{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>FECHA</th>\n",
       "      <th>CHUQUIBAMBILLA</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1956-01-01</td>\n",
       "      <td>142.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1956-02-01</td>\n",
       "      <td>75.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1956-03-01</td>\n",
       "      <td>42.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1956-04-01</td>\n",
       "      <td>8.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1956-05-01</td>\n",
       "      <td>3.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>691</th>\n",
       "      <td>2013-08-01</td>\n",
       "      <td>7.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>692</th>\n",
       "      <td>2013-09-01</td>\n",
       "      <td>5.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>693</th>\n",
       "      <td>2013-10-01</td>\n",
       "      <td>57.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>694</th>\n",
       "      <td>2013-11-01</td>\n",
       "      <td>44.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>695</th>\n",
       "      <td>2013-12-01</td>\n",
       "      <td>215.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>696 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         FECHA  CHUQUIBAMBILLA\n",
       "0   1956-01-01           142.8\n",
       "1   1956-02-01            75.1\n",
       "2   1956-03-01            42.6\n",
       "3   1956-04-01             8.1\n",
       "4   1956-05-01             3.6\n",
       "..         ...             ...\n",
       "691 2013-08-01             7.4\n",
       "692 2013-09-01             5.3\n",
       "693 2013-10-01            57.3\n",
       "694 2013-11-01            44.6\n",
       "695 2013-12-01           215.8\n",
       "\n",
       "[696 rows x 2 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%reset -sf\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "file=\"Chuquibambilla_Puno.xlsx\"\n",
    "data=pd.read_excel(file)\n",
    "data\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>CHUQUIBAMBILLA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FECHA</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1956-01-01</th>\n",
       "      <td>142.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1956-02-01</th>\n",
       "      <td>75.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1956-03-01</th>\n",
       "      <td>42.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1956-04-01</th>\n",
       "      <td>8.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1956-05-01</th>\n",
       "      <td>3.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-08-01</th>\n",
       "      <td>7.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-09-01</th>\n",
       "      <td>5.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-10-01</th>\n",
       "      <td>57.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-11-01</th>\n",
       "      <td>44.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-01</th>\n",
       "      <td>215.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>696 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            CHUQUIBAMBILLA\n",
       "FECHA                     \n",
       "1956-01-01           142.8\n",
       "1956-02-01            75.1\n",
       "1956-03-01            42.6\n",
       "1956-04-01             8.1\n",
       "1956-05-01             3.6\n",
       "...                    ...\n",
       "2013-08-01             7.4\n",
       "2013-09-01             5.3\n",
       "2013-10-01            57.3\n",
       "2013-11-01            44.6\n",
       "2013-12-01           215.8\n",
       "\n",
       "[696 rows x 1 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_idx=data.set_index(\"FECHA\")\n",
    "data_idx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1b4b1121f88>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# sacamos anomalias de enero\n",
    "data_ene=data_idx.loc[data_idx.index.month==1]\n",
    "data_ene\n",
    "data_ene_c=data_ene.loc[\"1981-01-1\":\"2010-01-01\"]\n",
    "data_ene_anom=data_ene-data_ene_c.mean()\n",
    "(data_ene_anom).plot(marker=\"*\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# levantamos el netcdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (lat: 89, lon: 180, nbnds: 2, time: 2010)\n",
       "Coordinates:\n",
       "  * lat        (lat) float32 88.0 86.0 84.0 82.0 ... -82.0 -84.0 -86.0 -88.0\n",
       "  * lon        (lon) float32 0.0 2.0 4.0 6.0 8.0 ... 352.0 354.0 356.0 358.0\n",
       "  * time       (time) datetime64[ns] 1854-01-01 1854-02-01 ... 2021-06-01\n",
       "Dimensions without coordinates: nbnds\n",
       "Data variables:\n",
       "    time_bnds  (time, nbnds) float64 9.969e+36 9.969e+36 ... 9.969e+36 9.969e+36\n",
       "    sst        (time, lat, lon) float32 ...\n",
       "Attributes:\n",
       "    climatology:               Climatology is based on 1971-2000 SST, Xue, Y....\n",
       "    description:               In situ data: ICOADS2.5 before 2007 and NCEP i...\n",
       "    keywords_vocabulary:       NASA Global Change Master Directory (GCMD) Sci...\n",
       "    keywords:                  Earth Science &gt; Oceans &gt; Ocean Temperature &gt; S...\n",
       "    instrument:                Conventional thermometers\n",
       "    source_comment:            SSTs were observed by conventional thermometer...\n",
       "    geospatial_lon_min:        -1.0\n",
       "    geospatial_lon_max:        359.0\n",
       "    geospatial_laty_max:       89.0\n",
       "    geospatial_laty_min:       -89.0\n",
       "    geospatial_lat_max:        89.0\n",
       "    geospatial_lat_min:        -89.0\n",
       "    geospatial_lat_units:      degrees_north\n",
       "    geospatial_lon_units:      degrees_east\n",
       "    cdm_data_type:             Grid\n",
       "    project:                   NOAA Extended Reconstructed Sea Surface Temper...\n",
       "    original_publisher_url:    http://www.ncdc.noaa.gov\n",
       "    References:                https://www.ncdc.noaa.gov/data-access/marineoc...\n",
       "    source:                    In situ data: ICOADS R3.0 before 2015, NCEP in...\n",
       "    title:                     NOAA ERSSTv5 (in situ only)\n",
       "    history:                   created 07/2017 by PSD data using NCEI&#x27;s ERSST...\n",
       "    institution:               This version written at NOAA/ESRL PSD: obtaine...\n",
       "    citation:                  Huang et al, 2017: Extended Reconstructed Sea ...\n",
       "    platform:                  Ship and Buoy SSTs from ICOADS R3.0 and NCEP GTS\n",
       "    standard_name_vocabulary:  CF Standard Name Table (v40, 25 January 2017)\n",
       "    processing_level:          NOAA Level 4\n",
       "    Conventions:               CF-1.6, ACDD-1.3\n",
       "    metadata_link:             :metadata_link = https://doi.org/10.7289/V5T72...\n",
       "    creator_name:              Boyin Huang (original)\n",
       "    date_created:              2017-06-30T12:18:00Z (original)\n",
       "    product_version:           Version 5\n",
       "    creator_url_original:      https://www.ncei.noaa.gov\n",
       "    license:                   No constraints on data access or use\n",
       "    comment:                   SSTs were observed by conventional thermometer...\n",
       "    summary:                   ERSST.v5 is developed based on v4 after revisi...\n",
       "    dataset_title:             NOAA Extended Reconstructed SST V5\n",
       "    data_modified:             2021-08-02</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-e90d5719-c8c0-4299-8f09-ab9527cf3bd6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e90d5719-c8c0-4299-8f09-ab9527cf3bd6' 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'>lat</span>: 89</li><li><span class='xr-has-index'>lon</span>: 180</li><li><span>nbnds</span>: 2</li><li><span class='xr-has-index'>time</span>: 2010</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-a46f096a-ce21-4eeb-b240-c5f18b236770' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a46f096a-ce21-4eeb-b240-c5f18b236770' 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'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>88.0 86.0 84.0 ... -86.0 -88.0</div><input id='attrs-b21c5f22-3111-4619-a9a7-09849c519cd0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b21c5f22-3111-4619-a9a7-09849c519cd0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e48c2b83-51bf-481d-abdb-403055f31338' class='xr-var-data-in' type='checkbox'><label for='data-e48c2b83-51bf-481d-abdb-403055f31338' 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>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>actual_range :</span></dt><dd>[ 88. -88.]</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>coordinate_defines :</span></dt><dd>center</dd></dl></div><div class='xr-var-data'><pre>array([ 88.,  86.,  84.,  82.,  80.,  78.,  76.,  74.,  72.,  70.,  68.,  66.,\n",
       "        64.,  62.,  60.,  58.,  56.,  54.,  52.,  50.,  48.,  46.,  44.,  42.,\n",
       "        40.,  38.,  36.,  34.,  32.,  30.,  28.,  26.,  24.,  22.,  20.,  18.,\n",
       "        16.,  14.,  12.,  10.,   8.,   6.,   4.,   2.,   0.,  -2.,  -4.,  -6.,\n",
       "        -8., -10., -12., -14., -16., -18., -20., -22., -24., -26., -28., -30.,\n",
       "       -32., -34., -36., -38., -40., -42., -44., -46., -48., -50., -52., -54.,\n",
       "       -56., -58., -60., -62., -64., -66., -68., -70., -72., -74., -76., -78.,\n",
       "       -80., -82., -84., -86., -88.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-b1a36a46-6755-455b-b6e1-166694794840' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b1a36a46-6755-455b-b6e1-166694794840' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1b86d013-c47b-4e81-bc6b-27a483b9cb2e' class='xr-var-data-in' type='checkbox'><label for='data-1b86d013-c47b-4e81-bc6b-27a483b9cb2e' 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>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>actual_range :</span></dt><dd>[  0. 358.]</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>coordinate_defines :</span></dt><dd>center</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.],\n",
       "      dtype=float32)</pre></div></li><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'>1854-01-01 ... 2021-06-01</div><input id='attrs-68f1c8f2-dc4a-43a7-bf85-876c8d49f4cb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-68f1c8f2-dc4a-43a7-bf85-876c8d49f4cb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce0a2306-2993-4f7b-afff-c806f5dedbb0' class='xr-var-data-in' type='checkbox'><label for='data-ce0a2306-2993-4f7b-afff-c806f5dedbb0' 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>Time</dd><dt><span>delta_t :</span></dt><dd>0000-01-00 00:00:00</dd><dt><span>avg_period :</span></dt><dd>0000-01-00 00:00:00</dd><dt><span>prev_avg_period :</span></dt><dd>0000-00-07 00:00:00</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>actual_range :</span></dt><dd>[19723. 80870.]</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1854-01-01T00:00:00.000000000&#x27;, &#x27;1854-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1854-03-01T00:00:00.000000000&#x27;, ..., &#x27;2021-04-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-05-01T00:00:00.000000000&#x27;, &#x27;2021-06-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ff630e89-5fce-4cfc-8b63-4e88152ea43b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ff630e89-5fce-4cfc-8b63-4e88152ea43b' class='xr-section-summary' >Data variables: <span>(2)</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>time_bnds</span></div><div class='xr-var-dims'>(time, nbnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-92acd675-2909-4b86-98f8-291c64eb7cbe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-92acd675-2909-4b86-98f8-291c64eb7cbe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4bd32dbe-5421-4cfa-a6af-3685af68bad4' class='xr-var-data-in' type='checkbox'><label for='data-4bd32dbe-5421-4cfa-a6af-3685af68bad4' 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>Time Boundaries</dd></dl></div><div class='xr-var-data'><pre>array([[9.96921e+36, 9.96921e+36],\n",
       "       [9.96921e+36, 9.96921e+36],\n",
       "       [9.96921e+36, 9.96921e+36],\n",
       "       ...,\n",
       "       [9.96921e+36, 9.96921e+36],\n",
       "       [9.96921e+36, 9.96921e+36],\n",
       "       [9.96921e+36, 9.96921e+36]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1507aee4-ddbf-448a-a5a7-dc32b53281ae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1507aee4-ddbf-448a-a5a7-dc32b53281ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a2a55582-2c26-4a52-aca2-0e82f179b2c3' class='xr-var-data-in' type='checkbox'><label for='data-a2a55582-2c26-4a52-aca2-0e82f179b2c3' 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>Monthly Means of Sea Surface Temperature</dd><dt><span>units :</span></dt><dd>degC</dd><dt><span>var_desc :</span></dt><dd>Sea Surface Temperature</dd><dt><span>level_desc :</span></dt><dd>Surface</dd><dt><span>statistic :</span></dt><dd>Mean</dd><dt><span>dataset :</span></dt><dd>NOAA Extended Reconstructed SST V5</dd><dt><span>parent_stat :</span></dt><dd>Individual Values</dd><dt><span>actual_range :</span></dt><dd>[-1.8     42.32636]</dd><dt><span>valid_range :</span></dt><dd>[-1.8 45. ]</dd></dl></div><div class='xr-var-data'><pre>[32200200 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6ebd136d-8ae7-46f5-8460-54c7cb9534e6' class='xr-section-summary-in' type='checkbox'  ><label for='section-6ebd136d-8ae7-46f5-8460-54c7cb9534e6' class='xr-section-summary' >Attributes: <span>(37)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>climatology :</span></dt><dd>Climatology is based on 1971-2000 SST, Xue, Y., T. M. Smith, and R. W. Reynolds, 2003: Interdecadal changes of 30-yr SST normals during 1871.2000. Journal of Climate, 16, 1601-1612.</dd><dt><span>description :</span></dt><dd>In situ data: ICOADS2.5 before 2007 and NCEP in situ data from 2008 to present. Ice data: HadISST ice before 2010 and NCEP ice after 2010.</dd><dt><span>keywords_vocabulary :</span></dt><dd>NASA Global Change Master Directory (GCMD) Science Keywords</dd><dt><span>keywords :</span></dt><dd>Earth Science &gt; Oceans &gt; Ocean Temperature &gt; Sea Surface Temperature &gt;</dd><dt><span>instrument :</span></dt><dd>Conventional thermometers</dd><dt><span>source_comment :</span></dt><dd>SSTs were observed by conventional thermometers in Buckets (insulated or un-insulated canvas and wooded buckets) or Engine Room Intaker</dd><dt><span>geospatial_lon_min :</span></dt><dd>-1.0</dd><dt><span>geospatial_lon_max :</span></dt><dd>359.0</dd><dt><span>geospatial_laty_max :</span></dt><dd>89.0</dd><dt><span>geospatial_laty_min :</span></dt><dd>-89.0</dd><dt><span>geospatial_lat_max :</span></dt><dd>89.0</dd><dt><span>geospatial_lat_min :</span></dt><dd>-89.0</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>cdm_data_type :</span></dt><dd>Grid</dd><dt><span>project :</span></dt><dd>NOAA Extended Reconstructed Sea Surface Temperature (ERSST)</dd><dt><span>original_publisher_url :</span></dt><dd>http://www.ncdc.noaa.gov</dd><dt><span>References :</span></dt><dd>https://www.ncdc.noaa.gov/data-access/marineocean-data/extended-reconstructed-sea-surface-temperature-ersst-v5 at NCEI and http://www.esrl.noaa.gov/psd/data/gridded/data.noaa.ersst.v5.html</dd><dt><span>source :</span></dt><dd>In situ data: ICOADS R3.0 before 2015, NCEP in situ GTS from 2016 to present, and Argo SST from 1999 to present. Ice data: HadISST2 ice before 2015, and NCEP ice after 2015</dd><dt><span>title :</span></dt><dd>NOAA ERSSTv5 (in situ only)</dd><dt><span>history :</span></dt><dd>created 07/2017 by PSD data using NCEI&#x27;s ERSST V5 NetCDF values</dd><dt><span>institution :</span></dt><dd>This version written at NOAA/ESRL PSD: obtained from NOAA/NESDIS/National Centers for Environmental Information and time aggregated. Original Full Source: NOAA/NESDIS/NCEI/CCOG</dd><dt><span>citation :</span></dt><dd>Huang et al, 2017: Extended Reconstructed Sea Surface Temperatures Version 5 (ERSSTv5): Upgrades, Validations, and Intercomparisons. Journal of Climate, https://doi.org/10.1175/JCLI-D-16-0836.1</dd><dt><span>platform :</span></dt><dd>Ship and Buoy SSTs from ICOADS R3.0 and NCEP GTS</dd><dt><span>standard_name_vocabulary :</span></dt><dd>CF Standard Name Table (v40, 25 January 2017)</dd><dt><span>processing_level :</span></dt><dd>NOAA Level 4</dd><dt><span>Conventions :</span></dt><dd>CF-1.6, ACDD-1.3</dd><dt><span>metadata_link :</span></dt><dd>:metadata_link = https://doi.org/10.7289/V5T72FNM (original format)</dd><dt><span>creator_name :</span></dt><dd>Boyin Huang (original)</dd><dt><span>date_created :</span></dt><dd>2017-06-30T12:18:00Z (original)</dd><dt><span>product_version :</span></dt><dd>Version 5</dd><dt><span>creator_url_original :</span></dt><dd>https://www.ncei.noaa.gov</dd><dt><span>license :</span></dt><dd>No constraints on data access or use</dd><dt><span>comment :</span></dt><dd>SSTs were observed by conventional thermometers in Buckets (insulated or un-insulated canvas and wooded buckets), Engine Room Intakers, or floats and drifters</dd><dt><span>summary :</span></dt><dd>ERSST.v5 is developed based on v4 after revisions of 8 parameters using updated data sets and advanced knowledge of ERSST analysis</dd><dt><span>dataset_title :</span></dt><dd>NOAA Extended Reconstructed SST V5</dd><dt><span>data_modified :</span></dt><dd>2021-08-02</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (lat: 89, lon: 180, nbnds: 2, time: 2010)\n",
       "Coordinates:\n",
       "  * lat        (lat) float32 88.0 86.0 84.0 82.0 ... -82.0 -84.0 -86.0 -88.0\n",
       "  * lon        (lon) float32 0.0 2.0 4.0 6.0 8.0 ... 352.0 354.0 356.0 358.0\n",
       "  * time       (time) datetime64[ns] 1854-01-01 1854-02-01 ... 2021-06-01\n",
       "Dimensions without coordinates: nbnds\n",
       "Data variables:\n",
       "    time_bnds  (time, nbnds) float64 ...\n",
       "    sst        (time, lat, lon) float32 ...\n",
       "Attributes:\n",
       "    climatology:               Climatology is based on 1971-2000 SST, Xue, Y....\n",
       "    description:               In situ data: ICOADS2.5 before 2007 and NCEP i...\n",
       "    keywords_vocabulary:       NASA Global Change Master Directory (GCMD) Sci...\n",
       "    keywords:                  Earth Science > Oceans > Ocean Temperature > S...\n",
       "    instrument:                Conventional thermometers\n",
       "    source_comment:            SSTs were observed by conventional thermometer...\n",
       "    geospatial_lon_min:        -1.0\n",
       "    geospatial_lon_max:        359.0\n",
       "    geospatial_laty_max:       89.0\n",
       "    geospatial_laty_min:       -89.0\n",
       "    geospatial_lat_max:        89.0\n",
       "    geospatial_lat_min:        -89.0\n",
       "    geospatial_lat_units:      degrees_north\n",
       "    geospatial_lon_units:      degrees_east\n",
       "    cdm_data_type:             Grid\n",
       "    project:                   NOAA Extended Reconstructed Sea Surface Temper...\n",
       "    original_publisher_url:    http://www.ncdc.noaa.gov\n",
       "    References:                https://www.ncdc.noaa.gov/data-access/marineoc...\n",
       "    source:                    In situ data: ICOADS R3.0 before 2015, NCEP in...\n",
       "    title:                     NOAA ERSSTv5 (in situ only)\n",
       "    history:                   created 07/2017 by PSD data using NCEI's ERSST...\n",
       "    institution:               This version written at NOAA/ESRL PSD: obtaine...\n",
       "    citation:                  Huang et al, 2017: Extended Reconstructed Sea ...\n",
       "    platform:                  Ship and Buoy SSTs from ICOADS R3.0 and NCEP GTS\n",
       "    standard_name_vocabulary:  CF Standard Name Table (v40, 25 January 2017)\n",
       "    processing_level:          NOAA Level 4\n",
       "    Conventions:               CF-1.6, ACDD-1.3\n",
       "    metadata_link:             :metadata_link = https://doi.org/10.7289/V5T72...\n",
       "    creator_name:              Boyin Huang (original)\n",
       "    date_created:              2017-06-30T12:18:00Z (original)\n",
       "    product_version:           Version 5\n",
       "    creator_url_original:      https://www.ncei.noaa.gov\n",
       "    license:                   No constraints on data access or use\n",
       "    comment:                   SSTs were observed by conventional thermometer...\n",
       "    summary:                   ERSST.v5 is developed based on v4 after revisi...\n",
       "    dataset_title:             NOAA Extended Reconstructed SST V5\n",
       "    data_modified:             2021-08-02"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import xarray as xr\n",
    "\n",
    "dset = xr.open_dataset(\"sst.mnmean.nc\")\n",
    "dset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
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       "  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, 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;sst&#x27; (time: 2010, lat: 89, lon: 180)&gt;\n",
       "[32200200 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * lat      (lat) float32 88.0 86.0 84.0 82.0 80.0 ... -82.0 -84.0 -86.0 -88.0\n",
       "  * lon      (lon) float32 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * time     (time) datetime64[ns] 1854-01-01 1854-02-01 ... 2021-06-01\n",
       "Attributes:\n",
       "    long_name:     Monthly Means of Sea Surface Temperature\n",
       "    units:         degC\n",
       "    var_desc:      Sea Surface Temperature\n",
       "    level_desc:    Surface\n",
       "    statistic:     Mean\n",
       "    dataset:       NOAA Extended Reconstructed SST V5\n",
       "    parent_stat:   Individual Values\n",
       "    actual_range:  [-1.8     42.32636]\n",
       "    valid_range:   [-1.8 45. ]</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 2010</li><li><span class='xr-has-index'>lat</span>: 89</li><li><span class='xr-has-index'>lon</span>: 180</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-fc1476bb-7c76-49ec-81ef-36f74271812f' class='xr-array-in' type='checkbox' checked><label for='section-fc1476bb-7c76-49ec-81ef-36f74271812f' 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>[32200200 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-7407f637-5b11-41cb-af18-9d3068d831e2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7407f637-5b11-41cb-af18-9d3068d831e2' 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'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>88.0 86.0 84.0 ... -86.0 -88.0</div><input id='attrs-f760a359-ed0d-47fa-8ce4-a7d6d8bef390' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f760a359-ed0d-47fa-8ce4-a7d6d8bef390' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-60aa482d-5b7e-4618-8a4e-574cc67f1d66' class='xr-var-data-in' type='checkbox'><label for='data-60aa482d-5b7e-4618-8a4e-574cc67f1d66' 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>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>actual_range :</span></dt><dd>[ 88. -88.]</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>coordinate_defines :</span></dt><dd>center</dd></dl></div><div class='xr-var-data'><pre>array([ 88.,  86.,  84.,  82.,  80.,  78.,  76.,  74.,  72.,  70.,  68.,  66.,\n",
       "        64.,  62.,  60.,  58.,  56.,  54.,  52.,  50.,  48.,  46.,  44.,  42.,\n",
       "        40.,  38.,  36.,  34.,  32.,  30.,  28.,  26.,  24.,  22.,  20.,  18.,\n",
       "        16.,  14.,  12.,  10.,   8.,   6.,   4.,   2.,   0.,  -2.,  -4.,  -6.,\n",
       "        -8., -10., -12., -14., -16., -18., -20., -22., -24., -26., -28., -30.,\n",
       "       -32., -34., -36., -38., -40., -42., -44., -46., -48., -50., -52., -54.,\n",
       "       -56., -58., -60., -62., -64., -66., -68., -70., -72., -74., -76., -78.,\n",
       "       -80., -82., -84., -86., -88.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-073d88e7-b0ca-4807-8277-3012bafa4f32' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-073d88e7-b0ca-4807-8277-3012bafa4f32' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-35570bb4-b341-4aea-af21-60590a3f9f43' class='xr-var-data-in' type='checkbox'><label for='data-35570bb4-b341-4aea-af21-60590a3f9f43' 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>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>actual_range :</span></dt><dd>[  0. 358.]</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>coordinate_defines :</span></dt><dd>center</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.],\n",
       "      dtype=float32)</pre></div></li><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'>1854-01-01 ... 2021-06-01</div><input id='attrs-7f5366d0-ca7e-4a17-b12c-97784f5d5f7c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7f5366d0-ca7e-4a17-b12c-97784f5d5f7c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bed9d2ff-433f-4782-9f10-a41bb16ec880' class='xr-var-data-in' type='checkbox'><label for='data-bed9d2ff-433f-4782-9f10-a41bb16ec880' 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>Time</dd><dt><span>delta_t :</span></dt><dd>0000-01-00 00:00:00</dd><dt><span>avg_period :</span></dt><dd>0000-01-00 00:00:00</dd><dt><span>prev_avg_period :</span></dt><dd>0000-00-07 00:00:00</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>actual_range :</span></dt><dd>[19723. 80870.]</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1854-01-01T00:00:00.000000000&#x27;, &#x27;1854-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1854-03-01T00:00:00.000000000&#x27;, ..., &#x27;2021-04-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-05-01T00:00:00.000000000&#x27;, &#x27;2021-06-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-00ee304f-0a94-4a8b-b7f5-bd42c17fb660' class='xr-section-summary-in' type='checkbox'  checked><label for='section-00ee304f-0a94-4a8b-b7f5-bd42c17fb660' class='xr-section-summary' >Attributes: <span>(9)</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>Monthly Means of Sea Surface Temperature</dd><dt><span>units :</span></dt><dd>degC</dd><dt><span>var_desc :</span></dt><dd>Sea Surface Temperature</dd><dt><span>level_desc :</span></dt><dd>Surface</dd><dt><span>statistic :</span></dt><dd>Mean</dd><dt><span>dataset :</span></dt><dd>NOAA Extended Reconstructed SST V5</dd><dt><span>parent_stat :</span></dt><dd>Individual Values</dd><dt><span>actual_range :</span></dt><dd>[-1.8     42.32636]</dd><dt><span>valid_range :</span></dt><dd>[-1.8 45. ]</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'sst' (time: 2010, lat: 89, lon: 180)>\n",
       "[32200200 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * lat      (lat) float32 88.0 86.0 84.0 82.0 80.0 ... -82.0 -84.0 -86.0 -88.0\n",
       "  * lon      (lon) float32 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * time     (time) datetime64[ns] 1854-01-01 1854-02-01 ... 2021-06-01\n",
       "Attributes:\n",
       "    long_name:     Monthly Means of Sea Surface Temperature\n",
       "    units:         degC\n",
       "    var_desc:      Sea Surface Temperature\n",
       "    level_desc:    Surface\n",
       "    statistic:     Mean\n",
       "    dataset:       NOAA Extended Reconstructed SST V5\n",
       "    parent_stat:   Individual Values\n",
       "    actual_range:  [-1.8     42.32636]\n",
       "    valid_range:   [-1.8 45. ]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sst=dset.sst\n",
    "sst"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x1b4b1209988>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# seleccionamos solo tropicos\n",
    "sst_trop=sst.sel(lat=slice(30,-30))\n",
    "sst_trop.sel(time=\"2010-01-01\").plot(robust=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Christian\\anaconda3\\lib\\site-packages\\xarray\\core\\nanops.py:142: RuntimeWarning: Mean of empty slice\n",
      "  return np.nanmean(a, axis=axis, dtype=dtype)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x1b4b12d3708>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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LvYRTeTkrA/q5tLYVkTZsRV443+LgtK2v6TggcuV0hilv/tSdPPdRp69RVkpXQVVR8rW3G4VsODzvEtLceTjLrOMs7t7MSlly6WA7g8ZuzfcgKJxzEVO42WaNqSKPBvEqp9q8XrqJ0u0mLp3RT+z+fpIVcuUoECIXT2CsWy/gFjay5Q1S5aSr96rcdrsIGM/kPlV93ojjv4eV5O4KfKMxYR7z9netu3/wobducyQez95nvQZ0UpgaK/OJNyz0eDweD9gJuzJiUEP2oNTINxoej8ezBYLYEATBpnlMf++1Gr7R8Hg8ni0gZvSTxl70RveNhsfj8WwBCQTju6c8Ho/HUwcxpjC53DDPHmw1fKOxRdLB2a0WnzunAqBWZqgmRFInFR30SD/3PoKrn1i7zHtf/TMArNz9AJ3jC8X+R7zxb0e+965X/iTJSg+A/qklhit9ALI0I3By17X/JKlzjz3NNTaXuAZlXs0yJHQy2yxD+z2XTkn7/SJf0LR5TBxinNRTGk0kLB1yzcy8y9MEt1+qEt5KDHnc9r0NNIgKaSlZBk6aqmFUSEWT1jxdseUt9DMWTtj47u8MONktJZ7Hl+z+qmy2O0wLaWlgpJDctqKAhkunmRbS2u4wpTtIiv0zTXs95802OTRlY7hgvsnRGVsXM42QoavvqEbXhwKpQq4CFrLyfgtiAif91iwr68ms6ad3clo1IRo1in25zFaDCI2tE24Wtxnk7ryJFtJfVS32dxNlZWj/f050h3SGNp5MtVAjRUYKmW31WhuhKWSuqWqx/8LpBncvl/fRdhBEhiDavFEwe3AVJt9onCEPu/6vgHLugsfj2R1sp9wWVs8l2jCPH9PweDweD4CpNabhGw2Px+PxYAe5RzUKsgeXe/WNhsfj8WwBYwzGd095PB6Ppw4SG0w8otHwA+Eej8fjATCBf9LwnAFhKyKeaXPbz/8wAJe/5s9rvze581ZoW9moaFY6imbpqtlA2u+RfOKd9nyPecqmZXbf/hriGSsZ7T6wWOzvLw742Pd+J4/96/+76fuzYVJIaLM0I6vIaNVJJTWoOJ9W/mEkMEgus42iIo8B1LnNZsOkdJQNyzwAQaNR/q2Uk7urStwsHGjN9DymlTutRmjgpLZBUEhAq3JQRIo61SC0x0InG1Ut5adhg77afEv9tHBNvXeldLM92R1ysmOv58TygFO5/LZTutPm7rV5uuXkyjPNkFZsYwrWfJFU98+3bN0cPdgqZLaXzrWYbtjYkhSWnES3EY6eA5ApDDMlcZrbZQLmcldlEXB1IVDIaYu6AyRLyvtz7ZyEvL8+KOt0kJbnGqTK0KWTrJTcLvVTTri666dZISEeZqsltzmBkVWv21FQ/J11TsCREb50fIkrz5sZWSfjos6M8L3YaOzozBMRuURE3isit4rILSLys27/QRH5vyLyJff3wE7G6fF4PGsxRkZue3EgfKenKybAf1DVhwPXAT8lIlcDLwXeo6pXAu9xrz0ej2fXEMTByM3UeBo819jRK1LVu1X14y69BNwKHAWeAdzgst0APHNnIvR4PJ71EVPao2+47b02Y/eMaYjIZcBjgH8GzlfVu8E2LCJy3gbveTHwYoBLL710ewL1eDwe6s4I33utxq64IhGZBt4G/JyqLo7Kn6Oq16vqtap67ZEjRyYXoMfj8awhd7ndbPNPGhNARCJsg/FGVf0rt/teEbnQPWVcCBzfuQg9Ho/ndIIwIIhGLMI04knkXGRHGw2x0oLXAreq6m9VDt0IvBB4lfv7jh0IbySzD74QgMb8DEt/+ivM/Ktf2TT/8PhXbSJqFftUtXC2lXSAWjWllZuudRtdh/4//KlNmIAstZLWbDAkdc6hYaveR1x1qjWBKZxtNdVCVhhEIWlvQNCMaR6aJWw6qWwzrpSTIkHVYTZ3vK3IdaO4lNZWH99NsMrNVhpWchrMzCPtOVt+EJE5t1wNynI0jNGwWZRTSm4NQ+fwmmZq3V61POXAubB2OhkDV39L/bRwTD3ZHRYS14XOkAUnvz3VHbLcs+kk08LZNs2UQcUBOV1nILQVBbRd/QYVN9dWHHCgba/t0rkmDz5g75ODzaDIM8yUhpsw1k0CVOHTdy0QuuNXXzB72vmqzCTlg7wGoZUhu3oq3GzFlPWapVYWbl+sX6j103B5KOpiWJHZDlJlxdXLQj+hn8ts06yQK+fyXIDEqY8AIhXSzKUrX8KhEWJ3b+6EsrXOcq91AhOR1wFPB46r6iPWOS7AbwNPAzrAj+ZjwTvBTjeD3wy8AHiSiHzSbU/DNhbfKSJfAr7Tvd5VXPUnb9/pEHaMM5mT4tkZHnbeLA87b5aHHJnh0oPTHJppc2imvdNh7SnyMY1Nt3qt2RuAzSZiPRW40m0vBv7wrIM/C3b0SUNV/x92XtF6fMd2xuLxeDxnQr1FmGqseaL6AScE2ohnAH+qqgp8WETm8+77Mwh3bOz4mIbH4/GciwRRQBBv/hVqwgDgOhG5ubL7elW9/gxOdRS4o/L6mNvnGw2Px+M5V6gjuXVjGh9W1eeczanW2afr7NsWfKPh8Xg8W2FM3VM1OAZcUnl9MXDXOAreCjs9EO7xeDznJBIEo7fxTO67EfhXYrkOWNip8QwY8aQhIr9To4xFVX3ZmOI5p2gftZLbwnV1HQYL99tEloCTiq6a8aNZ6RZalS6KQSpuo9ltN2Muv3ZV2cN/fruVr0LpIAuYOKIxa+WwYTNm5tLzuffVP8PUUTsBcvr5L1831tipa4IoJOhZyWlVPhvPtGkcmOb+3/kPxDNTGNefa8JolTxYnXS16opq4qB4LWGEtK00VKIIcfUiYVS42UpzupTNBgFZLgcNm4UbK0FM5uTLCQan7rQSWKezTTUrJKAZVg7aKY4pQ/emzjDlpJPQdoYpy87ldrGfsNyz6UFSykOhdKeFpHC3DYwwNx0X+auOtrGT3840Qw66PK0oKJxdm6HhkJPcHp1tMuNkuWFFlhsIxRoOgcDAXVsgVn769RPLGEr5al4nDzmyvvurRk5RtcEvYm1MobnUNstK+S1OmgtsNINNlcLxtjvMCulyL8lWyXLzWIdptkp2m9dLVdW6PEjpDO39dbgdMdewEu1wtDp97Nh5Gpt31lT/fzbMI/Im4InAYRE5BrwCiABU9Y+Am7By2y9jJbc/djZxny2juqeeAaz/DVPyUmBfNhp7iUte+Vru/K8/vtNheCZMfOAC4ILi9fDe23cumHOcejYitdRTzxtxXIGfOqPgJsioRuM1qnrDZhm8bbnH49mPjKvRONfYtNFQ1f85qoA6eTwej2evITJ6IHwvmk/VUk+JyBHg3wKXVd+jqv96MmF5PB7P7sY/aWzOO4APAu8G0hF5PR6PZ89j4tqT+/YUdRuNtqr+4kQj8Xg8nnOIcdmInGvUbTT+RkSepqo3TTSac5joG76F9I7PWEloaCWhGrcrstFolSw2RzQrpItqwlJmawZolqzKu/b2lGa7kp6iccDKKjXLaB2yktaw3aR15KB9/4F117IqaByYtu9Ps8L1tvr4XU1rlpX/MKYipw2CUn5rgtNcbME6+OYyZTM1gzRtWqMWmjvYmhANIre/WTjYatggqUhr8ypNVQt5Z9Vd1TrQlnn6SUbPyWM7w7SQeHaGKctOEppVZKBV0kxpONlsIzTF+aYbIa3Yvne5Nyxkua04KPJPNyNmGvaznWtHTLlfqM3QELkujEZoaEdlfeVOsIExRJU4pCLRDSruulFFlhtWdKrTkaG/smTrz91rzXZe542y4Ox0F9uqkzBY11tgtfTWrP4ayY9k6lyFgWFWcbNNMzLnLpxlSurSvTSj65xwBxVZ7iDJVkmajzg5eS9pEc3b65mS7f9FL6b2jPA9xah5GkvY6eoC/LKI9IGhe62qurkP8x6n/ayXFOn0js/sYCQej2e78WMa66Cq688I8ng8nn1OEIUEUbRpHhPsPaemWnowEXlPnX0ej8ezX8i7pzbb9mP3VBOYwk5vP0DptjgLXDTh2Dwej2fX4run1ufHgZ/DNhAfo2w0FoHfn2BcHo/Hs6uppZ7ab42Gqv62iPwe8Muq+mvbFJPH4/HsekwUFKadG1HHsPBcY+Qojaqmbt1u32hsggZOKipmlYQ2dVJRABM4/WFFrmjTpexRU+u0KukA0tWS28H9xwCID19s88weRhorNh1GmJl5AKILe6W8tdHExM0iTRiTfv6Dhfw3uPqJRfmN+VL3kD92izFkQxtH2huQOPfbbJCgzazIU/xzmFJyK8Yg7tyYoHTkDaNiv8RN1DnVZo1pNLZpgriQLmdBVEho+4OMrtPcDtJSWpuhOOVmIecEGKalpLOfZKucbftpxtDJWvtJRpatL/3M5Z5ppoVTLYC7GtJMCxfaVhQU5wtEaDun2ulmSMulW3FQxNgZpoVUNlVohKUcuBFKcZ35JQVSSm4DAcmltcHqX7R5maERQrLinstMRDfJWFnq2Lhi59CcpUjSc+ny/pRBh3T6sE1nKZLf25Vz2Xvenk/1dNluXhe5/DhVCqfaKmmmRV13BylLzl14oTuk6+TQgRE67rOZbYSkau+jVrgDv+j36ZNGXWOUd4nIs2QvzlTZj6wzX8Tj8ZwZYoKR2771ngJ+ATsgnopIFz9Pw+Px7HcqT9Ubsl8bDT9fw+PxeFYjYYiMmKexL8c0ckTk+4Bvcy/fp6p/M5mQPB6P5xygzpPGeJZ73VXUtUZ/FfCNwBvdrp8VkW9R1ZdOLDKPx+PZzfjuqU15GvBoddIIEbkB+AR2qVePx+PZd3iX29HMAydcem4CsexJFp080GDljwBRYIpZkiqmcPPMFIz75RJHbYwTNkqWrJLpDk7cZfe3DyANK5mUqXmCtKKKcn2pqxxIh30r5QW03yFbOkX2z28nevwz6d74O4TzB4usEjqH2SxD+l23d3ld99tVVJVZxqBOvimAuvhM3Cz7goOocLYliNDIOvdq2KDvLrnbT0vJbVLKbIdZVshn04rMtjNMC3fVtOJYO0wzJ7Mt81alr8t9K+vsDtJC+tkZpKXbapqRdp2c1ghB5Quh6ySkacUdNzBSlPnAyqCQ5caBKdKN0BRS3IPTMZGTzs41wsKdV5XiekTAuJhFhOrv3LwOMkAqmtgEQypxcW19J1kOjdBo2P1R1i1/Feef7RrJ90ZkEhTXLSLkRr1pYFDneatajTQpFMK9pKzDfuWeqsqY49CQZsaFZphp2nu6HQXMuHkS03HAbJAWbr6NqW0YhjXGd09twn8DPiEi78X+/38b8EvjCEBEXgc8HTiuqo9w+w4Cb8GuFPhV4NmqenIc55sU4UUPW//Awsr2BlID7Xd2OgTPOUA+H2gUnW5vwpHsTiSIih9XG2LqfcWKyFOA3wYC4E9U9VVrjv8o8N+BO92u31PVPzmziMdDrWZQVd8EXAf8ldueoKpvHlMMbwCesmbfS4H3qOqVwHvw3WAej2e3kY9pbLbV6J4SkQBry/RU4GrgeSJy9TpZ36Kqj3bbjjQYUH9yX573fuAk8FAR+bYR+Wuhqh+g7PbKeQZwg0vfADxzHOfyeDyesZF3T2261fqKfRzwZVW9TVUHwJux34G7krrqqd8EngPcQrkwlwIfmFBc56vq3QCqereIrLvknIi8GHgxwKWXXjqhUDwej+d0JAhGzsMYNVDuOArcUXl9DHj8Ovme5X6sfxH4eVW9Y508E6fumMYzgYepan+SwZwpqno9cD3Atddee/r6nB6PxzMpggjqjWlcJyI3V/Ze7767ctbrw1r7ffbXwJtUtS8iP4HtgXnSGcc8Buo2GrcBEbBdjca9InKhe8q4EDi+Tef1eDyeWljJ7ah5GgLwYVV9zia5jgGXVF5fDNxVzaCqD1Re/i/gN88k1nFSt9HoAJ90q/UVDYeq/vuJRAU3Ai8EXuX+vmNC55kon793sRgHi4yUkttUiv2qFJLQimqUOFDiIHczDQidCiMwgsmdRqN2IcVdK8vNVRsqxh4DpLeE6S1BO4bekpXEDnoMPvRWzOyh4lFb07RM97tFf2QYBISzc0UegKzXgSxDk6HLFJVy4ixAEifxDeNiv4QR5DJbMWWscRsN7C+3fkYhrU2zUso6zJSek5XHGIAAACAASURBVMMuD5LCLbWXZIXstZeWjrXDTBmkZb1UJbELnSGnOjbu5X7Ccs+mV8lsk4w0yWWjiubS0op7qWZK6mSsaeVcmmmRzxghdFrUqBEy17bX2Y4DDk5ZN984NBxs2XrpDFOag7Jro+lcXEMtpb5GdK25rYsTUkqJcqplXfbSjMSpoqsLy8032wTdwemF1SQPwwg0glxaLAxS5/4bKtOxcecKi3hOdIcsOFlyRQnNdDMsnIbnk/LXfCsOOG/a1tclcy3akS2/GQq4e1KSHoPBCvGBC7Z8PbUwZvSYRb3uqY8CV4rIg7HqqOcCP1zNkP+Idi+/D7j1TMMdF3UbjRvdNnZE5E3AE7GrAx4DXoFtLN4qIi8Cvg780CTOvW/pLY2tqOnnv5zOX7x6bOV5dgdn8oXbbjVZ7nRHZ9xjFE62m+WpMSNcVRMR+Wng77GS29ep6i0i8qvAzap6I/DvnZVTghUO/ehZhr9l6hoW3rDZcRF5m6o+aysBqOrzNjj0HVspz+PxeLaFsMaYRk3DQlW9Cbhpzb6XV9K/xJjmxp0tZzIjfDMuH1M5Ho/Hc06wavGxjfLsY++pUXjlksfj2V94l1uPx+Px1Ma73J4Ve8/K0ePxeDZBwnC099R+XoQpR0QOAJeo6qcru39xfCFtDe0sknzinfbFmr7G4BE7M6Z+38qwMAyNjKER2hfhmsXmc6lthpL738aBFJLb0AiBUVeOEIi9NqmYoVV90SqqUoxA5ESzRjNUM2hMIQv3IHETiZu2rCguHGq13yPrOIWVCTDtGbLOEsGhC4vHbR0O0c4ivZv+ELIUde+VLFj1j1J1uc2dbaXRRCIrm9SoQRa1bDqIyNy1JWlG30lde6nSdemlfsKJrnOO7Qx4oGNloieWByz1nEvtMF0ln81JM6XTS0icNLffTeh3bb5BNynksmmSoe5D0UwL+a5usLa6Vq6/SlVdE8YRjaa9/tZMTH/aSmvbU3Eh751phpxwstdMtZCiWjfXoEjn91EgQuiqOljjcZTfYqmTLucy5X6aFu65zdAU74sDod2aX/f6tkqc9mk4V2XEoA17/VnYKD7b6dhwspdfm2F5YG/kXpIVDsRGpJAWt6OAw21bd/PNkKmorIsqMugyvPd2ovMfPNZrWn0SU+NJYu/9nq717CQi7xORWec++yng9SLyW/lxVX3XpAL0TIbgqm89o/ytp//UhCLx7AWm2y2m2y1m3N/pdmunQ9oGTNlwbLjt00YDmFPVReAHgNer6mOBJ08uLI/H49ndqJiR214c06h7RaGz83g24NcG93g8npFPGYa92D1Vd0zjV7GzFT+kqh8VkcuBL00uLI/H49nlBGb0QPd+ldyq6l8Af1F5fRuwpRngHo/HsxcouqA2zbP3njTqDoQ/VETeIyKfda8fKSIvm2xoHo/Hs4vx3VOb8r+A/wj8MYCqflpE/hx45aQCO1MkCDAbLCafffFDRdo89JsnHsv/+aw1o8wqtrVGhKaTSjYqUkez5pdI5LSFU3FAqrnLrRTS3bVy3WqrX6yOVZHchkYKh1TCWWaDcj1nmT1cZqy44RLGq8rVLGX40RsJDhwpz7WyRDpwZYURkuQBrf4dkkt6zdQMpj1r97Vm0NBKbrN4unC81SAupLUL/ZSVoU2f6ibc76S19yz3+foDdo3zL967xHGX7i4PCjfaYT+l5/JrpiQDa8ycdJcZ9pZJusv2dW+FpN916WUmgXHXFk/NEc8cAKA1fwFN5xY8Nddg0bm23n2iy7Rzv51phsROTxuHhtjdAO04YLpp/22nmyFTsU23o4B2lN9fAZG7T4aZ0hmmhcQ1EArJ7uF2zLwrK1NIsvEbOwRL99pEWkqSNYwI4ykAmtNHaLi5DtNxQMd95p1hukpyG7n7qhWZQmbbCoWWS5uqKYVmheNzesdnkGF/5BPBlqgz0L2PB8LbqvqRNfuSdXN6PB4P0JgZ77yPM8UMOxMtX004etuDjUbdJ437ReQKnMeUiPwgcPfmb/F4PJ69jOzLJ426jcZPYZdVvUpE7gRuB35kYlF5PB7Pbkdk9OS9vTekUVs9dRvwZBGZAoyqjm8VH4/H4zkX8TYiGyMi54vIa4G/VNUlEbnararn8Xg8+xINwpHbSBfcc5C6HW5vwE7uu8i9/iLwc5MIyOPxeM4J6khu9+A8jbpjGodV9a0i8ktQrGm7vuXnDqEmIGtbtYakSeHYKhX53XZw4+fuoZ9WZINOxhgFhmFmf3X0kowoyN05V7+/6mCqLi2imDTPWEoLq/ejKqR6umSyEQqp2nKmI8NS6zxmusdJ7vqCtXV2LrRkKSoG0QyJGsj8EbJT960qS9pzRTqXkoJdwUwHpZQ3l9BKGCENJ7ltTiEtK7NUE6Jx26ajBupcbnupsjyw8Zzspty9bKWyx1f6HDtppbGfv3uRO+618tj7ji2yfP/9AHRP3kM6sHnSQY/+0onT6mInyBIr/e0t3Edvwdbn0l1foTln5cthc4qoNQ1A1J4jdOkgNATuHskyxTgJrRghath/2zAyxC7dnIqYmnLur+2I6WZp2T1Iyvu/FQdcfMDW96MumqPh5NjTsT3XJGS3ANl9Xy/uNQkjzJSTXw9WODht62J2epZl50rcTQKGWVWybv8Gssb9Of8n0PLrSJIBohkaNiEdQNRAA3e/jnNgWmoMhNf+XX7uULfRWBGRQ5TqqeuAhYlF5ZkokvQ3PGYuv5bsK1ZdHT72e1Ydy267eaJxeXaemTG70waXfAMA2T23j7XcWuS27JOi1jyN/fuk8QvAjcAVIvIh4AjwgxOLyuPxeHY5+VyMTfPsQcntyCsSuzJ6E/h24JuAHweuWbMIk8fj8ewvcsntqK1WUfIUEfmCiHxZRF66zvGGiLzFHf9nEblszFdTm5GNhqpmwP+nqomq3qKqn1XV4TbE5vF4PLuY8QyEi0gA/D7wVOBq4HkicvWabC8CTqrqQ4DXAL855oupTd1np3eJyLNE9mAHncfj8WwBFRm9CFO9r9jHAV9W1dtUdQC8GXjGmjzPAG5w6b8EvmOnvo/PZExjCkhEpIedsaKqOjuxyDwej2cXoyZAR8zDUGu0eJ2IVFUk16vq9ZXXR4E7Kq+PAY9fU1SRx6lXF4BDwP1biV1EHqyqt4/atx51Z4Svbx+7mxBjJXYAMigcWzXbHrntR79+EoDISOFcG4is+qFRut7KqnT1eDrM403oJU5+ayDN1pZh3T+DSvnDVNfZHxIZuz/JlOk4YHDgQcQnv+Yktk6anCWgGdmXP+zCKgtO7rzVJhpThXxZxGBmKs6lTnKr6WoltuTy20bTSnyBLGqsGiDM08OUQmbZGaZ0hraspX7C8UUnv13s03HplRMn6Z68x+Z/4K5Ccrvb0Swt4g7iViG5DVcWMJGtLxPGGPeFJJUvJjFB8dqEcSHRbbQimlO2fu9rhIRR+Z4syVbdN186ZOXOc+2IR55vZdBBb9EebDbHe7F5DAsPlP+LWYqcPG7Pe+hCgsT2dstUj7mWlXW3ori4n5NMcUkyLXt8lPJ+iUxA4KyWNZeDB5GVkpug3DfGgWnV1Y7SG+UBPqyqz9kk23pPDGtLrpPnTHgb8C/W7PtL4LGj3lir0RCRtYWDldx+TVUn4nYrIk8BfhsIgD9R1VdN4jz7lfCih5Ecu2XD4+aKx21jNB7PBMgmO5VMVVc1xhvlqcEx4JLK64uBuzbIc0xEQmAOOOPJSCJyFXANMCciP1A5NIsVPI2kbvfUH2Bbpc+4198AfAo4JCI/oarvqllOLSoDQ9+JrayPisiNqvq5cZ7H4/F4tooy+qd+zUeBjwJXisiDgTuB5wI/vCbPjcALgX/CTnf4B63ZIq3hYcDTgXngeyv7l4B/W6eAuo3GV4EXqeotAG5k/z8Cvwb8FTDWRoPKwJA7Xz4w5BsNj8ezK8jUbptR51vdjVH8NNaqKQBep6q3iMivAjer6o3Aa4H/LSJfxj5hPHcrMavqO4B3iMgTVPWftlJG3UbjqrzBcCf+nIg8RlVvm9AAfp2BIUTkxcCLAS69+Ogk4vB4PJ51SVVJR7QaWU1bFlW9Cbhpzb6XV9I94IfOPMoN+X4RuQXoAu8EHgX8nKr+2ag31h0V+oKI/KGIfLvb/gD4oog0gEnM2ag16KOq16vqtap67eFDBycQhsfj8ayP1tx2Kd+lqovYrqpjwEOxvUcjqfuk8aPAv8M62wrw/4CXYBuMf3mGwdahzsCQx+Px7Bjj6p7aIXJHy6cBb1LVE3V7jepKbrvu6eJvVPULaw4v1w6zPnUGhlYjUnrXZ6aQcW6H9cuxE8tMxfbcwywsHGyXjKxy6oycVWcUmMLdNtVSRturSCOHqSEw5Yc4dJrbVEtnXCNC0znhGhGiIC+/lP1CKddNFQbuRTs/6PKpCTesLI2nXKIiXzZh8ThoshTN5bSDHjgJpaYpWXcF05qyn03u0+PcdAFIBpjBCgCteIZ+Yks92IoYOolmkmYMDrfdNShfdHWaDM8rJKqNmYOFi2x/+WR57f1u4TS7HYgJCgfgeGqO1oHzbXxzR4hbp5sBGiPELVt3QSiFs60YKWSzQWjI/6HFUDjemsAQuM+/FQe03T0Yh6boNuknGQudIcunrCR6ZbFPMrBrqH36jgUef9Q6Q59/aLxGhZuhvZVCAivLpwinrKJfwqjo+ogb00TO/XioQtdJ0dNM6Tu95kC0+J8KBOLA1WPzAJG7OXPpfXny8UnwVXW0Omr3tho3isjnsd1T/05EjgC9Ee8B6i/C9H3AJ7F9X4jIo0Xkxi0GOxIn480Hhm4F3lodU/GMh/Dia7blPNHjn7kt5/HsXhpP/jGa3/Uimt+1fWu3ndZgjJlM7Q+xzbYJOc2Pg48D3wVcC/wi8EbsJO6R1O2eegVW0fQ+AFX95KQNs9YbGPJ4PJ7dQp3uqe1byeeM+S+q+kgR+Rbgu4H/AfwW6wiO1lK38yZRVb9+hsfj8TjsjHDddBs5ZXznyGc+fg/wh06KG2+Sv6Buo/FZEflhIBCRK0Xkd4F/PPM4PR6PZ2+Q1dx2KXeKyB8DzwZuckrYWu1B3UbjZ7BTz/vAm4BF/BrhHo9nH5NmOnLb2qTtbeHZ2DHjp6jqKeAg45TcqmoH+M9u83g8nn3PGG1Eth33nf5Xldd3A3fXee+mjYaI/DWbXLeqfl/NGCeOmhCNrSxT0iHiZJ9oVkhxNQhJjt0yNtXQwop1VY0DoRU6jV8zoh3Zh9JGYFgeWAXHcIMRs0yVXmLzd4cpaSG51VV5csltlUYYFOXOxAGRu852FBRy3WCNE24eRqdr1XUNt1+jRiG51ahFumAdl1UMErfLAnLJopgibSoqFWMCso5zTE03MYxz6zdLlhTGcrFmHGpbCWgYpMSB9U+ba0ScN20jvWS+xZXnW2fXz1+wxJfusulB7wIG/StsupuQujpN04xkYMsf9gdkyaBw4tUsXeWMKxVX2Vw2a6K4TBtB8noNDFHD/vs0WmGRjhpBIZU9ONvg4gO27g5Nx0w3bZ7AyKrPp+3yN0JTSEgbYVDIqduRKfIERjBO7BxU1vgJRMgV2pnCwN0/p3pDji32+cQdpwD4yFceKOS3X7t/hXd9ycqU3/UleMl1F274cW0HMuwX96AEIRrazzzNhNz8uZcqibuJM2XVNZtKXbiqw4gg4hyngWa4uZX5maB15mns1lbjLBj1pPE/3N8fAC4A8inmz8P6UXnOQfIvI4DgQY8C2NTxdhwEVz+xSJttOJ/nzGlMbc8KCK1n/vy6+9PbPz7W85gJr1FUyxp9ohHsDJs2Gqr6fgAR+TVV/bbKob8WkQ9MNDKPx+PZxaSqRc/ARuzieRpbpu5A+BERuTx/4WZqH5lMSB6Px7P7ySjnamy07cfuqZyfB94nIre515fh3GU9Ho9nP+K7pzZBVd8pIlcCV7ldn1fV/uTC8ng8nt1NhpKNaBZ0DzYbm3ZPVZd5VdW+qn7Kbf318ng8Hs9+IX/SGLXtNUY9abxeRJ7I+utb5LwWeMzYItoiw1RZDqz8crptChmoDLoT++RyiV8cCHn7GxgtnFqr6o3OMF21nnCuqB2mGYmT01ZltcPKXNIs00Jam6oSGXuuanlRUMoyW5EhdsHFgSFyPw0aoaFhABQZdjG9RdL7reOpQOFOiwlRJ4klbFoH3JxcchvGkDo327iF5FLJpHwAzTqLkGUMPvhmG8u3nr7YmAy6iNj3aNKznxdwsDnD1LR1151pGA627LVdPNvgCidjffCBNo+8ZA6Ae0716Dhp7SDJCjffQZIxSOz+fpLRHaT0Xb5kuFoSbJw2OY4DYqcwi0NDmNdlaAhMuX/ayWzn2xEHp60stxkYGk7WebgdMedktnONiIaTZTcDIQxKyW0c5J+VYFz9SdJH+tZA2gyWkZ6tF+130KH7bJIhmjsKJwNwrsASNzFzh+z+uQt49JWX8PAjti4vOzzFx75mXYAfWO7zaSfFBXjOGz7CW350Z9eGL0wGswx1EujBMC0+z26Scapr8/TTrHDzrf4vVP/vhpldx7vhPtuDrYhxkaS6Shq/HqMWaToXGdVozAEfY/NG477xhePZDmTYHZ1pwuRzZcYts/ScuwQP/hekd3xmbOVtNDdqXGSqqxqr9dh3Txqqetk2xeHxeDznFLUkt3twTKOuesrj8Xg8FbTWk4ZvNDwej8eD7f4aNaaRnKXNrYgcBN6CnebwVeDZqnpynXwpkPftfX2SFk/bsBiqx+Px7D3y7qnNtjF0T70UeI+qXgm8x71ej66qPtptE/UErLvcq4jIj4jIy93rS0VkZ2UWHo/Hs4OMmg0+phnhzwBucOkbgB1fO7lu99QfYGfNPwn4VWAJeBvwjROK64zpJSnHO1aKZ6batFtWilltFTVsTuTcUnGSjRQSY++U0Mgqc8B+RVq7nvx2VTpTjClFa7n7qVHBKTQxIqucUKdim54KDS2ns40DIdZcfryEJM5dNukjSQ/prwCgvZXCDVg0KyS0ZJmV18IqZ1s0K11xK7JciRoY504qUYT2y7Xqk4/9LeFjv4f++964qv6CA9aRxrSmIHTS0sEyzdhKqOPWHNPtFmDdW+ebNs7ZZsD5Tup6/1yLhd7pa0IPs4zMqWiGmdIdpnSd5Db/C9Y9NpfZVtNxaAqHVCNl3TfCgEZR96UjbWSk2D8VB7RcuhWawgm5FRnMoOM+hx7SdTLbYQfjPo9s8QTpwgO23k4dZ3jS9kgMV7okHVunSXdA2rOf57DTRd39ZaKQ1nkHAJi7/GLiqx7Lwy6z06mmrjjIhTP28/nM3Yt86V4r6z2+WH5OO0l+P0pjpvjCHaRKZ2hfnOgMub9jr3mhnxTdQ1llUDrNlIHrF1ruJQySjFZs75kjMw3GRebWzNg0jz18nYjcXNl9vapeX/M05zvbclT1bhE5b4N8TXeOBHiVqr69ZvlnTN1G4/Gq+i9E5BMAqnpSRGotDejZfVTnUng8e5XldX5EjJNhZf7URrhG5cOq+pyN8ojIu7Eu4ms5k/WLLlXVu5xH4D+IyGdU9Stn8P7a1G00hiIS4KxUROQIu3olQ4/H45kstgvq7G1EVPXJGx0TkXtF5EL3lHEhcHyDMu5yf28TkfdhJ1xPpNGoOxD+O8D/Ac4TkV8H/h/wG5MIyOPxeM4F6iz3mp39T+sbgRe69AuBd6zNICIH3BrfiMhh4JuBz531mTegrmHhG0XkY8B3YGeHP1NVb51UUB6Px7PbqTVP4+zVU68C3ioiLwK+DvwQgIhcC/yEqv4b4OHAH4tIhn0QeJWq7kyj4TTCOceBN1WPqeqJSQXm8Xg8u5mhjh7TSM5SPqWqD2B/rK/dfzPwb1z6H4FvOKsTnQGjnjQ+hh3HEOBS4KRLz2NbvQdPNDqPx+PZpWSZFsq8jdA9OPI7ynvqwQAi8kfAjap6k3v9VGDDwZudYJAqdy1ZVVA7MrQadr1jHfYLKWnWPsBAQnqdLjNOwjluMi3dHQMDkdNoDjPAKTxTLd0vh5nSdy6svTQrpIKBEQJzuk9kIFJIQAMpHT0bQVC4pTZCQ9tJboPuKUzPOdkOOoVySod9yFKyimNqIbk1ASaX08YJ6txsqa65nKVI5T9CI1ufCoiT3xpAmlNF/qy7QvKpd50mxc06Sy6RIQ17LskSTGrrRZIexpUfteZpx1Y22QykkLTONyMW+1YtM0y1kECnmZXd5vur9T2s/NMbI4VLcP53LWlWdkc0QlOROweF83C1mgJTSqUDU7oiu0ourzl3ZE6T0jl40LMyaCBdWWK4YqXIg6UOw0Ur1x12ugxcerAyJHHur0Fs6J+yUtpskHAAyKWOFx+9mvZRJ8dthIW0+FRnwD33LHPdK98NwIdftv3/3ouvfzmtq600WKYOFRLaQaYsDey13d8ZcH/H1tFib1gopAZJRt/976ROWg2w3BvST7JCBv3A8vhk95mulsuvm2dsZ9s91B0I/8a8wQBQ1b8Dvv1sTiwiPyQit4hI5vrnqsd+SUS+LCJfEJHvPpvzbMRS5+ydXmfarYk1PpNEh15y69n7LPeGEy0/d7ndbNvP3lP3i8jLgD/D/pj8EeCBszz3Z4EfAP64ulNErgaeC1wDXAS8W0Qeqqrp6UV4PB7PzlDL5XYPNhp1nzSeBxzBym7fDpzn9m0ZVb1VVb+wzqFnAG92KwXeDnwZ8JYlHo9nVzF0izBttqV7sH+qruT2BPCzE44l5yjw4crrY27faYjIi4EXAxy84KLJR+bxeDyOOpLbfbuehoi8F06/elV90oj3bTg9XlVPm6SSv22dfevWvPNvuR7gQQ9/5N77dDwez66lTvfUHuydqj2m8ZJKugk8C2uMtSmbTY/fhGPAJZXXFwN3baEcj8fjmRip1jEs3HutRt3uqY+t2fUhEXn/BOIBO23+z0Xkt7AD4VcCHxn1pkyVzrBcfH7QtAvIx1MHSQMr0VwepAycjHOuub6scitYKaZNq5ZzQNOMok9zmCodJwPsJRmJO7A0SAtJaHew2oG1ekPm8ts4NEw3y48tlxJWb04jYJy01vSWMCtWs5AtPEDqZJyFv0Fo60nCCMnTxqBOTivpAHJJqGbl+7JSl6BRAwL7XsSg8RQycO65TiqLKsZJenXQQ4dOWhsExXmpyFY1GZaPnFqRpSb9osx23KbRtk6401HGrHP57SblOgYGKdJJauW3uTNq9VdiIFLIo+PAFPLlQEpZperq9xTSWpFSWiulzNJQfm6GwvGUJFPCyEo/jQiZcxGWsIHEbbs/nsLMzNv03CHCpVMAtJZOkq5YOe1gcYXBkpPfLnZIek5OnWWYyH2WgWGwsIS509oQRVHMoSOXA/Dww6Ws9cTygJMLVga9eKLLY/7z3/GJX38q28FXf9G6ZMxfcRR1LsyYkIGr+O5QC5nt8ZUBt99n761T3WEhUU/X8esIjJz2pT7qS/5MGCalm+5GJKM0uecgdbunqjPDDfBY1u92qo2IfD/wu9gB9r8VkU+q6ner6i0i8lasd0oC/NQklFMLvZSZ9rhLPUcYgyHOKMKjDwcg/dqnJn4uj2c9xtlAbFS+f9LYmOrM8AS4HXjR2ZxYVf8PVo213rFfB379bMr3eDyeSeIbjc15uKquWqUld1X0eDye/UitRmMPSm7rztP4x3X2/dM4A/F4PJ5ziaGz/dlsS/ZgqzHK5fYC7ByJlog8hlIOOwvs1xEBj8fjqdk9tU3BbCOjuqe+G/hRrOz1tyr7l4BfnlBMHo/Hs+up1z2191qNUS63NwA3iMizVPVt2xTTlshUWXZOmN1hxkLPCq7iIGTFGZfli9PPNer2ytUjMFL8pBCRYvArDoT7VhJ37pSek+f1k6wiv10ts11yrp0L3WFhuNZPskK62Y4DDk7Z4aTBbEbk7FwX+glTsZW0NgJlqmllnCoGHdjhqKyzRLayaPcnQyRuYlrWhVbaM0WasDJclaaIOnnssEvWrUh2q86uRx5UpAuZLaDB6beYOXIpYu5054qQyHmwmgCplJnLeoWK7Ff66NBejw67SHcBgOmwwVRrztZLs5Rrrl3vIElNIaHNVIt6DUQKZ9z8tf1butNWJZyZljNOA4GwYmGbl1/9Qqk63KaZFrJfI+X1m3imKMcMe8isldPKoT5hYq9Zhv1CztxaWSJbtlJc7XfRpHTIrUqiCWMrw2220e4KZsUugzMft7nigP2s7r9knlNd+/7bWhHbSdS28uNwqomZtjLjrDnD8sD+v9y93OeOBWswesudi3ztAXv9nV6y6ks5cPLzODS03P9CWLgM27+jJuOdCWmmJH4gfDUi8iOq+mfAZSLyC2uPq+pvrfO2Xc/FB6d3OoQdJf9ymRTRkUsnWr7nzDHN/debHK6ztMA4GaQZ4ah5GvvtSQNwPz1Z71t279WGx+Px1CTT0U8ue7DNGNk9lduWv1tVP1Q9JiLfPLGoPB6PZ5ezX+dp1O3c/92a+zwej2dfkDcam237biBcRJ4AfBNwZM2YxiwwPvMmj8fjOcfYDsmtiPwQ8CvAw4HHqerNG+R7CvDb2O/lP1HVV53dmTdm1JhGjB3PCIGZyv5F4AcnFZTH4/HsdoZpSpBsbouXnP0qTOuucFpFRALg94HvxLqEf1REblTVz53tyddj1JjG+4H3i8gbVPVrkwhgXAQiGCeT7CUZvYrkMpfaLvTHqxrq9qwMMjKCM0UlDoRuRVGRxwRl/+Ywy+gl+cL3SSG57QxSFpzs8YHlPgvL1vFz2E+LtYbjZkhnUN6oubSwEZrCaVU1LuSjB6YOIU6uaYaDMpbuinWXzZ1tg6B0qtXMOtq6dK62yrorhcSzuL7Zg9QmKB9OcwdXzAYPrFmKFo662WoJqXuPGXZB3IWKIetZ+W0zbNJoWA2HBnFxXVkQrZHBCsZ5YYpmkDppcTooy3VlA7D2+6FSR2WhIerOp2FMDx5kuQAAHSRJREFURin1rDoh56QKaeWLRdz9YiQupLhBQ0rZrwjGaVAkHSB5zFlSfGaSlPvJEiQpP3eMQcNmcWzeuT1fc2S6uD8fdKjNci/hZX93a+Hi+urvvYZJMXPp+QCER44is4cBSBvTLHasa+/dS30+f/cSAF+6d4mFE1Z+2+8Oi7oMAkPUsF9nzanyc55vR7TjgFZsj82PUU5c50njbNcIV9VbobwvNuBxwJdV9TaX983YFVC3v9Go0BGR/45dt7uZ7xy1CNN+5SFHyoeyu5fOdin18VPMtRgD4aO+a/PjF9svm+TYLWM7p8dTh/n2ZOebJDXmaYxzXsgmHAXuqLw+Bjx+Uier22i8EXgL8HTgJ4AXAvdNKiiPx+PZ7WT1xzSuE5HqWMT1btVRYMsrnFapvdrpOKjbaBxS1deKyM9WuqwmtQiTx+Px7HoGiSL1FmH6sKo+Z6M8W1zhtMq2rnZat9HIBwPuFpHvwQZ08WRC8ng8nt3PLlru9aPAlSLyYOBO4LnAD0/qZHXnabxSROaA/4BdL/xPgJ+bVFAej8ez28nqzNM4y0ZDRL5fRI4BT8CucPr3bv9FInITgKomwE8Dfw/cCrxVVSc2iFh3jfC/cckF4F8CiIhvNDwez75FM0VHTcQ4S8XtRiucqupdwNMqr28Cbjq7s9WjbvfUevwC8D/HFcjZUpWkDVMtXE4jI+SH5hrjU1MMTh3HGFd9Ygiqskusc+jn7lmkHVlJYz/NCvltdQCtO0gLCe1yPymcbZc6QwbO8bbfHRY3Z5pknHBnCY2U7p2Z0nf9q0uDlF5inWr77ZBDBy8HIG4fIFh5gACQ7qJ1Q3XyVQmjQjqqyRDtW1ljdekxrUo3x4QG8Sp5bxFDVWabpWjq0slwfcNFY5DQSVSnZtDYSW7DqJCYmiAicHnASVOTvkv3ICnlq4WMVkwhuVWzwb9LEJT1VJG0atjAuPOF1XKCqHD/zSQonHiTTIt0PynTChW5bqnISTPBTqWCMIgLyXUQCOJCNUDo9OC5NDz/X1HVQlLbjoSrj1iLuek4LFxlb79vhbsXurzgz+w47v/+kWvXr4OzID5qHZKDA0dQJ5XuJ1nFUbj8f0mSrPhfUNXiY7KLHTknZCMEgeH+xT4z7YjpZsS0k+NON8/mK281aZqtkkuvR7bfFmEawWQtJD0TQ7qLYykn/tbn1s6bS2/Xkt7+8bHE4tmcaMKOr7uRmQlLbus8aexB66mzajT2YHV4PB5PPTId7S11tpP7diOjvKeWWL9xEPI+GI/H49mHVHpTN86z99qMkTYiM5sd93g8nv1KVmtMY++1GuMbFfJ4PJ59RD31lG80PB6Px0PdgXDfaOxaqtqQYZYVssSmEVpuwflGaGiFwnKny3R7a0Myyd1fsucLovKcWVrKRgGc82srFAKTz59c7bDqFMEMmqW0sDtcX+EiRoqbMxmmdJ377b2qhVz3xMqA+2aszHa6GXJw2koxz5tqcPFsw6VnmJubhzmYCRXTW8D0rXmhpgPMwMostb+I9jo2naVWjjtBcldYoHRtDUETtzNbbS+rWUV+m5bHxLnoZp3FQn4rzTZBy61aHERW9prLevsdshWrJMt6HdS5AGsyXNdVV+Im0rByWtnIndcYJHYS30YLiWzdqwmLcjSMrfsuEAQRoYtVoxZD52zbISvukV6a0U/si+VBQmdo4+8M01X3VC6/NlK6LqeV76ymc0KO3MF2FBC5+zMw5ZraB1shiz371RCHZuSs57Mh+djfEh45auOemSd19RIHhiknV79gusFVF9me8kGaccw5O3e6Q9Kqo7SLP4wC2s3w/2/vzIMlq+o7/vnd3t8y771ZHRYHGEcULTQ4IgbiEilEEiUollgkEtQiblFiUaUEyxAtKiYkpsodJAZiwAURg7gAIogby6gz48g6DFCsMzDLm7f0du/95Y9zuvvOs997Pe+97n7T8/tU3erT556+99enb/fpc873fg9RrAz3ZUgFQs7/BmTTrd7PPDuxzn7Hdw+2Gd1rNLxr7puBCvAwcK6q7vH7LgTegzOj/rCq3rTQ559Pw3GgM5ie+5W8PzLbVkgdeRzRY5sW9JjGH5NfwB/LA4V2u9zGUUw8i/dUL85pdPNKugV4qaoeCzwIXAggIsfgvFNeApwKfMkvMmIYhrFoiP1yrjNtvTg81bVGQ1Vv9p4pAHfSMEA8HfimqpZV9RFgK26REcMwjEWDqs669eL41GLps74b+JFPN1tQ5NBmLxKR80Rkg4hsGNuzq1kRwzCM9hA37tWYduu9NqO9cxqtLC4iIhfhTGOurr2sSfmmVe8XMrkc4IgXH9uDH49hGIuV2hDUTMx289+BSFsbjdkWFxGRc3CrAb5BG4N/HV1QxDAMYy60NhHee61GN9VTpwIfA16rqpOJXTcA14jIZ4FDgHXA3a0csyZ/K4cxFS9R7M9AIeNG4fpTSlB1p6pk+ucXf1hGIu/6GkVN/1IUMgF53xTmUwH9WRfHWDliyLtuDuXTjPa5qZ3dkxWyqcaI4R6veCkVA0Ivs6yUQ6plVz6sRpSLLr13rMyj210nLZdLU/CyxGUDOdYs6wNgzdI+Dh9yctBDl+QYyQ3RNzQCQCYqoxNuPfNUWCbykttppaULiGb8svNxWHd/lShEaq6wgJCQwzahJretH9M78upkRDy+x5VJZ9Gwgvo10uPJsYbkthqiibt7Nenu6/NT+SypnJPQSi5fl9Du48ILSM6p8iSbR7ykVXIF8NLlIJuvy5glk0Vy7vPRdI4gvwSATGGIvoI7zmRVmAhcDOkgQ21NtFIYM1qpTQtCOXQxlKK47l6bCoSil2VXwngfyWk2HTBccHEM5dIM5V06SrjtVhJus+0gGF5Rlx/H6Uy9TgONGMq5WI8Yydfdopf3Zdk+7pyJx0th/X1Wpvx4195nIZsiirX+vOZ2uxDEOvt6GTY8tbB8AcgBt3ir5jtV9X2q+gcR+TZwL27Y6oOqGs1wnDmRrU5wsNpnHerv22iVzCvf0qZIjE4x9Uf1YKD2x6ld2M19HUZVXzDDvkuASzoYjmEYxn7Rko2INRqGYRgGQBQpYoaFhmEYRktoC8NTPTgqaI2GYRjGHIhjRWxOwzAMw2gFjaOGeeZ0ZXqwq9EzjUY6kH3WQa5J4ZJ/BCQOIfYSxWCebz15MWjs3FM9Y5POLTafasTTlwkYjF2ZoVyK5X3u/JPVPKNlJ6HcVQxZ6Z1qVy7JsdO72e6aqLDTywz3jpWZ9PlhJSKsuvzJvY0Q0pkU4uvi2VyaJ3Y5+ey24QLHHj7ExqfhhcsHWDOcZ2nexTGSzxPU3GbTOSTfN7/6mSOa8ecNKvU8IeFsO0UCXJfapjN1ebDGUd2lVssl8PLbONyDlpzcNtw7SmXvBFGpwkxEU6S46byTh2b6CwRZV3caxfUykgqQhGw65csH2TyS8ZLWdLYuxdU4bshys3lSIyvd8YdXkCoMAZAtDLGk36UnQ6XfS8gHc+m6EeFYOSTV5LbY8VJYl9yOlUJ2TVSoeGluUoo6VMiyethJn4f6MnW11Z5itX4dzpf4wV+6x4kxgn7nWhv3DaNZJ3/XIA01yXVYZtBLkbMpYYlXQq0ezDLu308pjOvf8yie3nG2lFCOVRdwjiEOq0g4c91oFM64fzZE5O3AxcCLgeNVdcM05R4FxnAmr6Gqrp/XiWegZxqN/Sae34d5IPPC5QPdDmEf0occXU9Xtz/S9vOFe0fbfo7Fxljp4L3e24VOuT+neZl59zS2AG8FLmuh7OtV9bn5nnA2Dt5GwzAMYx60Mjw135lwVb0PwN/LtihYLIaFhmEYBxS1RmPGzTUaJ9SMVf12XjvCAW4Wkd+06fh1rKdhGIYxB1qb04jAuV28Y7oyrRi7tsCJqvqUiKzEuWzcr6p3tPja/cIaDcMwjLmwQOqp2YxdW0FVn/KPO0TketwaRG1pNGx4yjAMYw7EGhHHM2+dkNyKSL+IDNbSwCm4CfS20DM9jVw64NAlTjKYEiHvZYlBcv5I5tdGhk890DhGkEZr6VS24dTZN1IvnwqEtA8gCMvUlgXpTwvq5ZpVAkqhS49VIg7zZoLbB/PsLjkp7u5ilWdGSwA8sbvIY8852WhxvELk5YRhNaqnq+XGv59KMaTiXXHH95YpVkLuengnr1q7jJRAJnCmjdmUMJR1Esc4WyAYGJ5XXc2Z2oSfBBAkPq+ahDas1NNAvYwEqUaahBtuHNUVLFqaIJoYQ1IBUalCOFki9lJZjeJ9pLI1CW3S/VajuC7RDUuVuvxWUgFBxn+Vooi42lAqBUUniU5lS/XjS+J9/ZG65rGHAcgM9BN4+W161eGkhlx6sG+Yfn+NDeezdcn0eDVib8nVy65ilXHvfjuZyzBeCXneEIwWq1TCmG173bU0MVGpuycHKeGhfvd+Vg8XGPLut+Olav26mg/liTGCJW4EJpXKoGl3ncd9I4SFpYCTw9Zk86m4SlBxUvECUPBVtrQvQ6nPvbaciGvqRHHyex/FSq3kZHXhfsQ1jmfvacxTPSUiZwCfB1YAPxCRjar6RhE5BLhCVU8DVgHX+zpIA9eo6o/ndeIZ6JlGw2idV61d1u0Qusps92b0IqPF5pbyxtzpkHrqeuD6JvlPAaf59DbgZfM60X5gjYZhGMYciKuVfW5CbVpmnjf3LUas0TAMw5gDqrMPT/WiY6E1GoZhGHOgJe8pW+7VMAzDgNpE+MyNgrncGoZhGIC7uW+2OQ3tQY+7nmk0sinhsEEnGazEitTzg33cP2vSWIDy3l3klixt+RxSLaGZfP04WnOFTaUbrrkiZGrn07ixslccIV5CKGEZ8WOdKQnIefnhktwAK72c8JCBDKNlV6YYxuz26pdH9xR5aMjFsO3ZcfZMuvxiKaxLbculKrGXI0ZRTNVLbgMR9kxWuen3z3DcmhGeN5BjeZ+rj4FMQFxwbqOS7SdOyJM7eTOPVJ1DMBpD7V+cxsRFJzPW0iRaTXxRE663km58tqTdZyNB0CgTVgjKJYKBDOFkkdzwINUJdz6dsgKbphqutUnJbf1cCTfbIJMmXcjVy9T+fUalSl1+G5Uq9fJ/dC5fPixW6squOI4pLHsKgP5DnyQ9ssKda2QlmRWHApDqG6GQd26xy/sHKfprZ6KarUtLS1HMnqKLYXepykhflpTXo97/9F72lp38tjRRoejdbCcnKgz7aywVCEMDWUbn6XT7+CQcMuTi1lx/PT/ODzHhYw1jJeu/rP2pgCB0sUlYaSybKkLBS8Pz6cZa9xJVoerLx2Fdli0ag8bOQRdY6p2DFwL192LMXMaGp4we4Lg1I7MX6mFCb11/MFG752eu3Hb+axYoks4hbZ6E1jiC9rvcLjqs0TAMw5gDyXVbZijUmWA6iDUahmEYcyAOq4jYfRqGYRjG7BS1OgmJOdJmqJuj66nxUDMsNAzD2H++Gu2Y2RNQNSbetRXg2x2JqENYo2EYhrH//JjyKFoem7aA7tpKMHQ4qrqrg3G1nZ4ZngqiKityTpZX1BQ1M8tAqDvNouzrdCtCeXyU3MDMMrzo3ttd8Wy+If3LBWjGyyzT+YY7Kw3ZqESJ8c4oRELneBpUJ8G7sAZxWI9JMzmCjJMTZvODLBl0cspyDMsKXjLYl2GZl8keOlKou9/uHK/w7FgjHVbdBF213HC/TWdSpAJh0+N7WLdqkMlqxKZn9rJuWT/FMM1k6F14C8NI0J1LQ8bcEsfiJbPg3Gm15OTK0ejOfcvXyoUZNO3qVFKpuuSWIIXknORWMhkIUmSHvAtuWCHrJadRudyQ1sZxPZ10vgX2ya852waZtHPZxU2OJl9TnXDH10q4z2uTstuaLLc6UaQy5t5nWKxS2unWMp/csYfs4JMAZJf0kV3iJKvZZctILVsNQHpkBYP9ThU3kOsnzroy2jfIxEABKDBZjRkd6WP1oLtuVy7Jcc8j7vds+46JujS7NFllV6S++ua3zOinbnkAgNevXU4h7eplIDtUd6Gthlq/AU6EujxeEpJrqRaRSrGeX/vexZm+ukJKyhNQcj/gWi6ilZLzlE440UqQqkuX54uqanrtKUTbN5F+/klN9sdEz94HpV095w7atZ6GiHxaRDaLyEYRudlb/SKOz4nIVr//uG7F2KusWzXYSC/rn6Fkb1K3TT+IWEhL8AOGhNxVEvfzLBTRtluC6XobvdrLgO4OT12qqseq6suBG4FP+vw3Aev8dh7w5S7FZxiGMS2qqsGqlxFt3zQl3/Uy4u2beq6XAV1sNFR1b+JpP7UViuB04H/UcScwLCKrOx6gYRjGLDTrbfRyLwO6PBEuIpeIyOPA2TR6GocCjyeKPeHzmr3+PBHZICIbntvZk5+PYRiLmKm9jV7vZUCbGw0R+YmIbGmynQ6gqhep6uHA1cCHai9rcqimVpGqermqrlfV9cuXte4hZRiGsVAkexu93suANqunVPXkFoteA/wA+Cdcz+LwxL7DgKcWODTDMIwFoa6keuZ3aHF3TyqmknRTPbUu8fQtwP0+fQPwLq+iOgEYVdWnOx5gD/PQ9um15YbRMwSd+3mr9TZ6vZcBIN1aJERErgOOBmLgMeB9qvqkiAjwBeBUYBI4V1U3tHC8Z4EJ4Ln2RT0nlmMxtcJijAkWZ1wWU2vMFNMaVV2YmzY8ItIHVFW1pzXdXWs02oGIbFDV9d2OI4nF1BqLMSZYnHFZTK2xGGPqBcxGxDAMw2gZazQMwzCMlum1RuPybgfQBIupNRZjTLA447KYWmMxxnTA01NzGoZhGEZ76bWehmEYhtFGrNEwDMMwWqYnGg0ROVVEHvB26h/vciyPisjvveX7Bp+3VERuEZGH/ONIm2P4mojsEJEtibymMXTKin6amC4WkSd9XW0UkdMS+y70MT0gIm9sU0yHi8htInKfiPxBRD7i87tWVzPE1LW6EpG8iNwtIpt8TP/s848Ukbt8PX1LRLI+P+efb/X7j1jomGaJ60oReSRRVy/3+R251nseVT2gNyAFPAwcBWSBTcAxXYznUWD5lLx/Az7u0x8H/rXNMbwGOA7YMlsMwGnAj3CeXycAd3UwpouBC5qUPcZ/jjngSP/5ptoQ02rgOJ8eBB705+5aXc0QU9fqyr/fAZ/OAHf59/9t4Cyf/xXg/T79AeArPn0W8K02XVPTxXUlcGaT8h251nt964WexvHAVlXdpqoV4Js4e/XFxOnAVT59FfBX7TyZqt4BTLUymC6GjljRTxPTdJwOfFNVy6r6CLAV9zkvdExPq+pvfXoMuA/nqNy1upohpuloe1359zvun2b8psCfA9/x+VPrqVZ/3wHe4J0eFpQZ4poOW3ZhAeiFRqNlK/UOocDNIvIbETnP561S75/lH1d2Ia7pYuh2/X3IDxV8LTFs1/GY/BDKn+D+rS6KupoSE3SxrkQkJSIbgR3ALbgezR5VDZuctx6T3z8KtMXEb2pcqlqrq0t8Xf2niOSmxtUkZqNFeqHRaNlKvUOcqKrH4VYg/KCIvKaLsbRCN+vvy8Ba4OXA08B/dCMmERkArgPO130XB/ujok3y2hJXk5i6WleqGqlbZfMwXE/mxTOct2P1NDUuEXkpcCHwIuCVwFLgY52Oq5fphUZjUVmpq+pT/nEHcD3uC7a91g32jzu6ENp0MXSt/lR1u//Sx8BXaQyrdCwmEcngfpyvVtXv+uyu1lWzmBZDXfk49gC34+YEhkWktrxC8rz1mPz+IVofmpxvXKf6IT5V1TLw33SprnqVXmg07gHWeSVHFjfxdkM3AhGRfhEZrKWBU4AtPp5zfLFzgP/rQnjTxdA1K/op48ln4OqqFtNZXoVzJG69+LvbcH4B/gu4T1U/m9jVtbqaLqZu1pWIrBCRYZ8uACfj5lpuA870xabWU63+zgR+qqoL/o9+mrjuTzT4gptnSdaVLbswX7o9E78QG04V8SBunPWiLsZxFE7Jsgn4Qy0W3HjurcBD/nFpm+P4Bm4Io4r7d/We6WLAddm/6Ovu98D6Dsb0dX/Ozbgv9OpE+Yt8TA8Ab2pTTCfhhic2Axv9dlo362qGmLpWV8CxwO/8ubcAn0xc73fjJt+vBXI+P++fb/X7j2rT5zddXD/1dbUF+F8aCquOXOu9vpmNiGEYhtEyvTA8ZRiGYXQIazQMwzCMlrFGwzAMw2gZazQMwzCMlrFGwzAMw2gZazQMwzCMlrFG4yBARMZnLzWv418hIsf49D/O4fVHSMIyvcXyRe851Gz/xSJywf7GcSAiIsMi8oHE87XeDrytn7lx8GKNhjFvVPW9qnqvf7rfjcYceVid51DbEJFUO4+/QAzjrMgBUNW214txcGONxkGKiKwRkVu9E+itIvJ8n3+lX6jmVyKyTUTO9PmBiHzJL3Zzo4j8MLHvdhFZLyKfAQr+n+7VU3sQInKBiFzs068Qt3jOr4EPJsqkRORSEbnHx/Z3Lb6fi8QtQvQT4OhE/loR+bF3Hf65iLwokX+nP8+nav/MReR14hZBugZ31zAi8tfiFvvZKCKX1RoTETlFRH4tIr8VkWu9ySAi8hkRudfH/+8zxLxCRK7zMdwjIif6/ON9/f/OPx7t81+SiGOziKwDPgPUeheXtlJXhjEvun1Lum3t34DxJnnfB87x6XcD3/PpK3EWEAFugZ+tPv9M4Ic+/3nAbvxCNzijuPVTzwUcwb6LLl0AXOzTm4HX+vSltXLAecAnfDoHbACOnBL71OO+AvcD3wcswdlXXOD33Qqs8+lX4XyQAG4E3unT76vFDbwOmKidE+fm+n0g459/CXgXsBy4A+j3+R8DPolzVX0A6m4LwzN8LtcAJ/n083F+U/j3kPbpk4HrfPrzwNk+nQUKU+tips/cNtsWYqs5VBoHH68G3urTX8etVlfje+rcVO8VkVU+7yTgWp//jIjcNtcTi8gQ7sf0Z4nzv8mnTwGOrfVicA6p64BHZjjknwHXq+qkP/4N/nEA+FPgWmmsAVRbW+HVNBYNugZI9gjuVregEcAbcI3SPf4YBZzr7Qm4RvWXPj8L/BrYC5SAK0TkB7jGaTpOBo5JxLZEnOHlEHCV70kobnEh/PEvEpHDgO+q6kOy8GsbGcaMWKNh1EiakJUTaZnyuD+E7DsEmk8cazrTMwH+XlVv2s9zNTtegFsoaH/H+CemxHOVql6YLCAib8Yt+vPOqS8WkeNxjc1ZwIdwK9w1IwBerarFKa//PHCbqp4hbiGm2wFU9RoRuQv4C+AmEXkvsG0/35thzAub0zh4+RXuRw3gbOAXs5T/BfA2P7exCjeM04yquPUgALYDK0VkmbjV0/4S6msfjIrISYnz17gJeH/tGCLyQnE28zNxB3CGiBT8P/U3+/PsBR4Rkbf7Y4mIvMy/5k7gbT591tQDJrgVOFNEVvpjLBWRNf71J4rIC3x+n491ABhS1R8C5+MWTZqOm3GNCv4YtbJDwJM+/beJ/UcB21T1czin22OBMdxa4obREazRODjoE5EnEttHgQ8D54rIZuBvgI/McozrcJbmW4DLcEuQjjYpdzmwWUSuVtUq8Clf9kbg/kS5c4Ev+onw5D/tK4B7gd/6SfTLmKVHrG5N7W/hbMSvA36e2H028B4RqdnV19aPPx/4qIjcDaye5r2gThX2CdwSvptxS52uVtVncT/o3/D5d+JWixsEbvR5PwP+YYbQPwys95Pa9+LmVsANFf6LiPwSSCq43gFsESc1fhFuveuduCGyLTYRbnQCs0Y3WkZEBlR1XESW4dZJOFFVn+lCHEcAN6rqS+dxjD6gqKoqImfhJsVPn+11BwoiMq6qA92Ow+g9bE7D2B9uFLdSWhb4dDcaDE8EDInIxjnMV9R4BfAFcTPJe3AKsgMeEVmL621t73YsRm9iPQ3DaDMichHw9inZ16rqJd2IxzDmgzUahmEYRsvYRLhhGIbRMtZoGIZhGC1jjYZhGIbRMtZoGIZhGC3z/9c1o4binRZvAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "month_idxs=sst_trop.groupby(\"time.month\").groups\n",
    "jan_idxs=month_idxs[1]\n",
    "sst_trop_jan=sst_trop.isel(time=jan_idxs)\n",
    "\n",
    "# seleccionamos solo el rango chuquibambilla\n",
    "\n",
    "sst_trop_jan=sst_trop_jan.sel(time=slice(\"1956-01-01\",\"2013-01-01\"))\n",
    "\n",
    "# seleccionar solo el rango el rango climatico\n",
    "\n",
    "sst_trop_jan_c=sst_trop_jan.sel(time=slice(\"1981-01-01\",\"2010-01-01\")).mean(dim=\"time\",skipna=True)\n",
    "\n",
    "#calcular de anomalias de temp de mar\n",
    "\n",
    "sst_trop_jan_anom=(sst_trop_jan-sst_trop_jan_c)\n",
    "sst_trop_jan_anom.sel(time=\"1999-01-01\").plot(robust=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x1b4b104ebc8>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sst_trop_jan_anom.sel(time=\"1983-01-01\").plot(robust=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "#idx de chuqui\n",
    "idx_chuqui=data_ene_anom[\"CHUQUIBAMBILLA\"].to_numpy()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-0.26413145623645673 0.04512244568245074\n"
     ]
    }
   ],
   "source": [
    "from scipy import stats\n",
    "sst_info=sst_trop_jan_anom.isel(lat=30,lon=1).values # a matriz\n",
    "r, p =stats.pearsonr(idx_chuqui, sst_info)\n",
    "print(r, p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(58, 31, 180)"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sst_trop_jan_anom.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "# go\n",
    "\n",
    "m_corr_pearson =np.zeros((sst_trop_jan_anom.shape[1],sst_trop_jan_anom.shape[2]), dtype=float)\n",
    "m_pvalues =np.zeros((sst_trop_jan_anom.shape[1],sst_trop_jan_anom.shape[2]), dtype=float)\n",
    "\n",
    "for ni in range(0,sst_trop_jan_anom.shape[2]): # hacemos looping en longitudes\n",
    "    for nj in range(0,sst_trop_jan_anom.shape[1]): # loop sobre las latitudes\n",
    "        \n",
    "        info=sst_trop_jan_anom.isel(lat=nj,lon=ni).values\n",
    "        \n",
    "        array_sum = np.sum(info)\n",
    "        \n",
    "        array_es_nan = np.isnan(array_sum)\n",
    "        \n",
    "        if array_es_nan == True:\n",
    "            m_corr_pearson[nj,ni] = np.nan\n",
    "            m_pvalues[nj,ni] = np.nan\n",
    "        else:\n",
    "            \n",
    "            r, p = stats.pearsonr(idx_chuqui, info)\n",
    "            \n",
    "            m_corr_pearson[nj,ni] = r\n",
    "            m_pvalues[nj,ni] = p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_set = xr.Dataset( coords={\"lon\": ([\"lon\"],sst_trop_jan_anom.lon),\n",
    "                              \"lat\": ([\"lat\"], sst_trop_jan_anom.lat)})\n",
    "\n",
    "data_set[\"corr_pearson\"] = ([\"lat\", \"lon\"], m_corr_pearson)\n",
    "data_set[\"p_val\"] = ([\"lat\", \"lon\"], m_pvalues)\n",
    "\n",
    "data_set.to_netcdf(\"correlacion_de_pearson_ejercicio_mapa.nc\",mode=\"w\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x1b4b21d15c8>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plotear la correlaciond de chuquibambilla con atsm\n",
    "dset_2 = xr.open_dataset(\"correlacion_de_pearson_ejercicio_mapa.nc\")\n",
    "corr=dset_2.corr_pearson\n",
    "corr.plot(robust=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.contour.QuadContourSet at 0x1b4b21a8dc8>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plotear los pvalores\n",
    "pv=dset_2.p_val\n",
    "pv.where(pv < 0.05).plot.contourf(robust=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot con marcas en el mapa de correlacion\n",
    "corr.plot(robust=True,figsize=(10,3))\n",
    "\n",
    "for ni in range(0,pv.shape[1]): # en longitudes\n",
    "    for nj in range(0,pv.shape[0]): #en latitudes\n",
    "        if pv.isel(lat=nj, lon=ni) <= 0.05:\n",
    "            plt.plot(pv.lon[ni].values,pv.lat[nj].values, markersize=5, marker=\"+\", color=\"g\" )\n",
    "            \n",
    "plt.savefig(\"pearson_corr_ejercicio_con_mapa.png\", dpi=300)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# EJERCICIO con huanuco, con los datos mensuales, enero"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# correlacion con bootsraping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "58"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(idx_chuqui)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1b4b26f20c8>]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(idx_chuqui)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1b4b29f7408>]"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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OEqb5A8CZxZwnx7YdqWT+Jq2eYd6C6yU8+PcRVtYOAO/zt0KUlKrpXoaa+TuXfXKCpNtC96Lunxcl/OJnn/W9VVVf3h41Kfhqt+VF3vHjBTz49xFZsWw64AVw2ccKsaxYZP4uZR+xjF1DcYwNRHuy42d+OYfHTy3jB+fWfD2OvMnydga32vYW8zSR05NkilLdFi8G9/YxR5Bki8zfXWdJVlufOTkYw5ml3gv+TLZay5d8PY6Crvmbt3oCXPbxCp75dwlLGQF/+PVTkOTmA3RWsM/8S5LCOyVqsMv88y67fVKxEG7YkcaZpRyUHtsCxgrWaz4Xq+2GvPQW3BZln3MrOfzPx0733GvkNTz4dwlPzS3jf337HOZXmi8WNtL8Ad4pUYtV5u/WPjgnqs/9wckUimUZl3rM5qF7Mn9Zb7WtxavM/9+OL+IvnnwZL7fwWesHePDvEpiVwHqu+Q9fRpMezND3+HZp8F/YLOJn/+YH2Cx0NvhYZf5Jl90+WaGMgWgI10+mAABzPSb95LQZkbUW3n9ekC9JSISDIITUfU8P/i1q/ltF9bG+dHWrpZ/T6/Dg3yWwzpJWMq+sUEY6bqX5s8y/O/XSp8+v4bvzaziz1LlsjFIKUaq3dwDUzN+N7JMTJAxEw7h+xwCA3rN5YJn/ehdk/maOnoB3ss+G9hiPX+29riwvaXvBlxByAUAWgAxAopQeIYSMAPgKgFkAFwC8h1K60e5j6WZYltms5ipKMkRJMbV2AAzBv0t7/Rc2BQBwFXBbpSxTKBR6i6aRhAvZR1Yo8iUZqVgIiUgIu0cSPRf8s2L3aP5mjp6Ad7LPppb5H+eZf0d4PaX0MKX0iPb1RwE8QSk9AOAJ7ettDXtDN5t52Zm6Aaq3D9C9ss/ilhr8O7k3t7LC0cxBMgRJoY7M8FjWzJ77GyZTPSj7VK48/WwKKIiSZeYf96jVc6ugBv8TC1vbuujrl+xzP4DPav/+LIB3+XQcXQMbXFltV/Dvctnn2lbnM//KCsf6j0FcnyZtfDy1wf/gZArnV/Nd+1ybwR6DKCm+LklXNX/z93AkGEAoQFoe8toolBAg6tKY82v5ln5WL9OJ4E8BfIMQ8hwh5AHtth2U0msAoP09UfufCCEPEEKOEkKOrqysdOAw/YUVsZq97M7aePkDxuDfnZn/ta0igNb1XDfYZf5uJAb23A9E1ef++h0pyArF/HLvdJOw5AForemgVQoWW7wAgBCCuAe2zpvFMm6ZHgKwvaWfTgT/uymltwO4D8CHCCE/6uQ/UUo/TSk9Qik9Mj4+3t4j7AIKLRbcKqZuDbp9ulTzX9Qz/07KPupzYWrsFnVu61y7O/mg1vHTS8NeOUPwX837p/sXStaaP+CuFmMGpRSbhRLunB1GJBTgwb+dUEoXtL+XAfwzgDsBLBFCdgKA9vdyu4+j28nrBd9mZR9rO2fA2OfffVKEUJb1LqdO+rULZZvM34Xsw7LmAe25nx1LIhIM4HQPFX2zooSJVBSAz5m/KOnavhnJSKglabBQklGWKcYGorhxMrWt2z3bGvwJIUlCSIr9G8BbABwH8CiAD2p3+yCAR9p5HL0AC3rNtnqyoaKpwbjp97tZ9lnKCPq/O6n522b+bmQfpvlrVwvhYADXjSd7quMnJ5YxO5oEAKz5mPnnSzKSNsHf7fBdLRvaHMlQIoybdw3ixNXMti36tjvz3wHgO4SQFwA8A+BfKaX/DuDjAN5MCDkL4M3a19saFvS2imWUm7B4OLOUw450FIOJ3hvyYsVeoLPdPizzr13mArhb5ViRfSrP/cHJFM70UvAXJOweTQDwd8q3WJJ1yc2MVlc5bmqdPkOJCG7eNYisKPXcNLZXtLXPn1J6DsCtJrevAXhjO393r1EQZRACUKoOoUykY67+/5mlLK7fkbL8fqXPv/tkH6b3hwKkazJ/Zins5Hj0gq9BcrthMo1/ObaArWIZg3HzE3K3QClFTpQwnooiEQn6NuVbkhSUZMU2809EQi1NgbPp3qF4GLuG1Kvk4wtbmB1LNv0zexU+4dsl5EsSdqTUgL/q8sOnaJ0lByZsgn8Xe/ssaJ0+e0YTHXVsFO0yfxeLQ3KiBEJQFbRumFQnfc/2QNFXlBSUZYqBaAijAxHfpnzZVVa8QcG3lfcIk32GkxEc2DGAcJBsW92fB/8ugFKKYknGzIiaibj98F3ZKKJYlvWAY0Y3yz6LWwIG42GMDUQ7uqjDiebvRPbJChIGoqEqP5obJtMA0BNFX+OcwkgyilWfpnzZVVYjzd8T2SceRjQUxA2TKZzYpjYPPPh3ASVZgaRQzIwwzdXdh49Nkx5wIvt0YbfPtS0BOwdjLWd1bmFtr6bGbq5kH0kv9jKmBmNIRUM9UfRlNYuBaAhjyYhvso++wtFG81cN95pPEJhkxGpjN08N4qWrW9vS6pwH/y6AFTlnhrXg7/LDx/rJD0zYZf7d6+1zbauIycEYEtHW2vjcImgnQjNL52goAEIcFnxNNqgRQnB9j9g8sMx/IBrCSNI/2YcF9YTJ68HwouCbiAT1K+Gbdw1iq1jGlY1i0z+zV+HBvwtg0707B2MIBojrzP/sUlbNNC0GvAA1GEVC3bnHd3FLwM7BOJKRYGe9fWwyf0IIEmFngSYrSFXFXsYNkynMLWa7Pqs0zimMDkSxlhd9OWZma2414Quoso8oKZCbbM/cKJQxZCjA37xrEED7Jn3/4+wK/uOsM4eCz33/gj7p3gl48O8C2HTvQCyE4YT7zGtuKaf7yNvRjXt8RUnGaq6kyT6tXdK7RW/1tMg0E1Fnx8MWudRyw44UtoplLGX8dcpshK75R8MYTUZQlqk+u9BJimWm+dvLPoCz4TsztoolDCUi+tcHJ1MIBdpT9JUVit/6hxfwJ9840/C+6/kS/tsjJ/B337vg+XFYwYN/F8CmexORIMYGIq66fWSF4uWVnG2bJ6Mb9/gubamBcXIwhmRUzbQ7lXWKkoIAUVtMzXAqMbCCby039Mhil5xYaVUdHVADox+6P8v8kw0yf6D5SfDNQhlDhlmYWDiIAztSOL7gfdH36XNrWMqIyGitwHZktBbU5y50ztmeB/8uQNc6I+4114treZQkxVbvZ0RDga7T/Nll7tRgHImIZqPcYMhN1WhbH8xhi1zMtkYBarun0+BvJrndoJ2Q5xa7u5vEWPAdSarBf92HKV/2OWjU6qnet7ngv1EoYdiQ+QPAzVNpHG9D0feRYwsAKr5bdrATxItXtzp2dc6DfxfAdO5kRNNcXbTasWLvDU5kn3D3yT6LmrXD5GBMb/FrpPt/8ptn8J6/+n7Lv1soK6Z2zoykQ9knK5RNZZ/hZARjAxG8vNzdtsFZQ6vn2IDq7+N21sQL9My/wZAX0LwNyFaxXDcFf8v0INbzpapJ81YRJRlfP34NABxm/urjKUlKxzaM8eDfBeT1jCeI0WTE1Xg9W3u431Hm332yD9vgtVPr9gEaf7CXswIWtgSsZFvLTq1WODKcyD4lSYEoKaayDwCMJCPYLPq7GrEROUFCOKguTa9k/p0/ZrakJeEg829G9lEdPcsYrgn+N02pRV8vdf8nT68gK0h41d4RlCRFry9ZYTxBPHdx3bPjsIMH/y6ABZhkVA3+WUFynKGfWcpiZiRu+4FhRLuw22dxq4h0LIRkNGQo5tk/dtadcrpFOaVR5h8PNzYRy9cscqklHQs7uuz3k5xYGVJjwd+PdY55UUIooHalWdGK7JMTJUgKxVC8WvY5tDONAAFOeBj8H33hKsYGIrjv5kkA1fsSzGAWIclIEM9d7Izuz4N/F6APt0RCGNEKbhv5xpeKgBr8b3BQ7AWY5t9dss+C1uYJVD7YjaZ8WXfK6WutFVIbZf5JB3MHWYNebsZgPOzost9PcoZW1Vg4iIFoyBdzt0JJ1t8DViRa6PZh0721sk88EsT+iQHPMv+MUMbjp5bx9ldMYVg7mTZ6D7AE4TUHxvDcxY2OND3w4N8FsFbPRCSI0STTXBtnXmVZwfnVvO1kr5FouPtkn8UtATuHVE8jp1kdC7in2p35O7APzopsj4L5jEU6HtbNxLqVrCjpW8gAYHTAnynfQknSJ6utaCXzZ8G/tuALqP3+L13NeBJ0Hzu+iJKk4J2Hp/TNepkG74GMUEaAAK89MI7VXAkX19rvNMqDfxeQL8mIBAMIBwN6q50TzfXCah5lmeL6HY31fqA7ZR9m7QAYLBUaZf5CZzJ/J0NejXYnp2Ohhh98v8nV2FP4NeWbd5T5txD8ixUv/1pu2TWI1ZyI5RbrSADw6AsL2D2SwG0zQ0jH1ec100D2yRTVKfFXzo4AQEekHx78NS6vF/An35jzZbFDsSTpU42jTHN10Gqne/rYuHka6bYhL3XAS8Rkulr2KTaQppjsM7+ca2r3QeX3K6ambgx1yEu2fU/UrnCsZTAeRlaUunphSE6snlAe9cncrSBKDWtXlfWa7mWfDT3zrw/+bNL3pSutST/LWQHfnV/F/YenQAjRM/9sI9lHkJCOh3BgYgCpWAhHefDvHH/2xFk89K15vLzS+aXbecPeUib7OLnsPrOUQ4A46/QBtG6fLurzX9YmX5nsU8n8rYO/oqje87OjCZQ02atZhLLSsNsHqHgAmcFkHyvNPx0Pg1L4MjHrFFbwZbjtOPMKJ5m/G6vtWraYqVu8XvbR9y4vt3Y1+X9euAaFAvcfngJQkQMbFf2zQhnpWBiBAMHtu4c70vHDgz/U3t+vvagOZLQSTJqlUKrsLU3HQwgFiKMP39mlLPaMJi3tCWpR+/y7J/izvmom+1Qu6a0/KKwAe0S7PD51rXndX5Rk+8zfgcSQq9nfW0s67kzz9ZNab6LRgQg28qWOX60US3JDzT8YUFtSm2n1ZJm/2XKdVCyM8VQU51da+/w/8sICbppKY792NV6RfRoXfNlVwpE9wzizlGt7rYgHfwCPHLsKQcuI/Qj+ebGyt5S12zlZoj23lHU02cvoNtmHTfdWgn/jzJ9JPrfODCEcJDjVgu4vlhXTRS4MvbPE5nhYRp+2Kvhqt3dz0Tcnlus0f0mhHe9Sypfsl7cznHRhmbFZKGMgGrJsJd07lmzp839+NY8XLm/qWT+gXqmEAsRRwZdJh3fMDgMAfnipvdLPtg/+lFJ88elLuGXXIEaTEV+Cf7EkV2mdzFnRDlGScXGt4Giyl9FtQ14s85/UWj2DAYJYOGCb+bMC60gign3jAy31+jvO/Mv2xxPSslEznGZ+flGWFQjl6iE1NuXbaemnINovb2c4td2oZbNQsl2peV2Lwf/RYwsgBHjHrZXgTwhBOh5u2OefKZb1q8TDM0MIBkjbfX62ffA/dnkTpxezeN+du7F3LIlzfmT+JalK63Ri7nZuJQ9ZoY7bPAE18y9JStdYDC9uCUjFQlWBJxmxz+qM9sM37ky31PHTKPOPO5R9UrGQpT/QYNyZ5usXebFetqoMenU4+JcaF3wB9aTcjOyzWSxjOGkd/PeOJbGWLzV1lUYpxSPHruJVe0f0uRVGKhZqePLPChXZJxEJ4dDOdNs7frZ98P/i05eQiATxzsNTLV/2NUuhJFdtL3LSasc8fZy2eQLdt8d3YbOoSz6MeANPf+PikYOTKSxmBGw0maEKDTL/pBPZRyhb6v0AHPd5+4XZkFql3bhzHT+UUhRKsq2jJ0Nd+tNc5l873WuELXG/0EQMuLxexLnVPN52y86676lT3tavv6yoFtrsKhEA7tgzjGOXN1vqZmvEtg7+GUEt9N5/eAoD0RD2jiexkhX1ANMpCiWp6nJ3NNnY3O3MUhahAMF1Y240/+7a47uYEeqypEaZv7G18uDO5vfkygpFWaaWcg3grACdqxmQqkUv+Hap7GM2p1AZNOxc5s9WmTrK/MNBFJvU/M16/BnXacG/mQTw5DW1RfTW6aG676XjIds+/8p7unJsd+wZRrEstzzLYse2Dv6PPK8Wen/mzj0AKi9+M2f+ViiIclWha3QggnxJtjWDOrOUw+xY0tYHpZZu2+NrHPBiJKL2em7O0Fp5o1bvaEb3F21WODLiDuYOMoL5IhdGKhoCId2b+VeupCqBxw9zN3Z11ajVk92nuSEv++C/ezQBQtCU9HtiIYNggMszXzMAACAASURBVJjW4NKxsG2fP0sM0ob30RGt6Hu0jS2f2zb4U0rx909fws270rhlWh3wYJd9ndT9KaXIl6Sq7UWVQS/rD9+ZpawryQforj2+JUlRB7xqgr+6oNtOZqlo1OOpKEaSkaayI7sVjsZjARp0H5ksbzcSCBCkoqGu7fYxLnJhREIBpGKhjpq75fWdFs5kH7fBX1FoQ9knGgpiejjeXOa/kMH+8QHTZKKRuZ8e/A3F6J2Dcewaird12GvbBn9joZcxO6pd9rXY6+sGUVKg0Oq9pXrmZXHZXSzJuLRecLS9y0g03D2yz1JGAKXqEhcjiUjQ1t5BD/4Rtch6cDLVZOavPgdOMv9Gso9d5g+oRmKNxvv9wsqYbmwg2tFun6vaAvWJdKzBPZnthrvnMytKUKi5tYOR2dFkU1f+JxYyODSVNv1eo4IvOzHUtgvfvmcYP+TB33u+9IxW6DW0ZcXCQewaiuPCWueCv27nXNPqCQCrFgW3l1dyoBTug38XyT7GJS5Gkg2yOjaNGtBWL964M425pazrhd5MUnOi+dt1ljQq+AKNC35+krOwpB5NdtbcjTUwHHTQuhxvQvbZLDBfH+vMH6i0e7rpiFvLiVjMCLjJIvin42EUSrJl8ZadGGpfgyN7hnFtS8DVzfYsdd+WwT8jlPG1F67h/sNTdW6MnW73ZFlulebfIPNvptMHMAZ//zP/hc3qAS+GqufaF8eMWerByRSEsoKLLk/Y7Dmws3cIBwOIBAOWnSWUUi3zt88m07HudfbMWWT+nTZ3m1vKIhULYdJB5t/MrudNG18fI3vHksiJElZcSF4ntSnzQzstgr8W1HMWV38sMaidQbhjj6b7X2iP7u9b8CeE3EsImSOEzBNCPtrJ3/3I81dRLMtVkg9j71gS51dyHeuFN8/87c3d5payCAcJ9mgylVP0bh8Tzf/8ah4/+zc/0DOkdrPIrB2Garp9oqGGE77GTPtG7QNnNel7ZaNgKiOxzN/O0hlgWab5h1aUFJRlaunrw/DT0/8Pv34KDz972fL7OVECIfVau5NBQy85s5jDDTtSlvMSRhKREGSFukpiNrUA20j22TuuJlRupN8T2vJ3K9mnUccXk95qZZ+DkykkIsG2ST++BH9CSBDAXwC4D8AhAO8jhBzqxO++vF7An31rXi30ak5+RmbHksgIUseyHn15u0HzH4iGEAkGLDXXU9ey2Dc+gHDQ3ctX6fOvD67ff3kN351fw1NzK65+ZrNc2xKQiobqAmciEkSxLFvKONkaE7L9EwMIEPOOn+WMgLd+8tv408fP1H3PSeYPqCdiK4fLRnbOjHTcv4LvPzx3Rd8la0ZWqGzxMjKqZf6d8PehlGJuKYvrHU6rj2nJkZs1nm5kHwCupN+TCxnsGopb/uxG5m7spFArH4aCAdy2e6htRV+/Mv87AcxTSs9RSksAvgzg/nb/0o18CR/822cglmV84j2HTbOMVnp9m0Hf4mUoPBJCLBdqKArF85c2cNvuYde/y072YRr8915edf1zm+HaVrFO7wca2zrXLkuPhYO4bnzANPP/xDfPIF+ScXa53qnVaea/ayiuFyNrsdLLaxmM+7PKsSQpWM+XdPdUM3KiebfS6EAECq1kzO1kOStiq1h2vJFuZjgBQE3knMJknyEbewcAmBqKIxIMuJJ+TyxsWWb9QEX2scr8M0X1BBwM1Mej33vbIfzFz9zu+Fjc4Ffw3wXAeC16RbtNhxDyACHkKCHk6MpK69moUJbxi587iisbRfzNB19pWSzd2+HgzySJWjdDK831zHIWWUHCkT3NBH/rbp8lTYb57vxaRyQvdYNXvO72ipmaebDMmfTVm3X8zC1m8fDRyyDEPEg4zfx3DcVxVVsyXwvr3bYb8gLUy/liWUapw7UWdsVit6AkV+PoyejkLt+5RVbDchb8p7Xgf8XipGzGhm7nbP9aBQMEu0cTjmWfQknCudW8ZbEXqMg+Vr3+GaFc1eNv5NBUWm9B9xq/gr+ZsFcVcSiln6aUHqGUHhkfH2/pl8kKxa996Xn88NIG/vSnD+POvSOW950ejiMUIB0L/izDNdVcTT54RzWzJzYE4oZKn399Vs0y/6ubRVxykVE1y8KWgJ0mxT023m/VzVHrPQ+ouv+VjWJVZvWH/3YKA9EQfvL2aVzZKNad0CpDXo0z/9WcaDpw12iRC8OvKV8W9NfyIiSLThOz5xPorLmb2waGnUMxBAhwecNd5p+KhRByIJW6sXk5vZgFpdbFXsBo621d8E03OCm1A7+C/xUAM4avpwEstOMXUUrx+4+ewDdOLuFjbz9k6r1hJBQMqGf+jmX+leXtRqwWahy9sI6xgSh2jyRc/y47b5/FLQH7xtUM43svr7n+2W6wGvACDLbOFkVWtdunvjAGAGe0DPI7Z1fx1NwKfvUNB3DL9CBESanTh4Wys8x/Srs6YQ6kRjIWnTK1DPrk6b+kndAptbZqyIoSBky6lTpp7ja3mMXYQFRvcW5EOBjAzsG4S9mn1LDYy7huLImL6wVH7cOs2HuTSf2QkWog+xhN3TqJX8H/WQAHCCF7CSERAO8F8Gg7ftFfPvUyPv+Di/il112Hn7t7r6P/s3e0cwZvZgVfwLrP+ujFDbxydthRV0QtdrLPYkbAXfvGsCMdxXfn26v7L2e1Aa8hk8yfyT4mmb+iUORK9TIF8/g5taj2+z/49VOYHo7jA3ft0fXh2qsZlvnbGbsBwK5hNfib6f65Bl7+DKd7XL3GKPcsZ82lq5xQttT8gc6Yu51ZyuKGSXdty9PDcVeyz2axbLq43Yy9Y0mUJEVvR7bj5EIGg/EwpkwSGYY6kGh98s/U1LE6hS/Bn1IqAfgwgMcAnALwMKX0hNe/Z345hz/5xhzedXgKH3nrQcf/j132daLTwazgCwAjAxEUy3JVm+FSRsCVjaLe/+sWqyEvoSxjq1jG5GAMd+0bw/dfXmvrY6/18TfCToJm7ZmFsgxKURespgZjSMVCOH0tg39+/ipOXcvgt+89iGgoiJkR9XfUSgQs87ezdAZU2QeAaSDIWnRp1OLXQpeVTCXgWxV9rWQfFijbbe6mKBRnlnKuBxZnRhKuZZ9Gej9j1kXd7+TCFm6aStsmY8ziw+rknxG2l+wDSunXKaXXU0r3UUofbMfv2D8xgC/8wqvwP37yVn0i1Al7x5MQJUXXwdtJviQhEgrUaZFjJrt8K3q/dc3CDitvH9ZzP5mO4a59o1jLl1reZWpH7fpGI3aZv1WwJYTgxsk0jl3exB8/NodbZ4bwjleo8t603hlSHbydZv6TgzEQAlwxCf5WA1K1+CX7LGdFvYPEquhrVfANBwMYSoTb3vJ8ZaOIYll23OnDmBlOYCljXosxY7NQcpz5O+34k2QFpxeztno/I20z66GucNwmmX8nuWv/mCvnS6CzHT9W24vMnBWPXlxHLByw7SywgxCCSKh+j28lE4/hrv1jANSun3axuGU+3QtUCt9mmb9dgfXgzhROLGSwmBHwe2+7Uc/EYuEgJlLROn3YibEboAbBHamYpewTDQUavr9YVtfpzH85K2K/NrRkJvvICkW+JFtKDiPJSNsHveZYsdfFRjoA+hWdE2kGaOzoaWQ8FUUyEmz4+T+3mocoKbhpV+PPY8rC3I1Sqi5v306ZfzfDPPI7YfOQt9heZDble/TCBm6dHnI93GXEbI8vKwzuSMewayiO2dEEvt/Gfv+FTQED0ZCpLQJreTXN/EXrTJtN+r7l0I66bi4ziUCQZERCAUe1k13DcdMg08jOmTHoW7ePgKmhGEaTEdPMnxXVra5cxpLRthd8WaePm13UgOGKzoHuLysUW8Vywx5/BiEEe8cb1/1OLKge/jdNWRd7GWkLc7d8SYZCG3eMtQMe/E3YkY4iHg52xN2zaLG9SG+10z58eVHCyWsZvLJJyYdhtse31mTtrv1jePrcumV7YKtc3SyaFnsBQ+Zv0u1jl/m/Zv8Y7tgzjN99241135sZjtfLPmWlYdbPmBqKm5prOfH1AdQTbiQY6Pig11JGxEQqhvFUFMsmEmajVtURi44zL5lbzGLXUNzR82hEr+U46PjJCmVQ2ni618isg6aPkwsZREMBXSayw2qPL5MCt1O3T1dDCMHsWLIj7p75koy4SeY/UuPp/8LlTcgKxR1N9PcbiYYCppr/gMFq4a59o8iKEl68utXS77Li4lre0pcoGgogQMydNM0WjzBmRhL46q/cZToQMzOSwLWtYpWroijJtnbORnYNxXFtq1hXBM8K5YZ6P8CWeHfW4kFWKNZyIibSUUykY6aZv93zCahXn+3W/NVOH3eSDwDsSMUQDhJHRd+NgjNfHyPXjSVxZaNg64B7YiGDg5MpR7MDVs6uZl7+nYIHfwuu69A+34IomWr+iUgQsXBA//AdvbgBQoDbm7B1MBIN18s+i1tCVc/9j1w3CkD1+7Gi2W4gRaG4tF7AHos5BUKIusrRxNzNaXdNLTMjCSi0Wh92k/nvGoqhLNM6p8dah1E77Ap+zdBoCnstJ0KhwEQqiolU1LTbx7gYx4zRZAQbhZJru2ynlGUFL6+47/QB1A6aXUPO2j2Zr4/Tgi+gNn0o1PrKglJq6+Ffi5Wnv5WpWyfgwd+CvWNJXFovtHWBMqAtbzfJ/AkhGE1G9RH9Zy+s4/qJlON2NSusZB+jle7oQBQHJ1Om/f6KQvGrX3oeb3/oO7ar6axYzooQygr22Fwqq6sc6y+RrRaPNGLGpONHcJP5s17/Gukn61DzB7z19H/oibN44yf+P9sTAMv0x1MxTKTU91HtCTtnU0MB1PcBpRVrBK+5sJpHWaaue/wZMyMJXHEg+zB/okEXmf9ere53ftX85y9sCdgqlnHIgd4PqCf/nCjVvQbsPcE1/y5i71gSskJdTRE2Q6EkWa6uY5fdskLx/KXNliUfgBV8q4P/UkbAjhqrhbv3j+HoxY26Vro/f3IeX3thASevZfBfHn7B9RUA8923yvwBtsTdTvZxm/nX9/q7y/zVY63t+Km1l7YjHfcm+F9eL+ChJ+dxbiWvyxlmsO6eibSa+UsKxXpNEHei+QPtm/LVO32ayPwBtejrpODbVObPtvqt1psCAsCJq6zY6yzzT8dCoLTStMDgsk8X4mbQoxXyFgVfQCu45UqYW8wiJzZn5laLqvlXAqusUCxnRUwOVo/W37VvFCVJqfIS/9bpJXzy8TN492278LF3HMI3Ty7hz5+cd/X7L66pAXjWZhdBIho0NXbLCapEZuZ+aMfOQdWvyXgiFyXFcebPitO1HT9Zoez4cl319G+94PvH35jTDeLsPJiYzLMjHdNP7LXSj76/1zLzb6+525nFLIIBgn3jzWX+08NxrOdLtms/AeeOnkYGE2GMJCOWn/+T1zIgxNnmMcDa3K2ywpFn/l1Dp6ydixayDwCMJqNYz5fw3EV1k0+rnT6AusfXmPmv5UTICq2btr1z7wiCAYLvai2f51fz+PUvH8ONk2n8wbtvwc/dNYt337YLn3z8DJ48vez4919czyMUIJbdPoDq72Pa7eMi0zYSDBBMDcWrskShLDvO/FOxMNKxUJXsw7Z4Odb8Y60XfI9d3sQjxxbw5kM7ANh3uuiyz0AUE+modlt1x09jzb+95m5zS1nMjiYcn4RrmRlx5u65USiDEPfZ9d6xJM5ZdPydWMjgurGk5We3Ft3WuabjqyL78My/axhORjCUCLc1+FNKtT5/a9lnNSfi2QsbmEhFMT1cb4fgllrZ55phutdIKhbGrdOD+N7La8iLEn7p80cRDBD8r/90B+KRIAgh+IN334JDO9P4tS8/73jp9YW1guqcatMhkbTY0Vq7yMUNMyPxuszfafAH1HZPY+ZfcNmfPajJPs3aZVNK8eC/nsTYQAQPvvtmAPaZ/1JGwHAijEgogImUVeav2YlbJR/tzvyXck11+jBmhp21e24VSkjHwq6vGPfadPydXMg41vuBSkG3tuibFSXEwo0HBdsBD/42uLF2bQahrIDSekdPxmgyAlFS8J35VRxp0sytltohL73H38Re+a59Y3jxyhZ+/cvPY345hz9/3+16tgWoKw7/6v13IBQgeODzRxtefgPApbUCdjdYP5mIhkx/VlYwd6B0wu6RRFWQEMrOC75AvZFYo6y5lnQ8DEmhlktqGvHYiUU8e2EDv/Hm6zGRimFsINIw82dBfzxlnvk3ktGGExEQgra0ewplGRfW8k3r/YAx87cP/hsF59O9RvaOJbGUEevei5uFEq5uFl1N2qctLD4yRefSodfw4G9Du4M/kzbsNH9A/fDdsad1yQfQun0Mff76dO9gvZ3uXftHISsUj59axkfuPYjXHBiru8/MSAIPve92zC/n8Nv/+KJtZkspxYW1PGZH7e2oE2HzzN/KgdIJ08MJrBn04VYz/0Z6eS2tmLuVJAUf/7fTODAxgJ8+ojqhNzI2W86KutwTCweRjoXqev2zFr4+jGCAYDgRwWobgv/8cg6UwrWnj5HRZATxcLBh0Ve1dnBe7GVYSb/6zl4Hnj4M9vrXDnr5ZeoG8OBvy97RJK5tCaYDR17Afm7cIgMdM/ibe1HsBViffyX4L24JCAWIbiRn5Pbdw0jHQnj7K3bigR+9zvJnvubAGH7zLTfgX1+6hheuWA+GbRbKyApSw10EyWjIPPiLzlsra6nVh90MeQHqoFdGkPSCXcZlf/Zgg4UednzhBxdxYa2A3/2xG3W5bPdIwlb2WckIesYPQB30MpF9Gp28dg7GcPpa/X7kVtG3d7Ug+xBCMD3c2Nd/q1ByVexl1DZ9CGUZf/3tc/jQF3+IWDhgugPcioqtd33B149iL8CDvy17x90vc3ZDJfO3b7WLh4OOh0kaUSf7bKltnmaup7FwEE/919fj/33vbQ0lp3fdpm7hPG4zFcyeR7tOH0AdcDPr83czVFVLrT4suGj1BCpLXVjRN+da9rFf6GHFVqGMP/vWWbz2wBjuub6y0W5mOIGFTcHUgoNSdSCNyT6AOuxVV/C1WORi5F2Hd+GHlzZxyuMTwJmlLCKhgG3LrxPUK6DGBd/hJmQf9j6dX87h4Wcv4/V//BQe/Pop3LJrEP/4y3dhOOn8aoK9b2tP/upOap75dx3tdvesbPGyLvgCwOGZ1szcjNQOeS1mBOxIW29QGklGHBXKpgZjGIyH9UtiM1imuqeB7JOMhlCWad3O22yT3T5AJfNnUokoyYi6yfyHq10knS5vZ+iyj01vvhl//uRZbBXL+J37bqw6Ae8eSUBWqOmGsY1CGWWZVr2uO0wsHpzIaD91ZBrRUACf+/5FV8fdiLmlLPaPDziyRrBDrcXYZ/7qFi/3sk88EsTUYAwPfessfvurL2IiFcUXf/FV+PwvvAo3u8j6AXVDYDISrM/8BYnLPt3I7Gh7gz+TfawKvmMDUURCAbxas1vwgmgogJKk6Nr8YkYwXafoFkIIbppK46RNhnhhtQBCUFU0NoOdDI3ZP2utbFbz1/XhdXWfr1BWEHOR+bOlLmzQq7K83Xm3D+Au8y9JCr70zGXcf+tU3ZUfew7NpB99wKsu8xerajJOZJ+hRATvvHUK//L8VU+9ic4sNufpU8vMcAJZQbI8qUqygowgNT0Z/9oD49g/MYBP/ezt+JcP3a1bnjeDau5mVvDlsk/XkYyGMDYQaZhZNAuTfawy/1g4iK99+DX4pddZ6+1uMe7xpZTqso8XHNqZxulrGUs30IvreUymYw219qS+x7ciT+VL6havZjN/Qoja8bNRQEk7PjeZ//hAFJFgAFc31cCa1adjnQUVq24PO45eWEdOlPBjr5iq+x6bWjYL/kuatj9hyPzHU1GUJKUqgFstcqnlAz8yi2JZxj/98IrjY7cjI5SxsCW01OnDsNrUVvld6uvUjOwDAH/0k6/AN37jdbjvlp0td9ulazz9KaW84NvNzDQorLVCoYHmDwA3TKaaHoIxw7jHNytKKJRk0zbPZjg0lYYoKZZXShfXCg0lH6CyytE45VvZmtX8B4X1+jPZy43mHwgQ7ByK6Zq/W58hlt1tuSj4Pjm3jEgwgLv311/5sall08w/wzL/6oIvUL3Ry+ncxC3Tgzg8M4TP/+Bi03MKRs5qtg7NevoYYb7+Vgka8yVqRvbxmlpzN1FSUJapL74+AA/+DZkZbmfwVzNbM1fPdmHc47u0Ve3j3ypsqYWV7n9xrYA9I429z80yf9Za2coHZXpY7fVnfkVuMn8AmBqMV2n+CRdWE1aarx1Pzq3gVdeNmMqCwYB1pwsL8LWyD1AZ9NJlNIfP5wd+ZA/OreQ92fB2erE1Tx8jZqZ9RjabsHNuF7XOrn56+QM8+Ddk94h1V0WrFLSCb9yP4F9WbAe8muG68SQioYCp7p8TJazmROwZc5D5R+ozf7dDVWbMjCSQL8n6zmI3mj+gFn2Z5p9z4ejJSMfDjnXzy+sFzC/n8PobJizvM1MzuMZYyYpIRUNV76uJmkGvApPRHF65vO2WnRhJRvC5719wdH87vju/ivFUVK+jtMJgIoxULGQp+2wVuyfzT8dCVX3+fpq6ATz4N8Suq6JVKpp/5y77WLYrSkplcbtHmX84GMDByZS+3s7IJc3QzUnmnzDN/DWNvcmCL1Bp95xfVp0aXWf+Q3EsZQWUZQVZ0dkiFyODLpw9n5xT/ZJef9A++FsVfMdrOrhqZR/dIdXhCSwWDuKnXzmDx08tmW41c4pQlvHU3ArecmiHJxPrgJr9W/n7bOTV57tZzd9Lap1dt3w0dQN48G/ItIt1cW4plGTEwgHXniOtYJR9WPD3quALqEXfkwuZOm1Yt3J2o/mXvM/8AeAsC/4uM//poTgoVWcjVC9/dwElHXO+0OXJ08uYHU3o7cZm7B5JYKNQrusgWc6I2JGqfk0HoiEkI0Fd9mlmN8LPvmo3AOCLTzff9vmds6solGS89abJpn9GLXaDXszLfyjuf+avav6S/tngmX+Xs9umpa5VChbL29tJJfirss9wIuxpQfmmqTQ2CuW6K6WLDnv8gYrmb5zyzTW5yMUIC/4s83f7uI2DXm4WuTDUVY6NC77Fkozvvbxmm/UDlfdmrd69lBWqOn0YE+kYljTZx+2cAqDWTN5wcAe+8uzlqkFBWaF4am4ZH3vkuJ5QWPHYiUWkYiFP25dnRtTM36wYvVkoIUD8WZZSSzoWhqxQ/X1d2eLlz7H5/4x0OXZdFa1SEGXLNs92oXf7lBXTJS6twvrRTy5k9GAJqJn/SDLiKFtmmb/RUCuryz7NZ0kD0RBGkpGK7NOE5g+ovf45UcJOl3JZOh7GqWvZhvf7wbk1iJJiq/cDlWLnpfWC/rxTSrGcEas6fRjjqShWtMy/2e6pD/zIHjx+agn/fnwRr9o7ioePXsZXnr2sS0EUwH+//2bT/yvJCh4/tYQ3Hpzw1MVyZjiOYlnGaq5UZWkBqAXfwXjYdIK901Q8/SUkoyFe8O12ggGCXcNxRxuD3JIvSZZ2uu2i0ucvezbgZeTgZBqEoK7o67TNE1CN3QCLzL/FLGlmOK5LUG4zfxbs1cy/7D7zdyj7PDm3jHg4iDv32pv5VTL/SmKSESSIklLV6cMwWjy4NaZjvGb/GPaOJfHfHjmBuz7+BD7xzTOYHUvgoffdhnfcOoV/+uFV/aqilmcvbGCjUPZU8gHs2z03mpzubQe1ts5c9ukBGploNUuhJHe00wcAYqHqgq9XnT6MZDSEvaPJuqKv2ubpLPiHggFEQ4GqhS45seyqtdKKaW2ZO+A+84+FgxgbiGJhs6j5DLn70A7Gw8gKku1CdEopvnV6GXfvH214chpMqEtmjJ0uK4b1jbVMpCoWD5UhNXfBPxAg+PDr9yMVC+GBH92Hp37rHvz9L74a77h1Cj9/9yxyooR/thgGe+zEIqKhAF53w7jp95ulYt1Rn6BtFZuzc24H7LlmGX+mKCGivdf9gAd/B7D+cK8p2KxwbBcs888JElZzJc9lH0CVfoyZvyjJWNgqYk8DQzcjyWhIb4UFnFkROIFJJYD7zB8Adg3FcHmjgHxJbqrVE6hcxZjx8koOVzaKuKeB5MPYPVqdmLCCbq38AagnhEJJRk6Umt6HDAA/ccc0vvORN+Cj9x3UnS8B4LaZIdy8K43Pfb9+GIxSim+eXMJrD4x7XueatljqMreYxdPn17G/yTWRXpOusfhgV49edT25hQd/B+weSWA9X7K8nG2WvOhfwZdli251ayccmkrj8npR72lX/XScFXsZiUiwKvPPOLQiaASzAwDcZ/6AqvvPLao1A/eyD5vytZZ+njy9AsC+xdNI7RCi2YAXozLoJXgmoxkhhOADr57F2eUcnj6/XvW941czuLpZxFtv2uHZ72MktVrOlZo1nb/2peeRjoXwkfsOev47m4G9/uyqy09TN6CNwZ8Q8vuEkKuEkGPan7cZvvc7hJB5QsgcIeSt7ToGrzDTVr2gUPKv4Mv67ne0IfizSV9mA3xpnbV5usj8IzWZv9C8qZsR4y6BpoL/UByr2lpDt8Hfibnbk3PLuGFHyvEA1G6t00XRpCSm6Zs5te4w9PrntPWBXrnFMt5x6xQG42F8vsYF9LETiwgGCN50o/fBH1BrOUbN/+P/dhpzS1n88U/dWrUXw09q/Z38NHUD2p/5f5JSelj783UAIIQcAvBeADcBuBfAXxJCOhsBXWJnotUKBZvl7e2CyT7MW99rzR+obDhiNg8XVp23eTLikSAK5RrZx4vMv0XZx9jB5Fbzb2TulhXKeOb8Ou456FwTnxlJoCQpesa/lBERDwdN5RyW+S9lBM3Xx/usMx4J4j1HpvHYiUV9SxygBv87Z0dceeC7Ydow7fyt00v4u+9dwM/fPetYPusEuuavZ/7+mboB/sg+9wP4MqVUpJSeBzAP4E4fjsMx7cv8pY76+gCVbJedyNoR/MdTUYyniuB4kwAAEl1JREFUoji5wDL/AgaiIYy6+OAno8E6Y7dW2jwZU0NxMIm12cyf4fZk1GiV43fnVyEptGGLp5HaORS2vtFMR2ZS0EpWbMqewinvf/UeSArFF5++BAA4t5LD2eVcWyQfxsxwAlc3i1jKCPiv//AiDk6m8JF7u0PuYURDQURDAf3k38ysiJe0O/h/mBDyIiHkM4QQtodwF4DLhvtc0W6rghDyACHkKCHk6MrKSpsP057BuOYf4mHwV7Rhj4QHUoYbItpl/mquhGgo0LZOiJum0nrHz4W1PHaPJFwVthKRUJ29gxeZfyQUwM50DKEAaWqRiDHzdy37JOxlnydPryAVC+EOFys7a339lzOCaY8/oA6ZRUIBXfbxooBuxp7RJF53/Ti+9MwllGUFj51YAgC82eMWTyPTw3GUZYr/63NHkRMlPPS+2zwdXvQK1dxNy/x9XN4OtBj8CSGPE0KOm/y5H8CnAOwDcBjANQB/wv6byY+q632jlH6aUnqEUnpkfNzb1jC3EEI8d/cUJPstXu2CEKJnvJODsbZ1Ghzamcb8cg6iJOPSWgGzDgzdjCRrVjlmBfdeOlZMjySabq9jnSWAe5+htN7qV984QCnFk3PL+NED4650+F3alQxLTFayommxF1Bf+4lUVC/4tiv4A+ow2HJWxGMnFvHYiUXcsmvQEyM3K9hJ8MUrW/i/f+xGHPDAMbQdpA22zj0t+1BK30QpvdnkzyOU0iVKqUwpVQD8NSrSzhUAM4YfMw1goZXj6AS7HewKNWM9XzLt62YrHDst+wAVuaMdbZ6Mm6YGISkUp69lcXmjgN0ODN2MJKIh/Tlyaz/ciL2jSdsdCnYMxsP6Cdutt89ANIQAMZd9Tl3LYjkruu6Bj4QCmBqseNssZ0XTNk8G2+jVykpMJ9xzwwSmh+N46Il5HLu82VbJBwBmtXrSm26cwPtfvaetv6sVmLmbKMkQykp/FnwJITsNX74bwHHt348CeC8hJEoI2QvgAIBn2nUcXrF7VC0oKTYDOrV8b34Vr/6DJ0yNsAo+OHoymJtlO/R+BrMbeOLUEsoy1T+cTjFm/oWSDMWF/XAj/vObD+BT77+9qf9LCNEzWLfBkxBS5+nOePq86pN/dxNrAqeH47i0XkBe6983G/BisEGvnNh4f28rBAME73/1Hsxpi1u8nuqtZc9oEn/1/tvxiZ8+7FvfvBNSMVX2cbsJrh20U/P/H4SQlwghLwJ4PYDfAABK6QkADwM4CeDfAXyIUipb/5juYGY4DlFSsJITG98ZwOnFDH7p88+hJCs4frXe375Q8kf2AVAl+7SLPSMJJCNBfP34IgD15OmGRCSkBn2FurYfbsTOwTju2GNvnWAHKxo3c9WmrvKrD/7PnF/HrqF4U9IIW0/JOn5qHT2N7EgbZJ82Z53vOTKDSCiA68aS2D/R/kGre2/e6auG7gTV079cMXWL+5f5t+03U0r/k833HgTwYLt+dzuYMXT8NJJLrm0V8fN/+ywS0SAmB2N4eSVXdx898+9wwRcwBP82Zv6BAMGNO9M4enEDADDroscfgD75XCzLXZElGdk7lsSJhUxTGeagyUIXSimevbCO1x5orra1eySBpYyoSz+2mX86howgIUC8u5KyYiQZwcd//BYMJyNdnY13ElX2kXw3dQP4hK9jnFo7Z4Qyfv5vn0VWkPC3P3cnjswOmwZ/fzV/TfZpY+YPqB0/gKpLuz3RVBa6SJ4scvGSX3vjAXzhF5vrTk7HQ3q3B+Pcah6ruVJDIzcr2FXVDy+pJ1qrgi9QsX1QqLfTvVb8+O3TrlpX+x1m7ue3qRvAg79jdg2zrgrrom9JUvArX3gO88s5fOr9t+PQVBr7xgewUShjPV+qui/L/Dtt7AZUBr3aWfAFKrr/7pGEa0tdJocVS7K+rKQTwcoJI8kIDk6mm/q/6Vh95v+sZoXwytnmgj9ztXzuIgv+9gVfRrecTLcTqVgIJUlpekrcS3jwd0g0FMRkOmaZ+VNK8dGvvojvzq/hj37iFfol/D7NVOpcTfZfWd7uo+zT9sxftXlw6uZpRM/8RdmTRS7dgtkqx2fOr2M0GcG+cXfSGINdlT5/aRORoP3shvGqoFtOptsJlumzXdBc9ukRZmzcPf/l2FX80/NX8Ztvvh4/cce0fjsL/rXSDxtgSnTY1RNQT2SE2GeIXnBgxwCioQD2NVHsSxpWOWZbcKDsNsy6fZ65sI5Xzo40rYuPDUQQDweREyWMp8ynexnGekA77B049rDWTmZCx2WfHmFG66ow46vPXcWe0QQ+/Ib9VbfvGo4jEgrg5ZV81e3MusCXVs9QAGMDUc9Nvep/TxD/8Ms/gl953T7X/9e4xD3XpPd8NzIYD0MoK/oaxKubRVzZKDat9wPaEKLmP2XX4w8AI4kIQpoE1w8n016DBfsrG0UEmuwY8woe/F2weySBxYwAoVzdmbqcFfC9l1dx/61TdVlXMECwdzSJl5fNZZ+4DyPob7pxB376yEzjO3rAK6aHmjLz0jP/Fr3nu43aKV+m97cS/IGK9GPm5mkkECD6CaIfTqa9Bnv9r24WkYqFfe2C4q++C2ZG4qBUfeH2GRZE/OuL16BQ4J2Hp0z/376JZN3u1kJJQjzc+maqZnjPKzsT+Fshacz8RfW5asaLp9swLvQYT0XxzIV1DERDuHFncwVkBmtFtuv0YUykori2JfTFybTXYBr/1c1iwxN1u+n9T1MHsXL3fOTYAg7tTGP/hLmfyL7xAVxaL+iX+oAa1Dq9xauXYN0+hZKk+vr0SZbKgj/r+Hnm/Dru2DPcchKwWw/+jQPKuHaC6JfntJdgr39JUnwfSOPB3wVmwf/iWh7HLm9aZv2AGvxlheoLVAC1hdGPNs9egXnv5EV1yKtf2hL1Jd7FMtZyIuaXcy1LPkBlT4HdgBeD3Ydn/p3HGPB58O8hxlNRREOBqnbPr72getK941b74A9Ud/zkRcmXNs9eIRoKIEDUzN8rO+duYDBeWeX47AW1L/9VHgT/W6YHMZmO4RXTQw3v+8rZYdyya9C3xeHbmVg4oBfc/a659McnqkOoXRUJfdCLUopHji3glbPDtp4se7X+bWPHjx8rHHsJQoju79Nu++FOUtH8JVxY3UIkFMAt04Mt/9wd6Rh+8LtvdHTfd982jXffNt34jhzPYeZ+6/mSr22eAM/8XbN7pOLrf3oxi7PLObzzcN0umioGoiFMpqs9fvKlzi9v7zUSmrOnl3bOfmOUfZ45v47bZoZ0uw3O9oB1/HDZp8eYGVa901nWHwwQvO3mxna1+yaSVZl/kWf+DUlqnv5ZoT37Zv0gFlZX+S1sFnFiYcsTvZ/TW7CM309HT4AHf9fMjCSQFSVsFMr42gsLeO2BMYwONC6y7RsfwLnlHChV9wHkS1LTC0W2Cyzzzwrlvsn8AfXD/9TcChTaen8/p/dg72W/XWp58HcJ6/h55NhVXN0s4p02hV4j+8YHkBUlrGie6wWRd/s0IhkJIacNefWL5g+ol/1XN4sIBghu3+18Xy+nP2Byj59bvAAe/F3Dhmk+/e1ziIYCeIvDDUXX1RR9CyXZ19HuXiARDWItV+qY/XCnGNQu+2+eSvOrv22IHvx5wbe3YMH/2paAN924w3FGamz3lBWKYlnmBd8GJCMhLGUEAP3Vk84+9M1aOHN6G6b184JvjzEQDWFU86qxG+yqZTIdQyISxMsrORTL/q1w7CUSkaC++KSvNH/tQ8/1/u0J0/r9fk/3zyeqg0yPJFCSFdxzg/O1e4EAwXXjasePnyscewmjJOL3B8VLBnnmv61hWv+gz7JP/3yiOsiHX78fhZLkuj973/gAnru4gYKPKxx7CWNBvF9aPQF1sfnsWLIpt1NO7/PWmyexXihjeth6MLQT8ODfBG8+tKOp/3fd2AAefWEBa3m144fLPvYkq4J//7xVb5ke9GSql9Ob7ByM47+8+Xq/D4Nr/p1k30QSlAInFjIA/Fnk0ksYn59+kn04nG6AB/8Owjp+XrqyBQDc0rkBxuennzJ/Dqcb4MG/g+wdS4IQ4KWravDnmb89xuenn/r8OZxugAf/DhILBzE9HMdZbaUj1/ztYZl/LBxo+75hDme7wT9RHea6MXWxC8Az/0aw56efOn04nG6BB/8OY9z9yzV/e9iyG17s5XC8p6XgTwj5KULICUKIQgg5UvO93yGEzBNC5gghbzXcfq922zwh5KOt/P5eZN9EUv93jPu425LQTo682MvheE+rmf9xAD8O4NvGGwkhhwC8F8BNAO4F8JeEkCAhJAjgLwDcB+AQgPdp9902sMw/EQki0OLS7n6H1UR48OdwvKelTxWl9BSgriar4X4AX6aUigDOE0LmAdypfW+eUnpO+39f1u57spXj6CUqwZ8HtEYkuOzD4bSNdmn+uwBcNnx9RbvN6vY6CCEPEEKOEkKOrqystOkwO8/YQASpWIh3+jhAz/x58OdwPKfhp4oQ8jgAM9P636OUPmL130xuozA/2VCzH0Ap/TSATwPAkSNHTO/TixBCsG98AILm7MmxJhwMIBIKcNmHw2kDDT9VlNI3NfFzrwCYMXw9DWBB+7fV7duGX33DfuRLPPg74XfvO4g79nD3Sw7Ha9qVUj0K4IuEkE8AmAJwAMAzUK8IDhBC9gK4CrUo/DNtOoau5Y03NmcMtx35ubv3+n0IHE5f0lLwJ4S8G8BDAMYB/Csh5Bil9K2U0hOEkIehFnIlAB+ilMra//kwgMcABAF8hlJ6oqVHwOFwOBzXEEq7X04/cuQIPXr0qN+HweFwOD0FIeQ5SukRs+/xCV8Oh8PZhvDgz+FwONsQHvw5HA5nG8KDP4fD4WxDePDncDicbQgP/hwOh7MN6YlWT0LICoCLLfyIMQCrHh1Ot8AfU+/Qj4+rHx8T0H+Paw+ldNzsGz0R/FuFEHLUqte1V+GPqXfox8fVj48J6N/HZQaXfTgcDmcbwoM/h8PhbEO2S/D/tN8H0Ab4Y+od+vFx9eNjAvr3cdWxLTR/DofD4VSzXTJ/DofD4RjgwZ/D4XC2IX0d/Akh9xJC5ggh84SQj/p9PM1CCPkMIWSZEHLccNsIIeSbhJCz2t/Dfh6jWwghM4SQJwkhpwghJwghv67d3rOPixASI4Q8Qwh5QXtM/492+15CyNPaY/oKISTi97G6hRASJIQ8Twj5P9rX/fCYLhBCXiKEHCOEHNVu69n3n1v6NvgTQoIA/gLAfQAOAXgfIeSQv0fVNH8H4N6a2z4K4AlK6QEAT2hf9xISgN+klN4I4NUAPqS9Pr38uEQAb6CU3grgMIB7CSGvBvBHAD6pPaYNAL/g4zE2y68DOGX4uh8eEwC8nlJ62NDb38vvP1f0bfAHcCeAeUrpOUppCcCXAdzv8zE1BaX02wDWa26+H8BntX9/FsC7OnpQLUIpvUYp/aH27yzUwLILPfy4qEpO+zKs/aEA3gDgH7Xbe+oxAQAhZBrAjwH4G+1rgh5/TDb07PvPLf0c/HcBuGz4+op2W7+wg1J6DVADKYAJn4+naQghswBuA/A0evxxafLIMQDLAL4J4GUAm5RSSbtLL74P/xTAbwNQtK9H0fuPCVBPzN8ghDxHCHlAu62n339uaNcC926AmNzG+1q7DELIAICvAvjPlNKMmlT2Ltqu6sOEkCEA/wzgRrO7dfaomocQ8nYAy5TS5wgh97CbTe7aM4/JwN2U0gVCyASAbxJCTvt9QJ2knzP/KwBmDF9PA1jw6VjawRIhZCcAaH8v+3w8riGEhKEG/r+nlP6TdnPPPy4AoJRuAngKaj1jiBDCEq1eex/eDeCdhJALUKXTN0C9EujlxwQAoJQuaH8vQz1R34k+ef85oZ+D/7MADmhdCREA7wXwqM/H5CWPAvig9u8PAnjEx2NxjaYb/28ApyilnzB8q2cfFyFkXMv4QQiJA3gT1FrGkwB+UrtbTz0mSunvUEqnKaWzUD9D36KU/ix6+DEBACEkSQhJsX8DeAuA4+jh959b+nrClxDyNqhZShDAZyilD/p8SE1BCPkSgHug2s0uAfgYgH8B8DCA3QAuAfgpSmltUbhrIYS8BsB/AHgJFS35d6Hq/j35uAghr4BaJAxCTaweppT+d0LIdVCz5hEAzwN4P6VU9O9Im0OTfX6LUvr2Xn9M2vH/s/ZlCMAXKaUPEkJG0aPvP7f0dfDncDgcjjn9LPtwOBwOxwIe/DkcDmcbwoM/h8PhbEN48OdwOJxtCA/+HA6Hsw3hwZ/D4XC2ITz4czgczjbk/wcZfE35Cv1AYwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(np.random.choice(idx_chuqui,size=58,replace=True))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "# corre lacion con bootstrapping\n",
    "\n",
    "# go\n",
    "\n",
    "m_corr_pearson =np.zeros((sst_trop_jan_anom.shape[1],sst_trop_jan_anom.shape[2]), dtype=float)\n",
    "m_corr_pearson_inf =np.zeros((sst_trop_jan_anom.shape[1],sst_trop_jan_anom.shape[2]), dtype=float)\n",
    "m_corr_pearson_sup =np.zeros((sst_trop_jan_anom.shape[1],sst_trop_jan_anom.shape[2]), dtype=float)\n",
    "\n",
    "\n",
    "for ni in range(0,sst_trop_jan_anom.shape[2]): # hacemos looping en longitudes\n",
    "    for nj in range(0,sst_trop_jan_anom.shape[1]): # loop sobre las latitudes\n",
    "        \n",
    "        info=sst_trop_jan_anom.isel(lat=nj,lon=ni).values\n",
    "        \n",
    "        array_sum = np.sum(info)\n",
    "        \n",
    "        array_es_nan = np.isnan(array_sum)\n",
    "        \n",
    "        if array_es_nan == True:\n",
    "            m_corr_pearson[nj,ni] = np.nan\n",
    "            m_pvalues[nj,ni] = np.nan\n",
    "        else:\n",
    "            \n",
    "            r_boot=[]\n",
    "            r_inf=[]\n",
    "            r_sup=[]\n",
    "            \n",
    "            for i in np.arange(0,1000):\n",
    "                alt=np.random.choice(np.arange(0,len(idx_chuqui)),size=58,replace=True)\n",
    "                random_chuqui=idx_chuqui[alt]\n",
    "                random_sst=info[alt]\n",
    "                \n",
    "                r,p = stats.pearsonr(random_chuqui,random_sst)\n",
    "                r_boot.append(r)\n",
    "                \n",
    "            m_corr_pearson[nj,ni] = np.mean(r_boot)\n",
    "            m_corr_pearson_inf[nj,ni] = np.percentile(r_boot,2.5)\n",
    "            m_corr_pearson_sup[nj,ni] = np.percentile(r_boot,97.5)\n",
    "           \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "# almacenamos en netcdfs\n",
    "data_set = xr.Dataset( coords={\"lon\": ([\"lon\"],sst_trop_jan_anom.lon),\n",
    "                              \"lat\": ([\"lat\"], sst_trop_jan_anom.lat)})\n",
    "\n",
    "data_set[\"corr_pearson\"] = ([\"lat\", \"lon\"], m_corr_pearson)\n",
    "data_set[\"corr_pearson_inf\"] = ([\"lat\", \"lon\"], m_corr_pearson_inf)\n",
    "data_set[\"corr_pearson_sup\"] = ([\"lat\", \"lon\"], m_corr_pearson_sup)\n",
    "\n",
    "data_set.to_netcdf(\"umbrales_de_corr.nc\",mode=\"w\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([  4.,  31., 117., 240., 270., 211.,  84.,  30.,   9.,   4.]),\n",
       " array([-0.65107702, -0.56059934, -0.47012167, -0.37964399, -0.28916631,\n",
       "        -0.19868864, -0.10821096, -0.01773328,  0.07274439,  0.16322207,\n",
       "         0.25369975]),\n",
       " <a list of 10 Patch objects>)"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAAD4CAYAAAAXUaZHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjMsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+AADFEAAAOi0lEQVR4nO3df6zdd13H8ecLyjARkM3dzdoVL2JJGIl2eDNnCAEdytgSOxLRLQKFLCkJI4GIJgVMIJolVQSUoIvFLXQEgfHLNdlURiUSEgfcwVK21bEKdbu0aS+C/MgSdOPtH/d76Vl3bs+599xzzu2nz0dy8v2ez/fzPd/3/bR93W8+/X6/J1WFJKktT5p2AZKk9We4S1KDDHdJapDhLkkNMtwlqUGbpl0AwPnnn1+zs7PTLkOSzih33333t6tqpt+2DRHus7OzzM/PT7sMSTqjJPmvlbY5LSNJDTLcJalBhrskNchwl6QGGe6S1CDDXZIaZLhLUoMMd0lqkOEuSQ3aEHeoSoPM7r59asc+sueqqR1bWivP3CWpQYa7JDXIcJekBhnuktQgw12SGmS4S1KDDHdJapDhLkkNMtwlqUGGuyQ1yHCXpAYNDPckW5N8LsmhJPcleVPX/s4k30pyT/e6smeftyY5nOSBJC8b5w8gSXqiYR4c9ijwlqr6SpKnA3cnubPb9t6q+svezkkuBq4Bng/8PPDZJM+tqsfWs3BJ0soGnrlX1bGq+kq3/gPgELDlNLvsAD5aVT+qqm8Ch4FL16NYSdJwVjXnnmQWuAT4Ytf0xiQHk9yc5NyubQvwcM9uC/T5ZZBkV5L5JPOLi4urLlyStLKhwz3J04BPAm+uqu8DNwLPAbYDx4B3L3fts3s9oaFqb1XNVdXczMzMqguXJK1sqHBP8hSWgv3DVfUpgKo6XlWPVdWPgQ9wcuplAdjas/tFwNH1K1mSNMgwV8sEuAk4VFXv6Wnf3NPtFcC93fp+4JokT03ybGAb8KX1K1mSNMgwV8u8EHg18LUk93RtbwOuTbKdpSmXI8DrAarqviS3AvezdKXN9V4pI0mTNTDcq+oL9J9Hv+M0+9wA3DBCXZKkEXiHqiQ1yHCXpAYNM+cu/cTs7tunXYKkIXjmLkkNMtwlqUGGuyQ1yHCXpAYZ7pLUIMNdkhpkuEtSgwx3SWqQ4S5JDTLcJalBhrskNchwl6QGGe6S1CDDXZIaZLhLUoMMd0lqkOEuSQ0y3CWpQYa7JDXIcJekBhnuktSgTdMuQNroZnffPpXjHtlz1VSOqzZ45i5JDTLcJalBhrskNchwl6QGDQz3JFuTfC7JoST3JXlT135ekjuTPNgtz+3ak+R9SQ4nOZjkBeP+ISRJjzfMmfujwFuq6nnAZcD1SS4GdgMHqmobcKB7D/ByYFv32gXcuO5VS5JOa2C4V9WxqvpKt/4D4BCwBdgB7Ou67QOu7tZ3ALfUkruAZybZvO6VS5JWtKo59ySzwCXAF4ELq+oYLP0CAC7oum0BHu7ZbaFrO/WzdiWZTzK/uLi4+solSSsaOtyTPA34JPDmqvr+6br2aasnNFTtraq5qpqbmZkZtgxJ0hCGCvckT2Ep2D9cVZ/qmo8vT7d0yxNd+wKwtWf3i4Cj61OuJGkYw1wtE+Am4FBVvadn035gZ7e+E7itp/013VUzlwHfW56+kSRNxjDPlnkh8Grga0nu6dreBuwBbk1yHfAQ8Mpu2x3AlcBh4BHgdetasSRpoIHhXlVfoP88OsDlffoXcP2IdUmSRuAdqpLUIMNdkhpkuEtSgwx3SWqQ4S5JDTLcJalBhrskNchwl6QGGe6S1CDDXZIaZLhLUoMMd0lqkOEuSQ0y3CWpQYa7JDXIcJekBhnuktQgw12SGmS4S1KDDHdJapDhLkkNMtwlqUGGuyQ1yHCXpAYZ7pLUIMNdkhpkuEtSgwx3SWqQ4S5JDTLcJalBA8M9yc1JTiS5t6ftnUm+leSe7nVlz7a3Jjmc5IEkLxtX4ZKklQ1z5v5B4Io+7e+tqu3d6w6AJBcD1wDP7/b52yRPXq9iJUnDGRjuVfV54DtDft4O4KNV9aOq+iZwGLh0hPokSWswypz7G5Mc7KZtzu3atgAP9/RZ6NqeIMmuJPNJ5hcXF0coQ5J0qrWG+43Ac4DtwDHg3V17+vStfh9QVXuraq6q5mZmZtZYhiSpnzWFe1Udr6rHqurHwAc4OfWyAGzt6XoRcHS0EiVJq7WmcE+yueftK4DlK2n2A9ckeWqSZwPbgC+NVqIkabU2DeqQ5CPAS4DzkywA7wBekmQ7S1MuR4DXA1TVfUluBe4HHgWur6rHxlO6JGklA8O9qq7t03zTafrfANwwSlGSpNF4h6okNchwl6QGGe6S1CDDXZIaZLhLUoMMd0lqkOEuSQ0y3CWpQYa7JDXIcJekBhnuktQgw12SGmS4S1KDDHdJapDhLkkNMtwlqUGGuyQ1yHCXpAYZ7pLUoIHfoaqNZ3b37dMuQdIG55m7JDXIcJekBhnuktQgw12SGmS4S1KDDHdJapDhLkkNMtwlqUGGuyQ1aGC4J7k5yYkk9/a0nZfkziQPdstzu/YkeV+Sw0kOJnnBOIuXJPU3zJn7B4ErTmnbDRyoqm3Age49wMuBbd1rF3Dj+pQpSVqNgeFeVZ8HvnNK8w5gX7e+D7i6p/2WWnIX8Mwkm9erWEnScNY6535hVR0D6JYXdO1bgId7+i10bU+QZFeS+STzi4uLayxDktTPev+Havq0Vb+OVbW3quaqam5mZmady5Cks9taw/348nRLtzzRtS8AW3v6XQQcXXt5kqS1WGu47wd2dus7gdt62l/TXTVzGfC95ekbSdLkDPyyjiQfAV4CnJ9kAXgHsAe4Ncl1wEPAK7vudwBXAoeBR4DXjaFmSdIAA8O9qq5dYdPlffoWcP2oRUmSRuMdqpLUIMNdkhpkuEtSgwx3SWqQ4S5JDTLcJalBAy+FlDQds7tvn8pxj+y5airH1fryzF2SGmS4S1KDDHdJapDhLkkNMtwlqUGGuyQ1yHCXpAYZ7pLUIMNdkhpkuEtSgwx3SWqQ4S5JDTLcJalBhrskNchwl6QGGe6S1CDDXZIaZLhLUoMMd0lqkOEuSQ0y3CWpQYa7JDVo0yg7JzkC/AB4DHi0quaSnAd8DJgFjgC/V1XfHa1MSdJqrMeZ+29U1faqmuve7wYOVNU24ED3XpI0QeOYltkB7OvW9wFXj+EYkqTTGDXcC/hMkruT7OraLqyqYwDd8oJ+OybZlWQ+yfzi4uKIZUiSeo005w68sKqOJrkAuDPJfwy7Y1XtBfYCzM3N1Yh1SJJ6jHTmXlVHu+UJ4NPApcDxJJsBuuWJUYuUJK3OmsM9yU8nefryOvDbwL3AfmBn120ncNuoRUqSVmeUaZkLgU8nWf6cf6iqf07yZeDWJNcBDwGvHL1MSdJqrDncq+obwK/0af9v4PJRipIkjcY7VCWpQYa7JDXIcJekBhnuktQgw12SGmS4S1KDDHdJapDhLkkNMtwlqUGjPhXyrDa7+/ZplyBJfRnukh5nmictR/ZcNbVjt8ZpGUlqkOEuSQ0y3CWpQYa7JDXIcJekBhnuktQgw12SGmS4S1KDDHdJapDhLkkNMtwlqUGGuyQ1yHCXpAYZ7pLUIMNdkhrk89wlbRjTepZ8i8+R98xdkhpkuEtSgwx3SWrQ2Obck1wB/DXwZODvq2rPOI7jl1RLGlWL3xs7ljP3JE8G/gZ4OXAxcG2Si8dxLEnSE41rWuZS4HBVfaOq/hf4KLBjTMeSJJ1iXNMyW4CHe94vAL/W2yHJLmBX9/aHSR4YUy3DOh/49pRr2Cgci5Mci5Mci8dbl/HIn4+0+y+stGFc4Z4+bfW4N1V7gb1jOv6qJZmvqrlp17EROBYnORYnORaPt9HHY1zTMgvA1p73FwFHx3QsSdIpxhXuXwa2JXl2knOAa4D9YzqWJOkUY5mWqapHk7wR+BeWLoW8uaruG8ex1tGGmSLaAByLkxyLkxyLx9vQ45GqGtxLknRG8Q5VSWqQ4S5JDTprwz3JeUnuTPJgtzx3hX7PSvKZJIeS3J9kdrKVjt+wY9H1fUaSbyV5/yRrnJRhxiLJ9iT/nuS+JAeT/P40ah2XJFckeSDJ4SS7+2x/apKPddu/2OK/iWVDjMUfdrlwMMmBJCtedz5pZ224A7uBA1W1DTjQve/nFuBdVfU8lu68PTGh+iZp2LEA+DPg3yZS1XQMMxaPAK+pqucDVwB/leSZE6xxbIZ8dMh1wHer6peA9wKj3YazQQ05Fl8F5qrql4FPAH8x2SpXdjaH+w5gX7e+D7j61A7dH+SmqroToKp+WFWPTK7EiRk4FgBJfhW4EPjMhOqahoFjUVVfr6oHu/WjLP3Cn5lYheM1zKNDesfoE8DlSfrduHimGzgWVfW5nky4i6V7ejaEszncL6yqYwDd8oI+fZ4L/E+STyX5apJ3db/NWzNwLJI8CXg38McTrm3Shvl78RNJLgXOAf5zArVNQr9Hh2xZqU9VPQp8D/jZiVQ3WcOMRa/rgH8aa0Wr0PTX7CX5LPBzfTa9fciP2AS8CLgEeAj4GPBa4Kb1qG+S1mEs3gDcUVUPn+knaeswFsufsxn4ELCzqn68HrVtAAMfHTJknxYM/XMmeRUwB7x4rBWtQtPhXlUvXWlbkuNJNlfVse4fab+59AXgq1X1jW6ffwQu4wwM93UYi18HXpTkDcDTgHOS/LCqTjc/vyGtw1iQ5BnA7cCfVNVdYyp1GoZ5dMhyn4Ukm4CfAb4zmfImaqjHqCR5KUsnBi+uqh9NqLaBzuZpmf3Azm59J3Bbnz5fBs5Nsjyf+pvA/ROobdIGjkVV/UFVPauqZoE/Am45E4N9CAPHonukxqdZGoOPT7C2SRjm0SG9Y/S7wL9Wm3dDDhyLJJcAfwf8TlVtrIstquqsfLE0R3gAeLBbnte1z7H0zVHL/X4LOAh8DfggcM60a5/WWPT0fy3w/mnXPa2xAF4F/B9wT89r+7RrX8cxuBL4Okv/j/D2ru1PWQowgJ8CPg4cBr4E/OK0a57iWHwWON7z92D/tGtefvn4AUlq0Nk8LSNJzTLcJalBhrskNchwl6QGGe6S1CDDXZIaZLhLUoP+H87wcKLY6rHsAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(r_boot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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h4o/ZTMns22zJr19G0P6hfc2JWzcTK7xWWxZmrhHRzwH4HMyt4EPM/BAR/SaAo8x8J4DfAdAH4OP2nnucmV/TcqXriHaOOkDmRa+Pp2uf+N0O1kRRFEXZKLK2879ZaTVCFLQ3cgRmvgvAXUts7xPTL1tF9dYU7RwpiqIoirIiqxk52mxo50hRFEVRlBUJU8mvdalFp2kzo50jRVEURVFWJMyEifblAr9uVrRzpCiKoijKilBLX34dOVoziGgfgA8D2Akggomm+QdENALgowAOADgG4HXMvHEuXRsMhaYnHgyMovylD8f27Ev/3ZptY+b2XwUA9O/fEduqC8aLpDLvvZxyQ9abRaSCyAyYEP0924dw5rd/HgCw4//9wwuqx7s//XCTLS/+ifTlTHMMA8If/NPTsf0dL7z0grbX5JECxBcx1Xz4jEyYs7P8Be5Gid29ICM9m6rmmMnw/8HCFIBG75wwY9abDtOxbSAhXYGrJ5d8CpD67CQAILLfAFC36+aq9ySrzfn0Ho70sEmfQbnepnmU9t5QLlVHmMs0lavb9B1hVXgH1Vun3k4P9DaVC9N+2eyw8Uzr3TMW2zIHjgAAUjv2xzaXAqTe79vqNJv6nV3w53Nxypy/2bK3zdvpsqhnn/Wsa/Q0M9OR8DxKWw+pQdcGRXmXUqQnLbwZ7Trk2wTnyVSsNXs59UCkV7HpNlI1fx4zNrVEZNPGAMCNe414d7Lgyz3a7+e3hfDCapi2yLQdlE6jevIpP/O5x4094z2sgkHjWUhiXc47sj7t0xM5b7VIerUl4Npe0DvgbaM7zbdIH4K8mR/1eEFzlDfTldAfk3rk0nf4E+My+gQV76nprr/IerrJVC4V67EnvQ+dw1lFtC13ns8t+PNzfNZco6fn/X3gxJTxyJtaKOPj3zwR2//yjTdisxGmW40cbb3OUSfHwmoA/hMzXwngBQDebpPQvQvA3cx8GMDd9reiKIqyjmRe+LpOV0HpcsJMkPjZip2jjo0cMfM4gHE7PU9Ej8DkXrkFwEtssTsA3APgnR2ooqIoiqIollaaI9qCmqOu2CMiOgDgegBfB7DDdpxcB2p7i2VuI6KjRHT03LlzSUUURVEURVkjKKDkz9YbOOp854iI+gB8AsB/ZOZmAUULmPl2Zr6RmW8cGxtbeQFFURRFUS6YMBMmfrbiyFFHvdWIKA3TMforZv47az5DRLuYeZyIdgHoaH6VjSIQkVMplUHtW58FAKSuf+UFra/0+T+Pp7M7jcBRSjnZppYoT0z5ZWaMULQ650XartG71BEXghNXZ0SMDJcaoVhpTtfghNmrhSo2NQF7ESXVrXhSpBTI9Zojkwn9kHEgkkWX6ox0wTfDoGRTesx7sXTNCqdZpOfgBDFq0nF0Iu6k1B6lSZ8+pGbTfEihs0sDk+rxotlUj09XEm+3xwhagx4vfHVC26DktxvaOjihrEsn0rCtnG9JrlxU9cJot49OGA4AqV0HzbZ2H4pt1W2XAQCmhYB5omjWc/acPHamDlJo7dKvVIXNzc8mpAVBgk0KrN10r31tIFO5uEUb1msnayLFhKuJTAtid6dB0B/L3+tCDG1T0eSz/tztGzTn58b9/t6wy6af2d6XxR33P2fm7/apcK7e5c/v+cCLcyjd9cdATYr9TduT5zZlU4QEeSH2t+LshrZv05LI9h63NyG+dk4Dobz/uflZv43IpuJxImwAKAWmHRbKzW1ACuoz9oSngh5fZftdLZt6SvG1S/chbS5ViEwpMls25++MEGQ7IfazE/4eOrVgnAfmSwkOIpuM1q78W2/oqJPeagTgzwE8wsy/J2bdCeBWAB+w35/qQPU2jPxrfxEAUL1v7fKWKWvLUF8Pqs0poBSl6wmPvKitcqW7/nida6JsBVq68msQyDXlhQB+GsB3iejb1varMJ2ijxHRWwEcB/ATHaqfoiiKoiiWlq782jlaO5j5XgCtjujNG1kXRVEURVGWJ8y0SB+ir9UURVEURbkY0fQhyoYTjuz0P+j8Glr01Dfiaa4a8V9qbI8oYEXPMqqtFQFT9rjfbHjaFK944aATYzoxbnaoP464DQBDt/3XxDr92TeejadzKbPdnYNeNDxbNGLGuhCvOiF2rxi6He3J4JMPjiO3JOHhq47sQLvISNlsJ0mIiIJFE4A9CEXUaitMpVoZtRkgKHuxKUpGuF6f9iLtaH7GrF9EyHaid0gRtou+K4SvcfnIC0trNoK5E2FLG4uI1pkBIzLNjXpRroswTEI068SwlPLL0jbR5lwd6vWG/ciVvLA0FoxHXkRPKRP9m4SQOBw23qM8sje2VYYvAQCcWfAi5Plps2+LVb++WStarYp24f6UOhG2nF9LiNpdqPv1OYHuYNafWxcF20XPBoC8bV/5lI2gniDoTSdclvIsuiDLNaHkTYqaHeSMqDhMNwvnpeDXPW8ODPtyewbMedzW48/jJYPmHKRrRZTnjINFMTDlThV825fRna/b44XNK5EeEALqtI32LtqRFGLH5ex8yoro2gMmurZrHwAQ9I8AAKKM38coY9ot26jh0lYSx8c5dUgBvNvFKmRbaR7VcG+BUgmvg9w9qSLWW7bnT7ZV2R4dLuL/aF9z1Pl8ZvM/blsmmN16A0faOVK2LuGB6wA0dh4VRWkm98M/23Le4sd/ewNronQzLUeOUjpypCiKoijKRUiQTu4yrCbUS7einSNFURRFUVYkbPFqUINAKoqiKIpyUdKqE9RSi7SJ0c5RF1Mb2g1MnQIAUN0IK6WQOI4ALcSM7KLKDoiUdFbgzULoHVSN0DZtBbUAwFUjL63MiUjNVpDtIjBnt7eXqkUKah0y6vCwFZSmhQuoE83KyMVOPJtexbAty+PjjkHDsTDHkWsimq+Lqs3NoksnQI0F1/DRsN0xBIDIRb4WAvd6qVmIHUchT7jxpHu9oJXrLkK1F3s6IXY4OBrbQivGd2JXAOC0iSbMoRCK2mjhnOAAELjo3lZ8DgDurFDaR8h2x7ae99Gwqz1muiayE5WteHUg68+taw/ZlG8D23pMe5wu+mPmIhAntSmhz43bUl9CLJYgIflTUj4otz5RpVjwK0XVtYS6OFOdmwXC8yKKszvNsp07IfZi1QvWnRB8lxD3ukjboyLcfWrGOFU40TIALITZpnrmraJ8Wz6FyXlz/ffaHV0Q+zba7yNJA0D6wJF42gn1WdSTrdhfOiM40X7Q0x+bgl4zTYP+3lTvtYLsvHcoqARmf6U4vV4xx08K5d20lLtE8bH35dxq5Pr8vYiXlPblayJ4v9tsvxg5cedP3pucbXuvP0FFK+KWYu7NSpBOJ9r1tZqybgSHbmo22o6RoiiKonSasJXmKEwWam9mtHOkKIqiKMqKtHytljQMu8nRzpGiKIqiKCvS0ltNBdmKoiiKolyMBBeRt9rW2yNFURRFUdacMJ1K/ARtCrKJ6JVE9BgRPUlE70qY/6+J6JtEVCOiH1/zHTgPdOSom0lKIyJssQeSSEPAGeNp0uCVZNOGSK8krhiPq1CkWkiVjM0H7Uec7sJ5mqQvvcavY3AnauNPmGV3HW6opksPAgAZ606SzXtPh77Y08O/q3YeHkN53ywzCQkNyzXGA6dmUa03egzdsC85JUJteH88TbWyNVaabQIObV2d90uq1lRGptFw65MeO85LrbrgPQwr1ktI5iLK9Bsvo7TwEqIh4wEUifQd2SFzDlxKF8B7qaX2HPLLDmwz5bLee8l53VFdeNNlzfpYphSxXpHsnG2EF1HsuRcKD0fXptLeq86RrvvjmnHbFd5//TZdSy3vW9yU9VIbFm2g10blnVz0bWq6ZKZl+3GeSjIljUs7E4pyrt3MCI84Vy6d0N5ceZkuwqUlqYqUHK45Spsv5+uUtdsqCu+lvL0enLceAIzY6yUkL3bttbNlSpzIegdWMt4zrLhg5kfCc65iN3eq4I+jOwbjBXOuxueFxxmAd7zwUvBl3lkknDFOIjw1HtvYXgcs2ipg0usE/d6L0bXVumhTbNtNPfTeXXMls75iTR5bsx/yfGfsdEqcs4z9vy+99Nh6pOWFC6JrD+4qbPBJtctKL0rnzybvR27ZkZzwOoyaPe3c9NL71Wak5QhRG678RBQC+CMALwdwAsB9RHQnMz8sih0H8CYAv7zKqq4aHTlSFEVR1pz8a36h01VQ1pggnUr8tPla7SYATzLz08xcAfARALfIAsx8jJkfwJL+aifQzpGiKIqiKCsSZtKJHzsS/goiOio+ty1ZfA+A58TvE9bWlehrNUVRFEVRVmSF3GqfZ+a3LbN40ru3rn3XqJ0jRVEURVFWZDWaI5iRon3i914AXRvpuKOdIyL6EIBXAzjLzNdY2wiAjwI4AOAYgNcx83Sn6rgZqPf5lB6RFW/KVAvMLkS+b8BZm2qAcl7Emdp5AAAQ9AzENspbUW+vETtLcfNc5MWjrgYf+LIRaFdqMl2C2W4oAoUlpQpxQuzetEjj4fZB7G/RinrLQkw+W6rhM4+eAQC86sgOAMCjZ+YatmW2ZwSTubQQWIuULA4OzDJUMwJVqgqxqfXMoKwXwpMVYpOoEy8aW1LKkEiIdiO7DEfiNbtdX23BC2TdjUn+eyOb/kWKYSlt9jsQol1OGcGrTNPg9lGK/OP5rs2IdTgxdbwcgHraiMgD9vsdC9wDIVS1YmF5HtP25ErhrZsSOuJYjCvFxU70PC2E/wtW4CzF1zl7zGQ7c+LnRpF2ZLdlfpdFnar2vEhboWyOS6Hkj8+8nZbOCBWbg0JeD85BIS/cog/v6LP746+pfitEz4u6O+G43B9Xhdmyv006YXXSdosVf66enTTt5sSU+V4U+7N7JI+ffmYK/+kHL4ttV42Y6z8U55aEY0L9xONYLa49lEVKE9cG6uLZXA2sSDsS9zV7vlPi3OadcFvYnPA+6ZHu2gBz86CGXIdrP5RQTsIJARKDWhnlwqypc99g0/xuZYWRo5W4D8BhIjoI4CSA1wP4qTWrXFK9jAh8B0Rfh5mPt7Nsp0eO/jeADwL4sLC9C8DdzPwB6+r3LgDv7EDdOk5meGdb5WqLCysXUhRFWWcyL3p9w+/081/bVCbpMZqRP4Q3ndJdUCqTbA9WTh/CzDUi+jkAn4NJ1fghZn6IiH4TwFFmvpOIvg/AJwEMA/gRIvoNZr76gupK9PMAfg3AGYj/XQCe187yHe0cMfNXiOjAEvMtAF5ip+8AcA8u0s6RoiiKonQNrUaI2kwfwsx3Abhrie19Yvo+mNdta8E7AFzBzJMXsnCnR46S2MHM4wDAzONEtD2pkFXC3wYA+/fvTyqiKIqiKMoaQenkkSOE3diVwHMAZi904a7co3Zg5tsB3A4AN954Y9cq3hVFURRlK+A0jk32NiNkbzBPA7iHiD4NII5Iy8y/187C3dg5OkNEu+yo0S4AZztdoW6lZLVGNfEWv2aFpaW6FGSb76x4LUxBc7RjF2kXPT6qbd1GWS7njO3MghdsnpwzIs7jsyUAUwCAvpxpUlJ87SICj/b4fx3DNvqvFJa66LNZ4RHh9I8LVS8sXbTC28UEWzoMcOfDp802cmYbMlptjxV7D4qDkbNi4bQYGSYr0iYb+ZqqIor2wDbw3AQklLMC99ryegmuN8c2c0JsKb52wkcZNduVkzcitlHNa+dO+mUXrCC730cMD4fNAGwgo3o7MbcQWEd2c5xqjnjtyjkRNiCF/75OZRteu1j2x71oj4vcfSd0lpGnXRThRRE9umAjjReEkHjGRsieKnix+4yNoO3E0oAXRGdSop3Z9igjaTvhct3WSQqZXbRlKWReWDDbrZS9rWRtNdEuA9uAI7GtPhv9PCuigDtBdLiC14+re0/G78+irdesiCBetqJwEZA81t1XRZ2L9vj5uvt5kyPG4eB/CuH4m24yzkaXDXuRNgCMTj22bL0vBNkGZBtx9LtrOC0fzKacFE7n7PXSIyJex04DLnK8PFBumpu3KW3xvaFeFTZ7DQvHjNipQSwbZzAgQl289AkvubZ5m91EC80R2tAcdYDj9pPBEllbO3Rj5+hOALcC+ID9/lRnq6MozaSufQUqX/1Ip6uhKF1BePB712xdl42ZPyv3HVcn5W6j5QhRm5qjjZ6vsrsAACAASURBVISZfwMAiKjf/OTC+Szf0bEwIvobAF8DcAURnSCit8J0il5ORE/A5GD5QCfrqCiKoigKzMhR0qcLR46I6Boi+haABwE8RET3E1Hbnm+d9lZ7Q4tZN29oRRRFURRFWRZKt9Achd3XOYLRJP8SM38ZAIjoJQD+F4AfaGfhbnytpiiKoihKl9EqzlE3jhwB6HUdIwBg5nuIqLfdhbdE54irJdROPeZFbgA4Y6MXB427mBnctpFVW1ecEFu66jntsRS+xpFew+b3wpz2wlvOGKEtC5F2JTDHdKpoBIYTQvQ5XjCixqqI7OwE1jIq9aAVRktbr4v+K0SSLjL2QEYIzG3VpSDTbaMnHcb1cWLddCDEsPY9uIysHHHKzoMoZ9ZXAdBr65OatvkRF4zuoXbWC565tIDqY0fBSeJrIXh27+fTvT6SdmDFrVFFRK920Zkrfn21kjm2tOCjdztBdqa/+fqmjN9u5OogxddOzC28TYJhE0mcc/66oYrdXt3WT7QPJ8SW52KqZLYhxdJTVgw8K6Itu/myrTjBrRQSO9HzvFzWCqxnFitN5YqinBMTR/XlnVfrtv5SfOym67bBRWIf6/b8VKXQe2He2Ba9p3DdCnRD8QBxwfFkkLyZcdMeQhlhPeHh4sTcKeG0EFhBdpCg8aiI+rkI7FII7qgVvfSiXJhqsMl61GtGdP3Is17788VhU+dj2xrb4E9d3/YzZ82Yt8LyKRGR3EUxl8dn36Bpwzt6/f2nz52XshHCB0V/HmPniwRBdoNw24q6I9sWAKBuHSS47J0r2EXPz/hrKeg1uip5vCmbQ/3BuwEA4TVd+vJkE2mOADxNRP8fgL+0v98I4Jl2F94SnSPl4uVlh03ikjvuf26Fku2Ry5ubf32FcoqirC/ft3942flfffqCYvspq2A1EbI7wFsA/AaAv4PJFPOPAN7c7sLaOVIURVEUZUVaaY668bWazcn6C0CcY62XmefaXb4rIzcpiqIoitJlBGHypwtfqxHRXxPRgNUZPQTgMSL6lXaX186RoiiKoigrQql08qcLR44AXGVHil4Lk89tP4Cfbndhfa2mKIqiKMrKhK1eq3XlOEuaiNIwnaMPMnOViNpONbYlOkccZlAa2t+QJqJovU4qIpR/scZAcQ51bjw+37NrcGMqugacsyk7AJ9uQ+KcU1jso0tJID204pQRqWxsq4dmuiJc3RbKZtql75AeSC7Vg/SIydo0DX0i5cD23oyd5yuQTyWk8agbT6lw6kxsS9l67gPwXHqnXXfzv5R8utlWrjXLql26C+nNUqhE2NOfxuDT98LtXe3kUwCA+qwRfS6e9uLPqk3zkR3qi22ZAeOtE2b98QytFxiJdCgwziwNaUSiaq3hW1IXXm1uPTJKrfN+I+EF5rzUopJvK9Q7YOrUP+aL5YzHTJTxnkacNftUCsx+yBQthXnjFTQpvIOcx1lZeHfNW0+yuZIvN11MSPdhbQVRLikVRmnBTEtvsdi7TBzHWqXZC815psnrgaPmdlu3Xnps0z6w8PSLrBdareI9B513V3XRSxiq1iaXDayAdaV/1mG6uVxgPQsDIYINEhJ/LldniVt3JLwsXTk3L90z4OuUMm1LpkN54ozxzJKpVAAA1yfv10bw3TPeW+zklL2HiJvdAetZd3jUp705ZL3udtr0SCj5dSSl+4hzrwicF5r7ljhvNACgYXPNNcQCct5ywnuU09YZpH876hMnjC1vnk2R6JQQt/18X3M4SO4ycMLx6QL+BMAxAN8B8BUiugRA25qjLdE5Ui4ODm4zN5wnz82vUPL8Ge3vQXPXRFGUbuVFl44CAL45fsGJ15XzpWUnqLs0R0QUADjDzHuE7TiAH2x3HV3Z3VMURVEUpcsIw+RPl71WY+YIwM8tsTEzt/0fWEeOFEVRFEVZkVav1VqPKHWULxDRLwP4KGJBA8DMU+0srJ0jRVEURVFWZnN1jt5iv98ubAzg0nYW3hKdo9lyHXc9OY1JkV5gasFMF0rNo2hSrAdsDkH2MxNGZzMgBMxpux8yxITXaPvGygkCPpeWo05e4Llow/HXhVC1ZEXXTqRdFfPSdmPp0DejrBUND+aEzQqxnQgbAPpsqpB81euHgsI5sz9z53zdbRj+oLcf0fxZAKZlPz38PJRrjIfGjb5uhxV9LxXbx/tWdWkFzO+JxQq29bTIEwRg/rHHAQCFkxMAgIVx/2ejbtfVM+qFzPntJppv787R2JYeMAJQKdJOIkrblCYJyRsDIWwPbLmw1wvBg7ypA+V8XcjaApGuwAmyo96R2OYEoE6EDXgh9qxtC0UhtJ4rNYuvXVoQKdSfLRvB77m5cmybtELsc/OlJltZCLyd+FeKr8tFM11pKOfSfYiUGVZcHFX9fcCJlKVYeem8pPlRkiBbpN2oLJh2VysVsBx1IeJejlqzpjcWSa8kyHb7K0XYSfu7dL0AENo0S9n+Yfvt20fapvvJZJvb5YnpRewd7mmyd5r7nzHXqRTbf9OmPzm8w4ukf+BSs5837DHXxb7hS+J5Yd2326VQ3bdB6jX3LhoSjg82hZVzdgC8w4MULZNNPSK9v4psjrNLyQMA01MuPY+v0/xSMfwG0kp4zV2mOQIAZj64muW3ROdIufi4bKw/7hi1w6uvNHnEvvSk73g9b3djpzh17Sv8jy99ZnUVVJQtzn/7N1d1ugoAgHe80A8E3Hn/yWVKKqumlddl0H2dIwAgomsAXAUg/qfIzB9uZ1ntHCmKoiiKsiKbSXNERL8G4CUwnaO7ALwKwL0A2uocdd8eKYqiKIrSfQRB8qcL04cA+HEANwM4zcxvBnAtgOU1DgIdOVIURVEUZWVajhx1ZfqQIjNHRFQjogEAZ9GmGBtos3NERL/FzO9cybaWENErAfwBgBDAnzHzB1qVPTdfxu1febpBxOmi6lbKCYLsVOOA2X951ZVrUue15r7j0/H0aI8V40rxtVVxxhFdAQRO4CdEnEn6vZoVLLpI4mY6airnbFNWDJsUdTot3jf3WxFnThxjN7837W29ZNYXLPp9pJnTAHxUagDgqikXiUjE4eAo6g/ejSMAHh39PgCNEbmb6hcSHjhlAsVt68lgYrE5ejAAnPv9X4ynS5Nme8WzMwCA6kK1qXyqNx9Pu2jZMho2JcT+cGLq9Pbd3uhEwzLSrj1/Qd+QX182Z9frb0RxhF0RadeJtJ3gGgDYRgJuiIZtRaPVwLeVohVEO1G+jDrvxO4l0U6qVqi/KKJSu+jW80KkXbDXobQ5IXZJRMOuWPG1FGm76eqCD/bnxMfLCY9bUV9mWWeTou5Y6C0iS1/Ids+XuC4JQmvZBs73WMhyTlDuInRXhcDci959G8gvc511A4tW5F8seAGzC3Q9dS725sazk2b6+Mw2AMClwrliW4+5lnpE1P1+u9+Z0A88ZFLmekxl/P0vvq9WxL20YmypQERzj8z6ZkR0+PF5c+yfmfYC76fPmnpOLfj9mVlsvhdtFKuNkL3Sc52IsjCvvW4AMAngJ5n52AVW9ygRDQH4XwDuB1AA8I12F273tdrLE2yvancj5wsRhQD+yG7jKgBvIKLuUP8pXcXVuwZw9a6BlQsKXnrZGF562djKBRVFURRPECZ/2nit1uZz/a0Appn5MgC/D+C3LrSqzPw2Zp5h5j+B6cPcal+vtcWynSMi+lki+i6AK4joAfF5BsADF1rpNrgJwJPM/DQzVwB8BMAt67g9RVEURVGWg4LkT3uu/O08128BcIed/lsANxNdmKCJDG8kovfZ0acZIrqp3eVXGjn6awA/AuBO++0+NzDzGy+kwm2yB8Bz4vcJa4shotuI6CgRHa0WZtaxKoqiKIqicJBK/FhvtVe4Z7L93LZk8RWf67KMTfUxC2AUF8b/BPD9AN5gf8/DjFy1xbIvkJl51lbuDQBARNth4gX0EVEfMx+/kBq3QVJPsSG6HzPfDuB2ABjYf6RzaYoVRVEU5SIgajFCZINAfp6Z37bM4is+19ss0y7PZ+bvJaJvAQAzTxNR68i/S2hXkP0jAH4PwG4YxfclAB4BcPX517ctTgDYJ37vBXCqVeFatY6JU3OoCRFcyYpuqyUvcqVWAay6jE981+zqngEf4Ti0I4tZIXQO5syIWRxtFV5wm877AIc160kgtLWx4FaKa622tkGEe8YKHM9agWNDhGwrtM5mmiNkp4UY2dU9JYTbVDZCw6DoRba1aROgMSp64WS8X3NepF07dSye7rnm5qay8XZtFaIWUbOXMvxSL6OrjZttjM6bY1wreKFqmDPXVzi8PbYFNgI11xNEsUuEsvXpsw0RrR3U47VTTlQd9PpIu+g1UYw5LbxRbUReKYiMomYnhEQhpa1XSlwW4ZIR7CDhXpUOm23yGMdibtG2KlbIL22RbWc14THgpqUguzJvoh5LsfByka+lmHo5lo2QLcTX9YTI21IkvRYk3ZvO17YakXh53kWW9utI54zzwMKwF/ZPFlpHj+5W5qaMwDklBNZs2+hnF5rPY7+Ntn/pmI8cf+l2cz2Oiaj67l4snUGcI0qQ8CaoUPHXpYtyPScE2admzbPqxLSPqn52zthm5v1xdxHjO0GrDARRe/2Xdp7rrswJIkoBGATQVi60BKpW58QAQERjAJq9jlrQruvBfwHwAgBfZObriegH4Yeq1oP7ABwmooMATgJ4PYCfWsftKZucG/YZr677n+v+V6w9P/bLKN/zV52uhqJsOb72q81/lg7e9rcdqMnWJGrRB2rz/2c7z/U7AdwK4GswcYq+xEn5r9rjfwD4JIAdRPR+u773trtwu52jKjNPElFARAEzf5mILlhFvhLMXCOinwPwORiXvw8x80PrtT1FURRFUZan3qJ31E73pdVznYh+E8BRZr4TwJ8D+EsiehJmxOj1F1pXZv4rIrofJhAkALyWmR9pd/l2O0czRNQH4CsA/oqIzgJY17E9Zr4LJuS3oiiKoigdpt6iE9Tuu6qk5zozv09MlwD8xAVWL4kemI4YA8ivULaBduMc3QKgCOAXAXwWwFMwXmuKoiiKolwEMHPip933ahsJEb0PJizACIBtAP6CiNb2tRozS4XsHS0LKoqiKIqyJVntyNEG8wYA19vRKBDRBwB8E0ZDvSLLdo6IaB7JbnQEgJn5/EITrxMcAdVSHYvCk8J5uFQWZ0U5652T8aNrYSaPPW+4HQBw8m+WhmXYOD74tWfi6e29xhtJenzlU8b7ISyJNBqFCTMhvNVgHSzqwlvNvSaWXmhuWjZ254k2JTyFjs8az4lJ69URCo+zobwJs98n/jU4DzHpAZW1dc8ILyeqmjpzVYT5t55ekUgfEu+DSK1Rnp43tmoNCyLlx9gv/n7DMu74lZakRbn/uRlkUr4ug1lT2e2Xv8jvx+4jZj+qZv8zwhss0fPL5igIaqXmea3yES1DOGwieLNM92FTgHDKe6uxTTNCVbHdeqWhTgAQ2PlcF945JXNtRDnfVgZsSpFM3qYvIekB1bwfZXtsZaqFvpwpVxCpQmaLzd47dbtsJBphnLKi4j123LT0xnKeY9JrzHmYSZvz5GpIuZKQ1mWpx5csH6Zae/8mebwleY0FYh1h1tx/5H0osOlfgoRtUSi8rBK8IZO2W7fXS628/HFcikzR4u6d88J76jtHT+LaG5eGptn8TJycj6eLA+b6WhTt99y8OZ47B/05cx5s2xscT5uvEXdfld5q0/YeOyW85VxaEHmP7cmYcz8rvN+ihDRPG0UrzVEroXaHOQYTesjdHLMwb73aYqU4R/3LzVeUbsN5rQHAQ+Nzy5TsLNmX/D/Lzo8e/6cNqominB+feMvzO12F8+KZ2398xTLX/PI/bEBNNj+tRo668K0aAJQBPEREX4AZ5Hk5gHuJ6H8AADP/wnILd3cWQUVRFEVRuoJWMeP4guM0riuftB/HPeezsHaOFEVRFEVZkZaaoy7sGzHzsvpoIvoEM/9Yq/naOVIURVEUZUVaRcjuwr5RO1y63Mwt0TliMOr1RpGaEzZK0aMLkV8VosZuSSki0yo43XJOpArpSduw9NNerBzNGkE2SwFq74iZF6ZjW9GGqq+IY1R2gmxx2OatYHBcCNufnTSh98/a8PWZ0NepMmTSm+SEbVuP367DXU9SzBfa80IyFYYTigrBbHXGRLxmUdEwY7aRHfaSuPSuAyh/6cNIHb4+th0B8GjqEgzm/DmuJPz1qdl6zYj0M/keI4hOyJTh6yGEk07wLEXQSRBHqNjzlhnctmxZAIiEsJ7tOeVMjy+QlE7CisgDIWp26UWCsnc8ZTs/LIjo/L1Gs5Xvs/svtu/Sv7SbI1ue70XbBhdFqhCXIqRa9ueb3DbEfqVsGotAiq9TZroubVakzZFPuxMLsoWoOUn0vJxIOSk9RyyCTkoXI5e125XbzPSYY+qE2QCQzpk6h+JacukugtTyEVecQFfeA73Y3duqJXMtS9G1uyeWC9NN++OmK4u+zeT7+3HFz/89AOCxP3ztsvXarCzMmXudfIWUtcLoS0a9+rrfpg3pz/i2lfTaKcnm0ovkxbL91pFBplly11A+551kFuc6l8Kl3uL2FnWpu9oKLNun2xKdI0VpxdW7BvDkufmVC3YZweUvBADUzzyzQklFUVbLg7/76nhaxdmt6VLh9bqgnSNFURRFUVakZeLZzdlrWnYMvN0I2YqiKIqiXMRU65z46TZBNhGFRPR/Vij2zuVm6siRoiiKoigr0tKVv8tGjpi5TkRjRJRh5kqLMp9fbh1bonPEEaNarqFWLMS2IG0EkOlwsKm8FHE6sWenkYJspxmWQ5iJTc8Kl0kKTK0gmIR41Gk8g8iPIjqhcUUIiAtWLHt2wQv+TtjouOMzVrwbNI9EDvf47c/aqLIyunfNVmWh6rfVmzZi6pGdV8a2lIskHfjEyUHeRoUWEbKdCDkc3u6X3bEPAFBPe7FyeWA3sFhEXghaQzJ1kMfTCSDlMKrbTSecDOv+mJCLSB6J3MtOkRiKS8pF1ZbRte001UqoTJ2K7ZmR3ahMnPDbrxgRLAHgsFFATCLKNZMVH0shuJsWkdN5weiu6oUZb7MCZinqTm2zkdCtGDcjLp9RG0k7J6KLD1ux+3De7/egFZb2CbHpQK5ZqO8iaEcJIvmUiLhdq5o2UBaR2921LkXniA+Fb/tOCC0F0VKcvZTzddBojKSdsjZxndmLT+5Pxh6rXK8Qadso7bm8P07bbaTmwbwv5yIm18RfdXfvkA4Xsa3mj8W8Pd4zs/5actGv56fMdykhOn0onFoo4frfarh9lOJ4J5Ye6fPnYiBrbDI6vJuWUfnL9rykZeTruJw/32M2M8Ji1Z+zU/a+O7vor/lzHeyIVFsor1u9buswxwD8ExHdCSD2KmDm32tn4S3ROVKUrUx6x0EAaOg8KYqibDTVFoGOuu21muWU/QQAzjvbh3aOFEVRFEVZkWqLXlC3jRwRUQigj5l/5ULXoZ0jRVEURVFWZLMknrWao+9dzTq0c6QoiqIoyoq0GjnqUlf+b1u90cfRqDn6u3YW7kjniIh+AsCvA7gSwE3MfFTMezeAtwKoA/gFZv5cO+us12ooi0i/aSu0Tvd6RambltLQnsEBAEC+L4Pr3/MZAMC33v+q892lNcUJoqWAL2tFsPtGDsa2dMYIVUkKb1NG1EdCoJuzAtRQhDZOBaYxy4jRsyUjeD094wWbJ6ZMVN2CiMqatuLRqR5jmxARtV1U72khnnWbKNeaowkfGPYC6sMjlwMABm88EtvyMOsJiz6qL1vRMwvxdcXud01co8Va8wXr6iej0GasOj0HL7CmktlesDjtbTOnzTbOnjTbFyLxYHDUrHd0Z2yLeky0aU6JiM1CkO3LDaMyfbqxokLEXRt/wphchGxZjM35ISFMpqo5HyzEky6KeizCBsAle78QYuXqiafMOlLHY1t6vzkvUZ+J6D0Q+NsGW7HuSM7v454+c1729Pvo59NWDHxgyIt7n9tnrsfHz3hHimcnTZ3OTPv9KS2YNlASotRy0dS5WvbnrFoyx7ReFiLtBJw4O531+x04UX6qOUK1gxMeDGFD+WbxtVufE1wDQK8VYm8f8MdsxNr2jvjjs9vO39Xnj6MTu0ucDls+oJxwVmpEnEh4UhzH41bw++i4C5R6EM+eNefDRWIul/y1TPYeMritBy/5/X+M7ff84oub6rXZOPKOTwEA0lZonRbnzEXGvnK7l65cZs9VNiGMvtBjY8EKrJP0OlLg7M5PQUSRd6ueLPhzdiLbuTGNaosQ2a1GlDrMCIBJAC8VNgbQvZ0jAA8C+FEAfyqNRHQVgNcDuBrAbgBfJKLLmXn5GP1rzPXv+cyGd5De9YOH4+kPfq17oyLLG8bFhOsYXWy4jtHFxtKO0cWC6xhdbLiOkbI8LV35uzC7GjO/eTXLdyQIJDM/wsyPJcy6BcBHmLnMzM8AeBLATRtbO0VRFEVRllKNOPHTjQNHRLSXiD5JRGeJ6AwRfYKI9ra7fLdFyN4D4Dnx+4S1KYqiKIrSQVpFyO7S12p/AeBOmLdQewD8X2tri3V7rUZEXwSwM2HWe5i51RhmUoSxxKNORLcBuA0Awt6Vs5sriqIoinLhtAoC2aWC7DFmlp2h/01E/7Hdhdetc8TML7uAxU4A2Cd+74UJ4pS0/tsB3A4A2bFDXXlmFEVRFGWrELUYIerOvhEmiOiNAP7G/n4DjEC7LbrNlf9OAH9NRL8HMxR2GMA32lkwTKUa0oc4ctaLCAByvcb7Iy3U/rle4wHUTQLMh07OAQBO5r3XzdkF461w1ZhPd3J41OzbUK9flurWs0R6qwXOQ6v5Lar8JzBuvc6cxxAALNrtJl0ULkWBSwMBAGftOmSakSnrafHEmfnYduqc2UYgyl2xz3h3PW+f9zDc02/O2bYesZNx3b0XTTowmn0Zyj9vvYd6036/89brT9pSJZNSI1jw140TYFdPHQMAFJ96Ip63cNqUq5W8B0l+1Hg99u3b0VDH7Iv+bcPvwHrdUcUfY7JpSCLhfYd6czogV46kt5jzfhPlXTkWaXLiNBcitQbX7PGr+eMYLZi2V1s0nl/l57xzQHp42CxX9p52ofXOC8f82+9U1njx7M0PxLZdA+a47B/wtkPW2+fGPf58j8+b9nNsxrf9J6w326Pjc7Ft2qa7qAivSOfBVlr0XmDOg02SythrXqQ3ySzxUJL3g+VSZqREO3JtWd5f8nYbo8LjbNegqd/OIV/PMZuCZ1Sk4tlny431+PUNhOb8UdlfS2jxb95U0K/PpaGpht7jar5ilp06YtY7LjxPn7Keqvc/6z02XRqhS8V96Np9g/jQUePd+JYb97euSxdy7bvuAtB4zpxnYVakchnsMdM9aZmKyJzvjEgz4pqKTJXkUhDl0r4d5ewy0jV+znpeloWrm2tTPbKtJngsbhSbJQik5S0APgjg92HeQP0zgLZF2p1y5f+3AP4QwBiATxPRt5n5h5j5ISL6GICHAdQAvH2jPdUUZS1J7b264Xf92Lc7VBNFUZTVUWnlyr/KzhERjQD4KIADMDnRXsfM0wnlPgvgBQDuZeZXr7Da/wzgVrceu43fhek0rUinvNU+ycx7mTnLzDuY+YfEvPcz8yFmvoKZP9OJ+imKoiiK0kilFiV+1kCQ/S4AdzPzYQB3299J/A6An25znc+THSxmngJwfbsV6jZvNUVRFEVRupB6xImfNXBWuwXAHXb6DgCvTSrEzHcDmE+al0BARMPuhx05avttWbdpjhRFURRF6UIqtRav1Uz071cQ0XuF+XbrONUOO5h5HACYeZyItq+qoob/DuCfiehvYTRHrwPw/nYX3hKdIyJKCPVvpErS3mcFkH1CCNkjRHdO5Nlpnp0wYt2zQoQ3Y4WnJZGC45vjs/jJa3ZgvuaFfr1ps2+hSE/hRNqBSGPhUnnMCjH17KIpNy7Sh1SKVixs3ynnevzxytjUCPNiHU6AmhFpFRZtOPyzYr1njxthcnHe/wk4fcwIo78z5sXX/Va0Oyi22xNvQ4qvzfSuoeaUDJeKFCWXj5r1DWSEiLJk6iCjYLsUIbVz5rs46dOXlGd8ncOcEdounp2Jv7ffcAVawZNmffVF8edHCOXp0A3m24qknbgaANimD4lE2guXLkamG4mykTX5y5sCI2YOIu+gEK9DCrJnTAqeypxpg1J0Hh0/Y76rvk5B+pjZHylO326E9elenwoj3W/OQc/ortjWPzwGAAhHfMSPq62tvt/fG08tmjo/NrEY25xg+wmReuTpc2Z6Zt6LimtWcMxCE+FSYIhDFqcBcfcL6VDg2rK0uelUgq0v59vqqG2Dsv1ut2lVtgnx9TY7f0gsO2iFwf0pX/dw1rRRmvVttT45br6nz3nbrHEaYKERCbNmu6lhf2xH+8252mEF9Vf0+fbxr/bsBgDcfOlIbDs20yxw39GXabJtFnoGsk22bN5cN3tH/H1jmxXU58R9LYJLweSPses7uJQhADBh76vy1VNPggPQtE3TcnLOH+PTs2Z6ckGk/emg+Lll58js2+eZ+W2tll0uvM+aVG4JzPxhIjoKkz6EAPwoMz/c7vJbonO0VnztV2/udBXOm52DvTg3t7hyQWVdOPBbZiT4mV/2r8F73/DeVsVXJL3zEAAVbiuK0n200ha102FbLryPjWC9y44a7QJw9oIr2bjNh2EcvM4b1RwpiqIoirIi5VqU+KmtXnR0J4Bb7fStADqe7E47R4qiKIqirMg6eqt9AMDLiegJAC+3v0FENxLRn7lCRPRVAB8HcDMRnSCiH0pc2xqgr9UURVEURVmR9YpzxMyTAJp0Lcx8FMC/F79ftKoNnQdbonPEzKiUaw02FxE41+vFgntt5OVrRETekS4RE/7Yh74eTzthZ7HiRX3PTizgkm3NUaIBYLzgBbWjVkw4kPVCQxfJtSjEdMWaXNuEAwAAHZ1JREFUaczzYhtOkM3iX0B9ycVQE0JDJ7Qe6/cDkH02eqsUZLv9yOdkZHIbzXjBCxMLE+Y188KUt2WtYDQnxKvpnJnfEOncClqfEOd715ARBM/u8sfHHdu8iEY9kjblQhlNuGKEkE7QSiIKbs/OUSyebjsKfSJOMLsSnPbnka2gnjNe6MwZ0ybkrYlqxkZlH4U7sOrjIPDH1u0jqv74pAbMtZG1+10T++mE2FKQXl2wkbTnvAiaHznZtB+BFdEHoRcwu8jTKeEUkR3qt98+AvPOwybq8v4jN/i6HLkOADB5ZCy2nZo3+/HUtNfgnV0w9ZJR3F17TPq360XVzVGu00I47wS1ZeEg4US4Urjdn3HXo1/fiN1fKcjusw4CfcJRoDc09QvnvfwisNPVUz5yeeXE0wCAuWfGY5trnwtn/bkqzxlRb3bAbzdl9zM3bNpMfiz2fMbAQSOe33/4e2Lbwb2XAwBqgyIfuLs2OEK5YB0XRCT27IAXdHcb33/1jiZbvz0ml4r77eFRc78YlQ4p9jzXRTOaK5v9nlj0AupJOz1V8teZa3vungsAJ6aNk8HjJ73zR3HeLCujtJdFVPiNprXmaIMrsgFsic7RxcIf//i1na6CYjn0Bx9p+H3wd/+yreVSN/wbAED1H/5ozeukKIqynlRqyQkrasulsNmkaOdIURRFUZQVWcGVf0uhnSNFURRFUVakrJ0jRVEURVEUT6tO0BbsG22NzlGtvIipJ7+J8vxUbOsZ3d1U7pJRI7C7Yd9QbDskoqB2gl/61IMAgCEhznQNUAo7k7jtYyZQ4A2XeBGlEw7uEZFfc1YwGQnVnBOPSkGpE1GnhJg6a8WjLqowR0DKikbdEOsTZ+bjaLJO7Fqs1GMhq9uPFxwaxbOTVix7wHwNjfnjP2vnzQgRackKlysL/viEWS9IdqQypp69Az5C9qKNKiuP455Bs+y+QX98hnutQD/XH9uCQRMpmCZNJOL+/TswbyNEbyQsopq7CNkIhXDcRsFmIbQmO1/G6YjYnKuA/LFIjdl2MT8jCprzl8mZayWza288vzJtvvv374gjaC+eM7b8dmBx3EbXFtF8nQh48VkjMq1X/D9PJ86uCrF0ZNtPIKLDh+mjZhvDd8W2wUsGAADbr78stl1z400AgOsOXhPbagf2mTqlfJsp2DosVH1dKlZVKy8558iQTVGTrbGc+ZbCXFpy6eaEEN1F1U5H/jhRxUYwn/Ni3GDBHM/amediW/HEk2YfnvNt0bXLwrhfduGMuZYKZ70of8ZGt65Ih4uEh9qOfhvV+xLnuPIl9O82AvnBA17APHLNQQBA9vLr/H7sPgwAiPJ2WQpQmfbRvDPDSQGSO8dtL9gfT89bMbX0vHJCeimUz4TN92XXpsp1mw1AXAPPTJpzEN/7AIzbCO8yK0PBnp+5CXEezx0HAHA9Weuz0ehrNUVpQSrTHBprb0IHM59pDo8vbw6bkV3vXjsRdf7Vb192fnjAPHBq40+s2TYvhIaOk8V1jCSuYyRxHaPNSLi0d9PS1rxsQrFNg+sYSVzHSOI6RhLXMdqMuI6RRHoYOpbrGF0M1Fp0jiLtHCmKoiiKcjHSqhPUyXxv64V2jhRFURRFWZGoRRBI1pEjRVEURVEuRuq1FiNHW/DNonaOFEVRFEVZkaUZExyqOVojiOh3APwIgAqApwC8mZln7Lx3A3grgDqAX2Dmz620Pq5VURQeEQBQOHMMADD5nA9zf/rINgA+fD8A7O03033RIiqzE7E9M7jtvPerXd796Yfjaafyl+k2Mta7bEiEqk/iseeMWLYgwtJPW0+8wyL0/bDdX5n+YNamWylUmoWIowkpVZK8EZzngvRgcOWGxDF203uHvceQu5ikt8xEwaR6eEiEzz8+XjD1FWLugvX0KE76NBWR9bIqz48Im0ktMd7vPdPO2XQS00XvIbWjx3iE9QpvtW6E6ja9S114OVlvNYpE+hybKoSFVxuypj1E5NsA2XQpQejPVdDvPTkBkWIEQLpohNj5Be9N2HfOnIPCs/5czDtPqhPTsa1mj3c9U2+ysWgEVSuMLYq0CkU7v3jSbxcPnjPfn34qNg2mvwAA2H2JTw+043tMG+jdORrbeveYa3twl/e8CkdNqgxKm2PBIqVKVDDXGRe9ED0Sx2UpQcZ7GLr1QXgTOo/Aetmvo7Zo2nR1wXsvVeZNmy/PFGJbadJcG6VpX25xomhtpSbbdMW3i1nrnTclrvk5e+26VBjnhDB5Z8G0s5GnvSi/9wlzTqcePxXbtl1jvOm2vfAFsS19pfEclN6Wdq3oBqpnTPqVg9arrj7gnUqcV6/0cg3qrj34tlohc+3Nl/39b9Z6XjoPNcDfz46f8u13Oc+0wuljvi617nJqaPn6TDVHa8YXALybmWtE9FsA3g3gnUR0FYDXA7gawG4AXySiy5m5O/wYlYuGzPf/WMN3p0jt8h5AnfZcUxTl4qblyNEW7Bw1+2VvAMz8eWZ2f2n+BcBeO30LgI8wc5mZnwHwJICbOlFHRVEURVE8US1K/Kgge314C4CP2uk9MJ0lxwlra4KIbgNwGwAgnZytXlEURVGUtaHVyJF2js4DIvoikl8wv4eZP2XLvAdADcBfucUSyicedWa+HcDtABD0bNt6Z0ZRFEVRuohWXmlb8K3a+nWOmPlly80nolsBvBrAzewjSJ0AsE8U2wvg1NJlz4fpZx+Mp4+fOgAAmCp6sWUsuiu3FliuNWfny/G0E1P35bwodrsVEI+JFCBJ1KzAcl6kXzg7Z9YtBd5OfC0j/FbtP4CS+Cfglhnp9dt1x2fRijil+NoJxkd7vfD3MisE3ylE0E4InhbRZZ0tFC92q1Z4e9UOL4x2Yfi/e8ILF7/ztEkpckoIJufPPGvWsejLFQsmxcS8ON4nbLj+h4Vg/OFzBfzokfUT4K8ZVnRNVb8/sfhaCl/tYeGUPwdumtJeFE+VheZl7d0vLi/uhlQz200X/TEOrYB7oNefs+ywmU73eJF2btgIectzvu5uWgqJUwVzS8qINt1rhdsTZW87befLVBizVSsqftxH684/ZbYrAxvvsNdadjDB8cBGOy6K9A9OyHxSiPidgFmmmliw11KvaNRjWSPEHkx7QXZv3uxjKu9vvxQ0Kxw4ihrqBHgRezUSqU/sMZDHwk0XavL4mGt4TlzDRVvnOjfvj5s3JbY/Zo97VRwfVz+5D9tS5hiHo0v+H+/qjijaYcEI+oOKEbuH0nnBOS1Ix4e6dR5I+XLZXiPy78/6NxfpsDG1EgCcPGOus4mTc7GtcNZcG9KRaHFyVY+6DaF+EUXI7ojmiIheCeCdAF7DzDKnxJ0AXk9EWSI6COAwgG+0s876kW8lTitKOwz19SC981D8URRF6Tbcs61Tz7h6PUr8bMUI2R3pHAH4IIB+AF8gom8T0Z8AADM/BOBjAB4G8FkAb2/XUy068u3EaUVRFEXZCrhnW6eecRxx8mcLdo46Ishm5suWmfd+AO8/r/UNmdcs1df+RWxz0/zU85F5+vsvpJqKoiiK0nHqR74Vd4jcs6362r8AzuCGDa1Hi9dqW1GQ3amRozWFZsy73/Tfvxnpv39zw7R2jBRFUZTNTPjo9Q3Ptvh7HPdvZD2iepT42Yqdo25w5V9XqgtePDo1biKUPimil96w24hHc/lBbBTHzvqIt841cj4vxJ4pJ1Zudt578X+/x5fLmdMnI2n3ZIzwszfjT60TYleF+Hqh2iyw7rPrc98GIzactRGLZaTsQbvdS0d8dNnLrSB7MCsEqGmzP5mweX/k+qzuFTv6/P646LMHhryQ+NLtZhv/V4hcT1ghZHnBH9vQ2gJxHN32Jhe6K/LshUIJEXSdwFoebXbC7UCc24w5jpxpDoXhomtHYi1hZNpAJASoYdoIt9NZIeq20aDlFZUbNeL4etW389KkEagWz/oIzEUrzq4JQbYTIWdFlPT8pBHWO7E04KOt96V8nTMJ15BzQliY9FGm3bKFWnMU6VMJ4u/lOAe/7DER6XsjSbjUYqQ4vFh3380R64HWCbPyQkSfmzDnJY6MDqDnMZMFILutMXNB6tpXLFftNaN62kdOd+Lr2vix5oKp5iwE7JxzxLXlxPFB3rf91K4DAIDh7ZfHtr3WiWaPyAaQyphrTyZtrdjnUmXBi7Q3A/VaLdEeRa3bymZlS4wcAQAmdjRNqzBb2Uqk9lyJ1J4rkd5xMP4o3cHRl8w0TZ+vTc5TlETxtXvOyefdBsJRPfGzFX35t07naNuZpmkVZiuKshHc/5LZpunztcl5ipIovnbPOfm820CiaiXxw/XVZfgiohEi+gIRPWG/hxPKXEdEXyOih4joASL6yVVtdAW2xGu15QTZ7jt49DoAr9nwuimKsnU5+pKZuFPzp7/+bGx30+drc9833DOIG+9pTAKsXBy0FF9bOinIbpUIl6NVpz99F4C7mfkDRPQu+/udS8osAvh3zPwEEe0GcD8Rfc4lrV9rtsTIUStBtrSFj17fsfopirI1ufGeIfyHX78EAPAffv2Shunztcl52jG6eGklvu4KQXatkvhZg87RLQDusNN3AHjt0gLM/DgzP2GnTwE4C2BstRtuxZboHCmKoiiKsr600hyxiaT/CiI6Kj63nceqdzDzOADY7+3LFSaimwBkADy1XLnVsCVeqwHutVnjtLQBwOwpM2T95Uf8cb9irM98b+tpKHvFOuSyfdkH7wUAVEQahIr1xCGR2mN20QxdynQfdWb87N9+B1fs8/8o+7Lm9G0XaUZ2DRivoeF8sxdGodzsaZBLec+VfuvplhfeLM5jrj7MtrzvT++yKUK2iTQIYxnzDyIo+Hfiwax57UAiHD/cPw2R4qLeY14zD/T4180jOeP1Mdrj67Rv0Ozj7gHvIfXJITP92OMTsc0d0wGRysR58yV5Am5KXHoPmebDphlBzXsUufQHECkenFebTDPiUie4rBO1Bi8Uc+xy+eGm8oHwgkvbFAuU8xdRpmBHvsWwfHXapPYobp+ObQvj5hV5Zd57pkXWcyw37M93z6jZtx3Cq42tNxCFzf/5AuG+FVmXLBbeQ+y8tawX56DwZHMeb6fEtgpL4r3ccM9g0/T52uS81VJfRh8rPfGal/MLhtR8HJO84AJ7vGX6kMq88QiOlmhRGu+ya0/1638PAOCKb/ul08cBAMUz52Kb8z5L5UzbD9KppnnVBd8Gooo594HwAu459QwAIHPZZGy79ND3AQDql4zEtpPTZj13i/Qz9ZoJ9Uehv6/NnXi8YV+SnmOtnm0bRX3512qfZ+a3tVp2uXyr51MHItoF4C8B3MrcKtvb6tGRI0VRlFWy1q/BLtTjbem0oqwlLQXZbbxWY+aXMfM1CZ9PAThjOz2u83M2aR1ENADg0wDey8z/soa71sSW6RwlpQ9RbzVFUTaatfBWWwubsrlJeo51+tm2wmu11XAngFvt9K0APrW0ABFlAHwSwIeZ+eOr3eBKbInXam17q1Wu3fjKKYpyUZDkuXah3mprZVOvt83HReqt9gEAHyOitwI4DuAnAICIbgTwM8z87wG8DsC/BjBKRG+yy72Jmdelp7glRo7UW01RlE6z1HPNfV+It9pa2NTrbXPS3d5q1cQPrzJCNjNPMvPNzHzYfk9Z+1HbMQIz/x9mTjPzdeKzbkNoW2LkqF3mThlh+/EnD8W2z9h0F9MHvYBuOJ/GYzYk/muuStKPXRiHd5pUJeMzXuhXsGlD9ooUHNdfYm5oYz2Z2JayosditbmHLsXX23vNMumgud+7mPPLLtr1REKAmbbb6En7Zd16eqxIW+i3MeLSl5T862F69lEAQH1yPLZVZ63IdnIqttUrJq1CZsCLdtPbd5vvvf78pPq3AQByGX98RtJGpL37kD9ne/qNWPcuK7AHgMfPmHQxo31ecJzfYoLsoGhGKjjtxcouRQjJoW4n0hY2Tptjyrl+X8ylFLG/paNAzabPWKj5NpPNGhFxOvRtNbDTqfxAbKOqafNc8ql7wmkjkE0NnPDrGzJ1Kc/Mx7a6FcP2l/y/1pqdrknRrBVYh0I060TXMm2JE3jLdA4uN5QTaw+I9BgjJ0yKh/1T3nbSimufK/r0IEtF2psBJ7B2onPpBDJgnS/6hBPGiL1+eoQTSNqm+wmEEL48XYi/e/dsW4eaJzP79a8CAOaP+3uSTE/jCHOmzql8xv72+xPYe16tVI5tzkFAis4LJ43zR98Z7wTSN2nSpVx+7Utj29u/fz8A4AbhTPPVp8w98WsP+WPz7HfMtTTx+H3L7mMnWUGQvaXYOp2jhPQhnQqxrijKxUuS99muY9mG7yTbcvMuxHb0JTNdMXI0+nO/0+kqbEpij7Quera1ioS92pGjbmRLvFYDkJg+pFMh1hVFuXhxHRLZMRk/UG74TrItN+9CbCrM3tzEUpAueratYxDIrmNLjBy1K8hOHXvRxldOUZSLlvMVaa+1IFuF2ZuXJGG2nO6AIJvrpXmQjItmiUqzADDdNGMTsyVGjlSQrShKN3I+Iu3l5q3Wph2jzcdSYXYXCLJvj8493GTkSgEozQDAVzawLutOR0aOiOg/w+RSiWCCPb2JmU+RUX/+AYAfhkky9yZm/uZabTfbbyL7pjLNfUIZGbZuxZk96RCfe8wI+37oimWjmbfki0/4qKwvPmzEd4tCVB3ZbR0Y9oLjAzba83DOq59dnWbL/t1u0QpA80Iw6cTUMkiwm4zghds1KzwtCnFtyQpUA3hRZj5NDesdEscuNWOFtKd8ZNfKsUfMPp70gmwniCxN+mH+hbNGcCujGfftMhqNgQOP+O1vN+csyPnjQ1kjyO7b44XbN132AgDAYG5PbHvQCrKnSl40W7HHrLhMlODNBJWN8BViWJtSzdHRUas2mZxgOwp8O6PQLOsE1pEQ6DoNe0m0mcWqjTQceEF4fsicg6Dio1yTjdZNQtAZDpprKhjwwvpw1Fwv2YIX0fKCEUTXy/7VURIuyjFlcs0zhSaiXjT1qsx5cXh5ptBYXAi4x2y5+ZP+j/GO50ydDj07F9smbAT644v+WE+Laz3TJU4Ash4Hesz5ztvrUN4avU3cD6wgOysF2dYxQ17LSVHK14vJD/5KPD3xgHG6mX7an6swoc5klejuLMto6a4dSR2Nm19dEBHeF0x7rAvhtivXO+ujZo/uNILsHzn4PbHth19mOq+P37Qvtn36UVPuH75xJLY9eu/X4dfUce6IZo/fHoxd1TB6FJ15AMGO56H29BeXicu++ejUyNHvMPPzmPk6AP8A4H3W/ioAh+3nNgB/3PYaE0RrnQqxriiKIrnpHwcbvoHl04c4UfVKKUiSyiXZlM1L/tTN8XQn04cwcyUcOwI5esSVArg4hfozd2+Jt1CSjuwQM8+Jn73wnsO3wES/ZBsafMiFFF+RBNGavkpTFKUbeP4/Djd8A83C7SQBt7T9/+3db4xUVxnH8e8PCltr0ZUuNtiiRUOs1URKEGswiEq0rS+oiim+sI0x0SoYfWEU7AswsUnVqEnfWDHSomlLCUramPqnSYtEG4GqIP/b1dKCIFSa0jaarSyPL+6Z5WYzM8uyM3t3zvw+yWbunDlszpPnMvvMuefOOd9+9dqsc11ybMnQce1vWlV/2waPPNFz9vRzxJniHKvNGkVEVrNGUOGCbEl3ALcAp4EPpuYrgCOlbkdT23GGSTv+Frv+pvKp3qK1SQfnukgys45QbwF3vcXU9frNPNwzVBh5Iba1Q0S8etGbF3L2+f1MumwO8d8XOHvqUHazRtDG4qjZDrwR8VBE3A7cLmk1sBJYA9S7KF+3Io2IdcA6gEmX9EVwamih2v9uumfo2MysU8zf2sv8rb38eO2zQ4uqR9tvpH9rNhaDR57o4eLpAzFwOsu1RjVtK44iYsnIvQC4n2KX3TUUM0WzSq9dCRxr8dDMzMzsAgzNHp16Ksu1RjWq4lKhpDkR8XQ6/jLwgYhYJuljFLNINwLvBe6KiAXn8fueZxpTeJl+AF7Hm3ipa4qqPuDfI/bKj+PuLt0V97n3sOZx13uvy+P9r7vyfc5o435LRMxo12C6WVVrju6U9HaKW/mfBW5L7Y9QFEb9FLfyn9e1sYiYIenJiJjfjsFOZI67uzju7uK4u0u3xj0RVVIcRcQnG7QHsGKch2NmZmY2JNvrhWZmZmYXIqfiaF3VA6iI4+4ujru7OO7u0q1xTziVLMg2MzMzm6hymjkyMzMzGzMXR2ZmZmYlWRRHkq6XdEhSv6RVVY+nnSQdlrRH0i5JT6a26ZIelfR0enzDSL9nopO0XtJJSXtLbXXjVOGulP+/SZpX3cjHpkHcayX9M+V8l6QbS6+tTnEfkvTRakY9dpJmSXpc0gFJ+yR9JbVnnfMmcWedc0kXS9ohaXeK+1upfbak7SnfD0qamtp70vP+9PpVVY7/QjWJ+15Jz5TyPTe1Z3Ged6SI6OgfYDLwd+CtwFRgN3BN1eNqY7yHgb5hbd8FVqXjVcB3qh5nC+JcBMwD9o4UJ8V3Y/2aYvuZ64DtVY+/xXGvBb5Wp+816XzvAWan/weTq47hAuOeCcxLx9OAp1J8Wee8SdxZ5zzl7dJ0PAXYnvK4CVie2u8GvpiOvwTcnY6XAw9WHUOL474XWFanfxbneSf+5DBztADoj4h/RMSrwEZgacVjGm9LgQ3peANwU4VjaYmI2Aa8MKy5UZxLgZ9F4U9Ar6SZ4zPS1moQdyNLgY0RMRARz1B8eeqI3yg/EUXE8Yj4Szp+GThAsel01jlvEncjWeQ85e2V9HRK+gngQ8Dm1D4837XzYDPwYUn19uKc0JrE3UgW53knyqE4ugI4Unp+lOZvLp0ugN9J+rOkz6e2yyPiOBRvtsAbKxtdezWKsxvOgZVpWn196bJplnGnSybXUnyq7pqcD4sbMs+5pMmSdgEngUcpZsFejIgzqUs5tqG40+ungcvGd8StMTzuiKjl+46U7x9K6klt2eS70+RQHNX79JDz9xMsjIh5wA3ACkmLqh7QBJD7OfAj4G3AXOA48P3Unl3cki4FfgF8NSJeata1TlvHxl4n7uxzHhGDETGXYoPxBcA76nVLj9nGLeldwGrgauA9wHTgG6l7NnF3mhyKo6PArNLzK6HjN11sKCKOpceTwBaKN5UTtanW9HiyuhG2VaM4sz4HIuJEekM9C/yEc5dRsopb0hSKAuG+iPhlas4+5/Xi7pacA0TEi8BWijU1vZJq21qVYxuKO73+es7/8vOEVIr7+nR5NSJiALiHjPPdKXIojnYCc9JdDlMpFus9XPGY2kLSayVNqx0DHwH2UsR7a+p2K/BQNSNsu0ZxPgzcku7suA44XbsUk4Nhaww+TpFzKOJenu7kmQ3MAXaM9/haIa0f+SlwICJ+UHop65w3ijv3nEuaIak3Hb8GWEKx3upxYFnqNjzftfNgGfBYRHTcDEqDuA+WPgCIYp1VOd8df553oko2nm2liDgjaSXwW4o719ZHxL6Kh9UulwNb0jrEi4D7I+I3knYCmyR9DngO+FSFY2wJSQ8Ai4E+SUeBNcCd1I/zEYq7OvqB/wCfHfcBt0iDuBenW3uD4m7FLwBExD5Jm4D9wBlgRUQMVjHuFlgIfAbYk9ZjAHyT/HPeKO5PZ57zmcAGSZMpPqRviohfSdoPbJT0beCvFIUj6fHnkvopZoyWVzHoFmgU92OSZlBcRtsF3Jb653KedxxvH2JmZmZWksNlNTMzM7OWcXFkZmZmVuLiyMzMzKzExZGZmZlZiYsjMzMzsxIXR2Y2IkmvjNzLzCwPLo7MzMzMSlwcmdl5S9/U+z1JeyXtkXRzal8saaukzZIOSrqvE3dNNzODDL4h28zG1ScoNkN9N9AH7JS0Lb12LfBOir2f/kjx7c9/qGKQZmZj4ZkjMxuN9wMPpE1RTwC/p9hJHGBHRBxNm6XuAq6qaIxmZmPi4sjMRqPZpbKB0vEgnpk2sw7l4sjMRmMbcLOkyWmjzEV04K7wZmbN+JOdmY3GFuB9wG6KHeO/HhH/knR1tcMyM2sdRUTVYzAzMzObMHxZzczMzKzExZGZmZlZiYsjMzMzsxIXR2ZmZmYlLo7MzMzMSlwcmZmZmZW4ODIzMzMr+T/JQmmjM3Gf2AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot con marcas en el mapa de correlacion\n",
    "corr.plot(robust=True,figsize=(10,3))\n",
    "\n",
    "for ni in range(0,pv.shape[1]): # en longitudes\n",
    "    for nj in range(0,pv.shape[0]): #en latitudes\n",
    "        if pv.isel(lat=nj, lon=ni) <= 0.05:\n",
    "            plt.plot(pv.lon[ni].values,pv.lat[nj].values, markersize=5, marker=\"+\", color=\"g\" )\n",
    "            \n",
    "plt.savefig(\"pearson_corr_ejercicio_con_mapa.png\", dpi=300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x1b4b2ce8188>"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dset_3=xr.open_dataset(\"umbrales_de_corr.nc\")\n",
    "\n",
    "corr_inf=dset_3.corr_pearson_inf\n",
    "corr_inf.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x1b4b2a69a88>"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "corr_sup=dset_3.corr_pearson_sup\n",
    "corr_sup.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x1b4b2d8eb48>"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "(corr_sup-corr_inf).plot(robust=True,cmap=\"hot\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}