Dados_Era5_precipitação-Copy1-checkpoint.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "654e0692",
   "metadata": {},
   "source": [
    "## Extration using data from Era5 by Angola (Luanda)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ae218fbe",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Importando bibliotecas\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import xarray as xr\n",
    "import proplot as pplt\n",
    "import os\n",
    "import cartopy\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.gridspec import GridSpec\n",
    "%matplotlib inline\n",
    "%config InlineBackend.figure_format='retina'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b76d0dac",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Abrindo o ficheiro netcdf apartir do google Drive na pasta Pymeteo_clima\n",
    "\n",
    "era_1 = xr.open_dataset('ERA5_1964_1975.nc')\n",
    "era_2 = xr.open_dataset('ERA5_1976_1987.nc')\n",
    "era_3 = xr.open_dataset('ERA5_1988_1999.nc')\n",
    "era_4 = xr.open_dataset('ERA5_2000_2011.nc')\n",
    "era_5 = xr.open_dataset('ERA5_2012_2022.nc')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "fb24bcfb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/mnt/e/Ajdata'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pwd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "672424af",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "#1.import as seguintes bibliotecas e defina o caminho para os dados:\n",
    "\n",
    "%matplotlib inline\n",
    "import os\n",
    "import iris\n",
    "import iris.coord_categorisation\n",
    "import iris.quickplot as qplt\n",
    "import iris.plot as iplt\n",
    "from iris.time import PartialDateTime\n",
    "import cartopy.crs as ccrs\n",
    "import cartopy.feature as cfeature\n",
    "import cartopy.feature as cf\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import dask\n",
    "dask.config.set(scheduler=dask.get)\n",
    "import dask.array as da\n",
    "from iris.analysis import Aggregator\n",
    "from iris.experimental.equalise_cubes import equalise_attributes\n",
    "from iris.util import unify_time_units\n",
    "\n",
    "DATADIR = '/mnt/e/Ajdata/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "c5b5c2d2",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0: Total precipitation / (m)           (time: 105192; latitude: 61; longitude: 61)\n",
      "1: Total precipitation / (m)           (time: 105192; latitude: 61; longitude: 61)\n",
      "2: Total precipitation / (m)           (time: 105192; latitude: 61; longitude: 61)\n",
      "3: Total precipitation / (m)           (time: 105192; latitude: 61; longitude: 61)\n",
      "4: Total precipitation / (m)           (time: 96432; latitude: 61; longitude: 61)\n",
      "************************************************************************************************************************\n",
      "************************************************************************************************************************\n",
      "Saved: /mnt/e/Ajdata/ERA5_All.nc\n"
     ]
    }
   ],
   "source": [
    "#2.Leia os dados, concatena e salve.\n",
    "\n",
    "time = iris.Constraint(time=lambda cell: PartialDateTime(year=1964)\n",
    "                            <= cell.point <= PartialDateTime(year=2022))\n",
    "\n",
    "infile = os.path.join(DATADIR, 'ERA5_*.nc')\n",
    "data = iris.load(infile, time)\n",
    "\n",
    "print(data)\n",
    "\n",
    "print('*' * 120)\n",
    "\n",
    "unify_time_units(data)\n",
    "\n",
    "equalise_attributes(data)\n",
    "         \n",
    "cube = data.concatenate_cube()\n",
    "\n",
    "print('*' * 120)\n",
    "\n",
    "outfile = os.path.join(DATADIR, 'ERA5_All.nc')\n",
    "iris.save(cube, outfile)\n",
    "print('Saved: {}'.format(outfile))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "37313a06",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total precipitation / (m)           (time: 517200; latitude: 61; longitude: 61)\n",
      "     Dimension coordinates:\n",
      "          time                           x                 -              -\n",
      "          latitude                       -                 x              -\n",
      "          longitude                      -                 -              x\n",
      "     Attributes:\n",
      "          Conventions: CF-1.7\n"
     ]
    }
   ],
   "source": [
    "dados = iris.load_cube(os.path.join(DATADIR, 'ERA5_All.nc'))\n",
    "\n",
    "print(dados)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1fb26881",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "dialy_prec = xr.open_dataset('ERA5_All.nc')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "46f1147f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/amilcar/anaconda3/envs/pyprecis-environment2/lib/python3.6/site-packages/iris/coords.py:1193: UserWarning: Coordinate 'longitude' is not bounded, guessing contiguous bounds.\n",
      "  'contiguous bounds.'.format(self.name()))\n",
      "/home/amilcar/anaconda3/envs/pyprecis-environment2/lib/python3.6/site-packages/iris/coords.py:1193: UserWarning: Coordinate 'latitude' is not bounded, guessing contiguous bounds.\n",
      "  'contiguous bounds.'.format(self.name()))\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7fef13b1e048>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 400x400 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 400,
       "width": 400
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "qplt.pcolormesh(dados[0]*1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6367e6c8",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       ".xr-wrap {\n",
       "  display: block;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (latitude: 61, longitude: 61, time: 517200)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1964-01-01 ... 2022-12-31T23:00:00\n",
       "  * latitude   (latitude) float32 -4.0 -4.25 -4.5 -4.75 ... -18.5 -18.75 -19.0\n",
       "  * longitude  (longitude) float32 10.0 10.25 10.5 10.75 ... 24.5 24.75 25.0\n",
       "Data variables:\n",
       "    tp         (time, latitude, longitude) float64 ...\n",
       "Attributes:\n",
       "    Conventions:  CF-1.7</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-39b47297-a727-4b4f-9e19-b187255fae72' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-39b47297-a727-4b4f-9e19-b187255fae72' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>latitude</span>: 61</li><li><span class='xr-has-index'>longitude</span>: 61</li><li><span class='xr-has-index'>time</span>: 517200</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-eed82ac9-3f48-4fd4-a528-72117850907f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-eed82ac9-3f48-4fd4-a528-72117850907f' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1964-01-01 ... 2022-12-31T23:00:00</div><input id='attrs-a0f7d558-28ae-4202-a00b-ccf8c5d82f13' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a0f7d558-28ae-4202-a00b-ccf8c5d82f13' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e80fa21-4ce0-41da-a1a8-0a3552c0abb2' class='xr-var-data-in' type='checkbox'><label for='data-5e80fa21-4ce0-41da-a1a8-0a3552c0abb2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1964-01-01T00:00:00.000000000&#x27;, &#x27;1964-01-01T01:00:00.000000000&#x27;,\n",
       "       &#x27;1964-01-01T02:00:00.000000000&#x27;, ..., &#x27;2022-12-31T21:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-31T22:00:00.000000000&#x27;, &#x27;2022-12-31T23:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-4.0 -4.25 -4.5 ... -18.75 -19.0</div><input id='attrs-45ddd574-9473-4187-a95e-1df0a5825ff6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-45ddd574-9473-4187-a95e-1df0a5825ff6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f487bc3-e4d4-4a19-bf80-928de851394e' class='xr-var-data-in' type='checkbox'><label for='data-0f487bc3-e4d4-4a19-bf80-928de851394e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([ -4.  ,  -4.25,  -4.5 ,  -4.75,  -5.  ,  -5.25,  -5.5 ,  -5.75,  -6.  ,\n",
       "        -6.25,  -6.5 ,  -6.75,  -7.  ,  -7.25,  -7.5 ,  -7.75,  -8.  ,  -8.25,\n",
       "        -8.5 ,  -8.75,  -9.  ,  -9.25,  -9.5 ,  -9.75, -10.  , -10.25, -10.5 ,\n",
       "       -10.75, -11.  , -11.25, -11.5 , -11.75, -12.  , -12.25, -12.5 , -12.75,\n",
       "       -13.  , -13.25, -13.5 , -13.75, -14.  , -14.25, -14.5 , -14.75, -15.  ,\n",
       "       -15.25, -15.5 , -15.75, -16.  , -16.25, -16.5 , -16.75, -17.  , -17.25,\n",
       "       -17.5 , -17.75, -18.  , -18.25, -18.5 , -18.75, -19.  ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>10.0 10.25 10.5 ... 24.5 24.75 25.0</div><input id='attrs-ffd84a2b-a85b-4bcd-a6f6-00df812c3de1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ffd84a2b-a85b-4bcd-a6f6-00df812c3de1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d999bec-62af-4bd0-b8cb-79e27fa11814' class='xr-var-data-in' type='checkbox'><label for='data-5d999bec-62af-4bd0-b8cb-79e27fa11814' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([10.  , 10.25, 10.5 , 10.75, 11.  , 11.25, 11.5 , 11.75, 12.  , 12.25,\n",
       "       12.5 , 12.75, 13.  , 13.25, 13.5 , 13.75, 14.  , 14.25, 14.5 , 14.75,\n",
       "       15.  , 15.25, 15.5 , 15.75, 16.  , 16.25, 16.5 , 16.75, 17.  , 17.25,\n",
       "       17.5 , 17.75, 18.  , 18.25, 18.5 , 18.75, 19.  , 19.25, 19.5 , 19.75,\n",
       "       20.  , 20.25, 20.5 , 20.75, 21.  , 21.25, 21.5 , 21.75, 22.  , 22.25,\n",
       "       22.5 , 22.75, 23.  , 23.25, 23.5 , 23.75, 24.  , 24.25, 24.5 , 24.75,\n",
       "       25.  ], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c1772415-ada2-4dcb-ad33-c326b498a3f9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c1772415-ada2-4dcb-ad33-c326b498a3f9' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>tp</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b4cc03b9-6981-417a-8b47-45ebe5d38c54' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b4cc03b9-6981-417a-8b47-45ebe5d38c54' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fea36679-0fef-4912-938c-cb1022f12787' class='xr-var-data-in' type='checkbox'><label for='data-fea36679-0fef-4912-938c-cb1022f12787' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Total precipitation</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>[1924501200 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a9a7d36a-723b-4d65-987c-c9d66d8b7105' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a9a7d36a-723b-4d65-987c-c9d66d8b7105' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (latitude: 61, longitude: 61, time: 517200)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1964-01-01 ... 2022-12-31T23:00:00\n",
       "  * latitude   (latitude) float32 -4.0 -4.25 -4.5 -4.75 ... -18.5 -18.75 -19.0\n",
       "  * longitude  (longitude) float32 10.0 10.25 10.5 10.75 ... 24.5 24.75 25.0\n",
       "Data variables:\n",
       "    tp         (time, latitude, longitude) float64 ...\n",
       "Attributes:\n",
       "    Conventions:  CF-1.7"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Verificado os dados netcdf\n",
    "dialy_prec"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "4c4eddd6",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;tp&#x27; (time: 517200, latitude: 61, longitude: 61)&gt;\n",
       "[1924501200 values with dtype=float64]\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1964-01-01 ... 2022-12-31T23:00:00\n",
       "  * latitude   (latitude) float32 -4.0 -4.25 -4.5 -4.75 ... -18.5 -18.75 -19.0\n",
       "  * longitude  (longitude) float32 10.0 10.25 10.5 10.75 ... 24.5 24.75 25.0\n",
       "Attributes:\n",
       "    long_name:  Total precipitation\n",
       "    units:      m</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'tp'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 517200</li><li><span class='xr-has-index'>latitude</span>: 61</li><li><span class='xr-has-index'>longitude</span>: 61</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-e508b3b2-d0d8-4b7f-9baf-03e51664b723' class='xr-array-in' type='checkbox' checked><label for='section-e508b3b2-d0d8-4b7f-9baf-03e51664b723' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[1924501200 values with dtype=float64]</pre></div></div></li><li class='xr-section-item'><input id='section-dde41d3f-3a3b-44ad-b214-78117157cd92' class='xr-section-summary-in' type='checkbox'  checked><label for='section-dde41d3f-3a3b-44ad-b214-78117157cd92' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1964-01-01 ... 2022-12-31T23:00:00</div><input id='attrs-2fdb70a6-a2ae-4e6d-8029-bc92d85acb3c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2fdb70a6-a2ae-4e6d-8029-bc92d85acb3c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-82b49a28-9ed0-4d52-94dc-2ca07ce483e4' class='xr-var-data-in' type='checkbox'><label for='data-82b49a28-9ed0-4d52-94dc-2ca07ce483e4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1964-01-01T00:00:00.000000000&#x27;, &#x27;1964-01-01T01:00:00.000000000&#x27;,\n",
       "       &#x27;1964-01-01T02:00:00.000000000&#x27;, ..., &#x27;2022-12-31T21:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-31T22:00:00.000000000&#x27;, &#x27;2022-12-31T23:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-4.0 -4.25 -4.5 ... -18.75 -19.0</div><input id='attrs-ff582924-cda3-49dd-9812-16bd2afcf349' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ff582924-cda3-49dd-9812-16bd2afcf349' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-072a1410-caf3-4900-8255-74122110b1fd' class='xr-var-data-in' type='checkbox'><label for='data-072a1410-caf3-4900-8255-74122110b1fd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([ -4.  ,  -4.25,  -4.5 ,  -4.75,  -5.  ,  -5.25,  -5.5 ,  -5.75,  -6.  ,\n",
       "        -6.25,  -6.5 ,  -6.75,  -7.  ,  -7.25,  -7.5 ,  -7.75,  -8.  ,  -8.25,\n",
       "        -8.5 ,  -8.75,  -9.  ,  -9.25,  -9.5 ,  -9.75, -10.  , -10.25, -10.5 ,\n",
       "       -10.75, -11.  , -11.25, -11.5 , -11.75, -12.  , -12.25, -12.5 , -12.75,\n",
       "       -13.  , -13.25, -13.5 , -13.75, -14.  , -14.25, -14.5 , -14.75, -15.  ,\n",
       "       -15.25, -15.5 , -15.75, -16.  , -16.25, -16.5 , -16.75, -17.  , -17.25,\n",
       "       -17.5 , -17.75, -18.  , -18.25, -18.5 , -18.75, -19.  ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>10.0 10.25 10.5 ... 24.5 24.75 25.0</div><input id='attrs-e6ec584b-19ed-4c9c-a655-668963ab502e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e6ec584b-19ed-4c9c-a655-668963ab502e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1e3ddb5d-e6fa-432e-ac7c-00e9cf699256' class='xr-var-data-in' type='checkbox'><label for='data-1e3ddb5d-e6fa-432e-ac7c-00e9cf699256' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([10.  , 10.25, 10.5 , 10.75, 11.  , 11.25, 11.5 , 11.75, 12.  , 12.25,\n",
       "       12.5 , 12.75, 13.  , 13.25, 13.5 , 13.75, 14.  , 14.25, 14.5 , 14.75,\n",
       "       15.  , 15.25, 15.5 , 15.75, 16.  , 16.25, 16.5 , 16.75, 17.  , 17.25,\n",
       "       17.5 , 17.75, 18.  , 18.25, 18.5 , 18.75, 19.  , 19.25, 19.5 , 19.75,\n",
       "       20.  , 20.25, 20.5 , 20.75, 21.  , 21.25, 21.5 , 21.75, 22.  , 22.25,\n",
       "       22.5 , 22.75, 23.  , 23.25, 23.5 , 23.75, 24.  , 24.25, 24.5 , 24.75,\n",
       "       25.  ], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1cc410fd-2338-4568-a0aa-b114f716aafb' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1cc410fd-2338-4568-a0aa-b114f716aafb' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Total precipitation</dd><dt><span>units :</span></dt><dd>m</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'tp' (time: 517200, latitude: 61, longitude: 61)>\n",
       "[1924501200 values with dtype=float64]\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1964-01-01 ... 2022-12-31T23:00:00\n",
       "  * latitude   (latitude) float32 -4.0 -4.25 -4.5 -4.75 ... -18.5 -18.75 -19.0\n",
       "  * longitude  (longitude) float32 10.0 10.25 10.5 10.75 ... 24.5 24.75 25.0\n",
       "Attributes:\n",
       "    long_name:  Total precipitation\n",
       "    units:      m"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Definido a variavel'tp'(precipitacão total).\n",
    "\n",
    "dialy_prec['tp']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "99e6150c",
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (latitude: 9, longitude: 10, time: 262992)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1991-01-01 ... 2020-12-31T23:00:00\n",
       "  * latitude   (latitude) float32 -8.5 -8.75 -9.0 -9.25 ... -10.0 -10.25 -10.5\n",
       "  * longitude  (longitude) float32 12.5 12.75 13.0 13.25 ... 14.25 14.5 14.75\n",
       "Data variables:\n",
       "    tp         (time, latitude, longitude) float64 ...\n",
       "Attributes:\n",
       "    Conventions:  CF-1.7</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-01f60966-6ba8-4384-8516-7491efa90d47' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-01f60966-6ba8-4384-8516-7491efa90d47' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>latitude</span>: 9</li><li><span class='xr-has-index'>longitude</span>: 10</li><li><span class='xr-has-index'>time</span>: 262992</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-17b20157-46e9-4c39-a448-e54fa849d486' class='xr-section-summary-in' type='checkbox'  checked><label for='section-17b20157-46e9-4c39-a448-e54fa849d486' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1991-01-01 ... 2020-12-31T23:00:00</div><input id='attrs-039a272e-3884-4b4e-981f-d5b9a4be255d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-039a272e-3884-4b4e-981f-d5b9a4be255d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e796ced-c2c5-4fbc-b501-8f1fa5ce23a9' class='xr-var-data-in' type='checkbox'><label for='data-3e796ced-c2c5-4fbc-b501-8f1fa5ce23a9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1991-01-01T00:00:00.000000000&#x27;, &#x27;1991-01-01T01:00:00.000000000&#x27;,\n",
       "       &#x27;1991-01-01T02:00:00.000000000&#x27;, ..., &#x27;2020-12-31T21:00:00.000000000&#x27;,\n",
       "       &#x27;2020-12-31T22:00:00.000000000&#x27;, &#x27;2020-12-31T23:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-8.5 -8.75 -9.0 ... -10.25 -10.5</div><input id='attrs-c56ef26d-0100-4f20-aaed-38b92994221c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c56ef26d-0100-4f20-aaed-38b92994221c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f5545e7-c66d-46bf-8af5-323da58528c8' class='xr-var-data-in' type='checkbox'><label for='data-9f5545e7-c66d-46bf-8af5-323da58528c8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([ -8.5 ,  -8.75,  -9.  ,  -9.25,  -9.5 ,  -9.75, -10.  , -10.25, -10.5 ],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.5 12.75 13.0 ... 14.5 14.75</div><input id='attrs-c0247543-dd0d-43ef-9b43-8d0c05a61d0b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c0247543-dd0d-43ef-9b43-8d0c05a61d0b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-de6481d8-f755-4446-921f-c377fc591369' class='xr-var-data-in' type='checkbox'><label for='data-de6481d8-f755-4446-921f-c377fc591369' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([12.5 , 12.75, 13.  , 13.25, 13.5 , 13.75, 14.  , 14.25, 14.5 , 14.75],\n",
       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-df3b2d0a-8511-498a-8869-9a1272134790' class='xr-section-summary-in' type='checkbox'  checked><label for='section-df3b2d0a-8511-498a-8869-9a1272134790' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>tp</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a1f7799e-c0b5-413d-9105-8ba7ae9b670d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a1f7799e-c0b5-413d-9105-8ba7ae9b670d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-36fb64e9-b935-4f8b-88ee-c7ab53283fc3' class='xr-var-data-in' type='checkbox'><label for='data-36fb64e9-b935-4f8b-88ee-c7ab53283fc3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Total precipitation</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>[23669280 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a33ddbf5-24d9-43e6-a845-5158987bfc94' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a33ddbf5-24d9-43e6-a845-5158987bfc94' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (latitude: 9, longitude: 10, time: 262992)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1991-01-01 ... 2020-12-31T23:00:00\n",
       "  * latitude   (latitude) float32 -8.5 -8.75 -9.0 -9.25 ... -10.0 -10.25 -10.5\n",
       "  * longitude  (longitude) float32 12.5 12.75 13.0 13.25 ... 14.25 14.5 14.75\n",
       "Data variables:\n",
       "    tp         (time, latitude, longitude) float64 ...\n",
       "Attributes:\n",
       "    Conventions:  CF-1.7"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#ANGOLA:Extrair dados de precipitação da província de Luanda na sua coordenada.\n",
    "ds_lu = dialy_prec.sel(latitude=slice(-8.5, -10.5), longitude=slice(12.5, 14.75), time=slice('1991-01-01', '2020-12-31'))\n",
    "ds_lu"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "1033c334",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Passar os dados de hora em hora para mês (observação fazer isto quando é precipitação).\n",
    "\n",
    "lu_mensal = ds_lu.resample(time='1M').sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a7c9163d",
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (latitude: 9, longitude: 10, time: 360)\n",
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       "  * longitude  (longitude) float32 12.5 12.75 13.0 13.25 ... 14.25 14.5 14.75\n",
       "Data variables:\n",
       "    tp         (time, latitude, longitude) float64 0.009411 0.01022 ... 0.08456</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-32a96412-2526-45db-8329-5f278d6b2d96' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-32a96412-2526-45db-8329-5f278d6b2d96' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>latitude</span>: 9</li><li><span class='xr-has-index'>longitude</span>: 10</li><li><span class='xr-has-index'>time</span>: 360</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-80a46a68-27cd-46b0-8503-4d7b9bf7efe6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-80a46a68-27cd-46b0-8503-4d7b9bf7efe6' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1991-01-31 ... 2020-12-31</div><input id='attrs-a044e4e7-8155-44d8-ac5a-85938a489d5d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a044e4e7-8155-44d8-ac5a-85938a489d5d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-99e5cc2a-8566-415c-8fa0-07d9358b1086' class='xr-var-data-in' type='checkbox'><label for='data-99e5cc2a-8566-415c-8fa0-07d9358b1086' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1991-01-31T00:00:00.000000000&#x27;, &#x27;1991-02-28T00:00:00.000000000&#x27;,\n",
       "       &#x27;1991-03-31T00:00:00.000000000&#x27;, ..., &#x27;2020-10-31T00:00:00.000000000&#x27;,\n",
       "       &#x27;2020-11-30T00:00:00.000000000&#x27;, &#x27;2020-12-31T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-8.5 -8.75 -9.0 ... -10.25 -10.5</div><input id='attrs-cc80d94b-c04c-4beb-a24b-cf94eb7b2bca' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc80d94b-c04c-4beb-a24b-cf94eb7b2bca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b11fe69e-65a3-49e6-919d-570935da023b' class='xr-var-data-in' type='checkbox'><label for='data-b11fe69e-65a3-49e6-919d-570935da023b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([ -8.5 ,  -8.75,  -9.  ,  -9.25,  -9.5 ,  -9.75, -10.  , -10.25, -10.5 ],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.5 12.75 13.0 ... 14.5 14.75</div><input id='attrs-b1f48ee7-942c-4476-a5eb-ab5d2cda1c94' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b1f48ee7-942c-4476-a5eb-ab5d2cda1c94' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-62b3f3a8-86d0-474b-9164-2cf133fb9b38' class='xr-var-data-in' type='checkbox'><label for='data-62b3f3a8-86d0-474b-9164-2cf133fb9b38' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([12.5 , 12.75, 13.  , 13.25, 13.5 , 13.75, 14.  , 14.25, 14.5 , 14.75],\n",
       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0db23422-a436-425f-acf9-4c814d60a124' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0db23422-a436-425f-acf9-4c814d60a124' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>tp</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.009411 0.01022 ... 0.08456</div><input id='attrs-59bc1559-537e-4eeb-a33f-7f36606478c3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-59bc1559-537e-4eeb-a33f-7f36606478c3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ea288027-7177-4b7e-aa1c-ec6c9e925678' class='xr-var-data-in' type='checkbox'><label for='data-ea288027-7177-4b7e-aa1c-ec6c9e925678' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[0.00941056, 0.01022144, 0.00908511, ..., 0.04593511,\n",
       "         0.07629699, 0.09546657],\n",
       "        [0.00755869, 0.00832355, 0.00735159, ..., 0.03500251,\n",
       "         0.04063482, 0.05787911],\n",
       "        [0.0068037 , 0.00764855, 0.00867529, ..., 0.03287779,\n",
       "         0.03844216, 0.04639753],\n",
       "        ...,\n",
       "        [0.00335966, 0.00339254, 0.00372456, ..., 0.02346833,\n",
       "         0.03763457, 0.06526906],\n",
       "        [0.00445106, 0.00520167, 0.00538247, ..., 0.01919478,\n",
       "         0.04363726, 0.08314562],\n",
       "        [0.00387906, 0.00499237, 0.0061813 , ..., 0.0254999 ,\n",
       "         0.05493147, 0.11001853]],\n",
       "\n",
       "       [[0.00558738, 0.00682233, 0.00709956, ..., 0.02699783,\n",
       "         0.03798084, 0.0543518 ],\n",
       "        [0.00482253, 0.00456064, 0.00398754, ..., 0.02336751,\n",
       "         0.02792486, 0.04292719],\n",
       "        [0.00409384, 0.00380126, 0.00421218, ..., 0.02498598,\n",
       "         0.0291105 , 0.0423278 ],\n",
       "...\n",
       "        [0.00904943, 0.01231194, 0.0153229 , ..., 0.03785032,\n",
       "         0.05567089, 0.10738129],\n",
       "        [0.01033202, 0.01209987, 0.01445871, ..., 0.04538536,\n",
       "         0.08589001, 0.15208078],\n",
       "        [0.00734526, 0.00919145, 0.01155538, ..., 0.07168093,\n",
       "         0.13175554, 0.20407776]],\n",
       "\n",
       "       [[0.0100671 , 0.01016835, 0.01063706, ..., 0.10002266,\n",
       "         0.11356242, 0.12258956],\n",
       "        [0.00911694, 0.00904115, 0.00940288, ..., 0.08811384,\n",
       "         0.10050474, 0.10860211],\n",
       "        [0.00817824, 0.00813876, 0.01319778, ..., 0.08906272,\n",
       "         0.09988192, 0.11376939],\n",
       "        ...,\n",
       "        [0.00933665, 0.01418615, 0.01994441, ..., 0.03976274,\n",
       "         0.04261257, 0.06195072],\n",
       "        [0.00715548, 0.01013205, 0.01505479, ..., 0.03750706,\n",
       "         0.04484532, 0.06798665],\n",
       "        [0.0058678 , 0.00734781, 0.01232786, ..., 0.04405755,\n",
       "         0.06127122, 0.08455902]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a2613724-22c6-4f18-a5b3-1b627d353e5b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a2613724-22c6-4f18-a5b3-1b627d353e5b' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (latitude: 9, longitude: 10, time: 360)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1991-01-31 1991-02-28 ... 2020-12-31\n",
       "  * latitude   (latitude) float32 -8.5 -8.75 -9.0 -9.25 ... -10.0 -10.25 -10.5\n",
       "  * longitude  (longitude) float32 12.5 12.75 13.0 13.25 ... 14.25 14.5 14.75\n",
       "Data variables:\n",
       "    tp         (time, latitude, longitude) float64 0.009411 0.01022 ... 0.08456"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lu_mensal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "aac83c19",
   "metadata": {},
   "outputs": [
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       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;tp&#x27; (time: 360, latitude: 9, longitude: 10)&gt;\n",
       "array([[[  9.41056099,  10.22143839,   9.08511425, ...,  45.93510907,\n",
       "          76.2969889 ,  95.46656901],\n",
       "        [  7.55869233,   8.32354696,   7.35158986, ...,  35.00250928,\n",
       "          40.63481989,  57.87911406],\n",
       "        [  6.80369972,   7.64854631,   8.67529243, ...,  32.87779133,\n",
       "          38.44216356,  46.39752835],\n",
       "        ...,\n",
       "        [  3.35966232,   3.39253573,   3.72455715, ...,  23.46832612,\n",
       "          37.6345735 ,  65.26905622],\n",
       "        [  4.45105947,   5.20166896,   5.3824727 , ...,  19.19478305,\n",
       "          43.63725784,  83.14561561],\n",
       "        [  3.87906217,   4.99237493,   6.18129652, ...,  25.49990275,\n",
       "          54.93146512, 110.01853104]],\n",
       "\n",
       "       [[  5.58738362,   6.82232798,   7.09956039, ...,  26.99783438,\n",
       "          37.98084007,  54.35179736],\n",
       "        [  4.82252898,   4.5606375 ,   3.98754442, ...,  23.36751434,\n",
       "          27.9248645 ,  42.92719222],\n",
       "        [  4.0938351 ,   3.80126177,   4.21217937, ...,  24.9859818 ,\n",
       "          29.11049875,  42.32780041],\n",
       "...\n",
       "        [  9.04943266,  12.311941  ,  15.32289931, ...,  37.85031879,\n",
       "          55.67088699, 107.38129392],\n",
       "        [ 10.33201938,  12.09987477,  14.45871352, ...,  45.3853566 ,\n",
       "          85.89000582, 152.08077867],\n",
       "        [  7.34526082,   9.19144698,  11.55538041, ...,  71.68093182,\n",
       "         131.75553639, 204.07776158]],\n",
       "\n",
       "       [[ 10.06709581,  10.16835266,  10.6370636 , ..., 100.02265955,\n",
       "         113.56241942, 122.58956284],\n",
       "        [  9.11693722,   9.0411538 ,   9.40287637, ...,  88.11383543,\n",
       "         100.50474404, 108.6021076 ],\n",
       "        [  8.17824167,   8.13875787,  13.1977792 , ...,  89.06272035,\n",
       "          99.8819189 , 113.76939096],\n",
       "        ...,\n",
       "        [  9.33664548,  14.18614792,  19.94441464, ...,  39.76273584,\n",
       "          42.61257477,  61.950722  ],\n",
       "        [  7.15548384,  10.13205303,  15.05479156, ...,  37.50706445,\n",
       "          44.84532008,  67.986649  ],\n",
       "        [  5.86780243,   7.34780816,  12.32786189, ...,  44.05755455,\n",
       "          61.2712185 ,  84.55901959]]])\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1991-01-31 1991-02-28 ... 2020-12-31\n",
       "  * latitude   (latitude) float32 -8.5 -8.75 -9.0 -9.25 ... -10.0 -10.25 -10.5\n",
       "  * longitude  (longitude) float32 12.5 12.75 13.0 13.25 ... 14.25 14.5 14.75</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'tp'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 360</li><li><span class='xr-has-index'>latitude</span>: 9</li><li><span class='xr-has-index'>longitude</span>: 10</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-509ad0d3-94f4-474e-b939-199ca09296ec' class='xr-array-in' type='checkbox' checked><label for='section-509ad0d3-94f4-474e-b939-199ca09296ec' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>9.411 10.22 9.085 7.513 12.64 17.92 ... 27.58 35.44 44.06 61.27 84.56</span></div><div class='xr-array-data'><pre>array([[[  9.41056099,  10.22143839,   9.08511425, ...,  45.93510907,\n",
       "          76.2969889 ,  95.46656901],\n",
       "        [  7.55869233,   8.32354696,   7.35158986, ...,  35.00250928,\n",
       "          40.63481989,  57.87911406],\n",
       "        [  6.80369972,   7.64854631,   8.67529243, ...,  32.87779133,\n",
       "          38.44216356,  46.39752835],\n",
       "        ...,\n",
       "        [  3.35966232,   3.39253573,   3.72455715, ...,  23.46832612,\n",
       "          37.6345735 ,  65.26905622],\n",
       "        [  4.45105947,   5.20166896,   5.3824727 , ...,  19.19478305,\n",
       "          43.63725784,  83.14561561],\n",
       "        [  3.87906217,   4.99237493,   6.18129652, ...,  25.49990275,\n",
       "          54.93146512, 110.01853104]],\n",
       "\n",
       "       [[  5.58738362,   6.82232798,   7.09956039, ...,  26.99783438,\n",
       "          37.98084007,  54.35179736],\n",
       "        [  4.82252898,   4.5606375 ,   3.98754442, ...,  23.36751434,\n",
       "          27.9248645 ,  42.92719222],\n",
       "        [  4.0938351 ,   3.80126177,   4.21217937, ...,  24.9859818 ,\n",
       "          29.11049875,  42.32780041],\n",
       "...\n",
       "        [  9.04943266,  12.311941  ,  15.32289931, ...,  37.85031879,\n",
       "          55.67088699, 107.38129392],\n",
       "        [ 10.33201938,  12.09987477,  14.45871352, ...,  45.3853566 ,\n",
       "          85.89000582, 152.08077867],\n",
       "        [  7.34526082,   9.19144698,  11.55538041, ...,  71.68093182,\n",
       "         131.75553639, 204.07776158]],\n",
       "\n",
       "       [[ 10.06709581,  10.16835266,  10.6370636 , ..., 100.02265955,\n",
       "         113.56241942, 122.58956284],\n",
       "        [  9.11693722,   9.0411538 ,   9.40287637, ...,  88.11383543,\n",
       "         100.50474404, 108.6021076 ],\n",
       "        [  8.17824167,   8.13875787,  13.1977792 , ...,  89.06272035,\n",
       "          99.8819189 , 113.76939096],\n",
       "        ...,\n",
       "        [  9.33664548,  14.18614792,  19.94441464, ...,  39.76273584,\n",
       "          42.61257477,  61.950722  ],\n",
       "        [  7.15548384,  10.13205303,  15.05479156, ...,  37.50706445,\n",
       "          44.84532008,  67.986649  ],\n",
       "        [  5.86780243,   7.34780816,  12.32786189, ...,  44.05755455,\n",
       "          61.2712185 ,  84.55901959]]])</pre></div></div></li><li class='xr-section-item'><input id='section-0c9ee73b-28ef-4524-8831-3ff1a3582e34' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0c9ee73b-28ef-4524-8831-3ff1a3582e34' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1991-01-31 ... 2020-12-31</div><input id='attrs-d0dc95e2-ed81-47fa-909d-884b7234d4ef' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d0dc95e2-ed81-47fa-909d-884b7234d4ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6f851a7e-2d02-49dd-8c3e-c897da88138b' class='xr-var-data-in' type='checkbox'><label for='data-6f851a7e-2d02-49dd-8c3e-c897da88138b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1991-01-31T00:00:00.000000000&#x27;, &#x27;1991-02-28T00:00:00.000000000&#x27;,\n",
       "       &#x27;1991-03-31T00:00:00.000000000&#x27;, ..., &#x27;2020-10-31T00:00:00.000000000&#x27;,\n",
       "       &#x27;2020-11-30T00:00:00.000000000&#x27;, &#x27;2020-12-31T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-8.5 -8.75 -9.0 ... -10.25 -10.5</div><input id='attrs-148c5e82-7ab1-47e2-b988-edef375d5b64' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-148c5e82-7ab1-47e2-b988-edef375d5b64' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3bb4ee6b-af9a-47a9-b3a2-d029c4be3e02' class='xr-var-data-in' type='checkbox'><label for='data-3bb4ee6b-af9a-47a9-b3a2-d029c4be3e02' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([ -8.5 ,  -8.75,  -9.  ,  -9.25,  -9.5 ,  -9.75, -10.  , -10.25, -10.5 ],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.5 12.75 13.0 ... 14.5 14.75</div><input id='attrs-32a20edd-e1b1-4625-b902-ad7760d562b5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-32a20edd-e1b1-4625-b902-ad7760d562b5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-592e2ed9-db6a-4d07-bbc8-80ff8b922c8e' class='xr-var-data-in' type='checkbox'><label for='data-592e2ed9-db6a-4d07-bbc8-80ff8b922c8e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([12.5 , 12.75, 13.  , 13.25, 13.5 , 13.75, 14.  , 14.25, 14.5 , 14.75],\n",
       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-29e7ee8f-bea4-4e8a-b666-6ffdd1f0d91e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-29e7ee8f-bea4-4e8a-b666-6ffdd1f0d91e' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'tp' (time: 360, latitude: 9, longitude: 10)>\n",
       "array([[[  9.41056099,  10.22143839,   9.08511425, ...,  45.93510907,\n",
       "          76.2969889 ,  95.46656901],\n",
       "        [  7.55869233,   8.32354696,   7.35158986, ...,  35.00250928,\n",
       "          40.63481989,  57.87911406],\n",
       "        [  6.80369972,   7.64854631,   8.67529243, ...,  32.87779133,\n",
       "          38.44216356,  46.39752835],\n",
       "        ...,\n",
       "        [  3.35966232,   3.39253573,   3.72455715, ...,  23.46832612,\n",
       "          37.6345735 ,  65.26905622],\n",
       "        [  4.45105947,   5.20166896,   5.3824727 , ...,  19.19478305,\n",
       "          43.63725784,  83.14561561],\n",
       "        [  3.87906217,   4.99237493,   6.18129652, ...,  25.49990275,\n",
       "          54.93146512, 110.01853104]],\n",
       "\n",
       "       [[  5.58738362,   6.82232798,   7.09956039, ...,  26.99783438,\n",
       "          37.98084007,  54.35179736],\n",
       "        [  4.82252898,   4.5606375 ,   3.98754442, ...,  23.36751434,\n",
       "          27.9248645 ,  42.92719222],\n",
       "        [  4.0938351 ,   3.80126177,   4.21217937, ...,  24.9859818 ,\n",
       "          29.11049875,  42.32780041],\n",
       "...\n",
       "        [  9.04943266,  12.311941  ,  15.32289931, ...,  37.85031879,\n",
       "          55.67088699, 107.38129392],\n",
       "        [ 10.33201938,  12.09987477,  14.45871352, ...,  45.3853566 ,\n",
       "          85.89000582, 152.08077867],\n",
       "        [  7.34526082,   9.19144698,  11.55538041, ...,  71.68093182,\n",
       "         131.75553639, 204.07776158]],\n",
       "\n",
       "       [[ 10.06709581,  10.16835266,  10.6370636 , ..., 100.02265955,\n",
       "         113.56241942, 122.58956284],\n",
       "        [  9.11693722,   9.0411538 ,   9.40287637, ...,  88.11383543,\n",
       "         100.50474404, 108.6021076 ],\n",
       "        [  8.17824167,   8.13875787,  13.1977792 , ...,  89.06272035,\n",
       "          99.8819189 , 113.76939096],\n",
       "        ...,\n",
       "        [  9.33664548,  14.18614792,  19.94441464, ...,  39.76273584,\n",
       "          42.61257477,  61.950722  ],\n",
       "        [  7.15548384,  10.13205303,  15.05479156, ...,  37.50706445,\n",
       "          44.84532008,  67.986649  ],\n",
       "        [  5.86780243,   7.34780816,  12.32786189, ...,  44.05755455,\n",
       "          61.2712185 ,  84.55901959]]])\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1991-01-31 1991-02-28 ... 2020-12-31\n",
       "  * latitude   (latitude) float32 -8.5 -8.75 -9.0 -9.25 ... -10.0 -10.25 -10.5\n",
       "  * longitude  (longitude) float32 12.5 12.75 13.0 13.25 ... 14.25 14.5 14.75"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##Fazendo a conversão metros dados mensais em mm.\n",
    "\n",
    "era_c = lu_mensal['tp']*1000\n",
    "era_c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "42ccdfa3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1991-01-31 1991-02-28 ... 2020-12-31\n",
       "  * latitude   (latitude) float32 -8.5 -8.75 -9.0 -9.25 ... -10.0 -10.25 -10.5\n",
       "  * longitude  (longitude) float32 12.5 12.75 13.0 13.25 ... 14.25 14.5 14.75"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Visualizando as coordenadas\n",
    "era_c.coords"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "2764c435",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;latitude&#x27; (latitude: 9)&gt;\n",
       "array([ -8.5 ,  -8.75,  -9.  ,  -9.25,  -9.5 ,  -9.75, -10.  , -10.25, -10.5 ],\n",
       "      dtype=float32)\n",
       "Coordinates:\n",
       "  * latitude  (latitude) float32 -8.5 -8.75 -9.0 -9.25 ... -10.0 -10.25 -10.5\n",
       "Attributes:\n",
       "    axis:           Y\n",
       "    units:          degrees_north\n",
       "    standard_name:  latitude\n",
       "    long_name:      latitude</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'latitude'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>latitude</span>: 9</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-682d9548-e95c-4747-b609-8eefbbafbf1d' class='xr-array-in' type='checkbox' checked><label for='section-682d9548-e95c-4747-b609-8eefbbafbf1d' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>-8.5 -8.75 -9.0 -9.25 -9.5 -9.75 -10.0 -10.25 -10.5</span></div><div class='xr-array-data'><pre>array([ -8.5 ,  -8.75,  -9.  ,  -9.25,  -9.5 ,  -9.75, -10.  , -10.25, -10.5 ],\n",
       "      dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-83ed63b4-60c7-41a6-9e11-095074512d4a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-83ed63b4-60c7-41a6-9e11-095074512d4a' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-8.5 -8.75 -9.0 ... -10.25 -10.5</div><input id='attrs-cadd5b5e-6d04-4cf0-ba6b-92650d05b569' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cadd5b5e-6d04-4cf0-ba6b-92650d05b569' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e0d27895-f34d-48c1-b668-48eff8b9faa9' class='xr-var-data-in' type='checkbox'><label for='data-e0d27895-f34d-48c1-b668-48eff8b9faa9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([ -8.5 ,  -8.75,  -9.  ,  -9.25,  -9.5 ,  -9.75, -10.  , -10.25, -10.5 ],\n",
       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-900e7d37-f51f-4e99-aa29-286910b4cc54' class='xr-section-summary-in' type='checkbox'  checked><label for='section-900e7d37-f51f-4e99-aa29-286910b4cc54' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'latitude' (latitude: 9)>\n",
       "array([ -8.5 ,  -8.75,  -9.  ,  -9.25,  -9.5 ,  -9.75, -10.  , -10.25, -10.5 ],\n",
       "      dtype=float32)\n",
       "Coordinates:\n",
       "  * latitude  (latitude) float32 -8.5 -8.75 -9.0 -9.25 ... -10.0 -10.25 -10.5\n",
       "Attributes:\n",
       "    axis:           Y\n",
       "    units:          degrees_north\n",
       "    standard_name:  latitude\n",
       "    long_name:      latitude"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Extraindo a coordenada desejada\n",
    "\n",
    "era_c.latitude"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "7b82b3ef",
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       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
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       "\n",
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       "  margin-left: 2px;\n",
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       "\n",
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       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-sections {\n",
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       ".xr-section-item input {\n",
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       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
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       "\n",
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       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
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       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
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       "  padding-left: 0.5em;\n",
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       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-section-summary-in + label:before {\n",
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       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
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       "  padding: 0;\n",
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       ".xr-dim-list li:not(:last-child):after {\n",
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       "\n",
       ".xr-var-list,\n",
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       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
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       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
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       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
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       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
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       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
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       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
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       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
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       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;longitude&#x27; (longitude: 10)&gt;\n",
       "array([12.5 , 12.75, 13.  , 13.25, 13.5 , 13.75, 14.  , 14.25, 14.5 , 14.75],\n",
       "      dtype=float32)\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float32 12.5 12.75 13.0 13.25 ... 14.25 14.5 14.75\n",
       "Attributes:\n",
       "    axis:           X\n",
       "    units:          degrees_east\n",
       "    standard_name:  longitude\n",
       "    long_name:      longitude</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'longitude'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>longitude</span>: 10</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-2b91ce57-9871-4ede-8c06-a00c8c4f5f3e' class='xr-array-in' type='checkbox' checked><label for='section-2b91ce57-9871-4ede-8c06-a00c8c4f5f3e' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>12.5 12.75 13.0 13.25 13.5 13.75 14.0 14.25 14.5 14.75</span></div><div class='xr-array-data'><pre>array([12.5 , 12.75, 13.  , 13.25, 13.5 , 13.75, 14.  , 14.25, 14.5 , 14.75],\n",
       "      dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-4d0e3185-d7f7-4919-baf3-b882db35b9da' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4d0e3185-d7f7-4919-baf3-b882db35b9da' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.5 12.75 13.0 ... 14.5 14.75</div><input id='attrs-0032792f-1bcb-4e2b-b848-746b6170e13a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0032792f-1bcb-4e2b-b848-746b6170e13a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0cf697b7-37e1-4754-892d-682f988af358' class='xr-var-data-in' type='checkbox'><label for='data-0cf697b7-37e1-4754-892d-682f988af358' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([12.5 , 12.75, 13.  , 13.25, 13.5 , 13.75, 14.  , 14.25, 14.5 , 14.75],\n",
       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-57bf0927-294d-49d5-92b5-46ca5ef1add8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-57bf0927-294d-49d5-92b5-46ca5ef1add8' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'longitude' (longitude: 10)>\n",
       "array([12.5 , 12.75, 13.  , 13.25, 13.5 , 13.75, 14.  , 14.25, 14.5 , 14.75],\n",
       "      dtype=float32)\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float32 12.5 12.75 13.0 13.25 ... 14.25 14.5 14.75\n",
       "Attributes:\n",
       "    axis:           X\n",
       "    units:          degrees_east\n",
       "    standard_name:  longitude\n",
       "    long_name:      longitude"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Extraindo a coordenada desejada\n",
    "\n",
    "era_conv.longitude"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "2d531d46",
   "metadata": {},
   "outputs": [
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       "        [  9.40096586,  14.28358375,  21.92560992, ...,  76.36549386,\n",
       "          89.30344417, 111.12142889],\n",
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       "        [  9.04943266,  12.311941  ,  15.32289931, ...,  37.85031879,\n",
       "          55.67088699, 107.38129392],\n",
       "        [ 10.33201938,  12.09987477,  14.45871352, ...,  45.3853566 ,\n",
       "          85.89000582, 152.08077867],\n",
       "        [  7.34526082,   9.19144698,  11.55538041, ...,  71.68093182,\n",
       "         131.75553639, 204.07776158]],\n",
       "\n",
       "       [[ 10.06709581,  10.16835266,  10.6370636 , ..., 100.02265955,\n",
       "         113.56241942, 122.58956284],\n",
       "        [  9.11693722,   9.0411538 ,   9.40287637, ...,  88.11383543,\n",
       "         100.50474404, 108.6021076 ],\n",
       "        [  8.17824167,   8.13875787,  13.1977792 , ...,  89.06272035,\n",
       "          99.8819189 , 113.76939096],\n",
       "        ...,\n",
       "        [  9.33664548,  14.18614792,  19.94441464, ...,  39.76273584,\n",
       "          42.61257477,  61.950722  ],\n",
       "        [  7.15548384,  10.13205303,  15.05479156, ...,  37.50706445,\n",
       "          44.84532008,  67.986649  ],\n",
       "        [  5.86780243,   7.34780816,  12.32786189, ...,  44.05755455,\n",
       "          61.2712185 ,  84.55901959]]])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Acessando o nosso dado\n",
    "\n",
    "era_c.data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "0b9bd3b3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('time', 'latitude', 'longitude')"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Acessando as dimensoes espaciais \n",
    "\n",
    "era_c.dims"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "56f29f79",
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;time&#x27; (time: 360)&gt;\n",
       "array([&#x27;1991-01-31T00:00:00.000000000&#x27;, &#x27;1991-02-28T00:00:00.000000000&#x27;,\n",
       "       &#x27;1991-03-31T00:00:00.000000000&#x27;, ..., &#x27;2020-10-31T00:00:00.000000000&#x27;,\n",
       "       &#x27;2020-11-30T00:00:00.000000000&#x27;, &#x27;2020-12-31T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1991-01-31 1991-02-28 ... 2020-12-31</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'time'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 360</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-441c3bea-1936-447f-8c44-42fdca35715f' class='xr-array-in' type='checkbox' checked><label for='section-441c3bea-1936-447f-8c44-42fdca35715f' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1991-01-31 1991-02-28 1991-03-31 ... 2020-10-31 2020-11-30 2020-12-31</span></div><div class='xr-array-data'><pre>array([&#x27;1991-01-31T00:00:00.000000000&#x27;, &#x27;1991-02-28T00:00:00.000000000&#x27;,\n",
       "       &#x27;1991-03-31T00:00:00.000000000&#x27;, ..., &#x27;2020-10-31T00:00:00.000000000&#x27;,\n",
       "       &#x27;2020-11-30T00:00:00.000000000&#x27;, &#x27;2020-12-31T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></div></li><li class='xr-section-item'><input id='section-9e441f88-73b2-4b94-87fa-330b2cdb784e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9e441f88-73b2-4b94-87fa-330b2cdb784e' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1991-01-31 ... 2020-12-31</div><input id='attrs-0d25d652-8757-4b28-bcda-de80c6c5121b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0d25d652-8757-4b28-bcda-de80c6c5121b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1c177897-d765-48da-b2b8-12dfc48f91a2' class='xr-var-data-in' type='checkbox'><label for='data-1c177897-d765-48da-b2b8-12dfc48f91a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1991-01-31T00:00:00.000000000&#x27;, &#x27;1991-02-28T00:00:00.000000000&#x27;,\n",
       "       &#x27;1991-03-31T00:00:00.000000000&#x27;, ..., &#x27;2020-10-31T00:00:00.000000000&#x27;,\n",
       "       &#x27;2020-11-30T00:00:00.000000000&#x27;, &#x27;2020-12-31T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-362c7fb9-bce6-4c14-b94b-8e91ec4cfdd1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-362c7fb9-bce6-4c14-b94b-8e91ec4cfdd1' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'time' (time: 360)>\n",
       "array(['1991-01-31T00:00:00.000000000', '1991-02-28T00:00:00.000000000',\n",
       "       '1991-03-31T00:00:00.000000000', ..., '2020-10-31T00:00:00.000000000',\n",
       "       '2020-11-30T00:00:00.000000000', '2020-12-31T00:00:00.000000000'],\n",
       "      dtype='datetime64[ns]')\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1991-01-31 1991-02-28 ... 2020-12-31"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "era_c.time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "3fa4d0cd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'units': 'mm'}"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Atribuindo unidade em mm.\n",
    "\n",
    "era_c.attrs['units'] = 'mm'\n",
    "era_c.attrs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "f10b4f73",
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'era_conv' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-22-9bf2a26f5dde>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# plot mapa\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mera_conv\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m: name 'era_conv' is not defined"
     ]
    }
   ],
   "source": [
    "# plot mapa\n",
    "era_c[0].plot()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "6a6530bd",
   "metadata": {},
   "outputs": [
    {
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       "      <th>time</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">1991-01-31</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">-8.5</th>\n",
       "      <th>12.50</th>\n",
       "      <td>9.410561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12.75</th>\n",
       "      <td>10.221438</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13.00</th>\n",
       "      <td>9.085114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13.25</th>\n",
       "      <td>7.512670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13.50</th>\n",
       "      <td>12.642017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2020-12-31</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">-10.5</th>\n",
       "      <th>13.75</th>\n",
       "      <td>27.581983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14.00</th>\n",
       "      <td>35.435439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14.25</th>\n",
       "      <td>44.057555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14.50</th>\n",
       "      <td>61.271219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14.75</th>\n",
       "      <td>84.559020</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>32400 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      tp\n",
       "time       latitude longitude           \n",
       "1991-01-31 -8.5     12.50       9.410561\n",
       "                    12.75      10.221438\n",
       "                    13.00       9.085114\n",
       "                    13.25       7.512670\n",
       "                    13.50      12.642017\n",
       "...                                  ...\n",
       "2020-12-31 -10.5    13.75      27.581983\n",
       "                    14.00      35.435439\n",
       "                    14.25      44.057555\n",
       "                    14.50      61.271219\n",
       "                    14.75      84.559020\n",
       "\n",
       "[32400 rows x 1 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_data = era_c.to_dataframe()\n",
    "df_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "57181a00",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "time        latitude  longitude\n",
       "1991-01-31  -8.5      12.50         9.410561\n",
       "                      12.75        10.221438\n",
       "                      13.00         9.085114\n",
       "                      13.25         7.512670\n",
       "                      13.50        12.642017\n",
       "                                     ...    \n",
       "2020-12-31  -10.5     13.75        27.581983\n",
       "                      14.00        35.435439\n",
       "                      14.25        44.057555\n",
       "                      14.50        61.271219\n",
       "                      14.75        84.559020\n",
       "Name: tp, Length: 32400, dtype: float64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Acessando a variável do DataArray\n",
    "df_data['tp']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "755e4be2",
   "metadata": {},
   "outputs": [],
   "source": [
    "## DEFINER O PERIODO CLIMATOLOGICO 1991-2020 e Calculo de Anomalia\n",
    "\n",
    "df_clim = era_c.sel(time=slice(\"1991-01-01\" , \"2020-12-31\")).mean(dim='time') \n",
    "df_anml = (era_c - df_clim)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "c1065bd1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DataArrayGroupBy, grouped over 'season' \n",
       "4 groups with labels 'DJF', 'JJA', 'MAM', 'SON'."
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Separando por estações do ano\n",
    "ds = era_c.groupby(\"time.season\")\n",
    "ds "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "63f50bc9",
   "metadata": {},
   "outputs": [
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       "          26.05278117,  39.08092228,  35.39822154,  38.55739847,\n",
       "          56.65316522, 105.680089  ],\n",
       "        [  7.96063147,   8.8207642 ,  11.42892745,  13.49627183,\n",
       "          22.87615836,  24.59740916,  31.36351674,  43.41959233,\n",
       "          76.89204969, 139.75086451],\n",
       "        [  7.35700047,   8.39319989,  11.05842931,  11.84060299,\n",
       "          18.63524838,  21.93796217,  34.67904935,  62.74383081,\n",
       "         113.64090015, 176.6925932 ]]])\n",
       "Coordinates:\n",
       "  * latitude   (latitude) float32 -8.5 -8.75 -9.0 -9.25 ... -10.0 -10.25 -10.5\n",
       "  * longitude  (longitude) float32 12.5 12.75 13.0 13.25 ... 14.25 14.5 14.75\n",
       "  * season     (season) object &#x27;DJF&#x27; &#x27;JJA&#x27; &#x27;MAM&#x27; &#x27;SON&#x27;</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'tp'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>season</span>: 4</li><li><span class='xr-has-index'>latitude</span>: 9</li><li><span class='xr-has-index'>longitude</span>: 10</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-508ae45e-39ce-4501-9690-7a5446914896' class='xr-array-in' type='checkbox' checked><label for='section-508ae45e-39ce-4501-9690-7a5446914896' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>42.36 44.15 43.72 42.16 61.66 79.62 ... 21.94 34.68 62.74 113.6 176.7</span></div><div class='xr-array-data'><pre>array([[[ 42.36152852,  44.15309424,  43.72093309,  42.15528071,\n",
       "          61.658884  ,  79.62124116, 102.09400076, 134.45289487,\n",
       "         155.43647918, 160.17514125],\n",
       "        [ 36.59855414,  36.32295564,  35.38038532,  46.53635346,\n",
       "          78.43711971,  79.55431022,  93.26690521, 116.76566464,\n",
       "         131.145653  , 136.86316546],\n",
       "        [ 31.5829911 ,  31.42798269,  35.95894039,  52.51414255,\n",
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       "          76.33216263,  68.5210818 ,  82.14294328,  98.92739747,\n",
       "         111.95982821, 131.12103413],\n",
       "        [ 26.8659675 ,  28.78688352,  28.25718263,  37.71494607,\n",
       "          61.86803622,  71.31892354,  80.64708822,  81.27225758,\n",
       "          94.1160457 , 102.35443864],\n",
       "        [ 24.90003169,  28.17089607,  27.87473244,  30.09562492,\n",
       "          50.03944581,  79.06902066,  79.18653424,  73.13594316,\n",
       "          76.70262317,  85.25545479],\n",
       "        [ 23.26511395,  26.3577959 ,  28.70568162,  30.90213076,\n",
       "          38.8549509 ,  73.66880195,  72.45889699,  71.80701371,\n",
       "...\n",
       "          39.71948277,  38.40440005,  51.73254846,  66.48832444,\n",
       "          84.95695477, 110.633518  ],\n",
       "        [ 10.25294967,  11.23205344,  16.34215182,  28.08648107,\n",
       "          35.69342752,  34.4353121 ,  43.98993934,  57.89273351,\n",
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       "          59.24809796,  71.38643031],\n",
       "        [  9.00873531,  10.18196585,  11.96044989,  18.22374161,\n",
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       "          49.5518918 ,  62.00446948],\n",
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       "          26.05278117,  39.08092228,  35.39822154,  38.55739847,\n",
       "          56.65316522, 105.680089  ],\n",
       "        [  7.96063147,   8.8207642 ,  11.42892745,  13.49627183,\n",
       "          22.87615836,  24.59740916,  31.36351674,  43.41959233,\n",
       "          76.89204969, 139.75086451],\n",
       "        [  7.35700047,   8.39319989,  11.05842931,  11.84060299,\n",
       "          18.63524838,  21.93796217,  34.67904935,  62.74383081,\n",
       "         113.64090015, 176.6925932 ]]])</pre></div></div></li><li class='xr-section-item'><input id='section-3538dba1-2829-44c2-a024-fa167f260ad8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3538dba1-2829-44c2-a024-fa167f260ad8' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-8.5 -8.75 -9.0 ... -10.25 -10.5</div><input id='attrs-565486e5-d5cb-4ab2-bb9d-29ed68608ae9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-565486e5-d5cb-4ab2-bb9d-29ed68608ae9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d1faa7fa-198f-4598-aeb8-d2cd94484efe' class='xr-var-data-in' type='checkbox'><label for='data-d1faa7fa-198f-4598-aeb8-d2cd94484efe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([ -8.5 ,  -8.75,  -9.  ,  -9.25,  -9.5 ,  -9.75, -10.  , -10.25, -10.5 ],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.5 12.75 13.0 ... 14.5 14.75</div><input id='attrs-86474bc4-9b0e-4c2f-8b6a-398ec3818f58' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-86474bc4-9b0e-4c2f-8b6a-398ec3818f58' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f1a2244-d434-44df-aab2-05cb760f52a7' class='xr-var-data-in' type='checkbox'><label for='data-4f1a2244-d434-44df-aab2-05cb760f52a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([12.5 , 12.75, 13.  , 13.25, 13.5 , 13.75, 14.  , 14.25, 14.5 , 14.75],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>season</span></div><div class='xr-var-dims'>(season)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;DJF&#x27; &#x27;JJA&#x27; &#x27;MAM&#x27; &#x27;SON&#x27;</div><input id='attrs-81d1d76a-a2c9-44e2-bd2e-7b0210186dd7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-81d1d76a-a2c9-44e2-bd2e-7b0210186dd7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cf5bdf4a-d752-488f-8c81-b8a656c653af' class='xr-var-data-in' type='checkbox'><label for='data-cf5bdf4a-d752-488f-8c81-b8a656c653af' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;DJF&#x27;, &#x27;JJA&#x27;, &#x27;MAM&#x27;, &#x27;SON&#x27;], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5a38ea3e-06b8-4458-a7c2-c66d76f185f0' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5a38ea3e-06b8-4458-a7c2-c66d76f185f0' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
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       "          61.658884  ,  79.62124116, 102.09400076, 134.45289487,\n",
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       "         131.145653  , 136.86316546],\n",
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       "          94.1160457 , 102.35443864],\n",
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       "          50.03944581,  79.06902066,  79.18653424,  73.13594316,\n",
       "          76.70262317,  85.25545479],\n",
       "        [ 23.26511395,  26.3577959 ,  28.70568162,  30.90213076,\n",
       "          38.8549509 ,  73.66880195,  72.45889699,  71.80701371,\n",
       "...\n",
       "          39.71948277,  38.40440005,  51.73254846,  66.48832444,\n",
       "          84.95695477, 110.633518  ],\n",
       "        [ 10.25294967,  11.23205344,  16.34215182,  28.08648107,\n",
       "          35.69342752,  34.4353121 ,  43.98993934,  57.89273351,\n",
       "          74.47319202, 100.12941443],\n",
       "        [  9.79420064,  10.69021131,  13.22484689,  24.45281964,\n",
       "          32.50122786,  37.27521302,  42.69060565,  44.36131372,\n",
       "          59.24809796,  71.38643031],\n",
       "        [  9.00873531,  10.18196585,  11.96044989,  18.22374161,\n",
       "          31.20975705,  44.45800489,  40.21548986,  38.11805484,\n",
       "          49.5518918 ,  62.00446948],\n",
       "        [  8.16585534,   9.59262915,  11.13877228,  15.25504163,\n",
       "          26.05278117,  39.08092228,  35.39822154,  38.55739847,\n",
       "          56.65316522, 105.680089  ],\n",
       "        [  7.96063147,   8.8207642 ,  11.42892745,  13.49627183,\n",
       "          22.87615836,  24.59740916,  31.36351674,  43.41959233,\n",
       "          76.89204969, 139.75086451],\n",
       "        [  7.35700047,   8.39319989,  11.05842931,  11.84060299,\n",
       "          18.63524838,  21.93796217,  34.67904935,  62.74383081,\n",
       "         113.64090015, 176.6925932 ]]])\n",
       "Coordinates:\n",
       "  * latitude   (latitude) float32 -8.5 -8.75 -9.0 -9.25 ... -10.0 -10.25 -10.5\n",
       "  * longitude  (longitude) float32 12.5 12.75 13.0 13.25 ... 14.25 14.5 14.75\n",
       "  * season     (season) object 'DJF' 'JJA' 'MAM' 'SON'"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculando média sazonal\n",
    "media_sazonal = era_c.groupby(\"time.season\").mean()\n",
    "media_sazonal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "04e3a523",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
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       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;tp&#x27; (season: 4, latitude: 9, longitude: 10)&gt;\n",
       "array([[[ 42.36152852,  44.15309424,  43.72093309,  42.15528071,\n",
       "          61.658884  ,  79.62124116, 102.09400076, 134.45289487,\n",
       "         155.43647918, 160.17514125],\n",
       "        [ 36.59855414,  36.32295564,  35.38038532,  46.53635346,\n",
       "          78.43711971,  79.55431022,  93.26690521, 116.76566464,\n",
       "         131.145653  , 136.86316546],\n",
       "        [ 31.5829911 ,  31.42798269,  35.95894039,  52.51414255,\n",
       "          85.98208437,  75.6740048 ,  89.28058723, 105.45914711,\n",
       "         119.66773092, 138.84334492],\n",
       "        [ 27.75180737,  29.26759349,  33.79036794,  48.47097865,\n",
       "          76.33216263,  68.5210818 ,  82.14294328,  98.92739747,\n",
       "         111.95982821, 131.12103413],\n",
       "        [ 26.8659675 ,  28.78688352,  28.25718263,  37.71494607,\n",
       "          61.86803622,  71.31892354,  80.64708822,  81.27225758,\n",
       "          94.1160457 , 102.35443864],\n",
       "        [ 24.90003169,  28.17089607,  27.87473244,  30.09562492,\n",
       "          50.03944581,  79.06902066,  79.18653424,  73.13594316,\n",
       "          76.70262317,  85.25545479],\n",
       "        [ 23.26511395,  26.3577959 ,  28.70568162,  30.90213076,\n",
       "          38.8549509 ,  73.66880195,  72.45889699,  71.80701371,\n",
       "...\n",
       "          39.71948277,  38.40440005,  51.73254846,  66.48832444,\n",
       "          84.95695477, 110.633518  ],\n",
       "        [ 10.25294967,  11.23205344,  16.34215182,  28.08648107,\n",
       "          35.69342752,  34.4353121 ,  43.98993934,  57.89273351,\n",
       "          74.47319202, 100.12941443],\n",
       "        [  9.79420064,  10.69021131,  13.22484689,  24.45281964,\n",
       "          32.50122786,  37.27521302,  42.69060565,  44.36131372,\n",
       "          59.24809796,  71.38643031],\n",
       "        [  9.00873531,  10.18196585,  11.96044989,  18.22374161,\n",
       "          31.20975705,  44.45800489,  40.21548986,  38.11805484,\n",
       "          49.5518918 ,  62.00446948],\n",
       "        [  8.16585534,   9.59262915,  11.13877228,  15.25504163,\n",
       "          26.05278117,  39.08092228,  35.39822154,  38.55739847,\n",
       "          56.65316522, 105.680089  ],\n",
       "        [  7.96063147,   8.8207642 ,  11.42892745,  13.49627183,\n",
       "          22.87615836,  24.59740916,  31.36351674,  43.41959233,\n",
       "          76.89204969, 139.75086451],\n",
       "        [  7.35700047,   8.39319989,  11.05842931,  11.84060299,\n",
       "          18.63524838,  21.93796217,  34.67904935,  62.74383081,\n",
       "         113.64090015, 176.6925932 ]]])\n",
       "Coordinates:\n",
       "  * latitude   (latitude) float32 -8.5 -8.75 -9.0 -9.25 ... -10.0 -10.25 -10.5\n",
       "  * longitude  (longitude) float32 12.5 12.75 13.0 13.25 ... 14.25 14.5 14.75\n",
       "  * season     (season) object &#x27;DJF&#x27; &#x27;JJA&#x27; &#x27;MAM&#x27; &#x27;SON&#x27;</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'tp'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>season</span>: 4</li><li><span class='xr-has-index'>latitude</span>: 9</li><li><span class='xr-has-index'>longitude</span>: 10</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-6524178b-dc45-468b-9e71-b7e0a844cba4' class='xr-array-in' type='checkbox' checked><label for='section-6524178b-dc45-468b-9e71-b7e0a844cba4' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>42.36 44.15 43.72 42.16 61.66 79.62 ... 21.94 34.68 62.74 113.6 176.7</span></div><div class='xr-array-data'><pre>array([[[ 42.36152852,  44.15309424,  43.72093309,  42.15528071,\n",
       "          61.658884  ,  79.62124116, 102.09400076, 134.45289487,\n",
       "         155.43647918, 160.17514125],\n",
       "        [ 36.59855414,  36.32295564,  35.38038532,  46.53635346,\n",
       "          78.43711971,  79.55431022,  93.26690521, 116.76566464,\n",
       "         131.145653  , 136.86316546],\n",
       "        [ 31.5829911 ,  31.42798269,  35.95894039,  52.51414255,\n",
       "          85.98208437,  75.6740048 ,  89.28058723, 105.45914711,\n",
       "         119.66773092, 138.84334492],\n",
       "        [ 27.75180737,  29.26759349,  33.79036794,  48.47097865,\n",
       "          76.33216263,  68.5210818 ,  82.14294328,  98.92739747,\n",
       "         111.95982821, 131.12103413],\n",
       "        [ 26.8659675 ,  28.78688352,  28.25718263,  37.71494607,\n",
       "          61.86803622,  71.31892354,  80.64708822,  81.27225758,\n",
       "          94.1160457 , 102.35443864],\n",
       "        [ 24.90003169,  28.17089607,  27.87473244,  30.09562492,\n",
       "          50.03944581,  79.06902066,  79.18653424,  73.13594316,\n",
       "          76.70262317,  85.25545479],\n",
       "        [ 23.26511395,  26.3577959 ,  28.70568162,  30.90213076,\n",
       "          38.8549509 ,  73.66880195,  72.45889699,  71.80701371,\n",
       "...\n",
       "          39.71948277,  38.40440005,  51.73254846,  66.48832444,\n",
       "          84.95695477, 110.633518  ],\n",
       "        [ 10.25294967,  11.23205344,  16.34215182,  28.08648107,\n",
       "          35.69342752,  34.4353121 ,  43.98993934,  57.89273351,\n",
       "          74.47319202, 100.12941443],\n",
       "        [  9.79420064,  10.69021131,  13.22484689,  24.45281964,\n",
       "          32.50122786,  37.27521302,  42.69060565,  44.36131372,\n",
       "          59.24809796,  71.38643031],\n",
       "        [  9.00873531,  10.18196585,  11.96044989,  18.22374161,\n",
       "          31.20975705,  44.45800489,  40.21548986,  38.11805484,\n",
       "          49.5518918 ,  62.00446948],\n",
       "        [  8.16585534,   9.59262915,  11.13877228,  15.25504163,\n",
       "          26.05278117,  39.08092228,  35.39822154,  38.55739847,\n",
       "          56.65316522, 105.680089  ],\n",
       "        [  7.96063147,   8.8207642 ,  11.42892745,  13.49627183,\n",
       "          22.87615836,  24.59740916,  31.36351674,  43.41959233,\n",
       "          76.89204969, 139.75086451],\n",
       "        [  7.35700047,   8.39319989,  11.05842931,  11.84060299,\n",
       "          18.63524838,  21.93796217,  34.67904935,  62.74383081,\n",
       "         113.64090015, 176.6925932 ]]])</pre></div></div></li><li class='xr-section-item'><input id='section-0cc3edc6-f985-4db9-8953-036509161910' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0cc3edc6-f985-4db9-8953-036509161910' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-8.5 -8.75 -9.0 ... -10.25 -10.5</div><input id='attrs-2bcabe25-5a91-467e-bb2c-93b4e487bc8f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2bcabe25-5a91-467e-bb2c-93b4e487bc8f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-acb829ff-f89b-4b3c-bb5a-8780607bc79a' class='xr-var-data-in' type='checkbox'><label for='data-acb829ff-f89b-4b3c-bb5a-8780607bc79a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([ -8.5 ,  -8.75,  -9.  ,  -9.25,  -9.5 ,  -9.75, -10.  , -10.25, -10.5 ],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.5 12.75 13.0 ... 14.5 14.75</div><input id='attrs-f4cf4eba-28e0-4ca0-a731-288b21aa5480' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f4cf4eba-28e0-4ca0-a731-288b21aa5480' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4cb71644-9347-4f40-bd06-e64605ca06e6' class='xr-var-data-in' type='checkbox'><label for='data-4cb71644-9347-4f40-bd06-e64605ca06e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([12.5 , 12.75, 13.  , 13.25, 13.5 , 13.75, 14.  , 14.25, 14.5 , 14.75],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>season</span></div><div class='xr-var-dims'>(season)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;DJF&#x27; &#x27;JJA&#x27; &#x27;MAM&#x27; &#x27;SON&#x27;</div><input id='attrs-81168892-7f6a-424a-bec6-233a83ba551c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-81168892-7f6a-424a-bec6-233a83ba551c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-00633df2-51ab-46b4-831b-4ff4ab753185' class='xr-var-data-in' type='checkbox'><label for='data-00633df2-51ab-46b4-831b-4ff4ab753185' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;DJF&#x27;, &#x27;JJA&#x27;, &#x27;MAM&#x27;, &#x27;SON&#x27;], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-aae66a59-12d2-4405-ba36-e32e52df5301' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-aae66a59-12d2-4405-ba36-e32e52df5301' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'tp' (season: 4, latitude: 9, longitude: 10)>\n",
       "array([[[ 42.36152852,  44.15309424,  43.72093309,  42.15528071,\n",
       "          61.658884  ,  79.62124116, 102.09400076, 134.45289487,\n",
       "         155.43647918, 160.17514125],\n",
       "        [ 36.59855414,  36.32295564,  35.38038532,  46.53635346,\n",
       "          78.43711971,  79.55431022,  93.26690521, 116.76566464,\n",
       "         131.145653  , 136.86316546],\n",
       "        [ 31.5829911 ,  31.42798269,  35.95894039,  52.51414255,\n",
       "          85.98208437,  75.6740048 ,  89.28058723, 105.45914711,\n",
       "         119.66773092, 138.84334492],\n",
       "        [ 27.75180737,  29.26759349,  33.79036794,  48.47097865,\n",
       "          76.33216263,  68.5210818 ,  82.14294328,  98.92739747,\n",
       "         111.95982821, 131.12103413],\n",
       "        [ 26.8659675 ,  28.78688352,  28.25718263,  37.71494607,\n",
       "          61.86803622,  71.31892354,  80.64708822,  81.27225758,\n",
       "          94.1160457 , 102.35443864],\n",
       "        [ 24.90003169,  28.17089607,  27.87473244,  30.09562492,\n",
       "          50.03944581,  79.06902066,  79.18653424,  73.13594316,\n",
       "          76.70262317,  85.25545479],\n",
       "        [ 23.26511395,  26.3577959 ,  28.70568162,  30.90213076,\n",
       "          38.8549509 ,  73.66880195,  72.45889699,  71.80701371,\n",
       "...\n",
       "          39.71948277,  38.40440005,  51.73254846,  66.48832444,\n",
       "          84.95695477, 110.633518  ],\n",
       "        [ 10.25294967,  11.23205344,  16.34215182,  28.08648107,\n",
       "          35.69342752,  34.4353121 ,  43.98993934,  57.89273351,\n",
       "          74.47319202, 100.12941443],\n",
       "        [  9.79420064,  10.69021131,  13.22484689,  24.45281964,\n",
       "          32.50122786,  37.27521302,  42.69060565,  44.36131372,\n",
       "          59.24809796,  71.38643031],\n",
       "        [  9.00873531,  10.18196585,  11.96044989,  18.22374161,\n",
       "          31.20975705,  44.45800489,  40.21548986,  38.11805484,\n",
       "          49.5518918 ,  62.00446948],\n",
       "        [  8.16585534,   9.59262915,  11.13877228,  15.25504163,\n",
       "          26.05278117,  39.08092228,  35.39822154,  38.55739847,\n",
       "          56.65316522, 105.680089  ],\n",
       "        [  7.96063147,   8.8207642 ,  11.42892745,  13.49627183,\n",
       "          22.87615836,  24.59740916,  31.36351674,  43.41959233,\n",
       "          76.89204969, 139.75086451],\n",
       "        [  7.35700047,   8.39319989,  11.05842931,  11.84060299,\n",
       "          18.63524838,  21.93796217,  34.67904935,  62.74383081,\n",
       "         113.64090015, 176.6925932 ]]])\n",
       "Coordinates:\n",
       "  * latitude   (latitude) float32 -8.5 -8.75 -9.0 -9.25 ... -10.0 -10.25 -10.5\n",
       "  * longitude  (longitude) float32 12.5 12.75 13.0 13.25 ... 14.25 14.5 14.75\n",
       "  * season     (season) object 'DJF' 'JJA' 'MAM' 'SON'"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Ordenando as estações do ano\n",
    "\n",
    "media_sazonal = media_sazonal.sel(season=[\"DJF\" , \"JJA\" , \"MAM\" , \"SON\"])\n",
    "media_sazonal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "2a8ef980",
   "metadata": {},
   "outputs": [
    {
     "ename": "IndentationError",
     "evalue": "unexpected indent (<ipython-input-70-adbc6213fc06>, line 27)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-70-adbc6213fc06>\"\u001b[0;36m, line \u001b[0;32m27\u001b[0m\n\u001b[0;31m    seasons\u001b[0m\n\u001b[0m    ^\u001b[0m\n\u001b[0;31mIndentationError\u001b[0m\u001b[0;31m:\u001b[0m unexpected indent\n"
     ]
    }
   ],
   "source": [
    "#Create new list groups season\n",
    "\n",
    "djf = [12, 1, 2]\n",
    "jfm = [1, 2, 3]\n",
    "fma = [2, 3, 4]\n",
    "mam = [3, 4, 5]\n",
    "mjj = [5, 6, 7]\n",
    "jja = [6, 7, 8]\n",
    "son = [9, 10, 11]\n",
    "ond = [10, 11, 12]\n",
    "ndj = [11, 12, 1]\n",
    "\n",
    "sea_new = djf + jfm + fma + mam + mjj + jja + son + ond + ndjseasons = {\n",
    "    1: 'Summer',\n",
    "    2: 'Summer',\n",
    "    3: 'Summer',\n",
    "    4: 'Summer',\n",
    "    5: 'Winter',\n",
    "    6: 'Winter',\n",
    "    7: 'Winter',\n",
    "    8: 'Winter',\n",
    "    9: 'Summer',\n",
    "    10: 'Summer',\n",
    "    11: 'Summer',\n",
    "    12: 'Summer'\n",
    "}\n",
    " .seasons[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "d8aed8e7",
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;month&#x27; (time: 360)&gt;\n",
       "array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,\n",
       "        6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10,\n",
       "       11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,\n",
       "        4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,\n",
       "        9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,\n",
       "        2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,\n",
       "        7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11,\n",
       "       12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,\n",
       "        5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9,\n",
       "       10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,\n",
       "        3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,\n",
       "        8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,\n",
       "        1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,\n",
       "        6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10,\n",
       "       11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,\n",
       "        4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,\n",
       "        9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,\n",
       "        2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,\n",
       "        7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11,\n",
       "       12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,\n",
       "        5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9,\n",
       "       10, 11, 12])\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1991-01-31 1991-02-28 ... 2020-12-31</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'month'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 360</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-9ffb8423-4a52-4643-a18f-ae67f65fa3d4' class='xr-array-in' type='checkbox' checked><label for='section-9ffb8423-4a52-4643-a18f-ae67f65fa3d4' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 ... 11 12 1 2 3 4 5 6 7 8 9 10 11 12</span></div><div class='xr-array-data'><pre>array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,\n",
       "        6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10,\n",
       "       11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,\n",
       "        4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,\n",
       "        9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,\n",
       "        2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,\n",
       "        7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11,\n",
       "       12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,\n",
       "        5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9,\n",
       "       10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,\n",
       "        3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,\n",
       "        8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,\n",
       "        1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,\n",
       "        6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10,\n",
       "       11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,\n",
       "        4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,\n",
       "        9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,\n",
       "        2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,\n",
       "        7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11,\n",
       "       12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,\n",
       "        5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9,\n",
       "       10, 11, 12])</pre></div></div></li><li class='xr-section-item'><input id='section-3e5160eb-dd6e-49be-801c-05098b4e9c6e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3e5160eb-dd6e-49be-801c-05098b4e9c6e' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1991-01-31 ... 2020-12-31</div><input id='attrs-5d7e25d6-9d59-44e7-b027-f9d71649e09f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5d7e25d6-9d59-44e7-b027-f9d71649e09f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a528f312-513b-4213-a29a-2edd9c35512a' class='xr-var-data-in' type='checkbox'><label for='data-a528f312-513b-4213-a29a-2edd9c35512a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1991-01-31T00:00:00.000000000&#x27;, &#x27;1991-02-28T00:00:00.000000000&#x27;,\n",
       "       &#x27;1991-03-31T00:00:00.000000000&#x27;, ..., &#x27;2020-10-31T00:00:00.000000000&#x27;,\n",
       "       &#x27;2020-11-30T00:00:00.000000000&#x27;, &#x27;2020-12-31T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6c5eca12-114c-49ea-a8ec-c806b4d9fa5f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6c5eca12-114c-49ea-a8ec-c806b4d9fa5f' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'month' (time: 360)>\n",
       "array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,\n",
       "        6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10,\n",
       "       11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,\n",
       "        4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,\n",
       "        9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,\n",
       "        2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,\n",
       "        7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11,\n",
       "       12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,\n",
       "        5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9,\n",
       "       10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,\n",
       "        3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,\n",
       "        8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,\n",
       "        1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,\n",
       "        6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10,\n",
       "       11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,\n",
       "        4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,\n",
       "        9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,\n",
       "        2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,\n",
       "        7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11,\n",
       "       12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,\n",
       "        5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9,\n",
       "       10, 11, 12])\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1991-01-31 1991-02-28 ... 2020-12-31"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "era_c.time.dt.month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "db383324",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Q1\n"
     ]
    }
   ],
   "source": [
    "def get_quarter(month):\n",
    "    quarter_dictionary = {\n",
    "        \"Q1\" : [1,2,3],\n",
    "        \"Q2\" : [2,3,4],\n",
    "        \"Q3\" : [3,4,5],\n",
    "        \"Q4\" : [5,6,7],\n",
    "        \"Q5\" : [6,7,8],\n",
    "        \"Q6\" : [9,10,11],\n",
    "        \"Q7\" : [10,11,12],\n",
    "        \"Q8\" : [11,12,1],\n",
    "        \"Q9\" : [12,2,1]\n",
    "    }\n",
    "\n",
    "    for key,values in quarter_dictionary.items():\n",
    "        for value in values:\n",
    "            if value == month:\n",
    "                return key\n",
    "\n",
    "print(get_quarter(3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "435c1ec1",
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "Only valid with DatetimeIndex, TimedeltaIndex or PeriodIndex, but got an instance of 'CategoricalIndex'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-60-650c0f2445f9>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mdf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mDataFrame\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0;34m'Quarter'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mquarters\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Quarter'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mCategorical\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Quarter'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcategories\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mquarters\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m \u001b[0mdf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgroupby\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mGrouper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Quarter'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfreq\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Q'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      7\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/pyprecis-environment2/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36mgroupby\u001b[0;34m(self, by, axis, level, as_index, sort, group_keys, squeeze, observed, dropna)\u001b[0m\n\u001b[1;32m   6523\u001b[0m             \u001b[0msqueeze\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msqueeze\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   6524\u001b[0m             \u001b[0mobserved\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mobserved\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 6525\u001b[0;31m             \u001b[0mdropna\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdropna\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   6526\u001b[0m         )\n\u001b[1;32m   6527\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/pyprecis-environment2/lib/python3.6/site-packages/pandas/core/groupby/groupby.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, obj, keys, axis, level, grouper, exclusions, selection, as_index, sort, group_keys, squeeze, observed, mutated, dropna)\u001b[0m\n\u001b[1;32m    531\u001b[0m                 \u001b[0mobserved\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mobserved\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    532\u001b[0m                 \u001b[0mmutated\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmutated\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 533\u001b[0;31m                 \u001b[0mdropna\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdropna\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    534\u001b[0m             )\n\u001b[1;32m    535\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/pyprecis-environment2/lib/python3.6/site-packages/pandas/core/groupby/grouper.py\u001b[0m in \u001b[0;36mget_grouper\u001b[0;34m(obj, key, axis, level, sort, observed, mutated, validate, dropna)\u001b[0m\n\u001b[1;32m    692\u001b[0m     \u001b[0;31m# a passed-in Grouper, directly convert\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    693\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mGrouper\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 694\u001b[0;31m         \u001b[0mbinner\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgrouper\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_grouper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalidate\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    695\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkey\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    696\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mgrouper\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/pyprecis-environment2/lib/python3.6/site-packages/pandas/core/resample.py\u001b[0m in \u001b[0;36m_get_grouper\u001b[0;34m(self, obj, validate)\u001b[0m\n\u001b[1;32m   1441\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_get_grouper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalidate\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mbool\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1442\u001b[0m         \u001b[0;31m# create the resampler and return our binner\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1443\u001b[0;31m         \u001b[0mr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_resampler\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1444\u001b[0m         \u001b[0mr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_set_binner\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1445\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbinner\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgrouper\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/pyprecis-environment2/lib/python3.6/site-packages/pandas/core/resample.py\u001b[0m in \u001b[0;36m_get_resampler\u001b[0;34m(self, obj, kind)\u001b[0m\n\u001b[1;32m   1434\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1435\u001b[0m         raise TypeError(\n\u001b[0;32m-> 1436\u001b[0;31m             \u001b[0;34m\"Only valid with DatetimeIndex, \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1437\u001b[0m             \u001b[0;34m\"TimedeltaIndex or PeriodIndex, \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1438\u001b[0m             \u001b[0;34mf\"but got an instance of '{type(ax).__name__}'\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mTypeError\u001b[0m: Only valid with DatetimeIndex, TimedeltaIndex or PeriodIndex, but got an instance of 'CategoricalIndex'"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "quarters = ['DJF', 'JFM', 'FMA', 'MAM', 'MJJ', 'JJA', 'SON' , 'NDJ' , 'OND']\n",
    "df = pd.DataFrame({'Quarter': quarters})\n",
    "df['Quarter'] = pd.Categorical(df['Quarter'], categories=quarters)\n",
    "df = df.groupby(pd.Grouper(key='Quarter', freq='Q')).sum()\n",
    "print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "e098087c",
   "metadata": {},
   "outputs": [],
   "source": [
    "media_sa = get_quarter([\"Q1\", \"Q2\", \"Q3\", \"Q4\",\"Q5\", \"Q6\",\"Q7\",\"Q8\", \"Q9\"])\n",
    "media_sa"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "9104527c",
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'NoneType' object has no attribute 'groupby'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-59-3a3a678aa5a8>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0ma\u001b[0m\u001b[0;34m=\u001b[0m \u001b[0mmedia_sa\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgroupby\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"time.season\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmean\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m: 'NoneType' object has no attribute 'groupby'"
     ]
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "88be99aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Acresentar vários trimestre da estacao do ano (Climatologia)\n",
    "DJF = era_conv.resample(time='QS-DEC').mean()\n",
    "JFM = era_conv.resample(time='QS-Jan').mean()\n",
    "FMA = era_conv.resample(time='QS-Feb').mean()\n",
    "MAM = era_conv.resample(time='QS-Mar').mean()\n",
    "JJA = era_conv.resample(time='QS-Jun').mean()\n",
    "SON = era_conv.resample(time='QS-Sep').mean()\n",
    "OND = era_conv.resample(time='QS-Oct').mean()\n",
    "NDJ = era_conv.resample(time='QS-Nov').mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "id": "6bb2c649",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>tp</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
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       "  <tbody>\n",
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       "      <th rowspan=\"5\" valign=\"top\">1990-12-01</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">-8.5</th>\n",
       "      <th>12.50</th>\n",
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       "      <th rowspan=\"5\" valign=\"top\">2020-12-01</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">-10.5</th>\n",
       "      <th>13.75</th>\n",
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      ],
      "text/plain": [
       "                                      tp\n",
       "time       latitude longitude           \n",
       "1990-12-01 -8.5     12.50       7.498972\n",
       "                    12.75       8.521883\n",
       "                    13.00       8.092337\n",
       "                    13.25       5.965428\n",
       "                    13.50      10.304718\n",
       "...                                  ...\n",
       "2020-12-01 -10.5    13.75      27.581983\n",
       "                    14.00      35.435439\n",
       "                    14.25      44.057555\n",
       "                    14.50      61.271219\n",
       "                    14.75      84.559020\n",
       "\n",
       "[10890 rows x 1 columns]"
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Criando data frame (Tabela)\n",
    "\n",
    "data_djf = DJF.to_dataframe()\n",
    "data_djf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "id": "baec6f84",
   "metadata": {},
   "outputs": [],
   "source": [
    "path = '/mnt/e/Ajdata'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "id": "f33ef092",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/mnt/e/Ajdata'"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "id": "3d6e3e6a",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Salvando Data frame dos Trimestre Sazonais\n",
    "data_djf.to_csv('/mnt/e/Ajdata/djf.csv')\n",
    "data_djf.to_csv('/mnt/e/Ajdata/djf.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "id": "5fae4f1f",
   "metadata": {},
   "outputs": [
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       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;tp&#x27; (year: 30, latitude: 9, longitude: 10)&gt;\n",
       "array([[[ 21.4616785 ,  18.7635022 ,  17.74661811, ...,  87.31031117,\n",
       "         101.22735985,  99.42470998],\n",
       "        [ 15.98177266,  15.54583474,  14.44649318, ...,  81.11038638,\n",
       "          91.38898798,  89.93379177],\n",
       "        [ 13.8734001 ,  13.31245192,  17.27762415, ...,  73.37956523,\n",
       "          85.03072294,  99.39603707],\n",
       "        ...,\n",
       "        [  8.55466528,   8.45951503,   8.70086063, ...,  39.4234348 ,\n",
       "          58.55110131,  91.37894332],\n",
       "        [  8.42581978,   8.40089078,   8.78852306, ...,  42.79250256,\n",
       "          70.3595948 , 102.32259223],\n",
       "        [  6.97391092,   6.93309311,   7.92723976, ...,  63.57808463,\n",
       "          93.54256148, 119.72878794]],\n",
       "\n",
       "       [[ 15.04214108,  16.11098342,  17.02842545, ...,  85.10678835,\n",
       "         104.42210724, 108.66697739],\n",
       "        [ 13.50147401,  14.37006251,  14.93073675, ...,  76.5978719 ,\n",
       "          95.53149399, 100.61810602],\n",
       "        [ 11.29685542,  12.17347964,  16.60737188, ...,  68.01919076,\n",
       "          87.41943262, 105.02652137],\n",
       "...\n",
       "        [ 21.07750423,  23.26975741,  24.02228471, ...,  63.50396382,\n",
       "          76.39924615, 104.72484071],\n",
       "        [ 19.14837024,  21.59583527,  24.10353431, ...,  63.20682698,\n",
       "          86.40186236, 113.27547195],\n",
       "        [ 17.77959845,  20.37130671,  23.31407055, ...,  79.92301626,\n",
       "         107.47936659, 130.59129493]],\n",
       "\n",
       "       [[ 28.5528387 ,  30.28264317,  30.38708419, ...,  94.47486697,\n",
       "         106.47252964, 106.98194498],\n",
       "        [ 27.38440474,  27.44002171,  28.0173131 , ...,  83.8167878 ,\n",
       "          95.18918414,  97.20869569],\n",
       "        [ 25.5803028 ,  25.69848886,  30.06500463, ...,  75.89715441,\n",
       "          87.19971112, 100.58111123],\n",
       "        ...,\n",
       "        [ 21.75048016,  24.94415719,  27.83411675, ...,  68.78226884,\n",
       "          74.72845511,  89.83859828],\n",
       "        [ 21.88649761,  24.77799619,  29.19238077, ...,  75.84806501,\n",
       "          84.70554483,  93.18803467],\n",
       "        [ 20.70139979,  24.67307754,  31.30640933, ...,  92.28818609,\n",
       "          97.72060531, 103.91897844]]])\n",
       "Coordinates:\n",
       "  * latitude   (latitude) float32 -8.5 -8.75 -9.0 -9.25 ... -10.0 -10.25 -10.5\n",
       "  * longitude  (longitude) float32 12.5 12.75 13.0 13.25 ... 14.25 14.5 14.75\n",
       "  * year       (year) int64 1991 1992 1993 1994 1995 ... 2017 2018 2019 2020</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'tp'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>year</span>: 30</li><li><span class='xr-has-index'>latitude</span>: 9</li><li><span class='xr-has-index'>longitude</span>: 10</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-fff691c0-cf27-4b99-ba84-bc1549440dbd' class='xr-array-in' type='checkbox' checked><label for='section-fff691c0-cf27-4b99-ba84-bc1549440dbd' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>21.46 18.76 17.75 18.77 35.26 45.74 ... 49.26 74.98 92.29 97.72 103.9</span></div><div class='xr-array-data'><pre>array([[[ 21.4616785 ,  18.7635022 ,  17.74661811, ...,  87.31031117,\n",
       "         101.22735985,  99.42470998],\n",
       "        [ 15.98177266,  15.54583474,  14.44649318, ...,  81.11038638,\n",
       "          91.38898798,  89.93379177],\n",
       "        [ 13.8734001 ,  13.31245192,  17.27762415, ...,  73.37956523,\n",
       "          85.03072294,  99.39603707],\n",
       "        ...,\n",
       "        [  8.55466528,   8.45951503,   8.70086063, ...,  39.4234348 ,\n",
       "          58.55110131,  91.37894332],\n",
       "        [  8.42581978,   8.40089078,   8.78852306, ...,  42.79250256,\n",
       "          70.3595948 , 102.32259223],\n",
       "        [  6.97391092,   6.93309311,   7.92723976, ...,  63.57808463,\n",
       "          93.54256148, 119.72878794]],\n",
       "\n",
       "       [[ 15.04214108,  16.11098342,  17.02842545, ...,  85.10678835,\n",
       "         104.42210724, 108.66697739],\n",
       "        [ 13.50147401,  14.37006251,  14.93073675, ...,  76.5978719 ,\n",
       "          95.53149399, 100.61810602],\n",
       "        [ 11.29685542,  12.17347964,  16.60737188, ...,  68.01919076,\n",
       "          87.41943262, 105.02652137],\n",
       "...\n",
       "        [ 21.07750423,  23.26975741,  24.02228471, ...,  63.50396382,\n",
       "          76.39924615, 104.72484071],\n",
       "        [ 19.14837024,  21.59583527,  24.10353431, ...,  63.20682698,\n",
       "          86.40186236, 113.27547195],\n",
       "        [ 17.77959845,  20.37130671,  23.31407055, ...,  79.92301626,\n",
       "         107.47936659, 130.59129493]],\n",
       "\n",
       "       [[ 28.5528387 ,  30.28264317,  30.38708419, ...,  94.47486697,\n",
       "         106.47252964, 106.98194498],\n",
       "        [ 27.38440474,  27.44002171,  28.0173131 , ...,  83.8167878 ,\n",
       "          95.18918414,  97.20869569],\n",
       "        [ 25.5803028 ,  25.69848886,  30.06500463, ...,  75.89715441,\n",
       "          87.19971112, 100.58111123],\n",
       "        ...,\n",
       "        [ 21.75048016,  24.94415719,  27.83411675, ...,  68.78226884,\n",
       "          74.72845511,  89.83859828],\n",
       "        [ 21.88649761,  24.77799619,  29.19238077, ...,  75.84806501,\n",
       "          84.70554483,  93.18803467],\n",
       "        [ 20.70139979,  24.67307754,  31.30640933, ...,  92.28818609,\n",
       "          97.72060531, 103.91897844]]])</pre></div></div></li><li class='xr-section-item'><input id='section-09f7ad15-b17c-4658-b1c7-14e17c455c4e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-09f7ad15-b17c-4658-b1c7-14e17c455c4e' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-8.5 -8.75 -9.0 ... -10.25 -10.5</div><input id='attrs-32e3e240-40ad-463f-83aa-87372cddaaae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-32e3e240-40ad-463f-83aa-87372cddaaae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d965cb3-2ae0-467a-98a6-1086c78382ab' class='xr-var-data-in' type='checkbox'><label for='data-1d965cb3-2ae0-467a-98a6-1086c78382ab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([ -8.5 ,  -8.75,  -9.  ,  -9.25,  -9.5 ,  -9.75, -10.  , -10.25, -10.5 ],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.5 12.75 13.0 ... 14.5 14.75</div><input id='attrs-f85f58e7-6a57-4891-aef4-f6764211f083' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f85f58e7-6a57-4891-aef4-f6764211f083' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d7fa8ff5-0bb4-4872-90e8-781feed18e6f' class='xr-var-data-in' type='checkbox'><label for='data-d7fa8ff5-0bb4-4872-90e8-781feed18e6f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([12.5 , 12.75, 13.  , 13.25, 13.5 , 13.75, 14.  , 14.25, 14.5 , 14.75],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>year</span></div><div class='xr-var-dims'>(year)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1991 1992 1993 ... 2018 2019 2020</div><input id='attrs-74107f16-c829-4b17-83f9-00823d7de474' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-74107f16-c829-4b17-83f9-00823d7de474' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6cf40bcf-2262-4ddf-96cd-8db206b19555' class='xr-var-data-in' type='checkbox'><label for='data-6cf40bcf-2262-4ddf-96cd-8db206b19555' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002,\n",
       "       2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014,\n",
       "       2015, 2016, 2017, 2018, 2019, 2020])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b84cf0f6-efa5-457e-a905-7c54c23240cd' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b84cf0f6-efa5-457e-a905-7c54c23240cd' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'tp' (year: 30, latitude: 9, longitude: 10)>\n",
       "array([[[ 21.4616785 ,  18.7635022 ,  17.74661811, ...,  87.31031117,\n",
       "         101.22735985,  99.42470998],\n",
       "        [ 15.98177266,  15.54583474,  14.44649318, ...,  81.11038638,\n",
       "          91.38898798,  89.93379177],\n",
       "        [ 13.8734001 ,  13.31245192,  17.27762415, ...,  73.37956523,\n",
       "          85.03072294,  99.39603707],\n",
       "        ...,\n",
       "        [  8.55466528,   8.45951503,   8.70086063, ...,  39.4234348 ,\n",
       "          58.55110131,  91.37894332],\n",
       "        [  8.42581978,   8.40089078,   8.78852306, ...,  42.79250256,\n",
       "          70.3595948 , 102.32259223],\n",
       "        [  6.97391092,   6.93309311,   7.92723976, ...,  63.57808463,\n",
       "          93.54256148, 119.72878794]],\n",
       "\n",
       "       [[ 15.04214108,  16.11098342,  17.02842545, ...,  85.10678835,\n",
       "         104.42210724, 108.66697739],\n",
       "        [ 13.50147401,  14.37006251,  14.93073675, ...,  76.5978719 ,\n",
       "          95.53149399, 100.61810602],\n",
       "        [ 11.29685542,  12.17347964,  16.60737188, ...,  68.01919076,\n",
       "          87.41943262, 105.02652137],\n",
       "...\n",
       "        [ 21.07750423,  23.26975741,  24.02228471, ...,  63.50396382,\n",
       "          76.39924615, 104.72484071],\n",
       "        [ 19.14837024,  21.59583527,  24.10353431, ...,  63.20682698,\n",
       "          86.40186236, 113.27547195],\n",
       "        [ 17.77959845,  20.37130671,  23.31407055, ...,  79.92301626,\n",
       "         107.47936659, 130.59129493]],\n",
       "\n",
       "       [[ 28.5528387 ,  30.28264317,  30.38708419, ...,  94.47486697,\n",
       "         106.47252964, 106.98194498],\n",
       "        [ 27.38440474,  27.44002171,  28.0173131 , ...,  83.8167878 ,\n",
       "          95.18918414,  97.20869569],\n",
       "        [ 25.5803028 ,  25.69848886,  30.06500463, ...,  75.89715441,\n",
       "          87.19971112, 100.58111123],\n",
       "        ...,\n",
       "        [ 21.75048016,  24.94415719,  27.83411675, ...,  68.78226884,\n",
       "          74.72845511,  89.83859828],\n",
       "        [ 21.88649761,  24.77799619,  29.19238077, ...,  75.84806501,\n",
       "          84.70554483,  93.18803467],\n",
       "        [ 20.70139979,  24.67307754,  31.30640933, ...,  92.28818609,\n",
       "          97.72060531, 103.91897844]]])\n",
       "Coordinates:\n",
       "  * latitude   (latitude) float32 -8.5 -8.75 -9.0 -9.25 ... -10.0 -10.25 -10.5\n",
       "  * longitude  (longitude) float32 12.5 12.75 13.0 13.25 ... 14.25 14.5 14.75\n",
       "  * year       (year) int64 1991 1992 1993 1994 1995 ... 2017 2018 2019 2020"
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Obtendo medias anuais\n",
    "media_anual = era_conv.groupby(\"time.year\").mean()\n",
    "media_anual "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "id": "45a24c6d",
   "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></th>\n",
       "      <th></th>\n",
       "      <th>tp</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">1991</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">-8.5</th>\n",
       "      <th>12.50</th>\n",
       "      <td>21.461678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12.75</th>\n",
       "      <td>18.763502</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13.00</th>\n",
       "      <td>17.746618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13.25</th>\n",
       "      <td>18.765602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13.50</th>\n",
       "      <td>35.255269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2020</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">-10.5</th>\n",
       "      <th>13.75</th>\n",
       "      <td>49.257741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14.00</th>\n",
       "      <td>74.982712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14.25</th>\n",
       "      <td>92.288186</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14.50</th>\n",
       "      <td>97.720605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14.75</th>\n",
       "      <td>103.918978</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2700 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 tp\n",
       "year latitude longitude            \n",
       "1991 -8.5     12.50       21.461678\n",
       "              12.75       18.763502\n",
       "              13.00       17.746618\n",
       "              13.25       18.765602\n",
       "              13.50       35.255269\n",
       "...                             ...\n",
       "2020 -10.5    13.75       49.257741\n",
       "              14.00       74.982712\n",
       "              14.25       92.288186\n",
       "              14.50       97.720605\n",
       "              14.75      103.918978\n",
       "\n",
       "[2700 rows x 1 columns]"
      ]
     },
     "execution_count": 173,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Criando data frame (Tabela) medias anuais\n",
    "\n",
    "data_anual = media_anual.to_dataframe()\n",
    "data_anual"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "id": "7ab37395",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "time        latitude  longitude\n",
       "1991-01-31  -8.5      12.50         9.410561\n",
       "                      12.75        10.221438\n",
       "                      13.00         9.085114\n",
       "                      13.25         7.512670\n",
       "                      13.50        12.642017\n",
       "                                     ...    \n",
       "2020-12-31  -10.5     13.75        27.581983\n",
       "                      14.00        35.435439\n",
       "                      14.25        44.057555\n",
       "                      14.50        61.271219\n",
       "                      14.75        84.559020\n",
       "Name: tp, Length: 32400, dtype: float64"
      ]
     },
     "execution_count": 185,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_data['tp']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "id": "1ac32167",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_use = df_data['tp']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "id": "414b7926",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Index data must be 1-dimensional",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-221-d5ec17cb10af>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mmedia_sazonal\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcol\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"season\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvmin\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m20\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvmax\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m40\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcmap\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'viridis'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mmask_lu\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmedia_sazonal\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m~/anaconda3/envs/pyprecis-environment2/lib/python3.6/site-packages/geopandas/plotting.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m    923\u001b[0m             \u001b[0mkind\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"kind\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"geo\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    924\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mkind\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"geo\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 925\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mplot_dataframe\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    926\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mkind\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_pandas_kinds\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    927\u001b[0m                 \u001b[0;31m# Access pandas plots\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/pyprecis-environment2/lib/python3.6/site-packages/geopandas/plotting.py\u001b[0m in \u001b[0;36mplot_dataframe\u001b[0;34m(df, column, cmap, color, ax, cax, categorical, legend, scheme, k, vmin, vmax, markersize, figsize, legend_kwds, categories, classification_kwds, missing_kwds, aspect, **style_kwds)\u001b[0m\n\u001b[1;32m    711\u001b[0m                 \u001b[0mvalues\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mvalues\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreindex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    712\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 713\u001b[0;31m         \u001b[0mvalues\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mcolumn\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    714\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    715\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapi\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtypes\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_categorical_dtype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/pyprecis-environment2/lib/python3.6/site-packages/geopandas/geodataframe.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   1297\u001b[0m         \u001b[0mGeoDataFrame\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1298\u001b[0m         \"\"\"\n\u001b[0;32m-> 1299\u001b[0;31m         \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mGeoDataFrame\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__getitem__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1300\u001b[0m         \u001b[0mgeo_col\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_geometry_column_name\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1301\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mSeries\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mGeometryDtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/pyprecis-environment2/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   2910\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mis_iterator\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2911\u001b[0m                 \u001b[0mkey\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2912\u001b[0;31m             \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_listlike_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mraise_missing\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2913\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2914\u001b[0m         \u001b[0;31m# take() does not accept boolean indexers\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/pyprecis-environment2/lib/python3.6/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_get_listlike_indexer\u001b[0;34m(self, key, axis, raise_missing)\u001b[0m\n\u001b[1;32m   1247\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1248\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_unique\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"is_overlapping\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1249\u001b[0;31m             \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_indexer_for\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1250\u001b[0m             \u001b[0mkeyarr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreindex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1251\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/pyprecis-environment2/lib/python3.6/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_indexer_for\u001b[0;34m(self, target, **kwargs)\u001b[0m\n\u001b[1;32m   4714\u001b[0m         \"\"\"\n\u001b[1;32m   4715\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_unique\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 4716\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtarget\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   4717\u001b[0m         \u001b[0mindexer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0m_\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_indexer_non_unique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtarget\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4718\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/pyprecis-environment2/lib/python3.6/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_indexer\u001b[0;34m(self, target, method, limit, tolerance)\u001b[0m\n\u001b[1;32m   2963\u001b[0m     ) -> np.ndarray:\n\u001b[1;32m   2964\u001b[0m         \u001b[0mmethod\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmissing\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclean_reindex_fill_method\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2965\u001b[0;31m         \u001b[0mtarget\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mensure_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtarget\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2966\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mtolerance\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2967\u001b[0m             \u001b[0mtolerance\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_convert_tolerance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtolerance\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtarget\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/pyprecis-environment2/lib/python3.6/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mensure_index\u001b[0;34m(index_like, copy)\u001b[0m\n\u001b[1;32m   5621\u001b[0m             \u001b[0mindex_like\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcopy_func\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindex_like\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5622\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 5623\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mIndex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindex_like\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   5624\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5625\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/pyprecis-environment2/lib/python3.6/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36m__new__\u001b[0;34m(cls, data, dtype, copy, name, tupleize_cols, **kwargs)\u001b[0m\n\u001b[1;32m    387\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mUInt64Index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    388\u001b[0m             \u001b[0;32melif\u001b[0m \u001b[0mis_float_dtype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 389\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mFloat64Index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    390\u001b[0m             \u001b[0;32melif\u001b[0m \u001b[0missubclass\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbool\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mis_bool_dtype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    391\u001b[0m                 \u001b[0msubarr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"object\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/pyprecis-environment2/lib/python3.6/site-packages/pandas/core/indexes/numeric.py\u001b[0m in \u001b[0;36m__new__\u001b[0;34m(cls, data, dtype, copy, name)\u001b[0m\n\u001b[1;32m     74\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0msubarr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndim\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     75\u001b[0m             \u001b[0;31m# GH#13601, GH#20285, GH#27125\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 76\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Index data must be 1-dimensional\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     77\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     78\u001b[0m         \u001b[0msubarr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0masarray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msubarr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: Index data must be 1-dimensional"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1300x300 with 5 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 300,
       "width": 1300
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 400x400 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 400,
       "width": 400
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#imprimindo plot da media sazonal\n",
    "\n",
    "media_sazonal.plot(col=\"season\", vmin=20, vmax=40, cmap='viridis')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "id": "39dfc493",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/amilcar/anaconda3/envs/pyprecis-environment2/lib/python3.6/site-packages/pyproj/crs/crs.py:53: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  return _prepare_from_string(\" \".join(pjargs))\n",
      "/home/amilcar/anaconda3/envs/pyprecis-environment2/lib/python3.6/site-packages/pyproj/crs/crs.py:294: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  projstring = _prepare_from_string(\" \".join((projstring, projkwargs)))\n",
      "/home/amilcar/anaconda3/envs/pyprecis-environment2/lib/python3.6/site-packages/pyproj/crs/crs.py:53: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  return _prepare_from_string(\" \".join(pjargs))\n",
      "/home/amilcar/anaconda3/envs/pyprecis-environment2/lib/python3.6/site-packages/pyproj/crs/crs.py:294: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  projstring = _prepare_from_string(\" \".join((projstring, projkwargs)))\n"
     ]
    }
   ],
   "source": [
    "import geos\n",
    "import geopandas as gp\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import sys\n",
    "import pyproj\n",
    "import geopandas\n",
    "from shapely.geometry import Point\n",
    "from functools import partial\n",
    "from pyproj import Proj, transform\n",
    "proj_4326 = Proj(init=\"epsg:4326\")\n",
    "proj_3857 = Proj(init=\"epsg:3857\")\n",
    "ANGOLA = gp.read_file('/mnt/e/Ajdata/fnlu_shp/')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "id": "03f1221e",
   "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>RECNUM</th>\n",
       "      <th>Name 1</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10</td>\n",
       "      <td>Luanda</td>\n",
       "      <td>MULTIPOLYGON (((14.56225 -10.43832, 14.55990 -...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  RECNUM  Name 1                                           geometry\n",
       "0     10  Luanda  MULTIPOLYGON (((14.56225 -10.43832, 14.55990 -..."
      ]
     },
     "execution_count": 217,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mask_lu = ANGOLA \n",
    "mask_lu "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "id": "6f2b537e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 220,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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a15gzfzM8z82raZfz79S7e+7/2Mk5cRsfh7WotiE/f3x6fvXEjCxb3bTZrxvYp3smf/l12XmHHtt0fe9XuhLvV7oS71e6Eu9XuhLvV9qCNUAoN3eAbCf++te/Zscdd9ysH4cffniS5IEHHkhDQ0OOOeaYDS4s/v73vz8DBw7MokWL8vTTT2/xXOPGjcszzzyTgw8+eJviR5LsvPPOSZLm5uY0Nzdv07kA2DzNLa05/9pn2i1+JMny1U15wxUjMmr28q16/aqG5vzf/ZMz5NIH850HpmxR/EiSpXVN+erdE7fq2gAAAED5WANkO9GvX78cdNBBm3XsHnvskeSlO0CSZK+99trgsZWVldljjz2ydOnSNcdviWuuuSZJct555230uKeeeio1NTU59NBDs/fee6/3mJqal7751rdv33Tv3n2LZwHYVo3NrWlobk1FRbJjz+3jr9jP3zkhD0xZ3O7XeTmC/PYdR+Xdx+6xWXf5tbSWcs3Ts/O/f5+UeTXb9liuK5+alY+8ct+ctM9O23QeAAAAoONsH9+dIWeeeWaeffbZLXrNLrvskiSZNWvWBo9pbW3NvHnz1jp+czU2NubPf/5zkuRtb3vbRo+98sorc9NNN+Ud73jHmmjy70aMGJEkOe6447ZoDoBtVVPflJ88Oi2/fGJGFq9qTLfKihw2eMdcePI+ueiU/VLVrZg3XP5lzPz8Ytj0Drve8tVNec/1o/PTx6fnJ/9xRE7ed8B6jyuVSrlv0qL8z9AJGTt/ZZtcu1RKLvrLmIz4zGvaZEF0AAAAoP0V8zsytInTTz89FRUVGTt2bB566KH1HnPNNddk6dKl6dOnT175yldu0flHjBiRpUuXZvDgwTnqqKM2euzLgWTo0KEZM2bMOvtramryq1/9Kkny7ne/e4vmANgWf352bo65/NFcct/kLF7VmOSlOw/GLViZz94+Psf9+LFMWNA234TvTO6bVJ33/Wl0Wa49YuayvOrnw3LBdc9kxtK6tLSWMnrO8vz0sWl5+x+fzuBv3pezr3yqzeLHy0bNXpFX/OzxPDVzWZueFwAAAGgfAggbNGTIkFxwwQVJkve85z350Y9+lGnTpmX16tWZOHFivvzlL+dzn/tckuRzn/tc+vTps+a1d955Z4477rgcd9xxG1zk6OGHH06SnHbaaZuc5ZxzzsmRRx6ZhoaGvOMd78gtt9ySxYsXp66uLg899FDOPvvszJgxI0cffXTe+973butvHWCT5tfU5+O3jskFfxqdGUtXb/C4cQtW5qSfPZ4/jJyV1U0tSZKP3vJ8zr/2mbS2ljpq3DZ14+i5efNVI1Pf3FrWOW56bl4O/f7DGfi/f88JP3k8n7tjfP46dsGaENUeRs9ZkZN/PiwX3vx8Ftc2tNt1AAAAgG3nEVhs1E9/+tMsWLAgDz30UC655JJccskl6xzzgQ98IF/60pfW2lZTU5MpU6YkSerq6tZ77pcDyIknnrjJObp165Zrrrkmb3rTmzJ//vx86EMfWueYgw46KDfddFN69OixyfMB24e7Jy7Mp/4yLqM+95oM7NN2fzY8O2dFLrj+mUxatGqzjq9rbMmH//x8PvmXsamqrMzKhuYkycGDdshXzjwwfXp0jb+O6xqb84W7JuQ3T84s9yhrNPxj3ZWOdtVTs3LbmPm57M2H5iOv3NdjsQAAAKATcgcIG9WnT5/cfvvtueqqq3LGGWdk4MCBqaqqyqBBg/KmN70pt912W37zm9+ksnLL3krLly/P6NEvPTrl6KOP3qzXHHLIIXnqqafyuc99Loceemh69eqVPn365Kijjso3vvGNDBs2LPvss88W/x6BYqpe2ZAP3fRcTtt/YHbq1b1NzlkqlfK9B6fklT9/fLPjx79a3dS6Jn4kyXcemJL/uPrpjJq9PPNWbNsi3e2tVCrlPdeN7lTxo9yWrW7Kx28dm1f+7PGMnOWxWAAAANDZVNTW1nbN529AOzvxxBNTWVmZ8ePHl3uUDlVdXZ0kGTx4cJkngU3b0Pt1xMxlOff3I/OqfQfk+vcdl35tEEBaW0v54tAJufzRadt8rvXp27Mql55zaD5w4l7ZqXfbBJu20tpayiduG5PfjZhV7lE6rZ5VlXn8k6fmpH122uAx/nylK/F+pSvxfqUr8X6lK/F+pS0cccQRaW1t3eAj8qG9uQMEgEKZsGBlzrpiRD796iH5y3+e2CbxI0kenbak3eJHkqxsaM5nbh+Xs64YkcdeXNJu19lSL4cf8WPjGppbc94fn86Cms59Jw8AAABsTwQQAArjkamLc+Zvh+fDr9g73zjr4FR1a7u/5i65d1KbnWtjnp69PGf85smc+/uRWb66qUOuuSGlUilfuXtiu4afIpm7oj7vuGZUGppbyj0KAAAAEAEEgIK47MEpOet3I7K0rimffvWQNj33PRMX5rFpS9v0nBtTKiVDJyzMgd99MP93/+TNXl9iWV1jqlc2tNkcX7vnhfzg4Rfb7HzbgydnLMsnbxuXUskTRgEAAKDcBBAAurwvD52Yr979QpLkp287IgfsskObnv/HZboDYkldU77x90k5+3dP5dEXF2/02BEzl+VNV43Mnt++Px+95fnM34ZHMTU2t+bzd4zPZQ9O3epzbM9+P3JWfjFsernHAAAAgO2eAAJAl/bFoePz/YenZp8BvfOn9x2fT5yyX5uef+HKhgyb3nF3f6zPstVNOeuKp/KbJ2ess2/q4lU5/9pn8qqfD8uImcvS3FrKlSNm5ZRfDMuyusYtvlZTS2ve96fR+cljHnu1LT53x/jcPXFhuccAAACA7VpVuQcAgK0xb0V9Pnvb2Nw6Zl6O2H/vPPv509K9Ddf8eNk3752U+ubWNj/vlmpsac1Ft43N1+95IeccOjiv2GenjJq9Ijc8Ozctres+bmnG0tU558qn8shFp6RX926bdY0XFq7Mm64amelL69p6/O1Oayl5z3Wj88SnT81Ru/cr9zgAAACwXRJAAOhyFq5syH/fMS63jpmXJDlp753aJX4kyf2TF7XLebfW0rqm/Gn03Pxp9NxNHvvUrOW5csSsfPo1/1wT5ZnZy3PPC9X5+hsOXrOtpbWUByYvyvnXPZMV9c3tMvf2aGVDc97y+5H5ztmHZHVTaxZWL0xdY0sqd1iSVY0tWdXYkrrGlqxqbE5dU8uabV953YE5/7g9yz0+AAAAdHkCCABdyoyldXnHNaMyes6KJMk5hw7OFe88ul2uNXzG0szo4ndDfPnuiVlS15j+vaoydXFd/vD0rOzQoypvOmxwDh28Y64dNSe/fGJGxi9YWe5RC2nWstX54I3PvfSLuuUv/dxnp42+5gt3Tchbj9wtvTfzzh0AAABg/QQQALqMv46dnwtvfj5L6pqSJB9/1b756usPSo+q9rn749EXl2Q9T5fqUuoaW/Kt+yavtW11U2Ne+bNh6dOjW2rc8dHpzFlRn+aWUtK93JMAAABA1yaAANAlXP7Ii/nS3yautd7F3jv1Ts8qn5LfGs2tJfGjkxoysE/69vJPNAAAANhWvroGoFObsGBl/vfvL2TohOq0tJayY89uOfPAXfLpVw/JzhXt+3iql+80gY509O59yz0CAAAAFIIAAkCntKqhOT99fFoufWBKVje1rtl+/XuPz38cuVuSpLq6ul1nOHnfndr1/LA+R+/Rr9wjAAAAQCEIIAB0Ojc/Ny+f/uvYVNc2Jkk+dep++cCJe+W+SYvWxI+OUNvQ0mHXgpcdvbsAAgAAAG1BAAGg02hqac2PHnkx//v3STlhr/757psOywE798kZB+6SJHnFPgPafYaZS+uy78A+aWhuyS+fmN7u14N/d/iuHoEFAAAAbUEAAaBTWFTbkI/eMia3j1uQdx69e373rqMzoE+PDrv+uPk1GT5zWS59YEredcweeX7eioyavaLDrg8v23dA73KPAAAAAIUggABQdrc8Py/vvX50mltL6VVVmY+8cp8OjR9J0lpKPnHb2LS0lvKjR17s0GvDy3bu0z079PTPMwAAAGgLleUeAABGzFyW5tZSkuTytx6RNx46uMNnmLp4VaoqKzr8uvCv9t7J3R8AAADQVnzEEICy+tlj0/LjR6flAyfslYtO3S+v2Hunssxx1VOz0tDcWpZrw8v27N+r3CMAAABAYQggAJTNtCWr8qsnZuTvF76yLHd9vKy5pTXPzbPeB+XXUiqVewQAAAAoDAEEgLJ5fl5Nbv1/J+boPfqVdY5fPzkj82sayjoDJMmqxpZyjwAAAACFIYAAUBbTl9TlLYfvmu7dyrsc1Q2j5+SLQyeWdQZ4mQACAAAAbcci6ACUxWduH5fVTVv+zd6bn5uXBTX123TtUqmUxubWjJlXk4/fOtbaH3QatQ3N5R4BAAAACsMdIAB0uOqVDVnV2Jx+vbpv0etKpVI++ZexOWnvnXL3ha9cZ//wGUuzyw49svMOPbJjj6r0qFp/57921Jz84OGpmVhdG0su0Jm4AwQAAADajgACQIe7dcz8nHHALlv8uiuGz8ziVY05ds911wz53fCZ+crdE3PgLjtk4cqG7NS7ez5/+v553/F7pVtlRZbWNeYLd07I5EW1GT5zWVqFDzqhBSsbMm5+TY7cvbzr4gAAAEARCCCQpLq6OosXL15rW0NDQ3r06FGmiaC4ltY15vsPT82Yi0/foteNm1+zZq2Ox15ckkvunZTJM+dm3or6zGvulSmLVyVJRs5aniSZuWx1/t+Nz+WK4TNz6OAdc8Pouan3qCs6uZbWUj5y8/N54tOvTrfKinKPAwAAAF2aAAJJrrzyylx22WXrbB80aFAZpoHiKpVK+dLQiZm9fHUW1jakf+/NfwTW0AkLs/If6yM8MWNZnpixLKlb/tLOPjtt8HVPzliWJ2cs24apoWM9NWt5fv3EjHz6NUPKPQoAAAB0aQIIJLnwwgtz3nnnrbXt/PPPdwcItLFrnp6Tq56alRP37p+DB+242a9raS3lbxOr23Ey6Fy+es/EvO3I3bL3gN7lHgUAAAC6LAEEkgwePDiDBw9ea1vPnj1TWbn+BZSBLVff1JJfPzkjSfKl1x64Ra+9e+LCDJu+tB2mgs6ptqElF/1lbO788EmpqPAoLAAAANgavrsLQLtbsbopJ/98WI7YrW9+/Y6j0rAFa3E0NrfmC3dNaMfpoHMaOmFhbn5uXrnHAAAAgC5LAAGg3V0xfGbedczuuerdx+Q3T87IR28dk/k19Zv12v8ZOiGTF61q5wmhc/rM7eOytK6x3GMAAABAlySAANDunp9Xky+/7qA8P29Fpi+tS11jS77x90kbfU2pVMrFd47Pzx+f3kFTQudTXduYL9zpDigAAADYGtYAAaBd3T1xYWYsq8tZV4zIQ1MXr9l+1VOzst/A3vnSaw9MVbe1e/yk6tp854HJuf6ZuR09LnQ6f3h6dg7YpU+6VVRk0arGVNc2pHplYxatasjOfXrki689MK8/eBdrhQAAAMC/EUAAaDdTFtXmfX96NstXN613/9fvmZS/TajOZ18zJEly+7gFaWot5e8vVGdVY0tHjgqd2tfv2fAdUw9MWZyT9t4pX3v9QTn38F1TWSmEAAAAQCKAANCOrnpqVlpaS9mrf6/MWbH+NT+Gz1yW4TOXdfBkUCxPz16et/3h6Ry1e988ctEpGdinR7lHAgAAgLKzBggA7ebo3fvl8U+dkr9+6KR4Og+0v7HzV+Y7908p9xgAAADQKQggALSb952wV47Zo3/qGltSKpV7Gtg+/PKJ6ZmyqLbcYwAAAEDZCSAAtLuJ1SvLPQJsN5paSvni0InlHgMAAADKTgABoF1UXHxXkmTc/Jp8/NaxZZ4Gti+3j1uQR6YuLvcYAAAAUFYCCADtasay1eUeAbZLn79zfFpaPXsOAACA7ZcAAkC7aW0t5bdPzij3GLBdenZuTa4bNafcYwAAAEDZVJV7AACKqXT5uRkxc1n+NrG63KPAdutLf5uQ+uaWvPPo3bPLjj3LPQ4AAAB0KHeAANBuGppbyj0CbNeqaxvzidvGZvdv3Z9zfz8yN46em1UNzeUeCwAAADqEO0AAaDdNLdYfgM6gubWUoRMWZuiEhdmhR7e87cjd8t7j98wbDh6U7t18HgYAAIBiEkAA2CYvLFyZR6ctyYNTFue0/XfOTr2755g9+uXI3frm+w9NLfd4wL9Z1diSP42emz+NnptdduiRdx+zR953/J551X4DUlFRUe7x1qu1tZRn5qzIPS9U57l5K3Lcnv3zmiEDc8aBu5R7NAAAADoxAQSArTZq9vK88XcjcuEr983XX3/wmm2f+svY/Ol9x2fErGVlnhDYmMWrGvPrJ2fk10/OyH4De+e9x+2Z9x2/Vw7frW+Hz1IqlbKqsSWLahuzaFVDFtU2ZsHKhjz64pL8fVJ1FtU2rjn2r2MXJEm+edbBueSNh3T4rAAAAHQNAggAW+13I2bm2288JBedut+aT44fvUe/fPiV+yRJPnTSPvnFsOnlHBHYTDOWrs53H5ya7z44Ncfs0S/vO37PvOfYPbP3gN5tep3mltY8NHVxbhszPzOXrc6iVY1ZVPtS8Khvbt2ic33rvsk5Ya/+OfeI3dp0RgAAAIpBAAFgqyyta8x1o+bknh165I2HDs6Bu+yQJGlqac38mvrs2LMqQycsLPOUwNZ4fl5Nnp9Xky/9bWLuvfDkvOGQQdt0vlKplKdmLc8No+fmz8/NTfW/3M2xrS66bWxOP2Dn9OvVvc3OCQAAQDEIIABslaV1Tfn22Yfks6/ZPz2q/rmI8rNzV+SVPxuWnlWVadjCT3MDnUuplPzyielbHUAmLFiZG56dmxtGz830pXVtPN1L5qyoz9fufiG/ePtR7XJ+AAAAui4BBICtcuAuO+R/XnvgOtubWkpJIn5AQQydsDAzl9Zl34F9Nuv4WcvqctOz83LDs3Pz/Lyadp7uJb96ckbee/yeedV+AzvkegAAAHQNAggAbWrs/I75hifQMVpLL633c+mbDtvgMc0trbnumTn5w9Oz8/i0pR043UtKpeTCW8Zk9OdOW+uONAAAALZvvkIEYKuVSqW0tJYyv6Y+j0xdnMbm1vz5uXnlHgtoY1c+NSuNG7ir67EXl+SEnzyeD//5+bLEj5eNX7AyP3h46mYdWyqVNvj7AQAAoDjcAQLAVvvOA1Ny7ag5Wd3Uknk19Tl9/53zyItLyj0W0MYW1Tbm6dnLc+qQfz5ias7y1fmfuybkpk4UPf/v/il559G759Bd+66zb+HKhtw/edGaHzv0qMoN7zs+J+2zU8cPCgAAQIcQQADYas/MXp6pi1et+bX4AcX15IylOXXIwDQ0t+THj07Ldx6YkrrGlnKPtZbGltZ89NYxeeQTp6ShpTXDpi3N/ZMX5b7Ji9azHklDTvnFsFx6zqH5whkHpLKyoiwzAwAA0H4EEAC22u79epV7BKCDPDljWYZOWJj/vn1cXlxSV+5xNujxaUvzip89nvELVqZ+E4+5am4t5Ut/m5h7Jy3Kte89Nnv2791BUwIAANARrAECwFY7fq/+5R4B6CB3jF+Qc38/slPHj5c9M2fFJuPHv3po6uIc86NHc8e4Be04FQAAAB1NAAFgq+26Y89yjwB0kFKp3BO0ryV1TXnbH57ORbeNSV1jc7nHAQAAoA0IIABstSN375tunpsPFMhvnpyZk376eMass2YIAAAAXY0AAsBW23/nHbJTL8tJAcUyYWFtXvGzx/OLx6enVPRbXwAAAApMAAFgm/zgLYeXewSANtfQ3JrP3D4ub/n9yFSvbCj3OAAAAGwFH9uFJNXV1Vm8ePFa2xoaGtKjR48yTQRdx6v2G1DuEQDazd0Tq3P05Y/mmvccmzceOrjc4wAAALAFBBBIcuWVV+ayyy5bZ/ugQYPKMA0A0JksXNmQs698Kp8/ff98902HpmdVt3KPBAAAwGYQQCDJhRdemPPOO2+tbeeff747QACANX786LQ8NGVx/vS+43P4bn3LPQ4AAACbIIBAksGDB2fw4LUfa9GzZ89UVlomBzbl2bkryj0CQId5bl5Njv/JY/nemw/LZ149JJWVFeUeCQAAgA3w3V0AtsnVI2eXewSADtXQ3JrP3TE+b7hiRGYtqyv3OAAAAGyAAALAVpu+pC4jZy0v9xgAZfHQ1MU56keP5vpn5qRUKpV7HAAAAP6NAALAVvvhI1OzsqG53GMAlE1NfXM+cMOzefe1z2TJqsZyjwMAAMC/EEAA2CqTqms9/grgH24dMz9H/vCR3DNxYblHAQAA4B8EEAC2ypUjZqahubXcYwB0GgtWNuRNV43MJ24dk1XujgMAACg7AQSgC5m4cGXGza8p9xhZuLIhf3ja3R8A6/Pb4TNz7I8fy4iZy8o9CgAAwHatqtwDALBhq5tacuPouRk6cWFuH7cgL6+x27OqMmO+cHoOHrRjWeb63B3js7SuqSzXBugKpi5elVN/MSxfOfOgfOMNB6dHlc8dAQAAdDQBBKATWlrXmF88Pj0/fmxaaurXfYxKQ3Nr/jZhYQ4+veMDyLj5Nbnx2bkdfl2Arqa1lFz6wJTc80J1rrvguBy+W99yjwQAALBd8VE0gE5m1OzlOeqHj+aS+yavN34kSWVFske/Xh08WTJrWV0+cMOzHX5dgK5s9JwVOf4nj+XyR15Mc4u1kwAAADqKO0AAOpH6ppZ88i9jM6+mfoPH7LJDj/TrVZVHpy3J49OX5rUH7pwlq5oyZ8XqvGrfATnnsF1TcfFdKV1+bpvO1tJayhfumpDn5pV/DRKArqahuTVfuGtCbnpubq569zE5Zo/+5R4JAACg8AQQgE7k8WlLM3LW8vXu61lVmb/854k586Bd0rOqW5KkVCrloSmLc9Oz83Lb2PnpXlmZmV8/s83jR5J89e6JueX5+W1+XoDtyajZK3LCTx7P/5xxQL5x1sHp3b1buUcCAAAoLAEEoBO56qlZG9x3+4dOytmHDl5rW0VFRc48eFDOPHhQJlXX5oXq2uzWDo/GemTq4vz88eltfl6A7VFLaynfe2hqbh0zP1e88+i87qBdyj0SAABAIVkDBKCTGDlrWW5+ft569+3Wt2dO3W/gRl9/yOAd8x9H7tbmc01YsDIfvPHZ1Dd7bj1AW5q6eFXO/O3w/Nefn8vSusZyjwMAAFA4AghAJ3DfpOq87Q9Pr/n1wYN2SEXFP/fvO6B3+vbq2Jv2WltLufqpWTnxp49l9vINr0kCwLa5euTsHPb9h3Pzc/NSKpXKPQ4AAEBheAQWQBnVNjTn038dlz8+PXut7aP++7Q8O3dFZi6ry+zl9bnw5H06dK75NfU57w9P56kNrEcCQNuqrm3M+dc9k+ue2TW/fvtR2XtA73KPBAAA0OUJIABlUCqV8oth0/Pb4TMzcWHtWvv26t8rvbpX5rQDdk6yc4fPdvvY+bn4rgmZtqSuw68NsL0bOmFhHnlxcb73psPyiVP2S2VlxaZfBAAAwHp5BBZAB2tobskHbng2n719/DrxI0l26NEt37x3UiYuXNmhc42ZV5NTfj4s77z2GfEDoIxqG1ryqb+Oy6t/+UTGL+jYvwsAAACKxB0gAB3sM38dlz+NnrvB/ZMWrcplD07NitXN+dU7jmrXWeqbWvLt+yfnhtFzM2dFfVpaPXseoLMYPnNZjvvxo/nK6w7KV19/YHpWdSv3SAAAAF2KO0AAOtD8mvpc9dSszTr2LYcPbtdZSqVSPn7rmFz24NTMXLZa/ADohJpaSvn2/ZNz7OWPZdi0JeUeBwAAoEsRQAA60AvVtdmczvCqfQfk7EPbN4D86okZuWbUnHa9BgBt44Xq2rzmV0/mI39+PkvrGss9DgAAQJcggAB0oPsmLdqs4z556n6pqGi/hW/vnrgw/33H+HY7PwDt4/cjZ+XQ7z+c60bNTqnkzj0AAICNEUAAOtD9kzcvgCxe1b6f7r130iKPvALoohbVNuaDNz6X1/92RCYvqi33OAAAAJ2WAALQQe4avyCj564o9xhJkpGzlpd7BAC20UNTF+eoHz6ab907KQ3NLeUeBwAAoNMRQAA6wNfunph3XDMqm/u0kqmLV7XbLMvqGvPikvY7PwAdp7GlNZfcNzlH/+jRPDx1cbnHAQAA6FSqyj0AQNH9bvjMfPfBqZs87rg9++WNhwzOuYfvmhP27t9u8/xl7IIsqrWALkCRTF60Kq/7zfB84IS9cvlbD8+gHXuWeyQAAICyE0AA2klDc0u+/LeJ+dnj09e7/5T9BuTVQwbmNfvvnJP23imDd+zRrgufv+zxaUva/RoAlMd1z8zJ0AkL88NzD8+HTto7lZXt//cKAABAZyWAALSD1U0tueC6Z3LH+IVrbe/XqyofOGGvfPTkfXP0Hv06fK7lq5ty03PzOvy6AHScZaub8pGbn88fn56d377z6ByxW99yjwQAAFAWAghAG1tc25AzfzsiY+bXrLX9v16xT3701sOzU+/uZZosuWrErDQ0t5bt+gB0nGHTl+bYyx/NF197QL7+hoPTu3u3co8EAADQoSyCDtCGJi5cmddfsXb8OGTQDrnrv16Rq84/pqzxo7ahOT94ZNNrkQBQHM2tpXz3wak58oeP5Pax81Mqlco9EgAAQIdxBwhAG7ln4sL8183PZ35NQ5KXHnf1+dP2z5ded2B6dYJP3Q6bvtTi5wDbqWlL6nLeH0flmD365X/fcFDOO3J364MAAACFJ4AAbKNVDc25+K4JuWL4zLW2f+60/fPNNx5SpqnW9tCUxXn7H58u9xgAlNnz82ryzmueyRG79c3XX39Q3nXMHukmhAAAAAUlgECS6urqLF68eK1tDQ0N6dGjR5kmoqt4cPKiXHjLmExfWrfW9v69qvLuY/Yo01T/1Npayu3jFuQjNz+f1U3W/gDgJeMXrMwF14/OJfdOytdef1AuOG7PVHXzdFwAAKBYBBBIcuWVV+ayyy5bZ/ugQYPKMA1dweqmlnxp6MT88onp+ffHqfftWZX7PnZyDt+tb3mGS9LY3Jo7xy/Ix28dkyV1TWWbA4DObdKiVfngjc/lW/dNzlfPPCgfOHGvdBdCAACAghBAIMmFF16Y8847b61t559/vjtAWK9HX1ycj9w8JlMXr1pn3+79eubWD56YV+wzoAyTJYtqG/LjR6fldyNmZqnwAcBmenFJXf7r5ufzfw9Mzpdfd2DetG/P9Kwq//pVAAAA20IAgSSDBw/O4MGD19rWs2fPVFb6BCT/NHNpXb5x76RcO2rOevfv2b9Xhn3q1Ow3sE+7XL/i4rvW/Hfp8nPX2f/Fuybk9yNnCR8AbLUZS1fn47eOze7dVuczrxmS/z575/Tq3jYhpFQqZeay1Rk5a3l27NktZx8y2ELsAABAuxJAADbDotqGnPCTxzb4OKmKiuQP5x+7wfjxy2HT01oq5bwjd8/eA3pv8zwVF9+1TgQZOXu5+AFAm5i/siFfufuF/Hz0snzxtQfmoyfvkz49tuxLh8W1DXl69vKMnLU8I//x8+JVjWv2H7TLDvn0q4fkP0/aO317+bIEAABoe77SANgMP3rkxY2upfGeY/fMGw5Z/5oxy1c35bO3j0trKbn4zgl5+BOvyqv333mLrv/y3R/ru/PjX68DAG1pfk1DPnfH+Fz24JR84YwD8olT9suOPdf9EqKusTmj56xYEzqenr0805bUbfTcUxavymduH5ev3fNCPvyKvfPpVw/JAbvs0F6/FQAAYDskgABswl/Hzs8PHn5xo8dcePI+691e39SSQ773UFr/sVB6c2spUxfXbXEASTYcP8YvWJkLrn8mY+ev3OJzAsDmqK5tzBeHTsz3H5qaz59+QN54yKCMnrtizR0e4xasTMvLf9ltoZUNzfnZ49Pz82HT8+bDds1nXzMkZx60SyoqPB4LAADYNgIIwEaMmVeTC64fvdFjqiorcuwe/da774Xq2lTXNq617dQhW75A+sbu/PjFsOniBwAdYkldU752zwv52j0vtPm5S6Vk6ISFGTphYY7YrW8+8+ohef8Je27xo7cAAABeZoVngA1oaS3l/OueSUNz6waPqahILnnjwRnQp8d69z8zZ8U624ZNX9pmMybJ8/Nq2vR8AFBu4xeszMduHZO9vv1AvjR0QmYt2/jjtAAAANbHx6kANuCu8QvyQnXtOtt369szHzhhr7x6yMAct2f/jS5qPno9AWRZG6/VccJe/TNi5rI2PScAdAbLVjflBw+/mB898mLOO2r3fPY1Q/LqIQM9HgsAANgsAgjABvx82PR1th27R78M+9Sp2WE9C8Cuz7/f7VFVWZET9urfJvO97IMn7pVfPTGjTc8JAJ1Jaym5bcz83DZmfk7Yq3+ue+9xOWzXvuUeCwAA6OQ8AgtgPV5YuDKPTVv3UVXH7dl/s+PHvBX1mVi99tocZx86OKcfsEubzPiyY/bolwG9u7fpOQGgs3pmzoqc/PNhGTphYblHAQAAOjkBBGA9Ln1wSlpaS+ts792922af4yePTUtTy9rneMU+O23raOuobWjJyobmNj8vAHRWNfXNeevVI3PZg1NSKq379zUAAEDiEVgA65i6eFX+/Ny89e7r02PzAsjfX6jOzx9f9xFaP350WoYM7JP3n7DXNs34r6oqK9K9W0Wa1xNsAKCoSqXkq3e/kDHzavL7849Jnx6+tKHzWrKqMb8dPiMrVq//Qyub+lfcbn175r9euU92ctcvAMAW8VUCwL9YsqoxH7tlzDp3bryscjPWXJ23oj4XXD86jS2t6+xramlNTX3b3q3Rv3f39O/VPaubGtr0vADQFdz03LxMWlSb2z90UvYZ0Kfc48Ba6hqb87PHp+d7D03d5n8Dfuu+yfnkqfvlv0/bP7v27dlGEwIAFJtHYAEkaWhuyW+fnJH9v/tgHpq6eIPHveHgQZs811fvnpjlq5vWu+/Kdx2Ti07db2vHXK+mltY0rSe2AMD24tm5NTnxp4/n8WlLyj0KJEmaW1pz1YiZOeiyh/PVu19okw/ArGxozvcempr9vvNAPvPXcZm1rK4NJgUAKDYBBNiutbaWcuPouTns+4/kE7eN3eQXp/dNWrTBfS8uXpU3X/VUrhk1Z4PHVHXbjFtIttDqppbUNbW0+XkBoCtZVNuYM387PL8bPrPco7AdK5VKuXPcghxz+aO58JYxmVdT3+bXqG9uzS+GTc8B330oz85Z0ebnBwAoEo/AArZbC2rq8/Y/jsrwmcs26/gdenTLf71yn/Xum76kLmf+dnhmLlu9yXO0tX69uufU/QbmgSkbvnMFALYHTS2lfOzWMXlu3or87G1Hpns3n/ei4wyfsTRfHDoxw6Yv7ZDrnXXIoBy7Z78OuRYAQFclgADbpefmrsh//OHpzFpPsBjYp3tef9Cg9Kh66W6NGUtX55BBO+aiU/fNIYN3XOvY6Uvq8r2HpuSm5+Zt8u6Rg3bZIWcfMrjtfhP/wnOgAeCffvPkzIxfsDK3/r8TM2hHf0fSviZV1+Yrd0/MX8cu6LBr9unRLb96+1GpqGj7u4sBAIpEAAG2O1MXr8rrfzs8S+rWv07H9958WC48ed/NOtf3HpqS342YtVnHHr7rjqncnFXUt1CptP4F2wFge/bYtKU56aeP5/YPnZRj9+xf7nG2Ww3NLVlU25hFtY2pb27JyfsOKMw37efX1Odb903OVU/NSktrx/577NtvPCT7DezTodcEAOiKBBBgu9Lc0poLrn9mg/EjSfbs32uzztXaWsrouZv/3OXTDth5s4/dEhffOSFDJyxsl3MDQFc2c9nqnPrLJ/LH9xybdx2zR7nH6fJKpVJqG1qyeFVjFq1qWBM21vz3qsYsqm34x/6X9q1sWPsO2fOP3SO/e9fR6dere5l+F9uupr4pP3z4xfz4sWmpa+z4ddiO27NfPvuaIR1+XQCArkgAAbYrd4xfkFGzNx4tbnx2bt502K6bPNfwmcs2ea6XnXPo4Hzy1P0269gtdfTu/dLUwZ86BICuoq6xJe++9pl8/fU1+dYbD2mXuzGLbNayutz83Pz8+fm5GTt/ZRqaW7fpfH9+bl5GzV6eP3/ghJyw905tM2QHaWxuzW+Hz8j/3T8li1c1lmWGyorkd+86JlXWtwEA2CwCCLDdaG0t5dv3TdnoMUfv3i8/eesRmzzXvBX1+dLQCZt13W6VFfnV249Kz6q2XwC9sbk1375/clk+fQgAXcl3HpiS28ctyOsP3iWn779zTjtg5wzs06PcY3VKC1c25Jbn5+WmZ+fmiRnL2vz8Ly6py6t+MSw/OvfwfPrVQzr9I7FaW0u5+fl5+do9L2TakrqyzvLpVw/JiV0sHAEAlJMAAmw3bnpubsbMr9ng/q+//qB85cwD06fHxv9ovGv8gnzyL2Mze3n9Jq/ZrbIiP/uPIzJk53Wf0Vxx8V0pXX7upgffiFnLV5ftE4gA0NWMW7Ay4xaszE8fm54kOWr3vjnjgF1y+gEDc9r+O2/XC6YvrWvMX8bMz03PzcvDUxenvW8ubWop5bO3j89DUxbn6vcc22lj1IQFK/OxW8dk2PSl5R4l/XtV5f/OPrTcYwAAdCkCCFB4TS2tuXrkrHz5by9s8Jhj9+iXr73+oPTqvuG7NBbVNuTCm5/PHeM3f72Nq88/Jh88ce91tldcfNdaP29tCPl/Nz67zrO1AYDNM3b+yoydvzK/GPZSEDl81x1z+gE75/T9d87pB+yc3fpt3rpgXVVNfVPuHL8wNz07N/dOWpTmMjxS847xC3Pcjx/LTe8/Pq/ab2CHX39D6ptacukDU/L9h6emqaVzPGr0kME7pm8vX8IDAGwJ/3oCCu3ZOSty0V/GZsTMDT++oWdVZa4+/9iNxo8kOf+6Z/Lw1CVbdP2zDh60RcdvqdoGj74CgLYyYWFtJiyszW+enJkkOWTQDi8FkX/8GLxjzyxf3ZRlq5te+rnuX/77H79eXv+Pn1evva+5tZR9duqdIQP7ZL+BfbLfwN7Zb0Cff/y6d3bq3b1DHgVV19icuydW56bn5uVvExamfhvX9GgLs5atzmt+9WQuPefQ/M8ZB5R9nZaHpizOx28dkymLV5V1jn+374De5R4BAKDLEUCAwpqyqDav/c2TWVG/8TskLj3n0By3V/+NHlO9siGPTdvyRx88M2dF3nz4up8eLV1+7pq7P7ZWbUPzRh/pBQBsm0mLVmXSolX53YhZbXK+lx/BtT79elX9I4j0/kcg6ZP9BvTOkJ37ZO+deqd75UuLXpey9t0IpX/5ZWmt7f/8VWspGT5zWW56dm7uGL+gU36AoqW1lC//bWIenro4115wXAb37fjHkS2ubcgX7pqQa0bN6fBrb459B6z7SFUAADZOAAEKafiMpfnK3S9sMn4MGdgnn3r1fps8398mLkzLVjwW4hfDpufNh++60WO29vFXfTZxxwoA0HXU1L/0wYbt/cMN905alGN//GhueN/xOePAXTrkmqVSKdeOmpOL7xyfJXVNHXLNreEOEACALVdZ7gEA2lJraym/fmJGXvub4Xn0xY0/rmqn3t3zs7cdkZ5VGw8JLy5etebZ4JsysE/39P/Hs5l7d6/M24/afYPH/nv4qLj4rm2+KwQAoKubX9OQM387PN+6d9JWfQBlS0xZVJvX/3ZE/vOm5zp1/EgEEACAreEOEKAw5tfU59N/HZfbxszf6HE9qyrzjqN2z3ffdGj2HbjpRwksXtWYZ+du3qcxLznrkHzsVfvmlufnZfd+vXLwoB02evy/RpAtvRPkiRlb/kguAICuoLWUXHLf5Dw6bUmuf+/x2aN/2y5I39jcmh88PDXfeWBKGjrBOiibwyOwAAC2nAACFMKDkxflQ39+LrOX12/0uP137pPhn371Fj1X+pg9+mW3vj2zYGXDJo/97zvG5YXq2pdmmrIo3zzrkFxw/J6bfa0tMXlR51qYEwCgrT08dUmO/fGj+dXbj8rJ+wzIHv17pds2LpI+bNqSfOzWMZmwsLaNpuwY7gABANhyAgjQpTW1tOab907KDx5+cZOPSDht/4G5/K1HbPGimr26d8vv3nV0Lrh+dFY1rn/R0D49uuWUfQfkjYcMzpj5NbnumTl5y+G75vxj99iia22JuycubLdzAwB0FotqG/Pua59JklRVVmTvnXpn3wEv/+iTgVmVvXbqnWMrd8jeO/VOj6r1P+l5WV1jvvy3iW22qH1H2ql39/Tv3b3cYwAAdDkCCNBlTVlUmw//+fkMm77hR0EdtMsO+eCJe+U/T9o7e/bvlYqKrfvE4LlH7Jbl3zk7R/zwkTV3XvToVpnTDxiY847aPR84Ya/s2POlP1JLpVJ+f/4x6VZRkcpt/ITihtw+dn7+Om5Bu5wbAKCzam4tZfrSukxfWvfPjXXLX/q5z9RUVCR79Ou1Jo68HEpKSb513+Qs3Iw7ejsjd38AAGwdAQTokkqlUi66bewG40ffnlX5wVsOy8dP2a/NrlnVrTKXnnNoHp66JOMXrsy333hITjtg53WOq6ioSPdu7RM+Xnb/5MUpte+aoAAAXU6plMxdUZ+5K+rz5Ixl5R6nzQggAABbRwABuqTRc1bkgSmL17tvhx7d8sSnT81Ru/dr8+u+85g98s5j2u+xVpujsbk1906qLusMAAB0HAugAwBsHQEEklRXV2fx4rW/md7Q0JAePXqUaSI25f/un7ze7RUVyc/fdmS7xI/OYMXqprzzmlF5cUndpg8GAKAQ3AECALB1BBBIcuWVV+ayyy5bZ/ugQYPKMA2b8qth03PH+HUXAD92j375n9cekPcev1cZpmp/pVIpH7n5+Q3e+QIAQDEJIAAAW0cAgSQXXnhhzjvvvLW2nX/++e4A6YTuGr8gn79zwlrb+vasyqXnHJqLTt0v3dpp0fHOoLq2MbeOmV/uMQAA6GAegQUAsHUEEEgyePDgDB48eK1tPXv2TGVlZZkm4t+1tpby7fsn57IHp6axpXXN9qrKitz9kVfk1fuvuxh5R5mxtC4zltbljAN3adfrfPu+9T/2CwCAYnMHCADA1hFAgE5vxtK6vPf60Rk+c9k6+y4959Cyxo/HXlySc656KvVNLTnvqN3zmiEDs3x1U2Yvr0/fXt0yZGCf1De15qbn5mbyolUZ+4UzMmTnLf8EX0trKdePntMOvwMAADq7656Zk0+9er/0rOpW7lEAALoUAQTo1B6ftiTv+9PozF5ev86+Nxy8S/77tP3LMNVLbn1+Xt593TMplV769W1j5ue2TTyi6lv3TcpFp+6XV+wzYLOv09payiX3TkpNffO2jAsAQBf1hbsm5BfDpufScw7NBcftmcoCP/YVAKAteb4P0Cm1tpby88en5awrRqw3fnTvVpGr3n1MelR17B9j05fU5Z6JC/OXMfPzXzc/vyZ+bK5rRs3Jqb94Is/PW7HZr/ngjc/mOw9M2cJJAQAokpnLVuf9NzybE3/6WB6YvKjc4wAAdAnuAAE6nYbmlnzytnH5/chZGzzmw6/YJ/uUYTHI/xk6YZN3eWxKc2spb7hiRB676JQM7NMjz8+rycA+3fPzYdOzV/9eeesRu+WO8Qsyv6YhhwzaITc8O7eNpgcAoKt7dm5N3nDFiJx18KB8/y2H5dg9+5d7JACATksAATqd79w/ZaPxY9COPfKV1x3YgRO9ZGV9cx6ZurhNzrWotjFH/ujRVOSlIPKvvvvg1Da5BgAAxXXf5EW5/yeL8r7j98x3zj40+w7s+A8HAQB0dh6BBXQqT05fmsse2nAAqKqsyFXvOqbDv8BramnNh/78XJbUNbXZOVtaS+vEDwAA2FylUnL9M3Nz8PcezhfuHJ+ldY3lHgkAoFMRQIBOY2V9c977p9Fp2UgU+N83HJy3HrlbB071khtGz93mR18BAEB7aGxpzeWPTssB330oP3x4auqbWso9EgBApyCAAJ3GL5+YnpnLVm9w/0G77JCvnNnxj75K4tN0AAB0estXN+WLQyfm4O89lGuenr3RDxYBAGwPBBCgU1hZ35yfPjZto8e89/g9071bef7YOnnfAWW5LgAAbKnZy+vznzc9l+N+/Gj+/kJ1SiUhBADYPlkEHegUfjdiZqprN3yXxXF79svFpx/QgROt7cEpbbP4OQAAdJSx81fmnCufytG798v/O2mvvO/4vbJr357lHgsAoMO4AwQou7rG5vzwkRc3uH/Qjj1yx4dekb69ytNsx82vyfcf3vDC7AAA0JmNmV+Ti++ckD2/fX/O/f3I3Pr8vDQ0WycEACg+d4AAZXfVU7OycGXDeve97/g985UzD8reA3p38FT/9MenZ6e2wReIAAB0bS2tpQydsDBDJyzMgN7d857j9sh/nrR3Ttp7p1RUVJR7PACANieAAGW1uqkllz24/rsrBvbpnh+85fDs0b9XB0/1Twtq6nP5oxtfmwQAALqaZaub8psnZ+Y3T87MoYN3zP87ca984MS9smf/8n3wCACgrXkEFlBWVz81KwvWc/dHRUVy7QXHlTV+tLaWcu7VI8t2fQAA6AgvVNfmK3e/kH3+74G88YoRuXH03Kxucgc0AND1uQMEKJvahuZ876H13/3x1TMPypsP37WDJ3pJxcV3JUn+cP6xGTV7RVlmAACAjtZaSu6bvCj3TV6Ufr2q8u5j9sjXX39Q9h3Yp9yjAQBsFXeAAGVz8Z3jM2dF/TrbLzx5n3znnEPLMNE/lS4/N39+fm5ZZwAAgHKpqW/OVU/Nymt+9UReXLyq3OMAAGwVAQQoi1uen5crn5q13n3H7N4vSbKyvrkjR1rL8tVNGTZ9admuDwAAncHs5fU57VdPZlJ1bblHAQDYYgII0OHmrajPh//8XEql9e//67gFufyRF/OHp9cfSDrCA5MXpbbBc48BAGBeTX3O+PWTmbBgZblHAQDYItYAATrct+6blNqGlhy7R78cu2f/HLdnv1SkIvvv3Cc79e6eusaW9O1VlZP3HVC2GTe0NgkAAGyPFqxsyBm/eTIPfOxVOXqPfuUeBwBgswggQIe6b1J1fjdiVnbu0z1DP/KK7Nm/d7lHWsfwz7w6p/3qiXKPAQAAncqi2sa89jdP5v6PnZzj99qp3OMAAGySR2ABHaausTmfv3NCdurdPddccNwWxY+Ki+9qx8nWdvfEhWlq2cDzuQAAYDu2tK4pZ/52RJ6etbzcowAAbJIAAnSYyx+dlvELVuabZx2cNx++6xa/vuLiu9o9hJRKpfz9hUXteg0AAOjKlq9uyuuvGJ7hM5aWexQAgI0SQOhynnzyyVxwwQUZMmRIBg4cmEMPPTQf//jHM3ny5HKPxkYsqm3I5Y+8mKrKivznSXuXe5wNWtnQnKdnLy/3GAAA0KnV1DfnrN+NyOPTlpR7FACADRJA6FIuv/zynHXWWbnrrruyaNGiNDY2Zs6cObn++utz6qmn5oEHHij3iGzAdx+ckhX1zfnoyftmp97dt/j1pcvPXevn9vLTx6a36/kBAKAoahtacvaVT+XhqYvLPQoAwHoJIHQZd9xxR775zW8mST7xiU9k/PjxWbp0aYYNG5Yzzjgjq1evzgc/+MEsXuwf353NsrrGXD1ydnbs2S0/eMthW32e9o4fSfLrJ2e0+zUAAKAo6hpb8qYrn8p9k6rLPQoAwDoEELqEUqmUb3zjG0mSz372s/nhD3+YfffdNz169Mixxx6b22+/Pa961atSU1OTX/7yl2Weln93+aPTUlPfnP0H7pAdelaVe5wNunviwixc2VDuMQAAoEupb27Nub9/On+bsLDcowAArEUAoUuYMGFCXnzxxXTv3j1f/OIX19lfVVWVr3/960leulOEzqOmvim/emJGenSrzDfOOqjc42zQCwtX5pJ7rSMDAABbo7GlNef98encMW5BuUcBAFhDAKFLmDJlSpJk//33T//+/dd7zMknn7zmWI/B6jx+/cSMtLSWcuv/OyHvOHqPco+zXk/NXJYTfvq4xc8BAGAbNLWU8s5rRuXW5+eVexQAgCQCCF1EY2PjWj+vT/fu3VNZ+dJb+uVgQnmtrG/O5Y9Oy70ffWXOPWK3co+zXjc/Ny9vvXpk6hpbyj0KAAB0ec2tpbzn+tG5cfTcco8CACCA0DXsvvvuSZJZs2alrq5uvceMGzcura2tSZIlS5Z02Gxs2G+enJFDBu2QV+03sNyjrNdVI2bmvX8aneraDYc1AABgy7S0lvL+G0Zn8qLaco8CAGznBBC6hBNPPDF9+/ZNS0vLBhc5/+53v7vmv1etWtVRo7ERfxo9N5e9+bByj7HG6qaWDJ2wMBffOT6v+eUTufCWMWlpLZV7LAAAKJzWUnLdqDnlHgMA2M5VlXsA2By9e/fOJz/5yXzve9/LZZddlu7du+e9731vBgwYkBdeeCGXXXZZhg4duub4lx+FtT4nnnjiZl1z2rRpGTJkSKqrq7d5/q5k0aJFbXKeVQ3N+Y8hvXLIji1l/384ubo237x3Ul5csiozl60u6yy0sdU15Z4ANp/3K12J9ytdifdrp3XNY2PzyeMGpLKyotyjdBpt9fUWdATvV9pCS0tLKir8PUD5uAOELuPLX/5y3vKWt6SpqSn/+7//mwMOOCADBw7MKaeckrvuuisf/vCHs+uuuyZJdtxxxzJPu30rlUr53kNTcuqQ8j76qrmlNT965MWcc9VTeWjqYvEDAAA60Ozl9Rk5a1m5xwAAtmPuAKHLqKqqyg033JDrrrsu1157bcaNG5ckOeqoo/Kxj30s73rXu3LLLbckSXbZZZcNnmfUqFGbdb0TTzwxlZWVGTx48LYP3wVty+979JzlOWzI3nnj8fu34URb7v+zd+dhWtb1/sA/z6zMwLDPsO+LLIqCKG6khlupGWmamlombXba82R57Jw2LLPOyeVUtFjZ6iktydIsLTfcV1BBUBAUhmEfBmb//WHyi9gGmJnvM/O8Xtc1FzP3cz/3/X647muW+/18v9+v//XFuPqhqoj8bhGlSaPQ1kp7pk4ALed6pSNxvdKRuF6z0tyltfG2w3Pzb6rdydW/M+mYXK/sj/z8/G1r9kIKChDa3S233BIXXHBBi/YdOnRoLFiwYNvXeXl5cdFFF8VFF120w75r166NTZs2RUTEmDFjWics+2R8v7KYNKB76hhRVGCQGwAApPTrJ1+Nb7/9wOhSmJ86CgCQgxQgtLvu3bu3uKAYOHBgi4/7+OOPR0TEiBEjomfPnvsSjVZSkiV/3MxfuSl1BAAAyGkbtjbEH55bFWdOavnfdgAArUUBQrubMWNGPPHEE3v9vNNPPz2qqqri2muv3elC5rfeemtERJx88sn7G5H98OxrG2NIz5LoUVKYOkoc2L8sdQQAAMh5P310uQIEAEjC/DB0GBUVFfHMM8/EDTfcsMNjzz33XPzyl7+MTCYTF198cYJ0vOHtP3okbn+uMnWMiIi496W1qSMAAEDOu/35ylizuS51DAAgBylA6DAuueSSyMvLi1//+tdx+eWXx4oVK6K6ujrmzp0bZ5xxRmzdujUuuOCCmDBhQuqoOWtzbUO8tLYmVm+uTR0l1tbUxW+efi11DAAAyHn1jc3xqydfTR0DAMhBChA6jCOPPDIuu+yyiIi49tpr44ADDoj+/fvHu971rnj11Vdj+vTpcc011yROmds++4fnoqk5Yum6LamjxIYtDakjAAAA//DTx5anjgAA5CAFCB3KFVdcETfeeGNMmzYtSktLo6ysLKZMmRJXX311zJ07N0pKSlJHzFkvramJm/8x4uKOF1YnzbJkzeY472ePJ80AAAD8f/OWrotFq6tTxwAAcoxF0OlwzjrrrDjrrLNSx+Bf/ODhZbFq0+tTXy1YtSlWbNgSg3qkKaTef/PTMbpvacxbui7J+QEAgB3d9NiK+K9TDkgdAwDIIUaAAPtta31j3Prsym1fNzdHPL8q3bu7Pn/CmGhsSnZ6AABgJ256fHk0NzenjgEA5BAFCLDfXlpbE/NXbtpu2/0vpxl9ccfzlbF8/Zb488K003ABAADbW7KmJh5M9HcCAJCbFCDAfmlubt5u9EdERM+SwjhyWK92z/LH51bFg0vXxYW/eDKqNte1+/kBAIDdsxg6ANCeFCDAfqmubYzP3f78tq/fe9iQePTj0+PEA8rbNceGLfVx/s+eiONH94mJ/cva9dwAAEDL/OrJV6O2oTF1DAAgRyhAgP0y56Gl2z4vLsiL/z3roBjVt2u75/jtM6/FKePKo66hOV6s2tzu5wcAAPZs3Zb6uP25ytQxAIAcoQAB9svHp4+MW997WGQyEbUNTfHy2i1Jckwe1D221jfFSd+bF7UNVkAHAIBs9asnX00dAQDIEQWpAwAdW15eJs44sH88+G/HxPyVm2JsefuP/nixanOc/L2HorLauh8AAJDt1tb4vR0AaB8KEGCvvLphayxbvyWO+JdFzqcN6xXTEix8XlPXEO/66WPKDwAAAABgO6bAAvaorqEpXqisjpO++2AM+dKf45ZnXksdaZufPLo8Hlu+IXUMAAAAACDLGAECbNPc3ByPL18f77/5qSjr1Tc21zVG365FsXhNTazfUh+ZTMRPzp0cZ04akDrqNhu2NqSOAAAAAABkIQUIEBGvlx9X/fXF+Nz/PfT6hrrqiIhYum7LP+0T8d0Hl8bPHl8ePzl3cpR3K04RdZsHXlobV/zx+aQZAAAAAIDsZAosICJeLzY+d/v2ZUKXgrwo71YUmcz/33bfS2vjT8+vjiO+fV/8+JFX2jnl9v7w3KpoaGpOmgEAAAAAyE4KECAiIq6976Udth0xrFesuPLEeNPIPjs8tmRNTbznl0/G+371ZPz00fYvQp5ftSm+dvfidj8vAAAAANAxmAILiE1bG2JR1eYdtt+zeE38fv7K+Nqp4+PuF6tibHm3WLi6Ouav2hSPvrIhnq+sjh8+/EoM6tGl3TM/V1kdjUZ/AAAAAAC7oAAB4pZnX4v6xu3LhB5dCuL9RwyLMycNjIiIacN67fC8Tf9YgLysS/t/K/n9/FXtfk4AAAAAoONQgACxYGX1Dts+ddyouOKEMbt9XoriIyLi1Q1b4ycJpt0CAAAAADoOa4AA8Vzlph22XfmnF+Kvi6oSpNmzvy9ZE2a/AgAAAAB2RwECxKbahp1u/8gtz0ZExNb6xvaMs0eX3/5c6ggAAAAAQJZTgECO27i1Ph5atn6njz1fWR3v+uljMeiLf45Tv/9QLF+/pX3D7cSGLfVRWV2XOgYAAAAAkOUUIJDjNtU2RE3drkd4/OrJV2NtTX3c/lxlnPjdee2YbOduemz5bvMCAAAAAEQoQCDnrdiwtcX7Lqra3IZJ9mxtTV18/Z7FSTMAAAAAAB2DAgRyXEeZTqq5uTnmzFsWy9aln4YLAADYd+MqylJHAAByhAIEctzmXSyAvjPDepW0YZLdu3fJ2vjsHyx+DgAAHdmUwT3ia6eNTx0DAMgRBakDQDaorKyMqqqq7bbV1tZGUVFRokTt57HlG1q87+dnjGnDJLvW2NQcs/+6KMm5AQCA1tG7tDB+c9HUKCnMTx0FAMgRChCIiDlz5sTs2bN32F5eXp4gTft6cU3L1vUY1qskLjpsSBun2bkbH3kl/vT86iTnBgAA9l8mE/Gz86fE8N6lqaMAADlEAQIRMWvWrJg5c+Z2284555ycGAHSUu84aEDk52WSnPuqv76Y5LwAAEDr+K+TD4hTxlWkjgEA5BgFCERERUVFVFRs/8t4cXFx5OV1/mVy1tXUt2i/d00e2MZJdtTQ2BRfuOOFeLGqZaNUAACA7HPq+Ipk0+kCALlNAQI57uV1NXvcp2dJYUwa0L0d0vx/qzbVxvk/ezz+sqhqzzsDAABZaWSf0vjpeZMjL9FocgAgtylAIIet31IfL6/dssf9DhvSI7q040KFv3n61fjAzU/HmhaOTgEAALJPl4K8+O17pkavUlMLAwBpKECAPRrco6RNj9/Q2BR3v7gmnlm5Meav3BQ/fPiVNj0fAADQ9r77zklx8MAeqWMAADlMAQI57KU1e57+KiLivpfWtmmOD/zf00oPAADoRD581PC4cOqQ1DEAgBzX+Vd4BnZp/daWTTHV1NzcZhn+fe4C5QcAAHQiRwzrFd86Y2LqGAAAChBgz844sH+bHPe2+Svjmr8taZNjAwAA7a+8W1HcfOGhUVTgdgMAkJ7fSIDdGtarJN57WOsPXb9t/so468ePRWNT240uAQAA2k9eJuJXFxwag3u27RqCAAAtZQ0QyGEvVFbv8rGDBpTFQf27x2VvHhUHDujequddurYmzvrxY1HX2NSqxwUAANL52qkT4vjRfVPHAADYRgECOaymvnGXj22ua4ybzp8cmUymVc9ZXdsQb/vhI8oPAADoRM6cNCA+ddzI1DEAALZjCixgp5asqYmFqze3yrFeWlMTdQ1Nsa6mLt73q6fi6dc2tspxAQCAtPLzMvHOgwfEj845pNXfPAUAsL+MAAF26ct3LYyfnjdln5//xPIN8aW7FsZt81fFsF4lsX5LfaypqW/FhAAAQAoV3Yri/UcMiw8cOcyaHwBA1lKAQA57dcPW3T5+02MrYnxFWVx2/Kh48tWNcejgHnv1rq5zfvpYLKp6fRTJ4jU1+5UVAABIb9rQnvGRY0bEOw8eEMUF+anjAADslgIEctiq6to97vOlPy+MHz/6SixcvTkOGlAWhw7uGR86algcPrTXbp/39b++uK38AAAAOq6i/Lx41+SB8ZGjR8RhQ3umjgMA0GIKEGC3tjY0bVsLZG1Nfdy7ZE3cs7gq/vC+aTGhf9kun/fAy2vbKyIAANAGBvfoEh86anjMOmJolHcrTh0HAGCvKUCAPTphTN+44/1HRCYT0djUHA8uXReDenRJHQsAAGgDx4/uEx85ekS8bWK/KMjPSx0HAGCfKUCAPTp0cM/Iy3t97Y+C/ExMH9lnj8/ZVNvY1rEAAIBWUlqUHxceOjguPXp4HDige+o4AACtQgEC7NGw3iV7tf/NT70af1uypo3SAAAAe1KUnxfFBa9//PPnO/v6xLHl8Z7DhkTPksLUsQEAWpUCBNije5esjfcfMSzy/zEKZHcee2V9fPzW+dHY1NwOyQAAILdN7F8W3ztrUowt7xrFBflRXJAXhfmZyGT2/Ls7AEBnpwCBHNazS8ve4fWLJ1bE2yb2i3dNHrTLfeav3BSV1bVx1o8fjbU19a0VEQAA2IlMJuIzx42KL55yQBQX5KeOAwCQlRQgkMNG9Clt8b6X/PqpGNyjSxyzi/U/Tvzug/HaxtrWigYAAOzCqD6l8eNzJ8fRI3qnjgIAkNXyUgcAOobNdY3x7p8/Ec3NO05t1dzcHDvZDAAAtLIPHzU8nvzUscoPAIAWMAIEcljXor0bKr903ZZYsKo6JvYv2277I6+sj5WbjP4AAIC2MqhHl/jhOQfHSQdUpI4CANBhKEAgh40t77ZX+/crK466hqYdtj++fENrRQIAAP7FBYcOjm/PPDB6lrRsDT8AAF6nAIEc1r+seK/2715cEJMH99hh++MrFCAAANDayrsVxXfPmhQzDxqQOgoAQIdkDRDIYUN7lkRJYcu/DSyq2hz/dccLUV3bsG1bXUNT3PrsyraIBwAAOWvmQf3j2U8fp/wAANgPChDIYV2LC2Jcxd5Ng/W1u1+Mvyyq2vb16s21sWFLw26eAQAAtFSPLgXx0/Mmx28umhoVezliGwCA7ZkCC3LcMSP6xBMrNrZo37dN7BffOmNijOzTddu2j/z22ahr3HFdEAAAYO+cNLY8fnDOwTG4Z0nqKAAAnYICBHLc1CE7rumxM09+6k1x8MAd971k2tBYtak2Hlu+QRECAAD7oCAvE9+eeWB88MhhkclkUscBAOg0TIEFOe6Mif2jS8HuvxUM7tElDuzffaePnTqhXzzw0WPihLF92yIeAAB0em8dXxEfOmq48gMAoJUpQCDH9SgpjKNH9N7tPseN7hP5ebv/Y6xgD48DAAA7d+7kQakjAAB0SgoQIM6fsvs/uC48dEg7JQEAgNxSWpQfp0/olzoGAECnZA0QiIjKysqoqqrablttbW0UFRUlStS+Lpw6JL5xz+JYsKp6h8dKCvNi2rCeezzG0nVb2iAZAAB0bm+b0C+6FvvTHACgLfgtCyJizpw5MXv27B22l5eXJ0jT/vLzMnH9Ow6K4//3wR0eKynMj+5dCnf7/F89sSKeenVjW8UDAIBOy/RXAABtxxRYEBGzZs2Khx9+eLuPESNGRO/eu18bozM5dlSf+PBRw3fYvn5LfcyZtzTWbK6L5ubmHR5vbm6Ob/19STskBACAzqVnSWGcPC433nQFAJCCAgQioqKiIiZMmLDdR3FxceTn56eO1m4ymUx85a3jouxfht83NUe8/+ano++Vd8QPHlq2w/MeWrY+Hlq2vp1SAgBA5/GOg/pHcUHu/M0BANDeTIEFbNOzpDC+ftqEeGLF+rhxfnXUNTZt9/h/3/tSbNjaEBdNHRwRES+s3hzvuPGRFFEBAKDDM/0VAEDbUoAA23nHpAHxjkkDYsTgDXH57c9v99j8lZvi07ctiE/ftiBROgAA6Bz6lRXH8aP7po4BANCpmQIL2KlPHzcqBvXokjoGAAB0Su+cNCDy8zKpYwAAdGoKEGCnCvLzYsqgHqljAABAp2T6KwCAtqcAAXbphjMPiuIC3yYAAKA1DetVEkcO75U6BgBAp+fOJrBLg3uWxIePGp46BgAAdCrnHDIwMhnTXwEAtDUFCLBbV58+IS47flTqGAAA0GmY/goAoH0oQIDdys/LxKeOHRXj+3VLHQUAADq8cRXd4uCB3VPHAADICQoQYI8qyorjLx88MvqXFaeOAgAAHdq7TH8FANBuFCBAiwzo3iWuf8dBqWMAAECHdvYhA1NHAADIGQoQoMVmHtQ/rpt5YBTme8caAADsiy//eVE0NDaljgEAkBMUIECLZTKZuPSYEfG1U8enjgIAAB3Sz59YEe+66fGoa1CCAAC0NQUIsNc+ceyo+P7ZB0dBnpEgAACwt37z9Gtx5o8fja31jamjAAB0agoQYJ+8b9rQuO4dB0a+EgQAAPba3AWr4m0/fDhq6hpSRwEA6LQUIMA++8CRw+Mn5x6SOgYAAHRIf15YFW+Z81Bs2qoEAQBoCwoQYL+cO3lQfP00a4IAAMC++PuStXHS9+bF+i31qaMAAHQ6ChBgv2QymfjUsaNiyuAeqaMAAECHNG/pupjxnQdjzea61FEAADoVBQiw3/LyMvH7iw+LcRXdUkcBAIAO6fHlG+K4Gx6IVZtqU0cBAOg0FCBAqxjUoySe+/fjY0zfrqmjAABAh/Tsyk1x7PX3x4oNW1JHAQDoFBQgQKv61QWHxqAeXVLHAACADumF1ZvjTdc/EEvX1qSOAgDQ4SlAgFY1eXCPuP8jR8dgJQgAAOyTJWtqYvr198eLVZtTRwEA6NAUIECrG9a7NGYdMSx1DAAA6LBeWb813nT9/bFg5abUUQAAOiwFCNAmPnXsyBjaqyR1DAAA6LBe21gbx/3vA/HUqxtSRwEA6JAUIECb6FpcELe8Z2pUdCtKHQUAADqs1dV1cfwND8ajr6xPHQUAoMMpSB0A6LymDO4Zv7loapz0vXmxpb4pdRwAAOiQ1m2pjxnfeTB+eu7kGNZ7+1HWzc077r/TbdEcdY3NsbW+MbbUN8aW+qbY2vCPf7f7ujG2NjT9/33qt99W39gcvUoLo6JbcZR3LYqKbsVRUVb0/z/vVhzl3YqiS2F+G/1vAAC0nAIEaFPHjOwTJ40tj9/NX5U6CgAAdFgbtzbEGT96JHWMFisrLoiKbkXbCpHXy5GiKP/Hv4N7lMT0kb0jk8mkjgoAdGIKEKDNXT5jTNy2YFU07eSdaAAAQOezqbYhNtU2xOI1Nbvc57QJ/WLOOydF/+5d2jEZAJBLrAECtLlpw3rFpUePSB0DAADIInMXrIoDr74nfvP0q6mjAACdlAIEaBcHD+yeOgIAAJBl1tTUx1k/fiwu+PnjsX5Lfeo4AEAnowAB2sVhQ3rGuIpuqWMAAABZ6KbHVsRBV98Tdy1cnToKANCJKECAdjFpYPe4buaBqWMAAABZavmGrXHid+fFR295NmrqGlLHAQA6AYugQ0RUVlZGVVXVdttqa2ujqKgoUaLOacbY8jiwf1k8u3JT6igAAECWuva+l+LOFyrjJ+dNjsOH9kodBwDowIwAgYiYM2dOHH744dt9vPTSS7F27drU0Tqdr7xlXOoIAABAlnth9eY46tr74wt/eiHqG5tSxwEAOigFCETErFmz4uGHH97uY8SIEdG7d+/U0Tqdtx3YP95xUP/UMQAAgCzX2NQcX/zzwjji2/fFAqPIAYB9YAosiIiKioqoqKjYbltxcXHk5ekI28K3Zx4Yv5+/KhqamlNHAQAAstzjyzfElG/9Pa46dXx89JgRkZeXSR0JAOgg3N0F2t2gHiXx1beaCgsAAGiZ2oam+MTv5seM7zwYS9fWpI4DAHQQChAgiQsOHRylRfmpYwAAAB3IPYvXxEHf+Fvc9Njy1FEAgA5AAQIk0b97l5gxum/qGAAAQAezqbYhLvrFE9YFAQD2SAECJPO2if1SRwAAADqgpuaIz8xdkDoGAJDlFCBAMieOLY98CxgCAAD74PbnKuOuhatTxwAAspgCBEhmWO/SOGZE79QxAACADurTty2Ixqbm1DEAgCylAAGSOvvggakjAAAAHdRTr26Mnzz6SuoYAECWUoAASZ0w1kLoAADAvvv8H5+PzbUNqWMAAFlIAQIkNba8WxzYvyx1DAAAoIN6bWNtfOOexaljAABZSAECJPfBI4eljgAAAHRgX79ncby6YWvqGABAllGAAMl96KjhMaxXSeoYAABAB1VT1xj/8afnU8cAALKMAgRILi8vE99828TUMQAAgA7sR4+8Ek+9uiF1DAAgiyhAgKxw+sR+MbhHl9QxAACADqq5OeLTv18Qzc3NqaMAAFlCAQJkhcL8vPjw0cNTxwAAADqwuxZVxZ+er0wdAwDIEgoQIGucc8jAyM/LpI4BAAB0YJ++bUE0NDaljgEAZAEFCJA1RvbpGmdM7Jc6BgAA0IEtWFUdP3h4WeoYAEAWUIAAWeW/zzgwepYUpo4BAAB0YFf+6YXYuLU+dQwAIDEFCJBVhvQqMQoEAADYL5XVdfH1uxenjgEAJKYAAbLOWQcPjO5dClLHAAAAOqh+ZcVx5kEDUscAABJTgABZ57QJ/eKiqUNSxwAAADqgMX27xgP/dnRMHtwjdRQAIDEFCJCVPvGmkVGU71sUAADQcocN6Rn3/9vRMbJP19RRAIAs4O4ikJVG9CmN900zCgQAAGiZt4yriL9+6Mgo71acOgoAkCUUIEDWuuz40akjAAAAHcB7DhsSv7v4sOhWbC1BAOD/U4AAWWt479K46tTxkZdJnQQAAMhWn5sxOn54zsFRaApdAOBf+O0AyGr//ubRcfzovqljAAAAWSaTibh25oHxlbeOj0zGu6YAgB0pQICs9+NzD4niAt+uAACA1xXl58WvLzg0PnLMiNRRAIAs5o4ikPUG9SiJcycPSh0DAADIAt27FMQd758WZx08MHUUACDLKUCADuG/z5gYhw/tmToGAACQ0MDuXeLeS4+O40yTCwC0gAIE6BB6lBTGzRceGmXFBamjAAAACYyr6BYPfvTomDSwe+ooAEAHoQABOoyhvUrjczNGp44BAAC0syOH9Yr7PnJ0DO1VmjoKANCBeCs10KF8dPqIKCrIi0/9fkHqKAAAQDt428R+8Yt3T4nSIrcwAIC947cHiIjKysqoqqrablttbW0UFRUlSsSulBYVxCePHRW/n78q/rZ4Teo4AABAG5p1xNC44R0HRUG+CSwAgL2nAIGImDNnTsyePXuH7eXl5QnS0BI3nTc5pv73vbFqU23qKAAAQBu44NDB8d2zJkUmk0kdBQDooBQgEBGzZs2KmTNnbrftnHPOMQIkiw3uWRJ/+/BRcfZPHounX9uYOg4AANDKpo/srfwAAPaLAgQioqKiIioqKrbbVlxcHHl5hllnswMqusWHjx4WH/y/Z1JHAQAAWtnQniWpIwAAHZy7u0CH9oEjh8eXTjkgdQwAAKCVDe2lAAEA9o8CBOjwrjhxbMw8qH/qGAAAQCsyAgQA2F8KEKBT+M1FU+OA8q6pYwAAAK2gT2lhdC02azcAsH8UIECnkMlk4rfvOSx1DAAAoBWY/goAaA0KEKDTGN+vW7xpZO/UMQAAgP1k+isAoDUoQIBOI5PJxPXvOCj6di1KHQUAANgPw3qXpo4AAHQCChCgUzlwQPe46tTxkZdJnQQAANhXRoAAAK1BAQJ0Ou+bNjQuPnxo6hgAAMA+sgYIANAaFCBApzTn7INjyuAeqWMAAAD7wAgQAKA1KECATuvbbz8wdQQAAGAfGAECALQGBQjQaR01vFd8+S0HRIEFQQAAoMMoys+Lft2KU8cAADoBBQjQaWUymfj8CWPjLeMqUkcBAABaaEjPLpHnTUwAQCtQgACd3g/OOTiGGUIPAAAdgumvAIDWogABOr3ybsUxY0zf1DEAAIAWKMzLi+bm5tQxAIBOQAEC5IT3HDYkMkbRAwBA1rtz4ep4/81PR0NjU+ooAEAHpwABcsL0kX1i8qAeqWMAAAAt8P2HlsU7bnw0auoaUkcBADowBQiQM945aUDqCAAAQAvdtmBVzPjOvKiqrk0dBQDooBQgQM44bUK/1BEAAIC9MG/pujj6uvvj5bU1qaMAAB2QAgTIGQcO6B4vfPb4GNC9OHUUAACghRau3hxHfvu+eHLFhtRRAIAORgEC5JSx5d3iiycfkDoGAACwF1Zuqo03Xf9A/GXh6tRRAIAORAEC5Jz3HDYkxvfrljoGAACwFzbVNsRbvv9Q/OLxFamjAAAdhAIEyDkF+XnxnycZBQIAAB1NfWNznPezx+OaexanjgIAdAAKECAnnX3IwLj48CGpYwAAAPvg07ctiE/9fn40NTWnjgIAZDEFCC3ywAMPxLnnnhsjRoyI3r17x7hx4+KDH/xgLFy4MHU02Gdfecu4GNWnNHUMAABgH3zzb0vi3T9/ImobGlNHAQCylAKEPbrmmmvipJNOittuuy1Wr14ddXV1sXz58rjpppvi6KOPjrvuumuvj1lXVxf/+7//GyeccEIMHjw4evXqFePGjYtLLrkknnnmmZ0+Z+HChdGtW7c9fmzdunV/XzI5on/3LvGdsyZFUb5vhQAA0BH94okV8dY5D8fGrfWpowAAWchdP3brd7/7XXzhC1+IiIgPfehDMX/+/Fi7dm3cd999cdxxx8WWLVviwgsvjKqqqhYfs6amJk499dT4zGc+E/PmzYv169dHfX19LF++PH75y1/G9OnT44c//OEOz1u0aFGrvS54wwljy2P6yN6pYwAAAPvory9WxZuufyBe3eDNcADA9hQg7FJzc3NceeWVERHxsY99LK6++uoYNmxYFBUVxSGHHBK33nprHHnkkbFx48a47rrrWnzcL3/5y/Hggw9GcXFxXHXVVbF48eJYtWpV/OUvf4ljjz02Ghoa4uMf/3g88MAD2z3vxRdfjIiICy64IKqrq3f50aVLl9b7TyAnfPxNI6O0KD91DAAAYB899erGOOra+2LZuprUUQCALKIAYZcWLFgQixcvjsLCwrjssst2eLygoCCuuOKKiHh9pEhL1NbWxo033hgREV/96lfjIx/5SPTr1y+6du0a06ZNi9tuuy1OOumkaGpqiquvvnq7574xAmTChAn78apgR6dN6BdfO3V86hgAAMB+WLpuS5z540dja701QQCA1ylA2KU3CoeRI0dGjx49drrPEUccsW3flkyD9cwzz8TGjRujsLAwLrjggh0ez8vLi49//OMREXH//fdv99gbI0AUILSFiw8fEgO7Gz0EAAAd2aOvbIh/u+XZ1DEAgCyhAGGX6urqtvt3ZwoLCyMv7/XLqCVrdLzyyisRETF8+PAoLS3d6T4VFRUREbFly5ZoaGjYtv2NAmTz5s1x7rnnxtChQ6NPnz5xyCGHxOWXXx6rV69uwauCnSstKojzpwxKHQMAANhP339oWcyZtzR1DAAgCyhA2KUBAwZERMSyZcuipmbn86g+++yz0dTUFBERa9as2eMxp0yZEj/60Y/iG9/4xi73eeqppyIiYvDgwVFQUBAREdXV1bFy5cqIiHj3u98dt912W6xduzZqa2vjxRdfjGuvvTaOOOKIePZZ7/Rh311yxFBrgQAAQCfwkd8+Gw8tXZc6BgCQWEHqAGSvqVOnRllZWWzatCmuu+66na4D8tWvfnXb55s3b97jMYcNGxbDhg3b5ePr16+Pq666KiIiTjvttG3b3xj9ERExduzYuPrqq+Pwww+P+vr6uPPOO+Nzn/tcrFy5Ms4777yYN2/eLkeXvPG6WmLJkiUxYsSIqKysbNH+nUUuj6TpGRFnjiqJnz62PHUUWmrLxtQJoOVcr3Qkrlc6EtcrO1EXEW+//s/x5w8eGRXdilPH2SaX/96i43G90hoaGxsjk8mkjkEOMwKEXSopKYlLL700IiJmz54d3/rWt2LVqlVRV1cXTz/9dJx77rkxd+7cbfu/MRXWvnr++efjrW99ayxatCj69OkTn/jEJ7Y9tnbt2hg/fnxMnz497rzzzjj++OOja9eu0bNnzzj77LPj9ttvj9LS0liyZEn89Kc/3a8c5LYzJw1IHQEAAGgFKzfVxgdufjoaGptSRwEAEslUV1c3pw5B9mpoaIh3v/vd2xUd/+ziiy+OP/zhD7Fq1aq4+eab4y1vecten2PdunXxta99Lb773e9GfX199OzZM2699dYWj9R4w8c+9rH4wQ9+ECeeeGLccsste53jX02dOjXy8vJi/vz5+32sjuSNES9vrMWSa77+1xfj3//wXOoYtFTN+tf/Le2ZMgW0jOuVjsT1SkfiemUPPnXsyPjG2yamjhER/t6iY3G90homTpwYTU1N8eijj6aOQo4yAoTdKigoiJ///Odx/fXXx7Rp06Jr167RtWvXOOKII+JHP/pRfPvb3962Pkjfvn336tjNzc1x4403xsEHHxzXXXdd1NfXx4wZM+Khhx7a6/IjIuKYY46JiO2ny4K9Nbz3rqdPAwAAOp5r/rYkfvXEitQxAIAErAGSI2655Za44IILWrTv0KFDY8GCBdu+zsvLi4suuiguuuiiHfZdu3ZtbNq0KSIixowZ0+I8VVVVcckll8Rdd90VEa+v6/GlL30pTj311BYf41+9UcBs3bp1n48BKzZsSR0BAABoZRf/+qmY2L8sDhzQPXUUAKAdKUByRPfu3VtcUAwcOLDFx3388ccjImLEiBHRs2fPFj1n1apVccopp8SiRYuiuLg4rrzyyrj00kujoGDXl+M999wT9fX1ccghh0R5eflO99mwYUNERPTu3bvF+eFfveewIXHT4yvi8eUbUkfpVD5z3Kh48tUN8eeFVamjAACQg2rqGmPmjY/GIx+fHj1LClPHAQDaiQIkR8yYMSOeeOKJvX7e6aefHlVVVXHttdfudFqqW2+9NSIiTj755BYf85JLLolFixZFeXl53HLLLXHIIYfs8Tlf+cpX4sEHH4xPfvKT8cUvfnGn+zz00EMRETFlypQWZ4F/1au0KH78rkNi+vUPxPot9anjdBrnHzoofvLY8tQxAADIYS9WbY4Lfv5E/O69h0VeXiZ1HACgHVgDhN2qqKiIZ555Jm644YYdHnvuuefil7/8ZWQymbj44otbdLyHH3447r777shkMvGLX/yiReVHRMTb3/72iIi48cYbY8WKHeduXb58efz0pz+NiIizzz67RceEXTlwQPe4duaBqWN0KvOWrotVm2pTxwAAIMfNXbAqvnzXotQxAIB2ogBhty655JLIy8uLX//613H55ZfHihUrorq6OubOnRtnnHFGbN26NS644IKYMGHCds/7/e9/H5MnT47JkyfHo48+um37n//854iImDZtWhxxxBEtznHhhRdG//79Y+3atXHaaafFHXfcERs2bIiNGzfG7373uzjllFNi/fr1cfLJJ8fxxx/fOi+enPbuQwfHzIP6p47RaWTCO+wAAMgO/3nnC3H7c6tSxwAA2oEpsNitI488Mi677LK46qqr4tprr41rr712u8enT58e11xzzQ7P27hxYyxa9Pq7ampqarZtf+GFFyIiYt68edGtW7c9nr+6ujoiIsrKyuInP/lJnHnmmbFo0aI488wzd9j38MMPjzlz5rT8xcEe/OqCQ2Pgf/05qjbXpY7S4a2tqYuSwrzYUt+UOgoAADmuuTni/J89EY9+fHqM6ts1dRwAoA0ZAcIeXXHFFXHjjTfGtGnTorS0NMrKymLKlClx9dVXx9y5c6OkpKTFx1q/fv0+5zjqqKNi3rx5MWvWrBg5cmQUFRVFWVlZHHbYYfGNb3wj7rjjDgug06oK8/PiG6dPiMJ8oxf213/f+1J8+S3j/F8CAJAV1m+pj5k3PhKbaxtSRwEA2lCmurq6OXUIyEZTp06NvLy8mD9/fuoo7aqysjIiXl//hdf9+9wF8fW7F6eO0eHNGNM3uhXlx+/mt+J0AzXrX/+3tGfrHRPaiuuVjsT1SkfiemU/nDd5UNx0/uTIZNrnjTr+3qIjcb3SGiZOnBhNTU3bTZEP7ckIEIA9+NyMMfHm0X1Tx+jwuhT4kQMAQHb5+RMr4tv3vpQ6BgDQRtyNAtiDHiWFceO7DomCPNM37YuKbkXxvsOHxsEDu7fu6A8AAGgFn7ptQdz/0trUMQCANmARdIAWGNKrJC47flR89S8vpo7SYRTmZ+JTx46KvEzEdx5cGmtr6lNHAgCAHTQ2NcfzldVx9AhrSgJAZ6MAAWih/zz5gFixYWv8+NHlqaNkvTF9u8blM0bHTx5dHvcsXpM6DgAA7NbovqWpIwAAbUABAtBChfl5Mefsg+OZlZvi8eUbUsfJWuP7dYv/PmNivPX7D0djU3PqOAAAsEdj+nZLHQEAaAPWAAHYC4X5efHZN4+OwnzrgexMcUFefOfMSfGh3zyj/AAAoEMoLcqPAd2LU8cAANqAAgRgL73z4IFx0tjy1DGy0senj4yv3f1iLFlTkzoKAAC0yOg+XSOT8QYnAOiMFCAA++Crbx0fPUsKU8fIKuXdiqJ7l4K4/bnK1FEAAKDFxpR3TR0BAGgjChCAfTBpYPf47zMmpo6RVWYe2D9++8xrqWMAAMBeGdNXAQIAnZUCBGAfnTdlUJwwpm/qGFnjwP7d4zGLwwMA0MGMVoAAQKelAAHYR4X5eXHVqeNTx8gazWHRcwAAOh4jQACg81KAAOyHQ4f0jMuOH5U6RnKZTMTq6rrUMQAAYK9ZAwQAOi8FCMB++tyMMTG+X7fUMZIa27drrKlRgAAA0LF0LcqP/mXFqWMAAG1EAQKwn3qUFMYPzj44dYykpo/sE/e9tDZ1DAAA2Cuj+3aNTCaTOgYA0EYUIACt4MjhveOTx45MHSOZyYN6xAuVm1PHAACAvWL9DwDo3BQgAK3kqlPHx1mTBqSO0e7yMhEFeZmoa2xKHQUAAPaK9T8AoHNTgAC0ksL8vPiftx8YE3JoPZDigryYdcSwuPmpV1NHAQCAvTa6jwIEADqzgtQBADqTgT26xK8vnBpHXXtfbNzakDpOqxjSs0ucffDAGNqrJHqXFkVBXibWbH59wfMt9U3xs8eXx5OvbkycEgAA9p4RIADQuSlAAFrZxP5l8eVTxsVHb302dZT9NqZv1/jM8aPiK3ctilc3bo36xubUkQAAoNVYAwQAOjdTYAG0gUuPHh6fffPo1DH224wxfeN/H3g5lq7bovwAAKBT+dSxI6NfWXHqGABAGzICBKAN5OVl4ounHBA19Y3x7XtfSh1nn62qro3+ZV0iwhRXAAB0DnmZiGtnHhQfPnp46igAQBszAgSgjRTm58XVp02I0yb0Sx1ln93yzMoozM/EN982IQZ09+44AAA6tq5F+fH7iw9XfgBAjlCAALShooK8+Ppp4zv00Prfz18V/3XnwvjwUcPjyGG9UscBAIB9MrB7l7jvI0fHqR34DUoAwN4xBRZERGVlZVRVVW23rba2NoqKihIlojMZ368sBnYvjlWbalNH2WcbtjbEf/zphfjcjNGxZG1Nh34tAADknoMHdo+57zs8BvcsSR0FAGhHChCIiDlz5sTs2bN32F5eXp4gDZ3RwO5dYv7K6qhrbEodZb/86slX45CB3eOOF1anjgIAAC3ylnEV8asLDo2yLm6BAECu8dMfImLWrFkxc+bM7badc845RoDQar73zoOjqbk5zv7JY/Hg0nXtdt4DyrvGhP5lccszK1vleIcP7RUvra1plWMBAEBb++CRw+LamQdGQb4ZwAEgFylAICIqKiqioqJiu23FxcWRl+eXZFrHwB5dIiLiu++cFJO/+fdobGpul/Ou39oQJ44tb7UC5IhhPeMXT6xolWMBAEBbyWQirj5tQnzy2JGRyWRSxwEAEnF3F6AdHTSge1x69PB2O9+qTbVR30rTbl1w6OC46THlBwAA2a1LQV7cfOGh8anjRik/ACDHKUAA2tnlbx4dfUoL2+18ZcX7N9gvPy8TF00dHGPLu8Yjr6xvnVAAANAGKroVxT0fPirOnDQwdRQAIAuYAgugnfXv3iXu/MARMe1/7ouGdpgKK28f3/X2rkMGxpTBPaIwPy9++8xr8eNHl7dyMgAAaD3j+3WLP7xvWozoU5o6CgCQJRQgAAlMGdwzLj16ePzPvS+1+bkeX7Fhr5/z3sOGxEtra+Kyuc+1QSIAAGhdx4/uE7+5aGr0Ki1KHQUAyCKmwAJI5KtvHRc9S9p+KqzfPbsyDhpQtlfPmTyoR9yzeE0bJQIAgNZz0dTB8adZRyg/AIAdKEAAEiktKog3jezd5udZum5LDO5REudOHtTi51TXNcQB5V3bMBUAAOy//zhxTPzoXYdEUYHbGwDAjvyGAJDQyHaan/iPz1fGglWb4p0HD2jR/tfcszjOPsTCkQAAZKdMJuL6dxwUXzxlXGT2cc07AKDzU4AAJPSlU8bF1CE92uVcT726MQ4b0rNF+66pqY/yrsVtGwgAAPZBUX5e/PqCQ+PDRw9PHQUAyHIKEICEuhUXxE/PnRzt9aa1yuq6Fu87sf/erRsCAABtray4IP44a1qcdbDRygDAnilAABIb168srnrr+DY9R14m4vwpg+LOF1a3aP+y4oJYXV3bppkAAGBv9Csrjr99+Kh485i+qaMAAB2EAgQgC3zm+FFx6ODWnwqrf1lxHDSgLH54ziGxfMPWePq1jS163owxfeN381e1eh4AANgXI/uUxv0fOTomt8HvzABA51WQOgAAEZlMJj46fURc9Isn9/tY3Yrz43MzxsT5UwbFoB4lkZeJeM8vn4y/LV7T4mMcNbxXXPHHF/Y7CwAA7K/Jg7rHH2cdEf3KrFEHAOwdBQhAlnjXIYPiP+9YGC+trdnnY5QVF8Ttlxwe4/uVxbf+viRuf25VvOuQQfGXRVUtPka34vzo0aUw6hqb9jkHAAC0hjeP7hu3vHdqdO9SmDoKANABmQILIEsUFeTF5TNG79cxzj54YBw1vHdc+ttn4it3LYonVmyMecvWxeFDe7b4GOccPCieerVlU2UBAEBbeefBA+L2WYcrPwCAfaYAAcgipxxQEZnMvj23W3F+fOktB8T3H1oWv3ry1W3bn1tVHf26tWy6gLxMxEenj4jvzVu6byEAAKAVXHr08PjFuw+N4oL81FEAgA5MAQKQRYb0KolTDqjYp+eO6F0a/boVx//cu2S77a9t3BoDe3Rp0TGOGdE77lq0OhqamvcpAwAA7K8vnXJAXDvzwMjP28d3BgEA/IMCBCDLfPq4Ufs0CuTcyYOiqbk5qjbXbbe9uq4x+nYtijMm9tvt8w8e2D1mjCmPf5/73N6fHAAA9lNeJuJ775wUV5w4NjL7OiwaAOCfWAQdIMu8eUzf+OCRw+J/H2j5NFTdivNj1rShce9La6OyevsCpLGpOT7xu/nx0WNGxHUzy+P25ytj+fqtsX5rfRTkZeKwIT3j6OG9Y+Hq6vjPO1+IZoM/AABoZ8UFefHLd0+Jtx80IHUUAKATUYAAZKHL3zwmfvzo8qipa2zR/hP6lUXfbsXx98Uv7/Tx2oamuPqexdG3a1G846D+cdqEftHcHLF8w5Z4ZNn6+Oitz7ZiegAAaLkeXQri9xcfHm8a1Sd1FACgk1GAAGShIb1K4soTx8Zn/9Cy6ahOHFseERFdi3b/bb1qc118b96y/c4HAACtobggL/526VFx8MAeqaMAAJ2QNUAAstRnjhu1x3U73nDo4Nf/YCwp9G0dAICO45JpQ5UfAECbcacMIEvl5WXimrdNjME9uuxx3+IC384BAOhYCvMz8e/Hj04dAwDoxNwxA8hio/p2jZvOnxx5md3v17NLYURELFhV3Q6pAABg/118+NAY0qskdQwAoBNTgABkuekj+sSX3zJul4/3LyuOgvxMNDY1xx+eW9WOyQAAYN8U5GXis282+gMAaFsKEIAsl/ePPw4/Nn3EDo8dMaxX/P3So+Lwob1ia31jLF23JUFCAADYOxdOHRzDe5emjgEAdHIFqQMAsGeZTCa+8pZx8afnK+OF1ZsjIuK29x0ep034/4uk/27+ylTxAACgxfLzMvG5GWNSxwAAcoARIAAdRNfigrjixLHbvn7z6D7bPn9i+YZ4/81Pp4gFAAB75fwpg2JU366pYwAAOcAIEIAOZMaYvtGntDDKuhREQd7/77A/9JunY3NdY8JkAACwZ3mZMPoDAGg3ChCADmRA9y7x4EePidc21kZRwesFyC8eXxEPv7I+bTAAAGiBcw4ZFAdUdEsdAwDIEQoQgA5mTHm3GFP++h+Nf1+8Jmbd/FQ0NycOBQAAe5DJRHz+BKM/AID2owAB6IBWbNgS35+3LL7454XRpPwAAKADOGvSgJjYvyx1DAAghyhAICIqKyujqqpqu221tbVRVFSUKBHs6OW1NfE/9y6JoT1L4vr7X47Fa2pSRwIAgBa74oSxqSMAADlGAQIRMWfOnJg9e/YO28vLyxOkgZ0b3rs01myuj2vvezkaDfsAAKADmXlQ/5g0sHvqGABAjlGAQETMmjUrZs6cud22c845xwgQss5PzpscE/uXxWf/8FzqKAAA0GJXWPsDAEhAAQIRUVFRERUVFdttKy4ujry8vESJYNearHgOAEAHctqEfjFlcM/UMQCAHOTuLkAHM7RnSeoIAADQYqdP6Jc6AgCQoxQgAB1MYb5v3QAAdBwV3UwtDACk4S4aQAezua4hdQQAAGixim7FqSMAADlKAQLQwYzvV5Y6AgAAtFi5ESAAQCIKEIAOZtKAshjVpzR1DAAAaJFyI0AAgEQUIAAdTGlRQZQU5qeOAQAAe1SYn4keXQpSxwAAcpQCBKADWltTnzoCAADsUXnX4shkMqljAAA5SgEC0AF96riRqSMAAMAeWf8DAEhJAQLQAX3oqOHx1vEVqWMAAMBuVShAAICEFCAAHVBJYX7c+K5DomuRtUAAAMhe5V0tgA4ApKMAAeigyrsVx9dPm5A6BgAA7FJFmREgAEA6ChCADuziw4fEuw8dlDoGAADslBEgAEBKChCADqxLYX588MjhUVzg2zkAANnHIugAQErumAF0cEeP6B2HDu6ROgYAAOygopsRIABAOgoQgE7gW2dMjIK8TOoYAACwnfKuRoAAAOkoQAA6gcOH9oqjR/ROHQMAALZjCiwAICUFCEAn8YOzD45uxfmpYwAAQEREFOZnYmivktQxAIAcpgAB6CRG9e0aMw8ckDoGAABERMTEfmVRXOANOgBAOgoQgE7k3MkDU0cAAICIiJgyuEfqCABAjlOAAHQip4yriLdN7Jc6BgAAxORBChAAIC0FCEAnkslk4vMnjEkdAwAAYooCBABITAEC0MkcNqRnnDbBKBAAANLJZCImDeyeOgYAkOMUIACdTCaTicuOHxX5eZnUUQAAyFEHlHeLbsUFqWMAADlOAQLQCU0f2SdOPqA8dQwAAHKU9T8AgGygAAHopGa/dXzqCAAA5CjrfwAA2UABAtBJTRrYPY4f3Sd1DAAActDkQdb/AADSU4AAdGJfP21C6ggAAOSgyYONAAEA0lOAAHRihw7uESeNtRYIAADtZ1ivkuhdWpQ6BgCAAgSgM8tkMnHDmQdFn9LC1FEAAMgRU4z+AACyhAIEoJMb1bdrnDqhX+oYAADkiMkWQAcAsoQCBCAHvHvK4NQRAADIEVMUIABAlihIHQCyQWVlZVRVVW23rba2NoqKzFtL5/DmMX3jbRP7xe/nr0odBQCATqy4IC+OHdUndQwAgIhQgEBERMyZMydmz569w/bycotH0znk52XirEkDFCAAALSpE8b0jW7FbjUAANnBbyUQEbNmzYqZM2dut+2cc84xAoRO5bQJ/aIwPxP1jc2powAA0EmdcWD/1BEAALZRgEBEVFRUREVFxXbbiouLIy/PMjl0Hr1Ki+LA/mXxxIqNqaMAANAJZTIRp0/olzoGAMA27u4C5JCTxlbseScAANgH04b2iv7du6SOAQCwjQIEIIe8/8ih0a04P3UMAAA6oTMmGv0BAGQXBQhADhnZp2t85rjRqWMAANAJWf8DAMg2ChCAHPPp40bGyD6lqWMAANCJjC3vGuMquqWOAQCwHQUIQI4pLSqIt5meAACAVnTGxP6RyWRSxwAA2I4CBCAHXXr0iCgp9CMAAIDWYforACAbufsFkIMG9egSRfl+BAAAsP/KuxXFEcN6pY4BALADd78AclBJYX4cOrhn6hgAAHQCp0/oF/l5pr8CALKPAgQgR43vZ5FKAAD23xkTTX8FAGQnBQhAjnp25abUEQAA6OBKCvPihLF9U8cAANgpBQhAjlq4ujp1BAAAOriTxpZHaVFB6hgAADulAAHIQfctWROvbaxNHQMAgA7ujANNfwUAZC8FCEAOuveltakjAADQweVlIk6b0C91DACAXVKAAAAAAHvt3YcOjvJuxaljAADskgIEIAfV1DWmjgAAQAdWWpQfX33ruNQxAAB2SwECkINKi/JTRwAAoAO77LhRMahHSeoYAAC7pQAByEFb65tSRwAAoIMa3KNLfOb4UaljAADskQIEIAe9tLYmdQQAADqo2aeOj9KigtQxAAD2SAECkIPG9+uWOgIAAB3QYUN6xnmTB6WOAQDQIgoQgBz06CvrU0cAAKAD+tYZEyMvL5M6BgBAiyhAAHKQKbAAANhb5xwyMI4e0Tt1DACAFlOAAOSgL5x0QOoIAAB0IMUFefG1U8enjgEAsFcUIAA56LQJ/aKiW1HqGAAAdBCfPHZkDOtdmjoGAMBeUYAA5KD8vEzkm7sZAIAW6FdWHJe/eUzqGAAAe00BApCj3jy6b+oIAAB0AF8+5YAo61KQOgYAwF5TgADkqM++eXTqCAAAZLmDB3aP9x4+NHUMAIB9ogAByFGLqjanjgAAQJb71hkTTZ0KAHRYChCAHPX9h5aljgAAQBY7Y2K/ON60qQBAB2YST4Acs2FLfcy88ZF4eNn61FEAAMhiX3nr+NQRAAD2iwIEIMc8/drGuPvFNaljAACQxU6b0C8m9i9LHQMAYL+YAgsgh2ypb4zZf3kxdQwAALLcZ44blToCAMB+MwIEIqKysjKqqqq221ZbWxtFRUWJEkHbuPOF1fHH5ytTxwAAIItNG9ozpo/snToGAMB+U4BARMyZMydmz569w/by8vIEaaDt/Obp11JHAAAgy33m+FGRyWRSxwAA2G8KEIiIWbNmxcyZM7fbds455xgBQqfyx+dWxU8fW546BgAAWWx0367x9gMHpI4BANAqFCAQERUVFVFRUbHdtuLi4sjLs0wOncNX71oUX/zzwtQxAADIcp86dmTk5xn9AQB0Du7uAnRyC1Zuii/9eWHUNjSljgIAQBYr71YUFx02JHUMAIBWowAB6MSamprjHTc+EluVHwAA7MG/HTMiSgrzU8cAAGg1ChCATuzel9bEC6s3p44BAECWKy3Kjw8fNTx1DACAVqUAAejE3jSyT0wb2jN1DAAAstz7Dh8afboWpY4BANCqFCAAnVgmk4l/O2ZE6hgAAGSx/LxMfPLYkaljAAC0OgUIQCd37Kg+UVZckDoGAABZ6p2TBsTw3qWpYwAAtDoFCEAnN7hnSUwf2Tt1DAAAstRnjh+VOgIAQJtQgAB0crUNjfHQ0nWpYwAAkIVmjOkbUwb3TB0DAKBNKEAAOrnigvz477cfmDoGAABZ6DKjPwCATkwBApADzp8yKN5kGiwAAP7JwQO7x4ljy1PHAABoMwoQgByQyWTiu2dNit6lhamjAACQJT593KjIZDKpYwAAtBkFCECOGNevLH50ziGpYwAAkAV6lxbG2QcPTB0DAKBNKUAAcsjpE/vF+VMGpY4BAEBi7zx4YBQVuCUAAHRuftsByCGZTCa+dMq4GNWnNHUUAAAS8qYYACAXKEAAcsyIPqXxnbMmpY4BAEAiQ3uVxNHDe6eOAQDQ5hQgADno2FF9YvKg7qljAACQwPlTBkVensXPAYDOTwECkIMK8/PilxccGsXmfQYAyDnnTxmcOgIAQLtw5wsgR40t72buZwCAHHPwwO4xsX9Z6hgAAO1CAQKQw/7zpAOiMN/0BwAAucIbYACAXKIAAchhQ3qVxHUzD0odAwCAdpDJRJw7WQECAOQOBQhAjpt1xNCYNrRn6hgAALSxY0f2icE9S1LHAABoNwoQgByXyWTikmlDU8cAAKCNmf4KAMg1ChDa1AMPPBDnnntujBgxInr37h3jxo2LD37wg7Fw4cLU0YB/8u5DB8eUwT1SxwAAoI0U5efFWQcPTB0DAKBdKUBoM9dcc02cdNJJcdttt8Xq1aujrq4uli9fHjfddFMcffTRcdddd+31MUeNGhXdunXb7cef//znNng10Ll1KcyPue87PEqL8lNHAQCgDZw2oSJ6lhSmjgEA0K4UILSJ3/3ud/GFL3whIiI+9KEPxfz582Pt2rVx3333xXHHHRdbtmyJCy+8MKqqqlp8zI0bN8aqVavaKjLkvAHdu8Q3Tp+QOgYAAG3g/CmDU0cAAGh3ChBaXXNzc1x55ZUREfGxj30srr766hg2bFgUFRXFIYccErfeemsceeSRsXHjxrjuuutafNwXX3wxIiKGDx8e1dXVu/w48cQT2+R1QS740FHD47zJ5oYGAOhMenQpiLeOr0gdAwCg3SlAaHULFiyIxYsXR2FhYVx22WU7PF5QUBBXXHFFRLw+UqSl3ihAJkzwDnVoS1edOj66dylIHQMAgFZy1qSB0aXQVKcAQO5RgNDqFi1aFBERI0eOjB49dr6o8hFHHLFt35ZOg/XGcRUg0LaG9CqJz88YkzoGAACt5PxDjfAFAHKTAoRWV1dXt92/O1NYWBh5ea9ffm8UG3vyxgiQnj17xsc//vEYN25c9OrVK0aPHh3vfe9749lnn93P5MAbPvamETF5UPfUMQAA2E+DenSJY0f2SR0DACAJBQitbsCAARERsWzZsqipqdnpPs8++2w0NTVFRMSaNWtadNw3CpArr7wyvv/978fy5cujvr4+Vq5cGTfffHNMnz49fv3rX7fCKwCKC/LjhjMnRUFeJnUUAAD2w7mTB0We3+kAgBylAKHVTZ06NcrKyqKxsXGXi5x/9atf3fb55s2bW3TcxYsXR0RE9+7d44Ybbohly5bF6tWr449//GMcdthhUV9fHx/84AeNBIFWcsSwXvGfJ49NHQMAgP3wbtNfAQA5zCq3tLqSkpK49NJL46qrrorZs2dHYWFhnHfeedGrV694/vnnY/bs2TF37txt+78xFdburF+/PgYNGhRDhw6NG264IaZMmbLtsenTp8ftt98exx57bCxYsCCuuuqquOmmm3Z5rKlTp7bodSxZsiRGjBgRlZWVLdq/s1i9enXqCGSR907sHnMfzcS8petSR9m5LRtTJ4CWc73Skbhe6Uhcr7t0QEW36J+/NSora1NH4R/8vUVH4nqlNTQ2NkYmYyQi6RgBQpv47Gc/G6eddlrU19fHf/zHf8SoUaOid+/ecdRRR8Vtt90WF198cfTr1y8iIrp167bH4/Xs2TMeeeSRmDdv3nblxxtKSkrisssui4iIu+66KxoaGlr3BUGOKsjPi2+9bWIUtqCoBAAgu5x50AA3nQCAnGYECG2ioKAgfv7zn8dPf/rT+MlPfrJtWqqDDjooPvCBD8Q73/nOuPnmmyMiom/fvq1yzunTp0dERHV1daxcuTIGDx680/0effTRFh1v6tSpkZeXFxUVFa2Sr6PJ1dfNjioqIo458LW4+8WWrdeTRGnP1Amg5VyvdCSuVzoS1+sO3v/mSVHRuzR1DHbC31t0JK5X9kd+fv62dYAhBQUIu3XLLbfEBRdc0KJ9hw4dGgsWLNj2dV5eXlx00UVx0UUX7bDv2rVrY9OmTRERMWbMmFbJ2qdPn22fb926tVWOCbzua6dOiMP/597UMQAAaKFjRvSOYcoPACDHKUDYre7du7e4oBg4cGCLj/v4449HRMSIESOiZ8+ee9z/6aefjlWrVsWwYcNi7NidL8q8YcOGbZ/37t27xVmAPTtsaM84enivuP/lLF0LBACA7Zw/xeLnAAAKEHZrxowZ8cQTT+z1804//fSoqqqKa6+9dqeLjt96660REXHyySe36Hi33nprfP3rX4/DDjss7r777p3u89BDD0VExPDhwxUg0AbefehgBQgAQAdQkJeJdx7c8jeoAQB0Vla1pU1UVFTEM888EzfccMMOjz333HPxy1/+MjKZTFx88cUtOt7b3/72iIh45JFH4s4779zh8YaGhvjGN74RERHvfOc79z04sEuzjhgWZ04akDoGAAB78JZxFdGna1HqGAAAySlAaBOXXHJJ5OXlxa9//eu4/PLLY8WKFVFdXR1z586NM844I7Zu3RoXXHBBTJgwYbvn/f73v4/JkyfH5MmTt1usfNKkSXHKKadERMR73/ve+MEPfhArV66MrVu3xkMPPRRnnHFGPPzwwzFw4MD4t3/7t3Z9rZAr8vMy8Z7DhqSOAQDAHrz70MGpIwAAZAUFCG3iyCOPjMsuuywiIq699to44IADon///vGud70rXn311Zg+fXpcc801Ozxv48aNsWjRoli0aFHU1NRs99j1118fY8eOjQ0bNsTHPvaxGD16dPTt2zdmzJgRf/vb36KioiL+7//+z/RX0IZmjOkbo/pYTBMAIFuVFRfE6RP7pY4BAJAVFCC0mSuuuCJuvPHGmDZtWpSWlkZZWVlMmTIlrr766pg7d26UlJTs1fH69esX9957b1x55ZUxadKkKC0tjS5dusTYsWPjk5/8ZDzyyCMxadKkNno1QERESWF+/PjcyaljAACwC+84qH+UFOanjgEAkBUy1dXVzalDQDaaOnVq5OXlxfz581NHaVeVlZUR8fo6LrArn7v9uZj9lxdTx4ioWf/6v6U9U6aAlnG90pG4XulIXK/bufP9R8SJB5SnjsEu+HuLjsT1SmuYOHFiNDU1bTfVPbQnI0AA2Gv/dsyI1BEAAPgX/cuK481j+qaOAQCQNRQgAOy1/mXFMfOg/qljAADwT941eWDk52VSxwAAyBoKEAD2WiaTiWtOnxhdCvwYAQDIFudPGZw6AgBAVnHnCoB9MqJPaVwybWjqGAAARMQB5V3j0ME9UscAAMgqChAA9tnXThsfw3qVpI4BAJDzzj90cGQypr8CAPhnChAA9llpUUF8bsaY1DEAAHLeeZMHpY4AAJB1FCAA7JcTx5ZHgcU2AQCSOWJYrxjVt2vqGAAAWUcBAsB+GdGnNN42sV/qGAAAOev8KUZ/AADsjAIEgP12yriK1BEAAHJW16L82LClPnUMAICsU5A6AAAdX0lhfuoIAAA56+JfPRWX/PqpmDK4Rxw/qm9MHtQjxlV0iwMqukZpkT/7AYDc5TchAPbbig1bU0cAAMhpTc0Rj76yIR59ZcN224f1KolxFd22+zhoQPfo07UoUVIAgPajAAFgny1cXR31jc3x1b8sSh0FAICdWLpuSyxdtyXueGH1tm2F+Zk4f8rg+Mxxo2JC/7KE6QAA2pYCBIB98ovHV8R5P3s8dQwAAPZSfWNz3PjIK3HjI6/E6RP6xb+/eXQcPaJ36lgAAK3OIugA7LWGxqb47O3PpY4BAMB+um3Bqjjmuvvj6Gvvi98/uzKamppTRwIAaDUKEAD2ytqauvjW35fEsnVbUkcBAKCVPPDyujjjR4/EF/+8MHUUAIBWYwosAFpsXU1dHH3t/fF8ZXXqKAAAtIEv37Uo3jq+Ig4f2it1FACA/WYECAAt1r1LYfToojsHAOisGpua490/eyI21zakjgIAsN8UIAC0WH5eJr5z1qTUMQAAaEOLqjbHZXOt9wYAdHwKEAD2yiGDesQ3Tp+QOgYAAG3ohgdejj8+typ1DACA/aIAAWCvfeSY4akjAADQxmbd/HRsqW9MHQMAYJ8pQADYa/mZTFR0K0odAwCANrRiw9b43oNLU8cAANhnChAA9lpBfl58+rhRqWMAANDGZv/1xaipsyA6ANAxKUAA2CfnTh6UOgIAAG1s1abauOF+o0AAgI5JAQLAPhnUo0sM7tEldQwAANrY1+5+MaprjQIBADqegtQBIBtUVlZGVVXVdttqa2ujqMgaB7ArjU3NUd/UnDoGAABtrGpzXVx730tx+YwxqaMAAOwVBQhExJw5c2L27Nk7bC8vL0+QBjqGh5etj1WbalPHAACgHVx99+L46DEjomux2wgAQMfhNxeIiFmzZsXMmTO323bOOecYAQI70djUHOtq6uLLdy1KHQUAgHaybkt93L14TZw2oV/qKAAALaYAgYioqKiIioqK7bYVFxdHXp5lcuANtQ2Ncd+StXHZH56LxVWbY8NW80ADAOSSPz5XqQABADoUBQgAu1Xb0Bjn3fR4PF9ZHQtWVaeOAwBAIrc/vyqamw+MTCaTOgoAQIsoQADYrSv++EL89pmVqWMAAJDYy2u3xAuV1TGuX1nqKAAALWJ+HwB2q0uBHxUAALzuj89Xpo4AANBi7moBsFtfesu4+LdjRqSOAQBAFlCAAAAdiQIEgD367zMmxuFDe6aOAQBAYn9bvDaqaxtSxwAAaBEFCAB7lJeXie+cOSlKi/JTRwEAIKG6xqa484XVqWMAALSIAgSAFpk8uEfcd+nRkZ+XSR0FAICEbnn2tdQRAABaRAECQItNHtwjrjxxbOoYAAAkdNv8VVHX0JQ6BgDAHilAANgrnz9hTFw0dXDqGAAAJLJha0P89cWq1DEAAPZIAQLAXsnPy8R/v/3A6FVSmDoKAACJ/PYZ02ABANlPAQLAXutZUhjzLzsu+nYtSh0FAIAEbn12ZTQ2NaeOAQCwWwoQAPbJgO5d4slPvSlOGlueOgoAAO1sdXVd3PfSmtQxAAB2SwECwD4b1KMkPnDksNQxAABI4K+LFCAAQHZTgACwX046oDxOGWcUCABArlmydnPqCAAAu6UAAWC/dCsuiJvOm5I6BgAA7WzJmprUEQAAdksBAsB+611aGJdMG5o6BgAA7UgBAgBkOwUIAPstk8nEF04aG/3LilNHAQCgnazcVBs1dQ2pYwAA7JICBIBWMbhnSVx50tjUMQAAaEcvrd2SOgIAwC4pQABoNR86anhMGdwjdQwAANrJkjUWQgcAspcCBIBW9b9nHpQ6AgAA7cQ6IABANlOAANCqDh/aKy4+fEjqGAAAtIPFChAAIIspQABodVecMDZG9+2aOgYAAG3sqVc3pI4AALBLChAAWt2IPqVxzekTUscAAKCNPfLK+qhvbEodAwBgpxQgALSJtx3YPy6fMTp1DAAA2tCW+qZ4+tWNqWMAAOyUAgSANvPho4bH2HJTYQEAdGYPvLwudQQAgJ1SgADQZgb3LIm/fPDIGNSjS+ooAAC0kQeXKkAAgOykAAGgTQ3uWRI/PW9y6hgAALSRB5euTR0BAGCnFCAAtLnjR/eNsw8emDoGAABt4OW1W+K1jVtTxwAA2IECBIB28T9vnxgT+5eljgEAQBt40DogAEAWUoAA0C76d+8SJ4zpmzoGAABt4JFX1qeOAACwg4LUASAbVFZWRlVV1Xbbamtro6ioKFEi6Jw+fPTw+NnjK6Jqc13qKAAAtKJHFSAAQBZSgEBEzJkzJ2bPnr3D9vLy8gRpoPMaW94tfvHuKfG2Hz4cW+qbUscBAKCVPLp8QzQ3N0cmk0kdBQBgG1NgQUTMmjUrHn744e0+RowYEb17904dDTqdE8aWx3+cODZ1DAAAWtH6LfWxZE1N6hgAANsxAgQioqKiIioqKrbbVlxcHHl5OkJoC5cdPzq+/9AyfyQDAHQij76yPkb17Zo6BgDANu7uAtDu8vMycaVRIAAAncqjyzekjgAAsB0FCABJXDh1cFw0dXDqGAAAtBILoQMA2UYBAkASmUwm3n/EsNQxAABoJQ8tWxebtjakjgEAsI0CBIBkjhrRO44a3it1DAAAWsGW+qb49VOvpo4BALCNAgSApLbUN6aOAABAK/nhw8tSRwAA2EYBAkBS5022DggAQGfxwMvr4rlVm1LHAACICAUIAIl98tiRMaxXSeoYAAC0kh8+/ErqCAAAEaEAASCxvLxMXHb86NQxAABoJT959JWob2xKHQMAQAECQHrvPnRQ9C4tTB0DAIBWUFldF39YsCp1DAAABQgA6XXvUhiXHj08dQwAAFrJf/zphajcVJs6BgCQ4xQgAGSFS6YNjcL8TOoYAAC0gmdXborp198fy9bVpI4CAOQwBQgAWWFor9I4++CBqWMAANBKFq7eHMdcd38sXF2dOgoAkKMUIABkjbMmDUgdAQCAVvTK+q0x/br748kVG1JHAQBykAIEgKxx4tjy1BEAAGhlldV1cdwND8T9L61NHQUAyDEKEACyRl6eNUAAADqjDVsb4oTvPBjX3/dSNDc3p44DAOQIBQgAWaMwLxPjKrqljgEAQBvY2tAUH7nl2TjtBw/Hqk21qeMAADlAAQJA1ijIz4v3HjYkdQwAANrQ7c9VxkHfuCfmLliVOgoA0MkpQADIKpMH9UgdAQCANra6ui5O/8HD8eHfPB01dQ2p4wAAnZQCBICsMmNM3zjnkIGpYwAA0A7+94GlceDVf4vvPbg0ahsaU8cBADoZBQgAWSUvLxOfeNPI1DEAAGgnL62tiQ/839Mx8it/jW/+bXFU13buESGVm7bGhi31qWMAQE4oSB0AAP7VIYO6R7fi/Kiu9S5AAIBc8erGrfGp3y+Ir9y1KD42fWR85Jjh0bu0KHWs/dLY1BzPrtwYD7y8Lu5/aW3c++ySWLZ+S2S69oxxFd3i8CE94/ChveLwoT1j0oDuUVTgfaoA0JoUIABkneKC/OhdWhTVtVtSRwEAoJ2tramPL9zxQlx9z4tx4tjymDq4Zxw6uEccOrhH9O1WnDrebjU2Nccjr6yPO19YHfe/tDbmLVsXG7f+04iWmtd/v21ujnhuVXU8t6o6fvzo8oiIKC7Ii0MGdo9pw3rFeZMHxbRhvVK8BADoVBQgAGSlsyYNiG/+bUnqGAAAJFJd2xi3PLMybnlm5bZtw3uXxKGDe8bUwT1i6pCeMXVIz+hZUpgwZcSGLfVx58LVMXfBqvjj85Wxurpun45T29AUDy1bHw8tWx/fvvelOH/KoJj91vExpFdJKycGgNyhAAEgK71pZB8FCAAA23l57ZZ4ee2W+M3Tr23bdkB5123TSB0+tGccPLB7FBfkt8n5m5ubY9Wm2liypiYeXLou/vDcqrh3ydpoaGpu9XP97PEV8dtnXovLjh8dnzluVHQtdgsHAPaWn54AZKVNnXzxSwAAWscLqzfHC6s3x08fe30qqaL8vDhkUPc4bEjPGNSjS5QW5kdpUX6UFuZHSWF+FBfkRWF+Jgrz86Iw7x///tPXRQV5sbW+KZasrYklazbHkjU1r3/84+st9U3t9tq21DfFf925ML7/0LKY/dZxcf6UwZGXl2m38wNAR6cAAQAAADqNusameHjZ+nh42frUUVrNig1b48JfPBkPvLwu/vesSanjAECHkZc6AADsTE1dY+oIAACQVb7z4NK4/r6XUscAgA5DAQJAVhpX0S11BAAAyDof+938uGvh6tQxAKBDUIAAkJWWrd+SOgIAAGSdxqbmeOdPHotFq6tTRwGArKcAASDr1NQ1xH/duTB1DAAAyErrt9TH6T94ODZsqU8dBQCymgIEgKxz3X0vx4tVm1PHAACArPXC6s0xd8Gq1DEAIKsVpA4A2aCysjKqqqq221ZbWxtFRUWJEkFuampqju88uDS+9fclqaMAAEDWe+SV9XH+oYNTxwCArKUAgYiYM2dOzJ49e4ft5eXlCdJA7npm5ca49LfPpI4BAAAdwiOvrE8dAQCymgIEImLWrFkxc+bM7badc845RoBAO2lubo6fPb4iPn7rs6mjAABAh/HEig3R0NgUBflmOAeAnVGAQERUVFRERUXFdtuKi4sjL88vkdAeFq+piQt+/kTqGAAA0KFsqW+K+as2xcEDe6SOAgBZyd1dAJJbuXFr6ggAANAhPbJsfeoIAJC1FCAAJFfX2Jw6AgAAdEjWAQGAXVOAAJDci1WbU0cAAIAOSQECALumAAEgqZseWx6X3/5c6hgAANAhPf3aplhXU5c6BgBkJQUIAO2uubk5FqzcFFf+6fm44OdPxNqa+tSRAACgQ2psao65C1aljgEAWakgdQAAcs//Pf1anP2Tx1LHAACATuG3z6yMC6YOSR0DALKOESAAtKvGpub4rzsXpo4BAACdxp+er4zNtQ2pYwBA1lGAANCubn7q1Zi/clPqGAAA0GlsbWiKPz5fmToGAGQdBQgA7WbByk3xgf97OnUMAADodH77zMrUEQAg6yhAAGgXm2sb4gP/93Rs3GpoPgAAtLa5C1ZFbUNj6hgAkFUUIAC0uS31jXH6Dx+O+15amzoKAAB0SptqG+L250yDBQD/TAECQJtqbGqOL965MO5+cU3qKAAA0Kn999+XpI4AAFlFAQJAm1m1qTZO+u68uOqvL6aOAgAAnd7fl6yNh5etSx0DALJGQeoAAHQer27YGl++a2Gs2lQbqzfXxcLVm2PVptrUsQAAIGdcc8+S+NWFh6aOAQBZQQECQKu4d8ma+OwfnosHXvaOMwAASOX/nn41XlozPkb0KU0dBQCSMwUWAHv06Cvr45TvzYtv/m1x1DU07fD4zx5bHsfd8IDyAwAAEmtqjvjve60FAgARChAAWuCV9VvijhdWx6d+vyC+9S8LKz6ybH2891dPRlNzonAAAMB2fvDQslhXU5c6BgAkZwosAPZoaM+SbZ9/9g/Pxf8+8HI0NjXHio1bo1nxAQAAWWVzXWNc+ttn4yfnHhIF+d77CkDuUoAAsEcDe3SJ3qWFsbamPiIilq7bkjgRAACwO794YkU0NTfHT8+bHIVKEABylJ+AAOzRgO5d4jPHjUodAwAA2Au/evLVOOenj+10Hb9c0dDYFCs3bo1nXtsYf11UFb9/dmU8sXxDbNhSnzoaAO3ACBAAWuTiw4fG5bc/nzoGAACwF255ZmWc+eNH4/8uOjSKC/JTx2kT62rq4sWqmlhUVb3dvy9WbY6qzbteC6VPaWGM7NM1RvUpjZF9SmNUn64xsk9pHDakZ3QtdssMoDPw3RyAFnl0+frUEQAAgH0wd8GqOOOHj8Qt7z0sSgo7dgnS1NQcT6zYEH94rjLufKEynqus3jZV795aU1Mfa2rWxyOvrN9ue5/Swvj4m0bGR44ZET1LClshNQCpKEAAaJHl67emjgAAAOyjO15YHcdcd39ceeLYOH1Cv8jLy6SO1GLVtQ3xl0VVMXfBqvjDc6vitY21bXq+NTX18R9/eiG+fvfi+PBRw+MTx46MfmXFbXpOANqGAgSAFllUtTl1BAAAYD88vnxDvP1Hj8S4im7xmeNGxfmHDsraabHW1tTFbfNXxW+feS3ueGF11CZYx2RTbUN87e4X43/uXRLvmzY0PnPcqBjWu7TdcwCw7xQgALTI5TNGxw8eWhbrLBYIAAAd2vOV1fG+Xz8V//GnF+ITbxoZ7z9yaHTvkn6qp5Ubt8atz66M3z7zWtz94ppoaGpOHSkiIrY2NMX1978cP3x4WXzzbRPjA0cOi0ym44ygAchlChAAWqR3aVEcObxX3P5cZeooAABAK3h149b4zNwF8eW7Fsa5kwfFKeMq4s2j+0ZZl/a7XbRhS3386slX46ePLY/7X14bzdnReezUlvqm+NBvnonbn6uMH5xzcJR3My0WQLZTgADQYiMM9wYAgE5nw9aG+M6DS+M7Dy6NgrxMHD2id5x8QHmcfEB5HDKwR6uvF9LU1Bx/fbEqfvTwK/HbZ16LrQmmt9ofty1YFQd9429x47sOiVPGVaSOA8BuKEAAaLGvnzY+Hl++IR5cui51FAAAoA00NDXH3xavib8tXhOfu/35qOhWFCeOLY8DKrpFRbeiqOhW/I+P1z/v3qVgl9NBNTc3R21DU1TXNsTmusZYW1Mfv33mtfjxo6/EK+u3tvMra12rNtXGW+Y8FB+bPiKuOnV8dCnMzrVUAHKdAgSAFistKojvn31wTLz6ntRRAACAdlBZXRc/e3zFLh8vys+Lim5FUd6tKJqbIzbXNUZ13euFR3VtQ2TJMh5t5n/ufSnmLlgV3zh9QpxxYH9rgwBkGQUIAHtlQv+ymDK4Rzy+fEPqKAAAQGJ1jU2xfMPWWL6hY4/o2B+L19TEzBsfjeNH94lvnTExDh7YI3UkAP4hL3UAADqea06fEF0K/AgBAAB4w90vronJ3/x7vP/mp2LVptrUcQAII0AgIiIqKyujqqpqu221tbVRVFSUKBFkt+NG940DB5TFo68YBQIAAPCG5uaIOfOWxS+feDU+eezIuPjwITG0V2nqWAA5SwECETFnzpyYPXv2DtvLy8sTpIGO4e0H9o/Hlm+I5k4+py8AAMDe2lTbEP9158L44p8XxozRfeM9hw2JmQf1j9Iit+IA2pPvuhARs2bNipkzZ2637ZxzzjECBHbj8yeMjV89+Wo889qm1FEAAACyUnNzxF2LquKuRVXRvUtBnHPIwHjP1CFx5PBeFkwHaAcKEIiIioqKqKio2G5bcXFx5OVZ4wB256xJA+OZ115IHQMAACDrbdzaEHPmLYs585bFoB5d4uQDyuPkAyrihLF9o3epN2ACtAUFCAD77IoTxsSI3iXxwd88EzV1janjAAAAdAgrNmyNHz78Svzw4VciLxNx+NBeccoB5XHyuIo4bEjPyM8zOgSgNShAANhneXmZuGDqkOhaVBDn/+zx2NrQlDoSAABAh9LUHDFv6bqYt3Rd/OedC6Nv16L4r5MPiA8cOUwRArCfzO8DwH57x6QBceO7DkkdAwAAoMOr2lwXl/72mTj8f+6NeUvXpY4D0KEpQABoFedMHhT/fcbEKPAOJQAAgP32+PINceS374tLfvVUrK6uTR0HoENSgADQaj72ppFx+YzRqWMAAAB0Gj94eFkccNXd8Z0HXo6mpubUcQA6FAUIAK3qyhPHxqGDe6SOAQAA0Gms21IfH/rNM/Hm7zwYS9ZsTh0HoMNQgADQqgry8+IX754SB/YvSx0FAACgU/nb4jUx6Rt/i+888HI0NxsNArAnChAAWt2Y8m7xk3MnR/cuBamjAAAAdCqb6xrjQ795Jk7+3rx4Zd2W1HEAspoCBIA2MXlwj7jyxLGpYwAAAHRKf15YFQd+45741RMrUkcByFoKEADazKeOGxWnjq9IHQMAAKBT2ri1IS78xZMxf+Wm1FEAspICBIA2dct7D4vx/bqljgEAANAp1TU2xXt++UQ0NDaljgKQdRQgALSpwvy8+PfjR6eOAQAA0Gk9+sqG+Prdi1PHAMg6ChAA2txFhw2JMycNSB0DAACg0/rPO1+IZ17bmDoGQFZRgADQLm46b3IM6F6cOgYAAECnVN/YHO/55ZNRbyosgG0UIAC0iy6F+fHwx6bHIQO7p44CAADQKT2+fENcc4+psADeoAABoN0M7lkSPzznkMjLpE4CAADQOX133tJobm5OHQMgKyhAAGhXkwf3iK++dXzqGAAAAJ3Sy2u3xJMrrAUCEKEAASCBf3/z6CgrLkgdAwAAoFP67TOvpY4AkBUUIAAkce9HjkodAQAAoFNSgAC8TgECQBKTBnSPtx/YP3UMAACATmfBqup4ftWm1DEAklOAAJBEJpOJK04YExXdilJHAQAA6HR++8zK1BEAklOAAJDMoUN6xtOfPi66FuWnjgIAANCp/MY0WAAKEADS6ldWHN8/++DIy6ROAgAA0Hk8vnxDzFu6LnUMgKQUILTIAw88EOeee26MGDEievfuHePGjYsPfvCDsXDhwtTRgE7gXZMHxUVTh6SOAQAA0Kl85a5FqSMAJKUAYY+uueaaOOmkk+K2226L1atXR11dXSxfvjxuuummOProo+Ouu+5q8bG+8pWvRLdu3Vr8cdNNN2177pYtW6KsrGyPz3nhhRfa4r8BaGOfPm5U9OhSkDoGAABApzF3wap46tUNqWMAJKMAYbd+97vfxRe+8IWIiPjQhz4U8+fPj7Vr18Z9990Xxx13XGzZsiUuvPDCqKqqapPzd+nSZdvnixcvjubm5jY5D5DehP5l8eNzJ6eOAQAA0KnM/suLqSMAJKMAYZeam5vjyiuvjIiIj33sY3H11VfHsGHDoqioKA455JC49dZb48gjj4yNGzfGdddd16Jjfv7zn4/q6urdftx+++2RyWTi6KOPjpkzZ2577qJFrw/bfNOb3rTb5x9wwAGt/58BtItTx1fE2yb2Sx0DAACg0/j1U6/GwtXVqWMAJKEAYZcWLFgQixcvjsLCwrjssst2eLygoCCuuOKKiHh9pEhrqK6ujg9/+MPRq1evuPHGGyM/P3/bYy+++Po7FiZMmNAq5wKyT0F+XvzoXYfEIQO7p44CAADQKTQ3R3ztr0aBALlJAcIuvTHiYuTIkdGjR4+d7nPEEUds27c1psH6/Oc/Hy+//HJ87WtfiwEDBmz3mAIEckPv0qK4+aKpUVLoRxQAAEBr+Mmjy+Ovi9pm+nKAbObuErtUV1e33b87U1hYGHl5r19GbxQm++qee+6JH/7whzFjxow499xzd3j8jQKkoKAgZs2aFSNHjozevXvH+PHj4yMf+UgsXbp0v84PZI/RfbvGz8+fkjoGAABAp9DQ1Byn/eCh+NtiJQiQWxQg7NIbIzCWLVsWNTU1O93n2WefjaampoiIWLNmzT6fq7m5OT73uc9Ffn5+XHXVVTvd542C5SMf+Uj84he/iMrKyqirq4tXXnklbrzxxjjiiCPinnvu2ecMQHZ5+0ED4gNHDksdAwAAoFPYUt8Up37/4bh3yb7fvwHoaApSByB7TZ06NcrKymLTpk1x3XXX7XQdkK9+9avbPt+8efM+n+s3v/lNPP300/He9743xo8fv8Pj69ati7Vr10bE68XM1772tZgxY0ZkMpm477774vLLL49FixbFhRdeGA8//HD0799/t6+rJZYsWRIjRoyIysrKfXtRHdTq1atTR4BtPnVYn7jtkefj1Y21O99hy8b2DQT7w/VKR+J6pSNxvdKRuF5JbHNNxCn/c0f86t2HxuHDeu12X/cHaA2NjY2RyWRSxyCHGQHCLpWUlMSll14aERGzZ8+Ob33rW7Fq1aqoq6uLp59+Os4999yYO3futv3fmAprbzU2NsZXvvKVKCgoiE9/+tM73ee1116L8ePHx5QpU+KOO+6It7/97VFWVhbdunWLU045Je68887o169frF27Nq699tp9ygFknx4lhfHNt01MHQMAAKDTqKlrjHfd9Hg8+sr61FEA2lymurq6OXUIsldDQ0O8+93v3q7o+GcXX3xx/OEPf4hVq1bFzTffHG95y1v2+hw/+9nP4gMf+ECcffbZ8cMf/nCfs37zm9+MK6+8MsaOHRuPP/74Ph/nDVOnTo28vLyYP3/+fh+rI3ljxEtFRUXiJPC65ubmmPXrp+MHDy/b8cGa9a//W9qzPSPBvnG90pG4XulIXK90JK5XskhJYV5cOHVIfOCIYTF5cI8dHnd/gNYwceLEaGpqikcffTR1FHKUESDsVkFBQfz85z+P66+/PqZNmxZdu3aNrl27xhFHHBE/+tGP4tvf/va29UH69u27T+f43ve+FxERl1xyyX5lPeaYYyLi9amrmpv1etBZZDKZuOrUcdG/rDh1FAAAgE5jS31TfPfBpTHlW3+Paf9zb/zo4WVRU9eQOhZAq7IGSI645ZZb4oILLmjRvkOHDo0FCxZs+zovLy8uuuiiuOiii3bYd+3atbFp06aIiBgzZsxe53r22Wfjsccei7Fjx8ZRRx2118//Z3369ImI10etNDQ0RGFh4X4dD8gefbsVx1ffOi4u/tVTqaMAAAB0Og8vWx8PL1sfn/jd/LjosCHxvsOHRr/8Zms3AB2eAiRHdO/evcUFxcCBA1t83DemmhoxYkT07Nlzr3P9+Mc/joiImTNn7na/hx56KDZu3Bjjxo2LIUOG7HSfjRtfX0yurKxM+QGd0HsPHxq3LVgVtzyzMnUUAACATmnD1ob49r0vxbfvfSkGFmyJN48pj3dMa4wZY/pG9y7utQAdjwIkR8yYMSOeeOKJvX7e6aefHlVVVXHttdfG1KlTd3j81ltvjYiIk08+ea+PXVdXF7/61a8iIuLtb3/7bvedM2dO/PKXv4wzzzxzW2nyr+bNmxcREZMnT97rLEDHcOWJYxUgAAAA7eDVjbVx02PL46bnqqMgLxPHjOgdbxlXEW8ZXxEH9i8zOgToEKwBwm5VVFTEM888EzfccMMOjz333HPxy1/+MjKZTFx88cV7fex58+bF2rVro6KiIg466KDd7vtGQTJ37tx4+umnd3h848aNcf3110dExNlnn73XWYCO4eCB3eOMif1SxwAAAMgpDU3Ncc/iNfHvf3guJn3jbzHkS3fF+371ZNz81KuxrqYudTyAXVKAsFuXXHJJ5OXlxa9//eu4/PLLY8WKFVFdXR1z586NM844I7Zu3RoXXHBBTJgwYbvn/f73v4/JkyfH5MmT49FHH93pse++++6IiHjTm960xxxvectb4sADD4za2to488wz4+abb46qqqqoqamJv/71r3HKKafEyy+/HJMmTYrzzjtv/184kJUymUz8x4ljoyjfjy8AAIBUVmzYGj98+JU4+yePRd8r74gjv31f/NcdL8S8peuisak5dTyAbUyBxW4deeSRcdlll8VVV10V1157bVx77bXbPT59+vS45pprdnjexo0bY9GiRRERUVNTs9Njv1GA7GxqrX+Vn58fP/7xj+Otb31rvPbaa/He9753h33GjBkTv/zlL6OoqGiPxwM6rkOH9IyPv2lEfP3uxamjAAAA5Lym5oh5S9fFvKXr4j/vXBgH9i+LBz96THQrdtsRSM9baNmjK664Im688caYNm1alJaWRllZWUyZMiWuvvrqmDt3bpSUlOz1MdevX79tAfVJkya16DkHHHBAPPTQQ/GJT3wixo0bF126dInS0tI46KCD4sorr4z77rsvhg4dutdZgI7na6dNiJMPKE8dAwAAgH/x7MpN8f6bn47mZiNBgPQy1dXVvhvBTkydOjXy8vJi/vz5qaO0q8rKyoh4ff0XyGZra+rifT/6W9z67MqI0p6p48Ce1ax//V/XKx2B65WOxPVKR+J6pSPZz+v1228/MP5t+ohWi0PHNHHixGhqatrlFPnQ1owAAaBD6l1aFN9958Fx8MDuqaMAAADwLz75+/nxwEtrU8cAcpwCBIAO7X/PnGRRdAAAgCzT0NQc7/zJY7FqU23qKBERpuSCHOWOEQAd2sg+pXHfR46OgrxM6igAAAD8k1c3bo0Lf/5E6hjx5IoN8fk/Pp86BpCAAgSADi2TycRhQ3vG508YkzoKAAAA/+LOhavj3iVrkpy7sak5Zv9lURz+P/fGK+u3JMkApKUAAaBT+PRxo6J/WXHqGAAAAPyLr/5lUbufc+namnjT9ffH525/Puobm6Nnl8J2zwCkpwABoFPoVlwQd7z/COuBAAAAZJk/Pb86Hntlfbud7y8LV8eh3/p7PPDyum3bepUqQCAXuUsEQKcxaWD3uOP906Kk0I83AACAbNIeo0Cam5vjm39bHCd9b16sqanf7rEeRoBATnKHCIBO5bjRfePJTx2bOgYAAAD/5LfPrIwFKze12fFr6hri/J89EZ/6/YJoat7x8cadbQQ6PQUIAJ3OmL5d44JDB6eOAQAAwD+56q8vtslxF1dtjqOuvT9+8cSKXe6zsbahTc4NZLeC1AEAoLVlMpmYc/akeOrVjfH0axtTxwEAACAifv7EipgyuEd8+KjhUVSwf+/Lbmxqjj89Xxnfm7c0/vBc5R5HeGzYUr/bx4HOyQgQADql4oL8uOP906KPhe4AAACyQmNTc3zid/PjoG/cE3MXrIrm5r2flmrZupr4wp9eiOFfvitO+8HD8fv5q1o0vZURIJCbjAABoNPq371L/Oz8KXHKnIdSRwEAAOAfFq7eHKf/4OE4YUzf+OYZE+OgAd13ul9zc3O8trE2lqzZHIuqNsfNT70Wf3qhMvahN4mNWxUgkIsUIAB0aiePq4gzJvaL381flToKAAAA/+SuRVVxyDV/i/cfMSxOn9gvlqypiSVramLxms2xeE1NLFmzObbUN7XKuRQgkJsUIAB0etefeVD8fcnaWGfOVwAAgKzS1BzxnQeXxnceXNqm59lY6+9ByEXWAAGg0xvUoySuPn1C6hgAAAAksmGLESCQixQgAOSEiw8fEtNH9k4dAwAAgAQsgg65SQECQE7IZDLxvbMmRVG+H30AAAC5ZuNWU2BBLnIXCICcMa5fWXz5LQekjgEAAEA721LfFPWNrbOgOtBxKEAAyCkfnT4iDhvSM3UMAAAA2tkm02BBzlGAAJBTigvy4/tnHxz5eZnUUQAAAGhHFkKH3KMAASDnTBrYPf7jhDGpYwAAANCONtZaBwRyjQIEgJz02Rmj47QJ/VLHAAAAoJ1s3GoECOQaBQgAOemNqbCG9ipJHQUAAIB2oACB3FOQOgBkg8rKyqiqqtpuW21tbRQVFSVKBLSHfmXF8dFjRsSnb1uQOgoAAABtTAECuUcBAhExZ86cmD179g7by8vLE6QB2tNHjhkez1dWx/cfWpY6CgAAAG1ow1ZrgECuUYBARMyaNStmzpy53bZzzjnHCBDIAcUF+fG9d06Kl9fWxF2Lqvb8BAAAADokI0Ag9yhAICIqKiqioqJiu23FxcWRl2eZHMgFmUwmvn/2wTFq9l+jsak5dRwAAADawMZaBQjkGnd3ASAihvUujVnThqaOAQAAQBsxAgRyjwIEAP7hG6dPiIpupr4DAADojDZaAwRyjgIEAP6ha3FBfGz6yNQxAAAAaAMbjACBnKMAAYB/8unjRsXE/mWpYwDw/9i77/CoqsSN4+/UVNI7CZAGIdRA6E1AFFHRgIJYEBUUK3ZdddX9qYvruuuuXVHXrmtZrGBhdRUVEOwKCAJKJ6GGQHry+wPJkjWBlJmcmTvfz/PkIdy5c+cNz2GSzDvnHAAAAA9jCSwg8FCAAABwCLfTrjmn9lR0iMt0FAAAAACABxWXswQWEGgoQAAA+B+DOsXo+TP7yGG3mY4CAAAAAPAQZoAAgYcCBACABozNSdDZ+ammYwAAAAAAPIQCBAg8FCAAADTi9uNy1D4y2HQMAAAAAIAH7CljCSwg0FCAAADQiOSIYL1xbj9FBDtNRwEAAAAAtFJpZY0qq2tMxwDQhihAAAA4jO5JEbrjuBzTMQAAAAAAHrC3nGWwgEBCAQIAwGG4nXZdMjRdUSEu01EAAAAAAK3EPiBAYKEAAQCgCaayIToAAAAA+D0KECCwUIAAANAElw/LkMthMx0DAAAAANAKbIQOBBYKEAAAmiA9NlRn9GEWCAAAAAD4M2aAAIGFAgQAgCa65ZjOig93m44BAAAAAGghChAgsFCAAADQRJ1iQnX9qCzTMQAAAAAALVRczhJYQCChAAEAoBkuHZqu7Lgw0zEAAAAAAC3ADBAgsFCAAADQDC6HXX8cl2M6BgAAAACgBfZQgAABhQIEAIBmOqVXigZ0iDIdAwAAAADQTMwAAQILBQgAAC0wb8YAJbYLMh0DAAAAANAMxWXsAQIEEgoQAABaICbUrUuGdDIdAwAAAADQDMXlzAABAgkFCAAALXTTmM7KjA01HQMAAAAA0EQsgQUEFgoQAABaYUKPZNMRAAAAAABNtIclsICAQgECAEAr3Hh0tnITw03HAAAAAAA0ATNAgMBCAQIAQCtEhrg0NT/NdAwAAAAAQBNQgACBhQIEAIBWOrd/msKDHKZjAAAAAACOgE3QgcBCAQIAQCvFhwfpgoEdTccAAAAAABzB/opqVVXXmI4BoI1QgAAA4AHXj8pSqJtZIAAAAADg6/YyCwQIGBQgAAB4QFx4kG4f28V0DAAAAADAEexhHxAgYFCAAADgIZcOTVfXxHDTMQAAAAAAh8FG6EDgoAABAMBDnA677hnfzXQMAAAAAMBhFJdVmo4AoI04TQcAfEFhYaG2b99e71h5ebncbrehRAD81ZjO8Tq+a4LeXlFoOgoAAAAAoAHF7AECBAwKEEDSnDlzNHv27N8cj4+PN5AGgD+z223628nd9d6qD1VZXWs6DgAAAADgf7AEFhA4KEAASTNmzFBBQUG9Y5MnT2YGCIAWyYoL0+BOMfpozQ7TUQAAAAAA/2MPS2ABAYMCBJCUkJCghISEeseCgoJkt7NNDoCWKeieRAECAAAAAD6IGSBA4ODVXQAAvOCCQR3VOT7MdAwAAAAAwP+gAAECBwUIAABeEOxyaHy3JNMxAAAAAAD/g03QgcBBAQIAgJdcNSJDMaEu0zEAAAAAAIdgBggQOChAAADwkqSIYP395O6mYwAAAAAADsEm6EDgoAABAMCLJvRIUnQIs0AAAAAAwFcwAwQIHBQgAAB4UajbqQk9kk3HAAAAAAD8igIECBwUIAAAeNlxXeNNRwAAAAAA/KqYJbCAgEEBAgCAl43vlqThGTGmYwAAAAAAJBWXMwMECBQUIAAAeJnLYdclQ9NNxwAAAAAASNrDElhAwKAAAQCgDZzaK0VdE8NNxwAAAACAgLe/olpV1TWmYwBoAxQgAAC0ketHZZmOAAAAAACQtJdlsICAQAECAEAbGZ4Rq2An33oBAAAAwLRilsECAgKvwgAA0EY6xYSqczzLYAEAAACAaWyEDgQGChAAANpIVXUN06wBAAAAwAfsKa00HQFAG6AAAQCgjVz++g9at3O/6RgAAAAAEPCYAQIEBgoQAADawOJfdunBz342HQMAAAAAIPYAAQIFBQgAAG3gytd/UG2t6RQAAAAAAIkCBAgUFCAAALSB1dv3mY4AAAAAAPgVBQgQGChAAABoA6Fuh+kIAAAAAIBf7SljE3QgEFCAAADQBqKCXaYjAAAAAAB+xSboQGCgAAEAoA1sLi4zHQEAAAAA8CuWwAICAwUIAABeVlRSzvRqAAAAAPAhxfyOBgQEChAAALxs7Y79qqyuNR0DAAAAAPArZoAAgYECBAAALyssKTcdAQAAAABwiD0UIEBAoAABAMDLOseHm44AAAAAADgES2ABgYECBAAAL+uSEK6h6TGmYwAAAAAAflVczgwQIBBQgAAA0AYoQAAAAADAd7AHCBAYKEAAAGgDx3SJNx0BAAAAAPCrfRXVqq6pNR0DgJdRgAAA0AaGpcfo5jGdTccAAAAAAPyKfUAA66MAAQCgDTgddt16bGeWwgIAAAAAH8EyWID1UYAAANBGbDab/jI+13QMAAAAAIDYCB0IBE7TAQBfUFhYqO3bt9c7Vl5eLrfbbSgRAKvqmxqloekx+mTdTtNRAAAAACCgMQMEsD4KEEDSnDlzNHv27N8cj49n02IAnuWw2/TYpF4a9dAibS4uMx0HAAAAAAIWe4AA1kcBAkiaMWOGCgoK6h2bPHkyM0AAeEWXhHA9PaW3jn/8c5VX1ZiOAwAAAAABaQ8zQADLowABJCUkJCghIaHesaCgINntbJMDwDtGd47XjUdn6+Z3fjQdBQAAAAACEktgAdbHq7sAABhy6dB0BTv5VgwAAAAAJlCAANbHqy4AABgSFeLS7OO7mo4BAAAAAAGpuJw9QACrowABAMCgWcPSdXL3JNMxAAAAACDgMAMEsD4KEAAADLLZbJpzak9FBLMtFwAAAAC0JTZBB6yPAgQAAMPiwoP04IQepmMAAAAAQEApLmMJLMDqKEAAAPABk3unKK99hOkYAAAAABAwWAILsD4KEAAAfIDTYdcHFw5WXJjbdBQAAAAACAjF5RQggNVRgAAA4COiQly68/iupmMAAAAAQEBgBghgfRQgAAD4kFN7JSs7Lsx0DAAAAACwvN2l7AECWB0FCAAAPiQi2KV3zh9gOgYAAAAAWN4eNkEHLI8CBAAAH5MRG6aTuyeZjgEAAAAAllZaWaOKqhrTMQB4EQUIAAA+6O8nd1OIi2/TAAAAAOBNzAIBrI1XVgAA8EEdokN19VGZpmMAAAAAgKWxDwhgbRQgAAD4qEuHpstpt5mOAQAAAACWtbu0ynQEAF5EAQIAgI+KDw/SeQM6mI4BAAAAAJbFEliAtVGAAADgw24YnaW0qGDTMQAAAADAklgCC7A2ChAAAHxYh+hQXTY0w3QMAAAAALAkChDA2ihAAADwcSd1TxRbgQAAAACA57EHCGBtFCAAAPi47PhwTeyZbDoGAAAAAFgOe4AA1kYBAgCAH7hyRCazQAAAAADAw1gCC7A2ChAAAPzAwI7R6pMaaToGAAAAAFjKbmaAAJZGAQIAgJ+4dGi66QgAAAAAYCl72AMEsDQKEAAA/MTk3ikKD3KYjgEAAAAAlsEMEMDaKEAAAPATQU6HLhzUyXQMAAAAALAM9gABrI0CBAAAP3LegA6KDHaajgEAAAAAlrB+V6lqa2tNxwDgJRQgAAD4kS4J4Tqnf5rpGAAAAABgCXvKqvTT9n2mYwDwEgoQAAD8zJl9Uk1HAAAAAADLWLZhj+kIALyEAgQAAD/TMyVCXRPDTccAAAAAAEtYumG36QgAvIQCBAAAP+Ny2NUhKsR0DAAAAACwBAoQwLooQAAA8EPn9u9gOgIAAAAAWMKXm/aouoaN0AErogABAMAPjekcp3ZBTtMxAAAAAMDv7a+o1opte03HAOAFvHICSCosLNT27dvrHSsvL5fb7TaUCAAOLzrUrZyEcKZqAwAAAIAHLN2wW92TI0zHAOBhFCCApDlz5mj27Nm/OR4fH28gDQA0zd7yKtMRAAAAAMASlm3Yo3P6m04BwNMoQABJM2bMUEFBQb1jkydPZgYIAJ+WHBGklYUlpmMAAAAAgN9jdj1gTRQggKSEhAQlJCTUOxYUFCS7nW1yAPiunfsrTUcAAAAAAEv4ZnOxKqpq5HbyWhBgJfyPBgDAD1VW12jTnjLTMQAAAADAEiqqa/TdlmLTMQB4GAUIAAB+6N0fi7R9X4XpGAAAAABgGSyDBVgPBQgAAH5o0c87TUcAAAAAAEuhAAGshwIEAAA/U1Vdo6eWbTQdAwAAAAAsZdmGPaYjAPAwChAAAPzM+t2l2sHyVwAAAADgUT9s26v9FVWmYwDwIAoQAAD8zDVvLldZVY3pGAAAAABgKdU1tfpqExuhA1ZCAQIAgB/ZW1ald34sMh0DAAAAACynU0yIchPDTccA4EEUIAAA+JGL/vWt9ldUm44BAAAAAJbictj0z7P6KjrUbToKAA+iAAEAwE/8tH2fnv1ik+kYAAAAAGA5fz4hV/07RJuOAcDDKEAAAPADe0ordeO8laZjAAAAAIDlnNw9SZcNSzcdA4AXUIAAAOAH3lq+TS99s9l0DAAAAACwlE4xIXpici/ZbDbTUQB4AQUIAAA+bk9ppZ77kqWvAAAAAMCT2PcDsD6n6QAAAKBxW4rLVPCPpVqyfrfpKAAAAABgKXex7wdgeRQgAAC0gU/X7dRL32xWmNuhU3umKC818rDnl1VW67Xvt+rat5Zrw+6yNkoJAAAAAIHhpG6JmsW+H4DlUYAAAOBl76ws1LjHlqi29sDf//TBT+ocH65hGTEakRGryb1T5HTUX5VywpPLNH9loYG0AAAAAGBtHaND9I/TerPvBxAAKEAAAPCyF77aVFd+SFJNrbSysEQrC0s0Z/F6/fk/azS5d4pKK6vVMzlC76ws0rs/Un4AAAAAgKe5HDa9NJV9P4BAQQECAICXpUWFHPb2bzYX65vNxW2UBgAAAAACF/t+AIHFfuRTAABAa1xzVKZiQ12mYwAAAABAQGPfDyDwUIAAAOBlkSEuPTapl+kYAAAAABCw2PcDCEwUIAAAtIGxOQmKYRYIAAAAALQ59v0AAhcFCAAAbSDY5dADE3rIzpuNAAAAAKBN3Xl8V/b9AAIUBQgAAG3ktLz2umF0tukYAAAAABAwhmXE6PJhGaZjADCEAgR+Z9WqVZoxY4ays7MVGxurHj166Prrr9fOnTtNRwOAI/rDsV309JTeigh2mo4CAAAAAJYW7LTrsUm9ZGcqPhCwKEDgE9577z2Fh4dr/vz5hz3vs88+0/Dhw/XCCy9oy5YtKi8v17p163T//fdryJAh2rx5cxslBoCWsdttOis/Tfee3F3svQcAAAAA3vN/Y7uoc3y46RgADKIAgU946qmnjnjOvn37dPbZZ6ukpETDhw/XkiVLVFRUpHnz5ikjI0MbNmzQ9OnT2yAtALTe2f3S9OgpPU3HAAAAAABL6pcWpSuGs/QVEOgoQGDcM888o9dff/2I5z355JPasmWL0tLS9PLLL6tbt24KCQnR8OHD9eqrr8rtduvjjz/W4sWL2yA1ALTe9IEd9dfxuaZjAAAAAICluBw2PTG5l5wOXvoEAh3PAjDiySef1PTp05WTk6MLL7ywSfeZO3euJGnmzJkKCwurd1t2drZOPPFESWpSmQIAvmLWsAyd0y/NdAwAAAAAsIybju6s7skRpmMA8AEUIDDikUce0YsvvqiNGzc26fzS0lItXbpUkjRmzJgGzzl4fOHChZ4JCQBtwG63ac6kXnpwYg852JgPAAAAAFqlZ3KErh+VZToGAB/hNB0Agem5555TaWlp3d9PPvlkbdmypdHz165dq+rqarlcLuXk5DR4Ts+eB9bS/+mnnzwbFgC8zGG36cLBnfTcFxv16c+7TMcBAAAAAL/ksB9Y+srt5D3fAA6gAIERGRn1N6FyuVyHPf/gTJHk5GTZ7Q1/E0tJSZEklZSUaMeOHYqNjfVAUgBoOx9dPEQnPv655q8sNB0FAAAAAPzONUdlqm9alOkYAHwIdSj8QklJiSQpPDy80XMOvW3fvn1ezwQAnuaw2/TcGXnKT4s0HQUAAAAA/EqX+DDdckxn0zEA+BhmgMAvVFRUSJLcbnej5xx62/79+xs9Lz8/v0mPuXbtWqWnp6uwMLDeiV1UVGQ6AtBkVh2vz52coXGPLdGaHY0/l8EPlRabTgA0HeMV/oTxCn/CeIU/8afxapPuHt1Zxbt2yI9SB4Tq6mrZbOx3CXOYAQK/cLDcKC8vb/ScsrKyus+DgoK8ngkAvCUq1K3nz+yjgR2jTUcBAAAAAJ83vX8H9ef3JwANYAYI/MLB5a0OLoXVkL1799Z9HhYW1uh5y5Yta9Jj5ufny263KyEhoYkprSVQv274JyuO14QE6aULkpT314+0Y3+l6TjwpNAo0wmApmO8wp8wXuFPGK/wJz4+XtNjQvW3KUMUFsTLnL7I4XCopqbGdAwEMGaAoMXmzp2r8PDwJn3k5ua26rFSU1MlSVu3bm30SXPLli2SpODgYMXHx7fq8QDAF6RFh2jxrGEanhFjOgoAAAAA+KQ5p/ak/ADQKJ4d0GIRERHKzs5u0rkpKSmteqzMzEw5nU5VVlZqxYoV6tat22/O+f777yVJWVlZrC0IwDKy4sI0b/oA9f/7Qi3f1vgsOAAAAAAINNeNzNLozrwJFkDjKEDQYqNHj9ZXX33VJo8VHBysfv36adGiRVqwYEGDBciCBQskSSNGjGiTTADQVsKCnHp7+gAd/fAiNkYHAAAAAEnn9EvT7ONzTMcA4ONYAgt+o6CgQJL0yCOPqLS0tN5ta9eu1ZtvvilJmjhxYptnAwBv6xQTqrnn9FN0iMt0FAAAAAAwany3RD16ak9WAAFwRBQg8BvTpk1TcnKy1q9fr0mTJmnlypUqKyvTwoULNWHCBJWXl2vMmDHq37+/6agA4BU9kiN0X0F38TM+AAAAgEA1PCNGL57VV04HL2sCODKWwILfCA0N1TPPPKOCggJ9+OGHys/Pr3d7enq6Hn74YUPpAKBtnNE3VW6nXZOe/sJ0FAAAAABoU71SIvTGuf0V4nKYjgLAT1CVwq8MHDhQCxcu1JQpU5SUlKSgoCClp6frsssu08KFC5WYmGg6IgB43Sk9k3VOvzTTMQAAAACgzWTGhuqdGQMUybLAAJqBGSDwCcuXL2/yuVlZWZozZ44X0wCAb7PZbLqvoLvcTrseWfSL6TgAAAAA4FVJ7YL03gUDlRQRbDoKAD/DDBAAAPxQWJBTfzupmwZ2jDYdBQAAAAC8JjLYqXfOH6CM2DDTUQD4IQoQAAD8VLDLoZfO6qvwINa/BQAAAGA9wU673jyvv3qlRJqOAsBPUYAAAODH0qJDdM/4brLZTCcBAAAAAM9x2G16aWpfDcuINR0FgB+jAAEAwM9NH9hRr03rJ4edFgQAAACANTw+qZdO7JZkOgYAP0cBAgCABYzvnqRXz85XRLDTdBQAAAAAaJU/n5Crs/ulmY4BwAIoQAAAsIiTuifp0VN6mo4BAAAAAC127chMXT0y03QMABZBAQIAgIWc0itFX181XLmJ4aajAAAAAECznNs/TXce39V0DAAWQgECAICFOOw29UqJ1FvnDVB4kMN0HAAAAABoknFdE/TIKT1ls7G3IQDPoQABAMCC0mND9dzpfeR28K0eAAAAgO/rmhAuJ7+/APAwnlUAALCo8d2T9NSU3qZjAAAAAMARfbO52HQEABZEAQIAgIWdltde9xV0Nx0DAAAAAA7r683Fqq2tNR0DgMVQgAAAYHGXDE3Xncd3VZibPUEAAAAA+Kbt+yq0pbjcdAwAFkMBAgBAALhuVJZmj+sqh50NBQEAAAD4pq837zEdAYDFUIAAABAgLh2WrpO6JZqOAQAAAAAN+noT+4AA8CwKEAAAAsjfTuout4Nv/wAAAAB8DxuhA/A0XgEBACCApEWHKD7cbToGAAAAAPwGS2AB8DQKEAAAAshP2/epsISNBQEAAAD4ntXb92lfeZXpGAAshAIEAIAAsbqoRKMfXqTK6lrTUQAAAADgN2prpe+27jUdA4CFUIAAABAg/vXdVq3fVWo6BgAAAAA06utNLIMFwHMoQAAACBDzVmwzHQEAAAAADouN0AF4EgUIAAABIjki2HQEAAAAADisrylAAHgQBQgAAAHisUm9lNguyHQMAAAAAGjUd1uKVV3DvoUAPIMCBACAABEe5NRnlw5RqNthOgoAAAAANGhfRbXW7NhnOgYAi6AAAQAggGTEhunxSb3UMznCdBQAAAAAaNDXm1gGC4BnOE0HAHxBYWGhtm/fXu9YeXm53G63oUQA4D2n5bVXQY8knffPb/Tcl5tMxwEAAACAer7ZvEeTeqeYjgHAAihAAElz5szR7Nmzf3M8Pj7eQBoA8L4gp0NPT8lTWlSI7vrwJ7HELgAAAABfwUboADyFAgSQNGPGDBUUFNQ7NnnyZGaAALA0u92m2cd31Z6ySj302S+m4wAAAACAJOkbChAAHkIBAkhKSEhQQkJCvWNBQUGy29kmB4D1/XV8N8WHBen/3l9lOgoAAAAAaNOeMhWVlCs+PMh0FAB+jld3AQAIcMEuh/4wtosuH55uOgoAAAAASJI++3mX6QgALIACBAAASJL+OK6rfj8mWzab6SQAAAAAAt1N81eqsrrGdAwAfo4CBAAASJJCXA7939gcPT6plzJjQ03HAQAAABDAvt+6Vw9++rPpGAD8HAUIAACo55z+HfTvmYPUNTHcdBQAAAAAAezmd3/Utr3lpmMA8GMUIAAA4Dc6xoTqtXP6qXN8mOkoAAAAAAJUcVmVrn97hekYAPwYBQgAAGhQ5/hwfXrJEGXFUYIAAAAAMOPJpRu06OedpmMA8FMUIAAAoFFx4UH67NIh6pcWZToKAAAAgAB16dzvVV1TazoGAD9EAQIAAA4rPjxI718wUEdnx5mOAgAAACAAfbFxjx5fst50DAB+iAIEAAAcUWSIS+9dMFAzBnYwHQUAAABAAPrdvBXasa/CdAwAfoYCBAAANInNZtPfTuqms/NTTUcBAAAAEGB27q/U799ZaToGAD9DAQIAAJos1O3UE5N766GJPUxHAQAAABBgHl70i77cuNt0DAB+hAIEAAA0i91u08zBnfTPs/qqfWSw6TgAAAAAAkRtrXTJv75XDRuiA2giChAAANAik3qnaMYA9gQBAAAA0HYW/bJLz3650XQMAH6CAgQAALTYlSMydXpee9MxAAAAAASQa99aoT2llaZjAPADFCAAAKDF2gU79dSU3rrx6Gw57DbTcQAAAAAEgG17y/WH91aZjgHAD1CAAACAVnE67Lr9uByd2YeZIAAAAADaxr2frNMPW/eajgHAx1GAAAAAj3hsUi9NYTksAAAAAG2guqZWF//rO9XWsiE6gMZRgAAAAI9wOux68rTeOiE30XQUAAAAAAHgozU79NyXm0zHAODDKEAAAIDHuJ12/Wtavv5vbBfTUQAAAAAEgKve+EG72RAdQCMoQAAAgEe5HHb9fkxn3X1irsKDHHXH06KClRIRbDAZAAAAAKspLKnQTfNXmo4BwEdRgAAAAK+46qhM3TO+W93fH5/UW9nxYQYTAQAAALCiBz/7WV9s2G06BgAfRAECAAC85rwBHfTmef2VHRemtKhgfbx2h+lIAAAAACymtlaa+eq3qq5hQ3QA9VGAAAAAr7HZbDohN1FfXzVcqVEhcjv40QMAAACA5y3bsEePLv7FdAwAPoZXIQAAgNeFup2qqqlVRLDTdBQAAAAAFvW7t1do295y0zEA+BAKEAAA0CaiQlxactkwpUayEToAAAAAz9tTVqVr31puOgYAH0IBAgAA2kx6bKj+c9FgRYW4TEcBAAAAYEFPL9uoj9ZsNx0DgI+gAAEAAG0qMy5M78wYoMR2QaajAAAAALCgi179ThVVNaZjAPABFCAAAKDNDegYrTfP7a+UCJbDAgAAAOBZy7eV6G8frzUdA4APoAABAABG9OsQpY8uHqxOMSGmowAAAACwmD+8v0rrd+03HQOAYRQgAADAmKy4MC24YJDCgxymowAAAACwkP0V1br89R9MxwBgGAUIAAAwKjMuTJ9eMlSd48NMRwEAAABgIXO/26q3l28zHQOAQU7TAQBfUFhYqO3bt9c7Vl5eLrfbbSgRAASWnikReuu8/hp47yfaub/SdBwAAAAAFnHp3O81MitWoW5eBgUCETNAAElz5sxR//79632sW7dOO3fuNB0NAAJGdny4npqSJ4fdZjoKAAAAAItYt3O/7liw2nQMAIZQgACSZsyYoc8//7zeR3p6umJiYkxHA4CAckJuom4e09l0DAAAAAAWcteHa/TD1r2mYwAwgLlfgKSEhAQlJCTUOxYUFCS7nY4QANra78dka+mG3XqLtXoBAAAAeEBVTa1mvvKtPrposOzMOAcCCq/uAgAAn2Kz2fSPyb2UkxBuOgoAAAAAi/hk3U79Y+kG0zEAtDEKEAAA4HPiwoP0/Bl9FBXiMh0FAAAAgEVc8+ZyFe4tNx0DQBuiAAEAAD4pLzVSD07oIRsz1AEAAAB4wK7SSl395nLTMQC0IQoQAADgs6b0aa+nTutNCQIAAADAI575YqM+WL3ddAwAbYQCBAAA+LSz8tP0+KRelCAAAAAAPOLCV79VWWW16RgA2gAFCAAA8Hnn9O+gR07pSQkCAAAAoNVWFe3TnR/8ZDoGgDZAAQIAAPzCjIEd2RMEAAAAgEfM/vdP+rGwxHQMAF5GAQIAAPzGzMGddN/J3U3HAAAAAODnKqprdNGr36m2ttZ0FABeRAECAAD8ysVD03UvJQgAAACAVvrgp+169ouNpmMA8CIKEAAA4HcuGdpJ95zUzXQMAAAAAH7uyjeWa8e+CtMxAHgJBQgAAPA7NptNlw/P0F0ndDUdBQAAAIAf276vQte9tcJ0DABeQgECAAD81jUjszR7XI7pGAAAAAD82OOfr9fCtTtMxwDgBRQgAADAr10/OluXD083HQMAAACAH7vglW9VUVVjOgYAD6MAAQAAfq9HUoTpCAAAAAD82IptJbr7P2tMxwDgYRQgAAAAAAAAAALebe+v0prt+0zHAOBBFCAAAMDvnZCbqBAXP9YAAAAAaLmyqhpd/K/vVFtbazoKAA/hlQIAAOD3EtoF6bTe7U3HAAAAAODn3v2xSP/8erPpGAA8hAIEAABYQrekdqYjAAAAALCAy1//QeVV1aZjAPAAChAAAGAJfVMjTUcAAAAAYAHb9pZrT2mV6RgAPIACBAAAWILdZjMdAQAAAIBFVFTXmI4AwAMoQAAAAAAAAADgEOVVFCCAFVCAAAAAS2AJLAAAAACeQgECWAMFCAAAsAS3065OMSGmYwAAAACwAAoQwBooQAAAgCW4HHZ1jA41HQMAAACABbAHCGANFCAAAMASSsqrtGzDbtMxAAAAAFgAM0AAa6AAAQAAlvDmD9u0r6LadAwAAAAAFkABAlgDBQgAALCECT2TlBIRbDoGAAAAAAsoZwkswBIoQAAAgCUEOR16YEJ30zEAAAAAWEB5FbPLASugAAEAAJZxfG6ihmXEmI4BAAAAwM9VVNWajgDAAyhAAACAZbgcdi24YJD6d4gyHQUAAACAH2MPEMAanKYDAL6gsLBQ27dvr3esvLxcbrfbUCIAQEu5nXa9dFZf9bnnY+3cX2k6DgAAAAA/VF7NEliAFVCAAJLmzJmj2bNn/+Z4fHy8gTQAgNbqGBOq587ooxMe/1zVNUxdBwAAANA8zAABrIECBJA0Y8YMFRQU1Ds2efJkZoAAgB8bm5Og8wd20EOf/WI6CgAAAAA/wx4ggDVQgACSEhISlJCQUO9YUFCQ7Ha2yQEAf3bvyd21pbhcr32/1XQUAAAAAH4ir32ETuyWaDoGAA/g1V0AAGBZToddz5/ZR/lpkaajAAAAAPBxDrtNNx2drcWXDVOXhHDTcQB4AAUIAACwtBCXQ++eP1CDOkabjgIAAADAR3WOD9OnlwzRbcflyO3kJVPAKvjfDAAALC8m1K0HJ/YwHQMAAACAD7psWLq+unK4BvCmKcByKEAAAEBA6JUSodnjckzHAAAAAOAj0qKCteCCgfr7yd0V6marZMCKKEAAAEBAsNlsuuqoTPVIbmc6CgAAAADDzs5P1XdXH6XRneNNRwHgRRQgAAAgYLgcdj16ai/ZbaaTAAAAADAhPtytudPy9eSUPEWGuEzHAeBlFCAAACCgDOwYzYboAAAAQAAq6JGk768+Sif3SDYdBUAbYXE7AAAQcHaWVpqOAAAAAKCNRAQ7dV9Bd53VN1U2G9PBgUBCAQIAAAJOOBscAgAAAAFhdHacnpjcSx2iQ01HAWAAS2ABAICAkxUXZjoCAAAAAC8Kcdl1X0F3vXf+QMoPIIBRgAAAgIDz+zHZbIQOAAAAWNSADlH6+qoRumRouuz84A8ENAoQAAAQcLomttPJ3ZNMxwAAAADgYQM7RuuTS4aoc3y46SgAfAAFCAAACEhn9Ek1HQEAAACAh/3fsV3kdPCSJ4ADeDYAAAABaUtxmekIAAAAADxoSKdoHd05znQMAD7EaToAAABAW3ros5/1wertmrey0HQUAAAAAB70h2O7yGZjzw8A/0UBAgAAAkbh3nJdNvd7VdXUmo4CAAAAwIOGZcRoVDazPwDUxxJYAAAgYKzZsY/yAwAAALCgW49h9geA36IAAQAAAWN3aaXpCAAAAAA8bHhGjEZmxZqOAcAHUYAAAICA0b9DtJIjgkzHAAAAAOBB7P0BoDEUIAAAIGDEhrl1x3E5pmMAAAAA8JCjMmN1VBZ7fwBoGAUIAAAIKJN6pahdkNN0DAAAAAAe8Idju5iOAMCHUYAAAICAEhbkVJjbYToGAAAAgFYalRWn4Zns/QGgcRQgAAAg4JzUPcl0BAAAAACtdOuxnU1HAODjKEAAAEDAiQ5xmY4AAAAAoBVGZ8dpWAazPwAcHgUIAAAIOGf1TVUoy2ABAAAAfou9PwA0BQUIAAAIOLlJ7fTUab1NxwAAAADQAmM6x2lIeozpGAD8AAUIAAAISKf0StF1I7NMxwAAAADQTGf0STUdAYCfoAABAAAB67bjumhQx2jTMQAAAAA0w479FaYjAPATFCAAACBguRx2/fOsvkqNDDYdBQAAAEATbd5TZjoCAD9BAQIAAAJaWnSInjk9T8FOfiwCAAAA/MEmChAATcRv+gAAIOAdlRWnm8Zkm44BAAAAoAk2FVOAAGgap+kAgC8oLCzU9u3b6x0rLy+X2+02lAgA0NYuH5ahv328Ttv3sZ4wAAAA4MtYAgtAU1GAAJLmzJmj2bNn/+Z4fHy8gTQAABPCgpy6bmSWrnlruekoAAAAAA5j054y1dbWymazmY4CwMdRgACSZsyYoYKCgnrHJk+ezAwQAAgw5w/qoDv+vVq7SytNRwEAAADQiLKqGu0qrVRMKK/bADg8ChBAUkJCghISEuodCwoKkt3ONjkAEEgigl26cHBHzf73T6ajAAAAADiMzXvKKEAAHBGv7gIAAByioqrGdAQAAAAAR7CJfUAANAEFCAAAwCG2FJebjgAAAADgCChAADQFBQgAAAAAAAAAv7K5mAIEwJFRgAAAABzioiGd5LTbTMcAAAAAcBjMAAHQFBQgAAAAhxiSHqOHJvYwHQMAAADAYVCAAGgKp+kAAAAAvmb6wI5aUViiv3601nSUBsWEupQcEaykdkFKjghScrtgJUcEKTbMrW82F+vdH4v0w9a9pmMCAAAAXsMSWACaggIEAACgAbPHddXHa3do2YY9pqPIYbfpzD7tddVRmeocH6Ygp+Ow5/9F0sbdpXrvxyK9+2OR3l9VpF2llW0TFgAAAGgDKwtLtHN/hWJC3aajAPBhFCAAAAANcDvtunlMZ41/YqmxDA67TVP7puqGo7OVFRfWrPumRoXo3AEddO6ADqquqdWyDbv1+OfrNWfxei+lBQAAANrOvopq/fWjtbr9uBzTUQD4MPYAAQAAaMQJuYnqnRLR5o/rtNt0Xv8OWnX9SD1xWu9mlx//y2G3aUDHaD16ai/NnZav6BCXh5ICAAAA5vx94Vrt2FdhOgYAH0YBAgAA0AibzaZbj+3Sxo8pfT5rmB6b3EsZsa0rPhpyco9kfXPVCA3LiPH4tQEAAIC2VFJerb98tMZ0DAA+jAIEAADgMI7vmqCJPZPb7PHG5yYqLzXSq4+RFh2iD2YO0i3HdJbd5tWHAgAAALzqvk/WaXtJuekYAHwUBQgAAMBhOB12PT2lt8Z3S2yTx7tmZFabPI7TYdetx3bRfy4arGn90pSbGC4bZQgAAAD8TEl5te7+z1rTMQD4KDZBBwAAOIJQt1MvT83X45+v1yX/+k41td55nEEdozUkvW2XphqWEathGbGSpOKySn25cY8+X79bn2/YraUbdmv9rtI2zQMAAAA0132frtOVIzKU0C7IdBQAPoYCBAAAoAncTrsuHNxJPxaW6O8L13nlMa4ZmemV6zZVRLBLR2XF6aisuLpjW4vLlH3nByoprzaYDAAAAGjc/opq/fk/a/TnE3NNRwHgY1gCCwAAoBluPqazBneK9vh1s+LCNL5bksev21pJEcEKc/OeGQAAAPi2Bz5dp2172QsEQH0UIAAAAM0QE+rW29MHqGN0iEeve+WIDDl8dEfyEBc/MgIAAMC3lVbW6K4PfzIdA4CP4bdZAACAZooKcenFs/pqYEfPzAQJdTt0Zp9Uj1zLG0JcDtMRAAAAgCN66LOftbW4zHQMAD6EAgQAAKAFBnaM1gcXDtKoQ/bLaKkJPZLULth3l5miAAEAAIA/KK2s0Z+YBQLgEBQgAAAALRTicuiNc/upe1K7Vl3n7Pw0DyXyjhAnPzICAADAPzz82S/awiwQAL/it1kAAIBWCHE5NGtYujrFtGxPkPaRwRrpgVkk3hQe5LuzUwAAAIBDlVXV6M4PmAUC4AAKEAAAgFaw222aPrCj/j1zkJ4/o4+GdKq/L8h1I7MOe/+z+qb67ObnByWEB5mOAAAAADTZI4t+0aY9paZjAPABFCAAAAAekBEbpil92uuN8/rrsmHpdcdTIg9fHpyd77ubnx+U1I4CBAAAAP6jvKpGs//NLBAAEusZAAAAeFBMqFt/O6mbxnSO19L1uw97br+0KOUktm7/kLaQSAECAAAAPzNn8XpdNzJLadEtW6oWgDUwAwRNsmrVKs2YMUPZ2dmKjY1Vjx49dP3112vnzp2mowEA4HNsNpsqqmp0+4JVmvXaDw2eY7dJfz6xaxsnaxlmgAAAAMDfVFTXaPYHq03HAGAYBUgAe++99xQeHq758+cf9rzPPvtMw4cP1wsvvKAtW7aovLxc69at0/33368hQ4Zo8+bNzX7svXv36q677tKwYcOUkpJSV6rMmjVL69ata/A+CxYsUHh4+GE/MjIymp0FAABvmNAzWZ9dOlTH5SQ0ePv/je2iEZm+vfn5QcwAAQAAgD96bMl6rd+133QMAAZRgASwp5566ojn7Nu3T2effbZKSko0fPhwLVmyREVFRZo3b54yMjK0YcMGTZ8+vVmPu23bNo0YMUL/93//p6+++krFxcV1pcrjjz+ugQMHNljKrFq1qlmPAwCAaQM6Ruvs/FTltY+oO9a/Q5Q+uWSIbjy6s8FkzcMMEAAAAPijyupanfX8VyrcW246CgBDKEAC1DPPPKPXX3/9iOc9+eST2rJli9LS0vTyyy+rW7duCgkJ0fDhw/Xqq6/K7Xbr448/1uLFi5v82FdeeaVWrVqlyMhIPfzww1q/fr02bdqkN998U7169dK+ffs0depUrVmzpt79fvrpwOZVN954o0pKShr8WLt2bfP+IQAA8LLJee31z7P6KjexnR6a2FOLLh2qIekxpmM1CzNAAAAA4K8+XrtTfe75WJ+tYxl3IBBRgASQJ598UtOnT1dOTo4uvPDCJt1n7ty5kqSZM2cqLCys3m3Z2dk68cQTJalJZYokbd68WW+++aYk6fHHH9eZZ56pmJgYRUZGauTIkfr3v/+tHj16qLS0VPfee2+9+x4sQHJzc5v0WAAA+Irs+HB9eNFgTeiZLLvdZjpOs8WGuuXww9wAAACAJG3aU6YRD36mexeuVW1trek4ANoQBUgAeeSRR/Tiiy9q48aNTTq/tLRUS5culSSNGTOmwXMOHl+4cGGTrrlo0SLV1NSoffv2Gjt27G9uDw4O1sUXXyxJ+uSTT+rdRgECAIAZdrtN14/KMh0DAAAAaLGqmlrNeu0HTXn2S5WUV5mOA6CNUIAEkOeee05Lliyp+0hOTj7s+WvXrlV1dbVcLpdycnIaPKdnz56S/ltOHMnB8qVr166NnpOQcGCz2H379tUdKysr08aNGxUcHKy1a9fqpJNOUkpKiuLj49WvXz/98Y9/1N69e5uUAQAANN/tx+XozyfwJgQAAAD4t39+vVn9/rZQy7fyOhIQCJymA6DtZGRk1Pu7y+U67PkHy4rk5GTZ7Q13ZSkpKZKkkpIS7dixQ7GxsYe95pgxY5SSkqLU1NRGz/n6668lSR07dqw7tmbNGtXU1KiiokITJ06sd/6KFSu0YsUKvfzyy3rrrbfUvn37w2YAAAAtc/XITEWHunT+y9+ohpUDAAAA4KdWFpao/98X6rFJvXRaHq8jAVZGAYJGlZSUSJLCw8MbPefQ2/bt23fEAiQ3N/ewS1ht2LBBDz74oCTV7S8i/XeGSU1NjQYNGqQ77rhDPXv2VHFxsd544w3dfPPNWr16taZOnaoFCxbIZmt8nfL8/PzDZjxo7dq1Sk9PV2FhYZPOt4qioiLTEYAmY7zCn1hlvJ6YHqzHju+kC175VpU1NabjwFtKi00nAJqO8Qp/wniFP7H4eN23X5ry6Ada0L+Dbj22i9xOFsrxhurq6sO+Tgd4GwUIGlVRUSFJcrvdjZ5z6G379+9v1eMtXrxY5513nrZv367MzEydc845dbft3btXXbt2VWZmpp566ikFBQVJOrBnyPTp09WlSxeNGzdOS5Ys0bvvvtvg/iIAAMAzju+WqBdD++jfq7bL7bTL7bAryGGX22mT23ngc5fjwC+QldU1qqiuUWV1rSpralVZVaOKmlrtKa3QM19sUmllteGvBgAAAIHs8c/X6+vNxXpsUk+lRIaYjgPAwyhA0KiD5UZ5eXmj55SVldV9frCUaK4tW7bo1ltv1fPPP6/a2lq1b99er732msLCwurOOfPMM3XmmWc2eo1hw4bp6KOP1vvvv6/58+cftgBZtmxZk3Ll5+fLbrfX7UkSaAL164Z/YrzCn1hlvE5ISNCEAa27xnUn7NN5//xG/1mzwzOh4HmhUaYTAE3HeIU/YbzCnwTAeP1ipzTmmZV64cw+OrpzvOk4luJwOFTDzHEYxNwuNOrg8lYHl8JqyKEbjx9aWDRFZWWl/vKXv6hXr1567rnnVFtbq8mTJ2vx4sVKT09vdt6hQ4dKavqG7AAAwKyM2DD9e+YgPTChh8LcDtNxAAAAEMC276vQMY8u1h0LVqmGDe8Ay6AA8TNz585VeHh4kz4Ot9dGUxzcqHzr1q2NNrVbtmyRdGApqvj4pjfkP//8s0aNGqVbbrlF+/fvV35+vt599109/vjjio6OblHeg/uPHG7GCgAA8C12u00XDemk764+SqOy4kzHAQAAQACrrZVumv+jxj/xuXburzAdB4AHsASWn4mIiFB2dnaTzk1JSWnVY2VmZsrpdKqyslIrVqxQt27dfnPO999/L0nKyspq8oZGP/74o8aNG6dt27YpMjJSd911l84444xGz6+urtYHH3wgSRo0aFCjm7IXFx/YnCsmJqZJOQAAgO9Ijw3VgpkD9ejiX/S7t1dqV2ml6UgAAAAIUG+vKFTfez7WK1Pz1TctynQcAK1AAeJnRo8era+++qpNHis4OFj9+vXTokWLtGDBggYLkAULFkiSRowY0aRrVlVVacqUKdq2bZuysrL0+uuvq2PHjoe9j8Ph0KWXXqqNGzfqb3/7m6ZPn97geYsXL5Yk5eXlNSkLAADwLTabTRcM6qRTe6XoD++t0gOf/qxqlh8AAACAAT/vLNWQ+z/VAxN66LwBHUzHAdBCLIGFwyooKJAkPfLIIyotLa1329q1a/Xmm29KkiZOnNik682dO1erVq1SaGio5s6de8Ty46CTTjpJknTffffV23fkoG+++Ubz5s2T4EaTbwAAUslJREFU3W7XKaec0qRrAgAA3xQT6tbfT+6u764eoXFdrbFpPAAAAPxPeVWNpr/0ja54/XvemAP4KQoQHNa0adOUnJys9evXa9KkSVq5cqXKysq0cOFCTZgwQeXl5RozZoz69+9f734PP/yw8vLylJeXp82bN9cdPzhj5IQTTmjWRueXXHKJQkNDtWbNGo0fP16ffvqp9u3bpx07dui5557T+PHjVVVVpXPPPbfJS4QBAADf1jWxnd6ePkDvzBig3MSGl8AEAAAAvO1vH6/T+Cc+V3EZy7QC/oYlsHBYoaGheuaZZ1RQUKAPP/xQ+fn59W5PT0/Xww8//Jv77dixQ6tXr5YkVVb+95vDjz/+KEl66aWX9NJLLx32sTt06KDly5dLktLS0vTwww9r+vTpWrp0qY499tjfnH/88cfrzjvvbN4XCAAAfN6xOQn6JjtOjy5er5vfWakd+/nFEwAAAG1r3opCDb7vU715bn+lx4aajgOgiZgBgiMaOHCgFi5cqClTpigpKUlBQUFKT0/XZZddpoULFyoxMbHJ19q9e3eLc0yYMEEff/yxTj/9dKWmpsrlcikqKkrDhg3TY489phdffFHBwcEtvj4AAPBdToddFw3ppNW/G6UrR2TIabeZjgQAAIAA88PWver/94X6ZO0O01EANJGtpKSEBeyABuTn58tut+uHH34wHaVNFRYWSpISElhzHb6P8Qp/wnj1rFVFJbrmzeV644dtpqNY0/7dB/4MjTKZAmgaxiv8CeMV/oTx2ii3w645k3pqan6a6Sg+r1u3bqqpqdGyZctMR0GAYgYIAAAA/E7n+HC9fm5/LbhgoLoltTMdBwAAAAGkorpGZ7/wtX739grVsDk64NMoQAAAAOC3RneO11dXDtfdJ+YqPMhhOg4AAAACyJ0f/KSJTy1TSXmV6SgAGkEBAgAAAL/mcth11VGZWnndSJ3WO8V0HAAAAASQ177fqmH3f6oNu0pNRwHQAAoQAAAAWEL7yBC9cFZffXDhIHVNDDcdBwAAAAHi683F6v/3hfp8/S7TUQD8DwoQAAAAWMrIrDh9feUIPXJKT2XFhZmOAwAAgACwdW+5RjzwmV78apPpKAAOQQECAAAAy3E77Tp/UEetvG6kXjm7r/qlRZmOBADwc6mRwYoPd8tmM50EgK8qq6rRlGe/1K3v/qjaWjZHB3yB03QAAAAAwFscdpsm9kzRhB7J+s+aHfrTBz/p3R+LTMcCAPiJDtEhmtK7vU7v0149ktvJZrOpuqZWO/ZVqGhfhQpLylW4t1yFJRUq2nfgz4PHDtxeod2llaa/DABt7A/vrdKKbSV6ckpvhbgcpuMAAY0CBAAAAJZns9k0MitOI7Pi9O3mYj3x+Xq98NUmFZZUmI4GAPAxsaEuTeqdotPz2mtwpxjZ7fWnfDjsNiW0C1JCuyB1U7sjXq+iqkbb91VoS3GZvv5pvdbvKlVhTYjW7dyvtTv26+dd+1VZzTvFAat56ZvNWrdzv/5z0SCFunkJFjCF/30AAAAIKD1TIvS3k7vr7hNz9e/V2/Xcl5s09/stKimvNh0NAGBImNuhk7sn6fQ+7TWmc7xcDs+tGO522pUSGayUyGClBR0o3hMSEupur66p1eY9ZXWFyLqd+7V25766z7cUl3ssC4C2tXTDbs1ZvF6zhmeYjgIELAoQAAAABCSnw65jcxJ0bE6C9lf00Bs/bNPTyzZq/spC09EAAG3A5bBpbJcEnd6nvU7MTVRYkJmXSBx2m9KiQ5QWHaLhmbG/ub20slqb95Rp5/5K7dhfoR37KrRjf8WBv++r0I5f/9xZWqEd+w6cU1xWZeArAdCQP/9njWYO7qggJ0thASZQgAAAACDghbqdOi2vvU7La69HFv2si//1vaprWI4EAKzGZpNGZMTq9D7tNbFnsmJC3aYjHVGIy6HMuDBlNuM+ldU12rm/UjvrCpMDJcmm4jJ9vn63Fv28Uzv2szcJ0BY27SnT08s2asbAjqajAAGJAgQAAAA4xAWDOqljdKgmPf2F9pbzDloAsILYUJeuOipTZ/VNVWpUiOk4Xudy2JXYLkiJ7YIavL22tlY/bd+nRb/s0mc/79Kin3fp+63FovsHvOPOD37SOf3S5PTg8noAmoYCBAAAAPgfY3MS9MklQ3T8Y0u0cU+Z6TgAgBYKD3LoqhGZunJEhiKCXabj+Aybzabs+HBlx4dran6aJGlvWZU+X7+rrhRZ/Msu7SpllgjgCWt37NeLX2/WmX1TTUcBAg4FCAAAANCAnikRWjJrmE54fIm+2lRsOg4AoBmCnHZdPKSTfjcqS3HhDc+CQH3tgp0a3TleozvHS5Jqamq1qqhEi345UIq89PVm7WFvEaDFZv97tU7Pay+73WY6ChBQmHcFAAAANCIlMlgfXzyk0SVEAAC+xWG3acbADlp9/Sj9ZXw3yo9WsNttyklsp3P6d9Cjp/bSosuGKj0m1HQswG8t31ai177fajoGEHAoQAAAAIDDCA9yatqvy4MAAHzX5N4pWn7tUXr01F5Ki7b+Ph9trWtiOy2ZNVSDO0WbjgL4rdsXrFJtLZvtAG2JAgQAAAA4gukDO5iOAABoxLiuCfryiuF68ay+6hwfbjqOpcWHB+nfMwfptN4ppqMAfumrTcV6Z2Wh6RhAQKEAAQAAAI4gKy5Mo7LiTMcAABxiaHqMPr54sN6ePkB5qZGm4wSMYJdDz5/ZRzeP6Ww6CuCXbl+wmlkgQBuiAAEAAACa4HxmgQCAT+iVEqG3p/fXxxcP1rCMWNNxApLNZtMfxnbR01N6y+VgQ2egOT77eZc+WrPDdAwgYFCAAAAAAE1wco8kxYa6TMcAgICVHRemF8/soy+vGK5xXRNls/HCu2ln5adpwQWDFMP3R6BZ7liw2nQEIGBQgAAAAABNEOR0aFo/NkMHgLY2sGO0nj09Tz9ce5Qm57WX3U7x4UuGZ8Zq8WVDlR0XZjoK4DcWrN6uJb/sMh0DCAgUIAAAAEATXTCoo+kIABAQgpx2nZ2fqqWXD9Oiy4bqjL6pcjl4CcNXZceHa/GsoRqRyZJkQFMxCwRoG/z0AAAAADRRdny4ju0SbzoGAFhWWlSwZo/L0YbfH60np+QpPy3KdCQ0UUyoW++dP1Bn56eajgL4hTeXb9PyrXtNxwAsz2k6AOALCgsLtX379nrHysvL5Xa7DSUCAAC+6pKh6Xr3xyLTMQDAUkZlxemSoZ10Ym6inMz08Ftup13/OK23OseH68b5K03HAXze91v3KjepnekYgKVRgACS5syZo9mzZ//meHw87/AEAAD1HZeToPSYUK3bud90FADwa2Fuh6bmp+riIenqxguAlmGz2XTD0dnKigvT1Be+UnlVjelIgM8qKik3HQGwPAoQQNKMGTNUUFBQ79jkyZOZAQIAAH7DYbfposGddM1by01HAQC/lB0XpouHdNLZ/dIUFeIyHQdeMql3ijpEh2j8E5+rqKTCdBzAJxXt4/8G4G0UIICkhIQEJSQk1DsWFBQku52p1wAA4LfOHZCm37+zUmW8qxUAmsRmk8blJOiSoek6pnO87Hab6UhoAwM7Ruubq0Zo9r9/0qOLf2E2CPA/KAcB7+PVXQAAAKCZYkLdumRouukYAOAXxnSO0+rrR+mt6QM0NieB8iPAJEcE696C7lpzwyhdOjRdQU5eigIO2s4MEMDr+K4DAAAAtMDscTk6pjP7hQHA4Uzrl6a3pw9QZlyY6SgwrH1kSF0RcsmQTnKz2T2gon3sAQJ4G99tAAAAgBZwOux6aWpf5SaGm44CAD7p5jGd9cTkXnLxQjcO0T4yRPdN6EERAoglsIC2wHcZAAAAoIUiQ1x667wBigtzm44CAD7DYbdpzqk99YexXWSzsdwVGpYa9d8i5GKKEAQolsACvI/vLgAAAEArpMeG6rVz+vHCDQBICnU79Ma5/TR9YEfTUeAnUqNCdD9FCALU9n0Vqq2tNR0DsDS+qwAAAACtNCQ9Rk9M7mU6BgAYlRDu1kcXDda4rommo8APUYQgEFXV1Gp3aaXpGICl8d0EAAAA8IAz+qbqyhEZpmMAgBGd48O06LKhyk+LMh0Ffu5gEfLT70bposEUIbA+lsECvMtpOgAAAABgFXce31VLN+zWwrU7TUcBgDYzuFO03ji3v2LZDwkelBYdogcm9tD1o7I09/stkiSn3S6HXXLYbHWfH/jTVv9zW/3j63eVav7KIr2zslC7eLc9fExRSYWy402nAKyLAgQAAADwEJfDrn+e1Vd9/vqxtu4tNx0HALyuoEeSnjujj0JcDtNRYFFp0SG6bFjrZ1ielZ+mquoafb5+t+avLNS8lYX6cuMeDyQEWqeIGSCAV1GAAAAAAB6UHBGsl6b21ciHFqm6hk0tAVjXpUPTdc9J3eSw20xHAZrE6bBrcHqMBqfH6LbjcrS1uEzvrCzSvJXb9N6PRdpTVmU6IgIQS2AB3kUBAgAAAHjYsIxY3XVCV131xnLTUQDAK+4+MVdXjsiQzUb5Af+VFBGsaf3TNK1/miqra7T4l12at6JQ81YU6tstxabjIUAUlTBrGPAmChAAAADAC64YnqFFP+/SK99uMR0FADzG7bDrqSm9dVpee9NRAI9yOewalhGrYRmxmn18V23cXap3fl0qa8Gq7dpbzuwQeAdLYAHeZTcdAAAAALAim82mJyb3Vpf4MNNRAMAjokJceu+CAZQfCAipUSGaPrCj/jWtnwr/cIxGZMaajgSLKmbpNcCrKEAAAAAAL2kX7NS/pvVTmJvNgQH4t7SoYH1yyRCNyIwzHQVoc8Euh149O19ZcbypAZ7XJT7cdATA0ihAAAAAAC/KTWqnxyf1Mh0DAFosOSJIiy4bqm5J7UxHAYyJDXPrzXP7KTKY1eThWXntI0xHACyNAgQAAADwssl57TVrWLrpGADQbDab9OzpfdQ+MsR0FMC4nMR2euXsfDnsNtNRYCF5qZGmIwCWRgECAAAAtIG7TsjVkE7RpmMAQLPcdHS2RmWz7BVw0NGd43VfQXfTMWARHaNDFBPqNh0DsDQKEAAAAKANuJ12/XNqXyWE80suAP8wLCNGN4/pbDoG4HMuHNxJlzGzEx6Q157ZH4C3UYAAAAAAbaR9ZIj+eVZfsXIGAF8XE+rSc6f3kdPBywZAQ/5yYq7G5sSbjgE/14flrwCv4ycZAAAAoA0dlRWn2eO6mo4BAIf1j8m9lRbNvh9AY5wOu148s69yE8NNR4EfYwYI4H0UIAAAAEAbu2Zkpk7unmQ6BgA0aNawdI3nOQo4osgQl946b4DiwljeEi3ThwIE8DoKEAAAAKCN2Ww2PXlab2XHhZmOAgD19EmN1J9OYJYa0FTpsaGaOy1fbpaLQzMlhLuVHBFkOgZgeTw7AwAAAAZEhrj0xrn9FM+m6AB8RHiQQy+e2UdBTofpKIBfGZoRqzmTepqOAT+T1z5SNhsbwwHeRgECAAAAGJKT2E7vnT9QUSEu01EAQA9P7KnsePYzAFpian6afjc6y3QM+BE2QAfaBgUIAAAAYFDv9pGaN72/wty84xqAOef0S9MZfVNNxwD82u1jczShB/vnoGnYAB1oGxQgAAAAgGGDOsXojXP7K8jJj+cA2l5OQrjuK+huOgbg9+x2m56eksc7+9EkbIAOtA1+wwIAAAB8wKjsOL1ydr6cdtaCBtB2gpx2/fOsvgoLcpqOAlhCWJBTb5zbj82tcVgRwU6lx4SajgEEBAoQAAAAwEeckJuoM1mCBkAbuuekbuqZEmE6BmAp7SND9Ma5/RXi4mU3NCyvfaTsvOkFaBM8EwMAAAA+ZMaADl69fkK4W71TIjSoY7T4vRsIbBN7JmvmoI6mYwCWlJ8Wpaen5JmOAR+V157iGWgrzHEFAAAAfMigTtHKTQzX8m0lrbpOsNOuP5+Yq/aRwUqJOPCRFBEkl+O/74HatKdUz36xSU8u3aCVha17PAD+pVNMiB6b1Es2G00o4C2n9ErR7ceV6Kb5P5qOAh8zKivOdAQgYDADBAAAAPAhNptN5w9s/Tuyy6pqNKZzvAp6JGtAx2ilRYfUKz+kA0t0XDcqS8uvPUqLLxuqCwd3VFSIq9WPDcC3dYoJ0b9nDuL/O9AGbhidrZO7J5mOAR/SITpE47ommo4BBAwKEEBSYWGhli9fXu+jvLxc1dXVpqMBAIAAdFZ+qoKcrf9R/c0ftjXpPJvNpgEdo/XgxJ7acssYPXxKT2XGsjEnYEVZcWH6+KIhyogNMx0FCAg2m00Pn9JTsaEUjjjg/IEd5GAdUqDNUIAAkubMmaP+/fvX+1i3bp127txpOhoAAAhAMaFundIzudXXeWtF0wqQQwW7HCrokayPLh6iv53UjXeIAxbSNTFcH188WGnRIaajAAElsV2Q7p/Qw3QM+ACXw6bz+nt3vzcA9VGAAJJmzJihzz//vN5Henq6YmJiTEcDAAABasbA1v9y/Mm6ndq1v6JF93U57Jo1PEM//W6ULhnSiXcqAn6uZ3KE/nPhYCVHBJuOAgSkyb1TVNCDpbAC3cQeyUrieRhoUxQggKSEhATl5ubW+wgKCpLD4TAdDQAABKjhGbHKimvdEjXVNbV6Z2VRq64RG+bWfRN66NurRujYLvGtuhYAM/LTIvXhRYOU0C7IdBQgYNlsNj00kaWwAt1FQzqZjgAEHAoQAAAAwAfZbDad2z+t1dd5+osNHkgj5Sa10/wZA3TF8AyPXA9A2xjcKVoLLhikmFC36ShAwGMprMDWLamdhqaz0gjQ1ihAAAAAAB91dn6aWrvy1Dsri/T+j62bBXKQzWbTX8bn6nejszxyPQDedVRmrN49f6Ai2csH8BkshRW4LhrcSTYbS4oCbY0CBAAAAPBRKZHBGtc1sdXXufKNH1RVXeOBRAdKkDuOy9Gtx3T2yPUAeMcxneP19vT+Cg9ymo4C4BAshRWYwoMcOrNve9MxgIBEAQIAAAD4ME8sg/X91r16bMl6D6Q5wGaz6ZZju+iP43I8dk0AnnNibqLeOK+fQt2UH4AvYimswHNW31RFBFN6ASbw0xAAAADgw07ITVRCuFuFJRWtus7v3/lRp+W1V5QHl8L53ehspceE6r5P1umzn3d57LpNEeKyKz8tSoM7xig9NkRFJRXatrdc20rKtXVv+YHP95ZrT1lVm+YCTDu1V7KePb2P3E7e7wj4ssm9U/TSN5s197utpqOgDVw4uJPpCEDAogABAAAAfJjLYdf5Azvq9gWrW3Wd7fsqdMeC1frzibkeSnbAaXntdVpee60qKtHTyzbqqaUbtHFPmUcfQ5I6xYRoUMcYDeoYrUGdotUrJUIux5Ff4C2rrNa2veVasn633v2xUO+sLNLmYs/nA3zBWX1T9cTkXnI24f8GALMOLoX18Zod2rG/0nQceNHQ9Bj1SI4wHQMIWBQgAAAAgI/7w7F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      "text/plain": [
       "<Figure size 800x1200 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 1200,
       "width": 800
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "mask_lu.plot(figsize=(8,12))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7b7671b6",
   "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": "3.6.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}