Pyckpocket_6_Interprétation_de_modèle.ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "id": "ghT-qNrBMuDN",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ghT-qNrBMuDN",
        "outputId": "4ff917f7-1247-45b0-91ff-1c71651cf06e"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ],
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Import des librairies"
      ],
      "metadata": {
        "id": "JrqLvdKwv_Ee"
      },
      "id": "JrqLvdKwv_Ee"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "b2b318c9",
      "metadata": {
        "id": "b2b318c9"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "import statsmodels.api\n",
        "\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "\n",
        "from sklearn.model_selection import train_test_split, KFold, cross_validate\n",
        "from sklearn.neighbors import KNeighborsClassifier\n",
        "\n",
        "from sklearn import metrics\n",
        "from imblearn.metrics import classification_report_imbalanced"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "id": "9eb0b161",
      "metadata": {
        "id": "9eb0b161"
      },
      "outputs": [],
      "source": [
        "# Import DataFrame pour modélisation\n",
        "df = pd.read_csv('/content/df_model.csv', index_col=0)\n",
        "\n",
        "# La saison lue en tant que numérique est remise en chaine de caractère\n",
        "df['Saison'] = df['Saison'].astype(str)\n",
        "df_tot=df.copy()"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Sélection des variables"
      ],
      "metadata": {
        "id": "-dGojUB9wgN0"
      },
      "id": "-dGojUB9wgN0"
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "id": "k2fr067mby_S",
      "metadata": {
        "id": "k2fr067mby_S"
      },
      "outputs": [],
      "source": [
        "# Variables sélectionnées pour la modélisation\n",
        "xvars = ['Saison','Min_cote_domicile','Min_cote_exterieur','note_def_ext','note_gen_dom','Points_moy_match_saison_dom','Moy_buts_5_matchs_dom',\n",
        "           'Points_moy_match_saison_ext']\n",
        "\n",
        "df = df.loc[:, xvars + [\"Resultat_match\"]]\n",
        "df['Resultat_match'] = df['Resultat_match'].replace(['H','D','A'], [2, 1,0])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "5e957e0e",
      "metadata": {
        "id": "5e957e0e"
      },
      "outputs": [],
      "source": [
        "# Création des dataframes de cible et de données\n",
        "target = df[['Resultat_match','Saison']]\n",
        "data = df.loc[:, xvars]\n",
        "\n",
        "# Remplacement des modalités de target par des nombres pour la modélisation\n",
        "target['Resultat_match'] = target['Resultat_match'].replace(['H','D','A'], [2, 1,0])\n",
        "\n",
        "# Création des dataframe d'entrainement et de test : entrainement sur les saisons 2015 à 2020 et test sur 2021 (saison non encore terminée)\n",
        "X_train_=data.loc[data['Saison'] != '2021', :].drop('Saison',axis=1)\n",
        "X_test_=data.loc[data['Saison'] == '2021', :].drop('Saison',axis=1)\n",
        "y_train=target.loc[target['Saison'] != '2021', :].drop('Saison',axis=1)\n",
        "y_test=target.loc[target['Saison'] == '2021', :].drop('Saison',axis=1)\n",
        "\n",
        "# Standardisation des données\n",
        "scaler = StandardScaler()\n",
        "X_train = scaler.fit_transform(X_train_)\n",
        "X_test = scaler.transform(X_test_)\n",
        "\n",
        "y_test=y_test.to_numpy().reshape(220,)\n",
        "y_train=y_train.to_numpy().reshape(2178,)"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "EwTSUYvtze-o",
      "metadata": {
        "id": "EwTSUYvtze-o"
      },
      "source": [
        "# Modèle (KNN)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "id": "UMYoo9lHbh9M",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UMYoo9lHbh9M",
        "outputId": "5c63be93-abe6-48ef-810e-f1d1ce18a2b0"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy:  0.5181818181818182\n"
          ]
        }
      ],
      "source": [
        "# On reprend notre modèle KNN\n",
        "knn = KNeighborsClassifier(algorithm='auto', metric='minkowski', n_neighbors= 55, weights= 'uniform')\n",
        "cv = KFold(n_splits=3, random_state=22 , shuffle = True)\n",
        "\n",
        "scores = cross_validate(knn, X_train, y_train, cv=cv, scoring=['accuracy','f1_micro', 'f1_macro', 'f1_weighted'])\n",
        "knn.fit(X_train, y_train)\n",
        "\n",
        "y_pred_knn = knn.predict(X_test)\n",
        "confusion_matrix=pd.crosstab(y_test, y_pred_knn, rownames = ['Classe réelle'], colnames = ['Classe prédite par random forest'])\n",
        "\n",
        "print('Accuracy: ',metrics.accuracy_score(y_test, y_pred_knn));"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Etude de l'importance des variables conservées avec un modèle Lasso"
      ],
      "metadata": {
        "id": "bVMDwrktqUmN"
      },
      "id": "bVMDwrktqUmN"
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.linear_model import LassoCV\n",
        "reg = LassoCV()\n",
        "reg.fit(X_train, y_train)\n",
        "print(\"Best alpha using built-in LassoCV: %f\" % reg.alpha_)\n",
        "print(\"Best score using built-in LassoCV: %f\" %reg.score(X_train,y_train))\n",
        "coef = pd.Series(reg.coef_, index = X_train_.columns)\n",
        "print(\"Lasso picked \" + str(sum(coef != 0)) + \" variables and eliminated the other \" +  str(sum(coef == 0)) + \" variables\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_PHqc2KIlyCN",
        "outputId": "edd95eda-331e-410b-9e4b-762a857ea57e"
      },
      "id": "_PHqc2KIlyCN",
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Best alpha using built-in LassoCV: 0.011075\n",
            "Best score using built-in LassoCV: 0.151842\n",
            "Lasso picked 6 variables and eliminated the other 1 variables\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "fig = plt.figure(figsize=(6,6))\n",
        "imp_coef = coef.sort_values()\n",
        "plt.rcParams['figure.figsize'] = (8.0, 10.0)\n",
        "imp_coef.plot(kind = \"barh\")\n",
        "plt.title(\"Importance des variables en utilisation un modèle Lasso\")\n",
        "fig.savefig('importance_graph.png', dpi=200, bbox_inches = 'tight') ;"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 390
        },
        "id": "e-ZHqPvgl1TU",
        "outputId": "1f4cb540-25b5-40f6-ac8c-9f06aea7aef4"
      },
      "id": "e-ZHqPvgl1TU",
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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\n",
            "text/plain": [
              "<Figure size 432x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "La variable Points_moy_match_saison_ext n'a pas l'air d'avoir d'impact mais après un test sur le KNN sans cette variable, le résultat était moins bon. De même en enlevant la variables Points_moy_match_saison_dom qui, pour ce modèle, a peu d'importance.\n",
        "Ce graphique nous indique que plus la note générale de l'équipe à domicile est élevée, plus cette équipe a de chance de gagner (résultat 2). Au contraire, plus la note de l'équipe extérieur a une note de défense élevée, plus le résultat a de chance d'être une victoire de l'équipe à l'extérieur (résultat 0).\n",
        "De même, plus la cote des bookmakers pour l'équipe extérieur est élevée, plus l'équipe à domicile a une chance de gagner. Le contraire est valable avec le minimum de la cote à domicile qui a un effet négatif sur la chance de victoire de l'équipe à domicile."
      ],
      "metadata": {
        "id": "krZ-Euaol891"
      },
      "id": "krZ-Euaol891"
    },
    {
      "cell_type": "markdown",
      "source": [
        "Installation du package shap"
      ],
      "metadata": {
        "id": "OJfg7HSOpXcw"
      },
      "id": "OJfg7HSOpXcw"
    },
    {
      "cell_type": "code",
      "source": [
        "pip install shap"
      ],
      "metadata": {
        "id": "ligq13Okov9l"
      },
      "id": "ligq13Okov9l",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Summary plot"
      ],
      "metadata": {
        "id": "ogtwlN_SpaUM"
      },
      "id": "ogtwlN_SpaUM"
    },
    {
      "cell_type": "code",
      "source": [
        "import shap\n",
        "#X_train=pd.DataFrame(X_train,columns=X_train_.columns)\n",
        "X_test_df=pd.DataFrame(X_test,columns=X_train_.columns)\n",
        "\n",
        "# Création des valeurs SHAP\n",
        "knn_explainer = shap.KernelExplainer(knn.predict,X_test_df)\n",
        "knn_shap_values = knn_explainer.shap_values(X_test_df)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 67,
          "referenced_widgets": [
            "3592fb4fb773424eb308049f09ccb059",
            "0cceaf6b43434752adef131e4428e8c4",
            "a61dd028632642fb8acdca3067b58160",
            "56c4edbe5ac448e7958cc315521ecda8",
            "b7967b84fffb4fefa6b7ffa7ccd3adff",
            "aa1b38459d9447f48704f9e67ad77dab",
            "9bf8f69cfa1b48c5b199486e1b272e9b",
            "95c1386bd5ad40a89405815712d4839c",
            "3aed2d2853b24c1d8cdff9ce956f5203",
            "fe85260e4fca4379b38e858a9cbd08f5",
            "d3477ae940c34532aac1dbb4388d229e"
          ]
        },
        "id": "xsvZ0LPpmdMZ",
        "outputId": "e66e2a87-0992-4007-b077-fd6ca7a18816"
      },
      "id": "xsvZ0LPpmdMZ",
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Using 220 background data samples could cause slower run times. Consider using shap.sample(data, K) or shap.kmeans(data, K) to summarize the background as K samples.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "3592fb4fb773424eb308049f09ccb059",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "  0%|          | 0/220 [00:00<?, ?it/s]"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "fig = plt.figure(figsize=(12,8))\n",
        "shap.summary_plot(knn_shap_values, X_test_df)\n",
        "fig.savefig('summary_plot.png', dpi=200, bbox_inches = 'tight') ;"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 303
        },
        "id": "uU0feHAj1R68",
        "outputId": "6977fbb4-6168-4aae-beec-f5767bc13254"
      },
      "id": "uU0feHAj1R68",
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x309.6 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Dans ce graphique, les variables sont aussi triées par ordre décroissant d'importance. Là encore, plus les valeurs de la note défensive de l'équipe extérieure sont élevées (rouge), plus le résultat attendu est 0 (victoire de l'équipe extérieure) car c'est du côté négatif de l'axe que nous les trouvons. Au contraire, on retrouve des points rouges sur le côté positif de l'axe pour la note générale de l'équipe à domicile.\n",
        "Les 5 premières variables séparent bien les faibles et hautes valeurs, avec un effet négatif (plus de chance de perdre pour l'équipe à domicile) pour la note de défense de l'équipe extérieur et le minimum de la cote domicile et avec un effet positif (plus de chance de gagner pour l'équipe à domicile) pour les variables note générale à domicile, moyenne de buts sur 5 matchs à domicile et minimum de la cote de l'équipe extérieure.\n",
        "Les 2 variables restantes séparent moins bien les hautes et faibles valeurs sur l'axe même si on devine un effet négatif pour les points moyens par match sur la saison pour l'équipe extérieure.\n",
        "Tous ces résultats sont logiques par rapport à ce que nous pouvions attendre."
      ],
      "metadata": {
        "id": "R6j6B5vRqoR7"
      },
      "id": "R6j6B5vRqoR7"
    },
    {
      "cell_type": "code",
      "source": [
        "# plot de la valeur SHAP pour note_def_ext\n",
        "fig = plt.figure(figsize=(12,8))\n",
        "shap.dependence_plot(\"note_def_ext\", knn_shap_values, X_test_df, interaction_index= \"Min_cote_exterieur\",show=False)\n",
        "plt.savefig('shap_dependance_1.png', dpi=300, bbox_inches='tight');"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 355
        },
        "id": "BYBmx_YlotJ3",
        "outputId": "eb68157e-d249-49fa-9eb6-8e11b499e098"
      },
      "id": "BYBmx_YlotJ3",
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 864x576 with 0 Axes>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 540x360 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "On remarque une tendance linéaire négative marquée entre la note défensive de l'équipe extérieur et le résultat. Le minimum de la cote de l'équipe à l'extérieur baisse quand la note défensive augmente."
      ],
      "metadata": {
        "id": "mx_sUyCsudrc"
      },
      "id": "mx_sUyCsudrc"
    },
    {
      "cell_type": "code",
      "source": [
        "shap.dependence_plot(\"note_gen_dom\", knn_shap_values, X_test_df, interaction_index= \"Moy_buts_5_matchs_dom\",show=False)\n",
        "plt.savefig('shap_dependance_2.png', dpi=200, bbox_inches='tight')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 337
        },
        "id": "HSR2W_KyuA2O",
        "outputId": "69f3f391-4464-4afd-d505-aa4ed8fe855c"
      },
      "id": "HSR2W_KyuA2O",
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 540x360 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "On remarque une tendance linéaire positive entre la note générale de l'équipe à domicile et le résultat. Il n'y a pas d'interaction marquée entre cette variable et la moyenne des buts sur 5 matchs."
      ],
      "metadata": {
        "id": "V2RKpg3Ozjdw"
      },
      "id": "V2RKpg3Ozjdw"
    },
    {
      "cell_type": "markdown",
      "source": [
        "Niveau local sur un match"
      ],
      "metadata": {
        "id": "2Ln_8_dj0L2Z"
      },
      "id": "2Ln_8_dj0L2Z"
    },
    {
      "cell_type": "code",
      "source": [
        "shap.initjs()\n",
        "fig = plt.figure(figsize=(25,6))\n",
        "# A faire varier\n",
        "num_match_test = 3\n",
        "\n",
        "shap.force_plot(knn_explainer.expected_value,knn_shap_values[num_match_test,:], X_test_df.iloc[num_match_test,:].round(3), matplotlib=True,show=False)\n",
        "plt.savefig('shap_local_graph.png', dpi=300, bbox_inches='tight')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 317
        },
        "id": "-Jl_R6a4zh4W",
        "outputId": "023676ce-3fba-4a25-8871-2a80529aea01"
      },
      "id": "-Jl_R6a4zh4W",
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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n.childContextTypes?u(\"107\",this.getName()||\"ReactCompositeComponent\"):void 0;for(var i in e)i in n.childContextTypes?void 0:u(\"108\",this.getName()||\"ReactCompositeComponent\",i);return c({},t,e)}return t},_checkContextTypes:function(t,e,n){},receiveComponent:function(t,e,n){var r=this._currentElement,i=this._context;this._pendingElement=null,this.updateComponent(e,r,t,i,n)},performUpdateIfNecessary:function(t){null!=this._pendingElement?v.receiveComponent(this,this._pendingElement,t,this._context):null!==this._pendingStateQueue||this._pendingForceUpdate?this.updateComponent(t,this._currentElement,this._currentElement,this._context,this._context):this._updateBatchNumber=null},updateComponent:function(t,e,n,r,i){var o=this._instance;null==o?u(\"136\",this.getName()||\"ReactCompositeComponent\"):void 0;var a,c=!1;this._context===i?a=o.context:(a=this._processContext(i),c=!0);var s=e.props,l=n.props;e!==n&&(c=!0),c&&o.componentWillReceiveProps&&o.componentWillReceiveProps(l,a);var f=this._processPendingState(l,a),p=!0;this._pendingForceUpdate||(o.shouldComponentUpdate?p=o.shouldComponentUpdate(l,f,a):this._compositeType===_.PureClass&&(p=!m(s,l)||!m(o.state,f))),this._updateBatchNumber=null,p?(this._pendingForceUpdate=!1,this._performComponentUpdate(n,l,f,a,t,i)):(this._currentElement=n,this._context=i,o.props=l,o.state=f,o.context=a)},_processPendingState:function(t,e){var n=this._instance,r=this._pendingStateQueue,i=this._pendingReplaceState;if(this._pendingReplaceState=!1,this._pendingStateQueue=null,!r)return n.state;if(i&&1===r.length)return r[0];for(var o=c({},i?r[0]:n.state),a=i?1:0;a<r.length;a++){var u=r[a];c(o,\"function\"==typeof u?u.call(n,o,t,e):u)}return o},_performComponentUpdate:function(t,e,n,r,i,o){var a,u,c,s=this._instance,l=Boolean(s.componentDidUpdate);l&&(a=s.props,u=s.state,c=s.context),s.componentWillUpdate&&s.componentWillUpdate(e,n,r),this._currentElement=t,this._context=o,s.props=e,s.state=n,s.context=r,this._updateRenderedComponent(i,o),l&&i.getReactMountReady().enqueue(s.componentDidUpdate.bind(s,a,u,c),s)},_updateRenderedComponent:function(t,e){var n=this._renderedComponent,r=n._currentElement,i=this._renderValidatedComponent(),o=0;if(y(r,i))v.receiveComponent(n,i,t,this._processChildContext(e));else{var a=v.getHostNode(n);v.unmountComponent(n,!1);var u=d.getType(i);this._renderedNodeType=u;var c=this._instantiateReactComponent(i,u!==d.EMPTY);this._renderedComponent=c;var s=v.mountComponent(c,t,this._hostParent,this._hostContainerInfo,this._processChildContext(e),o);this._replaceNodeWithMarkup(a,s,n)}},_replaceNodeWithMarkup:function(t,e,n){l.replaceNodeWithMarkup(t,e,n)},_renderValidatedComponentWithoutOwnerOrContext:function(){var t,e=this._instance;return t=e.render()},_renderValidatedComponent:function(){var t;if(this._compositeType!==_.StatelessFunctional){f.current=this;try{t=this._renderValidatedComponentWithoutOwnerOrContext()}finally{f.current=null}}else t=this._renderValidatedComponentWithoutOwnerOrContext();return null===t||t===!1||s.isValidElement(t)?void 0:u(\"109\",this.getName()||\"ReactCompositeComponent\"),t},attachRef:function(t,e){var n=this.getPublicInstance();null==n?u(\"110\"):void 0;var r=e.getPublicInstance(),i=n.refs===g?n.refs={}:n.refs;i[t]=r},detachRef:function(t){var e=this.getPublicInstance().refs;delete e[t]},getName:function(){var t=this._currentElement.type,e=this._instance&&this._instance.constructor;return t.displayName||e&&e.displayName||t.name||e&&e.name||null},getPublicInstance:function(){var t=this._instance;return this._compositeType===_.StatelessFunctional?null:t},_instantiateReactComponent:null};t.exports=x},function(t,e,n){\"use strict\";var r=n(4),i=n(358),o=n(163),a=n(24),u=n(11),c=n(371),s=n(387),l=n(167),f=n(395);n(1);i.inject();var p={findDOMNode:s,render:o.render,unmountComponentAtNode:o.unmountComponentAtNode,version:c,unstable_batchedUpdates:u.batchedUpdates,unstable_renderSubtreeIntoContainer:f};\"undefined\"!=typeof __REACT_DEVTOOLS_GLOBAL_HOOK__&&\"function\"==typeof __REACT_DEVTOOLS_GLOBAL_HOOK__.inject&&__REACT_DEVTOOLS_GLOBAL_HOOK__.inject({ComponentTree:{getClosestInstanceFromNode:r.getClosestInstanceFromNode,getNodeFromInstance:function(t){return t._renderedComponent&&(t=l(t)),t?r.getNodeFromInstance(t):null}},Mount:o,Reconciler:a});t.exports=p},function(t,e,n){\"use strict\";function r(t){if(t){var e=t._currentElement._owner||null;if(e){var n=e.getName();if(n)return\" This DOM node was rendered by `\"+n+\"`.\"}}return\"\"}function i(t,e){e&&(G[t._tag]&&(null!=e.children||null!=e.dangerouslySetInnerHTML?v(\"137\",t._tag,t._currentElement._owner?\" Check the render method of \"+t._currentElement._owner.getName()+\".\":\"\"):void 0),null!=e.dangerouslySetInnerHTML&&(null!=e.children?v(\"60\"):void 0,\"object\"==typeof e.dangerouslySetInnerHTML&&V in e.dangerouslySetInnerHTML?void 0:v(\"61\")),null!=e.style&&\"object\"!=typeof e.style?v(\"62\",r(t)):void 0)}function o(t,e,n,r){if(!(r instanceof I)){var i=t._hostContainerInfo,o=i._node&&i._node.nodeType===H,u=o?i._node:i._ownerDocument;F(e,u),r.getReactMountReady().enqueue(a,{inst:t,registrationName:e,listener:n})}}function a(){var t=this;C.putListener(t.inst,t.registrationName,t.listener)}function u(){var t=this;S.postMountWrapper(t)}function c(){var t=this;A.postMountWrapper(t)}function s(){var t=this;P.postMountWrapper(t)}function l(){var t=this;t._rootNodeID?void 0:v(\"63\");var e=U(t);switch(e?void 0:v(\"64\"),t._tag){case\"iframe\":case\"object\":t._wrapperState.listeners=[k.trapBubbledEvent(\"topLoad\",\"load\",e)];break;case\"video\":case\"audio\":t._wrapperState.listeners=[];for(var n in q)q.hasOwnProperty(n)&&t._wrapperState.listeners.push(k.trapBubbledEvent(n,q[n],e));break;case\"source\":t._wrapperState.listeners=[k.trapBubbledEvent(\"topError\",\"error\",e)];break;case\"img\":t._wrapperState.listeners=[k.trapBubbledEvent(\"topError\",\"error\",e),k.trapBubbledEvent(\"topLoad\",\"load\",e)];break;case\"form\":t._wrapperState.listeners=[k.trapBubbledEvent(\"topReset\",\"reset\",e),k.trapBubbledEvent(\"topSubmit\",\"submit\",e)];break;case\"input\":case\"select\":case\"textarea\":t._wrapperState.listeners=[k.trapBubbledEvent(\"topInvalid\",\"invalid\",e)]}}function f(){N.postUpdateWrapper(this)}function p(t){Z.call(X,t)||($.test(t)?void 0:v(\"65\",t),X[t]=!0)}function h(t,e){return t.indexOf(\"-\")>=0||null!=e.is}function d(t){var e=t.type;p(e),this._currentElement=t,this._tag=e.toLowerCase(),this._namespaceURI=null,this._renderedChildren=null,this._previousStyle=null,this._previousStyleCopy=null,this._hostNode=null,this._hostParent=null,this._rootNodeID=0,this._domID=0,this._hostContainerInfo=null,this._wrapperState=null,this._topLevelWrapper=null,this._flags=0}var v=n(2),g=n(3),m=n(332),y=n(334),_=n(20),b=n(82),x=n(21),w=n(156),C=n(22),M=n(83),k=n(51),E=n(157),T=n(4),S=n(351),P=n(352),N=n(158),A=n(355),O=(n(9),n(364)),I=n(369),D=(n(8),n(54)),R=(n(0),n(94),n(80),n(96),n(1),E),L=C.deleteListener,U=T.getNodeFromInstance,F=k.listenTo,j=M.registrationNameModules,B={string:!0,number:!0},W=\"style\",V=\"__html\",z={children:null,dangerouslySetInnerHTML:null,suppressContentEditableWarning:null},H=11,q={topAbort:\"abort\",topCanPlay:\"canplay\",topCanPlayThrough:\"canplaythrough\",topDurationChange:\"durationchange\",topEmptied:\"emptied\",topEncrypted:\"encrypted\",topEnded:\"ended\",topError:\"error\",topLoadedData:\"loadeddata\",topLoadedMetadata:\"loadedmetadata\",topLoadStart:\"loadstart\",topPause:\"pause\",topPlay:\"play\",topPlaying:\"playing\",topProgress:\"progress\",topRateChange:\"ratechange\",topSeeked:\"seeked\",topSeeking:\"seeking\",topStalled:\"stalled\",topSuspend:\"suspend\",topTimeUpdate:\"timeupdate\",topVolumeChange:\"volumechange\",topWaiting:\"waiting\"},Y={area:!0,base:!0,br:!0,col:!0,embed:!0,hr:!0,img:!0,input:!0,keygen:!0,link:!0,meta:!0,param:!0,source:!0,track:!0,wbr:!0},K={listing:!0,pre:!0,textarea:!0},G=g({menuitem:!0},Y),$=/^[a-zA-Z][a-zA-Z:_\\.\\-\\d]*$/,X={},Z={}.hasOwnProperty,Q=1;d.displayName=\"ReactDOMComponent\",d.Mixin={mountComponent:function(t,e,n,r){this._rootNodeID=Q++,this._domID=n._idCounter++,this._hostParent=e,this._hostContainerInfo=n;var o=this._currentElement.props;switch(this._tag){case\"audio\":case\"form\":case\"iframe\":case\"img\":case\"link\":case\"object\":case\"source\":case\"video\":this._wrapperState={listeners:null},t.getReactMountReady().enqueue(l,this);break;case\"input\":S.mountWrapper(this,o,e),o=S.getHostProps(this,o),t.getReactMountReady().enqueue(l,this);break;case\"option\":P.mountWrapper(this,o,e),o=P.getHostProps(this,o);break;case\"select\":N.mountWrapper(this,o,e),o=N.getHostProps(this,o),t.getReactMountReady().enqueue(l,this);break;case\"textarea\":A.mountWrapper(this,o,e),o=A.getHostProps(this,o),t.getReactMountReady().enqueue(l,this)}i(this,o);var a,f;null!=e?(a=e._namespaceURI,f=e._tag):n._tag&&(a=n._namespaceURI,f=n._tag),(null==a||a===b.svg&&\"foreignobject\"===f)&&(a=b.html),a===b.html&&(\"svg\"===this._tag?a=b.svg:\"math\"===this._tag&&(a=b.mathml)),this._namespaceURI=a;var p;if(t.useCreateElement){var h,d=n._ownerDocument;if(a===b.html)if(\"script\"===this._tag){var v=d.createElement(\"div\"),g=this._currentElement.type;v.innerHTML=\"<\"+g+\"></\"+g+\">\",h=v.removeChild(v.firstChild)}else h=o.is?d.createElement(this._currentElement.type,o.is):d.createElement(this._currentElement.type);else h=d.createElementNS(a,this._currentElement.type);T.precacheNode(this,h),this._flags|=R.hasCachedChildNodes,this._hostParent||w.setAttributeForRoot(h),this._updateDOMProperties(null,o,t);var y=_(h);this._createInitialChildren(t,o,r,y),p=y}else{var x=this._createOpenTagMarkupAndPutListeners(t,o),C=this._createContentMarkup(t,o,r);p=!C&&Y[this._tag]?x+\"/>\":x+\">\"+C+\"</\"+this._currentElement.type+\">\"}switch(this._tag){case\"input\":t.getReactMountReady().enqueue(u,this),o.autoFocus&&t.getReactMountReady().enqueue(m.focusDOMComponent,this);break;case\"textarea\":t.getReactMountReady().enqueue(c,this),o.autoFocus&&t.getReactMountReady().enqueue(m.focusDOMComponent,this);break;case\"select\":o.autoFocus&&t.getReactMountReady().enqueue(m.focusDOMComponent,this);break;case\"button\":o.autoFocus&&t.getReactMountReady().enqueue(m.focusDOMComponent,this);break;case\"option\":t.getReactMountReady().enqueue(s,this)}return p},_createOpenTagMarkupAndPutListeners:function(t,e){var n=\"<\"+this._currentElement.type;for(var r in e)if(e.hasOwnProperty(r)){var i=e[r];if(null!=i)if(j.hasOwnProperty(r))i&&o(this,r,i,t);else{r===W&&(i&&(i=this._previousStyleCopy=g({},e.style)),i=y.createMarkupForStyles(i,this));var a=null;null!=this._tag&&h(this._tag,e)?z.hasOwnProperty(r)||(a=w.createMarkupForCustomAttribute(r,i)):a=w.createMarkupForProperty(r,i),a&&(n+=\" \"+a)}}return t.renderToStaticMarkup?n:(this._hostParent||(n+=\" \"+w.createMarkupForRoot()),n+=\" \"+w.createMarkupForID(this._domID))},_createContentMarkup:function(t,e,n){var r=\"\",i=e.dangerouslySetInnerHTML;if(null!=i)null!=i.__html&&(r=i.__html);else{var o=B[typeof e.children]?e.children:null,a=null!=o?null:e.children;if(null!=o)r=D(o);else if(null!=a){var u=this.mountChildren(a,t,n);r=u.join(\"\")}}return K[this._tag]&&\"\\n\"===r.charAt(0)?\"\\n\"+r:r},_createInitialChildren:function(t,e,n,r){var i=e.dangerouslySetInnerHTML;if(null!=i)null!=i.__html&&_.queueHTML(r,i.__html);else{var o=B[typeof e.children]?e.children:null,a=null!=o?null:e.children;if(null!=o)\"\"!==o&&_.queueText(r,o);else if(null!=a)for(var u=this.mountChildren(a,t,n),c=0;c<u.length;c++)_.queueChild(r,u[c])}},receiveComponent:function(t,e,n){var r=this._currentElement;this._currentElement=t,this.updateComponent(e,r,t,n)},updateComponent:function(t,e,n,r){var o=e.props,a=this._currentElement.props;switch(this._tag){case\"input\":o=S.getHostProps(this,o),a=S.getHostProps(this,a);break;case\"option\":o=P.getHostProps(this,o),a=P.getHostProps(this,a);break;case\"select\":o=N.getHostProps(this,o),a=N.getHostProps(this,a);break;case\"textarea\":o=A.getHostProps(this,o),a=A.getHostProps(this,a)}switch(i(this,a),this._updateDOMProperties(o,a,t),this._updateDOMChildren(o,a,t,r),this._tag){case\"input\":S.updateWrapper(this);break;case\"textarea\":A.updateWrapper(this);break;case\"select\":t.getReactMountReady().enqueue(f,this)}},_updateDOMProperties:function(t,e,n){var r,i,a;for(r in t)if(!e.hasOwnProperty(r)&&t.hasOwnProperty(r)&&null!=t[r])if(r===W){var u=this._previousStyleCopy;for(i in u)u.hasOwnProperty(i)&&(a=a||{},a[i]=\"\");this._previousStyleCopy=null}else j.hasOwnProperty(r)?t[r]&&L(this,r):h(this._tag,t)?z.hasOwnProperty(r)||w.deleteValueForAttribute(U(this),r):(x.properties[r]||x.isCustomAttribute(r))&&w.deleteValueForProperty(U(this),r);for(r in e){var c=e[r],s=r===W?this._previousStyleCopy:null!=t?t[r]:void 0;if(e.hasOwnProperty(r)&&c!==s&&(null!=c||null!=s))if(r===W)if(c?c=this._previousStyleCopy=g({},c):this._previousStyleCopy=null,s){for(i in s)!s.hasOwnProperty(i)||c&&c.hasOwnProperty(i)||(a=a||{},a[i]=\"\");for(i in c)c.hasOwnProperty(i)&&s[i]!==c[i]&&(a=a||{},a[i]=c[i])}else a=c;else if(j.hasOwnProperty(r))c?o(this,r,c,n):s&&L(this,r);else if(h(this._tag,e))z.hasOwnProperty(r)||w.setValueForAttribute(U(this),r,c);else if(x.properties[r]||x.isCustomAttribute(r)){var l=U(this);null!=c?w.setValueForProperty(l,r,c):w.deleteValueForProperty(l,r)}}a&&y.setValueForStyles(U(this),a,this)},_updateDOMChildren:function(t,e,n,r){var i=B[typeof t.children]?t.children:null,o=B[typeof e.children]?e.children:null,a=t.dangerouslySetInnerHTML&&t.dangerouslySetInnerHTML.__html,u=e.dangerouslySetInnerHTML&&e.dangerouslySetInnerHTML.__html,c=null!=i?null:t.children,s=null!=o?null:e.children,l=null!=i||null!=a,f=null!=o||null!=u;null!=c&&null==s?this.updateChildren(null,n,r):l&&!f&&this.updateTextContent(\"\"),null!=o?i!==o&&this.updateTextContent(\"\"+o):null!=u?a!==u&&this.updateMarkup(\"\"+u):null!=s&&this.updateChildren(s,n,r)},getHostNode:function(){return U(this)},unmountComponent:function(t){switch(this._tag){case\"audio\":case\"form\":case\"iframe\":case\"img\":case\"link\":case\"object\":case\"source\":case\"video\":var e=this._wrapperState.listeners;if(e)for(var n=0;n<e.length;n++)e[n].remove();break;case\"html\":case\"head\":case\"body\":v(\"66\",this._tag)}this.unmountChildren(t),T.uncacheNode(this),C.deleteAllListeners(this),this._rootNodeID=0,this._domID=0,this._wrapperState=null},getPublicInstance:function(){return U(this)}},g(d.prototype,d.Mixin,O.Mixin),t.exports=d},function(t,e,n){\"use strict\";function r(t,e){var n={_topLevelWrapper:t,_idCounter:1,_ownerDocument:e?e.nodeType===i?e:e.ownerDocument:null,_node:e,_tag:e?e.nodeName.toLowerCase():null,_namespaceURI:e?e.namespaceURI:null};return n}var i=(n(96),9);t.exports=r},function(t,e,n){\"use strict\";var r=n(3),i=n(20),o=n(4),a=function(t){this._currentElement=null,this._hostNode=null,this._hostParent=null,this._hostContainerInfo=null,this._domID=0};r(a.prototype,{mountComponent:function(t,e,n,r){var a=n._idCounter++;this._domID=a,this._hostParent=e,this._hostContainerInfo=n;var u=\" react-empty: \"+this._domID+\" \";if(t.useCreateElement){var c=n._ownerDocument,s=c.createComment(u);return o.precacheNode(this,s),i(s)}return t.renderToStaticMarkup?\"\":\"<!--\"+u+\"-->\"},receiveComponent:function(){},getHostNode:function(){return o.getNodeFromInstance(this)},unmountComponent:function(){o.uncacheNode(this)}}),t.exports=a},function(t,e,n){\"use strict\";var r={useCreateElement:!0,useFiber:!1};t.exports=r},function(t,e,n){\"use strict\";var r=n(81),i=n(4),o={dangerouslyProcessChildrenUpdates:function(t,e){var n=i.getNodeFromInstance(t);r.processUpdates(n,e)}};t.exports=o},function(t,e,n){\"use strict\";function r(){this._rootNodeID&&f.updateWrapper(this)}function i(t){var e=this._currentElement.props,n=c.executeOnChange(e,t);l.asap(r,this);var i=e.name;if(\"radio\"===e.type&&null!=i){for(var a=s.getNodeFromInstance(this),u=a;u.parentNode;)u=u.parentNode;for(var f=u.querySelectorAll(\"input[name=\"+JSON.stringify(\"\"+i)+'][type=\"radio\"]'),p=0;p<f.length;p++){var h=f[p];if(h!==a&&h.form===a.form){var d=s.getInstanceFromNode(h);d?void 0:o(\"90\"),l.asap(r,d)}}}return n}var o=n(2),a=n(3),u=n(156),c=n(85),s=n(4),l=n(11),f=(n(0),n(1),{getHostProps:function(t,e){var n=c.getValue(e),r=c.getChecked(e),i=a({type:void 0,step:void 0,min:void 0,max:void 0},e,{defaultChecked:void 0,defaultValue:void 0,value:null!=n?n:t._wrapperState.initialValue,checked:null!=r?r:t._wrapperState.initialChecked,onChange:t._wrapperState.onChange});return i},mountWrapper:function(t,e){var n=e.defaultValue;t._wrapperState={initialChecked:null!=e.checked?e.checked:e.defaultChecked,initialValue:null!=e.value?e.value:n,listeners:null,onChange:i.bind(t)}},updateWrapper:function(t){var e=t._currentElement.props,n=e.checked;null!=n&&u.setValueForProperty(s.getNodeFromInstance(t),\"checked\",n||!1);var r=s.getNodeFromInstance(t),i=c.getValue(e);if(null!=i){var o=\"\"+i;o!==r.value&&(r.value=o)}else null==e.value&&null!=e.defaultValue&&r.defaultValue!==\"\"+e.defaultValue&&(r.defaultValue=\"\"+e.defaultValue),null==e.checked&&null!=e.defaultChecked&&(r.defaultChecked=!!e.defaultChecked)},postMountWrapper:function(t){var e=t._currentElement.props,n=s.getNodeFromInstance(t);switch(e.type){case\"submit\":case\"reset\":break;case\"color\":case\"date\":case\"datetime\":case\"datetime-local\":case\"month\":case\"time\":case\"week\":n.value=\"\",n.value=n.defaultValue;break;default:n.value=n.value}var r=n.name;\"\"!==r&&(n.name=\"\"),n.defaultChecked=!n.defaultChecked,n.defaultChecked=!n.defaultChecked,\"\"!==r&&(n.name=r)}});t.exports=f},function(t,e,n){\"use strict\";function r(t){var e=\"\";return o.Children.forEach(t,function(t){null!=t&&(\"string\"==typeof t||\"number\"==typeof t?e+=t:c||(c=!0))}),e}var i=n(3),o=n(26),a=n(4),u=n(158),c=(n(1),!1),s={mountWrapper:function(t,e,n){var i=null;if(null!=n){var o=n;\"optgroup\"===o._tag&&(o=o._hostParent),null!=o&&\"select\"===o._tag&&(i=u.getSelectValueContext(o))}var a=null;if(null!=i){var c;if(c=null!=e.value?e.value+\"\":r(e.children),a=!1,Array.isArray(i)){for(var s=0;s<i.length;s++)if(\"\"+i[s]===c){a=!0;break}}else a=\"\"+i===c}t._wrapperState={selected:a}},postMountWrapper:function(t){var e=t._currentElement.props;if(null!=e.value){var n=a.getNodeFromInstance(t);n.setAttribute(\"value\",e.value)}},getHostProps:function(t,e){var n=i({selected:void 0,children:void 0},e);null!=t._wrapperState.selected&&(n.selected=t._wrapperState.selected);var o=r(e.children);return o&&(n.children=o),n}};t.exports=s},function(t,e,n){\"use strict\";function r(t,e,n,r){return t===n&&e===r}function i(t){var e=document.selection,n=e.createRange(),r=n.text.length,i=n.duplicate();i.moveToElementText(t),i.setEndPoint(\"EndToStart\",n);var o=i.text.length,a=o+r;return{start:o,end:a}}function o(t){var e=window.getSelection&&window.getSelection();if(!e||0===e.rangeCount)return null;var n=e.anchorNode,i=e.anchorOffset,o=e.focusNode,a=e.focusOffset,u=e.getRangeAt(0);try{u.startContainer.nodeType,u.endContainer.nodeType}catch(t){return null}var c=r(e.anchorNode,e.anchorOffset,e.focusNode,e.focusOffset),s=c?0:u.toString().length,l=u.cloneRange();l.selectNodeContents(t),l.setEnd(u.startContainer,u.startOffset);var f=r(l.startContainer,l.startOffset,l.endContainer,l.endOffset),p=f?0:l.toString().length,h=p+s,d=document.createRange();d.setStart(n,i),d.setEnd(o,a);var v=d.collapsed;return{start:v?h:p,end:v?p:h}}function a(t,e){var n,r,i=document.selection.createRange().duplicate();void 0===e.end?(n=e.start,r=n):e.start>e.end?(n=e.end,r=e.start):(n=e.start,r=e.end),i.moveToElementText(t),i.moveStart(\"character\",n),i.setEndPoint(\"EndToStart\",i),i.moveEnd(\"character\",r-n),i.select()}function u(t,e){if(window.getSelection){var n=window.getSelection(),r=t[l()].length,i=Math.min(e.start,r),o=void 0===e.end?i:Math.min(e.end,r);if(!n.extend&&i>o){var a=o;o=i,i=a}var u=s(t,i),c=s(t,o);if(u&&c){var f=document.createRange();f.setStart(u.node,u.offset),n.removeAllRanges(),i>o?(n.addRange(f),n.extend(c.node,c.offset)):(f.setEnd(c.node,c.offset),n.addRange(f))}}}var c=n(6),s=n(392),l=n(168),f=c.canUseDOM&&\"selection\"in document&&!(\"getSelection\"in window),p={getOffsets:f?i:o,setOffsets:f?a:u};t.exports=p},function(t,e,n){\"use strict\";var r=n(2),i=n(3),o=n(81),a=n(20),u=n(4),c=n(54),s=(n(0),n(96),function(t){this._currentElement=t,this._stringText=\"\"+t,this._hostNode=null,this._hostParent=null,this._domID=0,this._mountIndex=0,this._closingComment=null,this._commentNodes=null});i(s.prototype,{mountComponent:function(t,e,n,r){var i=n._idCounter++,o=\" react-text: \"+i+\" \",s=\" /react-text \";if(this._domID=i,this._hostParent=e,t.useCreateElement){var l=n._ownerDocument,f=l.createComment(o),p=l.createComment(s),h=a(l.createDocumentFragment());return a.queueChild(h,a(f)),this._stringText&&a.queueChild(h,a(l.createTextNode(this._stringText))),a.queueChild(h,a(p)),u.precacheNode(this,f),this._closingComment=p,h}var d=c(this._stringText);return t.renderToStaticMarkup?d:\"<!--\"+o+\"-->\"+d+\"<!--\"+s+\"-->\"},receiveComponent:function(t,e){if(t!==this._currentElement){this._currentElement=t;var n=\"\"+t;if(n!==this._stringText){this._stringText=n;var r=this.getHostNode();o.replaceDelimitedText(r[0],r[1],n)}}},getHostNode:function(){var t=this._commentNodes;if(t)return t;if(!this._closingComment)for(var e=u.getNodeFromInstance(this),n=e.nextSibling;;){if(null==n?r(\"67\",this._domID):void 0,8===n.nodeType&&\" /react-text \"===n.nodeValue){this._closingComment=n;break}n=n.nextSibling}return t=[this._hostNode,this._closingComment],this._commentNodes=t,t},unmountComponent:function(){this._closingComment=null,this._commentNodes=null,u.uncacheNode(this)}}),t.exports=s},function(t,e,n){\"use strict\";function r(){this._rootNodeID&&l.updateWrapper(this)}function i(t){var e=this._currentElement.props,n=u.executeOnChange(e,t);return s.asap(r,this),n}var o=n(2),a=n(3),u=n(85),c=n(4),s=n(11),l=(n(0),n(1),{getHostProps:function(t,e){null!=e.dangerouslySetInnerHTML?o(\"91\"):void 0;var n=a({},e,{value:void 0,defaultValue:void 0,children:\"\"+t._wrapperState.initialValue,onChange:t._wrapperState.onChange});return n},mountWrapper:function(t,e){var n=u.getValue(e),r=n;if(null==n){var a=e.defaultValue,c=e.children;null!=c&&(null!=a?o(\"92\"):void 0,Array.isArray(c)&&(c.length<=1?void 0:o(\"93\"),c=c[0]),a=\"\"+c),null==a&&(a=\"\"),r=a}t._wrapperState={initialValue:\"\"+r,listeners:null,onChange:i.bind(t)}},updateWrapper:function(t){var e=t._currentElement.props,n=c.getNodeFromInstance(t),r=u.getValue(e);if(null!=r){var i=\"\"+r;i!==n.value&&(n.value=i),null==e.defaultValue&&(n.defaultValue=i)}null!=e.defaultValue&&(n.defaultValue=e.defaultValue)},postMountWrapper:function(t){var e=c.getNodeFromInstance(t),n=e.textContent;\n",
              "n===t._wrapperState.initialValue&&(e.value=n)}});t.exports=l},function(t,e,n){\"use strict\";function r(t,e){\"_hostNode\"in t?void 0:c(\"33\"),\"_hostNode\"in e?void 0:c(\"33\");for(var n=0,r=t;r;r=r._hostParent)n++;for(var i=0,o=e;o;o=o._hostParent)i++;for(;n-i>0;)t=t._hostParent,n--;for(;i-n>0;)e=e._hostParent,i--;for(var a=n;a--;){if(t===e)return t;t=t._hostParent,e=e._hostParent}return null}function i(t,e){\"_hostNode\"in t?void 0:c(\"35\"),\"_hostNode\"in e?void 0:c(\"35\");for(;e;){if(e===t)return!0;e=e._hostParent}return!1}function o(t){return\"_hostNode\"in t?void 0:c(\"36\"),t._hostParent}function a(t,e,n){for(var r=[];t;)r.push(t),t=t._hostParent;var i;for(i=r.length;i-- >0;)e(r[i],\"captured\",n);for(i=0;i<r.length;i++)e(r[i],\"bubbled\",n)}function u(t,e,n,i,o){for(var a=t&&e?r(t,e):null,u=[];t&&t!==a;)u.push(t),t=t._hostParent;for(var c=[];e&&e!==a;)c.push(e),e=e._hostParent;var s;for(s=0;s<u.length;s++)n(u[s],\"bubbled\",i);for(s=c.length;s-- 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r(){C||(C=!0,y.EventEmitter.injectReactEventListener(m),y.EventPluginHub.injectEventPluginOrder(u),y.EventPluginUtils.injectComponentTree(p),y.EventPluginUtils.injectTreeTraversal(d),y.EventPluginHub.injectEventPluginsByName({SimpleEventPlugin:w,EnterLeaveEventPlugin:c,ChangeEventPlugin:a,SelectEventPlugin:x,BeforeInputEventPlugin:o}),y.HostComponent.injectGenericComponentClass(f),y.HostComponent.injectTextComponentClass(v),y.DOMProperty.injectDOMPropertyConfig(i),y.DOMProperty.injectDOMPropertyConfig(s),y.DOMProperty.injectDOMPropertyConfig(b),y.EmptyComponent.injectEmptyComponentFactory(function(t){return new h(t)}),y.Updates.injectReconcileTransaction(_),y.Updates.injectBatchingStrategy(g),y.Component.injectEnvironment(l))}var i=n(331),o=n(333),a=n(335),u=n(337),c=n(338),s=n(341),l=n(343),f=n(346),p=n(4),h=n(348),d=n(356),v=n(354),g=n(357),m=n(361),y=n(362),_=n(367),b=n(372),x=n(373),w=n(374),C=!1;t.exports={inject:r}},function(t,e,n){\"use strict\";var r=\"function\"==typeof 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v={_enabled:!0,_handleTopLevel:null,WINDOW_HANDLE:s.canUseDOM?window:null,setHandleTopLevel:function(t){v._handleTopLevel=t},setEnabled:function(t){v._enabled=!!t},isEnabled:function(){return v._enabled},trapBubbledEvent:function(t,e,n){return n?c.listen(n,e,v.dispatchEvent.bind(null,t)):null},trapCapturedEvent:function(t,e,n){return n?c.capture(n,e,v.dispatchEvent.bind(null,t)):null},monitorScrollValue:function(t){var e=a.bind(null,t);c.listen(window,\"scroll\",e)},dispatchEvent:function(t,e){if(v._enabled){var n=i.getPooled(t,e);try{p.batchedUpdates(o,n)}finally{i.release(n)}}}};t.exports=v},function(t,e,n){\"use strict\";var r=n(21),i=n(22),o=n(50),a=n(86),u=n(159),c=n(51),s=n(161),l=n(11),f={Component:a.injection,DOMProperty:r.injection,EmptyComponent:u.injection,EventPluginHub:i.injection,EventPluginUtils:o.injection,EventEmitter:c.injection,HostComponent:s.injection,Updates:l.injection};t.exports=f},function(t,e,n){\"use strict\";var r=n(385),i=/\\/?>/,o=/^<\\!\\-\\-/,a={CHECKSUM_ATTR_NAME:\"data-react-checksum\",addChecksumToMarkup:function(t){var e=r(t);return o.test(t)?t:t.replace(i,\" \"+a.CHECKSUM_ATTR_NAME+'=\"'+e+'\"$&')},canReuseMarkup:function(t,e){var n=e.getAttribute(a.CHECKSUM_ATTR_NAME);n=n&&parseInt(n,10);var i=r(t);return i===n}};t.exports=a},function(t,e,n){\"use strict\";function r(t,e,n){return{type:\"INSERT_MARKUP\",content:t,fromIndex:null,fromNode:null,toIndex:n,afterNode:e}}function i(t,e,n){return{type:\"MOVE_EXISTING\",content:null,fromIndex:t._mountIndex,fromNode:p.getHostNode(t),toIndex:n,afterNode:e}}function o(t,e){return{type:\"REMOVE_NODE\",content:null,fromIndex:t._mountIndex,fromNode:e,toIndex:null,afterNode:null}}function a(t){return{type:\"SET_MARKUP\",content:t,fromIndex:null,fromNode:null,toIndex:null,afterNode:null}}function u(t){return{type:\"TEXT_CONTENT\",content:t,fromIndex:null,fromNode:null,toIndex:null,afterNode:null}}function c(t,e){return e&&(t=t||[],t.push(e)),t}function s(t,e){f.processChildrenUpdates(t,e)}var l=n(2),f=n(86),p=(n(40),n(9),n(15),n(24)),h=n(342),d=(n(8),n(388)),v=(n(0),{Mixin:{_reconcilerInstantiateChildren:function(t,e,n){return h.instantiateChildren(t,e,n)},_reconcilerUpdateChildren:function(t,e,n,r,i,o){var a,u=0;return a=d(e,u),h.updateChildren(t,a,n,r,i,this,this._hostContainerInfo,o,u),a},mountChildren:function(t,e,n){var r=this._reconcilerInstantiateChildren(t,e,n);this._renderedChildren=r;var i=[],o=0;for(var a in r)if(r.hasOwnProperty(a)){var u=r[a],c=0,s=p.mountComponent(u,e,this,this._hostContainerInfo,n,c);u._mountIndex=o++,i.push(s)}return i},updateTextContent:function(t){var e=this._renderedChildren;h.unmountChildren(e,!1);for(var n in e)e.hasOwnProperty(n)&&l(\"118\");var r=[u(t)];s(this,r)},updateMarkup:function(t){var e=this._renderedChildren;h.unmountChildren(e,!1);for(var n in e)e.hasOwnProperty(n)&&l(\"118\");var r=[a(t)];s(this,r)},updateChildren:function(t,e,n){this._updateChildren(t,e,n)},_updateChildren:function(t,e,n){var r=this._renderedChildren,i={},o=[],a=this._reconcilerUpdateChildren(r,t,o,i,e,n);if(a||r){var u,l=null,f=0,h=0,d=0,v=null;for(u in a)if(a.hasOwnProperty(u)){var g=r&&r[u],m=a[u];g===m?(l=c(l,this.moveChild(g,v,f,h)),h=Math.max(g._mountIndex,h),g._mountIndex=f):(g&&(h=Math.max(g._mountIndex,h)),l=c(l,this._mountChildAtIndex(m,o[d],v,f,e,n)),d++),f++,v=p.getHostNode(m)}for(u in i)i.hasOwnProperty(u)&&(l=c(l,this._unmountChild(r[u],i[u])));l&&s(this,l),this._renderedChildren=a}},unmountChildren:function(t){var e=this._renderedChildren;h.unmountChildren(e,t),this._renderedChildren=null},moveChild:function(t,e,n,r){if(t._mountIndex<r)return i(t,e,n)},createChild:function(t,e,n){return r(n,e,t._mountIndex)},removeChild:function(t,e){return o(t,e)},_mountChildAtIndex:function(t,e,n,r,i,o){return t._mountIndex=r,this.createChild(t,n,e)},_unmountChild:function(t,e){var n=this.removeChild(t,e);return t._mountIndex=null,n}}});t.exports=v},function(t,e,n){\"use strict\";function r(t){return!(!t||\"function\"!=typeof t.attachRef||\"function\"!=typeof t.detachRef)}var i=n(2),o=(n(0),{addComponentAsRefTo:function(t,e,n){r(n)?void 0:i(\"119\"),n.attachRef(e,t)},removeComponentAsRefFrom:function(t,e,n){r(n)?void 0:i(\"120\");var o=n.getPublicInstance();o&&o.refs[e]===t.getPublicInstance()&&n.detachRef(e)}});t.exports=o},function(t,e,n){\"use strict\";var r=\"SECRET_DO_NOT_PASS_THIS_OR_YOU_WILL_BE_FIRED\";t.exports=r},function(t,e,n){\"use strict\";function r(t){this.reinitializeTransaction(),this.renderToStaticMarkup=!1,this.reactMountReady=o.getPooled(null),this.useCreateElement=t}var i=n(3),o=n(155),a=n(17),u=n(51),c=n(162),s=(n(9),n(53)),l=n(88),f={initialize:c.getSelectionInformation,close:c.restoreSelection},p={initialize:function(){var t=u.isEnabled();return u.setEnabled(!1),t},close:function(t){u.setEnabled(t)}},h={initialize:function(){this.reactMountReady.reset()},close:function(){this.reactMountReady.notifyAll()}},d=[f,p,h],v={getTransactionWrappers:function(){return d},getReactMountReady:function(){return this.reactMountReady},getUpdateQueue:function(){return l},checkpoint:function(){return this.reactMountReady.checkpoint()},rollback:function(t){this.reactMountReady.rollback(t)},destructor:function(){o.release(this.reactMountReady),this.reactMountReady=null}};i(r.prototype,s,v),a.addPoolingTo(r),t.exports=r},function(t,e,n){\"use strict\";function r(t,e,n){\"function\"==typeof t?t(e.getPublicInstance()):o.addComponentAsRefTo(e,t,n)}function i(t,e,n){\"function\"==typeof t?t(null):o.removeComponentAsRefFrom(e,t,n)}var o=n(365),a={};a.attachRefs=function(t,e){if(null!==e&&\"object\"==typeof e){var n=e.ref;null!=n&&r(n,t,e._owner)}},a.shouldUpdateRefs=function(t,e){var n=null,r=null;null!==t&&\"object\"==typeof 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            "text/plain": [
              "<Figure size 1440x216 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Pour le 4ème match de la saison 2021 (Rennes-Lens), la prévision est une victoire à domicile. Les variables qui entrainent cette prédiction haute sont les variables en rouge, en particulier la moyenne de buts sur 5 matchs à domicile, alors que la note défensive de l'équipe adverse à l'effet de faire diminuer cette probabilité."
      ],
      "metadata": {
        "id": "q0Zz1mj-2QGF"
      },
      "id": "q0Zz1mj-2QGF"
    },
    {
      "cell_type": "code",
      "source": [
        "fig = plt.figure(figsize=(25,6))\n",
        "num_match_test = 80\n",
        "shap.force_plot(knn_explainer.expected_value,knn_shap_values[num_match_test,:], X_test_df.iloc[num_match_test,:].round(3), matplotlib=True,show=False)\n",
        "plt.savefig('shap_local_graph_80.png', dpi=300, bbox_inches='tight')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 291
        },
        "id": "hmYLCV0ZMF8g",
        "outputId": "02ce9d79-fab0-40fd-d1af-b88cbbf39232"
      },
      "id": "hmYLCV0ZMF8g",
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1800x432 with 0 Axes>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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IyCChQI3Iflq4cCHvf//7CQaDDBs2jMsuu4y1a9f2+Hc//OEPOfTQQ/H7/YwcOZKrr76aHTs6Zz7u2LGDa665hpEjR+L3+zn00EO5++67++uliIiIiIiIyCCj0ieRrnX5wbjvvvu47rrrADjkkENoaGggFAoxcuRI/vWvfzF69OguH+zrX/86t912GwDTpk1jy5YttLe3M2PGDFasWEFJSQmtra0cffTRrFq1imAwyPjx41mzZk3m72+99dbuxqvSJxERERERkSKgjBqRXopGo9x8880AfPjDH+a9997j3Xffpby8nPr6er71rW91+Xc7duxgwYIFAHzpS19i9erVLF++HGMMq1at4p577gHgZz/7GatWrcIYw/Lly1m9ejU33XQTAHfeeede2TciIiIiIiJSfBSoEemlV155hV27dgFOoAZg7NixnHDCCQAsWbKky7976qmniMVinf7uyCOPZOrUqZ3+bvHixYCTcXPkkUd2un8sFuPpp5/u89ckIiIiIiIig4sCNSK9tHnz5sz5kSNHZs6PGjUKgE2bNh3U36Xv19V9unt8ERERERERKR4K1IgcpAPt89Sbv1MPKRERERERkaFFgRqRXpowYULmfH19/V7nJ06ceFB/l75fV/fp7vFFRERERESkeChQI9JLxx57LMOHDwfgoYceAqCuro7ly5cDcN555wEwc+ZMZs6cyY9+9CMAzjrrLDweT6e/e+ONNzJTeqf/Ln26Zs0a3njjjU7393q9nHXWWf37AkVERERERCTvND23SNe6/GD8/Oc/54YbbgA6T89dU1PDv/71L8aOHYsxzkzZ3/jGN/jmN78JwC233MIdd9wBwPTp09m8eTPt7e1MmzaN119/ndLSUlpaWnj/+9/PmjVrCAaDTJgwgdWrV2f+/vbbb+9uvJqeW0REREREpAgoo0ZkP3zqU5/it7/9LbNnz6aurg5jDB/60IdYtmwZY8eO3eff3X777dx1113MnDmT9evXU1payhVXXMHSpUspLS0FoKysjKVLl3LllVdSWlrK+vXrmTFjBt///ve57bbbBuolioiIiIgUvHA4bMPhsLISpCApo0aka4X2wVBGjYiIiIhISjpIU15erv1kKTjKqBERERERERERGSQUqBERERERERERGSQUqBERERERERERGSQUqBERERERERERGSQUqBERERERERERGSQUqBERERERERERGSQUqBHp2o58D2A/FNJYRUREREREpBsK1BQgY8wwY8zfjDFrUqfVXdxntjHmJWPM28aYN4wxH8vHWAvYaMAcyD9jzPnGmNXGmHXGmK+krw+Hw4TDYYwxAWPMH1O3/8MYc8iBPlfq3+j+fzuKkzHmPGPMKmPMWmPMzV3cfpMx5p3UZ+hpY0xtPsYpPS+rnPt92BhjjTHHDOT4JKs3y8oY89HUZ+ttY8zvBnqM0qvt30RjzLPGmNdT28AL8jFOAWPML40x9caYt/ZxuzHG3J1alm8YY94/0GOUXi2nT6SWz5vGmBeNMe8b6DGKo6dllXO/Y40xcWPMZQM1NumsN8vKGHOGMeafqX2KpQM5vv6kQE1huhl42lo7DXg6dXlPbcAV1trDgPOAu4wxVQM4xiHJGOMGfgycDxwK/Jsx5tA97nYt0GitnQp8H1gwsKMU6PWyeh04xlp7JPAg8O2BHaVAr5cVxphy4AvAywM7QknrzbIyxkwDvgKcnPqO+uKAD3SI6+Vn6mvAH621RwHzgJ8M7CglxwM4+3L7cj4wLfXvU8BPB2BMsrcH6H45rQdOt9YeAfw/4OcDMSjp0gN0v6zS28kFwJMDMSDZpwfoZlmljm9/Alyc2qf4yACNq98pUFOYLgF+lTr/K+CDe97BWrvaWrsmdb4OqAdGDNgIh67jgLXW2vestVFgIc7yypW7/B4EzjLGmAEcozh6XFbW2mettW2pi8uB8QM8RnH05nMFzo7vAiAykIOTTnqzrK4HfmytbQSw1tYP8Bild8vJAhWp85VA3QCOT3JYa58Hdndzl0uAX1vHcqDKGDNmYEYnaT0tJ2vti+ntHtqnyKtefKYA/gN4COcYSvKkF8vq48DD1tpNqfsXzfJSoKYwjbLWbkud3w6M6u7OxpjjAB+wrr8HJowDNudc3pK6rsv7WGvjQDMwfEBGJ7l6s6xyXQss7tcRyb70uKxSqf4TrLWPD+TAZC+9+VxNB6YbY5YZY5YbY7r9VVP6RW+W0zeBy40xW4C/4hy0yOC0v99nkn/apxjEjDHjgA+h7LRCMB2oNsY8Z4x5zRhzRb4H1Fc8+R6AdM0Y8xRd9x75au4Fa601xthuHmcM8BvgSmttsm9HKTI0GGMuB44BTs/3WGRvxhgX8D3gqjwPRXrHg1OicQbOL8rPG2OOsNY25XVUsqd/Ax6w1n7XGHMi8BtjzOHalxA5OMaYM3ECNafkeyyyT3cB8621SSW9D3oe4GjgLCAIvGSMWW6tXZ3fYR08BWoGKWvt2fu6zRizwxgzxlq7LRWI6TLFyxhTATwOfDWVCiv9byswIefy+NR1Xd1nizHGg5NS3jAww5McvVlWGGPOxgmQnm6t7RigsUlnPS2rcuBw4LnUDtVoYJEx5mJr7asDNkqB3n2utgAvW2tjwHpjzGqcwM0rAzNEoXfL6VpSfQGstS8ZYwJADSoDGIx69X0m+WeMORL4BXC+tVb7foPXMcDC1D5FDXCBMSZurX00v8OSLmwBGqy1rUCrMeZ54H1AwQdqVPpUmBYBV6bOXwk8tucdjDE+4BGcmuUHB3BsQ90rwDRjzCGpZTAPZ3nlyl1+lwHPWGv3mRUl/abHZWWMOQr4GU6DMh2c5E+3y8pa22ytrbHWTrLWTsKp/VeQJj96sw18FCebBmNMDU7a8nsDOUjp1XLahPMLJcaYWUAA2Dmgo5TeWgRckZr96QSgOadEXgYJY8xE4GHgk8Xwa38xs9YekrNP8SDwGQVpBq3HgFOMMR5jTAlwPPBunsfUJ5RRU5juBP5ojLkW2Ah8FMA409F+2lp7Xeq604DhxpirUn93lbX2n3kY75BhrY0bYz4HPAG4gV9aa982xtwaCoXSd7sPJ4V8LU5zrHn5Ge3Q1t2yAl611i4CvgOUAX9K/aqyyVp7cd4GPUT1clnJINDLZfUE8AFjzDtAAvgv/bI8sHq5nL4E3GuMuRGnsfBV+lEhP4wxv8cJbtakegZ9A/ACWGvvwekhdAGwFmfWz6vzM9KhrRfL6b9xehL+JLVPEbfWHpOf0Q5tvVhWMkj0tKyste8aY5YAbwBJ4BfW2m6nXS8URt+5IgMjHA5bgPLychW7ioiIiIj0I+17SyFT6ZOIiIiIiIiIyCChQI2IiIiIiIiIyCChQI2IiIiIiIiIyCChQI2IiIiIiIiIyCChQI2IiIiIiIiIyCChQE0RMMZ8Kt9jECkm+kwVDi2rwqFlVTi0rAqDllPh0LIqHFpWhaPYl5UCNcWhqFdSkTzQZ6pwaFkVDi2rwqFlVRi0nAqHllXh0LIqHEW9rBSoEREREREREREZJIy1dp83nnfeeXbXrl0DOBw5EDt37mTEiBH5Hob0IJlMAuByKT462OkzVTi0rAqHllXh0LIqDFpOhUPLKj8OZN9by6pwFMOyeu21156w1p7X1W3dBmqAbm8Ukd4Lh8MAlJeX53kkIiIiIiLFTfveUgDMvm7QT/siIiIiIiIiIoOEAjUiIiIiIiIiIoOEAjUiIiIiIiIiIoOEAjUiIiIiIiIiIoOEJ98DEBEREREREelLaiIshUwZNSIiIiIiIiIig4QCNSIiIiIiIiIig4QCNSIiIiIiIiIig4QCNSIiIiIiIiIig4QCNVKY4gmIxvM9CpGCZ62lI27zPQwpUlq35GBFE5ak1XokWUlriSa0TgxFsYQlkSzuZa/vTUnTrE9SWNqjsKke6nbDGxvg6TfyPaLe+78vAPDxhbvyPBCRrEnVHuYdWUpdKM7zGzrY0KgAqPSNEaUurj2mnPqWBH/fGGH1Lq1bsv8uO7yE8RUe/rktyitbOmiN6SBmqDtilJfzZwTZ1OR8b9WFEvkekgyQc6cFOGyUj7d3xFi+OUJzpLi2B8NLXFx/bDnRhGXqcA9VQeVUDGUK1Ehh6YjCzhB4PTBrAnzrQSd4U0CWbSys8UpxO3NyAICxFR5KvFGtn9JnPntCGQAjy9yMKHVz/2tteR6RFJox5W6mDvcCcNwEH798rYVt4WSeRyX59pHDS3AZw6RqL8+916HvrSGi1Gf44kkV+NyGo8b6+MMbbbxdH8v3sPrUp49zvjd9bkNTe1KBmiFOS18KS2UpBH3O+RI/nP2+/I5HpICNKnNx7Hhf5vLjKyN5HI0UkzKfyQQBAf6ysj2Po5FCdeGM7Dr02taogjTCrBEepqSCdx1xy5Nr9b01VJwzNUDAawBYvztedEGaEq9hzpTsNq+mVIfpQ53WACksxsDYYdnLFx0LJn/DESlkF84I4jLOB+i1rVHqwkofl75xzrQAfo+zbq1riPFOvcqeZP8EPYazp2YPWv78roJ9AnNnBjPnl66PEO4ortIX6ZrLOPssacUY/D97aoBgKhAV8DgZRDK0KVAjhWdkFbhTq+74Gnj/lPyOR6QABTzOwXSaDoKkr+y5Q/3nItyhlv535hQ/pT7nu35Lc5x/biuuX89l/w0Lujip1p+5rG3L0HH0OB+jy90AhDqSLF1fXJlUhs7fm8NL3RijQM1Qp0CNFB63C0ZVZS9fdFz+xiJSoM6YHKAsdRC0NRRnRZ1q/KVvHDfex6iy1A51JMkLGzryPCIpRHP3+PVceRNy/owAHpdz8PrWjigbGpUFOlRclJNJ9eSaCB1FtuiPHudjbIXzvek2UB1QkEYUqJFCNSan/Om4aZ3LoUSkR7k7PY+vjOggSPpMbmnCkjURokW2Qy39b/YYLxOqnPku2qJJnlmnYN9Q53HBudNyMvWUBTpkjK90c9RYp59eImn566riW/a535vVJS5cLgVqRIEaKVRBH1SXZS/PPSZ/YxEpMEeO9jIxfRAUS/L0uuJKIZb8mVjl5n1jsjvUi4twh1r6X24g+al1EdrjCiUPdadO8lOdmgFnZ2uC5ZuVBTpU5GbXvbw5ys7W4moqPq7CzdHjshM71JTo8FwcWhOkcOVm0ZwzOzsblIh0K/cg6Jl1HbTFdBAkfSN3h/qlTVF2tRXXDrX0v9FlLo7JmY3uL5qNTuj8vfXXVe0k9bU1JOw5E1IxNhG+MGfdrvAbfB5l04hDgRopXFU5U3WXBuCsI/M7HpECMKrMxXETcqfkLr6dHsmPUk3JLX3gwpnZ2ehe3dLBNs1GN+TNqPEwrcaZkjuasDy5RsG7oSJ3JqQNjXHe3FFcTcWDXsNZU7INsodrSm7JobVBCpcxnXvVzNVU3SI9uSBnSu4VdVG2hHQQJH3jnKkBAqkd6vd2x3m7vrh2qKX/BTx0npJbwT5h7ym5Q5qSe0jYcyakYgz+nz0lQInXORz3e6BMU3JLDgVqpLCNrMxO1T1xBMyenN/xiAxifg98IOcg6C9qxih9xGX2nqVHZH+ducdsdK/XKdg31FUHXZwyKZtxoFK4oSN3JqSWjiTPFeGU3HNnZvfJakpcmpJbOlGgRgqbx+0Ea9LUVFhkn06dFKDM72z261sSvKYpuaWPHDXWx6hyZ4e6NZpkaZHtUMvAOD8n2Ld4lWajEydTLz0l98qdMd7bHc/ziGSgXDAjG8R4el2EjiJb9O8b42VshTOxg8tAVVCH5dKZ1ggpfO05B5tbGvI3DpFBri6U3cupDLgoVYqt9JFtOSV0Qa/JzM4isj/qctaj9C/pMrTlrhOjytx4tGkZMrYW+fZgWzhB0jrh6KSFuHrvyx60uZPC1tYBTa3O+UQSHn81v+MRGcTeqY+zbrdTSuD3GM7JKYMSORh14QSvbXWC5i5jOvUVEOmt3JK5OZMDCiYLL23qYFerc8BeHXRxcq2/h7+QYvH4yvZMIOPY8X7GlBdXsGZHS5JXtmR/bN5VZNOOy8FToEYK27bd2fPLV0F9c/7GIlIA/pzTl8ZpLJzHwUhRyV23zpkWIODJ42CkIL21I8b6VGlLwGs4e4qCyUNdwsLi1dlSytzGwmcFFjQAACAASURBVFLctrckMz8AAFw4o/i2B7kN0xvbkyQ077zkUKBGClc8ATuaspf//Er+xiJSIF7Y0EEo4vxqM6rMzXHjfT38hUjvrKiLsjVVXlfmc3HG5OLbqZb+l5tVM3emgskCT6xpJ5ZwDmBnjvAybbiiwENF7g8AZ08NEPQU1wbhX9tibGpyvjeT1gnWiKQpUCOFa0eTs1UD2LAD3tiQ1+GIFIJoApas0a+T0vcs8HjOjCxzVf4kB8CZftk5WBld7ubocQomD3XNEcvzGzoyly/S99aQ8c9tMbY0O4GMUp+LM6cUX+lbbnB6V2sSa5VVIw4FaqQwWdu57GmRsmlEemvxqvZMeu37xviYWFVcdd+SP0+ti9AWcw6ya6s9HDnam+cRSaHpSMCTOcFkHZQLdD6YPWWSn6pAcWVWSNcse2TZFeEPAM++F6El6nxvRhPQElWgRhwK1EhhamyBiNMUlXA7PPtmfscjUkB2tSVZvjlb912MOz6SH+0xyzPr9Mu3HJy/5gSTjxrrY3ylgslD3dqGOO/WO/t9XrfhvOnatgwVz6zroC0VyJhQ5WH2mOL6ASASh6fXZoPTaiosaQrUSGGqy8mmeeJ16IjlbywiBSi37vtMza4ifejxnF8/jx3vY1SZdjVk/+xsTfKygsmyh9zMivOmBzRV9xDRHrc8ta64s+weX5Wd4SrcYemIK6tGFKiRQpQ7JXfSakpukQPwdn3n2VU0Vbf0lS2hBCvqnINst8twgQ6y5QB0mqp7SoASr4LJQ92LmzpoaHOm6h5e4uakicXXr0S69pec/mfHFOEPANvCnWe4alBWjaBAjRSi3N40L6/qPPOTiPRa7rSQF2qqbulDnabqnhrAr8oV2U9v7oixodEJJge9hrMVTB7y4klYoqm6h6Rt4QSvbnHKal3GcGER/gCQ+725W1N1CwrUSKGJJ6C+OXtZTYRFDties6sco9lVpI+8tjVKXcj55bvc7+J0TdUtB+AvewSTFUuWJauzU3XPGullqqbqHjJys2rOmRYgUGSLPneGK03VLaBAjRSaXSEItUEsDhvr4V/r8z0ikYIVzZldJRRJctokBWqkb1ichrAA4Y4kJ0/UuiX777n1EVo6kkTiloqAYepwpWYNdU0Ry99zpuo+/RCVPw0VK+qibA05gYwyn4uji+zHpT1nuGpqV0bNUGd6mKtda4gMrHgCmtuguRVC7dDUAg1h2BWGhpBzW9LC5JFQ4u+cXTPIhT99DgAPaIIqGUT8Hpg63Mujb7fT0JYg6DWUeA2lPhclXkOJz+Bz63ds2X9uFxwxysej77RR35IgYcHnNnjd4HMZvOnzOafp8y6jdU4ctVVu6kIJXquL0hG3JK3Bbei07njdBq8LvG4XPjf43OBxGzwu8Lic2zyu7GWPy1k/jdazguR3G4YFXbTFLM0dyjoYSir8LvweQ7gjQSSe79H0PQOMKXdT5nMxa5RH34VDwz4XsgI1MnCsdabUDrU5/5panX87Q7A77ARkWiPg94LPA16Pcxr0QanfCcwE/c7eVSGaOob37nmO9Z/+UL5HItKlWMIS7rCEOpKEIklCqfMGqAi4qPCb1KmLcr/Bo6Y2sh/iSWcmi464JRInder868g57UiAxwV+jyHgMc6p27nc6TqPwefWwfZQY60lnnT6lcSSlnjCWbfS52NJ5/aktSSswVpLIun8xpNIWhKp06Q1+D3Z9SzodU7T54MeQzAVqHb+pdZBt8GXWvd8qWCQ1kERETlA+/wCKbLqPskra6Elks2GaW51gi8NqWyYxlanZMnvdf553eD3OQGYYeUwoQYCPijWHR5jMAZcBRpnkuLndxn8XkNNzmwK1joH1engze72JOsb47R0WIJeQ0XAUOF3UZkK5JT4jH4Bki75XM4BbnkP97PWEk3QKXjjnEK4LdkpuBNPOllhgS6COM5p9kBcgcViYXC7wZ86f6CSqYBPLJEO/FhiCWiJJWmKOJfjSUgknXUyYSFhIZmEhE3fZnEZg98Nfo8LvxcnwOMxBLw5QR9vbsDHCRA5p9mAj1vrp4iI5FCgRnovnnACMKFUaVJzm9MzpiEEjS1OdozLBT6vk3fs80LQC6UBmDgCZo53MmSG6kGccXYpFaeRgmIMpV4o9boZU5btD5G0lpaoJRRJ0hyxbG6K0xyxRBOWcn/n4E1lwElVFukVYwh6nAPeniSSlo5E5wydjrilpSPJrlYnuNMec64zhkzGhBPI6RzgSZ/3e1R6NRS4jMHjhsBBlnYmUgGdPTN6QpEkDUmIJ9JZPOksn2x2T9xCIuEEgNJZZOkAY8Djcj4HXhcBjzPzld/jygR5fG6Dz0NOho8TMFJ2j4hIcVCgRrI6YtkATLo/zK6wE4xpbIGWdif44vc6P2F6PU42TEkARlQ65z1q9LdP6Ywa7UNJEXAZQ1XAUBXoHHqMJZxyqeaIc7otbGmOJHEbp3yqMicDR+VTcrBcbqfXTVkPPSWttcSSe5ZbQSRu2d3uZOl0xJzrowkn4TOQkxWxZ3AnHdTxquxlyHOl+uQczJxU6YydWCKb2eOUc0FjeyKT+ZMb8EmmMnwSqWygRJJUH6jO62h6Pc5m+ThBoHT5ln+PLB+f1msRkUFBgZqhwlpo7chmw4TaYHeLE4TZ3eIEYiIxpx9MOhDj8zjZMCMrYNIIpz+MDqoOnAGDykKkuPk9hhEeFyNKs9dZa2mPW5ojTtBmV1uSdbsTtHQkKfE6GTeVARcVAUOl30Wpz+ggQfqWMbhdEPBAZQ93TdpsECe39KotZtndbonEsn12ktZmD4rTpS6dsnSyWTsqbZF9MgY3TpDlYNiccq5YTjlXPGFpiNrM5T0ze/YM+FjIZJcFUn15Mj18ckq69uzX488t51K5oYjIQVGgplgkkhBu76I/TDoQ0+rU3QR82Wa96Sa9tSNg1gQnOKODo/6TyqjRWyxDjTGGUp+h1AdjK3LKp5KWcNQJ3oQilo2NCZo7YkTjlvJU8KYqJwNH5VMyENzGUOKDEl/P61s8YYkknOBNJJOtA42RZCZDJx3s8bj3zsrpKmtHDZLlQBlj8LmcIMnBSKbKt6K55VwJJ3gZ7rCZ8q50YCjToDnVvyeW6u2TW26Yu953Lucyncq3MkGfzPUqRRSRoUmBmkIRjWdnSkpnxewKO7Ml7W5xgjQ+DwS8qfIkj5MBUxaEUVVOeZJXZUl5ZYzTo0b7GyKAUzJQHTRUBzuXT0UTTu+bpohzurU5RnOHxW1IZd/kZOH4lakg+ePzOAeYFf7u75dukJwJ5sScLLNI3CkRdAI9zu3xpO3UNycb0GGv4I4yFqQ/uNyp/j0HUc4FTvAmls7wySnnao0maWpPB3ScGbji1uYEezo3c/a4splp/pzPQ9Djcj4X7mz/nj2DPv6c8wqAikghUaBmMLAW2qPZbJimVqcUaXdLNhATiTpBmKAv26S3xA8jK+GQUc71hTpt9VCRyqbRfrVI9wIeQ6DMzciy7HXWOqUn6fKp+pYEa3bFaYk65VNVQSdwU+l3URk0lHpVPiWDiDEEXU4GQU8Syc7ZOenATrjDsrMlmXObM+NQurxqz8yc3OvUIFnyId2/h16s9/uSOx17NJEt34olnabhu9uyAZ30bFyZZs2p62NJp6ePz21yAjt7lHKlzufOxuXvIuCj6dhFZKAoUDMQkkkIRzr3h9kVhsYwNLQ4TXstTrAl4MuWJZUFYNJIOGyiE6TRF0NhU0aNyIEzhnK/odwP4yuz2YGJpHMA2xRJ0hxxpg5v2pYklrCZrJvKVNNjlU9JIUg3SC7vRZZOLMkeZVeW9phlV1v2vNMg2eJ371lqRbbvSM5BqxrJyqCS6i/lB0r7aDr2dKAnneUTilgaUn190mVciZzMnkQqUBRPWix7zhZH5nzutOzpxszp8q1sDx9Nxy4ivaNATV+IpcqSmtP/Wp0AzO6Q0xumuc0pO0o36g34nGyY8iCMrnYa9vq0KIqeMamsGn05i/QVj9tQXQLVJZ1LOzviTuZNc3r68OY4zZEkHhdO0CaY7oGj8ikpTMYY/C6n0rl3DZIt7TE6BXVao5aGtqRThpUqx7KWTLPYbE+RnObIOdfrcyOFwp0O+Bzk7nZmOvaEU87oZPg4QZ7d7UlirbnZPKkgT07wJ13+5TZ0LuXK9PFxEfRC0JMb6Okc8MnN+lGmnEjxUnSgJ9Y6syGls2Ga21JlSeFseVJ7qiwpkMqICXid4MuoapgyxgnKqCxJQBk1IgMk6DUEvW5Gl2cDONZaWmOW5nan/82OcIJVO2O0dFjK/Nmsm6qAoTLoUvmUFA2XMXhSDb17EkvYvXvpxCyN7emATjbY43XRaRagPbMK0terP4gUi8x07AdZzpWejj2WDvSkzkcTlraoJZpMB3ycHj7O9OzZcq54qsGzLxXACXQK+GSnZPd7wO9xZaZiz5RzebJNm5VFJzI4KVBjrdOIN9SWnS2pscWZMakxNVtSIuE05g2mgjABv1OWdMhoODzgXK8NnPQkNeuTAjUieWIMFX5nFqkJOVcnkpZQqnyqqT3J2t0JmiM2Uz5VHVT5lAwd6V/5e8rSSTdIbovtHdRpimSzdCJxJ4MgE7jJycopyZnyOR3gUYNkKXqdpmM/+P496YyeaE7TZqevVZJoIlXGlcroiaV7+SScTJ94wunf48yy5QR1Mn189gjCprN50j17cqdn93sMbmWNi/Sp4g/UxBPZAEy6PCndoHd3i3O9xw0lvmxpUmkAKkpgzDAnIOP35vtVSDFQjxqRQcnlNgwvMQwv6Zz52BHPBm+aIkln+vBIEq/bUBV0AjdVARdVQZVPyRB0AA2S23OCOe1xpzn49ngyE9Bpj1lcLqfso1PJVSqQ42TKqUGyCJDt33Ow07Hbzn17cjN82qJJmiPkBHyys3llMntSlw055Vxu43R76KK5eTbgk+3Zky7lUv8ekazCD9R0xLIlSZn+MDnZMK0Rpxwp6HNmSgr6nKmqx1TD1NFOUMajaatlAKRmfdJ+pUhhCHgNo7son2qJOv1vmtotW8MJ3qmP0RLNlk9VBV1Up5oYl/pUPiXicRvK3Iay3jRITtApmJM+rW9NdmqQ3BF3+o0E98jI2fO0xKuZekS6k+7f0yfTsecEfJwMHyeIE+pI0tDulHtlmjWnAjzpqdjTDZs9ruw063uVdHnSzZxdmSBPp0BPKhDkV7mlFIHBHaixFlo7stkwobZsJszu1GxJ8YTTAyboTwViUmVJk0c7zXqDPnCpP4wMAumMmnyPQ0QOnDFU+g2VfhcTc2pDEkknO6ApkqSxPcmaXTEa25MkklAZTGfeGKpTWTg+lU+J7M0Y3KkDMQLd3zVp0yVXTmAnHcBpjVp2te7dIDm4j2BO0Nu5ebJ+zRc5MC6X0++mT8q5crJ7ojm9fJra08GdxF4zcsUzjZ6d7+R0E2Z/zsxcuTN2Bb3Z2bk69/Ahc73690g+5TdQk0hmAzDpbJh0g96mVuef25XtD1Pid0qUqkph/PBsWZI+QFIIjPPLuks7gSJFx+Uy1JRBTVnnDM1I3DqlU+1JGiNJNjTGaIok8bsNVakATnVQ5VMi+8uFocxNj1k64BzsZQI3OZk6uyNJ2sPO+XSvHZ87pzGyd4/z6YCOV7/Yi/QPg9vtTMd+MKzdd3ZPLGHZ3W6JtVriiZxgj832+ImnTjP9e3KCPsFUNk/Amw365PbrSWf4+N3ZLB/13pID0b+Bmmhq2uqm1uxpY0v2XzjiNOfNZMT4nODL2GEwY5xzXmVJUixMpxMRGQKCHkOw3M2YPcqnwtFsAGdLc4I3t8doiSap8GdLp6qDTjCnRLNPiRyUdHlEZS9KryJxsv10cnrnNLYnncupQE8saTOzXJWkgjedgjk5gR4dpIkMLGNSmTR9Uc6VZK+ZuWIJnIbNEUvMOgGfdPlWugQsmxlkcZlUo2ZPKnPH60zF7veYTAln5wbN2SbNTimXM1OX+nINLQceqLEW2jqysyWlM2Aac/rDROPZLJhg6rQs6PSGKQtCqV9lSTJ0qJmwiAAYQ1VqFimqs1fHk07vm8Z256Bw5c4EjRGnfKo66Ewbns6+qQ668Lm1MRHpU8aZwrzU17sGyensnPacTJ3mSJLt4c7Xu1ydmyEH92iOnD6vBskig0t6OnYOcjr2pIXoHpk96YBPe9QSak926tOTPo0myCnpsnjc6QyenMbNqdNgpjGzk/GTG/TJ7efjUzZgweg+UJMuR0qXJuVmwzS1OiVHpX6nOW86G6a6DCaOcM4HNG21SIam5xaRbvjchhGlbkaUdr6+PZbtfbO7Pcm63XGaI0n8HpPKvMmWT1UGjA70RAaAcwBnqOjhfrkNkttiOUGdmCXUkewU5InGrXPAtWcgZ4+ATplPZZIiBSM1HbvXDaV90L8n2im7Jxv8CXdALJEknkzkNGl2yrjSlzv178lk8XTdwye3SbM/57LfDSU+JVoMhH0HairmTeY/P+j0g8kNxIwbnipLCoJvcPciFhlUDKmMGu1ciUjvlfoMpT4X43KOCK21hDtsJnizqSnBK1uiHDnGx6EjvfkbrIh0lp5RxwvVwe7vmkhaOuLZbJx0YKelw7KzxWmQ3NJhqSl1MWdKD92WRaS4ZKZjP7iHSU/HnhvwSTdtjiYsoUiShlQmTybgk9Pvpz1u+eRRpYytUHuS/tbdovYyqgrOmT1ggxEpasqoEZG+YgxVqR42h6SuenVLlKS12saIFKh0lk53DZK3NMd5pz6uz7mIHBCXMXhczkx4B+LptRHiSdvHo5Ku9BCTM+ohI9JXUj1qlFAjIv3BpLL2tI0RKV7pz7c+5yKSF9r2DJjuAzUu9PO/SF8xKKNGRPqN0TZGpOi5TPafiMhA06Zn4PQio0aLQ6RPGINBjT5FpH84QRptY0SKmcmUUetzLiIDT5uegdNDRo1Kn0T6jHrUiEg/cqGMGpFi58pMTJDvkYjIUKRNz8DpPlCjbwKRvqO6chHpR+pRI1L80p9xfc5FJB+07Rk4PQRq9E0g0neUUSMi/Se9fdE2RqR4udSLSkTyyCinZsD03KPGrdInkT7hMoM6Se2y/9vFzadXcMx4X76HUtTqQgnm/moX//jsSDwDsDLc/myIkaUurj+urN+fS/Kr2EufXt0S5WtPNrPkmhH5HkrBuPCBnfz3nAqOn9jNfM8H4Rt/a2ZkmZvPnqjty0AxBVD6pP2JgTGU9yeuf3g3F8wI8KHDSvI9lKFnEG97is3gL3265Tcwuho+Pze/4+hL318EG+vhruv69nG3NsA534A37+4+wPaP1XDzr+GZ25zLJ98MC66AUw7t2/FIZwP0K9j59+9kd1sSl8sQ9BhOnuTjK6eXU+LrPuj68OU1+/Uc3zirghP6aee/0Dz2TjuPvN3OAx8Z1uN900mKA5X58PU5Ff3/JH3s2od2c+GMAJce3v87YM2RJN98KsRLmzqoDrr4j5PKuGBGsMv7PvBaK39+t51t4SRVQcNHjyjhqqNLM7df99Bu1jXEiSZgXKWbfz++lDOnBPZ6nG881cxj70RYdMVwJlb18HvJfhiojJrz79/JztYkf7t2BNXB7HblY79rYNWuOI9fVcO4CnefP2/uZ+dAzL57x0G/59c+tJs3t8dwpwYxstTFY1f0ftt5sLaGElz4wC5e/VzvD8z69XunALI7fvN6Kw+81kYkZjl7mp+vnlGBz7P3gGMJy1eWNPN2fYxt4ST3XlrNsXsEGt6tj/Gd58O8uzNO0GO49thSPjHb2U719vN/sAZy1iftTww87U/03mA4TN0fL2/u4I7nwmwPJzh8lJdbz6lkbA/fla9uiXLdw41cd2wpn8sJiHe3Xcv93AK8b7SXez5U3Wevo4De8oKXv9Knk+fDjib4x//CsPLs9ef/D7yzGf5+J0yogTuu6J/n7+0YF1zZ9wGM9Fva1+/t+Bp498c93+/4GfDs7Z3Hk+8yt8274D/vh3+uh3HD4NaP7/t9/8srcN9TznoyexL84cudb7/51/DyKlhfD9+5Cj5ycva2B5fB/U/DhnooC8Ilx8GXLwVP3x9U7M3JqOnvlEED3H1RNSdM9LOjJcG/P9rIva+08cWTy3v82/15DpP6T3I+0r14P3Lvq/evawO5ft3xXBiv2/DsdSNZuSvOfyxqZEaNl6nDvV3e//YPVDGtxsOW5gSffnQ3o8vdnD/dCezMP72CycM8eFyGN7ZHueGRRhZd4WNEaXb7sqIuypamROp19u1rNDnvXH8ywLgKN0tWR/j4+5xA1ZpdMSJxm7m9P8awP5+zfT/Gwb0/BvjK6RUDEkTc1/M7p717Hf39WTL03/LuC8s2dnD/q23ce2k1I0vd3Ph4Iz99ubXL70MDHDXWxyeOKuW//tq01+tqbE/ymcea+K9TyzlnaoBY0rKjJZm5T28+/31hoD7nznNpf2KgaX+idwptvWlsT/Klx5v5xlmVnH6Inx8vDzN/cTO//djwff5NLGH5zvNhjhjl7bQ96mm7lvu57Q+F8Y4Xh54DNf0569OEGvjzK3D12c7ld7dAJOqcd7kGx4xT/fEepIMig+H1peV7PJ+/F94/BX59Izz7Bvz7T+H5O2B4F9H76jK47hxYtx2Wvbv3uA+dABcfB9/6096vKxKHb34cjpoMDWG49m6490n47IX9+/ogNT33wET/079wjil3c+okH+sa4rgMPPtehB8sa6G+JcGMER6+PqeSycOczcC5v6znm2dXcuJEPz9ZHmbd7gR+Nzy9roMx5W5u/0Alh43y8pUnmtgWTvL5Pzfichk+fVwpn5hdyjeeaubvGztIJmFilZsfXVxNTTc7qFc/2MBRY338Y0uU1bviHDfex23nVHLH0hBL13cwqcrNdy+sYlyFM75/1kW5c2mIjU0Jaqvc3Hx6BbPH+nhiTYT7Xm3hj/+W/QXvVytaeXVrlB9etO9fEL76ZBNBj2FLKMGKuhgzajx8/8Iq7nu1lcfebWd4iYtvn1fFrJHOAfsvXmnhobfb2d2WZHS5i8+fWM5ZUwO8tzvObc+GiCfhhJ/uwGPgxX8fRSRu+eGLYf62NkK4wzJtuIefXzoss/wXr4rwo5fCROKWTx5Vyqd6SCV+c3uU2551Xr/fbbhwZoAvn+Z8Pm56vJEVdTE64pbpNR6+PqciE2j46pNNjCpz8/mTymlsT/K1J5t5vS6KMTB1uIf7LxuGyxje2x3n/z3TzKqdcUaWufnCyWWcOTmQfa+8LupCCV7bGmXKMA8LzqtkQg+ZCe/tjnPHcyHeqY8xLOjisyeWcd70IJub4sxb2MC9lw7j0JFe6lsSXPa7XXz3gipe2hRlRV2MN7bH+PYLYS6ZFeSrZ/bPr3htsSRPrY3wyOU1lPldHDPOxxmT/Ty+MsKNp+wdqLn2mOwymjzMw5mTA/xrW4wLUxk4M0dk/8ZtIJ601LckGFXmfA7iScuCpSFuO6eSy37X0Oe/ghrjlD8NxDbmollB/vJuO5fPdgI1f17ZzsWzgvzwpZbM6wp3JLnjuRB/39hBwGP48OElXH9sKYkknHFvPfdfNozpNc571tCW4Lz7d/LE1SMZVtL1d5ErFRW475UWfv16KyVew3+cVM7cmc77f/WDDcydGeTDqSDKo++08fBb7fz6o8O58k8NAHz0dw1g4NazKzh+gn+fn4fu7G8GyaPvtPHQW+0cPsrLY++0UxFwcee5lWxoivOjl1qIJeCmU8q55FDndTy/PsIPX2phc3OCMp/h0sOCfOYEZwf8mgd3A3DKz+oB+PmHqpk9xseDb7Xx6xWt7Ghxtk93nFvFoalt1+pdcf73hTDbwglOrvVz+wcq8XtMt9uDfXm3PsY3nmpmY1OCUyf598pyevCtNn75aivNkSTvH+vj63MqGJla/4/4wXa+ekYFv3m9lV1tSS4/qoQPzgrylSebWdsQ5+RaP3eeW4nX3Xcr8J/fbefSw4KZ9eyG48q4+Ylmbjpl70CD32O44v3O+uxy7Z2l8NvXWzm51sdFs5zlFMBQ7s+uqz19/vvKQPeo0f6E9icGw/7Eixs7uGNpiF2tSebODGLJrptJa7n3lVYeequNjjicXOvjK2dUUO53sTUU57z7d3Hr2RX8eHkLbTHLF08q59CRXv77qWa2hxNcOLP/9jPSnlkXYcpwD+dNd96Hz5xQxmk/q2dDYzzzudnTb15v5aRaPw1tzo876eXdm+1af24j1L524PRieu5+XBofPgkeehGuPce5/NAyuOxk+PbD2ef+4i9gTDXM/zC8uBL+4+dw/QfgJ391yntu/jB87NTun6c96jzm469CqA1mjoff/ycEffDk63DHg7C9EQ6b6GTwTBvrPM/W3XDN3c439o0Xw2cugNfWwf/8HtbUwbgaJ/PjpJndP/+mnXDjffDmRnj/ZJgyunO+3r7GAHD8f8JVZznv04Z6uOR45zXfeB/8Y40TcPjZZ6Cq1MlKOeG/YOMvnAyRxha49Q+w9C0nAHbCDPjl57Pv42vfy44xs7VLwk8Ww++WQnObk9Vy5xVOcKS/rNsOb22E338JSv0w91i472+weAVccebe9z/9cOf0d0u7znu8JhX4+95je2+prpqTPT9uGHzoRHjx3QGKngzczlX647MtnOCFDVHOnupnU1Oc+YubufuiKo4d7+PXr7fyuUWNLLqiBl9qxzj9dwZ47r0IP5hbze0fqOTuF1v41nMhfj9vOAvOq2LF1npuPcfZCQP44xtttEQtT187Ep8bVu6MU+I13b5WAyxZHeHnH6qmOuji439o4PI/NvD1ORXccW4lX/9bM/e83MrtH6ikKZLks4sa+coZFVwwI8ATqyN8dlEji68awVmT/dz6dDPrG+NMSX3Z/WVlOzccV9bj8z+xJsLPPzSMqcM9fPrRRi7/424+e0IZXz6tnB8tb+E7L4R54DIn/bi2ysNvPjKMmlIXT6yOMhlVTgAAIABJREFU8JUnmlk81svU4R7+e04FD73dzm8/mv1l5LsvhFnXEOP/PjacmhIXb2yP4UkdSAO8vi3K41eNYEOjE7Q4Z1ogM/6uLFga5pNHlXLxrCCt0SRrUzvLAKcd4hx8eV2G7/49zM1LmjOp54bsevfrFa2MLnfxwg0jAXhjeyxzQPG5RY1celiQey8dxoq6KP+xqIk//puHQ4Z5UsuqnXs+WM2hI6u45YlmfvhSC/97QdU+x9sWS3LDI7v53Ill/OxD1azZFee6h3czvcZ5z246pZyvPNHEH/+thq//rZlLZgU5foKf4yf4+WddlLmzglzWTdbCCT/Zsc/brj22lOuP7XmbtbkpgcdFp52kmSO8vLIl2uPn1FrLirooHz2ipNN9P/NYIy9t6iCacHYWjxjtzdz+29fbOGacL7Oz3tfbg4E8gJs9xstfVrazvjHOpConu+a3Hx3uBGpSY7lzaYiWqOWJq0fQ1J7k+kcaGVnq4sOHl3D+jACPr4ww81TnvViyOsLxE/zUlO77BwMDNLQmaYokefa6kfxre4x/f7SRI0Z5M+tp7us3qf+5DPzmo8M57K7tPHT5cGpTBwTf/3u4y89DdzuhBvjBi2HuWhZmUrWHL5xUxnETuv/V0gBvbo9x2eFBvvzpkfxoeQv/taSJMw4JsOSqEbyyNcoX/9LEB6b5KfW5KPEa7ji3kqnDPazZFef6RxqZNcLLWVMD/Pojw/jA/btY/u/Z0qcnVkf46fIW7r6omsNHedjUnMDrym5/ne1cNT6P4ZN/aGDRu+187MiSfW4P9vX6ownLF/7SyCePKuXj7yvhmfc6+PLiJq45phSXgeWbO/jBsjD3XjqMqcM8fOeFMF9e0sSvP5LdLr64qYM/fXw421sSXPa7Bv61LcaC8yqpCjjfAYtXR/jgoXuXHr62NcpnH2vc53v840uqOXrc3v1Q1u2Oc9YUf+a9mDXSS0NbklAkSVWw+3Vtz92LN7bHmF7j4ZN/bGBTU4IjRnv52pkVnUoXuvv895WBDMiC9ie0P5H//YnG9iQ3Pt7EbR+oZM5kP7/7Vxt/erONi2cFcRl49J12HnunnfsvG8awoItbnmjmjudC3HleVeY9emtHjMVXjeDVrVE+t6iRU2r93PfhauJJuOz/GjhvemCvUsf08r/tmdA+x/bw5TU9li+B88PVzBpP5n0u87mYUOXhvd1xpg7fe1nVhRI8+k47f/r4cG5/NtTpu60327WvPNFM0lpmjfDypVPLOwWSD5YCNQOn50Lt/vwmOGYqPPwSrN3mBC8W/QMe+2oqUEN2C58pvAd2NkNLO7z+fXj+bbjux3D+0U6gYl9u+wOs2gp//hqMrIQV68DjgvU74DP3wP2fd4ItP38SrvoBLP0W/PgGp5fLd6+B0w5zHmdbI1z5ffjhp+DMI+CFd+BTP3IyP2q6icR+7mdw9FRY+J+w4j345Pfh3KOc17Ru+77H4Estnr++Cn/4L4gn4Zz/hrc2wfeugWlj4PLvw/1PwZc+mN1ip78dv3AvlAbguf/f3p3HR1Xeexz/njMzmZlksieEfZM9gAsgIFBRERUVhYp0sVWr1qtS69bqdWvVirf3ovZSFa9b3WtdUOtWF9ygpeJWV1CkbkCABMg22Wa7fzyZySQzk4AmeGw/79eLV5jtPOc8c85znvM7z/Obq00A5PVP2uqxYw8k/pnbV0jPviUt/0+pOFe69D7p0nulZWekbtfG7dIhl2be7mt+LM2fmvn1uPWbpYGlUl7SRVn5QGn9ps73v11JWNBVb+a1j6RR/fbYMJd0caXuL0c6+4lquWwpkGXpwCFe/cfkgO54I6gDh3g1fbDpDJ0yMUf3vt2gdytazIWG1bZbWJa0X18zukCSjhnj1z1vB9vW3Wq/C3lcJtfHxpqwRpZ6NK73LpwQLGl+uV+DC81+/p3BXm3YYe6qStLhw31a2np3fuWnzRpU4E504I8e7dd97zTolU+bNK88ftHXqHOm5Wp9VUibayM6eKi3y91n1jBfYl0PHebVH99t0LxyU8aRI3364zsNiWUcMbIt18CRo/y67Y2g3t8a0iF7uRJNVfy90VhMj37QoAe+X6w+ueYEHr+IiL9n0ZSAsj2WxvTyaFSJRx9XhTQ8zck6zu2SvqwOq6YpqkK/rX37tnUokgMaP5sa0ORl2xRsiSrXa7dLPOlxSVXBqLbURzSowJ3olLy9uUWNoZh+un+ObMvSAQO9mjnUq2c+btSiqbmJutqnT1ai/n/7Sm2n9fvqp83ql+dKjG4oL/No9nCfnl/fpBElAS0cn61XPm3W9x/YLsuSlk3Lzbh/pbPmrLLML+6ixlBMgSy7XTm5XksNoWiXx+nvV9crFpO+W+5v996bjy1UKBLT6i9a9M8d4cTFdEVdRA+916CHf1iceH+3j6jpgWVmKsiSNHe0X0+sbdSk/lkaWuRW71xzErItE8h65qMmLT+hRLleW7leWydPyNET6xq1YFy25o3x69ynqnXBjIAsy9ITaxt1SusFfybx134+LSCfx9LkAVk6cIhXz65v0plTAin7TcfjMv5ccruV7njozPkzcjWs2C2Pbenpj5p01p+r9egJnee9sS2TsyR+LBw50qdb1gR11pQc+TyWZgz2yuOSNtZENLqX3W64+uheHs0Z6dMbm1p06HBf2n3nkQ8adMrEHO3dx7RlQwqT1sWSfrRvtnq3tkMzh/r0UWWo0/Ygk/e2hBSOSiftly3LsnTECJ/ufsuTqOOn1jVpfnm2xpaZ9ThvekBTlm1TRW1Y/fLNOp06MUd5Plt5PlvDi92aNigrETj7zmCv1lWGZFupgZpJ/bO+0jHfGIopz9d2jOd5rdbnoxlHbsV1PJa21ke0tjKk2+cXaUSJW0tW1umXz1Tr/u+1XVBnOv670x4dUUN/gv6EA/oTKz9r1rBit45oHY1y0n7ZuuutYLu256QJOYm25LzpuZp7T5UWHxZLLPfMKQH5W9tbv8eMIopPS5zQz6N1lSFNHpDaBs4d7dfc0enz1u2OhlBMRf4O/Y0sS40Z+hvXvFyrsw8IpNS71HW79j9HFGhMmUexmBmVc/qjO/XUiSXK83XPzAniNHvOLoyo6aHpMPHpP8dNkx7+mwlSDO8r9Ws94VmtU5+SpwlZtmkZLphnWplD9zUBiH9uNUGfdKJR6YGV0tO/alv25JHm7xNrpEP3kQ4abx6fNUe67Xkzamba6NQpSstXS4fsbcqVzOf2HiK99F7mUT0bq0zelYcukvxes9zZ+7Qtd1fW4ZTZUlnrkMspI01QaO8h5vGcCSZgFK8fyfy/slZ68T1p3U1tQax4zpfk9yV/F7Yt3fOStPjHJt+NZPK37HeudGMsNY/LwFJp/f+l3+7d0dhigjTJ+1pethlh1Nn+19UUMktt+1E6978ivfuZdP2pe2baV2tLuyci0TfMLdABg9rf5a0MRtQ3z06U77Is9cl1aVswmnguOVVRaU7be/0eqTkiRWKxRMcz+b3HjPFrS31U5z9drdrmmOaO9uucaYEuh7CXJJXh81gqzm7/uKElJstKXXfJ5MiIr/u8MX6d/3SNzpkW0BPrmnT4CJ+8nq4rutPy3W3lS+aOzZ1vBrWp1gxBbWiJqbqxte6S6k+Sqhujao6YIdsp33e8fgPJZZsTb2f7RvxO5Jw7K9U/3/zKykFDfYpEY/rdX+v1l4+btKOx7YRf3RRNnJTj39Upk3J0w+p6nbrc3Jk+fpxfP90/oMqGiHrn2okEqYn6rY9m3B8auljfirqI3t0S0v5JI18iUWnuaF/icwvG+XXm49W6clZeyvfVE2mzTlu+Q29uCkmSrpiVp72K3apvibYrJ9gSU06W3WnZ974d1ONrm3TfwqK0+1mW29KBQ7265+2gBhW6dPBePl3zcq3OnBpo11Gy1L3bGK+zPdHGWJY57n/0p+3aVBvRsWP8beVaZv8LRaV++W11mbxP7dM3Sz63pTUbW9Qr4NIXNREdMszX+bpbUp7PUk5SItO+ebYqg5G0bVjH4zL+VPxxpuOhM/skXdDMG+vXUx816tXPmvWjfTvpTllSSYe2RZJKk6bE+NyWGsPmmHqnokXXrqzX+u0hhSJmJMvhI3wpbU18eVvqIhpYmKatadXx2K0MxjptDzKpDEZUFrATCSolqW+eK7EulcGIysvcibICXlsFPlvbglH1b71Z3q7NdVspbXBVMNqt+2+2x1Iw6RgPhkwepRxv58e4pJTztc9tadYwn8a3BsTOmhrQ1GXbVN96ERuX7vjvTvHdYE/d1aY/QX/im+5PVAYj6pNrJ+1blnrntrU924IR9Uv6TvvluxSOSjsaook66rTtcVtd1tnuiP8aV9xbPytTTpalYKh9+1afob/x4oYmBUMxHTmqLUCUfIx01a5NSAq6nz45oMc+bNSbm1u6vS1Cz+v657l7MmRvW9LC6dLc30hfVpr/p7tdZCU9Lgy0jTSRpGyv1NiceT2310tNIWlIWep7tlabPDmJMl1mOszWnenXY9N2k1PnuX+0LSMcNgGQTOVvqzGBktykg2NAibR5h/nMrqxDWX7b//1ZZlRQ4rFXamhuv562JVXskApzpKI0na7k9yU/Z1tmlMzJ/9s+cOGype21Up+uM9DvkukXmWlakvTAL6SAz4ySSl6f+iaT7PdrjaixMt+Wf/oNk8Pm4Yuk0j2Uxd6SLFnqKv/B1y/GkmWlllMWcOnjqnDi+Vgspor6iHrnumRbVrvPWZbVesfOvDf5r21ZsjuU4XVbOvuAXJ19QK421oR12vKdGlrk1oJxmaeuxJPAxZfRcb2t1sCWbVkqy3XpuU+a221TRW1E3xnslW1Z2q+fV1ku6a3NIT25rlHXzinssp4tK035SY+T/26qDeuy52t013HF2revRy7b0ty7K6XW93f8THG2S163tLEmqtG92gc4O9ZlurLTGVrk0e+OKlQ0FtNz65v08yeqteasMj23vkkrNjTpzgVF6p/nUl1zTBNv3JpYXvJ25nldunhmvi6eKX1cFdKPH9yh8b2zVBZwa0tdtN36VdRFNLjQnbKMjtuQSd9cc4ftzgXpE+UFW6K65uU6HTfWrxv+Xq/DR/gTQ3Ztq+v62GfployvnT45oDMmp7Z9t3+3/bo0hKKKRKUvqiOJO7EfVYU1vNidseyH32vQra8Hdd/CYvXN6/wUGolJX9ZEZFuW/v6lyb2z5NW6xOvfe2CHLj0oL5Hz4uvq+D31lPixOiDfrf75br3yabMWH5bfbr8oznbJY0tb6qIaVmyOgYr6qMoCrsT75pVn68l1TSrJsXXYcJ/8nq5GOFiqbYqpKRxTdut7K+qiGlFivq9sj63mcNt+uT0YS3wueRnxx5mOh44XpZ3WxS7Uua30x03Hz8SXc8HTNTph32zd/t0ied2Wrn6pRjsbo7ItK3Hxk7wdfXJd2lgTTbsO6drVeNu+u9tfFmi92GpdjmSCRIMKTP2XBVyqqG1bj4aQmaYWP8d0XO943SS3g+nqRZJe39ii05bvyFjHt84vSjsiaHiJWx9VhXXkKLPMj6vCKsm2VZzd9VSFjus6stTTOkjXPOfKsE1xycd/d7I7nJ97Ev0J+hNO6E/0Cri0YkNzu/1tS10ksZxeAZcq6trani11ZlpzacClLXWRxPIznQssSxmPqT+vbdTlz9dkXLenTypNmfrUP9+tf5zdu91zw0s8euyDhnbt45c1YY0o8aSU+9qXLXp/a0jTbza5yOpaonJZltZXhbXs2KLdbtesbr7+2COj+SCpyxE16tlvw7KkQaXm3wvvSEtPSw2QtB09bWOtOq5T/PV0SvNMePmLbdLYQe1f61Nofjko/tlYzOSl6VuUWrZkRuQcP233fla7T6FUHTTBpJzWYM3mHW3b0dU6pNu+5OBDx+lO8f/3L5Z2BqW6Bim/w7SwdPUYL6NvkZnaNXlE19u2sUo64MLMr1/7k/a/uBT3t9+2f/xJhfR5pRRsknJbL1g+/MLkMOpqWlNyXXRkepOpr694RzrvDpOnaOzAzMvvbonOSs8XlW76w5Gj/Lrl7ir9/YtmTeqfpbveCsrrsjShX1bqYZe0nI5/bUsqzrG1qSaSeH71F80q8tsaVuxWnteWx2WSKXa1rcn10dqPSlvmQUN9uurFWj25rjExp/yTHWEdvFfbVIB55X5duaJWbtvS/mmGr6aUnab85HKTHzeFYrJk7sjYlrT8/QatrwonPl+aY2trfVThaExZLnMyPG5stv7rlVotmVOgkmxb72wJqbyXJ6Uu09VFOo992KAZg70qznYpv/XOltsyd+m8LktFflvN4ZiuW1XXbnnJ2/nihiYNLXJrUIFLeV5bLtvEYfft65HfY+m214M6ZWKO3tzUopc2NGv5Cbkpy4jXXXJdpXPwMK+WrKzT4x82JJK9rt0WUnaWpWHFHl39Uq3G9fbovw4v0CXPVetXL9To93PNyMGSbFsba8OdLv/dn/fO/OIuCmTZmj3cp6V/q9Pi2flaWxnWik+a9OAPitOW/fiHjbpuVZ3uXViUCOzEbdge1saasCYP8MplS0991Kg3NrbowgPzZFvSCz8pVTTp/VOXbdMt8wo1urT7cljE96k92cZcc3i+apuiCmTZCkdjidc8LktHjPTp+lV1+p85BappjOrON+t1ysS2XA/HjvHr6LsrleOxtWROftftRevf3/+tXufPyNU7FSG9/M9mndM6bW5ML7eeW9+kheOztbU+ooffb0gcs1J8v4poSGvuhkzHQ6b1qG2K6h8VZni8yzbD7d/Y2KLLD87rdN07diU6tjUd6zTYElOhz5bfY+mdihY9sbZJ0webdrok20yN2FTTth3Hj8/W4pdrNalflsrL3Pq8OiKPrcR0o473veLP7e7279fPbPc9bzfoh/tk68UNTXp3S0hTBpppIUeP9uucJ6s1d4xfexW5df2qOu3dx9NuWlhKm9/J42STB2R9pWN+XrlfFz5jcmCVBVxa9vd6zR/rz7iNza2/XCaZ2eahSExZLnMhvmCcX2c9vlMnVpppJTe9Vq+J/TzK99ldHv/dqbN66gn0J+hPfOP9iaE+XbWiVs+vb9Qhw3y69+2GxOg725KOHuXXLWvqNXOIV0XZtq5bVac5I32t9ZehjtT547hjx/jT5s3aXYcN9+q/X6nVc+sbddBQn25aXa+RpR4NL0m9FD93eq7+I+lm01Uv1qpXwKVFU8z5s7N2bXNtRBV1JodWLGZyCe1sjGli/6wujyE4zzc/osa2TGCgOmgu0sOR9q9Zaj+iJt2R1FnP1HZJPzxQuux+6eYzzGiUNzdIew+W5k2R/vdJaeUHZurVzc9KXreZXmRbUq88kwg4vuyF06VDLjNTnWaOlUJh6Y1PzGidfhl+Xm1QqbTvEJN357KFpuxn35IOn2CW29U6dNy+tD2bDu+JB1xm7S394k5pyclmitia9WY6Vbp6jH/+J7Okqx+SbjrdTG2qqjW5euZMTN22gaXSxjsyfLm7YURfadxAacmj0iULTNDugy+lu/dP/71GoqbuI1EpGpNaQubs4GndnVvCZspbLCZFIub1LLdk2yav0enLpHvOkSZlmC7XUzLsvj1UVEo5w4rduu7IAl35Yq221EU0ppdHt84vTAzDT/5cZ50c25LOnBzQr1fU6Lev1mrRlIDKcl26/PkabamPKttj6ahRvk47w1Lbbpx8sk4uM/lxcbat2+YX6aoXa3T58zUaXOjSbfOL2iUenVeeretX1WvR1M6T/iVva8dtTD60kv+OLPXo1Ek5WnB/lTlsx2QnOqS2JU0b5NXwEremLtsq25LeXNRbl8zM03+vrNX8e6sUbIlpdC+P7jquKKUu09VFOis/bdY1L9epMRRTvzyXlh5dqOwsS98d69eqz5s1/eZtyvfbOm9aQPe/k74J/bw6rCtW1GpHY1T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