Vizzuality/landgriffon

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "1061d66d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import rasterio as rio\n",
    "import rasterio.plot\n",
    "import geopandas as gpd\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.colors import ListedColormap\n",
    "import matplotlib.colors as colors\n",
    "import numpy\n",
    "\n",
    "from rasterstats import zonal_stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "b63c1a9d",
   "metadata": {},
   "outputs": [],
   "source": [
    "path = '../../datasets/raw/wf/QA/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "f80cb687",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GID_0</th>\n",
       "      <th>NAME_0</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>USA</td>\n",
       "      <td>United States</td>\n",
       "      <td>MULTIPOLYGON (((-154.99611 19.33694, -154.9966...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  GID_0         NAME_0                                           geometry\n",
       "0   USA  United States  MULTIPOLYGON (((-154.99611 19.33694, -154.9966..."
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gadm_usa = gpd.read_file(path+'gadm36_USA_0.shp')\n",
    "gadm_usa.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "12d9528a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dblbnd.adf  hdr.adf  metadata.xml  prj.adf  sta.adf  w001001.adf  w001001x.adf\r\n"
     ]
    }
   ],
   "source": [
    "!ls $path/wf_tot_mmyr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "a83366b9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Define the colors you want\n",
    "cmap = ListedColormap([\"#ffffff\", \"#fdae61\", \"#ffffbf\", \"#abdda4\"])\n",
    "\n",
    "# Define a normalization from values -> colors\n",
    "norm = colors.BoundaryNorm([0, 214, 429, 644, 858], 5)\n",
    "\n",
    "with rio.open(path + 'wf_tot_mmyr/hdr.adf') as src:\n",
    "    dat = src.read(1)\n",
    "    fig, ax = plt.subplots(figsize=[15,10])\n",
    "    ax.set_ylim((20,60))\n",
    "    ax.set_xlim((-130,-60))\n",
    "    rio.plot.show(dat, norm=norm, cmap=cmap, ax=ax, transform=src.transform)\n",
    "    gadm_usa.plot(ax=ax, color='red', alpha=.1, edgecolor='red')\n",
    "    ax.set_title('Total water footprint mm/yr')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a41fb2e1",
   "metadata": {},
   "source": [
    "## Zonal stats to calculate total water footprint within US\n",
    "\n",
    "The original raster has the information in mm/yr and the valye has been estimated by dividing the water footprint in one pixel by the area (1000*1000)m2.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "f112ccf6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1668, 4320)"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "src = rio.open(path + \"wf_tot_mmyr/hdr.adf\")\n",
    "src.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "c99563f4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-3.4028234663852886e+38"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "src.nodata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "7ac0d709",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "shape: (1668, 4320)\n",
      "noData: -3.4028234663852886e+38\n",
      "GLOBAL Total sum excluding no data: 111987304.0 mm/yr\n",
      "GLOBAL Total sum excluding no data: 111987.304 m3/yr\n"
     ]
    }
   ],
   "source": [
    "src = rio.open(path + \"wf_tot_mmyr/hdr.adf\")\n",
    "print('shape:',src.shape)\n",
    "print('noData:',src.nodata)\n",
    "\n",
    "image_read = src.read(1)\n",
    "src_masked = numpy.ma.masked_array(image_read, mask=(image_read == src.nodata))\n",
    "\n",
    "print(f'GLOBAL Total sum excluding no data: {src_masked.sum()} mm/yr')\n",
    "print(f'GLOBAL Total sum excluding no data: {src_masked.sum()*0.001} m3/yr')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "a869ce6e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0...10...20...30...40...50...60...70...80...90...100 - done.\n"
     ]
    }
   ],
   "source": [
    "#rasterise the gadm geometry\n",
    "\n",
    "!gdal_rasterize -l gadm36_USA_0 -burn 1.0 -tr 0.08333334 0.08333334 -a_nodata 0.0 -te -179.99166665 -55.902229309 180.00836215 83.097781811 -ot Float32 -of GTiff $path'gadm36_USA_0.shp' $path'gadm36_USA_0.tif'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "b9d42129",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Driver: GTiff/GeoTIFF\n",
      "Files: ../../datasets/raw/wf/QA/+gadm36_USA_0.tif\n",
      "Size is 4320, 1668\n",
      "Coordinate System is:\n",
      "GEOGCRS[\"WGS 84\",\n",
      "    DATUM[\"World Geodetic System 1984\",\n",
      "        ELLIPSOID[\"WGS 84\",6378137,298.257223563,\n",
      "            LENGTHUNIT[\"metre\",1]]],\n",
      "    PRIMEM[\"Greenwich\",0,\n",
      "        ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "    CS[ellipsoidal,2],\n",
      "        AXIS[\"geodetic latitude (Lat)\",north,\n",
      "            ORDER[1],\n",
      "            ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "        AXIS[\"geodetic longitude (Lon)\",east,\n",
      "            ORDER[2],\n",
      "            ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "    ID[\"EPSG\",4326]]\n",
      "Data axis to CRS axis mapping: 2,1\n",
      "Origin = (-179.991666650000013,83.097781811000004)\n",
      "Pixel Size = (0.083333340000000,-0.083333340000000)\n",
      "Metadata:\n",
      "  AREA_OR_POINT=Area\n",
      "Image Structure Metadata:\n",
      "  INTERLEAVE=BAND\n",
      "Corner Coordinates:\n",
      "Upper Left  (-179.9916667,  83.0977818) (179d59'30.00\"W, 83d 5'52.01\"N)\n",
      "Lower Left  (-179.9916667, -55.9022293) (179d59'30.00\"W, 55d54' 8.03\"S)\n",
      "Upper Right ( 180.0083622,  83.0977818) (180d 0'30.10\"E, 83d 5'52.01\"N)\n",
      "Lower Right ( 180.0083622, -55.9022293) (180d 0'30.10\"E, 55d54' 8.03\"S)\n",
      "Center      (   0.0083478,  13.5977763) (  0d 0'30.05\"E, 13d35'51.99\"N)\n",
      "Band 1 Block=4320x1 Type=Float32, ColorInterp=Gray\n",
      "  NoData Value=0\n"
     ]
    }
   ],
   "source": [
    "!gdalinfo $path+'gadm36_USA_0.tif'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "2cd19142",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Driver: AIG/Arc/Info Binary Grid\n",
      "Files: ../../datasets/raw/wf/QA//wf_tot_mmyr\n",
      "       ../../datasets/raw/wf/QA//wf_tot_mmyr/w001001.adf\n",
      "       ../../datasets/raw/wf/QA//wf_tot_mmyr/dblbnd.adf\n",
      "       ../../datasets/raw/wf/QA//wf_tot_mmyr/sta.adf\n",
      "       ../../datasets/raw/wf/QA//wf_tot_mmyr/prj.adf\n",
      "       ../../datasets/raw/wf/QA//wf_tot_mmyr/metadata.xml\n",
      "       ../../datasets/raw/wf/QA//wf_tot_mmyr/w001001x.adf\n",
      "       ../../datasets/raw/wf/QA//wf_tot_mmyr/hdr.adf\n",
      "Size is 4320, 1668\n",
      "Coordinate System is:\n",
      "GEOGCRS[\"WGS 84\",\n",
      "    DATUM[\"World Geodetic System 1984\",\n",
      "        ELLIPSOID[\"WGS 84\",6378137,298.257223563,\n",
      "            LENGTHUNIT[\"metre\",1]]],\n",
      "    PRIMEM[\"Greenwich\",0,\n",
      "        ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "    CS[ellipsoidal,2],\n",
      "        AXIS[\"geodetic latitude (Lat)\",north,\n",
      "            ORDER[1],\n",
      "            ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "        AXIS[\"geodetic longitude (Lon)\",east,\n",
      "            ORDER[2],\n",
      "            ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "    ID[\"EPSG\",4326]]\n",
      "Data axis to CRS axis mapping: 2,1\n",
      "Origin = (-179.991666649999985,83.097781810917979)\n",
      "Pixel Size = (0.083333340000000,-0.083333340000000)\n",
      "Corner Coordinates:\n",
      "Upper Left  (-179.9916666,  83.0977818) (179d59'30.00\"W, 83d 5'52.01\"N)\n",
      "Lower Left  (-179.9916666, -55.9022293) (179d59'30.00\"W, 55d54' 8.03\"S)\n",
      "Upper Right ( 180.0083622,  83.0977818) (180d 0'30.10\"E, 83d 5'52.01\"N)\n",
      "Lower Right ( 180.0083622, -55.9022293) (180d 0'30.10\"E, 55d54' 8.03\"S)\n",
      "Center      (   0.0083478,  13.5977763) (  0d 0'30.05\"E, 13d35'51.99\"N)\n",
      "Band 1 Block=512x4 Type=Float32, ColorInterp=Undefined\n",
      "  Min=0.000 Max=3889.404 \n",
      "  NoData Value=-3.4028234663852886e+38\n"
     ]
    }
   ],
   "source": [
    "!gdalinfo $path'/wf_tot_mmyr/hdr.adf'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "id": "1a60027a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 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87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 100 - Done\n"
     ]
    }
   ],
   "source": [
    "!gdal_calc.py --calc \"(A!=-3.40282e+38)*A\" --format GTiff --type Float32 --NoDataValue 0.0 -A $path\"/wf_tot_mmyr/hdr.adf\" --A_band 1 --outfile $path'hdr_nodata_0.tif'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "id": "4267c0ad",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Driver: GTiff/GeoTIFF\n",
      "Files: ../../datasets/raw/wf/QA/hdr_nodata_0.tif\n",
      "Size is 4320, 1668\n",
      "Coordinate System is:\n",
      "GEOGCRS[\"WGS 84\",\n",
      "    DATUM[\"World Geodetic System 1984\",\n",
      "        ELLIPSOID[\"WGS 84\",6378137,298.257223563,\n",
      "            LENGTHUNIT[\"metre\",1]]],\n",
      "    PRIMEM[\"Greenwich\",0,\n",
      "        ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "    CS[ellipsoidal,2],\n",
      "        AXIS[\"geodetic latitude (Lat)\",north,\n",
      "            ORDER[1],\n",
      "            ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "        AXIS[\"geodetic longitude (Lon)\",east,\n",
      "            ORDER[2],\n",
      "            ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "    ID[\"EPSG\",4326]]\n",
      "Data axis to CRS axis mapping: 2,1\n",
      "Origin = (-179.991666649999985,83.097781810917979)\n",
      "Pixel Size = (0.083333340000000,-0.083333340000000)\n",
      "Metadata:\n",
      "  AREA_OR_POINT=Area\n",
      "Image Structure Metadata:\n",
      "  INTERLEAVE=BAND\n",
      "Corner Coordinates:\n",
      "Upper Left  (-179.9916666,  83.0977818) (179d59'30.00\"W, 83d 5'52.01\"N)\n",
      "Lower Left  (-179.9916666, -55.9022293) (179d59'30.00\"W, 55d54' 8.03\"S)\n",
      "Upper Right ( 180.0083622,  83.0977818) (180d 0'30.10\"E, 83d 5'52.01\"N)\n",
      "Lower Right ( 180.0083622, -55.9022293) (180d 0'30.10\"E, 55d54' 8.03\"S)\n",
      "Center      (   0.0083478,  13.5977763) (  0d 0'30.05\"E, 13d35'51.99\"N)\n",
      "Band 1 Block=4320x1 Type=Float32, ColorInterp=Gray\n",
      "  NoData Value=0\n"
     ]
    }
   ],
   "source": [
    "!gdalinfo $path'hdr_nodata_0.tif'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "id": "48c74b2f",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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13.. 13.. 14.. 14.. 14.. 14.. 14.. 14.. 14.. 14.. 14.. 14.. 14.. 14.. 14.. 14.. 14.. 14.. 14.. 15.. 15.. 15.. 15.. 15.. 15.. 15.. 15.. 15.. 15.. 15.. 15.. 15.. 15.. 15.. 15.. 16.. 16.. 16.. 16.. 16.. 16.. 16.. 16.. 16.. 16.. 16.. 16.. 16.. 16.. 16.. 16.. 16.. 17.. 17.. 17.. 17.. 17.. 17.. 17.. 17.. 17.. 17.. 17.. 17.. 17.. 17.. 17.. 17.. 17.. 18.. 18.. 18.. 18.. 18.. 18.. 18.. 18.. 18.. 18.. 18.. 18.. 18.. 18.. 18.. 18.. 19.. 19.. 19.. 19.. 19.. 19.. 19.. 19.. 19.. 19.. 19.. 19.. 19.. 19.. 19.. 19.. 19.. 20.. 20.. 20.. 20.. 20.. 20.. 20.. 20.. 20.. 20.. 20.. 20.. 20.. 20.. 20.. 20.. 20.. 21.. 21.. 21.. 21.. 21.. 21.. 21.. 21.. 21.. 21.. 21.. 21.. 21.. 21.. 21.. 21.. 22.. 22.. 22.. 22.. 22.. 22.. 22.. 22.. 22.. 22.. 22.. 22.. 22.. 22.. 22.. 22.. 22.. 23.. 23.. 23.. 23.. 23.. 23.. 23.. 23.. 23.. 23.. 23.. 23.. 23.. 23.. 23.. 23.. 23.. 24.. 24.. 24.. 24.. 24.. 24.. 24.. 24.. 24.. 24.. 24.. 24.. 24.. 24.. 24.. 24.. 25.. 25.. 25.. 25.. 25.. 25.. 25.. 25.. 25.. 25.. 25.. 25.. 25.. 25.. 25.. 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49.. 49.. 50.. 50.. 50.. 50.. 50.. 50.. 50.. 50.. 50.. 50.. 50.. 50.. 50.. 50.. 50.. 50.. 50.. 51.. 51.. 51.. 51.. 51.. 51.. 51.. 51.. 51.. 51.. 51.. 51.. 51.. 51.. 51.. 51.. 51.. 52.. 52.. 52.. 52.. 52.. 52.. 52.. 52.. 52.. 52.. 52.. 52.. 52.. 52.. 52.. 52.. 52.. 53.. 53.. 53.. 53.. 53.. 53.. 53.. 53.. 53.. 53.. 53.. 53.. 53.. 53.. 53.. 53.. 54.. 54.. 54.. 54.. 54.. 54.. 54.. 54.. 54.. 54.. 54.. 54.. 54.. 54.. 54.. 54.. 54.. 55.. 55.. 55.. 55.. 55.. 55.. 55.. 55.. 55.. 55.. 55.. 55.. 55.. 55.. 55.. 55.. 55.. 56.. 56.. 56.. 56.. 56.. 56.. 56.. 56.. 56.. 56.. 56.. 56.. 56.. 56.. 56.. 56.. 57.. 57.. 57.. 57.. 57.. 57.. 57.. 57.. 57.. 57.. 57.. 57.. 57.. 57.. 57.. 57.. 57.. 58.. 58.. 58.. 58.. 58.. 58.. 58.. 58.. 58.. 58.. 58.. 58.. 58.. 58.. 58.. 58.. 58.. 59.. 59.. 59.. 59.. 59.. 59.. 59.. 59.. 59.. 59.. 59.. 59.. 59.. 59.. 59.. 59.. 60.. 60.. 60.. 60.. 60.. 60.. 60.. 60.. 60.. 60.. 60.. 60.. 60.. 60.. 60.. 60.. 60.. 61.. 61.. 61.. 61.. 61.. 61.. 61.. 61.. 61.. 61.. 61.. 61.. 61.. 61.. 61.. 61.. 61.. 62.. 62.. 62.. 62.. 62.. 62.. 62.. 62.. 62.. 62.. 62.. 62.. 62.. 62.. 62.. 62.. 63.. 63.. 63.. 63.. 63.. 63.. 63.. 63.. 63.. 63.. 63.. 63.. 63.. 63.. 63.. 63.. 63.. 64.. 64.. 64.. 64.. 64.. 64.. 64.. 64.. 64.. 64.. 64.. 64.. 64.. 64.. 64.. 64.. 64.. 65.. 65.. 65.. 65.. 65.. 65.. 65.. 65.. 65.. 65.. 65.. 65.. 65.. 65.. 65.. 65.. 66.. 66.. 66.. 66.. 66.. 66.. 66.. 66.. 66.. 66.. 66.. 66.. 66.. 66.. 66.. 66.. 66.. 67.. 67.. 67.. 67.. 67.. 67.. 67.. 67.. 67.. 67.. 67.. 67.. 67.. 67.. 67.. 67.. 67.. 68.. 68.. 68.. 68.. 68.. 68.. 68.. 68.. 68.. 68.. 68.. 68.. 68.. 68.. 68.. 68.. 69.. 69.. 69.. 69.. 69.. 69.. 69.. 69.. 69.. 69.. 69.. 69.. 69.. 69.. 69.. 69.. 69.. 70.. 70.. 70.. 70.. 70.. 70.. 70.. 70.. 70.. 70.. 70.. 70.. 70.. 70.. 70.. 70.. 70.. 71.. 71.. 71.. 71.. 71.. 71.. 71.. 71.. 71.. 71.. 71.. 71.. 71.. 71.. 71.. 71.. 72.. 72.. 72.. 72.. 72.. 72.. 72.. 72.. 72.. 72.. 72.. 72.. 72.. 72.. 72.. 72.. 72.. 73.. 73.. 73.. 73.. 73.. 73.. 73.. 73.. 73.. 73.. 73.. 73.. 73.. 73.. 73.. 73.. 73.. 74.. 74.. 74.. 74.. 74.. 74.. 74.. 74.. 74.. 74.. 74.. 74.. 74.. 74.. 74.. 74.. 75.. 75.. 75.. 75.. 75.. 75.. 75.. 75.. 75.. 75.. 75.. 75.. 75.. 75.. 75.. 75.. 75.. 76.. 76.. 76.. 76.. 76.. 76.. 76.. 76.. 76.. 76.. 76.. 76.. 76.. 76.. 76.. 76.. 76.. 77.. 77.. 77.. 77.. 77.. 77.. 77.. 77.. 77.. 77.. 77.. 77.. 77.. 77.. 77.. 77.. 77.. 78.. 78.. 78.. 78.. 78.. 78.. 78.. 78.. 78.. 78.. 78.. 78.. 78.. 78.. 78.. 78.. 79.. 79.. 79.. 79.. 79.. 79.. 79.. 79.. 79.. 79.. 79.. 79.. 79.. 79.. 79.. 79.. 79.. 80.. 80.. 80.. 80.. 80.. 80.. 80.. 80.. 80.. 80.. 80.. 80.. 80.. 80.. 80.. 80.. 80.. 81.. 81.. 81.. 81.. 81.. 81.. 81.. 81.. 81.. 81.. 81.. 81.. 81.. 81.. 81.. 81.. 82.. 82.. 82.. 82.. 82.. 82.. 82.. 82.. 82.. 82.. 82.. 82.. 82.. 82.. 82.. 82.. 82.. 83.. 83.. 83.. 83.. 83.. 83.. 83.. 83.. 83.. 83.. 83.. 83.. 83.. 83.. 83.. 83.. 83.. 84.. 84.. 84.. 84.. 84.. 84.. 84.. 84.. 84.. 84.. 84.. 84.. 84.. 84.. 84.. 84.. 85.. 85.. 85.. 85.. 85.. 85.. 85.. 85.. 85.. 85.. 85.. 85.. 85.. 85.. 85.. 85.. 85.. 86.. 86.. 86.. 86.. 86.. 86.. 86.. 86.. 86.. 86.. 86.. 86.. 86.. 86.. 86.. 86.. 86.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 100 - Done\r\n"
     ]
    }
   ],
   "source": [
    "!gdal_calc.py --calc \"A*B\" --format GTiff --type Float32 --NoDataValue 0.0 -A $path'gadm36_USA_0.tif' --A_band 1 -B $path'hdr_nodata_0.tif' --outfile $path'usa_tot_wf.tif'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "id": "902ed7d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Define the colors you want\n",
    "cmap = ListedColormap([\"#ffffff\", \"#fdae61\", \"#ffffbf\", \"#abdda4\"])\n",
    "\n",
    "# Define a normalization from values -> colors\n",
    "norm = colors.BoundaryNorm([0, 214, 429, 644, 858], 5)\n",
    "\n",
    "with rio.open(path + 'usa_tot_wf.tif') as src:\n",
    "    dat = src.read(1)\n",
    "    fig, ax = plt.subplots(figsize=[15,10])\n",
    "    ax.set_ylim((20,60))\n",
    "    ax.set_xlim((-130,-60))\n",
    "    rio.plot.show(dat, norm=norm, cmap=cmap, ax=ax, transform=src.transform)\n",
    "    gadm_usa.plot(ax=ax, color='red', alpha=.1, edgecolor='red')\n",
    "    ax.set_title('Total Water footprint mm/yr in USA ')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "id": "0695eace",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Driver: GTiff/GeoTIFF\n",
      "Files: ../../datasets/raw/wf/QA/usa_tot_wf.tif\n",
      "Size is 4320, 1668\n",
      "Coordinate System is:\n",
      "GEOGCRS[\"WGS 84\",\n",
      "    DATUM[\"World Geodetic System 1984\",\n",
      "        ELLIPSOID[\"WGS 84\",6378137,298.257223563,\n",
      "            LENGTHUNIT[\"metre\",1]]],\n",
      "    PRIMEM[\"Greenwich\",0,\n",
      "        ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "    CS[ellipsoidal,2],\n",
      "        AXIS[\"geodetic latitude (Lat)\",north,\n",
      "            ORDER[1],\n",
      "            ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "        AXIS[\"geodetic longitude (Lon)\",east,\n",
      "            ORDER[2],\n",
      "            ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "    ID[\"EPSG\",4326]]\n",
      "Data axis to CRS axis mapping: 2,1\n",
      "Origin = (-179.991666650000013,83.097781811000004)\n",
      "Pixel Size = (0.083333340000000,-0.083333340000000)\n",
      "Metadata:\n",
      "  AREA_OR_POINT=Area\n",
      "Image Structure Metadata:\n",
      "  INTERLEAVE=BAND\n",
      "Corner Coordinates:\n",
      "Upper Left  (-179.9916667,  83.0977818) (179d59'30.00\"W, 83d 5'52.01\"N)\n",
      "Lower Left  (-179.9916667, -55.9022293) (179d59'30.00\"W, 55d54' 8.03\"S)\n",
      "Upper Right ( 180.0083622,  83.0977818) (180d 0'30.10\"E, 83d 5'52.01\"N)\n",
      "Lower Right ( 180.0083622, -55.9022293) (180d 0'30.10\"E, 55d54' 8.03\"S)\n",
      "Center      (   0.0083478,  13.5977763) (  0d 0'30.05\"E, 13d35'51.99\"N)\n",
      "Band 1 Block=4320x1 Type=Float32, ColorInterp=Gray\n",
      "  NoData Value=0\n"
     ]
    }
   ],
   "source": [
    "#explore output for no data\n",
    "!gdalinfo $path'usa_tot_wf.tif'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "id": "ac006eb9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "shape: (1668, 4320)\n",
      "noData: 0.0\n",
      "GLOBAL Total sum excluding no data: 13675209.0 mm/yr\n",
      "GLOBAL Total sum excluding no data: 13675.209 m3/yr\n"
     ]
    }
   ],
   "source": [
    "src_usa = rio.open(path + \"usa_tot_wf.tif\")\n",
    "print('shape:',src_usa.shape)\n",
    "print('noData:',src_usa.nodata)\n",
    "\n",
    "image_read_usa = src_usa.read(1)\n",
    "src_masked_usa = numpy.ma.masked_array(image_read_usa, mask=(image_read == src_usa.nodata))\n",
    "\n",
    "print(f'GLOBAL Total sum excluding no data: {src_masked_usa.sum()} mm/yr')\n",
    "print(f'GLOBAL Total sum excluding no data: {src_masked_usa.sum()*0.001} m3/yr')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b7d979bd",
   "metadata": {},
   "source": [
    "The values obtained above are calculated with the zonal statistics for the entire USA using the gadm level 0 boundary, with no simplification, and without multiplying by the pixel area in m2. The value obtained is directly transformed from mm/yr to m3/yr by mutiplying by 0.001.\n",
    "\n",
    "Now we are going to obtain the value by multiplying each pixel by its area in m2 (being the area around 10km*10km):\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "id": "7a2dddc8",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 13.. 13.. 13.. 13.. 13.. 13.. 13.. 13.. 13.. 13.. 13.. 13.. 13.. 13.. 13.. 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97.. 97.. 97.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 100 - Done\r\n"
     ]
    }
   ],
   "source": [
    "!gdal_calc.py --calc \"(A>0.1)*A*10000*10000\" --format GTiff --type Float32 --NoDataValue 0.0 -A $path'usa_tot_wf.tif' --A_band 1 --outfile $path'usa_tot_wf_area.tif'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "id": "18f3e077",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Driver: GTiff/GeoTIFF\n",
      "Files: ../../datasets/raw/wf/QA/usa_tot_wf_area.tif\n",
      "Size is 4320, 1668\n",
      "Coordinate System is:\n",
      "GEOGCRS[\"WGS 84\",\n",
      "    DATUM[\"World Geodetic System 1984\",\n",
      "        ELLIPSOID[\"WGS 84\",6378137,298.257223563,\n",
      "            LENGTHUNIT[\"metre\",1]]],\n",
      "    PRIMEM[\"Greenwich\",0,\n",
      "        ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "    CS[ellipsoidal,2],\n",
      "        AXIS[\"geodetic latitude (Lat)\",north,\n",
      "            ORDER[1],\n",
      "            ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "        AXIS[\"geodetic longitude (Lon)\",east,\n",
      "            ORDER[2],\n",
      "            ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "    ID[\"EPSG\",4326]]\n",
      "Data axis to CRS axis mapping: 2,1\n",
      "Origin = (-179.991666650000013,83.097781811000004)\n",
      "Pixel Size = (0.083333340000000,-0.083333340000000)\n",
      "Metadata:\n",
      "  AREA_OR_POINT=Area\n",
      "Image Structure Metadata:\n",
      "  INTERLEAVE=BAND\n",
      "Corner Coordinates:\n",
      "Upper Left  (-179.9916667,  83.0977818) (179d59'30.00\"W, 83d 5'52.01\"N)\n",
      "Lower Left  (-179.9916667, -55.9022293) (179d59'30.00\"W, 55d54' 8.03\"S)\n",
      "Upper Right ( 180.0083622,  83.0977818) (180d 0'30.10\"E, 83d 5'52.01\"N)\n",
      "Lower Right ( 180.0083622, -55.9022293) (180d 0'30.10\"E, 55d54' 8.03\"S)\n",
      "Center      (   0.0083478,  13.5977763) (  0d 0'30.05\"E, 13d35'51.99\"N)\n",
      "Band 1 Block=4320x1 Type=Float32, ColorInterp=Gray\n",
      "  NoData Value=0\n"
     ]
    }
   ],
   "source": [
    "#explore output for no data\n",
    "!gdalinfo $path'usa_tot_wf_area.tif'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "id": "d6ddd04c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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JiIiIKDkYnRIRERFRajEYJiIiIqLUYjBMRERERKnFYJiIiIiIUovBMBERERGlFoNhIiIiIkqtaINhYyJ9OCIiIiKichgMExEREVFqeQqGRWS/iDwiIg+JyN78Ze8TkUP5yx4SkesrPxqrMoiIiIgoObI+rvtKY8xw0WV/boz5eJADIiIiIiKKClO1RERERJRaXoNhA+BrIvKAiNziuPz/iMjDIvLPItLndkMRuUVE9orI3qGhoZoHTEREREQUFK/B8HZjzEUAdgD4TRF5BYC/A3AGgAsBHAHwCbcbGmM+aYzZZozZ1t/fH8CQiYiIiIiC4SkYNsYcyn8/BuDLAC4xxhw1xiwaY3IA/gHAJeENk4iIiIgoeBWDYRHpEJEu+2cArwLwqIisc1ztJgCPhjNEIiIiIqJweOkmsQbAl0XEvv6/GWP+R0T+n4hcCK0n3g/g18MaJBERERFRGCoGw8aYfQAucLn8F0MZERERERFRRNhajYiIiIhSi8EwEREREaUWg2EiIiIiSi0Gw0RERESUWgyGiYiIiCi1GAwTERERUWoxGCYiIiKi1GIwTERERESpxWCYiIiIiFKLwTARERERpRaDYSIiIiJKLQbDRERERJRaDIaJiIiIKLUYDBMRERFRajEYJiIiIqLUYjBMRERERKnFYJiIiIiIUovBMBERERGlFoNhIiIiIkotBsNERERElFoMhomIiIgotRgMExEREVFqMRgmIiIiotRiMExEREREqcVgmIiIiIhSi8EwEREREaUWg2EiIiIiSi0Gw0RERESUWgyGiYiIiCi1GAwTERERUWoxGCYiIiKi1GIwTERERESpxWCYiIiIiFKLwTARERERpRaDYSIiIiJKLQbDRERERJRaDIaJiIiIKLUYDBMRERFRajEYJiIiIqLUYjBMRERERKnFYJiIiIiIUovBMBERERGlFoNhIiIiIkotBsNERERElFoMhomIiIgotRgMExEREVFqMRgmIiIiotRiMExEREREqcVgmIiIiIhSi8EwEREREaUWg2EiIiIiSi0Gw0RERESUWgyGiYiIiCi1GAwTERERUWoxGCYiIiKi1GIwTERERESpxWCYiIiIiFKLwTARERERpRaDYSIiIiJKrayXK4nIfgATABYBLBhjtonICgD/AWAzgP0A3mCMGQlnmEREREREwfOTGX6lMeZCY8y2/O/vAHCXMWYrgLvyvxMRERER1Y1ayiReB+DT+Z8/DeDGmkdDRERERBQhr8GwAfA1EXlARG7JX7bGGHMk//MggDVuNxSRW0Rkr4jsHRoaqnG4RERERETB8VQzDGC7MeaQiKwG8HURedL5R2OMERHjdkNjzCcBfBIAtm3b5nodIiIiIqI4eMoMG2MO5b8fA/BlAJcAOCoi6wAg//1YWIMkIiIiIgpDxWBYRDpEpMv+GcCrADwK4L8AvDl/tTcD+EpYgyQiIiIiCoOXMok1AL4sIvb1/80Y8z8i8kMAnxeRXwFwAMAbwhsmEREREVHwKgbDxph9AC5wufw4gKvDGBQRERERURS4Ah0RERERpRaDYSIiIiJKLa+t1YiIKGwzM8DgoP7c0QGsWAFkMvGOiYiowTEzTESUFMYAk5PA4iJw9GghMCYiotAwM0xElCRNTUBbG9DcrJliIiIKFTPDRERJYRyLdGYywMKCZomJiCg0DIaJiJJKBDh5Mu5REBE1NJZJRMkY4LnngDVrNOtz5AgwPw9ks0AuB1iOYxMR/fIilytc1+ttgrS4qI9rj98Y/bKsws/FRPTy4vFWM/6FBf2erXJ3trefPZ44tqHNbVsBhTG5/d3exs7XoNz9u21352P4YY8niG3m3G9quY9czvuks8VFfbwK48/dcSsgWHI967pPeBuPn+c0P7/092wWmJoCuru93Z6IiHxjMBwlEaCzUz8Yp6b0K5stBDHOD+RSQaQb5/W83iYMuVxhDCKF34HSz614vNWM3w40nI/nR/FY4tyGpVQak719vW6DUkF1Cbn/+YMlv1vX/VnhNvaBhMv1XG9TQe6Ot8G67s/K3lfF+3fZDu73Z6BRbiWiV3Vsotwdb/M2FjtA9yKT0VphW3MzM8NERCETE+EH/7Zt28zevXsje7xEW1gADhzQ711dcY+GqpTbcyusHbfFPYxEye25ddllfraR2+39Kn68IO6z1jHYfO8z4+PAWWfVljEnImpQ27Ztw969e2s6Pcl316gZAzzxBPDkk0B7u2aHh4eZ/alTDIRVuWAzjm1kjye359ZYAmE39liqCtSLyyeIiCgwDIajMjMDPPII8PTTwLPPAk89BRw8CDz2mPYTnZiIe4REp3gJ0JwBp/O7W/DrNSANOnC1dtyWiAOWctum4viam/Us0vPPA888Axw6pGeUqi0LIiKiJVgmEZWTJ4F/+RetCezrAzZvBmZnNTO8ciXQ0qLf45y8ReSRM2i1dtxWMtgrDm7LBX7VBMLO+3OOoTgDW650I8zMcWCBeC6n7xeWtTRLnM0Cra2FSbnG6HvK8eMaMLe16WXt7ToJj6UWRNRggiiT4AS6qLS2Auefr1ngp57S7ytWaNanq0sn1vmZBU8Uk+JA2PndTVSZWefjFAfEzoC91HXDUC4j7ItlaWAL6IHzqQfIAWNjGuxmsxowHzmi181m9YxULqdnnk6c0IC4u3vpJD0iopRjMByVTEaD4b4+/ZAaGwOmpzUgzmaBuTnkvvYHiTilS1RKNRMGvd7GT6a2mjF4uazuWJYeaB89WjiY7u52bzM4N6fLO+dy+j7U1BT9eImIEojnzPx69lmt+61mwtvKlcDq1XpK89xzgYsv1szN/v2FXrlECeY3CA3r4K7eAll78lwo425p0bNLPT16hqlUv+3mZv06cULfc+ya4/l51h8TUaoxM+zX3BwwOakfICtXFjK7Xq1dq1/z8/o1M6P1fZYF67I/Dm/cRDEJIyD2ep/1FjSHrrNTv4+N6QH9sWP6PpTJABs3Fkox4rK4qIkBZykIEVHImBn267TT9AOjqwsYHdXZ3YcP66QVPyxLT212dgIbNmjN3+xsKENuVElqm0XJUmniXqn64dRobtaD8Lk5Lauwa48rtXBbXNTrzc0FN5bFRWBkRFfntLvtHDzI90MiigyDYb/sDwzL0kC2vV1rf/ft09ZHY2M6WcXuHTw3VyiBOHxYvwC9vb0UrH1/nDznS5jdAJyntRl0R6tUcFqpO0Sp61YKduNYOCX2/amtTd+b7Il0nZ26uMczz+jXzMzS6+dyWl6xb58Gq8PDtY/BGH2vfPZZYGhIf+/q0uB8bk4vHxxkj2UiCh3LJPxaXFza/iyT0Q+WlhbNDo+N6d/n53WCSiaj30X0A6a5WRfdMEY/fJqaNANin6rM5dj+yIcwOwFQfNxeV7+vs5fWanHsO176MkfCLpkACkvFAxqgHj6sQWlvr77nDQ7q+1dHhyYATpzQ96upKf3dfk9cXNT3uL6+8u9js7N6ZmxqSu+zOBHQ2qrvqZOT+j65YoXeJxMGRBQCBsN+rVih5RHF7ExxMWMK/UF7erRGb3GxkFFuatI3+aEhvf7IiH4QrFsX6tMIQ1xLEwf1mF7GH3sAk3BBbp9ymf8g7j/OpbQTfRDX1aVntYaGCu9LTU1Ll43v6dFAFdDvxhQC4rExPRvW2anfRZa2hjtxQks0mps14C5FRN8njdH3xZERnYDc1cWEAREFiotu+DU5qTOx+/qqWyBjbq5QPjE9rR8I7e3Iff1dwNg0rFd/ALlvfwhY2VE3AVecQUWQGOgmT63LPNv7Zqn78bJISFhBa8PuZ/bCHwsLmsmdntbgtaWl8J7pzCZ7tbio99vUpB15OjqCHzsR1R0uuhGHzk59Uz9+HFi1yv/t7fZGi4t6+g8AsllY1/8ZMDyM3N6PASvr802+3oNiO/BxC6Dq+XnVGz/1wJX4DWbDztiWCr4bav8SWRqo2mfMjNGvarO6mYxmhefndX5GR4dmitl5gohqxHNN1di4UTMbbuUSXh0/rgFxJqPZ5vZ25O7/KNASz/FJLZPE/ExsSjprx22uq6rV+/OqF0Fu50r7tFsAWqpOOciyj+LLGioQLscul6hVU5OWV8zP61m6Y8fYp52IasJguBptbVrTK6IBrV/GaDajtVXriScntWxCpLrSixppJnSX79u4abQPdjtYabTnVW/C2P5h1SKXezweVAWotbXQBePZZzU5wcVDiKgKDIar1dqqM62np/3fdnJSg+FcToPgXA6YmIB1+XsDH2YYimfD2xgwUhTCDijdDn6CekznpEAGxwGwJ9m1tWl3iv37q1sdlIhSjTXD1bIsrV+bmPB3u4UFDX6npjQQtqxCx4m4V3/yoNKEpKg1ZM1livlZWa7Sdb3sp+Wyw372c/vMSm7P7orXZS16COz3Y7ueuKsL6O8v9FEmIiqDmeFqiWjwmstpMOvVyIiWVvT06Cm+bLZwH0Gu6hSw4qCzVPYsKUEyNb4o9jXvwXnlIFivx/+PUNn1xDMzhcVBqillI6JUYTBci0ymsFCGFzMzhYU4Jie11KKrqxBUZ7OR1Kg6P5ALGbbLyj6mn/GkIShu9OeXVH5WlvN6nWJR7b/MCoeorU2TDSMjGhSPj/tLWhAFaWhIlxv3eyaZIsNguFbZrPeMrt1KbXFRyyKGhrRB/fS0vnnPzISexXDW+3r9wPdyPXsSnv3l9Xa1CnNJZi+PS9Gq5nWu9rXy+1hes8MUEbvFW0sLcOQIcODA8mWmicI2MaGf9ZOTupKj20HZ3Jxej/tnbFgzXKu+PuDgQW/1vnb3iNlZfXPesEEne7S26j9CZ2eo3SSqrVUsdd1S9bp2UBBVwMjANB1qeZ0r7cOl+KkZ9hMMc5+NkN2feHa2sGDSypWayCAK09ycLm1ur95od42yzc7qZ//JkxosZzLA2rU6OZ8ixXeDWvX06PKis7OVm793dWl2eHhYs8EnTxaC4s5O5O76Y1g3/x2AMBawuHfJJB/n/RcHyZVaTrn1Yi0OBvT3+l6Eg9Ij6kmh/N+IQUuLTqgbH9ev1au1vjiGdpaUAsbo53s2q0GuPS/oxAktlxwZ0Yn0dkvVnh69zuCgXq+/n/tmhFgmUSuRQgN4L4zR+uCWFj0lMjen/yxr1pwKhIHgM0fFgapTEKUNhWzwLt9ZMqK4sMwmZezSiba2QulENe0xiSoZGdHPePussb3vHT4MHDqkcUBnpybJOju1I4p9FuP48doW9SLfGAwHoblZM8Ne6n1bWoDNm4EzztBTIQMDuqJdgEp9sGtGeLenQJUf1kTe+T344wTMmFmWJjEADYgHB7mKHQVnZkZXRrSXIrdls8CKFbrvNTe7r8goorc7elTnFFEkGAwHIZMp1P2OjZVu+i6iR31zcxo4r18PnHmm3j4gXhfEWFr2sNv1b167WhRPnCv1mESNzu9KjhSz5mYNTCYngX37NBvHrhNUi1xOs7+trdWXOWQyupjM8HCwY6OSGAwHwRgNbsfGNLswPFz6DbWtTQvk16zRHT7gmiA/ixY4J8DVUtbgdlu7ZpjIqzj2F+6jBEADj/b2wip2LJ2gatm9rWtd8MWyWDMcIU6gC0JLSyEgzmaBTZti3YlLBcTlJsE5VQoQiicbFWfDWC+cLrVMBkvaioa1qrTvN9JzbTj2KnZzc1o6sXmzZveIvJqa0glydvcIqhvMDAfBXvWovb1yR4mEKFcCUak8Ynk3ieIyi12n7se+PgOAxhVEy7OoJ7JVs0/6KRkqd/uwF9WhGjU361m72dm4R0L1ZGFByyPa25nRrUMMhoPS0aFZYXsxjRhU+oB3+/vScoldSy4rDlTsv7nf9+4l3/W+7mUQTJ4VB4lh7jvVBKS1jof/C3Ukm9U6YiKvjh7V7+xfXZf4qgWltVUD4oWFWLPDtSyp7Axk7V7Efu7D7jdMVI5bX2u3/SqK7GnQZQvlyiTKPdfC7d0XsqGINTfrKe9czn3GP5HT4qIePLE8om7xvzwozrY8tRbO16BUN4lSNEPmXvPr5wPZrXRiaW9j1kqSKtfZpJGVPqty67KzNvxfiZmIzgMZGlo6GXpujuUTtBzb8tU9BsNBsSx94xwZiXskvgNioHRLKD9BrN2VolR2LC1BD1Vmlym4BYL1JIh9mv8XCdXZqe/nJ07oe/uzz2qnif37vS+yROnAYLjuMRgOimXpP8TJkzqhLq5hFE3gqTXQ8BpYu9UXExHVtc5ODYRPnND3+NZW/c66ULIZU9g/qG7xPzooc3O6tvjUlL5RTkzoG2nEs0pLdXYoV6voVs7glhH22kJLr3Pvqft26xTAoDm9/NaihymOSXHlaqTrNUPesJwr1QEa+ORy+p0dAwjQDhIjI8DKlcHfdy4X/H2SKx7KBGVqSmeTGqPrio+MAA8+CDz9dGRDsE89O7/cujsUZ4uXzqy3g9hagwT2GqbyouockUTFZ1x4ZqVOiGiJBBflIECXXZ6YAFat4sFRnWMwHJTubj0ytHsMfu97wBe/CDzzTNwjO6U4QHVbstk5ea7W/rGlssJuvyddvY03yZz7VlJ67joPIKPitbMEJczCgi7bTDQxoT2pw8DgOlIMhoPS3g5s3aqn1R59FOjtBW64Abj66liHpR+2l5XM1IY5gcn5QZ+UoIeSKa59w22/jGMspc7UMCBOoJUrNQiangbGxvRrdFTba1G6iHDyXINgMByk9natFz77bOCaa4DLLquLiRZuQatbgBzkzPl6C4zrbbwUrDiD9VIYKMckk9H39YMHgUOHtDzu6FGtHWWNZ7qMjcU6YZ6Ck/xIrZ7MzmrN8OrViTvF4ZycU2mBg7A/ZBlYUpJFGWTapRJ+Fx1hIByz9nbNCHZ0FC4bG9OFF5wT7qhx2ZMp2UWiITAYDtLJk/oGmbBA2OYlCC31IcsAltIgCUFmuYPWaju8UAicZ/0WF/X39vb4xkPREtHXe2ICaGsL/v6N0f1qYaEuzjDXO27hILW31+0pk3JBAD9sFVvDpVe51z6qALrcCnbcH2M2NQWsWcOgJU1GRzUQDusAaHFRS3KYeY4Et3KQpqa01YqPiRRxZaKcNcFJyIbVG26zdPJbzuBVpYms3N8SLpvVxTnGx5cu30yNa3i4ME8oDHYJBoPhSHArB6mrS98MBwcrXrXcqdAoOcdRPLmNHSCW4ragMJQLgEsFyG7Z6Xpe1rrutbXp6nSHD+vEurm5uEdEYVlY0Nd5bi78kkhjNPtMoWMwHLTubmD9+rJXSdIHVnHAW6/dHqIS5nZJ0n5ByRNlL2Tui1XIZPT9f24O2L9fF15ilrixLC5qB5GJCW2fGlaPYQBoadFJ+QcPareS4WF2KwkRg+Eg2fVDMzMVrxrUB5qfDy23lefIP2bMG5OX/6UkTDB1a3kYZKDMQLhGbW36OXDsGHDggKfPA6oTo6P6enZ1RfN4vb3asWRyUs84z85G87gpxGr/IE1P61KdU1MVZ5cGNenFz30E+UHJYJCSzG0/rfQ/52w/mETOsdnPxT7ArdQa0a2sotxt+P9dI8vSgGl2VrPEq1YBK1aw/rOeLS5qUBp1t6hsVksz2trCzUSnHP8zg2RZ+g+zalX5qyXggyasMSQ5mEi6JOwXjaJ48RjnZFG39mRe6m0rZV7dyo3CVm5CX6lscXFQ7YYT+QLS0qJB8YkTGhRPT8c9IvLL7idsZ2bn56MfQ1OTPm5C27Y2AmaGg9bgTbgrZc8Y0FGSlNof/Z6ZqbRojZfsrF/l/tcqBd7lnrfz78X3U+nMD/+/qyACdHZqLfFzzwGbN2uQTMk1P6+vV1OT1gjncoU2Z2H0FK7EslgvHLLGjdrikMl4OnIrl6WqB/xApLQpFzyH1aIwjPcGZ8a8+PLijHGY7031+t5Xk+Zm/R5HZpG8O3lSa73379cvOzCeni50DYlaLqf7TybDSZkh8ZwZFpEMgL0ADhljdorIvwC4AsBY/iq/ZIx5KPAR1pO5Oe6oRHWg2gO6KJctLyeIGt/iybR2QOwMjMNY0CN1QbBTJqOn2js74x4JlTI/r69RT48Godmsfo+zTCGT0brhI0d0bL29WoNOgfGTGf4dAE8UXfYHxpgL818PBTesOtXaypoeojriNTBr9LMhtU6M9ZPpTXX7xmyW3SWSzO7r29ampQn2ghqWFX9pS2enrmMwO6ut1tjLOlCegmER2QjgBgD/GO5w6tzkpLZB8SGVHwhEEQhyIYqkZzP9tlis5nK3iYdu1/U6GTGVsllOoivFGA30jh/XFmZjY1qyMDWl22x6Wn8+eVI/aycm9Dr295ERve3QkPvXyMjS69u3sb+OH9cgc3w8nlKISixLs9U9PbqtRkfjHlFD8Vom8RcA3g6guLneh0XkvQDuAvAOY8yyJngicguAWwBg06ZN1Y+0Hiwuejp6THoLp0rCOHVKFBSv/YJLTR6rVVJKKbywx1qu7tmZyfUSEDv/Vuv7RMO919gdhxYWwlvGtx7NzRWCUpFCBwe3beScpG7/LAKIIPe1d8B69UfdH8OYwhdQeBz7vuyzulH1EK7WyIgeFMzNaWAcd8a6QVTMDIvITgDHjDEPFP3pnQDOAXAxgBUA/tDt9saYTxpjthljtvX399c63uTK5Xy1XWmoN3iiOlOp726l61f7OP5uu6vq27qplLH10pUiqlXw3PonNwwRDYZJPzdHRnSi2tiYBqJdXbqSX2+vlgYUf3V3L/+5owNob4d1418BbW3I3f1uLXVwfrW36/Xs29o/t7frl329pB+kjI0BjzwCPPaYtnujQHgpk3g5gNeKyH4AnwNwlYj8qzHmiFGzAD4F4JIQx5l84+N6lOmx7Uo9v9HX67ip8XlZcMLv30vdb63XtXbs8hTweg2Ki7vUFH9VGqvfSXl++i77kfRseiAYDGsgfPiwTgprb9fANKA5Nw39GbVqFbBunR4scI5SYCoGw8aYdxpjNhpjNgN4I4BvGmN+QUTWAYCICIAbATwa5kATz+fKMA39z0oUg2oWiiiezBXdYhm7XH8uvqz4eyXLA1pvAXel+wx7oqHbuIMYTyLZHSXSbH4eOHhQ6397exu6N39gBgf1wKG5GVizBjj33IoLfJF3tZwP+KyI9AMQAA8BeEsgI6pXbKlGFJtaF4LxWmcclNye3b5v4wwQvdy+OOAud5vi2mE3Xs5muS0Z7fX6lR7fy9/rQiaT7o4SuVyhRVjS63PjdvKkTuY7ckTPJtgT/wYGgNNO00VBKBC+DseMMXcbY3bmf77KGPNCY8z5xphfMMZMhjPEOjE9zYCYKCa1ZHTDCLBqvc/cnt2nglfnz7ag64kL97t08l9xL+Jyt/Oy9HMt28XrWBIvm01vZjiX0xXdpqd9d15qeEeOLK0B3r9f66mffFJrhO+6Sy9rbgbWr2cgHLCEV4rXkfZ27pxEMSrudhBURrjaThPBdFNYns31mlXO7dl9KmheHkx7G5dzIY5y13H73eu2dbtu8XgbIiNssyzN8jm7IqTF0JAGwmnOCNudM1pbtRvE0JB2GAH0IOnQIT178NRTWlO9b58eOFxxBXDllUBfX6zDb1RiIsxmbtu2zezduzeyx4vU0aN6ZLd6ddwjIUo1v0FopaWJG5nbdqp1AQ43lQ5SKpW5BLHiXqJMTgKbNxeWaE6D2VnNbKY5ED56VA+ELEvrptva9PfJSd0+zz0HrF2rNcF33qlJtu5uTbTdeKMGz7TMtm3bsHfv3ppmEzIzHKQkNuomShm/gVK54NdPlrMeuQW+xaUSwfQK3pXPVLvfV7nt3KjbHgsL6QiGFxd1oYtjx9LxfMtpatJSiNFRrfldWNDM8PPPA2edpcm0sTENiF/6Us0EZ7NL+yFTKBgMB2V6Ovn9CSNUz63jKH1K7at+M5b1qDgQDfN5lXtfKPf4zssa4n1FxHNP+ro2O6uB3sKCJovSHgzncrrS3cyMlkH09+sCGqtX69/6+4Gzz9bMcHf38gVBKDQ81AiKSMUjt0b44PQjbc+X0qVR9m/nAhdeWsxVVz+92/V+q1kyO8xAPbLXNA0dJcbHCxPCursZCC8uauA7NaXZ4IkJ4L//G3j4Yd0XDh3SOOLss9luLgbc2kHx0ES9ITIaDahRghoKRqmFO6JafS1OXmp7qylDCWJcYW//SF/bbLaxg+HpaZ1Dk8tp3WuEEvd+bs/LGh3VIHfLFj1QaG7W0pFVq/QswemnAy9+cZwjTTUGw0HyufBGo0rcm1EZzg/3Sj1W677ZP3niJSCKOii2F88IqqVapTZopS73O/mt+DEr3S7ojHQSuI47k9GuAo3YjnNuTksjWlr0K0Kx7yPGaGLMzooPD+u2GBvT7TI9DTz6qP6tpwc480zg4ou1b/CWLexIFSMGw0HI5fQUSMp35EaY/OIMeIsDYDsYqbfnRLWL+zV3thoLq8dw4bGc+3yp1mf+tkcc2eQoeDmAdr2eSOFzo9EMD2uwn7ayiLk54KGHgJ/8RLPiAPDss1oKceQI8O1vAz/8IbB9O3D99cC2bcDP/7wGw5dfrkssizTmPlEHGAwHpRGP8H0qNzEm7mCinHJtm4ozctWsHEb1p16CsXLKZZNrWWI5qP9lr1nmJL4WzjrrUn/3cpmX8rq6MjOjWdG2trhHEr3BQV0x7sc/Bh57TNuoHTigi2Y88ICWQ2zfDrzwhcDrXqfB7wUXLD1oMIaT5WLCYDgIjVz7lRJumbDiIIKBcLoVB5BRH+D53f/cVq7zym0hjVLlEsWt2JaPo7oFS9zG0VBEGi8YPnbMc2lEGP8/sdT0LyxowPvMM7qYxuQk8L3vaVZ461bgzW/WLPA112hA/NhjwD336EFDceBrWZw4FxNu9SDwSG6ZsE/lBqX0JKFduP3AIG4/MJi/bHfDT54ib+I801FNgFttQFzqjEml1eiCzhzHeVaplkC+4t8ymcZalnlqSmtiI64Tjt1jj+lSyT/8oS4qsrCg9b+trcArX6klEJdeqksor14NbNoEvOhF+jslBhvjBmFqinU+LpZnVpPZe7gwpnsB3Htq3DsH1uL2A4NlFwsgiovz/yuMsxbllmIul7n1en0vE/biUu0YfN2ukdqrGaNlAT4WnmqI99RDh7Q12qOP6gIZK1cCnZ26dHI2q9vDmKVrEPT3s6wygRgMB2Fyktlhh8KHaP3U2eb23Io7ztt+6vedA2sL3weWnzImilMUk+gq/c0tsPUaHNeLWpb1tm9vH1As+3s2q5nUuCwuapeDsTF/t7M/65yfecboBLK0LbVsWfqc3/524OUv120gsnQyvVv9NOOFxGGZRBAWFtL3JlCBvvkvP6WbhKxPKTsH1mLnwFpc//g9AJaekk76JEDyr+xs/xqFHQAW/1/FWZbk1p6w0vasZqJcHEG1l+fh9t7ga3tEnSVcXAROnAD27St0fshmvX1lMoW6VpHCl2VpRjRNxsa0P/Dll2sgDOhkuJR3lapXzAzXan5e677S2EqmgnparnZpqcTyFbPqObuVdpXKc8IIiOPY77XtX7BnYfx0kvBa4+unPMLZ1jBM5ZaCLvW3UstGezYzo4swRJUlNEYneB0/rj+3t3OyVrUWFvSMcHMzcNppcY+GAsD/hFodPqynRoaG4h5JIhXPOk9yUFn8QZfksZI/cXeCKCXIhTSCVq7kYWnXleVlRKXqhr0E087rR8HrflFp8RHfFhejzabmctrtobVVH5eBcPVEdDnllhY9oKG6x8xwLaam9Oh+cjJ9M2h9SHJQufQDLplBCdWmHs5QhJHVrZWXVmrF2eBSAW1x726351o+EN0Na8dlfoYfKs8dI0qxF2mK8nMjk9HWXqOjkS+R3FAmJ/VscHs7cN55cY+GAsJguBb2qZI1a4COjtiGkdQuDUnnNsmPnSMoDn4C4TgO2spNkKvUW7j4YKTccy3VbSLM/8koW7ideh4zMxqYRj2RqrdX64V9LO7Az5c8e5vNzgIrVgDnn8+JcA2EwXAtRHTiXIyBMJDszGu9sLNV3Jbp4AzQ4s4cV9M32H1VufAyy15XWqt1sQxn4BV1n+Gg9gNPXTZyuXg+N7JZrXNdXASy2WWdLvj+V8L8vB5ENDdrUNzUxEC4wTAYrsXkpJ56orp2+4FBXP/4PfwgaGDl6l/jDIprDWCjLq0ozhL6/Z+ptI1LvU5RZSer2QcqLUKyzPy8lkfENeF6cfFU79tKr2XSy4siMzysBxJTU0B3N9DXpwc0rLtuGHwlazE1xQ4SMaj1DVpvf28i6zQpes4JX7VMnLQnw1UqYwhq0lypDHEYKtUEe+1LnPTgKpLxTU1pMBWXlpZlK98VZ7PdJpymur2knfSyLO0bnM0yEG4wzAxXa35eu0i4NdSmQBRng4I4leesEwYuA7A7tKwwa+3ql99T9F6C0qAXoYnrYK5UaUSlCXclF5/wIKj/o0rvIUEE7BXbrdmT5+LS16dnNefnT42jXHlKXO9hftrWhf5eu3KldoxauVLb061axUmIDYaHNtU6fpwlEiGrNhAu18fU2rELtx8YhAbC94baQo2BcP1L2mtYHHRH3Zpt6cFk+es5fy6VQY5y+3oJcv2WcJS6nlumFYAGwu3t8SZROjqAdes8LwVdKetf6isoiWhzaVn6ed/UpBPnGAg3HDERrn6zbds2s3fv3sgeLzTGAD/5if5jMDMculJvrKVq3JwZuOIPpeLsnNfgOvY3Y0oM99XTdhVdJ5yM7dJ9exfcSiWizBaXy6T6zbKW6iTh9vdqlbtfr+8zXt8PXAP/uTn93NiwweuQgzc9DRw5ohPAKrR289pFpHjZ6YZ7v7Q7R61dq50kKFG2bduGvXv31jSjkZnhaojoaZKiuisKx/Km/nZAsPx0rZ35vf3AoEsWrbBEtJ9sQ8O9sdMytZ8a373kK2zOEonixwwzU+y2IqPXThOVhF2XGnW9q2t9ddRLLzvNzQGHDgEHDmims8Yex6l6X1xcBMbHdaGNXC7u0VAIWDNcra4uLZWYneWCGxFxbye1dNEMLYEodx/Jn8RD0SjVHzdVH/I+NfL/TqX3hkBqncfHo1+xbGFB24KdOKFZ6e5uzzet9L9gb7NG3i8A6Gf83Bxw9Khm1gcGeFa4wTAYrlZLi54uOXKEwXAClOq7WsuqVQyM6l9xJwP31l278tnV8hPB4uSnFKKWzLTzcco/RmFb1ksgVKkMw75OqQmCNVtY0KxiVJ8XuRwwNqZtweye+CH1xq2l3V5dmJnRZayHh/WAgtnhhsMyiVqIxDsrOOWsHbtwx3nbXQPhnQNrl/xeTYDDLHL989IDNuwWZdH0xw22U4XzPsPiJesYdWBVaQJd1WOan9eAat268CdfGaOn8/fv1w4IbW36mBEEwg1rbEwzw1u2aL13zAttUfA4ga4Wzz2np0y6ukK5e2Ym3RWyfcuzZW6T5/x2ouA2b0ylXtvlE51K70NJ4Bb4xtVmrVTf4drus/BcChn9XdAOMLXzMwGuuC2cl9sUs677hJZHDAyEHwhPT+up/JkZfawsT/5W49TrmDPA+AyQtWDd8GfAGWdw5bkECmICHYPhWhw8qG8+PEqMXbkuEhSvejrASFLQW05x8OvsLBF1N4liQbfVirPfrd99d9lzn1+Edfn7gNWrgf7+YAdnjGYr5+Z0IY+TJ/Xn1lYuBuXCz2t56nUcnQZgAGNg3fJZX/XWFB12k4jb/HzcI6C84k4RS90b2OPUS7CUNF5WKkuC4lPh9gGWWz/fKPr7eu0j7DwrEnXf4XK/l+K13CDu/aXqANwYYHoO1vWf0ABq1araB7O4qMmXkRHg+eeBp57SzhBHjmjbL3tyHANhV1W9lllLX8fMVcBjj/Ezv4HxHEoturv1TSmizHDcKwIlXekWT7VNpPPyGOSuePGFeuNsXxan4tKISuMJo4a4lOLVy4o7vLiNw8u+UFyiEtYZhuL3Va/zC8q+H88vwtr1f7UvbS2mpzXQnZzUrC+gbdGamvRzh6fsw9XZAswvInf8q7CaXwEcPgxs3MgFtxoQM8O1aG2NZAKd803Xy6Suegw6kobbMBj1evCQlNe/lmA2ygC+XADpdxxBZ7adwXSplfGKr1vq91L3v+x6OVNb14jFRa393b9f640zGZ2b0tWlQXBzMwPhqPS1A1tW6YHNxIS+HtRwGAzXorW1sDJNSNzeyOs1wIhLtdsrKQFRnNK6DUq1YHOKKtj0mg2OasGP0o9feylMWCUeXoLc2hdeuXVpWYtV5cfrzIyWP4yP69nHtjZOhEsCEf28HxsrXDYzowcsBw/Gu6AK1YzBcC0yGeC00/QoPqRaompmazNY9ie0vqINrvhArVzvVreVy+qF17pd53WDz25GG+QG9ToFNW57m1azqp37/VW/+mSlRSZye3ZrYOT3VHoup31s9+/XQJplEMmTy+mX/XlvWfo1O6sBMdUtBsO1WrFCT1kND8c9EvJoeSutylnAtKrUp7c4G1YpKK53fvaLcpPvwlJYQCTeGudqLM+8F1oollpivZxS+2E1B7tes96nWsJd/3F/p9OnpjQIPnFCSyE4CS5Wzom0yyZ7Tk9r/2ZAX6fTTtOAeHqaE+zqGIPhIGQyWjIRkuJ/RmYua+NtFnv9BRNxsxdAueO87QDurfv91LkoR/X3Ee1BVVD7bZSvXamDBbf/09sPDPoam/uBrvfFdIpXMPT8mC0tWl86PV3+ynZt8HPP6edIZyezwXFbXCwcyORyS8sf1q7V/s3O11WkcPAyNRXdOClQDIZrlctp3VDAR/KuzdtrWQGJPKn3AC5qui9eBuAy7Bx4PW4/MLjk7/W8PYMeez2dbaj2faa6rKt7AB/E9nfrQFFq0Z5y9+F7LCIaEB84oGcN3ZbvnZgAnn1Wv3d3czXTpJiZ0bKH2Vl97ewaYWOAwUH9OnoUGB3VGuKREX29x8Y0s091iVX5tRIp1AwF2GKNAW98vHbs4Gu03M6B12vw8HhhOyZ5W5WalOrWHqzU73r9yhnZejrbUO41i6JtW6Hc49Zl2/uO87Zjp+/7u+3UcyqUPCwff7WLiLhuq+ZmDXBPnNBJ1qtXFybVnTih2UeuEpc8uZy+bidPara+rU0vHxvTzO/QENDTo9l8+7pzcxo4s7ylbjEzXCsRYOvWQmcJahiV6mXJXfGEOT+nmKNUrgfy0rKkykGfl7rgsDPDQZ81qvSaBfl87TpnrwF2uUmv5VqmBTUBz6m4hG3J44to6YMx2pP+uef0a3pas8EMhJPHXtjk4EHNEmez2l/44EE9qGlv1zrh0VF9XefnC5Mdmd2vW/xPDIJdMzQ5CfT2erpJkrNlXtT7+Ctp5OcWteJAJMptW+4xi4P04sxhPYpy7MWrPS4PQP1njv0eMAS9qEs172uVJuqdqiH22He4kA0PZqEgKiGXc29/l8sVejsvLgLHj+trt7gIbNigf3/+eZ3ouHq1/q2vT4Pis86K/nlQIBgMB6WjI1X1Qo0aLDbq84qT28peSVCu1+zy1c+WBnbOUoFSAdypzgIR1QpHtX29ZsqrCYbt7em8bW7Pbux0uT+/k+C8jyH+g6IgV82kEoaGNLNbvErg7KwGwj09mum1JzWefTbwrW/p0trr1wMXXVRon2cMsGYNM/11jK9cUNrafJ0iYdBFaVC8emLU3IKaIM5qlAuCS12/kQUZOLptq6i3X5yBMD8bImCMBrh2pwj797k5LXmcn9cgubNTyyIeeUSzweedp9fr69OJdBs26O3tUgmqW6wZDsriIo8KKXXKZVedk5+qmpEf0JiKg4viBUCqWVihcF+lA+IoJprp48QXPLltp3rpmhHVdiu1KE3SzpQ0nLm55X1/7e5PR47oz6OjwA9/qDXBJ07o5/iKFcDllwMDA8DKlZroOucczQT39Gh5xOSkBtBTU1pjPDys5RRUtxi9BWV6mv0hGwCXvPbHrQvD8uBz17L60qTwM6ZqgrziU/5p6BdeLviPu/zAKa5xlKtTT+L/SF2yewUfPw4cOwa84AXaDaKnR0sb2ts1oJ2Z0aB43TrN9o6NaQlEse5ubYFnl01ks5pBPnxYyy06OjQ4np31XBtOycLMcFBmZyOfSZqED5UkjIGS7DIEPRGoUtbWa8DlpcNAeMsrB/N/U9y1I8xylCDut3jFwqQrNc5qx1/uTIr9M99TazA9rSv5jYzoZPZ164Azz9QAdt06DXR7e3XC+6pVwIUXAlddBWzcqIHwwoIGuG66urR0ore3EBBv2qT329mpGWV2k6hbzAwHYXZWjxo9dpJoJMxkkJNzf1g+Cc29fKHcwgjllKr99VMTXCkQBnTVs50Da0teb+n9LZ00V+2kr1pV2y+3HH8rvxWCxeXbwHu9dbWlJtVmoN1uVy4gbvRa8LoxMaEBcGendohYs0a/nIwBnnlGF8xYXAT6+zWYXVwsXMdtcRRbd7f75W6ZZKo7DIaDsLio/0SLi4XZpRFgIBq8JJ3GrQd+J6OVanFm31fhsvKBRqXHLHfa2e/rawfC1QTFYarm/7+agw63+6i8KE3pgNdvIOz8udo+xBR+CVgspR5TU1oO8cQTmhV+wxvcg9bFRc34Hj6sQXNzs9YU24Hw1q0MalNOjHPd7ZBt27bN7N27N7LHi9Qzz+hpE54moRSppTPD0uDXe/u1co9XvNSus1bZSxa4FHuZ6UrBcJSZwlq2e5i1y0trYAsHNcWX62OXO+DZtSSojjsLW+3Kg/4fp/6SHGH2nXdbhfD2A4OQhUU0HRpCrr0N1624QksYzjgDOHRoadliJqOB8vi4BsF2jW9rq9YQd3drvTDVrW3btmHv3r01TdpiMByEXA746U8Lp2iIyJWX5Y8rcS6tW/4xvAdczusXswNhIBnBsNesuJfrVrp9GIp7NFfaZuVKLqJWTWDudxJlqUmppcqJkhA8hx0M33He9qILc2g+dAyv2rIeufvuwtfOfile9cT3gZyB9cLfQu4HHwfam2G96iMaFE9O6sS2kyd18lxHh5ZJdHaGMmaKVhDBMCO3IBw6pKdbpqbiHglRIjknBlWqJfZyX+W4dbNwm7Rl/14uK+wMhN1+j1pQAUe15RFB8r/aXPz1uX6WjHbjZRtWag3o9/6SzNl2zss+2TR2Ei1DY+j86SF07h9E7pt34K5NFyEzNQvM5wAR5B7+a2BtD9Ddph2exsb0xvffr0sqr1gBbN7MQJiWYDBcK7udytCQnnYhoiXKlUP4Dcr8LnThtnKcW3bPz/3GHRAHpVQAUinjXo1C1wv/XRhqDUCrEWS3iyQE8Y1CFhbQMjSCzMwMZjesxl3nvgxzfZ2YXd0H9LYBLVkgZ4CJWVhrfkEXyhga0n7Br3oVcNNNWhvMNqhUhMFwrUZHtVfh6tVcdIOoBGfLL78lEU7O+lOv3IKRaoOdnQNrPU+iqySKrJ7XrhxhlkYsLQvYveR76duUz9o7s/1htGljAOud39ZwbplgL+8NbYeO4VUGeEVnO2b7ezGzuhezq7ohs3Nofu4I8PAB4MgJWNtuhfXyd2ktcEsLcMUVuoDGhg0MgqkkRm+1Gh/X7HBPT9wjIQpcrbWAzttXLm+oXBvqdSzLM9Ban+qcCOcliAqze4T/rLi/rh3lXrtKr0nxQhBBtmXzEhB7DZpLScqku0r89sROIrd2iqWUq2cv12oRAK5uagKmzkTu4X9Ae/tpuMw6C8CDeOqO+7C1ZwvQewZw4dXaD3jdOu0jzAnt5BEn0NVifh54+mkGwg0oKRNT4ubnNHqp29fSzaG4G0T1r8m9AJaXOASR5U3CpLlaBNmGLgilJtV5DXCL96WkBcRey1Aa7f3Hy/Nzu05uz634+voL0Hr4OK546XlAbpsujjEyov2FT5wAzj0X2LZNO0dwEnvqsJtE3MbHtSA/hYttpAED4tqC4Urbz26Z5FbXu/yy2rsiODPDtqiC4WpKRErdRxjKZeyiDoiLW6otHYu3wDZJHSjcVAoE6+19p1S7Pvf6fH9t/awdtwHDw1qOuHKlliNu3BhpT39KtiCCYZZJ1GJxcenqNQnAAC5+sTSfD0G1QZCX5+8sX1j+N7fLgtmvq1lAo1b1sB84T9fHfUo+6OC1uJVbOI/hrdwhjs4QYXwmFN9nuQC3mjp/5/Vze27VSXHT88D8Iqyr3qf9gtetq27wRC4YDNeiuztxNUmVagXJu2q3YZq2fbmaUy/cV5+rnJksvr63ustCALSzKHPot99tIyouR4kzKHbr/+wngHXrHR3m6+d1WzVKKYT3s0O1BcKFCwToaAZGpxOXgKLGwOKaWohofdLsbNwjWaJe32Ap+YLYt/yWXviZlON9DLuXtOzyEmh5zWLXMr5yAZtzBn7Y3R/8ZDntTiFhvO9UG8AWt9Ar/opSpUmMYQq6h3fx9ao9CCh327JlFD2tumjGqlWeHpfIK8/BsIhkRORBEbk9//sWEblPRJ4Wkf8QkebwhplQlqW1S3Nz+hWQuE9TOiVpLHEIu+1UUpV7zm7bpDgwquZ+3TLCjVJyYvPyPOopAx3eqf3dZX+vB87/hVKdE8IU1sIqfmubCwcl1WfFTx1wvfIjWiKRsDOyVP/8ZIZ/B8ATjt8/CuDPjTFnAhgB8CtBDqxutLcDmzZpZ4mEZYipdvUUmEShuKeok7cPxvLX8VNeEVRAUVz76O9DOtj9o/zS0aWDq2Ae2/tKYGFq9AUvwqjfLfd/GfRjAdU/Bz9jW3ZdY7SDBLtFUAg87VUishHADQD+Mf+7ALgKgP1O82kAN4YwvvrQ1gasWaNtXnK5uEcTqEbJyFVDP2R2p3IbuD1nL4sclAqoqulKUS4wdftQ9ptpKvdYXoNir8GWn9PKfu+z0t+8LIIQhCCDMHs/q6asoVSNcVL+j4MOVktlnYMuX7FryYvLGModRFXbrs81+zw9nchJ69QYPLVWE5HdAP4EQBeA3wfwSwB+kM8KQ0ROA7DHGHO+y21vAXALAGzatOklBw4cCGzwiWIMcOSIroNeQ9/hem6vQ43HT1mD8/pBtV9LirizpbZS27zSpEO/pStxT6CrlVtrteLJmksn6VX/fEvdtpbXJGnc/q8r7Tel2gmWug/n5G/X95GjR7UcccUKYOvWGp8RNZIgWqtVzAyLyE4Ax4wxD1TzAMaYTxpjthljtvX391dzF/VBRLPDTU1aMlGlenqDpMbnniEufMg5M55h1SgmQRLG6XUilp/JSm6BSqXA0JlxrHW7hFlz7MwqL8+eLl3u2c+ZCy/be/l4gj+wiOpgpZb9qdR1Kh0YuO5bxgB9fZw8R6HwUibxcgCvFZH9AD4HLY/4SwC9ImK3ZtsI4FAoI6wnmYwGxFNTNd1N4VT0vcGMi6gG5QJit1OySQgc/So+1eulzMMW5nOulIlz8pvFL3cflTLJfuqLvZW7VC7BcbvfSmMt9fdKXUQqZXu9TjQLswY7zv+zSuVJfl8Tz9vpxAmgtdXbIIl8qBgMG2PeaYzZaIzZDOCNAL5pjPl5AN8CYL9zvRnAV0IbZT1pa9PvVa7sl9tzK24/MHhqpax6PlXpRaM/v0bh5QOv2tey3AdhFPtHucf28iEd5aSzSmNyBrO1TLYLslyreLxBTpDz0sXEPahdmhn2cpviy2vZLvV2wFjpgK/4YLh4O5ULnj3vD0eOAKOj2k2CKGC1LLrxhwA+JyIfAvAggH8KZkh1LpsFOju1s0QVR7DWjl1APhC+/cBgfnGAewFcFuw4E6LePhTSzMvpcy+qmUwXpSACW6/1okFPbrNfI7fMtrMms/j6bo9Z6XrlLi89vkIQGmWnh+XP0X2552rvz6sk7edeVTNmr9liz/vDxARw7Bhw1llchplC4SsYNsbcDeDu/M/7AFwS/JAaQCajpRIBnM6xM8Q7B2q+K6KaBflhXulUvFvA6BZ8JS3AKBUI+Akyg+Snk4VbEO9Wz1n9WQD3INR/x4jS9bxex+Y2Fi+359ksn9tgclI/D/NnS3M/+igAH/+34+PAD38ItLQAL3mJ36ESecLlmMNgWVW3WLOD32JRzrqvlxn+VJ+8djbwOnEnScFxpVPJYd2/n4DX7307/+7MOvt9Ps5WacH3Z64ctLu1XHP+7PX5V6tR31NL/v8Zo4Hs8eNAf79OLC9anMrTQdDBg8BTTwHXXst6YQoNg+EwTE7qYhxV2DmwtmRAHBX90GJAbOO2iEZQGTe/r5efSWpJFGangrCywl6CIK+P5aV0R4N4b9nnUo9bj/tGGDxlzucXYV3yTi0bnJ/XxTKKPxNnZ2Fd9Sea8S3l6aeBf/on4JJLgJe/PIDRE7ljMBw0YzQrnK1u0+b27AbO277s8jvO246dtY7NxxjSEPwxyE2OoAKNIFp91VPQE+RYi3u8Ft9/LRPyqh1Pub9V6vjgdlkt7f8auXVgOb7fJ43RQLilRSe7bdqkZRLz88h96/2wbv47YGFBO0Nks5o9dmu7evw4cPfdwMmTwKWXgivPUZg8LboRlG3btpm9e/dG9nixeeYZXSWns7OKG9+7JDN8/eP34A5HcLxz4PUBDJAoOZxZyKRMTIpjHG6BZ6USkFrHWe0EvaRl0/1s90rjrXRftd6+3vh6vUenAQDWVe/TQLetDZicRO6uP9ZEUU9rvozQACNTsN7w17qynGVp8JzN6s8nTujn6E9+AvzMzwBnnBHuk6S6FsmiG1SFlpZltVFeuZVI7BxYu+Q7UaNwy0IWt2ny09O1+D6TxG8QVa49VRjt3LwGcV6uF3VAGOWZhUYLdispN1nRVWtWz45mMsDJk8jd/X6gtw3oay9kdy0BMvmfB/Kzw48eBQ4f1uD4xAkNpN/0JgbCFAmWSYSho0P7IVahuGb4jvO2AwcGTwXCYZzaZ7kAJYWXD95KE7iCmqhWqqdskNnYSs8r7P/LpTW11T+vUu3ZwhRUdjqo0phGfg8t9RnheoZhblGXTG5pAQYHYb3ij5B78GPL77Qpoyu3trcDXV2FM6lDQ8DYGLBlC7CWCSCKBoPhMPT16ZHt/Lwuz+zLZdg5cO+yDPHt+YA46FnYNgbEFKVqOxJUe5tquD2Ol8lDXroSxK2WSYZ+VBNoeu1BXM17VqmyE//9kpcG4kl4TcPk+QDNGA2GDx7UjO7UlAa5cwuwXvfGJfNRcl/5beT2/D6sX/88sH693n54GHj0Uf3svPLKEJ8R0VIMhsNg12FXvQqd+yQ6O0C+/vHq3nxrCUCIgsR9cDlnli3KNl9+M+B+WtlFkSEOqr67loA/TcouvmIAZC2gt1fLHo4f14RQNoPCEtj52zdlgMk5TRytXKmfl8PDOqFu5UrNFhNFhDXDYZiZ0bqnKlfKsXbchusfv6fsdYKsGUzbmzmRX2HU6FYSVLmH17rrco9fqbNDkPwswFGpLzWFz5ldt65+H6xX/JHOmcnlNMAdG4N17Y3A/CIwM1+4oYhOpDt5Un/P5bSm+PzzgZtuiv6JUKoxMxyGtjYtlRga0pYxUtMkx8C4TdCJul0SUT0q3cYr2GWFiycBVppU57y82mxx2AuFJAWD5RCMTmsmt7tbA9++Pv09lwNmZ7VEwhjkvrobmFnQ27Q6Sge7WpD7z9+B9Qv/pJ0ktm7VJZeJIsbMcFjWr9c3iKGhqm5u7djl2j3i+sfvCTSA5QfEctwm8auX18AtEPa+HPCtFTOb9nWKV35zrgZXKkD2M5ZqObPOcQbOXuZSNFJgnxiWaF0wABw7BoyMIPfd9+tZ0YkJ5B75Gy2ZsAPh9qblt2/OIvfPvwQ8/3xiEkeUPgyGwyICbN6sR8pHj1Z1F7c7ukgAS1urBXkKlZbiNomfM9gLm1vA6UW5AKxSWUGtnRv83L7WbehWI1z83lFNQOyna0Y1E4fdthPf8wIyPa9ZYQtLFsPIfev9+tnX3Ax0dMDa+Wf6s6156cloa8dtWmNsd5UgignLJMJkWcC6dVo/NT2t5RMe2ZPonF0l0rIyHLlLw6x1J68LQ9QymbTc38qXD5Qvj/Dbs9frwiOl/uZlkQ7nffvZl/xM7PN6f3ag6rW0w17KudQ2d7vc7cAh6Cx2vU9Krnr8c4uwdn4MmJpC7v6PwNr5F4UJ4zkDnH66nhmdnwcWFnQRDgC5b74P1vV/itw33g20N+vjj81oPfHsbGDPi8gvZobD1tysbwrT077+2cv1dKR04uvvzm/m0w7CKm1P9wVBdtVUJ1yqFKLc373ebxQlEfZjlRtHJcWBv9cAtZpt7qeMo5ZtGMcEy6D4D4QXABhgdBS5732osHgGAOvaD2pHCRFgYkLrh2dmkPvO+5H7zgc0KJ6ZgfWqP9HrX/cJvWFGkLvznVV3YCKqFTPDUVizRtditycWeMwQFy/AkbbMIFFY/NT1Lv29+sly5XrcVhpTuUVA7NsGtXhEJdW3ICuUOuT27HbZtv6XhvZ62+LsdrU9ihttsmFVXUYufocuqDE/D2v7HwGtrY4/WrCu+GNtlzY9rcGtMbB2/a0upGF3mejqKjx2TyswMg3rFe/V67NumGLAzHBUNmzQkonp6VMXVc4SLf3g1YxU/WYgiKqRhAlafpQaZ6nJbeX+p0tlsN0m1RVnvMudXUrKtgx6HF6y1sXfvYqi7KIuZLOa0MlktBfw7KzOi+nr0783NenEcfv3/n4NhGdm9Pc1azRrnGdd9SfA3Ly2WGMgTDFhZjhKvb3ahHxw0HWZSS9v0nZ2hVliSovi4MPPog/l7qtaxZO5gmyttvRx/P1/e52QFtb7RpiZ3aDVug1S3ZbSGGBxUYPiqSkNjOfngZERLQu0/7a4qJngQ4f0s6+5WX8/dkzvw15Uo7UV1uXv1OCZwTDFhJnhqLW16dfiYsXMjb34hr0Ax+0HBk992VliorQotb977QSRhP8Xt9IIvxPZitXL2aLig4ZqM7TVKhe8Vtq3Sv0tldas0dKInh4t/2tqAiYnNfjN5TTgnZ/XHsMierllaYBsWRoIr1lTuL/nn9eV51pa4ntOlHoMhqO2dq3+0x8/Xrgsf6RtXf2nhcvyvRutHbcBU3Ow5uaX3I0dEBPVm2ramDlvW8vfkyDqXsBR8RLUa61wdZl0e/JinBr1tfNNpPAZdvKklkJ0d2t21155dXYWeOELNRgeGipc3t2N3P+8bel9zc4Cp50W7XMgcmAwHDW7J6Nl6RE0oKeXTp48VXtlXfbHemrpwAFgZATWxW/H9RtXxzdmopBU2+M3SZIQoKXuVH2RWrPrfu+n2us3jExGs8BNTZodnprSBTe++FvAypWaOZ6bO3UWFPfdVyiPcMybwZNPAj/9KXDuucwMU6xYMxw155rtdhuZpiago0MD5Pl5ffOw27ANDQFtbch9/T9xfZMeWVs7dp0ql9g5cC+Ay+J5LlSX4q43L3e6vx7YPW+dqmm3Vq6LhJdT+UkMxEp1tKg1o1qYK1Gqz3D1Zxkq1f4mcTvHTqQwEc6uDW5uhvWK9yL3X78L66a/1iAZAF7wAs0iDw9rqcTmzXp5LgccOQL86EfAOefE9lSIAGaGo7ewoEfNq1ZpnZWdEZ6b0zeM1oeAzAPA+ePAwIAGyb29sF77v3DHedtxx3nbQ5uwQ+mQ1A/3pAcj9mn6oDPB1T6/ejl4AII9A+DeVq78aoClAnQvk/gqtcRLta4u5L7xXp0ct2KFToZ7+R9pkCyiCZ/xcS2h6Oo61YXCuvwDwMGDmgi6+mrgxS+O+5lQyjEYjlp7O7BxI7B+vc6wXVwsZIIzGWBhEejp0Os2N2tLtq6uJQHwHedtP/Wz9iG+N9rnQBSCSn12/dyP21ft46u+3jUofpYwjkvxuOyg038Jwq4l3+1t79aSzv5bucfwOxHOeQalHrLycbH+199qlndiQifNtbfrz8eOAfv3A5s2aS1xf79mhe0FqI4e1UB548ZCPTFRTFgmERcRfROYnQUOH9ZyiKYm5L6xG9YvvNnXXd1+YBDXP85Wa1RZkj/U4y3dWLoghFfLe4GH9xycJQhJet3KKTVmt59LB6W1HYB4qRN2BthuwTyVYVnaWWJqSvsJZzKa7Bke1r81N2s9cF8f8NhjGgCffz5w3nn6ObhlS9zPgIjBcOTsWmHL0jeC1lagsxO5L/0urNf8GazrPozcl94P6/U3L7mZteM27MS9S1akc7rjvO24nr2HT4m7Ljap4p7sVYnXDG5YvX79BsJeVo8rffvlq8Y1yj5bvECFl9KC4m1RyPaWrxem6C07wGlq0s+zbFYX15iaKsyFAYAzzyxMoLO7KZ1zjpYLEiUAyySiZvdhdGpthXX1a/T0Ul8fML9Y4saXYefA0sU6nL8nPdChZLAnXwLJqzuNMxiMI9jys/2XBoqVbxf3a1vVUr8lSircJi2GZWn5xa2+t3sauJa9dHdrENzRoaUQmYzWCAP62TYzo9/XrVu6Qh1RAjAYjloms3Qtd6DQOWJuTv+WKb0KT/EHtjNTfPuBQb5Z5zVKhi1ouT27sXNg7amDqLRuJ7dgy9vtClnKMJZH91PrXOlx6/21LWTddy/5Xun6XlSaVFeq+0W9b9PQOVuGWtapfvmYmgIyGeR++AnkvvJOnUzHOmFKEAbDSTAzg9w3bwcW70Xu326BdcPHkfvSv7te1V6VrhRmh6mcpbPnk3nauXKNZ3X7eHGgU0t/XufkrqX1xt4C42ozwrXcTz0qvFa7Tv1ebuVON16yu27369xfGARXMDKi2d7VqzUYHhpC7lO/XliYY3RUM8NzC7B+5s+0ppgoQRgMJ8GKFbBe82dA+ythveK9wMwMrFd+QCcauCgXEJeqKSay2V0RGukDfnnf39s8BzP1sB2qDXobIVjWWuLqJyoWv/718HrXndZWrRE+elTLJLq6YK28QXsIA9oxaWEBEOhiUuvWxTpcomKcQJcEHR2FOqs1a/RN48QJbb1WgrXjNuDAl5ZdvnNgLSePUVmFiUr3Ji4otvfdchPTiidWBcHLIhflb7/L17YstThFNcpNwEvSa1uLoHtQu+1fjbKtIrG4qJPhRAq1wePjGhSfPKndJa6+Wlut2dcfGYGVuVIv6+mJdfhExRgMJ0VLi76JADojd3Xl5Zd3DqzNr0Kn9Z+nVqXbsQtJDHQoWZK2f5TvM7y89VmpMo+gn1OSSo/cgugkvYZeeV11r5wgnrfXgxImGIocPqxzXVas0FVTV63SPsJjYxog2xPp2tq0bGJuDrnPvxNW/6s0K2zxpDQlC/fIpJidLSzP7JEzKLAnRgGFoDhJH+JElZSq2wQK+3iQk6jqldvKaUkvh0ha9ws/GeGkb9tYrFqlge78vJZHTE9rffDCgl42OKgLb6xfX5hUN5cD1q7V5ZmJEobBcFJ0duobRi7n+SbWjtuwc2DtqUk8xfXC7C5B9a4wi3/pamS2pNSCFq+O5kWtmVAvt48rUF7aY3jXqc4bNr/PPeiOHX5wAp2LtjZdHbW7Wz+zJif1srY2PbPZ3a2lEIuL+rsxsG54B5ddpsRimURS9PRojfDYmGv/xXKn6cpNmrM/hPhmTk71tj+UywiH8VyiCiBLtfCqdD0vknAg7Dx4cQbEUdY2e2mLZpdLFGfc6+3/JHJ2AAxoaYQxmikGNFt89Khmh9vatKTipS+Nb6xEZTAznCQbN2pT8uPH9Uh7fPxU6USpN+VKp43tcokkfDASeVVpad4ws3XFjx1lCzo/rby89BlOWlaz0Ke5uhX7auEMir22Z+P7pg8tLdo+rbu7EBBLvmf+GWcAV17J3sKUWMwMJ4mInno6ckRrr5qagMlJ5O7547Kzqa/fcyvuOG972bsul5UhSpIgs6NBPXZSezInUaUA8o7ztue73njfpsXLO9uXeXm84uv7eUzyIZPRs5onTuj36WlN6jz/vCZ1Nm4sBMdECcPMcNI0NwMDA3okfdppWmv16o+XvYnbm7ZzlTHn8rsAsx2UbMULY0T92ElQ6X+0OChM0rhLTdwtfh8qvl01j1VNIFwPEw7rlj3nZXRU58BMTuqZzvFx/ZkooRgMJ1k2q8FxLlfxzXvnwOtPBcB2EKyXFy6r1L+VKImiCvaS0u6r+H7qpZ1acSBsT+q1A2Dn+1Kp2weleGVAisj8vE6aE0HuzndrRjib1cvt1qFECcQyiaTL5ZC78/c99WXUvrG7yvxemN2tbao4QYTIVutCGGH+L/ldgjhqboGwzS0ILlUiUS7o93ogX67jSLnLKABtbbrwRr4cIvedDwLNFjA+DWvHn3DlOUosZoaTanYWOHhQTzVZVv4N/t6yN1k+Q7v4Q6GQLallIgtRo/La3SEKSSp/KKdcaQSwtNtN8ZmrcsrNk6jcG7h0T+p62KZ1za4L7m0DulpgXXQVMDQJPPOMr9ahRFFiMJxUJ09q3VVLSz5j5bWP6WWhD42IlkvjgaVbIOwMRJ3Bb9ArB5YKip33z8A3ZtPzyH3zdlg3flhbh46Pxz0iIlcMhpOqqUmPsPM9HJ0BcWXeAmK3ZvhEcYt7f6w2gEpb4FUpI+x+m+BXECyXQabweJqImBFALO0ukclwEh0lFoPhpGpv14DYsURzWJPfGBBTPXDuo2Hvr3GVKNTL/2G5QLjc5DUvgWsQ256BcDRK97/P78fZDLCqQxM7s7Pabo0ogRgMJ1Umo7Nw5+aWXOw1IGZfVKo3dqapUsBk7/tRtMjyGlQFEXzVSyBcSlDvOdVsB+cCI0kOhBuprduy7bywoF0j7L+/6iZgZAqYmkfuf94F9PfrohxECcRgOMmampasQmfz8mbvpayi3DLORFGpJkCIqw9xOdUGOX5vF3dAVTgY2e24bLfvkoni+6x0METJUHLfO3oUOHq08HfLgnXta2Bd/UH9DPvhD4E779SgmShh2FotyTZs0DeREyd08oFjKUu7DVQtHxzORTl2sicnRcC5CmKpvr6V9usg9v0gLO/eUnutsdcD3biUmjBX/jbOoDmeID4J+0ujrADqOn5jkLv3I4AlsK79CHJf/UNgeAyAAJkHYF33EQ2Cjx/XrzVrIh83UTnMDCeZZQGbNunkg9HRUB4i7uxwo5wyJG8qlfl4LYGIc2nmoB8/7kyvH6UC4XJZ4UI7x8olDGG9rlEFoJX2maDGEfX+4uXxrGs+BOu6jwLNzbCu/SByd38VaM5q3fCKFUB3t36fnY1gxET+MBiuB+vXayPzopm43j5YLlvS6qhcFieOD+R6z5KQf/VQ2wlE06Wg2mWI4+BlhT63/r7Fvyf9da9VFK9P4pYpF9GzmLOzhZagr/8rYP2NwOb/pZ9hp50GdHYC99/PUglKHJZJ1APL0pV7Dh7UpS4d5RKebu7IxhVncHYOrI09O0zpVeuqb2Eql70Octllv6fP4+py4Z4VLg50d3leXa4RNVqg72tfX1jQSXLz8xoYW5aWRAwO6vyXfJCM2Vm9bOPGUMdO5AeD4XrR2anZ4fFxLZuo0vIszS7PK0IRpUlUgXq9B1C1TJxbej9xBfn1vf2jVnKbZbM6vyWTQe6u9wAL+dXmFnKwbvwEMDWliZzTTweOHNE5MfZqdUQxY5lEPVm5stCvsUql+0Lu5ocCxcKtx2wSyihKBcJxjyvpli8DH82kwGpbspE7t/r9sr2+V6wAVq5E7vsfANqbge5W/bJEg+DOTr3ezIwuzTwyEsnzIPKCwXA96eoCenpqWtLSPqrnhwAlST3tk0Fmi+u9dMAOfEuXRuxO3HNM2niSzPk/WVzO474U9tJyGuu6T+gPi4vaEamtDVi9WhffeO658AZO5BOD4XqzapXWXdW4xns1S6kSNao4OzokvZtE6Qx5+fcPL4twBHkQ5OV+ai2LcMuQpk35jhlFnUOmp2Fd/X5dPCqX01KJri7gta/VGuOiHvpEcWEwXG9aWvTIuqnJ99KWYS3nTFTvnEFZVP8fzsdJela8UuBbzYF12M/ZS/cLv5K42EtYytXM5/bcitwdv4fc7b9buOyO3wNm55H7wmeR+8Jv6oXt7RoEz88XaoZbWnTeS3f3shVWieLCYLgerVihrWpmZvSNxidrxy5mhYnKiKLHcL0HVOXbNC6fg1AcSCZlKe20q/p1mF0AJuc08J2bA8ZmkPvP/4B17YdhXfm+wvXWrtXPqc5OnfeyYoXOfWlr0/IJogRgN4l61damq/gMDurPbW2eblZYvYvBMBFQeaJcmEFbPQRsXt4rbj8weKorTaGn+dLtFmUmvJ6y7nGrZvucus2xY6d64Fuv/GOguRm5b7wb1uXvBSYnkfvue2G98iN6nfZ2DYwBDZ7n5z1/bhGFjZnherZyJbB5s76p+MgQa0DsXCKVnSQoXew63Wo6RlQKjpO0KEYw97s0A2z3JXcGyc72jEmYDJmUjiT1xE9Zyanrrlyp5XoiOrkbgLXzExr4TkzAuugPCwmbtY4WngsLWurH1mqUEAyG65l9qimT8d1uzbk6HVA5OCBKk1oyi3EFYFE9rte+5EkMRBv1/S3KsxdLDjIyGT1DOTuL3Fdu1YzvxIQuuAEAHR3aT3jTpqV3euIE64UpUVgmUe9mZvRrxYqa7saZ5WEjekozt4lD1awUlzS1/F/r2aPlK9CVWpWuVH1wnNuukd/XgnpeVQfVq1cDLVlgbEzPUp5zDnDGGfnBOXJuMzPA8LB+97mSKlGYKmaGRaRVRO4XkR+LyGMi8v785f8iIs+KyEP5rwtDHy0t196u7dYmJrSJuc9WNfZkOi7JTGnlFkiUCi7qPZjyE+xUGxglcdsxI1y7ZWUnuRxw9Kh+tyxYl71Hz1Z2dGhyxrIKgfDcHHDokC62MTurn1vr1kU2dqJKvJRJzAK4yhhzAYALAVwnIpfm//YHxpgL818PhTRGKkdE31ROO01LJubnfd3cLpMorvkjSqNy+369/1/4mRDo7Kfrlv310kPY7bHjkISsdBiC7nnse/uMj2sgPDRUKHno7tbaYGfbz337gAce0ETNli2aMV6/XifVESVExTIJY4wBMJn/tSn/xU7ZSdPRod99nnpyPyV8WVCjIkqcUqfLGy1YcuPnOS5ZScxDRwm/AXKtypU9uJW5NKown1u5XsMQ0a+uLmB0VH/u7ta/HToE/PSnGgD39gLNzVo7zAlzlFCeaoZFJAPgAQBnAvhbY8x9IvJWAB8WkfcCuAvAO4wxy2ZxicgtAG4BgE3FRfQUHGN0hm5Li++bNvIHBSVXXAFLob3gbUsuI+UW/NiBrl1WFXXg66bUcsCVrtMoovx/cdXTo8Hv8ePaQ9gY4ORJDXizWS2HmJjQs5bnnhvJWImq5SkYNsYsArhQRHoBfFlEzgfwTgCDAJoBfBLAHwL4gMttP5n/O7Zt28aMcliM0azw3FxVATFRlOIOWho5SKqF83UpDniLM8XF7RkpekFPCiyXaXf9mx34jo+fapeW++b7AGNgrX8jcNFFwMaNgY2PKCy+ukkYY0ZF5FsArjPGfDx/8ayIfArA7wc+OvLOsrRm+ORJBsOUKJU+sOMITBu1jrRaS1vJOTvL7F522fLbJisQTtNr6ve5+m0ZaP/vnrruwoJ+z2Y169vSomUQxmg/4YUFXXxjelozx2ed5Wt8RHGpGAyLSD+A+Xwg3AbgWgAfFZF1xpgjIiIAbgTwaLhDpYrm57VljV0/TJQQ5Sb5RNXyyn6cpdlPBsW2UgGvbpt7Xf9mL9hjT7SLKzBu1G4RQapmGy37vzh2TAPhri7NBh8/rp87nZ0aDD/9tC7Ecf75OlnO8jJHnyh+XvbUdQC+JSIPA/ghgK8bY24H8FkReQTAIwBWAfhQeMMkTyxL36iIEiIpQUpSV41LOg1wby0Z5DqDpTgzxFxtzp+yE+PKaW/XyXCDg8BXvgJ86lPaUWLDBv1auRKYnNQOR0zKUB3x0k3iYQAvdrn8qlBGRNWbm9PMcH5ZTKJ6EVWGlkGvd3bv8evzvxcvsmH/nKRtyoDYu6q21dwc8PzzWo537rnA299e6CBx1lnA9u3Aww9rVpiojvAcRiNZsUK/jh3TVjeTk1q7NTVV091yqWaqlnsLs3L1p/HtY9y/3WkHCW8tzCi5lmbxq3jd5uc1EJ6b017CP//zhUD41INYwIUX8gwl1R0Gw42krw/o79d6rrY2/b2zU9+gTpzQIPnoUW2SfuyYxzu991Q7JQ1i3GsHidy4TcyqdDqdB17RK5clvP3AoGOBh2RNliN/Si2TXdH0NHDvvVomccklwJVXhjRConjw8K3RtLcX1oR3GhsrrBJkjM4EPnpU15TPN0L3O9OYqF4U78/F+3pxUBDVpL6kyu3ZDZy3/dTvbpPjSgXGad929cJzILywAHzuc8DAAHDppawFpobEzHBa9PRo1ri/XwPggQEtqRgeBnI5BsIUinITrIrLJZxnIAoTt8Ip0Sl1yjjN3SWcr4+147YlS7SXuy7VF9/79ne/CywuAq97HQNhalgMhtMqm9WVgbq7l9QUpzEIoOA5A9hSM/1LZRpze3a79rcNMyAuN840sjtIOANirtiXXF4OGn0vdDM/Dxw8COzbB7zxjVp+R9SgWCaRZpYFtLYCJ0/CevHbdVIEUQDcMq/FyyAv/3Au36c2jADMOZbiPsRpC/jK9RN20teImeF64z6Ztcw+/uSTwP79ehaRi2dQg2NmuNEYAxw4oM3PZ2aAw4e1Ofr+/cCzzwKHDunR/siItsdZt05LJ3p7tYH6xIR2oRgb09uZ8itoc/Y/VeLMuJbrb1rcusu+LArFY0xbIFxw2bJllncOrC0qodi15DvFr3hiXCC6u3Xi9WWXBXefRAnFzHCjMUYzvrmcBr0zM1oGIaIBblOTNk2fmtIZwi94AbBmjd5uclK/cjmdiDc5CQxtxe3T9yx5iOsfX9ohII4JMwyE61e5faVc8JvWjG0cnFn64lpie7U5SpbA/y9mZrSXMHsGUwowGG40lqW1wICuEjQ9rYHu6tV6pG8HusX1XyJ6mfPy7m69/WQOyCw/iRD3ByKDosbktQUbhaPS6mRx/9/HxXfNbb1YWNAzh5OT+vlhDLB+PXDnncDZZwOZTNwjJAodg+FGtmaN9hluba2uCXomA7S2ounkNOa7l88iZrBC1Squz3VTKihm667wec0Au9V587WpIwsLWko3N6clc+3t+nnR0gK87GWsFabUYM1wIxPRYLiW1YAWF/Hq/mvRcngYXY89i8zULIBCGywir9za9y3v6LB8n+K+Fr/yExv52tSlmRlgdlZL5V7xCuDFL9ZM8MCATqZ+7WuBc86Je5REkWBmmMprbQV6enBt/1XAGgvo6kLuqR/oqbT8Yh1RY2aw/pWbRGdb2lat/s9CuO239bYvl8oWs7SlzszNacncwIDOIXET0/s7URwYDFN569bp99NP1+/PPw/rsj8Chu4DVvdVfbfVBgFhTJzjxKxoeX0N3QKrenmN3PbvIALhKPfV4lKJUoGwW09oSripKWDjxtKBMFHKMBgmb+wswcaNWks89nLk/vO9sG58Y1XZoOKes95vV74XbS3qLUtXb6qpEQ7y9Yj69XV7rqX6GHsNckstK52E/ZZZ4ToxOwu0tWl9MBEBYM0w2Z57Djh2rPD76KjOMB4cXHo9ywI2bAB6emC94n3AzEVVfxBHfbvy91nc3zb4JYBJlXr9wlp1LurXslzXAbeln92u55XdEznM51d4XW4ruWqg/r2xM8P2tq7rPtTGaDC8bl1tc0mIGgyDYVJ9fcCKFYXf7dNnx49rv+Ji69fr9e1+xXlhBx1BZp+cQZK94ENxpo0BcbDKLQ7gFmzVqvj1C3//9H7/QS9vHMZzK1cWUS4wpgQ6cUK/7A5DRHQKDw3TaG5OMwQtLYXLivsOt7frynQnT+rX7OzS64toQGyMrmbX0qJZY4R7OjrM+y3O2i2tlazTTFAdsLe988AkrMeJS9iPHUZ2uLhGeOn/BwPfurK4CDzzjE6YW7067tEQJQ6D4TQ6elSzuaedprVjpbS3a0lELqcr17nZsEHfaIeGtK9xHak0wQkAbj8wiJ0xrbLXqLxka4MO7hr9tQsjEPYq7DINCoBlAePjmtQo9V5OlGIsk0ijNWuA3t5TmdySRPR6K1aUv+7KlRo4Ly4GUE93b6I+WHcOrI17CA3FPqho1OW7GyX77PW+igPhRj/oqFsi2k941SotbSOiJRgMp1Fzs54qc5Y91KKjQ8ssjh+v6W5uP/AlAMmaiKOngy+LexgNw2u3hKC6JMQVnNX9RCt4+z9M0oErlZDL6XtzczPQ3a3v10S0BINhcldq4lwpfX16+s2Yqh7O/lC9/cBghWuGS8dx76kWbs7MFz/4a+dlWwbdTi3o+6ykngNgJ791wY3yvBvKyAjw9NPAPfdo8qO/P+4RESUSg2Fyl81qXfHYmLfrt7Xpm23uHlRT6uD8IL39wGDIraIqB2J2IOz2N6pdqa4SSeqb64U98a/cVxSC3l5ukxmXdr9IztkbKmFxUb+vXQts21ZYOImIlmEwTO56erROeHgYmJz0dptsFphfrOrhosy6VgocCq2jbq274Cyp3CbNlWuzVu5yP6IqVQjzOUSt9FLZpbtJsBVhwhw6BDz5pLZQ27oVuPhiXSyJiFwxGKbSVq7UNmxessPG6GzlExNVPZS1Yxd2Dqw9NWGtXOYp7A/c4ub69RjQJJEdADtLJeo9eHLuH277Sb0/v2LFz5X/GwkyPKwLJz37LPDTn2qp28AAg2AiDxgMU2m9vcCWLbpaUSUiQCaD3Nf/q6q6YWemaefAWuTu+IKe5pubA2ZmdAb0xIROBolBowU1cXHbjm5Z4yC3N1+72lg7dpU8OC1uOcjgOCY//jHwwAPAkSP6XtnZCVx3HVeZI/KIwTCV19pauQWbrbsb1s/+JXKf+9fy1zMGWFjQnpfT08DkJKzt70fuS/8OTL4ImHwRrCs+pNdpatLZz729gAhye95W81Pyi8FU7SqVEYSVaYxixbmo64PDVO0KehSTXA549FENgjs69D1z3Trgyiv1PZOIPGEwTMHZsAFoaYF1zQeAhZxmdE+e1DKLycnC1/S0BsStrVqbvGYNsHEjrF/9rGaizzhD69y2bNH7XLNGM89zc7Bu+NlYnho/+GtXXHJSKgAOsv6UZS7BYyY4Zs4+wYcP6yJKMzM6iXnjRl0ZtKcnvvER1SGeQ6HgWJZmJ2ZmYF3/Ce1r2dSk37NZ/bv93a+5OeTu+iOgsyXyD2B+4Aer8gTG+siw1ss4/XBbTY5LLyfIAw8A+/ZpIuHhh3UV0bPPBs47TxfUGBiIe4REdYnBMAVrxQr9ClpfH6yb/lKzItPT+mEgEvzjUGzqbVJWvYyTGsjUlM6jeOgh4IkntCRiyxbg/PNZH0xUA5ZJUH1obQU2bdI3/q4uLb+YnCz00iSimjlbCbodnDRiNrxuzM1px4i77wYuuAD4mZ/RkogXvICBMFGN+B9E9aWlRZeSXrFCu0ucOKGTRlpbtSSDiGrGoDd6FXuaj4xoMPzww8BLXqJlEevW8X2PKAAMhqk+ZbO6BHRPj2aJjx/XPsfNzRoY07K2V0R+1VvpStSKDxpq3U5lb79qFXDuucBb3gJs366T5c44o6bHIyLFMgmqb5alZRObN+vkkdZWzRhPTVXV77jRMMOXPrW85qUWDuF+VFnoBwz79gEHDmip2HnnMRAmChCDYWocbW1aQ7dlC9Ddnfq6Ymbz0inI151BsDdBLR1e0uHDwB136HvZddcB/f01Px4RFTAYpsbT3Kx1xWecoR8ac3OaLZ6fj3tk1OAYPKZPJAedQ0NaG9zdravLEVGgWDNMjSuTYV0xRYrZ+HSJ5PUeHdWV5jo6dDEiTpgjChwzw9T47LrigYFCXfH4OOuKKVBJywpXOx63AI9Bfox+9CPtIHHxxcBVV7G/OlEImBmm9BDRuuK2Np2ZPT6urdkAvSyTiXd8bozRzFCV2SBr+/uZDY9A0gJhgAFs0GLpzrJvn5Z5XXSRBsNJfI8iagAMhimdmps1IO7r03ri48eT2a/YGO2tvHlz9fcxMQGMjyP3n78N68a/CmxoUaomEIkyeHFbxrhRpD2ojvV1PXlS3wNWrtRyLyIKBYNhSrdMBujtLXSfOH5cg8empuRkUi2rthWm+vqA9nZYV30ouDFFrJqALKogruJiCXXGGfw1ynMKQjXbouYDsoEB/f9dv776+yCiilgzTAQsrSvetEkzx+PjwPR0Y9QVt7QAra3I/dfvxD2S0EWdyXMuXVzvirddo2a7var1QKfS7cr2cM7lCgfmfX1VPT4RecNgmMjJriveuFH7FXd0aMb45En9cKpnq1cDc4vI3fF7cY8kVHEFpo0YODZKkB+2WiYrltzG9iIb9nsSEYWGZRJEpbS0AGvXar3e2BgwMqJZ4qROtqukrQ3oaoF16Xu1k0Z7e9wjagiNFAQ7a58ZCMe8DZ56Cjh6FHjZy+IbA1FKMBgmqqSpqTDZzu5AsbCwvMWRMbW1PbLLMZz3kctpyUYQRGD973/X0o9jxzTb3dERzH2nWCNPniPvAp+wOTioX+vWBXefROSKwTCRV85FPObmwnuc4oDaCriaqa0NWLMGOHhQn0dQwXaK1XsWtTgbXO/PJwqhTjQ8flwPVjdsaIw5C0QJx5phIr8sSztNhPXV0rL0K4xWb62t+kE7NQUsLgZ//5R4xdlsBsLLFU9ws38uDoQDPzPw2GNannX55fVZkkVUZ5gZJkqrtjY9BTs4qPXDSeqvTKGzg960lniUK2tw2ybF1y/1cyA6OzUYfslLgr1fInLFzDBRmvX1aSu56em4R0IxcMt6poWfALZ4OxXfNtBtZ5cunX56cnqdEzU4BsNEadferuUYExNxj4Qi5hYQlu19m1LOFmhugXCgmeHJyULnGiKKBINhorQT0b7K2axO2qFUYq1wgZ8SiMC3W2+vnrFZsSLY+yWiklgzTERaL7x+PfD888DwsK7G19IS96gSq5F68Sb6OdTarrAGsW0Xy9JgeOXKeB6fKIWYGSYi1damq+6tWKE1xLOzcY8o8RqhnCDRz+HoUeDIkbhHEb3paWB+Pu5REKUGg2EiKmhq0pKJ1auBmRkGxBUkOqtaQanaYGeXiVgD5VxOM8MLC+WXQjem8epru7uD7y9ORCXxv42Illu1SssmJifLByIpF3vAWKVKY05EkD87q5M7Ozo0IHYzOKjZ48OHox1b2Do6NCAmokgwGCYidz09QH+/ZoiJojY/r8FwW9vyhWHsA7RMRmuKi1uQzcxooLywoD/X28Iyi4ulDwCIKHCcQEdEpXV0AGNjcY8isRKRQfWoXDY48PZglczNAfv2acB79tka0E5PazY0l9MSgVxOg925uaVlELOzmg22Swm6uvTvR4/q/jo0pJd1d+sKi01NwIkTOiGtXkoPcjltdchJdESRYDBMRKVlMpqhinFWf1LVUyBcjcCf39iYtu7r6tLAd2FBg9XnntPLR0eBgYHCohMdHdpmrKkJOHZMM8RDQ3pf7e16m95e/dvion4dP64dUc46S/fd1la9v9ZWYHxcr29bXEzuUsddXRr02wcGRBQqBsNEVFp7u34wT07qdwJQf4Gw17rmUhniQDLHk5PaMswYLb/ZulUPsIaHNUP8xBO6DLFlaVbUPgjr79fAd3BQf9+3Tzue2IvEdHfr7bJZLe256ioNgBcXNeiemdHHnp3VDLHdpUFEH2vVqtqeVxjszDgDYaJIMBgmovJWrwaefZbZ4QbmDHRDCYhPntSgdcUKDVrHxoBHH9WfW1r0b+eco3+fn9egeWwMePJJ3f+M0eyuiB6UbdmiWeSmJvd90q4h7ujQ71NTGghPTOhtMplCCUUSiWgwnOTsNVEDqXjYKSKtInK/iPxYRB4TkffnL98iIveJyNMi8h8i0hz+cIkocq2tGoCw72nD8tpdwnfnjNlZ4NChQpa3u1uDXBENeEWAc8/VILizU0sZmpo0w3vGGRogd3VpecO55wLnnw/ccINmlZubvR+ctbdry8BNmzQAn50tZI79mJjQrLPd9i1MlqWPRUSh85IZngVwlTFmUkSaANwjInsA3Argz40xnxORvwfwKwD+LsSxElFcovjwp9B4CWYDbxE3Pa3B44oVGrgePw7s3g0cPAjceqsGe7Ozmvns7NSvYkGvgtjRoS0DH31Ua5TXrwcOHNAscznG6PVmZvTgsK1NA9XTTgt2fMXYUYIoEhUzw0ZN5n9tyn8ZAFcB2J2//NMAbgxjgESUAPXWmopceS1z8LIYR9ngeX5ev3p7tczh5EktebjrrsLkOUD7A5844fdp1KatDXjRi4A1azRAHx+v3Ev70CGdvLdiRWFRmlWrdLJeWGdMRHRsRBQ6TzXDIpIB8ACAMwH8LYBnAIwaY+zD1oMANpS47S0AbgGATZs21TpeIopDU5MGMUFn6lLKGUhaO24rG3wGrVyW2NqxK/+33cv+5uX2hStZhQlqExMa1H3968D+/cALX6iZYkCD0akpDTKj1NKiJRgPPlj5sUdGtLRiYECDaHtS28yMPreJCc1qNwdcKdjUxBUgiSLiaaqqMWbRGHMhgI0ALgFwjtcHMMZ80hizzRizrb+/v7pRElG87FZPQbMnNtnZQZZiALMLkWwHO6i1dtwG5Iw+7tSFpwLhUtlf+7KywXomowHkxIS+xtPT2jVidlbrfm0TE/GtcNjcDFxyie7bo6PL/273LjZGs8jd3UtrlFtbgQsv1Nrnycnlt6+VHQyzVIIodL76thhjRgF8C8DLAPSKiJ1Z3gjgULBDI6LE6O7W08tBBMTGaHB04oTe39q1mlk7cUIziKOjekr6xAn9fvx4wwYErgHl8UlgeFK30+AgcORI5TsyRrfl5KQGmIODhXZiZQJr65UfAR55BNZL/hDWqz8KzM3BuuJDwPyi69h8Zavb2nTi2r59wNNPA6efrl0gtm7Vv09OasAXdEbVj4UF3c+cHRuGhvRrcFC3ZXc3sGGDjt9twt769fpc/U7Gq0REx8Xl0IlCV7FMQkT6AcwbY0ZFpA3AtQA+Cg2KdwH4HIA3A/hKmAMlohjZs/8HB2svlRgf1wBoxQoNInp79Wd75nwup0Hc/LwGK/Pzml3s7q75aSSNa7uy2QVYl/2BBsG9vfrc3czP67YaH9ft2NFRWMHN/nlsTL8sy337HTmiAd9pp+nrOzwMiMC64gPAwkLtAfHwMPDFL2pJwQ03aOC4fr3+raUFWLdOa3Dj0tQE7N2rAfuFF+rYOjs1CG1v1/3UHm8pIrrv2ivGtbUFNz6uREcUCS81w+sAfDpfN2wB+Lwx5nYReRzA50TkQwAeBPBPIY6TiOJmf8jX0vt0YUFPn2/evPQ+RAq9YQENRGwzMzqTf3R06Qpidapi14YNfcjd9WFYN31UM5LPPrv07zMzmoVsb9eAsq+v0JqsWHe3BlN2KUoms/R0/8CAbveODt2+xuhr88QTekCSraEV/ewssGePjrejQyfRvexlOobFRc2+nnFG9fcflHPP1WDWrgWendWyCMvSVmxe2redc47uo2NjwQbDTU2aQWcwTBSqiu90xpiHAbzY5fJ90PphIkqDtjbNkh06VGgv5dfJkxq4+Qmm7ceyVxxrMMuC46wAK7v0tPzhwxpMHj6sGeKVKzUA3rixENRWOjjp6iqsInjsmGaS5+Y08LUsDaoPHNDvra3aIaGrS683O+t9ctuRIzrWnh69TS4HPPAA8PjjwEc/CuzcWRjnkSPJOf2/fbt+zc/rdpia0uB99Wrv9yGir8nMTLBjs/d7LnhDFCquQEdE3vX2ahBjr+ZVzRLN1WR316zRrPLoqD5mHa7KVSojvKybhIgGxPbEs4UFPYiYmNBODD09S5fp9bot7F6+9qS1sTEtA1i5UrPBdo0soBnpJ58EfvxjzR6/+MXumWenbFbH+bWvAeedpwHxq1+t97l/f6E2+OTJwjLLSdLUBJx5ZvW3z2SAp57S571lS3Djmp3Vg4dK5RpEVDUGw0Tkj31Kft8+zaZ5XdJ2YUGvW03NcUuLBmzHj+tXndUPF7dSK7bssrExzd52dQHPPaeB46WXBnMK3j6A6ekpXNbUpNt3eFgvz2aBq6/W3++8UwP07dvL329bmwbZd96p+8bLXw488gjwghdobfCDD+rzWLMm/MUq4iCiwfTnPqffr746mPtdWGjYCaREScFgmIj8a27WLhCHD+spZS8B8cxMbcGcZelCB/bKZtVkpUtwncgW4H371t5e6GqwcaNmhMM+TS6yNFubzQLXXKPbvadH++329RX+nstpWUFLix4U2fXNq1cDV16pgfDgoD6HTEbLL1pbgSuu0AC5lnrkpDr3XH2t7r9fD146Omq/z7Y2/T/buHHpGQEiCgz/s4ioOr29OsFocVEzmZVWyzKm9sUVRDTosid8BSjw5YhreZyf/ES3V3u7ljHEVS/a2anB3dycLqPsbB/24IPAPfcUWuANDhZWlHvwQS2V+NVf1cv27QMuuAD40Y80c/zoo/E8nyjs2qXt4x5/PJi66O5uPYgYHq79vojIVQMemhNRZOw61OlpDXomJjSTVZz1m5kptAKrVSajp90XFvRxaywdiCoIBkqvNnfK0aP6nLJZDfjPOmtpOUPUOjq0ZnhhQbO+Bw5oYDY6CnzhC5oJ3bpV64snJ4Gzz9bA/frrNTMK6Otz4IDWH2/bpn//2td0X7n88vieW5huvhn4h3/QTHpnpx44Orul+CFS6M1NRKFgZpiIatfWpnWgXV2F1l82u2/wxo3BlTZkMpplnp0NrCtBWGUSThXLMRYWtMxgYEC3Z5yBsK2rS3vwbt+u4/nrvwZ++7d1Utwv/ZKWy6xercHt1q2aGb3E0WjoqquA175WA33L0hXoRBp7qeH2dt1HDx3SgLjSWZNKOjr0vhp5mxHFiJlhIgqGvUDB9HShRVVvr2YM+/qC7xHc3a0lBJOTNWWHowiCPT1WLqfPQ0TLT7xOTIxKf7++huvXa8nDzTfrtj9yRIO9bFbbwa1atbysY+VK4Dd+A/j2tzUrfOmlwMUXx/I0ImFZehCwfn3hOb/zndXXSbe2aqlJd/fS5ayJKBAMhokoWG1tmtm0e9pmMksnXgX9WGNj4dx31OxttWZN8gJhmwjwvvdp/WpTk2b77YMRyypf23zsmGbzRTSbnISsd5jsoHVgQGukn3lGy0iqkc1qYP3kk7rARyNOPiSKEf+jiCh4bW2a3ZyZ0eCn1iWcSxHRx6jUAzcBymaFJyY0mNywIdnPJZstLOJh8zJeYzS7edVVwXRYqCfnngu85jXApz6l5SXV9gseGADe/W6tzf/t3w52jEQpx2CYiMIhEuzStG6cE/jCfqwqVSzDGBnRg4VVqwJtF5coIrpwRxq1tWm3jWeeqf1+LrtMD5q4Ih1RoDiBjojql90bd34+7pEsNT2tNdNDQ1pTOzWlE8iM0a+xMe2ucOiQlg5s3hx8TTUlx+OPa0bYzxLPbt7wBt1PDhwIZFhEpBgME1F9s1tWGRPvOJzGxjQQnpvTiYUzM1piMD6u9baLi1ou0NenbeJYA9rY3vpWrQc/erS2+2lt1brjubnAuqgQEcskiKje2XWsk5PJKTNob9c2aXbpRjarGeL+fp141tmpNaBJGS+F68or9fVfu7a2+7FbCY6P6yIn1dYfE9ESzAwTUX0T0dZduVxysmWWpV9dXZr5bWvTrF5bm3ZRsHsyUzp0dAAve5keINWip0cPqE6ebJwuKkQJwMwwEdW/1lbNxp48GW+QOTOjnSF6ezUIHh7WAMheNW/duvA6a1Byzc3p9+bm2u6nuVmzw3YHj4UFltgQBYD/RUTUGLq64l+ha25Og/KhIZ3U98Mf6uS5171OW2xROh0/rvtmrR0gWlr0gK+zs9DbmYhqxmCYiBpDR4cGoXHq7NTa5bExbaW1caNmgxkIp9viYmGiZ60WFgq9tRkMEwWCwTARNYbmZj1lPDMTXODhx/Cw1izPzupY+vq0t+6mTdGPhZJjZKTQTSQIlpXYntpE9YqHlUTUGER0dv3Cgvb5jcrkpAbClqUdAx57TLPBr3oVsGWL1gtTej3+uC5FHdTKgn19uq8nqZUgUZ1jZpiIGkdbmy5g8fzzWrPb1BTo3ef23Lrkd+vaj2ngbU/am5nR9lmrVunMf6LmZj1AC2rFuExG7y8pnVOIGgCDYSJqLM3N2n7q8OHAg2GbtWMXACD332+DdcHbdFLT7KyWRPT0cDU5Khgb032jrQ3o7g6mhGdhQeuQFxd55oEoACyTIKLG09lZWPktYHYgDADIZpC776M6We7ppzXgOfPMwB+T6pi96mB3t55FOHoUOHGitvtcswZ49llg//5AhkiUdgyGiajxWJYuxGH3dw1Y7t//H3Kf+1dgZArWOW8BvvMdreE866xQHo/q2Pr1wJo1yH359zQrPD+vQXEtC3DYNcNTU8GNkyjFGAwTUWNqayucSg6AXS+c27NbL2gSWDfepuUY8/MaCHMBBCo2P6/7CIDc198BjI5qMFxrDXF3N/DTn2rmmYhqwmCYiBpTU5Nmh0MIFqybfxHIGeTufLs+xtVXAy9/eeCPQw3g4ouBoSFY5/46rCs/WFiOu9Za3w0bkLvjIxoQE1FNGAwTUWMS0drKri5dAazG+mFrx22nfs7t2Q1kLODIKPDUU8AVV4Q2WY/qXGurlkT89Kf6fXw8kCW5c3tuBfo6WSpBFAAGw0TUuOzew6tW6Yz+gEomkMsBTRlYWy/WwGblymDulxrTVVfpaoTHjiF34B+X/Km4XZ8va/LdKdhzmKgmDIaJqLFls7oIRkeHBsQ1sHbcBuvVH4f1kncAiwa527+qSy13dAQ0WGpI9opxTU3AWIAdTrpbkfvyO3WVOyKqGmd7EFE6dHZqi6tqGaMToVpbARFYL3s3cMYx4IUvDG6M1Jja2rSd2umnA20BltNkM0DO6MqHK1YEd79EKcPMMBGlRy0z+EU0y7ywoF9TU7q4R19fcOOjxrR1K/CiF+nKiC3B5KBO1bD3trGLCVGNGAwTUTpMTtZWJpHLaXa4pUVbYz3/vF7OiXNUiWVpzfDRo7Cu+pOSV8vtudVzDbF9Peu1H9OsMyfSEVWNwTARpcPq1bVl0EQ0I+xcWrezM7jxUWPbsAG44ALg4MElFzu7lFg7blvyuxe5/3kXMDGhqyASUVUYDBNROrS2am/XXK6624todm/NGqC3VzPNAbTIopQQ0QOoyclg7zdj6UHa8ePB3i9RirDQiIjSwS5zqHXlLwDYtw8YGqr9fihdNm/WEpuTJ3U/bG+v/T67WrSjyfy8tg6sdTEPohRiZpiI0sGeAFfj4huYny8E1RMTwYyN0qGtrbAq4vg4MDgIPPoocOCA77taUk7R3AzMzQFHjwY4WKL0YDBMROkgot0fZmZqW6RgZEQzenbvYiI/slktlchktOY8m61qyfBTE+h23AYsLiJ357u5+AZRlVgmQUTp0dUF9PToqepqT1Hncno62rK0b/GWLcGOkRpbXx/w+ON6UHbTTZop7u/3fTd3nLcdAHC9o/tE7r9/F9ZbvhDYUInSgplhIkqX/v7almXu79dSiUxGJ+UR+dHeDgwMAP/5n8Dv/Z7nGvZSLdfuOG/7qcDYevXHgholUaowM0xE6dLcrL2BFxaqa7WWyQCrVmlfV3syFMslyI81a/T79DTwne8Ar3/9kj87SyCcQfDtB75U/n5ZJkFUFQbDRJQuIlqrOTFRW9/h1auBsTFgdJTBMPmzbp2eVfjJT7RsoigYdloyUa5MMGy98oZgOqUQpRDLJIgofdraql6NLrfnVq3zXFjQYOahh4IdGzW+9euBXbuAs87SmvNqe18D2DmwFtc/fk+AgyNKHwbDRJQ+bW36NT/v6er2Mrn2KevcnX+grawef5wrf1F1XvYy4AUvAI4c0VKJwcFTf3JbhS6351bsHFjrcvnuwi8WP9KJqsEyCSJKn2xWv0ZH9dRyV5fWERcpNWkJBlqfedllWj8c1GIelB4rVgC/8AvAAw8UzjD87u+e+rN7QLwbO3fsWnrZ4/nv3/oqrDfsCHHARI2Lh5FElE7r1gGnnab1w7Ozy5bJLRUIWztug/Wav9COFIuLeor7yJEIBkwNZf164KKLgF/7NeDFLwY2bSp79UJwfBmAy/IZ4cuKrsSPdKJq8D+HiNIpmwV6e3WJ3LVrNbs7PAwMDyP31d8D4J6dA/KBsmXp5Kenn45uzNSYLrkEuOqqildz7o+u+ybPThBVhcEwEVF3t2aKV64EurpgXXwtsFBhUtPq1Xqqe3Q0kiFSA1uzRlv21cJiIExULQbDRESABsQbNmimeNV1sF72HuS+8tuwrrkRWMwBOe3hWphE9/taInHWWdpzmKhamYx+VbEs8yn8NCeqGifQERE5iWhQbFlaOjF7EaxXviT/8z34+oEjuHrwYVjX/7l2AGhrA0ZG4h411bvHH9f9aefO6m7PzDBR1RgMExEVEwHWr4f1G1/UFmrNzdpXeKQP13ZOAhtv0OC4qUnrjbnoBtXqJz8BHn0UaGkBrrnGc/2vle8ukfviv2kNOxH5xhMrRETlNDfr92wW6O/XWuHOTuQ+9xsaBHd1cRY/1e7mm4E77wR++ZeBn/s54JFHvN92/yAwPuPaHpCIKuM7OBGRHx0dwJo1sH7mL7Ubxfr1+kVUi40bte/w1q3A/fcDr30t8NnPerttU37ynTHhjY+ogTEYJiLyq6tLJ9qtWBH3SKiRfPzjwJNPAldfreU5t7m39ltidh44fByYX2RmmKhKDIaJiIiS5PbbgWuv1fKb558vebXcnluB4VHkDj0I6xf/b4QDJGosDIaJiIiS5mtfA17wAuAb3yh/vbEpWNv/WEt2iKgqDIaJiIiS6D3vAU4/vWQtsLVjF+7MLQJ33611xkRUFQbDRERESXTmmdrH+rHHXP+c++oX8OqNO4EzzgDa2yMeHFHjYDBMRESUROvX6+qG73wn8NBDy/5s3fDnwL/9m35t3Rr9+IgaBINhIiKipLrnHuBHPwJe8xrg+99f+rf9+7WE4uyz2d6PqAYMhomIiJLqbW/TQDeXA+66C5id1WWbv/MdDYRvvBH41V+Ne5REda3icswichqAzwBYA8AA+KQx5i9F5H0Afg3AUP6q7zLG3BHWQImIiFJnehr48Ie1TGLlSuAd7wAmJ4ETJ4CLLwbe+lZmhYlqVDEYBrAA4G3GmB+JSBeAB0Tk6/m//bkx5uPhDY+IiCjF+vqAV75S+w1/5jPAc88BmYxevmoV0N0d9wiJ6l7FMgljzBFjzI/yP08AeALAhrAHRkRElHobNgBHjmjQe9NNQH8/kM0CZ50FvP71+nciqomvmmER2QzgxQDuy1/0f0TkYRH5ZxHpK3GbW0Rkr4jsHRoacrsKERERlbJmDXD55boIxwUXAOecA9xwA3DJJXGPjKgheA6GRaQTwBcB/K4xZhzA3wE4A8CFAI4A+ITb7YwxnzTGbDPGbOvv7699xERERI1sfl6/7r8fmJkBtmwBLroIGBjQQPiaa4Cf+zkNjomoZl5qhiEiTdBA+LPGmC8BgDHmqOPv/wDg9lBGSERElBZ79wLXXqvdIy66CPjlXwa2b9cWa3NzWiqxZQsnzREFqGJmWEQEwD8BeMIYc5vj8nWOq90E4NHgh0dERJQSt9wCvOIVwOgoMD4OPPEEIAJ873vA0aPAunUaGLNOmChQXjLDLwfwiwAeEZGH8pe9C8DNInIhtN3afgC/HsL4iIiI6tOhQ8DEhJY2uDl8WDO8hw8D738/8A//AFgW0NUFdHYCV16prdUuvxxYuxbo7Y1y9ESpUTEYNsbcA0Bc/sSewkRERKX09wPf/rYuqXzRRUv/9q1vAd/4BvCSlwDf/a72De7vB848E7j5Zu0gcfPNwAtfGM/YiVLEU80wERER+dTcrBPd3GzcCLS1aRlEfz+wYwfwa7+mLdM2b450mERpx2CYiIgoalu3Au95j/58003xjoUo5Xz1GSYiIiIiaiQMhomIiIgotRgMExEREVFqMRgmIiIiotRiMExEREREqcVgmIiIiIhSi8EwEREREaUWg2EiIiIiSi0Gw0RERESUWgyGiYiIiCi1GAwTERERUWoxGCYiIiKi1GIwTERERESpxWCYiIiIiFKLwTARERERpRaDYSIiIiJKLQbDRERERJRaDIaJiIiIKLUYDBMRERFRajEYJiIiIqLUYjBMRERERKnFYJiIiIiIUovBMBERERGlFoNhIiIiIkotBsNERERElFoMhomIiIgotRgMExEREVFqMRgmIiIiotRiMExEREREqcVgmIiIiIhSi8EwEREREaUWg2EiIiIiSi0Gw0RERESUWgyGiYiIiCi1GAwTERERUWoxGCYiIiKi1GIwTERERESpxWCYiIiIiFKLwTARERERpRaDYSIiIiJKLQbDRERERJRaDIaJiIiIKLUYDBMRERFRajEYJiIiIqLUYjBMRERERKnFYJiIiIiIUovBMBERERGlFoNhIiIiIkotBsNERERElFoMhomIiIgotRgMExEREVFqMRgmIiIiotRiMExEREREqcVgmIiIiIhSi8EwEREREaUWg2EiIiIiSi0Gw0RERESUWhWDYRE5TUS+JSKPi8hjIvI7+ctXiMjXReSp/Pe+8IdLRERERBQcL5nhBQBvM8acB+BSAL8pIucBeAeAu4wxWwHclf+diIiIiKhuVAyGjTFHjDE/yv88AeAJABsAvA7Ap/NX+zSAG0MaIxERERFRKLJ+riwimwG8GMB9ANYYY47k/zQIYE2J29wC4Jb8r7Mi8mh1Q6UarQIwHPcgUojbPT7c9vHhto8Pt308uN3jc3atdyDGGG9XFOkE8G0AHzbGfElERo0xvY6/jxhjytYNi8heY8y2WgZM1eG2jwe3e3y47ePDbR8fbvt4cLvHJ4ht76mbhIg0AfgigM8aY76Uv/ioiKzL/30dgGO1DISIiIiIKGpeukkIgH8C8IQx5jbHn/4LwJvzP78ZwFeCHx4RERERUXi81Ay/HMAvAnhERB7KX/YuAH8K4PMi8isADgB4g4f7+mQ1g6RAcNvHg9s9Ptz28eG2jw+3fTy43eNT87b3XDNMRERERNRouAIdEREREaUWg2EiIiIiSq1QgmER+dn80s05EdnmuPwSEXko//VjEbnJ8bfrROQnIvK0iHA1uyqV2fbXisgDIvJI/vtVjr+9JH/50yLyV/lJk+RTmW2/Mr+k+aSI/E3RbbjtA1Bq2+f/9s789v2JiLzacTnfcwImIheIyPfz+/R/i0i342+urwPVTkQuFJEf5D9b94rIJfnLJf++8rSIPCwiF8U91kYjIv/hiGv2O+ZWcZ+PgIj8log8mX///5jjcn/b3hgT+BeAc6FNkO8GsM1xeTuAbP5nux1bFkAGwDMATgfQDODHAM4LY2yN/lVm278YwPr8z+cDOOT42/3QpbYFwB4AO+J+HvX4VWbbdwDYDuAtAP6m6Dbc9uFu+/Py7yctALbk32cyfM8J7XX4IYAr8j//MoAPlnsd4h5vo3wB+Jr93gHgegB3O37ek39/uRTAfXGPtZG/AHwCwHvzP3OfD397vxLANwC05H9fXe22DyUzbIx5whjzE5fLp4wxC/lfWwHYs/cuAfC0MWafMWYOwOegyz2TT2W2/YPGmMP5Xx8D0CYiLfke0d3GmB8Y3Ys+Ay6tXZUy2/6kMeYeADPOy7ntg1Nq20PfRz5njJk1xjwL4Gno+w3fc8JxFoDv5H/+OoCfyf9c6nWgYBgAdha+B4D9Xv86AJ8x6gcAeu31AShY+bN6bwDw7/mLuM+H760A/tQYMwsAxhh7vQvf2z7ymmEReamIPAbgEQBvyQfHGwA877jawfxlFI6fAfCj/A60Abq9bdz20eG2D1+p9xa+54TjMRQOKn4WwGn5n7m9w/W7AP5MRJ4H8HEA78xfzu0encsBHDXGPJX/nds+fGcBuFxE7hORb4vIxfnLfW97L32GXYnINwCsdfnTu40xJRfgMMbcB+AFInIugE+LyJ5qx5BW1W77/G1fAOCjAF4VxtgaXS3bnmrDbZ8M5V4HaGnEX4nIH0EXZpqLcmyNrMJ2vxrA7xljvigib4AulHVNlONrZB7fe25GIStMAamw32cBrICWAF0MXfvi9Goep+pg2BhT0z+aMeYJEZlEvn4VhQwCAGzMX0Yuqt32IrIRwJcBvMkY80z+4kPQ7W3jti+j1v2+CLe9D1Vu+3LvLXzPqYKH1+FVACAiZwG4IX8Z3+NrVG67i8hnAPxO/tcvAPjH/M/c7gGotM+LSBbA6wG8xHExt30AKuz3bwXwpXyZ4f0ikgOwClVs+0jLJERkS36ngYgMADgHwH7opIut+b83A3gjNKtAARGRXgBfBfAOY8z37MuNMUcAjIvIpfmapzeBS2tHgts+Ev8F4I35+vgtALZCJy3yPScEIrI6/90C8B4Af5//U6nXgYJxGMAV+Z+vAmCfqv8vAG/Kd5W4FMBY/n2HgnUNgCeNMc6yN+7z4ftP6CQ6++C7GcAwqtj2VWeGyxFtmfbXAPoBfFVEHjLGvBo6o/4dIjIPIAfgN4wxw/nb/B8Ad0Jnef+zMeaxMMbW6Mps+/8D4EwA7xWR9+av/qp8wflvAPgXAG3QmccsXalCmW0PEdkPneDSLCI3Qrf94+C2D0SpbW+MeUxEPg/gcQALAH7TGLOYvw3fc4J3s4j8Zv7nLwH4FACUex0oEL8G4C/zyaYZALfkL78D2lHiaQBTAP53PMNreG9EUYkE9/lI/DOAfxaRR6ElWW/OZ4l9b3sux0xEREREqcUV6IiIiIgotRgMExEREVFqMRgmIiIiotRiMExEREREqcVgmIiIiIhSi8EwEREREaUWg2EiIiIiSq3/HxHVDCGLA+YAAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Define the colors you want\n",
    "cmap = ListedColormap([\"#ffffff\", \"#fdae61\", \"#ffffbf\", \"#abdda4\"])\n",
    "\n",
    "# Define a normalization from values -> colors\n",
    "norm = colors.BoundaryNorm([10093132, 23580922297, 47151751462, 70722580627, 94293409792], 5)\n",
    "\n",
    "with rio.open(path + 'usa_tot_wf_area.tif') as src:\n",
    "    dat = src.read(1)\n",
    "    fig, ax = plt.subplots(figsize=[15,10])\n",
    "    ax.set_ylim((20,60))\n",
    "    ax.set_xlim((-130,-60))\n",
    "    rio.plot.show(dat, norm=norm, cmap=cmap, ax=ax, transform=src.transform)\n",
    "    gadm_usa.plot(ax=ax, color='red', alpha=.1, edgecolor='red')\n",
    "    ax.set_title('Total Water footprint mm/yr * aream2 in USA ')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "id": "2b44dbe1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "shape: (1668, 4320)\n",
      "noData: 0.0\n",
      "GLOBAL Total sum excluding no data: 1367447391174656.0 mm/yr\n",
      "GLOBAL Total sum excluding no data: 1367.447391174656 m3/yr\n"
     ]
    }
   ],
   "source": [
    "src_usa_area = rio.open(path + \"usa_tot_wf_area.tif\")\n",
    "print('shape:',src_usa_area.shape)\n",
    "print('noData:',src_usa_area.nodata)\n",
    "\n",
    "image_read_usa_area = src_usa_area.read(1)\n",
    "src_masked_usa_area = numpy.ma.masked_array(image_read_usa_area, mask=(image_read == src_usa_area.nodata))\n",
    "\n",
    "print(f'GLOBAL Total sum excluding no data: {src_masked_usa_area.sum()} mm/yr')\n",
    "print(f'GLOBAL Total sum excluding no data: {src_masked_usa_area.sum()*0.001/1000000000} m3/yr')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b714c1f",
   "metadata": {},
   "source": [
    "Based on this link (https://www.waterfootprint.org/media/downloads/Report50-NationalWaterFootprints-Vol1.pdf) the total value of water footprint in USA was: 1053 Mm3/yr, and the value calculated above is 1367.447391174656 Mm3/yr.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "id": "c4eb7e0e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "absolute difference: -314\n",
      "relative difference: -0.2981956315289649\n"
     ]
    }
   ],
   "source": [
    "#compute difference between calculated value and value provided in the paper.\n",
    "\n",
    "value = 1053 \n",
    "value_es = round(1367.447391174656)\n",
    "\n",
    "difference_abs = value - value_es\n",
    "print(f'absolute difference: {difference_abs}')\n",
    "\n",
    "difference_rel = (value-value_es)/value\n",
    "print(f'relative difference: {difference_rel}')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "40bf0541",
   "metadata": {},
   "source": [
    "We can asume that this difference is due to differences in admin area boundaries. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b83855a1",
   "metadata": {},
   "source": [
    "### Calculate toal water footprint for india:\n",
    "\n",
    "Calculate total water footprint for india so we can compare with value provided in the paper."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "id": "dfa1a1f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GID_0</th>\n",
       "      <th>NAME_0</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>IND</td>\n",
       "      <td>India</td>\n",
       "      <td>MULTIPOLYGON (((93.78773 6.85264, 93.78849 6.8...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  GID_0 NAME_0                                           geometry\n",
       "0   IND  India  MULTIPOLYGON (((93.78773 6.85264, 93.78849 6.8..."
      ]
     },
     "execution_count": 150,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gadm_ind = gpd.read_file(path+'gadm36_IND_0.shp')\n",
    "gadm_ind.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "id": "bbb189c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Define the colors you want\n",
    "cmap = ListedColormap([\"#ffffff\", \"#fdae61\", \"#ffffbf\", \"#abdda4\"])\n",
    "\n",
    "# Define a normalization from values -> colors\n",
    "norm = colors.BoundaryNorm([0, 214, 429, 644, 858], 5)\n",
    "\n",
    "with rio.open(path + 'wf_tot_mmyr/hdr.adf') as src:\n",
    "    dat = src.read(1)\n",
    "    fig, ax = plt.subplots(figsize=[15,10])\n",
    "    ax.set_ylim((4,40))\n",
    "    ax.set_xlim((65,100))\n",
    "    rio.plot.show(dat, norm=norm, cmap=cmap, ax=ax, transform=src.transform)\n",
    "    gadm_ind.plot(ax=ax, color='red', alpha=.1, edgecolor='red')\n",
    "    ax.set_title('Total water footprint mm/yr')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "id": "67e530fa",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<string>:1: RuntimeWarning: overflow encountered in multiply\n",
      "/opt/conda/lib/python3.8/site-packages/osgeo/utils/gdal_calc.py:367: RuntimeWarning: invalid value encountered in multiply\n",
      "  myResult = ((1 * (myNDVs == 0)) * myResult) + (myOutNDV * myNDVs)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 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"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 100 - Done\r\n"
     ]
    }
   ],
   "source": [
    "## multiply raster by area\n",
    "!gdal_calc.py --calc \"A*10000*10000\" --format GTiff --type Float32 --NoDataValue 0.0 -A $path'wf_tot_mmyr/hdr.adf' --A_band 1 --outfile $path'tot_wf_mmyr_area.tif'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "id": "3710dbf3",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Driver: GTiff/GeoTIFF\n",
      "Files: ../../datasets/raw/wf/QA/tot_wf_mmyr_area.tif\n",
      "Size is 4320, 1668\n",
      "Coordinate System is:\n",
      "GEOGCRS[\"WGS 84\",\n",
      "    DATUM[\"World Geodetic System 1984\",\n",
      "        ELLIPSOID[\"WGS 84\",6378137,298.257223563,\n",
      "            LENGTHUNIT[\"metre\",1]]],\n",
      "    PRIMEM[\"Greenwich\",0,\n",
      "        ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "    CS[ellipsoidal,2],\n",
      "        AXIS[\"geodetic latitude (Lat)\",north,\n",
      "            ORDER[1],\n",
      "            ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "        AXIS[\"geodetic longitude (Lon)\",east,\n",
      "            ORDER[2],\n",
      "            ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "    ID[\"EPSG\",4326]]\n",
      "Data axis to CRS axis mapping: 2,1\n",
      "Origin = (-179.991666649999985,83.097781810917979)\n",
      "Pixel Size = (0.083333340000000,-0.083333340000000)\n",
      "Metadata:\n",
      "  AREA_OR_POINT=Area\n",
      "Image Structure Metadata:\n",
      "  INTERLEAVE=BAND\n",
      "Corner Coordinates:\n",
      "Upper Left  (-179.9916666,  83.0977818) (179d59'30.00\"W, 83d 5'52.01\"N)\n",
      "Lower Left  (-179.9916666, -55.9022293) (179d59'30.00\"W, 55d54' 8.03\"S)\n",
      "Upper Right ( 180.0083622,  83.0977818) (180d 0'30.10\"E, 83d 5'52.01\"N)\n",
      "Lower Right ( 180.0083622, -55.9022293) (180d 0'30.10\"E, 55d54' 8.03\"S)\n",
      "Center      (   0.0083478,  13.5977763) (  0d 0'30.05\"E, 13d35'51.99\"N)\n",
      "Band 1 Block=4320x1 Type=Float32, ColorInterp=Gray\n",
      "  NoData Value=0\n"
     ]
    }
   ],
   "source": [
    "!gdalinfo $path'tot_wf_mmyr_area.tif'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "id": "e479589f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0...10...20...30...40...50...60...70...80...90...100 - done.\n"
     ]
    }
   ],
   "source": [
    "# rasterize india shape for cliping data\n",
    "!gdal_rasterize -l gadm36_IND_0 -burn 1.0 -tr 0.08333334 0.08333334 -a_nodata 0.0 -te -179.99166665 -55.902229309 180.00836215 83.097781811 -ot Float32 -of GTiff $path'gadm36_IND_0.shp' $path'gadm36_IND_0.tif'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "id": "24f74218",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Driver: GTiff/GeoTIFF\n",
      "Files: ../../datasets/raw/wf/QA/gadm36_IND_0.tif\n",
      "Size is 4320, 1668\n",
      "Coordinate System is:\n",
      "GEOGCRS[\"WGS 84\",\n",
      "    DATUM[\"World Geodetic System 1984\",\n",
      "        ELLIPSOID[\"WGS 84\",6378137,298.257223563,\n",
      "            LENGTHUNIT[\"metre\",1]]],\n",
      "    PRIMEM[\"Greenwich\",0,\n",
      "        ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "    CS[ellipsoidal,2],\n",
      "        AXIS[\"geodetic latitude (Lat)\",north,\n",
      "            ORDER[1],\n",
      "            ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "        AXIS[\"geodetic longitude (Lon)\",east,\n",
      "            ORDER[2],\n",
      "            ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "    ID[\"EPSG\",4326]]\n",
      "Data axis to CRS axis mapping: 2,1\n",
      "Origin = (-179.991666650000013,83.097781811000004)\n",
      "Pixel Size = (0.083333340000000,-0.083333340000000)\n",
      "Metadata:\n",
      "  AREA_OR_POINT=Area\n",
      "Image Structure Metadata:\n",
      "  INTERLEAVE=BAND\n",
      "Corner Coordinates:\n",
      "Upper Left  (-179.9916667,  83.0977818) (179d59'30.00\"W, 83d 5'52.01\"N)\n",
      "Lower Left  (-179.9916667, -55.9022293) (179d59'30.00\"W, 55d54' 8.03\"S)\n",
      "Upper Right ( 180.0083622,  83.0977818) (180d 0'30.10\"E, 83d 5'52.01\"N)\n",
      "Lower Right ( 180.0083622, -55.9022293) (180d 0'30.10\"E, 55d54' 8.03\"S)\n",
      "Center      (   0.0083478,  13.5977763) (  0d 0'30.05\"E, 13d35'51.99\"N)\n",
      "Band 1 Block=4320x1 Type=Float32, ColorInterp=Gray\n",
      "  NoData Value=0\n"
     ]
    }
   ],
   "source": [
    "!gdalinfo $path'gadm36_IND_0.tif'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "id": "4e25e795",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 13.. 13.. 13.. 13.. 13.. 13.. 13.. 13.. 13.. 13.. 13.. 13.. 13.. 13.. 13.. 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85.. 85.. 85.. 86.. 86.. 86.. 86.. 86.. 86.. 86.. 86.. 86.. 86.. 86.. 86.. 86.. 86.. 86.. 86.. 86.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 87.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 88.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 100 - Done\r\n"
     ]
    }
   ],
   "source": [
    "#multiply by wft\n",
    "!gdal_calc.py --calc \"A*B\" --format GTiff --type Float32 --NoDataValue 0.0 -A $path'gadm36_IND_0.tif' --A_band 1 -B $path'tot_wf_mmyr_area.tif' --outfile $path'IND_tot_wf_mmyr_area.tif'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "id": "3a004633",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Driver: GTiff/GeoTIFF\n",
      "Files: ../../datasets/raw/wf/QA/IND_tot_wf_mmyr_area.tif\n",
      "Size is 4320, 1668\n",
      "Coordinate System is:\n",
      "GEOGCRS[\"WGS 84\",\n",
      "    DATUM[\"World Geodetic System 1984\",\n",
      "        ELLIPSOID[\"WGS 84\",6378137,298.257223563,\n",
      "            LENGTHUNIT[\"metre\",1]]],\n",
      "    PRIMEM[\"Greenwich\",0,\n",
      "        ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "    CS[ellipsoidal,2],\n",
      "        AXIS[\"geodetic latitude (Lat)\",north,\n",
      "            ORDER[1],\n",
      "            ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "        AXIS[\"geodetic longitude (Lon)\",east,\n",
      "            ORDER[2],\n",
      "            ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "    ID[\"EPSG\",4326]]\n",
      "Data axis to CRS axis mapping: 2,1\n",
      "Origin = (-179.991666650000013,83.097781811000004)\n",
      "Pixel Size = (0.083333340000000,-0.083333340000000)\n",
      "Metadata:\n",
      "  AREA_OR_POINT=Area\n",
      "Image Structure Metadata:\n",
      "  INTERLEAVE=BAND\n",
      "Corner Coordinates:\n",
      "Upper Left  (-179.9916667,  83.0977818) (179d59'30.00\"W, 83d 5'52.01\"N)\n",
      "Lower Left  (-179.9916667, -55.9022293) (179d59'30.00\"W, 55d54' 8.03\"S)\n",
      "Upper Right ( 180.0083622,  83.0977818) (180d 0'30.10\"E, 83d 5'52.01\"N)\n",
      "Lower Right ( 180.0083622, -55.9022293) (180d 0'30.10\"E, 55d54' 8.03\"S)\n",
      "Center      (   0.0083478,  13.5977763) (  0d 0'30.05\"E, 13d35'51.99\"N)\n",
      "Band 1 Block=4320x1 Type=Float32, ColorInterp=Gray\n",
      "  NoData Value=0\n"
     ]
    }
   ],
   "source": [
    "!gdalinfo $path'IND_tot_wf_mmyr_area.tif'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "id": "54ecba8c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Define the colors you want\n",
    "cmap = ListedColormap([\"#ffffff\", \"#fdae61\", \"#ffffbf\", \"#abdda4\"])\n",
    "\n",
    "# Define a normalization from values -> colors\n",
    "norm = colors.BoundaryNorm([10093132, 23580922297, 47151751462, 70722580627, 94293409792], 5)\n",
    "\n",
    "with rio.open(path + 'IND_tot_wf_mmyr_area.tif') as src:\n",
    "    dat = src.read(1)\n",
    "    fig, ax = plt.subplots(figsize=[15,10])\n",
    "    ax.set_ylim((4,40))\n",
    "    ax.set_xlim((65,100))\n",
    "    rio.plot.show(dat, norm=norm, cmap=cmap, ax=ax, transform=src.transform)\n",
    "    gadm_ind.plot(ax=ax, color='red', alpha=.1, edgecolor='red')\n",
    "    ax.set_title('Total water footprint mm/yr')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "id": "a261a619",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "shape: (1668, 4320)\n",
      "noData: 0.0\n",
      "GLOBAL Total sum excluding no data: 1406779091058688.0 mm/yr\n",
      "GLOBAL Total sum excluding no data: 1406.779091058688 m3/yr\n"
     ]
    }
   ],
   "source": [
    "src_india_area = rio.open(path + \"IND_tot_wf_mmyr_area.tif\")\n",
    "print('shape:',src_india_area.shape)\n",
    "print('noData:',src_india_area.nodata)\n",
    "\n",
    "src_india_area_array = src_india_area.read()\n",
    "#remove nans that appear outside boundary for extent\n",
    "src_india_area_array_nonan = src_india_area_array[~numpy.isnan(src_india_area_array)]\n",
    "\n",
    "print(f'GLOBAL Total sum excluding no data: {src_india_area_array_nonan.sum()} mm/yr')\n",
    "print(f'GLOBAL Total sum excluding no data: {src_india_area_array_nonan.sum()*0.001/1000000000} m3/yr')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "id": "67db2c46",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "absolute difference: -225\n",
      "relative difference: -0.19035532994923857\n"
     ]
    }
   ],
   "source": [
    "#compute difference\n",
    "value = 1182 \n",
    "value_es = round(1406.779091058688)\n",
    "\n",
    "difference_abs = value - value_es\n",
    "print(f'absolute difference: {difference_abs}')\n",
    "\n",
    "difference_rel = (value-value_es)/value\n",
    "print(f'relative difference: {difference_rel}')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1581cbad",
   "metadata": {},
   "source": [
    "As we have seen with the calculation performed in India, we are still working within the same kind of difference."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fba74dd7",
   "metadata": {},
   "source": [
    "### Compute total blue water footprint in india:\n",
    "\n",
    "Lets compute now thetotal blue water footprint to compare the result to the one shown on the report: https://www.waterfootprint.org/media/downloads/Report50-NationalWaterFootprints-Vol1.pdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "id": "7e4ab915",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "# Define the colors you want\n",
    "cmap = ListedColormap([\"#ffffff\", \"#73b3d8\", \"#2879b9\", \"#08306b\"])\n",
    "\n",
    "# Define a normalization from values -> colors\n",
    "norm = colors.BoundaryNorm([0, 10, 50, 115, 150], 5)\n",
    "\n",
    "with rio.open(path + 'wf_bltot_mmyr/hdr.adf') as src:\n",
    "    dat = src.read(1)\n",
    "    fig, ax = plt.subplots(figsize=[15,10])\n",
    "    ax.set_ylim((4,40))\n",
    "    ax.set_xlim((65,100))\n",
    "    rio.plot.show(dat, norm=norm, cmap=cmap, ax=ax, transform=src.transform)\n",
    "    gadm_ind.plot(ax=ax, color='red', alpha=.1, edgecolor='red')\n",
    "    ax.set_title('Blue water footprint mm/yr')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "id": "3832d62c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<string>:1: RuntimeWarning: overflow encountered in multiply\n",
      "/opt/conda/lib/python3.8/site-packages/osgeo/utils/gdal_calc.py:367: RuntimeWarning: invalid value encountered in multiply\n",
      "  myResult = ((1 * (myNDVs == 0)) * myResult) + (myOutNDV * myNDVs)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 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"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 89.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 90.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 91.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 92.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 93.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 94.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 95.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 100 - Done\r\n"
     ]
    }
   ],
   "source": [
    "#get the total blue water footprint per area\n",
    "!gdal_calc.py --calc \"A*10000*10000\" --format GTiff --type Float32 --NoDataValue 0.0 -A $path'wf_bltot_mmyr/hdr.adf' --A_band 1 --outfile $path'bl_wf_mmyr_area.tif'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "id": "876bc0e2",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Driver: GTiff/GeoTIFF\n",
      "Files: ../../datasets/raw/wf/QA/bl_wf_mmyr_area.tif\n",
      "Size is 4320, 1668\n",
      "Coordinate System is:\n",
      "GEOGCRS[\"WGS 84\",\n",
      "    DATUM[\"World Geodetic System 1984\",\n",
      "        ELLIPSOID[\"WGS 84\",6378137,298.257223563,\n",
      "            LENGTHUNIT[\"metre\",1]]],\n",
      "    PRIMEM[\"Greenwich\",0,\n",
      "        ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "    CS[ellipsoidal,2],\n",
      "        AXIS[\"geodetic latitude (Lat)\",north,\n",
      "            ORDER[1],\n",
      "            ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "        AXIS[\"geodetic longitude (Lon)\",east,\n",
      "            ORDER[2],\n",
      "            ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "    ID[\"EPSG\",4326]]\n",
      "Data axis to CRS axis mapping: 2,1\n",
      "Origin = (-179.991666649999985,83.088344470000010)\n",
      "Pixel Size = (0.083333340000000,-0.083333340000000)\n",
      "Metadata:\n",
      "  AREA_OR_POINT=Area\n",
      "Image Structure Metadata:\n",
      "  INTERLEAVE=BAND\n",
      "Corner Coordinates:\n",
      "Upper Left  (-179.9916666,  83.0883445) (179d59'30.00\"W, 83d 5'18.04\"N)\n",
      "Lower Left  (-179.9916666, -55.9116667) (179d59'30.00\"W, 55d54'42.00\"S)\n",
      "Upper Right ( 180.0083622,  83.0883445) (180d 0'30.10\"E, 83d 5'18.04\"N)\n",
      "Lower Right ( 180.0083622, -55.9116667) (180d 0'30.10\"E, 55d54'42.00\"S)\n",
      "Center      (   0.0083478,  13.5883389) (  0d 0'30.05\"E, 13d35'18.02\"N)\n",
      "Band 1 Block=4320x1 Type=Float32, ColorInterp=Gray\n",
      "  NoData Value=0\n"
     ]
    }
   ],
   "source": [
    "!gdalinfo $path'bl_wf_mmyr_area.tif'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "id": "3a0d53e0",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 0.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 1.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 2.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 3.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 4.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 5.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 6.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 7.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 8.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 9.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 10.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 11.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 12.. 13.. 13.. 13.. 13.. 13.. 13.. 13.. 13.. 13.. 13.. 13.. 13.. 13.. 13.. 13.. 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97.. 97.. 97.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 100 - Done\r\n"
     ]
    }
   ],
   "source": [
    "#get the area in india\n",
    "!gdal_calc.py --calc \"A*B\" --format GTiff --type Float32 --NoDataValue 0.0 -A $path'gadm36_IND_0.tif' --A_band 1 -B $path'bl_wf_mmyr_area.tif' --outfile $path'IND_bl_wf_mmyr_area.tif'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "id": "e16c33c0",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Driver: GTiff/GeoTIFF\n",
      "Files: ../../datasets/raw/wf/QA/IND_bl_wf_mmyr_area.tif\n",
      "Size is 4320, 1668\n",
      "Coordinate System is:\n",
      "GEOGCRS[\"WGS 84\",\n",
      "    DATUM[\"World Geodetic System 1984\",\n",
      "        ELLIPSOID[\"WGS 84\",6378137,298.257223563,\n",
      "            LENGTHUNIT[\"metre\",1]]],\n",
      "    PRIMEM[\"Greenwich\",0,\n",
      "        ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "    CS[ellipsoidal,2],\n",
      "        AXIS[\"geodetic latitude (Lat)\",north,\n",
      "            ORDER[1],\n",
      "            ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "        AXIS[\"geodetic longitude (Lon)\",east,\n",
      "            ORDER[2],\n",
      "            ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
      "    ID[\"EPSG\",4326]]\n",
      "Data axis to CRS axis mapping: 2,1\n",
      "Origin = (-179.991666650000013,83.097781811000004)\n",
      "Pixel Size = (0.083333340000000,-0.083333340000000)\n",
      "Metadata:\n",
      "  AREA_OR_POINT=Area\n",
      "Image Structure Metadata:\n",
      "  INTERLEAVE=BAND\n",
      "Corner Coordinates:\n",
      "Upper Left  (-179.9916667,  83.0977818) (179d59'30.00\"W, 83d 5'52.01\"N)\n",
      "Lower Left  (-179.9916667, -55.9022293) (179d59'30.00\"W, 55d54' 8.03\"S)\n",
      "Upper Right ( 180.0083622,  83.0977818) (180d 0'30.10\"E, 83d 5'52.01\"N)\n",
      "Lower Right ( 180.0083622, -55.9022293) (180d 0'30.10\"E, 55d54' 8.03\"S)\n",
      "Center      (   0.0083478,  13.5977763) (  0d 0'30.05\"E, 13d35'51.99\"N)\n",
      "Band 1 Block=4320x1 Type=Float32, ColorInterp=Gray\n",
      "  NoData Value=0\n"
     ]
    }
   ],
   "source": [
    "!gdalinfo $path'IND_bl_wf_mmyr_area.tif'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "id": "0eaf5c66",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "shape: (1668, 4320)\n",
      "noData: 0.0\n",
      "GLOBAL Total sum excluding no data: 304315713454080.0 mm/yr\n",
      "GLOBAL Total sum excluding no data: 304.31571345408 m3/yr\n"
     ]
    }
   ],
   "source": [
    "src_india_area_bl = rio.open(path + \"IND_bl_wf_mmyr_area.tif\")\n",
    "print('shape:',src_india_area_bl.shape)\n",
    "print('noData:',src_india_area_bl.nodata)\n",
    "\n",
    "src_india_area_array_bl = src_india_area_bl.read()\n",
    "#remove nans that appear outside boundary for extent\n",
    "src_india_area_array_nonan_bl = src_india_area_array_bl[~numpy.isnan(src_india_area_array_bl)]\n",
    "\n",
    "print(f'GLOBAL Total sum excluding no data: {src_india_area_array_nonan_bl.sum()} mm/yr')\n",
    "print(f'GLOBAL Total sum excluding no data: {src_india_area_array_nonan_bl.sum()*0.001/1000000000} m3/yr')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "id": "d9f5b962",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "absolute difference: -61\n",
      "relative difference: -0.25102880658436216\n"
     ]
    }
   ],
   "source": [
    "\n",
    "\n",
    "#compute difference\n",
    "value = 243 \n",
    "value_es = round(304.31571345408)\n",
    "\n",
    "difference_abs = value - value_es\n",
    "print(f'absolute difference: {difference_abs}')\n",
    "\n",
    "difference_rel = (value-value_es)/value\n",
    "print(f'relative difference: {difference_rel}')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2651a4dc",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cbc46954",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  }
 },
 "nbformat": 4,
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}