{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Décomposition d'une série temporelle\n",
    "\n",
    "Ce notebook présente quelques étapes simples pour une série temporelle. La plupart utilise le module [statsmodels.tsa](https://www.statsmodels.org/stable/tsa.html#module-statsmodels.tsa)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Données\n",
    "\n",
    "Les données sont artificielles mais simulent ce que pourraient être le chiffre d'affaires d'un magasin de quartier, des samedi très forts, une semaine morne, un Noël chargé, un été plat."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2023-03-06 00:39:51.820916</td>\n",
       "      <td>0.005036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2023-03-07 00:39:51.820916</td>\n",
       "      <td>0.004769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2023-03-08 00:39:51.820916</td>\n",
       "      <td>0.006293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2023-03-09 00:39:51.820916</td>\n",
       "      <td>0.006932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2023-03-10 00:39:51.820916</td>\n",
       "      <td>0.008666</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        date     value\n",
       "0 2023-03-06 00:39:51.820916  0.005036\n",
       "1 2023-03-07 00:39:51.820916  0.004769\n",
       "2 2023-03-08 00:39:51.820916  0.006293\n",
       "3 2023-03-09 00:39:51.820916  0.006932\n",
       "4 2023-03-10 00:39:51.820916  0.008666"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas\n",
    "from teachpyx.datasets.data_ts import generate_sells\n",
    "\n",
    "df = pandas.DataFrame(generate_sells())\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Premiers graphiques\n",
    "\n",
    "La série a deux saisonnalités, hebdomadaire, mensuelle."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, \"chiffre d'affaire sur deux ans\")"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "fig, ax = plt.subplots(1, 2, figsize=(14, 4))\n",
    "df.iloc[-30:].set_index(\"date\").plot(ax=ax[0])\n",
    "df.set_index(\"date\").plot(ax=ax[1])\n",
    "ax[0].set_title(\"chiffre d'affaire sur le dernier mois\")\n",
    "ax[1].set_title(\"chiffre d'affaire sur deux ans\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Elle a une vague tendance, on peut calculer un tendance à l'ordre 1, 2, ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'tendance')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from statsmodels.tsa.tsatools import detrend\n",
    "\n",
    "notrend = detrend(df.value, order=1)\n",
    "df[\"notrend\"] = notrend\n",
    "df[\"trend\"] = df[\"value\"] - notrend\n",
    "ax = df.plot(x=\"date\", y=[\"value\", \"trend\"], figsize=(14, 4))\n",
    "ax.set_title(\"tendance\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Autocorrélations..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1.00000000e+00,  2.05522806e-02, -5.81441890e-02, -2.01231811e-02,\n",
       "       -2.50535358e-02, -6.81166704e-02,  5.94423981e-04,  9.25077506e-01,\n",
       "       -3.79860291e-03, -8.24593539e-02, -4.47874626e-02, -4.84700550e-02,\n",
       "       -9.04852284e-02, -2.10021533e-02,  8.86200829e-01, -2.87651649e-02,\n",
       "       -1.01244603e-01, -6.63494241e-02, -6.78568361e-02, -1.06899756e-01,\n",
       "       -3.87558669e-02,  8.53901943e-01, -4.51168979e-02, -1.16356930e-01,\n",
       "       -8.69970753e-02, -8.95201510e-02, -1.25409915e-01, -6.73383807e-02,\n",
       "        8.10734998e-01])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from statsmodels.tsa.stattools import acf\n",
    "\n",
    "cor = acf(df.value)\n",
    "cor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Autocorrélogramme')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 1, figsize=(14, 2))\n",
    "ax.plot(cor)\n",
    "ax.set_title(\"Autocorrélogramme\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "La première saisonalité apparaît, 7, 14, 21... Les autocorrélations partielles confirment cela, plutôt 7 jours."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from statsmodels.tsa.stattools import pacf\n",
    "from statsmodels.graphics.tsaplots import plot_pacf\n",
    "\n",
    "plot_pacf(df.value, lags=50)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Comme il n'y a rien le dimanche, il vaut mieux les enlever. Garder des zéros nous priverait de modèles multiplicatifs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>value</th>\n",
       "      <th>notrend</th>\n",
       "      <th>trend</th>\n",
       "      <th>weekday</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2023-03-06 00:39:51.820916</td>\n",
       "      <td>0.005036</td>\n",
       "      <td>-0.000797</td>\n",
       "      <td>0.005833</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2023-03-07 00:39:51.820916</td>\n",
       "      <td>0.004769</td>\n",
       "      <td>-0.001068</td>\n",
       "      <td>0.005837</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2023-03-08 00:39:51.820916</td>\n",
       "      <td>0.006293</td>\n",
       "      <td>0.000451</td>\n",
       "      <td>0.005842</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2023-03-09 00:39:51.820916</td>\n",
       "      <td>0.006932</td>\n",
       "      <td>0.001086</td>\n",
       "      <td>0.005846</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2023-03-10 00:39:51.820916</td>\n",
       "      <td>0.008666</td>\n",
       "      <td>0.002815</td>\n",
       "      <td>0.005851</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        date     value   notrend     trend  weekday\n",
       "0 2023-03-06 00:39:51.820916  0.005036 -0.000797  0.005833        0\n",
       "1 2023-03-07 00:39:51.820916  0.004769 -0.001068  0.005837        1\n",
       "2 2023-03-08 00:39:51.820916  0.006293  0.000451  0.005842        2\n",
       "3 2023-03-09 00:39:51.820916  0.006932  0.001086  0.005846        3\n",
       "4 2023-03-10 00:39:51.820916  0.008666  0.002815  0.005851        4"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"weekday\"] = df.date.dt.weekday\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>value</th>\n",
       "      <th>notrend</th>\n",
       "      <th>trend</th>\n",
       "      <th>weekday</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2023-03-06 00:39:51.820916</td>\n",
       "      <td>0.005036</td>\n",
       "      <td>-0.000797</td>\n",
       "      <td>0.005833</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2023-03-07 00:39:51.820916</td>\n",
       "      <td>0.004769</td>\n",
       "      <td>-0.001068</td>\n",
       "      <td>0.005837</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2023-03-08 00:39:51.820916</td>\n",
       "      <td>0.006293</td>\n",
       "      <td>0.000451</td>\n",
       "      <td>0.005842</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2023-03-09 00:39:51.820916</td>\n",
       "      <td>0.006932</td>\n",
       "      <td>0.001086</td>\n",
       "      <td>0.005846</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2023-03-10 00:39:51.820916</td>\n",
       "      <td>0.008666</td>\n",
       "      <td>0.002815</td>\n",
       "      <td>0.005851</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2023-03-11 00:39:51.820916</td>\n",
       "      <td>0.014102</td>\n",
       "      <td>0.008247</td>\n",
       "      <td>0.005855</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2023-03-13 00:39:51.820916</td>\n",
       "      <td>0.004139</td>\n",
       "      <td>-0.001725</td>\n",
       "      <td>0.005864</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2023-03-14 00:39:51.820916</td>\n",
       "      <td>0.006453</td>\n",
       "      <td>0.000584</td>\n",
       "      <td>0.005869</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2023-03-15 00:39:51.820916</td>\n",
       "      <td>0.004974</td>\n",
       "      <td>-0.000900</td>\n",
       "      <td>0.005873</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2023-03-16 00:39:51.820916</td>\n",
       "      <td>0.007552</td>\n",
       "      <td>0.001674</td>\n",
       "      <td>0.005878</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         date     value   notrend     trend  weekday\n",
       "0  2023-03-06 00:39:51.820916  0.005036 -0.000797  0.005833        0\n",
       "1  2023-03-07 00:39:51.820916  0.004769 -0.001068  0.005837        1\n",
       "2  2023-03-08 00:39:51.820916  0.006293  0.000451  0.005842        2\n",
       "3  2023-03-09 00:39:51.820916  0.006932  0.001086  0.005846        3\n",
       "4  2023-03-10 00:39:51.820916  0.008666  0.002815  0.005851        4\n",
       "5  2023-03-11 00:39:51.820916  0.014102  0.008247  0.005855        5\n",
       "7  2023-03-13 00:39:51.820916  0.004139 -0.001725  0.005864        0\n",
       "8  2023-03-14 00:39:51.820916  0.006453  0.000584  0.005869        1\n",
       "9  2023-03-15 00:39:51.820916  0.004974 -0.000900  0.005873        2\n",
       "10 2023-03-16 00:39:51.820916  0.007552  0.001674  0.005878        3"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_nosunday = df[df.weekday != 6]\n",
    "df_nosunday.head(n=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 1, figsize=(14, 2))\n",
    "cor = acf(df_nosunday.value)\n",
    "ax.plot(cor)\n",
    "ax.set_title(\"Autocorrélogramme\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_pacf(df_nosunday.value, lags=50);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On décompose la série en tendance + saisonnalité. Les étés et Noël apparaissent."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from statsmodels.tsa.seasonal import seasonal_decompose\n",
    "\n",
    "res = seasonal_decompose(df_nosunday.value, period=7)\n",
    "res.plot();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Saisonnalité')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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DPvDAA/z5rVu3suHh4ezChQvZsrIy/lNZWelTXzxBUXsEQRAEEXr4sn6LkpDznXfeYbt3785qNBr2xhtvZH/++Wf+3C233MLOmDHDpf0XX3zBXn/99axGo2H79evXZkLOpKQkVqvVsmPHjmVLSkpc2lRWVrIPPPAAGxkZyer1enbmzJkuCTlnzJjhNvnWLbfc4lNfPEGCFEEQBEGEHr6s3wzLsqxk6rAOjtFoRHR0NGpqashfiiAIgiBCBF/Wb4raIwiCIAiC8BMSpAiCIAiCIPyEBCmCIAiCIAg/IUGKIAiCIAjCT0iQIjod5TUmvLv9BK7Wm6XuCuGB6gYz3tt+EqXVjVJ3hfBAo9mKv/94Eicv10ndFcIDFqsNH/73FA5eqJG6Kx0OEqSITsdHO0/jtfwSfFJwVuquEB74sugC/pJ/DCu2nZC6K4QHNh0px9LvjuHP3x2TuiuEB3afrsIr3x7FM+uKpe5Kh4MEKaLTwWmiTl2hHbScqeLG6XK9xD0hPMG/T6SRkjVXG5oBAL9W1OGS0SRxbzoWJEgRnY7GZisA4FxVg8Q9ITxB4xQaNDbbAADnrzbCZqO0hHKFe58AYNfJSgl70vEgQYrodDSa7RPK+SryvZEzppaJv6ymEc1Wm8S9IdqCW6DNFhsu1zVJ3BuiLVwFqSsS9qTjQYIU0engJpQrdU28UEXIj4aWsbGxQFk1mSLkSqPZwv//edIeyhbncdp5ohJU1CR4kCBFdDqcd2YXrtLEL1echdzzNE6yxfl9onGSL41mh1b3YnUjmcyDCAlSRKfDeYGmyUS+OC/QNE7yxXmBPldJ5nK54vw+AeQnFUxIkCI6HSbnHTQt0LKFxik0MJFGKiTgxkmjtC/7O0+Qn1SwIEGK6HS4miJoBy1XaJxCg0YSeEMCThM/4ro4AEDBSfKTChYkSBGdDjLthQY0TqGBiy8bjZNs4QTekdfFIUytRGW9GSUVtRL3qmNAghTR6TA1O3w6aOKXL87jdIHGSbY4a6TKjCaYLZSqQo5w46TXqXFDWiwAYNcJ8pMKBiRIEZ0Ki9UGs1NOogtXG0m9LVOcF+jKejPqmyweWhNS4ewjxbKg2ogyhRunMI0CI1vMe5RPKjiQIEV0Kkytdst1TRa+dAIhL1rn+CJHZnnSOhqMxkmecO9TmFqJm66LBwAUnqqChZLdBgwJUkSnoqElKR3DAIlRWgBk3pMjNhvLL9DJ0ToAlIlernCJU7lxIn82ecKNU5hGhcwUPfQ6FWqbLDh4sUbinoU+JEgRnQpTS86bMLUS3WPDAdAOWo40OWkO+yRFASCBV66YWhZoxziRwCtHeNOeWgmlgkE2b94jP6lAIUGK6FQ0Ok0mqZwgRRO/7HA2F12fGAmABF65wo1V3yQaJznjPPcBwMgW8x75SQUOCVJEp4KfTDQOQYpMEfKDGyeNSoEe8REASCMlR5qtNlhs9mCN60lzKGsanZzNAeCm3naN1N4zV10CBgjfIUGK6FQ4O1ymdgkDQPX25IjzOHUnzaFscdEckiAla7h3SteikbouIRKJUVo0WWzYd+6qlF0LeUiQIjoVJjcaKZr45YezPwcn8J6/2kCpKmQG5x+lVDDolWDXHF5taEYdpaqQFTYby/sdcqY9hmEcaRAon1RAkCBFdCq4HbTOyUfqYnUjrDZaoOWEswm2a5cwMIw96qiy3ixxzwhnnP1uonRqxISrAdDmRG6YLA7NYZhGyf//yN52P6md5CcVECRIEZ0KZ5ORQa+DWsmg2cqi3GiSuGeEM85mCK3KPlYALdByw3ljAoA3w5LfobxwzsmmUzkJUi0aqQMXalBronx6/kKCFNGpaGwVAtw1psVsRBO/rHCMk32KSu3CpaogPyk5wW9MNK3Gid4nWcG9T1qVAgoFwx/v1iUcPeLCYbWx2H26SqruhTwkSBGdCsfEb9+VkZ+UPHH2ZQOAbrEk8MqR1iH13DhdIIFXVrR+n5xxpEEgPyl/IUGK6FS0NkWQICVPGsyuCzRpOuRJY6txItOePOHep3C1O0HKbt7beYL8pPyFBCmiU9F6B00mI3nSOlSbstDLk2s2JiTwyhL+fXKjkeIynB8rr0VlXZOo/eookCBFdCq4CSWcN+2RyUiOcAt0+DUmWBJ45cS175N9nC5cbaRUFTKi9QbSmfhILdIN9hxgBafIvOcPggtSK1asQM+ePaHT6ZCVlYXdu3d7bL9u3Tqkp6dDp9NhwIAB2Lhxo8t5lmWxePFiJCcnIywsDDk5OTh+/LhLm6qqKkybNg16vR4xMTGYNWsW6urq+PMmkwmPPPIIBgwYAJVKhcmTJ1/Tj+3bt4NhmGs+5eXl/j8MQnJa+wpwO2gyRcgLU2vNYYvAe7G6karVy4jW71NKjA4MY1+4r9RRqgq50Pp9ag3nJ7WT8kn5haCC1Oeff4758+fjxRdfxL59+zBo0CDk5ubi0qVLbtvv2rULDzzwAGbNmoX9+/dj8uTJmDx5Mg4dOsS3ee211/D2229j5cqVKCwsREREBHJzc2EyOcLXp02bhsOHD2Pz5s3YsGEDduzYgTlz5vDnrVYrwsLC8OSTTyInJ8fjbygpKUFZWRn/SUxMDPCpEFLSVrj2pdomKpMgI1qbIpKidNAoFbDaWJTVUKoKudD6fdKqlEhuSVVBmxP50OjB2Rxw+EkVUD4pvxBUkFq2bBlmz56NmTNnIjMzEytXrkR4eDg++ugjt+3feustjB8/Hs8++ywyMjLw8ssvY+jQofjb3/4GwK6NevPNN7Fo0SLcfffdGDhwID755BOUlpZi/fr1AICjR48iPz8fH374IbKysjBq1Ci88847+Oyzz1BaWgoAiIiIwHvvvYfZs2fDYDB4/A2JiYkwGAz8R6Fo+5E1NTXBaDS6fAh50do5NiZcjUitCgBFGsmJ1qYIhYJBN6cM54Q8aDS7ZssGgG68eY/GSS5w46RrQyOV1SsWSgWDM5UNuFhN86CvCCZImc1mFBUVuWh8FAoFcnJyUFBQ4PaagoKCazREubm5fPvTp0+jvLzcpU10dDSysrL4NgUFBYiJicHw4cP5Njk5OVAoFCgsLPT5dwwePBjJycm4/fbbsXPnTo9tly5diujoaP6Tmprq8/cRwtK6cCfD0AItR9z5dPALNPlJyQZ340QO5/LDk48UAETp1BjYLRoAsIui93xGMEHqypUrsFqtSEpKcjmelJTUpp9ReXm5x/bcf9tr09r8plKpEBsb65N/U3JyMlauXIl//etf+Ne//oXU1FSMGTMG+/bta/OahQsXoqamhv+cP3/e6+8jxMGdr0B3SoEgO9zlveFq7pHJSD64GydKgSA/2vORAhzmPcon5TsqqTsgV/r27Yu+ffvy/x45ciROnjyJ5cuX45///Kfba7RaLbRarVhdJPygoVVYPUC5pORI6/QHAKVAkCPuxskRCUuaQ7nQOhGxO266Lh4rtp3EzhNXwLIsGIZpsy3himAaqfj4eCiVSlRUVLgcr6ioaNMvyWAweGzP/be9Nq2d2S0WC6qqqtr1h2qPG2+8ESdOnAjoHoS0uDdF0MQvN1on5ARI4JUjDe7eJxJ4ZUeDF4LU0B5doFEpcKm2CScv14vVtQ6BYIKURqPBsGHDsGXLFv6YzWbDli1bkJ2d7faa7Oxsl/YAsHnzZr59WloaDAaDSxuj0YjCwkK+TXZ2Nqqrq1FUVMS32bp1K2w2G7KysgL6TcXFxUhOTg7oHoS0mNxMKN3jyBQhN9yZIhypKkjglQvuNB2c5rCsxoRmSlUhC9rzkQLsWsXhPboAAHZR9J5PCGramz9/PmbMmIHhw4fjxhtvxJtvvon6+nrMnDkTADB9+nR07doVS5cuBQA89dRTuOWWW/DGG29g0qRJ+Oyzz7B37168//77AOyOwU8//TReeeUV9OnTB2lpafjDH/6AlJQUPhdURkYGxo8fj9mzZ2PlypVobm5GXl4epk6dipSUFL5vR44cgdlsRlVVFWpra1FcXAzA7lwOAG+++SbS0tLQr18/mEwmfPjhh9i6dSs2bdok5CMjBMajcyztoGWDu3BtboG+UteERrPV4+6aEAd3Am9CpBYalQJmiw1l1SZ+o0JIhzc+UgBwU+947DpZiV0nKjE9u6cIPesYCCpI3X///bh8+TIWL16M8vJyDB48GPn5+byz+Llz51zSCYwcORJr167FokWL8MILL6BPnz5Yv349+vfvz7dZsGAB6uvrMWfOHFRXV2PUqFHIz8+HTqfj26xZswZ5eXkYO3YsFAoFpkyZgrffftulbxMnTsTZs2f5fw8ZMgQA+Gy8ZrMZzzzzDC5evIjw8HAMHDgQP/zwA2699dbgPyhCNNwt0N1aBKlakwU1Dc2IDldL0jfCgbtxig5XI0qnQq3JggtXG9AnKUqq7hEtuBsnLlXFqcv1OH+1gQQpGeCpRIwzXLmYglOVsNpYKBXkJ+UNgjub5+XlIS8vz+257du3X3Psvvvuw3333dfm/RiGwZIlS7BkyZI228TGxmLt2rUe+3XmzBmP5xcsWIAFCxZ4bEOEFjYbC1PztXlvwjRKxEdqcaWuCeevNiA6PFqqLhItuMtPBNi1h0fKjDhPgpQsaJ2XjSO1S7hdkCJzuSzwxrQHAAO7RiNSq0JNYzOOlhnRvyvNhd5AtfaITkOTxeGv0dos1D2WQuvlRFumCC4i7FwljZMccJf+AKAUCHLDW0FKpVQgKy0WALCT8kl5DQlSRKeh0akEjE7VeoGmiDC5wLJsmyUtHCkQyOFcDrS1QPMpEGicZIGpVSJiT4zs3VJ3j/JJeQ0JUkSngZv0tSoFFK1s/+RwLh+arSysNruvYuuSFiTwyovWtfY4KLu5vHCX76stuMSce05XwWyhqEtvIEGK6DR4SkrnMEXQDlpqnDWH7nxvADIZyYW23qlUqrcnK7w17QFA36QoxEVo0NhsRfH5aoF71jEgQYroNLTlGAsA3VpMERdogZYczgyhVDBQK1tpDvkFupGPsCWkwWZjeb/Da017XKoKM+qbLKL3jXClLV82dygUDB+9R/mkvIMEKaLT4GlXxmk6LlxthM1GC7SUOGc1b12mgiswXddkQXVDs+h9Ixx40hxGh6mh19mDwi+Qn5TkcO9UuNq7QP2R19n9pHadID8pbyBBiug0tOXPAQDJ0TooFQzMVhsu1TaJ3TXCCU/+HDq1EolR9nqW5M8mLc6ClFZ17VJC/mzywDl4Q+eFszkA3NTbrpHaf/4qGsykUWwPEqSITgO3QIe7UW+rlAp0jaEUCHKAm/TdjRPgWKBpnKTFIfBeG7wBUAoEudBksYGzgnvjIwXYx65rTBiarSz2nLkqYO86BiRIEZ2G9vwEHFXraeKXkvbKWfApECgwQFJMvMDr3lxExYvlgck57YuXghTDMHz03i7KJ9UuJEgRnQZPpj2AUiDIhfbKWaR24XIU0ThJSXuRYPw4kcArKdw4qZUM1Ervl/yRvTmHc/KTag8SpIhOg6eoPYBMRnLBsUC7n566ke+NLHA27bmDUiDIA19ySDnDOZwfKq1BdYM56P3qSJAgRXQa2t1BcxM/7aAlpb1x6k6ClCxoK/s8h/PGhFJVSIcvOaScSdLr0DsxEiwL/HyqSoiudRhIkCI6De36SJHJSBa078tmX6AvVjfyGdAJ8WnPl40L3mgwW1FVTxoNqfAlh1RrRlI+Ka8gQYroNDS0o+LmNB3lRhOaLFa3bQjhac8UYdDroFYyaLayqDCaxOwa4UR7Poc6tRIGvQ4A1dyTkkaz+6Sp3sDnkyI/KY+QIEV0GtpTccdGaBCuUYJlgYs08UtGe+OkVDBIoVQVkuPNAs1FwtI4SUd7JlhPjOgVC4YBTlyqo02LB0iQIjoNJr4umPs/e4ZhnCL3SJCSivaCAgDyk5IDXKJGTws0FS+WHn6c/NBIxYRr0D8lGgCZ9zxBghTRafDG6ZJySUmPNzvobiTwSk57PlKAI8KSIvekw5tx8gSfBoHKxbQJCVJEp8GxQLddb4rKWkgPr5HypOkggVdy2vORAih5qhxoLy9bezj7SVH0pXtIkCI6Dd6YjCgpp/R4pTkkk5HkcD5SbZXyARyRsOQjJR2Nzf47mwPADT27QK1kcLG6kcaxDUiQIjoNjjDgtv/sU2kHLTnemCK6U/kRyfHOVG4fp1JKVSEZ/uaR4gjXqDAktQsAYCeZ99xCghTRafDJFEELtGR44yPFLdAVxiaXWmKEeHiTnyhJr4NGqYDFxqKshjYnUhBIHikOR7kYcjh3BwlSRKfBm51ZtxZTRHVDM4ymZlH6RbjiTUmLLuFqRLQsDBfI4VwSvBknpYJBVzLvSYq/JWKc4fykCk5WwkaaxWsgQYroNHjjxByhVSEuQgOA/G+kwhufDoZhHGZY0h5KgrcmI25zQqWXpCFQ0x4ADE6NQZhaicp6M0oqaoPVtQ4DCVJEp8EbZ3PAuSguTfxS4K0pwlEbkQQpKfA20SMJvNLSXhFwb9CoFLgxLRYAZTl3BwlSRKeAZVmvd2aU7FFavE0gyEXukclIGrzdmND7JC3cOIV7SPviDXzdvRPkJ9UaEqSIToHZagNn2m8vnwoVL5YWb306HLmkSHMoBd4EbwAk8EpNoHmkOG7qbfeTKjxdBYvVFnC/OhIkSBGdApPZ8eK3q+mgHbSkmJrbz08EUISl1Hjjcwg4CbwUFCAJwfCRAoCMZD2iw9Soa7LgwMWaYHStw0CCFNEp4CYTtZKBWun5z96xQNPELzYWqw1mq3cJBEnglRZvS49w79PlWkpVIQWBlojhUCoYZPeym/cKyE/KBRKkiE6Bt2YIwDVrNpVEEBeTxUlz2I6mg4sGM5osqGmgVBViw71T7WkOo8PUiNLa/XOo5p74NHqRiNhbbmrJJ7WT/KRcIEGK6BR46xgLAMkxOigYoMliw+XaJqG7RjjBjRMAaFWep6dwjQrxkVoAZN4TG+fgjfY2JwzD8JGw5CclPsHII8WR3ZJPau/Zq6RddEJwQWrFihXo2bMndDodsrKysHv3bo/t161bh/T0dOh0OgwYMAAbN250Oc+yLBYvXozk5GSEhYUhJycHx48fd2lTVVWFadOmQa/XIyYmBrNmzUJdXR1/3mQy4ZFHHsGAAQOgUqkwefJkt33Zvn07hg4dCq1Wi969e2P16tV+PQNCerwN1QYAtVKB5GhyOJcCZzMEwzDttqfixdLQZLGBU9Z6807xARwUGCA6wfKRAoDrEiKQpNfCbLFh39mrAd+voyCoIPX5559j/vz5ePHFF7Fv3z4MGjQIubm5uHTpktv2u3btwgMPPIBZs2Zh//79mDx5MiZPnoxDhw7xbV577TW8/fbbWLlyJQoLCxEREYHc3FyYTCa+zbRp03D48GFs3rwZGzZswI4dOzBnzhz+vNVqRVhYGJ588knk5OS47cvp06cxadIk3HrrrSguLsbTTz+Nxx57DN9//32Qng4hJr76CXSnHbQk+CLwAhQRJhXO2ghdO5pDgFIgSEkwSsRwMAzDZznfSeVieAQVpJYtW4bZs2dj5syZyMzMxMqVKxEeHo6PPvrIbfu33noL48ePx7PPPouMjAy8/PLLGDp0KP72t78BsGuj3nzzTSxatAh33303Bg4ciE8++QSlpaVYv349AODo0aPIz8/Hhx9+iKysLIwaNQrvvPMOPvvsM5SWlgIAIiIi8N5772H27NkwGAxu+7Jy5UqkpaXhjTfeQEZGBvLy8nDvvfdi+fLlwX9QhOA0+KjeptB6afDFBAs4R4TRAi0mnMCrUSqgaid4A3AEBpDAKy7NVhuarXbVYTA0UoBTPilyOOcRTJAym80oKipy0fgoFArk5OSgoKDA7TUFBQXXaIhyc3P59qdPn0Z5eblLm+joaGRlZfFtCgoKEBMTg+HDh/NtcnJyoFAoUFhY6HX/2+uLO5qammA0Gl0+hDzwVb3t7HBOiIfD78a7qak7ZaGXBIffjXfjRCkQpMFZcxgMjRQAjGzJJ3XgQg1qqR4pAAEFqStXrsBqtSIpKcnleFJSEsrLy91eU15e7rE999/22iQmJrqcV6lUiI2NbfN7femL0WhEY6P7yWDp0qWIjo7mP6mpqV5/HyEsJi9z3nB0j6MdtBR4m5uIgwReaWjw9X1yKudDkbDiwb1PCsauPQwGXWPC0DMuHFYbi92nq4Jyz1CHovaCyMKFC1FTU8N/zp8/L3WXiBZ81Uh1a1mgL9AOWlR81hzGOsaJqtKLh68+h9z7VNtkQU0jaTHEotHH4A1v4bRSO0+QeQ8QUJCKj4+HUqlERUWFy/GKioo2/ZIMBoPH9tx/22vT2pndYrGgqqqqze/1pS96vR5hYWFur9FqtdDr9S4fQh747MTcYoooq2lEM5VDEA2HRsq7umDJ0TooFQzMVhsuUaoK0fAlLxvXLiHKnqqCtLzi4eu85y0OPylyOAcEFKQ0Gg2GDRuGLVu28MdsNhu2bNmC7Oxst9dkZ2e7tAeAzZs38+3T0tJgMBhc2hiNRhQWFvJtsrOzUV1djaKiIr7N1q1bYbPZkJWV5XX/2+sLEVr46sScEKmFTq2AjQVKq0krJRa+VqpXKRVIidEBIIdzMXEUwvV+gSZ/NvEJZg4pZ7gM58fKa3GljjYwgpr25s+fjw8++AAff/wxjh49iieeeAL19fWYOXMmAGD69OlYuHAh3/6pp55Cfn4+3njjDRw7dgwvvfQS9u7di7y8PAD20Munn34ar7zyCr7++mscPHgQ06dPR0pKCp8LKiMjA+PHj8fs2bOxe/du7Ny5E3l5eZg6dSpSUlL47zpy5AiKi4tRVVWFmpoaFBcXo7i4mD//+OOP49SpU1iwYAGOHTuGd999F1988QXmzZsn5CMjBMLXEGCGYSi0XgL8KWfBj1MljZNY+KPpoGLg4hPMHFLOxEVqkW6IAkDlYgDAO/25n9x///24fPkyFi9ejPLycgwePBj5+fm8E/e5c+egUDhkuZEjR2Lt2rVYtGgRXnjhBfTp0wfr169H//79+TYLFixAfX095syZg+rqaowaNQr5+fnQ6XR8mzVr1iAvLw9jx46FQqHAlClT8Pbbb7v0beLEiTh79iz/7yFDhgAA7wiZlpaGb7/9FvPmzcNbb72Fbt264cMPP0Rubm7wHxQhOL6aIgC7/83xS3W0gxYRX53NAU6QqqQFWkT8EngpBYLoBDOHVGtu6h2PY+W12HWyEncOSmn/gg6MoIIUAOTl5fEapdZs3779mmP33Xcf7rvvvjbvxzAMlixZgiVLlrTZJjY2FmvXrvXYrzNnzng8DwBjxozB/v37221HyB9fTXsA7aClwB+Bl4uwJIFXPPwxGVGEpfg0mu3+ncE27QH2unv/+Ok0+UmBovaITkKDj743AO2gpcAfU0S3LlQmRmwam+0LtD8aKYqEFQ+hTHsAcEPPWCgVDM5WNnT6YtQkSBGdAl/zSAFOEz8t0KIRiMmINIfi4ZePVEsk7MWrjbBSqgpREFKQitKpMahbNADKck6CFNEp8MtHijNF0A5aNHxN9Ag4osHKjSY0WagivRg0mi0AfFugk6PDoGpJVVFhNLV/AREw3Dj5El3pC1zdvV0nOrd5jwQpolPgz86M20FX1ZtR12QRpF+EK/743sRFaBCmVoJlgdJqWqDFwJ+NiVLBoCuZYUWF95ESSpDq7ai715kz1pMgRXQKHHlvvI+viNKp0SVcDYAmfrHgFmhfdtAMw/BCL/mziQO3QPsaDUZaXnER0rQHAEO7d4FWpcCl2iacvFwnyHeEAiRIEZ0CRxiwb3/yvP8NLdCi4I+PFEARYWLj9ziRwCsq/o6Tt+jUSgzv2QVA5/aTIkGK6BT4Y4oAaActNvw4+arpIIdzUfG39Ahfw5IEKVHwJy+br3B+Ujs7sZ8UCVJEp8CfPFIAaaTEhsYpNPB3nLqTwCsq/m4gfYGru/fzqapOG41JghTRKTA1++nTEUvOsWJi8iM/EeCUPJWScoqCv743qVRvT1SE9pECgAFdoxGlVaGmsRlHSo2CfY+cIUGK6PBYrDaYrf4u0LSDFhN/TUZ8dnMaJ1Hwt/QIJ/CWG038PQjh8Nc31BdUSgWyesUCAHZ20iznJEgRHZ5GpwnbVxW3c8X6zhzeKxZ+m/ZaBN7qhmYYTc1B7xfhir8mo9gIDSJahK+L1aSVEhp/3ydf4fNJdVKHcxKkiA4PN+kzDKBV+fYnnxITBoax3+NKnVmI7hEtsCzr9wIdoVUhNkIDgMywYuDvAm1PVUH+bGIhho8U4Mgnted0FcwWm6DfJUdIkCI6PCazw6zHMIxP12pUCiTrdQDIbCQ0nH8U4F+UEflJiUcg0WDdKFWFaPiTP88f+iZFIT5Sg8ZmK4rPVwv6XXKEBCmiwxOowyXtoMXB2QTrz1g5iuLSOAlNIO+UI3KPBF6hEcPZHLBrGrM7cRoEEqSIDo+/DswcJEiJAzdOGpUCSoVvmkPAMU6U7FFYmq02WFrC3P0TeCkSViwaRXA25+DSIBR0Qj8pEqSIDk+gDpeOrNm0gxaS4I0TLdBC4hK84ccCTZGw4uFP7Up/ualFI7X//FU0mDtXbVISpIgOj7+h2hz8DpomfkEJtJwFmYzEwdSyOCsVDDRKPwQpTnNYSe+TkNhsLJos/qV98YfU2DB0jQlDs5XF7tNVgn+fnCBBiujwBBq5QtmYxSFwE6zDZESpKoTD2e/G1+ANwDFORpMFNY2UqkIoTBYnn0MBS8RwMAyDm3p3TvMeCVJEhydgk1GLIFVabYLF2vlCe8UiUDNESkwYFAzQZLHhcm1TMLtGOBHoxiRco0J8JKWqEBrufQIAnUp4QQoAburd4nDeyRJzkiBFdHgaAjQZJURqoVEpYLWxKKsxBbNrhBMOTYd/05JaqUByNJlhhcaR+sD/5YNSIAgP9z5pVQoo/Aje8IfsXnaN1OFSI6obOk/ePRKkiA6PKcAK6AoF45SjiCZ+oQjUlw1wNu+Rn5RQBCOknszlwhOM98lXEvU69EmMBMsCP5/qPOY9EqSIDk8wsvtSaL3wBKOcBRcRRuMkHIEGBQAk8IpBY0si4nARHM2d4dIgdKZyMSRIER2eYOygKWRbeBqCEKpNOb+EJyjjRO+T4HApCHQiaqQAYGTvzpeYkwQposPjKJNAO2g5wwm8QRknWqAFI5DyMByk4RUesbKat2ZEWhwUDHDycj3KO4lPKQlSRIcnGL4CPeIiAABHyoxB6RNxLcEwGXHjVFJeC6uNUiAIQTDGKS3ePk5nrtTj0MWaoPSLcCUY4+QP0eFq9O8aDQDYcfyyqN8tFSRIER2eYPhIjUiLg0rB4MSlOpy+Uh+srhFO8OkPAhB4B3SNRnSYGlcbmrH3TOdKCigWwdB0pMSEYdLAZNhYYOFXB0noFYBA87IFwtj0JADApsPlon+3FJAgRXR4guHEHB2uRnaLE+X3nWRyEJtgLNBqpQJjMxIBAN8frghKvwhXOCfmQBfoF+/MRJROhYMXa7B615kg9IxwhhsnMcrDtCa3v12Q2nH8CuqbOn65GBKkiA5PsAp35vYzACBBSiiC5dMx3mmcKMN58AnWOCVG6fDCxAwAwBubSnCB/NqCilQ+UgDQNykKPeLCYbbY8OOvHd+8R4IU0eEJhkYKAMZlJoFhgP3nqlFh7BxOlGISrLw3o69PQJhaiYvVjThcSj5twSaY+YnuH56KG3vGosFsxR/WHyLBN4hI5SMF2MvFjO9EG08SpIgOTzB8pAB7srkhqTEAgE1HyGwUbIJVqV6nVuKW6xMAdB4fDTEJ1jgB9mS3r94zABqlAttKLmPDgbKA70nYCUZ0ZSCMaxGkth69BLOlY5fWIkGK6PAEU8XNm/cO0QIdbII6Ti0+GvkkSAWdYJuMeidGYu6tvQEAf/zmMGoaqJBxMAjWBtJfhqTGIDFKi9omC3Z18Np7oghSK1asQM+ePaHT6ZCVlYXdu3d7bL9u3Tqkp6dDp9NhwIAB2Lhxo8t5lmWxePFiJCcnIywsDDk5OTh+/LhLm6qqKkybNg16vR4xMTGYNWsW6urqXNocOHAAN998M3Q6HVJTU/Haa6+5nF+9ejUYhnH56HS6AJ4EIQWBlohxhhOkfj5VSRN+kAmWCRYAbuubBJWCwa8VFGUZbBoE0HQ8PqYXeidG4kqdGUu/Oxq0+3ZmGoKQPy8QFAoGt2faNzQdPfBDcEHq888/x/z58/Hiiy9i3759GDRoEHJzc3Hp0iW37Xft2oUHHngAs2bNwv79+zF58mRMnjwZhw4d4tu89tprePvtt7Fy5UoUFhYiIiICubm5MJkcfivTpk3D4cOHsXnzZmzYsAE7duzAnDlz+PNGoxHjxo1Djx49UFRUhL/+9a946aWX8P7777v0R6/Xo6ysjP+cPXs2yE+IEJpg7qB7xkegb1IULDYWW4517MlBbIIZrk1RlsIhhO+NVqXE0nsGAAA+23O+U9VpEwopfaQ4uI3n5iMVHTrFheCC1LJlyzB79mzMnDkTmZmZWLlyJcLDw/HRRx+5bf/WW29h/PjxePbZZ5GRkYGXX34ZQ4cOxd/+9jcAdm3Um2++iUWLFuHuu+/GwIED8cknn6C0tBTr168HABw9ehT5+fn48MMPkZWVhVGjRuGdd97BZ599htLSUgDAmjVrYDab8dFHH6Ffv36YOnUqnnzySSxbtsylPwzDwGAw8J+kpCThHhYhCMHOp5Lbj9tl0QIdTII9TuM6kbOrmAhlMrqhZyymZXUHALzw1UFeECD8Ixh52QJlRK84ROlUuFLXhP3nrkrWD6ERVJAym80oKipCTk6O4wsVCuTk5KCgoMDtNQUFBS7tASA3N5dvf/r0aZSXl7u0iY6ORlZWFt+moKAAMTExGD58ON8mJycHCoUChYWFfJvRo0dDo9G4fE9JSQmuXnUMeF1dHXr06IHU1FTcfffdOHz4cJu/t6mpCUaj0eVDSIvNxsLU3JL3JkgTP7dA//jrZX6yIgKHz08UrHFqMStQlGVwEdKJecH4dCRGaXHqSj3e3XYi6PfvTEiZ/oBDo1JgbDqX163jbmgEFaSuXLkCq9V6jRYnKSkJ5eXuH2p5ebnH9tx/22uTmJjocl6lUiE2Ntaljbt7OH9H37598dFHH+E///kPPv30U9hsNowcORIXLlxw2/elS5ciOjqa/6SmprptR4hHk1O0SLAm/n4penSNCYOp2dZpSiCIQbBNEUl6HYZ0jwFAUZbBREiTUXSYGn+8qx8A4L0fT+LXitqgf0dnQQ6CFOCcf6+iw6a3oKg9D2RnZ2P69OkYPHgwbrnlFnz11VdISEjA3//+d7ftFy5ciJqaGv5z/vx5kXtMtKbRyTygUwVnQmEYhpJzBhmWZQUpacHlsqE0CMEjGMWlPTG+vwE5GUlotrJY+NVB2Dqwb42QmIKUiDhQbumbAK1KgXNVDThW3jEFY0GfcHx8PJRKJSoqXHeDFRUVMBgMbq8xGAwe23P/ba9Na2d2i8WCqqoqlzbu7uH8Ha1Rq9UYMmQITpxwr3LWarXQ6/UuH0JaGsz28gRalQIKBRO0+47vb/8b+eFIBZqtHTtHihg0W1neGTWYvjecwFtwkqIsg4XQYfUMw2DJ3f0QoVGi6OxVrNl9TpDv6egEM99XIIRrVLi5jz2vW34HTRsjqCCl0WgwbNgwbNmyhT9ms9mwZcsWZGdnu70mOzvbpT0AbN68mW+flpYGg8Hg0sZoNKKwsJBvk52djerqahQVFfFttm7dCpvNhqysLL7Njh070Nzc7PI9ffv2RZcuXdz2zWq14uDBg0hOTvblMRASEswszM4M69EFcREaGE0WFJ6i4riB4qw5DKYpgqIsg48YiR5TYsKwYHw6AOC1746hvIZ83HxFLqY9wLHx7KgafMF1fvPnz8cHH3yAjz/+GEePHsUTTzyB+vp6zJw5EwAwffp0LFy4kG//1FNPIT8/H2+88QaOHTuGl156CXv37kVeXh4A+27l6aefxiuvvIKvv/4aBw8exPTp05GSkoLJkycDADIyMjB+/HjMnj0bu3fvxs6dO5GXl4epU6ciJSUFAPDggw9Co9Fg1qxZOHz4MD7//HO89dZbmD9/Pt+XJUuWYNOmTTh16hT27duHhx56CGfPnsVjjz0m9GMjgkSwHZg5lC45Ujrm5CAmnMCrVDBQK4OnOQQoyjKY2Gws73co9AL90IgeGJwag9omC176uu0gH8I9Qm0i/SEnIxFKBYNj5bU4V9nxaioKLkjdf//9eP3117F48WIMHjwYxcXFyM/P5x27z507h7IyR1mAkSNHYu3atXj//fcxaNAgfPnll1i/fj369+/Pt1mwYAF+//vfY86cObjhhhtQV1eH/Px8l2SZa9asQXp6OsaOHYuJEydi1KhRLjmioqOjsWnTJpw+fRrDhg3DM888g8WLF7vkmrp69Spmz56NjIwMTJw4EUajEbt27UJmZqaQj4wIIkLuyjiz0aYj5eTHESDOyTgZJriCFEVZBg+TRRjNoTuUCgZL7xkAlYJB/uFyEoR9hPtbD1erJO4JEBOuQVZaLICOuaFh2I7qRi8DjEYjoqOjUVNTQ/5SEvHjr5cx46PdyEzWY+NTNwf13k0WK4a9/APqmiz49+9GYkh39yZhon2OlBox8e3/Ij5Si72Lctq/wAdYlsWov2zDxepG/P3hYbwATPjOlbomDH/lBwDAqVcnBtXvsC1eyz+Gd7efhEGvw+b5oxGlUwv+naEOy7Lo9cJGsCyw+/+NRWKU9BU5Pt51Bi9+fRjDe3TBl0+MlLo77eLL+k1Re0SHplHAMglalRJj+tqdKDt6CQShETISjKIsg4fDgTm4wRueeHJsH/SMC0e50YS/fl8iyneGOk0WGzgViRx8pABgXIuJvejcVVyubZK4N8GFBCmiQyO0n0CuU3g9KXf9R+hyFpyf1JajlyjKMgCkKDuiUyvx6m/s5WP++fNZFJ3tuBmyg4VzVnipo/Y4kqPDMKhbNFjWXjKmI0GCFNGhETpUe0zfBGiUCpy6Uo8Tl+rav4Bwi9DlLIb3jEVchAY1jc3YfZqiLP1Fqkiwkb3jce+wbmBZe/kYs4WEYU9w46RWMlAr5bPMd9SyTfJ5wgQhAM5OzEIQpVPjpt724rgdNUeKGDgWaGGmJKWCQU4GRe8FihipD9ri/03MQGyEBiUVtXh/x0nRvz+UkEsOqdZwGvxdJ6/AaOo4ed1IkCI8YrHacLG6Uepu+I0YO2je/+ZI6C3Ql4wmWRSHFWOcnHPZhFqUZVW9GfVNFqm7IUj2eW/pEqHB4jvsEdNvbz2BU5flpwGuaWhGrQwEBDnlkHKmd2IkrkuIQLOVxbZjl9q/IEQgQYrwyLvbT+KmP2/Fv/e7ry8od8TYQedkJkHBAIcuGnHhaujkSPnlfDVG/WUbnvpsv9RdESXnzcjecYjUqlBhbMIvF6oF+55gc6nWhDF/3YYZH+2WuiuS+Eg5c/fgFIy+PgFmiw0v/PugrPwSG8wW5L65A3f9bSefpV8q5JRDqjUdMfCDBCnCI9wf+8rtp2Q1aXmL0D5SABAfqcXwnvYcKZtCKHrv3e0nYLbasL3ksuQO2GKYIkI1yrLgZCWMJgv2nr2KqnqzpH0R433yBMMw+NPk/tCpFfj5VBXWFclng1d8vhrlRhNOy8BfUqhExMGA0wxvL7ksC214MCBBimiT+iYLjpYZAQAlFbXYcyb0omXEUnGH2i7rzJV6bGqJnGmy2PBrhbTFRMUep1CKsnSOUjsgsSZNDgt0amw45t9+PQDgT98elU0o/T6ncZJa4ym1wOuJAV2jkRKtQ4PZip+OX5G6O0GBBCmiTX45Xw1nDfWnP5+VrjN+YuJNe8L+qY9rKRez50wVKuvkMbF74h8/nYazHHHgQo10nYF4glQoRlm6ClIyGSeJTUaP3pSGfil61DQ24+UNRyTtC4esBF4B87IFCsMwHS56jwQpok32nbNPDH2TogAA3x0qk83uz1vEWqBTY8PRL0UPG2vPVSRnrtabsa7oPABgSPcYADKY+EWKBnOOsgyFSby+yYJj5Q5tofTjZHd4l9pkpFIq8Od7BkLBAF//UoptJdK+czYbi/3nq/l/Sy7wymSc2oJLzvnD0QpYOkBeNxKkiDbhdlhTb0zFkO4xaLay+GLveYl75RuOHbTw9aZCxby3pvAsTM02ZCbrMefmXgCAX85LPfGLp+lwjJP8/aR+uVANq40Fl0T8lws1kpok5WQyGtAtGo/elAYAWPTvQ2gwSxfVeOpKPaobmvlxOlpmRJNFOv8fofOyBcqNPWPRJVyNqw3NIeky0hoSpAi32Gws9p2rBgAM69EFD4/oAQBY8/NZySNSfEHoPFLOcAv0f49fQZ0MQtXdYWq2YvUuu4l29ug0DEyNAWD3gZPS8VPMcG0uyvLgxRrZp/bg/G5uS0+EUsHgcm0Tyo0myfrD+0jJZIGed/v16BoThovVjVi26VfJ+sGN0/AWAaHZyuJYmXR+h43N0vuyeUKlVGBsB8rrRoIU4ZZTV+pR09gMnVqBjGQ9Jg5IRpdwNUprTNgaQvk/HGHAwv+pX58UiZ5x4S2RcPJ8Rl8Xl+JKXRMMeh3uGJiClGgd4iM1sNpYHC41StYvMcPq4yO1GN6Di7KU9yTObWZGXheP61tM7FJqD+WWnyhCq8Irv+kPAPho52kclMikxrlBDOvRBQO6xQCQ1gwrt3FyRygGfrQFCVKEW7gd1sBuMVArFdCplfifG1IB2OtdhQpimiJci+PKz2zEsiw++O8pAMDMm3pCrVSAYRgMlNPEL5Kmg/PRkHM2ertW2LFAD+oWDUDacTLJ0In51r6JuGtQCmws8PxXByTxueHcIIZ1d4zTLxL6Sck5jxTHzX3iEa5RorTGhIMXpXUtCBQSpAi38BNDjy78sWk39gDDADt+vYwzV+ql6ppPNIho2gMctaS2HbskqY+EO7b/ehnHL9UhUqvCA1nd+eMD+QVaQk2HyCUtOIFXzlGWnN+NTq1AZoreSeDtPOPkLX+4IxPRYWocLjVi1c4zon53TUMzjrdEgA7t0UUeGxOZjpMzOrUSt1zP5XWT74bGG0iQItxSdM6xw+LoHheOMS1/+GsKQ0MrJfbObEhqDBKjtKhrsmDXyUpRvtNbPthh10bdf0Mq9Do1f3xQy8QvZe4bsX06QiHKktcKd7VrhQc6aaSkMoXI1WSUEKXF/5uYAQBYtvlXnK8Sr8LAvvP2cUqLj0BshIbXSJ24VCdZWR+5jlNr5KzB9wUSpIhrqGlo5nPscOHxHA9n253Ov9h7ISSy0orpbA4ACgXDm43k5H9zuLQGu05WQqlgMPOmni7nuAX61OV6yQqJSmGKkHuUJWfWG9qiFe5riIJGpYDRZMGZSmlKEcklj5Q77hveDSN6xaKx2Yr/t/6QaMLm/haBd2jLpjNRr4NBr4ONBQ5JZLISugh4sLg1PRFqJYMTl+pwUoa1E71F3k+ZkATnHVZcpNbl3C3XJ6JblzDUNDZjw4EyKbrnNSzLSrIz4xbozUcqZBPh+OF/TwMAJg5IRrcu4S7n4iK16BoTBgA4JJHZSGyBF3CKsjwhzyjL1uZ1tVKBzGQ9AOnMRlLX2vMEwzB49TcDoFEpsOPXy/j6l1JRvrfo3LVuEAMkNpebREwnEgjRYWpkXxcPQL4bGm8gQYq4hn2tdljOKBUMpmXZtVJydzo3W218ZnYx86mM6BUHvU6FK3VmXqsgJWU1jfimZVGZfXOa2zaDUlsmfol20FwOIDF9OvgoS4sNP5ZcFu17vcHF78ZJKzxI4gW6Qea+N70SIvHkbb0BAEu+OYKrAtcmtNpYFLdEVg7tEcMf58dJsvdJvPx5gZLbj0uDELrmPRKkiGvY52aH5cz/DO8GjVKBX85XS55p2RMmsyN6R8wdtNopR4ocosJW7zwDi41FVlos7wjbGqkdZE0tPlJiRoO5RllKP07O7G/RCveMC3fRCks9TmImTvWXOaOvw/VJkaisN+NPG48K+l0l5bWoN1sRpVWhT2IUf1zycZKx5rA1t2cmgWHsJcnKauSd160tSJAiXLBYbW53WM7ERWoxcYB9AZJz/T1uMlErGaiV4v6pO3ZZ0uZIqTU1Y23hOQDA7JYs5u4Y2LUlZFuCHEUWqw1mqzQJBOUaZclrhVttZjjN4aGLRknC/OVs2uPQqBRYes9AMAzwZdEF7DohXGFczqw3uHsMlFxaczj8Ds9WNqC6QVitmDtCYZw4EqN0vPVjU4hqpUiQIlwoqXC/w2oN53T+n+JS1DRI46DcHlKWsxh9fQK0KgUuXG3EkTLpEl1+vuc8apss6JUQgdvSE9ts179l4r9Y3Sh6OgCTxUlzKLKmg4uyrJVZlKU7vxsA6BUfiUitCo3NVpyQwDk3VDQdw3p0wUMtLggv/PugYIEx+9ykiQGAmHANesTZfRGlMMM2ipiIOBg4bzxDkdB4yoRocJmUW++wWjO0exdkJOvRZLHxBXDlhhQOzBzhGhVG8zlSpNllWaw2PqfOY6N6QeFhPPU6NXolRAAQf+LnxgkAtCpxpySFgsHtmfKKsnTxu2nlp6hQMOjftcXhXGTtoXPwhi4EFugF4/vCoNfhTGUD3tl6XJDv4CMr3fiTSmneC4U8Us5wJvbC01WC+7UJgfzfBuIaTlyqw1Of7cfcNfuCfm9PjubOMAzjqL9XeA42mUSnOdPY3FIBXSJ/DucSCFKw8VA5LlY3Ii5Cg3uGdm23vVT5pJzNEAzTtrAnFOP7O6Is5VCJnvO7idSq+LIwzkg1Tk0WGzgrdXgIODFH6dT44939AAB///EUSsqDW/vucm0TzlY2gGHsG8/WSJnhPFQ0hxw94iKQboiC1cZiSwiVIOMgQSoEUTB2k9r3h8uDbn93l9G8Le4enIIorQqnr9Rj50nh/BD8hS+wKtFkkpNhLzR7rLwWp0XOBM+yLJ+A8+HsHl7tTKXKcC51bqIRveLQJVyNK3Vm0bNiu4Mz6w1pQyssVYZzZ/OYTmTNob/k9jPg9swkWGwsVu86E9R7c9qovklRLgluOaTUSIVCiZjWcBvP/EPyTqvjjtB4GwgXeiVEIt0QBYuNxeYjwTMbXa5twrmqtndYrYnQqjBlWDcAwD8L5Od0LqWPFGD3kxh5XRwAYONBcSeHwtNVOHixBlqVgtcctofzxC+mg7yUJljAHmX53Ph0AMDrm0pEF3pb055WmBN4j5UbRXWQ594njVIBlcjBG4EwI7snALtmOJgaR26chrQxTv276qFggApjEyqMpqB9b3s0W21ottrf31DRSAHAhJYAph3Hr6BWosTA/hI6bwPhwoT+yQCA74IYXt/eDssdD42w12z74WiF7EJX5aDenjiAGydxBakPW4oTTxnW7Zqkqm3RL0UPlYLBlTozSmvEm/gdAq9009H9N6Tipt5xaLLY8NyXByQ1VbfOaN6abl3CEBuhQbOVxdGy4JqrPOHwuwmtZSOrVyy6hKtRWW/G7jNVQbtve2liwjWOgJ1fzlcH7Xvbw0VzGEKCVN+kKPRKiIDZYsPWEDPvhdYbQfBMGtiSlfn45aCV9Whvh+WO3olRGNErFjYW+L+WMHu5IIfsvuMyk6Bg7OHq50Qq63Hych1+aKkfN2uU+wSc7tCplbxPzgERJ36pTXuA3efvz/cMRLhGid1nqiRLNuvid5Ma47YNwzAudffEQg7j5A9qpQLjMu3z5XcHg7PxNFtsvO+TJzcIKczl3DgpGPGDNwKBYRhMbFEQiK3BD5TQecqEC70To9AnMRLNVhY/BMm854t/lDMPj+gJAPi/PedhtkjvrMshB41UXKQWI3rZzXtiaaW4cjA5GUm4LiHSp2u5PEViOshKbdrjSI0Nx/MT7Ca+v+QfE7XwLQen5bg+MQrRYW1rhTkzrJh5v+QyTv7AmY3yD5cHpWzT4dIamC02xEZo0DMuvM12A1uEYTEDA5zHSYrgjUDgxml7yWXJCj77AwlSIcyEAZz0Hvguy2yx8eUMfBWkxvVLQkKUFpdrm7DpiDxCyAH57KD5cRIhy/mVuiZ8te8CgLbLwXhCCgfZRhmVs3goqwdu7BmLBrMVz391QPRkqg6zXozHdoMk1EiFkrmIY+R18dDrVLhc24S9QTDv7ePTU8R4FFa4cTp4sUa0vyW5zHv+kJmsR4+4cDRZbNhWEjrmPRKkQpiJvHPe5YCd87zdYblDrVTggRvtvlJycjqXyw46t5+jBMKFq8JqOf5ZcBZNFhsGdYvGjWmxPl/PmSIOXqgRzU9ITpXqFQoGf7l3ILQqBXaeqMRne8TNkeZt+hFO4D1xuU60gsuhUB6mLTQqBW7nzHtB2NC0lXm+NekGPTRKBaobmnFOJA1nqOWQcoZhGIf/b5DMsGIgysy1YsUK9OzZEzqdDllZWdi9e7fH9uvWrUN6ejp0Oh0GDBiAjRs3upxnWRaLFy9GcnIywsLCkJOTg+PHXROuVVVVYdq0adDr9YiJicGsWbNQV+eaCfjAgQO4+eabodPpkJqaitdee83nvkhJ36Qo9IoPjnNeET+Be95htcUDN6ZCqWBQeLoKv1aI5wDrCbmEACdG6XBjT7tQI2TtPVOzlffteezmXn6N4/VJUdCqFKhtsuB0pTjRa3IrZ5EWH4Fnc/sCAP707VGUVosTROGt3w0AJERpkRKtA8sCh0QqjCsHU3kgcH6l3x0qC3iTUOSlwKtRKZCR3OJwLpK5POTHqUWDv/XYJZdkvXJGcEHq888/x/z58/Hiiy9i3759GDRoEHJzc3HpkvuFf9euXXjggQcwa9Ys7N+/H5MnT8bkyZNx6NAhvs1rr72Gt99+GytXrkRhYSEiIiKQm5sLk8kRaTRt2jQcPnwYmzdvxoYNG7Bjxw7MmTOHP280GjFu3Dj06NEDRUVF+Otf/4qXXnoJ77//vk99kRKGYXibcqDS+36+vp5vZj2O5Ogw3N5SqFcu9ffkZIqYOEB4J8qv9l1EVb0ZXWPCMKElyaSvqJUK9EtpyZwtktlIjpqOmTelYUj3GNQ1WfDCvw+KYpbhtMJdwtVIi49ot73YZli5Cby+clPveERpVagwNvFFof2htLoR5UYTlAqGT47qCX6cRArgkMsG0l/6d9WjW5cwNDZbsT1EzHuCC1LLli3D7NmzMXPmTGRmZmLlypUIDw/HRx995Lb9W2+9hfHjx+PZZ59FRkYGXn75ZQwdOhR/+9vfANi1UW+++SYWLVqEu+++GwMHDsQnn3yC0tJSrF+/HgBw9OhR5Ofn48MPP0RWVhZGjRqFd955B5999hlKS0sBAGvWrIHZbMZHH32Efv36YerUqXjyySexbNkyr/siB7gFelvJJb+d81iWxd6zdr+B9nZYnuDq732176Jo5gZPNMjEtAc4smfvOydMhXObjeVTHjw6Ki2gPD9iOzLLSeDlUCoY/PXegdAoFdhechlf7bso+HfucyoL4402cYDImbPlKPD6glalRE5LOaBA/Eo5bVS/FL1Xz0LsyD0uEbGc3idfYBjGsfEUwa80GAgqSJnNZhQVFSEnJ8fxhQoFcnJyUFBQ4PaagoICl/YAkJuby7c/ffo0ysvLXdpER0cjKyuLb1NQUICYmBgMHz6cb5OTkwOFQoHCwkK+zejRo6HRaFy+p6SkBFevXvWqL61pamqC0Wh0+QhNMJzzSmtMqDA2eb3DaouR18WhV0IE6posWL9f+IWnPeTke5Ok12F4i7ZPCPPe1mOXcOpKPaJ0Ktx/Q2pA9+Ii90TTSMlU09E7MQpP5fQBAPzxm8O4JHBSRW/9bjgGiayRamyWtlJAMOA0td8d9N+8561Zj2NQS+TeodKaoEQMtodc3ydf4MZp69EKwQpOBxNBV5grV67AarUiKSnJ5XhSUhLKy90vJuXl5R7bc/9tr01iomule5VKhdjYWJc27u7h/B3t9aU1S5cuRXR0NP9JTQ1sQfOGYDjn+brD8tQXruL6pz+fFT3iqTVyyCPlDBe9J4QT5fst2qgHs7ojUhtY9BunkTpcakSzCLXn5GwymjO6F/p31cNosmDR+kOC/k37mn6E00idr2pElQiFXkM5Goxj9PUJiNAoUVpj8jslQXsJU1tzXUIkwjVKNJitOHGprv0LAqQjCFKDU2OQEq1DvdmKHb9elro77SL9Vr0DsXDhQtTU1PCf8+fFifjhovf8dc7zNlLIG6YM6wadWoFj5bX8wiAVcjMZcbusPWergqrd+OV8NXafroJKweCRkT0Dvl9aXASitCo0WWyiBA7I2WSkVirw13sHQaVgsOlIBTYcEMbHzdnvhjMFtUd0mMOXSgytlJwFXm/RqZW4rcWX05/ovUazFUdK7ZYGbwVepYJB/66cGbba5+/0FbltIP2BYRiMD6HknIIKUvHx8VAqlaiocE0YWVFRAYPBvTOswWDw2J77b3ttWjuzWywWVFVVubRxdw/n72ivL63RarXQ6/UuHzEY0DWad8778VffzXu+7rA8ER2mxt2DugKAZNmhOeS2M0uJCcOQ7jFgWXtiwGDxQYs26q5BKUiODgv4fgqnif+gCH4dDTIP185I1mPurb0BAC9+fRiVdU1B/w5u05GZrEe4D/m0nNNVCE2D2e73KNdx8pZJLRvPjQfLfNYwHrhQDYuNhUGvQ0q0zuvrBok6TqEvSAGOKMsfjl4StaakPwgqSGk0GgwbNgxbtmzhj9lsNmzZsgXZ2dlur8nOznZpDwCbN2/m26elpcFgMLi0MRqNKCws5NtkZ2ejuroaRUVFfJutW7fCZrMhKyuLb7Njxw40Nze7fE/fvn3RpUsXr/oiF1yc83w0G/mzw2oPzul848EyXBFg0fEWTtPhy8IkNMEugXDhagO/s37s5l5BuScADBQxwzkn8IbLeOKfe2tvpBuiUFVvxotfHw76/f2tKsAHBogxTi1OzKG+QN9yfSLC1EpcuNqIQxd982MtckqY6kt6ETEjLOW2gfSXIaldkKTXoq7Jgp+OX5G6Ox4R3LQ3f/58fPDBB/j4449x9OhRPPHEE6ivr8fMmTMBANOnT8fChQv59k899RTy8/Pxxhtv4NixY3jppZewd+9e5OXlAbALDU8//TReeeUVfP311zh48CCmT5+OlJQUTJ48GQCQkZGB8ePHY/bs2di9ezd27tyJvLw8TJ06FSkpKQCABx98EBqNBrNmzcLhw4fx+eef46233sL8+fO97ouc4MxGW3x0zvN3h+WJ/l2jMTg1Bs1WFp+LnNDQGUcYsHws2Fz03u7TVbhcG7iQuWrnGVhtLG7qHYfMlOBpQMV0ZA4Fk5FGZTfxKRUMNhwoC3rAwH4/tcJiZjgPhXHyhjCNErel231ov/VxQ7PvbDUA390guPfpaFmt4GW0Oso4KRQO/99gVO8QEsFXmPvvvx+vv/46Fi9ejMGDB6O4uBj5+fm8E/e5c+dQVub4Yx45ciTWrl2L999/H4MGDcKXX36J9evXo3///nybBQsW4Pe//z3mzJmDG264AXV1dcjPz4dO5xAE1qxZg/T0dIwdOxYTJ07EqFGjXHJERUdHY9OmTTh9+jSGDRuGZ555BosXL3bJNeVNX+SCv855/u6w2uPhEXat1NrCc6JEqrhDbj5SgL2e28Bu0bCxCLicTk1jMz7bbS8UPTuI2ijAYTIqKa8VPGqGHyeZazoGdIvGnNH25/yH/xxCdUNwHLwbzVYcbtEKD+0e49O1/VKioVQwuFTbhPIaYaMKO4qmA3DUdPvukPfmPZZleTcIXzWHqbFh6BKuhtlqw7FyYaO55exz6CucgmDzkXJZ1XFtjShb9by8PJw9exZNTU0oLCzkzWsAsH37dqxevdql/X333YeSkhI0NTXh0KFDmDhxost5hmGwZMkSlJeXw2Qy4YcffsD111/v0iY2NhZr165FbW0tampq8NFHHyEy0rWA68CBA/Hf//4XJpMJFy5cwHPPPXdN39vri1xwds7zxYkymI7mzkwamIyYcDUuVjdiW4BZ1/1FLiViWjMxSNF7n+0+h3qzFdcnReKW6xOC0TWerjFhiIvQwGJjcaRMpIlfZuPkjqfG9sF1CRG4XNuEJRuOBOWenFY4Sa9F1xjffNzCNEr0SbTPa0I7MvOlRzrAAn1r30RoVQqcrWzw+u/7TGUDqurN0KgU6JfiXUAAB8MwGCCSGVaOG0h/Gd4zFvGRWhhNFuw8KV/znnxsHkTAcNF7Pxyp8Mo5z77DqgYQPP8oDp1aifuH29M/SOV0LtdwbW6XVXCq0u+wdbPFhlU7zwDwvxyMJxjGET0mdEZmUwjlJ9KplXjt3kFgGHvi2WBsEoqctBz+jKNYZtiOpJGK0Kowpq998+HthobzYxvYNRoale9L58Cu4rxPHWmclArGJfeXXCFBqgMxtLvdOa+2yYKdJ9qX3gPZYXnDg1ndwTDAj79exlmR6rZxNFttaLbaVfZym1B6xEWgX4oeVhuLTX5G7317sBTlRhMSorS4e3BKkHtox+EgK84OWm4Cb1sM69EFj96UBgBY+NVBGAMsGO6v3w3HQD6BqrDjZAqBoABfcC7b5I15z1+zHodYGc7l6BsaCJwZdtORClHy2vlDx3jSBABX57xvD7S/QAe6w2qPHnERvMlpbeG5oN/fE85+PXJUcQdSAoFlWXyw4zQA4JGRPaFVCfP7BvGRe9WC3J8jlEx7HP87ri96xIWj3GjC0o1H/b6Ps9+Nv+lHBjkJvEImDO1IJiMAuC09ERqVAqeu1KPEi3xpnBvEED8FXi7D+fFLtXwqCSEIxffJEzf2jEVchAbVDc34+VSl1N1xCwlSHQxfnPP8Dbn2BS7T+ed7z4ua6p+b9BkG0AogJAYKN067Tlzx2Wl518lKHCkzIkytxLSs7kJ0D4BDI3XqSj1qA9S6tAXLsiG5QIdplPjLlIEAgP/bfd7v8GxXrbB/UZd9DVHQqBSoaWzG2coGv+7hDR1tgY7SqTG6j32j115UmNHUzAtbQ3vE+PV9SXodkvRa2Fj4nHbBF0LxffKESqnAuH5c7i95Ru/Jb4UhAsLZOW9XO855/oZc+8Kt6YnoGhOG6oZmfCtQVmh3mMwOv5tg+w8Fg14JkUg3RMFiY7H5SEX7FzjBJeC8b3g3xIRr2mntP/GRdudnlgUOXhTGHNHkJOyHimmPY0SvOD469fmvDvhVNJzTcgzoGu23ZlGtVCAz2S6ECak9DDUTrDdwfqXt+d/8cr4aLAt0jw1HYpT/aWLEyCflyMsmn/x5gcKN06bD5bDI0LxHglQHQ6lgML5/SwkED9K7yw4ryBF7rfvzYIvWREyn81BwuOSj93ww7/1aUYvtJZfBMMCsUWlCdY1HaL+OBqeSRnIeq7Z4bkI6usaE4cLVRryWf8zn64sC9LvhGCSC/01H00gBwNiMJKiVDI5fqsNxD+a9YGnvuXESMnKvI47TiF5x6BKuRmW9GbtPV0ndnWsgQaoDwmXP/v5IeZvOecXnHDushCitoP25/4ZUqJUMis9Xi1IiAQiN3TO3y/rv8cuoafTOdPZhizYqN9OAHnERgvWNQ+gdNDdOGpUCSoX8NIftEalV4c9TBgAAPi446/MkH6z0I0KPU7PVBotNnsEbgRAdpsao3vEAPG9oivhxigno+8TUSHUUZ3PArnUdl9li3jskv+i9jvOkCZ4b02IR245zXqARKL4QH6nltS+fiqSVCoVdWe/EKPRJjESzlcWWo+2b9y7VmrB+fykAYPbo4CbgbAt+B31eGAE4FMapPW7uk8Cn+ljw5S9eFw4Pht8NBxcYcOiiURDTR6Nz8EYHWqAB1+g9d9hsLIpb0sQE6gbBaXjPVjYELaFraxplXrvSX7jovfxDFZIleW6LjvVGEADsznm57TjnBWuH5S2cL8l/frmImgZhHJedMYWARgoAJvhQI/GTXWdhttowtHuMKAIwAPRvmfgvVjcKUqy3o5Sz+H93ZMCg1+FMZQOWbS7x6hrO7yY1NiwgvxsASIuPRIRGicZmK05crgvoXu4wtSzOCgbQKDvWsnF7ZhJUCgbHymtxys2zO36pDrVNFkRolOibFBXQd8WEa9AjLhyAMGZYm43l/Q5D/Z1qzcjr4qHXqXClrgl7z8jLvNex3giCx5NznjWIOyxvGdajC9INUTA12/DlvguCf19DiOzKuHHacfyyx8i4BrMFnxbatXlzRNJGAYBep0avBLsJUYiJPxRMsN6g16nx6j320lH/+Ok0r/H1BO93EwQfRaWCQX8+4aOA4yTT4I1AiAnXYKQH8x43ToNSY6AKghAppHnP5JSIOdTfqdZoVArcnsmV9pFX9B4JUh2UEb3iEMM557WS3o9fqg3aDstbGIbBw9l2rdSan88Kmu8GCA1ncwDomxSFXgkRMFts2OohS/aXRRdQ3dCMHnHh/GQiFlxGZiEiwjqSGeK29CTcM6QrbCyw4MsD7ab7CHb6ES5PkSDjxAu8HScSzJmJ/TkN/rXmvaCPk4AO585mZZ1A+eWkZNJAR41Em4zMeyRIdVDsznnuo/e4TMqDuwdnh+Utkwd3RaRWhVNX6rHrpLCJ1UJFkGIYhg8OaCvK0mpj8Y+f7Ak4H70pTXSnbCEznDvGqWNMRYvvzER8pBYnLtXhna3H22zn7Hfjb4LH1ggZYekohNsxxqk14/oZoFQwOFxqvKYKQ7DTxAipkeLeJ61KAUUIBm+0x0294xGlVaHC2OSV1lcsOuZbQQBw+N/kHy53cc4rEqhQcXtEaFW4Z2hXAMA/C4R1OjeFUAV0zolyW8klt7mINh+pwNnKBkSHqXHf8G5id493ZD5woTromsRQ8WXzlphwDV6Z3A8AsPLHU21GqXJ+N+EaJdINwdEKcxnOj5Ubvaq16QuhsjHxl9gIDUb0igXgajaqqjfj1BW7YDU0NTjzZf+ueigYoMLYhAqjKSj35Oho71NrtColcloUBHJKzkmCVAfmphbnvMu1rs55gZakCISHWpzONx+tQFlNo2DfE0rZfTOT9egRF44miw3bSq4173EJOB8a0V2SJHuZydFQKhhcqTOjtCa4E39HiNprzfj+yZg0MBlWG4tnv/zFbYUBbjMzOEh+NwDQrUsYuoSr0WxlcbSs/ZInvtBRggI84S56j0tP0TsxEtHh6qB8T7hGhT6JduH5lyAXMG40d0xHc2f4IsYyMu+RINWBceecV1Vvxukg77B84fqkKGSlxcJqY/F/u88L9j2htINmGEeNxNbmvaKzV1F09io0SgVmZPeUoHf23e31Lb50B4NsjgglgdcX/nhXP3QJV+NYeS3e237ymvNCpB9hGIY3GwV9nFoW6I42Ts6MyzRAwdhNo+er7KV2+HEKsvaeM8MGu2JARwne8MTo6xMQoVGirMYkeB1QbyFBqoPDl0Bokd6F2GH5Cud0/n+7zwlWzZvTdIRKpfpJLbvhrccuuTiMcgk47x6cgkR9YCHygSCUg2xDiI2Tt8RHavHSXXYT39+2HcexctfaasFKxNka4cbJbnLuyAt0QpQWN6bZzXv5LRtP3g0iwDxfrRnIBwYINE4dWODVqZW4LYMz78kjOScJUh2cUX3iEdninLf//FVHSQqR/aOcGZdpQEKUFpdrm7DpsG915rwl1HwF+nfVo1uXMDQ2W/Hjr3bz3tnKenx/2D6hP3azeCkP3CGUg2xHNhndNSgFt2cmodnK4tl1B/g0JM5+N0OCnMeNxikwePPeoTI0W228xiPYedscJX2C63fYWcZp0gBHnkShI8C9gQSpDo5WpURORiIA+x9dsEN5/UGjUuCBG+yZoP/58xlBviPUTEYMw/CT+Lct5r2PfjoNGwvccn0C+gbJIdlfnCPCgumXwKc/CBGB1xcYhsGfJveHXqfCwYs1+OC/9shLZ61wsItOD2wJDDhxqc6vIsptEUqm8kDI7WcAwwD7z1Vj67FLMDXbEB2mRq/4yKB+T7pBD41SgeqGZpyvCp6vaGcw7QHALdcnIkytxMXqRsEKqvsCCVKdgAlOTpTcTjXYqmpfeSCrO5QKBj+fqvJYLNRfQtGJmXOi3Hq0AhVGE77Ya09cOltibRQA9DVEQatSoNZkwZlW4eGB0NEX6ES9DovvtJv4lv/wK05cqnMEewhQVSAxSofkaB1sLHAoiAsM7yPVwRfoJL0Ow1s2mX9pKUI9pHtM0FMJaFQKZCS3OJwHUXvYGXzZALugeFu6Q0EgNSRIdQJucXLOE2qH5SvJ0WG8pmxN4bmg3z8UC3cOTo1BSrQO9WYr5q7Zh8ZmKzKS9bipd5zUXYNaqUBmih5AcPMUdXRBCgCmDO2KW65PgNliw4Ivf8GelghaobTCQuST6gzjxMEFfpy6bN8wCOUGIYQZtlONk5P/r9TmvdBZZQi/cXbOA+w7YTkka3t4RE8AwL+KLgTVDAGEpkaKYRhee7i3xfwz++Y02ZTk4PIUBXMHHWq+bP7AMAyW3jMAkVoV9p2rxp4zwprXBwo4Th0tKMAd3ALNIbTAG0yH887iIwUAt/ZNhFalwNnKBhwpM7Z/gYCQINVJ4EogANL6Rzkz8ro4pMVHoLbJgv8Ulwb13qHmI8Ux0WkSN+h1uGNgioS9cUUQTUcHKhHjiZSYMLwwMYP/t5Ba4UECZKLvLOME2LXlnNlVwThK7wQb7r6HLta4JEwOhMYQSkQcKBFaFW7ty5n3pI3eI0GqkzCmbyK/S5EiEac7FAoG07K6AwA+KTgTVPVsqKq4h6R2QZJeCwB45Kae0Kjk84pymo7DpTXXFML2l1AdJ3944MZUjLzObqYVUis8oEXgPVfVgKv15qDcszONE+CI3stI1iNCK0wS3OsSIhGuUaLBbMXJy3VBuWeobiD9ZYJMovfkM0sTghKmUeKN/xmEJ8f2wYg06X1uOO4blgqdWoFj5bVBrZ0USiVinFEoGLx27yA8NipNsgScbdErPgJRWhVMzTb8WhGsib/jZ2LmYBgGy+8fjIdGdMcz4/oK9j3RYWqkxUcAAA4EyeG8s0SDcUzL6oFHb0rDiy2BAkKgVDDozxUED1KG88ZOZIIFgNvSE5FuiMLEAQY0W0mQIkRg4oBkzL/9eln4R3FEh6tx1yC7+SqY9fdCeQd9y/UJWHRHpuwWLYXTxB8sB9nGTpDo0ZkkvQ6vTB7AP0eh4M2wwVqgQ9DnMBDCNEosvjOTT9ApFAO7Btdc3tnGKUqnRv7To/Fsbrqk2nsSpAjJ4ZzONx4sx5W6pqDcs7PtoMWCy1MULAdZGidhcDicB3ecOovJSCy4DOfB25h03LxscoYEKUJyBnSLxqDUGJitNnyxN/D6ezYbC1MnMhmJycCuMQCCOfHTOAnBwG7B1hySwCsEXIbzo2W1botb+0ooa+JDGRKkCFnw8AhH/b1AaXKakGjiDy7cAl1SXsuHWgdCZwrXFpN+KXooGOBSbRPKa0wB34/GSRi6x4YjJlwNs9WGkvLAExOTICUNJEgRsuD2THueq/NVjQEv0FzhTgDQqWhCCSbduoRBq1LAYmNxyRiYGZZlWTLtCUS4RoWuXcIAABeuNgR8P1qghYFhGFyXYE+DEYxxMoVgIuKOAD1tQhbodSreWfBybWALNDfpa1UKWTnWdwQYhkFClD09w+UA/dmarSyfP4d8b4JPQqR9nILhdxiKlQJChaCOUyfK9yUn6K0gZAHDMEGbUDpDtmwpiQ/SODU6aR5J0xF8uHG6XBd4LimHj5QwOZU6M/FR9sLVQRkn0hxKgqCCVFVVFaZNmwa9Xo+YmBjMmjULdXWe88+YTCbMnTsXcXFxiIyMxJQpU1BRUeHS5ty5c5g0aRLCw8ORmJiIZ599FhaLa4mR7du3Y+jQodBqtejduzdWr159zXetWLECPXv2hE6nQ1ZWFnbv3u1yfsyYMWAYxuXz+OOP+/cwiHaJ5zQdgWqkyIFZUPgFOsBx4gRepYKBWkmaw2ATrPfJZmN5v0N6p4JPsN4ngDaRUiGoIDVt2jQcPnwYmzdvxoYNG7Bjxw7MmTPH4zXz5s3DN998g3Xr1uHHH39EaWkp7rnnHv681WrFpEmTYDabsWvXLnz88cdYvXo1Fi9ezLc5ffo0Jk2ahFtvvRXFxcV4+umn8dhjj+H777/n23z++eeYP38+XnzxRezbtw+DBg1Cbm4uLl265NKf2bNno6ysjP+89tprQXo6RGsSIu07sysB7sxoVyYsCVHcOAUq8DrGSS71BDsSwdIcmiykORSSYI0T0PnySMkFwQSpo0ePIj8/Hx9++CGysrIwatQovPPOO/jss89QWuq+rlpNTQ3+8Y9/YNmyZbjtttswbNgwrFq1Crt27cLPP/8MANi0aROOHDmCTz/9FIMHD8aECRPw8ssvY8WKFTCb7QvwypUrkZaWhjfeeAMZGRnIy8vDvffei+XLl/PftWzZMsyePRszZ85EZmYmVq5cifDwcHz00UcufQoPD4fBYOA/er1eoCdGBNtkRH4CwkDjFBrwG5OANbwOQUoro5JFHYVgvU8UvCEdgr0VBQUFiImJwfDhw/ljOTk5UCgUKCwsdHtNUVERmpubkZOTwx9LT09H9+7dUVBQwN93wIABSEpK4tvk5ubCaDTi8OHDfBvne3BtuHuYzWYUFRW5tFEoFMjJyeHbcKxZswbx8fHo378/Fi5ciIaGtiMrmpqaYDQaXT6E9wRtgTZ3rjIJYsOPU21gmsMGGidBCdb71MA7MFPwhhAES8PbZLGBq31MGilxEcxzsLy8HImJia5fplIhNjYW5eXlbV6j0WgQExPjcjwpKYm/pry83EWI4s5z5zy1MRqNaGxsxNWrV2G1Wt22OXbsGP/vBx98ED169EBKSgoOHDiA5557DiUlJfjqq6/c9n/p0qX44x//6PYc0T7xkcGZUMhPQFi4qL2gjRNN+oLgGKfABF4aJ2FJiNQBCHxj4pw2hrS84uKzIPX888/jL3/5i8c2R48e9btDcsLZn2vAgAFITk7G2LFjcfLkSVx33XXXtF+4cCHmz5/P/9toNCI1NVWUvnYEOOfYQCcUMhkJS7A1h1TOQhiCbYIlQUoYuKi9xmYr6pssiND6p9/gxkmtZKBWkglWTHwesWeeeQaPPPKIxza9evWCwWC4xnHbYrGgqqoKBoPB7XUGgwFmsxnV1dUuWqmKigr+GoPBcE10HRfV59ymdaRfRUUF9Ho9wsLCoFQqoVQq3bZpq28AkJWVBQA4ceKEW0FKq9VCq9W2eT3hmQQ+XDs4pgia+IWB0xwGK99XmJomfSHgNiYN5gAXaBJ4BSVco0K4RokGsxWXa5sCHyea90TH5xksISEB6enpHj8ajQbZ2dmorq5GUVERf+3WrVths9l4gaQ1w4YNg1qtxpYtW/hjJSUlOHfuHLKzswEA2dnZOHjwoIuQtnnzZuj1emRmZvJtnO/BteHuodFoMGzYMJc2NpsNW7Zs4du4o7i4GACQnJzszaMifMShkSKTkZzhxqnebHVxRPYV0nQIS4RGCV2LkBqIVorGSXiCoT2kcZIOwbaCGRkZGD9+PGbPno3du3dj586dyMvLw9SpU5GSkgIAuHjxItLT03kNU3R0NGbNmoX58+dj27ZtKCoqwsyZM5GdnY0RI0YAAMaNG4fMzEw8/PDD+OWXX/D9999j0aJFmDt3Lq8Nevzxx3Hq1CksWLAAx44dw7vvvosvvvgC8+bN4/s3f/58fPDBB/j4449x9OhRPPHEE6ivr8fMmTMBACdPnsTLL7+MoqIinDlzBl9//TWmT5+O0aNHY+DAgUI9tk4NN5nUNlkCKhNDBVaFJUrryEIfyMRPvmzCwjBMUBZo2pgITzD8Q+l9kg5B09SuWbMGeXl5GDt2LBQKBaZMmYK3336bP9/c3IySkhKXSLjly5fzbZuampCbm4t3332XP69UKrFhwwY88cQTyM7ORkREBGbMmIElS5bwbdLS0vDtt99i3rx5eOutt9CtWzd8+OGHyM3N5dvcf//9uHz5MhYvXozy8nIMHjwY+fn5vAO6RqPBDz/8gDfffBP19fVITU3FlClTsGjRIiEfWadGr1NBo1TAbLXhSl0TunUJ9+s+5CMlLFwW+ovVjbhc14TUWD/HiUwRghMfqcWFq424HIDfIYXUC08wstBTImLpEFSQio2Nxdq1a9s837NnT7As63JMp9NhxYoVWLFiRZvX9ejRAxs3bvT43WPGjMH+/fs9tsnLy0NeXp7bc6mpqfjxxx89Xk8EF/sOWoPSGhOu1JkDFqRoQhGO+Ci7IBWIGZbGSXiCEWFJC7TwJATBrYE2kNJBXp6ErAiGn5SJN+3Rn7dQBCMLPQlSwhNU3xvSSAkG+UiFNrTSELIiGJF7NKEITzDqg5Evm/AkBCHCstFsr2NK75NwBKMuIjdOlOBWfEiQImSFI2t2MHbQVKleKIKygyZBSnDig2HaI5OR4CQEwdmc0lRIBwlShKyID0K5BCrcKTzBiDIizaHwOATeIDgx0wItGEEZp2byZZMKEqQIWRGMCcURBkx/3kIRDE0HhdULD/nehAY0TqENrTSErIgPgo9UA4XVC05CUHbQZNoTmmBEg5HAKzwJTlnoG1p8nXyF8khJBwlShKygnVloEIzoSsojJTycCbY+gAWafG+EJ0Kr4ucrf2uN0vskHSRIEbIiIQjRK7QzE55gZKEnnw7hidSqoOWy0Pu7QNPGRBQ4/9DLdSa/rqdxkg4SpAhZwZmMak0BLNDkbC44XBZ6wH+hlwRe4XEuE+OvuZxboCmsXlgcKUUCFXhpWRcbeuKErNCHORboynrfJxSWZWlnJgJcFnrAfzMsCbziEGhgAPlIiUOgbg0mSiciGSRIEbKCYRjEcQu0H5oOs9UGW0vVIfLpEBZH+ZHAdtDk0yEsCQEu0OR7Iw6BClKUP086SJAiZEcgE4qpJecNQDtooQl44jeTyUgMErjcbH6ajBpI0yEKgdZFbCANr2SQIEXIjkBMRtyuTK1koFbSn7eQBJKF3mK1wWwlZ3MxCNhkRKY9UeCzm/sp8NI4SQetNITsCCRyj8xF4uGIMvJDc2hx0hySpkNQAq2LSD6H4hCsoABKRCw+9MQJ2RFIdvMGKrAqGoFoOjizHgA+PJ8QhkDGyTl4Q0cLtKAEGhRAvmzSQW8GITsC2ZlRSL14OEx7vgu8zmYIhmGC2i/ClUBM5U0WG9iW4A3anAhLoAXbSXMoHSRIEbIjkKzZfIFVmkwEJxDnWCoPIx6BRFc653Kjd0pYnLPQO2tsvYU2kdJBghQhO4LhbE7qbeEJRHNIOaTEg9uY1PmRhZ57nzRKBVQUvCEokVoVdC3JNH2d+5qtNjRb7apDeqfEh94MQnYEUhCX1NviEUgWeofAS1OQ0ERpVdCo/MtC7/C7oXESmkCy0Du/f7SJFB96OwjZwZkiahqb0WTxbYGm7L7i4ZyF3tcdNJn2xINhGF7o9XWBpnESF38jLLlxYhgK3pACeuKE7IgOU0OttDsgV/qolSKNlHi4ZKH3cZxMZNoTlXg/qwVQbiJx8TfCkktEHE7BG5JAghQhOxiGQVyEfxMK7aDFxd9II0e2bCpnIQb+phRpoJB6UfE3C31Dc0vaF5r3JIEEKUKWcMkefRakSNMhKv5G7lGlenHxe5zIVC4q/mqkKIeUtNAsRsgSf3MUkUZKXPyNsCSTkbj4vUDTOIkKjVNoQoIUIUv8jV6hnZm4+GsyIk2HuJDAGxr4qzmkHFLSQoIUIUv8rbdHOzNxCTTKiARecYj3933iNia0QIuC3+9Ti7M5vU/SQIIUIUsCV3HTn7YY8As0mSJkjd+aw2aqFCAm8X5GwdL7JC202hCyxG9TBJmMRIVMRqGBv9GV3AIdTu+TKPibhZ4EKWkhQYqQJf5mNyeTkbgk+lkXkXykxIUzldf6uECTwCsu/mahpw2ktJAgRciS+IDD6mlCEQNO02E0WXzKQk8Cr7jodf5loafgDXFxzkLv0ziRs7mkkCBFyBJuga5uaIbZYvP6Om7iD6dEj6Lgbxb6BjOZjMTEXsfNd/+bBtJ0iI5jE+nHOJHAKwmCCVJVVVWYNm0a9Ho9YmJiMGvWLNTV1Xm8xmQyYe7cuYiLi0NkZCSmTJmCiooKlzbnzp3DpEmTEB4ejsTERDz77LOwWCwubbZv346hQ4dCq9Wid+/eWL16tcv5HTt24M4770RKSgoYhsH69euv6QvLsli8eDGSk5MRFhaGnJwcHD9+3K9nQfhOTJgaKkXLAl3vg4qb35nRHkEMnLPQ+2SKIM2h6PgTuUfjJD4JLQIvjVPoINhqM23aNBw+fBibN2/Ghg0bsGPHDsyZM8fjNfPmzcM333yDdevW4ccff0RpaSnuuece/rzVasWkSZNgNpuxa9cufPzxx1i9ejUWL17Mtzl9+jQmTZqEW2+9FcXFxXj66afx2GOP4fvvv+fb1NfXY9CgQVixYkWbfXnttdfw9ttvY+XKlSgsLERERARyc3NhMpkCeCqEtygUTnXcfEjKSSYj8fEnCz0/TqTpEA1/ImHJVC4+fo0TaQ4lRRD7x9GjR5Gfn489e/Zg+PDhAIB33nkHEydOxOuvv46UlJRrrqmpqcE//vEPrF27FrfddhsAYNWqVcjIyMDPP/+MESNGYNOmTThy5Ah++OEHJCUlYfDgwXj55Zfx3HPP4aWXXoJGo8HKlSuRlpaGN954AwCQkZGBn376CcuXL0dubi4AYMKECZgwYUKb/WdZFm+++SYWLVqEu+++GwDwySefICkpCevXr8fUqVOD+rwI98RHalFhbPJpQiEVt/gENPHTOImGP4WLKY+U+AQi8NIGUhoE0UgVFBQgJiaGF6IAICcnBwqFAoWFhW6vKSoqQnNzM3Jycvhj6enp6N69OwoKCvj7DhgwAElJSXyb3NxcGI1GHD58mG/jfA+uDXcPbzh9+jTKy8td7hMdHY2srCyP92lqaoLRaHT5EP7jT3ZzyvArPv5EWJooP5Ho+JM1mzRS4uNPShEaJ2kRRJAqLy9HYmKiyzGVSoXY2FiUl5e3eY1Go0FMTIzL8aSkJP6a8vJyFyGKO8+d89TGaDSisbHR6/4739tdX9yxdOlSREdH85/U1FSvvo9wj687s2arDc1WFgBNKGLij+8NRRmJjz9JOcn3Rnx4Z3MfXBrIN1RafHrqzz//PBiG8fg5duyYUH2VPQsXLkRNTQ3/OX/+vNRdCml43xsvJxTn/Dik4hYPMu2FBv5oeBtpgRYdv9If0PskKT75SD3zzDN45JFHPLbp1asXDAYDLl265HLcYrGgqqoKBoPB7XUGgwFmsxnV1dUuWqmKigr+GoPBgN27d7tcx0X1ObdpHelXUVEBvV6PsLCwdn+j870qKiqQnJzscp/Bgwe3eZ1Wq4VWq/XqO4j2SfBx4ucmfYYBtCqa+MUi3scoI5ZlyadDAvzJbu5YoCmdiFgEouGl90kafFptEhISkJ6e7vGj0WiQnZ2N6upqFBUV8ddu3boVNpsNWVlZbu89bNgwqNVqbNmyhT9WUlKCc+fOITs7GwCQnZ2NgwcPughpmzdvhl6vR2ZmJt/G+R5cG+4e3pCWlgaDweByH6PRiMLCQp/uQwRGgo9Zs01mh98NwzCC9YtwxdcddJNTXjAy7YlHQouG1z+NFI2TWHACry9Z6MlHSloE2bZnZGRg/PjxmD17Nnbv3o2dO3ciLy8PU6dO5SP2Ll68iPT0dF7DFB0djVmzZmH+/PnYtm0bioqKMHPmTGRnZ2PEiBEAgHHjxiEzMxMPP/wwfvnlF3z//fdYtGgR5s6dy2uCHn/8cZw6dQoLFizAsWPH8O677+KLL77AvHnz+P7V1dWhuLgYxcXFAOzO5cXFxTh37hwAe26cp59+Gq+88gq+/vprHDx4ENOnT0dKSgomT54sxCMj3OCryYgmE2lI8DGBIKflAGisxCQhUgcAqDV5v0CTj5T4+JOF3kSJiCVFsKe+Zs0a5OXlYezYsVAoFJgyZQrefvtt/nxzczNKSkrQ0NDAH1u+fDnftqmpCbm5uXj33Xf580qlEhs2bMATTzyB7OxsREREYMaMGViyZAnfJi0tDd9++y3mzZuHt956C926dcOHH37Ipz4AgL179+LWW2/l/z1//nwAwIwZM/jknQsWLEB9fT3mzJmD6upqjBo1Cvn5+dDpdEF/VoR7/BakaPcsKtw41TTas9Br2jGrNrSMk0algFJBmkOx0IfZF2iz1YbKejO6xnh2daDgDWngstCX1phwpc6Mbl3C272mgXzZJEUwQSo2NhZr165t83zPnj3BsqzLMZ1OhxUrVnhMlNmjRw9s3LjR43ePGTMG+/fv93i+9Xe3hmEYLFmyxEVII8SF87252tCMZqsNaqXnSYIcLqUhuiULvcXGorK+CcnRnhdoGidpYBh7ktuyGhOu1Da1K0g1Ogdv0AItKvFRWrsg5aVbA9VElBZ6OwjZ0iVcw2ssqurbNxs1NttLBZFGSlx8zUJP5iLp8EXLy5mLFAx4UxMhDr74HdpsLO93SO+UNNDbQcgWhYJBXIT3EWGNLc7mtCsTH0doffsllMgEKx2+RFg6+xxS8Ia48O+TF+Nksjj5HNI7JQkkSBGyxpfcN+RsLh2O0HovNIdkhpAMXzRSJPBKhy/1K52DN3QqGispIEGKkDXxPqRAIEFKOrjIPd8EXpp+xMaXCEsSeKXDlyz03PukVSmgoOANSaCZjJA1jrpTXvjeUAV0yfDJ94Y0HZJBGt7QwJdxovdJekiQImSNL06XlN1XOnwReClqTzp80fByC3Q4LdCi45MJ1kyO5lJDghQha3xxuqQdtHTwpr1a753NSeAVH97Z3IcFmsZJfBJ8KBND8570kCBFyBqHT4f3Tpe0gxYff3w6aJzEJ8GHenvkbC4d3Dh5k4Wexkl6SJAiZA353oQGvpkiaActFdw4GU0WNFnaWaDNLXnZaJxEh8tCDwCV7eTQo3GSHhKkCFnjCAP2XtNBpgjx4TSH1S1Z6D3BR4ORwCs60WFqqJX2yK7Kdt4pMhlJB5eFHmhfe0gaKekhQYqQNdwO+mqDGZZ2FugG0nRIRkyYms9CTwu0fLEnufVOe8j7SNECLQneannJl016SJAiZE2XcA0UDMCy7ZeJMVHhTslwzkLf7sRPgpSkeJvskcZJWhyRsDROcodWHELWKBUMYlt20JfaU3GTRkpSvI2wJF82afF5nOh9kgRvI/donKSHBClC9ngbuUc+UtIS72V2c8qYLS3eRlg2UoJbSaFxCh1IkCJkj7fJHknFLS1kiggNvNVI0cZEWrzNbk7jJD0kSBGyx9vs5lQiRlp4zWE7hYsbmykTs5T4quGlfF/S4G0WetqYSA8JUoTsoQklNCCBNzTwVnNIvjfS4vU4USJiySFBipA9PpuMaEKRBG/DtRuaWxII0jhJQoKXvjcN5MsmKT6PE71PkkGCFCF7vPEVsNlYmMhkJCle+95QkVVJifcyGoycmKWFM8HWNDZ7zEJPmnjpIUGKkD3e+N6YnCYamvilwdv8RGQykhZO4K1pbIbZ0naSWxonafE2Cz0JUtJDghQhe7wxGXG7ZwDQqWhCkQJHFvq2y8SwLEsmWIlxyUJf7+GdogVaUhjGuyz0lIhYeujJE7KHW6CrPJSJ4SZ9rUoBRcsiQYhLl3ANv0C3lYW+2crCamMBkO+NVCgUjMPv0IOWt5EWaMnxRstLedmkh94QQvbERjiViWlwP/FTtmzpsWeht0/8bfnfcIszQJoOKfFFy0sLtHTw4+SNwEvjJBkkSBGyx3mBbmtCIQdmedDeAs0JvEoFw/t/EOLTXgCHzcaiyULvlNR4E2hDm0jpIUGKCAnam1BoVyYPOJNRmxopp3qIDEOClFS0F2HpHLwRrlGJ0ifiWrypt0c1RqWHBCkiJEhoJyknlUmQB+3lvqFxkgft+d44B29oVbRMSEV7Gl6X4A16pySD3hAiJGhvQmmk7L6yIL6d8iNUdkQeeC/wUvCGlLSXjNhstaEldoNMexJCghQRErQ3oZCfgDxor0wMmSHkQbsaXhonWdCuwOuc9oXGSjJIkCJCgvh2JhQqZyEPvDUZUTkLaWlXw0vmIlngrYZXrWSgVtJyLhX05ImQgCb+0KC9cG3HONHUIyXemspJ4JUWbpyqG9xnoacUFfJAsNmsqqoK06ZNg16vR0xMDGbNmoW6ujqP15hMJsydOxdxcXGIjIzElClTUFFR4dLm3LlzmDRpEsLDw5GYmIhnn30WFovFpc327dsxdOhQaLVa9O7dG6tXr3Y5v2PHDtx5551ISUkBwzBYv379NX155JFHwDCMy2f8+PF+PQsicNqrD0blLOQBRVeGBpypvK0s9DRO8iAmTA2Vhyz0NE7yQDBBatq0aTh8+DA2b96MDRs2YMeOHZgzZ47Ha+bNm4dvvvkG69atw48//ojS0lLcc889/Hmr1YpJkybBbDZj165d+Pjjj7F69WosXryYb3P69GlMmjQJt956K4qLi/H000/jsccew/fff8+3qa+vx6BBg7BixQqP/Rk/fjzKysr4z//93//5+TSIQPHa94Z20JLiKBPjPgs9+bLJA+cs9O7quNHGRB4oFAziPGShp/dJHgiSIOTo0aPIz8/Hnj17MHz4cADAO++8g4kTJ+L1119HSkrKNdfU1NTgH//4B9auXYvbbrsNALBq1SpkZGTg559/xogRI7Bp0yYcOXIEP/zwA5KSkjB48GC8/PLLeO655/DSSy9Bo9Fg5cqVSEtLwxtvvAEAyMjIwE8//YTly5cjNzcXADBhwgRMmDCh3d+h1WphMBiC9ViIAOB8b6rqzbDaWH4R4KCwennAZaG3sfaxStTrXM6TKUIeKBQM4iI0uFTbhCt1TTBEtxonWqBlQ3ykFhXGJrebSEpELA8E0UgVFBQgJiaGF6IAICcnBwqFAoWFhW6vKSoqQnNzM3Jycvhj6enp6N69OwoKCvj7DhgwAElJSXyb3NxcGI1GHD58mG/jfA+uDXcPX9i+fTsSExPRt29fPPHEE6isrPTYvqmpCUaj0eVDBIfYcA0YpwW6NaTilgf2LPRtm/donOSDJzMst0CTwCs9HseJNpCyQBBBqry8HImJiS7HVCoVYmNjUV5e3uY1Go0GMTExLseTkpL4a8rLy12EKO48d85TG6PRiMbGRq9/w/jx4/HJJ59gy5Yt+Mtf/oIff/wREyZMgNVqbfOapUuXIjo6mv+kpqZ6/X2EZ1RKBWLD244IM/GmPXJilhpHqgoSeOVMvIcUCJTvSz54Cgyg90ke+LTqPP/889c4YLf+HDt2TKi+isrUqVNx1113YcCAAZg8eTI2bNiAPXv2YPv27W1es3DhQtTU1PCf8+fPi9fhTgBNKKGBpxxFJvJlkw2eBF7ykZIPfEoRdz5SlIhYFvjkI/XMM8/gkUce8dimV69eMBgMuHTpkstxi8WCqqqqNn2ODAYDzGYzqqurXbRSFRUV/DUGgwG7d+92uY6L6nNu0zrSr6KiAnq9HmFhYe3+Rk+/Kz4+HidOnMDYsWPdttFqtdBqtX5/B+GZ+CgNSircR+45fDqoLpjUeDJFNJAgJRsSPNTbazDbI6HJZCQ9CR7fp5ZxovdJUnxadRISEpCQkNBuu+zsbFRXV6OoqAjDhg0DAGzduhU2mw1ZWVlurxk2bBjUajW2bNmCKVOmAABKSkpw7tw5ZGdn8/f905/+hEuXLvGmw82bN0Ov1yMzM5Nvs3HjRpd7b968mb+Hv1y4cAGVlZVITk4O6D6E/3iK3KNMzPKB13R4EnhpnCTHo4aXc2KmBVpyPGl4G5vJ2VwOCOJQkpGRgfHjx2P27NnYvXs3du7ciby8PEydOpWP2Lt48SLS09N5DVN0dDRmzZqF+fPnY9u2bSgqKsLMmTORnZ2NESNGAADGjRuHzMxMPPzww/jll1/w/fffY9GiRZg7dy6vCXr88cdx6tQpLFiwAMeOHcO7776LL774AvPmzeP7V1dXh+LiYhQXFwOwp0woLi7GuXPn+PPPPvssfv75Z5w5cwZbtmzB3Xffjd69e/ORf4T4eMpu7tBIkY+U1CR4yMZMJiP54GmcSOCVD+TSIH8EW3XWrFmD9PR0jB07FhMnTsSoUaPw/vvv8+ebm5tRUlKChoYG/tjy5ctxxx13YMqUKRg9ejQMBgO++uor/rxSqcSGDRugVCqRnZ2Nhx56CNOnT8eSJUv4Nmlpafj222+xefNmDBo0CG+88QY+/PBDFwFo7969GDJkCIYMGQIAmD9/PoYMGcLno1IqlThw4ADuuusuXH/99Zg1axaGDRuG//73v2S6kxCPzrEUVi8bvBN4aZykxtMCTQKvfPBqnOh9khTBHEpiY2Oxdu3aNs/37NkTLMu6HNPpdFixYoXHRJk9evS4xnTXmjFjxmD//v0ez7f+bmfCwsJcEngS8sCbMGCa+KXHs8mIBF654KiL6EbgpRIxsqF1Fnrnmnr0PskDsoMQIYNXUUY08UuOZ1ME+XTIBecs9K3LxNDGRD44Z6FvnUOPxkkekCBFhAzxHqKMyNlcPnCajsr6a8vEkMArH7qE27PQs26S3NICLR+4LPTAtXMfFQGXB/T0iZAhscVHqqq+CVabwzTLsixN/DKCy0LPskBVQ6sFmgRe2eCShb7VAm2i4A1Z0ZZbA+Vlkwf0lhAhQ2yEo0zMVacF2my1gZOryKdDelRKBb+Dbp1EkEpayIu2IvccAi/lZZMDbQXa0PskD0iQIkIGlVKBLm7KxJjMDvMRaTrkQVt+UlR6RF605XdI0ZXyor1xCqdExJJCghQRUjiSPTomFG4yUSsZl4gWQjrcCVJWGwuzhZzN5URbSW7JBCsvaJzkDa06REjhboGmchbyw7GDdowTJ/ACpOmQC+2ZjGiBlgftaXjJl01a6OkTIYW7yD2a9OWH23EyOwQprYqmHjnACbzOTszOwRs6WqBlAefLdk3UHuWRkgX0lhAhhTvnWAqplx+8psPJp8M5WzbDMJL0i3DFnaajyWIDl6+YNifyoF2NFI2TpJAgRYQU7sKA+QKrNJnIBnc+HeTALD8cBXGvFXgB0nTIhbay0NMmUh6QIEWEFO6iVygEWH7EuzFFkGOs/HCn6aDgDfnhnIWeS3LbbLWh2WpXHdI7JS30lhAhhTvnWFJvyw/PAi9NO3KBW6CrnBZo8ruRH+6y0JPmUD7QjEaEFO5MRpTdV35w4+SchZ5Me/IjNsJpgW5JcksbE/nhkoW+Ze7jxolhKHhDaujpEyEFt4OurDfD1nqBpolfNjhnoed30GTakx32Bdq1jpuJkqbKktaReyYn31AK3pAWEqSIkCKuxWRktbF8mRjSdMgPd1noHeNEWZjlhMNPquV9almgyVwkL1qby6lKgHwgQYoIKdRKBbqEqwE4JpQG0nTIktZmWMc40bQjJxJa+R1yCW5pYyIvrn2fKBGxXKAZjQg5WkcaUQiwPHGEbLcaJ5r4ZUXr94lM5fKkdaANjZN8IEGKCDmumfgpykiW8ONUy5mMSOCVI63L+ZDAK0/aHCd6nySHBCki5Gido4h2ZvKkLU0HCbzy4lofKa48DI2TnCBfNvlCghQRcrSuD+YQpOjPWU60rrdHAq88uXacqFKAHGkdtUfvk3yglYcIOVqXtaA8UvKktcBLJiN5Eh9FPlKhAPmyyRcSpIiQg0xGoUFClHuTEQm88qJ1NBj53siT1lnoaQMpH0iQIkKO1hM/7czkCQm8oQEXXVlVb4bVxlLwhkxpnYWe3if5QIIUEXK0FbUXTokeZQWnkapqyULP+d5QAkF5ERvumoWeEj3KE+cs9FdqaZzkBAlSRMjB7aAr6+wLtMMUQX/OcoKb9Lks9I1cokfaQcsKlVKBWKcs9I2U4Fa2OG8iaZzkA608RMgR11K802JjUd3YzGfMJhW3vHDOQn+5rslhiqAdtOxwjtwjU7l8cY7cI59D+UCCFBFyaFQKxPBlYmjilzPOEZa0g5YvCVHXajpI4JUfLhop8pGSDSRIESGJI2t2E0UZyRjnid9E+Ylki3PWbNqYyBcaJ3lCghQRknATSrnRhGYrC4AmFDnibgdNAq/8cM6aTfm+5IvbcSLfUMmhESBCEm5COV/VyB8jFbf84H1vyDlW1jgXxG2kBVq2kLO5PKF4cSIk4QWpqw0AAIYBtCqa+OUGF2Hp7MRMAq/8cCfw0jjJD+c6o0oFA4DGSQ4IuvJUVVVh2rRp0Ov1iImJwaxZs1BXV+fxGpPJhLlz5yIuLg6RkZGYMmUKKioqXNqcO3cOkyZNQnh4OBITE/Hss8/CYrG4tNm+fTuGDh0KrVaL3r17Y/Xq1S7nly5dihtuuAFRUVFITEzE5MmTUVJS4nNfCGngnGPPVdkFqTC1EgzDSNklwg3cAn3hqkNzSKY9+cGX86GoPVlDPlLyRFBBatq0aTh8+DA2b96MDRs2YMeOHZgzZ47Ha+bNm4dvvvkG69atw48//ojS0lLcc889/Hmr1YpJkybBbDZj165d+Pjjj7F69WosXryYb3P69GlMmjQJt956K4qLi/H000/jsccew/fff8+3+fHHHzF37lz8/PPP2Lx5M5qbmzFu3DjU19d73RdCOrjs5hecBClCfnACLzdOAI2VHHEu52NqpgS3csU5yW19U0teNtqYSA7DsiwrxI2PHj2KzMxM7NmzB8OHDwcA5OfnY+LEibhw4QJSUlKuuaampgYJCQlYu3Yt7r33XgDAsWPHkJGRgYKCAowYMQLfffcd7rjjDpSWliIpKQkAsHLlSjz33HO4fPkyNBoNnnvuOXz77bc4dOgQf++pU6eiuroa+fn5bvt7+fJlJCYm4scff8To0aO96kt7GI1GREdHo6amBnq93rcHSHhk67EKPLp6L5iWkgnduoThp+duk7pbRCsOXazBHe/8xI+TRqXAr69MkLpbRCsuGU248dUt/DgBwC+LxyG6Jc0IIQ8sVhv6LPoOLAt+rH6YPxq9E6Ok7lqHw5f1WzCNVEFBAWJiYnghCgBycnKgUChQWFjo9pqioiI0NzcjJyeHP5aeno7u3bujoKCAv++AAQN4IQoAcnNzYTQacfjwYb6N8z24Ntw93FFTUwMAiI2N9bovrWlqaoLRaHT5EMLAmYy4SZ+0HPKExik0iI3QuAhRAKAjZ3PZ4ZyFnhsr8pGSHsHelPLyciQmJrocU6lUiI2NRXl5eZvXaDQaxMTEuBxPSkrirykvL3cRorjz3DlPbYxGIxobG9Eam82Gp59+GjfddBP69+/vdV9as3TpUkRHR/Of1NRUt+2IwOEWaA5Sb8uTuBafDg4SpOSJSqlAl3DHWCkYQKMkQUqOXDP30TslOT6/Kc8//zwYhvH4OXbsmBB9FYy5c+fi0KFD+OyzzwK6z8KFC1FTU8N/zp8/H6QeEq1pvUDTrkyeqJWOLPQACbxyJt7pnaLgDfnCRcJy0DslPT57Ez7zzDN45JFHPLbp1asXDAYDLl265HLcYrGgqqoKBoPB7XUGgwFmsxnV1dUumqCKigr+GoPBgN27d7tcx0XSObdpHV1XUVEBvV6PsLAwl+N5eXm8I3y3bt186ktrtFottFqt23NEcNGqlNDrVDCaqBCu3ImP1KK6oRkACbxyJj5Si18r7FHVtDjLl9YaKZ2KxkpqfNZIJSQkID093eNHo9EgOzsb1dXVKCoq4q/dunUrbDYbsrKy3N572LBhUKvV2LJlC3+spKQE586dQ3Z2NgAgOzsbBw8edBHSNm/eDL1ej8zMTL6N8z24Ntw9AIBlWeTl5eHf//43tm7dirS0NJ/7QkgLF8ECkCAlZxIinceJzEVyxfl9IoFXvji/T1qVAgoFaQ6lRrBZLSMjA+PHj8fs2bOxe/du7Ny5E3l5eZg6dSofsXfx4kWkp6fzGqbo6GjMmjUL8+fPx7Zt21BUVISZM2ciOzubj5IbN24cMjMz8fDDD+OXX37B999/j0WLFmHu3Lm8Nujxxx/HqVOnsGDBAhw7dgzvvvsuvvjiC8ybN4/v39y5c/Hpp59i7dq1iIqKQnl5OcrLy3kfKm/6QkiL886MdtDyJT6KxikUcHmfSJCSLfQ+yQ9BE4WsWbMGeXl5GDt2LBQKBaZMmYK3336bP9/c3IySkhI0NDhyzCxfvpxv29TUhNzcXLz77rv8eaVSiQ0bNuCJJ55AdnY2IiIiMGPGDCxZsoRvk5aWhm+//Rbz5s3DW2+9hW7duuHDDz9Ebm4u3+a9994DAIwZM8alz6tWreJNl+31hZCWeNpBhwStfW8IeUIbk9CABF75IaggFRsbi7Vr17Z5vmfPnmidxkqn02HFihVYsWJFm9f16NEDGzdu9PjdY8aMwf79+9s87036LG/6QkhHAk0oIYHzxE8Cr3xxFnhpnOQLbUzkBzksECGL84QSTjto2eIs8NI4yRdnDS+Nk3whzaH8IEGKCFloQgkNnMO1aQctX0jDGxpQkI38IEGKCFkoyig0SIjU8f+vI4FXttACHRpwWegB2kDKBRKkiJCFnC5DA9JIhQaxEU4+UrRAyxa1UxZ62kDKAxKkiJDFNQyY/pTlSlwECbyhgH2Btmehp3GSN5x/KI2TPKDVhwhZ4iJI0xEKaFQKRIe1LNCk6ZA1nJaX3id5Q+MkL0iQIkIWnVqJKJ2K/39CvnA7aBonecMv0CTwyhoaJ3lBghQR0qR2CQfgaj4i5EdqLDdOmnZaElKSGmuvRRpL4yRraJzkhaAJOQlCaP5630AcLjWif1e91F0hPLD4jkzcnlmJ0dcnSN0VwgPzbr8e/btG4+7BKVJ3hfDArFG9kBilo3GSCQzrTYpvwi+MRiOio6NRU1MDvZ4WeoIgCIIIBXxZv8m0RxAEQRAE4SckSBEEQRAEQfgJCVIEQRAEQRB+QoIUQRAEQRCEn5AgRRAEQRAE4SckSBEEQRAEQfgJCVIEQRAEQRB+QoIUQRAEQRCEn5AgRRAEQRAE4SckSBEEQRAEQfgJCVIEQRAEQRB+QoIUQRAEQRCEn5AgRRAEQRAE4ScqqTvQkWFZFoC9ijRBEARBEKEBt25z67gnSJASkNraWgBAamqqxD0hCIIgCMJXamtrER0d7bENw3ojbhF+YbPZUFpaiqioKDAM02Y7o9GI1NRUnD9/Hnq9XsQeygt6DnboOTigZ2GHnoMdeg526Dk4EOpZsCyL2tpapKSkQKHw7AVFGikBUSgU6Natm9ft9Xp9p38pAHoOHPQcHNCzsEPPwQ49Bzv0HBwI8Sza00RxkLM5QRAEQRCEn5AgRRAEQRAE4SckSMkArVaLF198EVqtVuquSAo9Bzv0HBzQs7BDz8EOPQc79BwcyOFZkLM5QRAEQRCEn5BGiiAIgiAIwk9IkCIIgiAIgvATEqQIgiAIgiD8hAQpgiAIgiAIPyFBiiAIgiAIwk9IkBKIixcv4qGHHkJcXBzCwsIwYMAA7N27lz9fUVGBRx55BCkpKQgPD8f48eNx/Phxl3uMGTMGDMO4fB5//HGxf0pA9OzZ85rfwDAM5s6dCwAwmUyYO3cu4uLiEBkZiSlTpqCiosLlHufOncOkSZMQHh6OxMREPPvss7BYLFL8HL8JxnNwd/1nn30mxc/xm/aew/vvv48xY8ZAr9eDYRhUV1dfc4+qqipMmzYNer0eMTExmDVrFurq6kT+JYETjGfh7h5//vOfRf4lgeHpOVRVVeH3v/89+vbti7CwMHTv3h1PPvkkampqXO7R0ecIb59DR5gjgPbfjd/+9re47rrrEBYWhoSEBNx99904duyYyz3E/JugEjECcPXqVdx000249dZb8d133yEhIQHHjx9Hly5dANhr+EyePBlqtRr/+c9/oNfrsWzZMuTk5ODIkSOIiIjg7zV79mwsWbKE/3d4eLjovycQ9uzZA6vVyv/70KFDuP3223HfffcBAObNm4dvv/0W69atQ3R0NPLy8nDPPfdg586dAACr1YpJkybBYDBg165dKCsrw/Tp06FWq/Hqq69K8pv8IdDnwLFq1SqMHz+e/3dMTIwo/Q8W7T2HhoYGjB8/HuPHj8fChQvd3mPatGkoKyvD5s2b0dzcjJkzZ2LOnDlYu3atKL8hWATjWQDAkiVLMHv2bP7fUVFRwnVaADw9h9LSUpSWluL1119HZmYmzp49i8cffxylpaX48ssvAXSOOcKb58AR6nME0P67MWzYMEybNg3du3dHVVUVXnrpJYwbNw6nT5+GUqkU/2+CJYLOc889x44aNarN8yUlJSwA9tChQ/wxq9XKJiQksB988AF/7JZbbmGfeuopIbsqOk899RR73XXXsTabja2urmbVajW7bt06/vzRo0dZAGxBQQHLsiy7ceNGVqFQsOXl5Xyb9957j9Xr9WxTU5Po/Q8Wvj4HlmVZAOy///1vCXorHM7PwZlt27axANirV6+6HD9y5AgLgN2zZw9/7LvvvmMZhmEvXrwoRpcFw9dnwbIs26NHD3b58uXidFAk2noOHF988QWr0WjY5uZmlmU7xxzhjtbPgWU75hzBsu0/i19++YUFwJ44cYJlWfH/Jsi0JwBff/01hg8fjvvuuw+JiYkYMmQIPvjgA/58U1MTAECn0/HHFAoFtFotfvrpJ5d7rVmzBvHx8ejfvz8WLlyIhoYGcX6EAJjNZnz66ad49NFHwTAMioqK0NzcjJycHL5Neno6unfvjoKCAgBAQUEBBgwYgKSkJL5Nbm4ujEYjDh8+LPpvCAb+PAeOuXPnIj4+HjfeeCM++ugjsCGcT7f1c/CGgoICxMTEYPjw4fyxnJwcKBQKFBYWCtVVwfHnWXD8+c9/RlxcHIYMGYK//vWvIWfScsab51BTUwO9Xg+Vym5Q6QxzhDtaPweOjjRHAO0/i/r6eqxatQppaWlITU0FIP7fBJn2BODUqVN47733MH/+fLzwwgvYs2cPnnzySWg0GsyYMYNfJBcuXIi///3viIiIwPLly3HhwgWUlZXx93nwwQfRo0cPpKSk4MCBA3juuedQUlKCr776SsJf5z/r169HdXU1HnnkEQBAeXk5NBrNNarnpKQklJeX822cXwbuPHcuFPHnOQB2E85tt92G8PBwbNq0Cb/73e9QV1eHJ598UsTeB4/Wz8EbysvLkZiY6HJMpVIhNjY2ZP8eAP+eBQA8+eSTGDp0KGJjY7Fr1y4sXLgQZWVlWLZsmTAdFZj2nsOVK1fw8ssvY86cOfyxzjBHtMbdcwA63hwBtP0s3n33XSxYsAD19fXo27cvNm/eDI1GA0D8vwkSpATAZrNh+PDhvC12yJAhOHToEFauXIkZM2ZArVbjq6++wqxZsxAbGwulUomcnBxMmDDBZffg/JIMGDAAycnJGDt2LE6ePInrrrtO9N8VKP/4xz8wYcIEpKSkSN0VSfH3OfzhD3/g/3/IkCGor6/HX//615CdJOnvwYG/z2L+/Pn8/w8cOBAajQa//e1vsXTp0pCsw+bpORiNRkyaNAmZmZl46aWXxO+ciPj7HDraHAG0/SymTZuG22+/HWVlZXj99dfxP//zP9i5c6eLpUcsyLQnAMnJycjMzHQ5lpGRgXPnzvH/HjZsGIqLi1FdXY2ysjLk5+ejsrISvXr1avO+WVlZAIATJ04I03EBOXv2LH744Qc89thj/DGDwQCz2XxNNFJFRQUMBgPfpnX0Gvdvrk0o4e9zcEdWVhYuXLjAm4pDCXfPwRsMBgMuXbrkcsxisaCqqiok/x4A/5+FO7KysmCxWHDmzJnAOyYynp5DbW0txo8fj6ioKPz73/+GWq3mz3WGOYLD03NwRyjPEYDnZxEdHY0+ffpg9OjR+PLLL3Hs2DH8+9//BiD+3wQJUgJw0003oaSkxOXYr7/+ih49elzTNjo6mo/q27t3L+6+++4271tcXAzALqiFGqtWrUJiYiImTZrEHxs2bBjUajW2bNnCHyspKcG5c+eQnZ0NAMjOzsbBgwddFs/NmzdDr9dfI6yGAv4+B3cUFxejS5cuIal5cPccvCE7OxvV1dUoKirij23duhU2m43faIQa/j4LdxQXF0OhUFxj/gwF2noORqMR48aNg0ajwddff32NxqEzzBFA+8/BHaE8RwDevxssy4JlWV5gFP1vIuju6wS7e/duVqVSsX/605/Y48ePs2vWrGHDw8PZTz/9lG/zxRdfsNu2bWNPnjzJrl+/nu3Rowd7zz338OdPnDjBLlmyhN27dy97+vRp9j//+Q/bq1cvdvTo0VL8pICwWq1s9+7d2eeee+6ac48//jjbvXt3duvWrezevXvZ7OxsNjs7mz9vsVjY/v37s+PGjWOLi4vZ/Px8NiEhgV24cKGYPyEoBPIcvv76a/aDDz5gDx48yB4/fpx999132fDwcHbx4sVi/oSg4Ok5lJWVsfv372c/+OADFgC7Y8cOdv/+/WxlZSXfZvz48eyQIUPYwsJC9qeffmL79OnDPvDAA2L+hKARyLPYtWsXu3z5cra4uJg9efIk++mnn7IJCQns9OnTxf4ZAdPWc6ipqWGzsrLYAQMGsCdOnGDLysr4j8ViYVm2c8wR3jyHjjRHsGzbz+LkyZPsq6++yu7du5c9e/Ysu3PnTvbOO+9kY2Nj2YqKCpZlxf+bIEFKIL755hu2f//+rFarZdPT09n333/f5fxbb73FduvWjVWr1Wz37t3ZRYsWuYRlnjt3jh09ejQbGxvLarVatnfv3uyzzz7L1tTUiP1TAub7779nAbAlJSXXnGtsbGR/97vfsV26dGHDw8PZ3/zmN2xZWZlLmzNnzrATJkxgw8LC2Pj4ePaZZ55xCfkNFQJ5Dt999x07ePBgNjIyko2IiGAHDRrErly5krVarWL+hKDg6Tm8+OKLLIBrPqtWreLbVFZWsg888AAbGRnJ6vV6dubMmWxtba2IvyB4BPIsioqK2KysLDY6OprV6XRsRkYG++qrr7Imk0nkXxE4bT0HLvWDu8/p06f5dh19jvDmOXSkOYJl234WFy9eZCdMmMAmJiayarWa7datG/vggw+yx44dc2kn5t8Ew7IhHhtJEARBEAQhEeQjRRAEQRAE4SckSBEEQRAEQfgJCVIEQRAEQRB+QoIUQRAEQRCEn5AgRRAEQRAE4SckSBEEQRAEQfgJCVIEQRAEQRB+QoIUQRAEQRCEn5AgRRAEQRAE4SckSBEEQRAEQfgJCVIEQRAEQRB+8v8B6pAjb22e8ycAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(res.seasonal[-30:])\n",
    "plt.title(\"Saisonnalité\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f0cd93f1d30>]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cor = acf(res.trend[5:-5], fft=True)\n",
    "plt.plot(cor)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On cherche maintenant la saisonnalité de la série débarrassée de sa tendance herbdomadaire. On retrouve la saisonnalité mensuelle."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 4 Axes>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "res_year = seasonal_decompose(res.trend[5:-5], period=25)\n",
    "res_year.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Test de stationnarité\n",
    "\n",
    "Le test [KPSS](https://en.wikipedia.org/wiki/KPSS_test) permet de tester la stationnarité d'une série."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_59627/406539216.py:2: InterpolationWarning: The test statistic is outside of the range of p-values available in the\n",
      "look-up table. The actual p-value is smaller than the p-value returned.\n",
      "\n",
      "  kpss(res.trend[5:-5])\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(np.float64(1.245031416161398),\n",
       " np.float64(0.01),\n",
       " 16,\n",
       " {'10%': 0.347, '5%': 0.463, '2.5%': 0.574, '1%': 0.739})"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from statsmodels.tsa.stattools import kpss\n",
    "\n",
    "kpss(res.trend[5:-5])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Comme ce n'est pas toujours facile à interpréter, on simule une variable aléatoire gaussienne donc sans tendance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_59627/3765297593.py:3: InterpolationWarning: The test statistic is outside of the range of p-values available in the\n",
      "look-up table. The actual p-value is greater than the p-value returned.\n",
      "\n",
      "  kpss(bruit)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(np.float64(0.11384797070848017),\n",
       " np.float64(0.1),\n",
       " 1,\n",
       " {'10%': 0.347, '5%': 0.463, '2.5%': 0.574, '1%': 0.739})"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from numpy.random import randn\n",
    "\n",
    "bruit = randn(1000)\n",
    "kpss(bruit)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Et puis une série avec une tendance forte."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_59627/2615492180.py:4: InterpolationWarning: The test statistic is outside of the range of p-values available in the\n",
      "look-up table. The actual p-value is smaller than the p-value returned.\n",
      "\n",
      "  kpss(bruit)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(np.float64(4.201503723150045),\n",
       " np.float64(0.01),\n",
       " 11,\n",
       " {'10%': 0.347, '5%': 0.463, '2.5%': 0.574, '1%': 0.739})"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from numpy.random import randn\n",
    "from numpy import arange\n",
    "\n",
    "bruit = randn(1000) * 100 + arange(1000) / 10\n",
    "kpss(bruit)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Une valeur forte indique une tendance et la série en a clairement une."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Prédiction\n",
    "\n",
    "Les modèles *AR*, *ARMA*, *ARIMA* se concentrent sur une série à une dimension. En machine learning, il y a la série et plein d'autres informations. On construit une matrice avec des séries décalées."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>value</th>\n",
       "      <th>notrend</th>\n",
       "      <th>trend</th>\n",
       "      <th>weekday</th>\n",
       "      <th>lag1</th>\n",
       "      <th>lag2</th>\n",
       "      <th>lag3</th>\n",
       "      <th>lag4</th>\n",
       "      <th>lag5</th>\n",
       "      <th>lag6</th>\n",
       "      <th>lag7</th>\n",
       "      <th>lag8</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>725</th>\n",
       "      <td>2025-02-28 00:39:51.820916</td>\n",
       "      <td>0.011877</td>\n",
       "      <td>0.002777</td>\n",
       "      <td>0.009100</td>\n",
       "      <td>4</td>\n",
       "      <td>0.009749</td>\n",
       "      <td>0.008428</td>\n",
       "      <td>0.007654</td>\n",
       "      <td>0.007989</td>\n",
       "      <td>0.016468</td>\n",
       "      <td>0.013102</td>\n",
       "      <td>0.009676</td>\n",
       "      <td>0.008109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>726</th>\n",
       "      <td>2025-03-01 00:39:51.820916</td>\n",
       "      <td>0.019454</td>\n",
       "      <td>0.010350</td>\n",
       "      <td>0.009105</td>\n",
       "      <td>5</td>\n",
       "      <td>0.011877</td>\n",
       "      <td>0.009749</td>\n",
       "      <td>0.008428</td>\n",
       "      <td>0.007654</td>\n",
       "      <td>0.007989</td>\n",
       "      <td>0.016468</td>\n",
       "      <td>0.013102</td>\n",
       "      <td>0.009676</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>728</th>\n",
       "      <td>2025-03-03 00:39:51.820916</td>\n",
       "      <td>0.005494</td>\n",
       "      <td>-0.003620</td>\n",
       "      <td>0.009114</td>\n",
       "      <td>0</td>\n",
       "      <td>0.019454</td>\n",
       "      <td>0.011877</td>\n",
       "      <td>0.009749</td>\n",
       "      <td>0.008428</td>\n",
       "      <td>0.007654</td>\n",
       "      <td>0.007989</td>\n",
       "      <td>0.016468</td>\n",
       "      <td>0.013102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>729</th>\n",
       "      <td>2025-03-04 00:39:51.820916</td>\n",
       "      <td>0.007479</td>\n",
       "      <td>-0.001639</td>\n",
       "      <td>0.009118</td>\n",
       "      <td>1</td>\n",
       "      <td>0.005494</td>\n",
       "      <td>0.019454</td>\n",
       "      <td>0.011877</td>\n",
       "      <td>0.009749</td>\n",
       "      <td>0.008428</td>\n",
       "      <td>0.007654</td>\n",
       "      <td>0.007989</td>\n",
       "      <td>0.016468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>730</th>\n",
       "      <td>2025-03-05 00:39:51.820916</td>\n",
       "      <td>0.007589</td>\n",
       "      <td>-0.001534</td>\n",
       "      <td>0.009123</td>\n",
       "      <td>2</td>\n",
       "      <td>0.007479</td>\n",
       "      <td>0.005494</td>\n",
       "      <td>0.019454</td>\n",
       "      <td>0.011877</td>\n",
       "      <td>0.009749</td>\n",
       "      <td>0.008428</td>\n",
       "      <td>0.007654</td>\n",
       "      <td>0.007989</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          date     value   notrend     trend  weekday  \\\n",
       "725 2025-02-28 00:39:51.820916  0.011877  0.002777  0.009100        4   \n",
       "726 2025-03-01 00:39:51.820916  0.019454  0.010350  0.009105        5   \n",
       "728 2025-03-03 00:39:51.820916  0.005494 -0.003620  0.009114        0   \n",
       "729 2025-03-04 00:39:51.820916  0.007479 -0.001639  0.009118        1   \n",
       "730 2025-03-05 00:39:51.820916  0.007589 -0.001534  0.009123        2   \n",
       "\n",
       "         lag1      lag2      lag3      lag4      lag5      lag6      lag7  \\\n",
       "725  0.009749  0.008428  0.007654  0.007989  0.016468  0.013102  0.009676   \n",
       "726  0.011877  0.009749  0.008428  0.007654  0.007989  0.016468  0.013102   \n",
       "728  0.019454  0.011877  0.009749  0.008428  0.007654  0.007989  0.016468   \n",
       "729  0.005494  0.019454  0.011877  0.009749  0.008428  0.007654  0.007989   \n",
       "730  0.007479  0.005494  0.019454  0.011877  0.009749  0.008428  0.007654   \n",
       "\n",
       "         lag8  \n",
       "725  0.008109  \n",
       "726  0.009676  \n",
       "728  0.013102  \n",
       "729  0.016468  \n",
       "730  0.007989  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from statsmodels.tsa.tsatools import lagmat\n",
    "\n",
    "lag = 8\n",
    "X = lagmat(df_nosunday[\"value\"], lag)\n",
    "lagged = df_nosunday.copy()\n",
    "for c in range(1, lag + 1):\n",
    "    lagged[\"lag%d\" % c] = X[:, c - 1]\n",
    "lagged.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On ajoute ou on réécrit le jour de la semaine qu'on utilise comme variable supplémentaire."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "lagged[\"weekday\"] = lagged.date.dt.weekday"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((627, 9), (627,))"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = lagged.drop([\"date\", \"value\", \"notrend\", \"trend\"], axis=1)\n",
    "Y = lagged[\"value\"]\n",
    "X.shape, Y.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/xadupre/vv/this312/lib/python3.12/site-packages/numpy/lib/_function_base_impl.py:3045: RuntimeWarning: invalid value encountered in divide\n",
      "  c /= stddev[:, None]\n",
      "/home/xadupre/vv/this312/lib/python3.12/site-packages/numpy/lib/_function_base_impl.py:3046: RuntimeWarning: invalid value encountered in divide\n",
      "  c /= stddev[None, :]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,  1.        ,  0.99999247, ..., -0.69791204,\n",
       "         0.99986414,  0.99996236],\n",
       "       [        nan,  0.99999247,  1.        , ..., -0.69925528,\n",
       "         0.99991238,  0.99996712],\n",
       "       ...,\n",
       "       [        nan, -0.69791204, -0.69925528, ...,  1.        ,\n",
       "        -0.70192748, -0.70219418],\n",
       "       [        nan,  0.99986414,  0.99991238, ..., -0.70192748,\n",
       "         1.        ,  0.99987949],\n",
       "       [        nan,  0.99996236,  0.99996712, ..., -0.70219418,\n",
       "         0.99987949,  1.        ]], shape=(627, 627))"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from numpy import corrcoef\n",
    "\n",
    "corrcoef(X)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Etrange autant de grandes valeurs, cela veut dire que la tendance est trop forte pour calculer des corrélations, il vaudrait mieux tout recommencer avec la série $\\Delta Y_t = Y_t - Y_{t-1}$. Bref, passons..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['weekday', 'lag1', 'lag2', 'lag3', 'lag4', 'lag5', 'lag6', 'lag7',\n",
       "       'lag8'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Une régression linéaire car les modèles linéaires sont toujours de bonnes baseline et pour connaître le modèle simulé, on ne fera pas beaucoup mieux."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: #000;\n",
       "  --sklearn-color-text-muted: #666;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-1 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-1 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: flex;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "  align-items: start;\n",
       "  justify-content: space-between;\n",
       "  gap: 0.5em;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label .caption {\n",
       "  font-size: 0.6rem;\n",
       "  font-weight: lighter;\n",
       "  color: var(--sklearn-color-text-muted);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-1 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-1 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 0.5em;\n",
       "  text-align: center;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-1 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LinearRegression()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>LinearRegression</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.linear_model.LinearRegression.html\">?<span>Documentation for LinearRegression</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></div></label><div class=\"sk-toggleable__content fitted\"><pre>LinearRegression()</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "\n",
    "clr = LinearRegression()\n",
    "clr.fit(X, Y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8750652931937053"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics import r2_score\n",
    "\n",
    "r2_score(Y, clr.predict(X))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.00171654,  0.35489858,  0.2667268 ,  0.07460985,  0.01104078,\n",
       "       -0.06234941,  0.37933643, -0.12027835, -0.05625968])"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clr.coef_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On retrouve la saisonnalité, $Y_t$ et $Y_{t-6}$ sont de mèches."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X(t-1) -0.5343370770216411\n",
      "X(t-2) -0.9776153682766282\n",
      "X(t-3) -1.2540090159405772\n",
      "X(t-4) -1.01367860631983\n",
      "X(t-5) -0.602451646171541\n",
      "X(t-6) 0.7635187615860253\n",
      "X(t-7) -0.6454355106118854\n",
      "X(t-8) -1.0867844309933337\n"
     ]
    }
   ],
   "source": [
    "for i in range(1, X.shape[1]):\n",
    "    print(\"X(t-%d)\" % (i), r2_score(Y, X.iloc[:, i]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Auparavant (l'année dernière en fait), je construisais deux bases, apprentissage et tests, comme ceci :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "n = X.shape[0]\n",
    "X_train = X.iloc[: n * 2 // 3]\n",
    "X_test = X.iloc[n * 2 // 3 :]\n",
    "Y_train = Y[: n * 2 // 3]\n",
    "Y_test = Y[n * 2 // 3 :]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Et puis *scikit-learn* est arrivée avec [TimeSeriesSplit](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.TimeSeriesSplit.html)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TRAIN: (107, 13) TEST: (104, 13)\n",
      "TRAIN: (211, 13) TEST: (104, 13)\n",
      "TRAIN: (315, 13) TEST: (104, 13)\n",
      "TRAIN: (419, 13) TEST: (104, 13)\n",
      "TRAIN: (523, 13) TEST: (104, 13)\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import TimeSeriesSplit\n",
    "\n",
    "tscv = TimeSeriesSplit(n_splits=5)\n",
    "for train_index, test_index in tscv.split(lagged):\n",
    "    data_train, data_test = lagged.iloc[train_index, :], lagged.iloc[test_index, :]\n",
    "    print(\"TRAIN:\", data_train.shape, \"TEST:\", data_test.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Et on calé une forêt aléatoire..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.7830797306279333\n",
      "0.7892143392871785 0.710251489079545\n",
      "0.926515934247996 0.9254337080628354\n",
      "0.811090703869577 0.7717494202307796\n",
      "0.7646201099598264 0.6571969210691542\n"
     ]
    }
   ],
   "source": [
    "import warnings\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "\n",
    "clr = RandomForestRegressor()\n",
    "\n",
    "\n",
    "def train_test(clr, train_index, test_index):\n",
    "    data_train = lagged.iloc[train_index, :]\n",
    "    data_test = lagged.iloc[test_index, :]\n",
    "    clr.fit(\n",
    "        data_train.drop([\"value\", \"date\", \"notrend\", \"trend\"], axis=1), data_train.value\n",
    "    )\n",
    "    r2 = r2_score(\n",
    "        data_test.value,\n",
    "        clr.predict(\n",
    "            data_test.drop([\"value\", \"date\", \"notrend\", \"trend\"], axis=1).values\n",
    "        ),\n",
    "    )\n",
    "    return r2\n",
    "\n",
    "\n",
    "warnings.simplefilter(\"ignore\")\n",
    "last_test_index = None\n",
    "for train_index, test_index in tscv.split(lagged):\n",
    "    r2 = train_test(clr, train_index, test_index)\n",
    "    if last_test_index is not None:\n",
    "        r2_prime = train_test(clr, last_test_index, test_index)\n",
    "        print(r2, r2_prime)\n",
    "    else:\n",
    "        print(r2)\n",
    "    last_test_index = test_index"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2 ans coupé en 5, soit tous les 5 mois, ça veut dire que ce découpage inclut parfois Noël, parfois l'été et que les performances y seront très sensibles."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6571969210691542"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics import r2_score\n",
    "\n",
    "r2 = r2_score(\n",
    "    data_test.value,\n",
    "    clr.predict(data_test.drop([\"value\", \"date\", \"notrend\", \"trend\"], axis=1).values),\n",
    ")\n",
    "r2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On compare avec le $r_2$ avec le même $r_2$ obtenu en utilisant $Y_{t-1}$, $Y_{t-2}$, ... $Y_{t-d}$ comme prédiction."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 : -0.5315727068325993\n",
      "2 : -1.0250735581487076\n",
      "3 : -1.3208901364676007\n",
      "4 : -1.074139284130378\n",
      "5 : -0.6238251202278204\n",
      "6 : 0.657764576444329\n",
      "7 : -0.7208207891388771\n",
      "8 : -1.1824818758877917\n"
     ]
    }
   ],
   "source": [
    "for i in range(1, 9):\n",
    "    print(i, \":\", r2_score(data_test.value, data_test[\"lag%d\" % i]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>value</th>\n",
       "      <th>notrend</th>\n",
       "      <th>trend</th>\n",
       "      <th>weekday</th>\n",
       "      <th>lag1</th>\n",
       "      <th>lag2</th>\n",
       "      <th>lag3</th>\n",
       "      <th>lag4</th>\n",
       "      <th>lag5</th>\n",
       "      <th>lag6</th>\n",
       "      <th>lag7</th>\n",
       "      <th>lag8</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2023-03-06 00:39:51.820916</td>\n",
       "      <td>0.005036</td>\n",
       "      <td>-0.000797</td>\n",
       "      <td>0.005833</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2023-03-07 00:39:51.820916</td>\n",
       "      <td>0.004769</td>\n",
       "      <td>-0.001068</td>\n",
       "      <td>0.005837</td>\n",
       "      <td>1</td>\n",
       "      <td>0.005036</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2023-03-08 00:39:51.820916</td>\n",
       "      <td>0.006293</td>\n",
       "      <td>0.000451</td>\n",
       "      <td>0.005842</td>\n",
       "      <td>2</td>\n",
       "      <td>0.004769</td>\n",
       "      <td>0.005036</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2023-03-09 00:39:51.820916</td>\n",
       "      <td>0.006932</td>\n",
       "      <td>0.001086</td>\n",
       "      <td>0.005846</td>\n",
       "      <td>3</td>\n",
       "      <td>0.006293</td>\n",
       "      <td>0.004769</td>\n",
       "      <td>0.005036</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2023-03-10 00:39:51.820916</td>\n",
       "      <td>0.008666</td>\n",
       "      <td>0.002815</td>\n",
       "      <td>0.005851</td>\n",
       "      <td>4</td>\n",
       "      <td>0.006932</td>\n",
       "      <td>0.006293</td>\n",
       "      <td>0.004769</td>\n",
       "      <td>0.005036</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        date     value   notrend     trend  weekday      lag1  \\\n",
       "0 2023-03-06 00:39:51.820916  0.005036 -0.000797  0.005833        0  0.000000   \n",
       "1 2023-03-07 00:39:51.820916  0.004769 -0.001068  0.005837        1  0.005036   \n",
       "2 2023-03-08 00:39:51.820916  0.006293  0.000451  0.005842        2  0.004769   \n",
       "3 2023-03-09 00:39:51.820916  0.006932  0.001086  0.005846        3  0.006293   \n",
       "4 2023-03-10 00:39:51.820916  0.008666  0.002815  0.005851        4  0.006932   \n",
       "\n",
       "       lag2      lag3      lag4  lag5  lag6  lag7  lag8  \n",
       "0  0.000000  0.000000  0.000000   0.0   0.0   0.0   0.0  \n",
       "1  0.000000  0.000000  0.000000   0.0   0.0   0.0   0.0  \n",
       "2  0.005036  0.000000  0.000000   0.0   0.0   0.0   0.0  \n",
       "3  0.004769  0.005036  0.000000   0.0   0.0   0.0   0.0  \n",
       "4  0.006293  0.004769  0.005036   0.0   0.0   0.0   0.0  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lagged[:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "En fait le jour de la semaine est une variable catégorielle, on crée une colonne par jour."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.compose import ColumnTransformer\n",
    "from sklearn.preprocessing import OneHotEncoder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.        , 0.        , 0.        , 0.        , 0.        ,\n",
       "        0.        , 0.        , 0.        , 1.        , 0.        ,\n",
       "        0.        , 0.        , 0.        , 0.        ],\n",
       "       [0.00503561, 0.        , 0.        , 0.        , 0.        ,\n",
       "        0.        , 0.        , 0.        , 0.        , 1.        ,\n",
       "        0.        , 0.        , 0.        , 0.        ],\n",
       "       [0.00476948, 0.00503561, 0.        , 0.        , 0.        ,\n",
       "        0.        , 0.        , 0.        , 0.        , 0.        ,\n",
       "        1.        , 0.        , 0.        , 0.        ],\n",
       "       [0.00629279, 0.00476948, 0.00503561, 0.        , 0.        ,\n",
       "        0.        , 0.        , 0.        , 0.        , 0.        ,\n",
       "        0.        , 1.        , 0.        , 0.        ],\n",
       "       [0.00693242, 0.00629279, 0.00476948, 0.00503561, 0.        ,\n",
       "        0.        , 0.        , 0.        , 0.        , 0.        ,\n",
       "        0.        , 0.        , 1.        , 0.        ]])"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cols = [\"lag1\", \"lag2\", \"lag3\", \"lag4\", \"lag5\", \"lag6\", \"lag7\", \"lag8\"]\n",
    "ct = ColumnTransformer(\n",
    "    [(\"pass\", \"passthrough\", cols), (\"dummies\", OneHotEncoder(), [\"weekday\"])]\n",
    ")\n",
    "pred = ct.fit(lagged).transform(lagged[:5])\n",
    "pred"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On met tout dans un pipeline parce que c'est plus joli, plus pratique aussi."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-2 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: #000;\n",
       "  --sklearn-color-text-muted: #666;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-2 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-2 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-2 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: flex;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "  align-items: start;\n",
       "  justify-content: space-between;\n",
       "  gap: 0.5em;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label .caption {\n",
       "  font-size: 0.6rem;\n",
       "  font-weight: lighter;\n",
       "  color: var(--sklearn-color-text-muted);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-2 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-2 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-2 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-2 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 0.5em;\n",
       "  text-align: center;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-2 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;pipeline&#x27;,\n",
       "                 Pipeline(steps=[(&#x27;columntransformer&#x27;,\n",
       "                                  ColumnTransformer(transformers=[(&#x27;pass&#x27;,\n",
       "                                                                   &#x27;passthrough&#x27;,\n",
       "                                                                   [&#x27;lag1&#x27;,\n",
       "                                                                    &#x27;lag2&#x27;,\n",
       "                                                                    &#x27;lag3&#x27;,\n",
       "                                                                    &#x27;lag4&#x27;,\n",
       "                                                                    &#x27;lag5&#x27;,\n",
       "                                                                    &#x27;lag6&#x27;,\n",
       "                                                                    &#x27;lag7&#x27;,\n",
       "                                                                    &#x27;lag8&#x27;]),\n",
       "                                                                  (&#x27;dummies&#x27;,\n",
       "                                                                   Pipeline(steps=[(&#x27;onehotencoder&#x27;,\n",
       "                                                                                    OneHotEncoder()),\n",
       "                                                                                   (&#x27;truncatedsvd&#x27;,\n",
       "                                                                                    TruncatedSVD())]),\n",
       "                                                                   [&#x27;weekday&#x27;])])),\n",
       "                                 (&#x27;linearregression&#x27;, LinearRegression())]))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" ><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>Pipeline</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></div></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;pipeline&#x27;,\n",
       "                 Pipeline(steps=[(&#x27;columntransformer&#x27;,\n",
       "                                  ColumnTransformer(transformers=[(&#x27;pass&#x27;,\n",
       "                                                                   &#x27;passthrough&#x27;,\n",
       "                                                                   [&#x27;lag1&#x27;,\n",
       "                                                                    &#x27;lag2&#x27;,\n",
       "                                                                    &#x27;lag3&#x27;,\n",
       "                                                                    &#x27;lag4&#x27;,\n",
       "                                                                    &#x27;lag5&#x27;,\n",
       "                                                                    &#x27;lag6&#x27;,\n",
       "                                                                    &#x27;lag7&#x27;,\n",
       "                                                                    &#x27;lag8&#x27;]),\n",
       "                                                                  (&#x27;dummies&#x27;,\n",
       "                                                                   Pipeline(steps=[(&#x27;onehotencoder&#x27;,\n",
       "                                                                                    OneHotEncoder()),\n",
       "                                                                                   (&#x27;truncatedsvd&#x27;,\n",
       "                                                                                    TruncatedSVD())]),\n",
       "                                                                   [&#x27;weekday&#x27;])])),\n",
       "                                 (&#x27;linearregression&#x27;, LinearRegression())]))])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" ><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>pipeline: Pipeline</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for pipeline: Pipeline</span></a></div></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;columntransformer&#x27;,\n",
       "                 ColumnTransformer(transformers=[(&#x27;pass&#x27;, &#x27;passthrough&#x27;,\n",
       "                                                  [&#x27;lag1&#x27;, &#x27;lag2&#x27;, &#x27;lag3&#x27;,\n",
       "                                                   &#x27;lag4&#x27;, &#x27;lag5&#x27;, &#x27;lag6&#x27;,\n",
       "                                                   &#x27;lag7&#x27;, &#x27;lag8&#x27;]),\n",
       "                                                 (&#x27;dummies&#x27;,\n",
       "                                                  Pipeline(steps=[(&#x27;onehotencoder&#x27;,\n",
       "                                                                   OneHotEncoder()),\n",
       "                                                                  (&#x27;truncatedsvd&#x27;,\n",
       "                                                                   TruncatedSVD())]),\n",
       "                                                  [&#x27;weekday&#x27;])])),\n",
       "                (&#x27;linearregression&#x27;, LinearRegression())])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" ><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>columntransformer: ColumnTransformer</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.compose.ColumnTransformer.html\">?<span>Documentation for columntransformer: ColumnTransformer</span></a></div></label><div class=\"sk-toggleable__content fitted\"><pre>ColumnTransformer(transformers=[(&#x27;pass&#x27;, &#x27;passthrough&#x27;,\n",
       "                                 [&#x27;lag1&#x27;, &#x27;lag2&#x27;, &#x27;lag3&#x27;, &#x27;lag4&#x27;, &#x27;lag5&#x27;,\n",
       "                                  &#x27;lag6&#x27;, &#x27;lag7&#x27;, &#x27;lag8&#x27;]),\n",
       "                                (&#x27;dummies&#x27;,\n",
       "                                 Pipeline(steps=[(&#x27;onehotencoder&#x27;,\n",
       "                                                  OneHotEncoder()),\n",
       "                                                 (&#x27;truncatedsvd&#x27;,\n",
       "                                                  TruncatedSVD())]),\n",
       "                                 [&#x27;weekday&#x27;])])</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-5\" type=\"checkbox\" ><label for=\"sk-estimator-id-5\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>pass</div></div></label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;lag1&#x27;, &#x27;lag2&#x27;, &#x27;lag3&#x27;, &#x27;lag4&#x27;, &#x27;lag5&#x27;, &#x27;lag6&#x27;, &#x27;lag7&#x27;, &#x27;lag8&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-6\" type=\"checkbox\" ><label for=\"sk-estimator-id-6\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>passthrough</div></div></label><div class=\"sk-toggleable__content fitted\"><pre>passthrough</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-7\" type=\"checkbox\" ><label for=\"sk-estimator-id-7\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>dummies</div></div></label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;weekday&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-8\" type=\"checkbox\" ><label for=\"sk-estimator-id-8\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>OneHotEncoder</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.preprocessing.OneHotEncoder.html\">?<span>Documentation for OneHotEncoder</span></a></div></label><div class=\"sk-toggleable__content fitted\"><pre>OneHotEncoder()</pre></div> </div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-9\" type=\"checkbox\" ><label for=\"sk-estimator-id-9\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>TruncatedSVD</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.decomposition.TruncatedSVD.html\">?<span>Documentation for TruncatedSVD</span></a></div></label><div class=\"sk-toggleable__content fitted\"><pre>TruncatedSVD()</pre></div> </div></div></div></div></div></div></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-10\" type=\"checkbox\" ><label for=\"sk-estimator-id-10\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>LinearRegression</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.linear_model.LinearRegression.html\">?<span>Documentation for LinearRegression</span></a></div></label><div class=\"sk-toggleable__content fitted\"><pre>LinearRegression()</pre></div> </div></div></div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('pipeline',\n",
       "                 Pipeline(steps=[('columntransformer',\n",
       "                                  ColumnTransformer(transformers=[('pass',\n",
       "                                                                   'passthrough',\n",
       "                                                                   ['lag1',\n",
       "                                                                    'lag2',\n",
       "                                                                    'lag3',\n",
       "                                                                    'lag4',\n",
       "                                                                    'lag5',\n",
       "                                                                    'lag6',\n",
       "                                                                    'lag7',\n",
       "                                                                    'lag8']),\n",
       "                                                                  ('dummies',\n",
       "                                                                   Pipeline(steps=[('onehotencoder',\n",
       "                                                                                    OneHotEncoder()),\n",
       "                                                                                   ('truncatedsvd',\n",
       "                                                                                    TruncatedSVD())]),\n",
       "                                                                   ['weekday'])])),\n",
       "                                 ('linearregression', LinearRegression())]))])"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.pipeline import make_pipeline\n",
    "from sklearn.decomposition import PCA, TruncatedSVD\n",
    "\n",
    "cols = [\"lag1\", \"lag2\", \"lag3\", \"lag4\", \"lag5\", \"lag6\", \"lag7\", \"lag8\"]\n",
    "model = make_pipeline(\n",
    "    make_pipeline(\n",
    "        ColumnTransformer(\n",
    "            [\n",
    "                (\"pass\", \"passthrough\", cols),\n",
    "                (\n",
    "                    \"dummies\",\n",
    "                    make_pipeline(OneHotEncoder(), TruncatedSVD(n_components=2)),\n",
    "                    [\"weekday\"],\n",
    "                ),\n",
    "            ]\n",
    "        ),\n",
    "        LinearRegression(),\n",
    "    )\n",
    ")\n",
    "model.fit(lagged, lagged[\"value\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "C'est plus facile à voir visuellement."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8302843587445363"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r2_score(lagged[\"value\"], model.predict(lagged))"
   ]
  }
 ],
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