07.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "6oRi56aFck6Q",
    "outputId": "36994927-584d-4f68-a176-dd5a70515ac3"
   },
   "outputs": [],
   "source": [
    "#from google.colab import drive\n",
    "#drive.mount('/content/drive')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "3NABGHXccPC3"
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "0pz0_Gg_csZU"
   },
   "outputs": [],
   "source": [
    "#data = pd.read_csv('/content/drive/My Drive/solar-forecasting/data/meteo_galicia.csv', sep=';', parse_dates=['fecha'], decimal=',',\n",
    "#                 infer_datetime_format=True, low_memory=False, index_col='fecha').sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "YX0GnW63cPC8"
   },
   "outputs": [],
   "source": [
    "data = pd.read_csv('./data/meteo_galicia.csv', sep=';', parse_dates=['fecha'], decimal=',',\n",
    "                 infer_datetime_format=True, low_memory=False, index_col='fecha').sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 450
    },
    "colab_type": "code",
    "id": "MkioM9Z8cPDC",
    "outputId": "7aced18e-cadf-4767-c3a8-a1ad4d71ca3c"
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>estacionid</th>\n",
       "      <th>lat</th>\n",
       "      <th>lon</th>\n",
       "      <th>tamb</th>\n",
       "      <th>hum</th>\n",
       "      <th>pres</th>\n",
       "      <th>prec</th>\n",
       "      <th>rad</th>\n",
       "      <th>vvien</th>\n",
       "      <th>tipodered</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fecha</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-01-01 00:10:00</th>\n",
       "      <td>20284</td>\n",
       "      <td>42.4044</td>\n",
       "      <td>-8.6730</td>\n",
       "      <td>5.4</td>\n",
       "      <td>0</td>\n",
       "      <td>1022.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.7</td>\n",
       "      <td>OFICIAL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-01 00:10:00</th>\n",
       "      <td>20233</td>\n",
       "      <td>42.3554</td>\n",
       "      <td>-7.0086</td>\n",
       "      <td>7.3</td>\n",
       "      <td>0</td>\n",
       "      <td>892.1</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>3.5</td>\n",
       "      <td>OFICIAL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-01 00:10:00</th>\n",
       "      <td>20218</td>\n",
       "      <td>43.1626</td>\n",
       "      <td>-7.2826</td>\n",
       "      <td>9.2</td>\n",
       "      <td>0</td>\n",
       "      <td>955.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>OFICIAL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-01 00:10:00</th>\n",
       "      <td>20217</td>\n",
       "      <td>42.7071</td>\n",
       "      <td>-7.0471</td>\n",
       "      <td>8.5</td>\n",
       "      <td>0</td>\n",
       "      <td>882.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.3</td>\n",
       "      <td>OFICIAL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-01 00:10:00</th>\n",
       "      <td>20221</td>\n",
       "      <td>43.5407</td>\n",
       "      <td>-7.0830</td>\n",
       "      <td>5.3</td>\n",
       "      <td>0</td>\n",
       "      <td>1027.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>OFICIAL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-01 19:40:00</th>\n",
       "      <td>20249</td>\n",
       "      <td>42.2987</td>\n",
       "      <td>-7.5907</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0</td>\n",
       "      <td>909.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>402.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>OFICIAL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-01 19:40:00</th>\n",
       "      <td>20259</td>\n",
       "      <td>42.1630</td>\n",
       "      <td>-7.0896</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>922.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>374.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>OFICIAL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-01 19:40:00</th>\n",
       "      <td>20255</td>\n",
       "      <td>42.4631</td>\n",
       "      <td>-6.9295</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>378.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>OFICIAL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-01 19:40:00</th>\n",
       "      <td>20187</td>\n",
       "      <td>42.8760</td>\n",
       "      <td>-8.5594</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0</td>\n",
       "      <td>988.0</td>\n",
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       "    <tr>\n",
       "      <th>2019-06-01 19:40:00</th>\n",
       "      <td>20295</td>\n",
       "      <td>42.0786</td>\n",
       "      <td>-8.6794</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0</td>\n",
       "      <td>963.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>OFICIAL</td>\n",
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       "  </tbody>\n",
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       "<p>2510008 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     estacionid      lat     lon  tamb  hum    pres  prec  \\\n",
       "fecha                                                                       \n",
       "2019-01-01 00:10:00       20284  42.4044 -8.6730   5.4    0  1022.0   0.0   \n",
       "2019-01-01 00:10:00       20233  42.3554 -7.0086   7.3    0   892.1   0.0   \n",
       "2019-01-01 00:10:00       20218  43.1626 -7.2826   9.2    0   955.0   0.0   \n",
       "2019-01-01 00:10:00       20217  42.7071 -7.0471   8.5    0   882.5   0.0   \n",
       "2019-01-01 00:10:00       20221  43.5407 -7.0830   5.3    0  1027.0   0.0   \n",
       "...                         ...      ...     ...   ...  ...     ...   ...   \n",
       "2019-06-01 19:40:00       20249  42.2987 -7.5907  25.0    0   909.0   0.0   \n",
       "2019-06-01 19:40:00       20259  42.1630 -7.0896  27.0    0   922.0   0.0   \n",
       "2019-06-01 19:40:00       20255  42.4631 -6.9295  30.0    0     NaN   0.0   \n",
       "2019-06-01 19:40:00       20187  42.8760 -8.5594  28.0    0   988.0   0.0   \n",
       "2019-06-01 19:40:00       20295  42.0786 -8.6794  25.0    0   963.0   0.0   \n",
       "\n",
       "                       rad  vvien tipodered  \n",
       "fecha                                        \n",
       "2019-01-01 00:10:00    0.0    0.7   OFICIAL  \n",
       "2019-01-01 00:10:00    0.0    3.5   OFICIAL  \n",
       "2019-01-01 00:10:00    0.0    0.0   OFICIAL  \n",
       "2019-01-01 00:10:00    1.0    6.3   OFICIAL  \n",
       "2019-01-01 00:10:00    0.0    2.8   OFICIAL  \n",
       "...                    ...    ...       ...  \n",
       "2019-06-01 19:40:00  402.0    2.0   OFICIAL  \n",
       "2019-06-01 19:40:00  374.0    3.0   OFICIAL  \n",
       "2019-06-01 19:40:00  378.0    0.0   OFICIAL  \n",
       "2019-06-01 19:40:00  419.0    3.0   OFICIAL  \n",
       "2019-06-01 19:40:00   26.0    0.0   OFICIAL  \n",
       "\n",
       "[2510008 rows x 10 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "sOr0Ezu0cPDP"
   },
   "outputs": [],
   "source": [
    "data = data.drop(columns=['tipodered', 'hum'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "Y_LoelmgcPDV"
   },
   "outputs": [],
   "source": [
    "estaciones = [s for s in set(data['estacionid'])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "dSlwfD8GcPDc",
    "outputId": "b18d9a7b-deb7-4e85-b151-b6e4512003b7"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "142"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(estaciones)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "colab_type": "code",
    "id": "2t9H-evQcPDh",
    "outputId": "cd1ade07-bbba-4f07-b568-878e8ae06b60"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 4.05 s, sys: 36.6 ms, total: 4.08 s\n",
      "Wall time: 4.1 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "data_by_station = []\n",
    "\n",
    "for s in estaciones:\n",
    "    filter_station = data['estacionid'] == s\n",
    "    data_station = data[filter_station].drop(columns=['estacionid', 'lat', 'lon'])\n",
    "    d = data_station.describe()\n",
    "    if d.rad['max'] != 0:\n",
    "        data_by_station.append(data_station)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "v08rvKT8cPDm",
    "outputId": "48ccefc0-26b0-4533-fb95-9e3d61e92c62"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "111"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(data_by_station)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 0
    },
    "colab_type": "code",
    "id": "NsyRqbMIcPDs",
    "outputId": "8b4525e9-957e-4e87-a6c2-6c5adc5c5bf3"
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "sns.set(rc={'figure.figsize': (16, 6)})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "p1zSLOclcPDx"
   },
   "outputs": [],
   "source": [
    "data_train = data_by_station[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 0
    },
    "colab_type": "code",
    "id": "HlgXhiyccPD1",
    "outputId": "6cb3320d-c5f7-4fb3-ba95-660330aff0bf"
   },
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tamb</th>\n",
       "      <th>pres</th>\n",
       "      <th>prec</th>\n",
       "      <th>rad</th>\n",
       "      <th>vvien</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fecha</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-01-01 01:00:00</th>\n",
       "      <td>11.6</td>\n",
       "      <td>1017.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-01 01:10:00</th>\n",
       "      <td>10.9</td>\n",
       "      <td>1017.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-01 01:30:00</th>\n",
       "      <td>10.3</td>\n",
       "      <td>1016.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-01 01:40:00</th>\n",
       "      <td>10.0</td>\n",
       "      <td>1016.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-01 02:00:00</th>\n",
       "      <td>10.2</td>\n",
       "      <td>1017.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.8</td>\n",
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       "      <th>...</th>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-01 18:30:00</th>\n",
       "      <td>27.0</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>578.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-01 18:40:00</th>\n",
       "      <td>26.0</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>544.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-01 19:00:00</th>\n",
       "      <td>26.0</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>471.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-01 19:10:00</th>\n",
       "      <td>25.0</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>402.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-01 19:30:00</th>\n",
       "      <td>21.0</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>254.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>11573 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     tamb    pres  prec    rad  vvien\n",
       "fecha                                                \n",
       "2019-01-01 01:00:00  11.6  1017.0   0.0    0.0    1.0\n",
       "2019-01-01 01:10:00  10.9  1017.0   0.0    0.0    0.7\n",
       "2019-01-01 01:30:00  10.3  1016.9   0.0    0.0    1.3\n",
       "2019-01-01 01:40:00  10.0  1016.9   0.0    0.0    1.7\n",
       "2019-01-01 02:00:00  10.2  1017.0   0.0    0.0    0.8\n",
       "...                   ...     ...   ...    ...    ...\n",
       "2019-06-01 18:30:00  27.0  1003.0   0.0  578.0    1.0\n",
       "2019-06-01 18:40:00  26.0  1003.0   0.0  544.0    2.0\n",
       "2019-06-01 19:00:00  26.0  1003.0   0.0  471.0    2.0\n",
       "2019-06-01 19:10:00  25.0  1003.0   0.0  402.0    3.0\n",
       "2019-06-01 19:30:00  21.0  1003.0   0.0  254.0    2.0\n",
       "\n",
       "[11573 rows x 5 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "4XriK_hZcPD8"
   },
   "outputs": [],
   "source": [
    "data_train = data_train.resample('30T').mean().ffill()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "JED6zkzjcPEy"
   },
   "outputs": [],
   "source": [
    "data_train = data_train.drop(columns=['prec', 'vvien'])"
   ]
  },
  {
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   "execution_count": 16,
   "metadata": {
    "colab": {
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    "id": "6eOHb2QfcPE2",
    "outputId": "ed407c68-515c-439f-ea98-6e0772410386"
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   "outputs": [
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   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
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       "                      tamb     pres    rad  day  month\n",
       "fecha                                                 \n",
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       "2019-06-01 19:30:00  21.00  1003.00  254.0    1      6\n",
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       "[7286 rows x 5 columns]"
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     "execution_count": 17,
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   "source": [
    "data_train['day']=[x.day for x in data_train.index]\n",
    "data_train['month']=[x.month for x in data_train.index]\n",
    "data_train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 0
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    "colab_type": "code",
    "id": "zX_n7QKVcPE_",
    "outputId": "24eccb51-d5b0-4edf-9747-1d59a9bd43d8"
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    {
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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_train = data_train.loc[:'2019-05-01']\n",
    "\n",
    "plt.plot(data_train['rad'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "CFZ7ChKkcPFD"
   },
   "source": [
    "# II Preparación del conjunto de datos para el entrenamiento de una red neuronal recurrente."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "zPOV0Z_JcPFD"
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import tensorflow as tf\n",
    "\n",
    "np.random.seed(1)\n",
    "tf.random.set_seed(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "MTJSDLDZcPFI"
   },
   "outputs": [],
   "source": [
    "def series_to_supervised(data, n_in=1, n_out=1, dropnan=True):\n",
    "    n_vars = 1 if type(data) is list else data.shape[1]\n",
    "    dff = pd.DataFrame(data)\n",
    "    cols, names = list(), list()\n",
    "    \n",
    "    # input sequence (t-n, ... t-1)\n",
    "    for i in range(n_in, 0, -1):\n",
    "        cols.append(dff.shift(i))\n",
    "        names += [('var%d(t-%d)' % (j+1, i)) for j in range(n_vars)]\n",
    "    \n",
    "    # forecast sequence (t, t+1, ... t+n)\n",
    "    for i in range(0, n_out):\n",
    "        cols.append(dff.shift(-i))\n",
    "        if i == 0:\n",
    "            names += [('var%d(t)' % (j+1)) for j in range(n_vars)]\n",
    "        else:\n",
    "            names += [('var%d(t+%d)' % (j+1, i)) for j in range(n_vars)]\n",
    "\n",
    "    # put it all together\n",
    "    agg = pd.concat(cols, axis=1)\n",
    "    agg.columns = names\n",
    "    # drop rows with NaN values\n",
    "    if dropnan:\n",
    "        agg.dropna(inplace=True)\n",
    "    \n",
    "    return agg\n",
    "\n",
    "def get_rnn_dataset(data, past_history=10, forecast_horizon=1):\n",
    "    n_vars = data.shape[1]\n",
    "    values = series_to_supervised(data, past_history, forecast_horizon).values\n",
    "    train_X, train_y = values[:, :-1*n_vars*forecast_horizon], values[:, n_vars*past_history+2::n_vars]\n",
    "    \n",
    "    return train_X, train_y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 0
    },
    "colab_type": "code",
    "id": "dQAfo0r3cPFL",
    "outputId": "b2384ef5-1178-4df4-d320-10fe128c804a"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Past history 336 , 7 day\n",
      "Forecast horizon 48 , 1 day\n"
     ]
    }
   ],
   "source": [
    "one_day_min = 24*60\n",
    "\n",
    "interval_min = 30\n",
    "past_day = 7\n",
    "forecast_day = 1\n",
    "\n",
    "past_history = int((one_day_min / interval_min) * past_day)\n",
    "forecast_horizon = int((one_day_min / interval_min) * forecast_day)\n",
    "\n",
    "print(\"Past history {0} , {1} day\".format(past_history, past_day))\n",
    "print(\"Forecast horizon {0} , {1} day\".format(forecast_horizon, forecast_day))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Scaler:\n",
    "    def fit(self, data):\n",
    "        self._min = data.min()\n",
    "        self._max = data.max()\n",
    "    \n",
    "    def normalize(self, data):\n",
    "        return (data - self._min) / (self._max - self._min)\n",
    "    \n",
    "    def denormalize(self, data):\n",
    "        return data*(self._max-self._min)+self._min"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "rVkO7qN1cPFh"
   },
   "outputs": [],
   "source": [
    "data_test = data_by_station[1]\n",
    "data_test = data_test.resample('30T').mean().ffill()\n",
    "data_test = data_test.drop(columns=['prec', 'vvien'])\n",
    "\n",
    "data_test['day']=[x.day for x in data_test.index]\n",
    "data_test['month']=[x.month for x in data_test.index]\n",
    "\n",
    "data_test = data_test.loc[:'2019-05-01']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "### TRAIN\n",
    "tamb_scaler = Scaler()\n",
    "tamb_scaler.fit(data_train['tamb'])\n",
    "\n",
    "pres_scaler = Scaler()\n",
    "pres_scaler.fit(data_train['pres'])\n",
    "\n",
    "rad_scaler = Scaler()\n",
    "rad_scaler.fit(data_train['rad'])\n",
    "\n",
    "weekday_scaler = Scaler()\n",
    "weekday_scaler.fit(data_train['day'])\n",
    "\n",
    "month_scaler = Scaler()\n",
    "month_scaler.fit(data_train['month'])\n",
    "\n",
    "### TEST\n",
    "tamb_scaler_t = Scaler()\n",
    "tamb_scaler_t.fit(data_test['tamb'])\n",
    "\n",
    "pres_scaler_t = Scaler()\n",
    "pres_scaler_t.fit(data_test['pres'])\n",
    "\n",
    "rad_scaler_t = Scaler()\n",
    "rad_scaler_t.fit(data_test['rad'])\n",
    "\n",
    "weekday_scaler_t = Scaler()\n",
    "weekday_scaler_t.fit(data_train['day'])\n",
    "\n",
    "month_scaler_t = Scaler()\n",
    "month_scaler_t.fit(data_train['month'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_train = data_train.values\n",
    "data_test = data_test.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_train[:, 0] = tamb_scaler.normalize(data_train[:, 0])\n",
    "data_train[:, 1] = pres_scaler.normalize(data_train[:, 1])\n",
    "data_train[:, 2] = rad_scaler.normalize(data_train[:, 2])\n",
    "data_train[:, 3] = weekday_scaler.normalize(data_train[:, 3])\n",
    "data_train[:, 4] = month_scaler.normalize(data_train[:, 4])\n",
    "\n",
    "\n",
    "data_test[:, 0] = tamb_scaler_t.normalize(data_test[:, 0])\n",
    "data_test[:, 1] = pres_scaler_t.normalize(data_test[:, 1])\n",
    "data_test[:, 2] = rad_scaler_t.normalize(data_test[:, 2])\n",
    "data_test[:, 3] = weekday_scaler_t.normalize(data_test[:, 3])\n",
    "data_test[:, 4] = month_scaler_t.normalize(data_test[:, 4])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "#from sklearn.preprocessing import MinMaxScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "#scaler = MinMaxScaler(feature_range=(-1, 1))\n",
    "#scaler_t = MinMaxScaler(feature_range=(-1, 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "#data_train = scaler.fit_transform(data_train)\n",
    "#data_test = scaler_t.fit_transform(data_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_train = series_to_supervised(data_train, past_history, forecast_horizon)\n",
    "data_test = series_to_supervised(data_test, past_history, forecast_horizon)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "in_vars = []\n",
    "\n",
    "for v in range(1,4):\n",
    "    for i in range(past_history, 0, -1):\n",
    "        in_vars.append(('var%d(t-%d)' % (v,i)))\n",
    "\n",
    "\n",
    "rad_var = []\n",
    "\n",
    "for i in range(past_history, 0, -1):\n",
    "    rad_var.append(('var3(t-%d)' % i))\n",
    "        \n",
    "day_var = []\n",
    "\n",
    "for i in range(past_history, 0, -1):\n",
    "    day_var.append(('var4(t-%d)' % i))\n",
    "        \n",
    "month_var = []\n",
    "\n",
    "for i in range(past_history, 0, -1):\n",
    "    month_var.append(('var5(t-%d)' % i))\n",
    "\n",
    "target_var = []\n",
    "\n",
    "for i in range(0, forecast_horizon):\n",
    "    if i == 0:\n",
    "        target_var.append('var3(t)')\n",
    "    else:\n",
    "        target_var.append(('var3(t+%d)' % i))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>var1(t-336)</th>\n",
       "      <th>var1(t-335)</th>\n",
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       "    <tr>\n",
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       "      <td>0.256410</td>\n",
       "      <td>...</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5423 rows × 1008 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      var1(t-336)  var1(t-335)  var1(t-334)  var1(t-333)  var1(t-332)  \\\n",
       "336      0.371795     0.315385     0.323077     0.328205     0.279487   \n",
       "337      0.315385     0.323077     0.328205     0.279487     0.315385   \n",
       "338      0.323077     0.328205     0.279487     0.315385     0.356410   \n",
       "339      0.328205     0.279487     0.315385     0.356410     0.374359   \n",
       "340      0.279487     0.315385     0.356410     0.374359     0.397436   \n",
       "...           ...          ...          ...          ...          ...   \n",
       "5754     0.358974     0.307692     0.307692     0.307692     0.307692   \n",
       "5755     0.307692     0.307692     0.307692     0.307692     0.307692   \n",
       "5756     0.307692     0.307692     0.307692     0.307692     0.307692   \n",
       "5757     0.307692     0.307692     0.307692     0.307692     0.307692   \n",
       "5758     0.307692     0.307692     0.307692     0.307692     0.256410   \n",
       "\n",
       "      var1(t-331)  var1(t-330)  var1(t-329)  var1(t-328)  var1(t-327)  ...  \\\n",
       "336      0.315385     0.356410     0.374359     0.397436     0.389744  ...   \n",
       "337      0.356410     0.374359     0.397436     0.389744     0.392308  ...   \n",
       "338      0.374359     0.397436     0.389744     0.392308     0.402564  ...   \n",
       "339      0.397436     0.389744     0.392308     0.402564     0.374359  ...   \n",
       "340      0.389744     0.392308     0.402564     0.374359     0.320513  ...   \n",
       "...           ...          ...          ...          ...          ...  ...   \n",
       "5754     0.307692     0.307692     0.307692     0.256410     0.256410  ...   \n",
       "5755     0.307692     0.307692     0.256410     0.256410     0.230769  ...   \n",
       "5756     0.307692     0.256410     0.256410     0.230769     0.205128  ...   \n",
       "5757     0.256410     0.256410     0.230769     0.205128     0.205128  ...   \n",
       "5758     0.256410     0.230769     0.205128     0.205128     0.256410  ...   \n",
       "\n",
       "      var3(t-10)  var3(t-9)  var3(t-8)  var3(t-7)  var3(t-6)  var3(t-5)  \\\n",
       "336     0.000000   0.000000   0.000000   0.000000   0.000000   0.000000   \n",
       "337     0.000000   0.000000   0.000000   0.000000   0.000000   0.000000   \n",
       "338     0.000000   0.000000   0.000000   0.000000   0.000000   0.000000   \n",
       "339     0.000000   0.000000   0.000000   0.000000   0.000000   0.000000   \n",
       "340     0.000000   0.000000   0.000000   0.000000   0.000000   0.000000   \n",
       "...          ...        ...        ...        ...        ...        ...   \n",
       "5754    0.482090   0.412801   0.286553   0.201409   0.118614   0.110981   \n",
       "5755    0.412801   0.286553   0.201409   0.118614   0.110981   0.065179   \n",
       "5756    0.286553   0.201409   0.118614   0.110981   0.065179   0.032883   \n",
       "5757    0.201409   0.118614   0.110981   0.065179   0.032883   0.009395   \n",
       "5758    0.118614   0.110981   0.065179   0.032883   0.009395   0.000000   \n",
       "\n",
       "      var3(t-4)  var3(t-3)  var3(t-2)  var3(t-1)  \n",
       "336    0.000000   0.000000   0.000000        0.0  \n",
       "337    0.000000   0.000000   0.000000        0.0  \n",
       "338    0.000000   0.000000   0.000000        0.0  \n",
       "339    0.000000   0.000000   0.000000        0.0  \n",
       "340    0.000000   0.000000   0.000000        0.0  \n",
       "...         ...        ...        ...        ...  \n",
       "5754   0.065179   0.032883   0.009395        0.0  \n",
       "5755   0.032883   0.009395   0.000000        0.0  \n",
       "5756   0.009395   0.000000   0.000000        0.0  \n",
       "5757   0.000000   0.000000   0.000000        0.0  \n",
       "5758   0.000000   0.000000   0.000000        0.0  \n",
       "\n",
       "[5423 rows x 1008 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
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       "[5423 rows x 336 columns]"
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     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
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       "</table>\n",
       "<p>5423 rows × 336 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      var5(t-336)  var5(t-335)  var5(t-334)  var5(t-333)  var5(t-332)  \\\n",
       "336          0.00         0.00         0.00         0.00         0.00   \n",
       "337          0.00         0.00         0.00         0.00         0.00   \n",
       "338          0.00         0.00         0.00         0.00         0.00   \n",
       "339          0.00         0.00         0.00         0.00         0.00   \n",
       "340          0.00         0.00         0.00         0.00         0.00   \n",
       "...           ...          ...          ...          ...          ...   \n",
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       "5758         0.75         0.75         0.75         0.75         0.75   \n",
       "\n",
       "      var5(t-331)  var5(t-330)  var5(t-329)  var5(t-328)  var5(t-327)  ...  \\\n",
       "336          0.00         0.00         0.00         0.00         0.00  ...   \n",
       "337          0.00         0.00         0.00         0.00         0.00  ...   \n",
       "338          0.00         0.00         0.00         0.00         0.00  ...   \n",
       "339          0.00         0.00         0.00         0.00         0.00  ...   \n",
       "340          0.00         0.00         0.00         0.00         0.00  ...   \n",
       "...           ...          ...          ...          ...          ...  ...   \n",
       "5754         0.75         0.75         0.75         0.75         0.75  ...   \n",
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       "5758         0.75         0.75         0.75         0.75         0.75  ...   \n",
       "\n",
       "      var5(t-10)  var5(t-9)  var5(t-8)  var5(t-7)  var5(t-6)  var5(t-5)  \\\n",
       "336         0.00       0.00       0.00       0.00       0.00       0.00   \n",
       "337         0.00       0.00       0.00       0.00       0.00       0.00   \n",
       "338         0.00       0.00       0.00       0.00       0.00       0.00   \n",
       "339         0.00       0.00       0.00       0.00       0.00       0.00   \n",
       "340         0.00       0.00       0.00       0.00       0.00       0.00   \n",
       "...          ...        ...        ...        ...        ...        ...   \n",
       "5754        0.75       0.75       0.75       0.75       0.75       0.75   \n",
       "5755        0.75       0.75       0.75       0.75       0.75       0.75   \n",
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       "5758        0.75       0.75       0.75       0.75       0.75       0.75   \n",
       "\n",
       "      var5(t-4)  var5(t-3)  var5(t-2)  var5(t-1)  \n",
       "336        0.00       0.00       0.00       0.00  \n",
       "337        0.00       0.00       0.00       0.00  \n",
       "338        0.00       0.00       0.00       0.00  \n",
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       "340        0.00       0.00       0.00       0.00  \n",
       "...         ...        ...        ...        ...  \n",
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       "5756       0.75       0.75       0.75       0.75  \n",
       "5757       0.75       0.75       0.75       0.75  \n",
       "5758       0.75       0.75       0.75       0.75  \n",
       "\n",
       "[5423 rows x 336 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_train[month_var]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
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       "      <td>0.219612</td>\n",
       "      <td>0.201409</td>\n",
       "      <td>0.136817</td>\n",
       "      <td>0.052261</td>\n",
       "      <td>0.032296</td>\n",
       "      <td>0.024075</td>\n",
       "      <td>0.001762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5755</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.325895</td>\n",
       "      <td>0.168526</td>\n",
       "      <td>0.219612</td>\n",
       "      <td>0.201409</td>\n",
       "      <td>0.136817</td>\n",
       "      <td>0.052261</td>\n",
       "      <td>0.032296</td>\n",
       "      <td>0.024075</td>\n",
       "      <td>0.001762</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5756</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.168526</td>\n",
       "      <td>0.219612</td>\n",
       "      <td>0.201409</td>\n",
       "      <td>0.136817</td>\n",
       "      <td>0.052261</td>\n",
       "      <td>0.032296</td>\n",
       "      <td>0.024075</td>\n",
       "      <td>0.001762</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5757</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.219612</td>\n",
       "      <td>0.201409</td>\n",
       "      <td>0.136817</td>\n",
       "      <td>0.052261</td>\n",
       "      <td>0.032296</td>\n",
       "      <td>0.024075</td>\n",
       "      <td>0.001762</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5758</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.201409</td>\n",
       "      <td>0.136817</td>\n",
       "      <td>0.052261</td>\n",
       "      <td>0.032296</td>\n",
       "      <td>0.024075</td>\n",
       "      <td>0.001762</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5423 rows × 48 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      var3(t)  var3(t+1)  var3(t+2)  var3(t+3)  var3(t+4)  var3(t+5)  \\\n",
       "336       0.0        0.0        0.0        0.0        0.0        0.0   \n",
       "337       0.0        0.0        0.0        0.0        0.0        0.0   \n",
       "338       0.0        0.0        0.0        0.0        0.0        0.0   \n",
       "339       0.0        0.0        0.0        0.0        0.0        0.0   \n",
       "340       0.0        0.0        0.0        0.0        0.0        0.0   \n",
       "...       ...        ...        ...        ...        ...        ...   \n",
       "5754      0.0        0.0        0.0        0.0        0.0        0.0   \n",
       "5755      0.0        0.0        0.0        0.0        0.0        0.0   \n",
       "5756      0.0        0.0        0.0        0.0        0.0        0.0   \n",
       "5757      0.0        0.0        0.0        0.0        0.0        0.0   \n",
       "5758      0.0        0.0        0.0        0.0        0.0        0.0   \n",
       "\n",
       "      var3(t+6)  var3(t+7)  var3(t+8)  var3(t+9)  ...  var3(t+38)  var3(t+39)  \\\n",
       "336         0.0        0.0        0.0        0.0  ...    0.000000    0.000000   \n",
       "337         0.0        0.0        0.0        0.0  ...    0.000000    0.000000   \n",
       "338         0.0        0.0        0.0        0.0  ...    0.000000    0.000000   \n",
       "339         0.0        0.0        0.0        0.0  ...    0.000000    0.000000   \n",
       "340         0.0        0.0        0.0        0.0  ...    0.000000    0.000000   \n",
       "...         ...        ...        ...        ...  ...         ...         ...   \n",
       "5754        0.0        0.0        0.0        0.0  ...    0.368761    0.325895   \n",
       "5755        0.0        0.0        0.0        0.0  ...    0.325895    0.168526   \n",
       "5756        0.0        0.0        0.0        0.0  ...    0.168526    0.219612   \n",
       "5757        0.0        0.0        0.0        0.0  ...    0.219612    0.201409   \n",
       "5758        0.0        0.0        0.0        0.0  ...    0.201409    0.136817   \n",
       "\n",
       "      var3(t+40)  var3(t+41)  var3(t+42)  var3(t+43)  var3(t+44)  var3(t+45)  \\\n",
       "336     0.000000    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
       "337     0.000000    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
       "338     0.000000    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
       "339     0.000000    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
       "340     0.000000    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
       "...          ...         ...         ...         ...         ...         ...   \n",
       "5754    0.168526    0.219612    0.201409    0.136817    0.052261    0.032296   \n",
       "5755    0.219612    0.201409    0.136817    0.052261    0.032296    0.024075   \n",
       "5756    0.201409    0.136817    0.052261    0.032296    0.024075    0.001762   \n",
       "5757    0.136817    0.052261    0.032296    0.024075    0.001762    0.000000   \n",
       "5758    0.052261    0.032296    0.024075    0.001762    0.000000    0.000000   \n",
       "\n",
       "      var3(t+46)  var3(t+47)  \n",
       "336     0.000000    0.000000  \n",
       "337     0.000000    0.000000  \n",
       "338     0.000000    0.000000  \n",
       "339     0.000000    0.000000  \n",
       "340     0.000000    0.000000  \n",
       "...          ...         ...  \n",
       "5754    0.024075    0.001762  \n",
       "5755    0.001762    0.000000  \n",
       "5756    0.000000    0.000000  \n",
       "5757    0.000000    0.000000  \n",
       "5758    0.000000    0.000000  \n",
       "\n",
       "[5423 rows x 48 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_train[target_var]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 0
    },
    "colab_type": "code",
    "id": "9lISh8bJcPFl",
    "outputId": "039c1f43-b718-4f4f-8953-27e7b280b6ca"
   },
   "outputs": [],
   "source": [
    "#%%time\n",
    "#data, labels = get_rnn_dataset(data_train, past_history=past_history, forecast_horizon=forecast_horizon)\n",
    "#data_test, labels_test = get_rnn_dataset(data_test, past_history=past_history, forecast_horizon=forecast_horizon)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 0
    },
    "colab_type": "code",
    "id": "IpJ_EDCucPFp",
    "outputId": "e38bc0c6-994b-4b48-bcf4-8b667239ed5c"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((5423, 1920), (5425, 1920))"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_train.shape, data_test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "#data = data.reshape((data.shape[0], 1, data.shape[1]))\n",
    "#data_test = data_test.reshape((data_test.shape[0], 1, data_test.shape[1]))\n",
    "#data.shape, data_test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 0
    },
    "colab_type": "code",
    "id": "ZOxWVj47cPFt",
    "outputId": "b635228b-2d86-4bca-9c12-c0d20212cc50"
   },
   "outputs": [],
   "source": [
    "#labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "0gdGLi1IcPFz"
   },
   "outputs": [],
   "source": [
    "def plot_result(x, y, y_pred=None):\n",
    "    fig, ax = plt.subplots(1, 1, figsize=(15,5))\n",
    "    ax.plot(x, 'o-', c='steelblue', ms=3.5, label='History')\n",
    "    ax.plot([m for m in range(int(x.shape[0]), \n",
    "                              int(x.shape[0]+y.shape[0]))], y, 'x-', c='mediumseagreen', ms=3.5, label='Target')\n",
    "    \n",
    "    if y_pred is not None:\n",
    "        ax.plot([m for m in range(int(x.shape[0]), \n",
    "                              int(x.shape[0]+y.shape[0]))], y_pred, 'o-', c='salmon', ms=3.5, label='Predict')\n",
    "        \n",
    "    ax.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1008,)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_train.iloc[0][in_vars].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(336,)"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_train.iloc[0][rad_var].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(48,)"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_train.iloc[0][target_var].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_result(data_train.iloc[0][rad_var].values, data_train.iloc[0][target_var].values)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "-e43OEMNcPGA"
   },
   "source": [
    "# III Construcción del modelo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "G0fbXz3hcPGD"
   },
   "outputs": [],
   "source": [
    "import datetime\n",
    "from tensorflow.keras.models import Model\n",
    "from tensorflow.keras.layers import Dense, Flatten, Embedding, concatenate, Input\n",
    "from tensorflow.keras.losses import mae\n",
    "from tensorflow.keras.callbacks import EarlyStopping, TensorBoard"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "L9NTC0NvcPGN"
   },
   "source": [
    "### FF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_model(past_history, forecast_horizon):\n",
    "    emb_dias = 2 #tamanio profundidad de embeddings\n",
    "    emb_meses = 4\n",
    "\n",
    "    in_dias = Input(shape=past_history, name = 'dias')\n",
    "    emb_dias = Embedding(31+1, emb_dias)(in_dias)\n",
    "    \n",
    "    in_meses = Input(shape=past_history, name = 'meses')\n",
    "    emb_meses = Embedding(12+1, emb_meses)(in_meses)\n",
    "\n",
    "    in_cli = Input(shape=past_history*3, name = 'cli')\n",
    "\n",
    "    fe = concatenate([(emb_dias), (emb_meses)])\n",
    "\n",
    "    x = Flatten()(fe)\n",
    "    x = concatenate([(x), (in_cli)])\n",
    "    x = Dense(512,activation='sigmoid')(x)\n",
    "    x = Dense(256,activation='sigmoid')(x)\n",
    "    \n",
    "    outp = Dense(forecast_horizon,activation='sigmoid')(x)\n",
    "    \n",
    "    model = Model(inputs=[in_dias,in_meses,in_cli], outputs=outp)\n",
    "\n",
    "    model.compile(loss='mae', optimizer='adam')\n",
    "\n",
    "    model.summary()\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 221
    },
    "colab_type": "code",
    "id": "5z4x_QpHcPGO",
    "outputId": "9140932a-eaee-4183-b85d-2ec3445e7009"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"functional_1\"\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "dias (InputLayer)               [(None, 336)]        0                                            \n",
      "__________________________________________________________________________________________________\n",
      "meses (InputLayer)              [(None, 336)]        0                                            \n",
      "__________________________________________________________________________________________________\n",
      "embedding (Embedding)           (None, 336, 2)       64          dias[0][0]                       \n",
      "__________________________________________________________________________________________________\n",
      "embedding_1 (Embedding)         (None, 336, 4)       52          meses[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "concatenate (Concatenate)       (None, 336, 6)       0           embedding[0][0]                  \n",
      "                                                                 embedding_1[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "flatten (Flatten)               (None, 2016)         0           concatenate[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "cli (InputLayer)                [(None, 1008)]       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "concatenate_1 (Concatenate)     (None, 3024)         0           flatten[0][0]                    \n",
      "                                                                 cli[0][0]                        \n",
      "__________________________________________________________________________________________________\n",
      "dense (Dense)                   (None, 512)          1548800     concatenate_1[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "dense_1 (Dense)                 (None, 256)          131328      dense[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "dense_2 (Dense)                 (None, 48)           12336       dense_1[0][0]                    \n",
      "==================================================================================================\n",
      "Total params: 1,692,580\n",
      "Trainable params: 1,692,580\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model = make_model(past_history, forecast_horizon)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "log_dir = \"logs/fit/\" + datetime.datetime.now().strftime(\"%Y%m%d-%H%M%S\")\n",
    "tensorboard_callback = TensorBoard(log_dir=log_dir, histogram_freq=1)\n",
    "earlyStopping = EarlyStopping(monitor='val_loss', mode='min', patience=10, restore_best_weights=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 731
    },
    "colab_type": "code",
    "id": "YGYLZniucPGW",
    "outputId": "40bdce69-977e-4bcf-a460-52ee8d5339f5"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From /usr/lib/python3.8/site-packages/tensorflow/python/ops/summary_ops_v2.py:1277: stop (from tensorflow.python.eager.profiler) is deprecated and will be removed after 2020-07-01.\n",
      "Instructions for updating:\n",
      "use `tf.profiler.experimental.stop` instead.\n",
      "WARNING:tensorflow:Callbacks method `on_train_batch_end` is slow compared to the batch time (batch time: 0.0167s vs `on_train_batch_end` time: 0.0460s). Check your callbacks.\n",
      "CPU times: user 6min 39s, sys: 3min 53s, total: 10min 33s\n",
      "Wall time: 3min 3s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "history = model.fit([data_train[day_var].values, data_train[month_var].values, data_train[in_vars].values], \n",
    "                    data_train[target_var].values, epochs=100, \n",
    "                    validation_data=(\n",
    "                        [data_test[day_var].values, data_test[month_var].values, data_test[in_vars].values], \n",
    "                        data_test[target_var].values\n",
    "                    ), \n",
    "                    verbose=0, callbacks=[earlyStopping, tensorboard_callback])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 377
    },
    "colab_type": "code",
    "id": "m7FXgTEJcPGd",
    "outputId": "1a06a436-8053-41e3-cde2-5c51969f84a4"
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(history.history['loss'], label='loss')\n",
    "plt.plot(history.history['val_loss'], label='val_loss')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "colab_type": "code",
    "id": "P41icjgXcPGi",
    "outputId": "07e83402-ef6e-4932-f2e7-d267e3eec873"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 3.03 s, sys: 1.96 s, total: 4.99 s\n",
      "Wall time: 1.83 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "y_pred = model.predict([data_test[day_var].values, data_test[month_var].values, data_test[in_vars].values])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 949
    },
    "colab_type": "code",
    "id": "5s2opvk2cPGo",
    "outputId": "4cee8696-52f1-4096-96e5-34dc7d8e72d7"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MAE: 48.95309829711914\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "yp = rad_scaler_t.denormalize(y_pred)\n",
    "y = rad_scaler_t.denormalize(data_test[target_var].values)\n",
    "x = rad_scaler_t.denormalize(data_test[rad_var].values)\n",
    "\n",
    "error = np.mean(mae(y, yp))\n",
    "\n",
    "print(\"MAE: {}\".format(error))\n",
    "\n",
    "for _ in range(3):\n",
    "    i = np.random.randint(len(data_test))\n",
    "    plot_result(x[i], y[i], yp[i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.save('models/embedding_512.h5')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "err = mae(y, yp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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jq+aa1ED6TKoMaPpkbBIRERERTRAGqUTkO1ZKb9qaVMgydI3pvkRERESljEEqEfmPKJyUviZVVqzKv0RERERUmhikEpHv6F5rUmXJSgUmIiIiotLEIJWIfEf36pMqy5xJJSIiIipxDFKJyH+sFjRphyhZ4ZpUIiIiohLHIJWIfCeV7htw3M6ZVCIiIqLSxyCViHxHV5OAJBlBqY0ky9DZgoaIiIiopDFIJSLf0ZNqZtEkAJBlgOm+RERERCWNQSoR+Y+qAh5Bqs50XyIiIqKSxiCViHxHV91nUiWFa1KJiIiISh2DVCLyHa8gFZIM6Dp0netSiYiIiEoVg1Qi8h3dI93XClw5m0pERERUshikEpH/qCqkQCDjZlHtl71SiYiIiEoXg1Qi8h3PdF/RkoZtaIiIiIhKFoNUIvIdXU26F04SM6kqZ1KJiIiIShWDVCLyndwzqVyTSkRERFSqGKQSke/oSRVQsqxJ1RmkEhEREZUqBqlE5D+5ZlJVBqlEREREpYpBKhH5jveaVOM2nem+RERERCWLQSoR+U7uNaksnERERERUqhikEpHv6KoKZKvuyxY0RERERCWLQSoR+Y+qQgpkFk6Cwuq+RERERKWOQSoR+Y5Xuq8kiZlUpvsSERERlSoGqUTkO55rUjmTSkRERFTyGKQSkf/kXJPKIJWIiIioVDFIJSLf8ZxJlTiTSkRERFTqXCqTZDr99NPR2toKWZYRiURw8cUXY8mSJdi8eTNWrFiB3t5e1NbWYuXKlZg/fz4AZL2PiCgbzz6p5m26yjWpRERERKUqr5nUlStX4sEHH8SqVavwta99DRdccAEA4NJLL8Xy5cvx6KOPYvny5bjkkkus38l2HxFRNnoyV59UtqAhIiIiKlV5BalVVVXWvwcHByFJErq6urB27VosXboUALB06VKsXbsW3d3dWe8jIsrF6JOamehhrUnVme5LREREVKrySvcFgAsvvBDPPvssdF3H7bffjra2NjQ3N0MxZzsURUFTUxPa2tqg67rnffX19cX5S4iodHik+1ozqUz3JSIiIipZeQepV111FQBg1apVuOaaa3DOOecUbaOEhobKor/GeDQ2VuV+ENEocb8C1mkaKqrKM96L/s4qtAKoqS5DLd+nUeF+RYXGfYqKgfsVFRr3qakp7yBVOP7443HJJZdg5syZ2L17N1RVhaIoUFUV7e3taGlpga7rnveNRlfXIDSfrj1rbKxCR8fAZG8GlRjuV2Z7GU1DNK5lvBfRvigAoLd7EIlp/j6NBvcrKjTuU1QM3K+o0LhP+ZssS56TkjnXpA4NDaGtrc36+YknnkBNTQ0aGhqwZMkSrF69GgCwevVqLFmyBPX19VnvIyLKRlTuda3uyz6pRERERCUv50xqNBrFOeecg2g0ClmWUVNTg1tvvRWSJOGyyy7DihUrcMstt6C6uhorV660fi/bfUREnsR6U7c1qeI2BqlEREREJStnkDpjxgz86U9/cr1v0aJFuO+++0Z9HxGRl6wzqZKYSWXhJCIiIqJSlVcLGiKiiZItSIXCPqlEREREpY5BKhH5ip4l3Te1JpUzqURERESlikEqEfmLmgTgMZMqiZlUrkklIiIiKlUMUonIV7KuSVVY3ZeIiIio1DFIJSJfSQWpLnXdzHRfqAxSiYiIiEoVg1Qi8pesa1KN23SdQSoRERFRqWKQSkS+krW6rzWTysJJRERERKWKQSoR+UrWNalWdV+2oCEiIiIqVQxSichX8ppJZQsaIiIiopLFIJWI/CWvPqlck0pERERUqhikEpGv6Nn6pMrsk0pERERU6hikEpGv6Ml81qQySCUiIiIqVQxSichX8lqTqrNwEhEREVGpYpBKRP6Sz5pUtqAhIiIiKlkMUonIV7LOpALGbCrTfYmIiIhKFoNUIvKVXEGqJMtck0pERERUwhikEpGvWKm8SsD9AbIM6AxSiYiIiEoVg1Qi8hctn5lUFk4iIiIiKlUMUonIV/Jak8rCSUREREQli0EqEflKPkGqznRfIiIiopLFIJWI/CVLCxoAkCRW9yUiIiIqZQxSichX8ppJZZBKREREVLIYpBKRr+hqEpAkSLL74UlSZEBlkEpERERUqhikEpGv6EnVexYV4JpUIiIiohLHIJWI/EVVPdejAlyTSkRERFTqGKQSka/oau6ZVAapRERERKWLQSoR+UquIFVSWDiJiIiIqJQxSCUiX9FzpPtCYpBKREREVMoYpBKRv+SaSWW6LxEREVFJY5BKRL5ipPsGvB/AIJWIiIiopDFIJSJf0dVkzplUpvsSERERlS4GqUTkKznXpMoyoOkTt0FERERENKEYpBKRv+SxJlXX1AncICIiIiKaSAxSichX2CeViIiIaHpjkEpEvpKzTyrXpBIRERGVNAapROQrea1J1RmkEhEREZUqBqlE5C/5zKSqDFKJiIiIShWDVCLyFa5JJSIiIpreGKQSka8YQWrA+wFck0pERERU0hikEpGv6Goy65pUiWtSiYiIiEoag1Qi8hdW9yUiIiKa1hikEpGv5LUmlYWTiIiIiEoWg1Qi8hVdVSEFsgepOtN9iYiIiEoWg1Qi8pVcfVIlidV9iYiIiEoZg1Qi8pc80n25JpWIiIiodDFIJSJfybUmVVI4k0pERERUyhikEpGvsE8qERER0fTGIJWIfEPXdYBrUomIiIimtSzTFUREE0xVASB3CxoGqUREU0aytxet112DZF8faj9yBGZ85nOTvUlE5HOcSSUi39DzCFIlpvsSEU0pPY8/hnjbTmjDQxh87dXJ3hwimgIYpBKRb+QTpHImlYhoaolt3Yrw/AWoO/oTSOzeZSztICLKgkEqEfmHGaQi4L0SgTOpRERTS7xjN0LNzQjU1EJPJqGNjEz2JhGRz+UMUnt6evD1r38dRx99NI499liceeaZ6O7uBgBs3rwZJ5xwAo4++miccMIJ2LJli/V72e4jInLDmVQiotKjRaOQIxWQIxXGz0ODk7xFROR3OYNUSZJw6qmn4tFHH8VDDz2EuXPn4tprrwUAXHrppVi+fDkeffRRLF++HJdccon1e9nuIyJyk++aVACcTSUimiL0RAJyMAilwghS1eHhSd4iIvK7nEFqbW0tDj30UOvnAw88EDt37kRXVxfWrl2LpUuXAgCWLl2KtWvXoru7O+t9RERe8p5JBTibSkQ0Bei6Dj2RgBQKQq4QM6lDk7xVROR3o2pBo2ka7r33Xhx55JFoa2tDc3MzFPNiUlEUNDU1oa2tDbque95XX19f+L+CiEqDmjT+n+dMqjQR20RERGOmJ5OArkMKhiCXlQEA16QSUU6jClJ/+MMfIhKJ4Mtf/jLWrl1brG2yNDRUFv01xqOxsWqyN4FK0HTer4aGjAuYmrpKzPB4H2JV5egEMKM+AqW8fAK3bmqbzvsVFQf3KcpHcmgIGwBU1VWidkY1tgGoqgh5HuO5X1GhcZ+amvIOUleuXImtW7fi1ltvhSzLaGlpwe7du6GqKhRFgaqqaG9vR0tLC3Rd97xvNLq6BqFp/ixT3thYhY6OgcneDCox032/GunsBwAMDCWge7wPw9EEAKCjvR9KJDlh2zaVTff9igqP+xTlK9nXCwAYjulAfwwA0Ncz4HqM535FhcZ9yt9kWfKclMyrBc3111+PNWvW4Oabb0YoFAIANDQ0YMmSJVi9ejUAYPXq1ViyZAnq6+uz3kdE5IVrUomISoseNwYWpVAQUsA4tutJDjASUXY5Z1LXr1+PW2+9FfPnz8cXvvAFAMCcOXNw880347LLLsOKFStwyy23oLq6GitXrrR+L9t9RERurAuXfNak6gxSiYj8TkuYQWowCMnsgS0GJImIvOQMUvfaay+88847rvctWrQI991336jvIyJyNZqZVJVBKhGR3+lJI0iVg8HUACRnUokoh7zSfYmIJsJo0n3ZJ5WIaAoQx2pJhqSYM6lJzqQSUXYMUonIN/IJUkW6L5juS0Tkf7pZAFOWbOm+nEklouwYpBKRb1jrlLLNpEqcSSUimip0EaRCsgYguSaViHJhkEpE/mHNpHovl5cUVvclIpoyzCBVkiRjuYYksbovEeXEIJWIfEOkgOW1JpWFk4iIpg5JgiQZs6kMUokoFwapROQbXJNKRFRiNDPdV5KM/ysBpvsSUU4MUonIN0azJpXpvkREU4Hu+EkKKAALJxFRDgxSicg/RjGTysJJRET+JwoniWM3032JKB8MUonIN/Lqk8rCSUREU4eeNpOqKBxkJKKcGKQSkW9YQWqAM6lERCVBT1uTKsscZCSinBikEpF/cE0qEVFpSQtSJVlhdXYiyolBKhH5hp5Pn1TOpBJRHnb95g6sO/UkDK97Z7I3hYC0mVRW9yWi7BikEpFv6GrS6KUnZzk0yZxJJaLsYjt3oP/ZfwEAht54fZK3ZnqzCieJmVRF5iAjEeXEIJWIfENPqtmLJsFIFQM4k0pE3nqffML6t1JRMYlbMr3pum4rnCRmUlk4iYhyY5BKRP6hqtnXowKAbF7o8CKHiNIk+/owsnkTBl54HhUHvQeArf8yTahEZwc2nvUtDL76P+MG89AtyXKq/gARkQfvhV9ERBNMV/OZSeWaVCLKNPTmGuy4/lrr54alx2Holf8xIJokI9u2QRsZQZ+Y1batSeXxm4hyYZBKRL6RT5DKNalE5Kb3n/8AACi1tWj6/BdRtsd8QJI4kzpJ9HjMeYO1JlXh8ZuIcmKQSkS+oeeR7ss1qUTkRh0cQGTf/TDn3POs2yRFYZA6SbRYPO0W0YKGM6lElBvXpBKRf6gqpECOsTPOpBKRC3VoGEok4rxRCTBInSR6zDmTKsm2FjT8TIgoBwapROQb+a1JNS50OBJPRHba0BDkiLOSr6TIgJqcpC2a3rT0dF9rJpXVfYkoNwapROQbuprkmlQiGjVd16EOD2W0m5ECAehJBqmTQYulr0k1/6/IPH4TUU4MUonIN0ZTOIkj8UQkaCMjgKZBTgtSlcoqJAcGJmmrprf0dF+rcJIsMwWbiHJikEpE/qGqgJJ9TaoonASdQSoRGbShQQDIWJOqVFRAGx6ejE2a9vRkwvGzxBY0RDQKDFKJyDdGNZOq8iKHiAxa3AiI5HCZ8w5ZBnR9EraI9GT6bClb0BBR/hikEpFvjKZwEi9yiMgiiiOlHz8kibN2k0RPL1gl21vQMN2XiLJjkEpEvjGqmVSm+xKRSaxxTG9hJcks0jNZMted2lvQ8DMhouwYpBKRf6hq5kxIGklidV8ichIVfDMGuSSJ6b6TJKOqsmRrQcNBRiLKgUEqEflGXjOp5v2sDklEghWkusykMt13kqgqlJpa60fJ3oKGM6lElAODVCLyjfzWpIqZVP/OjmgjIxh+ay10zuAQTQgr3Tf9+MHCSZNGT6rOvrUS16QSUf4YpBKRb+hqMo81qeZwvI/TxXbcdCNar7sGw2+umexNIZoWrCI96S2sWDhp0uhqEnJ5eeoGqwUNq/sSUW4MUonIP0axJtXPF57R9esAAIOvvjLJW0I0TViFk5zHDxZOmjy6qkIOh2232GZSme5LRDkwSCUi3zDSfQPZHyT7u3CSNjJiXTBHN6yf5K0hmh5ET86M4wfTfSdNxvINyVbdl+m+RJQDg1Qi8o2816RKkm/XNCX7+wEAwRmNiO9ohTYSneQtIip9It03fSZVG4kh3rZzMjZp2tOTSUdmjCTWpCosZjVZdF1H79NPItHRkbqNRQjJpxikEpFv6Hmk+wIwR+L9OTui9vcBACLv2hfQdcR37Z7kLSIqfamZVOfxY3jN6wDAwaLJoKrOasuiui/XpE6aeNtOtP/ut9h9928BAH3/fgbrv3EKkn19k7xlRJkYpBKRf+TTggbGiLxfR+LFTGr5XnsDAOLtuyZzc4imhdRMqvtyAa6BnHh6Muma7ispMmfvJkmivR0AMPzmGqgDA+h66AEAwMALz03mZhG5YpBKRL6RV59UwJxJ9edFpzY4CAAoW7AQAJDYzZlUomKzgh6v44dPjxelLKPGgFiTKhnrhNmia+Kp5vkJAHqffhJ6PAEA6PjTHyZrk4g8MUglIt/IN0iVFMW3M6lqdBgAoNTUIFBfj3g7g1SiokuaM6kexw/O3E08XU2mrREWM6nmbT49hk+E2Pbt6H7k4Ql/XXXICFKlYNCcTTUyf6RQaMK3hSgXBqlE5Au6rufVggaAMRLv08JJWjQKSBLkcBjBpmbOpBJNABGEplf3rf/Uscb9Pj1elDKjxkDmTKokizZi0/cz2Xb1Fej8858mfLBVHRwEFAUV+x9gtUqDJCFQVzeh20GUDwapROQPqnvhEzeSLEOfgMJJajSKpDnSnC8tGoVcVgZJlhFqbuZMKtEE0D2OH8GmZsf9NIHS1qRK9hY0ADAN1gkPv/M2dv3mjozUZj2RcPx/omjDQ1AiEQTrG6zbQrNmQxsantDtIMpHjoaEREQTw2smxJUsFT1VTB0cxMZvnwkAqPvkpzD0+muYd+ElkHOkRWnRYcjlEQDGBbI2OAh1aAhKRUVRt5doOvNakyop0ycg8pvMPqnm/2TjNr8u2Sik1p/8GADQfOJXAXtRL7Ougjo0BDkcnrDt0aIjkMsjCDSkgtTw7NkYaNsJXddTAwlEPsCZVCLyBa8+h67k4vfZG377LevfPX//G+I7WhHbtjXn76nRKOTycgBAqHkmACDOlF+i4tI0QJYzLrLFoNd0Ti2dLHoymVZt2fxsxMDBNAhSBS19xtT823ufeHxityM6DLmsDIG6euu28Nw9jIC5f3RZQ0TFxiCViHzBmkn1aCFhJ01Anz17s3Nh4KUX0fOPRxE3y/i70aJRKJHUTCoAxHe2FmcjiQiAOWsnu1zSWKmlDFInkq5pgK47Z1JlsSbVnEmdRp9JelpvwEy3Dc+bN6HboY2MQI5EELTNpAabGgEAyb7eCd0WolwYpBKRL+jJ/NN9jTWpxb3Aie3YDqW62nFb7+OPoeOP96L1p9d4/p5YkwoAoaYmKJVVGF77ZlG3lWi6yyjSYxJBEvukTiy39GsJzjWp0yHdV9h+9Q8x9Mbr1s8iSLTekwmimuenYGOTdZsSMZaixHfsmNBtIcqFQSoR+YPZQiKv6r5Kcfuk6rqO4bfeQmSfJaj7xDFQampRccCB1v1qb6/37ybiVjl/KRBAeI89kOjMnJUlogJS1dT6U5tUkJqc6C0aleG333L0sJzy3ApZieq+0zDdN9HZgR03/jTj9oneL7URYzmKUlGBuk8cg4bjjkdgxgwAQPejf5/QbSHKhYWTiMgXUmtS85hJVZSipool2ndD7etF+T5LUHv4RzDjM5/D0OuvYei1V40HuKUVmvSk6vgblKoqxHfvKtq2ElGWHstToCdnoqMDrdeuRPVhH8LMk06Z7M0pCDFLKlJ7jR/S0n2nwTrhQH0Dkt1dANLObeZ7oScnNkjVR2KQw0amT+PnPu+4Lzxr1oRuC1EuDFKJyBdSa1LzaEFT9CDVWHManj3HeD1ZhlJVldfv6skEpEDQ+jlQXcOCFERFpmvuPZatnpw+Xf+oaxq2X3M1ACD6zjuTvDUFJAYF7LPbIrPVXJta6hWXk729VoCqVFU7Z03N/XKii+pp8RjkcGaF+mBjo9F/nMhHuEcSkS+IEeW8WtAoAWsNazEkOjsBwFFcIlBdk9fv6olk2kxqNfR4HFosVtiNJKIUVXXO2plS6b7+DFLju9qQ7OkBACQ62ksm5dcadLRnnZhB0HRpQTP8VqoWQe2RR0EbHk6d58yZ1J5HHp6w7dE1DXo8Dink0vJGUYBpMLNNUwuDVCLyBevknc9MqiwX9YSa6OqEFAhAsQWm9iJKejLpeYFlzKTagtRqYwaWs6lExTNV033jbTsdP/c++c9J2pIC08332zZwYHUHstaklnZQpMXj1r9Fn+zBV/6H/v8+b3szJo6oMOzWl1WSlaINGsR27sTue36X2YaHKAcGqUTkC9bIez7VfYud7tvZiUBDg2MWwHFi1zQkPYonpfcGVCqNIDU5MFCUbSUis3qvW+Ekn7Y76X/heWy7+gprFrX+mKUAYBVdm+pENWVnMSuxJnV6VPfVbUGqXFkJAGj75S3Y9atbJyVIFdk8rkGqIhftO9L5lz+h78l/YmTjhqI8P5UuBqlE5A8uLQs8FTlITfZ0O5qdez3GjZ5MQgraglSzZ6oWHS7cBhKRk6q6DnD5Nd131223YmTTJsS2bQMANBx3PCBJJXOcsIoi2dc5isBM9vfsdqHYe6OKwUrrPlsAq+v6xGyPGaS6DoTIStF6CYssotZrV6L3iccx+OorGF5XQuuvqWhYOImIfCGV7pvnTGoR13jq8ZhroSQ5EoE2bFxEaiMjmb+nqkYDe1vhJJlBKlHR6ZpXuq8ZJPksSBUGXn4RcqQCUiAAORyGNlIia9fdZlLTWtD4beCg0Ox1CMrm7eG4L9HVaf1bTyYgBYs/g67Fs82kFi/d135Ob//93da/9779zqK8HpUOzqQSkS/obn31PBQ73VeLxyG7jDYvvO5GzL3gEuMxLkGyW6Atm43S1WEGqUTFoquqa2soK91X98+snTo8ZP1bj8WgmT9LoZBjhm0qc29BY/5/msyk2s8RSmWlI0so2Z3KxNHjE7NWUyxRkcsjGfcV9ZyaT3YUkYucQerKlStx5JFHYvHixVi3bp11++bNm3HCCSfg6KOPxgknnIAtW7bkdR8RjV9sxw50/PlPJbWmZzQzqcVO9zUqIGYGqXIwaFxsANDdZlLN9C7HmlQxk8oglah4PAsniZlU/xwr47vc+ybLobA12zXliXRf28CBZFX3nR4zqY6WM0hV9M14XGJiBibaf/87YzvczrGyXLRBA50Fk2iMcgapRx11FO655x7Mnj3bcfull16K5cuX49FHH8Xy5ctxySWX5HUfEY3Prl/fhq2XXoieRx5GrHX7ZG9OwYgTer6Fk4qZvuc1kwoAcpnRCF0biWbcZ/0NtosAKRQCFIVBKlEReVX3TbU78U9AFNu6xfFz4wlfBFCiM6kuxayswHWC1mJOFj1hnA9avnG6cYNHkKpN0Exq+d6LAQBlCxdl3CfJxRv4dVsaQ5SPnEHqIYccgpaWFsdtXV1dWLt2LZYuNarRLV26FGvXrkV3d3fW+4hofJJ9vej/z7PWz6V08Bd9T/2Q7qvH455rhMR6nuzpvqk1qZIkQSmPMN2XqIg8g1Rr/aN/ZlIT3d2OFMi6jx0NwAhStRIJUq1ZOUe6r1iT6s9iVoWmJxMIzmhE1f+9FwA8zyl6Im70MC1y0B6oqgYUBXIwmHlnEav7aiNRKDW1GbdPVMEomrrGtCa1ra0Nzc3NUMwDjaIoaGpqQltbW9b7iGh84judPfWKWTxoolmpUfkUTpKVos2M6JoGPZHwbAUhhUJGFU7XdF8zSA06/wZ7wSUiKgJNc1/7Zq1/9E9ApEWjUFzWBcqlNJMqagzIMgJ1dcaNYiZREi1o/POZFEN6O7LZ55yL2o9+HMHmZuMGc39t/clKrD/ta+h9/LHibo+qOtqq2UmKUrR0X21kBFUHH4yZp33TeUeJD1LQ+Pm6um9DQ+Vkb0JWjY2Z1T+JxivbftW5znlQrwzLmFEi+2GyLIB2AI3NNQjWZP+beivKMKLrRfkOqrEY1gOoqq/2fP5N5eUIy1rG/UNDRsZITV2V43PZUVWJgBqf1GMGj1dUaH7ap3ZIOkLloYxtSpQBmwBUlAd9s709ehLBygosOOnLSAwMWtvVURVBon/AN9s5Hv0dZdgOoLa+EjOvuRr9b65FU3MNAGCwvwrbAVRXlqHB5W8thb8fADplQCuz7ZONBwHvOwivnH0uEgACkXIkBwahDho9tHv+9hD2Xv65om3PQEiBHAi4vr+d5WHovYU/p+q6jvUjI6isr0Ht/Fmwr8aurylDIFJe0NfzUir71HQzpiC1paUFu3fvhqqqUBQFqqqivb0dLS0t0HXd877R6uoahKb5Mx2gsbEKHR0Dk70ZVGJy7Ve9bZ3Onzt6oZfIfjjQZ1S47OqNQolnT/KIJTSoiURBvoPpaYLqgPGcw3HN8/mlcBhDPf0Z94909AEABoYTjs9FC4YQ7RuYtGMGj1dUaH7bpxKxBKQkMrZJjRprxwf7h32zvcO9/dBDYcgHHoowUtucgIL4UNQ32zkew92DAIC+gRgSUjmk/Q62/q5Yn5GF0tczCC3tb/XbfjUeI8MjUCFn7pOSeb4JlwEDg9btycFBtG3aYaTlFkF0KApdztweAIgnNSTjyYK/91oiDl1VMaLJGNSdrW86d/dCqUx6/GbhlNI+VYpkWfKclBxTum9DQwOWLFmC1atXAwBWr16NJUuWoL6+Put9RDQ+2pARyM0642wAgB4rxTWpefZJLUCqkK5p2PS9c9F+7z3WbWJNmFfhJACQw2Wu/QytNalpa37k8nJo0cxCS0RUIKqaquRrI9Ib+57990RvkSctGrUKsNlJwWDJpPum1qRmKZxUQtXp3ejJpOv6T5ECLIcy+5Um2tsLug2xHTvQ9eAq6Lpupvu613woVuEksSxGLitDoLbWcZ84XxJ5yRmkXnnllTj88MOxa9cunHzyyfjUpz4FALjssstw99134+ijj8bdd9+Nyy+/3PqdbPcR0dipQ0OQAgFE3rUvAECLlcgFDdwr43pSlIIUQkn29UHt70fvP/+R2g6zHYDkcgEhSGVl7mtSPdroKAxSiYrKu3CScVt8R+tEb5InbWQEcnlmmmMptaCxr0lNZxWzKvU1qYmE6/lMBK7huXOhVDrTUAtdu6D12h+j68FVUAcGjO9IwKMwoSIX5fMY2bTJ+IckQw6HUfPhIxCetweAzBY9ROlyXg1edNFFuOiiizJuX7RoEe677z7X38l2HxGNnTo8BLmi0pqpK5ULGsBW6dGjsIOd0YJm/Ce4ZE+P9W91eAhKpMI2k+pSAdEkl5W5zmLrycw+qYDRPF2LsnASUbHomkef1DyOJxNNiw5DbpmVcXsptqCB28ydVcyq9GdSpUhmgSyY2UJyOIzZ55yLbVddYd1V6CrwYvlKsqvT6BXsUT3fOKcW/vNQB/oBACGzjWXziV9F//P/wa7bf2UVGiTy4r+jNxF50oaHoVREjNFpRSmpdBlRCdGr4bldodJ9kz2p1liJ3buN7YjlnkmVw+Hs1X3TZ1IrKqBFoyXfcmG8tJER7Pr1bUh0dEz2ptAUo6uqa0AkyTIq9j/Amr3xAy06AtmlYIxstqApidYcok+q20yqbBzj/dQWqBj0ZNK1Wr34+yErCNQ5l8IVcibVfn2Q6OrMke5bnJnU3Xf+GgAQmpmqSyPOj5xJpVwYpBIVWLKvF4Ovv4bYjtaCX2yoQ0OQIxUAjJQhPTExTcAnRDJpjTDnIikKoOup0fqxvqRtJjW+26g7qCVyr0mVgiHX996tTyoAyBXGZ8Y2NNlF169D/3+exbaVV032ptBUk1QzWj9ZZHncx4pC0mIjrusRpVDICO5KYDDLSvd1WSc8nWZSZbflK2bgLikKlGqjSFJw5kwARkZPodjPb2233oKB/z7v3Ydckov6eSi2GWVxfiylQXYqDl+3oCGaanqfeQrtd99lHexDLbPQ9KUTEdlnSUGeXxsaQsAsQiYFgiV1kPdaU+bKXnhjHOl89pnU+C4jSBXpdl6N1wEjFVgEs3aea1LNIFUdGoRSxVL4XqKbNgIA1N7eyd0QmnL0ZMKz6JrRA9IfgZ+u6559mEXg2v7HezHw/H+w589/MdGbVzi6d7qvmF0t+TWpyUTGgCUASGafWEmWIcky5l14CYKNTdh03rcLOpCZsJ3fLF7n2CIP5NjPieJ1+p/7D8r2mF+U19v169vR/59/o+HTn0XjScuL8hp+pCeT0BIJKC5r3qcizqQSFUhsRyva77oTgZpazPn++Wg68STomoodN1yH4bffKshrqEPGukkAkIIBaw1kKdDVpHdRhzTiYnS86bPJ3h4EZzQi2NyM7tUPQtd1a52v20Wk9foes9hea1KVCqO8ujpUuFHyqULXdcRat+f12GRXqsVSKQ3AUPGJ5QJupAIVWisEcYxwrfoaNo45fU/+01geMIW/A+L9tlJb7ZTpU93XdXZfvCdmwFi2YCGUykrIFRUFrV0Q39WWcZtb+rV1e5HSzENz5jp+Futkex9/rCivpyeT6P+PUc276/6/FO55zQrJftZ2263YeNa3SmPJABikEhVMoqsLAND4heWI7L0YtR/+COZdcAnkikr0PvF4QV5DGx6yUkelQGml++pJNb/KvkhV7BzvmpZkdzcCdXXWTHdsy2bocfMiMkvhJO8g1X0mVQobMyRarHQKXeWr/9l/YetlF2No7Zs5H2svGqIODmZ5JFGKrutZg1TIsn9mUs3jS3qbKiCzJUmyv29CtqkoxPvtNpMqiZnUEg9SEx5LWMy6C5lV4CMFLZwkKsoH6upSL+01ECwXPt1XfL5V7zk4bcOK+7kX49wxtOZ1bL3sYmO22yWLyi8GX34JQKpd4VTHIJWoQHQzALEXCFAqKhCeNRvJAqQv6skktJERK3XUmEmduiPt6fRkMv9034AIUsd+4anrOmI7WhGaNQt1H/sEAGPkWbdmUrO0oPFakyoKJ6WNnouLT30aBqlDr78GwBgQyMVejEqMthPlJNY/es2kyj6aSTWPG67pvuaxXbCvKZxqRIDiuiZVmS5rUhPua1LNWa6MKvCRSEHTfbXoMCBJzuJMnoWTpIIPGlj7etrfWfme9wAAyhfvU9DXE0R9iUJJdHdjxw0/RXxHK9SBAd/Uluh+eDXWnXqS6+emDpXGIC+DVKJR8go4tZhoWu0MbgK1tQUJUlUzDUg2CxCU3EyqqnquKUtnpSyN48Iz2d0NbXgY4TnzEKitMW7r7bO1oMmyJjVorAdOPzmker2mFU4y0/i0EmkvMRpi38/nxK6NjFizDJpLi59C0jUNnQ/cj8QUDgTIYGUwuMxOAjB6QPokTU/MwritVVQqKx0/T+mBGnFsdq3ua86k+mTgoFh0VXXdJ62iUmn3yZECz6QORyGXlTn2q4ksnOT1vQzU1EKprUV0w3okursK+poA0PmXPxX0+ZJdzm3Uk/44lnQ+cD+AzO0DAHXIH4H0eDFIJRqFoTWvY9N538bWyy9GdMN6x33aiDFLJofLHLcrtbVI9vWOe5RSMw861kxqIFBSfcZ01b1cv5tUuu/YTxaxbVsAGA3V5bJySOEy43PKMtNhvb550k0fJPBM9xUzqSXU1zYfejJprYtyLeKRRhuJQqk2BgyKHdAn2tvR/dAD2PnzG4r6OlRY0Y0bsOPGn0I1UxkB2/fOq3CS7KPCSQmxnCDz+KKkzaSq/f0Tsk3FIIoiubY8EYGrXtigSB0Y8E0KsW5WaXad3feY+ZfDYcS2bEbHfX9E3GyJNh5aNAq5PGINbAPeQaokywVfx5iq0eAyeKTrgKo6esQWSsW7D3D8rI1zMD99VtKewdb9979heN0743r+sRLt+pJug1kl0t6HQSrRKEQ3GtVHY9u3o/2euxz3iZkfsf5QCNTUAqo67jUC4kApW4WTgiVVOAmjSPctROGkoTfeACQJ4bnzAACB2hqofb3QYjGjX2uWqsGi8m9GkJpIAGbFRjvZWpNa+MBrZNvWvNZ7TobY9m3WDKq9KJIXPRZDoNqofqwXOUgVF9FTet3fNNT3r2cw9MbriL691rrNuhj2aEEjKbJvZu2yrUlNr/yd7J3Cs/wiWHRJ903NpBZu4EAdGsLGc89C16q/Fuw5x8NrwBKwpUKn3RfbuhUA0PPo39H2y1vGvQ1qdBhyeblVbNF4UY8+5LJUxJlUt0DdeC21r/DH3/TrCPuA1likz/aKjCld19H5l/vQes2PxvX8YyX2I204M7XXL5kj48UglWgU7CPb6qAz6NRjMUBRMkdHzfTf8c4MiYt9x0xqKa1J9Rp1dmOtaRr7gTjR1Ynw3HlWABmoqUWyrw96PJ51FhWwzaQmM2dS3f4G8XzFmEnd9sPLsOOnP8Gm752LXb/99bhHjQsptnMnACDY2IREZ+4gVRsZgVJl9A0sepAqggWvizbyJfEdStoubnPNpEIJZBwrRrZsmZQCKLpI93ULUiPOmdSRLZsnZJuKwQrEJLc+qYUvnJTo7AAADL76SsGeczy8Kr0DtnTftPvqPvHJjMeMVqKjA9t/8mMkOjugRaNQIhHHWufhN9e4/6JkVPct5GyqVaPBNVAvXhAl3jsxgzyeFGo9mcTQK//LuA1AQSsxj4n5/XHtGqDrUIeGfJNZMFYMUolGQYvHEJgxAzVHHJVxgaPFY5CDwYyL3lRq6PguiEST71ThpKCvApLxGk3hJFGMYzyjhergoJVaChizGGp/P7REPGuPVCBV+VeLpwepHn3xgkFAkqz2NgVlXlQke3rQ/69n0PYr//RWjLftBBQF5Yv3yVk4Sdd1aLGYFaQWO903vttIQ9a10ijVP12IC177oEfWGRuYqYy2i7VEVye2XXkZNp5zZhG31J2WJd0XgLX/A971D6YC69jsckyXJMmY0StokGrsD+kp02Oh6zqG31o7rgv8bAFaKt3Xea6I7Luf9e9smTzZ9D75T0TfeRs9/3wc0XfeRnKgH4n23KnD1usVMkjNku5bzOJDXQ+uAgDMPPkUAEByHK/Vfu89GH5rreM2cbzJpxjgRHALUrVYDBvPOQMdf7hnEraocBikEo2CHotBDoWhmFX47KOOeiLpOjrulRo6WuJAZKX7Bkor3XdUhZMKsCZVHRqEUpm6oFGqq5Ec6Icej2ctmgRkW5Oqul4oS5Lk2bZmvNIvgkY2bAAAxHfvRrKvt+CvNxrxHa0INTcjOGMG1MGBrIGnnkwCmgalyijyUez1u4MvvVTU56fiEIGbo6dutoAAok9q6lgxYi7b0ONxDHnNLBWJyBDwKvJkb6s1tdN9zQq2Xn05FaWgszyi3YpbUDxaQ6/+D63XXYPep54Y83N4FdEz7nOfSQ3WN9gfNabXFcuNev/xKAAgsWsX5LKybL9ivJp5bvLKztIS8VEXmRPHeylLO7dC0xJxK9CWy8VM6tjTfYffSfW4b/j0ZwGk3iMxMJJ3BlgB2ScoNLPljv16VB0wsv56n35qQrer0BikEo2CFo9DDoeNNBJNc7QU0RMJ99535m3jnfUUa1oVUd231FrQqKp3D7d0IkgdR5U9bXDQUfUwUFUNbWgIWjSaO9034BWkJryLtwQCxakKaLsIrNj/AKgD/Yhu3IAtF/4AWy5cUfjXy5M2MoKhN15HePYcqwVCtpYa4uJdqTTW5RVzJlWLxTD8ztsAgLIFC4r2OlR48TYjhTxhD1LVHOm+aT0gR7Zttf694/pr3V9n1y4MvFz4gQyrMJtHtoY4pgcaGnxVCGi0rMJJXkFjgXvXWgO2Yxi4jG7cgKE1b1g/x3cZM4+Jjo6xb0+WwYhUdd+0Anu29yq2ffuYXje91271Bz5o1MXIofvh1QCAgf8+73p/269uxebvnTuq/TFpBnEBW3aAm0QhZyRtn79cVm5sxzgq3dqPKeV77e14DXE+05PJcQ1ojIW98rc6OIh4207Etm/LvH+Kr01lkEo0CnosBikUglxuHPzsax2M9YgeqZ4ozEyqFC6zRu2M6r4lNJOaHEV1X3l8a1JTPWdTQapIs0t0dVnrVD1fX6wxTUvh1pPJLMVbijSoYEsvD9TWAgC2/+hKAM6+oxMtaa7fLt9nCYL1Ikj1vhjRzAEfMXBQzDWp3Q+vhmamz0/1k/h0I2ZFRjZtsvaZVODnPmMjKYqx3s68wO555OGcr7PlohVo+8VNhdhkh1zbKgKYQF09oOupGcKpRgQzXjOpslzQVHtxbB1LUL/9R1dixw3XpbbNbBkmZiPHImG2BQk0NGTeqbmn+xq3jXNWLq1icvNJp6Duk8fkHHi1Ns2jl7dYlxnflX8P0tiOVgBAaNbsjPvs21PI86J9INi6Thvl2tHYzp1o/elP0PXQA1b6+MxTvm59Xq3XXYPeJ5+AOpgKFNvvvsv1uYrFXh8lvnsXtlx8AbZdebl1m2vF3ymIQSrRKGixGORw2JrNtC+c95pJLdia1KFBx3obORgsqRY0o6vuO750X3FyEbN2gJHuCwCJjvacQarX7LiecB+oAMxBhSKXhXctoDBJNLMadaC2zipgkS1oFum9cnk5pECguDOptgv/qbiuW9d1bLn4AvT96+nJ3pQJpWsa9NiIdUwd2bwJQOoz9OyT6lFNNjBjBkIts3K+ZiGJWgayVwqkCFLNAadirt0rJut986wmq+Q9QJTo7nLMfmfc39VlBUQFqWpagOBZHM8UM1ByPL1Zy0B2mU1feO0NCJhpv2Mp7GU/nlW9/wOQZBlyMISm5ScCAOqO/oTr79UvPdbc3ojr/ULnn/+Y/7ZEo5AjEdfzacW+77b+rXsExmNhP8daQWqWmdTYjh0ZhZU6/nAPhte+ia4H7ocWjaJi/wNQ/f4POjK92u+5C+pgZlXdiSLSeZWqqlQxLNuxKj2InaoYpBKNghaPQQqFrTQSzdGrL1eQOs6Z1IEBR4uC6bwmFeMMUmOtxgVNsKnJui00c6bxnPF4RhuhdNZnmhZI6ap7dV8AkAJKUQYVrLSyUAi1R32s4M8/ViIglcvLrTW+2QpHiaBUDoUhhUJFnUnVbbMNUzEbQRsaQrxtJ3b/9jeTvSlF0fXQA9h29Q8zBjXELE/1+z8IIDUzL46DcraZVADQNOvCf8ZnPofyPffK+fkXOkjMle4rWGnvU3D/BGAEoIriWT3b6MvpPgDQ89gj2PXr26yfN3//u9h2xaUZj+t66AEMr3sHm3/wXfT/65nU646TfUBZ13WMbN406sEK61jvdk4zZ1LlisyAUKmsRP0nP2U8bAxpqrrtOzPza1+3/l39gQ9i5mnfxIzPft7196o/8KGsz1vx7v0BAOF58/LeFm1kxHM9rP15xlpQMLZjR0YAZr8mEEGqV+EkdXgYWy+9MCPwFq0GAaONmmzrqOD4fVuQGp63xxj+grETmUpli/Z0vV8EsQDQ/vu7J2SbioFBKtEoiKI64uBnv4jSEgnXAKVQa1Izg9RSW5PqHeClsy46x3hBEjerHYoeqQAQbGq2Rv3T1/VkvL4ohpXegiaRJUhVCj+TqqsqoOuoOOg9WLDyWkT2Xoyq973ful8uQKXLsRIBhRF0Gu9ntsBTjKZLoRCkUGjMM6laPI7eJx7P+t2wDxZMxe/Q9mtXWv8e2bYVXX97CO1TvIqjoOs6uh64HyObNlqzY4IYFBQDSsleow2NFfh5ZDGIYkt9zzxlXfjLkQiUikqr/7T1GrGY46KuO4/U4NHIVThJEEXdpupApK5p2ds7KbLVKzNdx5/+gP7/PAvAmX5qbzvU++QT6Hrg/owelfZ1eXltp63YjDYyAm1kxGpnAxiz9duuugKd9/9ldM+rehfzmnX62ah67/sQamp2/V0RvIqK/qPRb1tTan//JVlG9Xvf513IKiDqPGQeD7VEHNH164z7RzHQqsW8g9T6Tx2LhuOOBzD2KrlbL70Q2398teM2R5AaDEIKBKyZUl3X0fv0k9bPYt1m3zOpjBQ9mYQecw6OpbeGEhz7mq5h+O23Ur1LYzG033sPkrZgsZBEFl+17Xxvl7TNpAZnNBZlGyYCg1QqCi0WK+p6OC2RQNeDq6CNTOx6HS0WgxS2zaSO2GdSk64j+aOdSdVGoth6+cXof8FZwEAdGHAUIJCCQaN4U4msqRtdC5rxzaTqMXPWzjZjKgeD1iCAWJPk+fqe1X3dByoAAEUYVBDPV75wkbVvOIpUTGLRFc080ctlYdtMqnfgaQW14TDkUHjUM6mDr/wP0Y0b0PfvZ9D++7vR+/STno+1X/iPNw1/okU3bkC8NVVUJdHZia77/4Lex/8xiVtVOPYlFOnpdOKcotTWQgqHrerVudZ59pmzbB1/vDfVyitSAaWiAlo06jiO7Lzl5+h94nHrZ1GoqVBypiablIi5NnuqzqRqWtZKu+ltgdzouu6YKdv03XOsf7ff470G0GtdpetjbdlQG84+HRvO/Cb6bBVRo28b1V2H17ye93MCtrZILsUAw3PnouW0b3qeK0SthLHMpKpmID/js/9vVL8nsph0NQndXL8tvn/brrjM+u6N9r31ClIlWUbF/gcCANp+ecuottVOHeh39nY1v8sNyz4NwJhNFUHpyIb1aP/db9FxrzGg51ZBXqxfnfGZz1m3BRtmAEDGoEJ85w6E584FYBS6ar12Jbr//jcAwMALz6P3n/+w2uEUmjg/VhxwEBZedwNCM1sAGCneAJDs7IBcUWHU2ihgW6GJxiCVimL7yquxacV5RXv+3iceR9eDq9D75MRWVNPNNalyuXHgdaT7esykplJD87vYGFqzBrHt29Hz6N8BAL1PP4mN3/02kt1dGem+wNScCXKjm+lh+RBBarKvb0zrQkR6UfqFYqC2DgByF04Ss+MZfVKzpfsWvrpvagYp9Zr23q/F7jWajWbNjIat9Olsa480W9qy0QN4dNu+8+afYfuProRqzppl2y/sVYa1keK2uikENRpFdKPRWkgUxRL6nnmq6K8/smWz80KwCIbXvYOhN9c4jqn2wiRAalBQLitDoKYWqghSrT6p7oFfw3HLUs8hZlIrKqz9MrphfWo70lrSDL326hj+Gm/iPJF1lhFItWKaokGqrqnZe316VPe1DxjoyURGunU+abejOSc4Huvy3AMvvQgg96BCunh7u/F7+S5hsRE1L9Jn+XMR34PKgw+xUobzJc6p7ff8Du1334VtP7wUG799JmI7dzgGanKtH1UHBtB5/1+gq6qR7hvOXJNrPVeBqjsPmkWdgNT+E2oxgja5rBxJs9iaGDhNmMsE3I79Yn8L1NVh0Y03o/7YZag54ggA7rPiLd843VEEquv+v0BLxDHwsrHfDK95A5tXfK/g52ItFgMkCVIggEBNrXW+FYG0NjKCQG0dpNDoz6V+wiCViiK2bSu0wcGizfJZ/alyrOspJF3TjNlS+0xqNDVb7F04aXR9Uq3G2+YJvvMvf7YuxhTHTGpgVM/rd3oyCTnfyobihPq7O7Hx22e6P5+mOVJeHPeZn1X6RVSgxgjwxOfrRc42k+q1Li4QAAqe7pvZi0+pTg1kQFUnbRBDNy8A5LKwLajPne4rh8OQw5lrUvVk0tF2xIuV2hWPITnQ75puFd+5A9WHHY7aIz864dkYY9F2y8+x/UdXYt2pJ1m3zT3/IgDOAhnFEN24AduuvBw95gxBsbRe8yPsuP5aRwaO10yqXFYOparKqmA5/JYx2+U1QFT38VSxmKR1LK1C5QEHAYAjvbPY9HjcSn/PRq6Y4kGqqnlW9gW8Z1LVtLZu4u8XM3LJ7i5svuAHWV97NMFdemqnUHP4RwAY1zLA6K41Bl952fq+jKVar1iPPNoBWBGoWK1SRsG+nX1PP2m1wElfC6x5vF9Cx1/vQ/ffHsLgq69Ai8ezZiWJ2T/AOF8Pvv4aops2ovvvD2Pw9dfy3vb23/8u9TwJ5znRPpNqHT+CQbNFWuo1kr29UIeHrfRhuTwCpaICM5Z92lHgaq9f/RpNXznJ+jnY1Jxxrup7+ilriUGiowOJzo6CH2M08zgiBrtEhoiY9QWMPuWBmhrPtfpTAYNUKjj7iSfR3VWc17AuVnI3qS7Ya8ZTa+bE66an+2ZtQZPn2qJ4hzECK0b07LN6odmpUu7ipDJV1yylM9q35HcwzSctuPOvf8am75zteqLX4zH3iw7zeQPV2fu6eVVs1pOq57YVYw1xagbJ1sstrZDCWItSjJeV7mueSI1iSM5tUQcHse1HV2LXb39tbaccNtawpp/4O/50Lzb/4DzXCsb2wKbP7FeX7O3DpnPPxqbvnON4rBqNQh0YQKi5GXJZGbSRkaLPEo6XWA9mV75oT9R+9OPWRXSxiHVbw+syt6EYtGH7TGpakBpNzaQqFRXWMXLghecAZGlBI0mo/5RRvXRky2YAQKipKVV1WrSy0TRAklBx4EEIzZmbet0CzoIYvbZzBzyiFdOULZykaalWYW5kxXXm0j67NfTaq9bfX/uxowEYs2bWQK7XS4+iyrlXJkXZfGf/5NHMpHauut/6t9jHRkNkTKmjbCNiP+aOVnowLdYxpreuEQPzuqpiy6UXoceWGg+kBlW0kSj0RNxa6uFGsb03g6/8Dzt/dj22X/1DdP7lT9j5s+uzbq/9XCqyZ4zbndlFciSSClLN44cUCKLtV7+wesMCwPaf/BhDr71iFRzy+tyMaslBx88Z25ZIIr6rzfl7Huvlx0qPxxzHETHgFmx2piTPOv1sz2JZUwGDVCo4e3pOwkx5KfhrmAfj0abgjO81bYVgZBlSOJyZ7us2k2oeLPO90LHSFfv7zNcdgVJdjZojjkTFfqmy7alAaeqn++qaZlWDzEfWix/TkDkSa0/tFLwuFCXJOCTKlZUZ9zkeJ2YGo1GsO/Uk7DT7KRprUr0rjBY8SE1kFucIzWzBnPN+gBmfM05MWmxiU320RBzq8JCxfjsQSF0shMIZ34GBF/+LkY0b0P+vZ1IzFqEQ5FAoY+3TsLk2zK2cvpgdczy3Gbikr8dJmiPawRmNRgE0TYMej0PXNAy8/KIvU6PS95uZp5wGAKg21x8VkxiIc1tbl/dzJOJZBwIcxXFsvXR7/v43x9/uqBgdiWSkgnr1KAZSWSiiR6pcVm4NAIo16trwMKDriOyzBPMv+yFmnvZNAMgZFI2GMZOaR5BqXiRP2ZlUTTWKI3nwnklNDTj1/+c/VtAhlmJ0/PHenK89moJDXoN4oTlzHD8Pr3kjr+dTh4cQtxX8ypXW7UbKoxq6GxFwS2WjD1LTz71iSZP9mgMARrZsQqK7C+u/cQriO1rRkV451vx79aRqprbnd42WGGWblIz2b+bxJbUW2DzvlJVZ1X1FgD34ysvW9YH99e0ZVNla8YT3mA8AiOy7n/H/tPeo8y9/yizqWOhWVrGYYzCi6UsnYs53v4/gjNRM6vyrr0GgttbRunCqYZBKBWdfR5S0jXAVkjVzMoGFYawWGeaFjVxWDtUxk+qxJlWSIAWDeV9siAqGRqXBKLRoFDUfPgLNX/qKY9QutSZ1al7E2Im01bzTUvIIZmXzRO3WyFuPJ1wvFMv2NGYhg/UuDdhtJFmGFAhY6wQHX37JeN5k0vNCOX0mdd1pX8OGs76V8+/IJjVq7HzfIvsssfosuhWHKJbohvXYdvml2Hj2GdCiw1YVbMC48NLTAuZkf6paZ2ybUSnRqwWNyF5QXQJSe9VPNyLABYD4biPgCDY1OQqgRd95G22/uBkbTv+Gr2dWZ57ydSs4Dc+e42h9UIztFrM5+aYtdt7/F/TaCs8kB/qx4VunofNPf3B9vBaLYceNP7V+FindAfNiS3zHAOeaVMU2QyJkuyCW5MxgIZWGbnxHxP4oZrJEVc9CFgHU4rGss0siRbZQrcsmjarlXpNqq+5rVUW1zWyGZs+2ajmUL1yY8RSNJ3zR9anzrf9gvJ77ZxuaORNzvvt9x225+lBrsRg2fffbeb+2F3F+Ge1nL1KX5fDoM8zSg2nxOajDzuUQWjSKzd//bpaNMI5B2tCg53nWTbytLfeD7C9jnh8CDQ2On61zovn9Ucoj1t+Qe2lH6viZbQY8PGs29vzFbZhzrlF3ZeYpX3d9XPk+S1LPrCYxsmULWq+7piADoemt8pSKCkSWvMuRYh+ytdibqhikUsGpA6kULa/1HuOVSs+auMq29hYZgDHSmM+aVMAMUPJcj5js7bGCsPiuXYCuO9Ji7M8JTOF0MBuroNAoCydlIwo2qP2ZAYzXhWLdxz+BeRdf5tl7zLENwSDiO20FJXTdbEGTex/Qk0lA0xwz8WORPmrseD1zlHU01RjHI9Hdje0/vspKc9KiUci20Wg5nDmTak/njO1oNfoqBgKQg6GME7m48HKdGU+7eJx/5Y8dP7faWraIWbFQc7N1IaIODWH4nbeNB+i6VdHTjyrfc4j1bykQwB6XXI6G4z9j3FCEGgCDZuGgrAGHTfffHkL77+60ft5xo5G21/OPR11nzvqf/w+i696xfhZrt5q+8CUAzn3EvibVmEkdQt+//wXAmN3INmtVtjD1nV5wzXXW32RPQx96w6jgGjCLj6VajRVu3XKuNakLfnQN5l5wcWoQcooe33U9jzWpZp/URE8P1p/2NfQ/9yxUW9DY+/hj1v4QqKtH9YcOdzyH13F6NLUw0gfxFl53I/a69XYokYqMQEXN0k5kx003YsMZ3yjY5yUFR98HXRQAK0SGmajnoI1EHbUw3NjPMeKcpg4OGm358tyW9HZTuYigVAw09v7TqG6enl0kl5dlpPu6CTY2GuuoTbnStO0D6vZ/ly1cZP07PGtWantVFe333o3ht9ZiZPPmrM+dDy3unkotssFKRWn9NT6342fXO3LgS5V9JrVYbWis5/Xos1aU17QVdgGMg2PGmlSvA7Ki5HXi1JJJqAMDVv9OMbooStLbpda6lkC6b9roZy75BKliJnFk86bM14vHXdekSpKEshwXu9Zjg0HHRYseGzFn07OtSTX2geQo1xp5sU7ILu+blco4QRV+01Mik/39mTOp6WtSBwaMNTSybPUgTj3Wud3iosMtO0PMhDWe8EU0feUkq4+mm3j7bijV1ZDLyq1CWWpfn6OCpVfBLWu7Bwex+567JqV6slvl6dGuex8NMSgw1sEO+3e1/7lnoaZdKA68+F8AsNLTE+0iHduYSdXM1E09mTQuMhUFcjCIMjPlbveddwAAyvfcK+t2lM2fj5Zvno4Zn/mcI1NCDoWtlPjO+/5oPNfifYz7xOz9GCqIe/G6uBSCDTNQvnDRlJ9JzdYzGoAxIGmeE0c2bQRg7Avp+1n36gcBGEFDIC1Ysvd/nPGZz6Hh0581XjvPAWFd01KDU6ZATY1jPaNdtuuZoVdfyes18yUFgqNeyiMGgcps2RVjJSYYRjashzrQj6r3HuqYGbQbfmut9e+krbq6nojnzI5qPvlU4/VcrmOy9bwVx15xHOgRQWoyvXBSBMnhYei67jkTXv2Bw8z05NTxPFeFfzv7wPTMr51q/TtoLwyVTFrf+0JkN+mxmPssdZ6DiVNFaf01PqbFYhh6/TV0/vXPk70pnmLbtxdkVs6+HqR4QapxoTOhM6miRYZ58FLKy62ROVH517P9iO2EnE2itw/QdZTtYZxkxIWz26ieXEpBqsvayqzynHEFgJ5HH3F5vfzTkLykB4bJvn7P4lmA0YpAfFb2Mv7jSdFMLxJhZ/UmnaiZ1C5nkbREZ4czSHVJeVcHB6BUVllrZsR3Sw6FMgJA8Xe4BqnmfZUH/x9qzaqce99+p2s6oNrXZ61vE0Fqsr8P8V27jIswScq5PqrzgfvR9+QTGHj+uayPmyiylbZa+IBG9C3N51ievi/rmuaoarn7N3dg2+WXOB4T274NNR8+ApUHvgcAkOhoByQJATOQVIeHoWsa1n/zVPQ88rAVOIpAUginrSF0U3XIe1F/zFLHbWLwxL7tYtZYzNLsuv1XBctYyXdNajEHHiaCnkxkDVAkWbKCKpHtMvT6axgxBylqPvyRtMfLVtVbwV7grv6YpdZ3P9+Z1LZf3oJ+cybejb1SKuBdVyJ94AUw6hpUHvJ/eW2Hm9EsERKsCuljKNaUc3uUACJp3zlhyNa2SdQHSPb3G8WzcgSpNR88DNXv/6CRQZYmvsv7OCwCvcr3HIzgjEaEzUJnqXOicY0gl6XqDtiXl5TvvRgV+x9gPKa8HMmebuy647bU3zuKYE+cf+s++Snr3AI4e5Yb535j8Dvfc3L/c/9B37P/dr3PqKvhMmA5imujqYBB6gTpfeKfBX2+kS2bM9bjjIcWi2Hr5Rdj580/G/9z2bZrvBfI2siI64lBjGzn0zOtUOyFkwAxk2pWuktmX1NpBCi5T5xxc9YiPG8+ACBmBqluC9+t6r5TdKTdzmqlkmdPuXwOxF5FJ5J9fUYAVeAgVe3vzz5QYUv3tZfxH8/nlzXd15pJzdKbNBFHdP16z/tHIz2wS3Z2OoNUl+rGyZ4eKFVV1rpH8d2SzBY09sBBBEtuFcOt1K+0z7T6gx/KeKw6PGxlJihmkNr5lz8jvqMVoZktUCor0fXgquzHLvO4k++MjfVriUTGzE0+AjnWSMvm8UHNsTbXzeDrr2Yd6NLySJUT0l8/umE91L4+R2BoD1q1kSi0oSEEZ8ywjnHG4EbE2HdkGdrQkGOWXuxTSqTCUbWybEHmmsV8yOEwtFjMauXT+MUv2V4rtbYvun5dQc43Wmwkr2PPVF/OkbNojq26r73w2cZbbgUA1JnVfO1E71jAGITKfIB5XsiyP/c+9QQ67vsDhta8btUS8CLJMhb97BbMNtceeh2rtbSWN/XHLsOia29Ay2ljrzkwlnRfLRZzba1WEIpiVcgW5l1yOeTyckhmgSxd06zvkQg68xmQibXtzCiCBpgDVh7E90IOhxGYMQPDb64xJgvSW9BEzGU/gwOO59Piccw6/SwsuuEmx/ccSB1PR2Pv2+9E42f/n7PjhO1ziO9qs84XHX+4FyNbNudsqbbrjl9h929ud73Pc7DLZe39VMYgdYKItAVpFCkEXnRNw7YrL3cUmxjX86mqtZYh3wp22YiLGaWmdtwzqRvPPQs70kqRJ/t6UzNRRerD6kaztaABzDWpYkbXo4CNIClKXhe08W6jsmV47lxjRsdM95UjLkFqAdLBht95G7vuuA2xnTvQ/8Jz6Hns0TE/Vza6rmPz+d9D10MPuN9vpa0WLkgVgYt99D3R2YFN3z0HyZ6ecc+kymnpwolu44TjdQEqBRTr73Ss4RnHuu1UCxqXdF+rQqR3Smr7736L7SuvKkgPt+G312bcpmQJUrVEHIndu6zUdiB1USKHwoCuOy7SxPrv2NYtAIChtW+i409/gK7r1vuZfnxVIhFUvf8DCNTXo++Zp43Kw0ODkCuMmQa5PAIpGETSDHwrDzzImo1sv/su7z/WvBAYbdDS8Yd70PqTHyO2c4fr/VoshujGDeha/SC6HnoAnav+Yvx9LsW/7MrmGwFadOPoBhyG1r6JnT+7AV2r3b+XWiJufWa59tPYzp1ou/2X1s8j27ai9ZofAYA1YwE4LwDF7HuwYYZxu5lmr0QikCQJSqQC6tAQ4vYg1VYUpu4Tn8T8q6/BXrf9xppJGS2RWi7Smu2zZ/Y11Tt++hPs/u1vxvQadmp/PxRzzWvW7RplwT2/ydVSzF7dN9mVqugsCu9IoTDqj13m+B2v4KHMLKpkDdya1wWJri6rpZvQfvdd6Hn0Eey4wXn91HzyKWj55ukZz61EItaglmeQmjagVfV/hxqVzccRLErB4KgHKLRYbExFk7y0fOuM1PaYf8+c762wblMqKsy0ZGM71YGB1MCDWaU7nyU8bnUGlKqqjM/Ozt4SMGoO/A2/tTazBY2ZDbHtysuR2J06jsS2bIYUCECprHR8zwFg4U+yt7/JZc53v49ZZ5zlOJao/f3W+5Ts6ca2Ky/H5h+cN+bXMKr7lv6a1NF3Gaa8dP/9b4iuewezz/kOgFRzadHqYDwHL7Gjj2zcAHV4GIn23VAqKhFsbMzxm+66HlqF7tUPjXl70qnDw0b1xfLycRWcGH5rLfREIqOIiX2dQrGqB7vRM9akpgonic/Es3BSljWpWiKOwZdfQtWh77eC1GB9A4IzZlhFaOwzUtZzWn1Sx57uu/OmG6FFo+h/7lnrtvLFi611HoWix2JIdHSg64H7ocViCM+e42yfMcqZ1HzWXYjgTI0a61EkSXKUnR9vWXbxWYdmtiC+q81qt+RVFEVSbIWT7Om+sRhQ5forOeVVOClLRUpRKCbW2upY3zWW7RjZlLn2137yN4LU1EWX2mvMugUbGtD05a8YQaG4QBUDMPEEYA4GiCrNWjQKPZlE1wP3Y2TjBqOwR2UVYFbEzNiGsjIku7ux+67fIN62E4lduxDZ20hbkyQJSk0Nkp2diOz3blTs924s+NE12PSds9H/3LPof+5ZhGbPwfzLr3Q+qWZup5yaQUh2d+V8D8Wxy23WAADafvULDJmFioTIu/aDFo0isuRd1vqtdMGmJsjl5Yh7BL9exMxnosN9kMLeszTXTOrWyy+2Bg2lQADbfniZdZ99vai9bYJVybehweg/WG4UQxLpinJFBbThIUeBOvtMhSRJ465gKWZSk/29AOAIICVJQrB5ppUl0P/svzDz5FPG/FrayAi0aNRaL59LIYLUzlV/RWjmTFS/r/jtiuz0RCJ7H3NZtvYXtxklJVKOhmOXIVBbZxWgcavNsPftd1oZF+nnxM0/+K71GADoMNccp5vz3e8blVE95BoQFtXDm086BdUfPGxMbWcyXnNM1X1jkPLowev5muEyRPbeG+V77Y2+f/8Lle85BBUHHoShV1+xBobtg75ikM8KvswZcaWqOtVvNI/B4HkXXoLN3/+O47ZAbV3WzBCxjlwOhTHrjLOtaxmRsSYGvMW1U3rP2erDUlk2oZYWx315LzvyYN+X5l1yOVqv+ZE1w1wo6dV9LVyTSvno/Mt9GHrjdcQ72p0LtnXd9WQ/+Oor6Hvm6bye215QZOulF2HblZdj249+OOa1bSMbnReXo6mM50YbHjYOXmVl40r37fBoWRBrNarABeobRl0RbjzcWtBoI1Gjqmsyx0xgIOD5vnat+it23f4r9P/rGcS7ewBJglJd7ahGqUTcgtTxzaT2PP4P133RfnFZKPY1Oz2PPIxdd/zKcZs22pnUPC4CrO+JqlrBkT3Vcrype2ImNmgW6RGzQm79VwEY+4DLrNR4sg2yzeCLi4P239+NvjVvZtw//PZb1om75x/5zaDruo4RcybTTlycBNMKFtnTqKRAAMm+vtTsibk+KFBT66hYC9gCbNFWQNehjYxYGQXq4KB10dT3zNNGteZw2HW/sM8siL9z+K3U+yF67oqZuEB1tWPAL76jNeMzsrIizG3YeM4Z2Lzie1AHBtD/wvOes9dWIO+x/0ZdUoHFbGSwsQnB+nrX35MkCXJFhevauOz0rNtjZcVUVeUuwGU7vsmVlVYbl4xttQ3kJTuN4EQUSRIDRyJIVSoiUIeGHIOdalpq5XiJKt07f3YDACBQ4yzOM8tldm2sRAqkfd1arm0bb5DavfpB7Lr9V+N6jrEYzUxqepAqhcOQy8ohyTJqP/wRlO+1NwC4VrkHUucDSZYBSco414pro55H/57xu41f/FLWABUApFDmuXZozRsY2bwJic4OdNx7DwCjYnghAlTAWDqUz2c//NZaW0bJyLhmUve6+VbMPuc7qD9mKRZcvdKYzTcDNitItX2v5bIySCHbTKoZVIZmz3Y8Jhf7cW3O91Zg3oWXGNW7sxzPrBohoSDKzSrPyd6ejHOi4jLADwANxx2f2sa096yQ6dJl8/aAUl0DdXBgVOnb9ut5t4kIrw4FRUn1nkSl9df40Jbzv4/Bl1+CZqsOmF5hLLp+PXbedCN235VfKpG9NUOypxuQJKj9/WNO2ROpb9bzj7MthhaNQo5EjJnGcVyA22dMt139Q2txfmxHK5TaWgSbmhwzUsWW2YImtSA/n5lUr3UySXP2tOuhVYh3d0OprjGKRIiiEJIEyeXEIwK6sRbW6PjDPWP6vbFwmznq/ltq9j5XuvSYXtN2Ua1FjbXNQ2vWQK40R+PH2VJSbGuguhpyJIKkeaHldZEgBQJGwKzrjl6Aie6uMWcEZCs4ZR9lXXPhJeh79l+ONFN7W5boO287ToqDr7xsVV2163/239j2w8sw+Ppr6H54NYbWGDOxYh+uOthZKMSRRqXrUPv70X6v0fxdBMhKVTUU8zMR6X3pVRD1eBxQVQTNWTN1cCDVjqSiAurAoGexELeLpPK9UwVAxKBT2YIF1m1l8xc4Hi+WQ1h/irgIFr0dzWNmzxOPY9dtt6LnscxiXem/3/vkExn9Xa1900X9MZ/K+pz2Qm750rVcQarxvQ3U1kKLxTwHQu3F8gBAte3PImXQbc1ooqvLSLkzC4yI3saKud/IkQqow8OOv8tr1nesht9c46hInx5Apv88nkJn4nseqJu4IHWyZGvJBhjH55GNGzD05hoku7pQc/iHrdktr/O6UlMLAIjst7/n80qKYlSCtl0nZZuRC81s8bxPsAqT2T6LHTdch21XXeG8nss3EygP+X72bbf/Ej2PPYL2u+8y033Hv6TMsR0iSDX/b89AkmQZsi0tWQxWhmenipjlE6TaRRbvg7IFCyG79EG2s9rthMKQKyuNQdCeHmOgTlGsfc8tC83YrtTthX7P0ilVVRh89RVHRkgu9kHB9Oriunndma2VValgkDoB4m07oQ4NWqlg6Yvse596wvp3PidAR6NqRcG8C41qiSMbNnj8RnbpX4DxtlVQo8NQChCk2o1s2oi2W2+GruuI79iB8Ow51sloomjxmBEwioNfWaqHnuZRuEXIlu4rLoKCMxqR6OmxUsGsiqfBoOvorDWTOsr3QNc09Dz+D8/7lerqcc+mp7PPfpTvtTfK916M4bW22T1bmmCh2AsGadFhbL/mR9BjI2g55TTUfeIYzDDbFYyVuHCRIxVQqqqsmVSvdefW36aqjqJOO392Azad9+0xbUO26r7pt+3+zR3YesmFns9l/67uvPnnaPvlLRmPEdWmY9u2ovOvf7bWdYlZ0cqDD8HMU0+zHm+/QBD71MALLxivZwYecrkxY7L37XdixrJPG9tuBanG9ypupluWzTPWr6pDQ1Y6mTY8jERnR0YlTmsbXC6Smk/8qvVvMWsanpNaG1uW1s5kxw3XOZ/A/M5FN6x3ZHyIpQluxz37d6r1mh+h/Z67sOm756Rtq/sFVbC5OWcqsRQKY+jVV7Djxp/mf0ww+1R6zf6Ii0Slps5cI+wx0GambtvXnqr9/ag54ihr4GL2d76HskV7Qh3ot2ZGB19+CUpVtTX6Ly66xIBDorMDsS2brRYlxhMXrw7BnPN+kLHeXamqQv0xSxHZdz8AGHPv72RfrzUwlG+6rxwY/bpEu/EE1ONltOPyPp6L7/+O668FYKZZ55iFVCIRLLz+Z5h95tlZHmQMBqr9qYGHnbf8HNt/kuqdvOBHP7H+HchnfbCVtWRmdti+B4VsT+R4zTyC1NiOVisA73v6Saj9fQWpe2In3p9UcUPn98OR7msOwoRmpWZS811G0vyVk9H4heXWz3Iw5Pn3q0ND6Hv6SeNxoZCRlj+jEbEdO6AND1lr2gHnOaj2ox9LPb/tvCD+Haivx4KV1+a1vaMR370LejyORGcHaj78EUdBLV1VMfzWWrT+9CeO/cq+Tjc9e0S8L7JHkFp/7DLMPf+iQv4Jk4ZBahGkpxFKigItGjX6ASJzJtWR+pejQAYAR/GZUPNMhM2eWLttDdQ9t01VsfmiFRj438vWbcmeHgSbmhFsNGYp7L2ixsJI9y2HHC4b8wnd9XmjUSTa25Hs6UZwxgzXaqHFpMeMkavUwa/M3K4R6DGReuIdoHgFfmKtXby9HSO7O6xRdmv9jUdaqjWTOsqLmIEXX7BmUcsW7Yk9f/ErzPnu9xFqmYXyfZZA7e/H+m+cgoGXMmfSxkrMmoXn7YE55/0A5XvtjVjrdisdXFyIjSZIbf7Kyda/3foPa/G4Vb1Vi44gtsVooB15175o/NznrfYjY2YWz1EqKqBUVlkpa16jsqn1UgnobkGMaMcwitmwrGtSPS740i9cA3VGqlX64JkbMXqdvs+JoEwpjzjWvoVbUhcr1npTsxKkCFTcRrrTiz6JFhXi4keLRlO9THXdWFPb1Oy6zW4Bgf39avrSiWj55ukINad+v8IMSOyG334LuqYh3t5ubdfA8885Zk3F+zPw3xcyZxfz6I2rj4xALi/HrDPOQt0njjEKqAFo+uKXc/7uyEZjkHLojdcdA59ZX098jrJ7ITIRSIj30GuGSwwY1H3saDQc/xnrdntbGKW8HOF586BFo9j4nXMQ27kDic4Oq8AKkLpYtIJUc9Z06PXXIJeXo+LAgzDz69/I62/Ll71NiNcgwYzPfM4KwL1aQuTS9cD91r9Hle47jhY0xTo/xnfvcvTGdKPlmEmt/sAHHT8rkUhe2S2Bquqs5wk9NoJkb491zACMQW57Kn2wsREt3zgdjZ//gvUdyyZ9Tapqu04TQXbVew91ZGOMlz346//v866ZdlFzYkKkQ8e2by/4Zy5mmu1ZHzNPPQ0zPvv/zA2VMfzmGiS6OtG16q/G79jWieeqTC7UHP5h1H3049bPRhqx81q098knsPXySxzXzGJAM7xgAeI7W43rT1tWjf38MuPTn0PzyaegbNGejrTYYFMz6pcei1lnnuM52Dke9q4P8V27UPXeQ60q4lsvuxit112D4bVvYtMPvmtdR2y5NDWgvPXSi6AODlrHQ6uIp8fSohnLPm2lQE91DFLHILZjB7bec6936tOAc4F0QhTDaXIPUu3pS/m0EBh4IdWbLzRrNiRZRuXBhxgVCl16Tdkle3uR2LUL7b/7LQDjgjXZ043KAw60mqnnXHvkIraj1fq7tKixJlUuC49rJlUEzXbxXW1QBwehVFU5WnpMBGPdW+qgIC5o1OFh66AxlplUbcg44al9vYi2tiJsXoiLcvtevzeamVRdVdF6w0/R9+9noPal9s/KAw6EHAwhsuRdmP/Dqx1r8fqf+0/O583XwH+fBwDMOvNsSIqCsoWLAE1DbNtWx98wmiC15vAPW/tI51//7EjvAoz9WIwCG/tkOWqOOKpgfcTECLGeTBrrdMRscJbCScbjVde12noigejGDdh41resNNpccq2FbvrSiRm39T75T3Q+cL91cq9farQV8Gp0bicCofS14FbqrRlk1B+7zLho29N2ohSDLWZAlJpJzZzpFM8jnlc1vyPBBuOCJ9nTbaT/ioG12AhCaethhfT1rukCNbWoOuS9jttCM1sy3rvWa1ei9ac/wZYLvu+c2bMzzwnJ7i50P/Sg4y57jz4vyYF+VB92OCoPOhiNn/s8mr9yMirevT/K916c83ft8l36IYLtpEcrBJGmL4JUe5ZNor8f6049CT3/eNQ65ylVVah67/usx6QfD0VFbD0et2adZ519rnV/2cJFxj/M4/r8y68yHp9MQqmswuwzz0H1oe/P62/LV8W7U6mjgbpaz8dVHmT0ce3/z7Oej8kmblZqB/JPgZSCwVGfj+2fvf13x7sGP9HViR0/vwEj27Zi29U/ROt112Q99+RqQZP+u3IkghnHfxplM5uxx6VXjGtbB178b0Yqfbqq/3sv6j7+ibyeTwSpQ2vewLYfXWktb7Br+PRnC7YeVbymeI92/epW9D3zNPpfeB7rTj0JCXOWTSz3mv3t71q/Zx/0KQQxaG6fca5+3wdQ/0lj+YE4J9gr1Ybs6b5jrKIvBZ29spO9PWi/5y7Etm9D1wOrUo8zrxkCNbVI9vUZhTtty0zS03prPvghzEubZZRkGTOO/yzKzAmfQrNvj5h5V8z6CiI7CTCu/4feXIPB11/LyBjZcvEF2Hz+94y6DlbmHtN9ycXQmtfR+qc/Q4+NQNd17L7ndxjZnCo+NGD23hIXFuICQIwu2WcsdF1HorPD+lJnO7Bq8XhGdTpx8VD/iWMAAJtXfM+xljNdx5/uBZDqD6gNDxsX83X1VgA22nRfdWgIWy+9CJtXGAcpNRqFHCk3CguNY32rFAwibFaZFQH0yMYNgK4bKWJZAr9iMEp+pw4KYn1c31NPpNakeh2Qs6Qmp8+4hFrMSoaiEbTHYMho+ujFd+/C8JrXsfvOX1v7AICM0uuiaikAz4v+sRD96ETRhbBZWCG2o9XoP5glbTWbOnO/B4CRzcZMqa5pSPb1GTOp5rreRFcntGgUIZeBj7GyKgJKkrWmEnD28rMTzcX1ZNI1SNVGotj+I6OK7I4bforep5/KuQ3WDLTHWqjK9xyccVvH7+9G90MPQI/HUXP4h639LVfamn0QYOjVV5z3md9zybz4nrHs02g57VuOizZxkZyaSR0x1g65FX0yU91FZWLN/I4EzFHuuFlJOWgbsbevg7ITbRPmXXQZ5pz3A+xxxVVZ/05BsTViF0RglT4r6va9Tx9AE5W60+2+6zfYefPPMfjqK9BjMccMf9mChZh9znfyutCbc94PUq/VlvlaAy+/hJ2/uMlxfI+1bgeQGkhNp0adQao96Ol/03gvOv54Lwb/9z8Axntm3/7yxam1vwAcg6jtv78bUrjMESSKmdd4uxFohWbOtDKQrDX6BVb9/tSMXsBc8+gmWN+A6sM+hGRvz6jPkbquI7bDWA9un2nORamsHFU6aXTDemxe8T1rttfR6mqcS2+iG9Zj6LVX0fPYI9b3Mtu26cmkZ99wAKj7uLMPqqQEEKitw8G/vMXRlmqsRrZkVhsHgJmnfXPUzyXJMqRgENF33sbIxg2uxePySRsejaHXX0Ois8PxHu+6zeghG9u2FYnubnSvfhByRQXkcBizzz0PcqQCc879XkG3I7Lfu9F88qloMJdi5FK2cJHnOtDRkEPOdGd7tpQY3AZSGUNKRSWgqhh+c03GutnJVv3Bw6x/i4JN6bVghGRPD3amtV0EUpNfm757jq2y8fja6E0Fk//pTUFWKlosDi0aRd+T/8S2q1Ijf+IA3nLaN6HU1FjT927pvurgAPRYLFWdLMto+4bTT8uoTidSZkTKr55MotOWVpROpIeIAESMCAbq6yDZRrmzaf/jvdh156+tn7eb1Se1qFHpVhsehlIegRyJZBQwGA0tHkNo1izsddtvUPPhIwAYI5mAcUKQlElI97Wlcoo0mMFXXs5rJtVrLZU2POxYAyeChkCOizJJlo3gN58gtdW9CnL6iH54XuriwF7cBzBm4fufezbnCLXr60QiqDjwIGsmJVDfACkYRPvdd2H7yqutViijLZxUsV8qLbPj3rux+647sf60rxlr/VTVumDu+MPvAaQGZwqh+gOHofGLX0Ldx452lOX3utC1p/tqsZGMIjnJnl7Hz+2/uxPxtp3ofeJx741QVSPQ8zgRi2q4LZ86xj2tNlJhvUc7rr8WAy+96PlSboEPkKq8C0XJelFqDSiZ26pGo8Z6VJfZB3GRIY6V4v9BM3UsYfbNtAep2dZiRRbvg7L58xHZZ4mVqZCLVTDE4ztd8e79rRmWWWecjdnnnueYmel94p+Ox9u/g1IggIBZ0bLvmacx+MrL2HnTjQCyB0rZRPZZggXX/BRV7/8AYjtajT6r9//Fun/3nXdg8OWXHGmPA2a2RKJ9t+txWosOm9XGzUFN21pq1ZZyJzIllMpKyOEwwnPnouH4z1iflyCObdbPadVQK/bdD+E95mPG8akLYjHY61UteLwkWcZev7wDe/4idwXcYMMMqH192HD6aYjt3On6GLcMK7W/D9rwEBq/8CU0LD0u721TKqvyShMXRIaDOJ7az+XjLohodShI3RZdv86zgn+uwknpfabHO9Obrnv1Q4AsZ8yWpu+T+bIfB9rvujPj/kIX3xHfFbfU/Z0/v8Fq2SKKclbsux/2/NnNBR1cBowgsOaDh3n+fbO/4wyKy/faK+t5IO/XDRr9i8X3yZ7Z5TZIZA/60gffD/zZ9UVZa5qvuo9/Ag3LPo2mr5yEqoONzB4xkwoAs876tvXvbo9e8nb2HrGljkHqGNiLetiLswhaLGZULKyphVxWZhVUCVTXQgqHHUFqosMIYMsWGWlO9nTf2I4dOQsfiBFHSVGsgNXrglVPJqGa1ddEimmyL1USXwSp2YJKdXAQvf94FP3/fsa6LW5L/dNjMUDTIJdHrHLx9l57o6GbM5eSJJnrmfawRtACDTOAgGL1xJoIWmzE2aNPllG+zxIEm2fayqF7BKnZ1qQODyHU2ISGZZ9G2cyZVvl2cWGYreJnviPtovBMxt+U1se29siPYt7FlyE4c2bGYv0tl12EXXfcllHsJZ2u645AVtc0aNGoY32aJMuO4DpuzjLk0/jbzj6zHdu+HX3PPOW431pvac4iRN6VvdXAaEiyjLqjPgY5HE5dQMuy50CFCBK1aBR6LJbRp1UEXnbbr12J9t/fjWTaEgIhV0qdHAxi79vvxMLTTsGeP/9FxrpNJRKx3iMAaLv1ZkcF4K7VDyK6fh0AuKa4Acb3NP274UpchIqKuCNRKB5rAK1WM+Y+GG9rM4JgsVbRnEm1z4wXPPXJPI6W77U35l10KcoWOqvTli1cZM22KlVVqNh3PzR+/guoOPAg6zHD77xtfccSnZ0IzmjE3rffib1uvR17XO4+o5tvUR03wfp6hJpnQu3tRdcD96P7bw9BGxlB1+oHrSDF3hPZousYtNUpELSo8bmKC1Sx9h4AEmmDKkCqqMoel/7QNRhrOHaZo01R+v4ol5Vjj4svc1RXLptvvO/5ruMcC0lRMoImN/YL9fRjDWC09dpwxjcyzqGij2Z4dn4DJNbrRcrzqlMhiIDWykBIKx43HuK6xZ7t0vbLW9Dxx3sRTUt/11UV0LRRZcakt/4ZK3v/y6pD34eKAw503F+IWb6JUGcW+ela9VejoJTHMpVZZ2Y/Hxdbxbv2ReMJX7R+FtXtZ515DmZ+7etjfl5xHu1e/aA1EFp92IcQapllpTTbP1t7B430ln0Ve8wrylrTfEmShIZjl6H28I9Yt8m2IDWyzxLX31OqqhznEyHRmb3+RSlhkDoGYsfQ4vGM2SbAuLCSKyqN3nXhMqvYhFJVZfbWTI1AJ831I2Xz9gAUxbq4H1r7JrZeeiH6n/0XAOfo7MxTvo6W08/CjM9+3jEK3XzyqShbuNBzxNTei0xc/ImS2HJ5xEr3zTaTuvPmn1n/XnfqSVh36knOv91My5MrItYFZT4nx20/vgqbLzTS1bREAu1/+D3UgQHHl9CeAiQKJxWz0mO69HRfwLigVAcHrJE9zyA125pUc6F//dLj8J5bb7JGIZWKCtQvPRYtp5zm+nuAEYTlswYlvnOHNXPjkDagIUkSyvaYD6WiMjVyLrYzz7Szvif/iU3fPcdKb9v1m9uNFO2IMyizp6KKINqrD54XqSzzIG3/DET/RQCoOOg9CLikcBaCmEnNllokHqMODho9P9Na1ey++66M3xGDVvZKf3ZaMjGqUesFV6+0GtsDxgx3elBtrwDcteqv2L7yamMb0ta7ixmuka1bjL8nR5AasIpYRa3/u61HBYzgWgqXGZkmum6sw1dVI+0uXIa4mEm1BTye/WnHSlSzDAZRNn+BNWgkSIEA6j9ppJsHbYH+rG+daf279Sc/xtbLL8HIls0Y+O/zjvWCXhcY6a8zWmLdrjC05g2roAlgFHUCzDWBkmRVvEzszhwk0aJRyGXl1nEv3r4bWy+/GJu+/x0Mbd7ieGzVew/Na/vmnX+xddxRPFLe0p93xv87YdzVuAuhyrYe1q1tVOef/2ist33nHcftIgNI9OLNl1wegTYykvcso7h+GH7rTUQ3rHecy9tuvQU7XNII8yWCVHFNIvQ98xS2X/1DDNmqtafWymc/Nom0/llnn4vIvu8e87bZ1Xzow9a/Zxz/GUQW7+MYEBptSxQh/XxYbPbBQ+g6Kl2CFSiK++0TrNZW8Eh8tysPPCijONZoiH2n64H7jYFSXUd47jwjQ8/crxvNZWCAsyL7eDtUTIRgvdnVobkZcjiMqve935FSPef752PuigvR8vVUenqlWTuha7VR72A6zKQWrt/DNCLZevjptotSXdcx/NZaqAMDqabktgNioKYmoy2LuGgJNjYhUFNjVaQbftM4qYnZC/vvVL3vA+4tSSQJSkWlsbA6mUTrddcgsu9+KFuwEBX77medwJSaGsS2bcXWyy9B7VHGBYocDlk98xwtbmy6//6wNaviRTUrbgaqa1JpfVl6XQkjZlXM3XffhURnB4bNk7r9wtjez0ypqjIDvwksnBSLZayLClRVQ+3vz72Q3WNbxSyjbJZMT/9cZxyf/cIs2NCAwZdfwsiWLSibP999u0eiGHjxv6h+/wcx+Nqr1vo+ILOvpbW5FRVWYKQnk5kl0DXNMyATKaMjWzYhNGuWlVKY3sey5RunQ4tGsfmC70MbHoYUCIz6oCsHQ6j92NEIz56DwVf/h/pPfgrli/bE8Lp30HnfHx399MJpqYaFZM2kZumTJ9atJnt7kezrg1JRgerDDreyEsTnMveCizHw/HOONF+vCyQ9FvOs8JcP8ZnMveBibL/6h56P02IxY/TWlrYenrcHouveQe8//wFd1z0rowpNy0/EwIv/tdYpamkFLtIFamuR6OjIKCYnl5dB7R0BJAnhualCF4VuvZDeg7b2iKMw/OYaQJKgx+NQBwdQ/8lPoebwjziKcaUX5kp0dGDblZcDcKas2r8/NUcchb4njfTg8VadDrU4Z+syinBJkpnt0Gtc+M2aYy5L6cp4Li02Arm8zNrHdv/mduu+jqefQdmChZh34SUYenMNyvfeO6/tUyoq0LDs0+i6/y95zX4r5eWoP/qTeT13sQVqarD37Xdi+09+7FqkUAxEivdSHRw0KlH39CA8f8GoU5YVkX0xEs0Y5HNjT+UeenMNym0X7vFdbZ7rovORfg5Il9i9Cz07d6DyoIOtAZhcyzcW/Pha6IlEzqUtoxGeNw+hWbNQvniJNXsWmpU69tuXZoxF2Z57YWTDegSbm62BnYXX/yzHb43hdRYughQyUl7lSAWalp+I6g8chp0/vwGAMUDXcuro19cWg6P2wDiqUXtpu/VmAOZyAts5w94/PrL3Ysw68xzsvOlGR3FIv5LLytHyzdNRtoeRNdJyqlG1vOZDhyPR3YPytMwdAJhx/Kcx+NJ/ETdrCbjVTSg1nEkdA3Fi1eJxx3qM7T++Cjt++hOjqIg58imCVFGN1i1IVaqqIZeVQamusQLJ+C5jZslKETRnsZq/cnLWCnJypALa8DBirUZBmq5Vf8WO669F37P/toqdRMyLxNj2bamGyOGwre1D5uxwfFcbOv/yJ8/XDc+dCykYtNbUKtXVtnTf7EGqPeW076knrAAVMAJywbH+TJImYU1q5kyqUl1tXLCaaVZeI8eSEkCysxOJnh7HNov3ZrQziELd0cZMTv/z3hUnRauAyH77Yc5530fjF75kzUorHqnESmWlNXK++67fYNN3v+24P9tsu3gPEu3tjlRwOe0iS1IUKJWVqQEdW2+z0Wg64YuoOexDmH3mOdba7sjeizHvwksQrEulCNqLLBWaNZOqZJtJNd7rXXf8CrGtWyBHImg+8atYeN2NKFuQOiGVzV+Amg9/xPG76cW1hLE2bxfrncQsbPnCRZh7wcWej9921eVIdnU6ZqZrzGIQ2siIOeOWfYZCqaoy1s6bx8Zkf1/WYjhle8w3CoSYGSBNZm9T+zHVHtAVOt1XzPKIwbGKfffDXr+4DTM+Y7Re0OKiaFVmGt7C626w/i2Fw9ZzLbzuRsfjFt1wE+qPXYYmsx2B/XXHyj5YJZeXG0G+JKHmiCPR+PkvALoObWjIVo+g3ujR7FLh15pJ9djHRHXlin33yytdVqh+/wcQmtmCmiOPGsVf5h+B2rqMIFUdHLSK3IkiJ5sv/AE2n/89qAMDVpXU0bAvEchFHRxEfOcOqzDL0BuvO5blCKOpEdH/wnPY9Zs7jN/LMZPY/feH0fGH32PH9ddaLUJkl0wXO6W8vKABKmAMXM6/4mo026pz288rY02RFG1exDHQnkWXa4BuLCRJQss3zwAANH/lqwjU1KDygAOtc0XTF5Z7DkxPhvpjlxn/kAoTVpQtSg2wiMkPuTziKEyYvn9F9t0XFQcehAbbmnY/qzrkvY6OCoBxbHELUAHjOkMcc5WamozfLUWcSR0DySqcFIO9ioAoxQ2kKjmKg5diFsOQy5y9Q+Pt7daOFqiqsnr/iZHYVAsG4wSRq8KhUlEBdWgw4wRqHwFvOHaZlfIl1ifJobA102efSR3ZthWB2jpsueh867bq938QUGT0/9tI+6n92NGQAgHEtm9HdJ0x0xqorrYqkOUKUnse/4fr7QtWXutYR5A+Up9tnWcxaLGRjBOcKHIS373LmAn0mF0UF7Kbv3cuIu/aF3PMYgOiemZ6AJev8oULEdl3Pwy/+WbGfUNvrrF6uEGSUHngeyCHwyibtwdqPnS462CEIFdUQh0cwM5f3GRV5gWAsoULMbJpU9Y1iGKNbKJ9t2Pm3atghWjZkj7TWiizzjgLWiIx5oGAfASqRLqvd3sbq++tSQoEISkKAjU1ju+1JMsZBWbEGvJ0Wizm2fImm+CMGUbpe9sFhT1QThffuRPxnTsRmjMXe1xxNboffsjaxuG1byI4ozFV7TiL2Lat1rpybXAo4z1J38aBl1+01p+Ki0TrmFpdA0mWIZeX5xUkj1bkXfti1pnnOKrPArCO1/aAPV2gphbzLroM/c//B71P/hN6LIaq9x6acXxQKisxI61qZiHaWLR883TI4TL0PP6YMQOu68ZnZM4oxbZvs85Rgbp6BGfMQNR2/hJEGrd99iI0s8X6XSk0tgIpwfoGzL/yR2P6XT8I1NUh2dmJ7odXY2jtm5h1xtlWpWQgdb4WgV18R+uo16MCqWOiOjSUc02dyFgSrbFiWzZbNSjsYttbPS+C0+267ZcAjNY89loalQcdjMFXnGuYk93mNUtsxDrnj/W85kezz/kO1CGjV+XA889BLiuDaiZ5FKJQkJvK/Q/AXr+8wzEQNvcHF2Bo7ZsFS48ulNoPH4F4ayvqzOy88SpfuBALVl6HzT9ItddRyiOOJTvpA5NyMITZk7xGtxiCMxqR6OyAHIlAqa5GoqMdwRmNBW155FecSR0Dq4hEPA7dZU0qYFwkAKmRHjFaKJeXQ7WNiiY6O6yLHnslP3XQLIAwEoU6OAh10OxDl2OUXa6oMNOLjFHyyoOcLSgiS/ZFqGUWZp1xthE4qyogSZBCIdsMsfE3td3xK2y74lJs+s7Zjudo/urJaP7Kyaj58EdQf8xSzPjMZ61guueRh43trK5JnWBzrUk1v2giXa/xi1/CXrf9JuOkHKiqRnBGI+o+ZpSulwIBQNMKXhXQi9uslajYHG9tzR4s2NYUD6990xqMEMHHeAKoyLv2RbxtJ6KbnCX3rQAVRgqJfdvlcDjr+kylogJ6PO4IUAGg6hBj3ZkW8x6NFzM08fZ2q2VS/bHLHJWD7cTMaz7pbGNRedDBqLb1biwGkcZX/aHDPR+TXkRk+O211r/F+qOajxxpPFaWHQUxvGZS9THOpIqU2/TshEU33IRFN96M6g8axUfCaX3j4q3bEZ41Cy2nfgNSIGAFcInOjqwFvjK2W9ehmr1rvSi1tYCqoutBo1q5OB6IYFTMos49/yLMOvvcUbcvykWSJFQeeFDGTGnF/gcYlXw/drTHbxrK5s83jvvmQJrIaPAy75LLHf0Ox6PqkPei4t37Q6mqSq33Lo9YRYhar7sG7ff8DoAxkxpqmYVkVxcS3d0YfP3VVAsTM/i3f07BmTNTx/YxVPouBaK4Vedf/4zo228ZrUnMtiRSIAB1cMBxngdS6eOjeh1zfbJYBtTxpz9g6xWXQtc0jGzehOj69annNwe/7en/yZ4eVH/gMEcq/Parr8grA8lekK979UOOVGHRPkYKBDJak2ixGPrNQfBiDgyORcijTVU+5LIyBBtmIDx3HsLz9kCzmdlRbOnHHykQQOX+B/guQAnU1mLWGWd5ZmeNRfr6ejkScQxmF/qY71dzV1yIPS6/0ijWKQZrp0HRJIAzqWPiqO6bts4wNGsWlKpqqzm8KI4icsflcBl0M6DTk0kku7oQfJ9RjMGo1DoAXdOs9IaeRx9Bz6OPWM8vZ5l5AFKzNbHt2wFFQcs3vgUAGNm2DbHt21B9qHGxXnnQe9D//H8w+PJLkEIhSJIE3TwYdq36KxJdndZaQiGy735o+ca3rAND84knWffVH/0Ja02VHKkwUofNwCxnum80CigKFl13A3Q9tQ7HzYIf/8T6tzh462oSklzcBeS6pkGPxzPWvYmLCHuvWzciyKj+wGHo/8+/MbJxPSoPOtha5zOeA3vlAQei874/YvvVV2DuBRejfOEix/1yJGKlKOYrfTCk5ZtnoOqQ/7N6ANuzAezaf/87K9UtZl60lS1clDFbZCfSvafyCUcuK8Oin/8i54kjst+7rXT2lm+cbt0uLnqDtuJWlQcehD0uvwpbr7jE8zukxWJjqgZbd/QnUXXw/2WkC4n9sPqDh6H/2X/lXCNc+9GPW+0uAqNY65Xs7QVUNetFrMhSSHQY6/bFeyuCVDFjFJ41O++2MoUgSRIq9t0v9wPhXI9f/8mlWR9bjEbygarq1NKTSMRY05W25EQpL0fFu/dH16q/YmTTBrTdegsAo01ZvG0nyvdZYhSyMtfHBWrrsMflV2HL+d9DZD9/zeZMlPSevMneHgyvWYPQrFmQgiFE33kbcVuVbABo+vKJGC2RYSEGr3seM64FouveQeu1KwEAe/7iNqPFjbn0SA6HrbV5gFmwMRyGaluaFGtttVJF1cFB9D75T9QfsxR9zzyNgRdfwJzvrUBfWqqwNjSEyoMPMdo57bkX5l99DZRIBHJFBbpsbe+04WH0/P1vxrb4KEhd9LNbCnKOUSoqsMcllxdgi2i0AtXVeWXslJpAba11ni9ftCd6gAnNIpxMnEkdA/vazfQeYXO/fwHmfm+F9fOQWQBJFK+wXyAkuruNNCyRY15VZcxevfRiql1DmlzVEJVKI7gY2bYVwbp6IwU1EED5woWo/fBH0go51RrbJIoc2Ebm+v+VuZYlNGu252xXcEYjao4wZoHCc40KhlIoBChKzsJJan8/AtXVkMvKswaoGUSQOgFtaPREAtD1jIqs9jTNbMGCWFNU8e79AUVBdKNRsl8EdOPpAWgvKJW0FT+RIxHUHHEU9vzZLaMOggNpqblixk3sK0lbGpk6OGjNZovekDWHpyosVpp9wbyIthb2dLmpSCkvz9k4fObXvo5AXR3mXXwZImZ1XACo/8QxmHX2t1H3yU85Hh+ePdsoYuXRP1mLj20mVZKkrOtZyhYsRNV734eZJ5+CvW77jVXJd8E1P814nFD1/g8gF9GzcPP3zgWQvdKmPZPCXoZfDE65Vqv2GTHbGpo1C7WTsP7SfnwSAYO9+qkg3uuOP/7Bum37j640fs8qgmNc4AdqaxGsq8P7/nhPwVL7ppryfZagYv8DrJ+TfX0Y2bIJ5XstRqilBcnubuv9E8bS/1YMOquDg46lE3228/Puu36DzT84zzqXSKGw40Jeqayy0vpFxoa9fU7Hn/+Ergfux9Drr6L9nrsQXfcOdv/2N679WcsWLETtkR+FJEkINTVBqTS6GJSZtQDSB7UK3hZqHBSXSubjNef752ccE6k49rj8KihVVah8T/briVJXtmhPBJtnos4nxeSKjUHqGIi0TiMN13kgTw8GRFqnmDGQy8uhDg4g1rodiQ5jrZUVpJozEW2/+oXjOZpPPsX2/NmDGfH6id27cqbfiaAqW5n4eRdeYv07lNbTLuP5zJOwCJokSTJTmLNXWlMH+sdUpcwaFS3AiNLQG6+j9fprM/qGCqlR6rSTsD2FNssJWRQaUqqqEGqeaaVOiQuB8VYcnPPd7xvbaQbD6vAwtOHhjHSZfFXa+o+1fOsMa5ZHBBU7bvgpep9+EonODmz89plov+d3GF6XarvQeMJyzD7nOwg2NqHa1rbBzayzjLRW++xOqQpUV2PhT65H2R7zHbcbKVwHuqZwhWfPQWzbNtfnM6r7Fv5CUA4G0XLaNxFqnglJkjD3++dj79vvdMz0As50vnxmAsNphT6ybXt4jz2sYjP274fYT8bTT3SiiGqw86+4elIyBezvkfis7CnpzV89GUAqgHVrZ5VeAM8asJrCmQ/jJUkSZp99Lva+/U4olVXofugBaNEoQs3NVkq13ViLYcmRCCBJGNm21WoFBcBoyST+bWY8DZttb+Rw2PF9CTY3Q5KN40q92bu275mn0PbLW7Dx22cZa9MB7Lz559bv9P/7GfQ8+neE5+2BBddcl3quGe4DW2LtbWRJqg91aNZshGwtokpRZO/FGcdEKg6xpttvac4TLVBdjQVX/RiVtkGyUjZ9zzLjIEbj7L3nvNR86MPo+fvfMOvMbxu/a17kb73sYjQt/zKA1IHfXrUMAOac9wPIZeUItbRgt1lhz62SpF2wyTgpaNFozvUgojm62/qUmaeehsi++yFQVW2scx0aQmSffbI+X+UBB2Hw5ZcclUkDdXWePR4BI+1v6I3XHa1C8mWl+5rbr+s69GQScjCI6KZNGHr9FTQc9+mcs1sAsOPnNwCahoGXXkKNrRm4oFnrfTJnfqoOfT8GXngOySzBeORd+yK6fh2U6hqEZs7E4P9exu57foeRzZsAWR53WpQYyU6YxStEqpnXRUU+6j5xDOSyMkebGvvFT/vvfmv9u+/pJ9H39JMAgD0uvxJyOIyKd++PBT+6JufriN6B1e8fe0+1UhaevwA9jz0CPZnMCHTcevdOtFlnnpN1bald1f8dil2/utX6Ob1AlJ0kSQjvMR/Jnh5H1WQ9YRR2E8cv8mbPshDFj8KzZqPx819AZMm7rCrfXsfIyL77Zczul++12PWx05UciViD1eF5e7hW4h1rf2bxuaQvvXHT+/hjxvaEw47vY9mChVbdB3s11IEX/wsAGQPtdlWHvg/B+gbM/vZ3sfvu31oZFekS5uBGZN/9MPTaqwCA2qM+mnObiXKpPOjgjLoms889b9qsyZzuGKSOgaQoRmXZtODObU3ijOM/g5oPfsgaUbTPWg6+/hrk8nJrtDu9jHn54n1GPWoUbGgw+pNqWs4iS4po36ClivrUffwTCM6ciWpb65e55/0A/f95FsHm7KOi4blzscelVzhuE70OvWw679sAUoUhRkNcsIt1wf3P/gu77/w1Fl57PXb/9teI72hF5XsOQXDGDMhl3qmY6vCwlV69+847UP2BD0KSZXTc90f0PPp3BOrqrRRmtwNj9fuMINVeHCld/aeORdUh/4dQyywruBZreAHvi8R8iYGT7tUPQk8k0PPo3wFgTG0PBHujbCGfFMv09Vq5SLKMRTfezJOOh1BTE6CqSPb2GO2qwmEkursRrK83qvtO8vs2mmbykiQhUF+PZHc3Kg95b8b66XRilsJelKzpi19G56q/OHpAkjtH2qdtIEykXdvZ1zFat51+VuocJEnG8pRxHFNKkVJVhUT7blS9932I7LMEI2b1artAlkrQOaWdV2ae8nXsuuM2z4fL5RFIsoyZp3wd4bnzjM9LBKnhMrR860y0/eKmnC9bfdiHUGsWcqvY791Y+ONrPR8bnNGI+I5WVL//g+j4/d3Ga42iJRGRl1lnnJVxW741AWjqY5A6RvYAVamqwozPfh4Rly+OpCieKS/Da95A1f+91wpQwnPmWrOWgDOtofELXwL03FVsJUVJFcrIUWTJSgWznQQbP/+FjMeF585D4wnulVlzCdTWOdbSaPE42n5xEyrevT9qj0yNtJYtyn6x6kZSzCDVXJPa/beHAADRjRusFKb+5/6Dvif/CT2ZxMxTvo7q938QuqZh6LVXENn33ZBDIWstZLCxEYmODkTfeRs7bvyp9Rkne7qtNDi3vm8ixTryrn29t9XWVqT+2OOtUWwA1mzGeFXsfwCGXn/NClCBzOqs4yWHQpj/w6uR7O1F56q/YmTjBjSffIo1079g5XU5nsFdrgGV6UwMNGxeYbQtavzil9Bx7z1G9V9VnXLBfbK3FwDQ8KnshYQAYMZnPodAXb0jqArPnYvZZ327SFtXWuwDn7lmuysPPAhzV1yIkS1brBZm9n1rwdXXQEskvH592hKDjtVm3+D0qvQ1HzkSDWaa7ViULViIkc2bMP+qHxuFF10GQ5Xqaqj9/Wg+6WtW1WtHZoo1k1qGyD5L0AZjkHru98/HlguNGhpKTS3Uvl6E585FzUeOQm1ar+ZsZp91DuLt7VDKy9Gw7NPoeuD+MbcnIiISGKQWgDow4Joi6qb60Pdj8H8vWz1VRTlpwAh297zxZqw79aSM36v76OgLVORM9zUr0wabitcQOFBbC21oCOvP+AbmXXAJWq//CVQzxbfm8I8Asoyq/zsUjZ87YdTPbc2kJuLQNc2asR1+800rUO/9x6PW43uf+Ceq3/9BRN95Gztv/jkqDz4Es751JmLbjfV+Ld86E9uuuBTtf7zXClD3uvV2dD/ysJXarZjvmV3ZgoWYe8HFKJu/IK/tDs+ahdnnnofuh1ej6QvLc85Q52vW6Wdh/TdPtX6ueu+hRenfFmqZhVDLLMzdZwn0ZAJyMISK/d4N6FNjneBUk57W2nHvPQCQqt5ZwJL/E6HxC8vR9eCqvNpByGXlqE9LN6XRmXnK16EODOa1JrZ8z708Z6inQ+P4saj9yJGIrnvHWjOnVFSg6ctfQfvdd1lV0cdj1plnY/CV/yHY1JyRWdX4hS8h2duD+qM/ieTAAMKz3NPnJVuQCsCoRB4MQgoEUH3Y4ajY792QFAU9jz+G2WefO+qBr+CMRmtpSf0nP4VAfcO0L3BDROPHIHWMZn96GXq3bMfQK//DnPN+kPfvBWpr0fzVk7H1kgsBwDVAmfP986GUj32NYs0RR6HvyX/mHDlXqqqMtae2YgeFJmaB9FgMWy+90HHfwP9eAjQNkXe9a0yzQUmzR1/v00/Bfu4WlQsD9Q1Idndhxmc+B3VoEL3/fBxaPG7NnA6++gp0XcfwW2sRqK+3ZjTj5v1zL7jE6AO39DijTP/jj3kWj8qVtpiuYt/9Cp6yIgUCWHTDTdj47TPNG4pbYECSJEhmStdYKldSfnKtvZTHcayYDHVHfhR1R3K92kThWu/iqnrvoah676GO22o/cqSVKjtegZrajOcKzZmLeOt2x+B1tgrxSnUNEh0dVvaRvYr+zJO+Zv278qD3jHt7pUAANeasMhHReLC67xjNP+krmH3G2dj79jsR2WfJqH7XUXnPpfpqZO/F1hrIsWg4bhkqDzoY1R/IfXFS/b4PFDXASK9iKldWWpVoRQGV8kVjW1sm/r6+J/9ptT4RBZiUyirMPvvbqPv4J1D70Y+jfPES6MkkNpx+Gobfedt4AlVF+913YXjtm6g4wKisOsuWRijSpgBjfeaiG27K2jLDD5TKSsz8+jcBAPWfGnuKGfmHXFGB6g8chpmnfN1qu1R58CEoN4875XtxbSbRdDLvwoux6Oe/yP1AU8s3z0DdJ45BaPbE9RMmIhovzqROAnt63niqr3oJVFW7LjafDKK9TuPnv4jQ7NkIz5mLQE0Nyhfvg+g7b0OpqkKwOXtrGy9KJILIfu/G8BqjF23tRz8GuawMw2teR9meeyI8Z661xjaydyqteujVVxBsbEKio92qSCsq2Npbr9h7DEqBwJRJq6w+9H2oPvR9k70ZVCCSJGHm14w0bqWyCjtu/ClmfPpzJd/egYjcycEQMIqVHMG6OtdCeEREflbUIHXz5s1YsWIFent7UVtbi5UrV2J+Wp+86UiSZcy/6seAJE9K77yJJIfD2Pv2OzNun/u9FdDNdaPj6XvV9IUvoe2XtyC+qw1Vh7wXejKJnsceRfX7nL055bJyzPz6N7HrNmP2tv6YTyG+cyd6zDWr9rXBFfsfgFjr9qKs5yQaj4p37+/6fSIiIiIqJUWNkC699FIsX74cy5YtwwMPPIBLLrkEd911VzFfcsoIFahYzlQ23rYrABCaOTOj7c2eN//SNfCtPvR9UIcG0fPI31H5nkMgvS+E3qeeQPniJY7+sy3fOmPc20VERERERGMj6W71zAugq6sLRx99NF544QUoigJVVXHooYfiscceQ30evRaN5xiEphVl88atsbEKHR3eTbDJv3Rdt4LYZH8/lEjENzPa3K+oGLhfUaFxn6Ji4H5FhcZ9yt9kWUJDg/tyuqJdmbe1taG5uRmKOUOlKAqamprQ1taWd5DqtdF+0djoXU2Ppggffobcr6gYuF9RoXGfomLgfkWFxn1qavLH9JEHzqTSdMP9ioqB+xUVGvcpKgbuV1Ro3Kf8LdtMatFa0LS0tGD37t1QVRUAoKoq2tvb0dLSUqyXJCIiIiIioimuaEFqQ0MDlixZgtWrVwMAVq9ejSVLluSd6ktERERERETTT1HTfS+77DKsWLECt9xyC6qrq7Fy5cpivhwRERERERFNcUUNUhctWoT77ruvmC9BREREREREJaRo6b5EREREREREo8UglYiIiIiIiHyDQSoRERERERH5BoNUIiIiIiIi8g0GqUREREREROQbDFKJiIiIiIjIN4ragma8ZFma7E3Iyu/bR1MT9ysqBu5XVGjcp6gYuF9RoXGf8q9sn42k67o+gdtCRERERERE5InpvkREREREROQbDFKJiIiIiIjINxikEhERERERkW8wSCUiIiIiIiLfYJBKREREREREvsEglYiIiIiIiHyDQSoRERERERH5BoNUIiIiIiIi8g0GqUREREREROQbDFLHYPPmzTjhhBNw9NFH44QTTsCWLVsme5PIh1auXIkjjzwSixcvxrp166zbs+0/Y72Ppoeenh58/etfx9FHH41jjz0WZ555Jrq7uwFwv6LxOf3003Hcccfh+OOPx/Lly/HWW28B4H5F43fTTTc5zoPcp2g8jjzySHziE5/AsmXLsGzZMvzrX/8CwP2qJOk0aieeeKK+atUqXdd1fdWqVfqJJ544yVtEfvTiiy/qO3fu1I844gj9nXfesW7Ptv+M9T6aHnp6evTnn3/e+vnHP/6xfv755+u6zv2Kxqe/v9/69z/+8Q/9+OOP13Wd+xWNz5o1a/RTTjlF/8hHPmKdB7lP0XikX1MJ3K9KD4PUUers7NQPPvhgPZlM6rqu68lkUj/44IP1rq6uSd4y8iv7ATXb/jPW+2j6euSRR/SvfvWr3K+ooO6//37905/+NPcrGpdYLKZ//vOf17dt22adB7lP0Xi5Bancr0pTYLJncqeatrY2NDc3Q1EUAICiKGhqakJbWxvq6+sneevI77LtP7quj+k+7nfTk6ZpuPfee3HkkUdyv6KCuPDCC/Hss89C13Xcfvvt3K9oXG688UYcd9xxmDt3rnUb9ykqhPPOOw+6ruPggw/Gd77zHe5XJYprUomIpqAf/vCHiEQi+PKXvzzZm0Il4qqrrsJTTz2Fc889F9dcc81kbw5NYa+88greeOMNLF++fLI3hUrMPffcgwcffBB/+ctfoOs6rrjiisneJCoSBqmj1NLSgt27d0NVVQCAqqpob29HS0vLJG8ZTQXZ9p+x3kfTz8qVK7F161bccMMNkGWZ+xUV1PHHH48XXngBM2fO5H5FY/Liiy9i06ZNOOqoo3DkkUdi165dOOWUU7Bt2zbuUzQu4jMPhUJYvnw5/ve///EcWKIYpI5SQ0MDlixZgtWrVwMAVq9ejSVLljAtgPKSbf8Z6300vVx//fVYs2YNbr75ZoRCIQDcr2h8hoaG0NbWZv38xBNPoKamhvsVjdlpp52Gf//733jiiSfwxBNPYObMmbjjjjtwzDHHcJ+iMRseHsbAwAAAQNd1PPzww1iyZAmPVSVK0nVdn+yNmGo2btyIFStWoL+/H9XV1Vi5ciUWLlw42ZtFPnPllVfiscceQ2dnJ+rq6lBbW4u//e1vWfefsd5H08P69euxdOlSzJ8/H2VlZQCAOXPm4Oabb+Z+RWPW2dmJ008/HdFoFLIso6amBj/4wQ+w7777cr+igjjyyCNx6623Yu+99+Y+RWO2fft2nHXWWVBVFZqmYdGiRbjooovQ1NTE/aoEMUglIiIiIiIi32C6LxEREREREfkGg1QiIiIiIiLyDQapRERERERE5BsMUomIiIiIiMg3GKQSERERERGRbzBIJSIiIiIiIt9gkEpERERERES+wSCViIiIiIiIfOP/A9zDLXe7sj9EAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title('MAE')\n",
    "plt.plot(err, c='r')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "accelerator": "GPU",
  "colab": {
   "collapsed_sections": [
    "PF4RcIAUcPC0",
    "052CIIzBcPDr",
    "TDG-dQYqcPEL",
    "BI-jnOpkcPES",
    "hyVUqdUAcPEZ",
    "saTPK1ZAcPEe",
    "CFZ7ChKkcPFD"
   ],
   "name": "00.ipynb",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}