{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "9d6173eb",
   "metadata": {},
   "source": [
    "# Detect High Data Drift \n",
    "<b>With this tutorial you:</b><br />\n",
    "Understand how to use Eurybia to detect datadrift\n",
    "\n",
    "Contents:\n",
    "- Detect data drift  \n",
    "- Compile Drift over years\n",
    "\n",
    "This public dataset comes from :\n",
    "\n",
    "https://www.kaggle.com/sobhanmoosavi/us-accidents/version/10\n",
    "\n",
    "---\n",
    "Acknowledgements\n",
    "- Moosavi, Sobhan, Mohammad Hossein Samavatian, Srinivasan Parthasarathy, and Rajiv Ramnath. “A Countrywide Traffic Accident Dataset.”, 2019.\n",
    "- Moosavi, Sobhan, Mohammad Hossein Samavatian, Srinivasan Parthasarathy, Radu Teodorescu, and Rajiv Ramnath. \"Accident Risk Prediction based on Heterogeneous Sparse Data: New Dataset and Insights.\" In proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM, 2019.\n",
    "---\n",
    "\n",
    "In this tutorial, the data are not loaded raw, a data preparation to facilitate the use of the tutorial has been done. You can find it here : \n",
    "https://github.com/MAIF/eurybia/blob/master/eurybia/data/dataprep_US_car_accidents.ipynb"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d83e6e7f",
   "metadata": {},
   "source": [
    "**Requirements notice** : the following tutorial may use third party modules not included in Eurybia.  \n",
    "You can find them all in one file [on our Github repository](https://github.com/MAIF/eurybia/blob/master/requirements.dev.txt) or you can manually install those you are missing, if any."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9aba586c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from category_encoders import OrdinalEncoder\n",
    "import catboost\n",
    "from eurybia import SmartDrift\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn import metrics\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6bc05d7f",
   "metadata": {},
   "source": [
    "## Import Dataset and split in training and production dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "391f650d",
   "metadata": {},
   "outputs": [],
   "source": [
    "from eurybia.data.data_loader import data_loading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f20754e8",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_car_accident = data_loading(\"us_car_accident\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8ed3eb88",
   "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>Start_Lat</th>\n",
       "      <th>Start_Lng</th>\n",
       "      <th>Distance(mi)</th>\n",
       "      <th>Temperature(F)</th>\n",
       "      <th>Humidity(%)</th>\n",
       "      <th>Visibility(mi)</th>\n",
       "      <th>day_of_week_acc</th>\n",
       "      <th>Nautical_Twilight</th>\n",
       "      <th>season_acc</th>\n",
       "      <th>target</th>\n",
       "      <th>target_multi</th>\n",
       "      <th>year_acc</th>\n",
       "      <th>Description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>33.0</td>\n",
       "      <td>-117.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3</td>\n",
       "      <td>Day</td>\n",
       "      <td>winter</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2019</td>\n",
       "      <td>At Carmel Mountain Rd - Accident.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>29.5</td>\n",
       "      <td>-98.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>4</td>\n",
       "      <td>Day</td>\n",
       "      <td>summer</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2017</td>\n",
       "      <td>At TX-345-SP/Woodlawn Ave/Exit 567B - Accident.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>32.7</td>\n",
       "      <td>-96.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Night</td>\n",
       "      <td>summer</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2021</td>\n",
       "      <td>Incident on RUGGED DR near BERKLEY AVE Expect ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>40.0</td>\n",
       "      <td>-76.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>4</td>\n",
       "      <td>Day</td>\n",
       "      <td>spring</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2020</td>\n",
       "      <td>At PA-741/Rohrerstown Rd - Accident.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>41.5</td>\n",
       "      <td>-81.8</td>\n",
       "      <td>1.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Day</td>\n",
       "      <td>summer</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2020</td>\n",
       "      <td>At 117th St/Exit 166 - Accident.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Start_Lat  Start_Lng  Distance(mi)  Temperature(F)  Humidity(%)  \\\n",
       "0       33.0     -117.1           0.0            40.0         93.0   \n",
       "1       29.5      -98.5           0.0            83.0         65.0   \n",
       "2       32.7      -96.8           0.0            88.0         57.0   \n",
       "3       40.0      -76.3           0.0            61.0         58.0   \n",
       "4       41.5      -81.8           1.0            71.0         53.0   \n",
       "\n",
       "   Visibility(mi)  day_of_week_acc Nautical_Twilight season_acc  target  \\\n",
       "0             2.0                3               Day     winter       0   \n",
       "1            10.0                4               Day     summer       1   \n",
       "2            10.0                0             Night     summer       0   \n",
       "3            10.0                4               Day     spring       0   \n",
       "4            10.0                0               Day     summer       0   \n",
       "\n",
       "   target_multi  year_acc                                        Description  \n",
       "0             2      2019                  At Carmel Mountain Rd - Accident.  \n",
       "1             3      2017    At TX-345-SP/Woodlawn Ave/Exit 567B - Accident.  \n",
       "2             2      2021  Incident on RUGGED DR near BERKLEY AVE Expect ...  \n",
       "3             2      2020               At PA-741/Rohrerstown Rd - Accident.  \n",
       "4             2      2020                   At 117th St/Exit 166 - Accident.  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_car_accident.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e2c4a06a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(50000, 13)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_car_accident.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "7a696ca4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Let us consider that the column \"year_acc\" corresponds to the reference date. \n",
    "#In 2016, a model was trained using data. And in next years, we want to detect data drift on new data in production to predict\n",
    "df_accident_baseline = df_car_accident.loc[df_car_accident['year_acc'] == 2016]\n",
    "df_accident_2017 = df_car_accident.loc[df_car_accident['year_acc'] == 2017]\n",
    "df_accident_2018 = df_car_accident.loc[df_car_accident['year_acc'] == 2018]\n",
    "df_accident_2019 = df_car_accident.loc[df_car_accident['year_acc'] == 2019]\n",
    "df_accident_2020 = df_car_accident.loc[df_car_accident['year_acc'] == 2020]\n",
    "df_accident_2021 = df_car_accident.loc[df_car_accident['year_acc'] == 2021]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "eb0e855a",
   "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>target</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year_acc</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>71.406287</td>\n",
       "      <td>28.593713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>67.254620</td>\n",
       "      <td>32.745380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>66.634662</td>\n",
       "      <td>33.365338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>79.551182</td>\n",
       "      <td>20.448818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020</th>\n",
       "      <td>89.944804</td>\n",
       "      <td>10.055196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021</th>\n",
       "      <td>98.259930</td>\n",
       "      <td>1.740070</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "target            0          1\n",
       "year_acc                      \n",
       "2016      71.406287  28.593713\n",
       "2017      67.254620  32.745380\n",
       "2018      66.634662  33.365338\n",
       "2019      79.551182  20.448818\n",
       "2020      89.944804  10.055196\n",
       "2021      98.259930   1.740070"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#We will train a classification model to predict the severity of an accident. 0 for a less severe accident and 1 for a severe accident.\n",
    "#Let's check percentage in class 0 and 1\n",
    "pd.crosstab(df_car_accident.year_acc, df_car_accident.target, normalize = 'index')*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a0c9e6b0",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_df_learning=df_accident_baseline['target'].to_frame()\n",
    "X_df_learning=df_accident_baseline[df_accident_baseline.columns.difference([\"target\", \"target_multi\", \"year_acc\", \"Description\"])]\n",
    "\n",
    "y_df_2017=df_accident_2017['target'].to_frame()\n",
    "X_df_2017=df_accident_2017[df_accident_2017.columns.difference([\"target\", \"target_multi\", \"year_acc\", \"Description\"])]\n",
    "\n",
    "y_df_2018=df_accident_2018['target'].to_frame()\n",
    "X_df_2018=df_accident_2018[df_accident_2018.columns.difference([\"target\", \"target_multi\", \"year_acc\", \"Description\"])]\n",
    "\n",
    "y_df_2019=df_accident_2019['target'].to_frame()\n",
    "X_df_2019=df_accident_2019[df_accident_2019.columns.difference([\"target\", \"target_multi\", \"year_acc\", \"Description\"])]\n",
    "\n",
    "y_df_2020=df_accident_2020['target'].to_frame()\n",
    "X_df_2020=df_accident_2020[df_accident_2020.columns.difference([\"target\", \"target_multi\", \"year_acc\", \"Description\"])]\n",
    "\n",
    "y_df_2021=df_accident_2021['target'].to_frame()\n",
    "X_df_2021=df_accident_2021[df_accident_2021.columns.difference([\"target\", \"target_multi\", \"year_acc\", \"Description\"])]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a8e0347a",
   "metadata": {},
   "source": [
    "## Building Supervized Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "7ca4fe9e",
   "metadata": {},
   "outputs": [],
   "source": [
    "features = ['Start_Lat', 'Start_Lng', 'Distance(mi)', 'Temperature(F)',\n",
    "       'Humidity(%)', 'Visibility(mi)', 'day_of_week_acc', 'Nautical_Twilight',\n",
    "       'season_acc']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "75deda6e",
   "metadata": {},
   "outputs": [],
   "source": [
    "features_to_encode = [col for col in X_df_learning[features].columns if X_df_learning[col].dtype not in ('float64','int64')]\n",
    "\n",
    "encoder = OrdinalEncoder(cols=features_to_encode)\n",
    "encoder = encoder.fit(X_df_learning[features])\n",
    "\n",
    "X_df_learning_encoded=encoder.transform(X_df_learning)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "8de8fb2c",
   "metadata": {},
   "outputs": [],
   "source": [
    "Xtrain, Xtest, ytrain, ytest = train_test_split(X_df_learning_encoded, y_df_learning, train_size=0.75, random_state=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c17eff5a",
   "metadata": {},
   "outputs": [],
   "source": [
    "train_pool_cat = catboost.Pool(data=Xtrain, label= ytrain, cat_features = features_to_encode)\n",
    "test_pool_cat = catboost.Pool(data=Xtest, label= ytest, cat_features = features_to_encode)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "b2928f7a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a2ae76b7cf46416c80f3f172db408232",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "MetricVisualizer(layout=Layout(align_self='stretch', height='500px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model = catboost.CatBoostClassifier(loss_function= \"Logloss\", eval_metric=\"Logloss\",\n",
    "                                    learning_rate=0.143852,\n",
    "                                    iterations=300,\n",
    "                                    l2_leaf_reg=15,\n",
    "                                    max_depth = 4,\n",
    "                                    use_best_model=True,\n",
    "                                    custom_loss=['Accuracy', 'AUC', 'Logloss'])\n",
    "\n",
    "model = model.fit(train_pool_cat, plot=True,eval_set=test_pool_cat, verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "3c3bf091",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.7589233355711246\n"
     ]
    }
   ],
   "source": [
    "proba = model.predict_proba(Xtest)\n",
    "print(metrics.roc_auc_score(ytest,proba[:,1]))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "339d1083",
   "metadata": {},
   "source": [
    "## Use Eurybia for data validation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "979f27b5",
   "metadata": {},
   "outputs": [],
   "source": [
    "from eurybia import SmartDrift"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "bcb4b433",
   "metadata": {},
   "outputs": [],
   "source": [
    "SD = SmartDrift(df_current=X_df_2017,\n",
    "                df_baseline=X_df_learning,\n",
    "                deployed_model=model, # Optional: put in perspective result with importance on deployed model\n",
    "                encoding=encoder # Optional: if deployed_model and encoder to use this model\n",
    "               )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "f0a4fa1a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: total: 0 ns\n",
      "Wall time: 0 ns\n",
      "The computed AUC on the X_test used to build datadrift_classifier is equal to: 0.6585689489728102\n"
     ]
    }
   ],
   "source": [
    "%time \n",
    "SD.compile(full_validation=True, # Optional: to save time, leave the default False value. If True, analyze consistency on modalities between columns.\n",
    "           date_compile_auc = '01/01/2017', # Optional: useful when computing the drift for a time that is not now\n",
    "           datadrift_file = \"car_accident_auc.csv\" # Optional: name of the csv file that contains the performance history of data drift\n",
    "          )\n",
    "                 "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0e097974",
   "metadata": {},
   "source": [
    "As soon as compile() method, Eurybia displays default consistency checks as warnings.<br />\n",
    "If some modalities are not present during training and are in production dataset, the deployed model will consider them wrongly.<br />\n",
    "Inversely, if some modalities are present during training and are not in production dataset, it means that some profiles are missing."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "f2d88c1b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "Report saved to ./report_car_accident_datadrift_2017.html. To upload and share your report, create a free Datapane account by running `!datapane signup`."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "SD.generate_report(    \n",
    "    output_file='report_car_accident_datadrift_2017.html',    \n",
    "    title_story=\"Data drift\",\n",
    "    title_description=\"\"\"Car accident Data drift 2017\"\"\", # Optional: add a subtitle to describe report\n",
    "    project_info_file=\"../../eurybia/data/project_info_car_accident.yml\" # Optional: add information on report\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "afc893f8",
   "metadata": {},
   "source": [
    "Eurybia is designed to generate an HTML report for analysis, and less for use in notebook mode. \n",
    "However, to illustrate functionalities, we will detail results with notebook mode analysis."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1762e71a",
   "metadata": {},
   "source": [
    "## First Analysis of results of the data drift"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9de8d0a",
   "metadata": {},
   "source": [
    "Data driftn methodology is based on the ability of a model to discriminate whether an individual belongs to one of the two datasets.\n",
    "For this purpose a target 0 is assigned to the baseline dataset and a target 1 to the current dataset.\n",
    "Then a classification model (catboost) is learned to predict this target.\n",
    "The level of capacity of the data drift classifier to detect if an individual belongs to one of the 2 datasets represents the level of difference between the 2 datasets"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1d4baec4",
   "metadata": {},
   "source": [
    "### Detection data drift performance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "2c3ecafd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Performance of datadrift classifier\n",
    "SD.plot.generate_indicator(fig_value=SD.auc, height=300, width=500, title=\"Datadrift classifier AUC\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "117022c4",
   "metadata": {},
   "source": [
    "An Auc close to 0.5 means that there is little drift"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c0dd1a7",
   "metadata": {},
   "source": [
    "### Importance of features in data drift"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "89ea4277",
   "metadata": {},
   "source": [
    "This graph represents the variables in the data drift classification model that are most important to differentiate between the two datasets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "61fc4a71",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "SD.xpl.plot.features_importance()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "723800cd",
   "metadata": {},
   "source": [
    "We get the features with most gaps, those that are most important to analyse.\n",
    "With date bias introduced, it is normal that date features are the most impacted. We will then decide to remove them.\n",
    "Let's analyse other important variables"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5776d01b",
   "metadata": {},
   "source": [
    "### Feature importance overview"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19ff31b6",
   "metadata": {},
   "source": [
    "This graph compares the importance of variables between the data drift classifier model and the deployed model. This allows us to put into perspective the importance of data drift in relation to the impacts to be expected on the deployed model. If the variable is at the top left, it means that the variable is very important for data drift classification, but that the variable has little influence on the deployed model. If the variable is at the bottom right, it means that the variable has little importance for data drift classification, and that the variable has a lot of influence on the deployed model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "e0738fdb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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LG8KKbdLh995lsfpUEgj1Oe77dCZSf62zvlpPPUzdzCa7Z6CjGF/q7f3HAffum3oguamL1jtoIPTOcHt32ty0aVPhXdhS79l53ZMOhO42eHdKjWqXUZtAaPzMsTeVjpdKA2GxXUbdO8q6j3Yx//AQxfio6v8x8DAEEMi0AIEw091H5RGIXyDoe11aQ+/GCd7dL//iL/7CaYjOirjPDPMLhKb1xQ7QNmHH+0VU73EHwmJLTcupJjlD6G6vvgdo+3GHbPc9pZZgumcV9Uu9zu7qOZH6cW+LX2pHyGoGQtvx5p6pjGJ8mfcubd2DBkI1s31PzGa3Xm+YLncOYRSbyviNzajOIbQJhO666fWVjpdKA6G3b8pZuf/Rptrjw6+P+HMEEMiPAIEwP31NSxGoioDtF3RTWLFd9Lwzdu6K6b+IDw4OFn7L+wXPvSGKt4xSwUevcz/X+2VU69PR0THhvEHzbA1E7l1K4wyEWody7bXt0GJny/nNMnmPnvCW5Z6ts6lHpTOE+my/XU+972FFNb78vshrPYq9/+p33qTbz70DbDFX22WzSQdC/XnTj/tn2bSn1Htzfm3XMfuHf/iHE46ysN1UptjPgNZH/1FEl0K736u1/fsoTCDUf4j65Cc/OWkHZHfZxZz8jIKMD5ufW65BAIF8CBAI89HPtBKBqgnYBEINUQsXLnQOvDYzS94K6Jf2bdu2Fb4Q6bVvfetbnUPhP/axjxW+SHq/4OgyrzvuuGPCYeU33XSTc06eWUZ45513OuFOQ8v111/vHJEwPDwsbW1tTjWKvf/lfa5eo2FM63PdddcVqh93ICzXXttO9W6Mo/fZfHHUIKb/uffeewth2WwAZJa42dYhTCDUMnTc7dq1a0JddNZL+0fPa4tjfGkZOsZ0JlvDgIYd9xjTPzebF1UyQ2jaoOZaRl9fn/Nb7jJK/TwV64ckl4xq+z/xiU84y3rNz6P5mSo3yxq0n20Dofrotd5++8hHPlJ4Ry/o30dhAqHpLw2qd911V+HvQdPXuvmTLo0u9qnW+LD92eU6BBCofQECYe33MS1EAAEEEEAgcgGbY1girwQFIIAAAggEFiAQBibjBgQQQAABBBDwChAIGRMIIIBANgUIhNnsN2qNAAIIIIBAqgQIhKnqDiqDAAIIWAsQCK2puBABBBBAAAEESgkQCBkbCCCAQDYFCITZ7DdqjQACCCCAQKoECISp6g4qgwACCFgLEAitqbgQAQQQQAABBBBAAAEEEKgtAQJhbfUnrUEAAQQQQAABBBBAAAEErAUIhNZUXIgAAggggAACCCCAAAII1JYAgbC2+pPWIIAAAggggAACCCCAAALWAgRCayouRAABBBBAAAEEEEAAAQRqS4BAWFv9SWsQQAABBBBAAAEEEEAAAWsBAqE1FRcigAACCCCAAAIIIIAAArUlQCCsrf6kNQgggAACCCCAAAIIIICAtQCB0JqKCxFAAAEEEEAAAQQQQACB2hIgENZWf9IaBBBAAAEEEEAAAQQQQMBagEBoTcWFCCCAAAIIIIAAAggggEBtCRAIa6s/aQ0CCCCAAAIIIIAAAgggYC1AILSm4kIEEEAAAQQQQAABBBBAoLYECIS11Z+0BgEEEEAAAQQQQAABBBCwFiAQWlNxIQIIIIAAAggggAACCCBQWwIEwtrqT1qDAAIIIIAAAggggAACCFgLEAitqbgQAQQQQAABBBBAAAEEEKgtAQJhbfUnrUEAAQQQQAABBBBAAAEErAUIhNZUXIgAAggggAACCCCAAAII1JYAgbC2+pPWIIAAAggggAACCCCAAALWAgRCayouRAABBBBAAAEEEEAAAQRqS4BAWFv9SWsQQAABBBBAAAEEEEAAAWsBAqE1FRcigAACCCCAAAIIIIAAArUlQCCsrf6kNQgggAACCCCAAAIIIICAtQCB0JqKCxFAAAEEEEAAAQQQQACB2hIgENZWf9IaBBBAAAEEEEAAAQQQQMBagEBoTcWFCCCAAAIIIIAAAggggEBtCRAIQ/TnVVddJUNDQyGewK0IIIAAAggggAACCCCAQHICBMIQ9gTCEHjcigACCCCAAAIIIIAAAokLEAhDdAGBMAQetyKAAAIIIIAAAggggEDiAgTCEF1AIAyBx60IIIAAAggggAACCCCQuACBMEQXEAhD4HErAggggAACCCCAAAIIJC5AIAzRBQTCEHjcigACCCCAAAIIIIAAAokLEAhDdAGBMAQetyKAAAIIIIAAAggggEDiAgTCEF1AIAyBx60IIIAAAggggAACCCCQuACBMEQXEAhD4HErAggggAACCCCAAAIIJC5AIAzRBQTCEHjcigACCCCAAAIIIIAAAokLEAhDdAGBMAQetyKAAAIIIIAAAggggEDiAgTCEF1AIAyBx60IIIAAAggggAACCCCQuACBMEQXEAhD4HErAggggAACCCCAAAIIJC5AIAzRBQTCEHjcigACCCCAAAIIIJAZgfb2dlmwYIG0tbVNqPOePXtk9erVMjQ0ZN2WrVu3it63fft263squdDUrb+/XxoaGqweod/vu7u7pampyer6WriIQBiiFwmEIfC4FQEEEEAAAQQQQCAzAtUMhGluNIEwzb2TwroRCFPYKVQJAQQQQAABBBBAoOoCtoFwx44dsnPnTmcmUWcOzcc9g2iu0RlC/d/r1q2bNMOos4gHDhyQzZs3i/7vLVu2TGjTrl27ZOHChc7v7d+/X5YtWyb6e/rf+rnlllvkxhtvdH5tZgjNjKH7QZs2bZKVK1c6v7Vq1SoZGBiYUI6ptynD/KE+3ztbWnX0mB7IDGEIaAJhCDxuRQABBBBAAAEEEMiMQJBAqAHPHZj0Xv1ouNOPOxDqr4vNyunvmdCngVDDnQmA3hBpwtrixYsnLEM1v+8OhE8//XQhALqDpHl2sbp4n2PC44oVKwrPykxHFqkogTBE7xEIQ+BxKwIIIIAAAggggEBmBIIEQp0hdL8fqDNzGurM73kDoXs2UEG813uRhoeHpbGxsRAYiwU2vafU77ufp7OC7mBXLBBq29/97ndPeK/Qr46Z6VgRIRCG6C0CYQg8bkUAAQQQQAABBBDIjEDYQOjeeMYbCL3BTcvS2T6zlFOR9Pc0aLo/ZgYxSCA0s4vu57iXjZaarSzVUUE200lrZxMIQ/QMgTAEHrcigAACCCCAAAIIZEYgykCoCGam7u1vf7sz++feGVS/c+ssnllyWukMoQmV7hBnM0NY6xvNEAhD/BgSCEPgcSsCCCCAAAIIIIBAZgS8yzpNxb2zfd5f63XeoymKXWN+T4Ofbuxiwl+x2b9KA2GxYGcTCEuF4cx0nk9FCYQhepJAGAKPWxFAAAEEEEAAAQQyI2BCmHt5pQlr7nP7Kg2E5vkK4n6eN/zpn5tdR4MuGfWGPxNUvTuN6hmE7h1EzXXe8wn1eVGfpRjHACEQhlAmEIbA41YEUi4wdvqk1E+bkfJaUj0EEEAAAQTiE3CHNlOqNyRVGgj1ecWWdOrve4+L0ACnO5kGDYTe+utOqPps96Yy3uMlSh07ofVyB8n4eqH6JREIQ5gSCEPgcSsCKRMYO3FMTj3ziIweflpGHn9Ixk+ekBkv/3WZcemrZercy2TKBQ0pqzHVQQABBBBAAAEEwgsQCEMYEghD4HErAikSGH3+oDz3tX+U4w9+o2itpl/xazJvxX+WqRdflqJaUxUEEEAAAQQQQCC8AIEwhCGBMAQetyKQEoEzR4flyb/9Axk7edy3Rpf+/t/IjCsW+l7HBQgggAACCCCAQFYECIQheopAGAKPWxFIgcCZ48/J8Pb/ISOPPWRVmylz5splf/A3MuWCeVbXcxECCCCAAAIIIJB2AQJhiB4iEIbA41YEUiBw9Ls75chX/1+gmpz3hhul4eY/DXQPFyOAAAIIIIAAAmkVIBCG6BkCYQg8bkUgBQLDOz8lxx/8ZqCaTL/8NXLJh/6b1M+5ONB9XIwAAggggAACCKRRgEAYolcIhCHwuBWBhAXOHD0kB7+wQU49+bNANamfMVsub/t7mXIhy0YDwXExAggggAACCKRSgEAYolsIhCHwuBWBhAVGn3tGnu78Iznz4vOBa3LZ2q0y/fJXB76PGxBAAAEEEEAgXQLeswn7+/uloSFfR00RCEOMSQJhCDxuRSBhgbMbymySkcceDFSTKXMulst+fwszhIHUuBgBBBBAIOsCW7dulS1btkxqhjkcPkj7ih1eb3O/94B6c0+QA+JXrVolTU1N0tbW5tze3t4uixcvlpUrVxaqoN/xu7u7netKffSach899N6UYdM27zVarwULFoR6hm25BEJbqSLXEQhD4HErAikQONS3RY7df1egmsx4xetl/qp1Un/eRYHu42IEEEAAAQSyLKCB8MCBA7J58+ZCM0xACxp+wgbCoaGhQh3MDJ+Guu3btwcm1u/z3lBrEwjdBRkHd70CV8RzA4EwrGBM9xMIY4KmGAQiEhh5+AfyzOc7Aj39oqUflQuvWxHoHi5GAAEEEEAg6wLFAqG2yQQy94yazsINDAxMaLIJS8Vm+cwMX7n79GHlglexmT+dYdOPmdnU5aC33XZbYebNW54GWy2jVN1L9WGpeu3fv1+WLVtWuM0bnL2zritWrHACd7HZ2EpmYm3HHDOEtlJFriMQhsDjVgRSIDB+ekSe+9o/yNHv91rVhtlBKyYuQgABBBCoQYFSgVCbqn+mocjM0GnQcs/W6WyXfszsYqkZQr/7ygVC82fmHUAtc+fOnZOWfnpn3orNBlZjhtCEQfc7ido+DX26PLWYgbv9zBBm5IeIQJiRjqKaCJQROH3ogDz39c/Ji/vuLes0/ZIrpWHVf5FpDVfgiQACCCCAQO4EygVCDTfr1q2TUksmvUHOdsmo975ygdAEMDOTVipQxRUItZx3v/vdE95D1Pqro4Zl/W/9lHrPkECYkR8xAmFGOopqIuAjcObYERn52X1yePdnZcyz62j9rAtkzptukjnXLhfdUIYPAggggAACeRQIGgiLbbpiAmO5QFjuviwFwnKbzqiDd+msd3dTAmFGfsoIhBnpKKqJgKXA6OEnnStPP/tL0eWk0y59ldTVT5X68y+S+umzLJ/CZQgggAACCNSegN+SUbPhjJmpc+/8aTNDaHOfzZJREzqTniG0XXbqfc/Qr/5RjCzeIQyhSiAMgcetCCCAAAIIIIAAApkRsN1Uptjsn00gtLmvkk1lvEsy41wyGuTYCLM5j9+S1ygGDIEwhCqBMAQetyKAAAIIIIAAAghkRqBYIDSzW+7dM4uFNrObp3enUfcyySD3ed9V1O/k3mMnwswQencs9eukYnU3v+c9z9BsHKP1u/XWW6WhocF5vHcTGu9GPX51CPPnBMIQegTCEHjcigACCCCAAAIIIJAZgSAH03uv1eWj3k1nzC6gCmCWl/rdF+Rg+jCBsNQyzlKdZXvshLutZiMe9zO97xG630Pk2ImU/qgQCFPaMVQLAQQQQAABBBBAAAEErASYIbRiKn4RgTAEHrcigAACCCCAAAIIIIBA4gI1GwjNWmX31Gwpbe+UrXtXpHI9RCBMfPxSAQQQQAABBBBAAAEEEAghUJOB0HvQowa3cutudY3x5s2bC4y228QSCEOMPG5FAAEEEEAAAQQQQACBxAVqMhB6A6A3IPqpa0DUnYpWrlxZ9lICoZ8kf44AAggggAACCCCAAAJpFqi5QGjO8HDv0qNLQgcGBibMApbqFHO/d4vYYtcTCNM8tKkbAggggAACCCCAAAII+AnUXCD0nuGhAMUOuiwV8PT3i71DeNddd0265Y/+6I/Eew6KHzh/jgACCCCAAAIIIIAAAgikRaBsIFyyZEmgeu7duzfQ9VFcHHaGUOukG9KsWLFiwpLR2267bVJ1Ozs7CYRRdCLPRAABBBBAAAEEEMidQKmzA3MHEXODay4Qql/Ydwht3zlkyWjMo5XiEEAAAQQQQAABBBIRKHYw/SE1s3QAACAASURBVC233CJtbW1Vqw+BsGqUgR5Uk4HQb5dRDXLuZaHFdhm1OXqCQBhorHExAggggAACCCCAQEYF9Pv1gQMHJu3MX81QSCBMZnAEfodww4YN0tfX59TWBC/9342Njcm0oESp5c4hLBYId+7cWXiSTRjUiwmEqepyKoMAAggggAACCCAQkUCxQGjO8tY9Nbzfr7Ua5lUuPf6toaFhUl7QV7TcR7+5A6H73oULFxZaVex4OP0989GTArZv3x6RQm0+NlAg9L5TqAPj4MGDsnHjRunp6XEGQp4+BMI89TZtRQABBBBAAAEE8ivgFwiLbeLo3ulfA57uyeE9+9u7am/BggXOMlTbQOgNiMXqmd9es2u5dSDs6uoS3UTF/VHwffv2Ob/f3NwsHR0ddqXWyFUEwhrpSJqBAAIIIIAAAgggUFbAG7RMYDOBrliA0xV7Gu6ampqKPtv7zKAzhBo4n3nmmQnvMRbbYJKuLS9gHQhXr14tg4ODhWWi2rnaiTr929LSIosWLRI9uy9PHwJhnnqbtiKAAAIIIIAAAvkVKLapjPc1K3egM0fBuY9oM7/nVnQvGw0aCPV692tf7ufqMlX3UtP89px/y60DoS4XNaFPD303gVDfHTRhMQ3HTvg3uXpXEAirZ8mTEEAAAQQQQAABBNIrYLMUc8+ePU4u0BDo3eTRvG/oDmphZwjZhKY646UqgdC8W0ggrE6n8BQEEEAAAQQQQAABBNIkYBMItb7mnT4Nhu7wVyy8lQuE5lnemT73O4PF3ltMk1lW6mIdCM0s4Pr162X+/PmFGUKzqQxLRrPS5dQTAQQQQAABBBBAAIFgAraB0Cwt9e72WeodxFJLRrV2+g6ivn9ozjo0z9bX1PT3zfuC3qMvNHzeeuutzqttfPwFrANhb2+vs5toqc/atWtlzZo1/iXW0BUsGa2hzqQpCCCAAAIIIIAAAiUFbAOheU+w2DFu7mPhNDBqqHOfbeidRTSBz1RKg6BOUplAaH7fe9KB9zgLurW8gHUg1MeYWcJij8zbclE1IBDy44UAAggggAACCCCAAAJZFggUCLWh7oPp9dd5PG7C/a8R7p2TsjwQqDsCCCCAAAIIIIAAAgjkTyBwIMwfUekWM0PIaEAAAQQQQAABBBBAAIEsCxAIQ/QegTAEHrcigAACCCCAAAIIIIBA4gJlA6E5TsK2lnl7j5BAaDsyuA4BBBBAAAEEEEAAAQTSKEAgDNErBMIQeNyKAAIIIIAAAggggAACiQsQCEN0AYEwBB63IoAAAggggAACCCCAQOIC1u8Q9vf3O4dCeg+gN7uO6tkkjY2NiTcozgoQCOPUpiwEEEAAAQQQQAABBBCotoB1IDRnEHqDX6mgWO2KpvF5BMI09gp1QgABBBBAAAEEEKimwIkTJ0T/k8Rn1qxZov/hE52AdSA0G8x4zx10n0vIpjLRdRRPRgABBBBAAAEEEEAgCYHPfe5z8o//vF1Gp0yLtfgpo6fldz+4SlpbW2MtN2+FWQdCM0NYCsi7lDQPkMwQ5qGXaSMCCCCAAAIIIJBvAQ2EGwaelEd+/cZYIV75469Lx+LLCIQRq1sHQrM0tFR9eIcw4p7i8QgggAACCCCAAAIIJCBAIEwAPcYirQOh1unQoUOydOnSSdXL21JRA8AMYYwjlaIQQAABBBBAAAEEEhEwgfDRmGcIr2SGMJb+DhQIY6lRhgohEGaos6gqAggggAACCCCAQEUCBMKK2DJzE4EwRFcRCEPgcSsCCCCAAAIIIIBAJgQ0EG4ceEoefV287xBe+eN7ZP0beYcw6kESOBC6dxXVynl3HY26wml6PoEwTb1BXRBAAAEEEEAAAQSiECAQRqGanmcGCoTm6Ili1c/je4QEwvQMZGqCAAIIIIAAAgggEI0AgTAa17Q81ToQdnV1SWdnZ8l6r127VtasWZOWdsVSDwJhLMwUggACCCCAAAIIIJCggAmEj8W8ZPQVLBmNpdetA6E5h9Ab/ExQ5BzCWPqLQhBAAAEEEEAAAQQQiFWAQBgrd+yFWQdCs1y0p6dHdGbMfIaGhqSlpcX5Zd6WjTJDGPt4pUAEEEAAAQQQQACBmAWcQPjAUxL7DOE+NpWJo6utAyEzhJO7g0AYxxClDAQQQAABBBBAAIEkBTQQ/ncnEL4z1mq8Yt898l/feKm0trbGWm7eCrMOhLxDSCDM2w8H7UUAAQQQQAABBBAQIRDW9iiwDoTKwC6jEwcDM4S1/cNB6xBAAAEEEEAAAQTOBcLHY54hfDkzhLEMv0CBUGvEOYTn+oVAGMsYpRAEEEAAAQQQQACBBAXMDCGBMMFOiLDowIEwwrpk7tEEwsx1GRVGAAEEEEAAAQQQCChQCITXxPsOoTND+AbeIQzYXYEvJxAGJmOGMAQZtyKAAAIIIIAAAghkTEAD4V888LQ8Hnsg/Jp8kkAY+WgpGwjLvTNYrGYcOxF5f1EAAggggAACCCCAAAKxChAIY+WOvTACYQhyloyGwONWBBBAAAEEEEAAgUwIpD0Q7tmzR/SIPPPRc9JtPsPDw9LY2CibNm2SlStX2txSk9cQCEN0K4EwBB63IoAAAggggAACCGRCwATCX8a8ZPRl+/yXjJpQ19/fLw0NDbJjxw4ZGBiQzZs3l7U19y1evFhWrFhBICylVWzJaE9Pj2gQ4iOOg+2/QOCFAAIIIIAAAggggEAWBZxA+KOnJfZA+JB/IPQGQG9ALOWt3+M1RN52222ioZAZwhJSNu8Qbt261ZlqzeOHQJjHXqfNCCCAAAIIIIBAvgQ0EP4PJxAujbXhL3voa/Jf3nCJtLa2lixXs4h+2traCtfod/Rdu3bJwoULi97n/vP29nYC4fj4+LhNz3Z1dUlnZ2fZS9lUxkaSaxBAAAEEEEAAAQQQyI5AkoHw0r13yqlTpyZg6cye+WigW7BgwaRA2N3dLU1NTZOQV61a5Vxr/oxAKFLxsRO9vb2ycePGCcgEwuz8YFNTBBBAAAEEEEAAAQRsBJIMhH/8mjny/ve/f0I1582bV/h1kBlCs5y0WJtvueWWCaHSxqVWrrEOhMwQTu5ylozWyo8B7UAAAQQQQAABBBAoJWAC4a9iXjL6Uoslo5W+Q+ieYeQdwjJLRm3eIVy/fr0sX748lz9BBMJcdjuNRgABBBBAAAEEciVQCISvj/cdQicQLir/DqHfLqMaGNetW1dyI0iWjPosGS0WCPO8iYz3J59AmKu/C2ksAggggAACCCCQS4GzgfAZ+VXsgXC3byDUDil3DiGB0H/Icg6hv1HJKwiEIfC4FQEEEEAAAQQQQCATAhoINyUUCNf5zBBmAjDllSQQhuggAmEIPG5FAAEEEEAAAQQQyIQAgTAT3VRxJQmEFdNxMH0IOm5FAAEEEEAAAQQQyIiACYRPxLxk9IqHdgszhNEPEutdRqOvSvZKYIYwe31GjRFAAAEEEEAAAQSCCTiBcPAZiT0QPkggDNZTlV1NIKzMzbmLQBgCj1sRQAABBBBAAAEEMiFAIMxEN1VcSQJhxXQEwhB03IoAAggggAACCCCQEQENhJudGcLfjrXGVzy4W9oXzZfW1tZYy81bYQTCED3ODGEIPG5FAAEEEEAAAQQQyIQAgTAT3VRxJQmEFdMxQxiCjlsRQAABBBBAAAEEMiJAIMxIR1VYzcwGwq1bt8qWLVucZq9YsUI2b95cksB7WKX3enNgpfsBfs/Ua5khrHDUcRsCCCCAAAIIIIBAZgRMIDywKN4lowt0yejrWTIa9UDJZCDUgKeBcPv27Y5Pe3u7LF68WFauXFnUS69taWmRhoYG589XrVrlhEhzvQbCgYGBsqGy2IMJhFEPT56PAAIIIIAAAgggkLQAgTDpHoi2/EyeQ+gNgN6A6EemAVE/bW1tzn8TCP3E+HMEEEAAAQQQQACBvApoIPzLwYMS/wzhV+U/M0MY+bDLZCDUGT4Nc01NTQ7Q/v37ZdmyZTI0NGQF5g2U3iWjNstFtSBmCK24uQgBBBBAAAEEEEAgwwIEwgx3nkXVMxkINYh1d3dPCoT9/f2FZaGl2m7eJywXHvX5mzZtmrAEVe/zflavXm0dQi36gksQQAABBBBAAAEEEEidAIEwdV1S1QpZv0OoYUtn5RYtWuSEMfPZsGGD9PX1Oe/0NTY2VrVypR5W6QyhCYN+wbHYElJtp/dz++23Ewhj6XEKQQABBBBAAAEEEEhKwATCJ2PeVObyB1kyGkefWwdCnQ0bHBycFPxKBcUoK1/JO4S2YVDrbftOIUtGo+xlno0AAggggAACCCCQBgEnED54UGIPhIMEwjj63zoQLlmyxKlPc3OzdHR0FOpmZgj1N/bu3RtHncVvl1HzTqBZFur9tbeSGjDNsRXDw8POTKd7SWqpRhEIY+luCkEAAQQQQAABBBBIUOBcIHxXrLW43AmE86S1tTXWcvNWmHUgNDOEpYC8S0mjhix3DqE3AOoSUz1WwvsxS0c1EO7cubPwx973BwmEUfcmz0cAAQQQQAABBBBIq4AGwk85M4TxB8I/JxBGPiysA6FZGlqqRnG+Qxi5imUBzBBaQnEZAggggAACCCCAQGYFCISZ7TqrilsHQn3aoUOHZOnSpZMeHNdSUasWxXgRgTBGbIpCAAEEEEAAAQQQSETABMKnYp4hvGzwq8IMYfRdHigQanXc7wyaA9719+PaYTR6EvsSCIT2VlyJAAIIIIAAAgggkE2BQiB8Q7xLRp1AeA3vEEY9agIFQrOxjKmUBsKDBw/Kxo0bpaenxzmoPU8fAmGeepu2IoAAAggggAAC+RQ4GwifladiD4R3EwhjGHLWgbCrq0s6OzsnVEkD4b59+5zf9+4+GkPdEy+CQJh4F1ABBBBAAAEEEEAAgYgFNBD+z4QC4SeYIYy4d0WsA6H7HEKtlR5Sr4GwoaFBWlpaJh1YH3nNU1AAgTAFnUAVEEAAAQQQQAABBCIVIBBGypv4w60DoS4XNUdLmB1Hzc6iJizmbXMZAmHi45cKIIAAAggggAACCEQsYALh0zEvGb108G5hhjDizpUAM4TlAqF5t5BAGH2HUQICCCCAAAIIIIAAAnEKOIHwoWcl9kD4IwJhHP1sPUNoZgHXr18v8+fPLywZNZvKxH0wfRw4fmUwQ+gnxJ8jgAACCCCAAAIIZF2AQJj1Hixff+tA2Nvb6+wmWuqzdu1aWbNmTW1reVpHIMxVd9NYBBBAAAEEEEAglwIaCP+XM0N4U6ztv/RHd8ufXdMgra2tsZabt8KsA6HCmFnCYkh5Wy6qBgTCvP240F4EEEAAAQQQQCB/AgTC2u7zQIFQKdwH0+uv83jchBkSBMLa/uGgdQgggAACCCCAAAIiBMLaHgWBA2FtcwRrHYEwmBdXI4AAAggggAACCGRPwATCZ94Y75LRS3TJ6OtYMhr1iCEQhhAmEIbA41YEEEAAAQQQQACBTAgQCDPRTRVX0joQ6tESusPo8uXLKy6s1m4kENZaj9IeBBBAAAEEEEAAAa+ABsK/emhY4p8hvEv+1GKGcM+ePc5eJ+YzNDRUthP1O7z7475+x44dsm7dugl/vmLFCtm8eXPNDoxAgdCtkMddRb2jgEBYsz8XNAwBBBBAAAEEEEDg3wTSHAiHh4elsbFR+vv7paGhQTTQDQwMlAxw+/fvl4ceekhWrlzptE6v37lzp2zfvr3w63L31+KgqDgQEg7ZZbQWfyBoEwIIIIAAAggggMBEgTQHQm8A9AZEv77UgLhs2TIxs4R+gdLveVn8c+tAqI3T5N3W1la2nVu3bnVSeh4+zBDmoZdpIwIIIIAAAgggkG8BJxDuG5aDMW8qM/8B/yWjmj30484o+h19165dsnDhQt+O0/t1yal7htC9ZLTWl4sqUKBAWExU3y30fvLyriGB0PdnjAsQQAABBBBAAAEEMi6QZCCc+a0eOXr06ARBndUzn/b2dlmwYMGkQNjd3S1NTU0l5d3vCpZ751C/72/atKmwxDTjXVm0+oECoc0MoZayaNEi0U6o9Q+BsNZ7mPYhgAACCCCAAAIInAuE744VQ2cI/+Tql8iHP/zhCeVOnTq18OuwM4RmQ5pSoTAPS0itA2GxmUDTEz09PaLhyB0Y9+7dG+uASaIwAmES6pSJAAIIIIAAAgggEKeABsLbnCWj8QfCW183V1pbW0s2N+w7hH7vHBIIXfTeQFjsXUFN1i0tLc5dBMI4f0wpCwEEEEAAAQQQQACBaATSHAj9dhk1S0Pdm8Zcc801hfcLvX+uS1DNERPm2X7LT6NRj++pgWYI/d4NNIGQJaPxdSAlIYAAAggggAACCCAQpYAJhM8ujneGcN4Dd8mtv15+hlDbXe4cQm/gM7uKur3cy0U1EOoxFOZT6+8PajutA6FB2bBhg/T19RWQmpubpaOjI8oxmNpns2Q0tV1DxRBAAAEEEEAAAQSqJJD2QFilZub2MYECYbn3CPOwRNQ7SgiEuf25oeEIIIAAAggggEBuBM4GwkMS/wzhv1rNEOamIyJqqHUg7Orqks7OzpLVWLt2raxZsyaiaqbzsQTCdPYLtUIAAQQQQAABBBConoAGwk8nFAj/xGLJaPVams8nWQfC1atXy+DgoHiDnwmKeXlv0D1MCIT5/KGh1QgggAACCCCAQJ4ECIS13dvWgdAsFzVHTBiWvO0sSiCs7R8IWocAAggggAACCCAwUcAJhD9OYMnowL8KM4TRj0brQMgM4eTOYIYw+gFKCQgggAACCCCAAALJCphAOBzzLqMNBMJYOt46EPIOIYEwlhFJIQgggAACCCCAAAKpEiAQpqo7ql4Z60CoJbPL6ER/ZgirPh55IAIIIIAAAggggEDKBDQQ/vWPD8nw4vfEWjOdIfzjX79YWltbYy03b4UFCoSKwzmE54YIgTBvPy60FwEEEEAAAQQQyJ8AgbC2+zxwIKxtjmCtIxAG8+JqBBBAAAEEEEAAgewJFALhkgRmCK9mhjDqEUMgDCFMIAyBx60IIIAAAggggAACmRAwgfBQzIFwri4ZJRBGPkYIhCGICYQh8LgVgX8TGHvxeamrr5OxY4dl7OjTUn/BpVJ33sVSJ+NSN+tCnBBAAAEEEEAgYQECYcIdEHHxZQNhuU1kitVr7969EVc3XY8nEKarP6hNxgTOnJbxE8/LyA96ZOyFZydVvn7OfJl17QdEZp4vMmV6xhpHdRFAAAEEEKgdgbOB8LDEP0P4FWYIYxhGBMIQyATCEHjcmm+BM6dl9KmH5eT9O3wdZrx5pUy95DUiUwmFvlhcgAACCCCAQAQCGgj/JqFA+J9YMhpBj058JIEwBDGBMAQet+ZaYOyFg3Li65+xNpj1jjapnzPP+nouRAABBBBAAIHqCTiB8CcJzBDu/YoQCKvXj6WexDuEIYwJhCHwuDW3AuMvPicnvvtPMn78sLVB/fkNMuO3PiL1sy+wvocLEUAAAQQQQKA6AiYQHo55U5mLCYTV6UCfpwQOhMXeK9y9e7fMnTs3lgqnqRACYZp6g7pkRUDfFzzx9a2Bqzv7xo9L3fkNge/jBgQQQAABBBAIJ0AgDOeX9rutA2F/f7+0tbWVbM/WrVulsbEx7e2tav0IhFXl5GE5EThz4Mcyct8dgVs78zdWyZTLrw58HzcggAACCCCAQDiBc4HwveEeFPDuszOEL5HW1taAd3J5EAHrQLh69WoZHBws+exFixZJd3d3kLIzfy2BMPNdSAMSEDh5/xdl9InSf5eUqtLUKxbJjDfdnECNKRIBBBBAAIF8C2gg3PKTw3J4SfyB8BYCYeSDzzoQmqWizc3N0tHRUajYhg0bpK+vz/k1x05E3l8UgEDmBUYff0BOPvDlwO2Ysfh9MvVlbwx8HzcggAACCCCAQDiBQiB8UwKB8LXMEIbrPf+7rQOhmSH0Lg01S0mZIfTH5goEEBAZf/4pefGbnYEpZr19rdRfeFng+7gBAQQQQAABBMIJEAjD+aX9butAaIKfd4awVFBMe8OrUT+WjFZDkWfkTWDs2LCc+Obfi5w5Zd30uqkzZebbfl/qz8/f5lXWSFyIAAIIIIBARAImEB6JeYbwJXu/IrcwQxhRr557rHUgLLa7aLna5WH5KIEw8vFJATUqMPrkT+XkD3usWzfjNz8gUy9baH09FyKAAAIIIIBA9QTOBsIjEn8gvJNAWL1uLPkkAmEIZAJhCDxuzbfA6RNy6uf9cvrhe30dpr327TLtyt+Quumzfa/lAgQQQAABBBCovoAGwv+dUCD8I2YIq9+hnicSCEMQEwhD4HFr7gXGTxyVM88+IicHdIOZ8ckedfWiG8lMabhS6mZxIH3uBwwACCCAAAKJCTiB8KcJzBDef6cQCKPvdutAGH1VslcCgTB7fUaN0yegB9WPHz8iZ44ckLHnDkj9RQtkysVXSN2sC6X+gvnpqzA1QgABBBBAIGcCBMLa7vDAgdB9zITuOGo+eTuUXttNIKztHw5ahwACCCCAAAIIICBiAuFzMW8qcxEzhLEMv0CB0LuxjAbCgwcPysaNG6Wnp8cJSHn6EAjz1Nu0FQEEEEAAAQQQyKcAgbC2+906EHZ1dUln58SzwzQQ7tu3z/l973EUSbOtWrVKBgYGnGps2rRJVq5cWbJK2o4tW7YU/tzvenMhgTDpXqZ8BBBAAAEEEEAAgagFzgXCZVEXNeH5Z2cIL5LW1tZYy81bYdaB0H3eoCK1tbWJBqmGhgZpaWmRNB1Mb5ayah31o8Ft165dsnBh8W3r29vbZfPmzc61w8PDostfy11PIMzbjwntRQABBBBAAAEE8iuggfBvf3pEnntz/IHw4wsJhFGPPOtAqMtFTegzh9Rr8NLwZMJiWs4e9AZAb0D0Q9XZRQ2TTU1NZS9lhtBPkj9HAAEEEEAAAQQQyLoAgTDrPVi+/lUJhObdwjQEQjPDp6FVZy/1s2PHDmf5qJkF9OtSvxlFZgj9BPlzBBBAAAEEEEAAgVoRMIHw+ZhnCC+8/06xmSHcs2ePM0FlPkNDQ76TOu4L/K6vlX4s1Q7rQGhmAdevXy/z588vLBk1m8qkZcno/v37ZdmyZeINhDt37pTt27f79qfOJh44cGBSeLz//vsn3fuBD3xA8j6AfEG5AAEEEEAAAQQQQCDTAmkOhN7JIL+JIM0KDz30UGF/Eb3eNidkuhPLVN46EPb29jq7iZb6rF27VtasWZO4U5gZQg2D+i8MxYKjvmfo/ejgIRAm3uVUAAEEEEAAAQQQQCBCgbOB8DmJf4Zwl+8MoTcAFssC5WjMZFKev9NbB0KFNLOExVDTsFzU1KuSdwjLhcFSg4h3CCP8m4dHI4AAAggggAACCKRCQAPh1v0JBML7dskfvOo80VV57s/s2bMLvyy2V4jt61/6kEoyQCo6pYqVCBQItVz3wfT667QdN2E6Vv+71C6jOkjcR0uY2T/bdwzdwTPP/5pQxXHIoxBAAAEEEEAAAQRSKpBkIJzyzX+W48ePT5B58MEHC7/W7/ELFiwofO/XP9Dv+t3d3WU3iNSZxXXr1jnPyfv3+cCBMKXjdFK1yp1D6A6EZlrZ+4DFixf7vnPIDGFWRgP1RAABBBBAAAEEEKhUIMlA2OZz7ETYGUKzIU2eQ2HNBsJKB3yQ+wiEQbS4FgEEEEAAAQQQQCCLAiYQHo15l9EL7tslfoEw7DuEQd85zGL/+dXZKhAeOnRIli5dWvRZPT09zrRsHj8Ewjz2Om1GAAEEEEAAAQTyJXAuEDbH2vCzgfBCaW1tLVmu3y6jZmmomQHUX19zzTWycOFC55neP4+1gSkpzDcQet8ZLFbvNL5HGIcvgTAOZcpAAAEEEEAAAQQQSFJAA+Fn9j8nR38j/kD4sV8rHwjVpdw5hN7AZ3YVdXvmebmoOpQNhH5HTbgh9XzC5cuXJzlWYy+bQBg7OQUigAACCCCAAAIIxCyQ9kAYM0fNFVc2ELqPmSh2zqA7MOZxlpBAWHM/DzQIAQQQQAABBBBAwCNAIKztIVE2EC5ZssRp/aJFi5ytW4t93EtK03QWYRzdRiCMQ5kyEEAAAQQQQAABBJIUMIHwhZiXjM65b5fYLBlN0qYWyrYKhMVmB03ju7q6pLOz0/klgbAWhgRtQAABBBBAAAEEEEDgnMDZQPi8xB8I+wiEMQxEAmEIZGYIQ+BxKwIIIIAAAggggEAmBJxA+HACgfCHBMI4BohVILStCDOEtlJchwACCCCAAAIIIIBANgQ0EP6fhALhf7TYZTQbiumtJYEwRN8wQxgCj1sRQAABBBBAAAEEMiFAIMxEN1VcSQJhxXQiBMIQeNyKAAIIIIAAAgggkAkBEwiPxbypzPk/7BNmCKMfIr4H00dfheyWQCDMbt9RcwQQQAABBBBAAAE7AQKhnVNWryIQhug5AmEIPG5FAAEEEEAAAQQQyITAuUC4PNb6np0hvEBaW1tjLTdvhREIQ/Q4gTAEHrcigAACCCCAAAIIZEJAA+HfPfy8HPvN+APhH76GQBj1ICEQhhAmEIbA41YEEEAAAQQQQACBTAgQCDPRTRVXkkBYMR2byoSg41YEEEAAAQQQQACBjAgQCDPSURVWk0BYIZzexgxhCDxuRQABBBBAAAEEEMiEgAmEx2NeMnreD/uEJaPRDxECYQhjAmEIPG5FAAEEEEAAAQQQyITA2UB4VOIPhL0EwhhGSEWBsLe3VzZu3OhUb/fu3TJ37twYqpq+IgiE6esTaoQAAggggAACCCBQXQENhJ0/SyAQ/qBX1rKpTHU7s8jTCIQhiAmEIfC4FQEEEEAAAQQQQCATAgTCTHRTxZUkEFZMxzuEIei4FQEEEEAAAQQQQCAjAgTCjHRUhdUkEFYIp7cxQxgCj1sRQAABBBBAAAEEMiFgAuGLMW8qM5slo7GMDwJhCGYCYQg8bkUAAQQQQAABBBDIhMC5QPi+WOt7NhDOkdbW1ljLzVthFQXCvCGVai+BQU61hgAAIABJREFUkJGAAAIIIIAAAgggUOsChUB4bQKB8CoCYdTji0AYQphAGAKPWxFAAAEEEEAAAQQyIaCB8O9/dlReTCAQ/gGBMPIxQiAMQUwgDIHHrQgggAACCCCAAAKZECAQZqKbKq4kgbBiOjaVCUHHrQgggAACCCCAAAIZETCB8ETMM4SzftArzBBGP0gIhCGMmSEMgcetCCCAAAIIIIAAApkQIBBmopsqrmTgQLhhwwbp6+tzCty6dWuh4MbGxoorkdUbCYRZ7TnqjQACCCCAAAIIIGAr4ATCoRck9hnC73+ZGULbTgpxXaBAuGTJkglFaSA8ePCgbNy4UXp6epxz+fL0IRDmqbdpKwIIIIAAAgggkE8BDYT/N6FA+PtsKhP5oLMOhF1dXdLZ2TkpEO7bt8/5/ebmZuno6Ii8wmkqgECYpt6gLggggAACCCCAAAJRCBAIo1BNzzOtA+Hq1atlcHCwsEy0ra3N+d8NDQ3S0tIiixYtku7u7vS0LIaaEAhjQKYIBBBAAAEEEEAAgUQFTCAciXlTmZnf/7IwQxh911sHQl0uakJff3+/mECo7w6asLh3797oa5yiEgiEKeoMqoIAAggggAACCCAQiQCBMBLW1Dy0KoHQvFtIIExNv1IRBBBAAAEEEEAAAQSqIlAIhI3/rirPs32IM0P46vOltbXV9hauq0DAOhCaWcD169fL/PnzCzOEZlMZloxWoM8tCCCAAAIIIIAAAgikXEADYdfQCzKSQCBcYxEI9+zZ46xYNJ+hoaGSosPDw+I9HcF9/Y4dO2TdunUT7l+xYoVs3rw55b1UefWsA2Fvb6+zm2ipz9q1a2XNmjWV1ySDd7JkNIOdRpURQAABBBBAAAEEAgmkORCagKevtOneJhroBgYGSgY4DY/6aWpqcv5b90Q5cOBA4Xq/+wPBZeRi60Co7TGzhMXalrflompAIMzIKKeaCCCAAAIIIIAAAhULpDkQegOcNyD6NVoDoobC7du3O5cSCP3ERMR9ML1ensfjJgwTgdBiwHAJAggggAACCCCAQKYFTCA8GfOS0Rnf/7K0XDIu73vf+yb4LViwoPBrDXP60Q0v3d/Rd+3aJQsXLvR19wZA75LRWl8uqkCBZgh9RXN2AYEwZx1OcxFAAAEEEEAAgRwKOIHw58ck9kDY/yWZ9p2dcubMmQnq9957b+HX7e3togHRGwj1ODyzLLRUl5nZxHLhUb/vb9q0SVauXFmzPR8oEOoLl3rmoFkeeujQIVm6dGnh1zWrVKJhBMK89TjtRQABBBBAAAEE8ieggfD/JRQIP+qzqUylM4QmDPoFxzwsIbUOhCYM6o/A7t27Ze7cuVLs9/L0I0IgzFNv01YEEEAAAQQQQCCfAmkOhJW8Q2gbBrW3CYSuMe9+d7Cnp8fZUMUcUK+XsctoPv+CoNUIIIAAAggggAACtS2Q5kDot8uoeSfQHC2xf/9+WbZsmZRaJqpLUM0RE0GCY5ZHgPUMofscwuXLlxfa3NXVJZ2dncI5hFkeBtQdAQQQQAABBBBAAIHiAiYQnop5U5np/V8SvyWjWuNy5xB6A6EuMd2yZcukhpqloxoId+7cWfjzWn9/UBtqHQiXLFniwJjZQaPkXjaat6MnWDLKX5sIIIAAAggggAACtS5QCIS/dXOsTXUC4avOk9bW1ljLzVthBMIQPU4gDIHHrQgggAACCCCAAAKZECAQZqKbKq6kdSA0S0a9S0NL/X7FNcrQjQTCaDrr2ZFRGR0bkyMnz8iU+jp5yYypIjIu82dOi6ZAnooAAggggAACCCBQUkAD4Wd/fkxOJTBD+HvMEEY+Mq0DoXlXsFSN2FQm8r6q+QJeOD0m9z97TP7uJ8/KgRdPyciZcafNs6bUyYLzpsvHrr5E3tgwW+ZMq695CxqIAAIIIIAAAgikRYBAmJaeiKYe1oFQizezgcWqkrf3B9WAGcLqDcrHj52U239+WL746JGyD2151cWy8pUXyyvOn169wnkSAggggAACCCCAQEkBEwhPxzxDOK3/S8IMYfQDM1Ag1Oq4j5/QX+dxd1HTLQTC6gxQnQn8233PSM8jh60e2HpVg/zBaxtk5hRmCq3AuAgBBBBAAAEEEAgh4ATCXxyT2APh9wiEIbrN+tbAgdD6yTm4kEBYnU7+3jPH5OPf+2Wgh32m8WVy7aXnB7qHixFAAAEEEEAAAQSCC5wNhMcTCIRfZIYweHcFviNQIPTODnpLy9uyUQJh4PE26YaRM2PScf8BuefJFwI97KYrLpS/ePOCQPdwMQIIIIAAAggggEBwAQ2E3QkFwtVsKhO8wwLeYR0I/TaV0XLjDITuQyVXrFghmzdv9m36/v37ZdmyZaJnJ7o/5sBK9+/ZPJNA6Evue8HwyKh87LuPy8+PnvS91n3B1RfNkk83vlTmzdQdSPkggAACCCCAAAIIRCVAIIxKNh3PtQ6E5mD6ctWOKxDu2bNHNBBu377dqU57e7ssXrxYVq5cWbR6w8PD0tjYWPizYoFwYGDAKlS6CyAQhh/Evzh6Uj74jUdkdPzsjqK2n5lT6uT2t79Srpwzw/YWrkMAAQQQQAABBBCoQIBAWAFahm4JHAibm5ulo6Mj0SZ6A6A3IJaqnF6nO6USCBPtvgmFP/PiaWm991HRmcIgn8tmT5N/eOuVMm8WM4RB3LgWAQQQQAABBBAIKmAC4ehbbg56a6jrp37vi7L6ledJa2trqOdwc3kB60Bo3h9cv369LF++PFHXVatWSVtbmzQ1NTn1KLUU1FvJcoFw3bp1hcttlovqxcwQhh8Gh0+OSvsPn5D7h18M9LBr558vG990ucx1Dq3ngwACCCCAAAIIIBCVwLlA+P6oiij63LOBcDaBMGJ160Cos2otLS2pOGZCg1h3d/ekQNjf3y8NDQ0lyUoFQu8N+vxNmzZNWIL605/+dNJzdbbUO9sYcX/V5OP/+wNPyZcfK3/+oLfhK668WNrfcGlNetAoBBBAAAEEEEAgTQIaCP/hF8dl9C3xB8LfJRBGPhSsA2Ga3iGs9gyhV1k3mfG+U/jxj398UmfcfffdBMIqDNEDx0/J7977mBw6abds9NJZ0+Qf33YlG8pUwZ5HIIAAAggggAACfgIEQj+hbP95JgNhtd8htAmExbqZJaPVG/z7jozIR771iNUDdTOZ11400+paLkIAAQQQQAABBBAIJ0AgDOeX9rszGQj9dhk1x0h4l3OWWjKqAdMcW2F2JHUvSS3ViQTC6g3v46NjcuDYKWm/7wl57Nipog9+9QUz5FO/+VKZP2uazJ5SV73CeRICCCCAAAIIIIBASQEnED5yXM7EvGR0yne/KCwZjX5gWgfC6KsSrIRy5xB6A6H32Aktyf2OoAbCnTt3FirgfX+QQBisb8JcrbuODhw6IT86dFwee+GkTKmrk5edP11eP3e2/Ob889hEJgwu9yKAAAIIIIAAAhUInA2ELyYQCP+FQFhBfwW9JbOBMGhDo7ieGcIoVM898/DIqOjphHM5fD5aaJ6OAAIIIIAAAgiUESAQ1vbwCBQIu7q6pLOzs6RIXAfTp6VLCIRp6QnqgQACCCCAAAIIIBCVgAbCf0xohvA/sMtoVN1aeK51IOzt7ZWNGzeWrRCBMPL+ogAEEEAAAQQQQAABBGIVIBDGyh17YdaBcPXq1TI4OEggdAkwQxj7eKVABBBAAAEEEEAAgZgFTCAcuy7ecwjrv/sv8h+u5GD6qLvbOhCacwh1FnDDhg1OvTo6OkQPg29raxPd5KWxsTHq+qbq+QTCVHUHlUEAAQQQQAABBBCIQOBcIFwRwdNLP/JsIJwlra2tsZabt8ICBcJFixaJHsdglo/u3r1b5s6d6wTExx9/3PmzPH0IhHnqbdqKAAIIIIAAAgjkU4BAWNv9HigQKoWGwMOHD0tLS4usX79eli9fLmY5Ke8Q1vZgoXUIIIAAAggggAAC+RPQQPhPj7woY9fFP0P4EWYIIx9w1oHQhD4zS2iWkLprSCCMvL8oAAEEEEAAAQQQQACBWAUIhLFyx16YdSA0y0Sbm5uddwd1mWhfX1+hwub3Y29BggWyZDRBfIpGAAEEEEAAAQQQiEXACYSPJjBD+J1/EWYIo+9i60CoVdEQePnll8uaNWvk0KFDsnTp0kIN8zY7qA0nEEY/QCkBAQQQQAABBBBAIFkBEwjHY14yWkcgjKXjAwXCWGqUoUIIhBnqLKqKAAIIIIAAAgggUJHA2UB4QuIPhDuZIayox4LdRCAM5jXhagJhCDxuRQABBBBAAAEEEMiEgAbCzyUUCFvZVCbyMWIdCM0mMt7zBs05hGazmchrnKICCIQp6gyqggACCCCAAAIIIBCJAIEwEtbUPDR0IBwaGnKOoNBP3t4jJBCmZhxTEQQQQAABBBBAAIGIBAqBsCneYyfqvrNTWl/BwfQRdWvhsWUDoTlqwrYSBEJbKa5DAAEEEEAAAQQQQCAbAiYQSsyBUCwD4Z49e5xz0c1HJ6xKfYaHh6WxsXHCH5e7Phs9FK6WZQOhe/bPrxiWjPoJ8ecIIIAAAggggAACCGRP4FwgXBlv5Z1AOFNaW1t9A56+xtbQ0CA7duyQgYEB2bx5c9F7NDzqp6mpyflvfR3uwIEDJa+Pt8HJlOa7ZNR73mCpau7evVvmzp2bTCsSKpUlownBUywCCCCAAAIIIIBAbAJpDoTeAGhmAE1A9EPSgKihcPv27X6X1uyf+wZC0/JSm8rUrIxFwwiEFkhcggACCCCAAAIIIJBpAQ2E2x49IdIU/wzhb88+Ku9617sm+L3uda8r/FrDnH7a2toKv6ff0Xft2iULFy70dfebUfR9QA1cYB0Ia6CtVW8CgbDqpDwQAQQQQAABBBBAIGUCTiB8LIFAuGenTPv+l2X69OkTRL785S8Xft3e3i4LFiyYFAi7u7sLy0JLcZrZRNvwmLJuqVp1rAOhvqipL2CuWbOmaoVn/UEEwqz3IPVHAAEEEEAAAQQQ8BMwgbAu5hnC8T075d/7vENY6QyhCYM2wdHPJ+t/bh0IzZLRtWvXEgr/rdcJhFkf/tQfAQQQQAABBBBAwE/gbCAckfgD4Q7fQFjJO4SEwYk9bh0Iu7q6pLOz07k7b8dLlPohIRD6/fXBnyOAAAIIIIAAAghkXSDNgdC7iYw3IOqv161bJ+Zoif3798uyZcus3zHMet/Z1N86EJoZwnIPzVtQJBDaDDGuQQABBBBAAAEEEMiygAbC2xOaIfywz5JRdS13DqE3EOoS0y1btkzqjjwvHSUQhvjpJBCGwONWBBBAAAEEEEAAgUwIFALhW+PdZXR8zw758MvLn0OYCcCUV5JAGKKDCIQh8LgVAQQQQAABBBBAIBMCBMJMdFPFlbQOhBWXUMM3EghruHNpGgIIIIAAAggggIAjYAJh/Vt/J1aRMWeGcIa0trbGWm7eCiMQhuhxAmEIPG5FAAEEEEAAAQQQyIQAgTAT3VRxJQMHwg0bNkhfX1+hwObmZuno6Ki4Alm+kUCY5d6j7ggggAACCCCAAAI2AhoIP//YiCQxQ/ghZghtuijUNYECYbmdRvO2w6iqEwhDjT1uRgABBBBAAAEEEMiAAIEwA50UoorWgdB9DmGx8vJ4YD2BMMTI41YEEEAAAQQQQACBTAg4gfDxBGYIv71DmCGMfohYB8LVq1fL4OCgeIOfCYqLFi0SPb8jTx8CYZ56m7YigAACCCCAAAL5FDCBcErMm8qcIRDGMuCsA6FZLtrT0+MslTSfoaEhaWlpcX6Zt2WjBMJYxiiFIIAAAggggAACCCQocDYQnpT4A+EdzBDG0O/WgZAZwsm9QSCMYYRSBAIIIIAAAggggECiAgTCRPkjL9w6EPIOIYEw8tFIAQgggAACCCCAAAKpE9BA+IWEZgg/yC6jkY8H60CoNWGX0Yn9wQxh5OOTAhBAAAEEEEAAAQQSFigEwuvjPZj+zLfvkA++jIPpo+7+QIFQK8M5hOe6hEAY9fDk+QgggAACCCCAAAJJC5hAODXmQDhKIIyl6wMHwlhqlZFCCIQZ6SiqiQACCCCAAAIIIFCxwLlAuKriZ1Ry49lAOF1aW1sruZ17LAUCB8Jiy0Z3794tc+fOtSyydi4jENZOX9ISBBBAAAEEEEAAgeICBMLaHhnWgbC/v1/a2tpKamzdulUaGxtrW8vTOgJhrrqbxiKAAAIIIIAAArkU0ED4z4+flKnXxz9D+AFmCCMfc9aB0Bw7UapGHEwfeV9RAAIIIIAAAggggAACsQs4gfCXCQTCe+8QAmH03W0dCM1S0ebmZuno6CjUzL3JDAfTR99hlIAAAggggAACCCCAQJwCBMI4teMvyzoQmhlC79JQs5SUGcL4O48SEUAAAQQQQAABBBCIWuBsIDwl02JeMnr63u3MEEbduSJiHQhN8PPOEJYKijHUPfEieIcw8S6gAggggAACCCCAAAIRCxAIIwZO+PHWgbDcofTF2pCH5aMEwoRHL8UjgAACCCCAAAIIRC6ggbAnoRnCFjaVibx/CYQhiAmEIfC4FQEEEEAAAQQQQCATAoVA+LZ4dxnVJaMtL+UcwqgHCYEwhDCBsDTe2KkRERkXOTMqdVOnidRPlbopU0NocysCCCCAAAIIIIBAEgIEwiTU4yvTOhDGV6XslEQgnNxX46dG5OSBfTI2clzGRo7J+Nio1E+fLfUzz5dpDS+VKXMuORsQ+SCAAAIIIIAAAghkQsAEwulva4m1vqecGcJp0traGmu5eSuMQBiixwmE5/DGR0dl7MUjcuIXP3RCYKnPtLkvk+mXvlrqZ84JIc+tCCCAAAIIIIAAAnEJEAjjkk6mHAJhCHcC4Tm8seNH5Pj+b1tpTr3wMpn58tdL3bSZVtdzEQIIIIAAAggggEByAgTC5OzjKDlQIDRHTJSqWB52FnW3nUB4VkPfFzzx8B4ZO/Wi9Zid+Yo3is4W8kEAAQQQQAABBBBIt4AGwu2/OiWxLxn91nZZxZLRyAeHdSDcsGGD9PX1la0QgTDy/kplAacPH5CRR+8PVLcpsy6QWVc1MksYSI2LEUAAAQQQQACB+AUIhPGbx1midSC0OYeQQBhn16WnrJFfPiinn300WIXq6uX8a26Uummzgt3H1QgggAACCCCAAAKxCphAOCPmTWVOMkMYSz9bB0KzXHTt2rWyZs2aWCoXppBVq1bJwMCA84hNmzbJypUrfR+3Y8cO557Nmzf7XqsXsGRUZPz0STnxyH1y5tghKzP3RbNf81syZc68wPdxAwIIIIAAAggggEB8AmcD4WmJPxD2sGQ0hm62DoT9/f3S1tYmzc3N0tHREUPVKi9i69atzs1aXxPcdu3aJQsXLiz60D179ogGXv2sWLGCQBiAfvzMaRl55H4ZPXowwF1nLz3v6rdJ/awLA9/HDQgggAACCCCAAALxCaQ9ELq/y6vK0NCQFY5O7ngzgk4QrVu3bsL9QfKBVcEpu8g6EGq9/ZaNpmXJqLdzvQGxVB/odQcOHCAQBhykI796SE4ffCTQXXX1U2X2r98g9dNZMhoIjosRQAABBBBAAIGYBTQQ3qEzhG+P9xzCk9/qkd+5ovw5hMPDw9LY2Cg6edXQ0CA2K/7cKwmLBcIgKwZj7opIirMOhH47jGrt0hAIvYNC62UzMPS6coHwsccem9QB73znO63/BSKS3kvJQ0cPPyEnHt0bqDb1sy6Q2a++VuoIhIHcuBgBBBBAAAEEEIhbIM2B0Ps9v1gWKOZlriMQilgHQr/ZwbQEwv3798uyZcsK/0pgAuHOnTtl+/btZX9+ygXCj370o5PuvffeewmEou8RnpATv7hPzhw/Yv33k+4wOvWC+dbXcyECCCCAAAIIIIBAMgImEM6MeYZwxGKGsNhKwGJLQb1y5QKhe8lorS8XVRfrQJiVTWWimiEs9uPHpjLnVMZGjsvxH99j9bfU9EuvkmmXvFrqp063up6LEEAAAQQQQAABBJITOBcIPxBrJTQQXjv2pFx//fUTym1qair8ur29XRYsWFDYO0T/QL+jd3d3i/s620DovU6fZbtBZaw4VSzMOhBmaVMZ3iGs4gixfdSZURkbHZERnSk8cbTkXTMWXC3TLn6p1E2faftkrkMAAQQQQAABBBBIUCDJQDhj71fkwgsnbkKoYc98qj1D6GW2ffUswe4JXbR1IMzKklEV8dtltFTSZ1OZ0ONJxkdH5NRTP5ex0ydkfOSYjJ8ekfpZc6RuxvkyveHlUjfrAqmrnxK+IJ6AAAIIIIAAAgggEIuABsIdT5yWmW+PeYbwmz2y8oqp0traWrKd1X6HkEBYZkhlKRBqM8qdQ+gNhN6tavX+csdUGCaWjJYZMONjMj56WvRYCpkyXeqnsTw0lr+xKQQBBBBAAAEEEKiyQJoDod8uo+YYCe9RFKXeIdQlqOZMcnON3/LTKnPH/rianCGMSzHTgXBsVKR+alxUlIMAAggggAACCCCQUYE0B0IlLXcOYbFA6J440vvdG8doINTNKM2n1t8f1HZaB8KMjt9Iq53VQDg+8oKMPnaf1J03V6Ze9msiU3mfL9KBwsMRQAABBBBAAIEMC5wNhKMyK+Yloye++c++S0YzzJqaqhMIQ3RFFgOhhsGR+3bI2JEDTsunvvQamb7wBufdPj4IIIAAAggggAACCHgFCIS1PSYIhCH6N0uBcPzUCTkz/LicvH/HpBbXzTxfZvxGi0yZ0yAyZVoIEW5FAAEEEEAAAQQQqDUBDYQ7dYbwhng3ldEZwhULym8qU2vWSbSHQBhCPSuBcPzEC3LqZ/fK6OMPlG3t9NfeIFNf9gapm3FeCBVuRQABBBBAAAEEEKglAQJhLfXm5LaUDYQ2O4u6H7l3797a1vK0LvWBcPSkjJ14QU7+sEfGjh+x6pv6i18qM5fczBJSKy0uQgABBBBAAAEEal+AQFjbfUwgDNG/qQ+EY6NycvArMvqrBwO1csY1N8nUK98U6B4uRgABBBBAAAEEEKhNARMIZ8e8ZPRFlozGMqAIhCGYUx8IReTM8GMy8r1tgVo56x1tUn/eSwLdw8UIIIAAAggggAACtSlwLhB+MNYGng2EU8oeTB9rhWq0MN4hDNGxWQiE4yeel5Fvf1bGTh63amn9S66Qmb+5Suqmz7a6nosQQAABBBBAAAEEalvACYQHRmX2DTEHwm8QCOMYWQTCEMpZCIRyZlRO/miXjB7YZ9XS6Ve/U6a9+lqra7kIAQQQQAABBBBAoPYFNBD+S0KB8P3MEEY+wAiEIYgzEQhFZPTZX8jJ/i9YtXTWOz4m9eddbHUtFyGAAAIIIIAAAgjUvgCBsLb7mEAYon+zEgj1MPoT3+yU8dMjZVtbf9HlMvPaD7BcNMSY4FYEEEAAAQQQQKDWBEwgPC/mJaPHv/HPwgxh9KOJQBjCOCuBUMZGZWTvl+TMU/vLtnbawrfL9NdcF0KEWxFAAAEEEEAAAQRqTeBsIDwj8QfCLxAIYxhMBMIQyJkJhLrb6NMPy6mf3FO2tTPevErq5zSEEOFWBBBAAAEEEEAAgVoTKATCd8S7qczxb3xB3n85u4xGPZ4CB8INGzZIX1+fU6+tW7cW6tfY2Bh1XVP3/CwFwvHTJ0TGxmR8fLyoY119vdRJncj0WalzpkIIIIAAAggggAACyQloIPyizhAmEAhvJhBG3vGBAuGSJUsmVEgD4cGDB2Xjxo3S09MjGpDy9MlSIMxTv9BWBBBAAAEEEEAAgeoJEAirZ5nGJ1kHwq6uLuns7JwUCPft2+f8fnNzs3R0dKSxjZHViUAYGS0PRgABBBBAAAEEEEiJAIEwJR0RUTWsA+Hq1atlcHCwsEy0ra3N+d8NDQ3S0tIiixYtku7u7oiqmc7HEgjT2S/UCgEEEEAAAQQQQKB6AiYQnv+OD1XvoRZPOvaNL8jNl9dLa2urxdVcUqmAdSDU5aIm9PX394sJhPruoAmLe/furbQembyPQJjJbqPSCCCAAAIIIIAAAgEEnED45BmJPRB+nUAYoJsqvrQqgdC8W0ggrLgfuBEBBBBAAAEEEEAAgVQKaCD8UkKB8N8xQxj5mLAOhGYWcP369TJ//vzCDKHZVIYlo5H3FQUggAACCCCAAAIIIBC7AIEwdvJYC7QOhL29vc5uoqU+a9eulTVr1sRa+aQLY8lo0j1A+QgggAACCCCAAAJRCxAIoxZO9vnWgVCraWYJi1U5b8tF1YBAmOzgpXQEEEAAAQQQQACB6AXOBsIxmRPzpjIvfP3zwpLR6Ps3UCDU6rgPptdf5/G4CdMtBMLoByglIIAAAggggAACCCQrUAiEN8a7y6gTCC9jl9Goez9wIIy6Qll6PoEwS71FXRFAAAEEEEAAAQQqESAQVqKWnXusA6EuF9UjJvL2nmC5riQQZmegU1MEEEAAAQQQQACBygQ0EH5Zl4wmMEP4PmYIK+u0AHdZB0JztEQeN48p5UkgDDDSuBQBBBBAAAEEEEAgkwIEwkx2m3WlrQNhV1eXdHZ2Og/O4wYyxUQJhNbjjAsRQAABBBBAAAEEMipgAuEFMc8QHv3654UZwugHjXUgNDOE5aqUt6BIIIx+gFICAggggAACCCCAQLICTiB8akwuuPHDsVbk6D0aCOuktbU11nLzVhiBMESPEwhD4HErAggggAACCCCAQCYECISZ6KaKK0kgrJiOcwhD0HErAggggAACCCCAQEYENBD2JjRDuJwZwshHiXUgjLwmGSyAGcIMdhpVRgABBBBAAAEEEAgkQCAMxJW5iwmEIbqMQBgCj1sRQAABBBBAAAEEMiGQ9kC4Z88e0SPyzGdoaMjKVb/L79q1SxYuXGh1fa1eZB0I2VRm8hAgENbqjwXtQgABBBBAAAEEEDACZwPhuFz4zng3lXn+nttl+aXlN5UZHh52zkrv7++XhoYG2bFjhwwMDMjmzZtLduCqVauca/RDIBQhEIb4WSeShOsWAAAgAElEQVQQhsDjVgQQQAABBBBAAIFMCKQ5EHoDoDcglgI21xEICYShfggJhKH4uBkBBBBAAAEEEEAgAwIaCPsSmiFs9pkh3Lp1qyPY1tZWkLRZCkogPDfwrGcIS41VXa87ODgoPT09ovh5+hAI89TbtBUBBBBAAAEEEMinQJKB8LUv/FyuvfbaCfDvec97Cr9ub2+XBQsWTAqE3d3d0tTUVLLDCIRVDIS9vb2yceNGaW5ulo6Ojlz9lBAIc9XdNBYBBBBAAAEEEMilQJKBcPqPvirz5s2b4L5ly5bCr5khDD8kQ88QbtiwQfr6+pya7N27N3yNMvQEAmGGOouqIoAAAggggAACCFQk4ATCp8flonf++4rur/Sm5752uzRfKtLa2lryEbxDWKnuufusAyG7jE7GJhCGH4A8AQEEEEAAAQQQQCDdAmkOhH67jGpgXLdunXiPomDJaASBcO3atbJmzZp0j+Yq145AWGVQHocAAggggAACCCCQOoE0B0LFKncOYbFA6D52Qu9fsWJF2WMqUtchVa5QVWYI8/j+oPYDgbDKo5HHIYAAAggggAACCKROQAPhroSWjC7zWTKaOqwMVsg6EGawbZFXmUAYOTEFIIAAAggggAACCCQsQCBMuAMiLp5AGAKYQBgCj1sRQAABBBBAAAEEMiFwNhCKvCTmTWWOfG2bMEMY/RCxDoRmUxnd2rWxsbFQs/7+fufcj0WLFome95GnD4EwT71NWxFAAAEEEEAAgXwKFALh0nh3GXUC4SXldxnNZ49Ut9WhA6Hu2NPS0uLUimMnqts5PA0BBBBAAAEEEEAAgaQFCIRJ90C05ZcNhKtXr5bBwUHrGhAIram4EAEEEEAAAQQQQACBTAhoILxTl4wmMEP4XmYIIx8jZQOhe/bPryYsGfUT4s8RQAABBBBAAAEEEMieAIEwe30WpMa+S0Y3bNggfX19vs/cvXu3zJ071/e6WrqAdwhrqTdpCwIIIIAAAggggEAxAQJhbY8L30Boml9qU5na5infOgJhDff+mVMip0Zk7MQxqZsxS+rOe0kNN5amIYAAAggggAACpQU0EH7lGZGLY14yenj3NnkPS0YjH5rWgVBr0tXVJZ2dnSUrxTuEkfcXBUQtcPw5Of3QN2T8yJMy9tzTMn70kEy5eIHUveRSqX/lEpnysqtFps6IuhY8HwEEEEAAAQQQSI2ABsJ/fUZkbsyB8NDubfJuAmHk48A6EPb29srGjRvLVijOQKjHX2zZssWpz4oVK2Tz5s1l61bu+h07dsi6desm3G/zTGYIIx+fsRYwfvSgnLr772Ts2V+WLHfaNTfI1EXvFLlwfqx1ozAEEEAAAQQQQCApARMIG3473mMnhjUQzufYiaj73ToQ2uw4Glcg3LNnj2jA2759u+PT3t4uixcvlpUrVxb18rteA+HAwIBvqPQ+nEAY9fCM7/njx4/Iyc99QsbHxnwLnfqqN8nUt35I6mZf4HstFyCAAAIIIIAAAlkX0EB41zMi82IOhM/u3iY3EQgjHz7WgdC8Q6ihTzea0U9HR4eYg+m9B9ZHWXNvAPQGPm/ZftcTCKPsrfQ/e/zF5+X017rkzBM/ta7s9HeslikL32J9PRcigAACCCCAAAJZFdBAePczIvNjDoQHd2+TdxEIIx82gQKhOVrCLB81O4tqQHz88celu7s78gprAatWrZK2tjZpampyytu/f78sW7ZM9JiMYh+/671LRostFx0eHp706MbGxpJlxgJBIVURGPvlQ3Jy198EelbdeRfJjPevk7o5+dpZNxASFyOAAAIIIIBATQhoIPzqQZFLYg6Ez3x1m/w2gTDyMRQoEGptNAQePnxYWlpaZP369bJ8+XIxy0njWjKqSzU1fHoDoc5WNjQ0TEKr5PpNmzZNWIKq7fV+tL2lQmjkPUcBVRMY/dFuOf3ds8uPg3xmtv4vqZtzcZBbuBYBBBBAAAEEEMicgAbC3QkFwqUEwsjHi3UgNKHPzBKaJaTuGsYVCP1m/LxqQa+3XULKO4SRj8/oCzhzWk59/bNyZui+wGXNeO9/kvqXXxP4Pm5AAAEEEEAAAQSyJKCB8GsHRS59V7ybyjz91W3yznlsKhP1WLEOhGaZaHNzs/PuoPfAevP7UVdYn+/3TqC3DkGvJxDG0YspKWP0lJz62v+VM488ELhC0971H2Xqq5YEvo8bEEAAAQQQQACBLAloILznoMhlMQfCp766TW4kEEY+VKwDodZEQ+Dll18ua9askUOHDsnSpUsLFYxrdlALtNk1VI+RMMs5/a7XwGiOrdB3BfXdQPeS1FK9wAxh5OMzlgJGH7hbTn9vR+CyZnx4k9RfeEng+7gBAQQQQAABBBDIkoAJhJfHHAifJBDGMkwCBcJYamRZiM25gu73+8pdr4Fw586dhZK97w8SCC07JaOXnXlsUE595X8Hqn3d7Atl+vvbpf6CeYHu42IEEEAAAQQQQCBrAhoIv/6syIKYA+GBu7fJO5ghjHy4BA6E7qWiGrLMR2fV8vZhhrBGevz4c3LyX/9Wxg4+Zt2gab+1QqZec4PI1BnW93AhAggggAACCCCQRQENhN94VuSKmAPhE3dvkxsIhJEPmUCB0LuRjAbCgwcPysaNG6Wnp0c0IOXpQyCsnd4eP3pQRra1WzWo/rJXy4zf/kOR8y6yup6LEEAAAQQQQACBLAtoIPxmQoHw7QTCyIeOdSDs6uqSzs7OCRXSQLhv3z7n9+PcVCZyFcsCCISWUFm47NQJGXvuaTl11/+R8WOHS9Z4ystfL1ObPiD1F87PQquoIwIIIIAAAgggEFpAA+G3nhV56U3x7jL6q7u3ydsa2GU0dAf6PMA6EJpjJ8wyUT0YXv+3nvunZ/SZ4yiirnCank8gTFNvVKkux5+T0z/4kow9/4wTEOXFF6T+wnlSd9GlMuXl10j9K5eIHkrPBwEEEEAAAQQQyIuABsJ7nxV5WcyB8Jd3b5PrCYSRDzPrQKjLRU3o0wPgTSDUdwfjPpg+chXLAgiEllAZvGz82BGROpHxE8ekbtb5zruCdTNmZ7AlVBkBBBBAAAEEEAgn4ATCYZGXxx0I79ombyUQhus8i7urEgjNu4VxHj1h0bbILyEQRk5MAQgggAACCCCAAAIJC2gg/PawyCtiDoSP37VNmgiEkfe+dSA0s4Dr16+X+fPnF2YIzaYyLBmNvK8oAAEEEEAAAQQQQACB2AU0EO4ZFrky5kD42F3b5DoCYeT9bR0Ie3t7nd1ES33Wrl3rHFifpw8zhHnqbdqKAAIIIIAAAgjkU0AD4XeGRV757ng3lXn0rm3ylrlsKhP1qLMOhFoRM0tYrFJ5Wy6qBgTCqIdn7T//zLEjMj4+JuPHj0rd7DkidXUyZeb5UjeN8w1rv/dpIQIIIIAAAtkQ0ED43QQC4SMEwlgGSKBAqDVyH0yvv87jcROmZwiEsYzRmixkbOS4nHj4B3J88Oty6tlfyZnnDzohcFrDS2XavCvkonf+nky9cF5Ntp1GIYAAAggggEC2BDQQfm9Y5FUxzxD+4q5t8lvMEEY+WAIHwshrlKECCIQZ6qwUVfX08K/k+W99Xo4/+K2StaqfPkvmfeC/yYwrrmJ30xT1HVVBAAEEEEAgjwIaCPsPibw65kD483/dJo0EwsiHXNlAaHYP1Y1kli9fHnllslYAgTBrPZZ8fUePHZHDX/q0nBi6z6oyl/7+38iMKxZaXctFCCCAAAIIIFAdgbFjR+SFvV+V897wDlbsiIgJhFclEAivJRBWZ1CXeUqgQGjOH9Tn5fGdQa8jgTDy8VlzBRzb+1U51PvX1u2a9pLL5ZKP/k+ZMqfB+h4uRAABBBBAAIHKBUafPyjP3d0lx3+8x3nI3Jv/TM77td+QullzKn9oxu/UQPj9QyKveU+8m8r8//buPriKKk/j+I8k5E0Z3gKjRFZ0NhqVN3FEo+DoojjriDoOENypdRSXWmvFqmV3anbCuLJaFvw1VeqyNdbqxnEoLQjMlhjx/W0mjvgaQUQZ4ysOiCG8GV9CYmDr3LVjp+m+3eee2337dn9v1ZSTcM7pcz7n3M59br91PLJKzhrlf1OZtra2zL1OrFdHR0dW8Wzl165dK0uXLh1Uf+7cubJixYoin0Xv7hMIDaaWQGiAl8Kq/d175NPfNknf7u1aox+z4FdSfepMrToURgABBBBAAAE9gcN9B6V3xzvS+cAtcqjn80GVj542W0bMukZKh43SazQhpVUgfGmPyMkRB8J3Hlkl030CYVdXlzQ0NIg6cFVTUyMq0LW3t3sGOL/yfvUTMqWDhkEgNJhVAqEBXgqr9n/WJTt+/TM5fLhfa/TDps+RUZfeoFWHwggggAACCCAQXODrz7rki9celf3P3u9ZqXT4WBn7d8ukvKZWZGhl8MYTUFIFwpcLEAj/HCAQOgOcM/A5+f3KEwgdYs5rCDlldDAQgTABe7gIh9Dz/ib59Le/1N5i5YTJUjO/SUqPHqldlwoIIIAAAgggkF1AfWGrjgr27sx+mqHVysiL/0GqJ18gZcNGp4ZWBcJX9orUR3yEcNuGVXKmzxHClStXZuZh8eLFA/OhPqO3trZKff2R92HwK+88ZTTpp4sqNI4QGryVCYQGeCms2vfJu7LzN9/urIISVNVNl5q5v5CSqqODVqEcAggggAACCAQQ6P+yWzrv/YX0fvpBgNLfFhn701uk6uSztOoUc2EVCF/dK3JKxIHw7Q2rpGz7Jpk8efIgvmuuuWbg56amJqmtrT0iEDY3N8vMmUdecqNbXn3eX758ucybN6+YpzBr3wMFwqCjT9uNZgiEQVcG5ZTA1/t3yc7//EdR1yjovIaft0BGXPjtjk+nLmURQAABBBBAILvAgWdWyf7nvE8VddZWj4Y69sb/TtXdR1UgfG2vyKkRB8K3NqySL978o0yYMGHQNNx0000DP/sd8XPOn275NJxCSiA02EsSCA3wUli1/7Pd8ul9v9K/qczcX0r15PNTKMaQEUAAAQQQCF+g79MPZed/XR94Q9X1Z8voH/88VWfuWIHwtEujvcuoCoTTRma/y6jfNYHOiTUtH3ihFFFBAqHBZBEIDfBSWlU9f7Bz1b8HHn3F+FNlTONSKf0Oj50IjEZBBBBAAAEENAT6D3RK5/3/Ib273g9Uq2buv8lRky8IVDYphVQgbN8rMjHiQLh1wyo53ScQBrlrqHqMhPUoCr/y6pRS6xETVlmv00+TMr9ZA2FSBhnWOAiEYckmt91DX3XLgbYW+ez5tYEGWfuvv5Oy4WMDlaUQAggggAACCOQmsP/Je+VA2xrfykNKh0rtv9yXusdPqED4+j6RSREHwjcfXiVTfQKhmrQgzxW0P5swW3kVCNetWzewFpJ+/aAaKIHQ963vXYBAaICX4qqHuvdI9+tPyf6n7vVUKD/mRBnTeJOUjR6XYimGjgACCCCAQDQCvZ+8L5/85p98N1ZV932pmdckJZVH+ZZNUgEVCDcVIBBuCRgIk2RdiLEQCA3UCYQGeCmveqi3R77evV0+b39c+vbskN7Oj6Ts6FFSVnOcDB09TtSzB9P68NuULw2GjwACCCBQAIH+A7ul83c3Se/uj7JuvebKn8tRUy8sQA8Lu0kVCDfvE5kc8RHCNx5eJVMCHCEsrE7xb51AaDCHBEIDPKoOCPR/vl8OHfxC1F3LSiqPliFDy9FBAAEEEEAAgYgF9j3xP9kv6RgyRGqX3CdlI9J3KYcKhFv2HpKpl/400lnZtOF+mTSyRK6++upIt5u2jREIDWacQGiAR1UEEEAAAQQQQCBGAn37dom6RtDrVVJaKoeHlEhp9Xdi1OtouqIC4da9fTLtRwui2eA3W2nfsFpOGzWUQBiyOoHQAJhAaIBHVQQQQAABBBBAAIGiEFCB8O09PXLmJfMj7e+rj6yV+tEVBMKQ1QmEBsAEQgM8qiKAAAIIIIAAAggUhYAKhO90fSlnXfKTSPv70qO/l5NGVxMIQ1YnEBoAEwgN8KiKAAIIIIAAAgggUBQCKhC+u7tbGv72ikj7u/GxB+Wva4YRCENWJxAaABMIDfCoigACCCCAAAIIIFAUAioQvr97v8z44WWR9vdPj7XKCWOGEwhDVicQGgAXQyA81N0lUlomh7u75PDBz6V0xDFyeGi1lJSViwytNBg9VRFAAAEEEEAAAQTSIKAC4Yede+S8i38U6XDbHn9Ejh87ikAYsjqB0AA4zoHwcO9X0r93u/Ru3iCHD34xaJRDysqldNwpMvSkH0hJ9XADAaoigAACCCCAAAIIJF1ABcKPP90t51/8w0iH+twTj8n4sWMIhCGrEwgNgOMaCA9/1S1ff/iq9HY8n3V0QyqOlsrpc6Vk5HgDBaoigAACCCCAAAIIJFlABcIdu3bJrNmzIx3mM08+KeO++10CYcjqBEID4FgGwv5e6dv+hvRueTTQyIZUj5DKc38mJVXpe6ZOICAKIYAAAggggAACKRdQgfCTXTvkootmRSrx1JPPyDHHjCMQhqxOIDQAjmMg7N+3Q3ramrVGNfT406X8tItFyrwfxqrVIIURQAABBBBAAAEEEiOgAmHnJx/LxReeH+mYHn/qORl77HgCYcjqBEID4DgGwr73XpTerU9qjarkqFFSec7fyxCOEmq5URgBBBBAAAEEEEiDgAqEXTs/lEsuPC/S4T76dJuMPvZ4AmHI6gRCA+DYBcJDX0tP+3rp3/mW9qiqZ/+zDKkcpl2PCggggAACCCCAAALJFlCBcO+O9+TSWedGOtANz7wgI8edSCAMWZ1AaAAcu0DYc0C+3PhA5hETuq+KaT+WsuMm6lajPAIIIIAAAggggEDCBVQgPLCjQy77m7MjHelDz7wow2vrCIQhqxMIDYBjFwj7eqTn9fXSv+sd7VFVzbpB1KmjvBBAAAEEEEAAAQQQsAuoQNj9l21yxQVnRgrz4LOvyLDj6gmEIasTCA2AYxcIRaR323PS906b1qhKqoZJ1YxrRap4JqEWHIURQAABBBBAAIEUCKhA+MXHW+UnF5wR6Wj/97l2qT7uVAJhyOoEQgPgOAZCdf1gz6u/1xpVyajxUjm9UYaUV2nVozACCCCAAAIIIIBA8gVUIOzZvkXmnT810sGu/cMmqRw/iUAYsjqB0AA4joFQ+r6S3reekb6P2gOPjBvKBKaiIAIIIIAAAgggkDoBFQgPfrRJ5v9gcqRjb/njFqn4qykEwpDVCYQGwLEMhGo8Pd3y1Svr5NC+v/iOrvLM+VJ67Mm+5SiAAAIIIIAAAgggkE6BTCD8sF3mz4z2BoQtbVulYsLpBMKQlx2B0AA4toFQRA73dEvfuy9I3/svu46w5KiRUnnmPBlSPUKkrMJAgaoIIIAAAggggAACSRbIBMIPXpX5M06JdJgtz78tFSd8n0AYsjqB0AA4zoEwM6z+Pjm0b4cc7v1Svt79gRw62C1loydI6YhxmRvIlFRzExmD6acqAggggAACCCCQCoFMIHzvZZl/brRnlbW88GepOHE6gTDkVUYgNACOfSA0GBtVEUAAAQQQQAABBBBQAplA+O6LMv+cukhBWjZ2SMX3ziYQhqxOIDQAJhAa4FEVAQQQQAABBBBAoCgEMoGw408y/+zvRdrflhffl4q6cwiEIasTCA2ACYQGeFRFAAEEEEAAAQQQKAqBTCB8p03mn3VCpP1teelDqThpBoEwZHUCoQEwgdAAj6oIIIAAAggggAACRSGQCYTb/iDzpx8faX9bXtkuFSefRyAMWZ1AaABMIDTAoyoCCCCAAAIIIIBAUQhkAuHbz0rjmeMj7W/Lqx9Lef0FBMKQ1QmEBsAEQgM8qiKAAAIIIIAAAggUhUAmEL71tDSeMS7S/ra8tlPKT51FIAxZnUBoAEwgNMCjKgIIIIAAAggggEBRCGQC4dYnpXHaMZH2t6V9l5SfdhGBMGR1AuE3wI2NjdLe3p75afny5TJv3jxfegKhLxEFEEAAAQQQQAABBIpcIBMItzwujaePjXQkLZs6pXzixQTCkNUJhCKycuXKDPPixYsz/1VBr7W1Verr67PyEwhDXp00jwACCCCAAAIIIFBwgUwgfOMRaZxaE2lfWjZ3SfmkS3wDYVtbmyxcuHCgbx0dHZH2s9g3RiB0CYDOgOg1yQTCYl/+9B8BBBBAAAEEEEDATyATCDc/LI2TR/kVzeu/t7yxV8qnXJo1EHZ1dUlDQ4Ns3LhRampqZO3atZmz/lasWJHXviS5sdQHQuciUpPttpB6enqOWAeTJk0SvoFI8tuDsSGAAAIIIIAAAghkAuGmh6Rx0ohIMVq27JfyqZdlDYTOz+1un+0j7XQRbiz1gXDbtm0yZ86cgW8VrEC4bt06WbNmzcCUqjLOl6pLICzCVU+XEUAAAQQQQAABBAILZAJh+4PSOHFY4Dr5KNiytVvKT78iayB0O7Mv6OVf+ehjEtpIfSAMeoTQbbI5ZTQJbwHGgAACCCCAAAIIIJBNQAXC1x9bLaeNLY8UamtnrxwcMSFzfw/7a8mSJQM/NjU1SW1t7cC9QNQ/qPLNzc0yc+bMSPtbrBtLfSC0Fo39JjJcQ1isy5l+I4AAAggggAACCORbYPPmzaL+V4jXBx98kLk20P664YYbBn7kCKH5rBAIucuo+SqiBQQQQAABBBBAAAEECiDANYTm6ATCbwx5DqH5YqIFBBBAAAEEEEAAAQSiFOAuo+baBEIDQ64hNMCjKgIIIIAAAggggAACeRDgOYRmiARCAz8CoQEeVRFAAAEEEEAAAQQQQKDgAgRCgykgEBrgURUBBBBAAAEEEEAAAQQKLkAgNJgCAqEBHlURQAABBBBAAAEEEECg4AIEQoMpIBAa4FEVAQQQQAABBBBAAAEECi5AIDSYAgKhAR5VEUAAAQQQQAABBBBAoOACBEKDKSAQGuBRFQEEEEAAAQQQQAABBAouQCA0mAIVCHkhgAACCCCAAAIIIFBogY6OjkJ3ge0XqQCBMKKJe/PNN+Wee+6R22+/PaItFvdmlixZItddd51MnDixuAcSQe9feuklaW1tldtuuy2CrRX/JhYtWiRLly6VE044ofgHE/IInn76aXn55Zelqakp5C0lo/mrrrpK7rzzThkzZkwyBhTiKNavXy/bt2+XG2+8McStJKfpOXPmSEtLi1RVVSVnUCGN5P7775fe3l659tprQ9oCzSKQPAECYURzSiDUgyYQBvciEAa3UiUJhMG9CITBrVRJAmFwLwJhcCtVkkAY3ItAGNyKkghYAgTCiNYCgVAPmkAY3ItAGNyKQKhnRSDU8yIQBvciEAa3IhDqWREI9bwojYASIBBGtA4IhHrQBMLgXgTC4FYEQj0rAqGeF4EwuBeBMLgVgVDPikCo50VpBAiEEa4BAqEeNoEwuBeBMLgVgVDPikCo50UgDO5FIAxuRSDUsyIQ6nlRGgECIWsAAQQQQAABBBBAAAEEEEixAKeMpnjyGToCCCCAAAIIIIAAAgikW4BAmO75Z/QIIIAAAggggAACCCCQYgECYYonn6EjgAACCCCAAAIIIIBAugUIhOmef0aPAAIIIIAAAggggAACKRYgEEYw+W1tbbJw4cKBLXV0dESw1fhtorGxUdrb2zMdW758ucybNy9rJ7OVb2pqknXr1g2qH6TN+KkE61Gua6iurk5aW1ulvr4+2IaKtJTu2lLDXLt2bWY9rlixYtCo07a2Vq5cKXfccUfGYO7cuUd42HGc69CvfJEup0Hd1llbdku3/Zx6PzpfSX5/6qytbdu2ZR6+br1YW4NXitpfLV26dOCXzr93rK3B+3GvfY+1D0vy+y4J+13GEL0AgTBk866uLmloaJCNGzdKTU2N54fQkLtR8ObVBwP1Wrx4cea/fkHFr7z60D5t2jTfUFnwgeehA7msIfuH2KT/4fNbK84psIcatw+daVpbykL5rVmzJsPkN3ZVdsGCBZl9mXqpdaYM/b7cycPboCBN6K4t5Wd9wWC9b+3vP7/9XkEGGdJGddeWCjyTJk0a+PJKWdbW1g78zQipmwVr1mRtWX9Dm5ubZebMmYH+phZsoCFsWHdtWV2w6qkvApP+dzEEdppMuACBMOQJdh6FcH64D3nzsWne+UHI+cfQ2VG/8n4fXGMz8Dx0JNc15PaBNA/diV0TfmvFq8NqDe7YscP1CGFavmxwvo+cH7T8JtvvfexXP+7/nuvassalArP6EiyNH9pN15bXEfy4r5mg/TNdW07fNH3ZkMvaUkegly1blvnyK01WQdcj5RAgEIa8Btw+MKVtZ+QWgrP9sQ9S3nlaX5JPF811DaUhEAZZK7kEQvvpyEleW87AYp22F/S09iR/MWOytqw159zXO0/rS/JRCtO1peqrIG2dVRLyn+pImzddW1Z95xFC+yBYW99qOPdrafsMFuniZmNFK0AgDHnq3E57UTsj+4485C4UvHlrZ2ydNqs6pAKh+tBtnapm72Su5ZP6BzDXNZSGQKi7VuzrzOsIodtaTOracu6L3Dy9diDWqbdBw2PBd0SaHTBZW2pTfuvLuiYsqX65ri3ry74kX0NosrasLxWyfVHF2vr2ze4WvgmEmjtDiqdCgEAY8jTnenQn5G5F2rzut6G65dVgknykItc1lIZAmMtasRa/3wd2q1yS11auR3GsMGj/kifSnUoEGzNdW8rI7Qsve9eT/ME017Wl+/6MYCnkfRMma8vqjN/1u6yt/5dy3gjLPplp+mI+74uYBhMnQCAMeUpzvf4r5G5F3rzu9RK65ZP8oT3XNZSGQKgWsu5a0f3AmeS1lcu1OGkIg9YayWVtqS8agoRBt7Ub+Y45xA3msrbs3dG9njXEoYTSdC5ry94Rv+t3kxwITddWkm1CWaw0mgoBAmHI05zLHSJD7lJBmve7o5rawauXdYe+bOWV6erVqweuLUn6B1S/NeR1elBaAqHu2soWCNO2tmAbyUUAAAoBSURBVPzu1udcW0k/Fc25c/RbW+qDpf3UPed+zBlw1M/WDWZ0gmNBdtqGG9VdW/Y7tKpNZ7M07FosqueytuyPyLGvPWXN2vr2ruN+a4dAGIu3AJ2ImQCBMIIJyfUZchF0LdJN+D1X0B4I1f/PVj5NN2dQFtnWkNuHdLudqp/k63H81orzw4HbKUTORwPY3xhJvX7QHoy9nkPoXFvOdWW1keRTR/32Q1YgtL6Ace5U1R1r1amjzufsqXJJvX4wl7XlfM5e0vdZfvstty8bvG52xdoa/PxUAmGkH+3YWEIECIQJmUiGgQACCCCAAAIIIIAAAgjoChAIdcUojwACCCCAAAIIIIAAAggkRIBAmJCJZBgIIIAAAggggAACCCCAgK4AgVBXjPIIIIAAAggggAACCCCAQEIECIQJmUiGgQACCCCAAAIIIIAAAgjoChAIdcUojwACCCCAAAIIIIAAAggkRIBAmJCJZBgIIIAAAggggAACCCCAgK4AgVBXjPIIIIAAAggggAACCCCAQEIECIQJmUiGgQACCCCAAAIIIIAAAgjoChAIdcUojwACCCCAAAIIIIAAAggkRIBAmJCJZBgIIIAAAggggAACCCCAgK4AgVBXjPIIIIAAAggggAACCCCAQEIECIQJmUiGgQACCCCAAAIIIIAAAgjoChAIdcUojwACCCCAAAIIIIAAAggkRIBAmJCJZBgIIIAAAggggAACCCCAgK4AgVBXjPIIIIAAAggggAACCCCAQEIECIQJmUiGgQACCCCAAAIIIIAAAgjoChAIdcUojwACqRE444wzPMc6ZcoUaW5uNra45ZZbZPbs2dLQ0GDclmqgo6NDFixYMNDWa6+95tuufZyrV6+Wurq6TJ2NGzfK4sWLB9V/4oknZPTo0ZnfrV+/Xjo7O2XRokVZt6HG+NBDD2XK5MvNd1ARFMj33EXQZTaBAAIIIIDAEQIEQhYFAggg4CGQLRBaVewBSQfSHpJWrlwZy0DoNn4VMFUQvPXWWzPDvf7661MXCMOaO531Q1kEEEAAAQTyJUAgzJck7SCAQOIE7IHIHnzsv7/ssstk2bJl2mNfuHChbN68OVOv0IHQrfN79uzJHLm0XvYjjXfffbfcddddqQ2EYc2d9iKiAgIIIIAAAnkQIBDmAZEmEEAgmQJegdB5KqX9KKHbaZZKxwqUzqBll7O3Yw8dXmXU7+1H69TP6pRPt1NG7WNR27HC3s033zxwtM+q39XVdcSpourfVFm1PSvI2vuVLdR6nTJq/72z36pt59FI9Tu7kbP+Aw88MHBqqtuRSzd7Z6C3n3Kr/k05WafNqhCs2nV76c6ds+8rVqwYcHU7rdZ5KrDVB7cj1G5rMNcvLpL5zmZUCCCAAAJ2AQIh6wEBBBDwEPAKhM5gYYUhrzBoNa/CxJVXXjnoyJtb2PMKg84Q4AyDbsOwjuw5j2qqa/qs4OG8hrAQgVBnEVpjsocqt/r2UOg3N1awcgZC69rHfM+dTt/95tkexu1Hb7OtBx1vyiKAAAIIJFuAQJjs+WV0CCBgIBA0EKojZ5dffrm4nUpoDxj2Iz9epx3ag4u9vNt1a25tOAOBVyC0n+bqdlOZbDenydcpo/YxWUew3I54jho1alCItm5843bk0avfbmO0j8PavrO+Nbf2ZZSPuXMbuzO0qrnz+vLB/ntrnTjDrDXHutd8GrxlqIoAAgggUIQCBMIinDS6jAAC0QjoBkJnr9yOAlkBLeh1aG6nCqqQMmPGjEEhye0Il+qPWyB0nt4Zh0BoBS+vQOzmZfe1Bzd7WRUe7Uc87SHb7TpJp7fbKZmmc6e+PHDru1uY9fKwrzU1DnXnV7+jg6pOku7yGs1egK0ggAACyRcgECZ/jhkhAgjkKBA0EFoBy+s6L/vmgwRCv9MJ3QKh1a7XzWC8Hi2h+paEQGgPuc7ApsZoXQdov5bOaaXC3969e30f25EtEAaZu1wDod91gATCHN/oVEMAAQRSLkAgTPkCYPgIIOAt4BUIncHPOoXRXt7tND77ETuvUOE8ZdIKOs4jSiZHCO3PGkxKIPQ6Qqj87IFQ9wih23McTecu10Dod3RP91Re3vsIIIAAAggoAQIh6wABBBDwEPAKhPZA4Bf8vK7p8woVbqcSOo9kuV2zaP0uyDWESQyEXvNgnfKZ6zWEOoFQZ+6CnjIa5BpCtXyzHd20byvIcyPZISCAAAIIpEuAQJiu+Wa0CCCgIaD7YPog5a2A4XZ6n9tjFty663a9ndew3K4hNA2EbnfsdLZp70+Qx06YXkPoNn7Tu4zaj+ja28/H3AUNhGq7OncZzXbKqt8RRo23BkURQAABBBIkQCBM0GQyFAQQyK9AtoDn9uHa7Tl3KpA5b3JSV1eX6aizfetoljNwqLA0duxY1+vgnGFBbc/ebhiBUPXdGTxMn0NoGghV/U2bNuX1OYRegTAfc6cTCNX2dJ5D6BYgOTKY330DrSGAAAJJEiAQJmk2GQsCCCCQIgGvu4ymiIChIoAAAgggYCxAIDQmpAEEEEAAgUIIEAgLoc42EUAAAQSSJkAgTNqMMh4EEEAgJQIEwpRMNMNEAAEEEAhVgEAYKi+NI4AAAggggAACCCCAAALxFSAQxndu6BkCCCCAAAIIIIAAAgggEKoAgTBUXhpHAAEEEEAAAQQQQAABBOIrQCCM79zQMwQQQAABBBBAAAEEEEAgVAECYai8NI4AAggggAACCCCAAAIIxFeAQBjfuaFnCCCAAAIIIIAAAggggECoAgTCUHlpHAEEEEAAAQQQQAABBBCIrwCBML5zQ88QQAABBBBAAAEEEEAAgVAFCISh8tI4AggggAACCCCAAAIIIBBfAQJhfOeGniGAAAIIIIAAAggggAACoQoQCEPlpXEEEEAAAQQQQAABBBBAIL4CBML4zg09QwABBBBAAAEEEEAAAQRCFSAQhspL4wgggAACCCCAAAIIIIBAfAUIhPGdG3qGAAIIIIAAAggggAACCIQqQCAMlZfGEUAAAQQQQAABBBBAAIH4ChAI4zs39AwBBBBAAAEEEEAAAQQQCFWAQBgqL40jgAACCCCAAAIIIIAAAvEVIBDGd27oGQIIIIAAAggggAACCCAQqgCBMFReGkcAAQQQQAABBBBAAAEE4itAIIzv3NAzBBBAAAEEEEAAAQQQQCBUAQJhqLw0jgACCCCAAAIIIIAAAgjEV4BAGN+5oWcIIIAAAggggAACCCCAQKgCBMJQeWkcAQQQQAABBBBAAAEEEIivAIEwvnNDzxBAAAEEEEAAAQQQQACBUAUIhKHy0jgCCCCAAAIIIIAAAgggEF8BAmF854aeIYAAAggggAACCCCAAAKhChAIQ+WlcQQQQAABBBBAAAEEEEAgvgIEwvjODT1DAAEEEEAAAQQQQAABBEIV+D+bq0GpDe2YMgAAAABJRU5ErkJggg=="
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "SD.plot.scatter_feature_importance() # works if deployed_model is filled"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d98c9275",
   "metadata": {},
   "source": [
    "Putting importance of the drift into perspective according to the importance of the model to be deployed, can help the data scientist to validate that his model can be deployed. <br />\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e52eefc9",
   "metadata": {},
   "source": [
    "### Univariate analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "707c0073",
   "metadata": {},
   "source": [
    "This graphs shows a particular feature's distribution over its possible values. In the drop-down menu, the variables are sorted by importance of the variables in the data drift classification. For categorical features, the possible values are sorted by descending difference between the two datasets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "ee7e5803",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "SD.plot.generate_fig_univariate('season_acc')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3fadad70",
   "metadata": {},
   "source": [
    "### Distribution of predicted values"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fd14d06a",
   "metadata": {},
   "source": [
    "This graph shows distributions of the production model outputs on both baseline and current datasets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "aa78bacc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "SD.plot.generate_fig_univariate(df_all=SD.df_predict,col='Score',hue=\"dataset\") # works if deployed_model is filled"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b800780c",
   "metadata": {},
   "source": [
    "Jensen Shannon Divergence (JSD). The JSD measures the effect of a data drift on the deployed model performance. A value close to 0 indicates similar data distributions, while a value close to 1 tend to indicate distinct data distributions with a negative effect on the deployed model performance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "cbd93ddd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "SD.plot.generate_indicator(\n",
    "                fig_value=SD.js_divergence,\n",
    "                height=280,\n",
    "                width=500,\n",
    "                title=\"Jensen Shannon Datadrift\",\n",
    "                min_gauge=0,\n",
    "                max_gauge=0.2,\n",
    "            ) #works if deployed_model is filled"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "192ce6b6",
   "metadata": {},
   "source": [
    "## Compile Drift over years"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "76890d30",
   "metadata": {},
   "source": [
    "### Compile Drift et generate report for Year 2018"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "cedd36b3",
   "metadata": {},
   "outputs": [],
   "source": [
    "SD = SmartDrift(df_current=X_df_2018,\n",
    "                df_baseline=X_df_learning,\n",
    "                deployed_model=model, # Optional: put in perspective result with importance on deployed model\n",
    "                encoding=encoder # Optional: if deployed_model and encoder to use this model\n",
    "               )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "56954c52",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The computed AUC on the X_test used to build datadrift_classifier is equal to: 0.7036329129677259\n"
     ]
    }
   ],
   "source": [
    "SD.compile(full_validation=True, # Optional: to save time, leave the default False value. If True, analyze consistency on modalities between columns.\n",
    "           date_compile_auc = '01/01/2018', # Optional: useful when computing the drift for a time that is not now\n",
    "           datadrift_file = \"car_accident_auc.csv\" # Optional: name of the csv file that contains the performance history of data drift\n",
    "          )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17c9fb32",
   "metadata": {},
   "source": [
    "----"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "ffd89494",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AAQIdFRAIO9rxmk2AAAECBAgQIECAAAGB0BggQIAAAQIECBAgQIBARwUEwo52vGYTIECAAAECBAgQIEBAIDQGCBAgQIAAAQIECBAg0FEBgbCjHa/ZBAgQIECAAAECBAgQEAiNAQIECBAgQIAAAQIECHRUQCDsaMdrNgECBAgQIECAAAECBARCY4AAAQIECBAgQIAAAQIdFRAIO9rxmk2AAAECBAgQIECAAAGB0BggQIAAAQIECBAgQIBARwUEwo52vGYTIECAAAECBAgQIEBAIDQGCBAgQIAAAQIECBAg0FEBgbCjHa/ZBAgQIECAAAECBAgQEAiNAQIECBAgQIAAAQIECHRUQCDsaMdrNgECBAgQIECAAAECBARCY4AAAQIECBAgQIAAAQIdFRAIO9rxmk2AAAECBAgQIECAAAGB0BggQIAAAQIECBAgQIBARwUEwo52vGYTIECAAAECBAgQIEBAIDQGCBAgQIAAAQIECBAg0FEBgbDS8ZcuXQo7OzthY2Ojo8NBswkQIECAQLsFrl69GtbW1nYbef369aENfv3rX7/n+6OOb7ee1hEg0EYBgTCEUH1zOHXqlEDYxpGuTQQIECDQeYEbN26EN73pTWF7ezssLS2FUX8IvnbtWvjd3/3dsLq62rOLx1++fDlcvHix85YACBBoj4BAWOnLCxcuhMcff1wgbM/41hICBAgQILArUA+A9YA4iioGxJMnTwazhKOkfJ8AgUUSEAgFwkUar66VAAECBAhMLBD/8Btf6+vru3XEJaFXrlwJx48fH1lvLB9XFZkhHEnlAAIEFkhAIGwYCB977LF93fqud71rgbrapRIgQIAAgXYLxBnAZ555Zk8j43LPI0eO9L529uzZcOzYsX2BcGtrK6ysrAzEifWeO3eu932zg+0eQ1pHoIsCAmHDQPjoo4/uGx8PP/ywN4Yu/tRoMwECBAjMnUC8N/DBBx8Mhw4d2hcIjx492vta7gxh2nNAKJy77ndBBAhkCAiEDQNhP+O4zMSbQsboU5QAAQIECBQSiIHwE5/4RLj33nsH1ph7D+G49xwWappqCBAgMFUBgVAgnOoAUzkBAgQIEJiFQJNAOGqX0bRpTLqnMAbIEydO7N5fmJaO+mPwLHrUOQgQmJWAQFh77ESCb3KDuRnCWQ1T5yFAgAABAsMFmgTCWMOw5xDWA2H6/+qZhUEjkQCBtgkIhBk9KhBm4ClKgAABAgQKCjQNhAVPqSoCBAi0QkAgzOhGgTADT1ECBAgQIFBQQCAsiKkqAgQ6JSAQZnS3QJiBpygBAgQIECgoIBAWxFQVAQKdEhAIM7pbIMzAU5QAAQIECBQUEAgLYqqKAIFOCQiEGd0tEGbgKUqAAAECBAoKCIQFMVVFgECnBATCjO4WCDPwFCVAgAABAgUFBMKCmAdYVXo0yLDd3uPnr62trbCystK70gsXLoTNzc3ef29vb4elpaWJWjDN50ymHWur13f69Omws7MTlpeXw/333x+OHTsW1tfXJ7p2hQjkCAiEGXoCYQaeogQIECBAoKCAQFgGsxquUo3nz58Pq6urjU7QL/g0KnjroHEDYTpfehxIzvlnGQjjMy1jGNzY2Oi1/OzZs1MJhKk/6wE7nv/y5cvh4sWLe7onfratH5uCazrwzJkzgus4g3oBjhUIMzpJIMzAU5QAAQIECBQU6FIgfOrp58Onf/+J8KUnnw4/8MfvDj/yA/cVk4wB4vHHH98NKrHiGAjiqx4e+p00J5DF+poEwup543MlP/WpT+1eb875pxkI61bR+b777msctCft4PhZNQb6J554Yk+IaxIIk0f9DwIxvL73ve+deCZ20rYoNz0BgTDDViDMwFOUAAECBAgUFOhKIPz3Tz4dfnTzM+GpZ76zq3fqh18bfn71DUU0+wXCFArjcsa4TDMFhXTCuOQxhcX42aj6irNNcQln7J9+x8evpRBXL3f8+PHdmbMY/OKMWgwncWYrXssf/uEfhnPnzu0WizNXaelo+uKgpaf1NsQlqA888EDvOtOyznjOtbW1PfVXl3RW21o1iIEpXmN6xfriK9X9wQ9+cM/347k///nP945J9devr9qOFPJS2we1Mbo+8sgj4d3vfnc4efJkSLOo8TxNAuGgsVBkoKlkrgQEwozuEAgz8BQlQIAAAQIFBRY1EP7K5x4PX/jKtxpLbP+br4b/6w++tu/4v/Kf/Mnw6rvuaFzPj/2Hx8L9S3fuO35QCKgucYxBI75iYIuvFFDistJ+M3TDjk/l0z2B9RnCFK7q996lcFoPNk1nCPvdh/jOd75zTyCMdaelsqneFL7idcUQmL4f3eI11ZeCxlB577337obi1I76EtFYvhoIq9eXgmkKdPF71QA6qNNjnW94wxt6IT7O8iazpoGwXqbx4HLgwgkIhBldJhBm4ClKgAABAgQKCixqIFz7x/8y/Pq1LzeXeOGFEG67bd/xL4QQ9n91cLW/8O7/OPyFB149USCsF6qGmSaBrHp8DDvx/9MMY79AWN9spRpUJgmE9XOm9oxaMlo976B7/gbNvNXrHhYI+11f9d6+epgd1MvVz6nxuqrLRpvMEAqEzX8sF/1IgTCjBwXCDDxFCRAgQIBAQYFFDYSLOEMYu62+LDJtNDIoEA46vj6jNotAWD/nsEBYXwJbn8lMZasbrVQ3YUkzeeMEwnh91aWw6Rzp3E0CYQyVcRlqfQlqmmUcFIqrwVMgLPgLas6rEggzOkggzMBTlAABAgQIFBRY1EA4LkG8h/Dtm58J36jcQ/hfLb82fPAnZ3cPYZzRi4EizeqNmiEcdvw8zxDGQBSXW6ZQNSggDdsIJ5Y5depU+PN//s/vWY467gxhdZw0CYT1AF4Plf0CYT20uodw3J/OxT1eIMzoO4EwA09RAgQIECBQUKArgTCSxV1GfzXuMvq1b/d2Gf0vfvA1xSQH7TIan5OXHpFQv9+tGpz6haNxjk/3y1Xv1RtnyWjTXUqb3ENYDYCp3jRLFwNX8qgGqY9//OMh3ouYnoWY6qhvWDPOPYSxc+Os4YkTJ3r3bTYJhPGY+jMZ6zOj1Xs/4znqwd0uo8V+rOa+IoEwo4sEwgw8RQkQIECAQEGBLgXCgmz7qmryHML6DphxBqwa2qp19NtltH58dYlk/F7coXPSQJiCTdptdNgOnHHnzerM2bBdRuPSz/hKG7PUnVJQHLQz6ThLRuN5Ru3kms7Xbyw0vY9x2Dmq9daXzY7zXMppjlV1lxMQCDMsBcIMPEUJECBAgEBBAYGwIKaqCBDolIBAmNHdAmEGnqIECBAgQKCggEBYEFNVBAh0SkAgzOhugTADT1ECBAgQIFBQQCAsiKkqAgQ6JSAQZnS3QJiBpygBAgQIECgoIBAWxFQVAQKdEhAIM7pbIMzAU5QAAQIECBQUEAgLYqqKAIFOCQiEGd0tEGbgKUqAAAECBAoKCIQFMVVFgECnBATCjO4WCDPwFCVAgAABAgUFBMKCmKoiQKBTAgJhRncLhBl4ihIgQIAAgYICAmFBTFURINApAYEwo7sFwgw8RQkQIECAQEEBgbAgpqoIEOiUgECY0d0CYQaeogQIECBAoKCAQFgQs+VVnT17Nhw7diysr6+3vKWTN+/06dPh1KlTYXV1NUzqdenSpXD58uVw8eLFyS8ko2T8nL61tRVWVlYyaulGUYEwo58Fwgw8RQkQIECAQEEBgbAM5tWrV8Pa2lqvsjNnzixsaIqBZmdnZxdleXl5N5hMGnDKCJeppdpPqcYrV66E48ePFznBJIGwHsCmGQjr/RsbXW+/QNh8KAiEza32HSkQZuApSoAAAQIECgp0KhA+8/UQrn0qhK//uxBecyKE4z9aUPJmVRcuXOj9exFn0aphJsHE9rz1rW/tBaY2BcLr16/3mpgC4vb2dlhaWsoeD/0MR1U6ywBWv74bN26E+Dtgkf+IMcp3mt8XCDN0BcIMPEUJECBAgEBBgc4Ewq9/MYSProTwzB+9qPfGnwrhv/xIQc39gTB94E4nqc7GxM9D58+fD+fOnet9uzobF/8/fj+9qt/LqXNQY1Odw4JRCoQxRKVZxOrxMTxubm7unqK67HBYW69duxZOnjy5x6IeUOK54zLK+Kp+L82mxeWN6dzDljumAJgCYawvhqQY4O+999591xGPG+Zd76f4/7FP45LR+h8H6vXE6/zUpz61265U9jWveU2vbHXJaHUsVNs3qk/q/d0vsNb7PnlE03je6pitH1ufcU2u/fq0n2W8vmr91TEUl95ubGz0mtCkn6uzn9UxMqjOEj/4AmGGokCYgacoAQIECBAoKLCwgfB3fzmEG/+mucS/vRrCv/vs/uN/+L8O4eX3Na/nz6yGcM+fGnh8PQRUZ3/qYSR+rxr0qh/E4wf9+L0YLOIr1ptmHSetc1Qj4/nvv//+3Q/h9eNTKEshsN7W+KE9XW/87xh0U0AY1tYUHtKH+HroqC+hrIaadJ4UkqJxPUxV29EkENbD6DDv+qxp9dqGjYVqn9ZnCOttqJ4j2aQQNapPmgTCeEx1vFXHYb8+fuKJJ3pjMfVbdTw8/vjjvfFT79N0HdW21tuS08/1fkg/L8PqHPXz0OT7AmETpQHHCIQZeIoSIECAAIGCAgsbCH/pJ0P417/aXOKFF0K47bbmxw868qcuhvCn/1KjQNgvnFRnXOpBoPqhfNDyzJw6mzS+OhMVj0+zXSk0VDeViR+240xhmsWp1l8PdcPaWg8WsZ6qUzWgxO9VDeof+FNd1RnAYYGwGlz7Xccw77jENP78VGdJBwXCYUF1WCDsN3NbDWn1cTKsT6LDoCWtgwJh3TOW/8AHPtBbQlwPi9Vjm1jWA2G9n6ttGdbPw2a3h9XZ5Odh1DEC4SihId8XCDPwFCVAgAABAgUFFjYQLsAMYQob9e5Ks1n9QlIKXPXlhWnWKqfOcYdN+lCfrrdf+KjuhpmOr54nhaVhbR0UCKtO1WWF1Vm+QUFh0NLXfpvK1Jc5VssO805LTOvLT9Muo9XANCyoDQuE/QJurDfNxI3qk3qfjxsIU4hMS2rf//7379lkKC3jrfd5HL9xGXDdsvoHhHogrP8xItaZZtCH9XM6V78/Agyrc9yfh37HC4QZigJhBp6iBAgQIECgoMDCBsJxDeI9hB95cwjPPvViyTf8lRB+/KPj1jT0+GoIGLV8cVhIqp6k+sH5K1/5ytAlkU3rbNroYbOW1Q/p6RpTiGsyQ5jC76hAOMkM4ahA2C88NJnV6tcv8zZDOOyRFePeQxjbm8JsDGfxVV3GHP+/3wZKTSxHzRBWrYcFwnhcfaY2la2PnabjvulxAmFTqT7HCYQZeIoSIECAAIGCAp0JhNGst8voPwvhyX8Xwh+Lu4y+o6DkzarqH7jrAS1+sD1x4kRvyd2w8BaDWFqKOSpcNa1zWGPjB/hHHnlkz/LP9KG+er9afcloCh+DNhspMUM46t6yfrOUpQJhNBvWh9X+TgaDNpWp15Puc6uPmXHvIRzUJ/36e9Auo9WlwfUQVZ2trrr2C31p3Pb7Xj0AptnaNL76PW4j1TdqJrjpPYTRpPqzlfsLQCDMEBQIM/AUJUCAAAECBQU6FQgLulWrqi4rrO6MGI+pL/2sbiIzLBAO27Fz0jpHNb+6k2c6thoARi1PrO/mGINaiUCYPsQP22U07cjZL4hU291vU5n0/UFlh3lXl8mmGbR+S0bjOepLaqsb4aRnWMZgNskuo2mWbtQzDJs8h7DfrFrs+/iq3y9aX4KbljYPsqz/rFTHSKx/0LgfFQhTcE99OWiX0fj9YbvQjvoZqX9fIBxXrHK8QJiBpygBAgQIECgoIBAWxFQVAQKNBUYtqW5c0QEeKBBm4AuEGXiKEiBAgACBggICYUHMOa5q0OYo6ZKrm7bMcTNc2oIL1Gcohz33chGaKhBm9JJAmIGnKAECBAgQKCggEBbEVBUBAp0SEAgzulsgzMBTlAABAgQIFBQQCNXEybsAACAASURBVAtiqooAgU4JCIQZ3S0QZuApSoAAAQIECgoIhAUxVUWAQKcEBMKM7hYIM/AUJUCAAAECBQUEwoKYqiJAoFMCAmFGdwuEGXiKEiBAgACBggICYUFMVREg0CkBgTCjuwXCDDxFCRAgQIBAQQGBsCCmqggQ6JSAQJjR3QJhBp6iBAgQIECgoIBAWBBTVQQIdEpAIMzoboEwA09RAgQIECBQUEAgLIipKgIEOiUgEGZ0t0CYgacoAQIECBAoKCAQFsRUFQECnRIQCDO6WyDMwFOUAAECBAgUFBAIC2KqigCBTgkIhBndLRBm4ClKgAABAgQKCgiEBTFVRYBApwQEwozuFggz8BQlQIAAAQIFBQTCgpiqIkCgUwICYUZ3C4QZeIoSIECAAIGCAgJhQUxVESDQKQGBMKO7BcIMPEUJECBAgEBBAYGwIKaqCBDolIBAmNHdAmEGnqIECBAgQKCggEBYEFNVBAh0SkAgzOhugTADT1ECBAgQIFBQQCAsiKkqAgQ6JSAQZnS3QJiBpygBAgQIECgo0MZAeOHChbC5udlTOn/+fO/f586dC2fOnAnr6+sF9VRFgECXBQTCjN4XCDPwFCVAgAABAgUF2hYIq2EwBcLV1dUQP3ssLy+HixcvFtRTFQECXRYQCDN6XyDMwFOUAAECBAgUFGhbIIyfMU6dOhU2NjZ6ITDOEMZAePbs2XD58uVw/fr1gnqqIkCgywICYUbvC4QZeIoSIECAAIGCAm0MhGlpaDUQnj59Ouzs7AiEBceOqgh0XUAgzBgBAmEGnqIECBAgQKCgQNsCYQx+8RWXhqZAeOLEiXDy5MndmcOCfKoiQKDDAgJhRucLhBl4ihIgQIAAgYICbQuEV69eDWtra32Ftra2wsrKSkE9VREg0GUBgTCj9wXCDDxFCRAgQIBAQYG2BcJIc+PGjRDbVX1duXIlHD9+vKCcqggQ6LqAQJgxAgTCDDxFCRAgQIBAQYE2BsKCPKoiQIDAQAGBMGNwCIQZeIoSIECAAIGCAm0LhOmxE9VnDvb7WkFCVREg0FEBgTCj4wXCDDxFCRAgQIBAQYGmgbB+b96wxzf0W7JZPf7SpUu9B8VXX+lREblNG7SbqOcQ5soqT4BAXUAgzBgTAmEGnqIECBAgQKCgQJNAmALe9vZ2WFpaCjHQxUc4xGf99XvF8BhfaQOXOEP3+OOP7x4/qnxO86rPIazW4zmEOarKEiDQT0AgzBgXAmEGnqIECBAgQKCgQJNAWA9w9YA46nJiQIyhMD4KIr6mHQiXl5d3z5WuzXMIR/WS7xMgMK6AQDiuWOV4gTADT1ECBAgQIFBQoEkgjGEuvtbX13fPHN/Lm+7cWQ+A9SWjpZaLxotLM4Hnz58Pq6urvetNy11LnqdgF6iKAIEFFRAIMzpOIMzAU5QAAQIECBQUiIHwwQcfDIcPH95TawxTR44c6X0thqxjx47tC4RNnuuXZhOHhcf0APkU4HKad+3atd5D6Pu9mgbYnPMrS4BAdwQEwoy+Fggz8BQlQIAAAQIFBVIgPHTo0L5AePTo0d7XJp0hTGFwVHAsvYS036Y26f7HgnSqIkCg4wICYcYAEAgz8BQlQIAAAQIFBZosGZ3kHsKmYTA2pXQgLMijKgIECAwUEAgzBodAmIGnKAECBAgQKCjQJBCO2mU0LdNMSzLr/1+/3LgENe1QOk5wLNhsVREgQCBbQCDMIBQIM/AUJUCAAAECBQWaBMJ4umHPIawHwPQg+PplpqWjaeOX9P3qBjAlmpZ2FO1X17DnJ5Y4tzoIEOiOgECY0dcCYQaeogQIECBAoKBA00BY8JRTraoeNusnEwinyq9yAp0SEAgzulsgzMBTlAABAgQIFBRoWyCMnzHiy46iBQeJqggQ6CsgEGYMDIEwA09RAgQIECBQUKCtgdBMYMFBoioCBATC0mNAICwtqj4CBAgQIDCZQNsCYVoyKhBONh6UIkCguYAZwuZW+44UCDPwFCVAgAABAgUF2hYIR+1wWpBOVQQIdFygtYGwujNXk12/0lr9OB6aHB+PEwg7/tOj+QQIECAwNwJtC4TVzyX9kM0czs3QcyEEFl6glYEwbhMdX+vr671/x1+qw27KjuHx1KlTYXV1NYzzHCGBcOHHvwYQIECAQEsEBMKWdKRmECAwc4FWBsJ6AKwHxKpyWpJR/UvbsOOrZQXCmY9XJyRAgAABAn0F2hYIdTMBAgRmJdC6QJhm+La3t8PS0lLP8dKlS2FnZydsbGzsc+0XCIcdLxDOamg6DwECBAgQaC4gEDa3ciQBAgSqAq0LhCng1QPh5cuXw8WLF/v2fpzp29raCisrKwMD5GOPPbav7EMPPRSs4fcDRYAAAQIEDl6gjYEwrlja3Nzs4cb9DeLr3Llz4cyZM7u3xRy8vCsgQGDRBVoXCMedIYwdmEJktTPrv2wfffTRfX398MMPC4SL/hPg+gkQIECgFQJtC4TVMJgCYdzrIP4Re3l5eeAfuVvRmRpBgMBMBVoXCKPeOPcQ9tOOz/55+9vfvjtjOKhH3EM407HqZAQIECBAYKBA2wJh/IwRN7yLt7vE/047oHs+oR8CAgRKC7QyEI7aZbT6i7UOGu8fHLa8tHq8QFh6OKqPAAECBAhMJtDGQJhWK1U/t6THarllZbJxohQBAvsFWhkIYzOHPYewHghjCIxr8uMr/TWuyWARCJsoOYYAAQIECExfoG2BMH6Oia+4/0H63HLixIlw8uTJsT6rTF/eGQgQWHSB1gbCWXSMQDgLZecgQIAAAQKjBdoWCK9evRrW1tb6Nry6Ed5oGUcQIEBguIBAmDFCBMIMPEUJECBAgEBBgbYFwkiTNsqrMl25ciUcP368oJyqCBDouoBAmDECBMIMPEUJECBAgEBBgTYGwoI8qiJAgMBAAYEwY3AIhBl4ihIgQIAAgYICAmFBTFURINApAYEwo7sFwgw8RQkQIECAQEGBtgXC+Blj1Mu9hKOEfJ8AgSYCAmETpQHHCIQZeIoSIECAAIGCAl0MhJFPKCw4iFRFoKMCAmFGxwuEGXiKEiBAgACBggJtC4Txmcpxp9H42In0unbtWu+xEzEE3nvvvb3/Xl5e3nNMQVJVESDQEQGBMKOjBcIMPEUJECBAgEBBgbYFwvgZo1/Yi19Pz0z2kPqCA0hVBDosIBBmdL5AmIGnKAECBAgQKCjQxkAYea5fv75HqRoUBcKCA0hVBDosIBBmdL5AmIGnKAECBAgQKCjQtkB49uzZcPny5XD+/Pmwurrak7p06VI4d+7c7gzhoFnEgqyqIkCgAwICYUYnC4QZeIoSIECAAIGCAm0LhOl+wX5E8R7CBx54IMQ2p+WjBSlVRYBAxwQEwowOFwgz8BQlQIAAAQIFBdoWCCPNjRs3eqGv+rpy5Uo4fvx4QTlVESDQdQGBMGMECIQZeIoSIECAAIGCAm0MhAV5VEWAAIGBAgJhxuAQCDPwFCVAgAABAgUF2hYI04PpPWew4CBRFQECfQUEwoyBIRBm4ClKgAABAgQKCrQtEKYdRC0RLThIVEWAgEBYegwIhKVF1UeAAAECBCYTaFsgjA+m39zcDALhZONBKQIEmguYIWxute9IgTADT1ECBAgQIFBQoG2BMO0yaslowUGiKgIEzBCWHgMCYWlR9REgQIAAgckE2hYI0z2EgzTqD6yfTE0pAgQIhGCGMGMUCIQZeIoSIECAAIGCAgJhQUxVESDQKQGBMKO7BcIMPEUJECBAgEBBgbYFwoI0qiJAgMBQAYEwY4AIhBl4ihIgQIAAgYICAmFBTFURINApAYEwo7sFwgw8RQkQIECAQEGBNgbCtNNoZDp//nxP69y5c+HMmTNhfX29oJ6qCBDosoBAmNH7AmEGnqIECBAgQKCgQNsCYTUMpkC4uroa4meP5eXlcPHixYJ6qiJAoMsCAmFG7wuEGXiKEiBAgACBggJtC4TxM8apU6fCxsZGLwTGGcIYCM+ePRsuX74c7DJacPCoikDHBQTCjAEgEGbgKUqAAAECBAoKtDEQpqWh1UB4+vTpsLOzIxAWHDuqItB1AYEwYwQIhBl4ihIgQIAAgYICbQuEMfjFV1wamgLhiRMnwsmTJ3dnDgvyqYoAgQ4LCIQZnS8QZuApSoAAAQIECgq0LRBevXo1rK2t9RXa2toKKysrBfVURYBAlwUEwozeFwgz8BQlQIAAAQIFBdoWCCPNjRs3QmxX9XXlypVw/PjxgnKqIkCg6wICYcYIEAgz8BQlQIAAAQIFBdoYCAvyqIoAAQIDBQTCjMEhEGbgKUqAAAECBAoKtC0Qxs8YZgMLDhBVESAgEE5jDAiE01BVJwECBAgQGF+gjYEwKXju4PjjQQkCBJoLmCFsbrXvSIEwA09RAgQIECBQUKDNgbDKlJ5HWJBOVQQIdFygWCCs7oZVXeJw7dq13hbJ8dW2XbEEwo7/9Gg+AQIECMyNQNsCYRX2woULYXNzc4+1B9PPzdBzIQQWXqBYIDx79my4fPly39CXwuKpU6fCxsbGwqOlBgiErelKDSFAgACBBRdocyCsds2lS5fCuXPnPJh+wceryycwTwLFAmEMR/HV7y9W1W2T2/QXLYFwnoayayFAgACBLgu0ORDGh9Tv7OyYIezyANd2AlMUmEkgjNc/LDBOsX1TrVognCqvygkQIECAQGOBtgXC9LmpDnDmzJmwvr7e2MWBBAgQGCVQLBCmv1712yI53UfYtl2yBMJRw8v3CRAgQIDAbATaHgjbtMJqNiPCWQgQaCpQLBCmNe3xxNvb22Fpaal3DdXlom3bGUsgbDrMHEeAAAECBKYr0MZA2LbN+KY7AtROgMCkAsUCYbyAfmvc04W1bXYwtksgnHTYKUeAAAECBMoKtC0QltVRGwECBAYLFA2E8TTVmcJ02rbNDKZ2CYR+tAgQIECAwHwICITz0Q+uggCBxRMoHggXj2DyKxYIJ7dTkgABAgQIlBRoQyCMnyvSiqpBm8okM/cUlhw96iLQbQGBMKP/BcIMPEUJECBAgEBBAYGwIKaqCBDolECxQDjqL1n9dh9ddGmBcNF70PUTIECAQFsE2hAI29IX2kGAwGIJzCwQRpa2hUKBcLEGu6slQIAAgfYKCITt7VstI0BgugLFAuGwy0wbzZw6dSpsbGxMt0UzrF0gnCG2UxEgQIAAgSECbQuE6RnO1Sa37Q/rBjQBAvMhMJNAGJualpS26SZogXA+BrGrIECAAAECbQqEFy5cCJubm307ta07txvBBAgcnIBAmGEvEGbgKUqAAAECBAoKtCUQVmcGqzOCV69eDWtraz0xM4UFB46qCBAIAmHGIBAIM/AUJUCAAAECBQWaBsJqsIqnH7Zy6caNGyHWW31Ne6XT2bNnw+XLl0O/mcC23oJTcBioigCBCQRmEgjb+gtMIJxgxClCgAABAgSmINAkEKaAt729HZaWlkL8fLKzszNwf4MYHuNrZWWl9++4lPPxxx+f6n4Ip0+f7l1TusYqVbr+9KzCKTCqkgCBDgoUC4SjHjsRbdu2xEEg7OBPjCYTIECAwFwKNAmE9QBYD4ijGhYDYgyFFy9eHHXoxN+vPpy+XyVt3JNhYiwFCRAoIjCzQNi2MBj1BcIiY1AlBAgQIEAgW6BJIIxhLr7W19d3zxffy5t+Rhk1o5jdiFufLYbNAAqEJZTVQYBAVaBYIOwiq0DYxV7XZgIECBCYR4EYCB988MFw+PDhPZe3uroajhw50vtavD/v2LFj+wLh1tbW7rLQQW1Ls4lNw+OkRmYIJ5VTjgCBSQUEwknlzBBmyClKgAABAgTKCqRAeOjQoX2B8OjRo72vTTpDmMJgk+CY26omt+DEc0x7c5vcdihPgMDiCMwkEFZ39GrTLzAzhIsz0F0pAQIECLRboMmS0UnuIZxlGIw9JBC2e5xqHYF5FJhqIEw7ZVUbLhDO4zBwTQQIECBAYLEFmgTCUbuMpmcApmWh9f9fbCFXT4AAgf4CxQNh/fk+1dPOYqnFLDvaDOEstZ2LAAECBAgMFmgSCGPpYc8hrAfAuMR0c3Nz30nb9nnGuCJAoNsCxQJhepDqIM42zQymNgqE3f7h0XoCBAgQmB+BpoFwfq7YlRAgQGA+BIoFwvqa9xQA07JRgXA+OtxVECBAgACBNgoIhG3sVW0iQGAWAsUCoRnCWXSXcxAgQIAAAQL9BARC44IAAQKTCRQLhOn0w+4hnPazeyYjmLyUJaOT2ylJgAABAgRKCgiEJTXVRYBAlwSKB8Iqnl1GuzSUtJUAAQIECBycgEB4cPbOTIDAYgtMNRD2mzVs072EZggXe/C7egIECBBoj0AbA2G/P6ynHmvT56n2jEItIbCYAjMJhItJM/qqBcLRRo4gQIAAAQKzEGhbIOzi3gyzGCfOQYDAfgGBMGNUCIQZeIoSIECAAIGCAm0LhGn39rbtv1Cwy1VFgEAhAYEwA1IgzMBTlAABAgQIFBRoayC0NLTgIFEVAQJ9BQTCjIEhEGbgKUqAAAECBAoKtC0QpiWjAmHBQaIqAgQEwtJjQCAsLao+AgQIECAwmUDbAuG1a9fCyZMngyWjk40HpQgQaC5ghrC51b4jBcIMPEUJECBAgEBBgbYFwnQP4SAiM4cFB4+qCHRcoHggTL/Atra2wsrKSqt5BcJWd6/GESBAgMACCQiEC9RZLpUAgbkSKB4I0zNzurDEQSCcq7HsYggQIECgwwJtC4Qd7kpNJ0BgxgLFA+GFCxfC5uZmJ9a8C4QzHq1OR4AAAQIEBgi0MRCm+wirTe7CH9wNcgIEZitQPBCmX16WjM62I52NAAECBAh0WaBtgfDq1athbW2tb5d24TNWl8eythOYtUDxQNilm6DNEM56uDofAQIECBDoL9C2QJgeO1GdEUx/dD916lTY2NgwFAgQIFBEQCDMYBQIM/AUJUCAAAECBQXaFgjjZ4x+wc/zCQsOGlURINATKB4Iu+QqEHapt7WVAAECBOZZQCCc595xbQQIzLNAawNh2u004p8/fz6srq4O7YfqUtemSzEEwnke2q6NAAECBLok0LZAaMlol0avthI4WIGpBMK002gKY/Hf586dC2fOnAnr6+tTb3E8f3ylc8XgNmxXrhgeYwhMobH+/4MuWCCcelc6AQECBAgQaCTQtkDYb4fRBGFTmUZDwkEECDQUKB4Iq2EwBcIYtGJ4Wl5eDhcvXmx4aZMfVg+A9YBYr3nc41N5gXDyPlKSAAECBAiUFGhbIIw2HjtRcoSoiwCBQQLFA2H1Juj432m55qxugr5x40aIbwrb29thaWmp1+5Lly6FnZ2dgTtyxe/HGcz0F7d43dXyg/AEQj9YBAgQIEBgPgTaGAjnQ9ZVECDQdoGpBMK0NLQaCNM9fdevX5+qafprWj0QXr58eeDsZCoTZzBjcOx3D+Fjjz2277ofeuihMO32TBVL5QQIECBAoCUCAmFLOlIzCBCYuUDxQBiDX3zFpaEpEJ44cSKcPHmyb9Aq3eJJZgjrM4JxNjO+qs/4efTRR/dd6sMPPywQlu5A9REgQIAAgQkEBMIJ0BQhQIDANB47cfXq1bC2ttYXd1Y3QY9zT2CaHazO9MUlpMNmFFPjLBn1M0SAAAECBOZDoA2BsLrfQnX3837CVijNx7hzFQTaIFB8hjCipFm6KtCwXT5LQ47aZbS6lDWeu/7/cZZzZWVl5I6oAmHpnlMfAQIECBCYTEAgnMxNKQIECEwlEM4D67DnENYDYD3ANn08hkA4Dz3tGggQIECAQOhtKPeJT3wi3HvvvTgIECBAYAyB1gbCMQwmPlQgnJhOQQIECBAgUFSgbYGwumt7Faq6V0NRQJURINBZAYEwo+sFwgw8RQkQIECAQEGBrgTCWT3Gq2DXqIoAgTkXKBIIu3oTtEA456Pb5REgQIBAZwS6Eghn9RivzgwcDSVAIAiEGYNAIMzAU5QAAQIECBQUaEMgTDufj2Lp97zkUWV8nwABAoMEigTCrvIKhF3tee0mQIAAgXkT6FIg3N7eDktLS/PWBa6HAIEFFSgSCKs3Pg+6CXpBfYZetkDYxl7VJgIECBBYRIE2BMKqe5c+Ty3ieHPNBNokIBBm9KZAmIGnKAECBAgQKCjQtkBYkEZVBAgQGCpQJBBWn/k3yvv69eujDlmY7wuEC9NVLpQAAQIEWi7QtkB44cKFsLm5GarPRu73tZZ3q+YRIDADgSKBsP5g92HXLRDOoFedggABAgQIdEygbYFw0G6i1Z3dO9bFmkuAwJQEigTC6rV1ac27GcIpjUrVEiBAgACBMQXaFggHfZ7yHMIxB4bDCRAYKVA8EI48Y4sOEAhb1JmaQoAAAQILLdDGQLi8vBwuXry4p188h3Chh6mLJzCXAgJhRrcIhBl4ihIgQIAAgYICbQuEaSbw/PnzYXV1tSd19erVsLa2FjyHsODAURUBAh5MnzMGBMIcPWUJECBAgEA5gbYFwmEPqb9y5Uo4fvx4OTw1ESDQaYEiM4TVG5zjfw972VSm0+NN4wkQIECAwFQE2hYII1K/Tfs8lH4qw0elBDotUCQQdlXQDGFXe167CRAgQGDeBNoYCOfN2PUQINBOAYEwo18Fwgw8RQkQIECAQEEBgbAgpqoIEOiUgECY0d0CYQaeogQIECBAoKBAGwJhV2/BKTgMVEWAwAQCxQPhhQsXwubmZtja2goPPPBAiL+g46vf1skTXO9cFREI56o7XAwBAgQIdFhAIOxw52s6AQJZAsUDYXw+TnzF5+akLZPTFZ45cyasr69nXfA8FRYI56k3XAsBAgQIdFmgDYGwy/2n7QQIHJxA8UAYQ1IKfmnH0bg98iOPPBIuX74c7DJ6cJ3tzAQIECBAoK0CAmFbe1a7CBCYtkDxQBhnCO+///7w3ve+d3e5aAyBaSmpQDjtLlU/AQIECBDonkAbAuGoR3dVe7VNn6e6N1q1mMB8CRQPhCn4pWaeOnUqbGxshOpS0vkimPxqLBmd3E5JAgQIECBQUkAgLKmpLgIEuiRQPBBGvBj+dnZ2eo7xL1iXLl0K586d211K2hZggbAtPakdBAgQILDoAm0IhNU+iPswfOELX+jtyZBe6UH158+fD6urq4veZa6fAIE5EZhKIJyTtk39MgTCqRM7AQECBAgQaCTQtkBYfQRFFaCNK64adbCDCBCYmoBAmEErEGbgKUqAAAECBAoKtDEQRp76vYJpFZZ7CAsOHlUR6LhA8UDoOYQdH1GaT4AAAQIEDkCgbYEwPbqrujz06tWrYW1trZXPdj6AIeOUBAjcEigeCD2H0NgiQIAAAQIEZi3QtkB47dq1cPLkyb6M7iGc9ehyPgLtFigeCD2HsN0DRusIECBAgMA8CrQtEEbjtIlM1XtrayusrKzMYxe4JgIEFlSgeCD0HMIFHQkumwABAgQILLBAGwPhAneHSydAYIEEigdCzyFcoN53qQQIECBAoCUCAmFLOlIzCBCYuUDxQBhb4DmEM+9HJyRAgAABAp0WaGMgrP6RPd43GF9tfK5zpweuxhOYA4GpBMI5aNdMLsFjJ2bC7CQECBAgQGCkQNsCYX3FVdpIZtDzCUcCOYAAAQIDBATCjKEhEGbgKUqAAAECBAoKtC0Qxs8Yp06dChsbGyH+dwqE6XEUnkNYcPCoikDHBaYSCOMvrkGvNv0CEwg7/tOj+QQIECAwNwJNA2F6ll+68KafS+J7/pUrV8Lx48d323zp0qXeEs7qK4W4XJj6ru0pEHowfa6s8gQI1AWKB8L0lyuB0GAjQIAAAQIEZiXQJBCmxzhsb2+HpaWlEAPdzs5ObxZu0Ku6L0K/QDiq/KTtrz7XOc0QnjhxovdswlKhc9JrU44AgXYJFA+EaW37hz/84RB/OadfnvEXW3xuzvr6emsEzRC2pis1hAABAgQWXKBJIKwHwHpAHESQjptlIKzPZFavzbMIF3ywunwCcyYwlUBYXfOefmm1cc27QDhno9nlECBAgEBnBZoEwrhRS3xV/zjdbyloHXFYIKwuGS09c9fvwfT1UNrZDtdwAgSKCRQPhOnB9HH5RXVWUCAs1mcqIkCAAAECBGoCMRA++OCD4fDhw3u+s7q6Go4cOdL7WvwscuzYsX2BcNSM26BAWO+E6uYvOogAAQKLIlA8EKbgF9fnf/zjHw+bm5u7FsvLy+HixYuLYjPyOs0QjiRyAAECBAgQmIlACoSHDh3aFwiPHj3a+1rpGcJ6w5rck9gUI23QNyqsNq3PcQQIEBgkUDwQ1k9UvRk73cTdlu4QCNvSk9pBgAABAosu0GTJaOl7CKcZCNPnJ0tEF31kun4C8y8w9UA4/wSTX6FAOLmdkgQIECBAoKRAk0A4apfRa9eu9XbxrIewQUtG46qotENpOqbUjF56ML1AWHKUqIsAgX4CAmHGuBAIM/AUJUCAAAECBQWaBMJ4umHPIewXCKsrnWL56sYx9UdtpWcFlmhWupZSAbPENamDAIF2CgiEGf0qEGbgKUqAAAECBAoKNA2EBU851arSPYSDTnL9+vWpnl/lBAh0R6BIIBz1S6vK2aZfYAJhd35QtJQAAQIE5ltAIJzv/nF1BAjMr4BAmNE3AmEGnqIECBAgQKCgQNsCYUEaVREgQGCoQJFA2FVjgbCrPa/dBAgQIDBvAgLhvPWI6yFAYFEEigfCtCvWmTNndh/82u9riwI07DoFwjb0ojYQIECAQBsEBMI29KI2ECBwEALFA2Hajat+r2AMTx5MfxBd7JwECBAgQKD9Am0KhOkP6anX2rT/QvtHohYSWDyB4oEwBr/qlsyJJG3N3KZfamYIF2/Au2ICBAgQaKdAWwLhpUuXwrlz5/Z1Ups+P7VzBGoVgcUVmEog7DcTOGjmcHHpQhAIF7n3XDsBAgQItEmgLYEwfV5Kzx9Ms4Uln3HYpn7XFgIE8gWKB8I0E1j9xZUeAttvuSFxywAAIABJREFU5jC/CQdXg0B4cPbOTIAAAQIEqgJtCYTpUV5pRjA9oL5tn6GMXgIE5kegeCBMv7j6NfHKlSvh+PHj89P6zCsRCDMBFSdAgAABAoUE2hQIqyutBMJCA0Q1BAgMFCgeCOOZbty4EeIv5upre3s7LC0ttaorBMJWdafGECBAgMACCwiEC9x5Lp0AgQMVmEogPNAWzfDkAuEMsZ2KAAECBAgMEWhTIGzS0TaZaaLkGAIEmggIhE2UBhwjEGbgKUqAAAECBAoKCIQFMVVFgECnBATCjO4WCDPwFCVAgAABAgUF2hIIC5KoigABAo0EBMJGTP0PEggz8BQlQIAAAQIFBQTCgpiqIkCgUwICYUZ3C4QZeIoSIECAAIGCAgJhQUxVESDQKQGBMKO7BcIMPEUJECBAgEBBAYGwIKaqCBDolIBAmNHdAmEGnqIECBAgQKCggEBYEFNVBAh0SqB4IIwh6dSpU2FjY2MP5OnTp3v/f/HixdYAC4St6UoNIUCAAIEFFxAIF7wDXT4BAgcmMLNAePbs2XD58uXQpufmCIQHNm6dmAABAgQI7BFoYyCMf0zf2dnp29Nt+jxlKBMgcLACMwuE6Zdam36BCYQHO3idnQABAgQIJIG2BcL0h/RBPdymz1NGMQECBytQJBBeu3YtnDx5cmRL+i0lHVlojg8QCOe4c1waAQIECHRKoG2BMH7GiK8rV66E48ePd6ovNZYAgdkKzDQQbm9vh6Wlpdm2cIpnEwiniKtqAgQIECAwhkBbA6GZwDEGgUMJEJhIoEggrG4kE//7+7//+8O/+Bf/YqILWqRCAuEi9ZZrJUCAAIE2C7QtELZx74U2jz9tI7DIAlMJhG1bGjqogwXCRR76rp0AAQIE2iTQtkCYbsexZLRNo1RbCMynQJFAOGwXrHqz27T0QSCcz0HtqggQIECgewJtC4TpHsJBPdmmz1PdG61aTGC+BIoEwhs3boT4i7jJq02/wATCJj3uGAIECBAgMH0BgXD6xs5AgEA7BYoEwirNoAfTt5FPIGxjr2oTAQIECCyiQNsC4SL2gWsmQGAxBYoHwsVkmOyqBcLJ3JQiQIAAAQKlBQTC0qLqI0CgKwICYUZPC4QZeIoSIECAAIGCAm0MhP2e82yTmYKDRlUECPQEBMKMgSAQZuApSoAAAQIECgq0LRBevXo1rK2t9RXa2toKKysrBfVURYBAlwWKBMIYjJaXl8PFixdDl3bFEgi7/KOj7QQIECAwTwJtC4TpOYTVGcE0Y9iVx3vN0/hyLQTaLCAQZvSuQJiBpygBAgQItE7gqaefDw998vfD5d/5Uq9tf/b+e8L/8I4fCD/4x++eelvbFggHbdLngfVTH0pOQKBzAkUC4TyqVZ+NeP78+bC6utr3Moc9MmPUIzIEwnnseddEgAABAgcl8IErvxf+p8/+wZ7Tv/aVR8Nvv+8/n/olCYRTJ3YCAgRaKlA8EKYlowe5vv3ChQu97lpfX+/9O17TODdhX7p0KTzxxBO75Qf1vUDY0p8KzSJAgACBvgJ/9PTz4SvffDZ89ZvPhRvfeDZ89VvPhq9847lwo/e1Z8P//m++Gr757Hf2lf2Dn/vRqYu2LRBaMjr1IeMEBAjcEigeCNPM3DgBrHRv1ANgPSCOOl8sv729HZaWloYeKhCOkvR9AgQIEJhnge9+74VemLsRA14Ker3/v/XPN567FfqeDV/71nPhO997YWhzXnghhNtu23+IQDj+KOi3w2iq5SD/6D5+S5QgQGDeBYoHwhi+Njc3x5qRK4mUloBWA12c8dvZ2QkbGxsjT9V0djBWJBCO5HQAAQIECMxY4NnvfC98+alnwo1v3ZrFuxX2dkNe5f+//u3nx7q6l9/xknDPy28PSy+/49Y/t4d7bv33vXfdEf63//eJ3fsHU8UP/LG7wj8/85axzjPJwW2bIYwGHjsxyUhQhgCBcQWKB8L0y+ug/nqVzl8PhJcvX+7tgjrqNWh28LHHHttX9KGHHgqj7jMcdT7fJ0CAAAECowSe/PbzvSWZu8s167N4u///XHj6+e+Oqm73+3E275Uvi6Hu9nDvy++4Fe5uhrz4/zH4pQD46rvvCLcfPjS07ripzId+7V+HT//eE+GpZ57vbSrzsyd/MPyJVx5tfE2THtjGQDiphXIECBAYR6B4IDzox07kzBAOW1r66KOP7nN9+OGHBcJxRptjCRAgQKAnUHqpZpU1hrYXZ/Fuzua9OIv34oxePOaeO+8Ih/os8VzEbhIIF7HXXDMBAvMg0LpAGFEnuYewX5Ac1UGWjI4S8n0CBAh0RyAu1XwiLtX8xrMvLte8telK3Hyl9/Vb9+vFzVnGeY1aqnnPnbeHpbvuCEt33h7uPvrScapuzbFtDITVHdPrHWWFUmuGroYQOHCB4oHwwFsUQhi1y2gMcvVHUYy78UwKnn4hz0OPuwYCBAiUF4gbpHz96ekt1XzVy26GuBjm4v13cbau9/+3lm+m5Zrxe6OWapZv/eLV2LZAmHYZHdQTPn8s3hh1xQTmVaCVgTBiD3sOYT0QXr16NaytrTXaWbTakWYI53VYuy4CBAj0F4hLNeN9eDdn6158XEL67+rGK3FXzXh801dXl2o29Zn2cW0LhOkWnIPctX3afaZ+AgTmQ6BIIBx132C1qW36i5ZAOB+D2FUQINBtgW89993ehivTWKp515GX7NlYJe2uWZ/Fi1+Px3odnEBbA2GbPjcd3OhwZgIEhgkIhBnjQyDMwFOUAAECAwTiUs0nv31z9m7Q8/F6D0aPu25+49kQ791r+oq7ajZdqvnqu46Elx5uyY4rTYEW+Li2BcK0ZFQgXOBB6dIJLIhAkUBYbWv8BfaFL3xhzyMe0oYt9fv2FsRo4GUKhIveg66fAIFZCcQHmvcC3hSWat7xkkN9ZvFe3E1zKT037647eo9YaMuumrPqu0U5T9sCYXqMliWjizICXSeBxRUoHghjSFpeXt73zL94T198NXkW4KJwCoSL0lOukwCBaQh889nvhN2Zum8+u/vfveflfePZ8NVbD0aPQfCpZ74z1iVYqjkWl4NDCG0LhKNuxzFzaNgTIFBKYCqBMF5c/RdV2uSlTb/ABMJSw1A9BAjMg8A0l2rGWblXxUcj7D7s/I5w7103n4OXHpfQ+/et71uqOQ8jYrGuQSBcrP5ytQQIzI9A8UCY1rxXl4emXTz7zRzOD8X4VyIQjm+mBAECsxWISzXjbN3ucs1bs3bxuXhf+cZzNzdjufVP3FVzjE01wzhLNeN9e/H+PS8C0xJoWyCclpN6CRAgUBcoHgjTmvd+1O4hNAAJECCQLzDNpZp339pVc8/z8XZn9W4P91b+Oz4s3YvAvAgIhPPSE66DAIFFEygeCCNA2kSmirG1tRVWVlYWzWfo9ZohbFV3agyBAxOISzW/FnfVTDN5A56Pl+7XG2dXzXGWasYHoL/EjisHNg6cOE+gjYGw+kzluk6bbsHJ63mlCRDIFZhKIMy9qEUpLxAuSk+5TgKzF3j+u7d21Rz0fLzMpZoxvMX77eLz8NJ9d3v//+bX466almrOvv+dcfYCbQuE6RacQZIC4ezHmDMSaKuAQJjRswJhBp6iBBZQ4BvPfKd3v12/nTXTfXjpe/HYcV6Wao6j5VgC+wXaFgjTLqMeO2G0EyAwbYGpBMJhWyW36S9aAuG0h6f6CUxXYJpLNQ8fuu3Wrpp7Z/DiM/HuuXUfXu/5eLdm+izVnG5fq739Am0NhG363NT+UaiFBBZToHgg7NISB4FwMQe9q263gKWa7e5frSMwSKBtgTB9nhIIjXkCBKYtUDwQpgfTf/jDH+49JDYtdYg3RsdNZdbX16fdppnVLxDOjNqJOi4wzaWa33f0paE3Uxdn7e66o/dcvH7Px4uzenfefrjjPaH5BOZXoG2BMO3absno/I45V0agLQJTCYSnTp0KGxsbIQamtLtoG//SJRC25cdAO2YtEJ919+SUdtUcZ6lmfIRCPN6LAIHFF2hbIBx2+03sLTOHiz9mtYDAvAgUD4RxJvD+++/vBcLqrKBAOC9d7joITEcgLtX88jee2b/hyjeeDTcfgh7/ffPRCvERC/H+vaavoy89vDuL17v/7q79O2vGcBe/94qjL7WrZlNYxxFokYBA2KLO1BQCBGYqUDwQpuC3vb0dPv7xj4fNzc3dBi0vL4eLFy/OtIHTPJkZwmnqqnseBOZhqeZ9dx8Jd7zk0DxwuAYCBOZYoG2BcI6pXRoBAi0TKB4I6z7Vh6rGkLi0tNQaQoGwNV3ZmYbEpZpxti49GuGr34wzd8/depTCs71/39h9KPpz4bnvfq+xTdwl81V33h7i8/HifXj9ZvFuPi/v5uyepZqNaR1IgEADAYGwAZJDCBAg0Edg6oGwzeoCYZt7d3HaFkNbbznmrSD3lfScvBkv1Xzly166OGiulACB1gm0MRB25TFerRuMGkRgwQQEwowOEwgz8BQdKvDU08+HG7fut4v33cXAd/OB6C/O4KUHpH/z2fEegP6Kl8VdNeNM3Yuzden/70nPxbvz9vBqSzWNUgIEFkigbYGwS4/xWqBh5lIJtFKgeCCMISntMloVi0tH48s9hK0cRxo1QsBSTUOEAAEC0xVoGgivXr0a1tbWdi+m6W6d8fPNLB8B0aXHeE13ZKidAIFRAjMLhHYZHdUVvr9oAnGp5pefSjN3N+/Du7lc8+YsXu/+vFvLN+MjFsbZVfNlt8ddNV+cwevtrPnyvc/Hi7N5cWfN+Bw9LwIECHRdoEkgvHHjRu8ZyWlPg0uXLoWdnZ3ezuiDXtW9EGYdCLvyGK+uj13tJ3DQAjMLhOkXatO/xB00TJPzWzLaRGmxjrFUc7H6y9USIEAgCTQJhPUAWA+IgzTTcbMMhF16jJdRTIDAwQoUCYTXrl0LJ0+eHNmSfktJRxaa4wMEwjnunFuX1luqWZmpu7mL5q378KqbrsQZvW89G+Kz9Jq+Xnr4tt5umr2Zut2dNffel5dm8eLum3bVbCrrOAIECIwv0CQQXrhwoVfx+vr67gmaLAU9iEDYpcd4jd/bShAgUFJgpoHQYydKdl1363r2Ozd31Uybqliq2d2xoOUECBBIAjEQPvjgg+Hw4cN7UFZXV8ORI0d6X4sh69ixY/sC4dbWVlhZWRmIeRCBsH4xbX6Ml1FMgMDBChQJhNUmDNpU5mCbOZ2zmyEs5/pHTz+/e7/djd2Zu/7Px/v2c99tfOLbbgvhlS+7/eYs3svjbN7NGbz47/j/8b683s6avfvz7vAA9MayDiRAgMB8CaRAeOjQoX2B8OjRo72vLdIM4XzpuhoCBNosUDwQthmr3jaBcHBvf/d7L4SvxcclpGfiHdBSzRj8Dt3WpVGprQQIEOimQJMlo4t0D2E3e1GrCRA4CIGpBMKuPEi1a4EwLtX88lPPvPh8vFsPQt9zX96t4Pf1bz8/1nh++R0v2Z2pS7trvriz5h3hnjtvD0t33RGW7rw93G1XzbFsHUyAAIEuCDQJhKN2GU17ItQ3jzmoJaPVZaL1PmzTJn1dGJ/aSGCeBYoHwi49SHXWgfDfP/l0byz9iVfeXPpS4jUPSzVfffcd4fbDe5f4lGibOggQIECgOwJNAmHUGPYcwn6BsB7KZrVBXpc+T3VnlGopgfkUKB4Iu/Qg1VkFwt/7/54KDz72f4cv3QqEr33l0fA/vus/Cj/4x+/eN6riUs3dXTT3Ldd8Ntz4xs3dNOOmLHFJ53fiNpwNXzG0pfvt4n14N++/qzwfr3JPXtx901LNhrAOI0CAAIFsgaaBMPtEM6ogrbaa5aMuZtQ0pyFAYM4EphIIu/Ig1VkFwv/05349PP71m7OD6fUfvPrlYeVPLe0JfzEITrpU8767j4RX3dp8pbdkMy7PrGzAEv/77iMvmbPh63IIECBAgMBNgbYGQktDjXACBKYtUDwQdulBqrMKhN//3/+z/ePghRdCiFto1l7xSzHYxUAX77urPh8v7bSZdtaM37NUc9o/YuonQIAAgVkItC0QpiWjAuEsRo9zEOi2QPFA2KUHqR5kIIzh7m/+Z3+q9wiFm+EvzurdfLSCFwECBAgQ6JpA2wLhoA1uutav2kuAwPQFigfC+iW3+UGqswqE7/3lz4f/eedLe2jP/IXXh//uL/7p6Y8QZyBAgAABAgsg0IZAOGyX9noXmDlcgEHpEgksiMDUA+GCOEx0mbMKhE89/Xz4hd/+t+H/+MJXe9f5Z++/RxicqMcUIkCAAIG2CgiEbe1Z7SJAYNoCAmGG8KwCYcYlKkqAAAECBDoh0IZA2ImO0kgCBOZOoHggTGveqy1t65bJAuHcjWcXRIAAAQIdFRAIO9rxmk2AQLZA0UB44cKFsLm52feizp8/H1ZXV7MveJ4qEAjnqTdcCwECBAgcuMAzXw/hfz0bwud+6ealfP+bQ/hLGyG85s9M/dLaEggvXboUzp07F5aXl8PFixd7btXPV238PDX1weEEBAgMFSgWCKszg9UZwatXr4a1tbXeRbRtplAg9NNFgAABAgQqAv/8fSH8nx/dS/KKPxnCf/u7U2dqSyBMu7VvbW2FlZWVUP0clRDT96aO6gQECHRCoFggTL/A+v3lKv21Kz2wvi2yAmFbelI7CBAgQGCgwAvfC+Hpr4fw9NdC+PbXQnj6yRf/u/f/la9/6V+G8Py391f1d/9o6sBtCYRpp9G0i2g1ID7wwAMhtrNtn6emPjicgACB2cwQpsdLbG9vh6WlpT0nvXHjRu8XWHX5Qxv6RSBsQy9qAwECBDok8Ny3bga4GOr2hLlKqKuHvLgM9IUXmiHF4267TSBsptX3qPjZovp5KQXE9Pkqfd7y2IkMZEUJENgjUGyGsP4LrO5c/4tXG/pBIGxDL2oDAQIEFlDge9+tzMylMDco1FW+/t3nJmvske8L4eirQnjZq0I4+spb//3KW/9f+frvfSKEnX+89xz3/VAIf/Ozk513jFJtmiFMgbDfH9QFwjEGhUMJEGgkIBA2Yup/kECYgacoAQIECNwUePap/bN1vRm8PrN4aWYvlpnk9ZIjL4a4GOx6Ae9WoEv/Xf/6kVeEcOhws7PF2cTf2Ajh2j8L4Zk/urmpzNt+LoRXvK5Z+Yyj2hII0xLROCP4G7/xG70NZs6cORPW19dDW1dcZXS7ogQIFBAQCDMQBcIMPEUJECDQNoE4+/btr74Y7urLMtNSzOrX43/H2b5xX3FZZm+mLs3WVYJdPdDtBr57QoiBsKWvtgTCfpvIpE352ronQ0uHpGYRWBiBooGwSavbtOZdIGzS444hQIDAggnETVTi7FZ9A5W0ecqgr/fbTKVJ02+/s7IcMy2/vLU0M87aVWfxUgiMs3b97tVrcr6WHtOWQBi7JwW/+N9ps740Oxi/ZpfRlg5izSJwQAICYQa8QJiBpygBAgRmITDtTVSqbTj0kpszdvsCXG1J5p778O4J4fBLZyHR+nO0KRC2vrM0kACBuRIoFgjnqlUzuhiBcEbQTkOAAIHeJiqVxx1UH3UwaLfMeMx3np3MrukmKrsbrbwqhDvumuxcShUR6FogTDOGZguLDB+VEOi0gECY0f0CYQaeogQIdFdgppuo3HFzOeag++r6fT1+rekmKt3txblruUA4d13igggQWBABgTCjowTCDDxFCRBYfIHeJiq3HkzeZAOVdO/d974zftsn2UQlBruXvmz8cymxkAIC4UJ2m4smQGAOBATCjE4QCDPwFCVAYH4E4sPE4+MCZrWJSgxpe+6zG7SBSuXrNlGZn/Eyp1ciEM5px7gsAgTmXkAgzOgigTADT1ECBKYjEHe6rM/WDbvfrndf3pMhxFA47muiTVReFcLh28c9k+MJjBQQCEcSOYAAAQJ9BQTCjIEhEGbgKUqAwHCBWW+icsfdt2bt+jzX7mUDnncXy3gRmBMBgXBOOsJlECCwcAICYUaXCYQZeIoS6JLAs98IYXeWLt5z9+SL997FZZrfvrV7ZvXr8Tl4k7xeYhOVSdiUWXwBgXDx+1ALCBA4GAGBMMNdIMzAU5TAIgp89/kQvv3Vm+FuFpuoxPvm+j3Xrn7/XfW5dvEh514EOiggEHaw0zWZAIEiAgJhBqNAmIGnKIGDFEibqKT756rPsRu0sUoMgfEh55O8JtpE5ftCuO3QJGdThkAnBQTCTna7RhMgUEBAIMxAFAgz8BQlUErgO8/cnLUb9HDy+tezNlE5fHPGbvdh5JX/3jNrV/36PTZRKdXX6iEwREAgNDwIECAwmYBAOJlbr5RAmIGnKIG6QNxEZffRB/G+ulvLMtO9d3uC3a177uLXYiCc5GUTlUnUlCEwtwJdC4Rz2xEujACBhRMQCDO6TCDMwFO03QKz3EQlPsJg3312r3pxx8y+99u9KoRDh9vdB1pHoGMCbQyEp0+fDjs7O3178vr16x3rYc0lQGBaAgJhhqxAmIGn6GIIxE1U+m2gMuq5drHcuK/bbgvBJirjqjmeAIFbAm0LhGfPng2XL18e2L8CoaFPgEApAYEwQ1IgzMBTdLYCM99E5WjlPrtX7Z/BS7N21Zm9o6+wicpsR4WzEWiVQNsCYfyMEV9XrlwJx48fb1VfaQwBAvMlIBBm9IdAmIGn6OQCvU1U4v116T67yiMQBn09bqTywvfGP2dcVjnuJipxw5X4LDwvAgQIzFCgrYHQTOAMB5FTEeiogECY0fECYQaeojcDWv1Zdr0dMG8FveKbqNxVC3fpPrv477QrZnUHzVeFcOT79BQBAgQWQqBtgTAtGRUIF2L4uUgCCy0gEGZ0n0CYgde2os9988VZu5EPLH/y5rFxR81JXhNtovLKEA69ZJKzKUOAAIGFEGhbILx27Vo4efKkJaMLMfpcJIHFFhAIM/pPIMzAm9ei3/vOzWfa7Zu5qzwGod+yzEk2UYkGcROV3v10r3zx3+kZd4Oea3f7y+dVz3URIEDgwATaFgjTPYSDQM0cHthQc2ICrRMQCDO6VCDMwJt20biJyrNP7b3P7ttpOWZlWWb9Prz4uIRJXi+1icokbMoQIECglIBAWEpSPQQIdE1AIMzocYEwA2+cot959tas3Qw2UbntUP/Zuj2zdrX77F52j01UxulPxxIgQGAKAm0LhFMgUiUBAgT6CgiEGQNDIBwTr7eJytcrs3YNNlCJM3jPPz3miW4dfscEm6jccXcI8Xl4XgQIECCwUAIC4UJ1l4slQGCOBATCjM7odCCc6SYqLx2wO2a67666W2a6H+8em6hkjG1FCRAgsGgCbQyEFy5cCJubm72uOH/+fO/f586dC2fOnAnr6+uL1kWulwCBORUQCDM6ZqaB8A+uhvAHn715tcffHsJr/kzGlVeKxk1UxtlApbehypMhfPe5yc5vE5XJ3JQiQIAAgaECbQuE1TCYAuHq6mqInz2Wl5fDxYsXjQgCBAgUERAIMxhnFgh/YyOE3/q5vVf6zo+FcPwde7/2zB/NbhOVlxy5tStmdYfMWzN1aXfM3Z0z0wzeK0OI9+h5ESBAgACBwgJtC4TxM8apU6fCxsZGLwTGGcIYCD2fsPDAUR0BAkEgzBgEMwuEG3/i5o6Z1VcMW0t/uvIQ869O3pJBAS49DiFtqLK7sUrcROXI5OdTkgABAgQIFBZoYyBMS0OrgfD06dNhZ2cneOxE4QGkOgIdFhAIMzp/ZoHw735fs6u8/c4Q6uEt/n+aqdv3XLtX3nwOnk1Umvk6igABAgTmVqBtgTAGv/iKS0NTIDxx4kTvYfVp5nBuO8OFESCwUAICYUZ3zSwQ9pshvPd4CD/6wReXbd71moyWKEqAAAECBBZboG2B8OrVq2Ftba1vp2xtbYWVlZXF7jBXT4DA3AgIhBldMbNA+LmPhfC//Dd7r7TfPYQZbVGUAAECBAgsskDbAmHsixs3boTYrurrypUr4fjx44vcVa6dAIE5ExAIMzpkZoEwXuMf/j8h/MFvh3Dk+0L4/jeH8IrXZVy5ogQIECBAoF0CbQyE7eohrSFAYF4FBMKMnplpIMy4TkUJECBAgEDbBQTCtvew9hEgMC2B1gbCtAtXhEtbNQ9DrC/L2N7eDktLS0PdBcJpDUv1EiBAgACB8QQEwvG8HE2AAIEk0MpAGB/mGl/r6+u9f8fgNmzN/bVr13q7do27Ll8g9INEgAABAgTmQ6BtgTA9mD5uIPPAAw/s3kvoofTzMd5cBYE2CbQyENYDYD0g1jswPuT17W9/+9g7dgmEbfpR0BYCBAgQWGSBtgXC6mMn0sPoU/+k5xMucn+5dgIE5kegdYEwLf2sLvm8dOlS7yGuGxsbfeVjsIt/cYvHxFfTv74JhPMzkF0JAQIECHRboG2BMH7GqD6YPvZuXMn0yCOPhMuXL3swfbeHu9YTKCrQukCYln/WA2H85Rkf7lp/pQBZXS4a/xIXX9UA+dhjj+0r+9BDD/mFXHQ4qowAAQIECEwm0LZAGGcI77///vDe9753d7no9evXQ1pKGv/biwABAiUEWhcIx50h7Hd8fBhs/IVbDZCPPvroPu+HH35YICwxCtVBgAABAgQyBdoWCFPwSyynTp3q/aG6upQ0k0xxAgQI9ARaFwhjo8a9h7B+fL9A2G+8WDLqp4gAAQIECMyHQNsCYVSt7pgeZwTjLTDnzp3bXUo6H/KuggCBRRdoZSActctoDHLVR1HE4x9//PHdJaLxF3D8S9zq6urQ/hUIF334u34CBAgQaItAGwNhW/pGOwgQmG+BVgbC+l/V6s8hrAfCeHx1B6+mu3cJhPM9uF0dAQIECHRHQCDsTl9rKQECZQVaGwjLMvWvTSCchbJzECBAgACB0QJtDITVJaN1AZvKjB4TjiBAoJmAQNjMqe9RAmEGnqIECBAgQKCgQNsCYf3ZgwJhwcGiKgIE9ggIhBkDQiDMwFOUAAECBAgUFGhbIIyfMeKr+lisglx0/joxAAAVXUlEQVSqIkCAwK6AQJgxGATCDDxFCRAgQIBAQYG2BkJLQwsOElURINBXQCDMGBgCYQaeogQIECBAoKBA2wJhWjIqEBYcJKoiQEAgLD0GBMLSouojQIAAAQKTCTQNhPFZw2tra7snGRW4hh2fngtYveL0APnJWvFiqWvXroWTJ09aMpoLqTwBAiMFzBCOJBp8gECYgacoAQIECBAoKNAkEN64cSPE47a3t8PS0lLvQe87Ozu7zyGuX86o40eVz2leuodwUB2jgmzOuZUlQKBbAgJhRn8LhBl4ihIgQIAAgYICTQJhPcDVA1/9ckYdLxAW7EBVESBwYAICYQa9QJiBpygBAgQIECgo0CQQXrhwoXfG9fX13TPH9/JBO3mOOr6+ZLTUctGCLKoiQIDASAGBcCTR4AMEwgw8RQkQIECAQEGBGAgffPDBcPjw4T21rq6uhiNHjvS+FjdqOXbs2L5AuLW1FVZWVvZdzbjHx88F58+fD/GcXgQIEFgUAYEwo6cEwgw8RQkQIECAQEGBFAgPHTq0LxAePXq097VRM371yxn3+NJLSOP5Nzc3e5cVg2Z8nTt3Lpw5c2ZPqC3IqCoCBDooIBBmdLpAmIGnKAECBAgQKCjQZMnoqHsC65eTe3xO86phMAXCOPMYP3ssLy+Hixcv5lSvLAECBHYFBMKMwSAQZuApSoAAAQIECgo0CYSjdg2tP+ph1PFxSenGxkavFenYQctPx21q/IyR7kmsLkX1fMJxJR1PgMAoAYFwlNCQ7wuEGXiKEiBAgACBggJNAmE83bDnCvZ79t+w41M4S80oef9g/IyRloZWA+Hp06d7j8rw2ImCg0dVBDouIBBmDACBMANPUQIECBAgUFCgaSAseMqpVhWDX3zFpaEpEJ44caL3sHq7mU6VXuUEOicgEGZ0uUCYgacoAQIECBAoKNC2QFifmaxSlVqWWpBfVQQILLCAQJjReQJhBp6iBAgQIECgoEDbAmGkSfclVpkGPTOxIKWqCBDomIBAmNHhAmEGnqIECBAgQKCgQBsDYUEeVREgQGCggECYMTgEwgw8RQkQIECAQEEBgbAgpqoIEOiUgECY0d0CYQaeogQIECBAoKBAWwJh/Gwx7OWh9AUHjaoIEOgJCIQZA0EgzMBTlAABAgQIFBToSiCMZDaVKThwVEWAgECYMwYEwhw9ZQkQIECAQDmBNgXC5eXl3uMm6q+086jHTpQbN2oiQMAMYdYYEAiz+BQmQIAAAQLFBLoQCCNWWlLqwfTFho6KCHRewJLRjCEgEGbgKUqAAAECBAoKCIQFMVVFgECnBATCjO4WCDPwFCVAgAABAgUF2hIIR5GYIRwl5PsECIwrIBCOK1Y5XiDMwFOUAAECBAgUFOhCILx27Vo4efJkGHSPYUFOVREg0CEBgTCjswXCDDxFCRAgQIBAQYEuBMKCXKoiQIDAroBAmDEYBMIMPEUJECBAgEBBAYGwIKaqCBDolIBAmNHdAmEGnqIECBAgQKCggEBYEFNVBAh0SkAgzOhugTADT1ECBAgQIFBQQCAsiKkqAgQ6JSAQZnS3QJiBpygBAgQIECgoIBAWxFQVAQKdEhAIM7pbIMzAU5QAAQIECBQUEAgLYqqKAIFOCQiEGd0tEGbgKUqAAAECBAoKCIQFMVVFgECnBATCjO4WCDPwFCVAgAABAgUFBMKCmKoiQKBTAgJhRncLhBl4ihIgQIAAgYICAmFBTFURINApAYEwo7sFwgw8RQkQIECAQEEBgbAgpqoIEOiUgECY0d0CYQaeogQIECBAoKCAQFgQU1UECHRKQCDM6G6BMANPUQIECBAgUFBAICyIqSoCBDolIBBmdLdAmIGnKAECBAgQKCggEBbEVBUBAp0SEAgzulsgzMBTlAABAgQIFBQQCAtiqooAgU4JCIQZ3S0QZuApSoAAAQIECgoIhAUxVUWAQKcEBMKM7hYIM/AUJUCAAAECBQUEwoKYqiJAoFMCAmFGdwuEGXiKEiBAgACBggICYUFMVREg0CkBgTCjuwXCDDxFCRAgQIBAQQGBsCCmqggQ6JSAQJjR3QJhBp6iBAgQIECgoIBAWBBTVQQIdEpAIMzoboEwA09RAgQIECBQUEAgLIipKgIEOiUgEGZ0t0CYgacoAQIECBAoKCAQFsRUFQECnRIQCDO6WyDMwFOUAAECBAgUFBAIC2KqigCBTgkIhBndLRBm4ClKgAABAgQKCgiEBTFVRYBApwQEwozuFggz8BQlQIAAAQIFBQTCgpiqIkCgUwICYUZ3C4QZeIoSIECAAIGCAgJhQUxVESDQKQGBMKO7BcIMPEUJECBAgEBBAYGwIKaqCBDolIBAmNHdAmEGnqIECBAgQKCggEBYEFNVBAh0SkAgzOhugTADT1ECBAgQIFBQQCAsiKkqAgQ6JSAQZnS3QJiBpygBAgQIECgoIBAWxFQVAQKdEhAIM7pbIMzAU5QAAQIECBQUEAgLYqqKAIFOCQiEGd0tEGbgKUqAAAECBAoKCIQFMVVFgECnBATCjO4WCDPwFCVAgAABAgUFBMKCmKoiQKBTAgJhRncLhBl4ihIgQIAAgYICAmFBTFURINApAYEwo7sFwgw8RQkQIECAQEEBgbAgpqoIEOiUgECY0d0CYQaeogQIECBAoKCAQFgQU1UECHRKQCDM6G6BMANPUQIECBAgUFBAICyIqSoCBDolIBBmdLdAmIGnKAECBAgQKCggEBbEVBUBAp0SEAgzulsgzMBTlAABAgQIFBQQCAtiqooAgU4JCIQZ3S0QZuApSoAAAQIECgoIhAUxVUWAQKcEBMKM7hYIM/AUJUCAAAECBQUEwoKYqiJAoFMCAmFGdwuEGXiKEiBAgACBggICYUFMVREg0CkBgTCjuwXCDDxFCRAgQIBAQQGBsCCmqggQ6JSAQJjR3QJhBp6iBAgQIECgoIBAWBBTVQQIdEpAIMzoboEwA09RAgQIECBQUEAgLIipKgIEOiUgEGZ0t0CYgacoAQIECBAoKCAQFsRUFQECnRIQCDO6WyDMwFOUAAECBAgUFBAIC2KqigCBTgkIhBndLRBm4ClKgAABAgQKCgiEBTFVRYBApwQEwozuFggz8BQlQIAAAQIFBQTCgpiqIkCgUwICYUZ3C4QZeIoSIECAAIGCAgJhQUxVESDQKYHWBsLTp0+HnZ2dXmeeP38+rK6uDuzYS5cuhXPnzu35/qlTp8LGxsbQwSAQdupnRWMJECBAYI4FmgbCq1evhrW1td2WXL9+fY5b5dIIECAwfYFWBsILFy705NbX13v/jsHtypUr4fjx431FYyCM4XFUAKwXFginP0CdgQABAgQINBFoEghv3LgR4nHb29thaWkpTPr+3+R6HEOAAIFFEWhlIKwHwHpArHfOpG8IAuGiDHPXSYAAAQJtF2gSCOvv9/WA2HYj7SNAgEA/gdYFwn6/3EcFvvqS0SbLRdPMo6UmfrAIECBAgMDBCzQJhP3+QDxqFdHBt8wVECBAYLoCrQuE165dCydPntxdDhL5YuC7fPlyuHjxYiPN+OZQv+/wscce21f2oYceCgJhI1IHESBAgACBqQrEQPjggw+Gw4cP7zlP3EPgyJEjva+dPXs2HDt2bPeWkvTH3a2trbCysjLV61M5AQIE5lWgdYFwkhnCeuf0m1F89NFH9/Xhww8/PK/96roIECBAgEDnBH7mZ34m3HbbbfsC4dGjR3tfM0PYuSGhwQQINBBoXSBMf+2rbiIz6h7CJoGwgeXUD/nIRz4S7rvvvvATP/ETUz+XExAgQIAAgUkFPv3pT4fPfe5z4e/8nb8zaRVTKecewqmwqpQAgQUXaGUgHLXLaH1JaFxCknYYTTOM87h8RCBc8J82l0+AAIGOCMxrILTLaEcGoGYSIDCWQCsDYRQY9hzCfoEw3mOYXqOeWziWcMGDBcKCmKoiQIAAgakJzGsgjA32HMKpdbuKCRBYUIHWBsIF7Y+hly0QtrFXtYkAAQLtE5jnQNg+bS0iQIBAnoBAmOc309IC4Uy5nYwAAQIEJhQQCCeEU4wAAQIHICAQHgC6UxIgQIAAAQIECBAgQGAeBATCeegF10CAAAECBAgQIECAAIEDEBAIDwDdKQkQIECAAAECBAgQIDAPAgLhPPSCayBAgAABAgQIECBAgMABCAiEM0SPj7u4cuVKOH78eJGzXrt2LZw8eTJcv369SH0qIUCAAAECUSA+n3d5eTmsrq4WAyn9HljswlREgACBjgsIhA0HwLDnGqYqhr3ZxfD2yCOPhI2Njd7h6eG4qWy/oDgq8F26dKlXPL5h1+uLX68HxSZt6PchoFquylUy3DbsBocRIECAwAiBCxcuhM3Nzd5Rp06d2n3fqRYbFfji+1n1PaTJ+0fT98Am71c5bYjvjefOndttrvcqPzIECBAYLiAQNhgh8Y0pvtbX13v/rr/pVd8oB73xxDruu+++3b+2xjKxvpWVlVAPfvU3y0EzgLGOD3zgA70Zx/ig3fiK9cVXPN/jjz+++0FgVBuqb77nz58f+lfheL3vf//7w8WLFxvoOYQAAQIEZiUQ3wvi7/P0+7ke/Jr8ro91fOpTn2r8/jHue+Co96ucNqSHzqf3zfr/z6ofnIcAAQKLJCAQNuitegCsh6tYRQpxgwJhrGN7ezssLS3tC4CxfDUgpksa9kY2KpTV31CbtCFdR/yL8rBlQvEDxtvf/vbd8NmA0CEECBAgMAOBegCsvxekS4jvOYN+19d/xzd5/xjnPbDOMCoAjtOGODu4s7OzbzVOev+dQRc4BQECBBZOQCAc0WXpTa76ZlJ/wxkVCOt/be335tZv+c6wQFifcaw3o3qNTdvQJBCOCqIL9xPgggkQINAigfofFwfdejAoEKb3izTD1vT9Y1ggrL8HDnu/6vcH0nHbEANsvP8xzpLG98Innnhid4VPi7paUwgQIFBMQCAcQZneiOqB8PLly3uWTA57M4zh7Q1veMPujFp8g6qXj4Hw2LFje960hgXC+Gb+4Q9/uDfjWH/Vr6VpG5oEQrODxX72VESAAIHiAjEMbW1t7b7f9Pv9P+x3fXzf+fznP7/7XtT0/WOc98Bqo/uVy21DfJ/6whe+0JspjC/3EBYfZiokQKBlAgLhiA4t8dfR+s35uTOE9Q1q+r25Vj8QNG3DqEA4aNlOy34mNIcAAQILK5A7QxjD1Lvf/e7d3bCbvn8MC4T198CEm8pU36/S+1C6xz7+/zgzhPUZwVRWKFzYIe3CCRCYgYBA2AA55/6Jfktl+r25jXMP4aDlooPeXGMTm7RhVCDsd40N+BxCgAABAjMSyLmHsL5cNF1yk/ePQYFw0HLRYe9XOW3od/tFfcZxRl3hNAQIEFgYAYGwQVeN2qEzVjHozXDQEsthu4ymSxq0ZLS6QU06dtRfQZu0YVggNDvYYKA4hAABAgcsMGqDlnR5/e4hHHS/XZP3j3HeA0e9X+W2IT5yor7LqE1lDnhgOj0BAnMtIBA27J5hz2CqP6cvPfdp0F9bqwEynb66nKXfM5rSoyAG/bW1upV4tUnVpTjD2tCvfH1TgfqynoZ0DiNAgACBGQoMe4bfsN/11UcZ1S+35Htgk/erSdsQr7tevzA4w8HnVAQILKSAQDjFbqvfnF/iVPUNakrUqQ4CBAgQ6LZA/EPke97znqLPl53Ge2C3e0nrCRAgMB0BgXA6rr1ah/21dZLTDptxnKQ+ZQgQIECAQJpVu++++4Y+g3ZcqdLvgeOe3/EECBAg0ExAIGzm5CgCBAgQIECAAAECBAi0TkAgbF2XahABAgQIECBAgAABAgSaCQiEzZwcRYAAAQIECBAgQIAAgdYJCISt61INIkCAAAECBAgQIECAQDMBgbCZk6MIECBAgAABAgQIECDQOgGBsHVdqkEECBAgQIAAAQIECBBoJiAQNnNyFAECBAgQIECAAAECBFonIBC2rks1iAABAgQIECBAgAABAs0EBMJmTo4iQIAAAQIECBAgQIBA6wQEwtZ1qQYRIECAAAECBAgQIECgmYBA2MzJUQQIECBAgAABAgQIEGidgEDYui7VIAIECBAgQIAAAQIECDQTEAibOTmKAAECBAgQIECAAAECrRMQCFvXpRpEgAABAgQIECBAgACBZgICYTMnRxEgQIAAAQIECBAgQKB1AgJh67pUgwgQIECAAAECBAgQINBMQCBs5uQoAgQIECBAgAABAgQItE5AIGxdl2oQAQIECBAgQIAAAQIEmgkIhM2cHEWAAAECBAgQIECAAIHWCQiEretSDSJAgAABAgQIECBAgEAzAYGwmZOjCBAgQIAAAQIECBAg0DoBgfD/b78OiQAAABCI9W9NhdfcPIahuJtUIQIECBAgQIAAAQIECDQBh7A5SREgQIAAAQIECBAgQOBOwCG8m1QhAgQIECBAgAABAgQINAGHsDlJESBAgAABAgQIECBA4E7AIbybVCECBAgQIECAAAECBAg0AYewOUkRIECAAAECBAgQIEDgTsAhvJtUIQIECBAgQIAAAQIECDQBh7A5SREgQIAAAQIECBAgQOBOwCG8m1QhAgQIECBAgAABAgQINAGHsDlJESBAgAABAgQIECBA4E7AIbybVCECBAgQIECAAAECBAg0AYewOUkRIECAAAECBAgQIEDgTsAhvJtUIQIECBAgQIAAAQIECDQBh7A5SREgQIAAAQIECBAgQOBOwCG8m1QhAgQIECBAgAABAgQINAGHsDlJESBAgAABAgQIECBA4E7AIbybVCECBAgQIECAAAECBAg0AYewOUkRIECAAAECBAgQIEDgTsAhvJtUIQIECBAgQIAAAQIECDQBh7A5SREgQIAAAQIECBAgQOBOwCG8m1QhAgQIECBAgAABAgQINAGHsDlJESBAgAABAgQIECBA4E7AIbybVCECBAgQIECAAAECBAg0AYewOUkRIECAAAECBAgQIEDgTsAhvJtUIQIECBAgQIAAAQIECDQBh7A5SREgQIAAAQIECBAgQOBOwCG8m1QhAgQIECBAgAABAgQINAGHsDlJESBAgAABAgQIECBA4E7AIbybVCECBAgQIECAAAECBAg0AYewOUkRIECAAAECBAgQIEDgTsAhvJtUIQIECBAgQIAAAQIECDQBh7A5SREgQIAAAQIECBAgQOBOwCG8m1QhAgQIECBAgAABAgQINAGHsDlJESBAgAABAgQIECBA4E7AIbybVCECBAgQIECAAAECBAg0AYewOUkRIECAAAECBAgQIEDgTsAhvJtUIQIECBAgQIAAAQIECDSBASYrMDGCAKJ0AAAAAElFTkSuQmCC"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "SD.plot.generate_historical_datadrift_metric() # works if date_compile_auc and/or datadrift_file are filled"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "b54f3c39",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "SD.plot.generate_fig_univariate(df_all=SD.df_predict,col='Score',hue=\"dataset\") # works if deployed_model is filled"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "8a34f826",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "SD.plot.generate_indicator(\n",
    "                fig_value=SD.js_divergence,\n",
    "                height=280,\n",
    "                width=500,\n",
    "                title=\"Jensen Shannon Datadrift\",\n",
    "                min_gauge=0,\n",
    "                max_gauge=0.2,\n",
    "            ) # works if deployed_model is filled"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9de0ccc4",
   "metadata": {},
   "source": [
    "------"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2368d89a",
   "metadata": {},
   "source": [
    "### Compile Drift et generate report for Year 2019"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "5889552c",
   "metadata": {},
   "outputs": [],
   "source": [
    "SD = SmartDrift(df_current=X_df_2019,\n",
    "                df_baseline=X_df_learning,\n",
    "                deployed_model=model, # Optional: put in perspective result with importance on deployed model\n",
    "                encoding=encoder # Optional: if deployed_model and encoder to use this model\n",
    "               )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "dfb1ac16",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The computed AUC on the X_test used to build datadrift_classifier is equal to: 0.7856527709300022\n"
     ]
    }
   ],
   "source": [
    "SD.compile(full_validation=True, # Optional: to save time, leave the default False value. If True, analyze consistency on modalities between columns.\n",
    "           date_compile_auc = '01/01/2019', # Optional: useful when computing the drift for a time that is not now\n",
    "           datadrift_file = \"car_accident_auc.csv\" # Optional: name of the csv file that contains the performance history of data drift\n",
    "          )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "5a71d951",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "SD.plot.generate_historical_datadrift_metric() # works if date_compile_auc and/or datadrift_file are filled"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a82b2857",
   "metadata": {},
   "source": [
    "This result is interesting because we see that the auc is very high, but not the Jensen Shannon datadrift. This shows the interest of the latter."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "3753c08b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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oucts7SkmEOp93OV0JVJ/rau+2k59mbpZTXavQIcxv9Tb+48D7tM39YXkpi3abr+B0LvC7T1pc926dZlnYXM9Z+d1L3cgdPfBe1JqWKeM2gRC42dee1PsfCk2EGY7ZdR9oqz71S7mHx7CmB8l/T8GboYAAokWIBAmevhoPALRC/h9rktb6D04wXv65Sc+8QmnI7oq4n5nWKFAaHqf7QXaJux4v4hqGXcgzLbVNJ9qOVcI3f3V5wBtP+6Q7S6Tawume1VRv9Tr6q6+J1I/7mPxc50IWcpAaDvf3CuVYcwv89ylrbvfQKhmts+J2ZzW6w3T+d5DGMahMoXmZljvIbQJhO626fXFzpdiA6F3bPJZuf/RptTzo9AY8ecIIJAeAQJhesaaniJQEgHbL+imsmyn6HlX7NwN038R7+npyfyW9wue+0AUbx25go9e576v98uotqe5uXnY+wbNvTUQuU8pjTIQahvy9dd2QLO9W67QKpP31RPeutyrdTbtKHaFUO9d6NRT73NYYc2vQl/ktR3Znn8t9L5Jt5/7BNhsrrbbZssdCPXnTT/un2XTn1zPzRXqu87Z973vfcNeZWF7qEy2nwFtj/6jiG6Fdj9Xa/v3UZBAqP8Q9dGPfnTECcjuurM5FTLyMz9sfm65BgEE0iFAIEzHONNLBEomYBMINUTNnj3beeG1WVnyNkC/tG/atCnzhUivvfLKK52Xwt9yyy2ZL5LeLzi6zevOO+8c9rLy6667znlPntlGeNdddznhTkPLVVdd5bwiob+/X5qampxmZHv+y3tfvUbDmLbnda97Xab5UQfCfP21HVTvwThazuaLowYx/c/999+fCcvmACCzxc22DUECodah827r1q3D2qKrXjo++r62KOaX1qFzTFeyNQxo2HHPMf1zc3hRMSuEpg9qrnV0dXU5v+WuI9fPU7ZxKOeWUe3/bbfd5mzrNT+P5mcq3yqr33G2DYTqo9d6x+1d73pX5hk9v38fBQmEZrw0qN5zzz2ZvwfNWOvhT7o1OtunVPPD9meX6xBAoPIFCISVP8b0EAEEEEAAgdAFbF7DEnojqAABBBBAwLcAgdA3GQUQQAABBBBAwCtAIGROIIAAAskUIBAmc9xoNQIIIIAAArESIBDGajhoDAIIIGAtQCC0puJCBBBAAAEEEMglQCBkbiCAAALJFCAQJnPcaDUCCCCAAAKxEiAQxmo4aAwCCCBgLUAgtKbiQgQQQAABBBBAAAEEEECgsgQIhJU1nvQGAQQQQAABBBBAAAEEELAWIBBaU3EhAggggAACCCCAAAIIIFBZAgTCyhpPeoMAAggggAACCCCAAAIIWAsQCK2puBABBBBAAAEEEEAAAQQQqCwBAmFljSe9QQABBBBAAAEEEEAAAQSsBQiE1lRciAACCCCAAAIIIIAAAghUlgCBsLLGk94ggAACCCCAAAIIIIAAAtYCBEJrKi5EAAEEEEAAAQQQQAABBCpLgEBYWeNJbxBAAAEEEEAAAQQQQAABawECoTUVFyKAAAIIIIAAAggggAAClSVAIKys8aQ3CCCAAAIIIIAAAggggIC1AIHQmooLEUAAAQQQQAABBBBAAIHKEiAQVtZ40hsEEEAAAQQQQAABBBBAwFqAQGhNxYUIIIAAAggggAACCCCAQGUJEAgrazzpDQIIIIAAAggggAACCCBgLUAgtKbiQgQQQAABBBBAAAEEEECgsgQIhJU1nvQGAQQQQAABBBBAAAEEELAWIBBaU3EhAggggAACCCCAAAIIIFBZAgTCyhpPeoMAAggggAACCCCAAAIIWAsQCK2puBABBBBAAAEEEEAAAQQQqCwBAmFljSe9QQABBBBAAAEEEEAAAQSsBQiE1lRciAACCCCAAAIIIIAAAghUlgCBsLLGk94ggAACCCCAAAIIIIAAAtYCBEJrKi5EAAEEEEAAAQQQQAABBCpLgEBYWeNJbxBAAAEEEEAAAQQQQAABawECoTUVFyKAAAIIIIAAAggggAAClSVAIAwwnldccYX09vYGuANFEUAAAQQQQAABBBBAAIHyCRAIA9gTCAPgURQBBBBAAAEEEEAAAQTKLkAgDDAEBMIAeBRFAAEEEEAAAQQQQACBsgsQCAMMAYEwAB5FEUAAAQQQQAABBBBAoOwCBMIAQ0AgDIBHUQQQQAABBBBAAAEEECi7AIEwwBAQCAPgURQBBBBAAAEEEEAAAQTKLkAgDDAEBMIAeBRFAAEEEEAAAQQQQACBsgsQCAMMAYEwAB5FEUAAAQQQQAABBBBAoOwCBMIAQ0AgDIBHUQQQQAABBBBAAAEEECi7AIEwwBAQCAPgURQBBBBAAAEEEEAAAQTKLkAgDDAEBMIAeBRFAAEEEEAAAQQQQACBsgsQCAMMAYEwAB5FEUAAAQQQQAABBBBAoOwCBMIAQ0AgDIBHUQQQQAABBBBAAAEEECi7AIEwwBAQCAPgURQBBBBAAAEEEEAgMQIrV66UmTNnSlNT07A2b9++XRobG6W3t9e6Lxs3bhQt19HRYV2mmAtN27q7u6W6utrqFvr9vq2tTebPn291fSVcRCAMMIoEwgB4FEUAAQQQQAABBBBIjEApA2GcO00gjPPoxLBtBMIYDgpNQgABBBBAAAEEECi5gG0g3Lx5s2zZssVZSdSVQ/NxryCaa3SFUP/3qlWrRqww6irinj17ZP369aL/e8OGDcP6tHXrVpk9e7bze7t375aFCxeK/p7+t35WrFgh1157rfNrs0JoVgzdN1q3bp0sWbLE+a2lS5fKzp07h9Vj2m3qMH+o9/eulpYcPaIbskIYAJpAGACPoggggAACCCCAAAKJEfATCDXguQOTltWPhjv9uAOh/jrbqpz+ngl9Ggg13JkA6A2RJqzNnTt32DZU8/vuQPj0009nAqA7SJp7Z2uL9z4mPC5evDhzr8QMZJaGEggDjB6BMAAeRRFAAAEEEEAAAQQSI+AnEOoKofv5QF2Z01Bnfs8bCN2rgQrivd6L1N/fL7W1tZnAmC2waZlcv+++n64KuoNdtkCofb/++uuHPVdYqI2JGVgRIRAGGC0CYQA8iiKAAAIIIIAAAggkRiBoIHQfPOMNhN7gpnXpap/ZyqlI+nsaNN0fs4LoJxCa1UX3fdzbRnOtVuYaKD+H6cR1sAmEAUaGQBgAj6IIIIAAAggggAACiREIMxAqglmpu/rqq53VP/fJoPqdW1fxzJbTYlcITah0hzibFcJKP2iGQBjgx5BAGACPoggggAACCCCAAAKJEfBu6zQN9672eX+t13lfTZHtGvN7Gvz0YBcT/rKt/hUbCLMFO5tAmCsMJ2bwCjSUQBhgJAmEAfAoigACCCCAAAIIIJAYARPC3NsrTVhzv7ev2EBo7q8g7vt5w5/+uTl11O+WUW/4M0HVe9KovoPQfYKouc77fkK9X9jvUoxighAIAygTCAPgURQBBBBAAAEEEEAgUQLu0GYa7g1JxQZCvV+2LZ3uFUZTpwY4PcnUbyD0tl9PQtWw5z5Uxvt6iVyvndC2uINkogbS01gCYYDRIxAGwKMoAggggAACCCAQM4EzB/bJmf4n5NQzv5UTv/2ZjJlSJZNe+CoZPWmyTHjuS2TUuIkxazHNQSC4AIEwgCGBMAAeRRFAAAEEEEAAgZgInD15TE73PS777lwvgwf7srZqSu1fyOTXLpaxU6pj0mqagUBpBAiEARwJhAHwKIoAAggggAACCMRE4Ngvfij72j9esDXjn/NSqVm6SsYQCgtacUFyBAiEAcaKQBgAj6IIIIAAAggggEAMBAYP7ZMnP3WzdUsmv/rNMu3av3S2kfJBoBIECIQBRpFAGACPoggggAACCCCAQJkFzp44In2bVsvJJ37hqyXT6/9eLnjpfF9luBiBuAoQCAOMDIEwAB5FEUAAAQQQQACBMgucOdgnT3/+AzJ4ZL+vlky7+maZevVNvspwMQJxFSAQBhgZAmEAPIoigAACCCCAAAJlFjg9sEee2vAe36244CWvkeolfyejxk7wXZYCCMRNgEAYYEQIhAHwKIoAAggggAACCJRZ4OjP/lf6t3zSdyvGX/YCmX5js4yddqnvshSIl4D33YTd3d1SXZ2uk2QJhAHmJIEwAB5FEUAAAQQQQACBMgsMHuqXJz/1Tt+tuPAV10j14tt8l0tygY0bN8qGDRtGdMG8HN5P37K9vN6mvL5EvrGxccSlfl4Qv3TpUpk/f740NTU591m5cqXMnTtXlixZkrmvfsdva2tzrsv10WvyffSl96YOm755r9F2zZw5M9A9bOslENpKZbmOQBgAj6IIIIAAAggggECZBQYP98szX7hNTj/7lK+WXHL9+2Tyny3yVSbpF2sg3LNnj6xfvz7TFRPQ/IafoIGwt7c30wazwqehrqOjwzezfp/3hlqbQOiuyDi42+W7IZ4CBMKgghGVJxBGBE01CCCAAAIIIIBACAJnT52QZ+9ukSM77/V19xnv+1cZd3n+FSJfN0zAxdkCoTbbBDL3ipquwu3cuXNYr0xYyrbKZ1b48pXTm+ULXtlW/nSFTT9mZVO3g95+++2ZlTdvfRpstY5cbc81TLnatXv3blm4cGGmmDc4e1ddFy9e7ATubKuxxazE2k4rVghtpbJcRyAMgEdRBBBAAAEEEEAgBgKDhwbk6S/eKmeefdqqNVV1H5CL/vhNVtdW0kW5AqH2Uf9MQ5FZodOg5V6t09Uu/ZjVxVwrhIXK5QuE5s/MM4Ba55YtW0Zs/fSuvGVbDSzFCqEJg+5nErV/Gvp0e2o2A3f/WSFMyE8PgTAhA0UzEUAAAQQQQACBPAInn3hU9rV/XAYP53/9xLTXv1MunPdGGTt1euo88wVCDTerVq2SXFsmvUHOdsuot1y+QGgCmFlJyxWoogqEWs/1118/7DlEbb86aljW/9ZPrucMCYQJ+REjECZkoGgmAggggAACCCBQQGDw4D458N0vy7Ff/EjOnjw67Ooxk6uk6i8+IBNmzpbRF0xOpaXfQJjt0BUTGPMFwnzlkhQI8x06ow7erbPe000JhAn5MSMQJmSgaCYCCCCAAAIIIGAhMHjskJw7fULOHjsip/b2ypjJl8j4mufJucEzMvaSyy3uULmXFNoyag6cMSt17pM/bVYIbcrZbBk1obPcK4S22069zxkWan8YM4xnCAOoEggD4FEUAQQQQAABBBBAIDECtofKZFv9swmENuWKOVTGuyUzyi2jfl4bYQ7nKbTlNYwJQyAMoEogDIBHUQQQQAABBBBAAIHECGQLhGZ1y316ZrbQZk7z9J406t4m6aec91lF/U7ufe1EkBVC74mlhQYpW9vN73nfZ2gOjtH23XrrrVJdXe3c3nsIjfegnkJtCPLnBMIAegTCAHgURQABBBBAAAEEEEiMgJ8X03uv1e2j3kNnzCmgCmC2lxYq5+fF9EECYa5tnLkGy/a1E+6+moN43Pf0Pkfofg6R107E9EeFQBjTgaFZCCCAAAIIIIAAAgggYCXACqEVU/aLCIQB8CiKAAIIIIAAAggggAACZReo2EBo9iq7l2ZzaXuXbN2nIuUbIQJh2ecvDUAAAQQQQAABBBBAAIEAAhUZCL0vetTglm/fre4xXr9+fYbR9phYAmGAmUdRBBBAAAEEEEAAAQQQKLtARQZCbwD0BsRC6hoQ9aSiJUuW5L2UQFhIkj9HAAEEEEAAAQQQQACBOAtUXCA07/Bwn9KjW0J37tw5bBUw16CY8t4jYrNdTyCM89SmbQgggAACCCCAAAIIIFBIoOICofcdHgqQ7UWXuQKe/n62ZwjvueeeEUXe//73i/c9KIXA+XMEEEAAAQQQQAABBBBAIC4CeQPhvHnzfLVzx44dvq4P4+KgK4TaJj2QZvHixcO2jN5+++0jmtvS0kIgDGMQuScCCCCAAAIIIIBA6gRyvTswdRARd7jiAqH6BX2G0PaZQ7aMRjxbqQ4BBBBAAAEEEECgLALZXky/YsUKaQeNmh0AACAASURBVGpqKll7CIQlo/R1o4oMhIVOGdUg594Wmu2UUZtXTxAIfc01LkYAAQQQQAABBBBIqIB+v96zZ8+Ik/lLGQoJhOWZHL6fIVyzZo10dXU5rTXBS/93bW1teXqQo9Z87yHMFgi3bNmSuZNNGNSLCYSxGnIagwACCCCAAAIIIBCSQLZAaN7lrWdqeL9fazPMo1z6+rfq6uoReUEf0XK/+s0dCN1lZ8+enelVttfD6e+Zj74poKOjIySFyrytr0DofaZQJ0ZfX5+sXbtW2tvbnYmQpg+BME2jTV8RQAABBBBAAIH0ChQKhNkOcXSf9K8BT8/k8L7727trb+bMmc42VNtA6A2I2dqZ3lGz67l1IGxtbRU9RMX9UfBdu3Y5v19XVyfNzc12tVbIVQTCChlIuoEAAggggAACCCCQV8AbtExgM4EuW4DTHXsa7ubPn5/13t57+l0h1MD5zDPPDHuOMdsBkwxtfgHrQNjY2Cg9PT2ZbaI6uDqIuvxbX18vc+bMEX13X5o+BMI0jTZ9RQABBBBAAAEE0iuQ7VAZ72NW7kBnXgXnfkWb+T23onvbqN9AqNe7H/ty31e3qbq3mqZ35Ar33DoQ6nZRE/r0pe8mEOqzgyYsxuG1E4W7XLorCISls+ROCCCAAAIIIIAAAvEVsNmKuX37dicXaAj0HvJonjd0B7WgK4QcQlOa+VKSQGieLSQQlmZQuAsCCCCAAAIIIIAAAnESsAmE2l7zTJ8GQ3f4yxbe8gVCcy/vSp/7mcFszy3GySwpbbEOhGYVcPXq1VJTU5NZITSHyrBlNClDTjsRQAABBBBAAAEEEPAnYBsIzdZS72mfuZ5BzLVlVFunzyDq84fmXYfm3vqYmv6+eV7Q++oLDZ+33nqr82gbn8IC1oGws7PTOU0012f58uWybNmywjVW0BVsGa2gwaQrCCCAAAIIIIAAAjkFbAOheU4w22vc3K+F08Cooc79bkPvKqIJfKZRGgR1kcoEQvP73jcdeF9nwbDmF7AOhHobs0qY7ZZp2y6qBgRCfrwQQAABBBBAAAEEEEAgyQK+AqF21P1iev11Gl834f7XCPfJSUmeCLQdAQQQQAABBBBAAAEE0ifgOxCmjyh3j1khZDYggAACCCCAAAIIIIBAkgUIhAFGj0AYAI+iCCCAAAIIIIAAAgggUHaBvIHQvE7CtpVpe46QQGg7M7gOAQQQQAABBBBAAAEE4ihAIAwwKgTCAHgURQABBBBAAAEEEEAAgbILEAgDDAGBMAAeRRFAAAEEEEAAAQQQQKDsAtbPEHZ3dzsvhfS+gN6cOqrvJqmtrS17h6JsAIEwSm3qQgABBBBAAAEEEEAAgVILWAdC8w5Cb/DLFRRL3dA43o9AGMdRoU0IIIAAAggggAACpRQ4fvy46H/K8Zk0aZLof/iEJ2AdCM0BM973DrrfS8ihMuENFHdGAAEEEEAAAQQQQKAcAl/+8pflS1/rkDNjxkVa/Zgzp+XdNy6VhoaGSOtNW2XWgdCsEOYC8m4lTQMkK4RpGGX6iAACCCCAAAIIpFtAA+GanU/Jb//o2kghXvDz/5HmuZcTCENWtw6EZmtorvbwDGHII8XtEUAAAQQQQAABBBAogwCBsAzoEVZpHQi1TQMDA7JgwYIRzUvbVlEDwAphhDOVqhBAAAEEEEAAAQTKImAC4WMRrxA+nxXCSMbbVyCMpEUJqoRAmKDBoqkIIIAAAggggAACRQnEPRDqd3LvZ+vWrTJ79uyi+pu2QgTCACNOIAyAR1EEEEAAAQQQQACBRAhoIFy7c6889rJonyF8/s/vk9WvKvwMoX4nJwAWP5V8B0L3qaJarffU0eKbkrySBMLkjRktRgABBBBAAAEEEPAnkORAqN/X9SyU6upqp9Pbt2+Xnp4e5/3qfIYEfAVC8+qJbHhpfI6QQMiPEQIIIIAAAggggEClCyQhELrHwL1aSCAsPDutA2Fra6u0tLTkvOPy5ctl2bJlhWusoCsIhBU0mHQFAQQQQAABBBBAIKuACYS/i3jL6PN+fp+8u/qMXH311cPa9ZrXvCbnSG3evFlWrVolvb29zjUEwsKT2joQmvcQeoOfCYq8h7AwNlcggAACCCCAAAIIIJA0gXIGwpf/7gGZPHnyMDJtT76P+5lCAmHh2WYdCM120fb2didpm4+m7/r6eueXads2ygph4QnGFQgggAACCCCAAALJFnAC4cN7JfIVwl12h8p4dQmE/uabdSBkhXAkLIHQ32TjagQQQAABBBBAAIHkCWgg/LgTCN8QaeOft+s++dirLpOGhoac9eohMfqZP3++898bN250Do7p6Ohwfq3f19va2jJ/vnLlSpk5cyaHyrhErQMhzxASCCP9G4DKEEAAAQQQQAABBGIhEOdAuHv3blm4cOEwJ/P8oAmEixcvli1btjjXrFixwvlvThk9T2YdCLUIp4wO/5lkhTAWf0fRCAQQQAABBBBAAIEQBUwgfDziFcI/sFghLNRt7zOEha5P45/7CoQKxHsIz08TAmEaf2ToMwIIIIAAAgggkC4BAmFlj7fvQFjZHP56RyD058XVCCCAAAIIIIAAAskTyATCl0f7DKGzQvjK/M8QJk8zfi0mEAYYEwJhADyKIoAAAggggAACCCRCQAPhJx5+Wh6PPBB+Rz5KIAx9juQNhPmeGczWMl47Efp4UQECCCCAAAIIIIAAApEKEAgj5Y68MgJhAHJWCAPgURQBBBBAAAEEEEAgEQIEwkQMU9GNJBAWTTf0XhP3sbYBbkVRBBBAAAEEEEAAAQRiKWAC4e8j3jL63F1sGY1iQvgOhO3t7U4Q4kMgZA4ggAACCCCAAAIIVL6AEwh/+rREHggfIRBGMbt8B0JvozZu3Ci1tbVRtDV2dbBCGLshoUEIIIAAAggggAACJRbQQPiPTiBcUOI757/dcx/5jvz9Ky+VhoaGSOtNW2XWp4y2trZKS0tLXh8OlUnb9KG/CCCAAAIIIIAAApUuQCCs7BG2DoRehs7OTlm7du2w3yYQVvZkoXcIIIAAAggggAAC6RMgEFb2mFsHQlYIR04EtoxW9g8HvUMAAQQQQAABBBAQMYHwiYi3jD6HLaORTL/AzxCuXr1aFi1aFElj41YJgTBuI0J7EEAAAQQQQAABBEotkAmEr4j2GUInEM7hGcJSj6f3fr4DYZoPkfHiEQjDnp7cHwEEEEAAAQQQQKDcAkOB8Bl5IvJAuI1AGMHg+w6E+drEM4QRjBhVIIAAAggggAACCCAQoYAGwnVlCoSrWCEMfaQJhAGIWSEMgEdRBBBAAAEEEEAAgUQIEAgTMUxFN5JAWDQdL6YPQEdRBBBAAAEEEEAAgYQImED4ZMRbRmc9sk1YIQx/klifMhp+U5JXAyuEyRszWowAAggggAACCCDgT8AJhD3PSOSB8GcEQn8jVdzVBMLi3JxSBMIAeBRFAAEEEEAAAQQQSIQAgTARw1R0IwmERdMRCAPQURQBBBBAAAEEEEAgIQIaCNc7K4RvjLTFs362TVbOqZGGhoZI601bZQTCACPOCmEAPIoigAACCCCAAAIIJEKAQJiIYSq6kQTCoulYIQxAR1EEEEAAAQQQQACBhAgQCBMyUEU2M7GBcOPGjbJhwwan24sXL5b169fnJNi+fbs0NjZm/tx7/ebNm2XVqlXDyhe6p17MCmGRs45iCCCAAAIIIIAAAokRMIFwz5xot4zO1C2jr2DLaNgTJZGBUAOeBsKOjg7HZ+XKlTJ37lxZsmRJVi+9tr6+Xqqrq50/X7p0qRMizfUaCHfu3Jk3VGa7MYEw7OnJ/RFAAAEEEEAAAQTKLUAgLPcIhFt/It9D6A2A3oBYiEwDon6ampqc/yYQFhLjzxFAAAEEEEAAAQTSKqCB8J96+iT6FcJvy/9jhTD0aZfIQKgrfBrm5s+f7wDt3r1bFi5cKL29vVZg3kDp3TJqs11UK2KF0IqbixBAAAEEEEAAAQQSLEAgTPDgWTQ9kYFQg1hbW9uIQNjd3Z3ZFpqr7+Z5wnzhUe+/bt26YVtQtZz3o88l2oZQi7HgEgQQQAABBBBAAAEEYidAIIzdkJS0QdbPEGrY0lW5OXPmOGHMfNasWSNdXV3OM321tbUlbVyumxW7QmjCYKHgmG0LqfbT+7njjjsIhJGMOJUggAACCCCAAAIIlEvABMKnIj5UZsbP2DIaxZhbB0JdDevp6RkR/HIFxTAbX8wzhLZhUNtt+0whW0bDHGXujQACCCCAAAIIIBAHAScQ/qxPIg+EPQTCKMbfOhDOmzfPaU9dXZ00Nzdn2mZWCPU3duzYEUWbpdApo+aZQLOd0/trbyM1YJrXVvT39zsrne4tqbk6RSCMZLipBAEEEEAAAQQQQKCMAucD4ZsibcUMJxBOl4aGhkjrTVtl1oHQrBDmAvJuJQ0bMt97CL0BULeY6mslvB+zdVQD4ZYtWzJ/7H1+kEAY9mhyfwQQQAABBBBAAIG4Cmgg/KSzQhh9IPw7AmHo08I6EJqtoblaFOUzhKGrWFbACqElFJchgAACCCCAAAIIJFaAQJjYobNquHUg1LsNDAzIggULRtw4qq2iVj2K8CICYYTYVIUAAggggAACCCBQFgETCPdGvEJ4ec+3hRXC8IfcVyDU5rifGTQveNffj+qE0fBJ7GsgENpbcSUCCCCAAAIIIIBAMgUygfCV0W4ZdQLhy3mGMOxZ4ysQmoNlTKM0EPb19cnatWulvb3deVF7mj4EwjSNNn1FAAEEEEAAAQTSKTAUCPfJ3sgD4b0EwgimnHUgbG1tlZaWlmFN0kC4a9cu5/e9p49G0PayV0EgLPsQ0AAEEEAAAQQQQACBkAU0EP5zmQLhbawQhjy6ItaB0P0eQm2VvqReA2F1dbXU19ePeGF96C2PQQUEwhgMAk1AAAEEEEAAAQQQCFWAQBgqb9lvbh0IdbuoebWEOXHUnCxqwmLaDpchEJZ9/tIABBBAAAEEEEAAgZAFTCB8OuIto5f13CusEIY8uOJjhTBfIDTPFhIIwx8wakAAAQQQQAABBBBAIEoBJxA+sk8iD4Q/JRBGMc7WK4RmFXD16tVSU1OT2TJqDpWJ+sX0UeAUqoMVwkJC/DkCCCCAAAIIIIBA0gUIhEkfwfzttw6EnZ2dzmmiuT7Lly+XZcuWVbaWp3cEwlQNN51FAAEEEEAAAQRSKaCB8P9zVgivi7T/l/30XvnIy6uloaEh0nrTVpl1IFQYs0qYDSlt20XVgECYth8X+osAAggggAACCKRPgEBY2WPuKxAqhfvF9PrrNL5uwkwJAmFl/3DQOwQQQAABBBBAAAERAmFlzwLfgbCyOfz1jkDoz4urEUAAAQQQQAABBJInYALhM6+Kdsvopbpl9GVsGQ17xhAIAwgTCAPgURQBBBBAAAEEEEAgEQIEwkQMU9GNtA6E+moJPWF00aJFRVdWaQUJhJU2ovQHAQQQQAABBBBAwCuggfBTj/RL9CuE98iHWSEMfUL6CoTu1qTxVFHvaBAIQ5+fVIAAAggggAACCCBQZgECYZkHIOTqiw6EhENOGQ15bnJ7BBBAAAEEEEAAgRgIEAhjMAghNsE6EGoburu7nRfS5/ts3LhRamtrQ2xyfG7NCmF8xoKWIIAAAggggAACCIQj4ATCXf3SF/GhMjUPs2U0nBEdfldfgTBbg/TZQu8nLc8aEgijmKLUgQACCCCAAAIIIFBOAQJhOfXDr9tXILRZIdQmz5kzR9ra2sJvfZlrIBCWeQCoHgEEEEAAAQQQQCB0gfOB8PrQ63JXMLRCWCUNDQ2R1pu2yqwDYbaVQIPV3t4uGo7cgXHHjh0Vb0kgrPghpoMIIIAAAggggEDqBTQQ3u5sGY0+EN5KIAx9/hUdCLM9K9jb2yv19fVOowmEoY8dFSCAAAIIIIAAAgggELoAgTB04rJW4CsQFno20ARCtoyWdUypHAEEEEAAAQQQQACBkgmYQLhvbrQrhNMfvkdu/SO2jJZsIHPcyDoQmvJr1qyRrq6uzO3q6uqkubk57HbG8v5sGY3lsNAoBBBAAAEEEEAAgRIKEAhLiBnDW/kKhPmeI0zDFlHv+BEIYzijaRICCCCAAAIIIIBASQWGAuGARL9CeDcrhCUdyew3sw6Era2t0tLSkrNJy5cvl2XLlkXQ5PhUQSCMz1jQEgQQQAABBBBAAIFwBDQQfrpMgfBDbBkNZ1Bdd7UOhI2NjdLT0yPe4GeCYlqeG3SPCIEw9PlJBQgggAACCCCAAAJlFiAQlnkAQq7eOhCa7aLmFROmXWk7WZRAGPKM5PYIIIAAAggggAACsRJwAuHPy7BldOfd4meFsL+/X2pra2XdunWyZMmSWBnGuTHWgZAVwpHDyAphnKc2bUMAAQQQQAABBBAohYAJhP0RnzJa7SMQmjA4d+5cWbx4MYHQx8BbB0KeISQQ+phXXIoAAggggAACCCBQIQJJCIS6UNPd3S233367aCg0K4Tm96urq53R2L59u/MYXFNTU4WMTvBuWAdCrYpTRoeDs0IYfAJyBwQQQAABBBBAAIF4C2gg/MzPB6R/7psjbaiuEH7wjy6RhoaGvPXqd/KtW7fK7NmzZeXKlQRCn6PkKxDqvXkP4XlhAqHP2cblCCCAAAIIIIAAAokTKGcgfMGvt8vUqVOHmbW1tWV+vXTpUme1b/78+c7vEQj9Ty/fgdB/FZVbgkBYuWNLzxBAAAEEEEAAAQSGBDKBcF70K4Rvu/CwXHXVVcOG4sorr3R+bZ4bzDZOK1ascIIiW0YLz2ICYWGjnFcQCAPgURQBBBBAAAEEEEAgEQImEA5EHAirdMvoSwtvGXUjskLof0oRCP2bZUoQCAPgURQBBBAoo8DgwX0io0RO9f1ezvQ/KeMue76MvWSGjB4zVkZfOK2MLaNqBBBAIH4CSQ+EusXUvaV05syZHCrjmmZ5A2G+Q2SyTdUdO3bEbwaH2CICYYi43BoBBBAIQeDcqRNy5kCf9H3lH+TMs0+NqGH85S+U6Tf+g4ydOj2E2rklAgggkEyBoUC4X6JfIfxWSVYI9TUUW7ZscfB1K6l+OGX0/FwkEAb4uSQQBsCjKAIIIBCxwLlTx+Xoru/LwDc/U7Dm6Uv/Xib94TwZNeGCgtdyAQIIIFDpAhoIP1umQPgBn1tGvWPhfYaw0seqmP4RCItR+78yBMIAeBRFAAEEIhY4+fjP5ekv3mpd64wVbTKuaob19VyIAAIIVKqAEwh/UYYVwh3fEgJh+LOKZwgDGBMIA+BRFAEEEIhQ4MyBZ2Tvf6yQs0cOWNc6/rLnS81Na2TM1BrrMlyIAAIIVKKACYT7Iz5U5pISBMJKHI9S98l3IMz2XOG2bdukqqqq1G2L/f0IhLEfIhqIAAIIOAInf/8LefoLH/KtMevWTTKG5wl9u1EAAQQqS4BAWFnj6e2NdSDs7u7O+/Dlxo0bpba2trK1PL0jEKZquOksAggkWODIQ/fIQNcG3z2oufnjMumKV/suRwEEEECgkgTOB8K3RNqtoRXCi6WhoSHSetNWmXUgbGxslJ6enpw+c+bMET3SNU0fAmGaRpu+IoBAkgX2fe3jcuzRH/ruwpTav5CLr1vuuxwFEEAAgUoS0EC44Rf7Zf+86APhCgJh6FPJOhCaraJ1dXXS3NycadiaNWukq6vL+TWvnQh9vKgAAQQQQKAIgYM/2CIHtn3Bd8np71gtF7zkNb7LUQABBBCoJIFMIPzjMgTCl7BCGPZcsg6EZoXQuzXUbCVlhTDsoeL+CCCAAALFCpx87Gfy9H/e5rv4jPd/QcZVz/JdjgIIIIBAJQkQCCtpNEf2xToQmuDnXSHMFRQrm22od2wZTcMo00cEEKgEgVP7Hpe9//peX10ZfdE0uezd/yzjpj/XVzkuRgABBCpNwATCZyNeIbx4x7dkBSuEoU8n60CY7XTRfK1Lw/ZRAmHo85MKEEAAgZIJHH14m/R/49PW96u5+R9l0hXzrK/nQgQQQKBSBYYC4bMSfSC8i0AYwaQiEAZAJhAGwKMoAgggELHA4OEBOfj9Djn846Hn3vN9pl37btEDZUaNm1DoUv4cAQQQqHgBDYT/UqZA+H5WCEOfXwTCAMQEwgB4FEUAAQTKIHDmUL+c6N0hA52fyVr7qDHjpPqGlTLhuX8kYy6cWoYWUiUCCCAQPwEnED5ahhXCh+4SAmH488E6EIbflOTVQCBM3pjRYgQQQEAFTu39jeiK4cknHpVTT/1aJsyaLeNnvUjGVc2UsZfMAAkBBBBAwCVAIKzs6eA7ELpfM6EnjppP2l5Kr/0mEFb2Dwe9QwABBBBAAAEEEBAxgfBAxIfKTGOFMJLp5ysQeg+W0UDY19cna9eulfb2dicgpelDIEzTaNNXBBBAAAEEEEAgnQIEwsoed+tA2NraKi0tLcM0NBDu2rXL+X3v6yjKzbZ06VLZuXOn04x169bJkiVLcjZJ+7Fhw4bMnxe63lxIICz3KFM/AggggAACCCCAQNgC5wPhwrCrGnb/oRXCadLQ0BBpvWmrzDoQut83qEhNTU2iQaq6ulrq6+slTi+mN1tZtY360eC2detWmT17dtbxXblypaxfv975s/7+ftHtr/muJxCm7ceE/iKAAAIIIIAAAukV0ED4r48+KwdeHX0g/NvZBMKwZ551INTtoib0mZfUa/DS8GTCYlzePegNgN6AWAhVVxc1TM6fPz/vpawQFpLkzxFAAAEEEEAAAQSSLkAgTPoI5m9/SQKhebYwDoHQrPBpaNXVS/1s3rzZ2T5qVgELDWmhFUVWCAsJ8ucIIIAAAggggAAClSJgAuHBiFcIpz50l7BCGP4ssg6EZhVw9erVUlNTk9kyag6VicuW0d27d8vChQvFGwi3bNkiHR0dBUV1NXHPnj0jwuNDDz00ouw73vEO6e3tLXhPLkAAAQQQQAABBBBAIKkCBMKkjpxdu60DYWdnp3OaaK7P8uXLZdmyZXa1hnhVkBVCDYPbt2/PGhz1OUPvR0MmgTDEweTWCCCAAAIIIIAAAmUXGAqEByT6FcKtrBBGMPrWgVDbYlYJs7UrDttFTbuKeYYwXxjMNQ48QxjBDKUKBBBAAAEEEEAAgbIKaCDcuLsMgfDBrdLEoTKhj72vQKitcb+YXn8dt9dNaJsKnTKqQc79agmz+mf7jKE7eLJCGPocpQIEEEAAAQQQQACBMgoQCMuIH0HVvgNhBG0qSRX53kPoDoRmi6m30rlz5xZ85pAVwpIMFTdBAAEEEEAAAQQQiLEAgTDGg1OCplVsICyBTcFbEAgLEnEBAggggAACCCCAQMIFTCA8FPEpo1PYMhrJzLEKhAMDA7JgwYKsDWpvb3de/J7GD4EwjaNOnxFAAAEEEEAAgXQJnA+EdZF2fCgQTpWGhoZI601bZQUDofeZwWxAcXyOMIqBJBBGoUwdCCCAAAIIIIAAAuUU0ED4b7sPyKE/iT4Q3vJiAmHYY583EBZ61YS7cfp+wkWLFoXd3ljdn0AYq+GgMQgggAACCCCAAAIhCBAIQ0CN0S3zBkL3ayayvWfQHRjTuEpIIIzRTKYpCCCAAAIIIIAAAqEIEAhDYY3NTfMGwnnz5jkNnTNnjrS1tWVttHtLaZzeRRiFMIEwCmXqQAABBBBAAAEEECingAmEhyPeMjr5wa3CltHwR94qEGZbHTRNa21tlZaWFueXBMLwB4waEEAAAQQQQAABBBCIUmAoEB6U6ANhF4EwgoEmEAZAZoUwAB5FEUAAAQQQQAABBBIh4ATCX5YhEP6EQBjFBLEKhLYNYYXQVorrEEAAAQQQQAABBBBIhoAGwn8vUyD8G04ZDX2SEAgDELNCGACPoggggAACCCCAAAKJECAQJmKYim4kgbBoOhECYQA8iiKAAAIIIIAAAggkQsAEwiMRHypz0U+6hBXC8KdIwRfTh9+E5NZAIEzu2NFyBBBAAAEEEEAAATsBAqGdU1KvIhAGGDkCYQA8iiKAAAIIIIAAAggkQuB8IFwUaXuHVginSENDQ6T1pq0yAmGAEScQBsCjKAIIIIAAAggggEAiBDQQfu6XB+XIn0YfCN/3IgJh2JOEQBhAmEAYAI+iCCCAAAIIIIAAAokQIBAmYpiKbiSBsGg6DpUJQEdRBBBAAAEEEEAAgYQIEAgTMlBFNpNAWCScFmOFMAAeRRFAAAEEEEAAAQQSIWAC4dGIt4xe+JMuYcto+FOEQBjAmEAYAI+iCCCAAAIIIIAAAokQGAqEhyT6QNhJIIxghhQVCDs7O2Xt2rVO87Zt2yZVVVURNDV+VRAI4zcmtAgBBBBAAAEEEECgtAIaCFt+VYZA+ONOWc6hMqUdzCx3IxAGICYQBsCjKAIIIIAAAggggEAiBAiEiRimohtJICyajmcIA9BRFAEEEEAAAQQQQCAhAgTChAxUkc0kEBYJp8VYIQyAR1EEEEAAAQQQQACBRAiYQHgs4kNlLmDLaCTzg0AYgJlAGACPoggggAACCCCAAAKJEDgfCP8i0vYOBcLJ0tDQEGm9aausqECYNqRc/SUQMhMQQAABBBBAAAEEKl0gEwj/rAyB8AoCYdjzi0AYQJhAGACPoggggAACCCCAAAKJENBA+PlfHZJjZQiE7yUQhj5HCIQBiAmEAfAoigACCCCAAAIIIJAIAQJhIoap6EYSCIum41CZAHQURQABBBBAAAEEEEiIgAmExyNeIZz0405hhTD8SUIgDGDMCmEAPIoigAACCCCAAAIIJEKAQJiIYSq6kb4D4Zo1a6Srq8upcOPGjZmKa2tri25EUgsSCJM6crQbAQQQQAABBBBAwFbACYS9hyXyFcIHvskKoe0gBbjOVyCcN2/esKo0EPb19cnatWulvb3deS9fmj4EwjSNNn1FAAEEEEAAAQTSKaCB8D/KFAj/mkNlQp901oGwtbVVWlpaRgTCXbt2Ob9fV1cnzc3NoTc4LI4E0wAAIABJREFUThUQCOM0GrQFAQQQQAABBBBAIAwBAmEYqvG5p3UgbGxslJ6ensw20aamJud/V1dXS319vcyZM0fa2tri07MIWkIgjACZKhBAAAEEEEAAAQTKKmAC4YmID5WZ+MA3hRXC8IfeOhDqdlET+rq7u8UEQn120ITFHTt2hN/iGNVAIIzRYNAUBBBAAAEEEEAAgVAECIShsMbmpiUJhObZQgJhbMaVhiCAAAIIIIAAAgggUBKBTCCsfWtJ7md7E2eF8A8vkoaGBtsiXFeEgHUgNKuAq1evlpqamswKoTlUhi2jRehTBAEEEEAAAQQQQACBmAtoIGztPSwnyhAIl1kEQu/Blr29vTEXjVfzrANhZ2enc5pors/y5ctl2bJl8epdyK1hy2jIwNweAQQQQAABBBBAoOwCcQ6Eu3fvlkceeUSWLFniOG3evFm2bNkiHR0dZXdLSgOsA6F2yKwSZutc2raLqgGBMCnTnHYigAACCCCAAAIIFCsQ50Do7ZMGxIULF4pZJdTv63r+iR6EqZ/t27c7B2XqeSh8hgR8BUIt4H4xvf46ja+bMJOHQMiPEQIIIIAAAggggEClC5hAeDLiLaMTHvimLK467QQ89+cFL3hBTnJ9C4KGPrNCSCAsPDt9B8LCt0zPFQTC9Iw1PUUAAQQQQAABBNIq4ATCXx+RyANh9zdkYvc3ZNSoUcPot23bNmIodKvoqlWrnN93P0NIICw8a30FQsXVdw6a7aEDAwOyYMGCzK8LV1dZVxAIK2s86Q0CCCCAAAIIIIDASAENhF8oUyD8K4tDZdwt1tVBfcyNLaP2M9k6EJowqLfWVF5VVeVAa0B0/5591cm/kkCY/DGkBwgggAACCCCAAAL5BZIUCPv7+0Xfk26eG2SFsPDstg6E7mcH29vbnQNVzAvqtRpOGS2MzRUIIIAAAggggAACCCRNIM6BULeKvvzlL5fZs2c7rGbrqHuFsK2tTebPn+/8+cqVK2XmzJkcKuOahNaB0P0ewkWLFmVu0draKi0tLcJ7CJP2o017EUAAAQQQQAABBBAoLGAC4amID5UZ3/0NKbRl1Jwq6u6F9xnCxYsXO6+i0M+KFSuc/+aU0fNi1oFw3rx5TimzOmhu4d42mrZXT7BltPBfIFyBAAIIIIAAAgggkGyBTCB8zdsi7YgTCF94oTQ0NBRdr3fLaNE3quCCBMIAg0sgDIBHUQQQQAABBBBAAIFECBAIEzFMRTfSOhCaLaPeraG5fr/oFiWoIIEwQYNFU4sSGDyyX+TsWTnd94SMvmiqjLlgssjocTLmomlF3Y9CCCCAAAIIIJA8AQ2EX/z1ETlVhhXC9wRcIUyedvQttg6E5lnBXE3kUJnoB48aEQhLYPDIATn+ywfkcPc35HT/Hjl39oxT1egJF8rYaTVy8ZvfJxNmvlhGjZsQVhO4LwIIIIAAAgjERIBAGJOBCKkZ1oFQ6zergdnakrbnB9WAFcKQZiW3LavAmf4nZf/dn5Pjv96Rtx1Tr75JJs99k4yZOr2s7aVyBBBAAAEEEAhXwATC0xGvEI7r/oawQhju2OrdfQVCLeB+/YT+Oo2ni5phIRCGP0GpIVoB3SK6/+7Py7Fd91tVPO1Nfy2T//g6GT1+ktX1XIQAAggggAACyRNwAuFvjkjkgfBHBMIoZovvQBhFo5JSB4EwKSNFO20Fju64V/o7P2t7uXPdjFs+J+Mufb6vMlyMAAIIIIAAAskRGAqER8sQCL/OCmEE08RXIPSuDnrbl7ZtowTCCGYoVUQmcPboAem7c72cfKzHV51Tat8qF1/3Xl9luBgBBBBAAAEEkiOggbCtTIGwkUNlQp8o1oGw0KEy2tIoA+HGjRtlw4YNDpC+bHL9+vUFscyLK90vq9RCmzdvllWrVg0rb3NPAmFBci5IkMDgwX2y9z9WyODh/b5aPemKP5HqxbfJ6EkX+SrHxQgggAACCCCQDAECYTLGqdhWWgdC82L6fBVFFQi3b98uGgg7Ojqc5qxcuVLmzp0rS5Ysydq8/v5+qa2tzfxZtkC4c+dOq1DproBAWOy0o1wcBU7t/Y3s/dwtvps2Zsp0ufyvPytjplT5LksBBBBAAAEEEIi/AIEw/mMUpIW+A2FdXZ00NzcHqTNwWW8A9AbEXBXodXpSKoEw8BBwgwoUGDzUL3tuf5ecOzfoq3fjZ75Yat6xmkDoS42LEUAAAQQQSI6ACYRnXvu2SBs99kdfl8YXXCgNDQ2R1pu2yqwDoXl+cPXq1bJo0aKyOi1dulSamppk/vz5TjtybQX1NjJfIHRvGbXZLqr3ZoWwrNOAykssMHjkWen7z/8np/Y97uvOF7ziz2X64o/4KsPFCCCAAAIIIJAcgfOB8O2RNnooEF5AIAxZ3ToQ6qpafX19LF4zoUGsra1tRCDs7u6W6urqnGS5AqG3gN5/3bp1w7agPvrooyPuq6ul3tXGkMeL2yMQmsC506dkX/taOd77kK86pl1zs0x9/U2+ynAxAggggAACCCRHQAPhf/7mqJx5bfSB8N0EwtAninUgjNMzhKVeIfQq6yEz3mcK//Zv/3bEYNx7770EwtCnKBVEKTB4aJ/s+fRfyrmzdttGx894kdTc2Mx20SgHiboQQAABBBCIWIBAGDF4xNUlMhCW+hlCm0CYbVzYMhrxbKW6SASO//LH0vcVu+eEZ3zgSzLukssiaReVIIAAAggggEB5BAiE5XGPqtZEBsJCp4ya10h4t3Pm2jKqAdO8tsKcSOrekpprMAiEUU1T6olU4PQJObmnV/ZtXp/zFRTjn/MSmX7DKhk7dXqkTaMyBBBAAAEEEIhewAmEvz0qgxFvGR3zw68LW0bDH2/rQBh+U/zVkO89hN5A6H3thNbkfkZQA+GWLVsyDfA+P0gg9Dc2XF0ZAvpewhOP/UxOPP6InO77vYyeOEnGVs2S8TOukInPf6WMnZr7ed3KEKAXCCCAAAIIIKACQ4HwWBkC4X8TCCOYgokNhBHYFKyCFcKCRFxQIQJnjz4rck5k9EUXV0iP6AYCCCCAAAII2AoQCG2lknmdr0DY2toqLS0tOXsa1Yvp40JNIIzLSNAOBBBAAAEEEEAAgbAENBB+qUwrhH/JKaNhDWvmvtaBsLOzU9auXZu3QQTC0MeLChBAAAEEEEAAAQQQiFSAQBgpd+SVWQfCxsZG6enpIRC6BFghjHy+UiECCCCAAAIIIIBAxAImEJ59XbTvIRz9w/+Wv3w+L6YPe7itA6F5D6GuAq5Zs8ZpV3Nzs+jL4JuamkQPeamtrQ27vbG6P4EwVsNBYxBAAAEEEEAAAQRCEDgfCBeHcPfctxwKhJOkoaEh0nrTVpmvQDhnzhzR1zGY7aPbtm2TqqoqJyA+/vjjzp+l6UMgTNNo01cEEEAAAQQQQCCdAgTCyh53X4FQKTQE7t+/X+rr62X16tWyaNEiMdtJeYawsicLvUMAAQQQQAABBBBIn4AGwv/67TE5+7roVwjfxQph6BPOOhCa0GdWCc0WUncLCYShjxcVIIAAAggggAACCCAQqQCBMFLuyCuzDoRmm2hdXZ3z7KBuE+3q6so02Px+5D0oY4VsGS0jPlUjgAACCCCAAAIIRCLgBMLHyrBC+IP/FlYIwx9i60CoTdEQOGPGDFm2bJkMDAzIggULMi1M2+qgdpxAGP4EpQYEEEAAAQQQQACB8gqYQHgu4i2jowiEkQy8r0AYSYsSVAmBMEGDRVMRQAABBBBAAAEEihIYCoTHJfpAuIUVwqJGzF8hAqE/r2FXEwgD4FEUAQQQQAABBBBAIBECGgi/XKZA2MChMqHPEetAaA6R8b5v0LyH0Bw2E3qLY1QBgTBGg0FTEEAAAQQQQAABBEIRIBCGwhqbmwYOhL29vc4rKPSTtucICYSxmcc0BAEEEEAAAQQQQCAkgUwgnB/taydG/WCLNDyPF9OHNKyZ2+YNhOZVE7aNIBDaSnEdAggggAACCCCAAALJEDCBUCIOhEIgjGSC5A2E7tW/Qq1hy2ghIf4cAQQQQAABBBBAAIHkCZwPhEuibbwTCCdKQ0NDtPWmrLaCW0a97xvM5bNt2zapqqpKFR9bRlM13HQWAQQQQAABBBBIpQCBsLKHvWAgNN3PdahMZfPk7x2BMM2jT98RQAABBBBAAIF0CGgg3PTYcZH50a8Q3swKYeiTzDoQht6SBFZAIEzgoNFkBBBAAAEEEEAAAV8CTiD8XRkC4fYtQiD0NVRFXWwdCPWAmdraWlm2bFlRFVViIQJhJY4qfUIAAQQQQAABBBBwC5hAOCriFcJzBMJIJqJ1IDRbRpcvX04o/L+hIRBGMkepBAEEEEAAAQQQQKCMAkOB8IREHwg3s0IYwbhbB8LW1lZpaWlxmpS210vkGgcCYQQzlCoQQAABBBBAAAEEyipAICwrf+iVWwdCs0KYr0VpC4oEwtDnJxUggAACCCCAAAIIlFlAA+EdZVohfCeHyoQ++gTCAMQEwgB4FEUAAQQQQAABBBBIhEAmEF4Z7Smj57Zvlnf+Ae8hDHuSEAgDCBMIA+BRFAEEEEAAAQQQQCARAgTCRAxT0Y20DoRF11DBBQmEFTy4dA0BBBBAAAEEEEDAETCBcPSVN0QqctZZIZwgDQ0NkdabtsoIhAFGnEAYAI+iCCCAAAIIIIAAAokQIBAmYpiKbqTvQLhmzRrp6urKVFhXVyfNzc1FNyDJBQmESR492o4AAggggAACCCBgI6CB8Cu/OyHlWCG8iRVCmyEKdI2vQJjvpNG0nTCq6gTCQHOPwggggAACCCCAAAIJECAQJmCQAjTROhC630OYrb40vrCeQBhg5lEUAQQQQAABBBBAIBECTiB8vAwrhN/fLKwQhj9FrANhY2Oj9PT0iDf4maA4Z84caWtrC7/FMaqBQBijwaApCCCAAAIIIIAAAqEImEA4JuJDZQYJhKGMp/em1oHQbBdtb293tkqaT29vr9TX1zu/TNu2UQJhJHOUShBAAAEEEEAAAQTKKDAUCE9K9IHwTlYIIxh360DICuHI0SAQRjBDqQIBBBBAAAEEEECgrAIEwrLyh165dSDkGUICYeizkQoQQAABBBBAAAEEYieggfCrZVohvJFTRkOfD9aBUFvCKaPDx4MVwtDnJxUggAACCCCAAAIIlFkgEwivivbF9IPfv1NufC4vpg97+H0FQm0M7yE8PyQEwrCnJ/dHAAEEEEAAAQQQKLeACYRjIw6EZwiEkQy970AYSasSUgmBMCEDRTMRQAABBBBAAAEEihY4HwiXFn2PYgoOBcLx0tDQUExxylgK+A6E2baNbtu2TaqqqiyrrJzLCISVM5b0BAEEEEAAAQQQQCC7AIGwsmeGdSDs7u6WpqamnBobN26U2traytby9I5AmKrhprMIIIAAAggggEAqBTQQfu3xkzL2quhXCN/BCmHoc846EJrXTuRqES+mD32sqAABBBBAAAEEEEAAgcgFnED4+zIEwvvvFAJh+MNtHQjNVtG6ujppbm7OtMx9yAwvpg9/wKgBAQQQQAABBBBAAIEoBeIcCPv7+0fsUuzt7Y2SJ/F1WQdCs0Lo3RpqtpKyQpj4uUAHEEAAAQQQQAABBBAYITAUCE/JuIi3jJ6+v6PgCuH27dud9s6fP9/5b80qe/bskfXr1zOSlgLWgdAEP+8KYa6gaFl/oi/jGcJEDx+NRwABBBBAAAEEELAQiHMg9DZfA6KGwo6ODueP9Pu65pjq6mrn1/rnPT09ec9GsSCpqEusA2G+l9JnE0nD9lECYUX9LNAZBBBAAAEEEEAAgSwCGgjby7RCWO/zUJnNmzfLzp07MyuEBMLCU5pAWNgo5xUEwgB4FEUAAQQQQAABBBBIhEAmEL4+2lNGdcvo9F9tl5kzZw5zWrduXVY38zzh1q1bZfbs2c41BMLCU4xAWNiIQBjAiKIIIGAncPbEUTl3+ricO3lCRk2YJDJqlIyecIGMGjfR7gZchQACCCCAQEgC5QyELz/UK96dijfccMOInpow2NbWlnmekEBoNyGsA6Hd7dJ1FSuE6RpveotAGALnzpySE7/eIYcfvFvO9O+R088+JaPGTZBx1bNk7JRquWTh+2XMlKowquaeCCCAAAIIWAmYQDj+9fVW15fqolP3d0j9c8ZJQ0ND3lvmCoMEQruRIBDaOWW9ikAYAI+iCCAgp/uflCMPdMqhn2zNrTFqtNTUf0zGz3qxjJl8CWoIIIAAAghELhDnQLh7925ZuHChuLeJuoH0+7p71XDlypXOFtSmpqbIHeNaIYEwwMgQCAPgURSBlAucO35Ynr3vS3L4wW9ZSVz6rvUy8YWvsrqWixBAAAEEECilQJwDoZ4oumHDhhHdNSFQv68vXrxYtmzZ4lyzYsUK578JhOfJfAVC84qJXBMsDSeLev/FgRdflvKvG+6FQHoEju1+QPZ99R+sOzz6gqly+fINMnbaZdZluBABBBBAAIFSCGgg7HjilES+ZfR7HbLUYstovj56D5UphUel3cM6EK5Zs0a6urry9p9AWGnTg/4ggEAYAoOH9klf+yfk1JO/9HX7i697r0ypfauvMlyMAAIIIIBAUAECYVDBeJe3DoQ27yEkEMZ7sGkdAgjEQ+DMgWdkb8v75eyxg74adOErrpHqxbf5KsPFCCCAAAIIBBUwgXBCxIfKnCzBCmHQvqehvHUgNNtFly9fLsuWLYu9zdKlS52XUupH31WyZMmSgm32vsiyUAGeISwkxJ8jgEA2gVNPPyZ7//19vnHGX/5CmX7jGhk7tdp3WQoggAACCCBQrMBQIDwt0QfC9sBbRovtc5rKWQfC7u5u5+HLuro6aW5ujrWRPlyqH/OwqAa3XCcP6XXbt28XDbz60YdO169fb9U/AqEVExchgIBH4Mz+p2TPZ4f+zvHzGf+cl8j0G/6eQOgHjWsRQAABBAILEAgDE8b6BtaBUHtRaNtoXLaMegOgNyDmGhG9bs+ePQTCWE9ZGodA8gX0GcK9n/+ADB4e8NWZi171Rql66wd9leFiBBBAAAEEggpoILxTVwivjvY9hCe/1y43zCr8HsKg/Ut7eetAWOiEUYWMQyA0L6bUFc3q6qFtVbZbQfMFwt/97ncj5sob3vAG4ZTRtP8I0X8E/AsMHnlW9n1trZx84lFfhave/Ddy0Z/W+SrDxQgggAACCAQVIBAGFYx3eetAWGh1MC6B0Lyc0hsI9d0jHR0deUcjXyD8q7/6qxFl77//fgJhvOc3rUMgtgIaBp9utV/tGz/9D6Sm4RMyZur02PaJhiGAAAIIVKaACYQTI14hPMEKYSQTyjoQJuVQmbBWCLONBs8QRjJHqQSBihQ4d/qkHO7+ujx7339Z9W/GLZ+XcZf+gdW1XIQAAggggEApBc4HwneU8rYF7zUUCMdKQ0NDwWu5oHgB60CYpENleIaw+AlBSQQQiE5g8GCfHP3Fj+TZe1pyVjr24stl+tJVMrZqhoyecGF0jaMmBBBAAAEE/k+AQFjZU8E6ECZly6gOV6FTRjUwZnsVBYfKVPZkp3cIxFHg7KnjcuZAnxz5cZecHtgjp575nYy5YIqMq54lY6ddKlNe+3YZM4XXTMRx7GgTAgggkBYBDYSbnzwtE6+OeIXwf9tlCSuEoU+zigyEqpbvPYTeQOh+7YQRz/eaCnMNW0ZDn59UgECqBAaPHJBzp4/LqHETZdSYcTJ60kWp6j+dRQABBBCIpwCBMJ7jUqpWVWwgLBVQvvsQCId0zp04KqMmspUtijlHHQgggAACCCCAQNQCBMKoxaOtzzoQRtusZNRGIBQZPNgvfV9plunv+JiMvfiyZAwcrUQAAQQQQAABBBCwFhgKhGdkUsRbRo//79fYMmo9SsVfSCAs3k7SHAgHjx+WE70PSf+WT2YEq972YZn0oj+VMRdMDqBKUQQQQAABBBBAAIE4CRAI4zQapW8LgTCAaVoD4eChATnw3U1yZOe9I/QufOW1Mu2aBhk7rSaALEURQAABBBBAAAEE4iKggXCLrhBeE+2hMrpCuHgmr50Iex4QCAMIpy0QOqchDuyVfV9bI2cOPJNTbsyU6XLpO/9BxlbNdA7H4IMAAggggAACCCCQXAECYXLHzqbleQOhzasm3JXs2LHDps6KuSZNgVAD4IlfPSgDd220Hr9pb3yPTH75VTJ6CquF1mhciAACCCCAAAIIxEyAQBizASlxcwiEAUBTFQiPPCt7P/seOXvqmLXYqHETZOaHviRjLrzYugwXIoAAAggggAACCMRLwATCCyLeMnqMLaORTAQCYQDmNAXCsyeOysDXPyXHdndbi0160Z9I9dtv411q1mJciAACCCCAAAIIxE/gfCC8MdLGDQXCMdLQ0BBpvWmrjGcIA4x4mgKhMh195HvSv/mfrMX01NGLXnmt9fVciAACCCCAAAIIIBA/AScQ7jkjF1wTcSD8LoEwitlAIAygnLZAOHh4QPZ85t1y7sypgmqjRo2RGR/eJGMnX1LwWi5AAAEEEEAAAQQQiK+ABsL/LlMgfDsrhKFPDAJhAOK0BcKzx49I/5Z/luO9PymoNvGFc2X60r+X0RMvLHgtFyCAAAIIIIAAAgjEV4BAGN+xKUXLCIQBFNMWCJXqyE/vc54lLPSpWtgkF736LYUu488RQAABBBBAAAEEYi5gAuGFEW8ZPfrdrwkrhOFPDgJhAOM0BsIzh/fLU5+6Wc6dG8wrN+vWTTJm6vQAuhRFAAEEEEAAAQQQiIPAUCAclOgD4VcJhBFMAAJhAOQ0BsJzetro3Z+TU088mlNu3IwrpOr65TL6wmkBdCmKAAIIIIAAAgggEAeBTCD882gPlTn63a/K22dwymjYc8B3IFyzZo10dXU57dq48fxLymtra8Nua+zun8ZAqINw5sgBETmXczxGjxpFGIzdbKVBCCCAAAIIIIBAcQIaCL+uK4RlCIRvIxAWN2g+SvkKhPPmzRt2aw2EfX19snbtWmlvbxcNSGn6pDUQpmmM6SsCCCCAAAIIIJB2AQJhZc8A60DY2toqLS0tIwLhrl27nN+vq6uT5ubmytby9I5AmKrhprMIIIAAAggggEAqBQiElT3s1oGwsbFRenp6MttEm5qanP9dXV0t9fX1MmfOHGlra6tsLQJhqsaXziKAAAIIIIAAAgiImEB40Z/fFCnHke9+Vd42Y7Q0NDREWm/aKrMOhLpd1IS+7u5uMYFQnx00YXHHjh2p8mOFMFXDTWcRQAABBBBAAIFUCjiB8KlBiTwQ/g+BMIoJV5JAaJ4tJBBGMWTUgQACCCCAAAIIIIBAdAIaCL9RpkD4VlYIQx9o60BoVgFXr14tNTU1mRVCc6gMW0ZDHysqQAABBBBAAAEEEEAgcgECYeTkkVZoHQg7Ozud00RzfZYvXy7Lli2LtPHlrowto+UeAepHAAEEEEAAAQQQCFuAQBi2cHnvbx0ItZlmlTBbk9O2XVQNCITlnbzUjgACCCCAAAIIIBC+wFAgPCuTIz5U5vD/fEXYMhr++PoKhNoc94vp9ddpfN2EGRYCYfgTlBoQQAABBBBAAAEEyiuQCYTXRnvKqBMIL+eU0bBH33cgDLtBSbo/gTBJo0VbEUAAAQQQQAABBIoRIBAWo5acMtaBULeL6ism0vacYL6hJBAmZ6LTUgQQQAABBBBAAIHiBDQQflO3jJZhhfAvWCEsbtB8lLIOhObVEmk8PCaXJ4HQx0zjUgQQQAABBBBAAIFEChAIEzls1o22DoStra3S0tLi3DiNB8hkEyUQWs8zLkQAAQQQQAABBBBIqIAJhFMiXiE89D9fEVYIw5801oHQrBDma1LagiKBMPwJSg0IIIAAAggggAAC5RVwAuHeszLl2ndG2pBD92kgHCUNDQ2R1pu2ygiEAUacQBgAj6IIIIAAAggggAACiRAgECZimIpuJIGwaDreQxiAjqIIIIAAAggggAACCRHQQNhZphXCRawQhj5LrANh6C1JYAWsECZw0GgyAggggAACCCCAgC8BAqEvrsRdTCAMMGQEwgB4FEUAAQQQQAABBBBIhACBMBHDVHQjrQMhh8qMNCYQFj3vKIgAAggggAACCCCQEIGhQHhOpr4h2kNlDt53hyy6jENlwp4mBMIAwgTCAHgURQABBBBAAAEEEEiEAIEwEcNUdCMJhEXTcahMADqKIoAAAggggAACCCREQANhV5lWCOtYIQx9llgHwlwtaWxslJ6eHmlvbxddMUvThxXCNI02fUUAAQQQQAABBNIpQCCs7HEPHAg7Oztl7dq1UldXJ83NzZWt5ekdgTBVw01nEUAAAQQQQACBVAoQCCt72AMHwjVr1khXV5ejtGPHjsrWIhCmanzpLAIIIIAAAggggICIEwifPifT3nBzpBwHvnOH1F0m0tDQEGm9aavMOhByyujIqcEKYdp+XOgvAggggAACCCCQPgECYWWPeckC4fLly2XZsmWVrcUKYarGl84igAACCCCAAAIIsEJY6XOgJIEwjc8P6sRghbDSfzzoHwIIIIAAAggggICuEG4t05bRhWwZDX0CWgfC0FuSwAoIhAkcNJqMAAIIIIAAAggg4EuAQOiLK3EXEwgDDBmBMAAeRRFAAAEEEEAAAQQSITAUCEUujvhQmWe/s0lYIQx/ilgHQnOozMaNG6W2tjbTsu7ubmlqapI5c+ZIW1tb+C2OUQ0EwhgNBk1BAAEEEEAAAQQQCEUgEwgXRHvKqBMIL+WU0VAG1XXTwIGwt7dX6uvrnVvy2omwh4v7I4AAAggggAACCCAQrQCBMFrvqGvLGwgbGxulp6fHuk0EQmsqLkQAAQQQQAABBBBAIBECGgjv0i2jZVghfIuPFULdvbd161aZPXt2Ilzj0si8gdC9+leowWwZLSTEnyOAAAIIIIAAAgggkDyBuAfCpUuXys6dOx1YAqH/+VVwy+iaNWukq6ur4J23bdte+/GlAAAgAElEQVQmVVVVBa+rpAt4hrCSRpO+IIAAAggggAACCGQTiHsg1Db39/c755x4A6F+X9czT6qrq52ubd++3dkBqWeg8BkSKBgIDVSuQ2XSDEkgTPPoD+/72dMnRU4ek7MnjsmoiZNk9MSLZNTY8QAhgAACCCCAAAKJF9BA+K1nRC6JeMvo/m2b5A0XnxJdAXR/Jk+ePMKUQFj8NLMOhFpFa2urtLS05KyNZwiLHwhKJlNg8MizcrTnf+XUnt1yuv9JOTOwR8ZWz5Jx1bNk4nNeIpNedqWMueiSZHaOViOAAAIIIIAAAiKigfDuZ0SqIg6EA9s2yRPf/LwcO3Zs2Dg8/PDDBMISzkzrQNjZ2Slr167NW3WUgVBff7FhwwanPYsXL5b169fnbVu+6zdv3iyrVq0aVt7mnqwQlnAmJvBWpwf2yLPf+nc58esdOVt/wcuukmnXvkvGXjIjgT2kyQgggAACCCCAwPlAWP3GaF870b9tk1xfY/faCVYIi5+p1oHQ5sTRqAKh7v3VgNfR0eH0fOXKlTJ37lxZsmRJVolC12sg1AdRC4VK780JhMVPvKSXHDw0IH1tH5HT+58q2JVxl71Qpt/ULGOn1hS8lgsQQAABBBBAAIG4CegK4T3PiEyPOBDu27ZJriMQhj4drAOheYZQQ58eNKOf5uZm5yFNfSjT+8L6MFvuDYDewOetu9D1BMIwR6vy7n3u9Ek5+J02OfRAp3XnJr/27TLtmptl1LiJ1mW4EAEEEEAAAQQQiIOABsJ7nxGpiTgQ9m3bJG8qQSBsa2uT+fPnO5SaC2bOnMmhMq6J5SsQmldLmO2j5mRRDYiPP/64KHYUH32wVEOoGdjdu3fLwoULRV+Tke1T6HrvltFs20V1Gdr70ZOMctUZhQN1lEfg9L4nZO+/LvNd+YwVX5CxVbN8l6MAAggggAACCCBQTgENhN/uE7k04kD4zLc3yRstAqH7tRPq5P4urzv69NdbtmxxCFesWOH8N6eMnp9RvgKhFtMQuH//fqmvr5fVq1fLokWLxGwnjWrLqA6sO+mbQOg+Utb9Q1PM9evWrRu2BVX76/1ofwmE5fzrqTx1H+99UPZt+pjvyi9t/GeZ8LxX+C5HAQQQQAABBBBAoJwCGgi3lSkQLrAIhPlsvK+dKKdjXOu2DoQm9JlVQrOF1N2xqAJhoRU/L7bf6223kPIMYVyndbjtOvjdO+Tg9+7wXcm0N/21THnN23yXowACCCCAAAIIIFBOAQ2E3+kTuexN0R4q8/S3N8kbptsdKpPLh0BYeOZYB0KzTbSurs55dtD7wnrz+4WrDH5FoWcCvTX4vZ5AGHyMKvkOB7Z9UQ79YLPvLk59/Y0y9ZoG3+UogAACCCCAAAIIlFNAA+F9fSKXRxwI9357k1wbMBCW0y0pdVsHQu2QhsAZM2bIsmXLZGBgQBYsWJDpZ1Srg1qhzamh+hoJs52z0PUaGM0Jo+bIWveW1Hz/4sCW0aRM9dK188SvfiJ9d6z2fcPpN/+jTLpinu9yFEAAAQQQQAABBMopYALhjIgD4VMEwkiG3VcgjKRFlpXYvFfQHdbyXa+B0DxoqtV7nx8kEFoOSkouO92/R/b+y3t893bGB78kYy++zHc5CiCAAAIIIIAAAuUU0ED4P/tEZkYcCPfcu0n+nBXC0IfedyB0bxXVkGU+euJm2j48Q5i2ER/q79njR+TZe1rk6E/vswaY/MfXydRrG2X0BZOty3AhAggggAACCCAQBwENhN/dJzIr4kD45L2b5BoCYehTwFcg9B4ko4Gwr69P1q5dK+3t7aIBKU0fAmGaRnt4X88c6JO9n7tFzh0/XBBh9OQqufyvPyNjeDF9QSsuQAABBBBAAIH4CWgg/N8yBcKrCYShTwjrQNja2iotLS3DGqSBcNeuXc7vR3moTOgqlhUQCC2hKvSy032/k4H//pSc2vvrnD0cP+vFUrXogzLu0udVqALdQgABBBBAAIFKF9BA+L19Is+5LtpTRp+4d5O8vjrYKaOVPjal6J91IDSvnTDbRPVljvq/q6urnXcSmtdRlKJRSbkHgTApIxVeOwcPD8jhBzrl1J5fyen+J2XwUL+zEjiuaqaMf85smfzqN8uYKdXhNYA7I4AAAggggAACIQtoILx/n8hzIw6Ev793k1xFIAx5dEWsA6FuFzWhT18AbwKhPjsY9YvpQ1exrIBAaAmVgssGjxwQGTwtZ48eFJk0WUaPGy9jLro4BT2niwgggAACCCBQ6QJOIOwX+YOoA+E9m+RKAmHo06skgdA8WxjlqydCl7GogEBogcQlCCCAAAIIIIAAAokW0ED4/X6R50UcCB+/Z5PMJxCGPnesA6FZBVy9erXU1NRkVgjNoTJsGQ19rKgAAQQQQAABBBBAAIHIBTQQbu8XeX7EgfB392yS1xEIQx9v60DY2dnpnCaa67N8+XLnhfVp+rBCmKbRpq8IIIAAAggggEA6BTQQ/qBf5AXXR3uozGP3bJLXVnGoTNizzjoQakPMKmG2RqVtu6gaEAjDnp7c3wicPXFUzp06IWdPHpPR4yfKqDFjZfTEC0TGTgAJAQQQQAABBBAIVUAD4Q/LEAh/SyAMdVzNzX0FQi3kfjG9/jqNr5sweATCSOZoqisZPHZYTv3+ETn84N3OKaZnnn1aRo0dL+OqZ8nYKdVySd0KGTOlKtVGdB4BBBBAAAEEwhXQQPijfpEXRrxC+Jt7NslrWCEMd3DFxymjobckgRUQCBM4aAlq8umnH5PDD31LDv/krtytHjVaauo/JuNnzZYxkznVNEHDS1MRQAABBBBIjIAGwu4BkT+MOBD++u5NUksgDH2e5F0hNKeH6kEyixYtCr0xSauAQJi0EUtOe88ePyIHvtMmhx+626rRNQ3/KJP+cJ7VtVyEAAIIVKrA2dMn5eRvHpbRky6S8TP+UEaNm1ipXaVfCEQqYALhFWUIhH9GIAx9rH0FQvP+QW1VGp8Z9I4GgTD0+ZnaCo49+iPZ97Xchzh5YUZPmiKXv2+jjJ1Wk1ozOo4AAukWOHt4vxz8wZ1yqPubDsS0q2+Wi+a9UcZMqU43DL1HoAQCGggfGBB50ZujPVSm9+5N8qeXcKhMCYYw7y0IhAGECYQB8CiaU2Dw4D7p6/hHOfXkbl9KF1/3XplS+1ZfZbgYAQQQqASBM/v3yr72j8upp387rDvjZ71YaupX86x1JQwyfSirgAbCHw+IvDjiQPiruzfJnxAIQx97AmEAYgJhADyK5hQ4c6BP9n6uSc4eP+RL6cJXXC1Viz4go8Zx8qgvOC5GAIHECgwePyInfvmA9H/9U3n7UF3/MZn4vFfImAsmJ7avNByBcgpoIPxJGQLhLwmEkQw7gTAAM4EwAB5Fcwrov3Dv/fe/8S00/rIXyvSb1sjYqWyP8o1HAQQQSJyA/uPZge9+WY7+9D6rtk+e9yaZevXNrBZaaXERAsMFNBA+uF9kdsQrhLu/tUlezQph6NORQBiAmEAYAI+iuVcI9z8lez7b6FtownNeKtOXruJ5Gd9yFEAAgaQJnDtzUvbf/Xk5Ynnwlunf1CvrZdq1f5m07tJeBMouoIHwof0iL4k4ED76rU3yxwTC0MffKhDatiJtB80QCG1nBtf5ERg82Cd7/+ODMnh4wE8xuehVb5Sqt37QVxkuRgABBJIqcOKxn8kz/3mbr+Zf9t5/kQkzX+SrDBcjgICIBsId+0VeGnEg/P/bu//Yqso8j+NfoLQUAaGU8nuQmanTGX7DqHQER4cRXAU0Ki3JJmS3GxNn7WbX/WfFGA3uhGbXXRMnzSwTNuyOZAwU1iA/HFDHH9uRqiMVRJSxIjhIB0tbFBRKKXbz3Hi6h8O5957T5zznnnvO+yaTCe15nvN8X99zaz89P+77uzbKPAKh8UOQQKhBTCDUwGNoWoFLX55OPWH0wvEPfCmNvuNvZdgNy32NYWMEEEAgXwV6vmiTk7/6B7n0ZaenEgpGjZexf1UnBaPGedqejRBA4P8FrEA4bWm4TxlVgXDuKJ4yavpYJBBqCBMINfAYmlFAhcGT672f7SscM0XKVv1cBl09BlkEEEAgEQK9F7ukY9tT8tXBVzzVO2zebVJyx89kQAEP3vIExkYI2ARUIGzuFJkeciA8tGujzCEQGj8WMwZC43vP8x0QCPO8gRFefu/FC3K26Vk5/dKvPa1ywgO/ksFjp3jalo0QQACBuAh0HWmWz379sKdyxv3Nv0nRlOmetmUjBBC4XEAFwndOi8wIORC+t3OjzCYQGj8cCYQaxARCDTyGZhVQ9xKqD6jvfH5d2m0LSibKmKrVUjB6vAwsuirrnGyAAAIIxElA3WvdWv+zrB/TU3B1mZTVPCGDR42NU/nUgkBoAioQ7s9BIDxIIAylxwRCDWYCoQYeQz0J9HZ3ibpP5uxbO6Wn44R0f3ZMBhUPl4LSSVIwamzqg+gHjeBjJjxhshECCMRO4NK5s9K5/Rdy7v3GjLUNm3OrlCyt5XNaY3cEUFBYAioQHjgtMjPkM4Tv7twoszhDaLzNBEINYgKhBh5DfQuoh830XjgnA4qKZdCQYSIFhb7nYAACCCAQN4Hzh34vbZt/nrGssX/9rzJk6sy4lU49CIQmoALhwc6vZfbSvwxtn2pH+3f9RmaMGiirVq0Kdb9J2xmBUKPjBEINPIYigAACCCAQgMClMx0iAwZIb2+v62wDBw6Ur3suSsHIsgD2xhQIJFNABcJDnRdl7h0rQwVo3rVJppUMJhAaVicQagATCDXwGIoAAggggAACCCCQFwIqEH7Q0SXX3V4V6nrffn6LVIwuIhAaVicQagATCDXwGIoAAggggAACCCCQFwIqEH7Yfk5uuP2eUNf75m//R64dPZRAaFidQKgBTCDUwGMoAggggAACCCCAQF4IqED40amzUvkXd4W63qbd2+S7pcMJhIbVCYQawARCDTyGIoAAAggggAACCOSFgAqEH5/6XBbctjzU9b6+e4dMHXM1gdCwOoFQAzgfAuEnX3ZL4UCRI2e6peNCj1SMHCIjCwdJ8aBBMkJ9gxcCCCCAAAIIIIAAAhkEVCA81tYhNy25I1Snxj3Py5SyEgKhYXUCoQZwlAPhme5L8k7HOfnnd1rl9IVLl1U5tGCgLJowQv5uWpmMHlKgIcBQBBBAAAEEEEAAgbgLqEB4/LNTcvOS20It9dUXdsvksjEEQsPqBEIN4KgGwrauHmk40in/9WF7xupKhxTIv8+fLNNHFWsoMBQBBBBAAAEEEEAgzgIqEJ44eVIWLV4capkvv/iiTBg7lkBoWJ1AqAEcxUB4vudrefboaXnyvc88VTZl2GD5jwVTZWwxZwo9gbERAggggAACCCCQMAEVCP988oTceuuiUCt/6cWXZdy4CQRCw+oEQg3gKAbCQ6fPy6pXj/qq6p6pJfKPM8tkyEDuKfQFx8YIIIAAAggggEACBFQgbPvzcVny05tDrXbPS69K2fjJBELD6gRCDeAoBsLffNQhTx70dnbQKv2aYYXyyxunyNihgzU0GIoAAggggAACCCAQRwEVCNtbj8ntP70p1PJ++7tGGT1+CoHQsDqBUAM4aoHwwte9smbfCdnz6RnfVe2+7VoZw2Wjvt0YgAACCCCAAAIIxF1ABcLOE0dk6aIbQy1118t7ZdSEbxMIDasTCDWAoxYIT57vkb9//Zh8dLbbd1VPXD9ZfjJxuO9xDEAAAQQQQAABBBCIt4AKhF+caJHlP5kfaqHbX35Drp5YTiA0rE4g1ACOWiA8e/GSPPZ2q7x28qzvqnYuKZfxXDLq240BCCCAAAIIIIBA3AVUIDz76WG565brQi112yt/kOGTKgiEhtUJhBrAUQuEqpR175+S9X885auqccWD5T9vuoZA6EuNjRFAAAEEEEAAgWQIqED41fFDcs8t80It+NlXm2XopB8QCA2rEwg1gKMYCF9qPSP/9Oanvqr6YelQeWL+ZBkxeJCvcWyMAAIIIIAAAgggEH8BFQi7/nRQVtw8O9Rit7y2X4ZMnkEgNKxOINQAjmIg/KL7kvzivTbZ9slpT5UVDBggO5Z8V8qKecKoJzA2QgABBBBAAAEEEiagAuGFT/ZL1Y9nhlp5w/8elKJvzSIQGlYnEGoARzEQqnJaz3XL6jdPyHufn89a3ZM3TJIfTxiRdTs2QAABBBBAAAEEEEimQCoQHmuWqoXTQwVoaDwkRdfMIRAaVicQagBHNRCqkk6d75H//rBdNn3c6Vrht4YNln+5frJMuqpQhhbwgfQahwFDEUAAAQQQQACBWAukAuHRt6VqwfdDrbPh9x9I0dQfEggNqxMINYCjHAhVWV2XeuVg53n5ortH3mr7Stq7emTemKHy/ZHFMv6qwTKey0Q1us9QBBBAAAEEEEAgGQKpQHjkLam68XuhFtyw949S9O3rCYSG1QmEGsBRD4QapTEUAQQQQAABBBBAAIGUQCoQfvSGVP2oPFSRhqYWKfrOfAKhYXUCoQYwgVADj6EIIIAAAggggAACeSGQCoQtr0vV/O+Eut6GNz6WovIfEQgNqxMINYAJhBp4DEUAAQQQQAABBBDIC4FUIPywUapumBrqehvePCZF1y4gEBpWJxBqABMINfAYigACCCCAAAIIIJAXAqlAePg1qbp+SqjrbfjDn6ToezcRCA2rEwg1gAmEGngMRQABBBBAAAEEEMgLgVQg/OAVqb5ucqjrbXj7uBRW3EIgNKxOINQAJhBq4DEUAQQQQAABBBBAIC8EUoHw/d9J9bwJoa63YV+rFP5gEYHQsDqBUAOYQKiBx1AEEEAAAQQQQACBvBBIBcJDL0r13HGhrreh+aQUTruVQGhYnUD4DXB1dbU0Nzen/rV27VpZsWJFVnoCYVYiNkAAAQQQQAABBBDIc4FUIDy4R6rnlIVaScP+NimcvoRAaFidQCgi9fX1Keba2trU/6ugt2PHDqmoqMjITyA0fHQyPQIIIIAAAggggEDOBVKB8N3npXp2aahraTjQLoUzbs8aCBsbG6WmpqZvbS0tLaGuM993RiB0CYDOgJiuyQTCfD/8WT8CCCCAAAIIIIBANoFUIDywU6pnlmTbNNDvN7zbKYWzlmYMhO3t7VJZWSlNTU1SWloqW7ZsSV31V1dXF+ha4jxZ4gOh8yBSzXY7kLq6uq44DmbMmCH8BSLObw9qQwABBBBAAAEEEEgFwv3bpXrGyFAxGg5+LoWzl2cMhM7f291+tw910Xm4s8QHwsOHD8uyZcv6/qpgBcKtW7fK5s2b+1qqtnG+1FgCYR4e9SwZAQQQQAABBBBAwLNAKhA2b5Pq6cM9jwliw4ZDZ6Vwzl0ZA6HblX1eb/8KYo1xmCPxgdDrGUK3ZnPJaBzeAtSAAAIIIIAAAgggkElABcJ3dm+SaWWFoUIdauuWCyOvST3fw/568MEH+/65evVqmThxYt+zQNQ31PYbNmyQhQsXhrrefN1Z4gOhddDYHyLDPYT5ejizbgQQQAABBBBAAIGgBQ4cOCDqf7l4HT16NHVvoP31wAMP9P2TM4T6XSEQ8pRR/aOIGRBAAAEEEEAAAQQQyIEA9xDqoxMIvzHkcwj1DyZmQAABBBBAAAEEEEAgTAGeMqqvTSDUMOQeQg08hiKAAAIIIIAAAgggEIAAn0Ooh0gg1PAjEGrgMRQBBBBAAAEEEEAAAQRyLkAg1GgBgVADj6EIIIAAAggggAACCCCQcwECoUYLCIQaeAxFAAEEEEAAAQQQQACBnAsQCDVaQCDUwGMoAggggAACCCCAAAII5FyAQKjRAgKhBh5DEUAAAQQQQAABBBBAIOcCBEKNFhAINfAYigACCCCAAAIIIIAAAjkXIBBqtEAFQl4IIIAAAggggAACCORaoKWlJddLYP95KkAgzNPGsWxzAsuWLZOGhgYpLi42txNmDlWgtbVVHnroIXn66adD3S87Myuwd+9e2bNnj6xZs8bsjpg9VIGNGzdKb2+vrFq1KtT9sjOzAo888ogsXbpU5s+fb3ZHzI4AAr4FCIS+yRgQdwECYfw6TCCMX09VRQTCePaVQBjPvhII49lXqoqHAIEwHn2kigAFCIQBYkZkKgJhRBoR8DIIhAGDRmQ6AmFEGhHwMgiEAYMyHQIBChAIA8RkqngIEAjj0Ud7FQTC+PWUM4Tx7KmqikAYz94SCOPZV6qKhwCBMB59pIoABQiEAWJGZCoCYUQaEfAyOEMYMGhEpiMQRqQRAS+DQBgwKNMhEKAAgTBATKZCAAEEEEAAAQQQQAABBPJJgECYT91irQgggAACCCCAAAIIIIBAgAIEwgAxmQoBBBBAAAEEEEAAAQQQyCcBAmE+dYu1IoAAAggggAACCCCAAAIBChAIA8RkKgQQQAABBBBAAAEEEEAgnwQIhPnULdbab4Hq6mppbm5OjV+7dq2sWLEi41yZti8vL79i7I4dO6SioqLf62OgvkBjY6PU1NT0TdTS0uJpUtVP+ueJKpSNguzj4cOHRT012PnyemyEUnBCd1JfXy9PPfVUqvp7771X6urq0ko4j4ls2yeUNCdlB9nH1atXy9atWy+rw8t/r3NSODtFIGYCBMKYNZRyrhRQ/8FSr9ra2tT/ZwsA2bbPNp4ehC/Q3t4ulZWV0tTUJKWlpbJly5bUHwAy/ZJpD/0EwvB75rbHoPtoBUICYDT6a61CBTz1c3bz5s2pL6kgMHfu3LR/qFPbrly5MvXeVi/13lWhMNsf9qJVdfxWE3Qfsx0H8ROkIgSiI0AgjE4vWIkhAWeAcwY+526zbU8gNNQojWmdAdAZLNJNbW1HINTAD3Bo0H0kEAbYnACncv7i7wwW2XaV7Wd4tvF8PxiBoPtIIAymL8yCQH8ECIT9UWNM3gi4BYNMZ4+8bO+8ZJQwkfvDwe0XRC/BnUCY+97ZVxB0H90uGeVsYe57rs7wqSs2Fi5cmFqM3+BOcMh9D9UKgu6j85JRLheNRp9ZRTIECITJ6HNiq7R+0bAuJVQQKhCq+xSsy5XsOH63V3M9/PDDwi+ZuT3E1C8SEydO7LssWK1GBcINGzb0/dLptkICYW775ty76T6q+dUr06XE0RKJ52qc7023n7vpKrfuJ+Rnbu6PDZN9tI4J/uCa+z6zgmQIEAiT0efEVunljJ8dx+/2VvDgP1q5PcSCPrOU22qSu3fTffR7Jiq5nTBbeX/PLFlh0P4HPrMrZfZMAqb7yJlgjj8EwhMgEIZnzZ5yJJDtnkDnsnS3z1GZid5t0PeeJRozh8Wb7iOBMIfNte26P/eeEQaj0Tv7Kkz3kUAYvZ6zovgKEAjj21sq+0bAy1ND7fcqZNpe/VKiXta9L2pb9TW3y09pQHgC2Z5Ome7yIy4ZDa9HXvYUdB/dnk6p3rvWE4e9rIltghfI9nRK56W9XJoffA+CmDHIPqr3/qZNm/rem/wBIIgOMQcC3gUIhN6t2DKPBbJ9rqDz5vV02/OQiugeBJk+v84tENp7rKris82i0dsg+2gFCasyehyNHqtVZPr8OmcgdL5XrSq4dDT3/QyyjzywLff9ZAXJFSAQJrf3VI4AAggggAACCCCAAAIJFyAQJvwAoHwEEEAAAQQQQAABBBBIrgCBMLm9p3IEEEAAAQQQQAABBBBIuACBMOEHAOUjgAACCCCAAAIIIIBAcgUIhMntPZUjgAACCCCAAAIIIIBAwgUIhAk/ACgfAQQQQAABBBBAAAEEkitAIExu76kcAQQQQAABBBBAAAEEEi5AIEz4AUD5CCCAAAIIIIAAAgggkFwBAmFye0/lCCCAAAIIIIAAAgggkHABAmHCDwDKRwABBBBAAAEEEEAAgeQKEAiT23sqRwABBBBAAAEEEEAAgYQLEAgTfgBQPgIIIIAAAggggAACCCRXgECY3N5TOQIIIIAAAggggAACCCRcgECY8AOA8hFAAAEEEEAAAQQQQCC5AgTC5PaeyhFAAAEEEEAAAQQQQCDhAgTChB8AlI8AAggggAACCCCAAALJFSAQJrf3VI4AAggggAACCCCAAAIJFyAQJvwAoHwEEEgvMG/evLTfnDVrlmzYsEGbb82aNbJ48WKprKzUnktN0NLSIitXruyba9++fVnntde5adMmKS8vT41pamqS2tray8a/8MILMnr06NTXnnvuOWlra5P77rsv4z5Ujdu3b09tE5Rb1qJC2CDo3oWwZHaBAAIIIIDAFQIEQg4KBBBAII1ApkBoDbEHJD+Q9pBUX18fyUDoVr8KmCoIPv7446ly77///sQFQlO983P8sC0CCCCAAAJBCRAIg5JkHgQQiJ2APRDZg4/968uXL5fHHnvMd+01NTVy4MCB1LhcB0K3xXd0dKTOXFov+5nG9evXy7p16xIbCE31zvdBxAAEEEAAAQQCECAQBoDIFAggEE+BdIHQeSml/Syh22WWSscKlM6gZZezz2MPHem2UV+3n61T/1aXfLpdMmqvRe3HCnuPPvpo39k+a3x7e/sVl4qq76lt1f6sIGtfV6ZQm+6SUfvXnetWczvPRqqv2Y2c45955pm+S1Pdzly62TsDvf2SW/U95WRdNqtCsJrX7eW3d86119XV9bm6XVbrvBTYWoPbGWq3Y7C/f7iI5zubqhBAAAEE7AIEQo4HBBBAII1AukDoDBZWGEoXBq3pVZi4++67Lzvz5hb20oVBZwhwhkG3Mqwze86zmuqePit4OO8hzEUg9HMQWjXZQ5XbeHsozNYbK1g5A6F172PQvfOz9mx9todx+9nbTMeDH2+2RQABBBCItwCBMN79pToEENAQ8BoI1ZmzO++8U9wuJbQHDPuZn3SXHdqDi317t/vW3OZwBoJ0gdB+mavbQ2UyPZwmqEtG7TVZZ7DczniWlJRcFqKtB9+4nXlMt263Gu11WPt3jrd6az+MguidW+3O0Kp6l+6PD/avW8eJM8xaPfZ7z6fGW4ahCCCAAE3vl2MAAAUDSURBVAJ5KEAgzMOmsWQEEAhHwG8gdK7K7SyQFdC83ofmdqmgCikLFiy4LCS5neFS63ELhM7LO6MQCK3glS4Qu3nZfe3Bzb6tCo/2M572kO12n6TT2+2STN3eqT8euK3dLcym87Afa6oO9eTXbGcH1Zg4PeU1nJ8C7AUBBBCIvwCBMP49pkIEEOingNdAaAWsdPd52XfvJRBmu5zQLRBa86Z7GEy6j5ZQa4tDILSHXGdgUzVa9wHa76VzWqnw19nZmfVjOzIFQi+9628gzHYfIIGwn290hiGAAAIJFyAQJvwAoHwEEEgvkC4QOoOfdQmjfXu3y/jsZ+zShQrnJZNW0HGeUdI5Q2j/rMG4BMJ0ZwiVnz0Q+j1D6PY5jrq9628gzHZ2z++lvLz3EUAAAQQQUAIEQo4DBBBAII1AukBoDwTZgl+6e/rShQq3SwmdZ7Lc7lm0vublHsI4BsJ0fbAu+ezvPYR+AqGf3nm9ZNTLPYTq8M10dtO+Ly+fG8kPBAQQQACBZAkQCJPVb6pFAAEfAn4/mN7L9lbAcLu8z+1jFtyW63a/Xbqy3O4h1A2Ebk/sdM5pX4+Xj53QvYfQrX7dp4zaz+ja5w+id14Dodqvn6eMZrpkNdsZRh9vDTZFAAEEEIiRAIEwRs2kFAQQCFYgU8Bz++Xa7XPuVCBzPuSkvLw8tVDn/NbZLGfgUGGprKzM9T44Z1hQ+7PPayIQqrU7g4fu5xDqBkI1fv/+/YF+DmG6QBhE7/wEQrU/P59D6BYgOTMY7M8GZkMAAQTiJEAgjFM3qQUBBBBIkEC6p4wmiIBSEUAAAQQQ0BYgEGoTMgECCCCAQC4ECIS5UGefCCCAAAJxEyAQxq2j1IMAAggkRIBAmJBGUyYCCCCAgFEBAqFRXiZHAAEEEEAAAQQQQAABBKIrQCCMbm9YGQIIIIAAAggggAACCCBgVIBAaJSXyRFAAAEEEEAAAQQQQACB6AoQCKPbG1aGAAIIIIAAAggggAACCBgVIBAa5WVyBBBAAAEEEEAAAQQQQCC6AgTC6PaGlSGAAAIIIIAAAggggAACRgUIhEZ5mRwBBBBAAAEEEEAAAQQQiK4AgTC6vWFlCCCAAAIIIIAAAggggIBRAQKhUV4mRwABBBBAAAEEEEAAAQSiK0AgjG5vWBkCCCCAAAIIIIAAAgggYFSAQGiUl8kRQAABBBBAAAEEEEAAgegKEAij2xtWhgACCCCAAAIIIIAAAggYFSAQGuVlcgQQQAABBBBAAAEEEEAgugIEwuj2hpUhgAACCCCAAAIIIIAAAkYFCIRGeZkcAQQQQAABBBBAAAEEEIiuAIEwur1hZQgggAACCCCAAAIIIICAUQECoVFeJkcAAQQQQAABBBBAAAEEoitAIIxub1gZAggggAACCCCAAAIIIGBUgEBolJfJEUAAAQQQQAABBBBAAIHoChAIo9sbVoYAAggggAACCCCAAAIIGBUgEBrlZXIEEEAAAQQQQAABBBBAILoCBMLo9oaVIYAAAggggAACCCCAAAJGBQiERnmZHAEEEEAAAQQQQAABBBCIrgCBMLq9YWUIIIAAAggggAACCCCAgFEBAqFRXiZHAAEEEEAAAQQQQAABBKIrQCCMbm9YGQIIIIAAAggggAACCCBgVIBAaJSXyRFAAAEEEEAAAQQQQACB6AoQCKPbG1aGAAIIIIAAAggggAACCBgV+D/lW7lP894eAAAAAABJRU5ErkJggg=="
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "SD.plot.scatter_feature_importance() # works if deployed_model is filled"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "abe585bd",
   "metadata": {},
   "source": [
    "the first 3 variables that explain the data drift by the auc of datadrift classifier are not very important for the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "3ef3b98f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "SD.plot.generate_fig_univariate(df_all=SD.df_predict,col='Score',hue=\"dataset\") # works if deployed_model is filled"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0805f1bb",
   "metadata": {},
   "source": [
    "We can see that despite the data drift, the impact on predictions is quite small"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "908cb91d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "SD.plot.generate_indicator(\n",
    "                fig_value=SD.js_divergence,\n",
    "                height=280,\n",
    "                width=500,\n",
    "                title=\"Jensen Shannon Datadrift\",\n",
    "                min_gauge=0,\n",
    "                max_gauge=0.2,\n",
    "            ) # works if deployed_model is filled"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34db9bb1",
   "metadata": {},
   "source": [
    "### Compile Drift et generate report for Year 2020"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "142dec09",
   "metadata": {},
   "outputs": [],
   "source": [
    "SD = SmartDrift(df_current=X_df_2020,\n",
    "                df_baseline=X_df_learning,\n",
    "                deployed_model=model, # Optional: put in perspective result with importance on deployed model\n",
    "                encoding=encoder # Optional: if deployed_model and encoder to use this model\n",
    "               )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "0a45a01e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The computed AUC on the X_test used to build datadrift_classifier is equal to: 0.7902450838961592\n"
     ]
    }
   ],
   "source": [
    "SD.compile(full_validation=True, # Optional: to save time, leave the default False value. If True, analyze consistency on modalities between columns.\n",
    "           date_compile_auc = '01/01/2020', # Optional: useful when computing the drift for a time that is not now\n",
    "           datadrift_file = \"car_accident_auc.csv\" # Optional: name of the csv file that contains the performance history of data drift\n",
    "          )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "b67329ec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "SD.plot.generate_historical_datadrift_metric() # works if date_compile_auc and/or datadrift_file are filled"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "a011c100",
   "metadata": {},
   "source": [
    "### Compile Drift et generate report for Year 2021"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "43e75cb6",
   "metadata": {},
   "outputs": [],
   "source": [
    "SD = SmartDrift(df_current=X_df_2021, df_baseline=X_df_learning, deployed_model=model, encoding=encoder)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "46ad16b6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The computed AUC on the X_test used to build datadrift_classifier is equal to: 0.7500011519622525\n"
     ]
    }
   ],
   "source": [
    "SD.compile(full_validation=True,\n",
    "           date_compile_auc = '01/01/2021', #optionnal, by default date of compile\n",
    "           datadrift_file = \"car_accident_auc.csv\"\n",
    "          )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "467b9f08",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "SD.plot.generate_historical_datadrift_metric()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "9f91ee44",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "Report saved to ./report_car_accident_datadrift_2021.html. To upload and share your report, create a free Datapane account by running `!datapane signup`."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "SD.generate_report(    \n",
    "    output_file='report_car_accident_datadrift_2021.html',    \n",
    "    title_story=\"Data drift\",\n",
    "    title_description=\"\"\"Car accident Data drift 2021\"\"\", # Optional: add a subtitle to describe report\n",
    "    project_info_file=\"../../eurybia/data/project_info_car_accident.yml\" # Optional: add information on report\n",
    "    )"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "eurybia_3_9",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {
    "height": "calc(100% - 180px)",
    "left": "10px",
    "top": "150px",
    "width": "336px"
   },
   "toc_section_display": true,
   "toc_window_display": true
  },
  "vscode": {
   "interpreter": {
    "hash": "36c4204cc0170e083c18487e195263df35fcafba9d65a5415ab6b0958d51e154"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}