kriging_french_temperatures-public.ipynb

{
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  {
   "cell_type": "markdown",
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   "source": [
    "# Project - Kriging the French temperatures\n",
    "\n",
    "## Some useful reading before we start\n",
    "\n",
    "**Theoretical resources**\n",
    "- [Bachelor thesis on Kriging methods](https://mediatum.ub.tum.de/1173364)\n",
    "- [Summer school tutorial on Kriging methods](https://hal.archives-ouvertes.fr/cel-01081304)\n",
    "- [Gaussian Process, not quite for dummies](https://yugeten.github.io/posts/2019/09/GP/)\n",
    "\n",
    "**Technical resources**\n",
    "- [Plotting map with cartopy](https://scitools.org.uk/cartopy/docs/v0.13/matplotlib/advanced_plotting.html)\n",
    "- [_Points in polygon_ technique](https://automating-gis-processes.github.io/2016/Lesson3-point-in-polygon.html)\n",
    "- [Draw a map with Python [FR]](http://www.xavierdupre.fr/app/papierstat/helpsphinx/notebooks/enedis_cartes.html)\n",
    "- [Plotting an static image over an interactive map (optional)](https://ocefpaf.github.io/python4oceanographers/blog/2015/07/13/interactive_geo/)\n",
    "\n",
    "## Intoduction\n",
    "\n",
    "**What we have:** the synchronized measurement of temperature $t$, from stations spread around Metropolitan France.\n",
    "\n",
    "**What we want:** a map of the temperature covering all the French Mainland, by **simple kriging** interpolation.\n",
    "\n",
    "The roadmap of the things to do is:\n",
    "1. Get the necessary data & preprocess:\n",
    "    1. Download information about station & plot on a map\n",
    "    2. Download temperature data, choose a month/year & plot a time serie\n",
    "2. Kriging, first step: fitting & choosing a model\n",
    "    1. Choose an hour/day\n",
    "    1. Create the variogram\n",
    "    2. Estimate the modeled covariance\n",
    "3. Kriging, second step: compute the simple Kriging\n",
    "    1. Krige the mean temperature & compute its variance\n",
    "    2. Create a rectangular set of coordinates which covers the MainLand\n",
    "    3. Compute Simple kriging on the zero-mean part of the signal & compute its variance\n",
    "5. Plot the kriged map\n",
    "\n",
    "## 1. Get the necessary data & preprocess\n",
    "### A. Download informations about stations & plot on map\n",
    "\n",
    "MeteoFrance partially provides open data from the *SYNOP* network:\n",
    "- link for station infos in GeoJSON [here](https://donneespubliques.meteofrance.fr/donnees_libres/Txt/Synop/postesSynop.json)\n",
    "- link for station infos in csv [here](https://donneespubliques.meteofrance.fr/donnees_libres/Txt/Synop/postesSynop.csv)\n",
    "\n",
    "First let's download this file. I go for the csv format. For the preprocessing, I keep stations on MainLand only, because kriging needs sensing nodes to be nearby."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "noble-marks",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "How the station file looks like\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Nom</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>Altitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7005</td>\n",
       "      <td>ABBEVILLE</td>\n",
       "      <td>50.136000</td>\n",
       "      <td>1.834000</td>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7015</td>\n",
       "      <td>LILLE-LESQUIN</td>\n",
       "      <td>50.570000</td>\n",
       "      <td>3.097500</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7020</td>\n",
       "      <td>PTE DE LA HAGUE</td>\n",
       "      <td>49.725167</td>\n",
       "      <td>-1.939833</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7027</td>\n",
       "      <td>CAEN-CARPIQUET</td>\n",
       "      <td>49.180000</td>\n",
       "      <td>-0.456167</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7037</td>\n",
       "      <td>ROUEN-BOOS</td>\n",
       "      <td>49.383000</td>\n",
       "      <td>1.181667</td>\n",
       "      <td>151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>7072</td>\n",
       "      <td>REIMS-PRUNAY</td>\n",
       "      <td>49.209667</td>\n",
       "      <td>4.155333</td>\n",
       "      <td>95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7110</td>\n",
       "      <td>BREST-GUIPAVAS</td>\n",
       "      <td>48.444167</td>\n",
       "      <td>-4.412000</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7117</td>\n",
       "      <td>PLOUMANAC'H</td>\n",
       "      <td>48.825833</td>\n",
       "      <td>-3.473167</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>7130</td>\n",
       "      <td>RENNES-ST JACQUES</td>\n",
       "      <td>48.068833</td>\n",
       "      <td>-1.734000</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>7139</td>\n",
       "      <td>ALENCON</td>\n",
       "      <td>48.445500</td>\n",
       "      <td>0.110167</td>\n",
       "      <td>143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>7149</td>\n",
       "      <td>ORLY</td>\n",
       "      <td>48.716833</td>\n",
       "      <td>2.384333</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>7168</td>\n",
       "      <td>TROYES-BARBEREY</td>\n",
       "      <td>48.324667</td>\n",
       "      <td>4.020000</td>\n",
       "      <td>112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>7181</td>\n",
       "      <td>NANCY-OCHEY</td>\n",
       "      <td>48.581000</td>\n",
       "      <td>5.959833</td>\n",
       "      <td>336</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>7190</td>\n",
       "      <td>STRASBOURG-ENTZHEIM</td>\n",
       "      <td>48.549500</td>\n",
       "      <td>7.640333</td>\n",
       "      <td>150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>7207</td>\n",
       "      <td>BELLE ILE-LE TALUT</td>\n",
       "      <td>47.294333</td>\n",
       "      <td>-3.218333</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>7222</td>\n",
       "      <td>NANTES-BOUGUENAIS</td>\n",
       "      <td>47.150000</td>\n",
       "      <td>-1.608833</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>7240</td>\n",
       "      <td>TOURS</td>\n",
       "      <td>47.444500</td>\n",
       "      <td>0.727333</td>\n",
       "      <td>108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>7255</td>\n",
       "      <td>BOURGES</td>\n",
       "      <td>47.059167</td>\n",
       "      <td>2.359833</td>\n",
       "      <td>161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>7280</td>\n",
       "      <td>DIJON-LONGVIC</td>\n",
       "      <td>47.267833</td>\n",
       "      <td>5.088333</td>\n",
       "      <td>219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>7299</td>\n",
       "      <td>BALE-MULHOUSE</td>\n",
       "      <td>47.614333</td>\n",
       "      <td>7.510000</td>\n",
       "      <td>263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>7314</td>\n",
       "      <td>PTE DE CHASSIRON</td>\n",
       "      <td>46.046833</td>\n",
       "      <td>-1.411500</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>7335</td>\n",
       "      <td>POITIERS-BIARD</td>\n",
       "      <td>46.593833</td>\n",
       "      <td>0.314333</td>\n",
       "      <td>123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>7434</td>\n",
       "      <td>LIMOGES-BELLEGARDE</td>\n",
       "      <td>45.861167</td>\n",
       "      <td>1.175000</td>\n",
       "      <td>402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>7460</td>\n",
       "      <td>CLERMONT-FD</td>\n",
       "      <td>45.786833</td>\n",
       "      <td>3.149333</td>\n",
       "      <td>331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>7471</td>\n",
       "      <td>LE PUY-LOUDES</td>\n",
       "      <td>45.074500</td>\n",
       "      <td>3.764000</td>\n",
       "      <td>833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>7481</td>\n",
       "      <td>LYON-ST EXUPERY</td>\n",
       "      <td>45.726500</td>\n",
       "      <td>5.077833</td>\n",
       "      <td>235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>7510</td>\n",
       "      <td>BORDEAUX-MERIGNAC</td>\n",
       "      <td>44.830667</td>\n",
       "      <td>-0.691333</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>7535</td>\n",
       "      <td>GOURDON</td>\n",
       "      <td>44.745000</td>\n",
       "      <td>1.396667</td>\n",
       "      <td>260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>7558</td>\n",
       "      <td>MILLAU</td>\n",
       "      <td>44.118500</td>\n",
       "      <td>3.019500</td>\n",
       "      <td>712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>7577</td>\n",
       "      <td>MONTELIMAR</td>\n",
       "      <td>44.581167</td>\n",
       "      <td>4.733000</td>\n",
       "      <td>73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>7591</td>\n",
       "      <td>EMBRUN</td>\n",
       "      <td>44.565667</td>\n",
       "      <td>6.502333</td>\n",
       "      <td>871</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>7607</td>\n",
       "      <td>MONT-DE-MARSAN</td>\n",
       "      <td>43.909833</td>\n",
       "      <td>-0.500167</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>7621</td>\n",
       "      <td>TARBES-OSSUN</td>\n",
       "      <td>43.188000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>7627</td>\n",
       "      <td>ST GIRONS</td>\n",
       "      <td>43.005333</td>\n",
       "      <td>1.106833</td>\n",
       "      <td>414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>7630</td>\n",
       "      <td>TOULOUSE-BLAGNAC</td>\n",
       "      <td>43.621000</td>\n",
       "      <td>1.378833</td>\n",
       "      <td>151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>7643</td>\n",
       "      <td>MONTPELLIER</td>\n",
       "      <td>43.577000</td>\n",
       "      <td>3.963167</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>7650</td>\n",
       "      <td>MARIGNANE</td>\n",
       "      <td>43.437667</td>\n",
       "      <td>5.216000</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>7661</td>\n",
       "      <td>CAP CEPET</td>\n",
       "      <td>43.079333</td>\n",
       "      <td>5.940833</td>\n",
       "      <td>115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>7690</td>\n",
       "      <td>NICE</td>\n",
       "      <td>43.648833</td>\n",
       "      <td>7.209000</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>7747</td>\n",
       "      <td>PERPIGNAN</td>\n",
       "      <td>42.737167</td>\n",
       "      <td>2.872833</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      ID                  Nom   Latitude  Longitude  Altitude\n",
       "0   7005            ABBEVILLE  50.136000   1.834000        69\n",
       "1   7015        LILLE-LESQUIN  50.570000   3.097500        47\n",
       "2   7020      PTE DE LA HAGUE  49.725167  -1.939833         6\n",
       "3   7027       CAEN-CARPIQUET  49.180000  -0.456167        67\n",
       "4   7037           ROUEN-BOOS  49.383000   1.181667       151\n",
       "5   7072         REIMS-PRUNAY  49.209667   4.155333        95\n",
       "6   7110       BREST-GUIPAVAS  48.444167  -4.412000        94\n",
       "7   7117          PLOUMANAC'H  48.825833  -3.473167        55\n",
       "8   7130    RENNES-ST JACQUES  48.068833  -1.734000        36\n",
       "9   7139              ALENCON  48.445500   0.110167       143\n",
       "10  7149                 ORLY  48.716833   2.384333        89\n",
       "11  7168      TROYES-BARBEREY  48.324667   4.020000       112\n",
       "12  7181          NANCY-OCHEY  48.581000   5.959833       336\n",
       "13  7190  STRASBOURG-ENTZHEIM  48.549500   7.640333       150\n",
       "14  7207   BELLE ILE-LE TALUT  47.294333  -3.218333        34\n",
       "15  7222    NANTES-BOUGUENAIS  47.150000  -1.608833        26\n",
       "16  7240                TOURS  47.444500   0.727333       108\n",
       "17  7255              BOURGES  47.059167   2.359833       161\n",
       "18  7280        DIJON-LONGVIC  47.267833   5.088333       219\n",
       "19  7299        BALE-MULHOUSE  47.614333   7.510000       263\n",
       "20  7314     PTE DE CHASSIRON  46.046833  -1.411500        11\n",
       "21  7335       POITIERS-BIARD  46.593833   0.314333       123\n",
       "22  7434   LIMOGES-BELLEGARDE  45.861167   1.175000       402\n",
       "23  7460          CLERMONT-FD  45.786833   3.149333       331\n",
       "24  7471        LE PUY-LOUDES  45.074500   3.764000       833\n",
       "25  7481      LYON-ST EXUPERY  45.726500   5.077833       235\n",
       "26  7510    BORDEAUX-MERIGNAC  44.830667  -0.691333        47\n",
       "27  7535              GOURDON  44.745000   1.396667       260\n",
       "28  7558               MILLAU  44.118500   3.019500       712\n",
       "29  7577           MONTELIMAR  44.581167   4.733000        73\n",
       "30  7591               EMBRUN  44.565667   6.502333       871\n",
       "31  7607       MONT-DE-MARSAN  43.909833  -0.500167        59\n",
       "32  7621         TARBES-OSSUN  43.188000   0.000000       360\n",
       "33  7627            ST GIRONS  43.005333   1.106833       414\n",
       "34  7630     TOULOUSE-BLAGNAC  43.621000   1.378833       151\n",
       "35  7643          MONTPELLIER  43.577000   3.963167         2\n",
       "36  7650            MARIGNANE  43.437667   5.216000         9\n",
       "37  7661            CAP CEPET  43.079333   5.940833       115\n",
       "38  7690                 NICE  43.648833   7.209000         2\n",
       "39  7747            PERPIGNAN  42.737167   2.872833        42"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import os\n",
    "import requests\n",
    "import pandas\n",
    "\n",
    "fname_stations = \"file_stations.csv\"\n",
    "url_stations = \"https://donneespubliques.meteofrance.fr/donnees_libres/Txt/Synop/postesSynop.csv\"\n",
    "\n",
    "if os.path.exists(fname_stations) is False:\n",
    "    with open(fname_stations, \"wb\") as fid:\n",
    "        file_stations = requests.get(url_stations)\n",
    "        fid.write(file_stations.content)\n",
    "\n",
    "fpd_st = pandas.read_csv(\"file_stations.csv\", delimiter=\";\")\n",
    "fpd_st = fpd_st[0:40]  # Mainland only\n",
    "\n",
    "print(\"How the station file looks like\")\n",
    "fpd_st"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "loose-guest",
   "metadata": {},
   "source": [
    "Let's visualize stations on a map with folium. We also prepare the rectangular bound in which the map will be computed later."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "collectible-credits",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe src=\"about:blank\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" 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onload=\"this.contentDocument.open();this.contentDocument.write(    decodeURIComponent(this.getAttribute('data-html')));this.contentDocument.close();\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x13824022a60>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import folium\n",
    "\n",
    "mapf = folium.Map(location=(47, 2), zoom_start=5)\n",
    "for _, station in fpd_st.iterrows():\n",
    "    marker = folium.Marker(location=(station.Latitude, station.Longitude),\n",
    "                                     weight=1, color=\"Green\",\n",
    "                                     tooltip=f\"{station.Nom.title()} | {station.ID}\")\n",
    "    marker.add_to(mapf)\n",
    "\n",
    "bound_map = ((42.3, -5), (51.1, 8.3))\n",
    "rect = folium.Rectangle(bound_map, color=\"Gray\",\n",
    "                        tooltip=\"Bounds for the temperature map to come\")\n",
    "rect.add_to(mapf)\n",
    "\n",
    "mapf"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "endangered-focus",
   "metadata": {},
   "source": [
    "### B. Download temperature data, choose a month/year & plot a time serie\n",
    "\n",
    "For the download:\n",
    "- we use the archive link of a température file. With MM the month and AAAA the year, the url is\n",
    "https://donneespubliques.meteofrance.fr/donnees_libres/Txt/Synop/Archive/synop.AAAAMM.csv.gz\n",
    "- I manage to find a year/month/day/hour in which there is no Nan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "adopted-agency",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Datatypes of the dataframe\n",
      "numer_sta      int64\n",
      "date           int64\n",
      "t            float64\n",
      "dtype: object\n",
      "How the dataframe looks like\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>numer_sta</th>\n",
       "      <th>date</th>\n",
       "      <th>t</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7005</td>\n",
       "      <td>20200101000000</td>\n",
       "      <td>274.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7015</td>\n",
       "      <td>20200101000000</td>\n",
       "      <td>275.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7020</td>\n",
       "      <td>20200101000000</td>\n",
       "      <td>280.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7027</td>\n",
       "      <td>20200101000000</td>\n",
       "      <td>275.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7037</td>\n",
       "      <td>20200101000000</td>\n",
       "      <td>272.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14809</th>\n",
       "      <td>7643</td>\n",
       "      <td>20200131210000</td>\n",
       "      <td>285.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14810</th>\n",
       "      <td>7650</td>\n",
       "      <td>20200131210000</td>\n",
       "      <td>282.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14811</th>\n",
       "      <td>7661</td>\n",
       "      <td>20200131210000</td>\n",
       "      <td>283.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14812</th>\n",
       "      <td>7690</td>\n",
       "      <td>20200131210000</td>\n",
       "      <td>286.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14813</th>\n",
       "      <td>7747</td>\n",
       "      <td>20200131210000</td>\n",
       "      <td>283.85</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9897 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       numer_sta            date       t\n",
       "0           7005  20200101000000  274.35\n",
       "1           7015  20200101000000  275.25\n",
       "2           7020  20200101000000  280.55\n",
       "3           7027  20200101000000  275.75\n",
       "4           7037  20200101000000  272.25\n",
       "...          ...             ...     ...\n",
       "14809       7643  20200131210000  285.95\n",
       "14810       7650  20200131210000  282.75\n",
       "14811       7661  20200131210000  283.65\n",
       "14812       7690  20200131210000  286.65\n",
       "14813       7747  20200131210000  283.85\n",
       "\n",
       "[9897 rows x 3 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import gzip\n",
    "\n",
    "year, month = \"2020\", \"01\"\n",
    "\n",
    "url_temp = \"https://donneespubliques.meteofrance.fr/donnees_libres/Txt/Synop/Archive/synop.{}{}.csv.gz\".format(year, month)\n",
    "fname_temp_end = url_temp.split(\"/\")[-1].replace(\"csv.gz\", \"csv\")  # calling gzip is not necessary (why...)\n",
    "fname_temp = \"file_{}\".format(fname_temp_end)\n",
    "\n",
    "if os.path.exists(fname_temp) is False:\n",
    "    zipped_content = requests.get(url_temp).content\n",
    "    with open(fname_temp, \"wb\") as fid:\n",
    "            fid.write(gzip.decompress(zipped_content))\n",
    "\n",
    "\n",
    "fpd_tp = pandas.read_csv(fname_temp, delimiter=\";\")\n",
    "\n",
    "# Preprocessing: drop useless data, cast to numeric datatypes\n",
    "fpd_tp = fpd_tp[[\"numer_sta\", \"date\", \"t\"]]  # keep useful columns\n",
    "fpd_tp = fpd_tp[fpd_tp[\"numer_sta\"].isin(fpd_st.ID)]  # keep metropolitan stations\n",
    "fpd_tp = fpd_tp.replace({\"mq\": \"nan\"})  # replace mq by nan\n",
    "fpd_tp = fpd_tp.astype({\"t\": float})  # convert temperatures to float\n",
    "\n",
    "print(\"Datatypes of the dataframe\")\n",
    "print(fpd_tp.dtypes, sep=\"\")\n",
    "print(\"How the dataframe looks like\")\n",
    "\n",
    "fpd_tp"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "rolled-integer",
   "metadata": {},
   "source": [
    "For vizualization, I take the time serie from Toulouse. Note that the measured temperature is in Kelvin."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "thermal-reset",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "const_k2c = 273.15  # to convert Kelvin to Celsius\n",
    "name_tls = \"TOULOUSE-BLAGNAC\"\n",
    "id_tls = int(fpd_st.ID[fpd_st.Nom == name_tls])\n",
    "fpd_tls = fpd_tp[fpd_tp.numer_sta == id_tls]  # data toulouse\n",
    "time_formatted = pandas.to_datetime(fpd_tls.date, format=\"%Y%m%d%H%M%S\")\n",
    "\n",
    "plt.figure(figsize=(12, 5))\n",
    "plt.plot(time_formatted, fpd_tls.t - const_k2c, \"-o\",\n",
    "         color=\"RoyalBlue\", linewidth=2, markersize=4)\n",
    "plt.title(f\"Temperature at {name_tls.title()} [°C]\")\n",
    "plt.margins(x=0)\n",
    "plt.grid()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "written-imaging",
   "metadata": {},
   "source": [
    "## 2. Kriging, first step: fitting & choosing a model\n",
    "\n",
    "From that point, if you want to understand how to do simple Kriging, you should definitely read the Chapter 6 of [Andreas Lichtenstern's Bachelor thesis](https://mediatum.ub.tum.de/doc/1173364/1173364.pdf).\n",
    "\n",
    "### A. Choose an hour/day\n",
    "We will focus on the synchronized measurements at the following time. Watch out, there are data every 3 hours only (00am, 3am, 6am, etc.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "liked-investing",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "20200101030000\n",
      "number of Nans at chosen date: 0\n"
     ]
    }
   ],
   "source": [
    "year, month, day, hour = year, month, \"01\", \"03\" # 2020-01-01 @03:00 am\n",
    "\n",
    "date = int(\"\".join((year, month, day, hour, \"00\", \"00\"))) #AAAAMMDDHHMMSS  \n",
    "print(date)\n",
    "temp = fpd_tp[fpd_tp.date == date]\n",
    "print(\"number of Nans at chosen date:\", np.sum(np.isnan(temp.t.values)))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "trained-continent",
   "metadata": {},
   "source": [
    "### B. Create a variogram\n",
    "To create the variogram we need:\n",
    "- the paiwise distances between stations $d_{ij} = \\| \\mathbf{x}_i - \\mathbf{x}_j \\|$, based on (latitude, longitude) coordinates. For accuracy, we compute the distances of arcs on the sphere rather than Euclidean distances.\n",
    "- raw values of the variogram $\\dfrac{\\left(t(\\mathbf{x}_i) - t(\\mathbf{x}_j)\\right)^2}{2}$, as a fonction of $d_{ij}$\n",
    "- the binned means of the variogram\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "expired-estonia",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x138282b2490>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "from scipy.spatial.distance import squareform\n",
    "from scipy.stats import binned_statistic\n",
    "import pymap3d\n",
    "\n",
    "# Compute the pairwise distances\n",
    "lats_st = fpd_st.Latitude.to_numpy()\n",
    "lons_st = fpd_st.Longitude.to_numpy()\n",
    "pdist = np.zeros((lats_st.size, lats_st.size))\n",
    "for i in range(lats_st.size):\n",
    "    for j in range(i):\n",
    "        pdist[i, j] = pymap3d.vincenty.vdist(lats_st[i], lons_st[i], lats_st[j], lons_st[j])[0]\n",
    "        pdist[j, i] = pdist[i, j]\n",
    "        \n",
    "# Compute the raw variogram values\n",
    "dissim = np.abs(temp[\"t\"].values[:, None] - temp[\"t\"].values[None, :])**2 / 2\n",
    "dissim_ = squareform(dissim)\n",
    "pdist_ = squareform(pdist)\n",
    "\n",
    "# Create a binned variogram\n",
    "variogram, edges, _ = binned_statistic(pdist_, dissim_,\n",
    "                                       statistic='mean', bins=20)\n",
    "dist_binned = edges[:-1] + (edges[1] - edges[0])/2\n",
    "plt.figure(figsize=(8, 4))\n",
    "plt.title(\"Variogram\")\n",
    "plt.plot(squareform(pdist)/1e3, squareform(dissim), \".\", markersize=1, label=\"raw variogram\")\n",
    "plt.xlabel(\"distance [km]\")\n",
    "plt.ylabel(r\"dissimilarity [K$^2$]\")    \n",
    "plt.scatter(dist_binned/1e3, variogram,\n",
    "            marker=\"*\", color=\"black\", label=\"binned variogram\")\n",
    "plt.xlabel(\"distance [km]\")\n",
    "plt.ylabel(r\"dissimilarity [K$^2$]\")\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "loving-repair",
   "metadata": {},
   "source": [
    "### C. Estimate the modeled covariance \n",
    "\n",
    "Finally, fit the binned variogram to the gaussian covariance model. If the gaussian covariance $C_{ij}$ is such that\n",
    "\n",
    "$$C_{ij} = b e^{- \\frac{d_{ij}^2}{2 a^2}} \\text{ ,}$$\n",
    "\n",
    "then the variogram $\\gamma_{ij}$ has the analytical form: \n",
    "\n",
    "$$\\gamma_{ij} = b \\left(1 - e^{- \\frac{d_{ij}^2}{2 a^2}} \\right)$$\n",
    "\n",
    "*Tips*: note that there are outliers, so:\n",
    "- use a robust loss function (e.g. $\\ell_1$ or huber, rather than $\\ell_2$ least-square)\n",
    "- weight the cost function by the number of samples per bin"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "sharing-bruce",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitted parameters with linear metric:\t a=258269.433304702 \t b=28.2710305114871\n",
      "Fitted parameters with huber metric:\t a=234637.337515012 \t b=27.000911357401638\n",
      "Fitted parameters with soft_l1 metric:\t a=234654.89510158176 \t b=27.00187003580491\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from scipy import optimize\n",
    "\n",
    "def covariance_gaussian(h, a, b):\n",
    "    return b*np.exp(-h**2 / (2*a**2))\n",
    "\n",
    "def variogram_gaussian(h, a, b):\n",
    "    return b*(1 - np.exp(-h**2 / (2*a**2)))\n",
    "\n",
    "def residual_variogram_gaussian(arr, variogram_data, variogram_dist,\n",
    "                                weight_res=None):\n",
    "    a, b = arr\n",
    "    res =  variogram_gaussian(variogram_dist, a, b) - variogram_data\n",
    "    if weight_res is None:\n",
    "        return res\n",
    "    else:\n",
    "        return weight_res * res\n",
    "\n",
    "# For fitting, I weight the data by the number of points in each bin:\n",
    "weight_res = np.histogram(squareform(pdist), bins=edges)[0].astype(float)\n",
    "# ...or not:\n",
    "#weight_res = None\n",
    "\n",
    "# Fitting here\n",
    "res_fit = {}\n",
    "metrics = [\"linear\", \"huber\", \"soft_l1\"]\n",
    "for metric_ in metrics:  # linear, soft_l1, huber, cauchy, arctan\n",
    "    res = optimize.least_squares(residual_variogram_gaussian, [300e3, 60],\n",
    "                                 bounds=([0., 0.], [np.inf, np.inf]),\n",
    "                                 loss=metric_,\n",
    "                                 args=[variogram, dist_binned, weight_res])\n",
    "    res_fit[metric_] = res\n",
    "\n",
    "plt.figure(figsize=(8, 4))\n",
    "plt.title(\"Variogram fitting\")\n",
    "plt.scatter(dist_binned/1e3, variogram,\n",
    "            s=weight_res,\n",
    "            marker=\"*\", color=\"black\", label=\"data\")\n",
    "for metric_, res_ in res_fit.items():\n",
    "    plt.plot(dist_binned/1e3, variogram_gaussian(dist_binned, *res_.x), \"--\", label=metric_)\n",
    "plt.grid()\n",
    "plt.ylim(ymin=0)\n",
    "plt.margins(x=1e-3)\n",
    "plt.xlabel(\"distance [km]\")\n",
    "plt.ylabel(r\"dissimilarity [K$^2$]\")\n",
    "plt.legend()\n",
    "\n",
    "for metric_, res_ in res_fit.items():\n",
    "    print(f\"Fitted parameters with {metric_} metric:\\t a={res_.x[0]} \\t b={res_.x[1]}\", )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "facial-anthony",
   "metadata": {},
   "source": [
    "Now we have $a$ and $b$ from fitting (by soft_l1), we can build the _learned_ covariance matrix."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "canadian-south",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "covariance condition number is 1248280.667782543\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x13828420af0>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "a_learned, b_learned = res_fit[\"soft_l1\"].x\n",
    "cov_learned = b_learned * np.exp(-pdist**2 / (2*a_learned**2))\n",
    "\n",
    "# Check the condition number before using cov_learned, as it will be\n",
    "# inversed the covariance matrix\n",
    "print(\"covariance condition number is\", np.linalg.cond(cov_learned))\n",
    "cov_learned_inv = np.linalg.pinv(cov_learned)  # \n",
    "\n",
    "plt.figure()\n",
    "plt.title(\"Covariance matrix at sensing points\")\n",
    "plt.imshow(cov_learned, vmin=0)\n",
    "plt.colorbar()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "functional-thomas",
   "metadata": {},
   "source": [
    "## 3. Kriging, second step: compute the simple Kriging\n",
    "### A. Krige the mean temperature & compute its variance\n",
    "\n",
    "Krige the mean, compute the variance, and compare with vanilla mean & variance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "satisfied-vacuum",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Temperature \t Mean [°C] \t\t Variance [°C²]\n",
      "Kriged  \t 10.822046005665129  \t 4.538199992829337\n",
      "Vanilla \t 3.2349999999999 \t 19.381820512820493\n"
     ]
    }
   ],
   "source": [
    "ones_ = np.ones(temp.shape[0])\n",
    "weights_mean = cov_learned_inv @ ones_ / cov_learned_inv.sum()\n",
    "\n",
    "mean_krig = temp.t.values @ weights_mean\n",
    "var_mean_krig = 1 / cov_learned_inv.sum()\n",
    "\n",
    "print(\"Temperature \\t Mean [°C] \\t\\t Variance [°C²]\")\n",
    "print(\"Kriged  \\t\", mean_krig - const_k2c, \" \\t {}\".format(var_mean_krig))\n",
    "print(\"Vanilla \\t\", temp.t.mean() - const_k2c, \"\\t {}\".format(temp.t.var()))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "developmental-communist",
   "metadata": {},
   "source": [
    "### B. Create a rectangular set of coordinates which covers the MainLand\n",
    "\n",
    "1. We create a set of interpolation points covering the Mainland (using the bounds defined in part 1.A.)\n",
    "2. Then we ompute the pairwise distances between interpolation and sensing points. For accuracy, we compute the distances of arcs on the sphere rather than Euclidean distances."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "bacterial-lingerie",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████████████████████████████████████████████████████████████████████████████| 40/40 [00:47<00:00,  1.20s/it]\n"
     ]
    }
   ],
   "source": [
    "from tqdm import tqdm\n",
    "\n",
    "# Create points for interpolation\n",
    "n_width = 100  # Takes time if n_width > 50...\n",
    "lat_map_uni = np.linspace(bound_map[0][0], bound_map[1][0], n_width)\n",
    "lon_map_uni = np.linspace(bound_map[0][1], bound_map[1][1], n_width)\n",
    "lat_map, lon_map = np.meshgrid(lat_map_uni, lon_map_uni)\n",
    "lat_map_ = lat_map.ravel()\n",
    "lon_map_ = lon_map.ravel()\n",
    "\n",
    "# Create the matrix of parwise distances between latitudes. It takes some time...\n",
    "rdist = np.zeros((lats_st.size, lat_map_.size))\n",
    "for i in tqdm(range(lats_st.size)):\n",
    "    for j in range(lat_map_.size):\n",
    "        rdist[i, j] = pymap3d.vincenty.vdist(lats_st[i], lons_st[i], lat_map_[j], lon_map_[j])[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "offensive-paste",
   "metadata": {},
   "source": [
    "### C. Compute Simple kriging on the zero-mean part of the signal & compute its variance\n",
    "Here we **do the simple kriging** (finally !), and interpolate the part of the signal fluctuating around the mean."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "destroyed-benefit",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Compute the gaussian covariance model\n",
    "cov_krig_meas = covariance_gaussian(rdist, a_learned, b_learned)\n",
    "\n",
    "# Do interpolation by simple kriging\n",
    "weights_sk = cov_learned_inv @ cov_krig_meas\n",
    "temp_sk = mean_krig + (temp.t.values - mean_krig) @ weights_sk\n",
    "var_sk = cov_learned[0, 0] - (cov_krig_meas * weights_sk).sum(axis=0)  # hypothesis : cov_learned diagonal elements are equal."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ecological-wheat",
   "metadata": {},
   "source": [
    "## 4. Plot the kriged map\n",
    "\n",
    "Since folium does not natively handles map vizualisation, I switch to cartopy. I vizualize both kriging and variance, and use either pcolor or contourf for the aspect."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "successful-adobe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x360 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import cartopy.crs as ccrs\n",
    "import cartopy.feature as cfeature\n",
    "\n",
    "map_temp_sk = temp_sk.reshape((n_width, n_width))\n",
    "map_var_sk = var_sk.reshape((n_width, n_width))\n",
    "\n",
    "map_type = \"pcolor\"  # map style of kriging (expectation)\n",
    "fig = plt.figure(figsize=(14, 5))\n",
    "\n",
    "# Kriging - Excpectation\n",
    "temp_sk_min = 5*np.floor((temp.t.min() - const_k2c)/5)\n",
    "temp_sk_max = 5*np.ceil((temp.t.max() - const_k2c)/5)\n",
    "ax = fig.add_subplot(121, projection=ccrs.PlateCarree())\n",
    "if map_type == \"pcolor\":\n",
    "    im = ax.pcolormesh(lon_map_uni, lat_map_uni, (map_temp_sk - const_k2c).T,\n",
    "                      vmin=temp_sk_min, vmax=temp_sk_max, cmap=\"jet\")\n",
    "elif map_type == \"contourf\":\n",
    "    levels = np.arange(temp_sk_min, temp_sk_max+1e-6, 1)\n",
    "    im = ax.contourf(lon_map_uni, lat_map_uni, (map_temp_sk - const_k2c).T,\n",
    "                     levels=levels,\n",
    "                     extend=\"min\",\n",
    "                     cmap=\"jet\")\n",
    "ax.scatter(lons_st, lats_st, c=temp.t.values - const_k2c,\n",
    "           cmap='jet', edgecolor=\"black\",\n",
    "           vmin=im.get_clim()[0], vmax=im.get_clim()[1])\n",
    "plt.colorbar(im)\n",
    "ax.margins(0)\n",
    "ax.add_feature(cfeature.BORDERS.with_scale('50m'), linestyle=':')\n",
    "ax.coastlines()\n",
    "ax.set_title(\"Simple kriging - temperature [°C]\")\n",
    "ax.set_aspect(\"auto\")\n",
    "\n",
    "# Kriging - Variance\n",
    "ax = fig.add_subplot(122, projection=ccrs.PlateCarree())\n",
    "im = ax.pcolormesh(lon_map_uni, lat_map_uni, (map_var_sk**0.5).T,\n",
    "                  vmin=0, vmax=0.3, cmap=\"magma\")\n",
    "ax.scatter(lons_st, lats_st, edgecolor=\"white\", facecolor=\"none\")\n",
    "plt.colorbar(im)\n",
    "ax.margins(0)\n",
    "ax.add_feature(cfeature.BORDERS.with_scale('50m'), linestyle=':')\n",
    "ax.coastlines()\n",
    "ax.set_title(\"Simple kriging - standard deviation  [°C]\")\n",
    "ax.set_aspect(\"auto\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fuzzy-apollo",
   "metadata": {},
   "source": [
    "### Mask the values so that the map convers the French MainLand only\n",
    "\n",
    "The temperature map provides inconsistent values beyond the Mainland. The idea here is to _crop_ the map and draw only the values of interest.\n",
    "\n",
    "From the polygons created by [Grégoire David](https://github.com/gregoiredavid/france-geojson), I subsampled the French Mainland one and saved it into `file_polygon_mainland_France.npy`. Based on the intersection of this polygon and the set of interpolated points, we can finally crop the previous map and plot only the useful part. To do so, the \"point in polygon\" algorithm helps to find the interpolation points which are inside the polygon."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "spread-casting",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/svg+xml": [
       "<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"100.0\" height=\"100.0\" viewBox=\"-5.315615636781656 41.83452079904054 14.059057492774874 9.77458733912831\" preserveAspectRatio=\"xMinYMin meet\"><g transform=\"matrix(1,0,0,-1,0,93.44362893720938)\"><path fill-rule=\"evenodd\" fill=\"#66cc99\" stroke=\"#555555\" stroke-width=\"0.28118114985549747\" opacity=\"0.6\" d=\"M 7.130345969302944,47.50302658239207 L 5.956063159932633,46.13208943594269 L 6.806217638297463,46.38037206259825 L 7.043890107046439,45.92361818207322 L 6.808418511070923,45.72515343860933 L 7.1842747748936695,45.407480631519924 L 6.627487761756953,45.10121505030452 L 7.06578600052752,44.71360743394211 L 7.008054894297459,44.236431060527 L 7.68458536705161,44.17401845696774 L 7.530159376168468,43.78804906400435 L 6.157072005051721,43.0283622233928 L 4.011185334395634,43.552446652511314 L 3.092876973759121,43.06914228496683 L 3.1741805499682005,42.435585934319825 L 2.02349649688789,42.35522663210627 L 0.708377779630982,42.86140184526933 L -0.5512049085825593,42.77751593074885 L -1.7297463174854624,43.295677171644435 L -1.0167859243981427,44.64936614924531 L -1.262052894231634,44.63219970212472 L -1.0911993078778204,45.56240962499771 L -0.803863792011378,45.3483837452359 L -0.6827151048736609,45.07868957712152 L -0.5906665446401641,45.041946989301174 L -0.80169109465095,45.45953126528613 L -1.2372284214926077,45.705896325440406 L -1.129404177492153,46.31027691915601 L -1.8136695999589263,46.49534718792214 L -2.466145152823908,47.51170094995204 L -4.362405222202317,47.79574452412905 L -4.716343505589336,48.06246408637442 L -4.223087545336637,48.296299071102354 L -4.79490980371592,48.41306522400434 L -3.2197192609615692,48.86646505727847 L -2.698438421518125,48.50568354123005 L -1.443640368193959,48.62752557033798 L -1.942245186733018,49.72555529334811 L -0.0005074304791027337,49.32556281264521 L 0.33898282435946164,49.440931306061266 L 0.06955005489894274,49.50639804169097 L 0.1916018630620729,49.70633817691035 L 1.6837994282613178,50.18302974967859 L 1.5835458071046016,50.87182012003101 L 2.5463252972819905,51.088402305103116 L 2.813275390169948,50.716947630173586 L 4.207538662540225,50.27297040073831 L 4.195936343936246,49.955694802056996 L 4.879565525415205,50.15202955288437 L 4.855382632112906,49.79236512744182 L 5.470910130592771,49.49720502129504 L 8.222736022927482,48.97597079725059 L 7.577312855212316,48.12036852180279 L 7.5847059048213925,47.57726432341283 L 7.130345969302944,47.50302658239207 z\" /></g></svg>"
      ],
      "text/plain": [
       "<shapely.geometry.polygon.Polygon at 0x13828447e50>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from shapely.geometry import Point, Polygon\n",
    "\n",
    "lonlat_poly = np.load(\"file_polygon_mainland_France.npy\")\n",
    "poly = Polygon(lonlat_poly.T)  # create a Polygon\n",
    "\n",
    "# create Point objects\n",
    "point_collection = [Point(lon_, lat_)\n",
    "                    for (lon_, lat_) in zip(lon_map_, lat_map_)]\n",
    "\n",
    "# create the mask with the point-in-polygon algorithm\n",
    "mask = np.array([p.within(poly) for p in point_collection])\n",
    "poly  # visualize the polygon"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "inside-crown",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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w/fotmjZtwNKla+nWrT0uLs4ZtCKT04lfBnV7im0Lk/w9C10aXYPqpofJBTrwzjXyeRfCzcUxcVshH08K+Ri15rqMTKYJC4/mzIXb1K1ZNjFS4+xkDwKEQYtSZQ6VKpZdq+dzZOdKChQqTL/+fXh37Y+4u6U/mjc9YRbXbyd7L90MJJ8k0aNmSdzW/UxE77EmsV3GcFat2si4cUNxddVFPWrVqkatWtVQq9XcvfsApVJpYQtlchsmF+iT+9fTo08flEr5CT+7uHXnCTExcVSp6G9pUyzO7Lmr+fHbb/H0LkTIyyAq16xHmzYt6NqhEd6FihB4/zolytUw2fFUcTHM+2wwHh6urF67mLo1SqdbPrOinJTQ6DiKhAs0t8Nw/GY60VOmGW+4TKYIDHzKjz9+pXd6m42NDdOmTSA4+BVff/0DX331iRzhkDEJJv8WBd69RoN61UzdrEw6LPpnM00btSZfvjJcvZlqOeQ8gVYr8dHHP/Hnb4v4dO5WPl+4l6/+OkzFuu3ZufsojRq2x87eCScXd9MdU6NhxS+fkt87H9s3zktXnN3UF9MUZ3H9djJxlm4GJhNn1c1QVDdDOX30Psuv3QMgOMBkaadlDGDixOlcupRmPgkAPDzcqVq1YjZZJJMXMLkHHRn+Gt+C+TIuKGMyZn85lIrlSzJm+HAa1WtJmy59+HHW+DzTrRDyOoL3R37NnYAAJszZgKu7FwAubp7UbdGdui26I0mSyZJ7hIcGs/rXz7hx4Sgly1Zi07p5aUaM0hPlpKT0llU3Q1PVqRznT2Vff17clpCHcWQPDx8G4uHhzrJlv2boFSuVSmrUqJJNlsnkBUwu0Hb2jkRGxZm6WZkMGNyvNVUr7+atVp3Zt30jnW/dZPeOxYkD9WJjVezcf5Znz18hhODt3i25euMBd+49pbCfN7Wrl8bO1nqyZ6WFVivxIPA5x05d49z5a1y5fI0r509QpW4rxsxchb2D/n5fU2beOrJjBVpVBEeObsO/SIFU+7MSxtYnzEm95eMvn7LywU0m+HehXGYNl8k0a9ZsplixwvTq1TnDslqtlg8+GM+WLctwdpaziclkHTMItAORUfKiQ5agWqXi7Ny9ie7dBhH44A7Vqreidfsu/PjtGHbuO80H77yLj18Jnj2+y+HDA9i/ezv5vP148fQBMVHhLF21nI5t6mTJhtt3n7Ji7W6iomLw9HQnIOAeVaqUp1+PFnh7uRnV5qWr9/lr6WYuXrjE3VtX0Wq0FCtdicIlKlKlYRe6f/g17vl8smR3ZijgW5xHt86mEmdDhTmzopzAw2B3fHBlUCG/zJosYyQTJgw3uKwum9gGM1ojk9cwuUArlDZERaWXa1zGnNSoUpI///6Vfr0GMP7nLWxb8SPVarbl+x9mMmnaV8ya/hme+Qvx8mUwDVr35sDWf1DFxuDq4cXAvgP4avYcRr6v31vQaiWOnLzGzdup+7nvP3jMrh27CHr8gKr1WmFra0/46ysULVONjZv2MHP6l1SoWptOndrQv1dLCuQ3rC/4mx9WMG/O9zRs05t6bQbSa3hFPPMXsmgu6go1m7D054mER8Tg6qITUn3inFlvOS1RToqNUBChKsjCe7uoVusZE8/IA8XMSUDAPT7/fBYrVizMsOyaNf/i51eQhg3TTa8sI2MwJhXooEcBPHlwi0b1KpmyWRkDiIqOxc9Xd90VShsq1WqKZwFfhnw8l4vHdzN6xFjqNWkOQH6fQlw6e5LI8J2J9Ws27siRHSshXviiomO5cTuQsqUKs3XXSbZs28exg/uxtXOgSIkKqQTS2c2TDgMmUKZKPZQ2tqnsi44K5/LJffy7dTuzvvqK8lVr0ax5Y3wLedOxTX0KFvBIVl6rlZj85R8s/fM3PvlpMz6FrSe/saOzG14F/Lh49S6N6lZItT+rwpxSlBO4G/Fmjm2L/DXJb+fOD7WXMO70IIPs1mg03L37QM4VnQlKlCjG55+PN2gMQ+HCvnh6emSPYTJ5ApMJ9I0LR1ny4wSGjhqd6mYrYx6u3XrEH39v4tGjxxw/uAeAMTNXcu3sAQ5sWcInA2pTo1F76rXswfDpizl/dDvjZq3h1qXjNOrwDh5ePjwLvMuLJ/d59TwQH79iVCznD8CkzxewbNF87B2cKFKyIpXrtmLUN8vxKVzSKO/V0cmVOs27Uqd5V2KiIrh8ah/nLp1i/3/HmfHlTJq2aoOvbwH69niLiuWKMvOHFWz9dwufzt1G/oKmWknONESGh/I6OAj/osnD6pkRZkO8ZUguykmJUvvwUA2rnizjeZXnfHtpQpr2fvXVDxQq5MOgQb0YPnwiO3aswsbG+scbWAMKhYJy5Urz1Vc/ULp0cfr27cb+/Ydp3rwRISGvCQsLx9+/KE+eBFGxYlnc3Y3rxpGR0YdJfqV3b5zjr9mj+P6n2fTu0tgUTVqUew+fcejYZV4Gv6Z1s1pmm18cFR3L+Mm/MO6jAZQuUShxu0qt4WHgCwr5eOLkaE/AvafM+20td+/cp5BvISpVLE2vrs14/8PJOLp54+dflrGzVhMbHcXlk3u5c+UEFy4eJDIqhkX/bGH5L5PQqDXUad6Nl88e0aLb/3B0cgWgTOV6gG6Ay4m9a3ln0IfUbdiMqKgImnV+h44DxuLs6mHS83ZwcqF2sy7UbtYF0D3cPb53nau37tOxYz+iIkJxcHTh4x82Wp04A5zYt446jVpQuJBX4ra0+piN8ZbTEuWAiNSJMLoX7E5QpAMDS33HggvDEzNZaTQa3n9/HHPmTGfMmA+wt7fDzs6ObdtWoFAoOHnyHHXrmm4+eG5nzJgPUKvVqFQqfv11Mc2bN+LcucscO3aazz8fz+efz+LmzQAOHNgkJyyRMRlClyJUP8VKV5EyWm5Sq9Xy+zcf0rRxbaZ/+o6JzTM/0TFx/PLbBjw83FAoBD/O+YWwkGD8y1bB2dWT6+cPky9/Qdp3as+gfu0pW8p0A3SGj5vDyr8XYmfvSPkqtejcpQNxcSoW/PKzzrbIcDzzFyIiLIR6LbtTrExVgp8/JjDgMueP78a3aBkGjf+BA//+xfG96wAoUbYK/278PZl4aLUSB45eZuXq7Zw7cxo7RzdGfvUPSj1rHkdHhbN3/e88vnedrkM+oWCRUiY7X0OQJAlVXCxKGxu99lkDM0e158svP6FLu3qJ29wvrzOLMOsTZYB74cl/t6fDduHvUJH3/2rM6dPnmTBhBEeOnKRevZqpvOUnT4KYPPkb/v57rryutAlZv34rPXp05PXrUDw8TDffPqfj6Vn6rCRJtczVvhCi54ypA9aaaLnJhZIkDTORaVkmS3fAyPDXLP5+NJq4KCZ81NdUNpmVyKhYlqzaw/ET56hQoQxrV63FztEVewcn4mKi6PLOJ1Su0zLxxqXVaLh1+QRnD22hZctuFCrsz5ixwxjQs3mW7HgRHMbKv3UDT5xc3Kndqh9fTR1OoaKlGPX1cvyKl0OliuXl04d45C+Y6PEm8Or5Y84c3My8zwYx4J13+f3nEzx7EULlCv6ppkspFIIWjavQonEVrt8OpEXTjuzb8Adv9Ur9PXR0cqXTwPFZOresIITAzt56k3DExcbw9GEA7Volv9+kJc4ZCXNWRDkptd3acC86jFkDjzFnly4y0aiR/sFKvr4FWbz4F9RqtRzqNiE9enREpVLRrl0/tm9fIfdHy2QZo3+dW5fO4b8ti2nXpSfz50zA3j71wCBLEBurwr9EXcZN+oSPR/VO3K7RaOne72NOHNpDyfI1qFCrOfsPnKJuqz40bj8gTU9CoVRSrlpDylVrSN/hX3HlzAGmTf2Cbdv/Y/6PkxLnGWcWby83bgWcxc7WhnZdPmDRTN10jnGz1uLirkv0YmtrT6Gi+rNTPb53g41/f0vRkuUJfvkKBwc7alZN39s9d+kO076ch1qtwsZOXk3MWCRJQqknaYUlhPledFiy93YKZz5tt5e7ip+5dHdemvUkSaJlyx4sX76QwoULpVlOJnPY2tpy8KAuzL1r13+0aZO1B3mZvI3RqT5PHfiXqdOns2jep1YjzgC2tjZoNWpmTJuCSq1J3P7jgvU8uH+PWSvOMmrGClp1f593J82jSYe3DQ7zKW1sqVqvNVPm7+R1uIp6Dbqy71Dy6TWnz99m3OR5DHzvC85duoNWm/bN1dvLDXc3J479t4xN2zYBEBdn2BS1GxePkr9gUd7qNZKg4CgaNOrKkZNppyI8dvoGXTsPwKd4Vb7++ygturxr0HFkkmNn74Cruxc3AvQPAAsOcEgmzg+D3ZOJ890I51TiHBChTCXO98KlxFdK7kWHJb70cVehW8GuSomRSbYqsLFxQqnUPZgJIdi4cbEszmbAzs4OlUrNxo3biZJzQshkAaM86KcPbxETFUGndvVNbU+WUSgEU7/6is8nTmDwB9OpWKEMG9dvIuTVS4Z9vggHx6wvB+fo5MqgcXM4d2Q7QwYPpXuf/sz+ahhXbzyke7e3qdeyB/YO3nTu1I+42Gg8vXzI5+2Dt7cPPgULULtWFQb2aYWjg11im0+evtT9kc6YgKT0+uBzen3wOQA1m3Tk5L4N9O/zLp179mHWl8NTrbe9e+8JajRuT6vuH2T5/PM6BQuX4NqNB1Qs+2YAm6k85rS85bTEOLF9hf5lZauUGMmNwCU4OHih0cSiUNgAEpGRQcTExLJnz0Fat26abtsymcfBwZ6FC7/j9etQduzYR48eHS1tkkwOxCCBjo4Mw9bOgdiYaMJCnrP+j6/pO+idZAORrAk7GxuUNraohAvHTl2jTd/RVKzZDIWJR1fWaNSeEuVrsuynj2nQpC/ePgVp1LYfXQZPBKDj22OJiYog9NVzXgcHEfrqGa9fPuOvv1Yy86sZdOzWk4I++VGp1Cz5+y8GjvmOfAWMG4RWt2V3ylVvxJqF06hVrzPfffcV7VvX5u6DILbuPM6Wf7dQumrOH2FvDTi7efIqRL9gZqcwpyXKSalZpzzBwSrc3R+h1aoBsLNzw9m5IOHh17lx47Ys0GYkODiEJ0+CLG2GTA7FIIGe0Lc6Wo0aR2dXnF09qNewCdMnW2eI9Pbdp3w9/UvGz15L8XLVzX48Dy8fRnz5D//9+zdrf59Orab2qFVx2NjqvGMHJxccnFySJdp4q9dQAu9d58yBzTwKuotSaUuT9gOp2SRrT9nu+Qrw/uQFnD+6gzGjJ/FhZDhCoaB8tYbUb9M/y+3L6HDz9Obe/cBU2zMSZ31hbH0Y6y0nJSj8PACdeg9k7tzf+Pmn33j+4igAcXFh2Nu7U6FCRcqWzd5R+nmNkiX9USqVbNy4nW7d2lvaHJkcRroCHRkewuTB9dFq1GzcupFmDa0/Q9gX3yygUZt+2SLOCQghaNH1XQ7vWMaZg5up3rAdNRql/2MsXLw8hYuXN4s91Ru2o1qDtoS+eo6bp7e8Nq2JqdOiB/OnvcP773ShpH9BgFT9zEkxhTAbIsrwRpgT8HB3I+jpcwAKeDdM3L5z1zp+/OFXCvna0qVLGzk9pRlp164FTk7y4hkymSfdO3dUeAj+JXWjiLt17EbvQZ8mG3hlbcTGqvhv11aadR5skeOXrFAr/v+aFjl+UoQQeHj5yOJsBp4F3gHg+Yvkc51TDgBLa/BXSjIa8GWoOAMUdE3+YLp330EGvN0r2TZ//6JUr16Z48dP8/df26hWrbLB7ctkjm+/nYtKpcbHx9vSpsjkQNK9e5cp7c/XX07AycUdW3sH9mxZx9bdp7LLtkxz7dYjXNzyZevKRkmp37o3H321xGLHl8kebl44wujx46hfu2ziNkOEOaU4pyXMCaKcGWFOSlKRXrZ0LW5urmzesoI+fboxavSH7N23kWnTviUsLJxCbrWpWX4on38+C4A9ew5y5859JEni4sWraLVao2yQ0VG1akUKFfKRR3PLGEW6IW4hBA1ql+PxozOAzkO1teI1gwv55CM89BUqVSy2ttk/zzfBg5bJ3USEvcKnQD69+wz1mPVhrCDrI6lID+75NT37tKJfn7cJC41kzIc/cObktcQytkpnVv19kS+/hKCg5/j45EelUjFx4pds376Co0dPERsbS4sW8iDDzNKuXUskSaJKlWYcPLgJGxsb7O3tsLeX8xDIZEym1NaU853DI2KYv2gT0VHRTJ88JMvtabUS+w6eIyYqnIArpylfvZEJrJSRSY1GrcLe3i7ZNmsRZn3ExsSx/J/tLP9nu979QihxsM2XZN70QUpoK+JIM5RKJUqlMjHjmCGrOskkRwjBhQv7USqVfP31DxQp4sfgwX0sbZZMDsAi7vCL4DB69BnF5bO6UaWfTxqMUpm1vtIpXy1i86Z/adtnpFUtTSiT+4iODEsl0EnRF8rWh7mF2VhKaCsm/t3VfwGb7utSwn7++SxKlSrOoEG906oqkwYJC2hMmvSRnF5VxmAsNoIoQZx/Xrggy+IM8ODBI/z8y+Hq7oVCyAOjZMzDq+ePefbkAS2bVEu1L61+5pRkpX/ZEnT1XwDAuHFDGTCgh4WtydnY2toyc+bPHD58wtKmyOQAsl3JOnQfRZlSb0Y533/wxCTtfjFlKL4+Hqz9fTp3b5w1SZsyMimJjgxHHadbcCUphgwAywnCnNR7TkpX/wU4Ojqwe/eB7DUoF9K9ewfKl9efY19GJilmj7VEx8Tx46/rOH/+CgDBL54n2//7/Hns3rmXDp3a8+lY41fEKulfECcnR4qWqkSlWi2yZLOMTFr4+pfF1cOLyePH4uHuQr8ezVKV0SfM6ZFy7nLKqVKZJS2RzciW9OoB9CrzB4Fx+9jl/gQRH6X68foA44zMw/j7FyUk5LWlzchdPH+ZbE12YxD3HpnIGNNhtEBrNFouXr3Htl3HGD+yN06OyUclqtQaVm84wDdfz8bLpwjVGrRDo1ETHqnCI/9jXr/Upb+r2bgDp/Zv4laZMkafxNWbD2lUryWOzq4Mm/YXdg6ORrclI5MeV07tx9nFjR9XLade7eSJZtIKZ+sjpSgnkFlxzkhUs1o+KQqhpKlHTwC0khaFUDCt2i/4DXfngw8GcfNmAB4e7vj4eKPRaBL7XWWSc+jQcXbvPsD3339haVNkrByjBDo6Jo5qNdujVqsJffWcNStWUbx0OSIjIoiKiiAqMoJXL4LwKlCY7v+bSuU6LRPrNu0wELUqjsmD6xP++iVdBk+kav02/PntSN4bacOieZ9w7PQNlq7Yyv8Gd6FWtfRDQfMXbWHhr79RtmoDGrXtT6mKtY05JRkZg7h74xwtWreiY5s6ybYbKs5pCTMYLs5ZEdmscif6InHaWCI0IXjbFaG6gx/nfrzF3EUrUPcNo0qVCnh4uFG5clOuXDlEREQkzs5O8rSiJLRq1UTOfy5jEEYJ9POXoTx/8oAf113l0d1rHNyymFLVWuDg5IqDkwuOTi64uHvhmV//UnY2tnaMm72Gh7cv4+jsRoUaTfhgykJ++rQfL54/48KZk1Rr0JbuXQcya84s+vXQ/2UODYviq8+m8v7kBVSo2VSe/iFjdl49f0SDGulP4cusMINh4mxJYU6ggG1RFEKJAOwVToTE2FDB1QMAm1VuXFsVSJzLA2b5fsDetqu59FYIhQr5yNOKkjBixCf07t2Z5s3lqaAy6WOUQI+d+B1NO7yNg5MLpSvVoXSlOhlXSkHBwiUpWLhk4vuyVRswesYKblw4yrTfZuDk4k7dFt34dOJQnj0fz5hh3VO1sWn7MfzLVqVirWbGnIaMTKZRxcUQHh6Z5n5ziLM1CHMCrjaeBpWzV+hyJlTa5UH7fb04e/YiNjY2VK1qPeeSnahUKn7/fSkffDCQL774GG9v61wJUMa6MGoUd2RkJH7FK5jaFspVa0jXdybi5KJbeKBE+ZqM+XYVP8z+jnWbj6Qqf/TYOcpVk7MbyWQfjdoO4I+FC2nbZSQaTfI0mLldnEF/KD+txT8AFEKws9Vynj17ydOnz8xpmtXy6lUINjY2xMWpiIqKwcdHXsBGxjAM/pYcP32T5m3fo2X7Dzl/4iCV6mTPSOmChUvywZSFjBs1gTWbDrF11ymiomPRaLQ8efIYlSo2W+yQkQEoV60RX/z+H08fBzJtxl/cDHgMpBbnoPDzWRLnEtqKVifOhpIyq1oJl0hKLLxNxYrl2L59r4Wssgy3b99lwIDhAIwd+yHu7q4WtkgmJ5FhiPvsxQD+XrqFzetW077/aDy8fGja5YM0+5fNQamKtXl30lw+HDIAz/yFiImOQAgFLm6e9GgkJ06QyR6O7FzJ6gWfY2fvSPFy1Zn/wyzm/zALP49WKIQSpVJByzZ1KV3Jg4ePKrNm9SZCQ/VnEctInI2huKNbuvszWmc6K9wLlyjumv4YkGtDFvOol5/ZbLA2JEmidOkSbN68RB4fI2MU6Qp0WHgUXbsMoOFbfRg9cyV+/mXTK25WylVrxA9rL2Pv6EJU+Gu0Wg1unvISbjLZw8OAy2xe8j37D2zHzs6G735awtUzBwBQayLwcPdh2bpv0BDDju17aNa0EVOnTqBjh75cvnwtWVumFOeMRDmtslkR63vRYRkeNyBCSSkX3dK0dyOc8XeOwM/RgzYfWmYpWEuwYMFiJElixIh3LW2KTA4lXYG+d/cevYdOp1kn6/hROTrrbgou7vpXEpKRMRcn962n79uDqFyhGACL5n3Kia33UWmjsLNxZ+hHPblz7xYDBw5NrDP4nX78uuB7Gjdqn7jNVOKcGWFOr74pver0vOhjwTEsebyJQww32fHu3LlPgQL5cXV1MVmbxhAVFc3mzbvo06cLW7fupkGD2nh55WPIkH5ERKQ9oFBGJiPS7YMWQkGT9m9nly0yMlaJJElcPrWPrp2bJ26rUmIkCoUt9ja6AY0t29Vg7i+/J6u3dMlqSpUqTsGCBQDTiHNxR7csi3PK9ozBEGFP2hddyN6Lj4qZ5l4SHh4BwO7d/7F5806TtJkVwsMjuHv3PgD37j0kODiEtWs3c/HiFXm0tkyWSFeg/YqXRyFnA5LJw0iSxKa/Z+Lq5kG9mrounjfLMuoICj+PRqPBxib5b0WpVKJQKNBotCYTZ3NgStFPOaI7QaSFEDyNfclnn32bpfYlSaJPn/e5eTOAYcOGULlyeSIjo7LUZlZs+fPP5bi5uTJ58hiEEIwa9T5lypTkr79WcOGCdeddl7F+MvCg5YENMnmb/RsXcfXMf+zY+hcKhdArzgDr1m7m4wkfJUtvOXTYEC5duooypkia7VtanLNCZsPjfg7e9OjR0ejjRUfHIEkS69b9RdmypQD47bclFpu+pVarefEiGI1Gk2pf9eqVqVevpp5aMjKGIy9MKiOjB61Wy971v3Fgy2J27lxNgfzuaYozwM8//0bDRnW5cOEgu3b/R8WK5ShRwp9BPaeleQxrE+fijm6ZFl19A8ZS9kUnDBhzVNoTHR1DeHiEUf3GS5eu4eXLV0yePCZx2/z5szLdjim4eTMASZL45JNRevf369eNIkXyzoh1GfMgC7SMTArCXr9kyZxxqGIj2LlzNWVK+qYrzgCxsbF06TyAhg3rUrt2dY4fO8WWLbvIZ69fhK1NnJMezxQDx9IaMLZ69SYKFx5ulECPH1KF2FgVDuqLhNlUZdWqTdjb29GtW/uMK5uYmzcDiI6OpVw5/WsF+PkVwsHBIZutksltyAItI5OEW5dPMP+T/+FjVx7JMR89W89IVSa9BCRHj57k6NGTQNaXjbTGsLY+DJl2dTtcQaw2lp9++tqgNh2/mY5tWd0APFG2MGdvPuaOsKNXlwYAuKkvUrNmFSQp7Sxm5iIuLo7OndumW2bq1Jn06NGJli3lTIcyxiPnm5ORiefk/g3M+2QIZR1bU8KhceKax0nJKDtYAlkdFJZTxDmBjFKAvoh7wdInS/m59vIM23L8Znqy95IkYWujwDk4OHFbbKwKV1cXypQpmbK62fn44+ls2bIr3TLz58+SxVkmy8gCLZPnCQ8NZvWCz1kxZypVnXuRz7a4UXm1E8hr4pxAeiJdwL4A7xV+D42kYXuLpWm2ETXkTZ+y6mYoZx88p8uo36lSshAd6pdL3Hf9ViATx442ofWGM3v257Rqlf5ykUIIpk2bzcuXwemWk5FJD1mgZfIkkeGhnD7wL39/N4ov3m/O7V2XqO7SD2ell15xzkuY6wEhRBXCn4F/AjCl2kR27NgHwPbte4mMjOJyr8msenCT4AAHPjlwls23H1GtSH4WvN0M6WYgAOL6bQCqVS7OxiWTzGJnevz++xIePXqCo2PG/cuVK5eX+6FlsoTcBy2TJ5AkiWeP73L55F72LV5ChOY57jaF8bItQRWb3tg76hYxSEucZe/ZMNIb1Z3PLh/vFH6HgAglfg75efTlBbZ/94TVTzdSoPhVwtXu2CteADDQqxrFimnR3g7HN74vOgFx/TZS+dK8+9F8+gz6gAYNamfb+Xl6euDubthn1LNnJx4/fsqGDdsYNKi3mS2TyY3IAi2Ta9GoVdy+coorp/dx+eQ+VHExOIQVoIh9LTxsiqAUtsnKm1Oc8xLpibS9wh4Af6c3i+30KdQNF5tIXGzsKURNIJSCjs642MUAulC3bVl3pJuBiLKFAZ1If/5xL9yLZd81P3PmAh07vmWQ95yAra0tsbFxZrRKJjcjh7hlcjwJQnzt7EGunz/CyX0b+PPbEUzsX4Mt/8zC39eVP//6mcpx/Sjj2Aov2xImF+eMyKlLRxpLRoPGUi5JqY/ggDdCqLoZCpAY6gYoERXG8uXrsy2T2C+/LMp0bu0CBfLz/vtvc+TIyVSLpsjIZITsQcvkWF48fcje9Qs5d2QH+X18cfPwRKPR4ObmRtu3mvLHvE/xL1KArv4L+H7ZQb2Z8dLrb86MOJvCe87p4e2UZDT9KuWKVyVcdOL3MNidol46QQ4OcMCrVEyyekk96SdPgoiLi8PZ2ckcp5CMf/6ZZ3Td4OBXCCGQJEnO0ChjMLJAy+Q47t+8wPE9azl7ZBu9+g9k5p51VCijS6c5tvxyeAKBN2L5ed6edJNumEqcMyKnec/ZuW60ISKdQEKoG96I9KefZs9I7ocPH/PDDwsMnsedki5d2gHwxx/LAHj/fXkRIpmMkUPcMjmGl0EP+XPWSH7/5kMqlPFl376N/Djzo+TinITsEme57zltMgp1p+RuhHPi3w+DdWKsL9QNOpFetGg5ixZlPLc6qzg5OTB4cJ8st9O3b1fatGlOeHgEXboMQqVSoVKpTGChTG5EFmgrwNlBSf1yHnSuW4CWVb3w8bCztElWRVxMNBv+/IZvR3eiSsWSnD+7i5nT3qdsqTe5jpOK873oMKPFWcb0mKs/GqB9+5Z069aOWbN+SczzHRz8KosWpyZ/fi8cHBw4d+5SltpxdXWhaFE/nJ2d+PLLSdja2vLNNz8xb96fJrJUJjchh7gtjKujkq71fAh4GsWZ26Hkc7XlrereHLn2invPoi1tnkVRq+I4d2Qbe9b/RiFfP44e206xwt56PWVDc0hnJM6y92weTN0fnRDu9vUtCICbmwuSJHH69Hk2bdrB3Lkz0Gg0yVYXyyoPHwYSERFJjRpVstyWQqGgalVd18e0aROy3J5M7kT2oLOZlLmDq5dw53pgJMdvvObJq1iuPIhgz/kX1C/nSV4dShIR+opty39iyjsNOL1/LZMmjWbbxnl6xTkBS4izIeS0/mdjuKu4muyVFik/o7TWjgb9oW5I7UknpAUdNmwITk6OtGjRmLlzZxAVFU3r1r2IiYk17qT00KZNc7p1a8/585dN1ibAy5evmDv3D5O2KWM+hBBthRA3hRABQohP9OwfIIS4FP86JoSommTffSHEZSHEBSHEmYyOJQt0NhEW8oIF0//H8A7+vH4ZlLi9UD577jzVTRPZtWY+s8Z0ZvniBezYthnUEQa3L0kSz5/c59Gdq8TFxmRcwQqRJIn9m/5i8jv1iQ0LZN36fzi8dzFv926JrY1Sr+dsqDCbQ5xzo/ecmQFiaV3X9K53RiKdrB0DRBpS5+4GcHJy5K+/fsLBwZ5Dh46bTKhjY+P44ovviI01nfAD5M+fz6TtyZgHIYQSmA+0AyoA/YQQFVIUuwc0lSSpCvAV8HuK/c0lSaomSVKtjI4nh7iziQvHdnHp5F7KV2+Em6d34vboOA1uTjaERKg4sW89fQf04+SJU8w8uZlY4UT3/03F178sSmXaH9WFYztZv+hrNGoVTi5uPH/yAM/8hfD1L0uLru9RulKd7DjFLCFJEkt+GMfzwAD27ttClYr+yfan7GM2FEP6m83hOcvorr0hEYSkI7uThrozg9u6nwjrOSbZNn//okiSxPLl66lYsSxRUVEolUqDM4Hpw9HRgX//XYJarTZJCF2tVvPwYSADBvTMUjsy2UYdIECSpLsAQohVQBcgcZK7JEnHkpQ/ARQ29mCyQGcTjdr1p1KdFnjmL5RsHuS1hxHULePOi9BYgp8FsvDHX/nu+xkIIfjoo1HM+KgTNjZKvHwKU656Q6rWb0uRkhVBkrB3cubh7cus+GUyv/05nzbNa6BQCGJjVVy+fp9V63azddkcxn672oJnbhh3r53h/s0LnDm5GWcne7r6L8haewYOBJPF2TgMvb76RNpc86Pd1v2U+HfCPOnQyj357bfvAfjtt3/QaLQMHz6E2NhY7O3tDToHfYwfP43WrZvSseNbRrcBcP/+IxYtWk6NGlXk+dFZ4WVosiQ2xiA9fA5QPkXo+XdJkpJ6wH7AoyTvA4G66TT7P2BH0sMAu4UQEvBbirZTIQt0NqFQKMjn7Ztqe8DTKFwdbejT2BfxzwqW/rWQjz8eg0I4Y6OMn/MpSfz991z+3XaQjYu+4tG9G9g7OKFQKlEolMyZO4d2LWsmtmlvb0utaqUpWdyXqsuWEvQogIJFSmXbuRrDheO7aNOhQ54WZ0PWVTb38c2BISJtzPxofYPGUuJ+eR2hlXXe6YcfDgZgx4597N17iDlzUofGDeXLLz/Bzc3F6PoAAQH3KFnSnwULZmepHRmTcl2SpGHp7Nf3FKW3n0YI0RydQDdKsrmhJElPhBAFgD1CiBuSJB1K62ByH7QVcP5uGMsOPMa5aAMGfvo3apUjUdEhiQPKhBB0af8u337xARfObObr7+awZ99mTp3aw6WL++nTtYnedj3dnenUvRfHdlu3By1JEheO7aRX99ZZaseQvuYEsirOubH/2Zzo+1xM3R+dco50Au6X1yVrq1WrJnz66SjCwyN4/Tp5MhRDcXFxYvjwSYSGhhtVH+CLL77jxo0Ao+vLWIRAoEiS94WBJykLCSGqAIuALpIkJa45KknSk/j/nwMb0YXM00QWaCtBpZZ4HhpHZIyGX7ZcQPeglrwvroB3QxQKwYj3OlO5QjEK+3qRz9M1zTbv3A9i09qVFCtdNc0y1kDg3WsgSdSvVS7jwmmQmbnN1uY5J8WcWbxMdVxj55FnVqRTzo82lUjb2tqSP78X69ZtyVKSky5d2mbJi1627FfKly9tdH0Zi3AaKC2EKC6EsAP6ApuTFhBCFAU2AAMlSbqVZLuzEMI14W/gLeBKegeTQ9xWileBgvy7eQnNG/VLtr2Ad0OD6s+a+wVTJ35C1XqtqdmkoxksNB3blv9Iz379USgy1wdnjFBYszjLpCbloLHMhruT5u1OGu4GGDy4D0IIgoKeU6BAfhQKw/2Vc+cu0bp1U6P7jb/8cg7durWncuXyRtWXsQySJKmFECOBXYAS+EuSpKtCiKHx+xcCnwNewK/x3w91/IhtH2Bj/DYbYIUkSTvTO57sQVshj+5cITIijOJFfYxuY/yIsXToP5YBo2aZ0DLTc+3cIZ4+vMVnEwcBGNT/nJlQdlIsIc7G2JndXnR2Hs+YUHd6mcay4kkrFAqEEHz66decOmX4dyMsLJw5cxagVqsNrpOSNm2aU7hwoYwLylgdkiRtlySpjCRJJSVJ+iZ+28J4cUaSpPckSfKMn0qVOJ1KkqS7kiRVjX9VTKibHrJAWxkxURH8PHkA38yaiZOjvdF9nQIl6/+YhdLGNuPCFmTT3zOZ8tknODmmPzjMkEQY6ZHTPOfsEs3MHscUaVKzKtJJQ91gnEgnFepFi36kXr2anDhxNllebEmSWLZsLVqtlsOHTzB79i9otVquXLnBqlW/Gz0KPCwsnHLlSuHp6WFUfZm8gyzQWUStimPPuoVsWfp9qixhxqDRqJEkCS+vNzedgq7VMy3UCoUTWimOjzpZ92Cm508e8M3ExanE2dDsVIaQ08Q5AUMTsWSlfUthaZGGN960UqlEkiSWLl1DYOAT/vvvCOvWbUEIwZUrN4iKiqZixbK0bduCkJDX/P77kix5z0eOnOSrr34wur5M3kGkJyrFSleRPp27NRvNyVncunyCFXM/xcXNlTvXLzJnzSWcXFJP9cgsNy4cYfH3Y7h8cT8Nq6TO02uo4Gg0EUhosVGmPXUnQfgnL093Op7ZOLJzJavnfYmHY1mUSkdsFE4ohP6QpiRpeRl5AUfb/LjYFzWofXOJc2YfmLKa8tPU06+MFefMDsbL6DqlvC76zjPp9KuUSUwS+qMTSLpEZdJ50imnYCX0SwPJ+qUBzp69iL29PZUqpT1oMTo6hmbNunD48Bbs7NJe3Obtt4czbNhgKlUqz+bNuxg4sFeaZXMrnp6lzxqSNctYhBA9Z3Svt3ZSu5oZF06HU/eeUX/GuoUZTLPKVmQP2ghCXj5l0+LZLJoxnKmff0yL1q1o3K6/ScQZoFy1RuQr4MfGbUf07jfUo1YonJAkFRptVJplgsLPExR+nlGdaxttb1Zo2KYvA8Z+Tf7Sjgj3Z7xSnaRIdSXhMQ+IjntOnDqU6LjnhEXfJfD1HmJUL1AKhwzbTTiv3IKpvOmstGPMSPnMfgYZ2ZbeyG5I35M2dBpWzZpV0xVnAAcHezZsWIydnR0zZ/7M7dt3E/eFhLymZ8//ERcXxy+/zKB+/dqEhoYTGal7mFiyZA3//af/ty0jkxRZoI3gr1mjOLF3DX/+s5BuHRtz6cIVSlZMLnAHt/zD/ZsXjD7GWz2HMf+XRemWyUiohVBgo3RHq41Cq804d7AlRFoIQb2WPRg9YyXTftvP9EUHKVG5KcVr+PMy8jzPwk/wMvI8oTG3ESjwcWuAo12BdNs0VBR8fQvy19+/8PzFLR4/ucoPP36Dq2vWkk+khamWuDRWYM0dLk9Kyuuf3sOSKQaNGSrSYPhc6YwQQuDnpxvkVbNmVQoUyM/hwyeYO/cPPD09mDp1LHZ2dnh6eqBQKCha1I+hQ99Bo9GwaNFyJk78EoB//lnN+vVylFJGP7JAG8GLoAeEvnrBwL6D8fevwbWLZyhb9c30J41GzaoFn3N010qjj+FXvALBSRbVSI/0RdoGpdINjTYMSdJm2JalPOnXwc/YvW4hq+dPZfvKudy8eJyqtRvj5lCC/C418HVvRmHP1tgp0573DYaLs5OTE3v3beJx4FMqV2pIg/ptcXFx5t/Nhs2LNcY7N+U61AmCa+jLGrCkSKfXL50g1ElThWaGt95qhru7G76+BWnbtgUA1apV0ltWqVRy6NC/nD69G9CJe5Mm9YmIiDT5AhwyOR95HrQRfLv0VOLfqrgYNBoNDo5vbhBajZqyVRvQts9Io48RFRGKs6s7b3LQpE9B1+pp3gAVwg4tNkiSGrBFK0WDpAUhAKH7J2wRQvd1MESkUz4UGNuHLUkSp/ZvZP2ir2nU4i26d21F4/rjqFiuKAqFoEoJw65hZgWzV+8u3Lh+i88+m5G47cMPxnLu3AGaNGnAoUPH0qmd9zBVhra0+qWzmg4Uks+RhuTzpCH91KAJIp3Uk5bSSCISZqM/8U/Jkv56t6dHQij9xx9/w97ejuHDh2S6DZnciyzQWcTWzoGUE5ls7RwYM9N47xnA1T0fT+4HoFZfw9ulFg62XhnWSbjxpbxJ6gYC6l4abTigRQhbkCRAixYJSRsJKFAo7FEIe3Rz8EkzEUPCMRKOOWPAB0aJ9O61Czi1fz3LVv5Jk/rJb9CGiLOx/cwVK5bj8OHjybZJksThI8epULGs2QTa0BWeZPRjapEGUgl1wgAycf22XpF2U18E0hZqYxg16j0kSUKSJHnRDJlE5BC3lZKvgB+Tft5M7Wad0Tg+4Xn4GaLjnhtUV5+HIqFGow1FkmJQCAeUCmeUSheUSldslG7YKL1QKlyQJA1qzWvUmheoNS9QqV+gUr9ErX6FRhOORhuJSh2MWh2CVhvNk7CTPAk7ydOws5kKj0eEhbDq16ns27iITRv/yrQ4Z3UQ2K1bAdSrl3pgab16tbh1845BbRh7fFOGurMDU9ublVA3GBfuNrRfGpL3TYvrtxHXb+u1N0GoTYFSqSQo6AXt2vUzyXRNmdyBLNBWTOHi5Xl34i+07T2CWHUwr6NvGlw3qUgLIXQCrPREIRwTQ9lJEUKgUNhho3TD1iY/tjYFsFF6Y6P0wkbpgULpCkIBkgalwjVxnrVWE4lWE4FaE4xGG8nITtXQatPu6w55+ZT9//7NjI/a4+4k2LVnHaVLJM+olFY60wRRNsXo7FUrN1CjZlUmThyFi4szXl75+PGnGahUav7773CW28+InCbShpCZzyU7RDqz/dJp9U1D2kLtpr6Y+Moqfn4F+e2372QPWiYROcSdA2jc4W2unTtE+OsgYp8aHgJL2i8thBKBEpSGZxYT8X3UoNCtsSaS11XwJpOSJKnRaqPQaMMY2bE0CqULAlsk1EiSKvEFEkLYoVA4sWPDTnZs0J+K1txTpCIiInmrdQ9mzZpG0LMbqNVq1q79l04dM+fBGDLXNy0SxMiaQ97mfJDISn80ZBzuhsyFvCF12DtBpJOGvUF//3RWQ99CCLy88vHrr38zbNg7slDLyAKdU+g/aiYT+9XA1d4fD6eyBtdLb/CYKUkYLa6QJCQpFo0mDF2ARotC6Pq1hcIZUFrNjefevQf07v0uQgiLhhWttV/alOJcs1Y1mjVtSPCrEDas30JYWOaXaTRUpIEM+6WBZAttAKmEWt8gMnMLtY2NDbGxcajVamxtrTtNr4z5kUPc2cSKXz5h6Y8TWLPwCz57txF/zBjG7rW/EhuTdhKRpLi6e9H1nUnEaTK/fq251i729PSgSpUKyeYO60LlDvF92k7YKPOhVLqiUDgghI3ViHNSsirOpngAMkVKU1NiKlsUCgWL/vyZFSv+wKdgAdq2acHVa8epG9//n5lQNxgW7obMh7wh47A3GB76BuPC3w4O9owd+yH37z8iIOCewfVkcieyQGcTR3atpkA+J7w9bBn38TjKlCrCg+vHmfJOA84c3JxxA0CTjgOJVYcQFHaclxHnUWkiDD6+KUXaxsaGH3+awc1bp1j8z68E3DnL9OmfJBPfBKEWIm98xUwVpbAGoTbl8fv27Ub58mWpWqUxEz+eRt++7zH0w3EsWbIgcXnH7BJpyHgAGZheqCHzYn3y5FmuXTN8zIlM7iRv3D2tgGr1WlOnTjUW/DgBP19vvp0+nH07/mTSlMks+eljtBpNhm04OrniaFsAlSaMaNVzgsKOZsoGU4n01KnjKV26BGXL1KFG9WZUrdKYFi2bMHzE/0zSfk7FlF0JlhJqUx+zR4/OzP35N2Ji3oSPt23bTXRUFDVqZhwCNoVIG+pN6xPqpGRGqLMq1m+/3YvOndvy8GFgqn2SJLFx43aio2P01JTJTcgCnU0obeyY8vF4GrccyLD3R1C/cXcOHL2CRqOlUJFSCAMXi/dyroZS4UBBt0b4ebTKtB2mEOkPPhzMRyMnERLyGoCgoOeMH/8ZQz98J8tt53RM3d9vqhW9DD2WqVEoFHpH9Wu02mQRl/SuW1ZFGgzzpiHjsDekL9SmFOuwsHCGDBlNTMybDGP37j1ACMH+/YdRKhWcOHGWHTv2pdm+TM5GHiSWTVSq3QIP70LcvHCUUV8v497NcwwbOp6gwLs0fKu3wX2zQghsFS6oNBHYKlPfYAwhKwPHbG1tcXd348GDR8m2B9y+S8FCPka1mdvIysju9EgqVKYaVGZu4d+4aRsjRr7Hv//uIC4uDoBWrZri7u7GubNZn5qU1sAxSL4KFqQ9yhtIdxAZJPemUyY6gdTJTiD5illJRTqtDGVJRTrMpipubq7s3bsOjUbDzZsBFC7sy//+N5Zdu1bzyy8zAbCzs8XBIXPrUmu1WjQajTwILQcgC3Q2Ubdld+omeV+sTBWadXqHqIhQg73nBOxsPAiOvICdsjE2Siej7DFWpFUqFRcvXqFDh7fYsuXNFKmu3Tpw9OhJo2zJjZhLpBPQJ6yGirY5RDmt79LyZWtp26YFZ8/uZ8OGrRQp6kfbti3p2+c9NCm6ddK7ZumNdNcn0pB6hDfoH+UNhgs1pD3qG/QLNWRNrDdsPcGFy/eY8Nm37N69BhubN7ftGjWq8PTpM44ePUnDhnX1NZXI1as38fX14cmTZ4wYMYkDBzalW17G8sgCbWGMW6JSFzJUKLL2BGysSE+dMoMlSxdQzL8Ip06do1nThowe8yGdOvXPkj25jZTpUM2NpQeX6UOj0dC//wc0blyfZs0acvr0eT6eMI3g4Fd6y5tDpEG/Nw2ZE2rQ71XrE2ownVh371iP7h3rQYJoq3X/JUzjevHiJadPX+D69QAiIiIYM+ZDZs36hUGDevP6dRg7d+5n7NgPWbt2M23btqBevZocOLCJhw8D+f77X/n552+scnaFjCzQOY7Jy39nVKfKFHCpg0JkPURljEjv33+Izp37M3r0h/Tr14MrV67TulV3edRpGpjbm84JHD58PFXuc2PISKQBg71pyJxQg+HhbzBMrCH13OrEcmkIdgIJXnajCtCoQj0iIqKJitZ1IxQrVhg3N1eUSiWVK5cH4IsvPk5W39e3ID17dtIdS84BbpXIAp0D8S5SiNJlCnL3tOWWpzt39iKDBw232PFzGtntTedkMnqgySixS2a9aTBeqCHzYg2Z964Ty6Yj2i4ujri4OIL6Ih/0LAHcBnso1cw90ftOmjzFxsaGJk3qs2fPQTZt2s78+bNQqVRy37QVIQt0DqRO827YqYP5ft9AuraYjkJPbu3MkF3ZxmRkoTYUc4k0ZE2oIetiDYZ715A10U6JvtHi3Zq60bBCO9zUF6ndaiJ/zxuJ8KjJihXrmTTpIx48eJSYr14me5EFOiciSaxZ+gdrlv4BgK97M5SKzI3kTIks0tlLbhJqS31vMsplnl7IG4wTakjbqwbDxBrS964h66KdWNcA8VYoFBT08QTgxO6ZCCF4GRxAnQoOuKkvsmvjvxT286Jdz+F89NGnzJkzHbVag42NEnv7rN13ZNJHFugcSPVG7dm0eBYA+Z2rm6QvGmSRtgS5SahNjaF994Z405A1oYbMedWQtlhD+oIN6YfEQb9oQ3LhhvTFO1l78UKuVOrOt4C3O13a1QFgwsguAKhjz9O8eSPs7e3ZuHET585dYvbsz7l//yHFihWR+7DNgCzQOZACvv4Mm/YnJ3Yu5eUt+Qk2N5D0wSgnibW5H+hMJdKQNaEGw8Ua0g+DQ9YFOwFDhTspKUUcDBNyW+DdMhAK9O3blT59uqDRaPjf/8aybt2fREZG4+rqgru7a4ZtmRrNi5g0r5GhqJ8anjo5u5AFOocS/OwRjk6OJEy5MhWyF215cqpYWxpDl+80VKjBOLGGzHnXkLFgJ2CocCeQUsDBMBFPQJ+Yu19el+z96R/7IgL3MmvPFXwKeNLt7dEGty+TPrJA51B8CpdkzcIvKOTeFBuF/h+zTM7HmkPg2fUgl9lpaoYu35mRUIPpxRoME2xILdpguHAnkFmvMjMeeeL0sPjQ9qTWlQCdhy1jGmSBzqHcunQCAKWwM3nbshdtfaT8PCwt2Nn9/TBGpMGw7GqGCDVkXqzBMMGGrIk2pC3cKUlLyBMwRNATRDyleB+/E8S9ii3oWNkgU2QMIFcJdMlCTlQq6oKzgw1BIbGcuxPK60h1unXUqjhsbE0vcuYm7FUQn3/zLX9//5+lTZGxAJYKg1vywc2YhC/GCDVkTqwha4INhnnZoF+0k5KWgCdgqJAnxdABbJp2A3F6qT9DnIxx5BqBruLvSvkiLhy/EUJopBp/H0c61/Xh3xPPCI3SiXR0ZBi/ffU+5Ws0oX7r3qyYN4WLx3cx9PNFVK3X2sJnYDiSJBF47zql3+tutmPIXnTOQd/nZGrRtpbvgrFZ2TIj1JB6pSxzCTYY7mUnkJZ4Q8YCnhbpCXtGYXXVzVACh36EU0goLVqYZhEXGR25QqCVCkH1km78uGQfp47so2jpyoRUa4RSIahWwo0VW49zct86Dmz5h6Ily7Fl2Y8c27MWX78itO/ej1uXjucogV6/6Cse3blG62bVmcwSS5sjY4WkJaiGipu1CLI+spI61dgVwcwl2GC4aCeQnnhD+gKeFpkR9gQxTxBup78ncXrnfq5cuc6ECSMyfWyZtMkVAu3mpCQyKo5fvxmNq5sLF45u45eAq7w//luO7V7Bk6cvaN2+E/9uXc+Fy7eZPH4sAwa9zecTB9G1zzgO7l7J/k1/Ur56I0Z9s9zSp5Mh1Rq048rp/1i3+bClTZHJYViz8GYGU+Q3z8ryneYUbMi8aCclIwE3FEPD7NL127Rt24K2bVuY5Lgyb8gVAn3//j2aDn0LXz8/dm5eAICXVxn+mPMJC37/g17dm6BU6pZ0bP9WRwA+nzgIgIO7tyS28yzwXjZbbhylKtamZuOOnDln3tWL5DC3Zcif34t8+Ty4c+d+qiUZZd5gykVIUq4Elt2CDcaJtj4MFfKMMCTMHqqK5uuJ01m//i/s7HLeWB5rJ1cI9JWzR3F2defwvo3ExLxEkjSEhT0iNFTBkHdGMmr4lMSyNkpPvJ0rUaXESCJidaMQl61ZwTv938HXvzQr502mYNHSNO0wCIXSsB+EJbB3cCYy8oWlzZAxIe7ubixY8D0tWzUlJCQUOztbPv3kS1av3mhp06wWc60UlpX1tiG1YINxop1YNwPxToqhQp4Z9CVmCY4LxdPWi837l8pZxMxErhDoag3asmvNfKZ/M4dvpn+GJEncv/+Yz6Z+ycGDR9P8AcepX+Ng682nH/7D9Zsn2Lj1CC9fhjD7q2lUrd+GfN6+2XwmhpOvgB9n9h/hQsCfVCv1kaXNkTEBf/31C0+DnlHcvzpRUVHUrFWNdesW8+DhI04cP2Np86yW7JorbgnRTqybjnhD5gTcGPSNRl/5ZB+fLZ8ii7MZsSqBliSJ6+cOsf/fP/Hy9qPfRzMT9x3fs5aD25bSe+gXSFotxctWT/Rwb1w4younD5n51XSGvt+THm1m8PxZCJIkpfujzedcKfHvFrU+5dLdeRw8pvsRxkZnfqBFdlKxdjP2rF/I2+9N49LdeVQpMdLSJslkgaJFC1O3Xi1KFK9OXJxuTd+zZy4we/Zchg4dIgu0AVgiqYs+0QbjR4uD4aKdrJ0MBDyrJH0A0EgaroSq2BqwHoVCYdbj5nUsKtCSJPHg1kUe37+BnYMTu9f+StCjOzR7qxN7t62g97AvUdrY8jr4GUt+nADA+t++IDo6As/8fpSpUh8bW1tA0KpDD24ei6BR1QlG21OlxEguBPzC+MnTmDtlAJ/8vBX3fAWMbk8VF8Pzx/fxK14uw7JxMdGc3L+BwLvXuH/rAg8DrvDrtvtpPp06OrkybvZaPh1Yh3sPR8gincMp5FuQBw8eJYpzAjdvBNCtW0cLWZUzsYbsa1nxtvWJNhgn3KYi6QPA/ZjrlOppL4tzNpAtAq1SxXLu8DaeP7lPg9a98fIpTFxMNH/OGknQowAqVavBoT1bUavi2LRtE2VL+VF+23rW/PYF6rhY7t+6BEBhj7dQPRcoJS2PX9zn7qU/iVG/xEbhhBAKCro1zLKt1Up9xKW78wh69oJ5nw9i6GeL8PJJnY/WEFb8MpkT+9bz4dTfqNagbZrl7t+8wOxxXZEkif+NGMPAPuN5f/AQnj++h0/hEmnWs3dwonnnd2jYoB2NWrRDrYlGqbBHCPmHk9O4euU6JUv6U6SIH48ePU7c3qlzW06ekL1nY8jKAMec0q+dXSQ8HERpwtl4bwYqlcpituQlzC7QK375lMun9lG0eGl8Cvrw1+yPqNOiOxv/nEFsTBSBj6/g7GSPVvstN+88pnxpnRi65/Pm0LZlydpK8CaFUODmUAIcQKWJQK2JwtbGtE+Xc2ePYfosT2aP68rYb1dRsEipdMvHxkSxb8MfvHh6n9KV63P/5nnu3zqPjY0d21fOxde/HAV8/RPLR4S+4vnT+4S/DmbpTx/zv5Hj+O7LoQDM/GEFVeq2TFecE+g0cAJNOw5m0oBaidsKuNbF3sbDqPOWsQwREZHMnjWXbdtWMX36bO4/eESvXl3o1KkNjRq2s7R5eY7MiHu1apUoU6weF8/dJPR15lZEyuro8eziXnQY0dpQbkTtQJI+xNbWNEvcyqSPSQVaq9Vycv8G1Ko4tFoNj25f4ujuNdSs35y9239n3eYjvD94CK6uLrRs34WAW7ewtdX1IysUIlGcARYv+Z2ypfyoU7UnEbEPcbT10XtMW6ULtkoXU55Goj3TP32Hp0+fcebQVjoOGJNu+eeP77Jl2Q/4l67IiX0b6Nx7EGPHjWbS2NE8unOVr0e0Ye7Gm2i1Wr6f0J2nD26Tr0Ahnjy4Td0mbyWKM0BUdDRKG1s0GjVK5ZuPSKvR8Pj+dXaunsfVMwdxcfPEy6cwd69eAcBO6UGc5jVh0QF4u9ZKZaOMdfPDD79y794D3nt/EAUK5OfQoeM0bdKRoKDnljZNRg9+foVYveYvvLzy8eDBI6pX/5jvv5vHd9/9kljG2NSkCZhbsNPqQ095fI2kwlHhTjXn3vKgsGzEZAIdGR7Kf5v/ZtvyH7F3dKZF285Uq1yC+XOOUcQ3PwDdOzak9YOLuLs56W1DXx+qp1N57G08sVHor5MWmflip/clbdigJgt/W5pu/aBHAWz6exZ+/mXYsO43ihfVPUz8vHAjCqUNP877hU8//oS5U97m+dP7BAc9YuD7I5g7ewy1GvTk5KHdvAoJJ5+nbh3VcSP6cPDAYSb2q07+gkVQKJTExkTxMugR7p7e9Hn7bZb/+SUvXoXSo/UneDlXwVbpIoe2cwEbN25j48ZtljZDxgCWLF3A9m27mTnzJyRJwte3IHv2bODKlevs2LEXyPoiJ+ndmwy9x2UkwgAurk6M/rg/Hbs2QalQsGPrUX6ctYy7Ibq6UeEB+NlXx9OmqGGGy5iELAt0WMgLHgZc4drZg/y3+W8A8uX3YcVfX6Yqq1CITIlzAk52BdPcZ4onzJRtVCkxkkt35wFQxK8AD25f5uS+DdRp0S3Z06NWo2HZzxO5dHIv/xs2gsnjBmBv/yb0M3poN0YP7QaAWvMN40fqzrF4mUr07KZLLTp8xPuMHzmSkiVqMOOHHxk2pCOeHi4c2rOYwCfB3LkfhEajwcnRgQpli+Dm6pjY/lv1puJg65Xl85dJ/8YpJ2uRSUmpUsUpUcKft2b1QJJ0A6iePAni229/4t13ByQKdEpMuciJIcJrCEIIFq/6kkcPgni7x2TUag3vD+/Oyk3f0rnVaFQqNY4uJXlFGJ7mHSwukwKjBVqlimXqOw0JC3lBlVqNeHjvNgA/LVjA4L6tMtVWZkcfmzvsU0Jbka7+C9h0fxgtGldh5ZqljB49mT3rf6PrkElUqq1Labdv0yJev3jItauHkgmnPrp1bMS+/f1wcnJi7EcDqFCmCADv9HuLKRNdiImKYO4PvzBsyJsRu4V9vSjsq1+A5RHbpsGQm2TKMrJgy3h4evDyZXCqTG9Pnz7Dw9O4BSssRaOm1XB2caT/oLcTHzYefPyUNVtm06ZDfdau3YBC2GJv48Gme8MsbG3ewmiB3rlqHnGx0Xw3dy7vDWxHnErNpm3HaNEkc0+FBbwbGnSTtMTgiQSRbtqgIudObqJJq0HsXD2fx/duEBH2ilP/bWT7jtUZijOAp7szy//UH1X4+tuZTBj1EYWL+aPVSigU6ffxyOKcdbLivSStK4t13uTSxasULOhDlSoVuHTpWuL2twf2Zu+egxa0LPMULmXPnn17EsUZdN/rIwcvUK5CwkBVkRhVlMk+jBLo0FfPObh1CYcOb6d0iUIA2Nna0Ltrk2TlhFBgY+MESKhUURTwbpCqrYxulJYe1Zgg0gqFwLdwYfZsWceda2d4Z+goJv+7nIplk/fJZFY8g8LPJ/4wzhw9gE+BhukOwrDk3E5z0KhRPapUrcidgHvs2XMArVZr9mOa8hrKYp03iYuLY+LH09iydRVzf/6N+/cf0rNnZ8qWK83oUZ9mWN9afsdB4ee5e7cgHTu1SbWvbKUCHNxzDUdbb1mcLYRRo4qunz9Mpep1E8VZH7a2Lri6FsPOzhU7Ozc0Gk/at0++pGN6X9IS2ooWF+cEuvrrFuBYs2Qmk6Z9xYD3RvDjzI+oXjn5NKiseLYKhTM2Sq8MR0jmFhFwcnJi5651/Prrd5QrV5rPp03k1Om9+Ph4m/W45rwxFnStbjU3Xpk3n4e+lylYuXI93bsPokRJf/r168HxE2do2qQjoaH65yub+vimoKBrdc4eeoF3fi+mTZuIi4szjo6OTJv8DdWrV2fjut045L9taTPzLEZ50C5unpw8tIuT525Tt0bpVPsVChscHb2JiAhEq1VRwLshtevUYMuWFVQoX59Xr0IyFGdrI8GT/mRMX737jRHnBLEVQqAUhi8RZ8qBJpZiypRxvHj+kvbteid6zd98M5UffviGAQM+sLB1WSPhM8ktD1M5DWPGFaTE0M/u7JkLnD1zwWg7rAG1WsPAntOZ/u0wnjzR3ceOHrpAvy6fEBcjcfDoKgtbmHcxSqCvnN5Pk9YdqVxe/5B7W1sXVKrwRHEGOH3qHHv3HKRL1/bsWHtNbz1jhDmz6e+yko0nQaSTYqzXbKqbtznTGppTYHr36UrnTv2ThbS//fYnAh9fwc7OLlXKS1OQ3TdMWaizF3N1XVgr+u6Xxo7sfvY0mKGDv9bNQhGC2Bjd70+tjSI4OIR8+TyzZKuMcRgl0I/uXOGbrz7BydFe734hFEiSNlGcQZd3e+a3X3Phwln8PFqiEMkPnRlxzkpO2qR1jRHrhHA3mG6agymwhvzDmcHW1paYmNhk2+LiVAghcl2OX1mozU9O+d4bQ2bujVkV7djY5Ck8VZowzp69SOnSGWc1lDE9Rt0JPfL5cPlqQJr7VapIbG1dcXBQotaEoVK/QK15wYULZynsU9locS7u6GbShPGmbs9QzHmjDgo/nyOEYMuWnYz86P1k2z74cDAHDx4jJibGQlaZF2vrfzQnjo6OVKtemUKF9GcAlNFPwtibpC9Tt5kZnOwK0bdvtyzbIGMcRnnQnt5+rF65ho9H9da7/8qNO3wxbThe3o7UaVyPfTs2MnLEaIoWqsovc1YnK2vIF8bcIlrc0c0ob7qEtqJVedFJsXaP+svp37F37wa2blvF/n2HqFmzGvUb1KbNWz0sbZrZye0jv0d+9D5Tpozj8eOn+PkV4uCBo7z//hjCwzOXp9pQrPU7bgiWGG+TkZedsD9AXKRqA4FWq811Ua2cglFX/cXT+/gUKkRsrIp6TfrRudc4/lq+i0nTfqN0ueY0bdQW+/xlmDDjb04d2c/P8+Zz+thdJk59l0chuwiJ0vVBZ/TlzE4P19hjWeOAtqRYqwC8ePGSOnVas3LFOgr4eHPw0FGqVW3C7dt3zXI8a72J5zavulOntgwb9i6NGrajVs0WlCheg9CwcObP/87SplkNpvSOTYU+m87e+JkRI96VxTkFQoi2QoibQogAIcQnevYPEEJcin8dE0JUNbRuSozyoBu1HcAfM4fhV7gqbh75qd64C4uXrMfR2Z2XzwLxKVyC9v1GM2tsF8LDQxk9cgT5CxZJrO9gk5/imvKQzowiS619aqw3bc1YqzcdGxvL8uXrYPk6S5ticXKLV/3Bh4P5Ytq33LlzH4Do6GjGj5vKnbvn8PLKR3DwK8saaAGsSYgNZdP9YVy7dovatatZ2hSrQgihBOYDrYFA4LQQYrMkSUlHPt8DmkqSFCKEaAf8DtQ1sG4yjBLoynVb8sPaK6jVKmzt7FEqbWjacRCn/tvIqf82UdCvBBq1is6DPiYq/DXObp6Uqlibb0a2I+hRAC8jz3OI8/jbN8TPvho2IvlgM0suTJ6bCQo/b3UiLZOanDyorGDBAty5ez/ZtoiISIKDQ8if3/QCba3f55woyglsuj8MSZL47LOZ/PrrbLPnJshh1AECJEm6CyCEWAV0ARJFVpKkY0nKnwAKG1o3JUan+rSxtcPG1i7BIFb/OpVLJ/dRpERZ7t++yKiuZXF0cUPSaihZoRZbl37Py6cPk7VxP/Yo3ralsVHqBNpahDmzXrQ190XL5Fxyold95MhJenTvxLmzFxO3VatWCUdHh0SvOjeSkwVZH0II1q//29JmWILyQogzSd7/LknS70ne+wGPkrwPBOqm097/gB1G1jXdcpMHty0DoHL1mvy58EvyebigUAhehYSzZPUeihYuSJsWNblz7yknz15n/dRL2AvXxMxZ1iLOCeTGUDfIXnROJaeI9Q9z5nPw0FZsbG3YsnknZcuVZvLksXw29RvUarWlzTMp2S3K2ZnzYcKEL3jvvQGUK5c6EZU1EhVsS3CAQ5baCA2xA7guSVJ6K4Lo65jVu8aXEKI5OoFulNm6CZhEoIUQjJ21mtDgZ/w1exQHj/bk6PELbPt3I9179+HdgR0pkN8dZyd7qlT0p0pFf7Z9fj+xvrWJcwKZEemc5EXnRZHOTedszatrPXr0mMaN2jNq9Id8/c0Unj4JYsg7Izl06FjGlXMI2SXMWb0vZiXnQ8+enfD3l9d+1kMgUCTJ+8LAk5SFhBBVgEVAO0mSgjNTNykm86DLVK5HVEQoNrZ22NrasHHNSt77ZD4718xj4U+zadSyA19OG0XVisXpXmJhYj1rFWdzUtC1usVvqoYIljXYKZMx1uZdP378lEkTv7C0GSYnO4TZXPdDQ8V60/1hbNu2h9atm2JnZ2cWW3I4p4HSQojiwGOgL9A/aQEhRFFgAzBQkqRbmambEpMJNICTizvFSldhcL+36TbkU0pWrM2I6f8QGf6a9X98Sffug3EOK0Qpx+aACZ4QXdNfWOJeeNZXF8+toW6Z3Ik1e9c5GXOLc3Y6KmmJ9ab7w4iNjWXHjn20atVEX9U8jyRJaiHESGAXoAT+kiTpqhBiaPz+hcDngBfwa3wXrlqSpFpp1U3veCYVaIA7187g6OxKs87vJG5zdvVg0Lgf+LvPdC6oVlPSoRklnIxf1DwjYU5ZzhRCbQg5KcxtKLIXnbOxNu86p2FOYbaG6GGCDT9eHwCAJMG8ed9a0iSrR5Kk7cD2FNsWJvn7PeA9Q+umh8kF+vvVF3FycWd1/7mp9jkId9xsPFBzB6hhVPuGinNuomjRwkRFRfPyZXDGhTNBbuqXNYS8dr4pyY1ibc7PNLeLcwIJ4nznzn3ee28s+/dvyHDZW5nsweQpYpxdPTj1v8WJmbmKO7pRzMGZ/LYaiju6UdCuGFFa40LGxopzThX1Jk0acPHiIQ4f2c7Va8fY9O8yChYskO125GVRy63ktgxmOQVL5f83hJIl/dmxY5UszlaEyT3oE0P+IlIbyou4QF6qHvNCFcgrdRA2wg6BQC2paOWZbr+41WGJfmh//6KsXPUH7783hu3b92Bvb8+nn45h46al1K/XJlttkcm95OSkKObEHN6ztQpzAv/+u4MGDerg4KB/lUKZ7CdLAh0dFc6tSyewd3Dk3s0LnF+1mReqQAC8bQvjbetHNZfm5Lf1xU7hQJg6mFhtNN52hTNoOTVZ9YKLu4ps64s2hIz6docM6c+yZWvZvn0PoEuL+cUXs+jWrQP1G9Tm+LHT2WUqkHv6ovN6mDstZKF+g6nF2dqFOYGbNwOoU8e4rkcZ85Algf5v019sWfYDZSrVokq1qtTzrEJhh/a8inbTGyZxs/HKyuFyBKYaKOZXuBCHD59Itf3atZsU9vPNcvsgh65lUiMLdd5l4sSPLG2CTAqM7oPWajRsWfYDxUpVoFfvbtSoXgkfex+clE442j0zpY1A1kdiW5P3bAinT5+nY4e3km1zdnaiSdMGnD17wSI25RZBl8UnY3JSH7U1f545xXsG6Nx5II8epZs3QyabMdqDViiVfPPPca6fO8TeAyfQatRcDdyHEiUx2hiquFahnXc7AiNN3s2dJ1i2dA3Dh73L/F+/488/l5HP04MpU8ezceM27t59YDG75FB33kL2qI0nJ4hz0rE1c+d+g6+vjwWtkUlJltQzn7cvDdv0pWGbvgBcuDuDp7FPqehSkc3PN7MocBG9C/YmLDafSYw1lpzmPQNERkbRvHkXJkwYwR9//ERERCTLlq1h0R9LLW1arkEWacPJLQ9mMm9IOfBVrdbw5MkzihQxTReaTNYx6TQrXwdfarrXxEHpQK+CvajhVoO/A/8mn4NpRkDnRKHNCq9ehTB58tfUrNGcpk068sfvS5Aky18DWdTyJtYc9ra2hwdr9571zUo5fPgEp06ds4A1MmlhUoEu8PM7iX8LIajrUZe6HnVZ/XQ1hZ3VJpmPfC9cSnyZopxM3sbabuw5AWsVaZmMuRcdluaU0SFD+tGjR8dstkgmPUyeqCSpSAM08myEi40Lx18fB1JPlwpVv2Tji3lGHSupCKd8mRJzzYHOyTe6nGx7SoLCz8tCnUms0ZuWP8P0yeg+9uWXcwgMfJpN1sgYgskFGlJ70o09G3Ml/EritqQi/Vr9glDNS0LVLxO3/ReymsVBX3A/5po5zJOR0Yt8g8881ibSMvoxxMmoUaMyrq4u2WCNjKGYRaAhuUj7OvgSqYnkRdyLZGUuRxzhVtRZADa+nMeJsG3cib7I07h7FLYvzamwHQTG3jaXiTJZJDfenGWRzjzW6E3LvMEQcQ4Pj6Bt2xa4u7tmg0UyhmI2gYY3Iq0USvwd/bkV+WZpzOKugkexN3kcF0AB2yI0du9GnDaWw6EbiZNiqOvanrpu7dgbspxncZabViQvNZn3kEPexmENIm2Kzy03rUhn6P1rxYr1zJ5tXFejjPkw+yTlAj+/w5XT/3Ft2jWqulVNtq+eZ3U2P39ELdfWFLArSknHqlRWNcRO4YCz0h1XG09KO1bnWuRJfOyKJdbTSGoUKK0yqXtu+nHndRJu9tYgPDkFed609ZAZ5+LDDwej1WrNaI2MMWRLFhGtVoMWLQdfHeR4yHHsFHYohIL70fep7dqGAnZFE8t62iafKF/PrQMbX87jwOu1CAS2wo5b0eco41iDUo7VcLPxwkHhbBa7Ze85Y/LC/FhZqDOPJb8X8vz2zN27goKes3nzTj74YJAZLZIxhmwR6Eq1mjN1/i5ioiOIjYkiNjoStSqO/uVr4OVTJN26J9/9mxYefXkSdwcFSkLVL2mf739cijzMybAdRGsjKGjnj6syHxpUVHZuhL3CKVkbkiTxb/ACfO1KUMetrUE2y+IskxJZqDOHJb3pvCzSht67EqJ9Gk1XXFzM4+TIZI1sEWiFUolf8XJG1a371xBOvvs3+WwLJtveyk63ZGVQ3H0iNK8JVb/keuQpojThNPHokVhOLcVxJHQTr9XPaeCmm+MXqQnllSoIlRRHCcfKqY6ZV8Q5L9/EskJKwZGvYfrkxCjLXcVVsyw5aW4MuXel7Ibz8ytE//490igtY0lyRKLsBJHWR0E7/8S/q7o0Yf2LuQTF3aegnT9BcffZ+WoxAP4OFRND6Zcjj3AjSrdco7PSLbF/O6vCLPc/501kwc4YS4h0XnsANUacAcaN+5ymTevTpUs7c5glkwVyhEBD+iKdgI2wo5F7Vw68Xktpx+o8ib2buM9NmQ+1FIeNsKO4Q6VEgb4edYoojadZbc/t5EQPyZzIgq0fS4S885pIp0daDsSXX05CqVRmszUyhpBjBBp0Im0IRQ/W4/H96zSt+D5Lp48nVPOSS5GHuRR5mLqu/+Nk+Buht6GASWwzxnuWRS1vIAt2cnLKA11Wwtz3osOyNR93Rt6zvvuTTyEvOnRuREDAE0qVKqqnloylMes8aEtRq2knugyeSMVazfh2y1mauI2lqnNvCtiW41S8OHvblqWh2wj87N/cLLWSmlvRe9BIKkuZLpMHSJhnnZfnW2fnQ0pevcbp0al7U/YcWUjR0m4sWbKKuDh7HBwsu+qgTGpypUCnpN+qMXjYFKacYzv8HRoCUMy+LjbCPlk5CYmncZe5Gb0LSdLNCdRIKh7FnuFg6A+8Ut3jetR2VFJMsno5ue9ZvnlZnrwq1jlBpHPCbzuz3rO7hwszvh9JixadGPrhOH744TO8vBTY2bmiVNqn0YqMJcgTAg3Qd+VohBAUta+Nr101LkWuJ0LzJvWoJGnRSmoAXqhuEa0NJTD2LEfDfuVuzGEALkdt5LnqBpci1lnkHGRyP3lNqPN6uN8StGhdh//+O8SVK9cBUKlUdO78Nq9ePcXWNuu5uF+9CiE2NpaoqGju3rVcFsjcQJ4RaNCJdN+Vo/ls07/0GT2NsxFLCfTdx1fb2/PYdz/Hwhcklj0d8TfBzjf58q8DLNh+n1krzlKqYm0A3G38EsvlhCfsjMiqIOQlQcku8pJQZ5dI58brmdWZJ89fHMXW1pYvv5zElSvXuH79plHtSJJEaKjOlr59P+TZsxc8eBDI11//kCX78jp5SqCTUrelbt7fnesXadKwFXduXEq2/61ew3ir11Cc3Ty5cGwnru5e1GvVE+9CRTl+Zwl3FVezJM7WdrOwNntkdOQVobZmkc4ND+FJ2b/nFE2bNeRlsG4mS0jIa6pVq8zBgyd4+PAuq1ZtYubMnwH4+++VPH36jNDQMNav3wrAjRu3uXZNt67C1KkzefUqhCNHTvLRR58CsHPnKooWLUz58qX566+fs+WcXkfZ8zDYPUuvoFDrW8krR43iNiVKpe7U2/cfTZP2b+OerwCR4a+5ffkE21b8zO61Om96zcIvAChetir3bl5k7CdTcXVx4KMvOjD94++IUb/E172JpU7D4uQF8bAG8sJ0oZwyujunE/o6Aju7GBwd/Xj9+hlt27bn7NkzTJo0ipiYV8TExPLqVUhieSEE0dEx3Lp1B4ArV25gZ2dLhQplqFOnOjY2NjRsWIcGDXQRRoUiz/p9JifPCvTLoIcA+PmXxT2fbqqVs6sH1Rq0pVqDtjy4dYn5097BM78338/5iqioGNzdXKhRpSTVanfhQcCbtaqDIy6ikVQ42nrjZFcIpcLOIueUVXK6CHh55cPNzZX79x8iSZKlzTE5eSHVaHaIdHZ9z7NjqlVxR7d0w9z6vP9Ld+ehUkXw7NljChTw4/TpQ2i1r4mJiQPAwcEeX19d5sYhQ/ol1vv009EA9OzZKXFb586GpU6WMY48K9AhL4MAuHR8NzUadUi1v1iZKoyesYIfP+3L5i3/cefuPc6fOIyERGx0JC7uXkSEBtOk/QCKlKqMRqNm1fypvI6+kdiGj1sD7JQ5a33VzNy8rMXbyZfPk4UL59CseSPCwyOIjY1jwvjP2L59j6VNMws5/UEqr5Cd86BBN+Nky4NRvHwZjJdXvgxX+5s3bxElShTl7bd7ZZOFMpklzwp0sVK6HNwn/9tElfptqNGofaoyfsXLMfLLf7h8ci+lqrag+4czUSgUhL8OxqdwiWRlty7/CYB+Qz7E1saWnStPYavQ36dhLcKWFoZ4atZ0DitW/sGVK9fxL1aNqKgomjZtyLLlv9G+XW8uX76WcQM5kNws0tboRVt7bu7ncTdo9LYXAEOHTmTy5NHUqFElzfKSJPHZZ+PkJSatnDwr0HYOjoybtYagwDsUKVkpzXL+ZariXyb5OtZOLu6pynn5FMbRyZWmjevQp1sTmA1VSow0ud3ZiTWJcFpUqFCW0qVL0L5d78SbzcGDR/l1/p+89/5ARo/61MIWmo/cHPKW+6MN43rkSbztCrPm1neJ3Tpr1y4iIiKSu3cfUKJEsVR1JEmiffv+rFnzB66u1jcwSuYNebo3v3TlujRu1x/vQllPc1e9QVuadhrM0Hf/x+//bOdFcBiX7s5LVU6+6ZgWX9+C3Lp1J5UncP36TQr7+VrIquxF/k4ZR264bh42Bfh6Xz/s7Oywt9clGRFCcPLkOf75ZzUAa9duRpIkTp06z+zZvyCE4Ntvp8rinAPIcwJtjpCOWhXH4R3LObpzJQCTxoxm5bp9qcrlhhuCtXHp0jVq1KiCl1fyNIUdOr7F6dN553rnxu9WbowMmIpXqiBuRJ2ikH1xihUrkmp/q1ZNmD59IpIkcfToKSIjoyhcuBDt2rUEoGpV6w3Xy7whTwn0jlVzGd2tLLvXLSQ2JsokbQbeu87Xw9tw7+oxvv9pNgDfzZ3LyPe7mqR9mfR5/vwFf/y+hO07VtO+fWuqVa/Md99/SePGDfj9938sbV62Iot05smp18xO4YCLMuNV+IQQ/PTT17i4OOPrW5DKlStkg3UypiJP9UEHB96kY6cuxL28wYzhrXn304UUK105S20KBFqtBr/ChendtQm9u97WWy6n3ghyAlOnfsONG7cYP2EEnp4e7Nt3iGZNOyabyykjk52YewS3k8KN59pHxGgjzXocGcuSZwS6fjkPvEZ+yLTPP+PMyd1s+ncfo0YNof+YHyhWugrOrh5GtetXvBxT5u9kTPfyeK5bxq2As3h7Jf9xyuJsfpYtW8uyZWstbYbFyc2juzNDhQpl6dSpLSqVig0btnL//kNLm2RStGgI14Qw63Q/jh07TdmyJVN188jkfPJEiDufiy2lCjnxMNaHuwG3WLl+O82aVWHx4r9Z8+sUPu5bjZCXT41uP/TV88S/O3b9AK32TZKMlOIsSRo02kg0mnDUmjDUmteoNSFotJGJK2jJyGSF3PZAmNkHjilTxrFz1zrye3tRzL8Ix47v5J0h/c1knWWwEbbsf/Qbbm6u/PffEZ48eWZpk2TMQJ7woIt4O3A3KBpndx96vP8ZM2b+zLD3rpE/vzf5PL0ICw3Bxta47F9qVRzT3msKQK0mnbhy5gAr1/9HbJyKvt2bJSsrSWrUmhAENkhoAQnQJu7TEgkoUCrdUIicmY1MxjrIq550tWqVeO/9QdSs0ZwXL14CMPfn3zh6bCc7d+wlKOh5Bi1knexIUPLj9QEAREREMmXKWLMfT8Yy5AmBjlNLONjpggWN2/Wncbv+xMXGUKGAivuPnhIqChgd4raxtWPKvB38M2csZw5tobB/GSZN+AS/YmX4feHixLmJkhSDRhsFKJHQIIQdAgUIJaBF0sYioQa0aDSvkYQTCoVzhtmAZGTyAobOi+7atQPLlq5JFGeAO3fus2PHXjp0bMOfi5aa08wsU9w149/7qFO6aEBMTCzNmnXlv/82ylOmcil5QqDvBkVRt4w7BT3sCHqtyzfr5+1Go1rePInxwDlWk6X2C5eowJT5u7h/6yLnDm+jRPmaVKnXmiU/jEN95QJCKJAkLUqFC1ptFAqFKwpFioXRFc5Ikha15iUCG7RSFJJWi1LhKou0jFHkRS9akiS9izUoFIo087Ob8joZ6z0bIsxJiY2Nxd7ejiNHtuLgYJ9xBZkcSZ7og45Vadl3MZg2Nb3pXKcAHWsXoENtbw5cfkVUFsU5Kf5lqtL9f5Op1qANCoWCQeN+YPi031EIe2yUHigU9khoEUKpt74QCmyU3giFAwJbJCkGteZVfP+07uZSrXpl3v9gEG3btkSp1N+OjEwCuak/2hAR3bBhK28P7E3BggUSt5UtW4q2bVuydcsuo9s1J5kVZ4DPP5/Fhg3bZHHO5eQJDxrg0csYlv33BD8v3Rf6yatY1BrzrnikUCioXLcl87ZeAWBU59oIYYtWikMp9F96IQRK4YQkHNFqI9FKUWi1kShtbFi5cgm1aldn796DDBzYh+++m06HDn15+DDQrOchI5NTuHz5Gr/M/Z0zZ/9jw4Yt2Nvb07lzW8aNncLz5y+MbtccebiNEWZJkoiJiWXKlLE4OTma3CYZ6yJPeNAJaLQSD1/E8PBFjNnFWR9zN5/W9TuT8bGFECiVLtjaFMDWpgBjx47Bzd2NCuXrM2zoeJo07sDSpWtYsHCO+Q2XydHkNS/6++/n0axpR+7euc+lS1epWaM5y5evM7ttmQlvGyPOANcjrjN58je4ubliY5Nn/Ks8i/wJZxP3b13knzlj0UpRKBUema7fp283Joz/HJVKlbjtp58WMuHjkeTP78XLl8EmtFZGJmcTEHCPn35aaGkz9GKsOKu0Kn69+iUREXJykrxCnvKgLclPn/bj2eN7ukFfiDQHrKSFvZ09UdHRybapVCrUajV2dramNFXGQiiVSjp1asukSaPp1q2DST2k3ORFWyOGes/GinOoKpQtLhsBcHPLWWvMyxiPLNDZxLfLTtPzvc/QSnGoNeGoNS9Qq0PQSqqMKwNbt+5ixIj/JdvWu3dXHjx4xJMnQeYwWSYb8fLKx/ETuxg/YQRubq6MGPkeZ8/uTzbYSUZHdg/qMlX/s7HiHKeN47Pzw9i8eaneEeoyuRf5084mHBydadH1XWyU7tja5MNG6Y1C4YBGE4pGE5Fh/e+/n0fFiuXYuWsdo8d8yO9//MT3c75i5MhJ2WC9jLn56uvJHD16imZNOzFlyte0atmNrVt38+2saSY7huxFmwdzJSYp5aKhhLOaba7/Ehj4VPac8yCyQGczczefBnSDwBQKR2yU+dBKMWiluHTrhYaG0aRxR/5ZvJKiRYtw7eoNalRvxtkzF8xvtIzZ6d69I9/Nnpts23ff/UL37h0tZFHeILu88cx4z6VcNJRy0aCVtCiEYMuWZRQuXMiM1slYK/IgMTPz/PE9rp07iEatpni56pQoX5O5m08zqnNtQDf3WSEckLSxoEw/vWdcXBwrV65n5cr12WG6TDYiROpxCZkdp5CXMDSzmDVgqDiXckmek2Hb8+MoELR3GWgOs2RyALIHbWZuXjrO6gXTUIU95Ncv3uX2lVPAG09akrRopWiEnHs7T7Nx4zbGTxiZbNu4ccPZtHG7SY+TU0TNWsio/zmj8LYx4ixJEpHqGNoVqEczr7yVCU4mObJAm5mGbfri6pGfieMGU6JMRaIiQhP3zd18Gq0UgxB2qVN/yuQppk75hhYtGrN330a++GISO3aupUePTkya9IWlTbNaLJ0BzFQkiLMkSWgliRuRD/nt4b/YCCXONnIykryMLNBmRqFQULVeK/73/kQunz3KP3PGEnA1wXuWkLSxKISDha2UsTQvXwZTp3Yrfp3/J2q1mr//Wk6NGs15+lReRtBcZFXgTeE9J/WcFz3ayrnQW5RzLsqY4r0AaL9fDm9bG0KItkKIm0KIACHEJ3r2lxNCHBdCxAohJqTYd18IcVkIcUEIcSajY8kCnQ10HjyR4hXq06htP6Ijw5k/bQivXj5l0cxhSEhyeFsGALVazYYNW/n66zmsWbOJuLj0Bw4aixzmtg5KuWgIjgtjxu2lqCUNfX1bUtO9jG4AqVDI4myFCN1CCvOBdkAFoJ8QokKKYq+AUcD3aTTTXJKkapIk1croePIgsWzA1d2LzoMmoFGrCLh6iqBHd1g1bwq+hbywUXrKq1XJyBiJOQeLZWX+c0bec4Ln7GXnxrtF2qNEgauNU+J+WZytljpAgCRJdwGEEKuALsC1hAKSJD0HngshOmT1YLIHnY0obWzp/r8pKG1suXv9HMM/7C+Ls4yMBTB3eDs9koa1T4Rcxc02+brvsjhblPJCiDNJXh+k2O8HPEryPjB+m6FIwG4hxFk9badC9qCzmcp1WtKgdS9qVS1Bk/oVef7iKAW8G1raLJk8Rl5cKzq7yMyc53tRT6noWtyM1uQNXsXacTfCOUttPIlyBLguSdKwdIrp+3AzMx+yoSRJT4QQBYA9QogbkiQdSquw7EFbALUqDldXl8T3z18ctaA1MjIyKTHH8pKQeq5zP79WyULbMlZPIFAkyfvCwBNDK0uS9CT+/+fARnQh8zSRBdoCuHsV5O69R8m2ySItI2McmY0EmDO8nZ73nFKcY7UqZgUsT3xfwiWSEi7ySlVWzmmgtBCiuNCN7u0LbDakohDCWQjhmvA38BZwJb06skBbgKr132Lj6uX8b+RMQl6/ycMti7RMdiKP5rYsSqGga8HGAInCXG7zUEuaJJMBkiSpgZHALuA6sEaSpKtCiKFCiKEAQoiCQohAYBwwVQgRKIRwA3yAI0KIi8ApYJskSTvTO57cB20B/MtU5ZOft7Bz9TwaNOnBjm1L8S8ir1okI5NbSek9A0RrYini6JP4XhbnnIEkSduB7Sm2LUzydxC60HdKwoCqmTmW7EFbiPwFi/L26NnUad6NDh0HE/gk2NImycjkesw5MC6zy0keD7nCfy/PArI4y+hHFmgzcfnUPs4d2U50ZFi65dr1HUX5Gk0ZMWZGNlkmI5P7MKXwpjdAzJjpVfq856DYV7zlXYcOPg3kaVUyaSILtBl4FniXX794ly1LZjOuV2X2bfgj3fId3x7H+VNH2XPwQvYYKCMTj9wPnf2Eq6P47cG/qLUaWZxl0kUWaDPgXagYFWo0Qa1WA7Bu0ddEhL5Ks7yDkwvd3v2Udwd9iFoTIi8zKCOTwzAkvB2liWX3i9O4KB35vPQ7dD7wjvkNk8nRyIPEzIBCqeSjr5cmvo+JjsTBMf1J9PVb96Juyx6M6FgKSVLl+fzcRYsWpkGDOjx//pIDB46g1WotbZJMDscSiVmShrcVCKI1MUhIdPxvcLbbIpPzkD3obCAjcU5AoVCgVDij0YahG82fN5k58zNOntpD585t+fqbyVy+fIRSpeRsSzKWxdj0ni9iX/P9nZXYK2zpUrCxLM4yBiMLtJUxb+tlFAonNNqIjAvnQnr06MRbbVpQvlw9+vf/gAb12/LLvD9YumxhxpVljELuhzYfr1UR5Ldzp7dvCznvvkymkQXaCvl+zQkkSYVWMs9yg9bM22/35rvZv/D6dWjitt8WLsbbOz/lypW2oGUyeQFjUnym1f/sYvOcuffWAVA0yXxnGRlDkQXaCnF0cqVRu35otTGWNiXbcXRyTCbOAJIkERYWjpOznLNYJm2sbfGPgg5eTC09SPacZYxGFmgrpVy1RtRq2MjSZmQ7O3fs5X//ezvZtrr1auHp6cGli1ctZFXuRw5zm5Znsc9Y82Q/CiHfYmWMR/72WCnFy1bj9JG9tOvextKmZCu//76EAj7e7Ny1jvc/GMSMGVPZsOEfPho5KXHamoyMPqzpIcNF6UIVt5KptsvznmUygyzQVoqnty8Am9cs5ejJdRa2JvuIioqidavuLF+2hlq1qqPVSjRr2omtW3dZ2jSZHEx2hr+1kpYobRTlXIol2y6Ls0xmkQXaShFC0KLLEAB69RnKpC/G5pkEJnFxcSxduoYPPxjL1KnfcPv2XUublCewJg80JxOiCuFYyO5k22RxljEGWaCtmF4ffsHcf2/RfsB4Fv+1hJoNq6PRRiFJctIOGRlrxcvOi/El+ya+l8VZxlhkgbZybG3tqVK3FeNnr8O/YkNKVKhAPh9nbt7exeOnh+Q1pGVkDCC7ogNRmihWP11tUNm4uLjE6NDatZsJDHzKq1chfP/9fADCwsKJi8t7Uy1l3iALdA7BwcmFZp3eod+Ib9Co1ZQv3xCfAuUpUboxIyZ8YGnzZHIJcpg7c6ScA20rbKnnUS/dOrGxsUiSxPbt+1i/fiugE2OVKg4HBwfy5fME4J9/VvPLL38CMGPGT6mmH+YEgoPTXoNAJmPkXNw5DN9iZfh68TFANz/4yYNbLPzyfyz4azbD3p1oYetkZPI2tgpbijkWY8XjnbTKX4sC9p6pygwaNJJx44bRpUtbunZtB8D//jcgcf+77/YH4KOP3kvcVqVKBcLDI/HwcDfzGZiWBQsWW9qEHI0s0DkYIQR+/mVp0mEgW7cf0BvuLuDd0AKWychkL9bm+ZdzKYabjXOy/ufz5y9TvnwZ/vrrZ5wzmXSnceN62NnlrAV0IiIimTJlLHPmLLC0KTkWOcSdCyhZsTaH9u2m96ApFPGvS9PWQwh8GgxgdB91Qdfqel8yuR9rE7uciL9jQZpu6JZs28qVG7lx43amxRlg9OgpnDt30VTmmZ2AgHt07z7E0mbkeGSBzgUUL1uddv1G4elXgY/nbMSvVDUaNOjI/0bMIOR1BBu3LaJKnUqoNSEZpg/NSIhlwZaRyZjwAU5s374PgJCQ19y//5DZsz+nWrVKRrW3ePEvNGxY15QmmgWVSsWxY6cpVao4mzb9I6c5zSJyiDsXIISgUdt+ie87D/qY2s268O/i2QwdPZOTR/7jrV4jqNN6AAumv4cQtgihTNaGsWKbUE/2umSsnaDw89nyUDnqVP9k76OjY5g06StWr/4jw7pRQ2bhVUrPQ3RJFz5ed4yZ3euj6j/BVKaanKCgFyxdupb69Wvh5ORoaXNyPLIHncORJElvApNCRcsweMKPXLl0kdBXL6jbohtV6rZCCFskSWVyO2SPOneRkx64rMnWUaf6c+3aLaZP/z5xm69vQVav/iPDRENRQ2aluc/WRkmd4j5Wm6zo7NmLTJ06kyJFfFmwYLbsOZsIWaBzKKGvnvP71x8wvIM/wzv48/j+zVRlHJ1cmTx3G9N+24ezqwc3LhxBktSk/NhNKayyUMvkdYoW9aNp0/rJtmk0Glq37pnmtKP0xDmBeiV8UCqs85ZdtmwpevbsZGkzch3W+WnLZIhGo+b8sTf5qb8e/hbD2hcjPDQ4WTmljS0+hUuyfO4klv08EaXCFYXizWhQc4mpLNI5H2vyTNPC0jbeC3/j0b6Me0n37u/g5ORIs2bJZ08oFAqWL1+Ik1PyAWJRQ2ZlKM62ZXVTq6ZvPs35hy9MZLlpOXjwGDExsZY2I9ch90HnUPJ5+zLpp83MGtM52faJ/WpQsHAJChUtTfOu71G6Uh2CHt3m0sm9XLqwj9IlW2ebjXL/tExe4W7UXYo6FKXavTooUni5hw+fYO3azQy/X5SQFPWKehl+jH/+1wqAsCzaag6cnZ1wdHSwtBm5DlmgczD+Zaryyc9buXnhKIWKlubs4S3cunSc/gMH4OzizE8zhvHeJ/O4efEYvkWK4+6W+ekdpqCga3VZpHMo2TWwylq4q7hKCW3FTNc7G3qWQvaF8LD1YG6dFYw61Z/w8AiCgp5Tv34t7nxyCjIhxinZevE+MWo1PWuWMr4RM9KsWUNCQ8PRaDQolcqMK5iY4DgFARFZO25gjPUFlGWBzuEUK12ZYqUrA1C5bkuunP6PxfOn4OTsSvjrl6z7/UtsbG0pWqwov/65xWJ2yt60jKkx5rtkrgeObgXfzHnWSBp+rr2c0tN9uHz5OpV3ecRnFIs0uv1iXq7EqjUmsNR8DB06gUmTPjJ6KplMamSBzmVUqt2cL/74jyf3bvL61TPyefuiUCg5feBfpkwYh1LhhkJhuVCU7E3nPPKaF20M96LucSHsAr0K9WL109V09qkB32upjEdimbsRzpRwMU6kKxf24tS9Z7wMj8Ya84lJksQ///wij942MbJA5wIc7RRULOaKt5sd4dFqrj4Mx9a2CkmXi/crXg4nF3c2/j0TIewt+kOSRVomt1HauTTFnYoD0K9Qv/jfV8Ye78Ngd4p6GbYIxp6rj2ha1pcqWTHUDDx5EsQHH4xn8+alqfrfZbKGfDVzOK6OSno0LIiDrYJrjyKIjtPQua4PvvnsU5Vt3L4/Alu02ggLWJoc2SPLWVjbA5Ul7LkXnf7wLBuh83fM9fA7pWMtGpX25ei0sVY1H7pQIR9+/vkbWZzNgHxFczg1S7lz41EkR66F8OB5NGcDwjhw+RUNyqdeRcfR2Q2F0hmtZB1rzMoiLWMJrO1hIyNUN9942GqNljU3H6M+ssSCFr3hhx8Wcvz4GUqW9Le0KbkSWaBzOH5eDtx6ouvXWvbTRIa1L8bPs6YhNDE42Kb+eAW2gIRaE2oVT+GySOccrEXYrMWOBJLOhTYFwQFpjxGxUSpYPKU3rk72nF8y26THNYYmTepRpkwJS5uRa5EFOocTq9Li7KCbXlCxdnOcXNyJC39Kk8YNePHsaarykqRCqXRDkqwnqYAs0jkHaxNHc3BXcdXSJqSLdDOQ+0EhrDtwGffL6yxjgySxe/cBypYtRf78WZg/JpMuskDncK4/iqBuGQ/sbARV672Fnb0D382YQqcu3fl2XDd+/WIIL4MeJpbXaEPRaF6jUDhb1YhLWaRl8gJ3I5xN0k7Zot7MG9uFgMCX3Lv3wCRtGkpC5G3Xrv+IjbWeB/3ciCzQOZyrDyN4/jqWAc386FK/EP5FfXnyJIiJ4wfxzczpeOVz5dC2pYnllQoXBLYohGWSlqSHLNI5A0t60aY6dnacg6GJMx4Guxt9jP3n7nLp0jWj64eHR/D33ysBOHPmArdu3Um3fGhoGG3a9CEuLo45c6bL3rOZkQU6F3DsxmtWHXrCuTuh5C9SibkLFgMSfbs3pU6dmjx9eDuxrBD2SKiQrGSgWEpkkc4Z5IVQtz4yGsmd3XzQuQ5durRDrVZnql5YWDiPHj3Bzs6Wx4+folarefz4KQEB99Bqtfzxx7JkbYaFhXP06Enc3d1YsGA29vapZ4nImB5ZoHMJ0XFaHgfH0mHQJ9y8cZ1+Q6aiUmto2rAa184d5sXThDCY0L2sKLydkuwSaWdnJ4aP+B+rVi1i7i/fUq165Ww5roxxWPNDgakHimWG7dv38e67ozMc9ClJEgcPHkOr1bJnz0FWrdqAvb09U6eOw8bGhi5d2tG+fSsiIiJ59uw5SqWSnTv3c/LkOYKDX7Fly24AecR2NiILdC7DwcmFcbPX8fBhIP8b/g31apVj2JgJzBrbhYiwEEC33KQkWXfaQHOLtJubKwcObqF5s0Zs2LCVwEdP2Lx5BX36dMu4sgxg3YKZVUw1UExfmNuQfuiUI7mTTrVKSmhEDM7ODkRGRnPzZkCyfVqtFoBjx06zZcsuhBAsX76e589f0qNHRz7+eKTeNt3cXJk6dRxCCGxtbbG1taF48WJ8++1nGdotY1rkTGK5EAdHZz6Y8hs/TOzF9Fn/8PXU/7F+zRoundyDWvMahXBEIaw/RGXOjGPDhr3L9Wu3GDRoWOK23bv3s3nLSjZu3EZcnHV2AVgb2ZUG1BzfA2tKYZqZjGJJCXgczOEbz1m37k+EEHz//a8UKeJHly5tqVatOZcvH8TFxSkxXP3773My1X7Llo0zbZOM6ZA96FyKo7MbH372B4t+ncfTZyEEP3/C0h8/RqlwRal0QQjdR2/tXpC5bqAtWzVl6dLVybZduHCF589fULlKBbMc09LY29vTu3dXxo8fQdOmDTOuYCDW/h0yNWn1Q2dnmPvivgt8v/IQNcv6JXq7AO++24/mzRvi4GDPmTN7sLW1pUqVijRpUj/bbJMxHbJA52LyFyxKuWoNmTr9VzzzF6JWk46A5ZOTWAOhr0Px8fFOtk2hUODllY+wUOsaCGQKSpb059LlIwx+px8FfLz5+ecZbNu+GgcH0yycYk6Rzo0PAMaEuQGuPA7mYXA4vu7OlCvmnWp/vnyeFCiQHwAXF9NM6ZKxHLJA53Kq1n+LDSsXU7ZqA8LDQtBKKkublGnM4UX/888qJk0aTcGCBRK3TZgwkvv3H3L79l2TH8/S/LpgDvPm/UGH9n2YNPELatRoTlRkFGPHDsu4soHkNiE1Zz+0PjKabqW6Gcq+64Fce/qK/K6OdPByJbRyT1OYKGOlyAKdy8lfsBgubvm4duYA929eQJJi0GpzXv+qqUV669ZdLF++jouXDrN12yquXj1G9x4dGTTQdIJlLeTP70X16pVZuODvxG1arZbvvp9Hz16dTXosU4u0Me1VqlSeJUsWcPXqMXbsXEv79q1NahNkf5hbpdGy8to9RrWsQttKunXqwnqOMcuxZKwHWaBzObcvn6Buo2bcuv4fV64cBkCjfY1WG51YJrd5Poby7bc/UbFCA+bPW8SgwcOpV/ctHj16bGmzTI5CoUCSpMRRvQloNBoUwvS3AEsmE6lUqTw7d63j3LmL9OgxmD8XLeXHn2YwaHBfk9hkLFkdzf0iOoarL18n9jXL4pw3kAU6lxP06DYNG9ZBoRDkz+eKjVKX+UejDUetCbOKBTMMxRyh7pcvg9mxYy9nz1wwedvWwvPnL7h27SbvDOmfuE0IwZjRQ9m4catZjplVkTa2/qRJo/nuu7n89NNCbty4zbp1m+nT512++GISSmVqkbS2h9O0wty+Lk583aQ6qpuhsjjnIWSBzuU8unuNEsX9eBUSDoAQSmyUXghhiyTFoNYEW9jCzGEt02JyGiOGf8zUqeNZvfpPPvtsAkeO7qBIUT/mzJlvtmMGhZ83SgCzIpo1a1Vjx/a9ybZdOH8ZhUKRbLyBoaTXD53ZMLexXjTokox0Wb+fZ5HRGReWyTXIAp3LEcA7/QdSveZbHDt9Q7dNKLFReqJUeqJQ6HJyW5snIWNarl27SeVKDdm1+z+USiUzZ/xIi+ZdiIyMMvuxM/Pdyur38NGjx1SsWC7Ztv+3d9/hURVfA8e/s5veIKRRQgkl9F4VpIMUERCQoljQH4IdCzawvIJiAwURREFBUVERBJUiiKggUgTpJUCAkISQXnZTdu+8f4SEJKTspm12M5/nyUNy95aTwp57ZubOBAUF4O7uRnx8YpnOXVkKVtFxYW4IIfi/WzpQy81VLVBRjaiJShzcC4s2oZlNHNy9mbsn/Q+zZkAn3BBCh044g3C2dYhWq8gJTBxZamoaK5Z/aZNrF/x95bSElPfv8cNFn/D2O68RFnaeI0eOExgYwMfLFrBq1RqMxsqrPs+nSEK8LZtO91yqJ4290krcr31gLa4a0rm1/xh27lyPk5N6+3Z06jfs4HQ6HTqdC1373I53jVr8vXUNe3/fiF5XA53OxdbhKdVURd1gbdy4mYBAfzb+9DWapuHl5cmqVWt48YXXS33Oc7pjNNZaF/raeWMyIe4+Fp8rLFVPU6+Sp9ktamaxAA83tvdvh5OTEyaTSSVpB6eauKuRFh16cf/MRcyY9zVmLQlNS883SMyeqlLVF60UZcXyL2napDN9+4ygUcMOPPP0bLKyKv/5f2seuSqpLzrvpCW+bq6smTCZuXPfL21oip1QCboaCm13E0+9tQazZsCsWT//r6JUdSaTiYsXIzAYSu5jL+uNqbVLUFo6cUlxxjZvyJxmZT6NUsWpBF0NJcZGU7dRc95dcwAps/JNXGJPVbSiVHVlqaILGyyWw8vFmSyzxiNDhtukdUCpHCpBVzMXw47wwj3dWfLaA3h61+SxOaswa8mYzal29Uw0qGZupfKU17SfOcqjivZ2c+auHqG5k5colUMIMUQIcUoIESaEeL6Q11sIIf4WQmQIIZ6x5tiCVIKuZn78/C169Lk1d9KGVp1689bqvUhMmM2JSGlWVbSiWKm4Zu6yPBddXBVtOp1Mf6ca7NlzwO5uru2VEEIPLAaGAq2AiUKIgsvfxQOPA++W4th8VIKuRs6fPMiVy+d4fuZ0oiPOkRh3BQAf3wA+3HgKoXPBZI5Hk/Y3V7eiVLSSqmhr+6LLgwQ++eQLEhISK/3a1VQ3IExKeU5KmQl8A4zMu4OUMkZKuQ8o2PdQ4rEFqQRdjeze+g2T7rmXPje35p4HHuStGbdz9vh+IPtxrMU/HUev88FsTiYqeZ+No7WMauZW7EF5VtF56YRg5coPcXV15epV+5oVsDzFZ0jOp5TtIzJNArQUQuzP8zG1wKXqAZfyfB1xbZslrD5WJehqJDb6Ih3aNQfg9Zem8Ma8OXw85yF++nI+GenZo10//Okwep0nJnMSUmrFnU5RlAJK09RtrYLrRPt8/z4bN25l2bJV5XL+au6ElLJLno9lBV4vrMPf0l+s1ceqBF2NGNNSqOV7fVKFiWP6sH37D6RcPc+L9/Tg7LHsqnnRxiMIoScy+W9bhaoolcrScRflPVgMyl5FA0x1CufFF5/k3LkLXL4cVa7xKflEAPXzfB0MRFbUsSpBVyPGtBRq1fTKt61Z4zr8+O17zF80n4/nTiPq4hmEELy46Ec0zaCqaEWxUkUNGMsrbxWddSp7LoMaaz9gz/zX2b3bPrqn7NQ+oJkQIkQI4QJMADZU1LFqnrhqxJCazIA+ExGFrAEcc3UX0Vdmsujle3nmvXUEN25FaNuuxJ27iodLkA2iVZSqqbipP3MUNwWoNfN051XU9J95TevbhkuD+hIREUVwcB2rr6EUT0ppEkI8CmwB9MAKKeUxIcS0a68vFULUBvYDPoAmhHgSaCWlTC7s2OKupyroakJKidGQQuHdIBAY0JMnHhrNHeMnsPiVezEaUjh77DjxhuOVG2gpqIFiiiMojyo6eeyTHDt2ivnzl5R/gAoAUspfpJShUsomUsq517YtlVIuvfZ5tJQyWErpI6Wsee3z5KKOLY6qoKuJrMwMhBCIIhI0ZCfp6Ct/ERUZzdPjOqHX+SC1VKKSD1DHp3MlRqsoVVtFVdElLaZRXBWdPPZJAG6+uSs33dSl2NgU+6Aq6GrCmJaMu2fJq+7UDurF5vVbQWpImYHACSlNlRChojie8hjVbUkVbXzpFQBWrlzDkiWfqdnFHIRK0NWE0ZCCh6e3RfsKIdDpPNG0dIRwQmJSs4spSgGWjui2NkmXNA1owRHdOckZYOTIIYwcOdSiuJSqTyXoasKYmoyHl2UJGkAIZyRZIPQMG13sZDeKUm2Vx2NXliTpoqpoj8+ey/1c0zSOHz9NnTpqUKejUAm6moi9comg2nWp7d3RokFVQuio6RfEuIee5eKFC9mjvFUVrSg3sCRJl2Ya0OKS9MW4GvmSM0B8fIJq3nYwKkFXE5fPnaBV6xYW7x9zdRdtO3YjMS6GqMsXc7cpiqOq6BvQ8pxlrMWGafm+jo6OISUllS+++KhUsSlVk0rQ1cTl8OO0vzbNJ1j2aFKr1s3Jykwn4Wo0GRnZ874fPvdhhcWoKPaqsvqjz6V65kvOmzf/hqZpbN36O7t27bUwWsVeqARdTVw6e5yunSyvoAGaNmlA4tXL1PAL5PTZ6zPSqaZuRblRRSXpvIb9Njn3c5PJxKZN24mLS+Cee+7k7rvHWRaoYjdUgq4GUpLiyMww0ryJpYuuZAtt2oCYyHAC6zbi5JmLFRRd2akbBqWqKI8kXVBYqp6wVH1ucs7IyOCxx14gLc3IBx/MJSDAr1SxKlWfStDVQMS5EzRs2hKdLv/gkZKaudu0aMDVqIv4BdXnTFj+BK2SYvUlhGD06OF89vmHLPvkfQYM6G3rkKqUsibpnCraaDYCsC12G72XtSMjI4Ply1fj6urKsGED8fLyKJ+AlSpLzSRWDVw+f4LQ5tY1bwcG9CTm6i6C6jUkKeEqx45nb1OUz1cupnnzpixbtgo3N1cWLpzHDz/8xOzZb9g6tCrDkpnGoOjZxv6Nj+Y/wyYORv5KzwOtCQ6uQ1qagdjYeACGDh1Q7jErVY+qoKuBxLgoGjUMtvq4wICejJ80gauR4fzywxqkzN8/pqro6qdfv1vo0L4NfXqPYMXyL/lo8XJ69RrG/VPuomnTEFuHV2bl+Tddlkra1zmIf8J/BqBz5/b4+/tRq5Yvzz33WLnFp1R9KkFXA6mJcQQGFt5PVVIz94I3FhF96Swg0aSxAqJT7MmgQX1Ys2YdGRkZudsSEhL56actDBjYx4aRVU3ndMdK9Zz0gYA1xMcnVlBUir1QCboaSE6MJSiwVqmOFUKHTucJSDTNgMmchKZl5FbTqoquXpKTU/EP8L9he2CAP8lJKTaIyD5Yk6QXnLiL779foQZ/KSpBVwcpibHUqV36/+w64Y4Q2ZPyS5mBWUvCZI5DSq28QlTsxDff/MCECaNp3/56/+qAAb3p3qMzGzdutmFkVZ+lSXpUoyUEBvqzfv0m3nzzg0qITKmq1CCxaiA5MY66tYuuoGt7dyy2EhZCoNd5Y9aSkTKnaVPDZE7A2Und5Vcn4eEXeezR59i85XsOHz6Om5srDRvWZ/ydD5Cammbr8MpFdMrBCltjPCdJlzSAbFSjJXx2cCK9e99UIXEo9kFV0A5O0zRSkxOoHehbpvMIIXDS10Cn8wJAJzzQ6bKratXMXb2sXbuRJo078/6CJfzfa2/TrGkX/vprj63DsiuWVNP/d/PPaJrGd99tqISIlKpIJWgHZ0hNws3dE3c3l3I5nxDO1/51Qq8rep1axbEZDAY2bdrG9u1/kJWVZetwyl1l3HRakqRfvmUtly9HVXgsStWkErSDS0mMxcf3ejN0Y611oc1r1jfpqRVzFKWsikvS543JeOi9ufCxVyVGpFQlKkE7uJSkOGr63jjq1lIeHh4EB9dFr8+etF+Q/a/EnG8/1cytKKVT3KNY543J7E/5leENn6rkqJSqQCVoB5eSGEfNWtY/YuXi4sL8BXMJv3CIv3Zt4vSZfUyefCdCZP/JSGkq71AVpUqp7JvOopJ0O89baOzejqmhH3HxYkSlxqTYlkrQDi4lMRZ/vxtHWpc0ivTtd16lUcP6tG51M40atmfMmHuZ/fKzDBkyAGenQPQ674oKWVGqjKqQpC9nZOIknInIOMMjvT9ASsmqVd/eMLOf4nhUgnZwKUlx+Fs44UFOP7SXlyeTJo1l6tQZXL0aC8Chg0eYPesNHn3sf0D2qG5FqQ6qSvdNc48uNHXvwGMtPuPYsZMIIfj009Vs2bLD1qEpFUQlaAeXlhRHYKB1fdABAf4kJSUTGxuXb/vRoyeoH1y3PMOrsnQ6HQMH9mHqQ/fS46Yutg5HqUYKq6LzTgXqrHMlc0MTZrRcTdeuHWjTxrqFcBT7oRK0g0spZprPopq5L126jIuLC23atMy3fejQgRz4979yj7GqCQoK4J+9v/L6nBdp374Nyz9dyMafvsbd3d3WoSk2Ym0VHZ1ysMgPS5SUpHN8PuEQBoORqKgrVsWn2Ac1k5iDS0mMo3aQHxPum4XRYCRLq4uLrvh1ZE0mE6+//g7fff85Lzz/GsePn2L48ME8OWM6gwaOrqTIbWfBgrls3bKDl16aA2RX06tXf8zzzz/BK6/Ms3F0iq3kTa4FH0u0JoEXd568LFmyMsRbsHHjVtq2bUmdOkEWx+BoErIyilxf21LJpqo3E55K0A4uKTGWs+cv89eOrdTLCiEi4y/aeY7FVVf4s5U5035++skXxFyJ5ZFHHyQ4uC779x9k8KA7OHHidCV/ByUraapSa7i6ujJs+CDqB7fN3aZpGnPnzuf7tStVglaA8uuXtnZa0YLrR59PkSx4alq5xKJUPSpBO7jE2GjmPf9/dPYeSJMa7Tic+ieH0tbQ3nMcbrobF4rPa8OGTWzYsKmSIq0a9Ho9QggyMjLzbTcajbi6ls9sbIqSV06yLyxRW1JFZ2ZmMm3aTD79dD46neq1dCTqt+nAsrIyyMwwUtctkMZu2RVhO69bcNfVZH/KF0DJj1tVNwaDgd279zHlgbvybX/4kQfVak1KhSqqKi/YH12wKdfFxYW77x6DwaDWa3c0qoJ2YKlJ8QDUc+4AgJQSIQSNXHty0PQVGVpqkU3d9qY8m7lnPPkimzZ/x803dePAv4fo3783IY0aMGCA4/e/K7ZlbZN3TOZFXnnlbV57bWYFRqXYiqqgHVhKYvYzzHXv7sjXiW/zbep8Djb6C5fuRpyure+s3OjkyTN07NCHPf/sJzi4HmvXbqRbt0G5z4QrtqHT6ejTpyejRg3D3796LXNa1CxjNZz8ufPOkZUcjVJZVAXtwM6fOgTAnm3fMm/+u/Tv3ZHN2/ZiMKTzwVtP8NzAwpexK89q1F4lJibx0eLltg5DuaZFi2asXbuSlNRUoiKv8PGyBbw17wPmz//I1qGViY+PN/fdP4muXTpyOTKKFcu/5PTpkqvo88ZkojJ30tKjG61bN6+kaJXKpipoB9a8/c0MGf8IURfPMn50HxoGB/DQfcOZ8fAYmjetx/rw6bYOsVxZvyKXYg+EEKxZs5x331tMj+6DGT16Mh079GHqQ/fRr98ttg6v1Pz9/di9ezPdu3Xml19+JTMjkx2/b2DgwD6F3iAXrKJDPTrj7WT9PPuK/VAVtAOrHdyERqEdaNrqEB7urkXu11hrbdHatIpiC527dADgsxWrc7dFRkbzwQdLmXzPnezY8Welx1SW56BzPP3MI/y2408ef+z53G1//LGbDz54kzZtehbZH61JM1GZh6kr2+Pv7Gx98IrdUBW0AzNlZbLxi/eYNGmsrUNRlFLz8fYmNi7+hu1xsfF4e1X+IMfCkmZt745Wt+AMHtyPlSu/ybdt27aduHu406hRgyKPM8tMTDIDEGWenEOp2lSCdmDnTx5EJ+Ch+4Zbfay9Nhfba9xK0f75Zz+tW7egRYtmuduEENxz7wS2bP2t0uKwJAlb8/eXlJSMv1/+Jmo3Nzc8PT1ITS18Vquz4ihCCBq69VAL1lQDKkE7sMB6jYiPjbZ1GIpSJmlpBp599hW2bF3LCy/M4N77JrJ5y/e4ubnyxapvbR3eDSytpletWsPsl5/Fxyd76VYhBLNmPc3u3ftynxgo2HSeZU7muOHn8g9aqZJUH7QDq1EriIx0A6lp6fh437jQw6hGS3I/d6R+aDUK3fF8sWoNRw4f4557J9K8RVO+/GINa9asJzMzs+SDy0FpWmZyjinqb3Hl51/Tpk1LTp3ey56/9xPavClxcfGMG3tfked0caqBs5cPqKWgqwWVoB1YVlYGUkq8PG985nlGy9WFHFF6qmlZqWiHDh3l0KGXbB2G1Yq6YZRS8szTs3l/wRI6dWrP5cgoDuw/VOL5ktLPkOIUgLe++i6OUV2oBO3A0pIT8fSugU6Xv6+qvJNzVaSqaKW8lMfNZ3HVdEREJBERkRafy905EDdRo8wxKVWf6oN2YElxV6hZKyDftrzJOe+qOIqiVLzSJPuCSd1F78M5HH9ddkUlaId2NeoCdYMblvp4e2+2tvf4FduriL+h0jySlZdJM5BsPFuOESlVlUrQDuxq9AUaNCz6ecqC1MpWilJ5SpuknfVe+Hm1L+dolKpIJWgHFh99kSaN69s6DEWxS5XRAlOaatqspROfdtRhnrpQiqYStAO7GnWBpk3yV9Ah3oIQ7+uDxhy9H1o1cyv2oLhEXXC7Trjg7qJGcFcHahS3A4uJukiLUFVBK4q1bHVjV9Kz0wBC6HB3DiA1I4IzzpXzHLhiGypBO6jMjHRSk+JoGlLH1qEoimIlS24QpDQjMVdCNIqtqCZuB3Ul4iyBdRvi4qzuwVQzt2INe/l78XZriF648fDDMwkPv2jrcJQKoBK0g4q+FEaDkCZWH1dwJLe9vFkpSnUkhGD7T5cJDq7L4cPHiIiIsnVISjlSCdpBRV8Ko1mzpvm2/dL/i9zPq9NAMUVxZK5OvnQKfZJ//z3C4cPHkFKSlZVl67CUcqAStIO6cimMli0a536dNzlXR9W1JaBt21aMGjWMZs0al7yzYrd/J4211qx/NYFhwwayffufPProC7YOSSkHKkE7qOiIs7Rplf2mfPL2pbnbm3pVzKASNe911eLl5cmGjV+xbv0X3H33nfy2YwOrVi3B2dnZ1qEpFWhUoyUMGHAL8+bNIjMzk//976ki15bOIaXk3LkLAISHXyQ+PqHc4tE0x1t2SwgxRAhxSggRJoR4vpDXhRBi4bXXDwshOuV5LVwIcUQIcUgIsb+ka6kRRA7IbDYRExlOu1Yhucm5sVca51I9bRyZUlneevtVrlyJYfSoyZjNZlxdXVnz7XJmznyMuXPn2zq8Ksleq+eCRocsJcTdB01qJGb6sKL/j4SlheHr7Ev3WjWB7PeD3fHnqOHsTv/6rty/Zz1/3T2Ev46cRRsxknvuubPMccTEJjHx3pllPk9VIoTQA4uBQUAEsE8IsUFKeTzPbkOBZtc+ugNLrv2bo5+UMtaS66kK2gHFRV+ihm9AoWtA55W3HzovNeWnfdPr9UyYcAcvvjAHszm7xSQjI4PZs97gnnsn2jg6pSIUnFXsvDEZndAR7NqM8ymSRFMiGVoGh5MyeDPsC86lemYvKS3BVa9nU88xuOj1/K9DaLkk58wsE7ePnkYNf8unGrYT3YAwKeU5KWUm8A0wssA+I4FVMtseoKYQolTPu6oE7YCiLoVRv1HTknfMozoMFHOUCqkkTk5OuLg4k5CQmG/71aux+Ph42SYoxaa61OhCXbe6CAT3Bw8DoGetxrT2uTFvLFu2ik2btpfpem+9/zXonRk79ZUynccGWgoh9uf5mFrg9XrApTxfR1zbZuk+EtgqhDhQyLlvoJq4HVD0pTCaNCv6EaumXmbCUvUWn0+trWxfMjIy+Pvv/Uy6ayyrVn6Tu/3+++9iy5bfbBhZ1VXRN2+FtUqV91za53TH8l3nvDE598b7fIokxFvgrnentptL9v6pnjT2SuNiXA0a+CURF+aGX9N0evXqQY0a3mWK5cCB/+jefww6XeXUgPG6K5jK+PPM0CUCnJBSTi9mt8KaHQt2tBe3T08pZaQQIhD4VQhxUkr5R1EXUwnaAcVEnKV/7+w3nAZ+SQBcjKuh+qGrkZkzX2Hjxq9p1641B/Yfok/fngwe3I8B/UfZOrRqo6SuoryvV+bCF2Gp+hIHi9apU7a5viMuhNO+d9mbyqugCCDv/MnBQKSl+0gpc/6NEUKsI7vJvMgErZq4HVD0pTO0amnZYzVF9UMr9u3QwSPc1GMwKckpDBs2iPPnLtCt60DOn79g69CqBWvHcTTWWpfL2I/C+qJzP08peUR16vOzeOaZV0hJKX7kd3E++HgdKclJhLbtXvLO9mcf0EwIESKEcAEmABsK7LMBuOfaaO4eQJKUMkoI4SmE8AYQQngCg4GjxV1MVdAORtM0Ii+epUMb6597DXH3yf0P3VhrbfVdfXTKwWrTz2sPIiIiee21t20dRpVX3n+zZUm0pfl/Vxo5VXTeZu4WG6ZhNpv55ZevS33eTdsP8N68t5kx7xv0To73SJ+U0iSEeBTYAuiBFVLKY0KIaddeXwr8AgwDwgADcP+1w4OAdUIIyM69X0kpNxd3PVVBO5i4KxG4e3hRJ8i30Ncbe2XfGVv7PHTeNzGdTkevXj0YPLgfXl6qyVxRoPyq4LKex9oq+lyqJy02TOPAgf+YPPmRUl8XYPasNxk//f+o06BZmc5TlUkpf5FShkopm0gp517btvRacuba6O1Hrr3eVkq5/9r2c1LK9tc+WuccWxyVoB3MpbNHadK8FQDuc1/Dr2k6cL0vuqzat2/N8RN7mL9gDs88+xhhZw9w993jyuXciqJcV1mPOw77bTIAnTq14/3355T6PJomib58Ab1eNcyWF5WgHUzEueO0at0Kn+/ft/gYS5+HdnJyYu0Pq5g9ay7dug5k8KA76NtnBG+8+TKtW7coS9iKYtcqKpmW9rzFVdE5cp7kkFIyZcoThIWdJzDQv1TXA3jy+YW4uXvi7lm2EeDKdSpBO5jL544xQn8GAOfmNYrdt7Bm7uKehx44sA8XL0bw3Xc/5m47efIMyz/9grsnO+SITUWxW0X1Zedt5g5L1SOEYMaMaTRu3LBU14mNT6HPoPvZ8svPzHx/A83b31yq8yg3UgnawcSd30+nPm3zbSvYzJ3TD22tBkHtiLly9Ybt0VdiqFkz+2ZAPS+tVDcV3RRdXucvrIo+nnKcFSu+om3bluj1ls+NkGPn7mNMuncmLh6+vLzkV3xqlr4CV26kErQDuRp1AZNZo1GdwgeIFceSx6327DpM3369CAoKyN2m1+u5665xbPv1d6uvqShKxSqpig52D6Z7985Wn9eYnsnDT73HPXf/j6BG7ZjwyFyHHLVta6o334Ec3fcbQ3s0RwgBzYORpyJwbl6DrFNFDxArbFaxoh63irkSz/z3PmLnHz+zaNEykhKTuH/KXSQmJrF+/S8V940pSjVXXo9f5Z1dLEvLIi4zjtatm1t0bExsEpu27eP3nf+w+48d1GkQykuLN6uquQKpBO1ATh36i+cf6FPoa35N04kLc6OBX1KZZhVbteRP/vnnAHfdPQ5PDw8+/+wrvv76h9xFGRSlOqnMhWVKm6QLTgGa42xKFocN+4o9NjI6nv97azl7/tpF9OVwmrTqTGjbm7j/2YU0DG3PtWd6lQqiErQDuXj2OJ3bj0KG1EacOIO4VkVbKsRbWDTb0M6du9i5c1eRr6sJSxSl6nPVuTM0YCinwi5Tw8eTs+FRAAghyMoys/ufwyxbvJgONw9h7EOv0Si0PU7OLjaOunpRCdpBGFKTMKQkEtIw8IbXyrOZW1GUqitnkGbBG+S8VfR5YzIN3byIyDjN59Hf8GGfpYDAP+j6okxCCOqFtGTKcx/SrE23SotfyU8laAcRdeE0wY2a5a4eI1s2Q5w4k2+f8mrmtldqhLli7yy9WS4sUZ/THSPEnD2J0R9Ja4l1jaJ9j8Hc/cQ8nF3dcXXzqJiglVJTo7gdxOXwUzRuduNgD9E82KrzWDKa25Lma5UMFcW2hBBcST2Ub1tU1lFOGbdg9DfQe9jdTJ31MV41/FRyrqJUgnYQkRdO0qpVaJGvl3XSksocDKMoSunVqRPEqlVLSEoOJyk5nEWfPE9Q7VqkZ8UTZtxOoj6cLr1HMmLy05W2XrNSOqqJ20FEhp/i3omDSHZqj4/pP6Bim7lre3cssUq218Fi3t5ePPHEQwwdNgij0chXX63lsxWrkbLkAXTloaifmWqVqBj29ndaXDO3s7MzW7Z8z48/bqJ+cFsyM9Nwcs7C17cm8YYIJs94m5sGqbnz7YVK0A5AM5u5HH6Srh0Kr6ArajS3I3J1dWXrr2s5ffosM599BW9vL154cQZdu3Zk+rSny/161iSGwvZVSVvJ6/bbh3A5MoqXXnoZiUTTUtHrvHlzzmzCkzKo12aArUNUrKDaNxxA+OlD1AqoS3BdPwCSndoXul95N3PbU9VhqTvvHElCQhL33vMwu3b9w+bN2xk65E5uu+1WQkOblNt1ant3LJefX855qsLvwte3Ju/Nn8OZsP2cOPkPc+a8hIeHffRtOsqNTmhoU+bOmYtZS0PTUgEdQrjSedBIRo8Zp1aasjMqQTuAI3u3c0vfvoW+JlveuC6rJXNzWzJYzBJV5Y3P0ji69+jChg2b8m0zGAxs376zVFMiFlSRydSWidrZ2Zmtv67F1dWF4cPGM27sfTRsWJ9167+wSTyOrqgxIZfPZXDq9HGc9DVw0vvhpK/Foo37qVvLlfiUrEqOUikrlaAdQPipg/TrU/yzitaO5s6rOg0Wi4qMJjS06Q3bQ0ObEBkZXaZzV1bytEWiHj16OAkJSTz6yExOnz7L0aMnuHVIW4IC/enTp2elxlJapbmZrGrzA7z74V0kJMTz56EjrPj1ECt+PUjPlr44O+m4EGO0dXiKlVSCtnNJ8Ve4dPY4XTrm73/O28ydt4rOaeYuqoourJm7OI72yNWqVWsYP34UQ4Zk99U5OTnx1FMP4+XpyY4df5X6vLaobCszUbdv34bt23bmfh1zNXumuZDGQbRrXz43dZpmJMsUg5RasftJKSttQJ8tFbxZ/nrTTKbPeBej0UhkRDjjetZmXM/a6HWCn/bGoDn+j8ThqA4JO7dmycuMmTiZkAZBJe6rBouV7NKly0yc8D8++ugdFn34Fh4e7hw/fooRIyahacUnhqLYun/YkhH3ZXXu/AUGD+pLzNVdfL/hLwbdNo2zp46RFB+Dt48vJnMKep0PQpS+JhAie5pJs5aCk77o8RSaNKBpaeh1NRDC2apr2tuI7tSMCNKzrhLSOoSB/UfRrvtAALbvOUWMLH2rmVI12H2CllJy4cxhYi6fp223/rh7+pR8kIM4tHszEWePsfHbd606rryn/qzqj1xZm5z++GM3bdr0pFmzxhiN6URERJb62lXlzT4njopK1Gu++YFFi+byyJPP8cPaH7jtrid5ec4CurdvwsrNJ/h03qPcfHM3Frz5WJHnCAwovilcCD1CuCJlBlLKIhdq0LR0hHBF0wxITDjp/cp0Y1CSohajqGgxmadIyTjPPc/MY++O9dwx5QV6DZ1E72F3EdKy7OMlFNuziwR9OfwUYUf/IaBOQ1p26o0QArMpi1++Xsie7WtxdnYh3ZjKP7/9wMOvrqgWIxXjrkTw1Ycv8dnKpXh6uBa6T3k8E10dq+gcZ86cK9PxVSU551VR1fR/RzYwYNhYjElxHD60H38/fyLi0tlyKAHvmgGkp6VwU/fCny7IEXN1lwVJ2hkpMwAJFDWQUaLXeSKEEyZzAr6+Hvzf669w4sQRGjUKITw8iqVLPiuyGdxequgk82Xqhzana9+RdO83MrcJu0nrrrYNTCk3xWYyKTXOHt+Pk5MLDUPbVVZMAISfOsSGlW9zIewoUmr07Hsr6z9/i4DaDUhOjCU54Sode/Rl9epldOvUjO1/HOKVV9/lgxcm0rxDL5q06kKLDvYxOKU0tv3wMcNHjWFA7+Lf9AqytJnb0aroylaVv8/yTtL//reB/rfeQ63A+kx+8XN+/i8D5GVMeTo9u/W/gzfmvkfL0Ia0bdWwyHNZkqSzFf2UgU7njsmciJPeF79awWRkxjNjxqOYTCaCgoL59ttvaNasCU/NeKnIc1j7t1rZVbSUkhqtXGnWrheA6l92UKK4wRQ6nV76+Pqj1zvhXdOPxi0706pzX1p36Vth64CeOPgXx//dyba1y5g15038/WrStVNzpjwwk9iYKOJiLgOw/IuVjBp2Ezrd9TgMxgyWff4zr734HACvfbqTwLqNyhSPlJIrl8/x3+4ttOrcm/pN2pTpfOUhOTGW16b2548/f6JJo9ol7p9TRQOIE2dyE3ROM3dcmBsAF+Oy+/VyquicBJ23gs5J0HDjCFZL3/QrO3lV9iC1qpyc8yqPn8umbSuZOGEqXfuO4rbJTxf5viClZMePn/HzV+/jXaMWvn4B1KxVC38/P/wD/AgM8MPHx4vo6KtEXI7mxzVfoxOuCOGa75xmzYCmpeKkDyj2PchsTgEEs2fPJiDQnyefeB6zORmdzp2aNQM4fWYfnTr2LXZkvrW/x8pM0K9svJU7Rt/D3M//RqfXl3yADU0f1vCAlLJLRZ1fCDG2hnuz73zcGpfpPBmmRGJS/lkqpZxeTqGVWbEVdMtWoWzc+BVubi7s3H2UXbsPsmHlPDZ+8S5DJzxO2+4DytycHHH+BAd2buTo/t9IjL1CanJ87muPPzQaZyc9P27aw6mj+6nbMHuk8s39h3HHbTffcC43VxcWvPNO7teR4SfRzCZq17/xsZmiJMXHMOfhWzEaUnBydsFsysLTuwbde/Vj4axPuPep+bTp2q8M33HZXDh9mC/ef5bRE+62KDkXpiyDxcpaRVc2lZwrzier3mP0yLsZPeWFEqePFELQf9QU+tw2mZjI86QkxmV/JMUSkxTP+UtnMKYl4+0bgK9/fSY+8gq7t67B09ODrT9/goe7K4EBPREi5/3GBDhfG7GdhaalIZHodV7ZzeBogIanpyvff7cWs5YKAoRwJTk5hf37D9G2batiE3RVqaKl1DBqibjrfDGTwR7DJ/TvPZ/hk56o8slZKZtiK+iOHdvKHTvW5dtmNmt8+d1vfLhoGeGnj+FVsxY1fAPw8fXHp2YAXjUD8PENoFWnW8jMMBJ3JYLQdjcTHxOBq5sHUkoSYqNIjIvmYthR/v1zI0Nvv4M7Rg6gZWgDPNxd8Pb2QCcEen32wA5Nk/QedC9dunblrdem4ezslK9yzqFpkudfXconi+YDENK8HQmxV/Dx9adRaAeCgpvSqdcwavoXntiS4q/w0atTuBh2lIjLRzEYM3BzdcHbK7vC3Lz9X+6bPIXQtt2p6Veb5u170q7HQJxd3Er1wy9JZkY6mtmEm4cXZlMWEedPsvjle3nmxed59MGRhf4MipJTRef0QxdWRedU0OA4VbRK0MUrzc9HSjOjJ45m80/rmTJzYYV1JWlmM28/NZIXX3ySO0f1BiDA/2ZM5qsAOOn90GQ6mpaOXucBiOxETM5oex0NGzZE0zQuR1xFp/NECIGTkxNnwvYzdMg4Tp48U+i187J1JX0sbSOxpjB8fP1ITogFYPT9zzNo7LQKa8ksT6qCLj2rE3ReBmMGl6PiiYiMJTLqKtFX4oi+cpVLlyL5c/smXFzdadikOf/t/QMvH1/cPLwQQuAfWIegOnWoV68uMx6dWOpKsCiXImKpV9cPnU6QZTKzZfsBDh89w6H/jrNrx2YahXZgynOL8PSumXtM2LF9fPrmw4y4YxxzZk+lhk/hUxT6+bVA08w8/NRz7PpzN+fDTtBjwFiate1Oiw69cHJ2KXP8WVkZbFj5Nn9u+pp6jVqQkZ5GzOXz1Aqoy+T77+OlpydZfc6yNnPD9SSdN0FD1U7SlZmg7S05g3U/HylNmDUD7p6u3DRoLP1HPUitgLoVFlv4qUMsff1/7Ny5nobBAbnbA/y7YzLntLQJdDoP9DrPazFKTOY49DpvdDpXQkObsOP3DTw09Sl+/nkrNWr4MPeNWdSvX4/bR1j+/8ia3215J+jdyUt4YckGUhLjqF2/KTq9E14+vuV6jYpUGQlap/P8LudvoLQ0mYXZnOA4Cbo4m7YfoEmjOoQ2qcu36/+gTasQWoXWL22c5SY5xcgTM+ezd8/f9Bw8gZjIs7i6eXEx7DDt27dh6fvPFnv8oNseIiU5mT1/fA3A/kNnWPXVL+zZvRuzWfL0O2vL1OyUkhTH5+88iZenK889O4033lzIk09MpU/PdrmVfGkUTNCQv4ouKkFDxVXRULFJTSVny1jyc9K0dMxaCiPvfYZbhk3G07v4ed3Lw8lDu/j83Sd5YNo0BvbtRrdOzXJb1QL8b8Jkjs3dVyfc0eu9ryXo2HyPVvXp05P35r9O/fr10Ov1rF69hhdfeJ20tHSr4rFFkk4wXSTKZx8vL91WLjf/tqASdOlVWIKuysxmjW/W7WTjT9vx8HAnOiqav3/fTPfeg9n84+JijzWmZ+Li7JT7RpFD0yT9hzxAckoKwyY+adVAurSURDZ+8Q67Nn+LyZTJHXdNYcmCZ9EJGD/+f3z88bv4+/uV+vvNURWraKi45KYStGVK+jlJmYXJnMhLH/5CcONWlRRVthMH/+LAzh85c2wfV6Mu4OTkjN7JBWdnF4yGFExZmQA88cZqWnTIHtG8euFzOEkjf237k+zJEiWg4evrS1paCgZjHCDRCffcZm9LVWaSPmXYSpwujIGjH+T2e4ovHKoylaBLr1om6ILMZo1R45/ir+0/k5BQcp9UUbJMZj77cgsLP1iMs4s7Nw8eT0jLTri6eRBz+Txnju6lXfcBNG7ZGWNaMqf+283BXb9wZO9vDBw2ivR0I79u/J4jx/cQXOd6Qs7KyuLXX/9g2LCyLRVXVBVdUoKGiq2iofwTnErO1inq5yWlhsmcwJTn3qdrn9srOar8NLMZU1YmWVmZmLIy0Ds5g5To9Ho8vK5X9GkpifywfA5njuwl3ZBKSlICOYlaINDpvRA4YTLH46T3RQjrWrwqI0mnmK9wQm7gjZV7cPPwKtU5qgqVoEtPJeg8kpINRfY9W8Ns1lj9/W+sXbuJsNMnyEw3ElgnmGbNQ/ll/bdITcPV3ZOmzdvQf2BfHrznNurWroWmSeISUgjwyz8b2qVLkSxevJx582azd+9Bmjdvgo+PN5qmobeyOb2qVtFQfolODQyzXnTKwewR0ZhAZo+AFsIVs5bKTQNHMHmGdbPVVTWP337j5B0mcxJCuKDXuVt9vopM0rFZZ7jo8jeTHp1Lh5uHWBtalaMSdOk5/pRbViiP5Ayg1+u4Z/xA7hk/8IbXDkyfyC9b/6Zp4wZMHNMn32s6nbghOQPUr1+XefNmA7Blyw6cnZ2oXTuQYcMmcvDgb/z55x5q1vShbVvrmx/La+ISa7i5ueHp6UFcXHy+7fY4kYm9xVsYKSVmzYimGQCuVZQCqaUS3LgF46a9ZtsAy8HCDftuSNI64YIm0wHrE7Q1f6vWPH6VpRk5ZthI/Tqt2bDqHXZvXcO0l5ej06l1jaojlaArWef2Tenc3vLnsguaPfup3M///jt73WKjMZ3MzLKt9ZozP7cl038WpaTnoj09PXhv/hzGjr0dTdOIiIjk2WdeZvv2P3L3KWuSrmrPYVd1mjQRn3YEqaXz1Ftf07RNt9w+2dTkBDw8fRzmWduFG/bl+3rP9rUc+mMdv29dkbvNslnMslVEkv7+9KO8Ns8LkKSmpLH++28sjkdxPOq2zI65uWXPwT14cF8GDLiF5577vxLXLC5qGUprhHhfH1STd63okqxYsQhXVxeah3YjMCCUF194nZWrltCmTct8+0WnHCxVolXJ2TpmLZOYlH0I4cTCH4/TrG33fAOmvHx8HSY5F+bEgd+5deggTp+NJMuUvczqpYjfrVqq0pq/uZLWjl4fPh13NxfmvTqVea8+xNZNPzNl5kJVPVdj6jfvQG69tR9eXtb3w4jm2cvS5awVnaO4taLzJum8ClYJORVGo0YN6NmrB9Meejq3aXvz5u0sWriMadPvL/RcliTqnH1skZztuXlbSkl82hFcnXx5d91uu32EpyyCm7Rm/htzGDRoLHXqtCWodjtCmnQHXVLumtOWrC1dHkl6ffj1bk9jeiaaJtHp9MRfm9pYqZ5UE7eDkFLSuXMHfHy8S9zX0lWuLGVJX3SDBsGcOnWGjIyMfNsPHTrCLb1vKvZYVRmXLyklicaTaNLEvO+228VsVBVh0JhpDBg9FZ1OR1ZWBuasLNKNafy27hMSrpzj4N/7MGvJgB4nfY0804zeqCzN3TnJeerjb7Pu65WYTJk0adkBZxdXh17wRymZStAOIjY2niFDxrN//6+lesPNGSxW1FrROX3ReQeLFbUUZWF90cePn6JNm5b4+dXKNzhs0OB+HDp4xOp4ldJLzbiEb7AXT7zxU/ajStVYTvOxs7Mrzs6uuHl4cdvkZ1i9cCZOLiYmP7qAuCsRxEUcZ+P3H1A7qFe+45s3b0qPm7oSHXWFbdt2YjabLUrUZ8VRamZ6EDrKl5Hjn0GnE+zbvZPZS7Zy+sgevHx8adttQLX//VR3qonbQQQE+FmVnEvqi/Zrmj3LUk4zd0lK6ot2ymjAihWr+XHDavr06Unjxg158cUZjB17Ox99tNyiayhlZ9LSMbte5d6nFlTKbGD2yMXVjfufXcg7aw7Rrd9oeg2dxIXz5+nQ5XZ6DeqJlGaEELw5bxadOjfj55+/4+FHpnD4yF80adKo0BYfs5ZBljk1t+k8KT2MOP+jSLfahLTtQ1BIR555dy2B9ULoNWQiHW4eopKzoipoR3D69FmWL1/NW2+9XKbzlLWKLm6lK4CFb/zEuQnhvP3Oq/j51eL33/+if7/bSxzYppQPs5aJ5nmBQUOnUi+kha3DqfKcnbMHYfrU9OfFDzcRdvQftq/7lBp+bgzoO4gLF86yatVKAG67bTS33jqIRR/OY9jQCblN3ulZ8SQaT2HWDAiRnXBruDVBuCczdda31A5uYrPvT6n6VIJ2AEFBgYwdOyL3623b/sDV1YU2bVrg61uzyOMs7YvOeeTKWgWTtJSST5at4pNlq6w+V3lzc3MjNLQxV65c5cqVq1Yfb48DxMY+dDN79vkwaMxDtg7F7uh0OkLb3YSzixtvPzWKkaNv5btvfgL0gBmpZbJ588/ExUVRo4YL8fFxRCbtQUoDvh6tcHcOQghBRlYCZo/LJMfEkpIQqxK0UiyVoB1AdPQVPDyuT7ISGxvH4cPH2b//P2bMsO7NuDyr6MJUhTWjpz88hVmznibmSix16gax7dedTJv2FKmpaTaNqyJJKVn3/VrueLBsrSzV3cWw7PESoc2acvLscdzc3Uk3pvLYnM+o17glRzYtxK9hW7I0HdvWLqNrn9uZ8tyifOfIzEjHmJaMj29AYZdQlFyqD9oBHD9+mjNnzpGWZuDrr39gwoTRvPHGS8yY8RC//76LxYtXFHlsWfqi8z52VZTCJmewZfU5fPhgHntsKn37jKBjxz40DulEekY6iz96x2YxVYZMczKGtFRC2xU/Yl4pXu/hkxk39RWGDh2Bl4c7878/ypJfLtCy0y20bhrMh0s+oc/Ih/jz5y8B2LdzA9vXL8dsuj6RkIurGzVqBVbb0fOK5VSCdgCjRw9j1KihJCYmERERme+1Fi2a0bNnN6SUzJ27gLQ0Q4nnK+q56Bw5z0XnVdzkJVUpST807T5ee/Utzpw5B4DBYODJJ15kyJAB+PnVsklMlcGQGcnNg+5Uk16UkRCC/qOmMHfVHtZu2MzI7kG0aehFr1a+9G/vx86j8UhNI6BuQ7r3G0XzDj1JTYrn0dub8tuPn9k6fMXOqP+tDqRevTo8++yj+bbVrh1Ihw5tyMzMJCDAHw8Pd379dSd//70/d5+KqKItTdKVnajr1AniTNi5fNtSU9OIi0vA399xE3R61lXadr9xbnildDQp2HwwgRMRqfh6OmPIMPP9rmgi4zOo6V+blz7czL3PvM+pQ7vYvOZDADLTb7yxVTW0UhyVoKsJV1dXpk6djBACJyc9er2ezMxMFi36tNCZkiydXSyvomYXy1HUXMSVmaR37fqHO0bflm9b+/at8fT04OzZcIvPY+t+dGuYzEZMWnqlr+Xs6DQJZyIN/Hk8gX/PJpOWnv9mVQjBa5/8zpDxj/DEG6u59c5HbjiH5ZOKKtWRGiRWDfXrlz3ZQnx8ApD9RvL64n9oGyIYNawbD89fzzvTh5F3ba/iZhezZsBYYY9fwfUkXdGJb/57H7Hzj5/Q63X8uGETzZs3Y/bsZ5g1ay4mk6lCr20L0SkH0bR0hHBRfZ42EFgvhJH3zrR1GIqdUhV0NVarli+PPfYgACNG3EqrbiORUtJ9YFfcXZ14999zpKZn5u5fsKk7bxVtaVN3SXKavSuqqr54MYLetwzH2cWFd999neHDBvG/B5/ki1VrKuR6tnT9ZkcgZRaaptk0HkVRrKMqaAWAxo0bApBCIKPu6kAKkPFHMom3jydo0fyijytkOcqCU4AWrKRzmrpLWt0nb1Udc3WXxd9LSUsGXrp0mWeenm3x+exNwVYInc4Vs5aEKTMDFzfr1z5WFMU2VAWtFOmxxx5ESslb3nXRrvVTWzpgrGB/dGGVtKWL2FuTnEuzv6MoalWvnOklnV0tXwBFURTbUwlaKZZOp8PV1YX0l1654bWSmrotTdLFJerD5z60Kt6kpGSklMRc3VVtEnXJy21qgF71QSuKnVEJWimWt7cXDz10LydPhvG6qz9wvYrOK2ck+Jm0S4Qbwos8X1F90oUlaUuTc3JyCm+/nT1b07hxD3DqVBixsXHs2XPAoZO0petgSzSE+q+uKHZH9UErFqldO4B27VoT0bkde/YcYPhLgzhx4gzOzk40adKIx2+9k++/X4HL3oN0dHGmZ89uJCQk4u/vV+GxZWVlUa9eHQC2bv0OKSWHDh3lzz//pkePzny4eCaPPPwmQujL7Zq2nou7sMTcvUcXxowZgU6nY90PP7Fr1z/ZL0gNhErQimJv1P9axSK+vjUZPLgvaWlGjh49CcDevf9y5sw5hBAsWDAHHx9vBg7sTe/eN3H48HEeeeT5SomtVi1f7rprbO7XQgg6dmybO2lLdHQMR49txM+jGZ7OvmVKrraYXCWvoqrml19+li+/XEpCfCJXY2JZvmIRb76ZPRAuu4JWzduKYm9EYZNU5OjYsa3csWNdJYajOBKz2YzBYOSddxYze/ZTODtXzPq2U6Y8wejRwxgx4tZi94uIiKLfTU/i7hxAakYEHi5B6K4tAVhSU7GtK2YoOsbmzZuybft6OrTvTVxcPAA1a9bg34O/M3rU3fx7cB9IM4t/PlmZ4SoKANOHNTwgpexSUecXQozV6Ty/0+s8S965GJrMwmxOWCqlnF7C9YYAH5C9lNmnUsp5BV4X114fBhiA+6SU/1pybEGqiVupMHq9HicnJ1q1Cq2w5AzwySfzC50NraDg4DqcubSGtiGPYNIMgI4scyogqkQCLkpJNw9Dhw5k7doNuckZIDExiTVr1jF8+ODsBK0oSpmJ7H6yxcAgIALYJ4TYIKU8nme3oUCzax/dgSVAdwuPzUc1cSsVyt3djQkTRnP69FlmzMj/7LHJZCIhIRGAjz9eSXj4RdLSDLkLWVhqx45dGAxGi/c/cn4xF6O2cvT8El57ZzSvvTMKKSWJxtNIKdGkKffRJHuQnpGBt7fXDdu9vb0wGtMRCCT28/0oipXMWHCDXqLsc5S0RF83IExKeU5KmQl8A4wssM9IYJXMtgeoKYSoY+Gx+agErVSKRo3qM378KDRN4/HHX8RsNrN+/SbefHMhAIGBAej1Thw6dJTly1cD8OSTs7h8OYp//z3MuHHZM55t2LCZvXuzK8qFCz8hKyuLrVt/typB53XnnSO5886RHDzzATrhhBACQ2YUSelny+G7rhw/rP2J4cMH07799ZHwLVuGMmbMCL777kckUo3iVhzZNk0ayDLFkWWKL/WHWUsCSBNC7M/zMbXAteoBl/J8HXFtmyX7WHJsPqqJW6kULi4u9OjRGYBbbumByWRi7NgRjB07AsheMhOgfv269OzZDYBx427Hx8eb2rUDWbr0bQA8PT1xd3cFwGAwYjZrvP32y2WOz8nJifDIX2jX+FG8XOsjpUaWOQ29zhWdqNr/TWJirjJ92tNs/fUHdv31D2azmd59buaJx18gIiISL5faoCpoxUFJKVOyW48lpV8fTOac67kSdizsAgXL96L2seTYfNRttVLpxo27HVdX1xL369mzG97eXuj1+ty1mgcMuIW2bbNXZXr++cdxcyv5PNbIefZaCB0pGRfIMqfkvpaSfhGTZkRKWalN4Jb0j69b9zOhzbqyZs061q7dSIvm3fn95/PU9u6ITujRpOMtBKIo12k+2TehpW3q1rAwHUYA9fN8HQxEWriPJcfmU7VLA0WxgYITpGRmZtKlxVPohB6BIEtLJSHtOEE+3TGZDeh0LhVeZRdM0oUNHEtKSmbnL+EAuBKSu10IJ5WgFYdWtio6p3o2WXLgPqCZECIEuAxMACYV2GcD8KgQ4huyB4klSSmjhBBXLTg2H5WgFaUYP/64iRdemMvanz9j/PAPANDjRoB3dnN9asYlXJ1r4e4cUKlxWTPqXCec0WRWBUajKFWB5gMkZydoa5K0xdUzUkqTEOJRYAvZj0qtkFIeE0JMu/b6UuAXsh+xCiP7Mav7izu2uOupBK0oxahdO4jAQH9atGjK4XMf0q7xo9enJZWAW/bnFw17CXAJxV1XEyh5pa7KpNe54KyV3yxqilIVla6Ktqp6zrnOL2Qn4bzblub5XAKPWHpscVSCVpRidO/eiV9//S53oYnD5z5kVKMlN+znqffPN1LakpW6KjqJ58SQQQr7tcNkphvVcpOKg7O2ira8erYFlaAVpRiRkdH8++9hbrttcO629eHT8yVpozmRmk710QvrJmMpLomXJnkXdT4X4UWAUzNmP9CL1p37MGjsNOo0CLX6/IpS1VlXRVtfPVc2laAVpRgGg5FLly7fsD1vko7JOomGiRC3XuV2XUvXyraEEIJQj0H838ahLFr6Dd9/8jqPvf5FuZ1fUaoWS6voql09Q1WPTlFsrGnTEKZPv7/Q12asbE//p5yo5dwYee1uPMUUXaVGTIe4++R+tGvdiNuG9SXhahRmc9WJUVHKk5QyJTu1FffIVdWvnkElaEUpVkxMLGPG3J9vru8DB/4jNjaO0NAm9OvXi+2XXqGx2y0AXMrcT6Y0UM/VhfpubvkSZGUxyyxOG39FSklkxlkupZ/KfW3owC7U9PXl940rKy0eRal8JT0XXfWrZ1BN3IpSLH//Wrz66rPExcXz9dfreOyxB9m1ay9paQZ6976JOnWCgOwm72zZ/37++Td8PmsbHb375Z6rNEn6vDG5wPmLtnHjFtLSDIwfP4o1axowbtwI/vvvGJmZWXTv3onhwyfx1VdLmXL/eN5/fxkDRj1gdTyKYg+K74u2j+oZ7OEWQlFsSKfT0bZtK8xmDT8/XwAef/x/9O59U7HH3XffBLZf+Jj4rGjSzEk3vG6WJgzmFKTU2JbwFSaZRZaWgblA83iIu0+RyVnTsmczmzr1aQwGI6GhTejQoQ1CCCZMGIVer6dTp3a5U6zOmzcbHx9vDGlppBvTrP5ZKIp9KaqKto/qGewlSkWxsaCgACZNGmPVMXq9nu5P1SLJFJu7LaepPMx4iNPGA0gkrT164CScuZBxggMp2wC4kH6CDM3IghN3FXruL7/8jlmz3gTgjjuGo9PpaN68KS1aNCt0fyEEbdu2RAhBXGI6bbr0tep7URR7U3hftP1Uz6CauBWlQj388P08/DCcOHGGli2bMX36TO67bwLduk3Kfbb6uruQUiKE4IUX5vDcc+M4cuQ4R4+eZOLEO/LtOWnSGNLSDAAMGdLfqphq1vQhI91Qlm9LUexEwRHd9lM9gz1Fqih2Kjz8Iq+88hYAM2c+QufO7QpJztlytr/55ixq1qyBq6srtWrlNK2/yMWLlzl37gKffvploWtAW+LmHu04tn8nP658hy3ffsS5EwfUqG7FIeWvou2regaVoBWlwjVq1IBvv/0UgJCQhjg5Wd5wFRrahFtvzR5oNmnSGGrVqomLiwseHqWfEax7p2a88/7bBPjAvh0/sOD5CXz0SuGPkimK/cvpi7av6hlA5H18pKCOHdvKHTvWVWI4iqJUpiyTmTfnr2bHzr08NGuZrcNRHND0YQ0PSCm72DIGIfQSJFJqdlM9QwkJWgixvxJjURRFURxPrJRyiK2DsEfFJmhFURRFUWzDvhrkFUVRFKWaUAlaURRFUaoglaAVRVEUpQpSCVpRFEVRqiCVoBVFURSlCvp/gMkqYwPdiRQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 648x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import cartopy.crs as ccrs\n",
    "import matplotlib.patheffects as pe\n",
    "\n",
    "# Mask the points outside the polygon\n",
    "temp_sk_masked = temp_sk.copy()\n",
    "temp_sk_masked[~mask] = np.nan\n",
    "map_temp_sk_masked = temp_sk_masked.reshape((n_width, n_width))\n",
    "var_sk_masked = var_sk.copy()\n",
    "var_sk_masked[~mask] = np.nan\n",
    "map_var_sk_masked = var_sk_masked.reshape((n_width, n_width))\n",
    "\n",
    "map_type = \"contourf\"  # map style of kriging (expectation)\n",
    "\n",
    "# Kriging - Excpectation\n",
    "fig = plt.figure(figsize=(9, 7))\n",
    "ax = fig.add_subplot(111, projection=ccrs.PlateCarree())\n",
    "if map_type == \"pcolor\":\n",
    "    im = ax.pcolormesh(lon_map_uni, lat_map_uni, (map_temp_sk_masked - const_k2c).T,\n",
    "                       vmin=temp_sk_min, vmax=temp_sk_max, cmap=\"jet\")\n",
    "elif map_type == \"contourf\":\n",
    "    levels = np.arange(temp_sk_min, temp_sk_max+1e-6, 1)\n",
    "    im = ax.contourf(lon_map_uni, lat_map_uni, (map_temp_sk_masked - const_k2c).T,\n",
    "                     levels=levels,\n",
    "                     extend=\"min\",\n",
    "                     cmap=\"jet\")\n",
    "ax.scatter(lons_st, lats_st, c=temp.t.values - const_k2c,\n",
    "           cmap='jet', edgecolor=\"black\",\n",
    "           vmin=im.get_clim()[0], vmax=im.get_clim()[1])\n",
    "plt.colorbar(im)\n",
    "ax.margins(0.1)\n",
    "ax.add_feature(cfeature.BORDERS.with_scale('50m'), linestyle=':')\n",
    "ax.coastlines()\n",
    "ax.add_feature(cfeature.LAND)\n",
    "ax.add_feature(cfeature.OCEAN)\n",
    "ax.set_title(\"Simple kriging - temperature [°C]\")\n",
    "ax.set_aspect(\"auto\")\n",
    "# print true values\n",
    "for _, station in fpd_st.iterrows():\n",
    "    plt.text(station.Longitude+0.2, station.Latitude,\n",
    "             str(round(float(temp[temp.numer_sta==station.ID].t -\n",
    "                             const_k2c), 2)),\n",
    "             fontsize=12, weight=\"bold\", color=\"black\",\n",
    "             path_effects=[pe.withStroke(linewidth=2, foreground=\"white\")])\n",
    "\n",
    "# Kriging - Variance\n",
    "fig = plt.figure(figsize=(9, 7))\n",
    "ax = fig.add_subplot(111, projection=ccrs.PlateCarree())\n",
    "if map_type == \"pcolor\":\n",
    "    im = ax.pcolormesh(lon_map_uni, lat_map_uni, (map_temp_sk_masked - const_k2c).T,\n",
    "                       vmin=0, vmax=0.3, cmap=\"magma\")\n",
    "elif map_type == \"contourf\":\n",
    "    levels = np.arange(0, 0.3+1e-6, 0.025)\n",
    "    im = ax.contourf(lon_map_uni, lat_map_uni, (map_var_sk_masked**0.5).T,\n",
    "                     levels=levels,\n",
    "                     extend=\"min\",\n",
    "                     cmap=\"magma\")\n",
    "\n",
    "ax.scatter(lons_st, lats_st, edgecolor=\"white\", facecolor=\"none\")\n",
    "plt.colorbar(im)\n",
    "ax.margins(0.1)\n",
    "ax.add_feature(cfeature.BORDERS.with_scale('50m'), linestyle=':')\n",
    "ax.coastlines()\n",
    "ax.add_feature(cfeature.LAND)\n",
    "ax.add_feature(cfeature.OCEAN)\n",
    "ax.set_title(\"Simple kriging - standard deviation  [°C]\")\n",
    "ax.set_aspect(\"auto\")"
   ]
  }
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