hw9_time_series.ipynb

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   "source": [
    "<center>\n",
    "<img src=\"../../img/ods_stickers.jpg\">\n",
    "## Открытый курс по машинному обучению\n",
    "</center>\n",
    "<center>Автор материала: аналитик-разработчик в команде Яндекс.Метрики Мария Мансурова"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <center> Домашнее задание № 9\n",
    "## <center> Анализ временных рядов"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.0.1\n"
     ]
    },
    {
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       "<script>requirejs.config({paths: { 'plotly': ['https://cdn.plot.ly/plotly-latest.min']},});if(!window.Plotly) {{require(['plotly'],function(plotly) {window.Plotly=plotly;});}}</script>"
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       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import os\n",
    "\n",
    "from plotly import __version__\n",
    "from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot\n",
    "from plotly import graph_objs as go\n",
    "import requests\n",
    "import pandas as pd\n",
    "\n",
    "print(__version__) # need 1.9.0 or greater\n",
    "\n",
    "init_notebook_mode(connected = True)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "def plotly_df(df, title = ''):\n",
    "    data = []\n",
    "    \n",
    "    for column in df.columns:\n",
    "        trace = go.Scatter(\n",
    "            x = df.index,\n",
    "            y = df[column],\n",
    "            mode = 'lines',\n",
    "            name = column\n",
    "        )\n",
    "        data.append(trace)\n",
    "    \n",
    "    layout = dict(title = title)\n",
    "    fig = dict(data = data, layout = layout)\n",
    "    iplot(fig, show_link=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Подготавливаем данные\n",
    "\n",
    "Для начала скачаем данные в `dataframe`. Сегодня будем предсказывать просмотры wiki-страницы [Machine Learning](https://en.wikipedia.org/wiki/Machine_learning). Данные я скачала с помощью библиотеки [Wikipediatrend](https://www.r-bloggers.com/using-wikipediatrend/) для `R`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 231,
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   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>count</th>\n",
       "      <th>lang</th>\n",
       "      <th>page</th>\n",
       "      <th>rank</th>\n",
       "      <th>month</th>\n",
       "      <th>title</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>2015-01-01</td>\n",
       "      <td>1414</td>\n",
       "      <td>en</td>\n",
       "      <td>Machine_learning</td>\n",
       "      <td>8708</td>\n",
       "      <td>201501</td>\n",
       "      <td>Machine_learning</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>2015-01-02</td>\n",
       "      <td>1920</td>\n",
       "      <td>en</td>\n",
       "      <td>Machine_learning</td>\n",
       "      <td>8708</td>\n",
       "      <td>201501</td>\n",
       "      <td>Machine_learning</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>2015-01-03</td>\n",
       "      <td>1338</td>\n",
       "      <td>en</td>\n",
       "      <td>Machine_learning</td>\n",
       "      <td>8708</td>\n",
       "      <td>201501</td>\n",
       "      <td>Machine_learning</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>2015-01-04</td>\n",
       "      <td>1404</td>\n",
       "      <td>en</td>\n",
       "      <td>Machine_learning</td>\n",
       "      <td>8708</td>\n",
       "      <td>201501</td>\n",
       "      <td>Machine_learning</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>2015-01-05</td>\n",
       "      <td>2264</td>\n",
       "      <td>en</td>\n",
       "      <td>Machine_learning</td>\n",
       "      <td>8708</td>\n",
       "      <td>201501</td>\n",
       "      <td>Machine_learning</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          date  count lang              page  rank   month             title\n",
       "81  2015-01-01   1414   en  Machine_learning  8708  201501  Machine_learning\n",
       "80  2015-01-02   1920   en  Machine_learning  8708  201501  Machine_learning\n",
       "79  2015-01-03   1338   en  Machine_learning  8708  201501  Machine_learning\n",
       "78  2015-01-04   1404   en  Machine_learning  8708  201501  Machine_learning\n",
       "77  2015-01-05   2264   en  Machine_learning  8708  201501  Machine_learning"
      ]
     },
     "execution_count": 231,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('../../data/wiki_machine_learning.csv', sep = ' ')\n",
    "df = df[df['count'] != 0]\n",
    "df.head()"
   ]
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    "df.shape"
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   "outputs": [],
   "source": [
    "df.date = pd.to_datetime(df.date)"
   ]
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotly_df(df.set_index('date')[['count']])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Предсказание с помощью Facebook Prophet\n",
    "\n",
    "Для начала построим предсказание с помощью простой библиотеки `Facebook Prophet`. Для того, чтобы посмотреть на качество модели, отбросим из обучающей выборки последние 30 дней."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from fbprophet import Prophet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "predictions = 30\n",
    "\n",
    "df = df[['date', 'count']]\n",
    "df.columns = ['ds', 'y']\n",
    "train_df = df[:-predictions].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<fbprophet.forecaster.Prophet at 0x7f3e3df100f0>"
      ]
     },
     "execution_count": 177,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = Prophet(yearly_seasonality=True)\n",
    "model.fit(train_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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      "text/plain": [
       "            ds\n",
       "378 2016-01-16\n",
       "379 2016-01-17\n",
       "380 2016-01-18\n",
       "381 2016-01-19\n",
       "382 2016-01-20"
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   ],
   "source": [
    "future = model.make_future_dataframe(periods=30)\n",
    "future.tail()"
   ]
  },
  {
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       "      <td>452.523426</td>\n",
       "      <td>452.523426</td>\n",
       "      <td>874.202169</td>\n",
       "      <td>3832.966614</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            ds         t        trend  seasonal_lower  seasonal_upper  \\\n",
       "378 2016-01-16  1.073446  2946.748331     -461.131891     -461.131891   \n",
       "379 2016-01-17  1.076271  2949.752360     -303.591130     -303.591130   \n",
       "380 2016-01-18  1.079096  2952.756388      713.816039      713.816039   \n",
       "381 2016-01-19  1.081921  2955.760417      981.307220      981.307220   \n",
       "382 2016-01-20  1.084746  2958.764445      874.202169      874.202169   \n",
       "\n",
       "     trend_lower  trend_upper   yhat_lower   yhat_upper      weekly  \\\n",
       "378  2946.748225  2946.748431  2096.804564  2866.325469 -860.441386   \n",
       "379  2949.752245  2949.752464  2293.459619  3017.393579 -720.143785   \n",
       "380  2952.756265  2952.756500  3292.709948  4006.462444  282.577995   \n",
       "381  2955.760287  2955.760535  3554.316647  4292.870481  538.054284   \n",
       "382  2958.764307  2958.764569  3464.272100  4196.759023  421.678742   \n",
       "\n",
       "     weekly_lower  weekly_upper      yearly  yearly_lower  yearly_upper  \\\n",
       "378   -860.441386   -860.441386  399.309494    399.309494    399.309494   \n",
       "379   -720.143785   -720.143785  416.552654    416.552654    416.552654   \n",
       "380    282.577995    282.577995  431.238044    431.238044    431.238044   \n",
       "381    538.054284    538.054284  443.252936    443.252936    443.252936   \n",
       "382    421.678742    421.678742  452.523426    452.523426    452.523426   \n",
       "\n",
       "       seasonal         yhat  \n",
       "378 -461.131891  2485.616440  \n",
       "379 -303.591130  2646.161230  \n",
       "380  713.816039  3666.572427  \n",
       "381  981.307220  3937.067637  \n",
       "382  874.202169  3832.966614  "
      ]
     },
     "execution_count": 179,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "forecast = model.predict(future)\n",
    "forecast.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "382    3833.0\n",
       "Name: yhat, dtype: float64"
      ]
     },
     "execution_count": 180,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "round(forecast['yhat'][-1:])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Вопрос 1:** Какое предсказание числа просмотров wiki-страницы на 20 января? Ответ округлите до целого числа.\n",
    "\n",
    "Оценим качество предсказания по последним 30 точкам."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MAPE 38.3882717622\n",
      "MAE 713.01104297\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "cmp_df = forecast.set_index('ds')[['yhat', 'yhat_lower', 'yhat_upper']].join(df.set_index('ds'))\n",
    "cmp_df['e'] = cmp_df['y'] - cmp_df['yhat']\n",
    "cmp_df['p'] = 100*cmp_df['e']/cmp_df['y']\n",
    "print('MAPE', np.mean(abs(cmp_df[-predictions:]['p'])))\n",
    "print('MAE', np.mean(abs(cmp_df[-predictions:]['e'])))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Вопрос 2**: Какое получилось MAPE?\n",
    "\n",
    "**Вопрос 3**: Какое получилось MAE?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Предсказываем с помощью ARIMA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy import stats\n",
    "import statsmodels.api as sm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 239,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "           ds     y\n",
      "81 2015-01-01  1414\n",
      "80 2015-01-02  1920\n",
      "79 2015-01-03  1338\n",
      "78 2015-01-04  1404\n",
      "77 2015-01-05  2264\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f3e3d364780>"
      ]
     },
     "execution_count": 239,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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llFUAPxLy/e8B8J5uHxdR2tlt+0kdZigBAKbVWAWks8w2UmvmVuP5IiKigbBaMQE0VgRS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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3e3d5490f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(train_df.head())\n",
    "train_df.index = train_df['ds']\n",
    "train_df['y'].plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Вопрос 4:** Проверим стационарность ряда с помощью критерия Дики-Фулера. Является ли ряд стационарным? Какое значение p-value?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Критерий Дики-Фуллера: p=0.107392\n"
     ]
    }
   ],
   "source": [
    "print(\"Критерий Дики-Фуллера: p=%f\" % sm.tsa.stattools.adfuller(train_df['y'])[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 247,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Критерий Дики-Фуллера: p=0.000000\n"
     ]
    }
   ],
   "source": [
    "train_df['y'] = train_df['y'] - train_df['y'].shift(7)\n",
    "print(\"Критерий Дики-Фуллера: p=%f\" % sm.tsa.stattools.adfuller(train_df['y'][7:])[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 248,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f3e3d1e6dd8>"
      ]
     },
     "execution_count": 248,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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CZ5+8gOWivtk3pasZTs9txA1uN/kGdYhcyUBUkRFRRFkyM5GrEfePqsiQJWZuu0G2oAEA\nJpeKm3xLiKibFVmWTCHA4JY27MzMCv7wK0fxnRcmN/umdDXDtKDIEmRmbisUNMPNQkY4UGpN7kop\nRUJElt0yZQqvTME+WJzKFDb5lhBRNyvqdqUUg1vqZAxuacMyTtaAmdtgieCWmdtK+ZKBRNTuH40o\nklt2S/WJQ5GIbGe6eUgSfuI5eJLBLREFyB0oxQsQ6mAMbmnDsk7WYKXIAQNB0k0LiiRBlpi59cpr\nBpLRCADYA6WYiVyVyNSK4WTM3IZflplbIgqYZVnlVUAarz+oczG4pQ1bdoNbZm6DZJoWFKWcuWX5\nrS1XMtzJvxwotTYR/EcUGaois+e2C4ie22xBR67E52Ei8p9mWBBLGpi5pU7G4JY2TFxYrfCiKlBu\n5pZ7bisUNAMJ0XOrcBXQWkTZdkSxM7cs4w6/TL783Du5xOwtEfnPG9Cy55Y6GYNb2jDRa5tjWXKg\nDKu655ZBHGCXJYueW0Vm5nYtuqcsWWUZd1cQB4wAMJXhxGQi8p83oGVwS52MwS1tmJjUuczMbaAM\nww5u3T23FoMSwC5LTqh2z60qSwz616B7BkopzHR3BdFzC7DvloiCISYlA0CRh8jUwXwJbiVJ+rgk\nSdOSJD3veduwJEnflSTplPPnkPN2SZKkj0iSdFqSpCOSJL3M8znvcD7+lCRJ7/DjtlHwRM9tjj23\ngbIzt3I5uGXGDYBTluydlsz7ZVUimI0oElSuTuoKmYKG0b4oAE5MJqJgMHNLYeFX5vaTAN5Y9bY/\nAPCQZVnXAHjI+X8AuBvANc5/vw7gY4AdDAP4AIDbAbwCwAdEQEydze25ZVlyoOxVQIAiMXPrlS+V\ne25VRYbGHtJV6VXTknWewIdetqBj20AcfbEIe26JKBAMbiksfAluLct6FMB81ZvvAfAp5++fAvAW\nz9v/1bI9AWBQkqTtAN4A4LuWZc1blrUA4LuoDZipA4meWw6UCpYd3MqQZQmSxJ5bIVfSuQqoBSJT\nqyoyIgozt90gW9DQH1Mxlo5hOsvgloj8V/QEtN4SZaJOE2TP7ZhlWVecv08CGHP+vhPARc/HTThv\na/R26nCi3ytX4pNdkAzTcodJKRJ7S4WCZrqrgDhQam0iUyuGkzFzG36ZvI50IoKxdJyZWyIKRJGZ\nWwqJtgyUsizLAuDblbgkSb8uSdJBSZIOzszM+PVlaZ2yTuZ2mT23gTKcVUCAHZgwuLUDtZJhIuHu\nueX9shbN03PL1UndIVvQ0B9XsS0d57RkIgoEy5IpLIIMbqeccmM4f047b78EYLfn43Y5b2v09hqW\nZf2TZVm3WZZ125YtW3y/4dQa0XPLgVLBssuSGdx6FZwX2ERU7Lllme1aDCdTq8oyy7i7RKagoz8e\nwdhAHNPZAkz+DhCRz7ylyCVW/FAHCzK4/RoAMfH4HQDu87z97c7U5DsALDnly98GcJckSUPOIKm7\nnLdRh3OnJWsGL6oCJPbcAnZwyyDO7rcFgES0vAqIZcmrE48bRZEQkWUekoScYVpYLupIO5lbzbAw\nnytt9s0ioi7DzC2FRcSPLyJJ0ucA/CSAUUmSJmBPPf4QgC9KkvQuAOcB/JLz4d8A8DMATgPIAfg1\nALAsa16SpA8CeNr5uD+1LKt6SFUg5pbtMq6Rvlg7vl3XyRZ0SBJgWUBeM5CK+fKwoip6VebW5LRk\nFEpO5lblKqBmac79o8oyIoqEAgeDhJpoB+mPRzCWtl/DJpcKGOXrGRH5yJutZXBLncyXKMSyrF9p\n8K7X1flYC8B7GnydjwP4uB+3qRVv/diP8NLdg/jbX7613d869HTDRF4zsLU/hulsESslncFtQExP\ncBth5haAfZgCeINbGTpXAa3KMCsHSjFzG26ZvN0Wko6rGEvHAQBTmQJu3jmwmTeLiLpMUbNfOyKy\nhCIrpKiDtWWgVKfrj0fc0lpqjcgabBuwL6py3HUbGG/mVpYkloDDW5bs9Nwy6F+Tm7lVJGe6NO+v\nMBPT6tOJiPs8zKFSROQ3kbntj0fcQJeoEzG4BdAXi7gTf6k14sJqa799UcWJycExPdOSGcTZ8iWR\nuRV7bmWWJa9BDCaTJMmZLs2LlDATA/364yq29MUgScBkhuuAiMhfohS5Lx7hQCnqaAxuAfTFVDdI\no9aI+23bgN3fxV23wdFNE4riZG5lZm4BYNEpyRxMqgDsbCQHSq1OM83KwWQ8DAi1TKHccxtRZIz2\nxTDFXbdE5DMxLbk/pqLEWQ3UwRjcwilLLmqbfTNCyS1Ldnq9Vko8JAiKaYGZ2yrzK/ZU2OFUFAC4\nt7UJumFBZe921xCZ23TcPuDZlo4zc0tEvqvI3HKgFHUwBrdgz+1GiAsrMchkhWXJgdFNExG5nLk1\nOC0Zi87KE5G5FattLN43DXn3JUcUGToz3aGW9WRuAfu5eIrBLRH5rKSbkCS7lY9lydTJGNzC/kVd\nLuq8IF4HDpRqH8OwIHsybkaPlJN+7fBl/PDUbN33za9oSEUVxCLOtGTn/mE2sjHNMKEqHMDVLcS0\n5H4nczuWjjG4JSLfFXUTUUVGVJGZuaWOxuAWdomFZlgo8pe1ZaLfS5Qlc6BUcAzLKmdupd7J3P7l\nt0/g44+dq/u+hVwJQ05JMmBnIgGwj3QVumEhoojMLYPbsMsWdcRVGdGI/djf2h/HQk5j7zkR+aqo\nm4hG7OcaBrfUyRjcAuh39rJyqFTrRFnyVie4zbHnNjCG6cncKr2xn9SyLExniu7jrNr8SsnttwXs\ngVKAPTSJ6tNNCxFZZG5Zlhx22YLmZm0BYKTP/n0Q/ehERH4oGSZiEQXRiMxkEHU0BrewM7cAs47r\nsVzQEZElpOMRqIqEFU5LDoxhljO3itQbwW2moKOomw0PnhZzJQwmPZlbUZbMzG1DummWM7dybzyO\nulkmr7v9tgAw2mdPrp9d5q5b6j2Pn5nD6enlzb4ZXamomYgxc0shwOAW9lhzABwqtQ7Zgo6+eASS\nJCEVi3CgVIB004IslVe49EJQMpO1ewcbBbfzuRKGk+WsVbksmS+8jejeQxJFgtYDj6Nulilo7qRk\nABh1Mrdzy8zcUu/5g3uP4KMPn9rsm9GVSoZdlhxjcEsdjsEtypnbLNcBtWy5WM4apKIRrHCgVGBM\nT1AipgJ3u+mMnX3KNChLXljRKntuZVGW3P33zXrphumWJas98jjqZtlCZeZ2xMnczq0wc0u9J1vQ\n3f3n5K+SbriZ2yIPkKmDMbiFPS0ZYM/temQLGvqczHcyqrDnNkC6Z4WLLKMngpLprH2BvlzUYVb9\ne0u6ieWijuFk7UCpXpkkvR7egVKiAoCT4sOrOnM7wswt9bBcSe+pKrylvIaPff9MWwbIiYFSMWda\nMl83qFMxuEV5P2AvPSH6xZs1SDkrlSgYpuXZTyrLPTEtedopS7YsIKdVVgW4O245UKol3rJkcX9x\nYnJ4ZQs60oly5rY/FkFUkTHDnlvqMYZpoaA1ntHQjb5/chof/tYJPHJyJvDvVRKrgJzJ7BoPkWmd\nirqBrxyaCOyAhMEtyvsBGZi1LlvQ3WnTqZiCHAdKBaYyc9sbK1ymMuUL9OqJyfNOcFuRuZW5Cmgt\n9kAp+35SeH+Fxr/88Bx+6/OHat5ePS1ZkiSM9EWZuaWek3cOQBtN1+9G4prroRNTgX+vkm4i5lk7\nVmJpMq3T90/O4Le/cBgnJrOBfH0Gt7CDMoDB7Xp4e26TUQ6UCoppWrAseDK3Uk2ZbjcSZclAbduA\nWHUylPIOlHIyt3zRbUgz6mVueX91us88eR7fPDpZ0Y5Q0k0UNNM9YBRG+2KYY+aWeoxoi+qlzK24\n5nro+HTg1wRFkbl1DkeLGpMZtD7idzSoVkYGt4C7t6vR0BpqLFvQ3IFcfbEIVthzGwhRgqw405Jl\nqTcyt9OZgvv36tP4xZz9/0PJ2rLkXrhv1sswK3tuAWZuO93EQg5nZ1ZQMkxM1vmdSCfUio8f6Yti\njntuqcfknSzmcql2RkO3Ev/m6WwRL1zOBPq9Sk7PbTRiJ4SYuaX1yjuxQlD7khncOvpjEfbctsiy\nLCdz6xkoxWnJgRDZGkXprcztTLaIHQNxAPbOWy+RuR329NyKMluDmciGvNOS3dVJPfBYCrMfnpp1\n/35+bsX9uzj99k5LBoCRVIxlydRzRImuZaFnDtpXSgZkCZAk4MHjwZYmlwwTsYiCmChL5jogWqcV\n53eVwW3A+uMchtSqom5CMyx32jQHSgXHDW49e257oZR0OlvEVVv7ANQOfFtwgttBz55bVawCYiay\nId203Ay3KE/uhcdSmP3g1CwSqp0tOT+Xc98uqo28PbeAvet2ZrnIaabUU7wzP3qlNDlfshMML9sz\nFHjfbVEznMwtg1vaGPG7WtQY3AaqL87MbavEi0fas+e2qJvQWariO7csWS4Ht92ebMuVdCwXdVy1\nxQ5ua3pucyX0xSKIOSVSgCcTyeC2Id2wKnq3xduoMxmmhR+ensXdt2yDqkgVwW31c7Aw0hd1V2UR\n9Yq8J7jtlcd+rmQgFVXwU9dvxfOXMphcKqz9SetUMsyK4DaorBt1v3JZcjDVngxuHX2xSM+c9PlF\n9Hv1xcvTkoHalS20cWJva0TunczttDMp+aotKQD1e269WVvAM1Cqy++bjdA805Ij7FHueEcvLWEp\nr+Enr9uK3UNJXJj3liXXz9yOpGIAuOuWeot3OE2vTEzOlQwkogpef8MYAODhE9OBfa+ibiIW4bRk\n2rgcy5Lboy+mItsjJ31+ESej/TH7wirllCdzYrL/6mZuu/x1RUxK3jOSgizVn5bs7bcFAJWrbdZk\nePbcRtij3PF+8OIMJAm48+pR7BlJYnzWU5acr99zO9rvBLcrnJhMvSPvOVivntHQrXIlHcloBNeO\n9WHnYAKPnZ5d+5PWqegMlIopLEumjckzuG0Pu+e2N076/CKCjT53FZCduV3hUCnfuT23TjCiSD2Q\nuc3a5VVj6ZhTWVH5+7mQK1VMSgbKwT+DtcZ0wyoPlGKPcsd79NQMbt4xgOFUFHuHk7gwn3N7aTON\npiU7hz6zzNxSD/Fee/RKm1muZCAZVSBJEvYMJzGVCaYs2bIse8+t0ntlyT84NdO1lQBfOTSB99bZ\nnx40MfAtqHVSDG4d/ey5bVn1pM5U1P4zqL1Vvawc3Nr/rygSur0iaMopSx7rj6M/XltZUTdzqzBY\nW4tmmOWBUorI3PL+6kTZgoZnLyzi1deMAgD2jqSwXNTdSeEiO9VXZ88twLJk6i2VZcm9cR0iglsA\nGO6Lus8NfhMlyDFVcedc9ELmNlvQ8PaPP4UvHZzY7JsSiAePTeObz0+2/fuyLLlNRM8tp0s2z+33\nqipL7pVBDu1UL3Pb7dnJ6WwBUUXGYFJFf7y2J75+z61YbdPd981GGGbtQCktJCcln33yAv7/b5/c\n7JvRNs+cX4BhWvjxq0RwmwQAjDtDpTJ5DX2xiPvzFIbdzC3Lkql35CumJXdnpq2aKEsG7IqNoPZb\ni0A2qvTWtOS8ZsCyurfFY2Ihh6JuBjbYqRGWJbdJXzwC3bR6pszCD27PbfVAKZYl+06vztzKUtdn\n22YyRWzpj0GSJKTjasXFSlE3sFzUMVxVlswy27XZmdvKgVJheSx9+4VJfO3w5c2+GW3zzPkFyBLw\n0j2DAMrBrRgq9fT4PK7b1l/zedGIjHQ8gjkGt9RDcpqBiCxBlnrnkD3vzdymoljKa4EcVrrBbcVA\nqe6/1hPXEkv57jwsubSYB9D+Sody5pZlyYHqd7KOvVLK4ofanltnoBTLkn1Xk7ntgeB2OmsHtwBq\nMreLOfuFZqimLJkDpdbizdwqITsMyBQ0t8+0FxwcX8AN29Nu2fGuoSQkCRifzeHSYh4vXM7gp28c\nq/u5o30xzAaUxSHqRCLQ66XtFytVwS1Qfn30k0j8xHpsz63m/BuDuE83W75kuHMZ2h/cip5bZm4D\nJVYp9Mppnx+WizriquwGFH3utOTuP81rNze4lcrlpEaXl9BPZwvY6gS3fVXB7ULOfkKuHihVXm3T\n/S+666WZlns/qSHruc0W9J5pH9EME89dXMRte4fct8VVBdvTcVyYz+HBY1MAsGpwy8wt9RJRotsf\nV3vmECzn8zpJAAAgAElEQVRfMpB0rr1EcBtE321F5rbDpyX7+fogsuDdmLkVWVvAbnFpJ/bctkmf\nm7ntvgdwULIFDX2xcs9jUpQlM3Pru3Lm1g5K5B7J3G5NlzO33oMn8eI9lKrquXXuH2ZuG9MN012Z\n5GZuQ3IYkMlrMEzLfWHsZsevZJDXDNy2b7ji7XtHUjg/t4LvHpvCgS0pXLWlr+7nj/RFOVCKeooY\nrtQrA0I1w0TJMJFUKzO3QfSHioFS3rLkIAITy7LwyIsz+PvvnV5XkHp6ehk3vP9bOD297MvtEf/u\ndgd/7TCx4Fkr1+bYJx9wWXJk7Q/pDaK0theeEP2SLegV+xXFEywzt/6rDm4jXR7cFnUDizkNW/vj\nAOzKimxBg2VZkCQJCyv2E3H1tGQOlFqdaVowrfLjSAS5RkgOA8QLcKaguQPsutXB8QUAwG37hire\nvnckiQeOXEFeM/CuV+9v+PkjfVE8cZaZW+od+ZKBRFRBMqr0RFmyOORLOGXJIyn7MDiIzK0oH41F\nFMQCCm4fOz2LP3vgOI5dyQAA7r55Gw40OLxr5NkLCyhoJi7Mr+Dqra19bj3d3HPrzdy28/fFsizk\nnBVAQWX/mbl1uJlbliU3raCZiDsBLWAHFnFVZs9tAEQJsshMypIE0/K3/KaTzGTti/Ktnp5bzSgP\nfJt3ypI5UKo1YjCZWAUkgtwwHAYUdQMFTZyid/9zzDMXFrBzMIHtA4mKt+8ZSSJb1KGbFu5qUJIM\n2Be6CzkNekgmYRNtVM7bc1vsvmCkmsh+iYM+Ucm0EERZsjM8Ksiy5N/70mEs5TX8u9t2A1hfm+DZ\nGXvYXsGnXs5uLkueWNicsuSSYbrJGZYlBywtem574LTPLyXDdMtThFQ0ghUeEPhOrP2Rq1a4dGv2\ndtoJbsfS5cwtUM7cLTov3oNJDpRqhQhiRYZbdXuUO//+8p4sd3s/nWVZeGZ8AS/fO1Tzvn0jKQDA\naF8UL91d+35htM/pv8uxNJnaa6Wo42f/7gd45vx8W79vrqQj4fTc9sK1nEgkiIFSYgZFEOuAip5V\nQLIsQVUkt2TXD5ZlYSZbxD0v3YG3vmwngPVlE8/O2OXIBc2fCkIxUGopr8EMwetkKyYW8hhxqt/a\nmbn1blRhcBswUZbMntvmlXQDMaXyIZSMKQxuAyBeQyKenlsgHEHJekxnCgDgTktOxyunmc/nSuiL\nRWoOVxRZgiSFIxO5GcTjJVI1LTkMhwEVwW0XnqJ7XVrMYzJTqClJBoA9w/Y6oNddP1az39ZrtM/+\n3WHfLbXbxYUcnr+UwacfP9/W75srGUg5Pbe9UJYsMrcJp4JOVWQMJNRgypLFtGTVfs2NKrKvmdtl\npxplMKl6rsfXEdzO2pnbvE/BrQjgTQtYDnlV4mefvIDf/eJh9/8vLeRw7Vg/ZKm9B8Y5z8+m6NPP\nqRqDW4fY0cppyc0r6Q0ytz0w7KXdRLAmS5WZW7NLy5KPXlqCIks4sMXOUvVVrepaWCnVDJMSIrLU\ntUH/RokgNuJWAIge5c6/v7wBbbdnbp85b/fb1svcXjPWh9ffMIa3vXLvql9jhMEtbZIlZ23Kg8en\nfcugNSPn9NxWT9fvVrmqsmQAGElFA8ncljyZW8AuT/YzuBWrdgaTUfTH1re9RDdMnJ/zuyy5/Nq4\nFPJ1QI++OIN7D01g0anmmVjIY9dQwp4u3sYD47znkICZ24DFIgqiEZk9ty0o1gtuYxFOSw6ASERG\nanolOz8oWY+nxxdw8460uzu5v6ptYCGn1fTbChFZZp9hA+KQRHEuUNzVSSG4v7wBbbdfuD5zfgF9\nsQiu35aueV8souB/vOM23LxzYNWvMdIX3ORUotVknN/P5aKOR1+cadv3zWt2z206rqJkmIFNYu0U\noixZDJQC7N3v8wEcaJU8e26BAIPbhOoZ8NpawDWxkHeD0VYOVU5MZvC9k9N136d5XhvD3ne7kCvB\nsuxhhUXdwHS2iF1DybZXOohDGUWWGNy2Q7pHxsf7paSb7imekIwqWOa0ZN9VZ25FcNttPSCA/bg6\nfHERL99bXoHSX9U2MJUpuJmpahFF6pmBUq1mRUTmVq3q3Q7DIYl3iFS3lyVfmM/hwJbUqmXHaxl1\nJqeK4WxE7SKCgIgs4YGjV9r2fct7btdf1homoiw56Qluh1NRdw+8n9yy5Ij9vaIR2dee28W8WO8X\nranUatbZ2fL6n1bKXT/2/TP4w3uP1n2fN7gN++uOOEB4enwelxft1q9dQwmk27wXWmxUGUyogR1A\nMbj16Iv1RimLX+oNlOqLRZBj9tt3ptWgVzIEQUmrXri8hKJuVvQbei9WDNPC2dnGY/5VRe76ntuj\nE0t496eexvXv+xaOTCw2/XluWbKbuXVWAYXgceSdh5Dp8ufpxZxWMyytVelEBLGIjCmnf52oXUQQ\n8PobxvDgsam2lCabpoWCZiKhKusOjsJGzDdJRdtYluxc88Uiiq+ByYIncxuNyIhF5JbLksWkZElq\nred2Iae5gV81b3Z6MeTBrTj0ePLcPC45k5J3DiXQH4+09TU1r9nfazCpuium/Mbg1qMvHmHPbQtK\nuumWqAhJTksOhAhKFLn7M7fufs+93uC2PC35wnwOJd1sGNxGZCkUA5LW6x++fxpv/ugP8YNTswCA\n83O5NT6jzJ2WXPU40kJUlpyKKqE/QV/LYq6EwUT9nvJmSZKEnYMJ94SeqF1E5vbfvWI3VkoGHmlD\nabIIZpJRpaaNpVuJf3OiOnO7UvJ9TWBJL68CAvwfKLWUq9yA0B+PtNwmeGZmBUNJFYMJtaWe26W8\nhrxm1P33VPTchvh1x7IsLOY0KLKE5y8t4cWpLAAnc5tob8+tKEseSkZZltwOfTGWJbei3kCp9Twh\n0dpE5tYNbqXuzdwePD+PPcNJbHXWAAGVA6VOOU/K16wW3Hbh/SI8dHwaN25P42u/cScAtNTj7k5L\ndnptxSqgMGRuM3kdsgRsG4h3/UCpxbyGoeTGglvAPpWfWMyv/YFEPlrKa+iPRXDn1aMYTKr4RhtK\nk3Mlb3DbG9sv3IFSnsztcCoK3bR83wVerNNz62dgIjK3A86h3nqux8/OLOPAlj7EVaWlagER2NUL\nXkue7HSYg9tcyUDJMPGKfcPQTQv3H7kMRZawLR1HOq5uSs/tYDLKsuR26IupDMxa0Ci4XS7qvp8a\nrsfEQg6/84XnuiKTLIKS6sxtGIKSVliWhWfOL1RkbQH735uKKlgu6jg1bffVNMzcKt09UCqT17B3\nJImxtN1T2UqPu8jQiinJYSpvzxQ0pBMqBhKq7xduncQwLSzlNQxssCwZAHYMJNzyM6J2Eb+rqiLj\ntddtxY/OzAX+Pd21ONGIexjabe0LF+Zy+C/3HnWfx3NFHZIExNXyddhwKpj91tVlyUEMlPKu91tP\nJeXZ2RUcGE0hriotlSWL6cH1Dk27JXMrSpJfd8NWyBJw6MIitqXjiCiyU5bczmnJInOrMnPbDul4\nBMvF8D54263YoOfWstAR64D++dGzuPfQJTw93t5F8kEweiS4HZ/LYXa5hNv2Dde8rz+uIlvQcGoq\nix0Dcbf0rFpEkaB12f3ilSloSMdVd5J0Kz3uRtWeW1WsAgpBGXe2oKM/HkE6oXZ1RiaT12BZ8C1z\nO7tcbOs6FqJM3g5uAWDHYBzzAZTJVhOTg8W0ZKD7Vjs+fGIKn3vqAs45u1xzJQMJVYEklQfPucGt\nz1PSS4YJSSq/dsT8HiiVK7lZW0DMwGn+eT5b0DCTLXoyt83dNsuy3EOQuplb59/YF4uEOrgVPcW7\nh5O4cYc9hX/XUAIAkE6oWC7qbWtzE7+rQ6koSroZyHMDg1uPXtmN5gfLsuyeW6U6c9sZvS65ko57\nn70EADg1tbzGR3c+N7itmpZsdECG3E8HnYMI7zApQYyrPzW9jKvH+ht+DbXLVwFl8jrSCfuEO6rI\nLS2W14zKsmRZliBJCMUArkzeDur742rXZWS8xNCSIR8ytzsH7YuXK0vsu6X2yeR1DCTsw7ehZBSG\naQX+O9sLZcnzzqAosbs6pxnuIacwkgpmv3XRmbEiAmm/e24X8xoGPQd6/S2WyophUge2pBBX5abL\nXZeLunt9VS94FVny0b5oqPfcisztUDKKV+wbAWAffgJ2Ys+y0NK1xEbkSwYkqVyC7uchicDg1kPU\n+HdCSW2nEw/Gmsxth7yo3H/4MrJFHRFZwkmnRzPMeiVze3B8AQMJFVdvqS057o/bJ6enp5cb9tsC\nduAWhkzkepR0E3nNcF8UUjEFuRbKksuZ2/LvrSrL4SlLjqtIxyNdPVBKXIQM+JS5BcDSZGqrJecg\nCigf0iwEMMHXq7wWJ+K5DumuQ7BZEdw6WdlcUa9YAwQAQyn7fp/3+f6uXv0YU/0NbhdypYoDvf5Y\na2XJYg3QVVtSiEea77n1BrT1Xlc0w4QiSxhKRUOduRU9zUNJFa/YbycPdg0lAcD9XW3X62quZCCp\nKm7/dhClyQxuPfriEeimFVgNeDcpVe08E9wT000uB/rMkxdw7Vgfbj8w7E6FC7Pq4NbdT9pFQdxT\n5+bxnWOTuG3vEOQ6+z374ypOTGZR1E1cO7ZacBuOYG09RF+MKPlLRiNuiU8zREZbZG4B+zEVhky3\nyFinE/ZOvm49hFz0nLBvlMjcXlpsfqI20UYt5TX3AC6oHtBqOU9ZsqrIiKutr5LpdPPLVZnbklET\n3LqZW5+D26JuIuq53osq/g6UWsppFQd6rfbcnp1ZgSJL2DOcQiLafM/t2sGthagiYyChhjq4XfRM\no759/whGUlHcunsQANq+FzpXMpCIRhBT7cdTEOuAGNx6iJLabjvtC0L1cAGhvwP2yx2dWMKRiSX8\n+9v34rqxNE5NLYd+ZY5e1SspO6VBZhdc4Bumhf/2nZP45X96HOmEit9/43V1P64/HnFPo6/e2rgs\n2Z6W3PnB2nqIF19x0pqKKS0NTBO9yKonuI0o4ZgunS1o6I+rSMdVaIbV0qqHMFn07HvcqG0DccgS\nM7fUXplCObgdcoLbxYCD2+q1OGJGQzcRGVsRuNYLbhNRBQlV8T1TXtSNitWPvg+UqpoQb/fcNl9J\neXZmBbuHEohG7IONZl8fvKXG9aclm1AVKfTB7cKK87qSVDGUiuKZ9/00Xnv9VgDlw/J2ZW7zJbvi\noJy59X8mBINbj353wt7aP+BumMC7EY3Kkjuh5/azT51HXJXxllt34tqxPuQ1AxMhv7irXgUkMm9h\nCErW8s3nr+AjD5/GW27diQf+31fj+m3puh8nTheBxpOSATu41booo+0lXlzLZckRt9esGYYT9Cue\nsuSw7AXOFHS7LDnR/PN0GJXLxzaeuVUVGWPpuO/rgF64vIRXfehhTGea7+X99OPj+OjDp3y9HdR5\nNMNErmS4F8zDSTHgKNjfV2/PLWBfz/nd5/vtFyZ9DehaNef23DplySW9pucWsLPlQZQl1wS3PlX8\nmKbl7Pb2lCXHVRhm84eYV5bybhvGesuSG/XcRiPhz9wu5Eroj0WgKrVhn1uW3Kbr9hXnUIZlyW0i\nLpifGV9Y9eP+5xPncfMffxtHJ5bacbM6kpu5VTqr57aoG/j64St40y07MJBQce02O8MX9r5bEXyU\ne27t+70bem4vOxfef3rPze4Kh3rEwclYOlYxVbGa2sWrgMSLjwjwUtHWSrfcgVKyN3Pb+WXcumFi\nuWiXJZcrbMJ7obGapVwJslR5mLMROwcT7u+YX548O49Li3kcurjY9Od85dAlfOXQJV9vB3We6gM4\n0QMadM+tG9yq9u9Nf7z1PamrOT29jP/w6WfwnWOTvn3NVoly5PlVMrcAMNIX9b0suXr1Y1RRfAv0\ns0UdpoWKgVLutWSTG0zymomE87OPtTAtWTxeZQl1V8xphgnVKUvOFLTQVgEu5koYTNW/bmr3ALa8\nG9yyLLktbtqRxq6hBB5YZeH4Vw5N4H33PQ/Lsk+ve1XDsmTnl2Szel0eOz2LbFHHz/7YdgBwBw+F\nve+2OnMrpiZ3Q3CbyeuQJSBV50XaS1RWXLvKpGQgPGW261GvLHldA6W8Zckh6LkVzydioBQALHXp\nrtuFnF3SWa/vfD12DiVwyefgdnzOnkx6err5SfRTmaKblabulakKbvtiEaiKFHjPbd7puQ2qLHkp\nX9nv2m6aYbqB2Go9t4Bd9eF35rZYL3PrU3Dr7QcVxOt9swcURc1wf/YJtfXM7faBRIPMreUGt5YV\n3rbFhZzWsBqo3WXJouIgprIsuS0kScKbbtmOx07P1h35/eCxKfzel47gjv0jiMgSzs/37pCOYoPg\nNhXd3OXp3zw6if54BD9+tT3qvD+uYudgou3B7aELC+6ACz/oXTwtOVOwdyJ6d/XVIw5OVitJBuxJ\nwN1allw9UCrV4kApsdbAOy05okgd/zgSFxRizy3QzWXJJV9KkoWdgwlcWSz4+jMen7Nf+840Gdya\npoXpbAGLuVLHP9ZoY0SAIKpLJEnCUDIaeOZ2pWQgIkvuNYno2fTLsnOIuBBwkN6I9/5zpyU7g3mq\njQRUlhytU5bsx2C/Rc8kX0FUcTWbKMlrBhJOsGT33DYXMC3mNURkCdsH4g333IqeW6B+6XIYLOZK\nFYcHXpszUIplyW119y3boZtW3dKTv37wRRwYTeGf33Ebdg0lcIHBbU1wq8iSu1KpHb53chrHr2QA\n2Bfu3zk2hZ++YaxiivO1Y314sY27bpeLOn7xvz+Ozz910bev2c2rgDKetRGrEeWo16wyTAqwM5FG\nlw6Uqi75S7Y4UEqUt1cMlJJld9BUpypfMKttX1vQbkt5zZc1QMLOoQR0J7j0y/isnbk9M9Pc8+p8\nrgTNsGBa3ftzI5s42Pa2jgTRA1otXypn7oDyXnS/iGuaxU2qPhBlxqN9Mffv+ZJet+IpkJ5bozK4\nFYGJH323C27mtk5ZcpM/w7xmIO5M342rCnTTaqoiSUz2btRTq+nlsmTx8WFkZ27rv66oioyEqrTt\nwDjHntv2e8muAewcTOCbz1cGt7ph4tT0Ml57/Vb0xSLYPZzEhbneDW7Lq4BqH0J9sQiWm+yT2Kj/\n8uWj+D8/8RSWchoePzOHpbyGu2/ZXvEx127rx5np5baVXi7mStBNC1M+Xky6wa1UFdx2wbTkTEF3\nT/lXM9Jnnzpev72JsmQniCvqhrv/sBtk8jqiiuz+3qViEay0NFCq8pAECMdhgJuxrhgoFc7ysLX4\nnbndMejvrtuSbmJiIQdJAs7MrDSVuZnyDJ7arMwXtUf1ARxgBy1B/9xzpcqdr/1x1df2KHGIuFnB\njShFvnasD4s5zR7cpdUvSx7uiyKv+fvaZ09LLn8vN7j1ITAR92lFWXKLwW1BM5Bwg1v7thWauG3e\n4LZecOcdKOW9rWGz1utKfzxSt+c4CLmanluWJQdOkiT8zC3b8INTMxUP4vG5FZR0E9c7A4r2jiRx\n3uk76kXitK5ucOvziWkjlmVhfqWEqUwRH/ja8/jm85NIRRW8+prRio+7dms/SobpltIFTfzb65W2\nr1fjzG3zLyyZgobf/Nwhd9Jip2g2c/vqa7bgM+++3d3N1oiqyNCc++V9X30e/9e/HvTldrZTox5J\nu4Q74pZwp6IRlHTTLTdei7hfvBMTlRBMlxYvuulEpOszt4s5zZc1QMIud9etP8HtxEIOpgW8dPcg\nlos6JpuYmMzgtncsVc0FAOxMYtD91rmS4bZFAeU9qX5VN4lAOeiVRo2IUmQxc+LKYgGWhbplyWJC\ntfgcP5R0s2KAaNTHrJsoufY+7/XHnM0bTRxQmM5UZZG5FUFuM8F9Jm+3RaUbZW5Fz62T9VzMh+/5\nSzdMZAt6RWa8WjqhNj28a6PyoueWmdv2uvuW7dAMCw8dn3LfdmLS7tm8TgS3wylkCrqvAUyYlKcl\n154a9re4fHu98pqBkmFix0AcX33uMr787AR+6oYx9wlOED+zU23quxUX3X5exBmmBVmCG9RE3OC2\n+a9xcHwe9x++jCMdNuU7U2guuFVkCa+6enTN3lzvaptjVzKhax947PQsXvWhh3FysvbxuuS8EAsp\npy+p2aFSep1pyaoid3x5uzdzG1cVRBU5tIM91rKY0xr2Rq2HWI/hV3Arhkm9/oYxAM0NlZpcKl9k\nB70ShjZXJl85FwBAW3puq8uS0z4PtxSZ28VNztxeM2bPnLi4YL+upWL1piXHAAAzWZ+D24ppyf5l\nbhfrZPtFWfJyE6WyIjgS134x589m+m5F5jadUJEt1B6GdEPPrbh/V8vcptuUubUsy604cDO3DG7b\n49bdg9gxEMe3PKXJJyezUGTJHWazZyQJADg/35vZ20bTkgG7LLkdJYPiJPj/ee3VuHlnGiXdxM/c\nvK3m467e2gdJat86IHHR7edJtWFZFUOAZKn1zK3Y9dtpgUwm31xZcrMiSnmg1JXFQuh2Uj973l5F\nduxK7SFEdZZb9Fs1O1RKDCbzPpbszG1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XyFxvtN3nmFOR0qinO+fpuQWc4JY9t+21NR3H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SAAAg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\nAAAAI4/kFgAAAAAw8v4Py95OdiV3gPkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3e3d1f1588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train_df.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Вопрос 5**: Далее перейдем к построению модели SARIMAX (`sm.tsa.statespace.SARIMAX`). Модель c какими параметрами лучшая по `AIC`-критерию?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 249,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "p = 1\n",
    "ds = range(0, 2)\n",
    "q = 2\n",
    "P = 3\n",
    "Ds = range(0, 3)\n",
    "Qs = range(0, 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 250,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12"
      ]
     },
     "execution_count": 250,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from itertools import product\n",
    "parameters = product(Ds, ds, Qs)\n",
    "parameters_list = list(parameters)\n",
    "len(parameters_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 251,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 17%|█▋        | 2/12 [00:16<01:19,  7.95s/it]       | 1/12 [00:07<01:24,  7.68s/it]/usr/local/lib/python3.5/dist-packages/statsmodels/tsa/statespace/tools.py:405: RuntimeWarning:\n",
      "\n",
      "invalid value encountered in sqrt\n",
      "\n",
      " 33%|███▎      | 4/12 [00:19<00:37,  4.75s/it]/usr/local/lib/python3.5/dist-packages/statsmodels/base/model.py:496: ConvergenceWarning:\n",
      "\n",
      "Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
      "\n",
      " 67%|██████▋   | 8/12 [00:52<00:23,  6.00s/it]/usr/local/lib/python3.5/dist-packages/statsmodels/base/model.py:496: ConvergenceWarning:\n",
      "\n",
      "Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
      "\n",
      " 75%|███████▌  | 9/12 [01:15<00:33, 11.05s/it]/usr/local/lib/python3.5/dist-packages/statsmodels/base/model.py:496: ConvergenceWarning:\n",
      "\n",
      "Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
      "\n",
      "100%|██████████| 12/12 [02:03<00:00, 11.51s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1min 18s, sys: 3min 1s, total: 4min 19s\n",
      "Wall time: 2min 3s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "from tqdm import tqdm\n",
    "results = []\n",
    "best_aic = float(\"inf\")\n",
    "\n",
    "\n",
    "\n",
    "for param in tqdm(parameters_list):\n",
    "    #try except нужен, потому что на некоторых наборах параметров модель не обучается\n",
    "    try:\n",
    "        model=sm.tsa.statespace.SARIMAX(train_df['y'], order=(p, param[1], q), \n",
    "                                        seasonal_order=(P, param[0], param[2], 7)).fit(disp=-1)\n",
    "    #выводим параметры, на которых модель не обучается и переходим к следующему набору\n",
    "    except ValueError:\n",
    "        print('wrong parameters:', param)\n",
    "        continue\n",
    "    aic = model.aic\n",
    "    #сохраняем лучшую модель, aic, параметры\n",
    "    if aic < best_aic:\n",
    "        best_model = model\n",
    "        best_aic = aic\n",
    "        best_param = param\n",
    "    results.append([param, model.aic])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 252,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   parameters          aic\n",
      "0   (0, 0, 0)  5020.963352\n",
      "1   (0, 0, 1)  5021.558923\n",
      "5   (1, 0, 1)  5083.499723\n",
      "4   (1, 0, 0)  5164.557176\n",
      "8   (2, 0, 0)  5307.134667\n",
      "9   (2, 0, 1)  5337.410335\n",
      "2   (0, 1, 0)          NaN\n",
      "3   (0, 1, 1)          NaN\n",
      "6   (1, 1, 0)          NaN\n",
      "7   (1, 1, 1)          NaN\n",
      "10  (2, 1, 0)          NaN\n",
      "11  (2, 1, 1)          NaN\n"
     ]
    }
   ],
   "source": [
    "result_table = pd.DataFrame(results)\n",
    "result_table.columns = ['parameters', 'aic']\n",
    "print(result_table.sort_values(by = 'aic', ascending=True))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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