Time series with fb prophet.ipynb

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   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "id": "rvdENjE99Y07"
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "id": "xyR_jSnl9eH2"
   },
   "outputs": [],
   "source": [
    "from fbprophet import Prophet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using matplotlib backend: agg\n"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "id": "D9VM5LAl-OnE"
   },
   "outputs": [],
   "source": [
    "df=pd.read_csv(\"/content/monthly_milk.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Month</th>\n",
       "      <th>Monthly milk production: pounds per cow. Jan 62 ? Dec 75</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1962-01</td>\n",
       "      <td>589.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1962-02</td>\n",
       "      <td>561.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1962-03</td>\n",
       "      <td>640.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1962-04</td>\n",
       "      <td>656.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1962-05</td>\n",
       "      <td>727.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>1975-09</td>\n",
       "      <td>817.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>1975-10</td>\n",
       "      <td>827.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>1975-11</td>\n",
       "      <td>797.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>1975-12</td>\n",
       "      <td>843.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>Monthly milk production: pounds per cow. Jan 6...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>169 rows × 2 columns</p>\n",
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      ],
      "text/plain": [
       "                                                 Month  Monthly milk production: pounds per cow. Jan 62 ? Dec 75\n",
       "0                                              1962-01                                              589.0       \n",
       "1                                              1962-02                                              561.0       \n",
       "2                                              1962-03                                              640.0       \n",
       "3                                              1962-04                                              656.0       \n",
       "4                                              1962-05                                              727.0       \n",
       "..                                                 ...                                                ...       \n",
       "164                                            1975-09                                              817.0       \n",
       "165                                            1975-10                                              827.0       \n",
       "166                                            1975-11                                              797.0       \n",
       "167                                            1975-12                                              843.0       \n",
       "168  Monthly milk production: pounds per cow. Jan 6...                                                NaN       \n",
       "\n",
       "[169 rows x 2 columns]"
      ]
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    "df"
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Month</th>\n",
       "      <th>Monthly milk production: pounds per cow. Jan 62 ? Dec 75</th>\n",
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       "      <td>1962-03</td>\n",
       "      <td>640.0</td>\n",
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       "      <th>3</th>\n",
       "      <td>1962-04</td>\n",
       "      <td>656.0</td>\n",
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       "      <td>1962-05</td>\n",
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      "text/plain": [
       "     Month  Monthly milk production: pounds per cow. Jan 62 ? Dec 75\n",
       "0  1962-01                                              589.0       \n",
       "1  1962-02                                              561.0       \n",
       "2  1962-03                                              640.0       \n",
       "3  1962-04                                              656.0       \n",
       "4  1962-05                                              727.0       "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
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   "execution_count": 7,
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       "      <th></th>\n",
       "      <th>Month</th>\n",
       "      <th>Monthly milk production: pounds per cow. Jan 62 ? Dec 75</th>\n",
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       "      <td>843.0</td>\n",
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       "      <td>Monthly milk production: pounds per cow. Jan 6...</td>\n",
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       "                                                 Month  Monthly milk production: pounds per cow. Jan 62 ? Dec 75\n",
       "164                                            1975-09                                              817.0       \n",
       "165                                            1975-10                                              827.0       \n",
       "166                                            1975-11                                              797.0       \n",
       "167                                            1975-12                                              843.0       \n",
       "168  Monthly milk production: pounds per cow. Jan 6...                                                NaN       "
      ]
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    "df.tail()"
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   "outputs": [],
   "source": [
    "df.drop(168,axis=0,inplace=True)"
   ]
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   "execution_count": 9,
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Month</th>\n",
       "      <th>Monthly milk production: pounds per cow. Jan 62 ? Dec 75</th>\n",
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      "text/plain": [
       "       Month  Monthly milk production: pounds per cow. Jan 62 ? Dec 75\n",
       "163  1975-08                                              858.0       \n",
       "164  1975-09                                              817.0       \n",
       "165  1975-10                                              827.0       \n",
       "166  1975-11                                              797.0       \n",
       "167  1975-12                                              843.0       "
      ]
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    "df.tail()"
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   "execution_count": 10,
   "metadata": {
    "id": "eBSYjVKc-qjU"
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   "source": [
    "df.columns=['ds','y']"
   ]
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   "execution_count": 11,
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       "  <thead>\n",
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       "      <td>1962-01</td>\n",
       "      <td>589.0</td>\n",
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       "      <th>1</th>\n",
       "      <td>1962-02</td>\n",
       "      <td>561.0</td>\n",
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       "      <th>2</th>\n",
       "      <td>1962-03</td>\n",
       "      <td>640.0</td>\n",
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       "      <th>3</th>\n",
       "      <td>1962-04</td>\n",
       "      <td>656.0</td>\n",
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       "      <th>4</th>\n",
       "      <td>1962-05</td>\n",
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      "text/plain": [
       "        ds      y\n",
       "0  1962-01  589.0\n",
       "1  1962-02  561.0\n",
       "2  1962-03  640.0\n",
       "3  1962-04  656.0\n",
       "4  1962-05  727.0"
      ]
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     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "id": "eBqQZyw5_wXE"
   },
   "outputs": [],
   "source": [
    "model=Prophet()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
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    "outputId": "5b68c81f-e70a-4a68-951a-4805cebe829d"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:numexpr.utils:NumExpr defaulting to 2 threads.\n",
      "INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this.\n",
      "INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<fbprophet.forecaster.Prophet at 0x7f17767c54d0>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "ULnvvcuHAOF8",
    "outputId": "1fd210a8-833c-4d19-bf56-bc1fa084fa70"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "OrderedDict([('yearly',\n",
       "              {'condition_name': None,\n",
       "               'fourier_order': 10,\n",
       "               'mode': 'additive',\n",
       "               'period': 365.25,\n",
       "               'prior_scale': 10.0})])"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.seasonalities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "pDKe-qYwBA-8",
    "outputId": "e1cc4faf-becc-46c9-9ba9-8357ae7d6268"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'additive': ['yearly',\n",
       "  'additive_terms',\n",
       "  'extra_regressors_additive',\n",
       "  'holidays'],\n",
       " 'multiplicative': ['multiplicative_terms', 'extra_regressors_multiplicative']}"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.component_modes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "id": "WBo-wwhEBbjt"
   },
   "outputs": [],
   "source": [
    "future=model.make_future_dataframe(periods=365)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "id": "7oW40HgGB_R0"
   },
   "outputs": [],
   "source": [
    "forecast=model.predict(future)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ds</th>\n",
       "      <th>trend</th>\n",
       "      <th>yhat_lower</th>\n",
       "      <th>yhat_upper</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>528</th>\n",
       "      <td>1976-11-26</td>\n",
       "      <td>875.028496</td>\n",
       "      <td>804.357861</td>\n",
       "      <td>826.260487</td>\n",
       "      <td>870.412958</td>\n",
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       "      <td>-59.680857</td>\n",
       "      <td>-59.680857</td>\n",
       "      <td>-59.680857</td>\n",
       "      <td>-59.680857</td>\n",
       "      <td>-59.680857</td>\n",
       "      <td>-59.680857</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>815.347638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>529</th>\n",
       "      <td>1976-11-27</td>\n",
       "      <td>875.046715</td>\n",
       "      <td>807.431295</td>\n",
       "      <td>829.873969</td>\n",
       "      <td>870.418677</td>\n",
       "      <td>879.448043</td>\n",
       "      <td>-56.567609</td>\n",
       "      <td>-56.567609</td>\n",
       "      <td>-56.567609</td>\n",
       "      <td>-56.567609</td>\n",
       "      <td>-56.567609</td>\n",
       "      <td>-56.567609</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>818.479106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>530</th>\n",
       "      <td>1976-11-28</td>\n",
       "      <td>875.064935</td>\n",
       "      <td>810.581710</td>\n",
       "      <td>833.289710</td>\n",
       "      <td>870.425147</td>\n",
       "      <td>879.477768</td>\n",
       "      <td>-53.274871</td>\n",
       "      <td>-53.274871</td>\n",
       "      <td>-53.274871</td>\n",
       "      <td>-53.274871</td>\n",
       "      <td>-53.274871</td>\n",
       "      <td>-53.274871</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>821.790064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>531</th>\n",
       "      <td>1976-11-29</td>\n",
       "      <td>875.083154</td>\n",
       "      <td>814.101042</td>\n",
       "      <td>835.892473</td>\n",
       "      <td>870.431617</td>\n",
       "      <td>879.508446</td>\n",
       "      <td>-49.863476</td>\n",
       "      <td>-49.863476</td>\n",
       "      <td>-49.863476</td>\n",
       "      <td>-49.863476</td>\n",
       "      <td>-49.863476</td>\n",
       "      <td>-49.863476</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>825.219679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>532</th>\n",
       "      <td>1976-11-30</td>\n",
       "      <td>875.101374</td>\n",
       "      <td>818.093653</td>\n",
       "      <td>839.281223</td>\n",
       "      <td>870.417873</td>\n",
       "      <td>879.543045</td>\n",
       "      <td>-46.401460</td>\n",
       "      <td>-46.401460</td>\n",
       "      <td>-46.401460</td>\n",
       "      <td>-46.401460</td>\n",
       "      <td>-46.401460</td>\n",
       "      <td>-46.401460</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>828.699914</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            ds       trend  ...  multiplicative_terms_upper        yhat\n",
       "528 1976-11-26  875.028496  ...                         0.0  815.347638\n",
       "529 1976-11-27  875.046715  ...                         0.0  818.479106\n",
       "530 1976-11-28  875.064935  ...                         0.0  821.790064\n",
       "531 1976-11-29  875.083154  ...                         0.0  825.219679\n",
       "532 1976-11-30  875.101374  ...                         0.0  828.699914\n",
       "\n",
       "[5 rows x 16 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "forecast.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 206
    },
    "id": "T2HKWUwGCpp3",
    "outputId": "58084777-875d-4e05-8551-cedfcb8dd7de"
   },
   "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>ds</th>\n",
       "      <th>yhat</th>\n",
       "      <th>yhat_lower</th>\n",
       "      <th>yhat_upper</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>528</th>\n",
       "      <td>1976-11-26</td>\n",
       "      <td>815.347638</td>\n",
       "      <td>804.357861</td>\n",
       "      <td>826.260487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>529</th>\n",
       "      <td>1976-11-27</td>\n",
       "      <td>818.479106</td>\n",
       "      <td>807.431295</td>\n",
       "      <td>829.873969</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>530</th>\n",
       "      <td>1976-11-28</td>\n",
       "      <td>821.790064</td>\n",
       "      <td>810.581710</td>\n",
       "      <td>833.289710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>531</th>\n",
       "      <td>1976-11-29</td>\n",
       "      <td>825.219679</td>\n",
       "      <td>814.101042</td>\n",
       "      <td>835.892473</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>532</th>\n",
       "      <td>1976-11-30</td>\n",
       "      <td>828.699914</td>\n",
       "      <td>818.093653</td>\n",
       "      <td>839.281223</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            ds        yhat  yhat_lower  yhat_upper\n",
       "528 1976-11-26  815.347638  804.357861  826.260487\n",
       "529 1976-11-27  818.479106  807.431295  829.873969\n",
       "530 1976-11-28  821.790064  810.581710  833.289710\n",
       "531 1976-11-29  825.219679  814.101042  835.892473\n",
       "532 1976-11-30  828.699914  818.093653  839.281223"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "forecast[['ds', 'yhat', 'yhat_lower', 'yhat_upper']].tail()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "id": "UDYGrEQmCxaE"
   },
   "outputs": [],
   "source": [
    "fig1 = model.plot(forecast)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 441
    },
    "id": "--bWioEYDCxV",
    "outputId": "ad4d216a-2943-4edb-f59c-4c5cacb32558"
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 441
    },
    "id": "SqIi9S4uDHS_",
    "outputId": "52ee3c7f-f8cb-422b-ffe8-52c0c28ae212"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ZsU99sc/d++Ky4Pfhhx+SmppKdHQ0ANdeey2ffvoptbW1WCwWvLy8KC0txWw2A+0jhCUlJSQmJmKxWKirqyMyMtJV5YuIdEu7q+q5+bUvWXuglol9ovm/S3szpneUbrkm4iZcdo5fcnIyn3/+OY2NjRiGQUFBAVlZWVx66aW89dZbACxatIirr74agClTprBo0SIA3nrrLcaOHYvJpB2ViMh3YbMZzP+kmIF/WMPOQ/XMndSXl28YxKUZ0Qp9Im7EZSN+w4cPZ+rUqQwePBgvLy8GDRpEXl4eV155JdOnT+cXv/gFgwYN4vbbbwfg9ttv5wc/+AHp6elERESwePFiV5UuItKtlNY2cdsbhazcXc2olHAeOn7LNS9PXYxZxN249ALOjzzyCI888sgpj6WlpbFu3brTXuvn58ebb77ZWaWJiHR7hmHw2sYyfvT3LbRabfx8XDqzRvUiMSzA1aWJiIvozh0iIj3QJ/sO8+uVRfxrdxUXJITwyGWZXNFPt1wTcXcKfiIiPYRhGHy4u5rfFhSxZu9hwv29uWd0Gj8clUJ6tO6+ISIKfiIi3Z5hGPxj20F+W1DEugO1xAT5cN+YNKYPMjPQHIqnJm+IyHEKfiIi3ZTVZvDWpnIeK9jD5oqjmEP8+Pm4dKYPNJMdF6zZuiJyGgU/EZFups1q49UNZcxdVcTuqgZSwv155PJMrh+YQGZ0kC51JSJnpOAnItJNNLdZWfhFCY+v2sNXNU1kRgUy78q+TB2QQFpkgAKfiHwrBT8RkS6uocVC/oaD5G/cSsXRFnLignlyShbX9o8nOUKXZhGR707BT0SkizEMgz3VDazaU01BUTUf7q6mpqmN3MRQHhqfwdU5cSSE+ru6TBHphhT8RES6gPK65o6gV1BURUltMwAxQT6MSglnQpIvM0b1IybY18WVikh3puAnIuICNY2trN57mFVF7WFvx6F6AEL9vBiSGMqNg8zkJoUxvFcY8SH+HKysUOgTkfOm4Cci0gkaWy18WlzTPqK3p4qNpXXYDPDz8mCQOZTZF6UyLDmMkSnhJIb66w4bIuIUCn4iIk7QZrXxxYFaCo4fvv1s/xFarQaeHib6xwVz+7BkhiWHMSo1gpRwfwJ8tDsWEefTnkZExAFsNoOtlccoKKqioKiaNXsPU99qBSAzOpBpFyQwNCmMUanhZEYHEeLn7eKKRcQdKfiJiJwDwzDYd7jx+GSMaj7aU01VQysAyWH+XN4nmqHJYYzsFUFOfDDh/t66zp6IuJyCn4jId1R59OSZt9V8VdMEQHSgD0OTwxiaGMawXmEMNocSE+SrW6aJSJej4Ccicga1TW2s2Xu44xIr2w+2z7wN9vUiNzGU6wcmMCwpjGHJYcSH+OHlqQkZItK1nVfwu+qqq77x0MW77757PqsXEelUTW1WPi0+0jGqt76kFpsBvl4eDEoI4ccXprRPyEiJIDHMD18vT1eXLCJyVs4r+N13330A/P3vf6eyspKbbroJgNdff53Y2Njzr05ExIksVhvrS+s6JmT8Z38NLRYbnh4msmODuW1YEkOTwrgwJYLUyADNvBWRbu+89mJjxowB4N5772X9+vUdj1911VXk5uaeX2UiIg5mGCdm3laz6vjM26MtFgAyowKZOiD+eNALJyM6iFB/zbwVkZ7FIb++NjQ0sG/fPtLS0gAoLi6moaHhG5fZtWsX119/fcfX+/bt49FHH6W2tpYXXniB6OhoAB577DEmTZoEwNy5c1mwYAGenp4888wzXH755Y4oX0R6sOLDjR0jeqv2VHOovn3mbWKoH+MyohiWHMaIXuH0jw8hIkAzb0WkZ3NI8HvyySe55JJLSEtLwzAMvvrqK55//vlvXKZPnz4UFhYCYLVaMZvNXHPNNSxcuJB77rmn4zDyCdu3b2fx4sVs27aN8vJyxo8fz+7du/H01Dk2IvJfB4+1dNwGbdWeaoqPNAIQGeDNsOQwhh6fjDEkMUwzb0XE7Tgk+E2cOJGioiJ27twJQN++ffH1/e73lCwoKKB379706tXrjK9ZtmwZ06dPx9fXl9TUVNLT01m3bh0jR4487/pFpPs62nzyzNtqtlYeAyDIx5PcpDC+PyCOYUnto3qaeSsi7s5hZypv2LCB/fv3Y7FY2LRpEwA333zzd1p28eLFzJgxo+PrZ599lpdffpnc3Fz+8Ic/EB4eTllZGSNGjOh4TWJiImVlZXbXl5+fT35+PgCVlZWUl5ef69v6zqqqqpy+je5IfbFPfbHvu/Sl2WJjfXk9nxw4xqcHjrGpsgGrAT6eJnKi/bl9YBSD4gLITQgiLsQX7xNBr6mWQ01OfgNOpM+MfeqLfeqLfeqLg4LfD37wA/bu3cvAgQM7Dr2aTKbvFPxaW1t59913mTt3LgCzZs3ioYcewmQy8dBDD3Hvvffy4osvnlU9eXl55OXlAZCbm0tCQsJZvqNz01nb6W7UF/vUF/u+3heL1cbGsrqOEb1Pi4/QbLHhaYLsuGBmDk1i2PFboaVFBBLo23Nn3uozY5/6Yp/6Yp+798Uhe8j169ezffv2czopesWKFQwePLjj8i8nXwbmzjvvZPLkyQCYzWZKSko6nistLcVsNp9n5SLS1RiGwfaD9afc87auuX3mbXpUANf0bz90Oyolgj4xmnkrInI2HBL8cnJyqKysJD4+/qyXff311085zFtRUdGxnnfeeYecnBwApkyZwg033MBPfvITysvLKSoqYtiwYY4oX0Rc7Ksj7fe8/efmEj4r20rlsRYAzKF+jE2PYmhSGCNSwhmgmbciIufFIcGvurqarKwshg0bdsqkjm+7c0dDQwMrV648ZQbw//3f/1FYWIjJZCIlJaXjuezsbKZNm0ZWVhZeXl7Mnz9fM3pFuqmq+uMzb/dUU7C7mn3HZ96G+3kyrFcEdySFMSwpjKHJmnkrIuJIDgl+Dz/88DktFxgYyOHDh0957JVXXjnj6x988EEefPDBc9qWiLjOsWYLa/YdpqCoilVF1WyuaJ95G+jjyZDEUK7tH8fQ5DDS/Vron5Hy3wkZIiLiUA4JfmPGjOGrr76iqKiI8ePH09jYiNVqdcSqRaQbarFY+Wx/TceEjHUltVhtBj6eJi5ICOGHo3odn5ARQVKYP37e7aP35eXlCn0iIk7kkOD3wgsvkJ+fz5EjR9i7dy9lZWXcddddFBQUOGL1ItLFWW0GG4/f83bVnmo+KT5CU5sNDxNkxQZz85BEhiWHcaEbzLwVEenKHLL3nT9/PuvWrWP48OEAZGRkcOjQIUesWkS6IMMw2HmovmNEb/Xeamqb2mfe9o4M4HvZceQeH9HrGxNEmGbeioh0CQ4Jfr6+vvj4+HR8bbFYNOtOpIdpaLHwztZK3t95iFVF1VQcn3mbEOLLmLRIhiaFMfL4zNvIQB/tA0REuiCHneP32GOP0dTUxMqVK/nzn//MVVdd5YhVi4gLGYbBv/cd4aUvSnhzUzn1rVYiArzJTQzjtmGhDE0OY1hyOLGaeSsi0i04JPg9/vjj/PWvf6V///48//zzTJo0iTvuuMMRqxYRF/jqSCMvbyjlpS9K2He4kQBvT8ZnRjElK5axGVEkhvlrEoaISDd03sHParWSnZ3Nzp07ufPOOx1Rk4i4QGOrhb9vqeSlL0pYtacaw4ChSaHMzM1kUt9Y+icE4+ula2eKiHRn5x38PD096dOnDwcOHCA5OdkRNYlIJzEMg//sr+GlL0p4o7CcYy0WzCF+5A1P5sp+sVyUFkF4gM+3r0hERLoFhxzqrampITs7m2HDhhEYGNjx+LfduUNEXKOkpolXjh/KLapuwN/bg/EZ0UzOiuGyPtEkhwXonD0RkR7IIcGvubmZf/7znx1fG4bB/fff74hVi4gDFZbV8ZsPi/j7lgoMAwabQ3n4skwm9YthQEKIDuWKiPRwDgl+FouFMWPGnPJYU1OTI1YtIg6wvqSWX6/czbvbDhLo48ktuUlcnRPLxWmRROhQroiI2ziv4Pfcc8/x5z//mX379jFgwICOx48dO8aFF1543sWJyPn5bP8Rfr2yiBU7DxHi68X/jEjmxsGJjEgJ16xcERE3dF7B74YbbuCKK67gZz/7GfPmzet4PDg4mIiIiPMuTkTOzcd7D/Prlbv5sKiaUD8vfjQqhRsGmxmWHIaXAp+IiNs6r+AXGhpKaGgor7/+uqPqEZFzZBgGH+05zKMrd7Nm72EiAryZc3EqNwwyMzgxVIFPREQcc46fiLiOYRj8a1cVj67czX/21xAV6MO9Y9KYMcjMQHMonpqdKyIixyn4iXRThmHw3o5DPPqv3XxRUktssC/3X9qbGYMS6B8fqsuxiIjIaRT8RLoZm81g2bZKfr1yN1+WHSUhxJcHx6UzfbCZrJhgBT4RETkjBT+RbsJqM3h7cwW/XrmbrZXHSArz41cTMrl+UAJ9Y4IwmRT4RETkmyn4iXRxFquNNwrL+c2HRew8VE9KuD+/ntiHaQPjyYhS4BMRke/OpdP8du3axcCBAzv+hISE8NRTT3HkyBEmTJhARkYGEyZMoKamBmg/p2n27Nmkp6czYMAANm7c6MryRZyqzWrjpXUlZP1uNTe99iVtVhuPXdGXD+8ayYPjM8iMDlboExGRs+LS4NenTx8KCwspLCxkw4YNBAQEcM011zBv3jzGjRtHUVER48aN67hG4IoVKygqKqKoqIj8/HxmzZrlyvJFnKLVYuOFz7+iz7yPuPWNQkwm+N3kfnx41wh+Nj6D3lGBCnwiInJOusyh3oKCAnr37k2vXr1YtmwZq1evBmDmzJlccsklPP744yxbtoybb74Zk8nEiBEjqK2tpaKigvj4eNcWL+IAzW1WXlxXwrxVRZTUNpMVG8STU7L4/oB4ksIDXF2eiIj0AF0m+C1evJgZM2YAcPDgwY4wFxcXx8GDBwEoKysjKSmpY5nExETKyspOC375+fnk5+cDUFlZSXl5udPrr6qqcvo2uiP1xb6T+9LUZuPVLVX8ed1BDja0kR3tx9yxZiamhxMT7AtNtZQ31bqw2s6jz8uZqTf2qS/2qS/2qS9dJPi1trby7rvvMnfu3NOeM5lMZ31YKy8vj7y8PAByc3NJSEhwSJ3fprO2092oL/aFRsbwl8++4vcf7eVgfQuDzaE8PDGZq7NjiQ/1d3V5LqPPy5mpN/apL/apL/a5e1+6RPBbsWIFgwcPJjY2FoDY2NiOQ7gVFRXExMQAYDabKSkp6ViutLQUs9nskppFztWxZgvPrq3khS+3UN3QyrDkMH49sQ9TcuKIDfZ1dXkiItKDdYmbd77++usdh3kBpkyZwqJFiwBYtGgRV199dcfjL7/8MoZh8PnnnxMaGqrz+6TbqG1q49crd9PrNx8y95MyMqMDeXHaBfzz9mHcObKXQp+IiDidy0f8GhoaWLlyJc8//3zHYw888ADTpk1jwYIF9OrViyVLlgAwadIkli9fTnp6OgEBASxcuNBVZYt8Z0caW3nq4308/e9ijjZbGJ0WwbTMIKaP6kdkoI+ryxMRETfi8uAXGBjI4cOHT3ksMjKSgoKC015rMpmYP39+Z5Umcl6q6lv445p9PPtJMfWtVsamR3L7sGSu6BdDU221Qp+IiHQ6lwc/kZ6m8mgzT6zey3P/+YqmNisTMqO5bVgSl/eNIczfGwA3maQrIiJdjIKfiIOU1TXxu4/2kv/ZV7RabVzeJ4bbhyUxoU80IX7eri5PREREwU/kfB2oaWTeqj0sWFuC1TCY1DeG24YlMS4jmmA/fYuJiEjXoZ9KIudo3+EG5hbsYdH6EgwDrsqK5ZahSYzLiCLQV99aIiLS9eink8hZONzQyjtbKliyqZxVew7jaYLv5cQxMzeJS9MjCfDRt5SIiHRd+ikl8i1qGltZurWSJZvK+XB3NRabQWKoHzNzE7luQDxj0qPw9/Z0dZkiIiLfSsFPxI66pjaWbatkSWE5/9pdRZvVICHElxsHm5mQGc2Y3hGYQ/3P+naCIiIirqTgJ3LcsWYL725rH9l7f+chWq0GccG+TB+YwPiMaC5Nj8Qc6o+Hh8KeiIh0Twp+4tbqWyz8c/tBlmwqZ/mOQ7RYbMQE+TB1QAITMqMYmx5FYpjCnoiI9AwKfo82TqUAACAASURBVOJ2GlstvLfjEEsKy3lvx0Ga2mxEBfpwTU4c44+HveTwADwV9kREpIdR8BO30NRmZcWOQyzZVM4/th2ksc1KZIA3k7NimZARzdiMKFIiFPZERKRnU/CTHqu5zcoHu6pYUljOu9sqqW+1EubvxcS+0VyWGc24jGhSIvzx8vRwdakiIiKdQsFPepRWi41/7W4Pe8u2VnK0xUKonxfjM6OZkBnF+Mwo0iICFfZERMQtKfhJt9dmtVFQVM0bheUs3VpBbZOFYF8vLukdyYTMKCZkRtM7KhBvhT0REXFzCn7SLVmsNj7ac5glm8r5+5YKjjS2EejjeTzsRTM+M4rM6CCFPRERkZMo+Em3YbUZrNnbHvbe3lxBdUMrAd6ejOkdwfiMaC7rE01mdBA+Xgp7IiIi9ij4SZdmtRl8UnyYJYUVvLW5nEP1rfh7e3Bx6n8P4/aNDcLXS7dMExER+TYKftLl2GwG/9l/hCWb2sNexdEWfL08uDg1gvHHw15WbDB+uj+uiIjIWVHwky7BZjNYe6CGJZvKeXNTBWV1zfh6ejAqNZz/vTCV8ZlR5MSH4K+wJyIics5cGvxqa2u544472Lp1KyaTiRdffJEPPviAF154gejoaAAee+wxJk2aBMDcuXNZsGABnp6ePPPMM1x++eWuLF/Ok2EYfFFSy5LCcpZsKqekthlvTxOjekUwa2QvJvSJJicumAAf/X4iIiLiCC79iTpnzhwmTpzIW2+9RWtrK42NjXzwwQfcc8893Hfffae8dvv27SxevJht27ZRXl7O+PHj2b17N56eGgHqTgzDYGNpHUs2lbOksJz9NU14eZgY2SucO4YnMyEzmgHxIQT6KuyJiIg4mst+utbV1fHxxx/z0ksvAeDj44OPj88ZX79s2TKmT5+Or68vqamppKens27dOkaOHNlJFcu5MgyDTeVHO8Le3sONeHqYGJ4UxszcJMZnRjHQHEqQwp6IiIhTuewnbXFxMdHR0dx6661s2rSJIUOG8PTTTwPw7LPP8vLLL5Obm8sf/vAHwsPDKSsrY8SIER3LJyYmUlZWZnfd+fn55OfnA1BZWUl5ebnT309VVZXTt9GdGIbBzupm3viylILSreyracHDBIPiAvjJ8FjG9AomKzaIAB9PoIWjhw9x1NVFdyJ9XuxTX85MvbFPfbFPfbFPfXFh8LNYLGzcuJE//elPDB8+nDlz5jBv3jx+/OMf89BDD2EymXjooYe49957efHFF89q3Xl5eeTl5QGQm5tLQkKCM97CaTprO13ZjoPHeKOwfWRvx6F6PEwwJDGU6we1j+zlJoUR4uft6jK7BH1e7FNfzky9sU99sU99sc/d++Ky4JeYmEhiYiLDhw8HYOrUqcybN4/Y2NiO19x5551MnjwZALPZTElJScdzpaWlmM3mzi1a7NpdVd8R9rZWHsMEDDKHcv+lvRkaCeMHZhDqr7AnIiLiai4LfnFxcSQlJbFr1y769OlDQUEBWVlZVFRUEB8fD8A777xDTk4OAFOmTOGGG27gJz/5CeXl5RQVFTFs2DBXle/29lQ3dMzG3VTefpB2YEII912SxviMaIb3CifM35vy8nKFPhERkS7CpWfT/+lPf+LGG2+ktbWVtLQ0Fi5cyOzZsyksLMRkMpGSksLzzz8PQHZ2NtOmTSMrKwsvLy/mz5+vGb2drPhwY/sEjU3lbCytA2BAfDA/GZ3GuIwoRqaEEx5w5gk6IiIi4louDX4DBw5k/fr1pzz2yiuvnPH1Dz74IA8++KCzy5KTHKhp5M1NFbxRWM4XJbUAZMcGc/fFqYzPiGJkagQRCnsiIiLdgq6fIacpqWni7S3tYe/zr2oA6BcTxP9elML4jGguTI0gMlBhT0REpLtR8BMA9h1u4O3NFby9uYK1B9pH9jKjA/nRqBTGZ0ZxUWoEUUG+Lq5SREREzoeCnxvbefAYb29pD3tflrVP0OgbE8QPR/VibHoUF6dFEhOssCciItJTKPi5EcMw2FJxrH1kb0sF2yqPAdA/rv2cvUvToxjeK5yYIB9MJpOLqxURERFHU/Dr4QzDYENpXcdh3KLqhuPX2Wu/9MqlvaMYnBhKbLCvwp6IiEgPp+DXA9lsBp9/VdNxGPermiY8TTAkKYyfjU3nkt6RDDSHEq2RPREREbei4NdDWG0G/953mLc3V/D3LRWUH23By8PEiF7hzMxNZHRae9jTbFwRERH3peDXjbVZbXy0p5q3N1ewdGslh+pb8fX0YFRKOLNGpTA6LZIBCSGE6c4ZIiIigoJft9NisbJyd3vYW7a1kpqmNvy9PbgoNYJx6VGM7h1JdlwwIX4KeyIiInIqBb9uoLHVwvs7q3h7cwX/3HGQo80Wgnw8Gd07krHpUYxJi6BfbDCBvvrvFBERkTNTUuiijjVbeG/HQd7eXMHyHYdobLMS6ufFpSfCXnokmdFB+HvrfsUiIiLy3Sj4dSE1ja38Y3t72PtgVxUtFhuRAd5M6hfD2PRIxqRH0jsyEF8vhT0RERE5ewp+LlZd38LSrZW8vaWCD3dXY7EZxAb5cG1OHGMzohidFklqZADenh6uLlVERES6OQU/F6g42sw7Wyp5e3MFa/YdxmozMIf6MWOQmXHpkVzcO5LkMH+8FPZERETEgRT8OsmBmkb+fjzsfbr/CIYBvcL9mZmb2H5f3NQIzGH+eHrogsoiIiLiHAp+TrS3uqHjvrjrDtQCkBEVSN7wZMZmRDEqJZyEEH88FPZERESkEyj4OdiOg8c67otbWH4UgKzYIH58YQpj06MYmRKu++KKiIiISyj4nSfDMNhccZSXPi3nX8W72H6wHoAB8SHcPTqVsb2jGJESTnSQr4srFREREXen4Hee6pot5D75b2yGwSBzKD+9pDeXpkcyvFc4EQG6L66IiIh0HS4NfrW1tdxxxx1s3boVk8nEiy++SJ8+fbj++uvZv38/KSkpLFmyhPDwcAzDYM6cOSxfvpyAgABeeuklBg8e7MryAQjz92bJzUPwbKxlzIB0QnVfXBEREemiXHq9kDlz5jBx4kR27tzJpk2b6NevH/PmzWPcuHEUFRUxbtw45s2bB8CKFSsoKiqiqKiI/Px8Zs2a5crST3FN/3hyk0IV+kRERKRLc1nwq6ur4+OPP+b2228HwMfHh7CwMJYtW8bMmTMBmDlzJkuXLgVg2bJl3HzzzZhMJkaMGEFtbS0VFRWuKl9ERESk23HZod7i4mKio6O59dZb2bRpE0OGDOHpp5/m4MGDxMfHAxAXF8fBgwcBKCsrIykpqWP5xMREysrKOl57svz8fPLz8wGorKykvLzc6e+nqqrK6dvojtQX+9QX+9SXM1Nv7FNf7FNf7FNfXBj8LBYLGzdu5E9/+hPDhw9nzpw5HYd1TzCZTOd02ZO8vDzy8vIAyM3NJSEhwSE1f5vO2k53o77Yp77Yp76cmXpjn/pin/pin7v3xWWHehMTE0lMTGT48OEATJ06lY0bNxIbG9txCLeiooKYmBgAzGYzJSUlHcuXlpZiNps7v3ARERGRbsplwS8uLo6kpCR27doFQEFBAVlZWUyZMoVFixYBsGjRIq6++moApkyZwssvv4xhGHz++eeEhobaPcwrIiIiIvaZDMMwXLXxwsJC7rjjDlpbW0lLS2PhwoXYbDamTZvGgQMH6NWrF0uWLCEiIgLDMPjxj3/M+++/T0BAAAsXLiQ3N/dbtxEVFUVKSorT30tVVRXR0dFO3053o77Yp77Yp76cmXpjn/pin/pin7v0Zf/+/VRXV9t9zqXBryfJzc1l/fr1ri6jy1Ff7FNf7FNfzky9sU99sU99sU99cfF1/ERERESk8yj4iYiIiLgJz4cffvhhVxfRUwwZMsTVJXRJ6ot96ot96suZqTf2qS/2qS/2uXtfdI6fiIiIiJvQoV4RERERN6HgJyIiIuImFPzO4LbbbiMmJoacnJyOxzZt2sTIkSPp378/V111FUePHu14bvPmzYwcOZLs7Gz69+9Pc3MzjY2NXHnllfTt25fs7GweeOABV7wVh3JEX042ZcqUU9bVnTmqN62treTl5ZGZmUnfvn15++23O/29OJKj+vL666/Tv39/BgwYwMSJE894jaru4mz68uqrrzJw4MCOPx4eHhQWFgKwYcMG+vfvT3p6OrNnz6a7n73jiL64+773mz4vJ7jrvvebetPT9r1nZIhda9asMTZs2GBkZ2d3PJabm2usXr3aMAzDWLBggfGLX/zCMAzDaGtrM/r3728UFhYahmEY1dXVhsViMRoaGoxVq1YZhmEYLS0txkUXXWQsX768k9+JYzmiLye8/fbbxowZM05ZV3fmqN788pe/NB588EHDMAzDarUaVVVVnfk2HM4RfWlrazOio6M7evHTn/7U+NWvftW5b8TBzqYvJ9u8ebORlpbW8fXQoUONzz77zLDZbMbEiRPdah9zspP74u773pN9/fNiGO697z3Z13vT0/a9Z6Lg9w2Ki4tP+SCFhIQYNpvNMAzDOHDggNGvXz/DMAzjvffeM2688cZvXd/s2bON/Px85xTbiRzRl2PHjhkXXnihsW3bth6z8zEMx/QmMTHRqK+vd36xneh8+9La2mpERUUZ+/fvN2w2m/E///M/xvPPP985xTvRd+3LyX72s58ZP//5zw3DMIzy8nKjT58+Hc+99tprRl5enpOrdr7z7cvXudu+92Rf74u773tP9vXe9MR9rz061HsWsrOzWbZsGQBvvvkmJSUlAOzevRuTycTll1/O4MGD+d3vfnfasrW1tfzjH/9g3LhxnVpzZziXvjz00EPce++9BAQEuKTmznK2vamtrQXa+zN48GCuu+46Dh486Jrinehs++Lt7c1zzz1H//79SUhIYPv27dx+++0uq99ZztSXk73xxhvMmDEDgLKyMhITEzueS0xMpKysrHOK7URn25eTueO+92Rf74u773tPdnJv3GXfCzrH76y8+OKL/PnPf2bIkCEcO3YMHx8fACwWC5988gmvvvoqn3zyCe+88w4FBQUdy1ksFmbMmMHs2bNJS0tzVflOc7Z9KSwsZO/evVxzzTUurtz5zrY3FouF0tJSRo0axcaNGxk5ciT33Xefi9+F451tX9ra2njuuef48ssvKS8vZ8CAAcydO9fF78LxztSXE9auXUtAQECPOTfruzrXvrjrvveEr/dF+97/+npv3GXfC+Dl6gK6k759+/Kvf/0LaB+ZeO+994D237JHjx5NVFQUAJMmTWLjxo0dv2Hm5eWRkZHB3Xff7ZrCnexs+xIUFMT69etJSUnBYrFw6NAhLrnkElavXu2qt+A0Z9ubsWPHEhAQwLXXXgvAddddx4IFC1xTvBOdbV9CQkIA6N27NwDTpk1j3rx5Lqjcuc7UlxMWL158yuiN2WymtLS04+vS0lLMZnPnFNuJzrYvJ7jrvveEr/fls88+c/t97wlf701kZKRb7HtBI35n5dChQwDYbDZ+85vfcNdddwFw+eWXs2XLFhobG7FYLKxZs4asrCwAfvGLX1BXV8dTTz3lsrqd7Wz7MmvWLMrLy9m/fz+ffPIJmZmZPXLHA2ffG5PJxFVXXdXRj4KCgo7PUk9ytn0xm81s376dqqoqAFauXEm/fv1cVr+znKkvJx5bsmQJ06dP73gsPj6ekJAQPv/8cwzD4OWXX+bqq6/u9Lqd7Wz7Au697z3x2Nf7on0vHY99vTfusu8FNKv3TKZPn27ExcUZXl5ehtlsNv76178aTz31lJGRkWFkZGQY999/f8eJo4ZhGK+88oqRlZVlZGdnGz/96U8NwzCMkpISAzD69u1rXHDBBcYFF1xgvPDCC656Sw7hiL6c7Osn5HZnjurN/v37jYsvvtjo37+/MXbsWOOrr75yxdtxGEf15bnnnjP69u1r9O/f35g8ebJRXV3tirfjMGfbl48++sgYPnz4aev54osvjOzsbCMtLc340Y9+dMoy3ZEj+qJ975k/Lye48773TL3pafveM9Et20RERETchA71ioiIiLgJBT8RERERN6HgJyIiIuImFPxERERE3ISCn4iIiIibUPATEXGwhx9+mCeeeMLVZYiInEbBT0RERMRNKPiJiDjAb3/7WzIzM7nooovYtWsXAM888wxZWVkMGDDgtDtLiIi4gu7VKyJynjZs2MDixYspLCzEYrEwePBghgwZwrx58yguLsbX15fa2lpXlykiohE/EZHz9e9//5trrrmGgIAAQkJCmDJlCgADBgzgxhtv5G9/+xteXvo9W0RcT8FPRMRJ3nvvPX70ox+xceNGhg4disVicXVJIuLmFPxERM7T6NGjWbp0KU1NTRw7dox//OMf2Gw2SkpKuPTSS3n88cepq6ujvr7e1aWKiJvTsQcRkfM0ePBgrr/+ei644AJiYmIYOnQoJpOJm266ibq6OgzDYPbs2YSFhbm6VBFxcybDMAxXFyEiIiIizqdDvSIiIiJuQsFPRERExE0o+ImIiIi4CQU/ERERETeh4CciIiLiJhT8RERERNyEgp+IiIiIm1DwExEREXETCn4iIiIibkLBT0RERMRNKPiJiIiIuAkvVxfgbFFRUaSkpDh9O21tbXh7ezt9O+5EPXUe9da51F/nU4+dS/11Lmf3d//+/VRXV9t9rscHv5SUFNavX+/07ZSXl5OQkOD07bgT9dR51FvnUn+dTz12LvXXuZzd39zc3DM+p0O9IiIiIm5CwU9ERETETbg0+N12223ExMSQk5PT8djDDz+M2Wxm4MCBDBw4kOXLl3c8N3fuXNLT0+nTpw8ffPCBK0oWERER6bZcGvxuueUW3n///dMev+eeeygsLKSwsJBJkyYBsH37dhYvXsy2bdt4//33+eEPf4jVau3skkVERES6LZcGv9GjRxMREfGdXrts2TKmT5+Or68vqamppKens27dOidXKCLfxmozONrchmEYri5FRES+RZec1fvss8/y8ssvk5ubyx/+8AfCw8MpKytjxIgRHa9JTEykrKzM7vL5+fnk5+cDUFlZSXl5udNrrqqqcvo23I166jzn29sjjRZeKjzEe0U17KpuxgCCfDwYkRjMTQOiGJ8Wislkckyx3ZA+u86nHjuX+utcruxvlwt+s2bN4qGHHsJkMvHQQw9x77338uKLL57VOvLy8sjLywPapzR31pR0TX13PPXUec6ltzabwZ8+Keah93dR32JhkDmEW4dFE+TjRVldE6v3HubDfXu5ODWCl28YREpEgBMq7x702XU+9di51F/nclV/u1zwi42N7fj3nXfeyeTJkwEwm82UlJR0PFdaWorZbO70+kTc1dHmNmb8bSPLdxxiVEo4d1+cyoQ+MYT5//cipC1tVh4rKOIPa/Yx6I9rWHbrMEb3jnRh1SIicrIudzmXioqKjn+/8847HTN+p0yZwuLFi2lpaaG4uJiioiKGDRvmqjJF3MrBYy1c8uf/8K9dVfzfpb1Z8oMhXDfQfEroA/D19uSRiX1ZO+cign29uOz5z/lwtw4ZiYh0FS4d8ZsxYwarV6+murqaxMREHnnkEVavXk1hYSEmk4mUlBSef/55ALKzs5k2bRpZWVl4eXkxf/58PD09XVm+iFs43NDK+L98xp7qBv44JYvbhycT4PPNu47suBDW330xw5/+hO8t/IKPfjiSoUnhnVSxiIicicno4VPxcnNzdcu2bko9dZ7v2tuGFguXPvcZm8rrePp7Odw2LBkfr+9+oKC0toncJz/G08PEpnvHEBXkez5ldxv67Dqfeuxc6q9zdcYt286UfbrcoV4R6RqsNoObXvuSDaW1zJ3Uj1uGJp1V6ANIDPNn6a1DqWpo5eoXv8Bm69G/Z4qIdHkKfiJi169X7mbp1kruGZ3GnSN64ed9bqdWjEiJ4HeTs/jPVzU8VlDk4CpFRORsKPiJyGk+3F3Foyt3c2W/GH56SW+C/c7vdOA5F6dySe9IfvNhEdsqjzqoShEROVsKfiJyivK6Zm58dSOp4QE8enkfYkP8znudJpOJV28cjJeHiTuXbNZdPkREXETBT0Q6WKw2ZvxtA0ebLcy7si+Dk8Ictu6EUD8endiHz76qYcG6Aw5br4iIfHcKfiLS4Vcf7OLjfUf42bh0rukf7/D1z74olb4xQTy0YhdHm9scvn4REflmCn4iAsD7Ow/xWMEers6OZfbFaXh5On734OXpQf51A6g81sJP3t3m8PWLiMg3U/ATEUprm7jp1Y2kRwXwyOV9TrsjhyNdnBbJ9IEJvLy+lK0VdU7bjoiInE7BT8TNtVltTH9lA01tNuZN6scF5lCnb/OPV2fjaTJx77s7nL4tERH5LwU/ETf3wHs7+HR/DT8fl86UnLhO2WZ8iB93j07jX7urWL2nulO2KSIiCn4ibu2tTeX8cc0+rh+YwF2jUvB2wnl9Z/LA2HTC/L144D2N+omIdBYFPxE3tetQPbcuLqR/XDA/H5dOZKBPp24/1N+bB8dlsvZALW8WlnfqtkVE3JWCn4gbqmu2cO1LX+DlaWLelf0YkOD88/rs+fFFKSSE+PKrD3bpos4iIp1AwU/EzbRYrNy+bC+7qxqYN6kfl/eNcVktft6e/PaKvuw4VE/+Z1+5rA4REXeh4NdFfXGglkkvrCX05ysY+tTHvPFlmatLkh7AZjOY+Xohn5XW86vLMvlBbiKeHiaX1vSD3CR6Rwbw+Ed7sNo06ici4kwKfl3Qsq2VjPnzp6wvqeXS9EgON7Qy/W8bmVtQ5OrSpBszDIN7/7GNNwrLuWNQFLNGpRDg4+XqsvD0MDF3Ul+KjzTx1Mf7XF2OiEiP5tLgd9tttxETE0NOTk7HY0eOHGHChAlkZGQwYcIEampqgPYfWrNnzyY9PZ0BAwawceNGV5XtVDsOHmP6KxtIiwjk1RsH8c6tQ9l1/6VMyIzi58t38trGUleXKN2QzWYwZ+k2nvq4mOkDE/jfYXGdPpnjm3x/QALZccE8uWYfLW1WV5cjItJjuTT43XLLLbz//vunPDZv3jzGjRtHUVER48aNY968eQCsWLGCoqIiioqKyM/PZ9asWa4o2alaLTZueu1L/Lw9+MOULCb0icFkMuHt5ck/bh9GZnQg9727ncZWi6tLlW6kvsXCdS+v50+fFHPjYDNPXJVFVJCvq8s6hYeHid9P7kfZ0WYe/2iPq8sREemxXBr8Ro8eTURExCmPLVu2jJkzZwIwc+ZMli5d2vH4zTffjMlkYsSIEdTW1lJRUdHpNTvTXz7bz8bSOn4+LoPxmdGnPOfr5cnzUwdQcaxF1z2T72x9SS1Dn/o3S7dWcvfoVJ64KgtzmL+ry7JrYt8YhiaF8uwn+/XLjYiIk7j+BJ+vOXjwIPHx8QDExcVx8OBBAMrKykhKSup4XWJiImVlZR2vPVl+fj75+fkAVFZWUl7u/GuEVVVVndfyTW02frtyFwNi/JmY6MXBytNDbWYATEgLYcHaA9w1IJQw/y733+dQ59tTd1Z2tJWn11aweEs14f5ezBubyLXZodjqj1Be33V7e//IWKYu2c0Df9/IA6MTXV3OOeuq/e1J1GPnUn+dy5X97dLJwWQyYTKd/YzDvLw88vLyAMjNzSUhIcHRpdl1Ptt5cs1eDjVY+M0VWfTP6HXG1z08yY8Ln/2UN4qaeGRin3PeXnfRWf93XY3VZrCnuoGS2iaaLTY8TOBhMhHg7UmInxfBvl4df/t6eVDXbGFvdQPrSmr55/aDvL/zEB4mE1MvSOCukcmMTovC42uzd7tib7+fAGM2HOblLYd5dMpAwgK6znmIZ6sr9renUY+dS/11Llf1t8sFv9jYWCoqKoiPj6eiooKYmPZrjJnNZkpKSjpeV1paitlsdlWZDmWx2vjjmn3kJobyvf7ffK/UkSnh5MQF8+rGUh6+PPOcgrF0TW1WG+9sqeRvG0r5aE819a3nNskhPtiXm4ck8v0B8YzNiOoSM3fPxu8nZzHs6X/zi/d38ey1/V1djohIj9LlfiJMmTKFRYsW8cADD7Bo0SKuvvrqjsefffZZpk+fztq1awkNDbV7mLc7em/HIUrrmrn74lSiv+Wke5PJxN2j07hjySaWba3ke/17Rg/c3duby7n/nzvYe7iR2CAfJvaNIScumIQQPwJ9PTEBVsPgWLOFhlZrx5/GVistVitBPl4khPqRGR1IbmIY8SF+p43wdRdDk8OY1DeGl74o4ZcTMogJ9nN1SSIiPYZLg9+MGTNYvXo11dXVJCYm8sgjj/DAAw8wbdo0FixYQK9evViyZAkAkyZNYvny5aSnpxMQEMDChQtdWbpDPfef/cQG+TA5O/Y7vX7aBQn88O3NLC4sV/Dr5o42t5H35mbeKCwnIyqQJ67K4ns5caRGBHTb4OYIj0/ux4An1vB//9zBSzMGubocEZEew6XB7/XXX7f7eEFBwWmPmUwm5s+f7+ySOt2+ww18sKuKu0b2IiMq6DstE+znxeV9YlhVVE2bxYa3l67D3R0dqGlk8oJ1bK88xl0je3H36FT6xAS7uqwuISc+hGkDE3j9yzJ+Ni6DPjHf7XtDRES+mRKDi722sf1WbJP7xZzVCM/0QQlUNbSybFuls0oTJzpQ08iY+f9h3+FGnv5eDk9claXQ9zW/n5yFyWTif/++xdWliIj0GAp+LmQYBq9uLGOwOYRRqRHfvsBJrsqKw8fTxNube9a1DN1BVX0L4/7yGdUNrfzl+/3JG9mLQN8ud7qtyyWF+3PfmDRWFlXz/o5Dri5HRKRHUPBzocKyo+w8VM/EvjGEn+VlK4L9vBibHsUnxUew6cb23UaLxco1C7+gpKaZZ76Xw/RBZrw99W14Jj8bl0FMkA8/eXebPuciIg6gnzgu9NqXZXh5mLisT/S3v9iOSf1iKa1rZt2BGgdXJs4yZ+k2Pt1fw8OXZ3LDEDNeCn3fKNDXi99PzuL/2bvv6CirWwMAPgAAIABJREFU9IHj35n0XkkPCSFAeg8QehVEDAICdiyIdVUsrMq6sru4ur+1V8RVwAauCmJHOkgLhE5IoQTSe09ImdzfH5GsSCeZzCR5PudwDjPzzn2fuTN555lbjxRW89qm44YORwghOj351jEQpRQrD+YR7+tIrI/jVZUxLqglYVx1SMb5dQbL9+bw/vaTzIzz4f5B/liYmhg6pE7htlgfor3t+cfadPIqTxs6HCGE6NQk8TOQ1MJqjpXUMjzAGdurHN/Vx9UGX0dLtp8sb+foRHvLLq/jvq8OEOFpz9OjAnG0MjN0SJ2GVqvhk1tiqG3UMfPzvYYORwghOjVJ/Azk28MtexCPCHS96jI0Gg3j+7mxO7ucqtON7RWaaGdKKR74+iD1Tc38fVxfgtxl9u6VCvWw45lRgazJKObjXVmXfoIQQojzksTPQL47nE+Qmy0D/JzaVM64oB7UNOj4OVU21DZWy/fm8n1KAQ8O8ufa4MtbpFuc6y9j+xLsZsucbw9TVFVv6HCEEKJTksTPAIqq69l2soxhAc5t7vIb2ssFgM3HS9ojNNHOiqrreeSbQ4R52PHo0F6Yy2LbV83MRMuy22OoON3ETZ8mo5TM8hVCiCsl30IG8ENKIUrBsACXNpflZmdBoKs1+3Ir2yEy0d7mrDpMeV0jz43tg5+ztaHD6fQivRz4+7i+rD9awj/WZBg6HCGE6HQk8TOAb1Pycbc1Z2Rg2xM/gBG9XdmXU0FtQ1O7lCfax5bjJXy2J4c74324PtTD0OF0Gc+M7sO4fj34+y9pfCcz2oUQ4opI4tfBTjfqWJ1axNAAFzzsLNulzGEBzlQ36Nh0rHt099Y36Xh10zEGvL4Fn7+vYdR721i0/SRNumZDh9ZK16z408pDuNtZcH+CP1ZmsnRLe9FoNPz3jlgCXGy4+bM9JGfLrHYhhLhckvh1sPVHi6lt1DEswPmK9ua9mKG/dRlvONr1E7+cijqiXtnME9+mUNeoI9LLnpOlLUulRL2yiYyiakOHCMB/dp5kf24ljw3tRYyPg6HD6XLsLc1Yd38CNuYmjFm4nf25FYYOSQghOgVJ/DrYDymFWJpq262bF8DPyQpPewv2d/FxfvmVpxn57nayyut4Y1Ioa+9P4IdZA8h4ZiQLbwwnu+I0A9741eA7mZTVNjDvx1RivB2YGeeDRtM+Cb44m6+TFZsfHISZVsvwd7ax8WixoUMSQgijJ4lfB/slvZA4X0cCXW3brUyNRkOCnxOH86vQddH9TJVS3PPf/Zwqr+PNG8J4YLA/bnYWAGi1Wu5L8Gfbn4Zgaarlmvd3kJJfZbBY5/+STlldI0+OCMDTwcpgcXQH/dzt2PrwYByszLhm0Q5e3XhMZvsKIcRFSOLXgY6X1HC0uJaBfo5YtvOYr4F+TuRUniat0Di6Otvb0l3Z/HikkD8N9ufWWG/MzrPHbYiHHZsfGoRWo+Ga93dQXN3xa72l5FfxztZMbgjzYGKITOjoCH3cbNkzZyj9fR154rsUhr2zjUN5Xbv1WwghrpbRJn7+/v6Eh4cTFRVFXFwcAKWlpYwdO5Y+ffowduxYysoM26V3pX5Ja1lkeWDPti3afD4DfiuzK3Z3VZ1u4qnvU4j2tuehIRff4zawhy0/zOpPYU09U5fu7tDWH6UUc1YdxspUywMJfthZXt1WfOLKudhYsOXhwbw4IYj9uZVEvrKJxI+SWJNWZFSTfoQQwtCMNvED2LBhA/v27WP37t0AvPTSS4wePZqMjAxGjx7NSy+9ZOAIr8wv6UV42lmQ4N/+iV+sjwMmGg17u+Ag97e3nqC4poFHhwbg72xzyeMT/J154dogNh8vZcHa9A6IsMUPRwr5Jb2Iewf6MbwNW/GJq6PRaHh6dB8ynh7JzDhfNh0t4ZpFO3D962queX8Hz/2Uylf7c9l2opQTJbWy/JEQolvqVE0Sq1atYuPGjQDMnDmTESNG8K9//cuwQV2mRl0z69KLGd3Htd2Wcfk9GwtTgt1tOZRnuLFt+lB1uomXNx5jsL8TE0Muf7uzJ0f0ZnVaEQvWZHBN3x4M8HPWY5TQ0NTM46sO4+dkxV39fc/bFS06hru9JR/dFMXrN4SydFcW6zKKSSmoZn1GEbo/NABbmmpxsTHH1cYcd1sL+rnZEuxuS7iHHQP8nOR9FEJ0OUab+Gk0Gq655ho0Gg333Xcfs2fPpqCgAE9PTwA8PDwoKCg473MXLVrEokWLAMjPzyc3N1fv8RYVXXyv3F051VTWNxHupCE/P08vMUT2sGBVWinHT2a1+xhCQygqKmLx3kJKaxu5KciW+opirqRB89UxXoxcXMb0pbtYPzMUKzP9fYm/v7uAjOIaXhjphXNzFbm5xj3W8lKf165iam9Lpvb2oVkp8qsaSCmsJaeynpK6JspO66iq11Hx278TxZVsPl7M6aaW7NDaTMtgXzuu7eNIYj/nK/r8dJf6NSSpY/2S+tUvQ9av0SZ+v/76K97e3hQWFjJ27FiCgoLOelyj0VxwmYzZs2cze/ZsAOLi4vDy8tJ7vMBFz7PnQBpaDYyLCsDLSz+tT8ODGvnsYDG5OmuG+LXfcjGGopRi2S8ZhLjbMm1gMO6/zeK9XF7A57dbMf6DnczfWsgnt8ToJc7Cqnpe37mfQX5O3DUsFE/79m/R1YeO+rswFj5AXNCFH1dKUdvQxJHCGraeKGXz8RK2ZZax5vhJ/rYph3sH9uTRoQH4OF7eTO3uVr+GIHWsX1K/+mWo+jXafgxvb28A3NzcmDx5MklJSbi7u5OX19JalpeXh5ubmyFDvCKr0woJdbcj1N1Ob+eI9m5ZKHjHyc416eVCdufWcDi/iinhnlec9J0xLsiNewf25NPkHL47rJ/tvZ77OZWaBh1zhgd0mqRPnEuj0WBjYUacryOPDgvg6zvjyX5uDF/eEUusjwOvbjpO4Ivree6nVBkfKITotIwy8aupqaGqqqr1/7/88gthYWEkJiaydOlSAJYuXcqkSZMMGeZlK61tYFdWOQP9nHCwMtPbecI87DDRaEjtIku6fHqgCBtzExLbuM/t65NC8XOyYvaXByivbWin6Fpszyzlg52nmB7hyfigzvNDRFweExMtN0Z6se6BQRx8cjjDApxZsDaDwH+u55uD+hmyIYQQ+mSUiV9BQQFDhgwhMjKS/v37c9111zF+/Hiefvpp1qxZQ58+fVi7di1PP/20oUO9LOsyimlWLWvt6ZOlmQn93GxIK6rR63k6Ql2jjp8yyhnTx5VIL/s2lWVtbsry22IorK7nzuX72inClj2D7/nvftxsLXhwsD+2FkY7ckK0gxAPe365L4Ef7umPrYUpk5fs5s5le6X1TwjRqRjlN1VAQAD79+8/534XFxfWrVtngIja5pe0ImzNTRgSoN/EDyDG24Ff0os43ajr1BM8fk4tpKaxmbF9e2Bu2vbfJwP9nXl8eAAvbzzOZ8nZ3Brr0+YyF6zJ4EhBNW/eEMogf/3OGhbGY0KIO2P69uChFQf4z84sNh8vYeWd8UR6y57MQgjjZ5Qtfl2JUopf0oqI7+mIn5O13s8X7eNAYXUD6UWdu7v3i325OFqYMLZf+62H98K1wQS52fKnlYfIrzzdprL251bw0vqjXBfsxvQob7Ra2Y+3OzE31fLB9Ci+uzueqnodCW/9yn/35Rg6LCGEuCRJ/PQsrbCaU+V1DOzpdNEdJ9pLlFdLq8PWzFK9n0tfahua+O5wAUN62hJwGQs2Xy5zUy1f3hFLTUMTkxbvuup9jU836rhz2T7sLU2ZMyzgqieeiM5vYqgHe+cMI8DZhhmf7GHej0dkr2AhhFGTxE/Pfkn/bZs2PY/vOyPKu2U83JGCztvitza9mNpGHUN72mLazgvohnna8/qkMJJOlfPYN4euqozHVh1mX24lfxnThxGyQ0e35+Nkxa45Q0kMdeef645yw0e7qGuUbeKEEMZJEj89+yWtiJ6OVsT5OnbI+ZytzfF1tCStsPNO8PjhSAE25iYM8m3bpI4LuX+QH7dEe/P21kze23riip77/vZM3t9+kjtifbirf09MpItXAFZmJnxzVzzzRvfhu5QCJn52hNyKtg0nEEIIfZDET4/qm3RsOFrCAD/HDu0OjPZ2IL2oulNuTq+U4ocjhQzo6Yivo37WxNNoNCy+KYpB/k786ZvDfLH38sZmrTiQx4NfH2SwvxPzxgbiqMeleUTno9FoWDAhiGW3xZBZUU/Mq5vYm11u6LCEEOIskvjp0bbMMmobdST4OXVoy1CMtwMny+rIKq/rsHO2l/25leRUnGZIL2e97pNqbqrlx1kDCHG35dbP9vDWluMXHZu1aPtJpn28mzAPO15NDKVvD/0txC06txnR3nw9vR8KGPz2VlbKen9CCCMiiZ8e/ZJWhIlWQ4J/x4zvOyPK2wEF7DzV+Xbw+OFIy/7LQwP0v+Wcg5UZ2/40hP49nXjkm8Nc/2ESaX9Y/Pp4SQ03Lt3NfV8dYKCfE+/fGEn/DhqvKTqvKE8bkh8bhr+TNVOX7OZf6zJk0ocQwigY5Tp+XcXqtEIiPe3o18O2Q88b/dsEj/05ldwU3aGnbrM16cX062FDjI8Dp8uL9X4+WwtTtjw8mHk/HuH1zScI+tcGwjzsCHCxJrviNHuyK7Aw0fLQIH8eHdaLPh38XorOy8fJil2PDSXxo108/WMqRwqr+WB6pF5bsoUQ4lLkCqQnhVX17M2pZICfE07W5h16bl9HKxwtTTvdDh61DU1szyylf09HnDuwzky0Gl6aGEL6MyN5YJAf9hampBRUYarR8OAgP1bcGcfLiSGS9IkrZmNhypr7BnJfgh9Ld2cz5O2tMulDCGFQl2zxe+KJJ7j77rsJDQ3tiHi6jLUZLcu4JBigW1Cj0RDl7UBaUTVKKTSazjHz9NcTpTToFPEdNAP6j3o6WfPu1AgAGnXNaDUambUr2kyr1bDwxggivex5fNVhwl/eyLJbY7hG9nYWQhjAJVv8goODmT17NgMGDGDhwoVUVFR0RFyd3uq0IhwsTRnQ0zDjwaK9HThWXEtFXefZR3RdRjGmWg2DjWD7MzMTrSR9ol09MMif7Y8MxtHSjPEf7OTRlYdkn18hRIe7ZOI3a9Ystm7dyscff0xmZiYRERHccsstbNiwoSPi65TObNPWv6cjfs5WBokhzMOOel0z+3M7T6K+NqOYCE876VIVXVaUtyP7nxjGlAhP3vz1BMH/2sD6DP2PZRVCiDMua4yfTqcjNTWV1NRUXF1diYyM5NVXX+Wmm27Sd3yd0qH8KvKr6knw65ht2s4nzLNluZHk7M6R+JXXNbI3p4I4X0fsLGXOkei6bC3N+GpmHN/cFYcCRi/czvX/2cnBvEpDhyaE6AYu+Q07Z84cvvvuO0aPHs2zzz5L//79Afjzn/9Mv3799B5gZ7Q6tWO3aTufEPeWxC+juHNM8NieWYpSLV3UQnQHk8I8Gdu3B3O/P8KSXVlEvryJyeGezBnWi8G9nDvN2FwhROdyycQvIiKCBQsWYGNjc85jSUlJegmqs/s5rZAAZ2tifQwzSQFalinxc7LiWEnnSPy2ZZZhooEBfoarMyE6mrW5KW9PCWfemEDm/ZjGF/tyWXEwj94u1twzoCfXBbsT7mknSaAQot1cMPHbs2cPAJGRkaSlpZ3zeExMDA4O0jrzR+V1jWw6VsJtMd70sO3YZVz+KNzTnpSCKnTNyugnKmzNLKVPD1t6u5z7A0OIrs7T3oqPbori5etDeHdbJisO5vHsj6k8+2MqbrbmjAx0JcbbgUgveyK97PGw1892hkKIru+Cid8TTzxxwSdpNBrWr1+vl4Au5eeff+bRRx9Fp9Mxa9Ysnn76aYPEcSE/HimgqVkxLMDF4L/Swz3t+Cm1kMKqejwdjPeLolHXzM6T5Vwf6o69pex/K7ovZxtz/jK2L38Z25dDeZV8tT+PHafK2HishC/25bYe52pjTrinHRGe9oR52BHmaU+Iu638/QghLumCid+GDRtobm5m+/btDB48uCNjuiCdTsdDDz3EmjVr8PHxIT4+nsTEREJCQgwdWqtvDxfgYm3G0N6GX5IkzMMOXbNib06FUSd++3MrqW3UEelpb+hQhDAaYZ72hP32N9GoayajuIYdmWWkFFSRXlTD8ZJaFp08SV1jc+tz/JysGBXoyug+rozp2wN3OwtDhS+EMFIXHeOn1Wp5+OGH2bt3b0fFc1FJSUkEBgYSEBAAwE033cSqVauMJvFraGrmp9RCRgW60tPR2tDhEObx29ZtuZVMCHE3cDQXtvVEKQD9ZXyfEOdlZqIlxN2uddLWGdWnGzmUX01ydjlHCqpJKazi6wN5LN6VhVYDI3q7cGe8L1PCPbGxkNnyQojLmNwxevRovv76a6ZMmWLwrsucnBx8fX1bb/v4+LBz585zjlu0aBGLFi0CID8/n9zc3HOOaW9FRUVsyqyk8nQTsa5aigvz9X7OS7FrasZEA4ezCsnNNd6xc2uP5OJmY4qXtvas96qoqMiAUXVtUrf61ZH129McegZYMDnAAnChvqmZ7VmV/JhexroTFdyxrISHvj7ArBh37olxw8mqaySA8hnWL6lf/TJk/V7yCvD+++/z6quvYmpqiqWlZesWYJWVxrvm1OzZs5k9ezYAcXFxeHl5dch5tx4rwdJUy/jIALy8DLeUy+/1dk0np07TYXVwpZRS7Mk/RLSPE0EBPc/5cWGscXcFUrf6Zcj67dUTbhkMOl0z3xzO560tmby2I4/3kwt5bFgv/jK2L1ZmhlljtD3JZ1i/pH71y1D1e8kFnKuqqmhubqahoYHKykqqqqoMlvR5e3uTlZXVejs7Oxtvb2+DxPJHSim+PZzPQD8ngv7QHWNIEZ72HCupoVHXfOmDDeBkWR25lfVEetkbvEVZiK7GxETL1AgvNj40iG1/Gswgfyf+ue4ogf9cz6pDhu+VEEJ0vMvauaOsrIykpCQ2b97c+s8Q4uPjycjI4MSJEzQ0NLB8+XISExMNEssfHSqsI6v8NMMCnLE1orE0YR52ZJefJqf8tKFDOa8z4/tkYocQ+pXg78ya+xNYdVccFqYabli8i0kfJVFW22Do0IQQHeiSGcp//vMf3njjDbKzs4mKimLHjh0kJCQYZDkXU1NT3n77bcaNG4dOp+Puu+8mNDS0w+M4n9VHy9FqYHhvF0OHcpYwTzsUkJxdjr+L4Sec/NHWzFJszE0MusuJEN1JYpgn44PceebHI7yxpWW/4GW3xTKyj6uhQxNCdIBLtvi98cYb7Nq1Cz8/PzZs2MDevXtxdDTc7MsJEyaQnp7OsWPHmDdvnsHi+D2lFKvSSon2diDGgLt1nM+Zmb2H8qsMHMn5bcssI8zDDi8jXm5GiK7G3FTLK4mhbHwwAQtTE0Yv3M5ffjxCc7MydGhCCD27ZOJnaWmJpWXLl3J9fT1BQUHn3cmjO9ubU8HxsnrG9euBo5VxLaDa28UaCxMtx0pqDR3KOWobmjiYV0m4px2WXWCguRCdzZBeLhyeO4KJIe68sO4oE/6zk6rTTYYOSwihR5dM/Hx8fCgvL+eGG25g7NixTJo0CT8/v46IrdNYtjcXUy1c06+HoUM5h6mJln5uNka5Z+++nEqaFeesTSaE6Di2Fqasujuev4/rx9r0IqJe3URGUbWhwxJC6Mklx/itXLkSgPnz5zNy5EgqKioYP3683gPrLJqbFcv35hDnaUOskXXznhHhZc+a9GLqm3RYmBpPy9ru7HIAIr1kYocQhqTRaHjumr7E+jpwy6d7iH1tC8tui+E6I174XQhxdS5rVu+vv/7K4sWLGT58OAkJCeTk5Og7rk6jsr6JBH8nrultb1SzeX8v1N2Ogqp6TpYaV3fv7qwKetiYE+ohiZ8QxmBCsDu75wzDw86CxI+S+PeGoygl4/6E6Eoumfj97W9/41//+hcvvvgiAI2Njdx22216D6yzcLQy4793xHFfvPEudHlmv8/d2RUGjuRsu7LKCXa3xdXG3NChCCF+E+hqw57HhzEswIW53x9h5rJ9RrsOqBDiyl1WV+/evXuJiYkBWlaarqoyzhmi4vzCPFrG0B02opm9lacbSSusZkRvP0y0snCzEMbE1sKUdfcn8PDKg7y37SRHi2v47p7+uMiPNNGJldU2sC6jmIziGmobdLjYmNPf15H4no6YmVxWB2iXcMnEz9zcHI1G07qrQk2N8U0SEBfX09EKG3MTjhvRzN69ORUoINjN1tChCCHOQ6vV8O7UCMI87Hhs1WGiX9nE6vsGEiyTsUQnczCvkgVrMvj6YB6635Ys0gBnBjG42phzf4IfT47ojYMeV+bIqzzN/txKxhl4IuglE7/p06dz3333UV5ezgcffMBHH33Evffe2xGxiXai1WoIcbc1qpm9u7Naup3jfI1zQowQosWDg3sR5GbLtI+TiX99C/+9I5YJwTLpQxi/ukYdz/2Uymubj2NlZsLNUV6MDHQlxseeHrYWFFbVs/5oCasO5fPC2gze2ZrJa5NCuSPORy9biL626TivbDpGytyRGPLn02W1+I0ZMwZ7e3vS0tL4+9//ztixYzsiNtGOIjwdWHkoj9ONOqNYM293VjkedhYEuUuLnxDGblSfHiQ9OoQJHyRx/YdJvDghiKdGBsr+2sJonSytZcrS3ezJrmBKuAcPD/ZncC8XzE3/16Xr7WBFtI8jT4zozaZjxTyy8hB3Lt/HN4fy+fSWaGzaccJmWW0D723L5Jq+PfB2sKSypLLdyr5Sl+zULiws5JlnnuHkyZOMGTOGMWPGdERcop2FedpRWttIRrFxtPrtyionxN0WJyNb8FoIcX69XW1JfnwYwwNc+PMPqSR+lERFXaOhwxLiHCn5VQx881fSCqt5NTGED2dEMbJPj7OSvj8a3tuVPY8P54nhvfn2cD5xr28hu7yu3WJ6d1sm1Q06Zsb5GnwFkEsmfgsWLCAjI4N77rmHJUuW0KdPH5599lmOHTvWEfGJdnJmgseuU+UGjqTll8+xklpC3O2kxUCITsTWwpS19yfw7OhAfjpSSOi/N5J0sszQYQnR6mBeJSPe3UajrpnFMyJ5eEivy95Ry0Sr4eXEEP57RyxZ5XVEv7qZne3w+S6va+S1TccZ7O/EuCDDb/RwWdNYNBoNHh4eeHh4YGpqSllZGTfeeCNz587Vd3yinYT+lvgdKTT8zN49vy0rEyzdvEJ0OlqthhcmBPPz7IE0NSsGvfUrT317mNONOkOHJrq5/bkVjHx3GwDv3xjBjZFeVzVbd2qEF1seGoSZVsOId7fxzcG8NsW1YE06pbWNPDjIHydrw8+Mv2SNvPHGG8TGxjJ37lwGDx7MwYMHee+990hOTubrr7/uiBhFO/Cws8DRyoxjxYaf2XtmPcH+PWVihxCd1Zi+PTj85HAmBLvz8qbjhP17I78eLzF0WKKbOllay7j3d2JqomXRtAimRHi2qUcp2seRPY8Po5ezNTcu3c27W09cVTkZRdW8+esJrg91Z2KocUyKumTiV1payooVK1i9ejXTpk3DzKylyVSr1fL999/rPUDRPjQaDWEedhw3gt07dmWV4+NgSaCrtPgJ0Zm52Frw7T39+eL2GGoadAx9ZxvXf7iTdNnrV3SgirpGrvtPEjUNTbw9OYxJYR7tMozIw96SpMeGMsDPiYdWHOLp71OuaCebRl0zt3++F0tTEx4c5I+9pXGMab+snTv8/PzO+1hwcHC7ByT0J8LTnmPFNdQ2NBk0jjM7djhYGucWd0KIKzM9ypv0p0fy8GB/1meUEPJ/G5m5bC+H8gw3c1F0D026ZmZ8kkxqUTX/NzGYyeFta+n7I1sLUzY+OIjJYR78a8Mxbvts72XvZPP86jR2nipn3uhARvdxbbeY2qr7LFUtCPO0o7pBx+ECw43zK6qu51RZnUzsEKKLsbM0460p4aTMHcHUcA++2JdL+MubGP3eNr7an0udjAEU7UwpxZ9WHmJ1WhHPjArk7gE99bITlJmJlq/vjOORIf58vjeH/q9v4eQles9e33ycF9cdZXKYB/cM6ImpEe0MYjyR/Gb+/Pl4e3sTFRVFVFQUP/74Y+tjL774IoGBgfTr14/Vq1cbMMrO6czM3uQsw+3Zm3xmYofs2CFEl+TnbM0Xd8Rx9JlRPDjIjwN5VUz7OJkef13N7Z/v4b/7cimpaTB0mG1WU9/E3uwK1qYX8d99uSzdlcWKA3kkZ5VTU2/YXpXu4vXNx1m4/SR3xPrw1MjeWJjqb41ajUbDG5PD+c/0CDKKawj+vw28uC6D6j+81zX1TTz09UHmrDrMqEAXXpoYhKuthd7iuhpG2dc2Z84cnnzyybPuS0lJYfny5Rw+fJjc3FzGjBlDeno6JiaGX4y4szgzsze10HDjb3ZnlaMB+vs5GSwGIYT++Tha8c7UCF6bFMYX+3L46kAeqw4V8GlyDhog0suewb2cifd1JN7XkX5utka9b3dpbQM/pxbyS1oRu7MqOFJYRfMFhnuZajVEedlzY6QXt8Z44+No1bHBdgPfHsrnie9SGBXowj+vC+qw8XP3DPBjaIAL93yxn2d/TOWfazMY27cHvV1tyK86zXeHC6g43cQt0d78ZWwf+vYwvi0OjTLxO59Vq1Zx0003YWFhQa9evQgMDCQpKYmEhARDh9ZpOFub425rzjEDLuK8O6scPycrejlbGywGIUTHMTfVcnucL7fH+VJb38SPqYWsTS9iV1YFi5OyeGdrJgA25iaEe9oR4WlPmIc94Z52hHnYGay1RClFamE136cU8H1KAVszy9A1KxwsTQn3tOee/j0JdLXB2doMN1sLrMxMqKxv5HhJLUcKqtl5qoynfzjCvJ9SmRbhyYJrg+jtamOQ19LV7Mku5+ZP9xDsZsvL14fg7dCxiXXfHrZsfmgQP6UW8t7WTHZllfPDkQLsLc3TvXVUAAAgAElEQVQY5O/MtAhPpkR46nXf37YwysTv7bff5uOPPyYuLo5XXnkFJycncnJyGDhwYOsxPj4+5OTknPf5ixYtYtGiRQDk5+eTm5ur95iLior0fo720MfZgvSCig6pk/PZebKUsB6W1JQWUnuJMX6dpU47I6lb/ZL6vbBBPWBQjx5AD6rrm9ibV82e3GrSSus5UVbPsj3ZVDX8b/C8i5UpwT2sCHJt+dfP1Yp+LpbUVpS2e2x1jc1sz65i/fEK1p+o4GRFS5d0bycLZoQ4keBjw0BfO9xsLTE9q3WyueWfHSS4WkM/a8CNg/nVLEou4JuDeXx1IJd7Y9yZO8QLcyMa73UhxvoZzq1qYOJnqdiaa5g/xA13bS25uYZZrSLKAd6f4EuzUlSdbunytTY3wcxES01ZETUXWfvZkPVrkMRvzJgx5Ofnn3P/Cy+8wAMPPMBzzz2HRqPhueee44knnuCjjz66ovJnz57N7NmzAYiLi8PLy6td4r6UjjpPW8T7l/HutkxsnXpg38G/RvIqT5Nf3citsb54e3tf1nM6Q512VlK3+iX1e3n69oIZv7tdU99IWlENu7LKSS2s5lhxLcdKavj0QDGnm/6XEPrYmxPlU0+4px3hHvaEetjRy9kauytYLaDydCO7TpWTlFXOluOlbDjacg4LUy3xvo7cHOvMsABnBvo5XdXCu15eMC6mL5mlNTyy8jDv7S5gw6kavrwjljBP+ysur6MZ22e4oq6RWcu2Ud3YzIfTI7kxyqtTTxI0VP0aJPFbu3btZR137733MnHiRAC8vb3JyspqfSw7O/uykwfxP2EedtQ3NbM/t5KhvV069NzJsmOHEOISbCzMiPFxJMbnfwu8K6WorGtif14FydkVZBTXcCSnlJSCKn5KLUT3u8F2Dpam+Dpa4edkhYuNOdZmJliZmdCoa6amQUdVfRNZ5XWcKK2lsPp/k0z8nayYHObB4F7ODO7lRB9XW2zaaU9Vf2cbvr2nP5/vyeHhFQeJfW0zr98QxgOD/Nul/O7gdKOOSYt3cTi/itcSQ9u8QHN3ZnRdvXl5eXh6egKwcuVKwsLCAEhMTOSWW27h8ccfJzc3l4yMDPr372/IUDulMxM8knPKOzzx23WqHK0G4n1lYocQ4vJpNBocrM0Y1tuVYb1b1kPLzc3F3cOTwqp69uSUcyC3iryq0+RX1VNQVU9GcQ17cyo43dTM6cZmTLUarMy0WJqZ4G5rwWB/Z7wdLAlysyXK256+PWxxsTZHq8cJJrfEeDMq0IXJi3fx4NcHOVJQxeuTwvR6zq6gSdfMzZ/uYdOxEhaM78fdA3yvais20cLoEr+5c+eyb98+NBoN/v7+vP/++wCEhoYyffp0QkJCMDU15Z133pEZvVchxL0l8Usv6vgJHruzy+nlbI2fk8xwE0K0nYlWg6eDJdc5eHBdiMdZjzU3K+oadTTomtE1KxSg1WgwN9FiaaY1WOLgYW/JlocHM3PZPt76NZOjxbV8fWccVmbyfXY+umbFvV8e4JtD+Tw5PICHhvTC2tzoUpdOxehq75NPPrngY/PmzWPevHkdGE3XY2dpSk9Hyw7fs1cpxe6scgb0dMJeduwQQuiZVqvBxsIUY5xHa2qi5dNbowlys+H51emMeHcb6+9PaLeu5a6ivknHbZ/t5asDecwe2JM/jwrE0UhnynYm0lbaDYV72nOspOaK9hxsq+zy0xRWNxDibivjMoQQ3Z5Go+G5a/rx/rQIdmeVM/SdrVSebjR0WEajur6J6z9M4qsDecwZFsCCa41vIeTOShK/bijc056TZXUUd+Dq+buzywEIdje+xSyFEMJQ7h3ox5KbojiQV8Xgt7ZSXifJ37HiGoa+vZV1GcU8P7Yv88b0oYckfe1GEr9uKMzDjqbmlq7XjrI7qxwTrYY4X4cOO6cQQnQGt8f58vmt0aQWVjPk7a1UdNPkTynF4qRTxL62meMltbyaGMqTI3vjYnPlS+mIC5PErxuK8m5JvnZ34J69u7MqCHSx7vAV1oUQojOYHuXN57fFkPZb8tfdun23nShl+LvbuPuL/fR2seaTW6J5aLA/tjLusd1JjXZD/XrYYG6iJb2oY/bsVUqxO7uc4QEuOMjEDiGEOK9pkV40Nytu/XwvQ9/eypaHB3fYHrSGkFVWx/dHCli6K4udp8pxsTbjmVGBzE7oib+zMU7L6RrkW7gbMjXREuJuS3oH7dl7orSW0tpGgmVihxBCXNSMaG+aleL2ZfsY9s42tjw0+Ip2I9G34up6tmWWkVJQRUpBNTkVp6msb6S6XgcorM1NsTEzwdbCpOX/5ibYmJtgqtVS26CjrlFHflU9qYVV5FbWA9DL2YqnRvRmWqQnMT6OmMi6hnplPJ8m0aFifBxYcTCPhiYd5qb6XT/qTJdyiEzsEEKIS7o5xodmBTOX7WX4u1vZ9KBhk79TZbV8vieH71IK2H6yjDMLQrjbmuNhb4mNmQle9qZoNBpON+qoadBRUtvA6cZm6hp11DXp0DWDpakWC1MtjlZmRHrZc0u0HfE9HRnSyxlPe0tpGOggkvh1U1FeDnyUlMWRgmoivfU74WJ3VjnmJhpifGRihxBCXI5bY31QSnHn8n0Mf3cr6x8Y1KFr2CmlWJdexNtbM/n2cD7NCoLdbJnVvycD/ByJ9nLAz9kae0vT8y6GrZSiUado1DXT2Kxat9Uz0WqwMNXKgtUGJIlfNxXl3bJB+PaTZfpP/LLL6eNqi7eDpV7PI4QQXcltcb4A3PXFfuJf38LGBxM6ZILcpmPFPLEyjeS8GhytTJkZ58uU8JZ9jJ2sL2+GrUajwdxUg7mpzCE1NpL4dVMRni2J38G8Sr2ep7lZkZxVwbh+Pbr0IGUhhNCH2+J8cbQ2Y8bHe4h7bQvrH0jQ23qoe7LLefbHVFanFeFqbcqzowO5KdqLEHd7GXfXhUgq3k05WJnR09GKDD3v2ZteVE1lfRPB7rZ6PY8QQnRVE0M8WP/AQBp1zfR/fQtf7M1p1/LTi6qZ8XEysa9tYcfJMh4d2ouvpgWy4Nogwj0dJOnrYqTFrxuL9rZnb24lSim9Dardeaplkejw31oYhRBCXLkBfs7sfHQokz7axU2f7mFNehFvTwnHsg1j5bLK6vjH2nQ+SsrC3ETDrAG+3DPAj/6+juTn58lkiy5KEr9uLNrbgW8PF5BbeVpv40Z2nCzD1tyEWJnYIYQQbdLb1YY9jw/jvq8O8GFSFhuOlrDwxgjG9utxReVkFFXz0vqjfLw7G4BpEZ7cFe/LyD6u552oIboWSfy6sShvBxSwPbOMGyP1l/iFetjhbif7LAohRFuZm2pZfFMU1wW7MWfVYa5ZtIOBPR15cmRvrgt2v2ALYEVdIysP5vP53mzWZRRjptUyJdyDO2J9GNnHFWtzSQe6C3mnu7Eor5bu1+TsCm6M9Gr38mvqmziQV8nd/X3loiKEEO3oxkgvrgt2Y8Hao3yYdIoblyZjbW5Cgp8ToR52uNqYo2tW5FWe5kBeFXuyy2nQKbwdLLm7vy/TIrwYEuAs1+ZuSN7xbqynkxX2lqZ627ptd3Y5zQrCPGR8nxBCtDcrc1NemBDE82P7sHxfLt+nFLA/r5IdJ8uoadAB4GRlhp+TFTOivBkd6MLQABf8nK1lwkY3ZpDE78svv2T+/PkcOXKEpKQk4uLiWh978cUX+fDDDzExMeHNN99k3LhxAPz88888+uij6HQ6Zs2axdNPP22I0LsUjUZDpKe93mb27jzZMrHjzJqBQggh2p+5mQl3xPtyR7wvSimq6puoON2IUmBp+r/t04QAAy3nEhYWxooVKxg2bNhZ96ekpLB8+XIOHz7Mzz//zIMPPohOp0On0/HQQw/x008/kZKSwrJly0hJSTFE6F1OjI8DGcU1lNc2tHvZO06V4etoSR9XWcpFCCE6gkajwd7SDF9Ha3o6WeNmZyFJnziLQT4NwcHB571/1apV3HTTTVhYWNCrVy8CAwNJSkoCIDAwkICAAABuuukmVq1aRUhISIfF3FXF+jhwuqmZHafKGR/k1m7lKqXYnllGtLcDbraXt9K7EEIIIfTLqH4G5OTkMHDgwNbbPj4+5OS0LFTp6+t71v07d+68YDmLFi1i0aJFAOTn55Obm6uniP+nqKhI7+fQBz/LRgDWHswkwr6p3crNqWwgv6qeQDsoLMi/qjI6a512BlK3+iX1q39Sx/ol9atfhqxfvSV+Y8aMIT//3C/8F154gUmTJunrtADMnj2b2bNnAxAXF4eXV/vPWD2fjjpPe/LwUNhZpHKiRtOu8W8takm24wO92lRuZ6zTzkLqVr+kfvVP6li/pH71y1D1q7fEb+3atVf8HG9vb7KyslpvZ2dn4+3tDXDB+0XbaLUa4nwdSSmobtcdPHacLMPCREusr2O7lCeEEEKItjOqJboTExNZvnw59fX1nDhxgoyMDPr37098fDwZGRmcOHGChoYGli9fTmJioqHD7TIG9HQio7iGwqr6ditzx8kygtxt8dXTjiBCCCGEuHIGSfxWrlyJj48P27dv57rrrmtdsiU0NJTp06cTEhLC+PHjeeeddzAxMcHU1JS3336bcePGERwczPTp0wkNDTVE6F1SvK8jumbF5uMl7VJefZOO5OwKwjzssLM0qmGkQgghRLdmkG/lyZMnM3ny5PM+Nm/ePObNm3fO/RMmTGDChAn6Dq1b6t+zpTt256lypkW1vQs96VQ59U3NRHvL/rxCCCGEMTGqrl5hGD6OVng7WLI/t7JdyjvTcjigp4zvE0IIIYyJJH4CgKG9nNmfW0ljk67NZW0+VkqgqzXB7nbtEJkQQggh2oskfgKAoQEuFNU0kJzdtla/Rl0zWzNLifZ2wNnarJ2iE0IIIUR7kMRPADCklzMAazPatqjk3pwKahp0xHo7tNvSMEIIIYRoH5L4CQBCPeywszBhb05Fm8rZcLRlfF+cjO8TQgghjI4kfgIAE62GBD9n9uVUopS66nJ+SSuij6sNkZ727RidEEIIIdqDJH6i1eg+rhwvreVwftVVPb+mvolfT5Qw0M8RFxvzdo5OCCGEEG0liZ9oNbZvDwC+OXTuHsuXY/PxEhp0igE9nWR8nxBCCGGEJPETrSK97HG2NmP7ybKrev4v6UWYm2gYGuDczpEJIYQQoj1I4idaabUaRvdxJelU+VWt5/dzahHR3g70drHRQ3RCCCGEaCtJ/MRZrunbg+KaBjYdL72i56UWVJFaWM2wABdsLGR/XiGEEMIYSeInzjI+yA2Abw5e2Ti/lb+NCxzR26XdYxJCCCFE+5DET5zFx9GKGB8H1h8tvqLnrTyYT6i7HQP8nPQUmRBCCCHaShI/cY4ZkV4cKaxmb3b5ZR2fVVbHrqxyRga6yDIuQgghhBGTxE+cY0qEJwCfJOdc1vGf7ckGWtYBFEIIIYTxMkji9+WXXxIaGopWq2X37t2t92dmZmJlZUVUVBRRUVHcf//9rY8lJycTHh5OYGAgjzzySJt2lxAXF+hqQ6i7HavTCi95rFKK/+w8RYy3A8NkfJ8QQghh1AyS+IWFhbFixQqGDRt2zmO9e/dm37597Nu3j4ULF7be/8ADD/DBBx+QkZFBRkYGP//8c0eG3O3MTuhJSkE1q1MvnvxtOlbCsZJaJoW542wt3bxCCCGEMTNI4hccHEy/fv0u+/i8vDwqKysZOHAgGo2GO+64g2+++UaPEYqZcb5Ymmp5d1vmRY97f/tJbM1NmBji3jGBCSGEEOKqGd0YvxMnThAdHc3w4cPZsmULADk5Ofj4+LQe4+PjQ07O5Y0/E1fHwcqMW2O8WZ1aRHZ53XmPOZxfxRf7c5kc7kmYh30HRyiEEEKIK6W3lXbHjBlDfv65a8G98MILTJo06bzP8fT05NSpU7i4uJCcnMwNN9zA4cOHr/jcixYtYtGiRQDk5+eTm5t7xWVcqaKiIr2fo6PdHmLH4l3NPLB8F+8nBp7z+Nxvj2FlquWGAAuKC69uf9+L6Yp1aiykbvVL6lf/pI71S+pXvwxZv3pL/NauXXvFz7GwsMDCwgKA2NhYevfuTXp6Ot7e3mRnZ7cel52djbe39wXLmT17NrNnzwYgLi4OLy+vK47lanTUeTqKlxfcn1DDe9tOcvy0BUMC/jd544eUAn7MKOfeAT2ZGBeEual+Go+7Wp0aE6lb/ZL61T+pY/2S+tUvQ9WvUXX1FhUVodO17BF7/PhxMjIyCAgIwNPTE3t7e3bs2IFSio8//viCrYaifb0wIRgnazOmfZzM0aJqAA7mVXLLZ3vo18OG+wf56S3pE0IIIUT7Msg39sqVK/Hx8WH79u1cd911jBs3DoDNmzcTERFBVFQUN954IwsXLsTZ2RmAd999l1mzZhEYGEjv3r259tprDRF6t+NoZcbq2QOpa9QR9epmRryzlehXN2Oq1fDK9SHE+DgaOkQhhBBCXCa9dfVezOTJk5k8efI590+dOpWpU6ee9zlxcXEcOnRI36GJ84jzdeTXhwfzzA9HSC+q4cYIT+6K92VM3x6GDk0IIYQQV8AgiZ/ofMI87flu1gCamxU6pTAzke5dIYQQorORxE9cEa1WgxaNocMQQgghxFWQZhshhBBCiG5CEj8hhBBCiG5CEj8hhBBCiG5CEj8hhBBCiG5CEj8hhBBCiG5Co5RShg5Cn1xdXfH399f7eYqKiujRQ9a1a09Sp/ojdatfUr/6J3WsX1K/+qXv+s3MzKS4uPi8j3X5xK+jxMXFsXv3bkOH0aVIneqP1K1+Sf3qn9Sxfkn96pch61e6eoUQQgghuglJ/IQQQgghugmT+fPnzzd0EF1FbGysoUPocqRO9UfqVr+kfvVP6li/pH71y1D1K2P8hBBCCCG6CenqFUIIIYToJiTxE0IIIYToJrpd4mdra2voEC7q7rvvxs3NjbCwMEOHclU0Gg233XZb6+2mpiZ69OjBxIkT26X8y3n/UlNTSUhIwMLCgpdffrldzmus9FnfJSUljBw5EltbWx5++OE2l9eZXepzN2LEiCtammHevHn4+voa/fXoUl544QVCQ0OJiIggKiqKnTt3XlU5GzduZNu2be0Wl7+//wXXMLsa48ePx9HRsd2uY1dCo9HwxBNPtN5++eWXMdTQ/Pb8vHaW64ux/41eTc7Q7RI/Q2hqarrsY++8805+/vlnPUajXzY2Nhw6dIi6ujoA1qxZg7e39xWVcSX1dT7Ozs68+eabPPnkk20qpzNoj/q+EEtLS/7xj390+eTZEK6//nqSkpIMHUabbN++ne+//549e/Zw4MAB1q5di6+v71WV1d6JX1uc7/rz1FNP8cknnxggGrCwsGDFihXtmsgawh/rVa4vF6bvnKFbJn7V1dWMHj2amJgYwsPDWbVqFdCy0nVwcDD33nsvoaGhXHPNNa1fqL//RV9cXNy6G0hmZiZDhw4lJiaGmJiY1ovXxo0bGTp0KImJiYSEhPDXv/6V119/vTWGefPm8cYbb5wT27Bhw3B2dtbny9e7CRMm8MMPPwCwbNkybr755tbHkpKSSEhIIDo6mkGDBpGWlgbAkiVLSExMZNSoUYwePZrq6mruuusuwsPDiYiI4Ouvv24tY968eURGRjJw4EAKCgrOOb+bmxvx8fGYmZnp+ZUah6up72HDhrFv377W44YMGcL+/fvPKtfGxoYhQ4ZgaWnZAa/C+G3cuPGsFp+HH36YJUuWnHXMRx99xGOPPdZ6+4MPPmDOnDnnlDVw4EA8PT31FmtHyMvLw9XVFQsLC6BllyQvLy8AkpOTGT58OLGxsYwbN468vDyg5Tr66KOPEhUVRVhYGElJSWRmZrJw4UJee+01oqKi2LJlC0VFRUydOpX4+Hji4+PZunUrAPPnz2fmzJkMHToUPz8/VqxYwdy5cwkPD2f8+PE0Nja2xvd///d/hIeH079/f44ePQpw0XJvv/12Bg8ezO23337Oax09ejR2dnb6q8yLMDU1Zfbs2bz22mvnPJaZmcmoUaOIiIhg9OjRnDp1ioqKCvz8/GhubgagpqYGX19fGhsbOXbsGOPHjyc2NpahQ4eSmpoKtCQPDzzwAAMHDiQgIICNGzdy9913ExwczJ133nnWOefMmUNoaCijR4+mqKgI4KLl3n///QwYMIC5c+eeVU5nur50uZxBdTM2NjaqsbFRVVRUKKWUKioqUr1791bNzc3qxIkTysTERO3du1cppdS0adPUJ598opRSavjw4WrXrl2tz/Hz81NKKVVTU6Pq6uqUUkqlp6er2NhYpZRSGzZsUNbW1ur48eNKKaVOnDihoqOjlVJK6XQ6FRAQoIqLi88b44kTJ1RoaKgeXr3+2djYqP3796upU6equro6FRkZqTZs2KCuu+46pZRSFRUVqrGxUSml1Jo1a9SUKVOUUkotXrxYeXt7q5KSEqWUUnPnzlWPPvpoa7mlpaVKKaUA9e233yqllHrqqafUP/7xjwvG8vzzz6t///vf7f8ijcjV1veSJUta6zctLa31c3s+ixcvVg899JCeX4lxs7GxOatelVLqoYceUosXL1ZK/e/6UFVVpQICAlRDQ4NSSqmEhAR14MCBi5bbWVVVVanIyEjVp08f9cADD6iNGzcqpZRqaGhQCQkJqrCwUCml1PLly9Vdd92llGqpp1mzZimllNq0aVPrde6Pf6s333yz2rJli1JKqZMnT6qgoKDW4wYPHqwaGhrUvn37lJWVlfrxxx+VUkrdcMMNauXKlUoppfz8/NSCBQuUUkotXbq09X27WLkxMTGqtrb2gq/3j+9/R7GxsVEVFRXKz89PlZeXq3//+9/q+eefV0opNXHiRLVkyRKllFIffvihmjRpklJKqcTERLV+/XqlVEv933PPPUoppUaNGqXS09OVUkrt2LFDjRw5Uiml1MyZM9WMGTNUc3Oz+uabb5SdnZ06cOCA0ul0KiYmpvU7EVCffvqpUkqpv/3tb63XhYuVe91116mmpqYLvj5jv750xZzB9MrSxK5BKcWzzz7L5s2b0Wq15OTktLYc9erVi6ioKKBljZ3MzMyLltXY2MjDDz/Mvn37MDExIT09vfWx/v3706tXL6BlzImLiwt79+6loKCA6OhoXFxc9PMCDSwiIoLMzEyWLVvGhAkTznqsoqKCmTNnkpGRgUajOesX+tixY1t/uaxdu5bly5e3Pubk5ASAubl5a6tLbGwsa9as0ffLMXpXU9/Tpk3jH//4B//+97/56KOPzvlVL66Ora0to0aN4vvvvyc4OJjGxkbCw8MNHZZe2NrakpyczJYtW9iwYQMzZszgpZdeIi4ujkOHDjF27FgAdDrdWa2bZ1qkhw0bRmVlJeXl5eeUvXbtWlJSUlpvV1ZWUl1dDcC1116LmZkZ4eHh6HQ6xo8fD0B4ePhZ1+sz57n55ptbW10vVm5iYiJWVlZtrhd9sLe354477uDNN988K8bt27ezYsUKAG6//fbWVrUZM2bwxRdfMHLkSJYvX86DDz5IdXU127ZtY9q0aa3Pr6+vb/3/9ddfj0ajITw8HHd399bPbWhoKJmZmURFRaHVapkxYwYAt912G1OmTLlkudOmTcPExEQPtdJxulrO0C0Tv88++4yioiKSk5MxMzPD39+f06dPA7R2WwCYmJi0Ntuampq2Np2fORbgtddew93dnf3799Pc3HxWs7WNjc1Z5501axZLliwhPz+fu+++W2+vzxgkJiby5JNPsnHjRkpKSlrvf+655xg5ciQrV64kMzOTESNGtD72x/o6HzMzMzQaDdDy/rR1PGBXcaX1bW1tzdixY1m1ahX//e9/SU5ONlDkncfvrwFw9nXg92bNmsU///lPgoKCuOuuuzoqPIMwMTFhxIgRjBgxgvDwcJYuXUpsbCyhoaFs3779vM858/d7odsAzc3N7Nix47zdgGeu0Vqt9qzrgVarPet68Ptyz/z/YuVezvXHkB577DFiYmIu6zOVmJjIs88+S2lpKcnJyYwaNYqamhocHR3PGuLxe7+v199/D/6xXn9Po9HQ3Nx80XKNvV4vR1fLGbrlGL+Kigrc3NwwMzNjw4YNnDx58pLP8ff3b/1y/Oqrr84qy9PTE61WyyeffIJOp7tgGZMnT+bnn39m165djBs3ru0vxIjdfffdPP/88+e0dlRUVLROPvjj+KjfGzt2LO+8807r7bKyMr3E2VVcTX3PmjWLRx55hPj4+NYWVXFhfn5+pKSkUF9fT3l5OevWrTvvcQMGDCArK4vPP//8rPGWXU1aWhoZGRmtt/ft24efnx/9+vWjqKioNfFrbGzk8OHDrcd98cUXAPz66684ODjg4OCAnZ0dVVVVrcdcc801vPXWW2eVfaXOnOeLL74gISGh3co1FGdnZ6ZPn86HH37Yet+gQYNae0Y+++wzhg4dCrS0xsbHx/Poo48yceJETExMsLe3p1evXnz55ZdASyvWH8f1Xkpzc3Pr99/nn3/OkCFD2qVcY9fVcoZulfg1NTVhYWHBrbfeyu7duwkPD+fjjz8mKCjoks998sknee+994iOjj5rdtWDDz7I0qVLiYyMJDU19aK/bszNzRk5ciTTp0+/YNP3zTffTEJCAmlpafj4+Jz1R96Z+Pj48Mgjj5xz/9y5c3nmmWeIjo6+aGvdX/7yF8rKyggLCyMyMpINGzZc9rnz8/Px8fHh1VdfZcGCBfj4+FBZWXlVr6OzuJr6jo2Nxd7e/qItCP7+/jz++OMsWbIEHx+fs7rJuosz1w1fX1+mT59OWFgY06dPJzo6+oLPmT59OoMHD75gQj137lx8fHyora3Fx8fHYMtztEV1dTUzZ84kJCSEiIgIUlJSmD9/Pubm5nz11Vf8+c9/JjIykqioqLNm7FpaWhIdHc3999/fen27/vrrWblyZevkjjfffJPdu3cTERFBSEgICxcuvOL4ysrKiIiI4CDb+SEAAAU8SURBVI033midGHG15Q4dOpRp06axbt06fHx8WL169RXH0x6eeOKJs75/3nrrLRYvXkxERASffPLJWYP/Z8yYwaefftraNQstyeGHH35IZGQkoaGhrZMULpeNjQ1JSUmEhYWxfv16/vrXv7apXGO/vnTVnKFbbdm2f/9+7r33XoMto9Dc3ExMTAxffvklffr0MUgMQpyRm5vLiBEjSE1NRavtVr8Br8jVXDcmTpzInDlzGD16tB4j63xGjBjByy+/TFxcnKFDEeKSumrO0G2u9gsXLuTmm29mwYIFBjl/SkoKgYGBjB49WpI+YXAff/wxAwYM4IUXXpCk7yKu9LpRXl5O3759sbKykqRPiE6sK+cM3arFTwghhBCiO5Of+kIIIYQQ3YQkfkIIIYQQ3YQkfkIIIYQQ3YQkfkKIbsPExISoqChCQ0OJjIzklVdeOWtRZn146qmnCA0N5amnntLreYQQ4nLI5A4hRLdha2vbukVXYWEht9xyC4MHD+Zvf/ub3s7p4OBAaWlph2xb1dTUhKlpt9yQSQhxmaTFTwjRLbm5ubFo0SLefvttlFJkZmYydOhQYmJiiImJaV10+I477uCbb75pfd6tt956zgK1SimeeuopwsLCCA8Pb901IjExkerqamJjY1vvg5b1ufr06UNRUVHr7cDAQIqKiigqKmLq1KnEx8cTHx/P1q1bAUhKSiIhIYHo6GgGDRpEWloa0LIjS2JiIqNGjZIlZIQQl6aEEKKbsLGxOec+BwcHlZ+fr2pqalRdXZ1SSqn09HQVGxurlFJq48aNatKkSUoppcrLy5W/v79qbGw8q4yvvvpKjRkzRjU1Nan8/Hzl6+urcnNzL3hOpZSaP3++eu2115RSSq1evVpNmTJFKaXUzTffrLZs2aKUUurkyZMqKChIKaVURUVF63nXrFnTevzixYuVt7e3KikpucpaEUJ0J9InIP6/vft3SS0O4zj+1rO4CQ2dRPwDFFRa2sKKdCxCHIKoiAaRE9QSOElT0SS1OBlRQQ3RPyAN1RAlYVskRPuZTkQOpTTEPdSNm3Cv0z2f13q+PN8vZ3p4vj8eEeGjp6xlWTQaDQzD4P7+HoBUKkWhUMC2bY6Pj8lms9+2Uy8uLpiensYwDEzTJJVKcX19zcTExB/nW1hYYHJykuXlZarVqts6r1arfWld9fT0xPPzM47jMDc3R7PZxOfz8fr66o5Jp9P09fX18neIyH9KiZ+IeNbDwwOGYdDf38/a2hqmaXJ7e0un0yEQCLjjZmdn2d/f5/DwkJ2dnZ7MHYlEME2T09NTrq6uODg4AD62fS8vL7/MD2BZFqOjo5ycnPD4+MjIyIj77ad+nyIin+mMn4h4km3b5PN5LMvC5/PhOA6hUAi/38/e3h7tdtsdOz8/T7lcBiAWi32LNTw8zNHREe12G9u2OTs7Y2hoqOsaFhcXmZmZIZfLuZc/MpkM29vb7phGowGA4ziEw2Hg41yfiMjfUOInIp7RarXc51zGx8fJZDKUSiUACoUCu7u7JJNJ7u7uvlTRTNMkGo2627G/m5qaIpFIkEwmGRsbY3Nzk4GBga7r+XX543Pcra0t6vU6iUSCWCxGpVIBYHV1lWKxyODgIG9vb//yG0TEw/Sci4hIFy8vL8TjcW5ubggGgz2LW6/XWVlZ4fz8vGcxRUR+ooqfiMgParUa0WiUpaWlniZ9GxsbZLNZ1tfXexZTRKQbVfxEREREPEIVPxERERGPUOInIiIi4hFK/EREREQ8QomfiIiIiEco8RMRERHxiHeO9GgZ+lMA1AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 648x432 with 2 Axes>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.plot_components(forecast)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "id": "8vDJ2r7kDw7E"
   },
   "outputs": [],
   "source": [
    "## Cross validation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "j_BMNbGKFUZU",
    "outputId": "de2e0e6c-52ff-4415-9dda-8b01d4120f15"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(168, 2)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "uKZHBYXWFtzo",
    "outputId": "bd318c82-1af7-4f99-88f7-8323e5810c25"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(533, 16)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "forecast.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "id": "W-Ei5KgLF2WQ"
   },
   "outputs": [],
   "source": [
    "from fbprophet.diagnostics import cross_validation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 188,
     "referenced_widgets": [
      "c6eb44f17e4b48608d18879473838655",
      "ba08807ce1d349489beebb23273fee38",
      "7961a10028e348fe8a1011c9bd329009",
      "631ae0b4c6f74e89bbd509de2bb5191e",
      "5361323ace854950a365eb9f25e71357",
      "85eefc9ea3864e3da3e025efe08592e0",
      "c4c4990a224c40c3b8a8cc97d2bf6060",
      "e57c103966f74d8082faee4c07d4cb9f",
      "a774b99e3441469ca96a67fd2d55e8f0",
      "4df71403e0e546889588b6475cae17ec",
      "37daa3af8eda439aa3645dd53d0f73ca"
     ]
    },
    "id": "0jERicKdGLqU",
    "outputId": "1b042731-2938-4df6-e8a9-1df54741228c"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:fbprophet:Making 27 forecasts with cutoffs between 1962-02-07 00:00:00 and 1974-12-01 00:00:00\n",
      "WARNING:fbprophet:Seasonality has period of 365.25 days which is larger than initial window. Consider increasing initial.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c6eb44f17e4b48608d18879473838655",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/27 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:fbprophet:n_changepoints greater than number of observations. Using 0.\n",
      "INFO:fbprophet:n_changepoints greater than number of observations. Using 5.\n",
      "INFO:fbprophet:n_changepoints greater than number of observations. Using 10.\n",
      "INFO:fbprophet:n_changepoints greater than number of observations. Using 15.\n",
      "INFO:fbprophet:n_changepoints greater than number of observations. Using 19.\n",
      "INFO:fbprophet:n_changepoints greater than number of observations. Using 23.\n"
     ]
    }
   ],
   "source": [
    "df_cv=cross_validation(model,horizon=\"365 days\",period=\"180 days\",initial=\"160\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "nW10qPP9IeKN",
    "outputId": "c33f6918-5424-4dbf-850e-db2b04098711"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(168, 2)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "EIp9o5yHL0iB",
    "outputId": "97ebf2dc-a1f4-4935-adfe-fe3f944ba7de"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(533, 16)"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "forecast.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "H3aRo275JW60",
    "outputId": "02a2006e-ec76-4fc2-ed56-d09a20e0999c"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(323, 6)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cv.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "id": "z23oH4RCJZLs"
   },
   "outputs": [],
   "source": [
    "from fbprophet.diagnostics import performance_metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "id": "PIkeU0-xL9XM"
   },
   "outputs": [],
   "source": [
    "df_performance=performance_metrics(df_cv)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 206
    },
    "id": "SgAS5dNPMGs0",
    "outputId": "32111745-c3c0-4ade-d9c0-277545c4e690"
   },
   "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>horizon</th>\n",
       "      <th>mse</th>\n",
       "      <th>rmse</th>\n",
       "      <th>mae</th>\n",
       "      <th>mape</th>\n",
       "      <th>mdape</th>\n",
       "      <th>coverage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>37 days</td>\n",
       "      <td>5.794601e+06</td>\n",
       "      <td>2407.197664</td>\n",
       "      <td>478.573875</td>\n",
       "      <td>0.828880</td>\n",
       "      <td>0.015609</td>\n",
       "      <td>0.312500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>38 days</td>\n",
       "      <td>5.794596e+06</td>\n",
       "      <td>2407.196754</td>\n",
       "      <td>478.350147</td>\n",
       "      <td>0.828632</td>\n",
       "      <td>0.014300</td>\n",
       "      <td>0.343750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>41 days</td>\n",
       "      <td>5.794556e+06</td>\n",
       "      <td>2407.188422</td>\n",
       "      <td>477.529642</td>\n",
       "      <td>0.827200</td>\n",
       "      <td>0.014300</td>\n",
       "      <td>0.343750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>42 days</td>\n",
       "      <td>5.794569e+06</td>\n",
       "      <td>2407.191125</td>\n",
       "      <td>478.000435</td>\n",
       "      <td>0.827817</td>\n",
       "      <td>0.014749</td>\n",
       "      <td>0.328125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>43 days</td>\n",
       "      <td>5.794582e+06</td>\n",
       "      <td>2407.193798</td>\n",
       "      <td>478.453931</td>\n",
       "      <td>0.828446</td>\n",
       "      <td>0.016469</td>\n",
       "      <td>0.312500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  horizon           mse         rmse         mae      mape     mdape  coverage\n",
       "0 37 days  5.794601e+06  2407.197664  478.573875  0.828880  0.015609  0.312500\n",
       "1 38 days  5.794596e+06  2407.196754  478.350147  0.828632  0.014300  0.343750\n",
       "2 41 days  5.794556e+06  2407.188422  477.529642  0.827200  0.014300  0.343750\n",
       "3 42 days  5.794569e+06  2407.191125  478.000435  0.827817  0.014749  0.328125\n",
       "4 43 days  5.794582e+06  2407.193798  478.453931  0.828446  0.016469  0.312500"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_performance.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "id": "QVniLiUBMjR0"
   },
   "outputs": [],
   "source": [
    "from fbprophet.plot import plot_cross_validation_metric"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 388
    },
    "id": "Jajxt6iDM2Ak",
    "outputId": "96d95925-615d-44e8-dcb6-9f9f1f80a3ed"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_cross_validation_metric(df_cv,metric=\"rmse\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 399
    },
    "id": "bKT7cLmDNAF8",
    "outputId": "700388a0-9849-4ae6-a7ae-88071637020d"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_cross_validation_metric(df_cv,metric=\"mse\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 388
    },
    "id": "PcxHr3I8NjWU",
    "outputId": "623fd703-53e5-4baf-aec8-cd271d11b825"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_cross_validation_metric(df_cv,metric=\"mae\")"
   ]
  }
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