tutorial/data_validation/tutorial01-data-validation.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "86df95a5",
   "metadata": {},
   "source": [
    "# Validate Data for model deployment\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1002fe1f",
   "metadata": {},
   "source": [
    "<b>With this tutorial you:</b><br />\n",
    "Understand how use Eurybia to do data validation in a simple use case<br />\n",
    "\n",
    "Contents:\n",
    "- Build a model to deploy\n",
    "- Do data validation between learning dataset and production dataset\n",
    "- Generate Report \n",
    "- Analysis of results\n",
    "\n",
    "Data from Kaggle [Titanic](https://www.kaggle.com/c/titanic)<br />"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "285f92bc",
   "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": "33cd7e4f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from category_encoders import OrdinalEncoder\n",
    "import catboost\n",
    "from eurybia.core.smartdrift import SmartDrift\n",
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6fcf7d9c",
   "metadata": {},
   "source": [
    "## Building Supervized Model\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a41f58d6",
   "metadata": {},
   "outputs": [],
   "source": [
    "from eurybia.data.data_loader import data_loading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ad036405",
   "metadata": {},
   "outputs": [],
   "source": [
    "titan_df = data_loading('titanic')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0e4deeff",
   "metadata": {},
   "outputs": [],
   "source": [
    "features = ['Pclass', 'Age', 'Embarked', 'Sex', 'SibSp', 'Parch', 'Fare']\n",
    "features_to_encode = ['Pclass', 'Embarked', 'Sex']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0a5ece1d",
   "metadata": {},
   "outputs": [],
   "source": [
    "encoder = OrdinalEncoder(cols=features_to_encode)\n",
    "encoder.fit(titan_df[features]) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2039bef4",
   "metadata": {},
   "outputs": [],
   "source": [
    "titan_df_encoded = encoder.transform(titan_df[features])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e8c52451",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    titan_df_encoded,\n",
    "    titan_df['Survived'].to_frame(),\n",
    "    test_size=0.2,\n",
    "    random_state=11\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "2fc50a27",
   "metadata": {},
   "outputs": [],
   "source": [
    "i=0\n",
    "indice_cat  = []\n",
    "for feature in titan_df_encoded:\n",
    "    if feature in features_to_encode:\n",
    "        indice_cat.append(i)\n",
    "    i=i+1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e7367561",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = catboost.CatBoostClassifier(loss_function= \"Logloss\", eval_metric=\"Logloss\",\n",
    "        learning_rate=0.143852,\n",
    "        iterations=500,\n",
    "        l2_leaf_reg=15,\n",
    "        max_depth = 4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "e0be1020",
   "metadata": {},
   "outputs": [],
   "source": [
    "train_pool_cat = catboost.Pool(data=X_train, label= y_train, cat_features = indice_cat)\n",
    "test_pool_cat = catboost.Pool(data=X_test, label=y_test, cat_features = indice_cat) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "596b695d",
   "metadata": {},
   "outputs": [],
   "source": [
    "model.fit(train_pool_cat, eval_set=test_pool_cat, silent=True)\n",
    "y_pred = model.predict(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df01806b",
   "metadata": {},
   "source": [
    "## Creating a fake dataset as a production dataset\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "a1118f41",
   "metadata": {},
   "outputs": [],
   "source": [
    "import random"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "75875239",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_production = titan_df.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "97659f0c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_production['Age'] = df_production['Age'].apply(lambda x: random.randrange(10, 76)).astype(float)\n",
    "df_production['Fare'] = df_production['Fare'].apply(lambda x: random.randrange(1, 100)).astype(float)\n",
    "list_sex= [\"male\", \"female\"]\n",
    "df_production['Sex'] = df_production['Sex'].apply(lambda x: random.choice(list_sex))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "1764606d",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_baseline = titan_df[features]\n",
    "df_current = df_production[features]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "c233105b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Age</th>\n",
       "      <th>Embarked</th>\n",
       "      <th>Sex</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Fare</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PassengerId</th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Third class</td>\n",
       "      <td>44.0</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>female</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>84.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>First class</td>\n",
       "      <td>40.0</td>\n",
       "      <td>Cherbourg</td>\n",
       "      <td>female</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Third class</td>\n",
       "      <td>48.0</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>First class</td>\n",
       "      <td>41.0</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>female</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>41.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Third class</td>\n",
       "      <td>61.0</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>61.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Pclass   Age     Embarked     Sex  SibSp  Parch  Fare\n",
       "PassengerId                                                            \n",
       "1            Third class  44.0  Southampton  female      1      0  84.0\n",
       "2            First class  40.0    Cherbourg  female      1      0   6.0\n",
       "3            Third class  48.0  Southampton    male      0      0   6.0\n",
       "4            First class  41.0  Southampton  female      1      0  41.0\n",
       "5            Third class  61.0  Southampton    male      0      0  61.0"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_current.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "cee47aba",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Age</th>\n",
       "      <th>Embarked</th>\n",
       "      <th>Sex</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Fare</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PassengerId</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Third class</td>\n",
       "      <td>22.0</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>male</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>First class</td>\n",
       "      <td>38.0</td>\n",
       "      <td>Cherbourg</td>\n",
       "      <td>female</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>71.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Third class</td>\n",
       "      <td>26.0</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>female</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>First class</td>\n",
       "      <td>35.0</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>female</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>53.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Third class</td>\n",
       "      <td>35.0</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Pclass   Age     Embarked     Sex  SibSp  Parch   Fare\n",
       "PassengerId                                                             \n",
       "1            Third class  22.0  Southampton    male      1      0   7.25\n",
       "2            First class  38.0    Cherbourg  female      1      0  71.28\n",
       "3            Third class  26.0  Southampton  female      0      0   7.92\n",
       "4            First class  35.0  Southampton  female      1      0  53.10\n",
       "5            Third class  35.0  Southampton    male      0      0   8.05"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_baseline.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "38508afd",
   "metadata": {},
   "source": [
    "## Use Eurybia for data validation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "c0e83ee0",
   "metadata": {},
   "outputs": [],
   "source": [
    "from eurybia import SmartDrift"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "808b5a25",
   "metadata": {},
   "outputs": [],
   "source": [
    "SD = SmartDrift(df_current=df_current,\n",
    "                df_baseline=df_baseline,\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": 21,
   "id": "0cc98756",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 6 µs, sys: 2 µs, total: 8 µs\n",
      "Wall time: 15.7 µs\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",
    "            )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "5e290645",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "Report saved to ./report_titanic.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_titanic.html',    \n",
    "    title_story=\"Data validation\",\n",
    "    title_description=\"\"\"Titanic Data validation\"\"\", # Optional: add a subtitle to describe report\n",
    "    project_info_file=\"../../eurybia/data/project_info_titanic.yml\" # Optional: add information on report     \n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20482b6f",
   "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": "579c308d",
   "metadata": {},
   "source": [
    "## Analysis of results of the data validation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8981606c",
   "metadata": {},
   "source": [
    "Data validation 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": "1744d311",
   "metadata": {},
   "source": [
    "### Detection data drift performance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "ab95a343",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Performance of data drift classifier\n",
    "SD.plot.generate_indicator(fig_value=SD.auc, height=300, width=500, title=\"Datadrift classifier AUC\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "32366d7b",
   "metadata": {},
   "source": [
    "such a high auc means that datasets are not similar.The differences should be analysed before deploying model in production"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8deda6d0",
   "metadata": {},
   "source": [
    "### Importance of features in data drift"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b686c77b",
   "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": 24,
   "id": "dff579c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "SD.xpl.plot.features_importance()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f140e52",
   "metadata": {},
   "source": [
    "Features that explain most differences are fare, age and sex. This makes sense because it is features that have been altered\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4376186f",
   "metadata": {},
   "source": [
    "### Feature importance overview"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e237594",
   "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": 25,
   "id": "2bea57fb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "SD.plot.scatter_feature_importance() # works if deployed_model is filled"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7795d380",
   "metadata": {},
   "source": [
    "Features that have the most difference are quite important for the deployed model."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "daf2cf3d",
   "metadata": {},
   "source": [
    "### Univariate analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2340efb1",
   "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": 26,
   "id": "41999b2f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "SD.plot.generate_fig_univariate('Sex')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f7343be",
   "metadata": {},
   "source": [
    "### Distribution of predicted values"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1603ea1f",
   "metadata": {},
   "source": [
    "This graph shows distributions of the production model outputs on both baseline and current datasets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "80822147",
   "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": "1d95ec02",
   "metadata": {},
   "source": [
    "Differences between 2 datasets generate a difference in the distribution of the predictions of the deployed model. These differences can have important impacts on the performance of the model in production"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "233c3845",
   "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": 28,
   "id": "d2c96e92",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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xI2qfrwr6U9a+svrL83JjFJPHHryDpwfdXWSMKiDtoWETq1zQrbXQlYtbubpVuhSCroLBBo16Q3tWli3SB8UZ91+rLVxq2cjy4Bm1hHJNt0e15QVrBd3W+ipqoV/ohEERdKv+/CWTBQER9Gr2OJQm6C9Pm8uiH1fS/95uWnStNakigm5Z//QPv+bjz3/W1sOVtarWRtUaqbeXh7aWawx6ulifqlLQe/Qfo21psgxas5XFzI+/5cOFP2oBaSowzTKZAtOKucptbaM8YqvWgdUBOr9+NqXEwS3q+VDPSWlr6Bc60rS4F6CiFrrattb/qcnay6BlxL1R5FXQowp+tEybd+yj31OTNG+KpaAv/nUNL035hBeffogHepkjwlXZ8tRXkTV0ewm68vh06/Os5t2a/rIcA2vN95ij5RFBd7QZLWM8pQm6cr2qPctOOPHBGyM1t6VlUu5Wte3m1i4dTL+2VWDUvuv2bVqUiEIe98anfPvzam29WK0bq6SiklV0stonrc6nLh5hro6u9fBwN62f2lPQp72/iK6xbU2xApYcjJa1m5srK7+ZocUDlMdCV1H3Kvq+713/Y8xTfU1NHDqaqLlmFe+qdrmrTqg1fRWtrXYPKEEwWroqUPG+xydokfmWh5mU56XhQo9nWS53FQw5ceZC7WAZdXbBVx+MN+2MUPvlb3ngOW1HxZfvjTNF56szztX2wP/2Hykh6CvWbWXomJlaMJoKSrNM5alP7Q5QL2PFo9yVta/+ti4W5W4vQVeerw63P6F52ZS3TVL1IyCCXs3m/EL70JXITJg2VzvgRAWcqfVpdfSmCjDasGU39erU5Ie5E8st6B17DNHEvF1Uc+rVCcHF2VkLONu4dY+253nRB+NN2+XUuvcjI6ZqgXrqyMvO10dre9zPpZxny6792l5ty2Mv7SnoytJSkd7KM6C+GEOCAkjPzNJEQYmKSsWtOltfbtQBJOqyjpPJZ7VteUqIVJCXOkRHWezqZeZSCLpanx4w/HW27z5I00ZqH3prsrJyUEGOKriwuPhVhqAXP/o1PSNb20ev5lyl6JZNtZ0MxS/BUeKsRFoFyal+qxeEP1Zv0tbS1X7/8xlZRSx0dXCS8gSpuAXlYTAGZ6qtiipGwtb6St2HnpbOz8v+LnMfur0EXfEx/n2rl291GJSzszM33XBNiS1x1exrr9oMVwS92ky1fqDGiHYlzkpILZP6glaRwv9s3aMd9uLl6aGdtqWi0VVkujrkxZhsFbGvvv+Tv/7Zxb6Dx7SobnVYTb3aIdxyYwf69LpJO2HOMilxUfuxf12xUfsyz83Lp0aQPw3D6mii1+PmGNNBMfYUdHWozKq/t2kHmChLLelMirZ/u3aNIKJaNtG2rSlRsUy2slBllXt02vtfoVzCyrIKr1+H+3rcSOz10XTtPeKSCLrqlwr+m/vVb/yyfD1HTyRpJ9ZFNmmgzZHaFlj8eTGeRmdN4N3F/tQudjlL3VohtIwM184tV5ezGA8UsqxPWeOz5y7RRFzNWa2QQG7ufC1P9r8T5fpXLyTFj5Rds2Ens+ctYf+hY9rBMCoZT4orT33qRfSdT7/TXoDUunr9ujW5/86byjwpzp6CrjwCr7/zOVt37kf1RyU5Ka76fMmLoFefudZGajzaVG3hUVt5JAkBISAEhIBjEBBBd4x5tGoUah38yRema1tk1FYZSUJACAgBIeA4BETQHWcuLzgSFei0acdeNm3fi9rGM35Ef3r3uPAe72qARIYoBISAEHA4AiLoDjelJQekAmXUPvMmDetpt2YVP3ylGiCQIQoBISAEHJ6ACLrDT7EMUAgIASEgBKoDARH06jDLMkYhIASEgBBweAIi6A4/xTJAISAEhIAQqA4ERNCrwyzLGIWAEBACQsDhCYigO/wUywCFgBAQAkKgOhAQQa8OsyxjFAJCQAgIAYcnIILu8FMsAxQCQkAICIHqQEAEvTrMsoxRCAgBISAEHJ6ACLrDT7EMsDoQWL5mC1Nnf6FdTNKudaR2v7y6qa60tOCbpSz57S+0a3Nvi2X8yAHVAZGMUQg4PAERdIefYhmgoxNQN7f16D+GyWMe4/p2LZk4Y4F2o90nbz1X6tCXrtqEm5sLv/25EW8vDxF0R39AZHzVhoAIerWZahmooxL4cOGP/L35X+ZMf14bYmLSWe0KVuNVoBca92szFlBQUCCC7qgPhoyr2hEQQa92Uy4DdjQCz736PiHBAYwe0sc0tI49hjD1pcF0at/qgsMVQXe0J0HGU90JiKBX9ydAxn/FExg6ZiYtmjVgyMBeprF06/MsIx7vTbfO14qgX/EzLAMQAtYREEG3jpPkEgKXLQGx0C/bqZGOCYEqJSCCXqW4pTEhYH8Cag19w5b/TEFwJ5PPctO9soZuf9JSoxC4vAmIoF/e8yO9EwJlEjh2Iok7B77Em+OfoEObFkycuZCTSWdNAv/NT6uoXTOYGzro19PzCwooKCjk9Xc+14LiXnz6IVxcnHF1cSmzLckgBITA5UtABP3ynRvpmRCwmsCyNZuZ+u4XJJ9NLbEP/bFn36RlZCOeHnS3Vt/Mj79FWfWW6ZE+t2lr7pKEgBC4cgmIoF+5cyc9FwJCQAgIASFgIiCCLg+DEBACQkAICAEHICCC7gCTKEMQAkJACAgBISCCLs+AEBACQkAICAEHICCC7gCTKEMQAhcjsGPHDnQ6HVFRUQJKCAgBByYggu7AkytDEwKKwIIFCzRB79evnwARAkLAgQmIoDvw5MrQhIAIujwDQqD6EBBBrz5zLSOtpgTEQq+mEy/DrnYERNCr3ZTLgKsbARH06jbjMt7qSkAEvbrOvIy72hCQoLhqM9Uy0GpOQAS9mj8AMvwrjEBhCuTugoIzkLsNnPwhczUUpIBLPcg7AZkrwS0ScvaaB5dvMU7XUMhNAN/O5jIugeAbCwVp4B0NriHgfTWo30sSAkLgiiAggn5FTJN0stoR0KVA3k7I+hPy4wEXSPtEj8EjDrJW6X92j4Ks7SV/Vr8ptKBmKeiWv/eIgkxDecuffeMgzdBGzUegsAA8wyGgC/i0AlcR+mr3TMqAL3sCIuiX/RRJB6sFgfxtkLsKcrZD9gooiAf3WMhebRBrCxF3i9LnKy7oyirPtrDKrRF0F4O1rr0oWIi7VxRkGNrwi4MUg7j7x0LKavAIh8AbwTsKguLAN7paTJMMUghczgRE0C/n2ZG+OS6BwnjI/h7yVkL+McjbrB+rSyzkGEXcQtCViGcbBNZS0F3CIPe4mVOBBTJrBN0yv6W4Wwq6+jnd0LZR0FUzfrFwztBX37bgUR+COkOtnnprXpIQEAJVSkAEvUpxS2PVmkDBNsieB7lLQBcA+UaBjoMcgwXsFgNZa/WYLIXbOQzyLITbUqwtRbkign6hsmrNPSdB3ydlkRvF3bs9pG3U/z4wDs4axuATBXmpUOtOCO0PfmK9V+vnXgZfZQRE0KsMtTRULQkoEc+dB3lLgFqQZxBAZYnnGqxbFyWABnFXwm1pcV9IuKtS0C8k9MqiL03oA2LhrGFs/u0hOwlq3wlh/cFfxL1a/h3IoKuEgAh6lWCWRqoVAV28XsRz54JTKOQbLG6XGMg1/OwcCXkXWO8u8Addmh6ZcwTk79P/7Gqxdu4aReqZ7ew7DIcS6nI4PpGUNMjOcScrO5esbPUz2r9ZOeAM+PuCv4/+v0A/8PX1x98jTf+7oEbU9DxMRAMIqGmxfq4s8vOGlw3PCMg09MU9FDINVrvqm+ULhsqXYcjnHwPnDGMOVN6HBKg/AOr3By9xy1ervwsZbKUTEEGvdMTSQLUhULAE8uZBYbJZxJ3bQ77BKndSbvZUMw5dKBQaRLGIld4ecg1l3GJISljLmn9g23/12HfgBAePwsGjLqSkWprO9qMc5O9Ck3oFNAmDpuH1aFzjBE1CoUlEO8I8N+kb8mkPqYY+Khe7UfSV0CvRNia1rS7f8HKirPUUo4s+BtxrQoMBUKen/TovNQmBakxABL0aT74M3R4EUqBgHuQvg/yfDFZ1NORtM1de6A8YLe72pbvd3fTr6JmZsHFnazZu3MGGrbBhmzsJibn26Khd6gj0hU6toXOHxsQ1O8Q1zcA52GL9vLi7/ZxxicEf8gwMVE+8IiDdYMXX6g717oF6PcFNtsPZZaKkkmpJQAS9Wk67DLriBJSQz4G8V4AUcAqDfMugtVDQGSxV55jS3e4uekt86Ur4bWUNVqw5zbZdFe9ZVdbg4wmxbfzo0uo8N1wNHdpbWOGW7vagWDhjWFf3joDzBjFXnTVa9UrMm4+D8IEi7FU5idKWwxAQQXeYqZSBVA2BFCicCQUzQOcLhRYirouCQmNwWyzkGQTMKRIKDOvlTgEcPpjKL8vg1+Ww4i80q9xRUrAf9OoIvWPhpjZ+uOjO64emRNxokStxP21g4xcFKQZmRnHPz4CI4dDsaRF2R3kwZBxVQkAEvUowSyNXPoEU0M0E3SIo2G0eji4GCg1BX04W6+UEQIF+vTwnB1asCeG3P87w6zLYd+DKp2HNCEL84S4l7l1CuDHiDC4uhlLF19WNbvmgGDhtYKmy+rSABvdBpAi7NbwljxAQQZdnQAiUSWAyFE4BDAFtliKuCytqpReaXe1HjrVl+tubmfMZpFksH5fZnANmqOEPdytxv6UlnRv8i7MKu/coFilvGVAXHAPJxv34yhX/HLR8wQHJyJCEgP0IiKDbj6XU5HAE1N7xZ4B40MWBznBwCmFQcAFXO7H88cdq3n4PfvkdCi23czkcn/INqEFNGNEDHr33Orwz1usrCWwPZwwBdOr/LcW9ZhycWgU+4dB2OoTdWb6GpZQQcHACIugOPsEyPNsJ6Ignt2Agbs6FODsZ1nqVC71QZ45Wt7TSiSYrfRvzFsKs95zZ/Z+ouDXUg/2cGHKLjqdvh5B6FmvpNQwCripxVXvynfQnz6kUEgs6Z+g0B3xlH7s1nCVP9SEggl595lpGagWBvMLp5BeOMOQMwMvVUsQtrXS1Rq4jKyuNWe/CG2+5cPp05ewLt6LbV3QWLw8nBnbW8VwPaFjPHwosBNxonRvFPd8JclPBPRBaj4OrlQdFkhAQAoqACLo8B3YlkJGZzbg3PmXlum34+3kz+KEe3NezywXbWL5mC1Nnf0HSmRTatY5k4vODqFVDvxf5ieens3q9OQLa18eLDT+/Z9f+Gisr0G0jK28ghbrDuLmYRdzNOQZXZ4tALbVGToIW6DZ7dhNen3qQpKRK6VK1q9TFGR69vS6vdE+kptq671lsjV2dNJdkmAtluRc6gW8jiJsDIZVzpOy7cxbz2eJl5OcX0P1/HRnzVF9cTdF9RafopSmfsGn7Xo6dSOKNsU9w200dTBl27T3MfY+/XKTA6CF96Hdvt2o3zzLgyiMggl55bKtlzUrM1RfatPFDOHw0kcGjp/H+lJG0bR1RgsfxxGR69B/D5DGPcX27lkycsYDTZ1P55K3nTILepVMbetwco/2/k1padXezO9f0vMkUFL5ucqe7OXfAyWmDqR0vdeQq+heL3Jzr+fDDv5n8Opw4YfeuSIXqEjcvGH0HjOx3PZ6pf+uZBERBssX2tuD2kGRYc1fiHvUCtHnervx++uNv3njvSz6e9iy+Pt48/tw0buvSgcH9epTazmffLaNZozAmTJvD0IF3lRD04WNn8fNCFVypT+rFwEW9xUgSAnYiIIJuJ5BSDeTlF3B99yc0AW8XFakhGTv1U+3fV597uASiDxf+yN+b/2XOdP0XcWLSWbr2HsHyr9+iTs1gzUK/Oa4dvW69oVLw5hduIyV7IOpfL7dYwLheDh6uUeh0egFxdY7GzXkbS5bAU0/BsWOV0h27VRoUAN6e4O3thbd7Ft5eoCuEc2lw7rwbSWfy7NZWZVZULwgm9Yb+amrU+fBphsNoAqPgtIW414yFhNVQIxpuXQx+9llbHzTqDa5pFcGT/fVH0/64dB3vzl3Cb59Pvf9K7LgAACAASURBVOiwewx4UfNMFbfQh497h2VfTatMZFJ3NScggl7NHwB7Dv/I8VPc9uBozS2u3OMqKavlp2V/88XssSWaeu7V9wkJDkC5Ho2pY48hTH1pMJ3at9IEfd9BvXqG16/DYw/dQYc2LezS5fTcueQUfElewe+m+nzcoyg0iLizUxiuzmqvWRpHj8Azw4L49ddzdmm7IpUosW4X5UuDOuk0qF+bBrVOER4G9RtcS5Na/+irNi7le8VBhiEyP9/QqnccpK/SLm1JSYWU83AuL4rEo9uJT4TDJwOJP55C/ClPDidkk5ldkd7ap2xUYx9m3JtB5+aGIDkXf8gw7DIIaQ+JFtHxod2g2f1w1YAKN9757uGMG9GfLjFttLr2Hz7OnQNfYsvSj/C4iKfoQoL+4NCJ1AoJxNPTgxvat2LIwDvx9vKscD+lAiFgJCCCLs+C3Qj8t/8I9zw6nl0r5uDkpBzk8MPStXz8+S/8MHdiiXaGjplJi2YNGDKwl+mzbn2eZcTjvenW+Vpt/bxGcID2Bbh8zWbNOlr0wQQiGoeVu8+FuhTOZD2DEnSV/NyjyDec7uZEAJ5u5vVzd5c4pkxexcvjyt1chQp6esI1rby5vk0m17evR5vIEzRuoO5Jj4VsgzfBGFDvEQeZBvG2QtCLCL9PHKQZyhrr84uFlNUkp0D8mQb8s/0oK3cGsHJTqva7S5H6dIDZz3Qk8Pw6ffPK1W4MklP/HxwFpwyWuxL02OngUf6z4dvfNph3Jg6nfRv1JmH2IP31/SyCAvwuiKA0QU8+k8LOPYdp0rAep5LPMeXdz2ncsK621i5JCNiLgAi6vUhKPdjbQi+OdPDot2jdojFPDijfPuS8wngSzz+Es3MSeQV6962rcxjuzmnoDJeneLh2wNlpA2vXwDNDYZ/FDadVMcWdY+DWrjXpcn0y7dTSvbo3PaeYeLvHQVYxAbaHoCvL13iBim8spBZrV4n8udX8G49e3LeksmqHC8kpVRfdXycAPnoIuis2ah39pPFWOkN0fI5he1tABHjWgtsWgH/5XPD2tNCLPztK3B8c8hqbfv8QN1fjEXpV8YRJG45MQATdkWe3isem1tCvu/0JPnpzlLb2qJIKktPpLryGvmHLf6YguJPJZ7npXvMaevHuD3vpbc06H/bwXTaPLDNvJQnne6EsdA8Xtb6faBJxb9cO6NAHwZ09A6+9VIMvFp62uY3yFAit58qtN+VzW1f4X5cYfN2Nx8iGQkECqAtccozBX1GQux3coiDbYImqgD31O/coyDKeIx8KeQlwEZc7bqGQbbg8xiMKMreDl8U96Orn9O1geTWqd3tI26g/4c14RWpAHOvXrmLRavhmrSvHkoy+/fLQsL5Mv841eOeO0/gZPdbK9W4p7p514dxevYXeczHU72x95Yacag1d7bwwBsGpILl35iwu1xp68cb3HDhK78cnsOnXDyol0NPmwUoBhyAggu4Q03j5DEIFwSUmnWHa+CeJP3aSR0e9wXuvj9Ci3BNPnWHht38wcvB9ODs7adHwak3yzfFPaGvjE2cu5GTSWU3gM7Ny+HPtFtpHt8DdzZVlazbz2oz5LJj1Iq1aNLZpwGez5nIu633ydebIdV+3TuQW/mWqx889ljWrV/PoQ3CmkrXc2xvuubM2j/Q9RWxHwHgvunMk5BlcAq4xkLsWnMMg17Be7G5wtavf5Rl/1x6yNxYVdKPgX0zQPS3E2yjo6o7z88aXh1DISQB/vetdSzplBaeBukUtxfDioYLVMvaZjnH9+z/4elMoXy9L4Hglc6wXAPP6Qde4WDhuDmikdgwkWGw1rNEe2jwBrW1bV1dBcG99uIhP3xqtxYQ89uybdOvc3iTw3/y0ito1g7mhQysNT15ePoU6Hfc+Op5BfW/X8rq5umrP+t+b/iUwwJewujVRL66vTp+v1Tl7suyjt+mPWTJflIAIujwgdiWg9qErUV/19zbtC0tFCBv3oW/ffZAHnnyV7cs/Me3lVUI99d0vSD6bWmQfemZWNo8/9xb7Dh3T9gCroLgn+vek6w1tberv0dQBnM2ap5UJ9Iwlp8D8xe/nEUtO/mrNgzB7mgfTJ+dU6lGt7dvBIw8F0ufuFPz8LW5gc7a4mU3dna5LA6Oga0JqsNaNgq5+Z/RyK1e7cr+7RkKO4WXAJOgxkGEQNqPh7NUeMjaCpaC7hEJuAvharKUb6/eLgdS1+qNYMw0WvVHQ1Rp2juGQest70L0j0J3fx687Qpj5zRn+2I7GuLLSoOtgRi/w8QDqxsIxC3GvEwtHDf/fagB0n2NTN975dDGfLyl9H7oS+JaRjXh60N1anSrobeuu/UXqVzs+lOB//dNKPlr4E0mnzxHg78sNHVozcnDvi67F29RRySwE5GAZeQauZALz588nJiaGJk2alBhGgS6FIynPUFC4n4w8s7UW6BVDTr75//PSmzB4wEHWrqwcEjVqwIN9avJov2SuUgH6TnGQb1j/dooAtZZvaZm7GCxzdb+68bx4Z/296ZqrPcfgVvfoBoXZ4NkVdPngFg6uhrVi52DwaH3xAWXtgPyz+jzZ8ZATryIKIHUZOHnCWUP0v7fB9a6E/ZzxshSj9W7xO6OlXuSa1Dg4vYr9J2DGbyHMW3qGjEqKmm9aA34dFU5TVzUOQ6oTA0ctLPV6MRDUDHqULuoHDx5k7dq19OvXr3IeBqlVCFQyAbHQKxmwVF95BNQX8Lhx43jllVeKiLoS8/+SbyQzbxsuTgF4udUm1xAEp3oT4Bmh/f+OLTCsvxOnEu1vPoaGwuiRjXjs4cN4KMtRFwGF+0AJdb7BXa4s83yjOzsUCtWauUHQVUedDJa5Rx/QuYN7NLhFg4ft68HlmoXUlZC+Tf9fQS6c/KLo+rkSeeV6t7w1Td11fsYwJuM6vY9+D3laJnzydzizvonncCWcrufvCd8qF7wK31BBccmGfetq8IERcP4UqKC52tHQbwV4miPgL/QslYubFBICl4iACPolAi/N2odA8S/i/MIU9p3pT1beSgqU61oFihcTdfX/i+ZkM2VcDnl2PmOlfn0nnn/Wg0cfycbN1eJqVacYMHkG2kOBWqu2+NzodndSl8AEgsed4HEzuHUEp/JvvbIPZUMt+SmQug5OL4XkJZBzDvLTwNLdrlzzKtjOvz0Y7zlXR7aeMVjK7qEUZiTw8ZpAxi5MJSnVvi9T6uC1N+8KYPj16iJ6Q8S7pZirobj7Q1hnuHueJuoi5nZ9SqSyS0hABP0Swpem7UPA+IX87ntTOZjRnfTcbfi4ReJEoknU3V3CcHZKI78gjVdHwZIv7NO2sZaGDd15fnQujzwMbq6xUGi0vGOg0CBmBeqA8jRwag/5huAz5yjIV5Hrd4BLF3C/E5zLt83KviOyoraseEhaAsl/QtKPEGAh4kZBV1vhcg3r7EExcNrAIjiG80fXMmmJcsc7kZ1rX2HvGw1z7wZXL39QfThvDCL0BxUBf3ov1Ikm/b6fePzp50p4eawYvWQRApcdARH0y25KpEPlIZCSlsDx7FGcyfrSVLy4qLsUNmP4wMP8tdx+W6s8PZ0YM0bH6NHgbnHmOwX6S1zQWVjhxEGBcf+4+twVPF4C165XjohfaHKUuCcvg/2vQWG+OYAuOA6SDWM23nGuLl3JMATYBURxZP92nv8SvjQc216e+S+tTMdwF354ohEhOQf0HyvL3CjmxgIt7yP9pmn41lTzIUkIXNkERNCv7PmT3gPKzb7pxI2cz91GsFcn0nPN29ECPTuQk7+BjHQYNRC22FE0utwE786uQ/OIk4Z5iIbCbfqfLe9L10WBOo3OuH7u2h/cR4BTGYFrV+rspu2AA2/BsXn66Hi1Zz2wPZwxeCWCYyDZYKmrS1fObddOfdtwwINhHyfzz2H7DbxJMKx6GEKVc6RWezhueUxsDBxZC3Wj4dEV4HWZLG3Yb/hSUzUjIIJezSbc0YabV5jCrqR+nM780TS04qLulNGBgXdt4JCdTn2rWw+mvtmCu+/9T2vTwyUOZyeDFaqEXGd0sRusdKKh4DC4Dtf/RzURjrwUODAD9s8Ar3BI2a6/EtVondewuA61RhycWKVtG3xrbWPGLjhEtp3iGxoGwqrn29IwfbP58Q81iLnxN83vgN7zRdQd7Quimo1HBL2aTbgjDVeJ+dqjKpr9MAGetcnMM0c1G0X95HEYfj+ofyua1DXYjw4O5KWXU/D1VUIegQ7VZgBerr56F7tloJtmpR8HlwngbNuhJhXt62VXPn4u/DsBPMPM1rnxvnMvZcWnQ24q+EXAuX3sPQl953iw+VCOXYYS6gdr+4MSd4qLeUgEpJyC4EYwYqtd2pNKhMClICCCfimoS5t2IbA1cQDH0vSHxrg6B5QQ9dyz19L/9n84Y4ctUrVqw8cL4fqYSNyc9aa+q3Mkzk76n9Ud6q7OhpPodLGgOwJOE8Cpmgt58Zk+PBd2TgCfcDhl8GqoALrTBle42uKWqn8xK/RsxpSv9zPhF8i1Q9iDEvXVz7alcaaFpW4U82xDRHy7AXC/bYfP2OVhlkqEgB0IiKDbAaJUUfUENiQMIDvvIBl5O8gv1EdRK1EP8YokLXejJuLP9IaTdri7vEMMzP3sOgJD1mvteLvFoUMvRh6useh0+oh2Ly0oTh1sMhpQt2hVE9e6rdOvXPH73oPdU8A7HJINh+XUioUTht0BteLguJ7xv7lt6fvmZrYb4uhsbc4yf20fWPUARIYA9drDqb1gFHMPf6jVGmo0Ve6BijQjZYXAJSEggn5JsEujFSFwOGUuGxMGalX4e0Si0yWaRF39zj2nPYN6biTB4tCw8rTn7AxDR7nz1Ohc3FyVW702BepwGMDHPYJC3T7UlavuLr7oSMDV+WncnCeIkFsLOzcFtk+Af2fq19ZzLdzuZwzLJ/4RkH6K/MxUHvvGjTl/V3xhvYYXrBzRhpbZFu51JeZedSHJEGihBL2DeFesnUrJd3kQEEG/POZBemElgVMZK9lxajRns8zRykrUXZzSyc5P4HwKvNAXjh20ssILZAuuAW9+ADfdFE2BTh+5rm5pc3HS39Lm6mJ2vbu7dMfDZSTOTlV0glvFhnb5lT65Era9DseNx82qNe194OYPHoZb01Svg6J4d8l2hn+vdjZUbBg1vWDzg1BfRb/7h4Kzr1nMVdX120PPKRAhc1ox0lK6KgmIoFclbWmrQgTSc+P5aV8bVDBcPb84Tmca1mC1NewA3AtqMuyeA8RXMJq9fjgs+jmaoNp6Ifd1jyPXsH/cxz2WQsOhMcr17u7SGU9XZZVLqjCBLRPg+EqTq53aFreo1Y2DY/r5XnW2Ob2m7+FcVsVavCoENg1rildmMmQZ1tBVlY1iYf9qfcT7mK0QcoUc9FMxHFLaAQiIoDvAJFaHIeQWpLAivjtJxtvDgDq+nTibpd9znpMFEwe5sG+78Zqw8lG5KgpmfwHBwQH4epjPgPd1b0+udlwr+Hm0R1d4iiCvJbg6R5evISlVOoHT2+CXO8GrNpwweGHU/nHjz+qM9rRTxJ9M5da5sCe5YiB7NHVlyS35ODkZ6gmPgQMWF7o0joEnfwJviYeoGGkpXRUERNCrgrK0UWECK+MHkJy5HncXHWk55u1pAR6R5Bcm8trgNLZa3JpZngY73gjvze9Ioes6rbg6LtbNJY1CXRrOTgF4uvqSX5iAv8dggr0m4yRBb+XBXHaZnBRY+wLsfB981Nnw6fpz2dV1req/NP0exLTADnSduIF/Khgs93xbmNzZH/zq6oPkjKmGulDHCRpfDw9LkFzZEyc5LjUBEfRLPQPSfpkE9p6Zy6p4fRCcu0sAtX2v5nSm2YpaOj+AhdMsXKZl1lgyw519/Bk9JQ0VCKfuTc/MM0auR4Jha5qna1tCvIbi6y7BUuVAbHuR3XNhyztwyrDNzDcCzhpe5urGwLG1pOdAt889WXe4YveyLrjViwfDLXz4ylI/tsvsih84B2Jk3m2fRClRlQRE0KuStrRlM4G0nHjWHH2ChLTfipStH6BfQ9+zGSYPAl0FgqT6Pw2PjgzAz7022fl6wQjyjDHdo+7v2Qmd7hhh/kvwcBEXu82TWJECSdvge+WCD9MEXEvqXnPjPedBEWSdPknP+Wn8UYEjY92cYW0vuLaWYQ19bzF3T4tu0P99qCHr6RWZTilbuQRE0CuXr9ReQQJf7ormdOZ2anpHk69LJiPX7F/VnW/CqDsPkV6BKzgfH9WAPkOPar1U+9g9XXSmG9qMou7pGkVEyEqcL5drTCvI9Iornp0Cn3WGpO1FxVy549UJc9mp5BVArx+D+HnXuXIPr463E7sHNyEo1XCZi6opMBS8a8LRbdAgGl6Rk+TKDVgKVjoBEfRKRywNlJfAphOTWX98jKm4crfX9IkkOWMjBfnw+gA4uqe8tcMtvWHEZIpc6GJ5Q5u6N72O3wBC/WaUvxEpaT8CS4fDtrn69fTiN6eFxpB/eC29l8Bic4iFzW3fXh9+utlQLFwF4+2FTIvlnLsmQY8XbK5XCgiBqiAggl4VlKUNmwkkZWzji12dCfOLJjHdvD1NVaTc7TNeWsfKb8p/yEjHrr688oEThZzX+mZ5oYtR1IO8etE4aK7NfZcClUjg+wGwZ3HRa1AtzmYvcPXj1q8K+GN/Zrk78U6sJ0Nu7QB7ij53NI2F+O0wdiU0lKWXcgOWgpVGQAS90tBKxRUhMHdbNMmZ+iNBQ/06kJ77H7kF+iNeN/0O88aVv/ar2sIrcyDYLxIwnzJnKeotaiyklk/f8jciJSuPwKYP4fvH9fVbXrSirHbvumSc2EvHL2BHObe0ebo6sb27jogAwxDUKXLBjeGI4WpcJeaTxfVeeRMsNZeXgAh6eclJuUojsOH4dNYnTDAJuGpIudvr+kby3/6NTLwf8sp5CVf9ZvDR4uvIcdWfy178Uhcl6qF+j1DHVyKaK22C7VHxlrmw8WP9feYqFbtk5WTgtbSZ/A8ny2moXx0Im7uDexN1h3oxt7sS+HsmwO3P2GMkUocQsBsBEXS7oZSK7EEgJTuetzc0wsM1gHp+kZxMNx/xquqfN8KffzfoLXVbk48/vLEYgmtDPd8YzmXrxcBS1FvWnEM9PxFzW9lekvyb58I3A0uIOeGxsG81O07D9V9DZjlvaht2bW3ebnqq6NCaqHvUdwFO8OZWqCVR75dk7qXRUgmIoMuDcVkRmLetM0dSzWuX9fyjyStIJj03gS2/w5evlK+7Ts4wdWELGkcnkGe4na2OTydSc/QnzSlRj67zLvX8xM1ePsKXqNT6D+Gn58w3poXFwCGD1e7uzx+p9bjlkz0U6srXvz9uhK51DNHuPjXhsMHtrqpr2RleXlG+iqWUEKgEAiLolQBVqiwfgd3JS1h/fAbJGVvJMayXq5qUtR5Y2JIRd6wrEnBsSyt9RsKt/UCdLIdTOll5+u1vStTVFax1fXvRpq4EwNnC9LLJ++UA2LlYf/XpQf0LmnbhipuvdvLbe7vgyTXl620dT9g/vBO+CTuLRrt7+UN4G+g+HDrcWb7KpZQQsDMBEXQ7A5Xqyk/gzXXhpGQfwcMlgDD/VhxLM3w5A99OhB1/lK/utje5MmF2S85l64Ps1EUu/p61OW84QjYi+Gna1JWtaeWje5mU+nY4rJqp70zdKDgdbz7lrV4U98z9l28Pls/3/mwETG1lMc4IdbDNLshI1bvcP6jAiTaXCT7phmMQEEF3jHm84kex6shk/jho3nOuBlTPNxoXZx3rVm1n/qjyDbFOOLy4ENw9oUFgZ5IzVpoqqusXQ0FhOt2aWLhRy9eMlLocCLwerbfKD1pcrtIoDvau4nwutPwOjmXY3lE3J9h9MzRVN/eotXNLt7uq7oFJcK/sTbedrJSwNwERdHsTlfpsJpCVn8JrqxvRMDCaU+e3FHG3FxbAhwM8OHPC9rB2D2+YsaQ9njX3mCLm6/p1ICP3P20d3cetId0jtuHuIjdp2Txpl2OBzBSYFA1nj+gPnqnVAg5t0PfU058NhU3o+P7Wcq2n/69RIEujUoqO2tMfGrWBA9vh08PgK8/R5fhYVKc+iaBXp9m+TMf6+8EJLD34sv571zWAhoFtOJqit6S3/gy/vFW+jvcZAx17QpBXJK5OOlINLnYftzCCvGpzff2PCfKUA0LKR/cyLXV8G8wfBOdOwTn9rWzUigCdEyTu5eVtMEG/8mJzWtIBetY1FGseBwe36d3uKj0wHvpOsLlOKSAE7ElABN2eNKUumwko63zWxo6cSv+vSNkAjzCCXRvwfPd1ZBQzjKxppFkbL8bNrU9Ktv4cULWPvY5vNCcNp87Fhc8hMkS2p1nD8orLs3YuzNHfzkeTWDi23RTQVlizGR0/O8aGRNtvZ2vgBfueuB6P08fgtOFlwQgnrAVMWydW+hX3sDhWh0XQHWs+r7jR/LJ/Ar8eeJmmwZ1IzT5Mao758pV/FsGaT2wfkpsHjPocgupA46DOJJ63WDf37UAt3zbc0OA92yuWElcOgQVPQPxWOGhwuaueN42D3au0dfSWv8D5csTIvdwMxjWzwBASCjUawb9/wYPj4SGx0q+ch8TxeiqC7nhzesWMSFnn41c0Qv1rTBEhcZxM30pqahofPQi55Tjp64GRTYi+66Cpzhrekbg56zRr3c+9Ife32oaHrJtfMc9JuTqq1tPHRsOZI3qXe6GT/qIVQ3o/tRlP/LLf5qq9nCHhJgjy84eGrfVCbkw+gTBf1tJthioF7EZABN1uKKUiWwksOzSdlfHTiljlqg61jr5tgT/LFhyztUrqNIXHP4BafpG4u+g4Z3C5q4qUtR7XcDo1vGXd3GawV2KBPSvhmwmaVW5K9aMgKxtdwl6uWQ7bLC5Ss3aIEzo2ZHztFPP6ubFgcCjcPRLukSNhrWUp+exLQATdvjylNisJZOalMPoPvXUeGaJObDO725VxNW8AFORaWZkhm7OLE6Pm18QnNMlUsHFQHGeytmpR7h3rjyemfuW7RNPSM9m6cz9HE06RkZmNp6c7oXVq0ObqZtQINt74YdvYrsTcubl5/HfgKIeOnCD1fAY5OXn4+ngSFOBP82YNaFS/Dk5OTpU7NCXo370M6vz1Bm3gX7O4b8iryXU/2H6DS5ArJMSBl4uh60rIazWCHX/p19C/ECu9cidVar8QARF0eTYuCYE/Ds3gq11FLRm1bU25xhe8tp3dv9verXa9oNtQaBrcmVPp5u1v/p5h1PeL5u6rfrS9UhtKHDxyglmffMefa7dQUFBYasnrrrmKIQN7cU0ry4VYGxopZ1b1YrF7Xzz/7o1n555D7NpzmOOJRcXs3UnD6dyx4t6LnXsOM//r3/hj9Wby8i68UB0S5M+dt3Si373dKvdFZ8odcGgbnDEEshlPedu1igc2wRfF4tusQTwtAkZ0jtK78g8UO8dg9By4RQIureEoeexLQATdvjylNisJzFh/BwlpWzmXbQ6CU0WzUuCLgaArXQ8vWLu7lzNDPy9EfVer5K+i5L3qceK8/nKXflErCA/sbGXvbM+26IcVTHp7IXn5BVYVfrRvd54edHelWqipaRm8/s7n7NpziMPHTqLTXfxA84oKunqJmfb+V8z/ZmmZbVlC8vf1ZtyI/tzapYNV7GzO9O9KGH+jvpi6Pe3sCVOUugp2b7rMmcx82x64et5uHG6Xh7tzsd6oILmm18DrP9jcTSkgBCpKQAS9ogSlvM0ENicuYeb6Xlq5hgHReLp6cDhFH4289UvY8oXNVdKhD9w3LBpXFx2n0s0bjdVpc02C4+jWtPKOdv3y+z95dfr8Ep12c3WhRkggZ8+lkZObV+Lz/vd247khfWwfrJUllMv/1r6jrcwNFRF09bIw+rUP+Hm5/lpay6Tc6soa9/Rw11zv59NLRjqqPBOfH0TPbjFW99emjJ8Oh12rip7y1kBvYU9auo0X9bsbbUofRsCj9QxFItpDXi7sN1jrExdDrJzxbhNQyVxhAiLoFUYoFdhKYMb6O9mS+H2RYkFeYdTxacxrPdaQmWLb1VgePjBoAah/VWoa1InzuYdJy0nQzoV/NiYeT9fKOcVLubAfePJV8gvMlnmThvUY/ti9dL4+GmdnJ81a3brrADM//oZN282R1qqvM14Zyv9i29mK0Kr8FxN0by9Prc9qnduYKiLoi39dw0tTiu4xbBBaS1teUBx8fbxM7Rw7kcS3P69m7le/FvFoKMH/af5k6tYOsWp8NmVShxk8Fq7fjx5ksdUMyC2EsBVOJOfY9tyFezlx8JFOOCcchuRifvtOPWHyEpu6KJmFQEUJiKBXlKCUt4lAUkY8s/95iIy8JE6lFzWLjq6HVVNtqk7LHDvIk3sebUd8isUWIiAyJI7IGt2Ia1h552wPfOZ1Nm7dY+p0qxaN+eiNUfj5epcYiBLQ5159n99X/mP6LKxuTX5a8DrKmrd3Mgq6h7sbzZs24OrmjWgZ2Uj7t1H9utw3+GVtXd0egt71vpEknjpj5tC8EZ9OH416cbhQ2rJzP4NGTi3iveh7V1fGPPWgvVHo6/t6Mmz+HXZaRL2r37eIZdKvG3hxt+3HC/94FXQPLtbdxlHg4QcTFkA9uS+9ciZTai2NgAi6PBdVSmDRvxP4erf+mNdgrzDC/JtwPHUrWflpLJsAiTts6453EPSbA67uEOgZRi2fcJOwB3k2ZGTHbXhVknW+fstuHhlhfgNRwrlkzkSUZXqhlJ6RRY8BYziVfM6UZfyI/vTuYVjjtW34F82dlZ3LkeMnadooFFeXki8M9z42wS6C/t/+I9zz6Pgifflh7kSahIeWOZp3Pl3Me/PN3pp6dWrwx5dvllmuXBnSU2BYNCQd0RdvHgMnj2jr6eqQmdBVcN66EAhT83eFwLctQAveaBINxw9BksFaHzQeHq38XRXlYiGFHJKACLpDTuvlO6gnfg7ndKbhocNtrgAAG4NJREFUC9Wim3Vz2zLrwc02d/y2J8Npc3dekb3sRmG/LuwRrq1XedHGo155j1//NJ9EZq11+fni5UycucA01qsiwvn6w6r/4reXoKt1c+V5MKZmjcJYMuc1q+by0NFE7uhX1IOyffknpb6AWFVhWZmWzYVfPzYJuSl7cCjP73diymbbQt7dnJ1IerADgXtKxg5QNxyWyNWqZU2JfG4/AiLo9mMpNZVB4NC5bXy4ZRhOujwOnLM4khPYPg/2/2wbQhc3eGA+uHsr93rRvezKOn/lRrM72baay86totk79RyKsriN6btPXiWySf0yC6ugsLi7ni7ial7+9VvUqVncd1tmVRXKYC9BL/6Cora+qfV4a5Jaw29z86NFsq774V0C/A0BEdZUYmueh8LNVrrFHvLkXAj7G3JtW0pnegMYXqdYJ5q3Bxd3GD0LIiu+FdDWIUr+6klABL16zvslGfWHm4fzw96ZWtvebgE0Dm5FZm4Sien7+H4g5Nl4V3X0LUG0fcLsulb1Gveydw4fznVhlWedF3e3qwNjVn2nH5s1qfja+7hn+nFfzy7WFLVbHnsJ+o9L1/H8pA9N/bqu7VV8Mu05q/qpot473jHElFctDWxZ+hEuLsX3g1lVnXWZls6Fb2eUuof8yZMhvLfHHAtgTYUtvWBXKyAsAgJqwYGdkG44gq7P0/Bs5e2wsKZ/kqf6EBBBrz5zfclHOvD7cJIzSrrbs/fWYPkrp23u361T4Oo2kQR51eTgWXNAnJdrALNuK8cVbTb0YO6i33hj9pemEl1vaMvMV4dZXcPbn3zLBwvMB930vqMz40dW3gtIaR2zl6AfOJxAz4EvmppQ+8rXfD/LKrf56vXbeeL56aay0S2b8tm7L1nNsdwZuwcWPbr1qhg4d5rde/fScovttW66rhZtc8wnFJpqUG73n8XtbjtRKVEeAiLo5aEmZWwmcPDcNt7eMBh3ZzeOpO4gMy/NVMfOT+Don7ZVGdwIbp9mLqNEvHFwG05n7KdTw0H0jKzcNelxb3yqbb0ypsH9ejDs4busHsQvyzfw7KvmG9/ato5g/ttjrC5vj4z2EnTVl14Pv8S+Q+b15xeG9eXBu/930W6qg2j6Pz2ZrbvMl6S8NvoRet16gz2Gd/E65k6Anz6G0Kawb5vZogau3Qab0m3rwpM14F3L1RZvFSTXCvLzYez70Fzc7rYRldzlISCCXh5qUsZmAu/9M5zFe8wu6RY1O2jiHp+yne8fOU+ejV+gcU8H0fWuKJIz9pc4be797ufwdqucfefGgT80bBJbdpq33b08aiD3dI+zmosSsQeHTjTlDw70Y82SWVaXt0dGewr62n928diz5uh05TpXp7/dfXtsqV1VcQTqpWjpqk2mz69pFcG8mS9oe/crPamI91uDijaj1tPDmvLu6u0M3WWbhyfQBZLa++HWrLVexHdaxIj0fRpGi9u90udUGkAEXR6CKiHw4HfhJJXibj+3BzZNsq0Lrl5wx8egguJUigzpgKszHDq3gU4N+vNY27m2VViO3Lc9OJojx0+ZSr4/ZSQ3dFALqdalxKSzdO09okjmXSvmVOpRsMV7Zk9BV3XP+/p3pr5b9Jg/dcjOjTFtCK9fBw93d9LSM7Rz5P9YvalIQKG6uObdycMJ8KvEYLjiACYOgN/mQWR70DnBLr0In8uH2lshz4rguDAPF+5tWofeQS5cl3q09MlXe9F/E7e7dX8ZkqsiBETQK0JPylpFIDE9npf+7EWARwDnshNJSDNbtnsWwrGlVlVjyhR9Wx1uGOqvBdNZJrWvfUynn2kY2Nq2CsuRu/Pdw0k+Y7biFswag7IwrU3qnPWOPczBYKrcP79+gLeXh7VVVDifvQVddWjNhh1MnvVZkZedi3VU3ULXv/ct3N+zS+UGwpXWiW1/wUv3Q3LR+wRUcNs9W87ybXzpcR31PJy5p4kScVc6ph7lghfG1Y+AGnUgLQ3eWQyhcshMhR9aqeCiBETQ5QGpdAKL/p3BrI3mm9VqeofRIKAJ+bpsPuqzgVwb76S+9lmoFQ1h/pHU9KlDUsYBzmYlUMO7Ie/dXnlb1SxBdbj9iSIW5lcfjOfqyEZWs8zOyaVtt8eK5FdR8lV5vWplCLoaUGZWNjM++pbPFy+76CUtQQF+PHTPzZpbvirHXQR6z3D9nvQaoVCvCZw+BUf28mMq9DhkzlnH3SjiLnRKO3ZhEb+qPbh5wbGDcNJiT/sL06G/dVv5rH6IJKMQKEZABF0eiUon8MLyO/nraNGz21Wj5w/BduvOHzH10c3Lma7vF+LsWrTbTYOjuT1iCP9rPKjSx6MaiO76SJFzyK3dg27sXGGhjlZdBhbp69Iv39TuTa+qZG9BV2Na8O1SPlr4E+dSz1s9DHd3Nx5/8A4ee/COqlk/t+zZ4o/hq3f1gXEWqUAH0QfduSG0BvcFuxB7IRGvqdbdm0BWDuwoerZCkQq79ITZcra71Q+FZCwXARH0cmGTQrYQ6L+kHX7ufmTkpXDgrPmL8+iPcHSxLTVBnevhxpH6I2NTlfv+vNnt/knPw9T2qRq3ZvvbBqPuGDem6m6hK4/DsBffZt2mXSYmaj28T6+b6NyxDQ3DauPl6UFqWrp23OwPS9fx24qNRSz4bp3b88bYwVXrej8RD90tPCvKTR5SV29hn7rAqXFNo8AnsKQVXtqjHBEFfoGQmQGLzWf42/bUS24hYB0BEXTrOEmuchLYd2YbDy1uU6R0ZI1o/N0DWTJ2MwlbrLfkVCWtn4LaFpeT1fDWi7uvuz/j4qruDurKWUN//6KXmZRzCi5YzJ4W+ogJ7xa5dKZV80a8M2n4RV3p6zfvZthLb2suemN66pG7efyhO+w91IvX91QPSE+7sIgrK1ztJ8/Nh8N74PxF1oiMAp6WCv8Vtfr5YStcJdvXqnZyq1drIujVa76rfLRf7JrBjPXm9XPLDmwaBoXm7/Iy++bi7sTgRTFkkFQksE4VHNxuOne1qLo1yuJR7h9MHUmn9tUzyn3V39t5Uq0RG5Lagvf93Emof8tKKtp9+Lh3TNmU+/3Pr99Cra9XWVowA94o9owqSz24Lpw+CYeLXnlbpF8NIqCmIfCtuIAXH8CL02Fg1T2jVcZPGrpsCIigXzZT4ZgdGffnwyRmHEJHASfTD5OcoY8ozkyAXTae/RJyDbQYqufk4xZAREgr1Jbl+JQdvN99O3V8q8bdrtp/aNhE1PWfxvTKsw9fcM91aTO77d8D9B1iDiBQAvbX91fmPvTHn5vGXxt3mob5zGP3MuiB261+oIt7Cqw5lMbqyq3JmBAPd0dB01b67Wv7dl7YCjcKeE4OHCzDWldtK+teRberoI8GjeHNT63pkeQRAuUiIIJeLmxSyFoC3RaEk5huPu61tk8YdfxCiV92lr9mmwXRmvqiHgnEL6bkgR+1fRryTe+qiW439nPs1E/57hfzSXFP9OvJ0Id7WTMMLY+6pU3d1mZMasub2vpWlckeLnd1x3uH255AraEbk7ppTd24Zm16d85iZs8zB01263wtb00ouqXP2rrKna9LOJwoeSwxtgq4crn7BkB2DhzaA8r1bkxh4bBO9qOXe46kYJkERNDLRCQZyksgLSeFTp8WO43LUNmxeZBykaDg0tq8ehyENw+jnl+4Zpkri/90ZgL3XPU0T3eo2pO45n71G2+8Zz7L/X+x7ZjxisF9YAWwWZ9+x/vzzWv+93bvzIRRV95Z7upe9y73FnVX27qffvGva3hpyicmauqQmYXvmM+GtwJnxbOo2+HmzzRb1MpSV5a75daz4q0o67tOqH6bmhLu3cXWzEvr1c5zEFC5pxhWHIbUcKUSEEG/UmfuCuj3xoQ1vPPPWJx0kJGfyr7T5i+8veMhN9n6QTi5Qbt3wKnYJVy1fMJ4vtMHxNS/zfrK7JBTBXQ9MnKqqaaK3rY29pl+2uEqVZnsYaEfT0ymW59ni3Rb3Zbm4W44xs+KAf2wdC0vTPrIlLP1VU34YvZYK0raMcvKX+Clxy8u4JbW96kESLTy7vRIFekeoHfnj34VrquCs+rtiEaqunIIiKBfOXN1xfX07Q0TmLXx5SL9bhwYiV9BIN8OtM08r9XKlx4T25JfmE1y5nHTWryqfFm/c/i5V63Vo+5Dj+kxpMjWNWv3oqs71GN7PVXkPvRli96ibq0r7z50NRZ1yI5l+vWzKTQIrW318/rhwh+Z+fG3pvy23KdudSNlZUxLgWssvEnlsb59/CGsEfgHQn4BnE6Gg8UC6kaOh2dtDB4pq+/yuRAwEBBBl0eh0gg898cAFu+ZV6L+zD1wYrZtzda8FepY7GYyrsU38G/MxJs+t60yO+Ue+fJsbS+1MfW963+MeapvmbV/+f2fvDp9vilfi2YN+eajoi8+ZVZihwz2sNBVN67v/iRp6ZmmHtnqbRgw/HX+2bbHVF6dHvf80AfsMEIbqxj2ABw5BNZY37UM7nYPL1Db7k4mwAkrLPbe/eHtyr9rwMaRS3YHISCC7iATeTkO4/nlgziacpDzuSmcy07mVLo+wj31L0heZFuPr302lOxGxc7cBnpE9ue1LpfmC/LvTf8yaNQbpoF4erijAsLq16t1wcGpw2h69B/DyeSzNgngwSMniD960lTG38+ba6Ob2waxWG57Cbradqa2nxmTGr/ioHiUlTbv2Ee/p4rezjN78jPEXR9VVlH7fz5iAHxT8gWUhuqwmZrg4gqpqXDk8MX3ohfvWe1QCK6ht9wbNYUZH9u/71KjEAC5bU2egsoj0HBGyWswW9aKZt8XJzn4k1mcrOlB46ng7Akta0bj7xlgWpfvGdmfh1pfur296j7vTdvNbtWoq5rw4Ruj8PXxKjEsFRH+/MQPtQh3Y1JHvf68cApuri4XxaBc0so1bUxXRYTz9YcVc93aS9D//GuLdkCMZep6Q1umjh180bX0Q0cTefiZKUUuualdM4jfPpuK2o9e5enjGfDVXPN6tzpAZpcVgW7GjoZH6EXbywuys0FtbSut/GkrrnGr8sFLg45AQCx0R5jFy3AMqTkptH6v9Aj35E8gy3xCaJm9dw2E8FdKz7bwrhV0CO1cZh2VlWHnnsP0HfIqBQWFpiaahIcy4rF7ib0uynQ2ubr/XImypWtZFXhrwpOoI0/LSuUV9D/XbmXDlt2lVv/L8vWcTTGf1HdjxzaE1i39LPlRg+/Dza3YAfoWtao99WpvvWVSHNSpb7EdWuPn62366NiJJL7/bS3zvv6NTHUGukV6bfQj9Lr1EgWNrV0Jd9948alQ6+QNGoGPr9liP3vaOne7seaDEule1vMun5ePgAh6+bhJqTIIrE/4i2nrxnI+R79v/D+LCPfEqZCXaD3CoEgfbp7YDmXvp+emFnHf7x926a2dz777g0lvf1ZiQMrqrhESyLmU80X2aRszPnj3/1CHqFiTyivob8z+krmLfrOmiYvm+efXix9Lq5YQHnjyVdQ2tuLJycmJkCB/zQWfej6D8xbr7ZZ57+vZhXHP9KtwXytUQR2DV8nSTa4eMbUtzVZXu2VHWkShPcDKgh/zGnTsVKFuSmEhUBoBEXR5LiqFwC/7lzBgScmDVlrVjmbloO0U5lkvxD7XQkgpMVJx4d2Yf2fFxcoeAL5YspzXZ32Ocqtbkx6+/zZGPH4vSuysSZe7oKsxJJw8zfMTPyhygp41Y3NxcebJ/ndemtvWinfw3ltgxe/WdLtoHkvBVp+kGA6U2VmKy/6nFXDDpfMq2T44KXGlEBBBv1Jm6grr59S1E3hzXcnI7YI0OGvjlakNe4ag63ymBIEOoXEsunflZUPmwOEE3v70W1as3Yq6SrS01L5Nc4YOvIu2rSNs6veVIOhqQGrcv6/ciHrBUUfj6nQXfnFTcQa33XQdylPRpGE9m3hUWuYenWHdqpLVN4rQr40rC7sswS6rc8+PhxcqFv9QVhPyefUkIIJePee90kc9+5/pLNqt35p1LiuZxPP6CPW8w5BiPvHUqn749QbPduDrHkCjoEZ4uHjg4+5FTIObGN7hJavqqMpMyq28Zec+jiUkaWvEytVcr04Nols2pVaNqt0vX5XjLt6WiujfuecQCYmnNTd7Tm4evj6eBPj7EtG4Pk3DQ6v+/vOygEx4Hjat129FU0Ftys1ueXxrWeUv9Lk6US7EEJ/Qpz8MK/3CovJWL+WEgCIggi7PQaUQeODbO/llv/l8bmMjQXvrED/Xtgj3gMHg3rhkN0d1HM9zMWLpVMoEVtdKJ0+A1204E+Aqw9q4ty8YgwYzsyE3B7KzYF8pN7X17Q8fXpqtltV1WqvLuEXQq8tMV/E4b/+sM2uPlXRd5qyCbBuXvW96uwPeNfTbwNJy9UF2OXmZPHXdC/S5umrPP69ijNJcVRP4bC68OVnvXlfJeO76/9u78xCr6jCM448zZhuWJZJSKEQlIjoYlpmaUoK0aYRp2iKa5ugEhZpjog1hQzUuaeICbmk2RmmKabTM5FpioDhTabS4VYzrkCChNGn8js1i3jt3mXF73+/9p3/uuec8n1d7PPee3zlhEUPlmfreOp61d+0ufX7p/FR0oYnZ3/kToNDPn63rTx66+in9eGSnTlT8pV/Kf6qyOFEknSxOjea6SVKDGCumPhm4Tt1acnFRapq8u1aBjeulBxMsXUuX8Nb/fodv01ZafO6qiHQ/lu0QqBSg0PmzcF4Eei7poU37zz1DzyhqpBMbqh+1mXDnDaTrz76RWNUmFHpCPd6QqkBthV7zd/DwuWEtesMa/9Ks/Kq9cp+745zJ39ddKuYMPdXR8P7EAhR6YiPX7yjetF0Fs5fp0NE/1bF9a+WPG5rUhV1Xvh57OVbFGulUKs9luUpqVONJmjc3vkXNrj1zcdGHfVepVZNWrudD+HoWKC2VhjwrheWEh49IfyRxf/Z0DiGJZZvhosJXJy/U+m92KNzqN/uZ3gpr9WO9wr0QVqzdqH2/H9QNTRqr36M9omWAvHwJUOi+5p1S2vBozHDf8TfGP6/OHdsqf/p7OlJ+TAumjU34OW1ntz7rq/bKDSpWSqe2J9y8+g2NpUZxdndyQvJr2VPYI2/1LnBFcvcGSJvptjukXTEulvvfB4YyD3fVm5qXoz37y5SdO1Vz3xodc8nj9HnLFZZEhtUDu/eV6aW8mcrNGag+vbqkfZhsePkJUOiX38wu2BGHe4dv2faDFr09Ltpn2aFy9ew3SsUfTVPzZrU/6rPBa3H+p7hcUgq3fb2m+dXqXNDpnMwVpyq0ftCmC2bBjhwJdOtafcV6rNh//yMdPx4fZM+eMw9xqe1Vy/r8sFl4PG/nR0ZEBd4xq3X0SRMLFkb/nTR2SMJh5E1ZpMzMzIt/572ER8ob6lOAQq9PTWOfNXbSXDW98Xrl5gyoSnZv7xwVTMhW17vb1Zo2bqEvk5T45KT6s1tIGh57V6fzOEM39kfu0oiT5N376nSwCQo9fHX+0NO52rp2TtWDft7/uEhrirZo2eyJCf6tcFqPPzcx+nr+yThf0dfp2Nn4khWg0C/Z0Vz8A3th/Ay1ub2lcgZX38K114CXNWp4P/XqcVd0gKWlpSopKTnrYLOyspS1Ms7jL8O9ZnankC38RD6YQk9BjLfWVeACFHppSUnMvzft27ePjn7Xz/vUd1ievl+3qOr2wKu/+FrzCz/V6nfza00Yvn7f/O13Kpw14eI8ta6u/myftgCFnjad/Q2TOUMPZR6z0LMuwvOs7Y+EhEYEEv29SfcMfX7hWq36bLMWz3gleiAOL18CFLqveaeUNvyGvnX7rqqL4MITtR54Irnf0FPaEW9GAIGzBMJv6Pc8PELzpozRne3O3Pc/XCQXvqmP9xt6eKreB6u+0pJ3xie1EgVyewIUur2Z1luicIXtY4MnaEreCHXq0Eb5M5bqwKHypK5yr7eD4IMQcCoQLoIrO3RUU/NGau9vBzRszGTNeXNUdJV72cGjWrriS43O7h/dDz/8vj6/cE10AWuLm5pGYhkZGQqP8OXlR4BC9zPrtJIWbdqmglnLdLj8WErr0NPaGRshgECVQFiHHkp9w5Yd0YVxIwf1qVqHXrLz1+j58yXFC9QwM1M9+4+OSr7m6/4uHTQz/0VEHQlQ6I6GTVQEEEAAAbsCFLrd2ZIMAQQQQMCRAIXuaNhERQABBBCwK0Ch250tyRBAAAEEHAlQ6I6GTVQEEEAAAbsCFLrd2ZIMAQQQQMCRAIXuaNhERQABBBCwK0Ch250tyRBAAAEEHAlQ6I6GTVQEEEAAAbsCFLrd2ZIMAQQQQMCRAIXuaNhERQABBBCwK0Ch250tyRBAAAEEHAlQ6I6GTVQEEEAAAbsCFLrd2ZIMAQQQQMCRAIXuaNhERQABBBCwK0Ch250tyRBAAAEEHAlQ6I6GTVQEEEAAAbsCFLrd2ZIMAQQQQMCRAIXuaNhERQABBBCwK0Ch250tyRBAAAEEHAlQ6I6GTVQEEEAAAbsCFLrd2ZIMAQQQQMCRAIXuaNhERQABBBCwK0Ch250tyRBAAAEEHAlQ6I6GTVQEEEAAAbsCFLrd2ZIMAQQQQMCRAIXuaNhERQABBBCwK0Ch250tyRBAAAEEHAlQ6I6GTVQEEEAAAbsCFLrd2ZIMAQQQQMCRAIXuaNhERQABBBCwK0Ch250tyRBAAAEEHAlQ6I6GTVQEEEAAAbsCFLrd2ZIMAQQQQMCRAIXuaNhERQABBBCwK0Ch250tyRBAAAEEHAlQ6I6GTVQEEEAAAbsCFLrd2ZIMAQQQQMCRAIXuaNhERQABBBCwK0Ch250tyRBAAAEEHAlQ6I6GTVQEEEAAAbsCFLrd2ZIMAQQQQMCRAIXuaNhERQABBBCwK0Ch250tyRBAAAEEHAlQ6I6GTVQEEEAAAbsCFLrd2ZIMAQQQQMCRAIXuaNhERQABBBCwK0Ch250tyRBAAAEEHAlQ6I6GTVQEEEAAAbsCFLrd2ZIMAQQQQMCRAIXuaNhERQABBBCwK0Ch250tyRBAAAEEHAlQ6I6GTVQEEEAAAbsCFLrd2ZIMAQQQQMCRAIXuaNhERQABBBCwK0Ch250tyRBAAAEEHAlQ6I6GTVQEEEAAAbsCFLrd2ZIMAQQQQMCRAIXuaNhERQABBBCwK0Ch250tyRBAAAEEHAlQ6I6GTVQEEEAAAbsCFLrd2ZIMAQQQQMCRAIXuaNhERQABBBCwK0Ch250tyRBAAAEEHAlQ6I6GTVQEEEAAAbsCFLrd2ZIMAQQQQMCRAIXuaNhERQABBBCwK0Ch250tyRBAAAEEHAlQ6I6GTVQEEEAAAbsCFLrd2ZIMAQQQQMCRAIXuaNhERQABBBCwK0Ch250tyRBAAAEEHAlQ6I6GTVQEEEAAAbsCFLrd2ZIMAQQQQMCRAIXuaNhERQABBBCwK0Ch250tyRBAAAEEHAn8CzmxrvN5LmDNAAAAAElFTkSuQmCC"
     },
     "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": "b149306f",
   "metadata": {},
   "source": [
    "### Feature contribution on data drift's detection"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "033b0175",
   "metadata": {},
   "source": [
    "This graph represents the contribution of a variable to the data drift detection. This graph can help to understand the drift when the analysis of the dataset, either numerical or graphical, does not allow a clear understanding. In the drop-down menu, the variables are sorted by importance of the variables in the data drift detection."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "d58a440c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "SD.xpl.plot.contribution_plot('Sex')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "626b024b",
   "metadata": {},
   "source": [
    "This graph is more complex and is usefull for few use case. It provides an understanding of interpretation of the datadrift classifier feature by feature"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "dev_eurybia",
   "language": "python",
   "name": "dev_eurybia"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  },
  "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": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}