aTsL6sylBX86lCopu2bNInb1e/BEUph1Km5YUssTxyc5MRlGIROoKNMik8HhMwGeOS05P/6smBzeclkHK1scvDgkqUlfHp3hqgVVXN5Vyc5eD+5wilqbjvcvl5LfvunI6xQY+YLIuZk444EkeVGkUBx5CSWzTASSXNJZzkQwWRoBPh/iqlPJOeOPs3fQx5J6K8/1et7WDeadVCR/jZvN/67jvBv/c+MHP/gBH/3oR/nwhz8MwP3338+2bdv4zW9+w1e/+tW/+bjv5GIZKfJ2/is11F8ywuuJSC6wX720nRf6fQx6osypNLG5q4JIMsvcqjLq7Xr2D/uZCEg24hc02YgVWXtjM1IDwhtNI4pi0WVOyiUumVNedBkWkAlSE2ZRnYXnet2saXXy+PFJCqJIXpTOp8mhx2ZQM+iJYjeoKYhSY2iW6XfGH2fzvEpu3dyBXq3AE0mzq8/DEycmOTEe4ppF1Txf5A45DCqUChmxdI4jY0H2DnqLIywZ9gx4efLEFHOryljd6uAfVzbw6LFJEpk8yxptvDDgJRDP0OoysqHDyZauCglefi5INJnlSxvbcZo0uMNJBj0xzhbX6cvmVXDF/Cr+eGiMeCBCVy5KVSqGbiqI6PMROL2NJn2e+KSbvMeLPhzAEgzQNjODEAqyVhT56Bs+r3KViqTRTExvIma2oC13UL1iISljGYezCiYEHbYaF11djSQNZaiddl7w5fjtyRkiaakxoFXKMWoUvG9ZLRULqwnEM+wdlJTODoOGi1rtlGmULFbKARGFTEY2X+CRvcNEtUZ0KgW1Vh1NDgPBeIZ/3TlA73SUVDbPq2NB+qYifKvooPzI0Qk6Kk0cHJ0pjaQnM3kyuQJppYw9A146KkzcfY20+dwzIDEL51Sa2DS3HKNGavqM+mJsnFPO3KoyLmyxSw3Hh04w5H2Nr3hodIaf37iY6XCqpNzVKORs7CxnSYOVymJzccATYeOc8lLO6Immuff6+Rw5F8ATSVNl1rK80cpUMkvPeJh1Ny0lUsQjdH/IQiZXoN8d4Vc90yypt9LkNHDkbPA119wmG2f8ce5+ph+NSs7V86u4fq6dgeFJ6tRw4PhZdr4ygiwWQxaP4SSLjQzLHGraDZAadaPQioTPeiEUwJEOUJdJos8k0WdSmPakUKVeW6PqgRuLfy4gEFPriGmNCBYz2monnToTRkHDRrURU0055Y3VaJ71sERt4nlfnh0ZFZX15WyaW87ieskt2GVS8/kNrZyajNDs0nNFdyV2g4oruiqRywWe63WXHMPTWcmUBmDIG0MURRodBvYMeLlyfhXPnnYz6JFyS5tBTUORF6WQybh/7zCxdB5fRGJ17eiRjJie7/NwSaeLNW1Odp7WEEhIBkEVZi3VZi1alZxyo3RPmOWVpotNr0aHnkA8w6hPyh+W1tvYftJNLJ0jL4pUWV5rLuUKEl4iXxzFnQyl8ERShJJZaqw6soM+posjaKIouSm/OCg1LQ1qBZFUFgGpoLV/yE+tVYea17AF40UuqkmrpL3cyG8/tJRvPnGKSCpHJl+QHD7lMrb1TNM7HaHJYWDrgiqWNlgZD0jc03MzCfYN+uidkvZQs3D08/OS19z0pCZwuUnDyhY7AhLjdtgX5+aHT5IviHx8VRM9kyGyebEEWAdKoo2/Jco0Cj67vpXd/R6GvfGSoY9Fp2Rj8Xv8djGbd02GpO+tRa4CIJKUnFqvWVSN4v8Rkfr/yKLU/2vxThyEd9oAXDG/klAii0WvJJuT3CAEAUKJDKcmw6xrd75uBjaZzdPsNBJMSPa/s6MmAGqFHAFKjnM1Vi1quYz1HU4OjkoWugAiQnHzaqcgQjiZ4bnTbi5stvP48UmGvTFCRT5Pg11K+tQKGelsjo1zynnPEmWpGzfsy9LsNNBVbWZduxO7QU08k6PBpkcuA0RwmdT8y3Xd0oZsRnL8uLDZjlIuI5TMcMfTfXzz8jn0TUeYCCb57Utn2TfkZ0m9laUNVlqcRmx6FUfOBuioMOGJpNjQ6WLvoI9Bb4x8QVJhZfIFxoNJdvd5uGJ+JYqifPb8mHXNGHTHAIHJUAKHUY07kuLDF9Yzt7Ks5Mg3FpCKi4l0jidPTHHX1ZIrz/N9Xmmja9ZIPIWRGS5osvHBC+r5zlOnyRfAqFEw6I2x7eQ0GzpdIILNoEJbBH0/3+dh1BejxWWkzWVk35CfiWAKEJkMJUlm82zpqsAbSXP79j4mQxJ82h1O0egwcO91XVzYbOdX+86weZ4aTzjFbw+c5cCIn69v7mR5o5UHj4xj0ij43IYOnCYN20+5iaVyVFu0fHBFPVvmVXJyIsRl8ypQyAXMOiX/+p5uTk9HePaUmwqzlg3tLgxqBVadigePjLOy2c6+IT8vj8yUiqTxdI7YmQB7BnxcOb+SSrOWWzd38uSJKUa8UTZ3V7K8wUYkleWmFfUcPhPg0WMTxNN5gokMk6EkCHDLoz34Y2ncEWlxfOTVCe68pouDoyGWNthYUwSr3/p4D/e9fyFbuiqJpXPMxNKM+mIIIty4op6nTkwXC6NqPr6qiXhaAsrvG/Iz5I3hMKppLTdyaDTAVCglXROCUOrSvzw6w5XzK3l5xI87LIE1Zx3s0rkCewd9bJ5Xwaf/9CoCsLrVSb4g8tsDZ9nd7yGaylEQpWvApFWW7JG/9OBJXGUarphfxdMnppiVqoVTWRrsejbPq8SgUfDnj60gL4okiqOhKoWcf3luoJSEBuIZjGold1/bxZXzq/jzK+PEM3lC8Qz1dj2KoptRriCSzcMDr4xTa9VRZ9NTZdGws9dbUlNJcnlp7GPPgJctXZWMBxL87uA5woks719Wy/5hP+dmEuTykjuhWiFjxBtjz4CXpQ1WCqLI0gYrjXbJcecjFzWSzRdY3eLAblSTzovs7vMw3euh1WVkfYeT9y6tJZHJ0zcdQSmX4YukKCB14oZ9Eow0X5Dk1n3TkjvO1Qslh6vziyqXdLpKZhHJbJ5kJk8omWFDh6uUUEVTOaLpLIaitfMsd2D2PryvaNYwy6NZUTQtuH1bH5FkloIIL4342T/k59YtHVwyx4VZq3rdmJvTqCmpG2a7iulcoQgFFVDIpOvh3EycmViaTE5ErZRh0irRKOWMnndOb+cG804qkr/GzeatXGAvarWztP61Dc278W68XWQyGY4ePcott9xSekwmk7FhwwZefvnlv+pYyWQSo9GIUBwdkVNgea2B/QMKpqK50vMqDDIWVelRyYXSaEM6k6WQz6FTy1/3XUwmi6YPajV5UcrNdvVOM+6PUGc3cu2SenL5AuUmDalUiovbzKxrsxFNS0wQh16JUyfjqw8cRZSryItFp7IyBbddNZdoIkWZTolCLqBXQjSRIZtRoFbIaCwWMKxqAZUcsoU886rKsBlUZLJ5RtwBvnVpK8en43gjklNTV4WeQDhGrVnD8fEQE8EkqUwWsZBDJkCVWdKaHB8PceKsn3q7lqvnV7Kk3oo7nCSdyTHuCxGKxFFrNNgMKvJ5kUI2w5gnhEpWxc0Pn2DUF8duUHJkxMPe3gm+c/XCUuNEpxAZmQ5yxYJqHj46wW/2n+HK+RVc2GCmzaokH0whP/4qEb+PHU8fIj8xxdxkiPJEmHwyiC4b4R/cXj6eSb3pM85qdWC3I5RZUdjtnC0rZ8rSgPpCJx3zmjHVVBDWGNjvz7BqaQselZ7PPjnCqF+ClfuCURodeu69YTFPn3RLIHEhj64gsDhk49bVXag1CubYkhh6faQzeQw6JQgyaq06ltVb8AYi3PnMIONhqcGXyOR58JCK266aw8FzEda2uwgns1SYVFw518G6Fhtng2lWtTowqJX84aU+Tpz1YzZIZiQAE4EYz508x5IGO/NrzRjUCiaCCcRcBkEU0auU6IqjjT2TQZbXGSEvcMsjPYz644jAgcFpDg9P86n1HfROS07EF3c4CERiNJhVPHLiNZMN8lnUcgF/NEkgIXFTnz01hVDI8clL26lzWni+z4MvmqbBqmJBdRnn/BHqHSbsRjV7B7yY1HBpuw2tTsuwJ8oTx6d4sX+KbC7PwWEvX7t8rmRkVCjw8KERfrJ7mGuWNtBRYeL27X30TwZJZ7IolAr2D1n5+uZOrl5YxbZj55gKRJDr6zDWVpFWKXixN84rTjDWqcgiI57KYTeqcdcZqVrTTKVSRUGpYP+hc9yz4zRyRAqCgCgokMkEvnRJK1e0mXn52CirK/Q891I/2/b1YUlHKUtGKcskqSRNtxGUhRTBcTfVuTjtsQiKF2YQIhEADMBHZq9FmZyo3kR7uRPBbidjsXFTuRPR7iBrMRM4aeAX41muumwx9sYa5jl1HD8rImbTKOSvrYtNdi3BaIxLO+z8dO9ZaUzs6i529Yxzzh9nfoOd1W3lWPQqhjwhdhwfR8hneb7Pw3WLa9jR4yaRSpHLpPjjwTPMrTJzx9XzeObUNP0TM3TXWFjTWYVSIeOCZjuPHjkLYoZ8ToKZNzn1rGqy8fzpSZRkSzmNUi6wuMaIihwXNpp5vraMcCKLUgZKMSe5ArY7eaZnmhqLDn84zrJaA08dkzGczkmg/EIeqxom/WES2Tw6leTIJxRyKGUiU4HX9lTTwQQj7hB6tZznTs8w6o/T5NCzsd3OLZc08sk/HUcmCFh0Kr75xCn6JwP4Y2mQK9lxys0913bRZFOz+9Q4q9rKX+N3iiLZdIZIvIDFqC/lN3IK2LUCV8xzIldI30O5TCASi3N8PMC3tw2gVckxqpXMRONUGGQcSCSxGnWl8cRCNk2FXoZw3hhrLpcjm80ik8lKpmgAqVRK4giqVGQLktOeLxynu8rEmmYr8Ry8MODFaVRzaYedXKaATKVCLpe/7riCIJAXFKW8S8xlQBQR5EoEmYROSWey0r1DEF7H3/57jHeLUn/n8U6d50QmXwIRvzHGAglkgkC9TY9FJ1VNc3mR6XCSbF6k2qJl2Bvj3ucGuGPrPFa3OuidjnBxp4v9wz7gtVGTQ2dmCCdzRd5Mjnq7ng0d5aRyEjz6rmu66J+O8vKIn8u6KlHKBZ44PsXieguHRgNs75mmxWXg9qvm8cKAl1FfjIV1FjZ0uLDqVSQzOVpcxpKy6cDwDCtb7CgEgV9/aAmBmFRomR25qSjTEE/L+PMrY6xucyBDoM1lZEtXBQqZjMNnpBvv4d4ggXiWUNFmtiCKaFUyvnfVHDRKBfuGfLw86qfGoqOrxkyuINmhGtQKRn3x172fqmJienJCKuZZ9CpanIbXPUcukwCMLS4DmVyeHT1uti6sZtvJaRbVWUlmcjzf52E6nOT6xTVcMqcch0GFO5LCF02xrt3J3kEfGoWcpfVWnj3l5tleN0+flJg671lSy54BL9miFXXPZJgLmu3c8uhJfnnjYvIFkdu29XJiIoxMgOf7vFw6t5xzM3EEobiRNWnQKWXcsKSGl4b9kkpJLiDTKAjEZYz4YlJnpMEKwPuW1pLM5vnelXM5ci7A830eruiuwlWmZkGNBbtBzS2PnGQilKTcpEEmwIFhqXg1p8qEL5rh+T4v48EEdVZJdfTZ9S30TUfYcWqa/ukot1zWzgeW15HOF/jz4XHJHlgukM1Ls/iZfIF+d5QtBRFBBulcnusWVWPSKvHH0jx+bJJTU2EqzFrWtjuos+n41lOnicVz6NUK9gz48MVSRJKSRFopl3F2JsHeAR9L6y0cGPFzw5IaNs4pp0yrIJ0t8M0nTnFsPMRMPEOhINJdY+aea7v4+KpG/nR4nA0dLuxGFWqljGggwQXNdlpcRnacmiYYzzAWkEYhg4kM2WKRwKhRMBZIoJDJmAyliuwlSUacyOQJxDOc8cdJ5fLMxDJ8Y0snLpOGmVi6xARwGNUUChLoO5XNU2vVIwgC5wIJJsOSFfi/3rCAg6Mz9EyGabLruW5JDYl0nh090wx5Y9RYtaxrd6FXK1ArpULURDBJg11PNi8yE09zbDzI5za0sq5dcl7qm46wts3Jg0fGGfXFUcgkbkGzQ8/FHS7kMgGDWsmgJ1oaO5HJXitgnfFL7phff6yHYV8Mm17FdYtr6JkMA6BXy8lk87xniWR7XWvT4zCqqbXpefL4JLv7vdRadaxudVCmVSKXwUwszY92DnAukEQE9gz42N4zzR1b52HSKkuwfZVchoBkeZ7LiyjkEsDeoFGgkgsll8NZuPvieguhRIalDdaSO161RVuElcJUKInLpEFf7PJlcgWEYq7R5DAQTGRLxftzgQQKuYyvFztwC+sk971AXBoB9EXTiKIEU37qxDSXdLowaZSvk6xv6a7gyRNTDHljktWzKP2clc12RBFWtjgAKNOq8ETTAAhJiKUUlJdp6KgwlRoNb8cleCcVyX/FMngdWP2840icsUYcRjUvDHjxRTN0lBtZ0+6k4i/gS70LSv+fF36/n3w+j8vlet3jLpeL/v7+t3xNOp0mnU6X/h4pbhg3bdrE7t27sVgsAPznf/4nP/vZz9hw6RZWbf5wSQ31b198P++9L8WTTz5JZWUlGqWcRx96gB/84Ads2rSJ2267rXTsyy+/nFAoxB/++Cd09iru2N7H4KHdhF9+gM6Fy7mo/fs8c1oa2zv+q1uIh/x88pv/wgMjcFGLnfbsCN+//bvkbE2UX/opYknJqcy37Qf80wM+vnHXD1nVOpeXhvykx3tg/38Qs9Yx771fYX2Hk2dPe4g8/1MKgQkqNn2cpQ2LJX6I6Ob7n7oZk6uGH9z/W2qtWuLpPN/88mfpOXGcz3/t21j1kvpEEZ6g7MivUZgcrPnyQzx0ZJyHj07gf/4XHPENsm3Ze/jpVz/KkgYLp/oH2H7nx1BpTeiu+AbpbAGDRkHqwKPs2XmKusRnmQo7eP+yWhbZ89z++Y8wotMzvvZhVjRaufuaeTz1o7uIPLOd/EVraIqr+Wr/CNW/n6R2uo+KTAZd4TUV/ieBgEKBV2/BZ6tlxF6NcVELv3vqMYIKBRNLP0zCbGPx4lZmRl9m184nWbflGt77D5/gK4+c5JwvivG5b8PMEI2LruDe9SuoNGs492/3s+lD32Xuyo1MGlciIjleqZ79HhNigScbfkZ3S62Ue5w9iHzwWfoal7C34ytc1GxnPJjA/8h3SCbiLPiH25jT2simueUc3rWNH//wX1DVdiMueR/prPS7BJ+8g88+FOUz3/sxL/QLrOtw8cLzz/KrH93DwqXLufPuf+GxYxNcs7CGJ//1qxD0MrXsI+QskoLYHh7g/j9+mRfmdhNYcBNf2dROlVnLzI4fUwhNYVj7MbRV7RREEXPkLB+46mM0trTxbz/5OWqFnHxB5Auf/gQnnurlj/HPs2nDBg6fmWF6tJ/P3fpFauvq6f7Qd3AY1SQyeZQHfwe+YbIr3sfpqXZWtTr4/TP7CW7/V+57yYV4yc2MBRJUmbU8/++/gelePvjJzyOsugS9WkGtKsYXPv5hjKYy3v+dX/KLF0clmP0rfyJz9hjJRVeyr93FVQuq8bin+cXNN6KWq3jPp54pNSLVpx5HNXGUeNM6Xs6sZd+Qj6VVGv7jK7fwFPDZSw4gAJFUjtCRpxBf3E6qcz2GBZchEwQy6RTb7vgi2+6AG773G95/QQsrW+z84bcHSJx6nkzdChJtl1JnlRrXWzavB6DhT4+z/PqNPKGo4MC+p2DsEOqmZTRv/ARzL2nlDwNefve1m0Cu4I7fbKOtsRajrMBdt/2Qc888gN1Wj6lqIYZoCEc6hqX3eQwzPuY3tJAdGcWciKD0ejCl03wB4IfStX4jcKVCQUAuJ+KoY1pvJ2O1Uz2k5olXDqJrauErn/oCR476KVRX8NIvv8PY+Dmu/8l96FRVBGNpHtu+i9Rj92I21/KE5qMsabBy97Vd3Pr5T+AdG2Hth76My6SWxi8Doxz40deZbGxi5Y9+yf4BH4sbrFT0/onenhN0b/0n5l2wkjVtDo4cPcYDt9+Mxmhn7sX/hgi8d2ktL/7nPVz7s4Pc8vVv8P1rLmbfoI9jPb3sefR75K02Zi77D145G6DWquOB++/l8Esv8oGPfYYV65Yz6ovjlEX56PWbUWl0ZDZ9A5tBLU3OHHucwrmjBDU3It88h1Q2z+kzk3zjk+8HQUZ8k0Q/Kogij//HvxHp3U/zRVeSL1wgITAm/YhPfRsbMLP+m4z6Yrw46CN57CkefuBPjF1+LY0XXi298WIB/c7vkgXEG+4o5Te/+c2v+eUvf8l1113HV77yldI9afWmi8nn89iv/RZynRmZIPD7P/yJo9v/iL5lKax472vr18Pf5qd/TLLu0Uepra0F4NFHH+Xuu+9m/fr1fP/73y89d+vWrfh8Pv7whz9QXd/EuZk4zz+7nd+99CfUVZ1YN3wMgAuabNx04/uZnJjgV7/6FfPnzwdgz549fPWrX2XhwoX8+L6flfIu//Z/JRecwnrxJ1FXtlFr1XH0lUPc/KUv0tnZyX/+53++5Tr69xLvFqX+zuOdOtizzlVvFbVWHSq5rDQne77VZaNDAqC9OOhjZbMdvUrOB5bXIQigVylY1+qk2WHEolNSY9Nx59Vd7BnwcmwsRLPTwPVLaogkczx8VJoxrrfpWd3m4FPrWnCHk3zv6V5OTUVY3mjl1FSYsUCCHz0/xLIGGxc223jfslqUMpkk3903Sp1Nz5J6K6FkRoKDAlqlDJtBjT+W4Y4d/UyFkuQLIi/0e9k/5OPmTe1MhlJ88YGT3Ht9F8/1ekoQ8q8+2sMfPrKMqVACpULgyNkg69pdHD4b5OuXtqNTKfjKIycZ8sQkFyu1Alefh69f1sHWBVVMhJLU23XIBYGCIGLRK7lucQ3LGiSZsUYpMSIunVfOngEPr46FMGmVGDVKGu16Ns0tZyaWYdupKRbVWfj+tV04jdLs90Qwwe1XzaPOpueFAS9n/fESQ6DSrOX6xTUsqLUURw6nyYsQSqR4ccjHmjYHO0+7mQglyRcBfL5omlFfnEQmx0sjM/hjEkR0linhjqRxGiUItlwmI53N8/ENLZKk3xvDG0mjVsgo0yqpteoIJ7P4oim6qsuotujYfsrNqD9OhUnDunYnyUyBfEHk9qvmoVfJea7XQyiZpbJMGqlMZvL0e2KMhxIg6LhjWy8nJ8IYtUri6Ry/PzjG3dd28dLwDC8O+Qgnsuzq93JFdyVymUCtTcvVC6tY3+7CXpzT393vpc6qk9znioWOIW8Mu0HFd57qJZLKEkpkS3bRd27t4kMX1LO9x43doCoVgtK5AmatJANWFJV0tTbJRTAvwpAnytyqMjRKBV+7rINHjk3wHwfOEk/nOTUpMT0+sLweu1HDpjnlFEQIxLO8NORnOpyixWXkY6sasevVrG51cHA0gEYpx25QsLbdyQVNNuqsOgQB1rc7SedybOgox26QRjUOnwlQbdGiVSqKBSk133ryFN/c0sn6Dic7e90MFq9Zu0FFvU0a45UJcFGLg31DPn69b5R7r+vmwiYbyxqsqBQywokst2/v4+WRmRIk88kTU9xzbTc2vYqLO13Ej08BEpekIIoMeWJEklmOj4e4fnENRo0Cp1HNfe9byIuDPs7MJKgs03Bhsx27UU3/dITWcuPr7kcCklLm2u5KbrqgHoAvb2xj94CXF/q9hJMZaqw6XhqewapX8fHVTTQ59OwZ8PF8n5e2ciMLas20OA089uwAZ/xxfm838OMb5lNv17NnYJrJcAqZAFNhiTMQTGR45rSbLV0VzK+xoJJLSrV4JkdbuZHn+zy4TBrUChnRVI5wXsRhlNRqU+E0T5+QvrM3LK1FJRfYccqNSSPB6zVKOYlMnl19Ht63rI7DZwNFcLCEd521Cd/d7yVYLDo5DGpyeUnVdM2iarL5Av6iQYCvWEAq00qqt2QmR61NhyeSYu+gn4lggiqLlota7PzmQ0t48JVxhrwx6m06Vrc5EUWRc4E4F7XY6ZuWQOZPnphixBdDFCXQr82gYkOni+0np9/WLQze7N46G+/0mrcaK9/cVc7q4nFaXUbsBjVfeviE5KRo1rJ30MuLQz6+dfmct+VLvQtKfzf+mrjzzjv5zne+8xc/36B+PRvqZ+/g2J0viBI7UZCKpLMKXk8kxajPW2KmgGRU8K0nTzPojhJKZtClc8gAi17NprkWHAY1cp90/c4WynOFAufXe/MFEW80zbeumMMD4jjb94PDqObWzZ1Y9SocRhUmjZIQcO3CGoa9Ue55dgBXerx0jD0DXpbUW7nn2X6MxcJ2mVbJt7bMYWefm56eBMeOgN2gokyrZCaewahREJFJ97GCKBJNZ6mz6dCrpO+9TBCYDErj4RadCoteRRiYDib51/U11Ee9nHhkHx9wu6nOF+j+xI3opydwjJ5hfar4HvX3k9fpGTU4GNdbOWI0MqXWENvwUT7+/tX8eTLHg9seITV6iHTTWhJNa6mxaPnUykr+dPgAAPd++6O0V5qRCwJ33vtK8X2Xs7c4cnkeT5lhb4y9g96SCzNALJWjqkZLNCU1WWdj1Bdn/UK1ZLJTREuIwHgRU/GrfaPkiu/lDUtrUJdZGCyOgYO01s265M6iJgAsehUHx2Jct7iGZEY6B28kTc9kWHLyozgOD1SUaVHa9QgCxCNC8XoosLrVQUWZhu4aM4+bNUyEQKuSkyuIVJRpWFhj4Yni7/b7g+dwGjVc1GJHUbyw2lwmuqrLuO99ixgfPCUdt2iaYtIoMOuUBOUCOSTzGV9Uygk/taaZ27ZLTcBkcbohm5dczlTAgCfKer0KBFDIXrsvD3qiWHRKBEEgXHx/Iklp/FQuo/TmqBQCLpO61MhSnSeiTWcLDLijXFjjKD324JFxNs0tx6BWUGnW0IOEFRFFad+il8OszmZpnQ2xAApBYE2bg+2npD3RxeuaWd3mKH1uAMfGg7y3voLvX9vNPVMHeLkPWlxGvn3FHLL5AplsAYVcRi4Pk8EEt/3qII9+aiVejYERrZaz9gpMSzagkAsUCiKR1BmyyRg/+/VvaG5uJiaDBx9+lH//4d201rZx7eU3MF+dwRgJ8uCPf4A6FKKjuoo5hTz2+BiFvePMCQRQjY/Dnt3UFc9zAxBSKNDc+H6iZU6yJgvv18qonp4mnCwQGD3Ecz8fYM2qeVQpwCuKNNj07Orzsm/Ix1j/CAD+WIZ0vsDXnzjFd6+YW2o4Xd5dQXmjlUdfneSZfdJzlXIZG+eW4zKqabDrOfwnefGzk5SC1yyqplMfZ8/PpSblK2cDbOgsZ0WjjR++LKlRw6ksF1WbubjDxfCZczyJ1ARrdhqIJHPY9GqiMoEM0GCT1PjpbOE1BEXx9xcEMGuUpIqF32WNNpxGyQnQoFEQKj7PadSQR8AbTWM+zyzmfW1Onuv1MOqJlD77WWfT8/ObbL7wlrB1GUJJETUrWlhUa2Hh0hrGAxK/9OcPyyn6OLwpZteSWWOu86/B80Hrb4xaq45Db33IUpyfv/nOe3w2fzvXO/62r/17C0F8J6u7d+P/eEQiEcrKygiHw5hMJlLZPA8dmeDBI2++qL5+WQeVFm3JAWA2qi3aErzttQTfy6nJMFUWSW0wE0sjCAJWvYoDI34C8Sy1Rdib06jGG00zHkxg1UkOZNl8gVROstAVRZEvPXRSgi/rlVh0KmqtOu68eh5PnZjmwSPjFESRWzd3cOhMgPv3jlBWHCVZ3mjj+sU13LWjD2/RWc9hVKOUC9x1dRfxdI7OShMapYxcAR4+Ms7PXxwlU2Qg6NUK0rkC1y6qpqPCxEf/8wj/vL6FpQ0Wnu/18g8rG/jE74/yzS0dpIpyVJtejdMk8Y8yOZFIKstZf5xDZwLs7HUTiEuWzdcvrmFLVyUFUSSeyXHrY6fwx9J87bIOyk0aDp8NMB1OSot+qx2XUUM0lSuBqMvLJMi4TJBu5gatgr6pMP5YljVtDsJJSQpr06v5clHyjgBKmYxFdWa+f00XCAK/3j/K0bNB3JEUBVFie3VVm/n4qkYeOjLBiiYblWYtdoOKfUN+vvP0aR775IX88fA59g74GAsmKRQT7o+tauTSueX86PkhRv1xLu50saHTRTpb4NCZGX66exidWs7W+VVcMqcci05KfJOZPF9//BQ9E+ESQL6iTMOtWzpRyAQePzbFTRfU8/O9I7w04ieVlVhV8iLT68c3LOCVswF+d/Ac7nCKSrMWbzRNJJnlM+ubWdZg48sPnSBXENk8r4LrF9cgCFICPh5MSiOIRejnhg4X1RYterUcTyTNNx4/xcdXN3JwNMBPdg9TXqbBpFEwFUqRyub59LpmltRb+cWLo/zg+m6eOjnNg6+Mk8lLrmmzs/P/tKaJqxdWE4inserVTIUTvNAvfZbd1WZWNNkYm4lz27Y+Epk8G+eU89VL21ErZIiIeCNpvvXkadzhFHlRJJLMUVGm4a5r5mHVqxh0R/nG46f4/CVt1Fi17BvyE0pkqLVKgFetSl4qNDTYpfnxyjItA+6IBG4XBOLpHHqVvDh2KLJn0MsZX5z2CiNbuipL4xTJbJ4Hjoyzd8DH7Vvncf/eEfqmI9y6uZNBT5RfvDiKN5pGLkhJd0EU+fS6ZjbPq2AimOTbT57m+iIk1aKXvo9ymcCPdw1ybDzMvdd2YzOoODkRpkyjxKxTFsf/ZOzt9/Gtp0/x3OdW449l+Oc/v8qwN45eLedbl8+h0WHg+FhQcrHRqVjb5mQ6nOSsP86FLXa+93QfFzbZWNfu5JZHexgv2qBn8pKy8Y6t83joyAR/ODSGIMC3tnRy9cJq7trRz6EzM6VRTZASl+sWVfO5Da08cnQCXyxNeZmGK7sriaZz3Latj/FAgqlQinQuT7PTwF1Xd7FvyMeqVkeJ/bFnwMuGThf7h/w8eGRckp4XraMBHvr4CrQqBdt7pgknM9Tb9CyotTAVSnLr4z1EU3kaHXru2DqPnskQq1ud1BQdYB46MsHvD57DHUlJ76NS6mzfurmDWquOWx7tIZjIolQIRSaYhq9e1olGISOYzBCMZ+iZCLO6zUkwnqGt3Mh9LwzRVW2m1qpnz6DE5mtxGtk0t5yKMg3PnJJGqN+usDO78fZHM1ICW1SRzPLUFDKBvCi+Trk0EUhwe3HtUStkrG51cFGrnRankZlYhmy+wI5T0/zu5XMYNApyBZFoKst1i2q4YUkNdqMapVz2puRvPJB4w7j669e0t1on343/f0Qmk0Gn0/Hwww9z1VVXlR6/6aabCIVCPPHEE296zVsppWpqanC73TidztL4XjabJZfLIZfLUalUpeefP5InK26uk+kME/4o+0cCuGMSf2RxvYUxb4hf7RvltmsW8OuXznJqMoJcKPDlDc0cHQvy51fdmHUqvJEUmUwKsQCfWN/GqlYnBrUSjVzk6WPjPHFiGqVagpz7omnIZ/jE6kaWNTu5+9khvnJpOx1OPal0BoVCjkGnxR9No9coiMQSDLoj7B0J8sSJaZKZAmoFfGFdIxc02cnLlOwZ8PLqWJDPrqnDpFZiMWjp88ZpsOtRyWA6GGXYG8eXKLCs0YY3mubeHadQCvCZDe3UOYwcPhNgYibG5ZUyTO5pzhwbIDd6hoqQh/qIB+30BMK5c8gTrxXm4koNE2VOYhU1NC+dyzFZGTsiSkKOctQtzXz+vSs5G0iAKGJWiQQTOcYiWS7vquSRVyf55Z5BjGqBnCjDF8+jV8v50iWtXNJmxRNN89KZMFMh6b55YYMFi1YOMjn/8vwwz/d5EQsiQkFShVpMei7vruIz65p55MhZVjZa2Dsc4DcHxjFoJMMTshlERLYurqe9ooyvPtqDXgGIeURBxodWNnNhs51/+sOrCLkM2UKBgkxBLF3gpgvquHZBJY8fHePxE9OE0qKkgM0VSp/n/HoH/e4Y71tWx788e5pHXhlj07xKbr2ii4lgknBSGse8Y3svgaSIKAgks3naXXpuvrgZg0ZJFgUvDvqYDCVx6WSsbLZRaTWSFSXe03Qozp3bTnFuJslkNEc6W6DZqed7l7dx9GyANR2VWAxq7tjeT5tLzxVzHYgIBNPwlYdPEEhk0ckLKGTQ6DTxuUs6eOCVMRBFPnJBLb/ef4aXzkYIxDPEMzlSqTQKATZ1VXHLlrkgwpFRP8sbyvDH0+wcCPLsaTe5vMiYL0w6l0ejUvLQJ1eiUyvYN+DljDdEmU7JR1a387uD57jn2QEEMYdaAFEmI4+cL1zcyg1La+ifmGE8mOAXL03wwRX1tJUbGPNFqTar2T8SZCqSYUGthaUNFkbdQfb0+/j8pjnkRQgmMjx7cpJ5FQbsZi2RlMQXuqDJxgMHRzg+HuLO6xbhMKkxqpWE4kmiiTSJbAGn2YBWJUcE0qkU2VyeJ0966fXE+ey6Zl4c9PDQ4bPkEciKcmKpLDPxDJ9YWc3W+dXkBAX+ovvvt584SSCaoICAUqnGqlNyy2UdTPjDWHRKOqqtyGWSS+cjR8b43UvDGDMpbJkExnAQddDPFics1OXQhEMkJ6eZGDhHRSaKJjiDIjCDrPB67m9eocCvLUN0OtFUuBAdDiJGMxmrjYLDxeG4kk3r5vG8N8ufzsT5+OaFVFsN7B30MeyJ0O7QcsmccurLzSW8Qi4rcamUSiUKhVQ0yufzxBMppkJJ7GYjgXia3x0c4+lj59g0p5yrF9fyraf7CMSyaJQCoWic71/dTVu1jWdPuzk1GabBpmZlo5VUHhqdZdiNanzRFN9/uoddfV4EparkEBhLpLmoycKnN7Rh0mt44vgU9+8ZQSfPo1HIEJRqBEHgvUtruLq7gslAjB+9MMJVC+twGNWS+t0dZF5VGRu6anCZJPe9cX+UPX1upiJp6hxlpUZYLpNmIpDgX3aPMhmS1hkxn6POquYbl8/FbNCV8iIxl3nbteTlM0G66uzolHIOjMww7gtRZdaybk4l1TY906EUtz11iomZKIJMhiBXlvIeh05WGvV7q/E9jUZT2uvvPjXBWCBOvbOMNe0SU3V2HF2rUpTG9/5ec6h3lVJ/5/FOHexqixZX2TvDOZVyCSh99cJq1ne4ODeTkNzF5AIXNNm55dEeQknpxnlwVHIj+MqmdvYP+2hyGHn2tJu17U5+vneE5/u8/Oz9Czk2HmLIG0U+C9Xm9eOEArCy2U6ZViW5SzVYeb7Xw6HRGTZ0uNg3JI2vRJNZSeJbKHDWn2R3v5dLOl2oFTLcYckNa8gbw6BWoNBJGzRRFElkcox4Y6xqlboow74Ym+aW0+jQo1fL+dF75lNp1uKLpXmh38tU2Ms1CyXA7p4BH6enwlSUScqf9nIj/7ZnhEyugD+WxqBRUCiIWHQqfn7jIoa9MUxaJXfu6MdddPBLpPM8fszI96/tQqeSs6Wrkpm45OL2XJ+b50570KvkfPPyOaRyIk1OQ3HzJWN+jYU/HDonOQ0CMkCtlOChE8Ek7RVG3rO4lk1zyvFEUpg0SlxlGnRKOZVmDTddUMcLAz4OnZmhyqxlaYOV266cS0EsUGPRIQgCRrUChVyQXHKKLJ9bLutg1B9nXlUZ23qmCSUyrG1z8nyvh39Y2UC9TdrMTgSTfHptM3sHfUyHklyzsJq17Q6sejWh4obYblDxyKsTXDqvnEqzlrGZRMn2NpMrEE1KFrfnAhIraNZqW6uUkczI8EbStLqM3H/jImKpbFHCq0QmSB3ZY+eCPHfKTV4UGfHFGZiOcOuWOchlsKvPiy+WpkyrKnbeBMKJLGatkjqbDlGEeDpPV3UZ939gIfmCyKoWOy8XweXnggnS2QJNDgOL66386fA5Lu+uRKOU4Q2n+e1LZ4in87w8MsPeQS9fuLiNaxZW82yvm44Ko7TwIPGIdvdLo10Kuayk5AvEM2w7Oc3qNgdVFh2/uGkxmVyB7zzVy0w8gwAoZDPsG/LxzxtaiaYkEOHB0RlOjIf4+uZOrAYVmXyBdK6AXBAIJ7OYtEoC8TQLasxs7JSKh3q1HF8kjSCTOnTvXVLL6lYHwXiaZqeBIU8Uq17FZDBJqjh6JggUu+Ew6o2jkMkoLwJ+Gx0GXhyUwLy1Vh3rO1x8ck0zx8dCHBjx01Fh4ntP93Jxp4sVTVKXyqZXs7TRyn98eCmBeAaHUc29181nV78Hp0FDZ4WJu57pxxtJE4xncEdSPHPKzb3XdXNuJoEvkubOrfNQFlVJgXgGl0mNTBAIJdKcncmyd8DHJXPKeejoBFadkvFgglyhgMMoAeOTxbE7pVyGUa2k0WFgwB3lF/tGcRjVIEKHy0hHVRnf2NzJs6fd9EyGaXEaWFMskAXiGXQqOQ6jhtNTYbzRNNtOTLNxbjlPn5wikysgEwSqzFpsehVyuYAoity4vBa5TFLwpbN5Dp8JsL7dRYvLyNp2BxqFnGgRNnnVgqrS/fylYR8ymaSYWNXqYEWTjbmVZTzy6gTDvhhGjQIRGbFUDk8kxc5eN9csrCaeyjHkjXHpvAqsOhXm4piiUaPkW0+eZktXJevbnWzocBFKZItFUF3pZ78x0tk87kiKF/q9TIeTrGp1lDhw+YKkmBOQoOmpbKGkSqy2aElm86Wu+sdXN+Esjuk9fmySf97QiihK3wdd0RUyWyjwzS2d1Nn0PHPaXVLZbprrQqOUlzqHE8FkSUU2G++C0v9nhEqlYtGiRezatatUlCoUCuzatYtPf/rTb/katVr9OlbHbGi12lJBCkCpVKJUvhkWq9W+WW3ui+e4d/eZUs4VjGd46KiKO7bOY+2casKpPDVWHa+OhVDKBWxmA6PHPQTjGcw6JeVlGmIpqYHmj2ZptBvIFwoEE1nWz6th/7kIoXgWvVriQNbYLayfW8PeAR/XLapmTkUZMhmk0gV6x8KEkwE6K0yU6ZT88qVxHn51QlqLRFDIBXIFOBPKcYPTTJ87gkGj4DtXzKFMp2IimMAbz9JebsQTSfOVR07ii6ax6lWIBZGeEyN8qU3NR30nMbgnWXzyAcaP9bLGN40rMI22yHJqAES9nnhlDRNlTipWrEJ5YwMvpHT8YqzAlNlFVG9CqZBTbtKwdUEVnZUmDj55GqVcQFmQ8dKwn81dlTx4ZJxhX4xmh6QSL4giS+otPGjQMhFMUGPRUK2S3Kcu7iwnlMzyw91nmAimCCUyBBIZdpzS88Pr51Np0tLiMvLsaY9UaJKpUMgEDBolFWUa0rkC5WYDw4EsG+ZU8cq5CGdm4gTj0uTA/FozG+dW8uKgF61STiSdI5oq0OqScmmDRkGtVctkSEArQHeNmUvnVtBWbiSdzbN+Xg3HpuIU/HFiaUkd0lBu5eKuWg6PznB5dyXucJLHT3jICUo6q63IBIGvPXoSgC9e0sZXt3Szb8gnGdyUaVjZbKfBaWA6nOJrj5xkyCcZ5miVMpoqLKg0WXb3eVneZGP/kJ/xcA5RriSVTVMQYdATY/+ZMMsanBwZC7GwCMPf2QvHxsLce303Bj386L0L2d3vYSyQpNVlYG2bk2gqy4NHJlApZNywrJ46l5lD41HKtEpkgsS+LADtlWZ0SkmlVqZXkZcpcJpVrGtX0jsZ5sRkmIwoR5DL+ejqZvRqBV968DhT4TQ2g6RO3roozYYOF0+fmCqxsAQBWux61ne4EBDY1jvDtpNTOE0aBtxR5teauePZQTbPq2Rdu5PNZRq0SjkOo5pwIsvVSw1oVQoePjpOpUXLJfOq2DvoZcdAoDTJYNGrMJv0fOOqejL5AvFUjmgqxz3PDjCnwsRVC6qIZ3I8fXKa6bBkRrC61cF1S+skx2uzhvWdFRw6E+TIuRDRtJTbtboMbFlQj1qj4OY/HeNLG9t59rSbo2MRVAoZ1RYtuUKBUDJX5ItWEUpkmInnKNNKqu6zgRR5uZqEQUMwZ0JrryJfEFm4spHueeUkBUFq4GbzPNMnXbNzyw04c3HyHi+pSTd5twdNcIbE2BTmWJDg2UlkA6OUxYIYoyHkwQBtAHfAe5H+S31HQ9pqo9HlQnA4yNkcGGoqiJZZOZ1RM6E0YKipZOHiNhxN1VAsSsnlckxGPeGswDOnp5lXZebVsSCpgpxdQwHWzqni7mu6OXouSL87itNYTUulFYVcoL3CyKoWB6FklkNnA+wd9LF1QVVRna+krdrGrqGQtKeRCUyFUhREkRqXmTOBNCd7PFzeVckzPdP0uaNUlKlRyaT3eXWrE51WTX25kq9cNpeXhv1kcgWu6K7EckE9eVHklTMB3EXH6LufG2IyJN3rDp2LvM6Zr75czR1XdxFOZJEV8+0ynbLo4ndek0/55rXEH8/xgxfO0llhQgA+98BxJoIJKsq0qBQxXpmI8fXL/j/2/jtMruu60offWznnqq7OOQPdyCBIEIEkmBAIBjEoWs6yNGOPNJZEBSrYSpQ9tmxFe0bWSFZkDiDBiMAEgogd0DmnyjnH749TKJKyJHs8nu9nP+Z5niaaJLq7quvWPfvsvda7enGbNXzm4LpfeZb/VYNEhUJRbQzCm2f9u3a0UyyVq+reh8+tsBBMvqk4V5b+XSvO32lK/QdY7l/TeKqpXKyX4Zy/ib9xufj54WvzLIfTfOrmXo5P+KpvjsuyxMVQiucueVlXb66m762PZ2lzGihd8uIwqqv2EHiTtVQql4mm8zTbdAw2mqk1aXn2kodQQgCS79oqVEhOg4pXpwPkiiXS+SJ1ehXhVJ5Cqcy0P84HLM1k8iWyhSIGtZI6i4ZpfwK1XEa9VUuhWMagVtDm0hNJ5ZBL0OkykM0XuXl9LXKZRJ1Viy+W5d7KZi7k2yW+/swEK5E0oUQObzzLk0Me7r9jgK0tVl6fC9Fo1eGPZ/hfL8/RXWPk2t4aNjRaWImkufemHoKJLE+PrHFkaI25YJJj4z7u2trIA2eWePTCaiXyvsxaVCh2nrvkZVOzlW88P8mnb+4lVyrSYNETS+dxmdTkCqWKvUvFf7mmE6texRMX1xhajtBba+KaHhfJbIEfvjpPX51ItVmLpggls+zscGA3qEnni1zRZkepkNjb4+KlqUA1uj6dL9Jk01Eol1Ah0WTTkSsUGVuNcnpOFLnfee9mktkCn3hoCG9MRMNm8iVGV6N8/MYeakwaXhj3MuNL0u7Sc9M6N3UWHX/3gc3UmYU09MFzS8z6BLdKpZDR4tChUcppqUhxS2UhCzdrlWhVCrrdYpryP1+a5Q92taNWyDk64mEhJCxhV7TZqbdq+fJTY0TTWeKZPMcnfNy+uQF/PIOERDiVo8Nl4OxCGKtehUwS6p90rohNr8QXz1IolskUCth0aj61X7x/pv3CinhFm2BmbW2xopLLSOeKdLuN/NaVLRwZ9lAul/HEshyb8LGp2crwilCmpHIFdCoF+WKJ80sRJElI01O5onj+chmzgSQ3rnNzbMLHuzY38sDZJbyxDIlsgWS2SJ1Fw+hqjGPjXnZ3Ozk+4SdbKDK6GuPEhLim5gIpXhj3MhdI0mLXcU2PiIjWKHOYNQo0KjmLoRQvVOKcW516ruutodmuh3KZWouWkeUooWSOeqtWNEekQvXakIBWp55iSTQNlQoZX3ryEm/Mh8mXhCT+sQsr/MWdG+itNRFN51HIJf5gV1vVejrrTzDYYOH6dW5yhTIXl0PcvL6WWrOG/etrcRrUPHphtdpgMGgU6DLicR+f8LGlxcqPTy3yZ4fXoZTLCCdzWPVCwVBGhCuAkP3v66vBoVdh1impMWkIJXNc01PD+cUIsXSeaFncg/rqTOxos/OjUwsoZDJyhRLX9LjQaRT88U/P87XbB7iizc6OdjvBRI6Tk35RSA7UVRMIdSo5t29qwBPLEEhk+fPD6zk9F8QXy1Jj1giemEHFaiTNkeE1EpkCN65zYzeoOThQi0xWRzCR5dRsiFAiy85OJ2WELLxYKuM0qvn0/j5envbT4zahU8l5ZTpIrVnLhCeORadCr5KzodHCri4nDoM4cBdLZdwmDT1uEy9NBfizJ0e5rs/N7+9q47o+N0dHROrOQ+eWUcllbGu18bmD/b8x+tcTy/D5x0cZraQlPnJ+lQ/taWdvt4v/8dwEf7CrnXyxxI9OLTPljYtmW7eLpVAKm17Fri4HxZKwAv3pgxeZCyQxa5Xc0C9+HyatEk9UFHp3bG6gyabnkw8NEc8WcJs0bGuxsRrJcGY+zFo0Tb1Vy9YWG3+4u53vnpip2qVAsLwuJ7Ams4Vf84zeWf/R10c/+lE+8IEPsGXLFrZt28Zf//Vfk0wmq2l8/y9XvihShI8Or3F2IYxKLsOiU5IrlqpJVFtbbIK32e1iaCnCmCeOP54Vw6cJEUaQyhfRqxVYdDJ6ao2kcgX+x3OT1VroK7cO8Owlj2D5bW/iynYH6VyBG9bVoFEqePziKkPLERqsWvZ0u1Arsnzm0RH+8Xe30eo0iHqtLO6TMklCkkGTTYskgUmjpNdtYiGYorFU5q9++irJyWm+faWd1Buj/N7FMdwhD86gh9qIB91bmk4FnY6Iq4Gczs5w50aesd6Ix+rGb6/l6n1buPbKXs4vRzk27qXdoeeOrU2ce2ESv8ZDuVjCVklXzhfLjKwK5uVCMIVaIaPVoWeuEsbwUKWpdnEpwgtjXj5zoA8oc//tA5yc8uOLZel2G9jWakcukyphLYIdmMkLxfNcIMnRUQ/v2d7MocE6Ts0EmPaLQYteLafOrGFTs4Wfv7HAu7Y0EUxmkUkSn7y5hycvCr5ieyXyXSGXuLrTSSpf4tJqjFaHUDOnc0XsehWfvKmXV2eC9LiNGNQKXp0J8sKYh9s2NVBv0fHRfd28MhNgKZQSivlOJ3KZxA39bhLZAvc9NkK5DG1OA/v63FxYChOvxNd/89g0OzscbG+10eY0oJBJnFkIU2vW8MTQKmcXI5i1SkrlMgONFkwaJR9/cAhfPMuWVhujqzHWohlcJg0WnYpwMkcZmPImuL7PzWIoxfX9bux6leAXhlMcGVrj0IY6mu1a3ntFM7lCidVImvNLYZrtelodBn7v6lZ0Kjk72uw8ObRGJCVS0AwaBTUmNQcG6lDIJX702jxfvm09Pzq1wM3ramm06vjMgX5eGPeyGEzRYNNyy4Z6Hjm3wpg3zj1bm9nX58KkVVIolqgza/n6uwZ5YczLtD9Jh1PP3h4XFp2S//HcBD9/YwmtSl6xOGnxx7KkcyUePrfCy9MB1AoZm5tt/O7OVk7Phzg0KAYw4VSep0c87O12sbXFJpqbqRyT3gRXttsZaLCImr0M6UKJl6cCHBqsq9Y7n3hoiLWoqIlVChnPjXr5wi391Jo1eKJZkrkCn7ipl+cueRldjVWwKE5MWiWPnl9hNZrBqlMy7UsItVWhRCJbwKYTw7RQModcJvE/X5qjw2Xg5vW16FQiSVomQTJXJJEtYNIq+eh1HTTZdTx0dpnVaIbGSoPh0GCdQDJIEqsRGU+G4swkXLS2tPKeu5qQ54t87PFRLnXFyBVFkEx/nYnP3tDJq6+N0ylLszA+z6uvjVGTidFUSGBNRTF7IvQHgpRffwWNx8fOTPKf3izNZnC5xIfTSZ3TySGTjYzVzt/Z7Fywq1hSGkksreKu7+HwhjoKpTLBZA6DRsE3j01xajYkrMxvGR4shlLkioJdd3CgjldnAgTiuUrIT7n6nn1x3MfjF1fY11vD1+4YrKoJf50w4/DG+krATYknh1Z59Pwq2UKJT93cyxNDq8wFUtXESXj7IEwuk0hmi7w0Le5DDVYte7tdvzERD97OhH7/jpYqoxQgns1jlatYDqc5Ufk5/5Kz/D+3Ln/NP1WcB9/WaPv3ut5pSv0HWP+SxtO/5OJ9a3OrzqLBF88KH7v87VCFaV+cXV0OFDIZH97TjlIhZ129GZkEoYSIHZUkr7CoaRQUS6Ih5Y1luLFfTLW+8rRIdSuX4dRckFOzAn5t1atEClNRxIrmKhwYuQSbmqxISDxwZomhlSiHBuu4aV0tr84EeW0mSDxTwKhR0GwXN6Vj4z6u663hto31uExq0vkSq5EMTqOaxy6ucG4pAsAVrTaeH/OyEkmTyReF/zidZz6Y5KUpP/v63KxG0lzRZufp4TUuLEYYX4vT4TJQKpd5esTD+FqMdpeBd21pZGuLjc89PsqMP4lSLmPKl6BYFgf9eKZAJl9ELhMphDf0i6LglZkAt25sQCGTaHHosevVUNkQd7TZcRjUfK4ScypJMLwS5fELq/zZ4XXUWrT8/I0lXhjz8hfvGsSqU/P0SKWocho4OFBHo02HUi/jw3s7ODUXxB/LVqOmC8US0Xyeex8e5tP7e6m1aFmNZvj0o8P84+9s59VK2p1Vr6o2fG7od+MwqPnEQ0OMe+LVa+P12SD33zFIJlviyaE1blpXw9/evYnZQAKnUYNNr0JbuRb3dgvO0XI4xc4OJ9f0uHAa1Vh0Kk7NCqVXoVTmv/7sPMmsaJj441kevbDClw6vZ2eHgwfPLQNwYTnCoQ11bG218eiFVc4vhrllQx2XVmOMrcXIFYWSpb/OxL4+Nz96bZ4z82G+/8GtBBM5ViNpNjdb2dvtQq2Uo1HKyORLpPMFgskcsUyeWpOW39nZxr6+GkLJPGcWQiSyBdocer5wSz9mreAk5IslAgnBQxKH+bzIuiuLxkGny0CwAi0vlEqcXQizFn0zOUghl6FXSURSeTpdRq7qcPDM6Bp6tQK3WUsgmeNPH7jIlD9RVY89e8nLX9+1EatOSa5Yxh/P8PEHh5gLJimVIF8q8dSwh2++eyONVh01Jjmf3t/HcjjFri4nr80EOT0XIlsoUS6X6XIbuabHVeUgvDIVYMwTJ1MoUqowMeaDKV4c83JgsI519WYKpTJNdr2wngaSUIbXZoKcmQ/xR9d0YFQrmA8kaXPocRmFJHrOn8Aby6CSyzDrlNRbtUTTeRZDae6o2OxATEfrrFpCyZxgf+mUmLQKElk5bU4D0bRQFTRatVzV4eDI0BrtTgOfPdDHqzNCZdZs13FoQx3eaJanhtewVRre21rtvDDmY3Q1xlwgyam5IH93chYJiffvaMZt1vLRX1wglRNpMLP+ZFXNdXLSTyJb4MBALY02XZXV9u6/P8XQimATuIxqXpsN8c13bySUyvMnPz/PfOBNS8uRkTX++s6NZPIl3pgL0VdrxGXScOvGBryxDJ97fJSh5ShNNh0Oo5pIKsef3rAel1HNi+PCijfYYGFfXw3FchlDSdgIt7XZqTVrUCtl1Ku1fOOejbw45mMlnKbbbWRvj+ttcfa/vFLZAi+O+zi/FObG/lr29QmFl1mjIJEt8MfXdiKTyfj4gxc5sxAW1+4lL89WuG2+eJYtzTayhRIvjvuqaaRymVRNNLymx8WzlzzM+VPs7XZybMLHajRDnVkUdU6jmo8/OFRV6wI8PbzGJ2/qZXeXk2cveQHBJju8sR5vPMuJCT/TK75/dr97Z/3HXHfddRd+v5/77rsPj8fDhg0bOHr06D+Bn/+/WJ4Km250LUYyWyRJEa3qcgJfsZpEdWzCR5tTz30H+3l6ZA1fLMv+9bWMrESZ9idYiaSpM2vprdUx0GDhb16c5omLa0gSPDPi4ae/fwU7OxxIkrC7m7RKEpkCyVyRP3tilNG1GL5YFpVCxrOXvHz1tgG2tVoZr4TRPHphmYm1BBJl7Pkk28sRDk0HKL30AONHX6cu4mVDPoJ6ZZHvX7bX/T0YNVqcFjcLJhevNq1nZf11rFhcNG/q43feu5ec2cr3Ts7y2kyQcCqPvpI+WCqXMaYUbMkUGFqOcNfWJmrNGlYiojmtVyswVdKHJUkinsnR6TISS+fpdhsRJaZEjUmDP5GtJBVLhJM5Iqk8Z+bFfh5K5rhpnRulXHAuVyNpCqUyY2sxfBV1l1opJ1VpTM36k4SSWXKFEl+9XaiNFoMp6qxaNjdbWQikCCSEwvsrT43zwStbKFSGF7u7ncQzBY5P+Hjswgr33tzL4Q11XNluxxvL8sDZJTL5Er93dRsGtYJbN9bjj2e57/ERxtbi3NBfQ7ZQ5oP/cJqru5zs7HBwXW8NmgpmogzEs0Jt019v5tCGeq7udOI2q1HKJL5e2V8ev7DCg2eXeWbUw452gbfQVviFU14RbmHQiKTX3V0ujk34mPQmcBpU+GJZWh06nh0tkajUx6GksBBdZo7WW8TQ+c4tjRwZXqNYKjMbEIPlQolqzfU3L0yjUcr40uH1fPu9m8jkinziwSHet6OZzx7o5cSEn/lgig2Nluq9+3+dnOGWDfW4jGpqTVo+++gIn7+ln0araAzIJWH7VsokfPEMXzq8nlaHnhOTfmZ8SdqcOm4ZrKfVIQaecplAI5i1Kqa8MZ4d9WKvsM8arVqu7a3hwbNL6FWKakjMWiSDa52alUiaJ4fWGFmJ8pn9/Vzd6eTkpJ8nh9Z4+PwKcgnkchnv3d5EqVTm1ekAN62v5eSkn/fvaKHGpMZt1pDKFXh5OkCiklAcz+Qxa5UsR9I8d8nLu7Y08KcPXmTCG+fzB/u5dWM9u7qchJJZnrvk5cBAHbP+JKZK+mR7JRBJKZcoFMuUyhBMiHOKBNyzvYlsvkihWEKjVHH75nqOT/p4fS6E0yD4pG6LlvuPjosGr1KOTJLe1mBYCCb50hExVEzkRHjCle12xtZijHviRNLC0prKwetzIY7PhrliRx9HRzzsefdGvq/t4Cn/P8Wx/KyCY1HlspgTEcyJMOZEhOsdElv1BZTBAPj94PMhP3cOk8+H0edDymapf8t9tSxJxPVmsDuocdegqXNzt6SjNSEnabYTN1qIGK1EDVY6uk3IK5yyequWr90+yIlfws/44llemvKjUyl4cmiN/3ptB3dubfwn5+NfDksRyqE1fnFmufrYLjcOLzeJZL/UICtW+J+/jBR4bSb4zzZ43sqEvizyuLxybxm4vTXh+N9CCf6bAtIuN9r+va53mlL/gdb/7cX6y82tbreRoeXoP/l7HS4jBrWSeDbPq9NBhpYj9NeZuWVDPUq5DJdZw5n5EKFkDplMYiEoUjkcRhVqlZyXhlYZWYmRLRQxaZTcsrGOHW32Knjx1k31XFyKMBNIkMiUMGmUDDaYubanhscvrvB3L80STed5YUwcxP/slnU8Myqmij1uYyVKV8GhwVo+cGULZcrMBVKsRtIMNFjI5IuMr8XJFUuYNApanQaOT/qRELDvcrlMk01HIltgJZzmjk06PnZ9Nxa9kla7AbVSxJjrVAq+8PgoY544nmhGFJSjHr586/oqzydbEFawMwthFBU7o4RUmYrpiaYFRNRU6aiXEVDqZ0Y9TFesiVd3OTk55SecyqOQCZheJJNnLpHkxXEfm5utPDW8xvoGC6Fkjq8/M4HbrOG2jQ1CspzJY88V0KvlGDUKruupwVxh1Tx3yYvbrOaN+TDBZI4z82H29Dh5eniNaX+SQqnMfFD8mcwK+OeJCT+/t6uNn5xeeDMyGNAoZAQqSYj719fy2cdGeG06wP3vGkAhlzg+4a9OCnd3OWm06rhvfx+ZQoliucxLk348McGX2tpiY3OzlYfPLTPhEdJwq16FRilnypvg2ISPvT0uHjy3LLg6Vi3BRI4tzTa+/1tbBUBWp+JPruvixQkvU17BZbqutwZThV/TX28mlMjxlafHeH02JOTvKhktdj2fO9jPlE/EFne4hGzdExVKjOHlKKvRDHu7XRjUAgS6HE7z1LCHG/prMKgVDC9Hq5PyWGXDl6AaIvDg2WXanXryhRJtTgEvLZcFM6tcLpPIFrAb1ISTWW7ZUMcVbTa+/NQYvbVGjo35mAsmkUuQL5WRKDPrT/JCJfJXKxMqpglvHKVcJhhmMpGc+MKYj/duF5Yyk1bBoMECwH0H+zg+4WPck6DJphUgeYOK12aCXNUp0oXSuSKF4pvk1lJR2CcVMgmLXsVqhU331o1VqZARSeex6dRYtCqOTfg4MrRGo03Hzk4Ht29p4KHzywQTOcIp0cgzqhWsqzdVi4RgIovbrOXQYB1dNUYev7jK4xdXcBo0bG+zc/P6Wqa9ce7a2si+vhoyuSJHhtb4k2s7sRtU3Lapnls31lOoMBVeHPNh0wsLZCQlLIXTvgRKuYzTc0Lh8PyYlzm/YEscm/BVJ2zZfIkyMB9McnzCx0CDhT/68Tn0agVbmq3IJIlLazFWIhkBcq+kKo6vxYhnCrw2E2ClUghIEjj0Kq7tEXHKaoWMKzvsnFsI892TM3z8xh6Ojfu4tBojnMpVI50VMgmXUc29Dw0z4Y2jUsiY9MZ5YczLFw+vQ6uScdfWRkrlMpFUnsfOrYAE1/TU8J7tTchk0q9kNf3ykslgW4uNp/94F3JJqtqBEtlC1Yr5/JiPWX+SCr+3ehA8Mennut4aFDLIFErM+EVDSq2QYVArODriYV29mcFGC39950ZeHPfR6jTwwpiPusogZEvLm+mGevWbQOVQMs/L0362tNg4Melnd5eTAwO1WPQq5gNJIqkcFxYj/5It7531H3R95CMf+bV2vf9X63Ih3+Ey0ObQV/97IiPUCslsoZqumS2U+PHri3zvfZu5od9NtlDCaVRz38F+TlTukR1OA1e020lmC1zfV8O7tzcRiIuD61okzRvzYf72xSn+6q4NnF0QjJPzSxEWw2kylftQsVRmxRPm4nOvcSdRVv7q5zSokvx0fIrs1AzG1SW06Tdj1Et6Pde4GxhRWpGu2UvI3cCQwsKM3sG+m7dzMlDiOydmq6qhfGWY85FtHYS1JuwqBU02PU8OrRFM5EhkBTYgkSlQY1KTLZTY2mJDp5KjkEvk8iV2djg5Mx8WgSYacaTorTWxr6+G5y55iKXzZPNFNjVbubrDyTOXPGTzJeQyCYtOKIAmvXEiqTxHhtfY3eVEKRf29XyxzIQnVmnW55FJkmjgVWqVdqceTyzLN1+c4m/u3siBgbrKgAouLEW4/5lx7jvYX0k9zlBj1vC9E7M8NbwGgMOgxqpXIpfJeHJojVqzlkPffAUJkR77X6/pYDmc5tJqlN+6soWFYJIP7GjBblBXlMDLXFyJ4q0EsoC4R96zrZFDG+oZW4nSW2tib48Ll1EoXh87v8roagy7QcUN/W663UY+/cgwsXSe9ooKrtttRKOUs7HJwtByBJVcRqhyjc34EoLzWirz/JiXu7c28twlL95Ytvr7b3cKa/obc0Gu63NzcSnMQIOFbx6bplyG/WolU744zTY9Zq2Sa3tqODLkYcaf4NOPDvPgH4pUs1gmz/98aY4rOxxsa7Gyr08kZlt1KjL5Iu+9sqXCnC1zdZdDpM6W4WMPXGQ1kiaazpPJl/j7929mT7cTg1rJJx8aYtqfqF5/pyqDTqdRQ6ks0AgAjVYdf7innaWKO2R7mx27XsmcP4nDqEJRUVc3WLVc0yOG1DJJYimc5uSUnwMDtbjNGmb8SWSSSO2rqyAvNCo5H7mmUwyYtjeTL5bY1GQllsnjMIh6IZDIoa7wVEtlgZ/wRDMUS2X+aE8HNr2KUDLLQiiFXJIYXomRygqu0UCDhXFPjBfGfdyyoZ5nRz0sBFMCeVIs4jCo2NZq47GLK1zbU8OMP8E3XphmXb2JG/rdfOPujTx4ZolAIsfhjfW8NOlnIZSu2q4u8y1PTvo5vLGeZ0a9rEYzuM0a8TsvCEv/hDeBWimrDhrzRaGCH/fEuWldLT9+fYHeWhNfvnU9Jyb9rIRTrKs3s6fbhUImqzZUcio1flsNfpsYDKjb7Qxe24nyV6iwpXIZEgnw+cDnI7PqYXJ4Bks8giEWIufzUfD4aY0EqV3xYEpEkJeKb36DLyGsgU4nSpeLJpeLe2x2MjYHQZ2ZiSNaToTKmNQmEiYrDX02SqUyurc8ll8XluIwqPFE396oCafytDn0vDIdoFyGEuVqY6rRphVJncUSfbWmqup/d5eTLS22ioKq8GvV6G9NI778cy6vt6qy/rmE4//T9ZsC0t7aAPv3uN5pSv0nXJqqksXFazPBaje1VC7TaNVyQ78buUzivz9wkXimgEImcWo2xMlJH392eD1tDgNfvX2AExN+Jjxxbuh3s6vTiVWrIl8QtiZvPINeJeePr+ukpZJw9uj5VfrrTezpcvK1OwbwxzIMr0aJpPLs6nKSyRd5aliwU7a12nAY1ETTOUrlMu/b0UK+WCKczDGyEiOSzrGz3UE6XyCQEByH9fVmNEoZgUSWrhoDF5c03HegT6R1mLX44msoZDLMWoWAwyll9NWZUMglfv7GEucXw3z2QD97ul1sarLy4oSPcW+8Mn0SVqApb4ITk372D9SiUcgZXY1yfX8NL4yJFDq1QoZcp6S31sShwToKhTJ/dss61Ao5j5xfYXg5wgeubOHPblnHi+M+Lq3FaHMYOD7hE5OUktjU05U4+ylvnGt6XHiiGa5st3Ni0sedWxpwGDUcf0t6n0mjoFxWcXo+xJXtDlQKMd2st2ipt2p59pIPh0HN82NeWhw6vnr7ACcn/Rg1Clodeh45tyJYAeUyPz+zyG/vbCGaymPTq0hmC2iUouGVK5YYX4tz+6YGPr2/l8EGC8Fkjs8+OsLwioCim7VKzsyH+NTNvVj0KoLJLPcfGWc1Iixs/niWFoeOb79nU0UxRkWCLGxA1/XWcE2PS8R1v3sTQytR9vY4GV2NsqnZyi/eWOI925s4MrxGOJljW6uNa7pdeGJZfnFmiRqTmt1dLgCeH/OyWmkg5IslLAolK5E0j19cpb/OxHOXvDwz6uHp4TW+evsAq7E0V3U6+PuTs2QKRdpdevLFMkdHPNWvabGLhuZiKMknburh9FyIC4sRmuw6rukRjKLhlQgfvKqFfKnELYP1jKzEWAwlkUsSy5UGyI42Oz98bYFzS2G+dHg9t26qx6pTMRtIijQahQy5RBUwvRxOUy6L6mIlnK4qs+QyCZkECpnEUihFsVyGUolvHZ/m965uo1QCrVLO7ZsbUcjEdLRcLiNJEvVWLRJQb9G+bZO8bA1pc+opVRL7GqxaYpk8Vp2KaDqHQi7DaRAHsWKpxL0PDzPmiaNTyTGoFZyY9PGZ/X38zlVtfPvEDKUKZL6v1sSOdjvZQlEowxJZHjy7zEIwSYtDz29f1cJdWxoZWomwu8tJjUlDrVnzZrKSDn7xhzuQyYSFJZMvksqJiZjLqGZfXw2vzQp1ZbksJsHdbiNTPtHs7K01VouwJrueZ0e9NNl0SEgoFTL0KjnFcplpX4K9Pa5qqt6JSR/X9bqZ8gm+h1wm4TCo2NPtYkuLFa1SzrY2Ox+8qpUnLq6iUcr44+u6cBnVPDWyRigpEoyu7nRwVbuDZEY0Jv/qrg0YNQoCiSyUy7xnexMPnVvBn8jiNKqr77vh1SgvTflxmxr45rEZLDoluzqdtDoNfPfEDOcWI/9iaXa+WMIXy/LabBBvLMP7d7RQKJV54uIKU94krU4dhzfU01drwqhREE3nhRq08hrM+BPcsbkBtUJGMJmjr9bE2flwFWgeS+f41rFpPnljD4ONFt63o5ky0F1rZGglKqLM3zI5fOu1p5SLxlSLXcdnDvShU8p5aSrAhCeOy6RmT7eLJqPE4//aDfCd9c76FetyIR9J5dhzOanJnySeLWDQKNjWauPGdW6mvQnu2dbIthY7S6E0OpWMYCIrFLTxLLu7nRzaUC84SnKJhUCKY0sRpn0J2ipqa7lMJCM/PbyKSSUnMDZDc7TMyrNv8N65OVz+FZyBVRojXtyJYPUxdssV0NKMtrkF6aodpJruJtzUjKy1jbMyK98aCvHnt64nGE7hbbTwxcdHGVmNkY2V8E8neff2Zh4fWiOUzCFVAllaHUJ9cH4pwg19NezsdPDA2SWi6TyFUolYukB3xeKsVsh49pKHGX+SdXUmbuyvwWnS8LlD/Zyc8LMUfhMvYdKKwdjGRgsdLgOHNtSTzhd4dtRTrXXkMonVcAaXUc18MMl3T8zw4riPb9y9Aa1CzpHhNfzxLHduaeTZUQ9LoTRalZxaswa7XiSLroTTfPKmXl6bDfKDV+b43KF1hJNZtEoRxOEyqXlhTAycIqkczXYBJkYSdZappECSYKDBjEIm8ffv34LTqCaVLdBg0/L9l+eIZQoo5OJ7PTXsYcaX4JM39RCIi6aISi6jUCwRqyjlL63FOTBYZkurjff/r9N0u43cuaWRTz8yTKks1DKLoRRPDXv4+h0D3LKhnjfmw+xos+MyqQmn8sz6E2xtsXF0ZI1YRgSeBBNZutxGJrxx4pkCR4ZW2dXp4Cu3DfB6RSF/++YGdnY4gDI39LsJp3I8NbzGB65spVAq0+4wsKvLySPnl+mrNXFwsI4Gq5ZvvXsjJyZ9OAwa6i1a1qLpiu2syIvjXl6dDvBHezuQJImjIx7emA/R6jSwr7eGFrsOm07FLRvqefj8CivhNJ5ohlxR1JSPnl/hY9d385PTi8wFxT2/XBYpgtF0gZOTfq7rq8EbzWAzqNHL5dgMKgYbRB29Fs3wizOLDNZb+dDeDs4uhPDHs1h0Kq5qt+ONZXh+zFttiq2EU2iUMu6/Y4B0rkggkcMby+A0qVHJZcwHkpxfijAXSGLTq9i/vpY6s5ZIOse4J47DqK4OG2OZfJXX2u7UI5MkLiyFmfKKIJ5rekQS7o42O812HRqljGt6XZyaDXBuIcy2Vhv33zHAS5MBwcw0a9jeasMby/LIuRVS2SLr6s08e8nDqzMBTs+HuPemXt63o6WaAjfjT1Svm2gyT65YqqIiSuUyi8EExVKZVE4oO00aBZF0jgarBrkkFIylsuC+lqH6fG7oF5ZBl1HNnZWB2OVE8ky+SINVR6kcqN5/LjdrfmMTRZLAaBQf7e2QL6K5KsUjI2vMVpT0e3tcWHUq0vkiR2b8+Je8tJdTbNcXsaaiqEKBalMLvx+FZw31+QvYVte4LhHjet7SVPkLKGs0b1oJXS5yJitjMRl5pRG10cqMwcJynZv3H97G1U1GTk69+ZzemA+yp3IWDiZzpHJFzFqFaGC22EV4VCjJri4nfXUmJAnsegFMf/T8Mv31ZvZ2u34l++mtTOgz86HqvrIUSmFUC0bbb0o4/teutzbDfnldfu2K//TL/l2sd5pS/0lXphIXfu9NvZyc8jEXSOE2adjZ6cCoUfDk0CrZfIl0rohBrcCmVxFM5jg24eOKNjsPnFniQ3s6uKrTgSea5umRNX5nZyvBRJYmmw6lTMYtG+pprth9lkJpmu06LiyFeWp4jfsO9BFK5RhosKBSyNCrFHzvxDQfvKoFt1nLi2Ne5gIp2l162l0Ggoksn3xwiFBKHIYNajlbmqwgyTm3EGY2kKTOrOWGdW5cRjWHBuuwaFXUmDX86LV59nS7eHHciz+RQ1aRFNv0agYbLPzo1CJPj3gIp3IcnxDwSJNGiTeaQa8SgL1Wh550vkg8k8cfy9LjNpLKFmm0aVHIZXzv/ZsZX4vz0pQfl0nDjjY73miWZC5Pq8PAV58eY9KbYCGY4sjIGn+4u513b2vm4EAdOrWcZrue12ZDKGQShVKpyurqrDESz+RxmTRYdSpcRg01Zg0f+8XF6uQlP7zG8Qk/f3XXIL5Yhk89PMR9B/urUySrXkWLXccbc0GCyTx/d3KWG/rdbGmx4TKqubLdwc8si0z7E5i1KsxaBWvRDM12PVadEr1aWDRjmQLhZI7+OhOlcpmh5Sg2vYqXJgNiCmnSiISOUpn5YIrnxry8a3MjL4z5KswckRBRKgvlz7FxPzs77BRLZZRyGSq5jI9c04nLqObUbJDHL6xSY9JwaLAOhUzGUDrKpDfOE0OrvGtLAxeWIkx7xZR4Y5MVp1EtGnixDC6TaHbF0lo+f7APo1ZJNJXn/GKYR84LldHubqeYHAET3gQvVuygJo2S/3ptJ49fXOPFMR8uo5qru5z01pl4ZTpAg7WRqzocfP3oOJOeOO/e3sShwTqCyRzjHmG7+MKhdRg1ClKZAplCkY/u6+LVmQCeaIb6ilJsLZbhpSk/8UyRN+ZDvO+KZgqlskhIUshEo04mUSyUUSlldLuN5IuCQ9Zba6LFoadQFHHFQuVSpq/WRCZfQqOUoVcqkEkSwVSWQqlEraQhni3w7KiXWb+wfl7f70atlHN1p4MTk35enQlWZcXtTlFwGTWiybit1c4HdrRw99YmQknBTFLLZdQY1fzkjUXOL0WqRWw0nadULnNi0s97rhANiWlfgv56EwfW12JQKxhdjeIwavji46MEkuJ9eWo2xMtTAT57oI+b19cKOwgSy+EkZ+bDLEfS1Jk1XNnuIJUrMLQcZVurTVhAFkLs7nLS6tDz2QN9nJwUSYpapYxbNtQJBVwkzV8+N8muTgH0dhhUdNQYeHkmgFyShBXOqiWRESmgBrWCv7lnI9l8Ea1Sjk2v4sN72lkarOX0XIget5FGm65qMa63aLlpvZvBRjOjK1GcBnW1ua9TyVmLZnhpys7Hb+xGq1bQVWMUkPFYhha7jl2dojgJJ7PCkpwTv8tktoBSLmMtmiGeLfL6XJBiqcyFpQif3d/Hd967CblM+mcZB5eXJ5rhy0+NsRBKsbPDQbZQ4t6HhxhaFg0jmSRxYTHCp/b3cmiwju+/Mk8qVxD8GiS6akQyUSiRQy5J7B+o5Y35sFCMZQtYdEph6bBoUSvlXMZQ7+l2cXLSz6XVGL7Kc1bIpWqBBsL+0+bQY9MLGO7lhD9vLEMyW+TZS14+dV3zr39y76x31r9iXS7kH7uw8jb1wIw/wbo6c7W2qLdokcskUrkC9x8d43MH1wESn31shDu3NAr14oVVas0aNjRa+drRcTyLXpSLCxBew1wI8S5bHuPaMj+amUXxx4sMVtIDO4CE1cGixc20pYbTzQOsWN1s2LWR1u0DyBsaODkT4pYNdZQQFhB/PMsb8yF++Mo80bSwo33gyhaeuLjKGwthktkCpTL86NQCH9jRwpdvXcfRUQ+zviRtFT6LL54lmS2wEEox60/ypVvXV1WM3TVGbl5fi1Yl57d/cJopbxKZDEZXIuztdhKIZ1kNp9nSYuOaXhdapRyNUs7oSoS+OjM72h0EE1mGliO0OPQY1AqRLiqXEUnlaXHo2Nvj4omLq1i0StK5Ii9NBTi8oZ6VcIpnR71c2W7jG3dvrAxRU7Q69Fzd6USvluOLZXjo7BJPDK2SK5Q5Menjmu4aZDIoFMsUiiW63UbOL4Y5MRHgxnVunh72CFZpReXTaNVy+6YGAgmxh78wlqarxojTqGZjo6U6NPji45c4txShWCpz26YGzDolGoXgHa2E0+SKJXLFEk6Diom1OG6zhu//1haCyRzPjnqJpvOYdUoKhRINVi3xTJ7XZoNiELO1EaVcRjxd4CtHxvDGM/zRng7uvbmX12dD+OICAXBosI5z82HeiIRQyGV898QMd25p5F2bG4W6rlhCJpcoFoXt6KtHx7m2R8Dk/8s1HezucjEfSPLg2WXev6O5igioMWl4344W/PEsoVQOi05FJJWvKoWuarfiMKj4wuOjhFM5pn0JSmU4OuLhm/dsFNZKhVATJbMi2EKSQIbEUyNr/Ld93URSwqadL5ZQyGRYdUoUcolOl5F0rsgL44JV2VNr4sBAHV01Js4uhPnjn58nmS3yM/kSv7uzjd++qgVJkgjEszw5tMazlzz4Ezmy+SJmrZLDG+vxxbIcn/AzH0zSaBVJsgqZwFN84qEh5DKJcFLUKReXItx3oA9vLMvTIx7u3NLI08NCOZbNl4hnCmxoNLOz08mDZ5f57olZ5DIwaZWkKjzSXCWd/NJalBabgT+9sYdXpgJcWIpg16u4Z3sThWKZCW+MY+M+Xhz3EUjkmPDE2dPjQpKE0ng1kualKT/X99eQy5eQgDqLDrkUYi2aqSrJkgh+aqFYZl+fm1dmQuSLJVaj4l7y8lSAWzbU8fpsqDLQFPe5VruO63qFevvWjcIq+MDZZTpcAgVi1okaQnDWHDw1vMqUL4FKLsOoUdLq0P0fNVEy+WKl6WshkMjxg1fnefaSl/vvGKDFruO2LU3kNjQQTuY474lj1avodhtRyGQo5G9a8Yr5ImvBFM8MLeOdXaFXnuEKQ5HUiofcmodBVRZFMEDB6yM5Ok7/moerEhH0b+Vh3Qf1wC80esIGC1GDlajRgqO7me801HKpoGFJYcDaXEdbXRtrE/P8w1CI1USBxy+u8r33biaZK/InPzvPfDCF3aBiZDX2G618doOKr9y2nkgyhyST+Ku7NnBqJvgr+Ve//Hv717KlflNA2uXXLpf+Dd/g/8P1TlPqP9nKF0usRTO8OOZjPpDgnu1N7F8v0uP88SzPX/JyfV8NF5YiyCSpYjcSze9UrsTFpQjbWmz89PQSOzscnF+K8Is3ltCpFXxoTzvnlyJc0yPsMXu6hf99xp+kxqRGkmA1mmHhMky9zsynHhnmS4fXY9LApmYbFp2KTzwoGi5lID9c4sp2O5dWY8wEkmTyRZrtOu470I9SIePjDw4x4xcpbBatknOLIT6zv486i5bDm+r5+eklHjm/zG2bG/jq7QM8d8nLTOVAvq+vBplM4vXZIKYKR2UmkOTmgVoMKgW9tSZeng6QyRerCiC9SUNPrRGVQk4omeexiysVW6GJ3V1OPnJNJxPeGA+dW+aJi6vcf8cgR4bXWAimKJWFIqBUgu8en0GvUnBosI6LSxG2ttgq8fJ50rkiRo0Ct0nD3h4nTw6t4YtlSGTzDDZaePziarUhdXn6sRpJc2zcz2CjhW8fn+HZSx62Ntv4+END/OWdg1zd6eTUTIBCqUy5TGUj9/KT37uCaDrHV24b4NximJVwmhqzBpdRza4uByen/Ex5E/jjWUrlMpuaLOzpdvHwuRWeuLjK7i4no6sxPBXpcDJXoFAsV3gQGQqlMivhtOB4pXLYDWriGSG9n/TGuWVDHX11JtK5IttabTiNKj772IjYyJDIFIo8N+blcwf7uHGdm2S2yGMf3olRo2BTk5Ub+93UmDTV66zdqeemdbXY9UrypTIahZwjw6tM+xJ0VSDNbU4DC8EkgXhWbNSSkDbP+BLcuaWRUDKHL5blh6/No1cpKJZKvDwt/PtDS2HOL0TY0WHnT2/s4eUpP/94apE93U563CbcXS788QxymQy5JJEvl4mn84SSeQYqsmiXUU0yV0Amgy/dup7X50L44sJOcWYxxNWdDl6edjC2FqumyvXVmdjb7aRYKnN+MczWFitHR9YIJnOUyiIdqrNGTECtelHYf/CqFhRyGQ6DiilvAr2qwId/fI4xT1xY/uQyjgyv8Y27N2LXq/jUzb28PB1gLiCiw/d2u3BUkgCTmQLL4RSvzQQZXonSaBOFjcsoLB0zFdA9ZTEBzRVFIbcQTJHOF9jaYuW6PsHbsOpVfOwXF/nAlS08PbLG+eUIFq0Kk1bBWiTDfDDJI+dX2NBoYdIrlJjfeGGK5XC6ev/6+ZklvnrbABPeOP/7tQXuv2OAtWiGjz1wkb+9eyM2g4oDA7Wk8yWSGaH4u+9gH8+PeRlejlJn0dJs1yFJsKfbWeFlJCmXxe9lXb2JmysJd/lSCaVczXV9NTx2YQVvLINVr+L2TQ0USmU+/8QoY6sxwc6Qyzg5VWE9WHU8fnGVlbAAeEcqtp/R1RiBRA6NUsFfPDPOXCBJLFMgWyjx9PAaX3/XILu7XByf8JPKFckVSlh0KgxqBQ0WLYuVx1kqwdhqjKMjHq7vrxHpg/+CptRlm5KwIEpc1eHg5KRQvV5uhF6W+L82E2RXl5Ojox7imQK5QomuGgP719dh1ChIZgrc/8w4hwbr+ei+Lk5M+lkIJhlssLC3wpC7zIvTKOWYNQphuR0XbKmb1tcyvBJ7m6T+cuFUBk5MBlitJOKo5DKSFJn1J3ll+p9OAN9Z76z/m/XWQv67J2bY1eVgS7ONG/trsBuEfSwQz1YDZuQyiY/f2EsmX+SFMQ9X6/P0Tl/ksYdOolucY48pA9PT/NXSAubMmxa7pEpLtrGZQk8n8v03E65t4JzcyojKjrW/iw3ddaxG0nz3xSkiqTy1Fi3vP7wOjUoM4B46t8z1/TX86NQC5xcjhJI5VAoZDoMatULOajSDUiFj0psgWzkoF0tlcoUSP3h1jj/Y3c7VHQ6u66nBn8jy5NAqy+E0n7ixh3SlvtIo5Ny8zk2pku5n0Sn536/OM+UV93mFTOKv796IQi5qsMt2LKNGqNK/eLgfbzzLF564VE2kk8skvnhoHfcd7OfsQpjlcAqrTsVVHWKw+fpssKKcyXNuIczBgTpuXl/Li+M+5JKwBe/ssCOXObEbVLwyHeD+oxMsR9LIJaEWliSYD6RwbFHhj2e5bXM9dWYtDoOaUzMixa23ViQnv/yWtLtbBuuIpfN87egY84EUhZJI1/3ZG4vcf8cgbQ49vzizRDCVQymXUabEsQkft21q4NRssMpCBGh3GNjd7eKhs0u0OPTcs60Jh0FNKCkaPcVSqWI/LItmVzyLVa/iqZFFbhms4/ikn4vLESw6Fd8+Ps3GRit7epzcsbkBSRLpwvfu760A4TO02PVsbbURSuUwqRUEkjmWw2mOT/h4ZTpAt9vI9f1uVHKJbRXL9DOjHqxaJbdtFI245y55cRnVdLuNfPXpcdbVm7mut4Yjw6vM+pNC4dvl5MSkH38ii0ImYdapCKdyzPjEQO/9V7aQzReprySzFkvlqkonkytVkmD1VXYgABJc2e7AolPy+cdHeW02iEySeGFcPPb7bx+k223ig1e1MulN0O7Qs7vbRTIr1NEapQybXsln9vfSZNMjSRKKikLxiYurPHZhlblAkkg6T/tpAz/53e0cGQ6yEBSNzUKphFGjYCGY4vikn83Noq7a1iLUTccrgS7r6s3sX19LKlfkyaFVTFoFn7qpl6ZK6MuTF1fpqTWxp9uJhIzVWJqx1RjX9rpEQ0GCi4sRPv/4KBqVvDJ8LpMtlOhwGQjEs1VGb7ks2D8GtZKVVJpnL61wQ38NJyrp2JdXm1PPzg4nE544Aw0WmmxaBhosbGy0YDOoyReK1Fm0fHp/L0dHPUx7RSDOtT011Fo0hBI5vvr0GNP+JBqljPG1OKMrUT69v49Gmw5PJMNqRKgQLzfnL+/9v4lVeXldrtWODq8xuibCA27bVM+2Vht/9dwk5xbCdDgNJCrNcL1KzvoGC6VymZ+eXiSQyNFiF/B4t1kMvKd9Cba0u7CuryecyvPUfIgTESfb9+2m75pO1hJZZDKJv3l+kpemAhg1SrTlPJZEFEsizA5DkVsaVGRX1ghPLlDweKlLRrFOjaE49RJXBPxclXnzd9wJ7AJiOhN+rRnHz5ooaEy8NyoRNVgpu5wkTDZiBgsXFBGce9ajcTlAJvsnFsJ6q5a9XU5a7XqabLpf23D6ddbDX5fC9+vWrwtI+5e8dv9frneaUv/Jliea4YuPj3J6PkS+WGZXl5OnRzw8ObSGUi4hlyQ2N1ur03+jRkGw4q02VBoBbrOGb79nE9F0vpr4lsoVKCOSyLyxDF++dT12vYqjI2u4jGpsejF1yeSLyCWJ2UCSa3preH02VPVFb2oSqqVpfxJlBcCsqjBKJrwJ9GoF4VSOqzuduEwafvz6AqOrUW7d2MAN/TUVj3eOdL5IOl9EIRNx621OkXj34piPgQYzV3c6CCRyPDG0yt5uFzs7HTw1vIbbpGGwwYxBpUAhl7G11cYvzixWIdXRdJ6rOhzs6XaRyRW592ERraxTyTm7EObkpJ8/vbGbZ0e8qBRy/vLODfTWGnlh3EcZ0KvlNFZuRsVKsyaUyvHVp8f5yDUdfOLGHs4vRpjxJeioxPMmsnl8sQwfuLIFt0mDUaNkMZRCUYHTl0tUfe+T3jjb22xYtEpm/Un2drsYXY0ythpjW6udT+/v51hl+uk2a9jaIrzYQ0tRrHoVhwbrCCSyrEQyfOfEDDvbHfy367o4Mx9iypeg2a7jhn4BIe2vM3JVxwYsOiX9dSaeGl4lms6jVclZjaRIZAvVG2+NSYNBrWAtksZaLlNv0RDLFGi26ygD37h7Iy9P+dnUbOXlKdEElEliopWpqPXOLoS5fVMD6VyRKV+cVrueWzfW4Y1l+dzjo6yE08hkEqMrUcZWo3z5tgHyxRJfPzrGqbkw+WKJ5ytWva/dPsCGRgt/d3JWvCkqVrXLHIfzi2E6XIbqVE0qw64uI0qFjN/b1c7F5QivzwTZ3mbjjs2C7QOQzBWIpHLUW3SEUzkePLtc3Yz3drsIJrLEKsX7y9MBFgJJ6q1ablrnplQu44tlMGsVKOUy7jvQx4lJX3Uz2dvtwqhV8sF/OM1cIMmfH15fLRbCyRwNNpHSZDeoyOSExfLZUQ/NDj1XttvprzPx09NLjFWg9aVK82gtmhHJH5sakMvg8AaBpwylclxcFrysK9rsbG2z8/s/PEO2IKafI6sxhpYifO5QP0q5RJtT2BwlxOFDsBNKtNh1zPmT3PvwMIONFv788DrimTyf2d8rJmI1Rna02Xl9NsTTI2sUKoenyYpttcNl4Oioh8WQ8MfH0qIxMhcQvLU93S5+/Poixyd87O128cCZZZ4f93LnliYeu7BKi0PPvQ8Ps6HBwhdu6WdXp5M9XUJqHUrmeGrYQ5fbwL0393JqNshSKEWDVcvVnU60Kjk/eHUeq17JlmYbX39mnMVwGqVMoliCm9a5eXkqwNkFcX1dXm/Mh3hl2s+tGxsEaNYqgP7xjDicZQtFbHoVJyf9LIRSeGPZKmD+/FKEZ0Y9vGtzIy6jiDM3aQXQ1aZXsaXFxuMXVymXy4RTWW7or2VHux2LTslCMIVeLcemV/PrViZfJF8ssVThDUiS4Kq8OO5Do5STzBaF1bVUIp7JMxdIcsuGet53RTNzgSTNFTWX26wmly9h0in50q3rCcSzTPniHByoxapXoZLLyBTeHke8u9tJNl/kpSmRYGbTKUWS1I3dvDQZwJ/I0vyWwilXKFW5CBJgrAwO8kUB6n1nvbP+rddbC/nZQJLzS2F2djg5vxjhe8em6C3H+O9tclicpzw9jWlmBml6mvdNT6OqHGY+BqwZHejX9TBU38Gphi2EXA0k6xtp3rKerVs6qbfp0Js0rMQy3PfYKN5YRuxDwwFOLCf5xI09fHhvB6Fkjl1dTmw6FS9PB/jmi1PIZRIqhYzfvqqVwo4yoWSOZ0c9vDjuw6BWMNhgRlaxZucLgt0kk0nIEQdhmSShUsh5fszLpC9Bu1PPH+3twKJTMrMQ58GzK3S6DFzbW0M8IyzHYt8V0O1cocQdmwXo/MevC4VsqVymUCxXLU8nJ/3s7HSikL15iMoVSnz60eEK+0kkJQcTOX7+xhK/OLtIMivg5Qa1nAMDtZQps63VzkMfuhK1Qs5/+ek55gJJDg3W8+G97Qw2Wvjybet5ZtTDw+eWKRTFwK3TZUCnkuM0qNnYaOXFcS/7B+r49P4+jo6ucWLKz81qBe/e1kQJkeInSXB80i+s/hKCr1i5Z19YDNPm0DNbSfarswhuz/OXBJj8cwf7OT0X4uxCmFaHnl1dTuYDYrBy8/pacoUSI6sxnBWmlEySMGmULIVThCtJZBeXogwtCbTDjD9BsSTuzcFEjl+cXeLnZ5bYP1DLx/Z1MeOLM9Bo4e4tjWQrCc5Hhtb45rEp7jvYj8uoZriyd9+1tZH962sxaZV85pFhJrwJUrkihVKJD+1pR6OU8+WnxlgMpvjswT6eHvFwdiFMMJFlsMHClw6v58VxH/54lg6nnuOVWrZchhqTGpdRTRkIp3IVJIAIuHlmZI3zlaChchlaHTrUShm7u0T4zaVK2qujom5/dSbIuCf+piWsLJTVJyYFk+nqDifX9dbgiWZ4/MIy79rSiFEtVPy7ukRKYjST5+WpAIFEFodBzbZWG3UWHV9/ZpxYRnAS8xXOZKtDj0wC21uSm+f8Sa7pceEwqPnr5ye5treGvT0ublpXi0Ypw6JT8T+eHyaRKXDPtiZaHHo+8dBQNXH2wnKEp4ZX+dKtAxRLJSKpAn/wo7Nc2eHg9k0C5t7qNLAUEgNluSTR6zayp9vF0yPi/HE5AKDFriOdK/DMyBpXdThwmzV87mA/z17yMOtP0u40sLvLiT+e5fximHX1Jr7zns2kKyiDaDqPXq+iUBT83Pdf0VJJ/8ujVshJZAocHfUQTOZwm9RIkmDZrkQy1fPYsQk/j11YYXeXk60tNq7vqyGcylcH0P+ceMcTzfClI5c4uxAmmRVmscshKbdsrGM5nBYQ8USWExM+vLEsXTVGNjdbqTVr+MWZJXQqRRXo7jZpCCZzfOfEzD/5WVd3OvEnsnz5yCXev6MFt1kEeUUzeRosWvIWJ36Lky3bGmFzIxalHE2lFloOp3nskpcTk34A/vpAJw8cPcfc6Cz2VBRLIoI+GsKSCFPjlFOeXWK7x4stKRpdiss8rL+tPBi5HBwOynYHSUlPk8aEuaLKOlHj4oa9AzjbG6GmRnwo9W97LpdV7P+3qXn/koC0f4/rnabUf6KVyRc5NiE4RpcloA6jmklvnHhaqAnyJWG5uWm9m+MTfhIZUWSolXIaKweLaDrP6GqUnZ0OrFoV333vZtK5Aiq5jNs2NXBkaJWzCyF+68o2+uvMnFuMVKO8i6UyMrmwZ8TSeWotGhZCSbKFIiq5jGg6R5NVyzW9NezucuIwqLDqVezrdTG0HKlaDNP5InOBBF+8ZV01zWPOn+B3r25DJZfxxMU15ivNl9s2NfDYhRX+92tz7B+oY1+fG6dBzUC9BW8sw/ZWG4+cX6HJquXG/locRjUPnVvGZVDzldsGOD7hZ9afoMNl4KZ1tdj0Kh49v0K0UoDtaHdUHqsapVzG7+1uYyGY4ti4T4DWHXpOzwUpVXbzUrmMRimjya4jlMwRTOb42xen2Npi4/ZNDSK6tFjCF8/ijWX57Z1thBJZHjm/wu2bGlhfb+bUTLDqK78Mt6w1awgkcpi0gq8VSeX4/KF11Fm1+OMZ6q06ru50cHCwloVgip+/scQVbUJy74ll+OGpBb754nQV4HxxKcKebheHN9Zz66aG6n+f8yc5NRdmPpDkwEAt1/fX8NK0n9HVGFaFima7rrppKuUSu7ocnJ4PsRRKVaxBwop24zo34WSO6cokqtGqI5gUjahsXnjjHXo1e7qdbGuxAeJG2+LQ8+j5Fa7treHV6QDeWAaZTCT5qBUy5oIpoum8UG2E0lVQaypfJJzMc34xwg39NZxfDOM0qsnki/S4jRwcrGM5LL5WLpNYDqdRyiX+7JZ1NNn1PF1Rsll0KpGcVIFWxjMFTk4FsGqVbG+zEU7l+NKRMS5VEpQkCZ4d9fA/7tqATaeqJhomswXUSjmvTAf4/KF+PLEMtRahqDk24WNLs40tLcKaVgaevLhKpGJ7+N6JGa7scFSijc0ADC1F+dnpRYwaBbu7XOzocPDd49McGVrj7z+whaVwqgpwVcqEXF8hlxj3xAgms3iiWeQyGX/+5CUWw+kqh+u5S14+dXMvV3Y4eP6Sl2RWqHpi6XyVBbGr08kTF9eq7AOVQkav28jubievzgS5Z1sTd29rJJEtcGzcx1I4RY1Rw1WdDgxqBXt6hD3yL5+ZYLryXrtcXD41vEapJJpdb23+zPoF8wlEAXtdbw2SBEuhtAg/CKbY3mbHqlMx5onx8DkxcTTrlASTOb7y1BhL4RQquYyrOx3saHNUI5YTuQIf/IfTTPuSfPs9mzg66qHeouN3drZh1asIJEQS1IQ3Qb5YolhRIAq1WIlJjzjAddYYeX7MS7ySqimTQK2QY9EqWQqJay1fEgdHeUW1N7IS447NZT5/Sz9PDq2yGsnQX2tiV5cTlUKGRiFDp5LzqZvFdPi1mSAPn89g0ym5aV0tOpXiN07ftrRYcehVwm6gkIil85WGt2j6FCoQzDIiWVAmwfY2O1tbbMJKmCuwGEzz6kyAsbVY1Qa6q9MFklCc/Ko44lem/fzxdV0UimW+/NSY2FcU4qByXV8NDVbt2wDtxVKZBquWXCVKW6OUUWPSkMwW6K4x/hvsiO+sd9bbl7JcojHi4fbABJnxCVKXJsiMT2Kbm+XHgVVUBZFsVpLJyNQ2QEcHih1XEnvXPUgdHXxvReJ/e2RklWr+/v1bGFmJ8LPTSziNav6kwpc7NuHjuUte/su1nRwb9zHhiZPJFzHrlOhUcryxDKfngty6sQFfPMPZhTArkTS7Op18en8fpTLki2VOzQrVapNNx20VDufDZ5fZ2elELsG1vULRPONPQEkMDPb1uTkyvEYiU+DGdW7erRcK9kgqx/nFcHXAdmo2yBvzIb5y2wBus5pUrshAvZlXpwOYtUpuXu8mnS8xURlyXFYcZ9+ikD04qKK/zsQb8yEyBQFUF8mw4j08vBKlr87M2cUwiYxILNaoZEKZ5DTw0NkVfPEsjTYxJPif799CvlgmmStydMTDUjiFRScUq9tbRVBIo03HwcE60vkip2YDbGq2sb5eNOlcJhXv2tyAL54lkMjyo1MLPH5xFbtBvFZLoRTlCqNQq5JjlIm66nIDv7PGUHUQ2PQqSmX4zrEZPr2/l4ODtWxpseKNZnj43DJPj6xyy4Z6fvfqVhQVHmNfrZHXZ4NMeEWwS5NNh02v4qZ1bnzxLJ850AflMi12PTVmNRJisANQKAk+6NhanA//5Bw39Lv50J52xtdiXNdXw9VdDprsOs4vCgv1YKNIazWoFdgNalbCKT60t4OXpgJ4oxlaHHoODdby6IVVzi2EsehUWLQqZnyiaeWL5/jmsSl2djrZ1Gih2a7HqFHSZNchTYmhRQmhBpfJBKMoX7lP1xg1fOW2AZ4cWmXSm6DFoWNPl4tktoDbpOW/Vq77WX+SwUYLnTUGnhwStdXlw7MkCWXsfDBJvlhCr1ZwajbIjD/Bri4nOpWCYxM+NjVZeXk6wJUddu59aJi5QJJGm6irHzm/zNduH2T/QC2Pnl8RAULpPA1WHZGU4KUpK/WzXCbRYBNsMLNW1AcvTwc4PuGjyabjvoP9leGKniNDHrZVQjgWK5BzpVxGKldkJSysd9f1uriuT1hSf/jaPD9/Y5HPHezno/u6uLAUYT6YrADaa1gOpTgx6SeQyFIGtrVY2d0lsAkf2tuBL5bBG83giWbY2GhlX6+baDrHyUk/Jyb93LG5oWrtf2JoVcD4r2xBLkk8dnEVu17FujoTVr0Ko0ZLqcIo9cUzqBQyYcn/pcS5crnMlhYrW1ushFN5zsyHODHpJ1sosavTwcYmy2+0l701/e2ywhlgzi+e69ZmG5lCEX8iy70PDbEQSuMyqjkx6eeBs0q+fOt6ru0RbNC3Jsb9OktaT62RJy6uMRdI8ewlD4cG63lqWMDlY5VUSpNGybYWO6lc4W2P+cx8mGcveVErZPzh7nbUFhPazg5e9sjQ1IjrQwRBFdn0e9t5ZSrAj04tiOdfLOEqZzDHw9zeoOZaO2giQUpeH7Ojc/hnlrDEQrSszmCOhzElo8i+/0uQcZ2u2qAqOpxkZAZ2Z1VEDRYiRhsRo5WI0coppwLn3n40qv+zts1/hEbUW9c7Tal/pyuZLWD6N/6el2HJlze6MmUC8SztTgOvzQQFv6ZY4vXZIAMNZr56+3pOz4aqypqdnQ5S2QI6lYKdnQ7yhSJ2o4pQIsdL0wGWQmkarFr2dDu5WVNLsVhmb4+4iSyFUpWkMKGq2NUl4lpVchn1Fh2UwRvL0Oow8K33NOA0akjni4QSWcbW4rQ59dx7Uw9ff2YCi1b8zP3r63AYRErVtD/B7ZsbyBXLfOSn58kXS2TypeqhxxvL8Ge3rKfOouXYhI/FYIpWp559fTXUmrX8zs5Wrmp3oFPJ8MezTHsTPHRmmd3dTra32SrAyCwT3hhus0ZsloUS//2GbhptWnyxbDXtT4aESi7xwJlFbt/UwO4uJ08NrYokjIqqqdasYW+3C4tOyVduW8/puRCPX1zlZ28s8f3f2kpfrYl/fH2Rp4bXql8j5L5FIRmfCTIfSlEslsgVSnS6DBzeWI9CJvGlw+vpcBlI5wqYdEpMaiWFUplgIst3T8xwYKCOc4vCBvDM6BoPfegqet0mnri4hlWnRK2QY9IqyBZKfOf4DLP+BPcd6KdYLhFMlrnv8RHOLURQyiXOLYT50q3r+NLh9bw05WchmMJpVLOzQzB/KAv49Gdu7uXJRgvxTB6nUc32VjtDy1G+dWyaYmUi+ePf3S6mGsUS/oSIw/7S4fW0OPS8PB3AH89SZ9GyqdkiIH4Vxc5SpfEkl0kEkzlCKcEnWg6nWI6ksWqVmHVKLAjZ+EokjUYp566tjcwHkjQ7BMhar1Lw7IiHa3pdlBFJirdubKTJrueTD10kVyyjU4kb/MWlMJ/e34dereBrT42xf7COOouWUFJI4YdXRBKR26zBH88w60/y+myQnZ1OTs+FKJTK5IslUrkiZ+bDHJ/wc31fDUqFjKeHPRwZWuPosIdUXmzm33mPYJbp1Ap0KsF4ePjcMqlcAadBzV88O8FcIEkqVyScyvHyVICv3DbAt96zmWlfgky+SIfLgFIuq0ZMK+Si8XZwUIMnmqHRpuP5MS8jq8I2KJdJGNQKfJVkoZ0ddn746jz5Ylk0RBUyLq3FODBQRzSdr8rdZ3wJeutMHByow6BWsL7BjEIS76uvHZ3AE02zGsmQzhfpvLDClw6vF2mL3S5uWOfGOCPAkw+dXWJvTw2dLiMXl6PIEcVfoVhGJhOR16lsgQ6nni0tVmSSUNN0u42EkznqzBpR0MUyVSaIwygax08OCUstlEmXivzizDJ/++I0nz3Qx4H1tULlthpHKZdwmdRsU9lQK+ScnPQxG0jRYtcx2GCh0aoV0drFchW9WZTKNNi0SEhsabaK+1Uyh0ImosLXN5jRqRRVJeHlVa78o9WhZ6lSpN26sR69SsR8j65G0ank/NZVrfzBrnZ8iSyfeniIcCpfTXccWo7yuUP9NP3SRO2t07dISqgvjgyvkcmXKiwuF6dmg8hlUtVe2+kysH+gltVIhvseGyFbKHF9Xw27upx8/NGLJLPFanF42Qba4tD/2jjipXCal6cCbGmx8ewlLwDZQolnL3mx6VW0OvRvK6A0SjlXVxgeiyEBZjaqFfTVmdjXX/NvsSW+s/4zrlwO5uZgelp8zMy8+fncHBQKaAClXEHCXkvQUc9a9xbMt/fQuHU9f7tUZv+BK3HajRyrTPi7K9bpA9kCP/zea5Av8cq0n/de0czQcpROlxGHQcXHH7zIajTDb1/VAoiEuGg6j8uoRlFRDpXKZcbW4tw8UGTSG+cHr8wxH0zx9Mga33vvFhLZAh/7xUWhTiqVeXkqwMlJP1+9bYD73zVIIJFjNZLGaVDzl3cO8sKYl2lfgk6XgR63kZenAmxsspDKFTkyPM98IEWrQ8e+Pjc1JqFqlyQIJXNVVaNMkrhxnZvX50PM+BKYtCqCiSwdLgPHxn28Gc8p3tNNNh3pXJHPVNh+Y2sxmu06ru2pwW5QsRxOEcvkcRpUfPnW9RwZWq2oMutocxq477FR5gJJLDolhckSTw2t8sXD67HqlHzlqUtcWoujUcrRq+So5TJu39zAox/eiUIm7Fv5QomtrXaOTfi5tCrs2rdsqKPGpEGnVDDrDxHPFPjAlS1c0+NCpZBVwcBySfChpIod0KAW6vQd7XaOT/g5NRsUacE6JQ02HQ02HeUyfOrhYSY8cTQqGZ870E+7y8Ar0+JQ3Vipi79xz0Yev7jKjC9Bg1XH3h4nNr2KWrMWuQwmPHH29rh4dUbYlpVykZzWUUn1feDMErliiW63AbNWSV+dmUfOrbAQSmLSKrm6w0kgkeUvn53ApFHytTsGePDsEj94ZZ4rOxxc0+Pi5vVuDGoFyWyRcwsRpIpSyBNN0+LQV4DZBZJZBc+MePjJ64t8YEczd21tZHeXk2PjIq02ls5XB3q7upxV+2IknSedL/Lu7U2kckX88Sz+RJaNNguPXlhh1p9gX5+b6/vdwnKJhNOoEvtoqUyxXMagVmDUKGi26ZHLpGrKLoBckvjZG0t0uAy8OOFjfb2Z58d8jHniVSarUi5jLpDi+ISPrS02nhnxEE7liaZz3LTOTYfLgEGtIJjIcmLKjz+W5dreGvzxLJ/Z38fxSR/zgRQdLgMHBmoJJnM8fmGFwxsbeGbEg1mnYtYvbPQqhQyTRkEyJ7iT84EkxgqT9gu39FeG2knWImm2ttg4MFiLQpIYW4sRSmTRaxTc0O9m2pdgsNHCTevcmLQK8fstFPnkQ8NsaLTwnu1NLEfSFEolLpcNdRYN+/pr8MYy3PvQEBeWo9yxuYF8ocxHH73Ah3a34zZreWbUizcmmpF7uoX99fK5r9JPrq5Gm458SaRlj67FaHOIa6+31sT3X5nj8MZ6vPEsJyb8eKJpdnY66a19OwPqcmiEsPQqoTKMU1Rq9Ca7DrVCzpNDq8SzBaw6JeVymXS+iN+b5eSkn709Ll6bFTb9y4lxv86SppDJWAqniGcEz29Do4X77xio/L006+tNbGyyshhK8c1jU/zpDT002nRvs2z31ZpwGtX85PUFru508tjFFeYDwvVRY9LQVWPAWAm8+PHrC/jiItwipJCzo7ubrpt6eGRe1FIuo5pHnpvk1Zm3YwZkpSLXOOX8XrceXSQEXq/48PnA66W85sEwM8y1AR+WWBhlMf/mF38ZygqFgLlfVlnV1Lz939/6ucMhUgz/g63/eI/4P8n6xRuL3LJNTa1Zg/rfqNMpr0xsVHIZ8XKBYqlchVGPrkZZCaer8usfnVrgW+/ZxP6BWnzxLCvhNP94aoGTE37WN5j51M191JhUeGJZvnRkrGKzELDlV6b8/Pcbe5j2xmlzGvj0/l6OT/hZrIDhrupwVDzvfloceq7tdVU2I7hlQx3+eJYfv77AnD/BzQN1bGy0IEnQX2fmL+8crMhTc2xssoq/FxQJFNf11nB8wsd0JR1Lp5JTKpcJJnPs7HBgrvCq5oOpag31+myQr94+wPX9bvQqOd8+Ns2mZhtmnZJkrsBTIx6+c2KmwmuQ8e7tTQDUW3Uc3lhPk02HJ5rBXkm2Wwgk6XIb2b++lp/83g5KpTILoRSfuKmXExM+pv0Jut1GDg3UYdKKCc1Ag5nBBgsHB2t55PwKbqPwDve6jYxWkuf2r6/DZhAbt0Yh496be3n4/DIzvgQbm6xc0+Miky/y4Lllak1aasxqYZvTCKjo55+4xO/sbMVt1vDMqEg4fGbUw5Q3wW3feYUnP3I1PW4jF5ciXD5e++NZiqUy6+rNyGSwEEhzbiFCMCG4Cg6DCpVCxqcfGeGLt6xj/0At5bJoqH7/lbnq6/u5g33oNAree0VTdfN47PwqT4+soVLIqo3SC0sRdnc7OTklZLS3bayn3aXns4+OkisUkSSJUDKHUaPk/jsGUFeSgwSAvoBeLSeUzFEolSmUSjTZRHKcPyHAj9YKONlpEJybWzbUUyyLZt3rsyFi6TzXrxMFWySVQ62U8Z7tTZyeCyGXydDJIZMrksgWiKSESuiqDgdOswa3Wct/f+Aif3nnhgozSIBjXUY1OpVIL1sOpZFJVJUoSrmMciVpcdwT49ZKU3E1miGaEu9DrUokCEXTOeqtWs4shARIWqtCKZexp0vYZ+cCSRRyGblinlqzkDk/N+blilYb5xbDtLv0XNvj4tHzKwwtR9GrFcQzBRorfnV/PEuHysCFxQiBRFbY7wolIpUY2+Vwml1dTgolofQTAHJwGYXXv9mmY9qf4JoeF3duaaw+7mv/8hjxdJFvvWcT55cirIRTpHJFssUSMpnEXCBZPfi8Phfk8MZ6btlQz8WlCI+cX8FuEI2Z12YFTF+vlhNOCaXl7m4XTw2vYdIqKw1lOX991wZqzVpOTvq5os3OYxdWCadEoorbrEGqxFBfVu0VKxbhXEEUenOBJEqFjBmfsIeVyqCQybDpVHz4J+fwxjIc3lDPQIO4J920vpbjEz7OLITfBIk6BCBeKZdosuv41ns28vyYj5Vwmm63kV1dDhLZAld3OXlqZI1zC5EqD6XdaeCmdW5sehF5rSjJ+OFr8zx4donPH1qHTa/mp6cXuLa3hpenAkTSQjkXSmZJV4CsL036uWNLQzWdEQSj4nKc8YlJP/11Jr757k0VOKsoHP/s8DpemgqwGErRaNWyu0s8h08/MlI9cGxpsfLiuI9wKo9WKafZLppfmXyJE5P+qp3jV8URyyQJTyxTVbddXr8ufSaTL5IrlvjiLeuqTIvLCsx8Nsk76531G9fYGHg8bzacLn8sLgogG4BGA21t0NEBBw+KPzs6yDa38oBX4ucX1qrf7lM39/LEXBCXs4jTbuTeh4eZDYjUqxa7nlenA9y7v5eP7O3gh68tYNWpMGmU/Ml1XWiVMp695CWcytNo1XJoQz2SBB+9vptbN9ZzZiHMD1+bJ5YuVBPjJjxxas1a9vS4eHrYQySZJ5sv8vpssGKTcnFlu73Cu8oRTGaps2p54MwiFp2KO7c0YterKlY5GcWSGCTs7LSjVSr47w9cZNafRKUQjf7XZoJ85bYB9vXV8PiFVbKFItOV+uL4hJffurKFP72hm6eG1ygUS0TTea7tFfzQWX+SEmVKQHeNgZ2dTh6/uMK7NjdwaLCOwxvqkGQScklYsO16NXu7RfOlt9bMFe129vXV4DSqefT8KheWIjRYtVUuzXwwxavTAa7ucvLKtDhIqxQSH711gEablofOLhOoBLvs7nJi1Cj55MNDnF+MUK5Y1cfX4vz54XXoNXL2D9SiksuQJIlzCyHOzIe4os3GySk/nmimmg7Y5hSH+GPjXu7a2sS9N/XwzCUBie+vN3Fdbw0z/gRtdj1/ddcGnrvkxa5X0Vdn4i+fnWAhmCaWEa/bkeFVvnb7IHdsamAplGI1muEfTy3y4piXdpeB+w700+YwgASf2d/HS1Pi4N1g1bKz00k4meOZ0TXaHQYODdYTz+T5ytPjjKxE0SjlqBUyXpkK8LlD/XzmQB/1Fi0KmcSj51dFUt/wKpIEvbUmUtkicrnEwcFapnxxYQG95OVdWxp5cczHlR12dnc5sehUZPJFXEY16WwBpULO5w/188TFVcY9cTpcBvZ0u6rW7tWoaIbe+u1XePa/7SZYYfzIJYlUrsiFpQhHRzwcGfJQY1ZTLpf5izsGOThYx2sVC59SLsOiU9Js13FFu52TFVvl1Z0O5DIJvUrObZvqyRfLPDW8xjU9rup+LerPYgVAXmCykqCbL5bZ0GChu8ZENJ1nwhNn0hunwarlnm1NOA1qtCo5K3nhUNjX68ZuEOD2xVCSP/jRG6RyJTY0Wrn/jgG0Shm9tUbemA+hV4shoaaCGmmy6ZBJEn//8iwapZwb+t3c0F+DP5HjB6/Mky+V+G/7uiiUynzoJ29wQ18t1/bWcNO6WlwmNQqZUMXfsK6Wx84scXE5wj3bhFVzfE087kabQGm8b0czxbLgn014hUp9b7eTYxM+etwmakwavv7MBGvRNPFMgUKxxNMja3z1tgEODdbx2MVVFoMpTBqBCGi06djZ4eDI0CoPnVvBE8twaibIucUInz/Ux9/es5FEtsBXnhrDH8/yh7vb0ank/OjUgggtsL/Z9Lrc5FXIxXAzli6QLRSpt2jQq+RIksR8IIlMklgMp6gxiXNPoVRmwhtnX5/7n6T9/TpLmkgK1JKriBG+8MQl3r29mW2tNm7dVI9SJuMXZ5d4aTJAtlCqKq80Snm10VUoljg66uHpkTWu663hh7+9nUy+SCiZI5LO0WrX44tnmPUl+dodAxwb9zPljdNRY+Dm9bWYNUoePb+KhMThjfW/Mv2uJJPjaGtENtDAr/I/FvJFnj+zzC/OLEG5jD6dwJwIY4mH2e+SscNYRBnwv9nImpqCl18Wn8fjb/9mkgR2+69vXBn/farN32lK/Ttd3zo+w4uzier0+f9k/TpZpUYpZ28l+tJuULG7y4XbpKbBquPrdwzy9MgaU94ELQ49O9rsZLJFxjwxQKp4v2twGEQU5tHRNW7b1MCL4z7mg0kSmQK5CpQ5Vyzx0qSfvjoTf/Cjs7xrSwP3bGuqAjfH1mJcWo1y26Z6dnc5SeeL/I/nJrhlsB69Ss6nHh5mdC3KFw6tw2FQ85PTi0RTeRpsOq7rddFsU2PVis56NCVsh5l8kVqzhicupqoHfYNGQaFYIpktcEWbnYfPLZMrljFplIRTAg4aTOY4Ni4SBTUKccA+Menj1o0NvD4bJJjIoa1s+PUWLdf21FCu3PgDiWy1IfXJh4dYCKaQSfDcmJdXpgN87fYBlsIpPvnQEHt7XFzXW8N1fTUE4lmWI2mMWiUPnV1m3BOnq8bItb0uPry3g8cvrKJTK7iizUaHS09HjZFQIsfPTi+yEknTV2vixnVu3ru9GYVcBpR5+NwKD5xZQi6TqjLev75rAzUmDY9dWGVTo4Vak5rfv7qNRK6IQibxw9/exsUKw2YxlGJ3l5MXxry8MR/CpFUK6bdexfX9boaWo9SatYx5hPWzyaajVBZcrHypxKPnV4RF4WcX+NodA5WiUYY3luGVqQCHNtTz/ZfnGGg0sxBI8fMzS1h1yqoqo94i4JgmjZLPHujj+ISfTU1WXpkRjCllhaGVK5aY8Sc4PuHjwEAte7pdPDnkwZ/IYNIqKZfFwV6rlLO7y8nP3lhkfE3YI8rlMja9imt6XWhUcrL5IqNrMTQKOevqzYSSWY6OetjXW0OdRcsDf7CDOouWxVCKqzocVTtpKJnjmVEvq5E0kiSxq9NZAWIm8ceztLsMPHvJS65QIpkT/KBCqUyTXUehWK6qWkrlNy1fTTYdskoj6Hd2tnBdr4vTcyEePb9CIJ7j+ISf2zY1cG4xzMWlKMVSGb1aQb1VyyvTAaLpPCatErNWiaJiPby4FOGKNjvfPjbD+YUw37hnI397z0aOV6K7a0yCK7YSSWPSiKlhs0NXLQRUCjGlTedFukyyAqwtVKwglwv2F8e9XN3ppNGmw2EQ3Ix8oUS+UOLrt2/AalDhNmk4OuJBXmmcXZ7Mlcsw7Uuyr89NIJHDaRCKge8c9/N7V7exp8eFWiHj84f6eWbUy0o4TbtTz452B+FUDpNGwecO9rMQSvHY+RU+cVMPFp2KLa1WFoMpXpn2o1bIBWi9t4ZYOl+FAvsrcFGzVoFVL6CtbpMGmSTR7Tby9IgHrVJMQTOFEn999wYsWhXxTJ6nRzwcn/Dy/h0tfO2OAV4Y83FuUYA7r+0VYOR8sUQgJtR979/RTKkMnmian7y+yLmFMJ+8uZcv37qep4bXmPQmaHPq2T9Qi0WrrNhT0tj1KnHv6KuhXIb7HhthXb0Zp1GNN5ahWCojIaKiRcpNmY4aA55ohpOTAZbCKRosWnZ1O/ne+zYTTGQJp/KYK0X763Mh7Ho1fbVGakwabt1YmUZX9o7lUAqzVlnlYVn1KtGwVciqzdVE5T084YmTK5ZQK+RVBUIiW8CgVmDWKoWiC3AYVNy9tfGfhW8WS2UeO7+CRil/G9Pi5KSfSCT6f7QnvrP+E64rrhB/6vXVZhN33fXm5x0dUFcHsn8Kj1UDux0pXlmIVBV/Vp1QzNy+qUHc79/CNQuncijkEi9NBnj39ia0KjnbWmw8fmGVWCbP+3a0EErmsOqUfGhPB3JJ4qGzK6xG0lj1Kq7pcdFi1/OZR4dpqSh3Hzy7jNOoZnOzjaMjHsw6JUqFDG8s+zYr4LRP3Dtu6HcjAbdtbuALj4/S4zbS7X5Tby+XSShkEj1uEz86tcCsXzR2ywhbfjCZ4/kxL9tbbRwZXsOqFupFEM3o1+eCdLqMXNFmx2FQY9IoWQglhUp62s+ML0mny8CBwVqMagV3bG5EJhM/97VZARlvqzSVs/kSRq2Cjz80xFduHaDOouWN+RDX9NawEBLBOGUgknozeXQ5nEYGZAolFDKJQ4MN1Fu0fOyBi4QT+crQAY5P+Pj4DT20OQycX4xUh7G3baonkMzyynSQ+YBocG9sshJI5Pjy02N86qY+/us1nVxYEq+50ygGqAqZxO5uF6dmglxcjnBdXw13bG7AqFaSL5XQxmU8eHaJLreR2zeJg+7D55dZCKZZjaar6Yevz4V5YmiVd29r4rGLq/z09CKJbKFipcpybMLH4Y11KGQSGqWaAwN1pPJFIqkcy6EULpOan/zuFZQl0KkFE2zGnyCUzCEBZq1QxJ+ZD3PbpnqUchl/88IkyVwBnVrOn1zXS4tdzzMjHi6txeh2G7m2t4bPHujl4w8M8eTQKle02fmH395KOJnn+TEPy+E03TXChm81qFmNpFmJpOmvM7O724U/nuUXZ5Y4Pu7jQ3va2dpqQy6TkalYOy8uR/ju8RnkMonvvW8zrQ59JbxFsJPypTJ/8vML/OCD2/jq7QNvU8Ds7HSiVsg4txjm528s8eiFZb56+6AYBnY6sOtVdNUYiabzdLgMYlAmQTwj9je3WcP6ejOlMtyxuYE7NjcQSef50D+eJZDIYdQoUMok3pgP85n9vdQrtdiNKmwGFZIkVXEiX3jiEsmssOj/+ZFL/PG1nbxrSyM3r6/ltZkg88EkcpkMhUyiyaZlX7+bbKFIg1XHT15frCRGpslWrtuPXNPBnD8hlOkf3cNSMIU/kSVXFKEmjw2v0VNrJJ0vMumJc+vGehptev7ox2cJJvOYNArOL4YZWorwseu7MWoVzAUFZzZfLGE3qpnxJ7h1YwOvzgRZi6ZZCafJVPhyF5YiPDm0ynu2N/P379vC63NBXhjz0ldrZm+Pi3S+yKPnV1HKJeotGvLFMhOeGE+PeLh7ayPHxv0shVLc0O/GaVRz78PCNmnVK7HqVLw6E+BLt66rKpBm/Uk80Qy5Yok2p57trXYeOb/KwcE6Wh16nr3krQ6zzVol8XSeDqfAN5TK5WqN8Mtn2ctLhCLBni4nTw+vcWEpSiZf4tlRD69MB7jvQB/PjHp4eTpQrW0vK6/gTfZSPJMnninwset7KJbLPHR2uZqKvKfbSY1JQyJQoM1lQK2QcUO/m+t6XRWuV4RNjRayhVKVf/rPpd/9qvXLqXlJnZGkzoisu5vWm3tR/iamVCpVVVxV/3zr5x4PDA2Jz4P/foNi3mlK/Ttek94Ez13y8u7tTejVv/mlEoduKtC4X0/tdxjUfPm29fjjWV6eCnB6PkS9WcPVnU6u73ezu6uEQa0QDSaZhNus5eiohxlfgs4aA9f11tBXa6JYLFfjSwtFISNP5Yrki2/yePb116BTyXnswioWnYrDG+rIlkq4jGretUUAorUqOeUynFsI89F93Ryb8DPlS3BosJ4Wu54/fUhM85wGNSatkldnAnx4TwctDiGZbrBqMWkUWHRKoukcLQ4d+VIJi0KJSi7x8Rt6qTFpiGfyjK3FSOcEu8GsVVBGTPgXgimhCItlODBYR7kEtRYN337vZiLJHKOrMSLpXBV+/KNTC9y5pZFWhx6VXMbz48IOWC6XyZeEgmTal+DkpJ/NLTbKwINnl3nk/AqSBCaNkv3ra3EZ1fzDq/MsBlNiyjUd4LMH+vDHs/zouUm+/1tb6Kwx4olm+PwTowQTORRyGafnQrw8FeCTN/egUcp58OwyP3ptAZNWiRyJRLZQOZT6uXVTA4MVpdnlG+ZLU4LD1GTTsafbxY52B6WyAEx/4ZZ+jo37mQsk6HQZBX/GoOIXbyyyu8tFq0PPU8NrNNv1JLMFimXR/Gxz6QkksiyFU7w85efGfjdn5sOUy2UWQkIKn8zleWnKz3u3i9S1YCWxxqoTxcWmJgueWBq7Xs26ehP1Vg1r0QzRiky81qzBqlOSyhaZCyQplUXq4NfvGOD0fIi1aJr962vZ1eUknMph16v58q0C1BlM5OitNXJVh4NktsDDZ5c4tKGeZrvgkY2vCRDp3m5XNXFIr1awEEpyxxYhhz5WSWLprDFy26Z69GoFxaKAdV6e1D0/5uXOLY08N+phLpiqPD+J7a1Wdnc5MWtV9NYaGV2Niw1Sgr5aI7dubAAgmSuSzBZwGNS8/4pm3r29SaSirEax6S837HyMr8VpdxmoMalpsukwqhXce1MPGxotKOWiKIykcvjjGdRKGf5EliNDa+zrr2Fzi5VrK0l4y5E0f/bECH//gW1cWhNw8WdGPEz7k1VoudOgZm/F4vDf9nWxFhEy/12dzorMX4Qc5Aol/vHUPJ5Yht++qhWVQsaUL8GFs2H+y7Wd9NaaGF2NVZvTl9VYLQ5dtTE26Y3jMqr59P4+FoNpAokMdq2SUhkGG8xcXYF+5oslcsUigw1m/HFhz/ujvR2VqGnBLjk9G+KqDge3mTRc319DoVQiky7y8nSA7W02Hr2wwpw/SSpXEPbkDjsHBmoplct8YEcLOzscKOUiReXoiAebTsXGJgv3PzPBrD9BIJHj/GKEO7c2cuvGem5eX0sik0ejlJPNiULJZlARqzQMH3hjia8eHcemFyrO3//RGzz8oZ28Z3sTiawYJKgrysNJbxy1QiYKxAsrfPOeTcwHE7x/Rwstdj3hZA6bXkU8Iwq5y021m9fXYtYq+fMjl1gMpohnCmhVck5M+vn4jT2MrcXxxDLc0FeDSinj0GAdkiRRKJYYXY0y5Utydaej2iSq+SW5vEWrrBaSOpW8WmxLkgDfzvoTGNRKJrxxfPEse7vFNfI/X56l2a7n4EAderXiXwTflFf2n1+cWara/S6vQ32Wf92m+s76z7OOHoXBQTEVfgsz5V+6ftkqolbIWF9vwapXMeNPUiiW0apk3L6poXpAyxVKlMvQV2ui3qplJZJmdDXKnVsbabbrMVVYQn9+5FL1XqhRynhl2s9nD/Tzjbs3UmPSsBxO8diFFfZ213B9n7s6vMkXS1zd6UCvVvDJh4aY8Martt9TM0L17TRouHl9Ld94YYodbXa2t9mpNWtxGFRCWSmTEU0JG322UEKrfNOuf2ktxu4uJwcH6tjV5aDNYUCSQC7T8ZWnRklmizTZdTx8bpmtLTbqzVoCySzX97kxbVagUyrQq+WsRdI8PeJlLpCgp9bEQIOF3V0uPv/ECM+MeviruzYgQ8KsUfHNF6e4e1sTd25tolAs0eE08OyoF6teRbby+yyVyzTbha2o8nS5tkekO8/6krhMakDA1j3RDMcmfOwfqOXcYhiAGyuvzyceHCKVE/yq5y750KsV3H/HADf21/KZR4e5dVM9v3NVKy6T2GPSuSKUQaeC4yEfwWQWi05JvlDmkUsrAm1h0rCv341Ro6BYLpMrFpkPJIll8tW6/PLVN1UBjW9psfHERaFguhwKMuERNUEmL/AFn354mNVIBpNW1P4NNh33HejDrFUik0nMB1OsRTJVK1cknQdJYqGSzlooltncbOOxC6vctqlB1NMPXqRYKqOQi2bPqzMB7jvQz5dvW89D51YwaRSkskW+fnRMOAokifOLEV6aCvC5g33UmrV878QsR4bXqof6y+zBuUCSfX01xCvDq8u10DMjYuj52kyQm9fX8twlb0WlXMIby9Bg0eJPZlkIJNnb48KgFlb7U7NBAvEMBwfrWd9g4YtPjPLiuJcNDRaOj/s4vKmeg4N15ApFemqMSMD/fm2+OuhzmzRc11uDViXjynY7aqWc584uM+VLQJmKpV5iMZTmxXEfhzfWsxYVDo5cvshvXdWKUiHjq7cNcGzCx3IoTZfbyN5uoVq7tBrlswf6eHk6wIQnXkkkdmHSKIim8lzT42JkOUqrU8+2Vns1ibbJpuORc8toVHKu6nAwtBLlxnVuJETTeEe7Hate2GO73EYG6s0VB4hoIscqdt+5YJIjw2vcvbWR2goTMprO448JJIvTqOblKT/xSrIvCKYliGTdRLZAJl+kzWFg4w1WEpXv+zcvTFX2dIlisYw3lqlenwDDKxHyxTJbKkmOcwHxuHKVn7EcTvPsqJfDG+u59+ZenhnxMLIafRuc/dHzK7Q4dOztcfHYhVX88SyJbAG9WsGOdjs3D9Qyshzl7q2N7Ol2/cqh1Vs5mZ5omvde0VxlmU35Egw2WLiy3c6EV6QIXx5Ub2mxVRXeb11KuYyrO53oVHI+WeGTgbiWXp6qnM1iWR4+v0JrZXCwEEzyhScu8cGrWglV3A2XVV3/2vS7f3Vqnk4HLS3i459b+TzMzkJPzz//d///vN5pSv07X9O+eDXd61ety2/M5XAai07JFx8fJZTKi0mEJFWp/bUWDWuRDHa9ikA8y188M8FSSETfemIZfnJ6ka/eNsDD55cZWYnyw9/ZTjiZ48+fvFRN0Tg24eOFMR/fuHsjBrUcfzyLRacikRUgOa1Kzmo4TSZfosasqcqjZVKZ3lojgUSOj/zkXDXFpVAs0+U28M17NlW+p4LZQBK5TGJPt4sXJ3wiah6qU4alUIrjkz6uV7hpseu4rq+GV2eCrETSvD4b4ppeF8fH/WQKRW7od1Nj0vDZx0b4xI091Fq0FSuPOISmc0WWI2ncZg0apZwfn15gV6dI/Hp6xMNSKEWjrdIlN2qIZ/P8/o/O0FVjQpKEJNmmVzPnFzDGt+BhkMskFkMpblznxqJTks4XRaocEjqVvJL+leXanhp2tIsNK5bOsxZNs7XFyreOzxBO5jFp8rw+FyKdK7Kvr4ar2h04Kn/XE83QX2dmsTJpSWYLNFi1OA1qDBoFE944xVIJnUrBU8Or7Opy8fGfX2A+mEKrlFNn0fDabJBP3tiDXCZV7FIqdnbYuX1TPXK5DAmh5rm6y8kb86Eq0LpcLoumVEm8hnu6XBwZXqNULjPlS3Btbw25QoliuYzDKKDKf7C7HW8sg9Oo5nvv30IomePCUoRMrsjWFhtqpZA/P3h2mb87Octf3bUBq05JLJOnXIZYpoBFp8SmV7GpyYrLKGwLkVSO2zc1kMoVWA6neXXaz65uJz89vUgwmeXm9XX014mJ8Q9enefZUQ9/sq8Lm05FIJmj02UgnMxxZHiVF8a9/OW7NgASL00FqLdoaHMa+PAD56rJdcpLXl4c9/E3d2/EolNSimXY2mqj3WVgR5uNZpuWb793M89d8rIUTNHlNrCl2VaNxv67923hp68vMu6J01Nr5J5tgr3w+KkVJrxxfuuqFvQqOY9fXGU5kqbeohUNj2wBbyzDbZsa8MWyrETSeKIZ9nQ5uaHfTaYgJlxTFX7IDevc9JvM9LjFNPHMfIiNTVY+9I/nyOaL9NWZ+JPrutjbW4NcJhFNi7S1r1SKsMsckv0DdTgMKigjEhArrLeZQII6i5Z3bWnEF8vyxSdGWY1muHNLA5l8iT99cIh0rkgyV+Chs8sc2lDPqdkAhZKwmWXyRdqcBvb2uAjEs7x7WxPpQolisYROJcdlUqNWytBpFDw94uEHr8yTyhX4wQe3cX4xQo1ZzUC9mWi6wHOXvFxai4nI4oFaTBolBwfrUFSu4VAyj9OgJlcssX+gFoNawbfu2cSzY17G1mIMNJi5fVMD4VSen51eIpjMVoMdNEoZyUyBvloTR4bXODUbpN6iRa+Si99FMkckna+qxMrlMvlCiUffWGHSK4qja3tdbGq2YtYqcBhU7Gh3cEWbHZ1KTrZYJp0rYDOoefT8CmcWwlXVllGjYMIT5+SUnz1dTkKpPH/64EWR/LipkUfOizj3RpsWt0nDbRsFb245nGYtmqk2fF6ZDnBkeJXtrTb+50uzrKsz0WDV8dDIMpdW43S6DFzfX4PTpOGvnpvgv+3rriaFuk0aDm+sp1QWEd+3bmxgoMGMSiFnLZoRHLLlKLu6nLw47kMpl7G1xcrfnZwhlc1z99Ym/ss1nVUI7N5uFw3/ghSZX54aXl4NVi1XtTv+hTvoO+s/7dqxA0z/ejLnL1tFVHIZ1/a68MUzNNt1KOQSnz8oglZOTvmZCyTprzVh6neL5NZkjs4aAx+8qhW1QsaONhuSJFXsSKJei6bylBUyQsk8b8yHuKHfzc/fWOLYuBeQ6HDp8cQyBBM52l16lHIREvKT04tM+RKUKg0PdUX1/cyohxv73RwarEcmSQyvRBlaFum6S6EUtRYtMhm8e3sTOrWCExM+krmiCKeQyxhsMGM3qLhpvZvXZoI8PezBbdZwbW8Nf7i7i9/+wWlu6HezscmKQaNAJpNYV2emhGCCLgVTWHUqvnJ0nNlKXXRqLoRCJuP+OwY4OFDHE0NrvD4b4ob+Gq7pEVzNXV1O8oUSz1zysLHJikUnrPZqhRimtjr07Ox0olHI6HAZWAylsBvVTPsSFaaPUAl5ohnqrVqWQml2djgJJXMCcNxq49iEr2oBV8jlZApFPLEMxyd8XNPj4qenF3no7ArFYplPH+jj28dmeGUmgEYhY2urnSvabIJbWijxpacucXYhgkImYdQoOD0X5L6D/eQKJaZ9YiB82RIOVHmDbU49kVQOu14lmoEaBYlsEblM/L9Cscx8MMmJSb/gKMokwukc9RYt5xfCPHJ+has7HXS6jLTadcJ6mSsiSVBn0aJWyHCbNSyFU5yZD3N1p4PPHexHr5ZzsmIHbLGL5LnVqMByXG4euUxi6PfI+VWOTfpRyoU7IJrMky8K9t+dWxrpqDEgHxUcqjLCtmbUKKizatEo5eRLZdqdBh6/sMK2Fhv33zHAK9MB4pk8OpWcb79nEycn/Vxai3OjUQTZ+KIZZvxJGm16Pn9slAvLkWrS6qMX1rj/jgH2r69l2isCTTarbeQKJZ4e9rAaSdNo03HrpnpuWu/mkfMrNFh1XNnu4P/H3n9HyX2W5//46z29t92Z7b3vanfV5SZLtmx1uUgu2ECAAAmBUEIxtinGYIyNqYEAgYTQwb1KtiTbapas3la72t7r9N7L749nNLYJEELI55fky3OOzrHnzO5OeZf7ue/rel2D80G+8mI/71tdR3WRDlcojkGtIJHKivtZPil4PhAnkc5waMjN8horiXSWXx+fxB9L8vZVNdy2vAq5TMpb9HN8bc8AZo2KRRUWWkqNLK224osmeeH8HGOuCJ/Y0EKxQcUjt3WzEIyzt2+BVy7GaC4RiuR6u4F9A05WNxVjN6jxRpIcG/Uy7YtRYdFwTasDWz7kRyWXM3xqunBdusSYTWVyDDlDxNNZVtbbODzsBuDYmGj+xZJpaov1b2lIySSJdCZHXbEYIkuSxN1PnuPhHd3M+WOUWjTcsqySbd3l+KJCof/YySmkjESD3UAyLZRLr496sOiUjLrfsNGrFG8oTsfcEZG8bVRzVVMxq5uKCyrnA4Musrkcx0a9rKor4qEdnbx4QaQKNubrELNGyZWNxZi0yt8ryPjtlLozU36+eGMHb19VQyyVIZtvvu6+MI9SLvGBNQ3YjWoODrl4+eJCwWp4SbShUcppKzMKFembVLBWnYopX5SdPbMsqbKyr9/JnkyO3b3zfPmmTt59ZS1r8ozk31ZC/Snpd38oNe8PweX/U0uphLKyP/3n/xvXX5pS/8NXo8NYkBz+rnXpxPyry2vZ0zvP2ekASrlEmVmLSiEVkgu2dJXx4K6LPLSji9eG3flUixzhRJpEKsuoK8K+ASfrWkuQEJPzg4MuAvEU1TYdqYywIrlDCQ4NCa7UoUEXa5pFwsuMP0qFRZtXIalY3VQseENb2rDqlFTZdJye8BVkkwaNnM1Lyri2tQSVQkZzqQlygk1j1CgoMb2hPgHQKAWgWSHJmPEJNo+AmWf4+2sbOTDoIpJIo1Uq+PYdSwqAwyPDwv51eNjNurYSdvXMMe6JEo6nMeuULKu2cnWzHbkk5MRlZg0P7OxjzB0lGEuRSGfZeX6Wr97SjUYp431X1VNq1vLsWdHAWdvsoKnEUOADZXI5lHlAdJlZ3KTfsaqaBodRpHqEE4x7IlxWV4RWJefOVdUcHHRxdNTNVY12OspNKOQSP/qrZTQ7jCjkEgvBOO9fXU91kb4Akm5wCPaMQiaxqMLM0TEP7lBCKCd0wsZWV6QnnRUpPevbSwvQwEqrlnA8TTghmjj7B100lxj56esTFBtU2I0akpkcJ8e9DCyEaC01sabZTqYqx4Q3wldv6eLslI+hhTBlZg1rW0ShfnjYjVwSvJ/5QJwpX5TL64tY3VjMz1+fYFt3OSVGLU+fmWEqPwFY22KnxKwhEE2hkMvI5nKMuiJEkmle7RdF0JlJPzP+GLmciLPuqDBxZWMR+/qdeCPJAjDz0ROTlJm1bOuuIJpMMxuIUWHRoVUKwOLTZ2Z49eICH7uumYZiA0+enuHctJ+mEsEAai8z8sDOixwaclFl1THqCtNcYuCVi06SGaHwu5TMk0hlODLi5uYllVj1Km7oLmfGLwq8J0/PsHFRKTuWVhbOwV8fm2RnzxxLq618fls7t62oIpLIYNQoiCYz3P9cL4eG3dyah1R+6InThaJWq5Sxb8DJJ9e3MOOL01pq4tlzMzx+chqHUc333r6URCbLR359hv5840wuk9jVM8u33raEv7m6ns8+fYEqm46FoEhciSbTDDnDnJ708e7La9FrhF3000+ep6PczLpWB9e3lxQk1TIJZvxxvrSzj/65EKk86Lyj3MTnt3YwG4jhz1vjllQL7tDgfIgys4bbllexqs6Gw6jmKzu6GJgPcWDAiU0vChaHUY1Fq+SZc7NcmAnQXGJka1cZRo0SbR5ke3WTnWw2R0upkVKzUD7NB+I4Qwnue643H/ec4/iYl+NjXu7d0kaVVScm1BLkSPLsOQHTLTFqWN1UjFGjZMeSCrJLKshmRZz5Qy9eLFyjQvE0z56d5cs3L+KOVdUo5RKPn5oimc6SzuYot2j5+2sbcRg17L4wjyeSoMysZV1bCZPeKN/bN0w0leX1EQ9HR9x8ckMr77qiluYSI3ajhn0DTo4Muyk2qriq0U4mk6NnOiDsKjJZATYvoK0RblxcwZNnZhh1R3CHE6zIF/wHB124Qwlayow02A3s7l3AH00RzVtHL01KhxfCrG8vFalMGiV3PXkOZzDBuEfIzZ89N8M/3bmUzV1lHBh0sTXPE8zkoacLoQQ1RTpWN9nRqxX88tgEdqOG91xRi1Wv4tSYj339ThryheUH1jRQZtby5OkZ5oIiHXBti6PQoP9jiqrfNzXUSck//ab6l/WX9Z9Ybz5ORcKuxJbOMtQKGfV2Pfc/10tHhZmbFldQatbgiySotxvQKGXctFjci0ZdEVrLTGRzOUZcERaCCdQKGQaNAgmJTC7HuSl/IQlYrZBxWb2NjYuEdf7uTa1c0yrqFGFrS1JsUBFNivPoUgLvfCCORadCKZe4dXkl69pKxGAzK+6dT5+ZwRtJUGnRsb69hEa7nvue70VCYlWtlW3dFUQSab688yK9s0EUMpE0d2zUw+e2tvOFGzq456ke/vXwGLkcfHRdE5s7y3jghV5eG/HwnTuWcnhENO4rrTp0KsF59EZEHbpxURknxn1MeiPo1Qreu7qO4XziWyKVYSEQRyUXDaxjo5784FM0raKJFHq1hq/f2s3+QSe5bI7uSguDCyERchIWyutoUtjNg/EUzmCCQFQk5k55ohjzjM1LCahmrZJwPE1nhZk7Vlazs2eWRocBmSSxuqk4f3/S4AzFOTbqodKi5fCIhylvDLNWQSCWZtYfRy4TzcZV9TZ29czxnivr2NM3z6kJXz53DJpLBH8pnEjTYDewcVEp+wacxFJZrFoF17WVcHEuiEWnYtwdJZPLIeVAhkQkkcGqV+EKJqgrNjDmEqqiQ8NuLkwHkMsltEo5WqWclXU29vYt8OrFBSDHDd0VyGUSL1900mAXyjdfRMDIAXpmAmzrFqEkaoUcdzhOg92QT9aTUCvk5BAhSdlcjq1dZRwZdjO4EC6k11XbdGxoL8UfTdI3G+SRW7rYP+jk9RE3JWY1b19Vg1wmEU9lyOZgc2cZVzQUM+6J8MSpaV66MMc/3iGaVeNekYgLouE64gpzYMDJta0lnJ8WSd4WnZIvPd/HuCeKWinj6KiXY6Me7t3cxkeubaJ3NohKLjHqEml817SIfU1lPv0xHE+Tzor0aq1KTqVVy6w/jj+aFI2cVJaX+xY4Pu7l1X4XmawI7LmqqZi/uryWlhITDQ4DT56e5nv7hnGYNKgVMiKJDOlslr1989y6rAoJ+O4rQ/QvhEhlBPvp8ZNTPHBzJxsWlaKQyWgqMfJAvq669JoO5W1nqjy7tbvSwuERN1qlHLNWKeyFCollNVYMagUKmcR9N3RweFgw0fRqBVVWnXC6XJjj1ISwsQL5ZoywnckkiTF3lMPDbu5YWY0zlOTAoJueGT9VNh0bF5XSVmbkZ69PsKbZTu9sgLUtgmPqjyapz9t7lXIJo1r57xhQOUS63WMnp95yTZUkiWqbLm/nV7Om2c7GjlJ80RR7excYcob41IbW39uQ+l1hKqF4mruf7OGT61vozCdSy2US92xuY8YXw6xT8sXne/FGUigVEkdHRSLwvVvaC8EwcpmEP5rEolWRSGdQK8TnHYimGFwIs65VBGOFEilcoQQnJ7y847Iaprwx7EY19y5p+3eKpj+1efTmn3uzKuz3uaD+r6y/NKX+B6/mEgPXt5f8USem9U1d61QmRyiRwipXIZMkJrzRQgpGJptlNhAnGBNg6EQqQyaXQyGTGHWFuXNVNRaduLiMeyL4o6k8DFdEpSrlEsMLYVbW2djdu0BTibGQuuUKJWguMbKk2oLDqMYbSXF8zMOUL8biSgvLaq3ct62DL+3s5b6tHdQU6dk34GR37zydFWauaCwW0M9xL6F4iuYSA3v6JDQK8bezOSCXZXGVhQqrFpkkMeKM0Fhi4N1X1CKXCRD2sDPE5fVFlFm0uMIJFDIZr1xcoLvSzL+8azmxZKZwIhs1CmSSxKwvynVtJZwY9zHujjLtE9YrcnBiwscL52d51xW1NNgN7OyZY0WtjZZSI1qVjK1d5bw25GJwIVwoEEuMai6rt6FSyFjd7GBP7zyjeVDv+o5SHCY1C4E49zx1nglPhM9v68CqV/Kr45P4o0kqrToa7AYsGiVXN9nRqRXc9YSwMl6aup0Y8/LwLV1c2+pg/4CTRCpLMiPk7jIZXNvqQCOXsWlRKWqlnFU5UVi8cnEBi04JCKbP0EKYVXU2yswaPri2kaVVFlzhJPV2A75oil8fm+DIsIu7N7eRzmYZnA+xsaOU7UsUjLjCvHxxgRfOz5LO5IT0trOMkxNe3r+6ni2dZRg0Ch4/NYVZp2RRuYmfHBln3BOhzKShqUSPTiWi6CVJwqRRsK27jAuzfpZUWSkyqLlnUyuv9DuZ9sVoLTVyVaMoZn52dIJYMsOZST8P3LyID13TJOxbchneCLzvqnoRs5sTaXEX50KsqBWqtAd29nF6UiQf7e6FvX0LPHhzp0gWycuVq206TFolOpWMz21tx55XZh0bFfG4Ro0CZygu7GB1RXxj7yB9s0GSGdGIaCszcfemVp44NcUTp6ZRK2XM+GMcGHBx05IKVAo5SrnEixfmOT3pJ53NcU1rCa/m7Xl2o7CsChZRnNOTPjZ3liGXSbzrcjGdebXfiUIu44XzMww7w8hlElqljM2dZVyTb/iurLPx3tV1LK+1icS+RBqrToUzlGDMFRGpNjkBtv/OHUuJJdPIZTLS2SwWrZb5YAy92sBz52Y5N+WnxKTh+vYSVtXZKDKo81B5XR7unsGqUzG0EEKllPHx9S1U23S8OuDkV8cm6aq0sL6jhA+vayaRyuRTnlLc9cQ5LswGkQHHRr2cGPPy8eubiSTTBWDn2hYHr/SLOHWrTsWm/DSwZyZALgdVVi06lZK+uSD7+p2847IaemdE8tIjuwcYd0eETz+Z4fFTBr56SxeHhlysaRa8gFf7nUx4BAB91h8nnRXQ0509c1zeUESTw0hnhZmemQBKuazAVrnriXOE4mksOhXZXI69ffPctbGNbd0VPHpyikQ6y5QvxtFRDzctrsAXFe932BWhxiZA/Tt75vjpe1bRVmbipd55QERiX7Io1xTpUMokZvIFu4B59nLj4grWt5dSadVSlI93r7RqC24ltUJGKJ7ON/6N+KJJVtbZeLV/gYH5MHaDqnA/uTgXYm/fAjcuLuf1kTGSaWFfeTMzwqhW8PgJUVRbtCqePTPDiTEvd29q5cJcgEgyQ4PdgAwxuf/kE+dwh5I4jGoh6+9b4Ou3diOXpD9q6vf7pobBYPq/dG/9y/q/v+KpzJ89wTidFdf2FbU23r6qmqdOz/Deq+qotOk4MOji6TMRaot1bO5UYDeoRZplIo0/lmLSGyWaTOMwqYkk00SSEIinqLCI8Jkl1VaUchlLqi20lZnY3FlGsUGFw6jBE05wZEQ0ae5cWU2NTV9QEWTyjL8cUGbRMu2LcmrCx7VtDkwaJUMLAlb+qSfPMekR4GytUs5rw27u2tjCfVs7CCfSIkEtleHJ09McHnYXlDf+qNiAvdQrNtrff8dS/u3wOJVWHbevqOKF83MMOSNUWLSUmTU8c1aoJKIJMSDzxwTSYdwTYWNHKcFYilKTFkmS+LfDYxwYdPPtty3m9KSfq5rs3P/cBTrz6tKbl1agkMkYWgjx8rCbLd1llFs0bOsqx6hRsGFRCScnvAwuhAnFU2Tz3Mi1LXYkCT56XVNBTdVdZeHMlJ9gLFUIafFHUxQbhfV5x9JKrm110Gg3IJGjukjPC+dnGV6YodFh4D1X1aGUyRhaCLMQFMl4Vp0Sg1pOOJFmyhflSlkxz52bYfuSCh7KW4mEgtfI2rztq8ysYcgZYuOiUi5rKOLiXJAtneXoVHIkSVz3t3WXcXDQSTiRIYsIblErVLSWGUmmMzz00kW+sK2d+7Z1cGDAyaRXpB6vrLPl0Rwu/jY/FHjs5BSrm+2UmTQFtWsiLep+ECo0uSTA7r5okmKDmnA8jUGjgByFPUC5RVgazVolD+/o4sCbBgWrm+wUG1WkMznCyQwTngjbusopygcExVMZ7nn8PO+8ooajo166Ki2cn/bzw4OjhXrVrFUy7omQyWYxahSEEmlyOaFoGnaG2bSoDKtehVYl57UhNzP+OOFEGl80Kyzz6Qx7Ly5wQ3cFr/Q7sWiVbO4qY9tiESq08/wsy2qsvJi3HipkopljN6hZVmPl+fNzVFh0mDRK0MCWrjI2dZZh0SkJxVMcH/Py7FmhllndXEw6k2PMJZL2BMokTi7vLDg/HcijIHI0OAyMuCNks+Kzi6UynBj3smNpBcl0lt29Cxwd9ZDO5FDIpYIVd/+AixsWlzPri7G+QxznM/4YEqJWW1ItLLGxVBqTRokum2N1kx2ZTCKbEQEuZRoND+/oLljaaouE7cwVTmA3qnny1DSSJDiPwXiKh17sZ8obJZXJ8fqoh0ODbr68fRHfftsSBuZD/PjwGH99ZR0Pbu/EG06wvqOUo2MevOFUgfv622qhP8RW0qkVKPOMzzcPnj61obXQ3PlddcKldL/fXol0ln0DTjorzYV9c5VNh02v4snT0wTjaZRyiVQ6RyieYiEYZ/eFeW5dXlm4lpaYNGhV8kLieS4nWLYN+f2QSiHDKhd1kzucRC2XF5JN/0vqpT+wflsVBp6CC6rqj1Cd/29af2lK/Q9df39NIzesaKTsD/hI33xi+vIpWZfWJX8viM1aMJbiA2sayGShyqJFIseGjlJW1RcVFDxymYRCktg34KSmqBabXsXVzXaubyvBbhIb8mQ6S0OxAYNGwd2bWjk35efUhJcrG+zUFeux6JQMzAeJJDI8tOsiw64waoWM/rkQu3rm+NTGVj67RTSkPvXEOUZcwpPfMxPg1ycm+d6dS/nSTYsYXAixcVEZx8e8eCIiJnnWF6PJYWB1kx1ykkircggmkDMQp9io5upmO8trbCKBLZPFblTjiyQpNoq0skgiU4jbrbbpWFVvo9SkYcofpb3cwoFBN8G4uAlbdUqMGiVKmYQrnCika61tcXB01M2+fqdQgqyo4uEd3ewbcDLuidJQLCLqTdp8LOzzvSwE4qSyOU5N+jk14ePeLW2MuMKcmfRz+4oqyvPpba5QgretqKa5xEgynSWVzrGsxsqPD4+9pSGlVshwR5IcGHCxpsXOpze2cmTEw4Q3QqPdwFWNxdiNQhY85Yth0amw6VV89LomPrKukVl/jEAszckJLzqlnEAsxQfXNtBaauTJ0zOcn/bTWGJgXWsJbaVG/vngKPv6XWxaVEprmShsJElIW+1GNStqbZSaNWxeJKxRnZUWSoIJTk36WFItOEcD8yGW19hQySVqi/TcvLicBoeR2YDw9A85w7SXmdi0qJRv3LqYaDrDe/7tOIurLVzfVsq1LQ4iSbHBfm3YxfnpADqVjA+ubcCVT9Cb8ESoyd94ZTJJFKBGNaNuwZ3oqjDzSr+TUXekYA241NzcP+Di8oYiBuZDzAdiXNcumjrLamy80DPHiDNMo8PAujYHLWVG2ktNvHLRSUupkZ09s/TNBtGp5Jjkgmc25Ayxs2eONc0OdvcuYMmDSPvmglzZWMz+QSc3L6lg0hspSJ/teT5VDnGDvTTdSmdzzPvjaJVynj49w1wgxlVNxfz1lXUo5TJGXWGygEIGn9/WQW2RnlcHnOzJN3zXt5eSzeXY3TtHLidhkkkUG1TUFOvyiqM4DoOGSCLNa8NuZnwxKm3afKqdgly+MZbKZPnbNfVU20RDedITpbXUyObOMj6/rYMvPt+LJyxg7xadkkqrlrufOs+YW3AuTk74ODHu4ZPrW9Gq5Ez5ohwZ8XB2yo9SLkOpkGHSKpj2RTkx4eWG7grOT/txmDR8ZddF3GFh1/RGkpyZ8vPx65u5aXEFT5yaJpLMYNXJiSQyTHvFzbul1MTjJ6cYcUWIJAimiFMAAQAASURBVNKkszlk0hvT185KCwcHXbz7yrqCyuyStVAuk8Sk1hnmuvYSzk372LiotKDGWlln45V+cc5XWQX4XyZJDDtFouDmzjL0ahnvX92ITiWKlUu23kgiQ4lR2BOVcokpb4yzUz6uay/h6TPTzPoFJyuZzmI3qFjXWoIyv7E6NuYlkRbWlqMjHk6O+7hteSVXNAg+xeX1IrHIqBaRzEq5jJq8KnH/gIsNHaWMuiIFWPmlDS0IjqFKIafUpCGb4y3MCLVCTjCexhtJsm/Ayap6G/98cJQRV4Ql1fNc1VTMwHyIbd1l2HQqjo17mfXFMOatNSAYcABzgRgHBt1/9NTvUsJOJpsjnsr8zuf8Zf1lvXk9c2aGTUvVf9ZpskyScIUSbPvuazz1wSspNqqpKtKJJD5XRDClgAMDLv7lXcvxBpO8Nuxmw6JSXrowjyec4Lr2Enb3zjPmFmp1fzRFa6mRlXU2JAk+sKYBtUI0PCY8ET7/rFCCJjNZpn0xMtkc25dWcmjIxcEhN0aNCBJQKWSsrLWxp2+BZ87OcGzUyxdv6uD2FdU8cWo6rxTRopCJ837WH+P4mJebllSQywmLb3WRjmFnGItOJI9N+2KFzXLvbJA1zXG0SgUfX98swOMyiQuzAaZ9Uax6FcFYkpsWl7NjSQWOPMvzpd55nj49Q22RnrmAUBRc1+YQzFKTlhFnmDl/HHcowbgiwhduWMShIRfPnJmldybIrcsFF7O2WM+kRwwWOsvNxFMZFDIZn1jfwp7eeUZcEeqK9WxaVIpSLuPfDo9yVZOD9e0laJUyrm118NqwOx8OQ8Hqd0VDMY+emKJvNshDO7ootWiY88X44gt9TPlihONpio3qwv3PYVLjy/NjgvmmIojBTCabJZbM8vLFeT52XQt3rqomlsoSiCaZC8QpNqiY9EZ5cNdFaor0fGFbO41d5XjCSXaeF1DoErOaTYvKeOTWbj71xDniSaGeqbJquay+CLkk8aFrGommskz7g6xtEazKaX+MPb3zvNy3wNIaK2VmLZ96QtSUkUSadW0lvHB+jnhapNP580DpG7rLyZHjrifO0VkhUqCfOyds4Y48d8ymU7Gyzsbjp6bZ0F5KiUlNe7mJpdVW3OEEvzo+ybQ3yt2b29i+pIJkJouEhCSJtN5nzsww5BLH1YQniiecYMeyKvb0zjORB0O7wwkaHQYuzAREg9WsIRRPk0xn6a62YDepmQ/EsOlVTPtiTHojxNPiswnG0yLgxSvUXGtb7Lxy0UmRXkUgluL5c3M8eXqK92uV3Lu5jQODLgYXQnRVWriurYTzM35OT3rZ2tXBz4+O845VNVRYtTx7dpbhfN13TauDFbU2Ki1asS+Qy1hSY2VwIYQ/liKXtzMm01nqikVS29mpAIurrLx4YZ4c4IkkUclluEKiqSlJEoMLIRKpLHq1nBsXV7Cu1UGRQY0s36B0h+O0lZu5e1Mb+/qdzAVilJk1rO8oRauSc37aT6lJyxef78UfS6GQSSTSWWqL9Ny/rYNSs5o7VlUTT2bwRVJ4IgmaHAZMGgUbO0owqBWsqLVxYFAIHC6psKxylWigjXnZ0lXG0EKIZDrLc+dm+MINHVTbBNf34R3dHPoD/KP/iJH0+wZPl1KSf5c6SIQX/Pt0O3hDpfXbSzhsBMd0LhAjlRE1yYXZANeEHQTjaVLpLKvqRGrzpSCIUrOGxjwP6+Cgq3AfAKixCRv3f6UZ9R8N536XKgwouKAupQj+X1l/aUr9D123Lq+i7D9I3XvziXly3MvaFgd7+hYKMb9APiLXQTKTwW5U86tjE9y0pILqIqECOTjoYnA+RHOpkRsXVxBPZ1lWY6V/Psgty6oKzJBRV5glVVbWtTlIZbJ865VBbHo117U6WAjGeWBnH7evqGJDRyktpSaePTtL33wQo1pwB6JJIZc9POxix9IqHj0xiS+apK5YL6x5AEi8Nuzm5qWVdFZaRNrFzZ28nOfFbOsuZ22zg0RapLFN+qI88lI/4x6x+Upncxwb83L3xlZ8UREPfOuyqsKNs9io5qO/OcOUN0ZlXmn1ysUF7ruhg5V1RaJhZ9WSyeaotOpQyiVC8TS+dIYysxaFXMhR73riHOlsjlhS8GR2XZjj229bwopaG0trrGgVMlRKOXqVgufPz+IMxklnc3jDAuanlEscGHDRXWVBLpO4Js/PmvHF+PLNndQVi0bbqCvConITGxaVisLJOkUwni54ysnlGHaFWVxtoWfazy3LKsnkcvgiSRZCCVIZofQwapTs6ZvHExaf95WNxcSSGU5PePNyVA1nJn1UWLV5BZGPQCyN8qLEyxcX+MrNXaxpsTMXjKFUyJj2RUXqojvCtu5ybl4ibqQX50I8f26W587NMpW/gH5kXSO+iAC0V9l0+KJJZJJENpdlc1cZ3nCSTz5+rmCZerFnjiMjbh68uZP5YJz5YIL9/S5OT/jz33GWt62o5rbl1Tx6YoobuiuoLtLz6SfOk0hnkUkSR0e9HBxy8fmt7VzT6uCxk9M4Qwmua3OgUcoZPTVNMJYqWJty5DCoFfijSdpKTTSXGJn2Rqm3q5kPJvjqS/28Puollcnyar+TvX3zfPWWbhwmDRfngqysszHqEpYqmSQV0n5SGWHVWN9eiiE/hZkLxHHkm2S/PjZJR7mZKqsOs1awsy6l9wGF8+JSalOlTVgKnzs3w/03LMJhVBNNZjBrhTLqpd55tnaVFRq+o64IJSYNvbNBDg+7+eA1jVzXVsqBAVe+6SJjcZWVZ8/O0l5uosoq5+9/dZqBBQFczeTtct+9cwkKuUR7uQmVQjQUX+130l1pYUN7ieA2SSL9pO1vLmfSE+G69hJiiQwHBl2MuMTk/BJ7YtYf5/VRD1s6y2gtMfL8uTmsOjG5NmoUZHM5JEli1h/HFRIg19298xwcctNcYhBqQAS34PCwm+vbS3jq9EweMiw2UM2lRrI5Uej2zgYBiCYFdFaZt4mOuCOs7yjlyLAbCSFrPzftJ5bMFNQHNr2KZbVWys1aJEShfM+mVia9UZZUW6jLJ5WeGPOyb8BJKpPDoFEw6opwx8pqllRbcIcTPHN2hhFnmI4KM6vqbNx3Qwff2zdMOJFGIZcoMYpJ4bIaG99+2xJeH/XkG+diomjTqxh3R7iisZhDQ27mAqJ4BKgwa7i62U48leXcpA+dUs4/XN/MqQkfI84wdXY9y2uszPpjPHVKAIqbSwxcnAsSiqeFqioHSEKdm8lkuabVQTqTfQszQpG3X0gSjOaP6yqbjnBcBCvUFOm5a2Nr3uLtZlm1lQe3d/Kjg6O4w8Jud+PiCnLAAzsvMpNvUMnexD78XVO/35auV1i1LCtT/yfvqH9Z/19bT52e4cx84s86TdarFazvKGVnzxwTngjtZSbBkXFHCowdgLlAnFBcBIEsrraQzubonQ1yfMxDV6WZr2zv4sCAkxFXhLYyIxsXlTLsDPO9fSOF4VEir6I4NxVAJkGFVYtVp+Jnr4+ztauMz25t59V+J9O+KA6jhpV1Npz5yb9ckrhxSTmeSBKjOsfFuQDRhFC/ZLI55vwiufPMpJ+tXeXEUmlcoQQmrZJGh4G+uSDBvO1XIRMDqHq7noVgggszAa5vL8FuEODmSw3sWN5KWGrW8ty5WUbOzNDgMLB9SSXXtDhwmETi6XfuXIJcktEzLZrwj56cYt+Ak+1LK/ncMxdYUm1hS1cZ17eX5JN3Zcgk+MGBEX5+dIJqm47r20vYtKiMzz1zgZV1Nq5vL+H69lLCiRRalZzv7R/mF0cn+dGhcTQKGfduaeOmxeU8vKOLYB4Inkxn0KlEuMaZST/xtAjBuKG7nGfOzbJ/0IVFq8SkVXJtq4NX+52k0lluX1nFiloberUCVyjB8THB8FvTbEcuk1hUYeLOVbWEE2l6Z4O0l5sK6aP7+l08lR86zAbiDDnD1NsNfPQ3ZwjEUnm1kBjUfOnGRXztlm52XZhncaWFNS3CNq1Tyqmy6bj/OcFwlCT4zOY2eqYDkIO7NrbSUmrEH02yolawhnb3ztNSauSLNy3i2JgHdzCBQasQA2ejmp8eGefUhI/BhRCLKkx8ZXtnHiAdp6nEwOIqK9O+GM+fncWoVnBlYzHv+vEJEulMwVKqkEmF78IdTuIMJfjKrj6e+LsruKyhiMsaiijSq9jWXcbnnu5hRZ1NJO4NiVpXkmBbVzlnJv30zASwG1RYdSqqrBo2dZRi0ijQKvVksmJ4l8oIDpqApot/JWYNMsCiFQOxhVCCbDZHf/5e9/CL/WxfWsnmzlLuXFWDQiYaMJNeJfffsIj5QBx/NMVcMM7X8urqaDKTt+B7eGhHJ1a9Cm84yUwgxqo6G68NuXCFEyBBJpOj3i5smq/2L+AJJ7mqqZhAVByXkUSaqAQWrYpUvtlbadWiUcn40o2L3oLo6KqyiOZhNM3mbx/k+rZS3n1lLcUGNQq5jEgixXt/coKPXdfM7t55Toz70KnkVFi1hOJCube3f4FbllViUivRKuQYNSKV8MyUjz298zTYjdy+oooSs4b5QLxwncvlRGhAKJ7iwkyAa1odrM2nAGuV8kJTDkQT6A9xk/4QI+nN67cfmw+IfeWlZsxv1wn/mXS7S3vlbE6wzS41pECkdbtCCYadIVbUCqXhgzd35mtXMShf31HCnD/OgXxT6g/9rT92/bGWvN+nCoO3pgj+X1l/tqaU3+/HYrH8uX7d/+fXf5S2B28FwR4YdNFWZuLBmzt5bdiFN5IScMjGYpRyCb1axa6eCX58eIw7V1VTW6QvWEjU+ZSsvtkAH7uumbpiPeenA9iNKb71srAkKeQSQwthnj83y5duWoRckvHdV4d5sWeer9/WxV9fWceaFjupTFZAlSe8ojBTKygza4gkMmjzihy9Wkzci/Rqwok0oXgKhUwoJCa9guWUymT519fGsGiVXN5QJJQv+caTWiEnC/mo1TixpJj8SBKcHPdyaNjFtq5yfn50An80RYNdz5oWB9FkmlgyQ7lFUwAU58hxeMjN6qZiJEliTYudly8uMOOPMe2LCWWY3cCKWhvxVIaDgy6mfDGqbTr86RSZXI6+2RDPnJlhSbWVf3j0LBs7SvnkxhZkEvTPiRQqpVyGVa/CoheyzzF3hLWtosF3Kb3tUhrc3U+eZ9wTJYeYXp6a8PHx9c3csLiCPb3zpLNZIvkCs9qmo9igZm2LA0mC58/M8Kvjk3xqQyuheIoivZq7nzyPK5TArFOyu3ee/QNO7r+xgw0dZbw+6uaaFgfNJUYePzXNqDuCSiFHIo1Mkhh1Rtg/6GR5jRWZJBFJpHl4Vz8DzjB6lZyaIj0NdgNWvQqjRkE8LaTXGqWMCouOa1ocvHzRSYVFy7o2B7t65khlRaFr0ar4zYlJRl0RFHJJfL/kODLi4cCAi+V1NhENnRMX5kBCpNkMLoS4cXE5D+/oRqeSFwCmJo0CuVxGLpfDG04y7olg1Qm+2UIwjjovE+6qtHB4xJP3tWvJ5sSevMKqZS4Q5+S4lzUtdtIZMfGeDcSpsmkLChpfJMWZST+1RXrKLRrc4QR1xXpygEwmmjnpTA6jRkGTw4A3kkAuSfhjKapsWq5tc7Dz/Bw54NWLTrYvq+DwsJtsLsfxMQ+bFpVxoN9JIp+25Akn6Kwwc1l9Ebt75/jslna0Kjm/PD7J4HyIpTVW1rWV8LVbu1HIBH9qxBVBoxTnVCqTZdwT4fSkj/dcWYdOJafEpGFFrY0xd4Rnz85wfXsJB4dcJDNZig2i2XVJdv/KRSdrW+ysabbTWSGYZ9e0CMvowWiSumIDVzQU4QoluDgXZFmNgNDL5TKePzdbYB4YNQpSefXXqEvw4uQyidZSI6cmvIV0KZVcWM6qbVpm/HHKzBoReCAJFsGlptIl2P/VzXZAgDZzwKo6G2tb7Jwc9wASdXY952f8aJVyYnkorFySaHYY8EeTlJqFQmxTZylnJn0EoikS6QzFRjWNdgNXNhSzp2+ecDyNRavEYdIgl8vY1TOPTiVnUbmJd15ew45lFfzm+BQHh1wsrbZgVCuYD8b50C8FJF8CTox7ebFnlns3t7Omxc7z52YJRMXmr7ZYXygwtnSWoZDL8EeTnJ/2M+WNckVjMRadio+sa+K1YXfB5ntZvY05f5wT415uXFLJlCfKgQEXGxaVsLmztJBGdHDQxaIKM6lMlm3dFZwc93Fi3Ff4PFtKjKzvKEGlkGPViWlrvV0MRi7ZATVKAXdvsOvxRcXU12ZQsajCjEIm8eTpaY4Mu0lnc+zqmeOeTW2sayvhV8cmsemVbOgo4dCgi3FPBG9+amzUKJnyRn/v1O+SdP2SrSAUT2FXZ/m/tv5SQ/3513/HNLnCouUn71mJWikTibb5tLM3Q8eNGgVGjWhafPrJ89y9sZVyi4YpX4y7njzPX11ey+X1RYW0MatOxclxLzctKWdVXREX54M02g0MLYSQJPG7RSqrilxOpPl+6JpGdiwVqa1Tvig7z8/xzJlpwokM776ilhKThk8/cZ67NrYUUAbeqIBm61RyMtkcHRUmJEk039e02Dkw4GRdm4Pe2SCnJrzIJHGNrrfrWdvsYF+/k1CeMziVt4xt6Szj0JCblbU25DIZ9z3by2wgJjbzox6OjXr4yvYuyswaSkwaEqkst37/MFu7K/jodU18/dZuXhtykUhn+MZt3bw+6mFfvxOrXsWmRaWMuITtqL5Yj1YpJxxPc2TYTUe5iS/dtIiT41729M5Tb9dzdbODwYUQT51+AwxdYdWxqs6GSiHHG41zcMjNpDdCmVnLFQ1FRJMZkmmh7JnI8/XWNNuZC8R59uwMvmgKvVpRGLYk0zkG5kMMLoSosGrZsaySUpMGtUJONJnm+29fRiKd5TfHJ7msoRhnMMF3Xx1id98CTQ7BH60t1pPOZCk1azg05GLUHcGoUSBJElU2LSPOCK/0O9mxtIKlNcLWOeWN8p1XBrlnczv7+p1cnA/l02ZlnJrwcceqahaCCfb2zbOv30mRQcVty6u4ttXBd14d4lsvD7Gls4xrWh3UFutIpkUCXiCaon8+hFIuI5HK8rlnLvDXV9WxrMZKVZcYmP3bkTEODrqQJImpvOIkkh+o5BAb7ERapLpt7izjC89f4DtvW8pjH7iCUDzN4SE352cCLCo3s76jhC/e1Mm9T59n+5Iq1rba2dJZRpFejVYl575t7RwadDGRHx5fVl+EO5zklX4nVzUWU5Uf1DxzdoahhXDBhtiQdwjI5cKeuKWzjEAsRZFBzbuvrMVuVHNg0EljiYFwMsPOCxO4gwlaSo1c2VRMPJnh3w6P8eFrm3jlopMpbxSZTMKsU5LO5JgLxhn3REln4cO/Po0EfPjaJu7Z3FYYnNcW6bk6n8q2t3eBt19WQzqTxaBRFBSKzSUGrm620zcXYGm1levbS0hnc28ZJqqVYk92YtzLh69t5OYllRwf8xaSKJOpDM+dneU9V4rv6eioh5ZSI5GESEPWq+WE4mkm8gm8Sr1ocviiSe5/rpe+uRA6tZyzUwH2Dzr5yvZOVtXZeOWiU9jbMrmCmqjCqmPKG+WnR8a5d0v77wwp+WOurf+Z6280meaVi056pgMk8zWhUaNk0hvlwKCTW5ZVUWbR8JXtnSIhE1EbapSytwDXL6mQVHIZa1vsHB52sRAUNksQjfZLCqhQIs26NiU/eOYCa5rtrKi1sb69hEAshU6lEDD9JRX/uUS8P7D+WEven6IK+9+8/qSm1MMPP0xtbS233347ALfddhtPPvkkpaWl7Nq1i+7u7j/ri/zL+v3rzdLIM5M+VjfZefuqmvwFMMsL52fZ1SMieH0REVc+5AwztBAmlEhjN6ohr0yY9sULk6LWEiMvnJ/j/HQAo0ZMZ/yxFBP59LuNi0p5+eICgViSE2NebllWxbQ/yp0/Oso3b1tCvd0AOXFRCOX96a785l0pl1FbpOOp03GSacFBUsplRJJpyvMJeZ6wiDz/10Nj7BtwFqC5+/Lsqg9f28i0L4pcBtq8Fz8YTaOSy5j2xvBEkvzgwAiZrIgSfn3Ew0eva+bmJRW8eGEejUKGw6gmlVcDXNPqwJNvHnzppkW8dGGe3tkAW7vKWVxlEeoNJJyhOBqFrBDfTk5wJkZckQIrqrlUvPeLcyFsBhXeSBKlXEYgJqYiuZzwOWsVMuqKDQV1THelhf15CyBANit84dP+GEdHvaxpLuZXxyZQK+SYtErqinRc2+rg4lyQIyNuys1altfasOrVOExqslkRyzvkDFNlE0oPo0ZB/3yIXT3zXN/mYHGVlXg6S5lZkwcfwh0rqlhSbcWmV+EOJ3CGEpSaNFj1Kp49O4snmqTapuWDaxuxG9U8d26WcFwk/922vIqtXWX0zQZZXmslmsxQbFDx+W3tFOlVTLojbFpUxpIqC8q8D18uk8jmKMiVs7kck94o69pLxOeQyzHjFw1CuUzCYVTnI3i12PRqnj07W/B/p7IZgrEUn9zRgt2g5ukzM1ycC2I3qtncWYZWKWNTZymnJ71MemPIZQLqr1bKWVlXxM6eOfb0zrNvwMnXb+tmxi/k4KlMFr1KpOVIkiQin2Mprm0t4dioh7UtDp4/N8e0L4pSLkMhl6gr0nFDdzmzfmG1s+lVXNFQzHwwxqEhN0q5jNdH3axrd3Dv5jZ29y3gDifQq+V8586lHBxycWLMy+bOMnYsrcQfS9FRbsqnyCToKDczH4jzT/uGOTrq4bNb2tGp5ezqmaPUpMGkFa9VIkc4kWHMHWHH0ko+uq6ZdCZL/3yI/vkg71tdT22xnl09c8gkAenXqeSCMRFJcmbSx5UNxVhNCuxGNeOeCJ9+6hy+SBKzVsnjp6aptOh45NYuPJEkX9szyGe2tGHSKKl3GCiZElPNUCwFkjhf6+0G0tksrw176awwk8nCuCdKuVmLVikA6mtbHJye8BFSy6mz67BolZDLoVfJ8ckkfNEkFVYtRXqVUORFU9QW6VjTLKbyKoWIPm8vN7G6qRitUsF8MCaS+vLAzpPjXq7Lpw/G4xk+uaGFwyNuBufDNJUYWFptpW8uyLf2DmLTq9AqZaxutvO5Zy/wzlU1lFu0PH9+jglPlMVVYsK/pMZKk91ANgd7ehfozzekQCRIymUSB4dcrKyz8WLPPIm0YJwsrrLytT0DSAil7Bef7yWVyeKPpvDHUuwfcPHQji5qinRU2qpQSJJQ3B2f4tETk8RTWZ4/N8fDt3Qx7o3wzwdHefcVtQRjScKJDC2lJq5qthOKpTCqFdx/Ywd7+xYKwQnr20ux6VU8enySM1N+PrOljQ0dpeztXSCUSCPLBzgU5W3d+wdcpLNZysxaVtTa+M6rQzx6Ygq1QiR7+qMpDg65WFVnY3fvPEq5aArP5afR4UQaCYlwIk2ZWfs7p35vlq6/uVB2+yL8b15/qaH+360/5zQ5lckyH4wXOJ4mrZLOSgtHx7wFVc+lZCyZTCS4jrkjvDrg5OYllbzYM8+IK8zjJ6d5uW+BdDbHd+5cAsA7L6/FpFGy8/wcX97Vx7ffJuqobN+CuE9lc3nVkoAEyySQS5DM5HhtyM2vj0+iVsgpM2tYVV/Eq/1iWHNkRASd7OqZY8QllB8Oo5oKi1DRv9rvJJbMsKWrjKubHcSSaT63tY09fQv0zgRpsOvzYSYJDgyK9zHhjfKJR8+yY1klty6v4pu3d5PLK1qHXWEsOsHZEVD2FIeGXNTb9fzq+BTvX12PO5IqNNgqLFo2dZYhk8TG9eYlFW8kLsslFDKRLLilq4xjY17OTflJpLP866ExbuguZ8eySrLZHBqlHG80icOk5m+vbmDIKRiea1vsaJVynME4dz9xHnckSSQhbMj1dj0P3tzJVU3FHBxyYTeKpK1jo15uW17Fylobn32mB3cowcbOMuwGNR/59Rmc+RQ3hVzG2Sk/923roNggI5nOolPLebXfSTSZwW5UYdYo+fj1zdTbDRwYdOKPZoilMqgUMoryVjSZJN5nIp0hnclh0SlxBkVt9K+vjWHSKNm0qIwPXtOEQi7RPx/CF02Sy0E6k8UXTRKMpfjW3gF6Z0MYNArC8TQ7e+b4yvZOLqsvYv+Aiz19CygVEvGUjUNDbt51RS3eSJxGh4HdvfMi5Cid5blzszx2coo7V1azvNbK4yenSWdy+WGjFoNGgVopKzRJxOuXqCnSoVHK+dyWdhRyAZ+///leXKEE88E4r1xc4LVhF1+8cREP7eji8JCHoYUQ5WbRNH3+7CyXNxZxQz58ZGA+xM9eH+epM9PEkmJA/MN3LsOkUfLQ9i5e6V9geEHY69a0OADBSW2wG3GGEuzqmWMuEKel1Mh17SVc1VSMTCbxqcfPMeOPUWnRcnLCx87zs9y7pZ0rGkSdNuuPFWyevkgSVzhBOpvDrFVyaNBF/3wIh0HN9/YP89Hrmti+tJJr8xbNx09OcWrCR32xns2dwkr6079eSTCWwhNOYtIpcAbF8HN5jQ2HScM7VtXwxKlp3OGkYIlqFCjlEjO+GEdGPLxtZTV3rKxGKZfhj6QwqOXcuKSCWD58yqxT4o+mMGkVheF9LCnqoWxWJGXncsLSfHY6QJFehSTBrF8EEu3pXWD70ko0SsGrTGaypDK5tzRtZvxxDr2pwf9fTYKLpzKkMsLdoMqjGy6tZDpLz4wfXzRV4HQFYinKLVqGnBGh2E7B7t4FWkqN6JRyjox4mAvEqCnSs6WzlEA8zYG8CunSY/duaWf3hXnOT/vzijY7C/kEzu1LK9Gp5NiNavb0LbCnbwEQiqjP5BtF/9kkvT/03v9YS94fSiH+ryi1/qeuP6kp9YMf/IBf/vKXAOzdu5e9e/fy4osv8thjj/GpT32KPXv2/Flf5F/W71+/TxoZT2V4+swcj50UE6NJT4Q1LXbWtTloLTWyp3eBdEY8X5YvdLK5XEHCadWrcAYTmLUK5LI32DvyN1k3CokvwTgKucTTp6dJZyic4C/1zDPmEbHABrWCJVUWVjfZUcgk1rQI1cz5mUCB3VJh0bC6yU6RXoVOJae11IgkQTKVpdKq4+Hd/SytsnLD4nI0SjlVVh2v4y2kg8hloFEqKDFrCjf6nATBWJpJX5TXhkU6yq9PTJHIpz+ZtEoa7HqUCol9/U5++vo4+z95Daubi9mxtAJ/LM2Tp6fpnw/xoWsaqbbpKTNriKezmLTKAqem3q7HG07kpc12Tox72T/o5JalVbx0YZ4JTwSyglfTUW5iXZsDpULGo397GYlUhvYyI5FkhufPzRa+20vqkmw2x4Qnwg3d5Xx0XRNjnij1xWLzPe2L8p1XhkhmcrhCcYpPT/PgzZ1olXJUCjnDzjC5nODBpLM5pr0C4N47E2B1UzH3PH2er9+6GLkk0VJq5JoWO6X55t+wM0y9Xc+WzjJKzBrCiTRnJn3EUhk2LyqjxKThnqd6CCfSBT7NwUE3n9/Wzk3dpSiyWZLxLE1NJuTpCFl3gAdXFTHvCfLayR5aAjZWRJwMuUbJJtMocxkUuSx2jYzLht0YE0NsGhli1hOmOZEmh4TDrOWmaT8njvgxaJTUt5Swec6HcsCJXC7DH8+wrK6I2otpfnlsCn88TUaS8OYkAq8bec81raBRc1enkZNzcqYiGSwWPUubShl1hfnF0XESaQHX9IbFVPnSNFIhF5HAVzQUcfuKKtRK0djcvrQSbzTJP96xmMPDbhaC8cLETC5J6NRy/m5tI75okqdOTbNvQKQGhuJpKqxahhbC1BXpubpJROBqFHJkMti0SCSl9c8F0arkJNNZjEUGHj85zfnpAHV2Pbfmk+3ue76Xly8u8LYV1XRWmLkwEyCVzSHlcvmNkkRT3hY4H4yTzeaosGr5+2uayOSbT5dA2a5wAgkwaZVY9SqW1lgxaRW4QnEcJg2vDbmZ9EQptwjmQyKVFYymQRcram18f/8IL5ybZUNHKYurLOy+MIczlMjzk2SYtEpW1FrpmQlQXSSaTY/c2sXpCR+z/hilZnEdiKcy1Dv0SEisbXZwdtLPwHwIdb4wLtKruLyhCH80xdtXVZNDYj6QZ02kMkRTaXQqwWXqmQ4wuBCm0qrl3VfUUqRX4QwnWN9egs2gZs4fy0v3k1zb6uDmJZW4QnF+fXyKl/sWsOhUSJJEnd3A3t4FllVbKbNouPvJ84zm44+PjXk4POzmM1vaUCvlZHM5ht6UIAoiNUuvluOLJMUx0lRMsVHNqnobYy6hWvvuHUvZP+BkPhinSC8aenajGk8kyd6+BS6rL+LkhI8rG4twhxO8cnGBeJ4heImVdVlDET0zAebzrL2fH53kxQvzqOQySkxqPr+1jSXVNm5ZVlmwagKcmfSSzuV45+U1SEhUWbV8544lHBwSDLf2chPX5FWn0WSaW5ZVcn17CXOBOC+cn0UmSaQyWZECqlXiDSepKdKzrNpKW5kJm15FuUWLN5IU133pjWCOKpv23039LknXs7ncv5Pd/29ef6mh/t+tP+c0+c1pxy/1zhOIJbl1WRWHh93MBmLEU0IpXmLSIJdEcq5GIeeF87Msq7by8C1dHBh0Mh+IF9Svnjyv8l9fG+Mzm9uIpoQl7tSEj+vbSwrcHaFohBqrltVNdo6NeXmxZ56/XVPPxkWlnJ7wMuWLF1iPk16RNvfc2VkWV1n46i3dHBgQgSGL8jZio0aBVinnF0cneH3EzT1b2oilJKw6Jbcuq+TaliTOUJyd52fZ2TNXUAg4jGo+dG0jmrw6yG5QI8kkvJEUJq1QlgTy6cVapZxxjxjatTgMeMIJ6u16rmqyI88DrnVqcX8bc0c4OuJhTYsdnUrBnt555gJxLDolmzvL+NKNHezsmWfSK/hRVzfZ0ShlhGJpfNEkz52dwRVKsGlRGes7SvFFk7zaL9iNrw25C8E3wq6fYmghzMFBF1c3FzPsCrOqrohd5+d4qXeeV/sXeHB7F3v+YQ3hRBqHUc2vjk8y7AyDRCFAQi5Jgk9YYWbvxQXedUUt7eUmFlWYeeLUNN5Ikka7gQ2LSmkqMfD5Zy8QiqepKzagUog61qRVFO4L3mgKjVLGHSurCcfT7OqZZ3VjMZlclp8cGeevLqvJJ7iqcYeSSJLElY1CdTvpFcwlAJNWwYQnyisXnVzZWMyr/U4qrRq2dpWTymQJxpME4yl80STX5OvxcXcUuUwiHE+zuNrCtW0l/Ob4JO6wUPuXmPUsrbGSy+X4m9X1/PDQKDIkkKC2SMc1rSJdVYR+wEsX5jgz6cNu1FBm1hCMCUvjvgFnHq1hI5PN8fTpaZ47N8tcIM6Tp6f57p1LOD8d5JfHJpjMM6cUeVj+3r4Fbl1emU+rLGJ9eymecIJT4142dJSiU8kZ90T52G/OMOKKoMtzl44Mu/ns1namfQL3UWPTEU9nCScEr+1S/RJLZWhyGDk/HSCTFSE5svxwr0ivYswjBiKJTJZMNscP9o/ygTUN1BTrCvzFd15ew8ZFpfijKfb2LbAQEjXhta0Ocjn44nN9rG62c3rSh14lp8FhwBmKF5wBMgniqWyhsWdQK/jm3kH2XpznHatq+bu19cwFhAq7q8rCbcurePr0bEHFo1bI6Ko0s7rJLoZzMZFuPbAgmplGjYJYMlNQu12cC5LL5fjijYs4PubJn3MqAUUPJQq2tUlvlHQmx1Tod7Oe/hh2XyqTZS4Q59WLToYWQlTatKxrLaHEpEaXx1x4I0mqbLpCQyqVyZLMQDCWoiaPsVAp5BQbVEjAxx49y7QvSplZy9YuBVO+GN/aO8hCKAHAkREPR0fd3Letg1uXV3JVUzGz/hiPn5xid+88i/Mp7AaN4i38q7piPes7StAohfVSLpP+KBfTf9Sw+89a8v4jLtf/pfUnNaXm5+epqqoC4IUXXuC2225j/fr11NbWsmrVqj/rC/zfuv7pn/6JRx55hPn5ebq7u/nOd77DypUr/9v+3m8f+G8+6NUKGTqVgiKDULUY1Io8ByBHOp1DpxJQuRlfjNuXV6FXi257c4mBV/udJNJCYSUmQxoa7HrmA3EmPOLk2dJZRjSZodKqx6hRsLdvnu1LK/jV+1cRT2cJxlKE4ynKzFriqQzffXWIzZ1lfPWWbhEB67kU2+oQKRCxFP5oimlvjBu6yjHrlOzqmeddl9fiMKo5POymxKhhTYudl3rnGXa+EU1bV6Tj6qZinjglmnFWvQprPk1wIRhnTbMdTzhBNieKihKjmtVNdtRyGWPuKIFYmtMTPqQ8EO+eJ3sYdQvrkFGj4PblVRwedhWYSZV5zsP17SX4o0keuLmTEpOaR09McmrcxxUNxXw1n1Qy7okUoNBmrZLnzs0yvBCmtljPujYHZWYNi8pNvDbkRq2UiTQWJJEQY1CTSGfY2FmGViFDIReR8dGkio+vb+HUhJdXLjoZzjcH1reXYtbKaSk1sjff8Q/HUhCLUZSKszSrIXbqLKbTpxlNjVFdoeMGX4CYL8DOI0PI/UGWpuMY0gncGokqhxZHKsE9Tj8eT5BavZx4OML3AxE0mRSKZBx1OokqnUKZyyDlJdW/i/xSn/8HcHP+3+9bH/ldD/74jZ8H2Jj/99vr/t/1s1944z8b3/RwRianRaHmKqWamFJNUq3F9lMrt1mMtPvT+FGCXk9LQymaISPTz0mMZeSYi8w01pdSYzOT1Wqp0mhJGrXEc3Hks0lOu5PcvXeMLctquGNlNX1zQSLJDFqVaBzX2HRc0VCERilHJpOY8ETY3bvAs2dnKDNreHB7F4MLYZbX2ogmM3zp+V7OTQcIxFKkszle7JnnkVu62NpVxqkJH9uXVggVy6CrUCAp5VBt03JVUzHHxjy8cH6uUCCZNEqePTfLwHyQW5dXcWrCSzqTyzcBhHLxyobiwoYoksgUGtdapZw1zXaubBSblBzgMKpRyATs+7r2HONukSx5esLHmCciwhOa7Mz4Y3zphT40CjkP3dJFNpvjxsUV+PPTxktqtUwmx/03LSKTy/GFGzp48cI8gwsh2kpNXN9eQpFBRTKd5ZfHJtnTO08kmWHaF6O2SMeP3rWcaCLDh399hmQ6Szqb4+QEnJn08dmt7dTa9MRSGX6TVwY1OQzctEQkEeZyOR49McXrI260KnmesZClSK9ixBXmxiUV7B9wMewKiymxXDR2ZgNCiXV1sx29WkuTw3AJ1wQIG85CIE6lVTD9PnJdE+lMjmfOzvDEqWksWhWlZg07e6KYtSIhU6+WI5eJqem5aT+XNxTxm+OT7OqZ4/Nb27lpSQU/OjQq0kIRjakbFpezob2UF87P0o6JBrtoSKrkIqa+yKDhth++TjSRQaeSM+qO0FVh4kfvWkGJWcvuC/M8c2aGrkoLGxeVsrW7nMvri0CS0KkUGDVK/v7aJvzRJOlsllMTPmJJ0czNZkVRZtEpqSvWY9YquWdzm2h4hhIsr7VSW6xnwpO3ZCJRbtZydZPj97IgQCTg/F9Zf6mh/t+sP+c0+dJ0e8orzs0RZ1gkPVVY+PC6Rk5N+Jj2iqb61c32vEpbT5lFRNA//GI/2xaXs7bFTk2RXjDa0lnC+cHWonJhjb6yoZjnzgo245IqM//yrhVCWSMXCm2TVsngfJB/ePQs6UyOw8Nuvn5bN3dvbuPQoJtz0wHUShlLqiz0zQaJpTJ8b98wq5vtLK60cPPSSpQyiW+9MsSFmQAP3tzJmhY7O8/P8cK5OZocBt72w9f5l3etoEiv4uS4j7lAnNuWV3F1s51pXxSFBDd0l+fVU6IeumNFVV4JnmPKFyWeyuY31yKRVSmX2LG8UgDFt3chA8bdUU6M+7imxY7dqKbYoGZJtUAFPPTixQIEmxycnvDxuW3tbO4sRa0Q9sPz036++fIglVYxmN20qIwP/eo0e/uEfe3SMWDTCxC4TJKY9EYoMqgLQ5VJb4xbllfy2S3tDDvDHBpyCet0LMUrFxe4vKGI42NCOeWPJrHolMTzQ02zVins6O4ImzvLhNoplUWnkvOxR8+KcJoc1Nn1HBpy86kNLdy9qQ1nUNjOZ/0xLm+wcWTYTP9CiFAe2F1XrOey+iKS6SybFpWyrasMtULOho4S+uaCLKu1cmjIRSIVJBBL4TCqGfdEkSRx7xJNCIkyswZPWAxAbl1exdVNxcRTwpp/14ZWXKEEpSYtc4EYj9zSLXhGrgjNJQKArs/jN7Z2ldPgEKqZaW+Unmk/77y8FrlchMTUFum4tq0Eq07Fr45O8Pqoh++/YxlzgTg5BNux2qbDoFFgRMGkN0YglmLGL1Jp/+3wOHajSKWUJIVwdCwIS2G1TceUL1oYYgzl6/01eZj5tC9KbZGejYtKsRs1RJJCITMfTGDTq/JoD4nxvK19SbWFcCJdaC6k866HGV+UW5YJtVCRQc2xMQ8THtHU2tBRypYuUbe/87IakcI5LBAQiXSWHxwY4VMbWwTXNR/G4Q4l+fijZxnL23uTmSwv9szxle1dbO4sY2mNlVf7nSyrsRCOp6mwCJREOpMlmswUBjsVFi19+UZekV7Na0Mu3r+6nj29CwwshBjzRFhZayukoLvDSdrLjKxusmNQy/NqeUQATb4OUMokfOkMOSgcn2PuCMfHvFzXXkK5WUPfXIiDgy4ODLoKtUW1TUc6m/0vJcHNB+J88blejo97C0OmF87P8fCOLsotGhQyGeem/KxptgvlZT74B0S66DWtdn5zfAq9WsFtywWf+FKtG0qkWF5r5ZWLC/TNB7HqVAUo+YgrwlOnZ9jcWUosmeHctB9/LMXbL6thc2cZNr0KhewNkYeUPzZSmSwLgTgX5wTQfnVT8e9twP1HnKhLzSoQgVk9+WCa5bU2rDrBnZPg3w1R/lgu1/+F9Sc1paxWK1NTU1RVVfHSSy/xwAMPAOJimMn8JRnn0Ucf5eMf/zg/+MEPWLVqFd/61rfYsGEDAwMDOByO/yev4c0+1DXNdjK5HPc9J5KxmhxGdiytYG2LHU8kyckJL0+fnuGyuiK2dJWRzeZIZLIsq7VhOzXFqCtJLJUhnEizotbG9e2lPHFymnKLlvpiPVu7y/FGEmzuLGVxlZlKm45gLM1z52aZ8cWoK9azpsVOIp3lc89eEGkaVRZay0xc1VTM1c12srkcerWCCW+Enx2Z4Lr2EpbXiDQauUzixsXl+CJJPvSr03RVWgjEU7iCce7a0Co8+a4IjfkbaSyZ4eS4lwa7nnQ2RzieJpXJUWXVYTequXdzG2cmfTQ4RLqcKJqUfHJDCzcuLi9ceH55bJL++RAKuYRcktjTO8/VTXY+sb6VY6MeJr1Raot0XNVkx6hRUGnREk1mmPXHCmDL7+0bZk2Lg8vri9i4qBRNnmv0d784xUIwTjKT4/CIm/0DTr52azfrO0o5NeFlwhsTEGSVjNpiHbe0WQkOjXH63BgJp4uKXJw2TRqd041maoG3q3PcGggxMDyL44U01Zoc8miED0YjvNPtRxOPoknEkOfeurH7zZv+Ww9k5QruUGqIqLTE1VpSag1JlRp/woStyITBYWMYHZWNJfS5E8zGc0RlSoI5OUmliqRcSVOVjTVtZQz74lTYjfzg8BRpmQyzUYtao+LWVXUcnwlxYNjLHVfWU+kw0bsQYS6aodSmp6u2mKlQkl+dnuPTWxeRlmTEMzmCkQRnJrw8f3Yam0bBjiXlbGgrgVyWQCTB8WE3w84Q71hZxdMnJ+mZ8pHLZJGkHNFIglgkxlXVJm5qK+Ybuy5glmX5u8urGJhwse/0OJp0AnU8hiadwJZLscKhxqSVaNeFCLh9qCNB9KfHCbr91CZitCbiqJPxt3ym2t86D7fk/8UUaiSziX82mwgqtYTUOuRmM7ayYqTDJvojOVyShsbGMv62yMrtdi2n/Bmm9vp52/JGkjNzvDYRZS4QE9NZmVA2jrrC7B90sq61hAuzAdKZHO5wgo+ua+LQkAtfVBSkVzUVMzgf4uOPnSskoe29OM/37lyGTa9kV88cVzYU8+lNbRwednN20kdNsbBtjLsj/OMrQ/z9tU3EUqJR1WDX89HrmnEY1SLN0Bmmq9LC9e0lfOmmRcz4YvijSb60s5ev39LNzUsrCMZSjLgiPHd2llf7F9Dk1URHRzzcvqKKZ8/O8pMjY6SzOSz5QjKVyXJi3MsVDUUY1Ao2LSrl2lYH3kiS587NsqzGwolxH4+emMKmVxXgvEPOMPFkhqOjAiy8vr2UIoOK+UCcV/udvNrv5MbF5Xzq8XMMzIdY11bCTUsqxAQ9liIcT1Ni0gjLTJ61AQJg3GA3YNWpGHNHCiojtULG9iWVrG21U27WYtEpUcllbOgo4bnzM1ycDRWaU62lpvzEVHwPCrnEjqWVtJebODDgQq+S011pYSDPDNGq5HjCSeLpLI12A+5QQqSR+mMcGHRyRUMRL12YF0lFGXFtLTKo0SrlbOsqZ8IbZeOiUk6MefFFk1zeUMS+fhGsUG3TkUhnkYBFFRa8kSRffbGfMU8UtULGhdkgh4Zc/MN1zQVJ//PnZhl1iUbp2hYHRXo1b1tRTSqd5UevjRLP27ErLaIh0DMTYPeFeWqL9VzZUIRFJ5Rx7lACh1GDTa9Cp5ZjUivfcu7EUxkkYE2eBeGPpogkRH1RW6xn6L9wf/z/9/pLDfXfv3Ysq2Djkvo/2zT50qAvlckJNWyxnkhPhs8808MdK6rZ0CGUrQa1QjSysyIO/dCQi0lPlCywp2+B05N+PrO5jcdOTlFm1nDHymp2XZhjbYuDX7w+jsOk5fPbOnhtyIVZJ5rur494mPJGqbLpuLKxmGhKbCgRCfI8sPMin93axtbuMpbXWiGX46omO6+PeBj3iObXEyen2du3wEPbu3jm7AxPnppGLpPYP+hkZa2NJ05NFxh9mWyuYOO+c1UNIBrKj56YZGfPHP/4tiVkgAde6GPCGyUYS5PN5Hj7ZdW8eEHYmRUyEfpRX6znioZi+udCdFVZMKgVnJrwsaLOyv5+YSk7MuIuWGQuxbePuaOE4qkCUyaby/H6iIfNnWU4Qwke3NnHXCBOIp3l/HSAi7NBHtrRyT/esYTXRzzM+mNUWnVcnm/uVFi0hBOiFowlBeO0SK+iu8qMQa0gTJp/fGWQXH4oMeuP0zsb5OpmO0+enhaMJatospu0SrJZAaqGHPXFelQKGX91eQ0apZxXLi6I7zwnNpDZbI7++RBHRjzc0F1O31yQA4MuXh/x8OmNrdy7pZ1nz80wmk8QXNNsJxBLUm83cH17Ca8Ne7g4F6TcouWaFjtGtYK7N7ZyeMTDuWk/WqWMxVUWBhdCBYbgmmYHGzpKqLMbMKoVXN1k5+kzgvmnVMj55u3dvNQ7T5PDSKlZTTCe5vr2EnZolehUcrRKOfsHXCzLMyv90SQHBl2C91lrQ6WQuKGrvACNVyvlHB3xsG/QRSSRJhBL0VZmKnDIEukssWQafyyVty1GMWtVDDtFQncmm6PYIKxrcpmMd19Zy9vzKu4TY16eODVNlhzdlWYUcomaIj23r6h6i33w6bMzXNlQzFwwjt2oJpPNkkxnkEki+XXYFWZtq+CFaZQy2kqN3LOpjcVVZjRKOQq5DKUM9CoF92wWaXedFWZ0ajlHhj3s7Vugyqrj9uXVrG128MODYhhkN6qpMGvRqxX5MCMZr4968EaTBR6jQiYx5AxzeNjNzUsrmPJGubyhiNZSI+F4mssbinjqzAxT3mjhZyqt2kK41J0rqzk45MJh1BRqP2W+UX3fcxe4obucdW0l1BXrsRvVPHFqmmua7Zh1KlLZLK5QgrUtDl68ME8qk0WjkBMiTaND8OIODopz0aZXUdZVxq+PT9DkMPKJ9S1YdUpiqQzVRToG5kP/qSS4N6uGAPYNOOmbC75F9TzqivBqv5OtXWUY1Qpm/TEkCR7a3iWSuRdCNJYY2NxZVlCeXjoG3xzGkkxnsehUjLojb0mgv7SGnSECsSKeOjPNtS0OrmsrwR1KcGbSj1mjLDR75DKJ+UBccK1m/FTbdKxtcaBSyHhkdz+f2tD6Oxtwv4sTdWJchBYE4+m3NKtWNxXztVu7cYcT7Msngjc6DGzrKv+9yt7/q42oN68/qSm1fft27rzzTpqamvB4PGzatAmAM2fO0NjY+B/89P/99Y1vfIP3v//9vOc97wGEVH/nzp38+Mc/5u677/6jfkcsFsNoNBYSllKpFOl0GrlcjkqlesvzANRqNbK8zS6dTpNLp7iizsSREcEZ2tfvpHfSxee2tVNhVvNsvmHkMCi4ut7CtU02KotMeCNJMtkse85PUW7V8sAN7Rwa9gorV7GWdc1FWNQSMhm8bUWVSJYIRyjWq4gmUsRSGVyhBF949jy+UAylXM6xMSUvXpjj7k1tdJYIwKNFq+D9Pz2JP5bCpJaTyyRRKxU8cMtS3nGZuLE/fmyUYWeY6mIj6xeVU2RQ8ddX1KCV59hzfoqfHJthx9JKNnSUsqbRypwvSiAax6zV4DBpGHeFmfWGSGWzNJXb6K6ycGrCx8a2IlbXm1gIpdk/4CScSPPOVdX8aP8gZp2CdYuqBAMqmsKul5PNZFAq5Zh0Kn5wYIR3X17NxjYboZgRtUaLWiln14U5FpcbeOSli1QXG9m+rIZnzswy4gyTiMfYd2GKOpuBe68qZ/DcPNcHRujUprElo6Q8fubPzeJ/+YfUSjG+7fEiBYLg9SL5vCiDAaS/TeLgreoegLTRhFmtwy/X4CgvolGmJKPVkXBY8ck0VFc7kKu19IbSTCflaIuttDSVo7eaSWu1hOUKFBYLcrMFe1kx/3hogpcvTAvwuFyFJJeRzmRpK9HzniuqGPfEqCo241LL6b3o5JmT43jCCSIZyOQEG+qDV9dxsdLIgUEXd1zewNMLr1FTpEOZS7MQSKAsbmD5iiKGnu/lS64MK7QGtq9uY225DYBDgy7+6chFXHEFj03E2dhZzqefPMdCIIZdJydns6K0mVh8WQd+hYwnT4xRadGw6Mou1phESqIuoWckPEI2J6FWq3GGRPLhqpVV9JUZ2XlGoqrYQPeyJrpvNHH050cZd8dIoECtkLG02sKSrS2MZLOY9FomvXEaHAZ+fnqK77/STyyVpcphJp7MYJAy3N5qYk25jpA/xPmhBRbmvVSrciyzSmgTMf5tdy/6RJTrK7TUKlPog0FywRCa2SmyF4N0+APIwyFkoSDydJoKoOO3vut3AnfI5EQ1ekJKDWGVlpBaj/YlK1W1JSw3GOFxPbFQjqLact5dYUduMZNI60hGzejSGt7RYiSpN3J5QxFWrYx4Is5l9UWkszl+cmSMb2xv57pmC1s6S0hl4MSEl+/sHUBOhv0XZ1i/qJIVtVZS2SwWNdzz2EkG3XFUSgUDCyFe7pvlrusb6Swr4ulzTpZUWWmvMBOKxHh4Zx+7Bzxk87ohjRxKjQpc/jAKuUxEK0dTlOrlkE6SQoZCocAdSlJl0ZBNp0inUnzz5REmvDHRsGiwMDbvw6AS1spkOoNcyqHIZcgkk3RXWeiqtLB/0MnofIAqq5obu8spNeuQSRIfv64JjSyLXC6xf8DFqQkftcU61jUXsb7Zyos9M4QTosniDcc5OTLPjYsriCTT1BXrBZhdyvL5Tc00lJg4OOLBHUrS7NCzssZIiUnD9+5cVpj41Repuba5GJtWxpw/ziv9C0x5otRZlaxpsfPhaxvJ5uCqJjtPn5rEFYpQbNSIJMQSA2ta7Ow6M4Eyl8KoFvHa69tLUUpZrOoclVYDGxeVYdWJe4RDL0Ov0KDRqPnqLd0cGnJh1ytY8IaoNAnpu0ouQ69WsLrOxO5zk8wGokQSaYKxHCpZjlQixrwvRGWxmb/5xUnG3VHK9DL6Zzy81DPL529YhDecZGtnCVfXm/jliWm6q4tFQ9MT4RsvXWBkIYxOJ6C+H1/fjEEpoTLIOTI8z2woQ22xUO5Z1GJD6I1lOTTsZT4QY2tXKR+7ppZjY160Gi2Lqy2oMnHqPv1H3Ur/R66/1FD//evGxRU4/kypeyCGYyLZKlWwhL14QTCiXul3cnjYjVoh5+u3dWPVqXjhvLAwf25rOzt75uifCxX4TAvBOL2zgQKXaF2Lg2gqy/Pn5wjF06xrc3DHyhpUCokHXuhjPpjAHU5g06k4OOTi3k1tfOnGRTz04kVMWqHcOTDgotKq4+bvHcGiVfAv71rBZ7a0sS+v7ioyCKahTAbrWh3cvKQCd571Y9GpROqwTUuxQc2v/+YyNEo5T56eZmBe2PhXN9npqrLw7LkZzFql4LX4Y2SyQln71JlpPrC2ns9vbWfvxQVGnG80WCa8Ec5N+llUYSaTzbG8zoKMN9LafNEU074YxUahrZ7wRJkNxIglM4WmQyieZiyvrnzpgmAFZXI5YqkM5HLU2fXCEm/RcuvyKmRA31yA35yYRK2QcduKKp4/N4sqz3y8xKhZWWsjkhA80mAsjU4lINHpbJYGhwh0kBB4hy1dZRwcdNI/H8KsE030MrOWFXU29vQuEIiluHlpBTN5G3o0mSkMNLK5HGcmfSyrsfI3PzuJTa/CrFNyelIo6jvKzFyXb/682DPPVU1FhONpvrV3kCFnmNlADAmJPX3zfPnmTlLpLDcuLufKhiKKDGqubXVwdMSDM5TgY+uahNV+2M2reej5ZfXFLK6ycGLcSyyV4bUhNzcvqeTp09MoZBJdlWZi6SxySSKREqEjU94o33p55i3waBAp1aFYmiKDGm8kiTucYP+Ai0NDIrAlkshwctzHmmY7+wfEhjuWTGPUKCkxacTjg05W1Nhocogk2FQmi0mj4P2r60lnsxwf83J+OkClVct1bSV0VJh57uwM17Q60KnE1lWlkBWUKVc3F9MzFaDaqsOqUzLhEUOjS7bBdDZHmVmDRiGn0W7AE4nzzbctIZvN8cyZWUbdgkG2vr2EEpOGEqOa9e0lJDNZHnihj0FnmFAshc2g5vCIm09vaOWvr6zDF02yplko/aa8UfYNOFndZGdoIZQP/ZGzkOeDaZVypnwxFDJxz90/4GJ37wJVFi03LC7n229bkme/hakvFuovvUrBs+dmWN9RypbOMmwGFXKZxIfXNbGho5RXB5y8cG6WJ07P8NjJaT6VH67//PUJkuks17Y60CoVlOYT9r66o4tjYx6cwQQ2g1CuO0MJ9g04C8pSg0bBl25cxEIwwSv9C0z7YjQ5jAJGr5SjVsgK6qlL67dtZ79LNbStu6zAh/ztNeIKI+V5WFc12bn/+V4ubyhmZZ2Na1sFMkCvUvDUmek8N8xAMi0awpeWSiHCYeqL9ZwY9/67v9HgEAzfx09O8/jJ6cKg8EPXNIi9aF6dfin5r2c6gC+aAsRA4cGbO2lyGH9nA+73caKaHEYWggm+vneggJUBD4dHXNy9sY2jIx5+fnQClUJG/1yI3pkAn9nS/mdLjP3ftv6kptQ3v/lNamtrmZqa4qtf/SoGg5AEzs3N8cEPfvDP+gL/t61kMsmpU6e45557Co/JZDKuu+46Xn/99X/3/EQiQSKRKPx/MCjiyzdu3Mirr76K1WoF4Gc/+xnf//73uemmm/jsZz9beP71119PPB7nueeeo7y8HIDHHnuMb3zjG6zfsIF7P/EZ5DKJZ85Mo9n3db68M4R1213MZEwY1Qp0c6f516OPccVVq/nSgw/jDMWpsur4zcMfJx7wsP6DX2TrmpWs7yhlz+6X+Ot7v8qy5Sv4yte/TSKVYS4Q4/6Pf5CZqQk+fv8jLF++jBcvzNN35jja079GYa/FtvGjDDnDHBlx0/vYIwwP9tN634N0V5VyaMhFZmEY/ys/IGMsxbn+X2h0GLj/+T7O/uqrKHzjxBbfzq6uVTx0cxe6yCyf+fjfo7Y4SKz4EE+enmZ37zyqEz8jOXORxTe+l2996n3cs7mN3+w9xtO/+SJak5UHf/oYM74Yn3mmh/qxZ5nsOY522c1oW6/ihu5yTvQO8+JDf4Ok1HDqPY/w3TuXUl2kQ9nzLInRE8gXbyXesoZsLs3MvJPN778ZCYniDXfzqxvruMm9wC/v+z5Le0/TWl5Ha20lzy8sEJ6dJzk5gjmdxpAVF/EqYMmbjoG0Ukm1xQY2KxdmpgnJ5RgXX4V6SRvl9eWcGx1iz4njeMvaUa/cyrSkYSyrQf7a18mS4+5v/ZRPvTDOR9Y1Ee97lSd//i9s6LySez77eTyxJKPuCPe+91YikTBf/M6/MWoWxeVjv3qUX/7oOzhal7Pjb+/iumLYvqyKZx7+MJloANOmjyO3VhCMp8hMnuF93/gAstJWrn3PXfzV5bVs7izjlw98GCngIrvivaQt1dQXGzD6Brjrsw9Q3tjOnVd8lyaHgUw2h2fXPyLzz3Ja/VGu69gmeDeRMfb+5l85V93A47/+ZQEqOffiPyH3TfLzmTtoL38bD+3o4tm9h3j+e1/EVlrJfT/+BWatgk88do6Bp79Fen6IzJLbaFmxmn+6YynVMh++R+8FnRXLTZ9FIZNRV6yn/4Uf8pvjR9B03EjIcBmRZBr33DSe39xLsd7Isg98g+YSA1u7yvmnrz3Avpf3svrmd3NB28k3b1/Msb5RZLu+gE6uJHTTA+hUcnIKBQdeeZrvHH4ZdddGXOVXksuVkQmFsT39VQCuu+fH/OjkFLLrm/Efe4pnnnycleu38/Uv3EU2B/5QhBs3rgNAuv5eFIkkbfoclwdPcuKlF7hm5WU4qrs5dHqUUimJ6szz6DNR9NY6OkwqtAEfvnOnic7N0a1Uos8KpRy8od5yAKuBnExGVKXBl02TMFkwdnSwX2dEbrOx+6FXcWcymK+6CWtTE21tNWyfP8OLu5/iwLGlbPjOP+IMJbhlaSW37biZsM+F45q/x+ioI5vLMXXhGB/88T+wZNlyrnrXp7llWTtGjZJ33PFOpifHka14DwlzLQDKhX58Z3/NyboWUtf/mPpiPWVmLYGXvknaM0Vy+TvRVHVQbdNy8sRJ7v7kx6iqbeDh7/4Lr496mPVH+c6X76Xn3Fk+dNfnaVpyOQcH3Ty25xCKwz/krouVfO2ff8YHf3maCU8Uw5lfoHANkn3fx3jbLTfzzJlZjp/t4fi/3Y/FVsTHvvZv7OmbJ53J8ewPHyEydpaP/sMnuPz6rQzMhxgZm+BnX3gvuwwGnnx+N4ZFoqiUnXmcRz58P9YVN5BuuBqNUsbpwXG++7H7kcvlHD7yOneuqiabg+9882u8/a4nece7/pqVm29j2hfjuVMjaPZ8mX8GHt35CnqNiv75IB3+o8w8/zjmKzZx8y3vZlVdEXO+MM8+8H4A7G97kK5KC0q5DP34IcYOP8fSrTdRYlpZmE5eu3YtmUyGXbt2Ue1wsMNUyS9+/nNe+d530TSswHzlnQCUm7U8+NG/IhqJoN/yaQIZg4ANTxwjdfEFfjN1Natu/wijLpFomXjpK8RjQeau+CAvN9pF8ujXf8LC/l9w2eVXcNONX+PUhJfPPd1LZu8jaENuQivfy7CyhUAsRc/5Y3zjwS8gFddj2/D3nBj3cnTUg+u5RxgfHab55o8SMtUBsO/AIZx7/5mW1jYe/PYP2NfvpG9i4Y++J/9PXH+pof771597qqxRylnbbOe5s7OCEVVj4as7ujg07CIcS2M3qbm6yY5Vp+Tzz/Qw4Azz/f3DPPl3V7Kho5RrWhz4Ikl29czxwvnZQuCJQiZRbFTzzZcHcYeTaFVyDg25ua6thOPjXs5NBygxaQoqzoVggr0XF9ixpALDTZ18b98w/liWSquWbDbHu6+o5R2X1ZDJZJn2xVhea2Vbdzn+aJJoMk02BycnfAwthKi3G9jSWYZJq6S7wsKKWhtzgRh6lYIHd/VxYSaIN5Iknc3x/Lk5vnpLF3eurMGiUzLhjbAQSKCQSwW4e+9sgGyOfHKVYP28eGGOR09M8YE1DWRzuUL631wgzuujHsbcEeqL9azvEEmhIGzgl+DMOURDJ5wUrC2FTIYzlCCTyzHti6GUS9y3rYPaIj07e+YIxFJUWXWsbrZTXSQSqF8dcKKUyXhoRxeHhlycnfRTUyTUD31zQZ45M8N9N3RwTauDY2OePI5Cx9o8CN4TTvBqv5NrWx184YYOYeP0RSm3aFlWYyWaSGPVK2kqMZBKZ7m21Y5WJeey+iIsWhW+aJKjox40CvHa03lWUbVVx7pWBy/2zvPoiSmUchkyCeqL9XRWNPD8+VnGPFHc4aRgpOaEquTQoIutXeW4QokCAyqRyfKx65txhuI4jGruf64PbzRJKpNj0hOh3j7L127tZm2zg0dPTtEzI8I+rmgspsysYWfPPI+dnCoc7+vbS7i62c6+QSfBWLpgg6q0alnT4mDKF6MoleHwsJufHBlHn7e5z+fVa/PBGAq5xKc3tXJ8zMuk5w1nQTKTLTTrblwsbIKtpUbqivXEUlnueeo8oXiaTFbYU48Me/jKjk7uv7EDo+YNRe18IM4ju/tpchhRK+R8fEMzckmi3KLl7KSfvrkgCrmMZCxFvV0o9uaCcb56SxcapUhq/sivzzCUZ6+ms1mePTfDP925jEqLwI08d36W89MBdGqBQMlkc0x5oxwb87B9aWVBXTPljRZUMo12A3ajmhl/jAqLFrNWSTSZQa9WUGpWk0hneWDnRfpmBcvJrFXyUt8837xtMRsXlZDJlBBMpARLMpzkioZiEukMVQ4D3nCS5/pnmfJFMWmUbF9SybJqK/c930uNVcf69hJOT/iZC8TpmwuytkU0yBZVmtEo5MwGYqxpsVNp0ZHJ5uiZ8XNgYIFNi8q4vr0kj2CQEYynC40UgPPTAY6Ouvn49S2sabZzYNDFmmZ7wXqmVshQvcnS9rtUQ4sqTJSbBSg/nEi/5fpab9eTyWSZDMYJxdPct62Do6Me9vc7KTVruK69BJ1KzvIaGwa1guW1NnrzgTV7+haY8kYxqpWcHPexrq2EnpkAC8E39tZVNi3r20vZ3StqvEsuHAFzdxCIppAXS29pLr0ZGTDqihS4Y/sHnP+O+/S7OFG5XI5lNVb2Xlxg3B0hFBeNWaVcYsorUA+dlWZKTELNK5MkZvzxP3tiLPzHnKv/KetPakoplUo++clP/rvH/+Ef/uG//IL+ty+3200mk6GkpOQtj5eUlNDf3//vnv+Vr3yF++//nfSb//KSSRJVNh2RRJqOcjPH5DKSwIwvRs5oIpHJsLnFzvNHxWPffmUIg0ZB2RItBrWCOLDz/Byvzp/DrFWQGJsBhETy/ucv8N6r6rHoVGJSBZyf9rNhjbiIXhIfiqIih1UnwOmXojjPTvq4besK1jbb+favxwvPLTaoOTjozl+s33gvoy6RYNMgExcJpVxCLRfpHwqZkHYDFBs0xFJZ1HIZnRUmnkb4cZ87O8fxMQ/ZLITj4vXK5TJsehVXNRbz1KGZwt+Kev1MHDvHpniA8dlR9E4nptf3Yj3xOnXpEB1SiO2DAxSl0yhO3QIPip/7ABCWyYgnkvgSCTJ2B9oVy9kd9hFQKPirT96D0mHHr9Zz308eY378NPH2taQX34jDrOWhm9t5/9brADBt+BBxVLSVmWgpOcbukWFkFXUU1bazEEjgiyWxSRJSLkeJSY1Jq8QZSlBrUBe+o3lflEQ2J2DJ+YaYTiWnvUrYdJ45I96zN5Lknw+OcmjIzRdu6ECjlBEBcRPN5Sg1aWjRGzmKKBCfODXNs+dm+PG7VmDTq5gLwJUNxXR2N7Km2cGLuwWk16xRIuWPhEAsXfiOrmoqpliv5lfvv4zXj2T4lwOC16WQSaiVMi5rKOIHChlpIJnO8aknz/P+1fWsbrLzPEJabdOreP78LNP+WOFvGDUKArEUQ85QgRegV8lZVi2sokurrXztS4+JL0uCUpOGKxqKWZgSx59KLuPTm1rRKGSCaZa/mbojCTzZJP68Fe5s/jhJZbKoFSqQxHELEIimkAE5SSL7JgXuxkWljHsibOkq50eHxPHX4DAw4Y1ydMRD39Qbca+fvLGLr+wZ4UQWVPoiThuNVLa10/Xu93Ls8XMMLYSxOE8DsOh9n6Njx0omcjmeffSX/Pqn/4K++TLe+/ef4Op6G9946iQT//wpjMkYV275azY12Nl3dIBw7wmM0xcwaS34oxKdUohczyRXLzgxplMYHv0esvy52gT8HcCFC+Se+gU1RhNYrfzA4yFAjnj0+0StJYS0RryxAB6Xi+KxUW4LDpMYdhM2WsjGEpDLUW7RMimTSGdyBdCSSSsKmus7Sjk54eV8/nNwmNQ0VotwhH95SrzfGX+UF3pmWdti55ZllXzwCfHcV/oX8Nt8bOkqwxit46eHxa8/MuJhxi9SFi/Z5YxqBfc+eZ5APE3SI0DkwViKcrOWmxZXcGTEXZgCeiJJDg66WdfmoEFbws8QxYdeLQdUfPP2br47tYtJBJg0ncoQiqeQJ8R0LZdn1y0EY0z744X44sMjbjIjoqhtL1byzTzXet+Ak+3LqhmcDxWulV2VFrYvreTJU9M8d+aNTUOJSc3lDUUALKm2MHYYNEoZC4E4+wdd4jqfv4bGU5kCB+XS1HtJtYUP3dqNL5rixLiHx58Wz40mMyAXPAVZ/hco5TJm/DEcBjUGjYJA/vdm85uk69tLCcXFe46lMkz5ojx5eoZMLld4DcUGNeFEGqtWxe45MXyRyySUcimf/hojlS9U3eEkalP+PMtfu1KZLI/sHqCpREyzH+F/7/pLDfW/czlMGh68uZOXeud5bdjNpkVK7swrmqa8YhP+Qs8cpyb9KBUyDBolvzw2wW3Lq/jangGOjniIp7NolTLet7qeLZ1l+aYLXN1s57UhN+5wkkTehjLuFrDydF51kMmKq0LPtGCulJg0LKowc3TMy8o6G8UGNe+8rIZwIs2nnzzPQjCBSavg+vYS3rZChEF8+olzBcuLYsBF32yQeza3cf+NQpvrjyZ5qVdY8Ez5zWMulWXcE+HgoIt1bQ5UCjl2g4ZAPEUmmyMYT1Fh0XJqws/WrnK++lI/Z6f8yPNhLZ2VZq5tc+AOJXj54gLrO0r54gt99BSCbiSOjnl4eEc3DqOKq5qKeeykgVHXG0ER9cUGrmwsRimXaLCLtLhoMsPbV1VTW6TnU0+cI5xIU2xQk8642Nkzy+e2dpDO5bh5SSXOUJwmh5ErG4tYWmPFHUrw5OlpXrk4z20rqpGAj65rYi5QhTMUx6RVMu2LcmDAiVmnJJHOcmE2yE2Ly9m+tJJUJos7FCcQFw2bM5N+RpxhllRbuGV5FQ6jlhfOzzLsFNzQ9e0lVFp1nJrwcn17CUuqLWzsKBXJwItKkUsSw85w/vpWiiKfvqaSy1DKJXK8UVBM5pVvepWCuWCcr+y6WGCm3r6iihcvzBOIp1DIJIKxNJIkMemNsn/ASVelmX98dYgKi5ZxT4Tv7R/moe1dFOlVvHkdGHTRVmbi81s7ODnuZTpv974EWDZpFKQyQonz+rCbcW+UQEy4JZpKDKxpduCLJjFrlFzRUMSaZjvZrNgLJDNZ3nFZTV4pKLGuVTQWTFolr494CMQEWycQS6FTyQknUhwb9XDr8qoCyyeeynBoyM0N3RU4TGq8kTzUetjD0hor92xu48iIWzhCTGpW1NqY8kX50cER1jQ7eO/qOn5zfIphZ7ig9sshUrP39M7zjstqsOpVTHqiBONpgnFxb1LKJcrM2kJ9eClY6s0qmZMTItX30nspMqgoyuWZSC0Ozk756J8LYdIoCCXSKOQygrEUu3rmWN1s5+ioh63dZXgjKXZdmGPUFWFbVxlmrYov7+zj+JiXSquWdFZYWj+3rZ3v3LGEGpseq07JL45NFM4TbyTF9/aPsGNZBTd2V1Bh1SKXgSuU5MCgkwa7kXdcVosvmuK1YRdrmx0UG9XsH3Ax648XmpEAM/44R0c9rG4upq3MhN2oZv+Ak0lvlM4KC+vaHJSahbL7d6mGDg652NRRxpERF55woqCYqrfrWddagkGj5MUL84WG12UNRYLLmYPzM37+7bV5qov0rG8vLaRwFxnUfPP2xRzN13p2o5oqq5b7tnW8BQx+ZWMxBrWc9e0C2dI/H6KpxMC1rQ6CsRS1xfoC0PxSc0kllxHhDTv9iCvM+vaS3xme8WZkzqWVyuQwaBRMe6MkMzl8+dThMrNwdAw7Q6xuKn7LZ3zp/P6zJsb+Ds6VTvqfyeiUcrncH/XOn3vuuT/6l95www1/8gv6375mZ2epqKjgyJEjXH755YXH77rrLg4cOMCxY8fe8vzfpZSqqqpifn4eh8PxJ9v3UimRVOSNi+S2YqOadDLODw+O8cqgB0mSc/uKSrZ1lvKZJ8/gjqSwmfS4w0mWVFv45LV1PHduhu8fmkQul6NXyVleY+Zj19TzYu8CCqWKdW0OPvP0BZKJOJFEhoVIml+87zIuzoX4yWsjKKQMc4EkdSVm0nkgelOxhodevEg0DRadhq/f1s3evjkePTqGO5zkwN3X8/PXJ3j05BTBSAylDOQKBcjkrG8v5SPX1CPPZXBFkty3c5Bxt0gB8wUjWPVKvnb7MhxmLb5IipcuzPLDVwdJZrMoZXK61SlKIl422zJ0yqO4R6aoTUdIzsziHp7A7PdQHPGhTcbf8h2lFUoC5iKSxQ60VRVkHA4yxcW49Ba+OxBn5eXt7Ni8jHNxBWqjjnuf6WPYk/8duRzLK/V84/bFxLNywok0B4fc/OPei0i5LDajliKjiHe+cXE5zcUaHnihF0mhRpYvKD6wupoVNRY+8XgPMoUSXzTJQjBONp3kQ2sbWNVYwpd29vNXl9ewptHGQiDCbCDJqsYSUukMr424ubrejEImQ6dVI0lyfn50nB8fGsGogtlAgmKzAbVCxjsuq+H6FhvPnpnGHc1SZzdyRWMxcrJ4w1FC8Sz7hrw8fWaGv726nluXlhJNpNFp1PhjaU5O+FjwR7mszoyEDJtJJ5Ix/DGyqSTfvK2buhIL+wfdXJwL0Vis5ZpmG6VmLQqlilQ2x+BCCCmd4uCQkzFvgsYSM2tb7GQzGSrMSs5N+WmuKObrewbY27eASQU6pQxnOE19iYlHbuni1IQHeS7LZXVFmI3CqpUjx9MnJ5j0hKksMnJdRxkquYy+WT+LSvVkczAVSHN4xM1Tp6dRShm+dEMH/c4o3zswxsZFpexYUsFnnzzNmDuK1WTAqFFQbtHy1e3tfGN3P68MuDHqxKQpk82iJM3SahsfXt9OKpMlB7w2MM+aRhvJrMSXXxxkNhDHHYoTisSoKdLylduWs/vCAvsHnayut/GeK6qQJBnhtGgYvD7qYc4dxKxTsLa9kvlgnH8+MEKpQcnHr2/AZtCi06h55swMvzg6QTAcRauSce/WLs7OBHnsxBQ6JTj9UUotWnIyBf/6rhXsH3Dx/VcuYtTImQ0k0caiNKvSvK1RR7c2zYmzY5RLKdo1GYyxEKP9E7im5jHEImgiIfTRIJZ4BGMiUgDdv3lllCqyFgtBnQm/xgBWK5aqEhRFxTw2FuWmdV1krVaOeVMMp5SU1Fey+vJ2oiotO77/GpG4sFEYdFrec2UtW7rK+OquHma9MTKSjHAyR5lFy5dvbMeiFo2Of3l9moODLpESmEjw0PZOeuZC/PL4TD6SPIc3GCGcTPN317axtMbKF57rZcYd5Lo2O5/Y2MGkP0GZWYNVp0CeTTPkDFFsNvHKxQXc4STvvaKK7+0b5KkzcyRzIoAgl82ilmW5dVkVH7iuFY1CcKEe2tXDlCeMM5wmkMjRYDfw8I5OfvP6CHv7Frh5RS3vX11POJEmEI5z95NnmA0mefjWpdQW6Tk46MQdEGDZK5rLmPLF+PHhMf5qVSUNRVrimRz3PT/AfDCOUaNElklgN2r4yq1LkcvlaJQyZLksC/4IB4e9jHrjglvRWoJVLXhkH3+ql/55AWclm6G+SMMv3ncZLw96+cXRCeQyCac3RCCWIidT8JHrm1lRY+MDPzvOVQ1W3ru6gUAix/mZAM+fmyUYFpBas15LFomfvGcFPzo4zIvnpjFqVKjUIvVRJkmsrDZy2/IKPvFEH1L+fpbLZvjkdY1cnAvSWG7DYVTz0ulR7r5pGYFAAJPJ9KfdrP8fr7/UUP9vVjAYxGw2/7cdG95IgglPFK1Sji+a4uS4l9VNxZyZ8rOi1saTp6d56vQM4XgKs07FO1dV876r65nxxdjVM8eEJ8L7VtejVyt4td/JqCtCax5MPOGJ8NCL/aQzOb5wQzunJ32iwRBN4Y0mAdHo/uDaBpZUW+mdDbC+o1SArWUSRo0SX0TAx7+7bwSZJAIpaop0/OAdy9jTt8APD44STWbQKkUSqkImccuyKq5sFGy6O1ZW86ODoxwYchWUSoLLmWVjRymf2NDCrD9KJgt3PXGOgYUwElBdpKO9zMT9N3bgCSfZ3TvPwHzo/8fee8fZdZd3/u9ze69z7/TeZ6SRRpIlNzXLlm0Vy3IBTA3ZJAsBAgnVJpjQDJiEJWRJIIXND5IA7t1yU7Xc1Eea3vvtvdffH98715ILOITNslme12tell7WzD33zLnnPM/n+RS6qozsXVODTa/i/3tphg1NVs4vRPjZiTkWgwLIU8llVJu1fPCKRvb11zLrj5PKFjhSSgFudRrY1ulEq5TR4tDjjqT501+cZWAhzI8+sJ6z8yH+4dgUTXZ92Q8qmc3z0W2trK238J1nRrjnlj4abDr+9tBE2VdHr1Jw164uKk0ajk/6CCVy1Fm1bOt0EElm+eTPz6BRKUhn89j0Kr68t5elUJL2SgNGjZLnhtx0VBr53APnmPTGkYA7NtVzx8ZGvvfcKFMlXyy5TKKn2sTde3pI5wrlUBCLTslyKMXBUQ/tTgMWnYpALM3AYph3b6jn8YFl7js5T66UUJrJFVApZHxkSyu3bRDJqfefnOdfXpkr+2/984c38vdHpzgxE8CmV5HNF1gKpcjmC1zXU8kfbG7hM/ef4zu39XF03Muzg27u2FjPVa0V/MnPz15yrasVMj6zs5PVdWZADN4KuYQrlOLouBe7XiWYT7kCiWwef0zIQR0GdTmt+PMPDuCNpnEa1SwEk9TZtHxzfx8vTnjZ0Gij2qzhG08NMx9I8lfvWsPfHp7khWE31WYNodIQbzeo2NMn0qdXFo7xtDA0r7VqOVySzN310Hmm/XEMajnv29TIlg4HbU4DMkni5yfm+OfjM8IvTaPg/o9cybeeHhbLk0KRi3GB29bXcfeentL5XeDvj02Wz71RLZgud2xs4Nb1dYAY/P/m4AQvTwpAwqhR8O1b+8jmCzw35GbKG6OlJA2sMKr56uODHBr14jCqy6wdmSRxdVsFf3JtO/FUjnAqy6fvO8eUVwDIP3hvP+eXwjw5sEw6V0Apl8jmi2iVct63qYH9/bXEM3lkksTAQpAHTy3yqes6mHDHCCYyZTBxxXD7/pMLlzDj1AoZWzsc7Omrxm5U8z8vej8X15Wtdj62vQ1vLM03nhhiKZxCJoFMJlFv1XHXrm6cRjXffW6Ml0rfXywWyeaLZHJ57r1tDU6TAL3G3FHqrTqu6XZSWZLufunRC0z7BCi0s6eSa7qcfO+FMZZCr89lDTbxOlUmTdlzLl8svokJdLGx+LmFEF97fJB7bllNrUVHKpfHH8uIRD+7jkqTthxAtHJuMrkCy+HX5YYf3dbK5vYKKgzqt5TXrbDlVhIjg/EMf/WuNQwvR/nRkckysGnVK7HqVNy8tpZVtWbueWr4kp/znsvqf2NMqYsZfCtVZ9Xyiatr6W2u/q3rod4xU+rmm29+R/9OkqT/p406KyoqkMvluN2XygvcbjdVVVVv+vdqtRq1+s0ZZVqttgxIgdisKpXKt/x3byyFQkGuKJEv5nGFoxwZ89Jfb2FTi53VDQ5enYuiUsjY2VPFsckAM+EcNp04BpNGwfmFMMdnInx4SycKlYaZkgHbDauqMGmUSLIAd2xs4JlB8WCXK9WYVaDWiM3FvrW1vDrlZ8oXR68TqV02vaqc8FKQKbHq5bgiKQ6PedjUUsHTF9w4rAY0Sjk1VuHTJFMokcllZUZFq1OPTC6nWJSjUkl8791reXnUhXd8jlp1kk2aMKl//EfcC4s0ZyP8ocvFvtFpTCEfFfHQJYbURUmizuEg76wkW+FAu2E1OacTl7mCkaIOZW01zavbuH8hy/o1LThMGrxREb+ezRf4xI52bAoZL33vKMdjRTZZqlhl1vIvr84yG0oj7C/FFiWclZGTlLw85WNjs40pbxy1SoXDqEYpF6wcs1bBhCfO5nYnBbmaZDqHqRSVvBjNcZPdTF2FkUlvvLQ5VfHeTW28b1MjyWye79zWR1sp6UujVtFeIyOZyWHQKLm+txpfNM2RcS+ucJKPb29nPpDEoBVpJxVmAwa1glyhyLQvjmJVFWuanDhNGioMKpRyGT95eYaR5RitTj23rKtje5cTp0lNtijnyKQfVyTFZY1W1tZb8Fi0PHreRWeVkZtqrNyxsYHBpQjXdDlpdRr42hNDzPoTyGQSAwshzsyHuWt3DxVKyOWLjJWMFK9ur2aXXk04KQw2LTolCoWFC+4U/c1y3r2hnlv6a3GYNMRSWV6dDnB0zItZq6SnxgJIPHTew6QnRptTmCS+a1Mz+YIYvk/OBAknslzT7USnU/GL1+b52Yk5VAo5Bo0SikoOToR494Z6jk0EePzcEle1VfCtd2/gyJiXUDxLlVnD5S12NCoVPfUVnF6ME0llyeSyQnuvU9NTb8eoUZDJiXSyG/vqCCezHJv04o6mkUkSSoWcglzJTFh4PWzpqOCJgSUaHUbkSjUnZ4OsqTPzwoiHm9fWkitUM+qK8cjZRU7PBommc+QL8PJMjMtb1SiVBeaDSYqAXq8TlHarnkfOLZPJF7DqNdQ5lCQzeRSsMFUSxHIytJKSWruaXN6AXyHjqNFE55YWfrB0Cm80Q4NNyz98aAPKXJGfHhjmzHwYXyxNrUWkzX3+unYujCxQ8Pm4vkZNwecjuezl6WNDtCnStCuy2OMR8PvRzkwTf/lV3hcJoX3un5EKBd44juflCo5qDATVBkJaIxGtkd6BJpYVejbHZcT0RmI6E1GdiZjPyMhLObZd0UVAKVKXMrkCZq0SSaekzmHmsQte5DKJTKnRkCvVFHMyJrwitjyRyYNCyX+/pps8Ms7MBbnfE2N1rZkbVlWRyCv4+ck5dq+u5q6HzvPhq5qotplJF9xi21qEoiQjVZRR5zAjQ/iXvDLlZzmaA7katUoG6TSTpbTM69c0cHQqTINNTyiRxWlS8/QFF3PhPMWinO8+O8b+dbVsarbRaK8ve7r8+Pg0WzscVFsN+NM5Iskcf7y9DadJMFYHFkO0O41EM3mOT3gwquWsqbfyneemcEVEMtLZ+RDn5kPcuasbq8nIPfvXcHBEDINtpWGwKBNGucfHvUz7EyjVaqScRLvTwLYOJ0fGPFRbDaxpcqJQqiim09y0pobTsyK5SyPJKSChUshQKeQ0Vhgx6HXE0nlymRQquQyjRklzpRmVWlsGpAAkmZwqm5FguojTqObOh84zseh503Pvt71+10P91yijRllidL++ha+3iTRNdyRFrUWLWiEjUhRDSV+9hVAiy6m5IGvqBYsmkyvw6fvOcmEpgkmj5Ox8kBfHvNy1u4c7d3Xx2Nll8oUiN62pZXAxwslIsByN3uIwsLnDwfNDblLZPA6DmpHlCH11Zp4f9rCp2ca0TxiNS5JgTftjGaLpHJPeGBadEoNasFwkhFzk9FyQy1tsPHR6kRtWVVFtEUyQYlEM2DqVHKNGQVe1kXyhwJ0PneejW9v4hw9tIJnJI5fJkCTBYj45FWTSF2VDo5UdXU4CiSxLYSGze3bIxXU9VUz7YmiUchEIcdGgPxdIoJCJdLBnxzysqbdwbU8l3miaY+Nedq2qJpUt4DCo+dYtfTx9QSTJPjfkps4qlk/+hAjmkcskJj0xdnRXMu0TyWvv29RAo12wSUAq+wd9/sEBIinRc80HEjw35OKr+1bx1X2rODTqwaRRcnW7g1FXlD9/9DyXNdr4H+9ey2WNVh45t8RkCTgoAju6Knl+yMXwsvCd0ijUIMFMKVn32h4n8XSeQDwjZF8lvx6zVlkO4nhiYImOSiOb2ys4Nu7FHUljlYtldL1VW/ZVEqwOkeC3pd1BhVGNTa+is8rIS5O+UmqsYNMnMnl6qk1olTLuvbWPhWCSI6NeZJJg+Vn7VNRZtZcMrw6jmlqrtgwEgRhyv/PMiBio68zMBxMcHfPhjaaoterY3FZBKJEhmsnx2kyQGV8Cq15JrlAknRM+Vb5YmvdtakSSJLxRkUY75ooSiGdoceh54pxInzNplWTzBYxqJY1vYKfIZRLd1UYeO7fE6lozh0Y9jHmiyCSJWDrPA6cWeGHEw3s3NrB/XS039AqT7ElfnBqzBoVMos1hoFh8nYO2knzW4TSU56/tXQ5emfIxF0iWwaMV76VCoUgwmUWjkFFp0pApgUVXtNgJJjIcHPGwrsHK5vYKXOEUjw0s8d6NjbQ6jBwb91MoCmlqNJkrG6ZTFGzjZ0p+dStVYVQz7o6VU/kC8Qz+eIZai4ZZf6Js4F8oFllbb2VDow21Uk6tRfsmydYbpWZqhYw/3tZKe6VRADn5IjVmDbmC8Bi7eBZdYQkdG/My4oqWQSGjRslcIMGRMQ/7++suYQ1l88UyuHNiJsANq6rY0l7B/v5a5DIBSisVYqH32eu7yvfWPX3VHBnzsfwGxtbFxuqilysgl0mXXKfwuoQ7nhZec3fu6uHxc8sAXN1WQYVRjUWnwqJTlUFJjVLOtk4HL036mA8kqDZriaYFk/6GVVVUGFSXSEgvLqdRzedv6OK5ITeuSBK7QU2dVYfDqOGh0wtlUCqTK1Bv1ZZCDLyX/Iz/HYmxb2VMf3zS9x/++f876h2DUoXCbyfV67etVCoV69ev54UXXig3oYVCgRdeeIGPf/zj/9tff4Wqd2jUw/BylIrShmExmCjfDM7MBZkLJjDrlEx4YqUbikIMx3IZ6VyWM3NBdnQ7WddgZdeqakLJDENLEa5ur+DankpyhSIz/gTFIoRTWXL5ImadkmPjXq7pcnLnrm6eGXThCqdocei5otWOVqkoAxqvTQd4fsiNJ5ymzqrjjo0NXNPlJJMrcFVbBa8MLTHtXcIa9lMRDdBDlNsjSoz/7KW4tESj1w2uZTp8vktYGXlJRtxagaqulojFjm3LFYzLjRxVm7G3NdK9vgtLawMejZnnJwKsa7SiVYlkjWlfDJtezbU9ldRbtQwvh3no2Dl+NHCKi3kfn9zRLhB5SWLvmhp+/to8Pzg4wTdv7SOUyOIwqElk86jlMsw6JTJJNIdzAWH82eLQl3TFMhaDSfLFIlqVnFanAVckhVIuodAoiaZyGNQKGq1aFDKJL9zYzYvjwlz09vV1qBRynhgQpogdlUbMOhWpbI5HziyK5qDdgUUn6Kjfe36MaX8ctUJGIpOjo9LAydkAepWgT4cSWRIZkawmkySC8Sz3Hhhh/7o6+urMPHp2iUgyx4sTXl6d8vPNW/qwG1S4Iyk2Ntv4zP1n+dGRSSoMarQqOQqZjPdubEAhk9i3tpZdq6vJ5gs8fGaRV6b8pU2PjDqrltPzIZ4YWOJ9mxpRyWVsbnfwjSeHODouGqZcvoBaIecr+3r5t9fmefTsoqDC23Q8dm6R8TOLpeHZwWVNNsxaJdF0jo/962mmfHEsWiVDyxGGlyP8+e4ejox6+PmJefJF0SQ9N+Ti3tvXUGXWkMsX2d5pZ1unkwqDmkgqi1oh46s39fLouSXOzocwqBW897IGCsC4O8qjZxe5vNnGlg4HD51eYC6QQCZJmDRKqs1aNjbbeeaCi9lAouzfkcrmmfbFy0k5Ro2CaGkbPVmSQ3VXm9jS4cCmV3Fw2M36RivXdDrJ5Qv89QvjHBv3lQBKsSHKFYTEYnuXE4VMRo1ZI+j0GSHbCicz7Ftbw7s21OMwqgmWEuzOL4bJ5QvUWnVk8gU80TR6lQKHUU04maXJoccbTeONZihSZNaf4LGzS7z7snr+fHcPjw8sM+OL01MjJJLDnhhfO77Erevq6G6t429mxrlp8wb699zC4TEPD/kTrGuwckWrnVl/gu89P8bnbuji1JSPnzx7gXqSNMsyGBJh3tduxD/nYnx4hqI/gCUVw5KKYlico2bZQ0M4iCkeQVF48xBvksn5A4uFPXIdPpWejMmC/WAdvy/Tsj4hx6vSE9IYyVusTBfUrGtXEFk0kMtk+cgWwWT4/IMDnJsPkysUeGXKz4mZAB+/pg2jWoErnOIb+1ejUcrY3FHB4wNLuMMp9CUpaq1FDA9FikiSxHwwgYSEXAYmjZJwMks6V2DCE+Pankp6a0xc2WrHHUnhNGmY9MbLLAKNUsbzw25eGBZpex+/pg1/XMh8NjTZODbu5V2X1eOJpDkw6GLKE6PFKfxi7AYVH/vX04QSWe68sYunzi/x2kyAarO2LOVb8THY01fD8Qk/fXUWdpSSaY6NC8mOSaPki7t7OTruZdoXw6pTsbndgTea5uiYj+YKHdf3VqFWiE1sMpPnM9d3cnjUizucoqfWxI0l49btnU4ePrPIYujSAejqNgcOo4p3X1ZHq8NYjklWK2Ssqbfw2Lmlcvzz/231ux7qv0a9VTy3XJIIxDPlAeSlST+vTvnJlRLFAvEM3miaLz86yN+9fz3nSssYuSShLn0G50NJXpzwsm9tLatrLWRyeZLZPF/Y1c1zQy4GFsI0V+jZXkpE/fHxaf77llZ8sTRtTgM6lVgoNth0NNp1ZHIFJIlST1cgWDq+Y+M+XGHBOqgya1ArZLQ6DAQTWXxx4VF0ZaudBpuWGb+QZIWSWVodejY1C7mwBMgkSKTzHJ/0sxBM0GwXfZ5KKeOZQTdPXXBRKIVPbG4XIQ7fvnUNNr2SXaurGXVFcRjVQn5fShFssOkACadJw7U9VTxfYpm0OQ1s73Ri0Qs5pEouY++aWja3OzBrlbQ5DZyaDZIvFEllC+SLRaQidFYZyxIwbzSNQa1gW6eDx88tsRROcnmrDW8szRdu7KbSpCEQT/PylJ8jo16OjXu5bX09zRV6hpaj3HdynsfOLpIqyfhGXBF6qs3M+V8f7iVJ3MemfQmS2Ty6nJxpfxyzVoVZq8QfT+M0aXjy3BJb2h3IJAmLTskzgy4mSzK//f21rG+08Pywi8/s7OJzN3Tx2rSf+cCl8rmV38Mt62pJZQscHBULuJvW1nDjqqryQiCVzZMriNS6XaurUcpFIE2LQ89nr+/k5EwQh1GNSiHjrl3dl4CtF78WvD7ktjuNtFcaWQ6l+LP7zjLpjVNhUGHRqnjo1AJf2ddLo13PL04uoJRLGNVKEtkcSrnEV25aRb1NxyNnFpkNJLDrVexeXc3qWhOHRz3s6avhuSEX7nAajUIw6JordG8a1DVKuZDXBRKCaWNS86MPbMBpVOOLpXlp0i9mnYCYUxrsOm5aW4MvJj6Ly+Ek1/VW8cT5ZYaXhV2IXCbRWWXk2p4qRpcjnJgJcPuGeu4snZeLJYxGjYL/7+UZRlxR9vZVs73TwdExL65wqhwu9eMXp3nKvEwsnSMYF/L2VTVmdvZWcmI2wEIgyWIoSTpXoNVh4LImGwMLIhBgtiThWukR/bEMbU4Dr0z5kZXAZqtOiV6toNaqxRNN8f0XJmh16rmup4oGq/ZtgY03Ss12dDlZVWcWrL0RN1VmLZe32Dk67sMVTiKXRNpzfQkwATg3H8ITTZeBumhaeL6Ne+LkC0W2loCduYBgC2bzRVoceq5qq+DJgWWeHXKXGUHK0j3wjffWQlGAWReDYis1F0iQyuZ5/NzyJbK0FTYYXDoPjy5HcZjU7OmrYS4Q59P3nyOVLfDxa1pptDdecq6qzJpLPgv1Ni1b2sUi/peBRd5omhcnvKyqNbO/v5ZAPM1PXp5mU3MF39i/miNjXia9MVbVmLl+VRWVRjXbOpxISG/7mfuP1Fv5XK3UG4Gq35b6tTylfle/vP7sz/6MD33oQ2zYsIGNGzfyve99j3g8Xk7j+99ZK+Zys34RHx9KZnn6got7b+3DFU5iN6j4wq4uHju7RCZXYHWtmXF3VHzoJRFPbtUpWd9oxagWXi8vjLiRgNs31JPI5PnBoQn+4qZemu06HjyVIpMvYNEqKRaLjHtivDrl5/pVYqje2umg1qIlmclz38l5pud9dBPnBkOWzZk5Ci8uUfNykv3TCxQWF9H6PdT4vfwocClttKhUUqisIu1w8mpSxdpNlzGlMPGwK0/WWYXfZMdvshM3WXj/la3s7qvmgRNzVJm1rK230KETUh21QoYvnuELD55nVa0JmSTxpz8/y2xAmFZm8wXOL4b5i5t6aXUY6a0x8XLJBwJE4sOOLicmjYKhpQi3ra+n2qTh1vX1yGUSjTYdFp0SC0oKJer7QjBBNlegxqLj2SEXt66r48xciOHlCOkSJdhhULGzp5JHzy4STmYxaUQs78pN6tEzi0z743xkaysGtQJvLF2mieYLRV6bDvCLk3N8fd9q0rkCP315lmcHXdy9pxeTVsm+tTXc+8xo2Wx0a6eIi57yxVkOpUhkRALWZU02fvrKLNd0Obmmq5Ixd4xNzTZCiWx5WxpKZnlu2M2qGhOfe2CAz13fyQ/fv4FkRmjjQUgGFHKJdL7Av7w8S3ulkStb7SwEkmiVCowaCZNWiVySsOhUeGMZcoUCCpnEhDfGx65p49CIl2AiQ51Vy6ZmO65IimcHXdzSX0s2X+Srjw+yGEoSTeV4edLPK1N+vnVLHzJJ4qUJP0uh17fW0VSOaV+cZ4ZcrKoxI0kSkUQGdyRNMpPnxQkfO7qc/NsfXk42X+DgiIfHB5aotWjZtaqaWquGK1vttDoNzAeT/PTVWR4+vYgnmqZQLIqY7kyOr+5bxeFRD0uhZNnHasIT5ScvzzDmiXFhMcznb+iiwqCmqUJseC06cR6qzRqiqSxd1UY0Shl37e4mlc3hjqS4e28vQ0shWhwGZDIZq2rNnJ4LEkxkSWXzwuS2WKTdacBpVJPK5tnQZMN2Yp7hSBSZTHhoIUk8MbDEuFskKt2+oZ5dq6swahRc1WqnuULPnD8uvH/0KmrMWrZ1OIWEoFAoN0hj7hjZfBGnSc2Nq6rKspGfvDzLQ2cWyBVgW6eT54fcnJ0PMRdIsKFJgGo7e6rQq+QYNAo+c98YM744Zq2ScV+CkEqH1mwjp1MK76YOB/veVcvx58Y4Nu4lmy+ilEv87A8v58JimPtOLlAsFkgHI0iBAC2KDPvqNbQrMzx+6AI31KipyMZRzC6jDgRQLy3QGwvTtOxFHwuhyl9ktvlj8Z/XJImi2UJUb+LPi2qCGiNhjYGMyULSaCHwSi3XNlXzg4Egq1Y3076rH7VCz1/ftppj00FGXFEabEISZy8xtQqFAvVWHeBDJoFSIdFg0xFJZVldKyLJv7i7B280RaNNR75QoKvKwKkZFQaNSOha8U5rsOlQymXsXVMtUhR1SmQSRJI5vvL4ICdnguKeCQzMh7hrVzdr6y08P+yhwqhm0hsnky8QTWexylXlDeRCSUpzXY+Tp867LhkG3eE0w8sR9q2pZX9/bdkUdmQ5ypm5IPv7a9nS4cCkUZTp90aNgv92dTN3XFaPWilHJZfhiqQIxjOkcgW+cpPwfJjyxml2iGE7U2JvXN3m4NkhMai1Ogy0ratDKZeY9cfL3h+/q9/V/8l643CiVco5NuFlW6eTL+/t4ciol1FXFJ1KjjuaYnunk2cGXTiNaiY9sdLPEAvBRCZPLJ1jaCnKjasKnJgJ8M2nRggmM/zDBzZw+/p6tnQ4mA8keeD0PE8NLNNoE0PY4FKYq9scBBMZGuw6Do54uGVdXfkzXEQwIcY9Ma7vFUDPUslnL5nJ01tjYke3uFevyGEiyRzfvnUNh0c9THrjJTNgB5GUYHHetr6OaouWP73vLNPeOEqFWDA9fWGZz9/YzfYuJwcuuADhl9VcoScQz/B3RybpqzWzs7eKz1zfyT1PDeOPp8kXxLPrqrYKFHIJsmDVKdm1ugqFTLDlTRoFwXiGYCJLs12PVimjwqDmwlKYy1vsvDLlZ8afECBfERrteraUGGUOo5ruaiPxTJ5RV5Qv7enhtWk/XVUmFkPCcHjaJ5aG13ZX0lVl4uRMgGy+wHI4xWfuP0siky95mEokMjmOjHlZW2+lv8HCq9N+MrkCGqWcWCpHi0PPa9N+FHIZTXY9uUKRcCKDw6hGJknsWl2NXqNgKZTiq48NcmYhJJZLxWK5XzdqxNLYH8uwv1/IxC5mvGTzgnmtUsj4s/vOMeYWLKEXJ7z85W1r+dKeHl4c95Z72y3tDuwGFdO+OM8NuZn1J2h16NnRLZawOpUCnU1xCdj6xmt8Zcjd1ukkmcnx/LC7LC8TPaICKQsnZgLc0l9Hb42JkeUoCrlEPlVk39paGu16vvXUMMMuodhIZvI8cnaJe2/t4+x8iIVggm/uFwlx3miaRru49t5qUFcpZKytt2LTqdnQaOPJ88vimeE0sKevmstb7Phj6TLDSq8Wy78pb4xXJlN86Komvv+efp4bcpVlotf1VAJF/uCnJwglcjw+sMwP37+em9bWIpeEfDGeyfHJn53htdKz9uiYl3tvW8OX9/ZweNRLjUWDJ5ouewcZ1YJZk8kVODbu5fIWO1/e08vTF5YZWAyzqsbEdT1VmLUKQqUlzNp6C8fHfaRyBdQKGafnglzbXckrU34iyRxalRyTVkmNWUt/g4UfH5/hyfPLSMDT51384L3r0KkUZcBnpVYkbXvXVCNJInlwZ28VgViGT99/lvlAEp1Kzpf39vDJHe2cnQ+yGBKSzO1dTqw6JUuhJHU2HfliEQqAJJ7I0VSORpuOKV+MZrueu3Z1c3jUw4XFMLVWHVs7xBLryJhgB72dd9LF8ruLwbMVX1oJqLVomfbFyxJEtSKIJBXZ01eDUi4r9xsr0rUVKd4zgy7u2b+aW9bVMbQcZvfqGgyaS6GQt1o8vPGz8Ebj8FQ2z6FRL/edXABeDwp4aTLA88Mebu6vZWOTnV2rqwWAW0pIrvsVr/MfqbfyuVqpOuubVVa/DfVrg1LxeJwjR44wNzdHJpO55P/9yZ/8yX/4wP5vrne/+914vV7uvvtuXC4Xa9eu5cCBA28yP/9N18VUPUkCtUIOZJn0xjg85uFDVzThjaaZ8MTorTFTZdJw46oqTs6I6NVMvkCVSUOr08CVbRU8N+TGHU2xe3U1Vp1g7jw75GL/ulosOiVXtNqpNmuY9sWxk0W3sEBfJsKuoUXm75/CMzZNBXFkmQi5qTk+GPBiSsUuOeaiWk3GUYm2sgq3wcZQ8xpUm2voXteBprGBtKOSrLOSgNrIUiRFq8OAOpQkatHSrFHQemaJJ88v01dn5o62CmosItLYHU2xrsGK06TBrFXyT8emeOTsIn/9nn4GlyKEkhm2dzk5NOphwhtDQiKeFrTYC4thDo142LOmmi/u7uHYuGgu60uDpsOoJpMr8NKkj49sa6PR1kgklWVqPsaGJitPDCwRTGRL0rwM9TYdGpWcq9rsHB/34omk+IubenjqvIuhpTAdVcYSWg5bO52oFDJ80QwWnZKb1tbgMGq4//QCqWyea7qcdFWbOFSS10RT4uGUyOTxRtNlbf0zg27kMYmXJn3cuLqarmoTH9/eTp1Vx2fuP8cfbG7hzl3dPDvk4sJihOYK0cDN+OL804tTKGQSm1psnJ0P4YtlCCYyhJPiwV5t1jDpiXFFix29Wi48J9I5Xpr0sxRK0mjTsbXTgV6t5ORMgJen/KgV4v13Vhk5PR8UIGixSKEISkmizaFHrZCjlEv807EpNjbb6W+wsLrWzFIoyQvDHg6NenAY1dywqprDYx4GSqlEFq0SSRJsr6NjXm5ZV8t8MEGDTUuhSCmCtoBJq2TMJY47Vyhg1amIpYVXRFeVsfT7SvO5BwdYDqcwaRScmA5wfjEs/AVkEsFEljOzQZ4+72IhlEQpkyGTJOwGNQ+dWkCvUbC2XkgWg4kM/+v4DIdHPFgNKhptOiY8Qq51x8YG1jdaecqqJZzMshhKolHIWVVr4obeKgrFIgq5jIfOLTPuiXLnrm7WNdrKqTVXtNp59Owi8XSearMGCXEON7c7SGRyPHR6kTqrtpw2dMOqKpDga48PMh8UQN7xCR+vlFhvplID/O1b+zgy5mHGl6C/wcJVrRXM+uM8dX5ZmJOXqs2pR1tujosE4mn+58EJnh1yUywKM9AKg5pJb6y8qX3g1AIHh4Vp7NVtYnO+p6+GHxyewBdN0+o0vA58JrLl5J19a2u4a1c3Tw6YmfDE6G+w0mTXYzeoeHJgmflgBr3JSE5voOA00HJ9B3PBJBt27qWgVxGQyaBQQK9VUtAqGfLF0ajkvDTuZdkVpEWeZrNdjjUVI7nsRhMNk/cHOHF6Av+cC0sqSnUiSEVwAWMijPlIFFUmzQ9WTsad0Fb6Y5PRRN5iJW0y41YamFQbaO9uwFrpYI/BTHwyhluuI6IzETOYMdU42d1dgVEnrk2jRkEgkUGXU7B7dQ1n50IMLkcwqpWoFEI2sLnDQTyd48nzwoy43qpl75oaHj27RCCeuSSueSmc4oURD9s6RWqYL5qm1aHn+WHRIIueUkSur4BdFUY12zod3LCqilAiy5ExDyPLUT51bQcvDHvwxzNs73RQZdGwtsHC6jpzuZlaod8fn/DRVW1Cp5Tz5HkX6xotGDVKPvnzM3z95lX807EpNCoF1/dUcl1PFYF4mofPLKBWyPnY9ja+fWCktOEucnI2yLFxLz9433r66iy8NOknw29vesw7rd/1UP+1qtKs4eo2B4dGPGiVcm7ur6VYAg00ChlzwQTfvGU1WqWM3hoTp+eCmLVK8kWIp/MYNaX0tnyB3hKb4h+OTfPqlJ/uahMUhcF5OJnjw1c1s7XTiTeaIpbOoZBLDC6F2drh4IsPX2Bdg5V7bxP3/rlAgjV1ZraU5Cp/cVMvL5TAhNaL2JQrZtBKmYwJTwxPNMWGRhHHHkxkOTTqocqkoaPSyI2ra3j49ALeaBpzSQ4oIeGNZTgy6qGvzsIPj0zSaNfT5jSwvtHKfScWODUjUv9OzQS4a3cPf7azg4dOL9JRaWR7p1OAZZLEjD/G4VEf13Q7sepUeKMpfPEMfTUmPrKllflggnwp5CWbz2PWKvnSnh6eH3azEEhi0Qm53Yw/zr+8Okt3tUmYp5+Y5+kLy2zpcPB7VzURSWb5+uNDnJ4PAQLoeWJgmXtv7UPX4WDaF8ekUfKhK5t4/Nwy8XROnG+ZRI1ZSzafZ1unMPqeDwpGx4nZQDn9a8XPR62UCylidyUUi0RSOdRKOUdGvQQSWeGJU8hDUZgpH5vw8t6Njfz8tTlsetVbDquucAp/LM3J2SCpbF4YiOcK6JRyvv/CGHfu6mZXXzWRUsiM3SDY0d97bqwsuzo5K/qbL+/txVwakn/ZULwy5Fp1SuQy2SXyMgB3JEWFQYU3mkatlHHDqmpOzwaZDyYxaBRc1+0kEE/zB1taMKoV+OMZTs0G+ekrMxwe9XB1m4MvPnyej25rZX+/MJPXqeTlAf6NpVMp2N1XhS+a4VsHRsosfGkQnh92853b1rC+0VJ+T28FNtj0at67qZFCsUg2X+DlST9//uh5QgmxsBpajnD/qXlu6quh2iIG+ScHlpn2J6gqyQBzhSJfe3yQr+xbxa3rapHLZXRWGTk3H0KSJFQKqSy/bHMakMsknCY1Wzoc3Nxfiww4uxDiwAUXPTVmtnU42L26mmNjPmb8cbL5Ag+eWmBdo5Vv3dLHwRE3i6EkTXY9lzXbGFyM8OjZ18OaJrwxnh9x88Ermsqg1JsNr7VsbnewqdmOTa/i316bY74kUUxlC3zl8SH29NXwwSsaqTRpGFyKIAHBRJbXpv1s73Ty9AWxOCoWBWBZa9WyvcvBE+eWGTFGuXVdHbesq2NHdyWz/gRHx7wcGfOW+5O3Mgy/uFakdMcnvEyX/Nky+QJr6i1c3mLnwKCQ4qkVMj6ytRWHUc19J+fxxTLccVk9R8aEBE+SpLJBfTiR5dWpAO/f1IBcLqO6pJBIZ3Nv+py91Wfh7YzDKwxqXOHX2UcvT/m5psvJ9+/o58VxH4uhJFPeGHVvkMO+3ev8Jmrl/J2Y8dPuNJaTEpPZPFZl7lf/gP8D9WuBUmfOnGHXrl0kEgni8Tg2mw2fz4dOp8PpdP6uoQI+/vGP/6fI9S6ui6l6MknCpFUQTsqRpCLVJi1qhRyrXsJp1PDI2QVksiLrGmz8ybUdvDDsZrnE7tjQaGXOn+CHRyaR8jkWBsb4SLsWe8jD+nPj1CaC5L3LVC4u8bjbheRaQp24VFJRrdLgNdgwNdezbLRzoW09PqONBa2FRa2FqMXB3hvXs3VjB7f88CX+9NpOruupxBZOEkhkGZJJ9NWZefr8Mo6UkkpVkc5qE8lMnpHlKI+fW6bdKZIT9q2twR/P8GJpyK61aLm81V72ceipNvNPL05j0ipoqtDz9IVlwolseRBfidpdiWwNxDOMe6LIpRpenfJxeYud3aurkSSJcDJDIp3j4bOL1Fl1qOUyfLE0X3r0Av5Ymo9saeULN3ZzbMJLJJmlyqRlXaOVC/NhGh16/nxPD0+fX6a72sT1PZVs73QQTmZ5cmCZ+0/NcX1vNR++qgmLTsXAQpi5QAKHUcOnr+vAYVRTadIgk0mMuWNIkogvNWqEESfAeEkKlM0XKBaLnF+McE23k2QmzzXdTv7X8WlckTRfeXyIn//h5VzZWsHmNgehZIb5gND+/+yProCiAJ8q9Gp+fnJe+JwUiuQKRSLJLJ1VRuLpHLtXV7Om3sJiMMllTVZiKSMnZgN858Aon7uxi3WNNn74fisgUv42Nts4MibilKOpHJlcgXangavbK0ikc2TyBe68sZsvPXqB+07Oc8/+1QwvRzgw6CrThCsMamb9CVQlDbpcJiR+oWSWcwsh9q6podGm41WZRDSRpVgsik1doUh7pQF3JE0okRVMIIuG63ur0KsVzPrjHB0XyY+FYpF4WpieLodSPDPo4j2XNeCJprimlBSzvtHKdSXjykqjmh3dldz50Hl+dGSK+z5yBT86PMnTF1w4jCJGWCZJeKJplsJJwsksy6Ek37qlj+eH3QwuRcrb6DNzIb74yHn+aHMLV7ZVcGhUmJG+67J6/v7IJDqVnP39dXz3XWs5NOphIZCkuULP5g4Hk94YVWbRQPzPQ+Pc0l/HB65oxK5X8dNX5jg+6cesVaJXyzHKRFrhi+Nebu6vpc6iJZkr8IHLm4SEVC4jnc3z3edGselVqBQy4eNQZWLf2lqUconlUJI5f4w19VZ6a8wcG/ehVckxqBUEE4JufnImCMUi9VYdkiQSCq06Jb5Ymut6K7myzc7QUpQ9q6sZXo4w64vji6VRyWWsqjVh0SipNGv4b1e3UCgWkckkXKEk86Ekf76nh4MjHmZ8cdY2WNje6UCvVpDNFXlhxM2E+3WT3Hg6h1YpJ5LKYjeouardgbyzkkKhgFqvYjqS4tND5/gf795DtVnL1Ml5/v7YFCq5DINGgYTY+u9bW8NllRpePDHBlgo5rfIM2miIU2cmOXNuCkMsjCUVw5aOYfL7KBxfQJWKoQwE+Gj80iYegE9AwWjkMqsVr1LPbFGN32ylf10b39SbGE4r8Cj02Osr6WpuQjM5yp2HFxhOK9GWTPyvaqtgvnTvr7Vqy58tmSSSVbd1OoiWQhb299fy7JCbYDxLNl8gns7RU2MqyyPkMukSz5xai5Y/3t7GXCDBj49Pky4B8nft6n6T2We56V9Xx3I4yTeeGmYplOKGVVU8cmaRC4thfNE0jRV6fnh4ikfOLGLXqzDrlMz6E/zpte3kC4UytTyUyBJMZFkKpTg1G2Rbp5PDo14WPdnf5KPzP71+10P916uVa3/f2lrCySzeaJoi8N1nR9m/rpZ6qw5fPI1dLyQkAwshZgNJMpkcJq0Cu15Vku+EabDr+L0rm3ll0s+WTgcLoQQ1Zi2/d1UTipJ/01IwiTuSYluHk1Q2jzss7plfv3kVx8a9FIpF9q6pwaJVksoWeGJgiSa7jp4aM3vW1JR9dLRKOcth4WvU32DFpFVyVZudj//bGf7+yBRFRG/ZWWXkf753HYWiuK94ommcRuE7E0pkKaqFpC+UyNJZZeD63irWNVi5qk3ItE/PCePtQlFYP7wwImLoK7dpUMnFe9IoVeQKBZorDPzRv5zi+RE3yUweT1SEAe3uq+bj29v4xpPDfGZnJ311Zqx6FTP+ODIkbuqrEcQNRBr0sTEvf7i5hd191YQTWZ4bdhGIZzg44ubDVzbx7JAbTyyNqiQ5LnIpKPSvr85i1Sm5qrWC+04sYNYqMWuVNNp1XNPlZMITQyGX85kbunhl0s9CKInTqKHOquXOG7uFvYBbME53dFdi1iqJpQXLat/aGhaCifKwHE1ly7YPoXgWuQw2d1TQZNe/6VrL5grkCkWaKvQ8MbCMSiErn1tJEn6JD5xa4MNXNfOuH71MlUmECp2bD+OJprFelLTnjqTfcQT9ypDri6WRSUI5gAQyBGBVKBbJFwTYICF6yLt29XBkzMNcMEF/o42lUPISueKOLieraky8OOGjqULP71/dzOYOB+fmQ/zwyCT7+2t/6bFplHKRshtMUm/VEU3lyBUKhJNZTs8GaXHUveX3XFx6tfDn+rvDUzx4aoFwModckpDJBD952pdAIRcp38W8WHSqFbKyBF+tkFFhUGHSKggmsyyFklzWZOPp88sE4lmUcqnsRbW1w1lm1oQSwrz+Cw8NMO2LIyExsBDmqfPLfPvWPu7e28ODpxcYc0dpcxqoNKmpMKhYVWvm5v46VAoZzwy6+OIj50lnC+IzXfpgzweSXJxjtqKiuVi29dKknzt3daNVyVgKJi/xbUplC9x/ap5cocinr+vgnqeG+c5tfcTSOXyxDDP+OPfe2icW+x5hIbJ7tfDtOjLmZX2jlUy+UJ6pfvLyzJvMtt+Jd5LDqObOXd0cHPEw5opSbdGyd001nmia54eEt+TWDgcOo5ovPCRM9StNGm7pr+X8YqjErhfL05XjCSUyVJk1FIvCbyoYzzC8HCWUzLK5veISCeAb683n0c9Lkz7u3NXN1e0Ojo77UCtk/P5VzeSLRaa9MdY3Wrm2p7KsEFDI3vpnv1W9kZH1760qs4av7VuFO5LmhRE3CyUPu8tqfzMSwd90/Vqg1J/+6Z+yd+9efvjDH2I2m3nllVdQKpW8//3v55Of/ORv+hh/V++w3kjVU8pltDn1fGRrK61OAw+dXmA2EKfapOWjW1tRxSK88MBBkjML3KBKUp8IkHlinuWhSZqWl3go4scSDV5iEL5OpSJqdVCoqcVrtOHp3oTzlhYqu5oJWyp4aLnAgYBEWqtnOZzmFx+5gp+/NsfZ+ZAw9SvphHOFIgNxGeszeZLZAsuRJGfnQ3zkX07RXmng3tvWIEkSGxptPHJ2kWqzhvUNVr51YIT5kmfP2bkgKoXE5nYH3356mMHlKKlsHqVcxpExL1/c3cOqWjP/38szqJUyfvj+9cgkEUHviaZxR1I0V+jJ5oW/kU4lJ5cvkC+UBmjg6nYHh0e9nJ4LlujyTmYDcY6N+7j3tjXki0WOjvtYU2fh8mYbFr2KYhGu667ColWgVsr5zjOjvDTh497b+lgKJemsMokYZJnE3Q8NEk3l8MXShJM5TswEuX1DPT8+PsajZxa5Y1MD6xqsnJkPMe2N01dv5l0b6qm3aXlpsoBaKSdXKKJWyiGVo91pwBsVdOVUrkCtRcO4O8bfHJzgr9+zlgqDCoVMsIpG3VHOLYR48OQCX76pl+YKPQdH3Ex642VT5xqrlllfnEzu9WvAZlBzdVsFRo2Cjkoj7miKV6f9TPsSZWClq9LIkTEPV7VW8LPX5jBplWzpcFBr1vDF3d08ObDMuCdGU4WOrR1Oxt0CTDk7JwbP/76llX84NolZp+CGVVUcHfMy7omhUgj2WZvTwNCSkD9qlDIWgkmS2Tw1Fi2LoSTrGq28OOEjms6BBIWCMNvf2VPJw2cWkRD02k3NNrqqTaXYXiGrkElSCegqlk0lR11RsvkC+//2OEc+u52/uaMfbyneemEoSVeViW2dDr58Uy9/dt8ZvJE0LU4DqlKzsqXdwZZO4X+hVcqRyeD7B8f50fs3sKnZztXtFYSTWR4/t8T9p+YpFmE2kODG1dUUKbIUTlEsQqVJy89OzAn2S4eTG1dXiQjsQpGBhRCf+NkZ/uaOdSVPkSL/+uocO7orUSnkjJR8E1ZqZdiYCyQJJ7I4TBp8sTRPn19mLiA2aTf313JniYK9EExSZ9VxeYsdTzTNgQsuruupJFcQA8B1vZWcnQ/RUWlgU4udGouG921qxKpT8ujZJeLpHIuhFPU2LVe22Xns3BKnZ4N8eW8vm9sr0Krk/OVta4ilc/hjGeKZLJ2VRjQqBbGMSPY5OxcinMyyvctJi13P4wOLwmur24lWKcdp1OCOCpB4zB0lXyjy1AUXzw+7+cF716FSyGiw6fncA+cYc8fKkeU1Zi1/el0HO3uryOQFzfvankpOzgbKBqcUocmuY09fDRqVHJPNzNExL8/G03x092aO6CY54vSWPeRkJR+Gq1or+MPNLfzxv56iv0rPtgo5rYoMqkiI4yfGmB1boFOd5QqLRHxmme5cHE0kBCdPoPf5uSIcQhGLXnKv/7vSfxNKDTG9Cf0PHfyBxsj2vIqg2kjCaCZuMBPVm1mTaYHcPKujbqYGs3gazXzrlj5OzwXLTd41JUnyynNjZZssYs/TPDGwXKbc7+ypZEOTDblMsEvfuPUDyBeLHBnzlRNzVAqJcY8A0k/OBtnZW8kzF1yMewSTzoySDY1Wrm53cDGbP5N//b7z5Pkl7ryxmz+7roODAzO88O95OP6W1e96qP+6tTKE/e3hcb60p5ev3bxKyL7kEk0VOlLZAoUifHF3D88NuVkMCmbP5nYH4+4odz92gXanke++ey0//MB68gUIJTM8cmaR+WACp1HD1e0Voj9pE+bWhUKRHT2VfOfACO2VRtY3WumqMlIAfDEBjq2uM3NqJsCJ2QDv3tBQlpKdngvyxYfOky+CXi3n6zevwqBR8PWbV3G0xBJvdQgZbyydxR1O0lFlpN6mIzniRi6TEU+LrbtJo6DSrEEhk/HH29qoNKl5ftjNv7wySyydJ5IUSXR2g4pRV5SNzTYmPTEa7XqOjntxhVJ0VBm5psvJ0c9uJ5IUQI0rLJ61dRYtkWSGj2xtxaxT8sCpBWb8cWFz0O5Ao5ITiGVYDCeptmj51HWdGNVyVAo5h0Y8XNZkp96qpb/RgkwmfP7UCjk1Zg2RVI5EJo9aIUChQrHIz1+bY2dvFXv6arhjUz1z/gRr6ixs73JSZdZgN6iFhE4uo8GmK0uRBhZCvDDi4fJmOzu6hFH7w6cXaK80sK7RxrQvXgIpdK8zafQqLKXeuLlCD0U4Oxfm6fOuS/xyAJbDSQ6NeNjUYsNhVIt0sJKsWSmXiCSz1Fl1hBIZikWIpLJolHLGPVGK8B+KoK8ya9Cr5WRyRa7rqeTZQRcz/gQSAuzprTVxRWsFI64oq2rNVBhU7FtbSzZfIJTI8JXHBjk9H0JCsE6evuDiO7f1cX1vFVadklvW1TGwIACpdK7wK4+tWBTnY8Uf0W54HXBbDCUv6Xl+WcllEvU2LWqlDEVGhgRlT6eWCj2FogAG8oUi1WYNy+EU8Uyu/PN39lZiUCu558lhAnFxjX7hxm5enPASiGdpKakRVn6HGqWc7mojP31llhlfoizPLxSLLIVEUucNqyrpr7dwTZcTXzTNcihFNJnj608Os6W9go9tbyOSLC1oLvqVqhUyuqoMyEu/519meH1sTCwl2yuN5US/lVLJZXRWGsrJn8FElng6y+Z2B3/x2AX66i1s73Syo7uSTC6PRa/kwZMLpHOFS1hQVWYNX9zVzUIwiVkngF1dCaB5u1phJB0d96JTyrmq1c5Na2pIZQukc3lOTgfwx4WiZH2jlYMjbsbdMSpKn8kV64+XJv1YdEqWwkIxoVXK2bOmhuVwqjxXOI1qtpVUKt95ZoTPXt/1lul6v+o87u6rps6qpafaJECyB8+zEEyU/TvrrNq3XOb9svf/RkbWLwPM3qqUchmRVI6/em60fNwDC2GODf12hqn8WqDU2bNn+dGPfoRMJkMul5NOp2lpaeHee+/lQx/6ELfccstv+jh/V++gVrYYr44uk5hdxBb2co0xS//Dxzn36iD1Hjdrwl4akiHMAQ+yZIJbL/r+nM1O0GjHIzcRrGwl3nslPlMFEyozDavaeO8tl6OtruIrTwyjVcl514Z6/uLBAaa8Me6wNXDb+joOPjZIVp8jlsxRRKDQ7U4jL036UcplFIvFsr5339oaAokMG5ts7FpdzZnZEJ+4po0tHQ7S2TyLwQTfeWaUYxM+fvDedTx5fplXpvzUWbTIJPDG0qyps3BwxMOrM0EyuULZHO+16QDHJ3zsWl3Na9MBPnhFE/U2Hadmg1zd5uDAedcl3guucBKTRiTQ9dSYuK6nksOjHja12NnTV82evmr8sTQnZoMEYhnu2tVdBmq6q4ysqjFxuOSP0mgX4FU8k6OlQs+EN8bN62ppqzQSSmRZCCYYcUXorTHzl7evKVPsq81armi1M+mN8dKEj1qrlia7jlQmz4+OTFEsCjnTju5Krumq5OCwB3kiI1JKNAoqDCq2dTp55MwiBrUCs1bJ1k4nD51ewB0RN+Ad3ZU0Vxgwa5XIZcLHiCKlG+gAU744KoWMMXeUlyb9fG1fL9+8tY/Vr84y4oqW07hm/Akua7IQTWY5OOJhTckY2RMREsJrup0E4iLO9/CoF388w6Nnl/jZH2xiLpBgXaOV7V1OXOEUD56e58mBZX7vymb66y0cGBS+W3VWLciKTHnjfKEEjEx54ySzefb21XBhIcSEN142CG91iGN74NQ8a+osfPb6Ll6Z8nF6LkRTyZdAAnZ0O9m1qooicHTcx5ExLza9ilvX1dFXZ+GJ88vCOwnKiXkilUTsYBeCScxaJd88MCKM6gtFDo54OD4h0pO+c9saXJEke1ZXM+6Ksq+/lmqzRjDEAglW15q5ut3BH2xuYdIb48x8iB8dmaLOqiWezpHJiWu4yS4MxvOFIm0OPSqFjK2dFTx9YQlfLMOT55dZ12jlwKCL67qreOzsEulsgeeH3bxrQz3PDrqY9iWEWXQ8Q1ulgQtLEZRyiWgqRzqXRasUD0qLXsVSMMkXHh5gOZTCqFEgl0kcGvXwzVtWs7uvBrkkMemN8ZOXZ3hiYAmNUs7xCR9/el0Hxyd8FIGv3twrNtHDHp4cSNJZZWRrh5PLW+z866tz2PXiGnVHUjx8ehGFXOLAheVSDHiC03NB5kuGj9d0OZHLZTx8eoGTM0Hq7Tqu6XQy7Y/z6fvP8le3r6Wj0sTJ2QDrG6zU1JgFGDLqJZHJY9GKrbtSLiObL5a3wUfGvARLCXcUIZXLM7gc4bWZAB+4vJETMwH+/ugkH7qymT+7rpNXpwPM+OJUWzRsbnNg0ChIpHP8j+fGmA0kCMYzXNlix25QC7C5ZNwLAoSvMKoZdkUIJLI8MeLjgVyez9/Qzc6rV9GyegPmWAalHBQNNuTRFPcPe5hwR6myaNjW4cQbTeMLRbnCKifvCzAxNkdlNo49HSPj8eGZXUYfi9AgpbBPzFPlcmOcimCKR9Cn4vAzcSy/WLnR3wUFs4Vem42sxUrKaMGt1OOy29F1NaB0OsBuR2O3UzSaeWokwqtB2LG2kZvW1qFRyvDH0rw04SOdL7Cl/dJGKZXNk80XyswtgExOeMaYtUpenvRxbbeTn/63TaSyecLJLOFUllqzMGaNJl9nQankMuKI5qnBpmfCE+O16QA7up2/2Yfnf3L9rof6r11VZg137+klmMxyeMTDfDBBpVHD5pJBslohw2lUc8u6WmLpPBPuKA+eXuDJ80vIJIkNTTaKhSI2oxp3JM1fPTvGUiiJK5IimyvwyNlFvnVLH0fHPGzrdAoGcyrLJ6/t4JUpHy9P+lhbb8EdSfHihJ+F0pLhup4qFoJJhpciKOstHBhc5opWO7dvqGdVrRmnSU21WcsPDo1j1qq4rMnK9k5xD3rg1DzxdI4/3NLK0HKEze0V/OLEHJFUjiqzhlg6R71NhB0kMmIZJJdJpSGygCeaIpcXEim9WkGb04BaLqfBpueLD18gnhGyuEOjXp4cWOae/asxaQXAN7QU5o6NDdRYNAwuhnEY1Xz18UEiKSFNe2UqwIsTPj5/fRexTA6HQaTQpbJ54pk8r0wF2NwuJDZFimiUcpKZPDVmLZ7oMkaNAktpWE5l8zhNaqa8MQpFqDCo8cfTbGyyc32PCHJwmtS4wykOvcXAmMkVODzq5diYj6cGlsvpZHq1gkKxyJo6C1UmIftaSflaWGGpSBINNg1bOhw8cX6ZB08vlK4owcb4xv5VxNN57nlqmElvnClfjP39dTxydpFMTizRLDpleTl4eFQwSVaWeXVWLWdLUsWL61fJqC4upVyGTS98KzVKGX9zxzqeH3YzH0jQUWVkc7uD+UCCdDaPJyJAhet7q8nlCxwa8eCNpUus4yJKuYwZn1jyvm9TA4lMnhFXlL87PFEGR37Vsa0s498ItP1735dGKWd7p5OjY15enQ4QT+coFKHNIRQZaoWMZDaPQpJxRasAN6d88TJwtWtVNS9NCpmWTJL44ZFJtnY42NBko9GuKzHULx25FTJZibWvJFPyl1UpZChkMmb9cfIF+IvHBrm63cGu1VV0VBrxxzNc2+PEYVCjlEtc0+Xk2JiXCytLWoWM3loz2zud6Eqv93aG14VikdlAQrAq11bz2rSfswuh8rH0VJvY2unkwAUhkzs5E2BrpwN3JM1X9glG5qNnl2greXh5I2leGPG8iQWllMuoNGsoQHnBWf8rQJYVRtJcIIE7kiKeztPi0HPP/tX4YmmubnfwylQATzSFQaNg3BNDIZfQq+WEE1lemhTyuRcn/MRSOeLpHEq5jN+7qgmdSs7nHxxgPpBEq5LjCqd4dsjNPftX0+40vi1z8JcZh4vkUBEWkMsXODDoIpTMUG3WopS/7tv5TlmJb8fIeiOo9auYVCtA2tIbEgwXg6lf+vr/p+rXAqWUSiWyEv3M6XQyNzdHd3c3ZrOZ+fn53+gB/q4uqmIRgkFYXHz9a2npkr/XLS7yN17vJYl0OZWaNUY7fnMFfouDiq1Xck5hwtnVygV0/Ggijdtg568/tIlzCyH+/sgUNr0Ki07J9q5Kbm+20VyhRyEX7J71jVb+8dgUV7dW8J3b+jhakmNplDK+/55+nh92c35RJMXUWXU4jRqePL9MKCHSouqsWhwGFTf0VhNOZrh7bw96tYLVdSaCCS0HRzxsbLbx6rSgQzfYdFSaNOUHQCIjJGuBeAanScOYO1oGpGQyCTlC4z3mirK7T0QIr2uwkszmeXJgiWt7qvjmras5OuYlnc3zg/f288qUn8VQskyvBfgfz43xz7+/iZ+8PItSLrG+0cbaeguhRIbnhtzE0lnu2tWNQaPkEz87LVJYhFUSR8c8/OgDG1Ar5fz4Q5eRzRcYdkU4NCIM7/QqBc8NuTFrhTfX7r5qCkVIZnJoSlTsFfTeG0vT5tTjj4nz99iZRd53eSNfvqlXHHcwSYNd3ODT2TwalYw7NgqG1Yw/zrODLiw6FUuhFBatEodRjVySyBcKVFl0/N5VTdx/cgF3JI1dr0KvVpDM5Hllys8zQ27u2NjAHRsbSOXy+EvJJQ6jmlwBkrkCV7TYyxHyrSVjZBkS6xstLASTRFJZjBoFk54YyZIZ4KtTfjyRFJGU0HFncgXG3FG2dzk5vxDmmi4nZp1gFR0Z8SJzSeWIaV+Jbv/F3b0cGRMmii0OA9f2VGLWKNjRXcmhEQ9ySeKWdXVc1VbBUijFg6cXeHZomXv299FRaeRrjw/iiqRLyWdm8oUiO3srOTLm4dXpADJJRNjXmLXs7Knk7HwQp1GNUa3gyJgXVyhZlhwq5TLmg0leHPeys7cKdzSFQa3gyzf1EEnl+OJD51kq+VQNLkU4Nu7jU9e2sxxOsa3TwYELy6RzBQwlT6EGq76c5qdRyNnc7oBikWlfnC/v7eXV6QBn5kI02XUcGvEQSmZoLTGznr6wzKZmG9+8RXiKSEiEEml2rarm/EJYePKUANVqs/D7SGZyTAfiXFiMABBN56g2axhainL/yQVu31DPfSfnefzcEtGUaNZMGiUXliIcGfOyqdnGqdkg9VYd33lmhOVwiiKiAXn6/BL33raGz13fSTJbIJzMMLgUIZBIY9aqqC9tmL/3/BiuSIpCochxEOfoug7mA0keO7cEwIHzLr59Wx+dlcJX7V0b6qk0aXh50s+RMS8fvqqZWX8cSomWCplIl5RJAkwsFEQksTeaxqpTlg3dlXIZS6EkiUyevzs8iSuS4iuPD/Kl3T3s769lMZTEE03z+MAS6xutnF8MM+WLIy993p8f9nDrujqOjHkIJ7MEYln0ajkOg5orWuwsh5N85aZeHKXrJ5Ur8MiZRU7NBemoNPK+TQ24Iym+9sQgr04HRVy7BM8Ouvn2rX30N1g4MR1gzeoeGtrbefq8Sxjz9ujZ3uXEHU2hsesxKuTCE8wfp9qs5eomM/ZMjMDsMmmXl2ZZisiCi+mxObyzLnTREMZQGGPcR9XEEPKjMfD7ISuAIS3wsdJXQaUiZTSTMVupczpodFSQs1iZRYOptQ59bSVBjYlTMRntPY3UZYrk0xlkKiWDS2F29lZyajbIvv4aJEniwdOLeCIpmirEAKWUS2hVctQloHQhmMSoUZaH3a0dIt1oaDnCjlbjf9JD939P/a6H+q9dK9vpbz41zJQ3znwwQaEAD59d5J79q3l5ys8t/QLg/evnx3hiYJl8oYhOLeerN/XSVKHnqQvLbO908mIpAQsoyfQlprxxDo546G8QS5z9/XXM+hMcX/ZxZWsF79pgxBvLcO8zI8z5E+QKRbL5Ii9O+Pji7h7MWgVPX3BxaMTDrlXV3LS2hmcH3Tx9wcVHt7XQZNdz/6kFfvbaHOGkkPkWgU9c00YokeHZIRd/ck0HX9+/msOjHpbDKbqqjOzoqqTKpMETTXFs3IPToObyFjtHRj2kcwW80TQgw65XcV1PpeiVxr34Y2kMJePvQrFIKJHhifNLXNFix6pTsbuvGoqgV8lZ12AlksrxiWvaOTkb4OCIh3haAE9PXVimv8HKh//5BJ1OA9+8tY9wMsvfH5vkL/au4geHJjBpFexdU8ORUWE4/fCZBSY8ccG0Namx61VsarZz4MIy3dVGNrdX8OCpRQ6PelHKhVT6o9ta+cbbDIwOo5o6qxaZjDITpFgU0sZGu55EJs/V7RXAWzNItCo56VyhbBS/UgtBwWg+VvKviqVzPHR6gf56K1+/eTUnZgLCgLoEPg4uhXl2yF1Ovzs5E+T63irOzYdYDL0+kP66EfQapRy5JGHVF3j3ZfUUixBIZHhuyMULwx6+c1sfh8e8PHZ2iXUNNuqsWkbd0fIMsLJMXEkGVilkPHJmkR8fn6ZYBKNGWU7dk0uClftWg/fKMn4F3PuPvK8qs4a79/ZyaMTN8HKUepuOHd1ObHoVFxbCuCKpstfiSpralC9Om0NPZ5WR54bc5Z+VzhV4dsjNs0Nurmy18yc72t/0egq5RJNdj/UizyyROVWkr86MWi7ju+9eW04If/qCC7texfYupzD69saps+v48k29HB71MheI02DTs63TQaXpdXnWG1U0xaK4H0RTWWw6Fb5oGrlcxjdvWc1TF5aZ9glP1q0dgkE9vCz6wiNjXrqrTdRYNIQTWa7rqeK29aJPz+QLPHpmsRx68kZjelc4xTcv+sy8/DYgC7yZkbSynJryxsv9pjea5ms3r+LZIRfFIvTVWhh1RckVivhiGR49s0hvjYlv7l/N8UkfJ2YCdFQaee/GRh49u8jgUgS1QgRNAOWffVmTjcOjnrdk5/0y4/AGmw6FXKLepiOaErYDVp3q12Il/jJG1gqoJZdJ74hJ9cuAtN/G+rVAqf7+fk6cOEF7eztbt27l7rvvxufz8dOf/pRVq1b9po/x/836wQ/EcPBG8Cn1BnTT6YTaWvG1cSNSbS3U1JCprCJXXUO+uoZ7X/XwynQAhUwiWyjy3Xet4b4jk1SbtNy0tgbVQwPkSk3ObevrODLqJV8o8pFtrdRatLw47uPwiIdKk4ZtXQ5291VzfNzHPx2fYnuXk8uabVzfW4XTpCaZydNSIcz3YqksD56aZ3WthXv2r+b4hI9Tc4GyeaYwqIYZXxyTTsm0N85XnxhEJZdz46oqFoMpJCQUMuHl1O408MKwRCYv6O/iQb9ykxAfvnxBUJgloM4mktfu2FRPZ5WRUCJDU4WB/3lwgs3tFWxstqPXKCgU4breStTyFb8ZFX/8r6fRqhUUi0WubqugiEiD8cYyHBoR0ey/f3UzuQK8Nu3nilY7X7ihC7tRTSCWxqxVEknmeHbQzWxARAJv7XBwS38dmXyBzz84QDiZZSGYJJXN01VtFIkjU36ubnfwZzs7cBo1pDJ50rkCH9vexj+/NMMVLXYua7YBItGmwqACBP1brxJMrz/c3MqkJ8ahUQ/PDLqw6lUY1Apu7q/BFUnxVCmhpNmh57ruSlqdBkKJDJVmwRwpJ1xIMOGOUigU+bdXZ1lVaxGAlkziSMmrIV8octdD5xl1R8uymwPnXfz1HWupsWj5ySuzZHNFDGqJIuCPZ2iy63ht2o9SIUNWokMXgXanAX8p3toTTTOwEGZHl5MtHU7mAgn+4CcnSWULyCWJP9jcxEe3tbFvbS27+2rI5wucWQjx9PllGu169q2tFTI5SUKSJKa8MRLpHO/f1MTaeiuPnl1kYDHM1/atotKk4fCYl4dOz/NHW1r5+s2reWHEzeBihDX1ZrZ2ONGr5VQYlPzo/euxG9TM+gVjS69WYJFLrFBj5oNJVHIZh0c8TPnifHZnJ69OBYiXgNSV9+uKpDg9F+LqNjvuaJrvvbuf12YEI6fepuOKFjuhZJbmkseCVa8kky9wYjrAvrW1XNlqZ12jFUVJavXKpJ/tXU6eGlhmyic+Rx+8vImtnQ6aHXqMGgUapYzP39DFU+eXmSglq+3oqmQ+IBhKq2vN5Q1ZMpMX0kWd8F3TKIX5bSydK6dLykqeZlPeODt7KlldZ+G5ITfzwSRKuYxcvoBOrSCYyHF4zMtVrRX81bOjtFca2N5VSaNdx5cePU9vrZnDo15GShJJq06ARBeWwhwccXNlm52/PzYFCAPPI6MeruupxB/LEEhk+OwD58pg9dVtFZh1yjJLM1JquowapWA4ZfK0OQ2cmAkgl8vK3hrpXAGbXiWAqax47xIQSeVYDifZ+zcvoiuBTDt7qxhzRYkks2K7rlPy0qSPbZ0O7t7by2vTAU7NBumuNnJ9b5VoEKQiB4c9VJWScr5zYITFUIp8QQCNW9orOLcQZiGUEg1fUhi9BxMZTs8GuXV9HVa9inAqy71Pj3BiNig8JCQ4NOLmb9+3HqNWiQTsW1tLrlAgny8yF0hw1zML/PnuHh6OiI3vSFWEJ1TLSKsoN6aZfIH/vqWV2zfUoVfJUSYT4vnj9xNZXCa84OHoyyNsMBaxJCMszS3DnBfHxDRtiQiKR4PIImEcwA2lR1Mr8EEgrtET/5oZS10VP6iwk3rUwrFAEYVch81sYUFn4oFKB++5sR9tQzUyRwV33djF0XFf2dPq8lY7iUweh1HNXf3d6KRLjcH/b6vf9VD/tevioSKWzpWXAOPuWHnwOTji5qa1tayqNXN8wk82X+DW9XU0Vxj4/AMDBBIZtnU6GVgMsxxO4TRpMGlF4EwmL5Y413Q7GVgIs7ndITyFCvCdZ0b5hw9u4OCwm/MLEbJ5cU83ahTMBxK8OO7l9g31LASTXN3mIJTM8rUnhvDFMihkEo+dFWlcL074SGTyRFIitKW5Qsf2TidHRr1Um7VMeKM8OeBiS4eDHV1qfLE03mgKmQR3PXyBKV+MSqOa37+6hU9e23GJXHhbyftPJZfhjabL70t4IolebsIt0gJfnvJzdasdfyJLvsSKGloKU23Rsr3TSWelka8/OUwik2PcE2NnbxU1Zg3BEot7a4eDv9i7Ck80zQvDbr60p4dnLrh59OwitVYt37ylj0MjHqZ9cVbXmbmupxJ3OE2FUc0dmxo4Oxfi/lPzaJRyLFoldVYtxWKRnmoT3mi6bNq8EExyfMLH7Rvq2NNXw2VNNhZDSQ6OeHj07CKNdj07up2YtUr8sUxJavdmBkmdVctlTTY+fFUzPypJ2FZKJpPKg2o2XxBMmscvsKevhndvqKfBrmM5nMJhUPHkuWUyuYJgaigkxtxRPnBFI1/c3VP2C/yPRtArFTJS2cKbvIrqrFqsehWLwSTpXIGvPznEj96/ngabDk8kjUmjwKBRoJQryRWKVJuFgfiGJhvxTJ5Jr/Ao2ttXjUmj4P5TC8z64287eFeZNdy1q/vXfl8Xs02qTRqu7apk9+oapJJH2oMnF3hhxMO6RitySeLUTABXJM32Tgc7uoW0zhNNU21569d7O8bWxYDaXEAAB4VCEYtOyeUtdoxaBXK5xNefGCqpAoT89dx8iLv39qJWyfnJSzNc3mJn75rqst+cSL+WveXriOCfIsvhpOg1W+08NrDE8FKEL+7u4bZ19WRKXq0apbycKr3iuxRMZFjXaKG5Qk+x+HoiZCqb54+2tr5tUt2vAlku/p43+iOvLKey+SKT3hg7eyq57+Qc9+zv49Z14nstpT7s1GyQQrFIOJXj0TNLfOXmXnb2VLK+0SqSf7N5DGoF//OOfpwmDaFEhmcG3TwxsFT+2e/k9/XLAFClXEb9f4C996sYWflCEW80/SuZVKmS13Dtb2nS3lvVrwVK3XPPPUSjwuPiG9/4Bh/84Af56Ec/Snt7Oz/+8Y9/owf4/2x97WtQVyfApoYGuOIKqKl5HYCqrYWqKlC9dSqFqvQVT+eot8V4ZTpAvihMqt0RMfg/fnaJjS02vnVLHy+MuJnxxdEoZPz1e/pZCCWw6lR87fEhgokMcplEOJnjpQkfX79lNd9/71pSWWG2GIhlSGRzTPviVBjUqJXyUmS4MAZ+7OwiX9wjGAe7+6qRSxIPnV7g8YElkllhmqmSy/jKvlXc0FvNw2cWCSeztFcaOD0XJF8o8uqUSDR5dtBFMCFuzA6jmkgyy7XdlTw5sMSIS+jlpaIwYNze5UQuSeztq0EmwXg0zZYOBwMLIkr+H49NUwQ6Kw18+7Y+fv7aPIlMni/v7WFdg5VXpvzYDWokSeLx0k27xWlg75parmipoMqiIZcvsLrOQl+dhYMjbia8cW5eW4NFp+KrTwyJhJS4YBc9dX6Jn/63y3nwlEitSWUFu0splzHhjnN41MNlzTZOzPi5vreKn702z0OnF1Ap5PzVu/r4893dmLUqkpkckVSOcDKLqeRRVCgKCnEqlycYz/CdZ0dZCiUxahQoZBI3r61BpZDzuQfOcX4xLC6SYZFQ8rfvXc/mdge/ODlPqJQaWGfVYlQraHUakMkkru2p4oURN1MDIjZ5e6dTyN/GvEz74yjlsjKNeTYQ5/iEj5oN9Tx2bgmDSlHW3XujaTa3Ozg+4SOXF0BCIpOnzWFga6eTI6OecipiqGTE/IWHBvj6zau5eW0tvzgxj0Ypo86qK/s/hJNZPvavpxl2RZEQYNrBEQ/ff08/kWSWg8Nubltfzy3r6sgVishlYNWr+MDljVSZtXz2gXNlT4TXpoL80bYWbl5by+3r618HkUJJzs1HcEc9vHdjI3UWHSBAmUJRRiKTJ5XNU2EQSTm3r6/HG0ujlMsYXAqzFEpSadLgjaaJp/NYdEoWggkcxlpMWhXZfIG9a2oIJ7Jkc3nMOhU1Fi3d1SZiqSwHhz3EM3luWCWSkr7+5BBPn3fz7VtXs63TwafvP0tThZ5v3drH4VEP3mgau0GNWiHnxXGRdnJlWwWDSxHWNVq5vreKUDLLoRGP8M1YVcW2TkfZZ2oFcDJrlTQ79KSzBVqdBl6e9COXSaXPt9h4rqo1UQSaK3QcHvGUAalwMluOyZ72xrm+t4qXpnw8U9oefuPm1Xxsezs2nYrh5QjL4RQKmUQ8naepQrCnprxxdnRVinSiogCdxz0xdvQIUOvwqJdIModVrySUyPJ86Xf90oSPfKFIIJ4hlS2wqlbLnr4aIqksN/fXcn4xzPBSpCyt6KkxsXdNDc9ccCEvGZLWWrTs6Hby6pSfYhE0CuHftpIUeHzSj4S4d0kKGX93eJJPXdvB9b1VbGq2ESqlKmXzBe55coRJb4zvvmstz1xwMeUTBrfxdI5kNo9KIWfcHUMmgSQJJgEIb6rFkGg6OquM/Py1OfrqLPy3zS2l4UYA4IlMnueH3Yy6onRVm9ja4RB+ZkY1vTUmDo952N7p4OCIh/df3si5+RBTvnh5aGhz6tnYbOPxc0ts63RSbzOC0Uiqth6pt49sNI1zW4yEUc0f33eO2eoEMplEhV7F6lozX9zdjVUtI+nyIvn9+GaX0McjSIEAi5MLFHw+qrJxGkiRmJmjZ9nDpngEUyKCKl+S63339edXvVLJe202ijY72G1gt5O32lhlt6NwOojofrUnw29z/a6H+q9dFw8VK56VK8/oSU+MnT1VPDvkIprMcEWLnUMjnjJr9tCoh8VQkiqzhkA8U0rLdBNL5TBqxH2Oolji+KJpWhx6lkNJLixFuKzJRk+NiWy+wMBCmGAiU34uh5PZMgOxUCxSZ9XS7jRyaMRTZsgCPD6wxOo6C5+7oYtXp/ycnQ/RWJK/++NpnCY11/dWlZ5HVRwe9fDYWcFk/dkfXc7hMS/BREakweWLfPfZUa5qr+CDVzSyt6+G8dLCrMqkYW9fDZ1VRs7MhcgVXgdfCkXoqBJ2BwMLgmUZy+T5xM/OlBcQwUSGZwZdfOuWPq7rqeR/vTQjzkU4SSpbQKMSBu5WnYqnLsxybMyHSiGnwqjm6QsiOOVvD01yWbONTc02dnRXIklg16tJZwtc212JJEl86dEL2PVqFHIJk0bJhiYb5xbCbO10sKO7kmgqi1mrJJzMUmXWsBhM8sKIhzl/gkqThjs2NvCejYJJlMkWiBSzaJXy8gC7wiCZDyTI5osUKfLUwBKfv7Gbq9oqeGHYLdKKEYDFSpS7Si6Sf7P5Ig+fWaTKpGFdo5URV5QGm447d3dzdMzDfCApgP0WO7OBBKlMnt19AsBQyH898+SLQZy3A4SEh45glURTObyxNNd0OXns3BLT3jixTA4JiWaHjs3tDrxRYbh+WZONnT2VyGQSKoWcLz5ygVn/yoD+1uyat0rVeyfv6618e7Z2Okhl83zyF2fLJuZbOxx8emcnjXYdCrmMm/tr+cTPzvDAqYXS60t8emcHO3uqODMX+ncxtpxGNZ+/oYvnhtxMeKK0Og1c210ppI3+BC9N+hhYCGMzqFApRPL3pC/OoVEPHZUGvv3MKE6DGp1agU4l5y9vX0NLhR7FG15u5fd0ZMzD8FKUSnMVWzucLAQT3HdC+JgeGvFw24a6sqdqKCuAqBfHvVSaNWzrcOA0ad7yvfyy8/1OQJaL683+yKUwgHSW7ioTGqWcu/f04o6kOHDBxZgnyu9d2cRf3NTLoVEPZ+fCrKo1cW1PJd5ImnyxyJ0PnSeRyfFvf3A5a+st5fTi5god+/trWd9oYSmUIpnN/9Lf18p5PD7hw6RR0l1txFoKArr4/e5bW8O+tTUshpJ8++kR/PHMO2bv/SpGFvC2IN/xCR8399eW0ti92PUqLm+2c3TMiyucKt9Laq3/hYzON2zYUP6z0+nkwIEDv7ED+l2VankZzOb/8I/RqxXs7K3i1ZmA0HnnChwaEZKswcUIf/PCOFe1VXBZk40bequpMmvQqoR87OEzi/jjoqmRJAmLTok/keHQiIer2uz8w9EpWh0GdvZW4TTpOTntx6pTMe6OMuYW0Zd7+2rK+vtxT4wr2+w8cW6ZA4Niw7auwUpNySPKqlPx2es7+fBVTVSaNNRatDxyZpERV5SHzizSW2vm3tvWcHI2wIQnRnOFHpNWgVIu49u3reHgsJsJT4wWh4Ed3U4qTaKp88XEh3NrpwNPJM1du7p5ftjNwHyItkrBHlgIJHn6gvA1CsQz3LS2hlvW1eKOpPjLZ0eZ8sZFUtmEj9em/Hzr1j6C8QyZvIjg/fjPTpcizOHW/loeO7fEYokxks7mkcskpn0JklnBvFDIZaSTWUr+yeSLRSa8cXZ0V3JyJsjaBis/fUUkv7giSQKxNGsbbMwHEjw/7GbWL0zFr+2upM6qLSd5fO+5Mfavq+XuPT0cHvMwWzLm3LumhodL6Ve5fLGs5x93x3huyM1t62ux69UE4wJIiKZy9NSY2dlThUouUWXSsGtVNYqSL5hOJadYLOKJplDKRAS9QibYUCq5DHckRSyVK9GwFcgkicubbdTZtGiVMr60R2zrZvxxKk0armytoFgssq3LyYwvzr+8MssnrmlHLpNYLG1Tru+t4tCoh1W1gr0kSeCPpzky6iOTL+A0rvgcCL+Io2NeblxdzeUtduaDCV6a8OOOpmi267m8xc6VLXYePL3AXAmQAkCC+04sIJMkru+tQqeSE0oIGcRSOEUqK5hrt6+v58UJHwvBBDP+RDnZb32jjYfPLIqYbb0KhVyiu9rEwEJYqG8TGWotOpRykXA2H0jw9KCLazqFceoLw24a7DrqgZcmxEDQYNeVZYvff36cu/Z0s6evhicGXFh0SuLpHF/a3cuLE15S2QJ71lRTadLii6V59MwiP3llhmIR/uW/bSKYyPD3x6aQS1J5A14AqkwaNAo5rQ6DSDKSiSaj0aZlW6eTV6b9bOtwoFXIWF1nwaZXEYhnmPBE2d7pxGlSk8jkaazQ89Kkj6VwinQJcF5hV8kk+MDlQioaSWaJprJ84PJGCkX48FVNADxdkjFSpLSd1xNOZoV0uCAkEG1OA4l0jgabjoVgAotOSbH07588v8xlTTbu3tvLiZmAkLzVW8pMzhXa+qeu7eD5ITeT3teTkex6FRubrSwEk9RatezocmLUKOmpNWHRKTBqFKSyeRKZHLesq2XcHWUu8HpT4DSqabDpiKdzPDfk5uUpP1+7qZeiBH/9nrVlr4hAPINWKWO2dN3ki0WWw4IhdWYekllhCKyUC3ZDTQn81ihl3La+nmg6y8ERL+PuKDu6nZi0Sr7yxBCeiGBeHR7z8vi5Jb6+fxVmrZI/2tLKXz47wrXdlQwuhak2a7hzVzcHLrg4txASPnEdTmb8ce4/uYCy1HSvNDXzQeFLtrO3ikQ6Vw5SKBSLmLVKOquNZPIFspKCiMmK1l5Bob6ZcBHkkgyLJDZ1SrmMZL7A958a4ecn5igCFIvosimsySjvadHz+z0mdNEw+P1Ipa8VxpZsaLD8Z0Kh//Cz8f9k/a6H+q9drw8Vr4MHK0vztkoDgXgai1aYfccyeT69s5OXJn3UmLV4I2lqLBoUchmnZ4Nc01XJ88Me3JEUSrlo2VcSRY+OicCLh88sEkll2dlTSXOFnkA8Q4NdRyYnZHcg0oVDiSyNdrHB39NXTbEIzw25qDJryOcLXNNdyc4ecS80qhXcsq6OvWtqCMYzjLqjtDkMtFQYeHJgmXMLYept2jIr6OEzi9hK7BiRaCzubQq5jEfOLBFJ5vjotla+9sQQTqOaL9zYxXI4xZZ2By9N+AiVzJSLReioFDYAT55fpsmuQy4JdvZcIIFJoyyn2I27Yxwe9bCj28mLE77yuZAkIVESUfZhfvHaPEaNEoVcIpHO01NjYmAhRDCR4eCIh395ZZZ8ochHt7WyqsbMPxyd5N7b16BVyvnY9jY8kTQWvZIt7Q4Wgkn+6pkRPn19F60OPUfHQgy7Iuztq8Zp0vCtp4c5MyeMvHVqBSdmAty1q5uh5QinZgN86tqOsrfQxQySFfaKViknXyhydNzL2noLBy64UCnEosSsU7K908nLk35y+WKJPQItDr1g1S2EuL63CqNGiVGj5Lb19aSyeaZ9cZ4ZdHFkzFuWz71Tw+WL661AnO2dDqotmrcEhC5mlTxzwcWtG+r41i1icTbli9Na8muyG1Tcf2K+LHcDuGtXNy8Mu8um8Cv1y3x5/r0A29v59nz+hi5u7q/hkTNLfGRrKw6jmqPjXp4fdtNkF6DbP3xwAw+fXmTaH6ezUpjzO4zqfzdjyxtN8+KEl1W1Zq5ur8ATSfH4wBLbO51UmTRMeeNESl5h/niGeDpPlVnDqCtKf4NItk7lCpi0Qtb74riPBpsO9RteZwW4299fx+b2NIvBJA+fWeCxc0soZcLzbD6YIJMr8Pi5ZWb8cSw6cc33N1j54ZFJXp70/9Lr5u38jd4IsqwAfSt+W2+sNzKSVsIA+irM7FpdTY1FGM1/8+kRprxxlsNJXhj28HtXNfHejY3csKoKtVzOuYUQ//TiNL9/VTPfvrWPSDJLPJPj3gOCbS5SyuGZQRf33raGy1srUMkFM+vt3s/Keby5vxZPJMXhMS+LwSTtpfRBd0SkdU94RG95fW8Vf/Pefp4bcnNZk+0dsfd+FSNLIZPeFuQzaZR4IuLcrKREfmRrK5+6toPTs0EWS5Y4/VVqfhvXX78WKPW7+k+ot6D9/bpVbdYIkGLUw/BylBqLljqbji/u7ubFcR+DS2FGXBHaKw3IZRKJjAAY5gJxAV4oZCWGiUQ2X+D0XJC19RYePL2IXCbxxPllvv+efja1VvCJn51hyhtHKZc4NSfj7HyQP9/TS41VW5LDwVwwwUe2tuI0qTk44uHQqIeWCgNXttlJZfIMlLZQBrWCr97cy+ERkZAw4YmyodFaihtPsRhM8uMXp9nQZKWzSjAdVtIxzFolqUyehVCCl6cC/PNL0zTYdTRV6Mnk8ty2ro7tnQ58sQwHLrj4ycsz1FmFufKYO8bm9gpCiQyPDywx60+QyuXRquQYNQrcpeSxnhoT6WyelyZ9zPoTSJKQvtmNasbd0fIwrlbKy6wofyxDo13P4TEvaoWceDpPoVhEIZNKvlGCheGPpklkclh1SmotWjoqBVX8sw+cY9afKEsUnz6/zF+/p59qs4ZfDM4zE0jwNwcnuKLVzpWtFezoqhTeOnKJSU+MdK5wSbpVoQhTPpE495e3r+HQqIdxT4zeGpMAVgxq5v0J5oJJ5DIJp1GNQaNAp1IgSRINNj1VZiE3yhWKqBUyDGoFjTY9OpWcz+7sZC6QoN4mmheHUUMml0eSJPatrS0nlMXSOUZdEZ4f9vDYuUWcRi1XtNjLZuzeaJpmh56PbW9jW4cDpUISxpMycY0F4xmMWiVGjTATTWbzTJfAFZ1KwSd+dpp4Oo9CLnGw4OHImJc/39ONXa8un0vVRfry+YBoDpdCSZ4YWObwmI/mCj3BhEjIW99o5XM3dPHylI9Xp4RW/ZouJ9O+GA6jGn88wytTfmx6JVe22nlx3MdSKIlZq0IpF15VlzXZODDo4oeHJ3lh2M1337WWW9fXsRBMcs9TI4wsR/BEhSnoC8PChLGn1sThUQ83ramls9KA3aDmn1+aQauSs6OrkkqTBl8sg1oh5++PTDKwGEanFLK1x84tsbuvmqcvuEhkcuQLRTK5HL01Jq5qq2AhmOA7t/WVDdnX1JvZ1umkWITP3HeGf/7w5dywqppnB11MeGMlQLoSlULG/acWuLarku0lf6yZ0udBMKj0XN0uIp4vb7FzbNzLx7a34zRpRFNXkizesbGBTc02vvvcGIUidFeb2N7p5MCgi2qzhlgqR51NpN/Z9EpUchlVZk05Gc+kVRBL5/jSoxf47rvWsrOnik3NdqrMImXqgVMLbGl3cHTcy6QnxpYOh0i1iaV54OQ87ZVG9q2t4QNXKAnEMzx8ZpFxd5Qv7e3lEzva+flr83x6ZycbmqzolHI+f2MXzw4KILy90sDOniq0KhmPnF5ka6eDW/prsRlUuCIpHjmzxLgnxqpaE1e1itSczz0wUE5COjTq5oOXN3FmTjCYAokMFMFmMLKl3UGyFAHuj6f53AMDLIeFGf3uvmoeO7fEckh8PiNJkbIUSmZ5acLP1k4Hcgn2rRUN/Jf39pIrFDBphTzgilY7vmiah88s8sTAUukep8QbSXFk3Eub08iGJiveaJpjY142tti4aW0NT513UW1S86nrOnAY1Twz6MIfy2DQKLimq5Jqs4YHTs1zdZuDZCZPU4UeTWnYanHoabTrS9vYArG0Gr/OgGJDO8UrGuEt0vzeVIEA2O2/sWfk7+p39Zusi4eKN4EHHU6OT/jY2uHg4TOLvDDs4kcf2MBt6+tRySU6qoycmhMSlOOTPq7pdvL9O/o5Pi68hN5zmYZNLTaKRbimu5JpX5wnBpb48FXNBBNZKk0aTs1G2drh4PFzy0x6Y+XjqjYLs3WFTMKfzpPLF0SCXKHAF/f0UGXScGhUSNl6q03csKoKp0lDnVVHnVVHLCOSUdsrDfjjGQ5cWEatkPGuDfVsarGjkEk02vUY1ArWN1oxahREUzlemfZj1irJ5gvc3F/DdT2VKGQyvvTIBf5oSwt37urmyKiXswuhcsqxO5Li/GKYz13fSSpbYMITE0lyySwGtYJqs4ZQIst8IMltG+r5/h39jCxHODLqQV2S2l3bXcnTF5ZL4TBiUekwqqi2aHj07BJTvjCVJg3VZg12vYqdPcIP8u6berHrVRwd83L7+nrSuTwz/gSHRj0cH/dx/SqxdPrCgwN4Yxlc4RQ3r63liYElZnwJ9GoFrrDwzHSFUzxxfomNTTbanAY0SnlZerbCICkUhYw6my+SK+TQqOSE4lnanAY2NFnprhaBIStgk2C8eJn2xakyiTRGhUxie6eTyjcMvY+fW+a+k5f61P17DJcvrndqvrxSF7OolkJJIokstRYtN62pQSaTKBSKmHRKArEML4x4Lvleq06JO5JiZ28lG5vsIrAlkeVkyTvrnaYFvl39MknZixM+9vTV0OYwYtYp+erjgwTiWZRyidemA7xUAmc+cEUj2byQnK4sZf89jK1UyWP1vpOCcVUoFgnGMwQTWSQk3rWhnpYKPUB54Rsnj0ImvIt80TQAmtKMppRLuCK/3MB6xX7jh4cnCSWzOIxqFDLhw1tr0TLmjvIvr8xQKAqW9oELLu7Zv5qtHQ6eHXK/5XXzq5LiLr4feqPptwD69G+SZb4VA29rh4Mqi0YsPGUSH7yiiRMzfp4f8uCLp/npy7PolApu31CHhAD8Vtea8cXSZcnhg6cXcEfT1JSYV5lcgUgqx9m5ELeur0OvVoiglkDil/o1eaPpMvADcHO/IDH88b+eZtj1OvP0sXNL/OC969i3tga57J2n5v0yRpZMEvfZlybfzKTqrjZyeOz16zqdK5RN9/f0VVNhVKOUy8gk4+/4WP4z69cCpZqbm8sUsLeqqampX/uAfle/+VIr5dRZtezvr2PPmgIzvjiecApXJMW+/hp2dDuRSRLJbJ6HzyyyEEjwnk0N1Fl1FIoQTWax6lWlhkAwFDzRNLmSh9OoK8qzQy5uW1/H0JIYpGWSQJSXQyK69spWOx/68Wt85/Y1bGq2YderufPB83hL8pP7Ty7QZNdx721r8Mcz3PPkEJ+8toNpb4L1jVau66kimMhwbj7E+iYrCpnErD9OIltgxpegq8pEhUFdfhAAxFI57Ho1k54YsVSeux+9wK3r6sqNlkouY9IbI5HJ89nru9jc7ihJ47K4IqkyGySdy5PPF/HE02X/o6HlCNs6nchlsrIPQCIjUqfCiSztlUZemQqQLxQxaRSkSjI1b0lCeODCMqFklkgqSzpXpLWUlnJqJsCt6+qIpLLc99+vIJLM8vKkH4NGweMDS8wFBKunWIQCIjnj4KiHD1zeSCCeKaVpJBlajvCPx6YB2Lumhnv2r6K90oBKLiNV8igoIjYWHZVGXJEUBwaX2dLu4PreKjQKGQ6jmj/5tzP82c5OHj6zyDODrrK3xB9va2Nrh4OtHQ4ODIqEGWXpvNfbdGzuqEAuk7i5v5ZwMotGKQAfTyTFwREvs4E4dVYtO7srUSvleEseUpFkjt+7spltnU4C8QwmnRKFXEZ3tRG7XsW6Biun54L0VJuQtGKb0eY0cGDQXTZNLxZFQ1Nv1VHIFzky5sUdSWPRKVkMJVlRCRwb93Flqx2jRrDt9GoF+SJQKNBgE0yjdE58XhSlAVolF0yXrzw+yFf3reKmNTWsrbcSTmZ5dshNKpNj79oavvDgOaLpPL5Yiq/tW82nrhNbioVgggqDmsuabCyFkzw35MagFuatCpmETCahU8npr7cw5oqgkEnIZRKTHkHXvqzJxpExDzIJvvfufhRyiTangZ++PMurpeutUCxyzy2raXEYOL8YLoGIcl6Z8rN7dTV/eXsfL477mPHHselVXN8rfBsePr2ASadi39oaKk0iZnpFIvmvf3AF6Vyee54aYSGUpFgscmImyLNDbu7e08OsL8Hdjw7yP96zhi/v7eW5IRcLwSRdVSau6XZi1alIpDWoFDI+fk0bFQYVf/HYBYKJbNkb7viE2FB+4cZu/LE0W0u+IzqlnA2NAni+ptuJ06jGFUqiUci5qrWCp867WA4Jo9haiwaLTkmNRcvgUpg6q5ZcvshdD5/n/GKIG3qrGFqK8IuT8/z8xDy5QhEJ4dVx67pa9q6p5t9eneWZQTc2vQqZBMfGvexbU0NXlZGuKiMgkS4FK1zZKoAdfyzD4VGPMDWPpPjGE0P84+9dhiea5i8eG2IhKMyGX5328+KEj0/uaOfm/loeOLVAvlBkeDmCTa/i8zd28dKEj1enA7SX2BAKuYxEOkcgnuHFCR/nF8MUEXIcu17FpCdGPJ3DVEr3iaZypLIZxtxR9q2twRfL0F9vJhDPcn4xRGPJd+TwqIcfHpmiyOvNvVwm0VttJJkrsLrWUt5oN1eIplEqwo2rqnh50s9V7Q7sBjWfe2CglAAqWJ3FIvzelU3csbFBDLClQQxEU72ju7J0faTQqeQ4jGrW1msFwPkOoo5T2Tzx384043dcv+uh/uvVG7fqr8tlLgUP5DKJa7udDC1HeGJgif39tchlEn/+8Hk+eW07m9sreLK0DPv49jaKReG7uaHJxrU9Qq6vUsjwRAS7prPKyD98cAO1Fi2LoUQ5aa1QLHLvbYKVsrK13726GoNKQTKb554nh+itMbOlw0GuUMBhEAm8y+Ek+/pr6a01k8oViKdz6FRyvKUF3uBSmJYK4Y902/o6gokMD55ewBfLsKPLya7VIuHvuSEXk944bSU5Up1VRyKdo6vKxKERLxuarKxvtPLd58b43A2d3Lq+jpvW1hCIZzi/ECaWyfHlPT0MLkWw6jI0V+jLUshULo9JocSgVtBba0KrlGHSaDk47GFHdyXVFg1XtNqx6JR84PImcoUCvliG84thzi0U2NlTyV/evoYnBpYYd0fprRWs8AqDCqtOybQvTlQnFjdI8DcHJzgw6EKrlGPSKLmy1YY/nuaPt7fhNGrwxdI0Veh59Owi0XQWi1aJUi6VE+SmvHF2r66hzqp7GwaJUDXo1cIXNJnJlQfgP9rSQoVBfUlyW71Nx20l4ANeB0T+vWlh7xTYWUlUzeULb+ml9XYA19vJ6gwaxSV/T6aFX+DFAFEql+eOjY0l4EYApSvWETqV/B2n6r1dvfHcrHipAswHEijlMlbXmXnw9AKRVO4SedbKe96/rpZgIvOW4MU7AfveeAwX+ydNemNCPdDp5OCIh0y+UP5/NRbB5P7pK7PoVHJMJX/eulJi9y8rjVLOtg4Hj51dIl8QC/HFUJKNTTYub7Hzk5dnWA6nqDRpMKgVTHpjHB7zsLHJzrND7re8bt4JWLlyP1wsmfp/6+kRvNEUIPHK1Jv//VtdO3KZxHIoxaFRD4OLYWosgsnfU23mH1+c4opWe/keq5TLuHVd3SX+WPF0rszkVCkkrPLX7W9WbBLeyftZuSZXfMBkkkSNRcvPX5sTpvAXXZpDyxGeHXLxvk2N6NXvHJR6O0bWyjW2e3UVL0/6mPLFy8dwsZfbxbViuh9L5/iTHe1olHIyybd61f/z9WuBUp/61Kcu+Xs2m+XMmTMcOHCAz372s7+J4/pd/YZLLpNRLOYoForY9WrmA3HaKg3IJJFMFUll+ebTIyyVPpipnDDdPDrmZXApIgwogWqLhm2dzvLmZcWDZtITQ5LEQK0spV1JQCZXYMQVZffqakxaJQeHPfz3rS3822tzTHiFxC+SEkagM/5EKXnPylPnlzk27qPNaeAPf3KqdJOXoZLL+Mvb1mAzqNjc4WB7iRmlUcrJF4sES4le6Wwem0FFJldgVY2ZY+M+1AoZxyd8vDYTQKOQ8bkburh5bS2hZIZALMO0L0Z16Wb/t4cnuK6nipYKA4dHvejVgoWRyYsHcXulgUQmh8OopsKgLkfxKmQyTs8F2d4pvGh8sQzFojhvNp2KWqswX//2rX0cG/eJZtWiYXNbBZIEt6yrJxDP8PyQu5xmd+PqalQKGa5wSmxlEM3MCqV5MZCkCLQ4DDwz6Cadfd3DAqCv1lyOjn1p0seMP1FmaPXUmNjcLkCygyNeDo96qdCr+fr+VZyeCzLjjxNOZmhx6MvMGm80ww+PTNLm0FNh1PDlPb08dX6Z8VLju73TydBSBF88Q6NVx0f/9RT3f+RKYuk8X3hwgAlPTDCqNApemwrwmZ2dLASTrKm3cF1PJcvhFPednKfGrKG/wUqdRcPVbRUE4hlGXVG+9uQgf/c+YThu0Ehc11PFs0NuJr0inVEhl+ipMXFlq50CMOOPYyhtbDM5cW5c4RTj7hh7+2pYWy9SAgPxDOFkls5KI1s6HFxYjGDVK2l1GsieXyaSEmka0dT/z957B0hZ3mv/n+l9dmZ32vZdlu2FjqAiVVCKDVtMPzlpJ70bTS+amPbmnJPEU3OSNzHGgr1hAURFOiywle11yk7v9ffHPTsCgqJiTvL+8v0Ldmefeer93N/rvkqaWDKLJ5TEE0pwy3+8SplJQzqT5YfXtrOj182EP45OJceoVnL3rgEumWvhhkUV2I3ljPmiPHlsipfz9+Rd18/DblTzXLcTbyRFsU7BmiYbDXY9tz90jEgyUzB+vbzFQU2JDqVcikohxaiWs7G9lL1DXo5PCA8Rk0ZJnzPE+hY7+4dFSl8ineG7V7Uhzcsh51ea2NRRigQJvdMh+qdDrG2xY9YqkUsljPnECtmgO0JbmVgxT6aFXDOXyxGIpnCHE0z6Y+zoFaDzzj430/44gWiK6xZUoM/LNhPpLI8cmWB0RjDmNraX8uiRiQIgFU6kMarlTAfj7B2aYcs8ocMfnYlSa9Fx9YIy/NEUnlCCaX8Mo1qOWS+MdcOJNN/Y1MyL/W6G3BEWVZu5tN6KTiXDFRT6+Xv3jzI8EyGZziKRSCg3a8jlxLglk0hIZ7PIEM1BLgdXtpeyf1gwFaQSCT1TIa5oddBRYcIZTLCz10XPdAirQcXqRiE3/fajxzGoFWRzsL7FwcERHyC8zbqngsTTGVRyGUa1nCl/jMOjPj54cTWheJq6vPTiwLAPtULK+lYHC6rNzOQZTDcsruDgiI+LaosZ8kQKz3YmnzJTZ9NzdNyfn+DGCs2C1aCi1xnCrFWiksuQS8R1ySFkpKvyLLRZBoJUIqG1rAibUc2IN8qt2zoZ9kTz43yO7V3T/OyG+cy1GZgKxFlWW8wLPUIiXGHWoJJL+OG17ZQWabj/4DgzoQTFeiWb2ksplUshB9PBOFP+GD+4pp2XTnronRYJR+ua7RTrlKdN5s6sU1djT064zv3Bv4H6+xzqb79mQSiJRPz76ePO15kxnw08yGRzBONpfr9nBIAPXVLDc10uqi06Epks474Yt17ZjCecoMyk4XuPnyh4PUolEmpKtHz/mjayOQnPdgtwt9Gux2ZQ015uIpJMc8lcC99+5DgVxYL9va7ZTiSZRqeSM+AOUaJXMeSJ4gknaS41csvSah48OE4gnypWbtawo8dFnzPMTUsqqS7RCd+jfAPdNx3i+ESA2ze1sLvPw29fGcJuVGPWKrDoVfzi2V66pkQq8oFhH0fH/Ny2sZk/vDrCw0cmsRlUhBNpltQUs71LBMe0lhVhUMuRSSVcWm8RQEg2x3+/PMT8ShNbF1bw5LFppgMx9HnWfYVZw8IqM7t63VxcZ+HKNgclehVT/hhalZxgLM3OXhedEwGqioVRuyuU4Iv3HeX7V7dyZZuDNU02XMEEv315iHgqwydX1lFqUqNSSKl3GDjpClNuUrOpvZS1TTasRhU1JTpGvVG2n5hmOP+eai41Fkzr4TUPHDEHNWLRK08DlkAABCsbrfkU4SCxlFgEai0zsrbZzkOHxzGqFWxdVPG6++9sZtJnJtS9mTfNmwE7p465szLuyxqsNJcaufsUE/Y3A7jeTGZnPwsrpt6mxx0SQSbdU0FyudP9Qt+OF9apNXtucjnPaYEfSpmUcpMmLwGlAGKcWaNeIXV7K8yxc+2DSu4ryNlMWgW+SJJ0VngAa5UyfnnzAl466WEsH/xxSb2FIo3wJa0widS3dEYoRBbXFNM5LhbkzjSEny2bUc0d14p3cJ8zxCajimvnlzOVlw6K8yHAaG8kyUlnmPXNDnK53Ovum/M1MZ8FWYp1Sh48NM50IH7aOU/nF5CvPwPcPPXfY94odzzZzag3WmCUbe9ycud17XxrcyupTJbd/W484SSVZ2E3nfk8nHpdZ4/rzY7n2oXlSIDF1cUsri7GG0mwf9iHBOh3hQvKi1Or3xk+DfR8K3UmIwtmePmkm9s2NnP7phYePjzBmDdKo8PA6ibbaV5uZ9b5PPP/2/W2QKnPfe5zZ/35r371Kw4cOPCOdujv9e6VQi5olEaNAqtBNHWeUAKDRsGrg156pkIioSqR5qHD48yvMvG1K5p4ecDDlD9OVYmWi2qLOT4R5JEjE4Xt5nKCrZLL+xTNslWS+dSXSrMY4GfCQjv9sZVzCERTlOhUwsA489oqxJAnwvpWu2Ar5f0GZqmx2WyOIp2CcCrNib4gDQ4DxSY1s0NuJpdDLpXy4MFxJgJxKk0arllYzhVtDvYNexnyCG22aL6MlBZp2HZonN+9MsyaJjsrG62oZML8cWG1mWe7prl5SRUv9rlxhuKUFqkJxtOUFWm4srWUIq2C6UCM5XUlPHl8ikQqQziR5vHOSZbUFHPndR3s7nczPBMt6NANKjn9riCBmEjcm/WEkeYjb/2xJHc82VWY0B0c9XFsIsC3NrdweYude/ePCZZGLodSJhVMJ4eBYCzFZQ0WHjo8gTMYz68USLikzpKXhMVJpDN8fl0DL5304AzGqS7WsaLBglGtwKRVMK+iqLCqWaJT8usd/USSGfYMzrC2yc5Tx6boc4WJpTJEkhkePzbF+5ZVo1fLWV5XwtoWOzOhBI8cmWA6EOcL6xt46NAEt1xUjd2o4k/7Rjk65i9IQQOxFFKJhFcGZ2grN/Lh3+7HpFWgkAmj5w8sr0Yll3Ln1g5BsY2luLzFzsIqE6msWP3QymUozVJ+edMCnusWqziNDgOXzrXgDMSxG4XPj0ouJZT36cnmcqSzOYp1CkKJFF+8vJH9w15eHZwRoFqTDaNagS+apN8ZYmWjlcePTjHkCaNVyqkwayjRK1lRb8GgVrC8roQpfxylTHixjXmjFGkU5HI55HIpo94oA3uGmQ7E+daWFiFZ7XGRyQrPBatBxVcfOEoineXaBeW0lhWhlEtZWlvCd65q49uPHieWzDDXrieWTAtG3YiP27Yd42c3dqBXKfjs2np29wmZ66JqMxfPsSCTSrltYzPPdjkxqhW0lhn50dNCgz/hj1JWpOHDl9SyZV4ZKoVg/B0c8WE3qvnyA0c56QwjkSBSM0e8fG5dAyvqrTzX7SysPoEw7l3bbEcCHJsIcFmDlWwuRzCeIprI8I1HjrOg0sTqJhGtLJGAJ5TgijYHi6qLseqVBGIp9gzO0DnuZ36VmY/+7gA6lYzqEi23b2qhRK+kWKckkTrF70CjYFWTjVw2x0U1JaxtsmPO3z8f/d1+eqbD3PeJ5fTlJwTqPCPv8mY7Dx+eZMgTLoC7c6w61jbZiCTSNDkMfHNzC68OzrC7301rmRFjXrZ7x5NdIpo7lmIqEOepY9PcdX0HWzrK2N7lZNwXZXldCeta7KSzOTrH/fjz3nHxpGAdlJuE2XCJTsXHLptDIJZiZ5+LQyM+vr6xmXA++W+2zFol474oDXYD1cXCAF4qlSCTiojmq+aVcWwiQNdksNAk1FkFy+rBg2PUWnRULK0ikRXMSlcwToVZgysY59/ev4h4MiNo5RIoUos0pBf73Jx0hQteOBIkDLlFctdNS6r42GVzqC7Rsb3LSYVZQyKdZU2TjQqzhi/ddxRvJInDKMbLo2N+br2yGZ1KxuOdU6TSGa5dWEGj3cDCKjOecIJth8aZ9Mf46hVNp03mIwmRyKWUSXGdkjaT+iulnp9v/X0O9bdbZ0pVSos0LK4xYzOo2HZonFcGTm9Mz9Y8pzJZvnd1G85gHL1STue4n6vmlfF8t4v/3D3INfPL+ezaep45Po07lCzMrUAsPjmDcX7yTC8jM4KBuavPxUsnPXxrSytT/hj1dj3fubqVJzqnePToJHMsOi5rsNLvClFnESD2rMz97l0D/Pym+UwFYly/pIIKs5YvP3CUfqeQ/d24uJLHOycZmYkgkUjwRZMk0yLIYlefiy3zS3ngkFiknF9p5vFjkwx5hNcfiIXJo+MBHu+czLPEp0lnX0vRgteaJZlUikyaJZ7K8rPtvVxab+UH17TxykkP8XSGX92ygFcHZ5jwxTBoFGzuKCWWzBBPZwUjWCUSd+15k/gfPN7FiakgM2ER1jNrjN5o1/PAoXGW1hTz7UdPEI6niaez/NOqOkr0KmYiCWKJDK8OzBBJpLlpaRVT/jjPdTuxG1XoVXK+/1gXR8b9SPKjtUQCWzrKeKnfgzucQCoFvUpOVamWy1scKGRnbwaL1HI+v66B57ud9DmF0fXaJjtGjRyTVsGlc9/YGPmNpFPnmxZ2rjqVMTIrLXu8c+o0Odep1+/t1tlYMSCCdKLJDMVaJfF0FrVchMrs7nefNxvpXDV7bnb1udg35C2w2uxWYRgfT2Xy872zN/iVxRp8keR5J8qdax9WN1qps+rQqeQFZvJcm54tHWUF/6FZ5mWBMSQRcrvvX9PO7j43g54IxTpxr0z4Yty9a6Dgb3U2cEwuk1CsE6x4fzTF8EyEeFqkOyfTAmhPZbIY1HIyuRy1Vh3TwTiOIvXr7pu3w8YbmYkyFYgVznkE0TsNeSLnBDdPBYtOZZQNuiPsGZjhuoUVfOR3+0mkRN+55ywA4fk8D5FE+g2PJ53JMRNJ8mK/m+MTgXzPYEUqEeETZ3sK6vMEkLdaZwJks8DWqDfKMyecrGq0Mq/SxKpGaz4NXIZWKX9Hz/z/dl1QT6krr7ySr3/96/z2t7+9kJv9e73DSmWyOANxxnwxGux64eETT/ODJ7poKi3iHy6pYdQbJZXJIkFQ/VKZHN997ARfu6KJq+aVMwu2Z7I5/u+rw8RTryWlNJcauLzFgUwi/H+GPJECfXKOVdC8/dEkVoOaHDkG3eF8vLEcmUyKWiElmhLgVp1VRyCfrldZosVmVPGVDY0MusNUmLVc0eYQoJpORSCe4o+vjuCNJCk3CzPocV+U3+0ZRqMUUrFthyf47YeX8KX1DWw/IUwTGx0GNneUEoyl+N0rw9y2sRmbUc0LvS4GXGHaykQssFwiJZbK8L2r29jV5yowPS5rsKJVysjmYNgTZY5Nxz/fvIDd/W56pkJUlmipMGmwGlSsbbajVYqJklwqIRBPcdIVZdATpqZEh80g/JJ29Di5ZkEFL/Z5GPXGUCtkhcjkAVeYJ49NcdOSSi6uK+HEZLDwwmwrN7Kq0UrfdIgGh4EfXdfOE8emOOkK01FRxPWLKpiJJPn0Hw8xHYpxRWsp61vsrG4UAEG/M4RSKvyNFlaZ8UWTPHx4gmsWlHN5q4NDowF293loLy/iR1tFdLIrlKDermdBlZlIPI1Bo6BEp+K5bifj+Xvs/ctrGPVG2Ds0w1c2NBFLZeh1ilUEmVQ0uul85P24L8bV88v40vpG+qZD1OYN3O1GNa5QnD/vH2PSH6PWoueSuSVEEhmOTQS4dK6F0iJ1fvVDwweW15DN5YinMnRPBTHrBKtpVaONfUMiASaSzJDN5lhYZWbLvHKkSLDolVy3sJwFVYIJ8/TxaRZUmrhkbgk/fqqXOVYdP87LIEa9URZVmVnRYMGsFfrub21uYXchhVBCe3kR3VNBJAgZRTKdJZvLCQPacJLLm+0cGfWzf9jLkppinu9xMR2Mc9fWDhxFGuHr5QzRXi6YYz+8tp0/7h3Nm6erUCul/GrnSeKpLEUaFf+26yRapZyr55dz89IqNAoZz3Y5+Zfn+/jqFc1ct7ACqRQezhvdhxNptEo5aoWM374yRCqT5b3Lqtnd52aOVc+z3U76nWEkCM8xhUzKmC/Gi/0eFlSaeL7bRbFOiUmrJJPN0VZeRCSeBoRJt14lZ3gmiiecYP+wl/csqaLGomNnr2DVfGZ1HdcsLCeeyvJst0j9nGXYyaUS3ME4vmiScEIA3Dt7XaxtshNPZ/jJ0z1MBRNM+WOkMlmQwC1Lq4ml0ox5Y/ROB1nZaON7V7ezs9eFBMEUPOkKI1dLuP/gKJ9YOZef3TiPHT35CaBVJwAzvZLeqSB6tYJXB2dY22xjSY2ZjgoTmZwYRz+7tgFfJMmBYS9PHJti0DNrtGtnZ5+bCrMWVzDOoioRP1xdoiObT78SUeeCGVZVLMyGD434GPPFqCrW8P2r2zHrFDxwYJzhmQg1JTo+dElNQYo6a/b/xLFpBtyCbfhcl5M1jVa+tbmFJ49NcWw8UDBBHvZEePnkDDqVnGxOgFv37B1h26ExHv30Ckr0KjzhJC+fnGHCn4+HnlNCiV7JdEAA27PMQolEeK65QglywC1Lq1ArZDQ5DDzb5cQXTXJxnYWdvWKC7DCqyeRyGDVyhjxRnjg2yc1LquiZDnL1/DIePix8HdY0CnPYi+tKODLuLyTHSICpQJztJ8SxfvSyObzUL2Kz387k7m+l/j6H+uuvszXq9x9Untaov1ljqlWJAINykxpfNEWNRYfFoGLIHUajkLFncIYPLK/hyJifqTwzSKuUkyPHomozz3aJsJNTm46uvJ/S4ppiPMEEMrmU915UTTSZxh1O4grGsRhUSKWSguwExHxvKp/211FhYkevixFPtODPaTWoOOkKE4ynKdIoWNUomFc2o0r43mmVXLeggu1dTsxaRd6YOYVNoSKRD03xRZMiNbXZjkGjIBRLUWfV44umXtcsaZVykukstVY933v8BO+9qIaltcWCHQVc3iKSyY5PBBjyRCjRK1k+p4TO8QA7e12sarTR5DDweOcUo94osVRGWE3kRJrrrj4XK/Ns/3XNdsLxNFqVnLZyXd4kXI5GKSOVyTIZiGPWKgjG0vziuT66J4P8aGsHTx+fxhNJ5pNmRaP4Py8Ps67ZznevbuXFPvdpqYUnXWF+/uwEX9lwOugeT2V44tg0M+EES2uLWd/iwB1O8OjRScpNGq5bWP46dtWpf5vJ5khlsuzqc/HIkcn8osTpzfi50vHezHD5zIZ4FggY80bZlU/Jm12UuFDN7qnbCMVT9DpDhGIptCo5Ro0AYkKxFD3TIVKZ7Dv+TqtBxVc3NPF0/j1TZ9WzssHKdCDO8YkAWxdWnLvBr7dxfDbJ+ox6K9JIh0lNOpvj69s66XeFUcql9EyFOJFnIp4KqJxaCgQYOGuRMTIT5cU+d8HM/o3GoGl/nFFvlHq7eH//ZtcANy6uYHNHGc90TdPvDOeDWSQszac1TwfifPWKJqyG0y3U3w4bz25Uo1HIKNHLC35W0UQah/Hs9+SsfHTsFLDo1EQ+Z1AsuguVyBub4r/Z8/BGxzO7APel+44QiKUY98V44tgUz5yY5k8fXcaGVgePHp2ka+o1T6mWUiPrWxznfI7fqGYBv9mAnllmmVwqzXvUKvj6tmOFxcibl1SydVHF237m/xrqgoJSDzzwAMXFxRdyk3+vC1DOgBiAdCo5kWQGvUrGE8em6HWG8UZS3LK0kqpirXjB5pH4HGKFyxVMcHTMz6tDHj64rAaZTMrPb5zP9i4n/c4QDXZD/kUuQJrbNjXz1LFphmcied8BOzajmgcOjOGNCCPcVwZmWN/q4MCIlyl/XEirEmkq80lfO/tceZNjK5lsjkvnWtjYXooEMfEKxVPU2wz85Jlexn3R/OqBlOe6prn1SpFM9syJadQKGV1TQe7dN8rlLQ4WVZu5os2BTCrBrFXys+29XDSnBKtRMFUG3CLlY8/ADIdGvHxxQyNmjRKZVMLS2mKW11lIZ0Wi2LEJP85ggi3zykims+hUMja0OtjcUUYqk8UbSZID0pksxyfDmDRKTFoFOqWcrYvK8YaT+GIp+l0hbEYVlcXCRFvI5VJ4I0nkUglzrHoCsRTHJwNcmy7nyxsaeXVwhnFvLJ/KZieaTKNSSPm3XQN8ZMUcls0pYW2zHbtBxMc+elQkhEgk8NDhCR48NE6JTsknV81lc0cp+4e8/PDJbrL5pLx0JovVoGJzRxm1Fi2j3hj/+sJJVjfZuLTeQp1Vz6Q/xh/3jtLvDPHLmxdgN6r4wPIacuSIJNLcf2Cc7V3TJNJitWUmLKKtn81BOps9zeiz0qwhmWcJSSQgySf3DM+E+eJ9R5kJJzGo5dx3YJzqEi0/uX4ernwq4p3XtROMp9jRI1YJK/ORvotqzEz54ty7f4z28iK+vL6JPYMzHBnz0VpWxJo8K+Y3O4dpKy9idaONfmeYHzxxAptBTXWJFotexdc3NvFcl5NgPMWWDmH8Hk1m+P2eYexGNVfPL0ejkLGpowxXKE42B8vnlPDn/aNk82zBVCbLHIuY7Nyzb4R/vHQOX72ikadPTFNrEXHfH1guEidnjewB9gx42T/i5asbmviX9ywQQGg2hzuQ4H3Lqjk84kMhk/DJ1XOJp7IYVOL30WSaQCwFEgl3PtXNrVc2sWxOSUGmVaxVos/LJPQyOZ5wglwux4p6CxKJhG2HxgurPbMyy1x+HFnTZCOdzeYljBka7Houb7ETiqWxGFQsr7OQSGd5ocfJxXMtWPRKaiy6wvMll0pY3WRlXoWJrzzQyYnJIDKJhGe7nAJIe8+CAkCSyeZIpLOMzkTRqWQ8fGSCvUNeykwarHoVH19VR22JjgcPjovob52SK9tKkUkkjHujbOoopbRITZFGwf5hL6PeGHsHvSyt8dFeXsTV84XZaiaTQymXcnw8QIlByeNHp/jz/jH2D3n511sWAuDKhxt0TQapywNorWVGvvPoCU66wlzeYqe51MiyOcX8fs8I/7SqjqPjfi6rP8VsOC8ZLDOJSXyOHFe2l5JMZ/DHUoz6IgQTSiqKNfzPK8OE4lM80zXNv75nIWuabNy67RiNDkPBJ2bCH6OjvAhHkQabQcX6FgcrG6y4w0kePzopZMoKKaVFGlKZLIl0hvcsreLq+eUkM1lmIkl++EQ3k36REuqPprh3/yi//4elVJVoKTdpCMfTpLI5NAopRRoBjrlDcf75+ZNsmVfKZQ1Wnu92sXfIi9WgYtAdQa+SF2Q4UomEQDxJn1Pce3MsOqwGFYtqilHJZezsdTHgDlNv07OmyU4O8t4lOR7rnOS/XxoinhKg6eExP6lMFtWZWdf/D9Xf51B/3XU2aUcyk82DHa816vDGjalCJqVYpyIUT9E9JRJMY8kM8yvN9EyHBJATEeEes74v6axYNLTohWdI+oxtJ9NZxnwx1jYrGJmJcmjEy3uXVRNLCgM2iUTCffvHUCkkXD2vgpf6PYQSaVRyKQa1gg2tDlKZLP2ucCF8RaOQEoilqLXo2Dc4wxfW1WMxCDP0QVeYjgoTRo2c6xdVsKvPjS+aYo5Fx/5hLxKJBJVchlIvRSqBBruBcDyNUiahzibeG4Foits2Nr+uWdKr5WzpKOOVAQ/PdU3zp32jRBJp6mw67ry2gyePTfHgoXE2tDr4yoZGuiaD/PzZPhLpLKsabYQTaU66wmRyOdRyGSHSkBNMgwF3hMtbHCyoNKFVyriivZTakryJcpGq4JUqlQjjcKkEnjg2SfdkEK1Kjt2o5uEjE6QyWRxGNZGksAVQyqU8emSSL1xez6X1VpbUFOOLpk4DCs5skDPZHCMzEV4ZmCncN7NsiEvmWlDIpK+TX50pqbPolFw0pwSHUVOQ1J3ZjL8V8+3ZOhsDZhYIcAZFWuzNSyrftWZ31iMnGE8TzC96zValWYtEIimkLb/dymRznHSFWVJTzPoW+2nXa1G1mWQme84G32pQ4T+ZOut23wpzLJ3JsbvfQzCexp4HZaQSCRP++Hkzrn73yvBZTa/PNgbNmqs/cmSCT66q4/JWYfOwu9/Domozd14rwm58kSQV+Z7MpFEQjqc56QxTbtKctr23ysaT5z319gx4OJFnd78mWRULk7MVzT9bvjwAbNGr8gtlkkIin1mmpNaiI3SG79e5zsG5fM7e7HjKTWpW1Fs5PObj6HiAsiI1FWYNoXgaZyDOI0cmuXFxJb+6ZSHPdE1z0vlaAI7DqH5b9+osQDabzJnK5MiRI53JYdIpkEgkpzEWZ4/17T7zfw31tkCpBQsWnGbSmcvlmJ6exu128+tf//qC7dzf651XPJVhzBdDp5Lz9W3H+PL6BubnGSFyqYR4WpibX9FWyov9brongxjU8sJEZFWjlQcPjeMwqtGrFXhCcSRSCdcvqhDGzBIJmWyWiUAMvVIYKm+ZV4pCJiWTT2OLxNMsrikmGE8zMhPFalBRlk8EfL7byVQgQYVZpK1Fk2msehVfuryRE5NBvv9YF1sXVbCh1cGX7j+CO5Tk1+9dwOPHpnh1cIaqYi3JbA6lTEK/K8yOXheXNVh55Mhk4Th6pkOsbrLxvcdOUGvRcfumFsKJNI0OI+3lRezsdTPifW1lUC6TMDQTZe+goIR+6b6j9LvChbQom0HF7ZtaiCQzBGIpPvjf+/j+NW0cHfVxRZuIBU5nxcRh0h/DqFHwXD7adtZsNJJI84k/HGQmkqS9rIgfXd+BRaekuliL1aDCpFUIQ3NyqOQy6qx6YZh3wsnaZjuLqovRq2QUaeT8Ye8w18yv4P6D48yvNFNj0bGr18XV88vJIdhcs+boEgkF6u+s/8zXtnUKcCgPBESTGY5PBNjUUcZtG2dTG4NolTJsBjXZXI7/eWWIcpOWGxdXcmIqyKERLx9YXsOBER9NDgNdU0HWNtlZUG3GbhSR9tcvqmBnj4tjE8KjTCaRUG/Xs6rRiiYPuITyExCZBJ48Nk3vdIjqEl3BD2rIE2Fnr4uL51pQyKW4ggl+sr2HE5NBNAphfvnU8Sm+taUVVzDOlnmlyJBQolNw7YJyrp5fRiab4559o9y3fwylXMrR8QA7elx84fIG/uGSWoo0Cq5odRCKCw+Om5dWMuWP4wwl+L+vjvLAwTHKTVruur6DP+4d4b0XVbPt0Dj37h9DIZPw0RVz+OG1HZyYCNA9HcKqVwrmykyEhw5PcNOSSnqmQiyuLsaoUVBv0zPXbuD5HhcDrghymZC/qhViNWTv4AzXLCgnnREeA7c/cpw7rm3jX25ZSDqbY8/ADCcmA9y2sRlPOMmoN8LS2mKePj7FTCTJf+weZI5Vz1ybgSNjftKZHP5oilA8RZFGSZlJQyqdRSYV8sN5FSZeGZjJNytyyOWIJbNUlWix6JVs7ihjwBVmjlVIQkZmopSb1PzypvlCjqKSMeaN4QklWFxTzOOdUwy4hdwqB5g1Sp7vcRFLZrDlgVOlXEoynWVHj4sGhwF3KIFKLsWoUTDXJqjPg+4IibyM8+YlVcyx6Hihx8XCKjOXNViZDsbYM+hhbaONBdVmuqeC/OHVES6qLeGza+s5MOJj0B3BFUqgUcowKZTE8ywCZzDGHIsOuVyKJh8M4Q4nyJHDGUzywye76ZkK4s6n3Tx1fJqfXN/BDYsrUStl6FVyvrm5GVcwQWmRGpNWiSuYIJ3J8ZPrO9hxitnw5o5SwT5wh/jCvUcJxdMU65REEmmuXVDO+5fX8PuPLGXAFeaFXhcPHx7nlmXVfGdLK8+cEMmJmztKxXOVzfGnvSOsbLShV8n50ZM9TARiKOVSstkcjiI1qxqtHB718eiRSepseq6eX45aIWP7iWl293sAwVCNJtN4wmIR4rIGK08fmyKbA6VMglwmpbRIyBoeOzrFzl4XL/a7+Mn18/ju1a081+1EKoG2MiO908HT5gfJTJY6qx5v3sdKq5ChkEr51D2HGPRERLqkTMqz3U5+ceMCwvE0jx6d5JI6C5VmDd99rAtPKEFVsZa9g15K9OdvFvrXWu/WHGrbtm3cfffdHDx4EK/Xy+HDh5k/f/5pn4nH43zpS1/i3nvvJZFIsGHDBn79619jt9sLnxkdHeWTn/wkO3bsQK/X88EPfpA777wTufzcU0av18tnPvMZHnvsMaRSKVu3buWXv/wler2+8JnOzk4+9alPsX//fqxWK5/5zGf46le/etp27r//fr75zW8yPDxMfX09P/7xj9m4cePbPicXss7WqM8mYp0qR4M3bkxnWS5SiWDqzoQTzK8yYTOqePjIBIFYileHvKxutPHMiWkhl4umiKUyxFIZGhwGXuhxIZGAQSVHq5KjkkupMmswqOUMz4S5tN5KMJ7mj3tHuWffaN5TTyw8Lawq5ttXtXJg2EuJToVCKmHSHxNzorIidve7KVIruHZhOVa9kvcvq2Zzh/C2/MT/PUjXVAiVXEqvM8SL/W5+eG0bKxusHBj2srbZTudEgEF3hFA8hVImpbW8iKvnl9M7HeS9F1WzosGKVa9CYnk9AwTEXMViUHLntcICoXsqhL1IxaoGG+6QYODajWqaHAbiqWwBkAIRcuKNJKm1aHl1cAaDWp4PlBHx73OsOuKpDGua7Vj1Sr6wrp50JodUCtOBBLv73fnwGi0r6i3oVHL+tG+0AI44g3FqLTqe7XJi0aswa18zS64q1pLJQvekYGqbtcLjB4TU+swG+WysjFkmaPU57p8zmXrOYJxHjk6+TlJ35ne93Yb41H2bBQKaSw1Y9Kq3nN73Vkopk7K2yc7jnVMMFuYPgnG+uslGKJbiuW7X63yD3krJpBJmIkl+s2vgdb+bfX7fCMRYUW8p3C+z9VaZY7NjyqkMYJVcysoGKwurzYIRzrmv3xsxe2otOhFudEoIgwSYDoi5/292DvCJlXV8dm09u/rcvNTvZlNHGe+9qIpMNseQJ8KTnVPs6nMTS2W4eUnlWffhtVAHF6Newfxe2WA7K1gplUgo0iiEZLXHWZgXrW2yU5S3MpkFXp/vdnFswk9VsZbrFlawpsnGk8emiCUzKOWSwnVa2Wh7nbn3bJ1rHH6j63M2IHJFvRWjRp6fF+WYDMQpyid+q+QKxn0x/FERjHXzkqrCwq5cKuGlfhdTweRbvldnPeeePDZ5Grt1rk3HirlWOsf9LD5lIeTMY/1bAaJOrbcFSl1zzTWn/V8qlWK1Wlm1ahVNTU0XYr/+XheoMtkcJq2C7SemGfJEeOmkhyW1xdRZdTxzYhpfNMWDB8dpchj5+pXNvHzSzciMeAiX11mIJtNUmDRsXVTJw0cmGHRHWNssommVMmle0xtm35CXe/aN8L5lNdyytAq5TIorJJgqh0a8NNgNrG6ys7bZjkYhxR0SJslXzS8vbCeH2Nc6m559Q16++cgxNrSU8r5l1YLeemUzewe9FOtUDHsi5HIUzPikUvJStwjXLSzn5zfNw6xV4osmyWaFH8MtF1WzpkkMlLlcji0dpSQzWR48KF54s6uDepUcXzRJ53iALfPKaXKIZn4W0Z+JJNk/LCaMSpm0kGy2tsnOU8en2dReikIuFbR7tZwv33+0IGkEeKnPzR3XdXBZg5WX+j14o8LY/Mr2UpbVlbD7pIfRmaiIiwc6Koxcu6CcWDJLDvjsnw5Ra9Xxr+9ZyL5hL+V5qeAnVtax+6Qbo0bOLRdVo86f5zlWHZlcjnyQDDKpBKVMSlWxRuiQlYLZkMnmmPTHSWWylJk19E2H2D/s5aYllaxptjHmjfF8t5NVjTY+v66RPmeIp45PsWdghivaHAy6w/RNh1hcbeZHW9tJZ3IcHffzXy8NUmESPge//8hFPHZ0kuMTAapKdGzuEAb4f9o7mtesa7i8xUaJTsWEX2jHZRIhMZBIxAtt0BNhfYuDJTXFPNftZNgTJZXOolfJ8UaSLK42I5NAS1kRY94I1SW6PN01ilwmZVefh0cOTyCVSogmMxjVcsZ8MfYOebllWTXBaIpthyc4POqjziqaeItBxa5+N95oko9eNodVDTZGZiL8z8tDXLewgnFfDLlMgiec5LaHjnHV/HJuvbKJzbkcPdMhHjg0xlPHprEaBNPKH03xwye7Wd9q5/qFlagVsnxYwGupiHq1nGw2R9dUkBUNVnb2ulhRb+WWi6pw5s/VNx8+TkeFiY9dNqcgES0zaSjRKfnXWxZybCLAgWEv08E4qxutvNDjZN+Qt/DidxSpWdlgZVefm3qHgV5nkMvzBukD7jCheBqDWk6JXsVl9VYm/XHmVZpY22zDF0nyYp+bnb0urltYwdXzy/nvl4f4h0tqaXQYCOX9166dX868ChPPdTt58tgkxXolx48EiKUymPIJinkEls6JAItqignGhQm6zaDi0noriXSW6hJtwTh9WV0xcpmEVY02dvW5hIzWKpJ5wok0k4E4H/ndAZQyKc92Obl+USWbO0q5Zn456UwWZzDOyyc93Li4kjKTBptRRSYj5KTXLapgjkXPz57tRS6V8kKPk+7JIEZNvrlJZZnwCXni+5ZV52nuUmKpNFF1mpayIhLpDBfNKeHrD3bSUWliTZONy1vshBPpQvLQc10uBtwRijQK1Aop/7SqkXKzVjC/gjGMagXXLaggm8uRSmepMGu4cUkl0aTwXjCqFYTiKXb3e3ihx8Xtm1r41lWtvNQvjPZL84DUSVeYL91/hGQ6R6JTgPk/3tqB1aCmWKcspE/ajcKH5ekT03z9ymZu29SST66M0+QwcFFtCSNe4Ss1S5v/zqMnuOO6dm5eUgXA2hY7z3c7OTYZxKRVYNYqqbcJluDz3U7qbQaqS8w8dHiCqUC8sLAhkcCQO8orAx4uqSvh7l0D3H9wnLu2drC5o4wdvW6uXVDOyyc9p0nH/1br3ZpDRSIRLr30Um688UY++tGPnvUzX/jCF3jiiSe4//77KSoq4tOf/jTXXXcdL7/8MgCZTIZNmzbhcDh45ZVXmJqa4gMf+AAKhYI77rjjnN/93ve+l6mpKZ599llSqRQf/vDdWTpPAAD/4UlEQVSH+djHPsY999wDQDAYZP369axbt467776bY8eO8Q//8A+YTCY+9rGPAfDKK6/wnve8hzvvvJPNmzdzzz33cM0113Do0CHa2tre9nm5UHU2o9xZb5NZORqcuzE9m//PZQ0WNEoZIKFIo+RnN8zjlYEZhjxhFDIJv7plIS/0uDg+EWCOVU+5SbB4tx0aRx2XIZdKCCfSlOi0LK0tIZnJsrGtFHcogU4po6pES1WxllA8TTorFgD+a/cQ39jUzI2LK0lnczx4cJyHZ5kTLXaOjPm5Zn4ZDpOap45P440mmWPRs2xOMR9fWcdPn+lFKZeSyuQYnonwYp+HdS12jo75qTBruG1jM090ThUkUWuabJi1ijzzSEImH9QgO4cUdzoQ5/8818vG9jI2dpRy1fxyYskMxyb8/PblYVKZXD4i3sahEV8BkALwRVNEEilWNdp4vttFKO/jF46nmWPTc9OSKnRKGbmckPccGPFhMyiptej5zmNdOAPxPONCGArfeV0HHRUmXjrpQSmXcmTMz5omW0G2PHsfVJg1rGywIpeKRNynjk8x6BGKgVWNNppLjXjCidc1jW+FZXI2pp5SJj0rU++d+jy90b6tbLC9LTnSWymFXIrdqOLHWzt4oUcwamfPpVmn4MED4zx5fPotGYufWedz/k8FdM485gshkzpzTFHJpXxiZR1Wg+oNTbvf7BhqLVqubHMwHTx9vFnZaOXqBeXsHfKSSGe5e9cAKxsEs6+6RItJoyCezvCDJ7oY8rwmHSvWvbGJuk4l0pBX1Av/X53q7IBIJpfjyWPTDLhDXFZvZV2zHU8owUOHx6m3Gdi6qAJ3MMEPnuji2HigMKbu6nNz9/sX8aOt7ezuE75t1aecb2n+ul0IH6WzJv9JJEz4olSV6PLWFmK+6IsK/8wKs4bhGWHEDoK5OhWI8Y8r5rCkppj7Xhh4W/eqVa/iW1ta2d4lgodmJabDMxF297v5x0vnvKNj/WsrSS73Ni3h/17vSgWDQYqKiggEAhiNxne8vXgqw0wkyV1P97D9hJP3LK3k4yvrcIUSQlLjClOUNz7/wPIarsozSXK52YQ34ROTyeb46TN97O53Y9YpWdMk4oB1Kjm+SJKe6SDDnigrGqwMuMLMtev5t50D7Bv2UqJTMuiJFLT3V7Y5+PiqOv579xBfvbKJCV+U9/3nPurten52wzwMannhZZDK5tjV66Zz3E+ZScO6ZjtWg4pHj0xy7/5RlPLX6M3pTJabllSxZV4Zf3h1mAF3hAa7nqvmleMoUhNPZkhls0yHYsgkUsqKNGSyOR44OM6/7RpEpRDMkERaNK2fXFXHxrZSxnwxPvK7/cw+KWqFlPcsreLz6+qR5OPhe6YCGDRKKs0auqeCNJcaRSxyt5N/feEkAFKJGOy0ShmfW1tPg8PAtx45wbg3ypomGx9fVceYN0p1sZYDIz5GvVFqSnQsn1NCJJnm0IiPZXUlSCDPCpJy19M9fHlDI5P+KDkkBSDupCvE5o4ykR7ij/Gl+45y0h0u7P8lcy18Y1MLBpWc2x86xog3SiCWwh1K0OQw8Jv3LSKcSAvdvlyKVCrh0/ccIpXJcdX8MtrLivinew5RWqTBblBx26bmggfRnsEZXME4Zp2Sy+qtOINiZa9ELyYYDqOKbP7+iibTfOm+o0z6Y4VJrlmr4O73L+Kxo1PcvWtAJB/mfSkkEvjEyjoWVJqwGlT831dHeWXAk/d2yPKZNfXUWHTsGfDgjSQxahRsbCulzKwmnRH39U+f6eXxY1MFJpAE8aK8sq2UT62ey/HJABqFDGcwwfPdTo5PBPjVexeikEnxRoQ3x/M9Lh4+MkE6k+PPH1/OkTE/9+4bZSoQF9I54L8+uJjSIjXJTJYdPaK5bykzcnmzACf+6Y+HGPdF+cE17ayot7Dt8AT/uXsQpUxaSK4bmYny0ctquai2mO891kWRRsFtm5qx6FTs7HNjN6qxGVQcHvPTVmZEr5IXGprSIg0bWh04itS4AnF8sSQlehWJlDC2TmezGNUKcjn4zJ8O8dHL5jDHogOJYAzu7ncz5Y9TUawRKYhmDT9+qocjY/4CmEeeQr++2c5n1tZz775RgrEU/7Cilkl/nAPDPvqcISwGwRab8sco1il5ddDLvftG0arkxFMZTFoFqUyO915UxcV1JfzyuX7m2kUzo5RJyQHxVJbbtnUSiqd58JMX440k+dyfDzPmjSGRQDYLdTYdP71hHga1gsvu2gFAaZFIhbq4zsKnVs/lf14ZRgJsmSfkmLPx5cOeCJs6ylhQZUYpk+AMiljkXzzXz85eF2qFrHCvfHr1XOpseg4M+xjzCvbnsjkljPuifOn+o/zqloVYDSoyWZEoM5BfDVxRbxUSCJOGbz96gic7p7AaVNyytIqVjVa+fP9RwvE0Ny6pZF6FiXKzkOYpZFLu3jWAzaBiWV0JwViSuTYDUomEMW+UvUNenME4l8610FpehFImJZnJcnjUx2fvPUwynUMhE2NVsVbJ59fVc8lcC5/4w0HCcZEqqpBJ0SllvOeiKjrKi3h10Mul9RZqLTqkEgnbT0zzqx0nUcplKOSCzZfLwbI5xXz4klq+9mAn/3BJLVaDil19biZ8Udorirh0rpVJf4yfP9sHwP+5aT7/88owu/vdhBKCASmXSsWkdq6FWy6q4kP/vR9nKM5n1sxlfoWJL91/lG9vaaG5tIh9QzOcnHDzvRuWXrD35P9rNTw8TG1t7euYUoFAAKvVyj333MP1118PQE9PD83NzezZs4dly5bx1FNPsXnzZiYnJwvsqbvvvpuvfe1ruN1ulErl676vu7ublpYW9u/fz+LFiwF4+umn2bhxI+Pj45SVlfGb3/yG22+/nenp6cI2br31Vh5++GF6enoAuOmmm4hEIjz++OOFbS9btoz58+dz9913n9exX+g51Jk1mwA1y1QBMcZ89YomTjrD+KLJQqN0ZgN56t+CYMg5itR8dUMTfc4QE/4oV7aVYtIqcYcTjM1E8McEk9JqUOGPpghEk6xosDIdjLO7z02vU8hfVzdZUctl7OxzsWKutSAFmgrEuOPJbsZOadbqrDq+f3WbCH6RSvjn5/rY3e/BolfxmbX1NDkMRJJpvv5gJ85QAoNKjkwqRaOU8c3NzWw/4eTP+8dIZbKUFmlY1Wjl02vmIpVIOD4R4NCoj/mVZsxaBb5oigPDQt571fwyZsLJs5pyz56reCrDtkMT2AwqrAYVO/tczIST1JTouGRuCbFUlp6pIJfMtWA1qNh2aII/7RstHNv6FhFa440kMWuV7OpzM+WP0Vxm5Kp5ZQTjaXb0uDiSB9BWN9qwGQRD7aHDE+RyoMn7gALcvrGZMpO6cA41ChmfWFmHo0jNoREfE/5YAYwoNamZ8sf57qMn2Df8mnn2HKuOH2/toMykplh3uifPLFB5NmDjzPsnkkjzz8/3nybVmm1+VzfZ+OTKOr7yQGcBGHw7QM1b2bdTAZt3oxlOZbKE4ikC0RRSqUiYU8ql9DtD/HrnwOu8dN7OPpzrGG0GlfB7fYN7dbbe6Xk4dVxY32LnsgYr33zkeMG0G3jDa3q2Y7iy3UE4keHO09IBxXa+dkUTL5108+f946f9fHb7p27vVBN1dyhxVhP1M8e1N9rf2Xt4Z6+7kE6plEsxqBSFceThw6K/cwbjRBKZwt9+Zs1cNrQ6SGbEIp1CJi2c77fyHL3d8kYSTPrjfOWBowU7DJVCyvI5Jdx6ZTNPHZtie5ez4DXoi6ZY32ovPJfw1u7VVEaE4xwd8wNg0asIxFLsH/HyfJeLLfPKuLTewqER31s+1nf7Pfl267yh7mAw+OYfytdf0wH+/73UChk6pYy5Nj3bTzi5dK6FP+8fpdai50fXdXBgxMu4N0aFWcP6FjvuUIJHjkzSPRVkrk00hZVmDRqFnPaKIiqLNVwzvxy1UsZMOMG+IS/xVIbLGqwsrCrmvv2j/NvuQf71PQups+k5MuYXjB+JBIlEgAJ1Nj2uYIK5dj1quZRnjjtRyCV8bm09aoWMZ044mQrEKTepWVRtxmFU8d/DPqaDU7zQ4+K/P7SEK9oc7Oh14g4nyeWyRJJp2kqNrGmy8eChMf7nlRFUcindU0EOjvj47lVt2I0qwuE0VWZh9j7oDqOSy7i82c7ewRmG8l4+4XhaSBcbbHROBJhr1YuUwGxOJLdlcpQWqZEg4XuPn6DOqmdDqwObUU0mkxXpLeEEZq2CAVe4cC2yeU8DtULGkCfC0tqSQrrUXLseTyjBr3ec5JK5Fj50cQ1apZxBT5gHD43zfLcThVzKviEvt21qRquUEYqn+f61bYWB+ZkTwsur0qzhknxiy7g3SqlJzb/esoDne5yMeWM0OgysarCilEnwhOPctkms9BybCFBdrOWGJZWEYmnGfFGsehUapRy9SsbPbpjP17d14o+kmGs3sL7FwaJqE0tqSoQPTDbHbduOkcgPpP5YiiePTfHDa9pZNqeEe/eP8eiRCZbVlWBUK6i1aHnkyCRjvlgBeJhN4OgcD7Cq0crLJwXrQ6aRE02mKS0Suu5th8a5bmE5DXY9Tx+fwm5Uc1m9reBfJKR3Qka2q8/NL26cj1EjRymX8U9r5rKxo5S9QzO80O0insqgksu4ZkE5rlCC3f0eBvMrvDcsrmRpbTG7+txcOtfCl+47wmQgXqBUSyTgDSdY3Whld58bbyRZuN5HxvzMsZSzq8/NwmozLaVG5DIJzxyfQquU86OtwhtoV5+L5lIDV7Y5OJw3vs7lcviiKaqKNaxtsrOj14VEIsEbTXJwxMcNiyoxauTYDCpu3dbJumY7UqmET91zKC890OCLpnisc5Jf3ryAYq2CwZkIaoWMPYNexr1RKopFOEAkmSYH/GbnAB+5tJZVjTbkMgmVxdVkczkymSyZnABVr11YTu90SDCtsjki8RQGjYKqEi0SCWxoc/BSvxtvJMXPt/cyNBNFLpUwHRTJRXde24ErFGdts41jeaNavUoAgyaNgmVzSgD4p9VzCcRSbD/hZNIf5SOXzmHUG+EnN8zjyKgfhVyaj0gWjWE2K2jSg27BBt3SXsZNSypZ32KntEiDP/aa4fzSGjN6tQKdWs50MM6X7z/KVCDGtza3UqJX8ce9IwRjKaqKtVw9v5xai46njmfwRVNoFDJuXFJBdYmOHzzWhTeaxB9LUaRR8MSxKb5/dRs3LKpke5eT915UxZFRPwurzKxvceCPCYP0dS12VHIpn10zF7NWwaERH4tqzOzqczPpj/GTG+ZRYdbwXLeLhw6P01FhYn2rnXmVRfx6xwB7Bma447p2IvE0I94IVcVCRqlXyVEppKjlMjLZHLGkaO7iySzyvPnnbGLnqC/GFp0StVzGYEgwRWVSCVaDgTVNdkLxFMU6JWatkq7JIDKphAl/jOlgouAropRLyZKjtEisTobi6dNWXa9fVEGRRoFKIQxTr11QXgjUqDBrUcilmGXKQlJrMJbColfiiyQp0sgJxGSMeqO8f1kNT3x2BWqFAPSrSyrxzTXyvXf97Xlh669hDnXw4EFSqRTr1q0r/KypqYmqqqoCKLVnzx7a29tPk/Nt2LCBT37yk5w4cYIFCxa8brt79uzBZDIVACmAdevWIZVK2bt3L9deey179uzhsssuOw3U2rBhAz/+8Y/x+XyYzWb27NnDF7/4xdO2vWHDBh5++OELeBbeWc2yI3b0uOidFsEml7fYcRjVlBVpkMvO3phGEgIA+sDyGg4Me9nV5yYUT7NvyMvTJ6ZZUmPmjie7eeToJL/78EU8e8LJL5/vB8CsE6xDqUTCzUsqBbvCpGHL/DK25BCLJaEExRoF61sczBKQFHIppSYNt29qeV3DGoinufPJbj6wvIYyk3hfhBNp/uX5fn564zxePjlDLJXFrFUWQP9Jf4wdPW6W1hbz8OEJLHoVCpmk4EmayeZ4ocfFKwMzPHls+rTjv7iuhGQ6e0bz+vqErEw2hym/UPr1bccY8kQKMsWXT3r49pYWti6sQJFv1s+UUM36AdWW6JgKxLm8RciCTBpF3kdPMDBcoQSZXI6njk/zH+9fhEkrfHOMs+zdfO3ud/PpNfWnnUNPOMHCahNzrBUFOwSARCrLzl4308F4gU2aTGfxRZMcGvExx1rxuvvizTxuTq2zSbVmx+O2siJycEF9ns61b6lMljFv9A3BxQtRs95rWqWcVEZ4ZT15bKrg0TVbb8VY/GzfcbZjHPdG+eGb3Kuz9U4BuVMZVwurzezud5+XafcbHQPAE53TZ00HfOmkh80dZUiQnJXhNbu98zFRB17H3nuj/Z29h5X59/9sSSWSQgDMrER6Vho9W73OEGuaBDuy1qI7bbtv5Tl6u2VQK6g0S/jlzQt4odvFWD7te1WTjUQqw64+d+GzycxrScizbC94a/fqdCDOrj4X7eUmbnvoGIPuSOF5n2PVsaHNgd2get25+Fuu8walTCbTaR4Ib1SZTObNP/T3+ovVqaaRNqOa/sMT/NdLQ3z/6jaumleOJ5QAiTDz/ekzvYz6BGvmlYEZjo75+d7VbYCEK9tEMsj2LidHxvxUlWhZ02jDHU7w46d6+OTquXlTXBn7hr1smVdG91SwIG0CKbUWLWuaRBralo4yIok0L/Q42bqgglqrju8/foITkyF0KhmRRAazTsGPruvg6gVl/PdLw7iCCZ45Mc26Zjvf3tLKgWEfg54INSViu3KplCfy7IN0Rhgy7x308nyPk5uXVJHJ5XjkyAQ9U8JgfE2TDYVcymfX1fN8twt3KEGD3cCiajOuYJxoIk04kRYG8BIJMqmIj19RbyUYS/HY0SnSmRw7elzccV0HmTz7ZGefi8ub7TQ6DDx1XEzOJIiB06CWU1mspVin4N/fv4hQIk2FWcNDhyaIJDL84VWRtHZ4zMmf9o0yE07ijSRRyqXMhJPs6nWzZV4pu3rdTAWFTGd1o43NHaUEoinS2SwapWhMH++cFMBbq50bF1eRy+VwhuK8OjhDW0URTx2b4rNrG7h6fnlB+uQNJxnLR9Y/3+Ni2BOhwS4SC394bTsHR31olTK+dmUjBpVC+BRlsxwZ8zOUB8XiqQwS4KTrtXSye/ePcdIVZl1e4vPBi2twBuPEkhmCmRRKuRSjWoFJq2Dv4AyLa4r58oYmdvaK61JhFulgvliSMpNanEOtksc7hcZ8XbOdF/vcTAXEOfFFU6SzOSbyL8cr20t58OA4o14RV722yU6D3cAPH+/iQ5fUopRJ+f7jJ9jZ62b2nfHUsWnuur6DMV+UYp2SqvxkJJRnl9Tb9NRZ9dgMKr61RfhvHR4VqTtrmq3IpBJW1FvZP+ylOi+hmA4m+O3LPWzuKGN1PsnIE05g1iq5fVMLz5yYEg2GTsnFdRZcoTgvdAupQDyVLUR1t5cVcdId5svrG5lXaeKRwxP4osnCfW9Uyxl0Cw+u9yytotai42sPduZfbIKZsjPvpbW4ppjd/W4CMTGJPjTiY2G1ABsDsVTBb63JbuTrVzbx1Qc6mQoKY3ebQcWKegGC2gxqNraXcd+BMXqcIXRKOQq5lLIiNd5wipdOerii1Y5Zp+I7W1ryPhsxKos1XFJnYcAd5tc7ThJJZsgB5HLcsLhS+C54oyyfU8KNSypJZrJ4wgnKzRr8EQEMgQSVXIo3nECnknHzkkp29bl55MhkwctJrZBSYdZy67ZO/uWWhTzX5aRnOsR7LxLn5yt5Q3a7UYVFrwIJrKy38kTnJIfH/EQSaeZXmngxL+VM5GWjsjxj7OCIj8+tqyeRylCkUWDUKNjR4+L5bidzrHrWtzqIJdP84tleKot13LSkikvqLJi0CgZcEW5cUkmlWctXHzjKoCcfvDDoZd+Ql8+sreeyBisPHBzHG0ny0kkP9x8YY1WjjcXVZiwGVUGi4zCoMeuUNDoMPH1iurDqPysLrTQLluh3rmot+F3V24WBeyqTZY5V3Ned4wF+/mwfKxusrGoUkhV3SHhtZbI5qoo1rG+188pJ4U2VSGfZ3uWkayrIbRubC3KHilMmi0qZlLXNNvYOzTDui5HJiXAEcz7+/KnjU0ilEuptOj65so5oMs3Tx6cLQPH6Vge6dyBL+d+qv4Y51CxLyWQynfZzu93O9PR04TOnAlKzv5/93bm2a7PZTvuZXC6nuLj4tO3W1taec7tms/mc332u7wVIJBIkEonC/98K+Pd2anbsbK8oYmmtMLN+snOKflfodelq8NoK/o5eFycmApSZhHlwU6mRO57oIpXJFfyoDGoF494YneN+Lm+181jnJGPeKAaVoiARm5VoJFIZXMEEt207xgcvrqaqWMej+cS5+ZUm1jbbKc2DBG/UsB4Y9rKq0cb2LieD7gieSIJMNkfXZIBc7jWPI5kUjGoF474oV7Q5MOuUr9uneCpzTn+bymINvkjyTZtXmVR4Fj16dJIhT95LKAfBeJru6SAv9ru5flEls9DR2SRUVcVaHCY19iL1acc82zwnM8IOgBwMuIV336VzLcTTWcxnjC1lJg0SCecEZ06VY37g4hqGZ8Q+n9l0T/hjvJEu5XyayjOlWrNMvVqLSKa2vUsN6uvS207xtRJ1bsDmQn7/gWFfQZ54ar1TqeKp3wGvmYGfL9DyTmqWZeUwqtm6qIJUJosnnDwv0+43OoZIIv06/7vZGvNGUcik5wXgnI+J+rm+52z7+2aSSaVMzNFOlUbPMg7rrHpieRLEufb33QRnFDIpRVolWqWc9y2vJpf3xtWq5IznGfOzx6SUSbFbhT3Gi6eAVed7r85KdR85MonDqOGOa9sF694tEuI3tDkK4/v/S3XeoNSOHTsK/x4eHubWW2/lQx/6EMuXLwfEStnvfvc77rzzzgu/l3+vd1RyqZRys4Yfb51HJpOlpczIwVEfljwr4Dc7B7j7fYsYcIcZ9kYKhsfZHHkQapr3LK0qgFbHJ4K4wwlhUNvt5EfXddDoMHBk1Mc/rqiltdRIIJ6i1Kji9k3N7O7zMOSJ4ChSc1mDaNSvbBNmv48cnUQhl3LT0kp293nYM+glk82hV2mIptI4p+Ls7HVxUW0JT+fBne6pIItrzJSZNGzqUBNJZvCGE4z7Yph0Cj50cS3ffvQ4ybRIKpBJJRjVCjxhoVOe8MVxheKEE2m2d03zo+s6cIcSLKwyU1WspUij4Pd7hul3hfnqFY1IJBL+aVWdaNxselY32ZAiUPscgr45E0myvWuadU12tEoZ/miSMW+Uq+aV8cpJD73OECq5jCKNgjkWHZe32PMvHaG/TqVzNNgN+GNJsrkcxXoVwzNRcjkxuZkdxNJ588GpQJzf7BrAoleSzOS478AYP7imnW2HxvnTvlEaHQZ+dctCltdZ+MET3dyzbxRvNEk2nwD26dVzqYqlWZGX1z12dJLldRbiqQzhRBqLXlVojJUyKU8fn+alfjc/2trBlo4ylHIpkvy10KvkefbXpIgozqc/JDNZclnod4VZ02xHAsy163GHEpx0RcjmcvkV2iRSiQStSkYmmyUYz2BQK5j0RVEpZFzZVkoyLRIBlXIJlqSSEp0SZzBGbYmen97QwbNdTiFTCwnTfIBALIlKLsWkVTA0E8EdivObnQOU6JWkMlle6nfzrc2tfO+aNuZXmHi0c5JRb4wirbLAeDrpDrOzz8U1ee+zb25pZVevi+GZCLUWPVe0OlArZXnNvZKbloh0M19EeJIdivq5al4ZWxdWIJGIl/fKBiuPd4qEt/sPjCORwIIqEz/ZOg+FTMLG9jL0ajmeUIJHj07wQo+LQXeEeFokP5YWqfGEE9iNaqKpDE8fn6a6REe/K4w5/8IMJ9IYZQqUcinOYJxUJsczJ6bxhJNY9KKZ8MdSvDo0w45eF0triukc87OywYpOJaPOahCR2P4Yz/e4GHJHqLWKNM2WsiK+e3UrDx6aoN4uDCqTmSzuYJwv3HeEf3v/YjzhBAa1gkw2RzyZQaOUYdYJA1qzTkkilUarlHPJXAsrpOIZMKjlKOVSYqkMEolI+2tyGFjXLJ6VJbXFqBUyRmeiyGUSinVKYskMJXoVJq2SeDqDQSVnVaONQCzFL57rp3sygEImpWc6yJExH9/e0spYHnSf9RQBWNVoE4lSbmG8nUrnyAH/vXtIJNJs7eDxo5MMuCPMtRl4qd+DXCae35lwgiKtApVcxoQ/SiKd5X9eGabGomNDi0jkFGw8KQ8cHOfJY1Nksjn2Dvl4+aSHr2xoRKeU01Yughd29LoYnnkteEEhFT5qu3pdLKg08W8vDiKTSCjRKfnS+kZKi9S4Qwn+uHeUI6M+Pru2HnuFmKxcM7+cvYMz9LvCrwHiZpE0tbvfzauDwph4bd7X4YGD48ik8OX1TajkUnb2ukiks+zqc9NWXsT/uXkBu/vd9DlDVBfrWNNko0ijEOmoEglDnkje68WKw6Q+p6zhNWNUN8OeCOVmIREdcIX5w94RJEi49YomVHIZtz7QyeFxP5K8degTx6b4waa6d/u1ecHrQs+h/vjHP/Lxj3+88P+nnnqKFStWXNid/huoO++8k+9+97t/se+LpzI80TnNfQfGCj+bNSZO5+VGp8pKZhv4UW+0IOnY3uXkjmvbWdNs5569o4XV9NlV8N39gu3zf26ajzuUwKxTUqRRoFXK0KvFtD2dzbE7/1xWFev4yoNHC4bQewe97B2cOWek/KkN664+N82lxkLTM+GLopZLaS830TsdOu3YFTIJ8ypMqOVSLp1reR3D4g0bznobxycCZz2npzavaoUMs055mrHv7HcbVArGvLHzTtM6ta8/9ZiVMqlg7yPG+Z7pENfML6fJoScUTxeAuDN9Wt4MnFnVaCtI0WeNmGfrQgAncBamXrFYkDWq5UjzxtzvZp3N1wreHcDm1Hqr/lvvpM4WaDBbb5eVdea78Gz+cqsarZTolVSatew5C7D7Vu4hmVR4bq5qtJ0mo93V5y5s583O2RuZqJ+6L+fzmVPrjby4FDJp4TqPeaMFxmFZkYYr2hxY9EoMasXrtvmXqlQm+zqfrtWN1oKkcfaYyk0aFlab82wnAUq9lXt19h480/drfYtIKbbnbR3+X6vzBqVWrlxZ+Pf3vvc9fv7zn/Oe97yn8LOrrrqK9vZ2/v3f/50PfvCDF3Yv/15vuc4cABUyKVXFWlLpLJvaSzk65qdYpyysRNVYdLzYJ140qYzwHSnWq5AgYSCvnX32hLMgv5illc6moS2oMvPY0UnWNNloKTeikEn5txcHmGszsKmjtBDXOWts+6d9I9y8tIqLaot5vsuJzaCmzxkilsygkEvJ5EAtlxEkTb8rzPpWBzKJiAGtKtaiykeYf+m+I5yYCpLLiaQJk0bBV65oYnNHGQ8dniCTBRmi6d/V62bCFydHDrlU+Bf1O8OFpvwbDx/nhsWVXFRbjFop42tXNKFXybh33xgdFWLlMRhLcWzcz8oGG02lBh7/9KVkcjlmwglGZiKkc1k0Cikb20v5/mNdfHrNXO68TiTIjMxECyyrUFzoqivzDdxgHrTbMq+Mg8M+NAop5UVqZHnj9VA8TTyVwaCWYy9SMx2IY9YqAAkyKUSTGfYOzbCu2c6f948x4Iqwo9fFdQvKqTCrSaQzSGMScrkcjQ4hy9w/7GXrwgoe65zk/gPjlJqEUeeUP8azXeJaK/ODXg446Yrw8kkPV88vZ9QXRSOXcWTMR7lZy0W1JbSVGdnd74YcmLSKvBdZhnqbAKLqrHpWNdi478AYdTYd8VSWFfVW/vjqKMF8Ss+4L0Z1iZaL55bwXy8Pc2DYx09v6GBXr5tivZKaEi3bTzi5YXElc216vOEkL/a6aSk1UqRRMNemY0ePC71aToVJi1wmWlm7Uc2EP04yn8CTSGdxhYRh/RVtDmLpDJ3jgQJjI5J4LYJ43BfDrFOSzGRFklCZkaU1IjnPE0nw3H7BYppj0XNFmwO1QkaJXsXaZjsyqfiuI2M+OipM2AxqRmYi/Dgv3TvpCtNUauCqeeVYjSoG3WGePD6Nw6hicXUxxyeDxFJZMjnhCTTHKow+46mMAFkf6+LQmJ/5eY+tCX+McpMGmVSkNzqMampKdMhlEsa9MdEwSaUUaRXoVbPm9jFuWFzBN7e0YNIqyQElehVjvihfuf8oQzPimVfKpDx1bIp/fs8CFtcUU1qkIRBLsbPXxUwkwU2Lq8jlJaoVZi0ShOSPU+Yk1cVaVHIZ4Xiabz7SyeFRP4FYijKTmmaHka9vbOabm1t4vttFjUXHsjnFuEMJDo54uWp+OZ5wgs/86RArG2xs6ijl0aOTjPtilBWp0SiVlBrVtJUX4QoluPWKJgKxpIjbPjFdmDR3VJjwx1L4IoIVqZJLRRpeXmorkQjfNXIQTWX4n5eH+cK6BlrLiljZaEMmkeAo0pDNCdBbrRTjazIjWJLdk0F+v2cErVJGMpXlqvll6FQy3KEEo94o7lACk05JNpNl1Btl35CX6xZWcEWbQyRM5htLQADZWsGS8EaT1Fp1mDVyirQKGh0GHuuc4qHDwvzypiWVfGLlHFLpHI8cmcQTjPOeZdX8aGtHYaJUXSJSZGx5k/NHjkxw737RXIukISGjBtH0zk42hW+ekHQ3OQwszZvRP3NiusAQ2bqwgmQmK0xBpRKm/K+fcM9OOmcbyWsXlIswilwu738XZXWjjbk2PVvmlfHwkQmOTgQKgBRAnzPMjh7XhXtZ/oXqQs+hrrrqKi666KLC/8vLy9/0bxwOB8lkEr/ffxpbyul04nA4Cp/Zt2/faX/ndDoLvzvXdl2u069JOp3G6/Wett3Z7Zxru+f6zLm+F+DrX//6aZK/YDBIZeXZU6IuRJ3ZsJ5qTPx0Pjym8pQGc7aBP3Xlf9AdYWefi5UNVl4dnCmsps+mm8216QtzNpVCxs5eF+O+2GmGxwDOUII1Ta8B6iCG23Q2y9gbgASnNptnNj3XL6qgRKc8jc04W5XFWlY32XAY1Xx2bf1ZG9tzNZxWgwr/yRRnqzObV2UeFNszOHOa58ysVPCtpmmdesynXgcQ76tyk4ZEOsuPt87Ly8Lf3LT6bODMgWEvlzWIhjoQTeGPpgqM6kvmWgoy6ndSZ2PqnToOvxtMpVPr3QBszrcuhLH4+dT5gjHnU2cDnzZ1nM3vSbDNfnht2wUB32RSCaVFah7rnOSk6zWT+EXVYvH97TDzzrUvb3V/30xqd+Z1riwWoLbNqPpfl6k585K6uTYDS2rM+KIpdva5WN1gO+2YJBIxRhyfCBTO+Vu5V88co7d3OQsswZuXVFJr0b3h35+JAbzb/m8Xqt5WfMKePXvOajq5ePFi/vEf//Ed79Tf6/zrfNH3QjNwisdAOpOlyWFg/7AXjUKkLyVSWaRS0CjlSBERrI0OIzlgJpJALpWglEsJxHJ5rygYcEdY12Kn1KSmZzrET7f3cse17USTYl9OukK8PDDDoupi5lh0QlqztIpYMkPvVIjPrWtAKZNQWSyM60waBXKphBK9Ep1KTmuZkUA0yUhevrOuyY5Ro+TJY1NM+AULRALEkhmyuRwvnXSzrtnOtkMTSCUwv9KERa9i3C+8eqKpDDqVDF9UGP8OuCKsa7JTolNyebPwe2kvLyKaFMljG1odjAdiKGQS6qx6WsuMhBJpdvS4WVxtJhBNcWTMz+UtYhvTgRhWg5rbN7fwykkPZq2SyxqslOTZZ/fuH+WXz/cTT2VRyiQ8c2KaO65tJxBL8aGLa3jvRdVksnB5q4P9w176XGHKTGoCsRRzbXouq7ew/YSTLBCMJomnMihkUtzBBNcuMKBTCebOuFdMhG/f1MJz3U7GvTEcRWpW1FuQS6Wsb7Hnm8cY1ywow6JX5hkYKkqLNNz9vkVY82aPL/S4eOWkhzFfjHAijcMgALP1LQ5+8nQvcyw6rmhzcGjEy4hX0NQdRjUleiUb2hxM+GPcdX0HwzMRjo0HeO+yanKI9IofX9/B0TE/fc4Qm9pVrGqy4QzEeeTIBIlUtqCz39Un0uf+fGAMq1GFzVDJk8eneeiwuM4b2hysarDxoH4cfySFUaPAFUowv6KIS+da+MOrIwJsQPiGhRNpDo74ChO7mhItL5/0UCQX/h2JtPCamldhQipBmJrvH+W/Xhriw5fUsqbJxq3bOpkKxHjv0mpWNQr5ynQwzqERH75IkstbHSRTGYwaBX94dYQbFldiTwtQcU2TjRsXi+Q9g1qGKxjn24+eYP+wD7VCyg+vaefz6xo4OOyleypImUmYspq0CjQKGY8cncQTSSKXSnihx8XWhRU8dWyaUEL4AUmQUGlWi8mwREK9w8DhMR/pbA5POEEuJ6S9beVFyKVSpgNxZBIJlcVacsALPS6GvdECYJBFPOvPdbu4aUklX7jvCAqZkJR+8OJqVAopX9/YzLAnQnt5Eb/Py1JsBhUlMimVxRourbeQy+XY2etmyBPBalBhM6qQAIOeCE8dnxJph3oVjiI1wXiaTDbHgmozwViKp09M0+cM44+mWFxj5kfXdbCzz4UrkKDBYeCKNgfeSJKnjk3RNRWkwW5gTZONORZdnq0QY3NHGf/x/sXo1Qquml/G/mEvwViKerue57rFOKpXy8nmcoXGsNcZ4qO/PwDAjUsq+fDFNewfmmHcH8OolpMDyvJ+Zw8cHEOtkPLNzS3UWnQ8cHC8IM+8eWkVa5ps3L1rgFBc+MmdmAxy8VwhFS43a2gpM/LygKdgeJ/N5XAFE5QVadAr5fz2w0sJxdP86KkeXhmYIZ3JIZdJyOZyXLugnJ8800PnRICZcJJHOif5+GVzuGZBOemMuO4HRnxEE2kua7Dyz+9ZyGf/dIh4KosEAeyvabIhzSddrj5lsjm/ysy2Q+P810tDBU8pEE35RF7ems3lUEqk5y3vyOZy/GbHAE8en8rLWYVM0BNKIJVK6JkKnSZ5USukbO4oY0nN37Zv5YWYQxkMBgwGw1v63kWLFqFQKHj++efZunUrAL29vYyOjhYYW8uXL+eHP/whLperIMl79tlnMRqNtLS0nHW7y5cvx+/3c/DgQRYtWgTACy+8QDabLQBny5cv5/bbbyeVSqFQKArbbWxsxGw2Fz7z/PPP8/nPf76w7Weffbawb2crlUqFSqU65+8vdJ3aLGRzOVY0WAr+R/5YsuD99MqAhzuvaz+tgZ9lQoUSKSZ9Ma5fVMmPt3a8bjV9Nt1szBs9rXHdc8pzJBYctNiNaoY9kfyinXhuZ5/Nc4EEZzabZ8puVQrZm7IZFGeRF4ljPHfDeab/0+zxntm8apVy1jbbeHXQUzBoP1Mq+FZq1k5g5TkYGBvbhLTbZlRx/Xl60pwNnJllnX1rcyv7hrwcyif4rmwQYQ9yqYSKdwganY2pN1vvJlNpti4kYPNW6y/hGwQXlpV1tndhW7mRo2OBs7LNtp9wcs2C8ncMvk0H4vzoqW6GPFFCiRQvn/Tw6tAMd17bgcN0/ts5HyDw7YKF5zqPf6nr/FYrnsoQTWVoLzexs9d1WrpmNJUhnsq8bhy7ZkH52zqGt3sPvh4D0LCi3koyk+WRwxM48sEUWslfZ4rx2wKlKisr+Y//+A/uuuuu037+n//5n+/qCtXf67V6q+j7qc3A7AN/KmsqlyOfAKYnlsygVkjxx1K05M3DI4k0NoOabA6RuBdNkkhlyQI1Fi3xVIYrWh3cs2+UIXeEF/vcbO4oRauSQU7C6kYbu/s9vNjnojqfKDcyE+V/9gzzjU3NqBRSLm928OqAl8lAjEAsRSabo94u2CcyiYSvbGgsJKUkM1lGZiKYdQo0ShmBWIqpQIxai45gLEVTqYFrFpTRWmZkZYONTC5XoLDqVLL8i1VDKJ6mudSAUi4a6n5XiH954SSRfCrU7Vc2s7bVjkohLTTSdqOa5XUl6JQyvnjfUb5/TRvOYIK7nunl25tbKTVpyeaEcfMlc0XcszYfQfzwkQl+s3OgEGuezuYK5+vyFkchMWfaHyOezvK1K5vZ3e9mwid8d2ZZMs91OxmbiZLNCeAwnclh0iqQSyTctKSK57udVBZryOXAoJZz85JKMlnBeJqdvD50eJxai46N7aVkc7Cj18VUIM7m9lIWVJsKkc5zrHq2LqzgsgYr3kgCdd5M2R2Kk87m+N41bfgiSWLJDJ9f18iL/W6mA3GqS8SqqkWvQquQcWTMjyeU4Gc3zsNmVDPpj/LJPxxgfauDL65rJBBPMeKJ8PSxaXb1uQpJKyddYVY32bAZ1KjkUurtgnGVyeWYDsbzK8M5Hjo0wRyLnjuubWfPwAzuUAKjRsGWjjKiyTTP9zgxa5XkENtNRYV3ji+a5Mlj01y/qIK9Q15mwklUCgEIlBWpuai2mFgig04tZ9ATIZXJsajazI5eF+O+KN+9qo0mh5FnTkxzZMxPTd43bcwb46f5dESdWs6aZhu+SAKrXoVOKUMmk4p0Q4Vg7Y3MRPn8unoMagXOYIJdfS5GZiJcNb+MzR1leCPieOQyKblcjpOuMMlMFkeRmt19bpbNKeEnN3Tw6uAM3kgSm0HF5S0OinVK9g3PsLDKxHNd07hDCWLJDNFkBrNWSUeFifsOjLG60YY/mqSyWEs2l2PM+1ozMCtFkElF2ls2m8MbSWLRq2h0GPJyXCXPnBjh968MceuVzfzk+g52n3Tjj6SotehYNqeEk64w6YxYxZdJJfijKeLpDGq5DKNGjiecIBBN8cX7jnD7pmYOjPj4w6sjlOhV3HV9RyE4IAf88vl+1jbbWD6nRKRAGlU481HCxycCOIMJnu1ysv3ENHdc187NS6uw6FX4oknuOzBGTYmOVU1WfnBNG/3OEFe2lbJ/yIsnLLyi4qkMrWVFrGm28/ChCTGcSqB/OkS5WcNtm1p4tmuaAVeYOpuey1vs5HLwXLeTLfPKqCnR8dUHO/FFktgMaryRJA8fmeDHWztYUW9le9c0IzMxbEYVw54In//zYX5+4/w8uCvSN/2xFL5okupiLUtri+maCrKw2sy2QxNM+uPUlGgJxsVYtaSmmOe6nEz446gVMtQKGRqFHGcwwYQ/xg+f6GbPwAwyqQS5TMKuPjff2NTCL29ewMNHJmi0G1jdZMOkVfLnA2Nc3uzAZlRx53Xt9EyFKDMJeWxpkabAlFXKJHzssjkYNQruPzBGvzPMR1bU8mKfpyC/mZXCnE3eoZBJqbcbyHRO8sDBcR44OJ7/uYSdX1lFnfW11UC1Qsq3t7RQVazjxRMjF/R9+peud2sO5fV6GR0dZXJyEhCAEwgGksPhoKioiI985CN88YtfpLi4GKPRyGc+8xmWL1/OsmXLAFi/fj0tLS28//3v56677mJ6eppvfOMbfOpTnzon+NPc3MwVV1zBRz/6Ue6++25SqRSf/vSnufnmmykrKwPglltu4bvf/S4f+chH+NrXvsbx48f55S9/yS9+8YvCdj73uc+xcuVKfvazn7Fp0ybuvfdeDhw4wL//+7+/7XNyoUutkLGy0cquPhddk0HmV5h4ocfJmC9KWZHmtPvdF0lSnpeTAwUmlFmmpK28CJNGgUYhPetq+vnIpFY12vCEE9TZ9KeFGcx6UL0RSPBmjeQ7bQzP9tm30rw6itSvM2h/q435qfPk6UCMqxeU55PHBDB1NgbGObC219XZwJlEOsuvd57k8+sa2NDq4KL8gtesSfS1C8rfMWj0VphK7wY7QiaRsLLBUgihma2/ZCT9X+I7LgQr61zPsEYho98VIpvLFcaL2RryRMhkc2/52Tv1WoPwT5vwx0/zNgvG0rx80sPWRRXnfZ+fzzjwboFIfw1A1KklQTx/swEMs7W9y8lPb5jH2Ubad3IMb3QPnuvZPhMETaazPHBwnO9d3YZaIeO+A2O8MuDhM5e+ObP6f6PeFij1i1/8gq1bt/LUU08VVsH27dtHf38/Dz744AXdwb/X2ets6Ht7hZFIIsMHlte8TkN8thUUhVyKzajmto0tJPI+Lr+8eQGvDs5wbCJAvU2kyo3MRDgy5mdzRxnPdU0zGYhTbhKATplJrDIVaUW0/NExPzajaF6aS41Ek2l80RTfebQLbySJRCIhlXHx+1dGuOv6Dm5aXEkyk2P/sJdF1cV8/5o2HuucpHc6xByrjtWNNib9grZ+4+LKvExGPIw2gxpnMIFKLqVEp8SkURBKpKkp0WHSKPnm5hbSmRwPHBzDH0uxvsXBY0cnGZ6JUlqkJpEWTLFN7aWoFDJ+t2eYbYfGiaWyyCRCZqjTyHEF43z/8S6OTwbxhBPIJBIePqLlh9d2MK+yiBf73FzR5uAHj3exq08YZloNYvLujyZJpuWQA61KzqQ/hlYpJ5LMFNgIs54GswN6Npfjt6+M8OrgDNcsKBOGpfM1SMhxYipIWZEGrVJGIi1StaQSCXNtQhZ4dNzPygYLA64wa/NePIF4Cm9ErJSM+6JUmsXAtrrRjj+WRKOQ8el7DnHSFeG9yypZWlPMT57u4dVBL/F0FglOnu92ctf181hcY0Yhk4oo90yOymINzmCCn2zvZToQY02znSU1xazKa6xlEgmPHZ1kRYOFtS32wqA+FYiRA2xGNQ8cmOCK1lIOjfr475eGcBSpC74OmWyOWquOSCLNpfUW1AopP71+HjKpFL1STm2Jjpf6PQXZ6TcePsZV88r50CU1WPMpiKFEGo1cRnu5iX5nSDBhVHLMpQZWN1l5onOKbYfG2dBq587r2nnq+DTHxgM02MXvu6eChBJpNrWXMidPmS3WKRl0R9jUXkZ1iY4fPdVNz3QIdyiBVCLh2S4nd17XTplZw1MnprluQTlmjUgxUsikqBRKZPmIY4VcikQCJXolz5xwMuSJUGPRct2CCpzBOA8dGucjK+YQS2XZfXKafmeID19SQ4PdwMsDHvzRNHq1nP94cZA1TTauml9W8FsCMVHO5cAVTPDNzS3sG/IyPBPBZhAsKsixqlEY91cWazky5qe6REuDXUhIZhmIUokEjVJGc6mRdDbLhlYHTQ4DF80pIZhPoLu82Q4IX7Eys5oPX1xLNidenLv63PzrCyf5rw8uptykZswbI5YS+yghhT8mpapYh1EjmEf7h32sabKxd3AGdziJJ5Rgjk2PMu8Tls5kuW//OM91OblxcSVb5pXxeOck/a4wRo2CcCJDIp3J+zG5Wd1oRadS8PTxafYMzvDAwXHu3T/K/7l5AVaD8KX60dYOnut20jkeoM6qY2N7GWatSBe8st3BXJsAaJ2BOM/1OGkvN7GiXsSPP3N8mqVzSljbZGdN3qNqZCaKRackk82iUwk/rBd6XCysMvPksSlaS42sarDx0OEJUpkcX3ngKH/+2MXctqmZp49P0znuZ65NsL3MWnHPBGIpTkwG8EWTFGkEqy+by2E1qHi8M0w6m0Ull1Jp1pADFtUU82yXk6m80a5GKWVTexkbWh0o5FKW15WwsEow0WQyCfuHvDx8eAIJEpbXlbA/b4RckjdO7xx/zRfm0norFr2K7zx6Anc4yVQgxk1LK+mc8JPKZIW3ikyKQiak12c2TWqFjDXNNl466aZrKliQ6rSUGlHJpaxvdfDEsSn6nGE2d5RRVazjGw8fJx493evmb63erTnUo48+yoc//OHC/2+++WYAvv3tb/Od73yn8N1SqZStW7eSSCTYsGEDv/71rwt/I5PJePzxx/nkJz/J8uXL0el0fPCDH+R733st73B4eJja2lp27NjBqlWrAOFx9elPf5q1a9cWtv/P//zPhb8pKipi+/btfOpTn2LRokVYLBa+9a1v8bGPfazwmYsvvph77rmHb3zjG9x2223U19fz8MMP09bW9rbPybtRRWo5n1/XwPM9TirMWp46Po3dqOZMi4/uqRCrGqzsGThdBldVrGVVo2BD6VRnX01Pps9tVDz7HDmK1OhUMja2lfJSv4fJQKwgc3szkOB8G8kL2Ri+leb1QjS6Z86T9w55uWaBWORRyKTvqHk+F5PBZlBhNai4/8DY60y5L4S87XyYSm+mmHg7lcr7pQWjKUw6JbfmF0zHfbF3TUZ3PvVuyZLeyf03u08AJTolKrn0tLRAXzRFhVnDkTH/6/72VCD5fL7vbNd6y7zS08aOU4Gvt3sPnq/c72+p3uq9M+vjdyogBYjU536PkFu/wfcoZVIyudx5f+fZ7kG5TILTH2fUF8OkFWE6urzXYDqTOw0EzeZyhOIpRr0pdvW5WVJTzPYuJ+O+GC8PeM77PP0l622BUhs3bqSvr4/f/OY39PT0ALBlyxY+8YlP/J0p9Reos6HvognR4gzG2d4lGttZWmFzqZHDo77TBqLZgWx3vxuDWsFFtcVIpQIgWTHXwrI5JZg0Co5NBPj8nw9TpFbw3ouq+dZVrWw/Mc10IE6jw8jqJityqZQX+9wsqy3hKxuasOhVaBTCCFsmlbBvln2QyqDL+yP5Ikl25FPBPOEEBpWCaX+cEW+UeRUm1jbZ8UWTvNDj4oVuJ9cvruTKNgd6lZyZSJInjk2xrLaEBw6NM+yJ5AEyNa1WwYzKIbxynjg2xb/tGkSlkFJv03PndcLLxxlMMNemY36lGZ1KjjcsGCy/vHkhNoMKTzhB57if9vIiHu+cYtwfI5kWYBUS4a+0K5+w98jRSeFLlMpw0h1hQZUZbTLDw4cnuP/gOO5QgkQ6wwOfuJgKs5YijZxoMk0iLRJgcjloKTOiVco4MOxlYbWZeruefcNenj4+zeOdU6jkUj6+so56q54SvZJvX9XK9jyAUWfTsarBxrgvyisDHj61up5vbm4hkcqyo1don+96upupgGA2heJpHjoywZ3XtlNp1rLt0DjJdBaTVsHKBhuPHp1kZCZKuVlDOC720xdJcWjER01JOX/eN8aJyQCt5UVsXVjBzl43J13hQpx0kVaJQS3nHy+t5ZK5IlnME0ry2JEpnME4RVoFqxqtFGtV/OCadnb3ufFHk1zZVsrxiQAT/hhapYyMVlEAPXUqObFUBqVMilmrJJJII5NJuLTeUgAiQKTiHRjxcv2iChLpDFVmHSp5EiQSvry+gWdOTBOMpaksFpO0VD6p7h9XzKHKrCWdzdFSauSSOgu+aJIdPW6e7ZpmUbWZaN408pmuabwR4e/TVlbEzl4Xk4F4YdIhlYqX1K5eN5fMtbDt0AQzDUm++OcjSCRCMrqqwconV9XlJYUyNnWU8r3Hujg85ieHWJF5rsvJndd10GDX5+Va3XgjSdzhJHKZhBsWVbK7383R8QCjM1GMGgWd436uXlBGMp3lnn2jDLjDdJSbuLzVzoQvik4pZ3OHMKUWoF+WUV8MfzRFdbGWfmeIW7d1ctfWDlY32Xixz83xyWBBythaZmRVoxWFVMpXNjSKtCSJpOC3lSPHDYsqiSTTPNE5Td90kDKzhmvmlzPHoiMcT2NQK1heV0K5ScOAO8zsqFRh0rJsTjF6lZxgPMWOHicX1RZz53UdPN/jxBlMsLm9lO7JIBP+GCMzUYp1Cm5cUsmm9jKkEgmuUIJwPI1ELafcpM57sQljyhqLnnQ2S6PDQCqdJZ3NMTwT5ZkT0yytKeaW/9jL969pY2NbKcvmlOAMxnn6+BRzLDq2zCtlQZUJdyhBKC5Yd48dneKRI5MF8DSdyZJIZ4WM1yD8wdRyKTqVHH9UpEuWmzW4QwmqirXcvKSSLfPLSKSy3Li4gtWNVl7sd/P40Qk+uWouy+tKWN/qQCWXolZI8UVSfPfRE3x2bX0hICCWylBWpCYHuIJx5lj07BvykkxnMeuU5HLCgH/CFyOdzaFXy/j2llaqi3Xs7HPxROckrWVFXNZgRaWQcc/eEV7sdxNOpDk86mdpbTF37xzgxT43d13fwepGW6HBzuZyLKkxMxNJ8Ll19RRplDiDceRSKTUlWvYMzKBWyJgKxPJyv9eYG6dOBstMar6zpZWdfS5GvTGqioV8SSmXUVqk5pc3L+DZLifL5hQLuWI2mzeZ/9utd2sO9aEPfYgPfehDb/gZtVrNr371K371q1+d8zPV1dU8+eST5/z90NAQJpOJefPmFX5WXFzMPffc84bf3dHRwe7du9/wMzfccAM33HDDG37mf7PiqQxPHJvCGUywqNpMkUZBvU3PCz0uYT+Q94ADCMZT+YW/N2ZcnK05OR/wQSGTUqxToVXK+fmN83mx38WY98KABO+mB8k7ZVydT51tnpxIZ/nz/nEkSE5bpH27x3o2JsOKBivxM+LhZ+tCpcS9maxnzBu94Ol40USaSX+c57sFK/CKVgdXtpWilEtRyqUX7B4532vxbgBvZ6u3clxn7lO5WcOy2hI+sbKOu3cNFOaIB4a9bGh1cHTM/47ZZueSB5YWac76+XdbYvm3UO/k3nGGEihkkkIiIAhm93Qw/rrPvtZne0SPp5DxysAMU4EY5WYNqxqs2IzqN73ep/5+3Btl1BtFp5Kz/cQ0g56I8ODsKBM2NWcsZCQz4p6bTXgtbOcM9t5fS70tUAoE/fyOO+64kPvy9zrPOht9d2WDFX8sxXcfO8HR8deMYWdTXlbUW08biGYHskF3hMlAjEw2yy9uWsDSmmL+dUc/z3e7+PV7F/LIkQmiySyxVII+Z5BIMkNHhYl1zSpCiTQPHZ7gT3tH+fjKOjRKGfuGvYx5oyyoNLGmyYZeraBnKkgsmcGokSOTSgoMjgF3GL1KTjyV4fuPd/GVDY08dHiC7V3TKGSisblkroXPX96Y96IS6SIv9rm5d98oDqOau/KG0f2uMPMqTVzR6qBYr+BPe0dZXmdh2CMS7EKxNF/fdoz3LatmZYOVCrMWo0bOz5/to62siC3zyrhqXhnPnHDy9PFp6m16kbgmlxYeXpVcSiSfPC2RQL8zzLpmO5s7SjFrFfzmfYuQSyWkszlUcuGropBKsBkEY+cPr45w4+JKHEWCwRCMpUllssy16tjSUYZcKuHAsJclNcVcNa+MllIjrw7OEE9lWNFgpUQn/HdkEsGWWFJj5vIWOzPhBDv7XOzsdXPdgnIMajkPHZ7ggQNjfHlDE08cm+TEZAijRs50IC6S0kIJnjg2xQcvrmFkJkoqk0OnkmEzqBnyRJjwxynRKwsMOKlEwrgvijOY4L9fGUIulXJ8Msilcy2MeiOoFFJkUsFUC8VTRBJpBj2RfCy1hq892MnwTAS7QY1cJmHPgIfvXNWGWi7llouqhCG9FL61pZUd3U66p0OFiHqFTMozx6dY22zHF02x7fA4CyrN7Ox1c82Ccr61RQClItZesEpcoTivDs7wubUN/PaVYQ6O+Li03sLi6mKaHCLl8MRkkCU1Zv5p9Vz6pkPE0lme7ZrmVzsGyOXAoldi0irxhJOU6FVM+GKEEmnu2jqPQCzJ+hY7cqlggmXy7JRZTw+JRHgkXd5ip86qwx8VwJg3ksQdSmDoKKXXGSKTg2sWlPNslzBLV8mlhZfIoCfCSyfdfGB5DQ8dniAYTyOXSVHLpTzeOcmiKjNfu6KJlwc8HBwRRuobWu0YVHK+8dBxdvS5yeZy7BmY4eCIl9s2NROMp4kk0vzHS4N85NI5wog8B412A8cnA9z+8DGuaCulpayIUCLNV69o4pWBGcbyDLvlc0qIJYXhvkouI5PNkSGHXCohk8tRpBHpSLdtO0a/K4xcKkxZj44F+MamZj50STXZXI5gLMWPrxfP7oArzFybnlWNNoKxlJDHzilhU3spzaXGAgAXSaTJAd/Y3ML2E9N0TwX45Mq5KBVSHjkywaJqM2VFGkxaRf4ZlRSks/U2A1OBGLdt6+R7V4vUq9+9Mkwml6NvOsTlLXaywEOHJ3AUqfnin48wPBPFblTxiZV1SIBDIz56nWE+taqOQDSFMs9SlEgkIAWpREoglqLBbsAXTTGvwiTkitkc3miSdDaHSaOg3q6nSCv8rCKJDI8cmaDfFabOquPaBRXolDJy5Cgr0oAEZsIJ0hkZL/S48MdSHBzxsbbZzvauaQZcEYLxNCaNgpOuMBva7Dzb7WTAHcaUyyGRSIgn0zTYDbzQ4+KqeeVU55O6RmeiWPUqDo/5uffAKHde24FSISWcyDDmjbFlXhmuYBxfNMW+IS9PHZtm66KKQhM24Y/RXl7EhD/GMyecnHSFmGPV4yhSc9OSKvYMevGEEqQyOUKJFB0WAX5F84DlmZPB6xdVntWY01Gk5gPLq0lksjzWOYVcKsWdT8f8W66/5TnUk08+yW233Vbwgvr/U2WyOQbcEe4/MMa/vzjI9YsquHZBOUUaBb5oEhDjT4VZwyVzLagVsrfFuHgrniJqhYyqEi3XGyvP+zvO1pjNpki5Qol3vdl/t+t8ZG7vFNg4F5vmzHh4uLDytjeT9VzodLxUOoszmOCrD3QWWCJPdE4zx6rjFzfNp7bkjU2Xz+s73uK1OF/fwr9kvX6fhM/X59c1sLLBWmDO9btCfGB59TuWp57rWr/U72FDq4NXBz3/axLLv+Z6u/eOTCqhpkRb8KM7NYSh1qJ7Hdg3+z0tpUYkwBfuO0I0mUEhkxCOp3n0yCR3XNuOxSASBd9szImnMoz5YuhU8tMkhNtPOHllwMOv37vodQsZSpmUCJlCwutsVZjPDlr+b9d5g1KdnZ20tbUhlUrp7Ox8w892dHS84x37e527zraCtrimmGdPOPFGRIrZLIo76BaN7Xsvqj5tVWhnrxgIQ/EU8VSGdDbH5+89zHNfXEl1sY5UJotUImFhdTG9zjAS4NUhL6sabHz1gU6C8RR6lTDhXVBpYm2zjT8fGOO+/WMY1HK6JoPsGZjhR1s7aCkrYt+wj0Q6i0Yho8ykJpxIs7i6GIkEnu1ycmjUjzucZI5Vl2d0Zfn4yjoqzBqe63bxfLeTJofwPGkqNaJXyfnuYye4sq2Uy1tEpDkSQZ3O5HK4QglCceFlM9vkx1NZ7jswzo5eNzcsruC6BRU02A1sbC9lJpzgZ8/2CXnOonJMGiW+aBKbUU11iZbnurOC5ZVIF85Nc6kBi16FXiVn26EJTrrDtJcXsbLBijxPn/dHk2yZX87KBgtmnRKjWsG3tggD9FlWwGUNVop1SpLpLBvaSnno8AQTvhgVxVquWVCOXiXn4cMTTPgF4+CSuSXMter5+B8O0D0Volgr4qKtBhWXNVg5Oubn/+4ZYTrPSjrpDKNSSAnGhPcMEnEPDbrDZLM54WMlAXcoiS+apMaiI53Nks3m8uCmSBmzGlQ4A7G8LxP4IknGfTGsejWpTE6YZOfZVclMlpoSHWqFVCQDeSJks+K66FQypBIJh0Z9bGovZcIvXgxahYxys4bLW+xsnleGJ5zglQEPM+Ek65rtGDQKnuic4sq2UjLZHI8enaTfFSQYz9BeYWJDmwN/NMkTnZM8cWyK9y+vIZPNcsOiSg6O+Hjs6BSPHZ1ic0cp65rt3H9gjIG8X9XPn+tlaU0x1y6o4MljUwx5omiUMhLpDG3lRWxsK6VrKkA0mWFhtYlSkxpyApxsLTNycMRHkUYkDibTWdKZHLUWHbFUhs0dZTxwcIxMJks8nWGOVc/qJhtKmZTLW2yks1mOTwbI5sRkMxxPE0tl0ChkeCNJcjk4MRHEFxFyLb1ajj+W4puPHOf2jS1cPb+cS+oslOiUpLM5Hj48Sa8rXADHNAoZk4E4L/Z5uKLNgVQi4WMr5qCQy/jp9l6e7XLyyKcu4enj09x6ZTPVJTpS2Sz/d88wy+aUsLHdgVIuI5nOcGwiwNFRPx9fVYczEAOphHQmi04pJ5xIYzWo2N3vJhgXHnTpbBZ/NMWeAQ+7+z3ctKQKiURC53iAQU+ENU021rXY8YQS3H9wjLk2Pc2lRm69solgLM22w+NM+eNUFmu5rMFCMpXFYlBxcV0JW+aVksrkuPXBTg6N+rl+UQXXLazgkaMTZLI54qkM04E45WYtC6tNPHx4ghOToULq1e/3DCNDQoPDQCCawqxV0FxqxB9NkcrmkEqFKfGl9RZeOulhcU0xG9tLUStk1Fh07BvyCkCKPD1eItIRTVoFxTrBFtw7JEzqs1lhFl+sUzG/0szewRnm2gzc8WQ3e4fEOP5cN+zq8/DPN88nns7yeOckh8f8VBZruW5BOa1lRrx5hmlzqZE7r+0opHK1lRexrLYYi17Fj65r54UeF65QnFqLnlqLnmKdim2HxlndaGVHr4shdwSdSo5BrUAqhQmfAHHfv6yaW5ZWAyCXSnjppBuTRs66FgfzKk0kM1msBhU3Lq4kkxONyncf62L/sJccgvX51PFp7n7fQn5x43yePDbF0XE/zQ4jGztKMarlfPOR4wyckjB45mQwlcky5o2+rjmxGlRUmjUMeSJEZ1cH/obq/6U51E9+8pP/7V34Xy27QVWYYz3eOcmiahM/3trBgRHBCq8+TzbUm9Vb9bV5pwwLiSTHpXOt/Pjpnr+qZv/tVrlZc1bfnlm2yIUCNs487/Z3OSXujaRl5yP7fKuVzGR5vsd5VtnSC90u3r+8+pzG9+dbb+VavBvA2zutc+3TdEAE32zuKCWcSBfuBa1KTpFW+Y7kqRJgcY25kAI3a9eyq8/NigYrt21sYXf/u5tU+LdW7+TeEQsFNl4ZmCl4ZoIYT1aeAfad+j0fWF7Dzl4XnlACvVrOhC9GJpfDFxXhPSvqLVj0qjcdczJZ4R28/cT0657FfmeYnqlgIczh1MRXq0FVSHiF/IJJneUtnbe/VJ03KDV//nymp6ex2WzMnz8fiUTEy59ZEomETCZzQXfy7yXqVFrrpg4H+4dnGPKIB8OsVdDvCp+W7jKL4nojKeTS114Yp64gJTPZQrpRPC/3WtVopbJEi0Yp45K6Eh47OkkkIVDd2hIdP7txHodGffROh7Ab1Vy7sJxEKsvTx6cL8rxk3u+oc8LPZQ0WXuhxMekXPkJKuZQOSxFrmmzEkhlOTAYJxVM8dWyK9yyt4qljUyyoEqyHrz94jEFPhAqzhpdOenjlpIcvrm9kZaON7SemeaHHxfYTTtQKIW+rLtZycMSHRa9i37CXlY3WgmE3CLZTuUnDZfVW9CoZV88vI5PN8WyXkw2tDirMGnb1uRl0R6i1aCnSKNnYXsq2Q+NEEkIqE4iJlKwbF1cRT2f47mNd9EwFMWoUdE8FebHPzdeubBLbK9Zi0avYmfeXaS41cP2iCjZ3lBJLCXaNP5riyKiPymIdv9pxMg8WppHLBCvs85c3EE6khWzGH+PBQ2P8yy0L+eebF/LQ4Ql8kSRWo4qLakvQKeW83O8hnEgTS2ZwBYUPT58zRCCdKUjDABrsBjyRJCsaLBwY8SKXRtg7NMPaJjs7e1wisUYC2RxUmjQFKRoAOUiksjzX7eR9y6rZNzTDrn4PRRrRkLdbdKxutKKWyxj1RpFKIIPQOCfSWRQyCQ02YTL+bJeTkZkoHRXinuh3htk7NMNFtSW0l5vwhBNMBmLMRBJ0TwXZ3FFKMp2l2WFgz6Dwu7njiW580SQT/hjZHMy1CjP9R49OsqrRxvWLKrhn7yhrmmxcXFdMnVXH965u4/keJ8l0hl/cOJ/9wz5ywD/fvJA9gx6GPVHKTGoub3Vg1igwqEuEflslZ9wb5a5nerh6fjnrWuzsH/Yy6Y/jMIqUxFKTmitaHRjUwjNkRYOFRDqL3ahmaW1xgVn09W3H+Mr6RsqK1Dzui2HUyCnWKjFqFEgAm0FNNJmm1KRmJpLEH0tRVayl3KQhEEvhjSYJxFLkgENjfmqKtUz4Y0TzcddKmRSDWoFEAqPeCMl0ll/vOEm93cCWeWXMrzBxYMiLN5JkQ6uDEr2Krz5wlNs3NnNj3u/tz/vHsBnULKw2sbDKzNLaEuRSCTKZFE84gTuUwFGkxlGkJprMMDwTzYM0kMkKuaLFoGLUGxH7HE6yptnOI/ce5oGD46SzIj2zpdTIxy+rQyKBMW+Mr2/rxBNOUqxTEoqneLHfzbc3t6BRCEbmXJuBfmeIAXeERDr7/7H35vFRlWf///vMvmQymUlmsocESEIChB1ERRAQFHBB1LrU2v1pv9auj7VVa+2mrV1t7VPb3/O0z1K7aLVWRRFUFhVU9i0kIQlLtkkmySST2bfz++PMDAkkkEBCEjjv18vXS5IzM2dO7nOf6/7c1/W5+Ne+JuZOsPCjW6az60QnLV2SKHtNsY3GTj/v17ajVSmod3q5riwLfVwEXVxi45X9zeSl6blpRg7N3X6uKLKSY9Fz/dQs1AoF3/nXIYJhaaK8bU4eH7+igO21/exCFtvZVtPOJJsRlz/MN1aUsPO4i70nXfGSUTvH4/PZ9rp2Wt0BrAaNVP6oUhCMSIHMtDwzf9hWT4c3RDQmcqChi4dXlbFqejbvVLXx2821LJ1iZ1aBhbWzc1EKCn79zlGOOnp4+q5ZfGyelDGhUyulTllKgV98bCYGtZI3DjvIStVh0qlRKaXneE6ajnZPEBB4ftdJml1+SrJM0u7u1xbjD0c50uLm9YMtZMe7tyTa3Xd4Q/Fzlzr41Tk9bDjk4N6FE7i6OIMrJ6WjVSnINGl5cU8j1Q4PPQGpVbpWpSQmetla3cba2XlolAoc7jMXJ+/XOnl4dTnXlWfx5w9OUO0df55Scgx1aaBSCCwqsfGv/c3UO70EwjG+92oln7yqkI8vmIBWpZAyWodhUTxSBsIDLcwm2UxsrHTEn9mnhJzRXOwPlUTGTaPLz7xCK28cbKHTG0762uXF53xVfEPlK8uK+yzoh+O7XswucaczEt3xYqLUzbk/GlxSh94LYahCwVDM3i8WA52TCDR2+ckwafnysuIzxsL5jotwNEZrT5B3a5wcbnH3sWt5dmsdVS1u1s3OG3Md7EabCx07g90o6P05FoOa+nYvhvj6OOEHDKfK6gYz5ygVAql66b1OR6NS8O7Rdh5YWtzn/PKtBhYVZ2AxSN5m8wqt5Fn06IWxmW0+aFHq2LFj2Gy25P/LXDz6S2tdXGrjBzdP441DkmKqVSmYnmum2uFGGe/ukmBihjF5A0Dvh5a0aBXiJTwi0OEJYTFqKBLhkZcPcsecfL57Yzn7G7o41OymucvP3EIr15VnsnBiOm09QQxqJc99eIIqR0/SvDs93pL+vaPtfGVZMd++YQpvV7XR0OljSraJpaX2uNeLn4k2I2qlgvUHm1lSYuPH6yowaJS8daSVLr9kCBiOSh3mjnf62FHfwaLiDP6xu5EUrTJZ6re4xMaW6jY+qO/k3oUT+N3mOibbUpJlQic6fMwqSGPhxHQUCimLxOULEwrH0KoV5KTp+fcX9nOs3Ys6fl3er+3g53fM4Ld3z2bDYQdNrlO1wAaNkjcOtdDc5UevUeILRUjVqTnc7OaNgy3ce0UhxfYUHnrxADWtHvRqJVUOKYPs31eU8taRVvY1dPHQDVOwmXRsPCwFg4kSu2yznoNN3WyqdLCgKJ31B1viokeEtyvbuGVWDvdeUYBCEGjpDvDy3iauKckgM02fzObaXNXKbXPyOdDQhScYxR+KIoow0WaUhL1DLdwwPZvvrCnnjUMOWuLf5ek7Z7G5uo3DTW4mZ6Zww7Qs/KEom6va0GuUCAJo1Qpe2d/EPQsK+M6N5VxV1UZjp5/CDCNLSqVy0agoMj3XzI66DoLx62zSqVhRnkWqXs33Xq2kstmNSafiUFM3O+ra+fKyEgQE/t9zexAEKZD68boKXtjVgD1VS01rD+kpWm6emcv3Xj3M9NwQP7mtgrcqWznU5Gay3cg1JTZOdHj50/vHERBYOzuX2QVpREVo7wnS6PKxraadablmSbRBYH4800SnVnC7JZ9wNIY3FGXvSRcbDjl4cGUpRq00ZWaadTy4cgrv17aTnqLl0dXlyXKqkqwUlsbLDv/60UlyLXpurMhlWk4aggAHG7tQKxVsr+vgeLuPbUedrJ2Vx8bKVqocPSCCJZ5pM7fQyu4TLq4ttfNG3PA5YXBdlp3KqulZGDUqgsoYLd1+5hdaKEiXuj9ajOqk6W04ImIxaGjo9LHtaDsfHe9EIcDy8kxJUKxx8tmri/jLRyepd0riUVGGkfUHWrh1dh7haIzNVW00dvmZYDWwcFI6HZ4QHx3vZFGxjZbuAFqVAptJS2aqNrk7rVZKnkGRqPT5tW0efru5lp/fPpNffWwmbx1ppTZevreyPIusNB3BcIyMFA0PrpzCruOdvF/XTjSmoqXLL3Uwmi1lOfpCEV4/0IxJp6LbH8YXivL4q4e5cUYOd80vIDdNMhL9+64GXt3fhM2kI9eiZ2pOKiIi31hRyoKJVlzeEFaDhpuX5RAMR5mSZSJ/abFUZqlT8T/bT2BLkcpOEWHvSRdr4y2b3z3a3icwsZm0dNWG6fSF2XOikw5viC8snsRNM3Jw9gT46HgnLm+YJaU21h9sQRQhVa9OZrUBVDt6mFdkJRSNodcoWFORw3XlksD5wNLJaJQK9p508fyuRt6qauXJtRW8dqCZDYcc6FRSZuLNM3MJx2J0u6US4jSjhtw0PVFR5IvxDNRt1U788Y0OQRDISdNT5XDzzDu1ZJg0fHCsgzcOtfDYmqk0dfkkYbLAwrNb65Lt7pu7/GiUAvkWQ3IzQqtWJLuzPvzSQWwmLQ+vKiMSL3tq6fYTjooIgtTJNRwVqWzpYZEnSCwmsrVG6oyVEG2iohg3q5e+1/9331z+/n4N3zzVtG1cIMdQlwYiUgz1xNrpbK1xUuf0MMmWwuISqeFBvtUwqh5Mg2GghZnFoE52OD2d0VrsD5VExo2zJ8gXFk/iWzeU8V6tk05vmIkZRhbH5+nmLj8bDjuocvScsaAfru86GiLA+baSPxuJLqn9eemUZpouuKxzqELBSAhvF8rp5ySKolS6HghjNWho7wmiUiqGLVOptTvAtpo2KUt6UjrtPZKNx7Wldm6ZlcNVkzNQqxTxYmKZBBc6dgYrOPf+HJdPmnsqm91JL+EEibK6wcw5OrUSo0bJZHsKGw+faqKgVgqYtGpy0/QIAsnzi0RFIrEYR1p6+PvOBrLMOpaU2sk06/B7I2f9rNFi0KLUhAkT+v3/4eSll17i2WefZffu3XR2drJ3715mzpzZ55hAIMA3vvEN/va3v/XpHJOZecrA6+TJk3zxi19k8+bNpKSkcN999/Hkk0+iUg38dTs7O3nggQd49dVXk51jnn76aVJSUpLHHDhwgPvvv5+dO3dis9l44IEH+OY3v9nnfV544QW+853vcPz4cYqLi/nJT37CqlWrLui6nC2tdd3svKTJ8LIyOx8e60im7cHA/gOJh1YkKtITlHxmJtlSuLrYhqM7wI66Djo8If7zvWMsLrFx94IClpZlcrzdy992NvC/O45hN+lQKgSeuXs2mSYdMVEkFpNad6fopGudm6bnYFMX/9rXwvKyTBYVZxCKxEhP0fLLt2qIREVunpmTNGz70etHuGVWLvctLKTLF8aoVeHyhghHpSyTLl+YeqeXm2bkcM+CAo62eajIM3P91CyiMZHvvXqYQCTGfVdO4JvXT+HdWicZKVo+eWUhKqUCURSpanGTYdTi6A6y4ZCD6Xlm5hdaee1gCw0uf/IBK4rSTk2ile9VkzNIi/tG/OHdeu6eX8DOeCczpUIgTa8BQRIRj3f4UMQ7jnmCEXLM0vURBIGdxzt5u6qNWQUW/rqzgY+OdbJ2Vi5N3X6pxC6evaZSSFkmR1s9rCjPIhSJSf4xBjUd3iB6tZLXDzno8ARZVGxjTlzAWFORw4ZDLew67mL9wRbmFVl5eFUZHx7rTHZWu6bYRqs7wP7Gbm6cIflQ3TorVxonceGkKMPIrAILnd5g3KBaRbE9hcYuP4IAqToVmamSyWqqTs3VkzOS185i1OB0B3nj0EmunmxLdgaKRKWSwCsnp7OjroOW7gBmvZTJo1QINLj87D3p4q75+XR4g1LZVrEkMB1p6eZj86ax4ZCD3DQ9t83J45vXS8LQ7II0ri7OYFGxDYc7wAu7G1h/oIVgJMa+xi5unJGD1ajloRcP8Jmri3j9kIM/bKtHrVRgN2lx+cJ0ekN8eelkrpiUToZRi8Wo5r/eq6fAauTfV5ZKZY5xEg+mW2blxgVAWDgxnSsmSsHBH98/zvqDzVgMGpZOsROOxnAHwkRjIiWZqSgUAv/Y3YTFqGbPiS6ummzjibXT2VzdRpMrwMx8M7MKLFQ7enj6rRq+c2N50qS/qSvA9NxUZuSncbjZzb6GLv7fksmUZaXicAe5ttTOB/GsOoUgEBNFrEY1i4ql9N2E59Kr+5u5cnIG31lTzpuHHSgEAbc/TJZZh82kJRiJcdOsHLzBCA+9eIAufxitSsE/ugLkWfT8cO10WroDfPMfB3jqtgqauqSunIuKbew54aKpKyAZqgMZKdLnrz/YgicY4fP/u5OvLC/htjl5qBSKZPfP5q4A79Y42d/YRU6anhumZzN7goX/2FyLLxylsqWHq9wBttY4uWVmLlOyU9l1wkWB1YA3KN0771S1UZJpIses53dbaqlyeEjRqlErBCZYDaycmoXVqCHNoMYXjGIxaJhbaGHrUSdvVbayuiKHleWZ8QytKB/US8FLpzdEKBJDp1ZS2eLm9rln7kIGwlFWTc/C5Q1x08xcvvK3vdz8zHv8533zsJu0LC6x4w5IWaxF6Ua21jjxBaPYU7XJOSffaqDLF8KkVfGV5cUUWI28U93GaweamZ5j5hNXFvKV5cW09wTRqpXUtLp5v7Ydu0lLJCaSqlUTE0WcPUG2Vbcxp9CKNxRlR710v+WY9Sydkslkewq/3FSDWqmgwGLgqkkZrD/YQr5VjyhKi4FGl5+NlQ6m55r59j8P8OTaiqQ3RqLdfaLNfXqKJpl1m2cx0OkNsXZWbnIXMRSJkWnSJsupU7VqVArJq25NRTbNXVJp8MGmLsJREbVS2qEPRyUPsoNN3VxbascTiHDTjBz6PnnHPhcjhpIZeXRqJQa1ko+OdTCv0MqKcsnr8GBTF0tK7OMiG2GghZnLF2aSPYWjbR6uLbUzt9Ca7OScaFwzljk94+bZrXUsLrExt9DKhHQD5nimc0Onjx+9foSDjd1Jn5WE/+riuJ1C7+86kqbvI8FQyz7Pxdm6pF475cLH/FCFgpEQ3oZCf+Ph9HMKR6Uu0/nxTbzXDrRQ2eIeljLYQDiKLxxlem6aZI8Rr+xYUirZQqypyEluoMr0ZbjGzmDMyROfsyvewXjPyS7cgTCBsICAZPeQKKsbrJiaolNxY0UO2+vaOdrq6eVpZehz/jq1koae0xsewI66Dh5eVYZ5jA6P8zqt//mf/yEjI4PVq1cD8M1vfpM//OEPlJeX89e//vW8Ay6v18vVV1/NHXfcwec+97l+j/na177G+vXreeGFFzCbzXzpS1/i1ltv5f333wcgGo2yevVqsrKy2L59Oy0tLXziE59ArVaf1VT0nnvuoaWlhU2bNhEOh/nUpz7F5z//+WQ3GbfbzYoVK1i+fDnPPvssBw8e5NOf/jRpaWnJlsbbt2/nrrvu4sknn2TNmjX85S9/4ZZbbmHPnj3n3dJ4MGmticlnKA+i9BQNT946HZc3xKFmN209ARZOTE/+rsHlQ0AyJX/7SBsqhcCSUju/eqsGdyBCOCqiUijIs+ixGNQsKbXz2gEpa8ikUyGKkGfRsXBSBv/3wXH+trOBv+1skMyj9Wr+4+NzyDbrefqtairyzFIXtqNOatu82FK08a5Merrj5s/pKRqUgkBPIEx6ioYOT5AFRVbWVGRjNWo43u7lc/+3i55AlPLsVAxqVbz1eTbd/jCv7G+mzumhwGLguvJMlAoF7kCIw83dtHuC3H/tZCk9uVd9m1alIFWv4kiLmxtn5LD7uIvDLd2snZXHnhMulpdlMtGeQuxwK3q1ArNeJZkrq5VMzzWjUghUO3po7pKySMx6Ncp4doDLF6Iiz8wTa6fT7gmiEASK0o0EI1LZRjQmJg3TSzJNdPtDyQwlT0Dy7omKIpkmLVNzUvEGI0zJMrH7eAcqpYInb63glX1N1LT20OzyM2eChZtnSmbuHd4gO4+58IUjPH7TVJSCkFwQqpWS0fYvNtbQ5Q8TjsT495WlWI0xvMEIX72uhHePOml1ByhMlzKSUrQqvvTXPZzo8CUzc75/81T2N3bzfztOkG818uVlxew83kmTy8+EdAPFmSY2HHIQiWd09S75PN7h5ZZZuXxnTTntPUF2nnDh8ob4/s3TaesJsvN4JxRaESEpDEVjIrtPuHh2Sx2dPiktNWH2X2A10OkLEY3G2F7XwVeXl3C0VdoN9oei9MQFN5cvRK3Tw/LyTN6pauPjCyfw1eUlKAShzwO+v4CkpcvPO1VtPLu1PnmcWa+SOq6l6WnrCfCbd2qZZDNyXXkWRRlGKvLNHGruRgR+t6WWeYVWFhRZuX2OidS4H9Gj/zqIzail2tHD0jID91whlYcIwH9sqeP5XQ186qoiqh09PPH6EbQqBY+uKeeR1ae8BPIseuYWWmmKC6wJwToUFXl5bxP3XzuZxaU2iGelGbUqJtpS6PJJIowgwPdunoYnILWVfX5XA/XtXrZUt7G8LJO/72xgS3UbK8ozCYRjqBQCD68u590aJyc6feRbJF8mbzDC3pMuALzhKD/bWM3UHDOfubqIv+86yW2z8/nOvw4RE0W6fGFc3hBvHWnlyVunc02pjf9v2zFWTtVQ5/Tyg9cqCYajXD8tmw/rOzjR4SPNoJF2ieLlGeFojCdurZBa+Hb4yE3TcV15ZryDXpi/72xge10HPQHJJ06vVmLSqej0hrAYNLT2BDColdwyK5cCq4H0FC3OniAHG7uYWZCGNxjBatQmx8TJDi9bapw0uSTvt8WlNv7wibm8sq+Z1w40c8WkdMqzzWhVCjzBCAsnp/PinkbC0Rhi/DuXZUsdTd845OCmmbkUxE3J651eslJ1HGrqlrKXbpxKpzdIeooWAQGtSkEgHMETiHDl5HSc7iDf/Md+5k6wolEquP+ve2hy+cm3GNCoFGw76uSh66fw5aXFONwBVpRn0e4J8taRVpSCQFcgjBj3TKtt87B0il3qKBlvK/zmYQeHmt1cU2LjlX3N8XlfuvfzrQaWlWWSadJSmGFEp1YSjkqlfVcXZ/DinsY+qex5FinLddtRJ/MLreRbDbxf24HVqCEcFWns9BGMZ46e6PTyw/VHeHj5+BZ1RiqGkrk4ZJp1LC6x94m1FpdIO9DjgYEWZnXOHlaWZzEtx4xRq2JL3A8y0d1prItSp2fcBCMxNla2srGylSsnpfPlZcXJmLq5K4BJp8YTlOLZxPyW8HdJzFsXo8PbcDMS5YPZZh3fvXEqW0/rkjocmT/nIxRcqPB2PkLjucZD4py21rRxpLmHTHM2i0tsOHuCbK1xEozEhqUMVkAa673NrkVENh1p5ee3z0QfL9uX6Z/hFm3P9Tnv17YjAo/dWM57R9s50NjFhHRjcmwcbevhwZVTBjUmVAqpi/NP1s1ga3UbDS5/vx6G59IOritOHdbvOlyclyj1xBNP8Lvf/Q6AHTt28Mwzz/CrX/2K1157ja997Wu89NJL53Uy9957LwDHjx/v9/fd3d3813/9F3/5y19YunQpAH/6058oKyvjgw8+4IorrmDjxo1UVlby1ltvkZmZycyZM/nBD37AQw89xOOPP45GoznjfY8cOcKGDRvYuXMnc+fOBeA3v/kNq1at4mc/+xk5OTk899xzhEIh/vjHP6LRaJg6dSr79u3jF7/4RVKUevrpp7n++ut58MEHAfjBD37Apk2beOaZZ3j22WfP65oMJa11MA+i/lqWLimxYTNlIgjSrrQkKBkIR6XuXS5fiOd3SibET95awYf1HRxxuCnPTmX2BAsNnVJpxy/umMHm6jaOtnqYkG5g1fRs2j1B9pxwYTdpCUSkrIRwNIbLG2J5mZ3tte38YVs9i4ozkhlZKoVAOBpjSYmN92vbae4KIIoiInD15AxurMihprUHpydIrsWAQhDY29DFsvju/3XlmdhTdbxb00amWc/3XztMhyeEXq3kw/pONla28tiacnRqJZPsKXR4gigVAhV5Zj6o70ChkIQllVJSs6dkpdLlDTFnQhpPbjjCnAkWfnJbBc6eINdPzWLXsU5c8e5avlCYqTmpLCuTOsBlmLR0+8MoBGmSyLXoSTNoyEnTc7LTx/7GLtZMz0YhwLVT7Gw45GBfYxdKhYAvGGF6rpnl5Zm8uq+ZNrd0nlNzUlkZzwzb29CVLH9aPV3DJ64sosMXwKrX8vErJhAIR+n2R2js9JOREiUqgrMnyPQ8M0qFVGZZ3+7l7ao26uOlZ2sqsnl0TTlf+etebpyZy4R0Iw+9eAC3L8Qd8wqYV2RlUbGNDKMGhVLg1X3NtPeESNOrUca9y/QaVdxgXclv3j7KlZMlb5llZZmkaFVolQoK0428r2inuTtAMBxDRCr5ssQ9dpTxzmZLSmwIgiSiBMJRri21YzNpkwFyYowviS+Qe3eYSOxEVDa7mZ5rpsBqoCcQpjgzhc3VbYhAIBIlNZ7ZN9meQntPkAaXD1EUMenUA947iYAkO02H2aCOd0RrpT5u4mzWq8kx65lVYOHPH5wgRatiWm4aCkEgGIly88wcPqyXfOHCUZEt1U4+qO/g+zdP42BjN1lmHVOyTHzhmklkmnVJc8MZeWlcOTmdijwzO4939jEwDEZiZ3gJCIA3FEEBfGNFadI7A+Ca4gwiMZF0o5YOb5ClU+y8vK8p6TumEATeqHRQ2eymNMvEDdOkjnjff/UwtW0eqcEAUl281ZhPTyCMQa0kM03HqopsfMEo3f4QJzt8mA1qPrdoIs9urSMak7zFZuSbyUnT86Vri/nn3iaOtnrItehJ1anwBiMcbfWwtdrJ3AlW1qc5WFJq54VdDYgiPP32Ua4psfHteHDR6PL3KaNr6w7Q2u1n/sR0lpdnYtAo8QWj3P/cbv7rk/Mpykjh+V2NhKKSkOYLRenyh8lN09MTjOD2h8hNM7Ok1Mabh1p5/WALxXYTt8zKRaEQ2FzdxurpOfhCEdp7Qnz7nwdoiS901EqBD+rbeXh1OXcvyMcfihETRV7c3chrB1pQKwW+uGQyP15Xwe4TLmpaJX++FVMzsRg1bK/r4GvLi9l21MnJDh9GjUoqU/SFOdbuZVOlgzkTrDz4/H6+f8s05hels6W6jTkT0tBrlLy4p5Hj7T4eXFGa3EkF6AlEsBrVHG3t4cNjHayenk2Vowd/OMp7te3UtnmYaDMm/eSEXveEgJD0PwhHRZq7fMydYOE7a8rZWuPkRIc0Nq+dYj9j0eboDtDhDaJSCFLGX00bPf4IGSYtCyem09IdYFu1E5UgcP3ULA40duPoDkgLxpiYLI9660groUiM3Sdcg3h6jl1GKoaSuThcLM+gkaS/hdniEhuZqTpE4NsvHeBom7QTX9XSw+Gmbh5ZXT6mzc4Hk3HTO6Y+3YO11R2gKMNIik7qCh0IR2n3BOnyhdh9wsX2uvFl+j6cYzIx5k/vkjpcDFUoON978EKExnOZsSfOae2sPBYVB2nuCrAtbjwejEgZwsNRGhqJidJmWy9vIQGBY04f7x1tp8BqQHtBn3BpcyHz91DETLVSsrRYXZGNQpA2D7Pn5nHzzBxc3hBHWnpwB8I8uHLKkAQxtVJBgdXA7XMHvhfPrR2YBv15F5PzEqUaGhqYPHkyAC+//DK33XYbn//857nqqqtYsmTJcJ5fH3bv3k04HGb58uXJn02ZMoWCggJ27NjBFVdcwY4dO5g+fXqfcr6VK1fyxS9+kcOHDzNr1qwz3nfHjh2kpaUlBSmA5cuXo1Ao+PDDD1m7di07duzgmmuu6SNqrVy5kp/85Ce4XC4sFgs7duzg61//ep/3XrlyJS+//PJ5f+fzqX89243SX8vSRDqf5IUgtX+9doq00H0/XuKnVAj8f+/W88zds7l5Vg43iTnERCk75RvP7yccjXHTzFyWl2WyoCidFI0SW4qWUCTGU7fNoMsX4sNjnXx4rIN7rygkTa/GH4ry9RUlvHe0HUd3AATwBqP88LVKOn0h/t+SyTx0/RTeq5XSFPMsepaV2UlP0bA4zUZjp49DjV2UZpm4fU4+IhCJSTvyLk+QIlsK6w+2cLjZDUC+xUBbT5Dj8YyGdXNyuWeBtCMtiiJLpth5v7adE3Gj8UA4SoldWgwZtUqUCgXlWSb+v231LC61saDQSpZZx09uq2BbjZOqlh4yTBrWzsojGI7y8r4mrivPYtNhB8c7fOjUSiJREYNaybxCK3/b2SB1BGvq5uFVZeRa9Px4neQPU9nipiIvjRumZaHXKDHrVSyclM5Em5FV07JJ1av59j8OsLnGSTQmsrGyle217fziYzMRRIEOT5DCjBQU8cnKYlQTjYpUt/bww9cqQRB4/MZy1EoFX3t+H/VOLyqFwKYjAu8fbedHa6ezuNTOnII03jrSSnVrD7YULW9WOvj7rgYc7gAPLJ3MxxdM4KPjUgmjzaTFYtCgEAS6fGHyrHr2NiiIifDSnkb+b8cJAL64ZBKrp2dzVXEGrx9s5kSnD0nLktJZr5yUwb6TXUywGrCmaGnq8vNWpYM6p5dJNiPLy7MosOjPGOf2VB1PrJ3OhsOOPj4fDncAdyBMJBqjLb5jtboim7eOtHK01YNOpUwufJeU2Hllf1O/PgkDBSSPrCoj06wj3yLwy4/N5J0jbTS4fEzJMjG/yEpVi5s5BVby0w1srm7jpT2NzMyX/ra9feHyrQaunpwRzx6DwnQD//mJeXR4QnzrxQO0uAPJzpZvHGzhR2un85u7ZnGkpScpMiXakCe8BBIB2NtH2jjY1EVB3Gx7ak4qBo2SLLOel/c2Ud/updAqtQT/v88sSJaO/nB9JQebuml1B3n7SBtvHGzhiVsrWF2Rg9Uo+SSolYKUnahRodeIpOrVtHQFePyVQ3xQ3xkfv2q0agU/vHk618RFtLvmS5l7wUgMnVpBpzdIdpoObzCCPkVDllkyjW/u8rNudh5P3VbB8XYvL++TzPYDkRj/u+MEj60p59bZecn5UqdW0tzpo7nbzyS7Cb1aSSgao6U7QEwUyYiXHV85KZ08i4Fj7VKnwmhMJN9q4IqJ6ahVCnItRto9IR5/pRKHO4BCgMPNbt6tdfLgylKK7Sba3AE6vCG21TipbJbMtz3BCNlmPU1dAbZWt3H91Cw6fSFStGpumJ6NiEhbT4h2T5BZE9JYk5ZNe4+VTm+YzVVtlGaaeGRVGekpGl7e24TNpMUUL8nr8ocREKht87K8LBNfOMpHxzq5YVpWMq0bSJrSZpi0ySYPAKFIDBFQKAQqm93MmWDh68/vY3lZJrfOzuPV/S1EopJBek8gQklWCteW2vnn3kZAEnldvhBWo5orJmbw8t4mIjExWcakVSnISu0b3Cd27Lp8IRaX2ni31snMvDSm5Zpx+UL89aMG9je4iMZgoi0Fi1HDQ9eX8kF9J4eaupPGxMc7vPz5wxNolAqcnvHXfa83oxVDyQwv402I6s1AC7NAOMq7R9txByLJknWFINAUX2CPZbPzwWTcBMLRZEydKD1OeLCWZZvQqBS0dAXYXN1GdUsP9lRtH7+p8WT6PhKM1Hc+X6FgqOdzvh0Xh2LGrlQIbKtp5/ldDWe8z3B5XrXGY6/TPb4c7sBZXiXTm6GMnaGKmWc73qBRoVMrsafqLkjcPZcp+ljzXRsM5yVKpaSk0NHRQUFBARs3bkwKMTqdDr+//w4Nw4HD4UCj0ZCWltbn55mZmTgcjuQxvQWpxO8Tvxvofe12e5+fqVQqrFZrn/ctKioa8H0tFsuAnz3Q5wIEg0GCwVMBttvt7vP74aydHuykqlYpsKXo+Ob1paw/mEpdm4eSTBNLSu3sb+ii3RNk7ew8tlU5ybcasKfqqG3z8PedDfx9ZwNXTLTy7Mfn0Nwd4N2j7exv6CI/3cDSUjsryjMRBHjqzSqcnhCLim3ML7JyTYmN3DQ9/9zbRIPLj4jIwcYuSrJSKMk0Ma/QSrc/zPqDLdS1evjGylJeO9DCxspWVAqB3DQd31pVTiwW47WDLYTCMT59dREnO3yIoqQah6MxdCoFoYhAuyeITqXkn3ubaHUH+NjcfAxaFd9eVcar+5upcvQw2Z4idcvq8FKUbiTTrObJdRW8cdDBoeZu1AoF1hQtSkFgeXkma2bkcLS1B61KwX++W89HxzuZWWDhqdtmsKWmjU5vmByzjismpnOiw8v22nbyLHpqnR42V7dx57wC7CYtd80vwBeKolMrqWpxs+eki9kTLFxdbKPDE0QEXtrdSK3TQzTeul4BtHQH2FzVxpqKHNyBMH98/xjVjh5KMlO4doqdDk+I0kwTz947B4UgkJmqY9cJF81dfgSkwFNAoNbp4b1aJ0unSAJgndMTL2WUDJmDYanEsLbNgyAITLKlsFGUMhgS7DreycqpWexv6KLB5UejVOAlmsxc2njYwR3z8nnsxqlsOiJlF020GVlSYqel28/22na+el0JPYEwP99YnTQI3Hmsk4NNbh6/sRyzoW/Wo06tJMOkYVFxRtLnY1uN5IHwleXF0rg2afnzhyeYmpPKk2srePeo1D0s06RjwUQrzd1+2txBPnP1xAHbu55+72yN3ztmgwadRsk9VxQQiYqolAIbK1s52NjFTTNyefAfUhmWCHxY38meEy4eXVOe9IXrvSjQqBS8ccjBNSUZvF/Xjj+eZahQSL5DkhjRwc2zcnF6AsyeYOmTTh8IRxGQApcnXz9CQ6eUjbWjvoN3j7bzzD2zCYajPBkPzsJRkY/qOyjOTIG4D9UbhxwcbfNg1qvxBiMEwpJX2taaNtZUZKNTK3ntQAtzJ1hYU5FDilaFWqUgEJYM8Q81u/GFowQiUmkcwM7jnayYmsUN07JRKwVe2tPEvgYXDywrJjfNgF6tjGcVSh0azXo103LNGLRKXtzSwEt7mwiEY8lMrqIMqeRVH3/IJ/5WnrD0s799dJJOX5jsVB3zJ1qxGqWyZZNWRVO3n5/dLgnKtW1eimwGlpTY6QmEyUjREAU21Thp7vLT5Q8TDEeTJR27jrtYNzuXVw+0ML/Q2qcbSjgq0hMMY1FqONbuJRCJ8R9b6phoM7JyahY3zcgFJINzlULg128fZdvR9uTr3z7SlswanZpj5lBcVG9zh5JdjibajFJDhEiMLLOOSfYUcix6IlERjVLBlOxU1Aeaae8JMskm+SIKSH5/oghqhUC+VU+XL0QgHOWV/VLnwqduq2DPCRcOtx+zXpMUdXefcDEz38x1ZZl0+cJ8Z005jS6/lLkUlURxIFki07s9eGLHbvcJF2XZqSwpsbO1xklrT5DZBWk0d/nwhWIsnGTFnqrj3/53F4tKbNw9v4Brp9ipbevh7ao2Xt7bhC8YJaSMkZumH/hBNw4YrRhK5uJyoV5EF8PLaKAd9t7d9xKMB7Pzc2Xc9BdTK5Jd+ewEwlGeeP0IJzt9tLoDeIPRPn5TGytbx8V1GK+MpNA31C5/vRlK1cpIe14pFQKF6YYzOq1L3kLGMSs4jHXONt8OVcw81/EjLWifcwyqxrnReW+uu+46PvvZzzJr1ixqamqSRt6HDx+msLBwUO/x3HPP8W//9m/Jf7/xxhssWrTofE5nXPPkk0/yve9976zHDFf9a3+TamKRc+K0STUmitS0epiVb2F5WSY9AUkQen7nSRaX2lk7K482d5BwVOQn6yrYWt1GXbuXYnsKd84rwO0P89SGKhrin3fE4WbfSRc/vGU6TV0+TnT6aPeEeGFXAxsOtRCLifz5s1dIwZACunwRZuSn8Y/djTy7pR6TToXNpMUfjmLQKNlU2crcQisbDjsQkXbx3jvqZE1FNrfMzCUW92OqyDOzva5DyqASwGxQo1AIFGUYqXK4efL1I0y0pXDzzFx84SCt7gBTc8wsLrXj7Any4u4GtlY7+cKSSSwrs6NSKJhZkMZVkzNw9gR5bX8LzV0+Hlw5hTS9GluKFl84Sk6anp5AhGfeOcrSKZnML7JSlm2i2RXgrSOtbDrSikqpkNqDhqO0ugP4Q1Gc3gAHG9zkW/WU56SypcbJe0fb+ctHJwlGYhjUSv7zvnlUt0pZGZGYiBAT0WuUpOhUHGuXTNcfevEAO4+7UAjwTpXkIfP7e+fS44/wQX1nUrmfM8HCj26ZzvdePZxML9aoFDS6/CwvlwybZ+SlcbTVg1opiRWq+K7AZHsK7R7JWHtTpQN34NQkd7Sth08snMAjq8vZVuOkvt2L1ajm6slSDfXbVW0snJyONxhlfqGVFWVZOD1B/rWviU2VrXz66iLUSkmYOdDYTapOhVmvJhITOdzUzZuHW7l7QcEZZo4mnZqMFG2vdqh6vra8hJOdPsKxGD+9rYKtNU7ePdqO1ajlnismoBSkzLJDzd10+yM8dMMU7Ka+yc+DDUja3MHkg+jnd1TQ7QtzTYmtTwmVQpDEgcauM33hQCqvfPKNKhpdfmZPsLCvoSvpU6RUKJKdOxpcfkQRrihK58pJGcRiIgatEl8wwvqDDmYVpPFujZN6pxe1UkCjUmBRavCHo/iDEd6tbach/rDSqBQsL7dj0qn59ksHeOzGqVQ7epLdJnPS9Lj9kvdSR0+I0qxUjrd7mZhh5L6FhWSnndotCkdjnOj0EQhL40kURVrdAcwGDc3dAfItejo8Id44JJXDzSuyEotJgsb7te043AF8oSgKhUBump4rJ2cQjYkcanInxyhIu9orpmaiUfVtv36630KqTkWKTsUrB5r40S3T6fAGsZt01Dh66PCGWFAkdRNt94T4594mss06ss16TDoVJzu9yTIyEXAHInT7wzR1+VEqFDS5/LjsUmeV3oQikk9UmkHD0daeZKeUjYelxU2Ty8/iUhsikGXuX2CJiWIyqDjZ6UepEIhERYozpQzAV/Y38bXrSijNNPH8zgb2N3YzJcvE6opsbpyRzY66dj461sn107J4p6oVlzeM2SB1mizKMLJyajav7G9Cq1Li9AT53quHWTMjh/sWFiZN04843GyqdHDjjBxWTs3CrFdjNWo42NTNoy8fxGLQouklQA20A/eJKwtZUmpnX4OLo609zCu0YjWosZt0PLp6Km8edjC/yMqOug56ghFe3ttEuyfIHXPz+dmb1XR6w5h0KjJStJRlm1g4Kb3fazZeGI4YSmbscq5d9XOJTaPpZTRed9gTDCbjZqCY2mbS8tKepuQiLrGZ1ttPb2Nl67i4DjJnMtQuf70Z6n0xkr5FkuBgZ3tdByc7T32fRAnu5ZjBdyEMZr5OiJlalSLZPMFiUBOJxghHYn024i5E/BxOzjYG/d7+u6yONuclSv32t7/l0UcfpaGhgRdffJH0dClA3L17N3fdddeg3uOmm25iwYIFyX/n5uae8zVZWVmEQiG6urr6ZEu1traSlZWVPOajjz7q87rW1tbk7wZ637a2tj4/i0QidHZ29nnfxPsM9L4DHTPQ5wJ8+9vf7lPy53a7yc/P73PMcPkX9J5Ue7crDUfF5ETpCUYQ4+3cu3whnnmnFk8wQqpeRZs7iDcUpTDdiDcYYWmZnW+8sI+y7FRumJbN9dOy8AQj6NUK3jzs4HiHF08gkuwOKADvHnUyK99Ck8tPJCbiESW/m9w0Pd2BMHkWAwLSJJFu0lLb6klmkQTCUbzBCEaNiuPtXq6enJHsJqVWCRzv8OELx3juw5PkWfSsnp7NtVPsvFfbTlOXn1AkRjQmMj03lSsnpfPXj06SnqJFIQh0+8PkW/T8YVs9GyulrB+FIF37dKOGEx0+3P4IdU4PeRaDZADq9DIl28Q9V0yh1S35Xuk1SoxaFaumZ7PzeCf17V7eONTC6wdb+P7N0kL/jUMOqWV6PIMk06wjJ03PsXYvoWiM1p4AP95QxX/cMwuDRkmnL4RRoyRNLxk5d/lDTLalsPdkl1QWpVJg0qkQEJhsT5EMu9skESnRar4820ynJ8RPNlTR3B0AURoPrx9s5qHry7hpRi7/2N2YbC1amG4kTa8m3agmVadi70mpm1okFiNVrybDpGFJieTvMyM/jZ/dMRO3L4zFqMGsV2PQKDHqVJgNmj6tSataeth70sXauHm0Jxjl+68e5qNjnYSi0t9nQrqR2QUWRKCuzUOXL4QnGKH3M7+2rScpqJ7tXgHYWu3kj+8fIyaKUtllkZXrp2YhAlqlgn/tb6IwPYViuwmXL8y7R50sKbGT12v3YzAByekPoi3VTlaUZxGOxnhpTxMKhWS9rtcoMemkrLPTA6HT36Mr3kp2Y6/sm8QOdm6anjqnh8f+dTj5+sxULV9dXkKHJ4gAHG5x09ItCVoalTQeRFFEUAic7JB2gjVKBSadmvmFVrZUt3E0fs0n2oyolAJt7gBZZj1WowYQmZJtAkTMejWrK7JJOy1jLbHrnDBkV8WFNJdX8h0D8IUiXDExnS01To45vZRkpnDn/AIeu1ESMXubN6bqVERFkV/fNYuNlQ6OtkoeaiumZpFp0vYJBkASarfXtjNngoV/X1FChkmL2x/mw2Od7Dnp4spJGRxv97Ko2MYPXqvk/3acQKkQMOlU5KbpuX1uHq/sb+KeBRPINOkIx6RdyGhM8rWLiSLZZl1yTCQ6q/T2E9OoFGSn6VlUnMFLe5qS55ZY3NxYkZ2cx3vvZmlVCr6weBJZZh0bDrUyPc/M168r5YP6Dk50ejHr1VxTYqMxLkhOsqXw4w1VHGjoossfZtdxHfsaXDy6Zio/XDuNNw87QIBn7p7Ntpp2qh09FGUYuHFGLkatknuvmMDCielsOOzgX/ua2HPSxbrZeWysdHDTjFxsKVo+fVURTk+I6tYeNAqBLTVO1s7Kw2bS4fKFkmPy9F3g3oHe8Q4vaQY11xRLovTPN1aTk6bj8ZumYk/VcHVxBpmpWl7aG6DLF6bLH+blfU0snJjOk7dWsL2unU5vmAKrnnlFVvbXNp9xH44nhiOGkhm79LdLvvN4Bz+4eRruQOScYtP5lhgNB6Pd2Wy4ONt5DhRTe4MRTnQkNo+EPkboCT+98XYdEoy3DoIjwYUIrkO9L0bad+5imXVfDpxrvk2ImYn4zGbSJptATMkysXp6Ntlp+uQcfiHi53BytjE4VvOxz0uUSktL45lnnjnj5+fK+OmNyWTCZBqa0dacOXNQq9W8/fbbrFu3DoDq6mpOnjzJwoULAVi4cCE/+tGPaGtrS5bkbdq0idTUVMrLy/t934ULF9LV1cXu3buZM2cOAO+88w6xWCwpnC1cuJBHHnmEcDiMWq1Ovm9paSkWiyV5zNtvv81Xv/rV5Htv2rQpeW79odVq0WoHZ0l3oRNa70m13umlpVsShuZOsLBsitSq/OW9TTR2+llVkc2iYslovNHlJypK5UiJjgF/2n6Mu+YX8PPbZ7Kl2snmqjYsBg3XlNiIxESOt3tp6PQTiwtcXqJ4ghFOdvq4ttQOCCRisGhMxBOM4PaFuDZ+fl2+sFR6Yk9Bp5ZEl55ABLVSQSQWoyTLRJpBQ16anqgoEhOldFaTVsXH5uaz8bCDJ16v5DtrpvLYmqlsOCx5S02ypXDzzBw6PCE+OtaJUSt123rvqJNPX11ESWYKHx3rxKBRolIqEEVR6qBm0RND6pyXZlDzsXmSwVwwHCMjRYNJp8aoUdDSHeRLf93JxxcU8MDSYjZXt9HU5aci10xhuhGbScdrB1okc229GkSRAquBuROsbK1pQxRhcYmN7bXtbK/tkMyzDzto7gqQmarDHQhzsKGLldOy+fB4J2L8+vUEImSZdVxTYuNQkxu9Wok/HEVAym66ttTOpiOtNHcFCEVjdHiC5Fr0dPnCvF/XzvIyO29XtfZpLZrI3slOUyQznhLd3K4utuEPRYiJIv5QlMJ0A53aEFvihtP5vYJtnVoJcb/wmQVpSZN1nVqJQRPlmyunJH2gJmYYWVRs41i7h3yrnilZJu6aX8DSKXYy4t3P3qluZZItpd/ygtPvlUA4Soc3lMyweauyjbcqJQH6Y/Py0KkU/OXDM+v+BYQ+uxn9iQeLS2xcXZxBUTxLRgAc3aem+nA0hkGrRCmomJ5rZkddBxqVghStKl6GJ54RCJ3+MOsteLT28grITZPKQN88fKo0OCaKVDa7eaeqjXmFVlwDCFrhqEg4EiM7TY83GE3em2a9ZHqvUSn46Hgn15ba2VjpoK7Ni9sfRqdSkGPRc/XkDGrbPGSb9f22HdYoFUnfqI+OdRKJiYSiMSZlpLB0itSyGODhlw5ytE3ardnboONgYzeP3zyVa0vtKBQChnj2n0qhoMsXIjNVy90LJkhzCgIgEohEMfRzDrMnWJhVYGFzdVvSX2zpFDsCUhCZbdbhD0V5ZLUU1B1r95KTpmdFeSa+UJQjLW5UCoFFJTb+Fe/cqVJKf6eJNmmMapQCi0tt/OzNKsqyU3li7fQ+ht9XTs6g3unhzcMtfc7tRIcXi1GTHFu9g0uLQUOB1cBTG6pwuAP8c6+CeYVWlk6xc/OsHCJRkUNN3exv6OLuBRPYUdfBlCwT9yyYgD1ViycQYdeJTt6vbWftrFxumJYtldUKUmbZ7AlpWPQaunwh/rG7FZcvRE6agTvn5XPXvAIEwKRXccfcAmKiyImOIB8d6+TvOxuYU2jhC4sn8a99zcwrsvLE2unsqOug0xfqt/tL70AvsQmyva6dx9ZM5ZvXl1KaaaI7EKHbF2ZLdRtTc8xYDGrJlF+AcETk5xtruHV2LjfNyCHDpCUUjeELRmnsGqsh1eAYjhhKZmwy0C55sd1EqzvIzzdV09yVmMvPFJvGwi775bLgPf06ni5a9DZCL8tKRatS8PCqsnF1HcZrB8GR4EIF1/O5L8aaB5dMXwYz3ybmhRStVLHTu+vhzuOd7G/o6tMEYqxlm46ncXFeohTAu+++y+9//3vq6+t54YUXyM3N5f/+7/8oKiri6quvPq/37Ozs5OTJkzQ3S7ug1dXVgJSBlJWVhdls5jOf+Qxf//rXsVqtpKam8sADD7Bw4UKuuOIKAFasWEF5eTn33nsvTz31FA6Hg0cffZT7779/QPGnrKyM66+/ns997nM8++yzhMNhvvSlL3HnnXeSkyMZx959991873vf4zOf+QwPPfQQhw4d4umnn+aXv/xl8n2+8pWvsHjxYn7+85+zevVq/va3v7Fr1y7+8Ic/nNf1GAmyzDq+vaqMNw9Jvkjl2VInN71GySf/9BFHWz0oFQKbjjj4xR0z+dYNZbxX6+Rom5fCdAOzCywca/fwwq5GXt3XzI9vq+COefl0+8Pxluht3Dkvn8xUHYFIFJVCiHdxEghFY2SbdRi0SibajMmsAoAcs57cNANZaToeXV3O5qo2OjxBVldkc6ipm9o2Dz3BCDlmHWl6NbMLLMREkaVTJLElO1XH3EIrBxq7yDBpWTc3j0ON3WyqbOXGGZLAdk2xDZdPytbYdLiVyhbJ/ykaE/nfHce5YXo2N8/MZX9DN4eauwn7I2jVCooyjCybkolCgDdOuHhhVwOT7ClcV5ZFvlWPSqFApYl3xDjqpMcf4em3j3JtaSZLSm2sMmlRK6VuekfbPHw73jK23umlIs/MsrJMqhxuttd1sKg4gyyzjp/ePoN3j0rdD5++axYfxkvu7CZdvGWxhu+sLmdjpYPaNmnRfV15JmkGDY5uv9RuPSiVW0nmzlqajvhRCOCL7/y5/RHSDGq6fGGKM02sqcjpd3HZ38MvYYT9jRWl6FRKHO5AsuQMYMcAO7un+zSFozFMOhXXT8tCFEU6vSG21jh5ZX8TBfHPPNHhY9ORVuraPEyyp/CxuQUUpBuAc+82nDUIKbZzqKm739f1t5vRu73rlOxUDGol2+s62HDIIbW1L7Vx86xcPjzWSTASY3aBhb99dJLcNAPLyzL58FgndU4PHd4QWqWCGfnmMwKh0x9mW2ucScHjo2OdOD1BJlgNLCq20ekLJQ3OE4SiMU52erl9Th49wQgfv2IC84usvHWkjb0nXQQjMaxGNTq1kqsmp/PSHuk+DEdF2j1BJttTqGrpYVu1k7KsVH50y3S2VDtp6wlSlm3iqskZWI0a8iyGMzKUkuNFpSDDqOHRNVL72ypHD3kWHcumZGI1Sp0V3zvaTmuPJIzqVEpERN6tbefvOxtYUGTlideryLPopQVAqo62niD+UDS5OzUxw8iSUjsGjTJpGplAo1Rg1Kj4yt/2Uuv0IIogCK28daSVp++chUap4ES3j0A4Sps7wKwCC0vLMtGrFIRjMRTAgyungCD9PRJikyRuGVlcIolb9U4vgkLg69eVsqO+g1Akxo0V2ViMGtRKBYeauvn91josBi0pWinbU6kQmJmfhlbVt4Sn9/314p5GHD0BSTyMRXl+VwN/fP8YX11WzPXTstCqlHzm6onoNUqm56YyPdfMlpo2ju/3UWQzsrTUjoi0GHl1fwslmSn0BMIoBIEcs55AJMYjLx/kSEsPaQY1FoOGncc6eHhVOdlmHc3dfjZVttAQF6BvnpXL0il2tte1094TJBCO8cT6I9wxL5+bKiSxSK1UnHFv9w70EobCbn+EXcc7WTc7jw5viCdfP0J5dirXlNjYUtPGNcU23ox3mdTE37PK0cOtsxVolAr+c1s9Fflp3DQjl38/180/xhmJGEpm9Blol3xuoZW3q1ppdPn7bKicLjaNhV32y3XBe3q8kJi3KjLMrJqeTbZZN+Bzb6wymll3AzGaWVsXIriOxftitD9/vDOY+daoVbGk1Ea7J8iW6rakIJWoLDm9CcSlkm06GpyXKPXiiy9y7733cs8997Bnz56kUXd3dzdPPPEEr7/++nmdzCuvvMKnPvWp5L/vvPNOAL773e/y+OOPA/DLX/4ShULBunXrCAaDrFy5kv/4j/9IvkapVPLaa6/xxS9+kYULF2I0Grnvvvv4/ve/nzzm+PHjFBUVsXnz5mSnm+eee44vfelLLFu2LPn+v/71r5OvMZvNbNy4kfvvv585c+aQkZHBY489xuc///nkMVdeeSV/+ctfePTRR3n44YcpLi7m5ZdfZtq0aed1PUYCtVJBpknL1cUZXD05gzSDGkGAv354kiPNPUkFtycQ5Tv/OsSTa6dzy6w8Oj1BlAoFMVHk/doAy8rs3DAtm2k5ZmKiiNsfZtdxF+/WtHPHnHwWFWfwjz0pHO9lADzRZuSKielolIrTFnopXD8tC1uq9lTb2bl5cV8WeHhVGe9UteHoDpBr0TOv0EpbT4DdJzpZVZGNVq1gTUUOnd4QT7x+BL1GxWNryinONBFo7CYakzJO/vzBSXoCYb69qoylZXZe3tdErdODIIAvFGN7bTt3zi/gq9eV8M6R1mS3t2VlmaTqVbyyr5nndzYQiEhGx4fihttGjYpQXPxpdPnRqBSolALv1zrZXN0miWeldu5eUMDjrxxmWZmd5WWZrJqWjT1VEkrbuoN864YyDGrJLytVp2Z+kZV0o1ReeNXkdNL02eg1SgTgqNONgIKPzZW6DvpCUQ43d/P2kVYWTExna40TAfAGI/jDUUKRKFOyTOw64aInKHk/BSNRQM3EDCNmvZqvLCs+60P29J8nvKWGurPbe+euweUjw6hhwcR0OjxBqlt7uGJiujQeUjS4AxF+/XYNh5t7CESi7D3ZxZEWN99ZXU67J8i0XPN5727ZTFq6asP9vqa/3YxkQDI7j5ZuPz96/cgZO94PXT+FW2bl8PedjXE/IQ9/fP8YP7m1ggeWTmZzdRu1bR6m5Zq5cXo22Wm6MwK0a3s9zIKRGM9ureOWWTncPjcPtVIhiRuCwHu17X08lgBMWhWfvLIIXzjKG4da6PCEKEw3csfcPG6ckUNlczezCiwcbe1BEPoKLjFR5MaKHA43d3PM6ePbLx3guvIsbpyRw5QsEx3eIBqlgmpHDxX5aRCJJcf96aKEQavCIorcOjs3eR93+0P8z/bjfGZREU5PEItBTU8ggkoh4A1K1+BYu5eVU7P6jJ+1s3KTHlHHO7yYtCoONHZzoLGbx24sT47zxPWLiiLb6zrivk+n/oZNLj8f1HWQZ9ETi4l868WDfVoqF9kM/Pz2mRRlGNCppUejQa3ko2Mdye5ynd4Q7x51ck2Jja3VUqvnW2blsKYiJ/m3SVyHnDQ99lQdwU4foKAnECY3Tcoy9Aalv0+jy99n5zoaE2ly+QlHRFq6/aSnaOPZoSKVLW6WTsnk8VcPEwhH+ef/u5IUrZqv/G0vdU4vUVFEADYedvD0xyTxzdHtZ9X0LBzdATYcdmAxaviwvpMuXxibSYsvKDUtaOoKsO2ok9XTs/neK4c56fLjCUii9obDDp68dTofX1jIrzbVAJIcfKTZza2z8jDp1GfcP9GYyDUlGUy2p7DreGeyJbZCEJKZt4k5w9kTpCw7VcqQEwR+fvuMuLdYkKIMKTM3cW1Wz8jBH4ry0p76s93yY56RiqFkRp+BdsktBvUZz8gEvcWmsbTLPtTF06VQInY20WK8ZRaNhay73oyFrK3hEJbG69iWOROlQmBJqZ0lpXYsBjUuXzgZs/Seb7PMOkw6Ff/Y3YhRq0way6vjGfSnbxhcLtmmw815iVI//OEPefbZZ/nEJz7B3/72t+TPr7rqKn74wx+e98l88pOf5JOf/ORZj9HpdPz2t7/lt7/97YDHTJgw4axB3bFjx0hLS2PGjBnJn1mtVv7yl7+c9bMrKip49913z3rM7bffzu23337WY0abRPevX2yq5s+fXYBBo6LO6eGOefmsKM/EZtLS3hPk/boOth1tZ3peGltr2vnXviYWl0jd8j42Lz/u+9FMqztAhlEq3SvLTqXR5UOvUfLUugq2HZVKYybZJHNelUJBXbuHbTXtyYWePxwlI+VUOUs4GqPTE0KjUkjt5A1q1lTkEIxEOd7u5YXdDexv6OKKonTyLQam5pipc0pt3ds9IfSaKG9XtbKmIoeybBNalYJFxTb+sbuRE50hfvxGJa89cA3P3D27T6bR7XPzeHV/M5UtbpaXZXJdfBH6VmUrJr2K8uxUzAY1afFr2OqWHq6LijP4284G7pyXT7ZZjxj3OuoJRHD5wggC5Fn1pKdo+PTVRRxq6uZgczfpKVr2NUgiyx1z8/GHovwo3vWluUvqrDXRZuSJtdM52NTF4hI7KToVL+xq5PldDcREkZ/dPoNnt9ax8XArFqOarFQdRRkp/PvKUj461klrT5D8ND2FGUZsKVpe3NNIwopJo1KQH1fu+yvDGixD3dk9fecuFImx6Ugrv71nNjkWPW8ecnCy08f9105mW42T5u5AXDxVI4pS179XDzSzvCxzULvGZwtCFhVn8O5R55B2M6KiyNaa9l6ClESjy897te2sqchBiPeHm55r5oijh59vqmFBUTrXltpYXpaJSavCnqqjpevMAM1u0vLIqjK2nvYwM2pVfQK3089dIQh88qpCjBolD714gINNbgQB0gxqPqxv55HVU1k3O489J7v4jy11gFQqmrgPdSoF2WYdD68qZ8OhFg40dmNP1aJXK3n3qJPvvVrJp64q4rryTEIRKbh8u6qVxk4/xZkmlpbZpZ1kpQK1UoHVqMUbjLD+YAt/39mAQhAIRWJ87pqJ5KbpaXUHCYSjpOpU+ONZcxMzjHT5Qn3HjyjyYX0H4WhM2tmNC1zH2r1sqW5jUbGNv+9sSF4/i0FDc7efLLMOTyBCMBJDrZRKgI93eJMm5C29Si11agVzCqxolIp4i2Wp016mWcfiEjvbapyc6PRhS9GyqNhGmzuYFFr+vrPxjHJPOBWUbK5qY39jFxPSjayYmolRq+QLz+2mxx+Jm4Sf2rnOStWRa9Envf58wQgmnQp3IMwkewpOjyReTLKnIAgC79e1Ux/3ohMEKUusodPPB/UdyTLbLn+Yx189zK4TLpaVZbK/sStpYG/SSfe9KIqc6PDiDUU40emjKS6ICgLsPdnF+gMt3LNgAouKbXT7w8zIS+PaKfYzAqzEomOgdurBSIwCqyEuTklzRkJ4TTxbJttTuHvBBIA+96paKX2/775xiMa2zgHv9/HASMVQMqPPQLvk/nCUYruJA41nZuf2XvyMx132sSA2DBdjMRvmfBkLWXe9GUtZW+P1byozvCgVAtlmHa8eaKa2zZPMwp8zwUJBry55iY3X0iwT+xq6APpkvJ6+YTDW55FAvIv6WOO8VqLV1dVcc801Z/zcbDbT1dV1oec04rz++us8/PDDSS+oyw2lIHDlpHRe2G2gvSdInkXBZxdNJBwV2dLLg2VNRTZGrQqNUpEMkjZWtiIiolMreeSfB5MLF4D1B1v4/s3TaPcE0aqVbK9rZ36hZCrt8oU52NTFkhI7GSYNVqOGLdVtyQV37932xIPrk1cWYjNpeWV/M8+8Uxsvw5EmEatRQ55VjycY4Qt/3s3yskz+bfEkAuEoJp2K2lYPKoWAxahJetp8/+ZpbKlpw5aixekO0OYJctOMnHj2kUAkFuNQUzdbe3nhqBUCSoXUxe/KSRmolYrkecREkf2N3cwvsrK9roMUrSpurO6k1R1MmmTmWw3MK7TS6g6ybnYeS6fYcXqCvH6whdcONFNgNXD3/AlsrZG8o5SCQFaqjp5gmFZ3gI+OdXL7XKlDWygSSwYZkhl9mBJ7Cqk6NcvL7NhTdbj90uuWltpJT5G+/xuHWshJ0/PDW/r63vS3sBzyeBrCzm5/O3dqpcCVkzJweUM89UYVVa09mLRqgpEYB5u6iUSlTLze3f1q2zysm503pF3j/h4I57ObcbZAr6HTh1qpYN2cPATAqFGy60Qnh5t7eONQC29XtVKencpTt1XQ1hM8a4B2rodZf+e+uiKbV/Y109QV6LOb09QV4N2j0s5ovkXPLbNymGQzndoZOtHJkhI7WrWSTJMkvFw1KYNWd4B/7m3itQPNBMIx6pwebtNLWYxf/fu+PmnM79U6+e6NU/sEl0atimtL7eyo66DR5UetlEo/F05KJydNx/F2SXTSqhRkZKRIXlRHT5UkJt6rpjVe9qhSSCb6cRF1z4kuZhVY2FLtRKNSsL2unSdvnU5ump5IVEx2bAxFY3R6Q6QZNBxr96JTK7l5ppTRplMr+O6N5RRYjWysdODyhft4oiX+FuFojEaXn7cqW5OCVIL+DOujMRG7Scui4gzmF0keX2qFghd2NnC4yY3FqE76fPXOClsSz8I61NSNJxRBp1GycGI6q6Znc6ixm3sWFHB1sS1plJ9vNSSzmjTxpgdNXX5EJB+p53c10Bm/ds4eqUTzw2OdKAQBtUqaz2KiSL7FQLcvLHUEjUo+VAlj96OtHnyhCDPzzcwqSEOjUmDQnBk+9F50hCIxWrr9fdqpV7a4uabEhkap6DNnBCMxNla2srGylTvn5fe7gx8IR9l21EmXL5zcnRyvjPcYSubs9Dc3T0g3kJ6i5cNjHecUm05/fVGGJGgnzLjH2gJnLIkNw8VYur7ny1jKuhtrWVsyMiDNXT9+4wjH2n30BMO8X9vOB8c6eHJtBVlpfdcBUiXDqXg2wdk2DMbamE5sILyxt+ncB48C5yVKZWVlUVtbe0br4vfee4+JEycOx3mNKD/96U9H+xRGlVA0hi8c5Ym102n3BLGZtLh8Ye7/yx6qWnpAkEybt9Y4+fWds1CrFH2CpFkFFrYddeIPR4nEJC8au0kHRPnoWCeLijNQKgTWVOTwXm17Mg1ycYmdzPjO2UAL7t4PLrNezd6GLq4ttfPmYQf1Ti+iKHk3ZabqWFJqZ+/JLiJRkcn2FJw9waQnQ3GmZKKvUghEYyL/2tuETq1kfmE6JZkpvLy3id9uqUMURXLT9CwutXPvFQWU5Zg50NiNLxxFrRAIx0REYpRlp2IxqPnJugo6PEG213Xwfm075Tkmuv1SCVjC/+eb10/ho2MdNHT6yU3Tc8WkdHyhKIeaullRnolWpWDvyS4c7gAfm1fA4oQ5fIckdCR8DCxKqauZ0xNMZp9EY2KfIGPfSRe3z8unpSvAO1WtHO+QAthrS+2k6FU8v7OBIlsKM/Mt7G/oIhA65Xsz0MJyqAxlZ7c/QUcQBK6YmC6VaLqDWAyapOBWkG5gz8ku0lO0WFM0iKK041yaacKgUZ5zwj9XOcH57Gb0F+gljM/XVGQTE0WUCGjVSrLT9HxnzVS21rRxstNPgVXP4hI7OrWS9QccFxSg9Xfu0ZhIU5efNIOahLt8YjcnIZzYTFqunmyLm5hLPl0ryrOwmaRSUhHYddzFnz84QUu3P545BCIixfYU9Golu0909il9C0el8rKtNW3cNif/rAusqCjiC0X58a0VbK6WynLLc1KZVWChodPHlipJlMqLm6q7fCEKrAbMenXyO+rUCnzBKKtnZJORouXnd8ygJyCVENc43CwusfFOVRtHWtynsotsKSwqzmDbUScGtZIV5VlsrGzlhmnZTEg38vBLB+kOhJPjr/eiKvF9dh13sbGyb4dVOBXgn54x8IkrC/nzhyf5sL4DQRD46W0V1MTN3UO9RC1RFKlv99LlD9PpC/PN60vZXtfBsXYveRY915VnkZGiITtVahzgC0kCbWG6kQ/qO7AY1RAXyxUKIXk+MVGg1R2Id8czJDtfHmrq5kiLWxLelQrKc1JZXGqjweWTynpFiCf7IYow0W7EHYiQqlf3W64HZy46EibBLl+IHXUdrKnI5pZZucnsiaFmg0RjIg2dPsIxkW5f/2W344XxHkPJnJ2BnismXWxQmyD9vd7ZE4w/M8ZWJpIsNoxdxlLW3VjL2pKRScxdTV0BNCpFcs3l9kd4v7addXPyON1CbryX5SU2EI41t4/2qfTLea1IP/e5z/GVr3yFP/7xjwiCQHNzMzt27OAb3/gGjz322HCfo8wwEghHiYkiaToVde1eUnUqlAoF7x5tJxIVsadqCUdFdCoFwXCM92rbkx3U8q0GbpmVSzgao6U7gCcQoScodWBrdQfIStXhjHd1S6Q6JrxATl/sD1ga1evB5fKFJdNutZInb53O5qpTHlSrpmeTplfzn+/WUZZjYkmpnZf2NGLSqUg3alheloleo6Syxc3UHDNZZj3P72pgY2UrT91Wwf7GbnoCYdKNUkentypb0aoErivPYnvc2N0TjAACU/LMLJ0imWK/tLeJSbYUVk7NYl6hlUk2I/XxxXmiDOXTVxWxdlYeQNL/JxSNMSXLhFIQqHL0MLtA6njo8oXZVuNkfpGVzFRtslshnBITJpwttV+QJtBfvVVDtaOHUDTGh/WnukFERDFZGrOmIrtfU+LhYLAT9bn8NgTh1Pfe1+Bi9fQcDjR0U9niJhCOolUpmZqbypqKHFJ0A09fQy0nGMr16K8T3xcWTyLLrGNrTTst3X19gvKtBm6bk39G6+nhCtBOF3XzLIZ+OxMmhIq2niA/2VDFyU7p8w81u9l7squPALOk1Mb7tZI41BMME4rEmGxLYU1FDhqVgjcOORAEycPKoFWhUiSEL/8Z5376AksEDjR20+4JMrfQSrpRg1mvRkRk94kAc4usFFoNLCqxEQxHiYRFVkzN5J2qVqpbPWhVCsx6Hd9cOYUJ6Qb+ubeJIy1uJttTuLZUMiFPM6h5/KZy3jjo4Iijh8k2I4tLbbR0BdhaLQnr107RYTFoWF5mZ2uNk6YuP9lmffLanb6oGkyA39Dp65MxsKTUTppBTTgqolEJyY6IQLx0TyIcFbEa1Zzo8PHzjdVcXZzBNcU21s2Wrtn+xi5+v7WOKVmpLCuLZzeKcO0UOzvq2mmIzwWS+HTqfALhKJmp0hysUSkwqKVy6K8uL2FztdRsYaLNyPKyTKwGDaIoUpppYudxV/LcJtuNLCmx0+0LJztN9sfpi47e4nqnL0SGSdtH0BpqcCcIxMs+AwR6ZU2OR+QY6vLgQtvEJ353+rwy2Eyki+HxNFSx4VLwnRoLDPY6jpVF9FjK2pKRgTPnrt5x80Bx+FgvyzsbA20gjCXOS5T61re+RSwWY9myZfh8Pq655hq0Wi0PPvggn/3sZ4f7HGWGgdMX6dlmPXMLLTi6Azi6A1Q53CgESDdK2RIJcaChnxuzpTuAxaCmyx8mJorxcjYRdyBMfi9BCoaeutj7wfXR8Q6WlNh5/NVDzC6Q2qJfPy0LfyiCxaBme10HN8/MZXGpjUA4ilGr5J4rJnDlpHSsRg2HGrvZfcLFjLy0PovJLl+YSTYjerUSs14yqhMEgW017Vw/LZtHVpez8XArzV1+ijKMXFNio6HTxy821dDuCfF+bQcf1nfw43UVaFQKUnr5MQUjMVy+0BkTVaJjizcY4Z2qNrbXnflgXl6eyZ4TLpp6eRXlpulYVGxDAILhKCKQnabjR2un0e0Lk2bQ8K99TbT1BLEYpUyicDRGZbOb1w+2MK/QyusHHWysbMUTjPDlZcX9/k0uNFAc7EQ9JL8NEVL1Kr6yvJh3qtqoae1hsj2FZVMk43mVYuAd4pEuJ+gd6FkMGgqsBp7aUIXDHUAQhDM+71ytp3tzIQHauYQTpSAkH0pn6wCVZdbxyOpyttU4Od7hJc9i4OriDFL1alpcPnItemwpWlRKQSr3isTQq5XkpenpRw9LnhtI43jhxHQeffkgrx1oRqlQoBRg7axcbp+Xj1apQKVUIACbq9rIsehpdPn51g1lbKlu42ibh3uuKCA3zcCjLx/kg/pOFAK8dURgU2Urv/zYTCJRkTS9hpXTsrimxBbPMmhhR10HIlCUYSQjRcPd8wvISdPj7AmSbdafURY2FPPK0x/4WpUCXyjCnfMKuH5qFu2eIP5wmHWz81hQlE6qXk23P8xHxzvYc9zF1ZNtbKtxEghHeeOgA18oyq3aXJ56o4qGeOnjoaZuPjzWkRxX2b3+Tv2dz5GWHhYUpbPhkIOpOWZunZPHGwcdOHuCXDk5neVlmTi6A7y6v5nCDCPXT83ix+sqePVAM9WOU/ebNxjp46/QHwONaYUgMMFqOEMMHkpwF47GQISFkzLI29VAdU/PgOcxHpBjqEuPoTxDh/KMPZ9MpIvp8TTYZ9ml5Ds1mgz1Oo6VRfRYytqSkYELi8NHeryOhHh/tg2EscJ5iVKCIPDII4/w4IMPUltbi8fjoby8nN///vcUFRXhcDiG+zxlLpDTF+miKPJerZNvXj8Fg1pJUYaRPSe6UAjEF9USp9+YSoVUVnVtqZ31B1qobfMkKz0m2Yx9Hi7nc1Pp1EoWl9rYWtPGy3uamJiRwmNrpvJ+bTvvVLVK5XAT0wlFY0zNSWX2hDTMejXBcIwvLp5MTBTp8oV5cVcjb1e1sXZWLiJ9F5Mub4gbpmVzsKkbR3cg+X1tJi0GtZI8q4F7FhQQisYIRWLUtPXwzX/sJxgVSdWpMOvVOD0hNla2cvXkdAqsBh5eVYbFoMYfjjIh3TDgNRhoEtxa4+T6aVk8vLqcd2ucNHf5ubo4gylZqSgVAt5QBIUg0NETJMOkxROM8m5tO4tLbBxt9RCJitKCWpCEL3cgQp3Tw4ryzAH/lnDhgeLp328wf+fB+m3MLEjjH7sa8IdjzCuURMn2niD/2N1IUYaRj83L79eg/WKUE5we6L24p5Euf5iVU7OYW2hNejW1dPvJStURFcUzrtNIBWhnE056e5KdTm8BJvH91s7KJRiJJe+r/Q0uiu0mVk3P5mBjNzvqOyRfOSAnTcfsCRYC4Wi/ZaGJsdbc5WeS3cgv7piJLxRBqVAQicUwaFQoBYGUeDZNIBylNMvEK/ub+e/tx1lTkcOSUhvLyjLJtehZf0AyYxdFEYVCgYAkon9Q18G6OXl0+UJ4AhG+8cJ+6pweyeNLq2JBkZXFJTbSDJrk368069wGxP393XvPbaHIqey3RPac3aRl/YEWGlxecsx6bp6ZgzcUpcrh5mibhzyLnhumZnPPggkcaOhia42TcFQyYb+iyMpbla00uPy0ugNkm/UoVcIZ4/hs5/PeUSdzJlh49t45dHpDRGMih5q6ea+2nU2VkvDV3O0nx6zn+mlZiIBWreCeBRMIhKO4/RHc/jAFVgOZ59hZP98xPZix7ugOSPNgMMKPbpnOG3vqefQX53zZmEWOoS4dRlpsOZ+yp4vp8TTY+/5S9J0aDc73Oo4F0ed8s7bk7DqZkWAsCqUj+Tw5mwg3VhiSKBUMBnn88cfZtGlTclfvlltu4U9/+hNr165FqVTyta99baTOVeY86W+RLggCre4gHx3r4PY5+Vw/LZu9J7vOeWPq1EryLHrqnB5+vK6CLfEW91OyTNw4IweNUkEgHMXZEzzvm8qsU/HV5SW8U9XG1po2rp+axcfmFaBVKXD5Qvznu8d483ALFoMWjUrBivJMlpdn8vRbNX2yjE4//9MXb9+9ceoZD8fEwkuhEHh1TwvzCi1sqmwjKoLLF8LlC6FSCCgVArVtPdw1vwCXN8S+BheNLj/FdhPpKVqMGukabO7nGlzbzyRoM0ldzvLi5xgTRZw9QV7c00hVi5SxsGJqJrlWPSc7/Tz1RhWtPUGK7SbsqVpauqXSI8noWDJYn2RLwRX3Xhlokj3fAOdCJs6z+W0kMsAUCgGzXk27J8hv3qnlv947luwaCHDTDMm7qT8upndBohSvtTvAFxZPwmbSsqW6jfp2qSzqxoocvKEIrx90cCKecZS4TiOVVn824eR0T7LenC7AhKMx2j1B1h9socrRw8QMI9dOsQNSGdW3bpjC6wcd1Ds9TLansKTUjqM7wKGmbm6ZlTvgWHP5QvxkXQWiCO/XdSTHz7WldqIxEW8wglGrQqdWYjFqONnpIxCO8Y/djbywuwG1UsHz/7aQ4+1ecsw6egIRQgmTb62api4/MVHknSon1hQ1P72tgq01TuqdXibbjVw/LTvpn5U4x+Ewr+z9wF9cYsNm0vKD1yrp9IbwBKOsm5NHizvIrzZV0+Dyo1II7GvoYn9DFw9eP4Xq1h784Sg9gTDBSIz0FC2NLj/haIxgJEZPMJw0Rj99HPcWwRNGyBqlglyLgerWHnIsep54vYp/u2YiOWl6OjwhPMEI2WYdxXYTkZhIql5Ne0+AVneA6XlppOrUpOrUKNMNg+7OORJjOvH8uq7czp4TLo46PSzMN5/3+40mcgx16XExxJZPXFnIklJ7slV5oslCfxtNo+HxdK77XvadGh7G+3UcatbWcC7QZWFLpj/GSnlrgpF8nvQW4Y75ved+wSgwJFHqscce4/e//z3Lly9n+/bt3H777XzqU5/igw8+4Oc//zm33347SqV8s481zt4tzE8kJsZbwQ/uxkxP0eAJamlw+Vk6xc7tc/PQqZQ0dfk40hxgep6ZJ9+oOq+bKhCOsv6ggw5PMNmq3uUL8ecPTmAzaVlQZOXtqlYsBm2y1Ob0LKOznX/vh9HZHo6JazbZnkJ2qi7Zlj0YiSXFkVXTs+nyhfjxG0ckTxckr5wPj3Xw0PVTeK/WyfO7Gs+4Btlp/V/rhCCmUgg0uAL8v+d2U9XSQ2Lp+a/9TfzlswvYUddBpcONxaBh1/FOlpTa2VjZissXwqLUoFYKzC+ycv20LGpbPdw5L7/fa3G+AU443lXrR68foTkpAg594uzvvb3xDLBGl588i54FRen8vyWT+N6rlQTCp4yhJ9tN/fomwcX3LlAqBK4utmHQKPn2SweTBuCpOhUHGrr52nUlSXP806/TSKbVD6V8sj8BxtEd4EevH+FgY3dS3NxY2cqTt07HoFVS09rDFROlcdYV90bbWiNl5vTnI5IYa8vL7HR6Q/zg1cN0+MLoVEoEoYP1B1r4/s1TmWg75VukUSmYnpvGjvoOQpFTwlOXL0R2mg6VUoHFqEkerxAkk2+po52Pf+7tZHGpjQVFp7qAHm31kB2/FxLfdzgCk97Xdm6hlS3VbTg9IXyhCF2+MHMK0th42MGhJjcGrQpPMILFoKHB5Wd7bTu3zZa6Gj6/q4GYKOIJRijJNLGxspVwPGszQX8CYn/B++rpWRzr8PLmIQc7j3VSYNVz66w8NlU6qHN68QQipBk05KZpuabYxqbKVoozTZzo8LGluo22niClWSauLbVfkOB8ISTmYlGEhZPS+dvOBv76XvUFvedoIcdQ44fBLGJHUiTofU8f7/CSZlBzTYmNsuxUnt1ah82k7Vc0Hw1D6XPd97LJ9fBwqVzHwd4Tw7FAl8tGZc7GWClvhYsjOidi3Q1763nzgt5pZBiSKPXCCy/wv//7v9x0000cOnSIiooKIpEI+/fv71PyJTO2GMwifSg3pihCqzuISohnDLV62Fzt5LUDzbzwbwvZUnP+N1U0JnKiw8v2uo4zulxdOSmdNRXZVOSa+2REnZ5lNJSJZaBjEtds13FpUbu9TupU4AlECMdESrNSmJVv4bUDzTR1Bc4wyNtU2cq0XHOfbJ7e1+Bs1zoYibHxsIMqxylBCuBISw/eUDTZbh1Odfx7Yu10dtR10OkLMSG+oLaZtOSm6Qe8FkMNcBIP90g0xobDDg42dmPSnfLkutCJ88wARPp+X15azJqKHP6xWxL4SjJTuK48c8DsjYudkqtTKynLNvF/H5zo05EuRaeissXNO1VtzCu0JsdzfwbaF8pQdgGzzDq+vaqMrdVtNLj8yfHSW4BJPBybuwLJzLtwVKTe6WVLtZO75uXT4Qnzh23Hznj//oS/3mNtfpGVzdVt7GmQyuVS9SrsKVp2n3TxXm07E9JPiVIGjYplZXY+qG9PCr8KQYiXpmYNmN2pUSrIsxjYXtfBW5VtvFXZhiiKhKMit83Jo9HlZ9dxV5/gdDgCk8QDX6kQeHlvI1qVgp6AiCBAhklLndNDIBIjVS8QAlaUZzKrwEKeRY9apeBj8wpYVJzBjroO8q167CYtf9t5Mp6hqejzHU8XEAcK3idmpPDCrkaMWiXba6UsridvreCdqjaauvxU5JpZVJKBUlCgVgpkpuqS4qpRq2RfQxc76jouWHA+XxJz8clOLwaNip/cVsGbe+p55FfD9hEXDTmGGvsMZRE7kiJB73s6MXdtr2vnsTVT+fcVpeRa9P2K5qNpKH2ueOpSN7ke6Wycy+U6wvAt0OWyUZnBMBay5y6G6JyIdW+emcvnL/jdhp8hiVKNjY3MmTMHgGnTpqHVavna174mB1NjnMEu0gf7QNUoFeSY9Xzt+X3UO08twifajFhTtDQN4Ow/mJvqXA9djUrRr7Fv5mmZDxdK4pr99M0qyrJT+feVpeyo68DRHWCizcjiUjtqpWLALga1bT1SO3tvSCotUkpldb2vwYAdCEWR2njbeAH6CFOd3hD5Fn2yc1ei49/5dNcbaoCTeLh/ZVkxVY4eXL5wvARIj0aV6L52fhPnQAGIozvAvoYuPnllIaFIlMl2E9eVZyYzXQbiYqfkqhQKunxhLEZ1MqNHq1LQ7Q+f4e0Fw/eAGeouYDgao7U7QJPLz9xCK8vK1Bg0SlJ0fY3jez8c1UqBbLM+2YWv1R1Aq1aytMzexwMMBhb+eo81i0HD8XYfgiAJ3DqVknBMRKdS0uoOcDq9TdcTf8tEedxAf2O1UsHqiiym5aaiVytx+cJ8UC8Fo/PjXk0bK1vPCE6Hy2vMG4wwNdfMoWY3GqXkd9XeE2SSLYXdx10oFQIPryoj16Ln7SNtvH4wSLE9hfkT05loSyFNr+afe5ooyTTx41sreLfWSbcvLM09JfZ+BcSBgvdbZuVSmmViX0MXAL9++ygz8tNYXGJn3Zxc1EoF/9rbxBWT0llWlslrB1qS4mpinhnN8pDEXLy1po2KvDS2VrdRnjs+y/fkGGrsM5RF7EiJBKff04lOlm5/hF3HO7l1dt6Y2ZQZDGPxnGD4RKSLlY0zVq/jSDAcC/TxXu4oc3lxMUXnsTruhyRKRaNRNJpTpRIqlYqUlJRhPymZ4edsi/Qhd/NQKchM1fKTddJue53TwyRbCkun2NEoL+ymOtdD16BRYbCqLkqqZZZZx4Mrp/BBfQf2VC13zM2TOoUpBIxaFYFwdMDvOtluIobID2+ZRoZJS3tPkG1HnYO6BkpBYLI95QxBShAkX6vFpTa2HXXS6g4CkjBV2eLmllm5fVqun4uhBDi9H+6929qHo2Ifr5vznTgHCkAUgkBzlx97qpZH15SjEIRB+dtc7JRclVKgMN2IxaDp83ONUtHH2yvBcD1ghroL2F82Wp5Ff8bxvR+OiQWRRSl9t7JsExqVYkglv73HmssXZpLdiC1FS4pWhVatQBShMN1AUYbxjOtytr/lQD8PR2N4glH2N3RztK2HPIueVdOzuOeKAg41drO1xgmMXHBq1KqSPlWRqFSKt7nayW1z8jjU1E1Jpok8i4EH/7Gfkx1SN8ONla38bWcDz9w9m2yzDp1aye6TLhZOTOfu+RNQKQQ0KsUZ4/9cwbtKISTP5WSnD2dPkOc+PMkHdZ08dVsFbxxq4Z2qNkJRkXsWFFAfF6TUSgGTVp3MAh3N8pAss44lJXZ84Sg3TM9m4776UTmPC0WOocY2Q13EjpRIcLbn4WDaeY81n5Sxdk7DLSJdzGycsXQdR5LhWKBfKuWOZ0P2yhodRuK6X06i80AMSZQSRZFPfvKTaLWSSWwgEOALX/gCRqOxz3EvvfTS8J2hzLBwtoVdQ6dvyA9Ug1ZFTpqOGyuyUSgEYjERs0GNTnPhN9VgHroX4+ZMXDObSUubO8CrB1pocvmTAUx2mq7f75pv0bNiaiYKQWDDIUdStFs7K488ix7lOXfFRVZMzWL9gRaOONzERCljqjwnlUKrEbtJy3dvnMqW6jZOdvopsOpZUmo/r6BksAFO74d7bx+reqc3WUp4IRPnQAGIKIrkpulp7wnyt50NQw4eL9YkPtDDpDwnlaVT7Gyuakv+bLgeMENdQA3l+P6+j0IQyLPoWVxiP6co1B+JsdbS7efGihwONHRT2eLGHQijUSooz0nt896nM5SfO7oDPBmf02KiyN6TXew67uLB60upbu1JGgXD2YPTCwk8Et93a42TY+1ectP05Fr0PHbjVERRZMMhB92+MLkWPaFIjG5/GJcvxFtHWrl7fgFXTEwn32qg2tHDm4dbWFJix2I8cz4+V/Deu/voluo2DjR2S3NXiZ0TnV5e3NOISSf5dCkEgSlZJnYe78SkVSd9+xLvNVrlIWqlgjyrgUA4igDcMbeAr47KmVwYcgw1tjmfRexIiAQXuiAfSz4pY/GchlNEutjZOGPpOo4kw7FAv5TLHWWvrNFhpK/75SI6D8SQRKn77ruvz78//vGPD+vJyIw8p0/k5/tAVSsVWI1aDBrVGQ/GC72pRuuhO9AC1NkT7Ne4/ZFVZf1+10UlNkxaFQ+9eID9DV0EIjF2H3dxqKmb76wpJ+UsmT6BcJTXDji4alI6T981k02VrdS1eZhkT2FFeRaZqTqUCgGDWsnCSelcNVkgJoro1UpiMRGGeJkGe617P9x7+1htrXHS6g5Qlp3KNSU2MlK0BMLRIf+9BgpAssw6rpiUTkyEtbNycfnCbK1pY0mJnbwx5gcw0LhP1amwmbRcOSl9WB8wQ11ADfX4wd7Hg/1bJ8ZaVqoObyjC164r4e0qSdicaDOybEomqbohPZL65fQ5TSEIxBA50uJm4+FW5hVaef2gI3l8f8HpcAQeie97W/zeAqmJgVmnJhCJ4vKGsBg1iEh/G7NeTbc/TGOnj0hM5KNjnWhUCuqdHhaX2JMlyqcz2OA932rg1tl5LJ2SSU1rD//c28RrB5oJhGNEY2GKMoxoVQpWT89mf0PXWTuZjhaJzx9sN8CxhhxDjW3OZxE7EvHKcO2Yj/b92h+jfU7DLSKNVjbOaF/Hi8GFriUu5cwT2StrdBjp6365iM4DMaTI7k9/+tNInYfMKHGhD9SBBKvhuKku1o14tgVoNCYOGMBsHcC0XAD+/OFJ9jd0YdCqSNULRGLSonhrjZM75uYTibdt769zTr3Tw7/2NfGZq4u4aUYuGpWCUCRGW0+A3DQ9TV1+vvy3vRxt9SRfV5KZwtN3zqIwo++O+2A517U+/eGe8LG6piSDiRkpxESRIy09/P2jk2SZ9ee1c3B6AJJv1XPVZBtGrZIXdjZQ0+ZhYoaRJaV2/OHoeYlfI8nZxv0ts3KH/QEz1AXUUI8fqYdjVBRZf7CFVneAuROsLC214/KF2VjpINusY+2sC9tZ7m9OUwgCJp2aEx3ePv5eAwWnwxl49PddwrEYuRY9Ll+IQDiGVqXAYlBj0qkoyTLhCYRZOS2LTJOWogzjoMzrBxO8G7UqOrwhnvvwBJUtbpQKAYtRTXl2KktK7Ri0KrIH8O27XHbqRhI5hhrbXMgidrifRZf7jvlIMdwi0qWcjTPaDEcMcineR7JX1uhwMa/7SP/9AuHoiL7/+TI+txtlho2RfKCOl0nxbAtQu0k7qACm93f1BiM0d/nxh6O4AxFA8oPKTNXR6PLR7Q/zP9uP95t9kfh7bK/r4HdbJOFnbqFVWrBqVcREkbePtPYRpABqWj1sqmzl7gUFI5ZFcPrD3WrUUGA10OUPJ0ulEpzPAv70AEQAuv1h/u1/d1Pl6Eket7GylZ/dPoOxGur1N+5H4l4Y6gLqfBdcw33uCeH1Lx828JtI7anPUSm5e0H+Be8sDzSnqZUCM/LS0KoUZ81auxiBRyAcZW6hFeuuBmrbPHiD0rxxxaR0lk6xY9Kp4p0th5aVNZjgPdus47s3TmVrzany397m6WNpp072y5C52IyVRexYug8vJYY75r2Us3GGwkjO1RfyfpfifXQ5eGWNNQLhKOFojLmFFrp8IbbWOAdtAzGWSCRhvLG3abRPpV9kUeoy53J/oA6mc9VQAxilQqAw3dCnY1mqTo1KKWAxaDjR4WN7XQf9ZV8k/h47j3dw04xcbCZt3DvKx/TcNJZOsVGRZ0anVhAIx/p8bm1bDzFx8JPiUIOI/h7uAOsPOIZ1AZ843huM8Or+5j6CFEC908t7R9spsBrQDumdLz2GuoAaKwsuu0lHINJ3pyYQiZKZeuHnoRQEFpdk8H6ts08JWr7VwLVT7GSl6vjysuIBx/1IB3yBcJQNh1qxm7T8+NYKttS0JUsYb5iWjd2kQ685v3l3KPfxbXPyz3r/j+bcL/tlyIwWY20Re6nHYBebkYh5x8pzdTQYL3P1pXQfydl5F4/e47vB5SPDqOGaEhtl2ak8u7UuKUyNl+ueSMI41tw+2qfSL7IoJXNZP1DPtQAFhhzASEGPne3xblcJUnUqFhXb2Bbv/AX9izdZZh2P3zSV9p4Q3/7nAVq6A5i0aqodPXxQ387Xrivltjl5vHWkDZVCKg30BSNMtpuSnbLOxoUGEadnhY3kAr61J4haKRCOnnoftVLA4Q6c5VWXD0NdQI30gmswQqdSAVcXZzBpdwp1zlMZf5NsKVw1OYPzjWMT4/rdo+2U56Ty9etK+aC+g6Yuf585Ta1UoFYN/CEjHfBFYyInOry8tKeRxSU25hems7I8C5cvTG2rh9w0/QW9/2AZS0H66eOmVfbLkBllxtL9ITO8DHfMO9aEzIuJ7G108bnckwkuJqeP71AkxvqDLXz/5mksLrGxsbJ13Fz3gZIwxhKyKCVzWT9QB7MAPZ8A5vTX5Fn0zC200hT3ourN6eKNWqnAoFHxwbEWAuEYFoMmKTY1dQX4oL6D66dl8a99zQQjkh/NtFwzK6dmDqp0bziDiJFcwCcyznIt+mQ5nxj/eVGG8aLuSoz1MqLzzUYbLoYidEZjoACeWidlCdW2eZhsT2FJiR2lIBCN9f8Z56L3uNaqFCwusXF1cQY3zcxBp1YOyRx4JAO+3iW6Gytb2VjZmvzdnfPyL9q49gYjxEQRhSCMmnF4Ytxsrm6j0eUnzyJ1Eg2Gozh7gn2O7S3gy8jIyJwvIxXzjsXYYCSRvY1Gj1Pdffsvw5e5cPob32qlQCAc46NjnSwvz8Qaz5waD9f9bEkYYwVZlJJJcq6Hx1hfmJ8PQ+lcNZQA5vSgB+BAY3efdM8E/Yk30ZhIk8vfb+ZTo8vHmhnZ3L2gILmgX1aWiVmvPuf3He4gYiQX8Dq1ksWldrbWOKlsdhOKxtAoFZTnpLJ4mHclBhrb4yU1fbQZitBp1KowaFS8XdXMzLw0lpdl0t4TZHtdOzdW5JyXQHL6uA5GYknB5855+UMWMgYrRJ/PnDjau5zBcJSeQIQuf0jqTCiKpOk1mHQqtBd5Xm/pDvD9Vw5T2XLq/t5W4+ThVWUsK7P36ZII48e3QUZGZuxzqcSxo4XsbTS6GLVKrpqUwaJigVhMxKiVx/Nw0t/4FgQBjUrA6QmSZ9EPqhHNWOFsSQRjBVmUkjknl/rCfLAL0AvtIJhn0WMzaQe1EB1o8oiJInaTjg5PiAVFVlZOzaLLF2JLVRs2k5ZbZuWe9TxHIogYyfJPs07FV5eX8E5VG3VOD5NsKSydYidVNzxT17nGtpyafm7OR+jMMutYU5HDpspW3jzsYLLdxJqKnCGPmYQoBJBu1KBVKc4Qfc9nXJ9rJ/1C58TRLJn2h6P4E9dNIRCNifjDUVRK4aKKUoFwlHeOtPHR8c5kea6XKB8d6+Tdo06WlWWeIUolBPyx2TdGRkZG5vJB9jYaPVq7A2ypaWOSzYTFoMblC/N+XTtLSuzkybHpsNDf+E5k4a+pyB69EztPem+IHvN7R/t0+kUWpWTOiTcYIRiJMdmeQpcvxL/2NV1SC/OLVb44lIXoQNkU+RY9Vxdn8OYhR5+yH4ArJ6Wfc/E9EkHESF2/QDjK+oMOOjxB5hVaWVGeicsXZvMgBbjBcDbRKStVJ6emD4LzETq1aiWFGUbuXlBwXiVkp4tCuRY9VxSl84XFk87IRryQ4Higv++FipWjVTIdjItRHd4gbx1po67NwyR7CsvLMjFolATD0RERpvrLKAtHYxxt7enjFyf9XKTG4WFNRU6fn/cW8ENj1xJBRkZG5rJgtLN+L1cC4Si+cJTpuWlsqW6jvt3LxAwjS0rt+MNRAuGofO2HgdPHt1al4AuLJ5Fl1rG1pp2Wbv+4S9JIrEM37K3nzdE+mX6QRSmZAQlHY7R0B9hwsIXDLe7kpJfoOnCpLcxH4nucvhgbykK0PxFrUYmNQDh6hi8VDG7xPdLldsNJwhA64b3Tm8EIcOdiMJ0X5dT0c3MhQuf5ehmdKQrBthonX11ewuISG1trnElPqaIM43l9xkAMZwnsxZ47RcDpCfLgPw5wot2HIMDbR9rYeNjBr++aNezeUmfLKFMIAnnW/k3d860GNCoFd87Lv+yab8jIyMiMFy7nRkmjhYAUH3/7pYMcaz+V8bKxspWf3T4DOT9t+Og9vi0GDQVWA09tqMLhDiAIAuOteiKxIXr6pt9YQRalZAbE0R3gR+sr2X3ChTcoFUxsrGzlibXTWVxikxfmZ+Fsi7HBLkQHyqZo7PQNugywP8ZLEHExuqCdTXSKiaKcmj4ILvZu6UCikKM7wJ4TLm6syGZRiQ2DWsn2ug42HHIM627WWPXRGIy/VSQm8s6RNk52SOM7FpOy1E50+Nhc1ca9CwuH9ZzOlYm4bEomrx1ood55KrCeaDOytMyOTqW8LJtvyMjIyIwXLudGSaNFJCbybo2zjyAFUO/08t7RdgqsBrSjdG6XGqeP7xf3NNLaE4wLUhLjqXoisTZ9Y3/zaJ9Kv8iilEy/9F74aZQKvHEXj3qnl601TuYVWql3euSF+QAMpxfR6ZNc5gWKSuMliLhYXdAGEp3USoWcmj5ILqbQOZAoJAgCTV1+stJ0KNxBfvT6EZq7AvHfDt9u1ljz0RiKv5UoijS6/ISiMcS4dhYTRaKiSGOnH1EcPkHtXBlld8zNJzNVy0/WVZzhGZdp0qJWKTh36wYZGRkZmdFGjocuLq09QdRKoU/5u1op4HAHzvIqmfNFp1biDUZocvXvHTBekjQSa9Njze2jfSr9IotSMv2SWPgpBAGTTo0nGElOfnVOD6umZ5Nn0csPon4Y6Ta5wyUqjYe/3UiKHYMRvcZLVtloczGFznOJQtEYbK1p7yVISQzX/TfWfDSGIoArBYHizBS0KgWB8CnfLa1KQUlWCsp+un2eL+fKKAtFYxi0KnLSdNxYkY1CIXUQMhvUGIa5jFBGRkZGRuZSQKkQKEw3kG3W0xMME4rE0KgUmLRqijKMcrLACDHWNiSHykBr07GEHPnJ9Evvm0+tFPpMftNyzGSkaIbdf+RS4WKV94wHUelCGWmx41yi03jJKhsrXIxrcy5RCBjx+2+siJVDFcCVCoHFJTa21Tg53OwmGImhVSmYmpPKomLbsAZVgwng1EoFVqMWg0Yl318yMjIyMmcwmNL0ywkpBrKzva6Dk52nYp0Cq4HFchb/iDHWNiSHytnWpmOFsW8VLzMqJG6+PIseQRDQqBRYDBrmTrCwcloWaQbNuOg0MBqcWoydyXhQ08ciOrUSo1Y17JN+b9Hpy8uKWTcnj/x46d7F+HyZ8yMhCt05L58rJ6Vz57x8yafIrLso999gx81IM1QBXIy/5qEbpvCFxZNYNzuXLyyexEM3TCEmigxn8nnvZ0hv+gvgEvcXSN1eA+HoMJ7J5UE4HOahhx5i+vTpGI1GcnJy+MQnPkFzc1/viM7OTu655x5SU1NJS0vjM5/5DB6Pp88xBw4cYNGiReh0OvLz83nqqafO+fknT55k9erVGAwG7HY7Dz74IJFIpM8xW7ZsYfbs2Wi1WiZPnsx///d/n/E+v/3tbyksLESn07FgwQI++uijoV8MGRmZcU84GqOh08cLuxr59dtHeWFXIw2dPsLR2LlffImTiIHump/PVZMzuGv+qRhIZuQ4W+w51jlbbDxWkFNdZAZkrGQDjDfGu5o+FhnpnTL5bzK+OFsGm1rJsNx/gxlzoz1uhppOrlMr0auVbKlpoyw7lSsnpePyhdl1vJMlJfZh/z42k5Zv31DGtqNtNHT6B3yGJHyxNle30ejyk2fRc22pfdy0WR4L+Hw+9uzZw3e+8x1mzJiBy+XiK1/5CjfddBO7du1KHnfPPffQ0tLCpk2bCIfDfOpTn+Lzn/88f/nLXwBwu92sWLGC5cuX8+yzz3Lw4EE+/elPk5aWxuc///l+PzsajbJ69WqysrLYvn07LS0tfOITn0CtVvPEE08AcOzYMVavXs0XvvAFnnvuOd5++20++9nPkp2dzcqVKwH4+9//zte//nWeffZZFixYwK9+9StWrlxJdXU1drt9hK+gjIzMWGI4vVkvRYxaJVdNymBRsVT6btTKcexIM56rJ3qvTY/5ved+wSggiMPpbHoBhMNhHn30UV5//XXq6+sxm80sX76cH//4x+TknGpd2NnZyQMPPMCrr76KQqFg3bp1PP3006SkpCSPOXDgAPfffz87d+7EZrPxwAMP8M1vfvOsn3/y5Em++MUvsnnzZlJSUrjvvvt48sknUalO6XZbtmzh61//OocPHyY/P59HH32UT37yk33e57e//S0//elPcTgczJgxg9/85jfMnz9/0NfB7XZjNpvp7u4mNTV10K8bSeTU2aGTWGT1J+jJi6zBMxQTZxmZBBdy/423MdfQ6TstcJcEuIEC94sxN/lCEUKRGC5fmJ5AmFStijSjBo1KgUFz5l7YyU4f33/lMJUtbkLRGBqlgvKcVL5749R+v8NYfE6ORXbu3Mn8+fM5ceIEBQUFHDlyhPLycnbu3MncuXMB2LBhA6tWraKxsZGcnBx+97vf8cgjj+BwONBoNAB861vf4uWXX6aqqqrfz3njjTdYs2YNzc3NZGZmAvDss8/y0EMP4XQ60Wg0PPTQQ6xfv55Dhw4lX3fnnXfS1dXFhg0bAFiwYAHz5s3jmWeeASAWi5Gfn88DDzzAt771rUF9Z3lsyMiMfwLhKC/sauT5XQ1n/O7OefnjotPZSDLU576MDJyK/zbsrefzy6ePuefkmImwe+/y7dmzh5deeonq6mpuuummPsfdc889HD58mE2bNvHaa6+xbdu2Prt3iV2+CRMmsHv3bn7605/y+OOP84c//GHAz07s8oVCIbZv387//M//8N///d889thjyWMSu3zXXnst+/bt46tf/Sqf/exnefPNN5PHJHb5vvvd77Jnzx5mzJjBypUraWtrG8YrdfGRS5eGzlgp7xnvJHbKnt/VwPa6Dp7f1cATrx/B0S13GJEZmAu5/8bbmBtqOvlIzk2Jcovndzbyg9cqeWVfE6IItU4vj/3rEB2e0BmvCYSjvHOkjY+Od+LyhfEGo7h8YT461snmqrZ+S/nk8r7B0d3djSAIpKWlAbBjxw7S0tKSghTA8uXLUSgUfPjhh8ljrrnmmqQgBSSzlVwuV7+fs2PHDqZPn54UpBKvcbvdHD58OHnM8uXL+7xu5cqV7NixA4BQKMTu3bv7HKNQKFi+fHnyGBkZmcuDi+XNOh45l5ek/HyUGYhE/HfzzNzRPpV+GTPle2azmU2bNvX52TPPPMP8+fM5efJkcpdvw4YNfXb5fvOb37Bq1Sp+9rOfkZOTw3PPPUcoFOKPf/wjGo2GqVOnsm/fPn7xi18MmHq+ceNGKisreeutt8jMzGTmzJn84Ac/4KGHHuLxxx9Ho9Hw7LPPUlRUxM9//nMAysrKeO+99/jlL3+ZTD3/xS9+wec+9zk+9alPAdJO4fr16/njH/846F0+mUsLWcg7f0a6i6HMpc9Qx8d4HHPnm04+Et/D0R3gh+srOdjYjcsXBmBjZStPrJ1Osd3U7zUMR2Mcbe3p09pa+rlIdWsP4WgseXxil++NvU3Dfu6XGoFAgIceeoi77roruRPqcDjOKINTqVRYrVYcDkfymKKioj7HJMQmh8OBxWI547McDkcfQer015ztGLfbjd/vx+VyEY1G+z1moAwtgGAwSDAYTP7b7XYPeKyMjMz4YLx3OhtJZMFO5kIZa3FsgjGdtiHv8snIXL7ID16Zi814HnOjndHaW9AL9TKirXd62VrjZG6htd9rqBAE8qz6098OgHyLAYVwavGRyGJ7aY8sSj333HOkpKQk/3v33XeTvwuHw9xxxx2Iosjvfve7UTzLkefJJ5/EbDYn/8vPzx/tU5KRkblAhtIo43JDbqYkc6kyZkWpC9nlO9eO3ekMxy5fe3v7gLt8A30uSLt8bre7z38yMjLyg1fmwgmEo0Pq5iaPufOnt6CnOa0UsM7pwWJQ93sNNUoFy6ZkMtFm7PPziTYjS8vsyfcaKIvtcuWmm25i3759yf8Sm3UJQerEiRNs2rSpj19EVlbWGXYCkUiEzs5OsrKykse0trb2OSbx78QxpzOY1wx0TGpqKnq9noyMDJRKZb/HDPS5AN/+9rfp7u5O/tfQcKYHjYyMzPhjPHc6G0lkwU7mUmXURCl5l09C3uWTkekf+cErc76cbytpecydPwlBTyEImHRq1MpT4tMkWwr+cLTfa6hWKchM1fKTdRV8cckkVkzN5ItLJvGTdRVkmrSoVVKYcrYstssRk8nE5MmTk//p9fpk7HT06FHeeust0tPT+7xm4cKFdHV1sXv37uTP3nnnHWKxGAsWLEges23bNsLhcPKYTZs2UVpa2m/pXuI1Bw8e7CN4JQSx8vLy5DFvv/12n9dt2rSJhQsXAqDRaJgzZ06fY2KxGG+//XbymP7QarWkpqb2+U9GRmb8I3uzDows2Mlcioyap9RNN92UDIIAcnMl063eu3zvvPPORdvl++ijj876mnPt8imVyvPe5fv617+e/Lfb7ZaFKRmZOIkHb3+dwmRkBuJCWknLY+786N1uuKHTR7ZZT08wTI5Zz/XTsshI0WDSqft9rUGrIidNx40V2SgUUntrs0GNQXsqRDmbx4iMFDvddttt7Nmzh9dee41oNJrM0rZarWg0GsrKyrj++uv53Oc+x7PPPks4HOZLX/oSd955Z7LL8d133833vvc9PvOZz/DQQw9x6NAhnn76aX75y18O+NkrVqygvLyce++9l6eeegqHw8Gjjz7K/fffj1arBeALX/gCzzzzDN/85jf59Kc/zTvvvMPzzz/P+vXrk+/z9a9/nfvuu4+5c+cyf/58fvWrX+H1epM+nTIyMpcf8mbQmZyvl6SMzFhm1EQpk8mEyWTq87Peu3ybN28+6y7fnDlzgP53+R555BHC4TBqtRQAD2aX70c/+hFtbW3J8sD+dvlef/31Pq8baJfvlltuAU7t8n3pS18a8Dpotdpk0CYjI9MX+cErM1Qu1KxcHnPnz+mCXr5VzzXFduyp2nNec6tRi0GjGvCa9xa9jvm9I/1Vxh1NTU288sorAMycObPP7zZv3sySJUsAKUv9S1/6EsuWLUOhULBu3Tp+/etfJ481m81s3LiR+++/nzlz5pCRkcFjjz3Wp1HMli1buPbaazl27BiFhYUolUpee+01vvjFL7Jw4UKMRiP33Xcf3//+95OvKSoqYv369Xzta1/j6aefJi8vj//8z/9MNooB+NjHPobT6eSxxx7D4XAwc+ZMNmzYcIYtgoyMjIyMLNjJXFoIoiiOCefW03f5egchiV0+gBtuuIHW1tbkLt+nPvUp5s6dy1/+8hdAMkcvLS1lxYoVyV2+T3/60/zyl78csPteNBpl5syZ5OTkJHf57r33Xj772c/yxBNPAHDs2DGmTZvG/fffn9zl+/KXv8z69euTQdXf//537rvvPn7/+98nd/mef/55qqqqBh1Uud1uzGYz3d3dchq6zFkJhKPyollGHgen4Q1G+PXbR9led2ZGzZWT0vnysmKM2jHTePaSZKTGZKL73oa99Xx++XT5OTlK/OlPf+KJJ56gsrIyufk3VpBjKBkZGRkZmYEZq8/JMROZy7t8MjKDI7Ewk7JBfORZDCwplcqL5Fr7ywd5HPSP3Ep69BkpcTSRxXbzzFz632KSuRi8/vrrPPHEE2NOkJKRkZGRkZEZn4yZTKmLibzLJzOeaej0neaXIxkxD8YvR+bSQR4HA3O5XJvLNUtOfk7KDIQ8NmRkZGRkZAZmrD4nx0ym1MVE3uWTGa9cqF+OzKWBPA7OzqVuVj7Ws+QuV7FMRkZGRkbmUkF+lstcTC5LUeqFF14Y7VOQkTkvztYW/WSnj2jsskt8vCyRx8HZudTNyi+ku+BIMtbFMhkZGRkZGZmzIz/LZUaDy1KUkpEZr8h+OTIgj4PBcikJUQnGcpbcWBXLZGRkZGRkZAaH/Cw/O3IG2cggy50yMuOIRFv0PIu+z8/zLHquKbHJk+NlgjwOLl/GapbcucSyQDg6rJ8lIyMjIyMjM7xczGf5eCMcjdHQ6eOFXY38+u2jvLCrkYZOH+FobLRP7ZJAzpSSkRnD9KfGX+p+OTKDQx4HlydjNUvuYohliZKCN/Y2XfB7ycjIyMjIyPRlrG58jQXkDLKRRRalZGTGIOeq576U/XJkBoc8Di5PElly2+vaz+guOJpZchdDLEsEhMea2y/4vWRkZGRkZGT6MlY3vkabsWydcKkgi1IyMmOQwajx8uQnA/I4uBwZi1lyIy2WDRQQysjIyMjIyAwPY3Xja7SRM8hGHlmUkpEZY8hqvIyMzNkYq1lyIymWnS0glJGRkZGRkRkexuLG12gjZ5CNPLIoJSMzxpDVeBkZmcFwIULUSHSPGUmx7GwBoYyMjIyMjMzwMFY3vkYTOYNs5JFFKRmZMYasxsvIyIwU5/KrGw5GIjjrHRDW+T3D/v4yMjIyMjIyp5CFlr7IGWQjiyxKyciMMWQ1XkZGZqQYz91j7CYtD10/hVd2qtg02icjIyMjIyMjc9kgZ5CNLLIoJSMzBpHV+EuLkSiVkhnfjMaYGO9+dc6eIO/VOinPNo/2qcjIyMjIyMhchozlOGk8I4tSMjJjEFmNvzS4GKVSMuOL0RwT49mvLhCOsrnayfO7Ggn7vaN9OjIyMjIyMjIyMsOELErJyIxhZCFqfDOeS6VkRobRHBPj2a9O7r4nIyMjIyMjI3NpIm/Vy8jIyIwA5yqVCoSjo3RmMqPFaI+JhF9dnkXf5+fjwa/ulKAmIyMjIyMjI3NpEghH8QYjl906Qc6UkpGRkRkBxnOplMzIMBbGxHj1q+vdAOKYXL4nIyMjIyMjcwlxuVt+yKKUjIyMzAgw1kqlZLP10WcsjInx7FeXENQ27K3nzdE+GRkZGRkZGRmZYeJyt/y49GW3/7+9O4+OqkzzOP7LVlkIlYQ1BMLiRAJBjE1gYs202BwyhCa2dusotDSNijJgoIUwrNrA2KfBlnZGFAURB5gzjALdDeOEEIyBEJawGAxLCHEhCKiBaEiKnST1zh82VwoSRZpUVcj3c06dQ9373Pu+eVKpenjqLgDgBb5yqlRNnUvHKs9p9QfH9Urux1r9wXEdqzynmjqXR8bHt3zlNXF5Li2CA5tMQ0r6tqH2wF0dvT0VAACAm8Lbl3fwBRwpBQCNxBdOlWru37z4Gl94TTR1TamRBgAA8F184fIO3kZTCgAaibdPlfq+b14eSurEf/A9zNuvics4nRMAAMD7fOHyDt5GUwoAGpm3/tPPNy++y1uvieZ+IU0AAABfcuXNXK78Irkp3B35ZqEpBQC3KL55wdU4nRMAAMC3NPfLO9CUAoBbFN+84EqczgkAAOB7fOXyDt5CUwoAbmHN/ZsXfIvTOQEAAHxXc2pEXYmmFADcwpr7Ny/4FqdzAgAAwNdwVVMAaAZCggLUIjiQhlQzdvl0zk5RoW7LOZ0TAAAA3sKRUgAANBOczgkAAABfQlMKAIBmgtM5AQAA4Et86vS92bNnq0ePHmrRooWioqKUkpKinTt3usVUVlZq+PDhstvtioyM1KhRo3TmzBm3mH379umee+5RSEiIYmNj9eKLL37v2EePHlVaWprCwsLUrl07TZ48WbW1tW4xeXl56tOnj4KDgxUXF6dly5Zds5/XXntNXbt2VUhIiJKTk7Vr164fnggAABoRp3MCAADAF/hUU6p79+5asGCB9u/fr61bt6pr164aNGiQKioqrJjhw4eruLhYOTk5yszMVH5+vkaPHm2tdzqdGjRokLp06aLCwkLNmzdPs2fP1uLFixsct66uTmlpabp06ZK2b9+u5cuXa9myZZo5c6YVU1ZWprS0NA0YMEBFRUWaMGGCnnzySW3YsMGKWblypTIyMjRr1izt2bNHiYmJSk1N1cmTJ29ypgAAAAAAAJo2P2OMz94D2ul0KiIiQu+//74GDhyokpISJSQkaPfu3erbt68kKTs7W0OGDNHx48cVExOjhQsX6tlnn1V5eblsNpskadq0aVq7dq0OHTpU7zjr16/Xfffdpy+++ELt27eXJC1atEhTp05VRUWFbDabpk6dqnXr1unAgQPWdsOGDVNVVZWys7MlScnJyerXr58WLFggSXK5XIqNjdX48eM1bdq0H/QzV1dXy26331jiAAC4RfE5iYbw2gAAoGG++jnpU0dKXenSpUtavHixIiIilJiYKEkqKChQZGSk1ZCSpJSUFPn7+1un+RUUFKh///5WQ0qSUlNTVVpaqlOnTtU7VkFBgXr37m01pC5v43Q6VVxcbMWkpKS4bZeamqqCggJrvoWFhW4x/v7+SklJsWLqc/HiRTmdTrcHAAAAAADArc7nmlKZmZkKDw9XSEiI/uM//kM5OTlq06aNJKm8vFzt2rVziw8MDFSrVq1UXl5uxVzZXJJkPb8cc7Xr2aahGKfTqfPnz+urr75SXV1dvTENjStJc+fOVUREhPWIjY1tMBYAAAAAAOBW4bWm1IoVKxQeHm49tmzZIknWNZu2b9+uwYMH65FHHrmlr8k0ffp0VVdXW49jx455e0oAAAAAAACNLtBbA99///1KTk62nnfs2FGS1KJFC8XFxSkuLk533323br/9dr311luaPn26oqOjr2lQ1dbWqrKyUtHR0ZKk6OhonThxwi3m8vPLMVeLjo6+5i55V2/T0H7tdrtCQ0MVEBCggICAemMaGleSgoODFRwc3OB6AAAAAACAW5HXjpRq2bKl1XyKi4tTaGhovXEul0sXL16UJDkcDlVVVamwsNBav3HjRrlcLqvB5XA4lJ+fr5qaGismJydH8fHxioqKqncMh8Oh/fv3uzW8cnJyZLfblZCQYMXk5ua6bZeTkyOHwyFJstlsSkpKcotxuVzKzc21YgAAAAAAAPANn7mm1NmzZzVjxgzt2LFDn332mQoLC/XEE0/o888/18MPPyxJ6tmzpwYPHqynnnpKu3bt0rZt2zRu3DgNGzZMMTExkqRHH31UNptNo0aNUnFxsVauXKn58+crIyOjwbEHDRqkhIQEjRgxQnv37tWGDRv03HPPKT093TqKacyYMTp8+LCmTJmiQ4cO6fXXX9eqVas0ceJEaz8ZGRl68803tXz5cpWUlGjs2LE6e/asHn/88UbMHAAAAAAAQNPjtdP3rhYQEKBDhw5p+fLl+uqrr9S6dWv169dPW7ZsUa9evay4FStWaNy4cRo4cKD8/f310EMP6ZVXXrHWR0RE6L333lN6erqSkpLUpk0bzZw5U6NHj7Zi8vLyNGDAAJWVlalr164KCAhQZmamxo4dK4fDoRYtWmjkyJF6/vnnrW26deumdevWaeLEiZo/f746deqkJUuWKDU11YoZOnSoKioqNHPmTJWXl+uuu+5Sdnb2NRc/BwAAAAAAaO78jDHG25PwtKVLl2rOnDk6ePCggoKCvD0dN06nUxEREaqurpbdbvf2dAAA8Cl8TtZv9uzZeuedd3Ts2DHrkgK///3v3a7fWVlZqfHjx+v//u//rC/25s+fr/DwcCtm3759Sk9P1+7du9W2bVuNHz9eU6ZM+c6xjx49qrFjx2rTpk0KDw/XyJEjNXfuXAUGfvvdZ15enjIyMlRcXKzY2Fg999xzeuyxx9z289prr2nevHkqLy9XYmKiXn31Vf393//9deeA1wYAAA3z1c9Jnzl9z5OysrI0Z84cn2tIAQAA3Iju3btrwYIF2r9/v7Zu3aquXbtq0KBBqqiosGKGDx+u4uJi5eTkKDMzU/n5+W5HkjudTg0aNEhdunRRYWGh5s2bp9mzZ2vx4sUNjltXV6e0tDRdunRJ27dv1/Lly7Vs2TLNnDnTiikrK1NaWpp1h+UJEyboySef1IYNG6yYlStXKiMjQ7NmzdKePXuUmJio1NTUW/oOzAAAoJkeKeXLfLV7CQCAL+Bz8vpcztP777+vgQMHqqSkRAkJCdq9e7f69u0rScrOztaQIUN0/PhxxcTEaOHChXr22WdVXl4um80mSZo2bZrWrl2rQ4cO1TvO+vXrdd999+mLL76wLlewaNEiTZ06VRUVFbLZbJo6darWrVunAwcOWNsNGzZMVVVVys7OliQlJyerX79+WrBggaRvbhYTGxur8ePHa9q0aT/oZ+a1AQDAtXz1c7JZHikFAABwq7p06ZIWL16siIgIJSYmSpIKCgoUGRlpNaQkKSUlRf7+/tq5c6cV079/f6shJUmpqakqLS3VqVOn6h2roKBAvXv3drt+ZmpqqpxOp4qLi62YlJQUt+1SU1NVUFBgzbewsNAtxt/fXykpKVYMAAC4NfnMhc4BAABw4zIzMzVs2DCdO3dOHTp0UE5Ojtq0aSNJKi8vV7t27dziAwMD1apVK5WXl1sx3bp1c4u53GwqLy9XVFTUNWOWl5dfc0OXK7f5rhin06nz58/r1KlTqqurqzemoSO0JOnixYu6ePGi9dzpdDYYCwAAfBNHSgEAADQhK1asUHh4uPXYsmWLJFnXbNq+fbsGDx6sRx555Ja+JtPcuXMVERFhPWJjY709JQAA8APRlAIAAGhC7r//fhUVFVmPy6fktWjRQnFxcbr77rv11ltvKTAwUG+99ZYkKTo6+poGVW1trSorKxUdHW3FnDhxwi3m8vPLMVe7nm0airHb7QoNDVWbNm0UEBBQb0xD40rS9OnTVV1dbT2OHTvWYCwAAPBNNKUAAACakJYtWyouLs56hIaG1hvncrms09scDoeqqqpUWFhord+4caNcLpeSk5OtmPz8fNXU1FgxOTk5io+Pr/fUvcvb7N+/363hlZOTI7vdroSEBCsmNzfXbbucnBw5HA5Jks1mU1JSkluMy+VSbm6uFVOf4OBg2e12twcAAGhaaEoBAAA0YWfPntWMGTO0Y8cOffbZZyosLNQTTzyhzz//XA8//LAkqWfPnho8eLCeeuop7dq1S9u2bdO4ceM0bNgwxcTESJIeffRR2Ww2jRo1SsXFxVq5cqXmz5+vjIyMBsceNGiQEhISNGLECO3du1cbNmzQc889p/T0dAUHB0uSxowZo8OHD2vKlCk6dOiQXn/9da1atUoTJ0609pORkaE333xTy5cvV0lJicaOHauzZ8/q8ccfb8TMAQAAb+NC5wAAAE1YQECADh06pOXLl+urr75S69at1a9fP23ZskW9evWy4lasWKFx48Zp4MCB8vf310MPPaRXXnnFWh8REaH33ntP6enpSkpKUps2bTRz5kyNHj3aisnLy9OAAQNUVlamrl27KiAgQJmZmRo7dqwcDodatGihkSNH6vnnn7e26datm9atW6eJEydq/vz56tSpk5YsWaLU1FQrZujQoaqoqNDMmTNVXl6uu+66S9nZ2ddc/BwAANxa/IwxxtuTwLecTqciIiJUXV3NYegAAFyFz0nvWrp0qebMmaODBw8qKCjI29Nxw2sDAICG+ernJKfvAQAA4LpkZWVpzpw5PteQAgAATROn7wEAAOC6rF692ttTAAAAtxCOlAIAAAAAAIDH0ZQCAAAAAACAx9GUAgAAAAAAgMfRlAIAAAAAAIDH0ZQCAAAAAACAx9GUAgAAAAAAgMfRlAIAAAAAAIDHBXp7AgBuzIWaOtW5jAL8/RQSFODt6QAAAAAA8IPQlAKamJo6l8qrLyivtELHT51Tp6gw/SS+raIjQhQUwMGPAAAAAICmgaYU0MSUV1/QnKwSHT91/q9Lvtb2T7/SjCE9FdsqzKtzAwAAAADgenFYBdCEXKip++sRUufdlh8/dV75H1XoQk2dl2YGAAAAAMAPQ1MKaELqXEbHT52rd93RynOqcxkPzwgAAAAAgBtDUwpoQgL8/dQpqv5T9Dq3ClOAv5+HZwQAAAAAwI2hKQU0ISFBAfpJfFt1igp1W94pKlT9u7flLnwAAAAAgCaDC50DTUx0RIhmDOmp/I8qdLTynDq3ClP/7t/cfQ8AAAAAgKbCZ4+UGjNmjPz8/PTyyy+7La+srNTw4cNlt9sVGRmpUaNG6cyZM24x+/bt0z333KOQkBDFxsbqxRdf/N7xjh49qrS0NIWFhaldu3aaPHmyamtr3WLy8vLUp08fBQcHKy4uTsuWLbtmP6+99pq6du2qkJAQJScna9euXT/4Zwe+S1CAv2JbhemhpE76zcDb9VBSJ8W2ClNQgM/+OQMAAAAAcA2f/F/smjVrtGPHDsXExFyzbvjw4SouLlZOTo4yMzOVn5+v0aNHW+udTqcGDRqkLl26qLCwUPPmzdPs2bO1ePHiBserq6tTWlqaLl26pO3bt2v58uVatmyZZs6cacWUlZUpLS1NAwYMUFFRkSZMmKAnn3xSGzZssGJWrlypjIwMzZo1S3v27FFiYqJSU1N18uTJm5QZ4FshQQFqERzIKXsAAAAAgCbJzxjjU7fr+vzzz5WcnKwNGzYoLS1NEyZM0IQJEyRJJSUlSkhI0O7du9W3b19JUnZ2toYMGaLjx48rJiZGCxcu1LPPPqvy8nLZbDZJ0rRp07R27VodOnSo3jHXr1+v++67T1988YXat28vSVq0aJGmTp2qiooK2Ww2TZ06VevWrdOBAwes7YYNG6aqqiplZ2dLkpKTk9WvXz8tWLBAkuRyuRQbG6vx48dr2rRp1/XzO51ORUREqLq6Wna7/YcnEACAWxifk2gIrw0AABrmq5+TPnWklMvl0ogRIzR58mT16tXrmvUFBQWKjIy0GlKSlJKSIn9/f+3cudOK6d+/v9WQkqTU1FSVlpbq1KlT9Y5bUFCg3r17Ww2py9s4nU4VFxdbMSkpKW7bpaamqqCgQJJ06dIlFRYWusX4+/srJSXFiqnPxYsX5XQ63R4AAAAAAAC3Op9qSv3hD39QYGCgfvOb39S7vry8XO3atXNbFhgYqFatWqm8vNyKubK5JMl6fjmmvv1+3zYNxTidTp0/f15fffWV6urq6o1paFxJmjt3riIiIqxHbGxsg7EAAAAAAAC3Cq81pVasWKHw8HDrsXnzZs2fP1/Lli2Tn5+ft6blcdOnT1d1dbX1OHbsmLenBAAAAAAA0OgCvTXw/fffr+TkZOv56tWrdfLkSXXu3NlaVldXp0mTJunll1/WkSNHFB0dfc1Fw2tra1VZWano6GhJUnR0tE6cOOEWc/n55ZirRUdHX3OXvKu3aWi/drtdoaGhCggIUEBAQL0xDY0rScHBwQoODm5wPQAAAAAAwK3Ia0dKtWzZUnFxcdZj9OjR2rdvn4qKiqxHTEyMJk+ebN3hzuFwqKqqSoWFhdZ+Nm7cKJfLZTW4HA6H8vPzVVNTY8Xk5OQoPj5eUVFR9c7F4XBo//79bg2vnJwc2e12JSQkWDG5ublu2+Xk5MjhcEiSbDabkpKS3GJcLpdyc3OtGAAAAAAAAHzDZ64p1bp1a91xxx1uj6CgIEVHRys+Pl6S1LNnTw0ePFhPPfWUdu3apW3btmncuHEaNmyYYmJiJEmPPvqobDabRo0apeLiYq1cuVLz589XRkZGg2MPGjRICQkJGjFihPbu3asNGzboueeeU3p6unUU05gxY3T48GFNmTJFhw4d0uuvv65Vq1Zp4sSJ1n4yMjL05ptvavny5SopKdHYsWN19uxZPf74442YOQAAAAAAgKbHZ5pS12vFihXq0aOHBg4cqCFDhujHP/6xFi9ebK2PiIjQe++9p7KyMiUlJWnSpEmaOXOmRo8ebcXk5eXJz89PR44ckSQFBAQoMzNTAQEBcjgc+tWvfqVf//rXev75561tunXrpnXr1iknJ0eJiYl66aWXtGTJEqWmploxQ4cO1R//+EfNnDlTd911l4qKipSdnX3Nxc8BANKFmjqdvVirCzV13p4KAPgE3hcBAM2NnzHGeHsSnrZ06VLNmTNHBw8eVFBQkLen48bpdCoiIkLV1dWy2+3eng4A3HQ1dS6VV19QXmmFjp86p05RYfpJfFtFR4QoKKDJfVcCD+NzEg1pyq8N3hcBAI3NVz8nvXahc2/KysrSnDlzfK4hBQDNQXn1Bc3JKtHxU+f/uuRrbf/0K80Y0lOxrcK8OjcA8AbeFwEAzVWz/Opl9erVevjhh709DQBodi7U1P31SIDzbsuPnzqv/I8qOGUFQLPD+yIAoDlrlk0pAIB31LmMjp86V++6o5XnVOdqdmeUA2jmeF8EADRnNKUAAB4T4O+nTlH1n4rSuVWYAvz9PDwjAPAu3hcBAM0ZTSkAgMeEBAXoJ/Ft1Skq1G15p6hQ9e/eViFBAV6aGQB4B++LAIDmrFle6BwA4D3RESGaMaSn8j+q0NHKc+rcKkz9u39zlykAaI54XwQANFc0pQAAHhUU4K/YVmF6KKmT6lxGAf5+HAkAoFnjfREA0FzRlAIAeAX/4QIAd7wvAgCaG64pBQAAAAAAAI+jKQUAAAAAAACPoykFAAAAAAAAj6MpBQAAAAAAAI+jKQUAAAAAAACPoykFAAAAAAAAj6MpBQAAAAAAAI8L9PYE4M4YI0lyOp1engkAAL7n8ufj5c9L4DJqKAAAGuarNRRNKR9z+vRpSVJsbKyXZwIAgO/6+uuvFRER4e1pwIdQQwEA8P18rYbyM77WJmvmXC6XvvjiC7Vs2VJ+fn7enk6T43Q6FRsbq2PHjslut3t7Os0KufcO8u495N47qqur1blzZ506dUqRkZHeng58CDXU34b3NO8g795D7r2DvHuPr9ZQHCnlY/z9/dWpUydvT6PJs9vtvMl5Cbn3DvLuPeTeO/z9uSwm3FFD3Ry8p3kHefcecu8d5N17fK2G8q3ZAAAAAAAAoFmgKQUAAAAAAACPoymFW0pwcLBmzZql4OBgb0+l2SH33kHevYfcewd5BxoHf1veQd69h9x7B3n3Hl/NPRc6BwAAAAAAgMdxpBQAAAAAAAA8jqYUAAAAAAAAPI6mFAAAAAAAADyOphQ8Ij8/Xz/72c8UExMjPz8/rV271m29MUYzZ85Uhw4dFBoaqpSUFH388cduMZWVlRo+fLjsdrsiIyM1atQonTlz5jvHvXDhgtLT09W6dWuFh4froYce0okTJ9xijh49qrS0NIWFhaldu3aaPHmyamtr3WLy8vLUp08fBQcHKy4uTsuWLbvhXHjS3Llz1a9fP7Vs2VLt2rXTz3/+c5WWlrrF3KwcXe16fl/79u3TPffco5CQEMXGxurFF1+8Zj+rV69Wjx49FBISot69eysrK+sGs+FZCxcu1J133im73S673S6Hw6H169db68m7Z7zwwgvy8/PThAkTrGXkvnHMnj1bfn5+bo8ePXpY68k7cGOoobyDGso7qJ98A/WT51A/STKAB2RlZZlnn33W/OUvfzGSzJo1a9zWv/DCCyYiIsKsXbvW7N2719x///2mW7du5vz581bM4MGDTWJiotmxY4fZsmWLiYuLM7/85S+/c9wxY8aY2NhYk5ubaz744ANz9913m3/4h3+w1tfW1po77rjDpKSkmA8//NBkZWWZNm3amOnTp1sxhw8fNmFhYSYjI8McPHjQvPrqqyYgIMBkZ2ffnOQ0otTUVLN06VJz4MABU1RUZIYMGWI6d+5szpw5Y8XcjBzV5/t+X9XV1aZ9+/Zm+PDh5sCBA+btt982oaGh5o033rBitm3bZgICAsyLL75oDh48aJ577jkTFBRk9u/ffxOz1Djeffdds27dOvPRRx+Z0tJSM2PGDBMUFGQOHDhgjCHvnrB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      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Coefficients:\n",
      "               Feature Coefficient\n",
      "1      total_rooms_log  -45,381.84\n",
      "2   total_bedrooms_log   69,517.14\n",
      "3       population_log  -53,158.41\n",
      "4       households_log   31,694.94\n",
      "5        median_income   11,180.16\n",
      "6      median_income^2  108,382.39\n",
      "7      median_income^3  -54,775.23\n",
      "8            longitude  -73,239.73\n",
      "9             latitude  -79,178.20\n",
      "10  housing_median_age    9,489.76\n"
     ]
    },
    {
     "data": {
      "image/png": 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SJS1O614OHz6s0aNHa+fOnUpJSdGdd96pwYMHq1q1alZHc0sdO3ZU8eLFNX78+Fzb9uzZo8aNGyshIcE+wxDO8dBDD+nRRx/Vc889l+f26dOn67PPPuNmDRYxxmjUqFF69913lZqaKkny8fHRwIED9dZbb1mczr0xNq7rxx9/1Jtvvunw/j9s2DA1b97c6mi4BopSAHALoJjr2i7foSogIMDiJIDr2bVrl7Zt26bu3bvnuX337t2aO3euhg8f7uRk7i0xMVEeHh4Os6Ou9N1338nPz0/333+/U3PBUXp6ug4dOqSUlBRVrlxZBQsWtDoSfsfYADcGRSk4XVJSkqZNm6Z9+/ZJkqpUqaKnn35agYGBFifD2rVr9f7779vHpnLlyho0aJAaNWpkcTLAdZ05c0YHDhyQJFWsWFFFihSxOBGknPVy4uPjlZ2d7dBevXp1ixIBAADgzyhKwam2bt2qFi1ayM/PT3Xr1pWUswbLxYsXtXz5ct15550WJ3Rf//73v9W9e3e1bdtWDRs2lJSzYOOCBQs0ffp0dezY0eKE7o1iruu5cOGC+vTpo5kzZ9oLH56enurSpYs++OAD5c+f3+KE7mnbtm3q2rWr9u3bpz+f4thsNi4RA+Cy2rZte919582bdxOT4M8YG9cXHByc581lbDabfH19FRkZqW7dul111i6sw0IxcKp+/fqpdevWOnr0qObNm6d58+YpOjpaDz/8sF5++WWr47m1d955R2PGjNHs2bPVt29f9e3bV3PmzNHo0aO5Pt5iW7duVdmyZTV+/HglJiYqMTFR48aNU9myZRUVFWV1PLfVv39/rV27Vt9++62SkpKUlJSkhQsXau3atRowYIDV8dzW008/rfLly2vjxo06cuSIoqOj7V9HjhyxOp5b433eNTEuriMwMND+FRAQoFWrVmnr1q327du2bdOqVav4QMoCjI3rGzZsmDw8PNSqVSuNHDlSI0eOVKtWreTh4aFevXqpfPnyeuGFF/TZZ59ZHRV/wkwpOJWfn5+2b9+uihUrOrTv3btXderUsS8WCOfz8fHRnj177LeHvuzQoUOqWrWq0tLSLEqGRo0aKTIyUp999pny5cu5aWpmZqaeeeYZHTlyROvWrbM4oXsqUqSIvvnmm1zrraxZs0ZPPPGEzpw5Y00wN+fv76/t27fnOpbBOllZWerWrZsOHTqkTZs2WR0Hv2NcXNvgwYOVmJioKVOmyNPTU1LOmL344osKCAjQe++9Z3FC98XYuKZ27drpgQce0PPPP+/Q/sknn2j58uWaO3euPvjgA3366af65ZdfLEqJvDBTCk4VEBCgmJiYXO2xsbHy9/e3IBEuCwsL06pVq3K1r1y50n67aFhj69atGjx4sL0gJUn58uXTK6+84vApHZwrNTVVxYsXz9VerFgxCuwWatq0qXbu3Gl1DPwuLS1NjzzyiHbv3q3vvvvO6jj4HePi+j7//HMNHDjQXvSQci4R79+/vz7//HMLk4GxcU3ff/+9mjVrlqu9adOm+v777yVJLVu2ZNa0C8r3112AG6d9+/bq0aOH3n//fTVo0ECStGHDBg0aNEhPPvmkxenc24ABA9S3b1/t2LHDYWymT5+uiRMnWpzOvV0u5v55hiHFXGvVr19fw4cP18yZM+Xr6ytJunjxokaOHKn69etbnM59TZ06VV27dtXu3btVtWpVeXl5OWxv3bq1RcncU7NmzZSYmKi1a9de9S5vcD7GxfVlZmZq//79qlChgkP7/v37c93AAc7F2LimQoUK6dtvv1W/fv0c2r/99lsVKlRIUs56oJw7ux6KUnCq999/XzabTV26dFFmZqYkycvLSy+88IJGjx5tcTr39sILLygkJERjx47VnDlzJEmVKlXS7Nmz1aZNG4vTuTeKua5p4sSJatGihUqWLKkaNWpIknbu3ClfX1/7J3Jwvk2bNmnDhg15zv5goXPn27hxoz744AMVLVrU6ii4AuPi+rp3764ePXro8OHD9psDbd68WaNHj2ahZosxNq5p6NCheuGFF7RmzRqHG2otXbpUU6ZMkSStWLFC9913n5UxkQfWlIIlUlNTdfjwYUlS2bJluUsVcA3p6ekaNGiQpkyZkmcx18fHx+KE7is1NVWzZs3S/v37JeUUcjt16iQ/Pz+Lk7mviIgIPfzwwxo6dGiel1fCuT744AO98sor+uabb9SqVSur4+B3jIvry87O1vvvv6+JEycqLi5OklSiRAm99NJLGjBggMOlY3AuxsZ1bdiwQZMnT9aBAwckSRUqVFCfPn3sH+rCNVGUAoBbBMVc4K/5+/trx44dKlu2rNVR8LtZs2bpxRdf1Pz589WkSROr4+B3jMutIzk5WVLO5fxwLYwN8M9RlMJN17Zt2+vuO2/evJuYBH8WHBwsm812XX0TExNvchrA9S1atOi6+7J2kTW6du2qRo0a6ZlnnrE6Cq6wdOlSde/eXadPn7Y6Cq7AuAC4HaWlpSk9Pd2hjcKh62JNKdx0gYGBVkfAVUyYMMHqCLgKirmu6dFHH72ufqxdZJ3y5cvr1Vdf1fr161WtWrVcC5337dvXomTurWXLlpo/f77VMfAnjIvrKl269DU/OOQOYtZhbFxTamqqXnnlFc2ZM0cJCQm5tnNe5rqYKQWXtGHDBtWpU4e1clzQ6NGj9fzzz3O3npvs7yyU+cUXX9zEJMCtpXTp0lfdZrPZ+GMBwC3hz3c+zsjI0Pbt27Vs2TINGjRIQ4YMsSgZGBvX1KtXL61Zs0ZvvfWWOnfurA8//FAnTpzQJ598otGjR6tTp05WR8RVUJSCSwoICNCOHTtUpkwZq6PgTxgb10Ux1zVVq1ZNS5cuVVhYmNVRAJeQnp6u6OholS1bVvnyMWnfVTAut4YPP/xQW7du5QMpF8TYWKtUqVKaOXOm7r//fgUEBCgqKkqRkZH68ssv9fXXX2vp0qVWR8RVeFgdAMgLtVLXxdi4roceekgnTpywOgb+5OjRo8rIyLA6hlsyxnDMciGpqanq0aOH8ufPrypVqigmJkaS1KdPH40ePdridO6Lcbm1PPTQQ5o7d67VMZAHxsZaiYmJ9g/NAwIC7Ovh3nPPPVq3bp2V0fAXKEoBwG2CP76BHDNnzlS1atXk5+cnPz8/Va9eXV9++aXVsdzeq6++qp07d+qHH36Qr6+vvb1Zs2aaPXu2hcncG+Nya/nmm29UqFAhq2MgD4yNtcqUKaPo6GhJUsWKFTVnzhxJ0rfffsuyIy6OubkAAOC2MW7cOA0dOlS9e/dWw4YNJUnr16/X888/r7Nnz6pfv34WJ3RfCxYs0OzZs3X33Xc7LBJcpUoVHT582MJk7o1xcU21atVyGA9jjE6dOqUzZ87oo48+sjAZGBvX1L17d+3cuVP33XefhgwZokceeUSTJ09WRkaGxo0bZ3U8XANFKQAAcNv44IMP9PHHH6tLly72ttatW6tKlSoaMWIERSkLnTlzRsWKFcvVfuHChWveyQo3F+Pimtq0aeOw/z08PFS0aFHdf//9qlixooXJwNi4pivf35s1a6b9+/dr27ZtioyMVPXq1S1Mhr9CUQouiZMgAMD/Ii4uTg0aNMjV3qBBA8XFxVmQCJfVqVNHS5YsUZ8+fST98V4/depU1a9f38pobo1xcU0jRoywOgKugrG5NYSHhys8PDxXOzegcT0UpeCSWBvHdTVq1Eh+fn5Wx0AeKOYCUmRkpObMmaPXXnvNoX327NkqV66cRakgSaNGjdJDDz2kvXv3KjMzUxMnTtTevXu1ceNGrV271up4botxcU2enp6Ki4vLNYstISFBxYoVU1ZWlkXJwNjc2rgBjeuhKAWnunjxoowxyp8/vyTp2LFjmj9/vipXrqzmzZvb+50/f96qiG4rKipKXl5eqlatmiRp4cKF+uKLL1S5cmWNGDFC3t7eksTtVF0YxVzrJSUl5VpM85NPPlHx4sWtCeSGRo4cqfbt22vdunX2NaU2bNigVatW2Rc9hTXuuece7dixQ6NHj1a1atW0fPly3Xnnndq0aZP9vQfOx7i4pqu9p1+6dMl+TgZrMDbAjWUz/BUDJ2revLnatm2r559/XklJSapYsaK8vLx09uxZjRs3Ti+88ILVEd3WXXfdpSFDhqhdu3Y6cuSIqlSposcee0w///yzWrVqpQkTJlgdEXAp//d//6eIiAi1b99ekvTEE09o7ty5CgkJ0dKlS1WjRg2LE7qvbdu2afz48dq3b58kqVKlShowYIBq1aplcTIAuLZJkyZJylkf56233lLBggXt27KysrRu3TodPXpU27dvtyqi22Jsbg/+/v7auXOnypQpY3UU/I6iFJyqSJEiWrt2rapUqaKpU6fqgw8+0Pbt2zV37lwNGzbM/gcEnC8wMFBRUVEqW7as/u///k+rV6/W999/rw0bNqhDhw6KjY21OqLbOn36tAYOHKhVq1YpPj4+1yd0TBO3RunSpTVr1iw1aNBAK1as0BNPPKHZs2drzpw5iomJ0fLly62OCLik+Ph4xcfHKzs726GdhWitxbi4htKlS0vKuZqgZMmS8vT0tG/z9vZWRESE3nzzTdWrV8+qiG6Lsbk9UJRyPVy+B6dKTU2Vv7+/JGn58uVq27atPDw8dPfdd+vYsWMWp3Nvxhj7iejKlSv18MMPS5LCwsJ09uxZK6O5vW7duikmJkZDhw5ViRIlWDvKRZw6dcq+SObixYv1xBNPqHnz5oqIiOCE1EJLly6Vp6enWrRo4dD+/fffKzs7Ww899JBFybBt2zZ17dpV+/bty1Vct9lsFNgtwri4lujoaElS48aNNW/ePAUHB1ucCJcxNsDNQVEKThUZGakFCxboscce0/fff2+/dWd8fLwCAgIsTufe6tSpo7ffflvNmjXT2rVr9fHHH0vKeQNmPRxrrV+/Xj/++KNq1qxpdRRcITg4WLGxsQoLC9OyZcv09ttvS8op8PJHnHWGDBmi0aNH52o3xmjIkCEUpSz09NNPq3z58po2bZqKFy9Ogd1FMC6uac2aNVZHwFUwNsCNRVEKTjVs2DB17NhR/fr1U9OmTe23Gl6+fDlrfVhswoQJ6tSpkxYsWKDXX39dkZGRkqRvvvkmz9urw3nCwsJYxNwFtW3bVh07dlS5cuWUkJBgL3Zs377d/vsD5zt48KAqV66cq71ixYo6dOiQBYlw2ZEjRzR37lx+P1wM4+I6+vfvr7feeksFChRQ//79r9l33LhxTkoFibG5nXADGtdDUQpO9fjjj+uee+5RXFycwyLATZs21WOPPWZhMlSvXl2//PJLrvb33nvP4Zp5ON+ECRM0ZMgQffLJJ4qIiLA6Dn43fvx4RUREKDY2VmPGjLEveBoXF6cXX3zR4nTuKzAwUEeOHMn1u3Lo0CEVKFDAmlCQlPNev3PnToofLoZxcR3bt2+336r+WotlM5vN+a4cm6ioKMbARa1atcq+Buuf18f7/PPPJUkdO3a0IhqugYXOAeSSkpKS60DO5ZXWCQ4OVmpqqjIzM5U/f355eXk5bE9MTLQoGeB6nnvuOW3atEnz589X2bJlJeUUpNq1a6e77rpLU6dOtTih+zp79qy6du2qunXrqmrVqrmOZa1bt7YomXtjXADcDkaOHKk333xTderUyXMN1vnz51uUDH+FohScKi0tTR988IHWrFmTZwU7KirKomSIjo5W79699cMPPygtLc3eboxhoVOLzZgx45rbu3bt6qQkWLRo0XX35Q85a5w7d04PPvigtm7dqpIlS0qSjh8/rkaNGmnevHkKCgqyNqAb+/bbb9W5c2clJyfn2sb7jHUYF+DvefrppzVx4kT7zZsuu3Dhgvr06WOfkQPnKlGihMaMGaPOnTtbHQV/E0UpOFWnTp20fPlyPf7443kupjl8+HCLkqFhw4Yyxuill17Kc2zuu+8+i5IBrsPDw8Phe5vN5rDe15W/N/whZx1jjFasWKGdO3fKz89P1atX17333mt1LLcXERGhhx9+WEOHDmU9DxfCuLimxx57LM9LxGw2m3x9fRUZGamOHTuqQoUKFqRzb56enoqLi1OxYsUc2s+ePauQkBBlZmZalMy9FS5cWFu2bLHPksatg6IUnCowMFBLly5Vw4YNrY6CPylYsKC2bdvGyY2LysrK0oIFC7Rv3z5JUpUqVdS6dWvW+7LQypUrNXjwYI0aNcp+04ZNmzbpjTfe0KhRo/TAAw9YnBBwLf7+/tqxYwd/MLgYxsU1devWTQsWLFBQUJBq164tKeeKgqSkJDVv3lw7d+7U0aNHtWrVKs6rnSQ5OVnGGAUHB+vgwYMqWrSofVtWVpa+/fZbDRkyRCdPnrQwpfsaPHiwChYsqKFDh1odBX8TC53Dqe64445cU13hGu666y7FxsZSlHJBhw4dUsuWLXXixAn7+Lz77rsKCwvTkiVL+EPCIi+//LKmTJmie+65x97WokUL5c+fXz179rQXEOF817PQKZyvbdu2WrNmDccsF8O4uKaQkBB17NhRkydPts/Szc7O1ksvvSR/f3/95z//0fPPP6/Bgwdr/fr1Fqd1D0FBQbLZbLLZbCpfvnyu7TabTSNHjrQgGaScZWI+/fRTrVy5UtWrV8+1Ph53RXRdzJSCU3333XeaNGmSpkyZovDwcKvj4AqHDx/W888/r6eeeirPhU6rV69uUTK0bNlSxhjNmjVLhQoVkiQlJCToqaeekoeHh5YsWWJxQvfk5+enn3/+WVWrVnVo37Vrl+rVq6eLFy9alMy9sdCp63rnnXc0YcIEtWrVStWqVcv1PtO3b1+Lkrk3xsU1FS1aVBs2bMhV/Pj111/VoEEDnT17Vr/88osaNWqkpKQka0K6mbVr18oYoyZNmmju3Ln2czJJ8vb2Vnh4uEJDQy1M6N4aN2581W02m02rV692Yhr8HRSl4FRnzpzRE088oXXr1nEXMRfz008/qWPHjjp69Ki97fJ6OSx0aq0CBQrop59+UrVq1Rzad+7cqYYNGyolJcWiZO7t3nvvla+vr7788kv7OiynT59Wly5dlJaWprVr11qc0D2x0KnrKl269FW32Ww2HTlyxIlpcBnj4pqCg4M1Y8aMXDfNWLRokbp27arffvtNBw8eVN26dfXbb79ZlNI9HTt2TGFhYbnWmQTwv+HyPTjVk08+qRMnTmjUqFF5LqYN6zz99NOqVauWvv76a8bGxfj4+Oj8+fO52lNSUuTt7W1BIkg5l4E99thjKlWqlMLCwiRJsbGxKleunBYsWGBtODeWnp6uBg0aWB0DeYiOjrY6AvLAuLimzp07q0ePHnrttdd01113SZJ+/vlnjRo1Sl26dJGUM3OnSpUqVsZ0S5ev9khNTVVMTIzS09MdtnN1AfD3MFMKTpU/f35t2rRJNWrUsDoK/qRAgQLauXOnIiMjrY6CP+nSpYuioqI0bdo01a1bV5K0efNmPfvss6pdu7amT59ubUA3dvkub/v375ckVapUSc2aNaOoayEWOr01XD795HfFtTAuriMrK0ujR4/W5MmTdfr0aUlS8eLF1adPHw0ePFienp6KiYmRh4eHSpYsaXFa93LmzBl1795d3333XZ7bubrAOlu3btWcOXPyLBbOmzfPolT4K8w5hFNVrFiRdVZcVJMmTbRz506rYyAPkyZNUtmyZVW/fn35+vrK19dXDRs2VGRkpCZOnGh1PLdms9nUvHlz9e3bV3379tUDDzzAH3MWS0tL07hx43TfffepT58+6t+/v8MXrDVz5kxVq1ZNfn5+8vPzU/Xq1fXll19aHcvtMS6ux9PTU6+//rri4uKUlJSkpKQkxcXF6bXXXrPfebdUqVIUpCzw8ssvKykpSZs3b5afn5+WLVumGTNmqFy5clq0aJHV8dzWf/7zHzVo0ED79u3T/PnzlZGRoT179mj16tUKDAy0Oh6ugcv34FSjR4/WgAED9M477+S5mGZAQIBFyfDII4+oX79++uWXX/Icmz+vaQDnCQoK0sKFC3Xw4EGHGTnManO+SZMmXXdfFge2xq5du1SzZk1J0u7dux22UTC01rhx4zR06FD17t3bfgv79evX6/nnn9fZs2fVr18/ixO6J8bF9XF+7FpWr16thQsXqk6dOvLw8FB4eLgeeOABBQQE6N1331WrVq2sjuiWRo0apfHjx6tXr17y9/fXxIkTVbp0aT333HMqUaKE1fFwDVy+B6e6vCDgn/8wYDFt611rsUbGBshxrQWBr8TiwEBupUuX1siRI+3r4Vw2Y8YMjRgxgrWNLMK4uKbTp09r4MCBWrVqleLj4/XnP9k4L7NOQECAdu3apYiICIWHh+urr75Sw4YNFR0drSpVqig1NdXqiG6pQIEC2rNnjyIiIlS4cGH98MMPqlatmvbt26cmTZooLi7O6oi4CmZKwanWrFljdQRcRXZ2ttURcIX+/fvrrbfeUoECBf7ykqNx48Y5KRX44wz438XFxeW5CH2DBg34Y8FCjItr6tatm2JiYjR06FCVKFGCmZ4upEKFCjpw4IAiIiJUo0YNffLJJ4qIiNCUKVOYkWOh4OBg+42B7rjjDu3evVvVqlVTUlIShUIXR1EKTnXfffdZHQG4JWzfvl0ZGRn2f8O1sTiwtdq2bavp06crICBAbdu2vWZfFjq1TmRkpObMmaPXXnvNoX327NkqV66cRanAuLim9evX68cff7RfjgzX8dJLL9kLtsOHD9eDDz6of//73/L29taMGTMsTue+7r33Xq1YsULVqlXTv/71L7300ktavXq1VqxYoaZNm1odD9dAUQpOl5SUpGnTpmnfvn2SpCpVqujpp59mAToXsHbtWr3//vv2salcubIGDRqkRo0aWZzM/Vw5q5AZhq5r5syZeu+993Tw4EFJUvny5TVo0CB17tzZ4mTuJTAw0F4Q5L3EdY0cOVLt27fXunXr7GsXbdiwQatWrdKcOXMsTue+GBfXFBYWluuSPbiGp556yv7v2rVr69ixY9q/f79KlSqlIkWKWJjMvU2ePFlpaWmSpNdff11eXl7auHGj2rVrpzfeeMPidLgW1pSCU23dulUtWrSQn5+f/db2P//8sy5evKjly5frzjvvtDih+/r3v/+t7t27q23btg4npfPnz9f06dPVsWNHixO6r6effloTJ06Uv7+/Q/uFCxfUp08fff755xYlc29XWxz4ww8/1Ntvv83iwC5uw4YNqlOnjnx8fKyO4la2bdum8ePH2z/8qFSpkgYMGKBatWpZnMy9MS6uZ/ny5Ro7dqz90jBY6+/cvZVlFYC/h6IUnKpRo0aKjIzUZ599pnz5cibqZWZm6plnntGRI0e0bt06ixO6r0qVKqlnz565/pAeN26cPvvsM/uJKpzP09NTcXFxKlasmEP72bNnFRISoszMTIuSuTcWB761BQQEaMeOHSpTpozVUQAgl+DgYKWmpiozM1P58+fPdVfkxMREi5K5p8aNG19XP5vNptWrV9/kNLgsOTnZfnfK5OTka/blLpaui8v34FRbt251KEhJUr58+fTKK6+oTp06FibDkSNH9Mgjj+Rqb926da51JuAcycnJMsbIGKPz58/L19fXvi0rK0tLly7NVaiC87A48K2Nz+Scb+nSpfL09FSLFi0c2r///ntlZ2froYcesiiZe2NcXNOECROsjoArsJSCawoODrZ/cBsUFJTn2p7c5d31UZSCUwUEBCgmJkYVK1Z0aI+Njc11aRKcKywsTKtWrVJkZKRD+8qVKxUWFmZRKvd2+c3VZrOpfPnyubbbbDaNHDnSgmSQWBwY+LuGDBmi0aNH52o3xmjIkCEUPyzCuLimrl27Wh0BcHmrV69WoUKFJFE4vJVRlIJTtW/fXj169ND7779vn2GwYcMGDRo0SE8++aTF6dzbgAED1LdvX+3YscNhbKZPn66JEydanM49rVmzRsYYNWnSRHPnzrW/6UqSt7e3wsPDFRoaamFC98biwMDfc/DgQVWuXDlXe8WKFXXo0CELEkFiXFxZVlaWFixY4HBzoNatW8vT09PiZIBruPLO7tzl/dZFUQpO9f7778tms6lLly72dXC8vLz0wgsv5PkpHZznhRdeUEhIiMaOHWv/g7pSpUqaPXu22rRpY3E693T5zTU6OlphYWHy8PCwOBGu1K5dO23evFnjx4/XggULJOX8zmzZsoXFgYE8BAYG6siRI7kWbT506JAKFChgTSgwLi7q0KFDatmypU6cOKEKFSpIkt59912FhYVpyZIlKlu2rMUJAevt2rXruvtWr179JibBP8FC57BEamqqDh8+LEkqW7as8ufPb3EiwPWlpqYqJiZG6enpDu28yQJ/HwudO99zzz2nTZs2af78+fY/qA8dOqR27drprrvu0tSpUy1O6J4YF9fUsmVLGWM0a9Ys+0zphIQEPfXUU/Lw8NCSJUssTghYz8PDQzabzb5u1LWwppTroigFyxw/flySVLJkSYuT4Erbtm1zmCbOjA/rnTlzRt27d9d3332X53beZK2TnZ2tQ4cOKT4+XtnZ2Q7b7r33XotS4Xr4+/tr586dFKWc6Ny5c3rwwQe1detW+3v/8ePH1ahRI82bN09BQUHWBnRTjItrKlCggH766SdVq1bNoX3nzp1q2LChUlJSLEoGuI5jx47Z/719+3YNHDhQgwYNUv369SVJmzZt0tixYzVmzBg9+uijFqXEX+HyPThVdna23n77bY0dO9b+Zurv768BAwbo9ddf5/IkC8XHx6tDhw764Ycf7CegSUlJaty4sf7zn/+oaNGi1gZ0Yy+//LKSkpK0efNm3X///Zo/f75Onz5t/12CNX766Sd17NhRx44dy3UnN+7y4vrOnz9vdQS3ExgYqI0bN2rFihXauXOn/Pz8VL16dQq4FmNcXJOPj0+ex6mUlBR5e3tbkAhwPeHh4fZ//+tf/9KkSZPUsmVLe1v16tUVFhamoUOHUpRyYcyUglO9+uqrmjZtmkaOHGlfGHj9+vUaMWKEnn32Wb3zzjsWJ3Rf7du315EjRzRz5kxVqlRJkrR371517dpVkZGR+vrrry1O6L5KlCihhQsXqm7dugoICNDWrVtVvnx5LVq0SGPGjNH69eutjuiWatasqfLly2vkyJEqUaJErmnjgYGBFiVzb6dPn9bAgQO1atUqxcfH5yoYUiwEcCvo0qWLoqKiNG3aNNWtW1eStHnzZj377LOqXbu2pk+fbm1AwMX4+fkpKirK/nfMZfv27dOdd96pixcvWpQMf4WiFJwqNDRUU6ZMUevWrR3aFy5cqBdffFEnTpywKBkCAwO1cuVK3XXXXQ7tW7ZsUfPmzZWUlGRNMCggIEC7du1SRESEwsPD9dVXX6lhw4aKjo5WlSpVlJqaanVEt1SgQAHt3LlTkZGRVkfBFR566CHFxMSod+/eeRYLuXGDtVatWmUvGP75ktfPP//colRgXFxPUlKSunbtqm+//VZeXl6SpIyMDLVp00ZffPEFl1UCf3LnnXeqatWqmjp1qn02YXp6up555hnt3r1bUVFRFifE1XD5HpwqMTFRFStWzNVesWJFJSYmWpAIl2VnZ9tPeq7k5eWV6wQVzlWhQgUdOHBAERERqlGjhj755BNFRERoypQpKlGihNXx3Fa9evV06NAhilIuZv369frxxx9Vs2ZNq6PgT0aOHKk333xTderUybNgCGswLq4pKChICxcu1KFDh+xrfVaqVIn3HOAqpkyZokceeUQlS5a03wRo165dstls+vbbby1Oh2thphScql69eqpXr54mTZrk0N6nTx/9/PPP+umnnyxKhjZt2igpKUlff/21QkNDJUknTpxQp06dFBwcrPnz51uc0H39+9//VmZmprp166Zt27bpwQcfVGJiory9vTV9+nS1b9/e6ohu48pbDx8+fFhvvPGGBg0apGrVquUq6nJXRGtUrlxZs2bN4iYNLqhEiRIaM2aMOnfubHUUXIFxcR39+/e/7r7jxo27iUmAW9OFCxc0a9Ys7d+/X1JOIbdjx44qUKCAxclwLRSl4FRr165Vq1atVKpUKYe7IsTGxmrp0qVq1KiRxQndV2xsrFq3bq09e/YoLCzM3la1alUtWrSIuyS6kNTUVO3fv1+lSpVSkSJFrI7jVq689XBerrwtMWsXWWP58uUaO3asfUYhXEfhwoW1ZcsWlS1b1uoouALj4joaN258Xf1sNptWr159k9MAgHNQlILTnTx5Uh9++KFDBfvFF1+0z86BdYwxWrlypcPYNGvWzOJUgOu48tbDf+XKO8LAeYKDg5WamqrMzEzlz58/1ww2LhW3zuDBg1WwYEENHTrU6ii4AuMC4Hbx5Zdf6pNPPtGRI0e0adMmhYeHa/z48SpTpgxrSrow1pSC02RkZOjBBx/UlClTuMuei8nIyJCfn5927NihBx54QA888IDVkdweU/hdE4Um1zdhwgSrI+Aq0tLS9Omnn2rlypWqXr16roIhxzJrMC4Abgcff/yxhg0bppdffllvv/22fcZ6cHCwJkyYQFHKhVGUgtN4eXk5rMcC1+Hl5aVSpUpxuZEL2b59+3X1Y0Faa3355ZeaMmWKoqOj7Z/ITZgwQaVLl+bkxyJdu3a1OgKuYteuXfYF6Hfv3u2wjWOZdRgXALeDDz74QJ999pkeffRRjR492t5ep04dDRw40MJk+Ctcvgen6tevn3x8fBwOFHAN06ZN07x58/Tll1+qUKFCVscBXN6Vn8i988472r17t8qUKaPp06drxowZWrNmjdUR3V5aWprS09Md2gICAixKAwAAbhY/Pz/t379f4eHh8vf3186dO1WmTBkdPHhQ1atX18WLF62OiKtgphScKjMzU59//rlWrlyp2rVr57oTAlPErTN58mQdOnRIoaGhCg8PzzU2UVFRFiUDXBOfyLmmCxcuaPDgwZozZ44SEhJybWdGKAAAt5/SpUtrx44duZZaWLZsmSpVqmRRKlwPilJwqt27d+vOO++UJP36668O25gibq1HH33U6gi4isaNG1/z94M78FgjOjpatWrVytXu4+OjCxcuWJAIkvTKK69ozZo1+vjjj9W5c2d9+OGHOnHihD755BNm6Vqgbdu2mj59ugICAtS2bdtr9p03b56TUoFxAXC76d+/v3r16qW0tDQZY7RlyxZ9/fXXevfddzV16lSr4+EaKErBqa73cpbjx48rNDRUHh4eNzkRLhs+fLjVEXAVl9f6uCwjI0M7duzQ7t27WT/HQnwi55q+/fZbzZw5U/fff7+6d++uRo0aKTIyUuHh4Zo1a5Y6depkdUS3EhgYaC+qBwYGWpwGlzEuAG43zzzzjPz8/PTGG28oNTVVHTt2VGhoqCZOnKgOHTpYHQ/XwJpScEkBAQHasWOHypQpY3UUwGWNGDFCKSkpev/9962O4pamTp2qESNGaOzYserRo4emTp2qw4cP2z+R4wTIGgULFtTevXtVqlQplSxZUvPmzVPdunUVHR2tatWqKSUlxeqI+AsbNmxQnTp15OPjY3UUXIFxAXCrSE1NVUpKiooVK2Z1FFwHZkrBJVErdY7g4ODrvmwyMTHxJqfB3/XUU0+pbt26FKUswidyrqlMmTKKjo5WqVKlVLFiRc2ZM0d169bVt99+q6CgIKvj4To89NBDfDDlghgXALeK/PnzK3/+/FbHwHWiKAW4sQkTJtj/nZCQoLffflstWrRQ/fr1JUmbNm3S999/r6FDh1qUENeyadMm+fr6Wh3DrXXq1EmdOnXiEzkX0r17d+3cuVP33XefhgwZokceeUSTJ09WRkYGN9O4RfDBlGtiXAC4soSEBA0bNkxr1qxRfHy8srOzHbbzAbvr4vI9uKQrb+MJ52jXrp0aN26s3r17O7RPnjxZK1eu1IIFC6wJhlyL0BpjFBcXp61bt2ro0KGsB2aRixcvyhhj/yTu2LFjmj9/vipXrqzmzZtbnA6XHTt2TNu2bVNkZKSqV69udRxcB84BXBPjAsCVtWzZUocOHVKPHj1UvHjxXFeDsA6r66IoBZfEiY/zFSxYUDt27FBkZKRD+6FDh1SzZk3WYbFQ9+7dHb738PBQ0aJF1aRJE4ofFmrevLnatm2r559/XklJSapQoYK8vb119uxZjRs3Ti+88ILVEYFbEucArolxAeDK/P39tX79etWoUcPqKPibuHwPLul61znCjVO4cGEtXLhQAwYMcGhfuHChChcubFEqSNIXX3xhdQTkISoqSuPHj5ckffPNNwoJCdH27ds1d+5cDRs2jKKUE02aNEk9e/aUr6+vJk2adM2+ffv2dVIqAADgLBUrVtTFixetjoH/AUUpuCQm8DnfyJEj9cwzz+iHH35QvXr1JEmbN2/WsmXL9Nlnn1mcDpK0detW7du3T5JUuXJl1a5d2+JE7i01NVX+/v6SpOXLl6tt27by8PDQ3XffrWPHjlmczr2MHz9enTp1kq+vr71QmBebzUZR6hbAB1OuiXEB4Mo++ugjDRkyRMOGDVPVqlXl5eXlsD0gIMCiZPgrFKXgkvbu3avQ0FCrY7iVbt26qVKlSpo0aZLmzZsnSapUqZLWr19vL1LBGsePH9eTTz6pDRs22O8elpSUpAYNGug///mPSpYsaW1ANxUZGakFCxboscce0/fff69+/fpJkuLj4znxcbLo6Og8/41bEx9MuSbGBYArCwoKUnJyspo0aeLQboyRzWZTVlaWRcnwV1hTCjfdnxdpvpbLxRAAf3jwwQeVlJSkGTNmqEKFCpKkAwcOqHv37goICNCyZcssTuievvnmG3Xs2FFZWVlq2rSpli9fLkl69913tW7dOn333XcWJwQAAHAPdevWVb58+fTSSy/ludD5fffdZ1Ey/BWKUrjp/rxI87Wwdo61Dh8+rC+++EJHjhzRhAkTVKxYMX333XcqVaqUqlSpYnU8t+Xn56eNGzeqVq1aDu3btm1To0aNlJqaalEynDp1SnFxcapRo4Y8PDwkSVu2bFFAQIAqVqxocTr30b9//+vuO27cuJuYBNdy+vRpDRw4UKtWrVJ8fHyumTd8im0NxgXA7SB//vzavn27/QNc3Dq4fA83HYWmW8PatWv10EMPqWHDhlq3bp3efvttFStWTDt37tS0adP0zTffWB3RbYWFhSkjIyNXe1ZWFpe5WiwkJEQhISEObXXr1rUojfvavn27w/dRUVHKzMy0n5j++uuv8vT0ZB02i3Xr1k0xMTEaOnSoSpQowRpFLoJxAXA7qFOnjmJjYylK3YIoSgGQJA0ZMkRvv/22+vfvb1+8WZKaNGmiyZMnW5gM7733nvr06aMPP/xQderUkZSz6PlLL72k999/3+J07qtx48bX/ONt9erVTkzj3tasWWP/97hx4+Tv768ZM2YoODhYkvTbb7+pe/fuatSokVURIWn9+vX68ccfVbNmTauj4AqMC4DbQZ8+ffTSSy9p0KBBqlatWq6FzqtXr25RMvwVLt+D033zzTeaM2eOYmJilJ6e7rAtKirKolQoWLCgfvnlF5UuXVr+/v7auXOnypQpo6NHj6pixYpKS0uzOqLbCg4OVmpqqjIzM5UvX85nCZf/XaBAAYe+iYmJVkR0S5cXNr8sIyNDO3bs0O7du9W1a1dNnDjRomTu7Y477tDy5ctzXXK8e/duNW/eXCdPnrQoGSpXrqxZs2bluhQZ1mJcANwOLi+jcCWbzcZC57cAZkrBqSZNmqTXX39d3bp108KFC9W9e3cdPnxYP//8s3r16mV1PLcWFBSkuLg4lS5d2qF9+/btuuOOOyxKBUmaMGGC1RGQh/Hjx+fZPmLECKWkpDg5DS5LTk7WmTNncrWfOXNG58+ftyARLpswYYKGDBmiTz75RBEREVbHwe8YFwC3A+6+e+tiphScqmLFiho+fLiefPJJh9k4w4YNU2JiIpeJWWjgwIHavHmz/vvf/6p8+fKKiorS6dOn1aVLF3Xp0kXDhw+3OiJwSzh06JDq1q3LrDWLdOnSRT/++KPGjh1rX99r8+bNGjRokBo1aqQZM2ZYnNB9XTnrM3/+/LkureB3xhqMCwB30qpVK02dOlUlSpSwOgp+x0wpOFVMTIwaNGggKeeOYpc/te7cubPuvvtuilIWGjVqlHr16qWwsDBlZWWpcuXKysrKUseOHfXGG29YHc/tZWVlacGCBdq3b58kqUqVKmrdurU8PT0tToY/27Rpk3x9fa2O4bamTJmigQMHqmPHjvYbBOTLl089evTQe++9Z3E698asT9fEuABwJ+vWrdPFixetjoErMFMKTlWmTBnNnTtXtWrVUp06dfTss8/queee0/Lly9WhQwc+jXMBMTEx2r17t1JSUlSrVi2VK1fO6khu79ChQ2rZsqVOnDhhv6PIgQMHFBYWpiVLlqhs2bIWJ3RPbdu2dfjeGKO4uDht3bpVQ4cOZXahxS5cuKDDhw9LksqWLZtr/TUAAOB+rrxaB66BmVJwqiZNmmjRokWqVauWunfvrn79+umbb77R1q1bc/2BB2uUKlVKYWFhksRtoV1E3759VbZsWf30008qVKiQJCkhIUFPPfWU+vbtqyVLllic0D0FBgY6fO/h4aEKFSrozTffVPPmzS1Khcvi4uIUFxene++9V35+fvaFTuEa0tLSct3sJCAgwKI0uIxxAQA4GzOl4FTZ2dnKzs6230HsP//5jzZu3Khy5crpueeek7e3t8UJ3du0adM0fvx4HTx4UJJUrlw5vfzyy3rmmWcsTubeChQooJ9++knVqlVzaN+5c6caNmzIotrAFRISEvTEE09ozZo1stlsOnjwoMqUKaOnn35awcHBGjt2rNUR3daFCxc0ePBgzZkzRwkJCbm2c2ckazAuANwJM6VcT+77JgI30fHjxx3WwOnQoYMmTZqk3r1769SpUxYmw7Bhw/TSSy/pkUce0X//+1/997//1SOPPKJ+/fpp2LBhVsdzaz4+PnneNSwlJYVCrgvYtm2b/v3vf+vf//63tm/fbnUct9evXz95eXkpJiZG+fPnt7e3b99ey5YtszAZXnnlFa1evVoff/yxfHx8NHXqVI0cOVKhoaGaOXOm1fHcFuMCALASM6XgVJ6enoqLi1OxYsUc2hMSElSsWDE+jbNQ0aJFNWnSJD355JMO7V9//bX69Omjs2fPWpQMXbp0UVRUlKZNm+ZwN7Fnn31WtWvX1vTp060N6Kbi4+PVoUMH/fDDDwoKCpIkJSUlqXHjxvrPf/6jokWLWhvQTYWEhOj7779XjRo1HD4NPXLkiKpXr87MQguVKlVKM2fO1P3336+AgABFRUUpMjJSX375pb7++mstXbrU6ohuiXEB4E6YKeV6mCkFp7ramh4pKSncrcpiGRkZqlOnTq722rVrKzMz04JEuGzSpEkqW7as6tevL19fX/n6+qpBgwaKjIzUxIkTrY7ntvr06aPz589rz549SkxMVGJionbv3q3k5GT17dvX6nhu68KFCw4zpC5LTEyUj4+PBYlwWWJiov2PgICAAPvNTe655x6tW7fOymhujXEB4E5ee+01+xqtcA0sdA6n6N+/v6SchbOHDh3q8AdDVlaWNm/erJo1a1qUDpLUuXNnffzxxxo3bpxD+6effqpOnTpZlAqSFBQUpIULF+rQoUPau3evJKly5cqKjIy0OJl7W7ZsmVauXKlKlSrZ2ypXrqwPP/yQhc4t1KhRI82cOVNvvfWWpJz3nezsbI0ZM0aNGze2OJ17K1OmjKKjo1WqVClVrFhRc+bMUd26dfXtt9/aZxvC+RgXALeDRYsW5dlus9nk6+uryMhIlS5dWq+++qqTk+GvUJSCU1xeZ8UYo19++cVhHRxvb2/VqFFDAwcOtCqe27pcLJRyDthTp07V8uXLdffdd0vKuUQsJiZGXbp0sSoifsci9K4nOztbXl5eudq9vLyUnZ1tQSJI0pgxY9S0aVNt3bpV6enpeuWVV+yz2TZs2GB1PLfWvXt37dy5U/fdd5+GDBmiRx55RJMnT1ZGRkauD0TgPIwLgNvBo48+KpvNpj+vTnS5zWaz6Z577tGCBQsUHBxsUUrkhTWl4FTdu3fXxIkTub2wi7jeWQM2m02rV6++yWlwNcOGDdO4cePUp08f1a9fX5K0adMmTZ48Wf369dObb75pcUL31KZNGyUlJenrr79WaGioJOnEiRPq1KmTgoODNX/+fIsTuq+kpCR9+OGH2rlzp1JSUnTnnXeqV69eKlGihNXRcIVjx45p27ZtioyMVPXq1a2Og98xLgBuRatWrdLrr7+ud955x74G65YtWzR06FC98cYbCgwM1HPPPad69epp2rRpFqfFlShKwTLHjx+XJJUsWdLiJPg7jh8/rtDQUHl4sCSds7AIvWuKjY1V69attWfPHoWFhUmSYmJiVK1aNS1atIhjm4XS0tK0a9cuxcfH55q11rp1a4tSAQCAm6Vq1ar69NNP1aBBA4f2DRs2qGfPntqzZ49Wrlypp59+WjExMRalRF64fA9OlZ2drbfffltjx4613wHJ399fAwYM0Ouvv06h4xZQuXJl7dixgztWOBGL0LumsLAwRUVFadWqVdq3b58kqVKlSmrWrJnFydzbsmXL1LlzZyUmJuY5hZ+7vDrXpEmT1LNnT/n6+mrSpEnX7MsNApyHcQFwuzl8+HCeV+MEBAToyJEjknKWv+DDXNfDTCk41auvvqpp06Zp5MiRatiwoSRp/fr1GjFihJ599lm98847FifEX+E2qs7Xp08feXl55VrbY+DAgbp48aI+/PBDi5Jh1apVWrVqVZ4zcj7//HOLUrm3cuXKqXnz5ho2bJiKFy9udRy3V7p0aW3dulWFCxdW6dKlr9rPZrPZ/2jAzce4ALjd3HPPPfL399fMmTNVtGhRSdKZM2fUpUsXXbhwQevWrdPKlSvVq1cvHThwwOK0uBJFKThVaGiopkyZkuvyiYULF+rFF1/UiRMnLEqG60VRyvn69OmjmTNnKiwsLM9F6K9cbJtFaZ1n5MiRevPNN1WnTh2VKFFCNpvNYTtrSlkjICBA27dvV9myZa2OAgAAnOTAgQNq06aNoqOj7csqxMbGqkyZMlq4cKHKly+vBQsW6Pz58+rcubPFaXElilJwKl9fX+3atUvly5d3aD9w4IBq1qypixcvWpQM14uilPOxIL1rKlGihMaMGcOJjYt5+umn1bBhQ/Xo0cPqKAAAwImys7O1fPly/frrr5KkChUq6IEHHmCJGBdHUQpOVa9ePdWrVy/X+gV9+vTRzz//rJ9++smiZLheFKWAHIULF9aWLVuYkeNiUlNT9a9//UtFixZVtWrVHGYSSqyP42z9+/e/7r7M9HQexgUA4CpY6BxONWbMGLVq1UorV650uLV9bGysli5danE6XI8/X6IEuKtnnnlGX331lYYOHWp1FFzh66+/1vLly+Xr66sffvjB4Zhls9koSjnZ9u3bHb6PiopSZmamKlSoIEn69ddf5enpqdq1a1sRz20xLgBuR6z1eWuiKAWnKl26tH799Vd9+OGH2r9/vySpbdu2evHFF7mL2C2CyZVwZ1fOLsjOztann36qlStXqnr16rlm5DC7wBqvv/66Ro4cqSFDhjBd3wWsWbPG/u9x48bJ399fM2bMUHBwsCTpt99+U/fu3dWoUSOrIrolxgXA7eav1vqE6+LyPTiVp6en4uLiVKxYMYf2hIQEFStWjFt13wJiY2MVGhoqT09Pq6MATsf6Xq6vUKFC+vnnn7ms0gXdcccdWr58uapUqeLQvnv3bjVv3lwnT560KJl7Y1wA3A5Y6/PWxUwpONXVaqApKSny9fV1chq0bdv2uvvOmzdPkux3swDc0ZWzC+CaunbtqtmzZ+u1116zOgr+JDk5WWfOnMnVfubMGZ0/f96CRJAYFwC3h/T0dDVo0MDqGPgfUJSCU1y+5MVms2nYsGHKnz+/fVtWVpY2b96smjVrWpTOfQUGBlodAQBuqKysLI0ZM0bff/89l1W6mMcee0zdu3fX2LFjVbduXUnS5s2bNWjQoL/1IQluLMYFwO2AtT5vXVy+B6e4fMnL2rVrVb9+fXl7e9u3eXt7KyIiQgMHDlS5cuWsiggAuA1c6xJLLqu0VmpqqgYOHKjPP/9cGRkZkqR8+fKpR48eeu+991SgQAGLE7onxgXA7eCll17SzJkzVb16dT6UusVQlIJTde/eXRMnTlRAQIDVUQAAgAUuXLigw4cPS5LKli1L0cNFMC4AbmV8KHXroigFwO6bb77RnDlzFBMTo/T0dIdtUVFRFqUCANxODh06pMOHD+vee++Vn5+fjDHcJckFMC4AACtwr2QAkqRJkyape/fuKl68uLZv3666deuqcOHCOnLkiB566CGr4wEAbnEJCQlq2rSpypcvr5YtWyouLk6S1KNHDw0YMMDidO6LcQEAWImiFABJ0kcffaRPP/1UH3zwgby9vfXKK69oxYoV6tu3r86dO2d1PADALa5fv37y8vJSTEyMww1P2rdvr2XLllmYzL0xLgBuVW3btlVycrL939f6guvi7nsAJEkxMTH226j6+fnZbwPduXNn3X333Zo8ebKV8QAAt7jly5fr+++/V8mSJR3ay5Urp2PHjlmUCowLgFtVYGCg/TJj7ip+66IoBUCSFBISosTERIWHh6tUqVL66aefVKNGDUVHR4ul5wAA/9SFCxccZuJclpiYKB8fHwsSQWJcANy6vvjiizz/jVsLl+8BkCQ1adJEixYtkpRzl8R+/frpgQceUPv27fXYY49ZnA4AcKtr1KiRZs6caf/eZrMpOztbY8aMueZdk3BzMS4AbgcXL15Uamqq/ftjx45pwoQJWr58uYWpcD24+x4ASVJ2drays7OVL1/OBMr//Oc/2rhxo8qVK6fnnntO3t7eFicEANzKdu/eraZNm+rOO+/U6tWr1bp1a+3Zs0eJiYnasGGDypYta3VEt8S4ALgdNG/eXG3bttXzzz+vpKQkVahQQd7e3jp79qzGjRunF154weqIuAqKUgAk5awpFRYWluv2z8YYxcbGqlSpUhYlAwDcLpKSkvThhx9q586dSklJ0Z133qlevXqpRIkSVkdza4wLgFtdkSJFtHbtWlWpUkVTp07VBx98oO3bt2vu3LkaNmyY9u3bZ3VEXAVFKQCSJE9PT8XFxalYsWIO7QkJCSpWrJiysrIsSgYAuF2kpaVp165dio+PV3Z2tsO21q1bW5QKjAuAW13+/Pm1f/9+lSpVSk888YSqVKmi4cOHKzY2VhUqVHC4tA+uhYXOAUjKmRH151lSkpSSkiJfX18LEgEAbifLli1T586dlZiYmOsGGjabjQ8/LMK4ALgdREZGasGCBXrsscf0/fffq1+/fpKk+Ph4BQQEWJwO18JMKcDN9e/fX5I0ceJEPfvssw534MnKytLmzZvl6empDRs2WBURAHAbKFeunJo3b65hw4apePHiVsfB7xgXALeDb775Rh07dlRWVpaaNm1qX+D83Xff1bp16/Tdd99ZnBBXQ1EKcHOX76yzdu1a1a9f32FBc29vb0VERGjgwIEqV66cVREBALeBgIAAbd++nYWzXQzjAuB2cerUKcXFxalGjRry8PCQJG3ZskUBAQGqWLGixelwNRSlAEiSunfvrokTJzK9FQBwUzz99NNq2LChevToYXUUXIFxAQBYiaIUgFyOHz8uSSpZsqTFSQAAt4vU1FT961//UtGiRVWtWjV5eXk5bO/bt69Fydwb4wLgdtC4ceM818e9bPXq1U5Mg7+Dhc4BSJKys7P19ttva+zYsUpJSZEk+fv7a8CAAXr99dftU2ABAPhffP3111q+fLl8fX31ww8/OPzxYLPZKH5YhHEBcDuoWbOmw/cZGRnasWOHdu/era5du1oTCteFmVIAJEmvvvqqpk2bppEjR6phw4aSpPXr12vEiBF69tln9c4771icEABwKwsJCVHfvn01ZMgQPuhwIYwLgNvZiBEjlJKSovfff9/qKLgKilIAJEmhoaGaMmWKWrdu7dC+cOFCvfjiizpx4oRFyQAAt4NChQrp559/ZkFtF8O4ALidHTp0SHXr1lViYqLVUXAVfBwCQJKUmJiY510pKlasyEEcAPCPde3aVbNnz7Y6Bv6EcQFwO9u0aZN8fX2tjoFrYE0pAJKkGjVqaPLkyZo0aZJD++TJk1WjRg2LUgEAbhdZWVkaM2aMvv/+e1WvXj3Xgtrjxo2zKJl7Y1wA3A7atm3r8L0xRnFxcdq6dauGDh1qUSpcDy7fAyBJWrt2rVq1aqVSpUqpfv36knI+WYiNjdXSpUvVqFEjixMCAG5ljRs3vuo2m83GnZEswrgAuB10797d4XsPDw8VLVpUTZo0UfPmzS1KhetBUQqAJCkmJkb58uXThx9+qP3790uSKlWqpBdffFGZmZkqVaqUxQkBAAAAALcTilIAJEmenp6Ki4tTsWLFHNoTEhJUrFgxZWVlWZQMAAAAAP7atm3btG/fPklSlSpVVKtWLYsT4a+wphQASTnXXeclJSWFxQEBAAAAuKz4+Hh16NBBP/zwg4KCgiRJSUlJaty4sf7zn/+oaNGi1gbEVVGUAtxc//79JeWsGzFs2DDlz5/fvi0rK0ubN29WzZo1LUoHAAAAANfWp08fnT9/Xnv27FGlSpUkSXv37lXXrl3Vt29fff311xYnxNVw+R7g5i4vcLp27VrVr19f3t7e9m3e3t6KiIjQwIEDVa5cOasiAgAAAMBVBQYGauXKlbrrrrsc2rds2aLmzZsrKSnJmmD4S8yUAtzcmjVrJOXcsWLixIkKCAiwOBEAAAAAXL/s7Gx5eXnlavfy8lJ2drYFiXC9mCkFAAAAAABuWW3atFFSUpK+/vprhYaGSpJOnDihTp06KTg4WPPnz7c4Ia6GohQAAAAAALhlxcbGqnXr1tqzZ4/CwsIkSTExMapWrZoWLVqkkiVLWpwQV0NRCgAAAAAA3NKMMVq1apX27dsnSapUqZKaNWtmcSr8FYpSAAAAAADglrZq1SqtWrVK8fHxudaR+vzzzy1Khb/CQucAAAAAAOCWNXLkSL355puqU6eOSpQoIZvNZnUkXCdmSgEAAAAAgFtWiRIlNGbMGHXu3NnqKPibPKwOAAAAAAAA8L9KT09XgwYNrI6B/wFFKQAAAAAAcMt65pln9NVXX1kdA/8DLt8DAAAAAAC3lP79+9v/nZ2drRkzZqh69eqqXr26vLy8HPqOGzfO2fFwnShKAQAAAACAW0rjxo2vq5/NZtPq1atvchr8ryhKAQAAAAAAwOlYUwoAAAAAAABOR1EKAAAAAAAATkdRCgAAAAAAAE5HUQoAAAAAAABOR1EKAAAAAAAATkdRCgAAAAAAAE5HUQoAAAAAAABOR1EKAAAAAAAATvf/PgpDhpb/ImAAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# For illustration, let's try doing a ridge model, and show cross-validation\n",
    "# We can also turn off VIF and PFI\n",
    "results_df, iteration_8 = dw.iterate_model(X1_train, X1_test, y1_train, y1_test,\n",
    "        transformers=['log', 'poly3'], scaler='stand', model='ridge', cross=True, cv_folds=5,\n",
    "        iteration='8', note='X1. Test size: 0.25, Pipeline: Log > Poly3 > Stand > Ridge. CV: 5',\n",
    "        plot=True, lowess=True, coef=True, perm=False, vif=False, decimal=2,\n",
    "        save=True, save_df=results_df, config=my_config)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-11 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-11 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-11 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-11 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-11 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-11 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-11 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-11 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-11 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-11 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-11 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-11 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-11 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-11 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-11 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-11 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-11 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-11 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-11 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-11 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-11 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-11 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-11 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-11 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-11 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-11 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-11 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-11 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-11 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-11 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-11 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-11 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-11 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-11 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-11 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-11 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-11 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-11 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-11 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-11 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-11 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-11 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-11\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;log_poly3&#x27;,\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;log&#x27;, LogTransformer(),\n",
       "                                                  [&#x27;total_rooms&#x27;,\n",
       "                                                   &#x27;total_bedrooms&#x27;,\n",
       "                                                   &#x27;population&#x27;,\n",
       "                                                   &#x27;households&#x27;]),\n",
       "                                                 (&#x27;poly3&#x27;,\n",
       "                                                  PolynomialFeatures(degree=3,\n",
       "                                                                     include_bias=False),\n",
       "                                                  [&#x27;median_income&#x27;])])),\n",
       "                (&#x27;stand&#x27;, StandardScaler()), (&#x27;ridge&#x27;, Ridge())])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-85\" type=\"checkbox\" ><label for=\"sk-estimator-id-85\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;log_poly3&#x27;,\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;log&#x27;, LogTransformer(),\n",
       "                                                  [&#x27;total_rooms&#x27;,\n",
       "                                                   &#x27;total_bedrooms&#x27;,\n",
       "                                                   &#x27;population&#x27;,\n",
       "                                                   &#x27;households&#x27;]),\n",
       "                                                 (&#x27;poly3&#x27;,\n",
       "                                                  PolynomialFeatures(degree=3,\n",
       "                                                                     include_bias=False),\n",
       "                                                  [&#x27;median_income&#x27;])])),\n",
       "                (&#x27;stand&#x27;, StandardScaler()), (&#x27;ridge&#x27;, Ridge())])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-86\" type=\"checkbox\" ><label for=\"sk-estimator-id-86\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;log_poly3: ColumnTransformer<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.compose.ColumnTransformer.html\">?<span>Documentation for log_poly3: ColumnTransformer</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>ColumnTransformer(force_int_remainder_cols=False, remainder=&#x27;passthrough&#x27;,\n",
       "                  transformers=[(&#x27;log&#x27;, LogTransformer(),\n",
       "                                 [&#x27;total_rooms&#x27;, &#x27;total_bedrooms&#x27;, &#x27;population&#x27;,\n",
       "                                  &#x27;households&#x27;]),\n",
       "                                (&#x27;poly3&#x27;,\n",
       "                                 PolynomialFeatures(degree=3,\n",
       "                                                    include_bias=False),\n",
       "                                 [&#x27;median_income&#x27;])])</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-87\" type=\"checkbox\" ><label for=\"sk-estimator-id-87\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">log</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;total_rooms&#x27;, &#x27;total_bedrooms&#x27;, &#x27;population&#x27;, &#x27;households&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-88\" type=\"checkbox\" ><label for=\"sk-estimator-id-88\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">LogTransformer</label><div class=\"sk-toggleable__content fitted\"><pre>LogTransformer()</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-89\" type=\"checkbox\" ><label for=\"sk-estimator-id-89\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">poly3</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;median_income&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-90\" type=\"checkbox\" ><label for=\"sk-estimator-id-90\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;PolynomialFeatures<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.PolynomialFeatures.html\">?<span>Documentation for PolynomialFeatures</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>PolynomialFeatures(degree=3, include_bias=False)</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-91\" type=\"checkbox\" ><label for=\"sk-estimator-id-91\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">remainder</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;longitude&#x27;, &#x27;latitude&#x27;, &#x27;housing_median_age&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-92\" type=\"checkbox\" ><label for=\"sk-estimator-id-92\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">passthrough</label><div class=\"sk-toggleable__content fitted\"><pre>passthrough</pre></div> </div></div></div></div></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-93\" type=\"checkbox\" ><label for=\"sk-estimator-id-93\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;StandardScaler<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.StandardScaler.html\">?<span>Documentation for StandardScaler</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>StandardScaler()</pre></div> </div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-94\" type=\"checkbox\" ><label for=\"sk-estimator-id-94\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;Ridge<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.linear_model.Ridge.html\">?<span>Documentation for Ridge</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>Ridge()</pre></div> </div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('log_poly3',\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder='passthrough',\n",
       "                                   transformers=[('log', LogTransformer(),\n",
       "                                                  ['total_rooms',\n",
       "                                                   'total_bedrooms',\n",
       "                                                   'population',\n",
       "                                                   'households']),\n",
       "                                                 ('poly3',\n",
       "                                                  PolynomialFeatures(degree=3,\n",
       "                                                                     include_bias=False),\n",
       "                                                  ['median_income'])])),\n",
       "                ('stand', StandardScaler()), ('ridge', Ridge())])"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the pipeline\n",
    "iteration_8"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Iteration 9: Ridge with Log, Poly3, Standard and Grid CV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "ITERATION 9 RESULTS\n",
      "\n",
      "Pipeline: log_poly3 -> stand -> ridge\n",
      "Note: X1. Test size: 0.25, Pipeline: Log > Poly3 > Stand > Ridge. Grid CV: 5\n",
      "May 30, 2024 09:17 AM UTC\n",
      "\n",
      "Grid Search:\n",
      "\n",
      "Fitting 5 folds for each of 8 candidates, totalling 40 fits\n",
      "[CV 1/5] END ................ridge__alpha=0.001;, score=0.640 total time=   0.0s\n",
      "[CV 2/5] END ................ridge__alpha=0.001;, score=0.615 total time=   0.0s\n",
      "[CV 3/5] END ................ridge__alpha=0.001;, score=0.640 total time=   0.0s\n",
      "[CV 4/5] END ................ridge__alpha=0.001;, score=0.642 total time=   0.0s\n",
      "[CV 5/5] END ................ridge__alpha=0.001;, score=0.648 total time=   0.0s\n",
      "[CV 1/5] END ..................ridge__alpha=0.1;, score=0.640 total time=   0.0s\n",
      "[CV 2/5] END ..................ridge__alpha=0.1;, score=0.615 total time=   0.0s\n",
      "[CV 3/5] END ..................ridge__alpha=0.1;, score=0.640 total time=   0.0s\n",
      "[CV 4/5] END ..................ridge__alpha=0.1;, score=0.642 total time=   0.0s\n",
      "[CV 5/5] END ..................ridge__alpha=0.1;, score=0.648 total time=   0.0s\n",
      "[CV 1/5] END ..................ridge__alpha=1.0;, score=0.640 total time=   0.0s\n",
      "[CV 2/5] END ..................ridge__alpha=1.0;, score=0.615 total time=   0.0s\n",
      "[CV 3/5] END ..................ridge__alpha=1.0;, score=0.640 total time=   0.0s\n",
      "[CV 4/5] END ..................ridge__alpha=1.0;, score=0.642 total time=   0.0s\n",
      "[CV 5/5] END ..................ridge__alpha=1.0;, score=0.648 total time=   0.0s\n",
      "[CV 1/5] END .................ridge__alpha=10.0;, score=0.640 total time=   0.0s\n",
      "[CV 2/5] END .................ridge__alpha=10.0;, score=0.615 total time=   0.0s\n",
      "[CV 3/5] END .................ridge__alpha=10.0;, score=0.640 total time=   0.0s\n",
      "[CV 4/5] END .................ridge__alpha=10.0;, score=0.642 total time=   0.0s\n",
      "[CV 5/5] END .................ridge__alpha=10.0;, score=0.646 total time=   0.0s\n",
      "[CV 1/5] END ................ridge__alpha=100.0;, score=0.636 total time=   0.0s\n",
      "[CV 2/5] END ................ridge__alpha=100.0;, score=0.614 total time=   0.1s\n",
      "[CV 3/5] END ................ridge__alpha=100.0;, score=0.636 total time=   0.0s\n",
      "[CV 4/5] END ................ridge__alpha=100.0;, score=0.638 total time=   0.0s\n",
      "[CV 5/5] END ................ridge__alpha=100.0;, score=0.639 total time=   0.0s\n",
      "[CV 1/5] END ...............ridge__alpha=1000.0;, score=0.580 total time=   0.0s\n",
      "[CV 2/5] END ...............ridge__alpha=1000.0;, score=0.563 total time=   0.0s\n",
      "[CV 3/5] END ...............ridge__alpha=1000.0;, score=0.582 total time=   0.0s\n",
      "[CV 4/5] END ...............ridge__alpha=1000.0;, score=0.581 total time=   0.0s\n",
      "[CV 5/5] END ...............ridge__alpha=1000.0;, score=0.581 total time=   0.0s\n",
      "[CV 1/5] END ..............ridge__alpha=10000.0;, score=0.438 total time=   0.0s\n",
      "[CV 2/5] END ..............ridge__alpha=10000.0;, score=0.422 total time=   0.0s\n",
      "[CV 3/5] END ..............ridge__alpha=10000.0;, score=0.439 total time=   0.0s\n",
      "[CV 4/5] END ..............ridge__alpha=10000.0;, score=0.435 total time=   0.0s\n",
      "[CV 5/5] END ..............ridge__alpha=10000.0;, score=0.447 total time=   0.0s\n",
      "[CV 1/5] END .............ridge__alpha=100000.0;, score=0.180 total time=   0.0s\n",
      "[CV 2/5] END .............ridge__alpha=100000.0;, score=0.173 total time=   0.0s\n",
      "[CV 3/5] END .............ridge__alpha=100000.0;, score=0.177 total time=   0.0s\n",
      "[CV 4/5] END .............ridge__alpha=100000.0;, score=0.181 total time=   0.0s\n",
      "[CV 5/5] END .............ridge__alpha=100000.0;, score=0.196 total time=   0.0s\n",
      "\n",
      "Best Grid mean score (r2): 0.64\n",
      "Best Grid parameters: ridge__alpha: 1.0\n",
      "\n",
      "Predictions:\n",
      "                          Train            Test\n",
      "MSE:            3,288,332,850.84 3,283,356,079.58\n",
      "RMSE:                 57,343.99       57,300.58\n",
      "MAE:                  42,229.62       42,182.13\n",
      "R^2 Score:                 0.64            0.65\n",
      "\n",
      "Permutation Feature Importance:\n",
      "           Feature Importance Mean Importance Std\n",
      "          latitude            1.38           0.01\n",
      "         longitude            1.17           0.01\n",
      "    total_bedrooms            1.06           0.01\n",
      "     median_income            1.04           0.01\n",
      "        population            0.62           0.01\n",
      "       total_rooms            0.46           0.01\n",
      "        households            0.22           0.00\n",
      "housing_median_age            0.02           0.00\n",
      "\n",
      "Variance Inflation Factor:\n",
      "          Features   VIF Multicollinearity\n",
      "    total_bedrooms 32.40              High\n",
      "        households 30.01              High\n",
      "       total_rooms 13.80              High\n",
      "          latitude  8.74          Moderate\n",
      "         longitude  8.43          Moderate\n",
      "        population  6.75          Moderate\n",
      "     median_income  1.83               Low\n",
      "housing_median_age  1.30               Low\n",
      "\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Coefficients:\n",
      "               Feature Coefficient\n",
      "1      total_rooms_log  -45,381.84\n",
      "2   total_bedrooms_log   69,517.14\n",
      "3       population_log  -53,158.41\n",
      "4       households_log   31,694.94\n",
      "5        median_income   11,180.16\n",
      "6      median_income^2  108,382.39\n",
      "7      median_income^3  -54,775.23\n",
      "8            longitude  -73,239.73\n",
      "9             latitude  -79,178.20\n",
      "10  housing_median_age    9,489.76\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Instead of just the cross-validation, let's try a grid search of Ridge hyper-parameters\n",
    "results_df, iteration_9, grid_9 = dw.iterate_model(X1_train, X1_test, y1_train, y1_test,\n",
    "        transformers=['log', 'poly3'], scaler='stand', model='ridge',\n",
    "        grid=True, grid_params='ridge', grid_cv='kfold_5', grid_verbose=4,\n",
    "        iteration='9', note='X1. Test size: 0.25, Pipeline: Log > Poly3 > Stand > Ridge. Grid CV: 5',\n",
    "        plot=True, lowess=True, coef=True, perm=True, vif=True, decimal=2,\n",
    "        save=True, save_df=results_df, config=my_config)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-12 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-12 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-12 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-12 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-12 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-12 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-12 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-12 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-12 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-12 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-12 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-12 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-12 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-12 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-12 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-12 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-12 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-12 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-12 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-12 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-12 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-12 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-12 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-12 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-12 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-12 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-12 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-12 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-12 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-12 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-12 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-12 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-12 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-12 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-12 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-12 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-12 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-12 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-12 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-12 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-12 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-12 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-12\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>GridSearchCV(cv=KFold(n_splits=5, random_state=42, shuffle=True),\n",
       "             estimator=Pipeline(steps=[(&#x27;log_poly3&#x27;,\n",
       "                                        ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                                          remainder=&#x27;passthrough&#x27;,\n",
       "                                                          transformers=[(&#x27;log&#x27;,\n",
       "                                                                         LogTransformer(),\n",
       "                                                                         [&#x27;total_rooms&#x27;,\n",
       "                                                                          &#x27;total_bedrooms&#x27;,\n",
       "                                                                          &#x27;population&#x27;,\n",
       "                                                                          &#x27;households&#x27;]),\n",
       "                                                                        (&#x27;poly3&#x27;,\n",
       "                                                                         PolynomialFeatures(degree=3,\n",
       "                                                                                            include_bias=False),\n",
       "                                                                         [&#x27;median_income&#x27;])])),\n",
       "                                       (&#x27;stand&#x27;, StandardScaler()),\n",
       "                                       (&#x27;ridge&#x27;, Ridge())]),\n",
       "             param_grid={&#x27;ridge__alpha&#x27;: array([1.e-03, 1.e-01, 1.e+00, 1.e+01, 1.e+02, 1.e+03, 1.e+04, 1.e+05])},\n",
       "             scoring=&#x27;r2&#x27;, verbose=4)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-95\" type=\"checkbox\" ><label for=\"sk-estimator-id-95\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;GridSearchCV<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.model_selection.GridSearchCV.html\">?<span>Documentation for GridSearchCV</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>GridSearchCV(cv=KFold(n_splits=5, random_state=42, shuffle=True),\n",
       "             estimator=Pipeline(steps=[(&#x27;log_poly3&#x27;,\n",
       "                                        ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                                          remainder=&#x27;passthrough&#x27;,\n",
       "                                                          transformers=[(&#x27;log&#x27;,\n",
       "                                                                         LogTransformer(),\n",
       "                                                                         [&#x27;total_rooms&#x27;,\n",
       "                                                                          &#x27;total_bedrooms&#x27;,\n",
       "                                                                          &#x27;population&#x27;,\n",
       "                                                                          &#x27;households&#x27;]),\n",
       "                                                                        (&#x27;poly3&#x27;,\n",
       "                                                                         PolynomialFeatures(degree=3,\n",
       "                                                                                            include_bias=False),\n",
       "                                                                         [&#x27;median_income&#x27;])])),\n",
       "                                       (&#x27;stand&#x27;, StandardScaler()),\n",
       "                                       (&#x27;ridge&#x27;, Ridge())]),\n",
       "             param_grid={&#x27;ridge__alpha&#x27;: array([1.e-03, 1.e-01, 1.e+00, 1.e+01, 1.e+02, 1.e+03, 1.e+04, 1.e+05])},\n",
       "             scoring=&#x27;r2&#x27;, verbose=4)</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-96\" type=\"checkbox\" ><label for=\"sk-estimator-id-96\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">best_estimator_: Pipeline</label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;log_poly3&#x27;,\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;log&#x27;, LogTransformer(),\n",
       "                                                  [&#x27;total_rooms&#x27;,\n",
       "                                                   &#x27;total_bedrooms&#x27;,\n",
       "                                                   &#x27;population&#x27;,\n",
       "                                                   &#x27;households&#x27;]),\n",
       "                                                 (&#x27;poly3&#x27;,\n",
       "                                                  PolynomialFeatures(degree=3,\n",
       "                                                                     include_bias=False),\n",
       "                                                  [&#x27;median_income&#x27;])])),\n",
       "                (&#x27;stand&#x27;, StandardScaler()), (&#x27;ridge&#x27;, Ridge())])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-97\" type=\"checkbox\" ><label for=\"sk-estimator-id-97\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;log_poly3: ColumnTransformer<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.compose.ColumnTransformer.html\">?<span>Documentation for log_poly3: ColumnTransformer</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>ColumnTransformer(force_int_remainder_cols=False, remainder=&#x27;passthrough&#x27;,\n",
       "                  transformers=[(&#x27;log&#x27;, LogTransformer(),\n",
       "                                 [&#x27;total_rooms&#x27;, &#x27;total_bedrooms&#x27;, &#x27;population&#x27;,\n",
       "                                  &#x27;households&#x27;]),\n",
       "                                (&#x27;poly3&#x27;,\n",
       "                                 PolynomialFeatures(degree=3,\n",
       "                                                    include_bias=False),\n",
       "                                 [&#x27;median_income&#x27;])])</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-98\" type=\"checkbox\" ><label for=\"sk-estimator-id-98\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">log</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;total_rooms&#x27;, &#x27;total_bedrooms&#x27;, &#x27;population&#x27;, &#x27;households&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-99\" type=\"checkbox\" ><label for=\"sk-estimator-id-99\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">LogTransformer</label><div class=\"sk-toggleable__content fitted\"><pre>LogTransformer()</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-100\" type=\"checkbox\" ><label for=\"sk-estimator-id-100\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">poly3</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;median_income&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-101\" type=\"checkbox\" ><label for=\"sk-estimator-id-101\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;PolynomialFeatures<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.PolynomialFeatures.html\">?<span>Documentation for PolynomialFeatures</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>PolynomialFeatures(degree=3, include_bias=False)</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-102\" type=\"checkbox\" ><label for=\"sk-estimator-id-102\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">remainder</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;longitude&#x27;, &#x27;latitude&#x27;, &#x27;housing_median_age&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-103\" type=\"checkbox\" ><label for=\"sk-estimator-id-103\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">passthrough</label><div class=\"sk-toggleable__content fitted\"><pre>passthrough</pre></div> </div></div></div></div></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-104\" type=\"checkbox\" ><label for=\"sk-estimator-id-104\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;StandardScaler<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.StandardScaler.html\">?<span>Documentation for StandardScaler</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>StandardScaler()</pre></div> </div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-105\" type=\"checkbox\" ><label for=\"sk-estimator-id-105\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;Ridge<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.linear_model.Ridge.html\">?<span>Documentation for Ridge</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>Ridge()</pre></div> </div></div></div></div></div></div></div></div></div></div></div>"
      ],
      "text/plain": [
       "GridSearchCV(cv=KFold(n_splits=5, random_state=42, shuffle=True),\n",
       "             estimator=Pipeline(steps=[('log_poly3',\n",
       "                                        ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                                          remainder='passthrough',\n",
       "                                                          transformers=[('log',\n",
       "                                                                         LogTransformer(),\n",
       "                                                                         ['total_rooms',\n",
       "                                                                          'total_bedrooms',\n",
       "                                                                          'population',\n",
       "                                                                          'households']),\n",
       "                                                                        ('poly3',\n",
       "                                                                         PolynomialFeatures(degree=3,\n",
       "                                                                                            include_bias=False),\n",
       "                                                                         ['median_income'])])),\n",
       "                                       ('stand', StandardScaler()),\n",
       "                                       ('ridge', Ridge())]),\n",
       "             param_grid={'ridge__alpha': array([1.e-03, 1.e-01, 1.e+00, 1.e+01, 1.e+02, 1.e+03, 1.e+04, 1.e+05])},\n",
       "             scoring='r2', verbose=4)"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the pipeline\n",
    "iteration_9"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Iteration 10: Decision Tree and Random Grid CV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "ITERATION 10 RESULTS\n",
      "\n",
      "Pipeline: tree_reg\n",
      "Note: X1. Test size: 0.25, Pipeline: Tree. Random Grid CV: 5\n",
      "May 30, 2024 09:17 AM UTC\n",
      "\n",
      "Randomized Grid Search:\n",
      "\n",
      "Fitting 5 folds for each of 10 candidates, totalling 50 fits\n",
      "[CV 1/5] END tree_reg__criterion=squared_error, tree_reg__max_depth=7, tree_reg__min_samples_leaf=4, tree_reg__min_samples_split=15;, score=0.620 total time=   0.1s\n",
      "[CV 2/5] END tree_reg__criterion=squared_error, tree_reg__max_depth=7, tree_reg__min_samples_leaf=4, tree_reg__min_samples_split=15;, score=0.614 total time=   0.0s\n",
      "[CV 3/5] END tree_reg__criterion=squared_error, tree_reg__max_depth=7, tree_reg__min_samples_leaf=4, tree_reg__min_samples_split=15;, score=0.649 total time=   0.0s\n",
      "[CV 4/5] END tree_reg__criterion=squared_error, tree_reg__max_depth=7, tree_reg__min_samples_leaf=4, tree_reg__min_samples_split=15;, score=0.658 total time=   0.0s\n",
      "[CV 5/5] END tree_reg__criterion=squared_error, tree_reg__max_depth=7, tree_reg__min_samples_leaf=4, tree_reg__min_samples_split=15;, score=0.656 total time=   0.0s\n",
      "[CV 1/5] END tree_reg__criterion=poisson, tree_reg__max_depth=5, tree_reg__min_samples_leaf=2, tree_reg__min_samples_split=10;, score=0.539 total time=   0.0s\n",
      "[CV 2/5] END tree_reg__criterion=poisson, tree_reg__max_depth=5, tree_reg__min_samples_leaf=2, tree_reg__min_samples_split=10;, score=0.528 total time=   0.0s\n",
      "[CV 3/5] END tree_reg__criterion=poisson, tree_reg__max_depth=5, tree_reg__min_samples_leaf=2, tree_reg__min_samples_split=10;, score=0.541 total time=   0.0s\n",
      "[CV 4/5] END tree_reg__criterion=poisson, tree_reg__max_depth=5, tree_reg__min_samples_leaf=2, tree_reg__min_samples_split=10;, score=0.550 total time=   0.0s\n",
      "[CV 5/5] END tree_reg__criterion=poisson, tree_reg__max_depth=5, tree_reg__min_samples_leaf=2, tree_reg__min_samples_split=10;, score=0.566 total time=   0.0s\n",
      "[CV 1/5] END tree_reg__criterion=poisson, tree_reg__max_depth=3, tree_reg__min_samples_leaf=4, tree_reg__min_samples_split=10;, score=0.448 total time=   0.0s\n",
      "[CV 2/5] END tree_reg__criterion=poisson, tree_reg__max_depth=3, tree_reg__min_samples_leaf=4, tree_reg__min_samples_split=10;, score=0.427 total time=   0.0s\n",
      "[CV 3/5] END tree_reg__criterion=poisson, tree_reg__max_depth=3, tree_reg__min_samples_leaf=4, tree_reg__min_samples_split=10;, score=0.456 total time=   0.0s\n",
      "[CV 4/5] END tree_reg__criterion=poisson, tree_reg__max_depth=3, tree_reg__min_samples_leaf=4, tree_reg__min_samples_split=10;, score=0.463 total time=   0.0s\n",
      "[CV 5/5] END tree_reg__criterion=poisson, tree_reg__max_depth=3, tree_reg__min_samples_leaf=4, tree_reg__min_samples_split=10;, score=0.474 total time=   0.0s\n",
      "[CV 1/5] END tree_reg__criterion=absolute_error, tree_reg__max_depth=3, tree_reg__min_samples_leaf=2, tree_reg__min_samples_split=15;, score=0.426 total time=   2.9s\n",
      "[CV 2/5] END tree_reg__criterion=absolute_error, tree_reg__max_depth=3, tree_reg__min_samples_leaf=2, tree_reg__min_samples_split=15;, score=0.396 total time=   2.8s\n",
      "[CV 3/5] END tree_reg__criterion=absolute_error, tree_reg__max_depth=3, tree_reg__min_samples_leaf=2, tree_reg__min_samples_split=15;, score=0.416 total time=   3.0s\n",
      "[CV 4/5] END tree_reg__criterion=absolute_error, tree_reg__max_depth=3, tree_reg__min_samples_leaf=2, tree_reg__min_samples_split=15;, score=0.426 total time=   3.0s\n",
      "[CV 5/5] END tree_reg__criterion=absolute_error, tree_reg__max_depth=3, tree_reg__min_samples_leaf=2, tree_reg__min_samples_split=15;, score=0.460 total time=   3.0s\n",
      "[CV 1/5] END tree_reg__criterion=squared_error, tree_reg__max_depth=3, tree_reg__min_samples_leaf=6, tree_reg__min_samples_split=15;, score=0.446 total time=   0.0s\n",
      "[CV 2/5] END tree_reg__criterion=squared_error, tree_reg__max_depth=3, tree_reg__min_samples_leaf=6, tree_reg__min_samples_split=15;, score=0.428 total time=   0.0s\n",
      "[CV 3/5] END tree_reg__criterion=squared_error, tree_reg__max_depth=3, tree_reg__min_samples_leaf=6, tree_reg__min_samples_split=15;, score=0.453 total time=   0.0s\n",
      "[CV 4/5] END tree_reg__criterion=squared_error, tree_reg__max_depth=3, tree_reg__min_samples_leaf=6, tree_reg__min_samples_split=15;, score=0.446 total time=   0.0s\n",
      "[CV 5/5] END tree_reg__criterion=squared_error, tree_reg__max_depth=3, tree_reg__min_samples_leaf=6, tree_reg__min_samples_split=15;, score=0.474 total time=   0.0s\n",
      "[CV 1/5] END tree_reg__criterion=squared_error, tree_reg__max_depth=5, tree_reg__min_samples_leaf=4, tree_reg__min_samples_split=10;, score=0.534 total time=   0.0s\n",
      "[CV 2/5] END tree_reg__criterion=squared_error, tree_reg__max_depth=5, tree_reg__min_samples_leaf=4, tree_reg__min_samples_split=10;, score=0.529 total time=   0.0s\n",
      "[CV 3/5] END tree_reg__criterion=squared_error, tree_reg__max_depth=5, tree_reg__min_samples_leaf=4, tree_reg__min_samples_split=10;, score=0.551 total time=   0.0s\n",
      "[CV 4/5] END tree_reg__criterion=squared_error, tree_reg__max_depth=5, tree_reg__min_samples_leaf=4, tree_reg__min_samples_split=10;, score=0.555 total time=   0.0s\n",
      "[CV 5/5] END tree_reg__criterion=squared_error, tree_reg__max_depth=5, tree_reg__min_samples_leaf=4, tree_reg__min_samples_split=10;, score=0.576 total time=   0.0s\n",
      "[CV 1/5] END tree_reg__criterion=friedman_mse, tree_reg__max_depth=3, tree_reg__min_samples_leaf=4, tree_reg__min_samples_split=5;, score=0.446 total time=   0.0s\n",
      "[CV 2/5] END tree_reg__criterion=friedman_mse, tree_reg__max_depth=3, tree_reg__min_samples_leaf=4, tree_reg__min_samples_split=5;, score=0.428 total time=   0.0s\n",
      "[CV 3/5] END tree_reg__criterion=friedman_mse, tree_reg__max_depth=3, tree_reg__min_samples_leaf=4, tree_reg__min_samples_split=5;, score=0.453 total time=   0.0s\n",
      "[CV 4/5] END tree_reg__criterion=friedman_mse, tree_reg__max_depth=3, tree_reg__min_samples_leaf=4, tree_reg__min_samples_split=5;, score=0.446 total time=   0.0s\n",
      "[CV 5/5] END tree_reg__criterion=friedman_mse, tree_reg__max_depth=3, tree_reg__min_samples_leaf=4, tree_reg__min_samples_split=5;, score=0.474 total time=   0.0s\n",
      "[CV 1/5] END tree_reg__criterion=friedman_mse, tree_reg__max_depth=7, tree_reg__min_samples_leaf=2, tree_reg__min_samples_split=5;, score=0.621 total time=   0.1s\n",
      "[CV 2/5] END tree_reg__criterion=friedman_mse, tree_reg__max_depth=7, tree_reg__min_samples_leaf=2, tree_reg__min_samples_split=5;, score=0.613 total time=   0.1s\n",
      "[CV 3/5] END tree_reg__criterion=friedman_mse, tree_reg__max_depth=7, tree_reg__min_samples_leaf=2, tree_reg__min_samples_split=5;, score=0.647 total time=   0.1s\n",
      "[CV 4/5] END tree_reg__criterion=friedman_mse, tree_reg__max_depth=7, tree_reg__min_samples_leaf=2, tree_reg__min_samples_split=5;, score=0.658 total time=   0.1s\n",
      "[CV 5/5] END tree_reg__criterion=friedman_mse, tree_reg__max_depth=7, tree_reg__min_samples_leaf=2, tree_reg__min_samples_split=5;, score=0.654 total time=   0.1s\n",
      "[CV 1/5] END tree_reg__criterion=absolute_error, tree_reg__max_depth=5, tree_reg__min_samples_leaf=4, tree_reg__min_samples_split=15;, score=0.534 total time=   3.4s\n",
      "[CV 2/5] END tree_reg__criterion=absolute_error, tree_reg__max_depth=5, tree_reg__min_samples_leaf=4, tree_reg__min_samples_split=15;, score=0.484 total time=   3.5s\n",
      "[CV 3/5] END tree_reg__criterion=absolute_error, tree_reg__max_depth=5, tree_reg__min_samples_leaf=4, tree_reg__min_samples_split=15;, score=0.529 total time=   4.2s\n",
      "[CV 4/5] END tree_reg__criterion=absolute_error, tree_reg__max_depth=5, tree_reg__min_samples_leaf=4, tree_reg__min_samples_split=15;, score=0.548 total time=   3.6s\n",
      "[CV 5/5] END tree_reg__criterion=absolute_error, tree_reg__max_depth=5, tree_reg__min_samples_leaf=4, tree_reg__min_samples_split=15;, score=0.568 total time=   3.5s\n",
      "[CV 1/5] END tree_reg__criterion=poisson, tree_reg__max_depth=5, tree_reg__min_samples_leaf=2, tree_reg__min_samples_split=15;, score=0.539 total time=   0.0s\n",
      "[CV 2/5] END tree_reg__criterion=poisson, tree_reg__max_depth=5, tree_reg__min_samples_leaf=2, tree_reg__min_samples_split=15;, score=0.528 total time=   0.0s\n",
      "[CV 3/5] END tree_reg__criterion=poisson, tree_reg__max_depth=5, tree_reg__min_samples_leaf=2, tree_reg__min_samples_split=15;, score=0.541 total time=   0.0s\n",
      "[CV 4/5] END tree_reg__criterion=poisson, tree_reg__max_depth=5, tree_reg__min_samples_leaf=2, tree_reg__min_samples_split=15;, score=0.550 total time=   0.0s\n",
      "[CV 5/5] END tree_reg__criterion=poisson, tree_reg__max_depth=5, tree_reg__min_samples_leaf=2, tree_reg__min_samples_split=15;, score=0.566 total time=   0.0s\n",
      "\n",
      "Best Grid mean score (r2): 0.64\n",
      "Best Grid parameters: tree_reg__min_samples_split: 15, tree_reg__min_samples_leaf: 4, tree_reg__max_depth: 7, tree_reg__criterion: squared_error\n",
      "\n",
      "Predictions:\n",
      "                          Train            Test\n",
      "MSE:            2,944,707,111.06 3,340,337,711.85\n",
      "RMSE:                 54,265.16       57,795.65\n",
      "MAE:                  39,005.07       41,031.86\n",
      "R^2 Score:                 0.68            0.65\n",
      "\n",
      "Permutation Feature Importance:\n",
      "           Feature Importance Mean Importance Std\n",
      "          latitude            0.92           0.01\n",
      "         longitude            0.81           0.01\n",
      "     median_income            0.79           0.01\n",
      "housing_median_age            0.07           0.00\n",
      "    total_bedrooms            0.03           0.00\n",
      "        population            0.01           0.00\n",
      "       total_rooms            0.01           0.00\n",
      "        households            0.00           0.00\n",
      "\n",
      "Variance Inflation Factor:\n",
      "          Features   VIF Multicollinearity\n",
      "    total_bedrooms 32.40              High\n",
      "        households 30.01              High\n",
      "       total_rooms 13.80              High\n",
      "          latitude  8.74          Moderate\n",
      "         longitude  8.43          Moderate\n",
      "        population  6.75          Moderate\n",
      "     median_income  1.83               Low\n",
      "housing_median_age  1.30               Low\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Let's try a Decision Tree and do a Random Grid Search over a few hyper-parameters\n",
    "results_df, iteration_10, grid_10 = dw.iterate_model(X1_train, X1_test, y1_train, y1_test,\n",
    "        model='tree_reg',\n",
    "        grid=True, search_type='random', grid_params='tree_reg', grid_cv='kfold_5', grid_verbose=4,\n",
    "        iteration='10', note='X1. Test size: 0.25, Pipeline: Tree. Random Grid CV: 5',\n",
    "        plot=True, lowess=True, coef=True, perm=True, vif=True, decimal=2,\n",
    "        save=True, save_df=results_df, config=my_config)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-13 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-13 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-13 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-13 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-13 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-13 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-13 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-13 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-13 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-13 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-13 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-13 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-13 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-13 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-13 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-13 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-13 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-13 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-13 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-13 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-13 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-13 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-13 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-13 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-13 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-13\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>RandomizedSearchCV(cv=KFold(n_splits=5, random_state=42, shuffle=True),\n",
       "                   estimator=Pipeline(steps=[(&#x27;tree_reg&#x27;,\n",
       "                                              DecisionTreeRegressor(random_state=42))]),\n",
       "                   param_distributions={&#x27;tree_reg__criterion&#x27;: [&#x27;poisson&#x27;,\n",
       "                                                                &#x27;friedman_mse&#x27;,\n",
       "                                                                &#x27;squared_error&#x27;,\n",
       "                                                                &#x27;absolute_error&#x27;],\n",
       "                                        &#x27;tree_reg__max_depth&#x27;: [3, 5, 7],\n",
       "                                        &#x27;tree_reg__min_samples_leaf&#x27;: [2, 4, 6],\n",
       "                                        &#x27;tree_reg__min_samples_split&#x27;: [5, 10,\n",
       "                                                                        15]},\n",
       "                   random_state=42, scoring=&#x27;r2&#x27;, verbose=4)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-106\" type=\"checkbox\" ><label for=\"sk-estimator-id-106\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;RandomizedSearchCV<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.model_selection.RandomizedSearchCV.html\">?<span>Documentation for RandomizedSearchCV</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>RandomizedSearchCV(cv=KFold(n_splits=5, random_state=42, shuffle=True),\n",
       "                   estimator=Pipeline(steps=[(&#x27;tree_reg&#x27;,\n",
       "                                              DecisionTreeRegressor(random_state=42))]),\n",
       "                   param_distributions={&#x27;tree_reg__criterion&#x27;: [&#x27;poisson&#x27;,\n",
       "                                                                &#x27;friedman_mse&#x27;,\n",
       "                                                                &#x27;squared_error&#x27;,\n",
       "                                                                &#x27;absolute_error&#x27;],\n",
       "                                        &#x27;tree_reg__max_depth&#x27;: [3, 5, 7],\n",
       "                                        &#x27;tree_reg__min_samples_leaf&#x27;: [2, 4, 6],\n",
       "                                        &#x27;tree_reg__min_samples_split&#x27;: [5, 10,\n",
       "                                                                        15]},\n",
       "                   random_state=42, scoring=&#x27;r2&#x27;, verbose=4)</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-107\" type=\"checkbox\" ><label for=\"sk-estimator-id-107\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">best_estimator_: Pipeline</label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;tree_reg&#x27;,\n",
       "                 DecisionTreeRegressor(max_depth=7, min_samples_leaf=4,\n",
       "                                       min_samples_split=15,\n",
       "                                       random_state=42))])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-108\" type=\"checkbox\" ><label for=\"sk-estimator-id-108\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;DecisionTreeRegressor<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.tree.DecisionTreeRegressor.html\">?<span>Documentation for DecisionTreeRegressor</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>DecisionTreeRegressor(max_depth=7, min_samples_leaf=4, min_samples_split=15,\n",
       "                      random_state=42)</pre></div> </div></div></div></div></div></div></div></div></div></div></div>"
      ],
      "text/plain": [
       "RandomizedSearchCV(cv=KFold(n_splits=5, random_state=42, shuffle=True),\n",
       "                   estimator=Pipeline(steps=[('tree_reg',\n",
       "                                              DecisionTreeRegressor(random_state=42))]),\n",
       "                   param_distributions={'tree_reg__criterion': ['poisson',\n",
       "                                                                'friedman_mse',\n",
       "                                                                'squared_error',\n",
       "                                                                'absolute_error'],\n",
       "                                        'tree_reg__max_depth': [3, 5, 7],\n",
       "                                        'tree_reg__min_samples_leaf': [2, 4, 6],\n",
       "                                        'tree_reg__min_samples_split': [5, 10,\n",
       "                                                                        15]},\n",
       "                   random_state=42, scoring='r2', verbose=4)"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the pipeline\n",
    "iteration_10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'cv': KFold(n_splits=5, random_state=42, shuffle=True),\n",
       " 'error_score': nan,\n",
       " 'estimator__memory': None,\n",
       " 'estimator__steps': [('tree_reg', DecisionTreeRegressor(random_state=42))],\n",
       " 'estimator__verbose': False,\n",
       " 'estimator__tree_reg': DecisionTreeRegressor(random_state=42),\n",
       " 'estimator__tree_reg__ccp_alpha': 0.0,\n",
       " 'estimator__tree_reg__criterion': 'squared_error',\n",
       " 'estimator__tree_reg__max_depth': None,\n",
       " 'estimator__tree_reg__max_features': None,\n",
       " 'estimator__tree_reg__max_leaf_nodes': None,\n",
       " 'estimator__tree_reg__min_impurity_decrease': 0.0,\n",
       " 'estimator__tree_reg__min_samples_leaf': 1,\n",
       " 'estimator__tree_reg__min_samples_split': 2,\n",
       " 'estimator__tree_reg__min_weight_fraction_leaf': 0.0,\n",
       " 'estimator__tree_reg__monotonic_cst': None,\n",
       " 'estimator__tree_reg__random_state': 42,\n",
       " 'estimator__tree_reg__splitter': 'best',\n",
       " 'estimator': Pipeline(steps=[('tree_reg', DecisionTreeRegressor(random_state=42))]),\n",
       " 'n_iter': 10,\n",
       " 'n_jobs': None,\n",
       " 'param_distributions': {'tree_reg__max_depth': [3, 5, 7],\n",
       "  'tree_reg__min_samples_split': [5, 10, 15],\n",
       "  'tree_reg__criterion': ['poisson',\n",
       "   'friedman_mse',\n",
       "   'squared_error',\n",
       "   'absolute_error'],\n",
       "  'tree_reg__min_samples_leaf': [2, 4, 6]},\n",
       " 'pre_dispatch': '2*n_jobs',\n",
       " 'random_state': 42,\n",
       " 'refit': True,\n",
       " 'return_train_score': False,\n",
       " 'scoring': 'r2',\n",
       " 'verbose': 4}"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the grid parameters\n",
    "iteration_10.get_params()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Review the Results\n",
    "\n",
    "Now that we've explored a few iterations, let's compare the results. We'll use `dw.format_df` to make the numbers easier to read. If we didn't use this, we'd see a lot of scientific notation and long decimal places that are unnecessary."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Iteration</th>\n",
       "      <th>Train MSE</th>\n",
       "      <th>Test MSE</th>\n",
       "      <th>Train RMSE</th>\n",
       "      <th>Test RMSE</th>\n",
       "      <th>Train MAE</th>\n",
       "      <th>Test MAE</th>\n",
       "      <th>Train R^2 Score</th>\n",
       "      <th>Test R^2 Score</th>\n",
       "      <th>Pipeline</th>\n",
       "      <th>Best Grid Params</th>\n",
       "      <th>Note</th>\n",
       "      <th>Date</th>\n",
       "      <th>Best Grid Mean Score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>3,568,722,087</td>\n",
       "      <td>3,614,822,637</td>\n",
       "      <td>59,739</td>\n",
       "      <td>60,123</td>\n",
       "      <td>44,354</td>\n",
       "      <td>44,485</td>\n",
       "      <td>0.61</td>\n",
       "      <td>0.62</td>\n",
       "      <td>linreg</td>\n",
       "      <td>NaN</td>\n",
       "      <td>X1. Baseline. Test size: 0.25, Pipeline: LinReg</td>\n",
       "      <td>May 30, 2024 09:17 AM UTC</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>3,333,110,642</td>\n",
       "      <td>3,356,136,123</td>\n",
       "      <td>57,733</td>\n",
       "      <td>57,932</td>\n",
       "      <td>42,498</td>\n",
       "      <td>42,621</td>\n",
       "      <td>0.63</td>\n",
       "      <td>0.64</td>\n",
       "      <td>log -&gt; linreg</td>\n",
       "      <td>NaN</td>\n",
       "      <td>X1. Test size: 0.25, Pipeline: Log &gt; LinReg</td>\n",
       "      <td>May 30, 2024 09:17 AM UTC</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>3,329,236,889</td>\n",
       "      <td>3,350,722,400</td>\n",
       "      <td>57,700</td>\n",
       "      <td>57,885</td>\n",
       "      <td>42,383</td>\n",
       "      <td>42,493</td>\n",
       "      <td>0.63</td>\n",
       "      <td>0.64</td>\n",
       "      <td>log_poly2 -&gt; linreg</td>\n",
       "      <td>NaN</td>\n",
       "      <td>X1. Test size: 0.25, Pipeline: Log &gt; Poly2 &gt; LinReg</td>\n",
       "      <td>May 30, 2024 09:17 AM UTC</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>3,231,250,156</td>\n",
       "      <td>3,242,416,486</td>\n",
       "      <td>56,844</td>\n",
       "      <td>56,942</td>\n",
       "      <td>41,276</td>\n",
       "      <td>41,406</td>\n",
       "      <td>0.64</td>\n",
       "      <td>0.66</td>\n",
       "      <td>ohe_log_poly2 -&gt; linreg</td>\n",
       "      <td>NaN</td>\n",
       "      <td>X2. Test size: 0.25, Pipeline: OHE &gt; Log &gt; Poly2 &gt; LinReg</td>\n",
       "      <td>May 30, 2024 09:17 AM UTC</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>3,323,311,153</td>\n",
       "      <td>3,339,547,363</td>\n",
       "      <td>57,648</td>\n",
       "      <td>57,789</td>\n",
       "      <td>42,307</td>\n",
       "      <td>42,379</td>\n",
       "      <td>0.63</td>\n",
       "      <td>0.65</td>\n",
       "      <td>ord_log_poly2 -&gt; linreg</td>\n",
       "      <td>NaN</td>\n",
       "      <td>X2. Test size: 0.25, Pipeline: Ord &gt; Log &gt; Poly2 &gt; LinReg</td>\n",
       "      <td>May 30, 2024 09:17 AM UTC</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>3,191,564,997</td>\n",
       "      <td>3,179,359,775</td>\n",
       "      <td>56,494</td>\n",
       "      <td>56,386</td>\n",
       "      <td>41,117</td>\n",
       "      <td>41,108</td>\n",
       "      <td>0.65</td>\n",
       "      <td>0.66</td>\n",
       "      <td>ohe_log_poly3 -&gt; linreg</td>\n",
       "      <td>NaN</td>\n",
       "      <td>X2. Test size: 0.25, Pipeline: OHE &gt; Log &gt; Poly3 &gt; LinReg</td>\n",
       "      <td>May 30, 2024 09:17 AM UTC</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>3,237,365,967</td>\n",
       "      <td>3,249,712,162</td>\n",
       "      <td>56,898</td>\n",
       "      <td>57,006</td>\n",
       "      <td>41,454</td>\n",
       "      <td>41,585</td>\n",
       "      <td>0.64</td>\n",
       "      <td>0.66</td>\n",
       "      <td>ohe_log -&gt; linreg</td>\n",
       "      <td>NaN</td>\n",
       "      <td>X2. Test size: 0.25, Pipeline: OHE &gt; Log &gt; LinReg</td>\n",
       "      <td>May 30, 2024 09:17 AM UTC</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>3,288,332,851</td>\n",
       "      <td>3,283,356,080</td>\n",
       "      <td>57,344</td>\n",
       "      <td>57,301</td>\n",
       "      <td>42,230</td>\n",
       "      <td>42,182</td>\n",
       "      <td>0.64</td>\n",
       "      <td>0.65</td>\n",
       "      <td>log_poly3 -&gt; stand -&gt; ridge</td>\n",
       "      <td>NaN</td>\n",
       "      <td>X1. Test size: 0.25, Pipeline: Log &gt; Poly3 &gt; Stand &gt; Ridge. CV: 5</td>\n",
       "      <td>May 30, 2024 09:17 AM UTC</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>3,288,332,851</td>\n",
       "      <td>3,283,356,080</td>\n",
       "      <td>57,344</td>\n",
       "      <td>57,301</td>\n",
       "      <td>42,230</td>\n",
       "      <td>42,182</td>\n",
       "      <td>0.64</td>\n",
       "      <td>0.65</td>\n",
       "      <td>log_poly3 -&gt; stand -&gt; ridge</td>\n",
       "      <td>{'ridge__alpha': 1.0}</td>\n",
       "      <td>X1. Test size: 0.25, Pipeline: Log &gt; Poly3 &gt; Stand &gt; Ridge. Grid CV: 5</td>\n",
       "      <td>May 30, 2024 09:17 AM UTC</td>\n",
       "      <td>0.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>2,944,707,111</td>\n",
       "      <td>3,340,337,712</td>\n",
       "      <td>54,265</td>\n",
       "      <td>57,796</td>\n",
       "      <td>39,005</td>\n",
       "      <td>41,032</td>\n",
       "      <td>0.68</td>\n",
       "      <td>0.65</td>\n",
       "      <td>tree_reg</td>\n",
       "      <td>{'tree_reg__min_samples_split': 15, 'tree_reg__min_samples_leaf': 4, 'tree_reg__max_depth': 7, 'tree_reg__criterion': 'squared_error'}</td>\n",
       "      <td>X1. Test size: 0.25, Pipeline: Tree. Random Grid CV: 5</td>\n",
       "      <td>May 30, 2024 09:17 AM UTC</td>\n",
       "      <td>0.64</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Iteration      Train MSE       Test MSE Train RMSE Test RMSE Train MAE Test MAE Train R^2 Score Test R^2 Score                     Pipeline                                                                                                                        Best Grid Params                                                                    Note                       Date Best Grid Mean Score\n",
       "0         1  3,568,722,087  3,614,822,637     59,739    60,123    44,354   44,485            0.61           0.62                       linreg                                                                                                                                     NaN                         X1. Baseline. Test size: 0.25, Pipeline: LinReg  May 30, 2024 09:17 AM UTC                  NaN\n",
       "1         2  3,333,110,642  3,356,136,123     57,733    57,932    42,498   42,621            0.63           0.64                log -> linreg                                                                                                                                     NaN                             X1. Test size: 0.25, Pipeline: Log > LinReg  May 30, 2024 09:17 AM UTC                  NaN\n",
       "2         3  3,329,236,889  3,350,722,400     57,700    57,885    42,383   42,493            0.63           0.64          log_poly2 -> linreg                                                                                                                                     NaN                     X1. Test size: 0.25, Pipeline: Log > Poly2 > LinReg  May 30, 2024 09:17 AM UTC                  NaN\n",
       "3         4  3,231,250,156  3,242,416,486     56,844    56,942    41,276   41,406            0.64           0.66      ohe_log_poly2 -> linreg                                                                                                                                     NaN               X2. Test size: 0.25, Pipeline: OHE > Log > Poly2 > LinReg  May 30, 2024 09:17 AM UTC                  NaN\n",
       "4         5  3,323,311,153  3,339,547,363     57,648    57,789    42,307   42,379            0.63           0.65      ord_log_poly2 -> linreg                                                                                                                                     NaN               X2. Test size: 0.25, Pipeline: Ord > Log > Poly2 > LinReg  May 30, 2024 09:17 AM UTC                  NaN\n",
       "5         6  3,191,564,997  3,179,359,775     56,494    56,386    41,117   41,108            0.65           0.66      ohe_log_poly3 -> linreg                                                                                                                                     NaN               X2. Test size: 0.25, Pipeline: OHE > Log > Poly3 > LinReg  May 30, 2024 09:17 AM UTC                  NaN\n",
       "6         7  3,237,365,967  3,249,712,162     56,898    57,006    41,454   41,585            0.64           0.66            ohe_log -> linreg                                                                                                                                     NaN                       X2. Test size: 0.25, Pipeline: OHE > Log > LinReg  May 30, 2024 09:17 AM UTC                  NaN\n",
       "7         8  3,288,332,851  3,283,356,080     57,344    57,301    42,230   42,182            0.64           0.65  log_poly3 -> stand -> ridge                                                                                                                                     NaN       X1. Test size: 0.25, Pipeline: Log > Poly3 > Stand > Ridge. CV: 5  May 30, 2024 09:17 AM UTC                  NaN\n",
       "8         9  3,288,332,851  3,283,356,080     57,344    57,301    42,230   42,182            0.64           0.65  log_poly3 -> stand -> ridge                                                                                                                   {'ridge__alpha': 1.0}  X1. Test size: 0.25, Pipeline: Log > Poly3 > Stand > Ridge. Grid CV: 5  May 30, 2024 09:17 AM UTC                 0.64\n",
       "9        10  2,944,707,111  3,340,337,712     54,265    57,796    39,005   41,032            0.68           0.65                     tree_reg  {'tree_reg__min_samples_split': 15, 'tree_reg__min_samples_leaf': 4, 'tree_reg__max_depth': 7, 'tree_reg__criterion': 'squared_error'}                  X1. Test size: 0.25, Pipeline: Tree. Random Grid CV: 5  May 30, 2024 09:17 AM UTC                 0.64"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the results, formatted for better readability\n",
    "formatted_results_df = dw.format_df(results_df, large_num_cols=['Train MSE', 'Test MSE', 'Train RMSE', 'Test RMSE',\n",
    "       'Train MAE', 'Test MAE'], small_num_cols=['Train R^2 Score', 'Test R^2 Score', 'Best Grid Mean Score'])\n",
    "formatted_results_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot the Results\n",
    "\n",
    "Let's plot the results so it's easier to see which model performed the best. We'll look at 'Train R^2 Score' and 'Test R^2 Score' across each model 'Iteration'. And then we'll look at 'Train MAE' and 'Test MAE' across each model 'Iteration'. We'll use `dw.plot_results` to simplify this to one line of code, and automatically select the best result, which will be marked on the chart with a vertical line."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Compare train/test R^2 scores across model iterations, and select the best 'Test R^2 Score'\n",
    "dw.plot_results(results_df, metrics=['Train R^2 Score', 'Test R^2 Score'], y_label='R^2 Score',\n",
    "                select_metric='Test R^2 Score', select_criteria='max', decimal=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Compare train/test MAE scores across model iterations, and select the best 'Test MAE'\n",
    "dw.plot_results(results_df, metrics=['Train MAE', 'Test MAE'], y_label='Mean Absolute Error',\n",
    "                select_metric='Test MAE', select_criteria='min', decimal=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Examine the Final Model\n",
    "\n",
    "Iteration 6, a Linear Regression, seems to be the best model. Even though Iteration 10, the Decision Tree, had a lower Test MAE, its Test R^2 Score was lower and overfit on the Train Data. Now that we know the best model, let's take a look at its details. With every iteration we ran, we saved the fitted model as an object. For example, we entered `results_df, iteration_6 = dw.iterate_model(...)` which both updated the `results_df` dataframe by appending the data from iteration 6, and stored the model as `iteration_6`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-14 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-14 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-14 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-14 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-14 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-14 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-14 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-14 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-14 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-14 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-14 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-14 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-14 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-14 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-14 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-14 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-14 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-14 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-14 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-14 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-14 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-14 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-14 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-14 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-14 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-14 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-14 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-14 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-14 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-14 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-14 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-14 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-14 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-14 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-14 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-14 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-14 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-14 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-14 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-14 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-14 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-14 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-14\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;ohe_log_poly3&#x27;,\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;ohe&#x27;,\n",
       "                                                  OneHotEncoder(drop=&#x27;if_binary&#x27;,\n",
       "                                                                handle_unknown=&#x27;ignore&#x27;),\n",
       "                                                  [&#x27;ocean_proximity&#x27;]),\n",
       "                                                 (&#x27;log&#x27;, LogTransformer(),\n",
       "                                                  [&#x27;total_rooms&#x27;,\n",
       "                                                   &#x27;total_bedrooms&#x27;,\n",
       "                                                   &#x27;population&#x27;,\n",
       "                                                   &#x27;households&#x27;]),\n",
       "                                                 (&#x27;poly3&#x27;,\n",
       "                                                  PolynomialFeatures(degree=3,\n",
       "                                                                     include_bias=False),\n",
       "                                                  [&#x27;median_income&#x27;])])),\n",
       "                (&#x27;linreg&#x27;, LinearRegression())])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-109\" type=\"checkbox\" ><label for=\"sk-estimator-id-109\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;ohe_log_poly3&#x27;,\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;ohe&#x27;,\n",
       "                                                  OneHotEncoder(drop=&#x27;if_binary&#x27;,\n",
       "                                                                handle_unknown=&#x27;ignore&#x27;),\n",
       "                                                  [&#x27;ocean_proximity&#x27;]),\n",
       "                                                 (&#x27;log&#x27;, LogTransformer(),\n",
       "                                                  [&#x27;total_rooms&#x27;,\n",
       "                                                   &#x27;total_bedrooms&#x27;,\n",
       "                                                   &#x27;population&#x27;,\n",
       "                                                   &#x27;households&#x27;]),\n",
       "                                                 (&#x27;poly3&#x27;,\n",
       "                                                  PolynomialFeatures(degree=3,\n",
       "                                                                     include_bias=False),\n",
       "                                                  [&#x27;median_income&#x27;])])),\n",
       "                (&#x27;linreg&#x27;, LinearRegression())])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-110\" type=\"checkbox\" ><label for=\"sk-estimator-id-110\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;ohe_log_poly3: ColumnTransformer<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.compose.ColumnTransformer.html\">?<span>Documentation for ohe_log_poly3: ColumnTransformer</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>ColumnTransformer(force_int_remainder_cols=False, remainder=&#x27;passthrough&#x27;,\n",
       "                  transformers=[(&#x27;ohe&#x27;,\n",
       "                                 OneHotEncoder(drop=&#x27;if_binary&#x27;,\n",
       "                                               handle_unknown=&#x27;ignore&#x27;),\n",
       "                                 [&#x27;ocean_proximity&#x27;]),\n",
       "                                (&#x27;log&#x27;, LogTransformer(),\n",
       "                                 [&#x27;total_rooms&#x27;, &#x27;total_bedrooms&#x27;, &#x27;population&#x27;,\n",
       "                                  &#x27;households&#x27;]),\n",
       "                                (&#x27;poly3&#x27;,\n",
       "                                 PolynomialFeatures(degree=3,\n",
       "                                                    include_bias=False),\n",
       "                                 [&#x27;median_income&#x27;])])</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-111\" type=\"checkbox\" ><label for=\"sk-estimator-id-111\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">ohe</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;ocean_proximity&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-112\" type=\"checkbox\" ><label for=\"sk-estimator-id-112\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;OneHotEncoder<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.OneHotEncoder.html\">?<span>Documentation for OneHotEncoder</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>OneHotEncoder(drop=&#x27;if_binary&#x27;, handle_unknown=&#x27;ignore&#x27;)</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-113\" type=\"checkbox\" ><label for=\"sk-estimator-id-113\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">log</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;total_rooms&#x27;, &#x27;total_bedrooms&#x27;, &#x27;population&#x27;, &#x27;households&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-114\" type=\"checkbox\" ><label for=\"sk-estimator-id-114\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">LogTransformer</label><div class=\"sk-toggleable__content fitted\"><pre>LogTransformer()</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-115\" type=\"checkbox\" ><label for=\"sk-estimator-id-115\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">poly3</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;median_income&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-116\" type=\"checkbox\" ><label for=\"sk-estimator-id-116\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;PolynomialFeatures<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.PolynomialFeatures.html\">?<span>Documentation for PolynomialFeatures</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>PolynomialFeatures(degree=3, include_bias=False)</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-117\" type=\"checkbox\" ><label for=\"sk-estimator-id-117\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">remainder</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;longitude&#x27;, &#x27;latitude&#x27;, &#x27;housing_median_age&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-118\" type=\"checkbox\" ><label for=\"sk-estimator-id-118\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">passthrough</label><div class=\"sk-toggleable__content fitted\"><pre>passthrough</pre></div> </div></div></div></div></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-119\" type=\"checkbox\" ><label for=\"sk-estimator-id-119\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;LinearRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.linear_model.LinearRegression.html\">?<span>Documentation for LinearRegression</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>LinearRegression()</pre></div> </div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('ohe_log_poly3',\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder='passthrough',\n",
       "                                   transformers=[('ohe',\n",
       "                                                  OneHotEncoder(drop='if_binary',\n",
       "                                                                handle_unknown='ignore'),\n",
       "                                                  ['ocean_proximity']),\n",
       "                                                 ('log', LogTransformer(),\n",
       "                                                  ['total_rooms',\n",
       "                                                   'total_bedrooms',\n",
       "                                                   'population',\n",
       "                                                   'households']),\n",
       "                                                 ('poly3',\n",
       "                                                  PolynomialFeatures(degree=3,\n",
       "                                                                     include_bias=False),\n",
       "                                                  ['median_income'])])),\n",
       "                ('linreg', LinearRegression())])"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the final model pipeline\n",
    "iteration_6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'memory': None,\n",
       " 'steps': [('ohe_log_poly3',\n",
       "   ColumnTransformer(force_int_remainder_cols=False, remainder='passthrough',\n",
       "                     transformers=[('ohe',\n",
       "                                    OneHotEncoder(drop='if_binary',\n",
       "                                                  handle_unknown='ignore'),\n",
       "                                    ['ocean_proximity']),\n",
       "                                   ('log', LogTransformer(),\n",
       "                                    ['total_rooms', 'total_bedrooms', 'population',\n",
       "                                     'households']),\n",
       "                                   ('poly3',\n",
       "                                    PolynomialFeatures(degree=3,\n",
       "                                                       include_bias=False),\n",
       "                                    ['median_income'])])),\n",
       "  ('linreg', LinearRegression())],\n",
       " 'verbose': False,\n",
       " 'ohe_log_poly3': ColumnTransformer(force_int_remainder_cols=False, remainder='passthrough',\n",
       "                   transformers=[('ohe',\n",
       "                                  OneHotEncoder(drop='if_binary',\n",
       "                                                handle_unknown='ignore'),\n",
       "                                  ['ocean_proximity']),\n",
       "                                 ('log', LogTransformer(),\n",
       "                                  ['total_rooms', 'total_bedrooms', 'population',\n",
       "                                   'households']),\n",
       "                                 ('poly3',\n",
       "                                  PolynomialFeatures(degree=3,\n",
       "                                                     include_bias=False),\n",
       "                                  ['median_income'])]),\n",
       " 'linreg': LinearRegression(),\n",
       " 'ohe_log_poly3__force_int_remainder_cols': False,\n",
       " 'ohe_log_poly3__n_jobs': None,\n",
       " 'ohe_log_poly3__remainder': 'passthrough',\n",
       " 'ohe_log_poly3__sparse_threshold': 0.3,\n",
       " 'ohe_log_poly3__transformer_weights': None,\n",
       " 'ohe_log_poly3__transformers': [('ohe',\n",
       "   OneHotEncoder(drop='if_binary', handle_unknown='ignore'),\n",
       "   ['ocean_proximity']),\n",
       "  ('log',\n",
       "   LogTransformer(),\n",
       "   ['total_rooms', 'total_bedrooms', 'population', 'households']),\n",
       "  ('poly3',\n",
       "   PolynomialFeatures(degree=3, include_bias=False),\n",
       "   ['median_income'])],\n",
       " 'ohe_log_poly3__verbose': False,\n",
       " 'ohe_log_poly3__verbose_feature_names_out': True,\n",
       " 'ohe_log_poly3__ohe': OneHotEncoder(drop='if_binary', handle_unknown='ignore'),\n",
       " 'ohe_log_poly3__log': LogTransformer(),\n",
       " 'ohe_log_poly3__poly3': PolynomialFeatures(degree=3, include_bias=False),\n",
       " 'ohe_log_poly3__ohe__categories': 'auto',\n",
       " 'ohe_log_poly3__ohe__drop': 'if_binary',\n",
       " 'ohe_log_poly3__ohe__dtype': numpy.float64,\n",
       " 'ohe_log_poly3__ohe__feature_name_combiner': 'concat',\n",
       " 'ohe_log_poly3__ohe__handle_unknown': 'ignore',\n",
       " 'ohe_log_poly3__ohe__max_categories': None,\n",
       " 'ohe_log_poly3__ohe__min_frequency': None,\n",
       " 'ohe_log_poly3__ohe__sparse_output': True,\n",
       " 'ohe_log_poly3__poly3__degree': 3,\n",
       " 'ohe_log_poly3__poly3__include_bias': False,\n",
       " 'ohe_log_poly3__poly3__interaction_only': False,\n",
       " 'ohe_log_poly3__poly3__order': 'C',\n",
       " 'linreg__copy_X': True,\n",
       " 'linreg__fit_intercept': True,\n",
       " 'linreg__n_jobs': None,\n",
       " 'linreg__positive': False}"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the final pipeline parameters\n",
    "iteration_6.get_params()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-4.56340164e+03, -3.79954870e+04,  6.87515120e+04,\n",
       "        -2.30277393e+04, -3.16488408e+03, -5.04981768e+04,\n",
       "         8.41837756e+04, -7.19954467e+04,  4.44049418e+04,\n",
       "        -2.58743880e+04, -2.41148753e+04,  7.28717064e+02,\n",
       "         4.16905337e+00]])"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Note the model coefficients are not part of the pipeline parameters, they are found here:\n",
    "iteration_6.steps[-1][1].coef_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot ACF Residuals\n",
    "\n",
    "`dw.plot_acf_residuals()` plots residuals, histogram, ACF, and PACF of a time series ARIMA model.\n",
    "\n",
    "This function takes the results of an ARIMA model and creates a 2x2 grid of\n",
    "plots to visualize the residuals, their histogram, autocorrelation function\n",
    "(ACF), and partial autocorrelation function (PACF). The residuals are plotted\n",
    "with lines indicating standard deviations from the mean if `show_std` is True.\n",
    "\n",
    "Use this function in time series analysis to assess the residuals of an ARIMA\n",
    "model and check for any patterns or autocorrelations that may indicate\n",
    "inadequacies in the model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load X_train data from a previous project on the ES futures close price\n",
    "X_train = pd.read_csv('data/X_train.csv', index_col=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert to datetime format and set the index\n",
    "X_train['Time'] = pd.to_datetime(X_train['Time'])\n",
    "X_train = X_train.set_index('Time')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create seasonal trend model\n",
    "stl = STL(X_train['Close'], period=55, trend=89)\n",
    "stl_result = stl.fit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x800 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the residuals\n",
    "dw.plot_acf_residuals(stl_result)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Evaluate Classification Model\n",
    "\n",
    "`dw.eval_model()` produces a detailed evaluation report for a classification model.\n",
    "\n",
    "This function provides a comprehensive evaluation of a binary or multi-class\n",
    "classification model based on `y_test` (the actual target values) and `y_pred`\n",
    "(the predicted target values). It displays a text-based classification report\n",
    "enhanced with True/False Positives/Negatives, and 4 charts if `plot` is\n",
    "True: Confusion Matrix, Histogram of Predicted Probabilities, ROC Curve, and\n",
    "Precision-Recall Curve.\n",
    "\n",
    "If `class_type` is 'binary' (default), it will treat this as a binary\n",
    "classification. If `class_type` is 'multi', it will treat this as a multi-class\n",
    "problem. To plot the curves or adjust the `threshold` (default 0.5), both\n",
    "`X_test` and `estimator` must be provided.\n",
    "\n",
    "A number of classification metrics are shown in the report: Accuracy,\n",
    "Precision, Recall, F1, and ROC AUC. In addition, for binary classification,\n",
    "True Positive Rate, False Positive Rate, True Negative Rate, and False\n",
    "Negative Rate are shown.\n",
    "\n",
    "Use this function to assess the performance of a trained classification\n",
    "model. You can experiment with different thresholds to see how they affect\n",
    "metrics like Precision, Recall, False Positive Rate and False Negative\n",
    "Rate. The plots make it easy to see if you're getting good separation and\n",
    "maximum area under the curve."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Separate X and Y\n",
    "\n",
    "Let's load the Bank dataset, which was already split into X and y. It's a binary classification dataset. y is either '0' or '1'."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Load the Bank dataset, already separated into X and y\n",
    "X = pd.read_csv('data/X_bank.csv').drop(columns=['Unnamed: 0'])\n",
    "y = pd.read_csv('data/y_bank.csv').drop(columns=['Unnamed: 0'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X: (40195, 57), y: (40195, 1)\n"
     ]
    }
   ],
   "source": [
    "# Verify X/Y split\n",
    "print(f'X: {X.shape}, y: {y.shape}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X: (57) ['age', 'duration', 'campaign', 'pdays', 'previous', 'emp.var.rate', 'cons.price.idx', 'cons.conf.idx', 'euribor3m', 'nr.employed', 'previously_contacted', 'job_admin.', 'job_blue-collar', 'job_entrepreneur', 'job_housemaid', 'job_management', 'job_retired', 'job_self-employed', 'job_services', 'job_student', 'job_technician', 'job_unemployed', 'job_unknown', 'marital_divorced', 'marital_married', 'marital_single', 'marital_unknown', 'education_basic.4y', 'education_basic.6y', 'education_basic.9y', 'education_high.school', 'education_illiterate', 'education_professional.course', 'education_university.degree', 'education_unknown', 'month_apr', 'month_aug', 'month_dec', 'month_jul', 'month_jun', 'month_mar', 'month_may', 'month_nov', 'month_oct', 'month_sep', 'day_of_week_fri', 'day_of_week_mon', 'day_of_week_thu', 'day_of_week_tue', 'day_of_week_wed', 'poutcome_failure', 'poutcome_nonexistent', 'poutcome_success', 'no_default_1', 'housing_yes', 'loan_yes', 'contact_telephone']\n",
      "y: (1) ['subscribed_enc']\n"
     ]
    }
   ],
   "source": [
    "# Verify X/Y columns\n",
    "print(f'X: ({len(X.columns)})', list(X.columns))\n",
    "print(f'y: ({len(y.columns)})', list(y.columns))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set column lists\n",
    "x_columns = list(X.columns)\n",
    "y_columns = list(y.columns)\n",
    "num_columns = x_columns\n",
    "cat_columns = []"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Split Train and Test\n",
    "\n",
    "Now we'll separate the train set from the test set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create training and test datasets\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X: (30146, 57) (10049, 57) (30146, 1) (10049, 1)\n"
     ]
    }
   ],
   "source": [
    "# Verify train/test split\n",
    "print('X:', X_train.shape, X_test.shape, y_train.shape, y_test.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Build a Pipeline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a pipeline with Standard Scaler and Logistic Regression\n",
    "pipe = dw.create_pipeline(scaler_key='stand', model_key='logreg', class_weight='balanced',\n",
    "                          num_columns=num_columns, cat_columns=cat_columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-15 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-15 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-15 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-15 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-15 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-15 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-15 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-15 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-15 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-15 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-15 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-15 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-15 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-15 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-15 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-15 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-15 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-15 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-15 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-15 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-15 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-15 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-15 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-15 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-15 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-15 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-15 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-15 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-15 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-15 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-15 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-15 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-15 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-15 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-15 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-15 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-15 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-15 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-15 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-15 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-15 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-15 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-15\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;stand&#x27;, StandardScaler()),\n",
       "                (&#x27;logreg&#x27;,\n",
       "                 LogisticRegression(class_weight=&#x27;balanced&#x27;, max_iter=10000,\n",
       "                                    random_state=42))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-120\" type=\"checkbox\" ><label for=\"sk-estimator-id-120\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link \">i<span>Not fitted</span></span></label><div class=\"sk-toggleable__content \"><pre>Pipeline(steps=[(&#x27;stand&#x27;, StandardScaler()),\n",
       "                (&#x27;logreg&#x27;,\n",
       "                 LogisticRegression(class_weight=&#x27;balanced&#x27;, max_iter=10000,\n",
       "                                    random_state=42))])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-121\" type=\"checkbox\" ><label for=\"sk-estimator-id-121\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;StandardScaler<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.StandardScaler.html\">?<span>Documentation for StandardScaler</span></a></label><div class=\"sk-toggleable__content \"><pre>StandardScaler()</pre></div> </div></div><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-122\" type=\"checkbox\" ><label for=\"sk-estimator-id-122\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;LogisticRegression<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.linear_model.LogisticRegression.html\">?<span>Documentation for LogisticRegression</span></a></label><div class=\"sk-toggleable__content \"><pre>LogisticRegression(class_weight=&#x27;balanced&#x27;, max_iter=10000, random_state=42)</pre></div> </div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('stand', StandardScaler()),\n",
       "                ('logreg',\n",
       "                 LogisticRegression(class_weight='balanced', max_iter=10000,\n",
       "                                    random_state=42))])"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the pipeline\n",
    "pipe"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Fit the Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-16 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-16 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-16 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-16 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-16 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-16 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-16 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-16 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-16 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-16 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-16 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-16 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-16 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-16 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-16 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-16 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-16 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-16 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-16 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-16 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-16 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-16 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-16 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-16 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-16 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-16 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-16 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-16 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-16 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-16 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-16 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-16 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-16 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-16 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-16 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-16 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-16 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-16 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-16 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-16 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-16 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-16 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-16\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;stand&#x27;, StandardScaler()),\n",
       "                (&#x27;logreg&#x27;,\n",
       "                 LogisticRegression(class_weight=&#x27;balanced&#x27;, max_iter=10000,\n",
       "                                    random_state=42))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-123\" type=\"checkbox\" ><label for=\"sk-estimator-id-123\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;stand&#x27;, StandardScaler()),\n",
       "                (&#x27;logreg&#x27;,\n",
       "                 LogisticRegression(class_weight=&#x27;balanced&#x27;, max_iter=10000,\n",
       "                                    random_state=42))])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-124\" type=\"checkbox\" ><label for=\"sk-estimator-id-124\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;StandardScaler<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.StandardScaler.html\">?<span>Documentation for StandardScaler</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>StandardScaler()</pre></div> </div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-125\" type=\"checkbox\" ><label for=\"sk-estimator-id-125\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;LogisticRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.linear_model.LogisticRegression.html\">?<span>Documentation for LogisticRegression</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>LogisticRegression(class_weight=&#x27;balanced&#x27;, max_iter=10000, random_state=42)</pre></div> </div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('stand', StandardScaler()),\n",
       "                ('logreg',\n",
       "                 LogisticRegression(class_weight='balanced', max_iter=10000,\n",
       "                                    random_state=42))])"
      ]
     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Fit the pipeline with the training data, after adjusting y_train shape\n",
    "pipe.fit(X_train, np.ravel(y_train))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Make Predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Make predictions with the test data\n",
    "y_pred = pipe.predict(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Evaluate Model Performance\n",
    "\n",
    "Let's now use `dw.eval_model` to evaluate a classification model's performance. Let's start with a basic summary that doesn't require the model and X_test to be passed, and then move on to examples that show charts and have customized values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a dictionary of class labels to display names\n",
    "class_map = {0: 'Declined', 1: 'Subscribed'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "LogReg Binary Classification Report\n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "    Declined       0.98      0.86      0.92      8872\n",
      "  Subscribed       0.46      0.89      0.61      1177\n",
      "\n",
      "    accuracy                           0.86     10049\n",
      "   macro avg       0.72      0.88      0.76     10049\n",
      "weighted avg       0.92      0.86      0.88     10049\n",
      "\n",
      "               Predicted:0         1         \n",
      "Actual: 0                7636      1236      \n",
      "Actual: 1                128       1049      \n",
      "\n",
      "True Positive Rate / Sensitivity: 0.89\n",
      "True Negative Rate / Specificity: 0.86\n",
      "False Positive Rate / Fall-out: 0.14\n",
      "False Negative Rate / Miss Rate: 0.11\n",
      "\n",
      "Positive Class: Subscribed (1)\n",
      "Threshold: 0.5\n"
     ]
    }
   ],
   "source": [
    "# Evaluate classification predictions with basic defaults\n",
    "dw.eval_model(y_test=y_test, y_pred=y_pred, model_name='LogReg', pos_label=1, class_map=class_map)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "LogReg Binary Classification Report\n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "    Declined       0.98      0.86      0.92      8872\n",
      "  Subscribed       0.46      0.89      0.61      1177\n",
      "\n",
      "    accuracy                           0.86     10049\n",
      "   macro avg       0.72      0.88      0.76     10049\n",
      "weighted avg       0.92      0.86      0.88     10049\n",
      "\n",
      "ROC AUC: 0.94\n",
      "\n",
      "               Predicted:0         1         \n",
      "Actual: 0                7636      1236      \n",
      "Actual: 1                128       1049      \n",
      "\n",
      "True Positive Rate / Sensitivity: 0.89\n",
      "True Negative Rate / Specificity: 0.86\n",
      "False Positive Rate / Fall-out: 0.14\n",
      "False Negative Rate / Miss Rate: 0.11\n",
      "\n",
      "Positive Class: Subscribed (1)\n",
      "Threshold: 0.5\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1100 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Evaluate classification model with charting enabled, and passing X_test and estimator for proababilities\n",
    "dw.eval_model(y_test=y_test, y_pred=y_pred, x_test=X_test, estimator=pipe, model_name='LogReg',\n",
    "              pos_label=1, class_map=class_map, plot=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "LogReg Binary Classification Report\n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "    Declined       0.99      0.81      0.89      8872\n",
      "  Subscribed       0.40      0.95      0.56      1177\n",
      "\n",
      "    accuracy                           0.83     10049\n",
      "   macro avg       0.70      0.88      0.73     10049\n",
      "weighted avg       0.92      0.83      0.85     10049\n",
      "\n",
      "ROC AUC: 0.94\n",
      "\n",
      "               Predicted:0         1         \n",
      "Actual: 0                7189      1683      \n",
      "Actual: 1                58        1119      \n",
      "\n",
      "True Positive Rate / Sensitivity: 0.95\n",
      "True Negative Rate / Specificity: 0.81\n",
      "False Positive Rate / Fall-out: 0.19\n",
      "False Negative Rate / Miss Rate: 0.05\n",
      "\n",
      "Positive Class: Subscribed (1)\n",
      "Threshold: 0.35\n"
     ]
    },
    {
     "data": {
      "image/png": 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XRNaXjkl5kZf9dNKkSWKZBw8eZFm2gYGB0KBBA/GcQhAEcVukpaWJ+1vNmjWFAwcOiJ9dfHy8sGHDBvHC19ixY7MsW5askEgkws8//yx+xpGRkcLIkSPlklb5TTTJkhgAhEGDBsl9ftHR0cI///wj9OjRQ26eL10MlHn9+rW4Xp07dxauXbsm7r+RkZHCzJkzxcTFvn375OZNS0sT6tatK56v7dy5U0hNTRUEQRDu3bsnNG7cWO6HflEkmuLj48UkS+ZtkNfzpRUrVojLGDZsmPDmzRux3mXLlonr/vn2FYT/7ZOyz3X06NFCVFSUIAjS74+5c+eKsY0bNy7L/Io4b9TT0xM0NTWFbt26icn3T58+CatXrxaTLp06dcpxfkUkmj7fHrn9FhGE3BNNx48fF9TU1AQNDQ1h8uTJQlhYmJCRkSFkZGQIISEhQrdu3QRAmqiXfQfKlC9fXgAgtGrVSrhz5444PjExUbh7967g5+eX7f9XcWGiiaiUmTFjhngAefXqVYHrGTFihHgglR2EMnvx4oV4kujj4yM3LfNJTqVKlYRPnz5lmX///v1imRcvXmSZXpSJpitXrgiA9OqY7AQhL3I7iVH29vqSz38oDRkyRAAgzJo1SyyTkZEhlC1bVgD+d2U0t0TTl/z6668CAKFFixZZpuU30QRA+P3333Ms96WT+rS0NKFhw4ZiIvDTp0/Cu3fvhDJlyognm0SkGjL/gP/8KvTnr8wtU/KTaJL90B42bFi+YstLouny5ctiTGvXrs22jCwRZWFhISQmJorj4+PjxWNRTq2eM2+f3BJN6urqwo0bN/K1fpnt2rVLACCUL18+y7TMx9uWLVsKGRkZWco0btxYLCO7OJJZWlqa4OzsLAAQ5s6dm6/YXr58Kf7gnjZtWrZlxo8fLwDSVgSyH/EyxZFoiomJEezs7ARAehFL1jIs87KdnJzEJOfnNm7cKJ53REdHZ1vm2rVrgkQiEbS0tMQkniAIwqtXr8TtM3PmzGzn7dWrV65Jk5wSTaGhoeIFoMmTJ2dbd3bymmiSJWJ79+6dY5mlS5cKAIQaNWrIjd+xY4e4jJMnT2aZLyEhQfzxX1SJJtm5FQBh2bJl4vi8nC99+vRJMDMzEwBpa7zs/P7772I9165dk5uWeZ/s27dvtvPLfodoaGjk+3dIXs4bZef+2bWEXL9+vVjmv//+y3b+rynRlJ6eLlSoUCHX73JBEIT27dsLAIQff/xRHBcZGSmu6+ffP18L9tFEVMq8f/9e/NvMzKxAdQiCgJ07dwIARowYARsbmyxl7O3tMWLECADA9u3bc6xrwoQJ0NXVzTK+TZs20NLSAvC/J8wVFxMTEwAQn8BXWCVxew0aNAgAsGHDBrH/hTNnzuDZs2dwdXXFt99+W+hleHt7AwCCgoLyfL9/TkxNTTF8+PACz6+uro6tW7fC1NQU9+/fx48//ohBgwbh1atXcHBwwPr16wsVHxGVTJGRkbm+3r17V6B6ZceZiIgIBUYrtWPHDgDS48qQIUOyLTN37lwAwLt373DixAlx/PHjxxEbGwsAmD59erbzTpgwAXp6el+Mo3Xr1qhVq1a+Ys9Mdox48uRJrttpypQp2faN6OXlJf49bdq0LNPV1dXRokULANI+nvJjz549SEtLg46ODqZOnZptmRkzZkBbWxupqal56pNIUaKjo3Hq1Ck0b94cr1+/BgD8+OOPYr89mY0ePTrHzshlfYSNHDky2z46AaBOnTqoUqUKUlJScObMGXH87t27kZaWBl1dXUycODHbebPrtywvNmzYgIyMDJibm4t94ChKUlIStm7dCkC6X+WkX79+AIBbt27J9a8pO39r2LChuG9lpqenh8mTJysyZADSvrAeP34MPz8/8QmDZmZm6N+/f5ayuZ0vnThxAh8+fACQ8+czatQo2NraAoC4rbIza9asbMdPmjQJurq6SEtLy7Ev0Jzk9bxxxowZ2e7vAwcOFPulze1c+2tx7tw5PHr0CBYWFjl+lwP/2x8z90tmaGgoboM3b94UbaAFxEQTEWURFhYmHog8PT1zLCd7tO779+8RFhaWbZkGDRpkO15DQwOWlpYAIC6ruJQvXx6VKlVCamoqGjRogF9++QXBwcEFToaUxO3l7u6OSpUq4fnz5+IjW/PaCXhmkZGRmD17Ntzd3WFubg4NDQ2xI8TKlSsDkHb++PHjx0LFW69ePTHRVlCOjo74888/AQB//vkn9u/fD3V1dWzevBmmpqaFqpuISiZB2ro/x1dO39Vf0rZtW0gkEuzfvx9t2rTBtm3bxKRAYV27dg0A0KxZs2x/bAGAm5sbypQpI1ceAG7cuAFA+n3o7Oyc7byGhoaoU6fOF+No2LDhF8vExcXh119/RdOmTWFlZQUtLS3xGJE5mfX5wzcyq1+/frbjra2tAUh/cJcrVy7XMvk9Bsm2Wb169WBkZJRtGVNTU9StW1eufFHJ3MmwqakpPD09xY6nv//++xyThjl9Runp6bh8+TIAacLBxsYmx1doaCgA6cM7ZGTrW7du3Ry3T8WKFcV9MD8uXboEQHrOpKOjk+/5c3P9+nWxs+hWrVrluM5VqlQR58luvZs3b57jMnKblh+ZHwigoaGBChUqwNfXF8nJybC0tMS///6b7blLbudLsvgdHBxQsWLFbMuoq6uL65DTfu3g4CA+8fBzRkZG4vdHdvMX9rxRQ0MDjRs3znaampqa+JCgov6fVISLFy8CAGJiYmBnZ5fj/jh06FAA8vuirq6umOxs3bo1Zs2ahStXriAlJaX4VyQHGsoOgIgUy9zcXPz7w4cPsLOzy3cdUVFR4t+5nSRkfppdVFRUtiethoaGOc6voSH9CkpNTc13jIWhrq6O7du3o1OnTggLC8PUqVMxdepU6Onp4dtvv0Xnzp3Rv3//PF3RBUru9ho4cCCmTJkCf39/1K9fH3v37oW6urp45eRLgoKC0LZtW0RHR4vjZE/KkEgkSE9PF1sDJCQkwMLCosCxWllZFXjezLp06YIuXbqIV9kmTpyIJk2aKKRuIiKZRo0a4ZdffsGMGTNw9OhRHD16FID0OODp6Yl+/frJPSUrP2THnC/9iLe3t8erV6/kjlFv374FgC+eG+QlQfCl7+WHDx+iRYsWckkkPT09mJiYiAkyWWuRhISEHOvJ6bgoOyYWxXEzP9s4c/miIkuYARCfEFarVi306dMn1/0op8/ow4cPSE5OBpD3JNynT5/Ev/O7D+aHrHWbk5NTvubLi8zJ3pyeBPy5/K73l570nFf6+vpiazQ1NTUYGBigXLlyaNGiBQYNGiR3vp9Zbv+XitqvvzS/bPrn8yvivFH2hM38LvtrJNsfU1NT87Q/JiYmyr1fv3492rdvj1u3bmHu3LmYO3cutLS0UK9ePXTo0AGDBw8u8N0tisAWTUSlTOarMDdv3lRiJF+3GjVqICQkBHv27MGwYcNQtWpVJCYm4uTJkxg1ahQqVapU7Lf0Fbe+fftCXV0d+/btw5o1a5CYmIjWrVuLTaZzk5aWhl69eiE6Oho1a9bE4cOHERsbi7i4OERGRiIiIkK8Wgqg0I+XVldXL9T8Ms+ePcPJkyfF9xcvXiz0bX1ERNmZNGkSwsLCsGzZMnTs2BFWVlZ4+fIlAgIC0Lx5c3Tr1q3YL7TIZHcrWn596Xt54MCBePnyJcqWLYtdu3bh/fv3SEhIQFRUFCIiIuQSEIU9RpR2ERER4uv58+e4fv061q9f/8VkZU6fUebj3pEjR77Ysk8QhALfCpdfitg3c5J5vRMTE/O03rIWMsVt4sSJ4mf++vVrPHz4EEePHsWkSZNyTDIBijtfUrTiPm8sCWT7Y4MGDfK0L36+TRwdHXHjxg0cPXoUY8aMQZ06dZCRkYGLFy9i8uTJcHFxwenTp5WxagCYaCIqdTI3pd+3b1+B6sh8NSS35uyZpymqxUleya5SyppAZycmJibXOrS0tNC5c2esXbsWd+7cwdu3b7FmzRqYmZnhxYsX2d77np2SsL2yY2tri9atWyMxMREzZ84EkPfb5oKCgvD8+XOoq6vj4MGDaNOmTZarykXRN0lhyE5yYmJiULFiRWhra+PChQtiXyZERIpmZ2eHsWPHYt++fYiMjMTt27fFvjh2796N1atX57tO2fEjt+NN5umZjzeyW7C/dBtffluhfO7FixfiLVDbtm1D165ds1xZ/9qOEZkVZhuXBLJblgD523HySra+X9pPCrIfyfq5LEhcea27oPXnZb0L+79TlBS1X+f1c888v6LOG9+9e5fr7WHZLftrpYh9XU1NDV5eXli+fDmuXbuGDx8+YMuWLXB0dMTHjx/Ru3dvpd1Ox0QTUSljbW2NLl26AJB24vfw4cM8zyvLlDs7O4snhLL+e7Ijaxlibm6eY18PRUV2X/qLFy9yLHPlypV81Wlubo7hw4fjl19+ASBtEZaXzsJLwvbKiaxT8JSUFFhYWKB9+/Z5mk+23S0tLXNsQp255dDnZMnQ4rxiNXv2bFy+fBl6enr4559/xM/5559/xoULF4otDiJSXdWqVcOff/4p9p2TuaNuIG/fjbJ+gc6cOYOMjIxsy4SEhIg/uOrVqyeOr127NgDpD5tnz55lO298fLzY/09BZT4259RheG7HCGXL3PdSThetoqOj5fpyKkk0NTXFvq8OHDiQ7/kzb5/4+Phsyzx69OiLCY3syB5GcuLEiVwvJn4uc39lOf3/ZO6/qDDrnblj9M8pswXJl8jif/nyZY6/D9LT08X1y2m/fvHiBZ48eZLttLi4OPH7Q7Y82TxAwc8bZdLS0nD+/PlspwmCgLNnz2ZZdlEp7Lms7DgQERGhsD6lDA0N0bt3b7Gz/8jISKXdocFEE1Ep9PPPP8PAwACJiYno3LnzF688fPz4EV26dBFPpiQSCXr06AEAWLt2bbZXGF6/fo21a9cCAHr16qXgNfiyGjVqiHFkl1CKiooSO37+nKxfgpxkfupbTh2tZlYStldOvvvuO0yaNAkTJkzAb7/9Bk1NzTzNJ3tCjezJTJ97+fIlfv/99xznl3Uemvk+/aJ05swZLFy4EACwbNkyuLm54ccff4S3tzfS09PRp0+fQndYTkQkk9fjzOfHmLx8N/bs2ROA9Mp9Tk/MlD0RysLCQu4hFa1atRKXMX/+/GznXbZsmVy/NAWR+Slmt27dyjI9Li4OP//8c6GWUZS6dOkCDQ0NJCUliRclPjd//nwkJydDU1NTvMBXkgwbNgwAcPjwYRw+fDjXsp8/hKRLly5QV1dHYmIiFi9enO08c+bMKVBcAwYMgLq6Ot6/f4/Zs2fneb7MnZLn9P+jr6+P3r17AwB++eUXhIeH51rn5+stO9e7cOECAgMDs5RPTEzEr7/+mueYi1vLli3F2+5yuhVy7dq1YovH3M5Xc2oNvmTJEiQmJkJDQ0Pu/6Kw542ZzZs3L9sk+4YNG8SEluyzKkqFPZdt1qyZ2Kn6uHHjvtjyKPP++KWy+f0tUxSYaCIqhSpWrIhNmzZBS0sL9+7dQ82aNfHLL7/g8ePHYpn09HTcvHkTs2bNQrly5bB37165On766SeYmJjgw4cP8PT0FJvAA9J+bTw9PREdHQ0zM7McH/1blL799luxo8j+/fvj2rVrEAQBGRkZCAwMhIeHR45Xerdv346GDRti7dq1ePr0qTg+PT0dx44dE9fH3d09z08j+9q3V040NTWxaNEiLF68GH369MnzfI0aNYK+vj4EQUD37t3FK2Oybejh4ZFrPwtVq1YFAMTGxmLnzp2FW4kveP/+Pfr27YuMjAx07txZPLkGAH9/f9ja2iI8PFx8qgcRUWF17NgRgwYNwpEjR+R+hHz48AE///yz2PpV9jhvGdl34+HDh3O8SFS/fn3xB9wPP/yAlStXiomhiIgIDB06FLt27QIg/TGY+cld+vr64mPd//zzT0yePFn88RIXF4dffvkFvr6+hX4Sp5ubGxwdHQFIW85mbiEVFBQEDw+Przq5X6ZMGfz4448AgIULF2L27Nni5xgdHY2ZM2eKCYXx48fnqW/Dr833338PT09PCIKATp064eeff5a7pTIhIQFnzpyBj49Plqf6lSlTBj4+PgCk+9iCBQsQFxcHQNrh/OjRo7F582a5hGNeubi4YNKkSQCARYsWYciQIXj06JE4PTY2Fjt27ECnTp3k5qtYsaLYWmn9+vU5tjKZP38+7Ozs8O7dO7i7u2PTpk1i7LL49+zZg06dOmVJtHTp0kVsFSh7sIisn50HDx6gTZs2Yof7XyNdXV0xwbRt2zaMGDFCTPp8+vQJv//+O8aOHQtAmqjJ6emTxsbG2LBhA3788Uex8+64uDjMnz9fTDD6+PjIPXSgsOeNMnp6erhw4QJ69+4ttphLSkrCunXrMHLkSABAhw4dcnxapSLJvq/v3bsnd96fVxoaGlizZg00NDRw4cIFNGnSBKdOnZLru+/p06dYs2YN6tWrh1WrVonjL126hOrVq2PZsmV48OCB+JtHEARcunRJ3Bb29vaoXr16YVaz4AQiKrUuXLgguLi4CADEl5aWlmBmZiaoqamJ4yQSidCrVy8hJSVFbv7AwEDB2NhYLKevry/o6+uL701MTIRz585lWW5YWJhYJiwsLMf4nJycBACCv79/lmlNmzYVAAizZ8/Ocf6jR48Kmpqa4rL09PQEHR0dAYBQoUIFYdu2beK0zPz9/eW2iba2tmBubi63Tezs7IQHDx7IzXfmzJls6/satteXyOrP77yyz6F///5Zpq1evVpuOxoYGIjb38LCQti/f3+u69WiRQtxuqGhoeDk5CQ4OTkJy5YtE8v0798/x+Vnlts2bN++vQBAcHBwED58+JBl3hMnTggSiUQAIKxbty4PW4WISrLZs2fn+l2eWebvlvwcq2TjZS8jIyPByMhIblzXrl2F9PR0ufkePnwofo+qqakJ1tbW4nfjixcvxHLR0dFyy9DQ0BBMTU3F7zIAwsSJE7Ndp9TUVKFr165iOTU1NcHU1FRQV1cXAAh9+/YV+vXrJwAQhg8fnmX+vB6LDhw4IGhoaMgdo/X09MTj48mTJ8VpZ86ckZv3S8dbQfjfsdzJySnHMrLPumnTprnGmp3k5GShe/fuWbZT5nOF7M6dBCHvx/Xc5Gc/LeiyY2JihHbt2mXZV01MTOT2JQ0NjSzzJiYmCp6enmIZdXV1uX1wypQpuZ7L5bYfpaWlCT4+PlnOMTLXb2xsnGW+wYMHy+1vjo6OgpOTkzBhwgS5cvfv3xcqVqwo99mamZnJnbMBEDw9PbMs48mTJ4KDg4PcOaTs3E9LS0v4999/c9yv80I2b27nv9nJ6/mSIAjCuHHj5H4DmJqayv2vNmvWTIiNjc0yX+b/p8mTJ8vNL/v+kG23xMTELPMX5rwx8//7ypUrxf3A1NRU7rdAjRo1hHfv3mVZdm7fFwWdlpqaKri6uorLNjU1Fb+vd+3aJZb70mezb98+wdDQUKxHU1NTMDc3F7S1teW2188//yzOk/k7MvM8mT9HIyOjbH93FBe2aCIqxRo2bIiQkBBs27YNffr0gYuLC3R0dBAXFwczMzM0atQI06dPx4MHD7B169Yst001bdoUDx48wIQJE+Dm5oaMjAwIggA3NzdMnDgRDx48QOPGjZW0doCXlxfOnz+Pdu3awdTUFOnp6XBwcMDUqVNx/fp1uU4fM2vfvj02btyIgQMHokaNGjA2NkZMTAwMDQ1Rv359zJ07F/fu3UOlSpXyFc/Xvr0UbcSIETh06BA8PDxgYGCAtLQ0lClTBj/88ANu3bqFatWq5Tr/7t27MW7cOFSsWBGpqal4/vw5nj9/rtDb6f744w/s378fampq2Lx5c7ZX6T09PcWrp2PHjsWDBw8UtnwiUk0rVqzAL7/8grZt26JChQoQBAGJiYmws7ND+/btsWfPHuzatSvLLQ0VKlTAmTNn0L59e1haWuL9+/fid2NaWppYztjYGKdOncJff/0FDw8PGBoaIj4+HjY2NujSpQvOnDmT4y08Ghoa2LlzJ9avX4/69etDV1cXaWlpqFu3LtavX4+NGzeK38MmJiYF3gbt2rXDuXPn4O3tDRMTE6SlpcHCwgIDBw7E9evX0aJFiwLXXRy0tLSwY8cO7N69G23atIG5uTni4uJgbm6ONm3aYO/evdmeO5UkRkZGOHDgAA4fPowePXrA0dERycnJ+PTpE8qUKYNWrVphwYIFCA0NzTKvjo4Ojhw5guXLl6NmzZrQ0tKCIAho3Lgxdu7cKd6uXhDq6upYuXIlLly4gD59+sDR0RGpqakQBAGVK1fG4MGDsWfPnizz/fHHH/D19RXPP8LDw/H8+XOx1Y2Mm5sbbt++jbVr16JVq1awsLBAbGwsBEGAi4sLunXrhnXr1mXb4rpcuXIIDg7G+PHj4ezsDEEQoKOjg65du+LSpUt57utSmZYuXYrTp0+jS5cusLa2Rnx8PAwNDdGsWTP8/fffOHHiRJaOuj/3yy+/YPv27WjUqBEEQYCWlhZq1qyJ5cuX4+jRo3ItKWUKe94o4+Pjg2PHjqF169ZQU1ODmpoaKlWqhDlz5iAoKCjXp/IpkoaGBk6dOoUhQ4bA2dkZCQkJ4vd1Tn2XZadjx454/PgxZs+ejfr168PAwADR0dHQ1tZGjRo1MGTIEOzbt088VwWk/Wft3LkTI0eORJ06dcR9WEdHBzVr1sTkyZOV/rtDIggq8OxAIiIiIiL6IkEQ4OjoiJcvX2Ljxo3o27evskMiIqIShi2aiIiIiIgIALBp0ya8fPkSGhoach2JExER5RUTTUREREREKqRXr17YvXu33C1FkZGRWLhwofhghH79+pXITq6JiEj5eOscEREREZEKMTExQUxMDADpU5w0NTXF9wDQuHFjHDx4UO6R8URERHnFRBMRERERkQrZuHEjjhw5gps3byIqKgrx8fEwMTFBzZo10bNnT/Tt27dEd3JNRETKxUQTEREREREREREpBPtoIiIiIiIiIiIihWCiiYiIiIiIiIiIFIKJJiIiIiIiIiIiUggmmoiIiIiIiIiISCGYaCIiIiIiIiIiIoVgoomIiIiIiIiIiBSCiSYiIiIiIiIiIlIIJpqIiIiIiIiIiEghmGgiIiIiIiIiIiKFYKKJiIiIiIiIiIgUgokmIiIiIiIiIiJSCCaaiIiIiIiIiIhIIZhoIiIiIiIiIiIihWCiiYiIiIiIiIiIFEJD2QHQ1y8jIwOvX7+GoaEhJBKJssMhIiKCIAiIi4uDnZ0d1NR43ay04jkIERHR1yE/515MNNEXvX79Gg4ODsoOg4iIKIsXL17A3t5e2WFQEeE5CBER0dclL+deTDTRFxkaGgIAtCr3h0RdS8nREJV8RzbNVHYIRCVeQnwcvmtURTxGUekk+3xfvHgBIyMjJUdDlA/BwUDTpsDZs0DNmsqOhoio0GJjY+Hg4JCncy8mmuiLZE3VJepaTDQRKYCBIX8sESkKb6cq3WSfr5GRERNNVLIYGPxvyH2XiEqRvJx7sVMDIiIiIiIiRdLQACwspEMiIhXDbz4iIiIiIiJFql4dePtW2VEQESkFWzQREREREREREZFCsEUTERERERGRIt27B3ToAPz7L1ClirKjoUJIT09HamqqssMgKnKamppQV1dXSF1MNBERERERESlScjLw5Il0SCWSIAiIiIhAdHS0skMhKjYmJiawsbEp9MNWmGgiIiIiIiIiykSWZLKysoKenh6fckqlmiAI+PTpE6KiogAAtra2haqPiSYiIiIiIiKi/5eeni4mmczNzZUdDlGx0NXVBQBERUXBysqqULfRsTNwIiIiIiIiov8n65NJT09PyZEQFS/ZPl/YfsmYaCIiIiIiIlIkFxfg6FHpkEos3i5HqkZR+zwTTURERERERIpkZAR4eUmHRPTVk0gk+OeffwpVh6+vL2rWrJlrmQEDBqBjx47iew8PD4wdO1Z8X7ZsWfz222+FXo6ysY8mIiIiIiIiRXrzBli7Fhg+HChkp7r0dXn79i1iY2OLbXlGRkawtLTMc/kBAwYgOjq60EmT3Hh4eODs2bMAAG1tbTg6OmLgwIGYOnVqkbcCy1y/kZERqlatirlz56J58+ZFulxFWb58OQRByHH61atXoa+vL76XSCTYt2+fXHJq4sSJ+OGHH4oyzEJjoomIiIiIiEiR3rwB/PyA9u2ZaCpF3r59i+8HDsGHuE/FtkwzQz1s9l+fr2RTcRg6dCjmzJmD5ORknD59GsOGDYOJiQlGjhxZ5Mv29/dH69at8e7dO0yfPh3t2rXD3bt3Ua5cuSxlU1NToampWeQx5ZWxsXGu0/PyORsYGMDAwEBRIRUJ3jpHRERERERE9AWxsbH4EPcJlu5dUNZ7VJG/LN274EPcJ4W2oDp79izq168PbW1t2NraYurUqUhLSxOnx8XFoU+fPtDX14etrS2WLVuW5fYuQNpptI2NDZycnDBw4EBUr14dJ06cEKcnJydj4sSJKFOmDPT19dGgQQMEBgbK1fHnn3/CwcEBenp66NSpE5YuXQoTE5MvroOJiQlsbGxQtWpVrF69GomJieKyJRIJVq9ejfbt20NfXx/z5s0DAKxevRrly5eHlpYWXF1dsWnTpiz1vnnzBm3atIGuri7KlSuH3bt3y02fMmUKKlasCD09PZQrVw4zZ87MttPstWvXiuvVvXt3xMTEiNM+v3Xuc5lvnStbtiwAoFOnTpBIJOL77G6dW79+Pdzc3KCjo4NKlSph1apV4rSUlBSMHj0atra20NHRgZOTExYsWJBjDIrAFk1EREREREREeaRvZg0jK/tiWdZbBdb16tUrtG3bFgMGDMDGjRsREhKCoUOHQkdHB76+vgCA8ePH4+LFi9i/fz+sra0xa9Ys3LhxI8c+gQRBwIULFxASEoIKFSqI40ePHo379+9j+/btsLOzw759+9C6dWvcuXMHFSpUwMWLFzFixAj88ssvaN++PU6ePImZM2fme510dXUBSJMpMr6+vli4cCF+++03aGhoYN++ffjxxx/x22+/wdPTEwcPHsTAgQNhb2+PZs2aifPNnDkTCxcuxPLly7Fp0yb07NkTd+7cgZubGwDA0NAQAQEBsLOzw507dzB06FAYGhpi8uTJYh2PHz/Gzp07ceDAAcTGxmLw4MEYNWoUtmzZku91u3r1KqysrMQWXOrq6tmW27JlC2bNmoWVK1eiVq1auHnzJoYOHQp9fX30798fv//+O/bv34+dO3fC0dERL168wIsXL/IdT34w0URERERERERUyq1atQoODg5YuXIlJBIJKlWqhNevX2PKlCmYNWsWEhISsGHDBmzduhUtWrQAIL1Nzc7OLtu61q9fj5SUFKSmpkJHRwdjxowBAISHh8Pf3x/h4eHivBMnTsTRo0fh7++P+fPnY8WKFWjTpg0mTpwIAKhYsSIuXbqEgwcP5nl9Pn36hBkzZkBdXR1NmzYVx/fu3RsDBw4U3/fq1QsDBgzAqFGjAEiTaZcvX8bixYvlEk3dunXDkCFDAABz587FiRMnsGLFCrF10IwZM8SyZcuWxcSJE7F9+3a5RFNSUhI2btyIMmXKAABWrFgBb29vLFmyBDY2NnleN+B/t9HJWnDlZPbs2ViyZAk6d+4MAHB2dsb9+/exdu1a9O/fH+Hh4ahQoQIaNWoEiUQCJyenfMVREEw0ERERERERKZKpKdCnj3RI9JV48OAB3N3d5TrUbtiwIeLj4/Hy5Ut8/PgRqampqF+/vjjd2NgYrq6uWerq06cPpk+fjo8fP2L27Nn49ttv8e233wIA7ty5g/T0dFSsWFFunuTkZJibmwMAQkND0alTJ7np9evXz1OiqVevXlBXV0diYiIsLS3x119/oXr16uL0unXrZlnvYcOGyY1r2LAhli9fLjfO3d09y/vg4GDx/Y4dO/D777/jyZMniI+PR1paGow+e7Kko6OjmGSS1ZGRkYHQ0NB8J5ryIiEhAU+ePMHgwYMxdOhQcXxaWprYH9SAAQPQsmVLuLq6onXr1mjXrh1atWql8FgyY6KJiIiIiFROUT05Kr9PiKJSytkZ2LxZ2VEQFRljY2O4uLgAAHbu3AkXFxd888038PT0RHx8PNTV1XH9+vUst3spohPrZcuWwdPTE8bGxtl+32Z+apuiBAUFoU+fPvDz84OXlxeMjY2xfft2LFmyROHLyo/4+HgA0v6uGjRoIDdNtu1r166NsLAwHDlyBCdPnkT37t3h6emZpQ8qRWKiiYiIiIhUSlE+OeprfUIUFbOkJODlS8DeHtDRUXY0RAAANzc37NmzB4IgiK2aLl68CENDQ9jb28PU1BSampq4evUqHB0dAQAxMTF4+PAhmjRpkmO9BgYG+PHHHzFx4kTcvHkTtWrVQnp6OqKiotC4ceNs53F1dcXVq1flxn3+Pic2NjZikisv3NzccPHiRfTv318cd/HiRVSuXFmu3OXLl9GvXz+597Vq1QIAXLp0CU5OTpg+fbo4/fnz51mWFR4ejtevX4u3DF6+fBlqamrZtgrLC01NTaSnp+c43draGnZ2dnj69Cn69OmTYzkjIyP06NEDPXr0QNeuXdG6dWt8+PABZmZmBYrrS5hoIiIiIiKVkvnJUfpm1gqrN+FDJN4G7UFsbCwTTaru/n2gTh3g+nWgdm1lR0MqJiYmRu6WLwAwNzfHqFGj8Ntvv+GHH37A6NGjERoaitmzZ2P8+PFQU1ODoaEh+vfvj0mTJsHMzAxWVlaYPXs21NTU5G63y87w4cMxd+5c7NmzB127dkWfPn3Qr18/LFmyBLVq1cLbt29x6tQpVK9eHd7e3vjhhx/QpEkTLF26FN999x1Onz6NI0eOfHE5BTFp0iR0794dtWrVgqenJw4cOIC9e/fi5MmTcuV27dqFunXrolGjRtiyZQv+++8//PXXXwCAChUqIDw8HNu3b0e9evVw6NAh7Nu3L8uydHR00L9/fyxevBixsbEYM2YMunfvXuDb5sqWLYtTp06hYcOG0NbWhmk2t+P6+flhzJgxMDY2RuvWrZGcnIxr167h48ePGD9+PJYuXQpbW1vUqlULampq2LVrF2xsbPL0hL+CYqKJiIiIiFRSUTw5SpFPiCKir1PCh8ivejmBgYFiSxyZwYMHY/369Th8+DAmTZqEGjVqwMzMDIMHD5br5Hrp0qUYMWIE2rVrByMjI0yePBkvXryAzhda5pmZmaFfv37w9fVF586d4e/vj59//hkTJkzAq1evYGFhgW+++Qbt2rUDIO0jac2aNfDz88OMGTPg5eWFcePGYeXKlQVa59x07NgRy5cvx+LFi/Hjjz/C2dkZ/v7+8PDwkCvn5+eH7du3Y9SoUbC1tcW2bdvEVk/t27fHuHHjMHr0aCQnJ8Pb2xszZ84Un9Yn4+Ligs6dO6Nt27b48OED2rVrJ3YmXhBLlizB+PHj8eeff6JMmTJ49uxZljJDhgyBnp4efv31V0yaNAn6+vqoVq0axo4dC0D6tLxFixbh0aNHUFdXR7169XD48GGoqakVOK4vkQiCIBRZ7VQqxMbGwtjYGNrVhkKirqXscIhKvHN75ik7BKISLz4uFs1rOiImJiZLR5xUesjOQRT9OT958gQ9B41AWe9RCk00xUa9xLNDq7D97zUoX768wuqlEujGDbZoKsGSkpIQFhYGZ2dnuQRLUd52mxNl346bkJCAMmXKYMmSJRg8eHCRLmvo0KEICQnB+fPni3Q5lLOc9n0gf8dktmgiIiIiIiIi+gJLS0ts9l9fJA8SyElxP2Dg5s2bCAkJQf369RETE4M5c+YAADp06KDwZS1evBgtW7aEvr4+jhw5gg0bNhSq9Q99PZhoIiIiIiIiIsoDS0vLUt8H2+LFixEaGgotLS3UqVMH58+fh4WFhcKX899//2HRokWIi4tDuXLl8Pvvv2PIkCEKXw4VPyaaiIiIiIiIFKl2bYA9lFAJVKtWLVy/fr1YlrVz585iWQ4Vv6Lr/YmIiIiIiIiIiFQKE01ERERERESKFBoKuLtLh0REKoaJJiIiIiIiIkVKSAAuX5YOiYhUDBNNRERERERERESkEEw0ERERERERERGRQjDRRERERERERERECsFEExERERERkSKVLQts2iQdEn1FAgMDIZFIEB0dXazLDQgIgImJSaHqePbsGSQSCYKDg3Mso6z1I3lMNBERERERESmSmRnw/ffSIVExkUgkub58fX2VHeJX6/bt22jcuDF0dHTg4OCARYsW5Vr+/fv3aN26Nezs7KCtrQ0HBweMHj0asbGxYhlZ0uvzV0RERFGvjtJpKDsAIiIiIiKiUuXtW2DnTqB7d8DSUtnRkIp48+aN+PeOHTswa9YshIaGiuMMDAxw7dq1fNebkpICLS0thcT4NYqNjUWrVq3g6emJNWvW4M6dOxg0aBBMTEwwbNiwbOdRU1NDhw4d8PPPP8PS0hKPHz+Gj48PPnz4gK1bt8qVDQ0NhZGRkfjeysqqSNfna8AWTURERERERIr04gUwerR0SFRMbGxsxJexsTEkEoncOAMDA7Hs9evXUbduXejp6eHbb7+VS0j5+vqiZs2aWL9+PZydnaGjowMAiI6OxpAhQ2BpaQkjIyM0b94ct27dEue7desWmjVrBkNDQxgZGaFOnTpZElvHjh2Dm5sbDAwM0Lp1a7nkWEZGBubMmQN7e3toa2ujZs2aOHr0aK7rfPjwYVSsWBG6urpo1qwZnj17lu/ttmXLFqSkpODvv/9GlSpV0LNnT4wZMwZLly7NcR5TU1OMHDkSdevWhZOTE1q0aIFRo0bh/PnzWcpaWVnJfQ5qaqU/DVP615CIiIiIiIiIRNOnT8eSJUtw7do1aGhoYNCgQXLTHz9+jD179mDv3r1in0jdunVDVFQUjhw5guvXr6N27dpo0aIFPnz4AADo06cP7O3tcfXqVVy/fh1Tp06FpqamWOenT5+wePFibNq0CefOnUN4eDgmTpwoTl++fDmWLFmCxYsX4/bt2/Dy8kL79u3x6NGjbNfhxYsX6Ny5M7777jsEBwdjyJAhmDp1apZyEokEAQEBOW6LoKAgNGnSRK7VlpeXF0JDQ/Hx48cvbksAeP36Nfbu3YumTZtmmVazZk3Y2tqiZcuWuHjxYp7qK+mYaCIiIiJSIatXr0b16tVhZGQEIyMjuLu748iRI+J0Dw+PLP1JjBgxQq6O8PBweHt7Q09PD1ZWVpg0aRLS0tLkygQGBqJ27drQ1taGi4tLrif5REQlxps3wI0b8q+wMOm0pKSs027c+N+8oaFZp/1/kgZv32adlkOCRRHmzZuHpk2bonLlypg6dSouXbqEpKQkcXpKSgo2btyIWrVqoXr16rhw4QL+++8/7Nq1C3Xr1kWFChWwePFimJiYYPfu3QCkxwZPT09UqlQJFSpUQLdu3VCjRg2xztTUVKxZswZ169ZF7dq1MXr0aJw6dUqcvnjxYkyZMgU9e/aEq6srfvnlF9SsWRO//fZbtuuwevVqlC9fHkuWLIGrqyv69OmDAQMGZCnn6uoKY2PjHLdFREQErK2t5cbJ3n+pP6VevXpBT08PZcqUgZGREdavXy9Os7W1xZo1a7Bnzx7s2bMHDg4O8PDwwI3M+0QpxT6aiIiIiFSIvb09Fi5ciAoVKkAQBGzYsAEdOnTAzZs3UaVKFQDA0KFDMWfOHHEePT098e/09HR4e3vDxsYGly5dwps3b9CvXz9oampi/vz5AICwsDB4e3tjxIgR2LJlC06dOoUhQ4bA1tYWXl5exbvCRESKtHYt4OcnP65PH2DzZuDlS6BOnazzCIJ0OGAAcPmy/LRNm6Qdx+/cKb3dMrNWrYBjxxQWembVq1cX/7a1tQUAREVFwdHREQDg5OQEy0z9i926dQvx8fEwNzeXqycxMRFPnjwBAIwfPx5DhgzBpk2b4OnpiW7duqF8+fJiWT09Pbn3tra2iIqKAiDtJ+n169do2LChXP0NGzaUuz0vswcPHqBBgwZy49zd3bOUCwkJyWErFN6yZcswe/ZsPHz4ENOmTcP48eOxatUqANIEl6urq1j222+/xZMnT7Bs2TJs2rSpyGL6GjDRRERERKRCvvvuO7n38+bNw+rVq3H58mUx0aSnpwcbG5ts5z9+/Dju37+PkydPwtraGjVr1sTcuXMxZcoU+Pr6QktLC2vWrIGzszOWLFkCAHBzc8OFCxewbNkyJppINRgaSpMEhobKjoQUbfhwoH17+XGmptKhvT1w/XrO8wYEAAkJ8uPKlpUOu3cHPk+SFOH+k/mWNolEAkDaR5KMvr6+XPn4+HjY2toiMDAwS10mJiYApH079e7dG4cOHcKRI0cwe/ZsbN++HZ06dcqyTNlyBVkSTolsbGwQGRkpN072PqdjYeZ5bWxsUKlSJZiZmaFx48aYOXOmmLz7XP369XHhwgXFBP4VY6KJiIiISEWlp6dj165dSEhIkLsKvGXLFmzevBk2Njb47rvvMHPmTLFVU1BQEKpVqyZ3m4GXlxdGjhyJe/fuoVatWggKCoKnp6fcsry8vDB27Nhc40lOTkZycrL4PvNjoolKlAoViqwlCimZra30lR0dHaB27ZznzdS6JQtLy6/6CYW1a9dGREQENDQ0UFaWHMtGxYoVUbFiRYwbNw69evWCv7+/mGjKjZGREezs7HDx4kW5fo4uXryI+vXrZzuPm5sb9u/fLzfu8uctxvLA3d0d06dPR2pqqpgMO3HiBFxdXWEqSyLmgSxRl/k49rng4OAck1ClCftoIiIiIlIxd+7cgYGBAbS1tTFixAjs27cPlStXBgD07t0bmzdvxpkzZzBt2jRs2rQJ33//vThvXvqyyKlMbGwsEhMTc4xrwYIFMDY2Fl8ODg4KWV+iYpeeDsTGSodEpYCnpyfc3d3RsWNHHD9+HM+ePcOlS5cwffp0XLt2DYmJiRg9ejQCAwPx/PlzXLx4EVevXoWbm1uelzFp0iT88ssv2LFjB0JDQzF16lQEBwfjxx9/zLb8iBEj8OjRI0yaNAmhoaHYunVrtv0BVqpUCfv27ctxub1794aWlhYGDx6Me/fuYceOHVi+fDnGjx8vltm3bx8qVaokvj98+DD8/f1x9+5dPHv2DIcOHcKIESPQsGFDMRH322+/4d9//8Xjx49x9+5djB07FqdPn4aPj0+et0lJxRZNRERERCrG1dUVwcHBiImJwe7du9G/f3+cPXsWlStXxrBhw8Ry1apVg62tLVq0aIEnT57I9a1RFGT9W8jExsYy2UQl061b0r56rl/PvYULUQkhkUhw+PBhTJ8+HQMHDsTbt29hY2ODJk2awNraGurq6nj//j369euHyMhIWFhYoHPnzvD7vD+rXIwZMwYxMTGYMGECoqKiULlyZezfvx8VKlTItryjoyP27NmDcePGYcWKFahfvz7mz5+f5Ql6oaGhiImJyXG5xsbGOH78OHx8fFCnTh1YWFhg1qxZcsfDmJgYhIaGiu91dXXx559/Yty4cUhOToaDgwM6d+4s99S7lJQUTJgwAa9evYKenh6qV6+OkydPolmzZnneJiWVRPgaboqkr1psbCyMjY2hXW0oJOpaX56BiHJ1bs88ZYdAVOLFx8WieU1HxMTEwMjISNnhlHienp4oX7481q5dm2VaQkICDAwMcPToUXh5eWHWrFnYv3+/+LhrQNr5d7ly5XDjxg3UqlULTZo0Qe3ateWeFOTv74+xY8fmerL/Odk5iKI/5ydPnqDnoBEo6z0KRlb2Cqs3Nuolnh1ahe1/rynypBx95W7cYKKpBEtKSkJYWBicnZ2ho6Oj7HCIik1u+35+jsm8dY6IiIhIxWVkZOTYp4QsoSTrU8Ld3R137twRnxQESPuyMDIyEm+/c3d3l3tktaxMdk8DIiIiotKFt84RERERqZBp06ahTZs2cHR0RFxcHLZu3YrAwEAcO3YMT548wdatW9G2bVuYm5vj9u3bGDduHJo0aSI+CrtVq1aoXLky+vbti0WLFiEiIgIzZsyAj48PtLW1AUj7zVi5ciUmT56MQYMG4fTp09i5cycOHTqkzFUnIiKiYsBEExEREZEKiYqKQr9+/fDmzRsYGxujevXqOHbsGFq2bIkXL17g5MmT+O2335CQkAAHBwd06dIFM2bMEOdXV1fHwYMHMXLkSLi7u0NfXx/9+/fHnDlzxDLOzs44dOgQxo0bh+XLl8Pe3h7r16+Hl5eXMlaZiIiIihETTUREREQq5K+//spxmoODA86ePfvFOpycnHD48OFcy3h4eODmzZv5jo+oVKhWDYiKAkxMlB0JEVGxY6KJiIiIiIhIkTQ1AUtLZUdBRKQU7AyciIiIiIhIkZ48Adq3lw6pxOID2knVKGqfZ6KJiIiIiIhIkWJigAMHpEMqcTQ1NQEAnz59UnIkRMVLts/L/gcKirfOEREREREREf0/dXV1mJiYICoqCgCgp6cHiUSi5KiIio4gCPj06ROioqJgYmICdXX1QtXHRBMRERERERFRJjY2NgAgJpuIVIGJiYm47xcGE01EREREREREmUgkEtja2sLKygqpqanKDoeoyGlqaha6JZMME01ERERERESKVKYMsGSJdEglmrq6usJ+fBOpCiaaiIiIiIiIFMnaGhg/XtlREBEpBZ86R0REREREpEgfPwK7dkmHREQqhokmIiIiIiIiRQoLA7p3lw6JiFQME01ERERERERERKQQTDQREREREREREZFCMNFEREREREREREQKwUQTERERERGRIunqArVqSYdERCpGQ9kBEBERERERlSpubsCNG8qOgohIKdiiiYiIiIiIiIiIFIKJJiIiIiIiIkW6eRPQ1pYOiYhUDBNNREREREREiiQIQEqKdEhEpGKYaCIiIiIiIiIiIoVgoomIiIiIiIiIiBSCiSYiIiIiIiIiIlIIDWUHQEREREREVKq4uQF37wLlyik7EiKiYsdEExERERERkSLp6gJVqig7CiIipeCtc0RERERERIr0/DkwZIh0SESkYphoIiIiIiIiUqT374G//pIOiYhUDBNNRERERERERESkEEw0ERERERERERGRQjDRRERERERERERECsFEExERERERkSJZWwNTp0qHREQqRkPZARAREREREZUqZcoACxYoOwoiIqVgiyYiIiIiIiJFiosDAgOlQyIiFcNEExERERERkSI9egQ0ayYdEhGpGCaaiIiIiIiIiIhIIZhoIiIiIiIiIiIihWCiiYiIiIiIiIiIFIKJJiIiIiIiIkXS1JQ+eU5TU9mREBEVOw1lB0BERERERFSqVKsGvHyp7CiIiJSCLZqIiIiIiIiIiEghmGgiIiIiIiJSpDt3AHt76ZCISMUw0URERERERKRIqanAq1fSIRGRimGiiYiIiIiIiIiIFIKJJiIiIiIiIiIiUggmmoiIiIiIiIiISCGYaCIiIiJSIatXr0b16tVhZGQEIyMjuLu748iRI+L0pKQk+Pj4wNzcHAYGBujSpQsiIyPl6ggPD4e3tzf09PRgZWWFSZMmIS0tTa5MYGAgateuDW1tbbi4uCAgIKA4Vo/o61ChAnDmjHRIRKRimGgiIiIiUiH29vZYuHAhrl+/jmvXrqF58+bo0KED7t27BwAYN24cDhw4gF27duHs2bN4/fo1OnfuLM6fnp4Ob29vpKSk4NKlS9iwYQMCAgIwa9YssUxYWBi8vb3RrFkzBAcHY+zYsRgyZAiOHTtW7OtLpBSGhoCHh3RIRKRiNJQdABEREREVn++++07u/bx587B69WpcvnwZ9vb2+Ouvv7B161Y0b94cAODv7w83NzdcvnwZ33zzDY4fP4779+/j5MmTsLa2Rs2aNTF37lxMmTIFvr6+0NLSwpo1a+Ds7IwlS5YAANzc3HDhwgUsW7YMXl5exb7ORMXu1Stg5Upg9GigTBllR0NEVKzYoomIiIhIRaWnp2P79u1ISEiAu7s7rl+/jtTUVHh6eoplKlWqBEdHRwQFBQEAgoKCUK1aNVhbW4tlvLy8EBsbK7aKCgoKkqtDVkZWB1GpFxkJLFwoHRIRqRi2aCIiIiJSMXfu3IG7uzuSkpJgYGCAffv2oXLlyggODoaWlhZMTEzkyltbWyMiIgIAEBERIZdkkk2XTcutTGxsLBITE6Grq5ttXMnJyUhOThbfx8bGFmo9iYiIqPgx0URUzHq1a4BVs/vmWubs1VB0HLUCAFC1Yhl08qyNGpUcUaOSPSxMDXHh+iN8N2J5jvPraGtiUJfG6N6mHpzszCGRAC/efMA/J2/iz51nEZuQlGWerl51MaRbY1SpYA+JBAgNi8D6Xeew7eCVwq0wURE6fjYYtx48w8Onr/D0eSRS09IxzacL2jSvneM8ryM/YPPes7ga/BgfouNgoK+DsvZW6Ni6AZp9W02ubHJyKv45dgXHzwXjTdRHQACsLU3Q7Nuq6NzGHQb6OnLl/9p2EndDwxH++h1i4hKgq60FGysTtGxcE+1b1YOOtlaRbAei/HJ1dUVwcDBiYmKwe/du9O/fH2fPnlV2WFiwYAH8/PyUHQYREREVAhNNRMXszsOXWLjucLbTOrSoCbfydjgd9EAc5920BsYP9EJySiqehL+FhWnunUpqqKth/+oxqFfNGbdDX2DrwcsAgMZ1K2LGqO/QxasOWvT/FYnJqeI8c8d2wug+LRDxLga7j15Falo6WjasglWz+8KtvB1mLd+ngDUnUrz1204g4m00jI30YG5qiIi30bmWv3rrMab/shkA8G3dSrCzNkNcfCKePI/AtdtP5BJNaWnp+HH2X7j/6AUqONuiTTNp8urm3adYv+0kTl24jbW/jJRLHu09ehn2tuaoV8MFpsb6+JSYjOB7YVgZcBhHA29g1fzhTDbRV0FLSwsuLi4AgDp16uDq1atYvnw5evTogZSUFERHR8u1aoqMjISNjQ0AwMbGBv/9959cfbKn0mUu8/mT6iIjI2FkZJRjayYAmDZtGsaPHy++j42NhYODQ8FXlIiIiIodE01Exezuw1e4+/BVlvGaGuoY2r0JUtPSse3Q/1oR/XvqBo6cu437j1/DzEQfoUcX5Fp/u2Y1UK+aMw6cCUa/yevlpm3+dSi8PWqgfYta2HFY+iOhppsjRvdpgSfhUfAcuBjRsZ8AAHor/sX+NWPww/ctcOB0MK7eCSvsqhMp3OSRnWBvaw4bK1Ns3nsW67Ycz7Fs5NtozFq8FRZmRlg2exCsLU3kpqelp8u9P3flPu4/eoHGDSpj3uQ+ctN+WrgZF64+QGDQPbT2qCWO3/vnFGhraWZZ9s/Ld+H4uWAcPn0Dndt8U4A1JSpaGRkZSE5ORp06daCpqYlTp06hS5cuAIDQ0FCEh4fD3d0dAODu7o558+YhKioKVlZWAIATJ07AyMgIlStXFsscPix/UeXEiRNiHTnR1taGtra2olePqPiZmwODB0uHREQqRqU7A/f19YVEIoFEIoGamhqMjY1RrVo1jB49Gg8ePPhyBQVQtmxZjB49Wnw/YMAAVK1atUiWlZOOHTvCw8OjWJdJX+btUR3mJgY4dv4u3n6IE8eHPI3A7dCXSEvPyFM9ZctYAABOXrqfZdrxi9JOWi1MDcRxbZtKW3Cs3nZGTDIBwKekFCz5W/oY6oGdG+VzbYiKR90aLrCxMs1T2U17A5HwKRkThnfIkmQCAA11dbn3ryM/AAC+qVUxS1n3Oq4AgOjYBLnx2SWZAMDjW+n3/KuI93mKlagoTZs2DefOncOzZ89w584dTJs2DYGBgejTpw+MjY0xePBgjB8/HmfOnMH169cxcOBAuLu745tvpEnSVq1aoXLlyujbty9u3bqFY8eOYcaMGfDx8RGTRCNGjMDTp08xefJkhISEYNWqVdi5cyfGjRunzFUnKj5OTsD69dIhEZGKUfkWTbq6ujh9+jQAIC4uDnfu3MG6devw559/4q+//sL3339fpMufOXMmEhISvlyQSr2+Hb4FAGz691Kh6nnw5A0AwPPbytj4j3xdrRpWQUZGBs5feyiOszI3AgA8f531B3D4/49rUi/rD22ikkQQBAReugtjQz3UqVYeoU9eIfheGDIEARXK2qJ2tXJQU5O/9lLOUdqR8eWbD/Fdy3py04Kuh0IikaBWVec8LT/oeigAwNnB+gsliYpeVFQU+vXrhzdv3sDY2BjVq1fHsWPH0LJlSwDAsmXLoKamhi5duiA5ORleXl5YtWqVOL+6ujoOHjyIkSNHwt3dHfr6+ujfvz/mzJkjlnF2dsahQ4cwbtw4LF++HPb29li/fj28vLyKfX2JlCIxEXj6FChXDsjldlEiotJI5RNNampq4hU6AGjZsiVGjRoFb29vDB48GN9++y3KlStXZMsvX758kdVNJYeDjSma1nPFq8iPOBmUtSVSfhy7cBcHz9zCd81q4uzmKbhw/REAaR9NTnbmGDt/G26HvhTLf4iWJjqd7LI27Xb8/3FlrE2hq60p168TUUnyJvIjYuMTUal8Gfy65h8cOHFVbnoFZ1ssmNYXVubG4jj3Oq5oXN8N56/cx+CJK1GzijSpdPPuU7yJ+ohJIzrAtVyZbJe39Z9zSEpORXxCEu6GPEfIk1eoV8NF7jY7ImX566+/cp2uo6ODP/74A3/88UeOZZycnLLcGvc5Dw8P3Lx5s0AxEpV4Dx4AdeoA168DtXN+QAURUWmk0rfO5URHRwcrVqxASkoK1q//Xx83AQEBqF69OnR0dFCmTBlMnz4d6Z/16fHq1Sv069cP1tbW0NXVRaVKlbB8ec5PB/v81rmAgABIJBLcvHkTbdq0gb6+PipUqICNGzdmmffQoUNo0KABdHV1YWlpiZEjR2ZpHfXgwQM0bdoUOjo6KF++PDZs2FDQzUJFqPd37lBXV8PWg5eRkSEUur5+U9bjtw3HUbVCGYzq3RyjejdHtYr2OBh4C4FXQuTKnrwkvZ1uRM9mMDL43xU3XW1NjBvQSnyfeRpRSfMxNh4A8CjsDU6ev4VpPl1waMMM7Fg9Ed951sWjsDeY9es2uXkkEgnmTuqN3h2b4PGzCOw6eAm7Dl7C42cRaFy/MupWd8lxedv+OY+Anaex+9AlhDx5hVZNamLupN7Q0FDPcR4iIiIiotJA5Vs05aRy5cooU6YMgoKCAABLly7F5MmTMW7cOCxZsgQPHjwQE00LFy4EALx//17s5HLevHkoV64cHj16hCdPnuR7+X369MHQoUMxfvx4/PnnnxgwYADq1asHNzc3AMDu3bvRo0cPDBw4EH5+fnjz5g2mTp2Kjx8/Yvv27QCApKQktGrVCvr6+ti0aRMAYNasWYiNjUWFChUKvY1IMSQSCfp89w0yMjKwef/lQtenq62J9fMGok7VshgyIwCB/0lv2fGo74oFE7rC070yPAcuxos30v5nLt18gu2HrqCndwNc3jkDR8/d+f+nzlWGhro6YuI+wdhQDxlC4RNgRMoiS+CmZ2RgcC9PtGkuvbpsaKCLSSM74cnzSNx/9AK3HzxDdbeyAICk5BT4LduBB49eYta47mJi6drtx1jx9yFcufkQaxaOhG02fUQdCJgOAHj/MQ437j7Fmk3HMGLqGiyeNUCu1RQRERERUWnDRFMuHBwcEBERgbi4OMyePRuTJ0/G/PnzAUhvsdPS0sL48eMxadIkmJubY+nSpYiKikJISAjKli0LAGjevHmBlj169GiMGjUKAPDtt9/i0KFD2LNnD2bMmAFBEDBx4kT06NFDrsWVra0t2rZti5kzZ6JKlSoICAjA69evERISIiaWatWqBVdX11wTTcnJyUhOThbfx8bGFmgdKG886rvCwdYMgf+FiH0iFcb4gV5o27Q6ek9YiyPn7ojj9524gaTkVGxdMhwTBnlh7Lz/td4Y5bcZNx+Eo297d/Rq1wBJyak4ffkBZv/+Dy7tmI7UtHR8jGFfYlRyGejpiH83quuWZfq3dV1x/9ELhDx5JSaaNu05i4tXQzB/6vdoVO9/87RoWB1amhqY/ssWbNoTiMkjO+W4XHNTQ7RsXAP2tuYYPmU1/gg4Ar8JPRW3YkREREREXxkmmnIhCAIkEgkuXbqE+Ph4dOvWDWlpaeJ0T09PJCYm4u7du2jatClOnTqF5s2bi0mmwmjV6n+3LOnr68PJyQkvX0r71Xn48CGeP3+O3377TS6epk2bQk1NDdeuXUOVKlVw5coVVK1aVS6p5OLigho1auS67AULFsDPz6/Q60B5I3YC/k+QQurz/Fb6aOnMHX7LyPprql7RQW68IAhYt+Ms1u04KzfewdYMhvo6CH4Qnuen3hF9jexszKCupob0jAwY6OtkmW6gL701NCXlf9+pV25K/4dqV83aT59s3KOw13lavpuLPQwNdBF872m+YyciohJIIgG0tKRDIiIVwz6acvHy5UvY2Njg3bt3AIDatWtDU1NTfMkSOC9evAAgvXXOzs5OIcs2MTGRe6+lpYWkpCQAEOPp1KmTXDx6enpIT08X43nz5g2srKyy1G1tnftTj6ZNm4aYmBjxJauPFM/UWB9tm1bDh+gEHAy8pZA6tTSl+WNzU4Ms08xNpONSUvPWqXf31tInbe09fl0hsREpi7aWJqq4OgIAnr2MyjJdNs7G0kQcl5om7YMvOpvWfNGx0nGaGnm7XvMpMRkJn5Kgoc4+moiIVEKtWkBysnRIRKRi2KIpB/fu3cOrV68wYMAAmJmZAQD27t0LBweHLGWdnaVPIjI3N8fr13m7ul0YsnhWrlyJBg0aZJkuS3bZ2trixo0bWaZHRkbCyMgox/q1tbWhra2toGgpNz3a1oO2lib8915ASmral2fIgyu3nqKyix2mDGkLnzmbIfx/30pqahJMG94WAHD+2iO5eQz1dRCXkCQ3zr1meYwd0Arhr9/Df+8FhcRGpEwdverj9oNn8N9xGr9M7ycmZZ+/fIujZ25AT1cbDWpVFMtXq+SIsPBI+O86jWk+naGmJr02k56egb93nAIA1MrU2ul1xAcY6OvAyFBPbrlpaelY4X8IGRkCvqldEUREREREpRkTTdlISkrCDz/8AG1tbQwZMgQmJibQ09PDy5cv0alTzn1xeHp6YvHixQgPD4ejo2ORxVepUiXY29vj6dOn8PHxybFc/fr1sXHjRjx+/BguLtJObB8/foxbt26hcePGRRYf5V3f9l++ba6CkzXGDmgJANDR1pSOK2uNP2Z/L5bx8dss/r3U/xjaNK2GXu0aoKabA85dld7+06S+K9zK2eLx8yis3HJKbhkBCwdDV1sT9x6/RlxCEiqXt4Pnt5XxMTYBfSatQ/ynZBB9jQ6evIrbD54DAJ6GR0rHnbqGm/9/i1p1Nye085S2zGvRqDrOXbmPwKC7GDR+BerVrICET0k4e/keUlLT8NMPXWGY6emKfTt74MJ/D3As8CYePnmF2tXKAwCu336CZy+jYG9rjp7tG4nlb91/hiXr/kW1Sk6wszaFkaEePkTH49rtJ3j7PgZO9pYY2vt/t0UTEVEp9uAB0KcPsGUL4Ja1b0AiotJM5RNNGRkZuHxZ+qSv+Ph43LlzB+vWrcPTp08REBAg9rc0Z84cTJ48GS9fvoSHhwfU1dXx9OlT/Pvvv9izZw/09PQwbtw4bNy4EU2aNMHMmTNRrlw5PH36FA8fPsQvv/yisJglEgmWLl2K3r17IyEhAd7e3tDX18fz589x6NAhzJ8/HxUrVsSAAQPw888/o127dpg7dy4A6VPnbGxsFBYLFVztyk6o7GKHa3ef4f6TnFvCWZkboXe7b+TGWX82LnOi6WXkRzTruwjjBrRCC3c3DOjcEIIAhL95j983nsDSgOOIiUuUq+/w2dvo1a4BurWuCx1tTbyKjMa6nWexLOA43n6IU9AaEyne7QfPcTTwpty4OyHPcSfkufhelmiSSCSYNa47qro64tCpazhw4io0NdVR1dURfbt4oGYVZ7l6rC1NsP5XH2zeexZXbj7C/uP/QSKRwMbSBL06NMb3nZvKJaaqVnLEdy3r4faDZ3j87A3iE5Kgq6sFJ3srdG3rjk5tGkBHW6sItwYREX01EhOBmzelQyIiFaPyiabExES4u7sDAAwMDFC2bFm0aNEC+/btQ6VKlcRyEyZMQJkyZbB06VKsWLECmpqaKF++PNq1awctLekPB3Nzc1y8eBHTpk3D5MmT8enTJ5QtW1Z8epwidevWDSYmJpg3bx42b5YmGcqWLYvWrVuLfTDp6uri+PHjGDlyJL7//nuUKVMGM2fOxL///ovo6GiFx0T5c+P+c5jWG/3FchdvPMpTucwi3sVgyuJdeS7/1+7z+Gv3+Xwtg+hr8NMPXfHTD13zXF5DXR3dv2uI7t81zFN5CzMjjB3yXZ7KOthZ4MfB7fIcCxERERFRaSQRZB24EOUgNjYWxsbG0K42FBJ1Xo0nKqxze+YpOwSiEi8+LhbNazoiJiYm134HqWSTnYMo+nN+8uQJeg4agbLeo2BkZa+wemOjXuLZoVXY/vcalC9fXmH1Ugl04wZQpw5w/TpQu7ayoyEiKrT8HJP51DkiIiIiIiIiIlIIJpqIiIiIiIgUydkZ2LlTOiQiUjEq30cTERERERGRQpmaAt26KTsKIiKlYIsmIiIiIiIiRYqMBJYulQ6JiFQME01ERERERESK9OoVMGGCdEhEpGKYaCIiIiIiIiIiIoVgoomIiIiIiIiIiBSCiSYiIiIiIiIiIlIIJpqIiIiIiIgUydgY+O476ZCISMVoKDsAIiIiIiKiUqV8eWD/fmVHQUSkFGzRREREREREpEipqcDbt9IhEZGKYaKJiIiIiIhIke7cAayspEMiIhXDRBMRERERERERESkEE01ERERERERERKQQTDQREREREREREZFCMNFEREREREREREQKoaHsAIiIiIiIiEqVGjWAmBhAX1/ZkRARFTsmmoiIiIiIiBRJXR0wMlJ2FERESsFb54iIiIiIiBTp0SPAy0s6JCJSMUw0ERERERERKVJcHHD8uHRIRKRimGgiIiIiIiIiIiKFYKKJiIiIiIiIiIgUgokmIiIiIiIiIiJSCCaaiIiIiIiIFMnBAVi5UjokIlIxGsoOgIiIiIiIqFSxtAR8fJQdBRGRUrBFExERERERkSJ9+ABs3iwdEhGpGCaaiIiIiIiIFOnZM6BvX+mQiEjFMNFEREREREREREQKwUQTEREREREREREpBBNNRERERERERESkEEw0ERERERERKZK+PvDNN9IhEZGK0VB2AERERERERKWKqysQFKTsKIiIlIItmoiIiIiIiIiISCGYaCIiIiIiIlKkGzcAiUQ6JCJSMUw0EREREamQBQsWoF69ejA0NISVlRU6duyI0NBQuTIeHh6QSCRyrxEjRsiVCQ8Ph7e3N/T09GBlZYVJkyYhLS1NrkxgYCBq164NbW1tuLi4ICAgoKhXj4iIiJSMiSYiIiIiFXL27Fn4+Pjg8uXLOHHiBFJTU9GqVSskJCTIlRs6dCjevHkjvhYtWiROS09Ph7e3N1JSUnDp0iVs2LABAQEBmDVrllgmLCwM3t7eaNasGYKDgzF27FgMGTIEx44dK7Z1JSIiouLHzsCJiIiIVMjRo0fl3gcEBMDKygrXr19HkyZNxPF6enqwsbHJto7jx4/j/v37OHnyJKytrVGzZk3MnTsXU6ZMga+vL7S0tLBmzRo4OztjyZIlAAA3NzdcuHABy5Ytg5eXV9GtIBERESkVWzQRERERqbCYmBgAgJmZmdz4LVu2wMLCAlWrVsW0adPw6dMncVpQUBCqVasGa2trcZyXlxdiY2Nx7949sYynp6dcnV5eXgjK5UlcycnJiI2NlXsRERFRycIWTUREREQqKiMjA2PHjkXDhg1RtWpVcXzv3r3h5OQEOzs73L59G1OmTEFoaCj27t0LAIiIiJBLMgEQ30dERORaJjY2FomJidDV1c0Sz4IFC+Dn56fQdSRSisqVgUePAHt7ZUdCRFTsmGgiIiIiUlE+Pj64e/cuLly4IDd+2LBh4t/VqlWDra0tWrRogSdPnqB8+fJFFs+0adMwfvx48X1sbCwcHByKbHlERUZHB3BxUXYURERKwVvniIiIiFTQ6NGjcfDgQZw5cwb2X2h10aBBAwDA48ePAQA2NjaIjIyUKyN7L+vXKacyRkZG2bZmAgBtbW0YGRnJvYhKpLAw4PvvpUMiIhXDRBMRERGRChEEAaNHj8a+fftw+vRpODs7f3Ge4OBgAICtrS0AwN3dHXfu3EFUVJRY5sSJEzAyMkLlypXFMqdOnZKr58SJE3B3d1fQmhB9xT5+BLZskQ6JiFQME01EREREKsTHxwebN2/G1q1bYWhoiIiICERERCAxMREA8OTJE8ydOxfXr1/Hs2fPsH//fvTr1w9NmjRB9erVAQCtWrVC5cqV0bdvX9y6dQvHjh3DjBkz4OPjA21tbQDAiBEj8PTpU0yePBkhISFYtWoVdu7ciXHjxilt3YmIiKjoMdFEREREpEJWr16NmJgYeHh4wNbWVnzt2LEDAKClpYWTJ0+iVatWqFSpEiZMmIAuXbrgwIEDYh3q6uo4ePAg1NXV4e7uju+//x79+vXDnDlzxDLOzs44dOgQTpw4gRo1amDJkiVYv349vLy8in2diYiIqPiwM3AiIiIiFSIIQq7THRwccPbs2S/W4+TkhMOHD+daxsPDAzdv3sxXfERERFSysUUTERERERGRItnaArNnS4dERCqGLZqIiIiIiIgUydYW8PVVdhRERErBFk1ERERERESKFBsLHDsmHRIRqRgmmoiIiIiIiBTp8WOgdWvpkIhIxTDRRERERERERERECsFEExERERERERERKUSeOgOfM2dOgSqXSCSYOXNmgeYlIiIiKu2Sk5Ohra2t7DCIiIiIFCZPiSbfAj4xgYkmIiIiopzZ2dnh+++/x5AhQ1CtWjVlh0NEiqKtDZQvLx0SEamYPCWazpw5U9RxEBEREakcQ0NDrFixAitXrkT9+vUxdOhQ9OzZE3p6esoOjYgKo0oVdgRORCorT4mmpk2bFnUcRERERConLCwMx48fx/r163HgwAEMHToU48aNQ69evTBkyBDUrVtX2SESERER5Qs7AyciIiJSEolEAi8vL+zatQsvX77EokWLUKZMGaxbtw4NGjRArVq1sHr1asTGxio7VCLKj9u3AUtL6ZCISMUUKtG0b98+dO/eHdWrV4eLi4s4PiQkBIsWLcKrV68KHSARERGRKrCwsMCECRNw//59nD9/Hv3798fjx48xevRo2NnZYeDAgfjvv/+UHSYR5UVaGvDunXRIRKRiCpRoysjIQI8ePdC1a1fs2bMHT58+RVhYmDjd1NQU06dPx8aNGxUWKBEREZGqMDQ0hJ6eHjQ0NCAIAtLT07Fhwwa4u7vD29sbUVFRyg6RiIiIKFsFSjQtW7YMu3btwvDhw/Hx40dMnDhRbrq1tTUaN26MQ4cOKSRIIiIiotIuPj4e69atQ/369VGrVi2sWrUKFStWxF9//YUPHz7gv//+Q9euXXHkyBEMHz5c2eESERERZStPnYF/LiAgAPXq1cOqVasASPsX+JyLiwsTTURERERfcPnyZfz555/YtWsX4uPjYWBggGHDhmH48OGoWbOmWK5u3brYsWMHtLS0sH//fuUFTERERJSLAiWaHj9+DB8fn1zLmJub4/379wUKioiIiEgVVKtWDffv34cgCKhVqxaGDx+O3r17w8DAIMd5qlSpgi1bthRjlESUbxUrApcuSYdERCqmQIkmXV1dxMTE5Frm+fPnMDExKUj1RERERCrh6dOnGDhwIIYPH4569erlaZ4+ffrA3d29iCMjokIxMAD4f0pEKqpAiaZatWrh2LFjSEpKgo6OTpbpHz58wNGjR9GkSZNCB0hERERUWr158wZGRkb5msfBwQEODg5FFBERKcTLl8DSpcD48YC9vbKjISIqVgXqDHzMmDF4+fIlunTpgpcvX8pNe/LkCTp16oSYmBiMGTNGIUESERERlUb6+vqIjY1FRkZGttMzMjIQGxuL9PT0Yo6MiAolKgpYtkw6JCJSMQVKNHXo0AFTpkzBkSNH4OTkhCVLlgAArKysULFiRZw/fx4zZsxA8+bNFRosERERUWni5+cHKyurHPu1fP/+PaytrTFv3rxijoyIiIioYAqUaAKABQsW4NixY2jXrh309PSgrq6OjIwMtG7dGkeOHIGfn58i4yQiIiIqdQ4ePIgWLVrA0tIy2+mWlpbw9PTEv//+W8yRERERERVMgfpokmnZsiVatmypqFiIiIiIVMrTp0/RrFmzXMu4urri4sWLxRQRERERUeEUuEUTERERERVOamoq1NRyPx2TSCRISkoqpoiISCEsLIBRo6RDIiIVU6gWTTdu3MCGDRtw8+ZNxMTEwNjYGLVq1UL//v1Ru3ZtRcVIREREVCq5uLjg9OnTuZY5ffo0nJ2diykiIlIIR0fgjz+UHQURkVIUuEXTpEmTUL9+faxYsQIXLlzAnTt3cOHCBaxYsQL169fH5MmTFRknERERUanTuXNnBAcHY9asWVmeLJeeno6ZM2ciODgY3bp1U1KERFQgnz4BN25Ih0REKqZAiaaVK1diyZIlqFChAjZt2oRnz54hMTERz549w8aNG+Hi4oIlS5Zg1apVio6XiIiIqNSYMGECKlasiHnz5sHNzQ3Dhw/HnDlzMHz4cLi5uWH+/Plwc3PDxIkTlR0qEeVHSAhQp450SESkYgp069yqVavg4OCA//77D4aGhuJ4R0dHfP/99/juu+9QrVo1rFy5EqNGjVJYsERERESliYGBAc6dO4eRI0di3759ePz4sThNTU0NXbt2xapVq2BgYKDEKImIiIjyrkCJprCwMIwcOVIuyZSZsbExunTpgjVr1hQqOCIiIqLSztLSErt370ZkZCSuXbuGmJgYmJiYoG7durCyslJ2eERERET5UqBEU15PeqytrQtSPREREZHKsba2hre3t7LDICIiIiqUAvXR1KtXL+zZswfx8fHZTo+NjcWePXvQq1evQgVHRERERERU4qipAYaG0iERkYopUIsmPz8/PHjwAPXr18esWbPQqFEjWFtbIzIyEufPn8fcuXNRu3Zt+Pn5KTpeIiIiolLl/v37WLlyJa5evYro6OgsT58DAIlEgidPnighOiIqkJo1gdhYZUdBRKQUeUo0qampQSKRZBkvCAL69OmT7fjQ0FDo6ekhLS2t8FESERERlUJnz55F69atkZycDA0NDVhbW0NDI+vpmSAISoiOiIiIKP/ylGhq0qRJtokmIiIiIiq4qVOnIi0tDevXr0f//v2hrq6u7JCISBHu3we6dQN27QIqV1Z2NERExSpPiabAwMAiDoOIiIhI9dy6dQs9e/bEoEGDlB0KESlSUpI02ZSUpOxIiIiKHXunIyIiIlISfX39PD/Nl4iIiKgkYKKJiIiISEnatm2L8+fPKzsMIiIiIoUp0FPnACA9PR07d+7EyZMn8fr1ayQnJ2cpI5FIcOrUqUIFSERERFRa/frrr2jUqBHGjBmDhQsXQk9PT9khERERERVKgRJNCQkJaNWqFS5fvgxBECCRSOSehiJ7zw7EiYiIiHLWs2dPGBgY4I8//kBAQAAqVqwIIyOjLOV48Y6ohClXDvj3X+mQiEjFFCjR9PPPPyMoKAhz5szBqFGjYGFhAV9fXwwfPhznzp3DTz/9hNq1a2PLli2KjpeIiIio1Mj8wJX4+HjcuHEj23K8eEdUwpiYAO3bKzsKIiKlKFAfTXv37sU333yDGTNmwMzMTBxvbW2Nbt264cyZMzh58iR+/fVXhQVKREREVNpkZGTk6ZWenq7sUIkoPyIigAULpEMiIhVToERTeHg4vvnmm/9VoqYm10eTvb09vL29sWHDhsJHSEREREREVJK8fg389JN0SESkYgp065y+vj7U1P6XozI2NsabN2/kytjY2CA8PLxw0RERERGpiPj4eDx8+BAJCQlo3LixssMhIiIiKpACtWhycnKSSyJVrVoVp0+fFls1CYKAU6dOwdbWVjFREhEREZVSz549Q4cOHWBqaop69eqhWbNm4rSLFy+icuXKcn05EREREX3NCpRoatGiBc6cOYO0tDQAQP/+/REeHg53d3dMmjQJjRo1QnBwMLp06aLQYImIiIhKE1l3BIcPH0aHDh3g7u4u9yTfBg0a4N27d9i2bZvClrlgwQLUq1cPhoaGsLKyQseOHREaGipXJikpCT4+PjA3N4eBgQG6dOmCyMjILLF7e3tDT08PVlZWmDRpknhuKBMYGIjatWtDW1sbLi4uCAgIUNh6EBER0depQImmoUOHYuLEiXj79i0AYNCgQfDx8cGtW7ewZMkSBAUFoXPnzvD19VVkrERERESlyuzZs/Hx40ecPXsWu3fvRsuWLeWma2hooHHjxrh48aLClnn27Fn4+Pjg8uXLOHHiBFJTU9GqVSskJCSIZcaNG4cDBw5g165dOHv2LF6/fo3OnTuL09PT0+Ht7Y2UlBRcunQJGzZsQEBAAGbNmiWWCQsLg7e3N5o1a4bg4GCMHTsWQ4YMwbFjxxS2LkRfLRMToGtX6ZCISMUUqI+mChUqYMqUKXLjVqxYgVmzZuHp06dwcnKCjY2NQgIkIiIiKq2OHTuGTp064dtvv82xjJOTE06fPq2wZR49elTufUBAAKysrHD9+nU0adIEMTEx+Ouvv7B161Y0b94cAODv7w83NzdcvnwZ33zzDY4fP4779+/j5MmTsLa2Rs2aNTF37lxMmTIFvr6+0NLSwpo1a+Ds7IwlS5YAANzc3HDhwgUsW7YMXl5eClsfoq9SuXLArl3KjoKISCkK1KIpJ5aWlmjQoAFsbGywf/9+zJkzR5HVExEREZUqHz58QNmyZXMtIwiC3NN9FS0mJgYAYGZmBgC4fv06UlNT4enpKZapVKkSHB0dERQUBAAICgpCtWrVYG1tLZbx8vJCbGws7t27J5bJXIesjKwOolItJQV4+VI6JCJSMQpNNGW2b98++Pn5FVX1RERERCWetbU1Hj16lGuZO3fuwNHRsUiWn5GRgbFjx6Jhw4aoWrUqACAiIgJaWlow+eyWH2tra0RERIhlMieZZNNl03IrExsbi8TExGzjSU5ORmxsrNyLqES6exdwcJAOiYhUTJElmoiIiIgody1btsTBgwdx+/btbKefP38ep0+fRtu2bYtk+T4+Prh79y62b99eJPXn14IFC2BsbCy+HBwclB0SERER5RMTTURERERKMmPGDOjq6qJJkyaYN28eHj9+DAA4cuQIZs6cidatW8PCwgKTJk1S+LJHjx6NgwcP4syZM7C3txfH29jYICUlBdHR0XLlIyMjxT44bWxssjyFTvb+S2WMjIygq6ubbUzTpk1DTEyM+Hrx4kWh1pGIiIiKHxNNREREREpStmxZHDt2DKamppg5cya2bt0KQRDQrl07zJs3D5aWljh8+DBsbW0VtkxBEDB69Gjs27cPp0+fhrOzs9z0OnXqQFNTE6dOnRLHhYaGIjw8HO7u7gAAd3d33LlzB1FRUWKZEydOwMjICJUrVxbLZK5DVkZWR3a0tbVhZGQk9yIiIqKSpUBPnSMiIiIixWjQoAEePXqEAwcO4MqVK/jw4QOMjIzQoEEDdOjQAVpaWgpdno+PD7Zu3Yp///0XhoaGYp9KxsbG0NXVhbGxMQYPHozx48fDzMwMRkZG+OGHH+Du7o5vvvkGANCqVStUrlwZffv2xaJFixAREYEZM2bAx8cH2traAIARI0Zg5cqVmDx5MgYNGoTTp09j586dOHTokELXh4iIiL4uTDQRERERKZmGhgY6deqETp06FfmyVq9eDQDw8PCQG+/v748BAwYAAJYtWwY1NTV06dIFycnJ8PLywqpVq8Sy6urqOHjwIEaOHAl3d3fo6+ujf//+ck8cdnZ2xqFDhzBu3DgsX74c9vb2WL9+Pby8vIp8HYmUrmZNICkJ0NRUdiRERMUuz4mmRYsW5aviO3fu5DsY+rqFBy5mE3YiBQh/90nZIRCVeOrp/PFWUIIgfLGMjo4O/vjjD/zxxx85lnFycsLhw4dzrcfDwwM3b97Md4xEJZ6aGvD/rfuIiFRNnhNNU6dOhUQiydPJiYxEIilQUERERESqIHMLoNxIJBLMnDmziKMhIoV5+BAYNgxYtw6oWFHZ0RARFas8J5r8/f2LMg4iIiIilePr65vrdNlFPiaaiEqY+Hjg7FnpkIhIxeQ50dS/f/+ijIOIiIhI5Zw5cybb8TExMbhx4wZ+//13eHp6wsfHp5gjIyIiIioYdgZOREREpCRNmzbNcVr79u3Rp08f1K5dG126dCnGqIiIiIgKTk3ZARARERFR9ipUqIBOnTph4cKFyg6FiIiIKE+YaCIiIiL6illZWSE0NFTZYRBRfjg6An/+KR0SEakY3jpHRERE9JVKTk7G0aNHYWJiouxQiCg/LCyAIUOUHQURkVIw0URERESkJBs3bsx2fFpaGl69eoXt27cjJCQEY8aMKebIiKhQ3r0D/vkH6NhRmnQiIlIhTDQRERERKcmAAQMgkUiyjBcEAQAgkUjQq1cv9tFEVNKEhwNDhwK1azPRREQqh4kmIiIiIiXx9/fPdryamhpMTU1Rp04d2NraFnNURERERAVXqERTSkoKTp48iZCQECQkJGDmzJkAgKSkJMTGxsLCwgJqauxvnIiIiCg7/fv3V3YIRERERApV4CzQ/v374ejoiO+++w4TJ06Er6+vOO327duwtbXF9u3bFREjERERERERERGVAAVq0XTx4kV07doVtra2WL58OS5fvoxt27aJ0+vXrw8XFxfs2bMHvXv3VliwRERERKXJuXPnCjxvkyZNFBgJESmUgQHQtKl0SESkYgqUaJo7dy5MTExw/fp1WFhY4P3791nK1K1bF1euXCl0gERERESllYeHR7adgedFenq6gqMhIoWpWBEIDFR2FERESlGgRNOVK1fQtWtXWOTyBAUHBwf8+++/BQ6MiIiIqLSbNWsWrly5gmPHjqFChQpo2LAhrK2tERkZiUuXLuHhw4fw8vLCN998o+xQiSg/MjKA1FRAUxNgn7VEpGIKlGhKTk6GkZFRrmWio6PZETgRERFRLlq0aIGFCxdi3bp1GDx4sFzrJkEQ8Oeff+LHH3/E9OnT0ahRIyVGSkT5EhwM1KkDXL8O1K6t7GiIiIpVgTJB5cqVw9WrV3MtExQUhEqVKhUoKCIiIiJVMHPmTHh7e2PIkCFZbqGTSCQYNmwY2rRpIz7Zl4iIiOhrV6BEU5cuXXDx4kX4+/tnO33x4sW4e/cuevToUajgiIiIiEqz69evw83NLdcybm5uuHbtWjFFRERERFQ4Bbp1btKkSdizZw+GDBmCrVu3Ijk5GQAwefJkBAUF4dKlS6hZsyZGjx6t0GCJiIiIShMtLS3cvHkz1zI3b96ElpZWMUVEREREVDgFatFkYGCA8+fPo2fPnggMDMSFCxcgCAIWL16MS5cuoXv37jh58iS0tbUVHS8RERFRqdGqVSscPXoUCxcuREpKity0lJQULFiwAMeOHYOXl5eSIiQiIiLKnwK1aAIAU1NTbNmyBb///juuXr2KDx8+wMjICPXq1YO1tbUiYyQiIiIqlX799VecP38e06dPx/Lly1G3bl1YWVkhKioK165dQ1RUFOzs7LBo0SJlh0pE+VG1KvDiBWBlpexIiIiKXYETTTLm5uZo3bq1ImIhIiIiUin29va4du0apk6dip07d+LQoUPiNB0dHfTt2xcLFy6EjY2NEqMkonzT0gLs7ZUdBRGRUhTo1jkiIiIiUgwbGxsEBAQgJiYGt2/fxvnz53H79m1ER0cjICCASSaikujpU6BbN+mQiEjFFKhFU/PmzfNUTiKR4NSpUwVZBBEREZFK0dTURNWqVZUdBhEpQnQ0sHs3MG2asiMhIip2BUo0BQYG5jpdIpFAEARIJJKCVE9ERESkUiIiIrB3716EhITg06dPWL9+PQDg7du3CAsLQ7Vq1aCrq6vkKImIiIi+rEC3zmVkZGT7io6OxunTp9GgQQN07do1y9NTiIiIiEjeqlWr4OzsjNGjR2PlypXw9/cXp0VFRcHd3R2bN29WYoREREREeafQPpqMjIzg4eGBY8eO4b///sO8efMUWT0RERFRqXLgwAGMHj0a1apVw/79+zFy5Ei56VWqVEH16tXxzz//KCdAIiIionwqks7ADQ0N0aZNG7krckREREQk79dff4WjoyPOnDmDdu3awSqbR6FXq1YN9+/fV0J0RFRgdnbA/PnSIRGRiimyp86pqanhzZs3RVU9ERERUYkXHBwMb29v6Ovr51imTJkyiIyMLMaoiKjQbGykHYHzqZFEpIKKJNH09OlT7Nq1C2XLli2K6omIiIhKhYyMDGhqauZaJioqCtra2sUUEREpRHQ0sH+/dEhEpGIK9NS5QYMGZTs+LS0Nr169woULF5Camoo5c+YUKjgiIiKi0szV1RXnz5/PcXpaWhrOnTuHatWqFWNURFRoT58CHToA168DtWsrOxoiomJVoERTQEBArtNdXV0xYcIEDBkypCDVExEREamEPn36YOLEifDz88Ps2bPlpqWnp2PixIl4+vQppkyZoqQIiYiIiPKnQImmsLCwbMerqanBxMQEhoaGhQqKiIiISBX88MMPOHDgAObMmYMtW7ZAR0cHANC9e3dcu3YNz549Q6tWrTB48GAlR0pERESUNwVKNEkkEmhpacGGndsRERERFZimpiaOHTsGPz8/rFmzBh8/fgQA7N69G0ZGRpgyZQr8/PwgkUiUHCkRERFR3hQo0eTs7Iz+/fvj77//VnQ8RERERCpFS0sL8+bNw88//4zQ0FB8+PABRkZGcHNzg7q6urLDI6KC0NEBKleWDomIVEyBEk2mpqYwNzdXdCxEREREKqVcuXJo06YN/vjjD0gkElSqVEnZIRGRIlSuDNy7p+woiIiUokCJpsaNG+PKlSuKjoWIiIhIpbx79w5GRkbKDoMUKDUlBc+fP1d4vUZGRrC0tFR4vURERIpWoETTggUL8M0332DOnDn46aefoKFRoGqIiIiIVFr16tXx8OFDZYdBCpIcH4NnYU8x9idfaGtrK7RuM0M9bPZfz2RTSREcDDRpApw7B9SsqexoiIiKVYEyRIsWLUK1atXg5+eHtWvXokaNGrC2ts7SUaVEIsFff/2lkECJiIiISpspU6agS5cuOHPmDJo1a6bscKiQUpMTkSHRgMU3nWFu56SwehM+ROJt0B7ExsYy0VRSZGQAcXHSIRGRislzokldXR2+vr6YOXMmAgICxPFv3rzBmzdvsp2HiSYiIiKinH38+BGtWrVCq1at0LFjR9SrVy/bi3cA0K9fPyVESAWhZ2oJIyt7hdb5VqG1ERERFZ08J5oEQYAgCACAsLCwIguIiIiISFUMGDAAEokEgiBgz5492LNnDwDIJZoEQYBEImGiiYiIiEqEAt065+SkuKbARERERKokNjYWOjo60NLSgr+/v7LDISIiIlIo9uJNREREVIxMTU3F7gj69+8PALhy5QquXLmCMWPGKDk6IlKISpWA69elQyIiFaOWn8LZ9RdARERERHmXuTsCmaNHj2LcuHFKioiIFE5PD6hdWzokIlIx+Uo0+fr6Ql1dPc8vDQ02mCIiIiL62pw7dw7fffcd7OzsIJFI8M8//8hNl/UdlfnVunVruTIfPnxAnz59YGRkBBMTEwwePBjx8fFyZW7fvo3GjRtDR0cHDg4OWLRoUVGvGtHXITwc8PGRDomIVEy+MkGyEwkiIiIiKrkSEhJQo0YNDBo0CJ07d862TOvWreX6kNLW1pab3qdPH7x58wYnTpxAamoqBg4ciGHDhmHr1q0ApH1RtWrVCp6enlizZg3u3LmDQYMGwcTEBMOGDSu6lSP6Grx7B6xaBQweDDg6KjsaIqJila9E07hx4zBr1qyiioWIiIiIikGbNm3Qpk2bXMtoa2vDxsYm22kPHjzA0aNHcfXqVdStWxcAsGLFCrRt2xaLFy+GnZ0dtmzZgpSUFPz999/Q0tJClSpVEBwcjKVLlzLRREREVIrl69Y5IiIiIlINgYGBsLKygqurK0aOHIn379+L04KCgmBiYiImmQDA09MTampquHLlilimSZMm0NLSEst4eXkhNDQUHz9+zHaZycnJiI2NlXsRERFRycJOlIiIiIiK2ebNm3H58mXx/ePHjwEAbdu2zba8RCLBoUOHiiU2QHrbXOfOneHs7IwnT57gp59+Qps2bRAUFAR1dXVERETAyspKbh4NDQ2YmZkhIiICABAREQFnZ2e5MtbW1uI0U1PTLMtdsGAB/Pz8imitiIiIqDgw0URERERUzB4/fiwmlzI7evRotuWL+8m/PXv2FP+uVq0aqlevjvLlyyMwMBAtWrQosuVOmzYN48ePF9/HxsbCwcGhyJZHVGSsrIBx46RDIiIVw0QTERERUTEKCwtTdgj5Vq5cOVhYWODx48do0aIFbGxsEBUVJVcmLS0NHz58EPt1srGxQWRkpFwZ2fuc+n7S1tbO0uk4UYlkbw8sXarsKIiIlCLPiaaMjIyijIOIiIhIJTg5OSk7hHx7+fIl3r9/D1tbWwCAu7s7oqOjcf36ddSpUwcAcPr0aWRkZKBBgwZimenTpyM1NRWampoAgBMnTsDV1TXb2+aISpX4eODOHaBaNcDAQNnREBEVK3YGTkRERKRi4uPjERwcjODgYADSVlbBwcEIDw9HfHw8Jk2ahMuXL+PZs2c4deoUOnToABcXF3h5eQEA3Nzc0Lp1awwdOhT//fcfLl68iNGjR6Nnz56ws7MDAPTu3RtaWloYPHgw7t27hx07dmD58uVyt8YRlVoPHwLffisdEhGpGCaaiIiIiFTMtWvXUKtWLdSqVQsAMH78eNSqVQuzZs2Curo6bt++jfbt26NixYoYPHgw6tSpg/Pnz8vd1rZlyxZUqlQJLVq0QNu2bdGoUSOsW7dOnG5sbIzjx48jLCwMderUwYQJEzBr1iwMGzas2NeXiIiIig/7aCIiIiJSMR4eHhAEIcfpx44d+2IdZmZm2Lp1a65lqlevjvPnz+c7PiIiIiq52KKJiIiIiIiIiIgUgokmIiIiIiIiRdLQACwspEMiIhXDbz4iIiIiIiJFql4dePtW2VEQESkFWzQREREREREREZFCMNFERERERESkSPfuAS4u0iERkYphoomIiIiIiEiRkpOBJ0+kQyIiFcNEExERERERERERKQQTTUREREREREREpBBMNBERERERERERkUIw0URERERERKRILi7A0aPSIRGRitFQdgBERERERESlipER4OWl7CiIiJSCLZqIiIiIiIgU6c0bwNdXOiQiUjFMNBERERERESnSmzeAnx8TTUSkkphoIiIiIiIiIiIihWCiiYiIiIiIiIiIFIKJJiIiIiIiIiIiUggmmoiIiIiIiBTJ1BTo00c6JCJSMRrKDoCIiIiIiKhUcXYGNm9WdhRERErBFk1ERERERESKlJQEPH4sHRIRqRgmmoiIiIiIiBTp/n2gQgXpkIhIxTDRRERERERERERECsFEExERERERERERKQQTTUREREREREREpBBMNBERERERERERkUJoKDsAIiIiIiKiUqV2bUAQlB0FEZFSsEUTEREREREREREpBBNNREREREREihQaCri7S4dERCqGiSYiIiIiIiJFSkgA/o+9+w6L4mrbAH4vbekg0hEBe8euWNGoWGKPJfaeRE0sMUajETW2+BoTTdTEHo01iiaW2FBjw9hj74iIgCBI75zvj/1247oszYFl5f5dF9eyM2fOPLOFOTxzzpnz5xWPRESlDBNNREREREREREQkCSaaiIiIiIiIiIhIEkw0ERERERERERGRJJhoIiIiIiIikpKnJ7B5s+KRiKiUMdJ1AERERERERO8UOztg0CBdR0FEpBPs0URERERERCSlqChgxQrFIxFRKcNEExERERERkZRCQ4Hx4xWPRESlDBNNREREREREREQkCSaaiIiIiIiIiIhIEkw0ERERERERERGRJJhoIiIiIiIikpKVFdChg+KRiKiUMdJ1AERERERERO+UypWBw4d1HQURkU6wRxMREREREZGUsrKA+HjFIxFRKcNEExERERERkZT+/RewsVE8EhGVMhw6R6QH6nSbhdDwmBzXNa9fCft/mai2LDzqFZb9egwnL9xFaHgMLMzlqODugGG9WqCPX0MYGjLHTO+G/cev4MrNYNx5+AwPgiOQkZmFuZP7onv7hhpl7z56jiOn/8XtB2G4+zAMsfFJaFi7AtYt/jjHulNS07HzQBDuPAzDnYdhCAmLhhACBzdOg5uTndaYDp64ih37z+He43AIIVCxvBP6dW2WY0xERERERO8a/rdJpCesLc3w5ehOGj8D3m+qVu7Js2i0HLAIq3f+jXLOdhjVtxXeb+ONJ8+i8Yn/Jnw2b4uOjoBIeit+PYzdf/2D8MhXcLCzzrXsiaCbWLfjBC5df4SydnlPzhoTl4ilaw/gr5PXkJ6eCWtLszy3WbJmH6Yv3oZn4THo3KYeundohFcJyZi1dCe+W7M/38dFVNROnTqFrl27wtXVFTKZDHv37lVbL4TArFmz4OLiAjMzM7Rr1w4PHjxQKxMTE4OBAwfC2toatra2GDlyJBITE9XKXL9+HS1btoSpqSnc3d2xePHioj40IiIi0jH2aCLSEzZWZpg2pkue5X78LRAvXyVi4eTe+PjDNqrl/uO6ocWAhdi6/x98OaYLyrto75FBpC/8J36A8q72cHUqg3U7T2D5hr+0lm3fsg58m9ZAJU8XxMUn472B3+RadxlrC/w8fxRqVC4HGytzfDJzLc5dvq+1/K37odgccBrlXcvitx8+hY2VOQAgOTUdo778BZsCTqFdi9rwru5RuIMlklBSUhK8vb0xYsQI9OrVS2P94sWLsXz5cvz666/w8vLC119/DT8/P9y+fRumpqYAgIEDByI8PBxHjx5FRkYGhg8fjjFjxmDr1q0AgPj4eHTo0AHt2rXDzz//jBs3bmDEiBGwtbXFmDFjivV4iYiIqPjoZY+mLVu2oHHjxrCxsYG1tTWqV6+OUaNG4cWLFwWq5+TJk5DJZLh06VIRRZq3YcOGoVatWqrnGzduhEwmQ3R0dJHtc+LEifD09Cyy+km3QsIUn532zWuqLbexMkdT74oAgJhXiRrbEemjpvUqw9WpTL7KVvJwRvVK5WBsZJiv8uZmcvjUr6JKGOXlxPnbAIBBPVuqbWNuaoLR/dsCAH4/cD5fdREVtU6dOmHevHno2bOnxjohBH744QfMnDkT3bt3R506dbBp0yY8f/5c1fPpzp07OHToENauXYsmTZqgRYsW+PHHH7F9+3Y8f/4cgKK9lp6ejvXr16NmzZro378/PvvsMyxdurQ4D5WIiIiKmd4lmhYvXozBgwejZcuW2LFjB3bs2IERI0bg0qVLqoaNPvn6669VV/6IcpOenomt+87juw2HsXrn37h080mO5apXdAEAHD17S215XEIy/rn+GE5lrVHVy7mowyUqdV7GJgBAjvM3uTkrll3492GxxkRUGMHBwYiIiEC7du1Uy2xsbNCkSRMEBQUBAIKCgmBra4uGDf+be6xdu3YwMDDAP//8oyrTqlUrmJiYqMr4+fnh3r17iI2NLaajIdKR2rWBFy8Uj0REpYzeDZ1bvnw5hg0bhu+++061rFOnTvjiiy+QnZ2tw8gKJiUlBWZmZqhYsaKuQyE9EfkyHuPm/qa2rH4ND6ydPwxe5RxUyz4d3A6HTt/EV98H4FjQHdSs7IqEpFQcPHkdZqYm2Py/0TAzNXmzeiJ6S7bWFgCAsEjNifvDIhTLIqPjkJKazu8glWgREREAACcnJ7XlTk5OqnURERFwdHRUW29kZAQ7Ozu1Ml5eXhp1KNeVKaPZGzEtLQ1paWmq5/Hx8W95NEQ6YmwMODjkXY6I6B2kdz2aYmNj4eLikuM6A4P/Dkcmk2HJkiVq63/44QfIZDKN7V68eIFevXrBwsICLi4uWLBggdr6Z8+eoW/fvnBycoKpqSm8vLwwadIktTJ37txBr169YGdnB3Nzc3h7e2Pbtm1q8SxatAhffvklnJ2dVY2zN4fOKT18+BBt27aFubk5PD09sX79eo0yQUFBaNu2LSwsLGBjY4MBAwZoDB98/vw5unXrBnNzc7i5uXESTj01sGtT/LHyU9w/vBBhp5fi1G/T0K9zY1y5HYLuY39EQlKqqqxjWWscWf853vOpjsCg21i+6Rg27D6D+MQU9O/SGLUqu+nwSIjeXS0aVgUA/LZX8X1TSklNx7odJ1TPE5NTNbYlIoWFCxfCxsZG9ePu7q7rkIgK59EjoFs3xSMRUSmjdz2aGjRogJ9//hleXl54//334ez89kOAxowZgw8//BABAQE4duwYZsyYATs7O3z8seKW10OGDMHz58+xfPlyODk54enTp2rzOj148AA+Pj5wd3fH8uXL4ezsjJs3b+Lp06dq+1m2bBmaNm2KdevWITMzM9eY+vfvj48++ghffvkltm/fjpEjR8LV1RUdO3YEoEgy+fr6onPnztixYweSkpJUcykou7UDQPfu3fHs2TOsWrUKtra2WLRoEUJDQ2FkpHdvfan25ejOas9rVy2Hn+cMAQDsOHgBm/aexbiB7wEAHodG4cPJP8PCTI6DayahdpVyiEtIxs6/LmL+z/sRGHQHf62ZBENDvcszE5VoDWpXwPvv1cf+wCvo9dEStG5aA0aGhjhz8S6ysrNhZWGKhKRUGORwwYOoJFG2rSIjI9Uu7kVGRqJu3bqqMm9e3MrMzERMTIxqe2dnZ0RGRqqVUT7X1n6bPn06Jk+erHoeHx/PZBPpp7g4YN8+YPZsXUdCRFTs9C7bsHLlSvTs2ROjR48GAHh5eaFr166YNGlSoSe4btu2Lf73v/8BUMwdEBkZiXnz5mHMmDEwMDDAhQsXsHDhQvTr10+1zZAhQ1S/z549GyYmJjh79iysrRW31359XgMlOzs7BAQE5Nir6k1DhgzB9OnTVTE9fvwYc+bMUSWapk2bhoYNG6rVV7t2bdSqVQsHDx5E586dcejQIVy6dAmBgYFo21YxEa2vry/c3d1hZ6f9jmPstq4/hvVqjh0HL+Cffx+rEk1j52xGaHgMru6dAyd7xefR0lyOScM6IComAau2ncDuI5fRt1MjXYZO9E76ZnJf1KhcDnsPX8SfRy9DLjdGs/pVMGlkZ/T6+DsYGRrAOp+TixPpipeXF5ydnREYGKhKLMXHx+Off/7BJ598AgDw8fHBq1evcPnyZTRo0AAAcPz4cWRnZ6NJkyaqMjNmzEBGRgaMjY0BAEePHkXVqlVzHDYHAHK5HHK5vIiPkIiIiIqS3nVpqFWrFm7duoUDBw5gwoQJsLGxwfLly1GnTh1cu3atUHW+eceVDz74AGFhYXj27BkAoH79+liyZAlWrVqFhw81J3INDAzEBx98oEoyadOpU6d8JZlyiql37964fPkysrKykJycjLNnz6JPnz7IyspCZmYmMjMzUaVKFbi7u+PixYsAgH/++Qc2NjaqJBOgmMwzpyTY69htXX+UtbEEACSnpAMAEpJS8c+/j1HFy1mVZHpdiwaVAQA37oUWX5BEpYiBgQEGdm+B31dOwsU/F+DM73OwePpAZAuB5JR0VPZyyfdd74iKUmJiIq5du6ZqOwUHB+PatWt4+vQpZDIZJk6ciHnz5uHPP//EjRs3MGTIELi6uqJHjx4AgOrVq6Njx44YPXo0Lly4gLNnz2L8+PHo378/XF1dAQADBgyAiYkJRo4ciVu3bmHHjh1YtmyZWo8lIiIievfoXaIJAExMTNC5c2f88MMPuHr1Kg4dOoTk5GTMnTu3UPW9OZmlcqLK8PBwAMCOHTvw3nvvYcaMGahcuTKqVauGgIAAVfmXL1+qGlW5eXNSzYLGlJGRgejoaMTGxiIrKwuTJk2CsbGx2s/Tp08RGhqqit8hh0kI84pj+vTpiIuLU/0o66OS5/KtJwAAd1dFD7WMDMWQzJevEnMsr1xuYqJ3nRmJ9NrB41cBAB1be+s4EiKFS5cuoV69eqhXrx4AYPLkyahXrx5mzZoFAJg6dSo+/fRTjBkzBo0aNUJiYiIOHToEU1NTVR1btmxBtWrV8N5776Fz585o0aIFVq9erVpvY2ODI0eOIDg4GA0aNMDnn3+OWbNmYcyYMcV7sERERFSs3on/Nv38/ODt7Y07d+6olsnlcqSnp6uV03Yr3TfnGFDOH6Ccl8DFxQXr16/H2rVrcfnyZcybNw/9+vXDvXv3UKFCBZQtWxbPnz/PM8789mZSxuTm9t+kzZGRkTA2Noa9vT1SU1Mhk8nw1Vdfqa4svs7e3l4Vd1RUlMb6N+dLeBO7rZcs959EoJyzHczfuEvV/ScRmP3jHwCAD/wUw+DsbC1R2cMJD0IisWnvOQzp0UxVPi4hGT/9FggAaNmgSjFFT1S6JCalwtLCVG3ZlZvBWLfzBFwdy6BP56Y6ioxIna+vL4QQWtfLZDLMnTs314t4dnZ22Lp1a677qVOnDk6fPl3oOIn0lpsb8N13ikciolJG7xJNkZGRGj1yUlJSEBoaipo1a6qWlStXTi3xBCjmBcjJnj171Iaq7dq1C66urihXrpxaOQMDAzRq1EjVlfzhw4eoUKEC2rVrh127duHbb7+FlZXV2x6iKiblVUYA2L17Nxo0aABDQ0NYWFjAx8cHd+7cwbx587TW0bhxY8TFxeH48eOq4XNxcXE4duxYrnM0UckScOQyVm49AZ96FeHubAdzMzkePX2Bo2dvISMzC5OGdUDz+pVU5edP6oUBn/+CCfO3IuDIZdSuqpgM/K9TNxAdm4hubevCt0k1HR4RkXQCDv2Dq//fs+/Bk4j/X3YBl64r7vJTr6YnenVUzBcTHPoC63cq7v6Wmp6hWPbsBb7+boeqvm8+/28uPgD4bs1+vIpPUqt/6ZoDMDdTJH57+jVG/Vr/3b798/mbkZaegSpeLrAwN8WDJ+E4e+kebCzN8f2sobAwV09CERHRO8rJCeAwUSIqpfQu0VS7dm107doVfn5+cHFxQVhYGH766SdER0djwoQJqnIffPABfvjhBzRq1AhVq1bFb7/9hrCwsBzrPH78OL744gu0b98eR48exebNm7FixQoYGBggLi4Ofn5+GDx4MKpWrYr09HT8+OOPsLW1Rf369QEA/v7+2L9/P1q0aIGpU6fCxcUFt2/fRnJyMqZOnVqo49y0aRPMzMxQv359bN++HadOncKBAwdU6//3v/+hbdu26NevH/r3748yZcrg2bNnOHr0KIYPHw5fX1907NgR9evXx8CBA/Htt9/C1tYWCxcuzHMuKSpZWjaogvvBkbh+PxRBVx8hJTUdZW0t0b55TYz8oCXaNq2uVr5985o4vO5z/PjbMZy/9ghnrzyAqdwYVTyd8cWoThjZu6WOjoRIeldvPcGfxy6rLbt2+wmu3X6ieq5MNEXHJmiUfRmbqLbszUTTsTM38PyFem/YY2dvqH5vWKeiWqKpbbOa+OPoZRw8cRWpaRlwdrDFh12bY2S/NihbRpoLEUREpAdiY4Fjx4B27QAtk98TEb2r9C7RNHv2bOzbtw+TJ09GVFQU7O3tUadOHQQGBqJNmzaqcl9//TVevHiBOXPmwMDAAB999BEmTJiAzz//XKPOX375BatXr8bKlSthZWWFb775BmPHjgUAmJqaonbt2vjxxx/x9OlTmJmZoWHDhjhy5IhqiFrlypVx7tw5TJ8+HWPHjlVNzD1t2rRCH+e2bdswffp0zJ07F46Ojli9ejU6d/7vFvfNmjXDmTNn4O/vj+HDhyM9PR3lypXDe++9h0qVFL1bZDIZ/vjjD3z88cf46KOPUKZMGXz66aeIjIzE3r17Cx0bFa/mDSqj+f9P4p1f9Wt6YMPCkUUUEVHJ8c3n/TSSQ9o0qlMR//61uED1//Xr9AKV7/d+M/R7v1neBYmI6N0WHAz07QtcvsxEExGVOjKR2wB9IihuaWxjY4PIl3HsDUUkgafRyboOgUjvJSbEo0EVF8TF8dz0LlO2QaR+nx89eoT+Iz6GZ5exsHYsl/cG+fT8ziWc3bQYrT6eBycP6eZDjH/xDE8OrMT29T+jYsWKktVLRejKFaBBA0Wi6f9HQRAR6bOCnJP18q5zRERERERERERU8jDRREREREREREREkmCiiYiIiIiISEpmZkC9eopHIqJSRu8mAyciIiIiIirRqldXzNNERFQKsUcTERERERERERFJgokmIiIiIiIiKV29CsjlikciolKGiSYiIiIiIiIpCQGkpyseiYhKGSaaiIiIiIiIiIhIEkw0ERERERERERGRJJhoIiIiIiIiIiIiSRjpOgAiIiIiIqJ3SvXqwM2bQIUKuo6EiKjYMdFEREREREQkJTMzoGZNXUdBRKQTHDpHREREREQkpZAQYNQoxSMRUSnDRBMREREREZGUXr4E1q1TPBIRlTJMNBERERERERERkSSYaCIiIiIiIiIiIklwMnAiIiIiohIuIz0dIUUw34+1tTUcHBwkr5eIiEovJpqIiIiIiEqwtMQ4PAl+jIlfzYZcLpe0bjsrc/y2YS2TTVJzcgKmTVM8EhGVMkw0ERERERGVYBlpKciWGcG+aS+UdfWQrN6kmEhEBe1GfHw8E01Sc3MDFi7UdRRERDrBRBMRERERkR4wL+MAa8dyktYZJWltpJKQAFy+DDRoAFhZ6ToaIqJixcnAiYiIiIiIpPTgAdCmjeKRiKiUYaKJiIiIiIiIiIgkwUQTERERERERERFJgokmIiIiIiIiIiKSBBNNREREREREUjI2Vtx5zthY15EQERU73nWOiIiIiIhISrVrA8+e6ToKIiKdYI8mIiIiIiIiIiKSBBNNREREREREUrpxAyhXTvFIRFTKMNFEREREREQkpYwMICxM8UhEVMow0URERERERERERJJgoomIiIiIiIiIiCTBRBMREREREREREUmCiSYiIiIiIiIpVa4MnDiheCQiKmWMdB0AERERERHRO8XKCvD11XUUREQ6wR5NREREREREUgoLA6ZPVzwSEZUy7NFEREREREQkpchIYNEioE8fwM1N19EQUQkVFRWF+Ph4yeu1traGg4OD5PXmFxNNRERERERERETFKCoqCoOGj0JMQrLkddtZmeO3DWt1lmxioomIiIiIiIiIqBjFx8cjJiEZDj69YWHnJFm9STGRiArajfj4eCaaiIiIiIiIiIhKEws7J1g7lpO0zihJays4TgZORERERGpmz54NmUym9lOtWjXV+tTUVIwbNw5ly5aFpaUlevfujcjISLU6nj59ii5dusDc3ByOjo744osvkJmZWdyHQqQbZcsCI0cqHomIShn2aCIiIiIiDTVr1sSxY8dUz42M/ms2Tpo0CQcOHMDvv/8OGxsbjB8/Hr169cLZs2cBAFlZWejSpQucnZ1x7tw5hIeHY8iQITA2NsaCBQuK/ViIip2HB7B2ra6jICLSCSaaiIiIiEiDkZERnJ2dNZbHxcVh3bp12Lp1K9q2bQsA2LBhA6pXr47z58+jadOmOHLkCG7fvo1jx47ByckJdevWxTfffIMvv/wSs2fPhomJSXEfDlHxSkkBHj8GKlQAzMx0HQ0RUbHi0DkiIiIi0vDgwQO4urqiQoUKGDhwIJ4+fQoAuHz5MjIyMtCuXTtV2WrVqqF8+fIICgoCAAQFBaF27dpwcvpvclM/Pz/Ex8fj1q1bxXsgRLpw5w5Qq5bikYiolGGPJiIiIiJS06RJE2zcuBFVq1ZFeHg45syZg5YtW+LmzZuIiIiAiYkJbG1t1bZxcnJCREQEACAiIkItyaRcr1ynTVpaGtLS0lTP4+PjJToiIiIiKi5MNBERERGRmk6dOql+r1OnDpo0aQIPDw/s3LkTZkU4DGjhwoWYM2dOkdVPRERERY9D54iIiIgoV7a2tqhSpQoePnwIZ2dnpKen49WrV2plIiMjVXM6OTs7a9yFTvk8p3mflKZPn464uDjVT2hoqLQHQkREREWOiSYiIiIiylViYiIePXoEFxcXNGjQAMbGxggMDFStv3fvHp4+fQofHx8AgI+PD27cuIEXL16oyhw9ehTW1taoUaOG1v3I5XJYW1ur/RDpJZkMMDFRPBIRlTIcOkdEREREaqZMmYKuXbvCw8MDz58/h7+/PwwNDfHhhx/CxsYGI0eOxOTJk2FnZwdra2t8+umn8PHxQdOmTQEAHTp0QI0aNTB48GAsXrwYERERmDlzJsaNGwe5XK7joyMqBvXqAa/NN0ZEVJow0UREREREap49e4YPP/wQL1++hIODA1q0aIHz58/DwcEBAPD999/DwMAAvXv3RlpaGvz8/LBy5UrV9oaGhti/fz8++eQT+Pj4wMLCAkOHDsXcuXN1dUhERERUTJhoIiIiIiI127dvz3W9qakpVqxYgRUrVmgt4+HhgYMHD0odGpF+uHMHGDgQ2LIFqF5d19EQERUrJpqIiIiIiEqpjPR0hISESF6vtbW1qgdcqZSSAly9qngkIiplmGgiIiIiIiqF0hLj8CT4MSZ+NVvyubPsrMzx24a1pTvZRERUSjHRRERERERUCmWkpSBbZgT7pr1Q1tVDsnqTYiIRFbQb8fHxTDQREZVCTDQREREREZVi5mUcYO1YTtI6oyStjYiI9ImBrgMgIiIiIiJ6p3h5ATt3Kh6JiEoZ9mgiIiIiIiKSUpkyQJ8+uo6CiEgn2KOJiIiIiIhISpGRwNKlikciolKGiSYiIiIiIiIphYUBn3+ueCQiKmWYaCIiIiIiIiIiIklwjiYiIiIiIpJURno6QkJCJK/X2toaDg4OktdLRETSYaKJiIiIiIgkk5YYhyfBjzHxq9mQy+WS1m1nZY7fNqxlsomIqARjoomIiIiIiCSTkZaCbJkR7Jv2QllXD8nqTYqJRFTQbsTHx5f8RJONDdC1q+KRiKiUYaKJiIiIiIgkZ17GAdaO5SStM0rS2opQxYrAn3/qOgoiIp3gZOBERERERERSysgAoqIUj0REpQwTTURERERERFK6cQNwdFQ8EhGVMkw0ERERERERERGRJJhoIiIiIiIiIiIiSTDRREREREREREREkmCiiYiIiIiIiIiIJGGk6wCIiIiIiIjeKd7eQFwcYGGh60iISAJRUVGIj4+XtM6QkBBkZmRKWmdJwUQTERERERGRlAwNAWtrXUdBVOoURULo5cuX+HLmbCSmZUhab2pKMp6FhaN8hrT1lgRMNBEREREREUnpwQNg/Hjgp5+AypV1HQ1RqRAVFYVBw0chJiFZ0nqVCaGG/SfB1qmcZPW+eHQTIaHrkZXJRBMRERERERHlJiEBOHJE8UhExSI+Ph4xCclw8OkNCzsnyepVJoTk1nawdpQu0ZT4MkKyukoaJpqIiIiIiEgvZKSnIyQkRPJ6ra2t4eDgIHm9RFT8LOycmBDSMSaaiIiIiIioxEtLjMOT4MeY+NVsyOVySeu2szLHbxvWMtlERCQBJpqIiIiIiKjEy0hLQbbMCPZNe6Gsq4dk9SbFRCIqaDfi4+OZaCIikgATTUREREREpDfMyzhIOiwGAJ5LPCTPIDMTlv7+iE1JgeGjR5LVq8ShfkRUkjHRREREREREpVZRDcnLSE9H2JqNKOfhBSNjaf/t4lC/ohcVFYX4+HjJ601PT4eJiYnk9TL5SCUJE01ERERERFRqFcWQPMvkBFQ89SfWZAajTOPuHOqnZ6KiojBo+CjEJCRLWm9GejrCnoboVfJRnxJuISEhyMzIlLROKhwmmoiIiIiIqNSTckhe+Sd3MfPEbhwu61IkQ/2iJK2N3hQfH4+YhGQ4+PSGhZ2TZPW+eHQTj5+sL5Lk4/O/t+HGjRvw8JCu3pcvX+LLmbORmJYhWZ1A0SXcUlOS8SwsHOUzpI2XCo6JJiIiIiIiIj2SIfGcUkr6OKyrKHrcKHvGWNg5SZokTHwZAUD6ecaKavinMnHTsP8k2DpJF29RJdxePLqJkND1yMpkoknXmGgiIiIiIiLSE0U6p5QeDusqiiFu+tYzpqjuyKhM3Mit7fQi4aasl3SPiSYiIiIiIiI9UZRJBX0a1gUoeh69iImHS6t+kg9x08eeMUzcUEnBRBMREREREZGE0uRmuOPqhaT0dNgU0T6KKqmgL8O6gNd6HlkVTY8bIiocJpqIiIiIiIgkFOnigcmDvsDDTYvhqutgdKyoemAB+tvziOhdx0QTERERERERFamiuPseex4RlUwGug6AiIiIiIjoXVL+yV38tXgsvDPSdB0KEVGxY6KJiIiIiIiIiIgkwUQTERERERERERFJgokmIiIiIiIiIiKSBBNNREREREREREQkCSaaiIiIiIiIJPTczQsjRs/GXSNjXYdCRFTsmGgiIiIiIiKSUKaxHOFlHJEm479bRFT6GOk6ACIiIiIioneJfVQYBu7fgGeZGboOhYio2DHFTkRERERFZsWKFfD09ISpqSmaNGmCCxcu6DokoiJnnpSAtrcvwlZk6zoUIqJix0QTERERERWJHTt2YPLkyfD398eVK1fg7e0NPz8/vHjxQtehERERURFhoomIiIiIisTSpUsxevRoDB8+HDVq1MDPP/8Mc3NzrF+/XtehERERURHhHE2UJyEEACAhPl7HkRC9GxITknUdApHeS0xMAPDfOYpKnvT0dFy+fBnTp09XLTMwMEC7du0QFBSU4zZpaWlIS0tTPY+LiwMAxEvcBklISEBWZiZehT9BRqp0f5PjXzyDyM5GfEQojGSSVct69bBey4gQxAPI1JN49bHeoqyb9bJefa43KfYFsjIzkZCQIOn5U1lXftpeMsEWGuXh2bNncHd313UYREREGkJDQ1GuXDldh0E5eP78Odzc3HDu3Dn4+Piolk+dOhV///03/vnnH41tZs+ejTlz5hRnmERERFQA+Wl7sUcT5cnV1RWhoaGwsrKCTCbxZQiSTHx8PNzd3REaGgpra2tdh0Ok1/h9KvmEEEhISICrq6uuQyEJTZ8+HZMnT1Y9z87ORkxMDMqWLStJG0Tfvtv6Fi+gfzEz3qKnbzEz3qKlb/EC+hdzUcVbkLYXE02UJwMDA14t1iPW1tZ68QeQSB/w+1Sy2djY6DoEyoW9vT0MDQ0RGRmptjwyMhLOzs45biOXyyGXy9WW2draSh6bvn239S1eQP9iZrxFT99iZrxFS9/iBfQv5qKIN79tL04GTkRERESSMzExQYMGDRAYGKhalp2djcDAQLWhdERERPRuYY8mIiIiIioSkydPxtChQ9GwYUM0btwYP/zwA5KSkjB8+HBdh0ZERERFhIkmoneEXC6Hv7+/xpADIio4fp+IpNGvXz9ERUVh1qxZiIiIQN26dXHo0CE4OTnpJB59+27rW7yA/sXMeIuevsXMeIuWvsUL6F/MJSFe3nWOiIiIiIiIiIgkwTmaiIiIiIiIiIhIEkw0ERERERERERGRJJhoIiIiIiIiIiIiSTDRRCSh2bNnQyaTQSaTwcDAADY2NqhduzbGjx+PO3fuFMk+PT09MX78eNXzYcOGoVatWkWyL2169OgBX1/fYt0n6bctW7agcePGsLGxgbW1NapXr45Ro0bhxYsXBarn5MmTkMlkuHTpUhFFmrc3v3MbN26ETCZDdHR0ke1z4sSJ8PT0LLL6iYiIiIgKi4kmIomZmZkhKCgI586dw65duzB8+HAcO3YMdevWxW+//Vbk+//666+xdevWIt8PUWEtXrwYgwcPRsuWLbFjxw7s2LEDI0aMwKVLl/D8+XNdh1dg/M4RlSwrVqyAp6cnTE1N0aRJE1y4cCHX8r///juqVasGU1NT1K5dGwcPHiymSBUKEu+tW7fQu3dveHp6QiaT4Ycffii+QF9TkJjXrFmDli1bokyZMihTpgzatWuX53sitYLEGxAQgIYNG8LW1hYWFhaoW7cuNm/eXIzRFvwzrLR9+3bIZDL06NGjaAN8Q0HiVV6Mef3H1NS0GKNVKOhr/OrVK4wbNw4uLi6Qy+WoUqVKsf6tKEi8vr6+Gq+xTCZDly5dSmS8APDDDz+gatWqMDMzg7u7OyZNmoTU1NRiilahIDFnZGRg7ty5qFixIkxNTeHt7Y1Dhw4VW6ynTp1C165d4erqCplMhr179+a5zcmTJ1G/fn3I5XJUqlQJGzduLNogBRFJxt/fX1hYWGgsT0lJEW3bthUmJibi0aNHku7Tw8NDjBs3TtI6C6p79+6idevWOo2B9Iebm5sYPnx4juuysrIKVNeJEycEAHHx4kUpQiuQ5OTkHJdv2LBBABBRUVFFtu8JEyYIDw+PIqufSF9t375dmJiYiPXr14tbt26J0aNHC1tbWxEZGZlj+bNnzwpDQ0OxePFicfv2bTFz5kxhbGwsbty4USLjvXDhgpgyZYrYtm2bcHZ2Ft9//32xxPm6gsY8YMAAsWLFCnH16lVx584dMWzYMGFjYyOePXtWIuM9ceKECAgIELdv3xYPHz4UP/zwgzA0NBSHDh0qkfEqBQcHCzc3N9GyZUvRvXv3YolViILHu2HDBmFtbS3Cw8NVPxEREcUWb2FiTktLEw0bNhSdO3cWZ86cEcHBweLkyZPi2rVrJTLely9fqr2+N2/eFIaGhmLDhg0lMt4tW7YIuVwutmzZIoKDg8Xhw4eFi4uLmDRpUrHEW5iYp06dKlxdXcWBAwfEo0ePxMqVK4Wpqam4cuVKscR78OBBMWPGDBEQECAAiD179uRa/vHjx8Lc3FxMnjxZ3L59W/z4449F/neNiSYiCWlLNAkhxK1btwQAMX36dNWyDRs2iNq1awu5XC5cXV3FV199JTIzM9W2e/bsmRg8eLBwdHQUpqamomrVquKHH35QrX8z0TR06FBRs2ZNtX0AEFeuXBEdO3YU5ubmolKlSuLXX3/ViHH//v2icePGwtTUVNjb24uPP/5YJCYmqpW5ffu2aNWqlZDL5aJChQpi48aNTDRRgZibm4uvvvoqz3IAxP/+9z+1Zd9//714/RqJMtF04MAB0bNnT2Fubi6cnZ3F/Pnz1bYLDQ0Vffr0EY6OjkIulwtPT08xceJEtTK3b98WPXv2FGXKlBFmZmaiTp06YuvWrWrxLFy4UEydOlU4OTkJS0tLIYT271xQUJBo06aNMDMzEx4eHmLdunUax3ju3DnRpk0bYW5uLqytrcWHH36o0agJCwsTXbt2FWZmZsLV1VV8++23TDQRadG4cWO1c2JWVpZwdXUVCxcuzLF83759RZcuXdSWNWnSRHz00UdFGqdSQeN9nYeHh04STW8TsxBCZGZmCisrqxzbIUXhbeMVQoh69eqJmTNnFkV4GgoTb2ZmpmjWrJlYu3atGDp0aLEmmgoa74YNG4SNjU0xRZezgsa8atUqUaFCBZGenl5cIap528/w999/L6ysrDTa9EWloPGOGzdOtG3bVm3Z5MmTRfPmzYs0ztcVNGYXFxfx008/qS3r1auXGDhwYJHGmZP8JJqmTp2q1lYVQoh+/foJPz+/IouLQ+eIikmNGjXg5uaGoKAgAMDSpUsxatQo+Pn5Yd++ffjyyy+xfPlyzJgxQ7XNy5cv4ePjg5MnT2L+/Pk4cOAAJk2ahLCwsALvf+DAgejQoQP27t2LevXqYdiwYWrzRu3atQvdunVD7dq1sWfPHixevBgBAQEYOXKkqkxqaio6dOiAyMhIbN68GYsWLcKiRYtw8eLFt3hlqLRp0KABfv75Z6xduxYRERGS1DlmzBhUrFgRAQEBGDRoEGbMmIGff/5ZtX7IkCG4fv06li9fjkOHDmHOnDnIyspSrX/w4AF8fHzw4MEDLF++HH/++SeGDx+Op0+fqu1n2bJluH//PtatW5fnUNj+/fujffv22LNnD9q0aYORI0eqdasOCgqCr68vbGxssGPHDqxevRoXL15E9+7d1erp3r07Ll68iFWrVmHlypXYs2cPdu3a9TYvF9E7KT09HZcvX0a7du1UywwMDNCuXTvVufdNQUFBauUBwM/PT2t5KRUmXl2TIubk5GRkZGTAzs6uqMJUedt4hRAIDAzEvXv30KpVq6IMFUDh4507dy4cHR3V2mzFobDxJiYmwsPDA+7u7ujevTtu3bpVHOECKFzMf/75J3x8fDBu3Dg4OTmhVq1aWLBggVo7oiTF+6Z169ahf//+sLCwKKowVQoTb7NmzXD58mXVULXHjx/j4MGD6Ny5c5HHW9iY09LSNIZ8mpmZ4cyZM0Uaa2Hp4lxnVGQ1E5EGd3d3REREICEhAf7+/pg6dSoWLFgAAGjfvj1MTEwwefJkfPHFFyhbtiyWLl2KFy9e4O7du6qJf9u2bVuofY8fPx5jx44FoPiDfuDAAezevRszZ86EEAJTpkxBv379sHbtWtU2Li4u6Ny5M77++mvUrFkTGzduxPPnz3H37l1UrlwZAFCvXj1UrVpV9ZwoLytXrkTPnj0xevRoAICXlxe6du2KSZMmFXqC67Zt2+J///sfAMWJMzIyEvPmzcOYMWNgYGCACxcuYOHChejXr59qmyFDhqh+nz17NkxMTHD27FlYW1sDgMYJGQDs7OwQEBAAmUyWZ0xDhgzB9OnTVTE9fvwYc+bMQceOHQEA06ZNQ8OGDdXqq127NmrVqqVqYB06dAiXLl1CYGCg6rvv6+sLd3f3YvknjUifREdHIysrC05OTmrLnZyccPfu3Ry3iYiIyLG8VEnw3BQmXl2TIuYvv/wSrq6uOf6NlVph442Li4ObmxvS0tJgaGiIlStXon379kUdbqHiPXPmDNatW4dr164VeXxvKky8VatWxfr161GnTh3ExcVhyZIlaNasGW7duoVy5cqVyJgfP36M48ePY+DAgTh48CAePnyIsWPHIiMjA/7+/iUu3tdduHABN2/exLp164oqRDWFiXfAgAGIjo5GixYtIIRAZmYmPv74Y3z11VfFEXKhYvbz88PSpUvRqlUrVKxYEYGBgQgICCiW5GNhaDvXxcfHIyUlBWZmZpLvkz2aiIqREAIymQznzp1DYmIi+vTpg8zMTNVPu3btkJKSgps3bwKA6p9LKe4u1aFDB9XvFhYW8PDwwLNnzwAA9+/fR0hICPr27asWT+vWrWFgYKC6o9c///yDWrVqqSWVKlWqBG9v77eOj0qPWrVq4datWzhw4AAmTJgAGxsbLF++HHXq1Cl0Q7lnz55qzz/44AOEhYWpPuP169fHkiVLsGrVKjx8+FBj+8DAQHzwwQeqJJM2nTp1yleSKaeYevfujcuXLyMrKwvJyck4e/Ys+vTpg6ysLNV3rkqVKnB3d1f1Evznn39gY2OjlmC2sbEpln/QiIiktmjRImzfvh179uzRyQTQ+WVlZYVr167h4sWLmD9/PiZPnoyTJ0/qOiwNCQkJGDx4MNasWQN7e3tdh5MvPj4+GDJkCOrWrYvWrVsjICAADg4O+OWXX3QdmlbZ2dlwdHTE6tWr0aBBA/Tr10+j53RJtW7dOtSuXRuNGzfWdShanTx5EgsWLMDKlStx5coVBAQE4MCBA/jmm290HZpWy5YtQ+XKlVGtWjWYmJhg/PjxGD58OAwMmF5R4itBVIyePXsGZ2dn1W3P69evD2NjY9WPMoETGhoKQDF0ztXVVZJ929raqj03MTFR3c1BGU/Pnj3V4jE3N0dWVpYqnvDwcDg6OmrU/WaGnCgvJiYm6Ny5M3744QdcvXoVhw4dQnJyMubOnVuo+t78XCo/k+Hh4QCAHTt24L333sOMGTNUDYOAgABV+fx+1wryWc8ppoyMDERHRyM2NhZZWVmYNGmS2nfO2NgYT58+VfvOOTg4vFUcRKWFvb09DA0NERkZqbY8MjISzs7OOW7j7OxcoPJSKky8uvY2MS9ZsgSLFi3CkSNHUKdOnaIMU6Ww8RoYGKBSpUqoW7cuPv/8c3zwwQdYuHBhUYdb4HgfPXqEJ0+eoGvXrjAyMoKRkRE2bdqEP//8E0ZGRnj06FGJijcnxsbGqFevXo4XgYpCYWJ2cXFBlSpVYGhoqFpWvXp1REREID09vcTFq5SUlITt27cX65DKwsT79ddfY/DgwRg1ahRq166Nnj17YsGCBVi4cCGys7NLZMwODg7Yu3cvkpKSEBISgrt378LS0hIVKlQo8ngLQ9u5ztraukh6MwFMNBEVm1u3biEsLAzNmjVTDXkJCAjAxYsXNX46deoEAChbtmyx3O5dGc9PP/2UYzwjRowAoDjRvnjxQmP7N/9wERWUn58fvL291eYNk8vlGg242NjYHLd/83Op/Ey6uLioHtevX4/o6GhcuHABVatWRb9+/fD48WMA+f+u5bc3k7aYjI2NYW9vD1tbW8hkMsyYMSPH79zMmTNVcUdFRWnUze8ckSYTExM0aNAAgYGBqmXZ2dkIDAyEj49Pjtv4+PiolQeAo0ePai0vpcLEq2uFjXnx4sX45ptvcOjQITRs2LA4QgUg3WucnZ2NtLS0oghRTUHjrVatGm7cuIFr166pfrp164Y2bdrg2rVrcHd3L1Hx5iQrKws3btxQna+LWmFibt68OR4+fKiW9Lh//z5cXFxgYmJS4uJV+v3335GWloZBgwYVaYyvK0y8ycnJGj2BlEk9IUTRBfv/3uY1NjU1hZubGzIzM7F7926NeTZLCp2c64psmnGiUkjbXedSUlJEmzZthFwuF8HBwSI2NlaYm5uL5cuX51rfjBkzhFwuFyEhIVrL5Peuc2/eat3b21sMHTpUCCFEdna2KFeunJg8eXKu8axcuVIYGBiIBw8eqJY9ePBAGBgY8K5zlG853cY4OTlZODg4CF9fX9WyihUrikGDBqmV8/HxyfGuc4MHD1YrN3jwYOHq6iqysrJyjOH69esCgDh8+LAQQoiBAwcKBwcHER8frzVu5HAXPCG0f+e+/vprtXKtWrUSTZs2VT1v1qyZ6NWrl9b9CaG4fS0AERgYqFr26tUrYWVlxbvOEeVg+/btQi6Xi40bN4rbt2+LMWPGCFtbW9XfncGDB4tp06apyp89e1YYGRmJJUuWiDt37gh/f39hbGwsbty4USLjTUtLE1evXhVXr14VLi4uYsqUKeLq1atq5+WSFvOiRYuEiYmJ2LVrl9ot1xMSEkpkvAsWLBBHjhwRjx49Erdv3xZLliwRRkZGYs2aNSUy3jcV913nChrvnDlzxOHDh8WjR4/E5cuXRf/+/YWpqam4detWiY356dOnwsrKSowfP17cu3dP7N+/Xzg6Oop58+aVyHiVWrRoIfr161csMb6uoPH6+/sLKysrsW3bNvH48WNx5MgRUbFiRdG3b98SG/P58+fF7t27xaNHj8SpU6dE27ZthZeXl4iNjS2WeBMSElTnAgBi6dKl4urVq6r/GadNm6bWNn78+LEwNzcXX3zxhbhz545YsWKFMDQ0FIcOHSqyGJloIpKQv7+/MDMzE0FBQSIoKEgcPXpULF26VFSrVk2YmJio3Sp9yZIlwtTUVEydOlUcPHhQHD58WKxatUp07NhRJCUlCSGEiI6OFu7u7sLDw0OsXbtWHD9+XKxdu1ZMnTpVVY8UiSYhhNi5c6cwMjISH330kfjzzz9FYGCgWL9+vejdu7e4d++eEEKRDHB1dRVVq1YVO3fuFDt37hTVqlUTrq6uTDRRvjk4OIgRI0aIHTt2iFOnTolt27aJ5s2bC5lMpnZ71i+//FLI5XKxbNkycejQITFo0CBRvnz5HBNNbm5uYsqUKeLw4cNiypQpAoBYsWKFEEKRmGnSpIn46aefxNGjR8WBAwdEx44dha2trep7cf/+fWFjYyPq1KkjfvvtNxEYGCh+/PFH8e2336r2VdBEk4eHh1iwYIE4dOiQGDZsmAAgDhw4oCp39uxZIZfLRd++fUVAQIA4ceKE2Lx5sxgyZIg4ceKEEEKRBK5fv75wdnYWv/76q/jjjz9E06ZNhZubGxNNRFr8+OOPonz58sLExEQ0btxYnD9/XrWudevWauc+IRTnvypVqggTExNRs2ZNte9pSYs3ODhYAND4Ke5zcEFi9vDwyDFmf3//EhnvjBkzRKVKlYSpqakoU6aM8PHxEdu3by+2WAsa75uKO9EkRMHinThxoqqsk5OT6Ny5s7hy5UqxxlvQmIUQ4ty5c6JJkyZCLpeLChUqiPnz54vMzMwSG+/du3cFAHHkyJFii/F1BYk3IyNDzJ49W1SsWFGYmpoKd3d3MXbs2GJL2hQm5pMnT4rq1asLuVwuypYtKwYPHizCwsKKLVZl+/fNH2WMQ4cO1TgvnDhxQtStW1eYmJiIChUqiA0bNhRpjEw0EUnI399f7ctuaWkpatWqJcaNGyfu3LmjUX7btm2iUaNGwszMTFhbW4t69eqJr7/+WmRkZKjKPH36VAwcOFDY2dkJU1NTUa1aNbWeUFIlmoQQ4siRI6J169bCwsJCWFhYiJo1a4rPP/9cvHr1SlXm5s2bomXLlsLExER4eXmJ9evXi+7duzPRRPm2YsUK0bFjR+Hm5iZMTEyEq6ur6Nixozh+/LhaucTERDF8+HBhZ2cn7O3txYwZM8R3332XY6Jp//79olu3bsLc3Fw4OTmJb775RlUmNTVVjBo1SlStWlWYmZkJOzs70aFDB3HhwgW1/d26dUt069ZNWFtbC3Nzc1G3bl21fy4Kmmg6d+6caN26tTA1NRXly5cXq1ev1tj24sWLonPnzsLGxkaYmZmJypUri48//liEhoaqyoSGhoouXboIU1NT4eLiIhYsWCAmTJjARBMRERERlUgyIYph4CMREREREREREb3zOBk4ERERERERERFJgokmIiIiIiIiIiKSBBNNREREREREREQkCSaaiIiIiIiIiIhIEkw0ERERERERERGRJJhoIiIiIiIiIiIiSTDRREREREREREREkmCiiYiIiIiIiIiIJMFEExERERERERERSYKJJiIiIiIiIiIikgQTTUREREREREREJAkmmoiIiIiIiIiISBJMNBERERERERERkSSYaCIiIiIiIiIiIkkw0URERERERERERJJgoomIiIiIiIiIiCTBRBMREREREREREUmCiSYiIiIiIiIiIpIEE01ERERERERERCQJJpqIiIiIiIiIiEgSTDQREREREREREZEkmGgiIiIiIiIiIiJJMNFEREREREREak6ePAmZTIbZs2cX2T5kMhl8fX3zXX727NmQyWQ4efJknvVoK0tERY+JJiJ6pz158gQymQzDhg1TW+7r6wuZTKaboArI09MTnp6eug4Dw4YNg0wmw5MnT4qkfm3vFRERUWmmPD++/mNiYgJ3d3cMGDAA169f13WIeoNtDaLiwUQTEUmitDWCijrpUljKq48ff/yxrkMhIiIiCVWsWBH+/v7w9/fHZ599Bg8PD2zbtg2NGzfG2bNndR1esRg/fjzu3LmDxo0bS1qWiKRlpOsAiOjdUrFiRQwaNAgAkJiYiPPnz2Pbtm0ICAhAYGAgmjdvruMIFTZt2oTk5GRdh0FERESUL5UqVdIYxjZz5kzMnz8fM2bMKBVDxOzt7WFvby95WSKSFns0EZGklI2g2bNnY8mSJThz5gxmzJiBtLQ0zJgxQ9fhqZQvXx7VqlXTdRhEREREhfbpp58CAC5evAjgv7mKwsLCMGTIEDg7O8PAwEAtCbVhwwY0adIElpaWsLS0RJMmTbBx48Zc93PmzBn4+vrCysoKtra26N27Nx4+fKhR7sSJExgxYgSqVq2qqr9hw4ZYvXp1rvU/e/YMH374Iezt7WFubo7mzZvj2LFjGuUKMu/Sm2U3btwILy8vAMCvv/6q1gv/5MmTmDlzJmQyGXbu3JljfevXr4dMJsPChQvz3DdRacdEExEVuTcbQUD+GkKnTp1C165dYW9vD7lcjsqVK2PmzJk59kTKysrCt99+i0qVKsHU1BSVKlXCwoULkZ2dnWNMuc3R9Mcff6BDhw4oW7YsTE1N4enpicGDB+PmzZsAFHMm/frrrwAALy8vVSPlzUkog4ODMWrUKJQvXx5yuRwuLi4YNmwYQkJCtO63UaNGMDMzg5OTE0aPHo3Y2NicX1QJPH/+HP7+/mjatCkcHR0hl8vh6emJsWPH4sWLF1q3y87OxuLFi1G5cmWYmprCy8sLc+fORUZGRo7lC/I+EhERUcG93qZ5+fIlfHx8cP36dfTv3x9jxoyBtbU1AOCzzz7DiBEjEBYWhpEjR2LkyJEICwvD8OHDMWHChBzrPn/+PN577z3Y2Njg008/RevWrbFnzx40a9YMjx8/Viv77bff4tSpU2jUqBHGjx+PQYMGITo6Gh999BE+//zzHOuPjY1F8+bN8eDBA4waNQoffvgh/v33X3Ts2BF79+6V5gUCULduXdUxent7q4Yh+vv7w9PTE6NHj4aBgQHWrl2b4/Zr1qyBkZERhg8fLllMRO8qDp0jomLzZmJH2RCys7ND//79kZqaqmoIrVq1CuPGjYOtrS26du0KR0dHXLp0CfPnz8eJEydw4sQJmJiYqOoaM2YM1q9fDy8vL4wbNw6pqalYunQpzp07V6AYP//8cyxduhR2dnbo0aMHHB0dERoaimPHjqFBgwaoVasWJk6ciI0bN+Lff//FhAkTYGtrCwBqE3b/888/8PPzQ1JSEt5//31UrlwZT548wZYtW/DXX38hKCgIFSpUUJXftGkThg4dCmtrawwePBi2trbYv38/2rVrh/T0dLVjlcqpU6fw3Xff4b333kOTJk1gbGyMq1evYtWqVTh8+DCuXLkCGxsbje0mTpyIs2fPom/fvrC0tMS+ffvg7++P69evY9euXWplC/o+EhERUf6tXLkSANTmIbp58yaGDx+ONWvWwNDQULX81KlT+PHHH1G9enUEBQWpzvGzZ89G06ZNsXz5cnzwwQdo2bKl2j4OHz6Mn3/+GR999JFq2S+//IKPP/4YEyZMwL59+1TLV61apeo1pJSZmYnOnTtj2bJlmDBhAsqXL6+2/vr16xgwYAB+++03VVtxwoQJaNSoEcaMGQM/Pz+YmZm9zcsEQJFomjhxIpYtW4a6devmeDc9Pz8/HDp0CE+ePFFr1926dQvnz59Hjx494Ozs/NaxEL3zBBGRBIKDgwUA4efnp7Fu1qxZAoBo06aNahkAAUAMHz5cZGZmqpW/deuWMDIyEt7e3iI6Olpt3cKFCwUAsWTJEtWyEydOCADC29tbJCYmqpY/e/ZM2NvbCwBi6NChavW0bt1avPkncN++fQKAqF27tsZ+MzIyREREhOr50KFDBQARHByscbzp6enC09NTWFlZiStXrqitO336tDA0NBTvv/++allcXJywtrYWFhYW4t69e2r1tGrVSgAQHh4eGvvJifK1+Oijj/IsGxkZKRISEjSW//rrrwKAmDdvntpy5TE7ODiI0NBQ1fK0tDRVnLt27VItL+j7qPwMvfleERERlWbK82PFihWFv7+/8Pf3F1OmTBEtW7YUAISpqak4d+6cEELRvjIxMRFRUVEa9YwYMUIAEDt27NBYt2XLFgFAjBgxQrVM2aaoUqWKyMrKUiuflZUlKleuLGQymXjx4kWex7B7924BQGzcuFFtOQBhaGgonjx5orHNyJEjNdoW/v7+AoA4ceKERj2tW7dWW5ZT2bzaGn/88YcAIGbOnKm2fOLEiQKAOHDgQJ7HSkRCcOgcEUnq4cOHqjmavvjiC7Rq1Qpz586Fqakp5s+fr1bWxMQEixcvVrvaBiiukmVmZuLHH39E2bJl1dZNnToVDg4O2LZtm2rZpk2bAACzZs2ChYWFarmbm5vWbuA5UV4VXLZsmcZ+jYyM4OTklK969u/fjydPnuCLL75AvXr11Na1aNEC3bt3x8GDBxEfHw8A2Lt3L+Lj4zFixAhUqVJFVdbY2FjjNZOSo6MjLC0tNZYPHjwY1tbWOc6NACiuMpYrV0713MTERBXn63M8FPR9JCIiIu0ePXqEOXPmYM6cOVi2bBmCg4MxYMAAXLhwAT4+PqpyXl5eOU6CffXqVQDQGOoPAG3atAEAXLt2TWNd8+bNYWCg/m+jgYEBmjdvDiEE/v33X9XyhIQE+Pv7w9vbG5aWlqrpBXr37g1AMWz/TeXLl4eHh4fGcmXPKmXcxaFLly5wc3PDhg0bkJWVBQBIT0/H5s2b4e7ujo4dOxZbLET6jEPniEhSykYQoEiUODk5YcCAAZg2bRpq166tVlZbQ+j8+fMAFF21AwMDNdYbGxvj7t27qufKBs6bXb21LdPmwoULkMvlaN26db63yYky/nv37uXYLTsiIgLZ2dm4f/8+GjZsmGv8Pj4+MDIquj/VAQEB+OWXX3DlyhXExsaqGlVAzo3BvOJ8vTFY0PeRiIiItFMO68qLtgtj8fHxMDAwgIODQ47byGQy1UWw/NSnXB4XFwdAkZDx9fXFlStXUK9ePQwePBhly5aFkZERnjx5gl9//RVpaWmFrr84GBoaYtSoUZgzZw7++usvvP/++9izZw9evnyJ8ePHayTciChnTDQRkaTy2wgCtDcsYmJiACDfvXni4uJgYGCQY9Iqv72QlPW4ubm9dSNCGf+WLVtyLZeUlKTaL6DoYfQmQ0NDjd5AUvnuu+8wZcoUODg4oEOHDihXrpxqDoQffvghx8YgkPNrqozz9cZgQd9HIiIienvabnZibW2N7OxsREVFabQ5Xrx4ASGEaq7M10VGRuZYn3K5cq6nP/74A1euXMHIkSM1JtTevn276kYqha2/uIwaNQrz5s3DmjVr8P7772Pt2rUwMDDAiBEjijUOIn3GRBMR6UxuDSFAceXNysoqz3psbGyQnZ2N6Ohojat02hovObG1tVX1NnqbZJMy/n379uH999/Ps7yyAZXTnd6ysrLw8uVLuLm5FTqenGRmZuKbb76Bi4sLrl27ptbgFEJg8eLFWreNjIxE1apVc4zz9SRUQd9HIiIiKjr16tXD1atXcfLkSfTt21dtnfKuv3Xr1tXY7uzZsxpto+zsbJw7dw4ymQze3t4AFL3aAaB79+4adZw+fVprXE+fPkVISIjG8DnlNm9OQ/A2lNM1vN6D+03lypVDly5dcPDgQZw7dw6BgYHo2LGjxiTmRKQd+/4RUYnTpEkTAP8NvcqLsoGTUyMmt4bNmxo3boy0tDT8/fffeZbNraGijD8oKChf+80t/qCgIGRmZuarnoKIjo5GXFwcfHx8NK5qXrp0CSkpKVq3zS3O1xuDBX0fiYiIqOgMHToUADBnzhy1IXJxcXGqaQ+UZV53//59rFmzRm3ZmjVrcP/+fXTp0kV1kU+ZKDpz5oxa2b///ltj+9dlZWXhq6++ghBCtez69evYvHkzHBwc0Llz54IcZq7KlCkDmUyG0NDQXMt99NFHyMzMRJ8+fSCEwOjRoyWLgag0YKKJiEqcsWPHwsjICJ9++imePn2qsf7Vq1dqcwENHjwYADB37lzVcDQACAsLw7Jly/K933HjxgFQTHatHPallJmZqdY7ys7ODgBybKh0794d5cuXx9KlS3Hq1CmN9RkZGWqNsO7du8Pa2hrr16/H/fv31crNnDkz3/EXhKOjI8zMzHDlyhUkJyerlsfGxuLTTz/Nddtly5bh2bNnqufp6emYMWMGAGDYsGGq5QV9H4mIiKjotGrVCp9++ilu376NWrVqYdKkSZg4cSJq1aqFu3fv4rPPPkOrVq00tvPz88Nnn32G7t2746uvvkL37t3xySefwN7eXq2d1bVrV3h6emLx4sXo0qULvvzyS/To0QPvvfdejr2clOrUqYMzZ86gUaNGmDZtGkaOHIlmzZohMzMTq1evVg3rl4KlpSUaNWqEU6dOYfDgwZg7dy7mzZuHkJAQtXIdO3aEh4cHnj9/DmdnZ3Tt2lWyGIhKAw6dI6ISp1atWli5ciU++eQTVK1aFZ07d0bFihWRkJCAx48f4++//8awYcPw888/A1DcKWX48OHYsGEDateujZ49eyItLQ07duxA06ZNsX///nztt3PnzpgyZQqWLFmCypUro2fPnnB0dERYWBgCAwMxZcoUTJw4EQDQtm1bLFmyBGPGjEHv3r1hYWEBDw8PDB48GHK5HLt27UKnTp3QunVrtG3bFrVr14ZMJkNISAhOnz6NsmXLqibCtrGxwfLlyzFs2DA0atQI/fv3h42NDfbv3w8zMzO4uLgU+DU8ceKEWtLndS1atMCoUaMwduxYfPfdd/D29kbXrl0RHx+Pv/76Cx4eHnB1ddVad9OmTeHt7Y1+/frBwsIC+/btw71799CrVy/VXWWAgr+PREREVLSWL1+OevXqYdWqVVi9ejUAoGbNmpg7dy6GDx+e4zZNmzbFzJkzMXPmTCxfvhyGhobo0aMHFi9ejAoVKqjKWVpa4vjx4/jiiy9w6tQpnDx5EjVr1sSWLVvg5OSEXbt25Vh/mTJlcODAAUyZMgVr1qxBcnIy6tWrhzlz5qB9+/aSvwabN2/GpEmTsH//fsTFxUEIgRYtWqgN3TMwMMDgwYMxb948DBs2rEhvzEL0ThJERBIIDg4WAISfn1++ygMQrVu3zrXMhQsXRP/+/YWrq6swNjYW9vb2on79+mLatGnizp07amUzMzPFwoULRYUKFYSJiYmoUKGCWLBggXj48KEAIIYOHapWvnXr1kLbn8Ddu3eLNm3aCBsbGyGXy4Wnp6cYPHiwuHnzplq5xYsXi8qVKwtjY+Mcj+fZs2diwoQJonLlykIulwtra2tRvXp1MWrUKBEYGKix3z179ogGDRoIuVwuHB0dxahRo0RMTIzw8PAQHh4eub5WSidOnBAAcv1Rvhbp6eli/vz5qvjKly8vPv/8c5GQkJDjPocOHSoAiEePHolFixaJSpUqCRMTE+Hh4SFmz54t0tLScowpv++j8jP05ntFREREVNy6dOkiZDKZePDgga5DIdI7MiFeGwxLREREREREVIophxe2b98ehw8f1nU4RHqHfQCJiIiIiIio1Nu6dSvu3buHTZs2AQD8/f11HBGRfmKiiYiIiIiIiEq91atX4/Tp0/Dw8MC6devQrFkzXYdEpJc4dI6IiIiIiIiIiCRhoOsAiIiIiIiIiIjo3cBEExERERERERERSYKJJiIiIiIiIiIikgQTTUREREREREREJAkmmoiIiIiIiIiISBJMNBERERERERERkSSYaCIiIiIiIiIiIkkw0URERERERERERJJgoomIiIiIiIiIiCTBRBMREREREREREUmCiSYiIiIiIiIiIpIEE01ERERERERERCQJJpqIiIiIiIiIiEgSTDQREREREREREZEkmGgiIiIiIiIiIiJJMNFERERERESUA5lMBplMhpMnT0pSn6enJ2QyGTZu3ChJfVS0cnv/pf5sEL1LmGgiomIze/Zs1Un59R+5XA5XV1f4+flh7dq1yMjIyHedf//9Nz766CNUr14dtra2MDU1hbu7O7p06YJVq1YhJSUl33VlZWVh586dGDJkCKpUqQJbW1uYmJjA0dERLVq0wPTp03Hz5s3CHLqa69ev48svv0Tjxo3h5OQEExMT2NjYoEaNGhg6dCj++OOPAr0GREREuqbtHG9qaopy5cqhW7du2LlzJ4QQug6VCqko2nEEvHjxAosWLUL79u1Rrlw5mJmZwcLCAp6enujRowdWr16NV69e6TpMooIRRETFxN/fXwAQAISTk5Pqx9zcXLUcgGjYsKGIiYnJta7o6GjRuXNnte3kcrmwsbFRW+bm5iaOHDmSZ2xBQUGiSpUqatsaGxsLOzs7YWBgoLa8V69eIi0trcDHHx8fLwYMGCBkMpmqLplMJmxtbYVcLlfbR8WKFcX58+cLvA8iIiJd0HaONzU1VTu/derUSaSmpuo63HyrWrWqqFq1qvjnn38kqa9t27aiatWqIiAgQJL6ipOU7Th9oTymEydOFGhdfmRnZ4v58+drvH6WlpbCyspKbZmNjY1Yt27d2x0MUTFijyYi0omIiAjVT1JSEkJCQjB69GgAwKVLl/DZZ59p3TYyMhJNmzbFwYMHYWhoiE8//RS3bt1CamoqXr16hdjYWGzYsAHu7u4ICwtD586dsXPnTq317du3D76+vrh//z7Kli2LhQsX4v79+0hPT8fLly+Rnp6OixcvYtq0abC2tkZAQACSk5MLdLyxsbHw8fHB1q1bAQD9+/fH33//jdTUVMTGxiI1NRVhYWFYu3Yt6tSpg0ePHiEoKKhA+yAiIioJ3jzH37x5E+3btwcA/PXXX5g5c6aOI8y/u3fv4u7du2jcuLEk9QUGBuLu3bvo2bOnJPXpytu04wgQQmDw4MGYMWMGkpOT0aRJE+zevRuxsbFISEhAfHw84uLisGfPHnTt2hVxcXH4888/dR02Uf7pOtNFRKXH61fCtGnbtq0AIExMTERCQoLG+uzsbFUZY2Nj8eeff2qtKzo6Wnh7ewsAwsLCQty5c0ejzP3794W1tbUAIGrUqCFCQ0NzPYaXL1+K7t27i9jY2FzLvalTp04CgDAyMhI7d+7MtWx2drZYuXKlWLVqVYH2QUREpCt5neNTUlJEpUqVBABhZWUlMjIyijlCeltStOP0DYqoR9OiRYtU20+cOFFkZ2fnWv7vv/8W48aNK/B+iHSFPZqIqETp2LEjACA9PR0PHjzQWL9//34cP34cADBjxgx07dpVa11ly5bF77//DlNTUyQlJeHrr7/WKDNz5kzEx8fD1NQUe/bsQbly5XKNz87ODnv37oWNjU2+j+mvv/7CX3/9BQCYNWsW+vTpk2t5mUyGTz75BGPGjFEte/LkiWouhCdPnmjdVtsko29u/+jRI4wZMwZeXl6Qy+Xw9PTEixcvYGxsDJlMludVs1mzZkEmk6FSpUo5rj979iwGDRoEDw8PmJqawsbGBo0bN8a3336LxMTEXOsmIqJ3j6mpqer8l5CQgLt37wLI3/npddnZ2diyZQs6d+6smufQwcEBHTp0wLZt2/KcA+rOnTsYN24catSoASsrK1haWqJq1aro378/du/ejezsbLXyuU34HBsbi1mzZqF+/fqwtraGiYkJnJ2dUadOHXz88ccIDAzU2CavycCzsrKwfv16tG3bFvb29pDL5XBzc0OfPn1ynXTa19cXMpkMs2fPhhACa9asQZMmTWBtbQ0rKyv4+Pjgt99+y/W1kUJe7ThA8f4vWrQIPj4+sLOzg1wuh7u7O/r375+v3txHjhxB//794eHhATMzM9jZ2aFOnTr49NNPNbbPzs5GYGAgPvvsMzRt2hTlypWDiYkJypYti9atW+Pnn38u9jmloqOj8c033wAA3nvvPSxduhQymSzXbVq1aoXly5erLcvPxPLDhg2DTCbDsGHDNNa9vn1iYiJmzZqF2rVrw8rKSvV99Pb2hkwmw+TJk3ON7/jx45DJZDAwMMDTp0811j958gQTJ05EzZo1YWlpCXNzc1SrVg0TJkzIsTy9A3Sd6SKi0iM/V8K+/fZbVZmLFy9qrO/YsaPqamh+r5QNHz5cABAGBgYiPDxctTwiIkI1/9LIkSMLfkD5pJxLysbGRiQmJhaqjuDgYNXrEhwcrLWch4eHACA2bNigdfstW7YIS0tLAUCYm5sLCwsL4eHhIYQQokuXLgKA+OCDD7TuIzs7W3h5eQkAYvbs2WrrsrKyxGeffaYx14ChoaHqedWqVcWTJ08K9ToQEVHJlJ9z/IoVK1Rlzp49K4TI//lJCEWv4latWmnMXfP6827dummdR3HRokVq8y6amppqzMX4Zo9l5fI3e62EhoaK8uXLq9YbGBiIMmXKqJ3vWrdurRGDtvO0EEK8evVK+Pr6qrY3NDQUtra2anM7TpkyJcdja926tQAgZs6cKbp3767qRa3sta38mTVrltb3Jy9StOOuXr0qypUrp3aMr89HJJPJxIIFC3KsOykpSfTp00fteKysrNQ+A97e3mrbvP75UrZJ3vzMtGzZUiQnJ+e4T23vf17rcrN48WLVtqdPny7Qtq/L7bOkNHToUAFADB06VOv2S5YsUc1TamJiImxtbVXtzf/9738CgHB2dhaZmZla9zNs2DABQPj6+mqs++2339TmIpXL5cLMzEztPTx8+HBhXgIqwdijiYhKlMOHDwNQXEH08vJSW5eZmYnTp08DADp06ABLS8t81dmrVy8Aiqtaf//9t2r5iRMnVFcui2quhMzMTJw6dQoA0L59e1hYWBTJfgrio48+Qs2aNXHx4kUkJSUhMTERR44cAQAMGTIEgGLeKm13ODl79iyCg4Mhk8kwePBgtXX+/v5Yvnw5HB0dsWLFCrx8+RIJCQlISUnBiRMnUK9ePdy7dw+9evXSuGpMRETvttd75NrZ2Wmsz+38lJWVhV69euHUqVOoW7cu9u3bh6SkJLx69QqJiYn49ddf4ejoiD///BNffvmlRt2rVq3CtGnTkJ2djW7duuHq1atISUlRnaeOHDmCfv36wcAgf/8ezZ49G0+fPoWnpyeOHTuG9PR0xMTEIC0tDU+ePMGqVavQtGnTAr0+I0eOxMmTJ2FiYoLly5cjPj4esbGxeP78OUaMGAEAWLJkCX7++WetdaxYsQInT57Exo0bVfP8hIaGqnqAz5s3T2tPIynk1o4LDw+Hn58fnj17hl69euHSpUtISUlBfHw8IiMj8fXXX8PQ0BBfffUV9u7dq1H38OHD8fvvv8PAwABffvklQkNDER8fj1evXiEqKgpbtmyBj4+P2jZGRkYYOHAg/vzzT9V7/erVKyQkJGDDhg1wdXXF6dOnMWPGjCJ7Td6k7Onm4OCAFi1aFNt+tZk9ezbi4+OxZ88eJCYmIjY2FqGhoXB0dMTAgQNhaGiIiIgIHD16NMftU1JSsHv3bgD/tSOVjh49iiFDhiArKwtTp05FcHAwUlJSkJSUhLt376JPnz5ISEhAnz592LPpXaPrTBcRlR65XQkLCQkRo0ePVrsi+aYHDx6o1s+bNy/f+w0NDVVtN3PmTNXymTNnqpaHhYUV7qDy8PDhQ9U+5s+fX+h6pOzR5OHhobU3WEpKiupK3y+//JJjmTFjxggAokWLFhr7MDQ0FGZmZuLatWs5bhsfH6+6krlnzx6tx0FERPolr94ucXFxwtXVVQAQdnZ2IisrSwiR//PTpk2bBABRrVo18erVqxzLXLp0SchkMmFiYiIiIyNVy2NiYlS9Zvr375/nfDivU8b2Zq+V6tWrCwBi69at+a5LCO3n6fPnz6v2pe3827t3bwFA2Nvbi5SUFLV1yh5NAMTx48c1tk1NTVW9/gVpQ73ubdtxI0aMEADEgAEDtO5j6dKlOfZMOnbsmKrulStXFir+nFy8eFEAirk833xNhSiaHk3KdlD79u0LGbWCVD2aDA0NxZUrV7TW4efnJwCIDz/8MMf1W7duFQCEmZmZiI+PVy3PysoSlStXzvUzLYQQ3bp1EwDEhAkTtJYh/cMeTUSkE87OzqofCwsLeHh4YM2aNQCAatWqYeXKlRrbvHz5UvV72bJl870ve3v7HOt4/fecrqxKoTj2UVDjx4/X2hvs9Tk0Nm/erLE+LS1NdQe/N3szbdy4EVlZWejYsSO8vb1zrN/Kygo9evQA8N9VTyIiene9evUKgYGBaNu2LZ4/fw4AmDBhQo49h3I7P61btw4A8Mknn2idJ7FBgwaoWbMm0tPTceLECdXyXbt2ISEhAcbGxvmaDyc/bG1tASh66Uhhx44dAIBy5cph1KhROZZRzusTHR2ttXdJ8+bN0aZNG43lcrkcfn5+AIDr16+/dbwFbcelpqaq7rybU48zJWWPmH///ReRkZGq5evXrwcA1KpVC5988slbx6/UsGFDODo6IikpCdeuXZOs3two24YlpV3YsWNH1KtXT+t6ZXtv7969SEhI0FivbC/26NEDVlZWquWnTp3CgwcPYG9vr/UzDfz3nrNd+G4x0nUARFQ6vd54eN2QIUPwyy+/wNTUtJgjKj2aN2+e6/ohQ4Zg7dq1qiFyr3d9379/P169egVTU1P07dtXbbuzZ88CUEzS6ezsrLV+5WTgISEhhT0EIiIqwXJL5AwaNEjrMCVt56esrCycP38egGKYz4IFC7TWHxMTA0D9HHPu3DkAikSUi4tL7sHn0/vvv4+goCBMmzYNd+/eRa9evdCsWTNYW1sXqr5Lly4BANq0aaN1+F716tXh5uaGsLAwXLp0KccbojRp0kTrPlxdXQH89xq9jYK24y5fvozU1FQAiukP8iMkJAROTk4A/nsP33///QLHmp6ejvXr1yMgIAA3b97Ey5cvkZ6erlHu2bNnBa77XZBXu7Bnz56wsrJCQkICdu/erTaxeGRkpMb0C0rKdmFcXJzqs5cT5XvBduG7hYkmItIJ8f93hRFCICIiAn/++SemTZuGTZs2oXbt2pgyZYrGNq/3Ynq9p1BeoqOjc6zj9d9jYmJyPQkW1pv7KAkcHR1zXd+iRQt4eXkhODgYv/32m9rd+pRXrbp27aq6mqukvFKdlJSEpKSkPONITk4uYORERKQPlMkBQNGTxt7eHvXq1cPAgQNz7G2jpO38pJz7CFDc6S0/Xj/HREREAAA8PDzytW1+fPHFF/j333+xc+dOrFmzBmvWrIFMJkPNmjXRsWNHjBo1ClWrVs13fS9evAAAuLm55VquXLlyCAsLU5V/0+s9St5kZKT41+/Nu6w1atQIoaGhGuWbNWuGgICAHOsqaDtO2UYAtCep3iTFe/jixQu0a9cON27cUC0zNTWFvb09DA0NAQBRUVHIzs7OV9tFCmXLlsWzZ8/0pl1obm6O3r17Y+PGjdi8ebNaomnbtm3IysqCs7Mz2rdvr7ad8j3PyMjI13uekpJS8OCpxOLQOSLSKZlMBhcXF3z00UfYs2cPZDIZpk6diuPHj2uU9fDwUE2mfeXKlXzv4+rVq6rfa9asmePvr5eRkoeHh2oYQFHto6CUDSttXp/k+/Xhcy9fvsTBgwcBaA6bAxRXnAFFl3ghRJ4/ud2mmYiI9FdERITqJyQkBJcvX8batWtzTTIB2s9PyvMLAPz111/5OsfMnj1btY0UQ+XeZGxsjB07duDatWuYNWsW2rZtC3Nzc9y8eRNLlixBzZo18d1330m+36IQFRWFyMhIjZ/8JELy2457/T1MSUnJ13vo6+urtp/CmDRpEm7cuIGyZcti/fr1CA8PR0pKCqKiolSfUeWFRmXyrKgp25/FNVQvL3m1C4H/eiudPHlSLSmpbCcOGDBAox7le96kSZN8vd/F9fpT8WCiiYhKDF9fXwwePBhCCHz66adqjRJA0ahr2bIlAMXwrJzGiedEeTXOwMBArdHyevf0PXv2SHAEmoyMjNCqVSsAijtvFPZqmfIqJABV1/OcxMXFFar+NykTSQ8ePFANV9ixYwcyMjLg4OCATp06aWyjHC7Hrs9ERCSlsmXLqs6DhTnHFOX5ydvbG3PmzEFgYCBevXqFY8eOoVWrVsjKylL1esoPZa+SvIZvKdfn1QulIJ48eSLJBaHc2nGvD6kvrvcwIyND1Qb86aefMHz4cI2h/VlZWWo934vDe++9B0CR4Dtz5kyh61F+J4qjXejr6wt3d3dkZ2djy5YtAIDbt2+rLvy+OWwOYLuwtGOiiYhKlFmzZsHQ0BC3b9/Gr7/+qrFeOQFkYmIili5dmmd9Dx48wPbt2wEoxpi/3sBwcnJC7969AQBbt27F/fv38x1nQa66jBs3DoDiZJ+fmJWys7NVv5cpU0b1e07d2wHg/v37ePXqVb7rz02lSpVUtwhWXq1SPn744YdqiS8l5Rj/Y8eO5droISIiKghjY2M0btwYALBv374Cb9+sWTMAinmQpJq8OydGRkZ47733cODAAcjlcgghcOzYsXxt27BhQwDAiRMn1M7/r7t79y7CwsIAKIa7lUTa2nGNGjWCiYkJgLd7DwuybVRUlKo9om2y6zNnzhR7m2X48OEwNzcHoJhzLL9tyjc/F8q2obZ2YXZ2tmrur7clk8kwaNAgAJrtwjp16uR4ExhluzAiIkKyOEh/MNFERCVKxYoV0a9fPwCKu6u8OY9A165dVb2S5s+fj/3792ut6+XLl+jTpw9SU1Nhbm6uulvL6+bNmwdLS0ukpKSgV69eqgacNrGxsejdu3eBrhB17txZNfHl3LlzsWvXrjy3Wb16teruLQBgYWGBihUrAgB2796d4zbz58/Pd0z5obw6tWPHDty6dUvVsymnq1YAMGLECBgZGSE6Ohr+/v651p2enq6aFJyIiCgvY8aMAQAcPHhQNYxbmzeHfPXp0wfW1tbIzMzEpEmTJBmio5wzKidyuVw1jEjbxN5v6t+/PwAgLCwMa9euzbHMrFmzACjuptuuXbuChFtstLXjLCwsMGDAAADAt99+i6dPn+Zaz5vv4ciRIwEAt27dwqpVq/IVi7W1tWrIXU49yzIzM7VOTF+U7O3tMXPmTABAYGAgPv/88zw/k2fPnsWECRPUlimTO3v27Mlx+19//VXSCc6V7b/bt2/j0qVLqp5N2tqFbdq0QaVKlQAohjDmNAH760rKnFUkEUFEVEz8/f0FAJHXn54bN24ImUwmAIhVq1ZprA8PDxcVKlQQAISRkZH47LPPxO3bt1XrX716JTZu3CjKly8vAAhDQ0OxdetWrfvbs2ePMDExEQCEvb29WLRokXjw4IFqfWZmprhy5Yr4+uuvha2trQAgYmNjC3Ts0dHRonr16gKAkMlkYsCAAeLUqVMiPT1dVeb58+di48aNon79+gKA+P7779XqmDlzpgAgjI2NxYoVK0RycrIQQoinT5+KkSNHCrlcLszNzQUAsWHDBrVtg4ODVa99cHBwvmKOiYlRvS4NGzYUAESNGjVy3WbOnDmq/QwePFjcuHFDtS4jI0NcvXpVzJkzR7i7u4vTp0/nKw4iIir58nuOf1N+z0+ZmZmiXbt2AoAwMTER33zzjQgLC1OtT0xMFMePHxdjx44VNjY2Gtv//PPPqv10795dXL16VbUuKSlJ7N+/X3Tr1k3ExcWpbafc5sSJE2rLnZycxLRp00RQUJBITU1VLX/w4IHo06ePACAMDAzErVu31Lbz8PDI8TwthBC9e/dWHd+PP/4okpKShBCKds+oUaNUseTUNmrdurUAIPz9/bW8gv+9R61bt9ZaJjdv2457/vy5cHV1FQCEq6ur2LRpk4iPj1etf/Hihdi1a5fo0aOH6NChg0a9/fv3V72u06ZNE6Ghoap1UVFRYs2aNWLEiBFq27Ro0UIAEG5ubiIwMFBkZWWpYmzfvr2Qy+XCwsJC63ui7f3Pa11esrOzRb9+/VR1+Pj4iICAALXPX3x8vNi3b5/o2bOnkMlkonv37mp1HDt2TLX9qFGjRHR0tBBCiLi4OLF06VJhYmIi7OzsBAAxdOhQjRhy+yxqo2wPKh8NDQ3F8+fPtZY/duyYMDIyEgBEkyZNxLFjx9Tavo8ePRKrVq0SDRs2FN98802+46CSj4kmIio2BWmEdu/eXQAQ5cqVU2vAKb148UL4+fmp6gMgTE1NVYkg5Y+Li4v466+/8tzfmTNnRKVKldS2VZ6gDQwMVMtkMpn48MMP1U6S+RUXFyf69u2ranwp6ytTpowwNTVV23f16tXFpUuX1LZPSEgQNWrUUJUxMDBQHa+xsbHYtm2b1kZDYRJNQgjRq1cvtbgWLlyYa/ns7Gzx9ddfqx2jmZmZKFu2rDA0NFSr68yZM/mOg4iISraiTjQJoTiPvv/++2rnEmtra2Fra6t23jEyMspx+wULFqid083MzDTO829eSNKWTHg9BgMDA41zuUwm07hgJETu/9y/evVKlTBSHkeZMmXUjm3KlCk5HltJSjQJob0dd/v2bVGlShW1187Ozk6V7FH+tGvXTqPOpKQkjXaJtbW1sLGxUT339vZW2+bSpUtqdcvlcmFlZaV6fTdt2pTre1JUiSYhFG2mOXPmCDMzM7VjsrKyUsWo/LGzsxObNm3SqGPw4MFq5WxtbVWf508//VQMHTpU0kTT8uXL1fbn5+eX5zZ79uxROx5jY2NRtmxZIZfL1eqaN29evuOgko9D54ioRFJ2ZX727Bl++eUXjfUODg44dOgQjh8/rrqFsImJCVJSUuDm5oZOnTphxYoVePjwITp27Jjn/po3b467d+9i27ZtGDhwICpVqgRTU1MkJCTAzs4OLVq0wIwZM3Dnzh1s3boVxsbGBT4ma2tr7NixA1evXsWUKVPQsGFD2NvbIyEhAcbGxqhevTqGDh2K/fv348aNG2jQoIHa9paWljhz5gwmT54MLy8vGBkZwdjYGL1790ZQUJCq272UXu8ObWBgoBqfr41MJsPcuXNx/fp1jB07FtWrV4ehoSHi4uJQpkwZNGvWDF988QXOnTunGrtPRESUH9bW1ti3bx8OHjyIfv36oXz58khLS0NycjLc3NzQoUMHLFy4EPfu3ctx++nTp+Pff//F6NGjVUN60tPTUblyZXz44YcICAiAtbV1vmI5cuQIpk+fjpYtW8Ld3V11a/ZKlSph+PDhuHjxIiZOnFig47OxsUFgYCDWrVsHX19fWFlZITExEc7OzujduzdOnDiB//3vfwWqU1e0teOqV6+O69ev45dffkGHDh1gb2+P+Ph4CCFQqVIl9OnTB6tXr8bOnTs16jQ3N8fu3buxf/9+9OzZE66urkhNTYWRkRHq1KmDzz77DKtXr1bbpkGDBrhw4QL69u0Le3t7ZGdnw8rKCn379sW5c+dyvItucZHJZJg1axYeP36MBQsWoG3btnB1dUV6ejoyMzPh4eGBHj16YO3atXjy5EmOsW7cuBHLli1D3bp1YWZmhuzsbDRv3hw7d+7E8uXLJY/5ww8/VGsDaxs297oePXrg4cOH8Pf3R+PGjWFpaYlXr15BLpfD29sbo0aNwp49e/DFF19IHi/pjkwI3keQiIiIiIiIiIjeHns0ERERERERERGRJJhoIiIiIiIiIiIiSTDRREREREREREREkmCiiYiIiIiIiIiIJMFEExERERERERERSYKJJiIiIiIiIiIikgQTTUREREREREREJAkmmoiIiIiIiIiISBJMNBERERERERERkSSYaCIiIiIiIiIiIkkw0URERERERERERJJgoomIiIiIiIiIiCTBRBMREREREREREUmCiSYiIiIiIiIiIpIEE01ERERERERERCQJJpqIiIiIiIiIiEgSTDQREREREREREZEkmGgiIiIiIiIiIiJJMNFERERERERERESSMNJ1AJQ/2dnZeP78OaysrCCTyXQdDhERUaklhEBCQgJcXV1hYMBrdkWJ7R8iIqKSoSDtHyaa9MTz58/h7u6u6zCIiIjo/4WGhqJcuXK6DuOdxvYPERFRyZKf9g8TTXrCysoKgOJNtba2lrz+p0+fonz58pLXW9T0NW5Af2Nn3MWLcRc/fY2dcRef+Ph4uLu7q87NVHSKuv1TlPTxsw3ob9yA/sbOuIsX4y5++ho741ZXkPYPE016Qtld3NraukgaWlZWVnrXgAP0N25Af2Nn3MWLcRc/fY2dcRc/DuUqekXd/ilK+vrZ1te4Af2NnXEXL8Zd/PQ1dsads/y0fzixABERERERERERSYKJJiIiIiIiIiIikgQTTUREREREREREJAkmmoiIiIiIiIiISBJMNBERERERERERkSSYaCIiIiIiIiIiIkkw0URERERERERERJJgoomIiIiIiIiIiCTBRBMREREREREREUmCiSYiIiIiIiIiIpIEE01ERERERERERCQJJpqIiIiIiIiIiEgSTDQREREREREREZEkmGgqhFOnTqFr165wdXWFTCbD3r1789zm5MmTqF+/PuRyOSpVqoSNGzcWeZxEREREUmH7h4iIiPKDiaZCSEpKgre3N1asWJGv8sHBwejSpQvatGmDa9euYeLEiRg1ahQOHz5cxJESERG9W8LjUnDuUTTC41LyVf7f0FisOf0I/4bGShZDRD73/a7RZfuntL7mRERE+shI1wHoo06dOqFTp075Lv/zzz/Dy8sL3333HQCgevXqOHPmDL7//nv4+fkVVZhElIvwuBQERyfBy94CLjZmug6nRPo3NBYXnsSgsacdvN3L6O0+6N2x4+JTTA+4gWwBGMiAOd1q4YMG5bSWnx5wHXuvPVc9b1C+DPo1cn+rGC4Ex+D3oPtvVYe+0mX7p8P3p/Dth03Qr1H5Am1HRERExY+JpmIQFBSEdu3aqS3z8/PDxIkTtW6TlpaGtLQ01fP4+PiiCo/onRJ4JwLH776AZ1kLQIYcExhv/rM6v2dt9G34dv98FpWsbIGsbFHs+/1i178IuBKmet7IswwGNvHI9/bR0a9gH5P7KWbjuWBcC41TPXexlqOGq03Bg5VYckoKzM1e6DqMAnvX407NyMLZRy9Vz7MF8PUfN/H1Hzfzva/LT2Nx+enb92wq/m+kfpKy/ZMtgK8CbqJVFQdeHCAiIirhmGgqBhEREXByclJb5uTkhPj4eKSkpMDMTLPBtHDhQsyZM0dj+dOnT2FlZSV5jMnJyQgJCZG83qKmr3ED+ht7ccT9IjEDz+LSUM5GDkdL4xzL3IlMxvWIJFibGCI+PQt1nC3w09lw3IzUHF7hZGmEymXlMDR8irTMbJx/mqhaly2A6QE3MD3gRpEdz9u7pesAcPFJLC4+Keg/6M8KVDo8Pg3h8SUlUZKg6wAKiXFTySFl+wcAsoTAP7ceo56bZZHEKzWe54ufvsbOuIsX4y5++ho741aXkJD/9hoTTSXU9OnTMXnyZNXz+Ph4uLu7o3z58rC2tpZ8fyEhIfDwyH9vhZJCX+MG9Dd2Zdzahp5pGwqV3yFSit5G91S9jRb2qq0xVOLzndew+7XeNnmJTMxEZGJmAY6SiPRFFSdL2FvKNZYnpGbgRphmb+CxvhXhbmde4P0IIRCfkolvD90tVJyUP9raPwBgKJOhSc0KetOjSd/P8/pIX2Nn3MWLcRc/fY2dcasryCgrJpqKgbOzMyIjI9WWRUZGwtraOsereQAgl8shl2s2nIkKKj9zERVknpw7kclYfOYyDt6MgHgjGfRmAqhFJXt81LoCvj96H1eevlIt97AzR5MKdhp1J6dnYv/1CNXzbAF8ufsG/P+4BZlMpliWnY20LOkHrnjZm6OsRcn7zqWlpRX734LEtEzcjdC8YjG6pRfKlcnfP+gxMTGws9N8j5WexSZjzelgjeWbRjRGLTfdDp8LDQ1V/WOrT971uCPjU9F52Wm1YWsyAL+OaKz1b9ubf5N613fD1I7VChzjkydPsG/fPgwYMABlLGpj2rYLBa6jNJKy/WMok2FBr1p6k2QiIiIqzZhoKgY+Pj44ePCg2rKjR4/Cx8dHRxFRaRAel4JFf93Bn9fCIZD/3kGtK9tjbJtKOda58sRD/P0gWm2ZMhk0Z98tJKdnq6078zAaZx6qlweAkJhkhMQk5/tYUjOz8y6Uh4Udy8O3XiW8iE9FjxXnNP5Z3Tq6aYn8B0ZXV1Jy+gd9Rpca+d4+JESWZ9wxSeka+2hVxaHgwUoswcwIdhYmug6jwN71uO0sTLCod21M330D2VDcNndh79q5fm+/61sXQ3w8cOlJLBp6linUhPNCCBw/fhwxMTE4deoU+vXsiXrOclT9vsBVlTpStn8OT2qJKu5OeRckIiIinWOiqRASExPx8OFD1fPg4GBcu3YNdnZ2KF++PKZPn46wsDBs2rQJAPDxxx/jp59+wtSpUzFixAgcP34cO3fuxIEDB3R1CPQOUk6C3baaI64+fYWfTjxSW69MCC0+dA+GBoreQemZ2XiVkqFW7u8H0RrJpPx4M8kkJRcbU9iYKeZqSknPREhMwW5z3bu+G5p5WcPFxgwuNmYF/me1NJLiH/SSsA96t/RrVB6tqjjgSXQyPO3N8/W99XZ/u8+WTCZD3759cfr0adXE1s6l9O+FLts/pfU1JyIi0kdMNBXCpUuX0KZNG9Vz5VwCQ4cOxcaNGxEeHo6nT5+q1nt5eeHAgQOYNGkSli1bhnLlymHt2rUFvrUv0ZvC41Jw9HYEfjj2EDFJ6QCALf+E5rrNy/8vJzVbU2O8Ss3QWP5eNQcE3o3SWP7jh3VRzVl9vrGohDQMXPuPRm+jgLHN1P6h1DZHU/3ytmpD9N6v44zRLSvA272M2oR4hflntTR623/QS8o+6N2iTBgXpezsbISFhamG9FlaWqJTp05Fuk99wPYPERER5QcTTYXg6+sLIbTPEbNx48Yct7l69WoRRkWlyZpTj7A5KARPYwvWswcAypgZw1yu+OqnZ2YjKjFNo0zPeq5wtDZVW/YiPhV7rj7PsU4ZgL8mtcSSw/c0hkJ917dujsOwunq7adRT2ckqX72NXu8JY21mhPiUTFWPmPC4lHwlkIrjn1Ui0j8ZGRnYuXMnHj9+jEGDBsHLy0vXIZUYbP8QERFRfjDRRFQCvT6B94v4VOy9GgZAhh71XDF840XEJGn2HMoPGYCDE1vm2jtImRzKiYFMptGT6PVkkLahUAUZIpXf3kbaesIwgUREb8PIyAhyuRwGBgZITy+aHqBERERE7zImmohKmNl/3sTGcyE5rttw7slb1b0oj95BeSWBvutbF+095QhLk8PT3hzmJsYaySBtCaCCDJFisoiIdEUmk6FHjx6Ijo6Gs7OzrsMhIiIi0jtMNBHpmHKepejEdOy+/Axhr1Il30cPb1d82blagXsH5aS6kzk66uAuaEREReXx48d49uwZWrVqBUDRq4lJJiIiIqLCYaKJSId+OfUICw/elbzecb4VYWQgg4O1HO9Vd2LvICIiLWJjY7FlyxZkZ2fD0dER1apV03VIRERERHqNiSYiHdl+NQqrzkdKVl9DD1v0qOfGxBIRUQGUKVMGLVq0QExMDCpVqqTrcIiIiIj0HhNNREUtPBz45Rfgo48AFxeEx6Xg0pOYQieZ6pe3xZWnr1TPx7TywvDmXkwuERHlU1ZWFrKzs2FsbAxAcWc0QDE/ExERERG9HSaaiIpSZCRw8CDw7Blw8CD+Z1wRK24nFaiKig7maF3ZEZAB3eu6wtu9DMLjUvK8KxsREWlKS0vDzp07IZfL8cEHH8DAwIAJJiIiIiIJMdFEVBRu3AAWLAB27QIyMxXL1q3DJJkBqlZrgRU+fXHPwTPPaoY29cCcHrU0lvOubEREhfPixQuEhITAwMAA0dHRcHR01HVIRERERO8UJpqIpHb4MNCjhyLBpEwy/T8jkY3Od8+gw/0gjOk1E6cqNFBbbwDg07aVOIk3EVERcXd3R69evWBra8skExEREVERYKKJSEo3biiSTGlpgBA5FjES2ZBlCawOmIfuQ79X69l0dnpbJpeIiCQWHBwMe3t7WFlZAQBq1Kih44iIiIiI3l0Gug6A6J2yYIGiF5OWJJOSIQSMsrMwNminatm3vWszyUREJLFbt27ht99+w7Zt25Cenq7rcIiIiIjeeezRRCSVyEj1OZnyYCSy0eXuGYTMnIc+XRoyyUREVARcXFxgamoKe3t7GBjw+hoRERFRUWOiSd9cuwZYWv73vEwZwMsLSE0Fbt/WLF+/vuLx3j0g6Y27nXl6AnZ2QFQUTG7eBF6+/G+dlRVQuTKQlQX8+69mvbVrA8bGwKNHQFyc+jo3N8DJCYiNBYKD1deZmQHVqyt+v3pVs+dP9eqKMiEh6vEAijrd3ICEBODBAwCASXi4opyxsSImQDF8LSNDfdvKlRXHFBamSAi9rmxZwMMDSEkB7txRXyeTAfXqKX6/c0dR5nVeXor3IDIS8St/gXU+k0xKRiIbnxmFA0wyEREVCTs7O4wePRo2Nja8uxwRERFRMWCiSd+0bq3+fOBA4LffgGfPgAYNNMsrEznDhgHnz6uv27wZGDQI2LkTLuPHq6/r0EExqXVSUs71vngBODgAkyYB+/apr/vuO2DyZODYMaBvX/V19eoBV64ofm/aFHhzGMPNm0DNmsA33wDr1qmvmzYNWLgQuHwZaNMGAOCiXOfmpngNAKBTJ0VC6XUnTgC+vsBPPwGLFqmvGzkSWLsWePxY81hNTBTzLQGK1/rqVfX1O3cCffrg8FdL4Ld+CQolPr5w2xERkYbU1FTs3bsXvr6+cHZ2BgDY2trqNigiIiKiUoSJJn3z99+aPZoAoFw5RQJGm40bc+7RBAB9+yLc0xMuLi7/rfv/CVNhYZFzvcpG+/ffA7Nnq69zc1M8tmunua3Zaz13zp/X7NFUoYLi8euvgbFj1dc5OSkeGzRQ1RseHq6I29j4v3J//ZVzjyYAGD8e6NNHfV3Zsv/t+814X7/6vWVLjj2ami44hkxzb1xtNQTTTm1CgVlbF3wbIiLK0bFjx3Dv3j1ER0dj7NixHC5HREREVMyYaNI3devmnJgwNf1vmFxOqlbVvs7BAem1aimGj73J0DD3eitW1L6uTJn/EmE5UQ5Jy4mHR87xAIok2P/HlB4SollOOYQuJ25u/yXC3mRmlvuxKof8vabKVweQng3Aogx21WmPKad/g5HI1l7Hm4yMFD2tiIhIEu3atcOrV6/Qrl07JpmIiIiIdIAtMKJCqjTt/5NM/y/aogwOVmuBTFn+vlbC0FDRu8rRsYgiJCIqHeJfG4JsamqKQYMGqYbNEREREVHxYqKJqIDC41JQYdoB5DTt9wqfvsg0MEQW8phwViaDMDICpk8vkhiJiEqLy5cvY/ny5bh7966uQyEiIiIiMNFEVCA7Lj6Fz8Lj0DY47p6DJ8b0molMIyNFj6WcGBkBcjmiVq/OfZgfERHlKTw8HFlZWXj48KGuQyEiIiIiMNFElG/hcSn4cveNPMs5ftAN8iuXIevbV5FUep2RkWK43IULSH3zDoJERFRgnTt3Rs+ePdGlSxddh0JEREREYKKJKN86fv93nmXGtamIJX3rKnoqbd0KhIUBCxcqVi5cqHi+dSt7MhERFVJKSgr++ecfiP+/a6mBgQHq1KkDmSyPIctEREREVCx41zmifPDfexNxqVm5lhnXpiK+8KumvtDREfj8c2DkSMDWFjA2LrogiYjecZmZmdiwYQOioqKQnZ0NHx8fXYdERERERG9gjyaiPITHpeDX8yG5lpneqZpmkknJ2BhwcGCSiYjoLRkZGaF+/fqwsrJChQoVdB0OEREREeWAiSaiXITHpaDNkpO5lvnfB7XxUeuK2gs8egR066Z4JCKiAlMOkwOApk2bYuzYsXByctJhRERERESkDRNNRFoo7zCXmqHtHnNAbTdr9GlYPveK4uKAffsUj0REVCAXL17Eli1bkJX13/BlU1NTHUZERERERLlhookoB/m5w1wZMyPs+7RlMUVERFT6JCQk4NixY3j06BFu3Mj7rp9EREREpHucDJwoB91/PJ1nmSV9vYshEiKi0svKygoffPABwsPD4e3Nv7lERERE+oCJJqI3BN6JwIvEjFzLVHSwwHvVnYspIiKi0iM5ORnp6emwtbUFAFSuXBmVK1fWbVBERERElG9MNBG9Yf7+O7mur2BvjsDPffNfoZsb8N13ikciItIqNjYWW7ZsAQCMGDEC5ubmOo6IiIiIiAqKczQV0ooVK+Dp6QlTU1M0adIEFy5c0Fo2IyMDc+fORcWKFWFqagpvb28cOnSoGKOl/AqPS8Hjl8la1//vg9o4PqVNwSp1cgImT1Y8EhGRVkZGRsjIyEBmZiaSk7X/LSbdYfuHiIiI8sJEUyHs2LEDkydPhr+/P65cuQJvb2/4+fnhxYsXOZafOXMmfvnlF/z444+4ffs2Pv74Y/Ts2RNXr14t5sgpL8duR2pdV8HePO87zOUkNhb4/XfFIxERaWVlZYVBgwZh5MiRsLe313U49Aa2f4iIiCg/mGgqhKVLl2L06NEYPnw4atSogZ9//hnm5uZYv359juU3b96Mr776Cp07d0aFChXwySefoHPnzvjuu++KOXLKy7x9t7Sum9GleuEqDQ4G+vZVPBIRkZo7d+4gJCRE9dzBwQFWVlY6jIi0YfuHiIiI8oOJpgJKT0/H5cuX0a5dO9UyAwMDtGvXDkFBQTluk5aWBlNTU7VlZmZmOHPmjNb9pKWlIT4+Xu2HilYt/7+Qlp3zOrmRjJN/ExFJ7N9//8U///yD7du3IyEhQdfhUC7Y/iEiIqL84mTgBRQdHY2srCw4vTHfjpOTE+7evZvjNn5+fli6dClatWqFihUrIjAwEAEBAcjKytK6n4ULF2LOnDkay58+fVokV3qTk5PVrijrC6niXnc+AonaskwAajiYFno/JuHhcAEQHh6O9NfqKO2veXFj3MVLX+MG9Dd2fYzb0tISZcuWhYeHB16+fImYmBhdh5QvpTEp9q62f4qSPn4nAf2NG9Df2Bl38WLcxU9fY2fc6grS/mGiqRgsW7YMo0ePRrVq1SCTyVCxYkUMHz5ca1dzAJg+fTomT56seh4fHw93d3eUL18e1tbWkscYEhICDw8PyestalLEPfvPm9h0NTrXMuM71ICHRyF7NL18CQBwcXEBXou1NL/musC4i5e+xg3ob+z6EndmZiaMjP5rfnTp4ejacAAA+zpJREFU0gVeXl46jKjg2Msmf/Sh/VOU9OU7+SZ9jRvQ39gZd/Fi3MVPX2Nn3OoK0v7h0LkCsre3h6GhISIj1SeNjoyMhLNzzokIBwcH7N27F0lJSQgJCcHdu3dhaWmJChUqaN2PXC6HtbW12g9Jr+MPf2PjudyzvbXdrN9u2JyZGVCvnuKRiKgUi4mJwapVq3Dt2jXVMgMDNkX0Ads/RERElF9s3RWQiYkJGjRogMDAQNWy7OxsBAYGwsfHJ9dtTU1N4ebmhszMTOzevRvdu3cv6nApF/57b+JuRGKuZWo6W2Hfpy3fbkfVqwNXrigeiYhKsRs3biAmJganT5/OdfgUlTxs/xAREVF+cehcIUyePBlDhw5Fw4YN0bhxY/zwww9ISkrC8OHDAQBDhgyBm5sbFi5cCAD4559/EBYWhrp16yIsLAyzZ89GdnY2pk6dqsvDKNXC41Lw6/m8x62uHd6oGKIhIiodWrVqBSEEGjZsCENDQ12HQwXE9g8RERHlBxNNhdCvXz9ERUVh1qxZiIiIQN26dXHo0CHVBJlPnz5VGwqQmpqKmTNn4vHjx7C0tETnzp2xefNm2Nra6ugIqOW3x/Ms823v2nCxkWC429WrQNOmwPnziiF0RESlhBACDx48QOXKlSGTySCTyeDr66vrsKiQ2P4hIiKi/GCiqZDGjx+P8ePH57ju5MmTas9bt26N27dvF0NUlB9jN19GpvYbzMHewhj7PmspTZIJAIQA0tMVj0REpcjRo0cRFBSE5s2bo127droOhyTA9g8RERHlhYkmKlXC41Jw8FaE1vVeZc1w4ou2xRgREdG7S9nTxYw3QyAiIiIqNZhoolKl6/LTua7fOib3CU2JiCj/vL294erqCgcHB12HQkRERETFhHedo1LDf+9NRCdlaF0/vXM16YbLERGVQtHR0di1axcyMv77W8skExEREVHpwh5NVCrkdZe58mVM8VGrikWz8+rVgZs3gQoViqZ+IqISIDs7G9u3b8fLly9hbm6Ozp076zokIiIiItIB9miiUuHL36/nut6/W82i27mZGVCzpuKRiOgdZWBggG7dusHDwwOtW7fWdThEREREpCNMNNE7LzwuBaceRmtd72ZriveqOxddACEhwKhRikcioneIEAJJSUmq5+XLl8fQoUNhYWGhw6iIiIiISJeYaKJ33sazwVrXGcuAs9PeK9oAXr4E1q1TPBIRvSOys7Nx8OBBrF69GvHx8arlMplMh1ERERERka4x0UTvvJthcVrXnZrWthgjISJ6d6SnpyM4OBjx8fF48uSJrsMhIiIiohKCk4HTOy9b5Ly8bVUH3mWOiKiQTE1NMXDgQERGRqJatWq6DoeIiIiISggmmuid9r/DdxH0OCbHdQbsz0dEVCBRUVGIj49HxYqKu3SWKVMGZcqU0XFURERERFSS8F9temf98vcjrDjxSOv6ZzEpxROIkxMwbZrikYhIT0VFRWH9+vXYsWMHwsPDdR0OEREREZVQ7NFE76TwuBQs/OturmV6NyhXPMG4uQELFxbPvoiIioidnR1cXV2RkZEBGxsbXYdDRERERCUUE030TsrtTnMAYGZsgNGtKhZPMAkJwOXLQIMGgJVV8eyTiEgCQigmuZPJZDA0NETfvn1hYGAAY2NjHUdGRERERCUVh87RO2ndae2JJmMD4M43nYovmAcPgDZtFI9ERHoiOzsb+/fvx/nz51XL5HI5k0xERERElCv2aKJ3TuCdCGRqudMcADxY0KX4giEi0lN3797FlStXYGBggGrVqnHSbyIiIiLKFyaa6J2z5vRjretqunDoGhFRflSvXh0+Pj4oX748k0xERERElG9MNNE75/LjWK3rJneoUoyREBHpl5iYGNjY2MDQ0BAymQwdOnTQdUhEREREpGc4RxO9UwLvRCBDyzq5kQzvVXcu1ngAAMbGijvPcV4TIirBgoODsXr1ahw4cEA1CTgRERERUUGxRxO9U5Ye1T7h9rBmnsUXyOtq1waePdPNvomI8ik9PR3p6el4+fIlMjMzOek3ERERERUKE030zgiPS8Gt5/Fa1w9r7lWM0RAR6ZeqVatiwIAB8PT0hJERmwdEREREVDgcOkfvjC9/v651nbO1HC42ZsUYzWtu3ADKlVM8EhGVEFlZWThx4gRSU1NVyypVqsQkExERERG9FSaa6J0QHpeCUw+jta4f2UKHvZkyMoCwMMUjEVEJsX//fpw6dQq///4752QiIiIiIskw0UTvhI1ng7WuMzUywOhWFYsxGiKikq9JkyawtLREkyZNIJPJdB0OEREREb0j2D+e3gmBdyO1rjvxhW/xBUJEVIJlZWXB0NAQAODs7IzPPvuMk34TERERkaTYo4neCQ9fJOe43MLEUHdzMxERlSCPHj3CihUrEBMTo1rGJBMRERERSY2JJtJ7a0490rrOzLgEfMQrVwZOnFA8EhHpgBACJ0+eRGxsLE6fPq3rcIiIiIjoHcahc6T3dl1+pnVdy8r2xRiJFlZWgK+vrqMgolJMJpOhX79+OHv2/9i77/Cmyv4N4HeSbroHbSmlLbtAoVA2WvZQVESWiDJEXKD+rANQAcFXwIWo4Isiy8kWfAVZhbJnGbLKKB20pIvumWb8/oiNDU1KW5KcnPb+XFevkOc5Se7Wmp7zzTOOYuDAgULHISIiIqJ6zAqGexA9mOrWsH33kVDLBTEmNRWYPVt7S0RkISqVCsnJybr7zs7OGDp0KGxs+BkTEREREZkPC00kejfSCg22uzrYWMf6TOnpwOLF2lsiIgtQKBT45Zdf8OOPPyIxMVHoOERERETUgLDQVEfLly9HcHAwHBwc0KNHD5w6dara45cuXYo2bdrA0dERgYGBePPNN1FaWmqhtPXXsYR8qIz02cm4XTcRNUy2trZwcHCAVCqFUqkUOg7VIzz/ISIiovvh+Pk62LBhA6KiorBixQr06NEDS5cuxdChQ3Ht2jU0bty4yvG//vorZs2ahdWrV6N37964fv06Jk+eDIlEgiVLlgjwHdQfH+27bbTPKtZnIiISgEQiwciRI5GTk2Pw7xJRXfD8h4iIiGqCI5rqYMmSJZg2bRqmTJmCdu3aYcWKFXBycsLq1asNHn/s2DH06dMHzzzzDIKDgzFkyBCMHz/+vp8CUvWir6ahWKkx2m8V6zMREVlISkqK3o5ytra2LDKRSfH8h4iIiGqChaZaUigUiI2NxaBBg3RtUqkUgwYNwvHjxw0+pnfv3oiNjdWdWN26dQs7d+7Eo48+apHM9dX0X84a7evbyts61mcCAC8vYOpU7S0RkRncvXsX0dHR2L9/P65duyZ0HKqHeP5DRERENcWpc7WUlZUFlUoFX19fvXZfX1/ExcUZfMwzzzyDrKwsPPTQQ9BoNFAqlXj55Zfx3nvvGX2dsrIylJWV6e7n5+eb5huoJ6KvpqG0mtFMi0d3tGCa+wgKAn74QegURFSPeXl5ISwsDBKJBC1bthQ6DtVDPP8hIiKimmKhyQJiYmKwcOFCfPvtt+jRowdu3ryJN954Ax999BHmzJlj8DGLFi3C/Pnzq7QnJyfDxcXF5BmLi4uRlJRk8uc1l9d+uWy0r11jByhyM5CUa7k81ZGUlsImORnKZs2gcXDQtYvtZ16BuS2LuS1PLNlVKhU0Gg1sbLR/ytu0aQMnJyekpKQInKx2xPLzrqygoEDoCKIghvMfcxLj7zYg3tyAeLMzt2Uxt+WJNTtz66vN+Y9Eo9EYHxZCVSgUCjg5OWHz5s148sknde2TJk1Cbm4utm/fXuUxDz/8MHr27InPPvtM1/bzzz/jxRdfRGFhIaTSqjMYDX2iFxgYiLy8PLi6upr2mwKQlJSEoKAgkz+vOURfTcPUdbFG+4/PHmA90+YA4OxZICICiI0FunTRNYvpZ14Zc1sWc1ueGLKXlJRg48aNcHR0xJgxYyCRSESR2xAx5s7Pz4ebm5vZ/iZbo/p6/mNOYvzdBsSbGxBvdua2LOa2PLFmZ259tTn/4RpNtWRnZ4eIiAhER0fr2tRqNaKjo9GrVy+DjykuLq5yMiWTyQAAxup89vb2cHV11fsirQ//MD6aqbm3k3UVmYiIzCAzMxPJycmIj4/H3bt3hY5DDQDPf4iIiKimOHWuDqKiojBp0iR07doV3bt3x9KlS1FUVIQpU6YAACZOnIiAgAAsWrQIAPD4449jyZIl6Ny5s27o+Jw5c/D444/rTrioZh77+jBu55Qa7X9/OHeaI6L6r1mzZhg1ahQ8PT3h7e0tdBxqIHj+Q0RERDXBQlMdjBs3DpmZmZg7dy7S0tIQHh6OXbt26RbITE5O1vsE74MPPoBEIsEHH3yA1NRU+Pj44PHHH8fHH38s1LcgStFX03DpjvFFQR1spBgY6mfBRERElnPz5k34+fnB2dkZANCuXTuBE1FDw/MfIiIiqgkWmupoxowZmDFjhsG+mJgYvfs2NjaYN28e5s2bZ4Fk9dfKw7eq7X9rSGsLJakliQSws9PeEhHVwcWLF/H777/Dz88PkydPhp2dndCRqIHi+Q8RERHdDwtNJBqxt3KM9jnbyzAtsoUF09RC585ApYVNiYhqKyAgAI6OjvD19eWUIyIiIiKyaiw0kShEX01DuZE+KYBL84dZMg4RkUV5enrixRdfhKurKyQcHUlEREREVoy7zpEoVDdtblpkiAWT1MHVq0CXLtpbIqIaKCkpwa+//oq0tDRdm5ubG4tMRERERGT1WGgiUUjJLjbaN7mPlReaSkqAc+e0t0RENbB3717cuHEDW7duNboNPBERERGRNeLUORKFlFzDaxw520ng7+Zo4TREROY1ZMgQFBQUYPDgwRzFRERERESiwkITWb2Vh+KN9nk72VowCRGR+eTl5cHNzQ0A4ODggAkTJgiciIiIiIio9jh1jqzef2OMF5p6BTtbMAkRkXmcOnUKX3/9Na5duyZ0FCIiIiKiB8JCE1k1eV4JsouN7TcHPBXmY8E0dRQSAmzcqL0lIrqHRqNBeno61Go1EhIShI5DRERERPRAOHWOrNorP8Ua7Wvu7YTGziKYOufhAYwZI3QKIrJSEokEw4cPR0hICNq3by90HCIiIiKiB8IRTWS15HklOJ+SZ7T//eGhFkzzANLTgSVLtLdERACKi4tx4sQJ3Y5yUqkUHTp04MLfRERERCR6LDSR1dp3xXhhxtFWioGhfhZM8wBSU4G33tLeElGDp1QqsXr1auzevRsnT54UOg4RERERkUmx0ERWK+ZahtG+Zc90tmASIiLTsbGxQUREBNzc3NCiRQuh4xARtKOoj8VnQZ5XInQUIiIi0eMaTWS1ouMyDbY72ohoNBMR0T80Go1ualzPnj3RpUsX2NvbC5yKiL47GI/Ff8VBA0AqARY9FYZx3ZoJHYuIiEi0OKKJrNKr1SwC3qellwWTEBE9uBMnTuDXX3+FSqUCoF0AnEUmIuF9dygei/4pMgGAWgO8t/USRzYRERE9ABaayOrI80qw83Ka0f6+bRpbMI0JuLkBjz+uvSWiBic/Px/79+/HzZs3cfnyZaHjENE/5HklWLQzrkq7SqNBYlaxAImIiIjqB06dI6tT3SLgADCona+FkphIixbAH38InYKIBOLq6ooxY8YgMzMTYWFhQschon/svWL8Q61gbycLJiEiIqpfWGgiq7P68C2jfcPD/ODv5mjBNCZQXg7k5gLu7oCtrdBpiMgCioqKUF5eDnd3dwBAq1at0KpVK2FDEZHOhtPJmLv9itAxiIiI6iVOnSOr8t3BeCRkG14XQQJg+YQIywYyhYsXgcaNtbdEVO9lZ2dj1apV+Pnnn1FSwnVeiKyJPK8Ef/59BzO3VP83mVPniIiI6o4jmshqyPNKsOivqmslVOgR4mHBNEREdWNrawuVSgWNRoOSkhI4OopsFCZRPbUiJh6f7Pp34W9jpODUOSIiogfBQhNZjbVHE6rtnxbZ3EJJiIjqzsXFBc8++yycnJzQqFEjoeMQEbS7yy3eZfzDrMpGdgkQ3zR9IiIiKyLqqXPnzp3Du+++iyeeeAKDBg3StSclJWHjxo3Izs4WMB3V1o/HEo32hQW4YmCon+XCEBHVkEajwbFjx5CcnKxr8/HxYZGJyErI80qwuJoR0/fadu4O5Hmc9kpERFRXoh3R9O677+KLL76ARqMdAC2RSHR9Go0GzzzzDL744gu88cYbQkWkWoi+moYSpeHB7E3d7fG/1x62cCIiopo5d+4c9u7dC0dHR7z66qtwdnYWOhIRVZKQVQTN/ebLVaLSaJCYVcxRTURERHUkyhFNa9asweeff47HHnsMf//9N2bPnq3XHxwcjO7du+MPbikvGnN+v2y076W+LS2YxAw6dQLy8rS3RFTvhIWFoWnTpoiMjGSRicgKNbKT1foxTnaiPEUmIiKyCqIc0fTtt98iNDQUW7ZsgY2NDezs7Koc07ZtW+zbt0+AdFRb8rwS3MkvNdo/qJ2vBdOYgUwGuLoKnYKITKi8vBy2trYAtIt/T5kyBVIpL0yJrNGff8tr/Zjb2SXoFCjcJiTyvBLEJuVAo9Gga7AnR1cREZGoiLLQdOXKFUybNg02Nsbj+/r6IiMjw4KpqK4SsoqM9rnay8R/cnXjBjBjBrBsGdCqldBpiOgBZWZm4tdff0W/fv3Q6Z+RiiwyEVkneV4Jfjhc/WYjhuSWKMyQ5l/yvBIkZBUhxLuR3nlO9NU0rDx0CycScnRtEgCLR4VhXLdmZs1ERERkKqIsNNnY2EChqP4E4M6dO5zCIBJ7L6UZ7XttYD0ozBQUAHv2aG+JSPQuX76M3NxcHD16FB06dIBMVvtpOURkGWcSs1GL5Zl0Pth2GUUKFV6KbGHyTJ/tisPymHgA2iLS9P4t8PbQthj65UFcSy+scrwGwMwtFxHZ2kf8H74REVGDIMpCU1hYGPbv3w+VSmXwBL+4uBj79u1DRESEAOmotrZduGO0b5oZTvCIiB5E3759IZFI0LVrVxaZiKxc5c1iamvRzjhAA7zU13TnIlPWnsKBuEzdfQ2AZQfisfpoAooV6mofezYpB8M7stBERETWT5Rj/Z9//nlcv34dL7/8MsrKyvT68vPzMXnyZKSlpWHatGkCJaTaKC4rN9jubC/KX08iqmc0Gg3i4uL0djnt27cvGjVqJHAyIrqfQI/qCzP3K0Mt+isO8rwSk2T5fHecXpGpsvsVmQAg8a7xpQaIiIisiSiv5J9//nk8/fTTWLVqFXx8fLBq1SoAQPfu3REQEIDNmzdj0qRJGD16tMBJ6X7keSUoUxnuC/XjAtpEJLxdu3Zhw4YN2L9/v9BRiKiW7rcQ+Kv97z9a6f9+O/fAOeR5JVh2IP6BnuNcUs79DyIiIrICopw6BwC//vor+vfvj2XLluHSpUvQaDQ4c+YMQkND8frrr+Oll14SOiLVwKNLDxnteyI8wIJJzCgwULsQeGCg0EmIqA78/f0hkUi47h+RyMjzSrDqiOGFwCUAZj3aFmEBblh+nwLQycQcXLidU6Nd6C7czsGpxGx0D/aEPL0Ye5Lj0T3YE/P+uFyXb0HPvrhMPP7NYfzvtYchzyvBvivpuJiSh2KFEk72NugQ4IrB7fy4jhMREQlOtIUmAJg2bRqmTZuGkpIS5OTkwNXV1WIXAsuXL8dnn32GtLQ0dOrUCd988w26d+9u8Nh+/frh4MGDVdofffRR7Nixw9xRrVb01TTklCiN9g9q52vBNGbk4wNMny50CiKqo/DwcAQGBsLLy0voKESCE9P5T0JWEdQGVgJ/LMwf7z8WCn83R8jzSiAB7rtg+LpjiXhnmEO1RZxXfo7FX9VscGIKF1Pz8dDiaKTkllbp23gGmLv9CnqEeODFyOYYGOpXq+euKF7dSEnHKKlrjQprREREhohy6tyhQ4eQnJysu+/o6IgmTZroFZlu376NQ4eMj5Z5EBs2bEBUVBTmzZuHs2fPolOnThg6dCgyMjIMHr9161bI5XLd16VLlyCTyTBmzBiz5BOLD6v5dK9zoFv9+UQuOxv4+WftLRFZvZycHGzatAnl5f+uH8ciE5H4zn+O3cwy2D4tMkTvHKMmu9JtPXcHvRftx4bTyQb7P98dZ/YiUwVDRabKTibkYOq6WDz17VEA2gLSsfgsvbWm7m377mA8ei3ajznbL+PH2CyMWH4Mr/4Sa5b8F27nYMnea1i08wq+2BOHC7c5JZCIqL4R5Yim/v37Y968eZg7d67RY3788UfMnTsXKpWRBYAewJIlSzBt2jRMmTIFALBixQrs2LEDq1evxqxZs6oc7+npqXd//fr1cHJyatCFpu8OxuN2jvETpW+frUc7BiYmAs89B8TGAvf8LhCRdVGpVNi/fz8KCgrg4uKCYcOGCR2JyGqI6fynujWRKi+8nZBV8wW2NQBmbbmItn4ueqN9TLH+UmXtm7jg8p2CB36es8m5eHvDeWw+lwpAO11w8agwXEnNx7oTSQAAqQTo29oHB65VXaR858U0fLYrDu8Ma1ulT55XgoSsIoR4N6rxB4PyvBI8v/Y0rsr1v7dv9sfD39UeQV5OaGRvAy9ne900QAA1fp0Lt3Pw05E7cLlQgCc7B3BEFhGRgERZaKrY+ac6arX6gba0NUahUCA2NhazZ8/WtUmlUgwaNAjHjx+v0XOsWrUKTz/9dLU7FpWVlentqJefn1/30FZGnleCRX/FGe3v28q7/oxmIiJRkclkeOihh3Dt2jVERkYKHYfIaojt/Oeb/TcNtksABHs76e6HeDeCVAKDU+wM0QAYsfwYPhkVhnHdmmlfK/pGnTIaMvvRtugZ4okRy4+Z5PkqikyANvvMLRf1+tUaGCwyVVgeE49newXpnZd9tisOy2P+LaxV/lkA/xahLqfm4cStu2jn74or8nxEG9lxDwDk+WWQ5//7371iGmAFqQRY9JT2de4tclUtYGVjzbEktPRphC/GdmLBiYhIAKIsNNXEjRs34ObmZvLnzcrKgkqlgq+v/vpBvr6+iIszXjypcOrUKVy6dEm3U54xixYtwvz586u0Jycnw8XFpXaha6C4uBhJSUkmf15Dtl26W23/jJ5eNc5iydx1ZSeXwx+AXC6HolJWMWQ3hLkti7nNT6PRoLS0FI6O2gspFxcXPPzww8jMNH5RZI3E9DOvTIy5CwoefLSJ2Ijp/CejsBy/nTQ8xe3xUHcocjOQlPtv29t9m+Dzg3dqXGwCtCOb3DRFkBeU49dTt2v+wH8819kbT3TwwrHEfNzOLUOgux16B7uhsbMNoM7HsDZu2HUtr9bPaw6r913CkLYeSMkrw3+PyXE9q0yvf+aWi0jLyETjRnb49VwGLqbrj1ivrsBUU2qN9nW++OsKMor/na3g52yDtELD633ezCzCiOXH0Le5KxYMbWbwGGshxvdBgLktTay5AfFmZ259tTn/EU2h6fnnn9e7v23bNiQmJlY5TqVS6dZneuSRRyyUruZWrVqFsLAwowtnVpg9ezaioqJ09/Pz8xEYGIhmzZrB1dXV5LmSkpIQFBRk8uc15O8D6Ub7JvcOQrf2LWv8XJbMXWd3tYU1f39/oFJWUWQ3gLkti7nNS6VSYceOHYiPj8cLL7wAFxcX0WS/F3NbTn0aZWwpljz/SY3PMrru0tQB7RB0zwiXV4OCMLJXWyRmFeNGRr7eSBpjNABe3nqrRnnuFeTpiI/G9QAAdGtv+JgVU4Jw4XYO/rPjKk4nCruG0e9XcrDytOF1uCp8edgy61NVLjIBMFpkquzgrXxsvFpicAqgtRDj+yDA3JYm1tyAeLMzt77anP+IptC0du1a3b8lEgnOnz+P8+fPGzxWIpGgW7du+PLLL02ew9vbGzKZDOnp+sWS9PR0+PlVv7tHUVER1q9fjwULFtz3dezt7WFvb/9AWa1VfKbhSqitFPjwiQ4WTmMBjRoBPXtqb4nIqigUCiQnJ6OgoADJyclo397IVR9RAyem858Qb+N/byuvz1SZv5sj/N0cEezthHnbr9RogfC6+np85xod1ynQAx8MD612Gl2wpxMSs4tNFc2grKLy+x9k5QxNASQiIvMRza5zCQkJSEhIwK1bt6DRaPB///d/urbKX8nJycjPz8eJEyfQsmXNR8bUlJ2dHSIiIhAdHa1rU6vViI6ORq9evap97KZNm1BWVoZnn33W5LnE5E624UXAA9zr6R//Nm2A48e1t0RkVRwdHTFhwgSMHz+eRSaiatSX8x8nu+pPff3dHDG+h/mmWY3qUrtFqjsFemBUlwC9tubeTnhjQEtsn94bMe/2xyejwkwds176cu81vZ33iIjIfEQzoqny0K81a9agc+fOgg1ji4qKwqRJk9C1a1d0794dS5cuRVFRkW4XlokTJyIgIACLFi3Se9yqVavw5JNPNuhtsqOvpkFh5GPClo2dLRuGiBqk9PR0FBYWokWLFgAADw8PeHhwsVii+xHL+c/qIwlG+4yNaKrstQEt8auRNZ5qoqWPE25mVh1ltGpSBAaGVj/6y5AvxoZjYq8gnEnMQddgjyqFqnHdmiGytQ/OJuVg+q/n6pzbkho720GhVCG31PS7Qxuz8UwqNp5JxeTeQfVzBD0RkRURTaGpskmTJgn6+uPGjUNmZibmzp2LtLQ0hIeHY9euXboFMpOTkyGV6n9idu3aNRw5cgR79uwRIrLV2HQmxWhf3zaNLZjEgs6eBSIigNhYoEsXodMQNWjp6elYs2YN1Go1nn/++ftO+SGif4nh/EeeV4JVRgpNUujvOGeMv5sjPhkVhtlbL9ZqgfAKbw5ug8Iype7xFTum1aXIVKFTYNUC072Zh3d0RGGZssrOcjU1uXcQ1h4z/6K3M/q3wNtDteslRV9Nw86LcoR4OyPU3wV7rqTjdEI2bmXVbTqgo40EJcrq/6OtPZaEn08kITzQHWEBbniyc+1GmRER0f2JstBUobS0FKdPn8adO3f0tsKtbOLEiWZ57RkzZmDGjBkG+2JiYqq0tWnTBhqNOWf8i0NWoeH/TgAwqJ2v0T4iIlPw9vZGQEAAVCqVWXYmJarvrP38JyGryGhxaNGosBqv0VMxSuib/Tfw68na7SrXJcgD/m6OaO6kgNLBA8HeThZbG6gi99azKTidmI2Ya1kGj9s+vTcupubhVmYRQrwbYVA7X/i7OcLZ3gbLDsQ/cA7PRrbo08ILbk62SMkpgYu9DbqHeOlep8LAUD+9AlzFv+V5JVhzNAHfHzI+Oq2yxs52WDmpK9zV+Xhu/U0k5xhepqGCUg2cScrFmaRcrDmWhFaNG+HHqT24hhMRkYmIttC0fPlyzJkzB3l5hrd+1Wg0kEgkZis0Ud0UlRkeIu3vas8/7kRkFhV/DwBAJpNh7NixkMlksLER7Z9AIjKikZ3MYHtdpq35uzli4ciO0GiA307VrNj0TPdA3flMY2dbBAVZfrkEfzdHTO/fCgCw4XSy3ggnCYDFo8KMjpB6e2hbxFy5g0vphtcy8nO1x3fPRaCxqwOir6YjJi4DSdlFsLORwd/VAc08G2FE5yYPPELI380R7z3aDlP6hOBsUg40GiDQ0xHFCjVScorwd0oe3B1tkVtSjn5tfHT/bZOS8jGmWyC+2HOjVq93I6MIvRbth1cjG7Tycca0vi0eaAQaEVFDJ8qz7K1bt+K1115DWFgY5syZg7feegtPPvkkevTogUOHDuGvv/7CqFGj8Nhjjwkdle7h2cjWYHsLH+7IRkSmp1Kp8L///Q9+fn7o2bMnANTbHT2JCChSGP5Ay8nO8PlHTbw+sFWNCk0SAK8NbFXn1zGHyus3aTRARLDHfT/YW/5UC7y4NRHX0gv12ge08cHqKd1195/tGYxnewabI7ZOxZRAfV4Y09X4Y0ZH1L7QVOFukRJ3i3JxIjEWHo42WPt8d06rIyKqA9HsOlfZ0qVL0bhxYxw/fhxvvvkmACA8PBwzZ87Ejh078PPPP2Pbtm2CLRZOxl24nSN0BCJqQK5cuYILFy5g7969RkfAElH9EeJd9YMrCWq2NpMx/m6OeKZ7YLXHSCXakULWODpbW6xpgsc6Nalxvt1v9sWqSRF4pIMvxkU0xfbpvfWKTNasYo2tB5VTosSI5cfw1sbzDx6KiKiBEeWIpr///htjx46Fk9O/Jw0q1b+fYD3zzDNYt24dFixYgH79+gmQkAyJvpqGQiNbzhWWKS2cxoLatQNu3ACaNhU6CVGD06FDB8jlcoSEhHBNJqKGSvLgT/HawFb41cCopun9W+Chlj4WXYfJUu5dP0lMKkZyJWYVY9dFOdadqPsi51vOpsLV3gYKtRoD2jYW7c+EiMiSRFloKi8vh4+Pj+6+o6MjcnNz9Y7p1KkTvv/+ewsno+qsPHzLaF+P5pZfw8BiHByAli2FTkHUYGRlZcHT0xNSqRQSiQRDhgwROhIRWchqAzvOaTRAYlbxAxWCdDvRbbkINbS1q1mPtsVLkS3qHpbMyt/NEf5ujujVwgsv92+BrWdTcORGJtLzS3Ery/AaVMasOa4tVP1y8jacbKWYP6I9xnRtZo7YRET1gigLTU2aNIFcLtfdDwoKwrlz5/SOSUpK4kKvViYl2/hWtZP7hFgwiYUlJABz5gAffQSE1OPvk8gK3Lx5E5s2bUKHDh3w2GOP6RYBJ6L6T55XglUGCk1SPNjUuQqVR8nUxxFM9VnFAukVi6QDwNsbzmPzudRaP1dxuRrvbL6IWVsu4pEOfpgW2ZzrOBER3UOUazR169YNZ8+e1d0fNmwYjh49ikWLFuHy5cv47rvvsHXrVnTr1k3AlHQvG6nhXzevRrb1+2QtJwf45RftLRGZlVKphEKhQHZ2NpTKejwll4iqSMgqgtrADP0XIkNMdp5RMUKmXp+3NBCfjwvH8dkD8GyPQAR5OsChluvFqzTAnxfTMGL5Mbz6S6x5QhIRiZQoC01jxoxBWVkZEhMTAQCzZ89G06ZN8cEHH6Bjx4545ZVX4OzsjE8//VTYoKQnq7DUYHuon4uFkxBRfdW2bVs8++yzePbZZ2FrW/ddpohIfC6mVl3wXwJgSn0eNU0PxN/NEf8Z2REH3x2IuI+Go08Lzzo9z86LaXh+7SkTpyMiEi9RFppGjhyJq1evIjg4GADg4+OD8+fPY/HixXjxxRexcOFCXLp0CWFhD77jBJlGdQuBO9jJLJyGiOoLlUqF6OholJb+W8hu0aIFZDK+rxA1JPK8EnzyV1yVdsNnHkSGvTusbZ0fuz8uE63e24FNZ5IBaHdaXnk4njsuE1GDVG8WMfLw8MA777wjdAwyYtOZFKN9xqbUERHdz/bt23Hx4kXI5XJMmDCBazIRNVDGps0BD74QODUcnQI9MKpLALacrf3aTQBQrgbe2XwRMzdrF42vYCeToFuwB94d1pbrORFRg1BvCk33Onz4MObMmYOYmBihoxAAVwfjv2pjuja1YBIB+PsD8+Zpb4nIpHr37o3ExET06tWLRSaiBizEu5HBdlMtBE4NxxdjwzGxVxC2n7+D5OwiFJYpkVtcjri0who/h/qe+wqVBkfjszFi+TE42EjQzNMJjext0KqxMyb0DIK7Sb8DIiLhibLQlJ2dDRsbG7i6ulbpO3HiBObMmYP9+/cLkIyMMvIpo2cjWwwM9bNsFkvz9wc+/FDoFET1hkql0k2N8/Pzw+uvv85dRokaMHleCfZdSTfY90q/FhzNRLXWKdCjysgjeV4Joq+mY/u5VJxOyq3zc5cqNbieUQQAOHc7DxtjU2EvA4K8EuDZyA59WnljdEQgf2+JSNRENWdpw4YNaN68OXx8fODh4YFOnTrh2LFjAAC5XI6nnnoKffr0QXR0NLp06YI//vhD4MRUYW9chsF2TUNYPCE/H9i9W3tLRA/k+vXrWLZsGbKzs3VtLDIRNVwbTiejz+L9mLP9ssF+z0Z2Fk5E9ZW/myOe7RmMTa/0waguASZ97jIVcD2jCCcScvDFnhvotWg/vjsUb9LXICKyJNGcnUdHR2P8+PEAgEaNtMOjL168iEcffRR79uzByJEjIZfL0aVLF8ybNw+PP/64kHHpHoUl5QbbS8sNt9crN28Cw4YBsbFAly5CpyESLY1Gg0OHDiE3NxdHjx7l+zxRAyfPK8HsrReNrs0EAF2DuR4OmV7F9Lpx359Aafm9E+VMY9HOOHy7/wY8nGzRyN4WjnYy5BYrUKxQoUypRls/Fzz/UAju5JbiVlYRQrydMLiddpZAQlYRQrwbGRwVdeF2Dn49mYzr6QXILVYgt1gJCTRwc7JFkKcTnusdXP9nGxCR2Ymm0LR06VJIpVL8+uuvGDt2LADgt99+w7PPPovBgwejvLwcP/zwA55//nmBk9K95HklKDdyEujVyN6yYYhItCQSCcaNG4cTJ05gwIABQschIoFVtwB4hcauDpYJQw1Op0APxH30CFYeisfHO6vueGgKeaUq5JWqAJRW6Tsan42j8dl6bXO3X9G7PzzMDy9GNsfKw7dwKTUXafmlKDXyGW92iRIJd0sQc+MuwgJc8b/XHsaF2zk4lZiN7sGeXMSciGpFNIWm06dPY/jw4boiEwCMHz8ev/32G3bs2IE1a9Zg4sSJAiYkYz41sN1wheEdm1gwCRGJjVKpxJ07d9CsWTMAgIuLCwYPHixwKiKyBiHejSCVoNpiE3ecI3ObFtkCro62mLnlol57y8aN4Opgg4u384x+4GpuOy6mYcfFtFo/7mJqPkJm7dBbYrWi+EREVBOiKTTdvXsX7du3r9Levn177NixA08++aTlQ1GNHLpheH0mAJjcJ8SCSYhITMrKyvDbb78hJSUFzz33HIKCgoSORERWxN/NERFBHjidmGOwnzvOkaWM69YMka19cDYpBxoNEBHsoVfgjL6ahuUHbuJSSh4U5plpZ3L31sYupuYjeNYO+LnaY0xEU7w1tK0guYhIHERTaFKpVHBwqDr8uaLN0A50ZB2c7W1wt0hZpd2rkU3D+JTR3h5o0UJ7S0Q1ZmdnBycnJ9jY2ECtFsmZORFZjDyvBGeMFJkAYNGosIZxnkFWwd/NEcM7Gv59Gxjqp1v36MLtHJxJzIFao8FPxxORnFN1Wpw1S8svwzcH4vHfg7ew7MkQLDhwCnHyfKg1gK1Mgodae+O1Aa35/x5RAyeaQhOJ1xOdAvDNgao7ZzzTvYGMTmjfXrsgOBHVikQiwciRI5GXlwdvb2+h4xCRlUnIKqoy6qKCBEBkax9LxiGqkU6BHrr1jqZFtoA8rwS7z9zAtqv5OJ+SJ3C6mlOqNXh5660q7b+eTMGvJ1PgYi+Di4MNmrg7IizADU92DuA6T0QNiKgKTcuWLcP69ev12rKysgAA7dq1q3K8RCLB5cuGt7sly0m4W2SwPdFIOxE1XNeuXUN6ejoiIyMBALa2tiwyEZFBId6NjPZpwPWZSBz83RzRv6UbJg/siAu3c/Dab+eQnF1i8FivRoZnCdSVt7MtFOUq5JeZftRwQZkKBWUq3Mkrw5mkXKw5lgTPRraY/UhbjOnazOSvR0TWRVSFpqysLF1h6V5xcebZ7YEeXHyG4YKSsfZ65++/gYEDgehooGNHodMQWa3MzExs2LABGo0G/v7+aNWqldCRiEikuD4TiVGnQA8ceneAbnpdsLcTSsvVeus+bTidrLfweKifM5wdbHAntwT2NlJkFJSh0EDhSCYB/N3s4ePqgIFtfTEqoqmuEPvWxvPYcjbV7N9fdlE53tl8Ee//fgkfPBaKTk3dUaRQIcS7EYvCRPWMaApNXJ9DvGxlEoPtLXyMfxJZryiVQFaW9paIjPLx8cFDDz2EwsJCNG/eXOg4RGTlvom+YbTvlX4teOFKolV5et29KhYeT8wqRrC3k8Hf8wu3c/DrqWRcTs2DjVSCCT2Dqh1F9MXYcEzsFYTt5+/gePxdpOYWw9neBoVlSuSXqkz2fVVQqDSYu/2KXpurgww+LvZ4uW8LjngiqgdEU2gicZLnleDv1HyDfR0D3S0bhoisTnl5OSQSCWxstH+O+vfvD0A79ZmIyBh5Xgl+O3XbaH+oPzeJofrL382x2kJqdYWq2j7mwu0cfLP/Bk7dykZ+memLThXyS1XILy3GO5svYuaWi/BztYdaA+5wRyRSUqEDUP326V/GpzQmZxdbMAkRWZvi4mL89NNP+P3336HRaJf0lUgkLDIR0X1VtxA4APBthMg0OgV64IdJ3fH3/GGY/YhlCj5qDXAnr0y3w13bD/6yyOsSkelwRBOZ1aEbGUb7+rXhbjBEDVlmZiZSU1Nha2uL7OxseHl5CR2JSFROnTqF06dPIzc3FypV1ZEGEokEc+bMESCZ+VW3ELhEAnQJ4u5WRKb2Ut8WeCK8CT79Kw4nEu7Cy1GCcT1aYFA7XwDAuqMJ+PNvOQpKy2ErkyKrqNwkr1uqVKPNBzvQq7k3AjwcUa7UABKgQ4ArBrfzg7+bI+R5JVh7NAGHrmcir6QcZUo1Atwd0djFHvL8UqTllUKhVKN3C0+8EOGJBrL3NZFgWGgis9IY+bjRTibBwFA/y4YRSuvWwLFj2lsi0gkKCsKoUaPg4+PDIhNRLWRnZ+PJJ5/E0aNHdaMBDanPhSZjJAAWPxXG9ZmIzMTfzRFfPt0ZAJCUlISgoH9LNrMebYdZj/67E/i9C5c/iDIlEHNdf1OojWeAuduvwNVeZnBa310Dha7dVzKx+0omhrTLwfwRHfheQWQmLDSR2cjzSpBdbHgB7HeGtrFwGgE5OwO9egmdgsgqXL9+HU2aNIGzszMAoF27dvd5BBHdKyoqCkeOHEG/fv0wadIkNG3aVLfOWUOx+kiCwfZlz3TG8I5NLJyGiAypWLj8bFIOEu8W4fuDt5BXavrNceqydtSeKxnYc2U/mro7oEMTV4zpFqj3Ibg8rwQJWUXcEY+ojhrWWQlZ1L4r6Ub7OgS4Wy6I0FJSgCVLgKgooGlTodMQCeb8+fPYvn07mjRpgsmTJ8PW1lboSESi9Oeff6J79+6Ijo5ukGuayfNKsMpAoUkKTpkjsjb+bo4Y3lFbqJnev5VucfGr8nxotDPgkJZXBvMtM169lNxSpOSWYteVDMgkQDNPR5SWqyHPL9MdM6N/C7zNBcmJaoWFJjKbP86nGu0L9nayYBKBZWQAX34JPPssC03UoDVr1gyOjo5o0qQJZDKZ0HGIRKukpASRkZENssgEaBcCVxuYMfhCZAhHHhBZuYrFxe+16Uwyvj90C3cLy4zOiDA3lQZIuFtSpX3ZgXjEZxbhv89GCJCKSJy461wdLV++HMHBwXBwcECPHj1w6tSpao/Pzc3F9OnT4e/vD3t7e7Ru3Ro7d+60UFph3MgoMNjuZCvhiSBRA+Tp6YmXX34Zjz76KKRS/vkhqqvw8HAkJiYK8trWcP7TyM5wodqW7ytEojWmazPsjeqHs3OHYtUk6yvo/HUpDf0/34+HFu9Dt//sRY+P92LgFwfQecEedFmwB1/sNr7TNlFDJOq/yL///jvGjh2Ljh07omXLlrr2uLg4fPrpp0hNNT6i5kFs2LABUVFRmDdvHs6ePYtOnTph6NChyMgwvMOaQqHA4MGDkZiYiM2bN+PatWtYuXIlAgICzJLPWjjYGh4w5+poZ+EkRCSEoqIi/Pzzz0hP/3caraura4MdhUFkKvPmzcMff/yBEydOWPR1reX8p0hheJLNf2PiIc+rOhqBiMRlYKgfujRzr/Pjbcx0hZuQVYKU3DJkFiqQXqBAfGYxcorLkV1cjm8OxCN41g70/zQa0VfTzBOASEREOXVOrVZj/Pjx2Lx5MwDA0dERJSX/nlh4eHjg/fffh0qlwuzZs03++kuWLMG0adMwZcoUAMCKFSuwY8cOrF69GrNmzapy/OrVq5GdnY1jx47p1iQJDg42eS5rIzNyLenrYm/ZIEQkiL179yI+Ph4FBQV4+eWXWWAiMpG0tDQMHz4cffv2xYQJE9ClSxe4uroaPHbixIkme11rOf8J8W5ksF0NIDGrmKOmieqBra/2QfTVNMRcy0S/Nj7ILlLgl5NJkEgkaN/EFbGJOUjKLoKLvS3cnWwhk0jwcGsfTO6jnUJ74XYO9sdlwNvZHoPa+cLfzRFh83ahoA4Lh9dGQnYppq6LRWNnO5z6YDAu3M5BdFwGvJ3t0KmpO4oUKi4wTg2CKAtNX375JTZt2oSXX34ZixcvxpIlS/DRRx/p+n19ffHwww9jx44dJi80KRQKxMbG6j2vVCrFoEGDcPz4cYOP+eOPP9CrVy9Mnz4d27dvh4+PD5555hnMnDnT6DolZWVlKCv7dxG6/Px8k34f5ibPK0FqXpnBvgZ3rentDbz6qvaWqAEZOnQoiouLMWTIEBaZiExo8uTJkEgk0Gg0WLt2LdauXVvl/zGNRgOJRGKyQpMYzn+kaGBrQBLVcwND/fR2ghvTtVmNH9sp0AOdAvU3B7g4fxg2nUnG4j8v426p2mQ5DckoVCB41g6j/R6ONhjczhcTegZVyUlUH4iy0LR27Vp069YN3377LQAYvIBp2bIlduww/j93XWVlZUGlUsHX11ev3dfXF3Fxhufm3rp1C/v378eECROwc+dO3Lx5E6+++irKy8sxb948g49ZtGgR5s+fX6U9OTkZLi4uD/6N3KO4uBhJSUkme76P9yYb7Qv1tjHZa5k6t9m8+y6g0QCVsoom+z2Y27LElrugoAAuLi4oLi5GRkYG+vTpg6KiIhQVFQkdrcbE9jOvwNyWU1BgeA1CS1mzZo3FX9Oazn/OphYafOzYTl5Q5GYgKbcW35gZifF3GxBvbkC82Znbcrr7AD+PC0ah2hapeWW4nlGCtbEZKC7/d4cBOymgMG8dCjklSmyMTcXG2FQ097THaw/5w9FGihKlGk3d7NHYuerOvGL8eVcQa3bm1leb8x9RFppu3ryJ6dOnV3uMl5cX7t69a6FE1VOr1WjcuDG+//57yGQyREREIDU1FZ999pnRE63Zs2cjKipKdz8/Px+BgYFo1qyZ0eHxDyIpKQlBQUEme75YufEF8V5/JNxkw0VNndssiouBuDigbVvA6d9PWkWR3QDmtiyx5NZoNDh+/Diio6Mxbtw4ODk5iSK3IWL5md+LuS1H6FHGkyZNEvT1a8pc5z+7kuKrPE4qAd54tJNVTUcR4+82IN7cgHizM7dlJSUlITQoCN3+uf/uk8CF2zk4k5iDrsHakVBtPtiJMqWB7S3N4FZ2Gd78I1GvLTzQFf99tqvee5pYf96AeLMzt77anP+IstDk6OiIvLy8ao9JSkqCu7u7yV/b29sbMplMb3FbAEhPT4efn5/Bx/j7+8PW1lZvmHhoaCjS0tKgUChgZ1d1cWx7e3vY24t3LSNnexvcLaq6NalXIxurOgm0iLg4ICICiI0FunQROg2R2WRlZUGtViMpKQmtW7cWOg4RmZC1nP/I80rwyV9VP8yaOaxtwzu/ICKTuXeq3bX/PIoeH+9FeoFC7zgPRxvYyKSQSYC0e/pM6fztfPRatB9dm7lj86t9zPY6ROYiykJT586dsXv3bpSWlsLBwaFKf3Z2Nnbt2oXIyEiTv7adnR0iIiIQHR2NJ598EoD2E7vo6GjMmDHD4GP69OmDX3/9FWq1Wrel9/Xr1+Hv72/wJKs+6BHshaTsqrv+DWzja+BoIhI7iUSC4cOHo2XLlggNDUVysvHps0RkGomJifjll19w/vx55Ofnw9XVFeHh4ZgwYYLJNx2xlvOfhKwiqA0MMujY1L1Oz0dEZMzJ9wcj+moadl6UI8TbGaMimlYpaK88FI8tsSmITy9EuRkynEnORfCsHfBztUNRqQKPdMjBp2PDzfBKRKZlps0fzev1119HSkoKRo0ahZSUFL2++Ph4jBw5Enl5eXj99dfN8vpRUVFYuXIl1q1bh6tXr+KVV15BUVGRbheWiRMn6i2W+corryA7OxtvvPEGrl+/jh07dmDhwoX3nf4nZneLDVf4c0rM8RZMREIoLCzE8ePHodFor/pkMhnatWvHhb+JLOCrr75CmzZtMHfuXGzZsgV79+7Fli1bMGfOHLRp0wZfffWVyV/TGs5/QrwbQWrgLebvlNw6PycRkTEDQ/3wxdjOmDGglcFRk9MiW2DXm31xY/FwtPF1NluOtHwFChTAxrOpaDHb9OsQE5maKEc0jRgxAjNnzsQnn3yCoKAgNGqk3ea2cePGuHv3LjQaDebMmYMBAwaY5fXHjRuHzMxMzJ07F2lpaQgPD8euXbt0C2QmJyfrPrkDgMDAQOzevRtvvvkmOnbsiICAALzxxhuYOXOmWfJZg5TsEoPtakMfQxKR6JSXl2P16tXIycmBVCpFjx49hI5E1GD8+eefePPNN+Ht7Y0333wT/fv3h7+/P9LS0nDgwAEsWbIEUVFRaNmyJYYPH26y17WG8x9/N0fMHNYGi/66ptf+6a5reCK8CafPEZFgdr/ZF9FX07D8wE3czi6GvY0MXo3scLdIAaVKu7q4KabbqTTAuxvPc2QTWTVRFpoA7a4kAwYMwLJly3Dy5EmUlpZCrVZj2LBheP311zF06FCzvv6MGTOMDhWPiYmp0tarVy+cOHHCrJmshTyvBNcyDO8Ik3BXPDtPmYxUCri4aG+J6glbW1t069YNp0+fRsuWLYWOQ9SgLFmyBJ6enjh79iyaNm2qaw8KCkKPHj0wYcIEdO7cGUuWLDFpoQmwjvOfVr5Vd99VaTRIzCpmoYmIBDUw1A8DQw2vWwdor5POJuXgva1/I69UVefX2Xg2FUPDqn8tIiGJttAEAIMHD8bgwYOFjkH32Hcl3Whfp6ZuFkxiJcLDAYF3KCIylcprrfTs2RNdunQR9cYFRGJ09uxZTJgwQa/IVFlgYCDGjh2LX3/91cLJLMPTqer6TjKJBMHeTgaOJiKyHv5ujhje0RHDOzZB9NU0/HD4Fm5nFwMA0vPKUF6LyR9T18WiSzN3bOVi4WSFRFlounnzJj9Bt2IZBaVG+959JNSCSYjIVDQaDY4ePYrExESMHz8eMpkMEomERSYiASgUCt2yAcY4OztDoTDfjkhCirmeqXdfAmDhUx04momIRMXQ6Kfoq2l4d/PfuFtUs3VtzybnYuWheEyLbGGOiER1Jsq5PK1bt0afPn2wYsUKZGdnCx2H7tHM0/AnimMiAhrmSeCVK0D79tpbIpHKy8vDoUOHEB8fj6tXrwodh6hBa926Nf73v/9BqVQa7Fcqlfjzzz/RunVrCyczP3leCZbuu6HXJpEAka19BEpERGQ6A0P9EDtnCLZP741BoT5wtrv/Bisf74zDWxvPmz8cUS2IstD02GOP4cyZM5g+fTqaNGmCkSNHYuvWrfX2kzuxuXKnwGC7i4OthZNYidJSbZGp1PhILyJr5+7ujtGjR2Po0KHo0KGD0HGIGrSJEyfi2rVrGDp0KGJjY/X6zpw5g0ceeQTXrl3DpEmTBEpoPquPJFRpU2uAxKxiAdIQEZlHp0AP/DCpOy4teBSuDvefhLTlbCpe+vEU5HmGN2QisjRRFpr++OMP3LlzB1999RU6deqE7du3Y8yYMfDz88NLL72Ew4cPCx2xQcs0MnXOWDsRWaeCggLk5ubq7rdu3Ro9e/YULhARAQDeeOMNPPHEEzhw4AC6d+8OFxcXtGjRAi4uLujRoweio6PxxBNP4I033hA6qknJ80rww+GqhSYpwPWZiKje+vvDobC9/8Am7L6SiV6L9uPz3XHmD0V0H6IsNAGAl5cXZsyYgZMnT+L69et4//334eHhgZUrV6Jfv35o3rw55syZI3TMBimn2PDIspwijjgjEousrCysWrUKv/zyC0pK+OkYkTWRyWTYtm0b1q5di379+sHOzg7Jycmws7ND//79sW7dOvz++++6hfvri4SsIhhaJ/eFyJCGOTWfiBqMG4uGo72vQ42OXXYgHm3e34FhSw9i05lkMycjMqxenIG0bNkSCxYsQHx8PI4cOYJp06YhNTUVCxcuFDpag5RtZPE6Y+1EZH3s7OygVquhVqtRVlYmdBwiMmDixImIjo7G3bt3UV5ejrt372Lfvn147rnnhI5mFo3sZAbbh4f5WzgJEZHlfftUSzzSwe/+BwIoUwFxaYV4Z/NFtJ+7y8zJiKqqF4WmCjdu3MDu3buxb98+lJezqCGUFj6Gd8Ix1l7vNW8ObN+uvSUSCVdXVzz33HOYOnUq3N3dhY5DRIQihcpge7FCbeEkRETC+O+zEXishsWmCkUKFYJn7cDKQ/FmSkVUlegLTVlZWfjmm2/Qo0cPtG3bFh999BFycnK4VpOA+rYxvPNLpJH2es/dHXjiCe0tkZXSaDQ4cuQIkpP/HWLt4+MDJyeue0JE1iHEu+oHVhIJ12ciooZl2bMRsJPVYNGme3y8Mw5dPtpjhkREVd1/CXsrVFpaim3btuHnn3/G3r17UV5eDjs7O4wYMQLPPfcchg8fDjs7O6FjNljGdp27KjfcXu+lpQFr1gBTpgB+tfsEgshSYmNjER0dDUdHR8yYMYMFJiIrIpVKIZVKceXKFbRu3RpSqRQSyf0vMiQSCZRKpQUSCsjQok1ERPXc9Y8fxfztl7D2eFKt3gazi8rR5v0dsLORYXSXppg3gjsJk3mIstDk6+uLwsJCaDQa9OrVC8899xzGjRsHDw8PoaMRgN/P3jbY3mB3nbtzB3jvPWDoUBaayGp16tQJFy5cQMeOHVlkIrIykZGRkEgkuv83K+43NAlZRVXaNAASs4q5GDgRNTjzRnTAvBEd8PaG89h8LrXGjytTAWUqFdYcT8Ivp5Jx/eNHzZiSGipRFpp8fHwQFRWFZ599Fi1atBA6DlUSfTUNuaWG11BwshPlrxtRvaVQKHSjP21tbTFlypR6t0sVUX0QExNT7f2GwtDUOZlEwqlzRNSgfT4uHG8Na4PZm//GqcS7KC6v+RgnhUqD+dsvcWQTmZwor/xv3rwpdAQyYuXhW0b7OgS4WTAJEVUnPT0dv/76KwYOHIiOHTsCAItMRGTVDl3PrNK28KkOHM1ERA2ev5sj1k7tobs/5MuDuJ5eWKPHbjhzm4UmMjleVZBJpWQXG+0b1M7XgkmIqDqXL19Gfn4+jh07BrWaOzYR1QeJiYlYuXIlfvrpJxQW1uwCQyzS8kowe+vFKu25xdxlmIjoXnve7Iv3H21bo2OLy9WY/kusmRNRQyOKEU0LFiyARCLB9OnT4enpiQULFtTocRKJBHPmzDFzOqosI6/MYLtXI9uG+4mjuzswejR3nSOr0r9/f9jY2KBbt24cyUQkMgsXLsTKlStx9uxZ3fqUMTExeOyxx1BSUgIA+Oijj3DixAl4enoKGdVkku4WQ21gNsgnf8XhifAmDfccg4jIiGmRLfDXpTScTc6977E7Lqbh6PzdOD9vqPmDUYMgikLThx9+CIlEgnHjxsHT0xMffvhhjR7HQpNlRV9Ng8LIlODOge4WzWJVmjcHNm0SOgU1cBqNBnFxcWjbti0kEgkkEgkiIyOFjkVEdbBt2zYEBwfrbYIyc+ZMqNVqzJ8/H2lpafj222+xdOnSGn84Z+2CvJwgkQCae84z1OBi4ERExmx9tQ+ir6bh013XcO0+U+lyS5QYvvQgfpjSne+p9MBEUWg6cOAAAKBZs2Z698m6VLc+U982jS2YxMooFEBGBtC4MfDPwstElvbnn3/i7NmzeOihhzBw4ECh4xDRA0hMTMSYMWN09+/cuYPTp0/jrbfewgcffAAAuHbtGn7//fd6U2jyc3PE9H4tsOxAfJU+JzuOyiQiMmZgqB8Ghvph05lkvLO56hTkyi6nFaLXov3wcLTBq/1bYlokN96iuhFFoalv377V3ifrkFWgMNrXoNdnunQJiIgAYmOBLl2ETkMNVNOmTXHu3Dm4cwonkejl5+fr/b986NAhSCQSPP7447q2Ll26YMWKFQKkM59ezb0NFpqKFVxnjojofsZ0bYYv9lxHWr7hpU4qyylR4uOdcfh4Zxz6NPfELy/2skBCqk9E+RHQjz/+iL///rvaYy5duoQff/zRQokIAJzsZAbbm7o7cPglkcA6d+6MGTNmICIiQugoRPSAfH19kZSUpLu/d+9e2Nvbo0ePf3ccKi0thUQiESKe2fi5OVRpk0kkCPZ2EiANEZH4nHhvEDo3c6/VY47eykbwrB34YneceUJRvSTKQtPkyZOxbdu2ao/Zvn07pkyZYplABAAoVxleoMnVwdbCSYgoLS0NGzduRHn5vzsy1ZdFgYkaum7dumH79u34888/sW/fPmzYsAH9+/eHvb297piEhAQ0adJEwJSm5+qofz4hk0iw8KkO/DCLiKgWfn+1T413pKvsmwPxCJ61AzN+5g51dH+iLDTVhEql4k5KFubZyHBByVg7EZmHSqXC+vXrcfXqVa5pR1QPvffee1AqlRgxYgSGDh2K0tJSvPfee7r+srIyHDp0SG+EU31QolABAGylEiwb3xlHZvXHuG7NBE5FRCQ+0yJboEstRzZV+PNSGoJn7cDUtadw4XaOaYNRvSGKNZrq4ty5c/z03sL4RkNkHWQyGUaOHIkjR45wZzmieqhLly44ceIEfvrpJwDA2LFj0b17d13/uXPn0L9/fzzzzDNCRTSLredSAADlag1eX38Oi54KY6GJiKiOKnake+mnWCjrsNRddFwmouMyIQEwpksAPh0bbuqIJGKiKTQNGDBA7/7atWsRExNT5TiVSoWUlBQkJiZi7NixFkpH0VfTUKgwPHWusExp4TRWJjwcKC0FbDmyi8xHo9GgqKgIzs7OAICgoCA0a9as3q3RQkRanTp1QqdOnQz29ezZE7///ruFE5lXWl4Jvoq+obuv1gDvbb2EyNY+nDpHRFRHA0P9cHPhcGw6k4xZWy7CyEoo1dIA2Hg2FRvPpmJKryDMG9HB5DlJfERTaKpcVJJIJEhMTERiYmKV46RSKTw9PTFmzBgsXbrUYvkauk1nUoz29WjuZcEkVkgqBSqtm0FkaiqVCn/88QeSkpIwdepUuLi4AACLTERUbyTdLYbmngsglUaDxKxiFpqIiB7QmK7NMKZrM0RfTcPm2BQcvJaO4vL7P+5ea44n4edTybjx8aOmD0miIppCk1r973g+qVSKDz/8EHPnzhUwEVWWdLfIaN/kPiEWTGKFrl8HXnwR+P57oHVrodNQPaRQKJCSkoL8/HykpKQgNDRU6EhEZEIVu+iOHDkSLi4utdpVd+LEieaKZVFBXk6QSKBXbOKOc0REpjUw1A8DQ/0AaGesvPxTLMprOa2uXKXBkC8OYN0LPflBQAMmmkJTZQcOHEBwcLDQMaiSu0UKg+0u9jK+wRQWAgcPam+JzMDR0RETJkxATk4OWrRoIXQcIjKxyZMnQyKRoGfPnnBxcdHdr45Go4FEIqk3hSY/N0c8070ZfjmZDIA7zhERmdvAUD/cWDgc0VfTMHVd7Xaau55ZjF6L9mNMRAA+GxNunoBk1URZaOrbt6/QEegefq4OyCioWmxq7t1IgDRE9Z9cLkdxcbGusOTp6ckNEIjqqdWrV0MikcDf3x8AsGbNGoETCSMiyAO/nExGWIArvp/YlUUmIiILGBjqh8TFwzHj51jsvJSG2gxw2hSbiq2xqXippy/eDQoyW0ayPqIoNHHIuPUrMrLgt4uDKH7FiERFLpdjzZo1kEgkeP755+Hr6yt0JCIyo8mTJ+vdnzRpkjBBBFb6z/wNX1dHFpmIiCxs2bMRALQ7jX+z/wb2Xc2s0eNUAL49kY7vT+3AzYXDzZiQrIkoqgAcMm7d5HkliM8qNtiXeNdwOxHVXePGjdG0aVNIJBK4ubkJHYeIyCJKy1UAAAdbqcBJiIgark6BHvhhUncAwLsbz2Pj2dQaPU6pBoJn7cD7j7bFtEgu9VDfiaLQZI1DxpcvX47PPvsMaWlp6NSpE7755ht0797d4LFr167FlClT9Nrs7e1RWlpqiahmt/ZogtE+GTe9Apo1A1au1N4S1VFF8RwAZDIZxo0bBxsbG8hkMoGTEZGlHT16FFu2bMG7774LPz+/Kv1yuRyfffYZxo4di549e5r0tYU8/ylTakc0OdjyfY+IyBp8OjYcLfxcsGhnXI0f8/HOOHy8Mw5TegVh3ogOZkxHQhJFocnahoxv2LABUVFRWLFiBXr06IGlS5di6NChuHbtGho3bmzwMa6urrh27Zrufn3adjw6Lt1o37O9gi0XxFp5ewMvvCB0ChIxpVKJ7du3o2nTpujRowcA7cUaETVMS5Yswd9//40lS5YY7Pf398eff/6J1NRUbNiwwWSvK/T5D0c0ERFZn5ciWwAaYNFfNS82AcCa40lYczwJwZ4OUKqBkZ0D8NbQtmZKSZbGv9R1sGTJEkybNg1TpkxBu3btsGLFCjg5OWH16tVGHyORSODn56f7qk9rqiiVGoPtEoDDIgEgKwv44QftLVEdXLlyBZcuXcLevXuRn58vdBwiEtjp06fx0EMPVXtMZGQkTpw4YdLXFfr8J6uoDACgUhk+7yAiImG81LcFjs8egJHhTWr92MTsUqTkluKbA/EInrUDzWftwMhlhyHPKzFDUrIUURaabt++jf3796O4+N/1f9RqNT755BP06dMHgwYNwo4dO8zy2gqFArGxsRg0aJCuTSqVYtCgQTh+/LjRxxUWFiIoKAiBgYEYMWIELl++bJZ8QugQYHiNmMfCqg7nb5CSk4Fp07S3RHUQFhaGXr164ZlnnoGrq6vQcYhIYBkZGQgICKj2GD8/P2RkZJjsNYU+/9kSexu/ntD+HV1/+jY2nObfVCIia+Lv5ogvn+6MxMXD0ad53XdCVgM4l5KPXov2I2TWDvT/NBrRV9NMF5QsQpSFpjlz5mDMmDGwtbXVtX388ceYPXs2jh8/jv379+PJJ5/E6dOnTf7aWVlZUKlUVT6R8/X1RVqa4f8B2rRpg9WrV2P79u34+eefoVar0bt3b6SkpBh9nbKyMuTn5+t9Watpkc0Ntr9gpJ2I7i8zMxNqtXY9EolEgiFDhqB5c/4/RUSAu7s7ku/z4UVSUhKcnZ1N9ppCn//M/98VVIxj0gB4b+slftpNRGSlfnmxFxIXD0cjuwcrN2gAJGSXYuq6WDz17VHThCOLEMUaTfc6evQoBg0apCs0aTQaLFu2DG3btsWePXuQlpaGQYMG4bPPPsPGjRsFTgv06tULvXr10t3v3bs3QkND8d133+Gjjz4y+JhFixZh/vz5VdqTk5Ph4uJi8ozFxcVISkqq02MX/Wl4MfAtx67Dvad5RzU9SG5LsZPL4Q/t4qyKSlnFkN0Q5ja/27dv4+DBg2jRogU6duwomtyViennfS+xZmduyykoKBD09Xv27Inff/8dt2/fRmBgYJX+5ORkbNu2DQMGDBAg3b9Mef6j1uh/OqrSaHDy8i10DjBdMc3UxPi7DYg3NyDe7MxtWcxtOTuntsNfV7OxOObOAz/X2eRcdJy7A6/2boJHQus+Yqo2xPgzB8yXuzbnP6IsNGVkZCAoKEh3//z588jMzMSHH36Ipk2bomnTpnjyySdx8OBBk7+2t7c3ZDIZ0tP1F8BOT083uPOLIba2tujcuTNu3rxp9JjZs2cjKipKdz8/Px+BgYFo1qyZWabOJCUl6f1Ma0qeV4ITty8Z7Nt5PQ8LxvV40GjVqmtui7p7F4B2cVZUyiqK7AYwt/kVFxdDqVRCqVTCwcFBNLkrE9PP+15izc7cliP0KOOoqCj873//Q58+ffCf//wHgwcPhr+/P+RyOfbs2YMPPvgAJSUleOutt0z2mkKf/0jvWUNcJpGgR/vm8HdzrPk3YWFi/N0GxJsbEG925rYs5rasl4OC8EioJ9aeL8Ca4w9W/MhXAItj7mBxzB34udrhrSFtMKar+Xb2FuvP3Fy5a3P+I8qpc2q1WjelBABiYmIgkUj0PrkLCAgwOpT7QdjZ2SEiIgLR0dF6eaKjo/U+tauOSqXCxYsXtYUHI+zt7eHq6qr3ZY32XTG+45zNvWeFDZWzM9C3r/aWqAZCQ0Px3HPPYfz48ZDJuI03EemLjIzEkiVLcOfOHUyZMgVNmzaFjY0NmjZtiueffx5paWn46quvEBkZabLXFPr8Z97j7XTHSCTAwqc6WHWRiYiI9M0b0eGB12+qLC1fgXc2X0TIrB0YtvQgNp3h2n3WRJQjmpo1a4ZTp07p7m/btg3+/v5o06aNri0tLQ3u7u5mef2oqChMmjQJXbt2Rffu3bF06VIUFRVhypQpAICJEyciICAAixYtAgAsWLAAPXv2RMuWLZGbm4vPPvsMSUlJeKEebHkfc834QqNTH+Z6MgCA1q2BmBihU5AVUyqViImJwUMPPQQHBwcA4HpMRFStN954A/3798eKFStw+vRp5OXlwd3dHd27d8fLL7+MDh06mPw1hTz/GRURiD+u5uJcci4+fKI9xnUz3yfYRERkPr+8qP1w4sLtHJxJzEFKdjF2Xk7D3fwyKOvwfBoAcWmFeGfzRXyz/yYOvSvstHHSEmWhadSoUfj4448xevRoODg44MiRI5gxY4beMVeuXDHbhdq4ceOQmZmJuXPnIi0tDeHh4di1a5dugczk5GRIpf8OFsvJycG0adOQlpYGDw8PRERE4NixY2jXrp2xlxCNy3cMD5+TAJgW2cKyYayVWg2UlwO2toBUlIMIycx+//13XLlyBRkZGRg/fjwkEo4GJKL769ixI7799luLvZ7Q5z+af1YD93d1eODvhYiIhNUp0AOdAj0AaEc7AdplWZbvv4HNsSkoVWqqe7hBydkl2HQm2azT6ahmRFloevvtt7Fnzx5s3boVgPZE68MPP9T1JyUl4dSpU5g1a5bZMsyYMaNKcatCzD2jV7788kt8+eWXZssipNJylcF2N0dR/mqZx/nzQEQEEBsLdOkidBqyQg899BBSUlLQu3dvFpmIyKoJef5Tcc7hYMspxURE9ZG/myP+M7Ij/jOyI7p8tAfZReW1fo53Nl9kockKiLIa4OrqihMnTuDSJe0i1KGhoVXWMdm6dSu6du0qRLwGpX0TVxyNz67S3qGJda4pRWQtVCqV7n3L398fr732GmxsRPmWTEQCUCqV+Oabb/Dbb78hLi5Ot4kAoN0k5fvvv8f//d//oXXr1gInNZ0ypXZ9ThaaiIjqv7NzhmDloXh8fygemYW1KzgFz9qBpu4OyCooRblKO6mksas9/m9QaxahLETU83g6dOiADh06VCkyBQUFYcSIEQgICBAoWcPxZGfDP+MRRtqJCIiLi8M333yDnJwcXRuLTERUUyUlJejfvz/efvttJCUlwdXVFRrNv1MMQkJCsGbNGvz4448CpjS9f0c0ifr0lYiIamhaZAuc/mAIEhcPx5ReQXCqxft/Sm4pSlWACkC5GkjNLcM7my8i8tP95gtMOqL/S3306FEsX74cixYtwvLly3H06FGhIzUoPx0zvEXloeuZFk5CJA5qtRqHDx9GXl4ejh8/LnQcIhKhhQsX4ujRo1i0aBHS0tKqLK7t5uaGvn37Yvfu3QIlNA9OnSMiarjmjeiAKx89gsTFw9HYxa7Oz5OcXYKVh+JNmIwMEe1H6MeOHcOUKVNw8+ZNAIBGo9GtbdKqVSusWbOmxtvtUt3I80rwt5HFwOPSDLcTNXRSqRRPP/00Tp8+jX79+gkdh4hEaMOGDejfvz/effddADC4tlvz5s1x7tw5S0czqxKFttCUX1L7NTuIiKj+OPX+YFy4nYOnvj0GVe3XDMfHO+Pwzf6bmNQrCG8NbWv6gCTOEU2XL1/GkCFDcOPGDQwaNAgff/wx1qxZg4ULF2Lw4MG4fv06hg4diitXrggdtV7bdyXdaJ9XI3sLJrFyHToAt29rb6lBKi8vR1LSv6P/XFxcMGDAAL3dmYiIaio5Ofm+61C6uLggLy/PQonMb/OZ2yj9Z42msd8dx4bTyQInIiIiIXUK9ED8ouFwtqvb+XR+qRLfHIhH6Jy/TJyMAJEWmhYsWACFQoGdO3di9+7dmDVrFiZNmoSZM2di165d2LlzJ0pLS7FgwQKho9ZrMdcyjPZNi2xuwSRWzs4OaNpUe0sNTmlpKX788Uf89NNPesUmIqK6cnFxQUaG8b/BABAfHw8fHx8LJTK/BX/+++GhWgO8t/US5HklAiYiIiJrcGnBI3C2r3tZo6RcjY7zdpkwEQEiLTTFxMRg9OjRGDZsmMH+YcOGYfTo0Thw4ICFkzUs8ZkFBtvtZBIMDPWzcBordusWMGaM9pYaHDs7Ozg7O8PW1lboKERUT/Ts2RP/+9//kJuba7D/9u3b2LlzJyIjIy0bzIzU90yNUGk0SMwqFiYMERFZlUvzH8H7j7aFu4MMUgDOdhK4O9R8laD8MhWCZ+3AE18fNl/IBkaUazTl5eUhJCSk2mNCQkLq1ZBxq6SpuiYEADRxc7BwECuXmwts3gzMni10EhKAVCrFU089hYKCAnh6egodh4jqgXfeeQf9+/fHwIED8fXXX0OpVAIAiouLcfz4cbz22mtQKpWIiooSOKnpSO855ZBJJAj2dhImDBERWZ1pkS0wLbKFXps8rwR9Fu2HuobP8fedfATP2oHExcNNH7CBEeWIpiZNmuDEiRPVHnPy5Ek0adLEQokapg4Bbgbbw4y0EzUUV65cweHD/34iYmtryyITEZlMZGQkli1bhosXLyIyMhILFy4EoJ1SN2TIENy8eRPffvstIiIiBE5qOv83uJXu3zKJBAuf6gB/N0cBExERkbXzd3PErcXD0SXQvVaPC561wzyBGhBRFpqeeOIJxMTEYM6cOSgtLdXrKy0txbx583DgwAGMGDFCoIQNQ982htd+iDTSTtQQZGRkYNOmTdi/fz/i47l1KhGZxyuvvIILFy5gxowZ6NatG1q0aIHOnTvj5Zdfxrlz5/DCCy8IHdGkBoX6AgDsbaQ4Mqs/xnVrJnAiIiISi63T++D47AFwqcXC4ZxG92BEOXVuzpw5+PPPP7Fw4UJ899136N69O3x9fZGeno7Tp08jMzMTzZs3x5w5c4SOWq9duWN4jaarcsPtRA1B48aN0adPHygUivtO8SUiqotDhw7B1dUV4eHh+Oqrr4SOYxHl/+w452gn40gmIiKqNX83R1xc8Ajaz92FIoXqvsf/fSffAqnqL1GOaPLy8sKJEycwadIkFBYWYufOnVizZg127tyJgoICTJkyBSdOnOBUFTPLLCitVXuD1aQJsHCh9pbqpfLyct0aKQAwcOBAPPLII5BKRfkWS0RWrn///vj++++FjmFRZf8Umuxt+L5KRER1d3nBMLzWv8X9DwQw9sc4M6epv0T719rb2xurV69GXl4eLly4gMOHD+PChQvIy8vDqlWr4O3tLXTEes/Hxd5wuzMXA9fj56ddCNyPO/HVR0VFRVi3bh22bdsGjUa7LZJEIoFEYnixfCKiB9W4cWM4ODSsv7UKlbbQZMdCExERPaC3hrZF4uLheKxD9ddn6UVKBM/agZd+PAV5XomF0tUPopo6l5OTg2+++QanT5+GRCJBjx49MH36dISFhQkdrUFytjf869PIXmbhJFYuNxc4dAiIjATc3YVOQyaWmZkJuVyO7Oxs5ObmwsPDQ+hIRFTPDR48GDExMdBoNA2mqF2u1Bby7WQsNBERkWksezYC5xbvQ2puWbXH7b6Sid1X9sNGAkgAlGuAjk1c8cfrD1smqAiJ5q/13bt3ERERgfnz52PHjh34888/MXfuXHTr1g3Z2dlCx2uQ/ve33GD7yQT+99Bz6xYwYoT2luqd4OBgjBo1ClOnTmWRiYgsYvHixbh79y5efPHFBnMO9O+IJn6YRUREpvPthJrv0KrUaItMgHYNp+BZOzjSyQjRFJoWLlyIxMRE9OvXD+vXr8f69evRr18/xMfHY/HixULHa3DkeSVIvFtssM/VQVQD5Yhq7erVqygsLNTdb9euHby8vARMREQNybPPPgt3d3esXr0aAQEBaNeuHfr3748BAwbofQ0cOFDoqCajUHLqHBERmV6nQA8MeIBd03st2o8Np5NNmKh+EE1FYOfOnWjZsiX27NkDmUz7adaoUaPQrl07/Pnnn/j0008FTtiw7LuSbrSvb5vGFkxCZFmxsbH4888/0aRJE0yePBm2trZCRyKiBiYmJkb377KyMsTFxSEuruqCpfVpWl35PyOayhQqyPNKuPMcERGZzOop3TF5zSnEXMus0+NnbrmIyNY+/NtUiWg+FkpKSsLQoUN1RSYAkMlkGDp0KBITE4UL1kBdTMkz2jeona8FkxBZVnBwMBwdHREYGKj3fkREZClqtbpGXyrV/bdvFoujN7MAAHHpBeizmJ8eExGRaa2d0h3bp/euc4Gk16L9GPLFAURfTTNpLrESTaGptLQUPj5Vh7R5eXmhrKz6xbvI9FJzDU+ba+nTiJXcezk4AO3aaW9J9Ly8vPDKK69g2LBhkEpF8xZKRPXA8ePHMWDAALi4uMDNzQ2DBw/GqVOnhI5lEVvPpur+rdYA7229xHUxiIjIpDoFeuDW4uF4/9G2sK3Daf71zGJMXReL7v/Za/pwIsOrJKoTY4Umpbr+fHpqMu3aAZcva29JdAoLC/Hjjz8iPf3f6aIuLi4CJiKihujixYsYOHAgYmJiUFRUhIKCAkRHR6N///64fPmy0PHMTnPPfZVGg8Qsw+ciRERED2JaZAvcWDgcm55rg9aNG0GC2q05lFGoQPCsHbhwO8dcEa2eaNZoAoAjR45UWYvpyJEjAIDPPvsMGs29pyHAu+++a5FsDY2DreFfHScj7URitWfPHiQkJGD79u2YNm1avVrzhIjEY/HixSgtLcX777+P1157DQCwfPlyfPTRR/jkk0/w448/CpzQsmQSCYK9nYSOQURE9VhjZ1vsieqn1xY8a0eNHz9i+TGM6hKAL8aGmzaYCIiqKrBv3z7s27fPYN/MmTOrtEkkEhaazGRwqC/i0gqrtA8M5fpMVZw/D0RGAocOAeHhQqehWnrkkUdQVlaGoUOHsshERII5fPgwHnroIXz00Ue6tvnz5yMmJgYHDx4UMJnlSQAsfKoDp+oTEZHFJS4eXqti05azqejZ3BNjujYzYyrrI5pC05o1a4SOQJUk3C0y2J5opL1BU6uBggLtLYlCdnY2PD09AQCOjo4YP368wImIqKFLT0/H008/XaW9R48eOHnypACJhBXZuu5bURMRET2I2hab3tl8EUv2XMfx9waZMZV1EU2hadKkSUJHoEqO37xrsP1iaq5lgxCZkEajwZEjR3DgwAE8/fTTaN26tdCRiIgAAOXl5XB2dq7S3qhRI5SXlwuQSDgaAIlZxRzRREREgklcPBwTvj+Oo7eya3S8PL8MwbN2IHHxcDMnsw5cDJxqTZ5XgrvFhk9qbbkLF4lcdnY2NBoNUlNT738wERFZnBTg+kxERCS4X17shcTFw2tVPGpZi5FQYiaaEU1kPfZdSTfaN4BrNJGISSQSPPbYY2jdujVCQ0OFjkNEpOfnn3/GiRMn9Npu3rwJAHj00UerHC+RSLBjR/07oV00KoyjmYiIyKrUdDqdEkDkJ9E4NHOg+UMJiIUmqrWLKXlG+yb3CbFgEpFo2xaIjdXektUpKCjAxYsX0atXL0gkEshkMhaZiMgq3bx5U1dYuteuXbuqtNXHDQwcbaUY161hLahKRETikLh4OEJm7YDmPscl55Qi+moaBob6WSSXEFhoolorVigNtndq6spPGA1xcgK6dBE6BRmgUCiwatUq5OXlwdbWFt26dRM6EhGRQQkJCUJHsAouDrZCRyAiIjIqYfFwvLvxPDaeNbwMh3dRDnomX8SeqN0YOLkP0K8f4Fv/ZgWx0ES15uNib7A9opmnhZOIRHIy8MknwMyZQDN+CmtN7Ozs0K1bN5w7dw4tW7YUOg4RkVFBQUFCR7AKjex56kpERNbt07Hh+HRsuN5UujaZiZh+fCMejTsCG80/u5Hv+gawsQFGjwbeew8ICxMoselx5WaqNWcjJ3mN7GUWTiISWVnAt99qb8kqqNVq3b979+6NF198ER4eHgImIiKimuC5BhERiUXFIuGRt2Kxfd2b+kWmCkolsHkz0L07sHu3ACnNg4WmOlq+fDmCg4Ph4OCAHj164NSpUzV63Pr16yGRSPDkk0+aN6AZ7YszvBh4tJF2Imuh0Whw8OBB/Pbbb7pik0QigZ2dncDJiIjEQejzHyc7jmgiIiLxeEp2F99v/Q9sVcqqRaYKSiVQVgY8+SRw8aJF85mLqAtNCoUCO3fuxJIlS/DRRx/p2ktLS5GRkaE3asGUNmzYgKioKMybNw9nz55Fp06dMHToUGRkZFT7uMTERLz99tt4+OGHzZLLUnKKFAbbs420E1mL3NxcHD16FDdv3sS1a9eEjkNEJCrWcP5jI61/C5wTEVH9teTWX7BRqyC73xLhGo224LRokWWCmZloC01//PEHmjVrhscffxxvv/02PvzwQ13f33//DX9/f6xfv94sr71kyRJMmzYNU6ZMQbt27bBixQo4OTlh9erVRh+jUqkwYcIEzJ8/H82bNzdLLktRKA3/T+Jgw+HsZN08PDwwatQoDB8+nDvLERHVkjWc/xyLv4sNp5Mf+HmIiIjMLj0d2LzZ+EimeymVwKZNwH0+wBEDUY4/Pnr0KEaPHg1/f3989dVXOHHiBH777Tddf/fu3dGyZUts2bIFzzzzjElfW6FQIDY2FrNnz9a1SaVSDBo0CMePHzf6uAULFqBx48aYOnUqDh8+fN/XKSsrQ1lZme5+fn7+gwU3EXleCbKLyw32+bgaXiS8wWvcGHjzTe0tWVx+fr7e6MY2bdoImIaISJyEPv9pm34LtnYOAICflt9E/zeHoHGnUKC0FLhypeoTVez2eu0aUFSk3xccDHh6ApmZwO3b+n0uLkCrVoBKBVy4UPV5w8IAW1sgPh7Iy9PvCwjQ7hyUkwMkJMBOLgfu3tX2OToCFR9wnDun/eS6stBQ7TFJSf8+poKvr/a5CwqAGzf0+2xt/1089uJFoPyec7RWrbTfU2qq9oKnMi8vICgIKCkBrl7VNdvJ5UB2NtC5s7bh6lXtMZWFhAAeHtrnTL1nZyU3N6BFC20WQ1NAOnUCZDLt91JQoN8XGAj4+GhfPzFRv69RI6Dib/jZs1Wft1077W1Cgva/QWX+/tqv/Hzg5k39Pnt7oH177b///lt7oVdZ69aAszOQklL14s/bW7vRS3ExEBen3yeVAuHh2n9fuaL9Xa2seXPA3R1IS4PdpUv6/93d3bX9CgVw6VLV7zU8XPv8168DhYX6fc2aaXNlZWk3pKnM2Vn7/ajVwPnzVZ+3QwfAzg64dQvIzdXva9IE8PPTtt+6BQD//o47OPz78z9/Xvv8lbVtq92FOTm56pqljRsDTZtqv4/r1/X7bGyAjh21/758WTu1qLKWLQFXV0Au135V5uGh/T018B5hJ5drf/cBQd8j9NTkPQKwivcIAIBEUqv3CL33QyHfIxwcavUeYSeXa3836/oecfx41ePvR6kEVq8GXn5Z+14gUqIsNH300Udwd3dHbGwsvL29cffe/9kAdO3aFSdPnjT5a2dlZUGlUsH3ni0IfX19EXfvH5h/HDlyBKtWrcJ5Q2/oRixatAjz58+v0p6cnAwXF5daZa6J4uJiJCUl3fe4bZeq/qwrOElUNXoOU6ppbsG98Yb2D1KlrKLJfg8x5c7JycHevXthZ2eHfv36CR2nTsT0865MrLkB8WZnbsspuPfEtwEQ+vxn82+z4Frp/m35cCR9vxw2iYkIMPD+nvTPBYjf+PGwP3dO/3v58ksUjRwJ5x9/hNfcuXp9JQ8/jIyffoKkoADNIiKqPO/t2Fiovbzg8/LLcNq3T68v+4MPUPDCC3DasQM+06fDv1JfWfv2SNuh3X2oWc+ekCj0lxu4s2cPylu3hufMmXDZsEGvL++VV5A7cybsjx+H3/jxen1KPz+knjgBAAgYMgQ2aWl6/Wm//YayXr3g/skncPvvf/X6CsaNQ/Ynn8D2+nU0GTJE1+4PQGNnh+R/Lvr9xoyB/eXLeo/NXL4cxcOHw+WHH+D5n//o9RUPGoTMH36A9O5dBBr4GSZfvAiNiwsaT50Kx3uKj3cXLEDhxIlo9Pvv8H7zTb2+ss6dkfb77wCAIAPPmxoTg+LGjVH43ntw3rZNry/3jTeQ9+abcDh4EL6TJun1lQcF4c7BgwCApv37Q5adrdcv37IFiogIeHz0EVxXrdLrK3juOWR/9BHsLl2C/2OP6fWpnZ1x+58ikf+TT8LungJAxsqVKBk8GK7Ll8P/s8/0+ooefRRZ334LmVyOpr16Vflek65dA+zt4TtxIhzuud65u3gxCp9+Gs7r18Nr1iy9vtIePZC+YQNQVmbwZ5hy/DhU/v7wfu01NNq5U68v5513kD99Ohz37kXjadO039c/fYpWrSDfuxcAEPjww5DeU/yS//knFB06wHPOHLj89JNeX/7UqciZMwd2sbHwHzVKr0/l6YmUfwoGTYYPh+09fyvS161Dad++cPvyS7h/9ZVeX+GTT+Lu0qUG3yP8YR3vEZXV5D2iuGlTFMyfL/h7BFD794jK74dCvkcog4PhFRVV4/cIfzzYe0Rpz55wqJKkBmbPRoa3N0oGD67Lo812blWb8x+JRnNvudT6eXh4YPTo0Vi5ciUAYP78+ViwYAFUKpXumFmzZmHZsmUovLfK/4Du3LmDgIAAHDt2DL0qvfG/++67OHjwYJXiVkFBATp27Ihvv/0WjzzyCABg8uTJyM3NxbZ7fsErM/SJXmBgIPLy8uDq6mr0cXWVlJRUo62T3910ARtjUwz2rZoUgYGhfqaOVq2a5hZUYaG2Wh8Wpq12/0MU2Q0QU+78/Hz88MMPsLe3R//+/dGu4tM2ERHTz7syseYGxJuduS0nPz8fbm5uZvubbI2EPv8ZPH6xbkSTBMBqEYxoksvl8Pf/5/JKRCOa5HI5/Js0EeWIpqT0dASp1aIb0SSPjf33dwUQzYgm3e+4yEY0yeVy+A/X7gYmphFNSRkZCAIEf48AUOsRTXrvhyIa0SSXy+EfHPxgI5pmzKia5T4W9Z2E2duW1nlEk7nOrWpz/iPKEU1lZWX3/cZyc3MhlZp+CSpvb2/IZDKk3/M/Ynp6Ovz8qhZZ4uPjkZiYiMcff1zXVjGNx8bGBteuXUOLFi2qPM7e3h729tY3Fa1YYXjon4eTjcWLTKJx/TrQuzcQG/vviS9ZhKurK5577jk4Ozvfd7FaIiIyTujznzjf5pDaOwEAPhkVhsadmmk7HByq/9ta3XRpHx/tlyEyWfXPayC7jocH4OEBRVLSv9NzKqu4ODMkKMjwYwDtxWB1mSouJg0JCNB+GeLoqPe8VXJXt6ahr6/2yxBb2+rztmplvM/TU/tlTHXPGxKi/TLE1bX6x1YUNQxp2lT7ZYiTU/XPW90HXX5+UHToYPi/u51d9c/burXxPm9v7ZchUmn1z1vdemru7rrHGvwdryiuGdKsmfbLEGfn6jNVXOgbUlEkMMTAe4Si8kgPAd8jjLLy94gqavAeYfB3RQTvEVVy1/Y9IiAA+L//q9X0OaVEis1hg3Fp41X88mLVEY1iIcrFwJs3b47Tp09Xe8zx48fRtm1bk7+2nZ0dIiIiEB0drWtTq9WIjo7W+4SvQtu2bXHx4kWcP39e9/XEE0+gf//+OH/+PAIDA02eUQgPtTTyh4zIgjQaDQ4ePIjblT598vHxgaOjo4CpiIjEz1rOf7ZP741x3YxcqBIREVkTX19g9Gjt6LwaUEqk2NH2Idxt5I6jt7Lv/wArJspC06hRo3D06FGsWbPGYP/nn3+OS5cuYdy4cWZ5/aioKKxcuRLr1q3D1atX8corr6CoqAhTpkwBAEycOFG3WKaDgwM6dOig9+Xu7g4XFxd06NABdnZ2ZsloLjnFCsPtRYbbiSzp1KlTiImJwfr161Fy7xBeIiJ6INZw/jPy22PcdY6IiMTjvfe0hSaJpNrDVJBAKZXh215jdW3Bs3ZgwvfGN9ywZqKcOvfOO+9gy5YteOGFF/Drr7/q5vK/++67OH78OI4dO4bw8HDMqMN8yJoYN24cMjMzMXfuXKSlpSE8PBy7du3SLZCZnJxslml71iC7yPCOc8baiSypc+fOuHTpEjp37sxRTEREJmYN5z9qDfDe1kuIbO0Dfze+zxMRkZULCwO2bQOefFI7hc7ANDqlRAqlVIYXn/oA13yC9fqO3spG8KwdSFw83CJxTUWUhSZnZ2ccPnwYM2bMwMaNG3WLgH/++eeQSCQYO3Ysvv32W7OucTRjxgyjhayYmJhqH7t27VrTB7KQ8koLrlemMNJO0Fawvb1rPGSSakehUOg+Gbezs8OUKVPqbaGXiEho1nD+o9JokJhVzEITERGJw9ChwKlTwKJFwKZNesUmpVSKHW0ewre9xlYpMlU24fvjolqzSbRXvh4eHvjll1/w9ddf4/Tp08jOzoarqyu6detWZetdMp30/DKD7fmlNV/grMHp2FG7awWZnFwux2+//YbBgwcj7J8FDllkIiKq32QSCYK9nYSOQUREVHNhYcCvvwJLlwIxMdod7lxdYdOvH95YUv360wBEt2aTaAtNFby8vDBs2DChYzQI8rwSFJQZHrkU5MkTPrK8K1euoKCgAMePH0f79u1ZZCIiquckABY+1YGjmYiISJwaNwbGjtVrSlw8HMGzdggUyDx4VUY1lpBVZLTviXAj22EScPky0LKl9pZMasCAARgwYAAmTpzIIhMRUQMgkQCRrY1sN05ERCQGBq4Pa7IGk5iKUaIc0TRgwIAaHSeRSPS24aUHU6IwPj1uUDtOVzSqrAyIj9fe0gPRaDS4cuUK2rVrB4lEAolEgocffljoWEREZCFqDbg+ExERiZuR68PExcPRctYOVLcozRNfH8Yfr1v/9Y8oC033W2xSIpFAo9FAcp8tBKl2fj+XarC9U1NXnvCRRWzfvh0XLlzAww8/XOOCMxER1R9cn4mIiOqzLdN7Y8TyY0b7/76Tb8E0dSfKuSZqtdrgV25uLvbv348ePXpg9OjRUCgUQketVy6l5hpszyvhz5ksIygoCFKpFJ6enkJHISIiAXB9JiIiqs86BXrAXib+ATOiLDQZ4+rqin79+mH37t04deoUPv74Y6Ej1Sv5JYYXAjfWTmRqnTt3xowZMxAeHi50FCIiIiIiIpO79vGj1fZPXXPKQknqrl4Vmiq4uLjgkUcewZo1a4SOUq9kF5cbbC9XVTeLlNCyJbBrl/aWauXOnTvYsGEDysv//d3z8PAQMBEREQnpva2XIM8rEToGERFR3T3g9WH0tUwTBzK9elloAgCpVAq5XC50jHoj+mqa0T43RzsLJhEhV1dg6FDtLdWYUqnE+vXrERcXh4MHDwodh4iIrIBKo0FiVrHQMYiIiOquBteHbX2dLRjI9OploenWrVvYtGkTgoODhY5Sb2w6k2K0b3jHJhZMIkJyOfDhh9pbqjEbGxs89dRTaN26NXeWIyIiAFwMnIiI6oEaXB/uerOv5fKYgSh3nXv++ecNtiuVSqSmpuLIkSMoLy/HggULLJys/soqLDPaN7lPiAWTiJBcDsyfDzzxBODvL3Qaq6bRaFBYWAgXFxcAQHBwMAvGRESkw8XAiYhI9ExwfTjh++P45cVeJg5mOqIsNK1du7ba/jZt2uCtt97CCy+8YJlADUBRmeEFv/1d7XnCRyahVCqxbds2pKamYurUqXB2FvdwUSIiMr1x3ZoJHYGIiEhwR29lCx2hWqIsNCUkJBhsl0qlcHd3142GINOxNbLFYmMXewsnofpKoVBALpcjPz8fd+7cQevWrYWOREREREREJAhPRxtklxjfeKvN+ztw7ePhFkxUc6IsNEkkEtjZ2cHPz0/oKA1GuUpTq3ai2nJycsKECROQl5eHkBBOxyQiIiIioobr7LyhCJ61w2i/kUlHVkGUi4GHhITgvffeEzpGg2JsRFMLn0YWTiJCHh7AhAnaW9KTkpKC+Ph43X1PT08WmYiIiIiIqP6qxfXhqkkR1fYP+9I6d+cW5YgmDw8PeHl5CR2jwZDnleDv1HyDfR0D3S0bRoxCQoCffxY6hdVJTU3FunXrIJVKMXXqVDRu3FjoSEREREREROZVi+vDgaHVz+KKSy80RSKTE+WIpocffhgnT54UOkaDsfao4TWxACA5u9iCSUSqtBS4eVN7Szp+fn5o2rQpmjVrBnd3d6HjEBERERERmV8trw+DPByq7e/58V5TpDIpURaaFi1ahL///hsLFiyAUml8cSwyjRPVrGjfr42PBZOI1JUrQKtW2tsGTqP5d00vmUyGp59+GuPHj4ednZ2AqYiIiIiIiCyklteHB2cOrLY/rUBhilQmJcqpc59++inCwsIwf/58fPfdd+jUqRN8fX0hkeivIySRSLBq1SqBUtYfzvYyg+0u9rL7DuUjqlBeXo7ff/8dwcHB6N69OwDA3p67FhIRUc099e1RbH21j9AxiIiILGpgGx9EX8s02h99Nc2qrs1FU2iSyWT48MMPMWfOHKxdu1bXLpfLIZfLDT6GhSbz6tTUTegIJCKXLl3C1atXcePGDbRr1w7Ozs5CRyIiIpE5m5xrdSfTRERE5rZqSvdqd6Cbti4WtxYPt2Ci6omm0KTRaHTTbhISjK8ZRKaXmmt4HaYUI+1EhoSHhyMzMxNt2rRhkYmIiOos5lomC01ERNTg2EkBhdpwn5FmwYim0FRZUFCQ0BEalNJyw7+2xtqJKmRkZMDb2xtSqRQSiQRDhgwROhIREYkc14ckIqKG6PrC4dWOarImoiw0kWVlG1lczMHG8NpNdI8uXYBKi2A3FFevXsXWrVsRHh6ORx99tMoaakRERLXVpZk7RzMREZG4NYDrQ1EVmnihannRV9OgMPL/QMvGnP5E1VMqlcjPz4darYZMxsIkERHV3apJESwyERERiYBU6AC18eGHH0Imk9X4y8ZGVHU0q7TpTIrRvr5tGlswiYhduwb06qW9bUBCQ0MxceJEjBs3jkUmIiJ6YCwyERFRvdAArg9FVYlxdXWFu7u70DEalKzCMqN9g9r5WjCJiBUVASdOaG/rsfLychw4cACRkZFwcHAAAISEhAicioiIiIiIyIo0gOtDURWa3nzzTcydO1foGA1KVmGpwXavRjbwd3O0cBqyZlu2bMG1a9dw9+5djB8/Xug4REREREREJABRTZ0jyzO2s5ytjL86pC8yMhJubm7o06eP0FGIiIiIiIhIIKIa0USWp1AaXgmcO84RoF3su2IttCZNmuC1117jekxEREREREQNGIel1NHy5csRHBwMBwcH9OjRA6dOnTJ67NatW9G1a1e4u7ujUaNGCA8Px08//WTBtHUjzytBdnG5wT4fV3sLpxGx4GDgp5+0t/XIpUuXsGzZMuTk5OjaWGQiIqrfGsL5DxERkVnV0+vDylhoqoMNGzYgKioK8+bNw9mzZ9GpUycMHToUGRkZBo/39PTE+++/j+PHj+Pvv//GlClTMGXKFOzevdvCyWtn35V0o31ejVhoqjFPT+DZZ7W39YRarcbRo0eRl5dX7UUGERHVHw3l/IeIiMis6uH14b1EU2hSq9VWsxD4kiVLMG3aNEyZMgXt2rXDihUr4OTkhNWrVxs8vl+/fhg5ciRCQ0PRokULvPHGG+jYsSOOHDli4eS1czElz2jfmK5NLZhE5DIzgeXLtbf1hFQqxTPPPIO+ffti8ODBQschIiILaCjnP0RERGZVD68P7yWaQpO1UCgUiI2NxaBBg3RtUqkUgwYNwvHjx+/7eI1Gg+joaFy7dg2RkZFGjysrK0N+fr7el6U1sjc8Daqxsx0GhvpZOI2I3b4NzJihvRUxhUKBpKQk3X0XFxf069cPUinfRoiI6ruGdP5DRERkVma6Poy+mmbS53sQXAy8lrKysqBSqeDr66vX7uvri7i4OKOPy8vLQ0BAAMrKyiCTyfDtt99WOxJk0aJFmD9/fpX25ORkuLi41P0bMKK4uFiviAAAPfxkWGPg2AVDmlY5ViiGclsbO7kc/gDkcjkUlbKKIXuFsrIy7NmzBzk5OejXr5/QcepETD/vypjb8sSanbktp6CgQOgIFif0+Q8A0f2eiPF3GxBvbkC82Znbspjb8sSa3Vy5jV0fPqip62Jx8JUOZstdm/MfFposxMXFBefPn0dhYSGio6MRFRWF5s2bG71onz17NqKionT38/PzERgYiGbNmsHV1dXk+ZKSkhAUFKTXFhQEDLxSiOi4f9deGNUlAMO6h5r89evKUG6rc/cuAMDf31/7Q/2HKLL/Q61W4+zZsygpKYGDg4Noclcmpp93ZcxteWLNztyWw1E2NWeq8x8Aovs9EePvNiDe3IB4szO3ZTG35Yk1u9lyG7k+rJlL1fYGBQWZLXdtzn9YaKolb29vyGQypKfrL5Sdnp4OPz/j08mkUilatmwJAAgPD8fVq1exaNEioyda9vb2sLfngttkHaRSKUaNGoXCwkJeYBERNUA8/yEiIhJe4uLhCJ61Q+gY98XFVWrJzs4OERERiI6O1rWp1WpER0ejV69eNX4etVqNsrIyc0Q0mQu3c/RGMwHAlrOpuHA7x8gjyCAXF2DIEO2tiFy8eBGHDx/W3be1tYWHh4eAiYiISChCn/9IJbV+CBERkXUS6fVhbXBEUx1ERUVh0qRJ6Nq1K7p3746lS5eiqKgIU6ZMAQBMnDgRAQEBWLRoEQDtegNdu3ZFixYtUFZWhp07d+Knn37Cf//7XyG/jfvadu6Owfbt5++gUyALDjXWqhUgsq2c09LSsHXrVgBA06ZNERISInAiIiISmpDnPzJWmoiIqL4Q4fVhbbHQVAfjxo1DZmYm5s6di7S0NISHh2PXrl26BTKTk5P1duIqKirCq6++ipSUFDg6OqJt27b4+eefMW7cOKG+hRrJLCitVTsZoVIBRUVAo0aAzPBOftbGz88Pffr0gVqtRnBwsNBxiIjICgh6/iNhoYmIiOoJEV4f1hYLTXU0Y8YMzJgxw2BfTEyM3v3//Oc/+M9//mOBVGSVLlwAIiKA2FigSxeh0xhVsSOQjY32bWHgwIGQ8MSeiIgqEer8R8Y/R0REVF+Y8fqwz6J9+PWZViZ9zrrgGk1EhIKCAqxduxbbt2+HRqMBABaZiIjIanDmHBER0f2l5lnHOtAsNJFROcUKw+1FhttJvLKyspCRkYFbt24hLy9P6DhERER6pPzwg4iICADgbGf9fxNZaCKjsovKa9VO4hUSEoJRo0bhhRdegLu7u9BxiIiI9LDQREREpHVpwaNCR7gvFprIqNvZhQbbPRvZWjgJmcPly5dRVFSku9+uXTt4eHA3QSIisj6cOkdERCQeXAycDIq+moZChcZgX4CHk4XTiFxYGJCRAVjRSKFTp07hr7/+QkBAACZNmgRbWxYPiYjIenFEExER1RtWeH1oaiw0kUGbzqQY7esQ4GbBJPWArS3g4yN0Cj3NmzeHo6MjgoODdbvMERERWSsphzQREVF9YYXXh6bGqXNkULlKbbRvUDtfCyapB+LjgSee0N4KqGI3OQDw9vbGq6++ikGDBnF3OSIisnoc0URERPWGlVwfmhMLTWRQM0/D0+MeauEFfzdHC6cRubw84H//094KJD8/H+vWrUNGRoauzdnZWbA8REREtcEBTUREVG9YwfWhubHQRAa1a+JqsH1E5yYWTkKmsGfPHiQlJeGPP/7QG9lEREQkBhx9S0REJB4sNJFB28/dqVU7Wbfhw4ejbdu2GD16NE/WiYhIdGQc0kRERCQaLDSRQYl3iwy2JxlpJ+tz9+5d3b8dHR0xbtw4uNfjnQ2IiKj+YqGJiIioZvr+95LQEVhoIsN6N/cy2N7LSDtVIyAA+OIL7a0FaDQaHDhwAMuXL8eNGzcs8ppERETmpFIb36SEiIhIVCxwfRh9Nc1sz10TLDSRQa38XQy2t/E3vHYTVcPXF4iK0t5aSF5eHjQaDeRyucVek4iIyFxSckqx4XSy0DGIiIgenAmuD/s096y2f+q62Do/tymw0EQGdQ82/IvbNdjDwknqgZwcYNMm7a0FSCQSPP7443j66acRGRlpkdckIiIyt/e2XoI8r0ToGERERA/GBNeHv7zYy4SBTI+FJiJzS0gAxo7V3ppJXl4ejh07prsvk8nQpk0bs70eERGRpak0GiRmFQsdg4iI6MGY6Prw+OwBJgpkejZCByDrdCox22D7mcQcdArkqCZrUlZWhlWrVqGgoAB2dnbo2rWr0JGIiIhMTiaRINjbSegYREREVsHfzVHoCEZxRBMZlF9cbrA9t1hh4SR0P/b29ujRowd8fHzQqlUroeMQERGZnFQCLHyqg1WfVBMREZEWRzSRQVfk+Qbb49IKLJyEjFGr1ZBKtbXi3r17o3v37rC1tRU4FRERkekte6YLHuvaTOgYREREVAMc0UQGtTOyu1xbP8O70VE1HB2Bzp21tyag0WgQHR2N9evXQ/3Pds8SiYRFJiIiqre8ne2EjkBERGQaJr4+tEYc0UQGxSbnGmwvUqgsG6Q+CA0Fzp412dNlZ2fjxIkTUCqVuHHjBhf9JovRaDRQKpVQqe7/PqBUKlFaWmqBVKYn1uzMbVq2traQyWRCxyAiIqL6xsTXh9aIhSaqQp5XgmPxdw32FZUpLZyG7uXl5YVRo0ahpKSERSayGIVCAblcjuLimu34pFQqkWDGnRbNSazZmdu0JBIJmjZtCmdnZ6GjEBEREYkKC01Uxb4r6Ub7OgS4WTBJPXHuHNCzJ3DihHaIZB3k5uZCIpHAzU3782/btq0pExJVS61WIyEhATKZDE2aNIGdnR0kEkm1j1EoFLCzE+dUF7FmZ27T0Wg0yMzMREpKClq1asWRTVbgPm85RERE4mGC60Nrx0ITVXExJc9o36B2vhZMUk9oNIBCob2tg7S0NPz8889wcnLC888/DwcHBxMHJKqeQqGAWq1GYGAgnJxqtrW4RCKBvb29mZOZh1izM7dp+fj4IDExEeXl5Sw0WQEJWGkiIqJ64gGvD8WAi4FTFam5hqfGtPRpxG2FBeDo6AiJRAKpVIry8nKh41ADVrHLIVFDcL9Re2RZ/M9BREQkHhzRRFUYKzQp1VwIXAhubm6YOHEiXF1drfJTfyIiIiIiIqIK/HiaqnCwNVx/dDLSTqal0Wiwf/9+pKSk6Np8fHxYZCIyI4lEgm3btgkdQ7Q+/PBDhIeH6+5PnjwZTz75pGB5qP7hiCYiIiLxYKGJqpj6UIjB9ilG2uk+QkOBS5e0tzVw4sQJHD58GL/99ptVbvlNJDZpaWl47bXX0Lx5c9jb2yMwMBCPP/44oqOjhY72wGJiYiCRSCCRSODg4ABHR0e0b98e33//vaC5vvrqK6xdu1bQDFS/cI0mIiKqN2p5fShGHKJCVbT2dalVO92HoyPQvn2ND4+IiMCVK1fQtWtXLvxN9IASExPRp08fuLu747PPPkNYWBjKy8uxe/duTJ8+HXFxcUJHNIlr167B3t4earUa//vf//DKK6+gRYsWGDhwoCB5KnbIJDIVjmgiIqJ6o5bXh2LEEU1UxanEbIPtZxJzLJyknkhKAl54QXtrRFlZme7fdnZ2eP7559GpUydLpCOq11599VVIJBKcOnUKo0aNQuvWrdG+fXtERUXhxIkTesdmZWVh5MiR8PDwQKtWrfDHH3/o+lQqFaZOnYqQkBA4OjqiTZs2+Oqrr/QeXzFd7PPPP4e/vz+8vLwwffp0vUX8y8rKMHPmTAQGBsLe3h4tW7bEqlWrdP2XLl3CI488AmdnZ/j6+uK5555DVlbWfb/Pxo0bw8/PDyEhIXj99dcREhKCs2fP6vp37dqFhx56CO7u7vDy8sJjjz2G+Ph4Xb9CocCMGTPg7+8PBwcHBAUFYdGiRbr+3NxcvPDCC/Dx8YGrqysGDBiACxcuGM1z79S5fv364fXXX8e7774LT09P+Pn54cMPP9R7TG1fg4iIiEiUanB9KHYsNNXR8uXLERwcDAcHB/To0QOnTp0yeuzKlSvx8MMPw8PDAx4eHhg0aFC1xwute7CnwfauwR4WTlJP3L0LrFqlvTUgNTUV33zzDS5evKhr425HJBYKhQIKhQKaStuzqlQqKBQKKJVKkx9bG9nZ2di1axemT5+ORo0aVel3d3fXuz9//nyMHTsWZ86cwaOPPooJEyYgO1tbeFer1WjatCk2bdqEK1euYO7cuXjvvfewceNGvec4cOAA4uPjceDAAaxbtw5r167Vm0I2ceJE/Pbbb/j6669x9epVfPfdd3B2dgagLbQMGDAAnTt3xpkzZ7Br1y6kp6dj7NixNf6eNRoNdu3aheTkZPTo0UPXXlRUhKioKJw5cwbR0dGQSqUYOXIk1Go1AODrr7/GH3/8gY0bN+LatWv45ZdfEBwcrHv8mDFjkJGRgb/++guxsbHo0qULBg4cqPv51MS6devQqFEjnDx5Ep9++ikWLFiAvXv3mvQ1yPyEOv/hX0UiIqo37nN9WB9w6lwdbNiwAVFRUVixYgV69OiBpUuXYujQobh27RoaN25c5fiYmBiMHz8evXv3hoODAz755BMMGTIEly9fRkBAgADfQfWupxcYbe8UyGKTqV29ehVFRUU4deoUOnTowCITiUrFqJe3335bV8w5evQoDhw4gM6dO+OJJ57QHfv555+jvLwcb7zxhq7Ic/r0aezevRthYWF46qmndMd+9dVXKC4uxiuvvKJ7Xz1//jwiIiJqnO3mzZvQaDRo27ZtjY6fPHkyxo8fj7KyMixcuBBff/01Tp06hWHDhsHW1hbz58/XHRsSEoLjx49j48aNeoUgDw8PLFu2DDKZDG3btsXw4cMRHR2NadOm4fr169i4cSP27t2LQYMGAQCaN2+ue+yyZcvQuXNnLFy4UNe2evVqBAYG4vr162jdurXR7E2bNgWgHTGlVquxYMECREZG6vpHjRqld/zq1avh4+ODK1euoEOHDkhOTkarVq3w0EMPQSKRICgoSHfskSNHcOrUKWRkZOg2Jfj888+xbds2bN68GS+++GKNfr4dO3bEvHnzAACtWrXCsmXLEB0djcjISJO9BpmXoOc//NNIREQkGhzRVAdLlizBtGnTMGXKFLRr1w4rVqyAk5MTVq9ebfD4X375Ba+++irCw8PRtm1b/PDDD1Cr1Va7EO3GMykG2zcZaacHM3DgQAwcOBDPPvssi0xEJlR5NFRNdOzYUffvRo0awdXVFRkZGbq25cuXIyIiAj4+PnB2dsb333+P5ORkvedo3749ZDKZ7r6/v7/uOc6fPw+ZTIa+ffsafP0LFy7gwIEDcHZ21n1VFMkqT3Mz5PDhwzh16hTOnz+PH374AQsXLsR///tfXf+NGzcwfvx4NG/eHK6urrrRShX5J0+ejPPnz6NNmzZ4/fXXsWfPHr1chYWF8PLy0suWkJBw31yVVf753vuzMdVrkHkJe/7Dv49ERERiwRFNtaRQKBAbG4vZs2fr2qRSKQYNGoTjx4/X6DmKi4tRXl4OT0/DU9SEdtbIWkx2Mp7kmYJGo8Hly5d102UkEgkeeughgVMR1U3Fe6Gtra2urU+fPujcuTMcHR31jn377berHNutWzd06dIFUqn+5x5vvPFGlWPDw8Nrla1Vq1aQSCQ1XvC78msB2v83K6aWrV+/Hm+//Ta++OIL9OrVCy4uLvjss89w8uTJGj/HvT+PexUWFuLxxx/HJ598UqXP39+/2sdWrB1lb2+P9u3b4+TJk/j444/xyiuvAAAef/xxBAUFYeXKlWjSpAnUajU6dOgAhUIBAOjSpQsSEhLw119/Yd++fRg7diwGDRqEzZs3o7CwEP7+/oiJianyuvdOP6xOdT8bU70GmU9DOP8hIiIi02ChqZaysrKgUqng6+ur1+7r61vji5mZM2eiSZMmuqkThpSVlektEJ2fn1+3wLW08lA8jK2CEuDhZJEM9Y6vLzBrFuDrC41Ggy1btuDy5cvo1KmT3hooRGJkZ2dXpU0mk8HOzg42NjY1OrbyCKD7HVsbnp6eGDp0KJYvX47XX3+9yjpNubm5NS5iHD16FL1798arr76qa6vtSJuwsDCo1WocPHjQ4Pt/ly5dsGXLFgQHB1f52dWWTCZDSUkJAODu3bu4du2abr0cQDsd7l6urq4YN24cxo0bh9GjR2PYsGHIzs5Gly5dkJaWBhsbG7O9Z1niNejBCH3+wwG/RERUb1S6PqyvWGiysMWLF2P9+vWIiYmpduv6RYsW6a0HUiE5ORkuLi4mz1VcXIykpCRsi000ekwTRyWSrGxl/IrcVu/llwGlEkhOhpubG6RSKRwcHMSR/R6i+Znfg7nrTqlUQqlUQqFQ1Hh6p1qt1rtYFMqSJUswYMAAdOvWDXPnzkVYWBiUSiWio6Px/fff6+1qVl5erlvjqCJ7RVtISAh+/PFH/PnnnwgODsYvv/yC06dPIzg4WHesSqWq8n1XbvP398ezzz6LKVOmYMmSJQgLC0NycjIyMzMxevRovPDCC1i5ciXGjRuHqKgoeHh44NatW9i4cSNWrFhhsNBWMSIpJSUFjRo1Qnl5Oc6cOYOffvoJI0eORFlZGZycnODl5YX//ve/8PLyQnJyMubMmaP3/X311Vfw8/NDeHg4pFIp1q9fDz8/Pzg6OuLhhx9Gjx49MGLECHz88cdo1aoV5HI5/vrrL4wYMQIRERFQKpXQaDRGfxZqtRoqlUrvZ1PRplara/QallaxSH1qamqVwl9BgeG1DMm4Bz3/SZenIUlWbuAR1ssa3r/rQqy5AfFmZ27LYm7LE2t2s+auuD4048/F1Nlrc/7DQlMteXt7QyaTIT09Xa89PT0dfn5+1T72888/x+LFi7Fv374qa1Xca/bs2YiKitLdz8/PR2BgIJo1awZXV9e6fwNGJCUlISgoCE9GKHF5p+FPJsc+1A7+btVP/bC0itxWraAAiI0FIiIAFxcEBQWhW7duyMvLs/7sBojiZ24Ac9ddaWkpEhISYGdnp1uo+X7KyspqfKw5hYaG4uzZs/j4448xa9YsyOVy+Pj4ICIiAitWrNDLaGtrC3t7e73sFW3Tp0/HxYsXdWupjR8/Hq+++ir++usv3bEymQxSqVTvOe9t+/777/Hee+/hjTfewN27d9GsWTO89957sLe3R0hICI4ePYqZM2fiscceQ1lZGYKCgjBs2DA4OjoaLPJVjPwKCwsDANjY2CAwMBAvvfQSPvzwQ93rrl+/Hq+//jq6dOmCNm3a4Ouvv0a/fv1035+Hhwe+/PJL3LhxAzKZDN26dcPOnTt10/127dqF999/Hy+99BIyMzPh5+eHyMhIBAYGwt7eHjY2NpBIJEZ/FlKpFDKZTO9nU9FWcdz9XsPSNBoNbGxsEBAQUKUwYqlRxtZE6PMf/yb+CAqqfgqptbGG9++6EGtuQLzZmduymNvyxJrdbLnvuT58MJeM9pg6e23OfySa2q6WSujRowe6d++Ob775BoD2U9lmzZphxowZmDVrlsHHfPrpp/j444+xe/du9OzZs9avmZ+fDzc3N+Tl5Zm10AQArd/fCYVK/9fik1FhGNetmclf90GJ4U0r/a+/4Pvoo1CePAmb7t117WLIbghzW5Y15K4oNIWEhFQ7EqEyayk01YVYszO3aVX3e2/uv8nWSsjznwu37qBjCAtNliDW3IB4szO3ZTG35Yk1u9lynz2rLTLFxgJdujzQUwXP2mG0L3Hx8Ad67nvV5vyHu87VQVRUFFauXIl169bh6tWreOWVV1BUVIQpU6YAACZOnKi3WOYnn3yCOXPmYPXq1QgODkZaWhrS0tJQWFgo1Ldg1IXbOVWKTADQ1s/00/UaAqVSqdu96ezZswKnISIiqjshz3+4RBMREVHt9P1EuF3uWWiqg3HjxuHzzz/H3LlzER4ejvPnz2PXrl26BTKTk5Mhl8t1x//3v/+FQqHA6NGj4e/vr/v6/PPPhfoWjFp5+JbB9h+MtFP1bGxsMGDAAABA586dBU5DRERUd0Ke/3AxcCIiotpJyikV7LW5RlMdzZgxAzNmzDDYd+/2zImJieYPZCJpeYZ/GdPzhfslFRu1Wo2ioiLdou0BAQEAqm7tTUREJDZCnf9IOKaJiIhINFhoIj3jugXiTFJulfYxXQMtH0aEysvLsXXrVqSlpWHq1KlwdnYGbG2BgADtLREREZmURqOBUqmESqUSOooepVKJ0lLxfVAn1tyAeLM31Ny2trYGd1QlqvdMeH2YuHh4tes0CYWFJtIzpmszfLDtMsqUal1bIzsZxnS1voXArVF5eTkyMjJQUFCAtLQ0tGzZEggLA1JShI5GREQkWsbGMykUCsjlchQXF1s0T00olUokJCQIHaPWxJobEG/2hppbIpGgadOm2g9miRqSBnB9yEIT6blwO0evyAQARQoVLtzOQadAD4FSiYeTkxOeeeYZFBUVoVkzFueIiIjMRa1WIyEhATKZDE2aNIGdnR0kVrSYk0KhgJ2dndAxak2suQHxZm+IuTUaDTIzM5GSkoJWrVpxZBNRPcNCE+k5lZhtsP1MIgtNxiQnJ0OpVKJ58+YAAC8vL3h5ef17wMWLwCOPAH/9pa1eExERUa0Yqh8pFAqo1WoEBgbCycnJ8qHuQyKRwN7eXugYtSbW3IB4szfU3D4+PkhMTER5eTkLTdSwNIDrQ+46R3q6B3sabO8azCKTIbdv38aPP/6IDRs2IDMz0/BB5eVAaqr2loiIiExKKuXpLJEYWdMIRCKLagDXhxzRRPQA/P39ERgYCHt7e7i7uwsdh4iIqF7iBSkREZF48CMg0jNp1UmD7T8cvmXhJNZLo9Ho/m1jY4Onn376/9u776gorjYM4M/Sduk2pCgCohQVUVQUULGgYO89isaWxN5rxK4xoFjRRMVYsRF7N2ABFQUhiICIFBvYQXq73x98TFhZcBd3F5D3d84eZObOzDPjcvfO3Zk7GDp0KJTpqXKEEEKITFA3EynLvn37xP7CT5Ky34OxY8eif//+3O+dOnXCzJkzKywPIaR6oI4mwrkemYRPWaIfDfz8Q+V7mktFyMnJgY+PD+7fv89N4/P5dNk+IZXUlw1sWejUqRN4PB54PB4EAgHMzMywbt06oU5pWSnaLo/Hg46ODtq0aYPTp0+XKJeZmQk3NzeYmZmBz+ejTp06GDJkCCIiIkqUTU1NxZIlS2BhYQGBQAA9PT04OTnB19e3zH3KycnBhg0bYG1tDTU1NdSpUwcODg7w9vZG7nd8aTiRj+/pgqbqVC9pa2vDwcEB//zzj0y3OWzYMDx58kTqZb+Fv79/iTq6Z8+eCA8Pl/m2CSGkotHZMeEcf1D6IxbbNqxd6rzq5NGjR3jy5AmuXr2K9PR08RZq3Bjw8yv8SQj5Lk2cOBGvX79GdHQ0Fi1ahGXLlmHnzp1y2ba3tzdev36NwMBAODg4YPDgwUInMtnZ2XBycsLevXuxevVqPHnyBBcuXEBeXh7atm2Lu3fvcmU/ffoEe3t77N+/H4sWLUJISAhu3ryJYcOGYf78+UhJSRGZIScnB87Ozli/fj0mTZqEwMBABAUFYcqUKdi6davIDi1xUScVIeVTGeqlgIAA1KlTB71798azZ6KvjpfG37iqqirq1q0r9bLSEB0djdevX+Py5cvIzs5Gr169kJOTI7ftE0IqoWpwfkgdTYSTm19Q6ryxDiZyTFJ5tWzZEnZ2dhg9ejTU1dXFW0hTE+jUqfAnIQSvUzIRGPsOr1MyKzoKbty4AVtbW/D5fOjr62PhwoXIy8vj5n/+/BmjRo2Curo69PX1sWnTJpG3HaipqUFPTw9GRkYYN24cmjdvjqtXr3Lzs7OzMXfuXNSrVw/q6upo27Yt/P39hdbx559/ck/PGjBgADZu3CjW7R01atSAnp4eGjdujFWrViEvLw9+fn7cfE9PT9y5cwfnzp3D0KFDYWRkBFtbW5w8eRKWlpYYP348d5XD4sWLER8fj3v37sHV1RVNmjSBmZkZJk6ciNDQUGhoaIjM4OnpiZs3b+L69euYMmUKWrRogYYNG2LkyJG4d+8eGv+/IWVsbAxPT0+hZW1tbbF8+XLudx6PBy8vL/Tt2xfq6upYtWoV6tevDy8vL6HlHj58CAUFBSQkJAAo7CSbMGECdHR0oKWlhS5duiAsLOyrx49UDTwZ3zxH9ZJs6qVmzZrBy8sLmZmZ3La//Btfs2YNAOD06dOwsbGBQCBAw4YNsWLFCqH9/vTpEyZPngxdXV0IBAI0a9YM586dA1DydriwsDB07twZmpqa0NLSQqtWrfDgwQORZQHAy8sLpqamUFFRgbm5OQ4cOCA0n8fjYffu3RgwYADU1NTQuHFjnDlz5qvHAQDq1q0LPT092NjYYObMmXj+/DmioqK4+bdv30aXLl2gqqoKQ0NDTJ8+XejLzOzsbCxYsIAbE7RRo0bYs2cPACA/Px/jx4+HiYkJVFVVYW5ujs2bN4uVixBSgarB+SF1NBFOVq7o2+Ya6ahDX1tVzmkqj6SkJBQUFHbC8Xg8dO/eHYaGhuKv4OVLYNGiwp+EVHNH7yfCYf0/GPnnPTis/wdH7ydWWJaXL1+iZ8+eaNOmDcLCwuDl5YU9e/Zg3bp1XJnZs2cjICAAZ86cwdWrV3Hr1i2EhISUuk7GGG7duoWoqCioqKhw06dOnYo7d+7Ax8cH//77L4YMGQIXFxfExMQAAAICAvDTTz9hxowZCA0NRbdu3biTL3Hl5eVxJx/Ft3348GF069YN1tbWQuUVFBQwa9YsPH78GGFhYSgoKICPjw9GjRoFAwODEuvX0NCAkpLoZ4gcOnQITk5OaNmyZYl5ysrK4nfM/9/y5csxYMAAhIeHY8KECRgxYgQOHz5cYpsODg4wMjICAAwZMgRv3rzBxYsXERwcDBsbG3Tt2hUfPnyQaNukchLn1jnGGDJy8iR+HbgTL1QvHbgTL/E6pHVLWmn10urVq7kysq6Xnj59CkA69RJQeAURAKGreIr/jf/444+4desWxowZgxkzZuDx48fYtWsX9u3bx22voKAAPXr0QEBAAA4ePIjHjx9j/fr1UFRUFLnNUaNGoX79+rh//z6Cg4OxcOHCUsfS/PvvvzFjxgzMmTMHjx49wuTJkzFu3DihDnsAWLFiBYYOHYp///0XPXv2xKhRoySqX1JSUuDj4wPgvzo6NjYWLi4uGDBgAP79918cPXoUt2/fxtSpU7nlxowZgyNHjmDLli2IjIzErl27uE7/goIC1K9fH8ePH8fjx4+xbNkyLF68GMeOHRM7FyGkAlSD80N66hzhfEgXfemyimL17Y989OgRTp06BRsbG/To0aN8T71JTgbWrweGDAHq1ZN+SEIqSJ+tt/H2c7bIeQysxBUI+QUMb9P+K1/AgAUnw+F++QkUFcT/29LR5OPstPblC13Mjh07YGhoiG3btoHH48HCwgKvXr3CggULsHLlSqSnp+Ovv/7C4cOH0bVrVwCFt4OI6oTZsWMHdu/ejZycHOTm5kIgEGD69OkAgMTERHh7eyMxMZFbdu7cubh06RK8vb2xdu1abN26FT169MDcuXMBAGZmZggMDOS+rS/LiBEjoKioiMzMTBQUFMDY2BhDhw7l5j958gSdO3cWuaylpSVXxsDAAB8/foSFhYUER7FQTEwMOnXqJPFypRk5ciTGjRvH/T5q1Ch4eHggMTERDRo04DrFli5dCqDwioCgoCC8efMGfD4fAODu7o5Tp07hxIkTmDRpktSykcorMzcfTZZd/qZ1FDDg19MR+PW0ZLd7Pl7pDDWVb29Wl1UvLVu2TC710l9//YUNGzZ8U71UJCMjA0uXLoWioiIcHR256V/+jf/4449YuHAhXF1dAQANGzbEqlWrMH/+fLi5ueHatWsICgpCZGQkzMzMuDKlSUxMxLx587j6rHEZt6e4u7tj7Nix+OWXXwAUduTdvXsX7u7uQnXn2LFjMWLECADA2rVrsWXLFgQFBcHFxaXMY1C/fn0A4K5S6tu3L5dr3bp1GDVqFKZNmwY+n4/GjRtjy5YtcHR0hJeXFxITE3Hs2DFcvXoVTk5OJfZbWVkZK1as4H43MTHBnTt3cOzYMaHPAUJIJVMNzg+po4lwaqmL/qantOnVgYKCAvLz85GWloaCgoJSvzkjpDp6+zkbSalZ376eNNGdVbIWGRkJOzs7oQ5kBwcHpKWl4cWLF/j48SNyc3Nha2vLzdfW1oa5uXmJdY0aNQpLlizBx48f4ebmBnt7e9jb2wMAwsPDkZ+fz50cFcnOzkbt2oXj30VHR2PAgAFC821tbcU6odu0aROcnJwQFRWFBQsWYMuWLahVq5ZQGXGutviWKzKkPcBw69athX5v0aIFLC0tcfjwYSxcuBA3btzAmzdvMGTIEACFt8mkpaVxx7NIZmYmYmNjpZqNVIzvaCzwMlWGeqlmzZoAvq1eKt4BrqOjgz179qB58+bc/C//xsPCwhAQECB0xVR+fj6ysrKQkZGB0NBQ1K9fv0Te0syePRsTJkzAgQMH4OTkhCFDhsDU1FRk2cjIyBKd0Q4ODiVuQSueX11dHVpaWnjz5g0AoGnTptxtvB06dMDFixe5srdu3YKamhru3r2LtWvXCo2TFRYWhn///ReHDh3ipjHGUFBQgLi4OISHh5fopPvS9u3bsXfvXiQmJiIzMxM5OTlo0aLFV44QIYTIFnU0EU5NNRXR09VFT68OmjRpAldXVxgZGZXvaiZCvmM6mvxS54lzRRO3Hg2+xFc0VTba2tpo1KgRAODYsWNo1KgR2rVrBycnJ6SlpUFRURHBwcElOqtLG/NIEnp6emjUqBEMDQ1Rt25d9OzZE48fP+YGuzUzM0NkZKTIZYumm5mZQUdHBzVq1BAaO0RcZmZmYi2noKBQolNK1EDAom61GzVqFNfRdPjwYbi4uHAdS2lpadDX1y8xvgyAavUY8++aGFWEqrIiHq90lmi1SSlZcNp4AwXF3pYKPODabEfoaQvEXo+qcuX7Iqq89VJpt5hJoqgDXFtbGzo6OiXmf/k3npaWhhUrVmDgwIElygoEAu72O3EtX74cI0eOxPnz53Hx4kW4ubnBx8enRMeZJL48Ljwejxta4cKFC1xd9mVWExMT1KhRA+bm5njz5g2GDRuGmzdvAijc78mTJ+Onn34Suq0RABo0aMDdxlgaHx8fzJ07Fx4eHrCzs4OmpiZ+//133Lt3r9z7SQgh0kAdTYQUk5OTg3/++QedO3fmbr8wNjau2FCEVFJl3b6WnZ3N/Q0Vd/R+Ihb7PkI+Y1Dk8bB2YDMMa9NAljFLZWlpiZMnT4IxxnUkBwQEQFNTE/Xr10fNmjWhrKyM+/fvo0GDwowpKSl48uQJOnbsWOp6NTQ0MGPGDMydOxcPHz5Ey5YtkZ+fjzdv3qBDhw4ilzE3N8f9+/eFpn35uzhsbW3RqlUrrFmzhvs2fvjw4ViyZAnCwsKExmkqKCjApk2b0KRJE1hbW4PH42H48OE4cOAA3NzcStyKk5aWBoFAIHKcppEjR2Lx4sXc/haXm5uLnJwcqKurQ0dHB69fv+bmpaamIj4+Xqx9GzlyJJYuXYrg4GCcOHFC6KoAGxsbJCUlQUlJiers75Q4g4HzeDyJb19rqKOBdQOtStRLDXW+vRO4PCpDvZSdXfiFwLfUS0Ud4OKysbFBdHR0qcs0b94cL168wJMnT8S+qsnMzAxmZmaYNWsWRowYAW9vb5EdTZaWlggICOBu2wMKj3mTJk3Ezl80VtzXTJkyBevWrcPff/+NAQMGwMbGBo8fP4apqanIz0wrKysUFBTgxo0b3K1zxQUEBMDe3p677Q8AXcVJCKkUqu/gO6SE0q4S0NEQ/xu9qu7EiRO4d+8eTp06Jb2V1q4NjB9f+JOQam5Ymwa4vbAzjkxsh9sLO8ulkyklJQWhoaFCr+fPn+OXX37B8+fPMW3aNERFReH06dNwc3PD9OnToaCgAE1NTbi6umLevHnw8/NDREQExo8fDwUFha9e4Th58mQ8efIEJ0+ehJmZGUaNGoUxY8bA19cXcXFxCAoKwrp163D+/HkAwLRp03DhwgVs3LgRMTEx2LVrFy5evFiuKylnzpyJXbt24eX/B5icNWsWbG1t0adPHxw/fhyJiYm4f/8+Bg0ahMjISOzZs4fbzpo1a2BoaIi2bdti//79ePz4MWJiYrB37160bNkSaWlppW7TwcEBXbt2xfbt2xEWFoZnz57h2LFjaNeuHTfoeZcuXXDgwAHcunUL4eHhcHV1FfuWZGNjY9jb22P8+PHIz89H3759uXlOTk6ws7ND//79ceXKFcTHxyMwMBBLlizhnjRFSGmqQr00e/ZsudVLRbd9SbNe+pply5Zh//79WLFiBSIiIhAZGSk0DpujoyM6duyIQYMG4erVq4iLi8PFixdx6dKlEuvKzMzE1KlT4e/vj4SEBAQEBOD+/fvcmHRfmjdvHvbt2wcvLy/ExMRg48aN8PX15camkiY1NTVMnDgRbm5uYIxhwYIFCAwMxMyZMxEaGoqYmBicPn2aGwzc2NgYrq6u+PHHH3Hq1CnExcXB39+fG+y7cePGePDgAS5fvownT57g119/LdeXFIQQOasG54fU0UQ4GnzR3wKq8yvf5eCy0qlTJ9SoUQMODg7SW6mREbB7d+FPQgj0tVVhZ1pbbk+z9Pf3R8uWLYVeK1asQL169XDhwgUEBQXB2toaP/30E8aPH49FixZxy27cuBF2dnbo3bs3nJyc4ODgAEtLSwgEZXfA16pVC2PGjMHy5ctRUFAAb29vjBkzBnPmzIG5uTn69+8vdEWCg4MDdu7ciY0bN8La2hqXLl3CrFmzvrodUVxcXGBiYsKNdSIQCPDPP/9gzJgxWLx4MRo1agQXFxcoKiri7t27aNeunVDuu3fv4ocffsDq1avRsmVLdOjQAUeOHMHvv/8ObW1tkdvk8/m4evUq5s+fj127dqFdu3Zo06YNtmzZgunTp6NZs2YAgEWLFsHR0RG9e/dGr1690L9//zIH9P3SqFGjEBYWhgEDBgjdnsLj8XDhwgV07NgR48aNg5mZGYYPH46EhATo6upKfAxJ5SPru9cre71U1OECyL5eKnqyrjTrpa9xdnbGuXPncOXKFbRp0wbt2rXDpk2bhK4UOnnyJNq0aYMRI0agSZMmmD9/PvLzSz4xWVFREe/fv8eYMWNgZmaGoUOHokePHkKDZhfXv39/bN68Ge7u7mjatCl27doFb29vqT7goLipU6ciMjISx48fR/PmzXHjxg3ExMSgQ4cOaNmyJZYtWyZ0RamXlxcGDx6MX375BRYWFpg4cSI3sPjkyZMxcOBADBs2DG3btsX79++Frm4ihFRS1eD8kMekPYInkYnU1FRoa2sjJSUFWlpaUl9/QkIC5l58ifvxH0vMszWuiWM/2Ut9m9KQkJAg9uXKpcnLyxO6FSQ/P1+6g35nZgLPngENGwLFToykkb0iUG75qgy5s7KyEBcXBxMTE7FPMEq7da4qKCt7eno66tWrBw8PD4wfP16mOSZOnIioqCjcunVLrPJV9ZhX1txlve9l/ZlM/lN0rONevoGxgfBYP+Wpm+RJXu9taddLZeWWtF6St8pan3xNdc1dUX/DlaFtVR5VNTdQdbPLLHcp54flZbzwfKnz4tf3+ub1F5Gk/UNXNBHOq48ZIqdn55b8tuh78e+//2Lr1q349OkTN03qT5aLjASaNSv8SQipUh4+fIgjR44gNjYWISEhGDVqFACgX79+Ut+Wu7s7wsLC8PTpU2zduhV//fWX0JghhFRr9EAODtVLhBBSxVWD80MaDJwAAN6k5eJliuhHjH+vbbv8/HzcuXMHqampePDggchBFgkhxN3dHdHR0VBRUUGrVq1w69Yt1KlTR+rbCQoKwoYNG/D582c0bNgQW7ZswYQJE6S+HUJI1Uf1EiGEkMqMOpoIAOBFKZ1MANC24fc5SJmioiJGjBiB0NDQUp8ERQip3lq2bIng4GC5bKtocFdCSEnf6Xde5UL1EiGEkMqObp0jAICYN5mlzhvrYCLHJLKVnZ0t9ChtLS0tdOzYUSZPUCGEEEKIdNDHNCGEEFJ1UEcTAQCEJqWLnN5EX1NuT2CRtYyMDHh7e+PgwYN4/vy5/DbM4wEqKtRKJoQQQsqJR9c0EUII+V5Ug/ND6mgiAIBGNUU/6aGrRV05J5EdgUAAbW1tCAQC6Q/4XZaWLYHs7MKfhBBCCCGEEEKqLzmeH5b1RDpZojGaCABAQ1V0x0sNNRU5J5EdBQUFDBo0CBkZGahRo0ZFxyGEEEKIuL7fL30JIYSQ7w5d0UQAAGmZ+SKnf8rIkXMS6QoNDcXt27e531VUVOTfyRQZCdjYfNePrySEEEJk6Tu+u4AQQkh1Uw3OD6mjiQAAQl+LHqPpXtwHOSeRnlevXuH06dO4fv06EhISKi5IZibw8GHhT0IIIYRIjPqZCCGEfDekfH4Yv76XVNYjTdTRRAAAtdRF30Wpq8mXcxLpMTAwgL29Pdq3b48GDRpUdBxCCAAkJwNHjwK7dxf+TE6u0Dj+/v7g8Xj49OmTXLe7b9++b766Mj4+HjweD6GhoaWWqaj9I6RKoXoJANVLhBBCpIc6mggAYLi1jsjpEzo2lHOSb5OVlYW8vDzudycnJ3Tt2hU8uuaekIoVHg6MGAHUrw8MHw5MnFj4s379wunh4VLfJI/HK/O1fPlyqW+zKsrKysKUKVNQu3ZtaGhoYNCgQUj+yon28uXLYWFhAXV1ddSsWRNOTk64d++eUBljY+MSx3z9+vWy3BXyHZPJ5zjVS1XKv//+iw4dOkAgEMDQ0BAbNmwos/z79+/h4uICAwMD8Pl8GBoaYurUqUhNTeXKFHV6fflKSkqS9e4QQsh3jTqaCADAUlcN1vW1haYNsqkHa8OaFZRIcikpKfD29saZM2fAGAMgo4YpIUQyly8DtrbAiRNAsY5gAIW/nzhROP/yZalu9vXr19zL09MTWlpaQtPmzp1brvXm5FTtseu+NGvWLJw9exbHjx/HjRs38OrVKwwcOLDMZczMzLBt2zaEh4fj9u3bMDY2Rvfu3fH27VuhcitXrhQ65tOmTZPlrpDvmNQ/zaleqlJSU1PRvXt3GBkZITg4GL///juWL1+OP/74o9RlFBQU0K9fP5w5cwZPnjzBvn37cO3aNfz0008lykZHRwv9P9St+/08dZkQUj2UdvtcRd1WRx1N5bR9+3YYGxtDIBCgbdu2CAoKKrVsREQEBg0axH276+npKb+g1cj79+/x7t07xMXF4fPnzxUd5z8mJsCxY4U/CaluwsOB/v0LH+H65clckby8wvn9+0v1CgI9PT3upa2tDR6PJzRNQ0ODKxscHIzWrVtDTU0NnTp1QnR0NDdv+fLlaNGiBXbv3g0TExMIBAIAwKdPnzBhwgTo6OhAS0sLXbp0QVhYGLdcWFgYOnfuDE1NTWhpaaFVq1Z48OCBUMbLly/D0tISGhoacHFxwevXr7l5BQUFWLlyJerXrw8+n48WLVrg0qVLZe7zhQsXYGZmBlVVVXTu3Bnx8fFllk9JScGePXuwceNGdOnSBa1atYK3tzcCAwNx9+7dUpcbOXIknJyc0LBhQzRt2hQbN25Eamoq/v33X6FympqaQsdcXV29zDyk8quo9o9UvzeqgvWSvb293Oqlq1evVmi9JMqhQ4eQk5ODvXv3omnTphg+fDimT5+OjRs3lrpMzZo18fPPP6N169YwMjJC165d8csvv+DWrVslytatW1fo/0FBgU6RCCEyJKPzwy87lSpy7CaqRcvh6NGjmD17Ntzc3BASEgJra2s4OzvjzZs3IstnZGSgYcOGWL9+PfT09OScVjyRyRkIe5EiNO1kyEuEPf9YQYkk17BhQwwePBgTJkyAlpZWRcf5T82awJAhhT8JqW7Wri08Yfv/VYalYqyw3Lp18sn1hSVLlsDDwwMPHjyAoqIifvzxR6H5T58+xcmTJ+Hr68uNPTJkyBC8efMGFy9eRHBwMGxsbNC1a1d8+FD4EIVRo0ahfv36uH//PoKDg7Fw4UIoKytz68zIyIC7uzsOHDiAmzdvIjExUehqhs2bN8PDwwPu7u74999/4ezsjL59+yImJkbkPjx//hwDBw5Enz59EBoaigkTJmDhwoVl7ndwcDByc3Ph5OTETbOwsECDBg1w584dsY5dTk4O/vjjD2hra8Pa2lpo3vr161G7dm20bNkSv//+u9CtzaTq+W7aP1WwXlJSUpJbvbRp0ya510s8Hg/79u0r9VjcuXMHHTt2hIqKCjfN2dkZ0dHR+PhRvLbqq1ev4OvrC0dHxxLzWrRoAX19fXTr1g0BAQFirY8QQspNhueH8et74cbPzSp+gHBGJGZra8umTJnC/Z6fn88MDAzYunXrvrqskZER27Rpk8TbTElJYQBYSkqKxMuKY87BQGa04FyJ14ozj2SyPWn5559/WFpaWkXHKFtSEmMeHoU/i4mPj6+gQN+GcstXZcidmZnJHj9+zDIzM8VeJisrq/A9r6TEWOHpmngvJSXGkpOlvg/e3t5MW1u7xHQ/Pz8GgF27do2bdurUKQaA2183NzemrKzM3rx5w5W5desW09LSKtzPYkxNTdmuXbsYY4xpamqyffv2lZoHAHv69Ck3bfv27UxXV5f73cDAgK1Zs0ZouTZt2rBffvmFMcZYXFwcA8AePnzIGGNs3rx5rEmTJkLlFyxYwACwjx8/isxx6NAhpqKiUmJ6mzZt2Pz580UuU+Ts2bNMXV2d8Xg8ZmBgwIKCgoTme3h4MD8/PxYWFsa8vLxYjRo12KxZs0qs58tjWFmU9b6X9WdyZVWR7Z+ktx9KzCtP3STPeulr721J6qXz58/LrV6KiIjgpn1rvbRo0SKx6iVzc3Pm6+srMhdjjHXr1o1NmjRJaFpERAQDwB4/fsxNE3XMhw8fzlRVVRkA1qdPH6H3S1RUFNu5cyd78OABCwgIYOPGjWNKSkosODi41CyyUFnrwa/51tzl+huWgsrQtiqPqpqbsaqbXWa5Szk/lBZZ5Zak/UNXNEkoJycHwcHBQt/+KigowMnJSexvf8WRnZ2N1NRUoZcsMZTyrd5XvuyrSHfu3MHNmzfh4+NTub8lf/kSmDOn8Cch1Ym/f+m3pZQmL69wOTlr3rw59++iKy+KX6VhZGQEHZ3/HpoQFhaGtLQ0bgDtoldcXBxiY2MBALNnz8aECRPg5OSE9evXc9OLqKmpwdTUlPtdX1+f22ZqaipevXoFBwcHoWUcHBwQGRkpch+io6PRtm1boWl2dnZiHwNJde7cGaGhoQgMDISLiwuGDh0qdMxmz56NTp06oXnz5vjpp5/g4eGBrVu3Ijs7W2aZiOxUdPtHarfOVdF6SV9fH0DVq5ciIyPFqpeioqIwYMCA0g/GN9i0aRNCQkJw+vRpxMbGYvbs2dw8c3NzTJ48Ga1atYK9vT327t0Le3t7bNq0SSZZCCEEQLU4PxT9THtSqnfv3iE/Px+6urpC03V1dREVFSW17axbtw4rVqwoMT0xMRGamppS206RBhqKIqfXVclBQkKC1LcnDWpqalBRUUHt2rXx4sWLSjvwt8rr19BH4QCgOcWOZUZGRqU9tmWh3PJVGXLn5eUhLy8POTk5Yv+dFRQUIPfDByh/vWgJue/fo0DKnRG5ubkAUKKTo2gA3YKCAm4e+//tNJmZmcjOzkZeXh7U1NSElv306RP09fVx5cqVEtvS1tZGdnY2Fi1ahMGDB+PixYu4fPky3NzccODAAfTr1w+5ublQVlYWWmdeXh4YY8jOzuam5+TkCJXJz8/nsn5ZhjGG/Px8ofLF91tUB0+tWrWQk5OD5ORkoceaJyUloU6dOmV2CikpKcHQ0BCGhobYsWMHmjZtil27dmH+/Pkiy7ds2RJ5eXl48uQJzMzMuOnFj31lkpOTg7y8PLx8+RJKSsLNpUo1DqCcVHT758Xz58hME/7SrTx1k4Ic66WvvbclqZeKysqjXiq+3W+tlwoKCiSul0TR0dHB69evhco/f/4cQOFYTEXTRR3zmjVrombNmjAxMYGGhga6du2K+fPnc513X2rVqhUCAwPlWi9V1nrwa741d1n1rCxVhrZVeVTV3EDVzS6r3KWdH0qLrHJL0v6hjqZKatGiRULfuKSmpsLQ0BANGjSQyfhDz2+/Ejn9Ta4KjIyMpL698mKMcY1JIyMj8Pl8WFhYVHCqr3j/HsD/v40sdiwTEhIq1bEVF+WWr8qQOysrC3FxcVBRUQGfzxdrmezsbCjXqlWu7SnXrg2IuR2x1/n/MUi+zF803gefz+fmFQ0CWzRNSUkJPB5PaFlbW1u4ublBTU0NxsbGpW63WbNmaNasGebNm4cRI0bg4MGDGDp0qMg8xafp6OjAwMAA9+/fR7du3bgyd+/eha2trVDeov8XCwsLXLhwQWidwcHBJfavODs7OygrK+P27dsYNGgQgMIro54/f44OHTqI/f8NgOvoKm2Zx48fQ0FBgRtEuEh2drZE25EXxhiUlJRQr149bqDlIrK+yrg6K639U9/QEHVrC49lUZ66CXKsl7723pakXvpymizrJQUFBW6931ovNW3aFGfOnJGoXhKlffv2WLJkCRQUFLhMN27cgLm5udD4X1875sU7M0orFx4eDgMDA7nWS5W1Hvyab81dVj0rS5WhbVUeVTU3UHWzyyx3KeeH0iKr3JK0f+jWOQnVqVMHioqKSE5OFpqenJws1YEu+Xw+tLS0hF6yVBVunfv06RO8vb2FHp+tqqpagYkIIWXq1AmQ9BtKJaXC5So5Jycn2NnZoX///rhy5Qri4+MRGBiIJUuW4MGDB8jMzMTUqVPh7++PhIQEBAQE4P79+7C0tBR7G/PmzcNvv/2Go0ePIjo6GgsXLkRoaChmzJghsvzEiRMRExODefPmITo6GocPHy5zcF2g8CqH8ePHY/bs2fDz80NwcDDGjRsHOzs7tGvXjitnYWGBv//+GwCQnp6OxYsX4+7du0hISEBwcDB+/PFHvHz5EkOGDAFQeGuzp6cnwsLC8OzZMxw6dAizZs3CDz/8gJr0YIQqqaLbP1K7aJnqJbnWSz/99JNY9VLxOkaUkSNHQkVFBePHj0dERASOHj2KzZs3C3VK/v3330K3G164cAHe3t549OgR4uPjcf78efz0009wcHDgOuI8PT1x+vRpPH36FI8ePcLMmTPxzz//YMqUKWIfE0IIISVRR5OEVFRU0KpVK1y/fp2bVlBQgOvXr8t0LAxZ69ZYdMO/X0sDOScp3ZUrV/D8+XOcPXuWu7WlStDWBvr0KfxJSHWiqwsMHiz+SZ2SUuETOOrWlW0uKeDxeLhw4QI6duyIcePGwczMDMOHD0dCQgJ0dXWhqKiI9+/fY8yYMTAzM8PQoUPRo0cPkbcElWb69OmYPXs25syZAysrK1y6dAlnzpxB48aNRZZv0KABTp48iVOnTsHa2ho7d+7E2rVrv7qdTZs2oXfv3hg0aBA6duwIPT09+Pr6CpWJjo5GSkrhk0kVFRURFRWFQYMGwczMDH369MH79+9x69YtNG3aFEBhZ4GPjw8cHR3RtGlTrFmzBrNmzcIff/wh9v6TyqWi2z88SKmnieqlSlkvFa9jRNHW1saVK1cQFxeHVq1aYc6cOVi2bBkmTZrElUlJScGTJ0+431VVVfHnn3+iffv2sLS0xKxZs9C3b1+cO3eOK5OTk8Pti6OjI8LCwnDt2jV07dpV7GNCCCESqwbnhzxWpc7YK4ejR4/C1dUVu3btgq2tLTw9PXHs2DFERUVBV1cXY8aMQb169bDu/4/DzcnJwePHjwEAPXv2xKhRozBq1ChoaGigUaNGYm0zNTUV2traSElJkcnVTQkJCXD0eiQ0TV1FERErXaS+rfLKyMjAuXPn4OLiwh2DqnoZJlB1s1Nu+aoMuYtuTzExMRH70nbucvrwcMDWFsjOLvtR4jxe4W0pQUGAlZWUkpdPdb2FoaJU1txlve9l/ZlcWVVk++fdh4+oXbOG0Lzy1E0A5FYvVdb39tdU1dxA1c1eXXOX+2/4G1WGtlV5VNXcQNXNTrmFSdL+oTGaymHYsGF4+/Ytli1bhqSkJLRo0QKXLl3iBshMTEzkxvgAgFevXqFly5bc7+7u7nB3d4ejoyP8K+ApJqKsu/68xLT0nHwcf5CIIa0bVECiQu/evUOdOnUAFA7+PXTo0ArLUm65ucCnT0CNGoByeYYgJaQKs7ICTp0C+vcvfHKTqKc9KSkVvk6dqvBOJkJI6b6b9g/VS4QQQipSNTg/pFvnymnq1KlISEhAdnY27t27J/ToVn9/f6H7z42NjcEYK/GqLJ1Mr1MycemJ6MuVz4aJHiRc1hhjuHbtGnbs2IGnT59WSAapCQ8vvOQ+PLyikxBSMZydC68IGDKk5O0qRbelBAUVliOEVGoV1f6R+nNlqV4ihBBSUarB+SFd0UQQ9y691HmW+hV3S0BaWhoYY0hOThb7EntCSCVlZQUcPgx4egL+/kBqKqClVTjAbhUY+4QQUrF4UhsNvBiqlwghhBCZoI4mgoiXpQ++ONbBRI5J/sPj8dCnTx80bdq01AEmCSFVUN26QFW8BZYQUqFk0M30H6qXCCGEEKmiW+cIrjxOFjndpLYa9LVV5Zbj48ePCAwM5H5XVFSkTiZCCCGEEEIIIaQKoSuaCLJz80VO1xLI7+2RlZWFPXv2ID09HQKBADY2NnLbNiGEEEIqN1ncOUcIIYQQ2aCOJoLcfNGP9i1tuiwIBAK0a9cOERER399VTNbWQEoKoK5e0UkIIYSQKkkmYzQRQgghFaEanB9SRxNBLXXRj1Qsbbo05efnQ1FREQDg4OCAtm3bQvl7e8SjomLh4KKEEEIIIYQQQqq3anB+SGM0kQrBGMOVK1dw9OhRFBQUACj8tvK762QCgJiYwscjx8RUdBJCCCGEEEIIIRWpGpwfUkcTwYf0XImmS8P79+9x//59xMTE4NmzZzLbTqXw+TNw5UrhT0IIIYSQCsDj8XDq1CmplyXy1alTJ8ycOZP73djYGJ6enhWWhxBSDtXg/JA6mghSM3NETldWlN14CHXq1MHAgQMxYMAANGrUSGbbIYRUXzwer8zX8uXLER8fLzStdu3a6NWrFx4+fMitp1OnTtx8gUAAMzMzrFu3DoxJPo7d8ePHYWFhAYFAACsrK1y4cOGry2zfvh2WlpZQVVWFubk59u/fLzR/3759XLbiOSUl6hi1b99e5HxtbW04ODjgn3/+4eaPHTuWm6+srAwTExPMnz8fWVlZEmfx9/eHjY0N+Hw+GjVqhH379pVZPisrC2PHjoWVlRWUlJTQv39/keW+diwJkYfifysqKipo1KgRVq5ciby8PJlu9/Xr1+jRo4fUy0oTYwzLli2Dvr4+VFVV4eTkhBgJvvH//fffwePxhDpigMI6YsqUKahduzY0NDQwaNAgJCeLfupyaYrqWh6PBwUFBejr62PYsGFITEyUaD2VQXmOR3JyMsaOHQsDAwOoqanBxcUFT58+FSpT/POy6PXTTz/JclcIIZUUdTRVc69TMvEyJVvkPGmPu/nhwwekpKRwv1taWqJ58+bS3QghhPzf69evuZenpye0tLSEps2dO5cre+3aNbx+/RqXL19Geno6evTogU+fPnHzJ06ciNevXyM6OhqLFi3CsmXLsHPnTonyBAYGYsSIERg/fjwePnyI/v37o3///nj06FGpy3h5eWHRokVYvnw5IiIisGLFCkyZMgVnz54VKqelpYX4+Hhu3xISEiTKVsTb21voGJ05c0bk/ICAANSpUwe9e/cWuirVxcUFr1+/xrNnz7Bp0ybs2rULbm5uEmWIi4tDr1690LlzZ4SGhmLmzJmYMGECLl++XOoy+fn5UFVVxfTp0+Hk5CSyjLjHkhB5KPpbiYmJwZw5c7B8+XL8/vvvIsvm5Ij+QlBSenp64PP5Ui8rTRs2bMCWLVuwc+dO3Lt3D+rq6nB2dharw/r+/fvYvXu3yLblrFmzcPbsWRw/fhw3btzAq1evMHDgQInzFX2OvHz5EidPnkR0dDSGDBki8XoqmqTHgzGG/v3749mzZzh9+jQePnwIIyMj9OjRA+np6UJliz4vi14bNmyQ9e4QQioh6miq5q49Lv3bi7YNa0ttO69evcKePXtw+PDhcn27TQghktLT0+Ne2tra4PF4QtM0NDS4srVr14aenh5at26NdevWITk5Gffu3ePmq6mpQU9PD0ZGRhg3bhyaN2+Oq1evSpRn8+bNcHFxwbx582BpaYlVq1bBxsYG27ZtK3WZAwcOYPLkyRg2bBgaNmyI4cOHY9KkSfjtt9+Eyn25b7q6uhJlK1KjRg2h9dSqVUvk/GbNmsHLywuZmZlCx4HP50NPTw+Ghobo378/nJycJD5OO3fuhImJCTw8PGBpaYmpU6di8ODB2LRpU6nLqKurw8vLCxMnToSenp7IMuIeS0LkoehvxcjICD///DOcnJy4jt2xY8eif//+WLNmDQwMDGBubg4AeP78OYYOHYoaNWqgVq1a6NevH+Lj44XWu3fvXjRt2hR8Ph/6+vqYOnUqN6/47XA5OTmYOnUq9PX1IRAIYGRkhHXr1oksCwDh4eHo0qULVFVVUbt2bUyaNAlpaWnc/KLM7u7u0NfXR+3atTFlyhTk5oo/DANjDJ6enli6dCn69euH5s2bY//+/Xj16tVXb+NLS0vDqFGjsGPHDtSsWVNoXkpKCvbs2YONGzeiS5cuaNWqFby9vREYGIi7d++KnQ/4r67V19eHvb09xo8fj6CgIKSmpnJlTp8+DRsbGwgEAjRs2BArVqwQulrt06dPmDx5MnR1dSEQCNCsWTPu6tb3799jxIgRqFevHtTU1GBlZYUjR45IlPFrynM8YmJicPfuXXh5eaFNmzYwNzeHl5cXsrKySuQr+rwseml95wMeE0JEo46mau7N59I7fcY6mEhtO+rq6lBQUICioqLMLw2vdAwNgW3bCn8SQio9VVVVAKKvImCM4datW4iKioKKigo33d/fHzwer8RJX3F37twpcbWNs7Mz7ty5U+oy2dnZJW6DU1VVRVBQkNAJXFpaGho3bgxDQ0P069cPERERZe6jNJR1nADg0aNHCAwMFDpORbcq+vv7l7re8hwncYh7LAmpCKqqqkJ/S9evX0d0dDSuXr2Kc+fOITc3F87OztDU1MStW7cQEBAADQ0NuLi4cMt5eXlhypQpmDRpEsLDw3HmzJlShyfYsmULzpw5g2PHjiE6OhqHDh2CsbGxyLLp6elwdnZGzZo1cf/+fRw/fhzXrl0T6sQCAD8/P8TGxsLPzw9//fUX9u3bJ3Tb6/Lly0vdBlB4NWNSUpLQ37+2tjbatm371b//KVOmoFevXujatWuJecHBwcjNzRVar4WFBRo0aPBN9cqbN2/w999/Q1FRkXuC8q1btzBmzBjMmDEDjx8/xq5du7Bv3z6sWbMGAFBQUIAePXogICAABw8exOPHj7F+/Xpu+aysLLRq1Qrnz5/Ho0ePMGnSJIwePRpBQUFi5xo7diw6depU6vzyHI/s7MK7H4rXoQoKClBRUcHt27eFyh46dAh16tRBs2bNsGjRImRkZIidnZBqoxqcHypVdABSsRrUUhM5fUiretDXVpXadrS1teHq6gotLS2hk45qQUcHmDKlolMQIhuvXxe+iqtZEzAwALKygMePSy5jY1P4Mzoa+OKSexgbA7VqAW/fAs+fC8/T1AQaN5ZadFE+ffqEdevWQUNDA7a2ttz0HTt2YPfu3cjJyUFubi4EAgGmT5/OzVdTU4O5uXmZT85MSkoqcaWRrq4ukpKSSl3G2dkZu3fvRv/+/WFjY4Pg4GDs3r0bubm5ePfuHfT19WFubo69e/fCwsICmZmZcHd3h729PSIiIlC/fn2J9n/EiBHcCQ8AHDx4UOR4RxkZGVi6dCkUFRXh6OjITT937hw0NDSQl5eH7OxsKCgoCF2xpaysDHNzc6ipif7sAUo/TqmpqcjMzOQ6uCQlzrEk34nS6iUTk0pXLzHGcP36dVy+fBnTpk3jpqurq2P37t1cm+ngwYMoKCjA7t27wfv/2Abe3t6oUaMG/P390b17d6xevRpz5szBjBkzuPW0adNG5HYTExPRuHFjtG/fHjweD0ZGRqVmLLoaff/+/VBXVwcAbNu2DX369MFvv/3G/b3WrFkT27Ztg6KiIiwsLNCrVy9cv34dEydOBFA4PqepqWmp2ymqCyWtJ318fBASEoL79++Xul4VFRXUqFFDovWKkpKSAg0NDTDGuA6U6dOnc8dlxYoVWLhwIVxdXQEADRs2xKpVqzB//ny4ubnh2rVrCAoKQmRkJMzMzLgyRR059erVE7qte9q0abh8+TKOHTsm9JlUFn19fe6JzqKU53gUdUQtWrQIu3btgrq6OjZt2oSXL1/idbG/tZEjR8LIyAgGBgb4999/sWDBAkRHR8PX11es7IRUG9Xg/JA6mqq5T5miv8W10Pu2y1wLCgpw/fp1NGnSBPXq1QNQ2MColj58AC5cAHr2LGyoEvI92bULWLFCeNqoUcCePcCLF0CrViWXKRpEe+xY4MvL9A8cAH74ATh2DPji23J07w6UMU7Pt7C3t4eCggLS09NhYmKCo0ePCp3sjBo1CkuWLMHHjx/h5uYGe3t72Nvbc/NtbW0RFRUl9Vy//vorkpKS0K5dOzDGoKurC1dXV2zYsAEKCoUXJdvZ2cHOzg7Z2dng8/mwt7eHpaUldu3ahVWrVkm0vU2bNgl9y/1l50tRR1RmZiZ0dHSwZ88eofFQOnfuDC8vL6Snp2PTpk1QUlLCoEGDuPn16tWTyXEShzjHknwnSquXDh6sNPVSUadsbm4uCgoKMHLkSCxfvpybb2VlJfTFXFhYGJ4+fQpNTU2h9WRlZSE2NhZv3rzBq1evRF7RI8rYsWPRrVs3mJubw8XFBb1790b37t1Flo2MjIS1tTXXmQIADg4OKCgoQHR0NFdXNm3aVKijWl9fH+Hh4dzvU6dOLXEV1Ld6/vw5ZsyYgatXr0IgEHAdNrKiqamJkJAQ5Obm4uLFizh06BB3tRJQ+P8UEBAgNC0/Px9ZWVnIyMhAaGgo6tevz3UyfSk/Px9r167FsWPH8PLlS+Tk5CA7O7vMzvkvFb8FUlqUlZXh6+uL8ePHo1atWlBUVISTkxOcnZ25jk8AmDRpEvdvKysr6Ovro2vXroiNjS2zk5GQaqcanB9SR1M1V0NV9LfvWqrf9tYIDAxEYGAgwsLCMG3atAoZULLSiI8HRo8GgoO/24qEVGOTJwN9+wpPKxofo379wvd9afbtE33lAAAMHQrY2QnP++IES5qOHj2KJk2aoHbt2lBVVS1RZ2lra3O3oBw7dgyNGjVCu3btSh14WhQ9Pb0ST/VJTk4udUwhoPB2mr1792LXrl1ITk6Gvr4+/vjjD2hqakJHR0fkMsrKymjZsmWJpwGJm7GsJ4EWdURpa2uL3L66ujq3/N69e2FtbY09e/Zg/PjxEmUQdZy0tLTKfTUTUL5jSaqoKlAvFXXKqqiowMDAAEpKwu2u4p06QOHtsa1atcKhQ4dKrEtHR0fizlIbGxvExcXh4sWLuHbtGoYOHQonJyecOHFC8p35vy+v6OTxeGVeWfOlorqw6O+zSHJyMlq0aCFymeDgYLx58wY2RVekobCz5ubNm9i2bRuys7Ohp6eHnJwcfPr0Segqnq/Vv6IoKChwdZylpSViY2Px888/48CBAwAK/59WrFghcmBtgUDw1Trs999/x+bNm+Hp6QkrKyuoq6tj5syZUhsQHkC5j0erVq0QGhqKlJQU5OTkQEdHB7a2tqVeNQcAbdu2BQA8ffqUOpoIKa4anB9SR1M1d+PJW5HTbz55iyGtG5R7vW3atEF0dDTatm1bvTuZCPne6esXvr6UnQ0IBP/djiLK/we4FUlHp/AlJ4aGhlwj+GvfiGtoaGDGjBmYO3cuHj58KPRtblns7Oxw/fp1ocduX716FXZfnriKoKyszN0G5+Pjg969e5d6Ypmfn4/w8HD07NlTrFyS+FpHVHEKCgpYvHgxZs+ejZEjR4rdSWRnZ8cNjFtE3OMkDkmOJamiSquXgEpTLxXvlBWHjY0Njh49irp165Y6uLKxsTGuX7+Ozp07i7VOLS0tDBs2DMOGDcPgwYPh4uKCDx8+lOjksrS0xL59+5Cens7NCwgIgIKCAjdQuTSYmJhAT08P169f5zqWUlNTce/ePfz8888il+natavQVVM5OTmYPHkyLCwssGDBAigqKqJVq1ZQVlbG9evXuSsso6OjkZiY+M31ysKFC2FqaopZs2bBxsYGNjY2iI6OLvX/tnnz5njx4gWePHki8qqmgIAA9OvXDz/88AOAwjsEnjx5giZNmnxTzuK+9Xhoa2sDKBwgPDg4GKtXry61bGhoKICSV8cSQr5/1LKq5pJSRA8Gnpwq+ZPhij9Njs/n48cff0SzZs3KnY0QQiqryZMn48mTJzh58iQAICgoCBYWFnj58mWpy8yYMQOXLl2Ch4cHoqKisHz5cjx48EDoVpJFixZhzJgx3O9PnjzBwYMHERMTg6CgIAwfPhyPHj3C2rVruTIrV67ElStX8OzZM4SEhOCHH35AQkICJkyYIIM9l8yQIUOgqKiI7du3AwBevnwJCwuLMge2/emnn/Ds2TPMnz8fUVFR2LFjB44dO4ZZs2ZxZbZt21biFqHHjx8jNDQUHz58QEpKCkJDQ7mTHEC8Y0lIZTVq1CjUqVMH/fr1w61btxAXFwd/f39Mnz4dL168AFA42LaHhwe2bNmCmJgYhISEYOvWrSLXt3HjRhw5cgRRUVF48uQJjh8/Dj09vRLj9hRtWyAQwNXVFY8ePYKfnx+mTZuG0aNHS/SES1F/t8XxeDzMnDkTq1evxpkzZxAeHo4xY8bAwMBAaKy4rl27cmO/aWpqolmzZtyradOmUFdXR+3atbk2qLa2NsaPH4/Zs2fDz88PwcHBGDduHOzs7NCuXTux84tiaGiIAQMGYNmyZQCAZcuWYf/+/VixYgUiIiIQGRkJHx8fLF26FADg6OiIjh07YtCgQbh69Sp3VdmVK1cAAI0bN8bVq1cRGBiIyMhITJ48ucQVnl/z5efIl8Q9HhYWFvj777+5348fPw5/f388e/YMp0+fRrdu3dC3b1/ulsvY2FisWrUKwcHBiI+Px5kzZzBmzBh07NhR6BZrQkj1QB1N1dywNqJHuh/SWrIR8BMTE7F161Y8evSImybut/yEEFLV1KpVC2PGjMHy5ctRUFCAjIwMREdHl/n0Mnt7exw+fBh//PEHrK2tceLECZw6dUqoQ/7169dITEzkfs/Pz4eHhwesra3RrVs3ZGVlITAwUOjJTR8/fsTEiRPRokUL9OzZE6mpqQgMDBT6BvxrT3uSFSUlJUydOhUbNmxAeno6cnNzER0dXeZTiExMTHD+/HlcvXoV1tbW8PDwwO7du+Hs7MyVeffuHWJjY4WW69mzJ1q2bImzZ8/C398fLVu2RMuWLbn54hxLQiorNTU13Lx5Ew0aNMDAgQNhaWmJ8ePHIysri7vCydXVFZ6entixYweaNm2K3r17IyYmRuT6NDU1sWHDBrRu3Rpt2rRBfHw8Lly4IPLqPjU1NVy+fBkfPnxAmzZtMHjwYKHOHnGJ+rv90vz58zFt2jRMmjQJbdq0QVpaGi5duiT0tLPY2Fi8e/dOom1v2rQJvXv3xqBBg9CxY0fo6emVGKDa2NhYaJwscc2aNQvnz59HUFAQnJ2dce7cOVy5cgVt2rRBu3btsGnTJqHB1k+ePIk2bdpgxIgRaNKkCebPn4/8/HwAwNKlS2FjYwNnZ2d06tQJenp6Ih/IUJYvP0dEEed4REdHIyUlRWi9o0ePhoWFBaZPn47Ro0dj//793HwVFRVcu3YN3bt3h4WFBebMmYNBgwbh7NmzEuUnhHwfeIwVjX5IKrPU1FRoa2sjJSWl1Eumy8t86UVk5/13D726iiIiVrpItI4rV67gzp07aNCgAcaOHSu3TqaEhIQyn5RSKURHFw4uum+f0CX5VSK7CJRbvipD7qysLMTFxcHExKTE4+FLUzQwdVVUVbOXldvV1RU8Hk/oUeOVRWU93mW972X5mUyElXWsy1M3yVNlfW9/TVXNDZQ/e0ZGBmrXro2LFy+iU6dO0g/2FVX1mH9r7or6G64MbavyqKq5gaqbXWa5Szk/lBZZ5Zak/UNjNFVzYc8/CnUyAUB6Tj7Cnn+EtWFNsdfj5OQEdXV1tGnThq5k+pK5OXDnTkWnIIRUU4wx+Pv74/bt2xUdhRBCKiU/Pz906dKlQjqZCCHVUDU4P6Rb56q5oPgPIqc/iP9Y5nIFBQX4999/UXRBnIKCAhwcHIQexUsIIaTi8Xg8JCQkwNBQsluiCSGkuujVqxfOnz9f0TEIIeS7QR1N1ZytsejHKbY2Lv1qJsYYTpw4gb///hs3btyQVbTvR0gIwOMV/iSEEEIIIYQQUn1Vg/ND6mgiEuPxeDA1NYWSkhLq1q1b0XEIIYQQQgghhBBSSdAYTdXcqYevRE4/HfqqzDGaWrVqhUaNGkFbW1tW0QghhBBCCCGEEFLF0BVN1dyT5FTR05OEpyckJMDHxwd5eXncNOpkIqR6oYeUkuqE3u9VB/1fEVI10d8uId8v6miq5r584lyRnPz/pufm5uL48eOIjo6mpxYRUg0pKysDKHz8MyHVRU5ODgBAUVGxgpOQ0lDdREjVRvUsId8vunWumrNrWBsPEj6VmN7WpDb3b2VlZQwaNAjBwcFwcHCQY7rvRJMmQEwMUL9+RSchpFwUFRVRo0YNvHnzBgCgpqYGHo9X5jI5OTlV9pvKqpqdcktPQUEB3r59CzU1NSgpUVOpsipP3SRPlfG9LY6qmhuoutmrY26qZ0m1Vg3OD+mvuppLy84XOT09OxepqanQ0tICAJiYmMDExESe0b4fAgHQqFFFpyDkm+jp6QEAd0L3NXl5eVW24VhVs1Nu6VJQUECDBg0qVccFKUnSukmeKut7+2uqam6g6mavrrmpniXVVjU4P6x6NRqRqtLGaLoRGgPtuH8wfvx4aGhoyDnVdyYuDvj1V2DVKoA660gVxePxoK+vj7p16yI3N/er5V++fIl69erJIZn0VdXslFu6VFRUoKBAIwxUdpLWTfJUWd/bX1NVcwNVN3t1zU31LKm2qsH5IXU0ldP27dvx+++/IykpCdbW1ti6dStsbW1LLX/8+HH8+uuviI+PR+PGjfHbb7+hZ8+eckwsWmljNGXl5iMtLQ1v3ryhjqZv9fEjcOgQMHv2d1uRkOpDUVFRrLEUlJSUIBAI5JBI+qpqdspN5KGytn/ErZvkqaq+t6tqbqDqZqfchFQz1eD8kLqQy+Ho0aOYPXs23NzcEBISAmtrazg7O5d62XZgYCBGjBiB8ePH4+HDh+jfvz/69++PR48eyTl5Sc8/iB5As0crU7i6uqJhw4ZyTkQIIYSQyqgi2z/hLz5+a3xCCCGEyAl1NJXDxo0bMXHiRIwbNw5NmjTBzp07oaamhr1794osv3nzZri4uGDevHmwtLTEqlWrYGNjg23btsk5ubDrkUlI/pwjcp66ujrqf8eDkxFCCCFEMhXZ/hnxZxDmHAv9xj0ghBBCiDzQrXMSysnJQXBwMBYtWsRNU1BQgJOTE+7cuSNymTt37mD27NlC05ydnXHq1KlSt5OdnY3s7Gzu95SUFABAaqroMZXKY+2pEBRki76iSZ2XI9Vtycrnz58rf860tP9+FstaJbKLQLnli3LLX1XNTrnlpyhvVXxKVHlVdPunIDsDx+/EYGCzmrCqX/Mb9kR+quJ7G6i6uYGqm51yyxfllr+qml1muUs5P5QWWeWWpP1DHU0SevfuHfLz86Grqys0XVdXF1FRUSKXSUpKElk+KSmp1O2sW7cOK1asKDHd0NCwHKklN9kTmCyXLVUjjo4VnYAQQogUvX//Htra2hUdQy4quv3z0mssAKC9p2S5CSGEkEqrip4ffv78+avtH+poqqQWLVok9C1gQUEBPnz4gNq1a0v9EaCpqakwNDTE8+fPoaWlJdV1y1JVzQ1U3eyUW74ot/xV1eyUW75SUlLQoEED1KpVq6KjfHe+bP98+vQJRkZGSExMrFKdelX1vV1VcwNVNzvlli/KLX9VNTvlLokxhs+fP8PAwOCrZamjSUJ16tSBoqIikpOThaYnJydDT09P5DJ6enoSlQcAPp8PPp8vNK1GjRrlCy0mLS2tKvVHVKSq5gaqbnbKLV+UW/6qanbKLV/V6bHcFdn+AQBtbe0q+R6pqu/tqpobqLrZKbd8UW75q6rZKbcwcb/0qT4tJClRUVFBq1atcP36dW5aQUEBrl+/Djs7O5HL2NnZCZUHgKtXr5ZanhBCCCGkMqH2DyGEEELERVc0lcPs2bPh6uqK1q1bw9bWFp6enkhPT8e4ceMAAGPGjEG9evWwbt06AMCMGTPg6OgIDw8P9OrVCz4+Pnjw4AH++OOPitwNQgghhBCxUfuHEEIIIeKgjqZyGDZsGN6+fYtly5YhKSkJLVq0wKVLl7gBLxMTE4Uup7e3t8fhw4exdOlSLF68GI0bN8apU6fQrFmzitoFIXw+H25ubiIvVa/MqmpuoOpmp9zyRbnlr6pmp9zyVVVzf6uKaP9U1WNNueWvqman3PJFueWvqman3N+Gx6rTs3kJIYQQQgghhBBCiMzQGE2EEEIIIYQQQgghRCqoo4kQQgghhBBCCCGESAV1NBFCCCGEEEIIIYQQqaCOJkIIIYQQQgghhBAiFdTRVE1s374dxsbGEAgEaNu2LYKCgsosf/z4cVhYWEAgEMDKygoXLlyQU1JhkuSOiIjAoEGDYGxsDB6PB09PT/kFFUGS7H/++Sc6dOiAmjVrombNmnBycvrq/5GsSJLb19cXrVu3Ro0aNaCuro4WLVrgwIEDckz7H0nf40V8fHzA4/HQv39/2QYshSS59+3bBx6PJ/QSCARyTPsfSY/3p0+fMGXKFOjr64PP58PMzKxK1CudOnUqccx5PB569eolx8SFJD3mnp6eMDc3h6qqKgwNDTFr1ixkZWXJKe1/JMmdm5uLlStXwtTUFAKBANbW1rh06ZIc0xa6efMm+vTpAwMDA/B4PJw6deqry/j7+8PGxgZ8Ph+NGjXCvn37ZJ7ze0FtFPmi9on8URtFvqpqG4XaJ/JHbRQZYuS75+Pjw1RUVNjevXtZREQEmzhxIqtRowZLTk4WWT4gIIApKiqyDRs2sMePH7OlS5cyZWVlFh4eXqlzBwUFsblz57IjR44wPT09tmnTJrnmLU7S7CNHjmTbt29nDx8+ZJGRkWzs2LFMW1ubvXjxolLn9vPzY76+vuzx48fs6dOnzNPTkykqKrJLly5V6txF4uLiWL169ViHDh1Yv3795BO2GElze3t7My0tLfb69WvulZSUJOfUkufOzs5mrVu3Zj179mS3b99mcXFxzN/fn4WGhso5ueTZ379/L3S8Hz16xBQVFZm3t3elzn3o0CHG5/PZoUOHWFxcHLt8+TLT19dns2bNqtS558+fzwwMDNj58+dZbGws27FjBxMIBCwkJESuuS9cuMCWLFnCfH19GQD2999/l1n+2bNnTE1Njc2ePZs9fvyYbd26tULqwqqI2ijyRe0T+f9NUhtFvqpqG4XaJ/JtnzBGbRRZ14fU0VQN2NrasilTpnC/5+fnMwMDA7Zu3TqR5YcOHcp69eolNK1t27Zs8uTJMs35JUlzF2dkZFShHU3fkp0xxvLy8pimpib766+/ZBVRpG/NzRhjLVu2ZEuXLpVFvFKVJ3deXh6zt7dnu3fvZq6urhXSiJM0t7e3N9PW1pZTutJJmtvLy4s1bNiQ5eTkyCtiqb71Pb5p0yamqanJ0tLSZBVRJElzT5kyhXXp0kVo2uzZs5mDg4NMc35J0tz6+vps27ZtQtMGDhzIRo0aJdOcZRGnETd//nzWtGlToWnDhg1jzs7OMkz2faA2inxR+0S+7RPGqI0ib1W1jULtE/m2TxijNoqs2yh069x3LicnB8HBwXBycuKmKSgowMnJCXfu3BG5zJ07d4TKA4Czs3Op5WWhPLkrC2lkz8jIQG5uLmrVqiWrmCV8a27GGK5fv47o6Gh07NhRllGFlDf3ypUrUbduXYwfP14eMUsob+60tDQYGRnB0NAQ/fr1Q0REhDzicsqT+8yZM7Czs8OUKVOgq6uLZs2aYe3atcjPz5dXbADS+dvcs2cPhg8fDnV1dVnFLKE8ue3t7REcHMxdAv7s2TNcuHABPXv2lEtmoHy5s7OzS9xqoaqqitu3b8s067eqDJ+bVRG1UeSL2ifybZ8A1EahNop4qH0i3/YJQG0UeXxuUkfTd+7du3fIz8+Hrq6u0HRdXV0kJSWJXCYpKUmi8rJQntyVhTSyL1iwAAYGBiUqBVkqb+6UlBRoaGhARUUFvXr1wtatW9GtWzdZx+WUJ/ft27exZ88e/Pnnn/KIKFJ5cpubm2Pv3r04ffo0Dh48iIKCAtjb2+PFixfyiAygfLmfPXuGEydOID8/HxcuXMCvv/4KDw8PrF69Wh6ROd/6txkUFIRHjx5hwoQJsoooUnlyjxw5EitXrkT79u2hrKwMU1NTdOrUCYsXL5ZHZADly+3s7IyNGzciJiYGBQUFuHr1Knx9ffH69Wt5RC630j43U1NTkZmZWUGpKj9qo8gXtU/k2z4BqI1CbRTxUPtEvu0TgNoo8mijUEcTIZXM+vXr4ePjg7///rvCBlGUhKamJkJDQ3H//n2sWbMGs2fPhr+/f0XHKtXnz58xevRo/Pnnn6hTp05Fx5GInZ0dxowZgxYtWsDR0RG+vr7Q0dHBrl27KjpamQoKClC3bl388ccfaNWqFYYNG4YlS5Zg586dFR1NInv27IGVlRVsbW0rOspX+fv7Y+3atdixYwdCQkLg6+uL8+fPY9WqVRUdrUybN29G48aNYWFhARUVFUydOhXjxo2DggI1VwipaNQ+kT1qo8jf99BGofaJfFAbRTJKFR2AyFadOnWgqKiI5ORkoenJycnQ09MTuYyenp5E5WWhPLkri2/J7u7ujvXr1+PatWto3ry5LGOWUN7cCgoKaNSoEQCgRYsWiIyMxLp169CpUydZxuVImjs2Nhbx8fHo06cPN62goAAAoKSkhOjoaJiamso2NKTzHldWVkbLli3x9OlTWUQUqTy59fX1oaysDEVFRW6apaUlkpKSkJOTAxUVFZlmLvItxzw9PR0+Pj5YuXKlLCOKVJ7cv/76K0aPHs19u2llZYX09HRMmjQJS5YskUujqDy5dXR0cOrUKWRlZeH9+/cwMDDAwoUL0bBhQ5nn/RalfW5qaWlBVVW1glJVftRGkS9qn8i3fQJQG4XaKOKh9ol82ycAtVHk0Uah7rfvnIqKClq1aoXr169z0woKCnD9+nXY2dmJXMbOzk6oPABcvXq11PKyUJ7clUV5s2/YsAGrVq3CpUuX0Lp1a3lEFSKtY15QUIDs7GxZRBRJ0twWFhYIDw9HaGgo9+rbty86d+6M0NBQGBoaVsrcouTn5yM8PBz6+vqyillCeXI7ODjg6dOnXGMZAJ48eQJ9fX25dTIB33bMjx8/juzsbPzwww+yjllCeXJnZGSUaKwVNaIZY7ILW8y3HG+BQIB69eohLy8PJ0+eRL9+/WQd95tUhs/NqojaKPJF7RP5tk8AaqNQG0U81D6Rb/sEoDaKXD43ZTrUOKkUfHx8GJ/PZ/v27WOPHz9mkyZNYjVq1OAeOTp69Gi2cOFCrnxAQABTUlJi7u7uLDIykrm5uVXYo4MlyZ2dnc0ePnzIHj58yPT19dncuXPZw4cPWUxMjFxzlyf7+vXrmYqKCjtx4oTQo0o/f/5cqXOvXbuWXblyhcXGxrLHjx8zd3d3pqSkxP78889KnftLFfVEF0lzr1ixgl2+fJnFxsay4OBgNnz4cCYQCFhERESlzp2YmMg0NTXZ1KlTWXR0NDt37hyrW7cuW716tVxzlyd7kfbt27Nhw4bJOy5H0txubm5MU1OTHTlyhD179oxduXKFmZqasqFDh1bq3Hfv3mUnT55ksbGx7ObNm6xLly7MxMSEffz4Ua65P3/+zH2eAGAbN25kDx8+ZAkJCYwxxhYuXMhGjx7NlS96dPC8efNYZGQk2759e4U9Sr2qoTaKfNso1D6Rb/ukPNm/RG0U2eauLG0Uap/It31SnuzURpEMdTRVE1u3bmUNGjRgKioqzNbWlt29e5eb5+joyFxdXYXKHzt2jJmZmTEVFRXWtGlTdv78eTknLiRJ7ri4OAagxMvR0VH+wZlk2Y2MjERmd3Nzq9S5lyxZwho1asQEAgGrWbMms7OzYz4+PnLPzJjk7/HiKqoRx5hkuWfOnMmV1dXVZT179mQhISEVkFry4x0YGMjatm3L+Hw+a9iwIVuzZg3Ly8uTc+pCkmaPiopiANiVK1fknFSYJLlzc3PZ8uXLmampKRMIBMzQ0JD98ssvcm8MSZrb39+fWVpaMj6fz2rXrs1Gjx7NXr58KffMfn5+Iuvkoqyurq4lPlv8/PxYixYtmIqKCmvYsCHz9vaWe+6qitoolTc3tU+kg9oo8lVV2yjUPpE/aqPIDo8xOV6jRgghhBBCCCGEEEK+WzRGEyGEEEIIIYQQQgiRCupoIoQQQgghhBBCCCFSQR1NhBBCCCGEEEIIIUQqqKOJEEIIIYQQQgghhEgFdTQRQgghhBBCCCGEEKmgjiZCCCGEEEIIIYQQIhXU0UQIIYQQQgghhBBCpII6mgghhBBCCCGEEEKIVFBHEyGEEEIIIYQQQgiRCupoIoQQQgghhBBCCCFSQR1NhBBCCCGEEEIIIUQqqKOJEEIIIYQQQgghhEgFdTQRQgghhBBCCCGEEKmgjiZCCCGEEEIIIYQQIhXU0UQIIYQQQgghhBBCpII6mgghhBBCCCGEEEKIVFBHEyGEEEIIIYQQQgiRCupoIoQQQgghhBBCCCFSQR1NhBBCCCGEEEIIIUQqqKOJEEIIIYQQQgghhEgFdTQRQgghhBBCCCGEEKmgjiZCCCGEEEIIIYQQIhXU0UQIIYQQQgghhBBCpII6mgghMtepUyfweLyKjlEpGBsbw9jYWKJl6PgRQgghhPxHVHtq37594PF42LdvX4VkIoT8hzqaCCGc+Ph48Hi8Ml+fPn2q6JjlZmxsLLQvioqKqFOnDrp3747Tp09XWK7ly5eDx+PB39+/wjKIqyhr8ZeamhqaNWuGJUuWIDU19Zu3MXbsWPB4PMTHx397YEIIIYSIJKrdp6ysjHr16mHo0KF48OBBRUckhFRRShUdgBBS+ZiamuKHH34QOU8gEMg5jXQpKipi6dKlAICcnBxERUXhzJkzuHr1Ktzd3TFnzhyZbv/69esSL7N//35kZGTIIE35DRo0CM2aNQMAJCcn48KFC1i7di3OnTuHoKAg8Pn8Ck5ICCGEEHEUb/elp6cjODgYx48fx6lTp3Dt2jV07NixghMSQqoa6mgihJTQqFEjLF++vKJjyISSklKJfbty5QpcXFywbNky/Pzzz1BTU5PZ9k1NTSVepkGDBjJI8m0GDx6M4cOHc79nZWWhXbt2CAsLw+HDhzFu3LgKTEcIIYQQcYlq961fvx6LFi3Cr7/+ihs3blRMMEJIlUW3zhFCJBYcHIypU6eiWbNm0NbWhqqqKqysrLB+/Xrk5uaKtY6CggLs3r0btra2qFWrFlRVVVG/fn306dNH5C1kN2/eRJ8+fVCnTh3w+Xw0btwYS5culcqVPt27d4e5uTkyMjIQERHBTT979iw6d+7M7aO1tTU2btyIvLy8Euvw8/NDjx49YGBgAD6fD11dXXTo0AF//PGHULkvxxTo1KkTVqxYAQDo3Lkzd+n6l2WKj9F04MAB8Hg8rFy5UuT+hISEgMfjYdSoUULT37x5g1mzZqFRo0bg8/moU6cOBg0ahEePHol9rEojEAi47QUHBwvNe/XqFdzc3NCuXTvUrVsXfD4fxsbG+OWXX/DmzRuhssbGxvjrr78AACYmJtzx6NSpk1C5uLg4TJgwAQ0aNACfz4e+vj7Gjh2LhISEb94XQgghpLobP348gJKf6Tk5Odi4cSNsbGygrq4OTU1NdOjQAWfOnBG5npycHGzatAlt2rSBpqYmNDQ00KRJE8yePRsfP37kyvn5+eHHH3+Eubk5NDQ0oKGhgdatW5doRxFCqga6ookQIrE///wTZ8+eRceOHdGzZ09kZGTA398fixYtwv3793Hy5MmvrmPRokXYsGEDTE1NMXLkSGhqauLly5e4ffs2rl27JtSx4OXlhSlTpqBGjRro06cP6tatiwcPHmDNmjXw8/ODn58fVFRUpLJvRR06GzduxJw5c1CrVi2MHDkS6urqOHPmDObMmYNbt27B19eXK3v+/Hn06dMHNWrUQL9+/aCvr4+3b98iLCwMBw4cwKRJk0rd3tixYwEAN27cgKurK9fBVKNGjVKXGThwIH7++WccOnQIy5YtKzH/wIEDAIDRo0dz02JjY9GpUye8ePEC3bt3R//+/fHmzRucPHkSly9fxvXr19G2bVtJDlWplJSEP1pu3rwJDw8PdO3aFW3btoWysjIePnwILy8vXL58GSEhIdDW1gYAzJw5E/v27UNYWBhmzJjBHYfiHW/37t2Ds7Mz0tPT0bt3bzRu3Bjx8fE4dOgQLl68iDt37qBhw4ZS2RdCCCGkOiv+mZ6dnQ0XFxf4+/ujRYsWGD9+PHJzc3H+/Hn069cPW7duxdSpU7nymZmZ6NatGwICAtC4cWOMGzcOfD4fMTEx2LVrF8aMGYOaNWsCAH777Tc8ffoU7dq1w4ABA/Dp0ydcunQJkydPRnR0NDw8POS+74SQb8AIIeT/4uLiGABmamrK3NzcSrzu3LnDGGMsISGB5eXlCS1bUFDAfvzxRwaA3b59W2ieo6Mj+7K6qVWrFjMwMGDp6eklcrx//577d0REBFNSUmLW1tbs3bt3QuXWrVvHADB3d3ex9s/IyIjx+fwS069du8Z4PB5TV1dnGRkZ7OnTp0xJSYnVrVuXJSYmcuWysrJY+/btGQC2f/9+bvrAgQMZABYaGlpi3V9mNjIyYkZGRkLT3NzcGADm5+cnMreo4/fDDz8wAOzevXtC0/Py8piuri7T09MT+j+yt7dnioqK7NKlS0Llo6OjmaamJrOyshK57S8VZT1y5IjQ9MzMTGZtbc0AsOPHjwvNS05OZp8/fy6xrr/++osBYKtXrxaa7urqygCwuLi4Esvk5OQwY2NjpqmpyUJCQoTm3bp1iykqKrLevXuLtS+EEEJIdVbU7nN2di4xb+3atQwA69WrFzdt8eLFDAD79ddfWUFBATc9NTWVtW7dmqmoqLCXL19y0+fMmcMAsNGjR5doN3769EmobfDs2bMSGXJzc1m3bt2YoqIiS0hIEJonqj3l7e3NADBvb2+x9p8QIjt06xwhpITY2FisWLGixOvu3bsACscMUlRUFFqGx+NhypQpAIBr166JtR0VFZUS6wGAWrVqcf/etWsX8vLysHXrVtSuXVuo3Pz586Gjo4MjR46IvW95eXlYvnw5li9fjiVLlmDw4MFwcXEBYwyrVq2CqqoqDh8+jLy8PMyZMweGhobcsnw+H7/99hsAiHx0rqqqaolpX2aWlqKrlQ4ePCg0/cqVK0hOTsbw4cO5Y/vw4UMEBgbC1dUVzs7OQuXNzMwwceJEhIeHS3QL3YkTJ7jj+Msvv8Dc3BxhYWEYMGAABg4cKFS2bt260NDQELkPWlpaYr9fAODcuXOIj4/HvHnz0LJlS6F57du3R79+/XDhwgWpPP2OEEIIqQ6ePn3KfabPmzcPXbp0weLFi6Grq4vff/8dQOGQB15eXjA1NcWKFSuEbunX1NTEsmXLkJOTA19fXwCF7a0//vgD2tra2Lx5c4n2nra2tlDbwMTEpEQuJSUl/PTTT8jPz4efn58sdp0QIiN06xwhpARnZ2dcunSp1Pk5OTnYtm0bfHx8EBUVhbS0NDDGuPmvXr366jaGDx+OHTt2oFmzZhg+fDg6d+4MOzu7Ep01RZ1bRbd3fUlZWRlRUVHi7hry8/O5MZEUFBRQs2ZNdOnSBVOmTEHfvn0BFHbMACgxLhAA2NnZQSAQIDQ0VGhffH190a5dO4wcORJdu3ZFhw4dUKdOHbFzSapr167Q19eHj48PNm7cyF3aXtTxVPy2uaJjmJycLHKQ96LjFxUVxT1J7mtOnjxZ4hbJIUOG4OjRo0KNzyK+vr7YtWsXQkJC8PHjR+Tn53PzxHm/FCnal+joaJH7kpSUhIKCAjx58gStW7cWe72EEEJIdVX0BWNxenp6uHXrFho1agSg8HP348ePMDAwKFEWAN6+fQtAuE3x+fNnODk5cbfHleXz589wd3fHqVOnEBsbi/T0dKH5krQVCCEVjzqaCCESGzx4MM6ePQszMzMMGzYMdevWhbKyMj59+oTNmzcjOzv7q+vYvHkzTExM4O3tjdWrV2P16tUQCAQYOnQoPDw8uE6aDx8+AADWrFkjlex8Ph9ZWVlllim6GkZXV7fEPB6PB11dXbx8+ZKbNmTIEJw6dQobN27Ezp07sX37dvB4PHTu3BkeHh5o0aKFVLIXp6ioiJEjR8LDwwOXL19Gr169kJaWhlOnTqFJkyawsbHhyhYdw/Pnz+P8+fOlrvPLRl1Zjhw5guHDhyMvLw/R0dGYO3cujh8/DnNzc6xatUqorIeHB+bOnQsdHR10794d9evX5zoUPT09xXq/fLkvhw4dKrOcJPtCCCGEVGfFv2B8+/Yt/vrrLyxYsAB9+/ZFUFAQNDQ0uM/fiIgIoQenfKno8zclJQUAUK9eva9uPycnB506dUJISAhatmyJ0aNHo3bt2lBSUkJ8fDz++usvidoKhJCKRx1NhBCJ3L9/H2fPnoWzszPOnz8vdCn03bt3sXnzZrHWo6SkhLlz52Lu3Ll49eoVbty4AW9vb+zfvx9JSUm4fPkyAEBLSwtAYeePpqam9HdIhKJtJicnw8jISGgeYwzJyclcmSL9+vVDv3798PnzZwQEBMDX1xd79uyBi4sLoqKiyhzcu7xGjx4NDw8PHDx4EL169cLJkyeRkZEhdDVT8f35cpBOaVBSUkLTpk3x999/w8rKCmvWrMGAAQO4jq68vDysWrUK+vr6CA0NRd26dbllGWPYsGGDRNsr2pezZ8+id+/e0tsRQgghhEBHRwdz585FSkoKVq9ejaVLl8LT05P7/B00aBBOnDjx1fUUtXuKfzFXmtOnTyMkJATjx4/H7t27heb5+PhwT6MlhFQdNEYTIUQisbGxAIBevXqVuN/+1q1b5VqngYEBRowYgUuXLqFRo0a4du0aMjMzAYB7ElrRLVPyUDT2j7+/f4l59+7dQ1ZWVqlXKWlqasLFxQV//PEHxo4di+TkZNy7d6/M7RUdx+K3k4nD2toaVlZWOH36ND5//oyDBw+Cx+Nh1KhRQuWKjuGdO3ckWr8kBAIB3N3dwRjDwoULuenv3r1DSkoK7OzshDqZAODBgwfc/3NxZR0PeewLIYQQUt0tXrwYBgYG2LFjB+Lj42FpaQktLS08ePAAubm5X13e3NwcWlpauH//Pj5+/Fhm2aK2Zb9+/UrMK2/bkhBSsaijiRAikaIrfG7fvi00PSIiAuvWrRNrHdnZ2QgMDCwxPT09HWlpaVBWVoaCQmH19Msvv0BJSQnTpk1DYmJiiWU+ffrEjakkLSNHjoSSkhI2btwoNCZATk4OFixYAAAYO3YsN/3mzZsiO0XevHkDoLATpixFg58/f/5c4qyjR49GZmYmtmzZgn/++QeOjo5CA5gDgK2tLdq2bYsjR47g6NGjJdZRUFCAGzduSLztL/Xr1w82Nja4evUq1zCsW7cuVFVVERISgoyMDK7sx48fMW3aNJHrKet49OvXDw0aNMDGjRtx8+bNEvNzc3NLvDcJIYQQIhlVVVUsWLAAubm5WLVqFZSUlPDzzz8jISEBc+fOFdnZ9OjRI67to6SkhMmTJyMlJQUzZswo0U5KSUlBWloagNLbljdu3MCff/4pi90jhMgY3TpHCJGIra0tbG1tcezYMbx+/Rrt2rVDYmIizpw5g169eol1OXVmZiYcHBxgZmaGVq1aoUGDBkhLS8O5c+eQlJSEuXPngs/nAwCaNWuGHTt24Oeff4a5uTl69uwJU1NTfP78Gc+ePcONGzcwduxY7Ny5U2r7aGpqit9++w1z5sxB8+bNMXToUKirq+Ps2bOIjo5Gv3798MMPP3Dlp0+fjlevXqF9+/YwNjYGj8fD7du3ERQUhHbt2qF9+/Zlbq9z587g8XhYvHgxIiIioK2tjRo1aoh1m9vIkSOxcOFCrFixAgUFBSVumyty5MgRdO7cGcOHD4enpydsbGygqqqKxMRE3LlzB2/fvv3q2FXiWL58Ofr27Ytly5bBz88PCgoK+OWXX+Dh4QFra2v06dMHqampuHjxIoyMjGBgYFBiHV26dIG7uzsmTZqEQYMGQV1dHUZGRhg9ejT4fD5OnDiBHj16wNHREV26dIGVlRV4PB4SEhJw69Yt1K5dW6IB4gkhhBBS0qRJk/Dbb79h//79WLx4MVasWIGQkBBs2bIF58+fR8eOHVG3bl28fPkS4eHhCAsLw507d7grmFeuXIm7d+/iwIEDuHv3Lnr06AE+n49nz57h0qVLuH37Nlq0aIE+ffrA2NgYGzZswKNHj9CsWTNER0fj3LlzGDBggFhtS0JIJcMIIeT/4uLiGADm7OxcZrk3b96wH3/8kRkYGDCBQMCsrKzY9u3b2bNnzxgA5urqKlTe0dGRFa9ucnJy2G+//ca6d+/O6tevz1RUVJiuri7r2LEjO3z4MCsoKCixzaCgIDZ8+HBmYGDAlJWVWZ06dZiNjQ1buHAhi4yMFGv/jIyMGJ/PF6ssY4ydPn2aOTo6Mk1NTcbn85mVlRXz8PBgubm5QuV8fHzY0KFDmampKVNTU2Pa2trM2tqa/fbbb+zz588lMhgZGZXY1r59+5iVlRXj8/kMgFCZL4/fl5ycnBgAJhAIWEpKSqnlPnz4wJYuXcqaNWvGVFVVmYaGBmvcuDEbOXIk8/X1FeuYuLm5MQDsyJEjpZZp3bo1A8CuX7/OGCv8/16zZg1r3Lgx4/P5rEGDBmzOnDns8+fPpR6PDRs2sMaNGzNlZWUGgDk6OgrNf/HiBZsxYwa3Ti0tLWZpackmTJjAbZcQQgghpROn3bd161YGgI0ePZoxxlheXh7btWsXc3BwYFpaWtznuouLC/Py8mJpaWlCy2dlZTF3d3fWokULru3RpEkTNmfOHPbx40eu3LNnz9igQYOYjo4OU1NTY23atGE+Pj7Mz8+PAWBubm5C6xXVfvD29mYAmLe397ccFkKIFPAYK/ZMckIIIYQQQgghhBBCyonGaCKEEEIIIYQQQgghUkEdTYQQQgghhBBCCCFEKqijiRBCCCGEEEIIIYRIBXU0EUIIIYQQQgghhBCpoI4mQgghhBBCCCGEECIV1NFECCGEEEIIIYQQQqSCOpoIIYQQQgghhBBCiFRQRxMhhBBCCCGEEEIIkQrqaCKEEEIIIYQQQgghUkEdTYQQQgghhBBCCCFEKqijiRBCCCGEEEIIIYRIBXU0EUIIIYQQQgghhBCpoI4mQgghhBBCCCGEECIV/wOEI/W/peKkxQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1200x1100 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Evaluate classification model with charting, custom threshold, and return metrics\n",
    "class_metrics = dw.eval_model(y_test=y_test, y_pred=y_pred, x_test=X_test, estimator=pipe, model_name='LogReg',\n",
    "                              pos_label=1, class_map=class_map, plot=True, bins=20, threshold=0.35, return_metrics=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'True Positives': 1119,\n",
       " 'False Positives': 1683,\n",
       " 'True Negatives': 7189,\n",
       " 'False Negatives': 58,\n",
       " 'TPR': 0.9507221750212405,\n",
       " 'TNR': 0.8103020739404869,\n",
       " 'FPR': 0.18969792605951308,\n",
       " 'FNR': 0.04927782497875956,\n",
       " 'Declined': {'precision': 0.9919966882848075,\n",
       "  'recall': 0.8103020739404869,\n",
       "  'f1-score': 0.8919908182889758,\n",
       "  'support': 8872.0},\n",
       " 'Subscribed': {'precision': 0.3993576017130621,\n",
       "  'recall': 0.9507221750212405,\n",
       "  'f1-score': 0.562452877607439,\n",
       "  'support': 1177.0},\n",
       " 'accuracy': 0.8267489302418151,\n",
       " 'macro avg': {'precision': 0.6956771449989347,\n",
       "  'recall': 0.8805121244808637,\n",
       "  'f1-score': 0.7272218479482073,\n",
       "  'support': 10049.0},\n",
       " 'weighted avg': {'precision': 0.9225831939177117,\n",
       "  'recall': 0.8267489302418151,\n",
       "  'f1-score': 0.8533933303616029,\n",
       "  'support': 10049.0},\n",
       " 'ROC AUC': 0.9387968831519055,\n",
       " 'Threshold': 0.35,\n",
       " 'Class Type': 'binary',\n",
       " 'Class Map': {0: 'Declined', 1: 'Subscribed'},\n",
       " 'Positive Label': 1,\n",
       " 'Title': None,\n",
       " 'Model Name': 'LogReg',\n",
       " 'Class Weight': None,\n",
       " 'Multi-Class': 'ovr',\n",
       " 'Average': 'macro'}"
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the extracted metrics\n",
    "class_metrics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Multi-Class Example\n",
    "\n",
    "Let's take a look at a mult-class classification dataset, where there are more than 2 classes. In this case, we won't see all the charts you get with binary classification. But we will see the classification report, and confusion matrix. And we'll see an ROC AUC score if the X_test and estimator are provided."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load Iris dataset for multi-class example\n",
    "X2, y2 = load_iris(return_X_y=True)\n",
    "X2 = pd.DataFrame(X2, columns=['sepal_length', 'sepal_width', 'petal_length', 'petal_width'])\n",
    "y2 = pd.Series(y2)\n",
    "X2_train, X2_test, y2_train, y2_test = train_test_split(X2, y2, test_size=0.2, random_state=42)\n",
    "class_map2 = {0: 'Setosa', 1: 'Versicolor', 2: 'Virginica'}\n",
    "model2 = SVC(kernel='linear', probability=True, random_state=42)\n",
    "model2.fit(X2_train, y2_train)\n",
    "SVC(kernel='linear', probability=True, random_state=42)\n",
    "y2_pred = model2.predict(X2_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Multi-Class Classification Report\n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "      Setosa       1.00      1.00      1.00        10\n",
      "  Versicolor       1.00      1.00      1.00         9\n",
      "   Virginica       1.00      1.00      1.00        11\n",
      "\n",
      "    accuracy                           1.00        30\n",
      "   macro avg       1.00      1.00      1.00        30\n",
      "weighted avg       1.00      1.00      1.00        30\n",
      "\n",
      "ROC AUC: 1.0\n",
      "\n",
      "Predicted   Setosa  Versicolor  Virginica\n",
      "Actual                                   \n",
      "Setosa          10           0          0\n",
      "Versicolor       0           9          0\n",
      "Virginica        0           0         11\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 510x510 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Evaluate a multi-class model, plot the charts, and return the metrics\n",
    "multi_metrics = dw.eval_model(y_test=y2_test, y_pred=y2_pred, x_test=X2_test, estimator=model2,\n",
    "                              class_map=class_map2, return_metrics=True, plot=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Setosa': {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 10.0},\n",
       " 'Versicolor': {'precision': 1.0,\n",
       "  'recall': 1.0,\n",
       "  'f1-score': 1.0,\n",
       "  'support': 9.0},\n",
       " 'Virginica': {'precision': 1.0,\n",
       "  'recall': 1.0,\n",
       "  'f1-score': 1.0,\n",
       "  'support': 11.0},\n",
       " 'accuracy': 1.0,\n",
       " 'macro avg': {'precision': 1.0,\n",
       "  'recall': 1.0,\n",
       "  'f1-score': 1.0,\n",
       "  'support': 30.0},\n",
       " 'weighted avg': {'precision': 1.0,\n",
       "  'recall': 1.0,\n",
       "  'f1-score': 1.0,\n",
       "  'support': 30.0},\n",
       " 'ROC AUC': 1.0,\n",
       " 'Threshold': 0.5,\n",
       " 'Class Type': 'multi',\n",
       " 'Class Map': {0: 'Setosa', 1: 'Versicolor', 2: 'Virginica'},\n",
       " 'Positive Label': None,\n",
       " 'Title': None,\n",
       " 'Model Name': 'Model',\n",
       " 'Class Weight': None,\n",
       " 'Multi-Class': 'ovr',\n",
       " 'Average': 'macro'}"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the extracted metrics\n",
    "multi_metrics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Compare Models\n",
    "\n",
    "`dw.compare models()` finds the best classification model and hyper-parameters for a dataset by\n",
    "automating the workflow for multiple models and comparing results.\n",
    "\n",
    "This function integrates a number of steps in a typical classification model\n",
    "workflow, and it does this for multiple models, all with one command line:\n",
    "\n",
    "1. Auto-detecting single vs. multi-class classification problems\n",
    "2. Option to Under-sample or Over-smple imbalanced data,\n",
    "3. Option to use a sub-sample of data for SVC or KNN, which can be computation intense\n",
    "4. Ability to split the Train/Test data at a specified ratio,\n",
    "5. Creation of a multiple-step Pipeline, including Imputation, multiple Column Transformer/Encoding steps,\n",
    "Scaling, Feature selection, and the Model,\n",
    "6. Grid Search of hyper-parameters, either full or random,\n",
    "7. Calculating performance metrics from the standard Classification Report (Accuracy, Precision, Recall, F1) but also with ROC AUC, and if binary, True Positive Rate, True Negative Rate, False Positive Rate, False Negative Rate,\n",
    "8. Evaluating this performance based on a customizable Threshold,\n",
    "9. Visually showing performance by plotting (a) a Confusion Matrix, and if binary, (b) a Histogram of Predicted Probabilities, (c) an ROC Curve, and (d) a Precision-Recall Curve.\n",
    "10. Save all the results in a DataFrame for reference and comparison, and\n",
    "11. Option to plot the results to visually compare performance of the specified metric across multiple model pipelines with their best parameters.\n",
    "\n",
    "To use this function, a configuration should be created that defines the\n",
    "desired model configurations and parameters you want to search.\n",
    "When `compare_models` is run, for each model in the `models` parameter, the\n",
    "`create_pipeline` function will be called to create a pipeline from the\n",
    "specified parameters. Each model iteration will have the same pipeline\n",
    "construction, except for the final model, which will vary. Here are the major\n",
    "pipeline parameters, along with the config sections they map to:\n",
    "\n",
    "* `imputer` (str) is selected from `config['imputers']`\n",
    "* `transformers` (list or str) are selected from `config['transformers']`\n",
    "* `scaler` (str) is selected from `config['scalers']`\n",
    "* `selector` (str) is selected from `config['selectors']`\n",
    "* `models` (list or str) are selected from `config['models']`\n",
    "\n",
    "Here is an example of the configuration dictionary structure. It is based on\n",
    "what `create_pipeline` requires to assemble the pipeline. But it adds some\n",
    "additional configuration parameters referenced by `compare_models`, which\n",
    "are `params` (grid search parameters, required) and `cv` (cross-validation\n",
    "parameters, optional if `grid_cv` is an integer). The configuration dictionary\n",
    "is passed to `compare_models` as the `config` parameter:\n",
    "\n",
    "    >>> config = {  # doctest: +SKIP\n",
    "    ...     'imputers': {\n",
    "    ...         'knn_imputer': KNNImputer().set_output(transform='pandas'),\n",
    "    ...         'simple_imputer': SimpleImputer()\n",
    "    ...     },\n",
    "    ...     'transformers': {\n",
    "    ...         'ohe': (OneHotEncoder(drop='if_binary', handle_unknown='ignore'),\n",
    "    ...                 cat_columns),\n",
    "    ...         'ord': (OrdinalEncoder(), cat_columns),\n",
    "    ...         'poly2': (PolynomialFeatures(degree=2, include_bias=False),\n",
    "    ...                   num_columns),\n",
    "    ...         'log': (FunctionTransformer(np.log1p, validate=True),\n",
    "    ...                 num_columns)\n",
    "    ...     },\n",
    "    ...     'scalers': {\n",
    "    ...         'stand': StandardScaler(),\n",
    "    ...         'minmax': MinMaxScaler()\n",
    "    ...     },\n",
    "    ...     'selectors': {\n",
    "    ...         'rfe_logreg': RFE(LogisticRegression(max_iter=max_iter,\n",
    "    ...                                         random_state=random_state,\n",
    "    ...                                         class_weight=class_weight)),\n",
    "    ...         'sfs_linreg': SequentialFeatureSelector(LinearRegression())\n",
    "    ...     },\n",
    "    ...     'models': {\n",
    "    ...         'linreg': LinearRegression(),\n",
    "    ...         'logreg': LogisticRegression(max_iter=max_iter,\n",
    "    ...                                      random_state=random_state,\n",
    "    ...                                      class_weight=class_weight),\n",
    "    ...         'tree_class': DecisionTreeClassifier(random_state=random_state),\n",
    "    ...         'tree_reg': DecisionTreeRegressor(random_state=random_state)\n",
    "    ...     },\n",
    "    ...     'no_scale': ['tree_class', 'tree_reg'],\n",
    "    ...     'no_poly': ['tree_class', 'tree_reg'],\n",
    "    ...     'params': {\n",
    "    ...         'sfs': {\n",
    "    ...             'Selector: sfs__n_features_to_select': np.arange(3, 13, 1),\n",
    "    ...         },\n",
    "    ...         'linreg': {\n",
    "    ...             'Model: linreg__fit_intercept': [True],\n",
    "    ...         },\n",
    "    ...         'ridge': {\n",
    "    ...             'Model: ridge__alpha': np.array([0.01, 0.1, 1, 10, 100, 1000]),\n",
    "    ...         }\n",
    "    ...     },\n",
    "    ...     'cv': {\n",
    "    ...         'kfold_5': KFold(n_splits=5, shuffle=True, random_state=42),\n",
    "    ...         'skf_5': StratifiedKFold(n_splits=5, shuffle=True, random_state=42),\n",
    "    ...     }\n",
    "    ... }\n",
    "\n",
    "In addition to the configuration file, you will need to define any column\n",
    "lists if you want to target certain transformations to a subset of columns.\n",
    "For example, you might define a 'ohe' transformer for One-Hot Encoding, and\n",
    "reference 'ohe_columns' or 'cat_columns' in its definition in the config.\n",
    "\n",
    "Here is an example of how to call this function in an organized manner:\n",
    "\n",
    "    >>> results_df = dw.compare_models(  # doctest: +SKIP\n",
    "    ...\n",
    "    ...     # Data split and sampling\n",
    "    ...     x=X, y=y, test_size=0.25, stratify=None, under_sample=None,\n",
    "    ...     over_sample=None, svm_knn_resample=None,\n",
    "    ...\n",
    "    ...     # Models and pipeline steps\n",
    "    ...     imputer=None, transformers=None, scaler='stand', selector=None,\n",
    "    ...     models=['logreg', 'knn_class', 'svm_proba', 'tree_class',\n",
    "    ...     'forest_class', 'xgb_class', 'keras_class'], svm_proba=True,\n",
    "    ...\n",
    "    ...     # Grid search\n",
    "    ...     search_type='random', scorer='accuracy', grid_cv='kfold_5', verbose=4,\n",
    "    ...\n",
    "    ...     # Model evaluation and charts\n",
    "    ...     model_eval=True, plot_perf=True, plot_curve=True, fig_size=(12,6),\n",
    "    ...     legend_loc='lower left', rotation=45, threshold=0.5,\n",
    "    ...     class_map=class_map, pos_label=1, title='Breast Cancer',\n",
    "    ...\n",
    "    ...     # Config, preferences and notes\n",
    "    ...     config=my_config, class_weight=None, random_state=42, decimal=4,\n",
    "    ...     n_jobs=None, debug=False, notes='Test Size=0.25, Threshold=0.50'\n",
    "    ... )\n",
    "\n",
    "Use this function when you want to find the best classification model and\n",
    "hyper-parameters for a dataset, after doing any required pre-processing or\n",
    "cleaning. It is a significant time saver, replacing numerous manual coding\n",
    "steps with one command."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Load and Prepare Data\n",
    "\n",
    "Let's load a simple binary classification dataset to illustrate how easy it is to compare multiple classification models using this function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load breast cancer data\n",
    "cancer_df = pd.read_csv('data/breast_cancer.csv', index_col=0).drop(columns='Unnamed: 32')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>diagnosis</th>\n",
       "      <th>radius_mean</th>\n",
       "      <th>texture_mean</th>\n",
       "      <th>perimeter_mean</th>\n",
       "      <th>area_mean</th>\n",
       "      <th>smoothness_mean</th>\n",
       "      <th>compactness_mean</th>\n",
       "      <th>concavity_mean</th>\n",
       "      <th>concave points_mean</th>\n",
       "      <th>symmetry_mean</th>\n",
       "      <th>fractal_dimension_mean</th>\n",
       "      <th>radius_se</th>\n",
       "      <th>texture_se</th>\n",
       "      <th>perimeter_se</th>\n",
       "      <th>area_se</th>\n",
       "      <th>smoothness_se</th>\n",
       "      <th>compactness_se</th>\n",
       "      <th>concavity_se</th>\n",
       "      <th>concave points_se</th>\n",
       "      <th>symmetry_se</th>\n",
       "      <th>fractal_dimension_se</th>\n",
       "      <th>radius_worst</th>\n",
       "      <th>texture_worst</th>\n",
       "      <th>perimeter_worst</th>\n",
       "      <th>area_worst</th>\n",
       "      <th>smoothness_worst</th>\n",
       "      <th>compactness_worst</th>\n",
       "      <th>concavity_worst</th>\n",
       "      <th>concave points_worst</th>\n",
       "      <th>symmetry_worst</th>\n",
       "      <th>fractal_dimension_worst</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>842302</th>\n",
       "      <td>M</td>\n",
       "      <td>17.99</td>\n",
       "      <td>10.38</td>\n",
       "      <td>122.80</td>\n",
       "      <td>1001.0</td>\n",
       "      <td>0.11840</td>\n",
       "      <td>0.27760</td>\n",
       "      <td>0.3001</td>\n",
       "      <td>0.14710</td>\n",
       "      <td>0.2419</td>\n",
       "      <td>0.07871</td>\n",
       "      <td>1.0950</td>\n",
       "      <td>0.9053</td>\n",
       "      <td>8.589</td>\n",
       "      <td>153.40</td>\n",
       "      <td>0.006399</td>\n",
       "      <td>0.04904</td>\n",
       "      <td>0.05373</td>\n",
       "      <td>0.01587</td>\n",
       "      <td>0.03003</td>\n",
       "      <td>0.006193</td>\n",
       "      <td>25.38</td>\n",
       "      <td>17.33</td>\n",
       "      <td>184.60</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>0.1622</td>\n",
       "      <td>0.6656</td>\n",
       "      <td>0.7119</td>\n",
       "      <td>0.2654</td>\n",
       "      <td>0.4601</td>\n",
       "      <td>0.11890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>842517</th>\n",
       "      <td>M</td>\n",
       "      <td>20.57</td>\n",
       "      <td>17.77</td>\n",
       "      <td>132.90</td>\n",
       "      <td>1326.0</td>\n",
       "      <td>0.08474</td>\n",
       "      <td>0.07864</td>\n",
       "      <td>0.0869</td>\n",
       "      <td>0.07017</td>\n",
       "      <td>0.1812</td>\n",
       "      <td>0.05667</td>\n",
       "      <td>0.5435</td>\n",
       "      <td>0.7339</td>\n",
       "      <td>3.398</td>\n",
       "      <td>74.08</td>\n",
       "      <td>0.005225</td>\n",
       "      <td>0.01308</td>\n",
       "      <td>0.01860</td>\n",
       "      <td>0.01340</td>\n",
       "      <td>0.01389</td>\n",
       "      <td>0.003532</td>\n",
       "      <td>24.99</td>\n",
       "      <td>23.41</td>\n",
       "      <td>158.80</td>\n",
       "      <td>1956.0</td>\n",
       "      <td>0.1238</td>\n",
       "      <td>0.1866</td>\n",
       "      <td>0.2416</td>\n",
       "      <td>0.1860</td>\n",
       "      <td>0.2750</td>\n",
       "      <td>0.08902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84300903</th>\n",
       "      <td>M</td>\n",
       "      <td>19.69</td>\n",
       "      <td>21.25</td>\n",
       "      <td>130.00</td>\n",
       "      <td>1203.0</td>\n",
       "      <td>0.10960</td>\n",
       "      <td>0.15990</td>\n",
       "      <td>0.1974</td>\n",
       "      <td>0.12790</td>\n",
       "      <td>0.2069</td>\n",
       "      <td>0.05999</td>\n",
       "      <td>0.7456</td>\n",
       "      <td>0.7869</td>\n",
       "      <td>4.585</td>\n",
       "      <td>94.03</td>\n",
       "      <td>0.006150</td>\n",
       "      <td>0.04006</td>\n",
       "      <td>0.03832</td>\n",
       "      <td>0.02058</td>\n",
       "      <td>0.02250</td>\n",
       "      <td>0.004571</td>\n",
       "      <td>23.57</td>\n",
       "      <td>25.53</td>\n",
       "      <td>152.50</td>\n",
       "      <td>1709.0</td>\n",
       "      <td>0.1444</td>\n",
       "      <td>0.4245</td>\n",
       "      <td>0.4504</td>\n",
       "      <td>0.2430</td>\n",
       "      <td>0.3613</td>\n",
       "      <td>0.08758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84348301</th>\n",
       "      <td>M</td>\n",
       "      <td>11.42</td>\n",
       "      <td>20.38</td>\n",
       "      <td>77.58</td>\n",
       "      <td>386.1</td>\n",
       "      <td>0.14250</td>\n",
       "      <td>0.28390</td>\n",
       "      <td>0.2414</td>\n",
       "      <td>0.10520</td>\n",
       "      <td>0.2597</td>\n",
       "      <td>0.09744</td>\n",
       "      <td>0.4956</td>\n",
       "      <td>1.1560</td>\n",
       "      <td>3.445</td>\n",
       "      <td>27.23</td>\n",
       "      <td>0.009110</td>\n",
       "      <td>0.07458</td>\n",
       "      <td>0.05661</td>\n",
       "      <td>0.01867</td>\n",
       "      <td>0.05963</td>\n",
       "      <td>0.009208</td>\n",
       "      <td>14.91</td>\n",
       "      <td>26.50</td>\n",
       "      <td>98.87</td>\n",
       "      <td>567.7</td>\n",
       "      <td>0.2098</td>\n",
       "      <td>0.8663</td>\n",
       "      <td>0.6869</td>\n",
       "      <td>0.2575</td>\n",
       "      <td>0.6638</td>\n",
       "      <td>0.17300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84358402</th>\n",
       "      <td>M</td>\n",
       "      <td>20.29</td>\n",
       "      <td>14.34</td>\n",
       "      <td>135.10</td>\n",
       "      <td>1297.0</td>\n",
       "      <td>0.10030</td>\n",
       "      <td>0.13280</td>\n",
       "      <td>0.1980</td>\n",
       "      <td>0.10430</td>\n",
       "      <td>0.1809</td>\n",
       "      <td>0.05883</td>\n",
       "      <td>0.7572</td>\n",
       "      <td>0.7813</td>\n",
       "      <td>5.438</td>\n",
       "      <td>94.44</td>\n",
       "      <td>0.011490</td>\n",
       "      <td>0.02461</td>\n",
       "      <td>0.05688</td>\n",
       "      <td>0.01885</td>\n",
       "      <td>0.01756</td>\n",
       "      <td>0.005115</td>\n",
       "      <td>22.54</td>\n",
       "      <td>16.67</td>\n",
       "      <td>152.20</td>\n",
       "      <td>1575.0</td>\n",
       "      <td>0.1374</td>\n",
       "      <td>0.2050</td>\n",
       "      <td>0.4000</td>\n",
       "      <td>0.1625</td>\n",
       "      <td>0.2364</td>\n",
       "      <td>0.07678</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         diagnosis  radius_mean  texture_mean  perimeter_mean  area_mean  smoothness_mean  compactness_mean  concavity_mean  concave points_mean  symmetry_mean  fractal_dimension_mean  radius_se  texture_se  perimeter_se  area_se  smoothness_se  compactness_se  concavity_se  concave points_se  symmetry_se  fractal_dimension_se  radius_worst  texture_worst  perimeter_worst  area_worst  smoothness_worst  compactness_worst  concavity_worst  concave points_worst  symmetry_worst  fractal_dimension_worst\n",
       "id                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     \n",
       "842302           M        17.99         10.38          122.80     1001.0          0.11840           0.27760          0.3001              0.14710         0.2419                 0.07871     1.0950      0.9053         8.589   153.40       0.006399         0.04904       0.05373            0.01587      0.03003              0.006193         25.38          17.33           184.60      2019.0            0.1622             0.6656           0.7119                0.2654          0.4601                  0.11890\n",
       "842517           M        20.57         17.77          132.90     1326.0          0.08474           0.07864          0.0869              0.07017         0.1812                 0.05667     0.5435      0.7339         3.398    74.08       0.005225         0.01308       0.01860            0.01340      0.01389              0.003532         24.99          23.41           158.80      1956.0            0.1238             0.1866           0.2416                0.1860          0.2750                  0.08902\n",
       "84300903         M        19.69         21.25          130.00     1203.0          0.10960           0.15990          0.1974              0.12790         0.2069                 0.05999     0.7456      0.7869         4.585    94.03       0.006150         0.04006       0.03832            0.02058      0.02250              0.004571         23.57          25.53           152.50      1709.0            0.1444             0.4245           0.4504                0.2430          0.3613                  0.08758\n",
       "84348301         M        11.42         20.38           77.58      386.1          0.14250           0.28390          0.2414              0.10520         0.2597                 0.09744     0.4956      1.1560         3.445    27.23       0.009110         0.07458       0.05661            0.01867      0.05963              0.009208         14.91          26.50            98.87       567.7            0.2098             0.8663           0.6869                0.2575          0.6638                  0.17300\n",
       "84358402         M        20.29         14.34          135.10     1297.0          0.10030           0.13280          0.1980              0.10430         0.1809                 0.05883     0.7572      0.7813         5.438    94.44       0.011490         0.02461       0.05688            0.01885      0.01756              0.005115         22.54          16.67           152.20      1575.0            0.1374             0.2050           0.4000                0.1625          0.2364                  0.07678"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the data\n",
    "cancer_df[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Separate X and y\n",
    "X = cancer_df.drop(columns='diagnosis')\n",
    "y = cancer_df['diagnosis']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Identify Class Labels\n",
    "\n",
    "To make sure we know the display names for the values or labels in 'y', a `class_map` dictionary shoudl be created. For binary classification, we will need to specify which of these labels represents the positive class as the `pos_label` parameter. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Encode to numeric values for XGB classifier\n",
    "mapping_dict = {'M': 1, 'B': 0}\n",
    "y_enc = y.map(mapping_dict)\n",
    "\n",
    "# Map class labels to display names\n",
    "class_map = {0: 'Benign', 1: 'Malignant'}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Define Configuration\n",
    "\n",
    "A configuration dictionary needs to be created, and it will require all the reference libraries to be imported, and any column lists or variable names to be defined."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set some variables referenced in the config\n",
    "random_state = 42\n",
    "class_weight = None\n",
    "max_iter = 10000\n",
    "\n",
    "# Set column lists referenced in the config\n",
    "num_columns = list(X.columns)\n",
    "cat_columns = []\n",
    "ohe_columns = []\n",
    "ord_columns = []\n",
    "poly2_columns = []\n",
    "log_columns = []\n",
    "\n",
    "# If you are doing One-Hot Encoding, you might specify a value to drop\n",
    "ohe_drop_value = []\n",
    "\n",
    "# If you are doing ordinal encoding, the ordering needs to be specified\n",
    "ord_category_order = [[]]\n",
    "\n",
    "# Define the callback for early stop, referenced by KerasClassifier\n",
    "stopper = EarlyStopping(patience=4)\n",
    "\n",
    "# Create a custom configuration file with model pipeline components and grid search params\n",
    "my_config = {\n",
    "    'models' : {\n",
    "        'logreg': LogisticRegression(max_iter=max_iter, random_state=random_state, class_weight=class_weight),\n",
    "        'knn_class': KNeighborsClassifier(),\n",
    "        'svm': SVC(random_state=random_state, probability=False, class_weight=class_weight),\n",
    "        'svm_proba': SVC(random_state=random_state, probability=True, class_weight=class_weight),\n",
    "        'tree_class': DecisionTreeClassifier(random_state=random_state, class_weight=class_weight),\n",
    "        'forest_class': RandomForestClassifier(random_state=random_state, class_weight=class_weight),\n",
    "        'xgb_class': XGBClassifier(random_state=random_state),\n",
    "        'keras_class': KerasClassifier(model=dw.create_nn_binary, hidden_layer_dim=50, second_layer_dim=None,\n",
    "                                       third_layer_dim=None, dropout_rate=0.2, epochs=50, l2_reg=0.0,\n",
    "                                       verbose=0, class_weight=class_weight, random_state=random_state,\n",
    "                                       fit__validation_split=0.2, fit__callbacks=[stopper],\n",
    "                                       fit__batch_size=32, metrics=['accuracy'])   \n",
    "    },\n",
    "    'imputers': {\n",
    "        'knn_imputer': KNNImputer().set_output(transform='pandas'),\n",
    "        'simple_imputer': SimpleImputer()\n",
    "    },\n",
    "    'transformers': {\n",
    "        'ohe': (OneHotEncoder(drop='if_binary', handle_unknown='ignore'), ohe_columns),\n",
    "        'ohe_drop': (OneHotEncoder(drop=ohe_drop_value, handle_unknown='ignore'), ohe_columns),\n",
    "        'ord': (OrdinalEncoder(categories=ord_category_order), ord_columns),\n",
    "        'poly2': (PolynomialFeatures(degree=2, include_bias=False), poly2_columns),\n",
    "        'log': (LogTransformer(), log_columns),\n",
    "    },\n",
    "    'scalers': {\n",
    "        'stand': StandardScaler(),\n",
    "        'robust': RobustScaler(),\n",
    "        'minmax': MinMaxScaler()\n",
    "    },\n",
    "    'selectors': {\n",
    "        'rfe_logreg': RFE(LogisticRegression(max_iter=max_iter, random_state=random_state,\n",
    "                                             class_weight=class_weight)),\n",
    "        'sfs_logreg': SequentialFeatureSelector(LogisticRegression(max_iter=max_iter, random_state=random_state,\n",
    "                                                                   class_weight=class_weight))\n",
    "    },\n",
    "    'params' : {\n",
    "        'logreg': {\n",
    "            'logreg__C': [0.0001, 0.001, 0.01, 0.1, 1, 10, 100],\n",
    "            'logreg__solver': ['newton-cg', 'lbfgs', 'saga']\n",
    "        },\n",
    "        'knn_class': {\n",
    "            'knn_class__n_neighbors': [3, 5, 10, 15, 20, 25],\n",
    "            'knn_class__weights': ['uniform', 'distance'],\n",
    "            'knn_class__metric': ['euclidean', 'manhattan']\n",
    "        },\n",
    "        'svm': {\n",
    "            'svm__C': [0.0001, 0.001, 0.01, 0.1, 1, 10, 100],\n",
    "            'svm__kernel': ['linear', 'poly', 'rbf', 'sigmoid']\n",
    "        },\n",
    "        'svm_proba': {\n",
    "            'svm_proba__C': [0.0001, 0.001, 0.01, 0.1, 1, 10, 100],\n",
    "            'svm_proba__kernel': ['linear', 'poly', 'rbf', 'sigmoid']\n",
    "        },\n",
    "        'tree_class': {\n",
    "            'tree_class__max_depth': [3, 5, 7],\n",
    "            'tree_class__min_samples_split': [5, 10, 15],\n",
    "            'tree_class__criterion': ['gini', 'entropy'],\n",
    "            'tree_class__min_samples_leaf': [2, 4, 6]\n",
    "        },\n",
    "        'forest_class': {\n",
    "            'forest_class__n_estimators' : [50, 100, 200],\n",
    "            'forest_class__max_depth': [3, 5, 7],\n",
    "            'forest_class__min_samples_split': [5, 10, 15],\n",
    "            'forest_class__criterion': ['gini', 'entropy'],\n",
    "            'forest_class__min_samples_leaf': [2, 4, 6]\n",
    "        },\n",
    "        'xgb_class': {\n",
    "            'xgb_class__learning_rate': [0.01, 0.1, 0.5],\n",
    "            'xgb_class__max_depth': [3, 5, 7],\n",
    "            'xgb_class__subsample': [0.7, 0.8, 0.9],\n",
    "            'xgb_class__colsample_bytree': [0.7, 0.8, 0.9],\n",
    "            'xgb_class__n_estimators': [50, 100, 200],\n",
    "            'xgb_class__objective': ['binary:logistic'],\n",
    "            'xgb_class__gamma': [0, 1, 5, 10]\n",
    "        },\n",
    "        'keras_class': {\n",
    "            'keras_class__loss': ['binary_crossentropy'],\n",
    "            'keras_class__optimizer': ['adam'],\n",
    "            'keras_class__hidden_layer_dim': [50, 100, 200],\n",
    "            'keras_class__dropout_rate': [0.5],\n",
    "            'keras_class__l2_reg': [0.0],\n",
    "            'keras_class__second_layer_dim': [50, 100],\n",
    "            'keras_class__third_layer_dim': [None, 25, 50],\n",
    "            'keras_class__optimizer__learning_rate': [0.001],\n",
    "            'keras_class__fit__batch_size': [32]\n",
    "        },\n",
    "    },\n",
    "    'cv': {\n",
    "        'kfold_3': KFold(n_splits=3, shuffle=True, random_state=42),\n",
    "        'kfold_5': KFold(n_splits=5, shuffle=True, random_state=42),\n",
    "        'skf_5': StratifiedKFold(n_splits=5, shuffle=True, random_state=42),\n",
    "    },\n",
    "    'no_scale': ['tree_class', 'forest_class'],\n",
    "    'no_poly': ['knn_class', 'tree_class', 'forest_class', 'xgb_class']\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Compare Binary Classification Models\n",
    "\n",
    "Let's now automatically build the same pipeline for 7 different models, perform a grid search to find the best hyper-parameters, capture a number of binary classification metrics, and plot the model's performance visually. Everything will be stored in the 'results_df' DataFrame so we can further anaylize or plot the metrics."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-----------------------------------------------------------------------------------------\n",
      "Starting Data Processing - May 30, 2024 09:18 AM UTC\n",
      "-----------------------------------------------------------------------------------------\n",
      "\n",
      "Classification type detected: binary\n",
      "Unique values in y: [0 1]\n",
      "\n",
      "Train/Test split, test_size:  0.25\n",
      "X_train, X_test, y_train, y_test shapes:  (426, 30) (143, 30) (426,) (143,)\n",
      "\n",
      "-----------------------------------------------------------------------------------------\n",
      "1/7: Starting LogisticRegression Random Search - May 30, 2024 09:18 AM UTC\n",
      "-----------------------------------------------------------------------------------------\n",
      "\n",
      "Fitting 5 folds for each of 10 candidates, totalling 50 fits\n",
      "[CV 1/5] END logreg__C=0.0001, logreg__solver=newton-cg;, score=0.733 total time=   0.0s\n",
      "[CV 2/5] END logreg__C=0.0001, logreg__solver=newton-cg;, score=0.612 total time=   0.0s\n",
      "[CV 3/5] END logreg__C=0.0001, logreg__solver=newton-cg;, score=0.682 total time=   0.0s\n",
      "[CV 4/5] END logreg__C=0.0001, logreg__solver=newton-cg;, score=0.588 total time=   0.0s\n",
      "[CV 5/5] END logreg__C=0.0001, logreg__solver=newton-cg;, score=0.565 total time=   0.0s\n",
      "[CV 1/5] END .logreg__C=10, logreg__solver=saga;, score=1.000 total time=   0.3s\n",
      "[CV 2/5] END .logreg__C=10, logreg__solver=saga;, score=0.929 total time=   0.3s\n",
      "[CV 3/5] END .logreg__C=10, logreg__solver=saga;, score=0.988 total time=   0.3s\n",
      "[CV 4/5] END .logreg__C=10, logreg__solver=saga;, score=0.988 total time=   0.2s\n",
      "[CV 5/5] END .logreg__C=10, logreg__solver=saga;, score=0.976 total time=   0.3s\n",
      "[CV 1/5] END logreg__C=10, logreg__solver=newton-cg;, score=1.000 total time=   0.0s\n",
      "[CV 2/5] END logreg__C=10, logreg__solver=newton-cg;, score=0.929 total time=   0.0s\n",
      "[CV 3/5] END logreg__C=10, logreg__solver=newton-cg;, score=0.988 total time=   0.0s\n",
      "[CV 4/5] END logreg__C=10, logreg__solver=newton-cg;, score=0.988 total time=   0.0s\n",
      "[CV 5/5] END logreg__C=10, logreg__solver=newton-cg;, score=0.976 total time=   0.0s\n",
      "[CV 1/5] END logreg__C=0.0001, logreg__solver=lbfgs;, score=0.733 total time=   0.0s\n",
      "[CV 2/5] END logreg__C=0.0001, logreg__solver=lbfgs;, score=0.612 total time=   0.0s\n",
      "[CV 3/5] END logreg__C=0.0001, logreg__solver=lbfgs;, score=0.682 total time=   0.0s\n",
      "[CV 4/5] END logreg__C=0.0001, logreg__solver=lbfgs;, score=0.588 total time=   0.0s\n",
      "[CV 5/5] END logreg__C=0.0001, logreg__solver=lbfgs;, score=0.565 total time=   0.0s\n",
      "[CV 1/5] END logreg__C=0.01, logreg__solver=saga;, score=0.965 total time=   0.0s\n",
      "[CV 2/5] END logreg__C=0.01, logreg__solver=saga;, score=0.871 total time=   0.0s\n",
      "[CV 3/5] END logreg__C=0.01, logreg__solver=saga;, score=1.000 total time=   0.0s\n",
      "[CV 4/5] END logreg__C=0.01, logreg__solver=saga;, score=0.953 total time=   0.0s\n",
      "[CV 5/5] END logreg__C=0.01, logreg__solver=saga;, score=0.929 total time=   0.0s\n",
      "[CV 1/5] END logreg__C=0.001, logreg__solver=saga;, score=0.930 total time=   0.0s\n",
      "[CV 2/5] END logreg__C=0.001, logreg__solver=saga;, score=0.812 total time=   0.0s\n",
      "[CV 3/5] END logreg__C=0.001, logreg__solver=saga;, score=0.965 total time=   0.0s\n",
      "[CV 4/5] END logreg__C=0.001, logreg__solver=saga;, score=0.859 total time=   0.0s\n",
      "[CV 5/5] END logreg__C=0.001, logreg__solver=saga;, score=0.871 total time=   0.0s\n",
      "[CV 1/5] END logreg__C=0.1, logreg__solver=saga;, score=0.988 total time=   0.0s\n",
      "[CV 2/5] END logreg__C=0.1, logreg__solver=saga;, score=0.906 total time=   0.0s\n",
      "[CV 3/5] END logreg__C=0.1, logreg__solver=saga;, score=1.000 total time=   0.0s\n",
      "[CV 4/5] END logreg__C=0.1, logreg__solver=saga;, score=0.988 total time=   0.0s\n",
      "[CV 5/5] END logreg__C=0.1, logreg__solver=saga;, score=0.965 total time=   0.0s\n",
      "[CV 1/5] END logreg__C=0.001, logreg__solver=newton-cg;, score=0.930 total time=   0.0s\n",
      "[CV 2/5] END logreg__C=0.001, logreg__solver=newton-cg;, score=0.812 total time=   0.0s\n",
      "[CV 3/5] END logreg__C=0.001, logreg__solver=newton-cg;, score=0.965 total time=   0.0s\n",
      "[CV 4/5] END logreg__C=0.001, logreg__solver=newton-cg;, score=0.859 total time=   0.0s\n",
      "[CV 5/5] END logreg__C=0.001, logreg__solver=newton-cg;, score=0.871 total time=   0.0s\n",
      "[CV 1/5] END logreg__C=100, logreg__solver=newton-cg;, score=0.977 total time=   0.0s\n",
      "[CV 2/5] END logreg__C=100, logreg__solver=newton-cg;, score=0.929 total time=   0.0s\n",
      "[CV 3/5] END logreg__C=100, logreg__solver=newton-cg;, score=0.988 total time=   0.0s\n",
      "[CV 4/5] END logreg__C=100, logreg__solver=newton-cg;, score=0.965 total time=   0.0s\n",
      "[CV 5/5] END logreg__C=100, logreg__solver=newton-cg;, score=0.988 total time=   0.0s\n",
      "[CV 1/5] END logreg__C=10, logreg__solver=lbfgs;, score=1.000 total time=   0.0s\n",
      "[CV 2/5] END logreg__C=10, logreg__solver=lbfgs;, score=0.929 total time=   0.0s\n",
      "[CV 3/5] END logreg__C=10, logreg__solver=lbfgs;, score=0.988 total time=   0.0s\n",
      "[CV 4/5] END logreg__C=10, logreg__solver=lbfgs;, score=0.988 total time=   0.0s\n",
      "[CV 5/5] END logreg__C=10, logreg__solver=lbfgs;, score=0.976 total time=   0.0s\n",
      "\n",
      "Total Time: 2.6005 seconds\n",
      "Average Fit Time: 0.0520 seconds\n",
      "Inference Time: 0.0013\n",
      "Best CV Accuracy Score: 0.9765\n",
      "Train Accuracy Score: 0.9906\n",
      "Test Accuracy Score: 0.9720\n",
      "Overfit: Yes\n",
      "Overfit Difference: 0.0186\n",
      "Best Parameters: {'logreg__solver': 'saga', 'logreg__C': 10}\n",
      "\n",
      "LogisticRegression Binary Classification Report\n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "      Benign     0.9885    0.9663    0.9773        89\n",
      "   Malignant     0.9464    0.9815    0.9636        54\n",
      "\n",
      "    accuracy                         0.9720       143\n",
      "   macro avg     0.9675    0.9739    0.9705       143\n",
      "weighted avg     0.9726    0.9720    0.9721       143\n",
      "\n",
      "ROC AUC: 0.9956\n",
      "\n",
      "               Predicted:0         1         \n",
      "Actual: 0                86        3         \n",
      "Actual: 1                1         53        \n",
      "\n",
      "True Positive Rate / Sensitivity: 0.9815\n",
      "True Negative Rate / Specificity: 0.9663\n",
      "False Positive Rate / Fall-out: 0.0337\n",
      "False Negative Rate / Miss Rate: 0.0185\n",
      "\n",
      "Positive Class: Malignant (1)\n",
      "Threshold: 0.5\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1100 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-----------------------------------------------------------------------------------------\n",
      "2/7: Starting KNeighborsClassifier Random Search - May 30, 2024 09:18 AM UTC\n",
      "-----------------------------------------------------------------------------------------\n",
      "\n",
      "Fitting 5 folds for each of 10 candidates, totalling 50 fits\n",
      "[CV 1/5] END knn_class__metric=euclidean, knn_class__n_neighbors=20, knn_class__weights=uniform;, score=0.965 total time=   0.1s\n",
      "[CV 2/5] END knn_class__metric=euclidean, knn_class__n_neighbors=20, knn_class__weights=uniform;, score=0.859 total time=   0.0s\n",
      "[CV 3/5] END knn_class__metric=euclidean, knn_class__n_neighbors=20, knn_class__weights=uniform;, score=0.988 total time=   0.0s\n",
      "[CV 4/5] END knn_class__metric=euclidean, knn_class__n_neighbors=20, knn_class__weights=uniform;, score=0.965 total time=   0.0s\n",
      "[CV 5/5] END knn_class__metric=euclidean, knn_class__n_neighbors=20, knn_class__weights=uniform;, score=0.941 total time=   0.0s\n",
      "[CV 1/5] END knn_class__metric=manhattan, knn_class__n_neighbors=10, knn_class__weights=uniform;, score=0.965 total time=   0.0s\n",
      "[CV 2/5] END knn_class__metric=manhattan, knn_class__n_neighbors=10, knn_class__weights=uniform;, score=0.882 total time=   0.0s\n",
      "[CV 3/5] END knn_class__metric=manhattan, knn_class__n_neighbors=10, knn_class__weights=uniform;, score=1.000 total time=   0.0s\n",
      "[CV 4/5] END knn_class__metric=manhattan, knn_class__n_neighbors=10, knn_class__weights=uniform;, score=0.976 total time=   0.0s\n",
      "[CV 5/5] END knn_class__metric=manhattan, knn_class__n_neighbors=10, knn_class__weights=uniform;, score=0.953 total time=   0.0s\n",
      "[CV 1/5] END knn_class__metric=euclidean, knn_class__n_neighbors=3, knn_class__weights=uniform;, score=0.988 total time=   0.0s\n",
      "[CV 2/5] END knn_class__metric=euclidean, knn_class__n_neighbors=3, knn_class__weights=uniform;, score=0.882 total time=   0.0s\n",
      "[CV 3/5] END knn_class__metric=euclidean, knn_class__n_neighbors=3, knn_class__weights=uniform;, score=1.000 total time=   0.0s\n",
      "[CV 4/5] END knn_class__metric=euclidean, knn_class__n_neighbors=3, knn_class__weights=uniform;, score=0.988 total time=   0.0s\n",
      "[CV 5/5] END knn_class__metric=euclidean, knn_class__n_neighbors=3, knn_class__weights=uniform;, score=0.976 total time=   0.0s\n",
      "[CV 1/5] END knn_class__metric=manhattan, knn_class__n_neighbors=15, knn_class__weights=uniform;, score=0.977 total time=   0.0s\n",
      "[CV 2/5] END knn_class__metric=manhattan, knn_class__n_neighbors=15, knn_class__weights=uniform;, score=0.894 total time=   0.0s\n",
      "[CV 3/5] END knn_class__metric=manhattan, knn_class__n_neighbors=15, knn_class__weights=uniform;, score=1.000 total time=   0.0s\n",
      "[CV 4/5] END knn_class__metric=manhattan, knn_class__n_neighbors=15, knn_class__weights=uniform;, score=0.965 total time=   0.0s\n",
      "[CV 5/5] END knn_class__metric=manhattan, knn_class__n_neighbors=15, knn_class__weights=uniform;, score=0.929 total time=   0.0s\n",
      "[CV 1/5] END knn_class__metric=euclidean, knn_class__n_neighbors=25, knn_class__weights=distance;, score=0.977 total time=   0.0s\n",
      "[CV 2/5] END knn_class__metric=euclidean, knn_class__n_neighbors=25, knn_class__weights=distance;, score=0.882 total time=   0.0s\n",
      "[CV 3/5] END knn_class__metric=euclidean, knn_class__n_neighbors=25, knn_class__weights=distance;, score=1.000 total time=   0.0s\n",
      "[CV 4/5] END knn_class__metric=euclidean, knn_class__n_neighbors=25, knn_class__weights=distance;, score=0.965 total time=   0.0s\n",
      "[CV 5/5] END knn_class__metric=euclidean, knn_class__n_neighbors=25, knn_class__weights=distance;, score=0.941 total time=   0.0s\n",
      "[CV 1/5] END knn_class__metric=euclidean, knn_class__n_neighbors=20, knn_class__weights=distance;, score=0.977 total time=   0.0s\n",
      "[CV 2/5] END knn_class__metric=euclidean, knn_class__n_neighbors=20, knn_class__weights=distance;, score=0.882 total time=   0.0s\n",
      "[CV 3/5] END knn_class__metric=euclidean, knn_class__n_neighbors=20, knn_class__weights=distance;, score=0.988 total time=   0.0s\n",
      "[CV 4/5] END knn_class__metric=euclidean, knn_class__n_neighbors=20, knn_class__weights=distance;, score=0.965 total time=   0.0s\n",
      "[CV 5/5] END knn_class__metric=euclidean, knn_class__n_neighbors=20, knn_class__weights=distance;, score=0.941 total time=   0.0s\n",
      "[CV 1/5] END knn_class__metric=manhattan, knn_class__n_neighbors=3, knn_class__weights=distance;, score=1.000 total time=   0.0s\n",
      "[CV 2/5] END knn_class__metric=manhattan, knn_class__n_neighbors=3, knn_class__weights=distance;, score=0.918 total time=   0.0s\n",
      "[CV 3/5] END knn_class__metric=manhattan, knn_class__n_neighbors=3, knn_class__weights=distance;, score=1.000 total time=   0.0s\n",
      "[CV 4/5] END knn_class__metric=manhattan, knn_class__n_neighbors=3, knn_class__weights=distance;, score=0.988 total time=   0.0s\n",
      "[CV 5/5] END knn_class__metric=manhattan, knn_class__n_neighbors=3, knn_class__weights=distance;, score=0.976 total time=   0.0s\n",
      "[CV 1/5] END knn_class__metric=euclidean, knn_class__n_neighbors=3, knn_class__weights=distance;, score=0.988 total time=   0.0s\n",
      "[CV 2/5] END knn_class__metric=euclidean, knn_class__n_neighbors=3, knn_class__weights=distance;, score=0.882 total time=   0.0s\n",
      "[CV 3/5] END knn_class__metric=euclidean, knn_class__n_neighbors=3, knn_class__weights=distance;, score=1.000 total time=   0.0s\n",
      "[CV 4/5] END knn_class__metric=euclidean, knn_class__n_neighbors=3, knn_class__weights=distance;, score=0.988 total time=   0.0s\n",
      "[CV 5/5] END knn_class__metric=euclidean, knn_class__n_neighbors=3, knn_class__weights=distance;, score=0.976 total time=   0.0s\n",
      "[CV 1/5] END knn_class__metric=manhattan, knn_class__n_neighbors=20, knn_class__weights=distance;, score=0.977 total time=   0.0s\n",
      "[CV 2/5] END knn_class__metric=manhattan, knn_class__n_neighbors=20, knn_class__weights=distance;, score=0.894 total time=   0.0s\n",
      "[CV 3/5] END knn_class__metric=manhattan, knn_class__n_neighbors=20, knn_class__weights=distance;, score=1.000 total time=   0.0s\n",
      "[CV 4/5] END knn_class__metric=manhattan, knn_class__n_neighbors=20, knn_class__weights=distance;, score=0.965 total time=   0.0s\n",
      "[CV 5/5] END knn_class__metric=manhattan, knn_class__n_neighbors=20, knn_class__weights=distance;, score=0.929 total time=   0.0s\n",
      "[CV 1/5] END knn_class__metric=euclidean, knn_class__n_neighbors=10, knn_class__weights=distance;, score=0.988 total time=   0.0s\n",
      "[CV 2/5] END knn_class__metric=euclidean, knn_class__n_neighbors=10, knn_class__weights=distance;, score=0.882 total time=   0.0s\n",
      "[CV 3/5] END knn_class__metric=euclidean, knn_class__n_neighbors=10, knn_class__weights=distance;, score=1.000 total time=   0.0s\n",
      "[CV 4/5] END knn_class__metric=euclidean, knn_class__n_neighbors=10, knn_class__weights=distance;, score=0.976 total time=   0.0s\n",
      "[CV 5/5] END knn_class__metric=euclidean, knn_class__n_neighbors=10, knn_class__weights=distance;, score=0.965 total time=   0.0s\n",
      "\n",
      "Total Time: 0.6090 seconds\n",
      "Average Fit Time: 0.0122 seconds\n",
      "Inference Time: 0.0043\n",
      "Best CV Accuracy Score: 0.9765\n",
      "Train Accuracy Score: 1.0000\n",
      "Test Accuracy Score: 0.9720\n",
      "Overfit: Yes\n",
      "Overfit Difference: 0.0280\n",
      "Best Parameters: {'knn_class__weights': 'distance', 'knn_class__n_neighbors': 3, 'knn_class__metric': 'manhattan'}\n",
      "\n",
      "KNeighborsClassifier Binary Classification Report\n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "      Benign     0.9775    0.9775    0.9775        89\n",
      "   Malignant     0.9630    0.9630    0.9630        54\n",
      "\n",
      "    accuracy                         0.9720       143\n",
      "   macro avg     0.9702    0.9702    0.9702       143\n",
      "weighted avg     0.9720    0.9720    0.9720       143\n",
      "\n",
      "ROC AUC: 0.9874\n",
      "\n",
      "               Predicted:0         1         \n",
      "Actual: 0                87        2         \n",
      "Actual: 1                2         52        \n",
      "\n",
      "True Positive Rate / Sensitivity: 0.963\n",
      "True Negative Rate / Specificity: 0.9775\n",
      "False Positive Rate / Fall-out: 0.0225\n",
      "False Negative Rate / Miss Rate: 0.037\n",
      "\n",
      "Positive Class: Malignant (1)\n",
      "Threshold: 0.5\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1100 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-----------------------------------------------------------------------------------------\n",
      "3/7: Starting SVC Random Search - May 30, 2024 09:18 AM UTC\n",
      "-----------------------------------------------------------------------------------------\n",
      "\n",
      "Fitting 5 folds for each of 10 candidates, totalling 50 fits\n",
      "[CV 1/5] END svm_proba__C=0.01, svm_proba__kernel=poly;, score=0.756 total time=   0.0s\n",
      "[CV 2/5] END svm_proba__C=0.01, svm_proba__kernel=poly;, score=0.671 total time=   0.0s\n",
      "[CV 3/5] END svm_proba__C=0.01, svm_proba__kernel=poly;, score=0.741 total time=   0.0s\n",
      "[CV 4/5] END svm_proba__C=0.01, svm_proba__kernel=poly;, score=0.635 total time=   0.0s\n",
      "[CV 5/5] END svm_proba__C=0.01, svm_proba__kernel=poly;, score=0.635 total time=   0.0s\n",
      "[CV 1/5] END svm_proba__C=100, svm_proba__kernel=poly;, score=0.988 total time=   0.0s\n",
      "[CV 2/5] END svm_proba__C=100, svm_proba__kernel=poly;, score=0.941 total time=   0.0s\n",
      "[CV 3/5] END svm_proba__C=100, svm_proba__kernel=poly;, score=0.953 total time=   0.0s\n",
      "[CV 4/5] END svm_proba__C=100, svm_proba__kernel=poly;, score=0.965 total time=   0.0s\n",
      "[CV 5/5] END svm_proba__C=100, svm_proba__kernel=poly;, score=0.953 total time=   0.0s\n",
      "[CV 1/5] END svm_proba__C=0.01, svm_proba__kernel=linear;, score=1.000 total time=   0.0s\n",
      "[CV 2/5] END svm_proba__C=0.01, svm_proba__kernel=linear;, score=0.906 total time=   0.0s\n",
      "[CV 3/5] END svm_proba__C=0.01, svm_proba__kernel=linear;, score=1.000 total time=   0.0s\n",
      "[CV 4/5] END svm_proba__C=0.01, svm_proba__kernel=linear;, score=0.953 total time=   0.0s\n",
      "[CV 5/5] END svm_proba__C=0.01, svm_proba__kernel=linear;, score=0.965 total time=   0.0s\n",
      "[CV 1/5] END svm_proba__C=10, svm_proba__kernel=poly;, score=0.988 total time=   0.0s\n",
      "[CV 2/5] END svm_proba__C=10, svm_proba__kernel=poly;, score=0.882 total time=   0.0s\n",
      "[CV 3/5] END svm_proba__C=10, svm_proba__kernel=poly;, score=0.988 total time=   0.0s\n",
      "[CV 4/5] END svm_proba__C=10, svm_proba__kernel=poly;, score=0.953 total time=   0.0s\n",
      "[CV 5/5] END svm_proba__C=10, svm_proba__kernel=poly;, score=0.941 total time=   0.0s\n",
      "[CV 1/5] END svm_proba__C=0.0001, svm_proba__kernel=linear;, score=0.721 total time=   0.0s\n",
      "[CV 2/5] END svm_proba__C=0.0001, svm_proba__kernel=linear;, score=0.612 total time=   0.0s\n",
      "[CV 3/5] END svm_proba__C=0.0001, svm_proba__kernel=linear;, score=0.682 total time=   0.0s\n",
      "[CV 4/5] END svm_proba__C=0.0001, svm_proba__kernel=linear;, score=0.588 total time=   0.0s\n",
      "[CV 5/5] END svm_proba__C=0.0001, svm_proba__kernel=linear;, score=0.565 total time=   0.0s\n",
      "[CV 1/5] END svm_proba__C=0.1, svm_proba__kernel=linear;, score=1.000 total time=   0.0s\n",
      "[CV 2/5] END svm_proba__C=0.1, svm_proba__kernel=linear;, score=0.929 total time=   0.0s\n",
      "[CV 3/5] END svm_proba__C=0.1, svm_proba__kernel=linear;, score=1.000 total time=   0.0s\n",
      "[CV 4/5] END svm_proba__C=0.1, svm_proba__kernel=linear;, score=0.988 total time=   0.0s\n",
      "[CV 5/5] END svm_proba__C=0.1, svm_proba__kernel=linear;, score=0.965 total time=   0.0s\n",
      "[CV 1/5] END svm_proba__C=1, svm_proba__kernel=poly;, score=0.930 total time=   0.0s\n",
      "[CV 2/5] END svm_proba__C=1, svm_proba__kernel=poly;, score=0.847 total time=   0.0s\n",
      "[CV 3/5] END svm_proba__C=1, svm_proba__kernel=poly;, score=0.953 total time=   0.0s\n",
      "[CV 4/5] END svm_proba__C=1, svm_proba__kernel=poly;, score=0.894 total time=   0.0s\n",
      "[CV 5/5] END svm_proba__C=1, svm_proba__kernel=poly;, score=0.894 total time=   0.0s\n",
      "[CV 1/5] END svm_proba__C=10, svm_proba__kernel=rbf;, score=1.000 total time=   0.0s\n",
      "[CV 2/5] END svm_proba__C=10, svm_proba__kernel=rbf;, score=0.965 total time=   0.0s\n",
      "[CV 3/5] END svm_proba__C=10, svm_proba__kernel=rbf;, score=0.976 total time=   0.0s\n",
      "[CV 4/5] END svm_proba__C=10, svm_proba__kernel=rbf;, score=0.988 total time=   0.0s\n",
      "[CV 5/5] END svm_proba__C=10, svm_proba__kernel=rbf;, score=0.965 total time=   0.0s\n",
      "[CV 1/5] END svm_proba__C=0.01, svm_proba__kernel=sigmoid;, score=0.884 total time=   0.0s\n",
      "[CV 2/5] END svm_proba__C=0.01, svm_proba__kernel=sigmoid;, score=0.776 total time=   0.0s\n",
      "[CV 3/5] END svm_proba__C=0.01, svm_proba__kernel=sigmoid;, score=0.918 total time=   0.0s\n",
      "[CV 4/5] END svm_proba__C=0.01, svm_proba__kernel=sigmoid;, score=0.824 total time=   0.0s\n",
      "[CV 5/5] END svm_proba__C=0.01, svm_proba__kernel=sigmoid;, score=0.812 total time=   0.0s\n",
      "[CV 1/5] END svm_proba__C=0.1, svm_proba__kernel=poly;, score=0.895 total time=   0.0s\n",
      "[CV 2/5] END svm_proba__C=0.1, svm_proba__kernel=poly;, score=0.788 total time=   0.0s\n",
      "[CV 3/5] END svm_proba__C=0.1, svm_proba__kernel=poly;, score=0.894 total time=   0.0s\n",
      "[CV 4/5] END svm_proba__C=0.1, svm_proba__kernel=poly;, score=0.812 total time=   0.0s\n",
      "[CV 5/5] END svm_proba__C=0.1, svm_proba__kernel=poly;, score=0.812 total time=   0.0s\n",
      "\n",
      "Total Time: 1.1188 seconds\n",
      "Average Fit Time: 0.0224 seconds\n",
      "Inference Time: 0.0032\n",
      "Best CV Accuracy Score: 0.9788\n",
      "Train Accuracy Score: 0.9930\n",
      "Test Accuracy Score: 0.9650\n",
      "Overfit: Yes\n",
      "Overfit Difference: 0.0279\n",
      "Best Parameters: {'svm_proba__kernel': 'rbf', 'svm_proba__C': 10}\n",
      "\n",
      "SVC Binary Classification Report\n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "      Benign     0.9773    0.9663    0.9718        89\n",
      "   Malignant     0.9455    0.9630    0.9541        54\n",
      "\n",
      "    accuracy                         0.9650       143\n",
      "   macro avg     0.9614    0.9646    0.9629       143\n",
      "weighted avg     0.9653    0.9650    0.9651       143\n",
      "\n",
      "ROC AUC: 0.9956\n",
      "\n",
      "               Predicted:0         1         \n",
      "Actual: 0                86        3         \n",
      "Actual: 1                2         52        \n",
      "\n",
      "True Positive Rate / Sensitivity: 0.963\n",
      "True Negative Rate / Specificity: 0.9663\n",
      "False Positive Rate / Fall-out: 0.0337\n",
      "False Negative Rate / Miss Rate: 0.037\n",
      "\n",
      "Positive Class: Malignant (1)\n",
      "Threshold: 0.5\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1200x1100 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-----------------------------------------------------------------------------------------\n",
      "4/7: Starting DecisionTreeClassifier Random Search - May 30, 2024 09:18 AM UTC\n",
      "-----------------------------------------------------------------------------------------\n",
      "\n",
      "Fitting 5 folds for each of 10 candidates, totalling 50 fits\n",
      "[CV 1/5] END tree_class__criterion=gini, tree_class__max_depth=7, tree_class__min_samples_leaf=2, tree_class__min_samples_split=10;, score=0.965 total time=   0.0s\n",
      "[CV 2/5] END tree_class__criterion=gini, tree_class__max_depth=7, tree_class__min_samples_leaf=2, tree_class__min_samples_split=10;, score=0.871 total time=   0.1s\n",
      "[CV 3/5] END tree_class__criterion=gini, tree_class__max_depth=7, tree_class__min_samples_leaf=2, tree_class__min_samples_split=10;, score=0.965 total time=   0.0s\n",
      "[CV 4/5] END tree_class__criterion=gini, tree_class__max_depth=7, tree_class__min_samples_leaf=2, tree_class__min_samples_split=10;, score=0.941 total time=   0.0s\n",
      "[CV 5/5] END tree_class__criterion=gini, tree_class__max_depth=7, tree_class__min_samples_leaf=2, tree_class__min_samples_split=10;, score=0.953 total time=   0.0s\n",
      "[CV 1/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=4, tree_class__min_samples_split=10;, score=0.907 total time=   0.0s\n",
      "[CV 2/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=4, tree_class__min_samples_split=10;, score=0.859 total time=   0.0s\n",
      "[CV 3/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=4, tree_class__min_samples_split=10;, score=0.988 total time=   0.0s\n",
      "[CV 4/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=4, tree_class__min_samples_split=10;, score=0.941 total time=   0.0s\n",
      "[CV 5/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=4, tree_class__min_samples_split=10;, score=0.918 total time=   0.0s\n",
      "[CV 1/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=0.895 total time=   0.0s\n",
      "[CV 2/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=0.882 total time=   0.0s\n",
      "[CV 3/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=0.988 total time=   0.0s\n",
      "[CV 4/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=0.941 total time=   0.0s\n",
      "[CV 5/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=0.918 total time=   0.0s\n",
      "[CV 1/5] END tree_class__criterion=gini, tree_class__max_depth=5, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=0.953 total time=   0.0s\n",
      "[CV 2/5] END tree_class__criterion=gini, tree_class__max_depth=5, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=0.871 total time=   0.0s\n",
      "[CV 3/5] END tree_class__criterion=gini, tree_class__max_depth=5, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=0.976 total time=   0.0s\n",
      "[CV 4/5] END tree_class__criterion=gini, tree_class__max_depth=5, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=0.941 total time=   0.0s\n",
      "[CV 5/5] END tree_class__criterion=gini, tree_class__max_depth=5, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=0.929 total time=   0.0s\n",
      "[CV 1/5] END tree_class__criterion=entropy, tree_class__max_depth=5, tree_class__min_samples_leaf=6, tree_class__min_samples_split=15;, score=0.930 total time=   0.0s\n",
      "[CV 2/5] END tree_class__criterion=entropy, tree_class__max_depth=5, tree_class__min_samples_leaf=6, tree_class__min_samples_split=15;, score=0.859 total time=   0.0s\n",
      "[CV 3/5] END tree_class__criterion=entropy, tree_class__max_depth=5, tree_class__min_samples_leaf=6, tree_class__min_samples_split=15;, score=1.000 total time=   0.0s\n",
      "[CV 4/5] END tree_class__criterion=entropy, tree_class__max_depth=5, tree_class__min_samples_leaf=6, tree_class__min_samples_split=15;, score=0.941 total time=   0.0s\n",
      "[CV 5/5] END tree_class__criterion=entropy, tree_class__max_depth=5, tree_class__min_samples_leaf=6, tree_class__min_samples_split=15;, score=0.894 total time=   0.0s\n",
      "[CV 1/5] END tree_class__criterion=gini, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=15;, score=0.907 total time=   0.0s\n",
      "[CV 2/5] END tree_class__criterion=gini, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=15;, score=0.871 total time=   0.0s\n",
      "[CV 3/5] END tree_class__criterion=gini, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=15;, score=0.988 total time=   0.0s\n",
      "[CV 4/5] END tree_class__criterion=gini, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=15;, score=0.941 total time=   0.0s\n",
      "[CV 5/5] END tree_class__criterion=gini, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=15;, score=0.941 total time=   0.0s\n",
      "[CV 1/5] END tree_class__criterion=gini, tree_class__max_depth=5, tree_class__min_samples_leaf=6, tree_class__min_samples_split=15;, score=0.907 total time=   0.0s\n",
      "[CV 2/5] END tree_class__criterion=gini, tree_class__max_depth=5, tree_class__min_samples_leaf=6, tree_class__min_samples_split=15;, score=0.894 total time=   0.0s\n",
      "[CV 3/5] END tree_class__criterion=gini, tree_class__max_depth=5, tree_class__min_samples_leaf=6, tree_class__min_samples_split=15;, score=0.988 total time=   0.0s\n",
      "[CV 4/5] END tree_class__criterion=gini, tree_class__max_depth=5, tree_class__min_samples_leaf=6, tree_class__min_samples_split=15;, score=0.941 total time=   0.0s\n",
      "[CV 5/5] END tree_class__criterion=gini, tree_class__max_depth=5, tree_class__min_samples_leaf=6, tree_class__min_samples_split=15;, score=0.941 total time=   0.0s\n",
      "[CV 1/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=6, tree_class__min_samples_split=10;, score=0.907 total time=   0.0s\n",
      "[CV 2/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=6, tree_class__min_samples_split=10;, score=0.859 total time=   0.0s\n",
      "[CV 3/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=6, tree_class__min_samples_split=10;, score=1.000 total time=   0.0s\n",
      "[CV 4/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=6, tree_class__min_samples_split=10;, score=0.941 total time=   0.0s\n",
      "[CV 5/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=6, tree_class__min_samples_split=10;, score=0.906 total time=   0.0s\n",
      "[CV 1/5] END tree_class__criterion=gini, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=0.965 total time=   0.0s\n",
      "[CV 2/5] END tree_class__criterion=gini, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=0.894 total time=   0.0s\n",
      "[CV 3/5] END tree_class__criterion=gini, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=0.988 total time=   0.0s\n",
      "[CV 4/5] END tree_class__criterion=gini, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=0.941 total time=   0.0s\n",
      "[CV 5/5] END tree_class__criterion=gini, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=0.941 total time=   0.0s\n",
      "[CV 1/5] END tree_class__criterion=entropy, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=15;, score=0.930 total time=   0.0s\n",
      "[CV 2/5] END tree_class__criterion=entropy, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=15;, score=0.859 total time=   0.0s\n",
      "[CV 3/5] END tree_class__criterion=entropy, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=15;, score=1.000 total time=   0.0s\n",
      "[CV 4/5] END tree_class__criterion=entropy, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=15;, score=0.941 total time=   0.0s\n",
      "[CV 5/5] END tree_class__criterion=entropy, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=15;, score=0.894 total time=   0.0s\n",
      "\n",
      "Total Time: 0.5181 seconds\n",
      "Average Fit Time: 0.0104 seconds\n",
      "Inference Time: 0.0010\n",
      "Best CV Accuracy Score: 0.9460\n",
      "Train Accuracy Score: 0.9695\n",
      "Test Accuracy Score: 0.9580\n",
      "Overfit: Yes\n",
      "Overfit Difference: 0.0114\n",
      "Best Parameters: {'tree_class__min_samples_split': 5, 'tree_class__min_samples_leaf': 4, 'tree_class__max_depth': 3, 'tree_class__criterion': 'gini'}\n",
      "\n",
      "DecisionTreeClassifier Binary Classification Report\n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "      Benign     0.9560    0.9775    0.9667        89\n",
      "   Malignant     0.9615    0.9259    0.9434        54\n",
      "\n",
      "    accuracy                         0.9580       143\n",
      "   macro avg     0.9588    0.9517    0.9550       143\n",
      "weighted avg     0.9581    0.9580    0.9579       143\n",
      "\n",
      "ROC AUC: 0.9526\n",
      "\n",
      "               Predicted:0         1         \n",
      "Actual: 0                87        2         \n",
      "Actual: 1                4         50        \n",
      "\n",
      "True Positive Rate / Sensitivity: 0.9259\n",
      "True Negative Rate / Specificity: 0.9775\n",
      "False Positive Rate / Fall-out: 0.0225\n",
      "False Negative Rate / Miss Rate: 0.0741\n",
      "\n",
      "Positive Class: Malignant (1)\n",
      "Threshold: 0.5\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1200x1100 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-----------------------------------------------------------------------------------------\n",
      "5/7: Starting RandomForestClassifier Random Search - May 30, 2024 09:18 AM UTC\n",
      "-----------------------------------------------------------------------------------------\n",
      "\n",
      "Fitting 5 folds for each of 10 candidates, totalling 50 fits\n",
      "[CV 1/5] END forest_class__criterion=entropy, forest_class__max_depth=7, forest_class__min_samples_leaf=6, forest_class__min_samples_split=10, forest_class__n_estimators=200;, score=0.942 total time=   0.3s\n",
      "[CV 2/5] END forest_class__criterion=entropy, forest_class__max_depth=7, forest_class__min_samples_leaf=6, forest_class__min_samples_split=10, forest_class__n_estimators=200;, score=0.929 total time=   0.3s\n",
      "[CV 3/5] END forest_class__criterion=entropy, forest_class__max_depth=7, forest_class__min_samples_leaf=6, forest_class__min_samples_split=10, forest_class__n_estimators=200;, score=1.000 total time=   0.4s\n",
      "[CV 4/5] END forest_class__criterion=entropy, forest_class__max_depth=7, forest_class__min_samples_leaf=6, forest_class__min_samples_split=10, forest_class__n_estimators=200;, score=0.976 total time=   0.4s\n",
      "[CV 5/5] END forest_class__criterion=entropy, forest_class__max_depth=7, forest_class__min_samples_leaf=6, forest_class__min_samples_split=10, forest_class__n_estimators=200;, score=0.941 total time=   0.4s\n",
      "[CV 1/5] END forest_class__criterion=entropy, forest_class__max_depth=5, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=0.942 total time=   0.2s\n",
      "[CV 2/5] END forest_class__criterion=entropy, forest_class__max_depth=5, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=0.929 total time=   0.2s\n",
      "[CV 3/5] END forest_class__criterion=entropy, forest_class__max_depth=5, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=1.000 total time=   0.2s\n",
      "[CV 4/5] END forest_class__criterion=entropy, forest_class__max_depth=5, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=0.976 total time=   0.2s\n",
      "[CV 5/5] END forest_class__criterion=entropy, forest_class__max_depth=5, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=0.965 total time=   0.2s\n",
      "[CV 1/5] END forest_class__criterion=entropy, forest_class__max_depth=5, forest_class__min_samples_leaf=6, forest_class__min_samples_split=10, forest_class__n_estimators=200;, score=0.942 total time=   0.4s\n",
      "[CV 2/5] END forest_class__criterion=entropy, forest_class__max_depth=5, forest_class__min_samples_leaf=6, forest_class__min_samples_split=10, forest_class__n_estimators=200;, score=0.918 total time=   0.4s\n",
      "[CV 3/5] END forest_class__criterion=entropy, forest_class__max_depth=5, forest_class__min_samples_leaf=6, forest_class__min_samples_split=10, forest_class__n_estimators=200;, score=1.000 total time=   0.3s\n",
      "[CV 4/5] END forest_class__criterion=entropy, forest_class__max_depth=5, forest_class__min_samples_leaf=6, forest_class__min_samples_split=10, forest_class__n_estimators=200;, score=0.976 total time=   0.3s\n",
      "[CV 5/5] END forest_class__criterion=entropy, forest_class__max_depth=5, forest_class__min_samples_leaf=6, forest_class__min_samples_split=10, forest_class__n_estimators=200;, score=0.929 total time=   0.4s\n",
      "[CV 1/5] END forest_class__criterion=gini, forest_class__max_depth=7, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=0.953 total time=   0.2s\n",
      "[CV 2/5] END forest_class__criterion=gini, forest_class__max_depth=7, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=0.929 total time=   0.2s\n",
      "[CV 3/5] END forest_class__criterion=gini, forest_class__max_depth=7, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=1.000 total time=   0.2s\n",
      "[CV 4/5] END forest_class__criterion=gini, forest_class__max_depth=7, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=0.965 total time=   0.2s\n",
      "[CV 5/5] END forest_class__criterion=gini, forest_class__max_depth=7, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=0.918 total time=   0.2s\n",
      "[CV 1/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=4, forest_class__min_samples_split=10, forest_class__n_estimators=100;, score=0.930 total time=   0.2s\n",
      "[CV 2/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=4, forest_class__min_samples_split=10, forest_class__n_estimators=100;, score=0.918 total time=   0.2s\n",
      "[CV 3/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=4, forest_class__min_samples_split=10, forest_class__n_estimators=100;, score=1.000 total time=   0.2s\n",
      "[CV 4/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=4, forest_class__min_samples_split=10, forest_class__n_estimators=100;, score=0.965 total time=   0.2s\n",
      "[CV 5/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=4, forest_class__min_samples_split=10, forest_class__n_estimators=100;, score=0.918 total time=   0.2s\n",
      "[CV 1/5] END forest_class__criterion=gini, forest_class__max_depth=5, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=200;, score=0.942 total time=   0.4s\n",
      "[CV 2/5] END forest_class__criterion=gini, forest_class__max_depth=5, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=200;, score=0.929 total time=   0.3s\n",
      "[CV 3/5] END forest_class__criterion=gini, forest_class__max_depth=5, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=200;, score=1.000 total time=   0.4s\n",
      "[CV 4/5] END forest_class__criterion=gini, forest_class__max_depth=5, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=200;, score=0.976 total time=   0.3s\n",
      "[CV 5/5] END forest_class__criterion=gini, forest_class__max_depth=5, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=200;, score=0.929 total time=   0.4s\n",
      "[CV 1/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=6, forest_class__min_samples_split=5, forest_class__n_estimators=200;, score=0.930 total time=   0.3s\n",
      "[CV 2/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=6, forest_class__min_samples_split=5, forest_class__n_estimators=200;, score=0.941 total time=   0.3s\n",
      "[CV 3/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=6, forest_class__min_samples_split=5, forest_class__n_estimators=200;, score=1.000 total time=   0.4s\n",
      "[CV 4/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=6, forest_class__min_samples_split=5, forest_class__n_estimators=200;, score=0.965 total time=   0.4s\n",
      "[CV 5/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=6, forest_class__min_samples_split=5, forest_class__n_estimators=200;, score=0.929 total time=   0.3s\n",
      "[CV 1/5] END forest_class__criterion=gini, forest_class__max_depth=5, forest_class__min_samples_leaf=6, forest_class__min_samples_split=15, forest_class__n_estimators=50;, score=0.953 total time=   0.1s\n",
      "[CV 2/5] END forest_class__criterion=gini, forest_class__max_depth=5, forest_class__min_samples_leaf=6, forest_class__min_samples_split=15, forest_class__n_estimators=50;, score=0.929 total time=   0.1s\n",
      "[CV 3/5] END forest_class__criterion=gini, forest_class__max_depth=5, forest_class__min_samples_leaf=6, forest_class__min_samples_split=15, forest_class__n_estimators=50;, score=1.000 total time=   0.1s\n",
      "[CV 4/5] END forest_class__criterion=gini, forest_class__max_depth=5, forest_class__min_samples_leaf=6, forest_class__min_samples_split=15, forest_class__n_estimators=50;, score=0.965 total time=   0.1s\n",
      "[CV 5/5] END forest_class__criterion=gini, forest_class__max_depth=5, forest_class__min_samples_leaf=6, forest_class__min_samples_split=15, forest_class__n_estimators=50;, score=0.918 total time=   0.1s\n",
      "[CV 1/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=6, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=0.930 total time=   0.3s\n",
      "[CV 2/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=6, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=0.929 total time=   0.2s\n",
      "[CV 3/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=6, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=1.000 total time=   0.2s\n",
      "[CV 4/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=6, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=0.965 total time=   0.2s\n",
      "[CV 5/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=6, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=0.918 total time=   0.2s\n",
      "[CV 1/5] END forest_class__criterion=entropy, forest_class__max_depth=7, forest_class__min_samples_leaf=4, forest_class__min_samples_split=5, forest_class__n_estimators=50;, score=0.953 total time=   0.1s\n",
      "[CV 2/5] END forest_class__criterion=entropy, forest_class__max_depth=7, forest_class__min_samples_leaf=4, forest_class__min_samples_split=5, forest_class__n_estimators=50;, score=0.918 total time=   0.1s\n",
      "[CV 3/5] END forest_class__criterion=entropy, forest_class__max_depth=7, forest_class__min_samples_leaf=4, forest_class__min_samples_split=5, forest_class__n_estimators=50;, score=1.000 total time=   0.1s\n",
      "[CV 4/5] END forest_class__criterion=entropy, forest_class__max_depth=7, forest_class__min_samples_leaf=4, forest_class__min_samples_split=5, forest_class__n_estimators=50;, score=0.976 total time=   0.1s\n",
      "[CV 5/5] END forest_class__criterion=entropy, forest_class__max_depth=7, forest_class__min_samples_leaf=4, forest_class__min_samples_split=5, forest_class__n_estimators=50;, score=0.941 total time=   0.1s\n",
      "\n",
      "Total Time: 11.8924 seconds\n",
      "Average Fit Time: 0.2378 seconds\n",
      "Inference Time: 0.0064\n",
      "Best CV Accuracy Score: 0.9625\n",
      "Train Accuracy Score: 0.9930\n",
      "Test Accuracy Score: 0.9720\n",
      "Overfit: Yes\n",
      "Overfit Difference: 0.0209\n",
      "Best Parameters: {'forest_class__n_estimators': 100, 'forest_class__min_samples_split': 5, 'forest_class__min_samples_leaf': 2, 'forest_class__max_depth': 5, 'forest_class__criterion': 'entropy'}\n",
      "\n",
      "RandomForestClassifier Binary Classification Report\n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "      Benign     0.9670    0.9888    0.9778        89\n",
      "   Malignant     0.9808    0.9444    0.9623        54\n",
      "\n",
      "    accuracy                         0.9720       143\n",
      "   macro avg     0.9739    0.9666    0.9700       143\n",
      "weighted avg     0.9722    0.9720    0.9719       143\n",
      "\n",
      "ROC AUC: 0.9971\n",
      "\n",
      "               Predicted:0         1         \n",
      "Actual: 0                88        1         \n",
      "Actual: 1                3         51        \n",
      "\n",
      "True Positive Rate / Sensitivity: 0.9444\n",
      "True Negative Rate / Specificity: 0.9888\n",
      "False Positive Rate / Fall-out: 0.0112\n",
      "False Negative Rate / Miss Rate: 0.0556\n",
      "\n",
      "Positive Class: Malignant (1)\n",
      "Threshold: 0.5\n"
     ]
    },
    {
     "data": {
      "image/png": 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bL730khEXF2cYhmGcOXPGeOaZZ8wv2Lt3785zf+ZkwIAB5pfg4cOHG2fPnjXX/corr+SZvLraeSo/8nOcDho0yCyzc+fObNv28vIy6tevb15nGIZh7ovU1FTzeKtRo4axdOlS8727cOGCMWvWLPMHsL59+2bbdmaCwmKxGG+88Yb5HsfFxRkvvPCCVaLqWpNLmYkLSUa3bt2s3r9z584ZX331ldGhQwerOlf7UTDT0aNHzdfVrl07Y9u2bebxGxcXZwwfPtxMVixevNiqbmpqqlGnTh3zGm7+/PlGSkqKYRiG8eeffxr33Xef1Zf7G5FcunDhgplYyboP8nsN9f7775vb6Nmzp3Hs2DFzvRMnTjRf+5X71zD+OyYz39fevXsbJ06cMAwj4/Nj9OjRZmz9+vXLVr8griU9PDwMZ2dno3379mbC/dKlS8YHH3xgJlratm2ba/2CSC5duT/y+n5iGHknl77//nvDwcHBcHJyMgYPHmzs37/fSE9PN9LT041du3YZ7du3N6SM5HzmZ2CmO++805BkNG/e3NixY4c5//Lly8Yff/xhjBw5Msf/r8JGcgm4Rbz22mvmCeLff/+1eT3PP/+8eaLMPMlkdfjwYfMisFevXlbLsl7EVK5c2bh06VK2+kuWLDHLHD58ONvyG5lc2rJliyFl/OKVeQGQH3ldpNh7f13NlV+EevToYUgyXn/9dbNMenq6UbZsWUP679fOvJJLV/P2228bkowHHngg27JrTS5JMt57771cy13toj01NdVo0KCBmfy7dOmScerUKaNkyZLmxSSAoivrl/Yrf22+8pG1Bcq1JJcyv1z37NnzmmLLT3Jp8+bNZkzTpk3LsUxm8ikoKMi4fPmyOf/ChQvm+Sm3Fs9Z909eySVHR0fjl19+uabXl9WCBQsMScadd96ZbVnWc3CzZs2M9PT0bGXuu+8+s0zmjyRZpaamGuXKlTMkGaNHj76m2I4cOWJ+yR42bFiOZfr3729IGa0FMr+4ZyqM5FJ8fLxRokQJQ8r4MSuzBVjWbYeFhZmJzSt9+umn5rXIuXPnciyzbds2w2KxGC4uLmbizjAM499//zX3z/Dhw3Os26lTpzwTJbkll3bv3m3+EDR48OAc152T/CaXMpOvTzzxRK5l3nnnHUOScffdd1vN/+KLL8xtrFq1Klu9ixcvml/4b1RyKfN6S5IxceJEc35+rqEuXbpkBAQEGFJGq7ucvPfee+Z6tm3bZrUs6zH51FNP5Vg/87uJk5PTNX83yc+1ZOb3gZxaPE6fPt0s8/PPP+dY/2ZKLqWlpRkVKlTI87PcMAyjdevWhiTj5ZdfNufFxcWZr/XKz5+bDX0uAbeI06dPm38HBATYtA7DMDR//nxJ0vPPP6+QkJBsZUqVKqXnn39ekjRv3rxc1zVgwAC5u7tnm9+qVSu5uLhI+m9kuMLi5+cnSebIedfrVtxf3bp1kyTNmjXL7DthzZo1OnDggCpVqqR77733urfx0EMPSZI2bdqU73v1c+Pv76/nnnvO5vqOjo6aM2eO/P399ddff+nll19Wt27d9O+//6p06dKaPn36dcUH4PYRFxeX5+PUqVM2rTfz3HP8+PECjDbDF198ISnjXNOjR48cy4wePVqSdOrUKa1cudKc//333yshIUGS9Oqrr+ZYd8CAAfLw8LhqHC1btlTNmjWvKfasMs8b+/bty3M/DRkyJMf+D1u0aGH+PWzYsGzLHR0d9cADD0jK6LPpWixatEipqalyc3PT0KFDcyzz2muvydXVVSkpKfnqY6ignDt3TqtXr1bTpk119OhRSdLLL79s9sOTVe/evXPtUDyzz68XXnghx344Jal27dqqWrWqkpOTtWbNGnP+woULlZqaKnd3dw0cODDHujn1Q5Yfs2bNUnp6ugIDA80+bQpKYmKi5syZIynjuMrN008/LUn67bffrPrQzLyma9CggXlsZeXh4aHBgwcXZMiSMvq22rt3r0aOHGmODBgQEKAuXbpkK5vXNdTKlSt15swZSbm/Py+++KJCQ0MlydxXOXn99ddznD9o0CC5u7srNTU11/4+c5Pfa8nXXnstx+O9a9euZt+zeV1/3yzWr1+vPXv2KCgoKNfPcum/4zFrP2Pe3t7mPjh27NiNDfQ6kVwCipD9+/ebJ5rIyMhcy2UOeXv69Gnt378/xzL169fPcb6Tk5OKFSsmSea2Csudd96pypUrKyUlRfXr19e4ceO0fft2mxMgt+L+ioiIUOXKlXXw4EFzKNX8duSdVVxcnEaMGKGIiAgFBgbKycnJ7LiwSpUqkjI6azx79ux1xVu3bl0zuWarMmXK6OOPP5Ykffzxx1qyZIkcHR31+eefy9/f/7rWDeD2YWS02M/1kdvn99U8+OCDslgsWrJkiVq1aqW5c+eaiYDrtW3bNklSkyZNcvyCJUnh4eEqWbKkVXlJ+uWXXyRlfEaWK1cux7re3t6qXbv2VeNo0KDBVcucP39eb7/9tho1aqTixYvLxcXFPG9kTWBdOahGVvXq1ctxfnBwsKSML9l33HFHnmWu9byUuc/q1q0rHx+fHMv4+/urTp06VuVvlKwdBfv7+ysyMtLsPPrJJ5/MNVGY23uUlpamzZs3S8pIMoSEhOT62L17t6SMQTkyZb7eOnXq5Lp/KlasaB6D1+Knn36SlHEd5ebmds318xIbG2t2+Ny8efNcX3PVqlXNOjm97qZNm+a6jbyWXYusnfo7OTmpQoUKio6OVlJSkooVK6avv/46x+uZvK6hMuMvXbq0KlasmGMZR0dH8zXkdlyXLl3aHKnwSj4+PubnR071r/da0snJSffdd1+OyxwcHMzBf270/2RB2LhxoyQpPj5eJUqUyPV4fPbZZyVZH4vu7u5mgrNly5Z6/fXXtWXLFiUnJxf+C7kKJ3sHACB/AgMDzb/PnDmjEiVKXPM6Tpw4Yf6d10VA1lHoTpw4keNFqbe3d671nZwyPlpSUlKuOcbr4ejoqHnz5qlt27bav3+/hg4dqqFDh8rDw0P33nuv2rVrpy5duuTrV1rp1t1fXbt21ZAhQxQTE6N69erpyy+/lKOjo/lryNVs2rRJDz74oM6dO2fOyxzNwmKxKC0tzfyF/+LFiwoKCrI51uLFi9tcN6uoqChFRUWZv5wNHDhQ999/f4GsGwDy0rBhQ40bN06vvfaali9fruXLl0vKODdERkbq6aefthrd6lpknoeu9sW9VKlS+vfff63OWydPnpSkq14v5CcpcLXP6r///lsPPPCAVeLIw8NDfn5+ZlIss1XIxYsXc11PbufKzPPkjTiXXss+zlr+RslMkkkyR/aqWbOmOnfunOdxlNt7dObMGSUlJUnKf+Lt0qVL5t/Xegxei8xWbGFhYddULz+yJnhzG9X3Stf6uq82anN+eXp6mq3OHBwc5OXlpTvuuEMPPPCAunXrZvUdIKu8/i8L6ri+Wv3M5VfWL4hrycyRMa912zejzOMxJSUlX8fj5cuXrZ5Pnz5drVu31m+//abRo0dr9OjRcnFxUd26dfXoo4+qe/fuNt/ZUpBouQTcIrL+svLrr7/aMZKb2913361du3Zp0aJF6tmzp+666y5dvnxZq1at0osvvqjKlSsX+u16he2pp56So6OjFi9erA8//FCXL19Wy5YtzabPeUlNTVWnTp107tw51ahRQ999950SEhJ0/vx5xcXF6fjx4+YvoJKue9hnR0fH66qf6cCBA1q1apX5fOPGjdd9yx4A5NegQYO0f/9+TZw4UW3atFHx4sV15MgRzZw5U02bNlX79u0L/QeXTDndZnatrvZZ3bVrVx05ckRly5bVggULdPr0aV28eFEnTpzQ8ePHrZIO13veuN0dP37cfBw8eFCxsbGaPn36VROUub1HWc+Fy5Ytu2oLPsMwbL7N7VoVxLGZm6yv+/Lly/l63ZktYQrbwIEDzff86NGj+vvvv7V8+XINGjQo18SSVHDXUAWtsK8lbwWZx2P9+vXzdSxeuU/KlCmjX375RcuXL1efPn1Uu3Ztpaena+PGjRo8eLDKly+vH374wR4vzQrJJeAWkbVJ/OLFi21aR9ZfOPJqlp51WUG1LMmvzF8eM5sy5yQ+Pj7Pdbi4uKhdu3aaNm2aduzYoZMnT+rDDz9UQECADh8+nON96zm5FfZXTkJDQ9WyZUtdvnxZw4cPl5T/W+I2bdqkgwcPytHRUd98841atWqV7ZfiG9GvyPXIvIiJj49XxYoV5erqqg0bNpj9kABAYShRooT69u2rxYsXKy4uTr///rvZt8bChQv1wQcfXPM6M88peZ2Dsi7Peg7KvOX6arfoXWtrkysdPnzYvL1p7ty5euyxx7L9gn6znTeyup59fCvIvB1Jsr7VJr8yX+/VjhNbjqPMvixtiSu/67Z1/fl53df7v3MjFdRxnd/3PWv9grqWPHXqVJ63fuW07ZtVQRzrDg4OatGihSZNmqRt27bpzJkzmj17tsqUKaOzZ8/qiSeesPutciSXgFtEcHCwoqKiJGV0uvf333/nu25m9rtcuXLmBV9mfzw5yWwBEhgYmGs/DTdK5j3lhw8fzrXMli1brmmdgYGBeu655zRu3DhJGS2/8tPh962wv3KT2bF3cnKygoKC1Lp163zVy9zvxYoVy7UpdNYWQlfKTIAW5q9QI0aM0ObNm+Xh4aGvvvrKfJ/feOMNbdiwodDiAICsqlWrpo8//tjsCydrZ9tS/j4vM/v5WbNmjdLT03Mss2vXLvNLVt26dc35tWrVkpTxZebAgQM51r1w4YLZn4+tsp6vc+v0O6/zhr1l7Usptx+vzp07Z9U3063E2dnZ7Mtq6dKl11w/6/65cOFCjmX27Nlz1SRGTjIHGVm5cmWePypeKWv/Y7n9/2Ttj+h6XnfWzs2vdDO0FMlNZvxHjhzJ9TtDWlqa+fpyO64PHz6sffv25bjs/Pnz5udH5vYy60i2X0tmSk1N1Y8//pjjMsMwtG7dumzbvlGu9/o28zxw/PjxAusjytvbW0888YTZYX9cXJzd784guQTcQt544w15eXnp8uXLateu3VV/TTh79qyioqLMiyWLxaIOHTpIkqZNm5bjrwZHjx7VtGnTJEmdOnUq4FdwdXfffbcZR05JpBMnTpidN18ps0+B3GQdrS23jlGzuhX2V24eeeQRDRo0SAMGDNC7774rZ2fnfNXLHEUmc/SkKx05ckTvvfdervUzO/vMeo/9jbRmzRqNHTtWkjRx4kSFh4fr5Zdf1kMPPaS0tDR17tz5ujsdB4C85Pfcc+V5Jz+flx07dpSU8Qt9bqNfZo7kFBQUZDX4RPPmzc1tvPnmmznWnThxolU/M7bIOvrYb7/9lm35+fPn9cYbb1zXNm6kqKgoOTk5KTEx0fxx4kpvvvmmkpKS5OzsbP7Qdyvp2bOnJOm7777Td999l2fZKwcXiYqKkqOjoy5fvqzx48fnWGfUqFE2xfXMM8/I0dFRp0+f1ogRI/JdL2vH4rn9/3h6euqJJ56QJI0bN06HDh3Kc51Xvu7M678NGzZo7dq12cpfvnxZb7/9dr5jLmzNmjUzb6nL7TbHadOmmS0b87qGza0l+IQJE3T58mU5OTlZ/V9c77VkVv/73/9yTKzPmjXLTGJlvlc30vVe3zZp0sTsGL1fv35XbWGU9Xi8Wtlr/X5zI5FcAm4hFStW1GeffSYXFxf9+eefqlGjhsaNG6e9e/eaZdLS0vTrr7/q9ddf1x133KEvv/zSah2vvPKK/Pz8dObMGUVGRppN2aWMfmoiIyN17tw5BQQE5Dok74107733mh07dunSRdu2bZNhGEpPT9fatWvVuHHjXH+9nTdvnho0aKBp06bpn3/+MeenpaVpxYoV5uuJiIjI9yhiN/v+yo2zs7PeeustjR8/Xp07d853vYYNG8rT01OGYejxxx83f+3K3IeNGzfOs4+Eu+66S5KUkJCg+fPnX9+LuIrTp0/rqaeeUnp6utq1a2dePEtSTEyMQkNDdejQIXPkDQC4Edq0aaNu3bpp2bJlVl88zpw5ozfeeMNs+Zo59HamzM/L7777Ltcfi+rVq2d+aXvppZc0efJkMxl0/PhxPfvss1qwYIGkjC+AWUfc8vT0NIdg//jjjzV48GDzC8v58+c1btw4RUdHX/eomuHh4SpTpoykjFazWVtCbdq0SY0bN76pk/wlS5bUyy+/LEkaO3asRowYYb6P586d0/Dhw80kQv/+/fPVf+HN5sknn1RkZKQMw1Dbtm31xhtvWN0uefHiRa1Zs0a9evXKNhpfyZIl1atXL0kZx9iYMWN0/vx5SRmdxvfu3Vuff/65VZIxv8qXL69BgwZJkt566y316NFDe/bsMZcnJCToiy++UNu2ba3qVaxY0WyVNH369Fxbk7z55psqUaKETp06pYiICH322Wdm7JnxL1q0SG3bts2WXImKijJb/2UOGJLZb87OnTvVqlUrs9P8m5G7u7uZVJo7d66ef/55M9Fz6dIlvffee+rbt6+kjORMbqNG+vr6atasWXr55ZfNDrjPnz+vN99800wq9urVy2rggOu9lszk4eGhDRs26IknnjBbxiUmJuqjjz7SCy+8IEl69NFHcx1lsiBlfl7/+eefVt8F8svJyUkffvihnJyctGHDBt1///1avXq1VV98//zzjz788EPVrVtXU6dONef/9NNPql69uiZOnKidO3ea34MMw9BPP/1k7otSpUqpevXq1/Myr58B4JazYcMGo3z58oYk8+Hi4mIEBAQYDg4O5jyLxWJ06tTJSE5Otqq/du1aw9fX1yzn6elpeHp6ms/9/PyM9evXZ9vu/v37zTL79+/PNb6wsDBDkhETE5NtWaNGjQxJxogRI3Ktv3z5csPZ2dncloeHh+Hm5mZIMipUqGDMnTvXXJZVTEyM1T5xdXU1AgMDrfZJiRIljJ07d1rVW7NmTY7ruxn219Vkrv9a62a+D126dMm27IMPPrDaj15eXub+DwoKMpYsWZLn63rggQfM5d7e3kZYWJgRFhZmTJw40SzTpUuXXLefVV77sHXr1oYko3Tp0saZM2ey1V25cqVhsVgMScZHH32Uj70C4HYzYsSIPD/fs8r6eXMt56/M+ZkPHx8fw8fHx2reY489ZqSlpVnV+/vvv83PVgcHByM4ONj8vDx8+LBZ7ty5c1bbcHJyMvz9/c3PN0nGwIEDc3xNKSkpxmOPPWaWc3BwMPz9/Q1HR0dDkvHUU08ZTz/9tCHJeO6557LVz+/5aenSpYaTk5PVedvDw8M8Z65atcpctmbNGqu6VzsHG8Z/5/ewsLBcy2S+140aNcoz1pwkJSUZjz/+eLb9lPX6IafrKcPI/7k+L9dynNq67fj4eOPhhx/Odqz6+flZHUtOTk7Z6l6+fNmIjIw0yzg6Olodg0OGDMnz+i6v4yg1NdXo1atXtuuOrOv39fXNVq979+5Wx1uZMmWMsLAwY8CAAVbl/vrrL6NixYpW721AQIDVdZwkIzIyMts29u3bZ5QuXdrqujLzetDFxcX4+uuvcz2u8yOzbl7XxDnJ7zWUYRhGv379rL4X+Pv7W/2vNmnSxEhISMhWL+v/0+DBg63qZ35+ZO63y5cvZ6t/PdeSWf/fJ0+ebB4H/v7+Vt8P7r77buPUqVPZtp3X54Wty1JSUoxKlSqZ2/b39zc/rxcsWGCWu9p7s3jxYsPb29tcj7OzsxEYGGi4urpa7a833njDrJP1MzJrnazvo4+PT47fRQobLZeAW1CDBg20a9cuzZ07V507d1b58uXl5uam8+fPKyAgQA0bNtSrr76qnTt3as6cOdluiWrUqJF27typAQMGKDw8XOnp6TIMQ+Hh4Ro4cKB27typ++67z06vTmrRooV+/PFHPfzww/L391daWppKly6toUOHKjY21qqTxqxat26tTz/9VF27dtXdd98tX19fxcfHy9vbW/Xq1dPo0aP1559/qnLlytcUz82+vwra888/r2+//VaNGzeWl5eXUlNTVbJkSb300kv67bffVK1atTzrL1y4UP369VPFihWVkpKigwcP6uDBgwV6q9yUKVO0ZMkSOTg46PPPP8/xl/fIyEjzF9G+fftq586dBbZ9AMj0/vvva9y4cXrwwQdVoUIFGYahy5cvq0SJEmrdurUWLVqkBQsWZLtdoUKFClqzZo1at26tYsWK6fTp0+bnZWpqqlnO19dXq1ev1owZM9S4cWN5e3vrwoULCgkJUVRUlNasWZPr7TlOTk6aP3++pk+frnr16snd3V2pqamqU6eOpk+frk8//dT8bPbz87N5Hzz88MNav369HnroIfn5+Sk1NVVBQUHq2rWrYmNj9cADD9i87sLg4uKiL774QgsXLlSrVq0UGBio8+fPKzAwUK1atdKXX36Z4/XUrcTHx0dLly7Vd999pw4dOqhMmTJKSkrSpUuXVLJkSTVv3lxjxozR7t27s9V1c3PTsmXLNGnSJNWoUUMuLi4yDEP33Xef5s+fb96ebgtHR0dNnjxZGzZsUOfOnVWmTBmlpKTIMAxVqVJF3bt316JFi7LVmzJliqKjo81rkkOHDungwYNm65pM4eHh+v333zVt2jQ1b95cQUFBSkhIkGEYKl++vNq3b6+PPvoox9bWd9xxh7Zv367+/furXLlyMgxDbm5ueuyxx/TTTz/luz9Le3rnnXf0ww8/KCoqSsHBwbpw4YK8vb3VpEkTffLJJ1q5cmW2zravNG7cOM2bN08NGzaUYRhycXFRjRo1NGnSJC1fvtyqxWSm672WzNSrVy+tWLFCLVu2lIODgxwcHFS5cmWNGjVKmzZtynM0vYLk5OSk1atXq0ePHipXrpwuXrxofl7n1hdZTtq0aaO9e/dqxIgRqlevnry8vHTu3Dm5urrq7rvvVo8ePbR48WLz+lXK6A9r/vz5euGFF1S7dm3zGHZzc1ONGjU0ePDgm+a7iMUwisDYfwAAAACsGIahMmXK6MiRI/r000/11FNP2TskAMAtipZLAAAAQBH02Wef6ciRI3JycrLqDBwAgGtFcgkAAAC4TXXq1EkLFy60ul0oLi5OY8eONQc8ePrpp2/JjqoBADcPbosDAAAAblN+fn6Kj4+XlDH6krOzs/lcku677z598803VsO7AwBwrUguAQAAALepTz/9VMuWLdOvv/6qEydO6MKFC/Lz81ONGjXUsWNHPfXUU7d0R9UAgJsDySUAAAAAAADYjD6XAAAAAAAAYDOSSwAAAAAAALAZySUAAAAAAADYjOQSAAAAAAAAbEZyCQAAAAAAADYjuQQAAAAAAACbkVwCAAAAAACAzUguAQAAAAAAwGYklwAAAAAAAGAzkksAAAAAAACwGcklAAAAAAAA2IzkEgAAAAAAAGxGcgkAAAAAAAA2I7kEAAAAAAAAmznZOwDYT3p6uo4ePSpvb29ZLBZ7hwMAgCTJMAydP39eJUqUkIMDv4PdzrgWAQDg5pbf6zKSS0XY0aNHVbp0aXuHAQBAjg4fPqxSpUrZOwzcQFyLAABwa7jadRnJpSLM29tbkuRSpYssji52jga49R1aO97eIQC3hfMJCSpfrrR5nsLtK/M9Pnz4sHx8fOwcDYACsX271KiRtG6dVKOGvaMBcJ0SEhJUuvTVr8tILhVhmc3PLY4uJJeAAsAXI6BgcZvU7S/zPfbx8eEzFLhdeHn9N+X/GrhtXO26jI4MAAAAAAAFw8lJCgrKmAIoMviPBwAAAAAUjOrVpZMn7R0FgEJGyyUAAAAAAADYjJZLAAAAAFCA0tLSlJKSYu8w7GPPHqlXL2nKFKlCBXtHA+AqnJ2d5ejoeN3rIbkEAAAAAAXAMAwdP35c586ds3co9pOeLr3ySsZ0/357RwMgH/z8/BQSEnJdg6mQXAIAAACAApCZWCpevLg8PDyK5qiXly5JKSlS6dKSh4e9owGQB8MwdOnSJZ04cUKSFBoaavO6SC4BAAAAwHVKS0szE0uBgYH2Dsd+0tIypq6ukpubfWMBcFXu7u6SpBMnTqh48eI23yJHh94AAAAAcJ0y+1jyoLUOgFtM5ufW9fQVR3IJAAAAAApIkbwVLis3t4yOvGm1BNwyCuJzi+QSAAAAAKBgODpKvr4Z03yyWCz66quvblxMt6nGjRurb9++hbKtK9+jXbt26Z577pGbm5tq1KihAwcOyGKxaPv27YUST0GIjo5WjRo1rns9Vzt+r9w3a9eulcViMTv+nzlzpvz8/K57O/ZGn0sAAAAAcAOdPHlSCQkJhbY9Hx8fFStWLN/ln3nmGc2aNUuS5OTkpFKlSql9+/YaNWqU3K61BVJysnTqlBQUJLm4XFvdGyyn1hkNGjTQhg0b7BBNBovFosWLF6tNmzZW85OTk/Xuu+9q9uzZ2rNnjzw8PFSpUiX16NFDTz75pJydnQs1zmPHjsnf3998PmLECHl6emr37t3y8vKSn5+fjh07pqCgoALfdnR0tEaOHClJcnR0VKlSpdS2bVuNHj1aXl5eBb69gla6dOk8902HDh304IMPms+jo6P11VdfZUvUXfke3GxILgEAAADADXLy5Ek92bWHzpy/VGjbDPD20Ocx068pwdSyZUvFxMQoJSVFsbGx6tKliywWi8aNG3dtG09JkY4ezWi9dJMllyQpJiZGLVu2NJ+7XEeMKSkpNyTJk5ycrBYtWui3337T6NGj1aBBA/n4+Gjz5s0aP368atasWSAtbq5FSEiI1fN9+/bpoYceUlhYWK5lrlVycnKu70fVqlW1atUqpaamauPGjerWrZsuXbqkadOmXdN67MHR0THPfePu7m52qp2X692/Nxq3xQEAAADADZKQkKAz5y+pWESUyj704g1/FIuI0pnzl665pZSrq6tCQkJUunRptWnTRpGRkVq5cqW5/PTp0+rUqZNKliwpDw8PVatWTXPnzrVaR+PGjdVn4EANfu89BZQurZCQEEVHR1uV2bNnj+6//365ubmpSpUqVtvItGPHDjVt2lTu7u4KDAxUz549deHCBXP5M888ozZt2ujNN99UcHCw/Pz8NGrUKKWmpmrQoEEKCAhQqVKlFBMTk23dfn5+CgkJMR8BAQGSpPT0dI0aNUqlSpWSq6uratSooeXLl5v1Mm9t+uKLL9SoUSO5ublp9uzZkqTp06crPDxcbm5uqly5sqZOnWrWS05OVu/evRUaGio3NzeFhYVpzJgxkqSyZctKktq2bSuLxWI+f/fdd7V+/XqtXr1avXr1Uo0aNXTHHXfoiSee0JYtW1ShQoUc38PPPvtMderUkbe3t0JCQvTEE0+YQ8xL0tmzZ9W5c2cVK1ZM7u7uqlChgrmP8opTsr4ly2KxKDY2VqNGjZLFYlF0dHSOt8X98ccfatWqlby8vBQcHKynnnpKp06dMpc3btxYvXv3Vt++fRUUFKQWLVrk+LqkjBZ1ISEhKlWqlDp06KDOnTtryZIlkv67vW369OkqV66c2dru0KFDevTRR+Xl5SUfHx89/vjjiouLy7buadOmqXTp0vLw8NDjjz+u+Ph4c9nWrVvVrFkzBQUFydfXV40aNdIvv/ySbR3Hjh1Tq1at5O7urjvuuEMLFy40l13tlsGst8XNnDlTI0eO1G+//SaLxSKLxaKZM2dmew8k6fDhw3r88cfl5+engIAAPfroozpw4IC5fO3atapXr548PT3l5+enBg0a6ODBg7nu4+tFyyUAAAAAuME8A4LlU7xUoWzr5HXW/+OPP/TTTz9ZtUpJTExU7dq1NWTIEPn4+Ojbb7/VU089pTvvvFP16tUzy82aM0f9O3bUljVrtOm33/TMM8+oQYMGatasmdLT09WuXTsFBwdry5Ytio+Pz9Zn0MWLF9WiRQtFRERo69atOnHihHr06KHevXubX7Il6YcfflCpUqW0fv16bdy4Ud27d9dPP/2k+++/X1u2bNEXX3yh5557Ts2aNVOpUlff75MmTdKECRM0bdo01axZU5988olat26tP//80yqZM3ToUE2YMEE1a9Y0E0yvv/66Jk+erJo1a+rXX3/Vs88+K09PT3Xp0kXvvfeelixZovnz56tMmTI6fPiwDh8+LCkjcVG8eHGzNVXmEPCzZ89WZGSkatasmS1OZ2fnXFtLpaSkaPTo0apUqZJOnDih/v3765lnntF3330nSRo+fLj++usvLVu2TEFBQdq7d68uX74sSXnGeaVjx44pMjJSLVu21MCBA+Xl5WWVNJKkc+fOqWnTpurRo4cmTpyoy5cva8iQIXr88cf1ww8/mOVmzZqlF154QRs3brzqe5SVu7u7kpOTzed79+7VokWL9OWXX8rR0VHp6elmYmndunVKTU1Vr1691KFDB61du9aq3vz587V06VIlJCSoe/fuevHFF83E4fnz59WlSxe9//77MgxDEyZM0IMPPqg9e/bI29vbXM/w4cM1duxYTZo0SZ999pk6duyoHTt2KDw8/JpeV4cOHfTHH39o+fLlWrVqlSTJ19c3W7mUlBTz/+THH3+Uk5OT3njjDbVs2VK///67HBwc1KZNGz377LOaO3eukpOT9fPPP9/QAQdILgEAAABAEffNN9/Iy8tLqampSkpKkoODgyZPnmwuL1mypAYOHGg+f+mll7RixQrNnz/fKrlUvWpVjXj2Wal8eVW4+25NnjxZq1evVrNmzbRq1Srt2rVLK1asUIkSJSRJb775plq1amXWnzNnjhITE/Xpp5/K09NTkjR58mQ98sgjGjdunIKDgyVJAQEBeu+99+Tg4KBKlSrprbfe0qVLl/TKK69IkoYNG6axY8dqw4YN6tixo7n+Tp06mUkcSfr888/Vpk0bjR8/XkOGDDHLjhs3TmvWrNG7776rKVOmmOX79u2rdu3amc9HjBihCRMmmPPKlSunv/76S9OmTVOXLl106NAhVahQQQ0bNpTFYrFK2GXetpjZmirTnj171Lhx4/y9cVl069bN/PuOO+7Qe++9p7p16+rChQvy8vLSoUOHVLNmTdWpU0fSfy2nJOUZ55VCQkLk5OQkLy8vM+4rk0uZybY333zTnPfJJ5+odOnS+vvvv1WxYkVJUoUKFfTWW29d0+uMjY3VnDlz1LRpU3NecnKyPv30U3Ofrly5Ujt27ND+/ftVunRpSdKnn36qqlWrauvWrapbt64kmcdayZIlJUnvv/++HnroIU2YMEEhISFW25Ckjz76SH5+flq3bp0efvhhc3779u3Vo0cPSdLo0aO1cuVKvf/++1at2PLD3d1dXl5eZkut3HzxxRdKT0/X9OnTzYRRTEyM/Pz8tHbtWtWpU0fx8fF6+OGHdeedd0rSNSe6rhW3xQEAAABAEdekSRNt375dW7ZsUZcuXdS1a1dFRUWZy9PS0jR69GhVq1ZNAQEB8vLy0ooVK3To0CGr9VSvXl0KCJCcMtoxhIaGmrdm7dy5U6VLlzYTS5IUERFhVX/nzp26++67zcSSlNHpdnp6unbv3m3Oq1q1qhwc/vs6GxwcrGrVqpnPHR0dFRgYaHVbmCRNnDhR27dvNx/NmjVTQkKCjh49qgYNGliVbdCggXbu3Gk1LzMxI2W0stq3b5+6d+8uLy8v8/HGG29o3759kjJu4du+fbsqVaqkPn366Pvvv8+2769kGMZVy+QkNjZWjzzyiMqUKSNvb281atRIksz36IUXXtC8efNUo0YNDR48WD/99JNZ15Y48/Lbb79pzZo1VvulcuXKkmTuG0mqXbt2vta3Y8cOeXl5yd3dXfXq1VNERIRV8jMsLMyqj7HMYy0zsSRJVapUkZ+fn9V7WqZMGTOxJGUcj1mPtbi4OD377LOqUKGCfH195ePjowsXLmQ77q88jiMiIrIdOwXpt99+0969e+Xt7W3u34CAACUmJmrfvn0KCAjQM888oxYtWuiRRx7RpEmTdOzYsRsWj0TLJQAAANymCnuErut1rSN8AQXJ09NT5cuXl5TRwuTuu+/WjBkz1L17d0nS22+/rUmTJundd99VtWrV5Onpqb59+1rdmiRJzm5u0h13mM8tFovS09MLPN4rbw2zWCw5zrty2yEhIebrzHQtnxNZk16Z/UB9/PHHql+/vlW5zNZRtWrV0v79+7Vs2TKtWrVKjz/+uCIjI6365LlSxYoVtWvXrnzHJP13O2GLFi00e/ZsFStWTIcOHVKLFi3M96hVq1Y6ePCgvvvuO61cuVIPPPCAevXqpfHjx9sUZ14uXLhgtja7UmhoqPl31v2Zl0qVKmnJkiVycnJSiRIlsnXYnd/1XKsuXbro9OnTmjRpksLCwuTq6qqIiIhsx31hu3DhgmrXrm3evpdV5nkkJiZGffr00fLly/XFF1/otdde08qVK3XPPffckJhILgEAAOC2Y48Ruq6XLSN8ATeCg4ODXnnlFfXv319PPPGE3N3dtXHjRj366KN68sknJWV0gP3333+rSpUq1pUNQ0pMzBgpzsH6Rpnw8HAdPnxYx44dMxMMmzdvzlZm5syZunjxopkw2Lhxo3n7243g4+OjEiVKaOPGjWZrn8ztZr3l70rBwcEqUaKE/vnnH3Xu3DnP9Xfo0EEdOnTQY489ppYtW+rMmTMKCAiQs7Oz0tLSrMo/8cQTeuWVV/Trr79m63cpJSVFycnJ2ZIpu3bt0unTpzV27Fiztc62bduyxVKsWDF16dJFXbp00X333adBgwZp/PjxV43zWtWqVUuLFi1S2bJl5eR0/WkHFxeXbEnBvGQea4cPHzb3x19//aVz585ZHbOHDh3S0aNHzdZ0mzdvtjrWNm7cqKlTp+rBBx+UlNGJ9pW3AGbWe/rpp62e59RnVn64uLhkOyauVKtWLX3xxRcqXry4fHx8ci1Xs2ZN1axZU8OGDVNERITmzJlDcgkAAACFp2zZsjmOKvPiiy9qypQpSkxM1IABAzRv3jwlJSWpRYsWmjp1qtkfir1lHaHLM+DmiCkvF8/E6eSmRUpISCC5hJtC+/btNWjQIE2ZMkUDBw5UhQoVtHDhQv3000/y9/fXO++8o7i4uOzJpdRU6Y8/pPBw6YoESGRkpCpWrKguXbro7bffVkJCgl599VWrMp07d9aIESPUpUsXRUdH6+TJk3rppZf01FNP3dDPl0GDBmnEiBG68847VaNGDcXExGj79u05tgzJauTIkerTp498fX3VsmVLJSUladu2bTp79qz69++vd955R6GhoapZs6YcHBy0YMEChYSEmKODlS1bVqtXr1aDBg3k6uoqf39/9e3bV99++60eeOABjR49Wg0bNpS3t7e2bdumcePGacaMGapRo4ZVHGXKlJGLi4vef/99Pf/88/rjjz80evRoqzKvv/66ateurapVqyopKUnffPON2Q/P1eK8Vr169dLHH3+sTp06afDgwQoICNDevXs1b948TZ8+3arfqxshMjJS1apVU+fOnfXuu+8qNTVVL774oho1amR1a6Obm5u6dOmi8ePHKyEhQX369NHjjz9u9ndUoUIFcxS+hIQEDRo0SO7u7tm2t2DBAtWpU0cNGzbU7Nmz9fPPP2vGjBk2xV62bFnt379f27dvV6lSpeTt7S1XV1erMp07d9bbb7+tRx991Bzl8ODBg/ryyy81ePBgpaSk6KOPPlLr1q1VokQJ7d69W3v27LFKgBU0kksAAADIZuvWrVa/nP7xxx9q1qyZ2rdvL0nq16+fvv32Wy1YsEC+vr7q3bu32rVrd80j/txohTlC1/W63hG+cHO7eCb7EOg383acnJzUu3dvvfXWW3rhhRf02muv6Z9//lGLFi3k4eGhnj17qk2bNlbDtl+Ng4ODFi9erO7du6tevXoqW7as3nvvPbVs2dIs4+HhoRUrVujll19W3bp15eHhoaioKL3zzjsF8rpy06dPH8XHx2vAgAE6ceKEqlSpoiVLlliNFJeTHj16yMPDQ2+//bYGDRokT09PVatWzRwFz9vbW2+99Zb27NkjR0dH1a1bV999953ZX9SECRPUv39/ffzxxypZsqQOHDggV1dXrVy5UhMnTtS0adM0cOBAeXh4KDw8XH369NFdd92VLY5ixYpp5syZeuWVV/Tee++pVq1aGj9+vFq3bm2WcXFx0bBhw3TgwAG5u7vrvvvu07x58/IV57XKbAk2ZMgQNW/eXElJSQoLC1PLli1tXue1sFgs+vrrr/XSSy/p/vvvl4ODg1q2bKn333/fqlz58uXVrl07Pfjggzpz5owefvhhq064Z8yYoZ49e6pWrVoqXbq03nzzTauO7TONHDlS8+bN04svvqjQ0FDNnTs3e+I1n6KiovTll1+qSZMmOnfunGJiYvTMM89YlfHw8ND69es1ZMgQtWvXTufPn1fJkiX1wAMPyMfHR5cvX9auXbs0a9YsnT59WqGhoerVq5eee+45m2LKD4tha29huOUlJCTI19dXrtWelcXR5eoVAOTp7NbJVy8E4KoSEhIUHOir+Pj4PJt6o3D17dtX33zzjfbs2WO2rpkzZ44ee+wxSRm3ZISHh2vTpk35bnKfeS1yI97rffv2qWO351X2oRdvieRSwokjOvDtVM375ENzZB/cWhITE7V//36VK1dObm5u5nx73KJp11ssL16Udu7MseUSgJtTbp9fUv7P1bRcAgAAQJ6Sk5P1+eefq3///rJYLIqNjVVKSooiIyPNMpUrV1aZMmWuKbkEFAXFihXT5zHTC7VzeTqHB1DYSC4BAAAgT1999ZXOnTtnNss/fvy4XFxcsvXFERwcrOPHj+e6nqSkJCUlJZnPb6WR3IDrUaxYMZI9AG5rN/5mRwAAANzSZsyYoVatWpmj6dhqzJgx8vX1NR+ZI/gAuI14ekp16nBLHFDEkFwCAABArg4ePKhVq1apR48e5ryQkBAlJyfr3LlzVmXj4uLMEXZyMmzYMMXHx5uPw4cP36iwAQBAISK5BAAAgFzFxMSoePHieuihh8x5tWvXlrOzs1avXm3O2717tw4dOqSIiIhc1+Xq6iofHx+rB4DbTGJiRofeiYn2jgRAIaLPJQAAAOQoPT1dMTEx6tKli5yc/rts9PX1Vffu3dW/f38FBATIx8dHL730kiIiIujMGyjq0tIyRoxLS7N3JAAKEcklAAAA5GjVqlU6dOiQunXrlm3ZxIkT5eDgoKioKCUlJalFixaaOnWqHaIEAAD2RnIJAAAAOWrevLkMw8hxmZubm6ZMmaIpU6YUclQAAOBmQ59LAAAAAAAAsBnJJQAAAABArtauXSuLxZJthMgcubpK5cplTK/TzJkz5efnd13rOHDggCwWi7Zv355rmWt6fQByRHIJAAAAAIooi8WS5yM6OvraVujkJAUGZkxvc7///rvuu+8+ubm5qXTp0nrrrbeuWienfTxv3jyrMmvXrlWtWrXk6uqq8uXLa+bMmdnWM2XKFJUtW1Zubm6qX7++fv75Z6vliYmJ6tWrlwIDA+Xl5aWoqCjFxcVd1+sF8kJyCQAAAACKqGPHjpmPd999Vz4+PlbzBg4ceG0rTEmRTpxQ8sWLNybgm0RCQoKaN2+usLAwxcbG6u2331Z0dLQ++uijq9aNiYmx2sdt2rQxl+3fv18PPfSQmjRpou3bt6tv377q0aOHVqxYYZb54osv1L9/f40YMUK//PKL7r77brVo0UInTpwwy/Tr109Lly7VggULtG7dOh09elTt2rUr0H0AZEVyCQAAAACKqJCQEPPh6+sri8ViNc/Ly8ssGxsbqzp16sjDw0P33nuvdu/ebS6Ljo5WjRo1NP2jj1SuZk25eXtLks6dO6cePXqoWLFi8vHxUdOmTfXbb7+Z9X777Tc1adJE3t7e8vHxUe3atbVt2zarGFesWKHw8HB5eXmpZcuWOnbsmLksPT1do0aNUqlSpeTq6qoaNWpo+fLleb7m7777ThUrVpS7u7uaNGmiAwcOXPN+mz17tpKTk/XJJ5+oatWq6tixo/r06aN33nnnqnX9/Pys9rGbm5u57MMPP1S5cuU0YcIEhYeHq3fv3nrsscc0ceJEs8w777yjZ599Vl27dlWVKlX04YcfysPDQ5988okkKT4+XjNmzNA777yjpk2bqnbt2oqJidFPP/2kzZs3X/NrBfKD5BIAAAAA4KpeffVVTZgwQdu2bZOTk5O6detmtXzv3r1a9PXX+vKtt7R90yZJUvv27XXixAktW7ZMsbGxqlWrlh544AGdOXNGktS5c2eVKlVKW7duVWxsrIYOHSpnZ2dznZcuXdL48eP12Wefaf369Tp06JBVa6pJkyZpwoQJGj9+vH7//Xe1aNFCrVu31p49e3J8DYcPH1a7du30yCOPaPv27erRo4eGDh2arZzFYsnxdrRMmzZt0v333y8XFxdzXosWLbR7926dPXs2z/3Yq1cvBQUFqV69evrkk0+sRuXctGmTIiMjrcq3aNFCm/5/fyYnJys2NtaqjIODgyIjI80ysbGxSklJsSpTuXJllSlTxiwDFLTb/0ZYAAAAALCnY8cyHln5+2d0fJ2YKP31V/Y6tWplTHfvlq68xaxsWSkgQDp5Ujp82HqZt7dUoUKBhZ7V//73PzVq1EiSNHToUD300ENKTEw0W94kJyfr048+UrFTp6TwcG3YsEE///yzTpw4Idf/7+B7/Pjx+uqrr7Rw4UL17NlThw4d0qBBg1S5cmVJUoUrYk9JSdGHH36oO++8U5LUu3dvjRo1ylw+fvx4DRkyRB07dpQkjRs3TmvWrNG7776rKVOmZHsNH3zwge68805NmDBBklSpUiXt2LFD48aNsypXqVIl+fr65rovjh8/rnLlylnNCw4ONpf5+/vnWG/UqFFq2rSpPDw89P333+vFF1/UhQsX1KdPH7Nu5nqyrjchIUGXL1/W2bNnlZaWlmOZXbt2metwcXHJ1hl6cHCwjh8/nutrAq4HySUAAAAAuJGmTZNGjrSe17mz9Pnn0pEjUu3a2etktmZ55hnpyluZPvtMevJJaf58qXdv62XNm0tZ+ucpSNWrVzf/Dg0NlSSdOHFCZcqUkSSFhYWpWLFi0qlTkjJuebtw4YICAwOt1nP58mXt27dPktS/f3/16NFDn332mSIjI9W+fXszkSRJHh4eVs9DQ0PNvoUSEhJ09OhRNWjQwGr9DRo0sLr1LqudO3eqfv36VvMiIiKylctM1BS04cOHm3/XrFlTFy9e1Ntvv20ml4BbFcklAAAAALiRnntOat3ael5my5ZSpaTY2NzrzpyZc8slSXr8cenKxMj/93V0I2S9Xc1isUjK6PMok6enp+ToKPn4SI6OunDhgkJDQ7V27dps68psVRMdHa0nnnhC3377rZYtW6YRI0Zo3rx5atu2bbZtZm43621k9hISEpJt9LXM5yEhIfleT/369TV69GglJSXJ1dU11/X6+PjI3d1djo6OcnR0zLFM5nZDQkKUnJysc+fOWbVeyloGKGgklwAAAADgRgoNzXjkxM3tv1vgclKpUu7LihXLeNxM3NykihUlSbVq1dLx48fl5OSkspkJsRxUrFhRFStWVL9+/dSpUyfFxMSYyaW8+Pj4qESJEtq4caN5u54kbdy4UfXq1cuxTnh4uJYsWWI1z5ZOriMiIvTqq68qJSXFTICtXLlSlSpVyvWWuJxs375d/v7+5m2DERER+u6776zKrFy50mxd5eLiotq1a2v16tXmKHPp6elavXq1ev9/K7batWvL2dlZq1evVlRUlCRp9+7dOnToUI6ttICCQIfeAAAAAICCYRhSWppkGIqMjFRERITatGmj77//XgcOHNBPP/2kV199Vdu2bdPly5fVu3dvrV27VgcPHtTGjRu1detWhYeH53tzgwYN0rhx4/TFF19o9+7dGjp0qLZv366XX345x/LPP/+89uzZo0GDBmn37t2aM2dOjh13V65cWYsXL851u0888YRcXFzUvXt3/fnnn/riiy80adIk9e/f3yyzePFisy8pSVq6dKmmT5+uP/74Q3v37tUHH3ygN998Uy+99JJVfP/8848GDx6sXbt2aerUqZo/f7769etnlunfv78+/vhjzZo1Szt37tQLL7ygixcvqmvXrpIkX19fde/eXf3799eaNWsUGxurrl27KiIiQvfcc0++9y1wLWi5BAAAAAAoGJcuSTt3SuHhsnh66rvvvtOrr76qrl276uTJkwoJCdH999+v4OBgOTo66vTp03r66acVFxenoKAgtWvXTiOv7J8qD3369FF8fLwGDBigEydOqEqVKlqyZEm2jsEzlSlTRosWLVK/fv30/vvvq169enrzzTezjXy3e/duxcfH57pdX19fff/99+rVq5dq166toKAgvf766+rZs6dZJj4+Xrt37zafOzs7a8qUKerXr58Mw1D58uX1zjvv6NlnnzXLlCtXTt9++6369eunSZMmqVSpUpo+fbpatGhhlunQoYNOnjyp119/XcePH1eNGjW0fPlyq06+J06cKAcHB0VFRSkpKUktWrTQ1KlT871fgWtlMW6GG1ZhFwkJCfL19ZVrtWdlcXS5egUAeTq7dbK9QwBuCwkJCQoO9FV8fLx8fHzsHQ5uoMxrkRvxXu/bt08duz2vsg+9KJ/ipQp03TdCwokjOvDtVM375EOrzotx60hMTNT+/ftVrlw5c/S0IuniRTO5JE9Pe0cDIB/y+vzK77ma2+IAAAAAAABgM5JLAAAAAAAAsBnJJQAAAAAAANiMDr0BAAAAAAXD3V26+27J0dHekQAoRCSXAAAAAAAFw8Eh4wGgSOG/HgAAAAAKSJEfjDsxUdqzJ2MK4JZQEJ9bJJcAAAAA4Do5OztLki5dumTnSOwsLU2Kj8+YArglZH5uZX6O2YLb4gAAAADgOjk6OsrPz08nTpyQJHl4eMhisdg5KjtISvpvSr9LwE3NMAxdunRJJ06ckJ+fnxyv43+W5BIAAAAAFICQkBBJMhNMRVJysnTqlOTsLLm42DsaAPng5+dnfn7ZiuQSAAAAABQAi8Wi0NBQFS9eXCkpKfYOxz7+/FN6/nlp0SKpUiV7RwPgKpydna+rxVImkksAAAAAUIAcHR0L5MvaLalUKalPn4ypm5u9owFQSEguAQAAAAAKRnCw1L+/vaMAUMgYLQ4AAAAAUDDOnpUWLMiYAigySC4BAAAAAArG/v3S449nTAEUGSSXAAAAAAAAYDOSSwAAAAAAALAZySUAAAAAAADYjOQSAAAAAKBguLtLNWtmTAEUGU72DgAAAAAAcJsID5d++cXeUQAoZLRcAgAAAAAAgM1ILgEAAAAACsavv0qurhlTAEUGySUAAAAAQMEwDCk5OWMKoMgguQQAAAAAAACbkVwCAAAAAACAzUguAQAAAAAAwGZO9g4AAAAAAHCbCA+X/vhDuuMOe0cCoBCRXAIAAAAAFAx3d6lqVXtHAaCQcVscAAAAAKBgHDwo9eiRMQVQZJBcAgAAAAAUjNOnpRkzMqYAigySSwAAAAAAALAZySUAAAAAAADYjOQSAAAAAAAAbEZyCQAAAABQMIKDpaFDM6YAigySSwAAAMjRv//+qyeffFKBgYFyd3dXtWrVtG3bNnO5YRh6/fXXFRoaKnd3d0VGRmrPnj12jBiA3ZUsKY0ZkzEFUGSQXAIAAEA2Z8+eVYMGDeTs7Kxly5bpr7/+0oQJE+Tv72+Weeutt/Tee+/pww8/1JYtW+Tp6akWLVooMTHRjpEDsKvz56W1azOmAIoMJ3sHAAAAgJvPuHHjVLp0acXExJjzypUrZ/5tGIbeffddvfbaa3r00UclSZ9++qmCg4P11VdfqWPHjoUeM4CbwJ49UpMmUmysVKuWvaMBUEhouQQAAIBslixZojp16qh9+/YqXry4atasqY8//thcvn//fh0/flyRkZHmPF9fX9WvX1+bNm2yR8gAAMBOSC4BAAAgm3/++UcffPCBKlSooBUrVuiFF15Qnz59NGvWLEnS8ePHJUnBV3TaGxwcbC67UlJSkhISEqweAADg1sdtcQAAAMgmPT1dderU0ZtvvilJqlmzpv744w99+OGH6tKli03rHDNmjEaOHFmQYQIAgJsALZcAAACQTWhoqKpUqWI1Lzw8XIcOHZIkhYSESJLi4uKsysTFxZnLrjRs2DDFx8ebj8OHD9+AyAHYlbNzxkhxzs72jgRAISK5BAAAgGwaNGig3bt3W837+++/FRYWJimjc++QkBCtXr3aXJ6QkKAtW7YoIiIix3W6urrKx8fH6gHgNlOtmnTkSMYUQJHBbXEAAADIpl+/frr33nv15ptv6vHHH9fPP/+sjz76SB999JEkyWKxqG/fvnrjjTdUoUIFlStXTsOHD1eJEiXUpk0b+wYPAAAKFS2XAAAAkE3dunW1ePFizZ07V3fddZdGjx6td999V507dzbLDB48WC+99JJ69uypunXr6sKFC1q+fLnc3NzsGDkAu9qxQypVKmMKoMig5RIAAABy9PDDD+vhhx/OdbnFYtGoUaM0atSoQowKwE0tJUX699+MKYAig5ZLAAAAAAAAsBnJJQAAAAAAANiM5BIAAAAAAABsRnIJAAAAAFAwKlSQ1qzJmAIoMujQGwAAAABQMLy9pcaN7R0FgEJGyyUAAAAAQMH4919p2LCMKYAig+QSAAAAAKBgxMVJY8dmTAEUGSSXAAAAAAAAYDP6XALs7OEmd6vn441UoWywfLzc9W/cWW2M3aN3P12pg/+etip7R+li6t+1he65+w6VKO6nswmXtHv/cX08f52Wrd9hp1cA3Ny++O5nbdq+T7/tOqS/9h5Tckqqprz+pJ545B57hwYAAADcFkguAXY0um9b9e78gI6djNd3a3/X+YuJqlqxpJ5uc6/aNa+tlj3e0c59xyRJtauGacmHL8vZyVHL1u/Q0jXbFeTvrUea3K05E57TmGnf6q3py+z8ioCbz/8+/EaHj51RoJ+XgoN8dPjYGXuHBAAAANxWSC4BdlI80FsvdGyiQ0dP674nxijhYqK57IVOTfRm/yi9+ERTvTR6tiRpyLMPysPNRU8MmGbVSumtj7/Thrmv6OUuzfTurJVKTkkt9NcC3Mzee/UJ3VGmuMqEBmjizO81asoSe4cEAMDtKzBQ6t49YwqgyKDPpSyio6NlsVjMh5ubm8LDw/XWW28pPT39hmzTYrFo/PjxN2TduLmVCQ2Uo6ODtvz+j1ViSZJWbPhDkhTk72XOCysZqPT0dK366S+rsoePn9XOfUfl4eYiTw/XGx84cItpXL+yyoQG2DsMAACKhrAwafr0jCmAIoOWS1dwd3fXDz/8IEm6fPmy1qxZo6FDhyo9PV1Dhw4t8O1t2rRJYXzwFkn7Dp9UUnKK6le/Q96ebjqfJcHUouFdkqR1W3eb83buO6aKZUMUeW8Vq5ZLpYL9FX5nCe34+4jOxl8svBcAAAAAXOnyZemff6Q77pDc3e0dDYBCQnLpCg4ODrrnnv86eW3SpIl27NihL7/88oYkl7JuC0XL2fiLGjl5id7o21ZbFgzXsnX/9bl0f52Kmr5gvT6ev94s/78PvlH9u+/QrHE9tGz9Du07dEJB/l56pEkNHfj3lLq9EmPHVwMAAABI2rlTql1bio2VatWydzQACgm3xeWDt7e3UlJSzOdJSUl65ZVXFBYWJldXV4WHh2vOnDlWdZ555hndddddWrt2rWrWrClPT0/Vq1dPsbGxVuWuvC3OMAyNGjVKISEh8vLyUvv27bVq1SpZLBatXbvWqt5bb72l6OhoBQcHKygoSF27dtXFi7RcuZV8MHeNur8aI093F3V77D693KWZIiOqKPaPA1q4fJvS0v67HXPPwTg17zpev+8+rNZNa6jfM8311KP3Ki09XbOXbtb+Iyft+EoAAAAAAEUVyaUcpKamKjU1VefPn9eSJUu0aNEiPfbYY+byxx9/XNOmTdOAAQP0zTffqGXLlnryySe1bJn1SF3Hjx9Xnz59NGjQIM2fP1+JiYlq27atVaLqSu+//76io6P1zDPP6Msvv9Sdd96pHj165Fh28uTJ2rNnj2bNmqXXX39dc+bM0ejRowtmJ6BQDOrRUtNGddHEmd+r6kOvqdT9/dWqxztydXXW0mkvq9X91cyytaqEacUnA3Uu4bIaPTlWJRr2U402IzTv2581bmB7TX+jqx1fCQAAAACgqOK2uCtcvHhRzs7OVvM6dOhg3hK3Zs0aLVmyRCtWrFDz5s0lSc2aNdOxY8c0YsQItWrVyqx35swZrVu3TlWrVpUkeXp6qkmTJtqyZYsaNmyYbdtpaWkaO3asunbtqrFjx0qSmjdvrlOnTmnGjBnZyoeGhmr27IyRxFq2bKlffvlFCxcuNOteKSkpSUlJSebzhISEfO8XFLxG9Srplece1pTZP+jdWSvN+Zt/+0ed+n+oX78aqdEvt9Wy9Tvk5OigGW92VXp6up4a9JEuJ2UkKA/+e1qvvfulwkoEqm2zWpo2b622/P6PvV4SAAAAAKAIouXSFdzd3bV161Zt3bpVGzZs0KRJk7R8+XI9++yzkqTvv/9eAQEBatq0qdnCKTU1Vc2aNdOvv/6qtLQ0c10lSpQwE0uSVKVKFUnSkSNHctz2kSNHdOzYMbVu3dpq/qOPPppj+WbNmlk9r1KlSq7rlqQxY8bI19fXfJQuXTqPPYEbLfLejONhQ+zf2ZadOH1eew7E6c4yxeXp7qKKZUNUtmSQYv88aCaWsvrx/9dRvVKpGxs0AAAAkBeLRXJxyZgCKDJouXQFBwcH1alTx3zeoEEDpaamasCAAerfv79OnTqlM2fOZGvdlOnYsWMqVSrjC76fn5/VMhcXF0lSYmLildXMupJUrFgxq/nFixfPsXxO68/aMulKw4YNU//+/c3nCQkJJJjsyMUp498v0M8rx+VB/l5KS0tXSmq6nJ0dM+blUVaSklJSb0CkAAAAQD7VrCnl8Z0EwO2J5FI+hIeHS5L+/PNPBQQEqFixYvruu+9yLJtbIig/QkNDJUknT1p3zHzixAmb15mVq6urXF1dC2RduH5bfvtHPTs0Uq/OTbX0h+1KuPhf0rFru4YqGeyvzdv3KTklVTv3HVPChcuqf/cdalK/stZs2WWWLRnsp2faNlR6ero2/rLXHi8FAAAAAFCEkVzKhz/++EOSFBQUpMjISL311ltycXFR9erVC3Q7pUqVUkhIiL7++murW+G++uqrAt0Obg5frf5F3X5pqAa1Kmjrote17McdSjh/WdUrl1ajupV0KTFZr078UpKUnJKq19/7Su++0kkLJr2oFRv+0J4DcSoe6KOHm9wtb083vf/5au07VDCJSOB28ulXP2nz9n2SpL/2Hc2Y9/VP2hC7R5J0T4079XSbe+0WHwAAt5WdO6XOnaXZs6X//5EewO2P5NIV0tPTtXnzZklScnKyYmNj9cYbb6hKlSq6//775ezsrEceeUQtW7bU4MGDVb16dV28eFF//vmn9u7dq+nTp9u8bUdHRw0bNkx9+/ZVcHCwmjRpojVr1mjVqlWSMm7Zw+0jPd1Qu95T9OITTdQmspYea1FHLs5OOnE6QV9897PeiVmhvw/EmeVnLd6og/+e1vMdG6te9XJq3qCqLl5O0u+7D2vW4o1asHybHV8NcPPavH2f5n67xWrelt/+0Zbf/uv8nuQSAAAF5PJl6ddfM6YAigySS1e4fPmyIiIiJElOTk4qXbq0nnzySY0YMcLsZylzRLapU6fq4MGD8vX11V133aWuXa9/KPiXXnpJZ8+e1dSpU/Xee+8pMjJSb7/9tjp06CBfX9/rXj9uLskpqXp31kqr0eLysvbnXVr7866rFwRgmhr9lKZGP2XvMAAAAIDblsUwDMPeQSBvw4cP14QJE3T69Gm5u7sX2HoTEhLk6+sr12rPyuLoUmDrBYqqs1sn2zsE4LaQkJCg4EBfxcfHy8fHx97h4AbKvBa5Ee/1vn371LHb8yr70IvyKX7zj6aacOKIDnw7VfM++VB33nmnvcMBbPfLL1Lt2lJsrFSrlr2jAXCd8nuupuXSTWbnzp36/PPPde+998rFxUVr167V+PHj9cILLxRoYgkAAAAAAKAgkFy6yXh4eGjTpk364IMPdP78eZUsWVKDBg1SdHS0vUMDAAAAgLyVKyfNn58xBVBkkFy6yYSFhemHH36wdxgAAAAAcO38/aX27e0dBYBCxvBjAAAAAICCERcnvfNOxhRAkUFyCQAAAABQMP79VxowIGMKoMgguQQAAAAAAACbkVwCAAAAAACAzUguAQAAAAAAwGYklwAAAAAABcPXV3rkkYwpgCLDyd4BAAAAAABuE3feKS1ZYu8oABQyWi4BAAAAAApGSop08mTGFECRQXIJAAAAAFAwduyQihfPmAIoMkguAQAAAAAAwGYklwAAAAAAAGAzkksAAAAAAACwGcklAAAAAAAA2MzJ3gEAAAAAAG4Td98txcdLnp72jgRAISK5BAAAAAAoGI6Oko+PvaMAUMi4LQ4AAAAAUDD27JFatMiYAigySC4BAAAAAArG+fPS999nTAEUGSSXAAAAAAAAYDOSSwAAAAAAALAZySUAAABkEx0dLYvFYvWoXLmyuTwxMVG9evVSYGCgvLy8FBUVpbi4ODtGDAAA7IXkEgAAAHJUtWpVHTt2zHxs2LDBXNavXz8tXbpUCxYs0Lp163T06FG1a9fOjtECuCmULi1NnpwxBVBkONk7AAAAANycnJycFBISkm1+fHy8ZsyYoTlz5qhp06aSpJiYGIWHh2vz5s265557CjtUADeLYsWkXr3sHQWAQkbLJQAAAORoz549KlGihO644w517txZhw4dkiTFxsYqJSVFkZGRZtnKlSurTJky2rRpU67rS0pKUkJCgtUDwG3mzBnp888zpgCKDJJLAAAAyKZ+/fqaOXOmli9frg8++ED79+/Xfffdp/Pnz+v48eNycXGRn5+fVZ3g4GAdP34813WOGTNGvr6+5qM0t80At58DB6SnnsqYAigyuC0OAAAA2bRq1cr8u3r16qpfv77CwsI0f/58ubu727TOYcOGqX///ubzhIQEEkwAANwGaLkEAACAq/Lz81PFihW1d+9ehYSEKDk5WefOnbMqExcXl2MfTZlcXV3l4+Nj9QAAALc+kksAAAC4qgsXLmjfvn0KDQ1V7dq15ezsrNWrV5vLd+/erUOHDikiIsKOUQIAAHvgtjgAAABkM3DgQD3yyCMKCwvT0aNHNWLECDk6OqpTp07y9fVV9+7d1b9/fwUEBMjHx0cvvfSSIiIiGCkOKOo8PaV77smYAigySC4BAAAgmyNHjqhTp046ffq0ihUrpoYNG2rz5s0qVqyYJGnixIlycHBQVFSUkpKS1KJFC02dOtXOUQOwu0qVpDxGjQRweyK5BAAAgGzmzZuX53I3NzdNmTJFU6ZMKaSIAADAzYo+lwAAAAAABeOXXySLJWMKoMgguQQAAAAAAACbkVwCAAAAAACAzUguAQAAAAAAwGYklwAAAAAAAGAzRosDAAAAABSMKlWkPXukUqXsHQmAQkRyCQAAAABQMNzcpPLl7R0FgELGbXEAAAAAgIKxf7/05JMZUwBFBsklAAAAAEDBOHtWmj07YwqgyCC5BAAAAAAAAJuRXAIAAAAAAIDNSC4BAAAAAADAZiSXAAAAAAAFIzRUGjEiYwqgyHCydwAAAAAAgNtEaKgUHW3vKAAUMlouAQAAAAAKRkKCtGJFxhRAkUFyCQAAAABQMPbulVq2zJgCKDJILgEAAAAAAMBmJJcAAAAAAABgs3x16D1q1CibVm6xWDR8+HCb6gIAACBDUlKSXF1d7R0GAABAjvKVXIq2sbd/kksAAADXr0SJEnryySfVo0cPVatWzd7hAEDuXF2lO+/MmAIoMvKVXFqzZs2NjgMAAAC58Pb21vvvv6/JkyerXr16evbZZ9WxY0d5eHjYOzQAsFa1Kp15A0VQvpJLjRo1utFxAAAAIBf79+/X999/r+nTp2vp0qV69tln1a9fP3Xq1Ek9evRQnTp17B0iAAC3lZMnTyohIcHeYeSbj4+PihUrZrft5yu5BAAAAPuxWCxq0aKFWrRooVOnTmnWrFmaMWOGPvroI3388ceqXr26evbsqc6dO8vHx8fe4QIoyn7/XXrgAWn1aql6dXtHA9jk5MmTerJrD505f8neoeRbgLeHPo+ZbrcE03UllxYvXqy5c+dq165dunTpkvb+f/PHXbt2acmSJercubNKlixZIIECAABACgoK0oABAzRgwABt3LhRM2bM0IIFC9S7d28NGjRI7du31wsvvKB69erZO1QARVFqqnTqVMYUuEUlJCTozPlLKhYRJc+AYHuHc1UXz8Tp5KZFSkhIuLWSS+np6erUqZMWLlwoSXJ3d9fly5fN5f7+/nr11VeVlpamYcOGFUykAAAAsOLt7S0PDw85OTnJMAylpaVp1qxZ+vTTT9WyZUvFxMSoePHi9g4TAIBbkmdAsHyKl7J3GPly0s7bd7Cl0sSJE7VgwQI999xzOnv2rAYOHGi1PDg4WPfdd5++/fbbAgkSAAAAGS5cuKCPPvpI9erVU82aNTV16lRVrFhRM2bM0JkzZ/Tzzz/rscce07Jly/Tcc8/ZO1wAAFAE2NRyaebMmapbt66mTp0qKaMfgCuVL1+e5BIAAEAB2bx5sz7++GMtWLBAFy5ckJeXl3r27KnnnntONWrUMMvVqVNHX3zxhVxcXLRkyRL7BQwAAIoMm5JLe/fuVa9evfIsExgYqNOnT9sUFAAAAP5TrVo1/fXXXzIMQzVr1tRzzz2nJ554Ql5eXrnWqVq1qmbPnl2IUQKApIoVpZ9+ypgCKDJsSi65u7srPj4+zzIHDx6Un5+fLasHAABAFv/884+6du2q5557TnXr1s1Xnc6dOysiIuIGRwYAV/DykvjsAYocm5JLNWvW1IoVK5SYmCg3N7dsy8+cOaPly5fr/vvvv+4AAQAAirpjx47Jx8fnmuqULl1apUuXvkERAUAujhyR3nlH6t9fKnVrdIQM4PrZ1KF3nz59dOTIEUVFRenIkSNWy/bt26e2bdsqPj5effr0KZAgAQAAijJPT08lJCQoPT09x+Xp6elKSEhQWlpaIUcGAFc4cUKaODFjCqDIsCm59Oijj2rIkCFatmyZwsLCNGHCBElS8eLFVbFiRf3444967bXX1LRp0wINFgAAoCgaOXKkihcvnmt/lqdPn1ZwcLD+97//FXJkAAAANiaXJGnMmDFasWKFHn74YXl4eMjR0VHp6elq2bKlli1bppEjRxZknAAAAEXWN998owceeEDFihXLcXmxYsUUGRmpr7/+upAjAwAAsLHPpUzNmjVTs2bNCioWAAAA5OCff/5RkyZN8ixTqVIlbdy4sZAiAgAA+I/NLZcAAABQOFJSUuTgkPdlm8ViUWJiYiFFBAC5CAqSXnwxYwqgyLiulku//PKLZs2apV9//VXx8fHy9fVVzZo11aVLF9WqVaugYgQAACjSypcvrx9++CHPMj/88IPKlStXSBEBQC7KlJGmTLF3FAAKmc0tlwYNGqR69erp/fff14YNG7Rjxw5t2LBB77//vurVq6fBgwcXZJwAAABFVrt27bR9+3a9/vrr2UaES0tL0/Dhw7V9+3a1b9/eThECwP+7dEn65ZeMKYAiw6bk0uTJkzVhwgRVqFBBn332mQ4cOKDLly/rwIED+vTTT1W+fHlNmDBBU6dOLeh4AQAAipwBAwaoYsWK+t///qfw8HA999xzGjVqlJ577jmFh4frzTffVHh4uAYOHGjvUAEUdbt2SbVrZ0wBFBk23RY3depUlS5dWj///LO8vb3N+WXKlNGTTz6pRx55RNWqVdPkyZP14osvFliwAAAARZGXl5fWr1+vF154QYsXL9bevXvNZQ4ODnrsscc0depUeXl52TFKAABQVNmUXNq/f79eeOEFq8RSVr6+voqKitKHH354XcEBAAAgQ7FixbRw4ULFxcVp27Ztio+Pl5+fn+rUqaPixYvbOzwAAFCE2ZRcyu8FTHBwsC2rBwAAQC6Cg4P10EMP2TsMAAAAk019LnXq1EmLFi3ShQsXclyekJCgRYsWqVOnTtcVHAAAAADgFuLgIHl7Z0wBFBk2tVwaOXKkdu7cqXr16un1119Xw4YNFRwcrLi4OP34448aPXq0atWqpZEjRxZ0vAAAAEXSX3/9pcmTJ2vr1q06d+5ctlHjJMlisWjfvn12iA4A/l+NGlJCgr2jAFDI8pVccnBwkMViyTbfMAx17tw5x/m7d++Wh4eHUlNTrz9KAACAImzdunVq2bKlkpKS5OTkpODgYDk5Zb+MMwzDDtEBAICiLl/Jpfvvvz/H5BIAAABuvKFDhyo1NVXTp09Xly5d5OjoaO+QACBnf/0ltW8vLVggVali72gAFJJ8JZfWrl17g8MAAABAbn777Td17NhR3bp1s3coAJC3xMSMBFNior0jAVCI6GUNAADgJufp6Znv0XpvlLFjx8pisahv377mvMTERPXq1UuBgYHy8vJSVFSU4uLi7BckAACwC5JLAAAAN7kHH3xQP/74o922v3XrVk2bNk3Vq1e3mt+vXz8tXbpUCxYs0Lp163T06FG1a9fOTlECAAB7sWm0OElKS0vT/PnztWrVKh09elRJSUnZylgsFq1evfq6AgQAACjq3n77bTVs2FB9+vTR2LFj5eHhUWjbvnDhgjp37qyPP/5Yb7zxhjk/Pj5eM2bM0Jw5c9S0aVNJUkxMjMLDw7V582bdc889hRYjAACwL5uSSxcvXlTz5s21efNmGYYhi8ViNTpJ5nM6AQcAALh+HTt2lJeXl6ZMmaKZM2eqYsWK8vHxyVbuRvyw16tXLz300EOKjIy0Si7FxsYqJSVFkZGR5rzKlSurTJky2rRpU47JpaSkJKsfJBMYrhy4/dxxh/T11xlTAEWGTcmlN954Q5s2bdKoUaP04osvKigoSNHR0Xruuee0fv16vfLKK6pVq5Zmz55d0PECAAAUOVkHV7lw4YJ++eWXHMsV9A978+bN0y+//KKtW7dmW3b8+HG5uLjIz8/Pan5wcLCOHz+e4/rGjBmjkSNHFmiMAG4yfn5S69b2jgJAIbOpz6Uvv/xS99xzj1577TUFBASY84ODg9W+fXutWbNGq1at0ttvv11ggQIAABRV6enp+XqkpaUV2DYPHz6sl19+WbNnz5abm1uBrHPYsGGKj483H4cPHy6Q9QK4iRw/Lo0ZkzEFUGTYlFw6dOiQVVNnBwcHqybOpUqV0kMPPaRZs2Zdf4QAAAAodLGxsTpx4oRq1aolJycnOTk5ad26dXrvvffk5OSk4OBgJScn69y5c1b14uLiFBISkuM6XV1d5ePjY/UAcJs5elR65ZWMKYAiw6bb4jw9PeXg8F9eytfXV8eOHbMqExISokOHDl1fdAAAALBy4cIF/f3337p48aLuu+++G7adBx54QDt27LCa17VrV1WuXFlDhgxR6dKl5ezsrNWrVysqKkqStHv3bh06dEgRERE3LC4AAHDzsSm5FBYWZpU4uuuuu/TDDz8oKSlJrq6uMgxDq1evVmhoaIEFCgAAUJQdOHBAL7/8sr777julp6fLYrEoNTVVkrRx40Y9++yzmjp1qho3blwg2/P29tZdd91lNc/T01OBgYHm/O7du6t///4KCAiQj4+PXnrpJUVERDBSHAAARYxNt8U98MADWrNmjXlB06VLF/NXqkGDBqlhw4bavn27+SsWAAAAbJfZJcF3332nRx99VBEREVYj9davX1+nTp3S3LlzCzWuiRMn6uGHH1ZUVJTuv/9+hYSE6MsvvyzUGAAAgP3Z1HLp2WefVWBgoE6ePKnQ0FB169ZNv/76q6ZOnart27dLkqKiohQdHV2AoQIAABRNI0aM0NmzZ7Vu3Trde++9GjlypDZt2mQud3Jy0n333aeNGzfe0DiyjlonSW5ubpoyZYqmTJlyQ7cL4Bbi5yc99ljGFECRYVPLpQoVKmjIkCFWt729//77On78uDZt2qSjR49qwYIF8vDwKLBAAQAAiqoVK1aobdu2uvfee3MtExYWpn///bcQowKAHNxxh7RgQcYUQJFhU3IpN8WKFVP9+vUVEhKiJUuWaNSoUQW5egAAgCLpzJkzKlu2bJ5lDMOwGr0XAOwiOVk6ciRjCqDIKNDkUlaLFy/WyJEjb9TqAQAAiozg4GDt2bMnzzI7duxQmTJlCikiAMjFH39IpUtnTAEUGTcsuQQAAICC0axZM33zzTf6/fffc1z+448/6ocfftCDDz5YyJEBAACQXAIAALjpvfbaa3J3d9f999+v//3vf9q7d68kadmyZRo+fLhatmypoKAgDRo0yM6RAgCAosim0eIAAABQeMqWLasVK1aoY8eOGj58uCwWiwzD0MMPPyzDMFSmTBktXLjQarAVAACAwkJyCQAA4BZQv3597dmzR0uXLtWWLVt05swZ+fj4qH79+nr00Ufl4uJi7xABAEARRXIJAADgFuHk5KS2bduqbdu29g4FAHJWo4aUmCg5O9s7EgCFKN/JpbfeeuuaVrxjx45rDgb28c/qt+Tj42PvMIBb3hOzYu0dAnBbSLl8wd4hAABs5eAgubraOwoAhSzfyaWhQ4ea9/fnl8VisSkoAAAA/GfUqFH5KmexWDR8+PAbHA0A5OHvv6WePaWPPpIqVrR3NAAKSb6TSzExMTcyDgAAAOQiOjo6z+WZPwCSXAJgdxcuSOvWZUwBFBn5Ti516dLlRsYBAACAXKxZsybH+fHx8frll1/03nvvKTIyUr169SrkyAAAAOjQGwAA4KbXqFGjXJe1bt1anTt3Vq1atRQVFVWIUQEAAGRwsHcAAAAAuD4VKlRQ27ZtNXbsWHuHAgAAiiCSSwAAALeB4sWLa/fu3fYOA0BRV6aM9PHHGVMARQa3xQEAANzikpKStHz5cvn5+dk7FABFXVCQ1KOHvaMAUMhILgEAANzkPv300xznp6am6t9//9W8efO0a9cu9enTp5AjA4ArnDolffWV1KZNRqIJQJFAcgkAAOAm98wzz8hisWSbbxiGJMlisahTp070uQTA/g4dkp59VqpVi+QSUISQXAIAALjJxcTE5DjfwcFB/v7+ql27tkJDQws5KgAAgAzXlVxKTk7WqlWrtGvXLl28eFHDhw+XJCUmJiohIUFBQUFycKDPcAAAgOvRpUsXe4cAAACQK5szP0uWLFGZMmX0yCOPaODAgYqOjjaX/f777woNDdW8efMKIkYAAAAAAADcpGxqubRx40Y99thjCg0N1aRJk7R582bNnTvXXF6vXj2VL19eixYt0hNPPFFgwQIAABRF69evt7nu/fffX4CRAMBVeHlJjRplTAEUGTYll0aPHi0/Pz/FxsYqKChIp0+fzlamTp062rJly3UHCAAAUNQ1btw4xw698yMtLa2AowGAPFSsKK1da+8oABQym5JLW7Zs0WOPPaagPHr/L126tL7++mubAwMAAECG119/XVu2bNGKFStUoUIFNWjQQMHBwYqLi9NPP/2kv//+Wy1atNA999xj71ABFHXp6VJKiuTsLNH/LlBk2JRcSkpKko+PT55lzp07R2feAAAABeCBBx7Q2LFj9dFHH6l79+5WrZgMw9DHH3+sl19+Wa+++qoaNmxox0gBFHnbt0u1a0uxsVKtWvaOBkAhsSn7c8cdd2jr1q15ltm0aZMqV65sU1AAAAD4z/Dhw/XQQw+pR48e2W6Ps1gs6tmzp1q1amWO3AsAAFCYbEouRUVFaePGjYqJiclx+fjx4/XHH3+oQ4cO1xUcAAAApNjYWIWHh+dZJjw8XNu2bSukiAAAAP5j021xgwYN0qJFi9SjRw/NmTNHSUlJkqTBgwdr06ZN+umnn1SjRg317t27QIMFAAAoilxcXPTrr7/mWebXX3+Vi4tLIUUEAADwH5taLnl5eenHH39Ux44dtXbtWm3YsEGGYWj8+PH66aef9Pjjj2vVqlVydXUt6HgBAACKnObNm2v58uUaO3askpOTrZYlJydrzJgxWrFihVq0aGGnCAEAQFFmU8slSfL399fs2bP13nvvaevWrTpz5ox8fHxUt25dBQcHF2SMAAAARdrbb7+tH3/8Ua+++qomTZqkOnXqqHjx4jpx4oS2bdumEydOqESJEnrrrbfsHSqAou6uu6TDh6Xixe0dCYBCZHNyKVNgYKBatmxZELEAAAAgB6VKldK2bds0dOhQzZ8/X99++625zM3NTU899ZTGjh2rkJAQO0YJAJJcXKRSpewdBYBCZtNtcQAAAChcISEhmjlzpuLj4/X777/rxx9/1O+//65z585p5syZJJYA3Bz++Udq3z5jCqDIsKnlUtOmTfNVzmKxaPXq1bZsAgAAADlwdnbWXXfdZe8wACBn585JCxdKw4bZOxIAhcim5NLatWvzXG6xWGQYhiwWiy2rBwAAQA6OHz+uL7/8Urt27dKlS5c0ffp0SdLJkye1f/9+VatWTe7u7naOEgAAFDU23RaXnp6e4+PcuXP64YcfVL9+fT322GPZRjMBAACAbaZOnapy5cqpd+/emjx5smJiYsxlJ06cUEREhD7//HM7RggAAIqqAu1zycfHR40bN9aKFSv0888/63//+19Brh4AAKBIWrp0qXr37q1q1appyZIleuGFF6yWV61aVdWrV9dXX31lnwABAECRdkM69Pb29larVq2sflEDAACAbd5++22VKVNGa9as0cMPP6ziOQzxXa1aNf311192iA4AsihRQnrzzYwpgCLjho0W5+DgoGPHjt2o1QMAABQZ27dv10MPPSRPT89cy5QsWVJxcXGFGBUA5CAkJKMzb0awBIqUG5Jc+ueff7RgwQKVLVv2RqweAACgSElPT5ezs3OeZU6cOCFXV9dCiggAcnHunLRkScYUQJFh02hx3bp1y3F+amqq/v33X23YsEEpKSkaNWrUdQUHAAAAqVKlSvrxxx9zXZ6amqr169erWrVqhRgVAOTgn3+kRx+VYmOlWrXsHQ2AQmJTcmnmzJl5Lq9UqZIGDBigHj162LJ6AAAAZNG5c2cNHDhQI0eO1IgRI6yWpaWlaeDAgfrnn380ZMgQO0UIAACKMpuSS/v3789xvoODg/z8/OTt7X1dQQEAAOA/L730kpYuXapRo0Zp9uzZcnNzkyQ9/vjj2rZtmw4cOKDmzZure/fudo4UAAAURTYllywWi1xcXBRCJ20AAAA3nLOzs1asWKGRI0fqww8/1NmzZyVJCxculI+Pj4YMGaKRI0fKYrHYOVIAAFAU2ZRcKleunLp06aJPPvmkoOMBAABADlxcXPS///1Pb7zxhnbv3q0zZ87Ix8dH4eHhcnR0tHd4AJDBzU2qUiVjCqDIsCm55O/vr8DAwIKOBQAAADm444471KpVK02ZMkUWi0WVK1e2d0gAkLMqVaQ//7R3FAAKmYMtle677z5t2bKloGMBAABADk6dOiUfH59C3eYHH3yg6tWry8fHRz4+PoqIiNCyZcvM5YmJierVq5cCAwPl5eWlqKgoxcXFFWqMAADg5mBTcmnMmDH6/fffNWrUKKWmphZ0TAAAAMiievXq+vvvvwt1m6VKldLYsWMVGxurbdu2qWnTpnr00Uf15/+3SOjXr5+WLl2qBQsWaN26dTp69KjatWtXqDECuAlt3y75+GRMARQZNt0W99Zbb6latWoaOXKkpk2bprvvvlvBwcHZOpG0WCyaMWNGgQQKAABQVA0ZMkRRUVFas2aNmjRpUijbfOSRR6ye/+9//9MHH3ygzZs3q1SpUpoxY4bmzJmjpk2bSpJiYmIUHh6uzZs365577imUGAHchNLTpfPnM6YAiox8J5ccHR0VHR2t4cOHa+bMmeb8Y8eO6dixYznWIbkEAABw/c6ePavmzZurefPmatOmjerWrZvjD3uS9PTTTxf49tPS0rRgwQJdvHhRERERio2NVUpKiiIjI80ylStXVpkyZbRp0yaSSwAAFDH5Ti4ZhiHDMCRJ+/fvv2EBAQAAwNozzzwji8UiwzC0aNEiLVq0SJKskkuGYchisRRocmnHjh2KiIhQYmKivLy8tHjxYlWpUkXbt2+Xi4uL/Pz8rMoHBwfr+PHjua4vKSlJSUlJ5vOEhIQCixUAANiPTbfFhYWFFXQcAAAAyCIhIUFubm5ycXFRTEyMXWKoVKmStm/frvj4eC1cuFBdunTRunXrbF7fmDFjNHLkyAKMEAAA3AxsSi4BAADgxvL39ze7JOjSpYskacuWLdqyZYv69OlTKDG4uLiofPnykqTatWtr69atmjRpkjp06KDk5GSdO3fOqvVSXFycQkJCcl3fsGHD1L9/f/N5QkKCSpcufcPiB2AHlStLsbEZUwBFxjWNFpfTff0AAAAoeFm7JMi0fPly9evXz04RSenp6UpKSlLt2rXl7Oys1atXm8t2796tQ4cOKSIiItf6rq6u8vHxsXoAuM14eEi1amVMARQZ15Rcio6OlqOjY74fTk40jAIAALgVDRs2TOvXr9eBAwe0Y8cODRs2TGvXrlXnzp3l6+ur7t27q3///lqzZo1iY2PVtWtXRURE0Jk3UNQdOiT16pUxBVBkXFP2x8fHJ1vHjQAAALj9nDhxQk8//bSOHTsmX19fVa9eXStWrFCzZs0kSRMnTpSDg4OioqKUlJSkFi1aaOrUqXaOGoDdnTolTZ0qde8ulSlj72gAFJJrSi7169dPr7/++o2KBQAAADeJGTNm5Lnczc1NU6ZM0ZQpUwopIgAAcLO6ptviAAAAAAAAgKzoFAkAAOAm9fnnn2vz5s3m871790qSHnzwwRzLWywWffvtt4USGwAAQCaSSwAAADepvXv3mgmlrJYvX55jeUb2BWB3xYtL/fplTAEUGSSXAAAAbkL79++3dwgAcO1KlZLeecfeUQAoZPlOLqWnp9/IOAAAAJBFWFiYvUMAgGt34YK0Y4dUrZrk5WXvaAAUEjr0BgAAAAAUjL//lu69N2MKoMgguQQAAAAAAACbkVwCAAAAAACAzUguAQAAAAAAwGYklwAAAAAABcPJSQoKypgCKDL4jwcAAAAAFIzq1aWTJ+0dBYBCRsslAAAAAAAA2IzkEgAAAACgYPz5p1S+fMYUQJFBcgkAAAAAUDCSkqR9+zKmAIoMkksAAAAAAACwGcklAAAAAAAA2IzkEgAAAAAAAGxGcgkAAAAAUDDKl5eWL8+YAigynOwdAAAAAADgNuHjI7VoYe8oABQyWi4BAAAAAArGsWNSdHTGFECRQXIJAAAAAFAwjh2TRo4kuQQUMSSXAAAAAAAAYDOSSwAAAAAAALAZySUAAAAAAADYjOQSAAAAAKBg+PtLnTtnTAEUGU72DgAAAAAAcJsoV076/HN7RwGgkNFyCQAAAABQMBITpb17M6YAigySSwAAAACAgvHXX1KFChlTAEUGySUAAAAAAADYjOQSAAAAAAAAbEZyCQAAAAAAADYjuQQAAAAAAACbOdk7AAAAAADAbaJWLckw7B0FgEJGyyUAAAAAAADYjOQSAAAAAKBg7N4tRURkTAEUGSSXAAAAAAAF4+JFafPmjCmAIoPkEgAAAAAAAGxGcgkAAAAAAAA2I7kEAAAAAAAAm5FcAgAAAAAUjLJlpc8+y5gCKDKc7B0AAAAAAOA2ERAgPfmkvaMAUMhouQQAAAAAKBgnT0pTpmRMARQZJJcAAAAAAAXj8GGpd++MKYAig+QSAAAAAAAAbEZyCQAAAAAAADYjuQQAAAAAAACbkVwCAABANmPGjFHdunXl7e2t4sWLq02bNtq9e7dVmcTERPXq1UuBgYHy8vJSVFSU4uLi7BQxgJuCt7fUvHnGFECRQXIJAAAA2axbt069evXS5s2btXLlSqWkpKh58+a6ePGiWaZfv35aunSpFixYoHXr1uno0aNq166dHaMGYHcVKkgrVmRMARQZTvYOAAAAADef5cuXWz2fOXOmihcvrtjYWN1///2Kj4/XjBkzNGfOHDVt2lSSFBMTo/DwcG3evFn33HOPPcIGYG9padLFi5Knp+ToaO9oABQSWi4BAADgquLj4yVJAQEBkqTY2FilpKQoMjLSLFO5cmWVKVNGmzZtskuMAG4Cv/0m+fpmTAEUGbRcAm4yiUkp+t8HS7V912HtP3JS5xIuycfLXWVLBunJRyPUvmVdOTvxKxBwpUlRd6mYl2uOy/46fl5vrPjbfF7c20X33RGosoEeKhfooQAPF528kKSXF/1RWOECt5T09HT17dtXDRo00F133SVJOn78uFxcXOTn52dVNjg4WMePH89xPUlJSUpKSjKfJyQk3LCYAQBA4SG5BNxkLl5O0szFG1WzShk1u7eqAv29FJ9wSas37dTLb8zR4pW/6IuJz8vBgYaHwJUuJqdq+V8nss0/eSHZ6nnl4t6KqlFCaemG/o1PlJ+bUVghArekXr166Y8//tCGDRuuaz1jxozRyJEjCygqAABwsyC5BNxk/H08tG/VOLk4W/97pqam6bE+U7R2yy6t2rRTzRtUtVOEwM3rUnKaFv127KrldsWd1+vf7tLBs5eUkmZo5pM1CyE64NbUu3dvffPNN1q/fr1KlSplzg8JCVFycrLOnTtn1XopLi5OISEhOa5r2LBh6t+/v/k8ISFBpUuXvmGxAwCAwnHLNX2Ijo6WxWJRyZIllZ6enm15gwYNZLFY9Mwzz+R7nQcOHJDFYtHChQvNeWXLllXv3r0LIuQb6sCBA4qOjtbRo0ftHQoKiIODQ7bEkiQ5OTnqwUZ3S5L2HzlZ2GEBt5UTF5K199RFpaTRYgnIjWEY6t27txYvXqwffvhB5cqVs1peu3ZtOTs7a/Xq1ea83bt369ChQ4qIiMhxna6urvLx8bF6AACAW98t2XLJ2dlZp06d0vr169W4cWNz/sGDB7Vp0yZ5eXld9zYWL14sf3//617PjXbgwAGNHDlSDz/8sEqUKGHvcHADpaen64fNOyVJ4XeE2jka4Obk5OCg++8MlL+Hsy6npGnfqYvad+qSvcMCbkm9evXSnDlz9PXXX8vb29vsR8nX11fu7u7y9fVV9+7d1b9/fwUEBMjHx0cvvfSSIiIiGCkOKMqqVZNOnJCu6I8NwO3tlkwuubi4KDIyUnPnzrVKLs2bN09Vq1aVYwEMeVmzJrdIwL6SU1L17szvZUg6E39RP279W3sOxqnTw/V1f91K9g4PuCn5ezjr+YZlrebtO3VR76//RyfOJ+dcCUCOPvjgA0myutaSpJiYGLOF+MSJE+Xg4KCoqCglJSWpRYsWmjp1aiFHCuCm4uwsFStm7ygAFLJb7ra4TJ06ddLChQuVkpJizpszZ46eeOIJq3K7du1Sx44dVbp0aXl4eKhKlSqaMGFCjrfUZZXTbXHTpk1TWFiYPDw81KxZM/3666+yWCyaOXNmtnpTpkxRWFiYfH191aZNG508+d9tTBcvXlTv3r1VqVIleXh4qGzZsnr++efNIX7zu661a9eqSZMmkqS6devKYrHIYrHkfyfippackqa3ZyzX+P9j777Dmyr/NoDf6d4tpaXQ0sHeFgTZsgSKIIIgQxQZshQRRGVopYAsEfiJypIpCgJKmSIiZSsqU/ZuC5S2UKB7J8/7R94cG5KukOQk7f25rlxpzrwzmjz55jnPWb0Xa34+ihu372Ps652waMpAuaMRWaTDNx5i1m/XMGbzvxj6w2lM3XkJR28+RA0fV3zStTac7Kz2I49IFkIIvZeCQw84OTlhyZIlePToETIyMhAZGVnoeEtEVE7cvAm8/LL6mojKDattaffs2RM5OTnYt28fAODSpUs4d+4cBg7U/uIdFxeHOnXqYOnSpdizZw9GjRqFmTNn4rPPPivV/nbu3IkxY8aga9eu2LZtGzp37oz+/fsXuuzOnTuxZMkSLF68GIcPH8a4ceOk+ZmZmVAqlZg9ezZ+/fVXzJo1C4cPH0bv3r1Lta1nn30WS5YsAaD+FfH48eM4fvx4qe4XWS43F0c8+OsrJP75Jf7dOQOff/gqfth5HL3e+RppGVlyxyOyOJH/xuNSQhpSs/ORqxSIfZyFZcdicPTmQ/i6OaJTbR+5IxIREZV9KSnArl3qayIqN6zysDgAcHFxQa9evbBp0yb06NEDP/74I1q1aqUz2OQLL7yAF154AYD6F7i2bdsiMzMT33zzDSIiIkq8v1mzZqFTp05YuXIlACAsLAx5eXn49NNPdZYVQmDnzp1wdHQEoB4Xac6cOVCpVLCxsYGvr6/U1RwA8vPzUa1aNbRt2xbXrl1D7dq1S7QtDw8P1K9fHwDQsGFDNGvWrMj7kJOTg5ycHOl2ampqie8/ycfGxgb+lSpgWN/n4e3lhhGfrMX/1u7DtHd7yR2NyCpEXX2A52tURO1Kbthz6b7ccYiIiIiIyhyr7bkEqA+N27FjB7KysrBp0ya89tprOstkZ2cjIiICNWvWhKOjI+zt7fHJJ58gPj4e6enpJdqPUqnEmTNn8PLLL2tN79VL/5f79u3bS8UgAKhfvz7y8vJw//5/X2q+//57NGnSBG5ubrC3t0fbtm0BANeuXSv1tkpq7ty58PT0lC489a/16diiLgDgj9M3ZE5CZD3ScvIBAI48LI6IiIiIyCSsuqUdFhYGe3t7TJs2DdHR0XoPU5s8eTK++OILjBw5Env27MGJEycQHh4OQF14KokHDx4gPz8fvk8MTFepUiW9y3s9cWYEBwcHrf1t27YNb775Jpo3b44tW7bgr7/+wrZt2/RmKm5bpTF16lSkpKRIlzt37pR6GySvhAfq7sV2dk8/aD1ReVHTxxUA8CCdA3oTEREREZmC1R4WBwD29vbo27cvFi1ahBdeeAF+fn46y/z0008YPXo0Jk+eLE375ZdfSrUfX19f2NnZaQ3KDcCg3kOaTI0bN8aKFSukaYcPHzZoW6Xh6Oio1QuKLNPV6HgEVqkIFycHremZ2bn4dLG6CNm5dX05ohFZLH8PRyRl5CJXKXSmD2xaFQDwZ/QjOaIRERGVLwEBwMKF6msiKjesurgEACNGjMD9+/cxcuRIvfOzsrKk3j6A+hC3TZs2lWoftra2aNKkCXbs2IHx48dL07dv325Q5iczAcCGDRsM2tbT9GQiy7Rj/xks+/EgWoTWQFAVb7i5OiHhQTKijl/Go5QMtGxcA2MGdpA7JpFFaVXNGy/W98OVxDQkZeQiJ1+FKh5OaBzgATtbG+w4F48rif8dCu3uaItBzapKt+0UCrg72mF0m2Bp2saTd5GWozTr/SAiIrJ6fn7AxIlypyAiM7P64lLz5s2LLPJ06dIFK1euRP369eHj44OlS5dqDWpdUuHh4ejVqxdGjhyJfv364cyZM/juu+8AqAdcLo0uXbpg7Nix+Oyzz9CqVSvs2bMHUVFRpc4EALVr14atrS3WrFkDOzs72NnZFTuwN1m2rm0bIiEpFSfOR+PkhWhkZObAw80Z9Wv645Uuz2LQSy15WBzREy4mpMHf0wkh3i6o6+cOBzsbpGXn42xcKn6/eh/n76VpLe9oZ4v2NbXPHudkoz1t69l4FpeIiIhK6/FjYP9+oHNnoEIFudMQkZlYfXGpOF9//TXGjBmDcePGwcXFBUOHDsUrr7xSaE+nwrz88stYtmwZ5syZgx9++AEtWrTAsmXL0LVrV3h6epZqW6NHj8atW7fw9ddf44svvkBYWBg2btyIli1blmo7AODj44MlS5Zg/vz5+P7775Gfnw8hRPErksVqXC8IjesFyR2DyKpcSUzX6plUnKSMXAz67pQJExEREZVT0dFA//7AqVMsLhGVI1ZXXJo+fTqmT59e5DJnz56V/vbz85MGyy5oxIgR0t8hISE6BZmYmBiddcaMGYMxY8ZIt1evXg0ACA0NLXK93r17a23f1tYWCxYswIIFC7SWK0mGJ7cFqItVo0eP1lmWiIiIiIiIiMjUrK64JJdHjx5hxowZ6NSpE9zd3XHixAnMnj0bvXr1QkhIiNzxiIiIiIiIiIhkweJSCdnb2+PmzZvYuHEjkpOT4evri8GDB+Pzzz+XOxoRERERERERkWxYXCohd3d37N69W+4YRERERERElsvZGWjSRH1NROUGi0tERERERERkHPXqAadPy52CiMzMRu4ARERERERERERkvVhcIiIiIiIiIuM4cwZwdFRfE1G5weISERERERERGYcQQG6u+pqIyg0Wl4iIiIiIiIiIyGAsLhERERERERERkcFYXCIiIiIiIiIiIoPZyR2AiIiIiIiIyoh69YALF4Dq1eVOQkRmxOISERERERERGYezM9CggdwpiMjMeFgcERERERERGUdsLDBihPqaiMoNFpeIiIiIiIjIOB4+BFavVl8TUbnB4hIRERERERERERmMxSUiIiIiIiIiIjIYi0tERERERERERGQwFpeIiIiIiIjIOPz8gClT1NdEVG7YyR2AiIiIiIiIyoiAAGDuXLlTEJGZsecSERERERERGUdaGnDokPqaiMoNFpeIiIiIiIjIOK5fBzp2VF8TUbnB4hIRERERERERERmMxSUiIiIiIiIiIjIYi0tERERERERERGQwFpeIiIiIiIjIOOzt1WeMs7eXOwkRmZGd3AGIiIiIiIiojGjUCLh7V+4URGRm7LlEREREREREREQGY3GJiIiIiIiIjOP8eaBqVfU1EZUbLC4RERERERGRceTlAXFx6msiKjdYXCIiIiIiIiIiIoOxuERERERERERERAZjcYmIiIiIiIiIiAzG4hIREREREREZR61awMGD6msiKjfs5A5AREREREREZYS7O9Chg9wpiMjM2HOJiIiIiIiIjCMuDpg6VX1NROUGi0tERERERERkHImJwLx56msiKjdYXCIiIiIiIiIiIoOxuEREREREeh05cgQ9e/aEv78/FAoFtm/frjVfCIFp06ahSpUqcHZ2RufOnXH9+nV5whIREZFsWFwiIiIiIr0yMjIQGhqKJUuW6J0/f/58fPXVV1i+fDn+/vtvuLq6IiwsDNnZ2WZOSkRERHLi2eKIiIiISK8XX3wRL774ot55Qgh8+eWXCA8PR69evQAA69evh5+fH7Zv346BAweaMyoRWYqKFYG33lJfE1G5wZ5LRERERFRq0dHRSEhIQOfOnaVpnp6eaNGiBY4fPy5jMiKSVXAwsGqV+pqIyg32XCIiIiKiUktISAAA+Pn5aU338/OT5j0pJycHOTk50u3U1FTTBSQieWRlAbduAdWrA87OcqchIjNhzyUiIiIiMou5c+fC09NTugQGBsodiYiM7fJloGFD9TURlRssLhERERFRqVWuXBkAkJiYqDU9MTFRmvekqVOnIiUlRbrcuXPH5DmJiIjI9FhcIiIiIqJSq1atGipXroyoqChpWmpqKv7++2+0atVK7zqOjo7w8PDQuhAREZH145hLRERERKRXeno6bty4Id2Ojo7G2bNn4e3tjaCgIEyYMAGzZs1CrVq1UK1aNXz66afw9/dH79695QtNREREZsfiEhERERHpdfLkSXTs2FG6PXHiRADAkCFDsG7dOkyaNAkZGRkYNWoUkpOT0bZtW+zduxdOTk5yRSYiuSkUgIOD+pqIyg0Wl4iIiIhIrw4dOkAIUeh8hUKBmTNnYubMmWZMRUQWrUkToMBZIYmofOCYS0REREREREREZDAWl4iIiIiIiMg4Ll8Gnn1WfU1E5QaLS0RERERERGQcWVnAmTPqayIqN1hcIiIiIiIiIiIig7G4REREREREREREBmNxiYiIiIiIiIiIDMbiEhERERERERlHtWrAli3qayIqN+zkDkBERERERERlRIUKQL9+cqcgIjNjzyUiIiIiIiIyjsREYNEi9TURlRssLhEREREREZFxxMUBH3ygviaicoOHxRERERERWYC83FzExsbKHaNUPDw84OvrK3cMIiKSGYtLREREREQyy0lPQUz0LUz4eDocHR3ljlNi3u4u+GHtKhaYiIjKORaXiIiIiIhklpeTBZXCDj4t+6Cif7DccUok41EiHhzfitTUVBaXiIjKORaXiIiIiIgshEsFX3hUqip3jBJ7IHcAsjyenkDPnuprIio3WFwiIiIiIiIi46hRA9i5U+4URGRmLC4REREREZFBrG0Q8tzcXDg4OMgdo1SsbtD0vDwgORnw8gLs7eVOQ0RmwuISERERERGVmrUNQp6Xm4u427GoGlwNdvbW8zXI6gZNP38eaNoUOHUKePZZudMQkZlYz7sqERERERFZDGsbhPz+zQu4FbMGFZr3soq8AAdNJyLrweISEREREREZzFoGIU9/mADAevJqcNB0IrIGNnIHICIiIiIiIiIi68XiEhERERERERERGYyHxREREREREZFxhIYCKSmAq6vcSYjIjFhcIiIiIiIiIuOwtQU8POROQURmxsPiiIiIiIiIyDiuXwfCwtTXRFRusLhERERERERExpGWBuzbp74monKDxSUiIiIiIiIiIjIYi0tERERERERERGQwDuhNRERERERERCbz4MEDpKamyh2jxGJjY5Gfly93DKvC4hIREREREREZR2Ag8M036msiqAtLbwwbgUdpmXJHKbHsrEzcjYtHUF6e3FGsBotLREREREREZBy+vsDYsXKnIAuSmpqKR2mZ8G3VF67efnLHKZH7Ny8g9s4aKPNZXCopFpeIiIiIiIjIOB49AvbsAbp3B7y95U5DFsTV2w8elarKHaNE0h8myB3B6nBAbyIiIiIiIjKOmBhg8GD1NRGVGywuERERERERERGRwVhcIiIiIiIiIiIig7G4REREREREREREBmNxiYiIiIiIiIzD1RVo2VJ9TUTlBs8WR0RERERERMZRpw5w/LjcKYjIzNhziYiIiIiIiIiIDMaeS0RERERERGQcp08DTZsCp04Bzz4rd5oy68GDB0hNTZU7RonExsYiPy9f7hhkYiwuEREREREREVmJBw8e4I1hI/AoLVPuKCWSnZWJu3HxCMrLkzsKmRCLS0RERERERERWIjU1FY/SMuHbqi9cvf3kjlOs+zcvIPbOGijzWVwqy1hcIiIiIiIiIrIyrt5+8KhUVe4YxUp/mCB3BDIDDuhNREREREREREQGY88lIiIiIiIiMo769YHr14Gqlt+jhoiMh8UlIiIiIiIiC5WXm4vY2Fi5Y5SKh6cnfJ2c5I5RYtZ05jWAZ18jy8TiEhERERERkQXKSU9BTPQtTPh4OhwdHeWOUyL+WVl4Ly4GjXdsR8VmzeSOUyxrO/MawLOvkWVicYmIiIiInsqSJUvwxRdfICEhAaGhofj666/RvHlzuWMRWb28nCyoFHbwadkHFf2D5Y5TIpUvncALJ/7Anbg4qyguWduZ1wCefY0sE4tLRERERGSwzZs3Y+LEiVi+fDlatGiBL7/8EmFhYbh69SoqVaokdzyiMsGlgq9VnBUMAJzjbsodwSDWcuY1gGdfI8vEs8URERERkcEWLVqEkSNHYtiwYahfvz6WL18OFxcXrFmzRu5oREREZCbsuVSOCSEAAGlp1jN4HZEly8tKlzsCUZmQl5UB4L/PKbJcubm5OHXqFKZOnSpNs7GxQefOnXH8+HGd5XNycpCTkyPdTklJAQCTDKSblpYGZX4+kuNjkJdt+WOppN6/C6FSITXhDuwUcqcpGWvLbG15AevMbPcgHqkArt+6hYdnz8odp1h37txBbna21bxXANb3urC2vID1Zc54fB/K/HykpaUZ/TNVs73i2mUKwZZbuXX37l0EBgbKHYOIiEivO3fuoCpPZW3R7t27h4CAAPz5559o1aqVNH3SpEk4fPgw/v77b63lp0+fjhkzZpg7JhERET2l4tpl7LlUjvn7++POnTtwd3eHQmEF5dhyKjU1FYGBgbhz5w48PDzkjkNk1fj/ZB2EEEhLS4O/v7/cUcjIpk6diokTJ0q3VSoVHj16hIoVKxq9LWJt/+/WlhewvszWlhdgZnOwtryA9WW2tryA9WU2Zd6StstYXCrHbGxs+IuwFfHw8LCKNzYia8D/J8vn6ekpdwQqAR8fH9ja2iIxMVFremJiIipXrqyzvKOjo87p1L28vEwZ0er+360tL2B9ma0tL8DM5mBteQHry2xteQHry2yqvCVpl3FAbyIiIiIyiIODA5o2bYqoqChpmkqlQlRUlNZhckRERFS2secSERERERls4sSJGDJkCJo1a4bmzZvjyy+/REZGBoYNGyZ3NCIiIjITFpeILJyjoyMiIiJ0DiMgotLj/xOR8Q0YMAAPHjzAtGnTkJCQgMaNG2Pv3r3w8/OTNZe1/b9bW17A+jJbW16Amc3B2vIC1pfZ2vIC1pfZEvLybHFERERERERERGQwjrlEREREREREREQGY3GJiIiIiIiIiIgMxuISEREREREREREZjMUloqc0ffp0KBQK6eLk5IR69eph/vz5UKlUJtmnQqHAggULTLJtImPT/I8EBATo/Z9o06YNFAoFhg4dWuJtxsTEQKFQ4Oeff5amhYSE4N133zVGZJOKiYnB9OnTce/ePbmjEBEREREZBYtLREbg7OyM48eP4/jx4/j111/Rr18/TJkyBfPnzzfJ/o4fP47XX3/dJNsmMgV7e3skJSXhyJEjWtNjY2Nx/PhxuLm5PfU+tm3bhg8//PCpt2NqMTExmDFjBotLREawZMkShISEwMnJCS1atMA///xT5PI//fQT6tatCycnJzRq1Ah79uwxU1K10uS9ePEi+vbti5CQECgUCnz55ZfmC1pAaTKvXLkSzz//PCpUqIAKFSqgc+fOxT4nxlaavJGRkWjWrBm8vLzg6uqKxo0b4/vvvzdjWrXSvo41Nm3aBIVCgd69e5s24BNKk3fdunVaP8Jqfog1t9I+xsnJyRg7diyqVKkCR0dH1K5d26LfLzp06KDzOCsUCvTo0cMi8wLAl19+iTp16sDZ2RmBgYF4//33kZ2dbaa0aqXJnJeXh5kzZ6JGjRpwcnJCaGgo9u7da7asR44cQc+ePeHv7w+FQoHt27cXu86hQ4fw7LPPwtHRETVr1sS6detMG1IQ0VOJiIgQrq6uOtN79+4tnnvuORkSEVkWzf9Ir169xKhRo7TmzZs3TzRs2FCEhoaKIUOGlHib0dHRAoD46aefjJzW9A4ePCgAiBMnTsgdhciqbdq0STg4OIg1a9aIixcvipEjRwovLy+RmJiod/k//vhD2Nraivnz54tLly6J8PBwYW9vL86fP2+Ref/55x/x4Ycfih9//FFUrlxZ/O9//zNLzoJKm3nQoEFiyZIl4syZM+Ly5cti6NChwtPTU9y9e9ci8x48eFBERkaKS5cuiRs3bogvv/xS2Nrair1795olryGZNaKjo0VAQIB4/vnnRa9evcwTVpQ+79q1a4WHh4eIj4+XLgkJCWbLa0jmnJwc0axZM9G9e3dx7NgxER0dLQ4dOiTOnj1rsZkfPnyo9RhfuHBB2NrairVr11pk3g0bNghHR0exYcMGER0dLX777TdRpUoV8f7775slryGZJ02aJPz9/cUvv/wibt68KZYuXSqcnJzE6dOnzZJ3z5494pNPPhGRkZECgNi2bVuRy9+6dUu4uLiIiRMnikuXLomvv/7a5O9vLC4RPaXCikuDBw8WjRs3lm5nZ2eLqVOniqCgIOHg4CDq1q0rNmzYoLXOkCFDRIMGDcTBgwdF48aNhYuLi3juuefEyZMntZYDIL744gvptkqlEjNmzBB+fn7C1dVVvPrqq+L3338XAMTBgwe11vv8889FRESEqFSpkqhYsaIYOnSoSE9PN9KjQaRL8z+yadMm4e3tLXJzc6V5zzzzjJgzZ45Wceny5ctiwIABomrVqsLZ2VnUq1dPLFiwQCiVSmk9fcWl4OBgMXbsWK19L1++XAQFBQlnZ2fRuXNncfr0aQFAq7GlWe+bb74RQUFBwsPDQ/Tq1Uvcv39fWiY9PV2MHTtW1K5dWzg7O4vg4GAxevRokZycrLW/4ralKSw9eSGi0mvevLnW/7xSqRT+/v5i7ty5epfv37+/6NGjh9a0Fi1aiNGjR5s0p0Zp8xYUHBwsS3HpaTILIUR+fr5wd3cX3333nakiannavEII0aRJExEeHm6KeHoZkjk/P1+0bt1arFq1SgwZMsSsxaXS5l27dq3w9PQ0Uzr9Spt52bJlonr16lrtFXN72tfy//73P+Hu7m62Nn5p844dO1Z06tRJa9rEiRNFmzZtTJqzoNJmrlKlivjmm2+0pvXp00e8/vrrJs2pT0mKS5MmTRINGjTQmjZgwAARFhZmslw8LI7ISPLz85Gfn4+0tDTs3LkTW7duxauvvirN79+/P1asWIEPPvgAu3fvRrdu3fDGG2/g119/1dpOQkIC3nvvPXz00UfYsmULsrOz8corryAvL6/QfX/99deYPn06hg4disjISNSoUQMjRozQu+w333yD69ev47vvvsO0adOwceNGfPbZZ8Z5EIiK0LNnT+Tk5GDfvn0AgEuXLuHcuXMYOHCg1nJxcXGoU6cOli5dij179mDUqFGYOXNmqV+nO3fuxJgxY9C1a1ds27YNnTt3Rv/+/QtddufOnViyZAkWL16Mw4cPY9y4cdL8zMxMKJVKzJ49G7/++itmzZqFw4cP6z0UoahtPfvss1iyZAkAYO3atdLhtERUOrm5uTh16hQ6d+4sTbOxsUHnzp0L/Z86fvy41vIAEBYWZpb/QUPyys0YmTMzM5GXlwdvb29TxZQ8bV4hBKKionD16lW0a9fOlFElhmaeOXMmKlWqhLfeesscMSWG5k1PT0dwcDACAwPRq1cvXLx40RxxARiWeefOnWjVqhXGjh0LPz8/NGzYEHPmzIFSqbTYzE9avXo1Bg4cCFdXV1PFlBiSt3Xr1jh16pR0GNqtW7ewZ88edO/e3eR5Dc2ck5Ojc0ins7Mzjh07ZtKshpLjM8/OZFsmKkcyMjJgb2+vNW3AgAGYMmUKAODgwYPYuXMnfvvtN3Tt2hUA0KVLF8THxyMiIgIvvviitN6jR49w+PBhNGjQAADg6uqKjh074u+//0bbtm119q1UKjFv3jwMGzYM8+bNAwB07doVSUlJWL16tc7yVapUwYYNGwAA3bp1w+nTp/Hzzz9L6xKZiouLC3r16oVNmzahR48e+PHHH9GqVStUq1ZNa7kXXngBL7zwAgB1Y79t27bIzMzEN998g4iIiBLvb9asWejUqRNWrlwJQP2BmpeXh08//VRnWSEEdu7cCUdHRwDqcZHmzJkDlUoFGxsb+Pr6YtmyZdLy+fn5qFatGtq2bYtr166hdu3aJdqWh4cH6tevDwBo2LAhmjVrVuL7Q0T/SUpKglKphJ+fn9Z0Pz8/XLlyRe86CQkJepdPSEgwWU4NQ/LKzRiZJ0+eDH9/f50vOKZgaN6UlBQEBAQgJycHtra2WLp0Kbp06WLquAAMy3zs2DGsXr0aZ8+eNUNCbYbkrVOnDtasWYNnnnkGKSkpWLBgAVq3bo2LFy+iatWqFpn51q1bOHDgAF5//XXs2bMHN27cwDvvvIO8vLxStUPMmbmgf/75BxcuXND7PcAUDMk7aNAgJCUloW3bthBCID8/H2PGjMHHH39sjsgGZQ4LC8OiRYvQrl071KhRA1FRUYiMjDRb0bG0CvvMS01NRVZWFpydnY2+T/ZcIjICZ2dnnDhxAidOnMCxY8ewePFi7N27FyNHjgQA7Nu3D97e3ujUqZPUwyk/Px9dunTBmTNntN6U/P39pcISAOmL6N27d/Xu++7du4iPj8fLL7+sNb1Xr156l3+ywVS/fv1Ct01kbK+99hp27NiBrKwsbNq0Ca+99prOMtnZ2YiIiEDNmjXh6OgIe3t7fPLJJ4iPj0d6enqJ9qNUKnHmzJkS/1+0b99eKgYB6v+LvLw83L9/X5r2/fffo0mTJnBzc4O9vb1U7L127Vqpt0VEVNbNmzcPmzZtwrZt22QZwLmk3N3dcfbsWZw4cQKzZ8/GxIkTcejQIblj6ZWWlobBgwdj5cqV8PHxkTtOibRq1QpvvvkmGjdujPbt2yMyMhK+vr5YsWKF3NEKpVKpUKlSJXz77bdo2rQpBgwYgE8++QTLly+XO1qJrF69Go0aNULz5s3ljlKoQ4cOYc6cOVi6dClOnz6NyMhI/PLLLxZ9NMXixYtRq1Yt1K1bFw4ODnj33XcxbNgw2NiwpKLBnktERmBjY6PVA6FNmzbIz8/HBx98gIkTJyIpKQmPHj3S6d2kER8fL/164+XlpTXPwcEBAAo9e0J8fDwAwNfXV2t6pUqV9C6vb/s5OTn67xiRkYWFhcHe3h7Tpk1DdHS03sPUJk+ejJUrVyIiIgJNmzaFl5cXduzYgVmzZiE7O7tEZ5Z78OAB8vPzn+r/Avjv/27btm148803MWrUKMyePRsVK1ZEfHw8XnnlFZ3/zdL+DxNR6fn4+MDW1haJiYla0xMTE1G5cmW961SuXLlUyxuTIXnl9jSZFyxYgHnz5mH//v145plnTBlTYmheGxsb1KxZEwDQuHFjXL58GXPnzkWHDh1MGRdA6TPfvHkTMTEx6NmzpzRNpVIBAOzs7HD16lXUqFHDYvLqY29vjyZNmuDGjRumiKjDkMxVqlSBvb09bG1tpWn16tVDQkICcnNzpc91S8qskZGRgU2bNmHmzJmmjKjFkLyffvopBg8eLA3j0ahRI2RkZGDUqFH45JNPTF6wMSSzr68vtm/fjuzsbDx8+BD+/v6YMmUKqlevbtKshirsM8/Dw8MkvZYA9lwiMpl69eoBUJ9K2NvbG76+vlLvpicvhX3hLYkqVaoAUH+ZLoi9JMgS2dvbo2/fvli0aBE6deqk010XUJ8qfPTo0Zg8eTI6d+6MZs2awc6udL+F+Pr6ws7Ozmj/Fz/99BMaN26MFStWoHv37mjRogUqVKhg0LaI6Ok5ODigadOmiIqKkqapVCpERUWhVatWetdp1aqV1vIA8Pvvvxe6vDEZklduhmaeP38+PvvsM+zdu9esh/4a6zFWqVRm+9GttJnr1q2L8+fP4+zZs9Ll5ZdfRseOHXH27FkEBgZaVF59lEolzp8/L7VfTc2QzG3atMGNGzekwh2g7qVcpUoVkxeWDM2s8dNPPyEnJwdvvPGGqWNKDMmbmZmpU0DSFPOEEKYL+/+e5jF2cnJCQEAA8vPzsXXr1kJ7xctNjs889lwiMpELFy4AUFfGO3fujPnz58PBwcHov+BVrVoVlStXxo4dO7Te3LZv327U/RAZy4gRI3D//n3psNEnZWVlaTXelEolNm3aVKp92NraokmTJtixYwfGjx8vTTf0/+LJTACksctKiz2ZiIxj4sSJGDJkCJo1a4bmzZvjyy+/REZGBoYNGwYAePPNNxEQEIC5c+cCAMaPH4/27dtj4cKF6NGjBzZt2oSTJ0/i22+/tci8ubm5uHTpkvR3XFwczp49Czc3N6mnjaVl/vzzz6WThYSEhEjjWbm5uZWo16m5886dOxfNmjVDjRo1kJOTgz179uD777/XGmPPkjI7OTmhYcOGWutress+Od0S8gLqwcdbtmyJmjVrIjk5GV988QViY2MLPfGMJWR+++238c0332D8+PEYN24crl+/jjlz5uC9996z2Mwaq1evRu/evVGxYkWzZTUkb8+ePbFo0SI0adIELVq0wI0bN/Dpp5+iZ8+eWj3GLCnz33//jbi4ODRu3BhxcXGYPn06VCoVJk2aZJa86enpWj3+oqOjcfbsWXh7eyMoKAhTp05FXFwc1q9fDwAYM2YMvvnmG0yaNAnDhw/HgQMHsGXLFvzyyy8my8jiEpERqFQq/PXXXwD+O/vArFmzUL9+fbRr1w729vbo2bMnunXrhkmTJuGZZ55BRkYGLl68iBs3bmDVqlUG79vW1hZTp07FhAkT4Ofnh44dO+LgwYPYv38/APA4YLI4zZs3L7LI06VLF6xcuRL169eHj48Pli5datCvyOHh4ejVqxdGjhyJfv364cyZM/juu+8AlP7/okuXLhg7diw+++wztGrVCnv27NH5NaikateuDVtbW6xZswZ2dnaws7PjwN5EBhgwYAAePHiAadOmISEhAY0bN8bevXulHpG3b9/W+l9v3bo1Nm7ciPDwcHz88ceoVasWtm/fbrYv5aXNe+/ePTRp0kS6vWDBAixYsADt27c325hApc28bNky5Obmap0tFwAiIiIwffp0i8ubkZGBd955B3fv3oWzszPq1q2LH374AQMGDDB5VkMzy620eR8/foyRI0ciISEBFSpUQNOmTfHnn39KY4paYubAwED89ttveP/99/HMM88gICAA48ePx+TJky02MwBcvXoVx44dk87Ka06lzRseHg6FQoHw8HDExcXB19cXPXv2xOzZsy02c3Z2NsLDw3Hr1i24ubmhe/fu+P7773WGQzCVkydPomPHjtLtiRMnAgCGDBmCdevWIT4+Hrdv35bmV6tWDb/88gvef/99LF68GFWrVsWqVasQFhZmupCCiJ5KRESEACBd7OzsRLVq1cQ777wjEhMTpeVycnLEjBkzRK1atYSDg4Pw9fUVHTt2FOvXr5eWGTJkiGjQoIHW9h8/fiwAiLVr10rTAIgvvvhCuq1SqcT06dNFpUqVhIuLi3j55ZfF5s2bBQBx9uzZQtcTQoj//e9/gm8FZEoRERHC1dW1yGVCQ0PFkCFDhBBCJCQkiN69ewt3d3fh5+cnJk+eLFauXCkAiAcPHgghhIiOjhYAxE8//SRtIzg4WIwdO1Zru8uWLROBgYHCyclJtG/fXuzbt08AENu3by9yvW3btgkAIjo6WgghRH5+vvjggw+Er6+vcHd3F6+++qr466+/SpThyW0JIcTy5ctF9erVhZ2dHf//iIiIiMjqKYQww0GNRGR2n376KRYuXIiHDx+abNA2ImuzevVqjBgxAtHR0QgJCZE7DhERERFRmcDD4ojKgMuXL+OHH35A69at4eDggEOHDmHBggV4++23WViicuvRo0eYMWMGOnXqBHd3d+k007169WJhiYiIiIjIiFhcIioDXFxccPz4cSxbtgxpaWkICAjARx99ZJbxDYgslb29PW7evImNGzciOTkZvr6+GDx4MD7//HO5oxERERERlSk8LI6IiIiIiIiIiAxmOaceICIiIiIiIiIiq8PiEhERERERERERGYzFJSIiIiIiIiIiMhiLS0REREREREREZDAWl4iIiIiIiIiIyGAsLhERERERERERkcFYXCIiIiIiIiIiIoOxuERERERERERERAZjcYmIiIiIiIiIiAzG4hIRERERERERERmMxSUiIiIiIiIiIjIYi0tERERERERERGQwFpeIiIiIiIiIiMhgLC4REREREREREZHBWFwiIiIiIiIiIiKDsbhEREREREREREQGY3GJiIiIiIiIiIgMxuISEREREREREREZjMUlIiIiIiIiIiIyGItLRERERERE5dihQ4egUCgwffp0k+1DoVCgQ4cOJV5++vTpUCgUOHToULHbKWxZIjIfFpeIyGrFxMRAoVBg6NChWtM7dOgAhUIhT6hSCgkJQUhIiNwxMHToUCgUCsTExJhk+4U9V0RERPQfzedlwYuDgwMCAwMxaNAgnDt3Tu6IVoNtDyLzYnGJiIpV3ho6pi60GErzq+KYMWPkjkJEREQmVKNGDURERCAiIgLvvfcegoOD8eOPP6J58+b4448/5I5nFu+++y4uX76M5s2bG3VZIjINO7kDEJH1qFGjBt544w0AQHp6Ov766y/8+OOPiIyMRFRUFNq0aSNzQrX169cjMzNT7hhEREREBqlZs6bOIWrh4eGYPXs2Pvnkk3Jx+JePjw98fHyMviwRmQZ7LhFRiWkaOtOnT8eCBQtw7NgxfPLJJ8jJycEnn3widzxJUFAQ6tatK3cMIiIiIqMZN24cAODEiRMA/ht7KC4uDm+++SYqV64MGxsbrcLT2rVr0aJFC7i5ucHNzQ0tWrTAunXritzPsWPH0KFDB7i7u8PLywt9+/bFjRs3dJY7ePAghg8fjjp16kjbb9asGb799tsit3/37l289tpr8PHxgYuLC9q0aYP9+/frLFeacZSeXHbdunWoVq0aAOC7777T6n1/6NAhhIeHQ6FQYMuWLXq3t2bNGigUCsydO7fYfRORGotLRPRUnmzoACVr7Bw5cgQ9e/aEj48PHB0dUatWLYSHh+vtcaRUKvH555+jZs2acHJyQs2aNTF37lyoVCq9mYoac2nHjh3o2rUrKlasCCcnJ4SEhGDw4MG4cOECAPUYSN999x0AoFq1alJD5MmBI6OjozFixAgEBQXB0dERVapUwdChQxEbG1vofp977jk4OzvDz88PI0eOxOPHj/U/qEZw7949REREoGXLlqhUqRIcHR0REhKCd955B/fv3y90PZVKhfnz56NWrVpwcnJCtWrVMHPmTOTl5eldvjTPIxERET29gm2chw8folWrVjh37hwGDhyIUaNGwcPDAwDw3nvvYfjw4YiLi8Nbb72Ft956C3FxcRg2bBjGjx+vd9t//fUXXnjhBXh6emLcuHFo3749tm3bhtatW+PWrVtay37++ec4cuQInnvuObz77rt44403kJSUhNGjR+ODDz7Qu/3Hjx+jTZs2uH79OkaMGIHXXnsN//77L7p164bt27cb5wEC0LhxY+k+hoaGSocYRkREICQkBCNHjoSNjQ1WrVqld/2VK1fCzs4Ow4YNM1omorKOh8URkVE8WczRNHa8vb0xcOBAZGdnS42dZcuWYezYsfDy8kLPnj1RqVIlnDx5ErNnz8bBgwdx8OBBODg4SNsaNWoU1qxZg2rVqmHs2LHIzs7GokWL8Oeff5Yq4wcffIBFixbB29sbvXv3RqVKlXDnzh3s378fTZs2RcOGDTFhwgSsW7cO//77L8aPHw8vLy8A0Bp0+++//0ZYWBgyMjLw0ksvoVatWoiJicGGDRvw66+/4vjx46hevbq0/Pr16zFkyBB4eHhg8ODB8PLywu7du9G5c2fk5uZq3VdjOXLkCBYuXIgXXngBLVq0gL29Pc6cOYNly5bht99+w+nTp+Hp6amz3oQJE/DHH3+gf//+cHNzw65duxAREYFz587h559/1lq2tM8jERERGW7p0qUAoDWu0IULFzBs2DCsXLkStra20vQjR47g66+/Rr169XD8+HHpM3/69Olo2bIlvvrqK7z66qt4/vnntfbx22+/Yfny5Rg9erQ0bcWKFRgzZgzGjx+PXbt2SdOXLVsm9Q7SyM/PR/fu3bF48WKMHz8eQUFBWvPPnTuHQYMG4YcffpDajuPHj8dzzz2HUaNGISwsDM7Ozk/zMAFQF5cmTJiAxYsXo3HjxnrPghcWFoa9e/ciJiZGq5138eJF/PXXX+jduzcqV6781FmIyg1BRFSM6OhoAUCEhYXpzJs2bZoAIDp27ChNAyAAiGHDhon8/Hyt5S9evCjs7OxEaGioSEpK0po3d+5cAUAsWLBAmnbw4EEBQISGhor09HRp+t27d4WPj48AIIYMGaK1nfbt24sn39527dolAIhGjRrp7DcvL08kJCRIt4cMGSIAiOjoaJ37m5ubK0JCQoS7u7s4ffq01ryjR48KW1tb8dJLL0nTUlJShIeHh3B1dRVXr17V2k67du0EABEcHKyzH300j8Xo0aOLXTYxMVGkpaXpTP/uu+8EADFr1iyt6Zr77OvrK+7cuSNNz8nJkXL+/PPP0vTSPo+a19CTzxURERH9R/N5WaNGDRERESEiIiLEhx9+KJ5//nkBQDg5OYk///xTCKFubzk4OIgHDx7obGf48OECgNi8ebPOvA0bNggAYvjw4dI0TRujdu3aQqlUai2vVCpFrVq1hEKhEPfv3y/2PmzdulUAEOvWrdOaDkDY2tqKmJgYnXXeeustnbZGRESEACAOHjyos5327dtrTdO3bHFtjx07dggAIjw8XGv6hAkTBADxyy+/FHtfieg/PCyOiErsxo0b0phLH330Edq1a4eZM2fCyckJs2fP1lrWwcEB8+fP1/oVDVD/+pWfn4+vv/4aFStW1Jo3adIk+Pr64scff5SmrV+/HgAwbdo0uLq6StMDAgIK7dKtj+bXvsWLF+vs187ODn5+fiXazu7duxETE4OPPvoITZo00ZrXtm1b9OrVC3v27EFqaioAYPv27UhNTcXw4cNRu3ZtaVl7e3udx8yYKlWqBDc3N53pgwcPhoeHh96xDQD1r4dVq1aVbjs4OEg5C47RUNrnkYiIiEru5s2bmDFjBmbMmIHFixcjOjoagwYNwj///INWrVpJy1WrVk3vQNZnzpwBAJ3D+gGgY8eOAICzZ8/qzGvTpg1sbLS/ItrY2KBNmzYQQuDff/+VpqelpSEiIgKhoaFwc3OThhLo27cvAPUh+k8KCgpCcHCwznRNDypNbnPo0aMHAgICsHbtWiiVSgBAbm4uvv/+ewQGBqJbt25my0JUFvCwOCIqMU1DB1AXR/z8/DBo0CBMmTIFjRo10lq2sMbOX3/9BUDd7ToqKkpnvr29Pa5cuSLd1jRinuy2Xdi0wvzzzz9wdHRE+/btS7yOPpr8V69e1dvFOiEhASqVCteuXUOzZs2KzN+qVSvY2ZnubTgyMhIrVqzA6dOn8fjxY6nhBOhv8BWXs2CDr7TPIxEREZWc5pCt4hT241hqaipsbGzg6+urdx2FQiH9EFaS7Wmmp6SkAFAXYTp06IDTp0+jSZMmGDx4MCpWrAg7OzvExMTgu+++Q05OjsHbNwdbW1uMGDECM2bMwK+//oqXXnoJ27Ztw8OHD/Huu+/qFNmIqGgsLhFRiZW0oQMU3nh49OgRAJS4105KSgpsbGz0FqpK2ttIs52AgICnbiho8m/YsKHI5TIyMqT9AuqeRE+ytbXV6fVjLAsXLsSHH34IX19fdO3aFVWrVpXGMPjyyy/1NvgA/Y+pJmfBBl9pn0ciIiIyvsJOYOLh4QGVSoUHDx7otEHu378PIYQ0FmZBiYmJerenma4Zu2nHjh04ffo03nrrLZ1BsTdt2iSdHMXQ7ZvLiBEjMGvWLKxcuRIvvfQSVq1aBRsbGwwfPtysOYjKAhaXiMgkimrsAOpf1Nzd3YvdjqenJ1QqFZKSknR+fSusgaKPl5eX1KvoaQpMmvy7du3CSy+9VOzymkaSvjO0KZVKPHz4EAEBAQbn0Sc/Px+fffYZqlSpgrNnz2o1KoUQmD9/fqHrJiYmok6dOnpzFiw8lfZ5JCIiIvNp0qQJzpw5g0OHDqF///5a8zRn723cuLHOen/88YdOW0mlUuHPP/+EQqFAaGgoAHVvdgDo1auXzjaOHj1aaK7bt28jNjZW59A4zTpPDjnwNDRDMxTsuf2kqlWrokePHtizZw/+/PNPREVFoVu3bjoDkRNR8djXj4jMqkWLFgD+O6yqOJpGjL6GSlGNlyc1b94cOTk5OHz4cLHLFtUY0eQ/fvx4ifZbVP7jx48jPz+/RNspjaSkJKSkpKBVq1Y6v1aePHkSWVlZha5bVM6CDb7SPo9ERERkPkOGDAEAzJgxQ+vwt5SUFGmIA80yBV27dg0rV67UmrZy5Upcu3YNPXr0kH7o0xSHjh07prXs4cOHddYvSKlU4uOPP4YQQpp27tw5fP/99/D19UX37t1LczeLVKFCBSgUCty5c6fI5UaPHo38/Hz069cPQgiMHDnSaBmIyhMWl4jIrN555x3Y2dlh3LhxuH37ts785ORkrbF9Bg8eDACYOXOmdKgZAMTFxWHx4sUl3u/YsWMBqAes1hzSpZGfn6/VC8rb2xsA9DZGevXqhaCgICxatAhHjhzRmZ+Xl6fV0OrVqxc8PDywZs0aXLt2TWu58PDwEucvjUqVKsHZ2RmnT59GZmamNP3x48cYN25ckesuXrwYd+/elW7n5ubik08+AQAMHTpUml7a55GIiIjMp127dhg3bhwuXbqEhg0b4v3338eECRPQsGFDXLlyBe+99x7atWuns15YWBjee+899OrVCx9//DF69eqFt99+Gz4+Plrtrp49eyIkJATz589Hjx49MHnyZPTu3RsvvPCC3t5MGs888wyOHTuG5557DlOmTMFbb72F1q1bIz8/H99++610CL8xuLm54bnnnsORI0cwePBgzJw5E7NmzUJsbKzWct26dUNwcDDu3buHypUro2fPnkbLQFSe8LA4IjKrhg0bYunSpXj77bdRp04ddO/eHTVq1EBaWhpu3bqFw4cPY+jQoVi+fDkA9RlNhg0bhrVr16JRo0Z45ZVXkJOTg82bN6Nly5bYvXt3ifbbvXt3fPjhh1iwYAFq1aqFV155BZUqVUJcXByioqLw4YcfYsKECQCATp06YcGCBRg1ahT69u0LV1dXBAcHY/DgwXB0dMTPP/+MF198Ee3bt0enTp3QqFEjKBQKxMbG4ujRo6hYsaI0mLWnpye++uorDB06FM899xwGDhwIT09P7N69G87OzqhSpUqpH8ODBw9qFXoKatu2LUaMGIF33nkHCxcuRGhoKHr27InU1FT8+uuvCA4Ohr+/f6HbbtmyJUJDQzFgwAC4urpi165duHr1Kvr06SOd/QUo/fNIRERE5vXVV1+hSZMmWLZsGb799lsAQIMGDTBz5kwMGzZM7zotW7ZEeHg4wsPD8dVXX8HW1ha9e/fG/PnzUb16dWk5Nzc3HDhwAB999BGOHDmCQ4cOoUGDBtiwYQP8/Pzw888/691+hQoV8Msvv+DDDz/EypUrkZmZiSZNmmDGjBno0qWL0R+D77//Hu+//z52796NlJQUCCHQtm1brcPybGxsMHjwYMyaNQtDhw416clWiMo0QURUjOjoaAFAhIWFlWh5AKJ9+/ZFLvPPP/+IgQMHCn9/f2Fvby98fHzEs88+K6ZMmSIuX76stWx+fr6YO3euqF69unBwcBDVq1cXc+bMETdu3BAAxJAhQ7SWb9++vSjs7W3r1q2iY8eOwtPTUzg6OoqQkBAxePBgceHCBa3l5s+fL2rVqiXs7e313p+7d++K8ePHi1q1aglHR0fh4eEh6tWrJ0aMGCGioqJ09rtt2zbRtGlT4ejoKCpVqiRGjBghHj16JIKDg0VwcHCRj5XGwYMHBYAiL5rHIjc3V8yePVvKFxQUJD744AORlpamd59DhgwRAMTNmzfFvHnzRM2aNYWDg4MIDg4W06dPFzk5OXozlfR51LyGnnyuiIiIiOTWo0cPoVAoxPXr1+WOQmS1FEIUOOCViIiIiIiIqJzQHDrYpUsX/Pbbb3LHIbJa7PNHRERERERE5crGjRtx9epVrF+/HgAQEREhcyIi68biEhEREREREZUr3377LY4ePYrg4GCsXr0arVu3ljsSkVXjYXFERERERERERGQwG7kDEBERERERERGR9WJxiYiIiIiIiIiIDMbiEhERERERERERGYzFJSIiIiIiIiIiMhiLS0REREREREREZDAWl4iIiIiIiIiIyGAsLhERERERERERkcFYXCIiIiIiIiIiIoOxuERERERERERERAZjcYmIiIiIiIiIiAzG4hIRERERERERERmMxSUiIiIiIiIiIjIYi0tERERERERERGQwFpeIiIiIiIiIiMhgLC4REREREREREZHBWFwiIiIiIqJyT6FQQKFQ4NChQ0bZXkhICBQKBdatW2eU7ZFpFfX8G/u1QVQWsbhERE9t+vTp0oduwYujoyP8/f0RFhaGVatWIS8vr8TbPHz4MEaPHo169erBy8sLTk5OCAwMRI8ePbBs2TJkZWWVeFtKpRJbtmzBm2++idq1a8PLywsODg6oVKkS2rZti6lTp+LChQuG3HUt586dw+TJk9G8eXP4+fnBwcEBnp6eqF+/PoYMGYIdO3aU6jEgIiKyRIV97js5OaFq1ap4+eWXsWXLFggh5I5KBjJF246A+/fvY968eejSpQuqVq0KZ2dnuLq6IiQkBL1798a3336L5ORkuWMSGUYQET2liIgIAUAAEH5+ftLFxcVFmg5ANGvWTDx69KjIbSUlJYnu3btrrefo6Cg8PT21pgUEBIh9+/YVm+348eOidu3aWuva29sLb29vYWNjozW9T58+Iicnp9T3PzU1VQwaNEgoFAppWwqFQnh5eQlHR0etfdSoUUP89ddfpd4HERGRpSjsc9/JyUnrM+/FF18U2dnZcsctsTp16og6deqIv//+2yjb69Spk6hTp46IjIw0yvbMyZhtO2uhuU8HDx4s1bySUKlUYvbs2TqPn5ubm3B3d9ea5unpKVavXv10d4ZIBuy5RERGlZCQIF0yMjIQGxuLkSNHAgBOnjyJ9957r9B1ExMT0bJlS+zZswe2trYYN24cLl68iOzsbCQnJ+Px48dYu3YtAgMDERcXh+7du2PLli2Fbm/Xrl3o0KEDrl27hooVK2Lu3Lm4du0acnNz8fDhQ+Tm5uLEiROYMmUKPDw8EBkZiczMzFLd38ePH6NVq1bYuHEjAGDgwIE4fPgwsrOz8fjxY2RnZyMuLg6rVq3CM888g5s3b+L48eOl2gcREZGlevJz/8KFC+jSpQsA4Ndff0V4eLjMCUvuypUruHLlCpo3b26U7UVFReHKlSt45ZVXjLI9uTxN244AIQQGDx6MTz75BJmZmWjRogW2bt2Kx48fIy0tDampqUhJScG2bdvQs2dPpKSkYOfOnXLHJio9uatbRGT9Cv66VZhOnToJAMLBwUGkpaXpzFepVNIy9vb2YufOnYVuKykpSYSGhgoAwtXVVVy+fFlnmWvXrgkPDw8BQNSvX1/cuXOnyPvw8OFD0atXL/H48eMil3vSiy++KAAIOzs7sWXLliKXValUYunSpWLZsmWl2gcREZElKe5zPysrS9SsWVMAEO7u7iIvL8/MCelpGaNtZ21gop5L8+bNk9afMGGCUKlURS5/+PBhMXbs2FLvh0hu7LlERGbRrVs3AEBubi6uX7+uM3/37t04cOAAAOCTTz5Bz549C91WxYoV8dNPP8HJyQkZGRn49NNPdZYJDw9HamoqnJycsG3bNlStWrXIfN7e3ti+fTs8PT1LfJ9+/fVX/PrrrwCAadOmoV+/fkUur1Ao8Pbbb2PUqFHStJiYGGkcg5iYmELXLWxQ0CfXv3nzJkaNGoVq1arB0dERISEhuH//Puzt7aFQKIr9JWzatGlQKBSoWbOm3vl//PEH3njjDQQHB8PJyQmenp5o3rw5Pv/8c6Snpxe5bSIiKh+cnJykz8S0tDRcuXIFQMk+swpSqVTYsGEDunfvLo1l6Ovri65du+LHH38sdkyny5cvY+zYsahfvz7c3d3h5uaGOnXqYODAgdi6dStUKpXW8kUN2vz48WNMmzYNzz77LDw8PODg4IDKlSvjmWeewZgxYxAVFaWzTnEDeiuVSqxZswadOnWCj48PHB0dERAQgH79+hU5cHSHDh2gUCgwffp0CCGwcuVKtGjRAh4eHnB3d0erVq3www8/FPnYGENxbTtA/fzPmzcPrVq1gre3NxwdHREYGIiBAweWqCf3vn37MHDgQAQHB8PZ2Rne3t545plnMG7cOJ31VSoVoqKi8N5776Fly5aoWrUqHBwcULFiRbRv3x7Lly83+xhRSUlJ+OyzzwAAL7zwAhYtWgSFQlHkOu3atcNXX32lNa0kg8MPHToUCoUCQ4cO1ZlXcP309HRMmzYNjRo1gru7u/T/GBoaCoVCgYkTJxaZ78CBA1AoFLCxscHt27d15sfExGDChAlo0KAB3Nzc4OLigrp162L8+PF6l6cyRO7qFhFZv5L8uvX5559Ly5w4cUJnfrdu3aRfOEv669ewYcMEAGFjYyPi4+Ol6QkJCdJ4Sm+99Vbp71AJacaG8vT0FOnp6QZtIzo6WnpcoqOjC10uODhYABBr164tdP0NGzYINzc3AUC4uLgIV1dXERwcLIQQokePHgKAePXVVwvdh0qlEtWqVRMAxPTp07XmKZVK8d577+mME2BrayvdrlOnjoiJiTHocSAiIutRks/9JUuWSMv88ccfQoiSf2YJoe5R3K5dO52xaArefvnllwsdK3HevHlaYys6OTnpjLf4ZG9lzfQne6fcuXNHBAUFSfNtbGxEhQoVtD4D27dvr5OhsM9uIYRITk4WHTp0kNa3tbUVXl5eWuM3fvjhh3rvW/v27QUAER4eLnr16iX1oNb02NZcpk2bVujzUxxjtO3OnDkjqlatqnUfC44vpFAoxJw5c/RuOyMjQ/Tr10/r/ri7u2u9BkJDQ7XWKfj60rRTnnzNPP/88yIzM1PvPgt7/oubV5T58+dL6x49erRU6xZU1GtJY8iQIQKAGDJkSKHrL1iwQBqL1MHBQXh5eUlt0C+++EIAEJUrVxb5+fmF7mfo0KECgOjQoYPOvB9++EFrvFFHR0fh7Oys9Rz+9ttvhjwEZAXYc4mIzOK3334DoP5VsFq1alrz8vPzcfToUQBA165d4ebmVqJt9unTB4D6l6rDhw9L0w8ePCj9GmmqcQ7y8/Nx5MgRAECXLl3g6upqkv2UxujRo9GgQQOcOHECGRkZSE9Px759+wAAb775JgD1OFSFnYXkjz/+QHR0NBQKBQYPHqw1LyIiAl999RUqVaqEJUuW4OHDh0hLS0NWVhYOHjyIJk2a4OrVq+jTp4/OL8FERFT+FOyN6+3trTO/qM8spVKJPn364MiRI2jcuDF27dqFjIwMJCcnIz09Hd999x0qVaqEnTt3YvLkyTrbXrZsGaZMmQKVSoWXX34ZZ86cQVZWlvTZtW/fPgwYMAA2NiX7KjR9+nTcvn0bISEh2L9/P3Jzc/Ho0SPk5OQgJiYGy5YtQ8uWLUv1+Lz11ls4dOgQHBwc8NVXXyE1NRWPHz/GvXv3MHz4cADAggULsHz58kK3sWTJEhw6dAjr1q2Txu25c+eO1Pt71qxZhfYoMoai2nbx8fEICwvD3bt30adPH5w8eRJZWVlITU1FYmIiPv30U9ja2uLjjz/G9u3bdbY9bNgw/PTTT7CxscHkyZNx584dpKamIjk5GQ8ePMCGDRvQqlUrrXXs7Ozw+uuvY+fOndJznZycjLS0NKxduxb+/v44evQoPvnkE5M9Jk/S9Gjz9fVF27ZtzbbfwkyfPh2pqanYtm0b0tPT8fjxY9y5cweVKlXC66+/DltbWyQkJOD333/Xu35WVha2bt0K4L+2pcbvv/+ON998E0qlEpMmTUJ0dDSysrKQkZGBK1euoF+/fkhLS0O/fv3Yg6mskru6RUTWr6hft2JjY8XIkSO1fmV80vXr16X5s2bNKvF+79y5I60XHh4uTQ8PD5emx8XFGXaninHjxg1pH7NnzzZ4O8bsuRQcHFxor6+srCzp17sVK1boXWbUqFECgGjbtq3OPmxtbYWzs7M4e/as3nVTU1OlXye3bdtW6P0gIiLrV1yvlpSUFOHv7y8ACG9vb6FUKoUQJf/MWr9+vQAg6tatK5KTk/Uuc/LkSaFQKISDg4NITEyUpj969EjqHTNw4MBix7cpSJPtyd4p9erVEwDExo0bS7wtIQr/7P7rr7+kfRX2mdy3b18BQPj4+IisrCyteZqeSwDEgQMHdNbNzs6WHv/StKsKetq23fDhwwUAMWjQoEL3sWjRIr09kPbv3y9te+nSpQbl1+fEiRMCUI/X+eRjKoRpei5p2kZdunQxMLWasXou2draitOnTxe6jbCwMAFAvPbaa3rnb9y4UQAQzs7OIjU1VZquVCpFrVq1inxNCyHEyy+/LACI8ePHF7oMWS/2XCIio6pcubJ0cXV1RXBwMFauXAkAqFu3LpYuXaqzzsOHD6W/K1asWOJ9+fj46N1Gwb/1/VpqDObYR2m9++67hfb6Kjj+xffff68zPycnRzrz3pO9ltatWwelUolu3bohNDRU7/bd3d3Ru3dvAP/9kklEROVLcnIyoqKi0KlTJ9y7dw8AMH78eL09hIr6zFq9ejUA4O233y50LMSmTZuiQYMGyM3NxcGDB6XpP//8M9LS0mBvb1+i8W1KwsvLC4C6N44xbN68GQBQtWpVjBgxQu8ymnF6kpKSCu1F0qZNG3Ts2FFnuqOjI8LCwgAA586de+q8pW3bZWdnS2fR1dezTEPT8+Xff/9FYmKiNH3NmjUAgIYNG+Ltt99+6vwazZo1Q6VKlZCRkYGzZ88abbtF0bQXLaWt2K1bNzRp0qTQ+Zo24Pbt25GWlqYzX9OG7N27N9zd3aXpR44cwfXr1+Hj41Poaxr47zlnW7FsspM7ABGVLQUbBwW9+eabWLFiBZycnMycqPxo06ZNkfPffPNNrFq1Sjr8rWAX9t27dyM5ORlOTk7o37+/1np//PEHAPWgmpUrVy50+5oBvWNjYw29C0REZGWKKt688cYbhR6CVNhnllKpxF9//QVAfQjPnDlzCt3+o0ePAGh/7vz5558A1MWnKlWqFB2+hF566SUcP34cU6ZMwZUrV9CnTx+0bt0aHh4eBm3v5MmTAICOHTsWemhevXr1EBAQgLi4OJw8eVLviU5atGhR6D78/f0B/PcYPY3Stu1OnTqF7OxsAOrhDkoiNjYWfn5+AP57Dl966aVSZ83NzcWaNWsQGRmJCxcu4OHDh8jNzdVZ7u7du6XedllQXFvxlVdegbu7O9LS0rB161atwcETExN1hlvQ0LQVU1JSpNeePprngm3FsonFJSIyKvH/Z24RQiAhIQE7d+7ElClTsH79ejRq1AgffvihzjoFeysV7BFUnKSkJL3bKPj3o0ePivyQM9ST+7AElSpVKnJ+27ZtUa1aNURHR+OHH37QOsue5peonj17Sr/Qamh+fc7IyEBGRkaxOTIzM0uZnIiIrJWmIACoe8z4+PigSZMmeP311/X2qtEo7DNLM5YRoD5DW0kU/NxJSEgAAAQHB5do3ZL46KOP8O+//2LLli1YuXIlVq5cCYVCgQYNGqBbt24YMWIE6tSpU+Lt3b9/HwAQEBBQ5HJVq1ZFXFyctPyTCvYceZKdnfpr3pNnR3vuuedw584dneVbt26NyMhIvdsqbdtO024ACi9MPckYz+H9+/fRuXNnnD9/Xprm5OQEHx8f2NraAgAePHgAlUpVovaMMVSsWBF37961mraii4sL+vbti3Xr1uH777/XKi79+OOPUCqVqFy5Mrp06aK1nuY5z8vLK9FznpWVVfrwZPF4WBwRmYRCoUCVKlUwevRobNu2DQqFApMmTcKBAwd0lg0ODpYGxD59+nSJ93HmzBnp7wYNGuj9u+AyxhQcHCx15zfVPkpL03AqTMGBugseGvfw4UPs2bMHgO4hcYD6V2RA3bVdCFHspajTJxMRUdmSkJAgXWJjY3Hq1CmsWrWqyMISUPhnluYzBwB+/fXXEn3uTJ8+XVrHGIfBPcne3h6bN2/G2bNnMW3aNHTq1AkuLi64cOECFixYgAYNGmDhwoVG368pPHjwAImJiTqXkhQ/Stq2K/gcZmVlleg57NChg9Z+DPH+++/j/PnzqFixItasWYP4+HhkZWXhwYMH0mtU84OjpmBmapo2qbkOwytOcW1F4L9eSYcOHdIqRGrajoMGDdLZjuY5b9GiRYmeb3M9/mReLC4Rkcl16NABgwcPhhAC48aN02p0AOpG2/PPPw9AfeiVvmO89dH8wmZjY6PVKCnYzXzbtm1GuAe67Ozs0K5dOwDqs2MY+guY5pdFAFIXcn1SUlIM2v6TNMWj69evS4cdbN68GXl5efD19cWLL76os47mUDh2YSYiIlOrWLGi9NloyOeOKT+zQkNDMWPGDERFRSE5ORn79+9Hu3btoFQqpd5NJaHpPVLcoVma+cX1NimNmJgYo/wwVFTbruAh9OZ6DvPy8qR24TfffINhw4bpHMqvVCq1er2bwwsvvABAXdQ7duyYwdvR/E+Yo63YoUMHBAYGQqVSYcOGDQCAS5cuST8AP3lIHMC2IqmxuEREZjFt2jTY2tri0qVL+O6773TmawZsTE9Px6JFi4rd3vXr17Fp0yYA6uPDCzYg/Pz80LdvXwDAxo0bce3atRLnLM0vKWPHjgWg/jAvSWYNlUol/V2hQgXpb33d1AHg2rVrSE5OLvH2i1KzZk3p1L2aX6A016+99ppWsUtDc3z+/v37i2zUEBERPS17e3s0b94cALBr165Sr9+6dWsA6nGNjDUAtz52dnZ44YUX8Msvv8DR0RFCCOzfv79E6zZr1gwAcPDgQa02QUFXrlxBXFwcAPWhbJaosLbdc889BwcHBwBP9xyWZt0HDx5IbZTCBqw+duyY2dsxw4YNg4uLCwD1GGIlbWc++brQtBcLayuqVCppLK+npVAo8MYbbwDQbSs+88wzek/uomkrJiQkGC0HWR8Wl4jILGrUqIEBAwYAUJ8B5ckxAHr27Cn1Ppo9ezZ2795d6LYePnyIfv36ITs7Gy4uLtIZVQqaNWsW3NzckJWVhT59+kgNtMI8fvwYffv2LdWvPt27d5cGqpw5cyZ+/vnnYtf59ttvpTOsAICrqytq1KgBANi6davedWbPnl3iTCWh+cVp8+bNuHjxotSDSd8vUQAwfPhw2NnZISkpCREREUVuOzc3VxrYm4iIyBCjRo0CAOzZs0c6bLswTx7O1a9fP3h4eCA/Px/vv/++UQ6/0YwBpY+jo6N0iFBhg3M/aeDAgQCAuLg4rFq1Su8y06ZNA6A+M27nzp1LE9dsCmvbubq6YtCgQQCAzz//HLdv3y5yO08+h2+99RYA4OLFi1i2bFmJsnh4eEiH0+nrQZafn1/o4PKm5OPjg/DwcABAVFQUPvjgg2Jfk3/88QfGjx+vNU1T0Nm2bZve9b/77jujDlKuaRNeunQJJ0+elHowFdZW7NixI2rWrAlAfXiivkHUC7KUMajIyAQR0VOKiIgQAERxbynnz58XCoVCABDLli3TmR8fHy+qV68uAAg7Ozvx3nvviUuXLknzk5OTxbp160RQUJAAIGxtbcXGjRsL3d+2bduEg4ODACB8fHzEvHnzxPXr16X5+fn54vTp0+LTTz8VXl5eAoB4/Phxqe57UlKSqFevngAgFAqFGDRokDhy5IjIzc2Vlrl3755Yt26dePbZZwUA8b///U9rG+Hh4QKAsLe3F0uWLBGZmZlCCCFu374t3nrrLeHo6ChcXFwEALF27VqtdaOjo6XHPjo6ukSZHz16JD0uzZo1EwBE/fr1i1xnxowZ0n4GDx4szp8/L83Ly8sTZ86cETNmzBCBgYHi6NGjJcpBRETWqaSf+08q6WdWfn6+6Ny5swAgHBwcxGeffSbi4uKk+enp6eLAgQPinXfeEZ6enjrrL1++XNpPr169xJkzZ6R5GRkZYvfu3eLll18WKSkpWutp1jl48KDWdD8/PzFlyhRx/PhxkZ2dLU2/fv266NevnwAgbGxsxMWLF7XWCw4O1vvZLYQQffv2le7f119/LTIyMoQQ6rbQiBEjpCz62kvt27cXAEREREQhj+B/z1H79u0LXaYoT9u2u3fvnvD39xcAhL+/v1i/fr1ITU2V5t+/f1/8/PPPonfv3qJr16462x04cKD0uE6ZMkXcuXNHmvfgwQOxcuVKMXz4cK112rZtKwCIgIAAERUVJZRKpZSxS5cuwtHRUbi6uhb6nBT2/Bc3rzgqlUoMGDBA2karVq1EZGSk1usvNTVV7Nq1S7zyyitCoVCIXr16aW1j//790vojRowQSUlJQgghUlJSxKJFi4SDg4Pw9vYWAMSQIUN0MhT1WiyMpo2ouba1tRX37t0rdPn9+/cLOzs7AUC0aNFC7N+/X6s9fPPmTbFs2TLRrFkz8dlnn5U4B1kPFpeI6KmVppHZq1cvAUBUrVpVq4Gmcf/+fREWFiZtD4BwcnKSij+aS5UqVcSvv/5a7P6OHTsmatasqbWu5gPYxsZGmqZQKMRrr72m9SFYUikpKaJ///5S40qzvQoVKggnJyetfderV0+cPHlSa/20tDRRv359aRkbGxvp/trb24sff/yx0EaBIcUlIYTo06ePVq65c+cWubxKpRKffvqp1n10dnYWFStWFLa2tlrbOnbsWIlzEBGR9TF1cUkI9WfrSy+9pPX54uHhIby8vLQ+i+zs7PSuP2fOHK3PeWdnZ53P/id/UCqsgFAwg42Njc7nu0Kh0PnhSIiiv9AnJydLRSLN/ahQoYLWffvwww/13jdLKi4JUXjb7tKlS6J27dpaj523t7dU4NFcOnfurLPNjIwMnbaKh4eH8PT0lG6HhoZqrXPy5EmtbTs6Ogp3d3fp8V2/fn2Rz4mpiktCqNtRM2bMEM7Ozlr3yd3dXcqouXh7e4v169frbGPw4MFay3l5eUmv53HjxokhQ4YYtbj01Vdfae0vLCys2HW2bdumdX/s7e1FxYoVhaOjo9a2Zs2aVeIcZD14WBwRmZWmS/Ldu3exYsUKnfm+vr7Yu3cvDhw4IJ3a18HBAVlZWQgICMCLL76IJUuW4MaNG+jWrVux+2vTpg2uXLmCH3/8Ea+//jpq1qwJJycnpKWlwdvbG23btsUnn3yCy5cvY+PGjbC3ty/1ffLw8MDmzZtx5swZfPjhh2jWrBl8fHyQlpYGe3t71KtXD0OGDMHu3btx/vx5NG3aVGt9Nzc3HDt2DBMnTkS1atVgZ2cHe3t79O3bF8ePH5e6zxtTwW7NNjY20rH1hVEoFJg5cybOnTuHd955B/Xq1YOtrS1SUlJQoUIFtG7dGh999BH+/PNP6bh7IiIiQ3l4eGDXrl3Ys2cPBgwYgKCgIOTk5CAzMxMBAQHo2rUr5s6di6tXr+pdf+rUqfj3338xcuRI6XCd3Nxc1KpVC6+99hoiIyPh4eFRoiz79u3D1KlT8fzzzyMwMFA6jXrNmjUxbNgwnDhxAhMmTCjV/fP09ERUVBRWr16NDh06wN3dHenp6ahcuTL69u2LgwcP4osvvijVNuVSWNuuXr16OHfuHFasWIGuXbvCx8cHqampEEKgZs2a6NevH7799lts2bJFZ5suLi7YunUrdu/ejVdeeQX+/v7Izs6GnZ0dnnnmGbz33nv49ttvtdZp2rQp/vnnH/Tv3x8+Pj5QqVRwd3dH//798eeff+o9I665KBQKTJs2Dbdu3cKcOXPQqVMn+Pv7Izc3F/n5+QgODkbv3r2xatUqxMTE6M26bt06LF68GI0bN4azszNUKhXatGmDLVu24KuvvjJ65tdee02rXVzYIXEF9e7dGzdu3EBERASaN28ONzc3JCcnw9HREaGhoRgxYgS2bduGjz76yOh5SX4KIXgeQCIiIiIiIiIiMgx7LhERERERERERkcFYXCIiIiIiIiIiIoOxuERERERERERERAZjcYmIiIiIiIiIiAzG4hIRERERERERERmMxSUiIiIiIiIiIjIYi0tERERERERERGQwFpeIiIiIiIiIiMhgLC4REREREREREZHBWFwiIiIiIiIiIiKDsbhEREREREREREQGY3GJiIiIiIiIiIgMxuISEREREREREREZjMUlIiIiIiIiIiIyGItLRERERERERERkMBaXiIiIiIiIiIjIYCwuERERERERERGRwVhcIiIiIiIiIiIig7G4REREREREREREBrOTO0B5pVKpcO/ePbi7u0OhUMgdh4iIiAoQQiAtLQ3+/v6wseFvcabC9hAREZFlK2mbiMUlmdy7dw+BgYFyxyAiIqIi3LlzB1WrVpU7RpnF9hAREZF1KK5NxOKSTNzd3QGonyAPDw+jb//27dsICgoy+nbNwVqzW2tugNnlYK25AWaXg7XmBqw3e2pqKgIDA6XPazINU7eHTM1aX98As8vBWnMDzC4Ha80NMLscTJm7pG0iFpdkoun67eHhYZLGlLu7u1U20gDrzW6tuQFml4O15gaYXQ7Wmhuw7uwAeKiWiZm6PWRq1vz6Znbzs9bcALPLwVpzA8wuB3PkLq5NxEEEiIiIiIiIiIjIYCwuERERERERERGRwVhcIiIiIiIiIiIig7G4REREREREREREBmNxiYiIiIiIiIiIDMbiEhERERERERERGYzFJSIiIiIiIiIiMhiLS0REREREREREZDAWl4iIiIiIiIiIyGAsLhERERERERERkcFYXCIiIiIiIiIiIoOxuERERERERERERAZjcYmIiIiIiIiIiAzG4hKAI0eOoGfPnvD394dCocD27duLXefQoUN49tln4ejoiJo1a2LdunUmz0lERERkKmwPERERkaFYXAKQkZGB0NBQLFmypETLR0dHo0ePHujYsSPOnj2LCRMmYMSIEfjtt99MnLT8ik/Jwp83kxCfkiV3FCIiq1Ga905Le58tLI+5ciZYyONgTnK2h8rj401kDsW9Z1rSe78xshpjGe5Hvv1YU1Zj7acssZM7gCV48cUX8eKLL5Z4+eXLl6NatWpYuHAhAKBevXo4duwY/ve//yEsLMxUMcutzSduY2rkeagEYKMA5vZphAHPBckdi4jIopXmvdPS3mcLy2OunJtP3MbkH/82+nYtnZztoa7/O4JZ/Zvj1aZVS7We3HLyVcjOU8odwyDMbn7mzv3zqbuYtuOC9J45s1dDrf+x4uYXZOrsxsha2DIFs5tyP8a+P9svPMTiY6bfjynuz/i2VTDa3zqyPjk/J1+FH/6KNfp+5G5bmYNCCCHkDmFJFAoFtm3bht69exe6TLt27fDss8/iyy+/lKatXbsWEyZMQEpKit51cnJykJOTI91OTU1FYGAgUlJS4OHhYaz4ktjYWAQHBxt9u+ZQMHt8ShbazDsA1ROvUl83R9jaKGRIVzilMh+2ttZZr2V287PW3ACzy6G0uZUqgQfpOTrT9b13lmZZQxgru7eLAx5l5upMN/bngWb/qpxM3Pmyv8k+py2dudtDgRO2wMbRxVjxiYiILIqtQoFjUzqiiqezSbZvyu//qamp8PT0LLZNZH0tbAuQkJAAPz8/rWl+fn5ITU1FVlYWnJ11XzBz587FjBkzdKbfvn0b7u7uRs+YmZmJ2NhYo2/XHApmPx2XrlNYAqD3i4dlyJc7wFNgdvOz1twAs8vh6XOX5r3TuO+zT59dX2EJsOTPg7LPmO0hIiKissYxPxeV05KQ4O6DHDsH/H3xFpoEuJlkX6b8/p+Wllai5VhcMpOpU6di4sSJ0m3NL3VBQUHsufSEgtkdvLJgsyuGPZdMjNnNz1pzA8wuB/ZcMk/PpZzcHGRl5yAbDkbZHukqrD0EqA8b+P399qjs6SRXvFK7fec2ggKt8zAHZjc/c+ZOSMlGl/8d1mpDF/wfK27+k0yZ3RhZi1omN/U+ggKDTL6fki5T0m10/t9hCDPsx1z3x1qynrpyE0M33Xjq/bw2azv6/Ps7phxZj3nt3kRkaFe0aFDdansulYT1tbAtQOXKlZGYmKg1LTExER4eHnp/pQMAR0dHODo6miNemVLF0xlz+zTC5K3npWmf97XM41XLSkHP2lhrdmvNDTC7HAzJvfnEbXwceQFKIWCrUGBOn4ZFjrlU0mVLy5jZTZkTAA4fPoxDh05AGdIC3/9rWT9gWCJjtodsFQrM7dMINSqZ5hddU3Gxt4Wro3U2p5nd/MyZu0YlN8zt00jnPVPzP1bcfHNmN0bWopaJzXoIV0c7k+/H2Pfno/b+WHg43uT7McX9+aB9FavJ+uQ2gr2cnm4/58+jxpw5+Ounn2CjVI/1NeXIekz6YwNsHuwGPv4YaNRI/z+DleOYS08oyRgDkydPxp49e3D+/H8Fj0GDBuHRo0fYu3dvifZT0uMWDWWtX6AA/dmfm7UfD9Jz4OvmiBPhnWVKVrSy9phbC2vNbq25AWaXg6G541OyEJOUiRAfl2J/KSvNsqVh7OymygkAQgjcunULNWrUwLU7iagTVJljLpmpPXT1dgJqB/oVv4KFsdb3FIDZ5SBH7uLeM0v6nmqO7MbIqm+ZJ7Obaj/Gvj+xsbFw8Kpk8v2Y4v7kJt/X+3qxxKxPzte8Xgzaz2+/Ab17A/n56suT7OzUl+3bASOfCIxjLlmI9PR03LhxQ7odHR2Ns2fPwtvbG0FBQZg6dSri4uKwfv16AMCYMWPwzTffYNKkSRg+fDgOHDiALVu24JdffpHrLhgsPiUL0UkZqObjarIuekREJI8qns4lfm8vzbLmUFgeY+ZMSUnB33//jc6dO8PGxgYKhQI1atQAAFS2oMfCXORsD5XHx5vIHIp7z7Sk935jZDXGMtzP0+8nNtl6shptmfPn1YWlnBygsP47+fmAUqle7p9/ylwPJhu5A1iCkydPokmTJmjSpAkAYOLEiWjSpAmmTZsGAIiPj8ft27el5atVq4ZffvkFv//+O0JDQ7Fw4UKsWrWq1KfdldvmE7fRZt4BDFr5N9rMO4DNJ24Xv5IMNp+4LY2/8SA9x2JzEhGR9VAqlVi3bh2OHz+Ow4cPyx3HIpTX9hAREdFTmzNHXTwq7sAwIdTLzZ1rnlxmxJ5LADp06ICijg5ct26d3nXOnDljwlSmFZ+ShamR56VByFQCmLz1PBb8dk32gbLVg7+qfznVN7Drx5EX0K62r8X8ykJERNbH1tYWnTt3xtGjR/Hss8/KHccilMf2EBER0VNLTAR+/ln/oXD65OcDP/0EfPklUKmSSaOZE4tL5VR0UobOGdgASzqlc+H/mEohEJOUyeISERGVWm5uLhwc1GeDa9CgAerWrQtbW1uZUxHOngXcCgwkXKECUK0akJ0NXLqku7ymIHj1KpCRoT0vJATw9gYePADu3NGe5+4O1KqlPizh3391t9uoEWBvD9y8CaSkaM8LCAD8/IDHj4HoaACAQ3w88PAh4OwM1KunXu7MGd1fruvVUy8TG6teviA/P/W209KA69e159nb/3fYxPnzQF6e9vxatdT3KS5O/eWmoIoVgeBgICsLuHxZe55CoX6MAPW8rCzt+dWqqZ+DxET1tgvy9ARq1FBnKTDeliQ0FLC1Vd+XJ09fHRgI+PoCjx4BMTHa81xdgTp11H+fPq273fr1AScnIDoaDpcuaT+OVaqoL6mpQIFDOwEAjo5Agwbqv8+d0/3yV7u2+rV39y5w/772PB8fICgIyMwErlzRnmdjAzRurP770iX1a7Wg6tUBLy8gIQG4dw9AgdeLl5d6fm4ucOGC7n1t3Fi9/WvXgPR07XlBQepcSUnA7Sd687u5qe+PSqX+n3pSw4aAgwNw6xaQnKw9z98fqFxZPf3WLe15Tk7q5wdQb1el0p5fty7g4qLOk5SkPa9SJaBqVfX9uHZNe56dHfDMM+q/L15UH05UUM2agIcHEB+vvhRUivcIhxs3tF8vZnyPkBjwHiG9XuR6j/j/XqwGvUfY2cn6HoHHj7XnleI9wuHOHe3XS0neI377reSFJY38fODQIaBdO/V7hCajNRMki5SUFAFApKSkmGT7MTExRc6/l5wpqk3ZLYIna1+affa7aDF7v6yXZjP3/vf3Z7/rZKw+5RdxLznTJI/b0yjuMbdkzG5+1ppbCGaXg7XmFsJysiuVSvHrr7+K5cuXi+zs7GKXN/XnNKlJj7P6q9Z/l9dfVy9w/br2dM1Fo2VL3Xnff6+e9803uvO6dtXsWP92799Xz+/ZU3fewoXqeVu26M5r0uS/TA4OuvMvXFDPe+st3XlTpqjnHTyoOy8g4L/tBgTozj94UD1vyhTdeW+9pZ534YLuPAeH//43mzTRnb9li3rewoW683r2VM+7f1//Y6j5n+naVXfeN9+o533/ve68li3/u6/6tnv9unre66/rzouIUM/bu1d3Xo0a/23Xx0d3/p9/que9/77uvHfeUc87dUp3nrv7f9utX193/o4d6nlz5ujOe/VV9bw7d/TfV817VPv2uvNWrlTPW7lSd1779up52dn6t3vnjnr+q6/qzpszRz1vxw7defXr//d6cXfXnX/qlHreO+/oznv/ffW8P//Unefj899jWKOG7vy9e9XzIiJ05/E9Qn0x4XuExID3iJiYmPL1HhEerj9TcZeVK/97j9BkNJAp21slbRPxbHEysYSzxW0+cRuTt/5XTf68byOjntLZUE9mN/Wpp43FWs9cAjC7HKw1N8DscrDW3IDlZE9LS8OKFSuQkZGBV199FQ00v1IWwtSf06QmPc6HD8PDCnsuxcfHo0qVKlbZcynW21v9v2mFPZfiL11SP+4aVtJzSXq9WGHPpVhXV/XrxQp7LsXfuKH9erGSnkvS68UKey7F2tkh2N/fKnsuxd+5o/16Kcl7xPr1wJAhupmKs3mz0XouWcLZ4lhckoklFJcA4LlZ+/EgPQe+bo44Ed7Z6DkMoS+7KU89bSyW8gXKEMxuftaaG2B2OVhrbsCyssfFxeHx48do2LBhscuyuGQe1v44W9Lru7SY3fysNTfA7HKw1txAOcyemKguopbm0Dg7O3VhzkhjLllCcYlniyvnNIN3yz2Id3GqeDqjVY2KFltYIiIiy/PgwQPEF/i1OyAgoESFJSIiIqIS8/MDXn1VXTAqCTs7oF+/MjWYN8DiEhEREZVBcXFxWL16NTZu3IiUJw9dICIiIjKmjz9WF40UxXTaUCjUy02dCkB9hM6fN5MQn5JV6ColWcYS8GxxREREVOZUrFgRnp6ecHJygr29vdxxiIiIqCxr1AjYvh3o3Vt9eJy+Q+Ts7NSX7duRX78BNvwZgxm7LkIlABsF8N4LtdCxTiXk5KuQnadETr4KB6/ex49/34aAepm5fSxjnGR9WFwiIiKiMsfJyQmDBw+Gk5MT7EraTZ2IiIjIUGFhwD//IGvmLNhv/Rl24r/B7/MVNthXty1WtO6PC4eVUB78VWtVlQC+3H8dX+6//uRWtZb5OPIC2tX2tcjhYtjaKg8SE4GdO4FDh4AOHYCXX1YfF0pERFRG5OfnY9euXahbty7q/f8ZedwKnn2MiIiIyNQaNcKZeUswrvLL6Hzjb7SKPYfjwc9gf80WeOjqpV5GVfg51XxcHeDhYg9HO1vk5itx84H2GVGVQiAmKZPFJTKz8+eBOXOAn3/+r1vexo3AO++oBxz7+GN58xERERnJyZMnce7cOVy5cgUhISFwdra8RhcRERGVfdV8XPHYzQsX/Grg871fY2XzV/DYzQsb3mqBwAoucLS3QXJmLl5cfFSrzmSrUGDXe22lwlF8ShZazz2AgqUoW4UCIT4u5r1DJcQBvcsop8OHgebNtQtLGvn56unNm6PF9RPyBCQiIjKi5s2bo1GjRujfvz8LS0RERCSbKp7OmNunEWz/f3BvW4UCc/s0QpuaPgiq6AI/DyfUqeyhs8ycPg21eiRV8XRGz1B/6ba+ZSwJey6VRefPo9KoUUBuLiAK6XKXnw8olZj/wzRcefN/SPGoa96MRERET+nRo0eoUKECFAoFbGxs0KdPH7kjEREREWHAc0HoNLQZsA5YPbQZfPUMwj3guSC0q+2LmKRMhPi46C0aNQ2ugJ3/3kPL6t7434DGFltYAthzqUzKmvEZRH5+4YUlDSFgq1LhneNboCziuE8iIiJLc/HiRSxduhTHjh2TOwoRERGRDl93J61rfap4OqNVjYrFFo2s4ds6i0tlzPa9p2AfuRU2SmWJlrdTKdHjyjGoEhOx+cRtE6cjIiIyjoyMDCiVSsTFxUEU92MKERERkbm5uwNdu6qvDXQq9jEA4O9bj9Bm3gGL/s7Ow+LkdvYsUPBsNhUqANWqAdnZwKVLuss/+6z6+upVIEN75PgEbz9ELd+C3gVOeVgSdkKFlrfP4+PIChZ7WkMiIqKCmjdvDnd3d9SpUweK/x+vgIiIiMhi1KoF/PabwavHp2Rh17/3pNsqAXwcecFiv7OzuCS39u21b7/+OvDDD8Ddu0DTprrLa36dHToU+OsvrVmpC5bCJSfLoBhuuZkWfVpDIiIq33JycvDHH3+gffv2sLW1BQDUq1dP5lREREREhVAq1R1CXF2B/2+7lEZ0UobO4XCW/J2dxSW5HT6s23MJAKpWBU6dKny9det0ei55ePsh82iMQTHSHVws+rSGRERUfgkhsHHjRty+fRsZGRno2bOn3JGIiIiIivbvv+oOI6dO/XcEUilU83GFAtrjLVnyd3YWl+TWuDHg4aE73cmp6BdgnTo6kyoDeGFMf+TvXAC7Uhwal6+wwYngZyz6tIZERFR+KRQKPP/889i1axea6uvVS0RERFTGVPF0Rs9Qf+z8/0PjbBUKi/7OzgG9y5je3ZoiqmE75CtK9tQKWzs87tEbOz57BQP0nB6RiIhILvn5+dLfNWvWxLhx4+Dv7y9jIiIiIiLzaRqsPrKpXhV3RL7TyqK/s7O4VAat7zAI+Ta2UKGYAU4VCijs7eA7Z7rFVj+JiKh8OnHiBFasWIHMzExpmp0dO1wTERFR+aE5W9zl+DS8svRPiz5bHItLZdDNytUxqk848uzsgMIa4nZ2gKMjsH070KiRWfMREREVJTc3F3/88QeSkpJw5swZueMQERERmV1hZ4uLTzHsJF6mxuJSGXWkelMMf3sJ0K+fboHJzk49/Z9/gLAweQISEREVwsHBAa+//jo6d+6M1q1byx2HiIiIqPQaNQLu3ze4M0dRZ4uzROxfXobdrFwd+Gok8OWXwKFDQGqqevDwDh2ASpVkTkdERPSfjIwMPH78GFWrVgUA+Pr6wtfXV+ZURERERAaytweeoi1jbWeLY8+l8qBSJfUpEHfuVF+zsERERBYkOTkZq1atwoYNG/DgwQO54xARERE9vZs3gZdfVl8bQHO2OA2eLY4sQ0oKsGuX+pqIiMiCuLq6ws3NDc7OzlAoijkZBREREZE1MMJ3cM3Z4lpW98axKR0t+mxxPCyOiIiIZGVvb4+BAwcCUBeaiIiIiOg/T469ZInYc4mIiIjMSgiBQ4cO4fTp09I0V1dXFpaIiIiICjgV+xgA8PetR2gz7wA2n7gtc6LCsecSERERmdWVK1dw+PBh2NjYICQkBN7e3nJHIiIiIrIo8SlZ2PXvPem2SgAfR15Au9q+FjnuEotL5UVAALBwofqaiIhIRnXr1kVoaCgCAwNZWCIiIqKy6Sm/g0cnZegcDqcUAjFJmRZZXOJhcf9vyZIlCAkJgZOTE1q0aIF//vmn0GXz8vIwc+ZM1KhRA05OTggNDcXevXvNmNYAfn7AxInqayIiIjNLS0uDEOomkkKhQK9evdC0aVOZU5E+Zb5NREREZA5P+R28mo8rnjzNia1CgRAfl6fPZgIsLgHYvHkzJk6ciIiICJw+fRqhoaEICwvD/fv39S4fHh6OFStW4Ouvv8alS5cwZswYvPLKKzhz5oyZk5fC48fATz+pr4mIiMzo7t27WLFiBX7//XdpGs8KZ5nKRZuIiIjIHJ7yO3gVT2f0DPWXbtsqFJjTp6FF9loCWFwCACxatAgjR47EsGHDUL9+fSxfvhwuLi5Ys2aN3uW///57fPzxx+jevTuqV6+Ot99+G927d8fChQvNnLwUoqOB/v3V10RERGb0+PFjZGRkIDo6Gnl5eXLHoSKUizYRERGRORjhO3jT4AoAgHpV3BH5TisMeC7IWOmMrtyPuZSbm4tTp05h6tSp0jQbGxt07twZx48f17tOTk4OnJyctKY5Ozvj2LFjhe4nJycHOTk50u3U1NSnTE5ERGQdGjVqBIVCgVq1asHe3l7uOFQIc7SJ2B4iIiIqOc3Z4i7Hp+GVpX9ibp9GFltgKvfFpaSkJCiVSvg9cRykn58frly5onedsLAwLFq0CO3atUONGjUQFRWFyMhIKJXKQvczd+5czJgxQ2f67du34e7u/nR34glKZb50HRsbCwBwiI9HFQDx8fHI/f9pliozM1PKbU2sNTfA7HKw1twAs8vB2nKrVCpcvHgRdevWRV5eHmJjY+Hu7o6EhAS5o5VYWlqa3BHMzhxtInO2h8zB2v43C2J287PW3ACzy8FacwPMrvG038Hvp+fpnC1uauR5VHfJRSU37R/rTPmYl7RNVO6LS4ZYvHgxRo4cibp160KhUKBGjRoYNmxYoV3GAWDq1KmYOHGidDs1NRWBgYEICgqCh4eHUfPZ2t4AkA9bWzsEBwerJz58CACoUqUKoJlmoWJjY//LbUWsNTfA7HKw1twAs8vB2nJv374d//77L9LT09GyZUuryq7BHjUlU9o2kTnbQ+Zgbf+bBTG7+VlrboDZ5WCtuQFmlzzld/C4m0k6Z4tTCSDfqQKCgytqTTflY17SNlG5H3PJx8cHtra2SExM1JqemJiIypUr613H19cX27dvR0ZGBmJjY3HlyhW4ubmhevXqhe7H0dERHh4eWhezcnYGmjRRXxMREZlQ06ZNpTOHceBu62GONpHs7SEiIiJzecrv4DxbnJVxcHBA06ZNERUVJU1TqVSIiopCq1atilzXyckJAQEByM/Px9atW9GrVy9TxzVcvXrA6dPqayIiIiNTqVTS34GBgZgwYQLq8TPHqpSbNhEREZE5POV3cJ4tzgpNnDgRK1euxHfffYfLly/j7bffRkZGBoYNGwYAePPNN7UGt/z7778RGRmJW7du4ejRo+jWrRtUKhUmTZok110gIiKSzY0bN7Bs2TKtbtOOjo4yJiJDsU1ERERkOazpbHEsLgEYMGAAFixYgGnTpqFx48Y4e/Ys9u7dKw1oefv2bcTHx0vLZ2dnIzw8HPXr18crr7yCgIAAHDt2DF5eXjLdgxI4cwZwdFRfExERGYlKpcL+/fuRlJSEo0ePyh2HnlK5aBMRERGZgxG+gz95trjNJ24bK53RcUDv//fuu+/i3Xff1Tvv0KFDWrfbt2+PS5cumSGVEQkB5Oaqr4mIiIzExsYGAwcOxF9//YUuXbrIHYeMoMy3iYiIiMzhKb+Dx6dk6Zwt7uPIC2hX29ciD41jzyUiIiIqlfz8fNy9e1e67eXlhW7dusHW1lbGVERERERlR3RShs7Z4pRCICYpU5Y8xWFxiYiIiEosOzsb69evx/r163Hv3r3iVyAiIiKiUuPZ4oiIiKjMcnBwgKOjI2xtbZGbmyt3HCIiIqIyydrOFscxl8qLevWACxeA6tXlTkJERFbMxsYGr776KtLS0uDj4yN3HCIiIiLLZITv4E2DK2Dnv/dQr4o75vVphNDACkYMaFzsuVReODsDDRqor4mIiErh/PnzOH78uHTb0dGRhSUiIiKiohjhO7g1nS2OxaXyIjYWGDFCfU1ERFRCcXFxiIyMxL59+3D7tuU2aIiIiIgsylN+By/sbHHxKVnGSmhULC6VFw8fAqtXq6+JiIhKyN/fH8899xxatWqFwMBAueMQERERWYen/A5ubWeL45hLREREpCU7Oxv29vawtbWFQqHAiy++CIXiyfOVEBEREZGpaM4WV7DAxLPFERERkVVITk7GmjVrsHv3bgihbs6wsERERERkXtZ2tjgWl4iIiEiSlJSEpKQk3Lx5E+np6XLHISIiIiq3mgarzw5Xr4o7It9phQHPBcmcqHAsLpUXfn7AlCnqayIiokLUrFkTffr0wYgRI+Du7i53HCIiIiLrZITv4DxbHFmegABg7lz1NRERUQFnz55FVtZ/Zx5p2LAhPDw8ZExEREREZOWe8js4zxZHliktDTh0SH1NRET0/w4fPowdO3Zg8+bNUCqVcschIiIiKhue8ju4tZ0tjsWl8uL6daBjR/U1ERHR/6tbty4cHR1Rq1Yt2NiwWUBERERkFE/5HVxztriC9J0tLj4lC6fj0mXv0WQn696JiIjI7IQQ0hng/Pz88N5778HFxTJPa0tERERUHmnOFrfz/w+Ns1FA52xxm0/cxtTI81AJwGZXDOb2aSTboN8sLhEREZUj9+/fx7Zt2/Dqq6+iYsWKAMDCEhEREZGFUwng3zspSM68iXvJWbiVlIGj15O05n8ceQHtavtqFaDMhcUlIiKicmTfvn1ISEjAb7/9hkGDBskdh4iIiIj0eHJAbwDY+E/RZ4vTjMnE4hKZjr29epR6e3u5kxARkYx69+6Nffv2oVu3bnJHISIiIiq7nvI7uL4BvQGgTY2KCA30goujHRbuuwpRYCF9YzKZC4tL5UWjRsDdu3KnICIiMxNCICEhAVWqVAEAuLm5oU+fPjKnIiIiIirjnvI7eDUfV9go1Ie7adgqFFjQP1TqmeTr5oDJW88DABR6xmQyJ54WhoiIqIxSKpWIjIzEqlWrEB0dLXccIiIiIiqhKp7OmNunEWz//yQstgpFkcUjoa+bkxmx51J5cf488OKLwK+/qiuoRERU5tnY2ED8f0sjLS1N5jRERERE5YgRvoMPeC4I7Wr7IiYpEyE+LlqFpfiULEyNPK+1PAf0JtPLywPi4tTXRERULigUCvTu3RstWrRAYGCg3HGIiIiIyg8jfQev4umst1gUnZShdcgcIO+A3jwsjoiIqAy5c+cOjh49Kt22s7NjYYmIiIiojNGMyVSQnAN6s7hERERURqSkpGD9+vU4cOAALl26JHccIiIiIjIRzZhMGnIP6M3D4oiIiMoIT09PtGnTBgkJCahZs6bccYiIiIjITDigN5lHrVrAwYPqayIiKjOUSiVUKhXs7e0BAO3bt4cQAjY27JxMREREJBsTfwe3tAG92fIsL9zdgQ4d1NdERFQm5OTk4Mcff0RkZCRUKhUA9SDeLCwRERERyczE38GLGtBbDmx9lhdxccDUqeprIiIqEx48eICYmBjcvHkTDx48kDsOEREREWmY+Ds4B/QmeSQmAvPmqa+JiKhMqFq1Kvr06YOhQ4fCz89P7jhEREREpGHi7+CWNqA3i0v/b8mSJQgJCYGTkxNatGiBf/75p8jlv/zyS9SpUwfOzs4IDAzE+++/j+zsbDOlJSKi8urGjRtIS0uTbtevXx/+/v4yJqKyhm0iIiIi6yP3gN4sLgHYvHkzJk6ciIiICJw+fRqhoaEICwvD/fv39S6/ceNGTJkyBREREbh8+TJWr16NzZs34+OPPzZzciIiKk/Onz+PjRs3YuPGjcjNzZU7DpVBbBMRERFZh8IG9I5PyZIlD4tLABYtWoSRI0di2LBhqF+/PpYvXw4XFxesWbNG7/J//vkn2rRpg0GDBiEkJARdu3bFa6+9Vuwve0RERE+jatWqcHZ2RpUqVWBrayt3HCqD2CYiIiKyDhzQ28Lk5ubi1KlT6Ny5szTNxsYGnTt3xvHjx/Wu07p1a5w6dUpqON26dQt79uxB9+7dzZLZIBUrAm+9pb4mIiKrVKFCBYwePRo9e/ZkcYmMrty0iYiIiMzBxN/BLW1AbztZ9mpBkpKSoFQqdQZC9fPzw5UrV/SuM2jQICQlJaFt27YQQiA/Px9jxowpsgt4Tk4OcnJypNupqanGuQMlFRwMrFpl3n0SEdFTSU9PR2RkJBo2bIjg4GAAgIeHh8ypqKwyR5tI9vYQERGRuZj4O7hmQO/JW9WHxsk9oHe5Ly4Z4tChQ5gzZw6WLl2KFi1a4MaNGxg/fjw+++wzfPrpp3rXmTt3LmbMmKEz/fbt23B3dzdqPqUyX7qOjY0FACiys2F3+zbyg4IgnJyMuj9jy8zMlHJbE2vNDTC7HKw1N8Ds5nTs2DFER0fj0aNH8Pb2hkKhKH4lC2Ntj7lGwUHTqXClbROZsz1kDtb6+gaYXQ7WmhtgdjlYa26A2TXM8R384cNH0t9CAA8fPkRsrHFH9i5pm0ghhNxjissrNzcXLi4u+Pnnn9G7d29p+pAhQ5CcnIwdO3borPP888+jZcuW+OKLL6RpP/zwA0aNGoX09HTY2Ogebajvl7rAwECkpKQY/VfolnOikJCajcoeTvjr4xfUE0+fBpo2BU6dAp591qj7M7bY2FjpF3prYq25AWaXg7XmBpjdnLKzs7F9+3Y0aNAAjRo1Kn4FC2Rtj7lGamoqPD09TfI5banM0SYyZ3vIHKz19Q0wuxysNTfA7HKw1twAs0tM/B08PiULbeYd0Bp3yVahwLEpHY3ae6mkbaJyP+aSg4MDmjZtiqioKGmaSqVCVFQUWrVqpXedzMxMncaSZuyLwmp1jo6O8PDw0LoQERE9KSkpSfrbyckJAwcO5GcGmYU52kRsDxERERmHpQ3ozcPiAEycOBFDhgxBs2bN0Lx5c3z55ZfIyMjAsGHDAABvvvkmAgICMHfuXABAz549sWjRIjRp0kTqAv7pp59ygFUiIjKYEAKHDx/GkSNH0L9/f9StW1fuSFQOsU1ERERkHTQDej/Zc4kDestowIABePDgAaZNm4aEhAQ0btwYe/fulQa0vH37ttavcuHh4VAoFAgPD0dcXBx8fX3Rs2dPzJ49W667QEREZUB6ejqEEEhISGBxiWTBNhEREZF14IDeFurdd9/Fu+++q3feoUOHtG7b2dkhIiICERERZkhmJAoF4OCgviYiIoujUCjQvXt31KlTB7Vq1ZI7DpVjZb5NREREZA5m/g4u92ja5X7MpXKjSRMgJ0d9TUREFuHx48c4fPiwNDaNjY0NC0tEREREZYGJv4PHp2RhauR5rWkfR15AfEqWSfZXHPZcIiIikkFOTg7WrFmD9PR0ODs7o3nz5nJHIiIiIiIrUdSA3nIcGseeS+XF5cvq0x9evix3EiIigvqsWW3btkXlypVRr149ueMQERERkTGZ+Du4ZkDvgjigN5leVhZw5oz6moiIZCGEgFKphJ2d+uO3RYsWaNq0O+m/bQAAyuZJREFUqXSbiIiIiMoIE38Hr+LpjFeaBGDr6ThpWu8m/rIN6M2eS0RERGagUqnwyy+/YMOGDVAqldJ0FpaIiIiIqLTiU7Kw7Uyc1rTtZ+7JNuYSi0tERERm8PjxY5w/fx4xMTGIjo6WOw4RERERWbGixlySA38uJSIiMoOKFSuiX79+yMvLQ82aNeWOQ0RERERWTDPmUsECk5xjLrHnUnlRrRqwZYv6moiIzCIhIQGPHj2SbtesWZODdxMRERGVByb+Dl7F0xlz+zSSbisUwJw+DWUbc4k9l8qLChWAfv3kTkFEVG7ExsZi48aNcHNzw1tvvQUXF3l+RSIiIiIiGZj5O7gQxS9jSuy5VF4kJgKLFqmviYjI5CpWrAhnZ2d4eHjAxoYft0RERETliom/g8enZGFq5HmtaR9HXuCA3mRicXHABx+or4mIyOTc3NwwdOhQvPHGG3BycpI7DhERERGZk4m/g1vagN4sLhERERlBXl4eIiMjERsbK03z8vKCra2tjKmIiIiIqCzSDOhdEAf0JiIisnLHjh3D+fPn8fPPPyMvL0/uOERERERUhlXxdMYrTQK0pvVu4i/bgN4sLhERERlB27ZtUatWLfTt2xf29vZyxyEiIiKiMiw+JQvbzmgfcrf9zD3Zxlzi2eLKC09PoGdP9TURERlFSkoKPP//fdXe3h6DBg2SORERERERWQQTfwcvaswlOXovsbhUXtSoAezcKXcKIqIy49y5c9i5cyd69OiBJk2ayB2HiIiIiCyJib+Da8ZcKlhg4phLZHp5ecCDB+prIiJ6ag8ePIBSqcStW7cghCh+BSIiIiIqP0z8HZxjLpE8zp8HKlVSXxMR0VPr1KkT+vTpgz59+kChUBS/AhERERGVHyb+Dm5pYy6xuERERFQC2dnZOHr0qNRLSaFQoFGjRiwsEREREZHZFTXmkhw45hIREVExVCoVvvvuOyQkJCAvLw+dOnWSOxIRERERlWMcc6kIZ86cwaRJk/Dyyy+jc+fO0vTY2Fhs2bIFjx49kjEdERGVVzY2NmjVqhU8PDxQv359ueMQERERUTlnaWMuWUzPpUmTJmHhwoVahxtoCCEwaNAgLFy4EOPHj5crIhERlTMqlQo2NurfYZ555hnUrVsXDg4OMqciIiIiovKusDGXPgyrI0uBySJ6Lq1duxYLFizASy+9hHPnzmHq1Kla80NCQtC8eXPsNOFp/Mq80FAgJUV9TURERRJC4K+//sKaNWuQV+AMHywsEREREVGJmPg7uKWNuWQRxaWlS5eiXr162Lp1Kxo2bKi38V63bl1cv35dhnRlhK0t4OGhviYioiJlZmbiyJEjiIuLw7lz5+SOQ0RERETWxsTfwTVjLmntsryPuXTp0iV06dIFdnaFH6Xn5+eH+/fvmzFVGXP9OhAWpr4mIqIiubq64rXXXkOXLl3w7LPPyh2HiIiIiKyNib+DW9qYSxZRXLKzs0Nubm6Ry9y7dw9ubm5mSlQGpaUB+/apr4mISEdaWprWjxiBgYFo3bq11hiAREREREQlYuLv4IWNuRSfkmWS/RXHIopLjRo1woEDB6BUKvXOz8zMxP79+9G0aVMzJyMiovIgKSkJq1atwg8//IDU1FS54xARERERFYljLukxfPhwXLt2DWPGjEFOTo7WvNTUVAwdOhQJCQkYOXKkTAmJiKgsc3V1hYODAxwcHAr9oYOIiIiIyFJY2phLhQ9yZEbDhw/H/v37sXr1amzevBleXl4AgObNm+Py5cvIyMjA0KFD8eqrr8oblIiIyiRnZ2e8/vrrcHR0hLOzPMepExERERGVlGbMpa2n/zs0rtyPuQQAGzduxIoVK1CtWjXExcVBCIGTJ08iKCgIy5Ytw5o1a+SOaN0CA4FvvlFfExGVc0IIREVF4erVq9I0Ly8vFpaIiIiIyDhM/B2cYy4VYeTIkfj333+Rnp6Ou3fvIjU1FRcvXsTo0aNNvu8lS5YgJCQETk5OaNGiBf75559Cl+3QoQMUCoXOpUePHibPaTBfX2DsWPU1EVE5d+bMGRw7dgxbt25Fenq63HGILEqZbxMRERGZg4m/g3PMJT2OHDmC27dvS7ednZ3h7++vdXa4O3fu4MiRIybZ/+bNmzFx4kRERETg9OnTCA0NRVhYmNZZgwqKjIxEfHy8dLlw4QJsbW3Rr18/k+QzikePgB9+UF8TEZVzoaGhqF27Nrp3784zkRIVUC7aREREROZg4u/gljbmkkUUlzp27Ih169YVucz69evRsWNHk+x/0aJFGDlyJIYNG4b69etj+fLlcHFxKfRQPG9vb1SuXFm6/P7773BxcbHshlRMDDB4sPqaiKgcysjIgBDqn3dsbW0xcOBANG7cWN5QRBamXLSJiIiIzMHE38E1Yy4VVO7HXNI09ouiUqmgUCiKXa60cnNzcerUKXTu3FmaZmNjg86dO+P48eMl2sbq1asxcOBAuLq6FrpMTk4OUlNTtS5ERGQet2/fxpIlS3Dp0iVpmik+U4ismTnaRGwPERERGYeljblkEWeLK4nr16/D09PT6NtNSkqCUqmEn5+f1nQ/Pz9cuXKl2PX/+ecfXLhwAatXry5yublz52LGjBk602/fvg13d/fShS6GUpkvXcfGxgIAHOLjUQVAfHw8cv9/mqXKzMyUclsTa80NMLscrDU3YJ3ZL168iKysLNy6dQvR0dGwsbGI31ZKzBofcw1rzZ6WliZ3BLMzR5vInO0hc7DW1zfA7HKw1twAs8vBWnMDzK5h6u/gp+PS9Y659PfFW2gSYLxhH0raJpKtuDR8+HCt29u3b0eMnu5iSqVSGm/pxRdfNFO6klu9ejUaNWqE5s2bF7nc1KlTMXHiROl2amoqAgMDERQUBA8PD6NmsrW9ASAftrZ2CA4OVk98+BAAUKVKFUAzzULFxsb+l9uKWGtugNnlYK25AevMHhQUhMqVK8PT0xPVqlWTO06pWeNjrmGt2dmjpvRK0iYyZ3vIHKz19Q0wuxysNTfA7HKw1twAs0tM/B3cwSsLip0xKFhfUiiA/2PvzsOiqh43gL/DAMO+I6CyuYE7gqJm7hiWue9ZKqn1NUmLbLF+rqXmkktlaZqaZrlr5q4kmjvivoAbiwugiIKAMMDc3x/EzZFFsJm5M8z7eR6e65x779x3Bpx7zplzz23ZsJZGL42raJ1Iss6lp+dYkslkOHv2LM6ePVvqtjKZDC1atMD8+fM1nsPFxQVyuRypqalq5ampqXB3dy933+zsbKxduxbTpk177nEUCgUUCsV/yvqfWFsDrVoVLYmIqrjCwkJER0ejRYsWkMvlkMlkCAwMNNhv0Yh0QRd1IsnrQ0RERLoiRRv8+TMOaY1k1wXEx8cjPj4eN2/ehCAI+OCDD8Syp3+SkpKQmZmJ48ePo06dOhrPYW5ujqCgIERGRoplKpUKkZGRaN26dbn7btiwAXl5eXjzzTc1nkvj/PyAY8eKlkREVdzGjRuxZ88e7Ny5U+ooRAbDaOpEREREuqDlNnh8WnaJviQBQEJajlaO9zySjVx6eqjZihUr0KxZM8mGzkVERGDYsGFo3rw5goODsWDBAmRnZyMsLAwAMHToUNSoUQMzZ85U2+/nn39Gr1694OzsLEVsIiIqQ0BAAOLj4+HHDnWiSmGdiIiIyDD4uljDRAa1eZfkMhl8XKwkyaMXE3oPGzZM0uMPHDgQ9+/fx6RJk5CSkoKAgADs3r1bnNAyKSmpxOSvcXFxOHz4MPbu3StF5Mo7fRoICgJiYoDAQKnTEBFpnCAI4h3g/Pz8MG7cOFhaSnMrViJDZRR1IiIiIl3Qchvcw94SvZvVwKbT/94xrlez6hqdb6ky9KJzqVhubi6io6Nx9+5d5OXllbrN0KFDtXLs8PBwhIeHl7ouKiqqRJmfnx8EQcILGomISBQXF4dDhw7hzTffFDuU2LFE9GJYJyIiItJ/yRlPsOXMHbWyrWfuYnyonyQdTHrTubRo0SJMnDgRGRkZpa4v/kZaW51LRERkmAoKCrBr1y5kZGTg6NGj6Ny5s9SRiIiIiIi0Kj4tW+2SOAAoFAQkpOVI0rkk2YTeT9u8eTPef/99eHp6Yu7cuRAEAT179sSMGTPQtWtXCIKAvn37Yvny5VJHJSIiPWNqaorBgwcjODgYHTp0kDoOEREREZHW+bpYQ/ZMmUwGyeZc0ovOpQULFqBatWo4duwYPvzwQwBFk7F++umn2LFjB3799Vds3bpVsgm/iYhIvyiVSrXbpbu5ueHVV1+FXC6XMBURERERkYQkvEpdLzqXzp8/jx49esDK6t8etsLCQvHfb7zxBjp16oRp06ZJEa9qaNAAuHataElEZMCys7Pxyy+/4JdffkF6errUcYiIiIiIStJyGzw+LbtEX5IAICEtRyvHex696FzKz8+Hq6ur+NjS0hKPHj1S26Zp06Y4ffq0jpNVIRYWQJ06RUsiIgNmZmYm/jsnR5qTJxERERFRubTcBudlcaWoXr06kpOTxcfe3t44c+aM2jaJiYkwNdWb+ccNT3w88OabRUsiIgNmbm6OwYMHY+TIkahZs6bUcYiIiIiISpKiDW7sl8W1aNFCbVRS165dceTIEcycOROXLl3CkiVLsHnzZrRo0ULClAbu4UNgzZqiJRGRgTl79izOnz8vPraxsYGTk5OEiYiIiIiIyqHlNjgviytF//79kZeXh4SEBADAhAkTULNmTfzf//0fmjRpgtGjR8PGxgazZ8+WNigREencjRs38Mcff+CPP/7AvXv3pI5DRERERCQ5XxdrmDxzXZxcJpPssji9uM6sd+/e6N27t/jY1dUVZ8+exbJly3Dz5k14e3vjrbfeQo0aNSRMSUREUqhVqxYaNGgAZ2dntfn5iIiIiIiMlYe9JXo3q4FNp++IZb2aVYeHvaUkefSic6k0jo6O+Pjjj6WOQUREEsjNzYVCoYBMJoNMJkPfvn1hYqIXg22JiIiIiCSXnPEEW87cUSvbeuYuxof6SdLBZDA19b///hsdOnSQOobh8vAAJk8uWhIR6bH09HQsW7YMf/31l1jGjiUiIiIiMihaboPHp2VD9cykS4WCYNxzLqWnpyMzM7PUdcePH0eXLl3QoUMH/P333zpOVoV4eABTprBziYj03u3bt/HgwQNcuHABubm5UschIiIiIqo8LbfBfV2s8cyUS5DJINmcS5J2Lq1btw61atWCq6srHB0d0bRpUxw9ehQAkJycjD59+qBNmzaIjIxEYGAgtm3bJmVcw5aZCezZU7QkItJjTZo0weuvv44RI0bAwsJC6jhERERERJUnRRv82dvH6ZBknUuRkZEYPHgwEhISYGVlBSsrK1y4cAGvvfYaTp48iebNm2Pr1q1o1qwZ/vjjD0RHR6Nbt25SxTV8168DXbsWLYmI9IggCDh37hzy8/PFsqCgINja2kqYioiIiIjoP9ByGzw+LbtEX5IAGN9lcQsWLICJiQnWrl2Lx48f4/Hjx1izZg0eP36MLl264OHDh1i2bBlOnTqF7t27SxWTiIi0bP/+/di6dSu2bNkCQZDw6xYiIiIiIgPBy+L+UTwSacCAAWLZ4MGD0a1bN2RlZWHx4sV4++23pYpHREQ6Uq9ePZiamsLLywsy2bOnSCIiIiIiqhBjvCzuwYMHaNiwYYny4rJevXrpOBEREenK0yOUvL29MXbsWLRq1UrCREREREREhoOXxf2jsLCw1Ilai8vs7Ox0HalqUyiA2rWLlkREEkpJScHy5cvx+PFjsYzzKxERERFRlaLlNjgviyNpNGxYNJFYKaPFiIh0RRAEbNu2Dbdv38a+ffukjkNEREREpB1StMElvCzOVLpDA99//z3Wrl2rVpaWlgYAaNCgQYntZTIZLl26pJNsRESkeTKZDP369cNff/2F1157Teo4REREREQGqbzL4jzsLXWeR9LOpbS0NLEz6VmxsbE6TlPFnT8PdO4MREYCTZpInYaIjIggCEhLS4OrqysAwMnJCf369ZM4FRERERGRFmm5DV58WdzTHUxGeVmcSqV6oR96QQUFQFpa0ZKISEfy8/OxYcMGLFu2DCkpKVLHISIiIiLSDSna4MZ4tzgiIqr6TExMkJubi8LCQqSnp0sdh4iIiIioStC3u8VJelkcERFVbXK5HAMGDMD9+/fh6ekpdRwiIiIioipB3y6LY+cSERFpVEJCAtLS0tC8eXMAgIWFBTuWiF7QyZMnER0djUePHqGwsLDEeplMhokTJ0qQjIiIiPSOsd4tjnSoXj3g6NGiJRGRlty7dw+rV6+GSqWCs7MzfH19pY5EZJDS09PRq1cvHDlyBIJQdk2RnUtERER6SsttcN4tjqRhYwO0bi11CiKq4lxdXREQEIC8vDyOViL6DyIiInD48GF06NABw4YNQ82aNWFqymobERGRwdByG5yXxZE0bt8G5s0DIiKAmjWlTkNEVUhhYSFkMhlMTEwgk8nQrVs3yGQyyGQyqaMRGazt27cjODgYkZGR/L9ERERkiKRog/NucaR19+4B8+cXLYmINOTJkyf49ddfsXPnTvHSneJOJiJ6cU+ePEG7du34f4mIiMhQabkNrm93i2Pn0j8WLVoEHx8fWFhYoGXLljh58mS52z969AhjxoyBh4cHFAoF6tWrh507d+ooLRGRfrhz5w4SEhJw4cIFPHr0SOo4RFVGQEAAEhISJDk260RERET6r/iyuKdJeVmcXnUubdmyBQMGDECTJk1Qp04dsTw2NhazZ8/GnTt3tHLcdevWISIiApMnT8bp06fRtGlThIaG4l4ZPYxKpRJdunRBQkICNm7ciLi4OCxduhQ1atTQSj4iIn1Vp04ddO/eHWFhYXB0dJQ6DlGVMXnyZGzbtg3Hjx/X6XFZJyIiIjJgxn63OJVKhcGDB2Pjxo0AAEtLSzx58kRc7+joiC+++AKFhYWYMGGCxo8/b948jBo1CmFhYQCAxYsXY8eOHVi+fDk+++yzEtsvX74c6enpOHr0KMzMzAAAPj4+Gs9FRKSPbt++DTc3N1hYWAAAAgMDJU5EVPWkpKSgW7duaN++PYYMGYLAwEDY2dmVuu3QoUM1dlzWiYiIiAyDvt0tTi9GLs2fPx8bNmzAu+++i4cPH2L8+PFq693c3NC2bVvs2LFD48dWKpWIiYlBSEiIWGZiYoKQkBAcO3as1H22bduG1q1bY8yYMXBzc0OjRo0wY8YMFBYWlnmcvLw8ZGZmqv3olIsL8N57RUsiohcUExOD/fv3Y/369eV+5hHRfzN8+HBs3boV+fn5WLlyJcaOHYuwsDC1n+HDh4udQJqgizqR5PUhIiIiXdFyG9zaXF5quZW5NN08ejFyaeXKlWjRogV++OEHACh18so6depopXMpLS0NhYWFcHNzUyt3c3NDbGxsqfvcvHkTf/31F4YMGYKdO3fi+vXreO+995Cfn4/JkyeXus/MmTMxderUEuVJSUmwtbX97y/kKYWFBeIyMTHx3xWffAIIAvB0mR7KyclRz20gDDU3wOxSMNTcMpkMpqamUCgUSEpKgomJXnxHUWGG+r4bam7AcLM/fvxY0uOvWLFC58fURZ1Il/UhXTDUv2+A2aVgqLkBZpeCoeYGmF2NFtvgN+9klVoef+suHFSa+/KmonUivehcun79OsaMGVPuNs7Oznjw4IGOEpVPpVKhWrVq+OmnnyCXyxEUFIQ7d+5gzpw5ZXYuTZgwAREREeLjzMxMeHp6wsvLq8xh7i9KLr8OoAByuSm8vb2LCnNygNhYwN8fsJJmgq+KSkxM/De3ATHU3ACzS8FQc3t7e8Pc3BwNGzY0yLtYGer7bqi5AcPNLvWImmHDhkl6/IqqbJ1Il/UhXTDUv2+A2aVgqLkBZpeCoeYGmF2k5Ta4ucMTyLYlqF0aJ5MBLRvW0uhlcRWtE+lF55KlpSUyMjLK3SYxMREODg4aP7aLiwvkcjlSU1PVylNTU+Hu7l7qPh4eHjAzM4Nc/u8wtPr16yMlJQVKpRLm5uYl9lEoFFAoFJoNXxmxsUBQEBATA3B+FCKqoMePH+OPP/5At27dxAm7bW1tDbJjiYjKp4s6keT1ISIiIl2Rog0u4YTeenE9Q7NmzbBnzx7k5uaWuj49PR27d+9Gq1atNH5sc3NzBAUFITIyUixTqVSIjIxE69atS92nTZs2uH79OlQqlVh29epVeHh4lNqxRERkqHbs2IEbN25g69atEAQJz1ZERiohIQHTp09H//79ERoaiv79+2P69OlISEjQ+LFYJyIiIjIc5U3oLQW96FwaO3Ysbt++jb59++L27dtq627cuIHevXsjIyMDY8eO1crxIyIisHTpUvzyyy+4cuUKRo8ejezsbHGSzKFDh6rdpW706NFIT0/HuHHjcPXqVezYsQMzZsx47qV9RESGplu3bqhduzZ69erF0UpEOrZw4UL4+flh0qRJ2LRpE/bt24dNmzZh4sSJ8PPzw8KFCzV+TNaJiIiIDIOvizWerZ3LZICPizTT4OjFZXE9e/bEp59+ilmzZsHb2xvW1tYAgGrVquHBgwcQBAETJ05Ep06dtHL8gQMH4v79+5g0aRJSUlIQEBCA3bt3ixNaPjtpraenJ/bs2YMPP/wQTZo0QY0aNTBu3Dh8+umnWslHRKRLDx8+VLsE7s0335Q4EZHx2b59Oz788EO4uLjgww8/RMeOHeHh4YGUlBQcOHAA8+bNQ0REBOrUqYNu3bpp7LisExERERkwCS800IvOJaDo7iGdOnXC999/jxMnTiA3NxcqlQpdu3bF2LFjERoaqtXjh4eHIzw8vNR1UVFRJcpat26N48ePazWTRpmYALa2RUsiolIIgoDIyEgcP34cQ4cOhZeXl9SRiIzWvHnz4OTkhNOnT6NmzZpiube3N1q2bIkhQ4agWbNmmDdvnkY7lwAjqBMRERHpgpbb4OVdFqfJCb0rSm86lwCgS5cu6NKli9QxqqaAAEDiO98Qkf578OABCgsLcfv2bXYuEUno9OnTGDJkiFrH0tM8PT0xYMAA/PbbbzpORkRERBWi5Ta4tbm81HIrc2kGlOhF59L169dRp04dqWMQERk1mUyGPn364ObNm/Dz85M6DpFRUyqV4jQBZbGxsYFSqdRRIiIiItIn2crCUstzlKpSy7VNL66RqlevHtq0aYPFixcjPT1d6jhV0+XLQMOGRUsion88ePAAJ0+eFB+bmZmxY4lID9SrVw9//vknCgoKSl1fUFCA7du3o169ejpORkRERBWi5Ta4vk3orRedS6+//jpOnTqFMWPGoHr16ujduzc2b97Mb+M0KTe36I86N1fqJESkJ7Kzs/Hzzz9j165duHjxotRxiOgpQ4cORVxcHEJDQxETE6O27tSpU3j11VcRFxeHYcOGSZSQiIiIyiVFG9zYJ/Tetm0bHjx4gN9//x2rV6/GH3/8gW3btsHe3h79+/fHm2++ibZt20odk4ioSrG2tkZgYCASEhLg6+srdRwiesq4ceNw6NAhbNu2DcHBwbCyskK1atVw79495OTkQBAE9OzZE+PGjZM6KhEREUlA3yb01ouRSwDg7OyM8PBwnDhxAlevXsUXX3wBR0dHLF26FB06dECtWrUwceJEqWMSERk0QRBQWPjv9dmdO3fG8OHDnzu3CxHpllwux9atW7Fy5Up06NAB5ubmSEpKgrm5OTp27IhffvkFW7ZsgQnvAktERGSU9G1Cb72skdSpUwfTpk3DjRs3cPjwYYwaNQp37tzBjBkzpI5GRGSwCgsLsW3bNmzZsgWCUPQ9h0wmg6mpXgxiJaJSDB06FJGRkXjw4AHy8/Px4MED7N+/H2+99ZbU0YiIiEhCnNC7Eq5du4Y9e/Zg//79yM/PlzqOYatVC/jjj6IlERml1NRUnD9/HpcvX8bt27eljkNEREREVHVpuQ2ubxN6693X1Wlpafj999/x66+/4tSpUxAEAY6Ojnj33Xf5LV0FFaoEtSUAwMEB6NFDmkBEpBeqV6+Onj17wtLSEp6enlLHISIiIiKquqRogxv7hN65ubnYunUrfv31V+zbtw/5+fkwNzdHz5498dZbb6Fbt24wNzeXOqZBWBedhPtZeQCA+1l5WBedhIEtvICUFGDFCiAsDHB3lzglEenK3bt3YWdnBxsbGwBAkyZNJE5ERKUxMTGBiYkJLl++jHr16sHExAQy2bPfR5Ykk8lQUFCgg4RERERUKVpug+vbhN560bnk5uaGrKwsCIKA1q1b46233sLAgQPh6OgodTSDkpzxBBM2X1Ar+3zzRbSr5wqPu3eBzz8HQkPZuURkJK5fv47169ejWrVqGDZsGMzMzKSORERlaNeuHWQyGaysrNQeExERkYHSchtc3yb01ovOJVdXV0RERODNN99E7dq1pY5jsOLTsqF6puuyUBCKei6liUREEnJ0dISpqSksLCygUkkzsR8RVUxUVFS5j4mIiIiepm8TeutF59L169eljlAl+LpYw0QGtQ4muUxWNKFXhnS5iEgazs7OePvtt+Ho6Ai5vPRvNoiIiIiIyPDo28glvb5bHFWOh70lZvZprFY2o08jSa63JCLdUyqV2Lx5M1JTU8UyFxcXdiwRVSEJCQlYunQpVq9ejaysLKnjEBERkUQ4cgnAtGnTIJPJMGbMGDg5OWHatGkV2k8mk2HixIlaTmfYBrbwwtw9V3E/Kw+uNoqiybyBopnq+/UrWhJRlbR//35cuHABd+7cwZgxY2Biwu8PiAzVjBkzsHTpUpw+fVqcgzIqKgqvv/46njx5AgD48ssvcfz4cTg5OUkZlYiIiEqj5Ta4vo1ckqRzacqUKZDJZBg4cCCcnJwwZcqUCu3HzqWKkZvI1JYAgFq1gA0bJEpERLrQsWNHpKamIiQkhB1LRAZu69at8PHxUbu5yaeffgqVSoWpU6ciJSUFP/zwAxYsWFDhL+mIiIhIh7TcBufIJQAHDhwAAHh5eak9Ji1SKoF794Bq1QBzc6nTEJGGPH78GLa2tgAAS0tLDB8+nHeYIqoCEhIS0L9/f/Hx3bt3ER0djY8++gj/93//BwCIi4vDli1b2LlERESkj7TcBvd1sYYMwNP39JLJUDTnsgQk6Vxq3759uY9JCy5eBIKCgJgYIDBQ6jREpAFnzpzBjh07MGDAANSrVw8A2LFEVEVkZmbC4alh9IcOHYJMJkP37t3FssDAQCxevFiCdERERPRcUrTBhedvoi16cd3EqlWrcP78+XK3uXjxIlatWqWjRERE+i8pKQmFhYWIi4uTOgoRaZibmxsSExPFx/v27YNCoUDLli3FstzcXHYoExERGan4tOwSfUkCgIS0HCni6Efn0vDhw7F169Zyt/njjz8QFhamm0BERAbg9ddfR48ePfD6669LHYWINKxFixb4448/sH37duzfvx/r1q1Dx44doVAoxG3i4+NRvXp1CVMSERGRVPRtQm+96FyqiMLCQk5QS0RGLScnBydOnIAgFH1HIZfL0axZM45cIKqCPv/8cxQUFKBnz54IDQ1Fbm4uPv/8c3F9Xl4eDh06pDaSiYiIiIwHJ/R+QWfOnOGtdonIaOXn52P58uV48OABZDIZgoODpY5ERFoUGBiI48ePY/Xq1QCAAQMGqP2/P3PmDDp27Ig33nhDqohEREQkIX0buSRZ51KnTp3UHq9cuRJRUVEltissLMTt27eRkJCAAQMG6ChdFRQQAOTmAmZmUichohdgZmaGwMBAnDx5Er6+vlLHISIdaNq0KZo2bVrqulatWmHLli06TkREREQVpuU2OEcu/ePpjiSZTIaEhAQkJCSU2M7ExAROTk7o378/FixYoLN8VY6JCfDUPA1EZBhUKpV4SXDr1q0RGBgICwsLiVMREREREVG5tNwG58ilf6hU//ammZiYYMqUKZg0aZJUcaq+q1eBd94BfvoJ+OeW5USkvwRBwJEjR5CYmIhBgwZBLpdDJpOxY4moiiq+I27v3r1ha2tbqTvkDh06VFuxiIiI6EVpuQ3OkUulOHDgAHx8fKSOUbVlZQEHDxYtiUjvZWRk4NChQ8jPz0dsbCwaNmwodSQi0qLhw4dDJpOhVatWsLW1FR+XRxAEyGQydi4RERHpIy23wTlyqRTt27eXOgIRkV5xcHBA37598ejRI3YsERmB5cuXQyaTwcPDAwCwYsUKiRMRERGRPuPIJXDoNxFRaTIyMiAIAhwcHAAAfn5+0gYiIp0ZPny42uNhw4ZJE4SIiIgMAkcugUO/iYielZqail9//RUWFhYYMWIE51YiIiIiIqIyceQS9HPo96JFizBnzhykpKSgadOm+O677xAcHFzqtitXrkRYWJhamUKhQG5uri6ivhgvL2Dp0qIlEekdS0tLyGQyyGQyKJVKdi4RGbkjR45g06ZN+OSTT+Du7l5ifXJyMubMmYMBAwagVatWGj12la8TERER6YKW2+AcuQT9G/q9bt06REREYPHixWjZsiUWLFiA0NBQxMXFoVq1aqXuY2dnh7i4OPHx80ZeSc7FBRg5UuoURFQGOzs7vPXWW7C1tWXHEhFh3rx5OH/+PObNm1fqeg8PD2zfvh137tzBunXrNHZco6gTERER6YKW2+D6NnJJmi4tPTNv3jyMGjUKYWFhaNCgARYvXgwrKyssX768zH1kMhnc3d3FHzc3Nx0mfgFpacCyZUVLIpKcSqXCvn37cOvWLbHM1dWVHUtEBACIjo7Gyy+/XO427dq1w/HjxzV6XKOoExEREemCltvg+jZySS86l27duoW//voLOTk5YplKpcKsWbPQpk0bhISEYMeOHVo5tlKpRExMDEJCQsQyExMThISE4NixY2Xul5WVBW9vb3h6eqJnz564dOmSVvJpTFISMGpU0ZKIJHf58mUcPXoUa9euRV5entRxiEjP3Lt3DzVq1Ch3G3d3d9y7d09jxzSaOhEREZEuaLkNrm8jlyS5LO5ZEydOxJ9//omUlBSxbPr06Zg8ebL4+ODBgzh69ChatGih0WOnpaWhsLCwxLdsbm5uiI2NLXUfPz8/LF++HE2aNEFGRgbmzp2Ll156CZcuXULNmjVL3ScvL0+tAZmZmam5F0FEBsfPzw+pqakIDg6GQqGQOg4R6RkHBwckPacympiYCBsbG40dUxd1ItaHiIiINEPfRi7pRefSkSNHEBISAjMzMwBFd4b7/vvv4e/vj7179yIlJQUhISGYM2cO1q9fL3FaoHXr1mjdurX4+KWXXkL9+vWxZMkSfPnll6XuM3PmTEydOrVEeVJSEmxtbTWar7CwQFwmJiYCAMyTk+GBoglAlf+U6aucnBwxtyEx1NwAs+tKXl6e2JGUn5+PTp06QSaTGUz+Yob0nj/LULMbam7AcLM/fvxY0uO3atUKW7Zswa1bt+Dp6VlifVJSErZu3YpOnTpJkO5fla0T6bI+pAuG+vcNMLsUDDU3wOxSMNTcALMX03Yb/OadrFLL42/dhYNKc1/eVLROpBedS/fu3YO3t7f4+OzZs7h//z6mTJmCmjVrombNmujVqxcOHjyo8WO7uLhALpcjNTVVrTw1NbXUu7OUxszMDM2aNcP169fL3GbChAmIiIgQH2dmZsLT0xNeXl6ws7N7sfBlkMuvAyiAXG767/v64AGAoglA8dR7rY8SExPV/h4MhaHmBphdF+Lj47Flyxa89tpraNy4scHkLg2z656h5gYMN7vUI2oiIiLw559/ok2bNvjqq6/QpUsXeHh4IDk5GXv37sX//d//4cmTJ/joo480dkxd1Il0WR/SBUP9+waYXQqGmhtgdikYam6A2UVaboM/MnkIIKFEua9ndXh7OmrsOBWtE+nFnEsqlQoq1b/XBUZFRUEmk6l9G1ejRg21y+Y0xdzcHEFBQYiMjFTLExkZqfZNXHkKCwtx4cKFoj+aMigUCtjZ2an96JSNDdC+fdGSiHTuxo0byM3NxZkzZyAIgtRxiEjPtWvXDvPmzcPdu3cRFhaGmjVrwtTUFDVr1sTbb7+NlJQULFy4EO3atdPYMXVRJ5K8PkRERKQrWm6D33r4pNTy22WUa5tejFzy8vLCyZMnxcdbt26Fh4cH/Pz8xLKUlBQ4ODho5fgREREYNmwYmjdvjuDgYCxYsADZ2dkICwsDAAwdOhQ1atTAzJkzAQDTpk1Dq1atUKdOHTx69Ahz5sxBYmIiRmrxNoP/Wb16QFSU1CmIjFbnzp1ha2uLoKAg3qabiCpk3Lhx6NixIxYvXozo6GhkZGTAwcEBwcHB+N///odGjRpp/JhGUSciIiLSBS23wcv6wlqq77H1onOpb9++mD59Ovr16wcLCwscPnwY4eHhattcvnwZtWrV0srxBw4ciPv372PSpElISUlBQEAAdu/eLU5omZSUBBOTfwd5PXz4EKNGjUJKSgocHR0RFBSEo0ePokGDBlrJV1mFKkFtCQBQqYD8fMDMDDDRiwFrRFVaQUEBzp07h8DAQMhkMshkMrRs2VLqWERkYJo0aYIffvhBZ8eranUiIiIiyWi5De7lZFVquaeTpcaPVRF60bk0fvx47N27F5s3bwZQVJGaMmWKuD4xMREnT57EZ599prUM4eHhJTq0ikU909s4f/58zJ8/X2tZ/ot10Um4n1V0F5b7WXlYF52EgS28gLNngaAgICYGCAyUNiRRFScIAn7//XfcvHkTmZmZ6Nixo9SRiIgqrKrUiYiIiCSl5TZ4trKw1PIcparUcm3TiyEsdnZ2OH78OM6fP4/z588jJiYGjo7qE1Bt3rwZ7733nkQJDUNyxhNM2HxBrezzzReRnCHNNZdExkomk6FRo0ZQKBTw8vKSOg4RGaiCggLMnz8fwcHBsLOzg6npv98Jnj17Fu+99x6uXr0qYUIiIiKSirW5vNRyK3Npunn0YuRSsbLmDvD29jbY2eZ1KT4tG6pnrq8sFAQkpOWg7KnGiUhTBEEQ51Nq1qwZ6tWrB2tra4lTEZEhevLkCV555RUcPXoULi4usLOzQ3Z2trje19cXK1asgJOTE7766isJkxIREZEUOHLpOY4cOYJFixZh5syZWLRoEY4cOSJ1JIPh62INk2fmCZbLZPBxKf1aTCLSnMuXL2P16tXIz88Xy9ixREQvasaMGThy5AhmzpyJlJSUEhNk29vbo3379tizZ49ECYmIiEhKHLlUhqNHjyIsLAzXr18HoD4CoG7dulixYkWFb4NrrDzsLTGzT2N8uunfS+Nm9GkED3tpJvQiMha5ubnYvn07njx5gpMnT6JNmzZSRyIiA7du3Tp07NgRn3zyCQCUepfJWrVq4cyZM7qORkRERHrg1sPSp7+5/fAJmno6lrpOm/Sic+nSpUt45ZVXkJOTgy5duqBjx47w8PBASkoKDhw4gL179yI0NBTHjx/n3UeeY2ALL8zdcxX3s/LgaqMomswbABo1Am7dAqpVkzYgURVkYWGBAQMGIDY2lp3gRKQRSUlJ6N27d7nb2NraIiMjQ0eJiIiIqFK03AYXBKGMcq0c7rn0onNp2rRpUCqV2LlzJ7p27aq27tNPP8Xu3bvRo0cPTJs2DWvXrpUopeGQ/3NtnPzpa+TMzYGaNSVKRFT15OXlITs7G05OTgAAHx8f+Pj4SBuKiKoMW1tb3Lt3r9xtbty4AVdXVx0lIiIiokrRchvcy6n06W88naS5ckkv5lyKiopCv379SnQsFevatSv69euHAwcO6DiZYSr8Z1bvwqdn9755E+jfv2hJRP/J48ePsWLFCqxatQpZWVlSxyGiKqhVq1b4888/8ejRo1LX37p1Czt37kS7du10G4yIiIgqRsttcE7oXYqMjAz4+vqWu42vry+HflfAuugk3M/KAwDcz8rDuuikohWPHgEbNxYtieg/kcvlyM/PR0FBATuXiEgrPv74Yzx8+BCdO3fGkSNHUFBQAADIyclBZGQkQkNDUVBQgIiICImTEhERUam03AbnhN6lqF69Oo4fP17uNidOnED16tV1lMgwJWc8wYTNF9TKPt98Ee3qucJDokxEVZGVlRWGDBkCExMTODg4SB2HiKqgdu3a4fvvv8e4cePURifZ2toCKOrk/uGHHxAUFCRVRCIiIpKQvk3orRcjl3r06IGoqChMnDgRubm5autyc3MxefJkHDhwAD179pQooWGIT8uG6pnJuwoFAQlpOdIEIqpCTp06Jd7NEgCcnJzYsUREWjV69GicO3cO4eHhaNGiBWrXro1mzZrhf//7H86cOYORI0dKHZGIiIgkwgm9SzFx4kRs374dM2bMwJIlSxAcHAw3NzekpqYiOjoa9+/fR61atTBx4kSpo+o1XxdrmMig1sEkl8ng42IF8IpCohd26dIl7NixA+bm5hg9ejQ7lYhI6w4dOgQ7OzsEBARg4cKFUschIiIiPcMJvUvh7OyM48ePY9iwYcjKysLOnTuxYsUK7Ny5E48fP0ZYWBiOHz8u3pWJSudhb4mZfRqrlc3o0wge9pZA9erAjBlFSyKqFH9/f/j4+OCll16Cvb291HGIyAh07NgRP/30k9QxiIiI6EVpuQ1e3mVxUtCLkUsA4OLiguXLl2PJkiWIjY1FZmYm7Ozs4O/vDzMzM6njGYyBLbwwd89V3M/Kg6uNAgNbeBWtcHcHJkyQNhyRAVEqlTA3NwdQNLfJW2+9BRMTveiPJyIjUK1aNVhYWEgdg4iIiF6UltvgvCzuKQ8fPsR3332H6OhoyGQytGzZEmPGjEHjxo2fvzOVSW4iU1sCKJqh/tAhoF07gJf0EJUrLS0Nv/32G1q1aoXg4GAAYMcSEelUly5dEBUVBUEQIJPJnr8DERER6Rctt8F5Wdw/Hjx4gKCgIEydOhU7duzA9u3bMWnSJLRo0QLp6elSxaq6bt4EevYsWhJRua5evYqHDx/ixIkT4u2/iYh06euvv8aDBw/wzjvvsF5ERERkiLTcBudlcf+YMWMGEhIS0LFjR7z77rsAgCVLluDAgQP4+uuvMXv2bKmiEZGRa926NQRBQEBAAExN9ebqYSIyIm+++SYcHBywfPly/Prrr/D19YWbm1uJUUwymQyRkZESpSQiIiKp8LK4f+zcuRN16tTB3r17IZfLAQB9+/ZFgwYNsH37dnYuEZHOCIKAixcvomHDhjAxMYFMJkObNm2kjkVERiwqKkr8d15eHmJjYxEbG1tiO14yR0REZJx4Wdw/EhMTERoaKnYsAUWT5oaGhiIhIUGqWERkhHbu3InNmzdj165dUkchIgIAqFSqCv0UFhZKHZWIiIgkoG+XxUnWuZSbmwtXV9cS5c7OzsjLy5MgURVnYQE0aFC0JCI1tWrVgomJCdzc3KSOQkRG7tixY+jUqRNsbW1hb2+PLl264OTJk1LHIiIiosrSchucl8WRNBo0AC5dkjoFkV6qX78+xo4dC3t7e6mjEJERu3DhAjp37ozc3FyxLDIyEkePHsXJkyfRsGFDCdMRERFRpWi5Da5vl8VJ2rl0+PDhEnMrHT58GAAwZ86cUnviPvnkE51kI6Kq686dO/jrr7/Qv39/WPzzTQI7lohIal9//TVyc3PxxRdf4P333wcALFq0CF9++SVmzZqFVatWSZyQiIiI9EV5l8U19XTUcRqJO5f279+P/fv3l7ru008/LVEmk8nYufSizp4F2rUDDh0CAgKkTkMkGZVKhU2bNuHhw4c4cOAAXn31VakjEREBAP7++2+8/PLL+PLLL8WyqVOnIioqCgcPHpQwGREREVWaltvgvCzuHytWrJDq0MZJpQIePy5aEhkxExMT9O/fH4cPH0anTp2kjkNEJEpNTcWgQYNKlLds2RInTpyQIBERERG9MC23wXlZ3D+GDRsm1aGJyMioVCo8evQITk5OAAAPDw/0799f4lREROry8/NhY2NTotza2hr5+fkSJCIiIiJ9pW+XxUl2tzgiIl1QKpVYt24dli9fjocPH0odh4iIiIiI6D97mKOsVLm28W5xRFSlCYKAzMxM5OXlIS0tDY6Ouu/FJyKqqF9//RXHjx9XK7t+/ToA4LXXXiuxvUwmw44dO3SSjYiIiPSHg6VZGeXmOk5ShJ1LxsLfH4iJKVoSGRGFQoHBgwcjMzMTNWvWlDoOEVG5rl+/LnYmPWv37t0lymQymbYjERER0YvQchu8uY9TqeVBPtJ8mc7OJWNhZQUEBkqdgkgnbty4gby8PDRo0AAAYGdnBzs7O4lTERGVLz4+XuoIREREpCk6aIPLAAjPPJYKO5eMRVISMGsW8OmngJeX1GmItObWrVtYs2YNTExM4OjoCA8PD6kjERFViLe3t9QRiIiISFO03AaPT8tW61gCijqaEtJy4GGv+zvGcUJvY5GWBvzwQ9GSqAqrUaMG6tWrh4YNG8LV1VXqOEREREREZIy03Ab3dbGGyTNDleQyGXxcrLRyvOdh59I/Fi1aBB8fH1hYWKBly5Y4efJkhfZbu3YtZDIZevXqpd2ARFSmgoICCEJRv72JiQn69euHXr16wdSUgzOJiCqLdSIiIiL952FviZl9GouPTWTAjD6NJBm1BOhZ55JSqcTOnTsxb948fPnll2J5bm4u7t27B5VKpZXjrlu3DhEREZg8eTJOnz6Npk2bIjQ0FPfu3St3v4SEBIwfPx5t27bVSi4ier7c3FysWrUKhw4dEstMTU05yS0R0QtgnYiIiMhwDGzhhYbVi+aWndmnCQa2kG4KHL3pXNq2bRu8vLzQvXt3jB8/HlOmTBHXnT9/Hh4eHli7dq1Wjj1v3jyMGjUKYWFhaNCgARYvXgwrKyssX768zH0KCwsxZMgQTJ06FbVq1dJKLiJ6vjt37uDWrVs4fvw4srOzpY5DRGTQWCciIiIyLOamRd06TtbmkubQi86lI0eOoF+/flAoFFi4cCHeeOMNtfXBwcGoU6cONm3apPFjK5VKxMTEICQkRCwzMTFBSEgIjh07VuZ+06ZNQ7Vq1TBixIgKHScvLw+ZmZlqPzpVrRrw4YdFS6IqpHbt2ujSpQvefvttWFtbSx2HiMhg6aJOJHl9iIiISFd01AZXFhRd4ZWerdTqcZ5HLyYk+fLLL+Hg4ICYmBi4uLjgwYMHJbZp3rw5Tpw4ofFjp6WlobCwEG5ubmrlbm5uiI2NLXWfw4cP4+eff8bZs2crfJyZM2di6tSpJcqTkpJga2tbqczPU1hYIC4TExP/XTFuHFBYCDxdpodycnLUcxsIQ80NGF72O3fuwM3NDaampsjJyUGNGjUM7jUYWt6nMbvuGWpuwHCzP378WOoIOqeLOpEu60O6YKh/3wCzS8FQcwPMLgVDzQ0wuxott8F3XEnHpbtFX9R8tuk8HjxIQ7f6Tho9RkXrRHrRuXTixAn069cPLi4uZW7j6emJP/74Q4epSvf48WO89dZbWLp0abl5nzVhwgRERESIjzMzM+Hp6QkvLy/Y2dlpNKNcfh1AAeRy039va5yVBVy4ADRuDNjYaPR4mpaYmGiQt2M21NyAYWU/duwY9u3bh0aNGqFPnz5ISkoymOxPM6T3/FnMrnuGmhsw3OwcUfN8L1In0mV9SBcM9e8bYHYpGGpugNmlYKi5AWYXabkNnpzxBHMPXhQfCwC+OZiM3q39NTqpd0XrRHrRuZSXl/fcCsWjR49gYqL5q/hcXFwgl8uRmpqqVp6amgp3d/cS29+4cQMJCQno3r27WFY80bipqSni4uJQu3btEvspFAooFAoNp6+Eq1eBl14CYmKAwEDpchD9R25ubjAxMYGNnneSEhEZGl3UiSSvDxEREemKltvg8WnZUAnqZYWCgIS0HEnuGKcXcy7VqlUL0dHR5W5z7Ngx+Pv7a/zY5ubmCAoKQmRkpFimUqkQGRmJ1q1bl9je398fFy5cwNmzZ8WfHj16oGPHjjh79iw8PT01npGI/lWrVi2MHj0aoaGhvCMcEZEGsU5ERERkOKzN5aWWW5lL082jFyOX+vbti6+++gorVqxAWFhYifVz587FxYsXMXv2bK0cPyIiAsOGDUPz5s0RHByMBQsWIDs7W8wydOhQ1KhRAzNnzoSFhQUaNWqktr+DgwMAlCgnov8uIyMDO3fuRI8ePcQJuytzSSoREVUc60RERESGIVtZWGp5jlKl4yRF9KJz6eOPP8amTZswcuRI/Pbbb8jLywMAfPLJJzh27BiOHj2KgIAAhIeHa+X4AwcOxP379zFp0iSkpKQgICAAu3fvFie0TEpK0soleURUPkEQsHnzZiQlJWH79u0YOHCg1JGIiKo01omIiIgMg6+LNUxkULs0Ti6TwcfFSpI8etG5ZGNjg7///hvh4eFYv349CguLeuDmzp0LmUyGAQMG4IcfftDqNfrh4eFldl5FRUWVu+/KlSs1H0jTTE0BF5eiJZGBkMlk6N69O7Zv346uXbtKHYeIyChU+ToRERGRLmi5De5hb4mZfRrj000XAAAyGTCjTyNJ5lsC9KRzCQAcHR2xZs0afPvtt4iOjkZ6ejrs7OzQokWLErfEpRfQpAlw/77UKYgqJDMzU5zk38XFBcOHD5c2EBERERERUWXouA0uCM/fRpv0pnOpmLOzM0coEBkplUqFvXv34uzZs3j77bdRrVo1qSMRERERERHpneSMJ5iw+YJa2eebL6JdPVfjvVsc6cClS0CdOkVLIj2lUqmQnJyMvLw8JCUlSR2HiIiIiIjoxWi5DR6flq023xIAFAoCEtJytHK859GLkUudOnWq0HYymUzt9rhUCXl5wI0bRUsiPWVqaoqBAwciKSkJ/v7+UschIiIiIiJ6MVpug3NC71I8b3JImUwGQRAgk8l0E4iIdObevXtISUlBkyZNAABWVlbsWCIiIiIiIipH8YTen2++iEJBgFwm44TeKpWq1PLMzEycPn0an3/+OWrWrInff/9dx8mISJsePnyI5cuXQ6lUwsbGBrVq1ZI6EhERERERkUEY2MIL7eq54sSlm2jZsJZkHUuAns+5ZGdnhw4dOmDPnj04efIkpk+fLnUkItIgBwcH1K9fH56ennB3d5c6DhERERERkUHxsLdEsxo2knYsAXreuVTM1tYWr776KlasWCF1FMNVpw6we3fRkkhCgiCIoxVlMhlef/11vPXWW7CykubaYCIiIiIiIo0zsja4XlwWVxEmJiZITk6WOobhsrMDQkOlTkFGrqCgANu2bYOlpSVeffVVAIBcLpc4FRERERERkYYZWRvcIEYu3bx5Exs2bICPj4/UUQxXcjIwZUrRkkgiiYmJuHDhAk6dOoX79+9LHYeIiIiIiEg7jKwNrhcjl95+++1SywsKCnDnzh0cPnwY+fn5mDZtmo6TVSHJycDUqUCPHoCHh9RpyEjVrl0boaGhcHV1haurq9RxiIiIiIiItMPI2uB60bm0cuXKctf7+fnho48+wsiRI3UTiIg05s6dO3BxcYFCoQAAtGrVSuJEREREREREpEl60bkUHx9farmJiQkcHBxga2ur40REpAmxsbHYuHEjfH19MXjwYJiYGMSVuERERERERFQJetG5JJPJYG5uzluRE1Uxtra2kMlkMDExQWFhITuXiIiIiIiIqiC9aOn5+vri888/lzpG1eboCAwZUrQk0pEaNWpgxIgRGDhwIMzMzKSOQ0REREREpBtG1gbXi84lR0dHODs7Sx2javP1BX79tWhJpCV5eXnYunUrHj16JJa5u7tzxBIRERERERkXI2uD60WLr23btjhx4oTUMaq23Fzg+vWiJZGW7NixA+fOncPGjRshCILUcYiIiIiIiKRhZG1wvehcmjlzJs6fP49p06ahoKBA6jhV0+XLQN26RUsiLencuTM8PDzw2muvQSaTSR2HiIiIiIhIGkbWBteLCb1nz56Nxo0bY+rUqViyZAmaNm0KNze3Eo1TmUyGn3/+WaKURFSanJwcWFlZAQDs7e0xatQodiwREREREREZEck6l+RyOaZMmYKJEydi5cqVYnlycjKSk5NL3YedS0T6JTo6Gvv378dbb72FmjVrAgA7loiIiIiIiIyMZJ1LgiCIc7LEx8dLFYOIXpAgCLh27RqUSiUuX74sdi4RERERERGRcdGLy+K8vb2ljkBElSSTydCvXz9cuHABgYGBUschIiIiIiIiiehF5xLpQGAgwLt30X+UnZ2N69evo2nTpgAAc3NzBAUFSZyKiIiIiIhIzxhZG1zSziXOzUJkOHJzc7Fs2TI8evQIcrkcjRo1kjoSERERERER6QETKQ8+ZcoUyOXyCv+YmnKg1QuLiwNaty5aEr0ACwsL+Pv7w9HRER4eHlLHISIiIiIi0l9G1gaXtLfGzs4ODg4OUkYwHtnZwPHjRUuiShAEQRxl+Morr6Bdu3awtLSUOBUREREREZEeM7I2uKSdSx9++CEmTZokZQQiKoMgCDh48CAePXqEnj17QiaTQSaTsWOJiIiIiIiI1Eh6WRwR6a979+7h0KFDOHfuHOLj46WOQ0RERERERHqKkxgRUanc3Nzw+uuvQxAE1KpVS+o4REREREREpKc4cukfixYtgo+PDywsLNCyZUucPHmyzG03b96M5s2bw8HBAdbW1ggICMDq1at1mPYF+PgAq1cXLYnK8PDhQ+Tk5IiPAwMDERQUJGEiIiLStSpfJyIiItIFI2uDs3MJwLp16xAREYHJkyfj9OnTaNq0KUJDQ3Hv3r1St3dycsIXX3yBY8eO4fz58wgLC0NYWBj27Nmj4+SV4OQEvPlm0ZKoFHfu3MHPP/+MtWvXoqCgQOo4REQkAaOoExEREemCkbXBJetcUqlUejOZ97x58zBq1CiEhYWhQYMGWLx4MaysrLB8+fJSt+/QoQN69+6N+vXro3bt2hg3bhyaNGmCw4cP6zh5Jdy/DyxaVLQkKoW5uTkKCgqQn5+PvLw8qeMQEZEEjKJOREREpAtG1gY3+pFLSqUSMTExCAkJEctMTEwQEhKCY8eOPXd/QRAQGRmJuLg4tGvXrszt8vLykJmZqfajU7duAeHhRUuiUri6umLo0KEICwuDtbW11HGIiEjHdFEnkrw+REREpCtG1gY3+gm909LSUFhYCDc3N7VyNzc3xMbGlrlfRkYGatSogby8PMjlcvzwww/o0qVLmdvPnDkTU6dOLVGelJQEW1vbF38BpSgsLBCXiYmJAADz5GR4AEhOTobynzJ9lZOTI+Y2JIaWW6VSISYmBnXr1oW5ubmYPTk5WeJklWNo73sxQ80NMLsUDDU3YLjZHz9+LHUEndNFnUiX9SFdMNS/b4DZpWCouQFml4Kh5gaYvZgu2+DafM8rWicy+s6lF2Vra4uzZ88iKysLkZGRiIiIQK1atdChQ4dSt58wYQIiIiLEx5mZmfD09ISXlxfs7Ow0mk0uvw6gAHK5Kby9vYsKHzwAAHh4eADFZXoqMTHx39wGxNByR0ZG4tKlS7h79y5ef/11g8r+NEN734sZam6A2aVgqLkBw83OETUVV5k6kS7rQ7pgqH/fALNLwVBzA8wuBUPNDTC7SIdtcG2+5xWtExl955KLiwvkcjlSU1PVylNTU+Hu7l7mfiYmJqhTpw4AICAgAFeuXMHMmTPL7FxSKBRQKBQay030X7Vu3RpXr15Fhw4dIJfLpY5DREQS00WdiPUhIiKiqsno51wyNzdHUFAQIiMjxTKVSoXIyEi0bt26ws+jUqn0exJkW1vglVeKlmS0nv4btbKywrvvvov69etLmIiIiPSF0dSJiIiIdMHI2uBGP3IJACIiIjBs2DA0b94cwcHBWLBgAbKzsxEWFgYAGDp0KGrUqIGZM2cCKJovoHnz5qhduzby8vKwc+dOrF69Gj/++KOUL6N8desCvC2wUbt+/To2bdqEfv36oXbt2gCKvm0mIiIqZhR1IiIiIl0wsjY4O5cADBw4EPfv38ekSZOQkpKCgIAA7N69W5zQMikpSa0Rnp2djffeew+3b9+GpaUl/P398euvv2LgwIFSvYTnKywEsrMBa2uAl0AZpUuXLiE3NxfR0dFi5xIREdHTjKJOREREpAtG1gZn59I/wsPDER4eXuq6qKgotcdfffUVvvrqKx2k0qBz54CgICAmBggMlDoNSaBbt25wdnau1KUNRERkfKp8nYiIiEgXjKwNzmtiiKqo/Px8nD9/XnxsamqKl19+mZN3ExERERERkUZx5BJRFVRYWIjVq1fj1q1byMvLQ4sWLaSORERERERERFUURy4RVUFyuRx16tSBhYUFXF1dpY5DREREREREVRhHLhFVIYIgQCaTAQDatm2LgIAA2NnZSZyKiIiIiIiIqjKOXDIWjRsD9+4VLalKunDhAjZu3AiVSgUAkMlk7FgiIiIiIiKSgpG1wTlyyViYmQG8PKrKevz4MbZt24aCggLUrl0bgUZwNwIiIiIiIiK9ZWRtcI5cMhY3bgA9ehQtqcqxtbVF79690bp1azRr1kzqOERERERERMbNyNrg7FwyFhkZwJ9/Fi2pSsjNzcXjx4/Fxw0aNMArr7wizrlEREREREREEjGyNjg7l4gM0KNHj7B8+XKsWbMGeXl5UschIiIiIiIiI8Y5l4gM1JMnTyCTyfD48WMoFAqp4xAREREREZGRYucSkQFycHDAkCFDYGVlxTvCERERERERkaR4WZyxqFED+OaboiUZpBMnTuDOnTviY3d3d3YsERERERER6SMja4Nz5JKxcHMDIiKkTkEvKCYmBrt374a1tTXee+89WFlZSR2JiIiIiIiIymJkbXCOXDIWDx8CGzYULcngNGrUCO7u7mjdujUsLS2ljkNERERERETlMbI2OEcuGYv4eGDAACAmBnB0lDoNVUBBQQFMTYv+iyoUCowYMUJ8TERERERERHrMyNrgHLlEpIfu3buH77//HpcuXRLL2LFERERERERE+oidS0R66Ny5c8jIyMDff/8NlUoldRwiIiIiIiKiMnEoBJEe6ty5M0xNTdGqVSuYmLAPmIiIiIiIiPQXW63GwtISaNasaEl6RxAEXL58GYIgAABMTEzQsWNHTt5NRERERERkiIysDc6RS8aifn3g9GmpU1ApBEHA1q1bcf78eXTs2BHt2rWTOpJWCYKAgoICFBYWauT5CgoKkJubq5Hn0iVDzQ0wuxQMNTegv9nlcjlMTU0hk8mkjkJERERVkZG1wdm5RCQxmUyGmjVr4uLFi7Czs5M6jlYplUokJycjJydHY89ZUFCA+Ph4jT2frhhqboDZpWCouQH9zm5lZQUPDw+Ym5tLHYWIiIjIoLFzyVicOQO0agUcP140NI/0SosWLVC7dm04OTlJHUVrVCoV4uPjIZfLUb16dZibm2tkxIBSqTTIhqGh5gaYXQqGmhvQz+yCIECpVOL+/fuIj49H3bp1Ob8dERERaZaRtcHZuWQsBAFQKouWJLmkpCQcP34cffr0galp0X/DqtyxBBQ1MFUqFTw9PWFlZaWx55XJZFAoFBp7Pl0x1NwAs0vBUHMD+pvd0tISZmZmSExMhFKphIWFhdSRiIiIqCoxsjY4v6Yj0rH8/HysX78eV65cweHDh6WOo3McHUBE+oKfR0RERESawVoVkY6ZmZmhT58+aNCgAdq0aSN1HCIiIiIiIqL/hJ1LRDpQWFiIzMxM8XGtWrXQv39/mJmZSZiKNE0mk2Hr1q1SxzBYU6ZMQUBAgPh4+PDh6NWrl2R5iIiIiIioYti5ZCzq1wcuXixakk7l5ubit99+w8qVK5GdnS11HHpBKSkpeP/991GrVi0oFAp4enqie/fuiIyMlDrafxYVFQWZTCb+WFpaomHDhvjpp58kzbVw4UKsXLlS0gxERERERC/EyNrgnNDbWFhaAg0bSp3CKBUWFiI9PR3Z2dm4f/8+rK2tpY5ElZSQkIA2bdrAwcEBc+bMQePGjZGfn489e/ZgzJgxiI2NlTqiRsTFxcHOzg5PnjzBn3/+idGjR6N27dro3LmzJHns7e0lOS4RERER0X9mZG1wjlwyFomJwMiRRUvSKWtrawwZMgTDhw+Hj4+P1HHoBbz33nuQyWQ4efIk+vbti3r16qFhw4aIiIjA8ePH1bZNS0tD7969YWVlhbp162Lbtm3iusLCQowYMQK+vr5wcHCAn58fFi5cqLZ/8aVgc+fOhYeHB5ydnTFmzBjk5+eL2+Tl5eHTTz+Fp6cnFAoF6tSpg59//llcf/HiRbz66quwsbGBm5sb3nrrLaSlpT33dVarVg3u7u7w9fXF2LFj4evri9OnT4vrd+/ejZdffhlubm5wdnbG66+/jhs3bojrlUolwsPD4eHhAQsLC3h7e2PmzJni+kePHmHkyJFwdXWFnZ0dOnXqhHPnzpWZ59nL4jp06ICxY8fik08+gZOTE9zd3TFlyhS1fSp7DCIiIiIirTCyNjg7l/6xaNEi+Pj4wMLCAi1btsTJkyfL3Hbp0qVo27YtHB0d4ejoiJCQkHK31wsPHgA//1y0JK27evUq4uPjxccuLi6oXr26hIn0m1KphFKphPDUbToLCwuhVCpRUFCg0W0rKz09Hbt378aYMWNKHXXm4OCg9njq1KkYMGAAzp8/j9deew1DhgxBeno6AEClUqFmzZrYsGEDzpw5g0mTJuHzzz/H+vXr1Z7jwIEDuHHjBg4cOIBffvkFK1euVLs8bOjQofj999/x7bff4sqVK1iyZAlsbGwAFHWudOrUCc2aNcOpU6ewe/dupKamYsCAARV+zYIgYPfu3UhKSkLLli3F8uzsbERERODo0aOIjIyEiYkJevfuDZVKBQD49ttvsW3bNqxfvx5xcXFYs2aNWodq//79ce/ePezatQsxMTEIDAxE586dxfenIn755RdYW1vjxIkTmD17NqZNm4Z9+/Zp9BhExq7K14mIiIh0wcja4LwsDsC6desQERGBxYsXo2XLlliwYAFCQ0MRFxeHatWqldg+KioKgwcPxksvvQQLCwvMmjULr7zyCi5duoQaNWpI8ApIn1y/fh1r166Fubk53nnnHTg5OUkdSe8Vj24ZP3682IFz5MgRHDhwAM2aNUOPHj3EbefOnYv8/HyMGzdO7NiJjo7Gnj170LhxY/Tp00fcduHChcjJycHo0aNL/b9cEdevX4cgCPD396/Q9sOHD8fgwYMBADNmzMC3336LkydPomvXrjAzM8PUqVMBFI0+8vf3x7Fjx7B+/Xq1zh9HR0d8//33kMvl8Pf3R7du3RAZGYlRo0bh6tWrWL9+Pfbt24eQkBAARRPEF/v+++/RrFkzzJgxQyxbvnw5PD09cfXqVdSrV6/M7DVr1hSzqVQqTJs2De3atRPX9+3bV1yvUCiwfPlyuLq64vLly2jUqBGSkpJQt25dvPzyy5DJZPD29hb3PXz4ME6ePIl79+5BoVAAKPpdbt26FRs3bsQ777xTofe3SZMmmDx5MgCgbt26+P777xEZGYkuXbpo7BhExox1IiIiInoRHLkEYN68eRg1ahTCwsLQoEEDLF68GFZWVli+fHmp269ZswbvvfceAgIC4O/vj2XLlkGlUlWJiX3pv/Px8UHNmjXRoEEDzhlTBVR21FOTJk3Ef1tbW8POzg737t0TyxYtWoSgoCDUrFkTNjY2+Omnn5CUlKT2HA0bNoRcLhcfe3h4iM9x9uxZyOVytG/fvtTjnzt3DgcOHICNjY34U9wx9vQlbKX5+++/cfbsWZw9exbLli3DjBkz8OOPP4rrr127hsGDB8Pf3x92dnbiqKTi/MOHD8fZs2fh5+eHsWPHYu/evWq5srKy4OzsrJYtPj7+ubme9vT7++x7o6ljEBkz1omIiIjoRRj9yCWlUomYmBhMmDBBLDMxMUFISAiOHTtWoefIyclBfn4+R6gYscLCQvHfpqamePPNN2FmZgaZTCZhKsNR/P/PzMxMLGvTpg1atWoFExP1PvDx48eX2LZFixYIDAwsse24ceNKbFtZdevWhUwmq/Ck3c8eSyaTiZeNrV27FuPHj8c333yDoKAgODs7Y86cOThx4kSFn8PS0rLc42dlZaF79+6YNWtWiXUeHh7l7ls8FxRQ1MF14sQJTJ8+HaNHjwYAdO/eHd7e3vjhhx/g4+MDlUqFRo0aQalUAgACAwMRHx+PXbt2Yf/+/RgwYABCQkKwceNGZGVlwcPDA1FRUSWO++ylheUp773R1DGIjBXrRERERPSijL5zKS0tDYWFhXBzc1Mrd3Nzq3Bj8tNPP0X16tXFS1RKk5eXh7y8PPFxZmbmiwV+UW5uwGefFS1Jo7KysvD777/Dx8dHvAzI3Nxc4lSGpbT3Sy6Xq43e0dS2leXk5ITQ0FAsWrQIY8eOLTHv0qNHjyrccXHkyBG89NJLeO+998RLyyo7oqZx48ZQqVQ4ePBgqZ85gYGB2LRpE3x8fGBq+t8+4uVyOZ48eQIAePDgAeLi4rB06VIEBwdDoVDg8OHDJfaxs7PDwIEDMXDgQPTr1w9du3ZFeno6AgMDkZKSAlNTU61NbK+LYxBVZbqoE0leHyIiItIVI2uDG33n0n/19ddfY+3atYiKioKFhUWZ282cOVOca+VpSUlJsLW11WimwsICcZn49Mz0//sfUFCg97PV5+TkqOfWc5cuXcLdu3eRnp4OX1/f/zRKRiq6eM8LCgpQUFAApVKp0RFdKpVKraGiDfPmzUOnTp3QokULTJo0CY0bN0ZBQQEiIyPx008/qd2NLD8/v0Se4jJfX1+sWrUK27dvh5eXF37//XdER0fDx8dH3KewsLDEa3q6zMPDA2+++SbCwsIwb948NG7cGElJSbh//z769euHkSNHYunSpRg4cCAiIiLg6OiImzdvYv369Vi8eHGpnXDFI49u376NjIwM5OXl4dSpU1i9ejV69+6NvLw8WFlZwdnZGT/++CMcHR1x+/ZtTJw4Ue31LVy4EO7u7ggICICJiQnWrl0Ld3d3WFpaom3btmjZsiV69uyJ6dOno27dukhOTsauXbvQs2dPBAUFoaCgAIIglPleqFQqFBYWqr03T5dV5Bi6+HvRBkPNDeh39uIbAdy5c6dEZ+zjx48lSmW4KlIn0mV9SBcMrc7yNGbXPUPNDTC7FAw1N8DsanTUBtfme17ROpHRdy65uLhALpcjNTVVrTw1NRXu7u7l7jt37lx8/fXX2L9/f4l5QJ41YcIEREREiI8zMzPh6ekJLy8v2NnZvfgLKIVcfh1AAeRy038n1H38GIiJAYKCAD2vvCUmJqpNBKzvvLy8oFAoUK1aNdSpU0fqOC9EF+95bm4u4uPjYW5uLk62rAnFI4C0qX79+jh9+jSmT5+Ozz77DMnJyXB1dUVQUBAWL16sdnwzM7MSeYrLxowZgwsXLuDNN9+ETCbD4MGD8d5772HXrl3iPnK5HCYmJmrP8WzZTz/9hM8//xzjxo3DgwcP4OXlhc8//xwKhQK+vr44cuQIPv30U7z++uvIy8uDt7c3unbtCktLy1I79opHeDVu3BhA0aWdnp6eePfddzFlyhTxuGvXrsXYsWPRvHlz+Pn54dtvv0WHDh3E1+fo6Ij58+fj2rVrkMvlaNGiBXbu3Cleyrd792588cUXePfdd3H//n24u7ujXbt28PT0hEKhgKmpKWQyWZnvhYmJCeRyudp782zZ846hi78XbTDU3IB+ZxcEAaampqhRo0aJzhBjHFGjizqRLutDumBodZanMbvuGWpugNmlYKi5AWYX6bANrs33vKJ1IpnwX+7RXUW0bNkSwcHB+O677wAUfcvq5eWF8PBwfPbZZ6XuM3v2bEyfPh179uxBq1atKn3MzMxM2NvbIyMjQ+OVqVYzIpGSmQt3Owsc/7xzUeHp00V/1DExQGCgRo+naYbwYXTz5k34+PiozfFjCLnLosvOJV9f33JH+VWWPjdcy2OouQFml4Kh5gb0O3t5n0vaPE/rM13XiQz9fea5XxqGmt1QcwPMLgVDzQ0wu0iHbXBtdy5V5Fxt9COXACAiIgLDhg1D8+bNERwcjAULFiA7OxthYWEAgKFDh6JGjRri7dJnzZqFSZMm4bfffoOPjw9SUlIAQLwzEVVthw4dwoEDB9CqVSuEhoZKHYeIiEhjWCciIiKiF8HOJQADBw7E/fv3MWnSJKSkpCAgIAC7d+8WJ7RMSkpSG6Hy448/QqlUol+/fmrPM3nyZEyZMkWX0UkCxXfAMTU1hSAIvCMcERFVGawTERER0Ytg59I/wsPDER4eXuq6Z29rnZCQoP1ApLcaNWoEFxeX584/QUREZIhYJyIiIqLKYueSsTAzA2rUKFpSpTx8+BCRkZHo0aOHOPExO5aIiIh0QxAEFBQUoLCwUOooJRQUFCA3N1fqGC+E2XXPUHMDzC6F0nLL5XLxBihkAIysDc7OJWPRuDFw+7bUKQyOIAj4/fffcf/+fZibm6NHjx5SRyIiIjIaSqUSycnJyMnJkTpKqQoKChAfHy91jBfC7LpnqLkBZpdCWbmtrKzg4eEhfulNeszI2uDsXCIqh0wmQ48ePbBv3z507NhR6jhERERGQ6VSIT4+HnK5HNWrV4e5ubnefVuvVCoNtoHH7LpnqLkBZpfCs7kFQYBSqcT9+/cRHx+PunXrqs2BRyQ1di4ZiwsXgFdfBXbtKupBpTIJgoDs7GzxLjc1a9bE8OHD9a5CS0REVJUplUqoVCp4enrCyspK6jilkslkUCgUUsd4Icyue4aaG2B2KZSW29LSEmZmZkhMTIRSqYSFhYVE6ahCjKwNzq5OY5GfD9y5U7SkMqlUKuzYsQNLlixBRkaGWM6OJSIiImnwm3kion/xM9GAGFkbnH+ZRE/Jz8/HrVu3kJWVhcTERKnjEBEREREREek9di4RPUWhUOCNN97AoEGD0KRJE6njEAEoGjm3detWqWMYnA4dOuCDDz7QybGe/R3FxsaiVatWsLCwQEBAABISEiCTyXD27Fmd5CEi48bzxovheUO7fHx8sGDBAo1va+ie/V1HRUVBJpPh0aNHkuYiqix2LpHRS0lJwdWrV8XH9vb28PPzkzAR6ZviObdkMhnMzMzg6+uLTz75xCBva1ue4tf49M/LL78seabSGkhKpRKzZ89G06ZNYWVlBRcXF7Rp0wYrVqxAvgRDj5OTk/Hqq6+KjydPngxra2vExcUhMjISnp6eSE5ORqNGjTR+7ClTpoi/L7lcDk9PT7zzzjtIT08vse3Ro0fx2muvwdHRERYWFmjcuDHmzZtX6i3eDxw4gNdeew3Ozs6wsrJCgwYN8NFHH+HOnTvl5jlz5gz69+8PNzc3WFhYoGHDhhg1apTa5yxRVcfzhrSZeN4o39PnDVNTU/j4+ODDDz9EVlaWxo/1tOjoaLzzzjsa3/a/6NChg/heWFhYoF69epg5cyYEQdD6sYmqGnYuGYu6dYEDB4qWJEpNTcWKFSuwYcMG3L17V+o4pMe6du2K5ORk3Lx5E/Pnz8eSJUswefJkqWNp3IoVK5CcnCz+bNu27YWfS1uVdaVSidDQUHz99dd45513cPToUZw8eRJjxozBd999h0uXLmnluOVxd3dXm3Tzxo0bePnll+Ht7Q1nZ2fI5XK4u7vD1PTF76OhVCrLXNewYUMkJycjKSkJK1aswO7duzF69Gi1bbZs2YL27dujZs2aOHDgAGJjYzFu3Dh89dVXGDRokFpFesmSJQgJCYG7uzs2bdqEy5cvY/HixcjIyMA333xTZo7t27ejVatWyMvLw5o1a3DlyhWsWLEC9vb2mDhxolZeO5G+4nmj8nje0P15IyEhAbNmzcJPP/2Ejz76qNLPUxmurq4Vnpy/Mtv+V6NGjUJycjLi4uIwYcIETJo0CYsXL9bJsamKM7Y2uECSyMjIEAAIGRkZGn/ultP3C96fbhdaTt+v8efWhYSEBJ0dq7CwUFizZo3wyy+/CE+ePPlPz6XL3Jqmi+xPnjwRLl++/J/f52J3H+UIR67fFxJSH2nk+cozbNgwoWfPnmplffr0EZo1ayY+TktLEwYNGiRUr15dsLS0FBo1aiT89ttvavu0b99eeP/994WPP/5YcHR0FNzc3ITJkyerbXP16lWhbdu2gkKhEOrXry/s3btXACBs2bJF3Ob8+fNCx44dBQsLC8HJyUkYNWqU8Pjx4xJ5p0+fLlSrVk2wt7cXpk6dKuTn5wvjx48XHB0dhRo1agjLly9XO/azx3laYWGhMHXqVKFGjRqCubm50LRpU2HXrl3i+vj4eAGAsHbtWqFdu3aCQqEQVqxYIQiCICxdulTw9/cXFAqF4OfnJyxatEjcLy8vTxgzZozg7u4uKBQKwcvLS5gxY4YgCILg7e0tABB/vL29BUEQhFmzZgkmJibC6dOnS+RUKpVCVlaW+H6PGzdOXLdq1SohMDBQsLGxEdzc3ITBgwcLqamp4vr09HThjTfeEFxcXAQLCwuhTp064ntUXs5n37unMwMQJk+eLL4/Z86cEfe5cOGC0LVrV8Ha2lqoVq2a8Oabbwr3798X17dv314YM2aMMG7cOMHZ2Vno0KFDqb+byZMnC02bNlUri4iIEBwdHcXHWVlZgrOzs9CnT58S+2/btk383QmCINy6dUswNzcXPvjgg1KP9/Dhw1LLs7OzBRcXF6FXr15q5bm5uWr7rVixQrC3t1fbZsuWLcLTVZLi17R06VLBx8dHkMlkwpIlSwQPDw+hsLBQbd8ePXoIYWFh4uOtW7cKzZo1ExQKheDr6ytMmTJFyM/PLzVzeZ9L2jxP07/Ke5+1dd64+yhHI88nCP/+fT/LEM4baWlpJfIaynnjf//7n87OG0FBQRo7b0ybNq3U904fzhujRo0S3N3d1dY//Rmcm5srPHz4UBgxYoTg4uIi2NraCh07dhTOnj2r9jzbtm0TmjdvLigUCsHZ2VntnODt7S3Mnz9fEARBUKlUwuTJkwVPT0/B3Nxc8PDwEN5///1StxUEQUhMTBR69OghWFtbC7a2tkL//v2FlJSUEq9p1apVgre3t2BnZycMHDhQyMzMLPP/afF79vTvXBAEITAwUOjdu7f4ODc3V/joo4+E6tWrC1ZWVkJwcLBw4MABtX0OHz4stG/fXrC0tBQcHByEV155RUhPTxcEQRB27doltGnTRrC3txecnJyEbt26CdevXxf3ffZ3feDAAQGA2ut7mqY/G7WB7SLd02buitaJOHLJWNy5A0yYULQ0coIgiN/Qm5iYoF+/fhgyZAhv5WlA1kUnoc3Xf+GNpSfQcf5hrItO0unxL168iKNHj8Lc3Fwsy83NRVBQEHbs2IGLFy/inXfewVtvvYWTJ0+q7fvLL7/A2toaf//9N2bPno1p06Zh3759AIruVtinTx+Ym5vjxIkTWLx4MT799FO1/bOzsxEaGgpHR0dER0djw4YN2L9/P8LDw9W2++uvv3D37l0cOnQI8+bNw+TJk/H666/D0dERJ06cwP/+9z+8++67uH37doVe88KFC/HNN99g7ty5OHXqFEJDQ9GjRw9cu3ZNbbvPPvsM48aNw5UrVxAaGoo1a9Zg0qRJmD59Oq5cuYIZM2Zg4sSJ+OWXXwAA3377LbZt24b169cjLi4Oa9asgY+PD4CiIfHAv9+KFz9es2YNQkJC0KxZsxI5zczMYG1tXepryM/Px+TJk3Hu3Dls3boVCQkJGD58uLh+4sSJuHz5Mnbt2oUrV67gxx9/hIuLy3NzPis5ORkNGzbERx99hOTkZIwfP77ENo8ePUKnTp3QrFkznDp1Crt370ZqaioGDBigtt0vv/wCc3NzHDhwoMLfoiYkJGDPnj1qf5979+7FgwcPSs3SvXt31KtXD7///jsAYMOGDVAqlfjkk09KfX4HB4dSy/fs2YO0tLRK71eW69evY9OmTdi8eTPOnj2L/v3748GDBzhw4IC4TXp6Onbv3o0hQ4YAAP7++28MHToU48aNw+XLl7FkyRKsXLkS06dPr9SxSX8JgoAcZUGlf1YfSxDPG22+/gurjyVU+jmE/3CZjCbOGydOnNDoeePZuYW0ed44f/68Rs8b27dv19l548svv9TYecPb27vU42jjvHHkyJFKjb6xtLRUG6H07GcwAPTv3x/37t3Drl27EBMTg8DAQHTu3Fm8DHvHjh3o3bs3XnvtNZw5cwaRkZEIDg4u9XibNm0SR/Rdu3YNW7duReMybtWuUqnQs2dPpKen4+DBg9i3bx9u3ryJgQMHqm1348YNbN26Fdu3b8f27dtx8OBBfP311xV+DwRBwN9//43Y2Fi1/6vh4eE4duwY1q5di/Pnz6N///7o2rWr+Ld89uxZdO7cGQ0aNMCxY8dw+PBhdO/eXbzkPDs7GxERETh16hQiIyNhYmKC3r17Q6VSVTgbGSgja4O/+DhLMiypqcDXXwP9+wM1akidRjL5+fnYsmULqlevLs4J8PTJg3Sv+3eHcf9xXoW3L1QJuJ/17/YqAfh00wXM3XMVchNZhZ7D1VaBP9+v3JwQ27dvh42NDQoKCpCXlwcTExN8//334voaNWqoVQbff/997NmzB+vXr1erWDVp0gSTJ09GXl4eGjZsiO+//x6RkZHo0qUL9u/fj9jYWOzZswfVq1cHAMyYMUNtTobffvsNubm5WLVqlVgZ/v7779G9e3fMmjULbm5uAAAnJyd8++23MDExgZ+fH2bPno2cnBx8/vnnAIAJEybg66+/xuHDhzFo0CDx+QcPHgy5XC4+/vXXX9GrVy/MnTsXn376KQYNGoS8vDzMmjULBw4cwIIFC7Bo0SJx+w8++AB9+vQRH0+ePBnffPONWObr6ys2+ocNG4akpCTUrVsXL7/8MmQymVrF29XVFUBRp4S7u7tYfu3aNXTo0KHCv7tib7/9NvLy8qBQKFCrVi18++23aNGiBbKysmBjY4OkpCQ0a9YMzZs3BwC1zqPycj6r+DIGGxsbMXdaWpraNt9//z2aNWuGGTNmiGXLly+Hp6cnrl69inr16gEA6tati9mzZ4u5y3LhwgXY2NigsLBQnNNl3rx54vri+Y7q169f6v7+/v7iNteuXYOdnR08PDzKPF5piivZ/v7+ldqvLEqlEqtWrRL/DgDg1VdfxW+//YbOnTsDADZu3AgXFxd07NgRADB16lR89tlnGDZsGACgVq1a+PLLL/HJJ59UycuRjNGT/EI0mLTnPz2HSgAm/nEJE/+o3KVQl6eFwsq84lVnTZ83gKLPBE2eN+bOnauT8wYAjZ436tSpo7PzRjFNnDdatGhR6nG0cd6ojJiYGPz222/o1KmTWPbsZ/Bff/2FkydP4t69e+L5aO7cudi6dSs2btyId955B9OnT8egQYMwdepU8XmaNm1a6jGTkpLg7u6OkJAQmJmZwcvLq8yOqMjISFy4cAHx8fHw9PQEAKxatQoNGzZEdHS0+L6qVCqsXLkStra2AIC33noLkZGRmDRpUrmv/4cffsCyZcugVCqRn58PCwsLjB07Vsy5YsUKJCUlif/Hxo8fj927d2PFihWYMWMGZs+ejebNm+OHH34Qn7Nhw4biv/v27at2vOXLl8PV1RWXL1/WypxapEeMrA3OziUyKnFxcbhy5QquXr2Kxo0bw97eXupIRu/+4zykZP73CU6f7nDSho4dO+LHH39EdnY25s+fD1NTU7XKQmFhIWbMmIH169fjzp07UCqVyMvLKzFfwLN3IfTw8MC9e/cAAFeuXIGnp6dYeQGA1q1bq21/5coVNG3aVO1b1jZt2kClUiEuLk5sJDRs2BAmJv8OTnVzc1OrwMjlcjg7O4vHLjZ//nyEhISo5cvMzMTdu3fRpk0btW3btGmDc+fOqZUVV7CBom/qbty4gREjRmDUqFFieUFBgfh/b/jw4ejSpQv8/PzQtWtXvP7663jllVdQnhcdPRATE4NJkybhwoULePjwofiNYVJSEho0aIDRo0ejb9++OH36NF555RX06tULL7300gvnLM+5c+dw4MAB2NjYlFh348YNsZEQFBRUoefz8/PDtm3bkJubi19//RVnz57F+++/X2K7irx3giBAJqtYR21ln7syvL291TqWAGDIkCEYNWoUfvjhBygUCqxZswaDBg0S/9bPnTuHI0eOqI1UKu5wy8nJ0dn8HUQAzxtV5bwxZcoUnDt3TiPnjfbt279QDkDz542nv5RQKpXo1q2bWufns5/BFy5cQFZWFpydndWe58mTJ7hx4waAohE8T//eytO/f38sWLAAtWrVQteuXfHaa6+he/fupc4xVfx3XtyxBAANGjSAg4MDrly5InYu+fj4iB1LgPr/lTVr1uDdd98V1+3atQtt27YFUHRu+eKLL/Dw4UNMnjwZL730kvh7vHDhAgoLC8X3t1heXp74XhSPri3LtWvXMGnSJJw4cQJpaWlqf0fsXKKqhJ1LZFQaNWqEe/fuoVatWuxY0hOutmWPxijNsyOXxOexUVRq5FJlWVtbo06dOgCKvnFq2rQpfv75Z4wYMQIAMGfOHCxcuBALFixA48aNYW1tjQ8++KDEJJhmZmZqj2UymVaGRZd2nIoc293dXXydxTIzMyt83KcbL8V3nVm6dClatmyptl3xt9yBgYGIj4/Hrl27sH//fgwYMAAhISHYuHFjmceoV68eYmNjK5wJ+PeykJCQEKxZswaurq5ISkpCaGio+Dt69dVXkZiYiJ07d2Lfvn3o3LkzxowZg7lz575QzvJkZWWJo82e9fSIobIu1XiWubm5+Hv7+uuv0a1bN0ydOhVffvklAIiV4itXrogV5qdduXIFDRo0ELfNyMhAcnJypUYvFR8jNja2ROP2aSYmJiUaeqVN4lvaa+/evTsEQcCOHTvQokUL/P3335g/f764PisrC1OnTlUbBVGMlz5XDZZmclyeFlqpfVIychEy7yBUT/3ZmciA/RHt4W5f8b8LSzP58zd6Cs8bFfMi543Y2Fj89ddfOjlvFF+qp4nzRqdOnbB58+ZK5Sim6fNG8ZcSpqamqF69eomR/M8+T1ZWFjw8PBAVFVXiuYove7a0tKzQsQHA09MTcXFx2L9/P/bt24f33nsPc+bMwcGDB0v83VVUeX+vPXr0UPubqvHUKBJ7e3vxb3j9+vWoU6cOWrVqhZCQEGRlZUEulyMmJkZthB4AsaPvea+7e/fu8Pb2xtKlS1G9enWoVCo0atSIN6ugKoedS1Tl3b17F25ubuIJ4ekhvyS9yl6eBhTNufT55osoFASYyICZfRpjYAsvLaQrnYmJCT7//HNERETgjTfegKWlJY4cOYKePXvizTffBFA0NPvq1atig70i6tevj1u3bqk16o8fP15im5UrVyI7O1us+B05ckS8jEEb7OzsUL16dRw5ckTtW9cjR46UOYQdKPrWu3r16rh586Y4J05Zzz9w4EAMHDgQ/fr1Q9euXZGeng4nJyeYmZmJcxYUe+ONN/D555/jzJkzJebPyM/Ph1KpLFEpjo2NxYMHD/DVV1+JFchTp06VyOLq6ophw4Zh2LBhaNu2LT7++GPMnTv3uTkrKzAwEJs2bYKPj89/uhNQWf7v//4PnTp1wujRo1G9enW88sorcHJywjfffFOic2nbtm24du2a2BHVr18/fPbZZ5g9e7Zax02xR48elTp/0iuvvAIXFxfMnj0bW7ZsKXM/V1dXPH78WO1vuHg+j+exsLBAnz59sGbNGly/fh1+fn4IDAwU1wcGBiIuLq5EQ5eqDplMVqlL0wCglqsNZvZpLJ435DIZZvRphFquJUeAaAvPGxCPa2jnja+//locMVOVzhtPfylREQEBAUhJSYGpqWmZcw42adIEkZGRCAsLq9BzWlpaonv37ujevTvGjBkDf39/XLhwQe1zHfj37/zWrVvi7+Ly5ct49OhRhf+/2Nraqo1qKouNjQ3GjRuH8ePHi38vhYWFuHfvnjjS6VnFr/vpywGLPXjwAHFxcVi6dKm4/+HDhyuUmcjQcEJvY+HsDIwYUbQ0IhcuXMDPP/+MP//8U+OXbJB0BrbwwuHPOuL3Ua1w4MOXddqxVKx///6Qy+XivBF169bFvn37cPToUVy5cgXvvvsuUlNTK/WcISEhqFevHoYNG4Zz587h77//xhdffKG2TfHk88OGDcPFixdx4MABvP/++3jrrbfESxu04eOPP8asWbOwbt06XL16FZ999hnOnj2LcePGlbvf1KlTMXPmTHz77be4evUqLly4gBUrVojzAc2bNw+///47YmNjcfXqVWzYsAHu7u5i54WPjw8iIyORkpKChw8fAiian6NNmzbo3LkzFi1ahHPnzuHmzZtYv349WrVqVWKyWADw8vKCubk5fvzxR9y8eRPbtm0TO1OKTZo0CX/88QeuX7+OS5cuYfv27eIcRc/LWVljxoxBeno6Bg8ejOjoaNy4cQN79uxBWFhYiUbRi2jdujWaNGkizs1hbW2NJUuW4I8//sA777yD8+fPIyEhAT///DOGDx+Ofv36iZPCenp6Yv78+Vi4cCFGjBiBgwcPIjExEUeOHMG7775b4n0rZm1tjWXLlmHHjh3o0aMH9u/fj4SEBMTExOCTTz7B//73PwBAy5YtYWVlhc8//xw3btzAb7/9hpUrV1b4tQ0ZMgQ7duzA8uXLSzQ+J02ahFWrVmHq1Km4dOkSrly5grVr1+L//u//XuBdpKrk6fPG4c868rzx/vt44403dHbeiIuL0+h5Y926dTo7b3z33XdGcd54ns6dO6N169bo1asX9u7di4SEBBw9ehRffPGF2Ok2efJk/P7775g8eTKuXLmCCxculDrSCgBWrlyJn3/+GRcvXsTNmzfx66+/wtLSstQ5DUNCQtC4cWMMGTIEp0+fxsmTJzF06FC0b99e7bJKTXn33Xdx9epVbNq0CfXq1cOQIUMwdOhQbN68GfHx8Th58iRmzpyJHTt2ACiajyw6Ohrvvfcezp8/j9jYWPz4449IS0uDo6MjnJ2d8dNPP+H69ev466+/EBERofHMpKeMrA3OziVj4e0NLFtWtDQilpaWEAQB+fn5vCNDFeNhb4nWtZ0rdUmDJpmamiI8PByzZ89GdnY2/u///g+BgYEIDQ1Fhw4d4O7ujl69elXqOU1MTLBlyxY8efIEwcHBGDlyZIm7XFlZWWHPnj1IT09HixYt0K9fP3Tu3FltngRtGDt2LCIiIvDRRx8hKCgIu3fvxrZt21C3bt1y9xs5ciSWLVuGFStWoHHjxmjfvj1WrlwJX19fAEXfJBZPhNmiRQskJCRg586d4rwf33zzDfbt2wdPT0/x22aFQoF9+/bhk08+wZIlS9CqVSu0aNEC3377LcaOHVvq/AWurq5YuXIlNm3ahAYNGuDrr78Wv1kuZm5ujgkTJqBJkyZo164d5HI51q5dW6GclVX8jX5hYSFeeeUVNG7cGB988AEcHBxe+Dmf9eGHH2LZsmW4desWgKIRSQcOHEBSUhLatm0LPz8/zJ8/H1988QXWrl2rNs/Se++9h7179+LOnTvo3bs3/P39MXLkSNjZ2ZV6F6NiPXv2xNGjR2FmZoY33ngD/v7+GDp0KDIyMvDVV18BKJo0+Ndff8XOnTvRuHFj/P7775gyZUqFX1enTp3g5OSEuLg4vPHGG2rrQkNDsX37duzduxctWrRAq1atMH/+/HInYCfjUXze8LCv+KU7mqRv540FCxZo7sWV4unzRuPGjTV63pg3b57OzhsbNmzQ2Hlj69aten3eKI9MJsPOnTvRrl07hIWFoV69ehg0aBASExPFTsoOHTpgw4YN2LZtGwICAtCpU6cSdz8s5uDggKVLl6JNmzZo0qQJ9u/fjz///LPEnE7Fx/7jjz/g6OiIdu3aISQkBLVq1cK6deu08lqdnJwwdOhQTJkyBSqVCitWrMDQoUPx0Ucfwc/PD7169UJ0dDS8vIo6qevVq4e9e/fi3LlzCA4ORuvWrfHHH3/A1NQUJiYmWLt2LWJiYtCoUSN8+OGHmDNnjlZykx4ysja4TOBwDklkZmbC3t4eGRkZsLOz0+hzt5oRiZTMXLjbWeD450V31MGTJ8DNm0CtWkAlroeWQmJiokYbArdv30aNGjVeaILaytB0bl3SRfbc3FzEx8fD19dXo3OfPO8uWvrKUHMDzC4FQ80N6Hf28j6XtHmepn+V9z5r67yhSfr89/08zK57hpobYHYplJXbED4b2S76hw7b4Np8zytaJ+LIJWNx5QrQqFHRsgrLzc3Ftm3bkJOTI5bVrFlT6x1LRERERERERCIjaYMXY+cSVSmbNm3CmTNnsHXrVqmjEBERERERERkF3i2OqpQuXbogIyODd4QjIiIiIiIi0hF2LpHBy83NFa83rlatGkaPHs3L4IiIiIiIiIh0hJfFGQuZDDA3L1pWEYIg4NixY/j222+RlpYmlrNjiYiIiIiIiCRVBdvg5eHIJWPRrBmQlyd1Co1SqVS4fPkynjx5gkuXLqF9+/ZSRyIiIiIiIiKqkm3w8rBziQyWXC7HoEGDcOXKFQQFBUkdh4iIiIiIiMgo8bI4Y3HlChAYaPC3QXz8+DFiY2PFx9bW1mjevDkvhSMiIiIiIiL9UUXa4BXFziVj8eQJcOZM0dJAPX78GMuWLcOGDRtw8+ZNqeMQERERERERla4KtMErg51LZDBsbGzg7e0NR0dHODo6Sh2HpJSaCqxbByxbBpMNG4oeSygqKgoymQyPHj3S6XFXrlwJBweH//QcCQkJkMlkOHv2bJnbSPX6iIg05qnzBtat43njP+B5g4iISsPOJdJ7giAAKLoLXI8ePTBixAh2LhmrCxeAwYOBmjWBQYOAUaNg9tZbRY8HDy5ar2EymazcnylTpmj8mIYoNzcXY8aMgbOzM2xsbNC3b1+kPqfxNnz48BLvZ9euXdW2SU9Px5AhQ2BnZwcHBweMGDECWVlZatucP38ebdu2hYWFBTw9PTF79uwSx9qwYQP8/f1hb2+Pxo0bY+fOnf/9RROR/ivlvIFBg3je0FMV+Tx/Vmnv8dq1a9W2iYqKQmBgIBQKBerUqYOVK1eWeJ5FixbBx8cHFhYWaNmyJU6ePKm2/kXOc0RExoSdS6S3BEHA/v37sX//frHM1NQUlpaWEqYiyezZAwQHAxs3AgUF6usKCorKg4OLttOg5ORk8WfBggWws7NTKxs/fvwLPa9SqdRoTql9+OGH+PPPP7FhwwYcPHgQd+/eRZ8+fZ67X9euXdXez99//11t/ZAhQ3Dp0iXs27cP27dvx6FDh/DOO++I6zMzM/HKK6/A29sbMTExmDNnDqZMmYKffvpJ3Obo0aMYPHgwRowYgRMnTqBXr17o1asXLl68qLk3gIj0D88bBqUin+dlWbFihdp73KtXL3FdfHw8unXrho4dO+Ls2bP44IMPMHLkSOx56ve+bt06REREYPLkyTh9+jSaNm2K0NBQ3Lt3T9zmRc9zRETGgp1L/3jetxVPu3TpEvr27QsfHx/IZDIsWLBAd0FflK8vsH590dJAJCUl4ciRIzh69Cju3r0rdRyS0oULQK9eRbfyfLaBUKygoGh9r14a/Sba3d1d/LG3t4dMJlMrs7GxEbeNiYlB8+bNYWVlhZdeeglxcXHiuilTpiAgIADLli2Dr68v7O3tAQCPHj3CyJEj4erqCjs7O3Tq1Annzp0T9zt37hw6duwIW1tb2NnZISgoCKdOnVLLuGfPHtSvXx82NjZiZ00xlUqFadOmoWbNmlAoFAgICMDu3bvLfc07d+5EvXr1YGlpiY4dOyIhIaHc7TMyMvDzzz9j3rx56NSpE4KCgrBixQocPXoUx48fL3dfhUKh9n4+PSrxypUr2L17N5YtW4aWLVvi5ZdfxnfffYe1a9eKnwlr1qyBUqnE8uXL0bBhQwwaNAhjx47FvHnzxOdZuHAhunbtio8//hj+/v748ssvERgYiO+//77cbETGqkrUiargecPCwgKA5s4bTZs2ley8UZqKfJ6XxcHBQe09Ln6vAGDx4sXw9fXFN998g/r16yM8PBz9+vXD/PnzxW3mzZuHUaNGISwsDA0aNMDixYthZWWF5cuXA/hv5zkiMmIG2Ab/L9i5hIp9W/G0nJwc1KpVC19//TXc3d11nPYFOToC/fsXLQ2Et7c3OnXqhJ49e6J69epSxyEpzZhR1Aj45xLJMglC0XYzZ+om1zO++OILfPPNNzh16hRMTU3x9ttvq62/fv06Nm3ahM2bN4uNtf79++PevXvYtWsXYmJiEBgYiM6dOyM9PR1A0cidmjVrIjo6GjExMfjss89gZmYmPmdOTg7mzp2L1atX49ChQ0hKSlL7VnzhwoX45ptvMHfuXJw/fx6hoaHo0aMHrl27VupruHXrFvr06YPu3bvj7NmzGDlyJD777LNyX3dMTAzy8/MREhIilvn7+8PLywvHjh0rd9+oqChUq1YNfn5+GD16NB48eCCuO3bsGBwcHNC8eXOxLCQkBCYmJjhx4oS4Tbt27WBubi5uExoairi4ODx8+FDc5ulsxds8LxuRMaoydaIqeN4onuNIU+eN5cuX6/S8IZPJSr0crVhFPs/LMmbMGLi4uCA4OBjLly8Xp1Qoft7yzgFKpRIxMTFq25iYmCAkJETc5r+c54jIiBlgG/y/YOcSnv9txbNatGiBOXPmYNCgQVAoFDpO+4JSU4F58ySfwPJ50tPTkZ+fLz5u27YtAgICpAtE0ktNLf2ShrIUFAAbNgBlNIS0afr06Wjfvj0aNGiAzz77DEePHkVubq64XqlUYtWqVWjWrBkaN26Mw4cP4+TJk9iwYQOaN2+OunXrYu7cuXBwcMDGjRsBFI3gCwkJgb+/P+rWrYv+/fujadOm4nPm5+dj8eLFaN68OQIDAxEeHo7IyEhx/dy5c/Hpp59i0KBB8PPzw6xZsxAQEFDm6IIff/wRtWvXxjfffAM/Pz8MGTIEw4cPL/d1p6SkwNzcvMQksW5ubkhJSSlzv65du2LVqlWIjIzErFmzcPDgQbz66qsoLCwUn7datWpq+5iamsLJyUl83pSUFLi5uZU4bvG68rYpLxuRsaoSdaIqet5o0qSJRs8bQUFBOj1v+Pn5iaN2S1ORz/PSTJs2DevXr8e+ffvQt29fvPfee/juu++e+7yZmZl48uQJ0tLSUFhYWO554kXPc0Rk5AykDa4pplIHkFrxtxUTJkwQy579tkIT8vLykJeXJz7OzMzU2HNXyJ07wEcfAR06AM+cPPVFUlIS1q5dCxcXF9SqVQsmJuz7JABRURVvIBQrKCjab8AAbSQqU5MmTcR/e3h4AADu3bsHLy8vAEWj8VxdXcVtzp07h6ysLDg7O6s9z5MnT3Djxg0AQEREBEaOHInVq1cjJCQE/fv3R+3atcVtrays1B57eHiIIwwyMzNx9+5dtGnTRu3527Rpo3YJxdOuXLmCli1bqpW1bt26Ym9AJQ0aNEj8d+PGjdGkSRPUrl0bUVFR6Ny5s1aOSURl00WdSCf1IZ43KnTeKP496Oq8ERsbW8478eImTpwo/rtZs2bIzs7GnDlzMHbsWK0cj4iowgygDa5JRt+5VN63FZo8Cc6cORNTp04tUZ6UlARbW1uNHQcACgsLxGViYiIAwDw5GR4ommRS+U+Zvrl37x7y8vKQnZ2N69ev6883oBWUk5Mjvt+GRhfZCwoKUFBQAKVSCZlMVuH9TNLTYfb8zUrIf/AAqqcaMJpQPKou75nnLZ5kVaVSieuKt33y5Any8vJQUFAAKysrcb1KpcKjR4/g4eGBvXv3ljiWvb098vLyMGHCBPTr1w+7du3Cnj17MHnyZKxevRo9e/ZEfn4+zMzM1PIUFBRAEAS1BpxSqVTbprCwUMz67DYqlQqFhYVq2z/9uou3eXq9k5MTlEolUlNT1b7VTUlJgYuLS4n3qyw1atSAi4sLrly5gpdffhnOzs7i58LTry89PR3Ozs7Iy8uDq6srkpOT1ba5desWAMDR0RF5eXlwc3PDnTt31LLfuXMHbm5uFc4mtWffc0Oiz9mVSiUKCgpw584dmJqqV4keP34sUSrp6KJOVJn6kCGcN573963J8wYAjZ43io+ti/NGRVTk87xYee97YGAgvvzyS2RmZkKhUKBatWq4e/eu2va3b9+GnZ0dTExMYGtrC7lcjtu3b6ttc/fuXVSrVg15eXkaO8/p8+fh8zC77pWVu7xzl75gu6iILtvg2nzPK1on0s+/xipowoQJiIiIEB9nZmbC09MTXl5esLOz0+ix5PLrAAogl5vC29u7qPCfeUw8PDyA4jI94+3tjWrVqqGgoEDtGzZDkZiY+O/7bWB0kT03Nxfx8fEwNzevXMehk9MLHc/M2RnQcAdl8ZwVz+Yvnh9CoVCI654tMzU1hUwmE9fn5eUhODgYkydPhpWVFXx8fMo8bqNGjdCoUSN8/PHHGDx4MH799VcMGDCg1DxPl7m6uqJ69eqIjo5Gly5dxG2OHz+O4ODgEnkVCgUaNmyIbdu2qT1nTEyM2mvJy8tTW9+6dWuYmZnh8OHD6Nu3LwAgLi4Ot27dQtu2bSv8+759+zYePHgALy8vKBQKtGvXDo8ePcLFixcRFBQEADh48CBUKhVefvllKBQKvPzyy/jiiy9gYmIivvaDBw/Cz89PnP/lpZdewsGDBzF+/Hgx+4EDB/DSSy8ZTCf2s++5IdHn7IIgwNTUFDVq1FCbABiQYISxkahMfcgQzhvP+/vW5HkDgEbPG8XZdXHeqIiKfJ4XK+99v3TpEhwdHcW/pzZt2mDnzp1q20dFRaF169ZivqCgIBw6dAj9+/cHUNSoj4qKQnh4OBQKhcbOc/r8efg8zK57ZeUu79ylL9gu+ocO2+DafM8rWicy+uuOXFxcIJfLkfrMdZCpqakanZhSoVDAzs5O7cfYFRYWYt++fWp/rN7e3nrbA08S6dABqOzfhKlp0X56LiQkBK1bt0avXr2wd+9eJCQk4OjRo/jiiy9w6tQpPHnyBOHh4YiKikJiYiKOHDmC6Oho1K9fv8LH+PjjjzFr1iysW7cOcXFx+Oyzz3D27FmMGzeu1O3/97//4dq1a/j4448RFxeH3377rdwJWIGib8tHjBiBiIgIHDhwADExMQgLC0Pr1q3RqlUrcTt/f39s2bIFAJCVlYWPP/4Yx48fR0JCAiIjI9GzZ0/UqVMHoaGhAID69euja9euGDVqFE6ePIkjR44gPDwcgwYNEif5f+ONN2Bubo4RI0bg0qVLWLduHRYuXKjWeB03bhx2796Nb775BnFxcZgyZQpOnTqF8PDwCr+PRMZAF3UindSHeN7Qy/PG0+eA0lTk83zLli3w9/cXH//5559YtmwZLl68iOvXr+PHH3/EjBkz8P7776vlu3nzJj755BPExsbihx9+wPr16/Hhhx+K20RERGDp0qX45ZdfcOXKFYwePRrZ2dkICwsDUPHzHBGRMTP6ziVzc3MEBQWpTWSoUqkQGRmptXlGJGFvD3TvXrTUE7t378bRo0exdu1aqFQqqeOQvnJzA/r1q3hDwdS06K4Mz0wErY9kMhl27tyJdu3aISwsDPXq1cOgQYOQmJgINzc3yOVyPHjwAEOHDkW9evUwYMAAvPrqq6VeUlKWsWPHIiIiAh999BEaN26M3bt3Y9u2bahbt26p23t5eWHTpk3YunUrmjZtisWLF2PGjBnPPc78+fPx+uuvo2/fvmjXrh3c3d2xefNmtW3i4uKQkZEBAJDL5Th//jx69OiBevXqYcSIEQgKCsLff/+t9i3dmjVr4O/vj86dO+O1117Dyy+/jJ9++klcb29vj7179yI+Ph5BQUH46KOPMGnSJLzzzjviNi+99BJ+++03/PTTT2jRogU2btyIrVu3olGjRhV+H4mMQZWpE/G8oZfnjafPAaWpyOd5RkYG4uLixMdmZmZYtGgRWrdujYCAACxZsgTz5s3D5MmTxW18fX2xY8cO7Nu3D02bNsU333yDZcuWiV9kAMDAgQMxd+5cTJo0CQEBATh79ix2796tdoloRc5zRERq9LANrk0yQXjePVqrvnXr1mHYsGFYsmQJgoODsWDBAqxfvx6xsbFwc3PD0KFDUaNGDcz85za1SqUSly9fBgC89tprGDJkCIYMGQIbGxvUqVOnQsfMzMyEvb09MjIyNP6tXasZkUjJzIW7nQWOf66/k+I+evQIq1atQteuXVGvXj2x3FCHURpqbkC3l8X5+vpWfgjvhQtAcDCQl1f+baVlsqJLGk6eBBo3/m+BtcxQh2gDzC4FQ80N6Hf28j6XtHme1me6rhOV9z4bwnlDn/++n4fZdc9QcwPMLoWycv+nz0YdYbtI97R9WVxF6kS8/ghF31bcv38fkyZNQkpKCgICAtS+rUhKSlK7c9ndu3fRrFkz8fHcuXMxd+5ctG/fHlFRUbqOXzH5+cCjR4CDA2D2ItNcaipGvngdvYODA8aMGQO5XC5ZHjIQjRsDW7cCvXoV3dGntLsAmZoW/WzdqvcdS0RE+qrK1Il43iAiIqnpSRtcV9i59I/w8PAy5994tnLk4+MDgxvwdeECEBQExMQAgYGSRIiLi8Off/6JN954Q5wvhR1LVGGhoUXfLM+cCWzYoN5QKL6kYcIENhCIiP6jKlMn4nmDiIikpAdtcF1i5xLphCAIiImJQXZ2Nk6ePIlevXpJHYkMUePGwG+/AQsWAFFRQGYm8i0tYdali0HMlUFERDpWynkDdnZFk3fzvEFERKQx7FwinZDJZOjbty+OHz+Ol19+Weo4ZOiqVQMGDAAAqPLyKn3raCIiMjJPnTeIiIhI84z+bnGkPUqlErGxseJjhUKB9u3b81I4IiIiIiIioiqEnUukFUqlEr/88gvWrVsn3kWGiIiIiIiIiKoeXhZnLJo2BTIyAGtrnRzOzMwMNWrUwMOHD2Fra6uTYxIRERERERHpBR23waXGziVjIZcXTWCpIzKZDF27dkWbNm1gb2+vs+MSERERERERSU7HbXCp8bI4Y3HtWtEtea9d09ohzpw5g+3bt4u3JDYxMWHHEhERERERERkfHbTB9Qk7l4zF48fA3r1FSy148OAB/vzzT8TExCAuLk4rxyAiIiKisslkMmzdurVC21pYWFR4WzJMPj4+WLBggfi4Mn8fRKQBWm6D6xt2LpFGODs7o2vXrmjbti38/PykjkOkMTKZrNyfKVOmICEhQa3M2dkZr7zyCs6cOSM+T4cOHcT1FhYWaNSoEWbOnCmO9KuMDRs2wN/fHxYWFmjcuDF27tz53H0WLVqE+vXrw9LSEn5+fli1alWZ265duxYymQy9evUqc5v//e9/kMlkapXWp+Xl5SEgIAAymQxnz559br6nTZkypdT3ev/+/SXWm5qawsfHBx9++CGysrIAoMTvw8nJCe3bt8fff/9dqRwAkJubizFjxsDZ2Rk2Njbo27cvUlNTy91HEARMmjQJHh4esLS0REhICK49843V9OnT8dJLL8HKygoODg6lPs/YsWMRFBQEhUKB4ODgEuujoqLQs2dPeHh4wNraGgEBAVizZk2lXyMRad7w4cPFzyBzc3PUqVMH06ZNQ0FBgVaPm5ycjFdffbVC2yYkJFR4W02qyGfksx4/fowPPvgA3t7esLS0RIcOHRAdHa22TVZWFsLDw1GzZk1YWlqiQYMGWLx4sdo2FflMj46ORufOneHg4ABHR0eEhobi3LlzlXqNT5+n5HI5PD098c477yA9Pb1Sz6MP0tPTMWTIELi6usLBwQEjRowQz7dluXHjBnr37g1XV1fY2dlhwIABZZ47K1JfuH79Omxtbcs8XwIVq7sQkXaxc4le2JMnT/DkyRPxcXBwMDp16gSZTCZhKiLNSk5OFn8WLFgAOzs7tbLx48eL2+7fvx/JycnYs2cPsrKy8Oqrr+LRo0fi+lGjRiE5ORlxcXH4+OOPMWnSpBIV3+c5evQoBg8ejBEjRuDMmTPo1asXevXqhYsXL5a5z48//ogJEyZgypQpuHTpEqZOnYoxY8bgzz//LLFtQkICxo8fj7Zt25b5fH/88QeOHz+O6tWrl7nNJ598Uu7652nYsKHa+5ycnIx27dqVWJ+QkIBZs2bhp59+wkcffaT2HMW/j0OHDqF69ep4/fXXn9sx9KwPP/wQf/75JzZs2ICDBw/i7t276NOnT7n7zJ49G99++y0WL16MEydOwNraGqGhocjNzRW3USqV6N+/P0aPHl3uc7399tsYOHBgqeuOHj2KJk2aYNOmTTh//jzCwsIwdOhQbN++vVKvkYi0o2vXrkhOTsa1a9fw0UcfYcqUKZgzZ06p2yqVSo0c093dHQqFQuPbalJFPiOfNXLkSOzbtw+rV6/GhQsX0LlzZ4SEhODOnTviNhEREdi9ezd+/fVXXLlyBR988AHCw8Oxbds2cZvnfaZnZWWha9eu8PLywokTJ3D48GHY2toiNDQU+fn5lXqdxeeppKQkrFixArt378bYsWMr9Rz6YMiQIbh06RJ27NiB7du349ChQ3jnnXfK3D47OxuvvPIKZDIZ/vrrLxw5cgRKpRLdu3eHSqUqsf3z6gv5+fkYPHhwufWSitRdiEgHBJJERkaGAEDIyMjQ+HO3nL5f8P50u9By+v5/C2NiBAEoWmrAgwcPhO+++05YuXKlUFBQoJHnLJaQkKDR59MVQ80tCLrJ/uTJE+Hy5cvCkydPNPq8ubm5Gn2+8qxYsUKwt7cvUR4fHy8AEM6cOSOWHTlyRAAg7N69WxAEQWjfvr0wbtw4cX1ubq4QGBgo9O7du1IZBgwYIHTr1k2trGXLlsK7775b5j6tW7cWxo8fr1YWEREhtGnTRq2soKBAeOmll4Rly5YJw4YNE3r27FniuW7fvi3UqFFDuHjxouDt7S3Mnz+/xDY7d+4U/P39hUuXLpV4Xypi8uTJQtOmTSu1ftSoUYK7u7sgCKX/Ps6fPy8AEDZu3FjhHI8ePRLMzMyEDRs2iGVXrlwRAAjHjh0rdR+VSiW4u7sLc+bMUXsehUIh/P777yW2L+tv6mmTJ08WmjRpUqHMr732mhAWFlahbXVFl/9HK6u8zyVtnqfpX+W9z9o6b2hSWX/fpX2GdunSRWjVqpXa+q+++krw8PAQfHx8BEEQhKSkJKF///6Cvb294OjoKPTo0UOIj49Xe56ff/5ZaNCggWBubi64u7sLY8aMEdcBELZs2SIIgiDk5eUJY8aMEdzd3QWFQiF4eXkJM2bMKHVbQSj6nOzYsaNgYWEhODk5CaNGjRIeP35c4jXNmTNHcHd3F5ycnIT33ntPUCqVFX6/KvsZKQiCkJOTI8jlcmH79u1iWfE59IsvvhDLGjZsKEybNk1t36e3qchnenR0tABASEpKUntfAAjXrl2r8Oss7TwVEREhODo6qpUtXbpU8Pf3FxQKheDn5ycsWrRIbf2tW7eEQYMGCY6OjoKVlZUQFBQkHD9+XBAEQbh+/brQo0cPoVq1aoK1tbXQvHlzYd++fWr7P3uefvZ3/jyXL18WAAjR0dHi3/quXbsEmUwm3Llzp9R99uzZI5iYmKj9n3706JEgk8lK5KtIfeGTTz4R3nzzzTLPlxWpu+jzeag8ZeU2hM9Gtov+oeE2eHm0+Z5XtE7EkUvGwtMT+P77oqUG5Ofn4/Hjx3j48CEeG8k1pESVYWlpCaD0b6MFQcDhw4cRGxsLc3NzsTwqKgoymQwJCQllPu+xY8cQEhKiVhYaGopjx46VuU9eXh4sLCxK5Dt58qTaN7HTpk1DtWrVMGLEiFKfR6VS4a233sKHH36Ihg0blrpNamoqRo0ahdWrV8PKyqrMTJpmaWlZ5jf/T548ES8DfPr9Hj58ODp06FDmc8bExCA/P1/t/fb394eXl1eZ73d8fDxSUlLU9rG3t0fLli3L/R1pSkZGBpycnLR+HCKqvGc/pyIjIxEXF4d9+/Zh+/btyM/PR2hoKGxtbfH333/jyJEjsLGxQdeuXcX9fvzxR4wZMwbvvPMOLly4gG3btqFOnTqlHu/bb7/Ftm3bsH79esTFxWHNmjXw8fEpddvs7GyEhobC0dER0dHR2LBhA/bv34/w8HC17Q4cOIAbN27gwIED+OWXX7By5UqsXLlSXD9lypQyjwG82GdkQUEBCgsLSz2PHT58WHz8/+3deVwU9f8H8NfCwoLI4cHpgYqImITiiZl4JSQSmn7VNAQz7SC/llfeqHgHpHmUV3iLqeSRJimhZuEF6teT8kBKBTUvkBs+vz+I+bmyILvALpuv5+PBo5j5zOxrhnXmvZ/9zEynTp2wZ88e3Lp1C0IIxMXF4ffff0evXr0AlO+Y7uLigjp16mDt2rXIzc1FVlYW1q5dC1dX1zK360WSk5MRExOjdA7avHkzZsyYgblz5+Ly5cuYN28epk+fjvXr1wMoGkXl5eWFW7duYc+ePTh37hwmTpwojf7JyMhA7969ERsbizNnzsDHxwd+fn5ISUkpd66uXbsiKCio1Pnx8fGwsrJC27ZtpWk9e/aEgYEBTpw4oXKZnJwcyGQypVFxJiYmMDAwUPp7lade+Pnnn7F9+3YsX7681Iwvql2IdKqSP4NXd3JdByAtsbYGgoMrbXW2trYYMmQIateuDXNz80pbL72k7twp+nlWrVpA48ZAdjZw6VLJZTw8AACy338Hnh+q3qgRULs2cO8e8OefyvPs7Yt+qtCjR48QGhqKmjVrKt0rZ8WKFVizZg1yc3ORl5cHExMTpSHyNWrUgIuLC4yMjEpdd2pqKmxtbZWm2draIjU1tdRlvL29sWbNGvTt2xceHh5ISEjAmjVrkJeXh/v378Pe3h7Hjh3D2rVry7w/0sKFCyGXyxFcyrFECIGgoCB8+OGHaNu2bZmdZC9y/vx51KxZU/q9RYsWOHnypMq2CQkJ2LJlC7p37640vVOnTjAwMEBmZiaEEGjTpg26desmzbe3t1c5RL9YamoqjI2NS9zjoaz9XTxd3b9RZfjuu+9w6tQprFy5skpfh6haqMB5A0lJwNOnyvPKOm+YmwPOzhpHFUIgNjYWMTExGD16tDTdzMwMa9askTocNm3ahMLCQqxZs0a6xUBkZCSsrKxw+PBh9OrVC3PmzMG4ceMwZswYaT3t2rVT+bopKSlwdnZG586dIZPJ4OjoWGrGLVu2IDs7Gxs2bICZmRkAYNmyZfDz88PChQulY1qtWrWwbNkyGBoaonnz5vD19UVsbCxGjhwJAKhbty6cnJxKfR1NjpHm5ubw9PREaGgoXF1dYWtriy1btiA+Pl6pY23p0qUYNWoU6tevD7lcDgMDA6xevVq6pLo8x3Rzc3McPnwYffv2RWhoKADA2dkZMTExkMvV+9hUfB4rKCiQLvlbtGiRND8kJATh4eHSZXmNGzfGpUuXsHLlSgQGBmLLli24d+8eTp06JX1p8Oz2uru7w93dXfo9NDQU33//Pfbs2VOiU7A0DRs2hH0ZNVFqaipsbGyUpsnlctSuXbvUv1fHjh1hZmaGzz//HPPmzYMQApMmTUJBQQHu/PNvtjz1wt9//42goCBs2rQJFqU8yr08tQuRTlXyZ/Dqjp1LL4sHD4D9+4HevYuKJzUJIXDixAk4OzujTp06AFBmkUKklpUrgVmzlKcNHQps2gT89RfQpk3JZf65EbZ85Ejg+W/PNm4E3n0X+O474PkCKyQEmDmz8rI/o7gz4+nTp2jSpAm2bdumVEAPHToUU6dOxcOHDzF9+nR07twZnTp1kua3b98eV65cqfRc06dPR2pqKjp27AghBGxtbREYGIhFixbBwMAA6enpCAgIwOrVq1G3bl2V60hISMCSJUuQmJhY6n3Vli5divT0dEyePLnCmV1cXJTuk/H8fUGeLdpzc3Ph6+uLZcuWKbXZtm0bmjdvjgsXLmDixIlYt26dUsfd/PnzK5yzuoiLi8Pw4cOxevXqUkeVEf2rVOC8gaAg4Phx5XllnTd69QJiYtSO+MMPP6BmzZrIy8tDYWEhhgwZgpnPnH/c3NyURrKcO3dOunHxs7Kzs3Ht2jXcvXsXt2/fRo8ePcr1+kFBQXjjjTfg4uICHx8f9OnTRxrF87zLly/D3d1d6lgCgNdeew2FhYVISkqSzmWvvPIKDA0NpTb29vY4f/689Psnn3xS7o4NdWzcuBHvvfce6tWrB0NDQ7Ru3RrvvPMOEhISpDZLly7F8ePHsWfPHjg6OuLo0aMIDg6Gg4NDiRG/pcnKysKIESPw2muvYevWrSgoKEBYWBh8fX1x6tQpaVRyeRSfx7Kzs7Fp0yacPXsWH3/8MYCikWLXrl3DiBEjpI45oGiUlqWlJQDg7NmzaN26damjUTMyMjBz5kzs27cPd+7cQX5+PrKystQauVTWwz00ZW1tje3bt+Ojjz7CV199BQMDA7zzzjvw8PCAgUHRRTPlqRdGjhyJIUOGKN1v8VnlqV2IdK6Cn8H1DTuXXhbJyUBAAJCQoNEbOz4+HgcPHsSpU6fwwQcfKBVDRBX2wQfAW28pT6tVq+i/9esXvW9Lkb96NYxVjVwCgIEDAU9P5XlVOGpp27ZtaNGiBerUqaPyiSaWlpbSt46bN2/GK6+8go4dO5a76AWKbsD6/E2p09LSYGdnV+oypqam+Pbbb7Fy5UqkpaXB3t4eq1atgrm5OaytrfG///0PycnJ8PPzk5YpHtEjl8uRlJSEX375BXfv3kXDhg2lNgUFBRg3bhwWL16M5ORk/Pzzz4iPjy/REdS2bVsMHTpUGupfHsVPVypNcdEul8vh4OCg8pjUoEEDODs7w9nZGfn5+ejXrx8SEhLUutltbm4uHj16pPT3LGt/F08v3s/PLtOqVatyva66jhw5Aj8/P3z55ZcYNmxYlbwGUbVTgfMG1q1TPXIJUH3e0HCEdrdu3fD111/D2NgYDg4OJUa+PNuRAxR1FrRp00blUx+tra2lD+bl5eHhgRs3buDHH3/EoUOHMHDgQPTs2RM7duxQf2P+8fzIWplMVuYI0Odpeox0cnLCkSNH8PTpUzx58gS1a9fGsGHD0KRJEwBFnUJTpkzB999/D19fXwDAq6++irNnzyIsLAw9e/Ys1zF9y5YtSE5ORnx8vLS/t2zZglq1amH37t0YPHhwubf12fPYggUL4Ovrizlz5mD+/PnS09ZWr16NDh06KC1X3Hn3oo6s8ePH4+DBgwgLC0PTpk1hamqKAQMGVNrN4YGiv9fdu3eVpuXn5+PBgwdl1h29evXCtWvXcP/+fcjlclhZWcHOzk76e5WnXvj555+xZ88ehIWFASj6oruwsBByuRyrVq2Ch4fHC2uXskbREWlFBT+D6xt2LlG5vPrqqzh9+jTat2/PjiWqfGVdqmZi8v+XMqggmjUDSusssLYu+tGSBg0alLuQqVmzJsaMGYPx48fjzJkz5X7KoqenJ2JjY/Hpp59K0w4ePAjP5z8MqWBkZIT69esDKHpkb58+fWBgYIDmzZsrffMMANOmTUN6ejqWLFmCBg0aICAgQOoEy83NhbGxMby9vREQEIDhw4cDKLq/x5w5c6R13L59G97e3ti2bVuJ4rmiXtT59LwBAwZgxowZWLlyJSZMmFCuZdq0aQMjIyPExsaif//+AICkpCSkpKSUur8bN24MOzs7xMbGSh+Unjx5ghMnTrzwyXCaOHz4MPr06YOFCxeW+fQeon+dCpw34OJS+rxKPG+YmZmpdZzy8PDAtm3bYGNjU+plQI0aNUJsbKzSJb5lsbCwwKBBgzBo0CAMGDAAPj4+ePDgQYnRMK6urli3bh2ePn0qdXr9+uuvMDAwgEtZ+0tNFT1GmpmZwczMDKmpqYiJiZEuM8vLy0NeXl6JDjhDQ0Opw6E8x/TMzEwYGBgonZOLf1enE02VadOmoXv37hg9ejQcHBzg4OCA69evY+jQoSrbv/rqq1izZo3KvxdQ9PcJCgpCv379ABR1TlbkcnRVPD098ejRIyQkJKBly5YAijqGCgsLy3VeLx5R9PPPP+Pu3bt4658O4fLUC/Hx8SgoKJDa7N69GwsXLsRvv/2GevXqwdTU9IW1CxFpFzuXqFQFBQXStyc1a9bERx99VOa9YIhIPR988AFCQ0Oxc+dODBgwACdPnsSwYcMQGxuLevXqqVxmzJgx8PLyQnh4OHx9fREVFYXTp09j1apVUpvJkyfj1q1b0nD333//HSdPnkSHDh3w8OFDRERE4MKFC9JIIhMTE6loLFb8rW7x9Dp16kiXxObk5EChUMDIyAh2dnbSB49nRzUBkO6Z5OTkJHVq6YpMJsN///tfzJw5E8HBwahRo0aJ/fQ8S0tLjBgxAmPHjkXt2rVhYWGB0aNHw9PTEx07dpTaNW/eHPPnz0e/fv0gk8nw6aefYs6cOXB2dkbjxo0xffp0ODg4oG/fvtIyKSkpePDgAVJSUlBQUCDdL6Jp06bSfrt69SoyMjKQmpqKrKwsqU2LFi1gbGyMuLg49OnTB2PGjEH//v2l+18YGxvzpt5Eemjo0KH44osv4O/vj9mzZ6N+/fq4efMmoqOjMXHiRNSvXx8zZ87Ehx9+CBsbG7z55ptIT0/Hr7/+qnQvp2IRERGwt7dH69atYWBggO3bt8POzk7lyNqhQ4ciJCQEgYGBmDlzJu7du4fRo0cjICCgxP2RyrJs2TJ8//33iI2NVTm/vMfIHj16oF+/ftIldjExMRBCwMXFBVevXsX48ePRvHlz6csNCwsLeHl5YcKECTA1NYWjoyOOHDmCDRs2ICIiAkD5julvvPEGJkyYgODgYIwePRqFhYVYsGAB5HJ5uTv0SuPp6Qk3NzfMmzcPy5Ytw6xZs/Df//4XlpaW8PHxQU5ODk6fPo2HDx9i7NixeOeddzBv3jz07dsX8+fPh729Pc6cOQMHBwd4enrC2dkZ0dHR8PPzg0wmw/Tp09XuABs2bBjq1atX6mXirq6u8PHxwciRI/HVV19BJpPhk08+weDBg+Hg4AAAuHXrFnr06IENGzZI95mMjIyEq6srrK2tER8fjzFjxuCzzz5Tq15wdXVVanP69GkYGBgo1Ssvql2ISLv4tDhS6c6dO1i2bJnSNyDsWCKqXMXD+mfOnInCwkJkZmYiKSlJ6Qluz+vUqRO2bNmCVatWwd3dHTt27MCuXbuUCqk7d+4o3XOhoKAA4eHhcHd3xxtvvIHs7Gz89ttvFXryTUXIZDKlpwtpS2BgIPLy8qR7Mz2/n1T58ssv0adPH/Tv3x9dunSBnZ0doqOjldokJSXh8ePH0u8TJ07E6NGjMWrUKLRr1w4ZGRk4cOCA0pOOZsyYgdatWyMkJAQZGRlo3bo1WrdujdOnT0tt3n//fbRu3RorV67EH3/8IbW5ffs2AGD9+vXIzMyUPnQU/xTfHJaI9EuNGjVw9OhRNGzYEG+//TZcXV0xYsQIZGdnSyOZAgMDsXjxYqxYsQKvvPIK+vTpgz/++EPl+szNzbFo0SK0bdsW7dq1Q3JyMvbv36/y8roaNWogJiYGDx48QLt27TBgwAD06NGjxL3sXuT+/fu4du1amW3Kc4wsvqSq2OPHjxEcHIzmzZtj2LBh6NSpE2JiYpRq06ioKLRr1w5Dhw5FixYtsGDBAsydOxcffvih1OZFx/TmzZtj7969+N///gdPT0+8/vrruH37Ng4cOKB0GZ+m57HRo0djzZo1+PPPP/H+++9jzZo1iIyMhJubG7y8vLBu3To0btwYQNEXBT/99BNsbGzQu3dvuLm5YcGCBdIXvxEREahVqxY6deoEPz8/eHt7w6OsEXsqpKSkSDfZLs3mzZvRvHlzvPnmm+jduzc6d+6s9IVWXl4ekpKSkJmZKU1LSkpC37594erqitmzZ2Pq1KnS5W1E9O8lE6L47oakTU+ePIGlpSUeP35c6tBnTXWcF4vUJ9mwszDB8Sn/3PQxKanoBpbr1pU9HPwfu3fvxtmzZ9GwYUMEBQWV+5KdynDz5k29vFm4vuYGtJM9OzsbN27cQOPGjUs8TrgiikfR6Bt9zQ1ULPuNGzfQrFkzXLp0Cc4VePqSpvR1v+trbqB6Zy/ruFSV52n6f2Xt56o6b1Sm6vz+fhFm10xFzmPc57qhr9lLy60Px0Z+LvqHmp/BK6Iq93l5ayJeFveycHEB4uPL3bx3794wNTVFly5dtNqxRET/bvv378eoUaN00rFERERUUTyPEVG5qfkZXN+xc4kAFD2B4erVq9KJ0sjIqNTH1RIRaSo4OFjXEYiIiDTG8xgRkWq859LLIjERkMmK/vscIQS2b9+OLVu2IFHFfCIiIiIiIiJSQxmfwf+N2LlEkMlksLa2hqGhIW/aTURERERERERq4WVxBADo2rUrWrZsCWtra11HISIiIiIiIiI9wpFLL6nk5GTs3r0bxQ8LLB69RFTV+IBKIqoueDzSD/w7ERH9Px4Tqbpi59JLKCsrC1u3bsXZs2dx8uRJXcehl0TxJZeZmZk6TkJEVKT4eMRLwqsnnjeIiEriuYuqK14W97Jo0QL44w+gfn2YmpigT58+SEpKQps2bXSdjF4ShoaGsLKywt27dwEANWrUgEwmq/B6c3Nz9fIbHH3NDTC7LuhrbqB6ZhdCIDMzE3fv3oWVlRUMDQ11HYlUqKrzRmWqju/v8mJ27dPX3ACz68LzuXnu0kPPfAZ/GbBz6SVRYGSEHAcH1DAxAQC4ubmhZcuW1a5Io383Ozs7AJA+KFSG/Px8yOX6dyjT19wAs+uCvuYGqnd2Kysr6bhE1VNVnDcqU3V+f78Is2ufvuYGmF0XSsvNc5ceMTEBmjbVdQqt0b9/ZaS2rKws7F++HK9u3w7HDRtg7OICAOxYIq2TyWSwt7eHjY0N8vLyKmWdt27dQr169SplXdqkr7kBZtcFfc0NVN/sRkZG/NZXD1TFeaMyVdf3d3kwu/bpa26A2XVBVW6eu/TMjRvA9OlAaCjQuLGu01Q5di79Y/ny5fjiiy+QmpoKd3d3LF26FO3bty+1/fbt2zF9+nQkJyfD2dkZCxcuRO/evbWYuPyys7OR8eefcD55Endv3IDNP51LRLpiaGhYaSdGuVwOk39G5OkTfc0NMLsu6GtuQL+zv6yqY01UmeeNyqTP729m1z59zQ0wuy7oa256xsOHwObNwNixL0XnEm/oDWDbtm0YO3YsQkJCkJiYCHd3d3h7e5c6BPu3337DO++8gxEjRuDMmTPo27cv+vbtiwsXLmg5uWoFhULpv7Vq1YKPjw8AwMbGRme5iIiIqHr7t9VEREREpB3sXAIQERGBkSNHYvjw4WjRogW++eYb1KhRA99++63K9kuWLIGPjw8mTJgAV1dXhIaGwsPDA8uWLdNy8pK2nUrBvYwcAMC9jBxsO5UCALC1tdVlLCIiItID/6aaiIiIiLTnpb8sLjc3FwkJCZg8ebI0zcDAAD179kR8fLzKZeLj4zF27Filad7e3ti1a1epr5OTk4OcnBzp98ePHwMAnjx5UoH0ylIfZ+HzrSdQ+MzDED7fegKt7RSwy8gompCRAVTia1aF9PT0St0v2qKvuQFm1wV9zQ0wuy7oa25Af7MXZ9bHJwxpShs1kTbqIW3S1/c3wOy6oK+5AWbXBX3NDTC7RIufwatyn5e3JnrpO5fu37+PgoKCEiN7bG1tceXKFZXLpKamqmyfmppa6uvMnz8fs2bNKjG9QYMGGqRWj8uXz/zi5VXlr0dERPRv8ffff8PS0lLXMbRCGzWRLushIiIinfiXfAZPT08vsyZ66TuXtGXy5MlK3+wVFhbiwYMHqFOnTqU/te3Jkydo0KAB/vzzT1hYWFTququavmbX19wAs+uCvuYGmF0X9DU3oN/ZHz9+jIYNG6J27dq6jvKv8nw99OjRIzg6OiIlJUXvOvH0+f3N7Nqnr7kBZtcFfc0NMLsuVHVuIQTS09Ph4OBQZruXvnOpbt26MDQ0RFpamtL0tLQ02NnZqVzGzs5OrfYAoFAooFAolKZZWVlpFrqcLCws9OofxbP0Nbu+5gaYXRf0NTfA7Lqgr7kB/c5uYPDy3J5SGzWRqnoIACwtLfX2PaLP729m1z59zQ0wuy7oa26A2XWhKnOX5wugl6diKoWxsTHatGmD2NhYaVphYSFiY2Ph6empchlPT0+l9gBw8ODBUtsTERERVXesiYiIiEhTL/3IJQAYO3YsAgMD0bZtW7Rv3x6LFy/G06dPMXz4cADAsGHDUK9ePcyfPx8AMGbMGHh5eSE8PBy+vr6IiorC6dOnsWrVKl1uBhEREVGFsCYiIiIiTbBzCcCgQYNw7949zJgxA6mpqWjVqhUOHDgg3aAyJSVFaVh8p06dsGXLFkybNg1TpkyBs7Mzdu3ahZYtW+pqE5QoFAqEhISoHHZe3elrdn3NDTC7LuhrboDZdUFfcwPMro+0XRPp835mdt3Q1+z6mhtgdl3Q19wAs+tCdcktEy/TM3aJiIiIiIiIiKhSvfT3XCIiIiIiIiIiIs2xc4mIiIiIiIiIiDTGziUiIiIiIiIiItIYO5eIiIiIiIiIiEhj7FzSU8uXL0ejRo1gYmKCDh064OTJk2W23759O5o3bw4TExO4ublh//79WkpakjrZL168iP79+6NRo0aQyWRYvHix9oI+R53cq1evxuuvv45atWqhVq1a6Nmz5wv/RlVJnezR0dFo27YtrKysYGZmhlatWmHjxo1aTKtM3fd6saioKMhkMvTt27dqA5ZCndzr1q2DTCZT+jExMdFiWmXq7vNHjx4hODgY9vb2UCgUaNasmc6OMepk79q1a4n9LpPJ4Ovrq8XERdTd54sXL4aLiwtMTU3RoEEDfPbZZ8jOztZSWmXqZM/Ly8Ps2bPh5OQEExMTuLu748CBA1pMW+To0aPw8/ODg4MDZDIZdu3a9cJlDh8+DA8PDygUCjRt2hTr1q2r8pz/FqxZdENf6xbWLLqhr3ULaxbt1yyA/tYt+lizAHpUtwjSO1FRUcLY2Fh8++234uLFi2LkyJHCyspKpKWlqWz/66+/CkNDQ7Fo0SJx6dIlMW3aNGFkZCTOnz+v5eTqZz958qQYP3682Lp1q7CzsxNffvmldgP/Q93cQ4YMEcuXLxdnzpwRly9fFkFBQcLS0lL89ddfWk6ufva4uDgRHR0tLl26JK5evSoWL14sDA0NxYEDB7ScXP3sxW7cuCHq1asnXn/9deHv76+dsM9QN3dkZKSwsLAQd+7ckX5SU1O1nLqIutlzcnJE27ZtRe/evcWxY8fEjRs3xOHDh8XZs2e1nFz97H///bfSPr9w4YIwNDQUkZGR1Tr35s2bhUKhEJs3bxY3btwQMTExwt7eXnz22WdazS2E+tknTpwoHBwcxL59+8S1a9fEihUrhImJiUhMTNRq7v3794upU6eK6OhoAUB8//33Zba/fv26qFGjhhg7dqy4dOmSWLp0qc6Oi/qGNYtu6GvdwprFXzthn6OvdQtrFu3XLELob92irzWLEPpTt7BzSQ+1b99eBAcHS78XFBQIBwcHMX/+fJXtBw4cKHx9fZWmdejQQXzwwQdVmlMVdbM/y9HRUWeFWkVyCyFEfn6+MDc3F+vXr6+qiKWqaHYhhGjdurWYNm1aVcQrkybZ8/PzRadOncSaNWtEYGCgTgo1dXNHRkYKS0tLLaUrm7rZv/76a9GkSRORm5urrYilquh7/csvvxTm5uYiIyOjqiKqpG7u4OBg0b17d6VpY8eOFa+99lqV5lRF3ez29vZi2bJlStPefvttMXTo0CrNWZbyFGkTJ04Ur7zyitK0QYMGCW9v7ypM9u/AmkU39LVuYc3ir4WkJelr3cKaRfs1ixD6W7f8G2oWIap33cLL4vRMbm4uEhIS0LNnT2magYEBevbsifj4eJXLxMfHK7UHAG9v71LbVxVNslcHlZE7MzMTeXl5qF27dlXFVKmi2YUQiI2NRVJSErp06VKVUUvQNPvs2bNhY2ODESNGaCNmCZrmzsjIgKOjIxo0aAB/f39cvHhRG3GVaJJ9z5498PT0RHBwMGxtbdGyZUvMmzcPBQUF2ooNoHL+na5duxaDBw+GmZlZVcUsQZPcnTp1QkJCgjSU+/r169i/fz969+6tlczFNMmek5NT4tIJU1NTHDt2rEqzVlR1OY/qG9YsuqGvdQtrFt3Q17qFNYv2axZAf+uWl6lmAXR3LmXnkp65f/8+CgoKYGtrqzTd1tYWqampKpdJTU1Vq31V0SR7dVAZuT///HM4ODiU+Ede1TTN/vjxY9SsWRPGxsbw9fXF0qVL8cYbb1R1XCWaZD927BjWrl2L1atXayOiSprkdnFxwbfffovdu3dj06ZNKCwsRKdOnfDXX39pI7JEk+zXr1/Hjh07UFBQgP3792P69OkIDw/HnDlztBFZUtF/pydPnsSFCxfw/vvvV1VElTTJPWTIEMyePRudO3eGkZERnJyc0LVrV0yZMkUbkSWaZPf29kZERAT++OMPFBYW4uDBg4iOjsadO3e0EVljpZ1Hnzx5gqysLB2lqv5Ys+iGvtYtrFl0Q1/rFtYs2q9ZAP2tW16mmgXQXd3CziWiKrZgwQJERUXh+++/1+lNmtVhbm6Os2fP4tSpU5g7dy7Gjh2Lw4cP6zpWmdLT0xEQEIDVq1ejbt26uo6jFk9PTwwbNgytWrWCl5cXoqOjYW1tjZUrV+o62gsVFhbCxsYGq1atQps2bTBo0CBMnToV33zzja6jqWXt2rVwc3ND+/btdR3lhQ4fPox58+ZhxYoVSExMRHR0NPbt24fQ0FBdR3uhJUuWwNnZGc2bN4exsTE++eQTDB8+HAYGLEeIqgt9q1tYs2ifvtYtrFl0Q1/rFtYs6pPrOgCpp27dujA0NERaWprS9LS0NNjZ2alcxs7OTq32VUWT7NVBRXKHhYVhwYIFOHToEF599dWqjKmSptkNDAzQtGlTAECrVq1w+fJlzJ8/H127dq3KuErUzX7t2jUkJyfDz89PmlZYWAgAkMvlSEpKgpOTU9WGRuW8z42MjNC6dWtcvXq1KiKWSpPs9vb2MDIygqGhoTTN1dUVqampyM3NhbGxcZVmLlaR/f706VNERUVh9uzZVRlRJU1yT58+HQEBAdI3lm5ubnj69ClGjRqFqVOnaq3o0SS7tbU1du3ahezsbPz9999wcHDApEmT0KRJE21E1lhp51ELCwuYmprqKFX1x5pFN/S1bmHNov2aBdDfuoU1i/ZrFkB/65aXqWYBdFe3sNtNzxgbG6NNmzaIjY2VphUWFiI2Nhaenp4ql/H09FRqDwAHDx4stX1V0SR7daBp7kWLFiE0NBQHDhxA27ZttRG1hMra54WFhcjJyamKiKVSN3vz5s1x/vx5nD17Vvp566230K1bN5w9exYNGjSolrlVKSgowPnz52Fvb19VMVXSJPtrr72Gq1evSkUxAPz++++wt7fXWpEGVGy/b9++HTk5OXj33XerOmYJmuTOzMwsUYgVF8pCiKoL+5yK7HMTExPUq1cP+fn52LlzJ/z9/as6boVUl/OovmHNohv6WrewZtF+zaJJdlV0UbewZtF+zQLob93yMtUsgA7PpVV6u3CqElFRUUKhUIh169aJS5cuiVGjRgkrKyvpEaABAQFi0qRJUvtff/1VyOVyERYWJi5fvixCQkJ0+lhfdbLn5OSIM2fOiDNnzgh7e3sxfvx4cebMGfHHH39U69wLFiwQxsbGYseOHUqPDU1PT9dqbk2yz5s3T/z000/i2rVr4tKlSyIsLEzI5XKxevXqap/9ebp68oq6uWfNmiViYmLEtWvXREJCghg8eLAwMTERFy9erPbZU1JShLm5ufjkk09EUlKS+OGHH4SNjY2YM2dOtc9erHPnzmLQoEHajitRN3dISIgwNzcXW7duFdevXxc//fSTcHJyEgMHDqz22Y8fPy527twprl27Jo4ePSq6d+8uGjduLB4+fKjV3Onp6dK5BYCIiIgQZ86cETdv3hRCCDFp0iQREBAgtS9+pO+ECRPE5cuXxfLly3X2uHN9w5pF+zWLJtmrS93CmsVfS2mV6WvdwppFN/S1btHXmkUI/alb2Lmkp5YuXSoaNmwojI2NRfv27cXx48eleV5eXiIwMFCp/XfffSeaNWsmjI2NxSuvvCL27dun5cT/T53sN27cEABK/Hh5eVXr3I6Ojipzh4SEaD23EOplnzp1qmjatKkwMTERtWrVEp6eniIqKkoHqYuo+15/li4LNXVyf/rpp1JbW1tb0bt3b5GYmKiD1EXU3ee//fab6NChg1AoFKJJkyZi7ty5Ij8/X8upi6ib/cqVKwKA+Omnn7ScVJk6ufPy8sTMmTOFk5OTMDExEQ0aNBAff/yxToodIdTLfvjwYeHq6ioUCoWoU6eOCAgIELdu3dJ65ri4OJXH6OKsgYGBJc4zcXFxolWrVsLY2Fg0adJEREZGaj23vmLN4qX94EJ/6xbWLLqhr3ULaxbd0Ne6RR9rFiH0p26RCaHFMfRERERERERERPSvwnsuERERERERERGRxti5REREREREREREGmPnEhERERERERERaYydS0REREREREREpDF2LhERERERERERkcbYuURERERERERERBpj5xIREREREREREWmMnUtERERERERERKQxdi4REREREREREZHG2LlEREREREREREQaY+cSERERERERERFpjJ1LRERERERERESkMXYuERERERERERGRxti5REREREREREREGmPnEhERERERERERaYydS0REREREREREpDF2LhERERERERERkcbYuURERERERERERBpj5xIREREREREREWmMnUtERERERERERKQxdi4REREREREREZHG2LlEREREREREREQaY+cSERERERERERFpjJ1LRKSxrl27QiaT6TpGtdCoUSM0atRIrWW4/4iIiIjKpqrGWrduHWQyGdatW6eTTERUEjuXiF4CycnJkMlkZf48evRI1zE11qhRI6VtMTQ0RN26ddGrVy/s3r1bZ7lmzpwJmUyGw4cP6yxDeRVnffanRo0aaNmyJaZOnYonT55U+DWCgoIgk8mQnJxc8cBERERUbqpqQSMjI9SrVw8DBw7E6dOndR2RiPScXNcBiEh7nJyc8O6776qcZ2JiouU0lcvQ0BDTpk0DAOTm5uLKlSvYs2cPDh48iLCwMIwbN65KXz82NlbtZTZs2IDMzMwqSKO5/v37o2XLlgCAtLQ07N+/H/PmzcMPP/yAkydPQqFQ6DghERERaerZWvDp06dISEjA9u3bsWvXLhw6dAhdunTRcUIi0lfsXCJ6iTRt2hQzZ87UdYwqIZfLS2zbTz/9BB8fH8yYMQMfffQRatSoUWWv7+TkpPYyDRs2rIIkFTNgwAAMHjxY+j07OxsdO3bEuXPnsGXLFgwfPlyH6YiIiKgiVNWCCxYswOTJkzF9+nQcOXJEN8GISO/xsjgikiQkJOCTTz5By5YtYWlpCVNTU7i5uWHBggXIy8sr1zoKCwuxZs0atG/fHrVr14apqSnq168PPz8/lZeHHT16FH5+fqhbty4UCgWcnZ0xbdq0ShnR06tXL7i4uCAzMxMXL16Upu/duxfdunWTttHd3R0RERHIz88vsY64uDi8+eabcHBwgEKhgK2tLV5//XWsWrVKqd3z9wPo2rUrZs2aBQDo1q2bNAT9+TbP3nNp48aNkMlkmD17tsrtSUxMhEwmw9ChQ5Wm3717F5999hmaNm0KhUKBunXron///rhw4UK591VpTExMpNdLSEhQmnf79m2EhISgY8eOsLGxgUKhQKNGjfDxxx/j7t27Sm0bNWqE9evXAwAaN24s7Y+uXbsqtbtx4wbef/99NGzYEAqFAvb29ggKCsLNmzcrvC1ERERU0ogRIwCUPM/n5uYiIiICHh4eMDMzg7m5OV5//XXs2bNH5Xpyc3Px5Zdfol27djA3N0fNmjXRokULjB07Fg8fPpTaxcXF4b333oOLiwtq1qyJmjVrom3btiVqKyLSLxy5RESS1atXY+/evejSpQt69+6NzMxMHD58GJMnT8apU6ewc+fOF65j8uTJWLRoEZycnDBkyBCYm5vj1q1bOHbsGA4dOqTUmfD1118jODgYVlZW8PPzg42NDU6fPo25c+ciLi4OcXFxMDY2rpRtK+7EiYiIwLhx41C7dm0MGTIEZmZm2LNnD8aNG4dffvkF0dHRUtt9+/bBz88PVlZW8Pf3h729Pe7du4dz585h48aNGDVqVKmvFxQUBAA4cuQIAgMDpU4lKyurUpd5++238dFHH2Hz5s2YMWNGifkbN24EAAQEBEjTrl27hq5du+Kvv/5Cr1690LdvX9y9exc7d+5ETEwMYmNj0aFDB3V2VankcuVTxtGjRxEeHo4ePXqgQ4cOMDIywpkzZ/D1118jJiYGiYmJsLS0BAB8+umnWLduHc6dO4cxY8ZI++HZzrYTJ07A29sbT58+RZ8+feDs7Izk5GRs3rwZP/74I+Lj49GkSZNK2RYiIiJS9ux5PicnBz4+Pjh8+DBatWqFESNGIC8vD/v27YO/vz+WLl2KTz75RGqflZWFN954A7/++iucnZ0xfPhwKBQK/PHHH1i5ciWGDRuGWrVqAQAWLlyIq1evomPHjujXrx8ePXqEAwcO4IMPPkBSUhLCw8O1vu1EVAkEEf3r3bhxQwAQTk5OIiQkpMRPfHy8EEKImzdvivz8fKVlCwsLxXvvvScAiGPHjinN8/LyEs8fRmrXri0cHBzE06dPS+T4+++/pf+/ePGikMvlwt3dXdy/f1+p3fz58wUAERYWVq7tc3R0FAqFosT0Q4cOCZlMJszMzERmZqa4evWqkMvlwsbGRqSkpEjtsrOzRefOnQUAsWHDBmn622+/LQCIs2fPllj385kdHR2Fo6Oj0rSQkBABQMTFxanMrWr/vfvuuwKAOHHihNL0/Px8YWtrK+zs7JT+Rp06dRKGhobiwIEDSu2TkpKEubm5cHNzU/nazyvOunXrVqXpWVlZwt3dXQAQ27dvV5qXlpYm0tPTS6xr/fr1AoCYM2eO0vTAwEABQNy4caPEMrm5uaJRo0bC3NxcJCYmKs375ZdfhKGhoejTp0+5toWIiIiUFdeC3t7eJebNmzdPABC+vr7StClTpggAYvr06aKwsFCa/uTJE9G2bVthbGwsbt26JU0fN26cACACAgJK1JKPHj1SqheuX79eIkNeXp544403hKGhobh586bSPFU1VmRkpAAgIiMjy7X9RFT1eFkc0Uvk2rVrmDVrVomf48ePAyi6B5ChoaHSMjKZDMHBwQCAQ4cOlet1jI2NS6wHAGrXri39/8qVK5Gfn4+lS5eiTp06Su0mTpwIa2trbN26tdzblp+fj5kzZ2LmzJmYOnUqBgwYAB8fHwghEBoaClNTU2zZsgX5+fkYN24cGjRoIC2rUCiwcOFCAFD5SFtTU9MS057PXFmKRyVt2rRJafpPP/2EtLQ0DB48WNq3Z86cwW+//YbAwEB4e3srtW/WrBlGjhyJ8+fPq3V53I4dO6T9+PHHH8PFxQXnzp1Dv3798Pbbbyu1tbGxQc2aNVVug4WFRbnfLwDwww8/IDk5GRMmTEDr1q2V5nXu3Bn+/v7Yv39/pTy1joiI6GV19epV6Tw/YcIEdO/eHVOmTIGtrS2++OILAEW3OPj666/h5OSEWbNmKV3Cb25ujhkzZiA3NxfR0dEAimqwVatWwdLSEkuWLClRA1paWirVC40bNy6RSy6X48MPP0RBQQHi4uKqYtOJqIrxsjiil4i3tzcOHDhQ6vzc3FwsW7YMUVFRuHLlCjIyMiCEkObfvn37ha8xePBgrFixAi1btsTgwYPRrVs3eHp6luigKe7QKr5063lGRka4cuVKeTcNBQUF0j2ODAwMUKtWLXTv3h3BwcF46623ABR1xgAocZ8fAPD09ISJiQnOnj2rtC3R0dHo2LEjhgwZgh49euD1119H3bp1y51LXT169IC9vT2ioqIQEREhDVEv7mx69pK44n2Ylpam8kbtxfvvypUr0hPgXmTnzp0lLn/8z3/+g23btikVl8Wio6OxcuVKJCYm4uHDhygoKJDmlef9Uqx4W5KSklRuS2pqKgoLC/H777+jbdu25V4vERER/b/iLxqfZWdnh19++QVNmzYFUHQufvjwIRwcHEq0BYB79+4BUK4z0tPT0bNnT+nSt7Kkp6cjLCwMu3btwrVr1/D06VOl+erUD0RUfbBziYgkAwYMwN69e9GsWTMMGjQINjY2MDIywqNHj7BkyRLk5OS8cB1LlixB48aNERkZiTlz5mDOnDkwMTHBwIEDER4eLnXMPHjwAAAwd+7cSsmuUCiQnZ1dZpviUS+2trYl5slkMtja2uLWrVvStP/85z/YtWsXIiIi8M0332D58uWQyWTo1q0bwsPD0apVq0rJ/ixDQ0MMGTIE4eHhiImJga+vLzIyMrBr1y60aNECHh4eUtvifbhv3z7s27ev1HU+X7SVZevWrRg8eDDy8/ORlJSE8ePHY/v27XBxcUFoaKhS2/DwcIwfPx7W1tbo1asX6tevL3UiLl68uFzvl+e3ZfPmzWW2U2dbiIiISNmzXzTeu3cP69evx+eff4633noLJ0+eRM2aNaVz8sWLF5UeiPK84nPy48ePAQD16tV74evn5uaia9euSExMROvWrREQEIA6depALpcjOTkZ69evV6t+IKLqg51LRAQAOHXqFPbu3Qtvb2/s27dPaUjz8ePHsWTJknKtRy6XY/z48Rg/fjxu376NI0eOIDIyEhs2bEBqaipiYmIAABYWFgCKOnzMzc0rf4NUKH7NtLQ0ODo6Ks0TQiAtLU1qU8zf3x/+/v5IT0/Hr7/+iujoaKxduxY+Pj64cuVKmTfo1lRAQADCw8OxadMm+Pr6YufOncjMzFQatfTs9jx/U83KIJfL8corr+D777+Hm5sb5s6di379+kmdW/n5+QgNDYW9vT3Onj0LGxsbaVkhBBYtWqTW6xVvy969e9GnT5/K2xAiIiJSydraGuPHj8fjx48xZ84cTJs2DYsXL5bOyf3798eOHTteuJ7iWujZL+hKs3v3biQmJmLEiBFYs2aN0ryoqCjpybJEpH94zyUiAlA0TBoAfH19S1wr/8svv2i0TgcHB7zzzjs4cOAAmjZtikOHDiErKwsApCeYFV8OpQ3F9/I5fPhwiXknTpxAdnZ2qaORzM3N4ePjg1WrViEoKAhpaWk4ceJEma9XvB+fvVSsPNzd3eHm5obdu3cjPT0dmzZtgkwmw9ChQ5XaFe/D+Ph4tdavDhMTE4SFhUEIgUmTJknT79+/j8ePH8PT01OpYwkATp8+Lf2dn1XW/tDGthAREVFJU6ZMgYODA1asWIHk5GS4urrCwsICp0+fRl5e3guXd3FxgYWFBU6dOoWHDx+W2ba43vT39y8xT9N6k4iqB3YuEREASCN5jh07pjT94sWLmD9/frnWkZOTg99++63E9KdPnyIjIwNGRkYwMCg67Hz88ceQy+UYPXo0UlJSSizz6NEj6R5JlWXIkCGQy+WIiIhQup4/NzcXn3/+OQAgKChImn706FGVHSF3794FUNTxUpbiG5j/+eefamcNCAhAVlYWvvrqK/z888/w8vJSugk5ALRv3x4dOnTA1q1bsW3bthLrKCwsxJEjR9R+7ef5+/vDw8MDBw8elAo/GxsbmJqaIjExEZmZmVLbhw8fYvTo0SrXU9b+8Pf3R8OGDREREYGjR4+WmJ+Xl1fivUlEREQVZ2pqis8//xx5eXkIDQ2FXC7HRx99hJs3b2L8+PEqO5guXLgg1UNyuRwffPABHj9+jDFjxpSonR4/foyMjAwApdebR44cwerVq6ti84hIS3hZHBEBKOqoaN++Pb777jvcuXMHHTt2REpKCvbs2QNfX99yDYvOysrCa6+9hmbNmqFNmzZo2LAhMjIy8MMPPyA1NRXjx4+HQqEAALRs2RIrVqzARx99BBcXF/Tu3RtOTk5IT0/H9evXceTIEQQFBeGbb76ptG10cnLCwoULMW7cOLz66qsYOHAgzMzMsHfvXiQlJcHf3x/vvvuu1P6///0vbt++jc6dO6NRo0aQyWQ4duwYTp48iY4dO6Jz585lvl63bt0gk8kwZcoUXLx4EZaWlrCysirXJWxDhgzBpEmTMGvWLBQWFpa4JK7Y1q1b0a1bNwwePBiLFy+Gh4cHTE1NkZKSgvj4eNy7d++F96Iqj5kzZ+Ktt97CjBkzEBcXBwMDA3z88ccIDw+Hu7s7/Pz88OTJE/z4449wdHSEg4NDiXV0794dYWFhGDVqFPr37w8zMzM4OjoiICAACoUCO3bswJtvvgkvLy90794dbm5ukMlkuHnzJn755RfUqVNHrZu8ExERUfmMGjUKCxcuxIYNGzBlyhTMmjULiYmJ+Oqrr7Bv3z506dIFNjY2uHXrFs6fP49z584hPj5eGr08e/ZsHD9+HBs3bsTx48fx5ptvQqFQ4Pr16zhw4ACOHTuGVq1awc/PD40aNcKiRYtw4cIFtGzZEklJSfjhhx/Qr1+/ctWbRFRNCSL617tx44YAILy9vctsd/fuXfHee+8JBwcHYWJiItzc3MTy5cvF9evXBQARGBio1N7Ly0s8exjJzc0VCxcuFL169RL169cXxsbGwtbWVnTp0kVs2bJFFBYWlnjNkydPisGDBwsHBwdhZGQk6tatKzw8PMSkSZPE5cuXy7V9jo6OQqFQlKutEELs3r1beHl5CXNzc6FQKISbm5sIDw8XeXl5Su2ioqLEwIEDhZOTk6hRo4awtLQU7u7uYuHChSI9Pb1EBkdHxxKvtW7dOuHm5iYUCoUAoNTm+f33vJ49ewoAwsTERDx+/LjUdg8ePBDTpk0TLVu2FKampqJmzZrC2dlZDBkyRERHR5drn4SEhAgAYuvWraW2adu2rQAgYmNjhRBFf++5c+cKZ2dnoVAoRMOGDcW4ceNEenp6qftj0aJFwtnZWRgZGQkAwsvLS2n+X3/9JcaMGSOt08LCQri6uor3339fel0iIiJST3lqwaVLlwoAIiAgQAghRH5+vli5cqV47bXXhIWFhXSu9/HxEV9//bXIyMhQWj47O1uEhYWJVq1aSfVIixYtxLhx48TDhw+ldtevXxf9+/cX1tbWokaNGqJdu3YiKipKxMXFCQAiJCREab2qaorIyEgBQERGRlZktxBRJZIJ8cxzxomIiIiIiIiIiNTAey4REREREREREZHG2LlEREREREREREQaY+cSERERERERERFpjJ1LRERERERERESkMXYuERERERERERGRxti5REREREREREREGmPnEhERERERERERaYydS0REREREREREpDF2LhERERERERERkcbYuURERERERERERBpj5xIREREREREREWmMnUtERERERERERKQxdi4REREREREREZHG/g+9sBOpyjoAdQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1200x1100 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-----------------------------------------------------------------------------------------\n",
      "6/7: Starting XGBClassifier Random Search - May 30, 2024 09:19 AM UTC\n",
      "-----------------------------------------------------------------------------------------\n",
      "\n",
      "Fitting 5 folds for each of 10 candidates, totalling 50 fits\n",
      "[CV 1/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=1, xgb_class__learning_rate=0.1, xgb_class__max_depth=5, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=0.965 total time=   0.1s\n",
      "[CV 2/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=1, xgb_class__learning_rate=0.1, xgb_class__max_depth=5, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=0.906 total time=   0.1s\n",
      "[CV 3/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=1, xgb_class__learning_rate=0.1, xgb_class__max_depth=5, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=1.000 total time=   0.1s\n",
      "[CV 4/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=1, xgb_class__learning_rate=0.1, xgb_class__max_depth=5, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=0.976 total time=   0.1s\n",
      "[CV 5/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=1, xgb_class__learning_rate=0.1, xgb_class__max_depth=5, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=0.953 total time=   0.1s\n",
      "[CV 1/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=0, xgb_class__learning_rate=0.5, xgb_class__max_depth=5, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.965 total time=   0.1s\n",
      "[CV 2/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=0, xgb_class__learning_rate=0.5, xgb_class__max_depth=5, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.941 total time=   0.1s\n",
      "[CV 3/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=0, xgb_class__learning_rate=0.5, xgb_class__max_depth=5, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=1.000 total time=   0.2s\n",
      "[CV 4/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=0, xgb_class__learning_rate=0.5, xgb_class__max_depth=5, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.965 total time=   0.2s\n",
      "[CV 5/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=0, xgb_class__learning_rate=0.5, xgb_class__max_depth=5, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.965 total time=   0.1s\n",
      "[CV 1/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=5, xgb_class__learning_rate=0.1, xgb_class__max_depth=7, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.7;, score=0.953 total time=   0.1s\n",
      "[CV 2/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=5, xgb_class__learning_rate=0.1, xgb_class__max_depth=7, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.7;, score=0.906 total time=   0.1s\n",
      "[CV 3/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=5, xgb_class__learning_rate=0.1, xgb_class__max_depth=7, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.7;, score=1.000 total time=   0.1s\n",
      "[CV 4/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=5, xgb_class__learning_rate=0.1, xgb_class__max_depth=7, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.7;, score=0.965 total time=   0.1s\n",
      "[CV 5/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=5, xgb_class__learning_rate=0.1, xgb_class__max_depth=7, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.7;, score=0.941 total time=   0.1s\n",
      "[CV 1/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=1, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=0.953 total time=   0.1s\n",
      "[CV 2/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=1, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=0.929 total time=   0.1s\n",
      "[CV 3/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=1, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=1.000 total time=   0.1s\n",
      "[CV 4/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=1, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=0.965 total time=   0.1s\n",
      "[CV 5/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=1, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=0.953 total time=   0.1s\n",
      "[CV 1/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=10, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=0.977 total time=   0.1s\n",
      "[CV 2/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=10, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=0.929 total time=   0.1s\n",
      "[CV 3/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=10, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=1.000 total time=   0.1s\n",
      "[CV 4/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=10, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=0.953 total time=   0.1s\n",
      "[CV 5/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=10, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=0.941 total time=   0.1s\n",
      "[CV 1/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=5, xgb_class__learning_rate=0.1, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.965 total time=   0.1s\n",
      "[CV 2/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=5, xgb_class__learning_rate=0.1, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.906 total time=   0.1s\n",
      "[CV 3/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=5, xgb_class__learning_rate=0.1, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=1.000 total time=   0.1s\n",
      "[CV 4/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=5, xgb_class__learning_rate=0.1, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.965 total time=   0.1s\n",
      "[CV 5/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=5, xgb_class__learning_rate=0.1, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.941 total time=   0.1s\n",
      "[CV 1/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=10, xgb_class__learning_rate=0.1, xgb_class__max_depth=3, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.942 total time=   0.1s\n",
      "[CV 2/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=10, xgb_class__learning_rate=0.1, xgb_class__max_depth=3, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.906 total time=   0.1s\n",
      "[CV 3/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=10, xgb_class__learning_rate=0.1, xgb_class__max_depth=3, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=1.000 total time=   0.1s\n",
      "[CV 4/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=10, xgb_class__learning_rate=0.1, xgb_class__max_depth=3, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.965 total time=   0.1s\n",
      "[CV 5/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=10, xgb_class__learning_rate=0.1, xgb_class__max_depth=3, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.929 total time=   0.1s\n",
      "[CV 1/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=10, xgb_class__learning_rate=0.1, xgb_class__max_depth=5, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.953 total time=   0.1s\n",
      "[CV 2/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=10, xgb_class__learning_rate=0.1, xgb_class__max_depth=5, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.906 total time=   0.1s\n",
      "[CV 3/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=10, xgb_class__learning_rate=0.1, xgb_class__max_depth=5, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=1.000 total time=   0.1s\n",
      "[CV 4/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=10, xgb_class__learning_rate=0.1, xgb_class__max_depth=5, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.965 total time=   0.1s\n",
      "[CV 5/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=10, xgb_class__learning_rate=0.1, xgb_class__max_depth=5, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.929 total time=   0.1s\n",
      "[CV 1/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=10, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.930 total time=   0.1s\n",
      "[CV 2/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=10, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.918 total time=   0.1s\n",
      "[CV 3/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=10, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=1.000 total time=   0.2s\n",
      "[CV 4/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=10, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.965 total time=   0.1s\n",
      "[CV 5/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=10, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.953 total time=   0.1s\n",
      "[CV 1/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=5, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.942 total time=   0.1s\n",
      "[CV 2/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=5, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.929 total time=   0.1s\n",
      "[CV 3/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=5, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=1.000 total time=   0.2s\n",
      "[CV 4/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=5, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.976 total time=   0.1s\n",
      "[CV 5/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=5, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.953 total time=   0.1s\n",
      "\n",
      "Total Time: 5.5002 seconds\n",
      "Average Fit Time: 0.1100 seconds\n",
      "Inference Time: 0.0026\n",
      "Best CV Accuracy Score: 0.9671\n",
      "Train Accuracy Score: 1.0000\n",
      "Test Accuracy Score: 0.9580\n",
      "Overfit: Yes\n",
      "Overfit Difference: 0.0420\n",
      "Best Parameters: {'xgb_class__subsample': 0.8, 'xgb_class__objective': 'binary:logistic', 'xgb_class__n_estimators': 200, 'xgb_class__max_depth': 5, 'xgb_class__learning_rate': 0.5, 'xgb_class__gamma': 0, 'xgb_class__colsample_bytree': 0.7}\n",
      "\n",
      "XGBClassifier Binary Classification Report\n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "      Benign     0.9770    0.9551    0.9659        89\n",
      "   Malignant     0.9286    0.9630    0.9455        54\n",
      "\n",
      "    accuracy                         0.9580       143\n",
      "   macro avg     0.9528    0.9590    0.9557       143\n",
      "weighted avg     0.9587    0.9580    0.9582       143\n",
      "\n",
      "ROC AUC: 0.9952\n",
      "\n",
      "               Predicted:0         1         \n",
      "Actual: 0                85        4         \n",
      "Actual: 1                2         52        \n",
      "\n",
      "True Positive Rate / Sensitivity: 0.963\n",
      "True Negative Rate / Specificity: 0.9551\n",
      "False Positive Rate / Fall-out: 0.0449\n",
      "False Negative Rate / Miss Rate: 0.037\n",
      "\n",
      "Positive Class: Malignant (1)\n",
      "Threshold: 0.5\n"
     ]
    },
    {
     "data": {
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7d28jKirKMAzDuHDhgtG5c2fzC/b+/fsz3J9p6d+/v/kleNiwYcbFixfNuv/3v/9lmLy61XkqMzJznA4cONAss3fv3lTb9vHxMapVq2ZeZxiGYe6LhIQE83irUKGCsXz5cvO1u3z5svHZZ5+ZP4C98cYbqbadnKCwWCzGmDFjzNc4KirKePXVV20SVbebXEpOXEgyunbtavP6RUdHG998843x7LPP2qxzqx8Fk50+fdp8Xm3atDG2b99uHr9RUVHGsGHDzGTF0qVLbdZNSEgwqlSpYl7DLViwwLhx44ZhGIbx119/GbVq1bL5cn83kkuXL182Eysp90Fmr6E++OADcxs9evQwzpw5Y9Y7ZcoU87nfvH8N479jMvl17dWrl3H27FnDMKyfH6NHjzZj69u3b6r1s+Ja0svLy3B1dTXatWtnJtyvXr1qzJgxw0y0tG7dOt31syK5dPP+yOj7iWFknFz68ccfDScnJ8PFxcUYNGiQceTIESMpKclISkoy9u3bZ7Rr186QrMn55M/AZA8//LAhyWjcuLGxZ88ec35cXJzx559/GiNHjkzz/ZXdSC4B94m33nrLPEGcOnXK7npeeeUV80SZfJJJ6cSJE+ZFYM+ePW2WpbyIKVWqlHH16tVU6y9btswsc+LEiVTL72ZyaevWrYZk/cUr+QIgMzK6SHH0/rqVm78Ide/e3ZBkDB8+3CyTlJRkFClSxJD++7Uzo+TSrbz77ruGJKNBgwaplt1uckmS8f7776db7lYX7QkJCUaNGjXM5N/Vq1eNf//91yhQoIB5MQkg50r5pf3mX5tvfqRsgXI7yaXkL9c9evS4rdgyk1zasmWLGdOsWbPSLJOcfAoODjbi4uLM+ZcvXzbPT+m1eE65fzJKLjk7Oxs7d+68reeX0sKFCw1JxsMPP5xqWcpzcKNGjYykpKRUZWrVqmWWSf6RJKWEhASjaNGihiRj9OjRtxXbyZMnzS/ZQ4cOTbNMv379DMnaWiD5i3uy7EguxcTEGPnz5zck649ZyS3AUm47NDTUTGzebO7cuea1SHR0dJpltm/fblgsFsPNzc1M3BmGYZw6dcrcP8OGDUtz3Q4dOmSYKEkvubR//37zh6BBgwalWXdaMptcSk6+Pvfcc+mWmTx5siHJePTRR23mf/311+Y21qxZk2q9K1eumF/471ZyKfl6S5IxZcoUc35mrqGuXr1q5MqVy5Csre7S8v7775v1bN++3WZZymPyhRdeSHP95O8mLi4ut/3dJDPXksnfB9Jq8Th79myzzG+//Zbm+vdScikxMdEoXrx4hp/lhmEYLVq0MCQZr7/+ujkvKirKfK43f/7caxhzCbhPnD9/3vw7V65cdtVhGIYWLFggSXrllVeUN2/eVGUKFiyoV155RZI0f/78dOvq37+/PD09U81v1qyZ3NzcJP13Z7jsEhAQIEnmnfPu1P24v7p27SpJ+uyzz8yxE9atW6ejR4+qZMmSql69+h1v48knn5Qkbd68OdN99dMTGBiol19+2e71nZ2d9dVXXykwMFB///23Xn/9dXXt2lWnTp1SoUKFNHv27DuKD8CDIyoqKsPHv//+a1e9yeeeyMjILIzW6uuvv5ZkPdd07949zTKjR4+WJP37779avXq1Of/HH39UbGysJOnNN99Mc93+/fvLy8vrlnE0bdpUFStWvK3YU0o+bxw+fDjD/TR48OA0xz9s0qSJ+ffQoUNTLXd2dlaDBg0kWcdsuh2LFy9WQkKCPDw8NGTIkDTLvPXWW3J3d9eNGzcyNcZQVomOjtbatWtVv359nT59WpL0+uuvm+PwpNSrV690BxRPHvPr1VdfTXMcTkmqXLmyypYtq+vXr2vdunXm/EWLFikhIUGenp4aMGBAmuumNQ5ZZnz22WdKSkpSUFCQOaZNVrl27Zq++uorSdbjKj0vvviiJOn333+3GUMz+ZquRo0a5rGVkpeXlwYNGpSVIUuyjm116NAhjRw50rwzYK5cudSpU6dUZTO6hlq9erUuXLggKf3X57XXXlO+fPkkydxXaRk+fHia8wcOHChPT08lJCSkO95nejJ7LfnWW2+lebx36dLFHHs2o+vve8XPP/+sgwcPKjg4ON3Pcum/4zHlOGO+vr7mPjhz5szdDfQOkVwCcpAjR46YJ5qGDRumWy75lrfnz5/XkSNH0ixTrVq1NOe7uLgod+7ckmRuK7s8/PDDKlWqlG7cuKFq1app/Pjx2r17t90JkPtxf4WFhalUqVI6duyYeSvVzA7knVJUVJRGjBihsLAwBQUFycXFxRy4sEyZMpKsgzVevHjxjuJ97LHHzOSavQoXLqyPP/5YkvTxxx9r2bJlcnZ21hdffKHAwMA7qhvAg8OwtthP95He5/etPPHEE7JYLFq2bJmaNWumefPmmYmAO7V9+3ZJUr169dL8giVJpUuXVoECBWzKS9LOnTslWT8jixYtmua6vr6+qly58i3jqFGjxi3LXLp0Se+++67q1KmjPHnyyM3NzTxvpExg3XxTjZSqVq2a5vyQkBBJ1i/ZDz30UIZlbve8lLzPHnvsMfn5+aVZJjAwUFWqVLEpf7ekHCg4MDBQDRs2NAePfv7559NNFKb3GiUmJmrLli2SrEmGvHnzpvvYv3+/JOtNOZIlP98qVaqku39KlChhHoO349dff5VkvY7y8PC47fUzsmPHDnPA58aNG6f7nMuWLWuuk9bzrl+/frrbyGjZ7Ug5qL+Li4uKFy+u8PBwxcfHK3fu3Pr222/TvJ7J6BoqOf5ChQqpRIkSaZZxdnY2n0N6x3WhQoXMOxXezM/Pz/z8SGv9O72WdHFxUa1atdJc5uTkZN78526/J7PCpk2bJEkxMTHKnz9/usfjSy+9JMn2WPT09DQTnE2bNtXw4cO1detWXb9+PfufyC24ODoAAJkTFBRk/n3hwgXlz5//tus4e/as+XdGFwEp70J39uzZNC9KfX19013fxcX60XLjxo3bjvFOODs7a/78+WrdurWOHDmiIUOGaMiQIfLy8lL16tXVpk0bderUKVO/0kr37/7q0qWLBg8erIiICFWtWlVLliyRs7Oz+WvIrWzevFlPPPGEoqOjzXnJd7OwWCxKTEw0f+G/cuWKgoOD7Y41T548dq+bUtu2bdW2bVvzl7MBAwaodu3aWVI3AGSkZs2aGj9+vN566y2tXLlSK1eulGQ9NzRs2FAvvviizd2tbkfyeehWX9wLFiyoU6dO2Zy3zp07J0m3vF7ITFLgVp/VBw4cUIMGDWwSR15eXgoICDCTYsmtQq5cuZJuPemdK5PPk3fjXHo7+zhl+bslOUkmybyzV8WKFdWxY8cMj6P0XqMLFy4oPj5eUuYTb1evXjX/vt1j8HYkt2ILDQ29rfUyI2WCN727+t7sdp/3re7anFne3t5mqzMnJyf5+PjooYceUoMGDdS1a1eb7wApZfS+zKrj+lbrJy+/ef2suJZMvjPm7W77XpR8PN64cSNTx2NcXJzN/7Nnz1aLFi30+++/a/To0Ro9erTc3Nz02GOPqWXLlurWrZvdPVuyEi2XgPtEyl9Wdu3a5cBI7m2PPvqo9u3bp8WLF6tHjx565JFHFBcXpzVr1ui1115TqVKlsr27XnZ74YUX5OzsrKVLl2rmzJmKi4tT06ZNzabPGUlISFCHDh0UHR2tChUq6IcfflBsbKwuXbqkqKgoRUZGmr+ASrrj2z47Ozvf0frJjh49qjVr1pj/b9q06Y677AFAZg0cOFBHjhzRlClT1KpVK+XJk0cnT57UnDlzVL9+fbVr1y7bf3BJllY3s9t1q8/qLl266OTJkypSpIgWLlyo8+fP68qVKzp79qwiIyNtkg53et540EVGRpqPY8eOaceOHZo9e/YtE5TpvUYpz4UrVqy4ZQs+wzDs7uZ2u7Li2ExPyucdFxeXqeed3BImuw0YMMB8zU+fPq0DBw5o5cqVGjhwYLqJJSnrrqGyWnZfS94Pko/HatWqZepYvHmfFC5cWDt37tTKlSvVp08fVa5cWUlJSdq0aZMGDRqkYsWK6aeffnLEU7NBcgm4T6RsEr906VK76kj5C0dGzdJTLsuqliWZlfzLY3JT5rTExMRkWIebm5vatGmjWbNmac+ePTp37pxmzpypXLly6cSJE2n2W0/L/bC/0pIvXz41bdpUcXFxGjZsmKTMd4nbvHmzjh07JmdnZ3333Xdq1qxZql+K78a4Inci+SImJiZGJUqUkLu7uzZu3GiOQwIA2SF//vx64403tHTpUkVFRemPP/4wx9ZYtGiRZsyYcdt1Jp9TMjoHpVye8hyU3OX6Vl30bre1yc1OnDhhdm+aN2+enn766VS/oN9r542U7mQf3w+SuyNJtl1tMiv5+d7qOLHnOEoey9KeuDJbt731Z+Z53+l7527KquM6s697yvWz6lry33//zbDrV1rbvldlxbHu5OSkJk2aaOrUqdq+fbsuXLigL7/8UoULF9bFixf13HPPObyrHMkl4D4REhKitm3bSrIOunfgwIFMr5uc/S5atKh5wZc8Hk9akluABAUFpTtOw92S3Kf8xIkT6ZbZunXrbdUZFBSkl19+WePHj5dkbfmVmQG/74f9lZ7kgb2vX7+u4OBgtWjRIlPrJe/33Llzp9sUOmULoZslJ0Cz81eoESNGaMuWLfLy8tI333xjvs5jxozRxo0bsy0OAEipXLly+vjjj82xcFIOti1l7vMyeZyfdevWKSkpKc0y+/btM79kPfbYY+b8SpUqSbJ+mTl69Gia616+fNkcz8deKc/X6Q36ndF5w9FSjqWU3o9X0dHRNmMz3U9cXV3NsayWL19+2+un3D+XL19Os8zBgwdvmcRIS/JNRlavXp3hj4o3Szn+WHrvn5TjEd3J8045uPnN7oWWIulJjv/kyZPpfmdITEw0n196x/WJEyd0+PDhNJddunTJ/PxI3l7yOpL915LJEhIS9Msvv6S5zDAMbdiwIdW275Y7vb5NPg9ERkZm2RhRvr6+eu6558wB+6OiohzeO4PkEnAfGTNmjHx8fBQXF6c2bdrc8teEixcvqm3btubFksVi0bPPPitJmjVrVpq/Gpw+fVqzZs2SJHXo0CGLn8GtPfroo2YcaSWRzp49aw7efLPkMQXSk/JubekNjJrS/bC/0vPUU09p4MCB6t+/v9577z25urpmar3ku8gk3z3pZidPntT777+f7vrJg32m7GN/N61bt07jxo2TJE2ZMkWlS5fW66+/rieffFKJiYnq2LHjHQ86DgAZyey55+bzTmY+L9u3by/J+gt9ene/TL6TU3BwsM3NJxo3bmxu45133klz3SlTptiMM2OPlHcf+/3331Mtv3TpksaMGXNH27ib2rZtKxcXF127ds38ceJm77zzjuLj4+Xq6mr+0Hc/6dGjhyTphx9+0A8//JBh2ZtvLtK2bVs5OzsrLi5OEydOTHOdUaNG2RVX586d5ezsrPPnz2vEiBGZXi/lwOLpvX+8vb313HPPSZLGjx+v48ePZ1jnzc87+fpv48aNWr9+farycXFxevfddzMdc3Zr1KiR2aUuvW6Os2bNMls2ZnQNm15L8EmTJikuLk4uLi4274s7vZZM6e23304zsf7ZZ5+ZSazk1+puutPr23r16pkDo/ft2/eWLYxSHo+3Knu732/uJpJLwH2kRIkS+vzzz+Xm5qa//vpLFSpU0Pjx43Xo0CGzTGJionbt2qXhw4froYce0pIlS2zq+N///qeAgABduHBBDRs2NJuyS9Zxaho2bKjo6GjlypUr3Vvy3k3Vq1c3B3bs1KmTtm/fLsMwlJSUpPXr16tu3brp/no7f/581ahRQ7NmzdI///xjzk9MTNSqVavM5xMWFpbpu4jd6/srPa6urpowYYImTpyojh07Znq9mjVrytvbW4Zh6JlnnjF/7Ureh3Xr1s1wjIRHHnlEkhQbG6sFCxbc2ZO4hfPnz+uFF15QUlKS2rRpY148S1JERITy5cun48ePm3feAIC7oVWrVuratatWrFhh88XjwoULGjNmjNnyNfnW28mSPy9/+OGHdH8sqlq1qvmlrXfv3vrwww/NZFBkZKReeuklLVy4UJL1C2DKO255e3ubt2D/+OOPNWjQIPMLy6VLlzR+/HiFh4ff8V01S5curcKFC0uytppN2RJq8+bNqlu37j2d5C9QoIBef/11SdK4ceM0YsQI83WMjo7WsGHDzCRCv379MjV+4b3m+eefV8OGDWUYhlq3bq0xY8bYdJe8cuWK1q1bp549e6a6G1+BAgXUs2dPSdZjbOzYsbp06ZIk66DxvXr10hdffGGTZMysYsWKaeDAgZKkCRMmqHv37jp48KC5PDY2Vl9//bVat25ts16JEiXMVkmzZ89OtzXJO++8o/z58+vff/9VWFiYPv/8czP25PgXL16s1q1bp0qutG3b1mz9l3zDkORxc/bu3atmzZqZg+bfizw9Pc2k0rx58/TKK6+YiZ6rV6/q/fff1xtvvCHJmpxJ766R/v7++uyzz/T666+bA3BfunRJ77zzjplU7Nmzp82NA+70WjKZl5eXNm7cqOeee85sGXft2jV99NFHevXVVyVJLVu2TPcuk1kp+fP6r7/+svkukFkuLi6aOXOmXFxctHHjRtWuXVtr1661GYvvn3/+0cyZM/XYY49p+vTp5vxff/1V5cuX15QpU7R3717ze5BhGPr111/NfVGwYEGVL1/+Tp7mnTMA3Hc2btxoFCtWzJBkPtzc3IxcuXIZTk5O5jyLxWJ06NDBuH79us3669evN/z9/c1y3t7ehre3t/l/QECA8fPPP6fa7pEjR8wyR44cSTe+0NBQQ5IRERGRalmdOnUMScaIESPSXX/lypWGq6uruS0vLy/Dw8PDkGQUL17cmDdvnrkspYiICJt94u7ubgQFBdnsk/z58xt79+61WW/dunVp1ncv7K9bSa7/dtdNfh06deqUatmMGTNs9qOPj4+5/4ODg41ly5Zl+LwaNGhgLvf19TVCQ0ON0NBQY8qUKWaZTp06pbv9lDLahy1atDAkGYUKFTIuXLiQat3Vq1cbFovFkGR89NFHmdgrAB40I0aMyPDzPaWUnze3c/5Knp/88PPzM/z8/GzmPf3000ZiYqLNegcOHDA/W52cnIyQkBDz8/LEiRNmuejoaJttuLi4GIGBgebnmyRjwIABaT6nGzduGE8//bRZzsnJyQgMDDScnZ0NScYLL7xgvPjii4Yk4+WXX061fmbPT8uXLzdcXFxsztteXl7mOXPNmjXmsnXr1tmse6tzsGH8d34PDQ1Nt0zya12nTp0MY01LfHy88cwzz6TaTymvH9K6njKMzJ/rM3I7x6m9246JiTGaN2+e6lgNCAiwOZZcXFxSrRsXF2c0bNjQLOPs7GxzDA4ePDjD67uMjqOEhASjZ8+eqa47Utbv7++far1u3brZHG+FCxc2QkNDjf79+9uU+/vvv40SJUrYvLa5cuWyuY6TZDRs2DDVNg4fPmwUKlTI5roy+XrQzc3N+Pbbb9M9rjMjed2MronTktlrKMMwjL59+9p8LwgMDLR5r9arV8+IjY1NtV7K99OgQYNs1k/+/Ejeb3FxcanWv5NryZTv9w8//NA8DgIDA22+Hzz66KPGv//+m2rbGX1e2Lvsxo0bRsmSJc1tBwYGmp/XCxcuNMvd6rVZunSp4evra9bj6upqBAUFGe7u7jb7a8yYMeY6KT8jU66T8nX08/NL87tIdqPlEnAfqlGjhvbt26d58+apY8eOKlasmDw8PHTp0iXlypVLNWvW1Jtvvqm9e/fqq6++StUlqk6dOtq7d6/69++v0qVLKykpSYZhqHTp0howYID27t2rWrVqOejZSU2aNNEvv/yi5s2bKzAwUImJiSpUqJCGDBmiHTt22AzSmFKLFi00d+5cdenSRY8++qj8/f0VExMjX19fVa1aVaNHj9Zff/2lUqVK3VY89/r+ymqvvPKKvv/+e9WtW1c+Pj5KSEhQgQIF1Lt3b/3+++8qV65chusvWrRIffv2VYkSJXTjxg0dO3ZMx44dy9KuctOmTdOyZcvk5OSkL774Is1f3hs2bGj+IvrGG29o7969WbZ9AEj2wQcfaPz48XriiSdUvHhxGYahuLg45c+fXy1atNDixYu1cOHCVN0VihcvrnXr1qlFixbKnTu3zp8/b35eJiQkmOX8/f21du1affLJJ6pbt658fX11+fJl5c2bV23bttW6devS7Z7j4uKiBQsWaPbs2apatao8PT2VkJCgKlWqaPbs2Zo7d6752RwQEGD3PmjevLl+/vlnPfnkkwoICFBCQoKCg4PVpUsX7dixQw0aNLC77uzg5uamr7/+WosWLVKzZs0UFBSkS5cuKSgoSM2aNdOSJUvSvJ66n/j5+Wn58uX64Ycf9Oyzz6pw4cKKj4/X1atXVaBAATVu3Fhjx47V/v37U63r4eGhFStWaOrUqapQoYLc3NxkGIZq1aqlBQsWmN3T7eHs7KwPP/xQGzduVMeOHVW4cGHduHFDhmGoTJky6tatmxYvXpxqvWnTpik8PNy8Jjl+/LiOHTtmtq5JVrp0af3xxx+aNWuWGjdurODgYMXGxsowDBUrVkzt2rXTRx99lGZr64ceeki7d+9Wv379VLRoURmGIQ8PDz399NP69ddfMz2epSNNnjxZP/30k9q2bauQkBBdvnxZvr6+qlevnj799FOtXr061WDbNxs/frzmz5+vmjVryjAMubm5qUKFCpo6dapWrlxp02Iy2Z1eSybr2bOnVq1apaZNm8rJyUlOTk4qVaqURo0apc2bN2d4N72s5OLiorVr16p79+4qWrSorly5Yn5epzcWWVpatWqlQ4cOacSIEapatap8fHwUHR0td3d3Pfroo+revbuWLl1qXr9K1vGwFixYoFdffVWVK1c2j2EPDw9VqFBBgwYNume+i1gMIwfc+w8AAACADcMwVLhwYZ08eVJz587VCy+84OiQAAD3KVouAQAAADnQ559/rpMnT8rFxcVmMHAAAG4XySUAAADgAdWhQwctWrTIprtQVFSUxo0bZ97w4MUXX7wvB6oGANw76BYHAAAAPKACAgIUExMjyXr3JVdXV/N/SapVq5a+++47m9u7AwBwu0guAQAAAA+ouXPnasWKFdq1a5fOnj2ry5cvKyAgQBUqVFD79u31wgsv3NcDVQMA7g0klwAAAAAAAGA3xlwCAAAAAACA3UguAQAAAAAAwG4klwAAAAAAAGA3kksAAAAAAACwG8klAAAAAAAA2I3kEgAAAAAAAOxGcgkAAAAAAAB2I7kEAAAAAAAAu5FcAgAAAAAAgN1ILgEAAAAAAMBuJJcAAAAAAABgN5JLAAAAAAAAsBvJJQAAAAAAANiN5BIAAAAAAADs5uLoAOA4SUlJOn36tHx9fWWxWBwdDgAAkiTDMHTp0iXlz59fTk78DvYg41oEAIB7W2avy0gu5WCnT59WoUKFHB0GAABpOnHihAoWLOjoMHAXcS0CAMD94VbXZSSXcjBfX19JkluZTrI4uzk4GuD+d3jNBEeHADwQLl2KVelioeZ5Cg+u5Nf4xIkT8vPzc3A0ALLE7t1SnTrShg1ShQqOjgbAHYqNjVWhQoVueV1GcikHS25+bnF2I7kEZAG+GAFZi25SD77k19jPz4/PUOBB4ePz35T3NfDAuNV1GQMZAAAAAACyhouLFBxsnQLIMXjHAwAAAACyRvny0rlzjo4CQDaj5RIAAAAAAADsRsslAAAAAEDW+OsvqWVL6dtvpbJlUy1OTEzUjRs3HBAYgLS4urrK2dn5jushuQQAAAAAyBrx8dLhw9ZpCoZhKDIyUtHR0Y6JC0C6AgIClDdv3ju6mQrJJQAAAADAXZWcWMqTJ4+8vLy4IyhwDzAMQ1evXtXZs2clSfny5bO7LpJLAAAAAIC7JjEx0UwsBQUFOTocACl4enpKks6ePas8efLY3UWOAb0BAAAAAHdN8hhLXl5eDo4EQFqS35t3Mh4aySUAAAAAQNYoVkxaudI6vQld4YB7U1a8N0kuAQAAAACyhp+f1KSJdYq7Zs6cOQoICMiWbXXu3FmtWrUy/zcMQz169FCuXLlksVi0e/du1a1bV2+88Ua2xJMVjh49asZ+J27eN2m5ed8UKVJE7733nvm/xWLRN998c8fbcTTGXAIAAAAAZI0zZ6RZs6SXX5YyMTjwuXPnFBsbmw2BSX5+fsqdO3emyiYmJqpWrVrKmzevlixZYs6PiYnRI488ohdffFFvv/22OX/x4sWaNm2adu3apWvXrqlw4cKqUaOGevfurYoVK0qyJoS6dOliruPt7a2SJUvqzTffVJs2bWy2v27dOr377rvaunWr4uLiVKRIETVr1kz9+vVTgQIF7mQ33LapU6fKMAzz/5UrV2rOnDlav369HnroIQUHB2vJkiVydXXN8m0fPXpURYsWNf/PlSuXKleurPHjx5v79V53q31z5swZBQYGSvrv+e7atUsVKlQwy9z8GtyLSC4BAAAAALLGmTPSyJFSixa3TC6dO3dOz3fprguXrmZLaLl8vfRFxOxMJZicnZ01Z84cVahQQV9++aU6duwoSerdu7dy5cqlESNGmGUHDx6sSZMmqU+fPho5cqRCQ0N17tw5rVixQkOHDtXKlSvNsn5+ftq/f78k6dKlS4qIiNAzzzyjv/76SyVLlpQkzZo1S6+99po6deqkxYsXq0iRIjp+/Ljmzp2rSZMmafLkyVm5W27J39/f5v/Dhw8rX758ql69ujkvV65cd7SNxMREWSwWOTml3blqzZo1Klu2rE6ePKk+ffqoWbNm2rdvX5qtt27cuHFXEl32utW+yZs37y3ruPk1uBfRLQ4AAAAAkO1iY2N14dJV5Q5rqyJPvnZXH7nD2urCpau31UqqRIkSGjdunHr37q0zZ87o22+/1fz58zV37ly5ublJkrZs2aIJEyZo8uTJmjx5smrVqqXChQurcuXKeuutt7RixQqbOi0Wi/Lmzau8efOqePHiGjNmjJycnPTHH39Ikpk86dOnjz799FPVrVtXRYoUUe3atTV79mwNHz48zVgPHz6sli1bKiQkRD4+Pnrssce0Zs0amzLTp09X8eLF5eHhoZCQED399NPmskWLFqlcuXLy9PRUUFCQGjZsqCtXrkiy7ZLVuXNn9e7dW8ePH5fFYlGRIkUkpe76FR8frwEDBqhAgQLy9vZWtWrVtH79enN5cre+ZcuWqUyZMnJ3d9fx48fTfS2CgoKUN29eValSRRMnTlRUVJS2bt1qdm/7+uuvVadOHXl4eOjLL79UUlKSRo0apYIFC8rd3V0VKlSwSfIl27dvn6pXry4PDw898sgj2rBhg7ksMTFR3bp1U9GiReXp6amSJUtq6tSpacY3cuRI5c6dW35+fnrllVd0/fp1c9mtugym7BaX3EqrYsWKslgsqlu3rrnfU3aLS0pK0tixY83YHn30US1atMhcfvHiRXXs2FG5c+eWp6enihcvroiIiHRjyAq0XAIAAEAqiYmJCg8P1xdffKHIyEjlz59fnTt31ltvvWUO/GkYhkaMGKGPP/5Y0dHRqlGjhmbMmKHixYs7OHoA9xPvXCHyy1Pwrm/nnB3r9O7dW0uXLtULL7ygPXv2aPjw4Xr00UfN5fPmzZOPj49ee+21NNfPaKDkxMREzZ07V5JUqVIlSdLChQt1/fp1DRo0KM110htn6fLly3riiSf09ttvy93dXXPnztVTTz2l/fv3q3Dhwtq+fbv69Omjzz//XNWrV9eFCxf0yy+/SLJ2y+rQoYMmTJig1q1b69KlS/rll1/S7IY1depUPfzww/roo4+0bdu2dG9b36tXL/3999+aP3++8ufPr6VLl6pp06bas2ePeY64evWqxo8fr9mzZysoKEh58uRJd1+l5OnpKUk2CZwhQ4Zo0qRJqlixojw8PDR16lRNmjRJs2bNUsWKFfXpp5+qRYsW+uuvv2zOUQMHDtR7772nMmXKaPLkyXrqqad05MgRBQUFKSkpSQULFtTChQsVFBSkX3/9VT169FC+fPn0zDPPmHWsXbtWHh4eWr9+vY4ePaouXbooKCjIpttkZv3222+qWrWq2VIrOYl5s7Fjx+qLL77QzJkzVbx4cf388896/vnnlTt3btWpU0fDhg3T33//rRUrVig4OFiHDh1SXFzcbcdzO0guAQAAIJXx48drxowZ+uyzz1S2bFlt375dXbp0kb+/v/r06SNJmjBhgt5//3199tlnKlq0qIYNG6YmTZro77//loeHh4OfAQDcOYvFohkzZqh06dIqV66chgwZYrP8wIEDeuihh+Ti8t9X68mTJ9u0MDp16pTZrSkmJkY+Pj6SpLi4OLm6uuqjjz7Sww8/LEk6ePCg/Pz8lC8T41Wl9Oijj9okvUaPHq2lS5dq2bJl6tWrl44fPy5vb281b95cvr6+Cg0NNccsOnPmjBISEtSmTRuFhoZKksqVK5fmdvz9/eXr6ytnZ+d0u3MdP35cEREROn78uPLnzy9JGjBggFauXKmIiAi98847kqzd16ZPn24T961ER0dr9OjR8vHxUdWqVc2EyRtvvGEzbtXEiRM1ePBgtW/fXpL1nLZu3Tq99957mjZtmlmuV69eatu2rSRpxowZWrlypT755BMNGjRIrq6uGjlypFm2aNGi2rx5sxYsWGCTXHJzc9Onn34qLy8vlS1bVqNGjdLAgQM1evTodLv5pSe5y2ZyS620xMfH65133tGaNWsUFhYmSXrooYe0ceNGzZo1S3Xq1NHx48dVsWJFValSRZLMFmZ3E8klAAAApPLrr7+qZcuWevLJJyVZL0znzZun3377TZK11dJ7772nt956Sy1btpQkzZ07VyEhIfrmm2/MC3oAOUxgoNSxo3X6gEhOHBw5ckQnT5685Rf1rl27qkWLFtq6dauef/55mxZAvr6+2rlzpyRry501a9bolVdeUVBQkJ566ikZhmHXbeEvX76s8PBwff/992ayKC4uzuxq1qhRI4WGhuqhhx5S06ZN1bRpU7Vu3VpeXl569NFH1aBBA5UrV05NmjRR48aN9fTTT5uDTN+uPXv2KDExUSVKlLCZHx8fr6CgIPN/Nzc3lS9fPlN1Vq9eXU5OTrpy5Yoeeughff311woJCdHRo0clyUyiSNbulqdPn1aNGjVs6qhRo4Z+//13m3nJyRlJcnFxUZUqVbR3715z3rRp0/Tpp5/q+PHjiouL0/Xr120G2pasiT0vLy+bOi9fvqwTJ06YybqsdOjQIV29elWNGjWymX/9+nUzYfjqq6+qbdu22rlzpxo3bqxWrVrZjJF1N5BcAgAAQCrVq1fXRx99pAMHDqhEiRL6/ffftXHjRnMg2SNHjigyMlINGzY01/H391e1atW0efPmNJNL8fHxio+PN/+/23eIys67UGWF27mTFXDPKlpU+uILR0eRZX799VdNmTJFP/74o8aMGaNu3bppzZo1ZgKoePHi2rhxo80g0gEBAQoICNDJkydT1efk5KRixYqZ/5cvX14//vijxo8fr6eeekolSpRQTEyMzpw5c1utlwYMGKDVq1dr4sSJKlasmDw9PfX000+bXceSk1rr16/Xjz/+qOHDhys8PFzbtm1TQECAVq9erV9//VU//vijPvjgA7355pvaunWrzZ3aMuvy5ctydnbWjh07UnWbS261JVm7t2U2kfb111+rTJkyCgoKSrNroLe3923HeSvz58/XgAEDNGnSJIWFhcnX19e8g58jXb58WZL0/fffp7pzoLu7uySpWbNmOnbsmH744QetXr1aDRo0UM+ePTVx4sS7FhfJJQAAAKQyZMgQxcbGqlSpUnJ2dlZiYqLefvtt845JkZGRkqSQkBCb9UJCQsxlNxs7dqxNF4O7KbvvQpUVbudOVsA969o16eRJqWBB6T7vHnv16lV17txZr776qurVq6eiRYuqXLlymjlzpl599VVJUocOHfTBBx9o+vTpev311+3ajrOzs9m96+mnn9aQIUM0YcIETZkyJVXZ6OjoNJMrmzZtUufOndW6dWtJ1gREcqueZC4uLmrYsKEaNmyoESNGKCAgQD/99JPatGkji8WiGjVqqEaNGho+fLhCQ0O1dOlS9evX77afT8WKFZWYmKizZ8+qVq1at71+WgoVKmR2HbwVPz8/5c+fX5s2bVKdOnXM+Zs2bVLVqlVtym7ZskW1a9eWJCUkJGjHjh3q1auXWb569eo242kdPnw41fZ+//13xcXFmWNBbdmyRT4+PipUqNDtPUnJHGMpMTEx3TIpB0BP+fxuljt3bnXq1EmdOnVSrVq1NHDgQJJLAAAAyF4LFizQl19+qa+++kply5bV7t279cYbbyh//vzq1KmTXXUOHTrU5otKbGysXRffmZHyLlTeuUJuvYKDXbkQpXObFys2NpbkEu5vf/8tVa4s7dgh/f8g1feroUOHyjAMjRs3TpK1e/DEiRM1YMAANWvWTEWKFFFYWJj69++v/v3769ixY2rTpo0KFSqkM2fO6JNPPpHFYrEZd8cwDDMBHxcXp9WrV2vVqlXmGE2FChXSlClT1KtXL8XGxurFF19UkSJFdPLkSc2dO1c+Pj6aNGlSqliLFy+uJUuW6KmnnpLFYtGwYcOUlJRkLv/uu+/0zz//qHbt2goMDNQPP/ygpKQklSxZUlu3btXatWvVuHFj5cmTR1u3btW5c+dUunRpu/ZbiRIl1LFjR7344ovmINvnzp3T2rVrVb58ebO79d00cOBAjRgxQg8//LAqVKigiIgI7d69W19++aVNuWnTpql48eIqXbq0pkyZoosXL6pr166SrPt07ty5WrVqlYoWLarPP/9c27ZtS9Wa6/r16+rWrZveeustHT16VCNGjFCvXr1ue7wlScqTJ488PT21cuVKFSxYUB4eHuZ4Xcl8fX01YMAA9e3bV0lJSapZs6ZiYmK0adMm+fn5qVOnTho+fLgqV66ssmXLKj4+Xt99953dr2dmkVwCAABAKgMHDtSQIUPM7m3lypXTsWPHNHbsWHXq1MkcaDQqKsqm60ZUVFSq8SiSubu7m032s0t23YUqK9hzJyvgQXDlQtQ9t40NGzZo2rRpWr9+vc14Oi+//LKWLFli0z1u4sSJqlq1qmbMmKFPP/1UV69eVUhIiGrXrq3NmzfLz8/PXD82Ntb8zHR3d1doaKhGjRqlwYMHm2Vee+01lShRQhMnTlTr1q0VFxenIkWKqHnz5um2JJo8ebK6du2q6tWrKzg4WIMHD7bpFhwQEKAlS5YoPDxc165dU/HixTVv3jyVLVtWe/fu1c8//6z33ntPsbGxCg0N1aRJk9SsWbPb2mcpRUREaMyYMerfv79OnTql4OBgPf7442revLnddd6OPn36KCYmRv3799fZs2dVpkwZLVu2LNXdTMeNG6dx48Zp9+7dKlasmJYtW6bg4GBJ1td6165devbZZ2WxWNShQwe99tprWrFihU0dDRo0UPHixVW7dm3Fx8erQ4cOCg8PtytuFxcXvf/++xo1apSGDx+uWrVqaf369anKjR49Wrlz59bYsWP1zz//KCAgQJUqVdL//vc/SdYWUEOHDtXRo0fl6empWrVqaf78+XbFlFkWI637CyJHiI2Nlb+/v9zLvSSLc9q3OASQeWc3v+/oEIAHQmxsrAqGBComJsbmghzZKygoSGPGjDG7fkjWbm0RERE6cOCADMNQ/vz5NWDAAPXv31+S9bXLkyeP5syZk6kBvZOvRe7Ga3348GG17/qKijz52n2RXIo9e1JHv5+u+Z/OzHTXD+CetHNnqpZL165d05EjR1S0aFGbO0lmd/dVup4CaUvvPSpl/lxNyyUAAACk8tRTT+ntt99W4cKFVbZsWe3atcv8ZVyy3p77jTfe0JgxY1S8eHEVLVpUw4YNU/78+dWqVSvHBg/gvpA7d259ETE72wbeZ9B84O4huQQAAIBUPvjgAw0bNkyvvfaazp49q/z58+vll182xwWRpEGDBunKlSvq0aOHoqOjVbNmTa1cuTLVr54AkJ7cuXOT8AEeACSXAAAAkIqvr6/ee+89vffee+mWsVgsGjVqlEaNGpV9gQG4t1WqJDHyCpDj3P7w5QAAAAAAAMD/I7kEAAAAAMga+/dLYWHWKYAcg+QSAAAAACBrXLkibdlinQLIMUguAQAAAAAAwG4klwAAAAAAAGA3kksAAAAAAACwG8klAAAAAEDWKFJE+vxz6/QBt379elksFkVHR2frdufMmaOAgIA7quPo0aOyWCzavXt3umUc9fxwfyK5BAAAAADIGrlySc8/b53exywWS4aP8PBwR4d4z/rjjz9Uq1YteXh4qFChQpowYcIt10lrH8+fP9+mzPr161WpUiW5u7urWLFimjNnTqp6pk2bpiJFisjDw0PVqlXTb7/9ZrP82rVr6tmzp4KCguTj46O2bdsqKirqjp4vrEguAQAAAACyxrlz0rRp1ul97MyZM+bjvffek5+fn828AQMG2FXv9evXszjSe0tsbKwaN26s0NBQ7dixQ++++67Cw8P10Ucf3XLdiIgIm33cqlUrc9mRI0f05JNPql69etq9e7feeOMNde/eXatWrTLLfP311+rXr59GjBihnTt36tFHH1WTJk109uxZs0zfvn21fPlyLVy4UBs2bNDp06fVpk2bLN0HORXJJQAAAABA1jhxQurVyzq9j+XNm9d8+Pv7y2Kx2Mzz8fExy+7YsUNVqlSRl5eXqlevrv3795vLwsPDVaFCBc2ePVtFixaVh4eHJCk6Olrdu3dX7ty55efnp/r16+v333831/v9999Vr149+fr6ys/PT5UrV9b27dttYly1apVKly4tHx8fNW3aVGfOnDGXJSUladSoUSpYsKDc3d1VoUIFrVy5MsPn/MMPP6hEiRLy9PRUvXr1dPTo0dveb19++aWuX7+uTz/9VGXLllX79u3Vp08fTZ48+ZbrBgQE2Ozj5H0lSTNnzlTRokU1adIklS5dWr169dLTTz+tKVOmmGUmT56sl156SV26dFGZMmU0c+ZMeXl56dNPP5UkxcTE6JNPPtHkyZNVv359Va5cWREREfr111+1ZcuW236usEVyCQAAAAAAO7355puaNGmStm/fLhcXF3Xt2tVm+aFDh7R48WItWbLEHOOoXbt2Onv2rFasWKEdO3aoUqVKatCggS5cuCBJ6tixowoWLKht27Zpx44dGjJkiFxdXc06r169qokTJ+rzzz/Xzz//rOPHj9u0ppo6daomTZqkiRMn6o8//lCTJk3UokULHTx4MM3ncOLECbVp00ZPPfWUdu/ere7du2vIkCGpylksljS7oyXbvHmzateuLTc3N3NekyZNtH//fl28eDHD/dizZ08FBweratWq+vTTT2UYhk29DRs2tCnfpEkTbd68WZK1RdiOHTtsyjg5Oalhw4ZmmR07dujGjRs2ZUqVKqXChQubZWA/F0cHAAAAAADIoc6csT5SCgyUihaVrl2T/v479TqVKlmn+/dLV67YLitSxDre07lzqVtP5ctnfWSxt99+W3Xq1JEkDRkyRE8++aSuXbtmtry5fv265s6dq9y5c0uSNm7cqN9++01nz56Vu7u7JGnixIn65ptvtGjRIvXo0UPHjx/XwIEDVapUKUlS8eLFbbZ548YNzZw5Uw8//LAkqVevXho1apS5fOLEiRo8eLDat28vSRo/frzWrVun9957T9OmTUv1HGbMmKGHH35YkyZNkiSVLFlSe/bs0fjx423KlSxZUv7+/unui8jISBUtWtRmXkhIiLksMDAwzfVGjRql+vXry8vLSz/++KNee+01Xb58WX369DHXTa4nZb2xsbGKi4vTxYsXlZiYmGaZffv2mXW4ubmlGgw9JCREkZGR6T4nZA7JJQAAAACAY8yaJY0caTuvY0fpiy+kkyelypVTr5PcoqVzZ+nm7kyff24dUHzBAmv3vJRGjJDuwkDc5cuXN//O9//Jq7Nnz6pw4cKSpNDQUDOxJFm7vF2+fFlBQUE29cTFxenw4cOSpH79+ql79+76/PPP1bBhQ7Vr185MJEmSl5eXzf/58uUzxxaKjY3V6dOnVaNGDZv6a9SoYdP1LqW9e/eqWrVqNvPCwsJSlUtO1GS1YcOGmX9XrFhRV65c0bvvvmsml3DvI7kEAAAAAMgavr5S48bWaWa8/LLUooXtvOTWLQULSjt2pL/unDlpt1ySpGeekW5OjtyFVkuSbLqrWSwWSdYxj5J5e3vblL98+bLy5cun9evXp6oruVVNeHi4nnvuOX3//fdasWKFRowYofnz56t169aptpm83ZTdyBwlb968qe6+lvx/3rx5M11PtWrVNHr0aMXHx8vd3T3dev38/OTp6SlnZ2c5OzunWSZ5u3nz5tX169cVHR1t03opZRnYj+QSAAAAACBrFC8upbiD1y1l1FXNw+O/LnBpKVky/WW5c1sf96BKlSopMjJSLi4uKpKcDEtDiRIlVKJECfXt21cdOnRQRESEmVzKiJ+fn/Lnz69NmzaZ3fUkadOmTapatWqa65QuXVrLli2zmWfPINdhYWF68803dePGDTMBtnr1apUsWTLdLnFp2b17twIDA81ug2FhYfrhhx9syqxevdpsXeXm5qbKlStr7dq15l3mkpKStHbtWvX6/xZslStXlqurq9auXau2bdtKkvbv36/jx4+n2UoLt4cBvQEAAAAAWSMxUYqNtU6RpoYNGyosLEytWrXSjz/+qKNHj+rXX3/Vm2++qe3btysuLk69evXS+vXrdezYMW3atEnbtm1T6dKlM72NgQMHavz48fr666+1f/9+DRkyRLt379brr7+eZvlXXnlFBw8e1MCBA7V//3599dVXaQ7cXapUKS1dujTd7T733HNyc3NTt27d9Ndff+nrr7/W1KlT1a9fP7PM0qVLzbGkJGn58uWaPXu2/vzzTx06dEgzZszQO++8o969e9vE988//2jQoEHat2+fpk+frgULFqhv375mmX79+unjjz/WZ599pr179+rVV1/VlStX1KVLF0mSv7+/unXrpn79+mndunXasWOHunTporCwMD3++OOZ3rdIGy2XAAAAAABZ4/ffreMk7diRcaujHMxiseiHH37Qm2++qS5duujcuXPKmzevateurZCQEDk7O+v8+fN68cUXFRUVpeDgYLVp00Yjbx6bKgN9+vRRTEyM+vfvr7Nnz6pMmTJatmxZqoHBkxUuXFiLFy9W37599cEHH6hq1ap65513Ut35bv/+/YqJiUl3u/7+/vrxxx/Vs2dPVa5cWcHBwRo+fLh69OhhlomJidH+/fvN/11dXTVt2jT17dtXhmGoWLFimjx5sl566SWzTNGiRfX999+rb9++mjp1qgoWLKjZs2erSZMmZplnn31W586d0/DhwxUZGakKFSpo5cqVNoN8T5kyRU5OTmrbtq3i4+PVpEkTTZ8+PdP7FemzGPdCx0w4RGxsrPz9/eVe7iVZnN1uvQKADJ3d/L6jQwAeCLGxsSoYEqiYmBj5+fk5OhzcRcnXInfjtT58+LDad31FRZ58TX55CmZp3XdD7NmTOvr9dM3/dKbNIL3AfWfnzlTJpWvXrunIkSMqWrSoeQc1APeOjN6jmT1X0y0OAAAAAAAAdiO5BAAAAAAAALuRXAIAAAAAAIDdGNAbAAAAAJA1ypWTzp6VAgIcHQmAbERyCQAAAACQNVxdpdy5HR0FgGxGtzgAAAAAQNY4fFhq0cI6vQk3KgfuTVnx3iS5BAAAAADIGjEx0vLl1un/c3V1lSRdvXrVUVEByEDyezP5vWoPusUBAAAAAO4aZ2dnBQQE6OzZs5IkLy8vWSwWB0cFwDAMXb16VWfPnlVAQICcnZ3trovkEgAAAADgrsqbN68kmQkmAPeOgIAA8z1qL5JLAAAAAIC7ymKxKF++fMqTJ49u3Ljh6HAA/D9XV9c7arGUjOQSAAAAACBrFCggTZpknabB2dk5S77IAri3kFwCAAAAAGSNkBCpXz9HRwEgm3G3OAAAAABA1rh4UVq40DoFkGOQXAIAAAAAZI0jR6RnnrFOAeQYJJcAAAAAAABgN5JLAAAAAAAAsBvJJQAAAAAAANiN5BIAAAAAIGt4ekoVK1qnAHIMF0cHAAAAAAB4QJQuLe3c6egoAGQzWi4BAAAAAADAbiSXAAAAAABZY9cuyd3dOgWQY5BcAgAAQCpFihSRxWJJ9ejZs6ck6dq1a+rZs6eCgoLk4+Ojtm3bKioqysFRA3A4w5CuX7dOAeQYJJcAAACQyrZt23TmzBnzsXr1aklSu3btJEl9+/bV8uXLtXDhQm3YsEGnT59WmzZtHBkyAABwEAb0BgAAQCq5c+e2+X/cuHF6+OGHVadOHcXExOiTTz7RV199pfr160uSIiIiVLp0aW3ZskWPP/64I0IGAAAOQsslAAAAZOj69ev64osv1LVrV1ksFu3YsUM3btxQw4YNzTKlSpVS4cKFtXnz5nTriY+PV2xsrM0DAADc/0guAQAAIEPffPONoqOj1blzZ0lSZGSk3NzcFBAQYFMuJCREkZGR6dYzduxY+fv7m49ChQrdxagBOETp0tKff1qnAHIMkksAAADI0CeffKJmzZopf/78d1TP0KFDFRMTYz5OnDiRRRECuGd4ekply1qnAHIMkksAAABI17Fjx7RmzRp1797dnJc3b15dv35d0dHRNmWjoqKUN2/edOtyd3eXn5+fzQPAA+bYMal7d+sUQI5BcgkAAADpioiIUJ48efTkk0+a8ypXrixXV1etXbvWnLd//34dP35cYWFhjggTwL3i/Hnpk0+sUwA5BneLAwAAQJqSkpIUERGhTp06ycXlv8tGf39/devWTf369VOuXLnk5+en3r17KywsjDvFAQCQA5FcAgAAQJrWrFmj48ePq2vXrqmWTZkyRU5OTmrbtq3i4+PVpEkTTZ8+3QFRAgAARyO5BAAAgDQ1btxYhmGkuczDw0PTpk3TtGnTsjkqAABwr2HMJQAAAABA1ggJkYYMsU4B5Bi0XAIAAAAAZI0CBaSxYx0dBYBsRsslAAAAAEDWuHRJWr/eOgWQY5BcAgAAAABkjYMHpXr1rFMAOQbJJQAAAAAAANiN5BIAAAAAAADsRnIJAAAAAAAAdiO5BAAAAADIGq6u1jvGubo6OhIA2cjF0QEAAAAAAB4Q5cpJJ086OgoA2YyWSwAAAAAAALAbySUAAAAAQNbYs0cqWNA6BZBjkFwCAAAAAGSNGzekU6esUwA5BsklAAAAAAAA2I3kEgAAAAAAAOxGcgkAAAAAAAB2I7kEAAAAAMgaxYtL69ZZpwByDBdHBwAAAAAAeED4+kp16zo6CgDZjJZLAAAAAICsceqUNHSodQogxyC5BAAAAADIGlFR0rhx1imAHIPkEgAAAAAAAOzGmEuAgzWv96h6PFNHxYuEyM/HU6eiLmrTjoN6b+5qHTt13iw3+KUnNKTHE+nWU77FcJ04cyE7Qgbua+9/vlpjpi+XJP3wcV9VeaSogyMCAAAA7m8klwAHGv1Ga/Xq2EBnzsXoh/V/6NKVaypbooBebFVdbRpXVtPuk7X38Bmbdb76bouOn06dRIq5FJddYQP3rb2HT+vd2Svk5emmq3HXHR0OAAAA8EAguQQ4SJ4gX73avp6Onz6vWs+NVeyVa+ayVzvU0zv92uq15+qr9+gvbdb7avlWbdp5MLvDBe57NxIS1Xv0F3qkeAEVLZRbi1Zud3RIAAA8eIKCpG7drFMAOQZjLqUQHh4ui8ViPjw8PFS6dGlNmDBBSUlJd2WbFotFEydOvCt1495WOF+QnJ2dtPWPf2wSS5K0auOfkqTgQB9HhAY8kKbMWaX9RyL13pvPydmJ0x8AAHdFaKg0e7Z1CiDHoOXSTTw9PfXTTz9JkuLi4rRu3ToNGTJESUlJGjJkSJZvb/PmzQrlgzdHOnzinOKv31C18g/J19tDl1IkmJrUfESStGHb/lTrVa/0sKo8EqqkJEOHT5zTht/26Qrde4AM/bH/hN6b86MGv/SEShbN5+hwAAB4cMXFSf/8Iz30kOTp6ehoAGQTkks3cXJy0uOPP27+X69ePe3Zs0dLliy5K8mllNtCznIx5opGfrhMY95ora0Lh2nFhv/GXKpdpYRmL/xZHy/4OdV6/3u5uc3/0bFXNWTSIn39w2/ZFTpwX4m/fkO9Rn2hR0oUVK/nGzo6HAAAHmx790qVK0s7dkiVKjk6GgDZhH4BmeDr66sbN26Y/8fHx+t///ufQkND5e7urtKlS+urr76yWadz58565JFHtH79elWsWFHe3t6qWrWqduzYYVPu5m5xhmFo1KhRyps3r3x8fNSuXTutWbNGFotF69evt1lvwoQJCg8PV0hIiIKDg9WlSxdduXLl7uwE3BUz5q1Ttzcj5O3ppq5P19LrnRqpYVgZ7fjzqBat3K7ExP+6Y/558KR6jvpCj7Ycobw13lD5FsM1aMICGYah6SOeV7Pa5Rz4TIB71/iPf9A/J85q6pvPydmZ0x4AAACQ1bjKTkNCQoISEhJ06dIlLVu2TIsXL9bTTz9tLn/mmWc0a9Ys9e/fX999952aNm2q559/XitWrLCpJzIyUn369NHAgQO1YMECXbt2Ta1bt7ZJVN3sgw8+UHh4uDp37qwlS5bo4YcfVvfu3dMs++GHH+rgwYP67LPPNHz4cH311VcaPXp01uwEZIuB3Ztq1qhOmjLnR5V98i0VrN1PzbpPlru7q5bPet0mYfT9+j/01fItOn76vOKvJ+jEmQv6eOHP6jz0E0nSm680T28zQI61bc8RTf/qJ/Xt3ESlH87v6HAAAACABxLd4m5y5coVubq62sx79tlnzS5x69at07Jly7Rq1So1btxYktSoUSOdOXNGI0aMULNmzcz1Lly4oA0bNqhs2bKSJG9vb9WrV09bt25VzZo1U207MTFR48aNU5cuXTRu3DhJUuPGjfXvv//qk08+SVU+X758+vJL653EmjZtqp07d2rRokXmujeLj49XfHy8+X9sbGym9wuyXp2qJfW/l5tr2pc/6b3PVpvzt/z+jzr0m6ld34zU6Ndba8XPezKs5+dtB3Tk5L8qW7xAqrGbgJws4f/vDlfm4fzq82IjR4cDAAAAPLBouXQTT09Pbdu2Tdu2bdPGjRs1depUrVy5Ui+99JIk6ccff1SuXLlUv359s4VTQkKCGjVqpF27dikxMdGsK3/+/GZiSZLKlCkjSTp58mSa2z558qTOnDmjFi1a2Mxv2bJlmuUbNbL9slSmTJl065aksWPHyt/f33wUKlQogz2Bu61hdevxsHHHgVTLzp6/pINHo/Rw4Tzy9nS7ZV3no63dIT09XG9REsg5rsTF658T5/TnwVMqUKuv8oT1MR/JY5Q98dIU5Qnrox82/OHgaAEAeEBYLJKbm3UKIMeg5dJNnJycVKVKFfP/GjVqKCEhQf3791e/fv3077//6sKFC6laNyU7c+aMChYsKEkKCAiwWebmZk0SXLuWdsuSM2fOSJJy585tMz9Pnjxplk+r/pQtk242dOhQ9evXz/w/NjaWBJMDublY335BAT5pLg8O9FFiYpJuJCSluTyZl4ebSj2UV5evxptJJgCSm6uLOj6V9k0TNu8+rH9OnFPTWo8oKMBHhfLlyuboAAB4QFWsKGXwnQTAg4nkUiaULl1akvTXX38pV65cyp07t3744Yc0y6aXCMqMfPmst8c+d+6czfyzZ8/aXWdK7u7ucnd3z5K6cOe2/v6PejxbRz071tfyn3YrNkV3ti5taqpASKC27D6s6zcS5OPlrpBgfx0+bnsseLi7auqbz8nPx1NfLNtsMwA4kNN5erhpyv+eS3NZ79Ff6J8T59TnxUaq8kjRbI4MAAAAeLCQXMqEP//8U5IUHByshg0basKECXJzc1P58uWzdDsFCxZU3rx59e2339p0hfvmm2+ydDu4N3yzdqe67qypGpWKa9vi4Vrxyx7FXopT+VKFVOexkrp67brenLJEkhTo763fFr6lnX8f14GjkTp7Pla5c/mpbtWSKhASqL8OntLw979x7BMCAAAA9u6VOnaUvvxS+v8f6QE8+Egu3SQpKUlbtmyRJF2/fl07duzQmDFjVKZMGdWuXVuurq566qmn1LRpUw0aNEjly5fXlStX9Ndff+nQoUOaPXu23dt2dnbW0KFD9cYbbygkJET16tXTunXrtGbNGknWLnt4cCQlGWrTa5pee66eWjWspKebVJGbq4vOno/V1z/8pskRq3TgaJQkKTr2qj5Z9IsqlQ1Vo+plFeDnpbhr13XgaJRmzV+vjxf+rGvx6d+FEAAAAMgWcXHSrl3WKYAcg+TSTeLi4hQWFiZJcnFxUaFChfT8889rxIgR5jhLyXdkmz59uo4dOyZ/f3898sgj6tKlyx1vv3fv3rp48aKmT5+u999/Xw0bNtS7776rZ599Vv7+/ndcP+4t128k6L3PVtvcLS4tl65c06B3F2ZTVMCD74Nhz+uDYc87OgwAAADggWAxDMNwdBDI2LBhwzRp0iSdP39enp6eWVZvbGys/P395V7uJVmcb31HMgAZO7v5fUeHADwQYmNjVTAkUDExMfLz83N0OLiLkq9F7sZrffjwYbXv+oqKPPma/PIUzNK674bYsyd19Pvpmv/pTD388MOODgew386dUuXK0o4dUqVKjo4GwB3K7Lmalkv3mL179+qLL75Q9erV5ebmpvXr12vixIl69dVXszSxBAAAAAAAkBVILt1jvLy8tHnzZs2YMUOXLl1SgQIFNHDgQIWHhzs6NAAAAADIWNGi0oIF1imAHIPk0j0mNDRUP/30k6PDAAAAAIDbFxgotWvn6CgAZDNuPwYAAIA0nTp1Ss8//7yCgoLk6empcuXKafv27eZywzA0fPhw5cuXT56enmrYsKEOHjzowIgBOFxUlDR5snUKIMcguQQAAIBULl68qBo1asjV1VUrVqzQ33//rUmTJikwMNAsM2HCBL3//vuaOXOmtm7dKm9vbzVp0kTXrl1zYOQAHOrUKal/f+sUQI5BtzgAAACkMn78eBUqVEgRERHmvKIpxlAxDEPvvfee3nrrLbVs2VKSNHfuXIWEhOibb75R+/btsz1mAADgGLRcAgAAQCrLli1TlSpV1K5dO+XJk0cVK1bUxx9/bC4/cuSIIiMj1bBhQ3Oev7+/qlWrps2bNzsiZAAA4CAklwAAAJDKP//8oxkzZqh48eJatWqVXn31VfXp00efffaZJCkyMlKSFBISYrNeSEiIuexm8fHxio2NtXkAAID7H93iAAAAkEpSUpKqVKmid955R5JUsWJF/fnnn5o5c6Y6depkV51jx47VyJEjszJMAPcaf3/pqaesUwA5Bi2XAAAAkEq+fPlUpkwZm3mlS5fW8ePHJUl58+aVJEXddEeoqKgoc9nNhg4dqpiYGPNx4sSJuxA5AId6+GFp2TLrFECOQXIJAAAAqdSoUUP79++3mXfgwAGFhoZKsg7unTdvXq1du9ZcHhsbq61btyosLCzNOt3d3eXn52fzAPCAuXFDOnfOOgWQY5BcAgAAQCp9+/bVli1b9M477+jQoUP66quv9NFHH6lnz56SJIvFojfeeENjxozRsmXLtGfPHr344ovKnz+/WrVq5djgATjOnj1SnjzWKYAcgzGXAAAAkMpjjz2mpUuXaujQoRo1apSKFi2q9957Tx07djTLDBo0SFeuXFGPHj0UHR2tmjVrauXKlfLw8HBg5AAAILuRXAIAAECamjdvrubNm6e73GKxaNSoURo1alQ2RgUAAO41dIsDAAAAAACA3UguAQAAAAAAwG50iwMAAAAAZI1HH5ViYiRvb0dHAiAbkVwCAAAAAGQNZ2fJz8/RUQDIZnSLAwAAAABkjYMHpSZNrFMAOQbJJQAAAABA1rh0SfrxR+sUQI5BcgkAAAAAAAB2I7kEAAAAAAAAu5FcAgAAAAAAgN1ILgEAAAAAskahQtKHH1qnAHIMF0cHAAAAAAB4QOTOLfXs6egoAGQzWi4BAAAAALLGhQvSF19YpwByDJJLAAAAAICscfSo9MIL1imAHIPkEgAAAAAAAOxGcgkAAAAAAAB2I7kEAAAAAAAAu5FcAgAAAABkDW9v6fHHrVMAOYaLowMAAAAAADwgSpaUNm92dBQAshktlwAAAAAAAGA3kksAAAAAgKyxc6dksVinAHIMkksAAAAAAACwG8klAAAAAAAA2I3kEgAAAAAAAOxGcgkAAAAAAAB2c3F0AAAAAACAB0SZMtLBg1LBgo6OBEA2IrkEAAAAAMgaHh5SsWKOjgJANqNbHAAAAAAgaxw5Ij3/vHUKIMcguQQAAAAAyBoXL0pffmmdAsgxSC4BAAAAAADAbiSXAAAAAAAAYDeSSwAAAAAAALAbySUAAAAAQNbIl08aMcI6BZBjuDg6AAAAAADAAyJfPik83NFRAMhmtFwCAAAAAGSN2Fhp1SrrFECOQXIJAAAAAJA1Dh2Smja1TgHkGCSXAAAAAAAAYDeSSwAAAAAAALBbpgb0HjVqlF2VWywWDRs2zK51AQAAYBUfHy93d3dHhwEAAJCmTCWXwu0c7Z/kEgAAwJ3Lnz+/nn/+eXXv3l3lypVzdDgAkD53d+nhh61TADlGppJL69atu9txAAAAIB2+vr764IMP9OGHH6pq1ap66aWX1L59e3l5eTk6NACwVbYsg3kDOVCmkkt16tS523EAAAAgHUeOHNGPP/6o2bNna/ny5XrppZfUt29fdejQQd27d1eVKlWyfJvh4eEaOXKkzbySJUtq3759kqRr166pf//+mj9/vuLj49WkSRNNnz5dISEhWR4LAAC4tzGgNwAAwD3OYrGoSZMmWrhwoU6ePKkJEyaoQIEC+uijj1StWjVVrFhRM2bMUGxsbJZut2zZsjpz5oz52Lhxo7msb9++Wr58uRYuXKgNGzbo9OnTatOmTZZuH8B96I8/pNy5rVMAOcYdJZeWLl2qZ555RuXLl1exYsXM+fv27dOECRN06tSpOw4QAAAA/wkODlb//v31999/65dfflGnTp106NAh9erVS/nz51eXLl3022+/Zcm2XFxclDdvXvMRHBwsSYqJidEnn3yiyZMnq379+qpcubIiIiL066+/asuWLVmybQD3qYQE6d9/rVMAOUamusXdLCkpSR06dNCiRYskSZ6enoqLizOXBwYG6s0331RiYqKGDh2aNZECAADAhq+vr7y8vOTi4iLDMJSYmKjPPvtMc+fOVdOmTRUREaE8efLYXf/BgweVP39+eXh4KCwsTGPHjlXhwoW1Y8cO3bhxQw0bNjTLlipVSoULF9bmzZv1+OOPp1lffHy84uPjzf+zuqUVAABZ5dy5c/fVecrPz0+5c+d22PbtSi5NmTJFCxcu1CuvvKJx48Zp8uTJGj16tLk8JCREtWrV0vfff09yCQAAIAtdvnxZX331lWbPnq0dO3bIMAw99thjeuWVV9S+fXv99ddfevfdd7Vw4UK9/PLLWrp0qV3bqVatmubMmaOSJUvqzJkzGjlypGrVqqU///xTkZGRcnNzU0BAgM06ISEhioyMTLfOsWPHphrHCQCAe825c+f0fJfuunDpqqNDybRcvl76ImK2wxJMdiWX5syZo8cee0zTp0+XZB0H4GbFihXT999/f2fRAQAAQJK0ZcsWffzxx1q4cKEuX74sHx8f9ejRQy+//LIqVKhglqtSpYq+/vprubm5admyZXZvr1mzZubf5cuXV7Vq1RQaGqoFCxbI09PTrjqHDh2qfv36mf/HxsaqUKFCdscIAMDdEBsbqwuXrip3WFt557r3b1Rx5UKUzm1erNjY2PsruXTo0CH17NkzwzJBQUE6f/68XUEBAADgP+XKldPff/8twzBUsWJFvfzyy3ruuefk4+OT7jply5bVl19+mWUxBAQEqESJEjp06JAaNWqk69evKzo62qb1UlRUlPLmzZtuHe7u7nJ3d8+ymADcg0qUkH791ToF7nPeuULkl6ego8PIlHMO3r5dA3p7enoqJiYmwzLHjh1L1VQaAAAAt++ff/5Rly5dtHXrVu3YsUM9evTIMLEkSR07dtS6deuyLIbLly/r8OHDypcvnypXrixXV1etXbvWXL5//34dP35cYWFhWbZNAPchHx8pLMw6BZBj2NVyqWLFilq1apWuXbsmDw+PVMsvXLiglStXqnbt2nccIAAAQE535swZ+fn53dY6hQoVuqMuZwMGDNBTTz2l0NBQnT59WiNGjJCzs7M6dOggf39/devWTf369VOuXLnk5+en3r17KywsLN3BvAHkECdPSpMnS/36SQXvjxYfAO6cXS2X+vTpo5MnT6pt27Y6efKkzbLDhw+rdevWiomJUZ8+fbIkSAAAgJzM29tbsbGxSkpKSnN5UlKSYmNjlZiYmGXbPHnypDp06KCSJUvqmWeeUVBQkLZs2WKO5TBlyhQ1b95cbdu2Ve3atZU3b14tWbIky7YP4D519qw0ZYp1CiDHsKvlUsuWLTV48GCNHz9eoaGh8vb2liTlyZNH58+fl2EYGjZsmOrXr5+lwQIAAOREI0eO1IQJE3TixIk0B+o8f/68ChcurKFDh2r48OFZss358+dnuNzDw0PTpk3TtGnTsmR7AADg/mVXyyXJeivZVatWqXnz5vLy8pKzs7OSkpLUtGlTrVixgtvMAgAAZJHvvvtODRo0SPcOMLlz51bDhg317bffZnNkAAAAdrZcStaoUSM1atQoq2IBAABAGv755x/Vq1cvwzIlS5bUpk2bsikiAACA/9jdcgkAAADZ48aNG3JyyviyzWKx6Nq1a9kUEQCkIzhYeu016xRAjnFHLZd27typzz77TLt27VJMTIz8/f1VsWJFderUSZUqVcqqGAEAAHK0YsWK6aeffsqwzE8//aSiRYtmU0QAkI7ChSXGYgNyHLtbLg0cOFBVq1bVBx98oI0bN2rPnj3auHGjPvjgA1WtWlWDBg3KyjgBAAByrDZt2mj37t0aPnx4qjvCJSYmatiwYdq9e7fatWvnoAgB4P9dvSrt3GmdAsgx7Eouffjhh5o0aZKKFy+uzz//XEePHlVcXJyOHj2quXPnqlixYpo0aZKmT5+e1fECAADkOP3791eJEiX09ttvq3Tp0nr55Zc1atQovfzyyypdurTeeecdlS5dWgMGDHB0qAByun37pMqVrVMAOYZd3eKmT5+uQoUK6bfffpOvr685v3Dhwnr++ef11FNPqVy5cvrwww/12muvZVmwAAAAOZGPj49+/vlnvfrqq1q6dKkOHTpkLnNyctLTTz+t6dOny8fHx4FRAgCAnMqu5NKRI0f06quv2iSWUvL391fbtm01c+bMOwoOAAAAVrlz59aiRYsUFRWl7du3KyYmRgEBAapSpYry5Mnj6PAAAEAOZldyKbMXMCEhIfZUDwAAgHSEhIToySefdHQYAAAAJrvGXOrQoYMWL16sy5cvp7k8NjZWixcvVocOHe4oOAAAAADAfcTJSfL1tU4B5Bh2tVwaOXKk9u7dq6pVq2r48OGqWbOmQkJCFBUVpV9++UWjR49WpUqVNHLkyKyOFwAAIEf6+++/9eGHH2rbtm2Kjo5Oddc4SbJYLDp8+LADogOA/1ehghQb6+goAGSzTCWXnJycZLFYUs03DEMdO3ZMc/7+/fvl5eWlhISEO48SAAAgB9uwYYOaNm2q+Ph4ubi4KCQkRC4uqS/jDMNwQHQAACCny1RyqXbt2mkmlwAAAHD3DRkyRAkJCZo9e7Y6deokZ2dnR4cEAGn7+2+pXTtp4UKpTBlHRwMgm2QqubR+/fq7HAYAAADS8/vvv6t9+/bq2rWro0MBgIxdu2ZNMF275uhIAGQjRlkDAAC4x3l7e2f6br0AAADZjeQSAADAPe6JJ57QL7/84ugwAAAA0mTX3eIkKTExUQsWLNCaNWt0+vRpxcfHpypjsVi0du3aOwoQAAAgp3v33XdVs2ZN9enTR+PGjZOXl5ejQwIAADDZlVy6cuWKGjdurC1btsgwDFksFpu7kyT/zyDgAAAAd659+/by8fHRtGnTNGfOHJUoUUJ+fn6pyvHDHgCHe+gh6dtvrVMAOYZdyaUxY8Zo8+bNGjVqlF577TUFBwcrPDxcL7/8sn7++Wf973//U6VKlfTll19mdbwAAAA5Tsqbq1y+fFk7d+5Msxw/7AFwuIAAqUULR0cBIJvZNebSkiVL9Pjjj+utt95Srly5zPkhISFq166d1q1bpzVr1ujdd9/NskABAAByqqSkpEw9EhMTHR0qgJwuMlIaO9Y6BZBj2JVcOn78uB5//PH/KnFyshlzqWDBgnryySf12Wef3XmEAAAAAID7w+nT0v/+Z50CyDHs6hbn7e0tJ6f/8lL+/v46c+aMTZm8efPq+PHjdxYdAAAAbFy+fFkHDhzQlStXVKtWLUeHAwAAYF/LpdDQUJvE0SOPPKKffvrJbL1kGIbWrl2rfPnyZU2UAAAAOdzRo0fVsmVLBQYG6rHHHlO9evXMZZs2bVKZMmVsxmYCAADILnYllxo0aKB169YpISFBktSpUycdP35cYWFhGjhwoGrWrKndu3erbdu2WRosAABATpQ8JMEPP/ygli1bKiwszOZOvdWqVdO///6refPmOTBKAACQU9nVLe6ll15SUFCQzp07p3z58qlr167atWuXpk+frt27d0uS2rZtq/Dw8CwMFQAAIGcaMWKELl68qA0bNqh69eoaOXKkNm/ebC53cXFRrVq1tGnTJgdGCQCy3i3u6aetUwA5hl0tl4oXL67BgwfbdHv74IMPFBkZqc2bN+v06dNauHChvLy8sixQAACAnGrVqlVq3bq1qlevnm6Z0NBQnTp1KhujAoA0PPSQtHChdQogx7AruZSe3Llzq1q1asqbN6+WLVumUaNGZWX1AAAAOdKFCxdUpEiRDMsYhmFz914AcIjr16WTJ61TADlGliaXUlq6dKlGjhx5t6oHAADIMUJCQnTw4MEMy+zZs0eFCxfOpogAIB1//ikVKmSdAsgx7lpyCQAAAFmjUaNG+u677/THH3+kufyXX37RTz/9pCeeeCKbIwMAACC5BAAAcM9766235Onpqdq1a+vtt9/WoUOHJEkrVqzQsGHD1LRpUwUHB2vgwIEOjhQAAOREdt0tDgAAANmnSJEiWrVqldq3b69hw4bJYrHIMAw1b95chmGocOHCWrRokc3NVgAAALILySUAAID7QLVq1XTw4EEtX75cW7du1YULF+Tn56dq1aqpZcuWcnNzc3SIAAAghyK5BAAAcJ9wcXFR69at1bp1a0eHAgBpq1BBunZNcnV1dCQAslGmk0sTJky4rYr37Nlz28HAMY6vnyg/Pz9HhwHc91p/vNXRIQAPhIS4K44OAQBgLycnyd3d0VEAyGaZTi4NGTLE7N+fWRaLxa6gAAAA8J9Ro0ZlqpzFYtGwYcPucjQAkIEDB6QePaSPPpJKlHB0NACySaaTSxEREXczDgAAAKQjPDw8w+XJPwCSXALgcJcvSxs2WKcAcoxMJ5c6dep0N+MAAABAOtatW5fm/JiYGO3cuVPvv/++GjZsqJ49e2ZzZAAAAAzoDQAAcM+rU6dOustatGihjh07qlKlSmrbtm02RgUAAGDl5OgAAAAAcGeKFy+u1q1ba9y4cY4OBQAA5EAklwAAAB4AefLk0f79++9a/ePGjZPFYtEbb7xhzrt27Zp69uypoKAg+fj4qG3btoqKirprMQC4DxQuLH38sXUKIMcguQQAAHCfi4+P18qVKxUQEHBX6t+2bZtmzZql8uXL28zv27evli9froULF2rDhg06ffq02rRpc1diAHCfCA6Wune3TgHkGIy5BAAAcI+bO3dumvMTEhJ06tQpzZ8/X/v27VOfPn2yfNuXL19Wx44d9fHHH2vMmDHm/JiYGH3yySf66quvVL9+fUnWuwuXLl1aW7Zs0eOPP57lsQC4D/z7r/TNN1KrViSYgByE5BIAAMA9rnPnzrJYLKnmG4YhSbJYLOrQocNdGXOpZ8+eevLJJ9WwYUOb5NKOHTt048YNNWzY0JxXqlQpFS5cWJs3bya5BORUx49LL70kVapEcgnIQUguAQAA3OMiIiLSnO/k5KTAwEBVrlxZ+fLly/Ltzp8/Xzt37tS2bdtSLYuMjJSbm1uqrnghISGKjIxMs774+HjFx8eb/8fGxmZpvAAAwDHuKLl0/fp1rVmzRvv27dOVK1c0bNgwSdbBHWNjYxUcHCwnJ4Z1AgAAuBOdOnXK9m2eOHFCr7/+ulavXi0PD48sqXPs2LEaOXJkltQFAADuHXZnfpYtW6bChQvrqaee0oABAxQeHm4u++OPP5QvXz7Nnz8/K2IEAABANtuxY4fOnj2rSpUqycXFRS4uLtqwYYPef/99ubi4KCQkRNevX1d0dLTNelFRUcqbN2+adQ4dOlQxMTHm48SJE9nwTAAAwN1mV8ulTZs26emnn1a+fPk0depUbdmyRfPmzTOXV61aVcWKFdPixYv13HPPZVmwAAAAOdHPP/9s97q1a9e2a70GDRpoz549NvO6dOmiUqVKafDgwSpUqJBcXV21du1atW3bVpK0f/9+HT9+XGFhYWnW6e7uLnd3d7viAXCf8PGR6tSxTgHkGHYll0aPHq2AgADt2LFDwcHBOn/+fKoyVapU0datW+84QAAAgJyubt26aQ7onRmJiYl2refr66tHHnnEZp63t7eCgoLM+d26dVO/fv2UK1cu+fn5qXfv3goLC2MwbyAnK1FCWr/e0VEAyGZ2JZe2bt2qp59+WsEZjP5fqFAhffvtt3YHBgAAAKvhw4dr69atWrVqlYoXL64aNWooJCREUVFR+vXXX3XgwAE1adIk25M6U6ZMkZOTk9q2bav4+Hg1adJE06dPz9YYANxjkpKkGzckV1eJ8XeBHMOu5FJ8fLz8/PwyLBMdHc1g3gAAAFmgQYMGGjdunD766CN169bNphWTYRj6+OOP9frrr+vNN99UzZo171oc629qjeDh4aFp06Zp2rRpd22bAO4zu3dLlStLO3ZIlSo5OhoA2cSu7M9DDz2U5i1pU9q8ebNKlSplV1AAAAD4z7Bhw/Tkk0+qe/fuqbrHWSwW9ejRQ82aNTPv3AsAAJCd7EoutW3bVps2bVJERESayydOnKg///xTzz777B0FBwAAAOud20qXLp1hmdKlS2v79u3ZFBEAAMB/7OoWN3DgQC1evFjdu3fXV199pfj4eEnSoEGDtHnzZv3666+qUKGCevXqlaXBAgAA5ERubm7atWtXhmV27dolNze3bIoIAADgP3a1XPLx8dEvv/yi9u3ba/369dq4caMMw9DEiRP166+/6plnntGaNWu41SwAAEAWaNy4sVauXKlx48bp+vXrNsuuX7+usWPHatWqVWrSpImDIgQAADmZXS2XJCkwMFBffvml3n//fW3btk0XLlyQn5+fHnvsMYWEhGRljAAAADnau+++q19++UVvvvmmpk6dqipVqihPnjw6e/astm/frrNnzyp//vyaMGGCo0MFkNM98oh04oSUJ4+jIwGQjexOLiULCgpS06ZNsyIWAAAApKFgwYLavn27hgwZogULFuj77783l3l4eOiFF17QuHHjlDdvXgdGCQCS3NykggUdHQWAbGZXtzgAAABkr7x582rOnDmKiYnRH3/8oV9++UV//PGHoqOjNWfOHBJLAO4N//wjtWtnnQLIMexquVS/fv1MlbNYLFq7dq09mwAAAEAaXF1d9cgjjzg6DABIW3S0tGiRNHSooyMBkI3sSi6tX78+w+UWi0WGYchisdhTPQAAANIQGRmpJUuWaN++fbp69apmz54tSTp37pyOHDmicuXKydPT08FRAgCAnMaubnFJSUlpPqKjo/XTTz+pWrVqevrpp1PdzQQAAAD2mT59uooWLapevXrpww8/VEREhLns7NmzCgsL0xdffOHACAEAQE6VpWMu+fn5qW7dulq1apV+++03vf3221lZPQAAQI60fPly9erVS+XKldOyZcv06quv2iwvW7asypcvr2+++cYxAQIAgBztrgzo7evrq2bNmtn8ogYAAAD7vPvuuypcuLDWrVun5s2bK08at/guV66c/v77bwdEBwAp5M8vvfOOdQogx7hrd4tzcnLSmTNn7lb1AAAAOcbu3bv15JNPytvbO90yBQoUUFRUVDZGBQBpyJvXOpg3d7AEcpS7klz6559/tHDhQhUpUuRuVA8AAJCjJCUlydXVNcMyZ8+elbu7ezZFBADpiI6Wli2zTgHkGHbdLa5r165pzk9ISNCpU6e0ceNG3bhxQ6NGjbqj4AAAACCVLFlSv/zyS7rLExIS9PPPP6tcuXLZGBUApOGff6SWLaUdO6RKlRwdDYBsYldyac6cORkuL1mypPr376/u3bvbUz0AAABS6NixowYMGKCRI0dqxIgRNssSExM1YMAA/fPPPxo8eLCDIgQAADmZXcmlI0eOpDnfyclJAQEB8vX1vaOgAAAA8J/evXtr+fLlGjVqlL788kt5eHhIkp555hlt375dR48eVePGjdWtWzcHRwoAAHIiu5JLFotFbm5uyssgbQAAAHedq6urVq1apZEjR2rmzJm6ePGiJGnRokXy8/PT4MGDNXLkSFksFgdHCgAAciK7kktFixZVp06d9Omnn2Z1PAAAAEiDm5ub3n77bY0ZM0b79+/XhQsX5Ofnp9KlS8vZ2dnR4QGAlYeHVKaMdQogx7AruRQYGKigoKCsjgUAAABpeOihh9SsWTNNmzZNFotFpUqVcnRIAJC2MmWkv/5ydBQAspmTPSvVqlVLW7duzepYAAAAkIZ///1Xfn5+jg4DAAAgTXYll8aOHas//vhDo0aNUkJCQlbHBAAAgBTKly+vAwcOODoMALi13bslPz/rFECOYVe3uAkTJqhcuXIaOXKkZs2apUcffVQhISGpBpG0WCz65JNPsiRQAACAnGrw4MFq27at1q1bp3r16jk6HABIX1KSdOmSdQogx8h0csnZ2Vnh4eEaNmyY5syZY84/c+aMzpw5k+Y6JJcAAADu3MWLF9W4cWM1btxYrVq10mOPPZbmD3uS9OKLLzogQgAAkJNlOrlkGIYMw5AkHTly5K4FBAAAAFudO3eWxWKRYRhavHixFi9eLEk2ySXDMGSxWEguAQCAbGdXt7jQ0NCsjgMAAAApxMbGysPDQ25uboqIiHB0OAAAAOmyK7kEAACAuyswMNAckqBTp06SpK1bt2rr1q3q06ePg6MDgHSUKiXt2GGdAsgxbutucWn16wcAAEDWSzkkQbKVK1eqb9++DooIADLBy0uqVMk6BZBj3FZyKTw8XM7Ozpl+uLjQMAoAAAAAcozjx6WePa1TADnGbWV//Pz8FBAQcJdCAQAAAADc1/79V5o+XerWTSpc2NHRAMgmt5Vc6tu3r4YPH363YgEAAAAAAMB95ra6xQEAAAAAAAApMSgSAADAPeqLL77Qli1bzP8PHTokSXriiSfSLG+xWPT9999nS2wAAADJSC4BAADcow4dOmQmlFJauXJlmuW5sy8Ah8uTR+rb1zoFkGOQXAIAALgHHTlyxNEhAMDtK1hQmjzZ0VEAyGaZTi4lJSXdzTgAAACQQmhoqKNDAIDbd/mytGePVK6c5OPj6GgAZBMG9AYAAAAAZI0DB6Tq1a1TADkGySUAAAAAAADYjeQSAAAAAAAA7EZyCQAAAAAAAHYjuQQAAIBUZsyYofLly8vPz09+fn4KCwvTihUrzOXXrl1Tz549FRQUJB8fH7Vt21ZRUVEOjBjAPcHFRQoOtk4B5BgklwAAAJBKwYIFNW7cOO3YsUPbt29X/fr11bJlS/3111+SpL59+2r58uVauHChNmzYoNOnT6tNmzYOjhqAw5UvL507Z50CyDFIJwMAACCVp556yub/t99+WzNmzNCWLVtUsGBBffLJJ/rqq69Uv359SVJERIRKly6tLVu26PHHH3dEyAAAwEFouQQAAIAMJSYmav78+bpy5YrCwsK0Y8cO3bhxQw0bNjTLlCpVSoULF9bmzZvTrSc+Pl6xsbE2DwAPmL/+kooVs04B5BgklwAAAJCmPXv2yMfHR+7u7nrllVe0dOlSlSlTRpGRkXJzc1NAQIBN+ZCQEEVGRqZb39ixY+Xv728+ChUqdJefAYBsFx8vHT5snQLIMUguAQAAIE0lS5bU7t27tXXrVr366qvq1KmT/v77b7vrGzp0qGJiYszHiRMnsjBaAADgKIy5BAAAgDS5ubmpWLFikqTKlStr27Ztmjp1qp599lldv35d0dHRNq2XoqKilDdv3nTrc3d3l7u7+90OGwAAZDNaLgEAACBTkpKSFB8fr8qVK8vV1VVr1641l+3fv1/Hjx9XWFiYAyMEAACOQMslAAAApDJ06FA1a9ZMhQsX1qVLl/TVV19p/fr1WrVqlfz9/dWtWzf169dPuXLlkp+fn3r37q2wsDDuFAfkdMWKSStXWqcAcgySSwAAAEjl7NmzevHFF3XmzBn5+/urfPnyWrVqlRo1aiRJmjJlipycnNS2bVvFx8erSZMmmj59uoOjBuBwfn5SkyaOjgJANiO5BAAAgFQ++eSTDJd7eHho2rRpmjZtWjZFBOC+cOaMNGuW9PLLUr58jo4GQDZhzCUAAAAAQNY4c0YaOdI6BZBjkFwCAAAAAACA3UguAQAAAAAAwG4klwAAAAAAAGA3kksAAAAAgKwRGCh17GidAsgxuFscAAAAACBrFC0qffGFo6MAkM1ouQQAAAAAyBrXrkmHDlmnAHIMkksAAAAAgKzx999S8eLWKYAcg+QSAAAAAAAA7EZyCQAAAAAAAHYjuQQAAAAAAAC7kVwCAAAAAACA3VwcHQAAAAAA4AFRqZJkGI6OAkA2o+USAAAAAAAA7EZyCQAAAACQNfbvl8LCrFMAOQbJJQAAAABA1rhyRdqyxToFkGOQXAIAAAAAAIDdSC4BAAAAAADAbiSXAAAAAAAAYDeSSwAAAACArFGkiPT559YpgBzDxdEBAAAAAAAeELlySc8/7+goAGQzWi4BAAAAALLGuXPStGnWKYAcg+QSAAAAACBrnDgh9eplnQLIMUguAQAAAAAAwG4klwAAAAAAAGA3kksAAAAAAACwG8klAAAAAEDW8PWVGje2TgHkGC6ODgAAAAAA8IAoXlxatcrRUQDIZrRcAgAAAABkjcREKTbWOgWQY5BcAgAAAABkjd9/l/z9rVMAOQbd4oB7zOmz0fp2zS6t/vUvHTgapbPnYxXo56Vqjz6kPi82UpVHijg6ROCeNKt9BeXxdU9z2Z+nYzXs+73m/5UK+uux0ECVCvFVbl83uThZdDrmmjb9c0HL9pzRjUQju8IGAAAA7nskl4B7zEdfb9DUuatVtGCw6j9eSkEBPvrnxDl9v+EPfb/hD308urPaNK7s6DCBe9KV+AQt/zMy1fyzl+LNv12dLRrWrJSuJyTpzzOx2n0yWq4uTqpY0F/PP1ZI1UID9dZ3e3U9MSk7QwcAAADuWySXgHtM5bKh+m7m66pRubjN/F93HVKr1z5Q//Ff68m65eXu5uqgCIF715Xrifp656kMyyQlSV9uO6EVf0fpyvX/xoNwtlg0qFFxVQ0N1BNlQ/TNH2fudrgAAADAA+G+G3MpPDxcFotFBQoUUFJS6l+Va9SoIYvFos6dO2e6zqNHj8pisWjRokXmvCJFiqhXr15ZEfJddfToUYWHh+v06dOODgVZ5Kn6FVIlliSpesViqlWluKJjr+rvQ7zegL0SDUOLdp+2SSwlz1+y2/reKpuP2ycDAAAAmXVftlxydXXVv//+q59//ll169Y15x87dkybN2+Wj4/PHW9j6dKlCgwMvON67rajR49q5MiRat68ufLnz+/ocHCXubg4W6fOzg6OBLg3uThbVK94sHJ5u+nq9UQdOndZB89dyfT6CUnWsZYSkxhzCQAAu5QrJ509KwUEODoSANnovkwuubm5qWHDhpo3b55Ncmn+/PkqW7asnLPgi3fFihXvuA4gK52IvKANv+1X3mA/lSlGIhFISy4vN/Wp+7DNvINnL2vyT4cUmWLcpfQ0KJlbkrT7ZMxdiQ8AgAeeq6uUO7ejowCQze67bnHJOnTooEWLFunGjRvmvK+++krPPfecTbl9+/apffv2KlSokLy8vFSmTBlNmjQpzS51KaXVLW7WrFkKDQ2Vl5eXGjVqpF27dslisWjOnDmp1ps2bZpCQ0Pl7++vVq1a6dy5c2aZK1euqFevXipZsqS8vLxUpEgRvfLKK4qJsf0yc6u61q9fr3r16kmSHnvsMVksFlkslszvRNw3biQk6pXhcxV/PUEjereSs/N9+9YF7pq1B85p+Pd71fnzHXr2023qu3iP1h08p+J5fDTyydLycM34fVOpoL8al8qjExfjtGb/uQzLAgCAdBw+LLVoYZ0CyDHu22+oTz31lOLj4/Xjjz9Kkv7++2/98ccfat++vU25U6dOqWTJkpo+fbp++OEH9ejRQ6NGjdLo0aNva3vLli3TK6+8osaNG2vp0qVq2LChnnnmmXTLLlu2TNOmTdPUqVO1YcMG9e7d21x+9epVJSYm6u2339aKFSs0ZswYbdiwQa1atbqtuipVqqRp06ZJkiIiIrR582Zt3rz5tp4X7n1JSUl6Lfxz/brrkDq1qq72T1R1dEjAPWnBzlPaczpWMdcSdD0xSUcvXNX76//RuoPnlMfXXY1L5Ul33WLB3urfoLiuXk/Uu2sPmt3jAADAbYqJkZYvt04B5Bj3Zbc4SfLy8lLLli01f/58Pfnkk5o3b57CwsJUtGhRm3INGjRQgwYNJEmGYahmzZq6evWqPvzwQ40YMSLT2xszZozq16+vjz/+WJLUpEkT3bhxQ8OGDUtV1jAMLVu2TO7u7pKs4yK98847SkpKkpOTk3Lnzq0ZM2aY5RMSElS0aFHVrFlTBw4cUIkSJTJVl5+fn8qUKSNJeuSRR1SlSpUMn0N8fLzi4//rFhIbG5vp5w/HSEpKUq9RX2rRqu16ptljmjy0/a1XAmDjx71nVa94bpUK8dWyPZGplj8c7K0RT5SSYRgatWKfTlyMc0CUAAAAwP3rvm25JFm7xn377beKi4vT/Pnz1aFDh1Rlrl27phEjRqhYsWJyd3eXq6ur3nzzTZ05c0aXL1/O1HYSExO1a9cutWjRwmZ+y5Yt0yxfp04dMxkkSWXKlNGNGzd09uxZc97nn3+uihUrysfHR66urqpZs6Yk6cCBA7ddV2aNHTtW/v7+5qNQoUK3XQeyT1JSknqO+kLzvt+qtk0qa/qIF+TkdF+/ZQGHiL2WIElyd0n9/nk42FvhT5SSxSKNXLFPh/7N/ODfwINu7Nixeuyxx+Tr66s8efKoVatW2r9/v02Za9euqWfPngoKCpLP/7F33+FNVX8YwN803ZvSQVs62NuC7CFLoAgiCCKIIhtURBAHoJUCskTAyVA2CgpKQZaoVIYoyJa9O6C0pQW6d3J+f+SX0DRpm4Y0t2nfz/PkSXPnm9WcfHPuuc7OGDRoEBITEyVKTERERFKx6G+qoaGhsLGxwcyZMxEVFaX3MLVp06bh008/xbhx47B3716cOHECYWFhAFQNIkMkJSWhoKAAXkUGpvP21n+IhXuRMyPY2tpq7W/79u149dVX0aZNG2zduhXHjh3D9u3b9WYqbVtlMWPGDKSmpmout2/fLvM2yDzUhaUf9xzH8z2fxDezR3CcJSIj1fdWnUE0KUN7QG91YclKJsPHv14t01nliKqCQ4cOYeLEiTh27Bj++OMP5Ofno1evXsjMfPReefvtt7Fr1y789NNPOHToEO7evYuBAwdKmJqIiIikYLGHxQGAjY0NBg0ahKVLl+Lpp5+Gj4+PzjI//fQTJkyYgGnTpmmm7dmzp0z78fLygrW1tdag3ACM6j2kztS8eXN88803mmmHDh0yaltlYWdnp9ULiiom9aFwP+45jgE9WuDbOSwsEZXG380eSRl5yFModaYPb6PqpXn4xn3N9NqejpjVpyHkMhnm7LuCq/cM68lKVJXs27dP6/b69evh7e2NU6dOoXPnzkhNTcWaNWuwefNmdO/eHYBqDMhGjRrh2LFjaNeunRSxiUhq/v7AkiWqayKqMiy6uAQAY8eOxb179zBu3Di987OzszW9fQDVIW4//vhjmfYhl8vRokUL/PLLL5g8ebJm+o4dO4zKXDQTAGzatMmobT1OTyaqmBat/hU/7PkXzo52qBPojcVr9+ks07dLCJo1qClBOqKKqVOd6niumS8uJaQhKT0POQUK+LnZ48kAd9jIrfDzmThcSkgHADjbyTHrmUZwtrPG6dspCPF3Q4i/m9b2MvMU2H1Bd3wmoqpMfVZbDw8PAMCpU6eQn5+PHj16aJZp2LAhAgMDcfToURaXiKoqHx9g6lSpUxCRmVl8calNmzYlFnl69uyJVatWoXHjxvD09MTy5cu1BrU2VFhYGPr3749x48Zh8ODBOHPmDDZs2AAAZR4Hp2fPnpg4cSI+/vhjtG/fHnv37kVkZGSZMwFA/fr1IZfLsXbtWlhbW8Pa2rrUgb2pYou9+wAAkJGViyVrf9O7TKBvdRaXiAq5cDcNNd0dUNvTEY1quMDO2gppOQU4fTsFv166h//iHp2xxsFGDhd71cffkwHueDLAXWd799JzWVwiKkSpVGLKlCno2LEjmjZtCgBISEiAra2tziH8Pj4+SEjQ//7hyUWIqoCHD4H9+4EePYBq1aROQ0RmYvHFpdJ89dVXeO211zBp0iQ4Ojpi5MiReP7554vt6VSc5557DitWrMD8+fPx/fffo23btlixYgV69eoFNze30jdQyIQJE3Dr1i189dVX+PTTTxEaGorNmzcb9Qufp6cnli1bhkWLFuG7775DQUEBhOAptC3Z8lnDsXzWcKljEFmUiwnpuPj/nkmlScrIw/Or/i3nRESVy8SJE3HhwgUcOXLksbazYMECzJ4920SpiKhCiooCXnwROHWKxSWiKsTiikuzZs3CrFmzSlzm7Nmzmr99fHw0g2UXNnbsWM3fwcHBOgWZ6OhonXVee+01vPbaa5rba9asAQCEhISUuN6AAQO0ti+Xy7F48WIsXrxYazlDMhTdFqAqVk2YMEFnWSIiIqLH9eabb2L37t04fPgwatZ81Gu2Ro0ayMvLQ0pKilbvpcTERNSoUUPvtmbMmIGphQ6XSUtL49lriYiIKgGLKy5J5cGDB5g9eza6d+8OFxcXnDhxAvPmzUP//v0RHBwsdTwiIiIikxJCYNKkSdi+fTsOHjyIWrVqac1v2bIlbGxsEBkZiUGDBgEArl69itjYWLRv317vNnlyESIiosqJxSUD2djY4ObNm9i8eTNSUlLg5eWF4cOH45NPPpE6GhEREZHJTZw4EZs3b8Yvv/wCFxcXzThKbm5ucHBwgJubG8aMGYOpU6fCw8MDrq6umDRpEtq3b8/BvImIiKoYFpcM5OLigt27d0sdg4iIiMgsVqxYAQDo2rWr1vR169Zh5MiRAIDPPvsMVlZWGDRoEHJzcxEaGorly5ebOSkRVSgODkCLFqprIqoyWFwiIiIiIh2GnCDE3t4ey5Ytw7Jly8yQiIgsQqNGwOnTUqcgIjOzkjoAERERERERERFZLhaXiIiIiIiIyDTOnAHs7FTXRFRlsLhEREREREREpiEEkJenuiaiKoPFJSIiIiIiIiIiMhqLS0REREREREREZDQWl4iIiIiIiIiIyGjWUgcgIiIiIiKiSqJRI+DCBaB2bamTEJEZsbhEREREREREpuHgADRpInUKIjIzHhZHREREREREphETA4wdq7omoiqDxSUiIiIiIiIyjfv3gTVrVNdEVGWwuEREREREREREREZjcYmIiIiIiIiIiIzG4hIRERERERERERmNxSUiIiIiIiIyDR8fYPp01TURVRnWUgcgIiIiIiKiSsLfH1iwQOoURGRm7LlEREREREREppGeDhw8qLomoiqDxSUiIiIiIiIyjevXgW7dVNdEVGWwuEREREREREREREZjcYmIiIiIiIiIiIzG4hIRERERERERERmNxSUiIiIiIiIyDRsb1RnjbGykTkJEZmQtdQAiIiIiIiKqJJo1A+7ckToFEZkZey4REREREREREZHRWFwiIiIiIiIi0zh/HqhZU3VNRFUGi0tERERERERkGvn5QFyc6pqIqgwWl4iIiIiIiIiIyGgsLhERERERERERkdFYXCIiIiIiIiIiIqOxuERERERERESmUa8ecOCA6pqIqgxrqQMQERERERFRJeHiAnTtKnUKIjIz9lwiIiIiIiIi04iLA2bMUF0TUZXB4hIRERERERGZRmIisHCh6pqIqgwWl4iIiIiIiIiIyGgsLhERERERERERkdFYXCIiIiIiIiIiIqOxuERERERERESmUb06MGaM6pqIqgxrqQMQERERERFRJREUBKxeLXUKIjIz9lwiIiIiIiIi08jOBi5eVF0TUZXB4hIRERERERGZxuXLQNOmqmsiqjJYXCIiIiIiIiIiIqOxuEREREREeh0+fBj9+vWDn58fZDIZduzYoTVfCIGZM2fC19cXDg4O6NGjB65fvy5NWCIiIpIMi0tEREREpFdmZiZCQkKwbNkyvfMXLVqEL7/8EitXrsS///4LJycnhIaGIicnx8xJiYiISEo8WxwRERER6fXMM8/gmWee0TtPCIHPP/8cYWFh6N+/PwBg48aN8PHxwY4dOzB06FBzRiWiikImA2xtVddEVGWw5xIRERERlVlUVBQSEhLQo0cPzTQ3Nze0bdsWR48e1btObm4u0tLStC5EVMm0aAHk5qquiajKYHGJiIiIiMosISEBAODj46M13cfHRzOvqAULFsDNzU1zCQgIKPecREREVP5YXCIiIiIis5gxYwZSU1M1l9u3b0sdiYhM7fJl4MknVddEVGWwuEREREREZVajRg0AQGJiotb0xMREzbyi7Ozs4OrqqnUhokomOxs4c0Z1TURVBotLRERERFRmtWrVQo0aNRAZGamZlpaWhn///Rft27eXMBkRERGZG88WR0RERER6ZWRk4MaNG5rbUVFROHv2LDw8PBAYGIgpU6Zg7ty5qFevHmrVqoWPPvoIfn5+GDBggHShiYiIyOxYXCIiIiIivU6ePIlu3bppbk+dOhUAMGLECKxfvx7vv/8+MjMzMX78eKSkpKBTp07Yt28f7O3tpYpMREREEmBxiYiIiIj06tq1K4QQxc6XyWSYM2cO5syZY8ZURFSh1aoFbN2quiaiKoPFJSIiIiIiIjKNatWAwYOlTkFEZsYBvYmIiIiIiMg0EhOBpUtV10RUZbC4RERERERERKYRFwe8847qmoiqDBaXiIiIiIiIiIjIaCwuERERERERERGR0VhcIiIiIiIiIiIio7G4RERERERERKbh5gb066e6JqIqw1rqAERERERERFRJ1KkD7NwpdQoiMjP2XCIiIiIiIiLTyM8HkpJU10RUZbC4RERERERERKZx/jzg7a26JqIqg8UlIiIiIiIiIiIyGotLRERERERERERkNBaXiIiIiIiIiIjIaCwuERERERERERGR0aylDkBERERERESVREgIkJoKODlJnYSIzIjFJSIiIiIiIjINuRxwdZU6BRGZGQ+LIyIiIiIiItO4fh0IDVVdE1GVweISERERERERmUZ6OvD776prIqoyWFwiIiIiIiIiIiKjsbhERERERERERERGY3GJiIiIiIiIiIiMxuISERERERERmUZAAPD116prIqoyrKUOQEREREREQH5eHmJiYqSOUSaurq7w8vKSOgZVJF5ewMSJUqegCiYpKQlpaWlSxzBYTEwMCvILpI5hUVhcIiIiIiKSWG5GKqKjbmHKB7NgZ2cndRyDebg44vt1q1lgokcePAD27gX69AE8PKROQxVAUlISXhk1Fg/Ss6SOYrCc7CzciYtHYH6+1FEsBotLREREREQSy8/NhlJmDc92A1HdL0jqOAbJfJCIpKPbkJaWxuISPRIdDQwfDpw6xeISAQDS0tLwID0LXu0HwcnDR+o4Brl38wJibq+FooDFJUOxuEREREREVEE4VvOCq3dNqWMYLEnqAERkMZw8fCzm/1vG/QSpI1gcDuhNRERERERERERGY3GJiIiIiIiIiIiMxuISERERERERmYaTE9CuneqaiKoMjrlEREREREREptGgAXD0qNQpiMjM2HOJiIiIiIiIiIiMxuISERERERERmcbp04BMpromoiqDxSUiIiIiIiIiIjIai0tERERERERERGQ0FpeIiIiIiIiIiMhoLC4REREREREREZHRrKUOQERERERERJVE48bA9etAzZpSJyEiM2JxiYiIiIiIjJKfl4eYmBipYxgsLy8Ptra2UscoE0vM7OrmBi97e6ljGCwpKQlpaWlSxygTS3pdxMTEoCC/QOoYVM5YXCIiIiIiojLLzUhFdNQtTPlgFuzs7KSOU6r8vDzExcagZlAtWNtYxtcgS8zsl52Nt+Ki0fyXHajeqpXUcUqVlJSEV0aNxYP0LKmjGMzSXhc52Vm4ExePwPx8qaNQOar4r0QiIiIiqtCWLVuGTz/9FAkJCQgJCcFXX32FNm3aSB2Lyll+bjaUMmt4thuI6n5BUscp1b2bF3Arei2qtelvEXkBy8xc49IJPH3ib9yOi7OI4lJaWhoepGfBq/0gOHn4SB3HIJb2urh38wJibq+FooDFpcqMxSUiIiIiMtqWLVswdepUrFy5Em3btsXnn3+O0NBQXL16Fd7e3lLHIzNwrOYFV++KP75Oxv0EAJaTF7DMzA5xN6WOYBQnDx+LeYwt7XWhzkuVG88WR0RERERGW7p0KcaNG4dRo0ahcePGWLlyJRwdHbF27VqpoxEREZGZsOdSFSaEAACkW9jgdUQVVUF2ptQRiCqFghzVe0n9OUUVV15eHk6dOoUZM2ZopllZWaFHjx44evSozvK5ubnIzc3V3E5NTQWAchlINz09HYqCAqTERyM/p+KPpZJ27w6EUom0hNuwlkmdxjCWltnS8gKWmdk6KR5pAK7fuoX7Z89KHadUt2/fRl5OjsX8rwAs73VhaXkBy8uc+fAeFAUFSE9PN/lnqnp7pbXLZIIttyrrzp07CAgIkDoGERGRXrdv30ZNnsq6Qrt79y78/f3xzz//oH379prp77//Pg4dOoR///1Xa/lZs2Zh9uzZ5o5JREREj6m0dhl7LlVhfn5+uH37NlxcXCCTWUA5topKS0tDQEAAbt++DVdXV6njEFk0vp8sgxAC6enp8PPzkzoKmdiMGTMwdepUzW2lUokHDx6gevXqJm+LWNr73dLyApaX2dLyAsxsDpaWF7C8zJaWF7C8zOWZ19B2GYtLVZiVlRV/EbYgrq6uFvGPjcgS8P1U8bm5uUkdgQzg6ekJuVyOxMREremJiYmoUaOGzvJ2dnY6p6x3d3cvz4gW9363tLyA5WW2tLwAM5uDpeUFLC+zpeUFLC9zeeU1pF3GAb2JiIiIyCi2trZo2bIlIiMjNdOUSiUiIyO1DpMjIiKiyo09l4iIiIjIaFOnTsWIESPQqlUrtGnTBp9//jkyMzMxatQoqaMRERGRmbC4RFTB2dnZITw8XOcwAiIqO76fiExvyJAhSEpKwsyZM5GQkIDmzZtj37598PHxkTSXpb3fLS0vYHmZLS0vwMzmYGl5AcvLbGl5AcvLXBHy8mxxRERERERERERkNI65RERERERERERERmNxiYiIiIiIiIiIjMbiEhERERERERERGY3FJaLHNGvWLMhkMs3F3t4ejRo1wqJFi6BUKstlnzKZDIsXLy6XbROZmvo94u/vr/c90bFjR8hkMowcOdLgbUZHR0Mmk+Hnn3/WTAsODsabb75pisjlKjo6GrNmzcLdu3eljkJEREREZBIsLhGZgIODA44ePYqjR4/i119/xeDBgzF9+nQsWrSoXPZ39OhRvPzyy+WybaLyYGNjg+TkZBw+fFhrekxMDI4ePQpnZ+fH3sf27dvx7rvvPvZ2ylt0dDRmz57N4hKRCSxbtgzBwcGwt7dH27Ztcfz48RKX/+mnn9CwYUPY29ujWbNm2Lt3r5mSqpQl78WLFzFo0CAEBwdDJpPh888/N1/QQsqSedWqVXjqqadQrVo1VKtWDT169Cj1OTG1suSNiIhAq1at4O7uDicnJzRv3hzfffedGdOqlPV1rPbjjz9CJpNhwIAB5RuwiLLkXb9+vdaPsOofYs2trI9xSkoKJk6cCF9fX9jZ2aF+/foV+v9F165ddR5nmUyGvn37Vsi8APD555+jQYMGcHBwQEBAAN5++23k5OSYKa1KWTLn5+djzpw5qFOnDuzt7RESEoJ9+/aZLevhw4fRr18/+Pn5QSaTYceOHaWuc/DgQTz55JOws7ND3bp1sX79+vINKYjosYSHhwsnJyed6QMGDBCtW7eWIBFRxaJ+j/Tv31+MHz9ea97ChQtF06ZNRUhIiBgxYoTB24yKihIAxE8//WTitOXvwIEDAoA4ceKE1FGILNqPP/4obG1txdq1a8XFixfFuHHjhLu7u0hMTNS7/N9//y3kcrlYtGiRuHTpkggLCxM2Njbi/PnzFTLv8ePHxbvvvit++OEHUaNGDfHZZ5+ZJWdhZc08bNgwsWzZMnHmzBlx+fJlMXLkSOHm5ibu3LlTIfMeOHBAREREiEuXLokbN26Izz//XMjlcrFv3z6z5DUms1pUVJTw9/cXTz31lOjfv795woqy5123bp1wdXUV8fHxmktCQoLZ8hqTOTc3V7Rq1Ur06dNHHDlyRERFRYmDBw+Ks2fPVtjM9+/f13qML1y4IORyuVi3bl2FzLtp0yZhZ2cnNm3aJKKiosRvv/0mfH19xdtvv22WvMZkfv/994Wfn5/Ys2ePuHnzpli+fLmwt7cXp0+fNkvevXv3ig8//FBEREQIAGL79u0lLn/r1i3h6Ogopk6dKi5duiS++uqrcv//xuIS0WMqrrg0fPhw0bx5c83tnJwcMWPGDBEYGChsbW1Fw4YNxaZNm7TWGTFihGjSpIk4cOCAaN68uXB0dBStW7cWJ0+e1FoOgPj00081t5VKpZg9e7bw8fERTk5O4oUXXhB//PGHACAOHDigtd4nn3wiwsPDhbe3t6hevboYOXKkyMjIMNGjQaRL/R758ccfhYeHh8jLy9PMe+KJJ8T8+fO1ikuXL18WQ4YMETVr1hQODg6iUaNGYvHixUKhUGjW01dcCgoKEhMnTtTa98qVK0VgYKBwcHAQPXr0EKdPnxYAtBpb6vW+/vprERgYKFxdXUX//v3FvXv3NMtkZGSIiRMnivr16wsHBwcRFBQkJkyYIFJSUrT2V9q21IWlohciKrs2bdpovecVCoXw8/MTCxYs0Lv8iy++KPr27as1rW3btmLChAnlmlOtrHkLCwoKkqS49DiZhRCioKBAuLi4iA0bNpRXRC2Pm1cIIVq0aCHCwsLKI55exmQuKCgQHTp0EKtXrxYjRowwa3GprHnXrVsn3NzczJROv7JmXrFihahdu7ZWe8XcHve1/NlnnwkXFxeztfHLmnfixImie/fuWtOmTp0qOnbsWK45CytrZl9fX/H1119rTRs4cKB4+eWXyzWnPoYUl95//33RpEkTrWlDhgwRoaGh5ZaLh8URmUhBQQEKCgqQnp6OnTt3Ytu2bXjhhRc081988UV88803eOedd7B792707t0br7zyCn799Vet7SQkJOCtt97Ce++9h61btyInJwfPP/888vPzi933V199hVmzZmHkyJGIiIhAnTp1MHbsWL3Lfv3117h+/To2bNiAmTNnYvPmzfj4449N8yAQlaBfv37Izc3F77//DgC4dOkSzp07h6FDh2otFxcXhwYNGmD58uXYu3cvxo8fjzlz5pT5dbpz50689tpr6NWrF7Zv344ePXrgxRdfLHbZnTt3YtmyZfjiiy9w6NAhTJo0STM/KysLCoUC8+bNw6+//oq5c+fi0KFDeg9FKGlbTz75JJYtWwYAWLduneZwWiIqm7y8PJw6dQo9evTQTLOyskKPHj2KfU8dPXpUa3kACA0NNct70Ji8UjNF5qysLOTn58PDw6O8Ymo8bl4hBCIjI3H16lV07ty5PKNqGJt5zpw58Pb2xpgxY8wRU8PYvBkZGQgKCkJAQAD69++PixcvmiMuAOMy79y5E+3bt8fEiRPh4+ODpk2bYv78+VAoFBU2c1Fr1qzB0KFD4eTkVF4xNYzJ26FDB5w6dUpzGNqtW7ewd+9e9OnTp9zzGps5NzdX55BOBwcHHDlypFyzGkuKzzzrctsyURWSmZkJGxsbrWlDhgzB9OnTAQAHDhzAzp078dtvv6FXr14AgJ49eyI+Ph7h4eF45plnNOs9ePAAhw4dQpMmTQAATk5O6NatG/7991906tRJZ98KhQILFy7EqFGjsHDhQgBAr169kJycjDVr1ugs7+vri02bNgEAevfujdOnT+Pnn3/WrEtUXhwdHdG/f3/8+OOP6Nu3L3744Qe0b98etWrV0lru6aefxtNPPw1A1djv1KkTsrKy8PXXXyM8PNzg/c2dOxfdu3fHqlWrAKg+UPPz8/HRRx/pLCuEwM6dO2FnZwdANS7S/PnzoVQqYWVlBS8vL6xYsUKzfEFBAWrVqoVOnTrh2rVrqF+/vkHbcnV1RePGjQEATZs2RatWrQy+P0T0SHJyMhQKBXx8fLSm+/j44MqVK3rXSUhI0Lt8QkJCueVUMyav1EyRedq0afDz89P5glMejM2bmpoKf39/5ObmQi6XY/ny5ejZs2d5xwVgXOYjR45gzZo1OHv2rBkSajMmb4MGDbB27Vo88cQTSE1NxeLFi9GhQwdcvHgRNWvWrJCZb926hT///BMvv/wy9u7dixs3buCNN95Afn5+mdoh5sxc2PHjx3HhwgW93wPKgzF5hw0bhuTkZHTq1AlCCBQUFOC1117DBx98YI7IRmUODQ3F0qVL0blzZ9SpUweRkZGIiIgwW9GxrIr7zEtLS0N2djYcHBxMvk/2XCIyAQcHB5w4cQInTpzAkSNH8MUXX2Dfvn0YN24cAOD333+Hh4cHunfvrunhVFBQgJ49e+LMmTNa/5T8/Pw0hSUAmi+id+7c0bvvO3fuID4+Hs8995zW9P79++tdvmiDqXHjxsVum8jUXnrpJfzyyy/Izs7Gjz/+iJdeeklnmZycHISHh6Nu3bqws7ODjY0NPvzwQ8THxyMjI8Og/SgUCpw5c8bg90WXLl00xSBA9b7Iz8/HvXv3NNO+++47tGjRAs7OzrCxsdEUe69du1bmbRERVXYLFy7Ejz/+iO3bt0sygLOhXFxccPbsWZw4cQLz5s3D1KlTcfDgQalj6ZWeno7hw4dj1apV8PT0lDqOQdq3b49XX30VzZs3R5cuXRAREQEvLy988803UkcrllKphLe3N7799lu0bNkSQ4YMwYcffoiVK1dKHc0ga9asQbNmzdCmTRupoxTr4MGDmD9/PpYvX47Tp08jIiICe/bsqdBHU3zxxReoV68eGjZsCFtbW7z55psYNWoUrKxYUlFjzyUiE7CystLqgdCxY0cUFBTgnXfewdSpU5GcnIwHDx7o9G5Si4+P1/x64+7urjXP1tYWAIo9e0J8fDwAwMvLS2u6t7e33uX1bT83N1f/HSMysdDQUNjY2GDmzJmIiorSe5jatGnTsGrVKoSHh6Nly5Zwd3fHL7/8grlz5yInJ8egM8slJSWhoKDgsd4XwKP33fbt2/Hqq69i/PjxmDdvHqpXr474+Hg8//zzOu/Nsr6HiajsPD09IZfLkZiYqDU9MTERNWrU0LtOjRo1yrS8KRmTV2qPk3nx4sVYuHAh9u/fjyeeeKI8Y2oYm9fKygp169YFADRv3hyXL1/GggUL0LVr1/KMC6DsmW/evIno6Gj069dPM02pVAIArK2tcfXqVdSpU6fC5NXHxsYGLVq0wI0bN8ojog5jMvv6+sLGxgZyuVwzrVGjRkhISEBeXp7mc70iZVbLzMzEjz/+iDlz5pRnRC3G5P3oo48wfPhwzTAezZo1Q2ZmJsaPH48PP/yw3As2xmT28vLCjh07kJOTg/v378PPzw/Tp09H7dq1yzWrsYr7zHN1dS2XXksAey4RlZtGjRoBUJ1K2MPDA15eXpreTUUvxX3hNYSvry8A1ZfpwthLgioiGxsbDBo0CEuXLkX37t11uusCqlOFT5gwAdOmTUOPHj3QqlUrWFuX7bcQLy8vWFtbm+x98dNPP6F58+b45ptv0KdPH7Rt2xbVqlUzaltE9PhsbW3RsmVLREZGaqYplUpERkaiffv2etdp37691vIA8McffxS7vCkZk1dqxmZetGgRPv74Y+zbt8+sh/6a6jFWKpVm+9GtrJkbNmyI8+fP4+zZs5rLc889h27duuHs2bMICAioUHn1USgUOH/+vKb9Wt6MydyxY0fcuHFDU7gDVL2UfX19y72wZGxmtZ9++gm5ubl45ZVXyjumhjF5s7KydApI6mKeEKL8wv7f4zzG9vb28Pf3R0FBAbZt21Zsr3ipSfGZx55LROXkwoULAFSV8R49emDRokWwtbU1+S94NWvWRI0aNfDLL79o/XPbsWOHSfdDZCpjx47FvXv3NIeNFpWdna3VeFMoFPjxxx/LtA+5XI4WLVrgl19+weTJkzXTjX1fFM0EQDN2WVmxJxORaUydOhUjRoxAq1at0KZNG3z++efIzMzEqFGjAACvvvoq/P39sWDBAgDA5MmT0aVLFyxZsgR9+/bFjz/+iJMnT+Lbb7+tkHnz8vJw6dIlzd9xcXE4e/YsnJ2dNT1tKlrmTz75RHOykODgYM14Vs7Ozgb1OjV33gULFqBVq1aoU6cOcnNzsXfvXnz33XdaY+xVpMz29vZo2rSp1vrq3rJFp1eEvIBq8PF27dqhbt26SElJwaeffoqYmJhiTzxTETK//vrr+PrrrzF58mRMmjQJ169fx/z58/HWW29V2Mxqa9aswYABA1C9enWzZTUmb79+/bB06VK0aNECbdu2xY0bN/DRRx+hX79+Wj3GKlLmf//9F3FxcWjevDni4uIwa9YsKJVKvP/++2bJm5GRodXjLyoqCmfPnoWHhwcCAwMxY8YMxMXFYePGjQCA1157DV9//TXef/99jB49Gn/++Se2bt2KPXv2lFtGFpeITECpVOLYsWMAHp19YO7cuWjcuDE6d+4MGxsb9OvXD71798b777+PJ554ApmZmbh48SJu3LiB1atXG71vuVyOGTNmYMqUKfDx8UG3bt1w4MAB7N+/HwB4HDBVOG3atCmxyNOzZ0+sWrUKjRs3hqenJ5YvX27Ur8hhYWHo378/xo0bh8GDB+PMmTPYsGEDgLK/L3r27ImJEyfi448/Rvv27bF3716dX4MMVb9+fcjlcqxduxbW1tawtrbmwN5ERhgyZAiSkpIwc+ZMJCQkoHnz5ti3b5+mR2RsbKzWe71Dhw7YvHkzwsLC8MEHH6BevXrYsWOH2b6UlzXv3bt30aJFC83txYsXY/HixejSpYvZxgQqa+YVK1YgLy9P62y5ABAeHo5Zs2ZVuLyZmZl44403cOfOHTg4OKBhw4b4/vvvMWTIkHLPamxmqZU178OHDzFu3DgkJCSgWrVqaNmyJf755x/NmKIVMXNAQAB+++03vP3223jiiSfg7++PyZMnY9q0aRU2MwBcvXoVR44c0ZyV15zKmjcsLAwymQxhYWGIi4uDl5cX+vXrh3nz5lXYzDk5OQgLC8OtW7fg7OyMPn364LvvvtMZDqG8nDx5Et26ddPcnjp1KgBgxIgRWL9+PeLj4xEbG6uZX6tWLezZswdvv/02vvjiC9SsWROrV69GaGho+YUURPRYwsPDBQDNxdraWtSqVUu88cYbIjExUbNcbm6umD17tqhXr56wtbUVXl5eolu3bmLjxo2aZUaMGCGaNGmitf2HDx8KAGLdunWaaQDEp59+qrmtVCrFrFmzhLe3t3B0dBTPPfec2LJliwAgzp49W+x6Qgjx2WefCf4roPIUHh4unJycSlwmJCREjBgxQgghREJCghgwYIBwcXERPj4+Ytq0aWLVqlUCgEhKShJCCBEVFSUAiJ9++kmzjaCgIDFx4kSt7a5YsUIEBAQIe3t70aVLF/H7778LAGLHjh0lrrd9+3YBQERFRQkhhCgoKBDvvPOO8PLyEi4uLuKFF14Qx44dMyhD0W0JIcTKlStF7dq1hbW1Nd9/RERERGTxZEKY4aBGIjK7jz76CEuWLMH9+/fLbdA2IkuzZs0ajB07FlFRUQgODpY6DhERERFRpcDD4ogqgcuXL+P7779Hhw4dYGtri4MHD2Lx4sV4/fXXWViiKuvBgweYPXs2unfvDhcXF81ppvv378/CEhERERGRCbG4RFQJODo64ujRo1ixYgXS09Ph7++P9957zyzjGxBVVDY2Nrh58yY2b96MlJQUeHl5Yfjw4fjkk0+kjkZEREREVKnwsDgiIiIiIiIiIjJaxTn1ABERERERERERWRwWl4iIiIiIiIiIyGgsLhERERERERERkdFYXCIiIiIiIiIiIqOxuEREREREREREREZjcYmIiIiIiIiIiIzG4hIRERERERERERmNxSUiIiIiIiIiIjIai0tERERERERERGQ0FpeIiIiIiIiIiMhoLC4REREREREREZHRWFwiIiIiIiIiIiKjsbhERERERERERERGY3GJiIiIiIiIiIiMxuISEREREREREREZjcUlIiIiIiIiIiIyGotLRERERERERERkNBaXiIiIiIiIiIjIaCwuERERERERERGR0VhcIiIiIiIiqsIOHjwImUyGWbNmlds+ZDIZunbtavDys2bNgkwmw8GDB0vdTnHLEpH5sLhERBYrOjoaMpkMI0eO1JretWtXyGQyaUKVUXBwMIKDg6WOgZEjR0ImkyE6Orpctl/cc0VERESPqD8vC19sbW0REBCAYcOG4dy5c1JHtBhsexCZF4tLRFSqqtbQKe9Ci7HUvyq+9tprUkchIiKiclSnTh2Eh4cjPDwcb731FoKCgvDDDz+gTZs2+Pvvv6WOZxZvvvkmLl++jDZt2ph0WSIqH9ZSByAiy1GnTh288sorAICMjAwcO3YMP/zwAyIiIhAZGYmOHTtKnFBl48aNyMrKkjoGERERkVHq1q2rc4haWFgY5s2bhw8//LBKHP7l6ekJT09Pky9LROWDPZeIyGDqhs6sWbOwePFiHDlyBB9++CFyc3Px4YcfSh1PIzAwEA0bNpQ6BhEREZHJTJo0CQBw4sQJAI/GHoqLi8Orr76KGjVqwMrKSqvwtG7dOrRt2xbOzs5wdnZG27ZtsX79+hL3c+TIEXTt2hUuLi5wd3fHoEGDcOPGDZ3lDhw4gNGjR6NBgwaa7bdq1Qrffvttidu/c+cOXnrpJXh6esLR0REdO3bE/v37dZYryzhKRZddv349atWqBQDYsGGDVu/7gwcPIiwsDDKZDFu3btW7vbVr10Imk2HBggWl7puIVFhcIqLHUrShAxjW2Dl8+DD69esHT09P2NnZoV69eggLC9Pb40ihUOCTTz5B3bp1YW9vj7p162LBggVQKpV6M5U05tIvv/yCXr16oXr16rC3t0dwcDCGDx+OCxcuAFCNgbRhwwYAQK1atTQNkaIDR0ZFRWHs2LEIDAyEnZ0dfH19MXLkSMTExBS739atW8PBwQE+Pj4YN24cHj58qP9BNYG7d+8iPDwc7dq1g7e3N+zs7BAcHIw33ngD9+7dK3Y9pVKJRYsWoV69erC3t0etWrUwZ84c5Ofn612+LM8jERERPb7CbZz79++jffv2OHfuHIYOHYrx48fD1dUVAPDWW29h9OjRiIuLw5gxYzBmzBjExcVh1KhRmDx5st5tHzt2DE8//TTc3NwwadIkdOnSBdu3b0eHDh1w69YtrWU/+eQTHD58GK1bt8abb76JV155BcnJyZgwYQLeeecdvdt/+PAhOnbsiOvXr2Ps2LF46aWX8N9//6F3797YsWOHaR4gAM2bN9fcx5CQEM0hhuHh4QgODsa4ceNgZWWF1atX611/1apVsLa2xqhRo0yWiaiy42FxRGQSRYs56saOh4cHhg4dipycHE1jZ8WKFZg4cSLc3d3Rr18/eHt74+TJk5g3bx4OHDiAAwcOwNbWVrOt8ePHY+3atahVqxYmTpyInJwcLF26FP/880+ZMr7zzjtYunQpPDw8MGDAAHh7e+P27dvYv38/WrZsiaZNm2LKlClYv349/vvvP0yePBnu7u4AoDXo9r///ovQ0FBkZmbi2WefRb169RAdHY1Nmzbh119/xdGjR1G7dm3N8hs3bsSIESPg6uqK4cOHw93dHbt370aPHj2Ql5endV9N5fDhw1iyZAmefvpptG3bFjY2Njhz5gxWrFiB3377DadPn4abm5vOelOmTMHff/+NF198Ec7Ozti1axfCw8Nx7tw5/Pzzz1rLlvV5JCIiIuMtX74cALTGFbpw4QJGjRqFVatWQS6Xa6YfPnwYX331FRo1aoSjR49qPvNnzZqFdu3a4csvv8QLL7yAp556Smsfv/32G1auXIkJEyZopn3zzTd47bXXMHnyZOzatUszfcWKFZreQWoFBQXo06cPvvjiC0yePBmBgYFa88+dO4dhw4bh+++/17QdJ0+ejNatW2P8+PEIDQ2Fg4PD4zxMAFTFpSlTpuCLL75A8+bN9Z4FLzQ0FPv27UN0dLRWO+/ixYs4duwYBgwYgBo1ajx2FqIqQxARlSIqKkoAEKGhoTrzZs6cKQCIbt26aaYBEADEqFGjREFBgdbyFy9eFNbW1iIkJEQkJydrzVuwYIEAIBYvXqyZduDAAQFAhISEiIyMDM30O3fuCE9PTwFAjBgxQms7Xbp0EUX/ve3atUsAEM2aNdPZb35+vkhISNDcHjFihAAgoqKidO5vXl6eCA4OFi4uLuL06dNa8/766y8hl8vFs88+q5mWmpoqXF1dhZOTk7h69arWdjp37iwAiKCgIJ396KN+LCZMmFDqsomJiSI9PV1n+oYNGwQAMXfuXK3p6vvs5eUlbt++rZmem5uryfnzzz9rppf1eVS/hoo+V0RERPSI+vOyTp06Ijw8XISHh4t3331XPPXUUwKAsLe3F//8848QQtXesrW1FUlJSTrbGT16tAAgtmzZojNv06ZNAoAYPXq0Zpq6jVG/fn2hUCi0llcoFKJevXpCJpOJe/fulXoftm3bJgCI9evXa00HIORyuYiOjtZZZ8yYMTptjfDwcAFAHDhwQGc7Xbp00Zqmb9nS2h6//PKLACDCwsK0pk+ZMkUAEHv27Cn1vhLRIzwsjogMduPGDc2YS++99x46d+6MOXPmwN7eHvPmzdNa1tbWFosWLdL6FQ1Q/fpVUFCAr776CtWrV9ea9/7778PLyws//PCDZtrGjRsBADNnzoSTk5Nmur+/f7FduvVR/9r3xRdf6OzX2toaPj4+Bm1n9+7diI6OxnvvvYcWLVpozevUqRP69++PvXv3Ii0tDQCwY8cOpKWlYfTo0ahfv75mWRsbG53HzJS8vb3h7OysM3348OFwdXXVO7YBoPr1sGbNmprbtra2mpyFx2go6/NIREREhrt58yZmz56N2bNn44svvkBUVBSGDRuG48ePo3379prlatWqpXcg6zNnzgCAzmH9ANCtWzcAwNmzZ3XmdezYEVZW2l8Rrays0LFjRwgh8N9//2mmp6enIzw8HCEhIXB2dtYMJTBo0CAAqkP0iwoMDERQUJDOdHUPKnVuc+jbty/8/f2xbt06KBQKAEBeXh6+++47BAQEoHfv3mbLQlQZ8LA4IjKYuqEDqIojPj4+GDZsGKZPn45mzZppLVtcY+fYsWMAVN2uIyMjdebb2NjgypUrmtvqRkzRbtvFTSvO8ePHYWdnhy5duhi8jj7q/FevXtXbxTohIQFKpRLXrl1Dq1atSszfvn17WFuX37/hiIgIfPPNNzh9+jQePnyoaTgB+ht8peUs3OAr6/NIREREhlMfslWa4n4cS0tLg5WVFby8vPSuI5PJND+EGbI99fTU1FQAqiJM165dcfr0abRo0QLDhw9H9erVYW1tjejoaGzYsAG5ublGb98c5HI5xo4di9mzZ+PXX3/Fs88+i+3bt+P+/ft48803dYpsRFQyFpeIyGCGNnSA4hsPDx48AACDe+2kpqbCyspKb6HK0N5G6u34+/s/dkNBnX/Tpk0lLpeZmanZL6DqSVSUXC7X6fVjKkuWLMG7774LLy8v9OrVCzVr1tSMYfD555/rbfAB+h9Tdc7CDb6yPo9ERERkesWdwMTV1RVKpRJJSUk6bZB79+5BCKEZC7OwxMREvdtTT1eP3fTLL7/g9OnTGDNmjM6g2D/++KPm5CjGbt9cxo4di7lz52LVqlV49tlnsXr1alhZWWH06NFmzUFUGbC4RETloqTGDqD6Rc3FxaXU7bi5uUGpVCI5OVnn17fiGij6uLu7a3oVPU6BSZ1/165dePbZZ0tdXt1I0neGNoVCgfv378Pf39/oPPoUFBTg448/hq+vL86ePavVqBRCYNGiRcWum5iYiAYNGujNWbjwVNbnkYiIiMynRYsWOHPmDA4ePIgXX3xRa5767L3NmzfXWe/vv//WaSsplUr8888/kMlkCAkJAaDqzQ4A/fv319nGX3/9VWyu2NhYxMTE6Bwap16n6JADj0M9NEPhnttF1axZE3379sXevXvxzz//IDIyEr1799YZiJyISse+fkRkVm3btgXw6LCq0qgbMfoaKiU1Xopq06YNcnNzcejQoVKXLakxos5/9OhRg/ZbUv6jR4+ioKDAoO2URXJyMlJTU9G+fXudXytPnjyJ7OzsYtctKWfhBl9Zn0ciIiIynxEjRgAAZs+erXX4W2pqqmaIA/UyhV27dg2rVq3SmrZq1Spcu3YNffv21fzQpy4OHTlyRGvZQ4cO6axfmEKhwAcffAAhhGbauXPn8N1338HLywt9+vQpy90sUbVq1SCTyXD79u0Sl5swYQIKCgowePBgCCEwbtw4k2UgqkpYXCIis3rjjTdgbW2NSZMmITY2Vmd+SkqK1tg+w4cPBwDMmTNHc6gZAMTFxeGLL74weL8TJ04EoBqwWn1Il1pBQYFWLygPDw8A0NsY6d+/PwIDA7F06VIcPnxYZ35+fr5WQ6t///5wdXXF2rVrce3aNa3lwsLCDM5fFt7e3nBwcMDp06eRlZWlmf7w4UNMmjSpxHW/+OIL3LlzR3M7Ly8PH374IQBg5MiRmullfR6JiIjIfDp37oxJkybh0qVLaNq0Kd5++21MmTIFTZs2xZUrV/DWW2+hc+fOOuuFhobirbfeQv/+/fHBBx+gf//+eP311+Hp6anV7urXrx+Cg4OxaNEi9O3bF9OmTcOAAQPw9NNP6+3NpPbEE0/gyJEjaN26NaZPn44xY8agQ4cOKCgowLfffqs5hN8UnJ2d0bp1axw+fBjDhw/HnDlzMHfuXMTExGgt17t3bwQFBeHu3buoUaMG+vXrZ7IMRFUJD4sjIrNq2rQpli9fjtdffx0NGjRAnz59UKdOHaSnp+PWrVs4dOgQRo4ciZUrVwJQndFk1KhRWLduHZo1a4bnn38eubm52LJlC9q1a4fdu3cbtN8+ffrg3XffxeLFi1GvXj08//zz8Pb2RlxcHCIjI/Huu+9iypQpAIDu3btj8eLFGD9+PAYNGgQnJycEBQVh+PDhsLOzw88//4xnnnkGXbp0Qffu3dGsWTPIZDLExMTgr7/+QvXq1TWDWbu5ueHLL7/EyJEj0bp1awwdOhRubm7YvXs3HBwc4OvrW+bH8MCBA1qFnsI6deqEsWPH4o033sCSJUsQEhKCfv36IS0tDb/++iuCgoLg5+dX7LbbtWuHkJAQDBkyBE5OTti1axeuXr2KgQMHas7+ApT9eSQiIiLz+vLLL9GiRQusWLEC3377LQCgSZMmmDNnDkaNGqV3nXbt2iEsLAxhYWH48ssvIZfLMWDAACxatAi1a9fWLOfs7Iw///wT7733Hg4fPoyDBw+iSZMm2LRpE3x8fPDzzz/r3X61atWwZ88evPvuu1i1ahWysrLQokULzJ49Gz179jT5Y/Ddd9/h7bffxu7du5GamgohBDp16qR1WJ6VlRWGDx+OuXPnYuTIkeV6shWiSk0QEZUiKipKABChoaEGLQ9AdOnSpcRljh8/LoYOHSr8/PyEjY2N8PT0FE8++aSYPn26uHz5stayBQUFYsGCBaJ27drC1tZW1K5dW8yfP1/cuHFDABAjRozQWr5Lly6iuH9v27ZtE926dRNubm7Czs5OBAcHi+HDh4sLFy5oLbdo0SJRr149YWNjo/f+3LlzR0yePFnUq1dP2NnZCVdXV9GoUSMxduxYERkZqbPf7du3i5YtWwo7Ozvh7e0txo4dKx48eCCCgoJEUFBQiY+V2oEDBwSAEi/qxyIvL0/MmzdPky8wMFC88847Ij09Xe8+R4wYIQCImzdvioULF4q6desKW1tbERQUJGbNmiVyc3P1ZjL0eVS/hoo+V0RERERS69u3r5DJZOL69etSRyGyWDIhCh3wSkRERERERFRFqA8d7NmzJ3777Tep4xBZLPb5IyIiIiIioipl8+bNuHr1KjZu3AgACA8PlzgRkWVjcYmIiIiIiIiqlG+//RZ//fUXgoKCsGbNGnTo0EHqSEQWjYfFERERERERERGR0aykDkBERERERERERJaLxSUiIiIiIiIiIjIai0tERERERERERGQ0FpeIiIiIiIiIiMhoLC4REREREREREZHRWFwiIiIiIiIiIiKjsbhERERERERERERGY3GJiIiIiIiIiIiMxuISEREREREREREZjcUlIiIiIiIiIiIyGotLRERERERERERkNBaXiIiIiIiIiIjIaCwuERERERERERGR0VhcIiIiIiIiIiIio7G4RERERERERERERmNxiYiIiIiIqjyZTAaZTIaDBw+aZHvBwcGQyWRYv369SbZH5auk59/Urw2iyojFJSJ6bLNmzdJ86Ba+2NnZwc/PD6GhoVi9ejXy8/MN3uahQ4cwYcIENGrUCO7u7rC3t0dAQAD69u2LFStWIDs72+BtKRQKbN26Fa+++irq168Pd3d32NrawtvbG506dcKMGTNw4cIFY+66lnPnzmHatGlo06YNfHx8YGtrCzc3NzRu3BgjRozAL7/8UqbHgIiIqCIq7nPf3t4eNWvWxHPPPYetW7dCCCF1VDJSebTtCLh37x4WLlyInj17ombNmnBwcICTkxOCg4MxYMAAfPvtt0hJSZE6JpFxBBHRYwoPDxcABADh4+OjuTg6OmqmAxCtWrUSDx48KHFbycnJok+fPlrr2dnZCTc3N61p/v7+4vfffy8129GjR0X9+vW11rWxsREeHh7CyspKa/rAgQNFbm5ume9/WlqaGDZsmJDJZJptyWQy4e7uLuzs7LT2UadOHXHs2LEy74OIiKiiKO5z397eXusz75lnnhE5OTlSxzVYgwYNRIMGDcS///5rku11795dNGjQQERERJhke+ZkyradpVDfpwMHDpRpniGUSqWYN2+ezuPn7OwsXFxctKa5ubmJNWvWPN6dIZIAey4RkUklJCRoLpmZmYiJicG4ceMAACdPnsRbb71V7LqJiYlo164d9u7dC7lcjkmTJuHixYvIyclBSkoKHj58iHXr1iEgIABxcXHo06cPtm7dWuz2du3aha5du+LatWuoXr06FixYgGvXriEvLw/3799HXl4eTpw4genTp8PV1RURERHIysoq0/19+PAh2rdvj82bNwMAhg4dikOHDiEnJwcPHz5ETk4O4uLisHr1ajzxxBO4efMmjh49WqZ9EBERVVRFP/cvXLiAnj17AgB+/fVXhIWFSZzQcFeuXMGVK1fQpk0bk2wvMjISV65cwfPPP2+S7Unlcdp2BAghMHz4cHz44YfIyspC27ZtsW3bNjx8+BDp6elIS0tDamoqtm/fjn79+iE1NRU7d+6UOjZR2Uld3SIiy1f4163idO/eXQAQtra2Ij09XWe+UqnULGNjYyN27txZ7LaSk5NFSEiIACCcnJzE5cuXdZa5du2acHV1FQBE48aNxe3bt0u8D/fv3xf9+/cXDx8+LHG5op555hkBQFhbW4utW7eWuKxSqRTLly8XK1asKNM+iIiIKpLSPvezs7NF3bp1BQDh4uIi8vPzzZyQHpcp2naWBuXUc2nhwoWa9adMmSKUSmWJyx86dEhMnDixzPshkhp7LhGRWfTu3RsAkJeXh+vXr+vM3717N/78808AwIcffoh+/foVu63q1avjp59+gr29PTIzM/HRRx/pLBMWFoa0tDTY29tj+/btqFmzZon5PDw8sGPHDri5uRl8n3799Vf8+uuvAICZM2di8ODBJS4vk8nw+uuvY/z48Zpp0dHRmnEMoqOji123uEFBi65/8+ZNjB8/HrVq1YKdnR2Cg4Nx79492NjYQCaTlfpL2MyZMyGTyVC3bl298//++2+88sorCAoKgr29Pdzc3NCmTRt88sknyMjIKHHbRERUNdjb22s+E9PT03HlyhUAhn1mFaZUKrFp0yb06dNHM5ahl5cXevXqhR9++KHUMZ0uX76MiRMnonHjxnBxcYGzszMaNGiAoUOHYtu2bVAqlVrLlzRo88OHDzFz5kw8+eSTcHV1ha2tLWrUqIEnnngCr732GiIjI3XWKW1Ab4VCgbVr16J79+7w9PSEnZ0d/P39MXjw4BIHju7atStkMhlmzZoFIQRWrVqFtm3bwtXVFS4uLmjfvj2+//77Eh8bUyitbQeonv+FCxeiffv28PDwgJ2dHQICAjB06FCDenL//vvvGDp0KIKCguDg4AAPDw888cQTmDRpks76SqUSkZGReOutt9CuXTvUrFkTtra2qF69Orp06YKVK1eafYyo5ORkfPzxxwCAp59+GkuXLoVMJitxnc6dO+PLL7/UmmbI4PAjR46ETCbDyJEjdeYVXj8jIwMzZ85Es2bN4OLionk/hoSEQCaTYerUqSXm+/PPPyGTyWBlZYXY2Fid+dHR0ZgyZQqaNGkCZ2dnODo6omHDhpg8ebLe5akSkbq6RUSWz5Bftz755BPNMidOnNCZ37t3b80vnIb++jVq1CgBQFhZWYn4+HjN9ISEBM14SmPGjCn7HTKQemwoNzc3kZGRYdQ2oqKiNI9LVFRUscsFBQUJAGLdunXFrr9p0ybh7OwsAAhHR0fh5OQkgoKChBBC9O3bVwAQL7zwQrH7UCqVolatWgKAmDVrltY8hUIh3nrrLZ1xAuRyueZ2gwYNRHR0tFGPAxERWQ5DPveXLVumWebvv/8WQhj+mSWEqkdx586ddcaiKXz7ueeeK3asxIULF2qNrWhvb68z3mLR3srq6UV7p9y+fVsEBgZq5ltZWYlq1appfQZ26dJFJ0Nxn91CCJGSkiK6du2qWV8ulwt3d3et8RvfffddvfetS5cuAoAICwsT/fv31/SgVvfYVl9mzpxZ7PNTGlO07c6cOSNq1qypdR8Ljy8kk8nE/Pnz9W47MzNTDB48WOv+uLi4aL0GQkJCtNYp/PpSt1OKvmaeeuopkZWVpXefxT3/pc0ryaJFizTr/vXXX2Vat7CSXktqI0aMEADEiBEjil1/8eLFmrFIbW1thbu7u6YN+umnnwoAokaNGqKgoKDY/YwcOVIAEF27dtWZ9/3332uNN2pnZyccHBy0nsPffvvNmIeALAB7LhGRWfz2228AVL8K1qpVS2teQUEB/vrrLwBAr1694OzsbNA2Bw4cCED1S9WhQ4c00w8cOKD5NbK8xjkoKCjA4cOHAQA9e/aEk5NTueynLCZMmIAmTZrgxIkTyMzMREZGBn7//XcAwKuvvgpANQ5VcWch+fvvvxEVFQWZTIbhw4drzQsPD8eXX34Jb29vLFu2DPfv30d6ejqys7Nx4MABtGjRAlevXsXAgQN1fgkmIqKqp3BvXA8PD535JX1mKRQKDBw4EIcPH0bz5s2xa9cuZGZmIiUlBRkZGdiwYQO8vb2xc+dOTJs2TWfbK1aswPTp06FUKvHcc8/hzJkzyM7O1nx2/f777xgyZAisrAz7KjRr1izExsYiODgY+/fvR15eHh48eIDc3FxER0djxYoVaNeuXZkenzFjxuDgwYOwtbXFl19+ibS0NDx8+BB3797F6NGjAQCLFy/GypUri93GsmXLcPDgQaxfv14zbs/t27c1vb/nzp1bbI8iUyipbRcfH4/Q0FDcuXMHAwcOxMmTJ5GdnY20tDQkJibio48+glwuxwcffIAdO3bobHvUqFH46aefYGVlhWnTpuH27dtIS0tDSkoKkpKSsGnTJrRv315rHWtra7z88svYuXOn5rlOSUlBeno61q1bBz8/P/z111/48MMPy+0xKUrdo83LywudOnUy236LM2vWLKSlpWH79u3IyMjAw4cPcfv2bXh7e+Pll1+GXC5HQkIC/vjjD73rZ2dnY9u2bQAetS3V/vjjD7z66qtQKBR4//33ERUVhezsbGRmZuLKlSsYPHgw0tPTMXjwYPZgqqykrm4RkeUr6detmJgYMW7cOK1fGYu6fv26Zv7cuXMN3u/t27c164WFhWmmh4WFaabHxcUZd6dKcePGDc0+5s2bZ/R2TNlzKSgoqNheX9nZ2Zpf77755hu9y4wfP14AEJ06ddLZh1wuFw4ODuLs2bN6101LS9P8Orl9+/Zi7wcREVm+0nq1pKamCj8/PwFAeHh4CIVCIYQw/DNr48aNAoBo2LChSElJ0bvMyZMnhUwmE7a2tiIxMVEz/cGDB5reMUOHDi11fJvC1NmK9k5p1KiRACA2b95s8LaEKP6z+9ixY5p9FfeZPGjQIAFAeHp6iuzsbK156p5LAMSff/6ps25OTo7m8S9Lu6qwx23bjR49WgAQw4YNK3YfS5cu1dsDaf/+/ZptL1++3Kj8+pw4cUIAqvE6iz6mQpRPzyV126hnz55GplYxVc8luVwuTp8+Xew2QkNDBQDx0ksv6Z2/efNmAUA4ODiItLQ0zXSFQiHq1atX4mtaCCGee+45AUBMnjy52GXIcrHnEhGZVI0aNTQXJycnBAUFYdWqVQCAhg0bYvny5Trr3L9/X/N39erVDd6Xp6en3m0U/lvfr6WmYI59lNWbb75ZbK+vwuNffPfddzrzc3NzNWfeK9praf369VAoFOjduzdCQkL0bt/FxQUDBgwA8OiXTCIiqlpSUlIQGRmJ7t274+7duwCAyZMn6+0hVNJn1po1awAAr7/+erFjIbZs2RJNmjRBXl4eDhw4oJn+888/Iz09HTY2NgaNb2MId3d3AKreOKawZcsWAEDNmjUxduxYvcuox+lJTk4uthdJx44d0a1bN53pdnZ2CA0NBQCcO3fusfOWtW2Xk5OjOYuuvp5lauqeL//99x8SExM109euXQsAaNq0KV5//fXHzq/WqlUreHt7IzMzE2fPnjXZdkuibi9WlLZi79690aJFi2Lnq9uAO3bsQHp6us58dRtywIABcHFx0Uw/fPgwrl+/Dk9Pz2Jf08Cj55xtxcrJWuoARFS5FG4cFPbqq6/im2++gb29vZkTVR0dO3Yscf6rr76K1atXaw5/K9yFfffu3UhJSYG9vT1efPFFrfX+/vtvAKpBNWvUqFHs9tUDesfExBh7F4iIyMKUVLx55ZVXij0EqbjPLIVCgWPHjgFQHcIzf/78Yrf/4MEDANqfO//88w8AVfHJ19e35PAGevbZZ3H06FFMnz4dV65cwcCBA9GhQwe4uroatb2TJ08CALp161bsoXmNGjWCv78/4uLicPLkSb0nOmnbtm2x+/Dz8wPw6DF6HGVt2506dQo5OTkAVMMdGCImJgY+Pj4AHj2Hzz77bJmz5uXlYe3atYiIiMCFCxdw//595OXl6Sx3586dMm+7Miitrfj888/DxcUF6enp2LZtm9bg4ImJiTrDLaip24qpqama154+6ueCbcXKicUlIjIp8f8ztwghkJCQgJ07d2L69OnYuHEjmjVrhnfffVdnncK9lQr3CCpNcnKy3m0U/vvBgwclfsgZq+g+KgJvb+8S53fq1Am1atVCVFQUvv/+e62z7Kl/ierXr5/mF1o19a/PmZmZyMzMLDVHVlZWGZMTEZGlUhcEAFWPGU9PT7Ro0QIvv/yy3l41asV9ZqnHMgJUZ2gzROHPnYSEBABAUFCQQesa4r333sN///2HrVu3YtWqVVi1ahVkMhmaNGmC3r17Y+zYsWjQoIHB27t37x4AwN/fv8Tlatasibi4OM3yRRXuOVKUtbXqa17Rs6O1bt0at2/f1lm+Q4cOiIiI0Lutsrbt1O0GoPjCVFGmeA7v3buHHj164Pz585pp9vb28PT0hFwuBwAkJSVBqVQa1J4xherVq+POnTsW01Z0dHTEoEGDsH79enz33XdaxaUffvgBCoUCNWrUQM+ePbXWUz/n+fn5Bj3n2dnZZQ9PFR4PiyOiciGTyeDr64sJEyZg+/btkMlkeP/99/Hnn3/qLBsUFKQZEPv06dMG7+PMmTOav5s0aaL378LLmFJQUJCmO3957aOs1A2n4hQeqLvwoXH379/H3r17AegeEgeofkUGVF3bhRClXko6fTIREVUuCQkJmktMTAxOnTqF1atXl1hYAor/zFJ/5gDAr7/+atDnzqxZszTrmOIwuKJsbGywZcsWnD17FjNnzkT37t3h6OiICxcuYPHixWjSpAmWLFli8v2Wh6SkJCQmJupcDCl+GNq2K/wcZmdnG/Qcdu3aVWs/xnj77bdx/vx5VK9eHWvXrkV8fDyys7ORlJSkeY2qf3BUF8zKm7pNaq7D8EpTWlsReNQr6eDBg1qFSHXbcdiwYTrbUT/nbdu2Nej5NtfjT+bF4hIRlbuuXbti+PDhEEJg0qRJWo0OQNVoe+qppwCoDr3Sd4y3Pupf2KysrLQaJYW7mW/fvt0E90CXtbU1OnfuDEB1dgxjfwFT/7IIQNOFXJ/U1FSjtl+Uunh0/fp1zWEHW7ZsQX5+Pry8vPDMM8/orKM+FI5dmImIqLxVr15d89lozOdOeX5mhYSEYPbs2YiMjERKSgr279+Pzp07Q6FQaHo3GULde6S0Q7PU80vrbVIW0dHRJvlhqKS2XeFD6M31HObn52vahV9//TVGjRqlcyi/QqHQ6vVuDk8//TQAVVHvyJEjRm9H/Z4wR1uxa9euCAgIgFKpxKZNmwAAly5d0vwAXPSQOIBtRVJhcYmIzGLmzJmQy+W4dOkSNmzYoDNfPWBjRkYGli5dWur2rl+/jh9//BGA6vjwwg0IHx8fDBo0CACwefNmXLt2zeCcZfklZeLEiQBUH+aGZFZTKpWav6tVq6b5W183dQC4du0aUlJSDN5+SerWras5da/6Fyj19UsvvaRV7FJTH5+/f//+Ehs1REREj8vGxgZt2rQBAOzatavM63fo0AGAalwjUw3ArY+1tTWefvpp7NmzB3Z2dhBCYP/+/Qat26pVKwDAgQMHtNoEhV25cgVxcXEAVIeyVUTFte1at24NW1tbAI/3HJZl3aSkJE0bpbgBq48cOWL2dsyoUaPg6OgIQDWGmKHtzKKvC3V7sbi2olKp1Izl9bhkMhleeeUVALptxSeeeELvyV3UbcWEhAST5SDLw+ISEZlFnTp1MGTIEACqM6AUHQOgX79+mt5H8+bNw+7du4vd1v379zF48GDk5OTA0dFRc0aVwubOnQtnZ2dkZ2dj4MCBmgZacR4+fIhBgwaV6VefPn36aAaqnDNnDn7++edS1/n22281Z1gBACcnJ9SpUwcAsG3bNr3rzJs3z+BMhlD/4rRlyxZcvHhR04NJ3y9RADB69GhYW1sjOTkZ4eHhJW47Ly9PM7A3ERGRMcaPHw8A2Lt3r+aw7eIUPZxr8ODBcHV1RUFBAd5++22THH6jHgNKHzs7O80hQsUNzl3U0KFDAQBxcXFYvXq13mVmzpwJQHVm3B49epQlrtkU17ZzcnLCsGHDAACffPIJYmNjS9xO0edwzJgxAICLFy9ixYoVBmVxdXXVHE6nrwdZQUFBsYPLlydPT0+EhYUBACIjI/HOO++U+pr8+++/MXnyZK1p6oLO9u3b9a6/YcMGkw5Srm4TXrp0CSdPntT0YCqurditWzfUrVsXgOrwRH2DqBdWUcagIhMTRESPKTw8XAAQpf1LOX/+vJDJZAKAWLFihc78+Ph4Ubt2bQFAWFtbi7feektcunRJMz8lJUWsX79eBAYGCgBCLpeLzZs3F7u/7du3C1tbWwFAeHp6ioULF4rr169r5hcUFIjTp0+Ljz76SLi7uwsA4uHDh2W678nJyaJRo0YCgJDJZGLYsGHi8OHDIi8vT7PM3bt3xfr168WTTz4pAIjPPvtMaxthYWECgLCxsRHLli0TWVlZQgghYmNjxZgxY4SdnZ1wdHQUAMS6deu01o2KitI89lFRUQZlfvDggeZxadWqlQAgGjduXOI6s2fP1uxn+PDh4vz585p5+fn54syZM2L27NkiICBA/PXXXwblICIiy2To535Rhn5mFRQUiB49eggAwtbWVnz88cciLi5OMz8jI0P8+eef4o033hBubm46669cuVKzn/79+4szZ85o5mVmZordu3eL5557TqSmpmqtp17nwIEDWtN9fHzE9OnTxdGjR0VOTo5m+vXr18XgwYMFAGFlZSUuXryotV5QUJDez24hhBg0aJDm/n311VciMzNTCKFqC40dO1aTRV97qUuXLgKACA8PL+YRfPQcdenSpdhlSvK4bbu7d+8KPz8/AUD4+fmJjRs3irS0NM38e/fuiZ9//lkMGDBA9OrVS2e7Q4cO1Tyu06dPF7dv39bMS0pKEqtWrRKjR4/WWqdTp04CgPD39xeRkZFCoVBoMvbs2VPY2dkJJyenYp+T4p7/0uaVRqlUiiFDhmi20b59exEREaH1+ktLSxO7du0Szz//vJDJZKJ///5a29i/f79m/bFjx4rk5GQhhBCpqali6dKlwtbWVnh4eAgAYsSIEToZSnotFkfdRlRfy+Vycffu3WKX379/v7C2thYARNu2bcX+/fu12sM3b94UK1asEK1atRIff/yxwTnIcrC4RESPrSyNzP79+wsAombNmloNNLV79+6J0NBQzfYACHt7e03xR33x9fUVv/76a6n7O3LkiKhbt67WuuoPYCsrK800mUwmXnrpJa0PQUOlpqaKF198UdO4Um+vWrVqwt7eXmvfjRo1EidPntRaPz09XTRu3FizjJWVleb+2tjYiB9++KHYRoExxSUhhBg4cKBWrgULFpS4vFKpFB999JHWfXRwcBDVq1cXcrlca1tHjhwxOAcREVme8i4uCaH6bH322We1Pl9cXV2Fu7u71meRtbW13vXnz5+v9Tnv4OCg89lf9Ael4goIhTNYWVnpfL7LZDKdH46EKPkLfUpKiqZIpL4f1apV07pv7777rt77VpGKS0IU37a7dOmSqF+/vtZj5+HhoSnwqC89evTQ2WZmZqZOW8XV1VW4ublpboeEhGitc/LkSa1t29nZCRcXF83ju3HjxhKfk/IqLgmhakfNnj1bODg4aN0nFxcXTUb1xcPDQ2zcuFFnG8OHD9dazt3dXfN6njRpkhgxYoRJi0tffvml1v5CQ0NLXWf79u1a98fGxkZUr15d2NnZaW1r7ty5Bucgy8HD4ojIrNRdku/cuYNvvvlGZ76Xlxf27duHP//8U3NqX1tbW2RnZ8Pf3x/PPPMMli1bhhs3bqB3796l7q9jx464cuUKfvjhB7z88suoW7cu7O3tkZ6eDg8PD3Tq1AkffvghLl++jM2bN8PGxqbM98nV1RVbtmzBmTNn8O6776JVq1bw9PREeno6bGxs0KhRI4wYMQK7d+/G+fPn0bJlS631nZ2dceTIEUydOhW1atWCtbU1bGxsMGjQIBw9elTTfd6UCndrtrKy0hxbXxyZTIY5c+bg3LlzeOONN9CoUSPI5XKkpqaiWrVq6NChA9577z38888/muPuiYiIjOXq6opdu3Zh7969GDJkCAIDA5Gbm4usrCz4+/ujV69eWLBgAa5evap3/RkzZuC///7DuHHjNIfr5OXloV69enjppZcQEREBV1dXg7L8/vvvmDFjBp566ikEBARoTqNet25djBo1CidOnMCUKVPKdP/c3NwQGRmJNWvWoGvXrnBxcUFGRgZq1KiBQYMG4cCBA/j000/LtE2pFNe2a9SoEc6dO4dvvvkGvXr1gqenJ9LS0iCEQN26dTF48GB8++232Lp1q842HR0dsW3bNuzevRvPP/88/Pz8kJOTA2trazzxxBN466238O2332qt07JlSxw/fhwvvvgiPD09oVQq4eLighdffBH//POP3jPimotMJsPMmTNx69YtzJ8/H927d4efnx/y8vJQUFCAoKAgDBgwAKtXr0Z0dLTerOvXr8cXX3yB5s2bw8HBAUqlEh07dsTWrVvx5ZdfmjzzSy+9pNUuLu6QuMIGDBiAGzduIDw8HG3atIGzszNSUlJgZ2eHkJAQjB07Ftu3b8d7771n8rwkPZkQPA8gEREREREREREZhz2XiIiIiIiIiIjIaCwuERERERERERGR0VhcIiIiIiIiIiIio7G4RERERERERERERmNxiYiIiIiIiIiIjMbiEhERERERERERGY3FJSIiIiIiIiIiMhqLS0REREREREREZDQWl4iIiIiIiIiIyGgsLhERERERERERkdFYXCIiIiIiIiIiIqOxuEREREREREREREZjcYmIiIiIiIiIiIzG4hIRERERERERERmNxSUiIiIiIiIiIjIai0tERERERERERGQ0FpeIiIiIiIiIiMhoLC4REREREREREZHRWFwiIiIiIiIiIiKjWUsdoKpSKpW4e/cuXFxcIJPJpI5DREREhQghkJ6eDj8/P1hZ8be48sL2EBERUcVmaJuIxSWJ3L17FwEBAVLHICIiohLcvn0bNWvWlDpGpcX2EBERkWUorU3E4pJEXFxcAKieIFdXV5NvPzY2FoGBgSbfrjlYanZLzQ0wuxQsNTfA7FKw1NyA5WZPS0tDQECA5vOaykd5t4fKm6W+vgFml4Kl5gaYXQqWmhtgdimUZ25D20QsLklE3fXb1dW1XBpTLi4uFtlIAyw3u6XmBphdCpaaG2B2KVhqbsCyswPgoVrlrLzbQ+XNkl/fzG5+lpobYHYpWGpugNmlYI7cpbWJOIgAEREREREREREZjcUlIiIiIiIiIiIyGotLRERERERERERkNBaXiIiIiIiIiIjIaCwuERERERERERGR0VhcIiIiIiIiIiIio7G4RERERERERERERmNxiYiIiIiIiIiIjMbiEhERERERERERGY3FJSIiIiIiIiIiMhqLS0REREREREREZDQWl4iIiIiIiIiIyGgsLhERERERERERkdFYXAJw+PBh9OvXD35+fpDJZNixY0ep6xw8eBBPPvkk7OzsULduXaxfv77ccxIRERGVF7aHiIiIyFgsLgHIzMxESEgIli1bZtDyUVFR6Nu3L7p164azZ89iypQpGDt2LH777bdyTkqmEp+ajX9uJiM+NVvqKEREVAElVMHPBynbQyU93oZ8Zpe2jCm2wf1U/qzcT/HbOB2XIfn9qWiPCfdTMbdRkfZT1VhLHaAieOaZZ/DMM88YvPzKlStRq1YtLFmyBADQqFEjHDlyBJ999hlCQ0PLKyaZyJYTsZgRcR5KAVjJgAUDm2FI60CpYxERUQWx5UQspv3wr9QxzE7K9lCvzw5j7ott8ELLmlrTfz51BzN/uaD5zJ7Tv2mZlzHFNopbpo2XEjn5inLfT3ncnx0X7uOLI+W7n/J6TCZ38sUEP/M8x6a8P7kFqteLlK/Zx9rPrmjJXgePsw31426urKbaT2nv0Yp8f4q+Ryty1qLzcwuU+P5YTJn3w++UgEwIIaQOUZHIZDJs374dAwYMKHaZzp0748knn8Tnn3+umbZu3TpMmTIFqampetfJzc1Fbm6u5nZaWhoCAgKQmpoKV1dXU8XXiImJQVBQkMm3aw7lmT0+NRsdF/4JZZFXvZezHeRWssfatkJRALncMuu1zG5+lpobYHYpWGpuwPKyK5QCSRm5UOZm4fbnL5bb53RFZ+72UMCUrbCyczRVfCIiIrOSy2Q4Mr0bfN0cJNl/eX6HTktLg5ubW6ltIstp7VUgCQkJ8PHx0Zrm4+ODtLQ0ZGdnw8FB9wW1YMECzJ49W2d6bGwsXFxcTJ4xKysLMTExJt+uOZRn9tNxGTqFJQBIysjVnWiUAhNtRwrMbn6WmhtgdilYam7AsrNTcUzZHiIiIrJkCiHw78VbaOHvLMn+y/M7dHp6ukHLsbhkJjNmzMDUqVM1t9W/1AUGBrLnUhHlmd3WPRtWu6LZc6kIZjc/S80NMLsULDU3YFnZc/NykZ2TixzYSh2l0iquPQSoDiv44+0uqOFmDwBISM1Bz88OaX1ml3UZU2yjpGXWD62Llg3rlPt+yuP+9PjsEEQ57scSH5Py3k/s7VjYunpXmvtjrv087jby0u4hMCDQ4h6Tkt6j5nrszbWfipT11JWbGPnjjdKfn6WHUPgrpVwmQ9smtSttzyVDWEZrr4KpUaMGEhMTtaYlJibC1dVV7690AGBnZwc7OztzxKMS+Lo5YMHAZpi27bxm2ieDTHN8LAt60rDU7JaaG2B2KVhqbsCysh86dAgHD56AIrgtvvvv8X5wqApM2R6Sy2RYMLAZ6ng/+sW3jrczFgxshg8iLkAhBOQyGeYPbFqmZUyxjZKWCXIXcLKzLvf9lMf9ea+LH5Ycii+3/ZTnY/JOF1+zPcem3I+jjRxBEr9mLXE/j7uNmOz7Br1PK9pjUtJ7tKI/x4XfoxU9a9FtBLnbG7SfIa0D8OOJ2wCgWUaqwlJFwTGXijBkjIFp06Zh7969OH/+UYFi2LBhePDgAfbt22fQfgw9btFYltSYL8oc2VvP3Y+kjFx4OdvhRFgPk2yTj7k0LDW7peYGmF0KlpobsKzsQgjcunULderUwbXbiWgQWINjLpmpPXQ1NgH1A3z0LhOfmo3o5CwEezoW23AvbRlTbEPfMkVf3+W1n/LYRkxMDGzdvct9P+XxmOSl3NP5v2IJj33h14tUr1ljt/HvxVsl9sowx/0xdhtlfZ9WlMfekPdoRb0/+t6jFTVr0fnq10tp29hxJg5TtpxFM39XfPtqK8kLSxxzqYLIyMjAjRs3NLejoqJw9uxZeHh4IDAwEDNmzEBcXBw2btwIAHjttdfw9ddf4/3338fo0aPx559/YuvWrdizZ49Ud6HcxadmIyo5E7U8nSR/4xAREZlCamoq/v33X/To0QNWVlaQyWSoU6cOAKBGFfysk7I9VNLj7evmUGrbo7RlTLEN7qfiZI1JMc9+ymsblrifFv7Oj7WdyviYcD/Fz9f3Hq2oWR9nGQBwd7Tl9+P/Y3EJwMmTJ9GtWzfNbfVYACNGjMD69esRHx+P2NhYzfxatWphz549ePvtt/HFF1+gZs2aWL16dZlPu2sptpyIxYyI85XmNItbTsRqBvBOysjFlhOxFn1/iIio7BQKBdavX4+UlBTY2NhotQOqKraHiIiIyiYlKw/xqdksMIHFJQBA165dUdLRgevXr9e7zpkzZ8oxVcUQn5qtKSwBgFIA07adx+Lfrj32ANjFUQ3+eqP0BY3Z9v9PMV3YBxEX0Lm+F/8hEBFVIXK5HD169MBff/2FJ598Uuo4FQLbQ0RERIY5dus+AOB8XBo6LvzT4jtgmAKLS1SiqORMnTOrAdAp0Jie+U5brRAC0clZLC4REVUBeXl5sLVVnQ2uSZMmaNiwIeRyucSpiIiIyFLEp2Zjy/8H8wZUHTDYYYHFJSpFLU8neGc9xLMXDmHE6V3Y8GQ/7GzSBTKfGuXcc6l8Xpr6ei7JZTIEezqWy/6IiKhiUCqV+P333xETE4ORI0dqzljGwhIRERGVRVRyJor2v2CHBRaXqCTnz8N3/nwc++knWCkUAICZB1Yj7PA6WA0eDHzwAdCsmcl3W95nFtpyIlbn1JJV+Z8AEVFVkJmZiQsXLiAzMxM3btxAkyZNpI5EREREFqiWpxNkgFaBiR0WWFyi4vz2GzBgAFBQoCksqVkpFMDPPwM7dqguFjZw55DWgehc36vUU1gSEVHl4eLigpdeegkPHz5kYYmIiIiM5uvmgCGtA/Dj/w+NY4cFFRaXSNf586rCUm4uUNzAngUFgEKhWu748XLpwVSeDD21JBERWa6kpCQUFBTA19cXAODv7w9/f3+JUxEREZGla1e7On48cRvN/F3x7aut+N0SgJXUAajiyZ79MUR+fvGFJTUhVEWmBQvME4yIiMhAcXFxWLNmDTZv3ozU1FSp4xAREVEl5O5oW2xhKT41G//cTEZ8araZU0mDxSXSsmPfKdhEbIOsyKFwxSooAH76Cbh3r3yDERERlUH16tXh5uYGDw8P2NjYSB2HiIiIKqGUrDy9xaMtJ2LRceGfGLbqX3Rc+Ce2nIiVIJ158bA4qZ09Czg7P7pdrRpQqxaQkwNcuqS7/JNPqq6vXgUyM7XnBQcDHh5AUhJsL1wA7t9/NM/FBahXT3Uo23//6W63WTPEZxXgv8XfYoBQlu0+FBQABw8CL75YtvWIiIjKib29PYYPHw57e3tYW7O5Q0RERKZz7Jbqu/b5uDS0X/AnWgVVg6+7A3LyFUjLzse/UQ80yyoF8EHEBXSu71WpD59ja0tqXbpo3375ZeD774E7d4CWLXWXVx+qNnIkcOyY9rzvvgNeeQXYuhW+b76pPa9XL9Ug3ZmZ+rd77x6i0mQYfO534+5HWppx6xEREZlAQUEBdu3ahYYNG6JRo0YAAOfCP94QERERmUB8aja2/H8wb7WTMQ+BmIfFrqMQAtHJWSwuUTk6dEi35xIA1KwJnDpV/Hrr1+vvuQQAL76I+OBgzQCmAFQ9lwDAyUn/dt3dUcu2AN8+0Qvhkd+W9V4Arq5lX4eIiMhETp48iXPnzuHKlSsIDg6Gg0PlbbwRERGRdKKSM6FvdOJX2wWhga8LcvIUmLvnstYycpkMwZ6O5oooCRaXpNa8uf7CjL39o0Pg9GnQoPh5Xl7Ia9oUCArSnSeXF7tdXzcbhLw7HgV/roZ1WQ6Ns7YGunY1fHkiIiITa9OmDe7evYuQkBAWloiIiKjc1PJ0gpVMdbibmlwmw+vd6mh6JjnbW2PatvMAAJkMmD+waaXutQRwQG8qYkDvlohs2hkFMgNfGtbWwODBgLd3+QYjIiIq4sGDBxD/P1zcysoKAwcORJ06dSRORURERJWZr5sDFgxsBrlMBkBVWCpaPBrSOhDtansAAD7s0whDWgdKktWc2HOpiotPzUZUciZqeTpp3gzrOg9Dl0t/w0ohYKW3w9//yWSq4tKMGWZKS0REpHLx4kVs374dXbp0wVNPPSV1HCIiIqpChrQOROf6XohOzkKwp6PRvZL0fR+3VCwuVWFbTsRiRsR5KAVgJQMWDGwGADjm7IfxA8PwbcRc2EIJK4VCd2Vra9Vlxw6gWTPzBicioiovMzMTCoUCcXFxEEJA9v9fD4mIiIjMwdfNodiC0JYTsTh2S3XGuHl7LsPF3lqn95K+7+OW3MOJxaUqKj41W/NCBlTHi6qPCQWAw7Vbov+IzzDx6E/od+0IZIULTOpD4WbMYGGJiIgk0aZNG7i4uKBBgwYsLBEREVGFof6urSag+q698WgMChQCmXkFyMgpQEp2vmYZpQA+iLiAzvW9LLYHE4tLVVRUcqbWAGT6XPUKxlvPvQffgSvR+tZZICkJ8PICunfnGEtERGRWubm5+Pvvv9GlSxfI5XIAQKNGjSRORURERKStuO/aF++mad32zHyI9jH/wSM7HQ8cXHA0KATRyVksLpFl0TfCvT5ymQw1GwQB1lnASy8Bp06xsERERGYlhMDmzZsRGxuLzMxM9OvXT+pIRERERHrp+64tkwELnm+GAA9HeNy6Cs8vl6Da3l+0ztJeILNCfvwgIPwjizxCiGeLq6LUI9wX9smgZvhkUMmj3hMREZmbTCbDU089BVdXV7Rs2VLqOERERETF0nc2uYUDm2Fom0B0vHkKjfr3gNdvu7QKSwBgLZRw+GU70KYN8NtvUkR/LOy5VIUNaR2Ixb9dQ1JGLryc7TSDh5li1HsiIqLHVVBQAGtrVVOlbt26mDRpkuY2ERERUUWl92xy588DAwYAubmAKOYQooICQKFQLXf8ONCsmcWcUY4ttCpObiXTugZKHvWeiIjIHE6cOIHjx49j1KhRcHR0BAAWloiIiMhi6Hyvnj9fVTwqrrCkJoRquQULsOXthRZzRjkeFlcJxadm43RcBuJTs0tdVvH/A0EVpQ2+REREZCZ5eXn4+++/kZycjDNnzkgdh4iIiOjxJCYCP/+sKhoZoqAAii1bsWjjX1pneP8g4oJB3/OlwJ8AK5ktJ2IfVTZ3RZdY2dxyIhZJGbkAgKSMXGw5EVt8FbRZM+DePcDdvZySExERqdja2uLll1/GtWvX0KFDB6njkDmcPQs4Oz+6Xa0aUKsWkJMDXLqku/yTT6qur14FMjO15wUHAx4eqrPc3r6tPc/FBahXT3XIwX//6W63WTPAxga4eRNITdWe5+8P+PgADx8CUVEAANv4eOD+fcDBAVCfvfDMGd1fpRs1Ui0TE6NavjAfH9W209OB69e159nYPBrU9fx5ID9fe369eqr7FBen+uJSWPXqQFAQkJ0NXL6sPU8mUz1GgGpedpEvKrVqqZ6DxETVtgtzcwPq1FFlOX8eOkJCALlcdV/S07XnBQSozjz84AEQHa09z8kJaNBA9ffp07rbbdwYsLcHoqJge+mS9uPo66u6pKUBN25or2dnBzRpovr73DndL3b166tee3fuqNq6hXl6AoGBQFYWcOWK9jwrK6B5c9Xfly6pXquF1a6tajcnJAB37wIo9Hpxd1fNz8sDLlzQva/Nm6u2f+0akJGhPS8wUJUrORmIjdWe5+ysuj9Kpeo9VVTTpoCtLXDrFpCSoj3Pzw+oUUM1/dYt7Xn29qrnB1BtV6k9TgwaNgQcHVV5kpO153l7AzVrqu7HtWva86ytgSeeUP198aLqUKHC6tYFXF2B+HjVpbAy/I+wvXFD+/Vixv8RGkb8j9C8XqT6H9GihepvY/5HWFtL+j8CDx9qzyvD/wjb27e1Xy+m+h+xc6fhhaX/kysVeOH8HzgSrHou7jl7IMnZo+KeUU6QJFJTUwUAkZqaarJt3k3JErWm7xZB07QvrT7+Q7Sdt1/r0urjP3SWqz19j7ibkmWyPMaKjo6WOoJRLDW3EMwuBUvNLQSzS8FScwthePaMjAxx+/btck5juPL4nCZdmsdZ9VXr0eXll1ULXL+uPV19UWvXTnfed9+p5n39te68Xr3UO9a/3Xv3VPP79dOdt2SJat7WrbrzWrR4lMnWVnf+hQuqeWPG6M6bPl0178AB3Xn+/o+26++vO//AAdW86dN1540Zo5p34YLuPFvbR+/NFi1052/dqpq3ZInuvH79VPPu3dP/GKrfM7166c77+mvVvO++053Xrt2j+6pvu9evq+a9/LLuvPBw1bx9+3Tn1anzaLuenrrz//lHNe/tt3XnvfGGat6pU7rzXFwebbdxY935v/yimjd/vu68F15Qzbt9W/99zclRze/SRXfeqlWqeatW6c7r0kU1LydH/3bV/2NfeEF33vz5qnm//KI7r3HjR68XFxfd+adOqea98YbuvLffVs375x/deZ6ejx7DOnV05+/bp5oXHq47j/8jVJdy/B+hYcT/iOjoaP6PKO1/hBGXzzq+VOx39vJsKxraJpIJIYS05a2qKS0tDW5ubkhNTYWrq6tJtvnPzWQMW/XvY23jh3Ht0L5Odd0ZN28Cb78NfPaZ6teqchQTE4OgoKBy3Ud5sNTcALNLwVJzA8wuBUvNDRiWPSUlBRs2bEBOTg5Gjx4NLy8vM6UrXnl8TpMuzeN86BBcLbDnUnx8PHx9fS2y51KMh4fqvWmBPZfiL11SPe5qFtJzSfN6scCeSzFOTqrXiwX2XIq/cUP79WIhPZc0rxcL7LkUY22NID8/i+y5FH/7tvbrxZQ9l2bM0M1dil+GTsK3dqrv3/ddquPtVzvrPdqoPNuKhraJWFySSHk0WuNTs9Fx4Z8oOnySl7Od1oDdgGqMJfUhcWpymQxHpnfT38Xu9GmgZUvg1KlH/6zLiaV+ibLU3ACzS8FScwPMLgVLzQ0Ylj0/Px8bN25EZmYmhg0bBk9PTzOlKx6LS+Zh6Y9zZX9vVlSWmt1ScwPMLgVLzQ0wu16JiapCa1kOjbO2xpYdRzHtr0S0q+2Bz4Y0L/ZwuIpQXOKYS5WIr5sDFgxshmnbHlWIPxlU8phLH0RcgEIIyGUyzB/YtGIeu0lERJWajY0Nhg4dCgBwUo/rQURERFRZ+PgAL7xg+KDe1tbA4MHIqeYJIBGW0COIZ4urZIa0DoSXsx0AVY+lkk5TOKR1II5M74YfxrXDkendKuwpDYmIqHIRQuDgwYM4Xahbu5OTEwtLREREVHl98IGqaCSTlbycTKZabsYMnIpRHeL3760H6LjwT2w5EVvyuhJicakSUh8CV/RQOH183RzQvk519lgiIiKzuXLlCg4dOoQ9e/bgwYMHUschIiIiKn/NmgE7dqjGebIu5iAya2vV/B07EB9YF7v+u6uZpRTABxEXEJ+arX9dibG4RIbx9weWLFFdExERPYaGDRsiJCQEffr0gYf6dOhERERElV1oKHD8ODB4sG6B6f+HwuH4cSA0FFHJmTqHwymEQHRyltnilgWLS/+3bNkyBAcHw97eHm3btsXx48eLXTY/Px9z5sxBnTp1YG9vj5CQEOzbt8+MaSXg4wNMnaq6JiIiKqP09HSozyEik8nQv39/tGzZUuJUpA/bREREROWoWTNg82bVmfa2bAFWrVJdx8Wppv//DIC1PJ1Q9FgkuUyGYE9H82c2AItLALZs2YKpU6ciPDwcp0+fRkhICEJDQ3Gv6KkG/y8sLAzffPMNvvrqK1y6dAmvvfYann/+eZw5c8bMyc3o4UPgp590T+tIRERUijt37uCbb77BH3/8oZkmK228AZIE20RERERm4u0N9OwJuLmprr29tWb7ujmgX4if5nZFPwkXi0sAli5dinHjxmHUqFFo3LgxVq5cCUdHR6xdu1bv8t999x0++OAD9OnTB7Vr18brr7+OPn36YMmSJWZObkZRUcCLL6quiYiIyuDhw4fIzMxEVFQU8vPzpY5DJWCbiIiIyIxK+Z7dMqgaAKCRrwsi3mhfoU/CVcwoUlVHXl4eTp06hRkzZmimWVlZoUePHjh69KjedXJzc2Fvb681zcHBAUeOHCl2P7m5ucjNzdXcTktLe8zkRERElqFZs2aQyWSoV68ebGxspI5DxTBHm4jtISIiIsOpzxZ3OT4dzy//BwsGNquwBaYqX1xKTk6GQqGAT5GxhHx8fHDlyhW964SGhmLp0qXo3Lkz6tSpg8jISEREREChUBS7nwULFmD27Nk602NjY+Hi4vJ4d6IIhaJAcx0TE2OSbdrGx8MXQHx8PPJMtM3iZGVlmSy3OVlqboDZpWCpuQFml4Kl5VYqlbh48SIaNmyI/Px8xMTEwMXFBQkJCVJHM1h6errUEczOHG0ic7aHzMHS3puFMbv5WWpugNmlYKm5AWYvi5K+Z9/LyNc5W9yMiPOo7ZgHb2ftH+vKM7ehbaIqX1wyxhdffIFx48ahYcOGkMlkqFOnDkaNGlVsl3EAmDFjBqZOnaq5nZaWhoCAAAQGBsLV1dWk+eTyGwAKIJdbIygoyDQbvX8fAODr6wuYapvFiImJMV1uM7LU3ACzS8FScwPMLgVLy71jxw78999/yMjIQLt27Swquxp71BimrG0ic7aHzMHS3puFMbv5WWpugNmlYKm5AWYvkxK+Z8fdTNY5W5xSAAX21RAUVF1rennmNrRNVOXHXPL09IRcLkdiYqLW9MTERNSoUUPvOl5eXtixYwcyMzMRExODK1euwNnZGbVr1y52P3Z2dnB1ddW6WBQHB6BFC9U1ERFRCVq2bKk5cxgH7rYc5mgTWXx7iIiIyJRK+J7Ns8VZGFtbW7Rs2RKRkZGaaUqlEpGRkWjfvn2J69rb28Pf3x8FBQXYtm0b+vfvX95xpdOoEXD6tOqaiIioCKVSqfk7ICAAU6ZMQSN+ZlgUtomIiIjMrITv2TxbnAWaOnUqVq1ahQ0bNuDy5ct4/fXXkZmZiVGjRgEAXn31Va3BLf/9919ERETg1q1b+Ouvv9C7d28olUq8//77Ut0FIiIiydy4cQMrVqzQ6jZtZ2cnYSIyFttEREREFYclnS2OxSUAQ4YMweLFizFz5kw0b94cZ8+exb59+zQDWsbGxiI+Pl6zfE5ODsLCwtC4cWM8//zz8Pf3x5EjR+Du7i7RPTCDM2cAOzvVNRER0f8plUrs378fycnJ+Ouvv6SOQ4+JbSIiIiIzKuV7dtGzxW05EWvOdGXCAb3/780338Sbb76pd97Bgwe1bnfp0gWXLl0yQ6oKRAggL091TURE9H9WVlYYOnQojh07hp49e0odh0yAbSIiIiIzKeF7dnxqts7Z4j6IuIDO9b0q5KFx7LlEREREZVJQUIA7d+5obru7u6N3796Qy+USpiIiIiKqPKKSM3XOFqcQAtHJWZLkKQ2LS0RERGSwnJwcbNy4ERs3bsTdu3dLX4GIiIiIyoxniyMiIqJKy9bWFnZ2dpDL5cjLy5M6DhEREVGlZGlni+OYS2SYRo2ACxeA2rWlTkJERBKysrLCCy+8gPT0dHh6ekodh4iIiMhylfI9u2VQNez87y4a+bpg4cBmCAmoZuaAhmPPJTKMgwPQpInqmoiIqpTz58/j6NGjmtt2dnYsLBERERE9rlK+Z1vS2eJYXCLDxMQAY8eqromIqMqIi4tDREQEfv/9d8TGVtwGDREREZHFKeF7dnFni4tPzTZnQoOxuESGuX8fWLNGdU1ERFWGn58fWrdujfbt2yMgIEDqOERERESVRwnfsy3tbHEcc4mIiIi05OTkwMbGBnK5HDKZDM888wxksqLnKyEiIiKi8qI+W1zhAhPPFkdEREQWISUlBWvXrsXu3bshhKo5w8ISERERkXlZ2tniWFwiIiIijeTkZCQnJ+PmzZvIyMiQOg4RERFRldUySHV2uEa+Loh4oz2GtA6UOFHxWFwiw/j4ANOnq66JiKjSqlu3LgYOHIixY8fCxcVF6jhERERElVcp37N5tjiqfPz9gQULVNdERFSpnD17FtnZj8480rRpU7i6ukqYiIiIiKgKKOF7Ns8WR5VTejpw8KDqmoiIKo1Dhw7hl19+wZYtW6BQKKSOQ0RERFR1lPA929LOFsfiEhnm+nWgWzfVNRERVRoNGzaEnZ0d6tWrBysrNguIiIiIzKaE79nqs8UVxrPFERERUYWhPgscAPj4+OCtt95Cx44deVY4IiIiogqi6NnirGTg2eKIiIioYrh37x6+/fZb3L9/XzPN0bFi/gJGRERERCqi6DFyFQyLS0RERFXI77//joSEBPz2229SRyEiIiKiYhQd0FuAA3pTZWBjoxrB3sZG6iRERPQYBgwYgGbNmmHAgAFSRyEiIiKq2kr4nm1pA3pbSx2ALESzZsCdO1KnICKiMhJCICEhAb6+vgAAZ2dnDBw4UOJURERERFTS92z1gN6FC0wc0JuIiIjMTqFQICIiAqtXr0ZUVJTUcYiIiIjIQBzQmyqn8+eBmjVV10REZBGsrKw0Z4ZLT0+XOA0RERERaSnD9+yKPqA3D4sjw+TnA3FxqmsiIrIIMpkMAwYMQNu2bREQECB1HCIiIiIqrITv2cUN6N25vleF7L3EnktERESVyO3bt/HXX39pbltbW7OwRERERGRhOKA3ERERSSI1NRUbN25EQUEBqlevjsaNG0sdiYiIiIiMwAG9iYiISBJubm7o2LEjGjRogLp160odh4iIiIiMZGkDerPnEhmmXj3gwAHVNRERVRgKhQJKpRI2NjYAgC5dukAIASsr/n5EREREVKGV4Xt2RR/Qmy1PMoyLC9C1q+qaiIgqhNzcXPzwww+IiIiAUqkEoBrEm4UlIiIiIgtQwvfs4gb0jk/NNl++MmDrkwwTFwfMmKG6JiKiCiEpKQnR0dG4efMmkpKSpI5DRERERGVRwvdsSxvQm8UlMkxiIrBwoeqaiIgqhJo1a2LgwIEYOXIkfHx8pI5DRERERGVRwvds9YDehXFAbwuwbNkyBAcHw97eHm3btsXx48dLXP7zzz9HgwYN4ODggICAALz99tvIyckxU1oiIqqqbty4gfT0dM3txo0bw8/Pr4Q1iMqGbSIiIiLpWdqA3iwuAdiyZQumTp2K8PBwnD59GiEhIQgNDcW9e/f0Lr9582ZMnz4d4eHhuHz5MtasWYMtW7bggw8+MHNyIiKqSs6fP4/Nmzdj8+bNyMvLkzoOVUJsExEREVVMHNDbAixduhTjxo3DqFGj0LhxY6xcuRKOjo5Yu3at3uX/+ecfdOzYEcOGDUNwcDB69eqFl156qdRf9oiIiB5HzZo14eDgAF9fX8jlcqnjUCXENhEREVHFwAG9LUxeXh5OnTqFHj16aKZZWVmhR48eOHr0qN51OnTogFOnTmkaTrdu3cLevXvRp08fs2SWRPXqwJgxqmsiIpJEtWrVMGHCBPTr14/FJTI5tomIiIjMrITv2ZY2oLe11AGklpycDIVCoTMQqo+PD65cuaJ3nWHDhiE5ORmdOnWCEAIFBQV47bXXSuwCnpubi9zcXM3ttLQ009wBcwkKAlavljoFEVGVkpGRgYiICDRt2hRBQUEAAFdXV4lTUWVljjaRxbeHiIiITKmE79nqAb0LF5j0Degdn5qN03EZsHXPlnQ8pipfXDLGwYMHMX/+fCxfvhxt27bFjRs3MHnyZHz88cf46KOP9K6zYMECzJ49W2d6bGwsXFxcTJpPoSjQXMfExJhkm7KcHFjHxqIgMBDC3t4k2yxOVlaWyXKbk6XmBphdCpaaG2B2czpy5AiioqLw4MEDeHh4QCYres6Qis/SHnO1woOmU/HK2iYyZ3vIHCz19Q0wuxQsNTfA7FKw1NwAs5dFad+zu9d1Q+SNVACqAb3f6eKLvJR7iElRzd9z+QEWH7oLpQCsdkXj3S5+6NvIw6QZDW0TVfnikqenJ+RyORKLnPovMTERNWrU0LvORx99hOHDh2Ps2LEAgGbNmiEzMxPjx4/Hhx9+CCsr3aMNZ8yYgalTp2pup6WlISAgAIGBgSb/FVouvwGgAHK5teaX7sd2+jTQqxdw6hTQoIFptlmMmJgY0+U2I0vNDTC7FCw1N8Ds5uTj44MdO3agSZMmCA4OljqOUSztMVerij1qzNEmMmd7yBws9fUNMLsULDU3wOxSsNTcALOXSSnfs52cHgBQFZeEAApsnHAt0x7RyZm4eDcVO84+GpNJKYAlh+LxfPuGJu3BZGibqMqPuWRra4uWLVsiMjJSM02pVCIyMhLt27fXu05WVpZOY0k99oUoZgh3Ozs7uLq6al2IiIiKSk5O1vxtb2+PoUOH8jODzMIcbSK2h4iIiAyjb0DvpX9cx7iNJzFv72WtwpKalGMyVfmeSwAwdepUjBgxAq1atUKbNm3w+eefIzMzE6NGjQIAvPrqq/D398eCBQsAAP369cPSpUvRokULTRfwjz76iAOsEhGR0YQQOHToEA4fPowXX3wRDRs2lDoSVUFsExEREVUM+gb0BoBgT0c09XODp5MdNhyNLnVMJnNhcQnAkCFDkJSUhJkzZyIhIQHNmzfHvn37NANaxsbGav0qFxYWBplMhrCwMMTFxcHLywv9+vXDvHnzpLoLRERUCWRkZEAIgYSEBBaXSBJsExEREVUMtTydYCVTHe6mJpcBP4xrpznsrZGfC6ZtOw8AkMmA+QObSjaoN4tL//fmm2/izTff1Dvv4MGDWretra0RHh6O8PBwMySrIGQywNZWdU1ERCYnk8nQp08fNGjQAPXq1ZM6DlVhbBMRERGZSQnfs33dHLBgYDN8EHEBCiEgl8lKLB4VM0KP2bC4RIZp0QIodOpgIiJ6fA8fPsS5c+fQuXNnyGQyWFlZsbBEREREVFWU8j17SOtAdK7vhejkLAR7OmoVluJTszEj4rzW8h9EXEDn+l6S9F5icYmIiEgCubm5WLt2LTIyMuDg4IA2bdpIHYmIiIiIKhhfNwe9xaKo5EytQ+aARwN6S1FcqvJniyMDXb4MPPmk6pqIiB6bnZ0dOnXqhBo1aqBRo0ZSxyEiIiIic3uM79nqMZkK44DeVPFlPWfbSwAAyPFJREFUZwNnzqiuiYjIKEIIKBQKWFurPn7btm2Lli1bam4TERERURXyGN+zfd0c8HwLf2w7HaeZNqCFn2QDerPnEhERkRkolUrs2bMHmzZtgkKh0ExnYYmIiIiIyio+NRvbz8RpTdtx5i7iU6XpEMLiEhERkRk8fPgQ58+fR3R0NKKioqSOQ0REREQWrKQxl6TAn0uJiIjMoHr16hg8eDDy8/NRt25dqeMQERERkQVTj7lUuMAk5ZhL7LlEhqlVC9i6VXVNREQGSUhIwIMHDzS369aty8G7iYiIiEjlMb5n+7o5YMHAZprbMhkwf2BTycZcYs8lMky1asDgwVKnICKyGDExMdi8eTOcnZ0xZswYODpK8ysSEREREVVQJvyeLUTpy5Qn9lwiwyQmAkuXqq6JiKhU1atXh4ODA1xdXWFlxY9bIiIiIiriMb5nx6dmY0bEea1pH0Rc4IDeVMHFxQHvvKO6JiKiUjk7O2PkyJF45ZVXYG9vL3UcIiIiIqpoHuN7dkUb0JvFJSIiIhPIz89HREQEYmJiNNPc3d0hl8slTEVERERElZF6QO/COKA3ERGRhTty5AjOnz+Pn3/+Gfn5+VLHISIiIqJKzNfNAc+38NeaNqCFn2QDerO4REREZAKdOnVCvXr1MGjQINjY2Egdh4iIiIgqsfjUbGw/o3043Y4zdyUbc4lniyPDuLkB/fqpromICACQmpoKt///X7SxscGwYcMkTkREREREFuMxvmeXNOaSFL2XWFwiw9SpA+zcKXUKIqIK49y5c9i5cyf69u2LFi1aSB2HiIiIiCzNY3zPVo+5VLjAxDGXqOLLzweSklTXRESEpKQkKBQK3Lp1C0KI0lcgIiIiIirsMb5nc8wlskznzwPe3qprIiJC9+7dMXDgQAwcOBAymaz0FYiIiIiICnuM79kVbcwlFpeIiIgMkJOTg7/++kvTS0kmk6FZs2YsLBERERGR2ZU05pIUOOYSERFRKZRKJTZs2ICEhATk5+eje/fuUkciIiIioiqMYy6V4MyZM3j//ffx3HPPoUePHprpMTEx2Lp1Kx48eCBhOiIiqqqsrKzQvn17uLq6onHjxlLHISIiIqIqrqKNuVRhei69//77WLJkidbhBmpCCAwbNgxLlizB5MmTpYpIRERVjFKphJWV6neYJ554Ag0bNoStra3EqYiIiIioqituzKV3QxtIUmCqED2X1q1bh8WLF+PZZ5/FuXPnMGPGDK35wcHBaNOmDXYaeYo+MoGQECA1VXVNRFTJCSFw7NgxrF27FvmFzt7BwhIRERERmcxjfM+uaGMuVYji0vLly9GoUSNs27YNTZs21dt4b9iwIa5fvy5BOgIAyOWAq6vqmoioksvKysLhw4cRFxeHc+fOSR2HiIiIiCqjx/ierR5zSWtzVX3MpUuXLqFnz56wti7+KD0fHx/cu3fPjKlIy/XrQGio6pqIqJJzcnLCSy+9hJ49e+LJJ5+UOg4RERERVUaP8T27oo25VCGKS9bW1sjLyytxmbt378LZ2dlMiUhHejrw+++qayKiSig9PV3rR4yAgAB06NBBawxAIiIiIiKTeYzv2cWNuRSfmm2qdGVSIYpLzZo1w59//gmFQqF3flZWFvbv34+WLVuaORkREVUFycnJWL16Nb7//nukpaVJHYeIiIiIqEQcc0mP0aNH49q1a3jttdeQm5urNS8tLQ0jR45EQkICxo0bJ1FCIiKqzJycnGBrawtbW9tif+ggIiIiIqooKtqYS8UPcmRGo0ePxv79+7FmzRps2bIF7u7uAIA2bdrg8uXLyMzMxMiRI/HCCy9IG5SIiColBwcHvPzyy7Czs4ODgzTHqRMRERERGUo95tK2048OjavyYy4BwObNm/HNN9+gVq1aiIuLgxACJ0+eRGBgIFasWIG1a9dKHbFqCwgAvv5adU1EZOGEEIiMjMTVq1c109zd3VlYIiIiIiLzeYzv2RxzqQTjxo3Df//9h4yMDNy5cwdpaWm4ePEiJkyYUO77XrZsGYKDg2Fvb4+2bdvi+PHjxS7btWtXyGQynUvfvn3LPadkvLyAiRNV10REFu7MmTM4cuQItm3bhoyMDKnjEFUobBMRERGZyWN8z+aYS3ocPnwYsbGxmtsODg7w8/PTOjvc7du3cfjw4XLZ/5YtWzB16lSEh4fj9OnTCAkJQWhoqNZZgwqLiIhAfHy85nLhwgXI5XIMHjy4XPJVCA8eAN9/r7omIrJwISEhqF+/Pvr06cMzkRIVwjYRERGRGT3G9+yKNuZShSgudevWDevXry9xmY0bN6Jbt27lsv+lS5di3LhxGDVqFBo3boyVK1fC0dGx2EPxPDw8UKNGDc3ljz/+gKOjY+VuSEVHA8OHq66JiCxQZmYmhFD9vCOXyzF06FA0b95c2lBEFQzbRERERGb0GN+z1WMuFVblx1xSN/ZLolQqIZPJSl2urPLy8nDq1Cn06NFDM83Kygo9evTA0aNHDdrGmjVrMHToUDg5ORW7TG5uLtLS0rQuRERkHrGxsVi2bBkuXbqkmVYenylElswcbSK2h4iIiEyjoo25VCHOFmeI69evw83NzeTbTU5OhkKhgI+Pj9Z0Hx8fXLlypdT1jx8/jgsXLmDNmjUlLrdgwQLMnj1bZ3psbCxcXFzKFroUCkWB5jomJsYk27SNj4cvgPj4eOSZaJvFycrKMlluc7LU3ACzS8FScwOWmf3ixYvIzs7GrVu3EBUVBSurCvHbisEs8TFXs9Ts6enpUkcwO3O0iczZHjIHS319A8wuBUvNDTC7FCw1N8DsZfE437NPx2XoHXPp34u30MLfdMM+GNomkqy4NHr0aK3bO3bsQLSermAKhUIz3tIzzzxjpnSGW7NmDZo1a4Y2bdqUuNyMGTMwdepUze20tDQEBAQgMDAQrq6uJs0kl98AUAC53BpBQUGm2ej9+wAAX19fwFTbLEZMTIzpcpuRpeYGmF0KlpobsMzsgYGBqFGjBtzc3PA/9u48LqqqcQP4c2eAYV+VRUAW9x1BUbRcMbRcc89yyex9TdIiS81XREutNJfKsjQ1zXLJJXNXktw3XHPBVBZFcAdkh5n7+4O4P0cWQYa5M/B8Px8+1zn3zr3PjMPlnDPnnuvj4yN3nHIzxve8kLFm54ia8itLnUif9SF9MNbPN8DscjDW3ACzy8FYcwPMXi4VaGeb2WdB2BqHJ/uXBAFo08RXp5fGlbVOJFvn0pNzLAmCgLNnz+Ls2bPFbisIAlq3bo0FCxboPEeNGjWgVCpx584drfI7d+7A1dW11OdmZGRg7dq1mDlz5jOPo1KpoFKpKpRVVlZWQNu2BUsiIgOnVqtx8uRJtG7dGkqlEoIgwN/f32i/RSPSB33UiYy+PkRERKRLum5nP3vGoUoj23UBsbGxiI2NxY0bNyCKIt577z2p7MmfhIQEpKWl4dixY6hbt67Oc5iZmSEgIACRkZFSmUajQWRkJIKCgkp97oYNG5CTk4PXX39d57kMToMGwNGjBUsiIgP322+/Yffu3dixY4fcUYiMButEREREelaBdnbs/YwifUkigLj7mTqJVl6yjVx6cqjZihUr0LJlS9mGzoWFhWHEiBFo1aoVAgMDsXDhQmRkZGDUqFEAgOHDh8Pd3R1z5szRet6PP/6Ivn37wsnJSY7YRERUAj8/P8TGxqIBO8SJyoV1IiIiIuPgU8MKCgFa8y4pBQHeNSxlyWMQE3qPGDFC1uMPHjwY9+7dQ3h4OJKTk+Hn54ddu3ZJE1omJCQUmfw1JiYGhw4dwp49e+SIrH+nTwMBAUB0NODvL3caIqIiRFGU7gDXoEEDTJgwARYW8tyKlchYsU5ERESkRxVoZ7vZWaBfS3dsPP3/d4zr27KWTudbKg+D6FwqlJ2djZMnT+L27dvIyckpdpvhw4dXyrFDQ0MRGhpa7LqoqKgiZQ0aNIAoynhBIxERSWJiYnDgwAG8/vrrUocSO5aIng/rRERERIYvKTULm88kapVtOXMbE0MayNLBZDCdS4sXL8a0adOQmppa7PrCb6Qrq3OJiIiMU35+Pnbu3InU1FQcOXIEXbt2lTsSEREREVGlir2foXVJHACoRRFx9zNl6VySbULvJ23atAnvvvsuPD09MW/ePIiiiD59+mD27Nno3r07RFFE//79sXz5crmjEhGRgTExMcHQoUMRGBiITp06yR2HiIiIiKjS+dSwgvBUmSBAtjmXDKJzaeHChXB2dsbRo0fx/vvvAyiYjHXSpEnYvn07fv75Z2zZskW2Cb+JiMiw5Obmat0u3cXFBT169IBSqZQxFRERERGRjGS8St0gOpfOnz+P3r17w9Ly/3vY1Gq19O/XXnsNXbp0wcyZM+WIRwDQuDHwzz8FSyIiGWVkZOCnn37CTz/9hIcPH8odh4iIiIjo+VSgnR17P6NIX5IIIO5+pk6ilZdBdC7l5eWhZs2a0mMLCwukpKRobdOiRQucPn1az8lIYm4O1K1bsCQikpGpqan078xMef54EhERERFVWAXa2bwsrhi1atVCUlKS9NjLywtnzpzR2iY+Ph4mJgYz/3j1ExsLvP56wZKISEZmZmYYOnQo3nrrLXh4eMgdh4iIiIjo+ei6nV3dL4tr3bq11qik7t274/Dhw5gzZw4uXryI77//Hps2bULr1q1lTFnNPXoErFlTsCQi0rOzZ8/i/Pnz0mNra2s4OjrKmIiIiIiIqIIq0M7mZXHFGDhwIHJychAXFwcAmDJlCjw8PPC///0PzZs3x9ixY2FtbY0vvvhC3qBERKR3169fx++//47ff/8dd+/elTsOEREREZHsfGpYQfHUdXFKQZDtsjiDuM6sX79+6Nevn/S4Zs2aOHv2LJYtW4YbN27Ay8sLb7zxBtzd3WVMSUREcvD19UXjxo3h5OSkNT8fEREREVF15WZngX4t3bHxdKJU1rdlLbjZWciSxyA6l4rj4OCADz/8UO4YREQkg+zsbKhUKgiCAEEQ0L9/fygUBjHYloiIiIhIdkmpWdh8JlGrbMuZ25gY0kCWDiajqakfPHgQnTp1kjtG9eXmBkyfXrAkIqpEDx8+xLJly/Dnn39KZexYIiIiIqIqpwLt7Nj7GdA8NemSWhSr95xLDx8+RFpaWrHrjh07hm7duqFTp044ePCgnpORxM0NiIhg5xIRVbpbt27hwYMHuHDhArKzs+WOQ0RERERUOSrQzvapYYWnplyCIEC2OZdk7Vxat24dfH19UbNmTTg4OKBFixY4cuQIACApKQmvvvoq2rdvj8jISPj7+2Pr1q1yxq3e0tKA3bsLlkRElah58+bo2bMnRo8eDXNzc7njEBERERFVDl23s5++fZweyda5FBkZiaFDhyIuLg6WlpawtLTEhQsX8PLLL+PEiRNo1aoVtmzZgpYtW+L333/HyZMn8corr8gVl65dA7p3L1gSEemQKIo4d+4c8vLypLKAgADY2NjImIqIiIiIqJJVoJ0dez+jSF+SCFS/y+IWLlwIhUKBtWvX4vHjx3j8+DHWrFmDx48fo1u3bnj06BGWLVuGU6dOoVevXnLFJCKiSrZv3z5s2bIFmzdvhijK+HULEREREZGR4GVx/yociTRo0CCpbOjQoXjllVeQnp6OJUuW4M0335QrHhER6Un9+vVhYmKC2rVrQxCe/hNJRERERERlUh0vi3vw4AGaNGlSpLywrG/fvnpORERE+vLkCCUvLy+MHz8ebdu2lTEREREREZHx4GVx/1Kr1cVO1FpYZmtrq+9IVBqVCqhTp2BJRFQBycnJWL58OR4/fiyVcX4lIiIiIqp2KtDO5mVxZJyaNCmYZKyY0WZERGUliiK2bt2KW7duYe/evXLHISIiIiKSj67b2TJeFmci36GBb775BmvXrtUqu3//PgCgcePGRbYXBAEXL17USzYiItI9QRAwYMAA/Pnnn3j55ZfljkNEREREZJRKuyzOzc5C73lk7Vy6f/++1Jn0tCtXrug5DZXq/Hmga1cgMhJo3lzuNERkRERRxP3791GzZk0AgKOjIwYMGCBzKiIiIiIimVWgnV14WdyTHUzV8rI4jUbzXD8kk/x84P79giURURnl5eVhw4YNWLZsGZKTk+WOQ0RERERkOHTdzq6Od4sjIqKqT6FQIDs7G2q1Gg8fPpQ7DhERERFRlWBod4uT9bI4IiKq2pRKJQYNGoR79+7B09NT7jhERERERFWCoV0Wx84lIiLSqbi4ONy/fx+tWrUCAJibm7Njieg5nThxAidPnkRKSgrUanWR9YIgYNq0aTIkIyIiIoNTXe8WR0akfn3gyJGCJRFRCe7evYvVq1dDo9HAyckJPj4+ckciMkoPHz5E3759cfjwYYhiyTVFdi4REREZsQq0s3m3ODJO1tZAUJDcKYjIwNWsWRN+fn7IycnhaCWiCggLC8OhQ4fQqVMnjBgxAh4eHjAxYbWNiIioSqlAO5uXxZFxunULmD8fCAsDPDzkTkNEBkStVkMQBCgUCgiCgFdeeQWCIEAQBLmjERmtbdu2ITAwEJGRkfxdIiIiqqp03c7m3eLI4N29CyxYULAkIvpXVlYWfv75Z+zYsUO6dKewk4mInl9WVhY6dOjA3yUiIqKqrALtbEO7Wxw7l/61ePFieHt7w9zcHG3atMGJEydK3T4lJQXjxo2Dm5sbVCoV6tevjx07dugpLRGRYUhMTERcXBwuXLiAlJQUueMQVRl+fn6Ii4uT5disExERERm+wsviniTnZXEG1bm0efNmDBo0CM2bN0fdunWl8itXruCLL75AYmJipRx33bp1CAsLw/Tp03H69Gm0aNECISEhuFtC72Fubi66deuGuLg4/Pbbb4iJicHSpUvh7u5eKfmIiAxV3bp10atXL4waNQoODg5yxyGqMqZPn46tW7fi2LFjej0u60RERERGrLrfLU6j0WDo0KH47bffAAAWFhbIysqS1js4OGDq1KlQq9WYMmWKzo8/f/58jBkzBqNGjQIALFmyBNu3b8fy5csxefLkItsvX74cDx8+xJEjR2BqagoA8Pb21nkuIiJDdOvWLbi4uMDc3BwA4O/vL3MioqonOTkZr7zyCjp27Ihhw4bB398ftra2xW47fPhwnR2XdSIiIiLjYGh3izOIkUsLFizAhg0b8J///AePHj3CxIkTtda7uLjgxRdfxPbt23V+7NzcXERHRyM4OFgqUygUCA4OxtGjR4t9ztatWxEUFIRx48bBxcUFTZs2xezZs6FWq0s8Tk5ODtLS0rR+jEqNGsA77xQsiajaio6Oxr59+7B+/fpSz3lEVDEjR47Eli1bkJeXh5UrV2L8+PEYNWqU1s/IkSOlTiBd0EedyOjrQ0RERLpUgXa2lZmy2HJLM3m6eQxi5NLKlSvRunVrfPvttwBQ7OSVdevWrZTOpfv370OtVsPFxUWr3MXFBVeuXCn2OTdu3MCff/6JYcOGYceOHbh27Rreeecd5OXlYfr06cU+Z86cOZgxY0aR8oSEBNjY2FT8hTxBrc6XlvHx8brb8UcfAaII6HKfxcjMzNRtbj0x1twAs8vBWHMLggATExOoVCokJCRAoTCI7yjKzFjfd2PNDRhv9sePH8t6/BUrVuj9mPqoE+mzPqQPxvr5BphdDsaaG2B2ORhrboDZy+0529k3EtOLLY+9eRv2Gt19eVPWOpFBdC5du3YN48aNK3UbJycnPHjwQE+JSqfRaODs7IwffvgBSqUSAQEBSExMxNy5c0vsXJoyZQrCwsKkx2lpafD09ETt2rVLHOb+vJTKawDyoVSawMvLSzc7zcwErlwBGjYELCt3grD4+Hjd5dYjY80NMLscjDW3l5cXzMzM0KRJE6O8i5Wxvu/Gmhsw3uxyj6gZMWKErMcvq/LWifRZH9IHY/18A8wuB2PNDTC7HIw1N8Ds5VKBdraZfRaErXFal8YJAtCmia9OL4sra53IIDqXLCwskJqaWuo28fHxsLe31/mxa9SoAaVSiTt37miV37lzB66ursU+x83NDaamplAq/38YWqNGjZCcnIzc3FyYmZkVeY5KpYJKpdJteH26cgUICACiowHOr0JUbTx+/Bi///47XnnlFWnCbhsbG6PsWCKi0umjTmT09SEiIiJd0nU7W8YJvQ3ieoaWLVti9+7dyM7OLnb9w4cPsWvXLrRt21bnxzYzM0NAQAAiIyOlMo1Gg8jISAQFBRX7nPbt2+PatWvQaDRS2dWrV+Hm5lZsxxIRkbHavn07rl+/ji1btkAUZfxrRVRNxcXFYdasWRg4cCBCQkIwcOBAzJo1C3FxcTo/FutERERExqO0Cb3lYBCdS+PHj8etW7fQv39/3Lp1S2vd9evX0a9fP6SmpmL8+PGVcvywsDAsXboUP/30Ey5fvoyxY8ciIyNDmiRz+PDhWnepGzt2LB4+fIgJEybg6tWr2L59O2bPnv3MS/uIiIzNK6+8gjp16qBv374crUSkZ4sWLUKDBg0QHh6OjRs3Yu/evdi4cSOmTZuGBg0aYNGiRTo/JutERERExsGnhhWerp0LAuBdo3KnsSmJQVwW16dPH0yaNAmff/45vLy8YGVlBQBwdnbGgwcPIIoipk2bhi5dulTK8QcPHox79+4hPDwcycnJ8PPzw65du6QJLZ+etNbT0xO7d+/G+++/j+bNm8Pd3R0TJkzApEmTKiUfEZE+PXr0SOsSuNdff13mRETVz7Zt2/D++++jRo0aeP/999G5c2e4ubkhOTkZ+/fvx/z58xEWFoa6devilVde0dlxWSciIiIyYjJeaGAQnUtAwd1DunTpgm+++QbHjx9HdnY2NBoNunfvjvHjxyMkJKRSjx8aGorQ0NBi10VFRRUpCwoKwrFjxyo1k0FRKAAbm4IlEVVJoigiMjISx44dw/Dhw1G7dm25IxFVW/Pnz4ejoyNOnz4NDw8PqdzLywtt2rTBsGHD0LJlS8yfP1+nnUsA60RERER6U4F2dmmXxelyQu+yMpjOJQDo1q0bunXrJncMKo6fHyDznXOIqPI9ePAAarUat27dYucSkYxOnz6NYcOGaXUsPcnT0xODBg3CL7/8oudkREREpDMVaGdbmSmLLbc0k2dAiEF0Ll27dg1169aVOwYRUbUmCAJeffVV3LhxAw0aNJA7DlG1lpubK00TUBJra2vk5ubqKREREREZkoxcdbHlmbmaYssrm0Fc41S/fn20b98eS5YswcOHD+WOQ8W5dAlo0qRgSURVxoMHD3DixAnpsampKTuWiAxA/fr18ccffyA/P7/Y9fn5+di2bRvq16+v52RERESkMxVoZxvahN4G0bnUs2dPnDp1CuPGjUOtWrXQr18/bNq0id/GGZLs7IIPfHa23EmISEcyMjLw448/YufOnfj777/ljkNETxg+fDhiYmIQEhKC6OhorXWnTp1Cjx49EBMTgxEjRsiUkIiIiCpM1+3s6j6h99atW/HgwQP8+uuvWL16NX7//Xds3boVdnZ2GDhwIF5//XW8+OKLcsckIqpSrKys4O/vj7i4OPj4+Mgdh4ieMGHCBBw4cABbt25FYGAgLC0t4ezsjLt37yIzMxOiKKJPnz6YMGGC3FGJiIhIBoY2obdBjFwCACcnJ4SGhuL48eO4evUqpk6dCgcHByxduhSdOnWCr68vpk2bJndMIiKjJooi1Or/vz67a9euGDly5DPndiEi/VIqldiyZQtWrlyJTp06wczMDAkJCTAzM0Pnzp3x008/YfPmzVDwLq5ERETVkqFN6G2QNZK6deti5syZuH79Og4dOoQxY8YgMTERs2fPljsaEZHRUqvV2Lp1KzZv3gxRLPieQxAEmJgYxCBWIirG8OHDERkZiQcPHiAvLw8PHjzAvn378MYbb8gdjYiIiGTECb3L4Z9//sHu3buxb98+5OXlyR2nevP1BX7/vWBJREbpzp07OH/+PC5duoRbt27JHYeIiIiIqHqrQDvb0Cb0Nrivq+/fv49ff/0VP//8M06dOgVRFOHg4ID//Oc//JZOTvb2QO/ecqcgogqoVasW+vTpAwsLC3h6esodh4iIiIioetN1O7u6T+idnZ2NLVu24Oeff8bevXuRl5cHMzMz9OnTB2+88QZeeeUVmJmZyR2zektOBlasAEaNAlxd5U5DRGV0+/Zt2NrawtraGgDQvHlzmRMRUXEUCgUUCgUuXbqE+vXrQ6FQQBCe/j6yKEEQkJ+fr4eEREREpHMVaGcb2oTeBtG55OLigvT0dIiiiKCgILzxxhsYPHgwHBwc5I5GhW7fBj7+GAgJYecSkZG4du0a1q9fD2dnZ4wYMQKmpqZyRyKiEnTo0AGCIMDS0lLrMREREVVhFWhnG9qE3gbRuVSzZk2EhYXh9ddfR506deSOQ0RUJTg4OMDExATm5ubQaOSZ2I+IyiYqKqrUx0RERERPMrQJvQ2ic+natWtyRyAiqnKcnJzw5ptvwsHBAUpl8d9sEBERERGR8TG0kUsGfbc4IiIqu9zcXGzatAl37tyRymrUqMGOJaIqJC4uDkuXLsXq1auRnp4udxwiIiKSCUcuAZg5cyYEQcC4cePg6OiImTNnlul5giBg2rRplZyOimVvDwwYULAkIoO0b98+XLhwAYmJiRg3bhwUCn5/QGSsZs+ejaVLl+L06dPSHJRRUVHo2bMnsrKyAACffPIJjh07BkdHRzmjEhER0fOqQDvb0EYuydK5FBERAUEQMHjwYDg6OiIiIqJMz2Pnkox8fYENG+ROQUSl6Ny5M+7cuYPg4GB2LBEZuS1btsDb21vr5iaTJk2CRqPBjBkzkJycjG+//RYLFy4s85d0REREZGAq0M7myCUA+/fvBwDUrl1b6zEZsNxc4O5dwNkZMDOTOw0R/evx48ewsbEBAFhYWGDkyJG8wxRRFRAXF4eBAwdKj2/fvo2TJ0/igw8+wP/+9z8AQExMDDZv3szOJSIiImNVgXa2Tw0rCADEJ8oEAfCuYanTiGUlS+dSx44dS31MBujvv4GAACA6GvD3lzsNEQE4c+YMtm/fjkGDBqF+/foAwI4loioiLS0N9k8MkT9w4AAEQUCvXr2kMn9/fyxZskSGdERERKQTum5ni8/epLIYxHUTq1atwvnz50vd5u+//8aqVav0lIiIyPAlJCRArVYjJiZG7ihEpGMuLi6Ij4+XHu/duxcqlQpt2rSRyrKzs9mhTEREVE3F3s8o0pckAoi7nylHHMPoXBo5ciS2bNlS6ja///47Ro0apZ9ARERGoGfPnujduzd69uwpdxQi0rHWrVvj999/x7Zt27Bv3z6sW7cOnTt3hkqlkraJjY1FrVq1ZExJREREcjG0Cb0NonOpLNRqNSeoJaJqLTMzE8ePH4coFnxHoVQq0bJlS45cIKqCPv74Y+Tn56NPnz4ICQlBdnY2Pv74Y2l9Tk4ODhw4oDWSiYiIiKoPTuj9nM6cOcNb7RJRtZWXl4fly5fjwYMHEAQBgYGBckciokrk7++PY8eOYfXq1QCAQYMGaf3enzlzBp07d8Zrr70mV0QiIiKSkaGNXJKtc6lLly5aj1euXImoqKgi26nVaty6dQtxcXEYNGiQntJREX5+QHY2YGoqdxKiasnU1BT+/v44ceIEfHx85I5DRHrQokULtGjRoth1bdu2xebNm/WciIiIiHSqAu1sjlz615MdSYIgIC4uDnFxcUW2UygUcHR0xMCBA7Fw4UK95aOnKBTAE/M8EJF+aDQa6ZLgoKAg+Pv7w9zcXOZURERERERUYRVoZ3Pk0r80mv/vTVMoFIiIiEB4eLhccehZrl4F3n4b+OEH4N9bnhNR5RFFEYcPH0Z8fDyGDBkCpVIJQRDYsURURRXeEbdfv36wsbEp1x1yhw8fXlmxiIiIqDJVoJ3NkUvF2L9/P7y9veWOQaVJTwf++qtgSUSVLjU1FQcOHEBeXh6uXLmCJk2ayB2JiCrRyJEjIQgC2rZtCxsbG+lxaURRhCAI7FwiIiIyVhVoZ3PkUjE6duwodwQiIoNib2+P/v37IyUlhR1LRNXA8uXLIQgC3NzcAAArVqyQOREREREZMo5cAod+ExEVJzU1FaIowt7eHgDQoEEDeQMRkd6MHDlS6/GIESPkCUJERERGgSOXwKHfRERPu3PnDn7++WeYm5tj9OjRnFuJiIiIiIhKxJFLMMyh34sXL8bcuXORnJyMFi1a4Ouvv0ZgYGCx265cuRKjRo3SKlOpVMjOztZHVHnUrg0sXVqwJCKds7CwgCAIEAQBubm57FwiquYOHz6MjRs34qOPPoKrq2uR9UlJSZg7dy4GDRqEtm3b6vTYrBMRERHpSQXa2Ry5BMMb+r1u3TqEhYVhyZIlaNOmDRYuXIiQkBDExMTA2dm52OfY2toiJiZGevyskVdGr0YN4K235E5BVGXZ2trijTfegI2NDTuWiAjz58/H+fPnMX/+/GLXu7m5Ydu2bUhMTMS6det0dlzWiYiIiPSoAu1sQxu5JE+XloGZP38+xowZg1GjRqFx48ZYsmQJLC0tsXz58hKfIwgCXF1dpR8XFxc9JpbB/fvAsmUFSyKqMI1Gg7179+LmzZtSWc2aNdmxREQAgJMnT+KFF14odZsOHTrg2LFjOj0u60RERER6VIF2tqGNXDKIzqWbN2/izz//RGZmplSm0Wjw+eefo3379ggODsb27dsr5di5ubmIjo5GcHCwVKZQKBAcHIyjR4+W+Lz09HR4eXnB09MTffr0wcWLFysln8FISADGjClYElGFXbp0CUeOHMHatWuRk5MjdxwiMjB3796Fu7t7qdu4urri7t27Ojsm60RERER6VoF2tqGNXJLlsrinTZs2DX/88QeSk5OlslmzZmH69OnS47/++gtHjhxB69atdXrs+/fvQ61WF/mWzcXFBVeuXCn2OQ0aNMDy5cvRvHlzpKamYt68eWjXrh0uXrwIDw+PYp+Tk5Oj1YBMS0vT3YsgIqPToEED3LlzB4GBgVCpVHLHISIDY29vj4RnVDTj4+NhbW2ts2Pqo07E+hAREZFuGNrIJYPoXDp8+DCCg4NhamoKoODOcN988w0aNmyIPXv2IDk5GcHBwZg7dy7Wr18vc1ogKCgIQUFB0uN27dqhUaNG+P777/HJJ58U+5w5c+ZgxowZRcoTEhJgY2Oj03xqdb60jI+P18k+zZKS4IaCCURzdbTPkmRmZuostz4Za26A2fUlJydH6kjKy8tDly5dIAiC0eQvZEzv+dOMNbux5gaMN/vjx49lPX7btm2xefNm3Lx5E56enkXWJyQkYMuWLejSpYsM6f5feetE+qwP6YOxfr4BZpeDseYGmF0OxpobYPbyqEg7+0ZierHlsTdvw16juy9vylonMojOpbt378LLy0t6fPbsWdy7dw8RERHw8PCAh4cH+vbti7/++kvnx65RowaUSiXu3LmjVX7nzp1i785SHFNTU7Rs2RLXrl0rcZspU6YgLCxMepyWlgZPT0/Url0btra2zxe+BErlNQD5UCpNtN7XCnnwAEDBBKLQ1T5LEB8fr7vcemSsuQFm14fY2Fhs3rwZL7/8Mpo1a2Y0uYvD7PpnrLkB480u94iasLAw/PHHH2jfvj0+/fRTdOvWDW5ubkhKSsKePXvwv//9D1lZWfjggw90dkx91In0WR/SB2P9fAPMLgdjzQ0wuxyMNTfA7OVSgXZ2iuIRgLgi5T6eteDl6aCDcAXKWicyiDmXNBoNNJr/vy4wKioKgiBofRvn7u6uddmcrpiZmSEgIACRkZFaeSIjI7W+iSuNWq3GhQsXCj4QJVCpVLC1tdX6MSrW1kDHjgVLIiq369evIzs7G2fOnIEoinLHISID16FDB8yfPx+3b9/GqFGj4OHhARMTE3h4eODNN99EcnIyFi1ahA4dOujsmPqoExl9fYiIiEiXKtDOvvkoq9jyWyWUVzaDGLlUu3ZtnDhxQnq8ZcsWuLm5oUGDBlJZcnIy7O3tK+X4YWFhGDFiBFq1aoXAwEAsXLgQGRkZGDVqFABg+PDhcHd3x5w5cwAAM2fORNu2bVG3bl2kpKRg7ty5iI+Px1vPeQtBo1C/PhAVJXcKIqPVtWtX2NjYICAggLfpJqIymTBhAjp37owlS5bg5MmTSE1Nhb29PQIDA/Hf//4XTZs21fkxWSciIiLSowq0s0v6wlqu77ENonOpf//+mDVrFgYMGABzc3McOnQIoaGhWttcunQJvr6+lXL8wYMH4969ewgPD0dycjL8/Pywa9cuaULLhIQEKBT/P8jr0aNHGDNmDJKTk+Hg4ICAgAAcOXIEjRs3rpR8BkGjAfLyAFNTQGEQA96IDFp+fj7OnTsHf39/CIIAQRDQpk0buWMRkZFp3rw5vv32W70dj3UiIiIiPapAO7u2o2Wx5Z6OFrpIVm4G0bk0ceJE7NmzB5s2bQJQUJGKiIiQ1sfHx+PEiROYPHlypWUIDQ0t0qFVKOqpnsQFCxZgwYIFlZbFIJ09CwQEANHRgL+/3GmIDJooivj1119x48YNpKWloXPnznJHIiIqM9aJiIiI9KQC7eyMXHWx5Zm5mmLLK5tBDEGxtbXFsWPHcP78eZw/fx7R0dFwcNCegGrTpk145513ZEpIRFR2giCgadOmUKlUqF27ttxxiMhI5efnY8GCBQgMDIStrS1MTP7/O8GzZ8/inXfewdWrV2VMSERERHKxMlMWW25pJk83j0GMXCpU0twBXl5eRjvbPBFVH6IoSvMptWzZEvXr14eVlZXMqYjIGGVlZeGll17CkSNHUKNGDdja2iIjI0Na7+PjgxUrVsDR0RGffvqpjEmJiIhIDhy59AyHDx/G4sWLMWfOHCxevBiHDx+WOxIR0TNdunQJq1evRl5enlTGjiUiel6zZ8/G4cOHMWfOHCQnJxeZINvOzg4dO3bE7t27ZUpIREREcuLIpRIcOXIEo0aNwrVr1wBojwCoV68eVqxYUebb4BIR6VN2dja2bduGrKwsnDhxAu3bt5c7EhEZuXXr1qFz58746KOPAKDYu0z6+vrizJkz+o5GREREBuDmo6xiy289ykILT4di11Umg+hcunjxIl566SVkZmaiW7du6Ny5M9zc3JCcnIz9+/djz549CAkJwbFjx3j3Ebk0bQrcvAk4O8udhMjgmJubY9CgQbhy5Qo7wYlIJxISEtCvX79St7GxsUFqaqqeEhEREZHOVaCdLYpiCeUVDfV8DKJzaebMmcjNzcWOHTvQvXt3rXWTJk3Crl270Lt3b8ycORNr166VKWU1Z2YGeHjInYLIYOTk5CAjIwOOjo4AAG9vb3h7e8sbioiqDBsbG9y9e7fUba5fv46aNWvqKRERERHpXAXa2bUdLYst93S0qEii52YQcy5FRUVhwIABRTqWCnXv3h0DBgzA/v379ZyMJDduAAMHFiyJqrnHjx9jxYoVWLVqFdLT0+WOQ0RVUNu2bfHHH38gJSWl2PU3b97Ejh070KFDB/0GIyIiIt2pQDubE3oXIzU1FT4+PqVu4+Pjw6HfckpJAX77rWBJVM0plUrk5eUhPz+fnUtEVCk+/PBDPHr0CF27dsXhw4eRn58PAMjMzERkZCRCQkKQn5+PsLAwmZMSERHRc6tAO5sTehejVq1aOHbsWKnbHD9+HLVq1dJTIiKikllaWmLYsGFQKBSwt7eXOw4RVUEdOnTAN998gwkTJmiNTrKxsQFQ0Mn97bffIiAgQK6IREREJCNDm9DbIEYu9e7dG1FRUZg2bRqys7O11mVnZ2P69OnYv38/+vTpI1NCIqruTp06Jd3NEgAcHR3ZsURElWrs2LE4d+4cQkND0bp1a9SpUwctW7bEf//7X5w5cwZvvfWW3BGJiIhIJpzQuxjTpk3Dtm3bMHv2bHz//fcIDAyEi4sL7ty5g5MnT+LevXvw9fXFtGnT5I5KRNXQxYsXsX37dpiZmWHs2LHsVCKiSnfgwAHY2trCz88PixYtkjsOERERGRhO6F0MJycnHDt2DCNGjEB6ejp27NiBFStWYMeOHXj8+DFGjRqFY8eOSXdlIhnUqgXMnl2wJKpmGjZsCG9vb7Rr1w52dnZyxyGiaqBz58744Ycf5I5BRERElakC7ezSLouTg0GMXAKAGjVqYPny5fj+++9x5coVpKWlwdbWFg0bNoSpqanc8cjVFZgyRe4URHqTm5sLMzMzAAVzm7zxxhtQKAyiP56IqgFnZ2eYm5vLHYOIiIgqUwXa2bws7gmPHj3C119/jZMnT0IQBLRp0wbjxo1Ds2bN5IxFxUlJAQ4cADp0AHhJEFVx9+/fxy+//IK2bdsiMDAQANixRER61a1bN0RFRUEURQiCIHccIiIiqgwVaGfzsrh/PXjwAAEBAZgxYwa2b9+Obdu2ITw8HK1bt8bDhw/likUluXED6NOnYElUxV29ehWPHj3C8ePHpdt/ExHp02effYYHDx7g7bffZr2IiIioqqpAO5uXxf1r9uzZiIuLQ+fOnfGf//wHAPD9999j//79+Oyzz/DFF1/IFY2IqrmgoCCIogg/Pz+YmBjM1cNEVI28/vrrsLe3x/Lly/Hzzz/Dx8cHLi4uRUYxCYKAyMhImVISERGRXHhZ3L927NiBunXrYs+ePVAqlQCA/v37o3Hjxti2bRs7l4hIb0RRxN9//40mTZpAoVBAEAS0b99e7lhEVI1FRUVJ/87JycGVK1dw5cqVItvxkjkiIqLqiZfF/Ss+Ph4hISFSxxJQMGluSEgI4uLi5IpFRNXQjh07sGnTJuzcuVPuKEREAACNRlOmH7VaLXdUIiIikoGhXRYnW+dSdnY2atasWaTcyckJOTk5MiSiUpmbA40bFyyJqhhfX18oFAq4uLjIHYWIqrmjR4+iS5cusLGxgZ2dHbp164YTJ07IHYuIiIgqQwXa2bwsjoxT48bAxYtypyCqFI0aNcL48eNhZ2cndxQiqsYuXLiArl27Ijs7WyqLjIzEkSNHcOLECTRp0kTGdERERKRzFWhnG9plcbJ2Lh06dKjI3EqHDh0CAMydO7fYnriPPvpIL9mIqOpKTEzEn3/+iYEDB8L8328J2LFERHL77LPPkJ2djalTp+Ldd98FACxevBiffPIJPv/8c6xatUrmhERERGQoSrssroWng57TyNy5tG/fPuzbt6/YdZMmTSpSJggCO5fkcvYs0KEDcOAA4Ocndxqi56bRaLBx40Y8evQI+/fvR48ePeSOREQEADh48CBeeOEFfPLJJ1LZjBkzEBUVhb/++kvGZERERFQpKtDO5mVx/1qxYoVch6bnodEAjx8XLImMmEKhwMCBA3Ho0CF06dJF7jhERJI7d+5gyJAhRcrbtGmD48ePy5CIiIiIKlUF2tm8LO5fI0aMkOvQRFTNaDQapKSkwNHREQDg5uaGgQMHypyKiEhbXl4erK2ti5RbWVkhLy9PhkRERERkqAztsjjZ7hZHRKQPubm5WLduHZYvX45Hjx7JHYeIiIiIiKjCHmXmlqu8svFucURUpYmiiLS0NOTk5OD+/ftwcNB/Lz4RUVn9/PPPOHbsmFbZtWvXAAAvv/xyke0FQcD27dv1ko2IiIgMh72FaQnlZnpOUoCdS1Q2DRsC0dEFSyIjolKpMHToUKSlpcHDw0PuOEREpbp27ZrUmfS0Xbt2FSkTBKGyIxEREVFlqUA7m3MukXGytAT8/eVOQVQm169fR05ODho3bgwAsLW1ha2trcypiIhKFxsbK3cEIiIi0qcKtLMNbc4ldi5R2SQkAJ9/DkyaBNSuLXcaohLdvHkTa9asgUKhgIODA9zc3OSORERUJl5eXnJHICIiIn2qQDvb0OZc4oTeVDb37wPffluwJDJg7u7uqF+/Ppo0aYKaNWvKHYeIiIiIiKh4Vaidzc6lfy1evBje3t4wNzdHmzZtcOLEiTI9b+3atRAEAX379q3cgERUovz8fIiiCABQKBQYMGAA+vbtCxMTDs4kIiov1omIiIgMn6FN6G1QnUu5ubnYsWMH5s+fj08++UQqz87Oxt27d6HRaCrluOvWrUNYWBimT5+O06dPo0WLFggJCcHdu3dLfV5cXBwmTpyIF198sVJyEdGzZWdnY9WqVThw4IBUZmJiwkluiYieA+tERERExsHQJvQ2mM6lrVu3onbt2ujVqxcmTpyIiIgIad358+fh5uaGtWvXVsqx58+fjzFjxmDUqFFo3LgxlixZAktLSyxfvrzE56jVagwbNgwzZsyAr69vpeQiomdLTEzEzZs3cezYMWRkZMgdh4jIqLFOREREZBxKm9BbDgbRuXT48GEMGDAAKpUKixYtwmuvvaa1PjAwEHXr1sXGjRt1fuzc3FxER0cjODhYKlMoFAgODsbRo0dLfN7MmTPh7OyM0aNHl+k4OTk5SEtL0/oxKs7OwPvvFyyJDEidOnXQrVs3vPnmm7CyspI7DhGR0dJHncjo60NERES6VIF2tqFN6G0QE5J88sknsLe3R3R0NGrUqIEHDx4U2aZVq1Y4fvy4zo99//59qNVquLi4aJW7uLjgypUrxT7n0KFD+PHHH3H27NkyH2fOnDmYMWNGkfKEhATY2NiUK/OzqNX50jI+Pl53O54wAVCrAV3usxiZmZm6za0nxpobML7siYmJcHFxgYmJCTIzM+Hu7m50r8HY8j6J2fXPWHMDxpv98ePHckfQO33UifRZH9IHY/18A8wuB2PNDTC7HIw1N8Ds5fac7eyHDx4WW/7gwUPEx+tuipCy1okMonPp+PHjGDBgAGrUqFHiNp6envj999/1mKp4jx8/xhtvvIGlS5eWmvdpU6ZMQVhYmPQ4LS0Nnp6eqF27NmxtbXWaUam8BiAfSqWJ7m5rnJ4OXLgANGsGWFvrZp8liI+PN8rbMRtrbsC4sh89ehR79+5F06ZN8eqrryIhIcFosj/JmN7zpzG7/hlrbsB4s3NEzbM9T51In/UhfTDWzzfA7HIw1twAs8vBWHMDzF4uFWhnOyaJAJKKlDs5Oer0NZS1TmQQnUs5OTnPrFCkpKRAodD9VXw1atSAUqnEnTt3tMrv3LkDV1fXIttfv34dcXFx6NWrl1RWONG4iYkJYmJiUKdOnSLPU6lUUKlUOk6vR1evAu3aAdHRgL+/3GmoGnNxcYFCoYB1JXdyEhFVN/qoExl9fYiIiEiXKtDO5t3iiuHr64uTJ0+Wus3Ro0fRsGFDnR/bzMwMAQEBiIyMlMo0Gg0iIyMRFBRUZPuGDRviwoULOHv2rPTTu3dvdO7cGWfPnoWnp6fOMxLR//P19cXYsWMREhLCO8IREekQ60RERETGw9DuFmcQI5f69++PTz/9FCtWrMCoUaOKrJ83bx7+/vtvfPHFF5Vy/LCwMIwYMQKtWrVCYGAgFi5ciIyMDCnL8OHD4e7ujjlz5sDc3BxNmzbVer69vT0AFCknoopLTU3Fjh070Lt3b2nC7vJckkpERGXHOhEREZFxKO1ucS08HfScxkA6lz788ENs3LgRb731Fn755Rfk5OQAAD766CMcPXoUR44cgZ+fH0JDQyvl+IMHD8a9e/cQHh6O5ORk+Pn5YdeuXdKElgkJCZVySR4RlU4URWzatAkJCQnYtm0bBg8eLHckIqIqjXUiIiIi48C7xRXD2toaBw8eRGhoKNavXw+1Wg2gYMSSIAgYNGgQvv3220q9Rj80NLTEzquoqKhSn7ty5UrdBzI0JiZAjRoFSyI9EQQBvXr1wrZt29C9e3e54xARVQusExEREelJFWpnG8wrcHBwwJo1a/DVV1/h5MmTePjwIWxtbdG6desit8QlGTRvDty7J3cKqibS0tKkSf5r1KiBkSNHyhuIiIiIiIhI16pQO9tgOpcKOTk5cYQCUTWl0WiwZ88enD17Fm+++SacnZ3ljkRERERERETPwIvmqWwuXgTq1i1YElUSjUaDpKQk5OTkICEhQe44RERERERElacC7Wx7C9MSys0qmuq5GMTIpS5dupRpO0EQtG6PS3qUkwNcv16wJKokJiYmGDx4MBISEtCwYUO54xAREREREVWeCrSzW3k7QgAgPlEmAAjw1v+d4gAD6Vx61uSQgiBAFEUIgqCfQESkN3fv3kVycjKaN28OALC0tGTHEhERERERUSnc7CzwWf9mmLLxAjQouCxtTv9mcLOzkCWPQXQuaTSaYsvT0tJw+vRpfPzxx/Dw8MCvv/6q52REVJkePXqE5cuXIzc3F9bW1vD19ZU7EhERERERkVEY3Lo2OtSvieMXb6BNE1/ZOpYAA59zydbWFp06dcLu3btx4sQJzJo1S+5IRKRD9vb2aNSoETw9PeHq6ip3HCIiIiIiIqPiZmeBlu7WsnYsAQbeuVTIxsYGPXr0wIoVK+SOUn3VrQvs2lWwJKoAURSl0YqCIKBnz5544403YGlpKXMyIiIiIiIiPapC7WyDuCyuLBQKBZKSkuSOUX3Z2gIhIXKnICOXn5+PrVu3wsLCAj169AAAKJVKmVMRERERERHJoAq1s41i5NKNGzewYcMGeHt7yx2l+kpKAiIiCpZEzyk+Ph4XLlzAqVOncO/ePbnjEBERERERyacKtbMNYuTSm2++WWx5fn4+EhMTcejQIeTl5WHmzJl6TkaSpCRgxgygd2/AzU3uNGSk6tSpg5CQENSsWRM1a9aUOw4REREREZF8qlA72yA6l1auXFnq+gYNGuCDDz7AW2+9pZ9ARKQziYmJqFGjBlQqFQCgbdu2MiciIiIiIiIiXTKIzqXY2NhiyxUKBezt7WFjY6PnRESkC1euXMFvv/0GHx8fDB06FAqFUVyJS0REREREROVgEJ1LgiDAzMyMtyInqmJsbGwgCAIUCgXUajU7l4iIiIiIiKogg2jp+fj44OOPP5Y7BpXGwQEYNqxgSVRG7u7uGD16NAYPHgxTU1O54xARERERERmOKtTONojOJQcHBzg5Ockdg0rj4wP8/HPBkqgEOTk52LJlC1JSUqQyV1dXjlgiIiIiIiJ6WhVqZxtEi+/FF1/E8ePH5Y5BpcnOBq5dK1gSlWD79u04d+4cfvvtN4iiKHccIiIiIiIiw1WF2tkG0bk0Z84cnD9/HjNnzkR+fr7ccag4ly4B9eoVLIlK0LVrV7i5ueHll1+GIAhyxyEiIiIiIjJcVaidbRATen/xxRdo1qwZZsyYge+//x4tWrSAi4tLkcapIAj48ccfZUpJRMXJzMyEpaUlAMDOzg5jxoxhxxIREREREVE1IlvnklKpREREBKZNm4aVK1dK5UlJSUhKSir2OexcIjIsJ0+exL59+/DGG2/Aw8MDANixREREREREVM3I1rkkiqI0J0tsbKxcMYjoOYmiiH/++Qe5ubm4dOmS1LlERERERERE1YtBXBbn5eUldwQiKidBEDBgwABcuHAB/v7+cschIiIiIiIimRhE5xIZAX9/gHf/qvYyMjJw7do1tGjRAgBgZmaGgIAAmVMREREREREZoSrUzpa1c4lzsxAZj+zsbCxbtgwpKSlQKpVo2rSp3JGIiIiIiIjIACjkPHhERASUSmWZf0xMONBKNjExQFBQwZKqJXNzczRs2BAODg5wc3OTOw4REREREZFxq0LtbFl7a2xtbWFvby9nBCqrjAzg2LGCJVUroihKowxfeukldOjQARYWFjKnIiIiIiIiMnJVqJ0ta+fS+++/j/DwcDkjEFEJRFHEX3/9hZSUFPTp0weCIEAQBHYsERERERERkRZZL4sjIsN19+5dHDhwAOfOnUNsbKzccYiIiIiIiMhAcRIjIiqWi4sLevbsCVEU4evrK3ccIiIiIiIiMlAcufSvxYsXw9vbG+bm5mjTpg1OnDhR4rabNm1Cq1atYG9vDysrK/j5+WH16tV6TCsDb29g9eqCJVVZjx49QmZmpvTY398fAQEBMiYiIiJ9Y52IiIhIT6pQO5udSwDWrVuHsLAwTJ8+HadPn0aLFi0QEhKCu3fvFru9o6Mjpk6diqNHj+L8+fMYNWoURo0ahd27d+s5uR45OgKvv16wpCopMTERP/74I9auXYv8/Hy54xARkQxYJyIiItKjKtTOlq1zSaPRGMxk3vPnz8eYMWMwatQoNG7cGEuWLIGlpSWWL19e7PadOnVCv3790KhRI9SpUwcTJkxA8+bNcejQIT0n16N794DFiwuWVCWZmZkhPz8feXl5yMnJkTsOERHJgHUiIiIiPapC7exqP3IpNzcX0dHRCA4OlsoUCgWCg4Nx9OjRZz5fFEVERkYiJiYGHTp0KHG7nJwcpKWlaf0YlZs3gdDQgiVVSTVr1sTw4cMxatQoWFlZyR2HiIj0TB91IqOvDxEREelSFWpnV/sJve/fvw+1Wg0XFxetchcXF1y5cqXE56WmpsLd3R05OTlQKpX49ttv0a1btxK3nzNnDmbMmFGkPCEhATY2Ns//AoqhVudLy/j4eJ3s0ywpCW4AkpKSkKujfZYkMzNTZ7n1ydhyazQaREdHo169ejAzM5OyJyUlyZysfIztfS9krLkBZpeDseYGjDf748eP5Y6gd/qoE+mzPqQPxvr5BphdDsaaG2B2ORhrboDZy0NX7ezKzF3WOlG171x6XjY2Njh79izS09MRGRmJsLAw+Pr6olOnTsVuP2XKFISFhUmP09LS4Onpidq1a8PW1lan2ZTKawDyoVSawMvLSzc7ffAAAODm5gboap8liI+P111uPTK23JGRkbh48SJu376Nnj17GlX2Jxnb+17IWHMDzC4HY80NGG92jqgpu/LUifRZH9IHY/18A8wuB2PNDTC7HIw1N8Ds5aKjdnZl5i5rnajady7VqFEDSqUSd+7c0Sq/c+cOXF1dS3yeQqFA3bp1AQB+fn64fPky5syZU2Lnkkqlgkql0lluoooKCgrC1atX0alTJyiVSrnjEBGRzPRRJ2J9iIiIqGqq9nMumZmZISAgAJGRkVKZRqNBZGQkgoKCyrwfjUZTtSdBtrEBXnqpYElG68nPqKWlJf7zn/+gUaNGMiYiIiJDwToRERGRnlWhdna1H7kEAGFhYRgxYgRatWqFwMBALFy4EBkZGRg1ahQAYPjw4XB3d8ecOXMAFMwX0KpVK9SpUwc5OTnYsWMHVq9eje+++07Ol1G56tUDeFtho3bt2jVs3LgRAwYMQJ06dQAUfNtMRERUiHUiIiIiPapC7Wx2LgEYPHgw7t27h/DwcCQnJ8PPzw+7du2SJrRMSEjQaoRnZGTgnXfewa1bt2BhYYGGDRvi559/xuDBg+V6CZVPrQYyMgArK4CXUBmlixcvIjs7GydPnpQ6l4iIiJ7EOhEREZEeVaF2NjuX/hUaGorQ0NBi10VFRWk9/vTTT/Hpp5/qIZUBOXcOCAgAoqMBf3+509BzeOWVV+Dk5FSuSxuIiKj6YZ2IiIhIT6pQO5vXxBBVUXl5eTh//rz02MTEBC+88AIn7yYiIiIiIiKd4sgloipIrVZj9erVuHnzJnJyctC6dWu5IxEREREREVEVxZFLRFWQUqlE3bp1YW5ujpo1a8odh4iIiIiIiKowjlwiqkJEUYQgCACAF198EX5+frC1tZU5FREREREREVVlHLlEZdOsGXD3bsGSDNKFCxfw22+/QaPRAAAEQWDHEhERERERkaGqQu1sjlyisjE1BXh5lcF6/Pgxtm7divz8fNSpUwf+Rn6nASIiIiIioiqvCrWzOXKJyub6daB374IlGRwbGxv069cPQUFBaNmypdxxiIiIiIiI6FmqUDubnUtUNqmpwB9/FCzJIGRnZ+Px48fS48aNG+Oll16S5lwiIiIiIiIiA1aF2tnsXCIyQikpKVi+fDnWrFmDnJwcueMQERERERFRNcY5l4iMVFZWFgRBwOPHj6FSqeSOQ0RERERERNUUO5eIjJC9vT2GDRsGS0tL3hGOiIiIiIiIZMXL4qhs3N2BL78sWJIsjh8/jsTEROmxq6srO5aIiIiIiIiMVRVqZ3PkEpWNiwsQFiZ3imorOjoau3btgpWVFd555x1YWlrKHYmIiIiIiIgqogq1szlyicrm0SNgw4aCJeld06ZN4erqiqCgIFhYWMgdh4iIiIiIiCqqCrWzOXKJyiY2Fhg0CIiOBhwc5E5TLeTn58PEpOBXVKVSYfTo0dJjIiIiIiIiMnJVqJ3NkUtEBuju3bv45ptvcPHiRamMHUtERERERERkiNi5RGSAzp07h9TUVBw8eBAajUbuOEREREREREQl4lAIIgPUtWtXmJiYoG3btlAo2AdMREREREREhoutViobCwugZcuCJemcKIq4dOkSRFEEACgUCnTu3JmTdxMREREREVVVVaidzZFLVDaNGgGnT8udokoSRRFbtmzB+fPn0blzZ3To0EHuSKRnoigiPz8farVa7ihlkp+fj+zsbLljPBdjzW6suQHDza5UKmFiYgJBEOSOQkRERNVVFWpns3OJSGaCIMDDwwN///03bG1t5Y5Depabm4ukpCRkZmbKHaXM8vPzERsbK3eM52Ks2Y01N2DY2S0tLeHm5gYzMzO5oxAREREZNXYuUdmcOQO0bQscO1YwbI90qnXr1qhTpw4cHR3ljkJ6pNFoEBsbC6VSiVq1asHMzMwoRlHk5uYabWPcWLMba27AMLOLoojc3Fzcu3cPsbGxqFevHue3IyIiIv2rQu1sdi5R2YgikJtbsKQKS0hIwLFjx/Dqq6/CxKTg15AdS9VPbm4uNBoNPD09YWlpKXecMhMEASqVSu4Yz8VYsxtrbsBws1tYWMDU1BTx8fHIzc2Fubm53JGIiIiouqlC7Wx+TUekZ3l5eVi/fj0uX76MQ4cOyR2HDABHTBDJg797RERERLrBWhWRnpmamuLVV19F48aN0b59e7njEBEREREREVUIO5eI9ECtViMtLU167Ovri4EDB8LU1FTGVESVSxAEbNmyRe4YRisiIgJ+fn7S45EjR6Jv376y5SEiIiIiKgk7l6hsGjUC/v67YEnlkp2djV9++QUrV65ERkaG3HGIdCI5ORnvvvsufH19oVKp4OnpiV69eiEyMlLuaBUWFRUFQRCkHwsLCzRp0gQ//PCDrLkWLVqElStXypqBiIiIiHSoCrWzOaE3lY2FBdCkidwpjJJarcbDhw+RkZGBe/fuwcrKSu5IRBUSFxeHLl26wN7eHnPnzkWzZs2Ql5eH3bt3Y9y4cbhy5YrcEXUiJiYGtra2yMrKwh9//IGxY8eiTp066Nq1qyx57OzsZDkuEREREVWSKtTO5sglKpv4eOCttwqWVC5WVlYYNmwYRo4cCW9vb7njEFXYhAkTIAgCTpw4gf79+6N+/fpo0qQJwsLCcOzYMa1t79+/j379+sHS0hL16tXD1q1bpXVqtRqjR4+Gj48PLCws0KBBAyxatEjr+YWXgs2bNw9ubm5wcnLCuHHjkJeXJ22Tk5ODSZMmwdPTEyqVCnXr1sWPP/4orf/777/Ro0cPWFtbo3bt2njjjTdw//79Z75OZ2dnuLq6wsfHB+PHj4ePjw9Onz4trd+1axdeeOEF2Nvbw8nJCT179sT169el9bm5uQgNDYWbmxvMzc3h5eWFOXPmSOtTUlLw1ltvoWbNmrC1tUWXLl1w7ty5EvM8fVlcp06dMH78eHz00UdwdHSEq6srIiIitJ5T3mMQERERkR5VoXY2O5f+tXjxYnh7e8Pc3Bxt2rTBiRMnStx26dKlePHFF+Hg4AAHBwcEBweXun2V8OAB8OOPBUt6pqtXryI2NlZ6XKNGDdSqVUvGRGRMcnNzkZubC/GJW5Kq1Wrk5uYiPz9f59uWx8OHD7Fnzx6MGzeu2FF49vb2Wo9nzJiBQYMG4fz583j55ZcxbNgwPHz4EACg0Wjg4eGBDRs24NKlSwgPD8fHH3+M9evXa+1j//79uH79Ovbv34+ffvoJK1eu1Lo8bPjw4fj111/x1Vdf4fLly/j+++9hbW0NoKBzpUuXLmjZsiVOnTqFrVu34s6dOxg0aFCZX7Moiti1axcSEhLQpk0bqTwjIwNhYWE4deoUIiMjoVAo0K9fP2g0GgDAV199ha1bt2L9+vWIiYnBmjVrtDqYBw4ciLt372Lnzp2Ijo6Gv78/unbtKr0/ZfHTTz/BysoKx48fxxdffIGZM2di7969Oj0GVT+sExEREelJFWpn87I4AOvWrUNYWBiWLFmCNm3aYOHChQgJCUFMTAycnZ2LbB8VFYWhQ4eiXbt2MDc3x+eff46XXnoJFy9ehLu7uwyvgAzJtWvXsHbtWpiZmeHtt9+Go6Oj3JHIyBSObpk4caLUgXP48GHs378fLVu2RO/evaVt582bh7y8PEyYMEHq2Dl58iR2796NZs2a4dVXX5W2XbRoETIzMzF27Fjp3Hb27FkEBASUOdu1a9cgiiIaNmxYpu1HjhyJoUOHAgBmz56Nr776CidOnED37t1hamqKGTNmSNv6+Pjg6NGjWL9+vVbnj4ODA7755hsolUo0bNgQr7zyCiIjIzFmzBhcvXoV69evx969exEcHAygYML8Qt988w1atmyJ2bNnAygY5bR8+XJ4enri6tWrqF+/fonZPTw8pOdoNBrMnDkTHTp0kNb3799fa/vly5ejZs2auHTpEpo2bYqEhATUq1cPL7zwAgRBgJeXl7TtoUOHcOLECdy9excqlQpAwf/lli1b8Ntvv+Htt98u0/vbvHlzTJ8+HQBQr149fPPNN4iMjES3bt10dgyqXlgnIiIioufBkUsA5s+fjzFjxmDUqFFo3LgxlixZAktLSyxfvrzY7desWYN33nkHfn5+aNiwIZYtWwaNRlMlJrKlivP29oaHhwcaN27MOVKoynly1FNZNG/eXPq3lZUVbG1tcffuXals8eLFCAgIQM2aNWFtbY0ffvgBCQkJWvto0qQJlEql9NjNzU3ax9mzZ6FUKtGxY8dij3/u3Dns378f1tbWsLa2hpOTk9Qx9uQlbMU5ePAgzp49i7Nnz2LZsmWYPXs2vvvuO2n9P//8g6FDh8LX1xe2trbSqKTC/CNHjsTZs2fRoEEDjB8/Hnv27NHKlZ6eDicnJymbtbU1YmNjn5nrSU++v0+/N7o6BlUvrBMRERHR86j2I5dyc3MRHR2NKVOmSGUKhQLBwcE4evRomfaRmZmJvLw8jlCpxp68tMjExASvv/46TE1NIQiCjKnIWBWej0xNTaWy9u3bo23btlAotL8TmDhxYpFtW7duDX9//yLbTpgwoci2T97qvizq1asHQRDKPGn3k8cCAEEQpMvG1q5di4kTJ+LLL79EUFAQbGxsMHfuXBw/frzM+7CwsCj1+Onp6ejVqxc+//xzAAXnfDMzMwAFHTGl8fHxkUaDNWnSBMePH8esWbMwduxYAECvXr3g5eWFpUuXolatWtBoNGjatClyc3MBAP7+/oiNjcXOnTuxb98+DBo0CMHBwfjtt9+Qnp4ONzc3REVFFTnu05cWlqa090ZXx6Dqg3UiIiIiel7VvnPp/v37UKvVcHFx0Sp3cXEpc+Np0qRJqFWrlnRJRnFycnKQk5MjPU5LS3u+wHJxcQEmTy5Ykpb09HT8+uuv8Pb2li57KWy8Ej2P4j4/SqVSa/SOLrctD0dHR3Tr1g2LFy/G+PHji8y7lJKSUuaOi8OHD6Ndu3Z45513pLLyjqhp1qwZNBoN/vrrr2LPwf7+/ti4cSO8vb1hYmKCnJwc6RKx8lIqlcjKygIAPHjwADExMdJ8M0DBpW5Ps7W1xeDBgzF48GAMGDAA3bt3x8OHD+Hv74/k5GSYmJhU2kT/+jgGVS36qBMZfX2IiIhIl6pQO7vady5V1GeffYa1a9ciKioK5ubmJW43Z84crblFCiUkJMDGxkanmdTqfGkZr8tZ5//7XyA/v9Jnss/MzNRt7kp28eJF3L59Gw8fPoSPj0+RkQTGwNje8ycZa/bMzEwkJiYiPz8fubm5RjXKbcGCBejatStat26N8PBwNGvWDPn5+YiMjMQPP/ygdTeyvLw8rYbkk2U+Pj5YtWoVtm3bBm9vb6xZswYnT56Et7e39By1Wg2NRqO1jyfL3Nzc8Prrr2PUqFGYP38+mjVrhoSEBNy7dw8DBgzAW2+9haVLl2Lw4MEICwuDvb09YmNjsX79eixZsqTYzrXCkUe3bt1CamoqcnJycOrUKaxevRr9+vVDTk4OLC0t4eTkhO+++w5OTk5ISEjAtGnTtF7fokWL4OrqCj8/PygUCqxduxaurq6wsLDAiy++iDZt2qBPnz6YNWsW6tWrh6SkJOzcuRN9+vRBQEAA8vPzIYqiNOfT0+9FYdmT782TZWU5hj48/f9nSAonvk9MTISJiXaV6PHjxzKlMl5lqRPpsz6kD8b6NwhgdjkYa26A2eVgrLkBZi83HbSzKzN3WetE1b5zqUaNGlAqlbhz545W+Z07d+Dq6lrqc+fNm4fPPvsM+/btKzLvxdOmTJmCsLAw6XFaWho8PT1Ru3Zt2NraPv8LKIZSeQ1APpRKE60JZCvk8WMgOhoICAAqufIXHx+vu9x6ULt2bahUKjg7O6Nu3bpyx3kuxvaeP8lYs8fHx8PFxQWxsbEwMzN77tE0cqhTpw5Onz6NWbNmYfLkyUhKSkLNmjUREBCAJUuWaL0WU1PTIq+tsGzcuHG4cOECXn/9dQiCgKFDh+Kdd97Bzp07pecolUooFAqtfTxd9sMPP+Djjz/GhAkT8ODBA9SuXRsff/wxVCoVfHx8cPjwYUyaNAk9e/ZETk4OvLy80L17d1hYWBTbqVc4wqtZs2YACi519fT0xH/+8x9ERERIx127di3Gjx8Pf39/NGjQAF999RU6deokvT4HBwcsWLAA//zzD5RKJVq3bo0dO3ZIl/Lt2rULU6dOxX/+8x/cu3cPrq6u6NChAzw9PaFSqWBiYgJBEKBSqZCTk1PkdSsUCiiVSq335umyZx1DHyoyWqyyiaIIExMTuLu7F+kMqY4javRRJ9JnfUgfjPVvEMDscjDW3ACzy8FYcwPMXi46amdXZu6y1okEsbyzs1ZBbdq0QWBgIL7++msABd+y1q5dG6GhoZg8eXKxz/niiy8wa9Ys7N69G23bti33MdPS0mBnZ4fU1FSdV6bazo5Eclo2XG3NcezjrrrZ6enTBR/46GjA3183+yyBMZyMbty4AW9vb605bYwhd0mYXf+e7Fzy8fEpdeSjoTHkzoJnMdbsxpobMOzs2dnZJf4OVubfaUOm7zqRsb/Pxvo3CGB2ORhrboDZ5WCsuQFmLxcdtbMru3OpLH+rq/3IJQAICwvDiBEj0KpVKwQGBmLhwoXIyMjAqFGjAADDhw+Hu7u7dHvwzz//HOHh4fjll1/g7e2N5ORkAJDuxENV24EDB7B//360bdsWISEhcschIiLSGdaJiIiI6HmwcwnA4MGDce/ePYSHhyM5ORl+fn7YtWuXNKFlQkKC1giV7777Drm5uRgwYIDWfqZPn46IiAh9RicZFN4Bx8TEBKIoGtVcOURERKVhnYiIiIieBzuX/hUaGorQ0NBi1z19G+e4uLjKD0QGq2nTpqhRo8Yz558gIiIyRqwTERERUXmxc4nKxtQUcHcvWFYzjx49QmRkJHr37i1N9MuOJSIiIv0QRRH5+flQq9VyRykiPz8f2dnZcsd4Lsyuf8aaG6ga2U1NTYu9SyyRrKpQO5udS1Q2zZoBt27JnULvRFHEr7/+inv37sHMzAy9e/eWOxIREVG1kZubi6SkJGRmZsodpVj5+fmIjY2VO8ZzYXb9M9bcQNXILggCPDw8OB8cGZYq1M5m5xJRKQRBQO/evbF371507txZ7jhERETVhkajQWxsLJRKJWrVqgUzMzODm+cwNzdXGtVsbJhd/4w1N2D82U1NTXHv3j3cunUL9erV4wgmokrAziUqmwsXgB49gJ07C3pXqzBRFJGRkSF9q+Hh4YGRI0caXIWWiIioKsvNzYVGo4GnpycsLS3ljlMsQRCgUqnkjvFcmF3/jDU3UDWy16xZE3FxccjLy2PnEhmOKtTOVjx7EyIAeXlAYmLBsgrTaDTYvn07vv/+e6Smpkrl7FgiIiKSx5N3pyMiel6sz5NBqkLtbP61JnpCXl4ebt68ifT0dMTHx8sdh4iIiIiIiMjgsXOJ6AkqlQqvvfYahgwZgubNm8sdh4jKaeXKlbC3t9fLsUaOHIm+fftKj0VRxNtvvw1HR0cIgoCzZ8+iU6dOeO+99/SSh4ioLHierFwRERHw8/PT+bZVwdP/197e3li4cKFseYhIt9i5RNVecnIyrl69Kj22s7NDgwYNZExEZLjUajU6deqEV199Vas8NTUVnp6emDp1qlb5xo0b0aVLFzg4OMDCwgINGjTAm2++iTNnzkjbrFy5EoIgSD/W1tYICAjApk2bihx///79ePnll+Hk5ARLS0s0btwYH3zwARITEyvnBZdi0aJFWLlypfR4165dWLlyJbZt24akpCQ0bdoUmzZtwieffKLzY8fFxWm9Z46OjujYsSMOHjxYZNuHDx/ivffeg5eXF8zMzFCrVi28+eabSEhIKLJtcnIy3n33Xfj6+kKlUsHT0xO9evVCZGRkqXnS0tIwdepUNGzYEObm5nB1dUVwcDA2bdoEURR19rqJjIFarUa7du14noRhnSednJzw0ksvab2vlWHixInPPGc+z7YV8eTnR6FQwM3NDYMHDy727wAR0fNi5xKVTb16wP79Bcsq5M6dO1ixYgU2bNiA27dvyx2HyOAplUosXboUu3btwpo1a6Tyd999F46Ojpg+fbpUNmnSJAwePBh+fn7YunUrYmJi8Msvv8DX1xdTpkzR2q+trS2SkpKQlJSEM2fOICQkBIMGDUJMTIy0zffff4/g4GC4urpi48aNuHTpEpYsWYLU1FR8+eWXlf/in2JnZ6f17f/169fh5uaGdu3awdXVFSYmJnB0dISNjc1zH0OtVkOj0ZS4ft++fUhKSsKBAwdQq1Yt9OzZE3fu3JHWP3z4EG3btsW+ffuwZMkSXLt2DWvXrsW1a9fQunVr3LhxQ9o2Li4OAQEB+PPPPzF37lxcuHABu3btQufOnTFu3LgSM6SkpKBdu3ZYtWoVpkyZgtOnT+PAgQMYPHgwPvroI63568orrwrMP0DVj1KpxMqVK3mehGGdJ3fv3o309HT06NEDKSkpxW6ri3OOtbU1nJycdL5tRRV+fhITE7Fx40bExMRg4MCBejk2EZWiKrWzRZJFamqqCEBMTU3V+b7bzNonek3aJraZtU/n+9aHuLg4vR1LrVaLa9asEX/66ScxKyurQvvSZ25dY3b9i4uLE7OyssRLly5V+LMniqJ4OyVTPHztnng7JVMH6UqXnZ0tLlq0SHRwcBBv374tbtmyRTQ1NRXPnj0rbXP06FERgLho0aJi96HRaKR/r1ixQrSzs9Nar1arRVNTU3H9+vWiKIrizZs3RTMzM/G9994rdn+PHj0qdl/Xrl0Te/fuLTo7O4tWVlZiQECAuHfvXq3nLl68WKxbt66oUqlEZ2dnsX///tK6DRs2iE2bNhXNzc1FR0dHsWvXrmJ6erooiqI4YsQIsU+fPtK/AUg/Xl5eoiiKYseOHcUJEyZovXcffPCBWKtWLdHS0lIMDAwU9+/fX+S9+P3338VGjRqJSqVSjI2NFbOzs7Uyx8bGigDEM2fOSGXnz58XAYi///67VPbf//5XtLKyEpOSkrSen5mZKbq7u4vdu3eXynr06CG6u7tLr6+497c4Y8eOFa2srMTExMQi6x4/fiztD4C4efNmrfV2dnbiihUrtF7T2rVrxQ4dOogqlUpctGiRaG5uLu7YsUPreZs2bRKtra3FjIwMURRFMSEhQRw4cKBoZ2cnOjg4iL179xZjY2NLzFyotN/Byvw7Tf+vtPdZl+dIUayc8+TTv5tPMvTzZGH2p8+TrVq1Msrz5NOKO08ePnxYBCDu2rWr2HNO4flo6dKlYsOGDUWVSiU2aNBAXLx4sda+b968KQ4ZMkR0cHAQLS0txYCAAPHYsWOiKIri9OnTxRYtWkjb7t+/X2zdurVoaWkp2tnZie3atZPqLk9vq1arxRkzZoju7u6imZmZ2KJFC3Hnzp1FXtPGjRvFTp06iRYWFmLz5s3FI0eOFHn9Tyru8/PVV18V+d3bsmWL2LJlS1GlUok+Pj5iRESEmJeXJ/2/PHr0SHz77bdFZ2dnUaVSiU2aNBH/+OMPURRF8f79++KQIUPEWrVqiRYWFmLTpk3FX375ReuYT/9fe3l5iQsWLCg1uy4UftZ1fU6pbMZaxxVFZpdDZeYua53IRK89WWS8EhOBb74BQkMBd3e501SI+O8lGoVDgwcMGAClUslbkpLRWncyAVM2XYBGBBQCMOfVZhjcunalHvPdd9/F5s2b8cYbb+DChQsIDw9HixYtpPW//vorrK2t8c477xT7/NLu2KJWq7Fq1SoAgL+/PwBgw4YNyM3NxUcffVTsc0qaPyQ9PR0vv/wyZs2aBZVKheXLl6NXr16IiYlB7dq1cerUKYwfPx6rV69Gu3bt8PDhQ+nSsqSkJAwdOhRffPEF+vXrh8ePH+PgwYPFXua1aNEi1KlTBz/88ANOnjxZ4vkkNDQUly5dwtq1a1GrVi1s3rwZ3bt3x4ULF1Dv32+sMjMz8fnnn2PZsmVwcnKCs7Nzie9VoaysLOk9MzMzA1Bw98u1a9di2LBhcHV11drewsIC77zzDv73v//h4cOHAAouV5k1axasrKzK/P4+eYxatWoVWW9tbY2cnJxn5n/S5MmT8eWXX6Jly5YwNzfHwYMH8csvv6BHjx7SNmvWrEHfvn1haWmJvLw8hISEICgoCAcPHoSJiQk+/fRTdO/eHefPn5feD6oaRFFEVp663M/bGH0L07delM6TM3o3Qf8Aj3Ltw8JUWa67TRnreXLVqlVV8jwJFJz7ACA3N1cqe/qcs2bNGoSHh+Obb75By5YtcebMGYwZMwZWVlYYMWIE0tPT0bFjR7i7u2Pr1q1wdXXF6dOnix09lZ+fj759+2LMmDH49ddfkZ6ejrNnz5b4f7to0SJ8+eWX+P7779GyZUssX74cvXv3xsWLF6XXDgBTp07FvHnzUK9ePUydOhVDhw7FtWvXYGJStqbd3bt3sXnzZq3678GDBzF8+HB89dVXePHFF3H9+nW8/fbbAIDp06dDo9GgR48eePz4MX7++WfUqVMHly5dkp6fnZ2NgIAATJo0Cba2tti+fTveeOMN1KlTB4GBgWXKRVQtVaF2NjuXqGzu3AE++wwYONCoP/R5eXnYvHkzatWqhRdeeAEA2PAgg9Lr60O497jsjXG1RsS99P/fXiMCkzZewLzdV6FUlL0RVNNGhT/efaHM2wuCgO+++w6NGjVCs2bNMHnyZK31V69eha+vr1ZFd/78+QgPD5ceJyYmws7ODkDBXCTW1tYACjpKTE1N8cMPP6BOnToAgH/++Qe2trZwc3Mrc0YAaNGihVZjLiIiAn/88Qe2bt2K0NBQJCQkwMrKCj179oSNjQ28vLzQsmVLAAWNpvz8fLz66qvw8vICADRr1qzY49jZ2cHGxgZKpbJIR06hhIQErFixAgkJCVJHzMSJE7Fr1y6sWLECs2fPBlBwnvr222+1cpfUQdOuXTsoFApkZmZCFEUEBASga9euAIB79+4hJSUFjRo1Kva5jRo1giiKuHbtGoCCRnvDhg2LfyNLcP/+fTx69KjczyvNe++9pzVXzbBhw/DGG28gMzMTlpaWSEtLw/bt27F582YAwLp166DRaLBs2TKpwbZixQrY29sjKioKL730ks6ykfyy8tRoHL67QvvQiMC03y9i2u8Xy/W8SzNDYGlW9qqzsZ4nP/nkE2zevNnozpPPkpKSgk8++QTW1tYIDAxEVlYWgKLnnOnTp+PLL7+Uynx8fHDp0iV8//33GDFiBH755Rfcu3cPJ0+ehKOjIwCgbt26xR4zLS0Nqamp6NmzJ+rUqYOcnJxSM8+bNw+TJk3CkCFDAACff/459u/fj4ULF2Lx4sXSdhMnTsQrr7wCAJgxYwaaNGmCa9eulXouLvz8iKKIzMxMAMD48eOlLxRmzJiByZMnY8SIEQAAX19ffPLJJ/joo48wffp0REZG4sSJE7h8+TLq168vbVPI3d0dEydOlB6/++672L17N9avX8/OJaLSVJF2NsDOJapmYmJicPnyZVy9ehXNmjWTKmxEhuLe4xwkp2VXfD/p5Rst8jyWL18OS0tLxMbG4tatW/D29i51+zfffBO9e/fG8ePH8frrr2t9s21jY4PTp08DKPhGet++ffjvf/8LJycn9OrVC6IolmvEQKH09HRERERg+/btUiMoKytLmsS0W7du8PLygq+vL7p3747u3bujX79+sLS0RIsWLdC1a1c0a9YMISEheOmllzBgwAA4ODiUOwcAXLhwAWq1WqqUF8rJydGac8PMzKzMd6tct24dGjZsiL///hsfffQRVq5cCVNTU61tihtB8LSybKPL55WmVatWWo9ffvllmJqaYuvWrRgyZAg2btwIW1tbBAcHAwDOnTuHa9euFZmzJTs7G9evX9d5PqLy4HmyfCrjPFnYCZ+RkQFfX1+sW7cOLi4uiIuLA6B9zsnIyMD169cxevRojBkzRirPz8+X6oxnz55Fy5YtpY6l0jg6OmLkyJEICQlBt27d0KlTJ7z22mvFdgCmpaXh9u3baN++vVZ5+/btce7cOa2yJ1974b7u3r2Lhg0bSh2QAPD6669jyZIlAP7/85OXl4edO3dizZo1mDVrlrTtuXPncPjwYa0ytVqN7OxsZGZm4vz58/Dw8Cjyf/PktrNnz8b69euRmJiI3Nxc5OTkwNLS8pnvExFVDexcomqladOmuHv3Lnx9fdmxRAappo2qXNs/PXJJ2o+1qtwjl8rjyJEjWLBgAfbs2YNPP/0Uo0ePxr59+6SGTb169XDo0CHk5eVJnR329vawt7fHrVu3iuxPoVBoffPbvHlz7NmzB59//jl69eqF+vXrIzU1FUlJSeX6Vn7ixInYu3cv5s2bh7p160KpVOK1116TLokorGxHRUVhz549CA8PR0REBE6ePAl7e3vs3bsXR44cwZ49e/D1119j6tSpOH78OHx8fMr1fgEFDTilUono6Ogil4M82RiwsLAocwPR09MT9erVQ7169ZCfn49+/frh77//hkqlQs2aNWFvb4/Lly8X+9zLly9DEATpfRcEAVeuXCnXayo8RlmeJwhCkc6o4ibPffqyPDMzMwwYMAC//PILhgwZgl9++QWDBw+WRnukp6cjICBAa+LkJ/NR1WJhqsSlmSHlek5yajaC5/8FzRMfP4UA7AvrCFc783IduzyM9TxpYWGBAQMGVJnz5Lp169C4cWM4OTkVe2ngk+ec9PR0AMDSpUvRpk0bre0K8xReWldWK1aswPjx47Fr1y789ttviIiIwN69e9G2bdty7edJT36JUPg+FF6Wd/bsWWmdra2t9O8nPz+NGjXC9evXMXbsWKxevRpAwWufMWNGkbscAoC5ufkzX/fcuXOxaNEiLFy4EM2aNYOVlRXee+89rUsQiahqY+cSVXm3b9+Gi4uLVCno0qWLzImISlaeS9MKrTuZgI83/Q21KEIpCJj9atNKnXMpMzMTI0eOxNixY9G5c2f4+PigWbNmWLJkCcaOHQsAGDp0KL7++mt8++23mDBhwnMdR6lUSpctDBgwAJMnT8YXX3yBBQsWFNk2JSWl2EbD4cOHMXLkSPTr1w8A8ODBA+nb6kImJiYIDg5GcHAwpk+fDnt7e/z555949dVXIQgC2rdvj/bt2yM8PBxeXl7YvHkzwsLCyv16WrZsCbVajbt37+LFF18s9/OfZcCAAQgPD8e3336L999/HwqFAoMGDcKaNWswc+ZMrctQsrKy8O233yIkJET69j0kJASLFy/WukyiUEnvr0KhwJAhQ7B69WpMnz69yLxL6enpEARB6uxKSkqS1v3zzz/SpRnPMmzYMHTr1g0XL17En3/+iU8//VRa5+/vj3Xr1sHZ2VmrIUVVkyAI5bo0DQB8a1pjzqvNipwnfWtaP/vJz8mYz5Pp6elV6jzp6ekpXTr4LC4uLqhVqxZu3LiBYcOGFbtN8+bNsWzZMjx8+LBMo5eAgtfVsmVLhIWFoVOnTvjll1+KdC7Z2tqiVq1aOHz4MDp27CiVHz58uFyXlZV0id7TJk+ejDp16uD999+Hv78//P39ERMTU+LzmzZtilu3buHq1avFjl46fPgw+vTpg9dffx1AQWfX1atX0bhx4zJnJyLjxs4lKhsnJ2D06IKlEblw4QK2bNmCZs2aoU+fPs81XJzI0A1uXRsd6tdE3P1MeNewhJtd+b5VLa9p06ZBFEV89tlnAABvb2/MmzcPEydORI8ePeDt7Y2goCB88MEH+OCDDxAfH49XX30Vnp6eSEpKwo8//ihNqF9IFEUkJycDKOj42Lt3L3bv3i3NPeLp6YkFCxYgNDQUaWlpGD58OLy9vXHr1i2sWrUK1tbWxd5mu169eti0aRN69eoFQRAwdepUrUlXt23bhhs3bqBDhw5wcHDAjh07oNFo0KBBAxw/fhyRkZF46aWX4OzsjOPHj+PevXslzmH0LPXr18ewYcMwfPhwafLYe/fuITIyEs2bN5fmz3hegiBg/PjxiIiIwH/+8x9YWlpi9uzZiIyMRLdu3fDFF1+gadOmiI2Nxf/+9z/k5eVpzeGxePFitG/fHoGBgZg5cyaaN2+O/Px87N27F999912JI6BmzZqFqKgotGnTBrNmzUKrVq1gamqKgwcPYs6cOTh06BCsrKzQpUsXfPPNNwgKCoJarcakSZOKXMJXkg4dOsDV1RXDhg2Dj4+P1oiCYcOGYe7cuejTpw9mzpwJDw8PxMfHY9OmTfjoo4/g4VG+SZupatL3eXLKlClGe56cNm1alT1PlsWMGTMwfvx42NnZoXv37sjJycGpU6fw6NEjhIWFYejQoZg9ezb69u2LOXPmwM3NDWfOnEGtWrUQFBSkta/Y2Fj88MMP6N27N2rVqoULFy7gn3/+wfDhw4s99ocffojp06ejTp068PPzw4oVK3D27NliR2ZWlKenJ/r164fw8HBs27YN4eHh6NmzJ2rXro0BAwZAoVDg3Llz+Pvvv/Hpp5+iQ4cO6NChA/r374/58+ejbt26uHLlCgRBQPfu3VGvXj389ttvOHLkCBwcHDB//nzcuXOHnUtEz2Kk7exiVcKd6qgMKvMWx21m7RO9Jm0T28zap/N964Mub6P4zz//iDNmzBDXr18v5ufn62y/xTHW21aKIrPLIS4uzuhuiSuKohgVFSUqlUrx4MGDRda99NJLYpcuXbRun71u3TqxU6dOop2dnWhqaip6eHiIr732mnTLZlEsuEUynrg9tUqlEuvXry/OmjWryO/t3r17xZCQENHBwUE0NzcXGzZsKE6cOFG8ffu2tK8nb7ccGxsrdu7cWbSwsBA9PT3FhQsXat0K+eDBg2LHjh1FBwcH6ZbO69atE0VRFC9duiSGhISINWvWlDJ9/fXX0r6fvMW2KIriggULpFtrF3r6tsu5ublieHi46O3tLZqamopubm5iv379xPPnzxebv9DTtzsv7hbboiiKGRkZooODg/j5559LZffu3RPfffdd0dPTUzQ1NRVdXFzEkSNHivHx8UWOc/v2bXHcuHGil5eXaGZmJrq7u4u9e/fWug14cVJSUsTJkyeL9erVE83MzEQXFxcxODhY3Lx5s/T5TkxMFF966SXRyspKrFevnrhjxw7Rzs5OuvV3Sa+p0EcffSQCEMPDw4usS0pKEocPHy7WqFFDVKlUoq+vrzhmzJhn/o0t7XewMv9O0/8r7X02hnPk07+bomg858nC7E+fJ7/55hujPE8+7VnnlNLWr1mzRvTz8xPNzMxEBwcHsUOHDuKmTZuk9XFxcWL//v1FW1tb0dLSUmzVqpV4/PhxURRFcfr06WKLFi1EURTF5ORksW/fvqKbm5toZmYm1q5dWwwPDxfVanWRbUVRFNVqtRgRESG6u7uLpqamYosWLcSdO3eWmvnRo0cigFLP0yW9Z0ePHhUBSNl37doltmvXTrSwsBBtbW3FwMBA8YcffhBFseCz/uDBA3HUqFGik5OTaG5uLjZt2lTctm2bKIqi+ODBA7FPnz6itbW16OzsLP7vf/8Thw8frvX///T/tZeXl7hgwYISc+tK4WfdGM4pTzLWOq4oMrscKjN3WetEgihWwmyc9ExpaWmws7NDamqqzofxt50dieS0bLjamuPYx111s9OsLODGDcDXFyjnteblFR8fL91xRBdu3boFd3f3Sh+1pOvc+sTs+hcfHw8XFxfExsbCx8cH5uZln/dDbjk5OVCpyjdHk6Ew1uzGmhsw7OzZ2dkl/g5W5t9p+n+lvc+l/f8YCkP+fD8Ls+ufseYGqkZ2YzinPMlY67gAs5eLjtrZlZm7rHUiRYlriJ50+TLQtGnB0oBlZ2dj69atWvN4eHh48HI4IiIiIiIiMixG0s4uC3YuUZWyceNGnDlzBlu2bJE7ChEREREREVG1wAm9qUrp1q0bUlNTeUc4IiIiIiIiIj1h5xIZvezsbOm6aWdnZ4wdO5aXwRERERERERHpCS+Lo7IRBMDMrGBpIERRxNGjR/HVV1/h/v37Ujk7loiIiIiIiMjgGWA7+3lx5BKVTcuWQE6O3Cm0aDQaXLp0CVlZWbh48SI6duwodyQiIiIiIiKisjHAdvbzYucSGS2lUokhQ4bg8uXLCAgIkDsOERERERERUbXEy+KobC5fBvz9Zb9F4uPHj3HlyhXpsZWVFVq1asVL4YiIiIiIiMi4GEg7WxfYuURlk5UFnDlTsJTJ48ePsWzZMmzYsAE3btyQLQcRERERERFRhRlAO1tX2LlERsPa2hpeXl5wcHCAg4OD3HGIDMedO8C6dcCyZQXLO3dkjRMVFQVBEJCSkqLX465cuRL29vYV2kdcXBwEQcDZs2dL3Eau10dEFcDzJACeJ4mIqPKwc4kMniiKAAruAte7d2+MHj2anUtEAHDhAjB0KODhAQwZAowZU7D08Cgov3BB54cUBAHm5uYQBKHYn4iICJ0f0xhlZ2dj3LhxcHJygrW1Nfr37487z2jMjhw5ssj72b17d61tHj58iGHDhsHW1hb29vYYPXo00tPTtbY5f/48XnzxRZibm8PT0xNffPFFkWNt2LABDRs2hLm5OZo1a4YdO3ZU/EUTGSKZzpOl/fA8WbKynL+eVtx7vHbtWq1toqKi4O/vD5VKhbp162LlypVF9rN48WJ4e3vD3Nwcbdq0wYkTJ7TWP895nYioOmHnEhksURSxb98+7Nu3TyozMTGBhYWFjKmIDMTu3UBgIPDbb0B+vva6/PyC8sDAgu10KCkpCXFxcUhKSsLChQtha2uLpKQk6WfixInPtd/c3Fyd5pTb+++/jz/++AMbNmzAX3/9hdu3b+PVV1995vO6d++u9X7++uuvWuuHDRuGixcvYu/evdi2bRsOHDiAt99+W1qflpaGl156CV5eXoiOjsbcuXMRERGBH374QdrmyJEjGDp0KEaPHo0zZ86gb9++6Nu3L/7++2/dvQFEhkDG82ThD8+TZVeW81dJVqxYofUe9+3bV1oXGxuLV155BZ07d8bZs2fx3nvv4a233sLuJ/7f161bh7CwMEyfPh2nT59GixYtEBISgrt370rbPO95nYioumDn0r+e9W3Fky5evIj+/fvD29sbgiBg4cKF+gsqFx8fYP36gqWeJCQk4PDhwzhy5Ahu376tt+MSGbwLF4C+fQtuW/p0g6lQfn7B+r59dfrNvKurq/RjZ2cHQRC0yqytraVto6Oj0apVK1haWqJdu3aIiYmR1kVERMDPzw/Lli2Dj48PzM3NAQApKSl46623ULNmTdja2qJLly44d+6c9Lxz586hc+fOsLGxga2tLQICAnDq1CmtjLt370ajRo1gbW0tddYU0mg0mDlzJjw8PKBSqeDn54ddu3aV+pp37NiB+vXrw8LCAp07d0ZcXFyp26empuLHH3/E/Pnz0aVLFwQEBGDFihU4cuQIjh07VupzVSqV1vv55CjNy5cvY9euXVi2bBnatGmDF154AV9//TXWrl0rnSPXrFmD3NxcLF++HE2aNMGQIUMwfvx4zJ8/X9rPokWL0L17d3z44Ydo1KgRPvnkE/j7++Obb74pNRtVH1WiTsTz5DPPky1atJDtPFmcspy/SmJvb6/1Hhe+VwCwZMkS+Pj44Msvv0SjRo0QGhqKAQMGYMGCBdI28+fPx5gxYzBq1Cg0btwYS5YsgaWlJZYvXw6gYud1IqJSydDOrizsXELZvq14UmZmJnx9ffHZZ5/B1dVVz2ll4uAADBxYsNQTLy8vdOnSBX369EGtWrX0dlwigzd7dkGj6N9LRkskigXbzZmjn1xPmTp1Kr788kucOnUKJiYmePPNN7XWX7t2DRs3bsSmTZukuTsGDhyIu3fvYufOnYiOjoa/vz+6du2Khw8fAigYuePh4YGTJ08iOjoakydPhqmpqbTPzMxMzJs3D6tXr8aBAweQkJCgNUrgm2++wZdffol58+bh/PnzCAkJQe/evfHPP/8U+xpu3ryJV199Fb169cLZs2fx1ltvYfLkyaW+7ujoaOTl5SE4OFgqa9iwIWrXro2jR4+W+tyoqCg4OzujQYMGGDt2LB48eCCtO3r0KOzt7dGqVSupLDg4GAqFAsePH5e26dChA8zMzKRtQkJCEBMTg0ePHknbPJmtcJtnZaPqocrUiXiefOZ5cvny5cWeJxctWlQp50lBEIq9HK1QWc5fJRk3bhxq1KiBwMBALF++XJpSoXC/pZ3zcnNzER0drbWNQqFAcHCwtE1FzutERKWSoZ1dWdi5hGd/W/G01q1bY+7cuRgyZAhUKpWe08rkzh1g/vxKnwDz4cOHyMvLkx6/+OKL8PPzq9RjEhmVO3eKv8SjJPn5wIYNQAkNw8o0a9YsdOzYEY0bN8bkyZNx5MgRZGdnS+tzc3OxatUqtGzZEs2bN8ehQ4dw4sQJbNiwAa1atUK9evUwb9482Nvb47fffgNQMKIxODgYDRs2RL169TBw4EC0aNFC2mdeXh6WLFmCVq1awd/fH6GhoYiMjJTWL1y4EJMmTcKQIUPQoEEDfP755/Dz8ytxtMV3332HOnXq4Msvv0SDBg0wbNgwjBw5stTXnZycDDMzsyKT5rq4uCA5ObnE53Xv3h2rVq1CZGQkPv/8c/z111/o0aMH1Gq1tF9nZ2et55iYmMDR0VHab3JyMlxcXIoct3BdaduUlo2qjypRJ+J5skznyYCAgGLPk/PmzauU82SDBg1gZ2dX4ntRlvNXcWbOnIn169dj79696N+/P9555x18/fXXz9xvWloasrKycP/+fajV6lLPi897XicieiY9tbP1wUTuAHIr/LZiypQpUtnT31boQk5ODnJycqTHaWlpOtu3XiQmAh98AHTqBDz1x1dXEhISsHbtWtSoUQO+vr5QKNj3SVREVFTZG0yF8vMLnjdoUGUkKlHz5s2lf7u5uQEA7t69i9q1awMoGJ1Ys2ZNaZtz584hPT0dTk5OWvvJysrC9evXAQBhYWF46623sHr1agQHB2PgwIGoU6eOtK2lpaXWYzc3N2nERVpaGm7fvo327dtr7b99+/Zal5Q86fLly2jTpo1WWVBQUNnegHIaMmSI9O9mzZqhefPmqFOnDqKiovDCCy9UyjGJnqSPOpFe6kM8T5bpPFn4/6Cv8+SVK1dKeSee37Rp06R/t2zZEhkZGZg7dy7Gjx9fKccjItIpPbSz9aXady6V9m2FLv8IzpkzBzNmzChSnpCQABsbG50dBwDU6nxpGR8fr5N9miUlwQ0Fk1Tm6mifT7t79y5ycnKQkZGBa9euGc43oGWUmZmps/db35hd/zIzM5GYmIj8/Hzk5uZCEIQyPU/x8CFMn71ZEXkPHkDzRIOuIjQaDXJycqRRhjlP7bdw0tnC7QBI22ZlZSEnJwf5+fmwtLTUem5KSgrc3NywZ8+eIse0s7NDTk4OpkyZggEDBmDnzp3YvXs3pk+fjtWrV6NPnz7Iy8uDqamp1j7z8/MhiqJWgzY3N1drG7VaLWV9ehuNRgO1Wq21/ZOv++nXDgCOjo7Izc3FnTt3tL7lTk5ORo0aNYp9TnHc3d1Ro0YNXL58Ge3atYOTk5N0nnzy9T18+BBOTk7IyclBzZo1kZSUpLXNzZs3AQAODg7IycmBi4sLEhMTtbZJTEyEi4tLmbOVx5OfA0OTm5uL/Px8JCYmwsREu0r0+PFjmVLJRx91ovLUh/Lz88t9jgT0e5581ufbkM+ThceW4zxZnLKcvwqV9r77+/vjk08+QVpaGlQqFZydnXH79m2t7W/dugVbW1soFArY2NhAqVTi1q1bWtvcvn0bzs7OyMnJ0dl53ZDPh89SFbKXds43RMZaxwWYvTx01c6uzNxlrRMZ/m9VFTFlyhSEhYVJj9PS0uDp6YnatWvD1tZWp8dSKq8ByIdSaQIvLy/d7PTfeT/c3NwAXe3zKV5eXnB2dkZ+fr7WN2zGIj4+Xnfvt54xu/7Fx8fDxcUFsbGxMDMzK3tnqqPjcx3P1MkJ0FGHbU5ODlQqlTSHx9PZC+fLUKlU0rqny0xMTCAIgtZzAwMDMX36dFhaWsLb27vE4zdt2hRNmzbFhx9+iKFDh+Lnn3/GoEGDis3zZFnNmjVRq1YtnDx5Et26dZO2OXbsGAIDA4vkValUaNKkCbZu3aq1z+jo6CKv70lBQUEwNTXFoUOH0L9/fwBATEwMbt68iRdffLHM/9e3bt3CgwcPULt2bSgUCnTo0AEpKSn4+++/ERAQAAD466+/oNFo8MILL0ClUuGFF17A1KlToVAopNf+119/oUGDBtJ8OO3atcNff/2lNcfK/v370a5du0rp1C/8vBgiURRhYmICd3d3rQmAASMcYWwkylMfys7OLv85EtDrefJZn29DPk8Wdy7X13myOGU5fxUq7X2/ePEiHBwcpM9T+/btsWPHDq3to6KiEBQUJOULCAjAgQMHMHDgQAAFnRFRUVEIDQ2FSqXS2XndkM+Hz1IVspd2zjdExlrHBZi9XHTUzq7M3GWtE1X7645q1KgBpVKJO09d43jnzh2dTkypUqlga2ur9VPdqdVq7N27V+vD6uXlZRTfJBDJplMnoLy/IyYmBc8zcMHBwQgKCkLfvn2xZ88exMXF4ciRI5g6dSpOnTqFrKwshIaGIioqCvHx8Th8+DBOnjyJRo0alfkY77//Pj7//HOsW7cOMTExmDx5Ms6ePYsJEyYUu/1///tf/PPPP/jwww8RExODX375pdQJaYGC0QOjR49GWFgY9u/fj+joaIwaNQpBQUFo27attF3Dhg2xefNmAEB6ejo+/PBDHDt2DHFxcYiMjESfPn1Qt25dhISEAAAaNWqE7t27Y8yYMThx4gQOHz6M0NBQDBkyRLrpwWuvvQYzMzOMHj0aFy9exLp167Bo0SKtxvyECROwa9cufPnll7hy5QoiIiJw6tQphIaGlvl9pKpJH3UivdSHeJ6s0Hnyww8/rJTz5JPnvOKU5fy1efNmNGzYUHr8xx9/YNmyZfj7779x7do1fPfdd5g9ezbeffddrXw3btzARx99hCtXruDbb7/F+vXr8f7770vbhIWFYenSpfjpp59w+fJljB07FhkZGRg1ahSAsp/XiYiqs2rfuWRmZoaAgACtiQw1Gg0iIyMrbV4No2RnB/TqVbDUkV27duHIkSNYu3YtNBqNzvZLVKW5uAADBpS94WRiUnAHiqcmgjZEgiBgx44d6NChA0aNGoX69etjyJAh0igvpVKJBw8eYPjw4ahfvz4GDRqEHj16FHuJTUnGjRuHsLAwfPDBB2jWrBl27dqFrVu3ol69esVuX7t2bWzcuBFbtmxBixYtsGTJEsyePfuZx1mwYAF69uyJ/v37o0OHDnB1dcWmTZu0tomJiUFqaioAQKlU4vz58+jduzfq16+P0aNHIyAgAAcPHtT6pnjNmjVo2LAhunbtipdffhkvvPACfvjhB2m9nZ0d9uzZg9jYWAQEBOCDDz5AeHg43n77bWmbdu3a4ZdffsEPP/yAFi1a4LfffsOWLVvQtGnTMr+PVDVVmToRz5MVOk+OHz++Us6TT57zilOW81dqaipiYmKkx6ampli8eDGCgoLg5+eH77//HvPnz8f06dOlbXx8fLB9+3bs3bsXLVq0wJdffolly5ZJHfcAMHjwYMybNw/h4eHw8/PD2bNnsWvXLq1LRMtyXiciKrdKaGfLRRDFZ92jtepbt24dRowYge+//x6BgYFYuHAh1q9fjytXrsDFxQXDhw+Hu7s75vx7m9rc3FxcunQJAPDyyy9j2LBhGDZsGKytrVG3bt0yHTMtLQ12dnZITU3V+bd2bWdHIjktG6625jj2cVed7luXUlJSsGrVKnTv3h3169eXyo11GKWx5gaYXQ5PXhbn4+NTvuHZFy4AgYFATk7pt9kWhIJLPE6cAJo1q3jof1WFofHGxlhzA4advfCyq+J+Byvz77Qh03edqLT3ubT/n2fS03nSkD/fz8Ls+mesuYGqkb1C5xQZGGsdF2B2OVT2ZXFlqRPx+iMUfFtx7949hIeHIzk5GX5+flrfViQkJGjduez27dto2bKl9HjevHmYN28eOnbsiKioKH3H14+8PCAlBbC3B0yfZ5rMwt3kSdfR29vbY9y4cVAqlbrJSFRdNGsGbNkC9O1bcIej4u6KZGJS8LNli047loioaqsydSKeJ4mIyBjoqJ1tCNi59K/Q0NAS55t4unLk7e2Najfg68IFICAAiI4G/P2faxcxMTH4448/8Nprr0nzg7Bjieg5hYQUfNM+Zw6wYYN2w6nwEo8pU9hgIqJyqzJ1Ip4niYjI0OmgnW0o2LlEeiGKIqKjo5GRkYETJ06gb9++ckciMn7NmgG//AIsXAhERQFpaYCtbcGktEYwdwgRUaXjeZKIiEgv2LlEeiEIAvr3749jx47hhRdekDsOUdXi7AwMGiR3CiIiw8XzJBERUaWq9neLo8qTm5uLK1euSI9VKhU6duzIS+GIiIiIiIiIqhB2LlGlyM3NxU8//YR169ZJd5EhIiIiIiIioqqHl8VR2bRoAaSmAlZWZdrc1NQU7u7uePToEWxsbCo5HBEREREREZGRKWc725Cxc4nKRqksmACzjARBQPfu3dG+fXvY2dlVYjAiIiIiIiIiI1TOdrYh42VxVDb//FNwS99//ilxkzNnzmDbtm3SLYkVCgU7loiIiIiIiIiKU4Z2trFg5xKVzePHwJ49BctiPHjwAH/88Qeio6MRExOj53BEREREJAgCtmzZUqZtzc3Ny7wtGSdvb28sXLhQelyezwcR6ckz2tnGhJ1LpBNOTk7o3r07XnzxRTRo0EDuOERUSQRBgLm5OQRBKPYnIiICcXFxWmVOTk546aWXcObMGWk/nTp1ktabm5ujfv36mDNnjjTysTw2bNiAhg0bwtzcHM2aNcOOHTue+ZzFixejUaNGsLCwQIMGDbBq1aoi26SkpGDcuHFwc3ODSqVC/fr1tfb93XffoXnz5rC1tYWtrS2CgoKwc+dOrX1kZ2dj3LhxcHJygrW1Nfr37487d+6U6/WtXLmy2Pd82bJl0vrCMoVCAQ8PD4waNQp3796V9vHk82xtbdG6dWv8/vvv5coBAKIoIjw8HG5ubrCwsEBwcDD+KcM3bYsXL4a3tzfMzc3Rpk0bnDhxosT99+jRo9QG0IMHD+Dh4QFBEJCSklLkOM/6fyXSh5EjR0q/c2ZmZqhbty5mzpyJ/Pz8Sj1uUlISevToUaZt4+LiyrytLj3PeeTx48d477334OXlBQsLC3Tq1AknT56U1ufl5WHSpElo1qwZrKysUKtWLQwfPhy3b9/W2s/Vq1fRp08f1KhRA7a2tnjhhRewf//+IsdbuXIlmjdvDnNzczg7O2PcuHHleo0RERHS/79SqYSnpyfefvttPHz4sFz7MQQPHz7EsGHDULNmTdjb22P06NFIT08v9TnXr19Hv379ULNmTdja2mLQoEHF/u3bvn072rRpAwsLCzg4OKBv377SugcPHqB79+6oVasWVCoVPD09ERoairS0NK19REVFwd/fHyqVCnXr1sXKlSt18bKJ6Dmwc4meW1ZWFrKysqTHgYGB6NKlCwRBkDEVEVWmpKQkxMXFISkpCQsXLoStrS2SkpKkn4kTJ0rb7tu3D0lJSdi9ezfS09PRo0cPrc6AMWPGICkpCTExMZgyZQrCw8OxZMmScuU5cuQIhg4ditGjR+PMmTPo27cv+vbti7///rvE53z33XeYMmUKIiIicPHiRcyYMQPjxo3DH3/8IW2Tm5uLbt26IS4uDr/99htiYmKwdOlSuLu7S9t4eHjgs88+Q3R0NE6dOoUuXbqgT58+uHjxorTN+++/jz/++AMbNmzAX3/9hdu3b+PVV18t12sEUOR9TkpKwrBhw4qsv3XrFpYuXYqdO3fijTfe0NrHihUrkJSUhFOnTqF9+/YYMGAALly4UK4cX3zxBb766issWbIEx48fh5WVFUJCQpCdnV3iczZs2ICwsDBMnz4dp0+fRosWLRASEqLV+VVo4cKFz/wbMnr0aDRv3rxIeVn+X4n0qXv37khKSsI///yDDz74ABEREZg7d26x2+bm5urkmK6urlCpVDrfVpee5zzy1ltvYe/evVi9ejUuXLiArl27Ijg4GImJiQCAzMxMnD59GtOmTcPp06exadMmxMTEoHfv3lr76dmzJ/Lz8/Hnn38iOjoaLVq0QM+ePZGcnCxtM3/+fEydOhWTJ0/GxYsXsW/fPoSEhJT7dTZp0gRJSUlISEjAihUrsGvXLowfP77c+5HbsGHDcPHiRWzfvh3btm3DgQMH8Pbbb5e4fUZGBl566SUIgoA///wThw8fRm5uLnr16gWNRiNtt3HjRrzxxhsYNWoUzp07h8OHD+O1116T1isUCvTp0wdbt27F1atXsXLlSuzbtw///e9/pW1iY2PxyiuvoHPnzjh79izee+89vPXWW9i9e3flvBlEVDqRZJGamioCEFNTU3W+7zaz9olek7aJbWbt091Oo6NFEShYiqL44MED8euvvxZXrlwp5ufn6+44oijGxcXpdH/6Yqy5RZHZ5RAXFydmZWWJly5dErOysuSOUy7Z2dmiKIriihUrRDs7uyLrY2NjRQDimTNnpLLDhw+LAMRdu3aJoiiKHTt2FCdMmKD1PH9/f7Ffv37lyjJo0CDxlVde0Spr06aN+J///KfE7EFBQeLEiRO1ysPCwsT27dtLj7/77jvR19dXzM3NLVceBwcHcdmyZaIoimJKSopoamoqbtiwQVp/+fJlEYB49OjRMu+zpPe5tPWzZs0SFQqFmJmZKYqiKAIQN2/eLK1PS0sTAYiLFi0qcw6NRiO6urqKc+fOlcpSUlJElUol/vrrryU+r3Xr1uK4ceOkx2q1WqxVq5Y4Z84cre3OnDkjuru7i0lJSUXyFvr222/Fjh07ipGRkSIA8dGjR9K6svy/Pq2038HK/DtN/6+099kYzpGF58OnjRgxQuzTp49WWbdu3cS2bdtqrf/0009FNzc30dvbWxRFUUxISBAHDhwo2tnZiQ4ODmLv3r3F2NhYrf38+OOPYuPGjUUzMzPR1dVV6/fryd+dnJwccdy4caKrq6uoUqnE2rVri7Nnzy52W1EUxfPnz4udO3cWzc3NRUdHR3HMmDHi48ePi7ymuXPniq6urqKjo6P4zjvvlOs8+TznkczMTFGpVIrbtm2TyrKzs0V/f39x6tSpJR7rxIkTIgAxPj5eFEVRvHfvnghAPHDggLRN4blw7969oiiK4sOHD0ULCwtx376K1aGnT58utmjRQqssLCxMdHBw0CpbunSp2LBhQ1GlUokNGjQQFy9erLX+5s2b4pAhQ0QHBwfR0tJSDAgIEI8dOyaKoiheu3ZN7N27t+js7CxaWVmJrVq1kl5HIS8vL3HBggXS45LOrSW5dOmSCEA8efKk9FnfuXOnKAiCmJiYWOxzdu/eLSoUCq3f6ZSUFFEQBClfXl6e6O7uLv29LKtFixaJHh4e0uOPPvpIbNKkidY2gwcPFkNCQrTKCrMbwznlScZaxxVFZi+Xp9rZz6syc5e1TsSRS1Q2np7AN98ULFEw/Pjx48d49OgRHleB60OJqHJZWFgAKP7beVEUcfDgQVy5cgVmZmZSeVRUFARBQFxcXIn7PXr0KIKDg7XKQkJCcPTo0RKfk5OTA3Nz8yL5Tpw4gby8PADA1q1bERQUhHHjxsHFxQVNmzbF7NmzoVari92nWq3G2rVrkZGRgaCgIABAdHQ08vLytPI1bNgQtWvXLjWfLlhYWECj0RR7CU5+fj5+/PFHANB6vyMiIuDt7V3iPmNjY5GcnKz1euzs7NCmTZsSX09ubi5Onz6t9RyFQoHg4GCt52RmZuK1117D4sWL4erqWuy+Ll26hJkzZ2LVqlVQKIpWX8ry/0okJwsLC61zYGRkJGJiYrB3715s27YNeXl5CAkJgY2NDQ4ePIjDhw/D2toa3bt3l5733XffYdy4cXj77bdx4cIFbN26FXXr1i32eF999RW2bt2K9evXIyYmBmvWrCnxdzwjIwMhISFwcHDAyZMnsWHDBuzbtw+hoaFa2+3fvx/Xr1/H/v378dNPP2HlypValyFVxnkkPz8farW62N/vQ4cOlXis1NRUCIIAe3t7AAVTOBReLpuRkYH8/Hx8//33cHZ2RkBAAABg79690Gg0SExMRKNGjeDh4YFBgwbh5s2bJR6nLOLi4rB7926tc+6aNWsQHh6OWbNm4fLly5g9ezamTZuGn376CQCQnp6Ojh07IjExEVu3bsW5c+fw0UcfSaN/0tPT8fLLLyMyMhJnzpxB9+7d0atXLyQkJJQ5V6dOnTBy5MgS1x89ehT29vZo1aqVVBYcHAyFQoHjx48X+5ycnBwIgqA1Ks7c3BwKhUL6/zp9+jQSExOhUCjQsmVLuLm5oUePHqWOOr59+zY2bdqEjh07auUrbx2AyOA81c42ZiZyByAjUbMm8MT15i4uLnjttdfg6OgIGxsbGYMRVUFJSQU/T3JwAHx8gOxs4NKlos/x9y9YxsQAGRna67y9AUdH4N494OkKso0NUK+ezqIXJyUlBZ988gmsra0RGBgolX/77bdYtmwZcnNzkZeXB3Nzc61LBiwtLdGgQQOYmpqWuO/k5GS4uLholbm4uGhd4vC0kJAQLFu2DH379oW/vz+io6OxbNky5OXl4f79+3Bzc8ONGzfw559/YtiwYdixYweuXbuGd955B3l5eZg+fbq0rwsXLiAoKAjZ2dmwtrbG5s2b0bhxYymbmZmZ1LApa77ipKamwtraWnpsbW1d4j7++ecfLFmyBK1atdI6Pw8dOhRKpRJZWVnQaDTw9vbGoEGDpPU1atRAnTp1SsxQeLz/a+/Ow6Iq3zeA38M2ILKo7C6gqEhBmDtuqKmYSFiaO6JZlpmZS7mH+5bgmuZSaG6YSmpioBK4mwvizxWVRdMCNRVBZJ339wdxvo4sMiPMMHp/rotLOfPOmfucGc4888xZVFnf9+/fR35+frH3uXr1qvT7mDFj0Lp1a/j5+RU7n+zsbPTv3x/fffcd6tSpg8TExCJjyvK80itEh7aTQghERUUhMjISo0aNkqabmppi3bp1UsNh06ZNUCgUWLdunXR4aEhICCwtLRETE4OuXbti9uzZGDduHEaPHi3Np3nz5sU+7q1bt9CgQQO0bdsWMpkMjo6OJWbcsmULsrKy8PPPP8PU1BQAsGLFCvj6+mLBggXS33C1atWwYsUK6Ovro1GjRvDx8UFUVBQ++eQTABWzHTEzM4OnpydmzZoFV1dX2NraYsuWLThx4kSJjbWsrCxMmDAB/fv3h/l/l/iWyWQ4ePAgevbsCTMzM+jp6cHGxgYRERGoVq0aACAxMREKhQJz587F0qVLYWFhgalTp6JLly74v//7P6Xm0ItcuHABVatWRX5+vnTI38KFC6XbAwMDERQUJB0qXbduXVy+fBmrV69GQEAAtmzZgnv37uH06dOoXr06ACgtr4eHBzw8PKTfZ82ahV9//RV79uwp0hQsSZ06dUrdNqakpMDGxkZpmoGBAapXr17i89WqVSuYmppiwoQJmDt3LoQQmDhxIvLz8/HPf3+zhdvw6dOnIzg4GE5OTggKCkKHDh1w7do1aXmBgveu3bt34+nTp/D19ZXON1iYr7jX0uPHj/H06VPpiy2iSu25z9m6jM0lKhPx779IWL4c1QcNQvX/3thKK1KI6CWsXg3MmKE8beBAYNMm4PZt4L9vWJUUngh7yBDg5Enl2zZuBAYNAn75BXi+4OzaFaigcxO0bt0aenp6ePLkCerVq4dt27YpFYEDBw7ElClT8PDhQwQGBqJ169Zo3bq1dHuLFi2UGhDlZdq0aUhJSUGrVq0ghICtrS0CAgKwcOFCaY8YhUIBGxsbrFmzBvr6+mjatCnu3LmD7777Tqm55OLigri4OKSlpWHHjh0ICAjAoUOHpAZTeTEzM0NsbKz0+/N77hQ2nxQKBbKystC2bVulAhwAFi9ejM6dOyMxMRFjxozBsmXLlAr4L774oswfSMrTnj178Mcffyid8P15kyZNgqurKwYNGlTimLI8r/QK0YHt5N69e1G1alXk5uZCoVBgwIABmD59unS7u7u7UrPi/PnzuHHjRpEv7bKyspCQkIC7d+/i77//xjvvvFOmxx8yZAi6dOkCFxcXdOvWDT169EDXrl2LHXvlyhV4eHhIjSUAaNOmDRQKBeLj46Vt95tvvgl9fX1pjL29vdK52ypqO7Jx40Z89NFHqFmzJvT19fH222+jf//+OHv2bJGxubm56NOnD4QQWLVqlTRdCIGRI0fCxsYGR44cgYmJCdatWwdfX1+cPn0a9vb2UCgUyM3NxbJly6R1tXXrVtjZ2SE6Olqlcy+5uLhgz549yMrKwqZNmxAXF4fPP/8cQMGeYgkJCRg2bJjUmAMK9tKysLAAAMTFxeHtt99W2k4/KyMjA9OnT0d4eDj++ecf5OXl4enTpyrtuVQRFz2wtrbG9u3bMWLECCxbtgx6enro378/mjRpovQeCwBTpkxBr169ABQ0UmvVqoXt27fj008/lea3ePFiBAYG4tq1a5g0aRLGjh2LlStXlntuIq158ADYtw/o3r3gSw4dxuYSlcn/7dkDjxkzEJqZiQ9mz1bpmxsiUtGnnwLPnYQU/32rilq1gGKKacn69cV/Iw8AffoA/x2yJanAPQ+3bduGN954AzVq1Ciy9w5QcChE4bewv/zyC+rXr49WrVoV2cW9NHZ2dkWuQJOamlrioVVAwaEUP/30E1avXo3U1FTY29tjzZo1MDMzg7W1NYCCD0yGhoZKH6JcXV2RkpKCnJwcaRtYeBUoAGjatClOnz6NpUuXYvXq1bCzs0NOTg4ePXqktPwvylccPT29Er+hB/7XfNLT05OuwPQ8Ozs71K9fH/Xr10dISAi6d++Oy5cvF/lWuiSFmQvX2bPL07hx42LvY2VlBX19/VKfoz/++AMJCQlFXiO9evVCu3btEBMTgz/++AMXLlzAjh07AEC6qqCVlRWmTJmCGTNmlOl5pVeIDmwnO3bsiFWrVsHIyAgODg4wMFAuu59t5AAFzYKmTZti8+bNReZlbW2tcpO0SZMmSEpKwu+//46DBw+iT58+6Ny5s/R3pI7n9ySVyWRKJ2l+EXW2IwDg7OyMQ4cO4cmTJ3j8+DGqV6+OwYMHo169ekrjChtLN2/exB9//CHttQQUbGv27t2Lhw8fStNXrlyJAwcOYMOGDZg4caKU6dkvCKytrWFlZaVS0wZQfn+YP38+fHx8MHv2bMybN0+62tratWvRsmVLpfsVvu+8aK+b8ePH48CBA1i0aBHq168PExMT9O7du9xODg8UPF/PX3whLy8PDx48KPV9rGvXrkhISMD9+/dhYGAAS0tL2NnZSc9XcetZLpejXr16RdaznZ0d7Ozs0KhRI1SvXh3t2rXDtGnTYG9vX2INYG5uzr2WSHckJwP+/gXvW2wu0eugwX+7g7/55ptsLBFVNHv7gp/iGBv/79CO4ri4lHybtXXBj4bUrl271MMjnlW1alWMHj0a48ePx7lz58p81UlPT09ERUXhq6++kqYdOHBAOu9RaQwNDVGrVi0AQGhoKHr06CF9eGvTpg22bNkChUIhTbt27Rrs7e1L3QYqFApkZ2cDKGg2GRoaIioqSvpmNj4+Hrdu3SpTPlW8qPn0vBYtWqBp06aYM2cOli5dWqb71K1bF3Z2doiKipI+BD5+/Bh//vknRowYUex9jIyM0KRJE0RFRUmXmFYoFIiKipL2bpg4cSI+/vhjpfu5u7tj8eLF8PX1BVBwVaFnr056+vRpfPTRRzhy5EiR11hpzyu9QnRgO2lqaqrS32WTJk2wbds22NjYKDVFnuXk5ISoqCh07NixTPM0NzdH37590bdvX/Tu3RvdunXDgwcPiuwN4+rqivXr1+PJkydS0+vYsWPQ09ODS2nrS0XqbEeeZWpqClNTU6SkpCAyMlLpMLPCxtL169cRHR2NGjVqKN03MzMTQNE9P/X09KQGWZs2bQAUbKsLtyMPHjzA/fv3X3qP/alTp6JTp04YNWoUHBwc4ODggMTERKUrfz7rrbfewrp164p9voCC52fIkCF4//33ARQ0J0s7R6E6PD098ejRI5w9exZubm4ACpp0CoWiSFOsOFZWVtJ97t69K129r2nTppDL5YiPj0fbtm0BFDx/ycnJpa7nwuep8H3W09MT+/btUxpT1hqAiMofqy0q0bMnrq1SpQqAgoKfiKgifPrpp7h27Rp27twJADh16hQaNWokXWq6OKNHj0ZERASCgoJw9epVTJ8+HWfOnFE6LGPSpEkYPHiw9Pu1a9ewadMmXL9+HadOnUK/fv1w8eJFzJ07VxozYsQIPHjwAKNHj8a1a9cQHh6OuXPnYuQzx8RPmjQJhw8fRnJyMi5cuIBJkyYhJiZG+qBgYWGBYcOGYezYsYiOjsbZs2cxdOhQeHp6olWrVuW23tT11VdfYfXq1dL6XbFiRamH28hkMnz11VeYPXs29uzZgwsXLmDw4MFwcHCQGkcA8M4772DFihXS719++SXWrl2LDRs24MqVKxgxYgSePHmCoUOHAij4VtrNzU3pByg4F0jdunUBFOy18OzthdNdXV2lPa/K8rwSVWYDBw6ElZUV/Pz8cOTIESQlJSEmJgZffvklbt++DaDgHDVBQUFYtmwZrl+/jtjYWCxfvrzY+QUHB2Pr1q24evUqrl27hu3bt8POzq7YPUkHDhwIY2NjBAQE4OLFi4iOjsaoUaPg7+9f5Jw2pamo7UhkZCQiIiKQlJSEAwcOwNvbG40aNZK2I7m5uejduzfOnDmDzZs3Iz8/HykpKdLepkBBI6JatWoICAjA+fPnce3aNXz99dfS5ewBoGHDhvDz88Po0aNx/PhxXLx4EQEBAWjUqFGZG3ol8fT0hLu7u7RNmjFjBubNm4dly5bh2rVruHDhAkJCQhAcHAyg4FxDdnZ26NmzJ44dO4bExETs3LlTOll1gwYNEBYWhri4OJw/fx4DBgxQaS8yABg8eDAmTZpU4u2urq7o1q0bPvnkE5w+fRrHjh3DF198gX79+sHBwQEAcOfOHTRq1AinTp2S7hcSEoKTJ08iISEBmzZtwocffogxY8ZIjUpzc3N89tlnCAwMxP79+xEfHy81Fz/88EMAwL59+xASEoKLFy8iOTkZ4eHh+Oyzz9CmTRvppPGfffYZEhMT8c033+Dq1atYuXIlfvnlF4wZM0al9UBE5YPNJSrWP//8gxUrVpT7NyBERCUpPMxh+vTpUCgUyMzMRHx8fKlX+mrdujW2bNmCNWvWwMPDAzt27MCuXbukBgVQsD17djf7/Px8BAUFwcPDA126dEFWVhaOHz+udIWj2rVrIzIyEqdPn8Zbb72FL7/8EqNHj8bEiROlMXfv3sXgwYPh4uKCd955B6dPn0ZkZCS6dOkijVm8eDF69OiBXr16oX379rCzs0NYWJjSMjg5OSmdh0VTunXrhrp162LOnDkACk6+nZCQUOp9vvnmG4waNQrDhw9H8+bNkZGRgYiICKWrOBUeClHoww8/xKJFi/Dtt9+icePGiIuLQ0REhEofWMuiLM8rUWVWpUoVHD58GHXq1MEHH3wAV1dXDBs2DFlZWdKeTAEBAViyZAlWrlyJN998Ez169MD169eLnZ+ZmRkWLlyIZs2aoXnz5khOTsa+ffuK3ZOvSpUqiIyMxIMHD9C8eXP07t27SIOnLCpqO5KWloaRI0eiUaNGGDx4MFq3bo3IyEjpML3CK6rdvn0bjRs3hr29vfRz/PhxAAV70URERCAjIwOdOnVCs2bNcPToUezevVvpxNg///wzWrZsCR8fH3h5ecHQ0BARERFKhwTKZDKlq+SV1ahRo7Bu3Tr89ddf+Pjjj7Fu3TqEhITA3d0dXl5eWL9+vdQ8NzIywv79+2FjY4Pu3bvD3d0d8+fPlw6bCw4ORrVq1dC6dWv4+vrC29sbTUrbY68Yt27dkk6yXZLNmzejUaNGePfdd9G9e3e0bdsWa9askW7Pzc1FfHy8tGcYULDnV8+ePeHq6oqZM2diypQpWLRokdJ8v/vuO/Tr1w/+/v5o3ry5dChj4cnVTUxMsHbtWrRt2xaurq4YM2YM3nvvPezdu1eaR926dREeHo4DBw7Aw8MDQUFBWLdunUrnxiKi8iMThScuII16/PgxLCwskJaWVuKuz+pqNTcKKY+zYGdujJOTy3bSx+ft3r0bcXFxqFOnDoYMGQLZtWsFJ8Bcv7703cnLwc2bN3XyZOG6mhtgdm24efMmbG1tkZSUhLp16xa5xHJllp2drXSJYV1S2bJnZmaiRo0a+P3339GhQ4cSx1W23KqozNmzsrJK/BusyPdp+p/S1nNpz09lUZlf3y/C7OpJSkpCw4YNcfnyZem0EWXFda4dhdl1YZvyLF2tcQFmV0l8fLl8zq7I3GWtiXjOJSpW9+7dYWJigvbt2xec+8TFBfhvN1wiIiof0dHR6NSpU6mNJSIiqjz27duH4cOHq9xYIiIq1iv0OZvNJQJQcOWdGzduSG+UhoaGJV6uloiIyoePj490rg8iIqr8nj33HhER/Q/PuUQQQmD79u3YsmULYmNjix8UGwvIZAX/EhEREREREdHLeYU+Z7O5RJDJZLC2toa+vr7SyQqJiIiIiIiIiF6Eh8W9gvIVQunfsujQoQPc3NxgbW1dUbGIiIiIiIiI6BXEPZdeMdtO38K9jGwAwL2MbGw7favYccnJydi9ezcKLxZYuPcSEWkeL9pJpB3829MNfJ6IqDxwW0JUsdhceoX8k/YUk8IuKE2bHHYR/6Q9VZr29OlTbN26FXFxcTh16pQmIxLRMwoPQ83MzNRyEqLXU+HfHg8Jr5y4jSSi8pSTkwMA0NfX13ISolcTD4t7hSTdf4Lnj4TLFwLJ9zNhb2EiTTMxMUGPHj0QHx+Ppk2blm3mb7wBXL8O1KpVjomJXm/6+vqwtLTE3bt3AQBVqlSBTCbTcqoXy8nJ0dlv/3Q1u67mBipndiEEMjMzcffuXVhaWvKDRiWlC9vIyvj6Litm1zxdzQ3ofvb8/Hzcu3cPVapUgYEBPwJTJfIKfc7mX9YrpK6VKfRkUGow6ctkcLKqgvz8fGRnZ6NKlSoAAHd3d7i5uZW9SDM2BurXr4DURK83Ozs7AJA+POmCvLw8nS3MdDW7ruYGKnd2S0tL6W+QKqfKvo2szK/vF2F2zdPV3MCrkV1PTw916tSpdE1qes29Qp+zdXMLQcWytzDBvA/cMWHn/w6Nm/uBGyyNgE2bNiE7OxtDhgyBkZERAKi2YU1KAqZNA2bNAurWLe/oRK8tmUwGe3t72NjYIDc3V9txyuTOnTuoWbOmtmOoRVez62puoPJmNzQ05B5LOqCybyMr6+u7LJhd83Q1N/BqZDcyMoKeHs8KQ5XMK/Q5m82l/3z//ff47rvvkJKSAg8PDyxfvhwtWrQocfz27dsxbdo0JCcno0GDBliwYAG6d++uwcTF69u8DhZFXsO9jGxYV5Wjb/M6ePjwIe7evYu8vDzcu3dPvTeGhw+BzZuBsWN1/kVPVBnp6+vrzAddAwMDGBsbazuGWnQ1u67mBnQ7++uqMtZElXUbqcuvb2bXPF3NDTA7UYV5hT5ns3ULYNu2bRg7diwCAwMRGxsLDw8PeHt7l7gL9vHjx9G/f38MGzYM586dQ8+ePdGzZ09cvHhRw8nLplq1aujfvz8++ugjnf3GgYiIiCreq14TERERUcVgcwlAcHAwPvnkEwwdOhRvvPEGfvjhB1SpUgU//fRTseOXLl2Kbt264euvv4arqytmzZqFJk2aYMWKFRpOXtS207dwLyMbAHAvIxvbTt8CANSqVQu2trbajEZERESV3KtUExEREZHmvPaHxeXk5ODs2bOYNGmSNE1PTw+dO3fGiRMnir3PiRMnMHbsWKVp3t7e2LVrV4mPk52djezsbOn3tLQ0AMDjx49fIr2ylLSnmLD1T6UTek/Y+ifetpPD7pmrxaklI+N//5Zj5uKkp6eX63rRFF3NDTC7NuhqboDZtUFXcwO6m70ws65eHUkdmqiJNFEPaZKuvr4BZtcGXc0NMLs26GpugNlVUk6fsysyd1lrote+uXT//n3k5+cX2avH1tYWV69eLfY+KSkpxY5PSUkp8XHmzZuHGTNmFJleu3ZtNVKrxmVxOc7My6scZ0ZERFS5/fvvv7CwsNB2DI3QRE2kzXqIiIio0tKBz9np6eml1kSvfXNJUyZNmqT0zZ5CocCDBw9Qo0aNcr8c5uPHj1G7dm389ddfMDc3L9d5VzRdza6ruQFm1wZdzQ0wuzboam5At7OnpaWhTp06qF69urajvFKer4cePXoER0dH3Lp1S+eaeLr8+mZ2zdPV3ACza4Ou5gaYXRsqOrcQAunp6XBwcCh13GvfXLKysoK+vj5SU1OVpqempsLOzq7Y+9jZ2ak0HgDkcjnkcrnSNEtLS/VCl5G5ublO/VE8S1ez62pugNm1QVdzA8yuDbqaG9Dt7K/TZas1URMVVw8BgIWFhc6+RnT59c3smqeruQFm1wZdzQ0wuzZUZO6yfAH0+lRMJTAyMkLTpk0RFRUlTVMoFIiKioKnp2ex9/H09FQaDwAHDhwocTwRERFRZceaiIiIiNT12u+5BABjx45FQEAAmjVrhhYtWmDJkiV48uQJhg4dCgAYPHgwatasiXnz5gEARo8eDS8vLwQFBcHHxwehoaE4c+YM1qxZo83FICIiInoprImIiIhIHWwuAejbty/u3buHb7/9FikpKWjcuDEiIiKkE1TeunVLabf41q1bY8uWLZg6dSomT56MBg0aYNeuXXBzc9PWIiiRy+UIDAwsdrfzyk5Xs+tqboDZtUFXcwPMrg26mhtgdl2k6ZpIl9czs2uHrmbX1dwAs2uDruYGmF0bKktumXidrrFLRERERERERETl6rU/5xIREREREREREamPzSUiIiIiIiIiIlIbm0tERERERERERKQ2NpeIiIiIiIiIiEhtbC7pqO+//x5OTk4wNjZGy5YtcerUqVLHb9++HY0aNYKxsTHc3d2xb98+DSUtSpXsly5dQq9eveDk5ASZTIYlS5ZoLuhzVMm9du1atGvXDtWqVUO1atXQuXPnFz5HFUmV7GFhYWjWrBksLS1hamqKxo0bY+PGjRpMq0zV13qh0NBQyGQy9OzZs2IDlkCV3OvXr4dMJlP6MTY21mBaZaqu80ePHmHkyJGwt7eHXC5Hw4YNtbaNUSV7hw4diqx3mUwGHx8fDSYuoOo6X7JkCVxcXGBiYoLatWtjzJgxyMrK0lBaZapkz83NxcyZM+Hs7AxjY2N4eHggIiJCg2kLHD58GL6+vnBwcIBMJsOuXbteeJ+YmBg0adIEcrkc9evXx/r16ys856uCNYt26GrdwppFO3S1bmHNovmaBdDdukUXaxZAh+oWQTonNDRUGBkZiZ9++klcunRJfPLJJ8LS0lKkpqYWO/7YsWNCX19fLFy4UFy+fFlMnTpVGBoaigsXLmg4uerZT506JcaPHy+2bt0q7OzsxOLFizUb+D+q5h4wYID4/vvvxblz58SVK1fEkCFDhIWFhbh9+7aGk6uePTo6WoSFhYnLly+LGzduiCVLlgh9fX0RERGh4eSqZy+UlJQkatasKdq1ayf8/Pw0E/YZquYOCQkR5ubm4p9//pF+UlJSNJy6gKrZs7OzRbNmzUT37t3F0aNHRVJSkoiJiRFxcXEaTq569n///VdpnV+8eFHo6+uLkJCQSp178+bNQi6Xi82bN4ukpCQRGRkp7O3txZgxYzSaWwjVs3/zzTfCwcFBhIeHi4SEBLFy5UphbGwsYmNjNZp73759YsqUKSIsLEwAEL/++mup4xMTE0WVKlXE2LFjxeXLl8Xy5cu1tl3UNaxZtENX6xbWLH6aCfscXa1bWLNovmYRQnfrFl2tWYTQnbqFzSUd1KJFCzFy5Ejp9/z8fOHg4CDmzZtX7Pg+ffoIHx8fpWktW7YUn376aYXmLI6q2Z/l6OiotULtZXILIUReXp4wMzMTGzZsqKiIJXrZ7EII8fbbb4upU6dWRLxSqZM9Ly9PtG7dWqxbt04EBARopVBTNXdISIiwsLDQULrSqZp91apVol69eiInJ0dTEUv0sq/1xYsXCzMzM5GRkVFREYulau6RI0eKTp06KU0bO3asaNOmTYXmLI6q2e3t7cWKFSuUpn3wwQdi4MCBFZqzNGUp0r755hvx5ptvKk3r27ev8Pb2rsBkrwbWLNqhq3ULaxY/DSQtSlfrFtYsmq9ZhNDduuVVqFmEqNx1Cw+L0zE5OTk4e/YsOnfuLE3T09ND586dceLEiWLvc+LECaXxAODt7V3i+IqiTvbKoDxyZ2ZmIjc3F9WrV6+omMV62exCCERFRSE+Ph7t27evyKhFqJt95syZsLGxwbBhwzQRswh1c2dkZMDR0RG1a9eGn58fLl26pIm4StTJvmfPHnh6emLkyJGwtbWFm5sb5s6di/z8fE3FBlA+f6c//vgj+vXrB1NT04qKWYQ6uVu3bo2zZ89Ku3InJiZi37596N69u0YyF1Ine3Z2dpFDJ0xMTHD06NEKzfqyKsv7qK5hzaIdulq3sGbRDl2tW1izaL5mAXS3bnmdahZAe++lbC7pmPv37yM/Px+2trZK021tbZGSklLsfVJSUlQaX1HUyV4ZlEfuCRMmwMHBocgfeUVTN3taWhqqVq0KIyMj+Pj4YPny5ejSpUtFx1WiTvajR4/ixx9/xNq1azURsVjq5HZxccFPP/2E3bt3Y9OmTVAoFGjdujVu376ticgSdbInJiZix44dyM/Px759+zBt2jQEBQVh9uzZmogsedm/01OnTuHixYv4+OOPKypisdTJPWDAAMycORNt27aFoaEhnJ2d0aFDB0yePFkTkSXqZPf29kZwcDCuX78OhUKBAwcOICwsDP/8848mIqutpPfRx48f4+nTp1pKVfmxZtEOXa1bWLNoh67WLaxZNF+zALpbt7xONQugvbqFzSWiCjZ//nyEhobi119/1epJmlVhZmaGuLg4nD59GnPmzMHYsWMRExOj7VilSk9Ph7+/P9auXQsrKyttx1GJp6cnBg8ejMaNG8PLywthYWGwtrbG6tWrtR3thRQKBWxsbLBmzRo0bdoUffv2xZQpU/DDDz9oO5pKfvzxR7i7u6NFixbajvJCMTExmDt3LlauXInY2FiEhYUhPDwcs2bN0na0F1q6dCkaNGiARo0awcjICF988QWGDh0KPT2WI0SVha7VLaxZNE9X6xbWLNqhq3ULaxbVGWg7AKnGysoK+vr6SE1NVZqempoKOzu7Yu9jZ2en0viKok72yuBlci9atAjz58/HwYMH8dZbb1VkzGKpm11PTw/169cHADRu3BhXrlzBvHnz0KFDh4qMq0TV7AkJCUhOToavr680TaFQAAAMDAwQHx8PZ2fnig2N8nmdGxoa4u2338aNGzcqImKJ1Mlub28PQ0ND6OvrS9NcXV2RkpKCnJwcGBkZVWjmQi+z3p88eYLQ0FDMnDmzIiMWS53c06ZNg7+/v/SNpbu7O548eYLhw4djypQpGit61MlubW2NXbt2ISsrC//++y8cHBwwceJE1KtXTxOR1VbS+6i5uTlMTEy0lKryY82iHbpat7Bm0XzNAuhu3cKaRfM1C6C7dcvrVLMA2qtb2HbTMUZGRmjatCmioqKkaQqFAlFRUfD09Cz2Pp6enkrjAeDAgQMljq8o6mSvDNTNvXDhQsyaNQsRERFo1qyZJqIWUV7rXKFQIDs7uyIilkjV7I0aNcKFCxcQFxcn/bz33nvo2LEj4uLiULt27UqZuzj5+fm4cOEC7O3tKypmsdTJ3qZNG9y4cUMqigHg2rVrsLe311iRBrzcet++fTuys7MxaNCgio5ZhDq5MzMzixRihYWyEKLiwj7nZda5sbExatasiby8POzcuRN+fn4VHfelVJb3UV3DmkU7dLVuYc2i+ZpFnezF0UbdwppF8zULoLt1y+tUswBafC+t0NOFU4UIDQ0VcrlcrF+/Xly+fFkMHz5cWFpaSpcA9ff3FxMnTpTGHzt2TBgYGIhFixaJK1euiMDAQK1e1leV7NnZ2eLcuXPi3Llzwt7eXowfP16cO3dOXL9+vVLnnj9/vjAyMhI7duxQumxoenq6RnOrk33u3Lli//79IiEhQVy+fFksWrRIGBgYiLVr11b67M/T1pVXVM09Y8YMERkZKRISEsTZs2dFv379hLGxsbh06VKlz37r1i1hZmYmvvjiCxEfHy/27t0rbGxsxOzZsyt99kJt27YVffv21XRciaq5AwMDhZmZmdi6datITEwU+/fvF87OzqJPnz6VPvvJkyfFzp07RUJCgjh8+LDo1KmTqFu3rnj48KFGc6enp0vvLQBEcHCwOHfunLh586YQQoiJEycKf39/aXzhJX2//vprceXKFfH9999r7XLnuoY1i+ZrFnWyV5a6hTWLn4bSKtPVuoU1i3boat2iqzWLELpTt7C5pKOWL18u6tSpI4yMjESLFi3EyZMnpdu8vLxEQECA0vhffvlFNGzYUBgZGYk333xThIeHazjx/6iSPSkpSQAo8uPl5VWpczs6OhabOzAwUOO5hVAt+5QpU0T9+vWFsbGxqFatmvD09BShoaFaSF1A1df6s7RZqKmS+6uvvpLG2traiu7du4vY2FgtpC6g6jo/fvy4aNmypZDL5aJevXpizpw5Ii8vT8OpC6ia/erVqwKA2L9/v4aTKlMld25urpg+fbpwdnYWxsbGonbt2uLzzz/XSrEjhGrZY2JihKurq5DL5aJGjRrC399f3LlzR+OZo6Oji91GF2YNCAgo8j4THR0tGjduLIyMjES9evVESEiIxnPrKtYsXpoPLnS3bmHNoh26WrewZtEOXa1bdLFmEUJ36haZEBrch56IiIiIiIiIiF4pPOcSERERERERERGpjc0lIiIiIiIiIiJSG5tLRERERERERESkNjaXiIiIiIiIiIhIbWwuERERERERERGR2thcIiIiIiIiIiIitbG5REREREREREREamNziYiIiIiIiIiI1MbmEhERERERERERqY3NJSIiIiIiIiIiUhubS0REREREREREpDY2l4iIiIiIiIiISG1sLhERERERERERkdrYXCIiIiIiIiIiIrWxuURERERERERERGpjc4mIiIiIiIiIiNTG5hIREREREREREamNzSUiIiIiIiIiIlIbm0tERERERERERKQ2NpeIiIiIiIiIiEhtbC4REREREREREZHa2FwiIiIiIiIiIiK1sblERERERERERERqY3OJiNTWoUMHyGQybceoFJycnODk5KTSfbj+iIiIiEpXXI21fv16yGQyrF+/XiuZiKgoNpeIXgPJycmQyWSl/jx69EjbMdXm5OSktCz6+vqwsrJC165dsXv3bq3lmj59OmQyGWJiYrSWoawKsz77U6VKFbi5uWHKlCl4/PjxSz/GkCFDIJPJkJyc/PKBiYiIqMyKqwUNDQ1Rs2ZN9OnTB2fOnNF2RCLScQbaDkBEmuPs7IxBgwYVe5uxsbGG05QvfX19TJ06FQCQk5ODq1evYs+ePThw4AAWLVqEcePGVejjR0VFqXyfn3/+GZmZmRWQRn29evWCm5sbACA1NRX79u3D3LlzsXfvXpw6dQpyuVzLCYmIiEhdz9aCT548wdmzZ7F9+3bs2rULBw8eRPv27bWckIh0FZtLRK+R+vXrY/r06dqOUSEMDAyKLNv+/fvRrVs3fPvttxgxYgSqVKlSYY/v7Oys8n3q1KlTAUleTu/evdGvXz/p96ysLLRq1Qrnz5/Hli1bMHToUC2mIyIiopdRXC04f/58TJo0CdOmTcOhQ4e0E4yIdB4PiyMiydmzZ/HFF1/Azc0NFhYWMDExgbu7O+bPn4/c3NwyzUOhUGDdunVo0aIFqlevDhMTE9SqVQu+vr7FHh52+PBh+Pr6wsrKCnK5HA0aNMDUqVPLZY+erl27wsXFBZmZmbh06ZI0/bfffkPHjh2lZfTw8EBwcDDy8vKKzCM6OhrvvvsuHBwcIJfLYWtri3bt2mHNmjVK454/H0CHDh0wY8YMAEDHjh2lXdCfH/PsOZc2btwImUyGmTNnFrs8sbGxkMlkGDhwoNL0u3fvYsyYMahfvz7kcjmsrKzQq1cvXLx4sczrqiTGxsbS4509e1bptr///huBgYFo1aoVbGxsIJfL4eTkhM8//xx3795VGuvk5IQNGzYAAOrWrSutjw4dOiiNS0pKwscff4w6depALpfD3t4eQ4YMwc2bN196WYiIiKioYcOGASj6Pp+Tk4Pg4GA0adIEpqamMDMzQ7t27bBnz55i55OTk4PFixejefPmMDMzQ9WqVfHGG29g7NixePjwoTQuOjoaH330EVxcXFC1alVUrVoVzZo1K1JbEZFu4Z5LRCRZu3YtfvvtN7Rv3x7du3dHZmYmYmJiMGnSJJw+fRo7d+584TwmTZqEhQsXwtnZGQMGDICZmRnu3LmDo0eP4uDBg0rNhFWrVmHkyJGwtLSEr68vbGxscObMGcyZMwfR0dGIjo6GkZFRuSxbYRMnODgY48aNQ/Xq1TFgwACYmppiz549GDduHI4cOYKwsDBpbHh4OHx9fWFpaQk/Pz/Y29vj3r17OH/+PDZu3Ijhw4eX+HhDhgwBABw6dAgBAQFSU8nS0rLE+3zwwQcYMWIENm/ejG+//bbI7Rs3bgQA+Pv7S9MSEhLQoUMH3L59G127dkXPnj1x9+5d7Ny5E5GRkYiKikLLli1VWVUlMjBQfss4fPgwgoKC8M4776Bly5YwNDTEuXPnsGrVKkRGRiI2NhYWFhYAgK+++grr16/H+fPnMXr0aGk9PNts+/PPP+Ht7Y0nT56gR48eaNCgAZKTk7F582b8/vvvOHHiBOrVq1cuy0JERETKnn2fz87ORrdu3RATE4PGjRtj2LBhyM3NRXh4OPz8/LB8+XJ88cUX0vinT5+iS5cuOHbsGBo0aIChQ4dCLpfj+vXrWL16NQYPHoxq1aoBABYsWIAbN26gVatWeP/99/Ho0SNERETg008/RXx8PIKCgjS+7ERUDgQRvfKSkpIEAOHs7CwCAwOL/Jw4cUIIIcTNmzdFXl6e0n0VCoX46KOPBABx9OhRpdu8vLzE85uR6tWrCwcHB/HkyZMiOf7991/p/5cuXRIGBgbCw8ND3L9/X2ncvHnzBACxaNGiMi2fo6OjkMvlRaYfPHhQyGQyYWpqKjIzM8WNGzeEgYGBsLGxEbdu3ZLGZWVlibZt2woA4ueff5amf/DBBwKAiIuLKzLv5zM7OjoKR0dHpWmBgYECgIiOji42d3Hrb9CgQQKA+PPPP5Wm5+XlCVtbW2FnZ6f0HLVu3Vro6+uLiIgIpfHx8fHCzMxMuLu7F/vYzyvMunXrVqXpT58+FR4eHgKA2L59u9JtqampIj09vci8NmzYIACI2bNnK00PCAgQAERSUlKR++Tk5AgnJydhZmYmYmNjlW47cuSI0NfXFz169CjTshAREZGywlrQ29u7yG1z584VAISPj480bfLkyQKAmDZtmlAoFNL0x48fi2bNmgkjIyNx584dafq4ceMEAOHv71+klnz06JFSvZCYmFgkQ25urujSpYvQ19cXN2/eVLqtuBorJCREABAhISFlWn4iqng8LI7oNZKQkIAZM2YU+Tl58iSAgnMA6evrK91HJpNh5MiRAICDBw+W6XGMjIyKzAcAqlevLv1/9erVyMvLw/Lly1GjRg2lcd988w2sra2xdevWMi9bXl4epk+fjunTp2PKlCno3bs3unXrBiEEZs2aBRMTE2zZsgV5eXkYN24cateuLd1XLpdjwYIFAFDsJW1NTEyKTHs+c3kp3Ctp06ZNStP379+P1NRU9OvXT1q3586dw/HjxxEQEABvb2+l8Q0bNsQnn3yCCxcuqHR43I4dO6T1+Pnnn8PFxQXnz5/H+++/jw8++EBprI2NDapWrVrsMpibm5f59QIAe/fuRXJyMr7++mu8/fbbSre1bdsWfn5+2LdvX7lctY6IiOh1dePGDel9/uuvv0anTp0wefJk2Nra4rvvvgNQcIqDVatWwdnZGTNmzFA6hN/MzAzffvstcnJyEBYWBqCgBluzZg0sLCywdOnSIjWghYWFUr1Qt27dIrkMDAzw2WefIT8/H9HR0RWx6ERUwXhYHNFrxNvbGxERESXenpOTgxUrViA0NBRXr15FRkYGhBDS7X///fcLH6Nfv35YuXIl3Nzc0K9fP3Ts2BGenp5FGjSFDa3CQ7eeZ2hoiKtXr5Z10ZCfny+d40hPTw/VqlVDp06dMHLkSLz33nsACpoxAIqc5wcAPD09YWxsjLi4OKVlCQsLQ6tWrTBgwAC88847aNeuHaysrMqcS1XvvPMO7O3tERoaiuDgYGkX9cJm07OHxBWuw9TU1GJP1F64/q5evSpdAe5Fdu7cWeTwxw8//BDbtm1TKi4LhYWFYfXq1YiNjcXDhw+Rn58v3VaW10uhwmWJj48vdllSUlKgUChw7do1NGvWrMzzJSIiov8p/KLxWXZ2djhy5Ajq168PoOC9+OHDh3BwcCgyFgDu3bsHQLnOSE9PR+fOnaVD30qTnp6ORYsWYdeuXUhISMCTJ0+UblelfiCiyoPNJSKS9O7dG7/99hsaNmyIvn37wsbGBoaGhnj06BGWLl2K7OzsF85j6dKlqFu3LkJCQjB79mzMnj0bxsbG6NOnD4KCgqTGzIMHDwAAc+bMKZfscrkcWVlZpY4p3OvF1ta2yG0ymQy2tra4c+eONO3DDz/Erl27EBwcjB9++AHff/89ZDIZOnbsiKCgIDRu3Lhcsj9LX18fAwYMQFBQECIjI+Hj44OMjAzs2rULb7zxBpo0aSKNLVyH4eHhCA8PL3Gezxdtpdm6dSv69euHvLw8xMfHY/z48di+fTtcXFwwa9YspbFBQUEYP348rK2t0bVrV9SqVUtqIi5ZsqRMr5fnl2Xz5s2ljlNlWYiIiEjZs1803rt3Dxs2bMCECRPw3nvv4dSpU6hatar0nnzp0iWlC6I8r/A9OS0tDQBQs2bNFz5+Tk4OOnTogNjYWLz99tvw9/dHjRo1YGBggOTkZGzYsEGl+oGIKg82l4gIAHD69Gn89ttv8Pb2Rnh4uNIuzSdPnsTSpUvLNB8DAwOMHz8e48ePx99//41Dhw4hJCQEP//8M1JSUhAZGQkAMDc3B1DQ8DEzMyv/BSpG4WOmpqbC0dFR6TYhBFJTU6Uxhfz8/ODn54f09HQcO3YMYWFh+PHHH9GtWzdcvXq11BN0q8vf3x9BQUHYtGkTfHx8sHPnTmRmZirttfTs8jx/Us3yYGBggDfffBO//vor3N3dMWfOHLz//vtScysvLw+zZs2Cvb094uLiYGNjI91XCIGFCxeq9HiFy/Lbb7+hR48e5bcgREREVCxra2uMHz8eaWlpmD17NqZOnYolS5ZI78m9evXCjh07Xjifwlro2S/oSrJ7927ExsZi2LBhWLdundJtoaGh0pVliUj38JxLRASgYDdpAPDx8SlyrPyRI0fUmqeDgwP69++PiIgI1K9fHwcPHsTTp08BQLqCWeHhUJpQeC6fmJiYIrf9+eefyMrKKnFvJDMzM3Tr1g1r1qzBkCFDkJqaij///LPUxytcj88eKlYWHh4ecHd3x+7du5Geno5NmzZBJpNh4MCBSuMK1+GJEydUmr8qjI2NsWjRIgghMHHiRGn6/fv3kZaWBk9PT6XGEgCcOXNGep6fVdr60MSyEBERUVGTJ0+Gg4MDVq5cieTkZLi6usLc3BxnzpxBbm7uC+/v4uICc3NznD59Gg8fPix1bGG96efnV+Q2detNIqoc2FwiIgCQ9uQ5evSo0vRLly5h3rx5ZZpHdnY2jh8/XmT6kydPkJGRAUNDQ+jpFWx2Pv/8cxgYGGDUqFG4detWkfs8evRIOkdSeRkwYAAMDAwQHBysdDx/Tk4OJkyYAAAYMmSINP3w4cPFNkLu3r0LoKDxUprCE5j/9ddfKmf19/fH06dPsWzZMvzxxx/w8vJSOgk5ALRo0QItW7bE1q1bsW3btiLzUCgUOHTokMqP/Tw/Pz80adIEBw4ckAo/GxsbmJiYIDY2FpmZmdLYhw8fYtSoUcXOp7T14efnhzp16iA4OBiHDx8ucntubm6R1yYRERG9PBMTE0yYMAG5ubmYNWsWDAwMMGLECNy8eRPjx48vtsF08eJFqR4yMDDAp59+irS0NIwePbpI7ZSWloaMjAwAJdebhw4dwtq1ayti8YhIQ3hYHBEBKGhUtGjRAr/88gv++ecftGrVCrdu3cKePXvg4+NTpt2inz59ijZt2qBhw4Zo2rQp6tSpg4yMDOzduxcpKSkYP3485HI5AMDNzQ0rV67EiBEj4OLigu7du8PZ2Rnp6elITEzEoUOHMGTIEPzwww/ltozOzs5YsGABxo0bh7feegt9+vSBqakpfvvtN8THx8PPzw+DBg2Sxn/55Zf4+++/0bZtWzg5OUEmk+Ho0aM4deoUWrVqhbZt25b6eB07doRMJsPkyZNx6dIlWFhYwNLSskyHsA0YMAATJ07EjBkzoFAoihwSV2jr1q3o2LEj+vXrhyVLlqBJkyYwMTHBrVu3cOLECdy7d++F56Iqi+nTp+O9997Dt99+i+joaOjp6eHzzz9HUFAQPDw84Ovri8ePH+P333+Ho6MjHBwcisyjU6dOWLRoEYYPH45evXrB1NQUjo6O8Pf3h1wux44dO/Duu+/Cy8sLnTp1gru7O2QyGW7evIkjR46gRo0aKp3knYiIiMpm+PDhWLBgAX7++WdMnjwZM2bMQGxsLJYtW4bw8HC0b98eNjY2uHPnDi5cuIDz58/jxIkT0t7LM2fOxMmTJ7Fx40acPHkS7777LuRyORITExEREYGjR4+icePG8PX1hZOTExYuXIiLFy/Czc0N8fHx2Lt3L95///0y1ZtEVEkJInrlJSUlCQDC29u71HF3794VH330kXBwcBDGxsbC3d1dfP/99yIxMVEAEAEBAUrjvby8xLObkZycHLFgwQLRtWtXUatWLWFkZCRsbW1F+/btxZYtW4RCoSjymKdOnRL9+vUTDg4OwtDQUFhZWYkmTZqIiRMniitXrpRp+RwdHYVcLi/TWCGE2L17t/Dy8hJmZmZCLpcLd3d3ERQUJHJzc5XGhYaGij59+ghnZ2dRpUoVYWFhITw8PMSCBQtEenp6kQyOjo5FHmv9+vXC3d1dyOVyAUBpzPPr73mdO3cWAISxsbFIS0srcdyDBw/E1KlThZubmzAxMRFVq1YVDRo0EAMGDBBhYWFlWieBgYECgNi6dWuJY5o1ayYAiKioKCFEwfM9Z84c0aBBAyGXy0WdOnXEuHHjRHp6eonrY+HChaJBgwbC0NBQABBeXl5Kt9++fVuMHj1amqe5ublwdXUVH3/8sfS4REREpJqy1ILLly8XAIS/v78QQoi8vDyxevVq0aZNG2Fubi6913fr1k2sWrVKZGRkKN0/KytLLFq0SDRu3FiqR9544w0xbtw48fDhQ2lcYmKi6NWrl7C2thZVqlQRzZs3F6GhoSI6OloAEIGBgUrzLa6mCAkJEQBESEjIy6wWIipHMiGeuc44ERERERERERGRCnjOJSIiIiIiIiIiUhubS0REREREREREpDY2l4iIiIiIiIiISG1sLhERERERERERkdrYXCIiIiIiIiIiIrWxuURERERERERERGpjc4mIiIiIiIiIiNTG5hIREREREREREamNzSUiIiIiIiIiIlIbm0tERERERERERKQ2NpeIiIiIiIiIiEhtbC4REREREREREZHa2FwiIiIiIiIiIiK1/T+eosMVMFazEQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1200x1100 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-----------------------------------------------------------------------------------------\n",
      "7/7: Starting KerasClassifier Random Search - May 30, 2024 09:19 AM UTC\n",
      "-----------------------------------------------------------------------------------------\n",
      "\n",
      "Fitting 5 folds for each of 10 candidates, totalling 50 fits\n",
      "[CV 1/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=None;, score=1.000 total time=   3.8s\n",
      "[CV 2/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=None;, score=0.929 total time=   3.0s\n",
      "WARNING:tensorflow:5 out of the last 7 calls to <function TensorFlowTrainer.make_predict_function.<locals>.one_step_on_data_distributed at 0x7fe80a47d430> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has reduce_retracing=True option that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
      "WARNING:tensorflow:6 out of the last 9 calls to <function TensorFlowTrainer.make_predict_function.<locals>.one_step_on_data_distributed at 0x7fe80a47d430> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has reduce_retracing=True option that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
      "[CV 3/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=None;, score=1.000 total time=   2.9s\n",
      "[CV 4/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=None;, score=0.965 total time=   3.8s\n",
      "[CV 5/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=None;, score=0.976 total time=   3.3s\n",
      "[CV 1/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=25;, score=0.988 total time=   3.4s\n",
      "[CV 2/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=25;, score=0.918 total time=   4.4s\n",
      "[CV 3/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=25;, score=1.000 total time=   3.7s\n",
      "[CV 4/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=25;, score=0.976 total time=   5.0s\n",
      "[CV 5/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=25;, score=0.965 total time=   4.6s\n",
      "[CV 1/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=100, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=50;, score=1.000 total time=   4.1s\n",
      "[CV 2/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=100, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=50;, score=0.918 total time=   3.7s\n",
      "[CV 3/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=100, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=50;, score=1.000 total time=   3.2s\n",
      "[CV 4/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=100, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=50;, score=0.976 total time=   3.7s\n",
      "[CV 5/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=100, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=50;, score=0.965 total time=   3.9s\n",
      "[CV 1/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=50;, score=0.988 total time=   3.4s\n",
      "[CV 2/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=50;, score=0.929 total time=   2.9s\n",
      "[CV 3/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=50;, score=1.000 total time=   2.7s\n",
      "[CV 4/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=50;, score=0.976 total time=   6.6s\n",
      "[CV 5/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=50;, score=0.965 total time=   4.8s\n",
      "[CV 1/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=None;, score=1.000 total time=   3.4s\n",
      "[CV 2/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=None;, score=0.929 total time=   3.8s\n",
      "[CV 3/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=None;, score=1.000 total time=   3.6s\n",
      "[CV 4/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=None;, score=0.988 total time=   4.0s\n",
      "[CV 5/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=None;, score=0.976 total time=   3.3s\n",
      "[CV 1/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=25;, score=1.000 total time=   2.7s\n",
      "[CV 2/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=25;, score=0.929 total time=   3.0s\n",
      "[CV 3/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=25;, score=1.000 total time=   3.5s\n",
      "[CV 4/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=25;, score=0.976 total time=   4.7s\n",
      "[CV 5/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=25;, score=0.965 total time=   5.1s\n",
      "[CV 1/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=25;, score=1.000 total time=   2.8s\n",
      "[CV 2/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=25;, score=0.929 total time=   3.1s\n",
      "[CV 3/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=25;, score=1.000 total time=   2.7s\n",
      "[CV 4/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=25;, score=0.976 total time=   3.7s\n",
      "[CV 5/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=25;, score=0.976 total time=   2.7s\n",
      "[CV 1/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=None;, score=0.988 total time=   2.1s\n",
      "[CV 2/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=None;, score=0.929 total time=   3.4s\n",
      "[CV 3/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=None;, score=1.000 total time=   2.7s\n",
      "[CV 4/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=None;, score=0.988 total time=   2.9s\n",
      "[CV 5/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=None;, score=0.976 total time=   2.3s\n",
      "[CV 1/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=100, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=50;, score=0.988 total time=   2.7s\n",
      "[CV 2/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=100, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=50;, score=0.929 total time=   4.9s\n",
      "[CV 3/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=100, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=50;, score=1.000 total time=   4.8s\n",
      "[CV 4/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=100, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=50;, score=0.976 total time=   4.0s\n",
      "[CV 5/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=100, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=50;, score=0.965 total time=   3.6s\n",
      "[CV 1/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=50;, score=1.000 total time=   3.5s\n",
      "[CV 2/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=50;, score=0.906 total time=   3.9s\n",
      "[CV 3/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=50;, score=1.000 total time=   3.9s\n",
      "[CV 4/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=50;, score=0.976 total time=   3.8s\n",
      "[CV 5/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=binary_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=50;, score=0.965 total time=   3.3s\n",
      "\n",
      "Total Time: 183.7382 seconds\n",
      "Average Fit Time: 3.6748 seconds\n",
      "Inference Time: 0.0684\n",
      "Best CV Accuracy Score: 0.9788\n",
      "Train Accuracy Score: 0.9836\n",
      "Test Accuracy Score: 0.9790\n",
      "Overfit: Yes\n",
      "Overfit Difference: 0.0045\n",
      "Best Parameters: {'keras_class__third_layer_dim': None, 'keras_class__second_layer_dim': 100, 'keras_class__optimizer__learning_rate': 0.001, 'keras_class__optimizer': 'adam', 'keras_class__loss': 'binary_crossentropy', 'keras_class__l2_reg': 0.0, 'keras_class__hidden_layer_dim': 50, 'keras_class__fit__batch_size': 32, 'keras_class__dropout_rate': 0.5}\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"Sequential\"</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1mModel: \"Sequential\"\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ Hidden_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">50</span>)             │         <span style=\"color: #00af00; text-decoration-color: #00af00\">1,550</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Dropout_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">50</span>)             │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Hidden_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">100</span>)            │         <span style=\"color: #00af00; text-decoration-color: #00af00\">5,100</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Dropout_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">100</span>)            │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Output (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                  │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">1</span>)              │           <span style=\"color: #00af00; text-decoration-color: #00af00\">101</span> │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ Hidden_1 (\u001b[38;5;33mDense\u001b[0m)                │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m50\u001b[0m)             │         \u001b[38;5;34m1,550\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Dropout_1 (\u001b[38;5;33mDropout\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m50\u001b[0m)             │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Hidden_2 (\u001b[38;5;33mDense\u001b[0m)                │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m100\u001b[0m)            │         \u001b[38;5;34m5,100\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Dropout_2 (\u001b[38;5;33mDropout\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m100\u001b[0m)            │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Output (\u001b[38;5;33mDense\u001b[0m)                  │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m)              │           \u001b[38;5;34m101\u001b[0m │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">20,255</span> (79.12 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m20,255\u001b[0m (79.12 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">6,751</span> (26.37 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m6,751\u001b[0m (26.37 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Optimizer params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">13,504</span> (52.75 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Optimizer params: \u001b[0m\u001b[38;5;34m13,504\u001b[0m (52.75 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "KerasClassifier Binary Classification Report\n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "      Benign     0.9886    0.9775    0.9831        89\n",
      "   Malignant     0.9636    0.9815    0.9725        54\n",
      "\n",
      "    accuracy                         0.9790       143\n",
      "   macro avg     0.9761    0.9795    0.9778       143\n",
      "weighted avg     0.9792    0.9790    0.9791       143\n",
      "\n",
      "ROC AUC: 0.9965\n",
      "\n",
      "               Predicted:0         1         \n",
      "Actual: 0                87        2         \n",
      "Actual: 1                1         53        \n",
      "\n",
      "True Positive Rate / Sensitivity: 0.9815\n",
      "True Negative Rate / Specificity: 0.9775\n",
      "False Positive Rate / Fall-out: 0.0225\n",
      "False Negative Rate / Miss Rate: 0.0185\n",
      "\n",
      "Positive Class: Malignant (1)\n",
      "Threshold: 0.5\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1100 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x550 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Evaluate multiple classification models by searching for the best hyper-parameters and comparing results\n",
    "results_df = dw.compare_models(\n",
    "    \n",
    "    # Data split and sampling\n",
    "    x=X, y=y_enc, test_size=0.25, stratify=None, under_sample=None, over_sample=None, svm_knn_resample=None,\n",
    "    \n",
    "    # Models and pipeline steps\n",
    "    imputer=None, transformers=None, scaler='stand', selector=None, svm_proba=True,\n",
    "    models=['logreg', 'knn_class', 'svm_proba', 'tree_class', 'forest_class', 'xgb_class', 'keras_class'],\n",
    "\n",
    "    # Grid search\n",
    "    search_type='random', scorer='accuracy', grid_cv='kfold_5', verbose=4,\n",
    "\n",
    "    # Model evaluation and charts\n",
    "    model_eval=True, plot_perf=True, plot_curve=True, fig_size=(12,6), legend_loc='lower left', rotation=45,\n",
    "    threshold=0.5, class_map=class_map, pos_label=1, title='Breast Cancer',\n",
    "\n",
    "    # Config, preferences and notes\n",
    "    config=my_config, class_weight=None, random_state=42, decimal=4, n_jobs=None,\n",
    "    notes='X, Test Size=0.25, Standard Scaler, Random Grid (Accuracy), T=0.50'\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Review the Best Models\n",
    "\n",
    "In addition to seeing the charts in the `dw.compare_models` output, we also have the metrics stored in a dataframe. So we can further analyze or plot the performance of the difference models.\n",
    "\n",
    "Multiple runs of this function can be stored as different dataframes, with different parameters (ex: varying the X dataset, changing the test size, or using different pre-processing steps in the Pipeline). You can make notes about these differences in the `notes` parameter. Then multiple dataframes can be concatenated and evaluate as one."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Model</th>\n",
       "      <th>Test Size</th>\n",
       "      <th>Over Sample</th>\n",
       "      <th>Under Sample</th>\n",
       "      <th>Resample</th>\n",
       "      <th>Total Fit Time</th>\n",
       "      <th>Fit Count</th>\n",
       "      <th>Average Fit Time</th>\n",
       "      <th>Inference Time</th>\n",
       "      <th>Grid Scorer</th>\n",
       "      <th>Best Params</th>\n",
       "      <th>Best CV Score</th>\n",
       "      <th>Train Score</th>\n",
       "      <th>Test Score</th>\n",
       "      <th>Overfit</th>\n",
       "      <th>Overfit Difference</th>\n",
       "      <th>Train Accuracy Score</th>\n",
       "      <th>Test Accuracy Score</th>\n",
       "      <th>Train Precision Score</th>\n",
       "      <th>Test Precision Score</th>\n",
       "      <th>Train Recall Score</th>\n",
       "      <th>Test Recall Score</th>\n",
       "      <th>Train F1 Score</th>\n",
       "      <th>Test F1 Score</th>\n",
       "      <th>Train ROC AUC Score</th>\n",
       "      <th>Test ROC AUC Score</th>\n",
       "      <th>Threshold</th>\n",
       "      <th>True Positives</th>\n",
       "      <th>False Positives</th>\n",
       "      <th>True Negatives</th>\n",
       "      <th>False Negatives</th>\n",
       "      <th>TPR</th>\n",
       "      <th>FPR</th>\n",
       "      <th>TNR</th>\n",
       "      <th>FNR</th>\n",
       "      <th>False Rate</th>\n",
       "      <th>Pipeline</th>\n",
       "      <th>Notes</th>\n",
       "      <th>Timestamp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>LogisticRegression</td>\n",
       "      <td>0.25</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>2.600479</td>\n",
       "      <td>50</td>\n",
       "      <td>0.052010</td>\n",
       "      <td>0.001263</td>\n",
       "      <td>Accuracy</td>\n",
       "      <td>{'logreg__solver': 'saga', 'logreg__C': 10}</td>\n",
       "      <td>0.976471</td>\n",
       "      <td>0.990610</td>\n",
       "      <td>0.972028</td>\n",
       "      <td>Yes</td>\n",
       "      <td>0.018582</td>\n",
       "      <td>0.990610</td>\n",
       "      <td>0.972028</td>\n",
       "      <td>0.993590</td>\n",
       "      <td>0.946429</td>\n",
       "      <td>0.981013</td>\n",
       "      <td>0.981481</td>\n",
       "      <td>0.987261</td>\n",
       "      <td>0.963636</td>\n",
       "      <td>0.998796</td>\n",
       "      <td>0.995630</td>\n",
       "      <td>0.5</td>\n",
       "      <td>53</td>\n",
       "      <td>3</td>\n",
       "      <td>86</td>\n",
       "      <td>1</td>\n",
       "      <td>0.981481</td>\n",
       "      <td>0.033708</td>\n",
       "      <td>0.966292</td>\n",
       "      <td>0.018519</td>\n",
       "      <td>0.052226</td>\n",
       "      <td>[stand, logreg]</td>\n",
       "      <td>X, Test Size=0.25, Standard Scaler, Random Grid (Accuracy), T=0.50</td>\n",
       "      <td>May 30, 2024 09:18 AM UTC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>KNeighborsClassifier</td>\n",
       "      <td>0.25</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.609048</td>\n",
       "      <td>50</td>\n",
       "      <td>0.012181</td>\n",
       "      <td>0.004320</td>\n",
       "      <td>Accuracy</td>\n",
       "      <td>{'knn_class__weights': 'distance', 'knn_class__n_neighbors': 3, 'knn_class__metric': 'manhattan'}</td>\n",
       "      <td>0.976471</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.972028</td>\n",
       "      <td>Yes</td>\n",
       "      <td>0.027972</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.972028</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.962963</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.962963</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.962963</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.987412</td>\n",
       "      <td>0.5</td>\n",
       "      <td>52</td>\n",
       "      <td>2</td>\n",
       "      <td>87</td>\n",
       "      <td>2</td>\n",
       "      <td>0.962963</td>\n",
       "      <td>0.022472</td>\n",
       "      <td>0.977528</td>\n",
       "      <td>0.037037</td>\n",
       "      <td>0.059509</td>\n",
       "      <td>[stand, knn_class]</td>\n",
       "      <td>X, Test Size=0.25, Standard Scaler, Random Grid (Accuracy), T=0.50</td>\n",
       "      <td>May 30, 2024 09:18 AM UTC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SVC</td>\n",
       "      <td>0.25</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>1.118782</td>\n",
       "      <td>50</td>\n",
       "      <td>0.022376</td>\n",
       "      <td>0.003180</td>\n",
       "      <td>Accuracy</td>\n",
       "      <td>{'svm_proba__kernel': 'rbf', 'svm_proba__C': 10}</td>\n",
       "      <td>0.978824</td>\n",
       "      <td>0.992958</td>\n",
       "      <td>0.965035</td>\n",
       "      <td>Yes</td>\n",
       "      <td>0.027923</td>\n",
       "      <td>0.992958</td>\n",
       "      <td>0.965035</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.945455</td>\n",
       "      <td>0.981013</td>\n",
       "      <td>0.962963</td>\n",
       "      <td>0.990415</td>\n",
       "      <td>0.954128</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.995630</td>\n",
       "      <td>0.5</td>\n",
       "      <td>52</td>\n",
       "      <td>3</td>\n",
       "      <td>86</td>\n",
       "      <td>2</td>\n",
       "      <td>0.962963</td>\n",
       "      <td>0.033708</td>\n",
       "      <td>0.966292</td>\n",
       "      <td>0.037037</td>\n",
       "      <td>0.070745</td>\n",
       "      <td>[stand, svm_proba]</td>\n",
       "      <td>X, Test Size=0.25, Standard Scaler, Random Grid (Accuracy), T=0.50</td>\n",
       "      <td>May 30, 2024 09:18 AM UTC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>DecisionTreeClassifier</td>\n",
       "      <td>0.25</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.518110</td>\n",
       "      <td>50</td>\n",
       "      <td>0.010362</td>\n",
       "      <td>0.000957</td>\n",
       "      <td>Accuracy</td>\n",
       "      <td>{'tree_class__min_samples_split': 5, 'tree_class__min_samples_leaf': 4, 'tree_class__max_depth': 3, 'tree_class__criterion': 'gini'}</td>\n",
       "      <td>0.945964</td>\n",
       "      <td>0.969484</td>\n",
       "      <td>0.958042</td>\n",
       "      <td>Yes</td>\n",
       "      <td>0.011442</td>\n",
       "      <td>0.969484</td>\n",
       "      <td>0.958042</td>\n",
       "      <td>0.986577</td>\n",
       "      <td>0.961538</td>\n",
       "      <td>0.930380</td>\n",
       "      <td>0.925926</td>\n",
       "      <td>0.957655</td>\n",
       "      <td>0.943396</td>\n",
       "      <td>0.989184</td>\n",
       "      <td>0.952559</td>\n",
       "      <td>0.5</td>\n",
       "      <td>50</td>\n",
       "      <td>2</td>\n",
       "      <td>87</td>\n",
       "      <td>4</td>\n",
       "      <td>0.925926</td>\n",
       "      <td>0.022472</td>\n",
       "      <td>0.977528</td>\n",
       "      <td>0.074074</td>\n",
       "      <td>0.096546</td>\n",
       "      <td>[tree_class]</td>\n",
       "      <td>X, Test Size=0.25, Standard Scaler, Random Grid (Accuracy), T=0.50</td>\n",
       "      <td>May 30, 2024 09:18 AM UTC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>RandomForestClassifier</td>\n",
       "      <td>0.25</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>11.892418</td>\n",
       "      <td>50</td>\n",
       "      <td>0.237848</td>\n",
       "      <td>0.006445</td>\n",
       "      <td>Accuracy</td>\n",
       "      <td>{'forest_class__n_estimators': 100, 'forest_class__min_samples_split': 5, 'forest_class__min_samples_leaf': 2, 'forest_class__max_depth': 5, 'forest_class__criterion': 'entropy'}</td>\n",
       "      <td>0.962490</td>\n",
       "      <td>0.992958</td>\n",
       "      <td>0.972028</td>\n",
       "      <td>Yes</td>\n",
       "      <td>0.020930</td>\n",
       "      <td>0.992958</td>\n",
       "      <td>0.972028</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.980769</td>\n",
       "      <td>0.981013</td>\n",
       "      <td>0.944444</td>\n",
       "      <td>0.990415</td>\n",
       "      <td>0.962264</td>\n",
       "      <td>0.999575</td>\n",
       "      <td>0.997087</td>\n",
       "      <td>0.5</td>\n",
       "      <td>51</td>\n",
       "      <td>1</td>\n",
       "      <td>88</td>\n",
       "      <td>3</td>\n",
       "      <td>0.944444</td>\n",
       "      <td>0.011236</td>\n",
       "      <td>0.988764</td>\n",
       "      <td>0.055556</td>\n",
       "      <td>0.066792</td>\n",
       "      <td>[forest_class]</td>\n",
       "      <td>X, Test Size=0.25, Standard Scaler, Random Grid (Accuracy), T=0.50</td>\n",
       "      <td>May 30, 2024 09:18 AM UTC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>XGBClassifier</td>\n",
       "      <td>0.25</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>5.500220</td>\n",
       "      <td>50</td>\n",
       "      <td>0.110004</td>\n",
       "      <td>0.002551</td>\n",
       "      <td>Accuracy</td>\n",
       "      <td>{'xgb_class__subsample': 0.8, 'xgb_class__objective': 'binary:logistic', 'xgb_class__n_estimators': 200, 'xgb_class__max_depth': 5, 'xgb_class__learning_rate': 0.5, 'xgb_class__gamma': 0, 'xgb_class__colsample_bytree': 0.7}</td>\n",
       "      <td>0.967141</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.958042</td>\n",
       "      <td>Yes</td>\n",
       "      <td>0.041958</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.958042</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.928571</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.962963</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.945455</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.995214</td>\n",
       "      <td>0.5</td>\n",
       "      <td>52</td>\n",
       "      <td>4</td>\n",
       "      <td>85</td>\n",
       "      <td>2</td>\n",
       "      <td>0.962963</td>\n",
       "      <td>0.044944</td>\n",
       "      <td>0.955056</td>\n",
       "      <td>0.037037</td>\n",
       "      <td>0.081981</td>\n",
       "      <td>[stand, xgb_class]</td>\n",
       "      <td>X, Test Size=0.25, Standard Scaler, Random Grid (Accuracy), T=0.50</td>\n",
       "      <td>May 30, 2024 09:19 AM UTC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>KerasClassifier</td>\n",
       "      <td>0.25</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>183.738184</td>\n",
       "      <td>50</td>\n",
       "      <td>3.674764</td>\n",
       "      <td>0.068376</td>\n",
       "      <td>Accuracy</td>\n",
       "      <td>{'keras_class__third_layer_dim': None, 'keras_class__second_layer_dim': 100, 'keras_class__optimizer__learning_rate': 0.001, 'keras_class__optimizer': 'adam', 'keras_class__loss': 'binary_crossentropy', 'keras_class__l2_reg': 0.0, 'keras_class__hidden_layer_dim': 50, 'keras_class__fit__batch_size': 32, 'keras_class__dropout_rate': 0.5}</td>\n",
       "      <td>0.978824</td>\n",
       "      <td>0.983568</td>\n",
       "      <td>0.979021</td>\n",
       "      <td>Yes</td>\n",
       "      <td>0.004547</td>\n",
       "      <td>0.983568</td>\n",
       "      <td>0.979021</td>\n",
       "      <td>0.974843</td>\n",
       "      <td>0.963636</td>\n",
       "      <td>0.981013</td>\n",
       "      <td>0.981481</td>\n",
       "      <td>0.977918</td>\n",
       "      <td>0.972477</td>\n",
       "      <td>0.999244</td>\n",
       "      <td>0.996463</td>\n",
       "      <td>0.5</td>\n",
       "      <td>53</td>\n",
       "      <td>2</td>\n",
       "      <td>87</td>\n",
       "      <td>1</td>\n",
       "      <td>0.981481</td>\n",
       "      <td>0.022472</td>\n",
       "      <td>0.977528</td>\n",
       "      <td>0.018519</td>\n",
       "      <td>0.040990</td>\n",
       "      <td>[stand, keras_class]</td>\n",
       "      <td>X, Test Size=0.25, Standard Scaler, Random Grid (Accuracy), T=0.50</td>\n",
       "      <td>May 30, 2024 09:19 AM UTC</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Model  Test Size Over Sample Under Sample Resample  Total Fit Time  Fit Count  Average Fit Time  Inference Time Grid Scorer                                                                                                                                                                                                                                                                                                                                        Best Params  Best CV Score  Train Score  Test Score Overfit  Overfit Difference  Train Accuracy Score  Test Accuracy Score  Train Precision Score  Test Precision Score  Train Recall Score  Test Recall Score  Train F1 Score  Test F1 Score  Train ROC AUC Score  Test ROC AUC Score  Threshold  True Positives  False Positives  True Negatives  False Negatives       TPR       FPR       TNR       FNR  False Rate              Pipeline                                                               Notes                  Timestamp\n",
       "0      LogisticRegression       0.25        None         None     None        2.600479         50          0.052010        0.001263    Accuracy                                                                                                                                                                                                                                                                                                        {'logreg__solver': 'saga', 'logreg__C': 10}       0.976471     0.990610    0.972028     Yes            0.018582              0.990610             0.972028               0.993590              0.946429            0.981013           0.981481        0.987261       0.963636             0.998796            0.995630        0.5              53                3              86                1  0.981481  0.033708  0.966292  0.018519    0.052226       [stand, logreg]  X, Test Size=0.25, Standard Scaler, Random Grid (Accuracy), T=0.50  May 30, 2024 09:18 AM UTC\n",
       "1    KNeighborsClassifier       0.25        None         None     None        0.609048         50          0.012181        0.004320    Accuracy                                                                                                                                                                                                                                                  {'knn_class__weights': 'distance', 'knn_class__n_neighbors': 3, 'knn_class__metric': 'manhattan'}       0.976471     1.000000    0.972028     Yes            0.027972              1.000000             0.972028               1.000000              0.962963            1.000000           0.962963        1.000000       0.962963             1.000000            0.987412        0.5              52                2              87                2  0.962963  0.022472  0.977528  0.037037    0.059509    [stand, knn_class]  X, Test Size=0.25, Standard Scaler, Random Grid (Accuracy), T=0.50  May 30, 2024 09:18 AM UTC\n",
       "2                     SVC       0.25        None         None     None        1.118782         50          0.022376        0.003180    Accuracy                                                                                                                                                                                                                                                                                                   {'svm_proba__kernel': 'rbf', 'svm_proba__C': 10}       0.978824     0.992958    0.965035     Yes            0.027923              0.992958             0.965035               1.000000              0.945455            0.981013           0.962963        0.990415       0.954128             1.000000            0.995630        0.5              52                3              86                2  0.962963  0.033708  0.966292  0.037037    0.070745    [stand, svm_proba]  X, Test Size=0.25, Standard Scaler, Random Grid (Accuracy), T=0.50  May 30, 2024 09:18 AM UTC\n",
       "3  DecisionTreeClassifier       0.25        None         None     None        0.518110         50          0.010362        0.000957    Accuracy                                                                                                                                                                                                               {'tree_class__min_samples_split': 5, 'tree_class__min_samples_leaf': 4, 'tree_class__max_depth': 3, 'tree_class__criterion': 'gini'}       0.945964     0.969484    0.958042     Yes            0.011442              0.969484             0.958042               0.986577              0.961538            0.930380           0.925926        0.957655       0.943396             0.989184            0.952559        0.5              50                2              87                4  0.925926  0.022472  0.977528  0.074074    0.096546          [tree_class]  X, Test Size=0.25, Standard Scaler, Random Grid (Accuracy), T=0.50  May 30, 2024 09:18 AM UTC\n",
       "4  RandomForestClassifier       0.25        None         None     None       11.892418         50          0.237848        0.006445    Accuracy                                                                                                                                                                 {'forest_class__n_estimators': 100, 'forest_class__min_samples_split': 5, 'forest_class__min_samples_leaf': 2, 'forest_class__max_depth': 5, 'forest_class__criterion': 'entropy'}       0.962490     0.992958    0.972028     Yes            0.020930              0.992958             0.972028               1.000000              0.980769            0.981013           0.944444        0.990415       0.962264             0.999575            0.997087        0.5              51                1              88                3  0.944444  0.011236  0.988764  0.055556    0.066792        [forest_class]  X, Test Size=0.25, Standard Scaler, Random Grid (Accuracy), T=0.50  May 30, 2024 09:18 AM UTC\n",
       "5           XGBClassifier       0.25        None         None     None        5.500220         50          0.110004        0.002551    Accuracy                                                                                                                    {'xgb_class__subsample': 0.8, 'xgb_class__objective': 'binary:logistic', 'xgb_class__n_estimators': 200, 'xgb_class__max_depth': 5, 'xgb_class__learning_rate': 0.5, 'xgb_class__gamma': 0, 'xgb_class__colsample_bytree': 0.7}       0.967141     1.000000    0.958042     Yes            0.041958              1.000000             0.958042               1.000000              0.928571            1.000000           0.962963        1.000000       0.945455             1.000000            0.995214        0.5              52                4              85                2  0.962963  0.044944  0.955056  0.037037    0.081981    [stand, xgb_class]  X, Test Size=0.25, Standard Scaler, Random Grid (Accuracy), T=0.50  May 30, 2024 09:19 AM UTC\n",
       "6         KerasClassifier       0.25        None         None     None      183.738184         50          3.674764        0.068376    Accuracy  {'keras_class__third_layer_dim': None, 'keras_class__second_layer_dim': 100, 'keras_class__optimizer__learning_rate': 0.001, 'keras_class__optimizer': 'adam', 'keras_class__loss': 'binary_crossentropy', 'keras_class__l2_reg': 0.0, 'keras_class__hidden_layer_dim': 50, 'keras_class__fit__batch_size': 32, 'keras_class__dropout_rate': 0.5}       0.978824     0.983568    0.979021     Yes            0.004547              0.983568             0.979021               0.974843              0.963636            0.981013           0.981481        0.977918       0.972477             0.999244            0.996463        0.5              53                2              87                1  0.981481  0.022472  0.977528  0.018519    0.040990  [stand, keras_class]  X, Test Size=0.25, Standard Scaler, Random Grid (Accuracy), T=0.50  May 30, 2024 09:19 AM UTC"
      ]
     },
     "execution_count": 143,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the results\n",
    "results_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot the Best Models\n",
    "\n",
    "In case you want to plot different metrics, you can create a custom chart, or you can call `dw.plot_results` and specify the metrics (column names) you want to plot, and which metric should be used to find the top performer (`select_metric`). With this data, instead of 'Iteration' for the `x_column` name, we set it to 'Model'. The style of the chart can be customized. You can choose to plot as a `chart_type` of 'line' or 'bar'. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "dw.plot_results(results_df, ['Test ROC AUC Score', 'Test Accuracy Score', 'Test F1 Score', 'Test Precision Score', 'Test Recall Score'], select_metric='Test F1 Score', x_column='Model',\n",
    "                          title='Test Scores by Model', chart_type='bar')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Compare Multi-Class Classification Models\n",
    "\n",
    "Let's repeat the process, but with a multi-class dataset. Some of the binary classification metrics and charts disappear, but the comparison still works."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a sample multi-class classification dataset\n",
    "X, y = load_iris(return_X_y=True)\n",
    "X = pd.DataFrame(X, columns=['sepal_length', 'sepal_width', 'petal_length', 'petal_width'])\n",
    "y = pd.Series(y)\n",
    "class_map = {0: 'Setosa', 1: 'Versicolor', 2: 'Virginica'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set some variables referenced in the config\n",
    "random_state = 42\n",
    "class_weight = None\n",
    "max_iter = 10000\n",
    "\n",
    "# Set column lists referenced in the config\n",
    "num_columns = list(X.columns)\n",
    "cat_columns = []\n",
    "\n",
    "# Define the callback for early stop, referenced by KerasClassifier\n",
    "stopper = EarlyStopping(patience=4)\n",
    "\n",
    "# Create a custom configuration file with model pipeline components and grid search params\n",
    "my_config = {\n",
    "    'models' : {\n",
    "        'logreg': LogisticRegression(max_iter=max_iter, random_state=random_state, class_weight=class_weight),\n",
    "        'knn_class': KNeighborsClassifier(),\n",
    "        'svm_proba': SVC(random_state=random_state, probability=True, class_weight=class_weight),\n",
    "        'tree_class': DecisionTreeClassifier(random_state=random_state, class_weight=class_weight),\n",
    "        'forest_class': RandomForestClassifier(random_state=random_state, class_weight=class_weight),\n",
    "        'xgb_class': XGBClassifier(random_state=random_state),\n",
    "        'keras_class': KerasClassifier(model=dw.create_nn_multi, hidden_layer_dim=50, second_layer_dim=None,\n",
    "                                       third_layer_dim=None, dropout_rate=0.2, epochs=50, l2_reg=0.0,\n",
    "                                       verbose=0, class_weight=class_weight, random_state=random_state,\n",
    "                                       fit__validation_split=0.2, fit__callbacks=[stopper],\n",
    "                                       fit__batch_size=32, metrics=['accuracy'])   \n",
    "    },\n",
    "    'scalers': {\n",
    "        'stand': StandardScaler(),\n",
    "    },\n",
    "    'params' : {\n",
    "        'logreg': {\n",
    "            'logreg__C': [0.0001, 0.001, 0.01, 0.1, 1, 10, 100],\n",
    "            'logreg__solver': ['newton-cg', 'lbfgs', 'saga']\n",
    "        },\n",
    "        'knn_class': {\n",
    "            'knn_class__n_neighbors': [3, 5, 10, 15, 20, 25],\n",
    "            'knn_class__weights': ['uniform', 'distance'],\n",
    "            'knn_class__metric': ['euclidean', 'manhattan']\n",
    "        },\n",
    "        'svm_proba': {\n",
    "            'svm_proba__C': [0.0001, 0.001, 0.01, 0.1, 1, 10, 100],\n",
    "            'svm_proba__kernel': ['linear', 'poly', 'rbf', 'sigmoid']\n",
    "        },\n",
    "        'tree_class': {\n",
    "            'tree_class__max_depth': [3, 5, 7],\n",
    "            'tree_class__min_samples_split': [5, 10, 15],\n",
    "            'tree_class__criterion': ['gini', 'entropy'],\n",
    "            'tree_class__min_samples_leaf': [2, 4, 6]\n",
    "        },\n",
    "        'forest_class': {\n",
    "            'forest_class__n_estimators' : [50, 100, 200],\n",
    "            'forest_class__max_depth': [3, 5, 7],\n",
    "            'forest_class__min_samples_split': [5, 10, 15],\n",
    "            'forest_class__criterion': ['gini', 'entropy'],\n",
    "            'forest_class__min_samples_leaf': [2, 4, 6]\n",
    "        },\n",
    "        'xgb_class': {\n",
    "            'xgb_class__learning_rate': [0.01, 0.1, 0.5],\n",
    "            'xgb_class__max_depth': [3, 5, 7],\n",
    "            'xgb_class__subsample': [0.7, 0.8, 0.9],\n",
    "            'xgb_class__colsample_bytree': [0.7, 0.8, 0.9],\n",
    "            'xgb_class__n_estimators': [50, 100, 200],\n",
    "            'xgb_class__objective': ['binary:logistic'],\n",
    "            'xgb_class__gamma': [0, 1, 5, 10]\n",
    "        },\n",
    "        'keras_class': {\n",
    "            'keras_class__loss': ['categorical_crossentropy'],\n",
    "            'keras_class__optimizer': ['adam'],\n",
    "            'keras_class__hidden_layer_dim': [50, 100, 200],\n",
    "            'keras_class__dropout_rate': [0.5],\n",
    "            'keras_class__l2_reg': [0.0],\n",
    "            'keras_class__second_layer_dim': [50, 100],\n",
    "            'keras_class__third_layer_dim': [None, 25, 50],\n",
    "            'keras_class__optimizer__learning_rate': [0.001],\n",
    "            'keras_class__fit__batch_size': [32]\n",
    "        }\n",
    "    },\n",
    "    'cv': {\n",
    "        'kfold_5': KFold(n_splits=5, shuffle=True, random_state=42),\n",
    "    },\n",
    "    'no_scale': ['tree_class', 'forest_class'],\n",
    "    'no_poly': ['knn_class', 'tree_class', 'forest_class', 'xgb_class']\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-----------------------------------------------------------------------------------------\n",
      "Starting Data Processing - May 30, 2024 09:22 AM UTC\n",
      "-----------------------------------------------------------------------------------------\n",
      "\n",
      "Classification type detected: multi\n",
      "Unique values in y: [0 1 2]\n",
      "\n",
      "Train/Test split, test_size:  0.25\n",
      "X_train, X_test, y_train, y_test shapes:  (112, 4) (38, 4) (112,) (38,)\n",
      "\n",
      "-----------------------------------------------------------------------------------------\n",
      "1/7: Starting LogisticRegression Random Search - May 30, 2024 09:22 AM UTC\n",
      "-----------------------------------------------------------------------------------------\n",
      "\n",
      "Fitting 5 folds for each of 10 candidates, totalling 50 fits\n",
      "[CV 1/5] END logreg__C=0.0001, logreg__solver=newton-cg;, score=0.304 total time=   0.0s\n",
      "[CV 2/5] END logreg__C=0.0001, logreg__solver=newton-cg;, score=0.261 total time=   0.0s\n",
      "[CV 3/5] END logreg__C=0.0001, logreg__solver=newton-cg;, score=0.227 total time=   0.0s\n",
      "[CV 4/5] END logreg__C=0.0001, logreg__solver=newton-cg;, score=0.273 total time=   0.0s\n",
      "[CV 5/5] END logreg__C=0.0001, logreg__solver=newton-cg;, score=0.273 total time=   0.0s\n",
      "[CV 1/5] END .logreg__C=10, logreg__solver=saga;, score=0.957 total time=   0.0s\n",
      "[CV 2/5] END .logreg__C=10, logreg__solver=saga;, score=1.000 total time=   0.0s\n",
      "[CV 3/5] END .logreg__C=10, logreg__solver=saga;, score=0.955 total time=   0.0s\n",
      "[CV 4/5] END .logreg__C=10, logreg__solver=saga;, score=0.909 total time=   0.0s\n",
      "[CV 5/5] END .logreg__C=10, logreg__solver=saga;, score=0.955 total time=   0.0s\n",
      "[CV 1/5] END logreg__C=10, logreg__solver=newton-cg;, score=0.957 total time=   0.0s\n",
      "[CV 2/5] END logreg__C=10, logreg__solver=newton-cg;, score=1.000 total time=   0.0s\n",
      "[CV 3/5] END logreg__C=10, logreg__solver=newton-cg;, score=0.955 total time=   0.0s\n",
      "[CV 4/5] END logreg__C=10, logreg__solver=newton-cg;, score=0.909 total time=   0.0s\n",
      "[CV 5/5] END logreg__C=10, logreg__solver=newton-cg;, score=0.955 total time=   0.0s\n",
      "[CV 1/5] END logreg__C=0.0001, logreg__solver=lbfgs;, score=0.304 total time=   0.0s\n",
      "[CV 2/5] END logreg__C=0.0001, logreg__solver=lbfgs;, score=0.261 total time=   0.0s\n",
      "[CV 3/5] END logreg__C=0.0001, logreg__solver=lbfgs;, score=0.227 total time=   0.0s\n",
      "[CV 4/5] END logreg__C=0.0001, logreg__solver=lbfgs;, score=0.273 total time=   0.0s\n",
      "[CV 5/5] END logreg__C=0.0001, logreg__solver=lbfgs;, score=0.273 total time=   0.0s\n",
      "[CV 1/5] END logreg__C=0.01, logreg__solver=saga;, score=0.696 total time=   0.0s\n",
      "[CV 2/5] END logreg__C=0.01, logreg__solver=saga;, score=0.913 total time=   0.0s\n",
      "[CV 3/5] END logreg__C=0.01, logreg__solver=saga;, score=0.864 total time=   0.0s\n",
      "[CV 4/5] END logreg__C=0.01, logreg__solver=saga;, score=0.818 total time=   0.0s\n",
      "[CV 5/5] END logreg__C=0.01, logreg__solver=saga;, score=0.636 total time=   0.0s\n",
      "[CV 1/5] END logreg__C=0.001, logreg__solver=saga;, score=0.522 total time=   0.0s\n",
      "[CV 2/5] END logreg__C=0.001, logreg__solver=saga;, score=0.304 total time=   0.0s\n",
      "[CV 3/5] END logreg__C=0.001, logreg__solver=saga;, score=0.273 total time=   0.0s\n",
      "[CV 4/5] END logreg__C=0.001, logreg__solver=saga;, score=0.455 total time=   0.0s\n",
      "[CV 5/5] END logreg__C=0.001, logreg__solver=saga;, score=0.500 total time=   0.0s\n",
      "[CV 1/5] END logreg__C=0.1, logreg__solver=saga;, score=0.826 total time=   0.0s\n",
      "[CV 2/5] END logreg__C=0.1, logreg__solver=saga;, score=1.000 total time=   0.0s\n",
      "[CV 3/5] END logreg__C=0.1, logreg__solver=saga;, score=0.864 total time=   0.0s\n",
      "[CV 4/5] END logreg__C=0.1, logreg__solver=saga;, score=0.818 total time=   0.0s\n",
      "[CV 5/5] END logreg__C=0.1, logreg__solver=saga;, score=0.773 total time=   0.0s\n",
      "[CV 1/5] END logreg__C=0.001, logreg__solver=newton-cg;, score=0.522 total time=   0.0s\n",
      "[CV 2/5] END logreg__C=0.001, logreg__solver=newton-cg;, score=0.304 total time=   0.0s\n",
      "[CV 3/5] END logreg__C=0.001, logreg__solver=newton-cg;, score=0.273 total time=   0.0s\n",
      "[CV 4/5] END logreg__C=0.001, logreg__solver=newton-cg;, score=0.455 total time=   0.0s\n",
      "[CV 5/5] END logreg__C=0.001, logreg__solver=newton-cg;, score=0.500 total time=   0.0s\n",
      "[CV 1/5] END logreg__C=100, logreg__solver=newton-cg;, score=0.957 total time=   0.0s\n",
      "[CV 2/5] END logreg__C=100, logreg__solver=newton-cg;, score=1.000 total time=   0.0s\n",
      "[CV 3/5] END logreg__C=100, logreg__solver=newton-cg;, score=0.909 total time=   0.0s\n",
      "[CV 4/5] END logreg__C=100, logreg__solver=newton-cg;, score=0.909 total time=   0.0s\n",
      "[CV 5/5] END logreg__C=100, logreg__solver=newton-cg;, score=0.955 total time=   0.0s\n",
      "[CV 1/5] END logreg__C=10, logreg__solver=lbfgs;, score=0.957 total time=   0.0s\n",
      "[CV 2/5] END logreg__C=10, logreg__solver=lbfgs;, score=1.000 total time=   0.0s\n",
      "[CV 3/5] END logreg__C=10, logreg__solver=lbfgs;, score=0.955 total time=   0.0s\n",
      "[CV 4/5] END logreg__C=10, logreg__solver=lbfgs;, score=0.909 total time=   0.0s\n",
      "[CV 5/5] END logreg__C=10, logreg__solver=lbfgs;, score=0.955 total time=   0.0s\n",
      "\n",
      "Total Time: 0.3992 seconds\n",
      "Average Fit Time: 0.0080 seconds\n",
      "Inference Time: 0.0008\n",
      "Best CV Accuracy Score: 0.9549\n",
      "Train Accuracy Score: 0.9821\n",
      "Test Accuracy Score: 1.0000\n",
      "Overfit: No\n",
      "Overfit Difference: -0.0179\n",
      "Best Parameters: {'logreg__solver': 'saga', 'logreg__C': 10}\n",
      "\n",
      "LogisticRegression Multi-Class Classification Report\n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "      Setosa     1.0000    1.0000    1.0000        15\n",
      "  Versicolor     1.0000    1.0000    1.0000        11\n",
      "   Virginica     1.0000    1.0000    1.0000        12\n",
      "\n",
      "    accuracy                         1.0000        38\n",
      "   macro avg     1.0000    1.0000    1.0000        38\n",
      "weighted avg     1.0000    1.0000    1.0000        38\n",
      "\n",
      "ROC AUC: 1.0\n",
      "\n",
      "Predicted   Setosa  Versicolor  Virginica\n",
      "Actual                                   \n",
      "Setosa          15           0          0\n",
      "Versicolor       0          11          0\n",
      "Virginica        0           0         12\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 450x450 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-----------------------------------------------------------------------------------------\n",
      "2/7: Starting KNeighborsClassifier Random Search - May 30, 2024 09:22 AM UTC\n",
      "-----------------------------------------------------------------------------------------\n",
      "\n",
      "Fitting 5 folds for each of 10 candidates, totalling 50 fits\n",
      "[CV 1/5] END knn_class__metric=euclidean, knn_class__n_neighbors=20, knn_class__weights=uniform;, score=0.870 total time=   0.0s\n",
      "[CV 2/5] END knn_class__metric=euclidean, knn_class__n_neighbors=20, knn_class__weights=uniform;, score=0.870 total time=   0.0s\n",
      "[CV 3/5] END knn_class__metric=euclidean, knn_class__n_neighbors=20, knn_class__weights=uniform;, score=0.909 total time=   0.0s\n",
      "[CV 4/5] END knn_class__metric=euclidean, knn_class__n_neighbors=20, knn_class__weights=uniform;, score=0.864 total time=   0.0s\n",
      "[CV 5/5] END knn_class__metric=euclidean, knn_class__n_neighbors=20, knn_class__weights=uniform;, score=0.864 total time=   0.0s\n",
      "[CV 1/5] END knn_class__metric=manhattan, knn_class__n_neighbors=10, knn_class__weights=uniform;, score=0.957 total time=   0.0s\n",
      "[CV 2/5] END knn_class__metric=manhattan, knn_class__n_neighbors=10, knn_class__weights=uniform;, score=0.957 total time=   0.0s\n",
      "[CV 3/5] END knn_class__metric=manhattan, knn_class__n_neighbors=10, knn_class__weights=uniform;, score=0.909 total time=   0.0s\n",
      "[CV 4/5] END knn_class__metric=manhattan, knn_class__n_neighbors=10, knn_class__weights=uniform;, score=0.864 total time=   0.0s\n",
      "[CV 5/5] END knn_class__metric=manhattan, knn_class__n_neighbors=10, knn_class__weights=uniform;, score=0.909 total time=   0.0s\n",
      "[CV 1/5] END knn_class__metric=euclidean, knn_class__n_neighbors=3, knn_class__weights=uniform;, score=1.000 total time=   0.0s\n",
      "[CV 2/5] END knn_class__metric=euclidean, knn_class__n_neighbors=3, knn_class__weights=uniform;, score=1.000 total time=   0.0s\n",
      "[CV 3/5] END knn_class__metric=euclidean, knn_class__n_neighbors=3, knn_class__weights=uniform;, score=0.955 total time=   0.0s\n",
      "[CV 4/5] END knn_class__metric=euclidean, knn_class__n_neighbors=3, knn_class__weights=uniform;, score=0.909 total time=   0.0s\n",
      "[CV 5/5] END knn_class__metric=euclidean, knn_class__n_neighbors=3, knn_class__weights=uniform;, score=0.909 total time=   0.0s\n",
      "[CV 1/5] END knn_class__metric=manhattan, knn_class__n_neighbors=15, knn_class__weights=uniform;, score=0.913 total time=   0.0s\n",
      "[CV 2/5] END knn_class__metric=manhattan, knn_class__n_neighbors=15, knn_class__weights=uniform;, score=0.957 total time=   0.0s\n",
      "[CV 3/5] END knn_class__metric=manhattan, knn_class__n_neighbors=15, knn_class__weights=uniform;, score=0.955 total time=   0.0s\n",
      "[CV 4/5] END knn_class__metric=manhattan, knn_class__n_neighbors=15, knn_class__weights=uniform;, score=0.864 total time=   0.0s\n",
      "[CV 5/5] END knn_class__metric=manhattan, knn_class__n_neighbors=15, knn_class__weights=uniform;, score=0.909 total time=   0.0s\n",
      "[CV 1/5] END knn_class__metric=euclidean, knn_class__n_neighbors=25, knn_class__weights=distance;, score=0.913 total time=   0.0s\n",
      "[CV 2/5] END knn_class__metric=euclidean, knn_class__n_neighbors=25, knn_class__weights=distance;, score=0.957 total time=   0.0s\n",
      "[CV 3/5] END knn_class__metric=euclidean, knn_class__n_neighbors=25, knn_class__weights=distance;, score=0.909 total time=   0.0s\n",
      "[CV 4/5] END knn_class__metric=euclidean, knn_class__n_neighbors=25, knn_class__weights=distance;, score=0.864 total time=   0.0s\n",
      "[CV 5/5] END knn_class__metric=euclidean, knn_class__n_neighbors=25, knn_class__weights=distance;, score=0.909 total time=   0.0s\n",
      "[CV 1/5] END knn_class__metric=euclidean, knn_class__n_neighbors=20, knn_class__weights=distance;, score=0.913 total time=   0.0s\n",
      "[CV 2/5] END knn_class__metric=euclidean, knn_class__n_neighbors=20, knn_class__weights=distance;, score=1.000 total time=   0.0s\n",
      "[CV 3/5] END knn_class__metric=euclidean, knn_class__n_neighbors=20, knn_class__weights=distance;, score=0.955 total time=   0.0s\n",
      "[CV 4/5] END knn_class__metric=euclidean, knn_class__n_neighbors=20, knn_class__weights=distance;, score=0.864 total time=   0.0s\n",
      "[CV 5/5] END knn_class__metric=euclidean, knn_class__n_neighbors=20, knn_class__weights=distance;, score=0.909 total time=   0.0s\n",
      "[CV 1/5] END knn_class__metric=manhattan, knn_class__n_neighbors=3, knn_class__weights=distance;, score=0.913 total time=   0.0s\n",
      "[CV 2/5] END knn_class__metric=manhattan, knn_class__n_neighbors=3, knn_class__weights=distance;, score=1.000 total time=   0.0s\n",
      "[CV 3/5] END knn_class__metric=manhattan, knn_class__n_neighbors=3, knn_class__weights=distance;, score=0.955 total time=   0.0s\n",
      "[CV 4/5] END knn_class__metric=manhattan, knn_class__n_neighbors=3, knn_class__weights=distance;, score=0.864 total time=   0.0s\n",
      "[CV 5/5] END knn_class__metric=manhattan, knn_class__n_neighbors=3, knn_class__weights=distance;, score=0.909 total time=   0.0s\n",
      "[CV 1/5] END knn_class__metric=euclidean, knn_class__n_neighbors=3, knn_class__weights=distance;, score=1.000 total time=   0.0s\n",
      "[CV 2/5] END knn_class__metric=euclidean, knn_class__n_neighbors=3, knn_class__weights=distance;, score=1.000 total time=   0.0s\n",
      "[CV 3/5] END knn_class__metric=euclidean, knn_class__n_neighbors=3, knn_class__weights=distance;, score=0.955 total time=   0.0s\n",
      "[CV 4/5] END knn_class__metric=euclidean, knn_class__n_neighbors=3, knn_class__weights=distance;, score=0.909 total time=   0.0s\n",
      "[CV 5/5] END knn_class__metric=euclidean, knn_class__n_neighbors=3, knn_class__weights=distance;, score=0.909 total time=   0.0s\n",
      "[CV 1/5] END knn_class__metric=manhattan, knn_class__n_neighbors=20, knn_class__weights=distance;, score=0.913 total time=   0.0s\n",
      "[CV 2/5] END knn_class__metric=manhattan, knn_class__n_neighbors=20, knn_class__weights=distance;, score=1.000 total time=   0.0s\n",
      "[CV 3/5] END knn_class__metric=manhattan, knn_class__n_neighbors=20, knn_class__weights=distance;, score=0.909 total time=   0.0s\n",
      "[CV 4/5] END knn_class__metric=manhattan, knn_class__n_neighbors=20, knn_class__weights=distance;, score=0.864 total time=   0.0s\n",
      "[CV 5/5] END knn_class__metric=manhattan, knn_class__n_neighbors=20, knn_class__weights=distance;, score=0.909 total time=   0.0s\n",
      "[CV 1/5] END knn_class__metric=euclidean, knn_class__n_neighbors=10, knn_class__weights=distance;, score=1.000 total time=   0.0s\n",
      "[CV 2/5] END knn_class__metric=euclidean, knn_class__n_neighbors=10, knn_class__weights=distance;, score=1.000 total time=   0.0s\n",
      "[CV 3/5] END knn_class__metric=euclidean, knn_class__n_neighbors=10, knn_class__weights=distance;, score=0.955 total time=   0.0s\n",
      "[CV 4/5] END knn_class__metric=euclidean, knn_class__n_neighbors=10, knn_class__weights=distance;, score=0.864 total time=   0.0s\n",
      "[CV 5/5] END knn_class__metric=euclidean, knn_class__n_neighbors=10, knn_class__weights=distance;, score=0.909 total time=   0.0s\n",
      "\n",
      "Total Time: 0.3394 seconds\n",
      "Average Fit Time: 0.0068 seconds\n",
      "Inference Time: 0.0039\n",
      "Best CV Accuracy Score: 0.9545\n",
      "Train Accuracy Score: 0.9464\n",
      "Test Accuracy Score: 1.0000\n",
      "Overfit: No\n",
      "Overfit Difference: -0.0536\n",
      "Best Parameters: {'knn_class__weights': 'uniform', 'knn_class__n_neighbors': 3, 'knn_class__metric': 'euclidean'}\n",
      "\n",
      "KNeighborsClassifier Multi-Class Classification Report\n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "      Setosa     1.0000    1.0000    1.0000        15\n",
      "  Versicolor     1.0000    1.0000    1.0000        11\n",
      "   Virginica     1.0000    1.0000    1.0000        12\n",
      "\n",
      "    accuracy                         1.0000        38\n",
      "   macro avg     1.0000    1.0000    1.0000        38\n",
      "weighted avg     1.0000    1.0000    1.0000        38\n",
      "\n",
      "ROC AUC: 1.0\n",
      "\n",
      "Predicted   Setosa  Versicolor  Virginica\n",
      "Actual                                   \n",
      "Setosa          15           0          0\n",
      "Versicolor       0          11          0\n",
      "Virginica        0           0         12\n",
      "\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 450x450 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-----------------------------------------------------------------------------------------\n",
      "3/7: Starting SVC Random Search - May 30, 2024 09:22 AM UTC\n",
      "-----------------------------------------------------------------------------------------\n",
      "\n",
      "Fitting 5 folds for each of 10 candidates, totalling 50 fits\n",
      "[CV 1/5] END svm_proba__C=0.01, svm_proba__kernel=poly;, score=0.522 total time=   0.0s\n",
      "[CV 2/5] END svm_proba__C=0.01, svm_proba__kernel=poly;, score=0.348 total time=   0.0s\n",
      "[CV 3/5] END svm_proba__C=0.01, svm_proba__kernel=poly;, score=0.409 total time=   0.0s\n",
      "[CV 4/5] END svm_proba__C=0.01, svm_proba__kernel=poly;, score=0.409 total time=   0.0s\n",
      "[CV 5/5] END svm_proba__C=0.01, svm_proba__kernel=poly;, score=0.500 total time=   0.0s\n",
      "[CV 1/5] END svm_proba__C=100, svm_proba__kernel=poly;, score=0.957 total time=   0.0s\n",
      "[CV 2/5] END svm_proba__C=100, svm_proba__kernel=poly;, score=0.957 total time=   0.0s\n",
      "[CV 3/5] END svm_proba__C=100, svm_proba__kernel=poly;, score=0.909 total time=   0.0s\n",
      "[CV 4/5] END svm_proba__C=100, svm_proba__kernel=poly;, score=0.909 total time=   0.0s\n",
      "[CV 5/5] END svm_proba__C=100, svm_proba__kernel=poly;, score=0.909 total time=   0.0s\n",
      "[CV 1/5] END svm_proba__C=0.01, svm_proba__kernel=linear;, score=0.696 total time=   0.0s\n",
      "[CV 2/5] END svm_proba__C=0.01, svm_proba__kernel=linear;, score=0.783 total time=   0.0s\n",
      "[CV 3/5] END svm_proba__C=0.01, svm_proba__kernel=linear;, score=0.909 total time=   0.0s\n",
      "[CV 4/5] END svm_proba__C=0.01, svm_proba__kernel=linear;, score=0.818 total time=   0.0s\n",
      "[CV 5/5] END svm_proba__C=0.01, svm_proba__kernel=linear;, score=0.591 total time=   0.0s\n",
      "[CV 1/5] END svm_proba__C=10, svm_proba__kernel=poly;, score=1.000 total time=   0.0s\n",
      "[CV 2/5] END svm_proba__C=10, svm_proba__kernel=poly;, score=0.957 total time=   0.0s\n",
      "[CV 3/5] END svm_proba__C=10, svm_proba__kernel=poly;, score=0.909 total time=   0.0s\n",
      "[CV 4/5] END svm_proba__C=10, svm_proba__kernel=poly;, score=0.864 total time=   0.0s\n",
      "[CV 5/5] END svm_proba__C=10, svm_proba__kernel=poly;, score=1.000 total time=   0.0s\n",
      "[CV 1/5] END svm_proba__C=0.0001, svm_proba__kernel=linear;, score=0.304 total time=   0.0s\n",
      "[CV 2/5] END svm_proba__C=0.0001, svm_proba__kernel=linear;, score=0.261 total time=   0.0s\n",
      "[CV 3/5] END svm_proba__C=0.0001, svm_proba__kernel=linear;, score=0.227 total time=   0.0s\n",
      "[CV 4/5] END svm_proba__C=0.0001, svm_proba__kernel=linear;, score=0.273 total time=   0.0s\n",
      "[CV 5/5] END svm_proba__C=0.0001, svm_proba__kernel=linear;, score=0.273 total time=   0.0s\n",
      "[CV 1/5] END svm_proba__C=0.1, svm_proba__kernel=linear;, score=0.957 total time=   0.0s\n",
      "[CV 2/5] END svm_proba__C=0.1, svm_proba__kernel=linear;, score=1.000 total time=   0.0s\n",
      "[CV 3/5] END svm_proba__C=0.1, svm_proba__kernel=linear;, score=0.909 total time=   0.0s\n",
      "[CV 4/5] END svm_proba__C=0.1, svm_proba__kernel=linear;, score=0.909 total time=   0.0s\n",
      "[CV 5/5] END svm_proba__C=0.1, svm_proba__kernel=linear;, score=0.909 total time=   0.0s\n",
      "[CV 1/5] END svm_proba__C=1, svm_proba__kernel=poly;, score=0.913 total time=   0.0s\n",
      "[CV 2/5] END svm_proba__C=1, svm_proba__kernel=poly;, score=0.826 total time=   0.0s\n",
      "[CV 3/5] END svm_proba__C=1, svm_proba__kernel=poly;, score=0.818 total time=   0.0s\n",
      "[CV 4/5] END svm_proba__C=1, svm_proba__kernel=poly;, score=0.909 total time=   0.0s\n",
      "[CV 5/5] END svm_proba__C=1, svm_proba__kernel=poly;, score=1.000 total time=   0.0s\n",
      "[CV 1/5] END svm_proba__C=10, svm_proba__kernel=rbf;, score=0.957 total time=   0.0s\n",
      "[CV 2/5] END svm_proba__C=10, svm_proba__kernel=rbf;, score=1.000 total time=   0.0s\n",
      "[CV 3/5] END svm_proba__C=10, svm_proba__kernel=rbf;, score=0.955 total time=   0.0s\n",
      "[CV 4/5] END svm_proba__C=10, svm_proba__kernel=rbf;, score=0.909 total time=   0.0s\n",
      "[CV 5/5] END svm_proba__C=10, svm_proba__kernel=rbf;, score=0.909 total time=   0.0s\n",
      "[CV 1/5] END svm_proba__C=0.01, svm_proba__kernel=sigmoid;, score=0.304 total time=   0.0s\n",
      "[CV 2/5] END svm_proba__C=0.01, svm_proba__kernel=sigmoid;, score=0.261 total time=   0.0s\n",
      "[CV 3/5] END svm_proba__C=0.01, svm_proba__kernel=sigmoid;, score=0.227 total time=   0.0s\n",
      "[CV 4/5] END svm_proba__C=0.01, svm_proba__kernel=sigmoid;, score=0.273 total time=   0.0s\n",
      "[CV 5/5] END svm_proba__C=0.01, svm_proba__kernel=sigmoid;, score=0.273 total time=   0.0s\n",
      "[CV 1/5] END svm_proba__C=0.1, svm_proba__kernel=poly;, score=0.870 total time=   0.0s\n",
      "[CV 2/5] END svm_proba__C=0.1, svm_proba__kernel=poly;, score=0.783 total time=   0.0s\n",
      "[CV 3/5] END svm_proba__C=0.1, svm_proba__kernel=poly;, score=0.773 total time=   0.0s\n",
      "[CV 4/5] END svm_proba__C=0.1, svm_proba__kernel=poly;, score=0.727 total time=   0.0s\n",
      "[CV 5/5] END svm_proba__C=0.1, svm_proba__kernel=poly;, score=0.909 total time=   0.0s\n",
      "\n",
      "Total Time: 0.3629 seconds\n",
      "Average Fit Time: 0.0073 seconds\n",
      "Inference Time: 0.0012\n",
      "Best CV Accuracy Score: 0.9458\n",
      "Train Accuracy Score: 0.9821\n",
      "Test Accuracy Score: 0.9737\n",
      "Overfit: Yes\n",
      "Overfit Difference: 0.0085\n",
      "Best Parameters: {'svm_proba__kernel': 'rbf', 'svm_proba__C': 10}\n",
      "\n",
      "SVC Multi-Class Classification Report\n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "      Setosa     1.0000    1.0000    1.0000        15\n",
      "  Versicolor     1.0000    0.9091    0.9524        11\n",
      "   Virginica     0.9231    1.0000    0.9600        12\n",
      "\n",
      "    accuracy                         0.9737        38\n",
      "   macro avg     0.9744    0.9697    0.9708        38\n",
      "weighted avg     0.9757    0.9737    0.9736        38\n",
      "\n",
      "ROC AUC: 1.0\n",
      "\n",
      "Predicted   Setosa  Versicolor  Virginica\n",
      "Actual                                   \n",
      "Setosa          15           0          0\n",
      "Versicolor       0          10          1\n",
      "Virginica        0           0         12\n",
      "\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 450x450 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-----------------------------------------------------------------------------------------\n",
      "4/7: Starting DecisionTreeClassifier Random Search - May 30, 2024 09:22 AM UTC\n",
      "-----------------------------------------------------------------------------------------\n",
      "\n",
      "Fitting 5 folds for each of 10 candidates, totalling 50 fits\n",
      "[CV 1/5] END tree_class__criterion=gini, tree_class__max_depth=7, tree_class__min_samples_leaf=2, tree_class__min_samples_split=10;, score=0.870 total time=   0.0s\n",
      "[CV 2/5] END tree_class__criterion=gini, tree_class__max_depth=7, tree_class__min_samples_leaf=2, tree_class__min_samples_split=10;, score=1.000 total time=   0.0s\n",
      "[CV 3/5] END tree_class__criterion=gini, tree_class__max_depth=7, tree_class__min_samples_leaf=2, tree_class__min_samples_split=10;, score=0.909 total time=   0.0s\n",
      "[CV 4/5] END tree_class__criterion=gini, tree_class__max_depth=7, tree_class__min_samples_leaf=2, tree_class__min_samples_split=10;, score=0.818 total time=   0.0s\n",
      "[CV 5/5] END tree_class__criterion=gini, tree_class__max_depth=7, tree_class__min_samples_leaf=2, tree_class__min_samples_split=10;, score=0.909 total time=   0.0s\n",
      "[CV 1/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=4, tree_class__min_samples_split=10;, score=0.913 total time=   0.0s\n",
      "[CV 2/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=4, tree_class__min_samples_split=10;, score=0.913 total time=   0.0s\n",
      "[CV 3/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=4, tree_class__min_samples_split=10;, score=1.000 total time=   0.0s\n",
      "[CV 4/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=4, tree_class__min_samples_split=10;, score=0.818 total time=   0.0s\n",
      "[CV 5/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=4, tree_class__min_samples_split=10;, score=0.909 total time=   0.0s\n",
      "[CV 1/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=1.000 total time=   0.0s\n",
      "[CV 2/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=0.957 total time=   0.0s\n",
      "[CV 3/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=1.000 total time=   0.0s\n",
      "[CV 4/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=0.818 total time=   0.0s\n",
      "[CV 5/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=0.909 total time=   0.0s\n",
      "[CV 1/5] END tree_class__criterion=gini, tree_class__max_depth=5, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=0.913 total time=   0.0s\n",
      "[CV 2/5] END tree_class__criterion=gini, tree_class__max_depth=5, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=1.000 total time=   0.0s\n",
      "[CV 3/5] END tree_class__criterion=gini, tree_class__max_depth=5, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=1.000 total time=   0.0s\n",
      "[CV 4/5] END tree_class__criterion=gini, tree_class__max_depth=5, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=0.818 total time=   0.0s\n",
      "[CV 5/5] END tree_class__criterion=gini, tree_class__max_depth=5, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=0.909 total time=   0.0s\n",
      "[CV 1/5] END tree_class__criterion=entropy, tree_class__max_depth=5, tree_class__min_samples_leaf=6, tree_class__min_samples_split=15;, score=0.913 total time=   0.0s\n",
      "[CV 2/5] END tree_class__criterion=entropy, tree_class__max_depth=5, tree_class__min_samples_leaf=6, tree_class__min_samples_split=15;, score=1.000 total time=   0.0s\n",
      "[CV 3/5] END tree_class__criterion=entropy, tree_class__max_depth=5, tree_class__min_samples_leaf=6, tree_class__min_samples_split=15;, score=0.955 total time=   0.0s\n",
      "[CV 4/5] END tree_class__criterion=entropy, tree_class__max_depth=5, tree_class__min_samples_leaf=6, tree_class__min_samples_split=15;, score=0.818 total time=   0.0s\n",
      "[CV 5/5] END tree_class__criterion=entropy, tree_class__max_depth=5, tree_class__min_samples_leaf=6, tree_class__min_samples_split=15;, score=0.909 total time=   0.0s\n",
      "[CV 1/5] END tree_class__criterion=gini, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=15;, score=0.913 total time=   0.0s\n",
      "[CV 2/5] END tree_class__criterion=gini, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=15;, score=1.000 total time=   0.0s\n",
      "[CV 3/5] END tree_class__criterion=gini, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=15;, score=1.000 total time=   0.0s\n",
      "[CV 4/5] END tree_class__criterion=gini, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=15;, score=0.818 total time=   0.0s\n",
      "[CV 5/5] END tree_class__criterion=gini, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=15;, score=0.909 total time=   0.0s\n",
      "[CV 1/5] END tree_class__criterion=gini, tree_class__max_depth=5, tree_class__min_samples_leaf=6, tree_class__min_samples_split=15;, score=0.913 total time=   0.0s\n",
      "[CV 2/5] END tree_class__criterion=gini, tree_class__max_depth=5, tree_class__min_samples_leaf=6, tree_class__min_samples_split=15;, score=1.000 total time=   0.0s\n",
      "[CV 3/5] END tree_class__criterion=gini, tree_class__max_depth=5, tree_class__min_samples_leaf=6, tree_class__min_samples_split=15;, score=0.955 total time=   0.0s\n",
      "[CV 4/5] END tree_class__criterion=gini, tree_class__max_depth=5, tree_class__min_samples_leaf=6, tree_class__min_samples_split=15;, score=0.818 total time=   0.0s\n",
      "[CV 5/5] END tree_class__criterion=gini, tree_class__max_depth=5, tree_class__min_samples_leaf=6, tree_class__min_samples_split=15;, score=0.909 total time=   0.0s\n",
      "[CV 1/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=6, tree_class__min_samples_split=10;, score=0.913 total time=   0.0s\n",
      "[CV 2/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=6, tree_class__min_samples_split=10;, score=1.000 total time=   0.0s\n",
      "[CV 3/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=6, tree_class__min_samples_split=10;, score=0.955 total time=   0.0s\n",
      "[CV 4/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=6, tree_class__min_samples_split=10;, score=0.818 total time=   0.0s\n",
      "[CV 5/5] END tree_class__criterion=entropy, tree_class__max_depth=7, tree_class__min_samples_leaf=6, tree_class__min_samples_split=10;, score=0.909 total time=   0.0s\n",
      "[CV 1/5] END tree_class__criterion=gini, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=0.913 total time=   0.0s\n",
      "[CV 2/5] END tree_class__criterion=gini, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=1.000 total time=   0.0s\n",
      "[CV 3/5] END tree_class__criterion=gini, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=1.000 total time=   0.0s\n",
      "[CV 4/5] END tree_class__criterion=gini, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=0.818 total time=   0.0s\n",
      "[CV 5/5] END tree_class__criterion=gini, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=5;, score=0.909 total time=   0.0s\n",
      "[CV 1/5] END tree_class__criterion=entropy, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=15;, score=0.913 total time=   0.1s\n",
      "[CV 2/5] END tree_class__criterion=entropy, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=15;, score=1.000 total time=   0.0s\n",
      "[CV 3/5] END tree_class__criterion=entropy, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=15;, score=1.000 total time=   0.0s\n",
      "[CV 4/5] END tree_class__criterion=entropy, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=15;, score=0.818 total time=   0.0s\n",
      "[CV 5/5] END tree_class__criterion=entropy, tree_class__max_depth=3, tree_class__min_samples_leaf=4, tree_class__min_samples_split=15;, score=0.909 total time=   0.0s\n",
      "\n",
      "Total Time: 0.3191 seconds\n",
      "Average Fit Time: 0.0064 seconds\n",
      "Inference Time: 0.0009\n",
      "Best CV Accuracy Score: 0.9368\n",
      "Train Accuracy Score: 0.9643\n",
      "Test Accuracy Score: 1.0000\n",
      "Overfit: No\n",
      "Overfit Difference: -0.0357\n",
      "Best Parameters: {'tree_class__min_samples_split': 5, 'tree_class__min_samples_leaf': 4, 'tree_class__max_depth': 7, 'tree_class__criterion': 'entropy'}\n",
      "\n",
      "DecisionTreeClassifier Multi-Class Classification Report\n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "      Setosa     1.0000    1.0000    1.0000        15\n",
      "  Versicolor     1.0000    1.0000    1.0000        11\n",
      "   Virginica     1.0000    1.0000    1.0000        12\n",
      "\n",
      "    accuracy                         1.0000        38\n",
      "   macro avg     1.0000    1.0000    1.0000        38\n",
      "weighted avg     1.0000    1.0000    1.0000        38\n",
      "\n",
      "ROC AUC: 1.0\n",
      "\n",
      "Predicted   Setosa  Versicolor  Virginica\n",
      "Actual                                   \n",
      "Setosa          15           0          0\n",
      "Versicolor       0          11          0\n",
      "Virginica        0           0         12\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 450x450 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-----------------------------------------------------------------------------------------\n",
      "5/7: Starting RandomForestClassifier Random Search - May 30, 2024 09:22 AM UTC\n",
      "-----------------------------------------------------------------------------------------\n",
      "\n",
      "Fitting 5 folds for each of 10 candidates, totalling 50 fits\n",
      "[CV 1/5] END forest_class__criterion=entropy, forest_class__max_depth=7, forest_class__min_samples_leaf=6, forest_class__min_samples_split=10, forest_class__n_estimators=200;, score=0.913 total time=   0.2s\n",
      "[CV 2/5] END forest_class__criterion=entropy, forest_class__max_depth=7, forest_class__min_samples_leaf=6, forest_class__min_samples_split=10, forest_class__n_estimators=200;, score=1.000 total time=   0.2s\n",
      "[CV 3/5] END forest_class__criterion=entropy, forest_class__max_depth=7, forest_class__min_samples_leaf=6, forest_class__min_samples_split=10, forest_class__n_estimators=200;, score=0.955 total time=   0.3s\n",
      "[CV 4/5] END forest_class__criterion=entropy, forest_class__max_depth=7, forest_class__min_samples_leaf=6, forest_class__min_samples_split=10, forest_class__n_estimators=200;, score=0.864 total time=   0.3s\n",
      "[CV 5/5] END forest_class__criterion=entropy, forest_class__max_depth=7, forest_class__min_samples_leaf=6, forest_class__min_samples_split=10, forest_class__n_estimators=200;, score=0.909 total time=   0.3s\n",
      "[CV 1/5] END forest_class__criterion=entropy, forest_class__max_depth=5, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=0.913 total time=   0.2s\n",
      "[CV 2/5] END forest_class__criterion=entropy, forest_class__max_depth=5, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=1.000 total time=   0.1s\n",
      "[CV 3/5] END forest_class__criterion=entropy, forest_class__max_depth=5, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=0.955 total time=   0.1s\n",
      "[CV 4/5] END forest_class__criterion=entropy, forest_class__max_depth=5, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=0.864 total time=   0.1s\n",
      "[CV 5/5] END forest_class__criterion=entropy, forest_class__max_depth=5, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=0.909 total time=   0.2s\n",
      "[CV 1/5] END forest_class__criterion=entropy, forest_class__max_depth=5, forest_class__min_samples_leaf=6, forest_class__min_samples_split=10, forest_class__n_estimators=200;, score=0.913 total time=   0.3s\n",
      "[CV 2/5] END forest_class__criterion=entropy, forest_class__max_depth=5, forest_class__min_samples_leaf=6, forest_class__min_samples_split=10, forest_class__n_estimators=200;, score=1.000 total time=   0.3s\n",
      "[CV 3/5] END forest_class__criterion=entropy, forest_class__max_depth=5, forest_class__min_samples_leaf=6, forest_class__min_samples_split=10, forest_class__n_estimators=200;, score=0.955 total time=   0.2s\n",
      "[CV 4/5] END forest_class__criterion=entropy, forest_class__max_depth=5, forest_class__min_samples_leaf=6, forest_class__min_samples_split=10, forest_class__n_estimators=200;, score=0.864 total time=   0.2s\n",
      "[CV 5/5] END forest_class__criterion=entropy, forest_class__max_depth=5, forest_class__min_samples_leaf=6, forest_class__min_samples_split=10, forest_class__n_estimators=200;, score=0.909 total time=   0.2s\n",
      "[CV 1/5] END forest_class__criterion=gini, forest_class__max_depth=7, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=0.913 total time=   0.1s\n",
      "[CV 2/5] END forest_class__criterion=gini, forest_class__max_depth=7, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=1.000 total time=   0.2s\n",
      "[CV 3/5] END forest_class__criterion=gini, forest_class__max_depth=7, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=0.955 total time=   0.1s\n",
      "[CV 4/5] END forest_class__criterion=gini, forest_class__max_depth=7, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=0.864 total time=   0.1s\n",
      "[CV 5/5] END forest_class__criterion=gini, forest_class__max_depth=7, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=0.909 total time=   0.1s\n",
      "[CV 1/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=4, forest_class__min_samples_split=10, forest_class__n_estimators=100;, score=0.913 total time=   0.1s\n",
      "[CV 2/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=4, forest_class__min_samples_split=10, forest_class__n_estimators=100;, score=1.000 total time=   0.1s\n",
      "[CV 3/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=4, forest_class__min_samples_split=10, forest_class__n_estimators=100;, score=0.955 total time=   0.1s\n",
      "[CV 4/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=4, forest_class__min_samples_split=10, forest_class__n_estimators=100;, score=0.864 total time=   0.1s\n",
      "[CV 5/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=4, forest_class__min_samples_split=10, forest_class__n_estimators=100;, score=0.909 total time=   0.1s\n",
      "[CV 1/5] END forest_class__criterion=gini, forest_class__max_depth=5, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=200;, score=0.913 total time=   0.2s\n",
      "[CV 2/5] END forest_class__criterion=gini, forest_class__max_depth=5, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=200;, score=1.000 total time=   0.2s\n",
      "[CV 3/5] END forest_class__criterion=gini, forest_class__max_depth=5, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=200;, score=0.955 total time=   0.2s\n",
      "[CV 4/5] END forest_class__criterion=gini, forest_class__max_depth=5, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=200;, score=0.864 total time=   0.2s\n",
      "[CV 5/5] END forest_class__criterion=gini, forest_class__max_depth=5, forest_class__min_samples_leaf=2, forest_class__min_samples_split=5, forest_class__n_estimators=200;, score=0.909 total time=   0.3s\n",
      "[CV 1/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=6, forest_class__min_samples_split=5, forest_class__n_estimators=200;, score=0.913 total time=   0.3s\n",
      "[CV 2/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=6, forest_class__min_samples_split=5, forest_class__n_estimators=200;, score=1.000 total time=   0.3s\n",
      "[CV 3/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=6, forest_class__min_samples_split=5, forest_class__n_estimators=200;, score=0.955 total time=   0.3s\n",
      "[CV 4/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=6, forest_class__min_samples_split=5, forest_class__n_estimators=200;, score=0.864 total time=   0.3s\n",
      "[CV 5/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=6, forest_class__min_samples_split=5, forest_class__n_estimators=200;, score=0.909 total time=   0.3s\n",
      "[CV 1/5] END forest_class__criterion=gini, forest_class__max_depth=5, forest_class__min_samples_leaf=6, forest_class__min_samples_split=15, forest_class__n_estimators=50;, score=0.913 total time=   0.1s\n",
      "[CV 2/5] END forest_class__criterion=gini, forest_class__max_depth=5, forest_class__min_samples_leaf=6, forest_class__min_samples_split=15, forest_class__n_estimators=50;, score=1.000 total time=   0.1s\n",
      "[CV 3/5] END forest_class__criterion=gini, forest_class__max_depth=5, forest_class__min_samples_leaf=6, forest_class__min_samples_split=15, forest_class__n_estimators=50;, score=1.000 total time=   0.1s\n",
      "[CV 4/5] END forest_class__criterion=gini, forest_class__max_depth=5, forest_class__min_samples_leaf=6, forest_class__min_samples_split=15, forest_class__n_estimators=50;, score=0.864 total time=   0.1s\n",
      "[CV 5/5] END forest_class__criterion=gini, forest_class__max_depth=5, forest_class__min_samples_leaf=6, forest_class__min_samples_split=15, forest_class__n_estimators=50;, score=0.909 total time=   0.1s\n",
      "[CV 1/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=6, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=0.913 total time=   0.1s\n",
      "[CV 2/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=6, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=1.000 total time=   0.2s\n",
      "[CV 3/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=6, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=0.955 total time=   0.2s\n",
      "[CV 4/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=6, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=0.864 total time=   0.2s\n",
      "[CV 5/5] END forest_class__criterion=entropy, forest_class__max_depth=3, forest_class__min_samples_leaf=6, forest_class__min_samples_split=5, forest_class__n_estimators=100;, score=0.909 total time=   0.1s\n",
      "[CV 1/5] END forest_class__criterion=entropy, forest_class__max_depth=7, forest_class__min_samples_leaf=4, forest_class__min_samples_split=5, forest_class__n_estimators=50;, score=0.913 total time=   0.1s\n",
      "[CV 2/5] END forest_class__criterion=entropy, forest_class__max_depth=7, forest_class__min_samples_leaf=4, forest_class__min_samples_split=5, forest_class__n_estimators=50;, score=1.000 total time=   0.1s\n",
      "[CV 3/5] END forest_class__criterion=entropy, forest_class__max_depth=7, forest_class__min_samples_leaf=4, forest_class__min_samples_split=5, forest_class__n_estimators=50;, score=0.955 total time=   0.1s\n",
      "[CV 4/5] END forest_class__criterion=entropy, forest_class__max_depth=7, forest_class__min_samples_leaf=4, forest_class__min_samples_split=5, forest_class__n_estimators=50;, score=0.864 total time=   0.1s\n",
      "[CV 5/5] END forest_class__criterion=entropy, forest_class__max_depth=7, forest_class__min_samples_leaf=4, forest_class__min_samples_split=5, forest_class__n_estimators=50;, score=0.909 total time=   0.1s\n",
      "\n",
      "Total Time: 8.7033 seconds\n",
      "Average Fit Time: 0.1741 seconds\n",
      "Inference Time: 0.0031\n",
      "Best CV Accuracy Score: 0.9372\n",
      "Train Accuracy Score: 0.9643\n",
      "Test Accuracy Score: 1.0000\n",
      "Overfit: No\n",
      "Overfit Difference: -0.0357\n",
      "Best Parameters: {'forest_class__n_estimators': 50, 'forest_class__min_samples_split': 15, 'forest_class__min_samples_leaf': 6, 'forest_class__max_depth': 5, 'forest_class__criterion': 'gini'}\n",
      "\n",
      "RandomForestClassifier Multi-Class Classification Report\n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "      Setosa     1.0000    1.0000    1.0000        15\n",
      "  Versicolor     1.0000    1.0000    1.0000        11\n",
      "   Virginica     1.0000    1.0000    1.0000        12\n",
      "\n",
      "    accuracy                         1.0000        38\n",
      "   macro avg     1.0000    1.0000    1.0000        38\n",
      "weighted avg     1.0000    1.0000    1.0000        38\n",
      "\n",
      "ROC AUC: 1.0\n",
      "\n",
      "Predicted   Setosa  Versicolor  Virginica\n",
      "Actual                                   \n",
      "Setosa          15           0          0\n",
      "Versicolor       0          11          0\n",
      "Virginica        0           0         12\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 450x450 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-----------------------------------------------------------------------------------------\n",
      "6/7: Starting XGBClassifier Random Search - May 30, 2024 09:22 AM UTC\n",
      "-----------------------------------------------------------------------------------------\n",
      "\n",
      "Fitting 5 folds for each of 10 candidates, totalling 50 fits\n",
      "[CV 1/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=1, xgb_class__learning_rate=0.1, xgb_class__max_depth=5, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=0.913 total time=   0.2s\n",
      "[CV 2/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=1, xgb_class__learning_rate=0.1, xgb_class__max_depth=5, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=1.000 total time=   0.3s\n",
      "[CV 3/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=1, xgb_class__learning_rate=0.1, xgb_class__max_depth=5, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=0.955 total time=   0.1s\n",
      "[CV 4/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=1, xgb_class__learning_rate=0.1, xgb_class__max_depth=5, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=0.864 total time=   0.2s\n",
      "[CV 5/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=1, xgb_class__learning_rate=0.1, xgb_class__max_depth=5, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=0.864 total time=   0.2s\n",
      "[CV 1/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=0, xgb_class__learning_rate=0.5, xgb_class__max_depth=5, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.870 total time=   0.7s\n",
      "[CV 2/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=0, xgb_class__learning_rate=0.5, xgb_class__max_depth=5, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.957 total time=   0.7s\n",
      "[CV 3/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=0, xgb_class__learning_rate=0.5, xgb_class__max_depth=5, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.955 total time=   0.6s\n",
      "[CV 4/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=0, xgb_class__learning_rate=0.5, xgb_class__max_depth=5, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.864 total time=   0.4s\n",
      "[CV 5/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=0, xgb_class__learning_rate=0.5, xgb_class__max_depth=5, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.864 total time=   0.5s\n",
      "[CV 1/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=5, xgb_class__learning_rate=0.1, xgb_class__max_depth=7, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.7;, score=0.913 total time=   0.1s\n",
      "[CV 2/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=5, xgb_class__learning_rate=0.1, xgb_class__max_depth=7, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.7;, score=1.000 total time=   0.1s\n",
      "[CV 3/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=5, xgb_class__learning_rate=0.1, xgb_class__max_depth=7, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.7;, score=0.955 total time=   0.1s\n",
      "[CV 4/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=5, xgb_class__learning_rate=0.1, xgb_class__max_depth=7, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.7;, score=0.864 total time=   0.1s\n",
      "[CV 5/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=5, xgb_class__learning_rate=0.1, xgb_class__max_depth=7, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.7;, score=0.864 total time=   0.1s\n",
      "[CV 1/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=1, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=0.957 total time=   0.4s\n",
      "[CV 2/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=1, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=1.000 total time=   0.4s\n",
      "[CV 3/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=1, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=0.955 total time=   0.4s\n",
      "[CV 4/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=1, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=0.864 total time=   0.5s\n",
      "[CV 5/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=1, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=0.864 total time=   0.4s\n",
      "[CV 1/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=10, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=0.913 total time=   0.2s\n",
      "[CV 2/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=10, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=1.000 total time=   0.2s\n",
      "[CV 3/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=10, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=0.955 total time=   0.2s\n",
      "[CV 4/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=10, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=0.864 total time=   0.1s\n",
      "[CV 5/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=10, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.9;, score=0.864 total time=   0.2s\n",
      "[CV 1/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=5, xgb_class__learning_rate=0.1, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.913 total time=   0.2s\n",
      "[CV 2/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=5, xgb_class__learning_rate=0.1, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=1.000 total time=   0.2s\n",
      "[CV 3/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=5, xgb_class__learning_rate=0.1, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.955 total time=   0.2s\n",
      "[CV 4/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=5, xgb_class__learning_rate=0.1, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.864 total time=   0.2s\n",
      "[CV 5/5] END xgb_class__colsample_bytree=0.8, xgb_class__gamma=5, xgb_class__learning_rate=0.1, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.864 total time=   0.2s\n",
      "[CV 1/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=10, xgb_class__learning_rate=0.1, xgb_class__max_depth=3, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.913 total time=   0.5s\n",
      "[CV 2/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=10, xgb_class__learning_rate=0.1, xgb_class__max_depth=3, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=1.000 total time=   0.5s\n",
      "[CV 3/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=10, xgb_class__learning_rate=0.1, xgb_class__max_depth=3, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.955 total time=   0.8s\n",
      "[CV 4/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=10, xgb_class__learning_rate=0.1, xgb_class__max_depth=3, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.864 total time=   1.0s\n",
      "[CV 5/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=10, xgb_class__learning_rate=0.1, xgb_class__max_depth=3, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.864 total time=   0.6s\n",
      "[CV 1/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=10, xgb_class__learning_rate=0.1, xgb_class__max_depth=5, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.913 total time=   0.1s\n",
      "[CV 2/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=10, xgb_class__learning_rate=0.1, xgb_class__max_depth=5, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=1.000 total time=   0.1s\n",
      "[CV 3/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=10, xgb_class__learning_rate=0.1, xgb_class__max_depth=5, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=1.000 total time=   0.1s\n",
      "[CV 4/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=10, xgb_class__learning_rate=0.1, xgb_class__max_depth=5, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.864 total time=   0.1s\n",
      "[CV 5/5] END xgb_class__colsample_bytree=0.7, xgb_class__gamma=10, xgb_class__learning_rate=0.1, xgb_class__max_depth=5, xgb_class__n_estimators=50, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.864 total time=   0.1s\n",
      "[CV 1/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=10, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.913 total time=   0.3s\n",
      "[CV 2/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=10, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=1.000 total time=   0.2s\n",
      "[CV 3/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=10, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.955 total time=   0.2s\n",
      "[CV 4/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=10, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.864 total time=   0.2s\n",
      "[CV 5/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=10, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=100, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.864 total time=   0.2s\n",
      "[CV 1/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=5, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.870 total time=   0.3s\n",
      "[CV 2/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=5, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=1.000 total time=   0.4s\n",
      "[CV 3/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=5, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=1.000 total time=   0.3s\n",
      "[CV 4/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=5, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.864 total time=   0.3s\n",
      "[CV 5/5] END xgb_class__colsample_bytree=0.9, xgb_class__gamma=5, xgb_class__learning_rate=0.5, xgb_class__max_depth=7, xgb_class__n_estimators=200, xgb_class__objective=binary:logistic, xgb_class__subsample=0.8;, score=0.864 total time=   0.4s\n",
      "\n",
      "Total Time: 15.2190 seconds\n",
      "Average Fit Time: 0.3044 seconds\n",
      "Inference Time: 0.0024\n",
      "Best CV Accuracy Score: 0.9281\n",
      "Train Accuracy Score: 0.9643\n",
      "Test Accuracy Score: 1.0000\n",
      "Overfit: No\n",
      "Overfit Difference: -0.0357\n",
      "Best Parameters: {'xgb_class__subsample': 0.8, 'xgb_class__objective': 'binary:logistic', 'xgb_class__n_estimators': 50, 'xgb_class__max_depth': 5, 'xgb_class__learning_rate': 0.1, 'xgb_class__gamma': 10, 'xgb_class__colsample_bytree': 0.7}\n",
      "\n",
      "XGBClassifier Multi-Class Classification Report\n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "      Setosa     1.0000    1.0000    1.0000        15\n",
      "  Versicolor     1.0000    1.0000    1.0000        11\n",
      "   Virginica     1.0000    1.0000    1.0000        12\n",
      "\n",
      "    accuracy                         1.0000        38\n",
      "   macro avg     1.0000    1.0000    1.0000        38\n",
      "weighted avg     1.0000    1.0000    1.0000        38\n",
      "\n",
      "ROC AUC: 1.0\n",
      "\n",
      "Predicted   Setosa  Versicolor  Virginica\n",
      "Actual                                   \n",
      "Setosa          15           0          0\n",
      "Versicolor       0          11          0\n",
      "Virginica        0           0         12\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 450x450 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-----------------------------------------------------------------------------------------\n",
      "7/7: Starting KerasClassifier Random Search - May 30, 2024 09:22 AM UTC\n",
      "-----------------------------------------------------------------------------------------\n",
      "\n",
      "Fitting 5 folds for each of 10 candidates, totalling 50 fits\n",
      "[CV 1/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=None;, score=0.696 total time=   3.3s\n",
      "[CV 2/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=None;, score=1.000 total time=   3.3s\n",
      "[CV 3/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=None;, score=0.909 total time=   3.6s\n",
      "[CV 4/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=None;, score=0.773 total time=   3.3s\n",
      "[CV 5/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=None;, score=0.682 total time=   3.2s\n",
      "[CV 1/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=25;, score=0.652 total time=   5.2s\n",
      "[CV 2/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=25;, score=1.000 total time=   9.1s\n",
      "[CV 3/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=25;, score=0.909 total time=   5.4s\n",
      "[CV 4/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=25;, score=0.773 total time=   4.0s\n",
      "[CV 5/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=25;, score=0.682 total time=   4.1s\n",
      "[CV 1/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=100, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=50;, score=0.739 total time=   3.8s\n",
      "[CV 2/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=100, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=50;, score=1.000 total time=   3.8s\n",
      "[CV 3/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=100, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=50;, score=0.909 total time=   3.7s\n",
      "[CV 4/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=100, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=50;, score=0.773 total time=   4.4s\n",
      "[CV 5/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=100, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=50;, score=0.773 total time=   3.9s\n",
      "[CV 1/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=50;, score=0.696 total time=   4.6s\n",
      "[CV 2/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=50;, score=1.000 total time=   4.7s\n",
      "[CV 3/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=50;, score=0.909 total time=   5.1s\n",
      "[CV 4/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=50;, score=0.773 total time=   4.6s\n",
      "[CV 5/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=50;, score=0.682 total time=   3.9s\n",
      "[CV 1/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=None;, score=0.739 total time=   3.4s\n",
      "[CV 2/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=None;, score=1.000 total time=   4.0s\n",
      "[CV 3/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=None;, score=0.864 total time=   3.3s\n",
      "[CV 4/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=None;, score=0.773 total time=   3.3s\n",
      "[CV 5/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=None;, score=0.682 total time=   3.4s\n",
      "[CV 1/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=25;, score=0.739 total time=   4.4s\n",
      "[CV 2/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=25;, score=1.000 total time=   4.4s\n",
      "[CV 3/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=25;, score=0.864 total time=   3.9s\n",
      "[CV 4/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=25;, score=0.773 total time=   4.2s\n",
      "[CV 5/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=25;, score=0.682 total time=   4.1s\n",
      "[CV 1/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=25;, score=0.739 total time=   3.9s\n",
      "[CV 2/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=25;, score=1.000 total time=   3.9s\n",
      "[CV 3/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=25;, score=0.909 total time=   3.8s\n",
      "[CV 4/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=25;, score=0.773 total time=   3.7s\n",
      "[CV 5/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=25;, score=0.773 total time=   3.8s\n",
      "[CV 1/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=None;, score=0.739 total time=   3.2s\n",
      "[CV 2/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=None;, score=1.000 total time=   4.2s\n",
      "[CV 3/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=None;, score=0.909 total time=   3.4s\n",
      "[CV 4/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=None;, score=0.818 total time=   4.3s\n",
      "[CV 5/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=200, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=None;, score=0.818 total time=   4.2s\n",
      "[CV 1/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=100, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=50;, score=0.739 total time=   3.8s\n",
      "[CV 2/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=100, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=50;, score=1.000 total time=   4.0s\n",
      "[CV 3/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=100, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=50;, score=0.864 total time=   3.9s\n",
      "[CV 4/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=100, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=50;, score=0.773 total time=   3.4s\n",
      "[CV 5/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=100, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=100, keras_class__third_layer_dim=50;, score=0.682 total time=   4.3s\n",
      "[CV 1/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=50;, score=0.696 total time=   3.7s\n",
      "[CV 2/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=50;, score=1.000 total time=   3.4s\n",
      "[CV 3/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=50;, score=0.909 total time=   3.4s\n",
      "[CV 4/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=50;, score=0.773 total time=   3.7s\n",
      "[CV 5/5] END keras_class__dropout_rate=0.5, keras_class__fit__batch_size=32, keras_class__hidden_layer_dim=50, keras_class__l2_reg=0.0, keras_class__loss=categorical_crossentropy, keras_class__optimizer=adam, keras_class__optimizer__learning_rate=0.001, keras_class__second_layer_dim=50, keras_class__third_layer_dim=50;, score=0.682 total time=  13.4s\n",
      "\n",
      "Total Time: 216.1515 seconds\n",
      "Average Fit Time: 4.3230 seconds\n",
      "Inference Time: 0.0748\n",
      "Best CV Accuracy Score: 0.8569\n",
      "Train Accuracy Score: 0.9554\n",
      "Test Accuracy Score: 1.0000\n",
      "Overfit: No\n",
      "Overfit Difference: -0.0446\n",
      "Best Parameters: {'keras_class__third_layer_dim': None, 'keras_class__second_layer_dim': 100, 'keras_class__optimizer__learning_rate': 0.001, 'keras_class__optimizer': 'adam', 'keras_class__loss': 'categorical_crossentropy', 'keras_class__l2_reg': 0.0, 'keras_class__hidden_layer_dim': 200, 'keras_class__fit__batch_size': 32, 'keras_class__dropout_rate': 0.5}\n",
      "\n"
     ]
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"Sequential\"</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1mModel: \"Sequential\"\u001b[0m\n"
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      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ Hidden_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">200</span>)            │         <span style=\"color: #00af00; text-decoration-color: #00af00\">1,000</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Dropout_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">200</span>)            │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Hidden_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">100</span>)            │        <span style=\"color: #00af00; text-decoration-color: #00af00\">20,100</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Dropout_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">100</span>)            │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Output (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                  │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">3</span>)              │           <span style=\"color: #00af00; text-decoration-color: #00af00\">303</span> │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ Hidden_1 (\u001b[38;5;33mDense\u001b[0m)                │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m200\u001b[0m)            │         \u001b[38;5;34m1,000\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Dropout_1 (\u001b[38;5;33mDropout\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m200\u001b[0m)            │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Hidden_2 (\u001b[38;5;33mDense\u001b[0m)                │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m100\u001b[0m)            │        \u001b[38;5;34m20,100\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Dropout_2 (\u001b[38;5;33mDropout\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m100\u001b[0m)            │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Output (\u001b[38;5;33mDense\u001b[0m)                  │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m3\u001b[0m)              │           \u001b[38;5;34m303\u001b[0m │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">64,211</span> (250.83 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m64,211\u001b[0m (250.83 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">21,403</span> (83.61 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m21,403\u001b[0m (83.61 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Optimizer params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">42,808</span> (167.22 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Optimizer params: \u001b[0m\u001b[38;5;34m42,808\u001b[0m (167.22 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "KerasClassifier Multi-Class Classification Report\n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "      Setosa     1.0000    1.0000    1.0000        15\n",
      "  Versicolor     1.0000    1.0000    1.0000        11\n",
      "   Virginica     1.0000    1.0000    1.0000        12\n",
      "\n",
      "    accuracy                         1.0000        38\n",
      "   macro avg     1.0000    1.0000    1.0000        38\n",
      "weighted avg     1.0000    1.0000    1.0000        38\n",
      "\n",
      "ROC AUC: 1.0\n",
      "\n",
      "Predicted   Setosa  Versicolor  Virginica\n",
      "Actual                                   \n",
      "Setosa          15           0          0\n",
      "Versicolor       0          11          0\n",
      "Virginica        0           0         12\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 450x450 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x550 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Evaluate multiple classification models by searching for the best hyper-parameters and comparing results\n",
    "multi_results_df = dw.compare_models(\n",
    "    \n",
    "    # Data split and sampling\n",
    "    x=X, y=y, test_size=0.25, stratify=None, under_sample=None, over_sample=None, svm_knn_resample=None,\n",
    "    \n",
    "    # Models and pipeline steps\n",
    "    imputer=None, transformers=None, scaler='stand', selector=None, svm_proba=True,\n",
    "    models=['logreg', 'knn_class', 'svm_proba', 'tree_class', 'forest_class', 'xgb_class', 'keras_class'],\n",
    "\n",
    "    # Grid search\n",
    "    search_type='random', scorer='accuracy', grid_cv='kfold_5', verbose=4,\n",
    "\n",
    "    # Model evaluation and charts\n",
    "    model_eval=True, plot_perf=True, plot_curve=True, fig_size=(12,6), legend_loc='lower left', rotation=45,\n",
    "    threshold=0.5, class_map=class_map, title='Iris',\n",
    "\n",
    "    # Config, preferences and notes\n",
    "    config=my_config, class_weight=None, random_state=42, decimal=4, n_jobs=None,\n",
    "    notes='X, Test Size=0.25, Standard Scaler, Random Grid (Accuracy), T=0.50'\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create Binary Classification Neural Network\n",
    "\n",
    "`dw.create_nn_binary()` creates a binary classification neural network model.\n",
    "\n",
    "This function allows for flexible configuration of the neural network\n",
    "structure for binary classification using the KerasClassifier in scikit-learn.\n",
    "It supports adding up to three hidden layers with customizable dimensions,\n",
    "dropout regularization, and L2 regularization.\n",
    "\n",
    "Use this function to create a neural network model with a specific structure\n",
    "and regularization settings for binary classification tasks. It is set as the `model`\n",
    "parameter of a KerasClassifier instance referenced in the configuration file\n",
    "for `dw.compare_models`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a sample classification dataset\n",
    "X, y = make_classification(n_samples=1000, n_features=10, random_state=42)\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
    "\n",
    "# Define the metadata that would be passed from KerasClassifier\n",
    "meta = {\"n_features_in_\": 10, \"X_shape_\": (80, 10)}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"Sequential\"</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1mModel: \"Sequential\"\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ Hidden_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>)             │           <span style=\"color: #00af00; text-decoration-color: #00af00\">352</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Dropout_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>)             │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Output (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                  │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">1</span>)              │            <span style=\"color: #00af00; text-decoration-color: #00af00\">33</span> │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ Hidden_1 (\u001b[38;5;33mDense\u001b[0m)                │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m)             │           \u001b[38;5;34m352\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Dropout_1 (\u001b[38;5;33mDropout\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m)             │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Output (\u001b[38;5;33mDense\u001b[0m)                  │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m)              │            \u001b[38;5;34m33\u001b[0m │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">385</span> (1.50 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m385\u001b[0m (1.50 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">385</span> (1.50 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m385\u001b[0m (1.50 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a basic neural network with default settings\n",
    "model = dw.create_nn_binary(hidden_layer_dim=32, dropout_rate=0.2, l2_reg=0.01, meta=meta)\n",
    "\n",
    "# Review the model summary\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"Sequential\"</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1mModel: \"Sequential\"\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ Hidden_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)             │           <span style=\"color: #00af00; text-decoration-color: #00af00\">704</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Dropout_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)             │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Hidden_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>)             │         <span style=\"color: #00af00; text-decoration-color: #00af00\">2,080</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Dropout_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>)             │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Hidden_3 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>)             │           <span style=\"color: #00af00; text-decoration-color: #00af00\">528</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Dropout_3 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>)             │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Output (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                  │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">1</span>)              │            <span style=\"color: #00af00; text-decoration-color: #00af00\">17</span> │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ Hidden_1 (\u001b[38;5;33mDense\u001b[0m)                │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m)             │           \u001b[38;5;34m704\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Dropout_1 (\u001b[38;5;33mDropout\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m)             │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Hidden_2 (\u001b[38;5;33mDense\u001b[0m)                │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m)             │         \u001b[38;5;34m2,080\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Dropout_2 (\u001b[38;5;33mDropout\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m)             │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Hidden_3 (\u001b[38;5;33mDense\u001b[0m)                │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m)             │           \u001b[38;5;34m528\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Dropout_3 (\u001b[38;5;33mDropout\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m)             │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Output (\u001b[38;5;33mDense\u001b[0m)                  │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m)              │            \u001b[38;5;34m17\u001b[0m │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">3,329</span> (13.00 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m3,329\u001b[0m (13.00 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">3,329</span> (13.00 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m3,329\u001b[0m (13.00 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a neural network with additional layers and regularization\n",
    "model = dw.create_nn_binary(hidden_layer_dim=64, dropout_rate=0.3, l2_reg=0.05,\n",
    "                         second_layer_dim=32, third_layer_dim=16, meta=meta)\n",
    "\n",
    "# Review the model summary\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Compile the model\n",
    "model.compile(optimizer='Adam', loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 12ms/step - accuracy: 0.5465 - loss: 4.5624 - val_accuracy: 0.7437 - val_loss: 4.0054\n",
      "Epoch 2/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.5945 - loss: 3.8493 - val_accuracy: 0.7750 - val_loss: 3.3740\n",
      "Epoch 3/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.7194 - loss: 3.2314 - val_accuracy: 0.8375 - val_loss: 2.8437\n",
      "Epoch 4/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.7780 - loss: 2.7182 - val_accuracy: 0.8375 - val_loss: 2.3995\n",
      "Epoch 5/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.8188 - loss: 2.2949 - val_accuracy: 0.8562 - val_loss: 2.0287\n",
      "Epoch 6/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8514 - loss: 1.9501 - val_accuracy: 0.8687 - val_loss: 1.7202\n",
      "Epoch 7/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 8ms/step - accuracy: 0.8587 - loss: 1.6467 - val_accuracy: 0.8750 - val_loss: 1.4680\n",
      "Epoch 8/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8490 - loss: 1.4198 - val_accuracy: 0.8750 - val_loss: 1.2664\n",
      "Epoch 9/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8605 - loss: 1.2370 - val_accuracy: 0.8750 - val_loss: 1.1052\n",
      "Epoch 10/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8466 - loss: 1.0839 - val_accuracy: 0.8687 - val_loss: 0.9770\n",
      "Epoch 11/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8831 - loss: 0.9437 - val_accuracy: 0.8687 - val_loss: 0.8743\n",
      "Epoch 12/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.8659 - loss: 0.8623 - val_accuracy: 0.8687 - val_loss: 0.7932\n",
      "Epoch 13/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8576 - loss: 0.7798 - val_accuracy: 0.8687 - val_loss: 0.7295\n",
      "Epoch 14/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8361 - loss: 0.7316 - val_accuracy: 0.8687 - val_loss: 0.6779\n",
      "Epoch 15/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8564 - loss: 0.6754 - val_accuracy: 0.8625 - val_loss: 0.6366\n",
      "Epoch 16/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8695 - loss: 0.6150 - val_accuracy: 0.8625 - val_loss: 0.6063\n",
      "Epoch 17/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.8625 - loss: 0.6024 - val_accuracy: 0.8625 - val_loss: 0.5803\n",
      "Epoch 18/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 8ms/step - accuracy: 0.8704 - loss: 0.5755 - val_accuracy: 0.8625 - val_loss: 0.5608\n",
      "Epoch 19/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8712 - loss: 0.5585 - val_accuracy: 0.8562 - val_loss: 0.5449\n",
      "Epoch 20/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8796 - loss: 0.5350 - val_accuracy: 0.8625 - val_loss: 0.5359\n",
      "Epoch 21/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.8756 - loss: 0.5094 - val_accuracy: 0.8625 - val_loss: 0.5269\n",
      "Epoch 22/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8470 - loss: 0.5304 - val_accuracy: 0.8625 - val_loss: 0.5156\n",
      "Epoch 23/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8638 - loss: 0.5149 - val_accuracy: 0.8625 - val_loss: 0.5073\n",
      "Epoch 24/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8637 - loss: 0.5026 - val_accuracy: 0.8562 - val_loss: 0.5044\n",
      "Epoch 25/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8711 - loss: 0.4832 - val_accuracy: 0.8562 - val_loss: 0.5002\n",
      "Epoch 26/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8642 - loss: 0.4935 - val_accuracy: 0.8625 - val_loss: 0.4966\n",
      "Epoch 27/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8662 - loss: 0.4689 - val_accuracy: 0.8625 - val_loss: 0.4971\n",
      "Epoch 28/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8748 - loss: 0.4767 - val_accuracy: 0.8625 - val_loss: 0.4897\n",
      "Epoch 29/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8765 - loss: 0.4768 - val_accuracy: 0.8562 - val_loss: 0.4856\n",
      "Epoch 30/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8666 - loss: 0.4752 - val_accuracy: 0.8625 - val_loss: 0.4869\n",
      "Epoch 31/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8726 - loss: 0.4772 - val_accuracy: 0.8625 - val_loss: 0.4884\n",
      "Epoch 32/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8725 - loss: 0.4773 - val_accuracy: 0.8562 - val_loss: 0.4843\n",
      "Epoch 33/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8578 - loss: 0.4773 - val_accuracy: 0.8625 - val_loss: 0.4907\n",
      "Epoch 34/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8504 - loss: 0.4856 - val_accuracy: 0.8562 - val_loss: 0.4816\n",
      "Epoch 35/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8752 - loss: 0.4727 - val_accuracy: 0.8625 - val_loss: 0.4815\n",
      "Epoch 36/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8635 - loss: 0.4765 - val_accuracy: 0.8562 - val_loss: 0.4823\n",
      "Epoch 37/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8791 - loss: 0.4622 - val_accuracy: 0.8562 - val_loss: 0.4809\n",
      "Epoch 38/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.8749 - loss: 0.4788 - val_accuracy: 0.8562 - val_loss: 0.4776\n",
      "Epoch 39/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8453 - loss: 0.4720 - val_accuracy: 0.8562 - val_loss: 0.4757\n",
      "Epoch 40/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8564 - loss: 0.4694 - val_accuracy: 0.8625 - val_loss: 0.4734\n",
      "Epoch 41/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8626 - loss: 0.4800 - val_accuracy: 0.8687 - val_loss: 0.4738\n",
      "Epoch 42/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8579 - loss: 0.4614 - val_accuracy: 0.8687 - val_loss: 0.4705\n",
      "Epoch 43/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.8517 - loss: 0.4719 - val_accuracy: 0.8687 - val_loss: 0.4742\n",
      "Epoch 44/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8601 - loss: 0.4575 - val_accuracy: 0.8687 - val_loss: 0.4764\n",
      "Epoch 45/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8484 - loss: 0.4763 - val_accuracy: 0.8625 - val_loss: 0.4745\n",
      "Epoch 46/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8657 - loss: 0.4630 - val_accuracy: 0.8562 - val_loss: 0.4699\n",
      "Epoch 47/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.8525 - loss: 0.4570 - val_accuracy: 0.8625 - val_loss: 0.4722\n",
      "Epoch 48/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8631 - loss: 0.4676 - val_accuracy: 0.8625 - val_loss: 0.4718\n",
      "Epoch 49/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.8789 - loss: 0.4570 - val_accuracy: 0.8687 - val_loss: 0.4716\n",
      "Epoch 50/50\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.8806 - loss: 0.4489 - val_accuracy: 0.8687 - val_loss: 0.4724\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.history.History at 0x7fe839f96f10>"
      ]
     },
     "execution_count": 152,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Fit the model\n",
    "model.fit(X_train, y_train, epochs=50, validation_split=0.2, shuffle=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x550 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the training history, including loss and accuracy\n",
    "dw.plot_train_history(model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create Multi-Class Classification Neural Network\n",
    "\n",
    "`dw.create_nn_multi()` creates a multi-class classification neural network model.\n",
    "\n",
    "This function allows for flexible configuration of the neural network\n",
    "structure for multi-class classification using the KerasClassifier in\n",
    "scikit-learn. It supports adding an optional hidden layer with customizable\n",
    "dimensions, dropout regularization, and L2 regularization.\n",
    "\n",
    "Use this function to create a neural network model with a specific structure\n",
    "and regularization settings for multi-class classification tasks. It is set as\n",
    "the `model` parameter of a KerasClassifier instance referenced in the\n",
    "configuration file for `dw.compare_models`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a sample classification dataset\n",
    "X, y = load_iris(return_X_y=True)\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
    "\n",
    "# Define the metadata that would be passed from KerasClassifier\n",
    "meta = {\"n_features_in_\": 4, \"X_shape_\": (120, 4), \"n_classes_\": 3}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {},
   "outputs": [],
   "source": [
    "# One-hot encode labels\n",
    "y_train = to_categorical(y_train, num_classes=3)\n",
    "y_test = to_categorical(y_test, num_classes=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"Sequential\"</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1mModel: \"Sequential\"\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ Hidden_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)             │           <span style=\"color: #00af00; text-decoration-color: #00af00\">320</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Dropout_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)             │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Output (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                  │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">3</span>)              │           <span style=\"color: #00af00; text-decoration-color: #00af00\">195</span> │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ Hidden_1 (\u001b[38;5;33mDense\u001b[0m)                │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m)             │           \u001b[38;5;34m320\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Dropout_1 (\u001b[38;5;33mDropout\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m)             │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Output (\u001b[38;5;33mDense\u001b[0m)                  │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m3\u001b[0m)              │           \u001b[38;5;34m195\u001b[0m │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">515</span> (2.01 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m515\u001b[0m (2.01 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">515</span> (2.01 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m515\u001b[0m (2.01 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a basic neural network with default settings:\n",
    "model = dw.create_nn_multi(hidden_layer_dim=64, dropout_rate=0.2, l2_reg=0.01, meta=meta)\n",
    "\n",
    "# Review the model summary\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"Sequential\"</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1mModel: \"Sequential\"\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ Hidden_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)            │           <span style=\"color: #00af00; text-decoration-color: #00af00\">640</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Dropout_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)            │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Hidden_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)             │         <span style=\"color: #00af00; text-decoration-color: #00af00\">8,256</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Dropout_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)             │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Output (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                  │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">3</span>)              │           <span style=\"color: #00af00; text-decoration-color: #00af00\">195</span> │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ Hidden_1 (\u001b[38;5;33mDense\u001b[0m)                │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m)            │           \u001b[38;5;34m640\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Dropout_1 (\u001b[38;5;33mDropout\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m)            │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Hidden_2 (\u001b[38;5;33mDense\u001b[0m)                │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m)             │         \u001b[38;5;34m8,256\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Dropout_2 (\u001b[38;5;33mDropout\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m)             │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Output (\u001b[38;5;33mDense\u001b[0m)                  │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m3\u001b[0m)              │           \u001b[38;5;34m195\u001b[0m │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">9,091</span> (35.51 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m9,091\u001b[0m (35.51 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">9,091</span> (35.51 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m9,091\u001b[0m (35.51 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a neural network with an additional hidden layer\n",
    "model = dw.create_nn_multi(hidden_layer_dim=128, dropout_rate=0.3, l2_reg=0.05,\n",
    "                        second_layer_dim=64, meta=meta)\n",
    "\n",
    "# Review the model summary\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Compile the model\n",
    "model.compile(optimizer='Adam', loss='categorical_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 123ms/step - accuracy: 0.3268 - loss: 5.9623 - val_accuracy: 0.2500 - val_loss: 5.6886\n",
      "Epoch 2/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - accuracy: 0.3359 - loss: 5.6368 - val_accuracy: 0.5000 - val_loss: 5.4026\n",
      "Epoch 3/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - accuracy: 0.4349 - loss: 5.3491 - val_accuracy: 0.5000 - val_loss: 5.1600\n",
      "Epoch 4/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - accuracy: 0.4401 - loss: 5.1631 - val_accuracy: 0.5000 - val_loss: 4.9341\n",
      "Epoch 5/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 15ms/step - accuracy: 0.4271 - loss: 4.9947 - val_accuracy: 0.5000 - val_loss: 4.7216\n",
      "Epoch 6/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - accuracy: 0.5078 - loss: 4.7129 - val_accuracy: 0.5417 - val_loss: 4.5287\n",
      "Epoch 7/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - accuracy: 0.6510 - loss: 4.5082 - val_accuracy: 0.8750 - val_loss: 4.3496\n",
      "Epoch 8/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 15ms/step - accuracy: 0.6055 - loss: 4.3775 - val_accuracy: 0.8333 - val_loss: 4.1839\n",
      "Epoch 9/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - accuracy: 0.5299 - loss: 4.2699 - val_accuracy: 0.7917 - val_loss: 4.0285\n",
      "Epoch 10/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - accuracy: 0.5833 - loss: 4.0422 - val_accuracy: 0.6667 - val_loss: 3.8753\n",
      "Epoch 11/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - accuracy: 0.6354 - loss: 3.9255 - val_accuracy: 0.7083 - val_loss: 3.7235\n",
      "Epoch 12/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - accuracy: 0.5951 - loss: 3.8146 - val_accuracy: 0.8333 - val_loss: 3.5749\n",
      "Epoch 13/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 16ms/step - accuracy: 0.6406 - loss: 3.6056 - val_accuracy: 0.9583 - val_loss: 3.4319\n",
      "Epoch 14/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 15ms/step - accuracy: 0.6875 - loss: 3.4174 - val_accuracy: 1.0000 - val_loss: 3.2955\n",
      "Epoch 15/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 14ms/step - accuracy: 0.7396 - loss: 3.3297 - val_accuracy: 1.0000 - val_loss: 3.1655\n",
      "Epoch 16/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 14ms/step - accuracy: 0.7383 - loss: 3.1917 - val_accuracy: 1.0000 - val_loss: 3.0485\n",
      "Epoch 17/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - accuracy: 0.6628 - loss: 3.0995 - val_accuracy: 1.0000 - val_loss: 2.9387\n",
      "Epoch 18/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - accuracy: 0.6576 - loss: 3.0011 - val_accuracy: 1.0000 - val_loss: 2.8313\n",
      "Epoch 19/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - accuracy: 0.8060 - loss: 2.8761 - val_accuracy: 1.0000 - val_loss: 2.7316\n",
      "Epoch 20/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - accuracy: 0.7109 - loss: 2.7606 - val_accuracy: 1.0000 - val_loss: 2.6391\n",
      "Epoch 21/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - accuracy: 0.7188 - loss: 2.7153 - val_accuracy: 1.0000 - val_loss: 2.5522\n",
      "Epoch 22/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - accuracy: 0.7604 - loss: 2.5919 - val_accuracy: 1.0000 - val_loss: 2.4675\n",
      "Epoch 23/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 14ms/step - accuracy: 0.7500 - loss: 2.5083 - val_accuracy: 1.0000 - val_loss: 2.3854\n",
      "Epoch 24/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 12ms/step - accuracy: 0.7357 - loss: 2.4210 - val_accuracy: 1.0000 - val_loss: 2.3059\n",
      "Epoch 25/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 11ms/step - accuracy: 0.7266 - loss: 2.3599 - val_accuracy: 1.0000 - val_loss: 2.2334\n",
      "Epoch 26/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 14ms/step - accuracy: 0.7148 - loss: 2.2805 - val_accuracy: 0.9583 - val_loss: 2.1639\n",
      "Epoch 27/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 16ms/step - accuracy: 0.7839 - loss: 2.2110 - val_accuracy: 0.9583 - val_loss: 2.0952\n",
      "Epoch 28/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - accuracy: 0.8125 - loss: 2.1009 - val_accuracy: 0.9583 - val_loss: 2.0300\n",
      "Epoch 29/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - accuracy: 0.8424 - loss: 2.0518 - val_accuracy: 0.9583 - val_loss: 1.9709\n",
      "Epoch 30/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - accuracy: 0.7956 - loss: 2.0167 - val_accuracy: 0.9583 - val_loss: 1.9101\n",
      "Epoch 31/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - accuracy: 0.8086 - loss: 1.9258 - val_accuracy: 0.9583 - val_loss: 1.8538\n",
      "Epoch 32/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - accuracy: 0.6927 - loss: 1.9363 - val_accuracy: 1.0000 - val_loss: 1.7921\n",
      "Epoch 33/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 16ms/step - accuracy: 0.8242 - loss: 1.8253 - val_accuracy: 1.0000 - val_loss: 1.7322\n",
      "Epoch 34/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - accuracy: 0.6276 - loss: 1.8331 - val_accuracy: 1.0000 - val_loss: 1.6782\n",
      "Epoch 35/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - accuracy: 0.7435 - loss: 1.7719 - val_accuracy: 1.0000 - val_loss: 1.6298\n",
      "Epoch 36/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - accuracy: 0.7982 - loss: 1.6800 - val_accuracy: 1.0000 - val_loss: 1.5811\n",
      "Epoch 37/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - accuracy: 0.7891 - loss: 1.6140 - val_accuracy: 1.0000 - val_loss: 1.5405\n",
      "Epoch 38/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - accuracy: 0.7096 - loss: 1.6489 - val_accuracy: 1.0000 - val_loss: 1.4983\n",
      "Epoch 39/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - accuracy: 0.8229 - loss: 1.5404 - val_accuracy: 1.0000 - val_loss: 1.4548\n",
      "Epoch 40/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step - accuracy: 0.7852 - loss: 1.5293 - val_accuracy: 1.0000 - val_loss: 1.4187\n",
      "Epoch 41/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - accuracy: 0.8372 - loss: 1.4426 - val_accuracy: 1.0000 - val_loss: 1.3853\n",
      "Epoch 42/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 14ms/step - accuracy: 0.8568 - loss: 1.3910 - val_accuracy: 1.0000 - val_loss: 1.3522\n",
      "Epoch 43/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 12ms/step - accuracy: 0.8698 - loss: 1.3877 - val_accuracy: 1.0000 - val_loss: 1.3188\n",
      "Epoch 44/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 11ms/step - accuracy: 0.7917 - loss: 1.3641 - val_accuracy: 1.0000 - val_loss: 1.2822\n",
      "Epoch 45/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 11ms/step - accuracy: 0.8411 - loss: 1.3193 - val_accuracy: 1.0000 - val_loss: 1.2456\n",
      "Epoch 46/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 16ms/step - accuracy: 0.8711 - loss: 1.2449 - val_accuracy: 1.0000 - val_loss: 1.2125\n",
      "Epoch 47/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - accuracy: 0.8177 - loss: 1.2584 - val_accuracy: 1.0000 - val_loss: 1.1836\n",
      "Epoch 48/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 15ms/step - accuracy: 0.8854 - loss: 1.2346 - val_accuracy: 1.0000 - val_loss: 1.1650\n",
      "Epoch 49/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 16ms/step - accuracy: 0.8424 - loss: 1.1907 - val_accuracy: 1.0000 - val_loss: 1.1572\n",
      "Epoch 50/50\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 16ms/step - accuracy: 0.8372 - loss: 1.1990 - val_accuracy: 0.9583 - val_loss: 1.1432\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.history.History at 0x7fe81a712b80>"
      ]
     },
     "execution_count": 159,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Fit the model\n",
    "model.fit(X_train, y_train, epochs=50, validation_split=0.2, shuffle=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x550 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the training history, including loss and accuracy\n",
    "dw.plot_train_history(model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot Training History\n",
    "\n",
    "`dw.plot_train_history()` visualizes the training history of a fitted Keras model or history dictionary.\n",
    "\n",
    "This function creates a grid of subplots to display the training and validation\n",
    "metrics over the epochs. You can pass a fitted model, in which case the history\n",
    "will be extracted from it. Alternatively, you can pass the history dictionary\n",
    "itself. This function will automatically detect the metrics present in the\n",
    "history and plot them all, unless a specific list of metrics is provided.\n",
    "The loss is plotted by default, but can be excluded by setting `plot_loss` to\n",
    "False.\n",
    "\n",
    "Use this function to quickly analyze the model's performance during training\n",
    "and identify potential issues such as overfitting or underfitting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a sample classification dataset\n",
    "X, y = make_classification(n_samples=1000, n_features=10, random_state=42)\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a simple example model\n",
    "model = Sequential([\n",
    "    Input(shape=(10,)),\n",
    "    Dense(50, activation='relu'),\n",
    "    Dense(1, activation='sigmoid')\n",
    "])\n",
    "model.compile(optimizer='adam', loss='binary_crossentropy',\n",
    "              metrics=['accuracy', 'precision', 'recall'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/20\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 27ms/step - accuracy: 0.4649 - loss: 0.7745 - precision: 0.4547 - recall: 0.4817 - val_accuracy: 0.5938 - val_loss: 0.6547 - val_precision: 0.5542 - val_recall: 0.6216\n",
      "Epoch 2/20\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.6490 - loss: 0.6451 - precision: 0.6329 - recall: 0.6617 - val_accuracy: 0.7688 - val_loss: 0.5623 - val_precision: 0.7284 - val_recall: 0.7973\n",
      "Epoch 3/20\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.7723 - loss: 0.5529 - precision: 0.7710 - recall: 0.7571 - val_accuracy: 0.8500 - val_loss: 0.5001 - val_precision: 0.8289 - val_recall: 0.8514\n",
      "Epoch 4/20\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.8266 - loss: 0.4870 - precision: 0.8244 - recall: 0.8162 - val_accuracy: 0.8687 - val_loss: 0.4574 - val_precision: 0.8630 - val_recall: 0.8514\n",
      "Epoch 5/20\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.8539 - loss: 0.4388 - precision: 0.8552 - recall: 0.8399 - val_accuracy: 0.8750 - val_loss: 0.4271 - val_precision: 0.8649 - val_recall: 0.8649\n",
      "Epoch 6/20\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8618 - loss: 0.4025 - precision: 0.8672 - recall: 0.8433 - val_accuracy: 0.8687 - val_loss: 0.4056 - val_precision: 0.8630 - val_recall: 0.8514\n",
      "Epoch 7/20\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8692 - loss: 0.3749 - precision: 0.8754 - recall: 0.8504 - val_accuracy: 0.8750 - val_loss: 0.3904 - val_precision: 0.8649 - val_recall: 0.8649\n",
      "Epoch 8/20\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.8765 - loss: 0.3541 - precision: 0.8883 - recall: 0.8507 - val_accuracy: 0.8750 - val_loss: 0.3797 - val_precision: 0.8649 - val_recall: 0.8649\n",
      "Epoch 9/20\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.8806 - loss: 0.3383 - precision: 0.8928 - recall: 0.8550 - val_accuracy: 0.8687 - val_loss: 0.3725 - val_precision: 0.8630 - val_recall: 0.8514\n",
      "Epoch 10/20\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.8806 - loss: 0.3263 - precision: 0.8928 - recall: 0.8550 - val_accuracy: 0.8687 - val_loss: 0.3677 - val_precision: 0.8630 - val_recall: 0.8514\n",
      "Epoch 11/20\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.8786 - loss: 0.3172 - precision: 0.8888 - recall: 0.8550 - val_accuracy: 0.8687 - val_loss: 0.3646 - val_precision: 0.8630 - val_recall: 0.8514\n",
      "Epoch 12/20\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8846 - loss: 0.3103 - precision: 0.8902 - recall: 0.8674 - val_accuracy: 0.8750 - val_loss: 0.3626 - val_precision: 0.8750 - val_recall: 0.8514\n",
      "Epoch 13/20\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8846 - loss: 0.3049 - precision: 0.8902 - recall: 0.8674 - val_accuracy: 0.8687 - val_loss: 0.3614 - val_precision: 0.8630 - val_recall: 0.8514\n",
      "Epoch 14/20\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.8846 - loss: 0.3006 - precision: 0.8902 - recall: 0.8674 - val_accuracy: 0.8625 - val_loss: 0.3607 - val_precision: 0.8514 - val_recall: 0.8514\n",
      "Epoch 15/20\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8825 - loss: 0.2970 - precision: 0.8897 - recall: 0.8631 - val_accuracy: 0.8625 - val_loss: 0.3603 - val_precision: 0.8514 - val_recall: 0.8514\n",
      "Epoch 16/20\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8846 - loss: 0.2941 - precision: 0.8902 - recall: 0.8674 - val_accuracy: 0.8625 - val_loss: 0.3602 - val_precision: 0.8514 - val_recall: 0.8514\n",
      "Epoch 17/20\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8851 - loss: 0.2918 - precision: 0.8888 - recall: 0.8703 - val_accuracy: 0.8625 - val_loss: 0.3602 - val_precision: 0.8514 - val_recall: 0.8514\n",
      "Epoch 18/20\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8830 - loss: 0.2897 - precision: 0.8883 - recall: 0.8660 - val_accuracy: 0.8625 - val_loss: 0.3603 - val_precision: 0.8514 - val_recall: 0.8514\n",
      "Epoch 19/20\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8878 - loss: 0.2879 - precision: 0.8895 - recall: 0.8759 - val_accuracy: 0.8625 - val_loss: 0.3603 - val_precision: 0.8514 - val_recall: 0.8514\n",
      "Epoch 20/20\n",
      "\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.8898 - loss: 0.2862 - precision: 0.8900 - recall: 0.8802 - val_accuracy: 0.8625 - val_loss: 0.3603 - val_precision: 0.8514 - val_recall: 0.8514\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.history.History at 0x7fe808b6d220>"
      ]
     },
     "execution_count": 163,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Fit the model\n",
    "model.fit(X_train, y_train, epochs=20, batch_size=32, validation_split=0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Capture the history\n",
    "history = model.history.history"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1100 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot all metrics in the training history from a model\n",
    "dw.plot_train_history(model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x1100 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the training history with specific metrics:\n",
    "dw.plot_train_history(model, metrics=['accuracy', 'precision'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1100 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the training history without the loss\n",
    "dw.plot_train_history(model, plot_loss=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a another example model\n",
    "model = Sequential([\n",
    "    Input(shape=(10,)),\n",
    "    Dense(50, activation='relu'),\n",
    "    Dense(1, activation='sigmoid')\n",
    "])\n",
    "model.compile(optimizer='adam', loss='binary_crossentropy',\n",
    "              metrics=['accuracy', 'precision', 'recall'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/20\n",
      "\u001b[1m25/25\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - accuracy: 0.5177 - loss: 0.7998 - precision: 0.2197 - recall: 0.0046        \n",
      "Epoch 2/20\n",
      "\u001b[1m25/25\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.5973 - loss: 0.6481 - precision: 0.9273 - recall: 0.1659 \n",
      "Epoch 3/20\n",
      "\u001b[1m25/25\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.7325 - loss: 0.5456 - precision: 0.8916 - recall: 0.4907 \n",
      "Epoch 4/20\n",
      "\u001b[1m25/25\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8453 - loss: 0.4716 - precision: 0.9095 - recall: 0.7479 \n",
      "Epoch 5/20\n",
      "\u001b[1m25/25\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8611 - loss: 0.4171 - precision: 0.8964 - recall: 0.7975 \n",
      "Epoch 6/20\n",
      "\u001b[1m25/25\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8779 - loss: 0.3775 - precision: 0.8985 - recall: 0.8344 \n",
      "Epoch 7/20\n",
      "\u001b[1m25/25\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8825 - loss: 0.3491 - precision: 0.8897 - recall: 0.8544 \n",
      "Epoch 8/20\n",
      "\u001b[1m25/25\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8892 - loss: 0.3290 - precision: 0.8866 - recall: 0.8737 \n",
      "Epoch 9/20\n",
      "\u001b[1m25/25\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8875 - loss: 0.3148 - precision: 0.8822 - recall: 0.8751 \n",
      "Epoch 10/20\n",
      "\u001b[1m25/25\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8899 - loss: 0.3045 - precision: 0.8789 - recall: 0.8851 \n",
      "Epoch 11/20\n",
      "\u001b[1m25/25\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8892 - loss: 0.2970 - precision: 0.8767 - recall: 0.8864 \n",
      "Epoch 12/20\n",
      "\u001b[1m25/25\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8884 - loss: 0.2913 - precision: 0.8754 - recall: 0.8864 \n",
      "Epoch 13/20\n",
      "\u001b[1m25/25\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8879 - loss: 0.2869 - precision: 0.8746 - recall: 0.8861 \n",
      "Epoch 14/20\n",
      "\u001b[1m25/25\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8879 - loss: 0.2833 - precision: 0.8746 - recall: 0.8861 \n",
      "Epoch 15/20\n",
      "\u001b[1m25/25\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8879 - loss: 0.2802 - precision: 0.8746 - recall: 0.8861 \n",
      "Epoch 16/20\n",
      "\u001b[1m25/25\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8879 - loss: 0.2776 - precision: 0.8746 - recall: 0.8861 \n",
      "Epoch 17/20\n",
      "\u001b[1m25/25\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8879 - loss: 0.2753 - precision: 0.8746 - recall: 0.8861 \n",
      "Epoch 18/20\n",
      "\u001b[1m25/25\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8878 - loss: 0.2732 - precision: 0.8745 - recall: 0.8861 \n",
      "Epoch 19/20\n",
      "\u001b[1m25/25\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8878 - loss: 0.2713 - precision: 0.8745 - recall: 0.8861 \n",
      "Epoch 20/20\n",
      "\u001b[1m25/25\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8878 - loss: 0.2695 - precision: 0.8745 - recall: 0.8861 \n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.history.History at 0x7fe809179f10>"
      ]
     },
     "execution_count": 169,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Fit a model without specifying validation\n",
    "model.fit(X_train, y_train, epochs=20, batch_size=32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1100 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot a model that doesn't have validation data\n",
    "dw.plot_train_history(model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1100 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the training history from a history dictionary\n",
    "dw.plot_train_history(history=history)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "## Tools\n",
    "\n",
    "The `dw.tools` module provides helper tools used in data analysis, cleaning, and modeling.\n",
    "This module provides helper tools used in data analysis, cleaning, and modeling.\n",
    "It contains functions to check for duplicates in lists, split a dataframe into\n",
    "by numeric vs. categorical variables, and format numbers on the axis of a chart.\n",
    "\n",
    "* [Log Transform](#Log-Transform) - *log_transform()*\n",
    "* [Check for Duplicates](#Check-for-Duplicates) - *check_for_duplicates()*\n",
    "* [Split Dataframe](#Split-Dataframe) - *split_dataframe()*\n",
    "* [Format Dataframe](#Format-Dataframe) - *format_df()*\n",
    "* [Format Chart Axis as Dollars](#Format-Chart-Axis-as-Dollars) - *dollars()*\n",
    "* [Format Chart Axis as Thousands](#Format-Chart-Axis-as-Thousands) - *thousands()*\n",
    "* [Calculate VIF](#Calculate-VIF) - *calc_vif()*\n",
    "* [Calculate PFI](#Calculate-PFI) - *calc_pfi()*\n",
    "* [Extract Coefficients](#Extract-Coefficients) - *extract_coef()*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Log Transform\n",
    "\n",
    "`dw.log_transform()` applies a log transformation to specified columns in a DataFrame.\n",
    "\n",
    "This function applies a log transformation (base e) to the specified\n",
    "columns of the input DataFrame. The log-transformed columns are\n",
    "appended to the DataFrame with the suffix '_log'. If a column\n",
    "contains a negative value, a log transformation is not possible. In this\n",
    "case, a warning message will be printed, and the function will continue\n",
    "and try to transform additional columns.\n",
    "\n",
    "Use this function when you need to log-transform skewed columns in\n",
    "a DataFrame to approximate a more normal distribution for modeling."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot histograms of skewed variables, dimensioned by the target variable\n",
    "dw.plot_charts(df, plot_type='cont', cont_cols=skew_columns, hue='y', multiple='stack')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Specify columns that have a skewed shape\n",
    "skew_columns = ['duration']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Log transform the specified columns in a dataframe\n",
    "df_log = dw.log_transform(df, columns=skew_columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 41188 entries, 0 to 41187\n",
      "Data columns (total 22 columns):\n",
      " #   Column          Non-Null Count  Dtype   \n",
      "---  ------          --------------  -----   \n",
      " 0   age             41188 non-null  float64 \n",
      " 1   job             41188 non-null  category\n",
      " 2   marital         41188 non-null  category\n",
      " 3   education       41188 non-null  category\n",
      " 4   default         41188 non-null  category\n",
      " 5   housing         41188 non-null  category\n",
      " 6   loan            41188 non-null  category\n",
      " 7   contact         41188 non-null  category\n",
      " 8   month           41188 non-null  category\n",
      " 9   day_of_week     41188 non-null  category\n",
      " 10  duration        41188 non-null  float64 \n",
      " 11  campaign        41188 non-null  float64 \n",
      " 12  pdays           41188 non-null  float64 \n",
      " 13  previous        41188 non-null  float64 \n",
      " 14  poutcome        41188 non-null  category\n",
      " 15  emp.var.rate    41188 non-null  float64 \n",
      " 16  cons.price.idx  41188 non-null  float64 \n",
      " 17  cons.conf.idx   41188 non-null  float64 \n",
      " 18  euribor3m       41188 non-null  float64 \n",
      " 19  nr.employed     41188 non-null  float64 \n",
      " 20  y               41188 non-null  category\n",
      " 21  duration_log    41188 non-null  float64 \n",
      "dtypes: category(11), float64(11)\n",
      "memory usage: 3.9 MB\n"
     ]
    }
   ],
   "source": [
    "# Notice the new column added with the _log suffix\n",
    "df_log.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot histograms of the log transformed variables, dimensioned by the target variable\n",
    "dw.plot_charts(df_log, plot_type='cont', cont_cols=['duration_log'], hue='y', multiple='stack')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div style=\"background-color: #e8f3ff; border: 1px solid #aecae8; padding: 10px; border-radius: 3px;\">\n",
    "    <b>Note:</b> You can also get this chart by just specifying the `log_scale=True` parameter in `dw.plot_charts`. But that does not save the log transformed data. So you have two options. If you want to transform the data for modeling, you would need to use `dw.log_transform`. But if you just want to evaluate if a log transformation would approximate a normal distribution, you can use `dw.plot_charts` with the `log_scale=True` parameter.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Example plot showing dw.plot_charts with log_scale=True\n",
    "dw.plot_charts(df, plot_type='cont', cont_cols=skew_columns, hue='y', multiple='stack', log_scale=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Check for Duplicates\n",
    "\n",
    "`dw.check_for_duplicates()` checks for duplicate items (ex: column names) across multiple lists.\n",
    "\n",
    "This function takes an arbitrary number of lists and checks for duplicate items\n",
    "across the lists, as well as items appearing more than once within each list.\n",
    "It prints a summary of the items and the lists they appear in. Additionally, if\n",
    "a DataFrame is provided, it checks for any columns in the DataFrame that are\n",
    "missing from the lists and prints them.\n",
    "\n",
    "Use this function when you are organizing columns in a large DataFrame into\n",
    "lists that represent their variable type (ex: num_columns, cat_columns). This\n",
    "helps to ensure you haven't duplicated a column accidentally. And the optional\n",
    "DataFrame check helps you identify columns that haven't been assigned to a list\n",
    "yet. This is really useful when you're dealing with a large dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>job</th>\n",
       "      <th>marital</th>\n",
       "      <th>education</th>\n",
       "      <th>default</th>\n",
       "      <th>housing</th>\n",
       "      <th>loan</th>\n",
       "      <th>contact</th>\n",
       "      <th>month</th>\n",
       "      <th>day_of_week</th>\n",
       "      <th>duration</th>\n",
       "      <th>campaign</th>\n",
       "      <th>pdays</th>\n",
       "      <th>previous</th>\n",
       "      <th>poutcome</th>\n",
       "      <th>emp.var.rate</th>\n",
       "      <th>cons.price.idx</th>\n",
       "      <th>cons.conf.idx</th>\n",
       "      <th>euribor3m</th>\n",
       "      <th>nr.employed</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>56.0</td>\n",
       "      <td>housemaid</td>\n",
       "      <td>married</td>\n",
       "      <td>basic.4y</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>261.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>999.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>1.1</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "      <td>5191.0</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>57.0</td>\n",
       "      <td>services</td>\n",
       "      <td>married</td>\n",
       "      <td>high.school</td>\n",
       "      <td>unknown</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>149.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>999.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>1.1</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "      <td>5191.0</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>37.0</td>\n",
       "      <td>services</td>\n",
       "      <td>married</td>\n",
       "      <td>high.school</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>226.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>999.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>1.1</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "      <td>5191.0</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>40.0</td>\n",
       "      <td>admin.</td>\n",
       "      <td>married</td>\n",
       "      <td>basic.6y</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>151.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>999.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>1.1</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "      <td>5191.0</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>56.0</td>\n",
       "      <td>services</td>\n",
       "      <td>married</td>\n",
       "      <td>high.school</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>307.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>999.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>1.1</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "      <td>5191.0</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    age        job  marital    education  default housing loan    contact month day_of_week  duration  campaign  pdays  previous     poutcome  emp.var.rate  cons.price.idx  cons.conf.idx  euribor3m  nr.employed   y\n",
       "0  56.0  housemaid  married     basic.4y       no      no   no  telephone   may         mon     261.0       1.0  999.0       0.0  nonexistent           1.1          93.994          -36.4      4.857       5191.0  no\n",
       "1  57.0   services  married  high.school  unknown      no   no  telephone   may         mon     149.0       1.0  999.0       0.0  nonexistent           1.1          93.994          -36.4      4.857       5191.0  no\n",
       "2  37.0   services  married  high.school       no     yes   no  telephone   may         mon     226.0       1.0  999.0       0.0  nonexistent           1.1          93.994          -36.4      4.857       5191.0  no\n",
       "3  40.0     admin.  married     basic.6y       no      no   no  telephone   may         mon     151.0       1.0  999.0       0.0  nonexistent           1.1          93.994          -36.4      4.857       5191.0  no\n",
       "4  56.0   services  married  high.school       no      no  yes  telephone   may         mon     307.0       1.0  999.0       0.0  nonexistent           1.1          93.994          -36.4      4.857       5191.0  no"
      ]
     },
     "execution_count": 178,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Scan the data we have in the dataframe\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 41188 entries, 0 to 41187\n",
      "Data columns (total 21 columns):\n",
      " #   Column          Non-Null Count  Dtype   \n",
      "---  ------          --------------  -----   \n",
      " 0   age             41188 non-null  float64 \n",
      " 1   job             41188 non-null  category\n",
      " 2   marital         41188 non-null  category\n",
      " 3   education       41188 non-null  category\n",
      " 4   default         41188 non-null  category\n",
      " 5   housing         41188 non-null  category\n",
      " 6   loan            41188 non-null  category\n",
      " 7   contact         41188 non-null  category\n",
      " 8   month           41188 non-null  category\n",
      " 9   day_of_week     41188 non-null  category\n",
      " 10  duration        41188 non-null  float64 \n",
      " 11  campaign        41188 non-null  float64 \n",
      " 12  pdays           41188 non-null  float64 \n",
      " 13  previous        41188 non-null  float64 \n",
      " 14  poutcome        41188 non-null  category\n",
      " 15  emp.var.rate    41188 non-null  float64 \n",
      " 16  cons.price.idx  41188 non-null  float64 \n",
      " 17  cons.conf.idx   41188 non-null  float64 \n",
      " 18  euribor3m       41188 non-null  float64 \n",
      " 19  nr.employed     41188 non-null  float64 \n",
      " 20  y               41188 non-null  category\n",
      "dtypes: category(11), float64(10)\n",
      "memory usage: 3.6 MB\n"
     ]
    }
   ],
   "source": [
    "# Review the dtypes\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "age                 78\n",
       "job                 12\n",
       "marital              4\n",
       "education            8\n",
       "default              3\n",
       "housing              3\n",
       "loan                 3\n",
       "contact              2\n",
       "month               10\n",
       "day_of_week          5\n",
       "duration          1544\n",
       "campaign            42\n",
       "pdays               27\n",
       "previous             8\n",
       "poutcome             3\n",
       "emp.var.rate        10\n",
       "cons.price.idx      26\n",
       "cons.conf.idx       26\n",
       "euribor3m          316\n",
       "nr.employed         11\n",
       "y                    2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 180,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the number of unique values in each column\n",
    "df.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create column lists based on what we've learned for various variable types\n",
    "cat_columns = ['job', 'marital', 'education', 'default', 'housing', 'loan', 'contact', 'month', 'day_of_week', 'previous', 'poutcome', 'y', 'y']\n",
    "num_columns = ['age', 'duration', 'pdays', 'previous', 'emp.var.rate', 'cons.price.idx', 'cons.conf.idx', 'euribor3m', 'nr.employed']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Items appearing in more than one list, or more than once per list:\n",
      "previous (2): cat_columns, num_columns\n",
      "y (2): cat_columns, cat_columns\n"
     ]
    }
   ],
   "source": [
    "# Check for duplicate column names in the lists, since they were created manually\n",
    "dw.check_for_duplicates(cat_columns, num_columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fix the duplicates\n",
    "cat_columns = ['job', 'marital', 'education', 'default', 'housing', 'loan', 'contact', 'month', 'day_of_week', 'poutcome', 'y']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Items appearing in more than one list, or more than once per list:\n",
      "None.\n",
      "\n",
      "Columns in the dataframe missing from the lists:\n",
      "campaign\n"
     ]
    }
   ],
   "source": [
    "# Re-check duplicates, and also see if we missed any columns in the dataframe\n",
    "dw.check_for_duplicates(cat_columns, num_columns, df=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add the missing column to a list\n",
    "num_columns.append('campaign')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Items appearing in more than one list, or more than once per list:\n",
      "None.\n",
      "\n",
      "Columns in the dataframe missing from the lists:\n",
      "None.\n"
     ]
    }
   ],
   "source": [
    "# Final re-check\n",
    "dw.check_for_duplicates(cat_columns, num_columns, df=df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Split Dataframe\n",
    "\n",
    "`dw.split_dataframe()` splits a DataFrame into categorical and numerical columns.\n",
    "\n",
    "This function splits the input DataFrame into two separate DataFrames based on\n",
    "the number of unique values in each column. Columns with `n` or fewer unique\n",
    "values are considered categorical and are placed in `df_cat`, while columns\n",
    "with more than `n` unique values are considered numerical and are placed in\n",
    "`df_num`.\n",
    "\n",
    "Use this function when you need to separate categorical and numerical columns\n",
    "in a DataFrame for further analysis or processing."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Split a dataframe in two, with unique values of 12 or less going into df_cat, the rest going into df_num\n",
    "df_cat, df_num = dw.split_dataframe(df, n=12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>job</th>\n",
       "      <th>marital</th>\n",
       "      <th>education</th>\n",
       "      <th>default</th>\n",
       "      <th>housing</th>\n",
       "      <th>loan</th>\n",
       "      <th>contact</th>\n",
       "      <th>month</th>\n",
       "      <th>day_of_week</th>\n",
       "      <th>previous</th>\n",
       "      <th>poutcome</th>\n",
       "      <th>emp.var.rate</th>\n",
       "      <th>nr.employed</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>housemaid</td>\n",
       "      <td>married</td>\n",
       "      <td>basic.4y</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>0.0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>1.1</td>\n",
       "      <td>5191.0</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>services</td>\n",
       "      <td>married</td>\n",
       "      <td>high.school</td>\n",
       "      <td>unknown</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>0.0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>1.1</td>\n",
       "      <td>5191.0</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>services</td>\n",
       "      <td>married</td>\n",
       "      <td>high.school</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>0.0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>1.1</td>\n",
       "      <td>5191.0</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>admin.</td>\n",
       "      <td>married</td>\n",
       "      <td>basic.6y</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>0.0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>1.1</td>\n",
       "      <td>5191.0</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>services</td>\n",
       "      <td>married</td>\n",
       "      <td>high.school</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>0.0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>1.1</td>\n",
       "      <td>5191.0</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         job  marital    education  default housing loan    contact month day_of_week  previous     poutcome  emp.var.rate  nr.employed   y\n",
       "0  housemaid  married     basic.4y       no      no   no  telephone   may         mon       0.0  nonexistent           1.1       5191.0  no\n",
       "1   services  married  high.school  unknown      no   no  telephone   may         mon       0.0  nonexistent           1.1       5191.0  no\n",
       "2   services  married  high.school       no     yes   no  telephone   may         mon       0.0  nonexistent           1.1       5191.0  no\n",
       "3     admin.  married     basic.6y       no      no   no  telephone   may         mon       0.0  nonexistent           1.1       5191.0  no\n",
       "4   services  married  high.school       no      no  yes  telephone   may         mon       0.0  nonexistent           1.1       5191.0  no"
      ]
     },
     "execution_count": 188,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the categorical dataframe, which we can see is not a perfect split\n",
    "df_cat.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>duration</th>\n",
       "      <th>campaign</th>\n",
       "      <th>pdays</th>\n",
       "      <th>cons.price.idx</th>\n",
       "      <th>cons.conf.idx</th>\n",
       "      <th>euribor3m</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>56.0</td>\n",
       "      <td>261.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>999.0</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>57.0</td>\n",
       "      <td>149.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>999.0</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>37.0</td>\n",
       "      <td>226.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>999.0</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>40.0</td>\n",
       "      <td>151.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>999.0</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>56.0</td>\n",
       "      <td>307.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>999.0</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    age  duration  campaign  pdays  cons.price.idx  cons.conf.idx  euribor3m\n",
       "0  56.0     261.0       1.0  999.0          93.994          -36.4      4.857\n",
       "1  57.0     149.0       1.0  999.0          93.994          -36.4      4.857\n",
       "2  37.0     226.0       1.0  999.0          93.994          -36.4      4.857\n",
       "3  40.0     151.0       1.0  999.0          93.994          -36.4      4.857\n",
       "4  56.0     307.0       1.0  999.0          93.994          -36.4      4.857"
      ]
     },
     "execution_count": 189,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the numeric dataframe\n",
    "df_num.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div style=\"background-color: #e8f3ff; border: 1px solid #aecae8; padding: 10px; border-radius: 3px;\">\n",
    "    <b>Observation:</b> Sometimes there's not a clear line, based on the unique value counts, that can be used to separate the categorical vs. numeric features. In practice, I don't often split the dataframe, but just create lists of columns and then pass df[num_columns] or df[cat_columns].\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Format Dataframe\n",
    "\n",
    "`dw.format_dataframe()` formats columns of a DataFrame as either large or small numbers.\n",
    "\n",
    "This function formats the specified columns in the input DataFrame.\n",
    "Large numbers are formatted with commas as thousands separators, and\n",
    "small numbers are formatted with a specified number of decimal places.\n",
    "Use `decimal` to define how many decimal places to display.\n",
    "\n",
    "Use this function when you need to format specific columns in a\n",
    "DataFrame for better readability or presentation purposes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load a dataframe that has a mix of a large and small numbers\n",
    "results_df = pd.read_csv('data/results_df.csv', index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Iteration</th>\n",
       "      <th>Train MSE</th>\n",
       "      <th>Test MSE</th>\n",
       "      <th>Train RMSE</th>\n",
       "      <th>Test RMSE</th>\n",
       "      <th>Train MAE</th>\n",
       "      <th>Test MAE</th>\n",
       "      <th>Train R^2 Score</th>\n",
       "      <th>Test R^2 Score</th>\n",
       "      <th>Pipeline</th>\n",
       "      <th>Note</th>\n",
       "      <th>Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>3.588930e+09</td>\n",
       "      <td>3.561885e+09</td>\n",
       "      <td>59907.682665</td>\n",
       "      <td>59681.527129</td>\n",
       "      <td>44454.606285</td>\n",
       "      <td>44197.778286</td>\n",
       "      <td>0.606782</td>\n",
       "      <td>0.616300</td>\n",
       "      <td>Model: linreg</td>\n",
       "      <td>No outliers. Drop ocean_proximity. LinReg</td>\n",
       "      <td>Aug 07, 2023 02:38 AM PST</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>3.449797e+09</td>\n",
       "      <td>3.409325e+09</td>\n",
       "      <td>58734.974249</td>\n",
       "      <td>58389.423619</td>\n",
       "      <td>43054.713459</td>\n",
       "      <td>42812.841927</td>\n",
       "      <td>0.622026</td>\n",
       "      <td>0.632734</td>\n",
       "      <td>transformer_ohe -&gt; Model: linreg</td>\n",
       "      <td>No outliers. OHE. LinReg</td>\n",
       "      <td>Aug 07, 2023 02:40 AM PST</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2.924153e+09</td>\n",
       "      <td>2.832674e+09</td>\n",
       "      <td>54075.438033</td>\n",
       "      <td>53222.870883</td>\n",
       "      <td>38868.694712</td>\n",
       "      <td>38094.346879</td>\n",
       "      <td>0.679617</td>\n",
       "      <td>0.694853</td>\n",
       "      <td>Transformer: ohe_poly2 -&gt; Model: linreg</td>\n",
       "      <td>No outliers. OHE. Poly 2. LinReg</td>\n",
       "      <td>Aug 07, 2023 02:42 AM PST</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2.645702e+09</td>\n",
       "      <td>2.821643e+09</td>\n",
       "      <td>51436.387928</td>\n",
       "      <td>53119.139273</td>\n",
       "      <td>36930.866995</td>\n",
       "      <td>37336.066047</td>\n",
       "      <td>0.710126</td>\n",
       "      <td>0.696042</td>\n",
       "      <td>Transformer: ohe_poly3 -&gt; Model: linreg</td>\n",
       "      <td>No outliers. OHE. Poly 3. LinReg</td>\n",
       "      <td>Aug 07, 2023 02:44 AM PST</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2.984159e+09</td>\n",
       "      <td>2.895566e+09</td>\n",
       "      <td>54627.455531</td>\n",
       "      <td>53810.461446</td>\n",
       "      <td>39389.146063</td>\n",
       "      <td>38716.775476</td>\n",
       "      <td>0.673043</td>\n",
       "      <td>0.688078</td>\n",
       "      <td>Transformer: ord_poly2 -&gt; Model: linreg</td>\n",
       "      <td>No outliers. Ordinal. Poly 2. LinReg</td>\n",
       "      <td>Aug 07, 2023 02:46 AM PST</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Iteration     Train MSE      Test MSE    Train RMSE     Test RMSE     Train MAE      Test MAE  Train R^2 Score  Test R^2 Score                                 Pipeline                                       Note                       Date\n",
       "0          1  3.588930e+09  3.561885e+09  59907.682665  59681.527129  44454.606285  44197.778286         0.606782        0.616300                            Model: linreg  No outliers. Drop ocean_proximity. LinReg  Aug 07, 2023 02:38 AM PST\n",
       "1          2  3.449797e+09  3.409325e+09  58734.974249  58389.423619  43054.713459  42812.841927         0.622026        0.632734         transformer_ohe -> Model: linreg                   No outliers. OHE. LinReg  Aug 07, 2023 02:40 AM PST\n",
       "2          3  2.924153e+09  2.832674e+09  54075.438033  53222.870883  38868.694712  38094.346879         0.679617        0.694853  Transformer: ohe_poly2 -> Model: linreg           No outliers. OHE. Poly 2. LinReg  Aug 07, 2023 02:42 AM PST\n",
       "3          4  2.645702e+09  2.821643e+09  51436.387928  53119.139273  36930.866995  37336.066047         0.710126        0.696042  Transformer: ohe_poly3 -> Model: linreg           No outliers. OHE. Poly 3. LinReg  Aug 07, 2023 02:44 AM PST\n",
       "4          5  2.984159e+09  2.895566e+09  54627.455531  53810.461446  39389.146063  38716.775476         0.673043        0.688078  Transformer: ord_poly2 -> Model: linreg       No outliers. Ordinal. Poly 2. LinReg  Aug 07, 2023 02:46 AM PST"
      ]
     },
     "execution_count": 191,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Preview the data, note the large numbers with scientific notation, and small numbers with long decimals\n",
    "results_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a formatted dataframe for better readability only - not for data analysis\n",
    "formatted_df = dw.format_df(results_df,\n",
    "                            large_num_cols=['Train MSE', 'Test MSE', 'Train RMSE', 'Test RMSE', 'Train MAE', 'Test MAE'],\n",
    "                            small_num_cols=['Train R^2 Score', 'Test R^2 Score'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Iteration</th>\n",
       "      <th>Train MSE</th>\n",
       "      <th>Test MSE</th>\n",
       "      <th>Train RMSE</th>\n",
       "      <th>Test RMSE</th>\n",
       "      <th>Train MAE</th>\n",
       "      <th>Test MAE</th>\n",
       "      <th>Train R^2 Score</th>\n",
       "      <th>Test R^2 Score</th>\n",
       "      <th>Pipeline</th>\n",
       "      <th>Note</th>\n",
       "      <th>Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>3,588,930,442</td>\n",
       "      <td>3,561,884,680</td>\n",
       "      <td>59,908</td>\n",
       "      <td>59,682</td>\n",
       "      <td>44,455</td>\n",
       "      <td>44,198</td>\n",
       "      <td>0.61</td>\n",
       "      <td>0.62</td>\n",
       "      <td>Model: linreg</td>\n",
       "      <td>No outliers. Drop ocean_proximity. LinReg</td>\n",
       "      <td>Aug 07, 2023 02:38 AM PST</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>3,449,797,200</td>\n",
       "      <td>3,409,324,791</td>\n",
       "      <td>58,735</td>\n",
       "      <td>58,389</td>\n",
       "      <td>43,055</td>\n",
       "      <td>42,813</td>\n",
       "      <td>0.62</td>\n",
       "      <td>0.63</td>\n",
       "      <td>transformer_ohe -&gt; Model: linreg</td>\n",
       "      <td>No outliers. OHE. LinReg</td>\n",
       "      <td>Aug 07, 2023 02:40 AM PST</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2,924,152,998</td>\n",
       "      <td>2,832,673,985</td>\n",
       "      <td>54,075</td>\n",
       "      <td>53,223</td>\n",
       "      <td>38,869</td>\n",
       "      <td>38,094</td>\n",
       "      <td>0.68</td>\n",
       "      <td>0.69</td>\n",
       "      <td>Transformer: ohe_poly2 -&gt; Model: linreg</td>\n",
       "      <td>No outliers. OHE. Poly 2. LinReg</td>\n",
       "      <td>Aug 07, 2023 02:42 AM PST</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2,645,702,003</td>\n",
       "      <td>2,821,642,957</td>\n",
       "      <td>51,436</td>\n",
       "      <td>53,119</td>\n",
       "      <td>36,931</td>\n",
       "      <td>37,336</td>\n",
       "      <td>0.71</td>\n",
       "      <td>0.70</td>\n",
       "      <td>Transformer: ohe_poly3 -&gt; Model: linreg</td>\n",
       "      <td>No outliers. OHE. Poly 3. LinReg</td>\n",
       "      <td>Aug 07, 2023 02:44 AM PST</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2,984,158,898</td>\n",
       "      <td>2,895,565,761</td>\n",
       "      <td>54,627</td>\n",
       "      <td>53,810</td>\n",
       "      <td>39,389</td>\n",
       "      <td>38,717</td>\n",
       "      <td>0.67</td>\n",
       "      <td>0.69</td>\n",
       "      <td>Transformer: ord_poly2 -&gt; Model: linreg</td>\n",
       "      <td>No outliers. Ordinal. Poly 2. LinReg</td>\n",
       "      <td>Aug 07, 2023 02:46 AM PST</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Iteration      Train MSE       Test MSE Train RMSE Test RMSE Train MAE Test MAE Train R^2 Score Test R^2 Score                                 Pipeline                                       Note                       Date\n",
       "0          1  3,588,930,442  3,561,884,680     59,908    59,682    44,455   44,198            0.61           0.62                            Model: linreg  No outliers. Drop ocean_proximity. LinReg  Aug 07, 2023 02:38 AM PST\n",
       "1          2  3,449,797,200  3,409,324,791     58,735    58,389    43,055   42,813            0.62           0.63         transformer_ohe -> Model: linreg                   No outliers. OHE. LinReg  Aug 07, 2023 02:40 AM PST\n",
       "2          3  2,924,152,998  2,832,673,985     54,075    53,223    38,869   38,094            0.68           0.69  Transformer: ohe_poly2 -> Model: linreg           No outliers. OHE. Poly 2. LinReg  Aug 07, 2023 02:42 AM PST\n",
       "3          4  2,645,702,003  2,821,642,957     51,436    53,119    36,931   37,336            0.71           0.70  Transformer: ohe_poly3 -> Model: linreg           No outliers. OHE. Poly 3. LinReg  Aug 07, 2023 02:44 AM PST\n",
       "4          5  2,984,158,898  2,895,565,761     54,627    53,810    39,389   38,717            0.67           0.69  Transformer: ord_poly2 -> Model: linreg       No outliers. Ordinal. Poly 2. LinReg  Aug 07, 2023 02:46 AM PST"
      ]
     },
     "execution_count": 193,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the formatted dataframe, which is much easier to read\n",
    "formatted_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Format Chart Axis as Dollars\n",
    "\n",
    "`dw.dollars()` formats a number as currency with thousands separators on a matplotlib chart axis.\n",
    "\n",
    "This function takes a numeric value `x` and formats it as a string with\n",
    "thousands separators and a dollar sign prefix. The `pos` parameter is required\n",
    "by the matplotlib library for tick formatting but is not used in this function.\n",
    "\n",
    "Use this function when you need to display currency values in a more readable\n",
    "format, particularly in the context of matplotlib or seaborn plots."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load some data with large numbers\n",
    "df_housing = pd.read_csv('data/housing_no_outliers.csv', index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "      <th>ocean_proximity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-122.23</td>\n",
       "      <td>37.88</td>\n",
       "      <td>41.0</td>\n",
       "      <td>880.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>322.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>83252.0</td>\n",
       "      <td>452600.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-122.22</td>\n",
       "      <td>37.86</td>\n",
       "      <td>21.0</td>\n",
       "      <td>7099.0</td>\n",
       "      <td>1106.0</td>\n",
       "      <td>2401.0</td>\n",
       "      <td>1138.0</td>\n",
       "      <td>83014.0</td>\n",
       "      <td>358500.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>-122.26</td>\n",
       "      <td>37.84</td>\n",
       "      <td>42.0</td>\n",
       "      <td>2555.0</td>\n",
       "      <td>665.0</td>\n",
       "      <td>1206.0</td>\n",
       "      <td>595.0</td>\n",
       "      <td>20804.0</td>\n",
       "      <td>226700.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>-122.26</td>\n",
       "      <td>37.85</td>\n",
       "      <td>50.0</td>\n",
       "      <td>1120.0</td>\n",
       "      <td>283.0</td>\n",
       "      <td>697.0</td>\n",
       "      <td>264.0</td>\n",
       "      <td>21250.0</td>\n",
       "      <td>140000.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>-122.26</td>\n",
       "      <td>37.84</td>\n",
       "      <td>50.0</td>\n",
       "      <td>2239.0</td>\n",
       "      <td>455.0</td>\n",
       "      <td>990.0</td>\n",
       "      <td>419.0</td>\n",
       "      <td>19911.0</td>\n",
       "      <td>158700.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    longitude  latitude  housing_median_age  total_rooms  total_bedrooms  population  households  median_income  median_house_value ocean_proximity\n",
       "0     -122.23     37.88                41.0        880.0           129.0       322.0       126.0        83252.0            452600.0        NEAR BAY\n",
       "1     -122.22     37.86                21.0       7099.0          1106.0      2401.0      1138.0        83014.0            358500.0        NEAR BAY\n",
       "8     -122.26     37.84                42.0       2555.0           665.0      1206.0       595.0        20804.0            226700.0        NEAR BAY\n",
       "15    -122.26     37.85                50.0       1120.0           283.0       697.0       264.0        21250.0            140000.0        NEAR BAY\n",
       "18    -122.26     37.84                50.0       2239.0           455.0       990.0       419.0        19911.0            158700.0        NEAR BAY"
      ]
     },
     "execution_count": 200,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the data, notice the float values don't have comma separators or dollar signs\n",
    "df_housing.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot a chart with thousand dollars formatting on the X and Y axis\n",
    "plt.figure(figsize=(12, 6))\n",
    "plt.title('Median Income vs. Median House Value by Ocean Proximity', fontsize=18, pad=15)\n",
    "sns.scatterplot(data=df_housing, x='median_income', y='median_house_value', hue='ocean_proximity')\n",
    "plt.xlabel('Median Income', fontsize=14, labelpad=10)\n",
    "plt.ylabel('Median House Value', fontsize=14, labelpad=10)\n",
    "plt.gca().xaxis.set_major_formatter(FuncFormatter(dw.dollars))  # Add thousand dollars formatting on X axis\n",
    "plt.gca().yaxis.set_major_formatter(FuncFormatter(dw.dollars))  # Add thousand dollars formatting on Y axis\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Format Chart Axis as Thousands\n",
    "\n",
    "`dw.thousands()` formats a number with thousands separators on a matplotlib chart axis.\n",
    "\n",
    "This function takes a numeric value `x` and formats it as a string with\n",
    "thousands separators. The `pos` parameter is required by the matplotlib\n",
    "library for tick formatting but is not used in this function.\n",
    "\n",
    "Use this function when you need to display large numbers in a more readable\n",
    "format, particularly in the context of matplotlib or seaborn plots."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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hQgVLciBL9l/5r/y12jAMIz093ejUqZPlAi63mIsjgZCXtLQ0o0mTJgZgfP7551fVZkHaL8rHddWqVTn2TUpKMkJCQgzAmDp1at4nm0fcQI6LZ8PIvKipXbu2ARh33HGHVdm5c+csFzMrVqywGVuFChUMINceTbakpKRYYnr00UcLvF96erolnoEDB1qVdejQwQCM2rVrG1FRUQU6XkxMjOW91Nb5GUbm+2XWhWfWa6mgvvnmGwMwbrzxxhxl2T8junbtarOXwnvvvWcAhpubmyXpU1AFSSA89dRTljrZe2Zkf07++OOPNvct7GdFbGysUatWLctnaHp6unHo0CFLT4yRI0faPGZBEgjF9flT2ASCYRjGiBEjDMBo27atzfI333zTgMxeDLZ6+YlcL5RAEJFikVsCYdeuXXleIGdp3bq1ARj33Xef1faiSiD8888/BmR2d7wyiVFUCQRvb29LN0h/f3+rLz9OTk7GokWLcuzfq1cvAzDatWuXaxvLly+3HGf37t2W7TNnzszzYtowMn9dyuq2f+VFQ9YXuGrVquX6i2XWl8aOHTvaLE9LS7Mc/6effrIqq1SpkgEYixcvzvXcrlZCQoLll8LsCYIsX331leUxyX5hkpCQYOmqe+Uvt8XNVgIhLS3NOHTokDFx4kTL4+fv729cunTJMAzDGDlypAGZv6TaulgxjP+e07YuHLIuKqpWrZrr3/bXX3+1+bzKHnNJJxAMwzDGjBljAMYTTzxxVW0WpP2ielxt/eKZ5aGHHjIAo2/fvnnGmFfceR3/448/NiCzl8OVF98DBgyw+T5qGP8l39zc3Cy/PhdEZGSk5fGw9et0XoKCggzA6NGjh2XbwYMHLce7MmGcl6zPgubNm+dZL+ui7vbbb7+qWBMSEixxZfVsyJL9M+K3336zuf/x48ctdf7555+raju3BEJycrLxzz//GMOHD7e8f9WuXdsqQZH1nLSVCMxS2M8KwzCMrVu3WhJCEydONFq2bGn5e2T1mrtSQRIIxfX5UxQJhP379+f6HmkYhlGvXr08kzIi1wtNoigiJWrr1q0AmM1mOnfunGu9rFm7s+pfi7NnzzJhwgTatWtHQEAAZrPZMjFSgwYNgMzJFi9fvnzNbeQlJiaGs2fPcvbsWavlGqtVq8bu3bttLmOZdb7du3fP9bhdu3bF0dHRqn72/7dq1Qpvb2+b+/r5+VnWDM/tsc0+k/qVgoKCLG3Y4ujoSIUKFQByPK533nknAEOGDGH06NH88ccfJCQk2DxOQbm5udGnTx8APv/88xzlWdvuuecefHx8rPbr1q0bkDmp5fjx49m8eTMpKSmFiudqZJ/4z2w2U7t2bSZOnEhycjIVK1bkhx9+wM/PD/jvb9W1a1fLBItXql+/vmV5stz+tlkTrNnSsWNHzGZznvsXl3Xr1jF06FDq1auHp6en1SRmM2bMADIn4CxqRfW4tmnTJtc2QkJCAAq1ZOstt9ySb1lGRkaOCeSefPJJAJYuXZpjSdBPPvkEgL59++Lr63vNsRXWhg0bgMz3jh49ehR4v/Xr1wOwb98+goODc71NnjwZyJx490qxsbG88cYbdO7cmcDAQJydnS3PO3d3d0u9vJ57uf3ts/7uULi//UMPPWSJycXFhQYNGvD++++TkZFBzZo1+fHHHy2v2+zat2+f6zGL4rOiRYsWvPbaa0Dm5Ihbt27Fw8ODRYsW4ezsfNXnmaW4Pn+KQt26dS0TLma9frKsW7eO/fv3YzKZeOyxx4q8bZHSRAkEESlR586dA7DMdJ6bKlWqWNW/Whs3bqRevXpMnjyZTZs2cenSJdzc3AgMDCQoKMjyJQMgPj7+mtrIz7x58zAye3oRHR3N6tWrad++PSdOnOChhx4iLi4uxz5Z55vXOtWurq6W+LM/PgXZF/J/bL28vHLdN+uLakHqpKamWm2fMWMGXbt2JS4ujrfffpsuXbrg7e1Ny5YtmTBhwjXPWD548GAA1q5da3WRcP78eVasWGFVJ7tPP/2Upk2bcv78eaZMmULbtm3x8vKiQ4cOvPHGG4X60l8QHh4eBAUFERQURKVKlahduzahoaHMmDGDffv20aFDB0vdovrb5ve8CggIyHP/4vDCCy/QqVMn5s+fz4EDB0hKSsLPz8/y2Hh4eADF8zotydfMla+Hq5FXfNnLroyvU6dONGjQgNTUVMuqCZA5m/7q1asB8lxBwRZ/f3/L/y9evFjg/TIyMiwXdVnPM4DIyEgg8zMh629dEFmrSyQlJVkStbZuMTExADmSlQcPHqRBgwaMGTOGtWvXcv78eZycnKhYsaLluZclr+debn/77Bf1hfnbe3t7W+IJCQmhXr163H333cyePZs9e/ZQr149m/sFBgbmesyiet6PGjXKkmQAePPNN6lTp06ex8xPcX3+FJWspNwXX3xBUlKSZfvHH38MZP74UbNmzWJpW6S0UAJBRK47aWlpDBgwgKioKJo1a8by5cuJiYkhNjaWs2fPEhkZyaZNmyz1jVyW6ipK3t7edOnShV9//ZWGDRuyadMmnn766WJvtzTx9fVl1apVrFu3jjFjxtC+fXvMZjPbtm1j8uTJ1K5dm4ULF171cTt16kT16tUxDMNqybxFixaRlpZGUFAQt912W479qlWrxvbt21mxYgXPPPMMLVq0ICMjg/Xr1zNmzBhq1arFqlWrCnXOeXnuueeIjIwkMjKSiIgIDh48yIoVK3j++eetLrCuZ7/99pulh8H//vc/9uzZQ3JyMpcuXbI8NiNHjgRK5nV6Pcq64Pn0008tj2HW/xs1akS7du2u6nhOTk7Url0bIM8lW6+0d+9eSw+fhg0bWrbn9mtzftLT0wHo16+fJVGb1y370n2Q+cv+qVOnqFGjBt988w0XL14kPj6ec+fOERkZaZXQtOdzb+bMmZbXwunTp9m3bx8//PADw4YNyzPhktVLrTht2bKFXbt2We5nX2bxetWrVy+CgoK4fPkyX3/9NZDZ2+Hbb78F4PHHH7dneCIlQgkEESlRWb+KXLhwgeTk5FzrZXUZzetXlNxs3LiR48eP4+joyLJly+jRo0eOXyyyfvUqae7u7rz//vsAzJ8/39J9N0vW+ebVZTYpKcnyy1/2x6cg+2Yvv5bHtih06NCB6dOn8+effxIVFcUPP/xA48aNSUxM5OGHH87R1To/JpOJgQMHAtbDGLL+P2DAAJtdfAEcHBwIDQ1l5syZbN26lUuXLvHll19SrVo1Ll++zAMPPFCiwxpyU1R/27x6eSQnJ9t8XsF/FyPZf3G7UnR0dJ6x2bJo0SIAQkNDmTVrFo0aNcpx4VOcr9Wy8prJ6++WvcxWfIMHD8bd3Z0jR46watUqUlNTCQ8PB66+90GWrOE/O3bs4OjRowXa57vvvrP8P/uQjODgYCDzM+Fqeplk7WdraEJ+Tp48aXnvXbhwIX369LHqWQH2+4woCUXxvI+JiWHAgAGkpqbSuHFjTCYTCxcutDy3rldOTk488sgjwH/DGLJ6IwQHB3P33XfbMzyREqEEgoiUqKzujmlpafzxxx+51vv999+BnGMds8Yp5/WL0MmTJwGoWLFirl00s45vD127drXM//Diiy9alWU9PitXrsx1/zVr1pCWlgZYPz7Zx6vmdjEXFRVlNf7V3lxdXbn77rstFxdJSUn8+eefV32crCEKBw4cYMuWLZZ/s5cVhJeXFw888ABhYWFA5jwae/bsuep4ilrW33b16tVkZGTYrLN//37LxWRuf9s//vgj19fOunXrLM+r7N2SActcDFmvrSvFxsayb9++fM4ip6zjNW/e3Ga5YRh59gIpyPtBXorqcS1uWcMN8ipzcHCw+Tj6+PgwYMAAILObddZ8CG5ubpbE29XK6tVgGIZljoG8XLx4kVmzZgGZY+dbt25tKbv55puBzB4FP//8c4FjyBrjv23bNs6cOVPg/cD6eZzbc8+enxHFrSg+K4YNG8a///5LUFAQv//+O88++ywAw4cP59ChQ8UUefHIPv9JQd5LHn/8cRwcHPjzzz/Zt2+fJZHw0EMP4eTkVGxxipQWSiCISIlq0qSJZQLDqVOnWrqhZrd8+XI2b94MYPnimyVrwqeoqKhc28iaLC9rDOyVTp06xXvvvXdN8ReVl19+Gci8aPvtt98s2/v37w9k9qL49ddfc+yXlpZm+cLeqFEjGjVqZCnr3bs3ZrOZpKQkpk+fbrPd1157jeTkZJycnOjdu3eRnU9+0tLScr1Ag8xJDbPkNpldXurUqWOZzOyzzz6z9D5o1KiRzQuE/HoVFDaeopb1vDh9+jSffvqpzTrjx48HMseS5zYJ54kTJ5g/f36O7RkZGZYJ0Ro0aEDjxo2typs2bQrA4sWLbR73zTffzLNHUW6yXqvZu0FnN2fOHP79999c9y/I+0FeiupxLW5//vkna9asybE9KSmJt956C8jsxZHbZIhZF/xLliyxDBkpzOSJTZs2tSTmwsPD+eijj3Ktm5SUxIABAzh//jwODg688cYbVuW1atWiU6dOALz00kuWOQvyc//99+Pr60tqaiqjRo3K88IvIyPD6jmSfUJVW8+92NhYpk6dWqA4yqLCflbMnz+fBQsWYDKZmD9/PoGBgUyfPp3mzZsTFxfHgAEDSkXPrYLKPpFkQd5Lqlevbpnw88knn2TPnj2aPFHKFft/KxKRcifrC8u6devo06ePpQtsamoqX375pSVpcPPNN3Pvvfda7Zt1wRwTE2MZf3ilDh064OHhgWEY9O3bl4MHDwKZv3D98ssvec5EX1JuvfVWy686WRcokPnFLutCuG/fvixYsMAyGdTRo0fp3bs3GzduBLBcCGSpXLmy5VegadOmMWHCBMuXoaioKMaNG2f58j5q1CgqVapUfCd4hVOnTlG7dm2mTp3Kjh07LL90A+zevdvyS6iHh0eeq3PkZdCgQUBmt/isuRCytl1pw4YNNGnShHfeeYd9+/ZZkhuGYbBhwwaGDRsGZE4i1qRJE6t9a9SogclkokuXLtcU57Vo3bq15Uv88OHD+eCDDyyTwkVGRvLYY4/xzTffADBlyhRcXV1tHsfHx4dhw4bxySefWIYjnDx5kgEDBlh+ybZ14ZT1mvzll1+YMGGC5SLvwoULvPTSS0ydOvWaLkZvv/12AH7++WemTJli6cIeFRXFa6+9xvDhw/OcDyLr/WD58uXXNAlnUT2uxc3Hx4fevXvz7bffWl47+/fvp2fPnuzfvx9HR8c8ewK0bNmSFi1akJKSYknOXuvwhSyzZ8+2/JL95JNPMmjQILZt22a5kE9MTOS7776jZcuWliTp66+/bpnFPruZM2fi6urKoUOHaN++PStWrLC876Wnp7NlyxaefPJJq14Bvr6+vPvuu0Dma75nz55s3rzZ8lrOyMhg3759vPXWWzRs2JBly5ZZ9q1fvz7VqlUD4OGHH2bbtm2Wso0bN9KlS5diW52nNCjMZ8Xhw4ct8/eMHDmS0NBQAJydnVm4cCEeHh5s27aNl156qQTPqHDq1KljWTki+1wheclKymXN+6DJE6VcKZnVIkWkvMla7zm3t5m3337bMJlMljq+vr6WNaUBo3Hjxsbp06dt7tutWzdLPS8vL6N69epG9erVjXfeecdS58MPP7TUAQxPT0/D1dXVAIwKFSoYP/74Y6HXhLYlt/W7bfn+++8tdZctW2bZfurUKaNhw4aWMmdnZ8PX19dy38HBwZg5c6bNYyYnJxt9+/a1quvn52dZMxwwBgwYYKSkpOTYN2sd7iFDhuQac9Ya4xMmTMi1Ttba9dnPP/vjAhiOjo6Gv7+/1d/c2dn5qtaBv9KFCxesjufg4JDrcyj73xgwnJycjICAAMNsNlu2eXt7G2vXrs31/GytZV4QWcfP6zG0JSoqyvL4A4bZbDb8/PysXkfPPfeczX2z9hs7dqzRoUMHyzn7+flZPQ6vvPKKzf3T0tKMrl27WuqZTCZL2yaTyXjjjTfyfG7Yek4YhmGkpKQYHTt2zHHcrOdrz549jVdeeSXXx/vgwYOW17WDg4MRFBRkeT84efJkvu0X1eOa198y673wWp4vWXG//fbbRt26dQ3AcHFxMXx8fKwes48//jjfY3366aeWfRo1anTVsdgSHx9vPPjggzleS1c+fr6+vkZ4eHiex/rll1+szivrNenk5GTZ9v333+fY78MPP7R63bu4uOTYDzC++OILq/2WLl1q9Xp3d3c33N3dDcDw8PAwfv/9d0vZ6tWrrfYt6GdEbvvn52o+R65UkOekYVzbZ0VKSorRsmVLAzCaN29uJCcn5zhuWFiY5Xn5yy+/WJXl9Voozs8fw7B+TK/8zDcMw3jkkUesngvVqlUzqlevbowePdpmO+np6Za2AOPbb7/NNSaR6416IIiIXYwcOZKtW7cycOBAqlatSkJCAm5ubrRt25Z33nmHLVu2WK2jnd23337LyJEjqVOnDqmpqRw/fpzjx49bdT188skn+emnn+jSpQuenp6kpaVRuXJlhg8fzq5du3J00baHe+65xzIbefZeCJUrV2br1q28/fbbtG3bFjc3NxISEqhatarlV75nnnnG5jGdnZ356quv+Pbbb+nRowcBAQHExsYSEBBAjx49+O6771iwYEGJj9OsXLkyP/74IyNHjqRt27ZUqlSJuLg4zGYzDRo04KmnnuLvv/+mT58+19xGQEAAd9xxh+V+t27dcn0OtWrViq+//pphw4bRokULKlSoQExMDK6urjRr1owxY8awb98+OnbseM3xFDUfHx9WrlxJWFgYXbp0wcvLi7i4OIKDg+nduzerV6/O0T38Ss7OzqxcuZLXXnuNunXrkpycjI+PD926deOnn35iypQpNvdzdHTkp59+YtKkSdSrVw9nZ2dMJhO33XYbv/32G88999w1nZOTkxO//vorEyZMoE6dOjg5OWEYBq1bt+bDDz/kxx9/zHM2+dq1a7N69WruvvtuKlasyMWLFy3vB9l7ueSlKB7X4ubn58dff/3Fiy++SLVq1UhOTsbf35+77rqL9evXF6jrdJ8+fSw9rwrb+yCLu7s7X3zxBVu3bmX48OE0atQIT09P4uLiCAoKokuXLkyfPp1///2XIUOG5Hms2267jUOHDvHyyy/TvHlz3NzciI+Pp3LlyoSGhvLRRx9ZTb6Y5cknn+TAgQM899xzNG3aFBcXF6KiovD09KRly5YMHz6c3377LcdwuDvvvJO1a9fSs2dPfH19SUtLo0KFCjz00ENs27bNMlHk9epaPiteeukltm7dioeHBwsXLrT8ap/dww8/TN++fTEMg8GDB5fokrCFMWvWLCZOnGj5bnDixAmOHz/OhQsXbNZ3cHDgvvvuA9DkiVLumAxD6yKJiIhcz7p06cIff/zBhAkTmDhxor3DETtYvHgxffr0wc3NjYiIiGue/0BEMjVu3Ji///6bsWPHWuaQESkP1ANBRERE5DqXtXzsgAEDlDwQKaQ1a9bw999/4+DgwOOPP27vcERKlBIIIiIiItexjz/+mD/++AMHBwdGjRpl73BEyrSzZ88yYsQIIHNoUI0aNewaj0hJM9s7ABEREREpWps2baJ///5ER0db5of53//+Z5l3RUSuTv/+/Vm/fj2RkZGkpaXh5eXFtGnT7B2WSIlTDwQRERGR60xSUhLHjx8nNjaWG264gUmTJvHOO+/YOyyRMisyMpJTp07h4eFB9+7dWbNmjZZulHJJkyiKiIiIiIiISL7UA0FERERERERE8qUEgoiIiIiIiIjkSwkEEREREREREcmXEggiIiIiIiIiki8lEEREREREREQkX0ogiIiIiIiIiEi+lEAQERERERERkXwpgSAiIiIiIiIi+VICQURERERERETypQSCiIiIiIiIiORLCQQRERERERERyZcSCCIiIiIiIiKSLyUQRERERERERCRfZnsHINYyMjKIiIjAy8sLk8lk73BERERERETkOmcYBrGxsYSEhODgkHs/AyUQSpmIiAiqVq1q7zBERERERESknDl58iRVqlTJtVwJhFLGy8sLyPzDeXt72zkaERERERERud7FxMRQtWpVy/VobpRAKGWyhi14e3srgSAiIiIiIiIlJr9h9JpEUURERERERETyVeYSCGvXruWuu+4iJCQEk8nEkiVLctTZt28fd999Nz4+Pnh4eNCqVStOnDiR53G/+eYb6tWrh6urK40bN2b58uVW5YZhMH78eCpVqoSbmxvdu3fn0KFDVnUuXbrEgw8+iLe3N76+vjzyyCPExcUV+pxFRERERERE7K3MJRDi4+Np2rQps2bNsll+5MgROnToQL169VizZg27d+9m3LhxuLq65nrMDRs2MGDAAB555BF27NjBvffey7333svff/9tqTNjxgzee+895syZw+bNm/Hw8CA0NJSkpCRLnQcffJC9e/fy22+/sWzZMtauXcvjjz9edCcvIiIiIiIiYicmwzAMewdxrUwmE99//z333nuvZVv//v1xcnLi888/L/Bx+vXrR3x8PMuWLbNsa9u2Lc2aNWPOnDkYhkFISAijR4/mueeeAyA6OpqgoCDCw8Pp378/+/bto0GDBmzZsoWWLVsCsGLFCu644w5OnTpFSEhIgWKJiYnBx8eH6OjoPOdASE9PJzU1tcDnKOWTk5MTjo6O9g5DRERERERKsYJeh15XkyhmZGTw008/MWbMGEJDQ9mxYwc1a9Zk7NixVkmGK23cuJFRo0ZZbQsNDbUMjzh69CiRkZF0797dUu7j40ObNm3YuHEj/fv3Z+PGjfj6+lqSBwDdu3fHwcGBzZs306tXL5ttJycnk5ycbLkfExOT5zkahkFkZCRRUVF51hPJ4uvrS3BwcL4TooiIiIiIiOTlukognDt3jri4OKZNm8bUqVOZPn06K1as4L777mP16tV07tzZ5n6RkZEEBQVZbQsKCiIyMtJSnrUtrzqBgYFW5WazGX9/f0sdW15//XUmTZpU4HPMSh4EBgbi7u6ui0LJlWEYJCQkcO7cOQAqVapk54hERERERKQsu64SCBkZGQDcc889jBw5EoBmzZqxYcMG5syZk2sCwZ7Gjh1r1fsha/1NW9LT0y3Jg4CAgJIKUcowNzc3IDO5FhgYqOEMIiIiIiJyzcrcJIp5qVChAmazmQYNGlhtr1+/fp6rMAQHB3P27FmrbWfPniU4ONhSnrUtrzpZv/RmSUtL49KlS5Y6tri4uODt7W11y03WnAfu7u651hG5UtbzRXNmiIiIiIhIYVxXCQRnZ2datWrFgQMHrLYfPHiQ6tWr57pfu3btWLlypdW23377jXbt2gFQs2ZNgoODrerExMSwefNmS5127doRFRXFtm3bLHVWrVpFRkYGbdq0KfS5ZadhC3I19HwREREREZGiUOaGMMTFxXH48GHL/aNHj7Jz5078/f2pVq0azz//PP369aNTp0507dqVFStWsHTpUtasWZPrMZ999lk6d+7MW2+9Rc+ePVm0aBFbt27l448/BjIvwEaMGMHUqVOpXbs2NWvWZNy4cYSEhFgmZ6xfvz633347jz32GHPmzCE1NZWnn36a/v37F3gFBhEREREREZHSqsz1QNi6dSvNmzenefPmAIwaNYrmzZszfvx4AHr16sWcOXOYMWMGjRs35tNPP2Xx4sV06NDBcoyhQ4fSpUsXy/2bb76ZBQsW8PHHH9O0aVO+/fZblixZQqNGjSx1xowZw/Dhw3n88cdp1aoVcXFxrFixAldXV0udL7/8knr16tGtWzfuuOMOOnToYElCSNlmMpksq3Jcq6FDh+a5GoiIiIiIiEhpZjIMw7B3ECWtc+fOdO3alYkTJ9o7lBzyWn8zKSmJo0ePUrNmTavEhRS/yMhI/Pz8cHFxueZjREdHYxgGvr6+AHTp0oVmzZrx7rvvFk2QudDzRkRERERE8pLXdWh2ZW4IQ2FFR0dz5MgRfvrpJ3uHIiUgJSUFZ2fnQh8nr4kwC8rHx6fQxxAREREREbGXMjeEobB8fHw4deoUnp6e9g6lxCUnJ/PMM88QGBiIq6srHTp0YMuWLZbyvXv3cuedd+Lt7Y2XlxcdO3bkyJEjlvJPP/2U+vXr4+rqSr169Zg9e7bV8V944QXq1KmDu7s7N9xwA+PGjbOa+X/ixIk0a9aMzz//nBo1auDj40P//v2JjY0tUPxdunTh6aef5umnn8bHx4cKFSowbtw4sneiqVGjBlOmTGHw4MF4e3vz+OOPA7B48WIaNmyIi4sLNWrU4K233rLsM3nyZEJCQrh48aJlW8+ePenatatladDsQxiOHTuGyWTi66+/pmPHjri5udGqVSsOHjzIli1baNmyJZ6envTo0YPz589bjpl9CMPQoUP5448/mDlzJiaTCZPJxNGjR6lVqxZvvvmm1Xnv3LkTk8lkNfeHiIiIiIhISSt3CYTybMyYMSxevJj58+ezfft2atWqRWhoKJcuXeL06dN06tQJFxcXVq1axbZt23j44YdJS0sDMud3GD9+PK+++ir79u3jtddeY9y4ccyfP99yfC8vL8LDw/nnn3+YOXMmn3zyCe+8845VDEeOHGHJkiUsW7aMZcuW8ccffzBt2rQCn8P8+fMxm8389ddfzJw5k7fffptPP/3Uqs6bb75J06ZN2bFjB+PGjWPbtm307duX/v37s2fPHiZOnMi4ceMIDw8H4OWXX6ZGjRo8+uijAMyaNYsNGzYwf/58HBxyf4lMmDCBV155he3bt2M2m3nggQcYM2YMM2fOZN26dRw+fNgyN8eVZs6cSbt27Xjsscc4c+YMZ86coVq1ajz88MPMmzfPqu68efPo1KkTtWrVKvDjJCIiIiIidpRwCc7th39+hGPrIfoU/P+Pk2WaIaVKdHS0ARjR0dE5yhITE41//vnHSExMvOrjxsXFGU5OTsaXX35p2ZaSkmKEhIQYM2bMMMaOHWvUrFnTSElJsbn/jTfeaCxYsMBq25QpU4x27drl2uYbb7xhtGjRwnJ/woQJhru7uxETE2PZ9vzzzxtt2rQp0Dl07tzZqF+/vpGRkWHZ9sILLxj169e33K9evbpx7733Wu33wAMPGLfeeqvVtueff95o0KCB5f6RI0cMLy8v44UXXjDc3NysHifDMAzA+P777w3DMIyjR48agPHpp59ayhcuXGgAxsqVKy3bXn/9daNu3bqW+0OGDDHuueceq/N59tlnrdo5ffq04ejoaGzevNkwjMy/UYUKFYzw8PC8Hpo8FeZ5IyIiIiIiVynmjGEsGGAYE7z/u02vYRinthpGepq9o7Mpr+vQ7NQDoZw4cuQIqamptG/f3rLNycmJ1q1bs2/fPnbu3EnHjh1xcnLKsW98fDxHjhzhkUcewdPT03KbOnWq1RCHr776ivbt2xMcHIynpyevvPIKJ06csDpWjRo18PLystyvVKkS586dK/B5tG3bFpPJZLnfrl07Dh06RHp6umVby5YtrfbZt2+f1XkDtG/f3mq/G264gTfffJPp06dz991388ADD+QbS5MmTSz/DwoKAqBx48ZW267m3ABCQkLo2bMnc+fOBWDp0qUkJydz//33X9VxRERERETEDtJSYONsOHDFnHsJl+CzeyHmtF3CKipKIAgAbm5uuZbFxcUB8Mknn7Bz507L7e+//2bTpk0AbNy4kQcffJA77riDZcuWsWPHDl5++WVSUlKsjnVlgsJkMlnmGSgqHh4e17Tf2rVrcXR05NixY5ahG3nJfi5ZSY0rt13LuT366KMsWrSIxMRE5s2bR79+/XB3d7/q44iIiIiISAmLOwtbP7VdlhwDZ3aVbDxFTAmEcuLGG2/E2dmZ9evXW7alpqayZcsWGjRoQJMmTVi3bp3VpIdZgoKCCAkJ4d9//6VWrVpWt5o1awKwYcMGqlevzssvv0zLli2pXbs2x48fL/Lz2Lx5s9X9TZs2Ubt2bRwdHXPdp379+lbnDbB+/Xrq1Klj2e+rr77iu+++Y82aNZw4cYIpU6YUeexXcnZ2tuo5keWOO+7Aw8ODDz/8kBUrVvDwww8XeywiIiIiIlIE0lMgJT738ktHSy6WYlDulnEsrzw8PBg2bBjPP/88/v7+VKtWjRkzZpCQkMAjjzxCRkYG77//Pv3792fs2LH4+PiwadMmWrduTd26dZk0aRLPPPMMPj4+3H777SQnJ7N161YuX77MqFGjqF27NidOnGDRokW0atWKn376ie+//77Iz+PEiROMGjWKJ554gu3bt/P+++9brahgy+jRo2nVqhVTpkyhX79+bNy4kQ8++MCyisSpU6cYNmwY06dPp0OHDsybN48777yTHj160LZt2yI/hyw1atRg8+bNHDt2DE9PT/z9/XFwcMDR0ZGhQ4cyduxYateuTbt27YotBhERERERKUJObuAVDLGRtstDmpdsPEVMPRDKkWnTptG7d28GDRrETTfdxOHDh/nll1/w8/MjICCAVatWERcXR+fOnWnRogWffPKJpUv+o48+yqeffsq8efNo3LgxnTt3Jjw83NID4e6772bkyJE8/fTTNGvWjA0bNjBu3LgiP4fBgweTmJhI69ateeqpp3j22WctSzXm5qabbuLrr79m0aJFNGrUiPHjxzN58mSGDh2KYRgMHTqU1q1b8/TTTwMQGhrKsGHDGDhwoGX4RnF47rnncHR0pEGDBlSsWNFqvohHHnmElJQUHnrooWJrX0REREREiphXJbgll+sg/xugQtleWc1kGIZh7yDkPzExMfj4+BAdHY23t7dVWVJSEkePHqVmzZq4urraKUL76dKlC82aNePdd9+1dyjFbt26dXTr1o2TJ09aJmi8VuX9eSMiIiIiUqISLsKeb2H1a5AUlbntxm5w5zvgV92uoeUmr+vQ7DSEQaQUSU5O5vz580ycOJH777+/0MkDEREREREpYe4B0PIRqHcHJMWA2RXcK4Cbj70jKzQNYZBS4cSJE1ZLRF55u3I5yOvVwoULqV69OlFRUcyYMcPe4YiIiIiIyLVwNINPVQhqCAE3XhfJA9AQhlKnvA5hSEtL49ixY7mW16hRA7NZHWauxfX8vBERERERkcLTEAYpU8xmM7Vqle0JRURERERERK5nGsIgIiIiIiJSmmSkQUaGvaMQyUE9EEREREREREqDmAg4vQ12fwXOXtDyoczx8+4B9o5MBFACQURERERExP5iTsMX98O5vf9t27UAWj0GXccqiSClgoYwiIiIiIiI2FN6Omz7zDp5kGXLJ3DpaMnHJGKDEggiIiIiIiL2FH8Ots3LvXzb/JKLRSQPSiCIiIiIiIjYk5EBaUm5lyfHaFJFKRWUQJBiN3ToUEwmE9OmTbPavmTJEkwmk+X+mjVrMJlMNm+RkZFW+546dQpnZ2caNWpks83s+3p7e9OqVSt++OGHfGPNvp/ZbKZatWqMGjWK5OTkHHUTExPx9/enQoUKlvKDBw/i7u7OggULrOpmZGRw880306dPn3xjEBEREZFyxt0P6t6Re3mzB8BBl25if3oWlkPRCSkcORfHjhOXOXI+juiElGJv09XVlenTp3P58uV86x44cIAzZ85Y3QIDA63qhIeH07dvX2JiYti8ebPN48ybN48zZ86wdetW2rdvT58+fdizZ0++7Wftd/ToUWbPns3nn3/O1KlTc9RbvHgxDRs2pF69eixZsgSAOnXqMG3aNIYPH86ZM2csdd966y3+/fdf5syZk2/7IiIiIlLOOLlDp+fAxTtnWaVmUKlJiYckYosSCOVMRFQiTy/cQbe3/6DX7A10e+sPhi/cQURUYrG22717d4KDg3n99dfzrRsYGEhwcLDVzSFbxtUwDObNm8egQYN44IEHCAsLs3kcX19fgoODqVOnDlOmTCEtLY3Vq1fn237WflWrVuXOO+/knnvuYfv27TnqhYWFMXDgQAYOHGgVw/Dhw2natCmPPfYYAPv372f8+PF8/PHHVKhQId/2RURERKQc8rsBHl8DzQeBuz/4VIFuE2DAQvCqZO/oRAAlEMqV6IQUXli8m3WHLlhtX3voAi8u3l2sPREcHR157bXXeP/99zl16lShjrV69WoSEhLo3r07AwcOZNGiRcTHx+daPy0tzXKB7+zsfFVtHTx4kFWrVtGmTRur7UeOHGHjxo307duXvn37sm7dOo4fPw5kDoOYN28e69at45NPPmHo0KH079+fu++++yrPVERERETKDQcHCLgRerwBT66HR1dC+2fBO8TekYlYKIFQjlyIS8mRPMiy9tAFLsQV71CGXr160axZMyZMmJBnvSpVquDp6Wm5NWzY0Ko8LCyM/v374+joSKNGjbjhhhv45ptvchxnwIABeHp64uLiwsiRI6lRowZ9+/bNN86s/VxdXalbty4NGzZk7NixVnXmzp1Ljx498PPzw9/fn9DQUObN+2/m3OrVq/Puu+/y5JNPcubMGWbOnJlvuyIiIiIiOLtlJg28gsHB0d7RiFhRAqEciUlKzbM8Np/yojB9+nTmz5/Pvn37cq2zbt06du7cabktX77cUhYVFcV3333HwIEDLduuHEKQ5Z133mHnzp38/PPPNGjQgE8//RR/f/98Y8zab9euXSxbtoyDBw8yaNAgS3l6ejrz58/PEUN4eDgZ2WbHfeihh6hUqRLDhw/H29vGeDYREREREZEyxGzvAKTkeLs65VnulU95UejUqROhoaGMHTuWoUOH2qxTs2ZNfH19bZYtWLCApKQkqyEFhmGQkZHBwYMHqVOnjmV7cHAwtWrVolatWsybN4877riDf/75J8eEjFfK2g+gbt26xMbGMmDAAKZOnUqtWrX45ZdfOH36NP369bPaLz09nZUrV3LrrbdatpnNZsxmvcxERERERKTsUw+EcqSCpzOdatuexK9T7QpU8Ly6+QGu1bRp01i6dCkbN2686n3DwsIYPXq0VQ+FXbt20bFjR+bOnZvrfq1bt6ZFixa8+uqrV92mo2Nm17HExERLDP3797eKYefOnfTv3z/XCR1FRERERETKOv00Wo74uDszrXcTXly8m7XZ5kLoVLsC03s3wce9ZBIIjRs35sEHH+S9996zWX7u3DmSkpKstgUEBLB37162b9/Ol19+Sb169azKBwwYwOTJk5k6dWquv/iPGDGCXr16MWbMGCpXrpxrfFFRUURGRpKRkcGhQ4eYPHkyderUoX79+pw/f56lS5fy448/0qhRI6v9Bg8eTK9evbh06VKBhkqIiIiIiIiUJeqBUM6E+Lrx/oDmrBzVmSX/u5mVozrz/oDmVPJ1K9E4Jk+ebDVfQHZ169alUqVKVrdt27YRFhZGgwYNciQPIHOCxnPnzlnNl3Cl22+/nZo1a+bbCyFr7oIqVaowYMAAGjZsyM8//4zZbOazzz7Dw8ODbt265divW7duuLm58cUXX+Rz9iIiIiIiImWPyTAMw95ByH9iYmLw8fEhOjo6x8R7SUlJHD16lJo1a+Lq6mqnCKWs0fNGRERERETyktd1aHbqgSAiIiIiIiIi+VICQURERERERETypQSCiIiIiIiIiORLCQQRERERERERyZcSCCIiIiIiIiKSLyUQRERERERERCRfSiCIiIiIiIiISL6UQBARERERERGRfCmBICIiIiIiIiL5UgJBRERERERERPKlBIKUOq+++io333wz7u7u+Pr65ig/duwYJpOJnTt35ijr0qULI0aMyPP4iYmJTJgwgTp16uDi4kKFChW4//772bt3b466MTExvPzyy9SrVw9XV1eCg4Pp3r073333HYZhWNo0mUw5bk8++WSO4z3xxBM4OjryzTff5CibOHGizf127tyJyWTi2LFjeZ6XiIiIiIhIcVICoTxKvAwXDsKprXDhUOZ9O7p8+TJxcXGW+ykpKdx///0MGzasyNtKTk6me/fuzJ07l6lTp3Lw4EGWL19OWloabdq0YdOmTZa6UVFR3HzzzXz22WeMHTuW7du3s3btWvr168eYMWOIjo621H3sscc4c+aM1W3GjBlWbSckJLBo0SLGjBnD3Llzbcbn6upKWFgYhw4dKvJzFxERERERKYwymUBYu3Ytd911FyEhIZhMJpYsWZJr3SeffBKTycS7776b73FnzZpFjRo1cHV1pU2bNvz1119W5UlJSTz11FMEBATg6elJ7969OXv2rFWdEydO0LNnT9zd3QkMDOT5558nLS3tWk6zeESfhm8ehg9awafd4IOW8O0jmdtLUFpaGj/99BP3338/lSpV4siRI5aySZMmMXLkSBo3blzk7b777rts3LiRZcuW0bdvX6pXr07r1q1ZvHgx9evX55FHHrH0LHjppZc4duwYmzdvZsiQITRo0IA6derw2GOPsXPnTjw9PS3HdXd3Jzg42Orm7e1t1fY333xDgwYNePHFF1m7di0nT57MEV/dunXp2rUrL7/8cpGfu4iIiIiISGGUyQRCfHw8TZs2ZdasWXnW+/7779m0aRMhISH5HvOrr75i1KhRTJgwge3bt9O0aVNCQ0M5d+6cpc7IkSNZunQp33zzDX/88QcRERHcd999lvL09HR69uxJSkoKGzZsYP78+YSHhzN+/PhrP9milHgZfnga/l1lvf3ISvhxeIn0RNizZw+jR4+mSpUqDB48mIoVK7J69WqaNm1a7G0DLFiwgFtvvTVHew4ODowcOZJ//vmHXbt2kZGRwaJFi3jwwQdtPn88PT0xm81X1XZYWBgDBw7Ex8eHHj16EB4ebrPetGnTWLx4MVu3br2q44uIiIiIiBSnMplA6NGjB1OnTqVXr1651jl9+jTDhw/nyy+/xMnJKd9jvv322zz22GM89NBDNGjQgDlz5uDu7m7pah4dHU1YWBhvv/02t9xyCy1atGDevHls2LDB0u39119/5Z9//uGLL76gWbNm9OjRgylTpjBr1ixSUlKK5uQLI/58zuRBliMrM8uLwcWLF5k5cyY33XQTLVu25N9//2X27NmcOXOG2bNn065du2s67s0334ynp6fVbd26dXnuc/DgQerXr2+zLGv7wYMHuXDhApcvX6ZevXoFimX27Nk5Yvnyyy8t5YcOHWLTpk3069cPgIEDBzJv3jxLb4fsbrrpJvr27csLL7xQoLZFRERERERKQplMIOQnIyODQYMG8fzzz9OwYcN866ekpLBt2za6d+9u2ebg4ED37t3ZuHEjANu2bSM1NdWqTr169ahWrZqlzsaNG2ncuDFBQUGWOqGhocTExNicoA8yx+THxMRY3YpNUj7Hzq/8Gr3//vuMGDECT09PDh8+zPfff899992Hs7NzoY771VdfsXPnTqtby5Yt893P1kX7tdTJ7sEHH8wRy913320pnzt3LqGhoVSoUAGAO+64g+joaFatsp3QmTp1KuvWrePXX3+9qjhERERERESKy9X1wS4jpk+fjtls5plnnilQ/QsXLpCenm514Q8QFBTE/v37AYiMjMTZ2TnHqgBBQUFERkZa6tg6RlaZLa+//jqTJk0qUJyF5upduPJr9Pjjj2M2m/nss89o2LAhvXv3ZtCgQXTp0gUHh2vPYVWtWpVatWpZbXNzc8tznzp16rBv3z6bZVnb69SpQ8WKFfH19bX8/fPj4+OTI5Ys6enpzJ8/n8jISKthD+np6cydO5du3brl2OfGG2/kscce48UXXyQsLKxAMYiIiIiIiBSn664HwrZt25g5cybh4eGYTCZ7h5OvsWPHEh0dbbnZmlivyHhUhBtzXqwCmds9KhZLsyEhIbzyyiscPHiQFStW4OzszH333Uf16tV58cUXc+2dURz69+/P77//zq5du6y2Z2Rk8M4779CgQQOaNm2Kg4MD/fv358svvyQiIiLHceLi4go8Oeby5cuJjY1lx44dVj0UFi5cyHfffUdUVJTN/caPH8/BgwdZtGjRVZ+niIiIiIhIUbvuEgjr1q3j3LlzVKtWDbPZjNls5vjx44wePZoaNWrY3KdChQo4OjrmWFHh7NmzBAcHAxAcHExKSkqOi70r69g6RlaZLS4uLnh7e1vdio2bH9z9fs4kwo3dMre7+RVf2//v5ptv5qOPPiIyMpI33niDnTt30rRpU/bs2WOpc+LECXbu3MmJEydIT0+3XHBnX+rxWo0cOZLWrVtz11138c0333DixAm2bNlC79692bdvH2FhYZbE06uvvkrVqlVp06YNn332Gf/88w+HDh1i7ty5NG/e3CqehIQEIiMjrW6XL2dOShkWFkbPnj1p2rQpjRo1stz69u2Lr6+v1VwJ2QUFBTFq1Cjee++9Qp+3iIiIiIhIYV13CYRBgwaxe/duq196Q0JCeP755/nll19s7uPs7EyLFi1YuXKlZVtGRgYrV660TPDXokULnJycrOocOHCAEydOWOq0a9eOPXv2WK3c8Ntvv+Ht7U2DBg2K43Svnk9l6BMGT2+BR1dm/tsnLHN7CXJ1daV///6sWLGCEydOUL16dUvZ+PHjad68ORMmTCAuLo7mzZvTvHnzIlmVwNXVlVWrVjF48GBeeuklatWqxe23346joyObNm2ibdu2lrr+/v5s2rSJgQMHMnXqVJo3b07Hjh1ZuHAhb7zxBj4+Ppa6n3zyCZUqVbK6DRgwgLNnz/LTTz/Ru3fvHLE4ODjQq1evPIcoPPfcc1bLRYqIiIiIiNiLybja2eJKgbi4OA4fPgxA8+bNefvtt+natSv+/v5Uq1YtR/0aNWowYsQIRowYkesxv/rqK4YMGcJHH31E69ateffdd/n666/Zv3+/ZR6DYcOGsXz5csLDw/H29mb48OEAbNiwAcgc096sWTNCQkKYMWMGkZGRDBo0iEcffZTXXnutQOcWExODj48P0dHROXojJCUlcfToUWrWrImrq2uBjiei542IiIiIiOQlr+vQ7MrkJIpbt26la9eulvujRo0CYMiQIYSHhxfoGF26dKFGjRqW+v369eP8+fOMHz+eyMhImjVrxooVK6wmRXznnXdwcHCgd+/eJCcnExoayuzZsy3ljo6OLFu2jGHDhtGuXTs8PDwYMmQIkydPLvxJi4iIiIiIiNhRmeyBUBSqV6/OpEmTGDp0qL1DsaIeCFLU9LwREREREZG8FLQHwnU3B0JB7N27Fx8fHwYPHmzvUERERERERETKhDI5hKGwGjZsyO7du+0dhoiIiIiIiEiZUS57IIiIiIiIiIjI1VECQURERERERETypQSCiIiIiIiIiORLCQQRERERERERyZcSCCIiIiIiIiKSLyUQRERERERERCRfSiBIiRg6dCj33nuv5f8mk4lp06ZZ1VmyZAkmk8lyf82aNZhMJqKiovI9fmhoKI6OjmzZssVm21fTnslkwsHBAR8fH5o3b86YMWM4c+bMVZytiIiIiIjI9UcJhHIoOjmao9FH2X1+N0ejjxKdHF3iMbi6ujJ9+nQuX75c6GOdOHGCDRs28PTTTzN37txCt3fgwAEiIiLYsmULL7zwAr///juNGjViz549hY5VRERERESugWFATASc2QWnt0HUCUhLsXdU5Y4SCOVMZHwkY9aO4e4ld/Pg8ge5e8ndvLD2BSLjI0s0ju7duxMcHMzrr79e6GPNmzePO++8k2HDhrFw4UISExML1V5gYCDBwcHUqVOH/v37s379eipWrMiwYcMKHauIiIiIiFyl9BQ4sRE+6QofdYJPboHZbWHnl5AYZe/oyhUlEMqR6ORoJmyYwIaIDVbb10esZ+KGiSXaE8HR0ZHXXnuN999/n1OnTl3zcQzDYN68eQwcOJB69epRq1Ytvv322yJtz83NjSeffJL169dz7ty5a45VRERERESuQdRJ+OweiM32o2dKPCwbAZG77BZWeaQEQjlyKelSjuRBlvUR67mUdKlE4+nVqxfNmjVjwoQJ13yM33//nYSEBEJDQwEYOHAgYWFhRd5evXr1ADh27Ng1xyoiIiIiItdg99eZvRBsWfUqJJTsdUx5pgRCORKbEluo8uIwffp05s+fz759+65p/7lz59KvXz/MZjMAAwYMYP369Rw5cqRI2zMMA8Bq0kURERERESlmackQsT338gsHIS2p5OIp55RAKEe8nL0KVV4cOnXqRGhoKGPHjr3qfS9dusT333/P7NmzMZvNmM1mKleuTFpaWq6TKV5re1kJhxo1alx1nCIiIiIico3MLlCpWe7lAbXB7FZi4ZR3SiCUI/6u/rQPaW+zrH1Ie/xd/Us4okzTpk1j6dKlbNy48ar2+/LLL6lSpQq7du1i586dlttbb71FeHg46enpRdJeYmIiH3/8MZ06daJixYpXFaOIiIiIiBRS0/7g6Gy77JaXwd2vZOMpx8z2DkBKjo+LDxNvnsjEDRNZH7Hesr19SHsm3jwRHxcfu8TVuHFjHnzwQd577z2b5Xv27MHL67/eESaTiaZNmxIWFkafPn1o1KiRVf2qVasyduxYVqxYQc+ePa+6vXPnzpGUlERsbCzbtm1jxowZXLhwge+++64QZykiIiIiItfEtyoMWgLfPgRxZzO3ObnDbVPz7p0gRU4JhHIm2COY6Z2mcynpErEpsXg5e+Hv6m+35EGWyZMn89VXX9ks69Spk9V9R0dHNm/ezK5du/jkk09y1Pfx8aFbt26EhYXZTCDk117dunUxmUx4enpyww03cNtttzFq1CiCg4Ov8qxERERERKTQHJ2hWjt4fA3En4eMNPCoCJ5BmUMcpMSYjKzZ4aRUiImJwcfHh+joaLy9va3KkpKSOHr0KDVr1sTV1dVOEUpZo+eNiIiIiIjkJa/r0OzUA0FERERERERKvYykJNIuXYL0dBzcPTAH2GcOt/JMCQQREREREREp1VLPnOHC7A+J/uEHjJQUXOrWJeiVl3Ft2BBHd3d7h1duaBUGERERERERKbVSz53jxONPEPXNNxgpKQAkHzjAicFDSN6/387RlS9KIIiIiIiIiEiplXzoMCmHDuUsMAzOvj6NtMuXSz6ockoJBBERERERESm14tatzbUsac8ejMTEEoymfFMCQUREREREREotp8CgXMscPD3BQZe1JUWPtIiIiIiIiJRanrd0BZPJZpnfAw9gDggo4YjKLyUQREREREREpNQyBwYS8uYbOXoauN50E34PPoDJyclOkZU/WsZRRERERERESi1Hd3c8b7mFG39eTtzGjaRfuoRHu3Y4V6mCuWJFe4dXriiBICIiIiIiIqWao5sbjtWr41+9ur1DKdc0hEGK3dChQzGZTEybNs1q+5IlSzBlG8u0Zs0aTCaTzVtkZKTVvqdOncLZ2ZlGjRrZbDP7vt7e3rRq1YoffvihQPEuW7aMzp074+Xlhbu7O61atSI8PNxm3cWLF9OlSxd8fHzw9PSkSZMmTJ48mUuXLgEQHh5u83xcXV1zHGvjxo04OjrSs2fPHGXHjh3DZDIRGBhIbGysVVmzZs2YOHFigc5NRERERETkWimBUA6lRUeT/O+/JO7aRfK/R0mLji72Nl1dXZk+fTqXC7BG64EDBzhz5ozVLTAw0KpOeHg4ffv2JSYmhs2bN9s8zrx58zhz5gxbt26lffv29OnThz179uTZ9vvvv88999xD+/bt2bx5M7t376Z///48+eSTPPfcc1Z1X375Zfr160erVq34+eef+fvvv3nrrbfYtWsXn3/+uaWet7d3jvM5fvx4jrbDwsIYPnw4a9euJSIiwmZ8sbGxvPnmm3meg4iIiIiISHHQEIZyJvVMJBGvvELC+vWWbe4dOhAyZQpOlYKLrd3u3btz+PBhXn/9dWbMmJFn3cDAQHx9fXMtNwyDefPmMXv2bKpUqUJYWBht2rTJUc/X15fg4GCCg4OZMmUKM2fOZPXq1TRu3NjmcU+ePMno0aMZMWIEr732mmX76NGjcXZ25plnnuH++++nTZs2/PXXX7z22mu8++67PPvss5a6NWrU4NZbbyUqKsqyzWQyERyc92MbFxfHV199xdatW4mMjCQ8PJyXXnopR73hw4fz9ttv89RTT+VIqoiISNmSkZJC+uXLYBg4eHnh6OFh75BERETypB4I5UhadHSO5AFAwp9/EjFuXLH2RHB0dOS1117j/fff59SpU4U61urVq0lISKB79+4MHDiQRYsWER8fn2v9tLQ0wsLCAHB2ds613rfffktqamqOngYATzzxBJ6enixcuBCAL7/8Ek9PT/73v//ZPFZeCRBbvv76a+rVq0fdunUZOHAgc+fOxTCMHPUGDBhArVq1mDx58lUdX0RESpeUiAjOvfEm/97RkyO33saZl18h+d+jGOnp9g5NREQkV0oglCPpFy/mSB5kSfjzT9IvXizW9nv16kWzZs2YMGFCnvWqVKmCp6en5dawYUOr8rCwMPr374+joyONGjXihhtu4JtvvslxnAEDBuDp6YmLiwsjR46kRo0a9O3bN9d2Dx48iI+PD5UqVcpR5uzszA033MDBgwcBOHToEDfccANOBVgyJjo62up8PD096dGjR45zGjhwIAC333470dHR/PHHHzmOlTWXxMcff8yRI0fybVtEREqf1MhITgwZyuXPPycjPh4jNZXYFSs4dv/9pBYyyS4iIlKcNIShHMm4YvK9nOVxxR7D9OnTueWWW2z+yp9l3bp1eHl5We5nv0iPioriu+++488//7RsGzhwIGFhYQwdOtTqOO+88w7du3fn33//ZeTIkbz33nv4+/sXyXnY6h2QGy8vL7Zv3261zc3NzfL/AwcO8Ndff/H9998DYDab6devH2FhYXTp0iXH8UJDQ+nQoQPjxo1jwYIF13YCIiJiN/GbNpF68mSO7Rnx8VycO5egsWNxsDHZroiIiL0pgVCOOGS7KLdd7lnsMXTq1InQ0FDGjh2b44I/S82aNXMdArBgwQKSkpKs5jwwDIOMjAwOHjxInTp1LNuDg4OpVasWtWrVYt68edxxxx38888/uc4dUKdOHaKjo4mIiCAkJMSqLCUlhSNHjtC1a1dL3T///JPU1NR8eyE4ODhQq1atXMvDwsJIS0uzatMwDFxcXPjggw/w8fHJsc+0adNo164dzz//fJ5ti4hI6ZKRlEzMT8tzLY9bvZoKTz2lBIKIiJRKGsJQjjgGBODeoYPNMvcOHXAMCCiROKZNm8bSpUvZuHHjVe8bFhbG6NGj2blzp+W2a9cuOnbsyNy5c3Pdr3Xr1rRo0YJXX3011zq9e/fGycmJt956K0fZnDlziI+PZ8CAAQA88MADxMXFMXv2bJvHyj6JYl7S0tL47LPPeOutt3KcU0hIiGXOBVvnc9999/Hiiy8WqB0RESklzI44eHvnWuzg4YnJQV/PRESkdFIPhHLE7ONDyJQpRIwbR0K2IQDuHToQMnUKZhu/dBeHxo0b8+CDD/Lee+/ZLD937hxJSUlW2wICAti7dy/bt2/nyy+/pF69elblAwYMYPLkyUydOhWz2fbTesSIEfTq1YsxY8ZQuXLlHOXVqlVjxowZjB49GldXVwYNGoSTkxM//PADL730EqNHj7b0fGjTpg1jxoxh9OjRnD59ml69ehESEsLhw4eZM2cOHTp0sKzOYBgGkZGROdoLDAxk2bJlXL58mUceeSRHT4PevXsTFhbGk08+afN8Xn31VRo2bJjr+YqISOnjYDbj/+ADxP70k81y/8GDMVeoUMJRich1IzEaUuPB7AruRTN0VyQ7pbjLGadKwVR+601uWP4TNb76ihuW/0Tlt97EKZ9lBova5MmTycjIsFlWt25dKlWqZHXbtm0bYWFhNGjQIEfyADInaDx37hzLl+feLfT222+nZs2aefZCGDFiBN9//z3r1q2jZcuWNGrUiAULFvDhhx/y5ptvWtWdPn06CxYsYPPmzYSGhtKwYUNGjRpFkyZNGDJkiKVeTExMjvOpVKkS586dIywsjO7du9scptC7d2+2bt3K7t27bcZap04dHn744RzJFhERKd2ca9bE7/8nzs3OrW1bPLvdYoeIRKTMS46Dk1vg64Ewpz183gsO/AwJxTtJupQ/JuNqZoOTYhcTE4OPjw/R0dF4X9HFMSkpiaNHj1KzZk1cNTZSCkjPGxGR0ictKorU0xFE//gjRmIC3nfeiXPNmjhVrGjv0DJFn4IzuyFiB1SsB1VbgXcV0PAKkdInIwMOLIevHsxZ1uUlaPcUuBT/XGdStuV1HZqd+j6LiIiIlDCzry9mX1/cGjawdyg5XTgI4XdC3Nn/trl4w5ClUKkpmEz2i01Ecoo7Az+NtF22djo06acEghQZpZFFREREJFP8Bfj2EevkAUByDCzsD7Fn7BOXiOQu4TLEnbNdlpEOl46UbDxyXVMCQUREREQyxV+ASNtz7xB7JmdiQUTsz8Ex73KzS8nEIeVCmUwgrF27lrvuuouQkBBMJhNLliyxlKWmpvLCCy/QuHFjPDw8CAkJYfDgwUREROR73FmzZlGjRg1cXV1p06YNf/31l1V5UlISTz31FAEBAXh6etK7d2/OnrX+ID1x4gQ9e/bE3d2dwMBAnn/+edLS0orkvEVERESKVVo+E/Mmx5VMGBlpaJoukQJyD4AKdWyXOXuCb/WSjUeua2UygRAfH0/Tpk2ZNWtWjrKEhAS2b9/OuHHj2L59O9999x0HDhzg7rvvzvOYX331FaNGjWLChAls376dpk2bEhoayrlz/3UHGjlyJEuXLuWbb77hjz/+ICIigvvuu89Snp6eTs+ePUlJSWHDhg3Mnz+f8PBwxo8fX3QnLyIiIlJc3P3Byd12mckBvHMug1yUIuIi+O7Qd4xeM5ppf03j4OWDxKWUTNJC7CwlES4fg8g9cOlfSIqxd0Rlh2cg3PcJOHtYbzc5QO9PwSvIPnHJdanMr8JgMpn4/vvvuffee3Ots2XLFlq3bs3x48epVq2azTpt2rShVatWfPDBBwBkZGRQtWpVhg8fzosvvkh0dDQVK1ZkwYIF9OnTB4D9+/dTv359Nm7cSNu2bfn555+58847iYiIICgo84U6Z84cXnjhBc6fP4+zs3O+56NVGKSo6XkjIiIFlpYMm+bA7zZ+/Gj1CHSfBC5exdL08ZjjDF0xlAuJF6y2T2g3gTtq3oF7bokNKftiz8Kf78DWMEhPybzwrXcn3D4NfIo3aVXaJaYmEpkQyU///sSJ2BPcHHIzrYNbE+IZYl0xIx2iTsDeJXBiA1SsC80HgW81cHKzS+xStmgVhmyio6MxmUz4+vraLE9JSWHbtm2MHTvWss3BwYHu3buzceNGALZt20Zqairdu3e31KlXrx7VqlWzJBA2btxI48aNLckDgNDQUIYNG8bevXtp3rx5jraTk5NJTk623I+JUbZVRERE7MTsAjcNBM8KsOpViDmd2T26w2ho0rfYkgdxKXHM+GtGjuQBwJRNU2gd3JpqTrZ/BJIyLiUR1r0Nf835b5uRAft+hISL0Pdz8AiwX3x2lJyezPqI9Yz+YzQZRgYAPx/9mQDXAMJvD6eGT43/Kjs4gn9N6DgS0v4Hjs5aMUWKRZkcwnA1kpKSeOGFFxgwYECumZQLFy6Qnp5udeEPEBQURGRkJACRkZE4OzvnSEJcWcfWMbLKbHn99dfx8fGx3KpWrXrV5ygiIiJSZNwDoNmD8OhKeHYXPPkntH0SPCsWW5NRyVGsO73OZlmGkcH2c9uLrW2xs/izsG2u7bLj6yE+l9UFyoELiRd4Ye0LluRBlotJF5m8aTLRydG2dzS7KHkgxea6TiCkpqbSt29fDMPgww8/tHc4No0dO5bo6GjL7eTJk/YOSURERAS8K4FfDfAOyX+W90JKN9IxyH1UbUJqQrG2L3aUFJM5bCE30adKLpZS5sClA6Rk2H5stkRuyT2BIFKMrtsEQlby4Pjx4/z22295juOoUKECjo6OOVZUOHv2LMHBwQAEBweTkpJCVFRUnnVsHSOrzBYXFxe8vb2tbiIiIiLliZeTF3X8cplFHmgZ1LIEo5ES5eyR96/lnoElF0spE58an2d5akZqCUUi8p/rMoGQlTw4dOgQv//+OwEBeY+bcnZ2pkWLFqxcudKyLSMjg5UrV9KuXTsAWrRogZOTk1WdAwcOcOLECUuddu3asWfPHquVG7KSFw0aNCjKUyxzhg4dapno8vz58wwbNoxq1arh4uJCcHAwoaGhrF+/3lK/Ro0avPvuu/ked+HChTg6OvLUU0/lKFuzZg0mk4mGDRuSnp5uVebr60t4eLhVeyaTCZPJhJubGzVq1KBv376sWrXqms5XRERECs7fzZ9X2r6CoylnT4ceNXoQ6FF+LyKvex4Voc4dtssCaoGn7R/hyoOGAQ1zLavsWRlvZ/3wKCWvTCYQ4uLi2LlzJzt37gTg6NGj7Ny5kxMnTpCamkqfPn3YunUrX375Jenp6URGRhIZGUlKSu7do0aNGsUnn3zC/Pnz2bdvH8OGDSM+Pp6HHnoIAB8fHx555BFGjRrF6tWr2bZtGw899BDt2rWjbdu2ANx22200aNCAQYMGsWvXLn755RdeeeUVnnrqKVxcXIr9cSmopPhULkfGc/ZoNJcj40mKL9nsZe/evdmxYwfz58/n4MGD/Pjjj3Tp0oWLFy9e9bHCwsIYM2YMCxcuJCnJ9trV//77L5999lm+x5o8eTJnzpzhwIEDfPbZZ/j6+tK9e3deffXVq45LRERErk59//osunMRnat0xtvZmxreNZh08yTGtB6Dr4uvvcOT4uLqDXe8AVXbWW8PuBEe+LpcL0EY4BZAr1q9cmw3YeKVNq9Q0b345iURyU2ZXIVh69atdO3a1XJ/1KhRAAwZMoSJEyfy448/AtCsWTOr/VavXk2XLl0A6NKlCzVq1LD8Ct2vXz/Onz/P+PHjiYyMpFmzZqxYscJqUsR33nkHBwcHevfuTXJyMqGhocyePdtS7ujoyLJlyxg2bBjt2rXDw8ODIUOGMHny5GJ4FK5N3KUkVn2+n5P7Llm2Va3vzy2D6uHpX/xL/EVFRbFu3TrWrFlD586dAahevTqtW7e+6mMdPXqUDRs2sHjxYlavXs13333HAw88kKPe8OHDmTBhAg888ECeiRwvLy/LUJNq1arRqVMnKlWqxPjx4+nTpw9169a96hhFRESkYFzNrtTzr8e0jtOIT43H7GAmwK18zr5f7vhUhv5fQNw5iD6ZOWzBqxJ4ld/eBwA+Lj48e9OzNK3YlE///pTzCedpGNCQkS1G5jnkR6Q4lckEQpcuXTCM3Cfayassy9GjRxk6dKjVtqeffpqnn346131cXV2ZNWsWs2bNyrVO9erVWb58eb7t20NSfGqO5AHAyX2XWPX5fm57tCGuHk7FGoOnpyeenp4sWbKEtm3bFqpnxrx58+jZsyc+Pj4MHDiQsLAwmwmEESNG8MUXX/D+++/z3HPPXVUbzz77LFOmTOGHH35gzJgx1xyriIiIFIynsyeezp72DkNKmkeFzFtQ+R72e6UAtwB61+lNpyqdSDfScTO74ePiY++wpBwrk0MYCmvv3r34+PgwePBge4dSohJjU3IkD7Kc3HeJxNg8ZsAtImazmfDwcObPn4+vry/t27fnpZdeYvfu3Vd1nIyMDMLDwxk4cCAA/fv3588//+To0aM56rq7uzNhwgRef/11oqOvbrZaf39/AgMDOXbs2FXtJyIiIiJSVCq6VyTYI1jJA7G7cplAaNiwIbt378bBoXydfkpiWqHKi0rv3r2JiIjgxx9/5Pbbb2fNmjXcdNNNVpMa5ue3334jPj6eO+7InHSnQoUK3Hrrrcyda3sd4UceeYSAgACmT59+1fEahoFJa+mKiIiIiEg5V76uoMs5Z7e8R6zkV16UXF1dufXWWxk3bhwbNmxg6NChTJgwocD7h4WFcenSJdzc3DCbzZjNZpYvX878+fPJyMjIUd9sNvPqq68yc+ZMIiIiCtzOxYsXOX/+PDVr1izwPiIiIiIiItcjJRDKETcvZ6rW97dZVrW+P25eziUc0X8aNGhAfHzea91muXjxIj/88AOLFi2yrMaxc+dOduzYweXLl/n1119t7nf//ffTsGFDJk2aVOC4Zs6ciYODg2UJShERERERkfKqTE6iKNfG1cOJWwbVs70Kw+B6xT6BImRe/N9///08/PDDNGnSBC8vL7Zu3cqMGTO45557rOqePn3aslRnlurVq/P5558TEBBA3759cwwtuOOOOwgLC+P222+32f60adMIDQ21WRYbG0tkZCSpqakcPXqUL774gk8//ZTXX3+dWrVqXftJi4iIiIiIXAeUQChnPP1due3RhiTGppCSmIazmxk3L+cSSR5A5ioMbdq04Z133uHIkSOkpqZStWpVHnvsMV566SWrum+++SZvvvmm1bbPP/+cuXPn0qtXL5vzEvTu3ZtBgwZx4cIFm+3fcsst3HLLLTZ7KYwfP57x48fj7OxMcHAwbdu2ZeXKlVZLhoqIiIiIiJRXJqMgax5KiYmJicHHx4fo6Gi8vb2typKSkjh69Cg1a9bE1dXVThFKWaPnjYiIiIiI5CWv69DsNAeCiIiIiIiIiORLCQQRESk8w4C0FHtHISIiIiLFSHMgiIjItUuOhagTsG0+RB2HWrdCndvAt5q9IxMRERGRIqYEgoiIXJvkeNi7BH58+r9tB1fAmgB4+BeoUNtuoYmIiIhI0dMQBhERuTbx52DZszm3J1yE5c9DYlSJhyQiIiIixUc9EMqgjIwMe4cgZYieL+VLYloil5IukZaRhqeTJwFuAcXX2Km/ICPddtm/qyHxMrj5Fl/7IiIiIlKilEAoQ5ydnXFwcCAiIoKKFSvi7OyMyWSyd1hSShmGQUpKCufPn8fBwQFnZ2d7hyTFLCIugg92fsDPR38mLSONmj41Gdt6LE0rNsXdyb3oG0xJzLs8I63o2xQRERERu1ECoQxxcHCgZs2anDlzhoiICHuHI2WEu7s71apVw8FBI5auZ+cSzvHkb09yNOaoZdvR6KM8/tvjzA2dS6vgVkXfaLU2uZcF1gdX36JvU0RERETsRgmEMsbZ2Zlq1aqRlpZGenouXYdF/p+joyNms1k9VcqBw5cPWyUPspuxZQYfd/8YPze/om3UMwiaD4Idn1tvd3CEnm+DZ8WibU9ERERE7EoJhDLIZDLh5OSEk5OTvUMRkVJi45mNuZbtv7SfxPRE/CjiBIK7P3SbADU6wJ/vQNxZqNoGur6sFRhEyprkOEiKBhPg5g9ObvaOSERESiElEERErgNB7kG5lnk6eeJociyehj0rQtP+cGM3yEgFZ09w9S6etkSk6GVkwKUjsHIKHPgJHMzQpD90HAV+1e0dnYiIlDIaFC0ich3oWKUjDibbb+kD6g0gwLUYV2OAzESCd4iSByJlTdQx+OQW2PdD5sSnaUmwPRzm9YCok/aOTkREShklEERErgNB7kG81fktzCbrjmUtg1rSv15/zI7qcCYiV0hLhk2zITkmZ1nMaTj0a8nHJHaRkZREamQkqZGRZCTms8KOiJRr+kYpInIdcDW70qFyB37s9SPbz27nctJlWgS3IMQjhAC3Yu59ICJlU+JlOJhHkuCfJZlDlJw9SiwkKXkpJ09yYc5HxCxbBhkZeN0eSsWnn8apWjVNwiwiOSiBICJynXA1u1LVqypVvaraOxQRKQsczODilXu5q29mHblupZw+zfEHHiTt/HnLtpily4hf9yc1vvka56r6PBERaxrCICIiIlIeeVSAdk/lXt7mSTC7lFw8UqKMjAxiV6ywSh5kSY+KImrxYozUVDtEJiKlmRIIIiIiIuXVjd2gTmjO7a0eg4r1Sj4eKTEZsbHE/PpbruWxv68kPTa2BCMSkbJA/dJEREREyiuvILj7A7h0FPZ+D47O0Lg3+FQBd82fcl1zcsLR0zPXYkdPT0yOxbQEsIiUWUogiIiIiJRnnoGZt2pt7B2JlCBHd3f8hw4hfv16m+X+Q4fi6ONTwlGJSGmnIQwiIiIiIuWQa4MG+Nx7b47tXqGhuLdsUfIBiUipZzIMw7B3EPKfmJgYfHx8iI6Oxtvb297hiIiIiMh1LO3yZVJPnSJ62U+Qno73nT1xrloVc4CGsIiUJwW9DtUQBhERERGRcsrs54fZzw+3xo3tHYqIlAEawiAiIiIiIiIi+VIPBBERERGRMi46OZqz8Wf5/cTvJKcl0616N6p4VsHfzd/eodlP/AVIigaTQ+aqIq4aHixSWEogiIiIiIgURlIMxJ+Hc/+A2RUq1AHPIHByLZHmLyddZt7f85i3d55l29y9c7ml6i2MazuOCu4VSiSOUiM1CSJ3w0+jM/81maDWrXD7NAi40d7RiZRpSiCIiIiIiFyr+Auw/j3Y+B5kzU1udoX7Ps68aHV2L/YQjsUcs0oeZFl1chXdqnfj7hvvLvYYSpWLR2BeD8hIy7xvGHDoVzizEx5dCb7V7BqeSFmmORBERERERK7V8fWwYeZ/yQOAtCT4ZghEnSj25lPSU1jwz4Jcy+fvnc/lpMvFHkepkRwLa179L3mQXdw5OLyy5GMSuY4ogSAiIiJSDqVlpHE2/iyR8ZHEpsTaO5wikZ6RTmR8JEeijnAq9hQJqQnF22D8BVj7hu0yw4Adn1knFopBekY6l5NzTxDEpMSQZuti+nqVHAvHN+RefnAFpKWUXDwi1xkNYRAREREpZ84lnOPbg9+ycP9CYlNiaRXcitEtRlPTtyYuji72Du+aXE66zK/Hf+WDHR8QlRyF2WSmR80ePHPTMwR7BBdPo+kpEH0q9/KLhyE9FczOxdM+4ObkRvfq3dkcudlmeafKnfB2LkeTBzo4gWcgJOaSVPGuAg66BBK5VuqBICIiIlKOXEi8wKg1o/hw14dEJUeRbqSz6cwmBvw0gCOXj9g7vGuSnpHOr8d/ZeqmqUQlRwGQZqSx9N+lPLfmOS4mXiyehp09oFKz3MtrdCrW5EGWzlU6E+QelGO7m9mNwQ0H42Ium0mha+JZEdqPyL285VBw0CWQyLXSq0dERESkHDkWfYxd53fl2J5mpDFj6wyik6PtEFXhnE88z6wds2yW7bqwizPxZ4qnYVcf6DYuc5Z/W2X17yqedq9QybMS4beHc8+N92B2MGPCROcqnVnYcyFVPKuUSAylSq3u0KSf9TaTA/R8G3yr2ycmkeuE+u+IiIiIlCNrT63NtWzb2W3Ep8bj4+JTghEVXnxqfJ7zABy6fIhGFRoVT+MV68KAr+Gnkf8NZ6jUFO79EHyqFk+bNlTxqsLLbV/mqeZPgQFezl54OnuWWPulimdg5pKN7UfAsXXg5A412oNHILiU08dEpIgogSAiIiJSjuSVHHB1dMXBVPY6qLo4umA2mUkzbE8WGOgeWHyNO3tCndsg+HdIisocX+/mDx4BxddmLtzMbriZ3Uq83VLJ3T/zFtTA3pGIXFfK3ieEiIiIiFyzrlW75lrWq3Yv/F39SzCaouHv6k+Pmj1slnk7e3ODzw3FH4R3JQisDxVq2yV5ICJSEpRAEBERESlHAj0CGdt6bI7tN/rcyMONHsbZsfgn/Stq7k7uPHPTMzSt0NRqu7ezNx/d+hFBHjknGBQRkatnMoxiXpxWrkpMTAw+Pj5ER0fj7V2OltwRERGREhObEsu5hHP89O9PXEy8SLfq3ajrV7fMX2hfTLzImfgzHLp8iCD3IGr61CTII6hMDssQESlJBb0OVQKhlFECQUREREREREpSQa9Dy2Q6du3atdx1112EhIRgMplYsmSJVblhGIwfP55KlSrh5uZG9+7dOXToUL7HnTVrFjVq1MDV1ZU2bdrw119/WZUnJSXx1FNPERAQgKenJ7179+bs2bNWdU6cOEHPnj1xd3cnMDCQ559/nrQ02xP6iIiIiIiIiJQVZTKBEB8fT9OmTZk1y/Z6vzNmzOC9995jzpw5bN68GQ8PD0JDQ0lKSsr1mF999RWjRo1iwoQJbN++naZNmxIaGsq5c+csdUaOHMnSpUv55ptv+OOPP4iIiOC+++6zlKenp9OzZ09SUlLYsGED8+fPJzw8nPHjxxfdyYuIiIhI3gwDok7CwV9g80dwbD3EnrF3VCIiZV6ZH8JgMpn4/vvvuffee4HM3gchISGMHj2a5557DoDo6GiCgoIIDw+nf//+No/Tpk0bWrVqxQcffABARkYGVatWZfjw4bz44otER0dTsWJFFixYQJ8+fQDYv38/9evXZ+PGjbRt25aff/6ZO++8k4iICIKCMscQzpkzhxdeeIHz58/j7Jz/pEQawiAiYltiWiIxyTFgAn8Xf5wcnewdkoiURoYBkXvgs7sh8fJ/2wNqwcDvwK+6/WIrhYy0NNLj4jA5O+Po7m7vcETETq7rIQx5OXr0KJGRkXTv3t2yzcfHhzZt2rBx40ab+6SkpLBt2zarfRwcHOjevbtln23btpGammpVp169elSrVs1SZ+PGjTRu3NiSPAAIDQ0lJiaGvXv32mw7OTmZmJgYq5uIiPwnw8jgeMxxpmyawt1L7qbPj334YOcHRMZH2js0ESuXky5zNPoohy4f4mz8WTKMDHuHVD7FRsCXva2TBwAXD8PSZyAxyi5hlTZGRgYpJ09yftYsTj7yCKefHUH8xo2kXb6c/84iUm6Z7R1AUYuMzPxCmf0iPut+VtmVLly4QHp6us199u/fbzmus7Mzvr6+uR43MjLS5jGyx3Wl119/nUmTJhXgzEREyqdTsacYsGwAsamxACSkJTD377msOrGKT277hGCPYDtHKAL/Rv3Ly+tf5u8LfwMQ4BrA2DZjaR/SHk9nTztHV85EnYK4c7bL/l0D8RfAzbckIyqVUo4e5Vj/AWTExlq2xa9bh/9DQ6nw5JM4+vjYMToRKa2uux4IZc3YsWOJjo623E6ePGnvkERESo3ktGTm751vSR5kdyzmGNvPbbdDVCLWIuIiGLJiiCV5AHAx6SLP/fEcey/a7oEoxSjhYt7lyertmR4bS+Rrr1slD7JcmhdO2vnzdohKRMqC6y6BEByc+UvUlasjnD171lJ2pQoVKuDo6JjnPsHBwaSkpBAVFZVnHVvHyB7XlVxcXPD29ra6iYhIpuiUaFadXJVr+bIjy0hOSy7BiERy+ivyL6KSo2yWvb3tbS4nqUt4iQq4MfcyFy9IiYfUxJKLpxRKj44mYcOGXMvj/vyzBKMRkbLkuksg1KxZk+DgYFauXGnZFhMTw+bNm2nXrp3NfZydnWnRooXVPhkZGaxcudKyT4sWLXBycrKqc+DAAU6cOGGp065dO/bs2WO1csNvv/2Gt7c3DRo0KNLzFBEpDxxMDribc5/Uy9PJE0cHxxKMSCSnvyL/yrXs4KWDJKcryZWX8wnn2RK5hY92f8SPh3/kVOwpUtJTrv5AackQdx5cvKHZg7brtHkCts3POT9CeZTXPOpleop1ESlOZXIOhLi4OA4fPmy5f/ToUXbu3Im/vz/VqlVjxIgRTJ06ldq1a1OzZk3GjRtHSEiIZaUGW0aNGsWQIUNo2bIlrVu35t133yU+Pp6HHnoIyJyI8ZFHHmHUqFH4+/vj7e3N8OHDadeuHW3btgXgtttuo0GDBgwaNIgZM2YQGRnJK6+8wlNPPYWLi0uxPiYiItejANcABtQbwPQt022W96/XH7NDmfwok+vIjT65/+Id7BGMo0lJrtyciT/DU78/xaGoQ5ZtTg5OzOo2i5ZBLQu22kp6GkQdg40fwrE/wCMQ2v4P6t0Jix+B1ATwqABthoGDGU5tBtMVv6EZBsRGQvz5zESEZyB4VATn63NVAkdvb9zbtSVh4yab5R4d2pdwRCJSVpTJb11bt26la9eulvujRo0CYMiQIYSHhzNmzBji4+N5/PHHiYqKokOHDqxYsQJXV1fLPl26dKFGjRqEh4cD0K9fP86fP8/48eOJjIykWbNmrFixwmpSxHfeeQcHBwd69+5NcnIyoaGhzJ4921Lu6OjIsmXLGDZsGO3atcPDw4MhQ4YwefLkYn5ERESuTyaTidtq3MZvx35j+3nr+Q761e1HTZ+adopM5D+3Vr+VD3Z8QJqRlqPs8SaPU9G9oh2iKv0S0xJ5f/v7VskDgNSMVJ5e+TQ/3PsDVbyq5H+g8/sg7Nb/hiVcOATH15PR6jHin1xLQnoyAbHnMP/5DhxdC7dOzkwyZMlIhzO74KuBEHM6c5ujE3R8Dlo9Bh4BRXTGpYejtzdBL73E8f79yYhPsCrze/ABzIGBuewpIuWdyTDy6r90/apevTqTJk1i6NCh9g7FSkHX3xQRKU/OJ5zncNRhfjzyI25mN3rV7kUVzyr4ufrZOzQRktOT2Rq5lVFrRpGQlnkxZsJEv7r9GNZ0GP5u/naOsHQ6HXuaO7+/02biBeCtzm9xW43b8j5IwiVY2B9ObrZZfGrwdwzYPJF+Ne+gr19jAv/8AO6fB96V/qt0+Th82C5zboQr3fcJNOlb0FMqU4z0dFJPn+byokXE/7keRz8/Ah59BNeGDTH76zkrUt4U9Dq0TPZAKKy9e/fi4+PD4MGD7R2KiIgUQEX3ilR0r0i7ENtz2YjYk4ujC22C2/D9Pd9zMvYk8anx3OBzAwFuAXg5e9k7vFIrNSM11+QBwIXEC/kfJCk61+QBgPuprQR6BPLRgQVsD2rJG/d/SkD25AHAv6ttJw8AVr8GNTuDV5Dt8jLM5OiIc7VqVBw5koBHH8Xk5ISjl56vIpK3cplAaNiwIbt377Z3GCIiIlIGRCdHk5SWhLOjc669XsyOZkI8QwjxDCnh6Moudyd3KntW5nTcaZvlTSo2KXQbhoMjGUYGAFvObuVMShQBXDEsImJn7ge4fBQyUgsdR2nm4OSEg3ociEgBXXerMIiIiIgUhbiUOLZGbmX4yuHc+8O9PPbrY6w6sYqopCh7h3ZdCHQP5PmWz9ssaxHYgkoelWyWWXHzgxodcy1OqHwT/0b/a7m/NXJrzkqVW+R+/IAbM+dDEBERQAkEERERkRzSMtJYe2otD/3yEDvO7yAuNY4Dlw/w7OpnWXRgEQmpCfkfpLTISIPUJHtHYVPrSq15/5b3qe5dHQA3sxsD6w9keufpBLgVYPJCN1+4443MpRuvEHvzcL6NWGfpgQDY7kFSs5PN/QHo+gp4Xn/DF0RErlW5nUSxtNIkiiIiIvYXGR9Jn6V9iE6OzlFmNplZ2mtpwVYIsKeES3DxCGz5BBIuQsP74IbO4FP64r6QeIHE1ETMjmYCXANwdnQu+M4ZGRB9AnYugCMrSfcI5HyzfvwSf4w394ZZqjmaHFnaaylVvarm3P/s3/D14MwhCwBObtB5LNw0CNzVvV+k1DAMiD4N5/ZmToAa3Aj8a4JXAXosSZ40iaKIiIjINYpKjrKZPABIM9I4HXe6dCcQEi/D+pmw/t3/th3+HXyqwkPLwbea3UKzpYJbBXC7xp0dHMCvBnR6Adr+j9j0JEb9MYo9F/b8V8XkwIxOMwh0s7E8oYMDVGoCD6+A+AuQngLuAeAZDE4u1xiUlCmJUZnLgDq5ZfZqkdLJMCByD3x2d+Z7XJaAWjDwO/Crbr/YyhElEERERESuYDbl/RXJxbGUX1hGn7JOHli2n4R1b8Pt08DJtcTDKlaOjuDmiy/wbtd3OXjpIBvPbCTIPYjOVTsT6BaIizmPv5tXcOZNyo+kmMzeJ6tfhQsHwb8WdH0JghsrkVAaxUTAl32skwcAFw/D0hGZS7Tq71bsCp1ASElJYcmSJWzZsoWoqCjS09Nz1DGZTISFhdnYW0RERKT08XX1pYZ3DY7FHMtR5uXkRZB7KR8Xv3dJ7mW7FkKn58GncomFU9IC3QMJdA+kQ5UO9g5FSqv0VNj/Eyx58r9tcedg/p1w5zvQ7EHIK+EkJS/6FMSdtV3276rMoVpKIBS7QiUQjh8/zq233sqRI0fIayoFJRBERESkLKngVoHpnabz0IqHSEj7b8JEs8nMm53fpKJ7RTtGVwCpibmXpacAmgJLyrnYSPh5jO2yX16GWt1L3VCfci/hYt7leb3vSZEpVAJh5MiRHD58mEGDBvHwww9TpUoVzGaNihAREZGyr65fXRbfvZiVJ1ay/ex2avvV5q4b7iLYMxizQyn/vtPgLtg0y3ZZ7dDcVx0QKS/iL0ByjO2y1ITMX7qVQChdAm7MvczFC1z1vlYSCvXpt2rVKrp168b8+fOLKh4RERGRUsHRwZEqXlUY0nAID9Z/sPQnDbLzvxFu7AZHVlpvd/aA7hP1RVvEwTGf8jL0ei8vPCpC3TvgwPKcZR2f10oMJcShMDtnZGTQvHnzoopFRERsSU3M7LaXVjrXcRcpD8pU8gDAMxDunQ13vgsV6oBnEDQbCI+vzZyxXKS886iQ+6SZ7gHgYWPFDrEvd//M+Sna/i9zxQzI/Fv1eAOaPwiOTvaNr5wwGXlNXpCPW2+9FVdXV5YuXVqUMZVrBV1/U0TKgeQ4uHQE/pwJFw9BcBO4+Snwq/nfB6eISH7izkFGOrj6grPeO0SAzCUBj2+Az+/9/3lB/p+DGR5cDDU75t9LQewjLTnzfS0tCZzcMxNB+lsVWkGvQwuVQNi2bRudOnVi/vz59OnT51oPI9kogSAiAKSlwL6lsPhh6+0OjvDAN3DjLWAy2Sc2ERGR60F6CkSdgJ0LIWJH5vKNzQdmzn2gFRiknCnodWih+uP99NNPdO3alX79+tG5c2duuukmm42ZTCbGjRtXmKZERMqXuLOw9Jmc2zPSYckweHwNeIeUeFgiIiLXDUfnzCE9XV+G9CRwdNEv2SL5KFQPBAeHgk2hYDKZSE9Pv9ZmyhX1QBARAE7+BWG35l7+5LrMIQ0i1yopBhIvZ/7f1RfcfOwajoiIiNhPifRAWL16dWF2FxGRXOWT29US7nKtDCNzTo1fXobDv2Xev6Er3P565mR7+vWt/EhLhZhTcHglXDgA1dpCldbgW9XekYmISClVqARC586diyoOERHJzqtS5nJrKfE5yzwDM2ePFrkWUcch7Lb/eh8A/Ls6s8fLE2vB/wb7xSYlJz0NTm2GL+7LnJAM4K+PM5dJe2h5ZjJJRETkCoVaxlFERIqJZ3Dm8mtXMjnAPbMzy0WuVno67FpknTzIkhwLf32aOYHn9SoxGs7uhd8nwtJn4cgqiI20d1T2ERcJix78L3mQJf48fP9k5tKxIiIiVyiSRY3Xr19PeHg4O3fuJCYmBm9vb5o3b87gwYPp0KFDUTQhIlK+mJ2hbo/MyRL/fBcuHs6cHfrm4Zm/EBdwDhoRK8kxcOiX3MuPrISOo8B8HfZwSYyCrWGwcvJ/27aFQ6VmMGBh+ZuU9PJxSIqyXXZ6G8RfzFxfXUREJJtCJxBGjhzJe++9R9ZcjCaTCcMw2LZtG2FhYTz77LO8/fbbhQ5URKTccfGCkOZw74eQmgjO7uCkNdylEMzO4J5HcsA9ABydSi6ekhR90jp5kOXMTtgaDp3HgGOR/K5SakUlRZFmpOHl5IVLcmzeldOT8y4v7zLSIfYMxJyGlATwrZ45/MPVy96RiYgUq0L9hDV//nxmzpxJ7dq1+fLLL4mIiCAtLY0zZ86wYMEC6tSpw8yZM/nss8+KKl4RketX9Ck48DP88Ubmv9GnMrc7u4NHgJIHUnjOHpm9WHLT/llwvU5XY9j1Ve5lWz+F+HMlF0sJu5h4kRVHV/DE708w6OdBvLHlDVL9auS+g5tf5s1OLiVd4mLiRdIy0uwWQ57SUjNXyvmoY+Z8Ip/fCx+0gDWvZg4BERG5jhVqGce2bdsSERHBnj178PHJ+YUjOjqaxo0bExISwqZNmwoVaHlxvS/jeDnpMqnpqbg5ueHlrCy9iMW5fTD/Toi/8N82jwowZBkE1rdfXHL9ib8If74NGz+w3t7iIbjllet3gs7vh8GuBbbLHJ3hmZ3gU7lEQyoJl5Mu89rm11hxbIXV9uH1B/No5Ekcts/PudM9s6Fp/xJfkeNc/DlWn1rNV/u/IiUjhdtr3M59te8jxLPgw0vSLlwgIykJk9mMuUIFTOZi6FVy6RjMbgNpSTnL7noPWgwp+jZFRIpZiSzjuHfvXh599FGbyQMAHx8fevfuzaefflqYZuQ6cDnpMjvO7WDOrjlExkdSP6A+Tzd7mht9b8Tdyd3e4YnYV+xZ+GqgdfIAMu9/NTBzRnTPIPvEJtcfjwDo9Bw0HwiHfgMjA2rfmrnyh7u/vaMrPg175Z5AuLFb5pChInAm7gy7L+xm9/nd1PKtRevg1gR5BGF2sM/wiIi4iBzJA4AP9n1Om05v0ySoIaY/386cTLJiXeg+OXM5x5JOHiScY9SaUey6sMuy7aPdH/Hdoe/4/I7PqeyZd3InPSaGhG3bOTdjOilHj+Hg5YXfoEH49e+HU2Bg0QZ7+DfbyQOAtTOgTih4aaJbEbk+FfunmclkKu4mpJSLT43ni3++4OM9H1u2bYjYwMaIjbx/y/t0qtJJzxMp3xIuZE6SaMvFw5mJBCUQpChldVEvB71bktKSSEhNwC2kCW5V28HJjdYVzC7QbTy4Fr7X379R//LQLw9xKemSZZub2Y1PbvuExhUa42CyMXI0ORaiT8OeryEmAur1hJCbiqw3xB+n/rC53cBg0NpRrOyzkor1784c0292zlwm1g7+vvC3VfIgy/nE83y1/yuGNx+OUy7zcxiGQdz6DUSMHGnZlhEby8XZs0n+5x8qvf4aZr8iHJKRFE3STYMxpyZgPvQbJEX/VxZ9Ckrr0AsRkSJQqDkQGjZsyOLFi4mLi7NZHhsby+LFi2nYsGFhmpEy7mLiRT79O2cvFAODKZumcC7x+h13KlIgqYmFKxeRHBJTEzl4+SATN0zk4V8f5sUtr7P7rteJu39e5jwPDo5Q+zZ4bDUE1C50e5eSLvHCuheskgcAiWmJPLPqGc4l2PisS46Dvxdndodf9xbsWpjZ6yi8J0SdKHRMAGZT7r8VOZgcSDVSwbsS+FaxW/IgJT2F7w59l2v58qPLiUqOyrU87dw5zr3+us2yuDVrSDtXdN8zzsSd4buKlRnhlsrLAX7s7D2bqK4v/lehYt3MITEiItepQiUQnnjiCU6dOkW7du1YvHgxFy5kdr+9cOEC3377LTfffDOnTp1i2LBhRRKslE1Ho4+SYWTYLDubcJaY5JgSjkiklHEPgNy6NzuYtZSayFXKMDLYenYr9y+9n5+O/sSRqCOsOrGKB38ezO8uDiQ/tRme3QO9wyCoIZgLv/JEVFIU+y/tt1l2KemS7QRCbCQsG5Fz++WjsHoapCYUOq6u1brmWnZr9VvxdfEtdBuFZTKZ8hzi4WjKezhFRlxcnkmCpL3/XHNs2UXERTBkxRAm/PUa6yPWs/z4LwzaMJa5TilEdxiRWan7JLslYkRESkKhEggPPfQQTz/9NHv37qVv374EBQXh5OREUFAQ/fr1Y+/evTz99NMMGaLJZMoz53wy8Ta7dIqUtLSUzO7D0achJb5k2/YMhDa5JFrbDNPwBZGrdD7hPOPWj7OZvH5106tcMGVkDhEogmELWVIyUvIsj0+18b5yZBXkNpf1319nTnhZSEHuQQxtODTH9gDXAIY3H14q5iFycnCiX91+uZb3rtMbf9fc5+cwOTlBHkMhHf0LP3whOS2Zj3d/zJn4MznK5h36lrM3doK73s+cP0JE5DpW6DkQ3nvvPe6//37Cw8PZuXMnMTExeHt707x5c4YMGULHjh2LIk4pw6p5V8PV0ZWk9JwTDtXxq4Ofi/2WihIBIOokbHgPdi6A9BSodyd0fRn8bwCHEkhwOXtAh2czuxH/+XbmnAceFaDDKGjSN3MZRxEpsKjkKC4m2b74TkpP4mz82Xwn5btaPs4+eDh52EwUmDDZbi8pKvcDpqeCkV7ouLxdvHmk8SN0rdqVL/75gsvJl7ml6i10q97tqlY3KG61/WpzS9VbWHVyldX2mj41ufvGu3HMY1JHR39/PLt2JW7VqhxlJjc3XGsXfojK5eTLLD2yNNfyXy7vpU6zp8CxZCefFBEpaUUyiWLHjh2VKJBcVXSryOsdX2f0H6Otfg3ycPLg1Q6v4u92Hc/6LaVf9KnM5RMvH/tv297v4PDv8MQfmUmEkuBREdo8CQ3uhfRkcHTJnMW7hGdCFykPTBT9xL0V3SryTPNneP2vnGPx+9XtZ/sX9BtvgdWv2j5gyE1QRMsd+7r4clPQTTQMaEhaRhruTu6lbvLiCm4VGNduHH3q9GHB/gUkpydz74330rpSa4I98l7RwNHTk6CXxpJ8+DCpJ/6bO8Lk5ETV2bMwF8EqDIZhkGbkPjliUnqykgciUi7YZ00hKVecHZ1pH9Ke7+7+jsWHFnMs+hitgltxa/VbS9WvH1JOHVljnTzIkhwDG2bB7a9lztJeEhwcr8t16EVKmq+LL4HugTbnHXAzuxHkUfTDgsyOZnrW7EmAWwAzt8/kZOxJKrhV4PEmj3Nb9dvwdPa0EWh1qNkFjq6x3u7gCD1mZC65mY/opGiSM5JxN7vbbiMbF7MLLpTQ+9k1qOBWgY5VOtIyuCUZRgYeTh4F3te5ShWqf/4ZyYcOkbBlK05Vq+DRpg3moKDMIQ6F5OXsRcfKHXNd1eLW6rcWug0RkbLAZBi5Db7L6cT/Z3UrV66Mo6Oj5X5BVKtW7eqjK4diYmLw8fEhOjoab++iG5tZWmQYGaSmp+JSUhdkInlJSYCvHswch2yLd2V4bJXW8xYpYwzDYPOZzQz7fViOX41ndJpBt2rd8p2fpzDOJ5wnNSMVs4OZim4V8/61PzYSdi2CTbMh8RJUaw+3TYYKdcHJNdfdLiddZvf53czZPYfI+Ega+DfgqeZPUdOnJm5mt2I4KzkSdYQBPw0gMc16ZZz2Ie15tcOrBLhpwlsRKbsKeh16VQkEBwcHTCYT+/bto06dOpb7+TGZTKSlaU3cgrjeEwgipUpaCnz3OPzzve3yivVg6LLM4QUiUqYkpydzKvYUX+77kn8u/sP/sXee4VEWbRs+t7dk03sj9N47iIAIgoIoFpRXEFTELmBDX1CwvypiARGVJmIDwYI0QXoTkN5LIIT0nmwv349HEpbdDQkJ7XNOjxySmXnmmS1Jdq657+uuZazFsCbDSAxMxKCu/Ml2jVCaC6YcKM2WqqoYIiSfk3O4nFCSBW4XqANAF1TxdPZS5uyfw2e7P/NolyHjs16f0SWuy+V4FJeNUlspFqcFg8qAVulfNLnaOF1OUktSmbV3FhvObiBAFcDQxkPpFt+NCL34OyEQCK5vKrsPrVIKw9ChQ5HJZAQFBXl8LxAIBNclSjV0qEBA6PiYEA8EgusUjUJDneA6vNT+JcwOM1qF9upEvxWekYTKUxvL2+LawN2zIfif6Ey5QjJRrSS55lw+3/O5V7sbN69tfo1v+n1DpP7aLyVYZC3iaMFRvtz7JWklaTQNb8rwJsNJCEy4JoUEhVxBLWMtXu7wMoW2QhQyhYg6EAgE/zqqFIEguPyICASB4ApTmgtr3oK/vvRsr90d7vhcpC8IBIJLx5wPCx6C46u8++LbwX3fV8rn4ELWpK7hqdVPlU8VGE+wJpgzxWcosBbw04CfqBdS/coDlxOzw8zCIwt59693PdoVMgUzbp5B+5j2V2llAoFA8O/kskQgCAQCwf87DGFSycZWD8Du78FhhmZ3Q3g9CLj2T/AEAsE1TGmOb/EA4MxfUkrDJQgIarnk39Ayog3DGzzLqWw5mYV2BjfR4VSmo5JX3zTwcpNrzuWD7R94tTvdTiZsmsDXfb8WaQECgUBwDVItAUGhUPDaa68xfvx4v2PefPNNXn31VeGBIBAIrl30odJXbMurvRKBQHAFyDJlYXVYUSlUhGvDUSou03mKtbjifkvBJU2bZEyidWQ77k16icdnH8diLy+RXCcigFnDr/2w+pTCFL9lEdNK0iiwFggBQSAQCK5BqvUX0+12U5kMCJElIRAIBAJBBTgsUJwJtmJQGSTvDU3FJfkEVafQWsjGtI1M2TmF9NJ0AlQBDGk0hHsb3Ht5NqvaIJDJwN/nIF3oJU0brg/nxVZvcfe0XR7iAcDx7BLeWnKE9+9pToDm2o1EkMvkFfYLjy2BQCC4NrnsKQzZ2dnodKKckEAgEAgEPinJgs1TYet0SUiQyaHxHdDnDTDGXu3VXbfkmfMosBYAEKQJIlgTzIpTK5i0eVLZmBJ7CZ/v+ZwTBSd4tdOrBGkrrn5QZQwR0Gigb6PWOjd5VmKoAhqFhvR8KLU5ffavOJBBXmnDa1pASDQmopKrsLvsXn1JxiSCNcFXflECgUAguChVFhDmzp3r8f2uXbu82gCcTiepqanMnTuXpk2bXvoKBQKBQCD4/4rdAps+hk2flLe5XbB/IZiy4a7Zl5Qj/2/G4XJwKO8QEzZO4GjBUQCSg5KZfONkPtr5kc9rVp5eyROtnqh5AUFrhFvelkShA4uk11Ymg/r94Nb3pdSpSySv1HvjfQ6XG2wOl9/+a4EIXQTjO45nwqYJHu0quYo3urxBuO7SxBWBQCAQXF6qLCA8+OCDZWFlMpmMn3/+mZ9//tlr3Lm0BZ1Ox2uvvVa9VQoEAoFA8P+RkkzYNsN338l1Ur8QEKpEWkkaDy57EKvTWtZ2svAkJwpPUGgt9HvdiYIT1AmuU/MLMsZA/ynQ8xWwFoEmUIpMqKZY0TjWv0N2RKCGAM217ZOtUWq4OelmGoQ0YO6BuZwuPk2LiBbc2+Be4gLirvbyBAKBQOCHKv91mTVrFiAJBCNGjGDgwIHcfvvtXuMUCgWhoaF06tSJkJCQ6q9UIBAIBIL/b1iLwGH131+YClGNr9x6rnPsTjvfH/rBQzw4h1Je8UeeyxoyrzVKXzVItFFL17phbDiW69U3rm9DoozaGr3f5SBAHUDj8MZM7DwRi9OCXqlHpbh20y4EAoFAcAkCwrBhw8r+vXbtWu644w4GDBhQo4sSCAQCgeBfgUpfscme4fpzoS8w2cgpsZFWYCZYpyI+REdYgOaK3NvkMLEza4fPvj3Ze2gf3Z5tGdvQKXW0jWqLSqFib/ZerE4r8cb4K7LGmiIsQMMH97Tki/UnmL/1NCabk/gQHeP6NqRL3fDryoRQo9SgUV6Z94hAIBAIqkfFFrgXYdasWdekeOB0Ohk/fjzJycnodDrq1KnD66+/ftFqEGvWrKF169ZoNBrq1q3L7NmzvcZMnTqVWrVqodVq6dChA9u2bfPot1gsPPHEE4SFhREQEMCgQYPIzMysyYcnEAgEgv8vGCKgfl/ffSG1IDDmii6numQWWRj30156TV7L3M1HKXSkM+/gbF7d+CrLTi4jvTT9st5fo9AQY/D9nP145Eceb/k4ExqP5ru6b/LihjCeW6rmq5Cn+OWGuUTqIi/r2i4HUUYtL/RpwMox3VjzXHcWPtaZW5vHEqxXX+2lCQQCgeD/KTWWIOd0OsnJycFq9R2KmZiYWFO3uijvvvsun332GXPmzKFJkyZs376d4cOHExQUxNNPP+3zmpMnT3LrrbcyatQovvnmG1atWsXDDz9MTEwMffr0AeD7779nzJgxTJ8+nQ4dOjBlyhT69OnD4cOHiYyUPniMHj2aJUuW8OOPPxIUFMSTTz7JnXfeycaNG6/Y4xcIBALBdYLWCP3eg9JsOPNXeXtwEgxZIOXPXyfYHC6+WHeCpfsy6FI3mH7ti3l6/eM43VKlgJ+O/USkPpJZfWaRaLw8nwm0Si0PNH6QP07/4dVXZCsi1Gwg9o9MCua8V97xy2/QsgXGjz5CERVFviUfp9tJkDrouginVysVxAXrr/YyBAKBQPAvQea+2LH8RdixYwcvv/wy69atw2az+b6JTIbD4ajObarEbbfdRlRUFF999VVZ26BBg9DpdMybN8/nNS+++CJLlixh3759ZW2DBw+moKCAZcuWAdChQwfatWvHp59+CoDL5SIhIYGnnnqKl156icLCQiIiIpg/fz533XUXAIcOHaJRo0Zs3ryZjh07XnTtRUVFBAUFUVhYiNFYs/mSAoFAILhGKc2G4gzIPwWB0WCMu67EA4Az+SZ6TV6Lxe7iq4fq8MKWIdhc3p8LOsd25v0b3ydQHXhZ1pFZks8vx35l6p7JZeKFXCZnZNNnuNfZnOwHHvB5XfjzYznUux4f/f0JJoeJmxJvKjP0u57SAQQCgUAguBQquw+tVgTCrl27uOGGG1AqlfTu3Ztff/2VFi1aEB0dzc6dO8nOzqZ79+4kJSVV5zZVpnPnzsyYMYMjR45Qv359du/ezYYNG5g8ebLfazZv3kyvXr082vr06cOzzz4LgM1mY8eOHYwbN66sXy6X06tXLzZv3gxIYordbveYp2HDhiQmJvoVEKxWq0fURlFR0SU9ZoFAIBBcxxgipK/oZld7JZeM1eHCYncRGagh23bSp3gAsOnsJvIt+ZdNQIgKCKFfrQE0De3IyaKjuNwuEgx1KSzSYv3RT8ULoHD+dxQ2G8bh/MMAzN4/m0XHFjG/3/zLFjEhEAgEAsH1RrUEhNdffx2ArVu30qhRI+RyOXfccQcTJkzAbDYzduxYFixYwMyZM2tksZXlpZdeoqioiIYNG6JQKHA6nbz55psMGTLE7zUZGRlERUV5tEVFRVFUVITZbCY/Px+n0+lzzKFDh8rmUKvVBAcHe43JyMjwed+3336biRMnXsKjFAgEAoEH1mIw5YLLKaUGXIcGhNczOpWCIJ0KrUpBqT2/wrEO1+WNSowLDkaj0BGmjia7xEaITk2rSDWFRcV+r3GVlqJVeBr5FVoL+WLvF7zS4RW0ymu/qoFAIBAIBJebapkobtiwgQEDBtCoUaOytnMZETqdjk8//ZTY2Fhefvnl6q2yivzwww988803zJ8/n507dzJnzhzef/995syZc0XXURnGjRtHYWFh2VdqaurVXpJAIBBcf+SdhJ9Gwset4JPW8PUdcHor2M1Xe2X/GqICNTzZoy5nC8wkGxv4HRdriCVAHXDZ1xMeqKF+tJEudcNpHGPEGKDF2P82v+PV3TqzqXiPV/vylOUUWgtrbF1Wh/WyCCiltlIySjPIMmXhdDlrfH6BQCAQCKCaEQiFhYXUrl277HuVSkVJSUnZ93K5nO7du/Ptt99W5zZV5vnnn+ell15i8ODBADRr1oxTp07x9ttve5ShPJ/o6GivagmZmZkYjUZ0Oh0KhQKFQuFzTHR0dNkcNpuNgoICjyiE88dciEajQaMRpYsEAoHgkilIhVl9ofg8h/+MvTC7LzyyBmKaX7Wl/ZtQKOTc0TqOUpuDvadM9Izvw+ozy73Gjeswjkj9Zap4YCsFhxXUAaD0rkSgb9UKde3a2E6c8GiXG/S4h97JL7ue8bpGKasZv+mM0gy2Z2xnycklBKgCuK/hfSQHJROiDanWvA6Xg1NFp/jk70/YmLYRg8rA4IaDubPenZfveRYIBALBv5ZqRSBERkaSn18ephgdHc3Ro0c9xlgsFkwmU3VuU2VMJhNyuedDUygUuFwuv9d06tSJVatWebStXLmSTp06AaBWq2nTpo3HGJfLxapVq8rGtGnTBpVK5THm8OHDnD59umyMQCAQXE0cLgfF1mKsDt8Vc65LUtZ7igfncDlh9SSwCG+ZK0V4gIbHbqzDnS3qM7rNczzf9kUidBHIkNEkrAmz+syibXTbmr+xuUCKOPlppBR9snIC5B4Dp+dJvyoqisSvviRs5CMogoORabUYb72VuB++5aUTU7A6vX8uBtYbWO1NfnppOg8tf4hxG8axIW0Dy1KWMWzZMD75+xPyLRWne1yMlMIU7v3tXladXoXFaSHXksvUXVN59s9nyTZlV2tugUAgEAgupFqyeuPGjTl8+HDZ9126dGHx4sVs3ryZTp06cfDgQX744QcaNmxY7YVWhf79+/Pmm2+SmJhIkyZN+Pvvv5k8eTIjRozwe82oUaP49NNPeeGFFxgxYgSrV6/mhx9+YMmSJWVjxowZw7Bhw2jbti3t27dnypQplJaWMnz4cACCgoJ46KGHGDNmDKGhoRiNRp566ik6depUqQoMAoFAcCGl9lLyzHmkl6ajU+qI0EcQqY9ELqua/utwOUgrSWPBkQX8nfU3CYEJDG08lITAhCsSTn7ZcLng8O/++09vAVuJ5IkguCJoVAoSQvWAnqSgIdyS3BuX24VGoan2Rtwn1hL4ex6seKW8LX0X7JgFw5dCXGuP4aqYGCKeeoqQIUPA7UZhNFIgs1AvvQEH8g95jI01xPKfRv9BrfCOZqgsdqedRUcX+RQKfjzyIwPqDMDtdhOqC63y3CW2Eqbs9C187M3Zy/GC40TohReIQCAQCGqOapVx/OSTTxg9ejSpqanExMSwe/duOnbsiM1mIzQ0lPz8fFwuFwsXLuSOO+6oyXVXSHFxMePHj2fRokVkZWURGxvLfffdx4QJE1CrpQ8Br732GrNnzyYlJaXsujVr1jB69GgOHDhAfHw848eP58EHH/SY+9NPP+W9994jIyODli1b8vHHH9OhQ4eyfovFwtixY/n222+xWq306dOHadOm+U1huBBRxlEgEJwjz5LH7H2zmXtgblk5ujBtGB/1+Igm4U1QyiuvAe/N3svw5cO9NhqTOk+iX3I/NMrrOJVq2cuwZarvvtDaMGIZBET57hdc/+SdgE/agNtHlGFUU3hgMQRcfBOdZ87jSP4Rvjn4DSX2Evom9+WG+BuIMZSX03Q4HZwtPcsfp//gYO5BWkS0oHtCd2IMMSjkCu9JrSU4itPJP7MFl0JJgSGcqccW8Gf6prIhd9S9A7VCTaeYTrSNakuQNqjSDz2jNINbFt5S9vvhQu6qdxevdn610vMJBAKB4N9LZfeh1RIQ7HY7eXl5hISElG3MN23axJtvvsmJEydISkriqaee4tZbb73UW1w2hg0bhkwmY/bs2Vd7KR4IAUEgEJzjp6M/8eom7w//WoWWRbcvIj4wvlLz5JhzGLF8BCcLT3r1qeQqfhn4S6XnuibJPACf+UkTu20KtB3us8vldpFryqfEIqeg1AXIiAjUEhmoQa30sRm8RnG73WSZsyi0FCKXyQnWBhOuC6+RuTNLM0krSSPTlEliYCLRhmjCdGE1MneNsX8x/Ojb3wjA9cRuHFYljpwcZEoVyvAwlJGRyP5Jdcy35GN32QlQBaBX6bE4LDhdTgxqg+c8bhd/Z/3NyBUjPUpU6pQ6ZvWZRZPwJp43NuXBthmw9t1ycUOpJa/vW3xcfJiFp5YCcFvt2zA7zKw6vYrn2z7PvQ3vRaOonKCXWZrJwJ8HUmIv8dk/oukIRrcZXam5BAKBQPDvprL70GqlMKhUKq+yhp07d/YI+78WcbvdrFmzhg0bNlztpQgEAoFPsk3ZTN893WefxWlh09lN3NPgnkrNVWgt9CkeANhddlIKU65vASE4Afp/DL8963kK3XggNOzn85J8Sz67Mw+QVxDOxMWnKDTbAdCrFbw2oAl9m0QTqFNd/rVXE7PdzM6snby66VUyTZLJb5Ixibe6vkXjsMZVilK5kOMFx3l05aNl8wI0Dm3MlB5TiAmIqeDK83DaoThDqoah0kqRIDUe7eL/HMTR4XkKf1tN9pSPcVul6BtFWBhxUz7E0bg2m7P+4su9X5JnyaN1VGsebf4oScYktGrvko1ZpizGrBnjIR4AmB1mnlv7HHP7zvVMFzizHda8fcGCLIT+NpZH/rOAX1L/wO6y0zGmI1N2TgHgk78/oVdSL2IDYiv1yEO1odxd/25m7Z/ls79fsu/3v0AgEAgEl0rNWAtfZ8hkMk6dOnW1lyEQCAR+cbqdpJf6MAb8hyP5Ryo9l7uCDda5e13XaAKh2SBIvgFSNoGtGGp1hcBYMHifljucDn4/+Ttx6rY8//1xnK7y58dkc/LCgj3UDjfQtlbVc9KvNKeKTvH4qsdxnSecnCo6xYjlI1g4YCFJxqQqzZdrzuVM8RmsTivjN473EA8ADuQd4M0tb/Jm1zexuCy43W6MaiN6ld57spIs2D4TNn8K1mJQ6aH9SOj4OATWYEpJTAuQyb1TGEJqYaEJWe96lpJ25uaSOuIhghbM4YUtL5T9fCxPWc6q06uYfctsWkS08LpNrjmXPEuezyWcKTlDviW/XEAw5cG6d32v1+0mbP/P3Bh3A9mWXGxOGznmHEASB/MseZUWEFQKFfc3up/1aes5VnDMo++JFk94pF8IBAKBQFATVElAOH369CXfKDEx8ZKvFQgEgn8bKrmKWsZapBSl+Oz3tcHxR5A6iPiAeM6UnPHqU8qU1A6u7eOq6wx1AIQGSJ4HFyHLnMXerP3szmnoIR6cz8erjzH1/lYEaq/dKIRSeynT90z3EA/OYXVaWXxsMU+2fNJ3br4Psk3ZTNg4ga0ZW3nnhnc4W3rW57h1aes4UXiCp/58CovDQre4bjzZ6kkSjYnlEQ82E2z4ELZMK7/QboKNUyRhoe+7NWdsaYiEnhNg1WsezY4mw8ieNs/nJW67HevyVbSp34btmdvLr3E5eGPLG3x+8+eEaj0FpAsjDy7E7raXf+O0QqH3z9s5tAWpDGr2BCU4mbBpgkefSl6191y0IZrpvaZzMO8gy04uI1gbzMA6A4kNiMWoEamQAoFAIKhZqiQg1KpVC5lMVuWbyGQyHA7HxQcKrgvyLfnkmHM4UXiCUE0o8cZ4ovRRVXaFFwg8sJvBlA8yQB92GcKcry/CdGE80/oZRq/xzl8O0gTRJqpNpeeK0EcwsfNERq4c6RVt8HTrpwnTXmM57ZeZEnsJgeow9uT43xCeyC7BbHNe0wKC2W7mYO5Bv/27snZhcVi8cvn9sSZ1DRvObiBIE0SRzX/pSzduss3ZFFoLAVh5eiUbzm7g+9u+JzkoWRpUkgV/feF7gj3fQrfnKJbLyDXn8lfGX7hx0zaqLeG68KpvejUB0PZBSGgviRbFZyGhI+76A7Gdmu/3MuWRU8Q0j/RqP5R3iGJrsZeAEKGLQCVXYXfZva4xqAyEaM6rMKHUSZERxRk+721LaMe6jK18e+R7j/a4gDiv+1aGKEMUUYYouid0r/K1AoFAIBBUhSoJCEOHDr0kAUHw/4dsUzYTN01kbdrasrYgTRDTe02nUWijSp90CQRluN2QfxLWvg8HF4NcCc0HQ+cnIfjfHbnUNrotr3R4hSk7p1BqLwWgbnBd/tftf1UOTW4e0Zwf+//IV3u/Ym/OXmIDYnmk2SM0CG3gO/y8qtgt0sbt6EooOA3J3SC6GRgrF4p9JdEoNGSYTlMnqjtbfVtDUD8yAJ362v59plaqiQ2I9RspkGRMqnR1jVxzLl8f+BqAYlsxETr/VQu0Cq3XZwGzw8z03dN5tdOr0vvJnCf5H/jC7cZVksm81BVM2z3No2tMmzEMie+F2lIILgcYwiEgGhQX+biiC4FaXaRNu8MCmkDkJWbUtWtj2bvX5yX2RsmkmXf77JPLvQXxcF04j7V4jI///tirb2ybseXPWUk27P4G2gyHoyuk33HnozbgajqIn1d4Gj/qlXom3zi5xsouZhdbSMk18dfJPKKMWtrVCiE6SHtdGYQKBAKB4NqjSgLCtVaxQHBlsTltzN4/20M8AMmg7ZEVj7BwwMJK520KBGUUnIIveoL5vBrp2z6Hw79L5feCrmNzv2oSrAlmUL1BdIvvRoG1ALVcTYg25JJc8LVKLfVC6vFq51cptZeiVWgJUAfUzEIdVji5Dr67T9r0gZT3HpIMQ3+GkKrl4V9uQrQhON12bmkewI9/ybA7vdMYnr6p/jUdfQBgVBsZ1WIUD6942KtPhoz7G91faRNFp9tZFnXgcrs4nH+Y9tHt2ZaxzWvsoPqDWJGywqt93Zl1FNuKJQFBXbEoZVdqvMSDNuEtuFUTjXrObZCfIjXqQqDv/6D+LR4pDyW2EhwuB4HqQE/hWhMgfQGKYA0Ro58ldcRDXveXabU4bmzHzh3e5oOdYjoRrAn2atcqtdxd/25qB9Vm6q6pnC4+Te2g2jzd+mmahzdHpVBJQtqWabBhMjS5AwZ+BqvfKE9niGwEA6ejDKnNwgELWX9mPftz99MsohldY7sSbahcyeeLkV5oZuTc7exNK48kUSlkzHigLV3qhgkRQSAQCASXzL/SRFFwaeSYc/jxyI8++0rsJRzKOyQEBEHVcNrhr5me4sE5ClPhyHJo5/3h/9+ESqEiNiC2xn62dEodOqWuRuYqozgDfvhPuXhwjvyTsOIVaROlCazZe1YDo9rIKx1e4fPdX/HB4Ht5/ZdUsoslh36jTsmbA5tRN7JyYf+Vxelykm3OJt+Sj0KmIFgbTKTeO3y+qjQMbcjYNmP5aOdHONzS869VaHm9y+vEB1RefAtUB9Ilrgu/HP8FgC/2fMG73d4lTBfGypSVONwOdEod9zW8j7iAOL45+I3XHAaVoTwyQR8Osa3g7N/eNwurywFLjkeTDBkTmzxM5DeDpXSmc5jz4adHYPgySOpErjmXA7kHmLN/DsW2Ynok9uC22rf5rSKia9qU6IkTyfrfu7hKTQAoY2KInfwBG3WZXuODNcGM6zCOQLXv92uwNpibkm6iZWRL7C47GoWGEO15qQslmbBlqvTv/Ysg9zjc+CJog0Emg8jGEFYHJRAfGM99je7zeZ/qYLE7mbr6mId4AGB3uhn59XZWjbmRxLCafX8LBAKB4N+DzO2+MLZOcDWpbP3Nq8GpwlPctvg2v/3Pt32eoU2GXsEVCa57SrJgZh/IO+G7P6kz3P/DNbX5/P+KPSsLV3ExMpUKRUgIisAqPOf7F8OPw3z3yeTw9N8QUqsmllmjZJmyyDZlY7PpcTn0KGRKIgJ1RAdqUShqztOlxF7CprRNTNoyqcw3IC4gjndveJcmYU1QXiw8/yKYHCbyzHmcKjqFSq4iPjCecF04aoW6SvOkFKZwz2/3YHZIG3i1XM1tdW6jZ0JPovRRGDVGLA4Lt/98u8/rn2n9DMObDC+PCMg7AV/fUR5NAGCMxfWfRTy15xPWpa0DQCFT8FTzR3mwoBDFhWUPz5HUBctdM3lzz1QWH1vs0RWiCeHrfl/7rTjhsttxZmfjyMtDplSiCAlFFRVJsa2YM8Vn+O7Qd2SYMuga15WeiT2JC4ir7FPmTfoe+PwG//0PLII6PS86TYmthDxLHiaHiUBVIOGyAGQFxbjtduQGA6pI/+JTWr6Jnh+sxerwNtcE+ODuFgxq8++N7BIIBAKBbyq7D63Wp5aePS/+RxAkE8VVq1ZV51aCawCtUkuELoJsc7bP/sZhja/wigTXPTKF5J7vD3UgCF+Ny4qzpATTtr/IfPMN7GlnQSbDcENXol8eh1pvg70/SI76jftDWF0IuGDjUpQmRRr4w+0CZ8Xu9d6LcoDbedmNNCP1kTUSBXAxjuUfY+zasR5tCpmCE3l5uKyFmK1uYoJ1hBnUGHVVT5vQK/XoA/V+T+ErS3xgPPP7zefDHR+yPm29VN7QDXVD6pZtqguthYxoOoKZ+2Z6XNssvBkD6gzwTCcIrS1FDuSfhOwjEFYHwmrjCoiifmh91qWtQylX8kWnN2helIvi7J/+F5d1ALu10Es8AMi35jNt17Ry/4ULkKtUyGNjUcV6RvEEqgNpFNaI8Z3G43A50Cg0Ht4ODpcDp8tZaR8JAFQXie7RXdwgMaM0g7e3vc2fp/8kSBPEl83fxjljAaUr/wCnE1VcHFEvj0Pfvr1Poc/ucvsVDwCyii0XXYNAIBAIBP6oloCwZs2aCvtlMhlut1sYL/4/IVIfyZOtnuTVTa969dUy1iLR+O82vBNcAoYwqSb84lG++zs+JtWOv14w5Uul6hQq7432NYpl/37OPP54eYPbTem69Zw6fIRa749Gtf59qX3rNEjuDnd+DoH/5GmXZMGix6Dbc/5vEJwElXXVL82B3KOw7QuwFkOzuyGpCwRGSeaa1yHF1mKm7prq0ZZsrM3oZu/xyo+pnC3cAkjR7YNaxfFi30ZEBEobVovDQq45l2xzNmq5klBlAJGmQsngzxBR/jrUEEq5krohdXmn2zuU2EqQyWSEaEI8NtBBmiBGNB3BLbVu4dfjv1JkK6Jfcj/qhdTzbf5njJG+kjqXPyelNm6O78+3h77lkbp302z7fNR2E4TX87+40GSOlaT57V6RsoLRbUZfkiGoUq708IooshZxpkSKTMg2Z9M9oTs3xN1QuTQiQ7hkIHpynXdfcJL0Xq6AfEs+49aPKyst+WbD51COfYvSk+UinT0tjTNPPEnCjM8J6NbNewlqBcnhBk7mlPq8R7taVa/yIBAIBALBOar1iczl8q1wFxUVsXPnTl5++WXi4+P59ttvq3MbwTWCTCajZ0JPrO2tfLrrU4psRciQ0TWuK690eOWKnOQJKofb4UCmvE42XHV6SCG9x1d7tre4D6KaXp01VRVrCWTug5UTIGMPGOOg2/NQt5e0obhGceTnk/W///nuy8zEfLoQVUhyeYTByTVw8Fdo97C04zXlQJdnoDDN92sI0Pfdym10Tbnw51uw/avytqMrpKiHAZ9A/mmo1RWCL+GU3WmXBAml9qLmfjWN2WnmWMExj7Ynmr3C6PkpFJjKqxS43bBgZxpxIXqe7FkXk72YRcd+4pO/P8XmkiI4wrRhfNDmBZpvmIaqKA0Gz5dM+apIXqmV9EILW07kYVAr6Fg7jMhADXqN9DsjUB3o1wMAJBEhSBNEo7Cq39vtdvPHwUyW7M1mzq1fEGwpQvP7JCnSqNMT8NdX3l4aAN1f4e/iFP/z/vNfdSm2FbPw6EIm75hc1rYhbQPhunDm3DLn4kK5LgRu/xS+uQeyD5W3B8bAkB+l/1dAjjmnTDwI04YRn+PGetJ3hE/mO++ibdwYZbjn75iIQC3jb2vMiNl/eV3TLM5IUth1JMoKBAKB4JrjsuwwjEYj3bt3Z/ny5TRr1ow333yTCRMmXI5bCa4wwdpg7mlwD90TulNiL5EMpDQhBIoc9WsC+9mzlG7ZQsnqP1FGRxN8912o4uJQBNSQ2/7lIDAa7vgcco7A7m9BroZW90sO/tfw5rsMtxtOrIHvh5S35R6DRY9Ch0ehxyugDbpqy6sIt8WCZf8Bv/2lfx/E2KieZ4rClmnQaIB0kupyweLHJKO7O2dAVBP4e570fVQTuHkSxHeo3GLyTnqKB+fIPQb7f4KCVFg9CR5cAqHJlZvT6YDC07B9NqSsl0pKdn4KwhuAPuSil9cEGoWGhIAEcsySaWCkPpL8Qj0FJt+pYDM3nOTeNnEcKf6LD87bxALkWnIZuXk8i7q/T+KcO2DObTBybZUqlWQXW5iweD9L92eUtcll8NadzbitWQxqlZsccw6F1kLUCjWhmlBCdDX3XGUWWXh/+WFevimOBn9/g6tWF6nD5YQtn8HAabD0xXJjVYUabpoAcW3oYPK/+b456WaCVIFgKwWFFhSXlvqUY87xEA8ubH+z65sYVBcxIAxOgqG/SOVMc49K34cmV6qkaUZp+euSZEyCXf5/Pm0nTuCy+E5HaFcrhFkPtmPSbwc4mVOKRinn7jbxPNGzLhGB2ouuQyAQCAQCf1zWI8rAwED69u3LrFmzhIDw/wiFXEFMQNVq0AsuP7bTpzn1n//gyCrfmOTPm0f0xNcIuu025IZr2HU7IFL6qtX1aq+k6hSnw+9+Qvi3zYB2I69ZAQG5HEV4OM6cHJ/d6pgIMF9Qxs9aJPkTAKTvklznARYMh9o9oc9bUtqJvRTCG4LWh7hoLQZLkRTFYIiQUj7+nud/nft+gptehSPLYNUk6YRXXYn3c/ZByaTT9k8o99mdcOg3aa72j1wRc84gTRCPtXyMkStHAhCuDSc1z78nRLHVgclm4dPd033221w2lmfv5JHETnBqE2Tur7SA4Ha7Wb4v00M8AHC54aWFe+lYR8ufZ5fw2e7PyowUG4c25t1u71IrqFal7nExZBYzc2+JJeTADnLygjCEh6G68W2UG1+DY3+ApQBu/UBKWXHaIaY5GONBrSdWDv1r9+fXE796zBmkCeLJ5o+iXz8ZzvwFUc2gzYMQnAiqqm2WN53d5Lfvz9Q/KbAUXFxAAElgC4yChHZVun+4rlw0LbIV4Y7yX7JVbjAg8yOUBGpV9GgYSZM4I2abE6VcRliABq3qOvCUsRRCcSYcXwVOqxTdZIwHvUi9EAgEgmuByx7jLJfLSU9Pv9y3EQj+1ThLSsh8510P8eAcGa9NRN+xI5prWUC4nrEUSCKCL9xuyDoA4XWv6JJ8YsqTDA+PLJfW1eAWlMYEwh4aQda7PtIYFAoCOraA3yZ5ttfpJZWkAyny4hxut/SB//g/hrkKNTy1w/Nap0OKKFg9SdosqvTQdgS0vUipTodVEhkADv4MN0+8uIBQmgu/PF0uHpzP6knQ+PYrVt2jcVhjXmz3Ih/u+JAMUwa1E/1XRwgzqFG6SjldfNrvmAMlZ3AFxiAHKXKnfp9KrSO72Mrn64/77GuZEMSmjHVep+8H8g4wYvkI5t86n2hD9TwXnKWlqNatxjVhArn/FIDK/mwmho7tiXliBqolw+DMdlgwQqrekdgZ7v26LO0kRBvC2LZj6V2rN3P2z6HIVkSPhB7ckdSH2O8egMx/TutProNtn8OQBZIfQRWMWK0Oq98+l9uFC//mhDVBuC6cWsZapBSlcKzgGPbWDUGlArvda2zI/fehCK84Sivyeos2MOXDX1/An2+Wt618FZoPht5vQIAPnw2BQCAQXFFqrk6VD06cOMGPP/5IrVq1LudtBIJ/Pc6CAkr8mZq63Zj+8s6FFdQQ8ou45lfmpPxyU5oDq1+H6V2l///5Bkzvimz1RIL69SGw7y0ew2VqNfHvTUJ1YIYkDJxDpZMME8/5CIRUkEoQGAOKC9zrc4/BF93h0BJJFDDnw/oPYP49UkSAP+r1hlMbpX+7nNLXxbDkSxEHvnC7pZPqK0SQJoi76t/FLwN/YXL3ybSIiyY2yPfG7qketQnJ3khykP/ntkVgEvLCVOmbiMr7EDjdbnJLfEc/DO4YzMz9vqMess3ZHM47XOn7+MORnkHm+PGe7ymgdMs2CreewJ10XgRSaG0YONXr1DlMF0b3hO583PNjvuz9JaPq3kPczFuRZV4Q6u9ywMKHoNgz2uJidI7t7LevZURLjOrLW145Qh/Bpzd9Si1jLQA+OjMP/YdvIFN7ik66jh0JeeAB5KqqV+24psk75ikenGPPd5Diw5hSIBAIBFecakUgjBgxwme7w+EgLS2NDRs2YLfbmTRpks9xAoGghnC6pHx0P7hLTVdwMf8ydKEQ29r3ZlWlh7AKnOWrSmmuZFxYmiNtrAwRlfOJSN8N22d6t2+fibLhbURPmED4Y49j2bcPhdGIpmEDlHqQb9ogGQ86bdImvtdrnqJB87th/ftSqcYL6fKsp+O8tUQSLuxm77GZ+6DgFDTqL5k0no82CFo/AN/dL30f17ZyKSEX89PztebLiFapJUgThNPtxO4qZO5DbRn7w152nymU+lVyRt1Yh/6NjAR9/RbP9J3Eo7neqX86pY6bwlpA6qvlhnzH/oCY1lK6iEzu98Q9QKOkfa1Q1hzxjlQKNsjINGX6Xf/+3P3cmHDjJTzycgqX/Oa3L//7xWhnf4wlcw32kFoYIhpjDKlFgclGap6JhTvTKLHaub1lHA2iAok0/hM9kr+7PI3mQky5UJoNQXGVXmOUIYpbat3CspRlHu0quYpxHcYRpLn86UhJxiRm9plJtjmbXHMucn0CSb/9gv3gYRy5OehatEAVE4My9P9ZSL/DBls/99+/8SOo3R30/tM6BAKBQHD5qZaAMHv27Ar7GzRowNixY3n44YercxuBQHAR5AEBaBo1wnrwoM9+ffv2V3hF/yIMYZLx26y+5cZvIG3i7ppZc6X2Cs/AT4/CqQ3lbfHt4a6vpFxvf1hLpA/e/tj4EcrB36CsXw9t/QvEjlvegm5jpRNjTZC3n4ExDu6aBT89LOWrn6P5vdDotgvWUSRtdP2xbxH0/0Qq27hthpR6UKcnNL8Hlr8iCQ8KFfR7r3K50LpgiGkhiScXIpNJz90VJKM0g7e3vc2fp//EjZsYfQyv9H+baE1T7E4ZQToVkUYNGkseqPQ0PbWDCS2f4v19X2FySAJgrCGW91qPIWbVG+UmlX9MhC5Pw+Hf4PBSqWRm2xFS2swFG61ArYrn+zRg/bEcnC5PhcXhlBOsCabAWuBz/XWC6lT7ObBn+I8GcOTnc6g0k1czVpKbkkvryNa81uE9Zqw9xZcbyk08F+xIo1ViMJ8NaUN0kLZC4RSoXLTKeYRoQ3ix/YvcEHcDs/bPIt+ST/vo9jza4lESA69cqeIIfYRnWcxQ0CUmXbH7XxVcdv9iEEhpWE7vVA6BQCAQXFmqJSCc9FNaSC6XExwcTGCgcOYXCK4EyrBQoidM4NR//gNOzw/MgbfcgjK64trjgmoS0RAeXSeVMTz+J0Q0gGZ3S+Z2Sv/57pXGlA8/P+UpHgCc2QYLH4bB30pChi+cVk9h40LMeVKEgS+UWkkk8IfaAPVvgSe3Q/oeSSSIawMB0T6qHMik8b4iEECK5NCHQIdR0HSQJCDkHodlL0mGag1vlSpahFXST8IQDv0/gpm3gOMCp/obnpNMO68QeZY8xq4Zy56cPWVt6aZ0nlzzICObj+TR5o+iVvzzPgmIgIGfYZzVl4G1utKl3XjylQr0+ihiNEForaVw2xRJUPr9OejzNvzxmmfJwD3fSaU2e7ziJbbUiQzg+5EdmfDzfg6kFyGXwc2No2kTn8gI9wifFQgCVAE0i2hW+QdsN0uv2dmd0usY3w6MMQT27EnRosU+L9G2bsX64gNl3g+ZpkzO5Fs8xINz/H26gF92p/Fw19rIDeGSaGIt8p5UbbiknPlwXTgD6g6gS1wXnG4nAaoA9CpR+vCyo9JD/b6Sh4Uvkm+UhEyBQCAQXFVkbrf7YoGegitIUVERQUFBFBYWYjRe3lxLwf8vXBYLtpMpZH38Mebt21GGhRE6YgSBPXt41QkXXEbcbumEuybJOQqftvXf//hWiGzou8/pgDVvS6kGvrjhOeg+DhQ146mbZ87jTMkZ/kz9E61Cy02JNxGpj8SoNMC6/8Had3xf+Oh6yXH/QkoypVNkTWDVTQ8ddihIgS3T4fRGCIiCrqMhuvkVdXQ/lHuIu3+722efTqlj0e2LiAs4T6hxOqSUju2zIHWLJEYFJ8KKVyRRRaGChv2h0xOwdwFs/cz3jR9eDfFtfHblllgptjhQyGWEGlQYNCpyzbl88vcn/HT0J9z/5ICE68KZ2nMqDcMaIpdVwjbJWgKHl8DixyUfgnO0egB72xc5NWwE9jNnPK+Ry9HP/oShJyeSZ8kD4JnWz3LoUBsW7EjzeZv4EB0LH+tMlEEB+xZKZVMvZMCnUjRMTYh4lcVhld6zpdlSJQlDhJRqUtO/E/6/UnAavughpWmdj1ILo9ZDeP2rsy6BQCD4F1DZfWiNVmE4ceIEhYWFBAUFUbt27ZqcWiAQXAS5Vou2YQPi3pqIy2wDtQaVEA6uPNXcKLjdbnLMOTjdTvRKPUaNUSp7WBG+Tl/PoVBKHgJ/fSlVjDgfbbDUV0PiQY4ph9c2v8baM2vL2j7d9Smjmo/iP43/Q1CbYXBkqXdaQbcXITjB96QB1YieUaogvJ6UimEtlipDaK+8MFtRRQWzw0yp/YJKEQolhNWBXq9Kp/lpO+DrgeX9Tjvs/wka9IX9C/3feMdsvwJCWICGsABPk8swXRjPtX2O4U2Hk16aToAqgAhdBJH6SGSVfV8Xpkqb+QvPJv7+GlWdniTNmU3WRx9TtHQp2O1oGzdGPnYkU/IXlokHAL0Se/PXLv/h7CVWh3QLhQoa9IMRK2DNW1JVirC60P1liGx8ZcUDc4Ek6KwcD/Z/fGcCouDu2RDfVnr/CSomOFF6LVeOl1Jy3C4pranvuxBcgWmrQCAQCK4Y1f7UWFhYyIQJE5g7dy5FReUfYo1GI8OGDWPixIkEBYmQM4HgslOYBod/R7H7WxQKNbQfCZrONZeDL7js5JpzWXV6FTP3zSTXnEvziOY82+ZZmmgCkctk3puyc+iCK544OAkeXimVQzvyjzlcvT7Qe5LUVwM4XA7+TP3TQzw4x/Q90+mW0I1m4c3g/u8hc790aqwLgRaDIShB+vflQqmRvqqJ0+Ukw5TB7sy/SSk+RbPw5tQLqXfR8oaRev/pEgqZAp1S56dTJW1Kl7/sZ0FWsFt89wHYSyWPAHnlCy4FqAMIUAeQZLzE98Xf8/y/T9e8herB34mZ+BqRzzyN0+kgT25mzN+vsT9vPwBGtZEJnSYQqQ9jQAsly/f7FhFuahhJkP6fjzBaIyR2gHu+ljbuKl3ljDZrmrM74fexnm0lmZL48/gWqbKE4OKE1YE7Ppc8D/jHf8UrJUogEAgEV4tqCQhZWVnccMMNHD16lODgYG688UaioqLIzMxk165dfPzxxyxdupT169cTGXnl8k0Fgn8dhWdgTn/IO1HednqzlDN654xrT0Qw50s50ifXSq7xtW+UTuquxof+a4QCSwHvbnuXpSlLy9q2ZWzjP7//h9/7fUdcw/5w8BfvC+v2Av1F8rxlMin0984Z0oYUt7Rhr2pKgB8cLgcnC0/y9cGv/Y757uB3NOrSCGVgjBTSXbdXjdz7SuFyu9ifs5eHV47E7Cj3cYg2RDOz90wSjH4iKJDMD6MN0WSUepsI9qnVh1CtdzpFvjkfi9NCuLUUVdYBr34ATm2WqmPsW+C7v/ngKokH1cblgPwU//0lWeByIA/QIY+LQwVEu118FPIReZY8XG4XobpQInQRKOVK2iTJqRNh4Hi2Z4SGXq3giR510aku+AijNV6VCBNA2uyuft13n8MKe36E7i9e2TVdz1xKypJAIBAIrgjV+mQxbtw4jh49yksvvURqaiqrV6/m22+/ZfXq1aSmpvLiiy9y9OhRXn7Zz+mJQCCoPk4n7JrvKR6c4+Ra3y70V5PSHPjzLZjWAZa+IBnBfdoONk/958Tp30mWKctDPDiHy+3i6Y3/xd7nLWh8R3mKhEwGDW6FAR9X/nROEyilCgQn1uiH8yxTFn9n/U2xzX+qRZ41D2cVHfGvJbKKz/DE6qc8xAOQqiuM3zieQmuh32sjDZF83utzYgwxHu3totoxus1oDCpDWVuxrZgtZ7fwyMpH6L2wNwfyj4A6wPfE+3+SfBA0PjbNsa19e0pcTuTKioWhuLaSseH5l8jkRBmiaBTWiCbhTYgxxKCUS8JAdJCWrx/qwKgbaxOkU6FRyrm1WQy/PtmVpDCDrztcPRwWyZ/CH+l/iwoCAoFAIPh/QbUiEH799Vd69uzJW2+95dVnMBh4++232bp1K7/84uPUTCAQ1AymHNj1jf/+7V9JkQgq7ZVbU0Wk7ZDK9F3I2nelGt9Jna/4kq4Fdmf7F3qOFBzhrMxF0oCP4abxYCmUTlr1EaC7+lEbR/KPsDdnL22i2rA8ZbnPMTcn3YymBtIILicWh4Vccy4F1gK0Si0hmhBCdVJ0wNniM35LHO7I2kG+JY+gChziawfXZl7feWSYMsg15xIfGE+4LpwQbbn443a72Zq+ldFrRpe1zT61lDda3o/B18+M0yZVrxi5BjZ8BEeWgMoA7R6CZvdcncijujdJFTAuNMGTyaX3bhWjjGKDdYztXZ8HO9fC7QajToVBU8WPLqY8cDtBGwoKRdWurSxKreS9kLbDd39sayklRSAQCASC65xqCQilpaV07NixwjGdOnVi27Zt1bmNQCCokIsUUrmWCq2YC2HjFP/9mz6F2JZSOa9LoMRWQqm9FKVcSZjOT1nDa5TzT6EvRIZMcsC/miHaFZBlymLZyWV81PMj1qauxeL0zMuP0kfRKaZTzd/YYZWMIWVK/2UsK0lmaSZrUtewO3s3OeYctmVso05wHd6/8X2SAxMoLPFOPzgf6znTvAqINEQSafCfzpdtyuadbZ5VKlanreN41/donL4bZerW8g6FSsr5D4yWxMF+70KPcdJG3RBxRVIXcs25pBSm8PPxn5HL5Nxe93aSjckED18Ky17GpYvGGdEGmUKJolYTZOENLuk+KoWC6CA/PhEVUZQulVbdNkPyi2gyCFrcK0Xg1DT6UOg53tPs8hxKDTS7q+bvKRAIBALBVaBaAkLTpk1JSUmpcExKSgpNmzatzm0EAkFF6COkUmVr3/Xd33b4tRN94LRK5c38UZqF2VKIWqFBIa/8SaHVYeVk4Uk+3fUpu7N3E64L5+FmD9MpplPZCfK1TrOIZihlShxuh1dfl9guBGuDr/yiKknjsMZYnBam7ZrG5O6TmXtgLlvTt6KQK7g56WaeaPEEMQExF5+osricUq795mlw/A+pmkTnJyG52yVVbSi0FJJtzibfmo/JYaJ2cG0eaPwAC48u5KHlD/FT79nUOr/M4gUEqgIxqvykGVSBYnsxmSZP00CX28VDm15hYvsn6dbzvzhPbcShC8ZY92ZUxvjyn22VTvq6QmSbspm0eRJrzqwpa1t4dCF9avXhv21fRtf5XXKmf07p+i+QBwQQ8sB/MN4Sjyry0sTBKlOcAQtHwKlN5W1Zb8COmTBi+eUREWJbwW0fwor/gu0f34bAGLhrlmQUKhAIBALB/wOqJSC8/PLL3HvvvTz44IP06uWd97hixQoWLFjAggV+DJ4EAkH1USikUny7v5Nqx59PYifpQ+21gjYIkrtDzlGf3aakzry/ZzoRhmhur3s7sQGxlZp2X+4+Hlr+EE63lGNfYC3gpfUvMajeIEa3GV1haPm1QoQugje6vsG49eNwnxdVEqGL4KUOLxGovnYNxWIMMbQIb8Hu7N2M2zCOO+rewd3178aNmxBNCInGGt6s5R6DL3qCraS8beHD0Ph2uHWyFEJfSVxuF2dKzvDoykcpspVXEvr20LeM7zieUnsph/KP0FgZSL+Em/g9dZXXHE81e4QIQzXKTf6DSu47xN3itPDizvd5vfPr/GY9TnpeOtMb30ZCVYTBKlZjuBg7s3Z6iAfn2Ji2EXlMBicHP4DbJEVlOPPzyXrrbYr/WEXcB++jiriI6WdNkL7bUzw4R9FZ2PallE5R0ykFumBo+R/JB6I0W/KEMERIIkI1y7sKBAKBQHCtUC0BobCwkN69e9OnTx9uvvlmunbtWlaFYf369fzxxx/cdttt5OfnM3fuXI9rhw4dWq2FCwSC8whKgOG/w/5FsOd7qd54+5FSdYPAGjz5rS5KDXQcJXk2XBjyrQ0iq15PFqx9Gjduvj/8PfP6zSM+ML7CKXPNuUzcPLFMPDifhUcXMrTx0OtCQNAqtfRI6MHi2xfz6/FfOVNyhm7x3Wgb1bZmT+8vA2G6MN7v/j6f7fqMX0/8yuz9s4nUR/Js62dpENoAWU1unixFUjnK88WDcxz4Gbo8WyUBIaM0g0mbJ3mIByAJC+9ue5d3u73LrrzDdNQk8HzSbdQOiGPu8cUU2YqIMcTwdKOhdI3vjlJZ/SifYE0wnWI6sTl9s1efVqHFqDGyNWMrdYLroFdW4iTf5YLCVKl0Z8oGiGwkeSMExVc6Kim9NJ2j+Uc5nHeYusF1aRjakEB1IF8f8F1x4/7EOyj8aGqZeHA+5m3bsKWkXH4BwWmHnXP89+/9ATo+BsbL8HOlVEvRDZcjwkEgEAgEgmsAmdt96QnScrkcmUzGxaY4/8Oj2+1GJpPhdF6/btyXk6KiIoKCgigsLMRovPZynS/EkZeHMzcXl8WCIigIZXg4cv0VClEVeONySSUSZfJrt2620wHZB2HJc5C6RWpK7kZmt9E8tedTjhSURycMbjiY59s+j1qh9jvdycKTDFg8wG//xM4TubPenTW3/ivEud+V1xMWh4VcSy52px2dUkekPrLmH0PBGfioGbhdvvu7joFer1Z6uqP5R7nzF//vj0mdJ6GUK7khP5NgmQpnQATZCiV2hRKNOoDIoKRLSpvwx+mi04xYPsIjlUEpUzKxy0QWH1vMXxl/8cXNX9Axttx/KLM0k/25+9mYtpHYgFhuSryJGH0MFJ9FtvkT1Id+h+J0abBcCfd9J0UCKSs+gT9RcIIRy0eQa8ktawvRhPBF7y+YsnMKG9I2eF2zvMtcCgcOBYd3Kg5A8H2DiXm18q/PJeG0w4IRvsuegiSgPLzq2itvKxAIBALBVaSy+9BqRSDMmjWrOpcLrnOsKadIGz0a68GDUoNSSciQ+wl/5BGU4ZU/ARTUIHJ5tc3kLjsKJUQ3g/u+xW0p4GxpOksztjBn66teLvdLTy7l4aYPE1VBeLhCVrFXgk5x5fLCa5LrTTwAKYoirgKvgOricruwKZSo6t+C4thK32XxqhiW7vInRPyD1WklVBuKxeCE74ehCK1NdP1boPWDEFG/xkPTE42JzOs3j73Ze9masZVIfSSNQxvzzaFvyLPkMePmGTQLb1Y2Pq04jYdXPMyZkjMA6JV6InQRHFEc4ucTv6LQyhl86xvULy0i/PcXpcoNC4bDY5ulkp5+yDXnMmbtGA/xACDfms+za55lYqeJXgKCQqbAqNBSpFbj9iMgXBGBWaGSvF/8CQgth4Be/I0SCAQCgeBSqJaAMGzYsJpah+A6w56ZyekRI3CcPVve6HCQP2cuyuBgwh5+GJlKlKwSVIA+FHQhfLr/C3478ZvPIXLkF91IB2uCaR/dnm0Z3tVeFDIFTSOubRNXl8WKTKlApqzWr+P/1zhcDs6WnOW3E7+xO3s3dWs14c5OI4nb8iXaQxe8dxr5j0a5ELfbjUFlIEof5WVeCFL1i5aRLfnwrw95I6yt1Jh3AnbMklJxLpPIE22IJtoQzc21bsbmsJFryeXlDi+jU+oI15VvfE12E5N3TC4TDwAmdZnErH2z2J+7v6ztzzNr6B7TmVdv/R/hvzwL1mIoOA3BCTicLjKLrBSabaiVckINakINGvIseRwvOO5zfWeKz2BQGQjThnkIDMGaYFz2NIL730L+9z/5vDaoX59qPjuVJKop1L9FSt84n9Da0HqoJGQKBAKBQCCoMuIvqOCSsKWkeIoH55E7cxZBt9+OKrZyBniCfy8ymYxB9Qb5FRAG1BlAiKbiVAyjxsh/O/6XoUuHekUwTOg0gXDttXnSaD97lpJ16yj+YxXK8DBChgxBnZiIIuja92u40hzIPcCI5SOwOq0AbALmHf2Rj9qPp6s5D+U5s7yOj4OxchEQWaVZrDq9ir8y/uLJlk8yftN4rzGDGwzmj1N/cEt0eyK2nJdTf8NzYLgy4e9qpbrMA6PIWkRKYQomh4lAVSAKmYI1qWvKxjYNb0pKYYqHeHCONembuCfhJm4IiofCM2A3U2CysWRvOu8uPUSRRYoYaBpnZMq9rXApK47McLgczOs3j6/2fcXSk0uRIaNfcj/0aj26O3tRsnk79tOnPa4JfeBelGFXKDUvIBL6fwxnd8DWz8FhgeaDod7NUgqDQCAQCASCS6JGBISUlBS++eYbdu3aRVFREUajkZYtWzJkyBBq1apVE7cQXGNYj/s+mQJwFRfjslj89gsE55MclMzNSTez8tRKj/YYQwz3N7ofVSVC0pODkvn+tu9Zd2YdG9I2EBcQx6D6g4gLiEN3BUvbVRbb6dOc+s9/cGSVl7QsXPwz4c88Teh//oMi8NqouOCy2XAWFIBMjjI87KqkVWSbsnlx/Ytl4kHZ2twuxu38gJ+6v03M1i+h0+MQ0aBS3h9ZpixGrxnNnpw9AGiUGj7t+Smz98/mYN5BovRRZVUkzhSmcKPWKLn6B0ZD93HQ8DZQaSq+SdFZaaNekgUhtaRrq2DueCEZpRlM3FyeNqCUKbm97u283uV1Xt7wMk63kxvjb2R5ynK/c3xzZjVt6/dGt302RDZgy8k8Xlm0z2PMvrQi7v18Mwsfb49KrsLu8k4TUcgUhGpDiQ+M56V2LzGq+SgAQrQhKEuy4fdBJL05DtOJPIrW/IXCaCDk1u6oVPkog6+gN0tgFDToB7W6gdspVYERCAQCgUBQLaplogjw0Ucf8cILL+BwOLzMFFUqFf/73/945plnqrXIfxPXi4liyebNpA4f4bNPbjBQ+9dfRASCoNLkmHPYn7OfeQfnYXaY6Zfcjx6JPYgxVN0l3e6yo5ApkMtqrmRdTeIsLSV9/HiKf1/qs7/2kiVo6tSu1j1KbaVYXVYCVAEVGlD6w+12Y09NJXfOXEpWrkSm0xFy/30Yb7kFVVTNGQZWhouZHM69ZQ6tQhtXuqoAwJrUNTy1+imPtjBtGCObj6RtdFvcbjdFtiKi9FGEaoIJsBSD0wpKbeVK8mUdhHmDoCitvC2pCwz6otIREueTZ8njmdXPsCt7l1ff7XVuRy6Ts+jYIp5p/QyLjy3mVNEp70mAdtHt+MQVjkFlILvdWO75Yjsnc0p9jv3kvpbkKf/g/e3ve/UNaTiEp1o/hUFl8L7Q7YaMvTB3ABgicMW0QeYwIytMhXtmi+oEAoFAIBBco1wRE8XffvuN0aNHEx4ezujRo+nRowcxMTFkZGTw559/MnnyZMaMGUPdunW59dZbq3MrwTWGJjkZZWQkjqwsr76QoUNRXIk634LrHmdxMc6CQoy46WJsSdsebXG6nASqAy/5tFslv7a9N1yFhRQvX+G3v2TtmksWEAothRzOP8ys/bPIMmXRJqoN9ze8n/jAeJTyyv+6t6emcvLue3AVFpa1Zb39DkW/LyX+k49RRUZe0voupNhWjNVhRa/So1f5NtfzVZ7zfBwuZ5XEA4fLQV7RGT5o/Tz59hLmn17OicIT5FpyeXvb24Trwvn+1u9pENqg/CLNxcVcs92My+3CYCmAr+8or3pwjlMbYeVr0H8KqH1svCsg15zrUzwAWHJyCR/c+AGLji1iR+YOusV381ticWDsjRh08RDTEptN7lc8ANh5uoDRve9AIVPwxd4vyLPkEawJZkTTEQyoM8C3eACSuBLdDB5dDzmHkeefhqgm/0Rh/CM+OZ1QkgluB6h0YBB/LwQCgUAguF6oloAwefJkQkND2blzJ/Hx5TmFSUlJdOjQgSFDhtCqVSsmT54sBIT/Z6iio0mcPYszTzyJ7eRJqVEuJ/jOOwkZcj9yYaAoqAC3y4XtxEky3noL0yYpf13Xrh3R//0v+rp1rssKBJXF7XJJGyg/XGr6T7GtmPmH5jNt97SytiP5R/jp6E/M7TuXxmGNKzWPy2Ihd8YXHuLBOSy7d2M5eKhSAoLFYSHHnEO+NR+NQkOoNrTMALDAWsDB3IPM2DODsyVnaRzWmFEtRpEYmOiVchKsCSZEE0K+Nd/rHkq5sswfoFI4bCjyjjNg/wqUqVtBH06vtsPYWc/Aczv+h8vtQilXVun9l2PK4UDeAb45+A1y5HxQ+270F4oH59i/EHq8AqFVExB8GTyWPSSXg1BtKM3Dm7MxbSMPNH6A5SnLyTJ5irvJQcm0T7oJjNLfaoXdRGSghqxiq69pqRcZgFFj5P5G99MrqRc2pw21Qk2ELgKFvOLKJ5Rkga0UgpIgppVnZZjiDNg5F7ZMk0rORjaCPm9BXFvQXrtRdwKBQCAQCCSqJSDs3LmTIUOGeIgH55OQkMA999zD/Pnzq3MbwTWKpnZtkr6eiyM3F5fJjDI0BEVYGIqAgKu9NMG1grkASnPAYZbyjwOiQanGnpZGyn334SouLh/611+k3HcftRf9hDop6ZJv6SwowJ6dje3YMRTBIaiSElFFRSFTXGTTc4WQBwaia9cO819/+ewPuPHGS5o315zLZ7s/82q3Oq1M3DSR6TdPJ0R78fxzZ2EhxX/84be/8KefCLihKzK5/xSRPEse8w7MY/b+2WU59EnGJD7s/iHxAfEsPLKQKTunlI0/W3qW1amr+eymz+gc19ljrghdBK90eIXn1j3ndZ9nWj3jUZXgomTuRTazD8pz5R+LMwhb8jxdmw5iTOPhvL//KwbVG0SoNrRS0+WYc5i0ZRJ/pv4JQJQ+ipLcI/gtVOhygsNU+fX+Q5jWf2lWuUxOqDaUqTdNxeK0oJQrmXPLHBYcWcCSk0tQypQMqj+I22rfRvQ/xo/27GzUq1bzWJtGTFyT6jWnViWna93wsvmjK2sY6bDB2b/h58cg9x+fnPB6cPs0iG0JliL45Rk4el5lhKyDUsTG4PnQ8CoeNNhMYCkAuQIMkZetwoZAIBAIBNc71RIQbDYbBkPFJykBAQHYbLbq3EZwDaMMD0cZfm263AuuMvmn4den4YS0uUJtgBvG4m41lILFiz3Eg3O4TSbyvplP5HNjkaurnrtvz8oiY+IkSlatKmuTG40kfD4dXbNm10SpRGVQENEvv0zKvffivuB3Y0Dv3qhiqu77ALAnZw9ufFvaHMg7QJG1qFICAjIZMrX/CCKZXlfh5srtdvPHqT/4Yu8XHu2nik4xYvkI5vWbxyd/f+J1ncvt4rXNrzGv3zwi9eURDrnmXNJK0viw+4d8f/h7jhUcIy4gjpHNR9I8vDlaZSXTF0y5sGQsOL1NAXX7FtKr9f38HFKPgXUHXvyE/R+O5h8tEw8A8i352EMqEL/UAaCuukFmhD6COsF1fJZV7JXYi1BtKAFqT+H2yZZPMqTREGTICNGGlD0mR0EBGZMmUbLyD7q//T7HWkQwf0825yyMgvUqvhzaltjgSzAfzU+BObd6Psc5R2H2rfDYJqkSwtFlvq9d+iLEtgbjpb3/LxmnA/JPwrr34fgfEBCNs8ckXAF1Qa1DGR5eoVgmEAgEAsG/jWr9Vaxfvz6//vorDofDZ7/D4eC3336jfv361bmNQCC43ijOgG/uLBcPQAppXjUJ9v6IMz/P76Wlmzb5FBcuhstuJ3/+fA/xAMBVVMTphx7GnpYK6Xukk1GLd3j+lURTtw7JixZhHDAAZUQEmnr1iHn7LWImjEcZWrnT7wuRUTMnpsrQUILvuttvf8g991QY4p9lyvIZCQFS6sK+nH1E6X0bMaaXplNoLX9trA4rn+/5nA93fsikzZOoH1KfR5o9Qvvo9nzy9ydYnFVI97AUSqfjfgjPOMCMm2dU+rTd4XLww+EfPNpsLhu7LFk4Y1v7vqjL01I1hvNwmc3YUlOxHDqM7XQqLpN3hEK4LpxPen5C3eC6Hu2dYjrxQrsXvMQDAKVCSYQ+gnB9uIcg4szJoWSlFGFiefl5Hjq1jmWDavFlvyS+u7MOS0Z1oFViCEpFFT8eOKyweapPgQanDfYuhLSd/q8vTAVrUdXuWQEFlgJSClM4ln+MzNJML5PnMnKPwefdYM93uINqYe3wFumfLebEwLtIuedecr/6CrsPrx+BQCAQCP6tVOs4bujQoTz33HP06dOH//3vf7Rp06asb/v27YwbN47Dhw/z/vveLs4CgeD/Mfkp0smjD2Tr/kdI31kUzP/OZ78yNATZJUQfOHNyyP96ns8+t8mEeeta1OlToCAF6vWBWz+4avXgZSoVmjq1iZn4Gs6iImRKJcow/2HqlaF5RHNkyHxGITQJa4KxEkaAADKlkuB77qZo+XJsF5RrDRp050XTS2wuGznmHL/9R/OPEmWI4mzpWZ/951fPyDHnsPjYYgDyrfnMPTDXY2xKYUrlw+uRSZETfjaSGk0QmiqkQ7jcLhxub/H8jb3TadDnHZI3z0Bx+Hdwu0Clx9X5KWRthiM7ryypPTubnKnTKFi4EOx2UCgwDuhP5LPPelW7SAhM4IveX5BnziPfmk+ELoJQbSjB2uBKrxnAeuJE+TduN9bZX8Hsr0gICMBtsxH24w8oIi+h3KG1BNJ8p+UAcGYrtBnuv18mBz8VQ4otdmwOF4FaJWrlxaNDThScYMLGCezO2Q1IqSUvd3iZDjEdPM0frcWSqGk3gTYIa+v/kjLiWdz/+JC4SkrI/mAyxX+uIf6jKaiEObBAIBAIBNUTEJ555hnWrVvHL7/8Qvv27dHr9URGRpKVlYXJZMLtdnP77beLMo4Cwb+NzAP++8z5qKP8n7KHPfwwisCqh3m77XZcpf5d5W1pGRAQKoUrH1kmGbgNng+6UMkx324CpUbKf66Cq391kOt0yHWXECp+DodFiuxQ6QnThvFkyyf5ZJdneoBOqePVTq9WLn3hH1TR0SR+9SWmnTspXPwzcoOekCFD0CTXvmiEhFquJkwbRq4l12d/3eC6rD692mdfclAywZpgnC43uSVWSh1mbC7/KXBnS3yLED7Rh+GucxOyYz78HWQyqNW18nMBaoWaO+vdyZrUNR7tLreLLKWKLQ1voEP7YSiddkpkMhamb2SwNY8Ghghk1mKcxYVkf/gZhT8tKr/Y6aRo0WJcxSXEvvkGiiDPjXy4Lrxqng8+UAT7fh+4SkoAkGk0lzaxSiuVaMzc76ffANHNpVKYDh+RIw36gsHzseWV2th9poAv1p2gcaye3s0DiAhQEaQNIFTn+3GklaQxbNkwCqwFZW2Zpkye+fMZ5twyh9ZR50WHWArLUiqcTe4n68tvy8SD87Hs3Int+HEhIAgEAoFAQDVTGBQKBYsXL2bOnDn06NEDtVrN6dOnUavV9OjRgzlz5rBo0SLkIn9QIPh3UVEeuEqHTB9I2MiR3pcNGYK2adNLuqVMq0UZG+u3X9e4HhScKm9I3SqZPO6cDTO6wadtpa/lr0CRHxf9yuJ2gyn/8qVK2C2S+dyS5yQDup+fICDnGPfWvYPZt8yme3x3Goc2ZljjYfzY/0fqhdSr8i1U0dEE9etH/CcfE/veexjatkUZdvH0igh9BKNajPLZF6QJIkIfwb0N7/Xq0yq0vNX1LZwOA5+tOcadn23ieKYdo9p/5ESd4DqVeiw55hw25+4nt/sLoPcR6dH7TQjwnVZREU3CmtAiooVH21317+Lrg1/z7u6p3Ll+LAM2vcT9G19k4YlfeGn9SzjzT8LCh3CePkTh4p99zlvyxx848vyn+VQHdUI8iuBgn336zp0vOYUGtQG6POu/v8vTYIyFe+fBhSVFQ2pBn7dBUy4cFphsfLTqCM9+t4uRPcOwGBfx+Np7GPBLPx5f9Ri7s3Zj8SFEbDm7xUM8OJ8Pd3zokSKDTAYKSTBxRXWidMNmv8svWurHu0EgEAgEgn8ZlxSBsHnzZl555RX++usvZDIZ7du3580336RDhw41vT6BQHA9ElEf9KFg8rEJajUMWXAsYQ8/RNDtAyjdtAlcbvSdO6GKjPQ6da0sqshIIseM4exz3m79qoQENA2bQcJkKVT64K9Qmi1FIqx4pXygwwrbv5Tyou/6yutEtFIUnoFDv8Oeb6XNSfuRkNTZK/f9knG74fRm+GaQ5OoPkL4b9i0k6M4vadP4dhp3+x9WpxWDyoBKUb2SqvIqnkjLZXJ6J/UmvSSduQfmloX5xwfG83L7l3l729s0Dm3MJz0/YUXKCtJL0+md1JvOcZ2RuVX8uOMYM9anUWR28N3mAgY3H86M/R953adecD3iAuMuup5sUzavbHiFzembpUoQd39BROp2gk9txW2MQdbuEQhJBk3Vq8dE6iOZ3H0y686s49tD32Jz2rg56WaGLh3qc/wLjYai/OYuyD2OM/FBcLn8zu3My4Pk5Cqv6ULcbjd5ljxcbhfBmmCUUVEkfD6d0yNG4Cot91tQJSQQM3EiCmM1SilGNIJb3oEV/wXXP+kdcqUkDkQ0AKUaat0AT/4Fx1ZBwWkp8iO6mSQunEdWsZU5m04x+b5kPtz7AicKj5X17c/dz9BlQ5nXbx7Nwpt5PNYt6Vv8Lu9g3kEsDgtBmn9+x+jDodUQ2PYFuGzINRpcfjydLiUqSiAQCASC/4/I3H6dhXyzd+9eOnTogOWCMD+9Xs+2bdto3LhytcYvN2lpabz44ossXboUk8lE3bp1mTVrFm3btvV7zZo1axgzZgz79+8nISGB//73vzz44IMeY6ZOncp7771HRkYGLVq04JNPPqF9+/Zl/RaLhbFjx/Ldd99htVrp06cP06ZNIyqqcqdbRUVFBAUFUVhYiLE6H+QEgpqiJAtKMqHorPQhPyAKAiIrvsbthsx98M1dkqHiOer3hf5Tam4zfQGOzFSKVywne+pXOAsKQCbD0Lkj0U8PRa13wKKRYCuBFvdBmwdh7kCpdJsvRm2E6CpGQxSegdm3SWkS55N8I9w5o2Yed9FZ+KKnlHZxIWoDPL5FCiW/ypjsJnItueSaczHZTaSWpDJ732zOlJwBpIiDHgk9GN50OIfyDjFz30xyzbk0i2jBfXUfZc5aE38eymfC7YkUKNbz3dHZmB1mZMjoEtuF8Z3GExvgP+LkHCtSVjB27ViPtubhzWkaXJfetW+lTUx7P1dWjXxLPi63ixxzDnf9epdXf5AmiAXNniX6x4cAsN66gBMPPO13vuRffkZbTQPiLFMWq0+v5ttD32J1Wumd1Jt7GtxDnD4Ge0YGlr37sJ0+hbZZMzS1a3v5LlwStlJJnMs6CMggoqH0+0Ltt7ilT2ZuOMnn647zwh0yXtv2rM8xrSNb83HPj8sFAWDarml+TTwTAxOZ03eOZxpIQSrM6Y8rsinZR5LJ+3aBz2uTf16MtkGDKj2GMpxOMGVL/9aHQTVFPYFAIBAILgeV3YdWOQLhnXfewWKx8Morr/DUU08B0qb69ddf55133mHu3LkXmeHyk5+fT5cuXejRowdLly4lIiKCo0ePEhLiPwf45MmT3HrrrYwaNYpvvvmGVatW8fDDDxMTE0OfPn0A+P777xkzZgzTp0+nQ4cOTJkyhT59+nD48GEiI6UN1ejRo1myZAk//vgjQUFBPPnkk9x5551s3Ljxijx2gaBGyT8F3w+BjL3lbdEtYPDXEFxBmoJMBlFN4ZE/pU21KU8KUw6IlCITLhPK0ysIdiwmYMpYnC4tcpUSRdYmFEuHQmwraHk/bPoEdsyGxgP9iwcAOUeqJiA4nbDza2/xAODkWqkCRE0ICKZc3+IBSJu3orOVFhAKLAUU2STne6PGSLAmuPrr+we9So9epSchMIHtGdt5Y8sbHv0Wp4XkoGRm75/N7yd/L2vfdHYDW9M3827X6RzP0jPp59P0btKGtzv2JCYEDGodoZpQAjUXPxEusZXw7aFvvdr35OyRvgqOML3XdI8N6KVyzmPiXORHqd3TjyMuIA5t5sGy75V5O9G1bYN5+w6vuTQNG1bbVDPLlMWYP8eUGQkCzNo/i1+O/8K8fvOIj4tHHXfxCI4qozZIXyG1qjWNTAYNo43syV3hd8zOrJ2YHCaP169fcj9m7JmB0+30Gj+y+UhvD4ngBHhwCfLTmwltmUjJlh3YTnr+DIc9NgpV9CX+7BaekX4v7J4vGWo2uwfajpDuKxAIBALBdUiVBYT169fTtWtXXn/99bK2iRMnsmbNGtauXVuji7tU3n33XRISEpg1a1ZZW/JFQkGnT59OcnIyH3zwAQCNGjViw4YNfPjhh2UCwuTJk3nkkUcYPnx42TVLlixh5syZvPTSSxQWFvLVV18xf/58evbsCcCsWbNo1KgRW7ZsoWPHjpfj4QoElwdTLix8yFM8AMjYDQsfgcHfgqGCTY5MJkUsGC9+SlwjuBxwfDWyU+tRnVqP1xlf2k5oet7JsN0kpTO4/YSRG6pomFaaCbu9N6tl7JgJtW+UjBovJ5UIKnO6nBwrOMbrW15nd7a0wWwe3pzxncZTN7guygtz1KtIviWfLFMWf2X8hVappU1UG6bdNK0sEsDtdmNUG+ka15Vpu6d5r8/tZMaB93igy6u8+auJFftzOJ5l5ruRHYkIrLzBpcvtwub0b8Joc9pw+Xv9L5EIXQSPNn+UyTsme7TnW/KRxZWLboq/pxL73GzOTCzFevBQWbu6dm3iP/6o2gLCgdwDHuLBOXItucw7OI8xbcag9lP14FrghnrhLNmTjlHtX3AMVAUiv8DKKcYQw5QeU3h+7fMeZT4HNxhM13g/RplBcdDsLlQOG4mzZmLeu5ei35agCAkh+O67UMXFX1pqVeEZmNMf8s6rfLFhMuz9AYYvEyKCQCAQCK5LqvwpMTMzk8GDB3u1d+jQga1bt9bIoqrLL7/8Qp8+fbj77rtZu3YtcXFxPP744zzyyCN+r9m8eTO9evXyaOvTpw/PPvssADabjR07djBu3LiyfrlcTq9evdi8WTJe2rFjB3a73WOehg0bkpiYyObNm30KCFarFavVWvZ9UVHN1cEWCKpFaTac8VOWLXUrmHIqFhCuNHJlxaeegdFgPs+T4eQ6qH8LHP7de6w+FEKrkH9ekglZB8BHCcUyqpYt5h99mPRYzk8NOYdKL22GLsLZkrM8sPQBzA5zWduenD088PsDLBywkETjpadA5JhzeHfbuyxLKTedkyHj5Q4vs6D/Ak4XnUYhV5BkTGJtqn/R+Uj+ER5pICv7/oGOSYQHVE18CVQH0r9Of/bk7PHZf1vt22ok+uB8VAoVA+sORK1Q89nuzyi0FqKWq7kh/gb0SV1BHSCl0VgKUS8fQeIz43BoRmHPN6NMrIsyKqrabv8Ol4NFxxb57V92chnDmwwnylADKQuXichALR1qh9I2/EZm4zslYXDDwYRpPX8HaZQaOsd2ZvHAxaQUplBqL6V+SH3CtGEXj1pRqlFFR6OKjibwppuQVccA2u2Gw8s8xYNzFJ6BfQug8zMgTKYFAoFAcJ1R5b9cdrudgABvsymDwYDdbq+RRVWXEydO8Nlnn1GvXj2WL1/OY489xtNPP82cOXP8XpORkeHlUxAVFUVRURFms5mcnBycTqfPMRkZGWVzqNVqgi9wuD5/zIW8/fbbBAUFlX0lJIgTCcE1grXkIv3F/vtMeVLkwoYpsOUzKR3AcgXEsVYPSJEPvmg9FPZ8X/79319D79ch8gLfFm0wDPkJAisZOWEthlWvS4+z4a3+x7UdUTPRB4ExcN/30GiA9O/zuXXyRasJOJwOFhxZ4CEenMPitDD/0PwKT+0vxrrUdWXigUFloFVkK5qGN+Wdbe9wsvAkz655lpErR/L06qdRyBV+55EhQ47U3zzOyC1NY5D5e239zSGT0T2hOwmB3r9X6wbXpX/t/shllfszaHfaOVtyljPFZ0gvScdkN/kdG6INYXCDwfzY/0d+vv1nfhn4Cy+0fQFVcBI8sFh6jwGY81GueQFNymw0XdqhbtyoRkoFykz5aGT+8+yVcuVFH3e2KZudmTuZu38uK1JWkFachsPl22DwcmDUqXi4a23CdBG82GYCMjxf+xbhLbi34b0oFd7nIGqFmriAOLrEdaF3rd7UCqpVqZSX86mWeABSBZY93/nv3/ujVEpWIBAIBILrjOrFqV6juFwu2rZty1tvvQVAq1at2LdvH9OnT2fYsGFXeXWejBs3jjFjxpR9X1RUJEQEwbWBLljajPs6OZfJwE8ddkqypFKIe3/wbO85Hto95P+6miA4Hu78EhaPAud5gmbze0Cl86hR745rg0wfLm3oCk5Bxh4ISoTIRmCMq/zJYEk27PoGcEOHR6UKDOeXiwRI6gIxLXxeXhUKrAWkFafx8+nfKYlN4NY2g6nvcBJx4DfoMArC6l1UpCixl1ToVP9Xxl+U2EsIVVTdqyLHnMOs/bNQyVU83fppYg2x7MrehVquZlSLUeSYc+gU24k1qWs4nH+YGEMMcpncZxpBl9iu5BQpmPFAG1rEBxMVVPnUhfOJNkTzVZ+v+PnYzyw+thilTMl/O/4XtULN94e/J0AVQLeEbkToIwhQ+a7EkGvOZcOZDUToI1h7Zi0nCk9Qy1iLexrcQ2JgIhofz7lCriDGEOM9WVxreGwDrtzjOEoyKTBG82f+Ab5YMYz7G91P/9r9idBXQ0QoOovih6Hc3e1Jlp5a7nPIXfXuIlTr//VNL03nyVVPciT/SFmbTqnjs16f0SKiRbVTXCpLiEFNiCGS+OC+dI5vx8az68m35NM1riuJxkRvP4NrCZm84p9Fhca/2CkQCAQCwTXMJX0KmDdvHlu2eH4APXZMKrHUr18/r/EymYwlS5Zcyq0uiZiYGK9qEI0aNWLhwoV+r4mOjiYzM9OjLTMzE6PRiE6nQ6FQoFAofI6J/sdcKTo6GpvNRkFBgUcUwvljLkSj0aCpYpk0wTWGpUgK97cUgjZIyp3X/j+ooGGIgEa3w4HF3n2N7/DvEXBynbd4ALD6dajdHeL9V0KpNuoAKQrgye2YT/9NaUkRQcltUB1fDr+Xl3d0RbXAfuunaHTBUkNgFCRcohu/KafcR+GXp+C2KZC2HY6skMrWtR0BdXpW20CxwFLAl3u/ZM6B8kiqX0/8SvPwZnzY+wMiA3xsVn2gUWgI14eDjwqbAGHaMNTyS8uNd7qc5FnymNh5Ir+e+JXNZzeX9X217ysebf4oPRN6siZ1DQA/H/+Z59s+z7t/vesxT7gunJfav0iMIQG1svoh3jGGGB5p9gh31bsLm8vGhI0T2JpRnnL3/o73Gdd+HP3r9CdQ7XlSbXVYWXZyGeH6cJ5c/SR2lyRMbUnfwo9HfuTjnh/TObZz5TfVcgUEJbCtNI3/7viCXHNuWanLD3d8yK6sXUzsPLHMlLHKZO6HM39ROz+dW+K7s+zMGo/u5KBkBtYb6Df6o8RayofbP/QQDwDMDjOP/fEYi25fRFzAZTBfrIBgXQDBugBqB9e6ovetFlojtH8UUjb47m8/8rIaygoEAoFAcLm4JAHh2LFjZYLBhSxbtsyrraphp9WlS5cuHD582KPtyJEjJCX5d43v1KkTv//umQu9cuVKOnXqBIBaraZNmzasWrWKgQMHAlKkw6pVq3jyyScBaNOmDSqVilWrVjFo0CAADh8+zOnTp8vmEVx/uGw2HNk52NPPgtOFKi4WRVg4Cp1Wcrxf+iIc+lU6qZfJoGF/6PvulTMPvFxog6DvO9LJ/d4fwOWUNj/NB0vRBL5EktJc2PiR/zm3fS6dxF/OMmYqHYTUIt0RzrBZ23Cuy2TSTb1odFcHlCUZ2APjOVRqoLk6iosUo/RLia2EXItUnjAgIJSwNsPQ/z1P8iX4djAkdYb6vcHpgISO3qkGl8Dp4tMe4sE59uTs5beTS3mw6YOVCsfXqXQMbzKcdWfW+ewf0WwEAWrfJ/EXw6AycEfdO0gvTfcQD87x+Z7PmdpzKjqlDrPDzPKU5dQPqc+C/gtYdGwRmaWZ9E3uS4uIFtXKz08vTedAzgF2Zu2klrEWnWI7Ea2PJlQXyuz9sz3Eg3O8ve1t2kW38xIQcsw5GNQG3vvrvTLx4BxOt5Nx68exYMAC39EGfsg2ZTNpyyQyTZlefX+m/skTpicuXUA4tgqAsOX/5aW+b3Fnxx7MT12FxWXj9ujOtE26iWiDfzEr05TLylMrffaZHWaO5R+74gLCdUtCB6jTC47/4dme1BnqdL8qSxIIBAKBoLpUWUA4edJHibJrjNGjR9O5c2feeust7rnnHrZt28aMGTOYMWOG32tGjRrFp59+ygsvvMCIESNYvXo1P/zwg0fkxJgxYxg2bBht27alffv2TJkyhdLS0rKqDEFBQTz00EOMGTOG0NBQjEYjTz31FJ06dRIVGK5TXCYTJevXc3bcy7hNUs6zTKUi8sUXCOrbG8XyMXBkafkFbjcc/EXabA+cJqUBXM8ExsCtH8CNL0ieCJrAf2q6G3yPd9mlE3l/lGSB0+ZTQCiwFJBnycPitBCoDiRcF45OqatweSW2EmxOGwHqAC9H+VCDmjaJISzedZaHfzqDRiknUBtEoTmP6f9JJtJ4aSHxGaUZvLvtXVadXoUbN0qZktuT+/LEXV8SseBh6bU/tUn6imkBnZ68pPucj8vtYsER3/XpAb49/C3961Q+9L1ecD0ea/EYn+32NKd7uOnDNAxpeMnrDFAHcGe9O3lq9VMe7Uq5kvvrDuL2mC4Y5Vomt/8vE3d/QkZpBsW2YuoE1+GxFo+RY85hT/YedmbtpGl4U8K14ehUFb8HLuRU4SlGrBhBlimrrE0tV/P5zZ+TEJjAvAPz/F776/FfGdN2jEdbsb2YQHWgz80+QJGtiBJrCSmOFLakb8HitNAxpiNR+ii/IkCJvYTU4lS/69idvZsGoQ0qephemB1mim3FyBvfRnjqVji7k7AlL9ApMJrWdW/GpQxAt+0bqNXH7xwlVjvpRSVlERG+yDFX8PMt8CQwSvo7kLkXts8CtxPaDJd+L9RESVeBQCAQCK4CVRYQKjrFv1Zo164dixYtYty4cUyaNInk5GSmTJnCkCFDysa89tprzJ49m5SUFEAq87hkyRJGjx7NRx99RHx8PF9++WVZCUeAe++9l+zsbCZMmEBGRgYtW7Zk2bJlHsaKH374IXK5nEGDBmG1WunTpw/TpnmXKRNcH9jOnCHt2dEePgBuu53MN95EU7c2hrPeNdwBOLxE2khf7wICSGJBaO3KjdUaIflG/+UMG/SVKgVcwJniM4xbP45d2buAfzacDe9nRNMRhOm8Kz3kW/I5kHuAmftmkmvJpX10e4Y0HEJcYFxZKHmwXs0rtzamZWIwn689QWaRhbhgHVOHtKZJrH/n/SxTFlmmLHItucQZ4gjThZVtBAssBYzfMJ4tGeUpXA63g4UnfsXtdvFS62Hots+UOoKT4K5ZEFB9UzyX20WRzb8JpcluqlI5wiBtEEMbD6Vfcj92ZO7AjZs2UW0I14V7ncBXFb1KT6GtsOz7hqENmdnxdXRbpqNcNRgcFqJjW/N9jxd5L3U5g+oNothWzPbM7RTbikktTmXxscXkW/KZ2HkivRJ7YfAnWF1AobWQCZsmeIgHADaXjadWP8X3t31PobXQz9X4FAl0Sh1quZrXWz5DY0McyGRsLTjKGUcJjcMaE6mPJKUohefXPY/T7Sy7rm+tvrzY/kWf71+VXOXX+wHAqK58CpTD5SC1OJUv9nzBprObCFQH8kC7e+mhepyIRY9DcQaav7+WBnd7AQz+426KzQ4yC1xE6CLINmf7HNMw9NIFpn8lgVHSV61ugPvyl3EVCAQCgeAyI3O7a6q22PXFsGHDkMlkzJ49+2ovxYOioiKCgoIoLCzEaPx/kEd/HeOy28l8/Q0KfvCRzw/oO3Yg/q54FNs/8T3Bw6sub77/tUr2Efj8BnBYPNsNEfDIagj2LBGYbcpmxPIRpBSleE01qvkoRjYfieq8iIUiaxEz9szwCufvGNORSR3HE3NBCUK3201WsRWXy41GpSDU4D+//0TBCR774zHOlp71mPeNLm8QZYjieMFxBv480Oe1CpmCX2/9noSULRBeTyopWYNpLCtPrWTMmjE++/rX6c/4juMvGrFR05zzPAAwKIPILXFQZC3lq8PvsPLUCiJ0ESzsMZWgH4cjzzroebFMjn34Uooi6rH57GZm7Z/F2ZKz1A+pz5BGQ1iftp7Fxxbz04CfqBdSr1LrSSlMof/i/n77f7ztR6bsnMLGsxt99r/a8VV6JfUiUGUkq8SKw+lGr7QRmL8f9e8vQOY+ANxJXcnv9V8e3/URqSWp9KnVh54JPRm/abzHCf2bXd5kQN0BXvcpsZXw8oaX+TP1T68+pVzJrwN/JT4wvlKP+Wj+Ue5fcj8Wp+fPW9foDrwR3IawpS9JDbVugDu/AKP/VIuMQgvP/biL3h3SeG/na179rSLa8GGPDyRRxJQPpVmQnyLl8gfGSXNfkLLoyM/HmZuLPS0NRWioVKYy8lKThwQCgUAgEFwuKrsP/VcWIHa73axZs4bXX3/9ai9FcA3jtlqxVZCyY089g0tbQRiqpvoCkNvpxJGdjT0rC9c1Uib1ooQkw8MrIfEf3w+ZHBreBiOWe4kHAGdLzvoUDwDmHpjrdRKaY87xEA+ahTbhlxs/4QNlIjFLXsD1x0TIOQp2aUMlk8mIMmqJCdZVKB5kmjIZuXKkh3gAklneRzs/wmQ3VRi+7XQ7KcYJbYZJOc417IHRPLw5dYLqeLXrlDpGNht5xcWD9JJ0Pt/zOUN+H8J9S+5j2q6pnCw4w1Pf7OOOWsNRyVWMbD4SV+Z+b/EAwO3Cenoj8w58zbgN4ziSf4QSewk7s3Yydu1Ymoc3p3l4cxYeWUhlde4LPQouJNOUyZOtnkQp8w6+SwhMIEAdQKHJzbS1x7llynr6TFmHM/sk6rm3l4kHALJTGwidfx9vNRtFka2IH4/8yJtb3+SVDq94zDlz/0xyzble9wpQB/BCuxe8fBPkMjnvdXuv0tUFimxFvL/9fS/xAGBDxlbOxLeEPm/Dw6vhrpkVigcAYQEqGscGkZaWzEtt3ijzStAoNAysfTeTOr8liQfFGZJh6NT2MP8e+LIXfNlDeo7Oe63smZmkPf8CJ27rT+qjo0i5+x5SBt+H9djxSj0+gUAgEAgE1x7/L8s4XgyZTMapU6cuPlDwr0au06Ft3hzTX3/57Nc0bIDcnxdgra5guGAT4LSD3QRKneTOfxHsGRkU/vwLBT/+iNtux9j3FkL+8x/U8ZU7maxJ3G43jswsnAVS3XJFSAjKyEjfBqlKFUQ3h8HfgrVQEhB0IZJ/gg/8iQcAJocJs8Ps0fZXRvnrER8Yz4eNhhM1/36wlQIgP7wUNn0M938Pyd1BoQSHHYrTpAoRucchsaO0xqByM7i04jS/ee5LTy7l8ZaPE6wJ9rtWAIOycqH2l0KUIYrpN0/nu0PfsfDoQiwOC90TuvN4y8dJCKxc6ddsUzYOlwOVXCVVYrhEMkozGLFiBGeKz5S1zTk4k2X6JYwfOJVPV2TzQa+viArSoN/8ud958uJaMXP9aJ99U3dNZUzbMaw8tRKn2+lz038hgepAQjQh5FvzffYnGhMptBbyQfcPmLlvJruzd6OSq+id1Jvbat/GkdwzLN5wnGX7pffB8HaRBP/1kWdJ0HOY8wk7uZ7WEa3Ymf03Z0rOcLroNA1DG3Io7xAgpbycn9ZwPvGB8cztO5cDuQfYlLaJuMA4eib2JEofhVZZOX+OEluJT7PKc/yZsZUWnZ6t1FwAKoWCBzvXYtisbWiPhjGi82RCAsDlUmC16glWh4PDCps+kYxjz6c4A+b0h0fXQ3ACLrOZ7I8+xrTBswqB4+xZTj/0ELW+/w6Vn+pEAoFAIBAIrl3+lQKCQFAZZAoFwXffRf7XX+O22S7olBH++BMo4o1w7BdIPc/VPbETDJxeXqLLYYWCU7DtK8jYA436S14AAdGg9n1qbM/IIHXkSKxHjpa15c2eQ+FvS6j13bdXVERwWSyYduwkfdw4HFlSbrkyMpKYt95C37YNcq2fzY4+RPq6CBU5umsUGrQKz/nPFy2erX8/UUtfLhMPyhftgAUjYNRGyQjyzFaYd6f0WgBsBIxx8OASCE0GfOe/n8PhdmB2mAnXhVM/pL5XiTuAG+JuIFR3ecuyRRuiebLlk9zf8H5cuDCqjeh9eEpcSJ4lj/Vn1jNt1zTOlp4lITCBp1s9TceYjgRrg6u0BrfbzZrUNR7iwTkyTZnsyvsTOc15YX4uM0cmYteF4vNdrg0mxZLj1wcg15KLVqGlS2yXSpdIjNBFMLbtWP678b9efQPqDCBMG4ZCpuC5tc9xZ707Gdp4KC63i3Vn1jF2zVg+6/49MW1N3NkpEhlyGmkCUP+4VTL9NESCrUQq1/oPQanbaVqnNTuz/wZg09lNtIhoUSYgtI1qS4DKf0WLaEM00YZoeib2rPBxuaxWHDk5uEpKkOv0KMJCURgMyGQylHKl38iLygoR5xMbrOPrEe3ZlVrIr7vTCNKrGdwulsQkPcF6NRSchnM+HxdizofsQxCcgCMnh8Jff/U5zJGZiT0tTQgIAoFAIBBchwgBQSCoAFVcHImzZ3H2+Rewp6UBoIyIIHrSRDTJtUCvl07aS7PBlAv6MCnX3/CPcZrbDanbYN4dULcX3DAGjiyD35+DuNbQ/D4prF/h+aNo2rHDQzw4hzMnh/zvviPimWeQqy5jKcTzsKWmkjpyJDjLT1IdWVmkPvooyYsXoa1Xufx0fyQEJhClj/K5gb+r3l1e4dztotuV/buhNgJyfZeUxVIIRdJrxreDy8WDcxSlwa9Pwz1fgy6YJKN/g1idUodBZSBMF8ZHPT7iqdVPcayg/L6tIlsxodOEahsQVgalQklkBUZ4F2J2mPnm4DfM2FNehSa1OJXn1z3P2LZjua/hfWgUlTd2K7YV89uJ3/z278nbyn8692bZnnyyCl2E1O6Gcf1k74EuO9qLCC4quYpu8d0AKLQUkmPJ4VTRKYI1wcQGxBKpj/QoXamQK+iR0INPen7C5O2TOVl0klBtKMObDOe2Ordh1BiRy+T0S+7nVYFieJPhnCzdzXt/v02pXRKkXmv5LNEdxuFQxmBNSUUZEowqWIFq+/vIsvZgC4gkx15cNodepcfqlN5nSrmSUS1GVUrgqQhHTg55c+aQ9/U83BYLKBQY+/UjcuwYQsJDuLX2rSw+ttjntb0Se13SPaMNMm5JcNAnPgKZOhD0wectyCpFUvkjT0r7clksUEHalT09/ZLWJhAIBAKB4OoiBASBoALkKhX61q1J+nY+zvwCcLtQBAdL4fvyfzYuhrByweBCitNh0UiIawONBsC390pl/gCO/SGFAg/7zcNs0WWxULhokd81FS9dSuiwYcgjqu/ufzFcVit5s2Z7iAdlOJ3kzZpN9ITx/qMQKkGUIYoZvWfw1KqnOF18uqy9d1Jv7q47lP8tO0aIXs0tTWOINmoI14UzsvlIZuyZgcztlASY5vdIJ8R5x2HPD9JJKEiRCLnHwVrs++Yn15VVy4jSR9E4tDEH8g54DRvWeBgROun5jg+M54veX5BjziHXnEukPpJwXbjfkn1Xm1xzLjP3+T4xnrZrGr2TehMbUHm/BrlMjspH7o5SpmRM2zFE6iNZffpzNLEutJohHLdbCLjlLYKXv+KRH++KaEB8SD10Sp1XmgpA/ZD61AmuQ2xALNmmbN7e+jYrT68s6w/RhDCzz8wygSlIE4RMJsOoMdI9oTtNw5tic9pQyBRE6CPKhIYAdQAPNn2QeiH1mL57OmdLztI6qjU3xN/AiOUjyuZXyBTU19Tj7KdfU7q+PAxfbjSSOHkS2n3vkNtsEH9um1DWd3PSzby//X2ahzfn5Q4vk2j09vyoCi6LhdyvZpI3a1Z5o9NJ0a+/4sjNJe6DDxjVYhRb07eSXuq5IR/VfBSR+kswKyw8A+snw65vkDkskNgZbnkbIhtJFQRUOkkoNXl7OwAQ1QQAuV6P3KDHVepbbFDXqlX1tQkEAoFAILjqCAFBIKgEqsjIS3MON+VC0Vno8xb8+ky5eHAOuxkWPiwZDAb+Uw5UJkOm9n8iLFOrfXsPXAZcJhOWA94b6nNYDhzAZTZXS0AACNeEM+2maRTZiii1lxKui2DTYRu3TN6F3SltOt9fcYTXb2/CwFZxDKo3iDrBdQjUxcONL8GOmdLGJ6oJ3D4V9i2EAz9LpRTTtld8c4eUnhKmC2NKjym8ueVN1qWto0l4EwYljyApsB6RhlDO95wN14VX2ugOkF5nm0lKWanmiXRVyTZLvge+MDvM5FnyqiQgBKgDGNJoCNszpedVhoyOsR15pOkjZJgymHdgXlk5zuWnlvFmlzc5Htec6Ad/wZCyEZW5COr2RBnRkIiAaN678T2eWf2Mh1dAgCqASZ0nkWvJxeV2cTT/KKtSV5X165V6XurwEhvSNrDi1AqcbicD6wykR2KPMuO/il6fUG0o/ev0p3NsZ+wuOwqZgvEbx3uMuTm2B4ELVnuIBwCuoiJOP/MyifO/4IfsJWXix8C6A2kV2Yp5fecRoA6oEUHJkZND/jff+OwzbdqEMzeHuLp1mdN3DlvTt7IiZQWh2lDubXgviYGJGKtq5Fp0Fube7hnVc3oTfHkTjFwD0c2klKBuL8CyF72vD60NYVLJV2VkJKEjRpDzyadewzSNG4v0BYFAIBAIrlOEgCAQXE7cbjiXv23xU38+/6R0Cv6PgCDXaAgZMoSS1at9Dg8efB+KMD8RDzWF0w7FGchtNtRJiVgPHfI5TJ2UVG3xIKM0g9c2vcbGsxuRIUMlV9E0vCkjGryCTqXA7izf/I7/eT+d6oSRFBaB3uXGcPBXWPu/8smKM+D4ahjwKdS6UfKhiGzs/+aGcNAGlX0bExDD293eJt9kZeuxUj74+RjphfsJ0CgZ1imJYZ1rEWmswuO1maTXd+PHkkN9eAPo+gyE1gGN/9z4muRCD4kLUSsubuh5IS0jW9I1titHC47yaqdX2ZaxjYlbJqKQKeid1JthTYbx6qZXKbIV8crGV5jacyqqiIZYwxvgkqsI0gShkCsA6BjdkUW3L+LX479yvOA4rSJbUT+kPq9uepXD+YcB6Jvcl0mdJzF+43jcuBnfcTxz989lf+7+sjUdyD3A/EPz+aL3F2UiwsUI00k/R9mmbE4UnvDouzeiN5aFr/i6DFepCfPJDCyhau6qdxcD6w0kMTCxxqNQXEXF3v4r52E/m46mbl1iDDEMrDuQvrX6opQry57bKpO+y3dKkMsBf7wmVXLQBkGzu6Q0hvXvl/uPJHeDAZ9IAgNS9FbI4MG47XbyZs3GbbWCTIbhhq5Ev/YayvBLN/EUCAQCgUBw9RACgkBwOdGHQUCkbxf387kgMkHboD6Bt/SheNlyz/YmTTDe0ufyRiCY8mDvAlg9CTkywu75guLlK3wODXv4YeS6Sy8fWGQt4s0tb7Lx7EYA3LixuWzszNqJy/0Go3qO5X+/e5r1LdmTzjO96tM1qD7K9Q94T+p2w59vSlEdaoOU2tB0kBSVcCE3v1G24TmHXmHg50N5/Hdxedm+EquDg0R2UQABAABJREFUqWuOczSrhHcHNSekgnKQZbhckLJe8l84ZxSYuQ/2L4S7ZklmmgoVWEukVJfDv0NJFtS9GSIbQuDFN8EOl4Nccy5u3BhUBp8eDGHaML8eE0nGJEK1VTd+DNeF83qX1ymwFvD4qsc9wuen75lO/ZD6vNLxFV5cJ51ST909lc97fe7TsFGj1JAclMzTrZ8mx5TDS+tf4oMdH3iMWXpyKbGGWDrGdiSjNINCW6GHeHCOlKIUlqcs54HGD3h4I1wMnVJHclCyx+PQuBS4zd6pFecoTDmKPEwOMgjXXp4UFpleBzKZR+rH+ShCPe+pUVbey8InB3ybHgJwcq30XtUGScJbpyclIcFSCEqt1KbzXI8yLIzwxx4j+K67cJWUINNqUYaGoqigtrRAIBAIBIJrm8p/whIIBFUnMAb6vS+VMFT4MT3Uh0pCw3kow8OJ/u94EmfPIrBPHwK6dyfuk0+InzYNVVTU5V3zybWw9HnJN8BahDp9CbGvvYDsPKFAptMR++47qGsnV+tWeZY81pxZ47NvV/bfNI73/hWVU/KPSV1+indKyDmKzpb7HuhDpBzum14tr4wRVhcGz5eqYcg975FZbOW95Yd9TrviQCbZJVaffWW4/hELitNh8WPl4sH5/Pq0FC1hK4GDv8DUdrByAmz+FL6+HeYNgsK0Cm+Tacpk2q5p3PnLnfRZ2IfRf47mYPY+bFkHIW2nlNLhdBChj2BKjynolZ6pE0a1kQ9u/ODiqRjFmZCxF05tgpxjYC4AIEQbwh+n//DKvQc4kn+EXHMudYLrAGBxWLA4LaQWp3Ky8CTZpmyft9qRuYOtGVt99v145Eduq30bHWM6svq07+gcgEXHFpFv8V3G0R8B6gBGtRjl0ZbjLkJZQdqSu2EdFh9bzIIjC3ht82sUWYuqdE+/mPIl347sIygDNBi6dfM5TJWYWOH6LomACn63aIOlkqznUKol/5HoZhBez0s8OIdco0EdH4+2YUM0tWoJ8UAgEAgEguscEYEgEFxO5HKo3R0KzsANz8Gat73H3DrZ52mzMjwMZXgYurZtweVCrlZLm7fCNOlU0hAFiksMVfZHcSb8MdGjSbFvLoHJZ9F98QYOhxFUOpTR0SgjIqQ1VYMSe0mF/aWOYhRyGU6Xm4hADW2TQhjc/h9juouF3svOe24CoqDLM9BisBQNotL63SwVme0Umv1HjBzPKqF+lI9qC0XpkL4b9nwvbbZa3uffaM5aDCWZkqP9z497nzBn7oNNH0OvSaDyPlXONmUz+s/R7M3ZW9a2NWMr9y99gG9ueI/GCx+TvB0GTkNWuweNQhvx04Cf2JK+hUN5h2gW3ow20W2INVzE+yDnKCx6FGr3kKqGmHLBkQy5xylw21hyYonfS9ekrqF9dHuOFxynd1JvFhxZwIw9M3DjJjEwkZc7vEyryFYeVQouTCM4R4Qugh6JPUgMTKTAUsDxguN+7yv757+qUi+4Hm92eZO3tr1Fqb2UL9N/4u0nRuB49R2vserkZE4H2Sk6JYkGW9K3kGfJq7rnwPm43ZBzBH55qqwsrCKqKTEvz+FMfj6WPXvKhqri4kj4fHqlfVlyzbk43U4CVYHoVBVEDDW/BzZ+6LuvwygpmkogEAgEAsG/GiEgCASXG7UBIhuAfgTEtoZ170J+ipSb33O85G5eQc6yXKkEuwXO7oIV/4VTG0EXDO1GQpsHwRjj99oq47RKOfsXruHkH6hP/oG68zPQe1KN3S5QFYgMGW58h2gblEZUikKm3R5HC3U6kcc/Q7ZNDa2HQnCC5Ahv9xFmHtGgPNqg7EEowHhxs0CNqmJRJkTvQ7goOgvf3C1t/M9Rt+dF78WRZX7D09k5Fzo/BUHxXl0nC096iAfncLgdvHfoa6a0GUbQ2vfg+yHw6AYU0U2JC4xjUOCgi6/pHEVn4aeRcNN4WPc+bPoI7pkLS0ZLpUl7ja8w114hV+B0OwnThtE6qjWPrny07HU+XXyaUX+MYs4tc2gd1brsmibhTTzmkMvkjG4zmhBNCEtPLuX97e/TKaYTY9uOZcyaMaSVeEdp3FH3jktKJwhQB9A3uS9to9uSZ8lDLpMT7Aom0K0he8pHOAsKQCZD260rtqcfYMJeT38Em9O/V0GlKEyFmX3KK4gAZO5D9e1NJExehaPYji01FVVkFMrYmEqJBznmHDambWTW/lnkW/JpF92OUc1HkWhM9O19ERQPfd+FpRcYJCZ2hJZDKvw9JRAIBAKB4N+BEBAE1x1utxtHejrmffuwHjqMpmFDdE2boIqtvJP8VSEgEur3lko2OiygMoAu6OLXAWTth69uLg/ZN+XB2nfgxBq49+uaOxmUq6ST+RLvfHkAIurXzH3+IVQbSs/Enqw6vcqrr310B7IKVMwclED7nS+iPH2eG/6ubyTxZeA0WDDCcxOu0sMdn1ftOXHYoCQDbKWEqSK4oV4464/meA0L0qlIDLugioLTATtme4oHIJnMGcKh1HseNIHS8+wvQgHAYcEhU5BXmoULFwHKAFQKFU63k4O5B/1etj1rJ6aOdxEE0vOyeSr0/1DKU68CdlMhWbfOpbQoD22HV4lqegTNwd8k8QAIPbSMe1oP5G0/0QC9k3qTVZrFjJtn8PSfT/sUiSZvn8ynN31a5o1QP6S+h1/DYy0e40DuAZaeXFp2ze7s3Sw8upD/dfsfo/4YhdVZnlKSbEymd63el+wRolKoiA2I9ahK4b77bgw33oi1KJ9Uawa/Ff3FN7ufp9ReWjbGoDIQoK6mKebhZZ7iwTksBSjXvIjyrlloGzWq9HT5lnze2fYOy1PKfVSWpyxn9enVfN33ay+xBgCtEVoMgdo9JU8Ocz7UvwXC6ojoA4FAIBAIBIAQEATXIdajRzk9dJh0IvgPiuBgEr+ei7Zevau3sIthypNOy1W6Sp2Ee1y39CXf+f6pW6R86Zr6cB8QBf0/lgQOALdTMlQ8shSUOqh1Q83c5x8CNYGM6zAOgNWnV5dtMjvHdmZi54kY5GHoD8xHcXoDyGQ4k7tjim7C/7F31uFRXG0fvtd3I7txIwnBHYK7Q9Hixa1QKFCsblSgQEtbKFAo3iIFWqw4FC/uEJwgCXH3ZH33+2MgyZIN9fd922/u6+IimXPmzJnZCeT8zvP8HqU+G9WZRTB0G4w/Axe/FdzjQ5tCrReE3OzfSl4qXFgh+A+Y8tG6eDN74BGGpBcQk1FUw95FKWP1iw3xf7oKQ34qXPqu5LjnlkHHGbBjoqMPgkTy2K0+ACq2h5PzHh+XFvVTuZM8eCOb7m9mU+RmXqr1Ev4u/uyL2ke+OZ92oe2Y12Yes87OIsglgEkhQ/E3qcFmI9tFglJezG8j9TaY9L9LQEjPM7LxBiw5fpN8kxW5VMLh0fUp+/PrRbcRd4H2Lafyk2dl7mRGOpzfJLAJTQKb4Oviy+xzs51GCgBcT7+OwWoo/D7ANYBVnVbxzol3eJj1kAoeFVh8dXGJ81L1qex4sIMl7Zew4MoCoYxjxV60Dm5dVIHBmAf5KcLfKnfBTFPl+pufQeF9ymQoAwPRe7qw/Mxyp2LX+Drj8dP8iZ9Biwkelu7rQPwlwS9D/dtTJJLzkx3EgyeYbWY+Pf+pINyoPEqeqHYX/vzFYqGIiIiIiIjIvwNRQBD5R2FOTSVu4iQH8QDAmpVF/OTJlF27Frmv739nckCWIYtsUzY2uw2tUiuUidNnCqZ2R2cKi33visLueVBdIRXh1zDmQdz50tvvHYCyTf+aG8hPgajjcOlbQexQuQtpEj2XCPPWlvlrrlMMfxd/ZjSfwdT6U8kz5eGmcMNL7SXkk+enwfnl2P2qE9/1U3Ynn+Nk+nV83b0Y3ncx5VNvoqvRDzp9JqRfyNXCgj7rkVA+09VHiEgoDbNBEA5OzS86VpBOyKbn2NRzPQ8kNbgan0NZbxfCQzwI1GmQSZ/e3bY5T6OIvyQ8rxG74Mp6SL4OPpWh+VTwKi+YanpXxNrucyyulbDmFiB1USHPv0eWnz9Tri3iZsYtptSbwvW063wZ/WXh0OeSzhHsHszilvNxuxWDcfxsjJnC7rWLqyuyd17DWmsksuurwa8GKJ/xDJ7CZLHy/dlHfHWoyI/AYrOTX2AQPBuK4f/TBBb1mM9lay5bE04gk8roWLYjANdSr9E0sCmeqtLTCbzV3iWqJZTVluWb9t9gsBhYe2ttqefufbiXV8JfYUn7JdiwoVMVi+bJSYRDH8GNLYLwJpVD7YHQbtofTvnRqXW83/h9Qt1D+eHuD+gterzV3rwS/godynZALnv836nVAjnxws9s+gMoU1/4DHTPEA1lCvB8hiGpe6AQHfQ7OJN4ptS2iNQI8kx5zgWEP4vNJqRjPDwmRKsE1BSiGHQhIBN/5RAREREREfmnI/5vLvKPwpqejjkmxmmbKSoaS0bGf0VAsNvtPMh6wPQz07maehWA8rryfNTkQ2pkJqD6cWhR5/hLsK4XdP8KwocKbubPQioVFsYWg/N2ze8vw+cUfbbgsXB9c9ExYy6c/hqaTIBqPf62BYBWqUWrdLK7arOCXEXUcx8x7PR75JiKnO4PxR7llZqjGapPx00iF55RzBnY95YQjSBTQq3+0PZdpz4CgJCqcW6p0+MBGzsQ8MpFmlf+lagWlQdU6iQsVp/m9k6oN0L4rM35gphRzMTOrJeSvPkGuQfnA0IkjbJCBbw++ZCkgq9xV7gT4h7CgssLSgydlJ+ET5aVjCnvgbUoOsWWn0/iB5+gXDEPF5dd0HQC/I7yfim5RpYdL2lmmGSQUV0bJHgjPMGQjf+mF+niW4V6vRbzXdxhVlxbQUJ+Agqpgp96/kQD/wZ8d/M7bE6qUQyoMgAvVcn394mHgb00fwjAho08Ux43024SpgsDu7DIR58Fe1+HO8UMHm0WuPo9WE3Qbe7v2skvjq+LL5PqTmJQ1UGYrCbUcjW+Lr5FIojNCglXhEoapqIUB3QhgpDkVYpIIJEIvh7nljj3xGj5Orj9vn/XVLLSP3OpRPr3lYJNuQWruwrlHZ9w6GMYvgOCG5WoeiIiIiIiIiLyz0L8n1zkH4Xd8OwSenbjr5TY+5uIz4tn+L7hheIBCI7yow+8xCMXd3CWH31gmqPXgKkAMqKE3eoziyHxqrAD7+ojGJiVRpXOf81NFKQ6igfFubBCaEcIjT706BBvH3+bLy98SWRmJLmm3L9mDsXI0Gdw35RBZsupzL692kE8eMLiG6tIy4qCLaMh+gR830cQD0BYLF79Hr7vJ5RUdIYhu3RhBoRIhmIYrUbi8+I5n3iec4nniMuNwyiTQ5t3BLPMpwmoDQE1hKoPLt4O4oEtO53Ur74i9+AhtD16ELJsGb6vvYZH3z5IE1KYW+sDGgY05Hjc8cJztEotw6qM4fNmK1jW+ge4+VBYfDohbc1WrP23gtpTiBzITYQHR4R0mJNfCRUWjCWrYOQZLBSYSqbLLDiXS0azaU6vZZMquJn9gPV31pOQLwgMZpuZB1kPuJZ6jfcbv49c6ig+tQpuRdOgpkU7907oUq5LqW1tQ9ry/e3vmXpsKr129GL6melCecj8VEfxoDg3tgjtfwKr3YrVbiXLlEW6IZ3UgtQicSQ3ETa84CgegLAjv2Oic4+DJ3iEQu/lJcu9NhgN5dtgtVnJMmT95nKRzYKaldrWLqTd3xN9kJsCW0Y6igcg/Iz9OKT0n0MRERERERGRfwxiBILIPwqZtxfI5WCxlGiTKBTIPP+i3fjfgd1u50D0AXLNJRfRFruFpfe3MrPOAFwurHJsNOULixmPECG/+c4e+GmcY7585U6CJ0HL14QFcppjrjndvnJaAvIPkVuKcSIIpQ/1mSQolIw5MIaY3KIokDW31vB2gzfpWak37kon5Q3/ABn6DD6/8Dn7o/ezrdtGzp27WGrf82nXCQsfDEdnOe+QeltYLLs7CV3/tdB+F+/CL/PMeRyNOcr0M9MLjfsUUgXvNnqXrmGdcR37C/zyuVBZQekiLPzqDnV+3fQHWOITyN61G++XXwa7jdgJEwojCSRKJeU+/pCW5RtyIUeothDuW5+XqrzPqmNpLL2fjlqRxQu1KzDyu/WYJ4/Dmum4ODVFRWNLiUK2dbBgtLlzsmDG+YTD06HHYqjR00HgUitkSCRFG+EquRR/rZqYjAJ+zKzCmOcXIz86QxC/pHKM1boT03AkH5wpKS4YLAYaBzZm1Y1VzG8zn7i8OPLN+VT2rMz9rPu/Wi0hxD2E9qHtS/gOaJVa+lXux9SjUwuPHYw5SJgujPHBHSk12N9uA0PWM6/5LLIMWfx0/ycWXVmEySZUXfBWe/NV26+o5V0LeVZM6SLBo5OCaaZGuGe9yUJanonYjAKkUgnBnhr8q3RDMfEiJF0XBMWguuDmR4K1gN3XV3Hg0QFcFC4Mqz6Mun518dH4lDpXH40Pr9d/nbmX5pY4/mr9V3FV/H4/iF+lIE34WXNGfprwzuj++jQoERERERERkf8cooAg8o9C7u2N18gRZKxcVaLNa9SLyH28nZxVRKYhE7PNjJvCzaH+/J/BYDFwNvFsqe0RGbfICxuA06s92ZXNToCfXi4Zvhz5sxAV0OQVIQQ46Trc2SuYJtbsK/wyrvprFu2/FtZtk2tYfm25g3jwhDkXv6BZYGPc3UIgLwX06YLpoqvPHzJ4fJD1gD1Rwi5ybEHKM/ta7TYhvzyl9MoERJ2Acq1KHnfxhQrt4UFJYzw8yoK2SJyJyYnhvZPvOXQx28zMODuDSp6VCPcLh+fnC6kgEolg2idzUvYuOw5Wd8PWdC5yLy9U5cuT8LZj2Ty7yUTye9NovHEF6jIe/BL3C2OqvseYb+9jtAgCU4HJypqLiZyIdmXlzM+xvjLGYQxluTCkSecEf4xL3zmKByC8aztfwRrckEcKOXa7HY1Cg87Fg+eq+3M8Mo3XuwRR1s/Co9z7eKq90cncyPbvhqZsI+zmfKRyDWsf7WPlybcczBABJEjQqXT4ufrRPrQ975x4B61Si0quwm63M7vZDAKlz17Eemm8+LDph3QO68zaW2vJM+fRqowQuTDn/Bz0FkfviQ13NvBCuW480+XgT4hcl1MuM+/SPIdj6YZ0xhwYw46eOyhT8IwIAyiMdsnWm/npShyz99zBZBU+T41Cxhcv1KZdlWBcqoUVnhKXG8ewfcNI0xdV87iScoX2oe35oMkHgs+KE9yUbvSp1IdGgY348c6PpOpTaRvSluZlmjtUmfhLsZmf3e7MK0RERERERETkH4UoIIj8o5C6uOD94osoAgJJW7oUa1oacl9fvCeMR9upE1KNxul5GfoMLiZfZOX1laQb0qnnV4+xtcdSVlvWeT3038GT0m+l4aPxQVmQUbJBGyQssAFubHWe+wyCyV+tfkJ/bZAQlfB34OonlGtLd1KWL7gBepUrux7sKvX0X2KPUr7ADgenCTnnAH7VoP868Pnt1TEsNgsb724s/P5W+i3q+NYhIjXCaf9GXtUhL11IIXg6dPwJpRnnaXTCov+HIZB0rVj/MjBkc2H0gNFiZPeD3aXOedX1VcxpNQcXpavzVIbixJ6H3ESkCinanj3I2uLEO+Ex1k078R7fg7E1J7HuZEaheFCch2n53JKGUjU01MEfxGdEX2Snx0PXL2HnROcXsNuxRu4jKawhl1Iu4a32ppZPLT5+viIPMz1ZevsTrt67VNjdXeHOovaLOPzoMOvvrKecrhzj6owr3I0vzgtVXuBo7FGsditvhU+kmUdlMm1G5GYDnnlp+N7YA5U6gL18SZEpOw6SbkDyDbz8qtE5sA7NOyzFbLNwIekCEw5PcOqpkG/OJ9dqJDCoHiRcLnm/oc2KfuZ+Jxn6DKcVIUBIbTn46CAj/Z9hZqr2gMdGj3cSc/h45y2HZr3ZyqSNV9g3uSVVAwUxz2gxsurGKgfx4AmHYw4zvPrwUgUEAK1KS3VVdT5s+iEWmwXV7/DC+ENovARB0+gkpUkq/33VZ0RERERERET+JxEFBJF/HHJvbzwHD8K9YwfsJhMSpRK5n1+ppmA5xhwWXV3E5sii/P790fs5FHOI1Z1WU8evzp+bj1TOwKoD2Xpvq9P2sdVH4rH3o6dOUkG/74rC27OdG0MCQuivreRiqVRyEoWUCJkCXHxA9Rvr07v7w8AfBAO44kZ5XuWhz0pyZQqnC8XCyxpz4e6xIvEAhKiANd3hpSO/OXTZZrfRwrce4W6h3Mh5xE/3f+L9xu/zxi9vlNjlHly+Jz4PfhFEj9oDhHKOTyOVQfk2pV/QIxSGboXseMh4IIgHnmXJVrkSm3aDbfe2oZAq6FyuM93KdyM2N5Z9Ufv4Je4XrHYh5SAmNwa9Rf/sqBabTfBUyEnENmw7MqUbnr26ELN3X+nnxCZiNehpHtCBeQ+ultptX7yJOjVqYI6JQermRsA7r6PKPS+E08sUz9z5teQmseL6Ci4mC2kiapmaxS0/527uQ66mXnLom2vO5ZXDr/BJ809Ye3st97PuszdqLwvbLmRz5GZupt/Ez8WPvpX6kmfO46tLX+Hv4s+EygMJvHeEwIMfOl78zEIYssVRQEiNhDXdhEiWJ2g8cR+5B/xroFPpnIoHAH4uftzJuo+y08eE7X0XkouiLuyB4Uj6LAOXP5bmZLaZickp/ef0RtoN7BV6IqnZVxAEn6bdB+AeSK7BzMLDzsP87XZYfTqaGT1ropRLyTJmsS+q9Pdjx/0d1POv96tzl0llyKROomH+atz9hdKlu18t2db8VXD971XIEREREREREflrEAUEkX8kEqkUhb//b+qbqk91EA+eYLFZ+OTsJyzvuByvP1nJoIxbGT5q+hEzz84sXFQCDK02lHqBDWHQRri+RTBGLFMPavbF5hqI9InoUakzXN3gfPCQxr+tDJ8hRyjBuP8dwbRNIoWq3aHTTCEc/1mY8gVDPW0g1uGHsOVmITOnCREdHiHgHojGmE19v/pcSrnkdIhWXtUhaVHJhtwkSL3z2wQEfSbKlDv0uroTaW4i+qBw0hu8z9q446zu9B3b7m3mXPIlvNRejA7rRq3sNHRH3hfutf9aIYogrphfglQOA74H91/Z+XTzE/6UqQtAtjGb1TdWs/LGSnpX7E1dv7pMPzOdB1kPcJG70K9yP5Z1XMbEwxMxWA1U96r+6znl2bEQfQqbTI508wgwZCOp8yLq6lUxx8c7PcVeuwoGhR1XpQtuKjl5xpLeHwBergr8Jk/AZ3Bv5HID8oSDSHwqQbd5Qk56aTvyQE5oQ+5dm4cECS3KtKBb+W7kYKVpcDPOJJ0tkZ6TZ84j05CJr8aXVH0qR2KOcDHpIq83eJ2+lfpyO+M2q2+uJjY3Vni0SjdkNiscmVny4hajsNgctgM8giEvFe7uEapWWC2CEeaV7yHqF/hhMIz6mXK6cgS7BxOXG1diuBdrvMiPd3/ky9xY3m05jjpqf2R5qVjc/UiW2Knh5s8f3YNXypSE6cK4k3HHaXst31pINJ7Q6VPwqQJnvxH8FnQh0P4jqNgeZHIMBUZiMgtKvc6D1DyMFitKuRTzr6QE/G2VFP4oMiVU7y38vB2eLvzce4ZBm3ehQrvfLmaKiIiIiIiI/M8iCggi/3oupzhfOAHczbxLjinnTwsI7kp3upXvRuPAxtxIu4HJaqK2b2181D64q9xB4wNt3sZm1GPJyCJrzQ8YIyPRhIej7dIFRXBjJB6hkPXUDqdEKuzoaZ5tNgcIofE/FqvWYLcJZQSTb8DIPc7Dh816yHgIJ+Zi8ayNUVqFtDWbMMfHo65RA59x41D4eCIDdGYjb9V/jSE/j8Bic1zINvRvQEhWYukGdSm3hQXUszDmwaW1cOjDwvIwmqRrBF/bxJvDtyMzmXkrKYE8//YogsLRXt8Gl9c+vlcrbB0jLDyfmw2xZ4WUjLLNsEq0WOKTsOXmInVzQ+blhVyne+ZUEvMSWXljJZU8KlHPv56D90GBpYC1t9ZyM/0mSzsuZfTPoxlVaxRqufrZ95dwBasEZPveKjwkvbMFn2FryT18tESUiUStxta1DQXWdG5mnqVPQx++OZzw9KgADKjnj2pbBwhuIHg9+FWB+wexyxTY6wxF6lcNfhzqaNAJWILqcRMjuaZcZjSfwYOsB8w6O4tccy4eKg8GVhlIu9B2zD432+G8VH0qOpWOVL1Q0SDHlMPSiKWMqDGCZdeWOUQITKz1Ml4mA/bmU7FoKmKXugIW5A9/Qnpvl1A1w5AFBAt/R58QFp92u/DeN58CIY3g+BeQn4p/QC3WdF7D5rub2R+9n+icaNwV7rxS9xVsdhvX0oRUlLcufYFMIsNV4Uq+OZ/avrX5Jrg5qj8oIXiqPZlcdzITDk8o0aaRa6jmXY2zCWep5l0NXcvXBQNNq0mowFHMSNNFKaNGoI7YDOdRIXVDPdEoZKQUpLDrwS7ah7Zn54OdTvv2rNjzD93L34qLp1AZpkx94f6lciEyQURERERERORfgSggiPzrUUmfvWAorOH+J9HINYS4hxDiHuK03W6xUHDhErHjxhdWkcg7eoy0pcsou2YNmhf3w8/vw52dQj15v2rQdS74Vf/1i+elwIH3nLdlPBTCwp0JCLHn4fve2Cr3JvsupCx8rbDJHBtL7oEDhKxYjltlH9gwgIrVe/JjhxUsvLGSs8kX0al0DA3rTvewTvgc+wJ6LwO5Gix6uLZJKBsI4Fvl1+8hPwUOf1zyuMWAYs8b0OFjVNc2Ccs/qRye+wR6L4Xbu4WFSvhgIVpDGwShjYV7SE4m+ZMPyT18uNBjwqV5c4JmfoIisGhRZ7fbHXZzdz4UFmz9q/Rn2bVlTqd7KfkSRquRjV03EuoeWvp95TwWVpRuyA48VanAmIsichUh82eR+NnXWBIEgUBZvjzyj17j40fL+bjFJ7xy5BUm1ZpGvbI6Lj9yLJH3apsQQrIuCl4ON7fBkRnC86nWA0nlzmQpVCRjpdKIXUiubiC1QkuyXLyQqHXIVO4sOzOdAVUGcC7xHLsfFvk8ZBmzWHptKYOrDqZ7+e4ObeV15XGRuzA7fCqBGl9clW54y91wyU+lXbPPuW3KYMXDnXxa+xVCU+9jMaeTlxJK6jffYElJQaLR4NHneby7rUWxbxTkJUGqAn4Y5OjBoc+EQx9D50+hTH3spnxMUVFI9u2jV0wcg5qPQdGuFnovV7RKLbPOO1bisNqtheU/mwQ2QSN37pHyW6ntW5v3G7/PvEvzCg0cg1yDeLvR2yy4tIBradd4s8GbvFDlBTSlRNwo5RLe7FQZpVzKgVtJGMxFYotKLmVQoxDkMilHY46y4voKvm73NWcSzhSKNU/oWLbjs9+7/zZuYrqCiIiIiIjIvxGJ3V6ac5vIf4OcnBx0Oh3Z2dlotc92xRdxjjU3F0taGgUXLwF2lPXCWRm/mZVRG0v0bRTQiK/afIVW9fc/a3NCAg979caWU7KOuyI0lLLrv0eh1Qil3mwWwYzst1YwyI4n4+YWzNoglFkxeF5aC5nRoAvG3HgaZgIwp+ehDA1FHhSEwtdXSC1Y9RxkPcLUYwsPhr/mtDymPCiIsJkvoTgwTjjQ8xvyFCryJCA15uJzbSvSlq8JYsS5pcKiT+MJDUcLfgLHPoMxR0AX/Ox7uLmd/JjTpFfpSJ7VhKtMideD47ifXyFESow5Bqu7CjvsNfsKPhKGHMFXIC8V2r4HandBTLEYsUrcSJwxh9wDB0tcyqVJE8osmE+yTcGZhxkcvZNMqJcLfeoFU8ZDw2cXZ/DT/Z+Y23our//yeqlTfrn2y7xQoQf+FouQ3/10RYzMaFjXW8i77zoXlrd2PpB/DUwtPsNUoMLspuJEwXVWxm1mav2pVPOuxrC9w8gx5TC/5bdk5ak4dTcPD42S7lXcCVIa0OljYPt4R98AAM8wrL2XMe7OKhr6N6CKZ2VmnJtJyuPKFsHuwbxW/zW0Si1jD4516i2gkCqY23ouk49OBqCyZ2XmNnwPbdxFvM6tgKxY8K8OTSbAo9OCD4VXeWwDvke65zXsUhVZ9q4kzVlQYmzX5k0JGtEUubsapAqhEokztEHQ5h2sPvWI7DzQIVpD7udH2e/XoQwN5WHWQ/rt6lci9N9N4cam5zeVKu79HsxWMwn5CTzIEoSODEMGa2+uJSonSpiPVM6uXrsIdnd8341mK7GZetaeieZGfDblfN14vnYg2y7HszMigVAvF77qX4daITpyTVm8uP9FonKiCHINYlqTaVxKvsSZhDO4KFzoVbEXzYKa4esiLtJFRERERERE/hp+6zpUjEAQ+Vdhycoic933pC12dEvv99KL+LR4hc/uFh3XqXS83/j9/4h4AGBOSXEqHgCYY2KwZmQKC/vfmSecZcjiUuZNFqUeI/ZhLOV15Znc+SPqJD9E6d6A2Dc+wRxfFPqurFCBkGVLUaryhcW32gNTYoZT8QDAkpCAVeKB4smBna/gVmcwbtW6g0wDXeYIi8YLK4tO0mfC9a3QaCy8dPjXxQMgxb8q81NPsOfkG9jsNiRIaFumJe8OWEPAjyNBnwGjfoaIDbDndTDmCN4OzSaBizdYjXDqO1C4gFqHVVOT3IOHnF7LcPs2MQV2Bqw6TWqesfD40uMPmd8/nH4VB/HT/Z+QSCTIJXIsdufPRqfSkZvxEP81vaHa89D5s6JIj4JM2P6KEAGidMNo1yHtuhpJ+i3kt9YKAs4Tkm8iTb1J0pwduL84DL/Wlfim6jf4uvgKzyG0LT/c+YEjCdvJNGSS75ZPss3CvXtSZtSZiO7ewZLiAUBmNNK4i1T0qEgVr6pMPjq5UCRwU7ghk8j49OynzG45u1RjQrPNjNlmRiaR0SGkHW/UHo/23HJczi8v6hR/Gba+BF0+h9CmEHMG6YYB0PZdLAY1qVO/dDp2/qkzWF6bjDxpp5CuUxo5Cdg9y5O2bmuJVA9LSgpJn8wkaO6XhLiHsLbLWqafmV7oVVDXty4fNP2AMm6/zcTz11DIFBgsBqYcneK03WKzEJ8X7yAg2O12LsVkMnzVeSw2QbO/HJPFtstxfD2oLlM6VMJdJcdPK6TB2Ow2CiyCT0JCfgITDk+gYUBDmgY1xWg1cj7pPJ3C/qZqLCIiIiIiIiIiz0AUEET+VRjv3SshHgDkrPyObk2XE19tGPez79MiqAXtQ9v/ffXQnWA3PdsQzW51vkh9FgaLgc2Rm1l4ZWHhsdsZtxl/9iN2NV+FddLHDuIBgOnBAxLefoeQL2ciAyEvXvZsh3YHsza7Ha6uF/5IJDD2OFz6rqjdp5JgGpcTLxj4RZ+Ess0FEUHqfJGYZ8pj7s3v2PvoQNFlsHMk/jhGq5E5nT5BJ5HC0VkQub/oxKxHsPcN6D4fsuIE8eXyWshNxtrmu1JLYyoGDuHjvXcdxIMnt/b65ggOvtaC2j61ORV/ivah7fn50c8lxpBL5YS6hyIzmYRneGuHUL6u7ypscjcsKRnYKk9A0ngWlpx8kie+jikqCnW1qviN+wpV8g5kt34QBlO6YnGpgPnRI/LWbaRBxzXI3YvK8w2vPpy9D/dyJOYIU+pNYdqpolSIpPK9CXhw2Ol9Akju7qF+q4lsu7cNm92Gn4sfk+tORiFVEJ8XT5BbEN4ab/xd/EkuSHY6RqhbGfa3/hr3yENojPlIi4tFxflljiCixJwRTCNlKqy4YM3KKnV+pofRqAOCQf6McqpKV+waPzK+3+S0Of/kSawpqagqVqCmT02WdVxGjjEHiUSCh9IDnfrZnhe/l19Le5JLHf9rTc4x8NqPEYXiAYBGIaNHXR8KrBkolFJ83IuijbRKLa2DW7Mpsuh+LyRd4ELSBQBmNZ/1654bIiIiIiIiIiJ/A6KAIPKvwVZQQPoqJ2X8HpO9ajWvLvgKi0aBWqb+jzuYK4ICQaEAc0khQebhgdyzmFFiQbqwo2zKE5zqk24K1Ru8whxKoaXp01gSscT5BbMLMEVFOW3SX7qEJd+MzKcypEWi9HVDolJhNxpL9FWWC0NmiIVKHaFaT8EULv6yUDXCxetxysXjyhO6EOg0G7aNFaIQQIhMUGkFI8fA2k7nk2HIYP+j/U7bTiWdI73eVHS56Y7iQXGOzoTeywUPicdIFaWXvrQ0bs6JXYnO22x2bsTnMb/dfHbf20lVn+pEZkUSlV30LOUSOR81/YgzCWcINxZ7jx4cwZKVQ8aW9WR8+y12g1B20rVZM/xenUrCW2+jv3KVRy9fJfiL6bgH3oasGMwdvyHxsxUA2HJysD8VDeKucOe7zt+x+sZqck25PF/+eXY93AXA3Zwowp9RPtKucEEuVxOZFYm32pvpzaYz8+xM4vOKKj8EuQYxq8Us3j3xbolc+6peVZGY1By4p6GszwAqSjwo41VeMD98moJ0wYn/CbmJSNU1BKGpFDFHprYL3he9loDSTXjnn6bBSxTcTyl1DOx2LBnpKMyhSBUKvNReeKn/nDHqs/BQeZRaCcJF7kKga6DDsYx8E0k5RSVI6wS780Z3b36KWsPCu6f59qEbg6sOpku5Lvi6+KKSqxhRYwT7ovaRa851GCvYPZhGgY3+nhsTEREREREREfkV/hr3OBGR/wFsJhPWVCdh3I+xpqUiMVvQyDX/lfJncm9vfKdMdtrmP+195L6PhYG0e7D+BfimCazsIJSvM+dB5D7Y+7ZDqHqqPtVpqTeFVIE9z8lCrBi2ggLBhFChQX5zFYHvTS3RR6JS4TdzOvLQyuBdEQ59KOTap92Fviuxt/+4SDwAaDZRWMQ/EQ+eYMwRDPJynC/ac0w5pYbQA2TlJUHKrdJvJj+txMJTnnQS11YtnHa3qTSlrkUB8owWfDW+DA9uR8XMRL5uu4B5beYxuOpgJtWdxMJ2C7mYdJEh/k3RnSkScOwVOpG5Yw/p33xTKB4A5J8+TcqXX+I7pSjsPWnuEkxtFlHQcAGxM5ZjuHYDAE2zZuTI1RjNwnPNNmTz9ZWvGbR7EAqpgka+4UyoNoxN7ZczpspgLEoNlgajS72X1Fp9uZl5hzKuZRhRYwTzL813EA9ACJOfc34OL9d29CDwd/HntTqfMPS7KD48lMyIH6PosfImdzt9D57lnF9QVkyX9ghFlvgLri2bO+0q1elQ6qRgyIbjXwrv49MVRyp1hqYTkPuW7geiCA3FnJiILTu71D5/Jb4uvsxpOQeVzNGgVSqRMrvFbHw1jt4ExV81d5WcN7p78fqpFzkYs49sYzbxefFsv7+dy8mXicyIJDo7GnelOz8+/yPdynVDJVPhrnBnePXhrHpuFQGuAf+BuxQRERERERERKYkYgSDyr0Hm6opLk6YYbjpfaLo0boLU7b9Uhzw/DWlGFB4NAlAt+IK0Fasxx8WjrFgRv6lTUVWtgkQuh+w4WN0N8oqFkhuy4fAM6DZX2IGPvwRVugCglDoP+zbbzFg9n+HtIJcjk+SCewUYtgPpjc24KVMot2EVGZt2YoqJhdpVsXZvS5K7BbefP0SScLXo/PuHIfokttEHMUkVaHwqCcKHLgTSIp1f05hHrtFKVkYBNrsdndyKhzEBEq7gVsZ5ZMITtBIZPCsMXSIRKg8UQ3Z1GYET1pJgsVBw+mzhcXW9etj83Snv48rDtHynw9UP9QSrGVnSdTxS7qLJiaNWSBMCA5sRb8pBU5DBZG0N/LaMcRBLLJUHk/HKLKdjGiPvIfP0QKLRYNfrsSQlYYhJJn7SO0W3oVZjGjCcbovO8kqbirzQMIRkQ2JhKHs7r+qU3/kq8vhL4FWBar5VQX8KGo7BHtYCSfRJx2tW6coVuY3NNzbzTqN3UMlV3M28W2Jubgo3/Fz8aBLYhE+af0JMTgzVvKojt4Ty5sY4UnOLIlPS802M2pbItg4z8N89zHEg/xqQ/lD42q866LOQXVtFwCvriI2NwxQVXdhV6upC6NzpyC/OFA4kXBZKNXabJ5iIWs2gDQSFGyTfRqarglvHDuQ97WshkeAzYQJ5vxzHrXUpJpV/A9W9qrO1x1Z23t9JRGoE5T3K079yf8q4lUEhUzj09XJR4u2qJD3fRL+GPmy8v6ywigNAp7KdaB3SmvmX5xOXJ0Q11PGtw/Rm0/mwyYe8Wv9VYRy1V4mxRURERERERET+k4gCgsi/BolCgWf//mRu3Ii9oMCxTaPBa+gQpEoldrsdO/a/rHzjr5KXAvvehpvbkAPunmFoxgzG7j8WSZlayH2LhTsnXHUUD4pzehE0GQ9nFkHZFqB2x1vjjbfam3RDOoGugYyr2I+abiGABKtEhlun58j7+UCJoTz7v4BcVgCnFghpBdX7IHt0AlnMOgIagq1zU84EhfFxxEdsqDrGUTx4gsWI9NB05B0+wj7geyRrewkLv+KodVChPXiE8rD8YGbuTuBoZAR2OzQo68H0Np5UubQWr8xmNA9owqmksyUuU8OrOl6JN8CrgpAKYXRiRFm+nZB3XxxzAYq9IyjTfxLWd97GmvQQqYcP5yRJLL36Jq91ns6k9fdKRCL0Cg/ET6vCYswhXuvHj7k3uZJ2hjKGh4wO60ELNLheWQ23d5WYhk3qiu0ZkR+m2DjkPj6YY2MBkGq1QlqLxYKmWTOUE6ey+IGRfKOV2fvuUDtYx+XcI6hlal6o0IsGNiUFZZuR3v49bmY/RCNXU1Xjj/eF1ahavIal2WRkERtBKie/dj/OmjP5/MZKngtuQ02PSsTpHSN05BI5H9aZQBOVP573DqM4vRht5ee4qPFDbS/DsJX3nN5HfJaeFJcK+Eukgv8DgNpD8L7Y8xr2cq2wd50PKJDW6Ivy1HuEfvIuJoMbhjv3kYeWRRPsieL4W0hSrhUNnBgBW14U3pvey2H3a0I1jwPTUFTthu+U6airViVr8xYsaWloatXEa+RIcg8exL1jR+QeHqU++78auUxOWW1ZJoRPwGQ1oZApSngfPMFfq2ZOv9qMWXuR+uU0fHCpSOjxVHnSrXw3phydgr1YrEJEagQj9o/gx+4//mUGkCIiIiIiIiIifxZRQBD5V6EILkPYhvUkTZ+B/soVANThdQj86CPyfN14lHKFrZFbMVqN9KzQkypeVf7+UmhxF+DmtqLvM6ORn5ktfD14ExQXEOIulD5OZhS4BwhGfY/TFvxc/JjbZi7LryxhRoV++B+ZLSzCAHtIEyxvLiPNy4vsrduwm0yCkDJkEF4tyyLd3L8op9zFG3ovg8trkWbHIQXChm+limcVPB6eKHVKkodHUaQPgbv7YOB6kMhArhYqIrR+G3yrwu1dxFYcQt910WQWFKVbXHyURZ/1OewdMZcKP3Xn434reMdq4FLq1cI+1b2qM7f2RLzu7IeghtBzMfw0Vijr+ATPMKESxI5XsDT/GLvKA2nWHcGg0JCFPOkkcv9Q8HIhzVvBl2dXEJ0TTfW6BnaMqMRnx9O4EpuDr7uKcY086OiZjIcpieumTEYefQWTzQTADW7wc8xhpjV8mx4dPkKdm4wk7nzRPHyrYPYOQaJQYHficwGg8PcrNBRUhYdzzTUDxfdzkCHFpvPinP4uniFJrG3YDmsO+NjT6ePfhBe86+ORcJUcpYZFCgNbfilKhVFIFXxa7w1a3voJddtp2IPqIjm1EM2VjdSp0IqNFYfh4VMN2flvsTQahUwiw2oX0iM+r/8Gra7vQXVnT9HjPLeMFtV7ktmyfuExb1clPet54+8hJS7dyo4raeTIPKHF65DxAILqYa/UAbvRhKXtYnJPXSatxzDcmjXD99XXsTTJw27RI1PpSKrkhY/ZBdfk60iSrjh/sfxrCD8LAbWKIlru7EFedyKoVHiPGYPC3w9LZiYZ369H7uWFa8MGpb2mfysyqQyNVPPMPlKphGYVvNk9qQUZhlSUMiWWxz4XPSr2YP3t9Q7iwROyjdmciDvBwKoDf//ErBYhrUeuAsWz5yciIiIiIiIi8lsRBQSRfxUSmQx11aoEL/lGKJlotyPVaslR25l3aR47Huwo7Ls/ej/1fOvxRZsv8HMpPb/6T2HIESIGSuP011C2Gajche99Kpfe19VH2H2v1qMwnF8qkVLHpw6L672OfHlrwXDxMZLYsyi+b4X/hF/w7toAuwWkPsHIbq1Gun+WoyFdQToceB+avgL73wVAbjZgtBqxqHxwzPQuhtJNuOb1zVCzD0SdgCYThGoLOQlw7DPsIU3Yfy/PQTx4gtFiY9nFXKZX7EbAjyP4qtXrZNR7lbS8BDw1PvioPPGKOQ+Z0bCmK5SpD31XCWJKXgqUawV+1bHoId9rLOlfr8WSmoa6dg38Rn2L8tEPSOsNgJMLoHoPXB6dpKI2DA+VB17391D+/EqW1BlDQcNw5IZEfK9Ph4Qr2Nq8x1ZFfqF4UJzPLs2leYt5eHf+lCxTFtLcZKwu3twwpnEtYRv9enZFv2VHifOeeFzYcnOReXggeXcC7938gHRDOiCY781sMZPbyWepZHqEz/0dSGJOCx4T9UdA+baczL7Dlui9DuOabWbevPgZ29ssorzdDu5+0HA0sqxH+BZkYNN4kuvuh6RGTzySb9GnfA82P/iJYPdgwo1mB/HgCZpbO5DUGkA5HxdaV3WnURUT2x4u4UxSHOV1Fflq2EiC1SbwqwLp9yDmNPmWasS+PMlhnJw9ezDcuknWl6/z5s3ZTK43mZryUPI/monb4F7IfKoiSbvjeHGpDJpOhD1vQI+FsHnE40l5Inm4G90LbyI3pGGPOoVEfwOPKR0hrDkSr7/eNDHDkEFyfjKXky+jVWkJ9wvHV+NbogKC3qwnVZ/KqfhTZBgyaBzYmDBdGD4an8I+Lko5NYJ05BqU9K7Ym/V31gNQTluObZHbKI0zCWfoV7lfqdENJbBaIDsGLq2B6BOgDYbmk8C7Emg8fvczEBEREREREREpjiggiPwrkXt4kO+iIEWfwtmE/fi7+juIB0+4nHqZIzFHGFBlwN9jrGg1CxEDpWHMFfo8IbSJsFtYfIf9CQ1GwZ190OUzYZH1GLndAueXO4gHhRiykV5djTLlFtw7AAM3wJVSKlWk3gWPskVTV7lxJeUKWc3m4Hp2qfNzaveH2zuFry9/L5Rq1HhBUG1Y0wOAgoAGHIkuuRB/wumYfHJbNEJzbS2eBz/GM+dlKqTeFUQSqRxubC3qHHteMJX0rgDuQdBkPFabC6lLviLrhx8Lu+X/cpJH124SumoF8vRbSGsMRqZW4FKlK2NctZyMOYbH9f2Qn4bu9Kc87a4gvbWdyo0HO52vxWbhvjWPawWJvHtpDq5yVwosBVjtVuRSOf1HrcY1NYv8X34pPEceGEiZuV+Ss28/mpnvQ7P6JJLFe7r3UMqUXE25yoY7G9AqtLxXeTDKjIegKwPNJglRJyfmkR5Qg5WRPzqdkx07O5LP8WpAPcEzw24TUjryUshuPA7FhZW4nV4EEikT+izFo4oaV7ka36s/lPq5qM8v5es+izibc4q3T39aeDwuL44T8b8wr/ksgl39kGVEYewwj5Q3nHs/mKKiKZsmYWqdaZTV+qCOzyX33AXi794j9OtPUcZsQ3pnC5j12Ms0gA4zkNzYLBgqXvoOzHoy2n3JA11j9kXDxPQovDb1BkNW0UVUWhi5GwLrlHo/v5ncJEi+SapSw8d313I84VRhk1wi57NWn9GqTCs0j3f19WY9x+KO8c6JdwqNQJdeW0pN75rMbzsff1d/h+Hd1RpG1BjBifgTxOTGkGXMws/Vj9ws5/9OhLiH/HbxAASz0W87gflxGlf8Jbi9Q6iOUm+EUOpUREREREREROQPIgoIIv9K8k357Ivex/Qz0+lZoSdnneTWP2HDnQ10LNsRb433Xz8RtQdU7Q5J1523V3u+yBzQaoWY80Lu967JjpUMavWHGn2gzmDwCAVTviAYqNzBkAtPmec5EH1CWDg8OOxcZCjOEw+Daj3QeVVidovZ3DLm4NP2PVRHZzv29a8BlZ4TqiuAsGDxqSQIFRlFJf4Uhgz8XEv3m/B0UaIwFrvXgNpwawcENyzpyP+E9AdgFLwGLGlpDuIBgK5nT9w7diBtwdcYHz5EWS4Mn5EDUd3bTZgkH2XD4XDneOnPQemC3lq66GFXuFDNpyYBtwNIyE8oPN6xbEdcAsrgOeczLGmpmGOikaklyO2pyDN2kzliOGa1nG9vL2Ff1J7CVIJmQc34uu3X1NH4o/xxqOP7onSDXkuwACkFpVcZiclPwHbma6TRp6B6T/AIJVuhwZYVLYgHAHYbPtteZny15zE2mwQXtpY6HsZcQjztjDw9r+T9Y2fGxS+o3mYhhv6ryDRkwYxxeBZIYMUPGE85+lEYzl7mQHB7JnXSYo4SPA+sWVlEjZqKtlN7PLutQCKXob/zAI3ZSzDlPDEPmo4nw785n8XXZNPeWJb0LIPX7tGO4gE8rvIxBEYfFIwX/yg5CfDDYKwqd3bVaOcgHgBY7BbeOv4WO3ruIEwXBkCKPsVBPHjCjfQbrL21lqn1ppYwPgx0C2RVp1VcTbnK1ZSrDKk6hBlnZ5SYjgQJvSv1/u3zz0+HnZOKxIPiHJgmmK+KAoKIiIiIiIjIn0AUEET+laToU5h+Zjog5IgbLIZS++ot+meWEPxTyGRQZxBcWCGUGiyOq6+wg/8kmiAvEX5+RxAIun4h+AkYc4UF0cNjUJAhONtHnYDTCwWzxXJtBJM5t4DSqx+4B0HlzsKiVOkqXK946cUnyNXCjn/tgdDhY9y1gXTWPjZvK5sNlbvA1Q2gz4CwlsI428YWjVWlq1CJQaZwiKBQRu5mZPcJ7ChFQxnXwA3Pi2uEbzzDoGxzGLEb5Brs+gwkF1Y6Pc/e8CUkrn7oI3agqRuOz4i+KHQaJBo3LCY5MeMmF5ppmmNjyT9+gsAP3kBr3UvY6WVYG7yILMq5iGCt/yIX0pyLMjKJjIpelQlxD2Fd13Wk6dPIMeUQ4BKAl9oLrUoLLiDLuYPqwktgysfuWYGb7Vez/Vomea5b2RO9s3C8doHNmFjxBXxSH6K03Yf2H8KDo3BuiZBmYsqDHRPQjP6Zmt41OJ/s3CejuUcVpOfWQ9I1QTQKbYKm91Kkh55amNrtKG7tRGHKh/JtIPmG8w+mXGtSzDkYrc5Fp0xjJklYGb9vKAUW4Tm7yF344JWpVAvyw7S5KOLH4OlLVHo+Fx640NbXn8KfRrOZnN37ydm9X/heKqV8o3D4+T3h+8BapJYfwaa9wrtdw8MMGQ+dzzc7FvJT/7iAYLUK73fCFdJ7L2btHefvnc1u4+Cjg4ypPQaAE3EnSv33Y3PkZoZVH+a07GKAawCdy3WmQ9kOZBuzicyM5Ie7RREhCqmC2S1mE+j2O+5HnwGJV5232W0QfwW8yv/28UREREREREREnuI/ZEMvIvKf5WD0wcKvr6ZepVlQs1L7dizbEZ3qGSUC/yyeZWH0IUFIkKuEP+FDhd1Sj9CifuYCYWc16RpsfQm2j4eDH8KG/nBmMaTegYgfYE13YZc/MQJOL4B1fYQc59JoPgnc/eG5mYIA0WhcKf2mQlBdoVzk04swjU4wRGwwSvj+2KfC/J7sBHtXgLJN4doPEHdRWJg+wZhDucQ9vNGq5CKqX21vGkvvCkZ8lTvD8B3gVU6IZPAIpsClDLZW75Q4jzL1kASFY8xJQV0plOBxbXC78R6qnwej3NEL9f3FlFsxF9lTrvxJc7/BUn0U8ls7kBVkQuVOJccu3waZwpUx5Xo4hI7LJDKeK/scazuvxmw2kJSfhLfam+re1WkS2IQwXZggHoCwE7z/XdBngdVMYqvZDN8SR9PKKvY/2l04Zq/Q5/jYuzGVvh+E50/jkO6YAOtfEHbUO39W7BnmIsmIYmj1YUgomWrjqfKkmba88O48IeYsspwk5MUjWYrz4AhU6igYaD6Nqy+ENafAUMq5j8k0ZRWKBwAFlgLevT6b/AHPIXV1efzgZFjqN+ZmQg5z9j7CJbQ8Mk/nkSVubdsgf1TMk+HWTvIMRZU9lDg3pyzk1yJsnkV+CjwWq2wqLRmGjFK7JuQVRZ2k6dNK7ae36AujTEpDLpXjrfFmUt1J7Oq1izkt57Cw7UJ29dpFm5A2uMhdfsdNlDRidGx+9lx+Lyarifi8eO5l3iMuNw7jn3n+IiIiIiIiIv8IxAgEkX8laYaiX+rvZ90n0DWQMG0Y0TnRDv10Kh2Dqg5CKVP+vRPyKgfdvxIqExhzQCIVdvCtZmHHHoQIgOL+BxaD8KdwsiGw3cniP+M+5CRCi9fgZLFwc4kE2k8HnyrC9wq1cK2AmtD2PWGxlJcC2iBoPF6IPrDbSg9xliuFcPq6Q4X5R+4XxqvRG2r0BbkGOn4Cbn6C2BDaBGKE1BGP058yvH42XUYN4WSqBpNNQsuKPvirrXhaPGHSFXDxAbW7wyXNJj2uEgkM2ggPfxFSN8JagMWI9dJqTO0/ws0ejeToW0Un2W1II/egyrhH0IdvE/vaB0VNBQVYCxDM5LLjoOWb2Fu+CeZ87PGXMPrXwKYLRnJqAbUK0tnSaj6ro/dwK+sBrzd4nRPxx3np4Fj0Fj0eKg9erv0yXct1xUvzlIGfuQASLgtfq9yJtfmSkR+L2V60oJRL5Lxctiue6/pSopbkle8FAcGvGqTcBsCYcZ+z2XpmtZjFN1e/IS4vDoD6vvX4qMaLBO18vcRHJruxFXOljigeHi35edrt2B4cRTpyL/wyB+7sFt6Z6r2g8TjYMgrfLrNwU7iRZy5ZmtLfxZ9sY3bJcYF1ybt4pWsn9Nt34/LpF8y6KggRRouNH6PNDFq2mKQx47FlF52vqlIF/wlDkO3oV2yOVuyPn820HqGoPBB+TpxFFMkU4PZnKqo8jvYA1Gn3qO1bm4jUCKc9W/jVK/y6aVBTVt1Y5bRfda/qTgWAAnMB6YZ07mbcBaCKVxW81d6E6cIKUyP+EBpPIbUo+WbJNolEMCH9i0jTp7Hu1jo23N6AwWpAIVXQp1IfXq798t9f2UZERERERETkv4YoIIj8IfQWPZmGTGx2G24KNzzUHv/tKTnQJrgNG+9sLPx+5tmZzGwxk1Pxp/g5+mfMNjMdy3ZkdM3RBLsF//0TMhuEsnTbJwih1iBEH3T5XFgkaoPBzR/qvwhnvyl5vquvUIWhIN35+Lsmw5QICB8sXEciFTwE3PyKKjyAcP728RDaFNp9IPgvGLKF9AhtoLCAMulBWUrZN10QYIPwYaQ3m0AmdswSOx5qL3zdgpD7VCzq22813PxJMHg05aK15aH11lChYpiDCSQ83o3OTxfSMKwWYYHvHojSZoRfPgWZEkIag0KNNeIHElpNZbu5Js2y7lP/yHTnc02LRNUAZB4ehaUTAVCphUoOpxbCyXnCfr7aA33LV9mnj2PG2bf5oPYrdIq9SYV1/ZlWoxeZTaaxLvZn6roE063xdLLMeayK3s2cC3PQW/SMrDHSMc9dKhOM/Yw5oHInNV/YRVdI1EiQYMdOk6AmeN/ZX1I8eMKl1dB4PNk5j7BL5NiDG7P1+CQuJF1gZM2ReKo8CXYNoMzDU+g2jS6ZIgNC1Erjl+HUAiHlpTgKDaZa/cgy5xEQFA7NJkJGlOCVoc+AzCj8Ti1mVrPXefXcJw5h+nKpnI+afkRBThybms/BLpFwKPUKGx/uIs+cR1R+LOpB72F7YSQzzqYSnWtiff8QyimzkBjuoQyqhf+mtVgfxmBPSkZdoSwqWzyKXYMEkegJtfojdfPhxRYFxNp28cWdNN5tMg73k/NL3muzqdhcfEjMjedc0jnuZNyhpk9N6vvXJ8g16NdNUtU6qNgRbm7DIzOGN+qMYfjRSSXKK5ZxK0MNVJCXCm6+lNeVp6pXVe5kOFaTkCDhrUZv4al2jLbINmaz/f52vrr0VaGYJJPIeK3+a/Sq2KsoiuWP4OoLzy+E77rA0x4erd4S2v8CCswFLItY5pByYbaZ+fHuj2QZs/io6Ue4K92fMYKIiIiIiIjIPxWJ3V7ab68i/w1ycnLQ6XRkZ2ej1f6JXyT/RuLz4ll8dTH7ovZhsVmo5VOLdxu9S2WvyqhkpRb8+4+SUpDC+IPjicwq8gWQSqS0DGrJqw1eFUQPlQcq+X9ovil3YGnzIpPCwknJYfAmrBov7mtc0JoK8PtlLrLbu4r66IJhyGZIvg1bR5V+jclXhUiHZ5EYActaFX3vV11IbbiwEu79LPgu1HoBWr8l+BE4wWa3cS/zHm8ef5Oo7CgA3BXuvN7gdTqW7ei4ALLbhSgHu00QBZ6qR19gspBdYMJHH4Vi54Si/G33QOxdv8QcUAflrklC3rYxGxIiuPv8HIafeo8CSwGbm8+h6veDSr1dS4OpxK65jeG6YMAg1WqptG0F0q3DhVKQbn5k1X2F7ICm2JGg1siY+fBbfok/ztZWX1F5/RCwGsl65TwkXMZmNZGh9ceEHXcXX1JNOYw/+Q4/9fyJILegogtbzViOzkJ+8iuQKYgbfpbMPD3BqnwsciOX82K4np/AG1ER4KSMIgBqHclDt/BqxHwsNgudyz5HOY8KTD8zvbD0YyP/BizVVEdxdKbTIezdv2KF3Ehnz+oEnF2J8u4esFmxhrUktdVU1qZcoE1gUxqZLYIJocUAKncM3b9Ckf4Q2bHZ6Gv0Ir7hSDbEHeZBbiw1vKoxrFJftDlJuB74UIi0kEgxV+xAYouJvHzxM+r5hfNhnYlcT5Xzwa7bfNtZQ+DuYQ4ihq1GH+42HkmBxUCdE4uQP+1HoS0Do/aTJPHjYVYULx/rD8BHdSbR3mjD88xiyIoBbRlsrd9GUrUrt/QpjPp5lENahVap5dtO31LFq0qp70khqZGwvDXU6E2BdwWuBVRi9o2VROVEIZPIaFemJa9V6Evw3ndh6FYhegdIyk9i1fVVbL+/HYPVQFWvqrzT6B2qeVXDReEYgXAl+QrD9w93evl1XdYR7hf+6/N8FlYTZEQLaU8xpwQPlJavCeakLn9NqcvYnFh6bO+BxW5x2r6r164/F0khIiLyP0FyfjIxuTHE5cYRpgsj2C1YjDASEfkX81vXoaKA8D/G/7qAkJSfxIv7XywMn36CXCJnY7eNVPWu+l+aWUmS8pNYc3MNW+9tRW/RE+4bzluN3qKSR6USddx/F6YCIV867T5IAO+KQvTAU4tjrFbBGNFmheOfC2HpzqgzCNz82eJbhlnXlzC56nA6eNfG26RH7R6I1D1QWKikRsLihs7HCGkMg3749QVCdhwsbSFUeHgsXrDlRSEKoTjuAYJvg0dIiSHi8+J5YecL5JpLlp1b0mYBLbxrCpEPT8hPE8wgZSpw9RY8IIDEbD1f/hzJy7XlVN7etaSzPmAfsRcyHyKJ3I++UgeywpqzKXofa2+txWQzsbbZbOpuGuvcdR6wtJ5D9OxtmGNjQSolZP6nuAaZkWwZhTUgnPttlzLtSAYXHgnXrhui5YPulZh7402q6cJ4L/Y+Up9KmH2r8cgzkLeuLuRe1j0AXBWuTKk1hgC3YIJ0YSUWqKasR8i3jkNSbyj2/DSkv3xWNE+fSqR1n4ci7T663a86nbu1XGtWVWvJ17fXAsIudS3fWrxc62XGHx4vfEwKd/Z1WIlu42BBEClOQG0sXT5n2I2FPMh6wAthXens3xipBM5l3GbNwx3oVDom1nmF5/JyYetocPEiof+3zLr3A+HaSvQOaIpH3EXkafcxVe6Iybs8apsdeUEGrO/rWIIUwM2fO30WI3Xxp/LWMVi7fEGSIpgy69s6/XxtLd8gtdEo3M0GVNGnkF1YBVYj1HxBMBh9/P7tvr+bd0+9W3heda/qjC3fA3+VF6nGLKqXbYfZbuZe5j2isqPYem8rMbkxhf1D3UNZ3Xn1r//ia7UIfhyX1wk/SxEbSG80hjyPYOQSCZ73juBydaNQfaTHIlC5Fn3eVhPphnSsNisuChe81CV/FgvMBbx1/C1+ifulRBtA2+C2zGk1p7BE5J/CbBB+7uQqUP+1/5fcTLvJwD0DS21f03kN9fzrldouIiLyv09UdhRjDowhuaBI+C2rLcvSDksJdv8PRG6KiIj8x/mt61AxhUHkdxGRGlFCPAChvNn8y/P5ovUX/zOhqwGuAbxa/1VG1BiBzW7DRe7y51Mt9FlwfTP8/G7R4kmmgC5fQM0+RSUZ81Ph6g9wci40GgMJV0sfM/kmaMtQxy0Ui83CvFvfMg/oXa4b7/mMQp2fKpQsVLtD63fgl88cz1e6QvsP+E2eqG6BQtrEtjFCSbfbO0uKBwC5SXBzG4QPA1fHhdCZ+DNOxQOA+RHfUD2kB14VOoDCFdLvw4VVUJAqeCTUHw4+VchQ+PH6pgjyjBZ8kiKcLi4BOPIJ1k7zuKH1YlX0HhLid1PFswoL2i1g7c215Fok2MKHIb2wrOS5Cg32wLrIfU/g2qwpXkOHIvfzRHJtDUikxLVfRJ91j8g3FRnLXYnNYfDKK6wYNY3NUYsx1x6AyrsCqflJvHjmA7KMRfPMN+cz+/J85rX6AoVUwYOsB+hUOnw0PgDcM+cR2PlrdAnnkB360HFuaffw+XE41tEHhbz1p40OJRLSm43n+0ufIpPImFRxFG1c6mB/+Ai3+wVsbbSMmfcXU82vJkuidjJkwGo8E6/hdnaZkOveYBRUaI9driHcpw430m6w9v5W1t53LNvYOLAxCptNiDwo25zcNu+wIuEIOpkbXcp1IsdqIikkHNdK7XCXu+Clz0UasV5Iw3laPADIS6Z8ahTpd+OxVO6PfNtoAodsLfXzlZ5fhn/9keBVQfhTtdvjaBWvojQXUwHqpypB3Mq4xdSMW0glUj5o8gGHYg/x7Y1vSSlIoZJHJcbWHsut9FtsuLMBgJjcGDL1ab8uIMjk4FsF2rwjRM5cWIH33rdwsJmUqwQvk2LiAYBSpiTQVTAfLTAXkJiXCIC70h03peArYrQaScxPLPXyiQWJGKyGv0ZAUKiFP38DvzY/N4VYKlJE5J9MWkEak45MchAPAB7lPOKdE++wqN2i/7nUVRERkf8cooAg8rs4EnOk1LaLyRfJN+f/zwgIIPxS76yE2h8mLRL2vuF4zGqG3VMhoBYENxA8BM58I+T+B9UFuauwk1pauTyPUMhPQVIs13pW3Vdpl/II9bJWRaaKwY2g25fgXw0ufieIFMENoXpPoVpDz2/AxePZ85fJhGoHI/cK+e4n55beN3K/4NBfpatDZMPllMulnvIg6wGmSu5w8VtslbtiTUzAqGiN2ZiKqkwYiqR4FFnxpAT14PSDdHrWCcAr+Uyp40mSr2M1Gnnv2mJicwXviMjMSE4mnGRju6X45Biw1xmJPeUWkkcnik5UumEbuBGbIY2QoZWRVHsOqbc7ZN0HbRksFTqy6bbRQTx4gsFsY+flXPo2eIFTlhzamPK5WhDnIB4UZ8HVRYyuOZoPT39ImDaMGc1nEOIWQmTMJcrm+SCL+NL5zekzkUafhAHr4dBHgncFgEdZcp6bzqK4Q2QaM1kcPpPg7w5j3L8EgExA6urKnIWfU1AplKtpESx/sBVPlSfd+6/ER+6Gl07YuVcAA6oOZFPkZkw2x5x4uUROj/I9qCDVgFsopN3D/fTXvF3pObLqtGLW5fkcSxBKWUqQ8FxIW96s/xr+geFwY0upn5nywWG4Wx5bs6EQfwSJM4HqCcZcx1x9ZxUh8lOoqtAhl8hLhMwPrTaUy8mX2fWwKOXnXtY9pp2axjuN3qGeX73C99WUHQsZcYK5ZzFfEEt6OtbsbJBIkOl0yL28BCNRlZvwc3J4BtzeIUQSlW0OnT99ZinE2NxYFl9ZzM/RP2PDRqsyrXi1/quE6cJwVbhSz68ekZnOS67W9a2Lq8LVadv/El4qL8J9w7maerVEW3ldeafRFyIiIv8c0g3pPMp55LQtIjWCTGOmKCCIiPw/RizjKPK78HPxK7XNQ+WBTCIrtf0fjynfscrB05xaIISo5ycLkQi9loBfVSF3v+nE0s+rMwjSIrmRHw9AQ/8GtM7OwO3k/CLxACDuPPw4FGw2YZe0anehMkNBBjSbIhj22X5DmTa1FsKaQ8V2RRETzlBpIfa8EI1QjGflkpdxL4M8Jwl71AmMaTYeTpxF7Bsfk/T5Yh6Ne5PYz7dicq1GbIZglJeWbyZPW6H0OejKYI5PooJHUZ+aXtX5sdF0An/+CNX37ZCtew4avoT9xUNYWs3E3GER+lYrScyT817iAeJrtEGqT4MfB8O3nUDlRl5gU07GOHHyf8zVR/kEuJTnWtY9bG5+XM2OKrXvo5xH1PesSs/QjkTnRDPq51FkGDOoIy2LTApkPCz1XEnKLSH1pcscGHUABm7A2usbvsq+xk8xB2ji34iQkw8w7j/ocJ7dZMLoquDV46/x8ZmP2X5/O9/d/I6+u/tzKOkMiXmJpBSkYLPbCHYLZlWnVZTTFvljBLsHM7vlbNwVWvytdljZAU7Nh3sHMIY25OOLXxSKBwB27Pwce4TPL83DFFhHqJhRCja1D9a8AiGlosFo7Mpn7Ea7+QmRKRaTYEqodyI2WIz4nP+Oj+tOdnx2SGga1NRBPCjO8mvL6VdZqOiglqnxtFphfT9IuCLM02xGHxFBzMgXedi1Gw+7dCVm1Gj0N25itzwWKrzKCakKk6/ClGuC2BNYR6hI4oSEvASG7xvOnqg9WOwWbHYbx+KOMWjPIOJy41DKlAyuNhiltOT5Sunjtr+7IsxfgIfag09bfkp5naOQUsatDAvbLsTnGe+HiIjI/z65JudRhk/QW/TPbBcREfl38/9CQPjss8+QSCRMnTr1mf02b95M1apVUavV1KpVi7179zq02+12PvzwQwIDA9FoNHTo0IF79+459MnIyGDIkCFotVo8PDwYPXo0eXklS6D9U+lRoUepbcOqD8Nb42QH8d+CWQ+ZzhV5QDB0MxuEHdXYc7BpGJxfASfnkaPUkNNpVmH+PwByFbmdPyXXxZPklq+y5N5mAMaEdUd3dknp17AY4MZP4F0BCtKE6IfNI2DjIOF6xd34n8w56gQ8Ov34/Mc7vtqgZwsbDUcL9xJz2uFwu9B2ThdAABMq9sfn8josNccTO36yQ5k+AGPkPZIXraGyTqhYcPZhBhkV+jxVlaEIW+PJ5GUbCn+ZUUgVfFn7FQI3DkF6/4Bg0mjMRbJlBJKfRmPxDCfqraVEv/Qa+qvXiMx5yMhz00n0rwLxl4RBf/kCZeX2+LopnF4TwMdNhZcph5f1NqRWM5XcQ0vt6+/ijyb2PK8GtuONWuP4NHwK2VmP0CRnY07PFEwwS8HuXRFzZgGGR0mYMvTYtOWR+ValeWBTAIb5d8f8fcndfnXX51iTub/QxLI4n5z9hPtZ9xmyZwhrbq4h05hJuF84yzouY/Pzm/m+y/fMaz2Pen71qKnxRbq9mIeEmz/pUgmnks45ne/B2KOkqF2xNplQ6j1Zyj6PVCVHHnsAdr8qCAgezp+ftfPnYDUIERhrusPGAXB3nyAmPEHljjruAh0enGdrq68YULk/Lcq0YHK9yeSZSv+3NcOQUWjqOr7qEHyuPK7K8vN7kJ+KOTaWR0OHYSz2b7jxzh0eDR2KKT6+2PVdhfl7lgUXx4oKxbHb7RyOOUyavmQ1jAJLAetur8NkNRHsFsx3nb9zEMUqelTku87f/WcqwvxFBLsHs/K5lWzotoE5Leewrss61nZZS1ld2f/21ERERP4kT1LxnCGXyv+nIk1FRET+8/zrBYQLFy6wbNkyateu/cx+p0+fZtCgQYwePZorV67Qq1cvevXqxY0bRWHnn3/+OQsXLmTp0qWcO3cOV1dXOnXqhMFQtJM5ZMgQbt68ycGDB9m9ezfHjx9n7Nixf9v9/acJdA1kWuNpJY43DWxK13JdkUr+xa+Uyg3KNCi9PaCWkMueEAF3i8Qna7nW/BB3lE8K7hI5eD3J/VaQ3G8lkYPX83HeLU5bs/g5P7Yw19BLrnFeku8J6Q+g+WS4sxfOLhHCwEEo0bj/bbi4CsxGwa/h6gbBeHFNd9g+Af2ZxegTrxaVyivXSkhReJo6AyH1rlCJwa+6Q1OgSyDLOi5DpyqKXpBJZLxUeSBN83MhKxZTgQpr5lN5/Y/JO3oMb3M+/loVVpudL87mk97tWyjuVi+RQP2RSCVWfCupmV1zPD81/YztrRfiG3/NsdTfE7IeIU87jyIoCKmbG5516/B21eGMr/QCdzIjhXKZgEnjQR4FvNSi9IXO0Ga+5FjTsSddR7rmeZoGtyRMG0avir3oVbGXQ1rMy1UG4ZMejbdMxbDbv9D54BwaHvkCv1A5NosUS52XnV9E6YpFF879geOJGvUGD4ZNJnnRGszZBdTxqk5933Dcpa5On6Otezt2xf9c6vyvpl7FW+PNvEvzeO/ku6RnPyJQqqKqV1Xq+NWhmtoX//xMZOmR0OlTaPs+KN1A6UaOsfSdJzt20vRpnHRzx1a9t2OjRIK12fvkRjzCd/yLSG3C4j43PYFH3X/EFtK02L27kdt2FnbvSkJVkLPfCCUnY87AxoFw5JOikqVuAdBxBq5XN1B5/WCGl+2Mn4sf55POY7Y58WEohkau4fP6b9HbYEF1a4dwMOk6NpOFjO9WYzeXPN9uMJD1449O255FgbngmSleJ+NPkmPKQSFTUNu3NqueW8WOnjvY0XMHK59bSW3f2shl/6ysQl8XX2r51KJr+a6E+4U/M0JNRETkn4OXxosuYV2ctg2qMuiZAoOIiMi/n3/Wbyu/k7y8PIYMGcKKFSuYOdN5mbMnLFiwgM6dO/Pmm28C8Mknn3Dw4EEWLVrE0qVLsdvtzJ8/n2nTptGzZ08A1q5di7+/P9u3b2fgwIHcvn2b/fv3c+HCBRo0EBaaX3/9NV27duXLL78kKCio1Ov/U3BTutG9fHcaBzbmVMIpck25NAtqRhm3Mv+O6AObFXITBZM4Yy54lhdqp2t0IFdD01eExWv150EiBbWHYPpmyBF8DjKj4dw3DkNmVmzLrvgjROdEsz/uGC5yYaH8pNRcjs3IgnpvMlhXBZvGS4hSUGmFlARneISAR1k4UFLIAeDkV4IAkJMo+DX4VCGl19dcN6ay6cEO7HdW0s/cm/CA+vipPaDFa8J93dgq3FP5NpB0DQ5+IOzwPyUgyGVy6vrVZUuX9aRk3EOCBK26IjJDPtaEi1CmPpb8Zyy+bDbyc/WsHd2AV3+8zq5bmeQYvflm1C+4plwGU55wf5H7YddkZEBQv++E+RiyBYPA7l/BnteE+T1BpaXAyxv7V9Owya3ozXoaXjuFKvY8uY3GYm/3IaYr6zhTty9v/DKRYVVeZkzrBqz4JcFheiOaBaJ1SSMi5yHeLV9HEz4Upd3OlLqT2f5gBxKJhHG1x2HHTkzGXdrJPJD4qGHDC0ifzCcnAVnsINwbv45R2QRJvZeRXV1VVMbTPRBLlyXEffAFPAmXN5vJ2rYDm8lCwIcf8HmzGRgyMjCXK4cpyjHSwK6QYXzKWLA4eaY8NHLB6O5s4jniU2/ifXoFdJop5P9vGS2kxDyhbDPo9y1sG4u76hlpLYBSrmbK+ZlMD59C96avIIk+BTYZtsBGoHHDK+QRkkvzBHPR7l+h1Lgz/MckRtSbTetmEmRWI9m4klAgo/PB94sEsOJcXgONxgqeCFIpVO4Efb+FQx8iKchg5/2dWOwW+lXqh6vClXxzSUGpjm8dKtlkBJxY6ug/otZhM1gouHKl1HssuHARa0EBct2zn0Vx5FK5g6j2NFqFFrmk6L9cb433v+PfTBERkX8dWqWWNxu+ibfGmy2RWzBYDbgqXBlefTgDqgwo/P9FRETk/yf/agHhlVdeoVu3bnTo0OFXBYQzZ87w2muvORzr1KkT27dvByAqKoqkpCQ6dOhQ2K7T6WjcuDFnzpxh4MCBnDlzBg8Pj0LxAKBDhw5IpVLOnTtH795P7dgBRqMRo7FoIZCTU8qi8X8IV6UrrkrXf1+db6tFqGm/cYDgK/CEusOFKgdufoJg4FMBtk+AxuOExdip+UWVDJ5fUKKqgQQ7Eomk8PviNeoBJBIJknNLkF/4Vgjlb/AS9oEbkKzp7tDPXLUrqQ1GkKUNQokEr86z8Tr1tSB4AATUwlzjJWzqAIwGyHbxxDTxDDKZiq8ufcWRuKOFY51JOEMdn9rMa/kpfqY8IboiuCHc3Q/bniqLeGw2hDYFN1+wGCEvGZnFSIDCBZVnA07dT2PesSii0vMp71OWNzsupKW89NByqVbLwwJ4c/VlVo6sTWRaCnqDBEXaLdj3lrDwLEh3FAdOfw31hsPR2XB1PdYOX2LrtQVJ6k3kdzdAXjIJA75jRuRGTt0QjCFVMhVDK/ZhWJmX8d4xGWoPxNDmbaYeHInVbmXlrYX0rTCUNWN7cDPOiFqmoVUFP3T5d/G9ugoKMqE6pATW5u3zs7hYzDDuWOwxGgc04pOqI/HOiIYjsxzn+xjZhQXIurUg5YIMrx4/IrXnIfPyxa7x4NG4dzDdu1/inJy9+/Ce8DJ+O3qT32IK+tcmkTrJ8d8myc371AmoTUTaNafPuI5fHXY/3F34/an069Q258G9g0KKQHHxAIT0FpkSGr2EV14qdXzrEJEaUWLcZoFNuZwagdVuZdqVeVTr+C2Va/aFc0uQyPVIDnwgpO88IeIH1LUHManJy7y9P5GLNXzoVtcdmcxK5TAltjs2SnVNuXcAAmoKX2s8oVZfKNsMb5uFHhWeZ9v9nziXeI4l7ZdwMv4kR2OPFpbY9FZ780mNsQT8OFwwGy1Oo5eRuOqQ+/thul/y+QPIgwKRqlRO20pDJVcxtNpQDsccdto+suZI0XRMRETkH4Oviy9T601laPWhGCwGNHINvhpfFLLS0/9ERET+f/CvFRB++OEHLl++zIULF35T/6SkJPz9/R2O+fv7k5SUVNj+5Niz+vj5OYZwyuVyvLy8Cvs8zaeffsr06dN/0xxF/mZy4mFtT8fFM8CVtVChrVBRIeEyuAfC4B8FM8N1PR373j8MZVsIaQaP8Yw8SN9anfkye6XTyw4s0xbNwTnCNzYrnF+GxLMstH4P7uyEkEZkVWjDDn0ci899WGheVNmzMp/3XUqFXa9hDWpJgbIZ6ct2YXl3PIuuf8HRxBPY7Dbq+tVldM3RZJmyHSooRKRd43T0QXqd+lbYoS1TTwhlT7wKWcW8HtLugUUvmCmemCc8D7MeQ72X2OAymi8OFe2OP0jNY9yG6+weWhX3pk0pOFOywoLypbEsv5lDXKaeb09Go/DdiURqo1dcpvOSkm7+wuIxpDH2wLrYXYPIOXKOlEVzkPv64jNsPMbnazD5ymfczSpyt6/qVZU4Qwa/uJfl+ardUFz7AUmjUUgoEnO2Pvienx5uoKy2LN3Ld0cma87p3OsYw+pSz7MK/sl3OJ9x00E8eMK5pPNEBLUm0L0M5CVBtR5CKU8kghAUuR+u/YjCxYi8YSOyTt1AVa4cKqUSe0qSU/FAeAds2LKyQKYgQufLRX0EPT95F+P85VjThbB++bVI3uz2OiMOjMJqdzTOrO1TmxxjDjmmIjFSq9IJ/hx+VQW/AWc8PAZNxuO5ZTSfj9rLW+dmOggUDf0b8kr4BF46WJSSZVO5C14a5VoiibvgKB48RnptIy1792XpiMqcTd/K9Ctb0Vv06FQ6xtUcSNcqXfDa97aTCdkhJ0EQ7ZSP01u0gbgAk+tNoVel3hyPO86sc7NQyBQMqDqAMG0Y2YZsavnWIDA5smT5yPJtoOFoZO5afMaOJeaUo7/HE3zGjUOq/v0lECt4VGBotaF8f/t7h+Mdy3akUUCj3z2eiIiIyH8TlVxFGbcy/+1piIiI/I/xrxQQYmNjmTJlCgcPHkT9B34J/E/y7rvvOkQ+5OTkEBIS8l+c0f9jok+WFA8AavUDfQZ800QwMAQh1L/JBGHBfXRWUd+7e2HIZrj5U2EKgvTRaTq1mMI2XXkeZjs68jf0q0cti11wrC/Oya+EEnLaQEi8wkl7AV9eX1rYLEGCj8aHMwVxqAasxfNBKnEvTkC9/hteuvE+6Yb0wr5XUq7w+i+vs6DtAqYenYrBWuTZ8UPMQdpU7YxH8g2Ivww7XoHOcwRTxid4lReEjb1ThEXxY1IrDWDheuemkhP2PuLAzBlkLl9B9k/bsZtMyDw9Ubw0jpPBdTh6NA6AvdfSmTmoHQ+yzyGp0VZIl3h4FO4fEnb0tWWgx9dC+sLP7yMBJBIpuuoDUEx/i9hXp5H46QKMW74uFA/CfcMZW3ssV1Ku8CjnEfGmDOI6fEBIfirSuIuEuIcQmxdLx6C21NSUx6aQUV1XFQ1yFlxdytHE49jsNgDmNJ/FD5GbcFW4MrBcd57zq4/UDjfyYll+fwsb4w7TvM5k3LsvEHL4dzxOcZEpoGZf6PstJoWctGZVCFBpSJ01G7vFSujyxU6f2xNkchsZDUYy9846IjMjueQbzthFb+JlVYNCwc/516hkzmFZx2Usj1jGxZRLuCvd6VGhB/X96/PuiXcdxmvuVw+S33Ws6uEMiwk8wvDPiOHTptPJsRaQZ8rDQ+2ByWZl4uGJhQKWp8pT2FGXySCgNhz6uNRh/W6vJrNWFzbdK1pYZxuzmXN9GQXVRzKyWg+Ut3c6nuRfA75uAPVHQoupQgTQY0xWE+8cf4eE/KL0kxtpN6jvV58vWn+Br4svqLxh4kWhPGZ+ulC+UVdGSEkCVFWr4jNlMmlfLxLEQEBZry6KOe/xs+EOURf3U8evDtW9q//mUrCeak/G1RlH74q9ORhzEIvNQvvQ9gS5BYmlDUVERERERET+FfwrBYRLly6RkpJCvXr1Co9ZrVaOHz/OokWLMBqNyGSOgbMBAQEkJyc7HEtOTiYgIKCw/cmxwMBAhz7h4eGFfVJSUhzGsFgsZGRkFJ7/NCqVCtXvDJUV+ZtIc1KbXa6CWv2FtIbiIep2G5xZJCxuPcoW7djbLHDgAxiyBU4vFAQFiRT/hBssazWX03HH+SnuKHKpnEEhHajrWQXf69tLXjc/FTIewK5JpPaYz9e3Vhc2+bn48XHTjzmbeJaNdzbyo+RHegV2osvWdRzNu+ggHjzBaDXy0/2f6FyuM9vvF13PYrNgL156MzdJSB/QhQg+ECCkauSnOYgHAKl2HUbLU+HhQLCnhnW9fFAdnYp/u5bo+20mN1dPlk3Gsps5nH4sHgCYrTbqedWgW9wxFKenCAerdRfy33dOgnbThCoTWTEOz156cyOaejq0z3VAf+Mmd9KF3fyKHhUZUWMErx17zUEoWXtzLavazqKyXk+VgkrMr/gW0q37sV0+gNzXF49+YZhTUpiS6MfEHt+wLfsYnX3D0bkFoVPq2NR8DoGnFqM4MBfsNqoGhtOy7VusTb+KRO0JSdfhwoqiOVrNEPED5KeR334ah27v4vk115AolHiNGorUzR11zRoYbtws8fw0dcORSnIwepcn8p4QtXI59SrjnoqC6G3vzaCynZlXrh/66qMwufqw7PY6Xj36KnaK3tUPG7yF783dwjtb3KjyaSQSrN4V0D8/n8kRC7hwRojekkvkWOwW6vvXZ1K9SUw/Mx0JEma1mIWfylPwrJDKnYtvT4Y25fMo64HTtpWRP9K94UcEFRcQ6o98LOjlw9nFQqnL1m+DXInFZmHrva0O4sETLqVc4mb6Tdq4tAGFWjAB9Qxzel25TofXsGHounbFcPMmaLU8qKBh7OEXi96dm4Ib+XedvvvNKVs6lQ6dSkdlr8q/qb+IiIiIiIiIyD+Jf6WA0L59e65fv+5w7MUXX6Rq1aq8/fbbJcQDgKZNm3L48GGHUo8HDx6kaVPBObxcuXIEBARw+PDhQsEgJyeHc+fOMX78+MIxsrKyuHTpEvXr1wfgyJEj2Gw2Gjdu/DfcqchvxpQPeSnCIkfpBu4BRSUVrVZhoVK1G1xYKSyInlCxA9ze5TS/HYBLq6F2fzj+RdGx5BuQcgtbx0+xt/4QS2oqcndXApa0oI93JTqWb43EbsHtyFwh1aHPcqHUX3bRwhptEOQlg7YMppBGJFyfV9j0YZMPmXl2psMCan7OMgy17URkO773xbmacpURNUY4HOsR1BKPa47lSkm9LZSty08RoizM+pLiikdZpG4eTq/zTXc/yu7sA3nJSBIuk/pcWwbsLLo3nUZBlQB39CYrlfxc8IlYjuLUV0UDnF0iVJh4fqEQxVFcPCiG7MY6PPssI+/kaQLUwq7yiBoj+Oz8Zw7iAYDBauC1S5/zfYflTNZ7kD90IvbH3iPGqGhsnjqkLw1CKq2Ou13KG2Y10k1jsAXUZkbn2XhvHCSIK09IvIr/D8MZ/+Je8vUZuF1e43SO3D+ErdWrGO1mVDWq4z16FClfzSd96TJCln5DwrQPHfLwVZUrE/TuePD1QpZ8FR+Nj9OygCBURPE35KM78BG6vivg8kYmlWtFG8/qHEmLwF+po3tQCwIkSlxPPS7XmXQde8X2SO6XzNO3V+lGpCmb4ykXuJBclPplsQsmj5eSL9GjQg/6VnqB16oMwi0jGulPLwvROLUHQLd5QgWFJ0aRxTDV6MXZ+F1O70Nv0ZPj4kVQmfrg4gU1+wni1ZFivjXnlkD9EeARSqYhk10PnI8FsCVyC00Dm6KS/7owK3NzQ+bmhrJsWZLyk5i0q1+JdydNn8a0k9NY1H6R6GEgIiIiIiIi8v+ef6WA4O7uTs2aNR2Oubq64u3tXeL4E6ZMmULr1q2ZO3cu3bp144cffuDixYssX74cEIzupk6dysyZM6lUqRLlypXjgw8+ICgoiF69egFQrVo1OnfuzJgxY1i6dClms5mJEycycODAf0UFhn8sOQlw8CO4uVUIxVdooPF4YXFsyoMr6+HRCdCFQp8V8OCwICSAEO5cygIWEBb9rsXKGWk8QSrH5l+P3KMnSZj2CZr69QkZUklYiCddwz3pKeO788shfDD88nnRsSYT4NoW6PE18pTbeKu9STek0yigEZeSLzndfY3OiXlmmLROpaOySznmVH+HiIJ7XMi+xnMe1ZDEfOjY0b8W1BkCMrlgJhlzVggnL0Z6swkkGh8QqFOTmF204Kro50Zg1mVB/AAoSKe88TatKpThYmwen7cLpqotG+mF06DV4V+vDeqIkvdC1iPsybfAu2Ixx4KnMOUjVUiw5efjl2bB38Ufd6V7YTnMp0kuSCbNnIfrpwsLxQOZhwfKJXP4PvsgOy5OwGA1UNc3nLerDadiaBNUucl4JFx1FA+eYLPgcvIrLK3eAKuptFliy47jVMYlxveZRezgodj1QgpA7ISJ+L46FUVgILaCfBTuEuRaFVZjNIfTYmmhcGNUhT58fmN5iTHlUjmdQ9riFX1OKOl5bDbYLAR4lSPAxYeOmbnYfcsgMVtg+5jC88zelZCHNAaJTDApBKFkZpWuSOoOwV/hxo5HpZeHPPToEJ/UfBP33ZORRB0varixVRDgus2FXVMcT/IqjzmsOZGPzS2doXYPhOdmwfVNQnWRp40PTfkOpTuLm5I+jVQifWZ7aSTkJZBtdOLBAUSkRZBpzBQFBBEREREREZH/9/wrBYTfwsiRI4mOjubYsWMANGvWjA0bNjBt2jTee+89KlWqxPbt2x0Eh7feeov8/HzGjh1LVlYWLVq0YP/+/Q4+C+vXr2fixIm0b98eqVRK3759Wbhw4X/69kSekJ8O28cLBnFPMOuFhUrF9rChf7GFyVnheIfpUKO34GOQkyRUJ3hQSn33wDqQ8VAIua7aTSidqA0CuYLs/cIur6JMILKcu6XPMTUS6o0UvparofkUYYHnVwUurMBXn8XY8Bf49PpSGgU0Yl/0PqfDnIg/wWctP2NP1B6n7SMqDSZo3ma8rl6hZr16THl5OuqLTy3qlK4Q3ADOfiMsCs16IXe8ek9BTHm8sMvyCmPJ9TnM6PMFU9Y/pMAkGPlV8nPDK+U8eJaDgjQw5uJ7cBJfdl+DvW1V8qa9h+nq1cLLxSycR+B7r+Je3Yrs1kaHqUhubcfa6cvSXfqVrtjMQmSIfd4Kvlm3mNjcuNJ6A2CxmjHcvFX4vWLWO0yN/pIHOUUeFFdSrzI07QbrW35B9Zt7kN0/VOp40kdncFW4PvOaavcgymvDyNm3t1A8kLi4oHhvMneCNZzKPYaPty8tA+vjd20z5joDOXhnDQV+jXi+/PNU0ZbjaMpFfnq0n3xzPhq5hvlNphOaEgm3tju+m/cPYw8MJ7/3N5zNuE0VuQzXxmPBbiU/uAEuSje81/QUUkQajxOiB1RukHIbto7FpfcStAptqfcS5BqELuGUo3jwhDt7hPKhzSYLZRilcmzhw7DUH02mQkmASwAquQqb3UZcblxhmkWjgEZ4qj2BRLj4rfMLy5SC8Ad4qb3oWaEn30R847TrC5VfQClTPvMzcUaeufTKIcAzy2aKiIiIiIiIiPx/4f+NgPBEKHhCVFQUbdu2dTj2wgsv8MILL5Q6hkQiYcaMGcyYMaPUPl5eXmzYsOFPzVXkLyQ/xVE8eELDl+Dn9xx2NQs58gmMPw0tXxcc4G0WOLPYMbUBhMVXs0mg8YaI9bBhgJBnDkiVrgSN/oIktRJLcgpW9wqlL4S9ygs7/MO2C7nkag8hn75ie9g8EqndRqfwgTyq3B+b3eZQS97hVs35JOUl8Ur1sSy+5bhr3SW4A7UfWMk7IOw6W/b/TP7hI4St+gaNmzdcXSekdgxYL0RC3NpedHLMWdj7JozYBTsnQtxFrHYbUTkP+SHqc3aN/4yT1xKINUCfRloiTP2ILVeHUNdAyuhz8Ds4A9/rq0hNqucgHgBgt5M4ax6a7xchu7NJiBB5glyJNd+GzCPUaRSIteYwMrcdBIkEzQdvsCPmCK2CW6GWqUuEoQNo5Bp8VF64vDEBVblQrPkGLvnYeRAXVaKvxW7hq7sbmFemLe6xz6jk4upNhqUAv3KtkUT9UrLdsxzuhlw+rtAPw83HpRMlEjSL5/B+2ioiIm4Udp17A96qOZZuKi0d/BvTQu2Pdv87NEq/TwPfakxuOZ84LLgqtfgd+xJZxfZOhS1J4lXMd/fybfZlbmXcppyuHBIkREX/wJamM/G2mgTfjvT7ELER9JlCmc4Ba5GbjXQr342bGSW9GQD6BXdFvu81p20AXPgWnl+AscFYErKNLDibyc4vr/N2lzAWtV/M6YRTAFTyqMTPj37mSsoVpjebjk6lA8+yjt4bxQkfKlTjAGRSGb0r9WbXw13E5jr2bRLYhKpeVUuf3zMIdQ8ttU2r1ApzFBERERERERH5f87/GwGhONnZ2Tx48IA9e5zv1Ir8vdhtNizJydjy85Eolci8vZG5PnsX9w9TWvqBd0XIjIZ6wwV398xowevAYhQEg9S7UL2H0NdmhRf3wU8vQ8rj3WtdsGDwd2cPeFcQBIbimPKRH5yE3+gtxLw/F2q+Brc3gd3qGJ4tV0P7jwTDPVdfwbn/xBdQd7hQOtFuA10w3m5BvOVXE5vChZbetRh36h2n4dbeSh0tpcG067Ce0xkXyTHl0a5MK1z2nUH/pSB8SbVa5D4+WNLSSPx0HqEfvYQ8fJAgIGTcdxQP3ANJ7jKbSImFiOg9BLccRwOvamitZnw1vjR0r4Z02tu0tYPl/Qm8cno8cXlFUQDB7sEs77ecgOQ0Mr+eU+rHlHPiIr7BjSCmqOyjvd6LSOQS7EO3I9kxDmIfL8ClMuy1B2MK6IIl4ASqH5by0BPWn17Pncw7vFjzRZZELClxjYnhE5HKZOh7tCUzLxFPVRC/RO8udU7nUy6RX6437lU6CzvqTsisN5y3I75madfPUW0ZhSS52MJbFwzdvkS6awruOQm49PwO44NOSH182G2/QUTGjRLjfX5jOfVCW9O8IB+PTb0Lj0vT7qG5s4tK3RdgCKhJbpu38Tz4Qalz97y+ld5NR3A9/Qb3s4o8FpKteip0mC6IasVNCzOj4dYOZKP2086tNuvvrCc+L95hzDo+dVHY3J5ploi5AJvZwLRfDGy+JLwHb3QJJk2+n367Vhd2kyBhcr3JTKgzAX/Xx6VxtUEwbJsgxGUUq1ZStTu0easwAgEgwDWAbzt9y7HYY+x6sAuFTMHgqoOp61dXqMDwB/BSe9GnYh+23d9Wom1KvSn4av7YuCIiTzBajKTp00jRpyCXyPFx8cFX44tc+v/yVzERERERkX8o/y//19LpdMTFPTvUWeTvwZKdTd6Ro6R8+aVQ014qxb19e/zeeRtlmb+h1rBrKb/0u/hCz8XCDmzCFfCrJuy+n18G9w4WGcEZ84QFv7kA+q4SBAC7DbDD+ZUQFF7kl/A0NivyhMOELJyLrSALaZcvkOjThVJyt3aAwhV7jV5w4yck+cnYy9THbMpFX6ULWokEid0O4UOEBdSx2cgSriCTSKhRrg3b2szhpUufEZUTXXi5JgGNqZrrDheuompaFw+7mpv5t3E5cB7jnIXIg4KQvvMB8a6+RGebKOehJCgnBavdinxVB+i9XFhIPkHtQWzfZbx0cbaD54JKpmJtu2/4oOE7+GfLMJxaiXr6W7x5c7aDeAAQlxvHa9e+Zm3V97Dl5pb6MVkzc8C3mIhUtjkSCSg2dsQe2gxb16+x5hcgU8uRWI3YZUpkMjfWt5WxOWIKnzT/BIPFwJGYI1TQVWB6s+msv72emJwYymrLMqLGCPxd/DmTfIHj8cfpX7k/G2N/RqfyKHVO7kp3JMY8eHRWEIuOznIw0zRW6cJ172Au3V/FiqhdTGr3Iah1EH8R3AMFX4Tdrwo+GTX6IHPXEtS/KnZjLj18q+DvOpXp1xZjtpkdrnvg0UFejXQS9WC3w6GPSBy0jh0x+5lqNZfsU/hATciRljh8KuchTcq0QHpgWslzzAVw8EPO1+3NO43e4UbaDY7FHkMpU/JccB88pDX49lIBn1TrgTT1i5LnA1TqiFmpZctlQbQI0Kop45fOsvOrHW8FOwsuL6C8rjxHYo7QJqQNZdzLgE9lQazLSwFDlvAcXX0Eb5GnCHANYECVAXQt1xWpRIqb0q305/Eb0Kq0TK43mfIe5Vl1fRWZxkyC3YN5td6rNA5sLC7yRP4U2cZsdj7YyfxL8zHZBM8UrVLL560+p0FAA1QysRqTiIiIiMg/A/E3IpH/KPknT5L4brEa9TYbuQcPYnzwgNDV36Hw8yv95D+CNlAo41Z8YVy5E6TchD3FQrGTrsONbdB7KeQkYgtshCU2BmtyLBJbPvKCB8ivLBJSHrp+CQlXBd8DqQIOfVzq5aWegchTTyM79HaR0Z5Eir3lG8Iieft4LJX7g08FpA/PoDz5FbIXViP5rjO4BUDvJbDquaJz7XYkD4/ilxTBhuE7eO36ImQSGS/4d6JcrBmWrcNrWG/khhTKuHjSpuJgjLYkrH6+WOcuZsT+eBKyi55FGQ8N64bVobyrn/A8hm4TSk8assmp3oNP7q4tYdhotBqZduEzFrb6HK1eTzygr16OyMtOymACdzLukO+mRVOvHvpLl5z2cWvdCnKzoEoXqNJVWCzvflV4XDGnIeoQMqkG6S+fgD4TCaAIbsibPb7GaDUSkRpB86DmHIk9worrK1jaYSkDqgxALVeTlJ/EkoglxObG0jCgIV3LdeXtE28zp+UcLDYL3950nnc/OKw7Ptc2w/3D0GgstnGnyX1wCLsxl/yQ+pzMecin54VKAXlWI0hlwsL33FLQZxWlvNQZCP614fs+SB8LEAFAlwptCWwyndGn33O4brpeENacos9Eacjll5SLDKvaBW9nXgSArUYfChQuhSUYpRIpHUPaMbjaEMwXvqO0pYrk4TEqNxvHwCOTqOdXj9YhranmWY0AZU3ic7OoUyWZNI9O+F1eW2SU+QSPslC5M5E5ikKd5fm6Xux89HUpV4Md93egU+lYem0p67qsE0olugcIf34DEokErap0z4bfi7fGm2HVh9E5rDMWmwWVXIWPxufXTxQR+RVupt3k8wufOxzLMeUw8fBEtvXcRjlduf/SzERERERERH4fooAg8h/DnJJCypfOndhNDx9ievTorxcQ3ANhyGb4vm9ROkO9EbBlVMm+Ngsc+hhLn03k7DpEysKvsRcI4drKihUp8/HXqM68jWT7eBj2k5A7bgf8azqE3hei0GAvUx/Zd50dj9ttSI5/jmXIIfTl3yftu61YUlLQ1KqOz/DZKG/tExbREimcWuDc4b8gA7fbu/k64Dly07RkTZ2Dukl9fAc1RH70xcIwcw+5GlunT1EunEf/I8kkZDt6A8Rn6Xlly22+bzEdncWCKd5CgaEbCj8v5OWbY7tdMu2ghncNXq7zMpOOv8lbZUfj7eFBnr30KgQACVmxlHtxJHFXroDN5tCmrFAeldYAVUcL3g+/zHEsaelbBYlai2TnJIfzJHEXUKztycuDvueuNR9/V3/OJJ6hsmdlIlIjnKYxXEi6QJewLrjKXTmTeAYflQ9v1H+dLy85vpfhvnXoW/kF7Hod5krDMGbayPhgAbIpL7Eg7UeOnJ3mYKrX2bce7JwC7T9wmLstsA62xuOQL29TYi7KB0epEtKI+r51uZR6pfB4u+DWcHFnif5FNy7hftZ9HtV4CU+/akhTbju2a4OQVOpEZ20YLYNbkGPKwUWqwDP1Hpn6LCTPKm8okWJ7bG54OeUyl1MuI5fIWfncSt45/xIWm4Xv3IJZP3gjHlc2Ir25TUgpqdEHScOXwD0IW0pRZITORUJ6hvMylCCUSAzRhpBlzGLuxbl82vLTPx1J8GeRSqRFaRUiIn8B2YZsFl9d7LTNYrew4/4OptSb8oeqh4iIiIiIiPynEQUEkf8Ydr0eS2Jiqe2Ga9dwbdjwr7+wT2UKRh8k05yDzWImKDcFmaWkyR4Aah0F1x+Q/Jnjwtl0/z4xE98nbNF0lLsHwaNTEHUc0u5Bl8+dCwjVe8FV54aa1vCXSd+0l4x1PxQey01KIvfIL4QunoNrjZqQFglnFpV+X7HnkAc0JfOjj7Hm5eHTtz3ynf0d+1gMSPe8inrETj7sFciSIymcvu/onfAwNR9VQBNipkzFeLcoikCiXMiHC2Yx3cfG+bTLwjEkTKo7iVePvYreomelcisfTnwJqV2FVCLFZncUB0BYkOm8AjAr7fisXkbel19juHYNiUqF7vnO+LzQEcX+0dB9vvPnVW8EnC6lkkleMurkW3wRvYkJFUeypesmciy5fHD6Q+f9gUMxh2gR3IKI1Ajm1nsTdfRpWrVeyNHUK2Rb8mnl34hQj8pkDXiZXJsVa1Y2tnzBbFN6+TKj1szlUsoVhpTrQU33sqjkKsIMBsiJB5W7kKtv1oNHWeJ7LsD76o+l/kOru7yOYZ2mFQoI5bTlqeJZGYw5zk9w9SXeJggXky7MZlnnGYQ8Oo/uxjawWcmr2oWs6j1Itvnw0do7+LoqGdjUh2j9ac6mHKG/qj/uZZtQWja/uUpnDqZcdDhmsVvIt+gLP9u4vDjaH3qJnuW6MnzAd2gVbrjrwlC5egPgp9Xjr1WRnGMkMtFMzaC6ROVEUcunFhW0YaQZMzmbcBaL3UJNn5o8zBL8Do7HHyfblP1fFxBERP5qjDZjCcPP4kRmRmKymlA9S9wTERERERH5H6GUOFkRkb8BhQKJRlN6c1DQ33LZhLwEZlyZT/fdA+hzYCSZJue13gEs1UaSssD5ot2alYX+QbJgmphyB1y8hTDuhCuCP4JbsV1L/5rQbDKSrOiSA0kkWEI6O4gHRRexkjRnMRZVGASGg+szIjJcfbBL5dgKCtA+1x7ZvR9L7ao4tZDLKVsY0NJEs4qObvL9a/mStWSpg3gAYDeZKJg6ja+qvcMrVYehU+loFNCIiJSr6C1COcLzKRc5VC4ftU3G8yFdnF77+fLdcdWnMubmNAY9+phH0wZRdvcmKqyaiX/tVBQ7B4IxF5s2EJztwOmCBaGmFDySb7O06TzqqCqw79ZPXEm9iuWJh4UTLDYLMomMfqGd8T0+H+2+tym3ti+jIvbwauR56m8Zh8+2l/EZ0gdzfEKheABgy8vD/1E2e5vNY+SdkzTaMp46O15Dl3QDXlgNV74XyoBKJKQ1n8T3j/ajykspdS7kp6FVuKGWqelTYSDzWi/meqydnC5zSj4LqYz0zrP5KlJ4b3JMOQw68TpTDffY0XI8WUM28aFCz8c3VxKi1PNZOw/6VVXx1c/xJCVUp7x7DT44/QHZSg2mpq+UnIurD0lNxrEpem+JJq1Sh0KqKHqGdgtbH+6k57GJPJBYCsUDEHwPvh3REK1Gzs830uhbfhjbWy9kiXsdPomLYp7JjV0tvqRfWDdaBbfi1OPKDDa7DXsxjwkRkX8LapmaCh4VSm2v5VPrD5UeFRERERER+W8gCggi/zHkPj54DOjvtE2i0aCuVfsvv2ZyThxjDoxhT9QeLHYLBquBdJWrUP3ACXZtWcyxpe8U6e88FHK9QxpB1iOh5GK5VnB5HXT4GPqvwzT6ACndPifbasAe0qTkILoQDJEPSx5/jCkqCmtONhyYBg1eLLWfre4wMt08UbVohjLQB2kxQ8WnkWfFEKT0YPr5N3ipjbdDW+8wDbl79zk9z240wpULvBQXyebGMxhQsR9X0yIc+sy/v4I3ExYzrPpQhlcbhlomPFuNXMPAKgPpVq476owotEotyQXJTLryARPuzuGmDlJq9yCp92ISX9zNA4kdc5WuJSdhyBYqZZRCnq4MUiS8HzmPRfe/5UTcCVqHtC61f5uQNpxPOk9Hr1pIbv0kHLRZIe6iEFVSkIEk7hyudSqWfI6+vriHuaP6tj3S+weEVJGcBDjxJZxfAeVaCyaKAzeSGVCDk/EnyQxrVupcbKHN8HKpyQfha0iL6cioFZGYbGpuasNIGrYVc/hgKFMfY/gQTGOPsTL3Djcel1gspy1H97CuaFU6DqZHEGnOpl9wO+apK+L3/fPU3NyCbhdfZH3zZPzldloFdsNsM9P34GiuVGyFYfgO7NV7QtnmGNt/xKMBaxh3+XPyzY6lTQNdA0nKUDK76SL8XYpEMhe5Cx83/ZhqXtUc+kskEqoFatk7uSVLh9ajKnoq/DAS3ZHZcHcvmvPLCV7Xl3e96nMq5mhhZEMD/wa4K91LfVYiIv9UtCotk+pOctqmkqnoVr6bmL4gIiIiIvKPQUxhEPmPIVUq8R41CmPkPQpOny467upKyPJlKAL+grzjvFQhlDztLvjX5G7WXWJyHUs5Lnu4nQ/bT8Pj56ec6KUy0AUg9/fHkvyUQdxj1GHBYDwLwQ0gcj+ED4aziyHqGPa8ROK6f8na6F0cSTqDRqZhQ9OZaM8uFswXn2CzIlH8ym6TIRMSLgsGfLVegOubi9okEmwdZmDwDOPza4uZOHoAxnXbsDWujjTeuUmhya8aRpmSL2u8R1Vs/DSoCt7uaqR5eXgq7OgnTSJj9WqsGRklzrVk5pLTtCuY9dQPCOd8wlmeTti4kXaD/j8PYVSNUax8biWp+lQ8VB74SzVozHrcLAbGVuzHxWQhPP5SWgTD0iJQSBXIpXI+a/kZKyNW8l6jF6lis6KI3F84tj35FjSdjOSgk8oBchWmsBbEZcVwJeMaAGcTzzKs+jCisqIosBRwP+s+WcYsACp7VsZb400jvwYocrMfV9RwjsSQiUSlEkSUx3gN6YvszGxwVgHh0SloNAYif4bbu7AM+5GY3BjiPYLw8QgtWVJUKiO18bv0/+4h6flFHhIqmZQyrhWwK/PJafs+2yM3cT8/nsEyCS3DOnA9M5IpIUPxjkxBufkCNk8t2hf6gswd9fXlqIu/KxkP8d7zEgPbf8mJ3NYMqzCQXu7Nke05T3p2Aa4jP+CS/ja7447QV9qIHJNj6oRWqeW9+p/z8ZYElHIpY9vMx9PdhM1uxcfFm9r/x95Zh0lVtn/8c6ZnZ7s7iKW7u1sQQRppUUBCVBQRBINQEAQFRAmRRlpCpLu7axe2O2enZ35/HNll3Vn1fX/6vq96PtfFpZwnznPOzALP97nv7x0YhlKu5JfIZAKhXi6EqgywdpxYUeFZHA5UO17j+f5r+O7eRjRyDe/UfwcPtUeJuf6/2PLzsaZnYLxxHQQBbdWqyH19/7zSsRISToj2imZ2s9nMPDuz8OcsWBfMnOZzCHb9c6LvJCQkJCQk/gwEhxQz+j9Fbm4uHh4e5OTk4O7+x7mL/y9hzczEmpKK8e5dFD7eqMuWReHvj6D4f+pZuUmwdSTEHoMXV8KdH5gVFMY6J3Xdh5TryQC/+gRcXoeQGQOB1aB6HxxZsWTfcZD8UckydYKLC2VWzUflqQIESLoKbgGweTDIlDwZtIX+p98lx1SUIlHdpwoLK4/E58f3IEU8OcYzAvNzG3nYvTdYS4baa2rUIOzNPih2DxHD2Fu9B+XaiOUlZXIIrA43t2O3WrA3mIjVJgMrKGyZKDY9V3JzK1ehH3yCtN37MH+3CYfNhuvQgahaN0eZloPcZEHuoUPtp8WakozhfhzpKzcWRmIErF3BsLg5PMx5SBmPMnzU+EMG7B2Ig+J/dPQM7cLYyEHoH9zDQ+uBNtAXxY2vkN3egiO0HvbWU9iefYvplz4rNq5b2W7U9q+Nq8qVj898zNByPejkXxcXm5UshxVXzyg8HXJkuXEIBeliVYQb34NcTVr3hdxUaDidfI51Dzfho/Hh1RqvUsWnCpdSL5FakEpV36o4HA7SDGnU9q+FUpDjdjcJX5UD9Z5exUozPou52/c87D+u2LXIb+ahPdDPaX8AGrwKydfg8Snih+2h14k30Sq0rGjwPsFnl6O6s1s06wysjqnDLF4/JmPP7axiUyzoXZ3OsXNQVWxPqjmbfve/RUDg/Ubvk2ZIo4WiMlkjxxWPlBEEyv2wGuV3bZyvS+tFav8DqGLiSHr1tSIjS0FAO30SaU2qcDjxKC3CmpFWkMaD7AdU8K6Ij6Ic07YkcCc5v8SU20Y3plZ4yfKKxUi/D1/ULb25x1JWGOPoXaE3oW6hf3ipRGt2Nlnr15O+cFHR5yyT4Tfxdbx69ULu8ccLFhISpWGz20g1pJJlzEIuyPHSeOHv8gcbB0tISEhISPyb/N59qBSBIPEfR+HtjcLbG02lin/cpFYznFksigfuIWLYe/ZjAiOqOe2+6sEW9iedZnPDabg/PAwhdWH3mwg2E25dv8U8eACZazaAzQaA3NeXsIXzUfrIRZd9ATEKQaWDOsMw1R3OikebiokHANcybtL/0hxWd/ucAJlKjERQuyG32Qmc8g7JMz4q1l/m6orf6FHkXLqOR/MPURybKnotbB8FCOCwwaEPweEQ84/kWrJv++LdpRWCIxlHv80Iu14rqgTgFkj+82tIn/M5hoOHUY8eRmbLaixO+YGUeyeo51ub7mGtcN17AlV1Leojb6MOqIJuzhSSvvwem97IWR7zMOchAI9yHvHdnTV82PhDPjr7EUabaEb5YbW3aXA+j9RxvcFmQw9oalTHf9QwNDU9kZ9fhHzFcV7ou446bb/hSu4j7IKCij4V+SnuEFvubmJ6tVf5qeHHmA2ZFMgU5On8WHN7La86QHZ4DkL8OZArcdQeDK8cx2EpwMWYQ0WlGot/dXzcA6jmU424/DgG7BlQTOCo5F2JT5rNIdgmoDowlbSk6ug9PVFFd0K4WzLn3xFcG4tfMMpvP0emNyLbtAfjufMIIWFQqRuENxTTHu7tEyMPnqLS4QiuSUaTcRjU7oytOZZZ52fR+8Rb9IzsRJfaa5DjwCx3YfdtN/bcji9x7/J+Lqgu34O0MPzu/8Soen15Ysnjm+vf0CuqO4bVa0qk2cg9PCDhptPvOgCGLDyFfB6Ofb14FQyHA8P7c/Dv2ImK/UcTqPKnQVCDwuZHafkk/vzZP0unqoGEe7uUfr+n/IoXBYCXTM342uP/NPM40737pH/+CwNOu520ufNwqV0bl9q1/5T7Skg4Qy6TE6QLIkgX9N9eioSEhISExL+NJCBI/D3Qp8KFFeL/e4aJFQwSLtKqzRQWlFId4PmwVuiOzYOYIzDiEMgEMOSjIBvfhq549VyPJSUFmZs3CjJQXJmOYNZD3WFQkAEbB4rCQ8eZZKu1HHhy0OnSEvWJfHJvPZ8Gt0X26CjU6IdcLuDu9QjNys/J2nEAS3IaulqVcO/SleyCXHJrlMfk40tQ7SEIWi/4Zam+n5HdXI9Hq1UkfLyIkA8nE//R5/gOnoNQ1o90UzqJdjMheSYMBw+j6v08h+qq+fzyW4Xjb2bcZKPie5a3/QRdYi6uHqGQchPl7sEET95NjEPALk8DoKJ3Rap6RpNj0XMs/hjbO23GxWbAFSX2LD1P1o4Dmw3XwS9hHdydLHse13LjcFM3pXL5RgTunoTsp6l49PyGhLw43BQuaLwrUse3BsP8G+EWcwLsNtR5SbhdWYup3stMrt4L2TdtiqIq3EMQKnSGzUMQ0u6gK9MSnXsIfmH1ueFVjlyHlY/OfFQoHtT1r83giE54qdxIz7yHmykQr7JtcW3ZkFxzHpmqBnjIlShu7Sh8J47Qeui7LWLY2fe5nXkbN6Ub/Uf0odfsaZj0+ajdghDOLAa5Cqq8AI1Gw/YxYMzGWrUn69LOc+jRRtxV7rxY/kU2dNnAtFPTWP9wB8dTLzKo8iD8iWbZsbtolXJsdgdmm/j9bFrOl6DE/dBkHOx5CyE3kdZVnuduaF1+jP0RP5Oa/B27SnwP7EYjqH89YkmGHJ5Jx3iWgh/3Ed5vOPlGB1nGLLKMWZhsJjy0Hvw4oTGrTsZz4HYq7hoFI5qVoX6UNz6uv2PTr/EEjzDIceIrIgjIg2og/5PEA5teT8bXX5fanvHNcjTzKiH7FWNXCQkJCQkJCQmJ4kgCgsTfAwfQ/kPQ+YFCKwoKDgcB51byad13mHRhDjaHrbB7g8D69PKojPzRbGj/sVjtYMhesFtA44XcuwwyQCFLR7auXfGT1J2XoN4IqDscLiyHs8sQ6gxCJSvd10Ct0CBofETh4dK3oE9HfnsnWqUL6lodcKi9kWUdQ9gwl/yBG3nh8psEuAQwpurLtNT58TRQ3F6hO9ZyfbCbHAhqJYrMy8jUCozXrmEzOig4c4bk1FTcP5jCQy8l62K2MyOjmfiKXuzMwsuvlVibwWrgo0dLmCvvg7ZcV+QXl4gb9ivL+D4whIoBtdje8gu8E67gFXMCs84PW6PRqB/+hOzUQshLwhFYkzJLp5EaUJY9iQf5/vQbFFgLaBTUiK5luzLt5re812MJ4RsGkZafyNLb3xHpHklDr0o0SbmH8PAQDvdghMovYM1PwVF3KNaCdFSHPi6ektF2uhiNEVJH/P97+yD7CfL0+1QLqMIxUwYOHMgFOV82mEbVpDt47JkmVssIqom93QwEbTm020agzY3HFlgdU7M3yG48Fmt+Ejq3INIEeOngiMI85TxLHt/cWkmvoEZ4rB8Az1ZVOD5PrLjR+VNs+jSWxuzkq7tFpSgPxx2mX8V+TKg9gTxLHjabDT8XP2y2bLaPr8CT3ATkghK53Yt7CQK9y9jxtvrCmSWiOSPg/eN7VHluPpV9KqMQ5DjMRX4JhV9/oxFLgQKl1gsMWSXbQ+shU6pRR5fHdM9JRQuHA41KhtIlk1EHJnMzQ4xm0Cq0jKoxilebdeDNhq44ZApUnv/C6al7EHT5DNb3Lpkq0nC0+PP6J+EwmbCmJJfabk1Oxm4ySQKChISEhISEhMS/gCQgSPz1sZnFE86Tn0NWrHit/yZQu6O9vZPmdiu7ms7jUl4MWeY86gY1INhkwPvaZui/GawmMfWhbGuQKeD6Jji1CEPvb3HZ/brzMOyLq7AP2Y/VrzkOtwg89Xom13qdN0+/5zTa4cWIrjhS7iJc3wy9v4Pvh4gNlgJkt7cV6xuYnci8uu9yNO0iH16YQ3q1lxlU+Xnk/o3IupxLxpwpOIxi6oC2di2CpndH4eeHLV+Ptm4dfIYOJfnNKUS4u/HemKHoPDUUhARzyxhTwrfgKbcybmGo7YvNUBO5QgNWI4qEC1Sv0Jy62mACNg6GvCQAVE1fh+OfwY0theOFhPNkmhN56+xKrqYVVWnYHbObI/FHmNdiHrNvf8fshq/ikMnwUHvwVa03Cd40VBRVELNCuLgKRdsZcP9HzNVeJK/q87jf/1GczC0IjLliGc2KXWB9HzGNAOD+fmTnv6bpS9sIcwujX0RH6l7egvrOD0UPmXQF2ernodvPZToLMpE/OoJLzFEMLyxl/JNt9K/Yn/kX55cwE2wV0gzXKxuLiwdPSbmBHYGjPhF8dXpyieb1d9bTKLgRU09MxWw3M6XBFNIN6Sy/vhyrQ/xuuSpd+aTZHDzV/rBiRAnTQfefpvFqv285knCN9o0aYjx9puQyvlhJ5CerETb0BouhqMEtENrPRLaxD6EfzCP21SnYsovPr4yIQBGqZfiB4aQWFD2jwWrgs4uf4emA7mfXIBRkQqspUKYV6IpX8yiVyMYw4iAc/FAseeoeDM3fEquXaP48nxeZqyvaunWdCyaAS/16yCQjRQkJCQkJCQmJfwmpjKPEX5psYzZZuYnYj8wsEg9A9AnosQzcAtHc3UPY6h48f3wpQ/Qmqupz8b77cwWFtLtw+COxf+wJ2Pcu7BqH1bccBmMWZMWUvKlchaXLStLW/sijVz/gUY/+PB71LnXO5XKkyUaGRvYp1v35qK743kjE6l0fmr6OTetZtPF1gktuEu0vf897OQXsar6AU4mnyW0ygdy7FtK/WlUoHgAYLl0mbsxYgj79BGVAIIFTppDw1iSsycmY7t3H/vU6lEFBCCo19t/yS9W5sFGVz90Baymo0Qdc/Ql1DcXnxOeF4gEyOYQ3KiYeAOAWyH2trph48BS9Rc/W+1vxdwkkpcqL3DZmsb75fIKOzi0UD4pxcAbU6Ivuh9dRhNaH3qvFX00nQMYD0ahw3zsl36FZj2L7aMZH96OVV+Xi4sGzHJ0D9YYX/d7hwOfgh4wu2wOtQkuGseSa2vvVRnfvx1JfnezaBs6nOa+AAXA99Ro7Wi5iR8vFuKtc+eraV4XiAUC+JZ9xh8eTrBBEb41fYsoj4tZeapdphGL8CAR1ybB/masrJqMnxvZrsDb9EFvNl7G0XkBBvc/Iu/gIu0cUyisL8O73QomxPtOm8bggpph48Cxf3llLWt3BkPkItgyHiyuLixROsOXlYUlLw26TixEjvVbB6NMweCdU7QE6318d//9FplLh/dIgp+9K0Gjw6tcPmbJkBQkJCQkJCQkJCYnSkSIQJP6SpOhTOJ5wnM13N2Nz2OhWpS3tm4wlcNto0KdB8nX4aRp0/RxkKtCniOHSKldY2Qk6zBTDzx8dETfFlbuDdxl4dAiA3NDa6O1mnJ2xWuu/RfJXO8k/VmSeZ01LI+XDj/AbN45BftFUr/0he9OO8qJ3GwLvZeCh02K8cwelJQ2jexA6zwjIfuz84fwqwPG5aC0GQm5sY2a/NSit7qSuXO+0uyUuDoPFTk5WPuqLZ3AUFBS2yTw9MSll+EycQBWdFgHBaRRCBa8KKF10fHpcNJybU3cSbVQvUl0XgvBMSUXcQ0R/iV8SWo8fUs46fx7geMJx3mv4Ho8y86nm3Y7QgusIMcecd3bYRff+nsvRnFwE1zaCzQRVe0GFTmJKgynP+diMB9RyDUeWdK3UtZATB1oxKcQa1YK0+sPIUaoIcA/FLlMQ6BJIckHx0HeLwwZOyhUWLlmuxmgvmVpQ2G7RE3rwY7LKtWZVlvP3ZHVY2flgF+O6zIetL5MfVoeMcq3JtZtxVbrirfGiXsI1Msu3w3vzBrIWL0V/6jRyNze8enfFrV1HYvoNxp6Tg6pcORQ+3lji12BJSESm01Fm6XSUuwfgOWAqWVt2Y01PR1ujOr7jx+DiuM2tTOf+CAApBSmYXJ75aTj2iVhe1Cui5HNkZ2O6dYvc06cwVI5E4emJb1h5NL4ByNw9S73Hn4EqNISINd+R9N5UTHfvAqCpXJnADz9AGRLyH12LhISEhISEhMTfAUlAkPjLkVqQyvjD4wvztAE+zbrLBrcwVvRYQuB3L4oX0+/BnklQ72UxysBqhD5rQeMBrv6ieOAWDP3Wi2kMSVfEvHqPUDRuQVzJvEF4SB0cGm9sAY3BbkYRuwerd23yj610uraMVasIfH8a9ZNVVDzjRcGemRizsmDePGxGC0LNXtw3ZVOp3QeoNw8uOUFkUzGS4unprqUA/+OfY2n8aYmw82cpuHOX9A5t8G9aB83xOhivXSPo3QmYWzfm07srMdr1jHMbychKQ/nq9opiY1UyFe/Vm8xHV+cWigvTLn9OjbZfE5xxr/hJv9UoVp4AcAvCWnkgDvcoHIFl0ab+VOr61HI1AgJ6g5KvLscwu55MTFkoDZkCjs1F9uhw0bXrm6BKjxLh/b/ETeGC1fVXSqMJAsjk5DYZxwH/SOZd+bQwZSHaK5qPm37MR2c/IianKPpka8IxWlZ7EfejnzidMq/6EPTph522AbTxqwWHvsRcsy8JcQml9ruf/xhrwnkyn/uUubdXs+/4xMLPpGFAPT6oOJgghw2iK6L5+GPs2RkIj08gv7UKY0J57DliFRDzgweYHxTNa9frsZrkKAG5ykrkx8NA7Yks6w7yy29Dj2WUKShZEeIpHmoPlGZ90QWrSRTqfiEg2PR6cnbuIq9aBDvqW9mVvBTyobOlFb3VfQnVlC31Hn8GglKJtlo1wleuwPbzu5F7eKDw9v6PrkNCQkJCQkJC4u+ClMIg8ZfjYsrFYuLBU+Ly4tibeQN7ZNOii14RkJ8sbnxBFA6q9ISnp98DNsOJz2BFe9g1HnaOhQ0DcEm5QZhbGIZ2X5GWVIvH8w8Qt+w8Ob4vY0otPXTbnpuLoFKTvXETCoeALUs0tHMYjbjUrArJ19GodXyRfYX0F78Wow1AdNBv8ArUfwUOPVPasUIn5A1GIlMrcOvaFdeWLRE0mhL3VUUFMO/6O4y+/wGHRtfH48dNqKIsLLm3ml0xe/gp+SjdjgzE1z2IeS3m0TCoIWU8yvBiuZ4sb/8Ni69/xbnkc4XzGW1G4nNixUiAZ0Pq81PBLRBbzZfR155L/OqbPJrwOQlTPqdraIdS30unqE7oZD6sOZnFwXvZmHQh4PcrZTyDa0Hs8ZLXD82AoBqiwOAMnS+PrXkYvMtAae7+US0g/QGXw2rw/pUFxfwO7mXd442jbzCp7qRiQ65n3ERW6QUc/lVLTGep0A27VxTTogfwTcMPqO1Xs1h7+5AWhKTcA3M+mswYynuUvomu5RmNRe3G/Fur2Pv4x2LRImdSzjPp5jIy+bm0qE6H0s8HRfw+hPizIPv1P84FmQARTRA8I1FG10PpKiCv2Az6bwS/SlTzq4ar0tXp2MFlX8Dv8i8iYOQlTUNt6RnkVgph1KNZfPNoLSkFKaQUpLAyZgPDjo4iMdtJNYb/AApvb9RRUaijoiTxQEJCQkJCQkLi/4EkIEj8pSiwFPD9ve9Lbd+WcJiscq2LLtQeJJ5cgygeZMVC/ZGgdIGaA+H+fnimhB8AlgLYMZYIix9xA4eRsWIN5pgYjLdukTxrAXIPz9IXKAgo/X2xZmQgc3MDwHfkINzrRaGM24ndkElQbipRumBGPFjHrmav8mjIdqz9N0DWY9g8uEjsaDgaIptjyTVjun4FwW5D4e9HyNxP8R46pPCWci8vEvxlXE+/TmxuLAsefM3Y8++SUq4p22P3FvZz4ODjsx8z69wsynqWZW6LuRRYDQzbP5zTSadLPIpVAB4cghaTi20WHTEnyBca82TUWxguX8Gel4fxyhU89p2lb9leJeaJco+iZ7neHLuh4tKTHFzUcmKtXhg7zhPTR35J9b6iN4Uz88rU23BjC47mk0q2AY5OnxBml6HRp2Hvubzk/O7B0HgcmSotC+6udTpHtimblIIUVrdfycaWi9jVdgU76y8j7f3PKYh+C3v3r6FcW2wVnsPc73uEWgPwXNUC16+a0GDXJJb4NuPDWhOp4lOFT+u8xWSf+ngd+AAAj0trGBfd1+l9tQot7fzrkelbDn/3MOoE1CnR52r6dTKtRSkqqHTQdCIAClke8lI2xwp/f+RCDnT6BDyCIKAyVO4GEY3BIxRkMgJ1gSxvvxxfbZE3gYDAC5GdeEEdjPzhoaIJvSKxuAWSbcrGaC3y5LCkpHDceof4/JLRDEn6JPY9+dGpyaiEhISEhISEhMRfA8Hh+C1nNYn/JLm5uXh4eJCTk4O7+5/nUP5XpSAvmfGnp3ImqaQLPUBZz7Is92mKz+E50OwNMOfDqUXiiXX3xWJ5PP8qUKOvmEu//RWnzvr2ij1IuRtO9vpNJdrK7NrC45eGO00p0DVpTOCkcWSs3441NRWX6tF4hSUjO7+4WD9jdEfO1HqRsec+QCFTsKvJp4Su7lnUwTUAOszEYvPkyZT5mB8+Kjbee8hgHHYHefv3o/psBmMfzyUmt7jh46r2yxmyfzi/pHV4a7qX7Y5O6YLBaiTfks/qW6u5lXGrsI9CpmBT563cvp1FhRBf/FyVeB15DyHmMJY2XxIz5oOSzy8IqCeNJbN9bb5/uA29VU/7iPZU8KzGpA0JXIkT+49tXY7TDzPw1Th4v7GKgEvzkMWdEwWe2kPAvyKO61sRLn9bYu0AeEViarkYuT4Wxc0VmAMqkVatJ0adLy7mAvysFhTnl4tGiVYjPD6FIz+V/PAGZPmWQWl34JAr6XBwhPP5gRfL9eQ914rIj84BmRxbpV6YtTVJmPkFkZ++gSP7LtboLqj2T0J+d3eJ8dYun5FfoQOe6/tDUnFjybw6gzlZpgFf3F1P09CmBOmCMFqNNAtpht6QwdJbqwpLYNbwq8GWu5sZHN6eYEGJYLfi5l0OnWcZUP4cYWHKh/v7cZz9moLI0TyZMAUsRaUvBZWK8KWfo61UBsE9GOSlZ645HA5SC1JJLUgl35JPsMYH78vrcDvxuehNAVjLtiG+y2w2PNjK5dTLBLsGM7TKUKI8ojA+jmX8vVlcT7/udP4KXhX4uv3XeGm8nLZLSEhISEhISEj8d/i9+1DJA0HiTyXXlEu6IZ2zyaJxXIPABvhqfXFX/4o4os8QT5+1niXC0F2y4+gd0rJUAaFnmefx9q4B0Z3h0THR56D2IKj8PJz9SiwjlxULNfqAi5fzsnyALaQleQuWAiBzdweHA3teHigUyAoSCPvsA56Mexd7fn7hGFVkJIHjXgJ9Em7t2pLy6VyCx7+IbP20EvNr7u2jWrlWlPUsy8Psh+xKvcBLDV7B9exXYoeGo7DZFWTuOVNCPADIXPUtEZs38aRrbWbcn8OTvCcl+lgcduSCHJujyMNgaJWhaBVa3jr2FiabaJrnpfbinfrvsP3hdk4nipEIIyq/xsKfUtl1JR1IolW0Lx+3moFfizexxWc792NwODDNWYhvmbkggLvKna33t9I5oBwdq7syoqU3Jgv4uXiz6JCYoH82Tsn09u/ToaUKhcOKWQYmgxG3Sr1QlCIg2Cr2J2n2F1gzs9B9OY816fvYdHISRpsRnVLHkPK96NV2Gj5Lm4M5D0Lqkt3qHUbd/oab126ikCn4pNknBOmCSNInOb1HtEsA8rNLxaoDgPz4TDR+FSnzzWqEGxsQznyJ0isUnIgHAIrDH5MbWBltZBPUvxAQ3C5+SxOfsgQ0+YCvri3j0JNDRLpHUterOnarvTCV5Eb6DV6I6szciK6otr0KBZniBEottPtQNDHUeoLaFSp1RQith9aQR5ltm8n5YS+m23dQV62CZ9cuKAIDETQuTtf6LIIgEKALIEAXIF6w26H2UPCMgoRLENWMW/5lGbq7H+afTSNvZdziwOMDvNvgXdr7t0DlJLXhKWq5GpkgBb5JSPwvYnfYSStII82QhsFqIFAXiLfGG51SKncqISEhIVGEJCBI/GlkGbNYeWMlK28WNxwcVnUYQ6oMKXkKmZcCDw/CmcWiy350R7Fkn2dEUX532m1qKlXU8a3BxfTiG7MyHmVoF9wUQZ8plpkzZENQdchJgPU/RxyAWIkh9Rb4VYbAamLFhl/isOPesS1eXVoiMyWBIMOm9Cd9zVbsNjmaa9OJWjodU3w25sQUNNFRqFyMKA+Mwt5/O+jNBH01H469X+r78bm0lj71+jIz+yGL767FrerL9BmyF3IKMCaZwKoje+uOUsfn7tvHD03ynIoHAPez7tMlsiM7Y8RNbpAuiLKeZXnv5HvF+mWZsphycgqL2yzGZrPxQpnB3IhxZdcVcXMtCGC124nLy8NPJ4dnQ+id4JDL+THmR6x2Kx83/hi1PIH1TxbzKOYRYW5h9C0/grc7RxGXamNsJR2W7zeSePECCj8/PLp1w1GgR2hcBUeT8QgnPy8+d3hTjMoqGC6vQjNqKAtiv2VPwoHCdr1Fz5e3VqF32Bld6Tm0V9ZB/HmsWTGF5RmtdivLbyynb4W+zL80v8T6VTIVTT2iRbHpGYS0OwgxB8GnLLgFif4QpVGQQaARDNGDkeszUVzbUNhkLd+e434RvL2vyEQzSZ/E6aTTTK89mbdrTGTO1c+QC3JGhndCtbpn8XQOiwH2vCn6Z0Q1F6/JleAZhswT1IDf+GgcFguCUokg/Kpd5a8jk4k+InUGQ53BZBgymPrjsELx4Fk+OfcJTbs3oV9kDy6mOC9p2b9SfzzUHv/+eiQkJP4UrHYrNzNuMv7Q+MI/K+WCnJcqv8TQqkPx1kjeIRISEhISIpKAIPGncSfzTgnxAGDFjRU0Dm5Mg6AGRRfzU2HHGHjwjJP/2aVwdQO8fBB8yonXfMrht6Ynn3RbwKWI9myIP4TVbqVHcHMau4QSmHoHto+GHstE0eApgkwUC2RKKNcWbu+CM0vFco4b+pVYo8JNjX9Lb2R7exdu3pRyFYHdp2FMzUEZUBXVD/1RuYeAiw9cjANDFvbG40hbsxVrehb5r71IhYKs0l+QIQt3hRaZIKN1cAtae7XE7HCn4MJhMpcsJnDGDOyG0g0bHfn5dAjvxLb725y2u8qDGBjdHL3VwMG4Q3Qr241rqVcZGNWLDFsORxKPY7CK81vtVs4nnubtajMYsOoOaXmieBDmrWX58wEEPN6Jx6k9oHJBaD4bVVQk5pjYEveUublh9NZhfWilZWhL8qx5TDk1pbA9NjeW2Rff45Xqr/J6eBsyuvfBYRRz6E337qE/eRKfkS/DlSsIKgf02yCaKVqMOMq3x2zxIm7AK+KaWzdkz6UxTp997d319Gk0i9Ar6wDwvrmLXpU6sOi2GNVwM+MmvaJ70b9Cfzbc21CYl++ucmd+i7kEnnFeZYO7u6HjbHETr/N13gdAJseenkPKW5PwXbEY14ajUD4+heAeTGpgRT76cZjTYXOuLWBD++/g6mc0DmqE963dzr0gAA7PhMDqYhTCLxAEAUFVeiTAv0uOKYdHOSUjYkAsQ/kg+yG1QxvS5EljTiadKtZeP7A+9QPr/+FrkihOljGLlIIUrqVdw1PtSRWfKvi5+P1qZIiERLI+mZf3v1z4dwKAzWFj1c1VRHlE0aN8j//i6iQkJCQk/peQBASJPwW9Wc/KG6VswoBVN1dR1bdqUWhkxsPi4sFTjNlweBZ0XQhqHXhFgWsA/ltG0tG3PE2j22OXK3A/uwYim4kh56Zc8fS4/ivw8AD2BuMQQmogxBwR88XLtQGFCo7MEk0UX/gKjszCHtwQm1dVBO8w5GGVkN2dIaZQmH/ewNnMKI69h7rXdtI9R6LTeaG7+C3kJoDWi4JW7/IkohEum77Dptfj7/DCVq4D8pijTt+BvUwrqnjU4mizzRi3/UDue6+QW1CArlEjwr5ehsxRQNhnH5K5eTf6k6fgF3Ylrs2bU/lSCj/U/ZpvkrawPWFfYVvDwCYY8oPovuYWc3qO4o1qr+JVoCJ99y6E89cgwJdXe85ii/4kqx9vBuBuzkMqKQ2k5ZlwUyuoF+nFzFbuBH7ftViqh2L3UII/WMSTVydg1z8TjaBQ4DZnOmeEJJa1W4av1p+Be/o7ffblN76hS8MGyLRalJUq4d6hA3I3V0z376M/ew6fF6dA/iOwWcVSm7HHEba/ir3nj+J7UCpJt+U6nRvAYreQg43Qn38vjznK841Hc8ArmttZ9wBwU7nhqnLli9ZfkG5Ix0Xpgs1h46vr3zCjzmBCb2wpuXmXKcUUm+fmi2vTeDotK2kv35mcg6expaeTM3chMe8MxjuyEVFZcWRlx5BnyXO6boPVQI4pB4WgIMzFH5dHzr0EAMh8KAoZTgSEP4tnq0KU1u7n6s9HTT/mbtZdNt/bjMPh4MXoF6noXRE/F7//0Er/maQVpDH91HSOJRwrvKaUKfms5Wc0DGqIRlGygouEBMDpxNPFxINnWXJ1Cc1Cmkk/vxISEhISgCQgSPxJmO3mwjBIZ6Qb0rHYLKD8+cKN0isrcHsntPtAFBDcg+ClrfD9cEi8hGv6fTF8u0Z/MaT7zJfimHPLsPT6gQKak7tyDzKX63g91xKV/R6KlR2hYld4YRlsGY5D7Y258yYyVqyi4PxOFL6++LzUC23Fl1BU7wtJV+D4vMLlyG59y7LAMDLkuQzvuwof9yi0egeOfD2hNi3Ch+8jy84lrv8wtPPeR+4aAPkpxZ9J6YI18kU8rzwmc9W3mO7cEed2dcWnf1dUaQdQPNgCNjPa7p2xvvoFT978EGtyMgCaqlWxZWaRPHUqyGSMnTqZqlUrcyz7Aq2DX8CkD2L6tieYbXY+/CGOo73DSXipP/bcnzfdCgW6tAwGDeqLSwU3lt5dQVW3CIK0MiY/F0ZEgAGTNQ7vq4dK+kRkxaC5OI2oTWvIPXQMw5XrWKNCsLdvyuzEdRw+dwJ/F38+a/EZBaWkO1jtVrJ0NmoseQu03hjjskmevwzPF54jYvpQZDuGQMYDsYpCdCeo/zIkXkJI/ImApUtJff11XOW/ntOv/UVJwoAtI/niubnc1Oo4n3GTdEM6y64vA0Cn1GGxWQpD89e5hvJ6xS4of1mho3I32DVO/K61/xj6fAcbBoii1c84/KtiLj+crE/eAMB4/CQRb7/O6oR9vB7/EFm1br+6bplM9K2I1Seh94tG9/Cg846+FcRqIn8SBZYCMowZmG1mdEodflo/PFQeRLpHEpsbW6K/XJBT3qu8uDQXX3xdfGkQ1AAHDpQyZYn+f2eMViPphnRupt8k35JPdb/q+Gn98NR4/mn3tNltbL2/tZh4AKKYNuHwBHZ230m4e/ifdn+Jvzb3fhZWnZGsT8ZaWiSUhISEhMQ/DklAkPhTcFW60iioUan/KGkU1Kh4zXm52mk/sU0pJuIXTh4IjceBZyjkJYubzDu7xY2dwwGCDEuHr3ky7h3MDx4WDsvdvQfPF7vh1+xdFKc/FlMZRp/FmGTgcc/eOMzi5tESH0/8lSt49eqOXwMVciEfmkyAkwvE5WQ/pkalNhxLv4a3JgLrgZOYHqega9AAW14ccg8PhNBQgmbNJP7dGYR/uZZcRzJWhwV1xiM8U+5hLdeH5MVrcW/foVA8AAidNQXtrTkIKUX+DvKMRcjdtxL+2RKeTJiG+3PP4VK7Folvvy12sNvJmPExLdZv4lpeTeZuzyQpJ7Zw/MhavqR/+FGheKB6vjPWl55nc/YJ4i17aOTRgC9af0F5rT8OmZJb8d/yxan9fN1wBqpfbqB/Rki+hOr6Qmw9XmdJdAxppkecu1KUCpBakIrsN+q7qI3ZyHcMBYcDnVck4XO+QMCCbOMLRZ3sNrjzA6TcgA6zsMZdY4XgwajvvibXRUG4W7hTD4jqvtXxdAvH3Gs/1vR0ZGolcnsa/kY9/sYC6lccyOtnpxf211v0xcYfSDrN0Iju+D37/JHNQJBD9mPxV8YD6DAb+m/ClpmII+UBdu+KmJL0JI5+B8fT9BOHAyUy7mffB5Ur3gXZ+Gh8nApsHmoPtHINDhycST5LdotF6M4vB1tJzwEajoaUm+AX/evpFP8GSfok5p2fx4EnB7A5bHipvRhbaywdojrwQeMPGLZ/WIkNxYTaE/DR+BS7ppD98/6KMVgMHEs4xjvH3yn2jjpGduTt+m8XK5P5R5JuSOe72985bbM5bBxPOM4A9wF/yr0l/vpU96vOhrsbnLZFuEeglP+zREAJCQkJidL55/3rTuI/glKupHeF3my6t6lEWKSLwoUXo19E8Ww5uWq9iqIHfkn1vuDyjIGTKRd+nAyhdcGrDFa7BkdwRwhohfzRNgSHlawfzxQTD56S/f1OPNvPRaF2gzOLsbpEkfzhokLx4FmyNm/H6/kvkO/pDb1Wie73FgP2kHrUCm1K/fBWmI6exk3QYsjOIm7UKNG1HlAEBxO6cAFha5dyOPUaix6uIDE/kWivaCbUG0PAtlMoFCr0Z88V3k8VFYlalVZMPCgkNwFV5lFCPp9P2sIvyFyxokQX+65tJId3JClH9BTQKuWYbXYa+SkxXLgg3qNtS273qcO7F18rDEc/8OQA3hpvVrVZSlzeAw7F7Xf+OfwSQc6ZjJvsinVeiUDrKH2D76PxwbcgpygtIysW5YEx0Ptb0ffg2ka4+Yy3Q1YsmPPJLd+Tb757Qv9QNQGpd/m84WxeOTmB1IKiKIlwt3BmNvoI8+odPPzmG7D+7GERHk7opzNQ+WpQnv4CF2Xp4dxahRZZSF0o21r0z6jUVWzY+1ZRp8xHYLdgd9jJ1pQl58tvsSRuxq4vLkaoo8ujVzmIy42DOu/it+8dZrd+k1Gn38fqKNpgygU5Mxt9xE8JR4j2iqZdRDtUnpHQezXsngi5iWJHjQe0fEdMv7m4EuoOh9ZTRC+OP4B0QzrjDo7jTlaRsJVlyuKDMx8gl8npUqYLW7puYfWt1VxNu0qQLojh1YZT3rM8Ln9iRMRfheSCZN46+laJdI99sfuoE1CHPhX6/P+MLUvB5rCRY8optT0hL+EPv6fE34c6AXXwUHs4/Q6NrzX+TxO+JCQkJCT+ekgCgsSfRohrCGs7r2Xm2ZlcSBE3sPUC6zG5/mRCXEOKd/aKgLrD4MIvNsYeoeLp/7O5uzIF6Hyxm82Y/LqR8slnGC5/h0zngucLz+HZpzfZi18pdV3ZP55AW605xJ3DLrhhvHGj1L76K7dQ+5aHBwchsinEHKOgVn/8HJCRmY3sxEUsQUHkbC1uZGhNTOTJ8JeJWjaLFoEVcLi9xvGE4+yL2cfLR0Yzu/0MGpepgPFSkViga1gXxZO9pa5FuLkFW/nKFJw+jaBUitsTi6Ww3ZacQkR1DYObBNK6igvZ5lS0Ci1BFgXpT+cY0Zep1yeU2NxkGjP56MKntI1oV3htd/IZalTqKlYycIKlem/up59z2gaQkv6Y2ZXf5uVLk4qd8KvlahbUewe/Hz8sPiD7MWQ/ge1joNEoaPo6nCiqkuBIvMoFW2PK+OqweJXBoAyGQa/x9ZQJJHs5iDMkE+kSin+yEZdN+zHcvFkoHgBYnjzhySuvE7VkBqprm+jfbS4H4w47XXv/iI74nPkKmr0pihnH5kJOXIl+Vlc/jhqSCVI40JSLxH7/F5UZ5HI0b4/nsuURfaOeg/T7yAKqUuvst2xtMZ/v449yKy+WCm4R9K7Yj2CtPzUDa9Ovcj88VB7IZXJQecCQPZAZA+Z8cNjgwkp46q1xYTnUGfqHCQgJeQnFxINnWXhpIY2DG1PGswyT609Gb9WjlqulMm/PsDdmb6leESturKBNeJs/JZdco9BQwasCd7PuOm0vZlorIfELgnRBrOywkreOvcXDbFF8d1G4MK72OMn8VEJCQkKiGJKAIPGnIZeJOdELWi0g1yyGz7ur3J2XcXPxhlZToEoPOLsEjLlQtQeUaweeYcX76nyhxduYMtXEDhwCNhsAdn0BmWs2oa3bGIfJVOq6bAYjjuhOCHVHgOPXnckFhQKMNrDowTOc1F4ruJP/hGZpJgR1GVwbNSR19hynY+05ORhjU3G/8SWOGt2wOWwsarOIuefn8sn1z9nY8GM8I7uRveHnsFG7XUzHKA2ZHF3VSCoc+h572mMcJjNWq4b0Vd+Tf+wkro3r8ny9ADY/+oqxx78v3MTMqfouFaPLY8vN454tqdRc1nMp5xlaTawOIBfkZFkKyGoyFrUDZNc2wM/pCQD2il05pH9CNb9qpS73nPEO/ZPKsK7SbM6a7nLd+IhK3hVo6RZJ0OE5yFKcCDf6NNHg8ugnormle3DhybvDM5y1lzOY0aUCVpuRgoNi+UbHvGX45uQQoNNhTU/HmJ+P2cODgMnvoD9+vNj0tuxsDI/TUCrUlMuM5/mI9ux4XDzioo5vDVppgkRfjuq94Oq6ohKgz+Liw3VTOlMuzGJD+xXEDGlFZN3q2L/bgjUjA3XN6givDOC6u55NdzbzSbUJCHsnQsXOqMu1Iercal73LYep/EuoNR4odr8NPZejUf+ivKnWA8y5sK5X6RUZbu+EoNI/i3+FO5nOxQOADGNGYUSRWqFGrfiV1KN/KHF5JYWmp6Qb0gvTfP5ovDXevFXvLUbsH1GiLcQ1hIreFf+U+0r8PRAEgfJe5VnefjlZxizMdjOeak/8tH5S+oKEhISERDEkAUHiT8dD7fH7ar/rfCGqGYTWEzdKatdSu1p965Dy4ZuF4sGz5B87hmurVuTu2uV0rEvXLnwt3MU1L49OfgG41K9PwTknJ+mCgEv1CrDrPtZ2H3DSUcCnt5ayseFHCDt6o+zxPTKdK7bs7FLXaXr0GNyyqaINZNLFTzkWd4y5Lecy9uBY9A4z3nY9PqNHkbF4CXnHTuPTfjjK+6WkEFTviywnBnaORWYRN3FKpQtBAz8gs2wkurrVSDVfZcejzcWGLXq8mmXvvol3WgE3NcZS1wrgotAyuf5kavvVYk/MHmZc+ZxKYRV5vsU5Qu4dRXVnG46aA3joHcY7R8bxSbNZbG7xOVrkmIHtKWdZd3c9WoWWdpHteaSNJ3DDjzS4eY9mwcH4vlwBzb63IaKRWILw4SHRS+Ap7sFg/DmE9uJKqN5HjEIQZAhh9fi6XAAuj/dgdRSQ3LERt+q5kWfVU90tGtcrD7F/8gUA9txcZBrnKQqmR0/APQjv/VOZ2HYaLzaexZbkU5jtFp6Peo7y+iz8to4SO1/fjKPJBIRjn5aYx9DhYz6/txGTzYSLqQA3L08+8NlJtxl98FK6cV3/AEF2kz6erWhVfQJyoxFHh5kIB96H9HtQri2KvCQUP06B1FtitIOmlJ8TB8UEnBL8gQZngbrAUttUMhUqmVQO0Bk2u41MYyYNghrww6MfnPap7lf9T62EUMW3Cl+0/oJZ52aRkJ+ATJDRKqwVb9V9iwBdwJ92338KDocDs82MUq5EJsj+28v5U/DR+uCj/WOimSQkJCQk/p5IAoLE/x6/kpv+FIcFDJcuO23L3bOH8FWryD98GHt+fvGpq1XhqmcOi64tBeBrzWa2T/4c4+CXiyoU/Izf6GEoHm3DEVQLk2sEsU8O465yR5V4FfJTkMlywMMVhZ8f1rQ0p2vRlA2DBwnIrWJERJ4lj10Pd/F2tQn4p7mQ8MlnuNSuTeiSxehPnsSqCEZRti3CwwPFJ/KvBBW7wJLGxa9bClAcehO/oT9hV2kIKLCzo/FsrDIle1PPs/bRDhLyEjB46bAt+Y6Kbw0t9Z2Gu4XjpfYm1DWEfnv7F0YqnEo8xerb3/Fl6y+pHF4f5b3dzEo+wML679HQZEOpsIulDFU63ghozmvhPchQCMy8PI/nyj5H8KjB+DqUCIYclB7uOOqNQHhadaP+y2IpxN0TIaAKpD8o2gxnPYbK3cWUlU6fICRdxS3vJ4xZjzhRvSuTTg4v5iHQ3L8RkxbOpGDUW2hr1cJ017mBp6ZMBDxKBIcd75+m463xpGZUMxwKNSZ3GeZHeZg7rECuNGLyCkJw9aPAt5yY0pD9GId/ZdIbvUq2RwgXr8ykXVgrdBkPqOYZzrhaY0nSJ5NpM/J82T6E6LOQbx4GaT+f6ut8oeW7YmWPS6uLFqX1gtovgbyUP5K1nlChk2gW6ozKv17Z4V+hvFd5XJWu5FuK/+woZAqm1H2LILsDchLENamk1AUQq4pcS7vGhMMTmNpoKv4u/sV8OQAEBF6v/frvE1P/TVyVrrQIa0Fln8rkW/JRypR4qb3QSZ/T/wurzUqiPpEfHv3AtbRrlPcqT4/yPQjSBUmlMSUkJCQk/nEIDofDebKmxH+F3NxcPDw8yMnJwd3d/b+9nP9ZLMnJPOrSBbveeZnAoI+n41KrDhlff03esZPItFrUvbuT2jia0VffK1ZesIJnNCtrzCFr1y7sZy+h8PPBp0cHVMbrYC7A7NGIJ+PfRV2nDv5Tp6CJ3YXs4BTwCEffbzfGPQdI/aTkCbXCz4/Iz95AuW849wesp8fxiYBYIWChx8ukvjwaQa3GvXNndI0bIff2wZaXi1u1UGQpV+DmFjF0ProDBNUUc91vbHX6vI4qPXA0HotsTQ8wZImVKKI7ENvoFb58uI3xN8MxLl6OeuwIVlRIZkfCvmLjBQQWtfocuVzJlBNTyDRmlriHn9aP2U1nEWV1cNOYSjOlJ/Lzy+H2jiIzRL+KOLp9SUGOknFP5uOr8eCDCoOQHZ+HskZ/OD4XEn8h/ITWhRaTxdz+74eJef4gVslo8OrPOf8rRI+MjQOJHbiJ54+/7jQUfHz5EbRZdgX/V18h8a1JJYQdubc3kUtnodratcRYW62RpJxykLNjN4JWi7BuIX3Pj+XdBu9SxqMMfoICgyGLVHM2/io3QhXuJJqz8dIF4vvt8+Cwc7XnYjYlnWRI1SF4FGTjv/oFMOWV/MD6bYA9b0JeElR4DtpMA5+yxauN/JL0+/BNm6IIjadU6wUdZ/9hlRhsdhu3Mm7x6oFXC1OP/F38+a7RTAKvbkJ2dQPYLVCxG7R6B7zKgOzveRr7e4nLi2P+hfm4qlzJN+fTM7on3976ljOJZ3DgINwtnCkNplDTv6ZkNPkX5ErqFUbsH4HJVpQapxAUfNHmCxoENfhHVhuRkJCQkPj78Xv3oZKA8D+GJCD8PuwWC2nz55O5YqXT9ugDW5DvGoHdpyq2wIYYQuvw+r0F3Mt+wKCy3WnuXRUcdm7kx7HswRb6V+rP3fQ7BCu86RHZBY+Hj7Glp5O18wAFZ84h9/JCU6kS2jp18GpbE8X6TuKN3IMxvLCV/N0Hyfj6m0LvBXWFCoS8PwH18QkUlG/LPDc1mx7tBGBe9amUfW81OBwETHmX7M3fk3/4MIJCjlv79viMGIHDRwkOB5pTC+HxSfEk/ua2opPsXxJcC6Ja4Hh8GrtfLQR7AbIHe7Dr/EntsJjcweOwpaeDTIZ2zjQuBBSwKmELqQWpVPepxriao9kes5uOEe0Z/tPLpb73Ba0W4KXypIrSE/WphXBxFQTXxhBSE7lJj+rej6DxwNZjLXeNefhbkvD9fgQEVIWqPeHA+84nfm4+XPxWPJl/Sr+NcHS2KDgo1NDtCzj/Dd9U78Dnt1Y5ncZH48O6xkvwkbmTuX4j2d+uKjSaVJUpQ+D701CXC0Z2dDaym5vE8ogqV2zVh6K3ViFh8odi6srsaXyqOsTRlFPUDahLtFc0G+5uYHGD96n94ATay2vAagKZAkeVFxAqPw9bRmAd9iNxOg8+PvMx8zRl8Tg82/nzhjeCHssAQYw++JV0nULsdtFo8sJKuLdXjABoPA7CGoCr/2+P/xew2W2kFqQSkxtDuiGddp6V0X73gmhy+SwaDxh5FLyj/tD7/5UosBRwL+se2x5sI60gjYreFakTUId7mfcI9whHhgwfrQ8nE07SIbIDoW6hqORSGshfhdSCVAbuGUiSPqlEm7vKne+7fU+QLui/sDIJCQkJCYk/lt+7D5Vkc4m/JDKlEu9Bg9CfOYvp1q1ibYHvvo7MUQApN5Gl3ER2ayNJ/deRZsxgQ8MPCTw6D3nMBwBUCKxO09bvcMZewP3cB/yY/YjO8hrkjBSjBWQ6F0I/mYbGX4k86SQOVQqCqxv2TvOQHXgPAqqgPfcx6nbD8ei0HltWJoK9AEX+XRSn3yav+oucCSjDpvOzCtdXTVuW7NhYwpZ9ReIbbxZ6KDhMkLNtO/ozZ4n8chZWrQlHyk2E1NuiQOBfqXQBwb8S1jLdyHngRd6mC8jd3fDuMQ81MbgJKrJyfj61ttsxvDWd2pUqUbtvTxz+nmitAg6tH1vvb+W5yE6/+t5tdhuH4w5To8wLEHuCxIGbOJb7kIPpl/F0cWNAzy+JTLyOhymNCLUfuj2viLn75dqKkQqlcXWDWOUi6Yp4kt56KtzcWhStYLeC0gVcvEi0ODnR/5lMYyaCGvTp91lZphWDN3TFzZCLoFRi1biwP9nMyZ9SeUfZCl3rLsjVcmR+IRjiMsnZtgPNy4OwtW3M4pStHE08BYhVIyx2C32iulH77iG0l74ruqHdinB9sxj10XgsNo0HK2+sxF/rg0di6dU9SLkhGma6h5Te55fIZOJGvc1UaDwW5EpRRPgTkMvkBLkGEeT688bowsqS4gGI0RBnl0K7D0SR5x+GyWriUNwh3j3+bqFp6fGE42y4s4HZzWcz/dR00g3pfNriUxZfXcyy68tY1m4Z9QLr/ZdXLvF7yTJmORUPAHLNuaQXpEsCgoSEhITEPwpJQJD4y6IMDCRs6RLMDx+Sd/gICi8P3BpWQWF+jFBQPHTdJSeRL2pPImT9QHGz95TkawRsHEyH4T8xvyANN5UbjtSfix4KAuELZ6G5Pgvh0qWiMecXYB+wFftLO5BdXQ/mfASZBWX2OSxKNbk+Eaioj75CA764v4G9z4gHlbwq4KHUYm3VivwDB50aMFqTksg7fREv9WEczSchrO0BN7dDr1Vwa0dJMz2ZAke9V4l9aSKWxMTCy/mHj+DV+wU8y9rQNWiA/sSJwjbT7dvIFyTj1asbns93wmaysrHVYnQ2G1qFttBp/1meluoz2ozIHBDf9TMGn/+gWK73vic/MSy6N8OUKrQyW9GmU5CBvaThZSEOG1TpjqNqDwS5Gk4sgBvPmEG6+IilPr2jaeJbg833tzidpppvNbR3dqHLjONh3iCafFfSB6FmmCc55mTSpnwpLk2txnfXRj57zk6O+R4Xr6wvlh7RtUxXFl1ZxKJab6A93Nf5+h8cgEZjyJHLORp/lGivaPRe4ZSaee4ZDvJ/c8MtV4LrH18GsFRM+WL0S2nc3SuW3HQr3Xzx70qaIY1pJ6eVKNuYZ8ljydUl9KnQh32x+0jITwBEr4QpJ6awpvMa/F3+2KgRiT8Hm+NX/twCLHYnFVokJCQkJCT+xvyzE1cl/vIo/f3RNWhA4GtD8O3VHrWvFrmbZ4mTXd/HZwh6fK64ePAUmwXVyUV0DGlBjjkHIUh0K9c1a4Iq8whC8qXi/ZtMQHZ/H7IV7cVKAdc3I6ztBQo1Lsk38MrMRZ2tQnsmlnfozM5GKxheaQiL6k3hi6heKJOP49a5E/rTpwunlOlcUFeogDIkGIDcQ6ewu5dFdnEl1oFbwStSNN3rvrj4Rs09BHv/zWTuOVlMPHhK1qZtOAwO/F8fD4oivdCjexeivnwPX+9TKLd0R7N1MNEZT/DPTuDN2hOdvutRNUbx/f3v6RjWhny5nMUxO0sYxQGsuLeJVBcPHM/mxccchQqdnc4LQLXeYDUhWM1gyBRLePZaBW2nwwtLocNMOL4AR82+VHEoCdYFO53mjRqj8Mx8jBDekuYR7vi5qokOcOWVhgEMbxBIiKeWxkEa5HeKogN8xoxGr5WRXJDM+eTzxcSDFgFNqa4rz+T6kwlRuP5qtQOHw46g1KJVaDmXfI7M6PaiAaQzWrzzb3sWpOhTuJhykR0PdnAl9QppBc4NPP8wZApQu5XernYt/Tn/5tzPul/qBvJG+g3Ke5VnYKWBbL1f5F2SpE8i25T9H1qhxP8XL40X7irnYZxquZoAF6m6hYSEhITEP4t/5r/6JP4+5KXAjS1wehHo0yGsPjQcDam3oUwreHRY7Kd2QxlzrNRpZHGn6dPwZVy0Plg93VFXqYx393bIr08q3lHpIpr+bRxYYg5hx2gsg06S+sGn6E89Kw7oGL50MTIhA92WviQNWI8yMBKZzgWZzgW/iRNR+PhgvHMXhY83ytBQ9BcuINji4fZOsqv15HzzUURqfPF1DcPWby0WfRq+Wl+uFyQSrY0kdeGE0l/RjwfQdamO+6rFWL9Zh0ylxL97bRS7+heZHxZkImx/BVWPr+kYXI+wNktYev1rHuc+Jsojit4VenMp5RIOm4VwF38emDPZG3/I6f2CdcFcybiF4B5FOf9K4mcRfx6aTgCfcsXLNgL4VRBP5Fd1KfysaDkZchPh7h5R9LGZsfffRIY5l8Af3mR5z6XMfbCZw4knsDvsRLhH8G6VEVTISSdXaEHWgh209jtF73HDIfUS2lsbQa7klbaDcQmKIH7GGZTh4fiOeYX7FTwYs38A7zZ4lx7lenAs4RhyQU6XqM5EZ6gxX77G1JyFrK4/lchS3zI4dP74aH3oW6Ev8y7OY/6DzUx5YTE+P7xRZKQok0PTiRDR5FdmKp3YnFhG/jSyWEh1hHsES9suJdQt9N+a8zdRakQzyzvOSxPScPQfZuD4V+NZUz1neKg9uJJ6hce5j4tdl6yH/jr4a/2Z0nAKbx97u0TbhNoT8NX+M7/7EhISEhL/XCQTxf8xJBNFJ+TEQ9I1MR/erwKE1gePUPGkeudYcZP5LIIMXlwhGrxdXgu3tkGl58XN2/XNJeeXybE1nYYpojN5KQmo3Tyxe7rhohHQLKlXPPQ+ugO4BhQvwfcz9grdSX0QSdbaTSXaBK0W7+9XY9JZyMCGDYEyZ+JQuLuTvvQrjNeuFfVVqwn9fAEuicuRmTLIavc+Q87P5FHuI2Y2ncncC3NpGNSQ3hV6k5SfRG3CMU//FLmnF8abN1HUqYm9V0fylXa0ghK3PAuuIRpS5Q5C83NRuQUibB4kVgB4lrrDREM/Uy421yASK3XkoSGF25l3OZ14mi5BjWjtVRmv3DQu+IYy8qeRxUK36wTUYXDlwSTqEymwFFA7oDYhch2BK58DfZqYhtBtkfg53vkBEKBGP1FU2DG6RHSIY+BWhPT7oFCJJoGX12FpOx3ld8+DMRd9rQFklWuJ1eHANTcJ37PLsNR7h5hxn2LLziZyxedoLk1FSC/uG+Eo1w5Hi6mYcrNJCQmj+84ehWHKIa4h1A2oi81h43zyeZaWm4J85VY29/TDX+fBSzd+Qh57vOR3yDca80vbMGk9MFgNvH74da6lX6OuX01ej+6Hv8WEi0NAF1AVuWvg7zNN/AXphnSG/TiMmJyYEm3VfavzRZsv8NJ4/cvz/i706XDoQ9E081nKtobuS/6R6QsgCjpdt5es6AEQ6hbKxNoTmXi0eERPgEsA6zqvw18npTD8Vcg353M/+z5fXv6SB9kPCHMLY3TN0VT2qfynluWUkJCQkJD4TyKZKEr8PUi/L55M56cUXVO7wZCfN6C/FA9ALIV39BOo9RK4eMPIY6BPx6HSiYZ3v+hrab+EtJ1XyNnWvfBEXhkaisuXC3FU64NwdV1Rf4UGzHqnS7WWeYHsTz5w2uYwGHDcvs/r9rXczboLwPdNl+O2Ymcx8QDAYTKRMnceUd98hi39Hu4xF/m+ynjyXX05Y0qgknclBlUexGuHXqNVWCuiy5fl6MQmJBek0DhkMl4aL945MbnwlLpBYH1meL5D2dUvQnYs9P6upHggU0B0R1jXG2QK5D2WEXbma/zsViqH1KSXd318c/Ix+ajJ0OpwVeoYWHkg390SDQXrBtSlV3Qv3jr2VrFT2eq+1Zk38iAB579FiD8Ld3ZDk3GicGDMgYTLsKGf03fG0U+wtZ6BfMfLhV4K8kavY6s/EfmBN9Gd/Qrd2a+K+vuUw5Rhx5adjUv9eihzzpYQDwCEBz/hqDec99MO0lbXvliOc0J+QmG+eqR7JHY/H4SGNRgQ1oDx12fQrNWbRO3NRpZ8vWhCrygKeq1izOmpAIysNpJPW3xKTE4MOx/uZHvqBXpG90TjGoJc4+n8WX8HGYYMp+IBwLX0a2QZs/48AUHnK5aarD0Yrm0UK1BU6wW+5f/wChB/JXy0PgyuPJhvb31b7LpMkDGp7iQWXl5Y7LpckPNBkw/wc/kPelhI/L9xVblSy78Wn7X6DKPFiFqhloQDCQkJCYl/LJKAIPG/iz4dtgwvLh6AGA6+/30o367wksO/EqnNJpDl5o8V8LQ78FHoUCXdxVagwparQ+HlgqLtDISD0wuFAkfZDmSdjiNn6/Zit7DEx/Nk2MtErV2B8sZmsP2c55xwCZq/KaZNlECBw1DSfPAp+U9ikIfLUcqUtItoh5egI/OHkmHhypAQwj+eiGxNkXAiB7x8ytK+zwbCa41l/OHxtAhtQR3fmry4u09hJMCmB98T5hbGtEbTmHhkIgargbPJ5xh97E2+afkGftvHim7+vySktlguEsQ8/60vQ7XeaCp2QeOw41B7EOcTxqpb33Eo/igahYYXy7/IgpYLmHJyCoOqDOLNI29itpuLTXst/RpfX/+GSWpP1H4VoSADVj0Hz38BSTcg/kyp70vIuIegci3m/m+/e4z8DC/c281BdnIOFGSCIOAo1x5zlddIHD0ZAI92TVDcX1r63BdX4RZeHo1CU6JNLsh5t8G7WO1W3r86i1xNLk0SEvik+SfcTL9PWpu3KS/XodNnoPCIIAYLo46NJ6VA/KwupFxgQKUBjKkxhsbBjREEodR1/CvoLc6Fq6c4M778Q3HxEX+F1P5z7/MfJK0gjce5jzmbdBY/Fz8aBjUkwCUA9e+sKOGmcmNYtWHU9K/JsmvLSC1IpapvVcbUHEOgLpDpjaez/NpynuQ/obJPZYZWGUq4W/gf9p2Q+M/irnIv1Q9BQkJCQkLin4IkIEj871KQDklXnbfVGlAY8m4NrUtM+w8pyCnA7UEuyswszGUiuO9hwSf4eXK79gCbeMrsN/YVfF45gxBzCCx6rKFdyOo1yOktbBkZmGKeoOy3EY7PEzfYBRkQWB3qvSyG5SddgaxYkMkRPPxQBAZiTU52Op9QORpLzgkWtV7Enpg9pOYmIjeVzKEOmDAC5ZEJJYQTh9YLy70fCK76IjmmHPqX70Pvvf1KOMDH5cWx7f42Okd1ZsvP1Qoe5TwiwbcsfuGNIOMRBFSBlJtFg+QqsBQU/d5ug6vrxV8KNXEvfU+/vYPINecWdllwaQFVfauyqNUi7mffLyEePGV7zB6G13uf4IPPRGcc/ACavQWGdLj/k9NxDq+y2OW6Yk6vDo8I0uYsIe/rFfgNaoUm6z4IYJf78HjoJGyZmeK7lst/teqDYLegEOR4yV0o41GGRzmPCtteq/UaJxJOcDjucOG1J3lP2Bm3l69af0ugLgCtRoXVbmfs0dc5k1RSBFl7ey29onvh9mvmg/8i3hrvUtsUggJ3tbSx+VdI1icz/vB4bmUUlYGVC3LmtZhH05Cmv1tE8NZ40zaiLXUC6mC2mdEpdbiqxBQVL40Xs5vPxmg1olPqfvecEhISEhISEhL/q0hVGCT+d7E6MSjT+ULnuWIIvncUCDIy2s9EnWhAM3wKptcmY572CaaBY9DNWo7SPwB1pUri0CYNcWtQDfvNvTisRvCJxm62YNeXfrJrfnAPTsyH8IZi6P/Iw0VlFAUZNJkg+i30Wo0yYT9+r491Oo8qKorHHmbG1hrL+6feZ+fDncRb03Hr1Am3jh3RVKksdpTJ0AR7iKLEU3zLk/DSFtbW6s4Ewz0+v7mcr9t/zfWM66WWGDv05BCNgxsXuxaTcRvqDhdTB9pMK+6sn3wDwhs5nctU5QWWP95bTDx4yo30G+gtecjtdicjRcx2M1a5svjFlJsgV+Co1E0UL5xgrf4KxrsxosEigHsI5lw5inYd+eBoEp3WJHFfFkVO3C2EJ8fRNapfODb32HlsUZ1KXZOt1kvcy3uCn8XEgloT8dOKIeUuChci3COKiQdP0Vv0fHPrC3RqBS5KF7LN2YXiQS2/OkyrN49PG3/DhBrvEe4WzpnE0qMr/h28Nd50jnJeyWJApQH4aiQzt9+LyWpi+fXlxcQDEEv2vXH0DVINJauL/BZeGi8CdAGF4sFTXJQueGu9JfFAQkJCQkJC4m+BFIEg8b+L1gtUuiLPgbrDIao5KNSwYwxENoXuSxHMGgxjRmPXFxQbbj51FsPazbi8Phr5VysIfqUzin39sZRvS2aZ5ggFKbh7hCP39MSWnQ2AplYtqFMVWYER0/7DqKLC4dItiD0OTSbgSL2NcGRm0U1ubgXf8jj6rCXLmIO8Wj28P3yfnAVfYMvIAJkM19at8H1jHK7yNDIFBxa7hY6hrakfVB7P52IRMu5i82yE1Ws0SZ9+BaZnNuou3sQ8N5dBZ6YWK/12K/M2bSPalvrqrI6S5QaDNT6w/XWxNGLWYxi8C27/ACnXwSMMfMrjiGyG8AuTwOwyzTl4e0mp99r1aDdjKpTiY4BoTKjVp5ds0Hhic7hC529Q3FgBkU1Ej4mkq9i8qpJ96iHG+0dwadMEmdIFc9M5JE38EGHqRxz8MQO7A9qt1NO4TFOahmnoOdQV2bGT2HNyyD92AuvLXyJ/uFOs5vAMjqCaWENqMdonlHvGHMrKdXzXeCaP8+PJF+BG6nUaBjUk2DWY1IJUTieeLhRqjsUfI8+cV7hJlAtyptX/lCeJ/nyyLY20vHQqBATxSuu5+Ln+esrBv4q72p03676Jt8abzfc2Y7KZiPaKZnL9yThwcDjuMBHuEQTqAvHR+vyh9/67kWnMZNuDbU7bbA4bZ5POEuYW9h9elYSEhISEhITE/z6SgCDxXye1IJV0Qzr55nwCdAH4aHzEDZproFjOb/97UK4N5rKtSJfLyXHzQ9f3W1QOB26uoVjPXi0hHjzFsGUH3r174zlqIIrz00gYuJH1CUfZF7sZpVzJeDdf6gwfSs6Gjcg/ncpR0w0OZ5/HVaGjf/e38Q6ogOvJTApqvYSiak9UZ76EGn0h5jjkimZ7pN/HcWEFD6s/z8prsygTHsWANUvRqVzJV1qQGdKQXVlAwLVNBARWZ2/3ZaizYpGv6FjoraBgGwqNB6FTVlIQUoasskfJs5nRqt24lnELq724IBCbG0uUR1Sp77ScZzmS9UWpFL5aXyJsdjHt48QC6P0tfNUcwhqAT1nIfgwrOyF0W4SjTCuEiyvBmA2RTRGCaqK66zxKAECj0OBjNlLJK5rbWfdKtL9ZewJ+eoNYFcOYI150C4SCDBw5T7ApQ5BXeA7h0gow63FEd8Qe1oTcz2agLlsWe62RmLPzSPt6I5aERFR2O0q5DJNVjHo49SiLU49gq5+OxV99i9vurRiPHiF5yVpCp25Cdn87wu1tIFfhqDMMW/k2pGc/IUjtRo7ag61JZzAashjhVh637ASCKrbDio1HOY8IcwtjQOsBrLuzjuMJx5E9E7TlrnLn7TozOHTZnR+uxhdev5uSx8T1eSzoUx17qAOZrPR8d6PViNVuxUXpgkz47YAwPxc/JtSewMDKA7HarRitRkYdGEWaIa2wTxWfKsxvNZ8gXdBvzvdPxeqw/moJxnSDE8FLQkJCQkJCQkLi71nGcdasWWzdupU7d+6g1Wpp3Lgxc+bMoUKFCr86bvPmzUydOpXY2FjKly/PnDlz6Ny5KGTY4XDw/vvv8/XXX5OdnU2TJk1YsmQJ5cuXL+yTmZnJ2LFj2bVrFzKZjJ49e/L555/j6vr7yrb9k8o4OhwO7mXd47VDrxVudgUEepTvwWu1XhPraxdkwr0fyQyqypYnP/H1vQ20DmvN4DK9UecY0Spd4Ng5sufOL/U+oRvXocm9TmpYOAPOTifDmFGsfXHtWYR7RjLszHhSC4qHLvcs14PXApohcwvAM+0+shtbAAdEdwKHDfa9AxYDqHQkD/2BdvsHE+UexactPuHbGyvZ/+QgckFO17C2DA1vR0h6jJh6sWlQ0Wb6KQo1KSP2M/Pmcg7FHym8XDegLsOrDuetY2+Rb8kvvP5W3bc4Fn+Ms8lni00jIDC7+Wy+vPwlT/KeEKwL5st6kym343XI/DnXf/AP8O1zzl9YlRewNXoLefYdeHwKa34KyyKqsuTuWqfdP2/1ObXy8zBpXPky7kd+ePITVruVIF0Qb9UYQ4O8LNzPfSOmTWwaBBYD9hdXIju1CEf7j+DobISYY8Un1Xph7vgtZr0cW2IMqpBABO8Qngx/BWXzFiyu0o3N19NKrEUuEzjycgUCY/cjlG2F4uCboFRBRFOIbIZVJqfg4UHuB1Xk65hdJOiTqOxdiZ7RPXGYDagcNkYcn1TMz0EhKPiwyYesu7OOcLdwpjWahovSBYA7yVl0XHDK6Xvxc1Wzc2wTgjy0JdqyjFk8yH7AmltryDZl0zq8Ne0i2hHsGuz8M3FCij6FAXsGFJo3PkvL0JZMqj8Jfxd/1HIpdP6XZBgyGLF/BA+yHzht/7bjt9QO+PuYRUpISEhISEhI/Ba/dx/6t/RAOHr0KGPGjOHMmTP89NNPWCwW2rdvj/5Xct1PnTpFv379GD58OJcvX6Z79+50796dGzduFPb55JNPWLhwIUuXLuXs2bPodDo6dOiA0Wgs7DNgwABu3rzJTz/9xA8//MCxY8cYOXLkn/q8f1WS9ckM3z+82Em5Awdb7m9hy70t4qm7izf2Gn04kHmdhbdWEuASwITIIWi/3ICp90hyB76CrnKVUu+h8PeHrFxsbh5sTDxWQjwA2Jdzmm8ebyghHgBsebCVFA9/PA7MQPb9ULjzg1iKcOdrOK5thucWiB0tBQhATb+avF3/bYbvH8GumD2YbCYKrAVsjNnJ4PMfkRTRQDRi/KV4AOS3nsqnt78tJh6A6Oq/9NpSRlQbUez655c+Z2KdiYypOAJPtScANXxrsLLtN1RxL8u7lYawoelcvis/iHLbxxeJB0oXsFtKfWc8OIjpURzW7Hw4/w2KOz/Qw68O5TzKlOjavezzxObE8lnKMXDYmawK54fGc9jVYhGrm8+nXV4u7jvHQ/J1uPQd9haTyX5pCxazHuoMQTBklhQPAAxZKO6tQRsVhIdhK6iTkLuqCZ49C49KFRldL5Agj5IVFIbU88ctZjdKH28Ud9ZC0/GQlwJHZoFCheXMYna6ahly6l1OJp0mNjeWPbF7GfnTKxhlAkvubyxhBml1WJlzfg5DqgxhTM0xheIBwMNU4y+XUEhavolcQ8n3nGPKYdm1ZQz7cRiH4g5xKfUScy/Mpf/u/jzJfeJkJuck65OdigcAR+OP8jD7IReTL5aIXpEQyy++Xe9tp22VfSoT7h7+H16RhISEhISEhMRfg79lBMIvSUtLw9/fn6NHj9K8eXOnffr06YNer+eHZ8rqNWzYkJo1a7J06VIcDgfBwcG88cYbvPnmmwDk5OQQEBDAqlWr6Nu3L7dv36Zy5cqcP3+eunXrArBv3z46d+5MfHw8wcG/fbr4T4pAOPTkEOMPj3fa5q5y5/tu3xOkCyJFn0KfH/qQYcxgabNFhK4+SMGG7wv7Bi+YT/qiLzA/fFhinsCPpuNaN4Isdz9eOjSaRH1iiT5zms9h6omppVYRGFxpIG/eOQ2PShrrObotgUdHsRvSeNL+faxKF7Y/3M7qW6udzjW5zpv0c4lCWN21RNuT0Sd4bu+AElUVnvJF6y947dBrxa6t6bgam9GAl9oLQRBQCypQKPGy5qFZ9ZwoVDy7gfSKIrPTbEzekcjjzuJ3aQ1C3Lniz1S2Demp9ZG5uuBVTY3s2EwQBFK6fsYVzOxKOoFOoaV3SCsizSbsGg+WJRzCKAgMr9CXJ+m3uZX7iHJuYbT9aXaRIaRMTsbwH8myGSl3fCHU6Af3f4SrG5w+Lyod9hFHMec5kLvIcZgcxLzYD4WfL9patTD1GsjxFAs/xhvwVMt5qao30SEueKedgdNfQvx50Siy17dwZR2o3Ymv0oWuJ99yuqkO0gUxsvpIZpye4XQ5azqtoYZ/jWLXbj3J5MTVWDItDrbcziItr3hY/OE3WhDlVzz66F7mPXru6un0Hp2jOvN+o/eLiRSl8Ws/PwDzWsxj+qnpbHl+i5TO4AS9Wc+NjBvMOTeH+9n30cg19Cjfg2FVhxGgC/hvL09CQkJCQkJC4j/K792H/iM8EHJyxNNeb+/Sy6CdPn2aiRMnFrvWoUMHtm/fDkBMTAzJycm0bVtkXOfh4UGDBg04ffo0ffv25fTp03h6ehaKBwBt27ZFJpNx9uxZXnjhhRL3NZlMmJ4p5ZebW9Lp/u9KTE5MqW255lzMNnFDb7KZCiMHKjr8Sduyo1jflOkzCJk/n8zvviP/yBGw25F7euI35mXcdA9RfPsKjDiAqhS3fwEBu6P0KgI2qwlkzoN1hEsrsLT8lAKtjeFHXqdfpX4ci3dyov4zP8YdolvdybiWaVVCkMizGUsVDwDyzHkoZUosP0cP9CzXnUi7gJvOH5NKy5bH+4l0+FEpXYMy3BU6zYEdrxUKCPn1hnO9Qhvm3fqGu1l38XfxZ0TtF2nf8FV8cpPF1AqbBbzL4ZphRe7IR/Z4Gzz3GcgUBMiUtFd506pcf2QXVqA4M1r0VBBkvNFrFavNSbz442BMNhMyQcauZvOLV5Ow23AR5OiOfw6Vu8O9vfBr4fUyJaaHscQOn4BH1074DuuPMjwc061bmGNiYes2mlWtQrPqtZAV6HHJDcC7dTnYPKRoDlMe3NsHTV+HvW/zxNyk1BP5JH0SHmqPUpdjp+g74rDZsCQl471xHW1PnkLm7U2v3gM47ghl+lHRD6FBlBdeupLfuYNPDpZ6j/2x+5lQe8LvEhBCXUNLbdMqxLSJPEseqfrUv5yAYLPbSDOkYbQaUSvU+Gn9UMj+2L+udCodDYIa8HX7rzFYDcgFOT5an1L/nJCQkJCQkJCQkPgHCAh2u50JEybQpEkTqlatWmq/5ORkAgKKnzoFBASQnJxc2P702q/18ff3L9auUCjw9vYu7PNLZs2axYwZzk88/+5U9K5YapuPxgdN5mO4sQvXSt1ZV/tztAUWtEY7fm9MJHPVt1h/fqe27GziXxtDyNzZBIzsjcOQj0wwoLi9CuHcCTKeX8ShzBt0iOzAV9e+wlvjTa/oXlT2qYzNYUOn0NEmvA0/Pv7R6Vo6BjWCY984X6jVhPFuLI+rBBPlGYXZZv7VzZ+L0oVku5HwzvNQ3dkFeclwbSMYMnFVuCAglCoi+Lv446H2wEfjw/Do3jRyK4NeqeZU2kWu5zyinHd5AnyjSQ+0YDHm4H/jMLIXV0BuIg65ipMe3rx58p3C+VILUpl5bTG3ynbjLXkg7uvFSgqCTIGm/xaEPT97Jpz/unCMAKgajwVzvigeADjsaHa/QY1unxYa002qMxHfy+uLP4DOF7Vch+z+T1BzINzdB90WweXvnD6vo3pfMjfuArudnB27UXh7EfjWOB4PfbWwj/HGTbhxE5RKAreshx8HlZwo7hw0ews8w37TqFAuyJ1eV8vV+Gv9ReEgJQXzoxjMMY/Q1auHXKMhfdnXcOoUzQYOZmz9tmy8nc3sntXxdCm5GbX8SvqIzWH7VRHpWfxc/GgQ2KCEBwZAr+he7I3ZC1BkFmg1g0UvprD8D5cUzDRksuPhDr65/g255lzclG4MrjKYntE9RV+UPxipYoWEhISEhISExO/nb+mB8Cxjxozhxo0bbNhQSpj0f5nJkyeTk5NT+CsuLu6/vaT/GGU9yxLg4jxU+NUKffE7PBtrvhH7pp0oB72JZfAEHvfsRc6WrQTNmIEqKrKwv11fgEJjRbW9G+of+6PcNxzh8XFMVXrwneEJH1+aR0XvirQOa83HTT/mXPI5xh8ez8QjEznwaD+jyg3GXVUyVKdVUDNCBK1TzwLcg0nquoBjIWY2PNlOBe8KNAtpxoCK/Ut95o6RHRl9fBJx5gy4v1+MbBi0AwZuxVumoU1YS6fjavjVIEqfw8ayA1nm14JOJhvpKg19Doxk0rmP+O7uOt4/PYMBeweSaExl0o2lXK/+PNYT8+HEfFJdvZl96TOnc29/uJOMoCrwdHOtdEEwpBd5JvySi6ugWq/i1/RpRCnd6RzVmQWtFlDbqyIud/cW62KtO4Hcg2ew1RktChAKFWTch2ovlryHZwTm0G7kHiiK0sjcuBW5hw6/0SNBqSy8LnN3J2zxQpT3voMMJ6Z4Oj9Q66D+SMIUrqWaCoa5hRV6SfySiXUm4qvyxnD1GjHdXyBuxAhSPp5J/KujMN68RfDsWSCTYV7zLcMqubN9TBOifJ0bp7YOb+30OkCL0BZOv4fO8NJ48XHTj+lapisKQdSCdUodQ6sMJdQtlANPDqAQFJR1DYHUO7D3bVj7IvwwEVJugtl55ZL/JgargVU3V/HZxc/INYvRWHmWPL648gVLriwh35z/GzNISEhISEhISEj8mfytIxBee+21QiPD0NDSw30BAgMDSUkpbkiWkpJCYGBgYfvTa0FBQcX61KxZs7BPampxIz6r1UpmZmbh+F+iVqtRq/93TwP/TAJ1gSxvv5xJxydxK+MWABq5huHRfWhvciAz55OX6UPa/E+KjTPdv0/iO+8QOGMGCePGFV4XVCVPe9Or92TNufcBmHpyKis7rmTk/pFkmbIK+5RXBKKcuYTvRn/C9xkHOZZ5DlelKwMCn6Naqga3XAE8I8RSh09RuRL/4jcMPf1OMRPINbfWsL7zWpoHN+VY4olia+kQ2YEcUw5J+iRWPtjCe57haE5/CRdX4ei9Gjd9Ou/UHIvVbuVIwvHCcXX8azOz4mD8Ng4pFDIyOs/hzVPvkW3KLnYPg9XAh2c+ZHzt8bx8eipbW88kdHVP8mTyXy1Ndz8vnijXAMhLAlf/4s/6S0x54CScXClT4sDB5OOTmddgGig0Yl/XAOzN3iHnUi6pn8/GOmYYnuWikDcYhXD4Y2g7Hcq1g1s7RGGhbBvsUe150u9VsBalGzgKCiA3Be+yabh//x2WpEQEtRalqxyFIg/h8DLs1YdgjeiCzWBBplEhTzuLolIrUOnApxw+celMqzGWKZfmllj7hNoTOJ14mrkt5rLhzgZicmIIdQtlVI1RVPOthpCWwZPhw3EYDMXG5h85gioiAtdmzcg/ehTHxfMED4wu9fWFuIbQMbIj+2L3AVDZuzKVfCphtVsZXnW4WML0dxKgC2BKgykMrDyQ+Lx47A47e2L2sPLmSgDea/AuXim3YV1vsNvEQfEX4Opa6L0GojuC/H/nr4EMQwbf3XYekfL9/e8ZXGXwv/R+JCQkJCQkJCQk/lj+d/7l+AficDgYO3Ys27Zt48iRI0RFRf3mmEaNGnHw4EEmTJhQeO2nn36iUaNGAERFRREYGMjBgwcLBYPc3FzOnj3LqFGjCufIzs7m4sWL1KlTB4BDhw5ht9tp0KDBH/uQfxMiPCJY2mYpmaZMTOZ8PHIS8b2yEfXNbVhazydtxhqn42xZWdgyM1CGhWGJi0MdHU2BbyTyukNJK9uSTI0ryFXoXAOp5luNCykXCHUL5Xj88WLiAYDJYcGWkoKpzyv0atOKnvW6IhQYcSzZgOHhQ9I6diTg3a3IL36L7M5WcDjIb/8xcx9sLhQP5IIcPxc/TFYTQ34cxtbnNvFCTk+Oxh9FJshoEtyE2NxY5l2cB8CVjJvk15iI5skZyIpBOPQRNB5HwJ0f+LjmGDKrv0KuxYCryhXvO/vwfEY8AMj0ieLh7ZKmkQBphjRcVa4YrUbO5j4k1L8yyt/IH3dVuoD154oC+nRwDym9s1ILv/SMcA/mliGFvTF7UQgKInwqY2y2GOwWrNl6MAeR8e0kcX1friBj1UbCFs1GU+dlZAc/AK0XlG8PAVWxBDYj/9g1At6ZjDUri5wdOzBeu4ZMp0PAjCzrDg7zffL9BARTCr4XN+OoMwxr792kf7eD7GlvFAoPLo0aEvThYFQAVhOagKq0sVeivH91Vt/dSFx+PNV8qtI0tBnLbyznfPJ5fDQ+dCvbjQ6RHQhzC6NhUEPkMjk5V46VEA+ekr11K4FT3yP/6NFffc8gRg68Xf9tniv7HCqZihsZN7iYfBFvjTf5lnxyTbm4q3+/gapOpSPcLZwCSwELLy3kfvZ9KnhVYHTN0TRzK4tsedsi8eApDgfsGA2vngTPMKfzWu1WZILsN9M+/kiyTdmlelTYHXYyjZlShQQJCQkJCQkJif8if0sBYcyYMaxbt44dO3bg5uZW6D/g4eGBVluyJjvA+PHjadGiBfPmzaNLly5s2LCBCxcusGzZMgAEQWDChAl89NFHlC9fnqioKKZOnUpwcDDdu3cHoFKlSnTs2JGXX36ZpUuXYrFYeO211+jbt+/vqsDwT8VL64WX1gtSb8PavoXXHRp/LAklqyY8xfj4MW6ff0FeXgGX8mXcuZlLoyqdmXZmBgXWAtqEtaFdZDsm1ZtEnjmPvTF7CyMdnuWH9KM079kZPriFcf8B2H+gWLu5fSPOpN+jmq0espCyIAhkCIEcjj+MXJAzpMoQagfU5nHuY1wULnhpvMg2pHM87hhZpizsDjvTTk1DbykqI+qv9UNts0KDV8ArEkPiRTICKxHn7oXMlE6oaygVCvJQmzLg4Icl1mxx2EpcexaT1YRcJueBMQPKtcUz8zG1/WtxKfVyib5ahZZImbbI08CYLf7XPRhynbz/Gv3g1s6i38sUpHf4iPn31wEwuupw1OdvknTmOtbW7bF6yNBpVeiaNyd3pzjOrtfzeNhYfF8egverp3GkPsHk6Y5D5ob9ThLZmzdjvH0bRVAQXn1649mzB9b4GBQPN2Fp+gbvxW7jSPxRPNQe9K/Zm04BDbAvXUnuLww2C06fIWHCRMLmTEax71XIS0YXXJtK7T5geoMpmHCgkqm4nHqZ62nXAcgwZrDy5ko6RHagbURb5DLRF8H8uPQSi/a8PISfI4l0jRr+6mcD4Kv1pYx7GQbvG0yaIa3w+q5HuxhTcwwDKg3ATeX2m/M8xVXlSt3Auixqswij1YhKrsJL4wVJVyG/ZHlSQBSk9KklBISk/CSupF5hX+w+PNQe9K7Qm1C30FLTO/5INIqSpTmf5ak5pISEhISEhISExH+Hv6WAsGTJEgBatmxZ7PrKlSsZMmQIAEOGDCE2NpYjR44A0LhxY9atW8d7773Hu+++S/ny5dm+fXsx48VJkyah1+sZOXIk2dnZNG3alH379qHRFP2jd+3atbz22mu0adMGmUxGz549Wbhw4Z/6vH8bNB7gFigaCwKCORuFnx/WtDSn3Y2RATxWyRiyLQGtUs6yEcGMOfImnmpPFrVaxP7H+5l6cipGq5GGwQ15reZrXEm9woEnxQWCu1l3Sao1hKC6tTFduFSszaVVS+4HyYgyakl6c3ThdfnqBdgddj5o/AEnE06y/MbyoseQa5jddCb9K/XnxR9+4RXwMyOinsNt5zjISyK32evs8o9g7t7+haevarmaGbUm0MojGmeWjJ52B1qFFoO15Im4XJDjqnLFardSwy0CTAl4FGQzo/oYhpx4u7CiBYBCpmBB/ffwP76o+CSHZ2Lv9S2y7a9Cxs+RDoIAlbpDvZfhxGcQUgd7UA2yavRmUcwONAotS5vPo4xHRfKD3DnjWoWP9t7DYLER6qXlve7DKKdzx7K+KKpEHlEG2e0d2HRlyHOriOXISfLfnl7Ybk1MJG3+Ajx69MDvpeew6v1ZkniIfT8bXhoLjMy/uojmqqpYN292+q6NN25gTU1DkfFQrEjx6DAsa4564DbUZVsBUDewLju67+BB9gNyTblU9KmIn8YPD01RVQZtjepO5wdQhgRjy8zCe/hwFH5+pfZ7SoGlgIWXFxYTD57y5ZUvaR/R/l8SEJ7iofYoXknit6r0PhNJUmApILUgldcOvcbj3KIUlm0PtjGi6giGVB3yq1Uq/gi81d5Ee0VzL+teibZwt3C8NaVX0pGQkJCQkJCQkPjzERyO3/oX5t+TFi1a0KpVK6ZPn/7fXkoxfm/9zb8lDgfc3AbfDwWZAkffdWScSyXto5klusp0LlhWzSVGpWDyugLaVfFGHbiF3TG7mdN8DkuuLCE2N7bYGJVMxdouaxm2bxh5lrxibRq5hk2Nl6F8GA879uOQy7B0a41XpRoUuClx3LiL6Uks8qt3Mf6wD/V7r7M08DZRHlF8eeXLEutTCApWd1rNqcRTLLm6BNvPEQMCAq9U6M8AswzPQx+Dzo8L3ecz9NS7Tl/Jxo7fUXnbWEi+Vuy6uWIX1kc3Ye71pSXG9Iruhd1h59CTQ2yo/z7Bq3uIDV6RJHWayRVzBudzHxGp8qKlf20CBS2q7SOLhAKZHFvtwWQ3GoU7chQ5cQj6NFHgeXQUYo6S3X0x+5JOYVeoqe9bHReVG2azkoVHs9h6JQm5TKBjlUC61ghm/IbLmKziRnVFtzJEfDgRc1w83kNewqe+F4pDbwJg6rWHx6+8gy3duVdD1A87+CpzB9/cXl2i7ftKc7EPmuB0HEDo7PdwuzcVCorEE7zLwNC9omj1O7CkpPC4/wAsCQkl2gKnT0dTuRLKsDAUXl6/OVdifiKdt3Yu/F78kol1JjK06tDfta5fJSceljYtii55FpUrjD4DnmFYbVaupl1l16NdbLm/xelU33f9ngreFf7/a/oNYnNiGbF/BCkFRZ40PhoflndYTlnPsn/6/SUkJCQkJCQk/on83n3o3zIC4bfIycnh4cOH7N69+7+9FIlnEQQo2xr6b4LcRIQLy1E0ex/1gF6Y1m8Bu7gJVfj7oZo7nWkxS+ga9RKVg3zo1yCQT689JNQtlFxTbgnxAMBsN7Pk6hLmt5rPqAOjipXT6xjVEaOHhr1+cTSYPJAt97eiUV2lr6YSd1KvsTZjLdnybOq3rcmglxYj+/p7hk0awejj40rcB8DqsHI47jAyQcbC1guJy4vD7rBTx68WQZmPyZMrSBm4Ho2LH7cybxGiCyHPklfoPP+U1fc28Fa/tfh80wHyitIJVAmXeL7DR/i7BbPw2jLi8+MJcAmgT4U+6JQ6tt7fysrGMwk2PONanxVL0KahBPXfTKe0BLh/EB5fg7rDofkk8CknhrsrtWS6+RJrySFVn8qT9Ot09m+An81OflR3PGsMY33sLhbfFaMu+lcYRvyjJuy+VnSabrM72H09CYPFxrAmUSw5KooTM8+ksvqLrwiUmdFeW4rs0MeFYxw52aWKBwCGBw/ZluP8Z9aqUSKTy8HmfEMuRJTHmlMVRcwzHgWZj8Qw/t8pICgDAghftZKk96dTcOoUAHJPT/xefx3X1q1Q/o7Ig6c4cJQqHsAzpRf/v7gFiaUyN71UMhqhy2fgKlZBSTOkkVKQUlj60Rl7Yvb8RwSESI9I1nRew6OcRzzMfkiUexRlvcoSpAv67cESEhISEhISEhJ/Kv9IAcHDw4P4+Pj/9jL+NlhsFtIN6ZhsJjQKDX5av8K88X8ZrScEVBXz7+/tw2CJZ2crFzp1X4wqMw80GuJU+cyLXcCj3BjG1SjDyOa+HLiZQnnPcphsZi4kXyh1+tOJp+lRrgeftfyMlIIUDFYDZTzKcDX1KvH58UR5RBHoHkqERxm6R3fnSPwRfor9idsZt3HgYLs+kX2Jh1g5Yi7uCg1pBc7TKwDSDekYbUa+uvYVAS4BqOVqwtzCWJd6gt0x+7A6rCgEBZ2jOjOv5TweZj9Eo9Cw4sYKbmbcBCA+L56TqRdp22slLun3IPsJhNYHlQ7P2NN0Cq1L3frvY9Z6YBdkWAsysJvz6ejXAu/NI6DHMhw9VuB4eAwhoCKCX1l4cBC8I8VSjI9PwncviAaKz3+B/foWnrR4ncGHXyPPnMfHTT/mSNplkq0FvBLVmxSjL5l6B89FdGZ7/F4S9Yk09GvH8B3OqzYcupPKwIYRhQLCg9R8zC6uqGLWIavcHu5tB734DgXFr39nZK46HNnOA6Z2Z52gb6cO6H/YU6JNFRXJeeKx1utPE/dgXK6uf2bSf+2PQFVYGKEL5mPLzMRuNiN3c0Ph748g/9e+765KV+oF1uN88nmn7c1Cmv1L85WKTA5lW8HIo3B8HqTeAp9oaPYG+EaLpTQRBQRBEH5VuPhPllAM1AUSqAukcXDj/9g9JSQkJCQkJCQkfpt/pIAg8ceRbkhn/Z31rLm1hgJrAR5qD16u9jLPlXkOH62P0zF6sx65TF7cME2fDoZsHDIlFr2A/vhlDDei0HoVEBgexosXXkMhU2Cz23AgbiJbhrYi0NWbPTHJ5BptDK73EstvrSg0e3NXueOr9SXTmFlY7tBN5UayPpmk9Ec879saoUCP2WIn2aajrqIcirRsbHkptAtpybrb60RHe+8KDKk6hG+uf8PFlIsYbUbmxq5kvPc4KnpX5HbmbafPWcWnCuW8ynE26SwpBSkMqjyIbQ+2cejJocI+VoeVnY92orfqCXENYdv9bUxvPJ3Vt1ZzNe0q0V7RHIo7SrXqIwm7sweFi5cYhr++N/RZC2l38Ns06Fc+oPtYXcqTtCufgPE1UG94Hmxmp11tAdXZ6Mjly1PvFkZCzDw7kxUdVqDL0BN0+COCYw5DZFPyG0xkReuvOJF0CrtNg/1XEqEKzFYEQTwAd1MrUOU8QLl/iphC0GUe/Lx+edY1tDVrYrhypcQcMp0LqvAwGjsa88OjH0q0b3iynZfHbYXcfPTHjhVeV5UrB3Pe4cObU0k3pLOh+WdUvrMbTLkQ3gi0/3pOvdzdHfn/M73IQ+3B2/XeZsCeASU27e0i2hGs+wNNV1WuEFQDnl8CFj0oXUBdshTildQrNA5uzPFnSog+S8eojn/cmiQkJCQkJCQkJP6SSAKCxL9NnjmPBRcXsONhkfN9jimHuRfmkmvOZWS1kagV6sK2JH0Sx+KPsS9mHy4KFwZWHkgFz/J4Zz2GXePBlI+p4Twej3kHe7542pmzdQcNJo3j48bTWXh9CSkFKbgoXOhb9kVeiO7Jl9cX8Cj3AWW8y6NVjOTV6q+SacikuboqoTkKHLFPEEKDSfVT8sHDL+letjtt1TVQOYKxnL2Lwt8Pe76e9rpA5LmPyDlyhNi+jRi7bwpWh2hoeC39GnqLngm1J7DhzgZ2x+zmYtpF8q16hlQZwtvH3y7xbvy0fvhoffjg9Ae8VvM1PjjzAQ2CGvDdQec17g89OcSi1otYfWs1U05M4dMWnzLxyERah7dm7MGxdCnbhdR6A6gtc0W5fZS4G39a7k7pApYC5x+SexCOPAP6U6fIDPAhoP5AZFdXlOjmCG9OvlXG7OtfFQo0IJbVe5L7hACjDL+ao1HGHIIHB3B9cABXoE9wbe51+PXTcq1SXhg9P6heIH4XZ4u/yXwEWbFixEnKDRTXlhE0bTOPR7yGLTOzaAKlkpBPZ6Lx9WW052iupl0lLi+u2D1eqzkBg6cngXNmkZH4CENKIoKHGzcdicy7+R7pBjE14puYnXxU9QVcbu+Crp+Dy2/7FfxZlPUsy+aum/n6+tecSTyDp9qTwVUG0ySkiViV5I9GrRN/OcFX68uBxweY0WQGF1IulDDnrONfhyj33y6HKyEhISEhISEh8fdGEhAk/m0yjZnsfLjTaduqG6t4odwLhLqFAqJp3NB9Q0nUF+XxH084zrTa79BFXRmh+hQE7wjyT54WvRB+xqVhQzx9Qmid5kXr+svId1NgwEyaMYPZFz+haWhTnivTGblMTpoxgzRDGo0cUWS89SW4uuLduzdyqwa/NCVra81HJVORPGYc5gcPCu+hDA8n+JM5JIwdh/yjSUy+PqtQPBhVYxSRHpH8GPsjn1/6nMbBjfmyzZd8cv4TVHIV8fnxzGk+h88ufFZo+lY3oC4jqo3gwzMfkpCfgIfaA41cg9FqLLY5fxYHjsKTaKPNSFxeHAtbLWT5ddFnQCEoGHXmfXa2WUZoXpJ4quxwwI0tUHcYnP6i5KSRTSEnEWOcGpmHB4Y7DzD1fhO1Wovs8gqwGEAmxx7dDVP4ADLuPkSn1JFvKR6qbrFb+FF/nUpBnbEM24fi4EcIjw6B0gW7bzW87RbqR3hx7nFJo75qIR5oZWKuf5Oy3gwqV4By4z7wigRBBo+OQFgDSLkBMgXqED8i162i4NwZCi7dQB0ehGu7digDAxFc3AjDjWXtlpFpzMRoNZJhyKSMZ1mCdYG4qd3IMeXwesxc7mfdxxxXMtLiQW4shlpv49LsTfAMd/pZ/KdQyBREeUQxteFU8sx5KAQF3v9GRMQfgZ/Wj4l1J/LllS9Z0GoBW+9t5UzyGVyVrvSJ7kOXMl3wdfH9r6xNQkJCQkJCQkLifwdJQJD4t0nVp5a6ITbbzYVh8GabmTW31xQTDwAW1JxBhX13efzdHBxmcbPn0qABIZ/NI/GtSfiMGIHDbCZl1ixs2dkIajWuLzyP/8vDSMJG/cD6lPMsx4Y7GziXfI536r9DVUUE2W++j65pUzRVKpPx1TIs8fEISiXuXTqjeuEFrCkpKEOCkelcMcfHY3nyhORp0/AZMYInPlqyY7MBGFR5EJnGTJZcXVK45gspF/DWePNZy894nPOYAksBlbwq8U79d7A77ChlSq6lX+OjMx/RIrQFUR5RuKvdqe1fGx+N85SOp6jlRdEamYZMrqdd50LKBbpEdeFY/DEsdgvn0y4T6lcRKnSCaxvh7h7o/Ck0mQAXloMpT8zrr/w8VO+DTeGN0p5H2cWTkeljQUjGGtYFe0BHBEsuDpTk7D9J1sw3UX09F2OSsdialDIlaoWaHHMWefICdmbepV+buVgibuMwWcjec5j8Twcyb9M2Rm+/x/WEIhPIioFuLO7ojp/+NAdH1cPTkYv2ypc8GbSF63mxWOxWqvtWxzcnEXeFBhq8Ah6hqDxAFRiA53OdQZCLvhhAviWfSymXmHV2FvH58cgEGS1CWzCp3iTc1GLJQ61CS3mv8oUeEr+krEdZtMG1xKiN/xG0Ci1ahfa/ugalXEnLsJZEukey5tYamoU0Y0iVIXhqPPHV+KJRan57EgkJCQkJCQmJ/2vvvsOjqL4Gjn+3Zze9N5JACEWq1NC7UhRFUbFSRCkigghSFAFFQEBAsOFPBQuCiggoICC9l0gvgUAoIb33zZZ5/8jLwpqEoKJYzud5eDRz7965M3PZMGfunCv+9SSAIH43N33Z96iv56IpvenIKs5iVdwqp7InovpQb/tlMj75zGl74b592DIzCf9iEQVbt5M2f76jTDGbyVv2DbYriZhe7kt0cDRDNg4huySbaW2mEZMSQzvf6mSaizE1aUzagmtP5RWLhZyVq7DqNBhXLuZY4iHSSzKp714L77MpmKfORRceht2lNBmeVq2lWVAzhm8eXua4Mosz+fLUlwSbgvni1Bd8cfILpredzsKjCzmTdYYOYR0Y13wcX8d+zbr4dfib/BlQdwCBpgAa+tbnSMaxMm028GtAbFas4+cIzwhWxq2kU3gnOoV3crwmkVCUDi2HlQYKds4trbx2DNS+F57ZdG2ZQksxWa4+uOk9Mf44qPR1gf+nN3pj6fo/Lr32ASXnSrfrQkOJ1+U4Zl5cNaDeANacW8P9kfcw9cxXDGv4PPlbj5C/fTvmU4OoEccAAGhZSURBVKewXLyI2tOToOR9LGqSQ1qXRiTnWwl00+Kfcwz/lQNAY6B6ny/JO/4tqyLqM2PHi9gVu2MfT9Z+gmfbjcLn+ifcLmVzDJxMP8mwTcMcP9sVO1sub+FM1hk+6/YZga6B6DV6nq77NAGmAAJMASTmJ7L63GrHKwzP1H8G098oePB34qpzpZZPLYY0HMKKuBV8c+YbglyD6Fe3H1U9quJh+I8tKyuEEEIIIcqQAIL43XyNvoS4hpSZWQBQz68e3i7X3uO22p1vTIeFPETiC0+U26757Fns2TlkfFZ+voDCHTvxH/40S7LWML3tdH6+9DP5Jfl0rdqV7OQ0QqZPRm3PJ2JsT1CpsXvWJvO7nyhMTuPiIy0ZufkpSuzXprc38mnAGx/Oxp5RjJ+pKgaNgVretfgl5ZcKj33LpS3MbDeTL059QYm9hOn7pzOy8Ug+PvYx91S7hxFbRjiW6csyZzF+53h6RfViepupjNw+hjNZZxxt1fSuydA7hzJ2e2mQoIpbFWp712ZK6ynsS9rH2B1jHeevUUhLOPAFHFvu3CG/GrBjNlzcAx4hFNS4m4MB4XTZ+4VT8ACAoix0Pz9H0Ii3uPTCK2gDA6ny4XtU8YKtHrMpVms5bc6gSG/iYu5FLuddxtvoz8AGgyiyFfNVwDEy71fR+cm+3FHohXrxclRph/Hb/zZ+ag136N2hJP9ajgaAokwuR3Vg2s7RZc7ll6eX0Dw4mo7hHSs835lFmcw8MLPcsiv5VziVeYpA10ByzbkkFSSxL2kfl/MuU82zGmObjeVI2hEa+jekqkfVCvfxb2Wz20gvTkdRFExa0w0DAXHZcfRd19eRA+Fo+lE2XNzAy81epneN3hJ8EUIIIYT4j5MAgvjdAkwBvNv5XZ7Z8AyZxdeS3oW4hvBW27ccAQRPgyd3V72blXErMWqNNA1ojCY3C3tBBYn/APOFC6gNBmwVlBfHn2edeR1LTy/lvc7vUcvujyY5G6PRBf3llah2z7tWWaXGv/3LJNR6nBE7nsZitzi1dSjzKF95bGdY2AMYVXpeaPQCGy9udAQAynP9E3QoXY3C3+jPk3c8yftH3i/3syvjVvJkrcdYeOco0g0mkvOT8HANJC7nHON3jCevJI/Wwa0Y1XQUg38e4nhqflUVtypEmcJQ7nwSVXEupJwAzyrQpD9knoOj3/x/5yykRDQjylaC6sL2Mv0AID8VlwgfIj6chS4iEu2Jj1DFfILL/2c7DA1tQmL3aVzgAkMaDmFN/BpcNC58fPxjRxMb2Ei4ezgfzF6AOuEX2A/YbVCc7bwvnYkSrwiWnCqbvPGq/x37H40DG+Np8Cy3vNhW7DRD49f2Je2jZXBLVp9bzVsH3nJszyzOJCYlhqmtp9IxvKPTayL/VoqikGXOAqV0lY8VZ1bw1emvyC3JpWlgU0Y1HUWkZ6TzKiiUzhSatGtSmQSKALMPzqZDWAcJIFQgvSidi7kX2Ze0Dz+jHy2CWxBgCihzjoUQQggh/ukkgCD+ED+jHx90+YC4rDgu512mpk9NanrXJNQt1FHHRevCC/UH81RIezwLsjC5h6DNLkGl06FYLOW2qw8JwZabW24ZgMrbi4LLBfiZ/AjNUpE1YiiKzUa1t4Y6Bw8AFDvas99xKrIOVT2qklaU5ljW8arvE9byZK3HWXLha/RaFx6r/Rjuenc+P/l5uftvEdyCY+nXXkV4qMZD+Bv98DB4EJ8TX2G/Y9IO83h6En7VO1H72I/YfKoT4htOoybjMKg0eF3YA78s5eW6A5l14lPSitJQoaJdaBvGNRpF0Df9IOcyNHgY6twHoc3g7AY4sgzcgyi6oyfJdXsy9MA0ljV9tcJ+AGgKLmGyxqP8shrVsa+dC6/EEPLDS0TfNYHB215iboe5PL/5+TJtXMq7xP9OLeLFWk/hU8FqEEUNH2VDxmGSC1Mr7Et6UToWW/ljAUCj0uBp8CTHnFNueahbKOlF6cyNmVtu+Vv736J5UHOC3YIr3Me/QUpBCpsubWL5meUMqDeAb2K/4XDaYUf5vuR9PL7mcb7s8SX1/Oo5fTbHnMPJzJPltmtX7BxPP06Ye9if2f1/pJSCFEZsGeGUd0Oj0jCr3SzaVmkrQQQhhBBC/KtIAEH8bplFmUzZM4XNlzfj6+KLr9GXZbHLMNvMLLtnGZFekaUVzfn4XdyH/+r/f3+95wLsBVl43teD7O9WlWlXGxiIzkuLsVFDCrbvLFOu8fUlxcNOkbWIN2uPxjJqMpYrV/Ab3B/tyUVlO+oVQXK3aeh1ajpHdCbMPQyNSsP8X+Y7Xr/QqDSkkceS2KXo1DruqXYPT9zxBN2rdmfdhXVOzRm1Rp6q8xTjd44HYEzTMVzMu8iL20bxeqvXb3jOXDR6qPcQFKRDZHs0lw8QtPl1gn5Vr1uVpjRu+Rx5vrXQ2tV4aT1wO7UeUv4/aLH/f6X/VakgshP2HrM5YzDw0fmVxMbMpG/dvlj0ptLVGkryKZdbEIpfbVSLu5VfnnKcEEVDQ/+GHEg5UOExrYtfR5fwLrR4dCmGb54C87XAj7VaO87U6caPccup51eP/cn7y22jUUCjGz7d9jP60a9OP+Yfml+mTKPS0K5KO9KK0pxeTbleniWPLHPWvzqAkFKQwnObnuNM1hk89B5o1Bqn4MFVNsXGW/vfYkGnBXi5eDm2V5QQ9Sq73X7D8v+iElsJi04sKpO006bYGL19ND/0+oFwj9u72ocQQgghxK2kvt0dEP9cCfkJbL68GYCM4gzOZJ0h25xNkbWIuTFzyb9645oVj2rFwNJlB3t/Aqd/QO0VjN+DbXBr39apTV1oKOFzJqPfPpqgYY9jqBHlVK7x8sLwzlRmxP8PrUpLlNUHy6VLAGi9PSAv2bmT7sHEPzCfQcfeZX/yAap7VifUNZRQ11A+uusjannXAqBX9V6sPLuSblW7Ma/jPLRqLQsOL6B3zd5MazONen71qOJehd41ejO3w1zePfwuOeYcanrXRK1SE+UVxVN1niI2K5bGAY3LPV9alZaGvvXg5CrYOq00N0GzgXDdTdxVqoSD+J3/Bf1r8ynq9BBpj/bH7lWvbF1FgXObUK8bi4vOlW6R9/JknSf5/uz3TDu1CHObEeX2Ral9L1avaphRSl87qIC2IBV3vXuZae0BpgCGNxrOvI7zmN52On5GP+an76O4zyosd32Apc2bWB74jsvtJzBw9yvsTdpLs8BmuOvcy+5DreXZ+s/eMICgUWvoFdWLDlU6OG3XqXXM6ziPAFMAWvWN46EaleaG5eXJKs7ifPZ5TqSf4HLuZQrLmWHxd7EveZ8jt0ZN75ocST1SYd3DaYcpsBY4bfPQe1DDq0a59VWoqOdfr9yy/7LM4kxWnF1RbpldsbMrcddf3CMhhBBCiD+XzEAQv9vmS5srLNuWsI28klzcFAX2flB6o9v8WfjlczjzE3hWQad3JfjBalhfHEleUgJ5rmo8/QMxbHwBUo6jX/804WOnUGL1wXwuHk1EFFdC3Xkx9m3O58ZT16curnkWri48WBwbj/3OJqivSxqY3m4UH11cz8vNXmbF2RUUWgtJyE9ge8J2dGodo5uOxtfFl/TCNFwNblzIucDzm553PI3dnrCdO3zu4LWWr3E07SiuOlcyikpXOrg6E6GgpICDyQfZcHEDPi4+vNn6TcbtHFdmuv3Y5i/jUZBBod6Iyb82bJ0Bp36Ex5bBIudZAEpQQ0p8O1KwozQAYE1MJGnuR1R5sB+aA++UPeEunliBs9lnWRW3iqSCJGKzYjF3/QqDSlN6DQrSQO+Kre7jFHt0IPdILNZanoSptc4JD69jdQvgaOxRXm72Mt/EluZYqOVdixGNR/De4fdYcGgBAGHuYTx/5/OkFlsofmkBajc37EXLSJg/ErPNDMDcX+by4V0fMvvgbA6lHgJKb3Qntph4U09p/U3+vN76dVILUzmadhQvgxd1fOvgb/JHr9Hjofeo8DWHYNdgp6SeN1JgKaDAUkCRpYgJOydwNP0oUBoAeqjmQwxuOBg/o18lrYDFZiGrOAtU4G3wRqfR3dT+f4/8kny+P/u94+diWzGuOtcK6xs0BtSqa/HjAksBFruFiS0mMnDDwDJ5QoY0HIKPi8+t7/g/nM1uKzdnxFVXvyuEEEIIIf4tJIAgfrcb3RBp1BrIvgQJh66tAhDRGvb8/9KKe96DViPQ1utFpgaW55yiiaEmeQWp6O59H4+1wyHhANqfh6M1+aFt+xKpkaE88tMTqFAxu8FE6lxUMBk9uPpP9Jy1G/B7dB7qM6vAVjqVPce/Jt21tXlhywu80foNvo792nHzCrAmfg13R9xNdFA0/nZ/3o55m3ZV2qFRaTiSdoSM4gxOZZ5i0u5J3BN5D9P3TyfULZReUb2Y2GIinlo3zuSeY8OBDUDpE8mZB2cyrc00jqcf53j6cULcQngw6gHyirMYd+JT1Co1fap2pWHwh/j/8GLprIkhu+HoMpTiXKx+rTBnqbgyfHxp4OX/Fe7ei23IHDSUDSDkNOnL5MMLsGFj2J3DOJ9zHm/UqGM+hdRY6DoNfCKxaVzIPpdC7idf4j9hLJkmKKnXG/3Rr8u0aQ+qz5GiFDKKM8gtyaVRQCMOpR5iZOORjNk+hnzLtVcjLuddZvzO8SzpvAidzYYlIQGXdm04VhjnqHMm6ww6tY72VdrzSvQrjpt+X6PvjQfadbxdvPF28aaWTy2n7ZnFmSw6tohxzcYxcddEp+UoDRoDM9rOIMAUcMO2rTYrF/Iu8O6hd2lfpT2fHv+UC7kXrpUrVpbFLsNN58bQO4ei1+grbCsxP5Glp5fy4/kfUaGiZ/We9KnVhxC3kJs+1t9ChcpphsXJjJM81/C5CuvfX/1+fAylAYFLeZeYc3AOWy5voUlgEz7o8gFrzq/hcOph/E3+PFv/WWr71sZdX3b2yH+dUWekpndNp1VVrhcdHP0X90gIIYQQ4s8lAQTxu3UJ78KHRz4st6xHWGe8Yr4AVBByJ1zaU3pTf90NMZYC2Psh7o1eovv3CZjXfopit5PTpTP25+ZRaMjGXpxFvs7A55fWE5hg4eO7Pya0RIf64+/J+XY5xhdewBQdTeG+fShmM0nzFhE8/DN0+96ElONg9OKzwwuI8ooiuSDZKXhw1YaLG+hatSs+Rh9eiX6FHVd2YLVbGdV0FEXWImYfmM35nPM0DWzKsIalN+cr41bS0L8hRo2xzFTx+Jx4hm0aRgO/BkR6RfJs3QG8tG00RzKOO+rsTdpLM/9GzOg5l4Bj35B9z2y0TQdB7GWSXh6HNS2t7ElVFOzasjdx5hp3cdjdiyMnS/vxavqrvNx0ND2LbbgdKF35IKfBw8TbC/jizJekm7NoNaQp3fwMjN05npcb9qOetRj9qdWO66NUaU5hz7m8v2scAPN/mc/8TvNJLkgmJjXGKXhwlV2x89HJTxnVuydFX3yNevCTfHNmgqO8Y1hHjqcfJ8ucxf6k/dwfdT869a15Kp9RlMHyuOUkFyWzoNMCdlzZ4VjGsVVIK4JdK899cD7nPI+teQyNWkO3qt2cggfXW3J6CQ/XerjCYEBSfhL9fupHcsG112k+Pf4p6+LX8Vm3zyrMw5BjznHMnvAweOBl8Kq0z1e56l15pNYj7EveB5Rei3Xx63ih0Qtl8kZU86jGM/WfwaA1kJSfRP91/UkrKh1vB5IPcCT1CF2rdmVex3n4m/wlcHADPi4+jG0+loHrB5Ypq+1T+z+5bKgQQggh/t0kgCB+tyDXIPrV7cdnJz5z2h5gCmBo1Z4Yv3wEvKvC/e/BwU9Boy9N+nc1iBAWTYmmCgn9B2FNvZahP/+n9RTu3oN20Rx6x0x0LImoQkW/8LtxSc4g/tvlAKR/9BFVFszHtX17XILd0XqYsBSosLd7F52fCY2Lnv3J+3mu4XOsi7+WDNGoNXJv5L20CG4BlCbp++7Md3wfd20a+I/nf6RJYBM+vvtjfI2+pBSkYLabaRzYmCENh/Dd2e+4kn+Fmt41yz0/R9OPciLjBH1q9HYKHlx1IO0QRyK60tmnGvOOLWTVuR9Y2+jD8oMHgNbfH7V3IJZey1Ff3oRKpya1Wiv2Facwef80p7rzD71LpxZv4AXkNX+Gpap83ttybRWFX1J/4Yv4r5nVbhbHs87i1vYFAtu+SEl+CkUaDccKk2iefZF328/mTN4lVCoVK86uoGVwS05mlJ+pH+B41kmUpl0I6NiJjwp+JrckFy+DF71r9CbKK4rZB2fzQZcP2HhxI0N+HoKXwYtBDQYR4haCVqXFXe/+u6b6J+aXJsPceWUnexL30CK4Bf4mf2IzY/ni5Bd82/Nbgqk4iJBbksvsg7MpsZdQxVTFkVyzPEXWIgqt5edCsCt2frrwk1Pw4KqkgiR+vvgzT9Z5EpVK5fSZc9nneHPfm8SkxADQ0K8hr7Z8lSivqEpzO1zVKKARTQObcjDlIAA/nP+BXlG9+OiujziYfJD04nQ6hXeitndtAl0DAdibvNcRPLiqxF7CD+d/IN+Sz7Q208rsRzir51uPT+7+hLcOvMWZrDO4aFzoFdWLgfUH4m/yv93dE0IIIYS4pSSAIH43T4Mnz9R7hk5hnfjq1Fdkm7PpEtaB9voAgr8fBtZiyDwH1hKUR75AlXwManSF5GNk9FhIoVcNXNatcwoeXGXPzUW3ajOL+39Maklm6ZNqxYYpbhMFp0pvvlwaNsR34EB0viZMmhLUuydAfgoYvbE3egbFqze6/DQMGgM6jY5iW2m2hBDXEF5r+RrfnvmWl7e/TKhbKBOiJzgFD6A0QPJE7Se4kn+F5WeX42f0o0lAE5bFLuOtA28xp/0cGgc2Ll3K8sgH5Z6jTmEd2ZW0r8JzuDRhE/XqDWXj9pHoNDo0Pt64d+lE3s9l80sEDB+Ibs8krDWfpMjUjtRaYTyxfVC5swGKbcWkYyfUPYT0pv14b90TZerkmHP47MRntAhuQZ+fnyXENYRHaz8KFpgZM4uNLabh+8tXbNDksP7/k2UWWgtv+CqAv8kfW70ajD/6Dm1C2/B2+NsUWYv48fyP/Hj+R56p/wz5lnxUKhXpRencE3kPZ7POMidmDjnmHNqGtqVPrT6Euoc6vaNfmetfg7ApNqfkdWqVGqPWeMPPF1gK2Ju0F4AscxZBpl+vi3GNQWPAqCm/vRxzDmvj11b42R/jf6RnVE/H7ILUglRyLbk8te4pCizXkhoeST/CU2ufYvl9y4nwiLhh36/yN/kzs91MjqQdYdnpZdgUG9FB0UR6RtIypGWZ+la7lS2XtlTYXkxKDAWWAtz0bje1//8qk85E8+Dm/O+u/1FoLUSj1uDr4nvDV1yEEEIIIf6pJIAg/hAvFy8auzSmnl89rHYrptRY+F+H0kLfKGg+CJtrGMVpV1CZWqDv+hBnshXGrEmgfZUrPPLzpgrbtmzfzfnOoUw6PReAz1u/hf7YcgpNj2Ns3Bifp56kYMdWVH2iyQ6tg/nJZegsxQSf+BH1L/9DyU/As8FD3Ff9Pg6lHqJ1SGsu5l5kXPPS9+SvPnl9o9UbfHbSeRaFh96DyS0nM2n3JFIKUxzbF6kWManlJEpsJYzaNoqvenyFSqXi0VqPsix2mVMb3gZvhtcdwCsHZlR4jDa7jQyVwqO1+nBfaHt8fxiG0ncILlERZCxdgT0nB321qgS8MARTyR5Uh35EF/sjOv9aXKk5p9zgwVU6twC4dw57E3dXWGd34m561+yN1W7lUt4lZh6YySO1HmFwg8HorGasJh9eqjcQF707P57/kZ1XdvJ2+7dZGbey3PYGNRiE3uTOvuR97Ena49j+eO3HeaDGA3x9+msWHl1IhEcEY5uNJackh0m7Jznqnc85z3dnv2NJjyXXlgG9CYGmQMLcw7icd7lMWcewjpUmAFShwqAxUGwrdiQUDHYNJqkgqUzdh2o8VGESRY1Kg0FjqHA/LhoXR66CuKw4Pjn2CR4GD6fgwVXFtmKWnFrC6Kajb/pm1N/kT5eILrQKaYVdsd/w5l+j0hBoCqyw3NvFuzSXibgpPkYffJBEk0IIIYT4d5NlHMUtodfoMVnNoHctfVWh+SC4bz54RaDe8Sauce9gsJ0n0eLGI5+f4URiLgU2wK3iGxy1mxs5tms3yGqApMOY6lTH99lnSJn9NsqIp4kPiGBT4WUm/DKHl46+y7Kq9UkcvIWSJn2J0So8XvtxLuVcom2VtrQKbsXZ7LOO4EGERwTF9uIyU9IfqPEAn534zCl4AKVPt6funcpjtR/DarcSmxXLxF0T8Tf5M6PtDNpXaU9D/4Y8W/9ZvuzyIRE7FnBXQLMKj/HBqF6EoOG5xHjCvxuGve6zWCyuuLVrTdUvPyXypzVUmT8HU5Q/mkPXzXJIi8U782KFN4A+Lj74ZlyALdOwWovLrQM4Vpu43vIzy+kc3pnVJSlMMp9HrXVhQvQEfuj1A591+4wQtxBeiX7FaWq9ChX96/ancUBjAkwBzOswz/HUv3VIa4Ldghm7fSy/pP5CtjmbI2lHGLl1JOlF6XQI6+C0/3xLPm/HvH1tGdCb4G/y54POHxDu7ryaQ5OAJoxrPq7Sp+g+Lj70iurl+Pndw+8yqeUkqnlWczrGHtV6MLD+QAza8oMEHgYPnrij7GyPq56s8yTuendSClIYtHEQ/iZ/xyoP5dmfvP83nYerTDpTpcesUql4qOZDFZb3r9v/plabEEIIIYQQ/x0yA0HcGnkpsH5C6XKAPWaDVzgcXwEHPubq297q4lx+yKpPvrk0Q/7a2Cz6PtgHtm0rt0nl0Z58n7rc8fOh7DPUD2uBNmkLBQUN0H8yhxxVCdP2T+dExglHvWPpx1jmVZ1Z7WZSmJ1DZnEmU9tMJbM4k5ebvczMgzMddRsFNGLrpa20CG7hmMIO0DigMZ+f+LzcfpXYS0gtSsXf6E9aYRpq1Cw4tAAfFx86hnUk3COcQ6mHaOZahfD4bXS78xG+ca9CQl6CUzs1PaOI9qyF996FkHqKogYTSXx9Hpb4C6UVdDp8B/RH7eaOSinEq8EANEcXOT7vv3M+s+6ZzjM7xlBiL3Fs16q1TGrxGl56XxT3YFr4Nazwst3pfydnMp0zyNsVO5dyL3EiN56Xm73seF/eqDXyfdz3TNo9iY5hHZnXYR7JhclYbVYa+DfAQ+9BUkES7np3mgU1Y+X9K7mSfwVPvSd9f+pb7v4/PvYx09tOZ+vlrU7bdyTsILckFze9G9bsbJSiYtCo0fr5oVKXH/eM8IxgcbfFpBWlkVaURohrCH5Gv5tavlGv0fN0vafZk7SHi7kXSS5I5rXdr/F0vaep7VMbAF8XX3xdfHE33DipYNPAprQKacXuX838aBPShjv97wRKczb0iOxB5/DOxOfEV9jWnz0V/urrO9P3TXcKJt0VcVeZwI4QQgghhBASQBB/nM0CB/4Hx///Zr/5YDDnwIGPnaoV+9Zm75VrN7pp+Wb2q8KIfvAhzCuWO9XVd2xHfJQb8Ueu3VwtPreSHm3HEbBjHkUt72dpylpCC0MdwYPqXtW5O+JuXHWunM48zdbL20jMT6Rvnb4UWYvQqrWoVCru9L/TcXNntVtJK0mjeXBzqlx3k2+1W8t9On9Vfkk+LloX6vnV49PjpSsdZBZn8t3Z7xx1QkxBtKzSjOAfXuTTRz5jTfovrD7/AxqVht7V76NLQDPctN4obUZjyS7GGhuH39MD0QYEkL9rF1lffknGR/8j8NVXyP7mB5QubfG492t0mbtRleRD7Xuo4xnJR3ctZGvCNuJz4on0jKR5UHNSci5A3ApUvpH4o+Wh6vez/Nwqp2Nw0bjwTP1nmLxncpnj83LxYnyz8fiaruUWSC1M5d1Dpctw7rqyix0JO6jqWZUJ0ROYEzPHkbxPq9byaK1Heab+MzQLasbx9OPlTtGH0oSENrutzHaVSoWLBQoPHyZ15iyKDh9G6+uLT/9+eNx3Hzr/8pPT+Zv8f3fiumC3YD65+xOOpR9jXfw6fF18aRLQhBC3EDwMHjfdjr/Jnzdbv8nZ7LMsP7O89El/jYeI8o5yPNE36oycyTzD6rjVjIsex9aEreW21a9uP1ILUimwFBBgCnBKvlgeu2InuSCZw6mHOZV5ijq+dWjo35Bg1+ByP+umd+O+yPtoFdKKfUn7KLQU0iK4BYGugTcVeBFCCCGEEP8tEkAQf1x+Muy7bjlHFRBXNreBviCFCE8NO67bNmHLZd7q8ggdH76PgnXrwGbDrVtXYrQJjDv2BlC6QkKAKYDUwlRmXFjN9K7TOWNOR6VSsenSJjQqDa+2eJUiaxGrz60mx5xDdHA0ncI7kVeSx8itIzmfcx4onao+uuloHoh6gO/jvmd34m7GNB3Dm/ve5I1Wb7D58mbWX1hPviWfENeQCrPxV/eqjo+LDznmnArzELjojFxuN5Iicy7uJl/uD27LAwVmVFoD3n7RXCw0sv1yLve45HJl+AvYsrP///yp8OjZk+ApU0iaOJGsJUvw6tOH1Blvkf6JgaorvqLYQ8WBjBOM/uF+FEWhaVBTwtzCeKz2Y4zaOoppdZ/BcHgJKApe+z5kePcZtG02gU8vrCGzOJPmgc24p/q9vPPLO6QXpTv1213nTlZxFmsz13J/1P2Om2ezzUyrgEb0i+iOR1Eeaq0BjUcVZsd+6QgeQGnw5ctTX2LSmhjccHCl79GXV96nZh/0py9y8emBjlU7rGlppM6aTeHBgwS/+SZan1v/vnmgayCBroF0Du9c6c36jfiZ/PAz+dEsqBkqVE7HmFSQxPObnne8HnMu+xx96/Tl85POM14eqfkIsZmxDNs0jABTAJNbTqZpYFOMuooTQp7JPMPT658mz5Ln2Oah92BRt0UVrhbiqnfFVe9608kahRBCCCHEf5fkQBB/nM0C5ms3LKh1YDWXqaY5t4Gn6hu5/r5MUWDilgTO+Op5s+llFrTNJzHCjSyjnSDXID5tNJNPvIYz2/Akn7RewDMNhpLo6sXRrFNEeUYBMLbZWAwaA54GT7pW7Ypeo2dl3EqSC5IZ8vMQR/AASmcJTNg5gbsi7qKKWxUAMoozaBzQmOGbh5NZnMnopqPxcfFhZJOR5R5ux7COlNhKmNB8AkfSjlR4WlqFtKb3lmFMj/0StbUI/8964rv3A3y8I7FmXeLldVfoGqzl8rODrgUP/v+k5K5ejSU1BWOTJpRcuozWv3TlA42nJyeLE7lrfV9G7ZuCXbGjoHAg+QAr4lZwIfcCLzZ5kRC18dpymYqCz9qxdNr4Fu8Za/F5cDeGVb0Xs9VcZvq8Vq3llRav8MXJL5h5cCYXci84ynwUFePwo8aXjxL4TX/8v3oMn8X3MimgHY9H9S5z/F+c+oL0onR8DD4Vrtzg6+JLocU5/4SXwYthEU+Q8sbUa8dwnfwtW8m/cpEreVcosZWUKb8V/kjw4HpatbZMgORE+gmn3BofHf2IYlsx73d+n5GNRzKh+QTe7/w+eo2e+YfmA6WzP57f/DwXcy9WuK/UwlRGbBnhFDyA0iUqX9zyImmF5S8PKoQQQgghxM2SAIL447Qu4P7/y955hoFGB3fcW7ae1UyV4x8yt1d19JprQ69ddQ9q6tVYrMW0CW3D5L2TCfcI54t6s6i6IxZT7dqcqq7jRHE8e9MOMHH3REx6EyHuIYxuMpo7A+7E0+BJemE6MSkx9K/bnyktp3Ao9VC5U+dreddCURQmtZzES01eoqF/Q4bdOYz5neajVWvZcnkLuSW5+Lr4Mrv9bOr41gFKZ0KMajKKMU3HcCDpAH1/6kvLkJZU9ahaZh99avXhVOYpiqxFPFLrEfxzU6HbWyj3zMFqM7K7IILhrQOw79uBUlx+ksOspcvw6tULQ2QklsTSmRDe48ew4NKXjiUpr+dv9CelMIWBGwaSaissU05WPJ7bZuO3fiIl5hwWHFrAm23eZETjEXSv1p2hDYfy8V0fsypulSOx36ITiyj+/ySMrmmxuG2dURowuqo4B8O3fXmx+oNlzkORtYhCS+myjzPbzUSvdn6XX6vWMrX1VLwMXrQNbUsDvwYMbzScZfcsw8WsUHL+PBXJ2LeTl7a9xL6kfZhtZYNVf2fX59q46pvYb3h+8/OsPreahv4NGb55OF+e+tKpjl2x8+HRDyt8HSSzOLPCGTOX8i6RZc76450XQgghhBD/afIKg/jj3IOhwyuwfjz0fAe+HwKPLkEJa4Eq6TD2mvdh94hEXZSMa/wG7m4ylEZPRlHkpSbXloNRp8aac4m3G7zAMVs+wxoOo642AHclnvR7mnCSJD4//SVnss4Q7BpMn1p9sNgteOg92J24myWnlpBRnMEdPnfQv15/9iTuKV1tIetsma7W9a3LoAaDeGXXK2Sbsx3bO4V1okdkD3xdfGlXpR0/XfiJen71aBUUzXtNJ2DNT0adn4LfyU3YjdV4stbDuGoNfBP7DRNbTCSlIIX1F9dj0pnoGtEVV50rgzYO4sEaD1LXswbq4ytB74otqCUJGVoWH83lw+h0ss9XnEDPlp6O2t0Nn759ydu6BdP7s/jZI5Vu7t2JSf3FKUeDRqVhVJNRjmnwe3LiCK3SDHXCgbINhzTCbvKlX91+2BQbifmJ1POtR3Wv6gzcMBCbci0nQVJ+EmabGZeSQlRbppXfUbsN5dAXjG82lsGbhjo269Q6XLQuqFQqGvg1YMX9K1hzfg3H049T26c23at1R4UKN70bM9vNxK7YcdW5km/Jx0waqNVgt1cw5lzJK8njhc0vsKrXKsI9wsuv9zcU5h5W7na7YifHnENiQaLTNbje6czTFFoKcdW5limrLJDyZ83WqEiOOYes4iyyzdm4693xdvGudDlNIYQQQgjx9yYBBPGHFFmLyCjKoLhaC0yDfibg+Cq0Ne8mN+sCtnvm45KWR9YXyyg+vRddeBV8nv6cy1ozcbo4pm6Z5nia6q5z5/XoV4jyiiLYDvojS1Au7eVg++cYu22CY3/nc84zff905naYy8fHP+bniz87yk5lnmLs9rFMbjmZQ6mHSpfgu+zc30ENBjF+x/gyyzZuvryZUPdQooOieeeXd4jNiqVZQBN8T/6AyWoFN38weEKtbqh3v0NE/DaG3vMxKZfcUX76Gr/zF2g2/kWOemQT4hbC7sTdvNf5PdxVWvw3vQEnVgKgbjWSA15PM7e7K4a1r2Ks81SF51YXEYHGz4+8qCB2hWXx2ZX3SLicwL2R9/JZ98/4OvZrLuRcoLZPbbpW7cqXp77kVOYpAObHfkmzu96k2ppxkHryWqP+tbnY9XWe2jqCLHMWRq2RSS0nUWwtZtimYU43ri1DWjKo/iDSCtPIU2nwqdoKU8oJKGdZSGPGebx0rujUOiz20hkKD9R4AC+DF1fyrmC2mTFqjQyuPxirYkWv0Zf7mkCuOZclp5ZQmJvJQ506UPTz5rInRqPBUieSS79cAmDnlZ087vF4hefx76ZDWAfmxczDqljLlPWv25/LuZfL+VSpULdQXDQu5Zb5uviiVWux2su2q1fr8Tb8dUkRUwpTeGPPG2xLuLbCSn2/+sxqP4tQt9C/rB9CCCGEEOLWkgCC+N1SClN499C7/Hj+R6x2K246NwbWeIQHI+4jTa3gfuICyc+9BLbSm1JrejppTX/B3D2a8ZtecWorz5LHqJ3j+bb7FxhsCuycQ8qjn/PWwdlO9dx17lT3ro6H3sMpeHC9hUcXMrjBYOr51WPxicWOm+IqblVIKkgqEzy46vuz33Nf9fvoVrUbLzd7mRp2DUZ9IHz1sHOOByh9TcPuQcFb147D3HcwrX9cRWzuBZq6R+BfVIDf3g/Rn9viqKMqTONut0TcbF5weT/GhiPQ+PlhS3dOZAjgP3IEC0rWs2TXMqftuxN3M7TuIFw0LnSv2p2qnlVRFAWLzYIKFQoKOrWOGHMaxt4LMRRmYsu+iMm3JrvzzjN172uO6exF1iK+PfMt45qNY1b7WWhVWo6lH8PL4EWBpYARW0aQW5KLRqWha1hnXnzsS4K+GVDmfOQF1iWtJAej1oilxELn8M4MqDuA+Yfms+LsCsw2M54GTwY3GMy91e7FoDWUew0SCxL54MgHmLQm7h86B92p01iuXDctX6XCNHUC8xOvrXZxOa/iG+6/o0BTIO90eodRW0c5zRroWrUr90beS6Y5k7m/zC13FZDBDQZXuIykr9GXAXUH8L9j/ytT9myDZx0rQPzZCkoKmLV/llPwAEqXVx25ZSQfdvkQX6NvBZ8WQgghhBB/ZxJAEL9LVnEWr+x8hX1J+xzb8i35vHPyUyw6Aw8HdCVr0gxH8EAXFoZ93mtstJ7k+IlF5bapoPD56WW8FtgWA5Cj1ZFZnAmASWvixSYv4mnwJDYzlnM553iv83ssO72MHVd2OLWTVJCEu94dFSqmtp7K1H1TKbAU4OPiQ1JBUoXHlG/JJ7UwlZVxK2liDMJD5YJVG4AmuDnqC9etKqEzYr//U1LmLnFuwG6naMs2GkUkoDrwMZhzy+zDFtyO1HGvwOCn8PSrgW7Xq0QseIfEN9+l+PhxANQeHvi/MIyT1XTU1NxBUGIQyQXJADQKaMSLjUeittqx2q0cST9CuEc4c3+ZS3RwNI/WfhSr3UqRtYj18eupWr8qg3e9xIhGI3Apuky+3Uyb0Dasv7CeYlsxfev0JdAUyKCNgxxBhb51+qIoCu8fef9avxUbay9tIKHgCvO7TMR3zctO5yOzRicCXYN4u/3buGhdyCvJY9q+aU7X5sHgbrSwRmDevI08dx8MkZFoAwJQ66/lRvjh3A8AFFoLGXLyNWbMHYNvfCbafUexB/ri0b07sy8uYkPiVsdnmgc1r/Ca/lVyzDmU2Eow6Uzlvl5wPRetCy2CW7Dq/lWcyTpDbkkudXzr4G/yx8vghUlnYma7mby2+zWKrEVAab6IUU1GUdundoXtGrVGnqzzJCFuIXx45ENSClMIcg1iWMNhtA9rX2HQ5lbLKM5g46WN5ZadzjxNRlGGBBCEEEIIIf6hJIAgfpf0onSn4MH1Fp1YzL3BXTA1aoBP7zGodXYyqtVk3MGpdAjrwKW80qnn9fzq8WitRzHpTKhVatKL0tmbuJcirQEDoP3/HJ9alZYZ7Waw8MhCTmSccOxHq9LyaotXUalUbE/Y7tiuQoVeo0ev0XMy4ySvt3odq2JFhQoXjQufnfis3H4HmgJJLUzlqWr3Enl+NzR8gouPD8f3iQdx7TkYdeZpFBcvVOGNSX53MQW7yibDs6SmktPjfrz2LChTpvjfgTqiEcHjn8dm0WKv+yrq7/ph2PQMYYOHYPN8BsViQaOHjCphfHrsXYqsRUxpNQVFUTDbzFzMvUhOSS7xRfFkm7Px0HugKAqvtXiNNfFrmLp3KjbFRteqXRkbPZaPjn7Ecw2fI9A1kC9Pfkl6UTr1/Ooxr+M81l9YTzXPakzZM8Wpn3V86zBtX/n5Do5mnCC5ztP4al1KX2XwrkZq92msSD3IY/5P8vru1zmZeZJ3Or7jFDyYUuclGq2Pp3jJELIUhSxAZTAQ8tZbuLZvh8ZYujRh7nVBl9TCVJ4+NIYq7lWI6hJFoSWNB7V1+CFxg6NOsGuwI8nl7ZBVnMXRtKMsPLqQ1MJU6vjW4bmGzxHhEXHD5Rb1Gj2h7qGEupedzm/SmegU3on6/vW5kncFm2IjzD0MX6MvRm3FbULpMqW9a/SmXZV2WOwWdGpdhStg/FkKLAXYlQpyVwDpxenUpPwlJYUQQgghxN+bBBDE73KjaeNF1iIKVSVEdTKh2T8aa5s3cLmQxusZbTFE1Oek50mivKJoGdKSuTFzySjOAKCKexUmNJ+A3iWQtMe/Rudfm5reNanqUZX9iftpFNCI/nX7U2IvYdOlTWy7vI039r7B/E7znQIILUJa4Gf0o6CkgHp+9Xhp20sYNAa0ai0TW0wk1C2UK/lXyvT7uYZDaGOqgufhVehqP4TVxRvT3V1Ife8TlBILpjZt8Bo4gKLlG8j7YW25x26PbsD0058x6vGl+O14B82FHaB3pahBH7TNB6Fb1BU3IPnRL1idfpj77n4Dz+1vo931eulfxuCGFN43n2+TtlPVoyptQ9vioffgqbVPoVFrmNdxHq/ved1pJsUP53+gX91+hLmHMajBIPQaPS2CWjB592QG1B/Az5d+Zt4v8xz1E/IT2HRpE190/4KXt7/860NAp9aRW1J29sRVZ6x5+DyxDIvNzLmSbE4VXuCJen2Jz47nWMYxvA3eTv2r5lmNRgk6ir/8xqkdxWzmyosvEvnDD2iiqgOl0/hXnlvpVC8hL4GEvAQ6VulISkHp8ocqVLQNbcv46PEEugZW2Nc/U35JPl+e/JKPjn3k2JZSmMK2hG0s7LKQFiEtfnfbeo2eULfQ35UvQKVS/eVBg+u56dzQqDQVJoL0N/r/xT0SQgghhBC3igQQxO/ibag4m7oKFUZbCZrjX1DS4wsuvzKHkrg4AMyuJp7+aj4pxhJGbBmBgoK3wZvWoa3RqXXMi5nHzPZvsSR9P51c3Xi1xasUWYqwY2fJqSUsPb0Uo9ZI92rdmd9pPhN2TiAhL4HBDQaz8OhCAk2BjG4ymk2XNtG2SlsiPCIY3GAwHx39CLPNzNsH32Zqm6l8fPRjDqSUrlDgofdgeP1BdLKo8Ty9AXvTERRkWXjv9GKq3RPOvY8vp8icz5GCODINF+jWvi2ZH38CivM76rrq1dFFRXH+yGIeOTiVp+reR7M2Q7ED/q7BhKx4FoqyKL6jJ1szjjLz+EfsCopmSO/3qWX0R6V14WDeBV7bMYq0ojQAlsUuo1dUL5678zku5l5k9bnV5b6G8dmJz3i307u8uOVF3mz7JodSD7EvZR/Dmwznm9hvytS32C2kF6U7ZoNcT61So1Vpy03yBxDsForKoyoWawE1tS60cvHDoDWw6HjpqymF1kK8DF6O+k8E9USZVrYPACgK2d+vIGD0aFQqFeEe4dzhc4cjGeRVLhoXnqjzBOHu4XQI64BOo8Pb4I2b3q38dv8CmcWZ5eYbsCt2puyZwufdP8ff5E9qYSophSkk5ScR6hZKgCkAf9O/9ybax+hDj2o9+OH8D2XKGvo3lNcXhBBCCCH+wSSAIH4Xf2MgAaYAUgtTy5S1D22Hz8nV2Bo/R/L7y7AkJOBSpw6KxYI5Lg6301f4wG0HKpWKkY1HEmAMYNOlTeTYcnigxgNkm3Nw1btiV+x8evRTnm/8PE+sfcKRcC7fks+3Z77lYMpBxjUbx8nMk0R6RvJZt88oshax5NQS2oe1p/9P/THbzLzcdAyrun/J8czTKCV2ArNhsqE3xQ2exGy34Fpow/D9QUwDBpCxPZHsWa+SPusFrBYrW5K24+Pmz6hdoxzHdzi0K6M++ZCcGW9jPnMGlV6Py73dKHzyHvruH8FbbaeX1ks/So7eSHVFR/D6iahtFjK6TeOopz8zDpS+IrAreR+7kvfxXMPniPSMZPTuV8qcz5VxK5nRdgbVPKuVO2PA0a+0w/zv7v+RY85h/tH5hLqFciCpnGUc/1+2ORtPgyc55hyn7buu7KJzRGfWX1hf5jNeBi8iPCMIcg0qUxZgCiDENYRsczYWuwU/ox/pRen467ywpKRU2I+S8/EoVisqnY64rDiGNhzKwZSDrDm/hgJLAS1DWvJIrUdYcGgBU1tPJdIrssK2/kpnss6Um+gQSmd55JTkUGwtZuimoVzMvegoq+FVgwWdF/xrVyNw1bkysslIrHYrP134yXGOmgc1Z2rrqbKUoxBCCCHEP5gEEMTvolPrea/dOwzZ+rzjFQSA2t41Gd9wBK4/v0ZJ0ynYu+zFMn4ge7KPYFK50ERfHXtOIbEJsbzQ6AVOpp9k7sW5js/vuLKDSM9I5nWcxy+pvxDoFsgHRz4od437+Jx4Cq2FNAlowuQ9k5nZbiYqVJh0JsZsG0OJvYRAUyDtg5oTnp2Cf5ovya+/RUlCAiX/P3tAC5gBs06He7NoCmPjsM+dyLhjrzC51WQm755MFfcqvN3+bXQaHUfTjvL16a8543aR2QumYs5MxKq281XmdtbEvIhNsVFoK2b52eU8FPUQS08vJczFh37dp7EjaS9fXdrAmdgzZY4lqSCJbHN2hed7w4UNPFnnSccSieUpsZXw6fFPaeDfAABFUdCoNRXWX3N+DX3v6MuCw875Gn44/wNzOswhuSCZI2lHHNu9DF58dNdHBJnKBg/SCtNo6N8QtUpNgCkAFSpmtJ3BmG1jiC26RGTdOhTt3lNuP0wtolHrdACY7WbGbh9Ly5CWDLtzGAatgWNpxxi9bXSl79bfKpnFmVzJv8L6C+tRo6Zr1a6EuIXg7eK8DKJOrbtxQwqM3DrSKXgAcDb7LOO3j2d+p/l4uXjd4t7/PQSYAnit5WsMazSMvJI8XHWu+Lj44GnwvN1dE0IIIYQQf4AEEMTvklachHtaPp8GvESKNySb06lqDMXrXBr+uUUU1xlDtpeOub4H2bxtluNzKlRMaDaOJ+94knCPcOyKnS4RXcgozmB13GpOZp7kfM55Vp5dSafwTujVet7Y+0aF/difvJ+HajxEtjmbz04s5rUGw0hwC+PRWg/TJKAxdYxBBB1fjRLeCl1IMJaEhDKvHgB49OhBTo1Alhi9WHloFM82eJYtl7fwUM2H+ODwB2xJKF2KMToompntZzJhxwTi1RkMPzra0YZapWZq66l4GbzYmbCTOj51GFjvaTLNWeTqXUuDB1llgwdQOrX7+if+Rq2RELcQ8kvySSlMIc+SR6ApkBbBLdibVDZ5I0DLkJasOb+GYmsx91e/nzkxc6juWZ06vnW4N/Je/Ix+XMm/woqzK7icd5kiaxH3Rd1HXHYc6y6sc7SjU+tw07kxr8M8UotSOZd9jgBTAOEe4QSZglCpVE77vZJ3hec2Pcf5nPOObSGuIbzR+g2mtCpN0Og9vD1Fe/aWOfdqd3dcOrRz/Hw1IeLuxN3sTtztVLeaZzU8DB7lHvutklGUwYz9M/jpwk+ObYtOLOLBqAcZ0WSE09PzKK8odGpduUGd2j610aq1FV7vQ2mHyDRn/msDCABuerfb+oqJEEIIIYS49SSAIH6XxPxE7vAMxmX9boIPHyaouBi3zp0x1rkDu8qNzLVL2XJ/BJsvb3H6nI+LDwfTfuGlJi9xLP0YGy6W3lSHuIbwSK1H6FWjF9P3TWdN/BoaBTYi1C0UN52bYzm7X/MyeLH8zHIAUgpTMRSk84hHFPyyHHZ/BSYfbNW7kOjiispWRPDrE0l67Q2nG1ldRAQezz3LN7lb8fEK5u3qb/Pj+R8diew+OnotSd6+5H2kF6czvNFw3HRuvNH6DY6mHcXbxZtG/o34Pu57glyDeL7R81TzrEbf9f2wK3a+6P4Ffev05dVdr5Y5Bm+DN02DmhKbFcuRtCOMaDwCP6Mfcdlx+Lj4EGAKwGKzEO4RzpimY3h87eNlZmS0CG5BgaWASa0msefKHrpV7cb3Z7+nxF5C7xq9WXxiMVfyrxDlFcXgBoM5n3OeeyLvIcg1iFdavMKQhkOIy47D0+BJuHs4/iZ/tGotfiY/6vjWochSRE5JDkfSjlBiLyHAGICPiw8KCq/sfMUpeACQWJDI1L1Tmd1+Nl4GL1alraT93KmUvPUu1qTSHA4u9erCK8P5JncLT9nD0Kq1+Lr48kz9Z8rkFtCqtExuORk/o19lQ/MPOZx62Cl4cNWKuBXcXfVuWoe2dmzzM/rxeqvXGb9zvFNdk9bEG63fIN+Sf8N9FVoKb02nhRBCCCGE+IuoFKWcx7HitsnNzcXT05OcnBw8PP7cp62/ly03l4IL58hb9i22tHRMLaJxa9uWtHfmU/TLLwSMfonspjUYGjOWhLwEoPSp9phmY3DVuXI59zLBbsFM2j2pTNsP1ngQvVrP+gvrGd5oOKHuocSkxDjdxF9vXsd5jNs+jmJbMb1r9Oblus9izTiL7tQqVApoGjyCVWfipDWHmMxTNHWtRU2bP4UbN2FNTcOlbWuuhLow+uR0htYfTD3/+pzJPktN7xqsilvN56c+L3fa/Nvt30ZB4a39bxHpGUm+JZ+TGSdRUBjffDwtglvQ58c+FNuKMWqNzGo3iz1JexwBiauvK9TxrVMaMHDxw0XrwoXcC3xw5AOOpx937MuoNTK/43w0ag3BrsEUW4v58MiH7E/ej4fBg/uq30eoWygTd02koX9D3mzzJiFuISQXJPP5ic/54tQXZfo/qeUkuoR1wcvoVen1Liwp5FL+JXZd2UVMSgyeBk86hXfCarNSw7sGD6x+oMLPLu+5HB8XH55Y+wSeBk+GhPYh1O4BGg2HzOf4+PLXhLuH827nd3HVuQKQXZzNiYwTLDy60PFqxDMNniHMPQyDxlBpf3+vvJI8nvv5OQ6nHS63vGVwS+Z1nIdJZ3JsKygp4Er+FZbFLuNy3mWaBjalR2QPQlxDuJx3mZ4re5bblkalYXWv1YR7hP8ZhyKEEEIIIcRvcrP3oTIDQfwmtrw8sr75hrTZbzu2FezYQdZnnxE8bRqWpESsmZnY3YxkFmU66kyInsCGixvYk7iHGW1nMGP/jHLb//7s97zf+X2KbcUcTDnIrIOz+KrHV+xO3O10Uw3Qt05fDqUeothWjE6t4/FajzLmwDTq+NbhsruBp+sNoJrFhjH1BE2OfUdos/48fXQmifmJNK/ZHJc6LpzOnENSYukT8e/PrwK1mgj3cCy2EhafXFzhecgoziAmOYa0ojTHiglX5VvyySrOothWDJTmJvAweLDk1BKaBjZlXPNx6NQ6tGot57LP8erOV3mv83voVDq2XNpS5jiLrEUM3zyct9q9xcD1A/m82+d4GDwY1mgYRdYifor/iRMZJwA4mHLQ8WTbYrew5PSScvs/N2Yuvi6+hLqHEuUVhVqlrvBYk4uSeX7T86QUXkuE+OP5H+lft3+lSyjmluQS4hZChEcEe5P2MjJzSpk6XcK7OAUGvFy8aB3amvp+9Sm2FWO32zmRcYJdV3ZR368+Ye5hf8oqBha75YazBvIseVjtzitTuOpdqelTkwnRE7DYLBi0Bse59DX6cnfE3Wy4uKFMW72ieslqBEIIIYQQ4h9HAgjiN7GmpTkFDxzbU9PIWroMY9OmuPS6m3yNncaBjdl5ZSfh7uFY7Bb2JJYm0dOpdRUmDFRQSClMYUDdATy65lGKrEXsuLKDwfUHk2vJ5ZeUX3DXuxMdHM3uxN18fuJzqntVZ2L0RN46OItO4Z1oGtgUDSqiNr8FnlVQojpBUH30thK8DF5czrvMnqSyCf18DN7Udo3kyZ+fZlqbaejVekrsJeX208/oV24bALW8azm9F29X7OjVeiI8IjiYcpCDKQed6jcNbIrVbuVE5glWn1tdbpvFtmJSClMIcg0itSiVb898W249gPM553HTuXEl70qFSQdzS3Kx2C30X9efb+/7tsIVAQothXx4+EOn4MFVi08s5t7Ie9GqtWVurK/yN/rjrndnaMOh5eZu0Kg09KnVB6267FeRSWciLjuOIT8PcXqFpaZXTd7t/C7BbsHl7vP38tB70CGsA3HZceWWdwnv4pgl8WtatbbMMbjr3RnbfCzuendWnVuF1W5Fr9bzcM2HGdhgYIVtCSGEEEII8XdV8WNHIcpRsGNnhWUWuwWGPsUvxRfJKM5kZOORvNbiNcY0HcPRtKOOeuXdLF4v1BSMdv5nfNF8Pt2q3MWSU0vIt+Zj1Bhx07kR7h5OgEsAvarfz3fdlvFh2wXMPDCTtKI0AkwBXM67jMkORS2GUFS/NwfshbztbiAnqD69onpVuN/HArpzLuk4ZpuZLZe30COyR7n1fF18CXMPI7ckt0xZm9A26DQ6pyf6CgpZ5izGNx9PsKvzTW8Nrxo8W/9ZcktysSv2CgMWUJrgz0PvgU6jQ4Wqwno6tY6B6wei1+grrHO1Xp4lj22Xt1VYJ6s4i40XN1ZYfj77PI/UfKTcsrsj7nYkHazhXYMpraZg1Bod5Z4GTxZ0qng5w9TCVIb+PLRM/osz2WeYEzPnlucQ0Kq19K7Ru9yVAnxdfOlWrdsNV7UoT4ApgLHNx/JDrx9Ycd8KVvdazYtNXsTfeOtnUAghhBBCCPFnkxkI4jexFxeX2aYNCUE3bTypYW4kZxyipndNCqwFzI2Zy4mMEwSYAni45sPU8a3DrAOziM+J5w6fOziVeapMW246NwISCij46htUK3/kuV73oDQdhNFYG42HB5FuERjtGlzzFFR2G8etyUyNe4t2Ye2o7VObSbsnMafDHO5d9ygqVI4bchUq2oS2oYFfA+6JvIc159c47XdgnacJKtDxUdbPAPwU/xNvtXuLjKIMdlzZ4agX5BrE5JaTMVvMfNjlQ+b/Mp+TmSfxNnjTu0ZvOoZ35Hz2eXJLcukU3onNlzYDsOTUErqEd+G5O5/DoDGQVphGkGsQmcWZ5JbkcjD5ILV9axPkGkRyQXK55z7KK4olp5YQkxJDm9A2Tv26qppnNVIKU7iUfwkVKjwNnuSYc8rUq+FVg0t5l4DS1x4erf1o+a8xqMCqlD+7AOBExgmervc0Jq2JJaeXUGQtQqfW8UCNBxjSYIhj1QR3vTv3Rt5Li+AWpBelo1Fp8DH64G/0rzCgFJcdR6G1/CDBxosbGdF4hFM+glsh1C2UJT2W8N6h90oDJyroXq07QxsMrTDQURmj1kgV9yq3tJ9CCCGEEELcDhJAEL+JoVU0zL32szY4GGXBFAafeoPE2ESqe1VnUP1BjN853jF9PtuczZv73uSBqAd44o4n+Or0V0xpOYXxO8c7vcqgVWuZ02YW/mkuWF59laLzZ9E0rI9rvcbsKoplzIYxNApoxHMNn+Nc0TnisuIIdA2kVWgrdl7ZyYdHPsTXxZfkguQyS+s1CWhMiMqLp34ezDP1nqFnZE8OJB9ArVITHRxNyJVidAG+7Dt9ACi9aR63YxwD6w1kYP2BJBcko9foyS/JZ+q+qbzY+EXm/TKPEY1GEOERgR072eZsrDYrU/dNxWq38mKTF3ko6iGOZRwjIT+BQNdAdGodS08vJbs4Gx+jDz2r98TL4MWKuBXUyKjBwHoDeXPfm2XO+x0+d5Bbkku+JZ9vYr/h3U7vkm/J51DqIUedah7VGNd8HK/uLF3p4dPjnzKn/RyG/jzUaWaDh96DF5u8yOt7Xwe4YQ4Ed507zQObsz9lf7nlnSM6E+gayNA7h/JwrYcptBTionXB3+iPQeuc8FCv0RPiFkKIW0i5bf1aemF6hWU2xUaJreLZGr+XSqUiwiOCya0mM6rpKKB0psT1MyeEEEIIIYT4r5IAgrhp2cXZ7LfHUf2ujujMNrweeIDCRtUZsPsFEgsSAXi01qO8e/jdct+9/z6uNEHiV6e/YubBmbze+nUu5lzkbNZZIj2q0l5dG78ULamvvYbHp++SfFdtkvKu0MWg4Q73GoS7h3Mo9RCv7X6NiS0m8v7h951eIzBqjUxqOYl3D7/rtF+NSsOI8L7YR09lxrixDDo4FoPGQE3vmoS7hREc5IHW141YbToTW0zk85OfczH3Ir5GX4w6I6cyTvH+4fcpshVhtVup5V2LhLwELuddZvT20Y79dK3aleigaMw2M+2rtCfSM5Jj6cfINmdzd8TdWO1WZuyfQauQVtT1rUtSQRK/pPyCXbFjsVs4mXGSXtV7MaXlFN4/8j4phSlo1VrujribJ+94kkEbBwGlSRU1ag1z2s8hLjuOhPwEfFx8SCtK49WdrzqSOl7IvUCkVyQre61kw4UNxGXHEeUVRXWv6syJmUNyQTJalZYe1cp/VQPAw+DBy81f5om1T5RZOrJDlQ5UcSt9sn41OHAr1fatXWGZn9HvT80hYNKZbvnsBiGEEEIIIf7pJIAgblpuSS5jj0xl40tLYcse9EEepGttjGoyCrVKzdG0o44cBBVJLEjkDu87SCpMYkfCDu6NvJcQYwD1154l+/3BaBd+iP/cWVzRmRmwZgDvtJiBRqUmFA2Lmr5KimIm2ZJLoIs/X3b/kv0p+zmdeZqqHlWJ9IwkwhTGnR51uJh7EbPNTAPferxUbSDu739LUUwMtQuf4393/Y9LeZeo430HWtRMOTSb/cmlT9jbhLTh7falSSJjM2NZGru0zKoIo5uNJsgUxMmMkxxMOYi3izeP1HwEk86Er4svT93xFNW9qjN883Bsig2ApaeXEu4ezuz2s/ng8AfkmHPoFN6J2MxY/nfsf0Dp6xth7mEsPrGYIQ2H4KH3QIWKELcQXtj8AvmWfHxdfBkfPZ6a3jVx17tzKvMUc2PmUmgpLPOqQe8avfFx8UGtUvNwzYfZenkrn5/8nNisWABcda683f7tSpMRVveszrc9v2XhkYXsTdqLp8GTp+o8RYewDvgZ/W5+AP1GQa5BNAtsxoGUA2XKXmzyIgGmgD9t30IIIYQQQoiyVIqiKLe7E/827733HrNmzSI5OZmGDRuyYMECmjdvflOfvdn1N2+Hy3mX2Rq3kXtOGVH8TFys6c4bRxY4stY3C2rGmKZjeOTH8pPqAcxsNxM1anJKctibtBd/gx+PF9an8PmxuHXpgtfYUewsOcXYHWMJMAWwuMsnLItdyp1+jbAoJcRlx3E+/xInM04yIXoCX53+ijFNxzD7wGwu5V/ikzumYl60BHvPzihaDepT57B+9g3WlNJVBLzGvsQo/00kFSRxh/cdjGwyEqtiJd+Sj6vOlRxzDlq1ljf3vsnY5mNZFruM7QnbsSt2qrhX4bmGz9HIvxFVPKpQZCkiryQPjVqDTbGxPWE7+5P3M7DeQB5d82i5KxN0rdqVjmEdMagNlCglrIxbSU5xDo0DG/NIrUf4Kf4nPj72MSX2Ehr6N2Rs87GEuIY4Vk3w1Hvib/J3vHKQXpjOpD2T2J6w3Wk/Nbxq8H6X9wlyDXJsK7AUkFGUwcXcixi1RkLcQggwBqDV3FwcsdBSSH5JPhq15i9bgjC1MJWPj37M93HfU2wrJsg1iFFNRtEqpFW5yQ6FEEIIIYQQv93N3odKAOEW+/rrr+nbty8ffvgh0dHRzJs3j2+//ZbY2FgCAip/Yvp3DiBk52XgkpJFwoiR2D6dRp/1fR1P2K8a2XgkWy5v4UjakTKf16q1fH/vcpSCFApR467zRPXVGvI/+QxTl47kDu7NKXUKHxz5gHD3cIbdOYxXdr1CckEybUPb4uPiw4/nf6RTeCf61+1PbkkuAcYAfrrwE9HB0eSX5BOcr0X9xEiUcpI9AvjOn82GKllU9ayKXbEzamvp7IkRjUdQ3bM6Rp2R6Xun82zDZ0kvSsdd506YR1jpqgcKTNoziVFNRtE6tHW57VvtVjZc2MDYHWPLLdeqtMxsP5NRW0fhZ/Tjroi76FGtB1ablTsD7sSm2Mg0Z2JX7Ljp3G7qJjm9MJ1TmadYenopJbYSHqjxAE0DmxLoGljpZ/8JzFYzGcUZWOwWjFqjzDwQQgghhBDiFpMAwm0SHR1Ns2bNePfd0vfw7XY7YWFhDB8+nHHjxlX6+b9zAKE4IxPr6VNkxOxlTt0LbE7YWqaOr4sv8zrOY9imYU75CVSomBo9mY4utXExaSi22tAWacjOTiNHZ2V97l6WXFzBkh5LyCzOJCY5hqWxSx1JFp+840meuuMpssxZFFuL0Wl0fHf2O3pU68GQn4dgs9t4scmL1POoTeBn6ylY8nWZvqnd3LAsnsnk8+8xrc00kguTMdvMeBm8UKvUbL60mYdrPozZZuaDIx+QkJdAFfcqNPBvQBW3Kry661WKrEV81u0zGgc2rvA8LTm5hBkHZlRY/nb7t3lp20ulfVKpWd5zOaFuoX/4nftiazF2xS7v7gshhBBCCCF+k5u9D5UcCLdQSUkJMTExjB8/3rFNrVbTpUsX9uzZU+5nzGYzZvO15HS5ubnl1vs7sBbmY8/Lw1ozgkNpq8qtk1Gcweq41Xza9VP2Je1jX/I+qhiCuN+3A17HL2NtpuWuLYPIKM5gUddFPLtruOPd/YktJvLuoXfZfHmzU5tqlZpWIa04m30WFSqm7J1CamEqAI0DGtO+Sns2XdrEnJg5hLiG8L8nZmK6nEjh9mvLHGq8vDAtmMFa62lGNx3ND+d+oGvVriQXJnM26ywKCk0Cm7Dx4kZCXEOo5V2LdlXaUWwtZuPFjRxMOQiUrmBQWc6AOwPurLAswiOCjOIMx8/dq3YnxDXkltz0u2hd/nAbQgghhBBCCFERCSDcQunp6dhsNgIDnaeOBwYGcvr06XI/M336dKZMmfJXdO8Ps2nVFMXEYOjYAj+zH1nmrHLrqVQQGJ/Fw/rGPFi1BTqdCntRNgfqe3C58AAZxRn0rtGbYmsxzYKaEeQaxD2R92BTbER6RbI1YatjFQej1sjLzV7maNpRLHYLDQMaOoIHUDrj4ZXmr9CnVh8S8hIwaAycVqdgfa4ztYY8BhcS8A2JpDDAnX2WOKyFNvYl72PxycV8fupzGgc0xtPgyYXcC5zLPsd7nd9j6t6pvNbitTLLTOrVet7p+A7+Rv8bnqdg12BaBLdgb9LeMmXP1n+WRScWoVFp6Fm9Jy80egFX/Z+3moAQQgghhBBC3CoSQLjNxo8fz6hRoxw/5+bmEhYWdht7VDGLyR19vbq4WfUMiHyUCb+8UW69h6vdj+ZMLpaUi7j4FZDpYWBt3jnCAxqw79wGJraYSIvgFtgVO6+3fh29Wk+OOYez2Wd5MOpBulXtxsXciygoaNVadibspFN4JxYeXYiXi5djP646VyK9IvF39afYVsx3Z76jV41exGbGcj7/PAnuEbRo04JMmxmdxs7Fy5dILkjm6XpPczz9OHuT9jpmFqhQMbrpaNbFryOpIInPT37Okh5LOJJ2hJiUGKK8omgf1p4gUxBa9Y3/2vgYfZjWZhpfx37NV6e+Is+SRy3vWoxuNppQ11BqeNfATeeGn9FPXjcQQgghhBBC/GNIDoRbqKSkBJPJxPLly+nVq5dje79+/cjOzmbVqvKn/V/v75wDIa8oF3JyyX3/I9QP38OH2T+y4vxKR7lapebVZuO5y6cVKquNI4UnOZJ5gsSSLHrX6E2OOQcVKu7wvaPMawAWm4WLuRdZGbeSnpE9SS5MJq0oDV8XXxLyE1h+Zjljmo3htV2vkVaUhovGhQ/v+pCG/g3RqrUoikJifiKrzq0iLiuOcI9wWoW0ItgtGL1aj5/RD41a49hfRlEGiQWJ7LmyB51GR5RXFKvOrWL9hfXU9qnN2+3fJtwj/A+dL6vdSkZRBjbFhovWBR8Xnz/UnhBCCCGEEEL8GSSJ4m0SHR1N8+bNWbBgAVCaRDE8PJznn3/+H59EESAtKwOtpRB9dgF5hdnkBpg4knMKg86Fen71MWlNuGldKbQWkGcpwI4dnVoHCqCi9Mm7ya/C9jOKMiiyFmG1W7mSf4VzOeeo7lmdcI9w0gvTS3MquFWhUWAjAk2BZWYDWO1W8kry0Kq1uOvdb+qYCi2FpBelk1OSg1FrxMfFR272hRBCCCGEEP8ZEkC4Tb7++mv69evHwoULad68OfPmzeObb77h9OnTZXIjlOfvHkAAMJcUkVmQj4tBi1atwWq34qIzYtQZb3fXhBBCCCGEEEL8RrIKw23Sp08f0tLSeO2110hOTubOO+/kp59+uqngwT+FQW8kWC/BAiGEEEIIIYT4L5EZCH8z/4QZCEIIIYQQQggh/j1u9j5U/Rf2SQghhBBCCCGEEP9QEkAQQgghhBBCCCFEpSSAIIQQQgghhBBCiEpJAEEIIYQQQgghhBCVkgCCEEIIIYQQQgghKiUBBCGEEEIIIYQQQlRKAghCCCGEEEIIIYSolAQQhBBCCCGEEEIIUSkJIAghhBBCCCGEEKJSEkAQQgghhBBCCCFEpSSAIIQQQgghhBBCiEpJAEEIIYQQQgghhBCVkgCCEEIIIYQQQgghKqW93R0QzhRFASA3N/c290QIIYQQQgghxH/B1fvPq/ejFZEAwt9MXl4eAGFhYbe5J0IIIYQQQggh/kvy8vLw9PSssFylVBZiEH8pu91OYmIi7u7uqFSq292dCuXm5hIWFsbly5fx8PC43d0Rt5mMB3E9GQ/iejIexPVkPIjryXgQ15PxcHspikJeXh4hISGo1RVnOpAZCH8zarWaKlWq3O5u3DQPDw/5Cy4cZDyI68l4ENeT8SCuJ+NBXE/Gg7iejIfb50YzD66SJIpCCCGEEEIIIYSolAQQhBBCCCGEEEIIUSkJIIjfxWAwMGnSJAwGw+3uivgbkPEgrifjQVxPxoO4nowHcT0ZD+J6Mh7+GSSJohBCCCGEEEIIISolMxCEEEIIIYQQQghRKQkgCCGEEEIIIYQQolISQBBCCCGEEEIIIUSlJIAghBBCCCGEEEKISkkAQQghhBBCCCGEEJWSAIL4Xd577z2qVq2Ki4sL0dHR7N+//3Z3SfwOkydPRqVSOf2pXbv2DT/z7bffUrt2bVxcXKhfvz5r1651KlcUhddee43g4GCMRiNdunTh7NmzTnUyMzN54okn8PDwwMvLi4EDB5Kfn3/Lj0/c2Pbt2+nZsychISGoVCpWrlzpVH4z17I8lX0/FBcXM2zYMHx9fXFzc6N3796kpKQ41bl06RL33HMPJpOJgIAAxowZg9Vq/cPHLCpW2Xjo379/me+Lbt26VdqujId/punTp9OsWTPc3d0JCAigV69exMbGOtW5mWv3a7fqd8TRo0dp27YtLi4uhIWFMXPmzFtz4KJcNzMeOnToUOY7YsiQITdsV8bDP9MHH3xAgwYN8PDwwMPDg5YtW7Ju3TpHuXw3/MspQvxGy5YtU/R6vfLpp58qJ06cUJ599lnFy8tLSUlJud1dE7/RpEmTlLp16ypJSUmOP2lpaRXW37Vrl6LRaJSZM2cqJ0+eVF599VVFp9Mpx44dc9SZMWOG4unpqaxcuVI5cuSIct999ynVqlVTioqKHHW6deumNGzYUNm7d6+yY8cOJSoqSnnsscf+1GMVZa1du1Z55ZVXlBUrViiA8v333zuV38y1/LWb+X4YMmSIEhYWpmzatEk5ePCg0qJFC6VVq1aOcqvVqtSrV0/p0qWLcujQIWXt2rWKn5+fMn78+Ft+DsQ1lY2Hfv36Kd26dXP6vsjMzLxhmzIe/rm6du2qLFq0SDl+/Lhy+PBhpUePHkp4eLiSn5/vqFPZtSvPrfgdkZOTowQGBipPPPGEcvz4cWXp0qWK0WhUFi5ceOtPhFAU5ebGQ/v27ZVnn33W6TsiJyfnhu3KePhnWr16tbJmzRrlzJkzSmxsrDJhwgRFp9Mpx48fVxRFvhv+7SSAIH6z5s2bK8OGDXP8bLPZlJCQEGX69Om3sVfi95g0aZLSsGHDm67/yCOPKPfcc4/TtujoaGXw4MGKoiiK3W5XgoKClFmzZjnKs7OzFYPBoCxdulRRFEU5efKkAigHDhxw1Fm3bp2iUqmUK1eu/IGjEX/Er28Yb+Zalqey74fs7GxFp9Mp3377raPOqVOnFEDZs2ePoiilN7JqtVpJTk521Pnggw8UDw8PxWw2/+FjFZWrKIBw//33/6Z2ZDz8e6SmpiqAsm3bNkVRbu7a/dqt+h3x/vvvK97e3k7Xf+zYsUqtWrVu3QGLG/r1eFCU0gDCiBEjbroNGQ//Lt7e3srHH38s3w3/AfIKg/hNSkpKiImJoUuXLo5tarWaLl26sGfPntvYM/F7nT17lpCQECIjI3niiSe4dOlShXX37NnjdO0Bunbt6rj28fHxJCcnO9Xx9PQkOjraUWfPnj14eXnRtGlTR50uXbqgVqvZt2/frTw08QfczLX8tZv5foiJicFisTjVqV27NuHh4U5jpH79+gQGBjrqdO3aldzcXE6cOHFLj1P8Nlu3biUgIIBatWoxdOhQMjIyKqwr4+HfJScnBwAfHx/g5q7dr92q3xF79uyhXbt26PV6R52uXbsSGxtLVlbWLTpicSO/Hg9XLVmyBD8/P+rVq8f48eMpLCyssA0ZD/8ONpuNZcuWUVBQQMuWLeW74T9Ae7s7IP5Z0tPTsdlsTv+QAwgMDOT06dO3qVfi94qOjmbx4sXUqlWLpKQkpkyZQtu2bTl+/Dju7u5l6icnJ5d77ZOTkx3lV7fdqE5AQIBTuVarxcfHx1FH3H43cy1/7Wa+H5KTk9Hr9Xh5eVXYbkXj7Pp+ib9et27dePDBB6lWrRrnzp1jwoQJdO/enT179qDRaMrUl/Hw72G32xk5ciStW7emXr16wM1du1+7Vb8jkpOTqVatWpk2rpZ5e3v/jqMUN6u88QDw+OOPExERQUhICEePHmXs2LHExsayYsWKctuR8fDPduzYMVq2bElxcTFubm58//331KlTh8OHD8t3w7+cBBCE+A/r3r274/8bNGhAdHQ0ERERfPPNNwwcOPA29kwI8Xfz6KOPOv6/fv36NGjQgOrVq7N161Y6d+58G3sm/mzDhg3j+PHj7Ny583Z3RfwNVDQeBg0a5Pj/+vXrExwcTOfOnTl37hzVq1f/q7sp/mS1atXi8OHD5OTksHz5cvr168e2bdtud7fEX0BeYRC/iZ+fHxqNpkwm1ZSUFIKCgm5Tr8St4uXlRc2aNYmLiyu3PCgo6IbX/up/K6uTmprqVG61WsnMzJQx9DdyM9fy127m+yEoKIiSkhKys7NvWKe8Nq7vl7j9IiMj8fPzq/D7QsbDv8Pzzz/Pjz/+yJYtW6hSpYpj+81cu1+7Vb8jZEzcPhWNh/JER0cD3PDfFCDj4Z9Kr9cTFRVFkyZNmD59Og0bNuSdd96R74b/AAkgiN9Er9fTpEkTNm3a5Nhmt9vZtGkTLVu2vI09E7dCfn4+586dIzg4uNzyli1bOl17gI0bNzqufbVq1QgKCnKqk5uby759+xx1WrZsSXZ2NjExMY46mzdvxm63O/6xIW6/m7mWv3Yz3w9NmjRBp9M51YmNjeXSpUtOY+TYsWNO/1DYuHEjHh4e1KlT55Yep/j9EhISyMjIqPD7QsbDP5uiKDz//PN8//33bN68ucy04Ju5dr92q35HtGzZku3bt2OxWBx1Nm7cSK1atWSK8p+ksvFQnsOHDwNU+B0h4+HfxW63Yzab5bvhv+B2Z3EU/zzLli1TDAaDsnjxYuXkyZPKoEGDFC8vL6cM2eKf4aWXXlK2bt2qxMfHK7t27VK6dOmi+Pn5KampqeXW37Vrl6LVapXZs2crp06dUiZNmlTuMo5eXl7KqlWrlKNHjyr3339/ucvwNGrUSNm3b5+yc+dOpUaNGrKM422Ql5enHDp0SDl06JACKHPmzFEOHTqkXLx4UVGUm7uWv3Yz3w9DhgxRwsPDlc2bNysHDx5UWrZsqbRs2dJRfnXZvrvvvls5fPiw8tNPPyn+/v6ybN+f7EbjIS8vTxk9erSyZ88eJT4+Xvn555+Vxo0bKzVq1FCKi4srbFPGwz/X0KFDFU9PT2Xr1q1Oy/IVFhY66lR27cpzK35HZGdnK4GBgcpTTz2lHD9+XFm2bJliMplkqbY/UWXjIS4uTnn99deVgwcPKvHx8cqqVauUyMhIpV27djdsV8bDP9O4ceOUbdu2KfHx8crRo0eVcePGKSqVStmwYYOiKPLd8G8nAQTxuyxYsEAJDw9X9Hq90rx5c2Xv3r23u0vid+jTp48SHBys6PV6JTQ0VOnTp48SFxfnKO/Xr5/Svn17p8988803Ss2aNRW9Xq/UrVtXWbNmjVO53W5XJk6cqAQGBioGg0Hp3LmzEhsb61QnIyNDeeyxxxQ3NzfFw8NDGTBggJKXl/enHaco35YtWxSgzJ9+/fopinJz17J9+/aO+ldV9v1QVFSkPPfcc4q3t7diMpmUBx54QElKSnKqc+HCBaV79+6K0WhU/Pz8lJdeekmxWCy3/ByIa240HgoLC5W7775b8ff3V3Q6nRIREaE8++yzZQLHMh7+PcobC4CyaNEiR52buXYRERHKpEmTHD/fqt8RR44cUdq0aaMYDAYlNDRUmTFjxi0/B+KaysbDpUuXlHbt2ik+Pj6KwWBQoqKilDFjxig5OTlO7ch4+Hd4+umnlYiICEWv1yv+/v5K586dHcEDRZHvhn87laIoyl8330EI8U/Svn17OnbsyOTJk293V8TfVEREBFOmTKF///63uyvib0DGg7heYWEhvr6+rFu3jg4dOtzu7ojbTMaDuErGwj+brMIghChXTk4O586dY82aNbe7K+Jv6sSJE3h6etK3b9/b3RXxNyDjQfzali1b6NSpk9wgCEDGg7hGxsI/m8xAEEIIIYQQQgghRKVkFQYhhBBCCCGEEEJUSgIIQgghhBBCCCGEqJQEEIQQQgghhBBCCFEpCSAIIYQQQgghhBCiUhJAEEIIIYQQQgghRKUkgCCEEEIIIYQQQohKSQBBCCGEEEIIIYQQlZIAghBCCCGEEEIIISolAQQhhBBCCCGEEEJUSgIIQgghhBBCCCGEqJQEEIQQQgghhBBCCFEpCSAIIYQQQgghhBCiUhJAEEIIIYQQQgghRKUkgCCEEEKIvwWVSkWHDh1udzeEEEIIUQEJIAghhBD/ciqV6jf9uVn9+/dHpVJx4cKFP6/zFdi6dWuZfhsMBqpWrcqAAQM4e/bsX94nIYQQ4t9Oe7s7IIQQQog/16RJk8psmzdvHjk5OeWW/ZM0adKEe++9F4CcnBx27drF4sWLWbFiBfv376dWrVq3uYdCCCHEv4cEEIQQQoh/ucmTJ5fZtnjxYnJycsot+ydp2rRpmWMYMmQICxcuZNq0aXz22We3p2NCCCHEv5C8wiCEEEIIh/T0dEaOHEm1atUwGAwEBATwyCOPcPz4cad6VatWddycV6tWzfEawfU5DL7//nsee+wxoqKiMJlMeHp60rZtW7777rs/9RgGDhwIQExMTJmyixcvMnDgQEJDQ9Hr9VSpUoWBAwdy6dKlctv6LfU7dOiASqXCbDYzYcIEwsPDMRqNNGnShJ9//hkonSUxbNgwQkJCcHFxoWXLluzfv79MW2fPnmXAgAGO6+Dj40PDhg0ZOXIkiqL8kdMjhBBC/G4yA0EIIYQQAKSlpdGyZUvOnTtHhw4dePTRR4mPj2f58uWsWbOG9evX06ZNGwBGjhzJ4sWLOXLkCCNGjMDLywsoDSxcNX78ePR6PW3atCE4OJi0tDRWr17NQw89xPz58xk+fPifejxarfM/c86cOUObNm1IS0ujZ8+e1K1bl+PHj/Ppp5/yww8/sHPnTmrWrPm761/Vp08fjh07xn333UdRURFLlizh3nvvZdeuXQwaNIiSkhIefvhh0tLS+Prrr+nWrRvx8fF4enoCkJiYSPPmzSkoKOCee+6hT58+FBQUcPbsWd5//31mz55d5tiEEEKIv4QihBBCiP+ciIgI5df/DBgwYIACKOPHj3favmbNGgVQoqKiFJvN5tjer18/BVDi4+PL3ce5c+fKbMvLy1Pq16+veHp6KgUFBU5lgNK+ffub6v+WLVsUQBk8eHCZssGDByuAMmzYMKftHTt2VABl4cKFTtvfe+89BVA6der0h+q3b99eAZQ2bdoo+fn5ju1ff/21AiheXl7Kww8/rFgsFkfZW2+9pQDK22+/7dg2f/58BVDmzZtX5tgyMjIqOiVCCCHEn05eYRBCCCEEJSUlLF26FF9fX1599VWnsh49enDXXXcRFxfHrl27brrNyMjIMtvc3Nzo378/OTk5HDhw4A/3++DBg0yePJnJkyczatQomjdvzsKFC6lZs6bTcVy6dIktW7ZQp04dnn32Wac2hgwZQu3atdm8eTOXL1/+XfWv9+abb+Lq6ur4+aGHHkKn05GdnV1m9sBjjz0GwJEjR8q0YzQay2zz8fG5mdMihBBC/Clk/psQQgghOH36NMXFxXTs2BGTyVSmvGPHjmzcuJHDhw/Ttm3bm2ozNTWVGTNmsG7dOi5evEhRUZFTeWJi4h/ud0xMTJlcB7Vq1WLnzp34+fk5th0+fBiA9u3bl1mqUq1W065dO06fPs3hw4cJCwv7zfWvd+edd5apHxAQQGFhIeHh4U5lwcHBgPO56NmzJ+PHj2fYsGFs2rSJbt260b59+3IDMkIIIcRfSWYgCCGEEILc3FwAAgMDyy2/eqN7tV5lMjMzadasGXPnzsXX15eBAwfy6quvMmnSJO6//34AzGbzH+734MGDURQFu93OlStXGD16NLGxsTz88MPYbDZHvd96fH/kfHh4eJTZptVqK9wOYLFYHNuqVq3K3r17uf/++1m7di1PP/001atX54477uDbb78ttz9CCCHEX0FmIAghhBDCcXObkpJSbnlycrJTvcp88sknXLp0iTfeeKPMKxEzZsxg1apVf6C3ZalUKkJCQpg1axbJycl8+eWXLFiwgJEjRzr1+2aP71afj9+qXr16LF++HIvFQkxMDOvWrWP+/Pn06dOHkJAQWrdu/afsVwghhLgRmYEghBBCCGrXro2LiwsHDhygsLCwTPnWrVsB5+n5Go0GwOlJ/1Xnzp0DcMw2uN6OHTtuQY8rNnPmTIxGI1OnTiUvLw+41u/t27eXWQZRURS2b9/uVO+31v+z6HQ6WrRowZQpU5g/fz6KovDjjz/+qfsUQgghKiIBBCGEEEKg1+t57LHHSE9PZ/r06U5lP/30E+vXrycqKsrpyffVhH7lJRKMiIgAYOfOnU7bv/rqK9auXXuru+8kODiYIUOGkJGRwbx58wAIDw+nY8eOnDhxgk8//dSp/kcffcSpU6fo1KmTI5/Bb61/K8XExJT7asTV2RAuLi63fJ9CCCHEzVApvw6rCyGEEOJfr2rVqly8eNHp6XpaWhotWrTg/PnzdOrUiejoaC5cuMC3336LXq9n/fr1tGnTxlF/3bp19OjRgxo1atC7d29cXV2JiIjgqaeeIiEhgXr16pGfn8+DDz5IREQER44cYdOmTfTq1YsVK1awaNEi+vfv72hPpVLRvn17x2yHG9m6dSsdO3Zk8ODBfPjhh2XKU1JSiIyMRK/XEx8fj5eXF7GxsbRp04aMjAzuu+8+6tSpw4kTJ1i9ejX+/v7s3LmTmjVrOtr4rfU7dOjAtm3bysxYuHq+AS5cuFCm7NfHPXLkSBYuXEi7du2oXr06Hh4enDx5krVr1+Lp6cmhQ4fKJGMUQggh/goyA0EIIYQQAPj7+7Nv3z5eeOEFzp07x+zZs9m4cSO9evVi3759TsEDgO7duzNz5kwA3n77bSZOnMgnn3wCQJUqVdi2bRudO3fm559/ZuHChZSUlLBhwwZ69uz5px9LYGAgQ4cOJTs7mzlz5gClqzMcPHiQ/v37s3//fmbNmsWBAwcYMGAABw4ccAoG/J76t8pjjz1Gv379SExMZOnSpcyfP5/Tp08zdOhQCR4IIYS4rWQGghBCCCGEEEIIISolMxCEEEIIIYQQQghRKQkgCCGEEEIIIYQQolISQBBCCCGEEEIIIUSlJIAghBBCCCGEEEKISkkAQQghhBBCCCGEEJWSAIIQQgghhBBCCCEqJQEEIYQQQgghhBBCVEoCCEIIIYQQQgghhKiUBBCEEEIIIYQQQghRKQkgCCGEEEIIIYQQolISQBBCCCGEEEIIIUSlJIAghBBCCCGEEEKISkkAQQghhBBCCCGEEJX6P39eprnsBZibAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot a chart with thousands separators on the X and Y axis\n",
    "plt.figure(figsize=(12, 6))\n",
    "plt.title('Total Rooms vs. Population by Ocean Proximity', fontsize=18, pad=15)\n",
    "sns.scatterplot(data=df_housing, x='total_rooms', y='population', hue='ocean_proximity')\n",
    "plt.xlabel('Total Rooms', fontsize=14, labelpad=10)\n",
    "plt.ylabel('Population', fontsize=14, labelpad=10)\n",
    "plt.gca().xaxis.set_major_formatter(FuncFormatter(dw.thousands))  # Add thousands separators on X axis\n",
    "plt.gca().yaxis.set_major_formatter(FuncFormatter(dw.thousands))  # Add thousands separators on Y axis\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calculate VIF\n",
    "\n",
    "`dw.calc_vif()` calculates the Variance Inflation Factor (VIF) for each feature in a dataset.\n",
    "\n",
    "This function calculates the VIF for each feature in the input dataset. VIF is\n",
    "a measure of multicollinearity, which indicates the degree to which a feature\n",
    "can be explained by other features in the dataset. A higher VIF value suggests\n",
    "higher multicollinearity, and a VIF value exceeding 5 or 10 is often regarded\n",
    "as indicating severe multicollinearity.\n",
    "\n",
    "By default, VIF will be calculated for all numeric columns in the `X`\n",
    "DataFrame. You can optionally specify columns with `num_columns`. You can also\n",
    "control how many decimal places are shown with `decimal`.\n",
    "\n",
    "Use this function to identify features with high multicollinearity in your\n",
    "dataset before performing further analysis or modeling."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate VIF for the numerical features in X\n",
    "vif_df = dw.calc_vif(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Features</th>\n",
       "      <th>VIF</th>\n",
       "      <th>Multicollinearity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>euribor3m</td>\n",
       "      <td>64.35</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>emp.var.rate</td>\n",
       "      <td>33.07</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>nr.employed</td>\n",
       "      <td>31.68</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>cons.price.idx</td>\n",
       "      <td>6.34</td>\n",
       "      <td>Moderate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>cons.conf.idx</td>\n",
       "      <td>2.65</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>previous</td>\n",
       "      <td>1.80</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>pdays</td>\n",
       "      <td>1.61</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>campaign</td>\n",
       "      <td>1.04</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>age</td>\n",
       "      <td>1.02</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>duration</td>\n",
       "      <td>1.01</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Features    VIF Multicollinearity\n",
       "8       euribor3m  64.35              High\n",
       "5    emp.var.rate  33.07              High\n",
       "9     nr.employed  31.68              High\n",
       "6  cons.price.idx   6.34          Moderate\n",
       "7   cons.conf.idx   2.65               Low\n",
       "4        previous   1.80               Low\n",
       "3           pdays   1.61               Low\n",
       "2        campaign   1.04               Low\n",
       "0             age   1.02               Low\n",
       "1        duration   1.01               Low"
      ]
     },
     "execution_count": 204,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the results\n",
    "vif_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calculate PFI\n",
    "\n",
    "`dw.calc_pfi()` calculates Permutation Feature Importance for a trained model.\n",
    "\n",
    "This function calculates the Permutation Feature Importance (PFI) for\n",
    "each feature in the input dataset using a trained model. PFI measures\n",
    "the importance of each feature by permuting its values and observing\n",
    "the impact on the model's performance. Features with higher\n",
    "permutation importance scores are considered more important for the\n",
    "model's predictions.\n",
    "\n",
    "The function returns a DataFrame with the feature names, mean\n",
    "permutation importance scores, and standard deviations of the scores.\n",
    "The DataFrame is sorted in descending order based on the mean scores.\n",
    "It's just a wrapper around the Scikit-learn `permutation_importance`\n",
    "function to display the results in a convenient format.\n",
    "\n",
    "Use this function to identify the most important features for a\n",
    "trained model and gain insights into the model's behavior."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Prepare an X, y dataset\n",
    "X = df[num_columns]\n",
    "y = df['y']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 206,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-17 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-17 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-17 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-17 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-17 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-17 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-17 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-17 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-17 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-17 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-17 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-17 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-17 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-17 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-17 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-17 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-17 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-17 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-17 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-17 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-17 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-17 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-17 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-17 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-17 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-17 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-17 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-17 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-17 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-17 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-17 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-17 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-17 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-17 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-17 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-17 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-17 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-17 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-17 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-17 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-17 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-17 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-17\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>RandomForestClassifier(random_state=42)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-126\" type=\"checkbox\" checked><label for=\"sk-estimator-id-126\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;RandomForestClassifier<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.ensemble.RandomForestClassifier.html\">?<span>Documentation for RandomForestClassifier</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>RandomForestClassifier(random_state=42)</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "RandomForestClassifier(random_state=42)"
      ]
     },
     "execution_count": 206,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create and fit a Random Forest Classifier model\n",
    "model = RandomForestClassifier(random_state=42)\n",
    "model.fit(X, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate Permutation Feature Importance\n",
    "pfi_df = dw.calc_pfi(model, X, y, n_repeats=3, decimal=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Feature</th>\n",
       "      <th>Importance Mean</th>\n",
       "      <th>Importance Std</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>duration</td>\n",
       "      <td>0.1289</td>\n",
       "      <td>0.0011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>euribor3m</td>\n",
       "      <td>0.0763</td>\n",
       "      <td>0.0004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>age</td>\n",
       "      <td>0.0501</td>\n",
       "      <td>0.0004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>campaign</td>\n",
       "      <td>0.0313</td>\n",
       "      <td>0.0008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>nr.employed</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>pdays</td>\n",
       "      <td>0.0169</td>\n",
       "      <td>0.0002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>cons.conf.idx</td>\n",
       "      <td>0.0138</td>\n",
       "      <td>0.0002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>cons.price.idx</td>\n",
       "      <td>0.0133</td>\n",
       "      <td>0.0003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>previous</td>\n",
       "      <td>0.0119</td>\n",
       "      <td>0.0002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>emp.var.rate</td>\n",
       "      <td>0.0083</td>\n",
       "      <td>0.0002</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Feature Importance Mean Importance Std\n",
       "1        duration          0.1289         0.0011\n",
       "7       euribor3m          0.0763         0.0004\n",
       "0             age          0.0501         0.0004\n",
       "9        campaign          0.0313         0.0008\n",
       "8     nr.employed          0.0200         0.0002\n",
       "2           pdays          0.0169         0.0002\n",
       "6   cons.conf.idx          0.0138         0.0002\n",
       "5  cons.price.idx          0.0133         0.0003\n",
       "3        previous          0.0119         0.0002\n",
       "4    emp.var.rate          0.0083         0.0002"
      ]
     },
     "execution_count": 208,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review the results\n",
    "pfi_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Extract Coefficients\n",
    "\n",
    "`dw.extract_coef()` extracts feature names and coefficients from a trained model.\n",
    "\n",
    "This function traverses through the steps of a GridSearchCV or\n",
    "Pipeline object and extracts the feature names and coefficients from\n",
    "the final trained model. It attempts to handle transformations such as\n",
    "ColumnTransformer and feature scaling steps. However, due to the complexity\n",
    "of some transformations, and inconsistent support on tracking feature\n",
    "names, the final output feature names may be different than the input.\n",
    "\n",
    "Note: This function currently supports only single target regression\n",
    "problems. It also checks against a list of known classes that support\n",
    "coefficient extraction. This list may not be comprehensive."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create some column lists we can use to target the right kind of variables\n",
    "all_housing = list(df_housing.columns)\n",
    "num_housing = [col for col in all_housing if df_housing[col].dtype in ['int64', 'float64']]\n",
    "cat_housing = [col for col in all_housing if df_housing[col].dtype in ['object', 'category', 'string']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Prepare an X, y dataset\n",
    "X = df_housing[num_housing].drop(columns='median_house_value')\n",
    "y = df_housing['median_house_value']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a pipeline\n",
    "pipe = Pipeline([\n",
    "    ('scaler', StandardScaler()),\n",
    "    ('model', Ridge())\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-18 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-18 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-18 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-18 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-18 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-18 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-18 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-18 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-18 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-18 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-18 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-18 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-18 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-18 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-18 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-18 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-18 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-18 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-18 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-18 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-18 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-18 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-18 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-18 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-18 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-18\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;scaler&#x27;, StandardScaler()), (&#x27;model&#x27;, Ridge())])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-127\" type=\"checkbox\" ><label for=\"sk-estimator-id-127\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;scaler&#x27;, StandardScaler()), (&#x27;model&#x27;, Ridge())])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-128\" type=\"checkbox\" ><label for=\"sk-estimator-id-128\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;StandardScaler<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.StandardScaler.html\">?<span>Documentation for StandardScaler</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>StandardScaler()</pre></div> </div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-129\" type=\"checkbox\" ><label for=\"sk-estimator-id-129\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;Ridge<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.linear_model.Ridge.html\">?<span>Documentation for Ridge</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>Ridge()</pre></div> </div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('scaler', StandardScaler()), ('model', Ridge())])"
      ]
     },
     "execution_count": 212,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Fit the pipeline\n",
    "pipe.fit(X, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Feature</th>\n",
       "      <th>Coefficient</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>longitude</td>\n",
       "      <td>-76,016.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>latitude</td>\n",
       "      <td>-82,155.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>housing_median_age</td>\n",
       "      <td>8,727.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>total_rooms</td>\n",
       "      <td>-19,698.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>total_bedrooms</td>\n",
       "      <td>38,903.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>population</td>\n",
       "      <td>-38,304.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>households</td>\n",
       "      <td>22,984.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>median_income</td>\n",
       "      <td>61,808.67</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Feature Coefficient\n",
       "0           longitude  -76,016.12\n",
       "1            latitude  -82,155.60\n",
       "2  housing_median_age    8,727.70\n",
       "3         total_rooms  -19,698.35\n",
       "4      total_bedrooms   38,903.99\n",
       "5          population  -38,304.18\n",
       "6          households   22,984.43\n",
       "7       median_income   61,808.67"
      ]
     },
     "execution_count": 213,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Extract the feature names and coefficients\n",
    "dw.extract_coef(pipe, X,)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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