Implementation of LSTM.ipynb

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      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import macpath\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns"
      ]
    },
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              "      <th></th>\n",
              "      <th>StationId</th>\n",
              "      <th>PM2.5</th>\n",
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              "      <th>NO</th>\n",
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              "      <th>Date</th>\n",
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              "    <tr>\n",
              "      <th>2017-11-24</th>\n",
              "      <td>AP001</td>\n",
              "      <td>71.36</td>\n",
              "      <td>115.75</td>\n",
              "      <td>1.75</td>\n",
              "      <td>20.65</td>\n",
              "      <td>12.40</td>\n",
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              "      <td>109.26</td>\n",
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              "      <td>NaN</td>\n",
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              "      <th>2017-11-25</th>\n",
              "      <td>AP001</td>\n",
              "      <td>81.40</td>\n",
              "      <td>124.50</td>\n",
              "      <td>1.44</td>\n",
              "      <td>20.50</td>\n",
              "      <td>12.08</td>\n",
              "      <td>10.72</td>\n",
              "      <td>0.12</td>\n",
              "      <td>15.24</td>\n",
              "      <td>127.09</td>\n",
              "      <td>0.20</td>\n",
              "      <td>6.50</td>\n",
              "      <td>0.06</td>\n",
              "      <td>184.0</td>\n",
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              "      <th>2017-11-26</th>\n",
              "      <td>AP001</td>\n",
              "      <td>78.32</td>\n",
              "      <td>129.06</td>\n",
              "      <td>1.26</td>\n",
              "      <td>26.00</td>\n",
              "      <td>14.85</td>\n",
              "      <td>10.28</td>\n",
              "      <td>0.14</td>\n",
              "      <td>26.96</td>\n",
              "      <td>117.44</td>\n",
              "      <td>0.22</td>\n",
              "      <td>7.95</td>\n",
              "      <td>0.08</td>\n",
              "      <td>197.0</td>\n",
              "      <td>Moderate</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-27</th>\n",
              "      <td>AP001</td>\n",
              "      <td>88.76</td>\n",
              "      <td>135.32</td>\n",
              "      <td>6.60</td>\n",
              "      <td>30.85</td>\n",
              "      <td>21.77</td>\n",
              "      <td>12.91</td>\n",
              "      <td>0.11</td>\n",
              "      <td>33.59</td>\n",
              "      <td>111.81</td>\n",
              "      <td>0.29</td>\n",
              "      <td>7.63</td>\n",
              "      <td>0.12</td>\n",
              "      <td>198.0</td>\n",
              "      <td>Moderate</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-28</th>\n",
              "      <td>AP001</td>\n",
              "      <td>64.18</td>\n",
              "      <td>104.09</td>\n",
              "      <td>2.56</td>\n",
              "      <td>28.07</td>\n",
              "      <td>17.01</td>\n",
              "      <td>11.42</td>\n",
              "      <td>0.09</td>\n",
              "      <td>19.00</td>\n",
              "      <td>138.18</td>\n",
              "      <td>0.17</td>\n",
              "      <td>5.02</td>\n",
              "      <td>0.07</td>\n",
              "      <td>188.0</td>\n",
              "      <td>Moderate</td>\n",
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            "text/plain": [
              "           StationId  PM2.5    PM10    NO    NO2    NOx    NH3    CO    SO2  \\\n",
              "Date                                                                          \n",
              "2017-11-24     AP001  71.36  115.75  1.75  20.65  12.40  12.19  0.10  10.76   \n",
              "2017-11-25     AP001  81.40  124.50  1.44  20.50  12.08  10.72  0.12  15.24   \n",
              "2017-11-26     AP001  78.32  129.06  1.26  26.00  14.85  10.28  0.14  26.96   \n",
              "2017-11-27     AP001  88.76  135.32  6.60  30.85  21.77  12.91  0.11  33.59   \n",
              "2017-11-28     AP001  64.18  104.09  2.56  28.07  17.01  11.42  0.09  19.00   \n",
              "\n",
              "                O3  Benzene  Toluene  Xylene    AQI AQI_Bucket  \n",
              "Date                                                            \n",
              "2017-11-24  109.26     0.17     5.92    0.10    NaN        NaN  \n",
              "2017-11-25  127.09     0.20     6.50    0.06  184.0   Moderate  \n",
              "2017-11-26  117.44     0.22     7.95    0.08  197.0   Moderate  \n",
              "2017-11-27  111.81     0.29     7.63    0.12  198.0   Moderate  \n",
              "2017-11-28  138.18     0.17     5.02    0.07  188.0   Moderate  "
            ]
          },
          "execution_count": 133,
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        }
      ],
      "source": [
        "city_data = pd.read_csv(\"E:\\Downloads\\stations.csv\", index_col = False)\n",
        "city_data.rename(columns={'Unnamed: 0':'Date'}, inplace = True)\n",
        "city_data.set_index('Date', inplace=True)\n",
        "city_data.head()"
      ]
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              "      <th>StationId</th>\n",
              "      <td>10314</td>\n",
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              "      <td>10314.0</td>\n",
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              "      <td>15.22</td>\n",
              "      <td>28.57</td>\n",
              "      <td>46.17</td>\n",
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              "      <td>10314.0</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>29.91121</td>\n",
              "      <td>28.188032</td>\n",
              "      <td>0.02</td>\n",
              "      <td>12.68</td>\n",
              "      <td>22.5</td>\n",
              "      <td>36.675</td>\n",
              "      <td>331.5</td>\n",
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              "      <th>NH3</th>\n",
              "      <td>10314.0</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>17.099812</td>\n",
              "      <td>12.737291</td>\n",
              "      <td>0.1</td>\n",
              "      <td>9.3325</td>\n",
              "      <td>13.85</td>\n",
              "      <td>21.97</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>0.699242</td>\n",
              "      <td>0.436917</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.42</td>\n",
              "      <td>0.63</td>\n",
              "      <td>0.9</td>\n",
              "      <td>4.74</td>\n",
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              "      <td>10314.0</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>9.90713</td>\n",
              "      <td>7.926233</td>\n",
              "      <td>0.1</td>\n",
              "      <td>4.37</td>\n",
              "      <td>7.86</td>\n",
              "      <td>12.81</td>\n",
              "      <td>67.26</td>\n",
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              "      <th>O3</th>\n",
              "      <td>10314.0</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>32.224498</td>\n",
              "      <td>19.937162</td>\n",
              "      <td>0.03</td>\n",
              "      <td>18.38</td>\n",
              "      <td>28.24</td>\n",
              "      <td>41.41</td>\n",
              "      <td>162.33</td>\n",
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              "      <th>Benzene</th>\n",
              "      <td>10314.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.429789</td>\n",
              "      <td>13.419295</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.23</td>\n",
              "      <td>1.52</td>\n",
              "      <td>4.16</td>\n",
              "      <td>165.41</td>\n",
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              "      <th>Toluene</th>\n",
              "      <td>10314.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>12.120517</td>\n",
              "      <td>23.774658</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.39</td>\n",
              "      <td>5.01</td>\n",
              "      <td>12.4675</td>\n",
              "      <td>259.03</td>\n",
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              "      <th>Xylene</th>\n",
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              "      <td>NaN</td>\n",
              "      <td>2.862333</td>\n",
              "      <td>7.048609</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.12</td>\n",
              "      <td>0.88</td>\n",
              "      <td>2.95</td>\n",
              "      <td>133.6</td>\n",
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              "      <th>AQI</th>\n",
              "      <td>10314.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>119.847004</td>\n",
              "      <td>75.075472</td>\n",
              "      <td>16.0</td>\n",
              "      <td>72.0</td>\n",
              "      <td>104.0</td>\n",
              "      <td>139.0</td>\n",
              "      <td>692.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>AQI_Bucket</th>\n",
              "      <td>10314</td>\n",
              "      <td>6</td>\n",
              "      <td>Moderate</td>\n",
              "      <td>4402</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "                                                     [key], {});\n",
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              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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              "  "
            ],
            "text/plain": [
              "              count unique       top  freq        mean        std   min  \\\n",
              "StationId     10314     20     TG004  1222         NaN        NaN   NaN   \n",
              "PM2.5       10314.0    NaN       NaN   NaN     52.4821  43.101142  1.09   \n",
              "PM10        10314.0    NaN       NaN   NaN  108.494813  67.881316  5.77   \n",
              "NO          10314.0    NaN       NaN   NaN   12.204897  18.880759  0.02   \n",
              "NO2         10314.0    NaN       NaN   NaN   33.188329  22.909939  0.01   \n",
              "NOx         10314.0    NaN       NaN   NaN    29.91121  28.188032  0.02   \n",
              "NH3         10314.0    NaN       NaN   NaN   17.099812  12.737291   0.1   \n",
              "CO          10314.0    NaN       NaN   NaN    0.699242   0.436917   0.0   \n",
              "SO2         10314.0    NaN       NaN   NaN     9.90713   7.926233   0.1   \n",
              "O3          10314.0    NaN       NaN   NaN   32.224498  19.937162  0.03   \n",
              "Benzene     10314.0    NaN       NaN   NaN    4.429789  13.419295   0.0   \n",
              "Toluene     10314.0    NaN       NaN   NaN   12.120517  23.774658   0.0   \n",
              "Xylene      10314.0    NaN       NaN   NaN    2.862333   7.048609   0.0   \n",
              "AQI         10314.0    NaN       NaN   NaN  119.847004  75.075472  16.0   \n",
              "AQI_Bucket    10314      6  Moderate  4402         NaN        NaN   NaN   \n",
              "\n",
              "                25%     50%       75%     max  \n",
              "StationId       NaN     NaN       NaN     NaN  \n",
              "PM2.5         25.74    43.4     66.21  734.56  \n",
              "PM10        62.6925  98.805  137.8375   830.1  \n",
              "NO             2.65    6.27     13.43   262.0  \n",
              "NO2           15.22   28.57     46.17  254.78  \n",
              "NOx           12.68    22.5    36.675   331.5  \n",
              "NH3          9.3325   13.85     21.97  269.93  \n",
              "CO             0.42    0.63       0.9    4.74  \n",
              "SO2            4.37    7.86     12.81   67.26  \n",
              "O3            18.38   28.24     41.41  162.33  \n",
              "Benzene        0.23    1.52      4.16  165.41  \n",
              "Toluene        1.39    5.01   12.4675  259.03  \n",
              "Xylene         0.12    0.88      2.95   133.6  \n",
              "AQI            72.0   104.0     139.0   692.0  \n",
              "AQI_Bucket      NaN     NaN       NaN     NaN  "
            ]
          },
          "execution_count": 134,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "city_data.isna().any()\n",
        "city_data.dropna(axis=0, inplace=True)\n",
        "city_data.describe(include='all').transpose()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "onjRm2bC_ty8"
      },
      "outputs": [],
      "source": [
        "\n",
        "AP001 = city_data[city_data['StationId']=='AP001']"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 457
        },
        "id": "6Xc0k3pI_uCT",
        "outputId": "64d65f41-8389-4016-ccd0-21d5e0a8af52"
      },
      "outputs": [
        {
          "data": {
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              "      <td>4.65</td>\n",
              "      <td>18.4250</td>\n",
              "      <td>33.570</td>\n",
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              "      <td>16.810</td>\n",
              "      <td>26.1975</td>\n",
              "      <td>140.17</td>\n",
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              "      <th>NOx</th>\n",
              "      <td>646.0</td>\n",
              "      <td>16.319598</td>\n",
              "      <td>13.555879</td>\n",
              "      <td>0.86</td>\n",
              "      <td>8.1950</td>\n",
              "      <td>11.685</td>\n",
              "      <td>19.1875</td>\n",
              "      <td>103.49</td>\n",
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              "    <tr>\n",
              "      <th>NH3</th>\n",
              "      <td>646.0</td>\n",
              "      <td>12.291161</td>\n",
              "      <td>5.976508</td>\n",
              "      <td>1.28</td>\n",
              "      <td>7.3850</td>\n",
              "      <td>12.230</td>\n",
              "      <td>17.2800</td>\n",
              "      <td>33.72</td>\n",
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              "    <tr>\n",
              "      <th>CO</th>\n",
              "      <td>646.0</td>\n",
              "      <td>0.611238</td>\n",
              "      <td>0.313681</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.4500</td>\n",
              "      <td>0.580</td>\n",
              "      <td>0.7600</td>\n",
              "      <td>1.81</td>\n",
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              "    <tr>\n",
              "      <th>SO2</th>\n",
              "      <td>646.0</td>\n",
              "      <td>15.021176</td>\n",
              "      <td>6.666924</td>\n",
              "      <td>4.65</td>\n",
              "      <td>10.6000</td>\n",
              "      <td>13.895</td>\n",
              "      <td>17.8800</td>\n",
              "      <td>66.39</td>\n",
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              "    <tr>\n",
              "      <th>O3</th>\n",
              "      <td>646.0</td>\n",
              "      <td>39.535217</td>\n",
              "      <td>19.835894</td>\n",
              "      <td>12.29</td>\n",
              "      <td>26.6425</td>\n",
              "      <td>34.585</td>\n",
              "      <td>46.1375</td>\n",
              "      <td>138.18</td>\n",
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              "      <th>Benzene</th>\n",
              "      <td>646.0</td>\n",
              "      <td>0.586981</td>\n",
              "      <td>3.255551</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0900</td>\n",
              "      <td>0.170</td>\n",
              "      <td>0.3400</td>\n",
              "      <td>53.89</td>\n",
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              "    <tr>\n",
              "      <th>Toluene</th>\n",
              "      <td>646.0</td>\n",
              "      <td>2.200820</td>\n",
              "      <td>2.554963</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.3800</td>\n",
              "      <td>1.395</td>\n",
              "      <td>3.0775</td>\n",
              "      <td>26.79</td>\n",
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              "      <th>Xylene</th>\n",
              "      <td>646.0</td>\n",
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              "      <td>7.230795</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.1000</td>\n",
              "      <td>0.130</td>\n",
              "      <td>0.1800</td>\n",
              "      <td>125.18</td>\n",
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              "      <td>646.0</td>\n",
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              "      <td>24.00</td>\n",
              "      <td>60.2500</td>\n",
              "      <td>83.000</td>\n",
              "      <td>124.7500</td>\n",
              "      <td>312.00</td>\n",
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            "text/plain": [
              "         count        mean        std    min      25%     50%       75%  \\\n",
              "PM2.5    646.0   41.713220  28.724483   4.65  18.4250  33.570   60.9875   \n",
              "PM10     646.0   81.809876  45.538467   7.80  44.7275  71.575  113.2925   \n",
              "NO       646.0    4.576610   4.526969   0.25   2.0425   3.190    5.3125   \n",
              "NO2      646.0   23.754613  20.915976   1.52  11.2925  16.810   26.1975   \n",
              "NOx      646.0   16.319598  13.555879   0.86   8.1950  11.685   19.1875   \n",
              "NH3      646.0   12.291161   5.976508   1.28   7.3850  12.230   17.2800   \n",
              "CO       646.0    0.611238   0.313681   0.00   0.4500   0.580    0.7600   \n",
              "SO2      646.0   15.021176   6.666924   4.65  10.6000  13.895   17.8800   \n",
              "O3       646.0   39.535217  19.835894  12.29  26.6425  34.585   46.1375   \n",
              "Benzene  646.0    0.586981   3.255551   0.00   0.0900   0.170    0.3400   \n",
              "Toluene  646.0    2.200820   2.554963   0.00   0.3800   1.395    3.0775   \n",
              "Xylene   646.0    0.813638   7.230795   0.01   0.1000   0.130    0.1800   \n",
              "AQI      646.0  101.500000  58.342420  24.00  60.2500  83.000  124.7500   \n",
              "\n",
              "            max  \n",
              "PM2.5    139.38  \n",
              "PM10     230.27  \n",
              "NO        43.76  \n",
              "NO2      140.17  \n",
              "NOx      103.49  \n",
              "NH3       33.72  \n",
              "CO         1.81  \n",
              "SO2       66.39  \n",
              "O3       138.18  \n",
              "Benzene   53.89  \n",
              "Toluene   26.79  \n",
              "Xylene   125.18  \n",
              "AQI      312.00  "
            ]
          },
          "execution_count": 136,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "AP001.describe().transpose()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pkxyqATJ_uQX",
        "outputId": "d14f30d3-62a1-4d0d-e402-f41a5f62df52"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "StationId     False\n",
              "PM2.5         False\n",
              "PM10          False\n",
              "NO            False\n",
              "NO2           False\n",
              "NOx           False\n",
              "NH3           False\n",
              "CO            False\n",
              "SO2           False\n",
              "O3            False\n",
              "Benzene       False\n",
              "Toluene       False\n",
              "Xylene        False\n",
              "AQI           False\n",
              "AQI_Bucket    False\n",
              "dtype: bool"
            ]
          },
          "execution_count": 137,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "AP001.isna().any()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-ed34Rd-_udy",
        "outputId": "1863ffd5-7b38-40c9-e704-8578fcca0c02"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "array([[ 81.4 , 124.5 ,  20.5 ,  15.24, 127.09],\n",
              "       [ 78.32, 129.06,  26.  ,  26.96, 117.44],\n",
              "       [ 88.76, 135.32,  30.85,  33.59, 111.81],\n",
              "       ...,\n",
              "       [ 16.65,  28.51,   8.32,  10.86,  37.34],\n",
              "       [ 20.96,  32.56,   9.55,  14.79,  43.29],\n",
              "       [ 21.34,  35.16,  10.69,  14.58,  45.32]])"
            ]
          },
          "execution_count": 138,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "AP = AP001[[\"PM2.5\",\"PM10\",\"NO2\",\"SO2\",\"O3\"]]\n",
        "newAp = AP.to_numpy()\n",
        "newAp"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "D8qvwLNg_xra",
        "outputId": "c908a11f-af71-4b08-93d5-89814d28021b"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "(646, 5)"
            ]
          },
          "execution_count": 139,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "newAp.shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "eTC3VOx-QeOa"
      },
      "outputs": [],
      "source": [
        "def unbox(a):\n",
        "  l = []\n",
        "  for i in range(len(a)):\n",
        "    l.append(a[i][0])\n",
        "  return l"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "fwS27Gr0_w-O"
      },
      "outputs": [],
      "source": [
        "k = [\"PM2.5\",\"PM10\",\"NO2\",\"SO2\",\"O3\"]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ALSH1EYODfMt"
      },
      "outputs": [],
      "source": [
        "from numpy import array\n",
        "def split_sequence(sequence, n_steps):\n",
        "\tX, y = list(), list()\n",
        "\tfor i in range(len(sequence)):\n",
        "\t\t# find the end of this pattern\n",
        "\t\tend_ix = i + n_steps\n",
        "\t\t# check if we are beyond the sequence\n",
        "\t\tif end_ix > len(sequence)-1:\n",
        "\t\t\tbreak\n",
        "\t\t# gather input and output parts of the pattern\n",
        "\t\tseq_x, seq_y = sequence[i:end_ix], sequence[end_ix]\n",
        "\t\tX.append(seq_x)\n",
        "\t\ty.append(seq_y)\n",
        "\treturn array(X), array(y)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "gB_clBHkE3W5"
      },
      "outputs": [],
      "source": [
        "from numpy import array\n",
        "from keras.models import Sequential\n",
        "from keras.layers import LSTM\n",
        "from keras.layers import Dense"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Ez0FRqFcLf-D"
      },
      "outputs": [],
      "source": [
        "def all_LSTM(n_features,n_steps,index_k):\n",
        "  newAp1 = AP001[[k[index_k]]]\n",
        "  newAp1 = array(newAp1)\n",
        "  newAp1 = unbox(newAp1)\n",
        "  train_data = newAp1[:500]\n",
        "  test_data = newAp1[500:605]\n",
        "  mn = min(test_data)\n",
        "  mx = max(test_data)\n",
        "  X , Y = split_sequence(train_data,n_steps)\n",
        "  model = Sequential()\n",
        "  model.add(LSTM(50, activation='relu', input_shape=(n_steps, n_features)))\n",
        "  model.add(Dense(1))\n",
        "  model.compile(optimizer='adam', loss='mse')\n",
        "  X = X.reshape((X.shape[0], X.shape[1], n_features))\n",
        "  model.fit(X, Y, epochs=200, verbose=0)\n",
        "  x2 , y2 = split_sequence(test_data,n_steps)\n",
        "  y_pred = []\n",
        "  for x_input in x2:\n",
        "    x_input = x_input.reshape((1, n_steps, n_features))\n",
        "    yhat = model.predict(x_input, verbose=0)\n",
        "    y_pred.append(yhat)\n",
        "\n",
        "  return unbox(unbox(y_pred)) , y2 , mn , mx"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "qg01SVNORK-m"
      },
      "outputs": [],
      "source": [
        "PM_pred , PM_y , m1 , m2= all_LSTM(1,5,0)\n",
        "PM10_pred , PM10_y , m3 ,   m4= all_LSTM(1,5,1)\n",
        "NO2_pred , NO2_y , m5 ,m6= all_LSTM(1,5,2)\n",
        "SO2_pred , SO2_y , m7, m8 = all_LSTM(1,5,3)\n",
        "O3_pred , O3_y ,m9 , m10 = all_LSTM(1,5,4)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "HL67uUhhSFSh",
        "outputId": "0ee7e213-4cd3-40bc-8e6c-1fc7f2337443"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        },
        {
          "data": {
            "image/png": 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vvx6Av/zlL5x11lmcfvrpXHLJJbS2tjIULS0tzJw50/6+aNEiAB566CHOPfdcLrvsMgAqKyu5++67bYE/55xzqKurA+Dss8+muTnvoEhHlMPJAzdMJNIp9T9lBHyi882/bGHrwVBJtzl/eg3//o4FQy6zcuVKrrjiCk466SQaGhpYu3YtS5cu5d5772XPnj2sX78ej8dDV1cX9fX1/OAHP+CZZ56hsXHogejPO+88XnrpJYQQ/OxnP+O//uu/+P73v19w+ZtuuokPfOAD3H333VxyySV8/OMfZ/r06WzZsoWlS5dmLXv88cfT399PKBSipibTEet9993HlVdeWcSRKS9GwA0KS7iNgBvKxMMPP8znP/95AD74wQ/y8MMPs3TpUp588kluvPFGPB4lR/X19SPabnNzMx/4wAdoaWkhHo8Pm0N9+eWXs2vXLh5//HEee+wxTj/9dDZvLr4h+TPPPMN9993HqlUjGhqzLBgBNyiMhXLMMFykXA66urp4+umn2bRpE0IIUqkUQgi+973vFb0NZ4qdM1f6s5/9LF/60pe45pprePbZZ7n99tuH3VZ9fT3XXXcd1113HVdffTXPP/888+fP5/nnn89abteuXVRVVdnR98aNG1mxYgWPPfYYDQ0NRZe9XBgP3KBIJ9X/VHxsy2GYkDzyyCN89KMfZe/evezZs4f9+/czd+5cXnjhBS699FJ++tOfkkyqa7CrS2VCVVdX09fXZ29jypQpbNu2jXQ6zR//+Ed7em9vLzNmzADggQceGLYsTz/9tF052tfXx86dO5k1axYf/vCHWbVqFU8++SSgKjU/97nP8ZWvfAWAffv2ce211/KrX/2Kk046qQRH5fAxAm5QpJLZ/w2GEvLwww/z7ne/O2vae97zHh5++GFWrFjBrFmzWLRoEYsXL+ahhx4C4IYbbuCKK66wKzG/853vcPXVV3POOecwbdo0ezu3334773vf+1i6dOmwfjnA2rVrWbZsGYsWLeItb3kLK1asYPny5VRUVLBy5UruuOMOTj75ZE477TSWL19upyL+x3/8B52dnXz6059myZIlLFu2rFSHZ9QUPSZmKVi2bJk0Azocpfzty/Dqz+D6v8Gc88a6NIYSs23bNk499dSxLoahCPKdKyHEWinloCeGicANCmOhGAzjDiPgBoWxUAyGcYcRcIPCZKEYDOMOI+AGhZ0HbiwUg2G8YATcoEgbC8VgGG8YATcoLAE3ForBMG4wAm5QGAvFUGbcbjdLlixh4cKFvO997zusngavv/56HnnkEQBWrFjB1q1bCy777LPPsnr16hHvY86cOXR0dAya/vOf/5zTTjuNRYsWsXDhQlauXAmoIdHuuOMOTjzxRE466STe9ra3sWXLFgDC4TBXXXUVp5xyCgsWLODWW28dcXnyYQTcoLAtFBOBG8pDRUUF69evZ/Pmzfh8Pu65556s+VZLzJHys5/9jPnz5xecP1oBz0dzczPf+ta3WLVqFRs3buSll16yezP8n//5H1avXs2GDRt44403+NrXvsY111xjN/u/+eabef3113nttdd48cUXeeyxxw67PEULuBDCLYR4TQjxV/19rhDiZSHEDiHEb4UQvsMujWHsMAJuOIKcf/757Nixg2effZbzzz+fa665hvnz55NKpbjllltYvnw5ixYt4qc//SmgotvPfOYznHzyyVxyySW0tbXZ27rwwguxGgg+/vjjnHHGGSxevJiLL76YPXv2cM899/DDH/6QJUuW8MILL9De3s573vMeli9fzvLly3nxxRcB6Ozs5LLLLmPBggWsWLGCfI0c29raqK6utru2raqqsjvP+u53v8vdd99NZWUlAJdddhnnnHMODz74IJWVlXaLUp/PxxlnnFGS7mhH0pnV54FtgNWn4neBH0opfyOEuAf4JPCTwy6RYWxImTTCY4bHboVDm0q7zamnwZXfKWrRZDLJY489xhVXXAHAunXr2Lx5M3PnzuXee++ltraWV199lVgsZvfP/dprr7F9+3a2bt1Ka2sr8+fP5xOf+ETWdtvb2/nUpz7F888/z9y5c+1uaW+88Uaqqqq4+eabAbjuuuv44he/yHnnnce+ffu4/PLL2bZtG9/85jc577zzuO222/jb3/7GfffdN6jsixcvZsqUKcydO5eLL76Ya6+9lne84x2EQiEGBgaYN29e1vLLli2zbRSLnp4e/vKXv9g9Mx4ORQm4EGImcBXwLeBLQnULdhFwnV7kAeB2jICPX0wEbigzkUiEJUuWACoC/+QnP8nq1as588wz7Sj2iSeeYOPGjba/3dvby5tvvsnzzz/Phz70IdxuN9OnT+eiiy4atP2XXnqJCy64wN5WoW5pn3zyySzPPBQK0d/fz/PPP8+jj6pxYa+66ip78AYnbrebxx9/nFdffZWnnnqKL37xi6xdu5YvfelLRR2DZDLJhz70IT73uc8NEvvRUGwEfifwFaBaf28AeqSUlmnVDMzIt6IQ4gbgBoBZs2aNvqSG8pI2/YEfMxQZKZcaywPPJRgM2p+llNx1111cfvnlWcv8/e9/L1k50uk0L730EoFAYFTrCyE488wzOfPMM7n00kv5+Mc/zu23304wGGTXrl1Zwrx27Vre+ta32t9vuOEGTjzxRL7whS8c9u+AIjxwIcTVQJuUcu1odiClvFdKuUxKuaypqWk0mzAcCVImjdAw9lx++eX85Cc/IZFQ1+Ebb7zBwMAAF1xwAb/97W9JpVK0tLTwzDPPDFr37LPP5vnnn2f37t1A4W5pL7vsMu666y77u/VQueCCC+yeEB977DG6u7sH7ePgwYOsW7cua93Zs2cDcMstt/C5z32OSESNL/vkk0+yatUqrrtOGRXf+MY36O3t5c477xzl0RlMMRH4ucA1Qoi3AwGUB/7fwCQhhEdH4TOBAyUrleHIYyJww1HAihUr2LNnD2eccQZSSpqamvjTn/7Eu9/9bp5++mnmz5/PrFmzeMtb3jJo3aamJu69916uvfZa0uk0kydP5h//+AfveMc7eO9738vKlSvt8TZvuukmFi1aRDKZ5IILLuCee+7h3//93/nQhz7EggULOOecc/I6BolEgptvvpmDBw8SCARoamqys2k++9nP0t3dzWmnnYbb7Wbq1KmsXLmSiooKO3vllFNO4YwzzgDgM5/5DCtWrDis4zWi7mSFEBcCN0sprxZC/B74g6MSc6OU8sdDrW+6kz2K+dHp0LULzvrXMXvFNpQP053s+OFIdSf7VVSF5g6UJz64ytYwfjAWisEw7hjRmJhSymeBZ/XnXcCZpS+SYUxIm5aYBsN4w7TENChMZ1YTniM5+pZhdIz0HBkBNyhMQ54JTSAQoLOz04j4UYyUks7OzhGlN47IQjFMYMyQahOamTNn0tzcTHt7+1gXxTAEgUCAmTNnFr28EXCDwu6N0FgoExGv12u3UDRMHIyFYlCY/sANhnGHEXADSAkypT4bC8VgGDcYATdkt740ForBMG4wAm7I2CdgInCDYRxhBNyQ7XsbD9xgGDcYATdk2ybGQjEYxg1GwA3GQjEYxilGwA3GQjEYxilGwA0mC8VgGKcYATdkLBRvpbFQDIZxhBFwg0PAK4yFYjCMI4yAGzIWijdoLBSDYRxhBNyQibq9AWOhGAzjCCPgBkjrflCMhWIwjCuMgBuyLZR0UnVuZTAYjnqGFXAhREAI8YoQYoMQYosQ4pt6+v1CiN1CiPX6b0n5i2soC04LBbLTCg0Gw1FLMQM6xICLpJT9QggvsEoI8Zied4uU8pHyFc9wRHCmEYIWdN+YFcdgMBTHsBG4VPTrr179Z96xJxKpHAE3FZkGw7igKA9cCOEWQqwH2oB/SClf1rO+JYTYKIT4oRDCX2DdG4QQa4QQa8x4fEcpgywUk0poMIwHihJwKWVKSrkEmAmcKYRYCHwNOAVYDtQDXy2w7r1SymVSymVNTU0lKrahpNiVmE4LxWAwHO2MKAtFStkDPANcIaVs0fZKDPgFcGY5Cmg4AthphMZCKTVbD4a45AfP0RsxD0VD6SkmC6VJCDFJf64ALgVeF0JM09ME8C5gczkLaigj6ZwI3FgoJWNrS4gdbf3s7wqPdVEME5BislCmAQ8IIdwowf+dlPKvQoinhRBNgADWAzeWsZyGcmJbKBX6u4nAS0Ukrh6GkURqjEtimIgMK+BSyo3A6XmmX1SWEhmOPM7OrMB44CXEEu6BmHmrMZQe0xLTMDgP3FgoJSMSTwMQjpsI3FB6jIAbjIVSRsIJ9TA0EbihHBgBNwyuxDQWSsmI6sjbROCGcmAE3DDYAzd9oZQM2wOPmwjcUHqMgBvyNKU3Al4qrMg7HDMRuKH0GAE/Bli9s4NH1jYXXiCdAOECtzfz3VASoiYCN5QRI+DHAA+s3sN/P/VG4QXSSXB5wa17IDSVmCXDslAixgM3lAEj4McAoUiSWCJdeIFUUkXfVgRu0ghLhmWhDBgBN5QBI+DHAL2RhP0qn5d0AlweY6GUgYjtgZuHoqH0GAE/BuiNJIgmh4jA00kl4C4rAjcWSqko2gM/uN5UHhtGjBHwY4BQNEE8mUYWGusylTAWSpkIF5MH3t8G914I2/58ZAplmDAYAZ/gpNKSvqgS5FihKNyuxDQWSqkpqi+UaC8gIdx1ZAplmDAYAZ/g9EUzYlywIjOVAJfbWChlwLJQhozAk1H1P2G6nDWMDCPgE5xQJBP5RZMFRCRtslDKQSKVJpFSttWQEXgypleIHoFSGSYSRsAnOM6RYApmolgWikv3Lmwi8JJg2Sd+j2vo/sCtCDwZOQKlMkwkjIBPcJwCXtADTyXA7QEhlJAbD7wkWB1ZNVb5SaQk8ULH37ZQjIAbRoYR8AlOKFpsBK6jb7fXpLOVCMv3bqjy6e8FbBTbQjECbhgZRsAnONkWSqEslESmAtMIeMmwbJOGoBLwgq0xbQvFeOCGkWEEfIKTbaEUEBCrKT0YC6WEWALeWOUHhmiNaUfgJgvFMDKMgE9wQkVF4EmVRgiqQysTgZeEiG2hKAEfNgI3WSiGETKsgAshAkKIV4QQG4QQW4QQ39TT5wohXhZC7BBC/FYI4St/cQ0jpbgsFKeF4jECXiIidiWm9sCHjcCNB24YGcVE4DHgIinlYmAJcIUQ4mzgu8APpZQnAN3AJ8tXTMNo6Y0k8LoFMFQWirFQyoHtgVcV64EbATeMjGEFXCr69Vev/pPARcAjevoDwLvKUkLDYRGKJmnSr/BDR+DGQik1toUS1B74sFkoxkIxjIyiPHAhhFsIsR5oA/4B7AR6pJTWFdkMzCiw7g1CiDVCiDXt7e2lKLNhBPRGEkyuCQBFNOQBY6GUkNwIvGBzetOU3jBKihJwKWVKSrkEmAmcCZxS7A6klPdKKZdJKZc1NTWNspiG0RKKJJhcrSLAoRvyGAul1FgCbr0BFWxOb0XgJo3QMEJGlIUipewBngHeAkwSQujWH8wEDpS4bIYSEIokaLQEvKgI3Gea0pcIK+KuCxYbgR9bHviz29v4xYu7x7oY45pislCahBCT9OcK4FJgG0rI36sX+xiwslyFNIwOKSW9kQSTKrz4Pa5hupO1PHCv6cyqREQTKQJeF163C7/HVXhQh2M0C+XRdQf46XO7xroY4xrP8IswDXhACOFGCf7vpJR/FUJsBX4jhLgDeA24r4zlNIyCcDxFMi2prfAS8LoLe+BZForHvMqXiEg8RaVP3WJBv4dwbJgIPBWDdBpcx0bzjFgyNfxIRYYhGVbApZQbgdPzTN+F8sMNRylWPyg1FV4CXtcwDXmMhVJqwvEUFV71ZlPhdQ8fgYNKJfQFj0Dpxp5YMk04nkJKiRBirIszLjk2HvXHKFYjntoKL36Pe4im9AljoZQBy0IBCPrdw0fgcEylEsYSaVJpWdjaMwyLEfAJTG84I+DDRuBuR2dWJgulJEQSGQul0uchXMjCyo3AjxGsgGLI0YoMQ2IEfAIT0mNh1gRUBJ53RB4ps5vSu7zGQikR4XjStlBUBF7IQnFG4MeSgKuAYsjRigxDYgR8AuO0UAJeV/4xMdNa1LP6Azc3VCmIJNIEfErAK32eIZrSOyLwY1DATQQ+eoyAT2CyBbxABJ7WYnLJF98AACAASURBVO12CriJwEtBNJ6i0orAfe6hm9L7a/XnY8gD19ejyUQZPUbAJzBWV7JVAQ9+TwEP3PK7XaYlZqkJJ5JUWBG438OAoxIzFE2w4oFXOdgTUaJdoQX8GGpOb70RFqzcNQyLEfAJTG8kQXXAg9sl8HsLZKFY/Z44KzGNhVISIvE0gQIR+KbmXp7c1sZr+3pUBF5Rp2YcQ1ko8ZQS8H7jgY8aI+ATmFAkQU1ACXPA4x6BB24slFIQTaSo1BF4hc9DOJ4inZYAtPQqoQ7HkyoCD0xSKx1LWShWBG4slFFjBHwCE4omqK1QAu73uvK3xLQtFC3gxkIpCVLK7CwULeRWB1eHeiOZ78kYVGgBP0YqMaWUDg/cWCijxQj4BKY3khHwgMedv8HEIAvFBzKdicwNoyKeSpOWZHngkMm4sCPwmI7AbQvl2BDwZFqiX0YKp1cahsUI+ASmN5KgpkIJR6BgBK5vHttC0f9Nn+CHRTSuHpa5EbhlFxzSAh6NRgGZsVCOEQF3BhMmAh89RsAnMKFIMmOheNwk05JkKicKzxVwKxvF2CiHRTihjmuFIw8csDNRrAg8HtOCXXFseeDOro1NBD56jIBPYLIsFN0nxyAbJZ+F4pxuGBXWcGrOlpjgiMBDSsATloD7qkC4j5ksFBOBlwYj4BOUeDJNJJGys1D8HnWqB9kouXngxkIpCVZl5aAIPJ4imkjRNaAyfZJxLeCeAHgrjkkLxWShjB4j4BMUqyvZ2korAldCMigCz00jNBZKSciNwK10wnAsSVso03Q+GdMNdzwB9XeMWChxZwRuGvKMGiPgExRnM3rICPigCNy2UKxKTMtCMbngh0NuBB50ROAtvRmRTsW1ZeLxg7fyGLJQHB64icBHjRHwCYrVjH6whZIbgedaKPq/aY15WAyKwB0euOV/T60JkLIE2xMAb2B8N6VPp1XvlkVgvQl6XML0RngYGAGfoFgReE1FroWS64HnZqHo/8ZCOSwKReDheMrOQJnXFCSdFYFXjO/OrO45D168s6hFrVaYdUGfqcQ8DIoZE9MwDslYKOoU+70FInAr0h6UhWIslMMhNwIPeF0IoTzwUDRJdcBDU7Uf2eGoxPRUjN8IXEpofx1atxS1uBVI1Ff66IuaYGG0mAh8gmIP5uDIAweIxuPZPmtuU3pjoZQEKwK3Ki+FEAR1n+AtvRGm1Qao9LmRVl/gHr+2UMZpBB4fAJmCgY6iFrcslLqg94hF4B+895/8bs3+I7KvI8WwAi6EOE4I8YwQYqsQYosQ4vN6+u1CiANCiPX67+3lL66hWHI9cCsPfMbme+Det2YWTBUQcGOhHBZWk3nLugKY4e3n2je+Ql93O1NrK6jwejKWiSegKjHHaxZKtFf9Dxcr4DoCD/qOSCVmNJHipV1d/Hn9wbLv60hSTASeBL4spZwPnA3cJISYr+f9UEq5RP/9vWylNIyY3kgCv8dlC4j9P7QbunZnFkznWChWZaaxUA6LaCKFEJnKY4Dlnh0sCL1AXe82ptWoCDwj4H4l4uM1D9wS8IHOoha3PfBKH4mUzEorfGLLId7zk9Wk0sVViBZDe59601m3r3twa+Qy0xtJ8O2/b2N3x0DJtz2sgEspW6SU6/TnPmAbMKPkJTGUlJCjFSZkhMQdD0Eqlom8B/WFYiyUUhDRo/EIIexp9S7lbyeiIabWBqj0u/Ghz4PdkGecWijOCLyITBSrL/D6oKpzcUbha/Z2s3ZvNwe6S/cwa++P6f2k2HIwVLLtFsM/d3Zy7/O77IdIKRmRBy6EmAOcDrysJ31GCLFRCPFzIURdgXVuEEKsEUKsaW9vP6zCGoqnN0fArQjcHdcXb7xf/c83oAOYCPwwCSdSdgaKRZ1bCXhQRpUH7nXjtwXcykIZXxF4OJ5UfZxbAp6KQ6xv2PWcEThkN6fv1q1Ud3X0l6ycTvF8dU9XybZbDC/u6CDoc3P6rEkl33bRAi6EqAL+AHxBShkCfgIcDywBWoDv51tPSnmvlHKZlHJZU1NTCYpsKIaecP4I3JuwBFy/zpnOrMpCNJ7K8r8B6oQS8CoRURG4z+MQ8MC4s1BSacn5332G+1btzgg4FOWDOz1wyO7QqjusBby9dJaDJeDVAQ+v7D6yAr5qRwdnzWvA6y59zkhRWxRCeFHi/aCU8lEAKWWrlDIlpUwD/wucWfLSGUZN50CMhiqf/d0SE29CRzWDBDw3AjcCfjhEHKPxWNQKdcyriDKttoIKX24EXqkEvMjGMGNNZ3+MzoE4f9vUAtGezIwifPBYMo0Q2N0dZ0XgYXVMSh2BCwEXnzKZNXu7kY5j/Ps1+3lme1vJ9uWkuTvM7o4BzjuhsSzbLyYLRQD3AduklD9wTJ/mWOzdwObSF88wWroG4jRU+e3vXrcLt0vgS+rX20EWSq4HbgT8cAjHU3YOuEU12kLREXjQ78YnEqRdXnC5VRohUo3QMw5o1X26bGjuIRxyRLVFReBp/B5XpoGTMwIfKEME3h+jvtLHW45voGsgzs52df239Eb4+h838ZNnd5ZsX05WvamOxfknlkfAi2nIcy7wUWCTEGK9nvZ14ENCiCWABPYA/6csJTSMmFRaKgEP+rKmBzzgT+mbIqYF3FgoZSGSGGyhVEt1zCe5Y9QEPFR4lYWSdvtVJOWpUAsmI1rMj27a+lSFq5Rw8FALJ1gzwkVE4IkUfo+boB6pyDmwcZe2UEqZtdHeF6Op2s/yOfUAvLqnmxMmV/PzVbtJpCR7O0ufIQLwwo4OptT4OWFyVVm2P6yASylXASLPLJM2eJTSE46TlgwS8AZPHGGlZtkWSqG+UIyAHw7RRGrQ8Q9K9fbT6I0jhKBSWyhpl17OqwU8EYWKI1na0WFF4D6Pi46Odk7w10Kst6jGPHYEnjPUXCot7RTYlt4o4XjS7or3cLAEfG5jkMYqH6/u7uLtC6fx0Mv78LoFraFYyfZlkU5LVu/o4G2nTM7KRiolpiXmBKRTv4I6LRSARo+jgswS8IJN6Y2AHw7h+OAslIqUisDrvUr4LAFPufR5sgV8fDSnb+uLIgRcOn8KA72dyJrp4PYXb6F4XfZQcwM6jbA3kkBKWDxTZWyUykbp6I/RVOVHCMGy2fW8sqeLX7+8l4F4ihsumAfAno7SHvetLSG6w4my2ScwzgX8uTfaueyHz6ka7XQaOsvjY403OvstAc+OAOvdjhzjuPbCrQhc6EuhjJ1Zrd3bzY624VPMJgKRPFkogZT67bUuLeB+D34RJ2lF4B5tmxwFHVq1hqJ87Oev0BoqXJbWUIyGoI9LTp1MINXPgKsKgo1FVWLGk2n8HndmsGfdJ7iVgXLGbJWVXAobRUppR+AAy+fW09wd4Z7ndvLWk5q4cqGqzhtko6QSkBx9Ou0L2v8+t0wVmDDOBXzd3m7eaO1XHeS//le4exmEJlZT2dHQOaAEojEnArfykIHsLBSXF6xXvDJ2ZnXL7zfw3ce3l3y7RyPRPFko/oQS8GqhRNHKA08Iy0KpVP+PgsY8v/znHp57o501e7oLLtPeF6WpOsAFJzZRIwZoTwSgsqHoNEK/x2VX9FoRuFWBefqsSQhRmgi8L5Yklkzb98OZ2gfviya58a3HM6cxCMDuXAF/7Cvw62tHvd9VO9o5ZWo1k6vLV58xrgXcelp3h+PQ8QbINIRajnxBpFRvAEcJVgRen+PB1rnyWSiJjH0CZWuJKaXkYG+kpK3rjmYGZaEkY3jSWrhRx8BKI8wIuL7Rx9hCSaTS/G5NM8CwEfiUGj8NVX4aPVH2Dnh0BF68B+52CSq8btsDt1IIp9dWML22oiSphFYOuBWBnzqtmiq/h8XHTeLsefVU+T00VvnZkxvt73lx1G/10USKV/d0ly190GJcdydreb3d4QT0aeGOFo4YysYz34Zdz8CKJ4/8vvPQORBHiEwrN4ta4RRwRxaKyyHgLjcgSm6hhKJJoom0PZjBREZKSSSRI+COhi6BtBJov8dFQCSIo4+/FYGPsYXy5NZWW/Tahmj+3dYX5dRp1QBMckXYG/YS99fg69wx7D5iibTdQ2bQ77YHdbAi8EmVXuY1BUtioeQKuMft4r6PLWNKTcCuXJzTUJntgSdj0LkjUy8xQtbt7SaeTJfVPoFxHoF36UizJxzPRN6RniHWKBPtr0Pr1iO/3wJ06pxXtyu75rtW98WBy5udRujKftXH7Su5hdKmhbtrID54WLcJhtVVaoUzo0FflyFXLb6UOg9CCCpEkjg5HvgYt8Z86JV9TK8NMLUmYJ+3XFJp5StPrg6AlARSffTKSvbHKotsyJPCp1sHV/o81IbegHW/tN+q64M+5jUG2dU+kNXoZjTkCjjAWfMabOsEYE5jkD1OC6V9u+oeN94/qrfRHTrPfP70mlGWujjGt4BbEfhAHEIH1MToGAh4tBcSA2N+41l09scHVWACVKMv0OpphS0UUN9LbKG0OgbyPdQ7saPwsD2Yg+P20tdlzZQ5uOJ9dmvLgEgQsyNwKwtl7K6jvZ0DvPBmBx9YPouptYGCEXjnQIy0hCk1foj3I2SamLuaXeFAUfeCZaGAysZZ2vkX+PstdIXj+NwuKn1u5jVV0R9LHnYnULaA59QJOZnbGKStL5YZ3q3NEZDFRt751d7OMAGvi8nVhfdZCsa3gIfzWChjEYHbXWkW1xdyuekciA3yvwFqCBMmAIHawZWYTlyeklsoTi+1pZwCfnD9mDdFzx1ODchcI7XHqboaLXB5BXwMO7R6+JX9uF2CDyw/jik1fruxTi5tISuqDdi/zVM5iYNx3WBlmHtBpRGq41Pl9+BJhiEZpa+vj7qgFyEE85pUhLzzMCsy2/tjeN0iq2+gXOY0qH3ZUbhzZKFRCfgAcxqCZcv/thi3Ai6ltP2y3oEw9Ou+DMYqAoeiWqAdCTpzmtFbBOUA/VSCL5hJI0wljoiF0uoQgkOhMgnUgXVqsIo9q8qz/SKxh1PLY6FQO1P913UQAZEgmtbLjbGFEk+meWTtfi46ZTJTawNMrg5kvTk5sYR9So3fvv69wTr2x/VDaJhMFNUSU0fgfg9ubStF+3vsupu5VnbIYfrgHX0xGqv8uFyFxXR2g6p/2NupbUZnBB4duYDv6Qzb2ywn41bAQ5EkSd2qMB06hGrRz9hE4NYTeoiLNhxP8vTrrUekOJ39cRrzROBBOUCIIPirsiPwI2ChtIVi9qhAZYvArbew9tfLs/0iyR0PE8gEFpaA6y5XfSSIWrkEY2yhrNrRTkd/nOvOnAUoce6NJPLWWVjCPrkmYN9zgeo6dof1bxjGB4+nMhZK0OfGk1K/OTmQEfDptRUEvC52aT9ZSkln/8jtlPb+WJb/nY85uQ+L1q3KaoTsnhZzSKflIEswnZbs6wozuyFYYK3SMW4F3Mp1BnD3O1IHj3QELh19IYcLd1P5x9cO8In71/BGa3kbssSTaXojibwReGW6n15pReCOpvT5LJRSR+ChKMfVVVJb4aWlp0wCbj28nSMOjQG2heIUcKtsNXosFFvA44TT+viPcUOeDft7cQk4a57Kk7byl/N50LaFUpWJwIO1jewKFxuBZ7JQKn0efDrFMhXppi6ojofLJZjTEGRXxwCReIqbHlrHWd9+asQReXtfbEj/G5SN01StUwkj3dB3EGa9RRc2fwSeTku+8Nv1XPC9Z+gNZyzHQ6Eo8WTaROBDYVVg+twufOFDaqK/5shH4IlwpkOoIXw/K//55TL3Reysxc+lMj1AT7oS6RTwVDLTE6GF21dyD/xQKMqUmgDTagPli8Cth3f3USLgvpwI3FsJlUocLQvFJxOEU/r4CzGmI9NvPtDL8U1Vdn8gTTVK9PL54G19UeqDPpVJogW8ZlIDnVKlFQ5nJ1pN6UGlEfrS6v6Q0VBW+uvxTVVsPRjiA/f+k79vOkQyLUc8IEO7tlCGY26DzkSxMsosAS9goXzvie38ecNB4sk0W1oyUbrlo88xEXhhLAGf01hJZVT735NPPfIReFZH9oUvWiv/eU2ZRwOxGvE05slC8af66aOCtCeYGTUlncw0n7dwe0veF0pbKMbkGj/TagPl88CtczHWEbhuVTjIQglMAp8WuFg/SIlXxhlIO47/GA6rtulAL6fNqLW/T9EReD4fvDUUy2RY6OM+qaGJEEHSwjNkMJNOyywLpdLnwS/VPlyxUFbwMbcxyKFQlB1t/dz70aVU+T1sai5saeSSSks6B+LDWiigtGRPZzjjf8+2BHzw/n790l5+8uxO3rF4OgBbHcO0WT66icCHwBLw45uqqE60q0506uZCpPiTWxKKHInE8smGappcCixrKZ+FEkj1E5JBkt5hLJQSC3g6LWnrUxH41NqK8qURWm9f3XvGNBMlbwQe6VHZP34t4PF+SCdxkSacK+BjkIXSForS1hdjgUPAJ1sReJ5c8Pa+qPK/wb4HmhqbAEHcN2nIe8EaD9NuyONzE9ACXs0AkxwR+GULpnD2vHoeufEcLqttZrV7BXv37Sn6d3WH46TScrCAt27NJD5oZjcEae+LkWjZrM5V48lqRo6FsnpHB7et3MzFp0zmh+9fzJQaf9Y4m3s6B/C5XUyrLX+XkuNWwDsdAt6Y7kBWT4OKuqM6AhcCDvREONBTvhvU7sgq10KREl+yjxCVJNwVSriTcW2h5Hrg3pJaKN3hOImUZEq1isA7+uP2kFolxTr3yQj0HSr99ovEygOvzE0jrJikKpBBiYL2uvuTjuXGaFi1zQfVdeyMwOsrfXhcIm8ueGsoxhRnBO6rZmqd+m0DnrohKzGt8TB9jiyUCqH2UUOY+mDmelw0cxK/ueEtqkHMgbXUpEMk2t7MGsV+KPI14gHgoffD41/LmmRlvcQPboLJC8DjU7ZXTgT+6GsHmFTp467rTsfjdrFgem1WBL6vM8zM+opBDenKwbgV8K6BOBVeN1NrA0wR3SSCU9UNEgtBehTicGDd6Pxz6+R6h26B1tobtTuTL6eN0qFr6RuCORdsfACXTBGSlSRc+tVOR4GD0whLG4Fbr+AqAtev5b1lGHXGeaONoQ++u30An8eV3ZWBbaFYAt5vj7zTn/KogYFBD6t25C2UzQdCCJHdctDlEjRV+wdZKOm0pL0/ZkfoRHshUEu130Olz03IVTNkBG49vJ1ZKJVoARfZEXgWOsuoJt3L9kPFJQPkFfB0WnV6t++fWcsqz1ri69wOU+arif6aQRH45gO9LJ5Za9cVzJ9Ww472fjtbZ09n+Ij43zCOBbx7IE590EddpY+pdBGpmKJuEBgy7Scv6RT84kpYfdfIC2Ltq35ewQi8L5pgIJ7iwpObqPJ7yjoqdtdAHI9L2GMN2uiLsI9K4m6ngJffQrFywCfXBJiuXytbessQZUZ6VEMZGFMffO2+bhbPrLUjTEBZe4HajIDH++0IPIqXqPVG4g3YlZhSSm7/8xZe3FH+BmKbDvQytzFIlT/7uplcExhUidk5oGwJu5e9qLKHhBBMrQ3QJauH9MCtrgYyHriLSmcEXkjAdXcZDSLExgPFBVtWQJOVhRLtUc3kQwegZ789eU5jJTPowJvsh8lawAM1WXoSTaR4s62fhY43lQXTa0ilJdsP9SGlGt3nSPjfMI4FXDVW8VFX4WGq6Kbf16QicFBpQCMh2qtupo43Rl4QW8DnFow6rFaIMyZVcMbsOl7dXT4f3GpGP6gFmC5nSAaJubQ3Fx/I35S+xBaK5aFOqfHbEbhv469h3a9Ktg9A3ZhTFoJwj1kEHk2k2Hygl6Wz63NmaAvF5VIiHuuzI/CY9Nq2C56ALey7Oga4f/UeHnp5X/kKvO8l+NEZ7G0+kGWfWEyu9tspgxZZjXjAjsABptUGaE1VDROBawHXlbw1nsy1ViPCgzphs+lTXUVP9w0UXZGZNwJ3Plz2v2x/rPR5OCuorbcpC9R/f01WFsrWlhCptMwRcPV5y8EQ7f0xwvFUdgTeuRN+fiXsf6WoMo+EcSvgXToCb3QP4BcJej2THRH4CK0QS/C79xS9Smd/jIM9kZwIvCuvfXOoN2MhLJ9dx/bWvqy80VLSORAbbJ9ARsCpJCocAn4EslDsRh/VGQtl7vb/hVf/t2T7ANRvDDaoxjJjFIFvbO4lkZIs0wMSAOqaiPVmrk9bwJUQxvDZjX/skemBZ15XlWxr9nYddodOBdn/MnTtZGr/FhZOLyDgORF4VjN6yBLwqTUVHIwH1bQC11CuhVIlMm0OqgnbeeCD0BH4icEoG0Yg4JW+zNibQPbDxSHgAMsrdZuSyaeq/4HaLAtl84HBdQUz6yqo9nvY2tKbPwOl4w3Yt5r8I1MeHsWMSn+cEOIZIcRWIcQWIcTn9fR6IcQ/hBBv6v91w22rlFgCXp9WtkWHq94RgY9UwEeevfDpB9dxw6/WqAvVUwHV0wGZd99WCuHUmgDLtA++dl95bJQOqyOr/a9kNynXUURIVmYi8FjfERLwKA06Z7jK72FyIElNpLn0FY0R7TPXzx2zCHzNXnVez3AKuPWQ1yKnWsL2OwTcEYF7M5WYz73RDqgH4MFyZe5oUVwo9mRFlRZTagJ0hxNZlc5DReBTa/3si2nxKmAp5looVa6MgNeK8CAbx0Z74Mf5w7zR2ldUr5Z5W2FaEXhlo3oDcbA00EKzbKQtrtfJsVA2NffSEPQxrTYzSIPLJTh1eg1bDoYcAu6MwHX3ug3HD1vekVJMBJ4EviylnA+cDdwkhJgP3Ao8JaU8EXhKfz9idA3Eqa/0URNXUUobDZkIZ6QWirV8LFTUuvs6w7y8u4s3DvWTtrzNoO73N8+r4yHt906tDbDkuEl43YJXRmKjpBLwgwWw/qFBszr71WCsFvZo9P/4d/j7LZkF9UXYR6Xq0AqOmIXSGoplUs6As4PtuJAqjWuIJvuPrG3mq49sLG4nyZjKPqmYpNJJSxiB/3NnJ89ubxt+QVQ/0POagtkNqaw3QivA8FdnVWLG8Noj0uCthGSEgViSl3d1cc7xDYAajq4YesLxIQdhGIQWxQWu3SyYMbjrUyvX29kaszWUY0tkCXgFHWmdKlnAB7eyUOw0Qu1/p6SgzhXO3wFUNGQ3fpri7iOVllmpe4XI24hnQD0YOflKaN2caRORiHJ86CXWpk/iKf32k2uhbDrQy8IZtYPKuGB6Da+39LGrvR+3SzBjkiOFsHOnypCrzLHVSsCwAi6lbJFSrtOf+4BtwAzgncADerEHgHeVvHQFiMRTRBIp6qt8divMg+m6zA0yWgsFirJR/via6ro2nkoT6etST2nr5OSJOg6FotRWeAl43VT43CycUTuyTJSefRBqViOE5PDhn73MN/642f7e2R9TOeChZujalRkpSB+TkAwSGWSh5KvELF1T+tZQNBOtAYv9uutfJAy0EU+mB0VTj65r5pZHNvDbNftJpopIGbOjXB2BR7pGXpldgNtWbua2lbp3ulSyYJqflJK1e7uz7ZPcskFeDzzi9MATUVbv7CSeSnPjW4+n0udmbZHXy20rt3DDr9YW/+P0W9ASzz5qAoOtiyn6wetMJWzri1JX6VUCnE6rwMfywGsCdKEfBAV8cNtC0S0xK7WF0kEtNaJAK1SrnxtUFgrApubh7/O8zeite/SUq1TPkM1r1Pdtf8Yd6+XJwOU8tU33WxTIZKFYFZj56goWTK8lkkjxzPZ2ZkyqyK7A7twBDScMW9bRMCIPXAgxBzgdeBmYIqW0juohYEpJSzYEdmOVoA/6Wkgj2JeodkTghyPgQ0duUkoefa3ZzrOO9nWpi7dSR+B5oo5DvTGmOiLQ5XPq2djcW/zABlY02fnmoFn7usI8sbWVWDJFJJ5iIJ6iIehRr8bJqF3xk4nAKxiQ+oIeMo2wdJ1ZtYaidqs+gJNFpuafvha++Nv1LLvjSb7/xHZ6wwke29TCzb/fYLdkDEWLKIt1zgM6AoeSROEHeyK82dbPvq4wfdEEPPEN+N+L8lptO9sH6A4nWJZbgRnJE4HHsyPwjIVSAYkIz25vI+hzc/a8BpYcN4m1+4qLwLcf6hvZsHX6+pghD+V94FlRtrMxj2qFab3F9SkRtCPwAJ1SC3ihCDzHQgmgtn1I1lNFgX5OLAGvn4cn2kVTtZ+Nlg8uJbz+t7y2X0ELJVALs88BRKZycc0voH4ejQsv5oU3O9RDNVCr7qNkjG15KjAt5k9Tv3lbS2hwBkrXLqgvvX0CIxBwIUQV8AfgC1LKrHcXqWpY8prHQogbhBBrhBBr2tvbD6uwFlYrzPqgH0IH6BGT6IpI5R96AmWNwNft62ZvZ5h/vVCdkFRYt7CrVK+6+SLw1lDUrrwDOP24ScRTad5sLXK8v65d6n9HtoBHEynC8RT9+nXberDN8A5kLBBrTL9YCOkOEMNHv7Qi8P6yWyjJVJqO/lhWBD47uYeIVA/Ajpa9/H1zC41VPu56egfnffdpPveb1zh9Vh3/9ypVkdQTLuJtwGlT1GsBL4EPvurNjAhta+mDQ5tUU+sD6wYtuzaf/+0sm+2BVw+qxLRtMG8FMhnh2e3tnHtCIz6Pi6Wz69jW0pcZbKAAUqpe8HrC8eIqPaVE9h1iW1r1PsihTYMWyR+B5+SAO36bnUYIRXvgAd2RVZusUy0y89W/WCNuTV2ECHewaHoNG3WFYvLAevjNdcjX/5aznxQ94UR+C6WyUZV58nzY/5IagWffajjjY1w8fxqxZJpVOzrAr89ZNJSpwJw5WMBPnFKFz61+T1YGSjys0hXHMgIXQnhR4v2glPJRPblVCDFNz58G5DUJpZT3SimXSSmXNTU1laLMDgH3QqiFHk+T3YkTgUmjiMC71IkKNg0r4H9Yd4CA18UHz5xFY5UfEevNEfA8EXgomhWBT9f+WNHjQ1oCHunKaixktUYF+MfWVvu4TMXxut2lBTzai9TNuMPSCwhtoeTLAy9df+CdA3HSkiwPvCmyk5fSSpxfBGm2jQAAIABJREFU27INATz4qbN57PPnc96JjZw1t4GfX7/cPk49kSIeJk4hqZujPpcgAn/+zXa7Um3rwV7o1Sl9m/8waNm1e7upq/RyfFNOI458FkqhCNxTgUgnae3p422nTAbUAyGVlmwYxjLo6I8TSaRIpiX9w4g9AOEuRCrO0+kl6nvLhkGLNATV0HxOX70tFHXkgGcLeH2ljwF3LRJRWMATVhaKesNy665kD0n94MvXeZT1Jjl1IaSTLJ/mZmd7P197dCO3/vyvAOzYsT1rlf1daruzGnKatIc7MnVWs86C/a/Cmp+r+2DJhzlzbj3Vfg9Pbm1VFgpALMSmA73UB31MdwRjFl63i5Omqhz/rAjcuncb5uU9FodLMVkoArgP2Cal/IFj1p+Bj+nPHwNWlr54+cmKwPta6PM10WOl5VVMGl0EXjFJ3fhDCHgsmeKvGw5yxYKpVPk9HN8UxJfoUxevN6BuzJwuZRNWBOo46XZrxGIF3BlJOmwUa0CLoM/Nk9taM40WpOMh0pkRcEtAokkyXcqmUwWyUEpjobTaOeD69/e3EYh38WJ6IVK42LtnF287eTIzJlVw6rQafvKRpfx6xVnUVnjtfOCiInCnheKv1g/j4QW8vS9W0MpKpSWrdnRw+YKp1Ad9bDvYrVrwAWx5NFO/oFmzt5uls+sGV8INslBy0ghlThYKECDOhSergOeM45SwrRumInNfV8Y/7ikmTVXbElvSc0hXTYWWwRXGLpegscpnpw6mrbEwC0TgLpegqbaCAXfhxjyZvlC0/MRVuVttAc9z/4Za1LnVDbWWT04jJaxcf5CzG5RQ97fvz1rF6nZ2bmNV9rYGOtX1AXDcWcoGevU+OPVqqGrC53Hx1pObeOr1NtK+Gvt3bjoQyluBaWHZKFkZKFYANYYR+LnAR4GLhBDr9d/bge8Alwoh3gQu0d+PCBkB90HoANGKKYcZgXerWuJhBPzpbW2EoknefYbqlP/4piCVsh9pvWZVNgy6aNv7YkhJVgTeEPThEiMQ8K5dMOU09dlho1gR+DsWT6elN8rzb6h91yWtNKmGTAQQ7UVUqHJGEykl4LE+baHkCHgJh1TLNKPXN7weqmqrnE2Pq47qRAcfOXt23nUn6SGwihKj3EyPIjJR0mnJ23/0Anc9PbhuAVTOb084wQUnNbJgeg2HDuxVdQazz1Pi52iK3TUQZ1f7wOAGPFbZXJ7MqPO+avWGo7MfYnjtHgytQR0WTvbZnSHVVno5cXLVsJko+7oy/nF3MQ89XYGZqpqGa9rivBE4qIdvq7ZQ3mjrI5mW9tvRoBRJ1LXeJeozD7sccrNQrJanrVgCnqfyua9FDbCgI+czGpKsvOlc1n7jUt57ghJUmbO/3R3Kopyb26x9oD3zxnzcWep/OgFLr7cXuXT+FDr6Y+zoUxIZH+jmzdY+TsuTqWNhVW7ObcyTQlg/RhG4lHKVlFJIKRdJKZfov79LKTullBdLKU+UUl4ipSxvP6kOOq3m4u44RHuJB6fSG0mQSsvDiMC1gPc2q06e8rBy/UEmV/s5V6d2ndTgwUuKsEufsMqGQa+NVt/XU2szPpzH7aKxyl+cgKdT6qEy763K2sgTgb936UxcQmVuAFTFW5VgzDzTIeAhRKAWn9ulPEhf1fAWSgkajwyKwHVXndvTx7EvUctsXy8XnJTfWptUObyAH+qN8qXfricc0sfdEpL6ucPaYc3dEdr7Ymw/lL8u4oU3VZ3NeSc0Mn9aDZEObZ+cuULl/jtsFCs6XjYnT3MI6+3HitysHgm13ZZy+ewIPC7UdXLB3OyocensOtbt68n0mZKHfZ2ZysvuoiJwJXh1U2bBtEXQsd2Ohp2o1pjqPP70uV1UeN1cdVrOaDVOAa+tYI+cmok+c8i0xLQicPXgOSTrs7fpJHQQaqbZyQIi3Mni4yapHh/1gObeSLaLu7tjgIagj9pKx/WdTqt71LJQ6uZA1RQlsHMusBe78KTJuF2C1c3qHjtwqJVkWuZt7GTxvmXHce9Hl3LCZMe569wFVVMz57zEjMuWmN0DceqCPoSOIGTVNKSE3khCR+AjTB9zCrhMQ+/+vIvt7w5z2oxaPLqy4qRadSG2JXQ0Emwc5IEPEjDN1NrC4w1mETqoxLThBHWRdeywZ1kR+AmTq1g6u45QNEnA68I70KoaFjWeoKLQdFqLSA1+jys7Apfp/BYKjK5TsBzaQlFcwtE7YutWCDYR9zfQJus4oaK/YK9t1QEvQgztgT+7vY1HXzvA6s07lah69IOybq5+GBc+xtsOKa+1uTt/6trzb3awcEYNDVV+5k+vYXJaV8I3naJyiLf+ybaantneht/jyptiRqQn82YAmR4JdT6yxxewBbw1oo7Fgqbs5uRnzK6jN5JgV0fhiu99XWH7GVGM7RTv0U3TZ86BaYvVteAcC1IzuSZAe1+MvZ0D/HnDQT5y9qxMnnseAZ9WG2BbYgqya3deK85KI7Qq/UiESSNol0P0ZdTXoq5pS3gHHAkRvUrAqxMdWZW3u9oHsqNhyPSDYlkoQsC7fgzv/qnq5kBTW+nlrLn13L9WPZif3ageRvkyUCwCXjeXLZiaPbFzR1ka8FiMSwHvtBqr6Cevq1YNU9Udjh9mBG5lL+zJu1h/LElVICN286rVxXkwqi/myoZBPRJafV9PzRFwNWBsdgTeE47zzrtXZeeIWxF0/Twl4o7+WroGYrhdgpqAl0vnqyzOBp2ZQ810lbqUiqmccN3Ywu91qxvIV5W5UfJZKFCSiszWkGpIYT30aN0Mk+cztTZAO3XUpwu/uFm/rXcIMbJ8zo6ONqIeR5RTPxeQKoe+ANtalIDn6963P5Zk3d5uzj9R3egLptcwQ+iHc+1MWPgeFcntfo7+WJI/vXaAqxdNJ+B1D9qW1dmTjdWh1UAnuDz4fX47C+WA1ufZtdm35lKd2TKUjbK/K8zxTWrb3QPDn7vetn10ympOntkIUxepiXlslMnVfjoH4tz19A7cLsGnznfYAdY15M9YC1NqAuxITUGkE9Czd9D2Ysk0PrcrM8hwIkJMBOiVwextWqRT0N+aFYFnBUpaBybLLtodzf53d+QRcGcrTIsTLoHjzhxUzu+9bzHXnKUq25tbDjGlxs/MuhH28d210wh4LlYzeiu1yFunBLwnHFcR+Ei6lE2nsyNwKCjgfdFkVjPfyR4V3e0Z0NPyWCitoSg+t2vQEGdTa7WFEuuDx27VaUohNjT38pVHNmYq1pwC3niSqpjTaVZdAwnqKn24XIJL56snf2OVT79uTs9cOJ07bQEPeF3Kg/QFMw+6fBYKDPbB0ylY+8CIujtt7XOkUKZTasDhKQt4+2nTmDVnHq5I55BR8qRK75B2wK6OAeY1BjmuMs6BqN+uHykmF9wS8L5oUr29Ofjnzk6Sacn5J6obfW5jFbPcnUTc1ep1+IRLlGhtfpQ/vXaAgXiKj5w9K/+OrCb+FlYEHu4AT4BKn9uOwJv7VAQ5PZhtlcxrDNIQ9PHXjS0FUwT3dYXtN4BiLJRYZzNtso4F02tg0ixVxrwCrs7fH9Y18/5lM7Myiqy+wJ1BwLTaALvS2mLpHGyjqPEwHdITHyDh8hNC1xHkjkHZ36beDqqn6WSB6kyglEpCXwspTyWVIsbeg+qtvC+aoK0vxtzcjCBL+IMNwxwd1fncl65eCsAXz5vCn246t2AFZl6ivepNoUw54DDuBVx5vpUNqma6eyDhaI1ZpI1iNUSoqFMXiNtXOAKPJql2tFZzxdWFtktXdBBsVM2545nKpEOhKFNq/YNO/JRq1cdE4vXH4eWfwK5n7CyCXR0D/PhZfeF371ZlqpkOjSeqSrTuvfo4xOzO7+c2BjllarWKECwBty6ctm0qEg/UKgslmQJ/FakBHf3mG5UeBr/+7vl/7Z13fFzlne6/7/QizYyqVd3k3g2GmI6B0BIgpJJNIZtC6k25N/dubu7uTbK7yW5YNtnN7oa9ZBPIkiwhHUghIZRgAoQSDDbuki1bsnqf0cxoynv/eM85c2Z0xiqWUPF5Ph9/LI1GmnPmnHne531+bTc89Ek4lJ9vezp0DplSzvqPqcyL6g185vVruHi7FpiNdhX9/UjAc1oL5XhvjFXVJWyrhIFsgC89pFVM6kEjfQG0wMHOET7r+QmfcP6MU50deT/bfaQHv9tpKF+nQ7DaN0SX0Lbebh+svR556Jd8/9lWNtSG2NYYKXwJBb0ToQ6vqdDF5cXvcRqVmMeHFTl7svmLmhCCj17exO4jvfzm1fHvVyKVoXM4wYrKICGfa3KZO9FOeh0VquxbCOWDd2qZKMeehAc/CSNdRgDaKQQfvrSAjExl9Dpqwj6OSUXgsu8I9/zhGA/vy72/yXQm538DpEZJOfzE8CGFY/xnV08hDKnxZQQrckQc7QKZJb1kKwBd7eqzcbxXfZZWjlPgmvUSnGRKs8MJnlJKGJ36hJ2+2c1AgQVM4BVBj+rl6y8nElEfsn5dgcPk+6Hoz/OXKQ8ssswy/SyZzjCWyVJqslD0G+3goPY2WhTzdA4lxtknkPPE4yf2aCfVwsmBUVwOwQ1b67jziaMc7R5RBFS2XN1IFavVczUbZSCWylP23/vg6/i7axvVIhKqVwuSywentKITbwif22ko8IyWrZOmYNtfzELRCz0KCopIj8E9b4SWJ8adZ8dQIhfA7dbIVW+WX6qptGJNrZIjrHN1FrVQMllJa98oKyqDBLNRyiuqeGDPKV5pG1SLqTeUywIoQDSZpqtvgI85fspn3T9i1fcvgEf/xrimzx3r57wV5blMCaDB0cfxdFlOATfsQMQHGOg8zrt3LiuuzopaKEqBBz0uQ4G3DGo7L4vJ9O+7cDnrakr564dezet/Azkff2l5gLKgZ1IKPJDsJhWozh13zRaVJfSfN8F3b4A/fRd+9wVjAX7T9noaywuqDAsXJ5QC76eUpKuUZ557ji8+tJ9vP5X7TOkWioGxGCmnH6fDofUeKSBwvYhHv18ClTki1uwTzzJlgQx2HQcwYgXjUwgtLJSJUNCRcNIwCNxW4AZSmSxD8RRlQY/yNyNLTdkKY1Pvh2ImcCiavTCilXPnE7h6jcNDTmV5WJTTd2nT2Auh54VLnRT7mjnRP0pDmZ8v3LCBoNfF53+6D9nfklOTldpKrmWi9MWSeQReWeIllNIi8aE6tSCVr4RTL6nHfBF8bieJdIahjBePVMSYyBQQTzELpRiB9x1V6vzAQ3kPD8TGGIqncpVpXfsBAVVaq85SLeAzkq9+Dfz+dv6682PERq2DjKcG44xlssrnTAxSVa3iAM09UaUoK5qKZkIc6hxhlWjHgeRrqbfSVr4Tdv8j/PKzpDNZWnpjrK/JzxyoSHfRmi7PeeZa0/+t3g5u2lZnfQ5SFrdQxkYMBT46llavO6ARuEW/FZfTwd++aROnhhJ849H8hUnfvTWWB4gEPBOmEWbSKSKZQVxh03HXbVeLdudeuOYrsPNj8PJ9rKeZj17exGevXjv+D1ko8KoSLw4hOJhaQrb3CGUBd17R2Vg6a/QCV+c6ij9Yynt2LkP4whYKvIDAg1U5C2VI7cJFww4A4n2K0I/1xhDCYrCwLq4CE1soBnwWi8pk0N8MiJydNwtYcASu35gVQY/KFok0UuJ14XIIpTo0Iv718wdJTaYJkk7gejOqsuXKoijwGaMagee1ujSGJARUMM1Q4MqakFIqBWqpwJUq9fZqqrT/GCf7R2ksD1BZ4uXz163nueN9ZHqP5W4Af5m6eTUCNawkM/Rc2JCKC1C+MqdCdQsllWVPV07BxbMFt4FO4IXplJ1a06xCVdtzMP/nGlq0AONK3YfsflUtkB7tQzWRAm97Hq9MUD1qraJzhRpBiA/hK1XX8NSgpl7Lmyw9WFD+9xqhPvyPOi/k3sa/ge3vgsO/4WTfCGPpbH46WGIYb3qEdllpzD8cLFHK6ub6ofx+02aMxVTWQ56FYloYnF7DA28biDOc0ewrq4ZZYzF2NAR527kN/MfuFo505caKnTD1oS4LuCfMnT9x4hgOISmpNPn2G94Eb78XPvUyXPBxuPxzEKjE9chf8RfXrM1rB5F7XwbHEbjL6aC61EdLtobtwT5u3FpnzGoFzULJ88BHCYfCfPHGjepvjVPgp9SuULc9zBaKfr9rBJ7V1Pqx3hh1Yf/4oHKsR72Gq8jQCCtY7Qomg76jqvDIbfG+zRAWHIEbRTwBzUIJL0UIobxSk4Xyy+cOnLZyLZXJ8v57nqe5VUsZ1BV42XLLtrJ6aXIhgWedXpJ4ONodHddSdiieIpnOWt74NSEfVQziS/aqCTL9LQaBg8rtXuaN4cqM5hcBVKyGvqNkspLBeEpVo5qhbSkNv9C8ffOF8bmd9IwkebEj94EaTRcocL2XiG55gApc9h4ChLoxzQtcj1bC3LUvrzoxrxIuq3V9q9mc+z1/uQqgWinwbMaoDFyVOqRy/AuQ+/t+SA7jDpYT9rtzU+8rmtQibxEkPdAxzEZPB9LhJh1eoSyI1VdDcoie/bsBWL3ERLTa+3qKSvZ3DNMzkuSLv+ugS0a4oKS4hz+uDwqoIJwOQ4FnONodJYFGLFYE/u2r4Z8288XqJyn3ZLjjt7nS8db+UQIeJxXamMGJFPiJVrWwVdWZiqicLthwY26B8YVh1+eh9SnVLMoK8fEKHOBLN21kx7nnE0x0ssSvds36IOJkuiCImYqBO5h7TSsFXlKTS/MLVKpdrpTquriDUFpLwlmCL9FFIpXhWG8sJxzMiPVOzT6BvI6Ep0UqofqL65+NvuZZK6HXsWAJvNo5orzeiFIQ5UE3A7EUGa0qMixi9EZPn3722MFumk9YEDiM88GHE0rRmIOYJIYQvjBCqG37qEu99l0PP8+RrhGj14mVhRL2u9ns1l57+cUwcor4aJSlGoE7HIIrqjSFZSbwSpVKqBoWQXmgIAA5fAqEQxUnQH4E3BfC53aohkeZnAIZR+C121ROdatp6GvPQa0K8SLVx8OsmnUFPhbNe99aeqK4HEIFVo/vVh/E9Tfmfs/hUDaKlQLvO6o+2MBWx1GGLQKZx3pjBD1OqlxJQIIvQm3YZxRPUbFKBagtLLGDnSNs83YiKldTV15C20AcVl4ODhfOlt8B5Pc00bfq4QZ+8NxJLrn9MR56pYNYeA3hEesdApBf4q/D6VKxCTA88Hgqw9GeKKNoC3LKoitffwuMjRJ8/C951P1pMod+a2TPnOwfZWl5QBMzEyvwnlMq2FfTOAHBnHOrynt/5K+sC9wsLBSAazbW0LhKLdbLhLq++qKislBMynhsNLcrK0bgodrc98FKZe8lhtR1CdeDEKQC1VSjms0ds8oBh/w+KJOFL2zdn8WMxBDcezN85xp44BPqveprntUAJixkAs9qXm9EZaBEAh76R8d4qk0p5TAx+mPF09NaelSQIzGibcX0D1iRVMKopQeuCLyhzM+Th3u44Vt7SUsHjngfN3/zae5/XhG0lQIXQnCeT1PLG24CYJnoMggcYEdY3cjJkGmbW7kGRvsY6leqr7yw09rwKaVW9LQuM/n7wsYHp7Yq5wGOI3CXR21JTzyde6xLs0c2am3fzTZKzyEIqfYC5o52x3pjLK0I4HY64JX71VZ03RvyX6u0xlqBn1LB3WiwkW2i2TITpaU3xoqqIMKkcmvCPjqHNfWqL14FNko2KznYMcwKeRKq1tFQFlAK3BeGxtdR07Wb2rAvf7HW8smXNK6ieyTB9ZtrefS/X8bKDeep888Wset0MioI9BmBTJeyUGLJNM3dUUpLSpVdkBzJf34mpUrOL/ok3PoLPL4gn3bcz2/2KXI8Ydq9lQU8RJNpQ/FaQe8b4g4X8e51OF1w9d+qxeOlghmmo/1KmeripxAaedVl1H2u9+oZn4USN1oIWJLlcEfOboOclTLap9U8KLtQlNayRAzw3LE+RpJpawKP9U4+A0XHRBZKtBvufgO0PQ+b3wZ7vgd3X6vG6M1iCiEsYAKPjGmqTWtuo3y/Mf7z+U4SeCZU4M09SuFkov3qw6R7YkU62VlbKKqRfVNVCX86MchIMkPWX86fbQqyvDLA3X84Dowv4tGx2XmCHmc11Ktc0+UFBL7O00NaOng1ZlI4WiZKvENtn8dN8NaLeIznF1oo6pJfsH658XCskMABll6gyFgnks69aqu6+mr1vV7Sn0kpMt9wo7KCCgh8ZWVQKaz9D6jnuAtSsYop8I494PLTs+JmmhwdjAyMb0V8vDem7BkTSdaGfSYLRVu8Cjz7toE42bEY5WOnoHo9DWV+hhNptcta/Xrqk0fZUVGw+A+1gcPNZ26+lGf/95V87e3bWF4ZVLMT03EYPD7+HCBnaRWqVN2mcPnwe5wk01kOd0dZVV1qrUJ1UvOFYcUleM57L5scx3niT68abWSXGQSuBfXj1ve/lJLM0CkyOCenRlddpe7Rp/8lv77iubsAaQiQcdDEQ3VSLRa6Dz4tC8V8T5uTBYZPKQUO+CoaWCIGeOSAEndFCXwqAUzIWShW+feDJ5Tq7m+GP/sBvOU/4C3fzsWDbAWeD/0mKElowQvNQikLeDjZH+fxQ92k3SGq3HGjP7YVmjUFLhKDSLM68gSVgi2YUG+dhaK2j7ec18gt5zXy609dgidUTSA9yI8+fCE3baujPuK3tFAAmrLHOMxyw3NeLjppLMsReH22g3ZZyZ5TpiyMSkXgmW6NwK2CmObtZmmtaqKkNVPa2hDhgpUVbF5RbzwlarXbXnaBsh/0Zvede9Wk7nCjslf0kv7+Y2o7W7sVqtYaSj2blblKuIO/VPbKllvGv05pbS5NzIxTe6BmE+n689Tf0zNpNCTTGdoGRo0MFAB8EWpCfnqjY6ra1F+mfPaCTJT9HcM0Ce3+0RQ4QPtAnGzTVQBc5S7ojT3UBqE6gj5PfiGLPvy2+8D4c3j5fpVLHaof/0H25itwUL58U3WwCIFr56jlkIumK9S3J37P/o5hEqksS7WMi4jRxdHaRukaThJK9ZLwVo4f5mEFIeCiTyl77MCD6rGxGPzx32Ht9bn3oBDeEiitIzSqdi99sST0HKIhefT0FsrYSK4GIRlV5JmnwDUCHulQi7+mwF3hOpaIQf7YrBb7lYUphIV9UCYLb0jZh4VxiWi3Srkc7YP3PqAWOoDNb4X3/QK2vlN9jmYRC47ATw3GWRLy4hxuU2+sRr6RgId4KoMEvKXlVDrjeZHvQrRoCjyYHSHjLdjeNuzIEZcGQ4FbEPi1m2r5+7dsUaPMtI6Efo+Tf75lO0/9xa788Uo6xkZZMnaSl9ONSG+IqCvCand3XuMd38gJOp21+X2gI8vA6cHVrxaYihIrAs+RM0IoJeQNgRDccv5S7rttJ05f7uaOpiwUeMN5yks/8YxSHp37VC9mh0ORka7AezTiqlqrApSaAj81FCeZziqF/MoPFPEvu2j865TWqK2mqfiJbFYVlNRuw91wDgDuznwCP9k/SlZqhRrxnIWiD5vV25+qY80n8IOdw6x1tGnHvY56rTy6bSDOKe9KOmQ52xPP5x/nUJux28tDlZZaZ+4hkh6DX34WfnabUq63PTG+mZHHrMDVPTWWzrKqqsSawJMmBQ5Qu5WMr4yLHXu5Uyv6MlsoULycfn/HEEvEAFJP45wM1r1R2QFP/ZO6H/70nyrQf/FnTv97FU34R9Rutn94FP7rHXwm/i85BZ5JKQFgVuDm8y1MIYScAu/aB8jc/V5ah4sMJZkh3E5hXFcDhX1QJgv9mMzXJD4I975ZLSDv+vH4UvzG8+Hmf5+1JlY6FhyBtw/GVeWYlgOuQ69IvGJtNe5gOWWO0aIELqWkuSdKQ5mfiIgy6ixoEdl4vlIb0dy2fTiRwuNy5CsHqwBOQTl90eKO7gM4yPJyainRZJoORx2rXQU2QX8LidJl7DlpInCnC+rOobxXzT2MmIOYiWGlXkIFvmbVulxQU4cnt70csXqbvKWqsKP1GfVeJ4eQSzbz8L5OshWrcraEnoFSuUYR+HA7xPqMDJG1JaPQ/BhseXtesyADpdqxmm2U/mal2Gu3EiqvpjlbS0lvfon3Ma3SbnllMN9CiSgC7zBnohRUYx7oGGZHoFulS5avNPpbtA2McrQnxhOZrdT1P5s/GWbopOqBYvU+RZbmK/BnvwnPfwsu+IRSZiXVFr+XU+BBT+6eKm6h6E2jtHvV4cS56gp2ufbxq71qN6Hbb/o9YVXMI6Xkh8+3UeMYwFdeP+7nReFwwoX/TVlbzY/C0/+qFmSLHiJ5qFyNs/8oHqeg4uRvYOAYZdmBnKjRF26zAjefr5EWWxDEhFzZf1gncLUg1YgBllUExzdJm04Rj/mY9EVlbBTuu0UF799x78TvwSxiwRF420BcbXkHT+Ypogotne7dO5eBP6I88CIWSm90jJFEmivWVRMhxjAFWy29R3BbToVHE2lKC3N9tQ5/eQhUQKy7eFBLh1ay/KpcRtdwgpbsEpZishJivZAYxF3VRGvfaL6aWnEp1SP7qfWO5S8ohTngOq79O7jl+/mPeXLnPFIsYWHZhdD+ArSrxeKQWMZHvvcih1LVKlc+PaZu4shStSAs2aR+r2uvQeBruh9WVoyVfQKmYh4TgWsBTOq2Efa7eVk2UTm4N8+DzOv1bLJQdAXeMWQKZA6357VJPdAxwib3KRVPcLqoCHrwuR20D8Q52h3liew2XKkROPlH9QuZtOa1WhA4qIIencClVBWMyy6Ca748vlGYDpMHHjAReHELZXzXP5quoFwOsJqTCIGxEJUFLQZhZDMQ7eHBl0/x8KudLHUP4wpPgcBBWQLBavjJB1Ubi4nUN0DFKkRikKZggvPa1Az0MobxOvVGVtp1cRchcEOBm0SJ26/uX53ADQWuSL5aDBTPQIFJ9UHJg976QI9D/OGfVLrgm+/K2SZzhAVF4JmspGMoTn3EZxQWFaSoAAAgAElEQVTx6Lh2Uw3feOd2NcXEF6FURosqcD0D5bI1VURElP5swcWu3abyk/UPMOM7EZJKGP1F8rDsQnXz7f3R6U+mcy9pdwltsoqOoQQHkpWUpXtyPttRlcpWskb1KM6zUVZcgoMsl/kKKiILe0boKKkeX85rIvDhYk7T0gtUSfdL9wKCw1K938+NVKit6MAxpcCr1qnn6znenXtp6YlR4hGUHLhfVfhVrbF+DaOYx7R4dewBpxeq1uF0CA45VxNM9eUNCMjr9RwfVAFUT5AarV9FngIHQ4Wf6BtVAb/sCahWxy2E0DJR4hzpinLAt13FDI78Vv1utFOdb8TCQgHlAfceVgta69Pqtba/p8ibqsGUhaJbKCVelwp4W2U9JAosFICVuwC4xLGX2pDPWMz1IGa/mcB/9Vnk1zfxvZ//kp2Nfnzp4dziOVm4fbDzI8o6WbJpcuSlef/vcf6W+sQRqN6IhzSlTk1c6Qurp4iF0rlX3QuF732gItdDRydwTaUvEQPje6DA1Pug6DCOSbsmR34LS3fCpjdP7e/MAhYUgXePJEhlJCtK0uoCmyyUoNfFjVvrlGXhjxDIjOQVD5ihZ6CsXVJCRMToShV4ZW4f1G3L88FHEmnLPijjCHzjm1VA77G/ye/alxyBI4/klHnnXlJVmwDBK21DNGc0i0PPfjn4SyitZeXWixGCfBul4XzGcHOBo6B383ARAreCyUIZHisyJGCpFoBpfgwqmmgdVqrpt12aeuw5qKpCdR84WKmUUuc+WnpjvC/0IqJ7P5z/4eLHUUyB12wymmod92pBMm0nAAW9nvV+HEJQ4nVR6nXlF/OAEci8++ljlDqShBKncgsPSr22DY5ytCdK7ZJqaLpSTSkfPGHkgJ9WgWfT6jVeulcRcLHMDB0WCrypKqju39MpcFPbVsL1ULWOG0oOsL4297jf7cTjcuSCmP3HkC9+F5FJ8A/yH7ljl6Z2J3OfFGLHB5S1duX/zQ2oOB00An9b/Mf0OiqR598GQESfi16owA21q51v69MqJuUqSJfVbRRvKLcL1mzCeueA5eDh6VsopmMa7Vf3p7Z4zjUWFIG3Dyh1utKtecxWQSUAXwRvJoqDrGVFWktPFJ/bQZ0/g5s07UmLLJHG16nJ41rxQrSgley4QbU6HA6VNzt0UkXpQZH3vW+G779VNQnqPwZdr+KqUz2YXzjeryaYgFJvqQQcfRTWXkeJz8Pq6hJeNhO428d+13q2ZwpmGOoEbg74FIPbr4KUwHAyn8DTmazqO11SlWugVbNZFbsAr8Q1BXP0d2oXYiJCPZDZ0dPLBxP3KPW95R3Fj8MXVlktugLPZtXWuHab8ZSekjWkceUR+PG+mPK/QSvnzl2HmrDPZKHkUglHEil+9EIb71utqb8CAj/ZH+dI1wirl5TA9f+g7JCffcTo/lj0ftOzME7+EV79ueoV7glYP1eHJYFrqtwXUcRmLpxJDgMin8ABmq5gS2Y/33hr7lyEEJQF3DnbbfcdZIWTT4z9N5Y6emh47JPq8akqcFAL5Ud2w5prJvf8yFJwuHCT4vuOG8loJBvOap8fg8BNeeCgPl/JqLoXllpkcugq2mwXOt0QrOJD2wK5iUFmTKcPCuRbKMd3A1IVfc0DLCgC1wmkHm0rZFLgedAyU0qxDmS2aPnDjqQixeOjFn0RGs9X5KR51SPJ9LgqTMCyCo0Vl8Kaa2H315RX/1/vUOSz8+PqhvzmTkjFcNdvpdTn4oXWAVqlrsBbVCvPVAzWqqKXbY0RXm4byusD/azcxNKx5vwhysPt6sYuVCtWEMLYxg8VvEUPv9rJW+58WqVa6mlQNZs5OTDK8ooAUREg5q6AQ79WP8sj8E3I3kO8aeQ+IuleuObvrIOX5uMw54IPHFOB2LocgQcDAVpcKw0CjyXTdA0ncwo8nt+Po8acC+4tVcqsr4UfvtBGNJnm7cu0wJkp/a0+EmAonmI4kVaZIGXL4PrbofUP8MTfqScVU+AVq5WF8+QdKif8nAnsEygo5FHCoEnvvVJoI4C637yh8e9l0xWIdIJgV37WjCqnT6n7ac99PBW+geeCl8Ouv9RaIjC5hf5M4XRD2XJGnSG+m7yUpEcV/ZRm9YCgHsQssFASQyoGJTPKliyErqILdxGltfji3dbJA9PpgwJ5k+lpflxlENWfM7W/MUtYUASud4GrSOtVmEUIXFNjYRGzzAVv7omqPglav5NTSf/4/skNWmRZ88FHEqn8IObpCBzgqi8pIrrzIrUNfPNdcO1X4KN/gPodSv02nMeSkI+RRJoREUQGKtQ2/NAv1U2y4hIAtjZG6I+NGQuYlJLHk5ptcXx37jX1PuCThfahGUjkK3B9p3O4cwSWah+eJUqBb2mIsKkuTCu1OU+x0uRv12xGZNN81PkQ7XXXTC4PtrRWpYS1PqOCQ5CnwMsCHl5lleqqmM0YAdKVhRaKhrxyeoCKVci+Zu55+hjnLS+jMd2qMlBMXeLMk1aMHihb3wnrb1CLir88z3bKg9uX67tSvRHqJvHhNrJQfDSU+bl5ez3XbdIUsVXamlXAHBS5OT1qx2ZCRCts48k7wOnm39M3srEuhOPiT6tiLOGcnoUyHVz1JX6/4W/oT3kYEurcSrPajtLSQhHqfFufVp8TqywPPRBZGIgtrc3FggoxnT4ooBZbvU95yxPqc1nYQ3+OMCGBCyG+I4ToFkLsMz32RSFEe8GU+llH20CciqAHT7RdbbuLbYW0zoINomecAk+mM2r0VGWOwAdlCa19BS1LQ7VqgdAIfFwQMzkBgVevU1Ouk0Nw07+p5H5Qyu7Wh+BTr0DVWqNKsy7sR5SvVDnLh34Nq640lPTWBkVOL2k2yuhYhhfTK0g5/Uqtgyr9b30mn0wngkZIoxlHbgIQuVmbLb0x2HgzXHc7mRWXc2owTkOZn0vXVPJKQkuNC9XnE4s2miuFi5FL/mpyx7HsAuWn330tPPAxFbQyqeNIwM2zmTUqtbD9TwaBF7dQ/PREk7lulOUrGes+zMn+OO+/aIV6LS0DRUcegetKWAh44z8rBa9X6BaDvgs55z2T84ZNCtztdPD1d2xjZVWBAs8j8GHre80TVH7sc9+CA78wHi4LePBHW+HlH5A+53083+dRPrnDAW+7Bz7w2+L37kxj/RuJLVcBz/akep+Dae3cCoOY5p7grc+oeJJVLrWhwAt2RaHa4t0tp9MHBdT19IZULcTAsXljn8DkFPg9wLUWj3/dPKV+Zg/LGm0Dql82g62KXIt9UJZdRNZXxvudvzb6L+ho7VMFIE3VJTkCp4TjfRbNgxpfByefQ2azkw9imnHd7fCJF1SbUjMcDiOqXq21lW0s96uUt9anVXTd1DNkXU0pJV4Xz7YoD68/NkYaF73lO+DYbpXm9pMPqffjikmSJhgkkpFOo1kXQO+Ies+ae6JKXb7uw3TGMqSzkoayAJeuruKoPjJLD2DqKFvBsK+ef03fRP2KdUwKV/5f+OxRuOU+uOjTWvpdTuFE/G5+k9igprUc+S37O4ZxO0Wu21yBhVIX9iEldI/oxTxNeJN9rA5LXr++GroPGhkoOvRqzFKfi6pSkwUVrIA//7Uaens6NOxQxSib3z65c9Z9VZdF/KWoAi9yr73pThV7+OF74IXvQDrJ1fFf8dXYX4HTTfOaD5LOylyg0xM02q++VtALzk7GnCSli0BaV+Da585tihn4wmp31/Z8bgdYCMMDH2+hEOuxbrw1nT4oxjGFoOVx9fXKy6f3N2YBExK4lPJJoPjk2dcQ7YNxVV1VkEI4Dt4SxAUf4yrnSzi780ui9RTClZUleQr8RKECB0XgIx0k+06QyUpKvJP0wHU43UbpezHoCnxpeUAF3GRGbW9Xv954jsvp4OJVlTx+sBsppdEPJlp3ofIzf/VZ5Re+8etK4U8WGoGncTIcz/UH79EWPV3pArQZAwP8nLOsjA6ntnWtKiBph4MvN32fHwTemR8zmAglVbDuenj9l+D8D+X9KBzwMChLyNSdC0cfYV/7EGuWlKq0OSnHWSh687BOLZDZ5Vb3ypcaX8R1zzUwdCJnkWmoLPHgdTlYXV0y3j+taCqeBqlj58fgky9NPsfYVMgzDsUIvDCAqSNYAbc+qNL6fvEZ+Np6bm6/g65sGPmuH7F3SKne9bWzWxV4OlRqdRodw0n6CeHXCdxQ4AUEfuxJFYOy8r8hVxxVyAN6YLZwTJ+UitinGsA0H1NmTC0QU9nlzjLOxAP/hBDiFc1iKdKODIQQtwkhXhBCvNDTM74h0WQhpaR9wFSFWSwjQH/d132YEQKc2/rtvMf1FEKzB+4vLee4JYGrD3nymOrKN66M3umxVlBTgN4npbEskMuYWHbhuA5vu9apfPGDnSMGgaeXXax++OLdqlBGt2kmC23bmqJAgWu2U0tPzAic6v57Q5nqLli6dAtZBFIv3jGhpS9uXUgxTUT8aiEYabwCTr1Ee1srW/Q0sdSoKsX2mT1wRVj6YIfdfYr4Ljz6NdV35YZvwHkfzHsNIQQXNlUYU+inDKcbSpdM/DwdZSvUNbZqdmRF4MnTKHBQ1/KW/1LnVbOZX227k5vHvsRwzQUc7BjG63LkJiPNAXQF3j4YZ0CW4hvT+u0XeuCg1K4eX7HKQAFYcZnaFS2/JP9xq8peKVVab6wnvx/9VKC1qWblrslZZK8RpkvgdwJNwDagA/jHYk+UUt4lpdwhpdxRVTXNDwdoDYqyLC9FEW+xAKYOX5hf+G5gy/Dv88qcm3ui1IR8aoJKfABcfmoqy2i1slCqN4I7iDj+FAChQgLX+oucCfTJPEsrArmRaYUtV4Fda5XieOxgt+FRBxq3KRIoW67S3qYKTQVmcOb12+6NJnEINZBCXyxODowiBNRppeobN27mhuTfcqwu/1iTaTWYoMmqmf40oZeGdy9RH9ZtyRfZpE1fN/dB0ZFT4IrAf3IiwG/cV8G1X4VP/gnOvdWyQvLuPz+fz7z+NVJXoVr4i+Mq370QvoJcaP3riTxrpxve8I/w3geINVwCCAZHxzjQOcyaJaW4nHOXs6A3XTs1GKdPluI1E7jDnR8U1M+zal3xHY3TBVtvGd+MS1fgrU/lOic+/hU1Lu/c96k89ulAvyYrL5/e788SpnVFpZRdUsqMlDILfAuY3WYA2ayRgbLSrbk5ExE48GT524jjU5F4DS09pkkd8QHwl7G8ImitwJ0u2HgzJQd/yGrRlp8HHh+YkSDQ1sYIG2pDavp57TbVivLcPx/3vOqQj031IZ441G3k95aX+lUjnff83DpDYSKYFLg+GCCbVRbNhjr19/SxaG0DcZaU5qr9Ll9bzQFW8IVfHDICoFJK/tePX2FgNMXVG6aRY1wEene9Dv9qEr4qdjn3sLm+QKWaLJSQz0XA46RjKMHQaIrnTgzz8rlfVlWEk0mxnGuYsx5A5cYnhqd0jY2GVqMpDnSMzKl9AuBzOyn1ujg1GGeAUjxJjcDNnQiNJ2vXtpj6Ph3KVyqb43dfhK9vhB+8C568XVXGvuHrp09pPR10+2rlZdP7/VnCtM5GCGFOIL0Z2FfsuTOCp79Bw4Nv53LHHhocE6QQmuALV/FT17Xw6k+hr9loYmUUTMQHwV/G0ooAvdEksWR6/B95/V+TcZfyVfddlHq0t+v4Uyrib8pVni5qw35+9alLVBBNCGWDFJmhd8Xaal5sHaClN4bbqaoOadiRG4E2VZg9cK1d7mA8RSYrOX+5Uj56zMAIIGtoLA/w1bdsYfeRXj76vRdJpjN87ZHDPLDnFP/zmrXsWmfRwGmaMIZWxzMcLn0dlzj2srZaOxZTHxQdQghjsMMTh7vJZCVXrp+CvTHXKKzGHIuiJg5NXjDo/VAOdynLzVypOVeoKPHQPhCnT4ZwJTUhZu4FrkM/T6vulRPBW6IyvN5+r8pgOfRr2PZuZZtNl7wB1l4LO94/veKnWcRk0gjvA54B1goh2oQQHwBuF0LsFUK8AuwCJtHV5gwQKMc3fIx7PLfnqsgm8MBBDT7+f2NaAs1L3zOaWFkpcMBIJewYihMf07ZfwQr2b/kc5ziO0th8n0rzu//daqV/w9dm9DQnwq511WQl/GpvB+VBT/FOh5NFoALp8mlBTKXA9aydrY1hPC6H0Xb3ZH88j8AB3rajka/cvJnHD/Vw8789zb88dpR37GjkY5fP7BQS3QMfHB3jicw2IiKGV28v2/yYcS5m6Lngjx7opiLoYVtjQcXsfIeZwCcTMC+A3g/lmWaVubSuZj4QuJfYWIYBWYprbFh1e7RU4Nq1mm4vbZdHDQ/5s/vhcyfgpn89M/IGlU77xq+f2d+YBRRplZaDlPKdFg9/2+Kx2cM57+WO45tJvfIjvhx+XN3Qhe1RLVBR4uXEWIjMhl049/6I/Y0fAWBtjbadHO2HiiaWaY3wf76nna8+fJDfH+7htktX8vnrVS7y4errGMx8j0ue/3s4eDcg1M1ROCZrlrG1IUJF0ENfbIza8Axsic//EGLVlXi+2WkEMfUUwqpSL8srArT0xkhnsnQOJ4xUOzP+7HVLSWWyfOHBV7lkdSV/e/OmM19YChD259qj/qR/FR/HifPIIyqF8sl/UKXrBcGpmpCfJ4/00Nwd5eqNNeNbi853mAlcr8gsloViAd1CebpZ9f+YawsFlKAC6Ef//PUpD9xdcF9tf5faYRerfJ0K9GyfRYoJCXy+4MRwms6y6+CjX1ZR5UmsqHrke3D1m6lo+Th9rz4OlJoCYEqB6wR+15MtVJZ4KQu4OdKVm0kYHcvwz+n3s5vPq8ZG731w+rbFGcDhEFy2poqfvtQ+fpDDdOALQ912Qr7fGWmEegphVYmXFZVBjnZH6RhKkMlKlatugVsvXM65y8pYVV2i5l/OMFxOB6VeF6+eGqIt4aGvdivVz35Tffi33AJv+ua4YHJdxEePthhdtX7m7JzXDGeowEN+N0Ko6Tu1YZ8RR5hLVGjzW/ulicDHYuMrXCNLx9dO2LDEgimlbxsYVTngQkx6O1SpkVxbzZXgKaHq2M9ZWRkk5HOrRUAj8FKfm798w3puf8sW/vC5XexYXm6koIHqRNgmq8nccj+852ezPibpdNC95fLgzAXjQn5XToFrKYSVJV5WVpVwon/UsJasFLiOTfVhfO5JjOeaJiJBt2EHZFZdrch7+7sVeVuMBdMzUTxOx/RTA+cSvnBOeU+DwJ0OYexc5oP/DbnPYz/a8cR6rRW4jUljQShwPQf8olVTK4PVhzz0Jhyw/ga2v/wA56z5tPrhSIcqFNDyrT94SW56e33EzzPNfUgpEUIQTabxuR24mi6dmRM6A1y6pgqnQxgfhplA2O82PPC+aBKX9uFfWRkklZE806K24YUe+GuJiF/NPHU7BeVXfhJWbVc9PYos5vpgh51NFSpldKEhT4Fb9AKfBMoCHgZHU/PCPoGchdInNQIf7VMe+GvRVGuRYkEo8KF4ithYRhXxTAG6zdAXHWNw9ZspYZTrPHvUTfODd6mVf+11436vPuInmkwbmRkjidTUqgpnEWG/m++877y8BedMEfK584KYFSUeHA5h9Ob4/eEeHCJXIDMX0DNR1taU4vUFVVbAaXZi+nDo1y9E+wRUIO8MLBTIvWfzIYAJOQtlQBZ44MWahNmYEAtCmpirAKcCQ4HHkrwU3Mx6WcY5Aw/Dz55Sne1u+b7lRO26iF7JFyfsd6s+KPNIxV22ZmYtgZDfzQmtVL43Okal9kHTi3H2tQ9TF/ZZD2d+jaDbAUb+9wRYvaSU777/fC5smmbp9FzDF1bpg5m09TCHSUAPZM4XC0UXVENCCywWC2LamDQWhALPEfjUFKDf4yTgcdIXHeOVU1EeyFxEWfvjcOAhuOYrlhWPkKs2PKUVD0WTBY2sFhlCPleeAtcJPBLwGOloU108Zxq6mtxcP/nMn8vWVM1KUPU1gU7WyWFVRu/yT7mPdVlA9XeZybYGZwL9vnK5PGqHEevV0gjnx/EtRCyIu7ttQKnDqVoooFb9vmiSve1D/DF0jZp1eN4HYedHi/5OvUmBgwpilixmAve7GU6kkFLSO5LMy3DRbZSGIhkorxUifnVMk1XgCx5GP5TByZXRW+ADF6/gjrdtnTcplLoH7nU7VFvXUTuIeaZYEKzUPhgn6HEaKmwqqAh66YuNcbhrhAubtsD1+1Uns9PkKleWePE4HbTpCjyRprJk8d5kYb+bVEYST2XojY5RVZLLcFlZGeTF1oE5V+DnLitja2Mkl8O/2GFuaFVsmMME2FAXMloizAdEAh4cArwuhyq8GmoH5MTj52wUxYIg8F1rq6mP+KdVIFJZ4uHltiF6RpJKvU2iY5zDIaiN+IxUwmjhOLVFhpB2bu0DccYyWWOrCyYFPocZKKDSJ2eyPH/eI4/AiwxzWGBwOgTlQY/qpxOozM04LSyltzFpLAgCv3RNFZdOM3BXEfQaBR1brCZVF0Fd2G9YKMOJVH4jq0WGkF+dm95qt7I0Z6Ho02mWldsq6TVFoQLXpkwtdFQEvWSlVF0Go1rLV/fcioOFjAXhgZ8JdD/XIZjSdrIuoghcSkk0mc5vJbvIoCvwll7VuMqswHetq+bf330u569YHASyYJA3nX14yhko8xWVpR5V8GXuXWNbKNPG4mUlDXru6arqEmP692RQH/HRNZxgOJ5GShZ9EBMwGleZCdzpEFy7aX51YDsrMM4DX/gWCsBnrlrD6FgGevfkHrQtlGlj8bKSBr1icSrpZ6AUeFbC0R7VEyVvnNoig7670FvHmgncxhzB6Ak+vKgIfMdybSc3aivwmcDit1C0Yp7N9VPbgurFPAc7FYEv5jxwvUimpTeGELlWpDbmEPp09miXmsU4nYEd8xnm6fC2Ap82Fj2Bb6wLcWFTxZQb+tdrWReHNAJfzBaKnmEzOJqiPOCZ09FbNkzwhdX8V/3rxQRzUNZW4NPG4mUlDWVBD//1oZ1T/r26cD6Bz6dS+pmGx+XA73YST2Vs+2Q+wRcyEfgCG0gxEQJmBW4T+HRhS60i8HuclAc9HOrSLZTFbSvoqYTmFEIbcwxfRPWfh0WThWLAbKHYpfTThk3gp0FdxMfgqOoRspgtFMilEtoKfB7BF1Ytj/WvFxPcAXBps1/tPPBpwybw06DO1D51MQcxIRfItAl8HsFM2ouNwIXI2Sgum8CnC5vAT4N6U/l4cAo55AsRIZvA5x/yCHyRWSigApnuwJkPHD6LMZmp9N8RQnQLIfaZHisXQjwihDii/V82u4c5N9C7EgY9znnT0W22oOeCz8isTRszg8WswEH54HYA84wwmaXvHuDagsc+BzwqpVwNPKp9v+ig54Iv9gAm5BR4la3A5w900na4FifRhRvyg5k2powJfQEp5ZNCiOUFD98EXK59/V3gCeAvZvC45gV0Al/sAUywg5jzEjqBe0OnbX+8YHHlF3ODm21MC9NlpiVSyg7t606gaJWMEOI24DaApUuXTvPl5gb6ZJ7FHsAEUxDTTiOcP9AJfDHaJ6A6EgYX6Mi7eYIzZiYppRRCyNP8/C7gLoAdO3YUfd58RGXQi8flWNStZHW8YUstWSmpCfnm+lBs6FjsBG7jjDHd8G+XEKIWQPu/e+YOaf7A4RAsrwicFb5wXcTPhy9rmtbQDBuzBL14ZzFmoNiYEUxXWj4I3Ar8vfb/AzN2RPMM33rvDvwe51wfho2zEbYCtzEBJiRwIcR9qIBlpRCiDfgCirh/KIT4ANAKvH02D3IusazCLvO1MUcwgpg2gduwxmSyUN5Z5EdXzvCx2LBhwwxvCBC2hWKjKBZ/dM6GjYUKhwOu+TIsv2Suj8TGPIVN4DZszGdc8PG5PgIb8xh2EwIbNmzYWKCwCdyGDRs2FihsArdhw4aNBQqbwG3YsGFjgcImcBs2bNhYoLAJ3IYNGzYWKGwCt2HDho0FCpvAbdiwYWOBQkj52nV4FUL0oHqnTAeVQO8MHs5Cwdl43mfjOcPZed5n4znD1M97mZSyqvDB15TAzwRCiBeklDvm+jhea5yN5302njOcned9Np4zzNx52xaKDRs2bCxQ2ARuw4YNGwsUC4nA75rrA5gjnI3nfTaeM5yd5302njPM0HkvGA/chg0bNmzkYyEpcBs2bNiwYYJN4DZs2LCxQLEgCFwIca0Q4pAQ4qgQ4nNzfTyzASFEoxDicSHEfiHEq0KIT2mPlwshHhFCHNH+L5vrY51pCCGcQoiXhBC/0L5fIYT4o3a97xdCeOb6GGcaQoiIEOLHQoiDQogDQogLFvu1FkJ8Rru39wkh7hNC+BbjtRZCfEcI0S2E2Gd6zPLaCoVvaOf/ihDinKm81rwncCGEE/g34DpgA/BOIcSGuT2qWUEa+B9Syg3ATuDj2nl+DnhUSrkaeFT7frHhU8AB0/dfBb4upVwFDAAfmJOjml38M/CwlHIdsBV1/ov2Wgsh6oFPAjuklJsAJ3ALi/Na3wNcW/BYsWt7HbBa+3cbcOdUXmjeEzhwPnBUStkipRwDfgDcNMfHNOOQUnZIKf+kfT2C+kDXo871u9rTvgu8aW6OcHYghGgA3gD8h/a9AK4Afqw9ZTGecxi4FPg2gJRyTEo5yCK/1qgRjn4hhAsIAB0swmstpXwS6C94uNi1vQn4T6nwLBARQtRO9rUWAoHXAydN37dpjy1aCCGWA9uBPwJLpJQd2o86gSVzdFizhX8C/heQ1b6vAAallGnt+8V4vVcAPcDdmnX0H0KIIIv4Wksp24E7gBMo4h4CXmTxX2sdxa7tGfHbQiDwswpCiBLgJ8CnpZTD5p9JlfO5aPI+hRBvBLqllC/O9bG8xnAB5wB3Sim3AzEK7JJFeK3LUGpzBVAHBBlvM5wVmMlruxAIvB1oNH3foD226CCEcKPI+/tSyp9qD3fpWyrt/+65Or5ZwEXAjUKI4yhr7AqUNxzRttLALWMAAAFiSURBVNmwOK93G9Ampfyj9v2PUYS+mK/1VcAxKWWPlDIF/BR1/Rf7tdZR7NqeEb8tBAJ/HlitRas9qMDHg3N8TDMOzfv9NnBASvk1048eBG7Vvr4VeOC1PrbZgpTyf0spG6SUy1HX9TEp5buAx4G3ak9bVOcMIKXsBE4KIdZqD10J7GcRX2uUdbJTCBHQ7nX9nBf1tTah2LV9EHivlo2yExgyWS0TQ0o57/8B1wOHgWbg/8z18czSOV6M2la9AuzR/l2P8oQfBY4AvwPK5/pYZ+n8Lwd+oX29EngOOAr8CPDO9fHNwvluA17QrvfPgbLFfq2BLwEHgX3AvYB3MV5r4D6Uz59C7bY+UOzaAgKVZdcM7EVl6Uz6texSehs2bNhYoFgIFooNGzZs2LCATeA2bNiwsUBhE7gNGzZsLFDYBG7Dhg0bCxQ2gduwYcPGAoVN4DZs2LCxQGETuA0bNmwsUPx/LEPfZCaXJ/kAAAAASUVORK5CYII=",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "from math import sqrt\n",
        "from sklearn.metrics import mean_absolute_error as Mae\n",
        "from sklearn.metrics import mean_squared_error as Mse\n",
        "mae = [Mae(PM_pred,PM_y),Mae(PM10_pred,PM10_y),Mae(NO2_pred,NO2_y),Mae(SO2_pred,SO2_y),Mae(O3_pred,O3_y)]\n",
        "rmse = [sqrt(Mse(PM_pred,PM_y)),sqrt(Mae(PM10_pred,PM10_y)),sqrt(Mae(NO2_pred,NO2_y)),sqrt(Mae(SO2_pred,SO2_y)),sqrt(Mae(O3_pred,O3_y))]\n",
        "ll_pred = [PM_pred,PM10_pred,NO2_pred,SO2_pred,O3_pred]\n",
        "ll_y = [PM_y,PM10_y,NO2_y,SO2_y,O3_y]\n",
        "l = [\"PM\",\"PMT\",\"NO2\",\"SO2\",\"O3\"]\n",
        "def plotting_all_data(l):\n",
        "  for i in range(0,5):\n",
        "    j = ll_y[i]\n",
        "    k = ll_pred[i]\n",
        "    plt.plot(j, color ='tab:blue',label='Actual '+l[i]) \n",
        "    plt.plot(k, color ='tab:orange', label=\"Predicted \"+l[i])\n",
        "    plt.title('Comparsion of Actual versus Predicted data in LSTM') \n",
        "    plt.legend(loc=\"upper right\")\n",
        "    plt.show()\n",
        "plotting_all_data(l)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "6aqST7rtWsYJ",
        "outputId": "5139bb9c-deb6-4e04-89bb-085d96cd5dde"
      },
      "outputs": [
        {
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>MAE</th>\n",
              "      <th>RMSE</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>PM</th>\n",
              "      <td>9.216221</td>\n",
              "      <td>11.930687</td>\n",
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              "    <tr>\n",
              "      <th>PMT</th>\n",
              "      <td>12.759925</td>\n",
              "      <td>3.572104</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>NO2</th>\n",
              "      <td>2.673244</td>\n",
              "      <td>1.635006</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SO2</th>\n",
              "      <td>4.493684</td>\n",
              "      <td>2.119831</td>\n",
              "    </tr>\n",
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              "      <th>O3</th>\n",
              "      <td>6.004746</td>\n",
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            "text/plain": [
              "           MAE       RMSE\n",
              "PM    9.216221  11.930687\n",
              "PMT  12.759925   3.572104\n",
              "NO2   2.673244   1.635006\n",
              "SO2   4.493684   2.119831\n",
              "O3    6.004746   2.450458"
            ]
          },
          "execution_count": 148,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "data = {'MAE':mae,'RMSE':rmse}\n",
        "mae_rmse_df = pd.DataFrame(data,index=l)\n",
        "mae_rmse_df"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 428
        },
        "id": "QKgOFQetZHnW",
        "outputId": "cb9ba03c-e8e1-4ce9-b5ec-93a64771ec03"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "File ‘colab_pdf.py’ already there; not retrieving.\n",
            "\n",
            "\n",
            "WARNING: apt does not have a stable CLI interface. Use with caution in scripts.\n",
            "\n",
            "\n",
            "WARNING: apt does not have a stable CLI interface. Use with caution in scripts.\n",
            "\n",
            "[NbConvertApp] Converting notebook /content/drive/MyDrive/Colab Notebooks/LSTM2.ipynb to pdf\n",
            "[NbConvertApp] Support files will be in LSTM2_files/\n",
            "[NbConvertApp] Making directory ./LSTM2_files\n",
            "[NbConvertApp] Making directory ./LSTM2_files\n",
            "[NbConvertApp] Making directory ./LSTM2_files\n",
            "[NbConvertApp] Making directory ./LSTM2_files\n",
            "[NbConvertApp] Making directory ./LSTM2_files\n",
            "[NbConvertApp] Writing 47826 bytes to ./notebook.tex\n",
            "[NbConvertApp] Building PDF\n",
            "[NbConvertApp] Running xelatex 3 times: ['xelatex', './notebook.tex', '-quiet']\n",
            "[NbConvertApp] Running bibtex 1 time: ['bibtex', './notebook']\n",
            "[NbConvertApp] WARNING | bibtex had problems, most likely because there were no citations\n",
            "[NbConvertApp] PDF successfully created\n",
            "[NbConvertApp] Writing 190205 bytes to /content/drive/My Drive/LSTM2.pdf\n"
          ]
        },
        {
          "data": {
            "application/javascript": "\n    async function download(id, filename, size) {\n      if (!google.colab.kernel.accessAllowed) {\n        return;\n      }\n      const div = document.createElement('div');\n      const label = document.createElement('label');\n      label.textContent = `Downloading \"${filename}\": `;\n      div.appendChild(label);\n      const progress = document.createElement('progress');\n      progress.max = size;\n      div.appendChild(progress);\n      document.body.appendChild(div);\n\n      const buffers = [];\n      let downloaded = 0;\n\n      const channel = await google.colab.kernel.comms.open(id);\n      // Send a message to notify the kernel that we're ready.\n      channel.send({})\n\n      for await (const message of channel.messages) {\n        // Send a message to notify the kernel that we're ready.\n        channel.send({})\n        if (message.buffers) {\n          for (const buffer of message.buffers) {\n            buffers.push(buffer);\n            downloaded += buffer.byteLength;\n            progress.value = downloaded;\n          }\n        }\n      }\n      const blob = new Blob(buffers, {type: 'application/binary'});\n      const a = document.createElement('a');\n      a.href = window.URL.createObjectURL(blob);\n      a.download = filename;\n      div.appendChild(a);\n      a.click();\n      div.remove();\n    }\n  ",
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "application/javascript": "download(\"download_24019b4f-4fe8-471b-9099-140760351a76\", \"LSTM2.pdf\", 190205)",
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'File ready to be Downloaded and Saved to Drive'"
            ]
          },
          "execution_count": 149,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "!wget -nc https://raw.githubusercontent.com/brpy/colab-pdf/master/colab_pdf.py\n",
        "from colab_pdf import colab_pdf\n",
        "colab_pdf('LSTM2.ipynb')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "NojPK2KxZKAx"
      },
      "outputs": [],
      "source": []
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}