{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exponential smoothing\n",
    "\n",
    "Let us consider chapter 7 of the excellent treatise on the subject of Exponential Smoothing By Hyndman and Athanasopoulos [1].\n",
    "We will work through all the examples in the chapter as they unfold.\n",
    "\n",
    "[1] [Hyndman, Rob J., and George Athanasopoulos. Forecasting: principles and practice. OTexts, 2014.](https://www.otexts.org/fpp/7)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loading data\n",
    "\n",
    "First we load some data. We have included the R data in the notebook for expedience."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-07T12:39:15.020317Z",
     "start_time": "2017-12-07T12:39:14.263100Z"
    }
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from statsmodels.tsa.api import ExponentialSmoothing, SimpleExpSmoothing, Holt\n",
    "%matplotlib inline\n",
    "\n",
    "data = [446.6565,  454.4733,  455.663 ,  423.6322,  456.2713,  440.5881, 425.3325,  485.1494,  506.0482,  526.792 ,  514.2689,  494.211 ]\n",
    "index= pd.date_range(start='1996', end='2008', freq='A')\n",
    "oildata = pd.Series(data, index)\n",
    "\n",
    "data = [17.5534,  21.86  ,  23.8866,  26.9293,  26.8885,  28.8314, 30.0751,  30.9535,  30.1857,  31.5797,  32.5776,  33.4774, 39.0216,  41.3864,  41.5966]\n",
    "index= pd.date_range(start='1990', end='2005', freq='A')\n",
    "air = pd.Series(data, index)\n",
    "\n",
    "data = [263.9177,  268.3072,  260.6626,  266.6394,  277.5158,  283.834 , 290.309 ,  292.4742,  300.8307,  309.2867,  318.3311,  329.3724, 338.884 ,  339.2441,  328.6006,  314.2554,  314.4597,  321.4138, 329.7893,  346.3852,  352.2979,  348.3705,  417.5629,  417.1236, 417.7495,  412.2339,  411.9468,  394.6971,  401.4993,  408.2705, 414.2428]\n",
    "index= pd.date_range(start='1970', end='2001', freq='A')\n",
    "livestock2 = pd.Series(data, index)\n",
    "\n",
    "data = [407.9979 ,  403.4608,  413.8249,  428.105 ,  445.3387,  452.9942, 455.7402]\n",
    "index= pd.date_range(start='2001', end='2008', freq='A')\n",
    "livestock3 = pd.Series(data, index)\n",
    "\n",
    "data = [41.7275,  24.0418,  32.3281,  37.3287,  46.2132,  29.3463, 36.4829,  42.9777,  48.9015,  31.1802,  37.7179,  40.4202, 51.2069,  31.8872,  40.9783,  43.7725,  55.5586,  33.8509, 42.0764,  45.6423,  59.7668,  35.1919,  44.3197,  47.9137]\n",
    "index= pd.date_range(start='2005', end='2010-Q4', freq='QS-OCT')\n",
    "aust = pd.Series(data, index)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simple Exponential Smoothing\n",
    "Lets use Simple Exponential Smoothing to forecast the below oil data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-07T12:39:15.189907Z",
     "start_time": "2017-12-07T12:39:15.022229Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Figure 7.1: Oil production in Saudi Arabia from 1996 to 2007.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax=oildata.plot()\n",
    "ax.set_xlabel(\"Year\")\n",
    "ax.set_ylabel(\"Oil (millions of tonnes)\")\n",
    "print(\"Figure 7.1: Oil production in Saudi Arabia from 1996 to 2007.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we run three variants of simple exponential smoothing:\n",
    "1. In ```fit1``` we do not use the auto optimization but instead choose to explicitly provide the model with the $\\alpha=0.2$ parameter\n",
    "2. In ```fit2``` as above we choose an $\\alpha=0.6$\n",
    "3. In ```fit3``` we allow statsmodels to automatically find an optimized $\\alpha$ value for us. This is the recommended approach."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-07T12:39:15.785068Z",
     "start_time": "2017-12-07T12:39:15.191930Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fe5f1387a60>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fit1 = SimpleExpSmoothing(oildata, initialization_method=\"heuristic\").fit(smoothing_level=0.2,optimized=False)\n",
    "fcast1 = fit1.forecast(3).rename(r'$\\alpha=0.2$')\n",
    "fit2 = SimpleExpSmoothing(oildata, initialization_method=\"heuristic\").fit(smoothing_level=0.6,optimized=False)\n",
    "fcast2 = fit2.forecast(3).rename(r'$\\alpha=0.6$')\n",
    "fit3 = SimpleExpSmoothing(oildata, initialization_method=\"estimated\").fit()\n",
    "fcast3 = fit3.forecast(3).rename(r'$\\alpha=%s$'%fit3.model.params['smoothing_level'])\n",
    "\n",
    "plt.figure(figsize=(12, 8))\n",
    "plt.plot(oildata, marker='o', color='black')\n",
    "plt.plot(fit1.fittedvalues, marker='o', color='blue')\n",
    "line1, = plt.plot(fcast1, marker='o', color='blue')\n",
    "plt.plot(fit2.fittedvalues, marker='o', color='red')\n",
    "line2, = plt.plot(fcast2, marker='o', color='red')\n",
    "plt.plot(fit3.fittedvalues, marker='o', color='green')\n",
    "line3, = plt.plot(fcast3, marker='o', color='green')\n",
    "plt.legend([line1, line2, line3], [fcast1.name, fcast2.name, fcast3.name])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Holt's Method\n",
    "\n",
    "Lets take a look at another example.\n",
    "This time we use air pollution data and the Holt's Method.\n",
    "We will fit three examples again.\n",
    "1. In ```fit1``` we again choose not to use the optimizer and provide explicit values for $\\alpha=0.8$ and $\\beta=0.2$\n",
    "2. In ```fit2``` we do the same as in ```fit1``` but choose to use an exponential model rather than a Holt's additive model.\n",
    "3. In ```fit3``` we used a damped versions of the Holt's additive model but allow the dampening parameter $\\phi$ to be optimized while fixing the values for $\\alpha=0.8$ and $\\beta=0.2$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-07T12:39:16.114361Z",
     "start_time": "2017-12-07T12:39:15.786542Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fe5f10d8ee0>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fit1 = Holt(air, initialization_method=\"estimated\").fit(smoothing_level=0.8, smoothing_trend=0.2, optimized=False)\n",
    "fcast1 = fit1.forecast(5).rename(\"Holt's linear trend\")\n",
    "fit2 = Holt(air, exponential=True, initialization_method=\"estimated\").fit(smoothing_level=0.8, smoothing_trend=0.2, optimized=False)\n",
    "fcast2 = fit2.forecast(5).rename(\"Exponential trend\")\n",
    "fit3 = Holt(air, damped_trend=True, initialization_method=\"estimated\").fit(smoothing_level=0.8, smoothing_trend=0.2)\n",
    "fcast3 = fit3.forecast(5).rename(\"Additive damped trend\")\n",
    "\n",
    "plt.figure(figsize=(12, 8))\n",
    "plt.plot(air, marker='o', color='black')\n",
    "plt.plot(fit1.fittedvalues, color='blue')\n",
    "line1, = plt.plot(fcast1, marker='o', color='blue')\n",
    "plt.plot(fit2.fittedvalues, color='red')\n",
    "line2, = plt.plot(fcast2, marker='o', color='red')\n",
    "plt.plot(fit3.fittedvalues, color='green')\n",
    "line3, = plt.plot(fcast3, marker='o', color='green')\n",
    "plt.legend([line1, line2, line3], [fcast1.name, fcast2.name, fcast3.name])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Seasonally adjusted data\n",
    "Lets look at some seasonally adjusted livestock data. We fit five Holt's models.\n",
    "The below table allows us to compare results when we use exponential versus additive and damped versus non-damped.\n",
    " \n",
    "Note: ```fit4``` does not allow the parameter $\\phi$ to be optimized by providing a fixed value of $\\phi=0.98$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-07T12:39:16.605618Z",
     "start_time": "2017-12-07T12:39:16.116424Z"
    }
   },
   "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>SES</th>\n",
       "      <th>Holt's</th>\n",
       "      <th>Exponential</th>\n",
       "      <th>Additive</th>\n",
       "      <th>Multiplicative</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>$\\alpha$</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.974316</td>\n",
       "      <td>0.977633</td>\n",
       "      <td>9.788623e-01</td>\n",
       "      <td>0.974913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$\\beta$</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.437128e-11</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$\\phi$</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.800000e-01</td>\n",
       "      <td>0.981646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$l_0$</th>\n",
       "      <td>263.917698</td>\n",
       "      <td>258.882555</td>\n",
       "      <td>260.344565</td>\n",
       "      <td>2.573572e+02</td>\n",
       "      <td>258.951736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$b_0$</th>\n",
       "      <td>NaN</td>\n",
       "      <td>5.010839</td>\n",
       "      <td>1.013780</td>\n",
       "      <td>6.645778e+00</td>\n",
       "      <td>1.038145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SSE</th>\n",
       "      <td>6761.350235</td>\n",
       "      <td>6004.138201</td>\n",
       "      <td>6104.194756</td>\n",
       "      <td>6.036555e+03</td>\n",
       "      <td>6081.995046</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  SES       Holt's  Exponential      Additive  Multiplicative\n",
       "$\\alpha$     1.000000     0.974316     0.977633  9.788623e-01        0.974913\n",
       "$\\beta$           NaN     0.000000     0.000000  7.437128e-11        0.000000\n",
       "$\\phi$            NaN          NaN          NaN  9.800000e-01        0.981646\n",
       "$l_0$      263.917698   258.882555   260.344565  2.573572e+02      258.951736\n",
       "$b_0$             NaN     5.010839     1.013780  6.645778e+00        1.038145\n",
       "SSE       6761.350235  6004.138201  6104.194756  6.036555e+03     6081.995046"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fit1 = SimpleExpSmoothing(livestock2, initialization_method=\"estimated\").fit()\n",
    "fit2 = Holt(livestock2, initialization_method=\"estimated\").fit()\n",
    "fit3 = Holt(livestock2,exponential=True, initialization_method=\"estimated\").fit()\n",
    "fit4 = Holt(livestock2,damped_trend=True, initialization_method=\"estimated\").fit(damping_trend=0.98)\n",
    "fit5 = Holt(livestock2,exponential=True, damped_trend=True, initialization_method=\"estimated\").fit()\n",
    "params = ['smoothing_level', 'smoothing_trend', 'damping_trend', 'initial_level', 'initial_trend']\n",
    "results=pd.DataFrame(index=[r\"$\\alpha$\",r\"$\\beta$\",r\"$\\phi$\",r\"$l_0$\",\"$b_0$\",\"SSE\"] ,columns=['SES', \"Holt's\",\"Exponential\", \"Additive\", \"Multiplicative\"])\n",
    "results[\"SES\"] =            [fit1.params[p] for p in params] + [fit1.sse]\n",
    "results[\"Holt's\"] =         [fit2.params[p] for p in params] + [fit2.sse]\n",
    "results[\"Exponential\"] =    [fit3.params[p] for p in params] + [fit3.sse]\n",
    "results[\"Additive\"] =       [fit4.params[p] for p in params] + [fit4.sse]\n",
    "results[\"Multiplicative\"] = [fit5.params[p] for p in params] + [fit5.sse]\n",
    "results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plots of Seasonally Adjusted Data\n",
    "The following plots allow us to evaluate the level and slope/trend components of the above table's fits."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-07T12:39:17.105928Z",
     "start_time": "2017-12-07T12:39:16.607306Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Figure 7.4: Level and slope components for Holt’s linear trend method and the additive damped trend method.\n"
     ]
    }
   ],
   "source": [
    "for fit in [fit2,fit4]:\n",
    "    pd.DataFrame(np.c_[fit.level,fit.trend]).rename(\n",
    "        columns={0:'level',1:'slope'}).plot(subplots=True)\n",
    "plt.show()\n",
    "print('Figure 7.4: Level and slope components for Holt’s linear trend method and the additive damped trend method.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Comparison\n",
    "Here we plot a comparison Simple Exponential Smoothing and Holt's Methods for various additive, exponential and damped combinations. All of the models parameters will be optimized by statsmodels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-07T12:39:18.038995Z",
     "start_time": "2017-12-07T12:39:17.108323Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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eeeQR/vjjj2zH2rx5c66//npq165N1apVefLJJzl06FC2x3WH1NdCREREfIwFhgHdgIbAMuBar0aUJUqoPWTKlCk0bdqUzz//PFvjPPbYY3Tv3h24MKEeN24c1atXz9b4Z0VHR7N27VrWrl2Lv78/HTt2dMu4IiIiImk6g7Pa4UvAfcA8oIxXI8oyJdQecOzYMZYuXcr48ePPSahPnDhB165dqV27Nl26dOHEiRMp+yZOnEiVKlVo1qwZS5cuTdk+ZMgQRowYwfTp01m5ciWhoaEEBwdz4sSJlBnuDz74gOeffz7lnEmTJtGnTx8AJk+eTIMGDQgODqZXr14kJiZmGHvhwoUZPnw4W7du5ffffwfgzjvvpF69etSoUYOoqKiUY4sXL86AAQOoV68erVq1YsWKFTRv3pxKlSoxe/bslFg6duxIu3btuP7664mIiEg5P73Y0rsWIiIi4iOOALcD44CXgcmAv1cjyhafvimx/9z+rNm9xq1jBl8ZzKh2ozI8ZubMmbRr144qVapQpkwZVq9eTd26dfnggw8ICAhImQmuW7cuALt27WLw4MGsWrWKUqVK0aJFC+rUqXPOmJ07d2b06NGMGDGCkJCQC/Y1btyY4cOHA/DFF18QHh7Oxo0b+eKLL1i6dCmFChXi8ccfJzo6OmXGOz0FChTghhtu4M8//+SGG25gwoQJlClThhMnTlC/fn3uvvtuLr30Uo4fP07z5s1544036NSpEy+//DLz5s3jjz/+4MEHH6RDhw4ArFixgvXr1xMQEED9+vW57bbbKFasWJqxtW7d+qLXQkRERPKwbcBtwEZgPNDTu+G4g08n1N4yZcoU+vfvD0DXrl2ZMmUKdevWZfHixfTt2xeA2rVrU7t2bQCWL19O8+bNKVu2LABdunRh8+bNLr9f2bJlqVSpEr/88guVK1dm06ZNNGnShDFjxrBq1Srq168PODPkl19+uUtjpl6S/t1332XGjBkAbNu2jZiYGC699FIKFy5Mu3btAKhVqxb+/v4UKlSIWrVqERsbm3J+69atufTSSwG46667WLJkCQULFkwztuxeCxEREcnFVuPMTB8HvgNaeTccd/HphPpiM8mecODAAf73v/+xfv16jDEkJiZijEmZPTYm7c7k6W13VZcuXZg6dSpVq1alU6dOGGOw1vLggw8ybNiwTI2VmJjIunXrqFatGgsXLmT+/PksW7aMgIAAmjdvzsmTJwEoVKhQStx+fn74+/unPE9ISEj3s2UU28yZM7N9LURERCQX+gbogtPJYylQ07vhZMapUxnvVw21m02fPp3u3bsTFxdHbGws27Zt45prrmHJkiXcfPPNREdHA7B+/XrWrl0LQMOGDVm4cCEHDhzgzJkzTJs2Lc2xS5QowdGjR9Pcd9dddzFz5kymTJlCly5dAGjZsiXTp09n7969ABw8eJC4uLgM4z9z5gwvvvgiV199NbVr1+bw4cOULl2agIAA/vzzT3755ZdMX5N58+Zx8OBBTpw4wcyZM2nSpEm6sbl6LURERCQPeR/oAFyP0xYvDyXTS5bAxapPlVC72ZQpU+jUqdM52+6++24+++wzevfuzbFjx6hduzbDhw+nQYMGAJQrV44hQ4bQuHFjWrVqlVJbfb4ePXrw2GOPpdyUmFrp0qWpXr06cXFxKeNWr16dV199lTZt2lC7dm1at27Nrl270hw7NDSU2rVrU7NmTY4fP86sWbMAaNeuHQkJCdSuXZuBAwfSqFGjTF+Tpk2b8sADDxAcHMzdd99NSEhIurG5ei1EREQkD0jCWTr8CZy66UVAOa9G5LJDh+Cxx+CmmyA+PuNjTepa2bwmJCTEnt/HeePGjVSrVs1LEcn5Jk2axMqVKxk9erS3Q8kyfadERESyIB54APgK6AOMBAp4NSKXWAvTp0PfvrB3Lzz1FEREQPHiZpW1NiStc3y6hlpEREREvGAvTonHCmAU0M+r0bhs61Z44gn4+muoWxe++cb5eTFKqMWjevToQY8ePbwdhoiIiOSUP4H2wG6c2ek7vRqNSxITYfRoCA93Zqjffhv69IGCLmbKSqhFRERExD0W4STQhZOf1/dqNC5ZswYefRRWroRbb4X334egoMyNoZsSRURERCT7JgOtcW46XE6uT6bj4+H55yEkxCn1+Pxzp8Qjs8k0KKEWERERkeywwFCcGxCb4vSYDvJmQBf3/fdQsya8+SY89BD8+Sd06QJZXQpDCbWIiIiIZM1p4CFgMNAdmAuU9mpEGdq7F+6/H9q1g8KFYeFC+OgjKJ3NmJVQe4AxhgceeCDldUJCAmXLluX222+/6LnFixcHIDY2ls8++yxl+8qVK1OWLU9PbGwsNWvWdPn49IwaNYr4VA0X27dvz6FDh7I0VmpBQUHUqlWLWrVqUb16dV5++WVOXWzpoRwyZMgQRowY4e0wRERE8o5DwK3Ax0AEMAmndjoXshYmToRq1WDqVBg0yKmdbtbMPeMrofaAYsWKsX79+pTFV+bNm8dVV12VqTHOT6hDQkJ49913XT4/s8endn5C/e2333LJJZdkaazzLViwgHXr1rFixQq2bNlCWFiYW8YVERGRHBQLNAF+Aj4BBgFZLJfwtM2boWVL6NkTqld3EumICChSxH3voYTaQ2699Va++eYbwFk9sVu3bin7zp8NrVmzJrGxseec/8ILL/DTTz8RHBzMyJEjWbhwYcoM95AhQ3jggQe45ZZbqFy5Mh999NEF75/6+GPHjvHQQw9Rq1YtateuzZdffglA7969CQkJoUaNGgwePBiAd999l507d9KiRQtatGgBODPL+/fvZ8CAAbz//vvnfI633noLgDfffJP69etTu3btlLEyUrx4cT788ENmzpzJwYMHOXbsGC1btqRu3brUqlUrZaXG2NhYqlatyiOPPELNmjUJDQ1l/vz5NGnShMqVK7NixYqLXpP0YouMjOT666+nVatWbNq06aIxi4iICPAr0AjYCfyAUzudC506Ba+8ArVrw+rVMHYsLFrkJNXu5tNt8/r3d/4V4k7BwTBq1MWP69q1K0OHDuX2229n7dq19OzZk59++snl93n99dcZMWIEX3/9NeAkyKmtXbuWX375hePHj1OnTh1uu+22dMd65ZVXKFWqFOvWrQPg33//BZyEskyZMiQmJtKyZUvWrl1L3759efvtt1mwYAGXXXbZBZ+pf//+PP744wBMnTqVuXPn8sMPPxATE8OKFSuw1tKhQwcWL17MzTffnOFnLFmyJNdccw0xMTHUq1ePGTNmULJkSfbv30+jRo3o0KEDAH/99RfTpk0jKiqK+vXr89lnn7FkyRJmz57Na6+9xsyZM9O9JuvXr08ztmLFivH555/z22+/kZCQQN26dalXr55rvxwREZH8ahbQDbgCWADk0oWEFy2CXr1g0ybnZsORI6GcB5c89+mE2ptq165NbGwsU6ZMoX379m4fv2PHjhQtWpSiRYvSokULVqxYQXBwcJrHzp8/n88//zzldenkyvupU6cSFRVFQkICu3bt4o8//qB27drpvmedOnXYu3cvO3fuZN++fZQuXZqKFSvy7rvv8sMPP1CnTh3AmRGPiYm5aEINYK1N+fnSSy+xePFi/Pz82LFjB3v27AHgmmuuoVatWgDUqFGDli1bYoyhVq1a58zsp3VNlixZkmZsR48epVOnTgQEBACkJO8iIiKSjneAp3Da4c3GSapzmf374bnnYNIkuOYa+O475wZET/PphNqVmWRP6tChA88++ywLFy7kwIEDKdsLFixIUlJSyuuTJ09memxzXl+X81+nZq29YP8///zDiBEj+PXXXyldujQ9evRwKY7OnTszffp0du/eTdeuXVPGf/HFF+nVq1emPsPRo0eJjY2lSpUqREdHs2/fPlatWkWhQoUICgpKicff3z/lHD8/v5TXfn5+JCQkpOxL65qkF9uoUaMyvGYiIiKSLBF4GngX6ITTbzrAqxFdwFr45BN45hk4fBheeAEGDoSAHIpTNdQe1LNnTwYNGpQyu3pWUFAQq1evBmD16tX8888/F5xbokQJjh49mu7Ys2bN4uTJkxw4cICFCxdSv3763dPbtGnD6NGjU17/+++/HDlyhGLFilGqVCn27NnDd99959J7d+3alc8//5zp06fTuXNnANq2bcuECRM4duwYADt27GDv3r3pxgPOTPHjjz/OnXfeSenSpTl8+DCXX345hQoVYsGCBcTFxWV4flrSuibpxXbzzTczY8YMTpw4wdGjR5kzZ06m309ERMTnHQfuwkmmnwamkeuS6U2b4JZboEcPuP56p1562DD3JtMb9m7IcL9Pz1B7W4UKFejXr98F2++++24++eQTgoODqV+/PlWqVLngmNq1a1OwYEFuuOEGevTokVKycFaDBg247bbb2Lp1KwMHDqR8+fIX3Nh41ssvv8wTTzxBzZo1KVCgAIMHD+auu+6iTp061KhRg0qVKtGkSZOU48PCwrj11lspV64cCxYsOGesGjVqcPToUa666irKJRcjtWnTho0bN9K4cWPAueFw8uTJXH755RfE0qJFC6y1JCUl0alTJwYOHAhAaGgod9xxByEhIQQHB1O1atUMrmza0rom5cuXTzO2unXr0qVLF4KDgwkMDOSmm27K9PuJiIj4tN3A7cBvwGjgCe+Gc76TJ+H11/9LnseOhUceAT83Thev37ueoYuGMu2PaRkeZ87WsOZFISEhduXKleds27hxI9Wq5dIKeTcZMmQIxYsX59lnn/V2KLmGJ69JfvhOiYiInGMD0B7YD3yBk1jnIv/7Hzz2GMTEwH33wdtvwxVurOlet2cdQxcPZfof0ylRuAR9GvThtVavrbLWhqR1vEo+REREROQ/PwI3Amdw+kznomR63z548EGnr3RiorOEeHS0+5Lp33f/zt1T76b2h7X5/q/vefmml4ntH0tky8gMz1PJRx40ZMgQb4eQ6+iaiIiIuMFEIAyoCnwDVPRuOGedXenwuefg6FEID3ceRYu6Z/w1u9cwdNFQZvw5g5L+JRl480D6N+pPmaJlXDpfCbWIiIhIfmdxVjt8FWgFTAdKeTUioqOjCQ8PJy4uAH//iZw61ZCmTZ1aaXctzvLbrt+IWBTBrE2zKOVfisHNBtOvYT9KFy2dqXF8MqFOq02cSFbk5XsMREREXHIK6Al8BjwMfAAU8mpEREdH8+ijfTlxoj8wgFOnjlG4cG/CwppSvXpotsdfvWs1EYsimL1pNqX8SzGk2RD6NerHJUUuydJ4PpdQFylShAMHDnDppZcqqZZssdZy4MABihQp4u1QREREPOMATm/pn4BI4EXAi+nT9u3bmTdvHr17z+LUqRXAtcCnwDOcPr2PgQO/44EHsp5Qr9q5iohFEczZPIdLilxCRPMI+jbsm+VE+iyfS6grVKjA9u3b2bdvn7dDER9QpEgRKlSo4O0wRERE3O9vnE4esTiz091yPoTjx4+zaNEifvjhB+bNm8cffxwCRgIzgU3ALThrnDu2bt2apff5dcevRCyK4JuYbyhdpDSvtHiFPg36UKqIe+pafC6hLlSoENdcc423wxARERHJvZYBHYAknK4eTd039Nna561bt1KxYkUiIyMJDXVmlZOSkvjtt99SEuglS5Zw5swZ/P2LERT0Jv7+PbG2EEWLjuDw4XDg9DljV6yYubskV+xYQcSiCL6N+ZYyRcvwaotX6dOwDyX9S7rr4wI+mFCLiIiISAamAQ8AVwPfApXdN3R0dDRhYWHEx8cDEBcXx6OPPsrChQs5duwY8+fPZ//+/QDccMMN9O/fn6uv7sz48SH8/rsf7drB6NHwyy/lCAsrSHz8fwl1QEAAkZEZt687a/n25UQsiuC7v76jTNEyRN4SSZ8GfSjhX8J9HzYVJdQiIiIi+YEF3gQG4PSZngVc5t63CA8PT0mmzzpx4gTjxo3jyiuvpH379rRp04ZWrVpRuPAVvPQS9OsH5crB1KnQuTMYA9deG5oyXloz3elZtm0ZEYsi+P7v77m06KUMazmMJ+o/4bFE+iyfWylRRERERM6TADwJjAW6AJMAD9xz7+fnl2aHLGMMiYmJGGOw1lmM5ZlnYP9+6NsXIiKgZDaqMJZtW8aQRUP44e8fuCzgMp5t/CxPNHiC4oWLZ+PTXPAZ0l0pUTPUIiIiIr7sKHAvMBd4AaebhwfWyk5KSqJkyZIcPnz4gn0VK1bEGMOff8Ljj8OCBdCgAcydC3XqZP09l25dSsSiCOZtmUfZgLIMbzWc3vV7uzWRdoXHlx43xhQwxvxmjPk6+fUQY8wOY8ya5Ef7VMe+aIz5yxizyRjT1tOxiYiIiPi07cBNwDwgChiGR7K/ffv20b59ew4fPkyBAgXO2RcQEMDgwa8zcCDUrg2//QYffAA//5z1ZHrJ1iW0/rQ1TSc25fc9v/Nm6zf5p98/PNfkuRxPpiFnZqj7ARuB1BP5I621I1IfZIypDnQFagDlgfnGmCrW2sQciFFERETEt6wBbsOZof4G8NBU5c8//8y9997L/v37GTt2LMWKFTun9vneeyfy6qst2LIF7r8fRoyAK67I2nv9FPcTEYsi+PGfH7m82OWMaD2Cx0Ieo1jhYu79UJnk0YTaGFMB51cZCTx9kcM7Ap9ba08B/xhj/gIa4DR2ERERERFXfYdT5nEJsASo7f63sNby9ttv88ILLxAYGMiyZcuokzzlHBoayo4d0L8/vPkmXH89/Pgj3HJL1t5rcdxihiwcwoLYBVxR7ArebvM2vUJ6EVAowH0fKBs8XfIxCngep8thak8aY9YaYyYYY84uln4VsC3VMduTt53DGBNmjFlpjFmpxVtEREREzvMhcAdOO7zleCSZPnToEJ06deLZZ5+lQ4cOrFq1KiWZTkiAkSOhalX4+mt49VX4/fesJdMLYxfS4uMWNJvUjI37NzKy7Ui29NvCU42fyjXJNHgwoTbG3A7stdauOm/XBzjrSAYDu4C3zp6SxjAX3CZqrY2y1oZYa0PKli3rxohFRERE8rAknGnM3kA7YDFOEa2brVq1irp16/LNN98wcuRIpk+fTqlSzoqDS5ZA3brw9NNw002wYQOEh4O/f+beY2HsQppPak6Lj1uwaf8mRrUdxZa+W+jfqH+uSqTP8mTJRxOgQ/JNh0WAksaYydba+88eYIz5CPg6+eV2nBbjZ1UAdnowPhERERHfcAJnsZYvcRLqd3F7lmet5cMPP6R///5cfvnlLF68mMaNGwOwdy8MGACTJsHVV8NXX8Gddzo9pTMz/oLYBUQsimBx3GLKFS/Hu+3e5ZG6j1C0UFH3fhg389gMtbX2RWttBWttEM7Nhv+z1t5vjCmX6rBOwPrk57OBrsYYf2PMNTh/qFjhqfhEREREfMJe4BbgK5y/+4/B7cn00aNHCQ0N5fHHH6dly5b89ttvNG7cmMREp2PH9dc7vaVfeAE2boROnVxPpq21/LjlR26edDMtP2nJ3wf/5r1b32NLvy30adgn1yfT4J0+1MONMcE45RyxQC8Aa+0GY8xU4A+c9uNPqMOHiIiISAb+BNrjFNFOB+5y/1usX7+ezp07ExMTQ2RkJC+88AJ+fn6sXAm9e8PKldCiBYwZA9WquT6utZYf//mRIQuHsHTbUq4qcRWjbx3Nw3UfpkhBD6w640E5klBbaxcCC5OfP5DBcZE4HUFEREREJCOLcP7WXwgny2qY/SGjo6PPaXnXtm1bPv30U0qWLMn8+fNp0aIF//4LL70EY8c67e+io6Fbt8zNSM/bMo+IRRH8vO1nKpSswPvt36dnnZ74F8xksXUuoZUSRURERPKayUBPnDYP3wLXZH/I6OhowsLCiI+PByAuLo6oqCiqVavG//73Py6//EomTYLnn4cDB/5bMjz5fsSLstbyw98/ELEogmXbl3F1yav54LYPeCj4oTybSJ+lhFpEREQkr7DAK8BgoDlO3XTpjE5wXXh4eEoyndrx48fZu/dKOneGpUuhcWP44QcIDnYxZGv5/u/viVgUwS/bf6FiqYp8eNuH9AjukecT6bOUUIuIiIjkBaeBMOBjoDvwEVDYfcNv3bo1ja0l2Lr1KerWhUsugfHjoUcP8HOhrYW1lu/++o6IRRGs2LGCwFKBjL19LD2Ce1C4gBsDzwWUUIuIiIjkdv8CdwMLgAhgIGmv4JENFStWJC4uLtWWLsDbwJU8/DC89hpceunFx7HW8m3Mt0QsiuDXnb8SdEkQH93xEd1v6O5zifRZnl4pUURERESy4x/gRpwlxD8BBuH2ZBpg8ODBGGOA64F5wOcYs4eIiB8YO/biybS1ljmb5tBgXANun3I7++L3Me6OcWx+cjOP1H3EZ5Np0Ay1iIiISO61AmcZ8dPADzh10x4SE7MLa4cBTwHxlCkzkFGjqvHAA/dleJ61ljmb5xCxKILVu1ZTqXQlxncYzwO1H6BQgUKeCzgHHAXmA99c5Dgl1CIiIiK50QwgFLgSp0VeVc+8jbXw/vv7GDbsQeAqevSAN94ozOWXv3KR8yyzN80mYlEEv+3+jUqlKzGhwwTur31/nk6k/8JJoL/GuexngJIXOUcJtYiIiEhuYoGRwLNAA5y1pC/3zFtt3AhPPgn/+19ZjPmdL78sSKdOV2R4TpJNYtafsxi6eChrdq/h2tLXMrHjREJrhebJRPo0TjXN2SR6c/L2akA/4DagCRnf/6mEWkRERCS3SMDJ4t7HuQnxU8ADK28fPQpDh8KoUVCkyBmgH0OGXEWnTuHpnpNkk5j550wiFkWwds9aritzHR/f+TH31bqPgn55K6XcA3yHk0D/gFPaURhoATyJk0RXysR4eevTi4iIiPiqY0BXnKnSZ4E3cHv7CGvhiy/gmWdg507o0SOJX35pycmT23juuT/SPCfJJvHVxq8Yumgo6/auo8qlVfjkzk/oVqtbnkmkk4DfcBLob4Bfk7eXx7nktwEtgeJZHD9vXAURERERX7YTuB34HfgAeMz9b7FhA/TpAwsWQN268OWXsHLl+0ya9BNfffUVRYueOxWeZJP48o8vGbp4KOv3ruf6S69ncqfJdK3ZlQJ+BdwfoJsdx+lVcjaJ3o3THKUhzto4twM34J6GKUqoRURERLzpd5zs7hAwB2jv3uGPHnWWCH/nHShRAj74AB59FP79dz+33jqQVq1aceedd6Ycn2STmP7HdIYuGsqGfRuoellVou+KpkuNLrk+kd6Gcwm/Bv4HnMK5obAdziVuB5T1wPsqoRYRERHxlrnAPUApnDvjbnDf0NbClCnw7LOwezc88oizOMtllzn7Bw4cyNGjR3nnnXcwxpCYlMi0P6bxyuJX+GPfH1S7rBpT7p7CPdXvybWJdBKwEieJnoPzbxOA64DHcZLomwBP3yqphFpERETEG8YCTwA1caZUK7hv6PXrne4dixZBSAjMnAkNGvy3/7fffmPs2LH07duX66tez5R1U3hl8Sts3L+R6mWr5+pE+mwpxxycUo49OKXmTYDhOG27r8cja9+kSwm1iIiISE5KAl4A3gRuBb4ASrhn6CNHYMgQePddKFUKxo6Fhx+GAqnyYmstffv2pcxlZajRtQY1P6jJn/v/pEbZGnzR+Qs6V++Mn8ldi2mnVcpRCqeE447kny6siu4xSqhFREREcsoJoDswHegNvItbsrGkJPj0UxgwAPbuhbAwiIxMe7nwzz7/jCVHlnBFvysI+z6MmpfXZNo907ir2l25JpFOAlbhtOBOXcpxLc5lu4OcKeVwlRJqERERkZywF+gILAfewlnh2w11CatXO+Udy5ZBw4bw9ddOmcf5EpISmLRyEr1X9Ia74IoyVzCm2Rg6VeuUKxLpkzizz2eT6J38V8rxBk4SXZWcLeVwlRJqEREREU/7E6d7xy6c2em7sj/k/v0QHg4ffQRly8LEidC9O/idlxsnJCXw2brPeHXxq8QcjIGTEFk7khfufMHrifR+nDro2cD3OPXRxXBKODrg9If2ZimHq5RQi4iIiHjSIqATTn3CQpxGyNmQkODURg8c6NRM9+8Pgwc7NdPnHJeUwOS1k4n8KZK/Dv5F9dLVKTi9IPfecC8vdXope0FkQwwwCyeJXopT3lEeeAAniW4BFPFadFmjhFpERETEUz4FHsbp4/YNcE32hvvpJ6e8Y+1auOUW5+bDGjXOPeZM4pmURPrvf/+mzpV1mNllJhNfnEjcP3EMnzs8e0FkUiJOlctsnET6z+TttYFwnCS6Lm5fFDJH5eXYRURERHInC0Tg3IDYFGcqNhvJ9I4dcN99cPPN8O+/MG0azJ9/bjJ9JvEME36bQNUxVek5uyelipRiVtdZrApbRcC2AGbNnEV4eDhXXXVVtj6aK+JxkueHcWafm+CUjV+Fcx/mPzg3Gg4FQsj7CalmqEVERETc6TTwKPAJ8CAQBRTO2lCnTsGoUfDKK06px8CB8MILEBDw3zFnEs/w8e8f89pPr/HPoX+oV64ec7rN4bbKt2GM4cyZM/Tr149rr72Wp556KrufLl0HcNrazcSphz6Bs0phe5xZ6FuBSzz27t6lhFpERETEXf7FueFwIc7068tkuS3Fd99Bv34QEwMdOsDIkVCp0n/7Tyee5uM1H/PakteIPRRL/fL1ee/W92hfuT3G/PemY8aMYePGjcyePZsiRdxbnRyLMxM9E1iMUw99FdATp6FJM7L8b4k8RQm1iIiIiDtswZmO/Qendvr+rA3z99/w1FMwZw5UqeIk1u3a/bf/dOJpJq2ZxGs/vUbc4TgaXNWAMe3HcOt1t56TSAPs3buXIUOG0LZtW26//fYsfrD/WGAtTgI9E1iTvL0m8BJwJ049dG5sbedJSqhFREREsusXnLqGBJx1sW/O/BDx8TBsGLz5JhQsCG+84XTwKJw8xXsq4RQT10xk2JJhbD28lYZXNeTD2z+k7bVtL0ikzwoPD+f48eOMGjUq3WMuJgFYgpNAz8KZlTY4ddEjcGair8vSyL5DCbWIiIhIdnyJMxtdHvgWuD5zp1sLU6fCc8/Btm3OzYfDh8PZewdPJZxiwm8TGLZkGNuObKNRhUZE3R5Fm2vbZJgkr1q1ivHjx/P0009TtWrVTMUUD/yAk0TPAQ4C/kBrnCqW24ErMvcxfZoSahEREZGssDhTtM8DjXGmb8tmbog1a6BvX6cdXnAwREfDTTc5+04lnGL8b+MZtmQY249s58arb2Rch3G0rtT6orPN1lr69OlD2bJlGThwoEux/ItzU+FX/HdT4SU4yfOdQFugeOY+Xr6hhFpEREQksxKAJ4GxwD3Ax0BR10/fvx9eftlZ5bBMGWehlocfhgIF4GTCScatHsfrS15nx9EdNLm6CRM7TqTlNS1dLtuIjo5m2bJlTJgwgVLnr/iSyi6cWegZwILkj3X2psJOOJUrhVz/WPmWEmoRERGRzDgC3Iszjfsi8CouN1I+cwY++MBZ2fDoUejTx3leurSTSL+//CNeX/o6O4/upGnFpnx858fccs0tmap/Pnr0KM8//zz169fnwQcfvGD/3zgJ9AxgGc5Ee2XgGZwkur7rH0eSKaEWERERcdU24DbgD+Aj4BHXT50/32mD98cf0KqV01+6Rg04ceYE7y7/iDeWvsHOozu5OfBmPu30KS2CWmQqkY6OjiY8PJy4uDgAevXqhZ+fHxZYj1PK8RVOlw6AOjhrz9wFVCf/deZwJyXUIiIiIq5YjVNQfBz4DucOPRds2QLPPAMzZ8I118CMGdCxI5xMOMGoX8byxtI32H1sN80CmzG502SaBzXPdEeO6OhowsLCiI+PdzYYw7AFC/j1nnv4s3p1/ua/zhxv49REZ3MVdElFCbWIiIjIxXwNdAUuxVlGvObFTzl2zGmD99ZbTm10ZCQ8/TQkFYhn1C9jGf7zcHYf203zoOZMuXsKzYOaZzm88PBw4k+dgltugbvugk6dOFW+PN+cPk1bnPsmO6LOHJ6ihFpEREQkI+8B/XFqJOYA5TI+3Fr47DN4/nnYuRNCQ52e0qUvj+f9lR8yfOlw9hzfwy3X3MIXnb/g5sAsNK1Odhr4EYgbNMhZTvGyy+D4cWc1mBkz4Ntvmfvvv1keX1yjhFpEREQkLYnA08C7ONO70UCxjE9Ztcppg/fzz1CvHkybBjeEHOeDlR/w5pQ32Xt8Ly2vacm0ZtO4KfCmLIV1AqdH9HSc/P4wYO65BztrFnz5JXz/PZw4AUBgYGCW3kMyRwm1iIiIyPmOA/cBs3Fmp0cABdI/fO9eeOklmDDBmSQeNw7uue84Y1e/z53vvMm++H20qtSKwc0G07Ri00yHcwynbHs68E1yeKVxbijscOYMferUYfvff59zTkBAAJGRkZl+L8k8dUURERERSW0XTgPmr3HKPUaSbjJ9+rRTI125Mnz8MTz1FPy24RgHqg7n2tFBPD//eeqUq8PSnkuZ98C8TCXTh4HJOK3syuJ06luIsyjjD8AeYALw0wsvsP3vv3n22WcJDAzEGENgYCBRUVGEhoZm8SJIZhhrbcYHGBMC3ISzoOYJnM4r8621Bz0fXsZCQkLsypUrvR2GiIiI+Ip1OG3xDgKf43T1SIO18PXXTveOmBho1w5efeM48468x1vL3mJ//H7aXtuWwc0G0/jqxi6//QGcBRe/BOYBZ3ASsLuTH005N7f/8ccfadWqFY8//jhjxozJ9McV1xljVllrQ9Lal27JhzGmB9AX+AdYBWwCiuD8LgcYY9YDA621W90esYiIiEhO+wHojLO+9mKgbtqHbdjgzETPmwfXXw/TZ8WzufQ7tJ37FgdOHKDdde0Y3GwwjSo0cult9+EssjINZ7XCRCAIJwm7G2hI2iUFBw8e5MEHH6Rq1aq8+eabmfmk4mYZ1VAXA5pYa0+ktdMYE4yzsI4SahEREcnbPgJ646xw8g1w9YWHHDjgrGr44YdQogS8PuIkp+uOIuzXNzl44iC3Xncrg5sNpmGFhhd9u738l0QvxEmirwOew8np65LxQivWWnr16sXevXuZPXs2AQEBmfm04mbpJtTW2gz/bmCtXeP2aERERERyUhLwEvAG0A74Aih57iFnlwsfMgQOH4aej57msvbv8cbGSP5d/C+3Vb6NQc0G0eCqBhm+1R7OTaKTgCrAC8A9QG1cX63wk08+Yfr06bz++uvUrZvOVLrkGFdqqIfjrFJ/ApgL3AD0t9ZO9nx4GVMNtYiIiGTLTzg3IPYCRnPBVOPcuc5iLBs3QvNbzlDj/vF8tvcl/j35L7dXuZ3BzQYTUj7NsloAduMs9z0Np4okCbgeJ4G+B6hF5pf83rJlCzfccAN169blf//7HwUKZNB+RNwmSzXUqbSx1j5vjOkEbMf5/S/AufFUREREJO+6CfgFaMA5me2mTU4i/e23UOnaRLpFTuNbv94s3HqIDtd3YNDNg6hXvl6aQ+7GuanwbBJtgapAOE4SVZPMJ9FnJSQk8MADD1CgQAE+/fRTJdO5hCsJdaHkn+2BKdbag5ldX15EREQk10pV8vzvvzB0KIweDUUDLK0fm8fyq+5nypl9dLy+I4OaDaJuuQtLLHbxXxL9E04SXQ0YiJNE1yDrSXRqw4YN4+eff+azzz6jYsWKbhhR3MGVhHqOMeZPnJKPx40xZYGTng1LREREJOckJDiLsbz8Mhw8aKnTfhUxN3RjXuG/6FS5E4OaDSL4yuBzztmLk0R/wX8z0dWBQfyXRLvT8uXLiYiI4L777qNbt25uHl2y46I11ADGmNLAEWttojEmAChprd3t8eguQjXUIiIikl3/+x/07w/r1kHgDf+w/+YHOH7pUu6qdheDbh7EDVfekHLsAZya6C9w6l+TcMo5uuAsvFLdQzEeO3aMOnXqcPr0aX7//XcuueQSD72TpCe7NdTg/NUiyBiT+vhPsh2ZiIiIiBf99BO0bAmlrvyXIvf1Ia5yNHdXv5tBzX6n9hW1AfgXmImTRM/nvxZ3L+Ik0tmpiXbVU089xd9//82CBQuUTOdCF1163BjzKc4K9k2B+smP9G9nFRER8RHR0dEEBQXh5+dHUFAQ0dHR3g5J3KzwNSsocvdjHH64HHfceZq1vdcy/d7pBF1Rm0+BO4ArgJ7AZuBZYHXy81fJWpeOzJo5cybjxo1jwIABNGvWzMPvJllx0YQaJ3luYq193FrbJ/nR19OBiYhI/uWORDa7Y0RHRxMWFkZcXBzWWuLi4ggLC1NS7WOCr7yBB3vAur4rmXDPVNZfUYtOwOVAd+B3nBULVwB/A68DdfB8En3Wrl27eOSRR6hbty4RERE59K6SWa70oZ4G9LXW7sqZkFynGmoREd9zNpGNj49P2RYQEEBUVBShoaEeG+PMmTMcOnSIw4cPc+jQIW677Tb27t17wXGBgYHExsZm7kNJrnUCZ2HEL5J/ngDK49xU2IX0l/3OCUlJSbRv357FixezevVqqlat6qVIBDKuoXYloV4ABOP84+zU2e3W2g5ujDFLlFCLiPieoKAg4uLi0tx3ySWXULx4cYoVK5bm4+y+qKgoDh8+fMH5xYsXp0OHDhw6dOiCR+rkOyPGGJKSkrL1GSX3WIlTy3oFzpLfXYAmeC+JTu29996jb9++vP/++/Tu3dvb4eR72U2o0yzWsdYuckNs2aKEWkTE9/j5+ZHe/zf16dOHY8eOcfz48QseqbefPJl+d9drr72WSy65JM1HqVKlUp4/+uij7Nmz54LzCxUqxIwZM2jfvj1alyHvszh9o5sAuWmJlA0bNlCvXj1atWrFnDlz9F3LBbKVUCcPcAXOP+AAVlhrL/wbmBcooRYR8T3pzVBnptQiMDCQrVu3ZmuMtMpG/P39ueSSS9izZw/NmzfnzTffJCRE9+mLe506dYoGDRqwa9cu1q1bxxVXXOHtkISME2pXunzci1PucQ9Oi8XlxpjO7g1RRETEERkZSdGiRc/ZFhAQQGRkpMtjvPbaawQEBGRrjNDQUKKioggMDMQYQ2BgIOPHj2fbtm2MHj2aDRs2UL9+fbp168aWLVtcHlfcw5c7sLz88susXbuWCRMmKJnOK6y1GT5wbnC9PNXrssDvFzsvJx716tWzIiLie55//nkLWGOMDQwMtJMnT870GJMnT7aBgYHZGiMjhw8fti+//LItWrSoLVSokO3fv7/dv3+/W99D0jZ58mQbEBBgcSo2LGADAgLc/jvOSam/r4Bt2bKlt0OS8wArbTo5qSs11OustbVSvfZLTqhrZXBajlDJh4iIbxo9ejR9+vRh165dXHnlld4OJ0M7d+5k8ODBTJgwgRIlSvDSSy/Rp0+fC2bZxX3cURZ0jv79Yc2a7IaVZXv27GHT5s3n3Ozq5+fH9VWqaIY6FzGLFmW95AOYa4z53hjTwxjTA6erzLfuDFBERCS1zZs3U7x48TyRTJQvX56PPvqItWvXctNNNzFgwACuv/56PvnkExITE70dnk9Kqz4+o+253T///HNB55ikpCT++ecfL0UkmeXqTYl349wAa4DF1toZng7MFZqhFhHxTbfeeit79uxh9erV3g4l0xYsWMDzzz/PypUrueGGGxg+fDj79u0jPDycrVu3UrFiRSIjI13uqX1WdHR0tsfwBd9//z233347CQkJF+zLqz3C0+tsoxaNuUtGNyUWdGUAa+2XwJdujUpERCQdMTExebZ7RosWLVi+fDlTp07lpZdeom3btvj5+aUkRmdXXASyvFBNVsbI6/755x+efvppZs6cyRVXXMGhQ4c4dSpleYxM33SaW1hrKVasGMeOHbtgX8WKFb0QkWRFujPUxpgl1tqmxpijOAX/KbsAa60tmRMBZkQz1CIivuf06dMULVqUl156iVdeecXb4WTLqVOnKFeuHP/+++8F+4wxXHHFFfj7++Pv70+RIkXSfO7v78/s2bM5fvz4BWPk1RnZzDhx4gRvvPEGb7zxBgUKFGDgwIH079+f6dOn5/kZe2st/fr147333qNgwYLnzLpndnVQ8bwszVBba5sm/yzhqcBERETOd7aetHLlyt4OJdv8/f05dOhQmvustXTo0IGTJ09y6tQpTp06lfI8Pj6egwcPpmxPK5mGvFsz7AprLbNmzeKpp54iNjaWrl278uabb1KhQgXAmZnPy8mmtZbnn3+e9957j6effpq6devm+X8g5GfpJtTGmDIZnWitPej+cEREJL+LiYkB8ImEGpw/26fXkWLs2LEujZFeVwtfLQnYtGkT/fr14/vvv6dmzZosWLCA5s2bezsstxo4cCAjRozgySefZMSIERhjlEDnYRl1+ViFs8T9qjQeqrMQERGPOJtQV6lSxcuRuEdkZGS2F5lJa4yiRYvmyZrhjBw9epQBAwZQq1Ytli1bxjvvvMNvv/3mc8n0K6+8QmRkJI8++ijvvPOOlhX3Aekm1Nbaa6y1lZJ/nv+olJNBiohI/rF582ZKly7NpZde6u1Q3CKtFRczWxt7/hgArVu3zrMzmmmtcvjZZ59RtWpVhg8fzv3338/mzZvp27cvBQu61D8hzxg+fDiDBg2ie/fufPjhh/j5udLBWHK7jG5KrJvRidZar/cy0k2JIiK+p1WrVhw9epTly5d7O5Rcq3v37nzxxRf88ccfXHvttd4OJ1PO71gCpHRBqVevHqNHj6ZRo0Y5Gk9O1S6/88479O/fn65duzJ58mQKFCjgkfcRz8jopsSMEuoFGYxprbW3uCO47FBCLSLiewIDA7npppuYPHmyt0PJtXbu3EmVKlVo1aoVM2fO9HY4mZJePXiZMmXYu3dvjiaZaSX3nuqu8eGHH9K7d2/uuusuPv/8cwoVKuTW8cXzMkqoMyr5aJHBw+vJtIiI+J4TJ06wbds2n6mf9pTy5cszcOBAZs2axQ8//ODtcDIlvc4k//77b47P2IaHh5+TTAPEx8cTHh7u1veZMGECvXv35o477mDKlClKpn1Qugm1MeaW5J93pfXIuRBFRCS/+Pvvv7HW+kyHD0/q378/1113Hf379+fMmTPeDsclhw8fvuDmyrO80bEkJ5Ywnzx5Mo888ght27Zl2rRpFC5c2G1jS+6RUSV8s+Sfd6TxuN3DcYmISD7kay3zPMnf35+RI0eyceNGxowZ4+1wLmr+/PnUqlWL48ePX3CjobdWOUwvibfWcvfdd/Pzzz9na/ypU6fy4IMP0qJFC2bMmIG/v3+2xpPcK6OSj8HJPx9K49Ez50IUEZH8Qgl15tx22220a9eOwYMHs3fvXm+Hk6ajR4/Su3dvWrduTUBAAL/88guTJk3KVtcTd0mvHWGHDh1YsGABTZo0oXHjxnz55ZckJiZmauyZM2dy3333ceONNzJ79myKFi3qztAll7lorxZjzCXGmL7GmLeNMe+efeREcCIikr/ExMRw+eWXU6pUKW+HkicYYxg1apRH6n7dYcGCBdSuXZuxY8fy7LPP8ttvv9GwYUNCQ0OJjY0lKSmJ2NhYr7X/S6ul4UcffcSsWbPYtm0b7733Hnv37qVz585UqVKF9957j2PHjl103G+//ZZ7772XkJAQvvnmG4oVK5YDn0a8Kd0uHykHGPMz8AuwDkg6u91a+7FnQ7s4dfkQEfEtzZo1IzExkSVLlng7lDzl2Wef5e233+bXX3+lXr163g6H48eP88ILLzB69Giuu+46Jk2aRJMmTbwdVpYkJiYya9YsRowYwbJlyyhdujSPPfYYffr0oVy5chccP2/ePO644w5q1qzJ/PnzueSSS3I+aPGILLXNS3Xyamtthj2pvUUJtYiIbylfvjxt27Zl4sSJ3g4lTzly5AhVqlShUqVKLF261Ksr7/3000/06NGDLVu20K9fP1577bV0b0TMa5YtW8Zbb73FjBkzKFCgAKGhoTz99NOsXbs2pZc1QIUKFVizZg1lypTxcsTiTllqm5fKp8aYR40x5YwxZc4+3ByjiIjkc8eOHWPXrl1qmZcFJUuWZNiwYSxbtozo6GivxBAfH89TTz1Fs2ZOT4OFCxcyatQon0mmARo3bsz06dPZvHkzvXr1YurUqdSuXZvu3bsTFxeHtRZrLfv37+e7777zdriSg1yZoX4CiAQOAWcPtrlh+XHNUIuI+I7ffvuNunXrMm3aNDp37uztcPKcpKQkGjVqxPbt29m0aRMlSpTIsfdetmwZPXr0YPPmzTzxxBO8/vrrFC9ePMfe31sOHjzItddey6FDhy7YFxgYSGxsbI7HJJ6T3Rnqp4HrrLVB1tprkh9eT6ZFRMS3qMNH9vj5+fHee++xa9cuXnvtNY+9T3R0NEFBQfj5+VGxYkVuv/12mjZtyqlTp/jxxx8ZPXp0vkimwVnd8fDhw2nuc2cva8n9XEmoNwDxFz1KREQkG84m1Nddd52XI8m7GjZsyIMPPsjbb7/NX3/95fbxzy7Vfba8Ydu2bXzzzTc0b96cdevWccst+W8h5fR6WXtjoRrxHlcS6kRgjTFmbFba5hljChhjfjPGfJ38uowxZp4xJib5Z+lUx75ojPnLGLPJGNM28x9HRETyqpiYGK666iq1GMumYcOGUbhwYZ5++mm3j53WUt3grHCZkyUmuUlavay9tVCNeI8rCfVMnBrqn4FVqR6u6gdsTPX6BeBHa21l4Mfk1xhjqgNdgRpAO+B9Y0yBTLyPiIjkYZs3b1a5hxuUK1eOQYMGMWfOHObOnevWsXNiqe68Jq1e1t5aqEa856I3JWZrcGMqAB/jJORPW2tvN8ZsAppba3cZY8oBC6211xtjXgSw1g5LPvd7YIi1dll64+umRBER31G2bFk6depEVFSUt0PJ806fPk3NmjXx8/Nj7dq1FC5cOFvjnTlzhsjISCIiItLcrxvwJD/I0k2Jxpg5xpg7jDGF0thXyRgz1BhzsSXIRwHPk2pBGOAKa+0ugOSflydvvwrYluq47cnbRETExx06dIj9+/drhtpNChcuzKhRo9i0aRPvvfdetsZat24dDRs2JCIigiZNmlywhLbKG0QyLvl4FLgJ+NMY86sx5ltjzP+MMf8AY4FV1toJ6Z1sjLkd2GutdbU8JK0u9BdMnxtjwowxK40xK/ft2+fi0CIikpudvSFRPajdp3379rRv356IiAh2796d6fMTEhIYNmwY9erVY8eOHXz11VcsWbKEjz76SOUNIucpmN4Oa+1unNnl540xQUA54ASw2VrrStePJkAHY0x7oAhQ0hgzGdhjjCmXquRjb/Lx24GrU51fAdiZRlxRQBQ4JR8uxCEiIrnc5s2bAbXMc7eRI0dSs2ZNXnrpJSZMSHcO7AIbN26kR48erFixgnvuuYcxY8ZQtmxZwKkZVgItci5XbkrEWhtrrV1mrV3jYjKNtfZFa20Fa20Qzs2G/7PW3g/MBh5MPuxBYFby89lAV2OMvzHmGqAysCITn0VERPKomJgYjDFUqqRlDtypSpUq9O/fn4kTJ7JixcX/LzUxMZG33nqLOnXq8Ndff/H5558zderUlGRaRNLmUkLtZq8DrY0xMUDr5NdYazcAU4E/gLnAE9baRC/EJyIiOSwmJobAwECKFCni7VB8zssvv8yVV15J3759SUpKSve4v/76i2bNmvHss8/Srl07NmzYQJcuXXIwUpG8K0cSamvtQmvt7cnPD1hrW1prKyf/PJjquEhr7bXW2uuttd/lRGwiIuJ9MTExKvfwkJIlS/L666+zfPlyJk+efMH+pKQkRo8ezQ033MD69ev55JNPmDFjBldeeaUXohXJm7wxQy0iIpLCWqse1B72wAMP0LBhQwYMGMDRo0dTtsfGxtKqVSv69OnDzTffzIYNG3jggQcwJq0+ASKSnnRvSjzLGFMZGAZUx7m5EABrrQrdREQk2/bv38/hw4eVUHuQn58f7777Lg0bNqRChQocPXqU0qVLc/z4cQoXLsxHH33Eww8/rERaJItcmaGeCHwAJAAtgE+ATz0ZlIiI5B9qmZczYmJiKFCgAEeOHMFay8GDBzlz5gyvvPIKjzzyiJJpkWxwJaEuaq39EWdVxThr7RDgFs+GJSIi+YVa5uWM8PBwEhPPvdc/KSmJkSNHeikiEd9x0ZIP4KQxxg+IMcY8Cezgv9UNRUREsuXszGlQUJC3Q/FpW7duzdR2EXGdKzPU/YEAoC9QD3iA//pIi4iIZEtMTAzXXHMNhQoV8nYoPq1ixYqZ2i4irrtoQm2t/dVae8xau91a+5C19i5r7S85EZyIiPi+mJgY1U/ngMjISAICAs7ZFhAQQGRkpJciEvEd6ZZ8GGNGWWv7G2PmABcs8W2t7eDRyERExOdZa4mJiaFZs2beDsXnnV0uPDw8nK1bt1KxYkUiIyO1jLiIG2RUQ322k8eInAhERETyn127dnH8+HHdkJhDQkNDlUCLeEC6CbW1dlXyz0VntxljSgNXW2vX5kBsIiLi4862zFNCLSJ52UVrqI0xC40xJY0xZYDfgYnGmLc9H5qIiPg69aAWEV/gSpePUtbaI8BdwERrbT2glWfDEhGR/GDz5s0ULlyYq6++2tuhiIhkmSsJdUFjTDngXuBrD8cjIiL5SExMDNdeey0FChTwdigiIlnmSkI9FPge+Mta+6sxphIQ49mwREQkP1DLPBHxBa70oZ5mra1trX08+fUW4HWPRyYiIj4tKSmJv/76Szckikie58rS4wAYY6oDXYFuwGEgxFNBiYiI79u2bRunTp1SQi0ieV6GCbUxJhAnge4GJACBQIi1NtbzoYmIiC9TyzwR8RXplnwYY34GvgUKAZ2Tu3scVTItIiLuoJZ5IuIrMqqh3geUAK4AyiZvu2AJchERkazYvHkzAQEBlC9f3tuhiIhkS7oJtbW2I1ALWA1EGGP+AUobYxrkVHAiIuK7YmJiuO666zDGeDsUEZFsybDLh7X2sLV2grW2NdAQGASMMsZsy5HoRETEZ8XExKh+WkR8git9qAGw1u611r5nrb0RaOrBmERExMclJCSwZcsW1U+LiE9wOaFOzVob5+5AREQk/4iNjSUhIUEz1CLiE7KUUIuIiGSHWuaJiC9RQi0iIjlOLfNExJdcdKVEY0xZ4FEgKPXx1tqengtLRER8WUxMDCVLlqRs2bIXP1hEJJdzZenxWcBPwHwg0bPhiIhIfrB582YqV66slnki4hNcSagDrLUDPB6JiIjkGzExMTRs2NDbYYiIuIUrNdRfG2PaezwSERHJF06dOkVcXJzqp0XEZ7iSUPfDSapPGGOOGGOOGmOOeDowERHxTVu2bCEpKUkdPkTEZ1y05MNaWyInAhERkfxBLfNExNekm1AbY6paa/80xtRNa7+1drXnwhIREV+lhFpEfE1GM9RPA2HAW2nss8AtHolIRER8WkxMDJdeeillypTxdigiIm6RbkJtrQ1L/tki58IRERFfd7ZlnoiIr9BKiSIikqNiYmKUUIuIT1FCLSIiOSY+Pp7t27croRYRn6KEWkREcszff/8NoB7UIuJTXFkpEWPMXUBTnJsRl1hrZ3g0KhER8UmbN28G1OFDRHzLRWeojTHvA48B64D1QC9jzBhPByYiIr5HLfNExBe5MkPdDKhprbUAxpiPcZJrERGRTImJieHKK6+kRAmtGSYivsOVGupNQMVUr68G1nomHBER8WXq8CEivsiVhPpSYKMxZqExZiHwB1DWGDPbGDPbo9GJiIhPUQ9qEfFFrpR8DPJ4FCIi4vOOHDnCnj17lFCLiM+5aEJtrV1kjAkEKltr5xtjigIFrbVHPR+eiIj4ir/++gtQyzwR8T2udPl4FJgOjE3eVAGY6cGYRETEB6llnoj4KldqqJ8AmgBHAKy1McDlngxKRER8z9mWeddee62XIxERcS9XEupT1trTZ18YYwriLPAiIiLispiYGCpUqEBAQIC3QxERcStXEupFxpiXgKLGmNbANGCOZ8MSERFfExMTo/ppEfFJriTULwD7cBZz6QV8C7zsyaBERMT3qGWeiPgqV7p8JBljJgOLrbWbciAmERHxMQcPHuTgwYNKqEXEJ7nS5aMDsAaYm/w6WAu6iIhIZpy9IVElHyLii1wp+RgMNAAOAVhr1wBBHotIRER8ztmEWjPUIuKLXEmoE6y1hz0eiYiI+KzNmzfj5+dHpUqVvB2KiIjbubL0+HpjzH1AAWNMZaAv8LNnwxIREV8SExNDYGAghQsX9nYoIiJu58oMdR+gBnAKmIKzwEt/D8YkIiI+Ri3zRMSXudLlIx4IT36IiIhkirWWmJgYGjdu7O1QREQ84qIJtTGmCvAszo2IKcdba2/xXFgiIuIr9u7dy5EjR3RDooj4LFdqqKcBHwLjgETPhiMiIr5GHT5ExNe5klAnWGs/8HgkIiLik9SDWkR8XboJtTGmTPLTOcaYx4EZODcmAmCtPejh2ERExAds3ryZggULEhgY6O1QREQ8IqMZ6lWABUzy6+dS7bOAmomKiMhFxcTEUKlSJQoWdOWPoiIieU+6/3Wz1l6Tk4GIiIhvUss8EfF1F+1DbYy5xxhTIvn5y8aYr4wxdTwfmoiI5HVJSUn89ddfuiFRRHyaKwu7DLTWHjXGNAXaAh/jdP0QERHJ0M6dO4mPj1dCLSI+zZWE+myrvNuAD6y1swCtHSsiIhellnkikh+4klDvMMaMBe4FvjXG+Lt4noiI5HNqmSci+YErifG9wPdAO2vtIaAM53b8EBERSVNMTAxFihShQoUK3g5FRMRjLtrDyFobD3yV6vUuYJcngxIREd+wefNmrr32Wvz89IdNEfFd+i+ciIh4TExMjOqnRcTnKaEWERGPSExM5O+//1b9tIj4PCXUIiLiEdu2beP06dOaoRYRn5fphNoYM98Y850x5nZPBCQiIr5h8+bNgFrmiYjvu+hNiWnoDpQDGrk5FhER8SHqQS0i+YUrS4/XS/3aWrsTKG+tHeOxqERExCuio6MJCgrCz8+PoKAgoqOjszxWTEwMxYoVo1y5cm6MUEQk93Gl5OMjY0ytsy+MMd2Alz0XkoiIeEN0dDRhYWHExcVhrSUuLo6wsLAsJ9WbN2+mcuXKGGPcHKmISO7iSkLdGfjYGFPNGPMo8DjQxrNhiYhITnvppZeIj48/Z1t8fDzh4eFZGk8t80Qkv7hoQm2t3QJ0Bb7ESa7bWGsPX+w8Y0wRY8wKY8zvxpgNxpiI5O1DjDE7jDFrkh/tU53zojHmL2PMJmNM26x/LBERyYw///yTrVu3prkvLi6OXbsyt57XmTNn+Oeff9QyT0TyhXQTamPMOmPMWmPMWmA6zpLjQcDy5G0Xcwq4xVp7AxAMtDPGnL2RcaS1Njj58W3y+1XHSdxrAO2A940xBbL4uURExAVHjhzh2WefpVatWhmWZlx99dV07NiROXPmkJCQcNFxY2NjSUxM1Ay1iOQLGXX5yFZbPGutBY4lvyyU/LAZnNIR+Nxaewr4xxjzF9AAWJadOERE5EJJSUl8+umnDBgwgL1799KzZ0/q1avHs88+e07ZR0BAAEOHDmX//v1MmjSJ2bNnU65cOR566CF69uzJtddem+b4apknIvlJujPU1to4a20cTou8g6leHwSudGVwY0wBY8waYC8wz1q7PHnXk8mz3xOMMaWTt10FbEt1+vbkbSIi4ka//vorN954Iz169OCaa65h+fLljBs3jt69exMVFUVgYCDGGAIDA4mKiuKZZ55h2LBhbN26lZkzZ1KvXj1ef/11rrvuOm655RY+++wzTp48ec57qGWeiOQnxplIzuAAY34D6ibPOGOM8QNWWmvruvwmxlwCzAD6APuA/Tiz1a8A5ay1PY0xY4Bl1trJyeeMB7611n553lhhQBhAxYoV68XFxbkahohIvrZ3715eeuklJkyYwOWXX87w4cO5//778fPL/KK5O3bs4OOPP2bcuHH8888/lC5dmvvvv59HHnmEdevW8dhjj3Hs2DEqVqzIa6+9RmhoqAc+kYhIzjHGrLLWhqS5z4WEeo21Nvi8bWuttbUzGcRg4Li1dkSqbUHA19bamsaYFwGstcOS930PDLHWplvyERISYleuXJmZMERE8p0zZ84wZswYhgwZwvHjx+nfvz8DBw6kZMmS2R47KSmJhQsXMm7cOL788ktOnz6Nn58fSUlJKccEBAQQFRWlpFpE8rSMEmpXpiW2GGP6GmMKJT/6AVtceNOyyTPTGGOKAq2AP40xqTv8dwLWJz+fDXQ1xvgbY64BKgMrXIhPRETS8eOPPxIcHMxTTz1Fo0aNWLduHW+++aZbkmkAPz+/lLKPnTt3Urp06XOSache6z0RkbzAlYT6MeBGYEfyoyHJJRcXUQ5YkNwR5FecGuqvgeFnO4gALYCnAKy1G4CpwB/AXOAJa21iJj+PiEi+lXqVwwoVKlC/fn1atWrFyZMnmT17Nt999x1Vq1b12PtfeumlHDp0KM196bXkExHxBRct+cjNVPIhIuI4u8rh+Quz3HPPPXzyyScUKVIkR+IICgoirXtbAgMDiY2NzZEYREQ8IVslH8aYCsaYGcaYvcaYPcaYL40xFdwfpoiIZFV4ePgFyTTAihUrciyZBoiMjCQgIOCcbQEBAURGRuZYDCIiOc2Vko+JOPXN5XHa2M1J3iYiIrlEeiUVOV1qERoammbrPd2QKCK+LKtdPi7Y5g0q+RARcVx++eXs27fvgu0qtRARcY/sdvnYb4y5P3mRlgLGmPuBA+4NUUREsurEiRNYay9YOlylFiIiOcOVhLoncC+wG9gFdAYe8mRQIiLiutdff539+/fz4osvqtRCRMQLXCn5aGKtXXqxbd6gkg8Rye9iYmKoVasWd999N9HR0d4OR0TEZ2W35OM9F7eJiEgOstbSp08f/P39GTFixMVPEBERjyiY3g5jTGOcBV3KGmOeTrWrJFDA04GJiEjGvvrqK77//nveeecdypUrd/ETRETEI9JNqIHCQPHkY0qk2n4Ep45aRES85NixY/Tr14/g4GAef/xxb4cjIpKvpZtQW2sXAYuMMZOstXEAxhg/oLi19khOBSgiIhcaOnQoO3bsYNq0aRQsmNHciIiIeJorNdTDjDEljTHFgD+ATcaY5zwcl4jkUtHR0QQFBeHn50dQUJBuhPOCDRs2MHLkSB5++GEaN27s7XBERPI9VxLq6skz0ncC3wIVgQc8GZSIuJ87EuHo6GjCwsKIi4vDWktcXBxhYWFKqnOQtZbHH3+ckiVL8vrrr3s7HBERIeMa6rMKGWMK4STUo621Z4wxGffaE5Fc5WwiHB8fD0BcXByPPvoou3fvplWrVpw4cSLlER8ff87r1I8PPvggZYyz4uPjCQ8PV7/jHBIdHc3ixYuJiorisssu83Y4IiKCa32o+wIDgN+B23BmqCdba2/yfHgZUx9qEdcEBQURFxeXrTGKFCnCyZMn09xnjCEpKSlb48vFHTp0iKpVqxIUFMTPP/+Mn58rf2QUERF3yKgP9UVnqK217wLvptoUZ4xp4a7gRMTztm7dmu6+6dOnExAQQNGiRS94nN3u7++fUiqSVmJesWJFT4YvyQYOHMi+ffv49ttvlUyLiOQiF02ojTFXAK8B5a21txpjqgONgfGeDk5Esi8xMZGAgACOHz9+wb7AwEDuvvtul8eKjIw8p3QEwM/Pj4EDB7olVknf6tWref/993n88cepW7eut8MREZFUXJnimAR8D5RPfr0Z6O+heETEjU6fPk23bt04fvw4hQoVOmdfQEAAkZGRmRovNDSUqKgoAgMDMcZQtmxZrLVER0enWw4i2ZeUlMTjjz9O2bJleeWVV7wdjoiInMeVhPoya+1UIAnAWpsAJHo0KhHJtvj4eO68806mTZvGiBEjmDhxYkoiHBgYSFRUVJZuJAwNDSU2NpakpCT27t3LJ598wsKFC7nnnns4c+aMBz6JjB8/nuXLlzNixAguueQSb4cjIiLncaXLx3FjzKWABTDGNAIOezQqEcmWI0eOcMcdd/DTTz8xduxYwsLCADzSieP+++/n2LFj9O7dmwceeIDo6GgKFCjg9vfJr/bv388LL7xAs2bN1ElFRCSXciWhfgaYDVxrjFkKlEVLj4vkWgcOHKBdu3asWbOG6OhounXr5vH3fOyxxzh69CjPP/88xYsX56OPPsIY4/H3zQ9eeOEFjhw5wpgxY3RNRURyKVe6fKwyxjQDrgcMsMlaq7/riuRCu3btonXr1vz111989dVX3HHHHTn23s899xxHjhzh1VdfpUSJErz99ttKALNp2bJljB8/nueee44aNWp4OxwREUmHK10+fge+AL6w1v7t+ZBEJCtiY2Np1aoVu3fv5ttvv+WWW27J8RiGDh3K0aNHGTVqFKVKlWLIkCE5HoOvSEhIoHfv3lSoUIFBgwZ5OxwREcmAKyUfHYAuwFRjTBJOcj3VWpt+Y1sRyVGbNm2iVatWHDt2jPnz59OoUSOvxGGM4e233+bo0aNERERQokQJnnnmGa/Ekte9//77/P7770yfPp3ixYt7OxwREcnARVdKPOdgYyoDA4FQa63X7zrSSokisGbNGtq0aYMxhnnz5lG7dm1vh0RiYiLdunVj2rRp59wUKa7ZtWsXVatWpXHjxnz33XcqnRERyQWytVJi8gBBwL04M9WJwPNui05Esuznn3+mffv2lCxZkvnz51OlShVvhwRAgQIFmDx5MvHx8Tz22GMUL16c++67z9th5RnPPvssJ0+e5L333lMyLSKSB7hSQ70cKARMA+6x1m7xeFQiclHz58+nY8eOlC9fnh9//DHXLf9duHBhpk2bRvv27enevTvFihWjY8eO3g4r11uwYAGfffYZgwYNonLlyt4OR0REXODKwi4PWmvrWmuHKZkWyR1mzZrFbbfdxrXXXstPP/2U65Lps4oWLcrs2bOpV68e9957L/Pnz/d2SLlSdHQ0QUFB+Pn50aZNGy677DJeeOEFb4clIiIuSjehNsbcn/y0vTHm6fMfORSfiHBuwnXZZZfRqVMngoODWbhwIVdeeaW3w8tQiRIl+O6776hatSodO3bk559/9nZIuUp0dDRhYWHExcVhrSUhIYGjR4/y1VdfeTs0ERFxUUYz1MWSf5ZI46FbzkVyyPkJ14EDBzDGEBYWRpkyZbwdnkvKlCnDDz/8wFVXXUX79u2JjIxM+QdCUFAQ0dHR3g7Ra8LDw4mPjz9n26lTpwgPD/dSRCIiklmZ6vKRcpIx/a21o9wfTuaoy4fkB0FBQcTFxV2wPTAwkNjY2JwPKBu2bt1KnTp1OHjw4DnbAwICiIqKypdLa/v5+ZHWf4eNMSQlJXkhIhERSUtGXT5cqaFOi0o+RHLI1q1pt3xPb3tuVrFiRYoUKXLB9vj4+Hw7I5veXxlya128iIhcKKsJtfo4ieSQsmXLprk9ryZcu3btSnN7XvwHQnYkJiby3HPPceDAAfz8zv1PcUBAAJGRkV6KTEREMiurCXXm60REJNOWLVvGv//+e0Ev4ryccKX3D4G8+g+ErDhy5Ah33nknI0aM4PHHH2fixIkEBgZijCEwMDDflr+IiORVGXX5OGqMOZLG4yhQPgdjFMmX/vjjD2677TYqVqzI6NGjfSbhioyMJCAg4JxtRYoUybP/QMisLVu2cOONN/Ldd98xZswYxowZQ/fu3YmNjSUpKYnY2Ng8+7sVEcmvsnRTYm6hmxLFV23dupUmTZqQkJDA0qVLqVSpkrdDcqvo6GjCw8PZunUrfn5+XHrppfz9998UL+7bDYQWL17MXXfdRVJSEtOmTaNly5beDklERFzkiZsSRcRD9u/fT9u2bTly5Ahz5871uWQaIDQ0NGVG9scff2Tfvn0888wz3g7Lo8aPH0+rVq247LLLWL58uZJpEREfooRaJBc5duwYt912G//88w9z5szhhhtu8HZIHtesWTOee+45oqKimDNnjrfDcbvExESeeeYZHnnkEVq0aMEvv/yiJcVFRHyMEmqRXOL06dN07tyZlStX8sUXX3DzzTd7O6QcM3ToUIKDg3n44YfZs2ePt8Nxm8OHD3PHHXfw9ttv07dvX7755hsuueQSb4clIiJupoRaJBdISkqiR48efP/990RFRdGxY0dvh5Sj/P39iY6O5ujRozz88MNpLnSS1/z99980btyYefPmMXbsWN555x0KFizo7bBERMQDlFCLeJm1lqeeeoopU6YwbNgwHn74YW+H5BXVq1dn+PDhfPPNN4wdO9bb4WTLwoULadCgAXv27OGHH34gLCzM2yGJiIgHKaEW8bJhw4bx7rvv0r9/fwYMGODtcLzqiSeeoE2bNjz99NNs2rTJ2+G4JDo6mqCgIPz8/AgKCuKRRx6hdevWXHHFFSxfvpwWLVp4O0QREfEwtc0T8aJx48bx6KOPEhoayieffHLBinn50c6dO6lVqxaVKlXi559/plChQt4OKV3R0dGEhYURHx9/zvbatWuzePFiSpUq5aXIRETE3dQ2TyQXmjFjBr169eLWW29l4sSJSqaTlS9fno8++oiVK1cydOhQb4eTofDw8AuSaYBDhw4pmRYRyUf0/+AiXrBo0SK6detGgwYNmDZtWq6ehfWGu+66i4ceeojXXnuNn3/+2dvhpGvr1q1pbt+2bVsORyIiIt6khFokh61Zs4YOHTpQqVIlvv76a4oVK+btkHKld955h8DAQO6//36OHj3q7XAucOLEiXRXdqxYsWIORyMiIt6khFokB/3999+0a9eOkiVL8v3333PppZd6O6Rcq0SJEnz66afExcXRr18/b4dzjtWrVxMSEsLRo0cvaIUXEBBAZGSklyITERFvUEIt4mGpu0BUrVqVY8eO8cMPP3D11Vd7O7Rcr0mTJrz00ktMnDiRL7/80tvhkJCQwKuvvkrDhg05dOgQc+fOZdKkSQQGBmKMITAwkKioKEJDQ70dqoiI5CB1+RDxoLS6QBQpUoRx48Yp6XLRmTNnuPHGG9myZQvr1q2jfPnyXolj8+bNdO/eneXLl9O1a1fGjBlDmTJlvBKLiIjkPHX5EPGStLpAnDx5kvDwcC9FlPcUKlSI6OhoTp48yUMPPURSUlKOvr+1lvfff5/g4GA2b97MlClTmDJlipJpERFJoYRaxIPS6wKR3nZJW5UqVXjrrbf44YcfGDNmTI69744dO7j11lt54oknuPnmm1m3bh1du3bNsfcXEZG8QQm1iIesX78+3d7S6gKReb169eK2227j+eefZ8OGDR5/v88//5xatWrx008/8f777/Pdd99x1VVXefx9RUQk71FCLeIBixcvpmnTppQoUYIiRYqcs09dILLGGMP48eMpUaIE999/P6dPn/bI+xw8eJBu3brRrVs3qlSpwpo1a+jduzfGGI+8n4iI5H1KqEXc7Msvv6RNmzaUK1eONWvWMG7cOHWBcJMrrriC8ePHs2bNGgYNGpTt8VJ3YAkKCmLAgAHUqlWL6dOn8+qrr7JkyRIqV67shshFRMSXqcuHiBu9//77PPnkkzRq1Ig5c+aoz7SH9OrVi6ioKK644gr27t1LxYoViYyMzNQ/VNLqwALO0udz5syhbt267g5bRETysIy6fBRMa6OIZI61loEDBxIZGckdd9zB559/TkBAgLfD8lkNGzbko48+Ys+ePQDExcXx6KOPsnfvXtq3b8+ZM2c4c+YMp0+fTnl+/rZ+/fpdkEwDFChQQMm0iIhkimaoRbIpISGBXr16MWHCBB555BE++OCDC1bPE/cKCgoiLi7OI2MbY3K8NZ+IiOR+mqEW8ZDjx4/TpUsXvvnmGwYNGsSQIUN081oOyKjtYHR0NIUKFaJQoUIULlw45fn529q0acPOnTsvOF8dWEREJLOUUItk0f79+7n99tv59ddf+fDDD+nVq5e3Q8o3KlasmOYMdWBgIPfdd59LYwwfPvyCGmp1YBERkaxQlw+RLIiNjaVJkyb8/vvvfPnll0qmc1hkZOQFNeqZTYZDQ0OJiopSBxYREck21VCLZNKaNWu49dZbOXnyJHPmzKFp06beDilfio6OJjw8nK1bt2apy4eIiEhmZFRDrYRaJBP+97//ceedd1KqVCnmzp1LjRo1vB2SiIiI5ICMEmqVfIhkIPXCH2XLlqV169ZUrFiRZcuWKZkWERERQDcliqTr/IU/9u/fj5+fH3379qVChQpejk5ERERyC81Qi6QjPDz8goU/kpKSeO2117wUkYiIiORGSqhF0pFer+OMeiCLiIhI/qOEWiQN27dvT3e1Qy38ISIiIqkpoRY5z6+//kr9+vXx8/PD39//nH1a+ENERETOp4RaJJWpU6dy8803U6RIEVatWsX48eO18IeIiIhkSF0+RABrLa+88gqDBw+mSZMmzJgxg7Jly1KjRg0l0CIiIpIhJdSS7504cYKHH36YKVOm0L17d6Kioi4o9RARERFJjxJqydd2797NnXfeyfLlyxk2bBgDBgzAGOPtsERERCQPUUIt+dbvv//OHXfcwYEDB/jqq6/o1KmTt0MSERGRPEg3JUq+NHv2bJo0aUJSUhJLlixRMi0iIiJZpoRa8hVrLW+++SZ33nkn1apVY8WKFdSpU8fbYYmIiEgepoRa8o3Tp0/z8MMP8/zzz3PPPfewaNEiypcv7+2wREREJI9TQi35wv79+2ndujUTJ05k0KBBTJkyhYCAAG+HJSIiIj7AYwm1MaaIMWaFMeZ3Y8wGY0xE8vYyxph5xpiY5J+lU53zojHmL2PMJmNMW0/FJvlDdHQ0QUFB+Pn5Ua5cOZYuXcpnn31GREQEfn76t6SIiIi4hyezilPALdbaG4BgoJ0xphHwAvCjtbYy8GPya4wx1YGuQA2gHfC+MaaAB+MTHxYdHU1YWBhxcXFYa0lISKBQoUIkJSV5OzQRERHxMR5LqK3jWPLLQskPC3QEPk7e/jFwZ/LzjsDn1tpT1tp/gL+ABp6KT3zbSy+9RHx8/DnbTp48SXh4uJciEhEREV/l0b97G2MKGGPWAHuBedba5cAV1tpdAMk/L08+/CpgW6rTtydvE8mUM2fOsHXr1jT3pbddREREJKs8mlBbaxOttcFABaCBMaZmBoentTydveAgY8KMMSuNMSv37dvnpkjFVxw4cIA2bdqku79ixYo5GI2IiIjkBzlyZ5a19hCwEKc2eo8xphxA8s+9yYdtB65OdVoFYGcaY0VZa0OstSFly5b1ZNiSx/zxxx80aNCAZcuW0bt37wu6eAQEBBAZGeml6ERERMRXebLLR1ljzCXJz4sCrYA/gdnAg8mHPQjMSn4+G+hqjPE3xlwDVAZWeCo+8S3ffvstjRo14vjx4yxcuJD333+fqKgoAgMDMcYQGBhIVFQUoaGh3g5VREREfIyx9oKqCvcMbExtnJsOC+Ak7lOttUONMZcCU4GKwFbgHmvtweRzwoGeQALQ31r7XUbvERISYleuXOmR+CVvsNby9ttv89xzzxEcHMysWbO4+uqrL36iiIiISCYYY1ZZa0PS3OephDonKKHO306dOkXv3r2ZOHEinTt3ZtKkSRQrVszbYYmIiIgPyiih1uoWkift3buXli1bMnHiRAYPHswXX3yhZFpERES8oqC3AxDJrLVr13LHHXewd+9evvjiC+69915vhyQiIiL5mGaoJU+ZNWsWN954IwkJCfz0009KpkVERMTrlFBLnmCtZdiwYXTq1Inq1avz66+/EhKSZhmTiIiISI5SyYfkeidPnuSRRx4hOjqabt26MX78eIoWLertsEREREQAzVBLLhUdHU1QUBB+fn6UKlWK6OhoIiMjiY6OVjItIiIiuYpmqCXXiY6OJiwsjPj4eABOnz6Nv79/yiItIiIiIrmJZqgl19i9ezezZs3i8ccfT0mmzzp16hTh4eFeikxEREQkfZqhFq+Ij49n9erVLF++POWxdevWDM+52H4RERERb9AMtbhV6trnoKAgoqOjSUpKYuPGjUyaNInevXtTt25dSpYsyU033cSzzz7LihUraNSoEW+99RZLlixJd+nwihUr5vCnEREREbk4LT0ubnN+7TOAn58f/v7+nDhxAoCSJUtSv359GjZsSMOGDWnQoAFXXnnlRccJCAggKiqK0NDQnPkwIiIiIqlktPS4Sj7EbcLDwy+ofU5KSqJAgQJMmDCBhg0bUrVqVfz8Mv7DyNmkOTw8nK1bt1KxYkUiIyOVTIuIiEiupBlqcYtjx45RokSJNPcZY0hKSsrhiERERETcJ6MZatVQS7bNnTuXGjVqpLtftc8iIiLiy5RQS5bt37+fBx54gFtvvZWAgAAGDRpEQEDAOccEBAQQGRnppQhFREREPE8JtWSatZbPPvuMatWq8fnnnzNw4EB+++03IiIiiIqKSlmAJTAwUDcSioiIiM9TDbVkytatW+nduzfffvstDRo0YNy4cdSqVcvbYYmIiIh4lGqoJduSkpIYPXo0NWrUYOHChYwcOZKff/5ZybSIiIjke2qbJxf1xx9/8Mgjj7Bs2TLatGnD2LFjCQoK8nZYIiIiIrmCZqglXadPn2bo0KHUqVOHTZs28cknnzB37lwl0yIiIiKpaIZaUkRHR6cspnLFFVdQoEABduzYQbdu3Rg1ahSXX365t0MUERERyXWUUAtw4XLfu3fvxhjDM888w4gRI7wcnYiIiEjupZIPAdJeNtxay/Tp070UkYiIiEjeoIRa2LlzJ3FxcWnu27p1aw5HIyIiIpK3KKHOxxITExkzZgxVq1ZN9xgtGy4iIiKSMSXU+dTatWtp0qQJTz75JI0aNeKtt97SsuEiIiIiWaCEOp+Jj49nwIAB1K1bly1btjB58mS+//57nn76aS0bLiIiIpIFWno8H5k7dy69e/cmNjaWhx9+mOHDh1OmTBlvhyUiIiKS62np8Xxu9+7ddO3alVtvvZUiRYqwaNEixo0bp2RaRERExA2UUPuwpKQkoqKiqFatGjNmzGDo0KGsWbOGm2++2duhiYiIiPgMJdQ+Ijo6mqCgIPz8/AgKCuKNN97g5ptvplevXtSpU4d169YxcOBA/P39vR2qiIiIiE/RSok+4PxVDuPi4njhhRcoVqwYkyZNonv37hhjvByliIiIiG9SQu0D0lrlEKB06dI8+OCDXohIREREJP9QyYcPSG81wx07duRwJCIiIiL5jxJqH3DllVemuV2rHIqIiIh4nhLqPC4mJoZjx45dUCOtVQ5FREREcoYS6jxsx44dtG7dmiJFijB8+HCtcigiIiLiBbopMY86cOAAbdq04eDBgyxcuJC6devy7LPPejssERERkXxHCXUedOzYMdq3b8/ff//N999/T926db0dkoiIiEi+pYQ6jzl16hR33nknq1at4quvvqJZs2beDklEREQkX1NCnYckJiYSGhrKjz/+yMcff0yHDh28HZKIiIhIvqebEvMIay29evXiyy+/ZOTIkXTv3t3bIYmIiIgISqjzjBdeeIHx48fz8ssv079/f2+HIyIiIiLJlFDnAcOHD2f48OE8/vjjDB061NvhiIiIiEgqSqhzuXHjxjFgwAC6devGe++9d8ECLiIiIiLiXUqoc7Hp06fTq1cvbr31Vj7++GP8/PTrEhEREclt8m2GFh0dTVBQEH5+fgQFBREdHe3tkM4xb9487rvvPho3bsz06dMpVKiQt0MSERERkTTky7Z50dHRhIWFER8fD0BcXBxhYWEAuWK57uXLl9OpUyeqVavG119/TUBAgLdDEhEREZF0GGutt2PIspCQELty5cpMnxcUFERcXNwF2wMDA4mNjXVDZFm3YcMGbrrpJsqUKcOSJUu48sorvRqPiIiIiIAxZpW1NiStffmu5GPnzp1pJtMAW7duzeFoHKnLT2644QaSkpKYN2+ekmkRERGRPCDfJNS//vor999/P4GBgekeU7RoUY4cOZKDUf1XfhIXF4e1lsTERE6dOsXPP/+co3GIiIiISNb4dEKdkJDA1KlTadKkCQ0aNGD27Nk88cQTvP322xfUJRcqVIj4+HhCQkJYu3ZtjsUYHh6eUst91smTJwkPD8+xGEREREQk63wyoT548CDDhw+nUqVKdOnShT179jBq1Ci2b9/OqFGjeOqpp4iKiiIwMBBjDIGBgUycOJGFCxdy7NgxGjZsyIQJEzweZ24sPxERERGRzMnTNyUaY2xgYCCRkZGEhoayceNG3n33XT7++GNOnDjBLbfcQr9+/bjtttsoUKCAS2Pu2bOH0NBQfvzxRx588EHGjBlDsWLF3Br36dOneeeddxg6dCjHjh1L85jccIOkiIiIiDgyuikxzyfUAP7+/lSpUoV169bh7+9PaGgo/fr1o3bt2lkaNzExkaFDh/LKK69QvXp1pk+fTtWqVd0S8w8//EDfvn3ZtGkTd9xxBy1atODll18+p+wjICCAqKioXNHCT0RERETyQZePU6dOsWHDBl555RW2bdvG+PHjs5xMAxQoUICIiAjmzp3Lnj17CAkJYcqUKdmKMTY2lrvuuou2bduSmJjIN998w+zZs9MsP1EyLSIiIpJ3+MQMdfJzkpKS3P4eO3bsoEuXLixdupTHHnuMkSNHUqRIEZfPP3HiBG+++SbDhg3Dz8+Pl19+maeffhp/f3+3xyoiIiIinuHzM9QAFStW9Mi4V111FQsWLOD555/nww8/pEmTJmzZsuWi51lrmT17NjVq1GDw4MF06NCBP//8kxdffFHJtIiIiIgP8YmEOiAggMjISI+NX6hQId544w1mzZrFli1bqFu3LjNmzEj3+M2bN9O+fXs6duxI0aJF+fHHH/niiy+4+uqrPRajiIiIiHhHnk+oc7LmuEOHDvz2229UrlyZu+66i2eeeYZPPvkkZZXDihUr0qFDB2rWrMnSpUt5++23WbNmDbfccovHYxMRERER78jTNdQhISF25cqVOf6+p06d4rnnnuO9997Dz8/vgtrtpk2bMm3aNC0dLiIiIuIj8kUNdU7y9/fn3Xff5bLLLkvzRsht27YpmRYRERHJJ5RQZ8OBAwfS3K5VDkVERETyDyXU2ZBeZxFPdRwRERERkdxHCXU2REZGEhAQcM42T3ccEREREZHcRQl1NoSGhmqVQxEREZF8Tl0+REREREQuQl0+REREREQ8RAm1iIiIiEg2KKEWEREREckGJdQiIiIiItmghFpEREREJBuUUIuIiIiIZIMSahERERGRbFBCLSIiIiKSDUqoRURERESywWMJtTHmamPMAmPMRmPMBmNMv+TtQ4wxO4wxa5If7VOd86Ix5i9jzCZjTFtPxSYiIiIi4i4FPTh2AvCMtXa1MaYEsMoYMy9530hr7YjUBxtjqgNdgRpAeWC+MaaKtTbRgzGKiIiIiGSLx2aorbW7rLWrk58fBTYCV2VwSkfgc2vtKWvtP8BfQANPxSciIiIi4g45UkNtjAkC6gDLkzc9aYxZa4yZYIwpnbztKmBbqtO2k3ECLiIiIiLidR5PqI0xxYEvgf7W2iPAB8C1QDCwC3jr7KFpnG7TGC/MGLPSGLNy3759nglaRERERMRFHk2ojTGFcJLpaGvtVwDW2j3W2kRrbRLwEf+VdWwHrk51egVg5/ljWmujrLUh1tqQsmXLejJ8EREREZGLMtZeMAnsnoGNMcDHwEFrbf9U28tZa3clP38KaGit7WqMqQF8hpNglwd+BCpndFOiMeYosCmboZYCDmdzDHeNk1vGuAzYnwvicNc4uWWM3HJdfe1340vXNTf9bnRd3T8G6Lp6Ygx3XFN3xeJLY+SW76q7xnHHGJWttaXS3GOt9cgDaIpTsrEWWJP8aA98CqxL3j4bKJfqnHDgb5wk+VYX3mOlG+KMctPnzfY4uWgMXVcfvq4++Lvxmeuay343uq6e+d3ourp/jGxf01z2eXLLGLniu5rLrkm6Y3isbZ61dglp10V/m8E5kUCkp2JKx5xcNE5uGcMddF09Izd9ltwUS3blls+Sm3437pBbrkluGcNdcsvnyS1juEtu+Ty5ZQx3yE3/TfPoGB4r+cgJxpiV1toQb8fha3RdPUPX1TN0XT1D19UzdF3dT9fUM3RdMyevLz0e5e0AfJSuq2founqGrqtn6Lp6hq6r++maeoauaybk6RlqERERERFvy+sz1CIiIiIiXpXrEurk1RP3GmPWp9p2gzFmmTFmnTFmjjGmZPL2UGPMmlSPJGNMcPK+esnH/2WMeTe5jV++5cbrutAYsynVvsu99JG8LpPXtJAx5uPk7RuNMS+mOkff1VTceF31XU0lk9e1sDFmYvL2340xzVOdo+9rKm68rvq+JjPGXG2MWZD8v+kNxph+ydvLGGPmGWNikn+WTnXOi8nfyU3GmLaptuv7mszN11Xf1/O5o52JOx/AzUBdYH2qbb8CzZKf9wReSeO8WsCWVK9XAI1xOo18hwtt+Hz54cbruhAI8fbnyQ2PzFxT4D7g8+TnAUAsEJT8Wt9Vz1xXfVezfl2fACYmP78cWAX4Jb/W99Uz11Xf1/+uXzmgbvLzEsBmoDowHHghefsLwBvJz6sDvwP+wDU47XcLJO/T99Uz11Xf1/MeuW6G2lq7GDh43ubrgcXJz+cBd6dxajdgCjiLxwAlrbXLrPOb/wS40yMB5xHuuK5yrkxeUwsUM8YUBIoCp4Ej+q5eyB3XNSfizGsyeV2r4yyuhbV2L3AICNH39ULuuK6ejzJvsdbustauTn5+FNgIXAV0xFkwjuSfdyY/74jzD+tT1tp/gL+ABvq+nstd1zVHg85Dcl1CnY71QIfk5/dw7hLlZ3Xhv8TvKpylzM/anrxNzpXZ63rWxOQ/8QzMz38+S0d613Q6cBzYBWwFRlhrD6Lvqqsye13P0nc1Y+ld19+BjsaYgsaYa4B6yfv0fXVNZq/rWfq+nscYEwTUAZYDV9jklZaTf54tM7gK2JbqtLPfS31f05HN63qWvq+p5JWEuifwhDFmFc6fKU6n3mmMaQjEW2vP1rCl9YtVO5MLZfa6AoRaa2sBNyU/HsipYPOI9K5pAyARKI/zp7NnjDGV0HfVVZm9rqDvqivSu64TcP7PcyUwCvgZSEDfV1dl9rqCvq8XMMYUB74E+ltrM/rLU3rfS31f0+CG6wr6vl7AYyslupO19k+gDYAxpgpw23mHdOXcWdTtQIVUrysAOz0ZY16UheuKtXZH8s+jxpjPcBKaTzwfbd6QwTW9D5hrrT0D7DXGLMX5U+9P6Lt6UVm4rlv0Xb249K6rtTYBeOrsccaYn4EY4F/0fb2oLFxX/bf1PMaYQjhJX7S19qvkzXuMMeWstbuSyzn2Jm/fzrkz/We/l8oFzuOm66rvaxryxAz12btHjTF+wMvAh6n2+eH8Se3zs9uS/2Rx1BjTKPnPEN2BWTkadB6Q2eua/GfKy5KfFwJux/nTpiTL4JpuBW4xjmJAI+BPfVddk9nrqu+qa9K7rsaYgOTriTGmNZBgrf1D31fXZPa66vt6ruTv1nhgo7X27VS7ZgMPJj9/kP++e7OBrsYY/+RSmsrACn1fz+Wu66rvazq8fVfk+Q+cGdFdwBmcfx09DPTDuRt1M/A6yQvSJB/fHPgljXFCcH7BfwOjU5+THx/uuK5AMZy70tcCG4B3SL7jNz8+MnNNgeLAtOTr9gfwXKpx9F1183XVdzXb1zUI2IRz09J8IDDVOPq+uvm66vt6wTVtilNasBZYk/xoD1yKc1NnTPLPMqnOCU/+Tm4iVScPfV/df131fU37oZUSRURERESyIU+UfIiIiIiI5FZKqEVEREREskEJtYiIiIhINiihFhERERHJBiXUIiIiIiLZoIRaRERERCQblFCLiIiIiGSDEmoRERERkWz4P8Fouzc7z37yAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Figure 7.5: Forecasting livestock, sheep in Asia: comparing forecasting performance of non-seasonal methods.\n"
     ]
    }
   ],
   "source": [
    "fit1 = SimpleExpSmoothing(livestock2, initialization_method=\"estimated\").fit()\n",
    "fcast1 = fit1.forecast(9).rename(\"SES\")\n",
    "fit2 = Holt(livestock2, initialization_method=\"estimated\").fit()\n",
    "fcast2 = fit2.forecast(9).rename(\"Holt's\")\n",
    "fit3 = Holt(livestock2, exponential=True, initialization_method=\"estimated\").fit()\n",
    "fcast3 = fit3.forecast(9).rename(\"Exponential\")\n",
    "fit4 = Holt(livestock2, damped_trend=True, initialization_method=\"estimated\").fit(damping_trend=0.98)\n",
    "fcast4 = fit4.forecast(9).rename(\"Additive Damped\")\n",
    "fit5 = Holt(livestock2, exponential=True, damped_trend=True, initialization_method=\"estimated\").fit()\n",
    "fcast5 = fit5.forecast(9).rename(\"Multiplicative Damped\")\n",
    "\n",
    "ax = livestock2.plot(color=\"black\", marker=\"o\", figsize=(12,8))\n",
    "livestock3.plot(ax=ax, color=\"black\", marker=\"o\", legend=False)\n",
    "fcast1.plot(ax=ax, color='red', legend=True)\n",
    "fcast2.plot(ax=ax, color='green', legend=True)\n",
    "fcast3.plot(ax=ax, color='blue', legend=True)\n",
    "fcast4.plot(ax=ax, color='cyan', legend=True)\n",
    "fcast5.plot(ax=ax, color='magenta', legend=True)\n",
    "ax.set_ylabel('Livestock, sheep in Asia (millions)')\n",
    "plt.show()\n",
    "print('Figure 7.5: Forecasting livestock, sheep in Asia: comparing forecasting performance of non-seasonal methods.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-10-05T09:40:15.958575Z",
     "start_time": "2017-10-05T09:40:15.615Z"
    }
   },
   "source": [
    "## Holt's Winters Seasonal\n",
    "Finally we are able to run full Holt's Winters Seasonal Exponential Smoothing  including a trend component and a seasonal component.\n",
    "statsmodels allows for all the combinations including as shown in the examples below:\n",
    "1. ```fit1``` additive trend, additive seasonal of period ```season_length=4``` and the use of a Box-Cox transformation.\n",
    "1. ```fit2``` additive trend, multiplicative seasonal of period ```season_length=4``` and the use of a Box-Cox transformation..\n",
    "1. ```fit3``` additive damped trend, additive seasonal of period ```season_length=4``` and the use of a Box-Cox transformation.\n",
    "1. ```fit4``` additive damped trend, multiplicative seasonal of period ```season_length=4``` and the use of a Box-Cox transformation.\n",
    "\n",
    "The plot shows the results and forecast for ```fit1``` and ```fit2```.\n",
    "The table allows us to compare the results and parameterizations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-07T12:39:28.375871Z",
     "start_time": "2017-12-07T12:39:18.040674Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Figure 7.6: Forecasting international visitor nights in Australia using Holt-Winters method with both additive and multiplicative seasonality.\n"
     ]
    },
    {
     "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>Additive</th>\n",
       "      <th>Multiplicative</th>\n",
       "      <th>Additive Dam</th>\n",
       "      <th>Multiplica Dam</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>$\\alpha$</th>\n",
       "      <td>1.490116e-08</td>\n",
       "      <td>1.490116e-08</td>\n",
       "      <td>1.490116e-08</td>\n",
       "      <td>1.490116e-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$\\beta$</th>\n",
       "      <td>1.409864e-08</td>\n",
       "      <td>5.533042e-25</td>\n",
       "      <td>6.490738e-09</td>\n",
       "      <td>5.042333e-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$\\phi$</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.430416e-01</td>\n",
       "      <td>9.536043e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$\\gamma$</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>5.388625e-16</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.899280e-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$l_0$</th>\n",
       "      <td>1.119348e+01</td>\n",
       "      <td>1.106373e+01</td>\n",
       "      <td>1.084022e+01</td>\n",
       "      <td>9.899275e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$b_0$</th>\n",
       "      <td>1.205395e-01</td>\n",
       "      <td>1.198953e-01</td>\n",
       "      <td>2.456749e-01</td>\n",
       "      <td>1.975443e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SSE</th>\n",
       "      <td>4.402746e+01</td>\n",
       "      <td>3.611262e+01</td>\n",
       "      <td>3.527619e+01</td>\n",
       "      <td>3.062033e+01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Additive  Multiplicative  Additive Dam  Multiplica Dam\n",
       "$\\alpha$  1.490116e-08    1.490116e-08  1.490116e-08    1.490116e-08\n",
       "$\\beta$   1.409864e-08    5.533042e-25  6.490738e-09    5.042333e-09\n",
       "$\\phi$             NaN             NaN  9.430416e-01    9.536043e-01\n",
       "$\\gamma$  0.000000e+00    5.388625e-16  0.000000e+00    1.899280e-15\n",
       "$l_0$     1.119348e+01    1.106373e+01  1.084022e+01    9.899275e+00\n",
       "$b_0$     1.205395e-01    1.198953e-01  2.456749e-01    1.975443e-01\n",
       "SSE       4.402746e+01    3.611262e+01  3.527619e+01    3.062033e+01"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fit1 = ExponentialSmoothing(aust, seasonal_periods=4, trend='add', seasonal='add', use_boxcox=True, initialization_method=\"estimated\").fit()\n",
    "fit2 = ExponentialSmoothing(aust, seasonal_periods=4, trend='add', seasonal='mul', use_boxcox=True, initialization_method=\"estimated\").fit()\n",
    "fit3 = ExponentialSmoothing(aust, seasonal_periods=4, trend='add', seasonal='add', damped_trend=True, use_boxcox=True, initialization_method=\"estimated\").fit()\n",
    "fit4 = ExponentialSmoothing(aust, seasonal_periods=4, trend='add', seasonal='mul', damped_trend=True, use_boxcox=True, initialization_method=\"estimated\").fit()\n",
    "results=pd.DataFrame(index=[r\"$\\alpha$\",r\"$\\beta$\",r\"$\\phi$\",r\"$\\gamma$\",r\"$l_0$\",\"$b_0$\",\"SSE\"])\n",
    "params = ['smoothing_level', 'smoothing_trend', 'damping_trend', 'smoothing_seasonal', 'initial_level', 'initial_trend']\n",
    "results[\"Additive\"]       = [fit1.params[p] for p in params] + [fit1.sse]\n",
    "results[\"Multiplicative\"] = [fit2.params[p] for p in params] + [fit2.sse]\n",
    "results[\"Additive Dam\"]   = [fit3.params[p] for p in params] + [fit3.sse]\n",
    "results[\"Multiplica Dam\"] = [fit4.params[p] for p in params] + [fit4.sse]\n",
    "\n",
    "ax = aust.plot(figsize=(10,6), marker='o', color='black', title=\"Forecasts from Holt-Winters' multiplicative method\" )\n",
    "ax.set_ylabel(\"International visitor night in Australia (millions)\")\n",
    "ax.set_xlabel(\"Year\")\n",
    "fit1.fittedvalues.plot(ax=ax, style='--', color='red')\n",
    "fit2.fittedvalues.plot(ax=ax, style='--', color='green')\n",
    "\n",
    "fit1.forecast(8).rename('Holt-Winters (add-add-seasonal)').plot(ax=ax, style='--', marker='o', color='red', legend=True)\n",
    "fit2.forecast(8).rename('Holt-Winters (add-mul-seasonal)').plot(ax=ax, style='--', marker='o', color='green', legend=True)\n",
    "\n",
    "plt.show()\n",
    "print(\"Figure 7.6: Forecasting international visitor nights in Australia using Holt-Winters method with both additive and multiplicative seasonality.\")\n",
    "\n",
    "results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The Internals\n",
    "It is possible to get at the internals of the Exponential Smoothing models. \n",
    "\n",
    "Here we show some tables that allow you to view side by side the original values $y_t$, the level $l_t$, the trend $b_t$, the season $s_t$ and the fitted values $\\hat{y}_t$. Note that these values only have meaningful values in the space of your original data if the fit is performed without a Box-Cox transformation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "fit1 = ExponentialSmoothing(aust, seasonal_periods=4, trend='add', seasonal='add', initialization_method=\"estimated\").fit()\n",
    "fit2 = ExponentialSmoothing(aust, seasonal_periods=4, trend='add', seasonal='mul', initialization_method=\"estimated\").fit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-07T12:39:28.399765Z",
     "start_time": "2017-12-07T12:39:28.377215Z"
    }
   },
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>$\\hat{y}_t$</th>\n",
       "      <th>$b_t$</th>\n",
       "      <th>$l_t$</th>\n",
       "      <th>$s_t$</th>\n",
       "      <th>$y_t$</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2005-01-01</th>\n",
       "      <td>44.584128</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>34.297595</td>\n",
       "      <td>10.286532</td>\n",
       "      <td>41.7275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-04-01</th>\n",
       "      <td>24.938189</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>34.895417</td>\n",
       "      <td>-9.957228</td>\n",
       "      <td>24.0418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-07-01</th>\n",
       "      <td>33.005765</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>35.493239</td>\n",
       "      <td>-2.487474</td>\n",
       "      <td>32.3281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-10-01</th>\n",
       "      <td>37.031107</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>36.091061</td>\n",
       "      <td>0.940046</td>\n",
       "      <td>37.3287</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-01-01</th>\n",
       "      <td>46.975416</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>36.688883</td>\n",
       "      <td>10.286532</td>\n",
       "      <td>46.2132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-04-01</th>\n",
       "      <td>27.329477</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>37.286705</td>\n",
       "      <td>-9.957228</td>\n",
       "      <td>29.3463</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-07-01</th>\n",
       "      <td>35.397053</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>37.884527</td>\n",
       "      <td>-2.487474</td>\n",
       "      <td>36.4829</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-01</th>\n",
       "      <td>39.422395</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>38.482349</td>\n",
       "      <td>0.940046</td>\n",
       "      <td>42.9777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-01-01</th>\n",
       "      <td>49.366704</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>39.080171</td>\n",
       "      <td>10.286532</td>\n",
       "      <td>48.9015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-04-01</th>\n",
       "      <td>29.720765</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>39.677993</td>\n",
       "      <td>-9.957228</td>\n",
       "      <td>31.1802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-07-01</th>\n",
       "      <td>37.788341</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>40.275815</td>\n",
       "      <td>-2.487474</td>\n",
       "      <td>37.7179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-10-01</th>\n",
       "      <td>41.813683</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>40.873637</td>\n",
       "      <td>0.940046</td>\n",
       "      <td>40.4202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-01</th>\n",
       "      <td>51.757991</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>41.471459</td>\n",
       "      <td>10.286532</td>\n",
       "      <td>51.2069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-01</th>\n",
       "      <td>32.112053</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>42.069281</td>\n",
       "      <td>-9.957228</td>\n",
       "      <td>31.8872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-07-01</th>\n",
       "      <td>40.179629</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>42.667103</td>\n",
       "      <td>-2.487474</td>\n",
       "      <td>40.9783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-10-01</th>\n",
       "      <td>44.204971</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>43.264925</td>\n",
       "      <td>0.940046</td>\n",
       "      <td>43.7725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-01-01</th>\n",
       "      <td>54.149279</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>43.862747</td>\n",
       "      <td>10.286532</td>\n",
       "      <td>55.5586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-04-01</th>\n",
       "      <td>34.503341</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>44.460569</td>\n",
       "      <td>-9.957228</td>\n",
       "      <td>33.8509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-07-01</th>\n",
       "      <td>42.570917</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>45.058391</td>\n",
       "      <td>-2.487474</td>\n",
       "      <td>42.0764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-10-01</th>\n",
       "      <td>46.596258</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>45.656213</td>\n",
       "      <td>0.940046</td>\n",
       "      <td>45.6423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>56.540567</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>46.254035</td>\n",
       "      <td>10.286532</td>\n",
       "      <td>59.7668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-04-01</th>\n",
       "      <td>36.894629</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>46.851857</td>\n",
       "      <td>-9.957228</td>\n",
       "      <td>35.1919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-07-01</th>\n",
       "      <td>44.962205</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>47.449679</td>\n",
       "      <td>-2.487474</td>\n",
       "      <td>44.3197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-10-01</th>\n",
       "      <td>48.987546</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>48.047501</td>\n",
       "      <td>0.940046</td>\n",
       "      <td>47.9137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>58.931855</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-04-01</th>\n",
       "      <td>39.285917</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-07-01</th>\n",
       "      <td>47.353493</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-10-01</th>\n",
       "      <td>51.378834</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-01</th>\n",
       "      <td>61.323143</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-04-01</th>\n",
       "      <td>41.677205</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-07-01</th>\n",
       "      <td>49.744781</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-01</th>\n",
       "      <td>53.770122</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            $\\hat{y}_t$     $b_t$      $l_t$      $s_t$    $y_t$\n",
       "2005-01-01    44.584128  0.597822  34.297595  10.286532  41.7275\n",
       "2005-04-01    24.938189  0.597822  34.895417  -9.957228  24.0418\n",
       "2005-07-01    33.005765  0.597822  35.493239  -2.487474  32.3281\n",
       "2005-10-01    37.031107  0.597822  36.091061   0.940046  37.3287\n",
       "2006-01-01    46.975416  0.597822  36.688883  10.286532  46.2132\n",
       "2006-04-01    27.329477  0.597822  37.286705  -9.957228  29.3463\n",
       "2006-07-01    35.397053  0.597822  37.884527  -2.487474  36.4829\n",
       "2006-10-01    39.422395  0.597822  38.482349   0.940046  42.9777\n",
       "2007-01-01    49.366704  0.597822  39.080171  10.286532  48.9015\n",
       "2007-04-01    29.720765  0.597822  39.677993  -9.957228  31.1802\n",
       "2007-07-01    37.788341  0.597822  40.275815  -2.487474  37.7179\n",
       "2007-10-01    41.813683  0.597822  40.873637   0.940046  40.4202\n",
       "2008-01-01    51.757991  0.597822  41.471459  10.286532  51.2069\n",
       "2008-04-01    32.112053  0.597822  42.069281  -9.957228  31.8872\n",
       "2008-07-01    40.179629  0.597822  42.667103  -2.487474  40.9783\n",
       "2008-10-01    44.204971  0.597822  43.264925   0.940046  43.7725\n",
       "2009-01-01    54.149279  0.597822  43.862747  10.286532  55.5586\n",
       "2009-04-01    34.503341  0.597822  44.460569  -9.957228  33.8509\n",
       "2009-07-01    42.570917  0.597822  45.058391  -2.487474  42.0764\n",
       "2009-10-01    46.596258  0.597822  45.656213   0.940046  45.6423\n",
       "2010-01-01    56.540567  0.597822  46.254035  10.286532  59.7668\n",
       "2010-04-01    36.894629  0.597822  46.851857  -9.957228  35.1919\n",
       "2010-07-01    44.962205  0.597822  47.449679  -2.487474  44.3197\n",
       "2010-10-01    48.987546  0.597822  48.047501   0.940046  47.9137\n",
       "2011-01-01    58.931855       NaN        NaN        NaN      NaN\n",
       "2011-04-01    39.285917       NaN        NaN        NaN      NaN\n",
       "2011-07-01    47.353493       NaN        NaN        NaN      NaN\n",
       "2011-10-01    51.378834       NaN        NaN        NaN      NaN\n",
       "2012-01-01    61.323143       NaN        NaN        NaN      NaN\n",
       "2012-04-01    41.677205       NaN        NaN        NaN      NaN\n",
       "2012-07-01    49.744781       NaN        NaN        NaN      NaN\n",
       "2012-10-01    53.770122       NaN        NaN        NaN      NaN"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(np.c_[aust, fit1.level, fit1.trend, fit1.season, fit1.fittedvalues],\n",
    "                  columns=[r'$y_t$',r'$l_t$',r'$b_t$',r'$s_t$',r'$\\hat{y}_t$'],index=aust.index)\n",
    "df.append(fit1.forecast(8).rename(r'$\\hat{y}_t$').to_frame(), sort=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-07T12:39:28.574783Z",
     "start_time": "2017-12-07T12:39:28.401234Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>$\\hat{y}_t$</th>\n",
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       "      <th>2005-01-01</th>\n",
       "      <td>43.005390</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>35.016131</td>\n",
       "      <td>1.228159</td>\n",
       "      <td>41.7275</td>\n",
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       "    <tr>\n",
       "      <th>2005-04-01</th>\n",
       "      <td>26.352949</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>35.637067</td>\n",
       "      <td>0.739481</td>\n",
       "      <td>24.0418</td>\n",
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       "    <tr>\n",
       "      <th>2005-07-01</th>\n",
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       "      <td>36.258004</td>\n",
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       "    <tr>\n",
       "      <th>2005-10-01</th>\n",
       "      <td>36.719508</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>36.878940</td>\n",
       "      <td>0.995677</td>\n",
       "      <td>37.3287</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-01-01</th>\n",
       "      <td>46.055825</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>37.499877</td>\n",
       "      <td>1.228159</td>\n",
       "      <td>46.2132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-04-01</th>\n",
       "      <td>28.189633</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>38.120813</td>\n",
       "      <td>0.739481</td>\n",
       "      <td>29.3463</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-07-01</th>\n",
       "      <td>35.564800</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>38.741750</td>\n",
       "      <td>0.917997</td>\n",
       "      <td>36.4829</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-01</th>\n",
       "      <td>39.192516</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>39.362686</td>\n",
       "      <td>0.995677</td>\n",
       "      <td>42.9777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-01-01</th>\n",
       "      <td>49.106261</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>39.983623</td>\n",
       "      <td>1.228159</td>\n",
       "      <td>48.9015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-04-01</th>\n",
       "      <td>30.026317</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>40.604559</td>\n",
       "      <td>0.739481</td>\n",
       "      <td>31.1802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-07-01</th>\n",
       "      <td>37.844870</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>41.225496</td>\n",
       "      <td>0.917997</td>\n",
       "      <td>37.7179</td>\n",
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       "    <tr>\n",
       "      <th>2007-10-01</th>\n",
       "      <td>41.665525</td>\n",
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       "      <td>41.846432</td>\n",
       "      <td>0.995677</td>\n",
       "      <td>40.4202</td>\n",
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       "    <tr>\n",
       "      <th>2008-01-01</th>\n",
       "      <td>52.156697</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>42.467369</td>\n",
       "      <td>1.228159</td>\n",
       "      <td>51.2069</td>\n",
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       "    <tr>\n",
       "      <th>2008-04-01</th>\n",
       "      <td>31.863001</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>43.088305</td>\n",
       "      <td>0.739481</td>\n",
       "      <td>31.8872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-07-01</th>\n",
       "      <td>40.124941</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>43.709242</td>\n",
       "      <td>0.917997</td>\n",
       "      <td>40.9783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-10-01</th>\n",
       "      <td>44.138533</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>44.330178</td>\n",
       "      <td>0.995677</td>\n",
       "      <td>43.7725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-01-01</th>\n",
       "      <td>55.207133</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>44.951115</td>\n",
       "      <td>1.228159</td>\n",
       "      <td>55.5586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-04-01</th>\n",
       "      <td>33.699685</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>45.572051</td>\n",
       "      <td>0.739481</td>\n",
       "      <td>33.8509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-07-01</th>\n",
       "      <td>42.405012</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>46.192988</td>\n",
       "      <td>0.917997</td>\n",
       "      <td>42.0764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-10-01</th>\n",
       "      <td>46.611542</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>46.813924</td>\n",
       "      <td>0.995677</td>\n",
       "      <td>45.6423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>58.257569</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>47.434861</td>\n",
       "      <td>1.228159</td>\n",
       "      <td>59.7668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-04-01</th>\n",
       "      <td>35.536369</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>48.055797</td>\n",
       "      <td>0.739481</td>\n",
       "      <td>35.1919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-07-01</th>\n",
       "      <td>44.685082</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>48.676733</td>\n",
       "      <td>0.917997</td>\n",
       "      <td>44.3197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-10-01</th>\n",
       "      <td>49.084550</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>49.297670</td>\n",
       "      <td>0.995677</td>\n",
       "      <td>47.9137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>61.308005</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-04-01</th>\n",
       "      <td>37.373053</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-07-01</th>\n",
       "      <td>46.965153</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-10-01</th>\n",
       "      <td>51.557558</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-01</th>\n",
       "      <td>64.358440</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-04-01</th>\n",
       "      <td>39.209737</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-07-01</th>\n",
       "      <td>49.245223</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-01</th>\n",
       "      <td>54.030567</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            $\\hat{y}_t$     $b_t$      $l_t$     $s_t$    $y_t$\n",
       "2005-01-01    43.005390  0.620936  35.016131  1.228159  41.7275\n",
       "2005-04-01    26.352949  0.620936  35.637067  0.739481  24.0418\n",
       "2005-07-01    33.284729  0.620936  36.258004  0.917997  32.3281\n",
       "2005-10-01    36.719508  0.620936  36.878940  0.995677  37.3287\n",
       "2006-01-01    46.055825  0.620936  37.499877  1.228159  46.2132\n",
       "2006-04-01    28.189633  0.620936  38.120813  0.739481  29.3463\n",
       "2006-07-01    35.564800  0.620936  38.741750  0.917997  36.4829\n",
       "2006-10-01    39.192516  0.620936  39.362686  0.995677  42.9777\n",
       "2007-01-01    49.106261  0.620936  39.983623  1.228159  48.9015\n",
       "2007-04-01    30.026317  0.620936  40.604559  0.739481  31.1802\n",
       "2007-07-01    37.844870  0.620936  41.225496  0.917997  37.7179\n",
       "2007-10-01    41.665525  0.620936  41.846432  0.995677  40.4202\n",
       "2008-01-01    52.156697  0.620936  42.467369  1.228159  51.2069\n",
       "2008-04-01    31.863001  0.620936  43.088305  0.739481  31.8872\n",
       "2008-07-01    40.124941  0.620936  43.709242  0.917997  40.9783\n",
       "2008-10-01    44.138533  0.620936  44.330178  0.995677  43.7725\n",
       "2009-01-01    55.207133  0.620936  44.951115  1.228159  55.5586\n",
       "2009-04-01    33.699685  0.620936  45.572051  0.739481  33.8509\n",
       "2009-07-01    42.405012  0.620936  46.192988  0.917997  42.0764\n",
       "2009-10-01    46.611542  0.620936  46.813924  0.995677  45.6423\n",
       "2010-01-01    58.257569  0.620936  47.434861  1.228159  59.7668\n",
       "2010-04-01    35.536369  0.620936  48.055797  0.739481  35.1919\n",
       "2010-07-01    44.685082  0.620936  48.676733  0.917997  44.3197\n",
       "2010-10-01    49.084550  0.620936  49.297670  0.995677  47.9137\n",
       "2011-01-01    61.308005       NaN        NaN       NaN      NaN\n",
       "2011-04-01    37.373053       NaN        NaN       NaN      NaN\n",
       "2011-07-01    46.965153       NaN        NaN       NaN      NaN\n",
       "2011-10-01    51.557558       NaN        NaN       NaN      NaN\n",
       "2012-01-01    64.358440       NaN        NaN       NaN      NaN\n",
       "2012-04-01    39.209737       NaN        NaN       NaN      NaN\n",
       "2012-07-01    49.245223       NaN        NaN       NaN      NaN\n",
       "2012-10-01    54.030567       NaN        NaN       NaN      NaN"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(np.c_[aust, fit2.level, fit2.trend, fit2.season, fit2.fittedvalues], \n",
    "                  columns=[r'$y_t$',r'$l_t$',r'$b_t$',r'$s_t$',r'$\\hat{y}_t$'],index=aust.index)\n",
    "df.append(fit2.forecast(8).rename(r'$\\hat{y}_t$').to_frame(), sort=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally lets look at the levels, slopes/trends and seasonal components of the models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-07T12:39:29.636548Z",
     "start_time": "2017-12-07T12:39:28.576279Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "states1 = pd.DataFrame(np.c_[fit1.level, fit1.trend, fit1.season], columns=['level','slope','seasonal'], index=aust.index)\n",
    "states2 = pd.DataFrame(np.c_[fit2.level, fit2.trend, fit2.season], columns=['level','slope','seasonal'], index=aust.index)\n",
    "fig, [[ax1, ax4],[ax2, ax5], [ax3, ax6]] = plt.subplots(3, 2, figsize=(12,8))\n",
    "states1[['level']].plot(ax=ax1)\n",
    "states1[['slope']].plot(ax=ax2)\n",
    "states1[['seasonal']].plot(ax=ax3)\n",
    "states2[['level']].plot(ax=ax4)\n",
    "states2[['slope']].plot(ax=ax5)\n",
    "states2[['seasonal']].plot(ax=ax6)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Simulations and Confidence Intervals\n",
    "\n",
    "By using a state space formulation, we can perform simulations of future values. The mathematical details are described in Hyndman and Athanasopoulos [2] and in the documentation of `HoltWintersResults.simulate`.\n",
    "\n",
    "Similar to the example in [2], we use the model with additive trend, multiplicative seasonality, and multiplicative error. We simulate up to 8 steps into the future, and perform 1000 simulations. As can be seen in the below figure, the simulations match the forecast values quite well.\n",
    "\n",
    "[2] [Hyndman, Rob J., and George Athanasopoulos. Forecasting: principles and practice, 2nd edition. OTexts, 2018.](https://otexts.com/fpp2/ets.html)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fit = ExponentialSmoothing(aust, seasonal_periods=4, trend='add', seasonal='mul', initialization_method=\"estimated\").fit()\n",
    "simulations = fit.simulate(8, repetitions=100, error='mul')\n",
    "\n",
    "ax = aust.plot(figsize=(10,6), marker='o', color='black', \n",
    "               title=\"Forecasts and simulations from Holt-Winters' multiplicative method\" )\n",
    "ax.set_ylabel(\"International visitor night in Australia (millions)\")\n",
    "ax.set_xlabel(\"Year\")\n",
    "fit.fittedvalues.plot(ax=ax, style='--', color='green')\n",
    "simulations.plot(ax=ax, style='-', alpha=0.05, color='grey', legend=False)\n",
    "fit.forecast(8).rename('Holt-Winters (add-mul-seasonal)').plot(ax=ax, style='--', marker='o', color='green', legend=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Simulations can also be started at different points in time, and there are multiple options for choosing the random noise."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fit = ExponentialSmoothing(aust, seasonal_periods=4, trend='add', seasonal='mul', initialization_method=\"estimated\").fit()\n",
    "simulations = fit.simulate(16, anchor='2009-01-01', repetitions=100, error='mul', random_errors='bootstrap')\n",
    "\n",
    "ax = aust.plot(figsize=(10,6), marker='o', color='black', \n",
    "               title=\"Forecasts and simulations from Holt-Winters' multiplicative method\" )\n",
    "ax.set_ylabel(\"International visitor night in Australia (millions)\")\n",
    "ax.set_xlabel(\"Year\")\n",
    "fit.fittedvalues.plot(ax=ax, style='--', color='green')\n",
    "simulations.plot(ax=ax, style='-', alpha=0.05, color='grey', legend=False)\n",
    "fit.forecast(8).rename('Holt-Winters (add-mul-seasonal)').plot(ax=ax, style='--', marker='o', color='green', legend=True)\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "hide_input": false,
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.6"
  },
  "latex_envs": {
   "LaTeX_envs_menu_present": true,
   "autocomplete": true,
   "bibliofile": "biblio.bib",
   "cite_by": "apalike",
   "current_citInitial": 1,
   "eqLabelWithNumbers": true,
   "eqNumInitial": 1,
   "hotkeys": {
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}
