02-First-predictions.ipynb

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    "<img width=\"800px\" src=\"../fidle/img/00-Fidle-header-01.svg\"></img>\n",
    "\n",
    "# <!-- TITLE --> [SYNOP2] - Time series with RNN - Try a prediction\n",
    "<!-- DESC --> Episode 2 : Training session and first predictions\n",
    "<!-- AUTHOR : Jean-Luc Parouty (CNRS/SIMaP) -->\n",
    "\n",
    "## Objectives :\n",
    " - Make a simple prediction (3h)\n",
    " - Understanding the use of a recurrent neural network\n",
    "\n",
    "\n",
    "SYNOP meteorological data, available at: https://public.opendatasoft.com\n",
    "\n",
    "## What we're going to do :\n",
    "\n",
    " - Read our dataset\n",
    " - Select our data and normalize it\n",
    " - Doing our training\n",
    " - Making simple predictions\n",
    "\n",
    "## Step 1 - Import and init\n",
    "### 1.1 - Python"
   ]
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      "\n",
      "FIDLE 2020 - Practical Work Module\n",
      "Version              : 0.5.0\n",
      "Run time             : Sunday 1 March 2020, 21:17:19\n",
      "TensorFlow version   : 2.0.0\n",
      "Keras version        : 2.2.4-tf\n"
     ]
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "from tensorflow import keras\n",
    "from tensorflow.keras.callbacks import TensorBoard\n",
    "from tensorflow.keras.preprocessing.sequence import TimeseriesGenerator\n",
    "\n",
    "import numpy as np\n",
    "import math, random\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import pandas as pd\n",
    "import h5py, json\n",
    "import os,time,sys\n",
    "\n",
    "from importlib import reload\n",
    "\n",
    "sys.path.append('..')\n",
    "import fidle.pwk as ooo\n",
    "\n",
    "ooo.init()\n",
    "\n",
    "def np_print(*args):\n",
    "    with np.printoptions(formatter={'float':'{:8.2f}'.format}, linewidth=np.inf):\n",
    "        for a in args:\n",
    "            print(a)    "
   ]
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   "source": [
    "### 1.2 - Where are we ? "
   ]
  },
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   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Well, we should be at HOME !\n",
      "We are going to use: /home/pjluc/datasets/SYNOP\n"
     ]
    }
   ],
   "source": [
    "place, dataset_dir = ooo.good_place( { 'GRICAD' : f'{os.getenv(\"SCRATCH_DIR\",\"\")}/PROJECTS/pr-fidle/datasets/SYNOP',\n",
    "                                       'IDRIS'  : f'{os.getenv(\"WORK\",\"\")}/datasets/SYNOP',\n",
    "                                       'HOME'   : f'{os.getenv(\"HOME\",\"\")}/datasets/SYNOP'} )"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 2 - Read and prepare dataset\n",
    "### 2.1 - Read it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
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       "<br>**Train dataset example :**"
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       "      <td>72.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>98580.0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>100.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>3.1</td>\n",
       "      <td>270.45</td>\n",
       "      <td>79.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>98680.0</td>\n",
       "      <td>4.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>300.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>268.55</td>\n",
       "      <td>70.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>98980.0</td>\n",
       "      <td>6.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>130.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>4.6</td>\n",
       "      <td>267.45</td>\n",
       "      <td>60.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>99110.0</td>\n",
       "      <td>7.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>150.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>5.7</td>\n",
       "      <td>267.45</td>\n",
       "      <td>59.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>99260.0</td>\n",
       "      <td>8.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>140.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>2.6</td>\n",
       "      <td>268.15</td>\n",
       "      <td>70.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>99400.0</td>\n",
       "      <td>5.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     tend  cod_tend     dd   ff      td     u    ww     pres  rafper  rr1  \\\n",
       "0  -120.0       6.0    0.0  0.0  278.75  88.0  60.0  96250.0     4.1  0.0   \n",
       "1  -150.0       6.0   60.0  1.0  278.65  93.0  61.0  96100.0     2.6  0.2   \n",
       "2    10.0       3.0  280.0  2.1  278.85  95.0  58.0  96110.0     2.6  0.0   \n",
       "3   230.0       3.0  310.0  2.6  279.15  96.0  50.0  96340.0     5.7  0.0   \n",
       "4   280.0       1.0  330.0  4.6  278.15  94.0  21.0  96620.0     8.7  0.4   \n",
       "5   480.0       3.0  350.0  5.1  276.95  91.0  60.0  97100.0     8.2  0.2   \n",
       "6   530.0       2.0  350.0  3.1  274.05  83.0  21.0  97630.0     7.2  0.0   \n",
       "7   450.0       2.0  340.0  6.2  272.15  81.0   2.0  98080.0     9.3  0.0   \n",
       "8   280.0       1.0  320.0  6.2  270.15  74.0   2.0  98360.0    10.3  0.0   \n",
       "9   220.0       1.0  290.0  2.6  269.65  72.0   2.0  98580.0     5.1  0.0   \n",
       "10  100.0       1.0  350.0  3.1  270.45  79.0   2.0  98680.0     4.1  0.0   \n",
       "11  300.0       3.0  350.0  5.1  268.55  70.0   2.0  98980.0     6.7  0.0   \n",
       "12  130.0       1.0   10.0  4.6  267.45  60.0   2.0  99110.0     7.7  0.0   \n",
       "13  150.0       3.0   10.0  5.7  267.45  59.0   2.0  99260.0     8.7  0.0   \n",
       "14  140.0       1.0   50.0  2.6  268.15  70.0   2.0  99400.0     5.7  0.0   \n",
       "\n",
       "    rr3   tc  \n",
       "0   0.0  7.5  \n",
       "1   0.6  6.6  \n",
       "2   0.4  6.4  \n",
       "3   3.0  6.6  \n",
       "4   0.8  5.9  \n",
       "5   0.4  5.2  \n",
       "6   0.0  3.5  \n",
       "7   0.0  1.9  \n",
       "8   0.0  1.1  \n",
       "9   0.0  1.0  \n",
       "10  0.0  0.5  \n",
       "11  0.0 -0.3  \n",
       "12  0.0  1.2  \n",
       "13  0.0  1.5  \n",
       "14  0.0 -0.8  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "<br>**After normalization :**"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >tend</th>        <th class=\"col_heading level0 col1\" >cod_tend</th>        <th class=\"col_heading level0 col2\" >dd</th>        <th class=\"col_heading level0 col3\" >ff</th>        <th class=\"col_heading level0 col4\" >td</th>        <th class=\"col_heading level0 col5\" >u</th>        <th class=\"col_heading level0 col6\" >ww</th>        <th class=\"col_heading level0 col7\" >pres</th>        <th class=\"col_heading level0 col8\" >rafper</th>        <th class=\"col_heading level0 col9\" >rr1</th>        <th class=\"col_heading level0 col10\" >rr3</th>        <th class=\"col_heading level0 col11\" >tc</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468level0_row0\" class=\"row_heading level0 row0\" >count</th>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row0_col0\" class=\"data row0 col0\" >25000.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row0_col1\" class=\"data row0 col1\" >25000.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row0_col2\" class=\"data row0 col2\" >25000.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row0_col3\" class=\"data row0 col3\" >25000.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row0_col4\" class=\"data row0 col4\" >25000.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row0_col5\" class=\"data row0 col5\" >25000.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row0_col6\" class=\"data row0 col6\" >25000.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row0_col7\" class=\"data row0 col7\" >25000.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row0_col8\" class=\"data row0 col8\" >25000.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row0_col9\" class=\"data row0 col9\" >25000.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row0_col10\" class=\"data row0 col10\" >25000.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row0_col11\" class=\"data row0 col11\" >25000.00</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468level0_row1\" class=\"row_heading level0 row1\" >mean</th>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row1_col0\" class=\"data row1 col0\" >-0.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row1_col1\" class=\"data row1 col1\" >-0.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row1_col2\" class=\"data row1 col2\" >0.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row1_col3\" class=\"data row1 col3\" >0.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row1_col4\" class=\"data row1 col4\" >-0.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row1_col5\" class=\"data row1 col5\" >0.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row1_col6\" class=\"data row1 col6\" >0.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row1_col7\" class=\"data row1 col7\" >-0.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row1_col8\" class=\"data row1 col8\" >-0.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row1_col9\" class=\"data row1 col9\" >-0.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row1_col10\" class=\"data row1 col10\" >0.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row1_col11\" class=\"data row1 col11\" >-0.00</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468level0_row2\" class=\"row_heading level0 row2\" >std</th>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row2_col0\" class=\"data row2 col0\" >1.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row2_col1\" class=\"data row2 col1\" >1.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row2_col2\" class=\"data row2 col2\" >1.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row2_col3\" class=\"data row2 col3\" >1.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row2_col4\" class=\"data row2 col4\" >1.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row2_col5\" class=\"data row2 col5\" >1.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row2_col6\" class=\"data row2 col6\" >1.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row2_col7\" class=\"data row2 col7\" >1.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row2_col8\" class=\"data row2 col8\" >1.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row2_col9\" class=\"data row2 col9\" >1.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row2_col10\" class=\"data row2 col10\" >1.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row2_col11\" class=\"data row2 col11\" >1.00</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468level0_row3\" class=\"row_heading level0 row3\" >min</th>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row3_col0\" class=\"data row3 col0\" >-6.80</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row3_col1\" class=\"data row3 col1\" >-1.59</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row3_col2\" class=\"data row3 col2\" >-1.75</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row3_col3\" class=\"data row3 col3\" >-1.37</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row3_col4\" class=\"data row3 col4\" >-5.18</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row3_col5\" class=\"data row3 col5\" >-3.82</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row3_col6\" class=\"data row3 col6\" >-0.52</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row3_col7\" class=\"data row3 col7\" >-4.94</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row3_col8\" class=\"data row3 col8\" >-1.64</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row3_col9\" class=\"data row3 col9\" >-0.31</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row3_col10\" class=\"data row3 col10\" >-0.27</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row3_col11\" class=\"data row3 col11\" >-3.03</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468level0_row4\" class=\"row_heading level0 row4\" >25%</th>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row4_col0\" class=\"data row4 col0\" >-0.64</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row4_col1\" class=\"data row4 col1\" >-0.85</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row4_col2\" class=\"data row4 col2\" >-0.64</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row4_col3\" class=\"data row4 col3\" >-0.76</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row4_col4\" class=\"data row4 col4\" >-0.72</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row4_col5\" class=\"data row4 col5\" >-0.71</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row4_col6\" class=\"data row4 col6\" >-0.42</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row4_col7\" class=\"data row4 col7\" >-0.55</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row4_col8\" class=\"data row4 col8\" >-0.69</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row4_col9\" class=\"data row4 col9\" >-0.15</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row4_col10\" class=\"data row4 col10\" >-0.20</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row4_col11\" class=\"data row4 col11\" >-0.75</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468level0_row5\" class=\"row_heading level0 row5\" >50%</th>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row5_col0\" class=\"data row5 col0\" >-0.00</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row5_col1\" class=\"data row5 col1\" >-0.48</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row5_col2\" class=\"data row5 col2\" >-0.12</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row5_col3\" class=\"data row5 col3\" >-0.19</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row5_col4\" class=\"data row5 col4\" >0.05</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row5_col5\" class=\"data row5 col5\" >0.18</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row5_col6\" class=\"data row5 col6\" >-0.42</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row5_col7\" class=\"data row5 col7\" >0.03</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row5_col8\" class=\"data row5 col8\" >-0.27</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row5_col9\" class=\"data row5 col9\" >-0.15</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row5_col10\" class=\"data row5 col10\" >-0.20</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row5_col11\" class=\"data row5 col11\" >-0.01</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468level0_row6\" class=\"row_heading level0 row6\" >75%</th>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row6_col0\" class=\"data row6 col0\" >0.63</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row6_col1\" class=\"data row6 col1\" >0.99</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row6_col2\" class=\"data row6 col2\" >1.08</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row6_col3\" class=\"data row6 col3\" >0.50</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row6_col4\" class=\"data row6 col4\" >0.79</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row6_col5\" class=\"data row6 col5\" >0.84</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row6_col6\" class=\"data row6 col6\" >-0.37</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row6_col7\" class=\"data row6 col7\" >0.61</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row6_col8\" class=\"data row6 col8\" >0.52</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row6_col9\" class=\"data row6 col9\" >-0.15</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row6_col10\" class=\"data row6 col10\" >-0.20</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row6_col11\" class=\"data row6 col11\" >0.72</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468level0_row7\" class=\"row_heading level0 row7\" >max</th>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row7_col0\" class=\"data row7 col0\" >7.16</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row7_col1\" class=\"data row7 col1\" >1.36</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row7_col2\" class=\"data row7 col2\" >1.34</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row7_col3\" class=\"data row7 col3\" >6.28</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row7_col4\" class=\"data row7 col4\" >2.40</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row7_col5\" class=\"data row7 col5\" >1.62</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row7_col6\" class=\"data row7 col6\" >4.46</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row7_col7\" class=\"data row7 col7\" >3.10</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row7_col8\" class=\"data row7 col8\" >6.29</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row7_col9\" class=\"data row7 col9\" >30.36</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row7_col10\" class=\"data row7 col10\" >31.27</td>\n",
       "                        <td id=\"T_a7c146fa_5bf9_11ea_a502_85a858c76468row7_col11\" class=\"data row7 col11\" >3.02</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f3c9dde0d50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dataset :  (29165, 14)\n",
      "Train dataset :  (25000, 12)\n",
      "Test  dataset :  (4165, 12)\n"
     ]
    }
   ],
   "source": [
    "dataset_filename = 'synop-LYS.csv'\n",
    "schema_filename  = 'synop.json'\n",
    "train_len        = 25000\n",
    "features         = ['tend', 'cod_tend', 'dd', 'ff', 'td', 'u', 'ww', 'pres', 'rafper', 'rr1', 'rr3', 'tc']\n",
    "features_len     = len(features)\n",
    "\n",
    "# ---- Read dataset\n",
    "\n",
    "df = pd.read_csv(f'{dataset_dir}/{dataset_filename}', header=0, sep=';')\n",
    "\n",
    "# ---- Train / Test\n",
    "\n",
    "dataset_train = df.loc[ :train_len-1, features ]\n",
    "dataset_test  = df.loc[train_len:,    features ]\n",
    "ooo.subtitle('Train dataset example :')\n",
    "display(dataset_train.head(15))\n",
    "\n",
    "# ---- Normalize, and convert to numpy array\n",
    "\n",
    "mean = dataset_train.mean()\n",
    "std  = dataset_train.std()\n",
    "dataset_train = (dataset_train - mean) / std\n",
    "dataset_test  = (dataset_test  - mean) / std\n",
    "\n",
    "ooo.subtitle('After normalization :')\n",
    "display(dataset_train.describe().style.format(\"{0:.2f}\"))\n",
    "\n",
    "dataset_train = dataset_train.to_numpy()\n",
    "dataset_test  = dataset_test.to_numpy()\n",
    "\n",
    "\n",
    "print('Dataset : ',df.shape)\n",
    "print('Train dataset : ',dataset_train.shape)\n",
    "print('Test  dataset : ',dataset_test.shape)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2 - Prepare data generator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Nombre de train batchs disponibles :  781\n",
      "batch x shape :  (32, 16, 12)\n",
      "batch y shape :  (32, 12)\n"
     ]
    }
   ],
   "source": [
    "sequence_len = 16\n",
    "batch_size   = 32\n",
    "\n",
    "# ---- Train generator\n",
    "train_generator = TimeseriesGenerator(dataset_train, dataset_train, length=sequence_len,  batch_size=batch_size)\n",
    "test_generator  = TimeseriesGenerator(dataset_test,  dataset_test,  length=sequence_len,  batch_size=batch_size)\n",
    "\n",
    "# ---- About\n",
    "\n",
    "x,y=train_generator[0]\n",
    "print(f'Nombre de train batchs disponibles : ', len(train_generator))\n",
    "print('batch x shape : ',x.shape)\n",
    "print('batch y shape : ',y.shape)\n",
    "\n",
    "# x,y=train_generator[0]\n",
    "# np_print(x[0])\n",
    "# np_print(y[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 3 - Create a model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = keras.models.Sequential()\n",
    "model.add( keras.layers.InputLayer(input_shape=(sequence_len, features_len)) )\n",
    "model.add( keras.layers.LSTM(100, activation='relu') )\n",
    "model.add( keras.layers.Dropout(0.2) )\n",
    "model.add( keras.layers.Dense(features_len) )\n",
    "\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Step 4 - Compile and run"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.1 - Callback"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "os.makedirs('./run/models',   mode=0o750, exist_ok=True)\n",
    "save_dir = \"./run/models/best_model.h5\"\n",
    "bestmodel_callback = tf.keras.callbacks.ModelCheckpoint(filepath=save_dir, verbose=0, save_best_only=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.2 - Compile"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.compile(optimizer='adam', \n",
    "              loss='mse', \n",
    "              metrics   = ['mae'] )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.3 - Fit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%time\n",
    "\n",
    "history=model.fit_generator(train_generator, \n",
    "                            epochs=10, \n",
    "                            verbose=1,\n",
    "                            validation_data = test_generator,\n",
    "                            callbacks = [bestmodel_callback])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ooo.plot_history(history,plot={'loss':['loss','val_loss'], 'mae':['mae','val_mae']})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 5 - Predict"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.1 - Load model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "loaded_model = tf.keras.models.load_model('./run/models/best_model.h5')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.2 Make a prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1152 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "s=random.randint(0,len(dataset_test)-sequence_len)\n",
    "\n",
    "sequence      = dataset_test[s:s+sequence_len]\n",
    "sequence_true = dataset_test[s:s+sequence_len+1]\n",
    "\n",
    "pred = loaded_model.predict( np.array([sequence]) )\n",
    "\n",
    "# ---- Show result\n",
    "reload(ooo)\n",
    "ooo.plot_multivariate_serie(sequence_true, predictions=pred, labels=features)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.3 Full prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gap between prediction and reality : 1.27 °C\n"
     ]
    },
    {
     "data": {
      "image/png": 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OzR09WJlvuPzFNGIJUcF47ttLMCE2DP9+XR5vJqMxs7vcCiHWA/glgI0A7pBS2i6+ZmDLr38CWCyEmHrBY0MBrANQCu6UQEREHsJqs+HZbcVYtzwbWg1PrHemgoxYHCxrUB2DvIBdr68IIb4N4FcAzgLYCuDmi85iqJdSfjDw+58BWAbgX0KI/wbQAuBu9I8lXD3Eai8REZFbeu9IFaLDdJiVEac6itcrSI/Fix+W4FbuRkFjZO/w0OAATAqAF4f4+E4AHwCAlLJMCDEPwKMAfgogAMBhAKuklFvHFpeIiMg1Orr78MquUmxYMxM8XNP5JidH4UxDG1o6ehAeHKA6Dnkwu8qtlPJ2ALfb+0mllMUAvjS6SEREROq9vrcc01JjkJkQoTqKTwjw0yJ3fDQOVzZi8eTEyz+AaBgcICIiIrpIY0sX/nnwDG5bzJfIXakgnXO3NHYst0RERBd5aWcJVuUnY1wk79x3pYL0WBwsb4CNt+fQGLDcEhERXaCyvgX7S89hzfwM1VF8TmJ0CIICtaisb1EdhTwYyy0REdEFntlmxJp5GQjV+auO4pMGV2+JRovlloiIaMDhikaYzrfjmoLxqqP4rJnpcSy3NCYst0RERACsNomntxbjrqXZ8Nfy26MqeeOjUVrbjPbuXtVRyEPx/14iIiIA24+bEOivwfyceNVRfJouwA85higcrTSrjkIeiuWWiIh8XnevFS/sKMHdy3N4YIMbKEiPRSFHE2iUWG6JiMjn/W1/JbISIzE5OVp1FEJ/uT1U3gDJLcFoFFhuiYjIp1nau/HmvgrctTRbdRQakBITCpuUqDK3q45CHojlloiIfNoru0uxeEoikvQhqqPQACEEtwSjUWO5JSIin1VtbsOOEzW4ZUGm6ih0EZZbGi2WWyIi8lnPbS/BV+ekITIkUHUUusi01BicrDqP7l6r6ijkYVhuiYjIJ504ex6naiy4flaq6ig0hBCdP9LjI3DsDLcEo5FhuSUiIp8jpcQzW4tx2+IsBPprVcehYXA0gUaD5ZbIwWqbOnD3kzux+pF3cfeTO1Hb1KE6EhFdZHdxHXr6bFiWl6Q6Cl3CzPRYHCxjuaWRYbklcrD1mwtR1dg2sI1NG9ZvLlQdiYgu0Gu14bntRqxbngMND2xwa2nx4Wjv7uMiAY0Iyy2RA0kpUdXYBvnp+0A192kkcitvHzwDgz4E09NiVEehy9AIgRnpMRxNoBFhuSVyEJuU+N/3TsDfT4MLF4PCg/15yg6Rm2jr6sWrH5Vh3bIc1VHITpy7pZFiuSVyAJuU+OM7x1FR34rH7pyLZH0oNEIgKToYYboA/Nc/j6Gnj9vZEKm2+aMyzJk4DhPiwlRHITtNT4vFsTNm9FptqqOQh/BTHYDI01ltEo+9fQw1TR349c2zEBzoh6e/tejTj3f29OH3bxXhpy/vx/obZnA/TSJF6i0d2FJUhf/7xkLVUWgEIoIDkKwPxSdV55E/gaMkdHlcuSUaA6tN4j//cRR1lg78eu1MBAd+8efFoAA/PHjDDOSN1+O+5/agsr5FQVIieuHDElxbMB76MJ3qKDRCBdw1gUaA5ZZolKw2G373VhHOt3Xj4bWzoAsY/oUQjRC4fUkWbl+chZ+8vB97S+pdmJSISmubUXTajBvmpKuOQqNQkMG5W7IfxxKIRqHPasOjfytCR08ffnVTgd2bwC/NTUJidDA2vH4IZxvbcOPcNAhuRUTkVFJKPL21GLcuzBzy1RVyf1mJEWho6YK5tYsr73RZXLklGqFeqw2/efMwuvus+OWNM0Z8ulF2UhQev3Medp2swR/+cZQ3mhE52YGyc2hq68aqacmqo9AoaTUaTE/jlmBkH5ZbohHo6bPikTcOwyqBX3x1OgL8RndsZ2x4EP7ztjno7rXi/o370NTW7eCkRAT0jw89s9WIu5ZlQ6vhtzxPVpAei0LO3ZId+H86kZ16+qx4+PVD0GoEHhxDsR2kC/DDz78yHdNTY3Hfc3tQXtfsoKRENOj9ompEhgTgisw41VFojArSY3GkshFWG7cEo0tjuSWyQ3evFb/8yyEE+vvh51+eBn+tY/7X0QiBry+eiLuWZeNnrxzAHmOdQz4vEfVvw7dx5yncvTyHs+1eQB+mQ1xEEIwmi+oo5OY4WU90GV29VvzytYOICA7A/ddPdcpLm4snJyIxKhi/GrjRbM28dH4zJhqjN/ZWIG+8HhMTI1VHIQcZPK1scnK06ijkxrhyS3QJXT19+MWrBxAdGoj7r8936szexMRIPH7HPHxsrMN/vFWE7l7eaEY0WubWLvy98DTuWJqlOgo5EI/iJXuw3BINo6O7Dw+8Woj4yGD8+3VTodU4fyU1JlyH3982BzabxI9f2gdza5fTn5PIG23ceQor85MRHxmsOgo50KTkKFSb22Fp5024NDyWW6IhtHf34oFNB5CsD8EPrs1zSbEdpPPX4mdfnoYrMuPwvef2oLSWN5oRjcTpc634uKQea+ZlqI5CDuav1WDqeD0OVzSqjkJujOWW6CJtXb34+SsHkDYuDPddnQuNgtlXIQRuWZiJb6yYhAc2HcDu4lqXZyDyVM9uK8aaeekIC/JXHYWcgKeV0eWw3BJdoKWzBz97eT+ykyLxndVTlBTbCy2YlIBf3zwL//evk3h5VymklErzELm7ospGnG1swzUF41VHIScpSIvFoYoG2Pj1kIbBcks0oKWjv9hOGR+Nb145yW12K8hMiMDjd85DYdk5/PavR3ijGdEQaps6cPeTO/GTl/ejzyphbuVMpreKjwpGqM4f5XUtqqOQm2K5JQJgae/G/Rv3YVpqDO5xwz0x9WE6/P7rs6HVCPzoxb280YzoIus3F6KqsQ0AYG7rwvrNhYoTkTNx1wS6FJZb8nlNbf3FdvbEcbhrWbbbFdtBAX5a3H99PuZlx+O+5/bgVA03MicaVG1ux+CL1FL2v0/ei+WWLoXllnyaubUL92/ch4U5Cbht8US3LbaDhBBYMz8D3145GQ++Wogdn9SojkTkFhKjP9vySwjAoA9RmIacLW+8HhV1LWjr6lUdhdwQyy35rMaWLtz/0j4smZKIWxe5f7G90NzsePz2livw3DYjXtpxijdWkM+7aV46Av010AiBZH0oNqyZqToSOVGgvxaTkqNwpJJbgtEX8fhd8knnmjvxk5f3YVV+Cm6al646zqikx4fj8Tvn4VevH8TZxlb86Ev50PlrVcciUuKcpRPXFUzAuuU5qqOQiwyOJizISVAdhdwMV27J59RbOnD/xn24ZsZ4jy22g6JCA/G7r81GoL8W//7Cx2ho6VQdiUgJY40FOYYo1THIhQbLLbdIpIux3JJPqWvqwI837sP1sybgK7PTVMdxiAA/LX503VQsmpyI7z23B0ZTk+pIRC4lpYTRZEF2UqTqKORCBn0ItBqBMw1tqqOQm7Gr3AohfiaEeF0IUSGEkEKI05e5frUQYpsQok4I0S6EKBFC/EEIMc4hqYlGwXS+HT/euA83zEnD9bNSVcdxKCEEbpybju+uzsX6zQex/bhJdSQil6k53wGdvxb6MJ3qKORCQgjumkBDsnfl9jcAlgIoB3DJZSEhxN0A3gUQAeA/APwAwC4A3wewVwjBW1jJ5arNbbh/4z6snZ+BawsmqI7jNHOyxuE/br0CL+wowQsflvBGM/IJxaYmZCdxJMEXsdzSUOwtt+lSSr2UcgWAy+099CMAtQDmSyn/W0r5lJTybgCPAkgFsGL0cYlG7mxjG36ycT++vmgirpqeojqO06WOC8cf75yHY2fMeOT1Q+js6VMdicipOJLgu/InxMBoakIXv87RBewqt1LKihF8znAATVLKi49QGizF3FmbXOb0uVb8ZOM+3L4kCyvzk1XHcZnIkEA8eusVCNH544cv7MW5Zt5oRt7LaLIgx8By64uCA/2QmRCBo2fMqqOQG3HGVmDvA7hNCPGfAJ4B0AZgJoBfANgJYLsTnpPoCyrqW/DApgO4e3kOluYmqY7jcgF+Wvzw2jy8ua8S33nmI+gCtGho7oJBH4INa2YiISr48p+EyM1191pxtqEVGfERqqOQIgXpcThY3oArMnlbD/Vzxm4J3wPw+sDbkwDOAngTwHsAVkgprU54TqLPKa9rxgObDuCbV07yyWI7SAiBr85JQ4CfBvWWTtikRJW5Des3F6qORuQQZXXNSIkNQyD3ePZZnLulizmj3Paiv9D+DcBtAG5A/wrubQCeGO5BQoh7hBAHnZCHfExpbTN+vukA7l01GYsmJ6qO4xbMrd2f/l5KoNrM6SDyDpy3pbRxYejqscJ0nl/XqJ9Dy60QQgNgC4C5AG6UUr4kpXxj4Iay3wNYJ4RYPtRjB248K3BkHvI9RpMFD2w6gO9dnctTay5g0Idg8HRhIfrfJ/IGxdUst75ucEuwQ1y9pQGOXrmdD2ABgDflF48MeX3g7SIHPycRAOBkdRPWby7ED6/Nw9yseNVx3MqGNTORrA8FAMSE6bBhzUzFiYgco6SG5Zb6RxMKWW5pgKNvKBscbhxq+MnvordEY1bb1IH1mwtRbe4/oeb71+Ri9kTeVHCxhKhgPP2tRdhy5CwOlDXwZjLyCubWLnT29CEpmq9E+LppaTF47O3j6OmzIsCP89e+ztErtycH3t4ihPC/6GO3D7zlnSzkMOs3F6KqsQ022T9L+sbeStWR3NqCnAQUVTaipaNHdRSiMSsZmLcVgzM35LPCgwIwPi4UJ87y+HGycxVVCPE1AOMH3o0FECCEeHDg/TNSyo0AIKU8KoR4E8BXABwUQrwMoAPASgDXAtgH4O8OzE8+rtrcjsH5FwneKHU5ITp/zMyIw86TNV59Uhv5hmKTBdmJHEmgfv1bgp3D9LQY1VFIMXtXbu8C8PDArzgAkRe8f9dF194M4CcDv98A4L8AZAP4LYDl3AqMHCk06LOfz3ijlH2W5yVh6zGT6hhEY2Y0NSHbwGN3qR+3BKNB9p5QtlhKKYb5tfiia3uklL+TUk6VUgZJKQOllBOllD+XUnJZjRzG3NoFq1UiMToYGiGQrA/ljVJ2mJ4Wg3PNnahqbFMdhWjUrDYbSmubkcWVWxqQmRCBprZunshIvLmLPNdLO07hqukpWLc8R3UUj6LVaLBkSiK2HTfh9iVZquMQjcrpc23Qh+kQFnTx7R3kq7QagelpsThU0YDV01JUxyGFnHGIA5HTVda3YF9pPdbMz1AdxSMtzzNg23ETbF/YsY/IM3ALMBpKQXosDpZxNMHXsdySR3pmmxFr52cgVMdVm9FIGxeOUJ0/jp85rzoK0agUVzchO4nztvR5M9JjUHS6EX1Wm+oopBDLLXmcwxWNqGlqx9Uzxl/+YhpW/41l1apjEI0Kj92loUSH6hAfGQyjyaI6CinEcksexSYlntlajDuXZMNfy/98x2LJlER8XFKHrp4+1VGIRqS9qxfnmjuRGhemOgq5Ie6aQGwH5FG2HTMhwF+D+Tk8XnesokN1yDFE4eOSetVRiEakpKYZ6fHh8OMPuDSEgow4llsfx68M5DG6e614cUcJ7l6ewxOJHGR5roGjCeRxjKYm5HB/WxpGTlIkapva0dTWrToKKcJySx7jb/srkZUYicnJ0aqjeI05WeNQUtOMxpYu1VGI7MZ5W7oUP60GUyfE4FAFV299FcsteQRLezfe3FeBO5dmq47iVQL9tZifE48PT/DEMvIMUkqWW7oszt36NpZb8giv7C7FkilJSOLxug63PM+AD45VQ3LPW/IAdZZO+Gs1iA0PUh2F3FhBeiwOVzTCauPXNV/Ecktur9rchh0nanDLwkzVUbzS5OQodPdaUV7XojoK0WUVVzchi6u2dBlxEUGICA5AWV2z6iikAMstub3ntpfgq3PSEBEcoDqKV9IIgWW5Bmw9ztEEcn9GkwU5LLdkh4IMnlbmq1huya19UnUep2osuH5WquooXm1ZXhI+PGHiqT7k9jhvS/bi3K3vYrkltyWlxNMfFOP2JVkI9NeqjuPVkqJDkBgVwm8E5NZ6+qw4fa4FmQkRqqOQB8hNicbpc61o7exVHYVcjOWW3Nbu4jr0Wm1YmpukOopP6D+Ol6MJ5L7K61pg0IdCF+CnOgp5gAA/LaakRJzbuSIAACAASURBVOFIZaPqKORiLLfklnqtNjy33Yh1y3Og4YENLrFwUiIOVTRwlYPcVrHJgmwDRxLIfv2nlZ1THYNcjOWW3NLbB8/AoA/BtNQY1VF8RliQP2akxWB3ca3qKERDKuG8LY3Q4Nwttzr0LSy35HbaunqxeU8Z1i3LUR3F5yzP43G85L6KTU3ITuKxu2S/pOgQBPhpcfpcq+oo5EIst+R2Nn9UhtkTx2FCXJjqKD6nID0WpvPtqDnfrjoK0ec0tXWjvasXBh7kQiPEXRN8D8stuZV6Swe2FFXh64smqo7ik/y0GiyenIht3POW3IzRZEFWYiRn8GnECtJjUchy61NYbsmtvPBhCa4rmAB9mE51FJ81OJrAGTVyJ0aOJNAoTZ2gx6kaCzq6+1RHIRdhuSW3UVrbjKLTZtwwN011FJ+WER+OQH8tTlQ1qY5C9Cke3kCjFRTgh6ykSBw9bVYdhVyE5ZbcgpQST28txq0LMxHEPSyVEkLwxjJyK1abxKnaZpZbGrX+uVtuCeYrWG7JLRwoO4emtm6smpasOgoBWDolCR8V16G716o6ChGqGtsQGRKA8OAA1VHIQ81Mj0MhtwTzGSy3pJzVZsMzW424a1k2tBr+J+kOYsJ1mJgYgb2n6lVHIUKxqQk5nLelMRgfGwqrVcLEnWB8ApsEKfd+UTUiQwJwRWac6ih0geW5SdjG0QRyA0aTBVkcSaAxEEJwSzAfwnJLSnX29GHjzlO4Z8UkCG7x41bmZcfjZHUTzrd1qY5CPs5YbUEOyy2NUUEGy62vYLklpd7YW4GpE/TITIhQHYUuogvww5yseOw4UaM6Cvmwju4+1Fo6kDouXHUU8nDTUmPwydkm3kvgA1huSRlzaxf+Xngaty/JUh2FhrE8Lwlbj/FAB1LnVI0F6ePC4a/ltysam1CdP1LHheHE2fOqo5CT8asFKbNx5ymszE9GfGSw6ig0jLzxerR09qCivkV1FPJR3N+WHIlzt76B5ZaUOH2uFR+X1GPNvAzVUegSNEJgWW4S97wlZYpZbsmBZmbEsdz6AJZbUuLZbcVYMz8DYUH+qqPQZSzLM+DDEzWw2myqo5CPkVKixGRBjoHbgJFjpMeHo7mjB/WWDtVRyIlYbsnliiobUWVux7UF41VHITukxIQiNjwIhysaVUchH1Pf3AkhgNhwneoo5CU03BLMJ7DckkvZBo7ZvWNJFm8Q8SC8sYxUGJy35TaB5Egst96P7YJc6sPjJvhpNVg4KUF1FBqBxZMTUVh2Du3dvaqjkA/hzWTkDNPTYnD0tBm9Vo5aeSuWW3KZ7l4rXthxCncvz+FKjIcJDw5A/gQ9PiquUx2FfIjR1IRsHrtLDhYZEoik6BAUVzepjkJOwnJLLvPWgdPIjA/HlJRo1VFoFJbnGbhrArlMT58VFfWtmJjIA17I8QrSY3GwjKMJ3orlllyiuaMHb+wtx53LslVHoVGamRmHMw1tqONdxuQCFfWtSIwKRlCAn+oo5IV4FK93Y7kll9i0uxSLJifCoA9VHYVGyX9gVnobbywjFygxNXHelpwmOykS9c2dMLd2qY5CTsByS05nOt+O7cdNuHVhpuooNEbL8wzYerwaUkrVUcjLFXN/W3IirUaDaakx3OLQS7HcktM9v92IL89OQ2RIoOooNEZZiRHQCIFik0V1FPJyRpMFWYlcuSXnmcnRBK/FcktOdbK6CcUmC/7tilTVUcgBhBC8sYycztLejeaOHqTEcoyJnGdGWiwOVzTAauMrUd7GrnIrhPiZEOJ1IUSFEEIKIU7b8ZivCSH2CCFahBBtQogTQohfjDkxeQwpJZ764CRuX5wFnb9WdRxykGW5Sdh1shY9fVbVUchLldT0r9pquGUgOVFMuA76MB1Ka/lKlLexd+X2NwCWAigHcNmN4YQQzwF4AYAJwE8B/DuAtwHwvFUf8pGxDt29NizNTVIdhRwoLiIIaePCsb/0nOoo5KWM1Ty8gVyDW4J5J3vLbbqUUi+lXAGg5lIXCiHuAnAHgNullDdKKZ+QUv6flPKnUsp1Yw1MnqHXasNz241YtzwbWg1XX7wNj+MlZzLWsNySaxSkx6KQc7dex65yK6WssOc60X/s1M8AHJZSbhz4szDB46h8zruHziAhKgQz0mJVRyEnmJ+dgONnzLC0d6uOQl7GJiVKeOwuucik5CicbWxDS0eP6ijkQI6+oSwLQDqAj4UQvxBCmAG0ALAIIf4shODdAT6gvasXmz4qwzoe2OC1ggP9MHviOOz85JIv5BCNWHVjG8KDA7i7CrlEgJ8WeSnR3BLMyzij3ALATeifs/0tgK8C+CuAbwD4J1dxvd9re8oxKyMOaePCVUchJ1qWl4QPOJpADlbMLcDIxXhamfdxdLkNG3gbC+CrUso/SCnflFLeAeBFAIsBrBrqgUKIe4QQBx2ch1zsXHMn3j1yFrctzrr8xeTR8ifE4HxbF06fa1UdhbyI0WRBjoHlllynID0OhyoaYOPhNF7D0eW2c+CtSUq59aKPvTjwdvFQD5RSPiWlLHBwHnKxFz4swbUzxiMmXKc6CjmZViOwdEoSth3n6i05jpHztuRiCVHBCA7wQ2V9i+oo5CCOLreDO7vXDfGx2oG3PE/RS5XVNuNIZSNumJuuOgq5yPI8A7YfN3ETdHKIzp4+mM63c6SJXI6jCd7F0eX2OPpXb4fa2NQw8JabY3ohKSWe3laMmxdkIjjQT3UccpEJcWGIDAnA0dNm1VHIC5TWNiM1LgwBfjz0hVyrIJ3l1ps4tNxKKTvQf/NYvBDi3y768LcG3r7ryOck93CwvAGNLV1YPS1ZdRRyMR7HS45SzMMbSJHc8XqU1jajvbtXdRRyALuW2IQQX8Nnp4vFAggQQjw48P6ZwT1tB/wcwHIAm4QQ/wPgNICrAFwN4CUp5ceOCE7uw2qz4emtxbhrWTb8tI5+MYDc3ZIpidi48xQ6e/oQFMBVexq9ElMTFk5KVB2DfJDOX4tJhigcrTRjbna86jg0RvY2kbsAPDzwKw5A5AXv33XhhVLKswBmo38F9w4Aj6F/79sfD7xPXuZfR6sRHhSAORPHqY5CCkSGBCI3JRofFQ81ak9kHyklinkzGSnE08q8h13LLFLKxSP5pFLK0wBuGUUe8jBdPX3YuPMUHrqxANzC2HctzzPg7UNnsGKq4fIXEw2hoaULNikxLjJIdRTyUQXpsXjrwGlIKfn9zMPxNWQakzf2VSI3Rc9N133cFRPjUF7fgnPNnZe/mGgIRpMF2YmRLBWkTHJMKCSAqsY21VFojFhuadTOt3XhrQOVuGMJD2zwdQF+WizIScB27nlLo2Q0NSHbwJ0iSR0hBHdN8BIstzRqG3eWYsVUA+KjglVHITewPC8JW49VQ/KUHxoFHt5A7oDl1juw3NKonGloxR5jHdbOz1AdhdzEJEMU+mwSp2qbVUchD9NntaG8rgUTEyNURyEfl5+qx8nqJnT1WlVHoTFguaVReXabETfNS0d4UIDqKOQmhBDc85ZGpfJcK8ZFBiEk0F91FPJxIYH+yEyIwPEzPJjGk7Hc0ogdPW3GmYZWXFsw/vIXk09ZlpuEnZ/UotdqUx2FPIjR1IScJM7bknvgaILnY7klu9U2deDuJ3fi/o370GeVMLd2q45EbiYhKhjJMaEoLOMp22S/4moLsjhvS26iID0WB8tYbj0Zyy3Zbf3mwk+3SDG3dWH95kLFicgd9d9Yxl0TyH5GkwU5LLfkJtLGhaOjpw+1TR2qo9AosdyS3arN7Ri8D17K/veJLrYwJwFFlY1o6ehRHYU8QEtHD5raupESG6Y6ChGA/vsHZqRxNMGTsdyS3aJCPrt5TAjAoA9RmIbcVYjOHzMz4rDzZI3qKOQBSmosyEyMgFbDwxvIfaTHh+PZbcVY/ci7uPvJnVzF9TAst2QXq03CX6tBXIQOGiGQrA/FhjUzVcciN8XRBLIX97cld/T2oTPo7LHCJiWqzG0cw/MwfqoDkGfYdbIG+nAd/vO2OTweky5reloM/uufx1DV2IbkmFDVcciNFZssuGZGiuoYRJ9Tc/6zlVqO4XkertzSZdmkxKbdZbh5QSaLLdlFq9Fg8ZREbONxvHQJNilRwpVbckMGfQgGv9txDM/zsNzSZe0prkNQgB9mpMWojkIeZHmuAduOm2Djcbw0DJO5HSGBfogO1amOQvQ5G9bM/LTQJkaFcAzPw7Dc0iXZpMQru0tx84IMrtrSiKTHhyMk0A/Hz5xXHYXcFOdtyV0lRAXjmXsX46rpKViel4SEqGDVkWgEWG7pkvadqodWI3BFZpzqKOSBeBwvXYrR1MRyS25t9bRkvF9UxVegPAzLLQ1LSolXdpVy1pZGbcmURHxcUoeuXqvqKOSGjCYLsg08dpfcV2ZCBIIC/HD0tFl1FBoBllsaVmFZA6w2iTlZ41RHIQ+lD9MhxxCFj411qqOQm+nqtaLK3I6M+HDVUYiGJYTA6mnJ2HKkSnUUGgGWWxqSHJi1XTs/Axqu2tIYLM/laAJ9UVltM8bHhiLAT6s6CtElLclNQmHZOZ666EFYbmlIhysb0dHdh/k5CaqjkIebkzUOJTXNaGzpUh2F3EixqQk5SRxJIPcXHhSAmRlx2H6CWxt6CpZb+oLBWdu18zN4JCaNWaC/FvOz4/EhvzHQBYzV3CmBPMfgaILkjWUegeWWvuDYmfOwtPdg0WSu2pJjLM9LwgfHqvmNgT5lrGG5Jc+RN0GPrl4rTtU2q45CdmC5pS/YtLsUa+anQ6vhfx7kGJNTotHVa0V5XYvqKOQGGlu60Ntn496h5DE0QuDKqQbeWOYh2F7ocz6pOo86SweWTklSHYW8iEYILMtNwlYex0vo3982KymSWwySR7lyajJ2naxFV0+f6ih0GSy39Dmv7C7DTfMy4KflfxrkWMtzDfjwhAl9VpvqKKSY0WRBdiJHEsizxITrMDk5CruKa1VHoctgg6FPGU0WVDW2YcVUg+oo5IWS9CFIiArGwfIG1VFIsf7DG1huyfOsyueet56A5ZY+tWl3KW6cmwZ/rtqSk6zIM2DrMY4m+DKrzYbS2mZkceWWPNCszDjUNnXgbGOb6ih0CWwxBAAorW1GeV0LVuYnq45CXmzhpEQcqmhAa2ev6iikyOlzrYiLCEKozl91FKIR89NqsDzPgPeLuHrrzlhuCQDw6u5SfHVOGk8LIqcKC/LHjLQY7ObMms8qNlmQxS3AyIOtzO8/dbGX9w+4LZZbQkV9C4pNFqyenqI6CvmA5Xk8jteXGU0W5LDckgcz6EORrA/F/lP1qqPQMFhuCa9+VIYvz06Fzp+rtuR8BemxqDa3o+Z8u+oopICxugnZPHaXPNyqacnYwtEEt8Vy6+PONrTi2BkzrpkxXnUU8hF+Wg2WTEnENu5563PaunrR2NqFCXGhqqMQjcn8nAQUV1twrrlTdRQaAsutj3v1ozL826xUBAX4qY5CPmRwNIHH8fqWEpMFmQkRPP2QPJ7OX4vFkxPwwVGOWLkjfoXxYSZzOw5VNOLamVy1JdfKiA9HgJ8Wn1Q1qY5CLlRssnALMPIaq6al4P2jVbDxh3S3w+U6H/bqnjJcN3MCQgK5JQ+5lhACszLjsP61QnR2W2HQh2DDmplIiApWHY2cqMTUhFXTeOMqeYfMhAiEBvqjqNKM6WkxquPQBbhy66Nqmzqw71Q9rp81QXUU8lF7S+rQ3tUHm5SoMrdh/eZC1ZHIiaSU/SeTcacE8iKrpiVjy5GzqmPQRVhufdRre8pw7Yzx3EidlKlt+uxGDCmBajN3T/BmNU0dCPTXQh+mUx2FyGGWTEnCwfIGtHT0qI5CF2C59UHnmjvxkbEO/3ZFquoo5MMM+hAI0f97IfrfJ+/VvwUYV23Ju4QF+eOKzDju/uJmWG590F8+LsfqaSkIDw5QHYV82IY1M5GsD4UAEOinxa9uKlAdiZzIWGPh/rbklVZNS8GWI1Xc/cWNsNz6mMaWLnx4ogZfmc1VW1IrISoYT39rEd7++WokRAWjpMaiOhI5kbGa87bknfLGR6O7z8qvYW6E5dbHvL63HFfmGxAZEqg6ChGA/kMdvn9NLp76oBgtnZxb80bdvVacaWxDRkKE6ihEDieEwKr8ZGw5whPL3AXLrQ8539aFrcdM+OrsNNVRiD4nOykK87Lj8exWo+oo5ARldc1IiQnlEd/ktVZMNWB3cS06e/pURyHYWW6FED8TQrwuhKgQQkghxGl7n0AI8buBx7SNOiU5xJv7KrEsN4l3K5NbumNpFg5WNODYGbPqKORgJdwCjLycPkyHKcnR2HWyVnUUgv0rt78BsBRAOQC7jxQSQuQD+AEAFlvFLO3deL+oCjfM5aotuaeQQH/cu3IyHn/nOHr6rKrjkAMVs9ySDxi8sYzUs7fcpksp9VLKFQBq7HmAEEIL4GkA7wE4NMp85CB/3V+JhZMSEBsepDoK0bDmZccjWR+K1/aUq45CDsSVW/IFszJjUWfpwJmGVtVRfJ5d5VZKWTGKz30fgEkAvjuKx5IDtXT24N3DZ3HT3HTVUYgu69urJ+MfhadxtpEv+HgDc2sXOnr6kBTNfYzJu2k1GqzIM2BLEVdvVXPKDWVCiPEAHgbwKynlGWc8B9nvrf2nMS8rHuMig1VHIbqs2PAg3LowE4+/cxw27hvp8UpMFmQlRkIMnthB5MVW5idj2zETeq021VF8mrN2S3gSQCWA/7L3AUKIe4QQB52Ux2e1d/XinwdP46Z5XLUlz3FNwQT09tnwPldAPJ7RZEEORxLIRyTpQzA+NhT7SupVR/FpDi+3Qoi1AFYB+IaU0u49MaSUT0kpeUSRg/298DRmZcYhkS8JkgfRagS+d3Uunt9egqa2btVxaAyKTU3IYrklH7IqPxnv8QdzpRxaboUQ0QAeA/CslPJjR35uGrmO7j68deA01szLUB2FaMTS48Nx5VQD/vyvk6qj0ChZbRJltS0st+RT5uck4FSNBeeaO1VH8VmOXrl9CEAIgKeFEBmDvwAEARAD7yc7+DlpGP88eAbTUmOQHBOqOgrRqNy6aCKMpiYUlp1THYVG4UxDK6JDAxEeFKA6CpHLBPprsXhyIv7F1VtlHF1ux6O/3O4HUHrBr1kAggd+/56Dn5OG0NXTh7/tr8Ta+Vy1Jc+l89fiu1fl4n/eO4EunvzjcYwmC7INXLUl37MqPxnvH62G1cabYlVwdLn9DwA3DPHrJICugd//wMHPSUN45/BZTEmJwoS4MNVRiMakID0WkwxReHlXqeooNEJGUxOyk6JUxyByuYyECIQH+aOoslF1FJ/kZ89FQoivoX9VFgBiAQQIIR4ceP+MlHIjAEgp9w7z+O8AGC+lfGOMeckO3b1WvLG3Ao+snaU6CpFDfPPKSbjnz7uwZEoi0uMjVMchOxlNFlxbMEF1DCIlVk1LwXtHqjAjPVZ1FJ9j78rtXejft/ZhAHEAIi94/y7nRKPR2nLkLLISI5EeH646CpFDRIYE4q5l2Xjs7eN8mc9DtHf3ot7SiVS+ekQ+asmURByuaEBzR4/qKD7H3hPKFkspxTC/Ftv5eN7V5AI9fVb8ZW8FblmYqToKkUNdOdUAXYAW/zx4WnUUssOpmmakx4fDT+us7dSJ3Fuozh+zJ47DtmPVqqP4HH7V8TL/OlqNtLgwZCbwpVvyLkII3HdVLl7ZVcotdjxAcXUTcgyctyXftnpaMt47UgXJ0xZdiuXWi/RabfjLnnLcvICrtuSdkmNC8aVZqfjTlk/4zcLNlZgsyE7kTgnk26akRMNqkzCaLKqj+BSWWy+y7Vg1EqNDuFpCXu3GuWkwmduwx1inOgoNQ0qJYm4DRgQhBFbmJ2PLEe5560ost17CarNh855yztqS1wvw0+J71+ThyfdPor2rV3UcGkKdpRN+WoHY8CDVUYiUWzE1CR8Za9HRzb26XYXl1kt8eKIGseE65KZEq45C5HS5KdGYmRGL5z8sUR2FhsD9bYk+Ex2qQ26KHrtO1qiO4jNYbr2A1Sbx6u4y3MJZW/Ihdy3LwR5jHU5WN6mOQhcxmizITuJIAtGgVdM4muBKLLdeYPfJWoQHB2DqBL3qKEQuExbkj2+smITH3z6OPqtNdRy6gNFkQQ7LLdGnZmbE4lxLJ06fa1UdxSew3Ho4m5TY9FEpblmYCSGE6jhELrVocgJiI3R4Y2+F6ig0oKfPispzrdyOkOgCWo0GK/IMeL+Iq7euwHLr4fYY6xDor8WMtBjVUYhcTgiB76yegjf3VcB0vl11HAJQUd8CQ3QIdAF2ne5O5DNW5idj23ETevqsqqN4PZZbDyalxKaBWVuu2pKvio8Mxo3z0vHHd49z71s3UFzNLcCIhpIYHYIJcWHYW1KvOorXY7n1YPtOnYNGAFdkxqmOQqTUl69IRWtHL7YdN6mO4vN4MxnR8FblJ3M0wQVYbj2UlBKv7C7FzVy1JYJWo8H3r8nFM1uNaO7oUR3Hp3EbMKLhzc+JR2ltM+osHaqjeDWWWw91sLwBvX02zMkapzoKkVuYmBiJRZMT8PTWYtVRfJalvRttXb0w6ENURyFySwF+Wiyekoh/FVWrjuLVWG49kJQSr+wqxc0LMqDhqi3Rp25bnIWjp80oqmxUHcUnGU0WZCVG8usS0SWsyk/Bv45WwWrjPQLOwnLrgY5UmtHW1Yv5OQmqoxC5leBAP3x71WT88d0TvCNZAaPJgizO2xJdUnp8OKJCAnG4okF1FK/FcuuBBmdttRqujhBdbPbEcUiNC8Oru8tUR/E5xaYm5HDeluiyVk7jjWXOxHLrYY6dMeN8WxcWTeaqLdFw7l01Ge8cPsvTgFzIapM4VdPMlVsiOyyZnIjDFY2wtHerjuKVWG49zCu7SrF2fga0Gv6rIxqOPkyHry2aiMffOQ4b9751iarGNkSGBCAiOEB1FCK3F6Lzx9yseGw9xu0LnYENyYN8UnUedZYOLJ2SpDoKkdu7ekYKJCTeO3xWdRSfYDQ1ITuRq7ZE9hocTeDhM47HcutBXtldhpvmZcBPy39tRJejEQLfvzoPL+44BXNrl+o4Xs9osiDbwHlbIntNSY6CzSZxsrpJdRSvw5bkIYwmC842tGLFVIPqKEQeY0JcGFZPS8aT759UHcXrGU0W5HDelshuQgismpaMLUd4Y5mjsdx6iE27S3HTvHT4c9WWaERuXpCJ8vpm7DvF89ydpaO7DzVNHUgdF646CpFHWZ5nwMcldWjv7lUdxauwKXmAstpmlNU1Y2V+suooRB4n0F+L+67KxZ+2fILOnj7VcbzSqVoL0seF84dvohGKCg3E1PF67PykVnUUr8KvRB5g00dluGFOOgL8tKqjEHmkaakxyBsfjZd2nFIdxSuVmCzI5kgC0aismpbC0QQHY7l1c5X1LSiubsLq6SmqoxB5tHtWTML2EyaU1jarjuJ1iqtZbolGa0Z6LMytXaisb1EdxWuw3Lq5Vz8qw5dnp0Lnz1VborGICA7AumU5eOztY7DabKrjeA0pJUpqWG6JRkurEbhyqgFbeGKZw7Dcuqnapg7c/r8fYufJWrx/pAq1TR2qIxF5vOV5SQjV+eOtA6dVR/Ea55o7AQBxEUGKkxB5rivzk/HhiRr09FlVR/EKLLduptdqg9FkwQ+e3/Npoa0+3471mwsVJyPyfEII3HdVLjZ/VIY6C39gdASjyYKsxEgIIVRHIfJYCVHBSB0Xho9LuKuLI/ipDuDrLO3dKK624GR1E05WN6GsthkJUcGwtPd8eo2UQLW5XWFKIu+RpA/Bv12Rij+9dwIb1sxkKRsjo8mCHANHEojGanV+/41liycnqo7i8VhuXcgmJc42tPUX2ar+MtvU3o2cpEhMMkTh5gUZyE6KREigP+5+cieqzG2QEhACMOhDVMcn8ho3zE3Ht5/ejV0na7GI30jGxGiy4LYlE1XHIPJ4c7PH4U9bTqCuqQPxUcGq43g0llsn6ujug9H02aqssboJESEBmGSIwiRDFL4yOxUpsWHQar64crRhzUys31yIanM7DPoQbFgzU8HfgMg7+Ws1+N7Vufj1m4cxIz0WoTp/1ZE8Uq/VhvL6FkxM4Mot0VgF+GmxNDcJ7x+twm2Ls1TH8Wgstw4ipUS9pfPTIvtJVRNM59uRER+OSYYoXDMjBfd/aSoiQwLt+nwJUcF4+luLnJyayHdNTo7G7Inj8Ow2I753da7qOB6por4FiVHBCA7ktxIiR1iZn4xfvFqIWxdOHHLhi+zDr0ij1NNnRVldy6fjBcXVTQCAycn9q7LL85KQHh/BE3uI3NidS7Nxz5934sTZJExJiVYdx+MYeXgDkUOljQtHdFggDpU3YFZmnOo4Hovl1k7n27o+u/Grqgnl9S1I1odgUnIUFuTE4xsrchAXEcSbU4g8SKjOH9+6cjIef+c4nrhnAX8YHSFjdRPyU2NUxyDyKqunpWBLURXL7Riw3KJ/T9kL51sfurEA3b3WT1dkT1Y3obWzF5MMkcgxROG2JRORlRiJoAD+4yPydPNz4vHBsWq8/nE5bl6QqTqORzHWWHDTvAzVMYi8yqLJCXhmazGa2roRFWrfKCN9HtsZgPWbC1HV2AYJ4GxjG9Y9uQOG6P5V2bzx0VgzLx2GmFBouCpL5HWEEPjO6in49tO7sXBSAgz6UNWRPEJzRw8s7T1IieU/LyJHCgn0x9zseGw9Vo0b5qarjuOR+Boc+veQlRe8LwA8c+9i/PDaqVg1LQUpsWEstkReLC4iCGsXZOKP756AlPLyDyCUmCyYmBjBr41ETrB6WjK2FFXx69Eosdyifw/Zwa/P/XvKciWCyNd8aeYENLf34JbHtmH1I+/i7id38tjrYdQ2deD3/yjC0Uoz/zkROcEkQxQEgE+qmlRH8Ugst+jfUzZZ3z92kKwP5Z6yRD5IqxHo6u2Dua0bNilRtGMtWgAAHfFJREFUZW7jsdfDWL+5EC0dvZAA/zkROYEQAisHVm9p5DhzC+4pS0T9zjV3ffp7Hns9vGpz26e/5z8nIudYkWfAnX/agfYrJyGEB82MCFduiYgGfG5ECTz2eig9fVZohMDgpC2PBydyjsiQQExLjcGOT2pUR/E4LLdERAMGR5SE6B9TeOCr01VHcjuv7SlH3vhoJMdwlIvI2VZxNGFU7BpLEEL8DMB0ADMApAI4I6WcMMR1OgBfA3ANgKkAxgGoBbAfwAYpZbFjYhMROd6FI0q/efMwth8z4c5l2YpTuY+zDa3458Ez+NPd8xEbHqQ6DpHXm54Wi8feOY7yuhakx4erjuMx7F25/Q2ApQDKAVzq1r0JAJ4CEA3gWQDfAfAqgJUAioQQS0adlIjIhb65chK2FFWhor5FdRS3YJMSj797ArcsyGCxJXIRrUZg5dRkvM/V2xGxt9ymSyn1UsoVAC41/NEAYJqUcoGU8mEp5bNSygcAzB/4+O/HEpaIyFWiQ3W4fUkWHn/nOKw27jX5flEVevtsuKZgguooRD7lynwDPjxhQk+fVXUUj2FXuZVSVth5nVlKWTTEn58EcALAlJHFIyJSZ9W0ZGg1Au8cOqM6ilJNbd14fnsJvn9NLrQaHtpA5ErxkcHISIjAHmOd6igewyU3lAkhNAASANS74vmIiBxBIwS+f3UuXt5VisaWrss/wEv9+V8nceVUA9LGceaPSIVV+cnYcoSjCfZy1W4J30J/uX1xuAuEEPcIIQ66KA8RkV1SYsNwzYzxeGLLCdVRlCgsO4eSGgv+v707D4+izvc9/v5mI4R93yFAWCXogCAiKriyePS4MIq4jQ6OG3I84537zHEZR505Xu9xEBwdBy46ykFHPcqowyKigCyiuJLILoQl7HtYQiD53T+qgyGE0Anprkr35/U8/VS6lvQn9XRXvv2rX/3qlos7+x1FJG6d36UZKzfv5c4X5zLk6Wnc/fI85mTn+h0rsCJe3JpZf+A5YCnehWllcs5NcM6dG+k8IiIVddOAjqzfcYBFK+PrtGB+wTFemJHN6CE9SE1O9DuOSNwq7pKw50A+zsHhI8eY9MkKFbinENHi1sx6A9PwLkIb6pyL3/N6IlJtpSQl8uCwTF6a+QMHjxz1O07UTP5sNd1bN6B3xyZ+RxGJa28uWEPNlCQKDuVjhYXsyMvHQvPlZBErbs2sF/AxsA8Y5JzT1wsRqbbOTm9Erw6NeW3OKr+jRMWaLfuYvXQT91zR3e8oInFv484D7DlwhJs+e5uH3h8PhUXs2J/Pxp0HTr9xHIpIcWtmP8MrbPPwCtv4vtRYRGLCLy/rxvzlW1iRu9fvKBFVWOQYNy2LOy/pSv1aNfyOIxL32jSuTZO6qbwz4Hpa78pl1KxXaFKnBm0a1/Y7WiBVeXEbKmxnAwfxCtt1Vf0aIiJ+qFszhVGXdWPctCyOFRb5HSdiPliSQ2pKIlec3drvKCICjBiQgQPqNq7P4yN/R5+139F1zfeMGJDhd7RACvf2u7cC7UJPmwApZvZo6Pl659zk0Hrt8FpsGwDjgf6hC8pKmuqcO3jGyUVEfDCoR0tmL93Ee1+s4+f9O/odp8pt33eYN+av5k939MdMY9qKBMGgHq0Ar4/tzlp1ePLf/8zIIecwqElYZVzcCXev3AVcXGreU6HpPGBy6Of2QKPQz0+c4ne1x2vVFRGpdsyM0UMzeXDSAi7q1oLmDdL8jlRlnHO8OCOba/q21+lOkYAZ1KPV8SK3sKiIXTv3w/m94ZlnYPhwn9MFS7h3KBvonLNTPAaWWG9uOesVP3Ii9ceIiERDiwZp3HB+R8bPyMa52Lk174IVW8ndfZCf9+/gdxQRKceSNTv4/ftZuHffhQcegFmz/I4UKNG6iYOISEy5vl97duflMyd7s99RqsTB/KO8/NEyxlzVk5QkjWkrEmR9OzWlsMixpFZLePddeOwxKCz0O1ZgqLgVEamEpMQE/u2qnkycvZz9hwv8jnPGXvl0BX0ympDZtqHfUUTkNBLMGDEggynzV+MuuAAWLYKCAvjxR7+jBYKKWxGRSuraqj4DujVn0uwVfkc5I8s27WHRym3cdWk3v6OISJgGdGvBXZd29Z4kJsK8eTBwIOTk+BkrEFTcioicgTsGdeGrtTtYun6X31Eq5WhhEeP+mcWvruhOnZrJfscRkTAlJhjdWjdgTvZmr+//4MHwm9/A5ZfDtm1+x/OVilsRkTNQq0Yy9195FuOmZVFwrPr1efufz9fSpF4qF3dv4XcUEamgBIPJn61i6frd3ozRo2HkSPjgA3+D+UzFrYjIGerftTltG9fmrYXVq79b7u6DvLd4LQ8M6aExbUWqocSEhON9b4974gkYNQoWLoTDh33L5icVtyIiVeC+wWfxwZIcNuzI8ztKWJxzjJ+exY0XZNC8fuyM1SsSby7p0Yptew+Rs73UsWfCBLjxRjh2zJ9gPlJxKyJSBZrUrcktF3dm3PRsiqrB2Lezl+Zy4PBRrj0v3e8oInIGkhITeOnuC0lvWufEBRMnwtGjcNddUBS7twsvi4pbEZEqclXvdhwrLOKj7zb6HaVc+w4VMOmTFYwZlkligv4NiFR3tWok894X61i5ee9PM1NSvDFwAXbv9ieYT3RUExGpIokJxphhmbz66Up2H8j3O84pTfx4OQN7tKRzy/p+RxGRKpKcaEz5bPWJM9PS4LXXoGZN+Pvf/QnmAxW3IiJVqEOzulx5Thv+Omu531HK9O26nXy/fhe3D+zsdxQRqUJXntOGNVv3sXrLvpMX5uXBI4/Ayy9HP5gPVNyKiFSxkRd1YuXmvSxZs93vKCc4crSQ8dOzuH/wWdRMSfI7johUoZSkRG66IIPlm/acvLB5c/j4Y3jqKXj77eiHizIVtyIiVSw1OZHRQ3rwwoxs8guCc6XymwvW0LFZXfp1buZ3FBGJgKv7pHN1n3Tvpg6ldegAM2bA9mB96Y4EFbciIhHQu2MTzmrdgMml+8D5JGd7HtO/2cC9V57ldxQRiaCvf9zB/33/+7IX9uwJDzzg3eTh88+jGyyKVNyKiETIr67ozuylm1hTVh+4KCpyjnHTsrhtYGca1Un1NYuIRFb3Ng34eu2O8sfcTk6Ga6+F7OzoBYsiFbciIhFSv1YN7rykK+OmZVFY5N/Yt9O/2QDA0F5tfcsgItFRMyWJa/u2580Fa0690pAhMHYsDB4M69ZFL1yUqLgVEYmgK85uTWpKIh8syfHl9Xfl5fP63FWMGZZJgm6xKxIX/qVPO5rXTyu7722xESPg2WehRo3oBYsSFbciIhFkZjw4NJM35q9m+77o3+f9Lx/9wNBebU++e5GIxKxaNZK5fVAXdh84Uv6KN98MDRvCfffB3r3lr1uNqLgVEYmwNo1rc03f9rw4I7v8lpQqtnjVNn7ctp8RAzKi9poiEgxHjhZy74T5bNlzqPwVa9SApCS4+mo4dJp1qwkVtyIiUfDz/h3YvOcQC1ZsjcrrHS44xoszf+DBoZnUSE6MymuKSHDUSE5kWK+2vLWwnL63AGbw/PPQti3ceCMUFUUnYASpuBURiYKUpETGDMvk5Y+WcTD/aMRf77W5qzi7XSN+1r5xxF9LRILp2vPas2DF1tN3iUpIgFdfhVGjvJ+ruer/F4iIVBM92jakT0YTXvl0RURfZ9XmvczN3syoy7tF9HVEJNjqpqXw+PDe1E5NPv3Kycle14RZs+DhhyGKXaiqmopbEZEouuvSbixauY1lZd0iswoUFhXx/D+zuOvSrtRLS4nIa4hI9dGzXSPWbtvPrrz88Dbo29e7Ve8f/hDZYBGk4lZEJIrq1EzmV1d0Z9w/szhaWPV926Z+kUOdtGQu69mqyn+3iFRPC1du5e1FP4a3cv368NFH8Le/weTJEc0VKSpuRUSi7OLuLWhSL5X/+Xxtlf7erXsP8dbCNTw4NBPTmLYiEnJDvw7MXprL7gNhtt42b+613l55ZbXsnqDiVkQkysyMB4b04L3Fa8ndfbBKfqdzjj/PyOa6fh1o1bBWlfxOEYkNjeqkcmlmK6Z9vSH8jdq3h6ZN4frrYebMyIWLABW3IiI+aF4/jRsvyGD89KwqGft23rIt7NiXzw3nd6iCdCISa24f1JmbKjPm9cMPw223waJFVR8qQlTcioj45Nrz0jlw+Cizl+ae0e/JO3yUv85axpirMklO1GFdRE5Wq0YyOdvz+OfX6yu2Yf/+8PrrcN11sGtXZMJVMR0FRUR8kpiQwJhhmUz6ZAX7DhVU+vdM+mQ5/bs0o3vrBlWYTkRiTd2ayfxtzkr2H67g8WbwYFi8GBo1goLKH6uiRcWtiIiPOresz8AeLZn48fJKbZ+1YTdL1uzgzku6VnEyEYk1zeqncUGX5vzji5yKb5yeDqtWQc+esDU6d1qsLBW3IiI+u31gZ75fv4tv1+2s0HYFxwoZPy2Le67sTq1wBmkXkbh34wUd+WHj7sr19e/cGUaO9EZR2Lu36sNVERW3IiI+q5mSxP2Dz2L89CyOHC0Me7u3F62lZYM0BnRtHsF0IhJLWjasxTO3nFf54QIffRQGDoRf/xqmTPFadBMSvOmUKVWYtPJU3IqIBEC/zs3o2Kwuby5YE9b6G3ce4P0v13H/kB4a01ZEKuTIsSIenLSQQ0eOVXxjMxg7Fs4/H0aNgvXrvbFw16+Hu+8ORIGr4lZEJCDuvfIspn+zgZzteeWu55xj/PQsbr6wE03r1YxSOhGJFanJibRokMaHX1Vw5IRiCQnw9NNw+PCJ8w8dgkceOfOAZ0jFrYhIQDSqk8ptAzszbloWReX0h5v1/SbyCwq5uk969MKJSEwZMSCD975YS35BJVpvATac4oYQp5ofRSpuRUQCZGivtgBM/6bsfxB7Dx7hlU9XMGZYJokJ6o4gIpWT3rQO1/RJr/wwhG3bVmx+FKm4FREJkAQzxgzL5PW5q9iVd/J94F+etYzLerYmo0U9H9KJSCy5+cJO1E1LoeBY+BeyHveHP0Ba2onz0tK8+T5TcSsiEjDpTeswtFdb/vLRDyfM/+rHHSzbtIdbL+rkUzIRiTXjp2Ux4xRniso1ciRMmADt2nkXmbVr5z0fObLqQ1aQilsRkQAaMSCDH7ftZ/GqbQDkHy3khelZjB7Sg9SUJJ/TiUisuPa89rz9+drKtd6OHAk5OVBU5E0DUNiCilsRkUCqkZzIg0MzeXHmDxwuOMZ/z1tF11YN6JPR1O9oIhJDOresT/umdZj1/Sa/o1QZff0XEQmon7VvTKfm9RgxdjaHCwpp3bAWW/YcokWDtNNvLCISplGXdaMyNywLKrXciogE2PqdeRwu8E4X5u45yON/X+JzIhGJNe2a1KF+rRRW5Ab3lroVEXZxa2a/NbN3zGytmTkzyznN+ueZ2WwzyzOz/WY208zOOePEIiJxZPPuQ8d/dg427TroYxoRiVUbdx3kmanfUlhU5HeUM1aRlts/ApcAPwJ7ylvRzPoB84D2wOPA74BOwHwzy6xcVBGR+NO6US2K765r5j0XEalqmW0b0qRuKnOyN/sd5YxVpLjt6Jxr5Jy7HDjdXz4eKAAucs6Ndc6NBS4CHPBc5aKKiMSfJ2/qQ5tGtUkwo02j2jx5Ux+/I4lIjLr5wk68s2gtrpp3wA37gjLn3Npw1jOzDKAP8IpzLrfE9rlm9g7wCzNr7pzbWuG0IiJxpkWDNCbee7HfMUQkDpyT3og/juyLWfW++2EkLigrblb4vIxliwEDekfgdUVERESkksyMWqnJvPrpCoqqcettJIrblqFpbhnLiue1Kr3AzO42s68ikEdEREREwlAjKYFv1u1k4fLqe4I9EsVt8QCMR8pYll9qneOccxOcc+dGII+IiIiIhMHMGHlhJ6bMX11tW28jUdwWj1tTo4xlqaXWEREREZEAOa9TU+rUTK62Qw9G4g5lxSMpnNT1oMS8srosiIiIiIjPzIxnb+1XbS8si0TLbfHtc84vY1k/vOHAvo7A64qIiIhIFTAzJny8jC9Xb/c7SoVVeXHrnFsDfAUMN7Pii8sI/Twc+FTDgImIiIgEW5eW9Zkyf3W1G/c27G4JZnYr0C70tAmQYmaPhp6vd85NLrH6GGAO3h3JXgjNG41XTP/6zCKLiIiISKQN6NaCyfNW8c26nfTu0MTvOGGrSJ/bu4DSI4k/FZrOA44Xt865RWY2EHg69HDAImC4c+77SqcVERERkahITDDuvKQrBw4f9TtKhVTkDmUDK/KLnXOfA5dWNJCIiIiIBEP/rs1xznHwyFFq1Uj2O05YInFBmYiIiIjEiMWrtvPk29VnLAAVtyIiIiJySn0ymrB17yF+2Ljb7yhhUXErIiIiIqeUlJjAjRdkMGX+Gr+jhCUSN3EQERERkRhy+dmtSU1OxDkX+Js7qOVWRERERMqVnJjAxWe1JGtD8LsmqLgVERERkdMqLCrimanfsmbLPr+jlEvFrYiIiIicVkpSIjec35E35q/2O0q5VNyKiIiISFiG9mrL8ty9bNiR53eUU9IFZSIiIiISltTkRMb+oj/N6tX0O8opqeVWRERERMLWvH4as5fmsmHnAb+jlEnFrYiIiIhUyM68fN4MaN9bdUsQERERkQq5uk87Rj7/CXe+OIctew7RpnFtRgzIYFCPVn5HU3ErIiIiIhXz5ertJCYYZ6c3YsI9F5O9cTdjP1wK4HuBq24JIiIiIlIhby5Yw6M39GbMsJ4kJSZwTnpjHvqXnry5wP9b9Kq4FREREZEK2bjzAJltG54wr0ebhmwMwEVmKm5FREREpELaNK5N9sYTb8WbvXE3bRrX9inRT1TcioiIiEiFjBiQwdgPl/Jdzk6OFRbxXc5Oxn64lBEDMvyOpgvKRERERKRiii8ae2nmD2zceYA2jWtzx6Auvl9MBipuRURERKQSBvVoFYhitjR1SxARERGRmKHiVkRERERihopbEREREYkZKm5FREREJGaouBURERGRmKHiVkRERERihopbEREREYkZKm5FREREJGaouBURERGRmKHiVkRERERihopbEREREYkZSX4HOJX77rvP7wgiIiIiEkzupZdesrIWqOVWRERERGKGOef8zhAYZvaVc+5cv3MEnfZTeLSfwqP9FB7tp/BoP4VH+yk82k/hCdp+UsutiIiIiMQMFbciIiIiEjNU3J5ogt8Bqgntp/BoP4VH+yk82k/h0X4Kj/ZTeLSfwhOo/aQ+tyIiIiISM9RyKyIiIiIxQ8WtiIiIiMSMuC5uzSzBzB4ysxVmlm9mG83sOTOr5Xe2oDCzzmb2pJktNrMdZpZnZt+Z2SPaT+UzszQzW2dmzsz+7HeeIDGzhmb2X2a2JvTZ22Fmc8zsQr+zBYWZ1Taz/zCzrNDnbqeZLTKzO8yszIHLY5mZ/dbM3jGztaHPVM5p1j/PzGaH9t1+M5tpZudEKa5vwt1PZpZqZqPM7H0zyzGzw6Ft3jSzblGOHXUVfT+V2vbZ0DYHIhgxECqzn8zsVjNbGPrcHTCzbDN7LApxf8oQz31uzWwc8CAwFZgBdANGA/OBy5xzRT7GCwQzewa4H/gAWAwcBQYBPweWAv2cc4f9SxhcZvZfwK+A2sCLzrkHfI4UCGbWDpiLt18mAauAekBP4CPn3N/9SxcMZpYAzAP6A6/hffbSgBFAX+BZ59z/9i9h9JmZA3YD3wC9gf3OufRTrNsP7z2WCxR/sXwAaAr0d85lRTqvX8LdT2bWFVgOLABmAZuBDsC9QC1gsHNuTpRiR11F3k+ltjsHWALk49VQtSOZ028V3U9m9gpwO/Au3mewEGgPNHbO/TLSeY/niNfi1szOArKAqc6560vMHw2MB0Y6597wK19QmNm5wGrn3L5S858GHgFGO+fUKlmKmfUCvgR+AzyHitvjzGw+kA70dc5t8TlOIJnZ+cAi4Hnn3EMl5qcAK4CGzrn6fuXzg5l1cM6tDf2cDdQup7j9EugKdHPO5YbmtcIr5hY7566ITuroC3c/mVkjoI1z7rtS87sD3wJZQRqUv6pV5P1UYptEvC+aW4C6wLlxUNxW5HN3F/D/gNucc5Ojl/Jk8dwtYQRgwPOl5k8EDgG3RD1RADnnvipd2Ia8FZr2iGae6iB0AJwIzATe8zlOoJjZRcAAvJbHLWaWbGZpfucKoLqh6eaSM51zBcBO4GDUE/ms+B/s6ZhZBtAHeKe4sA1tnwu8A1xmZs0jk9J/4e4n59yu0oVtaP4yIJsYP7aHu59KeRDojneGNy5U4HNnwG+Bb4oLWzOr41cXqngubvsARXita8c55/KB70LL5dRah6bbfE0RTA/htRqppfZkQ0PTDWb2IXAYOGhmq8xMXyh/8iWwF/iNmQ03s7Zm1sXM/hPv1OATvqYLtuJj9+dlLFuM16jRO3pxqpdQl5gW6Nh+glB3qqeA3zvn1vudJ4C6AB2BRWb2mJntAvYDe83sZTOLagt3UjRfLGBaAjudc0fKWJYL9DezlFBLiZQQapl8HDgGxH3XjZLMrD3we+BJ51yOmaX7myhwuoSmE4HVeH2zagD/Dkw2s2Tn3Kt+hQsK59weM7sa7xTf2yUW5QHXO+f+4U+yaqFlaJpbxrLiea2ilKU6uhevuH3K7yAB8xdgHfAnv4MEVPGx/UYgBXgab39dhXftSRczu8RFqS9sPBe3aUBZhS14HcWL11Fxe7LngX7AfzjnVvodJmB0ACxfndA0DxhU/OXRzKYCa4E/mtlrupgTgAN4p4c/wOt/2xDv4s43zOwa59zHfoYLsOJuLmUd3/NLrSMlmFl/vGsElgJ/9DlOYJjZCGAwMMA5d8zvPAFVfGxvAlzunJsdev5uqGvC7Xj7cEY0wsRzt4RDeC1GZUktsY6UYGZP4Z1un+Cc+0+/8wRJ6LT6FcA9zrmjfucJqOKRNd4seVbEObcHr4hrzk8tAHHLzDLxCtqPnXP/yzk31Tk3Ca+/8lZgYugMipys+Lhd1vFdx/ZTMLPewDS8ft5DQ1304p6ZNcRr0JnknFvkd54AKz6255YobIu9FpoOjFaYeC5uNwONzaysA2ArvC4LarUtwcyeAB4FXgXu8TdNsITeR38CpgNbzSwjdGFLu9Aq9ULz4uoK9zJsCk23lrGseOSEBlHKEmQP4RVi75Sc6Zw7hFeAtMMbcUJOVnwRXlldD4rnldVlIW6FRnf5GNiHd0ZF++cnv8MbGm1i8XE9dGyviXcdVYaZtfE3YiAE6tgez8XtEry/v2/JmWaWCpwDfOVHqKAys9/hfchfB34ZrX4z1UhNvNMxw/D6khY/5oaW3xJ6HrVx/gKq+ALO1mUsK563PUpZgqy4CCurdTap1FROtCQ0Pb+MZf0AB3wdvTjBZmY/wytsi7sK6WKpE7XDK26/4MRje1+87i2ridKp9oDLwmu9LetLZdSP7fFc3L6Fd5D7t1LzR+G9YadEPVFAmdnjeFdnTwZ+of6QZToIDC/jcV9o+czQ8w98SRcc/8D7J3pLyatnzawF8K94Yyqv8StcgCwLTe8oOTPU8n8NsAf4McqZqoXQ++crYLiZFV9cRujn4cCnzrmyWpfiTqiwnY13/BrknFvnc6Qg+j+UfWxfhteHezjemZa4Fjqr9B7Q3MyuLbX43tB0erTyxO1NHADM7AW8/qNT8XZ6N7xx7BYCl6iIAzO7H+8OPxuAx/CGTytpmy5sObXQaAnr0E0cjjOzu4G/Aj8Ar+BdWVt8hfZVzrlZPsYLhNCwQ9/gncabgndMaoj35TsduN8595JvAX1gZrfyUzef0Xjvm+dCz9eXHDQ+dGHUHLxTpS+U2KYZcIFz7vuohPZBuPsp9B77Gu999XvK/rI01TkXk2MqV+T9dIrt5xIfN3GoyOeuLd7ZuXp4n7scvOEfhwGvO+duj1JscM7F7QPvlN+vgZV4V9bm4vWbrO13tqA8gL/htXCf6jHX74xBfuAVIg74s99ZgvQArsMbc/QgXkvuLLyiw/dsQXngjRn5Gl6BdhRvzMjPgOv8zubT/phbkeMQXreET/BGncgDPgJ6+f13BGU/4V3cU96x3QHpfv89fu+n02x/wO+/I2j7KfQ/bwqwA2+0qeXAw0BCNHPHdcutiIiIiMSWeO5zKyIiIiIxRsWtiIiIiMQMFbciIiIiEjNU3IqIiIhIzFBxKyIiIiIxQ8WtiIiIiMQMFbciIiIiEjNU3IqIiIhIzFBxKyIiIiIxQ8WtiIiIiMSM/w8XWA/mKjgWxQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 3024x2304 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def denormalize(mean,std,seq):\n",
    "    nseq = seq.copy()\n",
    "    for i,s in enumerate(nseq):\n",
    "        s = s*std + mean\n",
    "        nseq[i]=s\n",
    "    return nseq\n",
    "\n",
    "\n",
    "# ---- Get a sequence\n",
    "\n",
    "i=random.randint(0,len(dataset_test)-sequence_len)\n",
    "sequence      = dataset_test[i:i+sequence_len]\n",
    "sequence_true = dataset_test[i:i+sequence_len+1]\n",
    "\n",
    "# ---- Prediction\n",
    "\n",
    "pred = loaded_model.predict( np.array([sequence]) )\n",
    "\n",
    "# ---- De-normalization\n",
    "\n",
    "sequence_true = denormalize(mean,std, sequence_true)\n",
    "pred          = denormalize(mean,std, pred)\n",
    "\n",
    "# ---- Show it\n",
    "feat=11\n",
    "\n",
    "delta_deg=abs(sequence_true[-1][feat]-pred[-1][feat])\n",
    "print(f'Gap between prediction and reality : {delta_deg:.2f} °C')\n",
    "\n",
    "reload(ooo)\n",
    "ooo.plot_multivariate_serie(sequence_true, predictions=pred, labels=features, only_features=[feat],width=14, height=8)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "<img width=\"80px\" src=\"../fidle/img/00-Fidle-logo-01.svg\"></img>"
   ]
  }
 ],
 "metadata": {
  "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": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}