Seasonal Bias ensemble average(GCM-chirps).ipynb

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    "#writing some conda package or module\n",
    "#!pip install netCDF4\n",
    "%matplotlib inline\n",
    "import warnings\n",
    "from netCDF4 import Dataset\n",
    "import numpy as np\n",
    "import xarray as xr\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "#!pip install cartopy\n",
    "import cartopy.feature as cfeature\n",
    "import cartopy.crs as ccrs\n",
    "import cartopy.mpl.ticker as cticker\n",
    "from cartopy.util import add_cyclic_point"
   ]
  },
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   "cell_type": "code",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (latitude: 2000, longitude: 7200, time: 496)\n",
       "Coordinates:\n",
       "  * latitude   (latitude) float32 -49.97 -49.92 -49.88 ... 49.87 49.92 49.97\n",
       "  * longitude  (longitude) float32 -180.0 -179.9 -179.9 ... 179.9 179.9 180.0\n",
       "  * time       (time) datetime64[ns] 1981-01-01 1981-02-01 ... 2022-04-01\n",
       "Data variables:\n",
       "    precip     (time, latitude, longitude) float32 ...\n",
       "Attributes: (12/15)\n",
       "    Conventions:       CF-1.6\n",
       "    title:             CHIRPS Version 2.0\n",
       "    history:           created by Climate Hazards Group\n",
       "    version:           Version 2.0\n",
       "    date_created:      2022-05-16\n",
       "    creator_name:      Pete Peterson\n",
       "    ...                ...\n",
       "    reference:         Funk, C.C., Peterson, P.J., Landsfeld, M.F., Pedreros,...\n",
       "    comments:           time variable denotes the first day of the given month.\n",
       "    acknowledgements:  The Climate Hazards Group InfraRed Precipitation with ...\n",
       "    ftp_url:           ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CH...\n",
       "    website:           http://chg.geog.ucsb.edu/data/chirps/index.html\n",
       "    faq:               http://chg-wiki.geog.ucsb.edu/wiki/CHIRPS_FAQ</pre><div class='xr-wrap' style='display:none'><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-975fb8f3-406b-4701-9915-1cba0b84a57f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-975fb8f3-406b-4701-9915-1cba0b84a57f' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>latitude</span>: 2000</li><li><span class='xr-has-index'>longitude</span>: 7200</li><li><span class='xr-has-index'>time</span>: 496</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-c9baf5b2-04dd-4fc9-893a-423bd41d5946' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c9baf5b2-04dd-4fc9-893a-423bd41d5946' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-49.97 -49.92 ... 49.92 49.97</div><input id='attrs-613c7090-e219-4894-a85e-da271f663069' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-613c7090-e219-4894-a85e-da271f663069' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-34bb4838-d837-47c4-8184-d2d42084eb29' class='xr-var-data-in' type='checkbox'><label for='data-34bb4838-d837-47c4-8184-d2d42084eb29' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-49.975   , -49.925   , -49.875   , ...,  49.874992,  49.924995,\n",
       "        49.975   ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-180.0 -179.9 ... 179.9 180.0</div><input id='attrs-b08fa44c-3207-4b5c-aede-549d0da506b2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b08fa44c-3207-4b5c-aede-549d0da506b2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-60f18971-83c0-42c6-a2a4-5dde2583910f' class='xr-var-data-in' type='checkbox'><label for='data-60f18971-83c0-42c6-a2a4-5dde2583910f' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-179.975  , -179.925  , -179.875  , ...,  179.875  ,  179.92499,\n",
       "        179.975  ], 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'>1981-01-01 ... 2022-04-01</div><input id='attrs-b66eb712-83b2-4a03-b6d0-7a9ee430bb45' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b66eb712-83b2-4a03-b6d0-7a9ee430bb45' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e98f2ec2-5c07-4d3f-a052-f5dfa70b17a6' class='xr-var-data-in' type='checkbox'><label for='data-e98f2ec2-5c07-4d3f-a052-f5dfa70b17a6' 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>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-01-01T00:00:00.000000000&#x27;, &#x27;1981-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1981-03-01T00:00:00.000000000&#x27;, ..., &#x27;2022-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-03-01T00:00:00.000000000&#x27;, &#x27;2022-04-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-182209a0-309d-4e06-a33f-575bf3be1f3c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-182209a0-309d-4e06-a33f-575bf3be1f3c' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>precip</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3ab30161-c68a-4001-9262-303239016f5a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3ab30161-c68a-4001-9262-303239016f5a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1b284e4d-4eb0-42fc-b716-ab82e44198e7' class='xr-var-data-in' type='checkbox'><label for='data-1b284e4d-4eb0-42fc-b716-ab82e44198e7' 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>mm/month</dd><dt><span>standard_name :</span></dt><dd>convective precipitation rate</dd><dt><span>long_name :</span></dt><dd>Climate Hazards group InfraRed Precipitation with Stations</dd><dt><span>time_step :</span></dt><dd>month</dd><dt><span>geostatial_lat_min :</span></dt><dd>-50.0</dd><dt><span>geostatial_lat_max :</span></dt><dd>50.0</dd><dt><span>geostatial_lon_min :</span></dt><dd>-180.0</dd><dt><span>geostatial_lon_max :</span></dt><dd>180.0</dd></dl></div><div class='xr-var-data'><pre>[7142400000 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4d52110e-44e8-4c06-8896-184bf39f7b75' class='xr-section-summary-in' type='checkbox'  ><label for='section-4d52110e-44e8-4c06-8896-184bf39f7b75' class='xr-section-summary' >Attributes: <span>(15)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>title :</span></dt><dd>CHIRPS Version 2.0</dd><dt><span>history :</span></dt><dd>created by Climate Hazards Group</dd><dt><span>version :</span></dt><dd>Version 2.0</dd><dt><span>date_created :</span></dt><dd>2022-05-16</dd><dt><span>creator_name :</span></dt><dd>Pete Peterson</dd><dt><span>creator_email :</span></dt><dd>pete@geog.ucsb.edu</dd><dt><span>institution :</span></dt><dd>Climate Hazards Group.  University of California at Santa Barbara</dd><dt><span>documentation :</span></dt><dd>http://pubs.usgs.gov/ds/832/</dd><dt><span>reference :</span></dt><dd>Funk, C.C., Peterson, P.J., Landsfeld, M.F., Pedreros, D.H., Verdin, J.P., Rowland, J.D., Romero, B.E., Husak, G.J., Michaelsen, J.C., and Verdin, A.P., 2014, A quasi-global precipitation time series for drought monitoring: U.S. Geological Survey Data Series 832, 4 p., http://dx.doi.org/110.3133/ds832. </dd><dt><span>comments :</span></dt><dd> time variable denotes the first day of the given month.</dd><dt><span>acknowledgements :</span></dt><dd>The Climate Hazards Group InfraRed Precipitation with Stations development process was carried out through U.S. Geological Survey (USGS) cooperative agreement #G09AC000001 &quot;Monitoring and Forecasting Climate, Water and Land Use for Food Production in the Developing World&quot; with funding from: U.S. Agency for International Development Office of Food for Peace, award #AID-FFP-P-10-00002 for &quot;Famine Early Warning Systems Network Support,&quot; the National Aeronautics and Space Administration Applied Sciences Program, Decisions award #NN10AN26I for &quot;A Land Data Assimilation System for Famine Early Warning,&quot; SERVIR award #NNH12AU22I for &quot;A Long Time-Series Indicator of Agricultural Drought for the Greater Horn of Africa,&quot; The National Oceanic and Atmospheric Administration award NA11OAR4310151 for &quot;A Global Standardized Precipitation Index supporting the US Drought Portal and the Famine Early Warning System Network,&quot; and the USGS Land Change Science Program.</dd><dt><span>ftp_url :</span></dt><dd>ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-latest/</dd><dt><span>website :</span></dt><dd>http://chg.geog.ucsb.edu/data/chirps/index.html</dd><dt><span>faq :</span></dt><dd>http://chg-wiki.geog.ucsb.edu/wiki/CHIRPS_FAQ</dd></dl></div></li></ul></div></div>"
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       "<xarray.Dataset>\n",
       "Dimensions:    (latitude: 2000, longitude: 7200, time: 496)\n",
       "Coordinates:\n",
       "  * latitude   (latitude) float32 -49.97 -49.92 -49.88 ... 49.87 49.92 49.97\n",
       "  * longitude  (longitude) float32 -180.0 -179.9 -179.9 ... 179.9 179.9 180.0\n",
       "  * time       (time) datetime64[ns] 1981-01-01 1981-02-01 ... 2022-04-01\n",
       "Data variables:\n",
       "    precip     (time, latitude, longitude) float32 ...\n",
       "Attributes: (12/15)\n",
       "    Conventions:       CF-1.6\n",
       "    title:             CHIRPS Version 2.0\n",
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       "    version:           Version 2.0\n",
       "    date_created:      2022-05-16\n",
       "    creator_name:      Pete Peterson\n",
       "    ...                ...\n",
       "    reference:         Funk, C.C., Peterson, P.J., Landsfeld, M.F., Pedreros,...\n",
       "    comments:           time variable denotes the first day of the given month.\n",
       "    acknowledgements:  The Climate Hazards Group InfraRed Precipitation with ...\n",
       "    ftp_url:           ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CH...\n",
       "    website:           http://chg.geog.ucsb.edu/data/chirps/index.html\n",
       "    faq:               http://chg-wiki.geog.ucsb.edu/wiki/CHIRPS_FAQ"
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     "execution_count": 2,
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   "source": [
    "data = xr.open_dataset('/home/mkibria/Academic/pr_of_thesis/observation/chirps/chirps-v2.0.monthly.nc')\n",
    " \n",
    "\n",
    "data"
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   "cell_type": "code",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (latitude: 2000, longitude: 7200, time: 299)\n",
       "Coordinates:\n",
       "  * latitude   (latitude) float32 -49.97 -49.92 -49.88 ... 49.87 49.92 49.97\n",
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       "Data variables:\n",
       "    precip     (time, latitude, longitude) float32 ...\n",
       "Attributes: (12/15)\n",
       "    Conventions:       CF-1.6\n",
       "    title:             CHIRPS Version 2.0\n",
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       "    version:           Version 2.0\n",
       "    date_created:      2022-05-16\n",
       "    creator_name:      Pete Peterson\n",
       "    ...                ...\n",
       "    reference:         Funk, C.C., Peterson, P.J., Landsfeld, M.F., Pedreros,...\n",
       "    comments:           time variable denotes the first day of the given month.\n",
       "    acknowledgements:  The Climate Hazards Group InfraRed Precipitation with ...\n",
       "    ftp_url:           ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CH...\n",
       "    website:           http://chg.geog.ucsb.edu/data/chirps/index.html\n",
       "    faq:               http://chg-wiki.geog.ucsb.edu/wiki/CHIRPS_FAQ</pre><div class='xr-wrap' style='display:none'><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-68168d77-84af-4354-8526-a6ff0c1640d6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-68168d77-84af-4354-8526-a6ff0c1640d6' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>latitude</span>: 2000</li><li><span class='xr-has-index'>longitude</span>: 7200</li><li><span class='xr-has-index'>time</span>: 299</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-6e85e119-100f-458d-8f8e-ad3f43db62b0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6e85e119-100f-458d-8f8e-ad3f43db62b0' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-49.97 -49.92 ... 49.92 49.97</div><input id='attrs-6293475b-6e90-49e1-94b0-8715e315d360' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6293475b-6e90-49e1-94b0-8715e315d360' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cc6bca12-66dc-48bc-aa01-d14d7044dbd6' class='xr-var-data-in' type='checkbox'><label for='data-cc6bca12-66dc-48bc-aa01-d14d7044dbd6' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-49.975   , -49.925   , -49.875   , ...,  49.874992,  49.924995,\n",
       "        49.975   ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-180.0 -179.9 ... 179.9 180.0</div><input id='attrs-a6c14ba5-1359-4cc3-9c21-221f19823196' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a6c14ba5-1359-4cc3-9c21-221f19823196' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-793067c4-c697-43b0-ad93-7e7f5bed6a49' class='xr-var-data-in' type='checkbox'><label for='data-793067c4-c697-43b0-ad93-7e7f5bed6a49' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-179.975  , -179.925  , -179.875  , ...,  179.875  ,  179.92499,\n",
       "        179.975  ], 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'>1981-02-01 ... 2005-12-01</div><input id='attrs-de97e13e-05fe-4058-8964-57dcf8bfdab1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-de97e13e-05fe-4058-8964-57dcf8bfdab1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c57d319b-c5c3-441e-a03c-2168ab9274ea' class='xr-var-data-in' type='checkbox'><label for='data-c57d319b-c5c3-441e-a03c-2168ab9274ea' 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>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-02-01T00:00:00.000000000&#x27;, &#x27;1981-03-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1981-04-01T00:00:00.000000000&#x27;, ..., &#x27;2005-10-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-11-01T00:00:00.000000000&#x27;, &#x27;2005-12-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d85d17db-cba0-409d-9dbf-c5a881d9b7f5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d85d17db-cba0-409d-9dbf-c5a881d9b7f5' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>precip</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2425cd47-b1a7-4ad1-87a8-c86f558cc473' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2425cd47-b1a7-4ad1-87a8-c86f558cc473' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-372fb942-883e-4050-96b7-4ca42750ebca' class='xr-var-data-in' type='checkbox'><label for='data-372fb942-883e-4050-96b7-4ca42750ebca' 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>mm/month</dd><dt><span>standard_name :</span></dt><dd>convective precipitation rate</dd><dt><span>long_name :</span></dt><dd>Climate Hazards group InfraRed Precipitation with Stations</dd><dt><span>time_step :</span></dt><dd>month</dd><dt><span>geostatial_lat_min :</span></dt><dd>-50.0</dd><dt><span>geostatial_lat_max :</span></dt><dd>50.0</dd><dt><span>geostatial_lon_min :</span></dt><dd>-180.0</dd><dt><span>geostatial_lon_max :</span></dt><dd>180.0</dd></dl></div><div class='xr-var-data'><pre>[4305600000 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-21adc7e6-46b9-43b5-8cbc-938a758b2705' class='xr-section-summary-in' type='checkbox'  ><label for='section-21adc7e6-46b9-43b5-8cbc-938a758b2705' class='xr-section-summary' >Attributes: <span>(15)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>title :</span></dt><dd>CHIRPS Version 2.0</dd><dt><span>history :</span></dt><dd>created by Climate Hazards Group</dd><dt><span>version :</span></dt><dd>Version 2.0</dd><dt><span>date_created :</span></dt><dd>2022-05-16</dd><dt><span>creator_name :</span></dt><dd>Pete Peterson</dd><dt><span>creator_email :</span></dt><dd>pete@geog.ucsb.edu</dd><dt><span>institution :</span></dt><dd>Climate Hazards Group.  University of California at Santa Barbara</dd><dt><span>documentation :</span></dt><dd>http://pubs.usgs.gov/ds/832/</dd><dt><span>reference :</span></dt><dd>Funk, C.C., Peterson, P.J., Landsfeld, M.F., Pedreros, D.H., Verdin, J.P., Rowland, J.D., Romero, B.E., Husak, G.J., Michaelsen, J.C., and Verdin, A.P., 2014, A quasi-global precipitation time series for drought monitoring: U.S. Geological Survey Data Series 832, 4 p., http://dx.doi.org/110.3133/ds832. </dd><dt><span>comments :</span></dt><dd> time variable denotes the first day of the given month.</dd><dt><span>acknowledgements :</span></dt><dd>The Climate Hazards Group InfraRed Precipitation with Stations development process was carried out through U.S. Geological Survey (USGS) cooperative agreement #G09AC000001 &quot;Monitoring and Forecasting Climate, Water and Land Use for Food Production in the Developing World&quot; with funding from: U.S. Agency for International Development Office of Food for Peace, award #AID-FFP-P-10-00002 for &quot;Famine Early Warning Systems Network Support,&quot; the National Aeronautics and Space Administration Applied Sciences Program, Decisions award #NN10AN26I for &quot;A Land Data Assimilation System for Famine Early Warning,&quot; SERVIR award #NNH12AU22I for &quot;A Long Time-Series Indicator of Agricultural Drought for the Greater Horn of Africa,&quot; The National Oceanic and Atmospheric Administration award NA11OAR4310151 for &quot;A Global Standardized Precipitation Index supporting the US Drought Portal and the Famine Early Warning System Network,&quot; and the USGS Land Change Science Program.</dd><dt><span>ftp_url :</span></dt><dd>ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-latest/</dd><dt><span>website :</span></dt><dd>http://chg.geog.ucsb.edu/data/chirps/index.html</dd><dt><span>faq :</span></dt><dd>http://chg-wiki.geog.ucsb.edu/wiki/CHIRPS_FAQ</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (latitude: 2000, longitude: 7200, time: 299)\n",
       "Coordinates:\n",
       "  * latitude   (latitude) float32 -49.97 -49.92 -49.88 ... 49.87 49.92 49.97\n",
       "  * longitude  (longitude) float32 -180.0 -179.9 -179.9 ... 179.9 179.9 180.0\n",
       "  * time       (time) datetime64[ns] 1981-02-01 1981-03-01 ... 2005-12-01\n",
       "Data variables:\n",
       "    precip     (time, latitude, longitude) float32 ...\n",
       "Attributes: (12/15)\n",
       "    Conventions:       CF-1.6\n",
       "    title:             CHIRPS Version 2.0\n",
       "    history:           created by Climate Hazards Group\n",
       "    version:           Version 2.0\n",
       "    date_created:      2022-05-16\n",
       "    creator_name:      Pete Peterson\n",
       "    ...                ...\n",
       "    reference:         Funk, C.C., Peterson, P.J., Landsfeld, M.F., Pedreros,...\n",
       "    comments:           time variable denotes the first day of the given month.\n",
       "    acknowledgements:  The Climate Hazards Group InfraRed Precipitation with ...\n",
       "    ftp_url:           ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CH...\n",
       "    website:           http://chg.geog.ucsb.edu/data/chirps/index.html\n",
       "    faq:               http://chg-wiki.geog.ucsb.edu/wiki/CHIRPS_FAQ"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#to select the year from 1980 to 2015\n",
    "data = data.sel(time=slice('1981-01-16T12:00:00.000000000','2005-12-16T00:00:00.000000000'))\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "10070b93",
   "metadata": {},
   "outputs": [
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       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (latitude: 2000, longitude: 7200, time: 100)\n",
       "Coordinates:\n",
       "  * latitude   (latitude) float32 -49.97 -49.92 -49.88 ... 49.87 49.92 49.97\n",
       "  * longitude  (longitude) float32 -180.0 -179.9 -179.9 ... 179.9 179.9 180.0\n",
       "  * time       (time) datetime64[ns] 1981-06-01 1981-07-01 ... 2005-09-01\n",
       "Data variables:\n",
       "    precip     (time, latitude, longitude) float32 ...\n",
       "Attributes: (12/15)\n",
       "    Conventions:       CF-1.6\n",
       "    title:             CHIRPS Version 2.0\n",
       "    history:           created by Climate Hazards Group\n",
       "    version:           Version 2.0\n",
       "    date_created:      2022-05-16\n",
       "    creator_name:      Pete Peterson\n",
       "    ...                ...\n",
       "    reference:         Funk, C.C., Peterson, P.J., Landsfeld, M.F., Pedreros,...\n",
       "    comments:           time variable denotes the first day of the given month.\n",
       "    acknowledgements:  The Climate Hazards Group InfraRed Precipitation with ...\n",
       "    ftp_url:           ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CH...\n",
       "    website:           http://chg.geog.ucsb.edu/data/chirps/index.html\n",
       "    faq:               http://chg-wiki.geog.ucsb.edu/wiki/CHIRPS_FAQ</pre><div class='xr-wrap' style='display:none'><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-2584375d-d077-4bcf-a62e-29c27148cb3d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2584375d-d077-4bcf-a62e-29c27148cb3d' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>latitude</span>: 2000</li><li><span class='xr-has-index'>longitude</span>: 7200</li><li><span class='xr-has-index'>time</span>: 100</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-410e9a0d-ca08-4145-bca7-53490a9dc918' class='xr-section-summary-in' type='checkbox'  checked><label for='section-410e9a0d-ca08-4145-bca7-53490a9dc918' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-49.97 -49.92 ... 49.92 49.97</div><input id='attrs-6ed2845e-637b-47d0-906e-a3241f0a69d9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6ed2845e-637b-47d0-906e-a3241f0a69d9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-385bf39c-ba32-4460-a204-3a7c84048727' class='xr-var-data-in' type='checkbox'><label for='data-385bf39c-ba32-4460-a204-3a7c84048727' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-49.975   , -49.925   , -49.875   , ...,  49.874992,  49.924995,\n",
       "        49.975   ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-180.0 -179.9 ... 179.9 180.0</div><input id='attrs-98b5701f-d3e5-4a61-8fff-9df37433bba9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-98b5701f-d3e5-4a61-8fff-9df37433bba9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4f059fe-55a8-4f7c-a70a-a90ac3f5ca53' class='xr-var-data-in' type='checkbox'><label for='data-f4f059fe-55a8-4f7c-a70a-a90ac3f5ca53' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-179.975  , -179.925  , -179.875  , ...,  179.875  ,  179.92499,\n",
       "        179.975  ], 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'>1981-06-01 ... 2005-09-01</div><input id='attrs-ebc84211-3572-4719-a991-dae190322675' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ebc84211-3572-4719-a991-dae190322675' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a8e1415f-8306-41f2-9002-91069b59fd29' class='xr-var-data-in' type='checkbox'><label for='data-a8e1415f-8306-41f2-9002-91069b59fd29' 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>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-06-01T00:00:00.000000000&#x27;, &#x27;1981-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1981-08-01T00:00:00.000000000&#x27;, &#x27;1981-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1982-06-01T00:00:00.000000000&#x27;, &#x27;1982-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1982-08-01T00:00:00.000000000&#x27;, &#x27;1982-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1983-06-01T00:00:00.000000000&#x27;, &#x27;1983-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1983-08-01T00:00:00.000000000&#x27;, &#x27;1983-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1984-06-01T00:00:00.000000000&#x27;, &#x27;1984-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1984-08-01T00:00:00.000000000&#x27;, &#x27;1984-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1985-06-01T00:00:00.000000000&#x27;, &#x27;1985-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1985-08-01T00:00:00.000000000&#x27;, &#x27;1985-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1986-06-01T00:00:00.000000000&#x27;, &#x27;1986-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1986-08-01T00:00:00.000000000&#x27;, &#x27;1986-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1987-06-01T00:00:00.000000000&#x27;, &#x27;1987-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1987-08-01T00:00:00.000000000&#x27;, &#x27;1987-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1988-06-01T00:00:00.000000000&#x27;, &#x27;1988-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1988-08-01T00:00:00.000000000&#x27;, &#x27;1988-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1989-06-01T00:00:00.000000000&#x27;, &#x27;1989-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1989-08-01T00:00:00.000000000&#x27;, &#x27;1989-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1990-06-01T00:00:00.000000000&#x27;, &#x27;1990-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1990-08-01T00:00:00.000000000&#x27;, &#x27;1990-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1991-06-01T00:00:00.000000000&#x27;, &#x27;1991-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1991-08-01T00:00:00.000000000&#x27;, &#x27;1991-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1992-06-01T00:00:00.000000000&#x27;, &#x27;1992-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1992-08-01T00:00:00.000000000&#x27;, &#x27;1992-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1993-06-01T00:00:00.000000000&#x27;, &#x27;1993-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1993-08-01T00:00:00.000000000&#x27;, &#x27;1993-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1994-06-01T00:00:00.000000000&#x27;, &#x27;1994-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1994-08-01T00:00:00.000000000&#x27;, &#x27;1994-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1995-06-01T00:00:00.000000000&#x27;, &#x27;1995-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1995-08-01T00:00:00.000000000&#x27;, &#x27;1995-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1996-06-01T00:00:00.000000000&#x27;, &#x27;1996-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1996-08-01T00:00:00.000000000&#x27;, &#x27;1996-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1997-06-01T00:00:00.000000000&#x27;, &#x27;1997-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1997-08-01T00:00:00.000000000&#x27;, &#x27;1997-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-06-01T00:00:00.000000000&#x27;, &#x27;1998-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-08-01T00:00:00.000000000&#x27;, &#x27;1998-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-06-01T00:00:00.000000000&#x27;, &#x27;1999-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-08-01T00:00:00.000000000&#x27;, &#x27;1999-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-06-01T00:00:00.000000000&#x27;, &#x27;2000-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-08-01T00:00:00.000000000&#x27;, &#x27;2000-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-06-01T00:00:00.000000000&#x27;, &#x27;2001-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-08-01T00:00:00.000000000&#x27;, &#x27;2001-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-06-01T00:00:00.000000000&#x27;, &#x27;2002-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-08-01T00:00:00.000000000&#x27;, &#x27;2002-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-06-01T00:00:00.000000000&#x27;, &#x27;2003-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-08-01T00:00:00.000000000&#x27;, &#x27;2003-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-06-01T00:00:00.000000000&#x27;, &#x27;2004-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-08-01T00:00:00.000000000&#x27;, &#x27;2004-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-06-01T00:00:00.000000000&#x27;, &#x27;2005-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-08-01T00:00:00.000000000&#x27;, &#x27;2005-09-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-dd2161d3-53e0-4ae1-9c82-b33aa9ad6784' class='xr-section-summary-in' type='checkbox'  checked><label for='section-dd2161d3-53e0-4ae1-9c82-b33aa9ad6784' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>precip</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fcd7c290-a2da-4841-9266-79a657abdf9d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fcd7c290-a2da-4841-9266-79a657abdf9d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a8d97bba-83a1-4398-b43c-56882d787810' class='xr-var-data-in' type='checkbox'><label for='data-a8d97bba-83a1-4398-b43c-56882d787810' 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>mm/month</dd><dt><span>standard_name :</span></dt><dd>convective precipitation rate</dd><dt><span>long_name :</span></dt><dd>Climate Hazards group InfraRed Precipitation with Stations</dd><dt><span>time_step :</span></dt><dd>month</dd><dt><span>geostatial_lat_min :</span></dt><dd>-50.0</dd><dt><span>geostatial_lat_max :</span></dt><dd>50.0</dd><dt><span>geostatial_lon_min :</span></dt><dd>-180.0</dd><dt><span>geostatial_lon_max :</span></dt><dd>180.0</dd></dl></div><div class='xr-var-data'><pre>[1440000000 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d7365d23-a24f-4402-acfc-eed2b8ab0b57' class='xr-section-summary-in' type='checkbox'  ><label for='section-d7365d23-a24f-4402-acfc-eed2b8ab0b57' class='xr-section-summary' >Attributes: <span>(15)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>title :</span></dt><dd>CHIRPS Version 2.0</dd><dt><span>history :</span></dt><dd>created by Climate Hazards Group</dd><dt><span>version :</span></dt><dd>Version 2.0</dd><dt><span>date_created :</span></dt><dd>2022-05-16</dd><dt><span>creator_name :</span></dt><dd>Pete Peterson</dd><dt><span>creator_email :</span></dt><dd>pete@geog.ucsb.edu</dd><dt><span>institution :</span></dt><dd>Climate Hazards Group.  University of California at Santa Barbara</dd><dt><span>documentation :</span></dt><dd>http://pubs.usgs.gov/ds/832/</dd><dt><span>reference :</span></dt><dd>Funk, C.C., Peterson, P.J., Landsfeld, M.F., Pedreros, D.H., Verdin, J.P., Rowland, J.D., Romero, B.E., Husak, G.J., Michaelsen, J.C., and Verdin, A.P., 2014, A quasi-global precipitation time series for drought monitoring: U.S. Geological Survey Data Series 832, 4 p., http://dx.doi.org/110.3133/ds832. </dd><dt><span>comments :</span></dt><dd> time variable denotes the first day of the given month.</dd><dt><span>acknowledgements :</span></dt><dd>The Climate Hazards Group InfraRed Precipitation with Stations development process was carried out through U.S. Geological Survey (USGS) cooperative agreement #G09AC000001 &quot;Monitoring and Forecasting Climate, Water and Land Use for Food Production in the Developing World&quot; with funding from: U.S. Agency for International Development Office of Food for Peace, award #AID-FFP-P-10-00002 for &quot;Famine Early Warning Systems Network Support,&quot; the National Aeronautics and Space Administration Applied Sciences Program, Decisions award #NN10AN26I for &quot;A Land Data Assimilation System for Famine Early Warning,&quot; SERVIR award #NNH12AU22I for &quot;A Long Time-Series Indicator of Agricultural Drought for the Greater Horn of Africa,&quot; The National Oceanic and Atmospheric Administration award NA11OAR4310151 for &quot;A Global Standardized Precipitation Index supporting the US Drought Portal and the Famine Early Warning System Network,&quot; and the USGS Land Change Science Program.</dd><dt><span>ftp_url :</span></dt><dd>ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-latest/</dd><dt><span>website :</span></dt><dd>http://chg.geog.ucsb.edu/data/chirps/index.html</dd><dt><span>faq :</span></dt><dd>http://chg-wiki.geog.ucsb.edu/wiki/CHIRPS_FAQ</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (latitude: 2000, longitude: 7200, time: 100)\n",
       "Coordinates:\n",
       "  * latitude   (latitude) float32 -49.97 -49.92 -49.88 ... 49.87 49.92 49.97\n",
       "  * longitude  (longitude) float32 -180.0 -179.9 -179.9 ... 179.9 179.9 180.0\n",
       "  * time       (time) datetime64[ns] 1981-06-01 1981-07-01 ... 2005-09-01\n",
       "Data variables:\n",
       "    precip     (time, latitude, longitude) float32 ...\n",
       "Attributes: (12/15)\n",
       "    Conventions:       CF-1.6\n",
       "    title:             CHIRPS Version 2.0\n",
       "    history:           created by Climate Hazards Group\n",
       "    version:           Version 2.0\n",
       "    date_created:      2022-05-16\n",
       "    creator_name:      Pete Peterson\n",
       "    ...                ...\n",
       "    reference:         Funk, C.C., Peterson, P.J., Landsfeld, M.F., Pedreros,...\n",
       "    comments:           time variable denotes the first day of the given month.\n",
       "    acknowledgements:  The Climate Hazards Group InfraRed Precipitation with ...\n",
       "    ftp_url:           ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CH...\n",
       "    website:           http://chg.geog.ucsb.edu/data/chirps/index.html\n",
       "    faq:               http://chg-wiki.geog.ucsb.edu/wiki/CHIRPS_FAQ"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#selecting only JJAS months\n",
    "\n",
    "def is_jjas(month):\n",
    "    return (month >= 6) & (month <= 9)\n",
    "\n",
    "jjas_data = data.sel(time=is_jjas(data['time.month']))\n",
    "\n",
    "jjas_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "735515f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "#for i in data.latitude.values:\n",
    " #   print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "fd310367",
   "metadata": {},
   "outputs": [],
   "source": [
    "#for i in data.longitude.values:\n",
    " #   print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2a9644bb",
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (latitude: 200, longitude: 160, time: 100)\n",
       "Coordinates:\n",
       "  * latitude   (latitude) float32 18.02 18.07 18.12 18.17 ... 27.88 27.92 27.97\n",
       "  * longitude  (longitude) float32 86.02 86.08 86.12 86.17 ... 93.88 93.92 93.98\n",
       "  * time       (time) datetime64[ns] 1981-06-01 1981-07-01 ... 2005-09-01\n",
       "Data variables:\n",
       "    precip     (time, latitude, longitude) float32 ...\n",
       "Attributes: (12/15)\n",
       "    Conventions:       CF-1.6\n",
       "    title:             CHIRPS Version 2.0\n",
       "    history:           created by Climate Hazards Group\n",
       "    version:           Version 2.0\n",
       "    date_created:      2022-05-16\n",
       "    creator_name:      Pete Peterson\n",
       "    ...                ...\n",
       "    reference:         Funk, C.C., Peterson, P.J., Landsfeld, M.F., Pedreros,...\n",
       "    comments:           time variable denotes the first day of the given month.\n",
       "    acknowledgements:  The Climate Hazards Group InfraRed Precipitation with ...\n",
       "    ftp_url:           ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CH...\n",
       "    website:           http://chg.geog.ucsb.edu/data/chirps/index.html\n",
       "    faq:               http://chg-wiki.geog.ucsb.edu/wiki/CHIRPS_FAQ</pre><div class='xr-wrap' style='display:none'><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-86cc4ff3-c5db-4898-aebe-53d72a33f72c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-86cc4ff3-c5db-4898-aebe-53d72a33f72c' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>latitude</span>: 200</li><li><span class='xr-has-index'>longitude</span>: 160</li><li><span class='xr-has-index'>time</span>: 100</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-118945e8-15b2-4071-ad0e-b23370889d18' class='xr-section-summary-in' type='checkbox'  checked><label for='section-118945e8-15b2-4071-ad0e-b23370889d18' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>18.02 18.07 18.12 ... 27.92 27.97</div><input id='attrs-8ab84617-15e4-4721-803b-b1e435744374' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8ab84617-15e4-4721-803b-b1e435744374' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8fbd915a-68d1-4129-98d5-19860a6322e0' class='xr-var-data-in' type='checkbox'><label for='data-8fbd915a-68d1-4129-98d5-19860a6322e0' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([18.024994, 18.074997, 18.125   , 18.174995, 18.224998, 18.274994,\n",
       "       18.324997, 18.375   , 18.424995, 18.474998, 18.524994, 18.574997,\n",
       "       18.625   , 18.674995, 18.724998, 18.774994, 18.824997, 18.875   ,\n",
       "       18.924995, 18.974998, 19.024994, 19.074997, 19.125   , 19.174995,\n",
       "       19.224998, 19.274994, 19.324997, 19.375   , 19.424995, 19.474998,\n",
       "       19.524994, 19.574997, 19.625   , 19.674995, 19.724998, 19.774994,\n",
       "       19.824997, 19.875   , 19.924995, 19.974998, 20.024994, 20.074997,\n",
       "       20.125   , 20.174995, 20.224998, 20.274994, 20.324997, 20.375   ,\n",
       "       20.424995, 20.474998, 20.524994, 20.574997, 20.625   , 20.674995,\n",
       "       20.724998, 20.774994, 20.824997, 20.875   , 20.924995, 20.974998,\n",
       "       21.024994, 21.074997, 21.125   , 21.174995, 21.224998, 21.274994,\n",
       "       21.324997, 21.375   , 21.424995, 21.474998, 21.524994, 21.574997,\n",
       "       21.625   , 21.674995, 21.724998, 21.774994, 21.824997, 21.875   ,\n",
       "       21.924995, 21.974998, 22.024994, 22.074997, 22.125   , 22.174995,\n",
       "       22.224998, 22.274994, 22.324997, 22.375   , 22.424995, 22.474998,\n",
       "       22.524994, 22.574997, 22.625   , 22.674995, 22.724998, 22.774994,\n",
       "       22.824997, 22.875   , 22.924995, 22.974998, 23.024994, 23.074997,\n",
       "       23.125   , 23.174995, 23.224998, 23.274994, 23.324997, 23.375   ,\n",
       "       23.424995, 23.474998, 23.524994, 23.574997, 23.625   , 23.674995,\n",
       "       23.724998, 23.774994, 23.824997, 23.875   , 23.924995, 23.974998,\n",
       "       24.024994, 24.074997, 24.125   , 24.174995, 24.224998, 24.274994,\n",
       "       24.324997, 24.375   , 24.424995, 24.474998, 24.524994, 24.574997,\n",
       "       24.625   , 24.674995, 24.724998, 24.774994, 24.824997, 24.875   ,\n",
       "       24.924995, 24.974998, 25.024994, 25.074997, 25.125   , 25.174995,\n",
       "       25.224998, 25.274994, 25.324997, 25.375   , 25.424995, 25.474998,\n",
       "       25.524994, 25.574997, 25.625   , 25.674995, 25.724998, 25.774994,\n",
       "       25.824997, 25.875   , 25.924995, 25.974998, 26.024994, 26.074997,\n",
       "       26.125   , 26.174995, 26.224998, 26.274994, 26.324997, 26.375   ,\n",
       "       26.424995, 26.474998, 26.524994, 26.574997, 26.625   , 26.674995,\n",
       "       26.724998, 26.774994, 26.824997, 26.875   , 26.924995, 26.974998,\n",
       "       27.024994, 27.074997, 27.125   , 27.174995, 27.224998, 27.274994,\n",
       "       27.324997, 27.375   , 27.424995, 27.474998, 27.524994, 27.574997,\n",
       "       27.625   , 27.674995, 27.724998, 27.774994, 27.824997, 27.875   ,\n",
       "       27.924995, 27.974998], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>86.02 86.08 86.12 ... 93.92 93.98</div><input id='attrs-eb1d6038-085d-45de-9bce-ca82231172b4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eb1d6038-085d-45de-9bce-ca82231172b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1631a14-389b-4550-b529-0b173fcd209f' class='xr-var-data-in' type='checkbox'><label for='data-b1631a14-389b-4550-b529-0b173fcd209f' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([86.024994, 86.07501 , 86.125   , 86.17499 , 86.225006, 86.274994,\n",
       "       86.32501 , 86.375   , 86.42499 , 86.475006, 86.524994, 86.57501 ,\n",
       "       86.625   , 86.67499 , 86.725006, 86.774994, 86.82501 , 86.875   ,\n",
       "       86.92499 , 86.975006, 87.024994, 87.07501 , 87.125   , 87.17499 ,\n",
       "       87.225006, 87.274994, 87.32501 , 87.375   , 87.42499 , 87.475006,\n",
       "       87.524994, 87.57501 , 87.625   , 87.67499 , 87.725006, 87.774994,\n",
       "       87.82501 , 87.875   , 87.92499 , 87.975006, 88.024994, 88.07501 ,\n",
       "       88.125   , 88.17499 , 88.225006, 88.274994, 88.32501 , 88.375   ,\n",
       "       88.42499 , 88.475006, 88.524994, 88.57501 , 88.625   , 88.67499 ,\n",
       "       88.725006, 88.774994, 88.82501 , 88.875   , 88.92499 , 88.975006,\n",
       "       89.024994, 89.07501 , 89.125   , 89.17499 , 89.225006, 89.274994,\n",
       "       89.32501 , 89.375   , 89.42499 , 89.475006, 89.524994, 89.57501 ,\n",
       "       89.625   , 89.67499 , 89.725006, 89.774994, 89.82501 , 89.875   ,\n",
       "       89.92499 , 89.975006, 90.024994, 90.07501 , 90.125   , 90.17499 ,\n",
       "       90.225006, 90.274994, 90.32501 , 90.375   , 90.42499 , 90.475006,\n",
       "       90.524994, 90.57501 , 90.625   , 90.67499 , 90.725006, 90.774994,\n",
       "       90.82501 , 90.875   , 90.92499 , 90.975006, 91.024994, 91.07501 ,\n",
       "       91.125   , 91.17499 , 91.225006, 91.274994, 91.32501 , 91.375   ,\n",
       "       91.42499 , 91.475006, 91.524994, 91.57501 , 91.625   , 91.67499 ,\n",
       "       91.725006, 91.774994, 91.82501 , 91.875   , 91.92499 , 91.975006,\n",
       "       92.024994, 92.07501 , 92.125   , 92.17499 , 92.225006, 92.274994,\n",
       "       92.32501 , 92.375   , 92.42499 , 92.475006, 92.524994, 92.57501 ,\n",
       "       92.625   , 92.67499 , 92.725006, 92.774994, 92.82501 , 92.875   ,\n",
       "       92.92499 , 92.975006, 93.024994, 93.07501 , 93.125   , 93.17499 ,\n",
       "       93.225006, 93.274994, 93.32501 , 93.375   , 93.42499 , 93.475006,\n",
       "       93.524994, 93.57501 , 93.625   , 93.67499 , 93.725006, 93.774994,\n",
       "       93.82501 , 93.875   , 93.92499 , 93.975006], 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'>1981-06-01 ... 2005-09-01</div><input id='attrs-925238d6-43b8-42fe-b3cb-44ae3f6eabdf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-925238d6-43b8-42fe-b3cb-44ae3f6eabdf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0d59978b-86d6-4685-a738-e453b0fe36ad' class='xr-var-data-in' type='checkbox'><label for='data-0d59978b-86d6-4685-a738-e453b0fe36ad' 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>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-06-01T00:00:00.000000000&#x27;, &#x27;1981-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1981-08-01T00:00:00.000000000&#x27;, &#x27;1981-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1982-06-01T00:00:00.000000000&#x27;, &#x27;1982-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1982-08-01T00:00:00.000000000&#x27;, &#x27;1982-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1983-06-01T00:00:00.000000000&#x27;, &#x27;1983-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1983-08-01T00:00:00.000000000&#x27;, &#x27;1983-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1984-06-01T00:00:00.000000000&#x27;, &#x27;1984-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1984-08-01T00:00:00.000000000&#x27;, &#x27;1984-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1985-06-01T00:00:00.000000000&#x27;, &#x27;1985-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1985-08-01T00:00:00.000000000&#x27;, &#x27;1985-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1986-06-01T00:00:00.000000000&#x27;, &#x27;1986-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1986-08-01T00:00:00.000000000&#x27;, &#x27;1986-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1987-06-01T00:00:00.000000000&#x27;, &#x27;1987-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1987-08-01T00:00:00.000000000&#x27;, &#x27;1987-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1988-06-01T00:00:00.000000000&#x27;, &#x27;1988-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1988-08-01T00:00:00.000000000&#x27;, &#x27;1988-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1989-06-01T00:00:00.000000000&#x27;, &#x27;1989-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1989-08-01T00:00:00.000000000&#x27;, &#x27;1989-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1990-06-01T00:00:00.000000000&#x27;, &#x27;1990-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1990-08-01T00:00:00.000000000&#x27;, &#x27;1990-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1991-06-01T00:00:00.000000000&#x27;, &#x27;1991-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1991-08-01T00:00:00.000000000&#x27;, &#x27;1991-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1992-06-01T00:00:00.000000000&#x27;, &#x27;1992-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1992-08-01T00:00:00.000000000&#x27;, &#x27;1992-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1993-06-01T00:00:00.000000000&#x27;, &#x27;1993-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1993-08-01T00:00:00.000000000&#x27;, &#x27;1993-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1994-06-01T00:00:00.000000000&#x27;, &#x27;1994-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1994-08-01T00:00:00.000000000&#x27;, &#x27;1994-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1995-06-01T00:00:00.000000000&#x27;, &#x27;1995-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1995-08-01T00:00:00.000000000&#x27;, &#x27;1995-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1996-06-01T00:00:00.000000000&#x27;, &#x27;1996-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1996-08-01T00:00:00.000000000&#x27;, &#x27;1996-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1997-06-01T00:00:00.000000000&#x27;, &#x27;1997-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1997-08-01T00:00:00.000000000&#x27;, &#x27;1997-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-06-01T00:00:00.000000000&#x27;, &#x27;1998-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-08-01T00:00:00.000000000&#x27;, &#x27;1998-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-06-01T00:00:00.000000000&#x27;, &#x27;1999-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-08-01T00:00:00.000000000&#x27;, &#x27;1999-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-06-01T00:00:00.000000000&#x27;, &#x27;2000-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-08-01T00:00:00.000000000&#x27;, &#x27;2000-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-06-01T00:00:00.000000000&#x27;, &#x27;2001-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-08-01T00:00:00.000000000&#x27;, &#x27;2001-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-06-01T00:00:00.000000000&#x27;, &#x27;2002-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-08-01T00:00:00.000000000&#x27;, &#x27;2002-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-06-01T00:00:00.000000000&#x27;, &#x27;2003-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-08-01T00:00:00.000000000&#x27;, &#x27;2003-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-06-01T00:00:00.000000000&#x27;, &#x27;2004-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-08-01T00:00:00.000000000&#x27;, &#x27;2004-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-06-01T00:00:00.000000000&#x27;, &#x27;2005-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-08-01T00:00:00.000000000&#x27;, &#x27;2005-09-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4fda642a-11f8-4b83-a01e-a666fa85e4d3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4fda642a-11f8-4b83-a01e-a666fa85e4d3' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>precip</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f248b3e1-843f-4922-ac99-3e5826cb9955' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f248b3e1-843f-4922-ac99-3e5826cb9955' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06e47b0c-069e-496f-b9e9-aef36d414282' class='xr-var-data-in' type='checkbox'><label for='data-06e47b0c-069e-496f-b9e9-aef36d414282' 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>mm/month</dd><dt><span>standard_name :</span></dt><dd>convective precipitation rate</dd><dt><span>long_name :</span></dt><dd>Climate Hazards group InfraRed Precipitation with Stations</dd><dt><span>time_step :</span></dt><dd>month</dd><dt><span>geostatial_lat_min :</span></dt><dd>-50.0</dd><dt><span>geostatial_lat_max :</span></dt><dd>50.0</dd><dt><span>geostatial_lon_min :</span></dt><dd>-180.0</dd><dt><span>geostatial_lon_max :</span></dt><dd>180.0</dd></dl></div><div class='xr-var-data'><pre>[3200000 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a6d15b7a-cada-48a9-b74a-c5194beba57f' class='xr-section-summary-in' type='checkbox'  ><label for='section-a6d15b7a-cada-48a9-b74a-c5194beba57f' class='xr-section-summary' >Attributes: <span>(15)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>title :</span></dt><dd>CHIRPS Version 2.0</dd><dt><span>history :</span></dt><dd>created by Climate Hazards Group</dd><dt><span>version :</span></dt><dd>Version 2.0</dd><dt><span>date_created :</span></dt><dd>2022-05-16</dd><dt><span>creator_name :</span></dt><dd>Pete Peterson</dd><dt><span>creator_email :</span></dt><dd>pete@geog.ucsb.edu</dd><dt><span>institution :</span></dt><dd>Climate Hazards Group.  University of California at Santa Barbara</dd><dt><span>documentation :</span></dt><dd>http://pubs.usgs.gov/ds/832/</dd><dt><span>reference :</span></dt><dd>Funk, C.C., Peterson, P.J., Landsfeld, M.F., Pedreros, D.H., Verdin, J.P., Rowland, J.D., Romero, B.E., Husak, G.J., Michaelsen, J.C., and Verdin, A.P., 2014, A quasi-global precipitation time series for drought monitoring: U.S. Geological Survey Data Series 832, 4 p., http://dx.doi.org/110.3133/ds832. </dd><dt><span>comments :</span></dt><dd> time variable denotes the first day of the given month.</dd><dt><span>acknowledgements :</span></dt><dd>The Climate Hazards Group InfraRed Precipitation with Stations development process was carried out through U.S. Geological Survey (USGS) cooperative agreement #G09AC000001 &quot;Monitoring and Forecasting Climate, Water and Land Use for Food Production in the Developing World&quot; with funding from: U.S. Agency for International Development Office of Food for Peace, award #AID-FFP-P-10-00002 for &quot;Famine Early Warning Systems Network Support,&quot; the National Aeronautics and Space Administration Applied Sciences Program, Decisions award #NN10AN26I for &quot;A Land Data Assimilation System for Famine Early Warning,&quot; SERVIR award #NNH12AU22I for &quot;A Long Time-Series Indicator of Agricultural Drought for the Greater Horn of Africa,&quot; The National Oceanic and Atmospheric Administration award NA11OAR4310151 for &quot;A Global Standardized Precipitation Index supporting the US Drought Portal and the Famine Early Warning System Network,&quot; and the USGS Land Change Science Program.</dd><dt><span>ftp_url :</span></dt><dd>ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-latest/</dd><dt><span>website :</span></dt><dd>http://chg.geog.ucsb.edu/data/chirps/index.html</dd><dt><span>faq :</span></dt><dd>http://chg-wiki.geog.ucsb.edu/wiki/CHIRPS_FAQ</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (latitude: 200, longitude: 160, time: 100)\n",
       "Coordinates:\n",
       "  * latitude   (latitude) float32 18.02 18.07 18.12 18.17 ... 27.88 27.92 27.97\n",
       "  * longitude  (longitude) float32 86.02 86.08 86.12 86.17 ... 93.88 93.92 93.98\n",
       "  * time       (time) datetime64[ns] 1981-06-01 1981-07-01 ... 2005-09-01\n",
       "Data variables:\n",
       "    precip     (time, latitude, longitude) float32 ...\n",
       "Attributes: (12/15)\n",
       "    Conventions:       CF-1.6\n",
       "    title:             CHIRPS Version 2.0\n",
       "    history:           created by Climate Hazards Group\n",
       "    version:           Version 2.0\n",
       "    date_created:      2022-05-16\n",
       "    creator_name:      Pete Peterson\n",
       "    ...                ...\n",
       "    reference:         Funk, C.C., Peterson, P.J., Landsfeld, M.F., Pedreros,...\n",
       "    comments:           time variable denotes the first day of the given month.\n",
       "    acknowledgements:  The Climate Hazards Group InfraRed Precipitation with ...\n",
       "    ftp_url:           ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CH...\n",
       "    website:           http://chg.geog.ucsb.edu/data/chirps/index.html\n",
       "    faq:               http://chg-wiki.geog.ucsb.edu/wiki/CHIRPS_FAQ"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#to select the x and y coordinates\n",
    "jjas_data = jjas_data.sel(longitude=slice(86,94),latitude=slice(18,28))\n",
    "jjas_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "91600dec",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (time: 100, latitude: 40, longitude: 32)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1981-06-01 1981-07-01 ... 2005-09-01\n",
       "  * longitude  (longitude) float64 86.12 86.38 86.62 86.88 ... 93.38 93.62 93.88\n",
       "  * latitude   (latitude) float64 18.12 18.38 18.62 18.88 ... 27.38 27.62 27.88\n",
       "Data variables:\n",
       "    precip     (time, latitude, longitude) float64 nan nan nan ... 230.4 188.8\n",
       "Attributes: (12/15)\n",
       "    Conventions:       CF-1.6\n",
       "    title:             CHIRPS Version 2.0\n",
       "    history:           created by Climate Hazards Group\n",
       "    version:           Version 2.0\n",
       "    date_created:      2022-05-16\n",
       "    creator_name:      Pete Peterson\n",
       "    ...                ...\n",
       "    reference:         Funk, C.C., Peterson, P.J., Landsfeld, M.F., Pedreros,...\n",
       "    comments:           time variable denotes the first day of the given month.\n",
       "    acknowledgements:  The Climate Hazards Group InfraRed Precipitation with ...\n",
       "    ftp_url:           ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CH...\n",
       "    website:           http://chg.geog.ucsb.edu/data/chirps/index.html\n",
       "    faq:               http://chg-wiki.geog.ucsb.edu/wiki/CHIRPS_FAQ</pre><div class='xr-wrap' style='display:none'><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-5693ae09-01ee-443c-9c55-8888f4ef1d06' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5693ae09-01ee-443c-9c55-8888f4ef1d06' 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'>time</span>: 100</li><li><span class='xr-has-index'>latitude</span>: 40</li><li><span class='xr-has-index'>longitude</span>: 32</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-314aba9a-45c7-498a-9f50-bda264fb4cd8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-314aba9a-45c7-498a-9f50-bda264fb4cd8' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1981-06-01 ... 2005-09-01</div><input id='attrs-6248a1d7-2904-46dc-a016-a8fba105cf25' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6248a1d7-2904-46dc-a016-a8fba105cf25' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e565504b-a536-46a0-b9d3-2931ae0b7ec6' class='xr-var-data-in' type='checkbox'><label for='data-e565504b-a536-46a0-b9d3-2931ae0b7ec6' 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>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-06-01T00:00:00.000000000&#x27;, &#x27;1981-07-01T00:00:00.000000000&#x27;,\n",
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       "       &#x27;1982-06-01T00:00:00.000000000&#x27;, &#x27;1982-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1982-08-01T00:00:00.000000000&#x27;, &#x27;1982-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1983-06-01T00:00:00.000000000&#x27;, &#x27;1983-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1983-08-01T00:00:00.000000000&#x27;, &#x27;1983-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1984-06-01T00:00:00.000000000&#x27;, &#x27;1984-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1984-08-01T00:00:00.000000000&#x27;, &#x27;1984-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1985-06-01T00:00:00.000000000&#x27;, &#x27;1985-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1985-08-01T00:00:00.000000000&#x27;, &#x27;1985-09-01T00:00:00.000000000&#x27;,\n",
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       "       &#x27;1989-08-01T00:00:00.000000000&#x27;, &#x27;1989-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1990-06-01T00:00:00.000000000&#x27;, &#x27;1990-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1990-08-01T00:00:00.000000000&#x27;, &#x27;1990-09-01T00:00:00.000000000&#x27;,\n",
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       "       &#x27;1993-08-01T00:00:00.000000000&#x27;, &#x27;1993-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1994-06-01T00:00:00.000000000&#x27;, &#x27;1994-07-01T00:00:00.000000000&#x27;,\n",
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       "       &#x27;1995-06-01T00:00:00.000000000&#x27;, &#x27;1995-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1995-08-01T00:00:00.000000000&#x27;, &#x27;1995-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1996-06-01T00:00:00.000000000&#x27;, &#x27;1996-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1996-08-01T00:00:00.000000000&#x27;, &#x27;1996-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1997-06-01T00:00:00.000000000&#x27;, &#x27;1997-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1997-08-01T00:00:00.000000000&#x27;, &#x27;1997-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-06-01T00:00:00.000000000&#x27;, &#x27;1998-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-08-01T00:00:00.000000000&#x27;, &#x27;1998-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-06-01T00:00:00.000000000&#x27;, &#x27;1999-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-08-01T00:00:00.000000000&#x27;, &#x27;1999-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-06-01T00:00:00.000000000&#x27;, &#x27;2000-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-08-01T00:00:00.000000000&#x27;, &#x27;2000-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-06-01T00:00:00.000000000&#x27;, &#x27;2001-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-08-01T00:00:00.000000000&#x27;, &#x27;2001-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-06-01T00:00:00.000000000&#x27;, &#x27;2002-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-08-01T00:00:00.000000000&#x27;, &#x27;2002-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-06-01T00:00:00.000000000&#x27;, &#x27;2003-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-08-01T00:00:00.000000000&#x27;, &#x27;2003-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-06-01T00:00:00.000000000&#x27;, &#x27;2004-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-08-01T00:00:00.000000000&#x27;, &#x27;2004-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-06-01T00:00:00.000000000&#x27;, &#x27;2005-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-08-01T00:00:00.000000000&#x27;, &#x27;2005-09-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>86.12 86.38 86.62 ... 93.62 93.88</div><input id='attrs-9882a62c-7b1a-4c08-a9f5-084c06e99b8e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9882a62c-7b1a-4c08-a9f5-084c06e99b8e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1b94b2eb-f8ae-44c8-9617-0ad14f4332dc' class='xr-var-data-in' type='checkbox'><label for='data-1b94b2eb-f8ae-44c8-9617-0ad14f4332dc' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([86.125, 86.375, 86.625, 86.875, 87.125, 87.375, 87.625, 87.875, 88.125,\n",
       "       88.375, 88.625, 88.875, 89.125, 89.375, 89.625, 89.875, 90.125, 90.375,\n",
       "       90.625, 90.875, 91.125, 91.375, 91.625, 91.875, 92.125, 92.375, 92.625,\n",
       "       92.875, 93.125, 93.375, 93.625, 93.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>18.12 18.38 18.62 ... 27.62 27.88</div><input id='attrs-74b7c6e7-78bd-41d5-a7bd-18c2331ad9eb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-74b7c6e7-78bd-41d5-a7bd-18c2331ad9eb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2ca79c6d-de31-41fa-9955-d54e070b0743' class='xr-var-data-in' type='checkbox'><label for='data-2ca79c6d-de31-41fa-9955-d54e070b0743' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([18.125, 18.375, 18.625, 18.875, 19.125, 19.375, 19.625, 19.875, 20.125,\n",
       "       20.375, 20.625, 20.875, 21.125, 21.375, 21.625, 21.875, 22.125, 22.375,\n",
       "       22.625, 22.875, 23.125, 23.375, 23.625, 23.875, 24.125, 24.375, 24.625,\n",
       "       24.875, 25.125, 25.375, 25.625, 25.875, 26.125, 26.375, 26.625, 26.875,\n",
       "       27.125, 27.375, 27.625, 27.875])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3d4c8530-93a0-4be1-8376-4fd6bf2eadb1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3d4c8530-93a0-4be1-8376-4fd6bf2eadb1' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>precip</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan ... 208.5 230.4 188.8</div><input id='attrs-c2cea64f-c169-4224-aa0d-4458836a8a58' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c2cea64f-c169-4224-aa0d-4458836a8a58' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8022894b-e7ad-4bf9-8e43-1928e5903784' class='xr-var-data-in' type='checkbox'><label for='data-8022894b-e7ad-4bf9-8e43-1928e5903784' 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>mm/month</dd><dt><span>standard_name :</span></dt><dd>convective precipitation rate</dd><dt><span>long_name :</span></dt><dd>Climate Hazards group InfraRed Precipitation with Stations</dd><dt><span>time_step :</span></dt><dd>month</dd><dt><span>geostatial_lat_min :</span></dt><dd>-50.0</dd><dt><span>geostatial_lat_max :</span></dt><dd>50.0</dd><dt><span>geostatial_lon_min :</span></dt><dd>-180.0</dd><dt><span>geostatial_lon_max :</span></dt><dd>180.0</dd></dl></div><div class='xr-var-data'><pre>array([[[         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        ...,\n",
       "        [133.89678967, 155.46110532, 230.98037665, ..., 275.52331618,\n",
       "         343.28179751, 500.43109415],\n",
       "        [187.11347962, 170.78231825, 248.30453512, ..., 167.09231545,\n",
       "         271.63955545, 400.34378066],\n",
       "        [232.34280369, 195.6734621 , 180.99826108, ..., 257.23327569,\n",
       "         329.25540136, 348.66754211]],\n",
       "\n",
       "       [[         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "...\n",
       "        [317.9128418 , 325.17346252, 361.66577163, ..., 267.84558099,\n",
       "         378.7408752 , 505.20745976],\n",
       "        [334.98004119, 357.34854129, 338.02715959, ..., 177.84597796,\n",
       "         306.22396758, 368.70544426],\n",
       "        [265.13412583, 263.09451302, 248.95587142, ..., 265.85815445,\n",
       "         271.34133922, 337.71618602]],\n",
       "\n",
       "       [[         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        ...,\n",
       "        [129.80400081, 152.13278199, 168.69747921, ..., 186.04707333,\n",
       "         176.43499721, 214.51762374],\n",
       "        [144.49536137, 150.51913454, 171.27456695, ..., 198.60873465,\n",
       "         200.0690004 , 184.13995347],\n",
       "        [149.36831664, 139.73352042, 117.9748386 , ..., 208.46441619,\n",
       "         230.43916316, 188.80070521]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f7b29db8-4861-4c6f-9086-f99ee8e17259' class='xr-section-summary-in' type='checkbox'  ><label for='section-f7b29db8-4861-4c6f-9086-f99ee8e17259' class='xr-section-summary' >Attributes: <span>(15)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>title :</span></dt><dd>CHIRPS Version 2.0</dd><dt><span>history :</span></dt><dd>created by Climate Hazards Group</dd><dt><span>version :</span></dt><dd>Version 2.0</dd><dt><span>date_created :</span></dt><dd>2022-05-16</dd><dt><span>creator_name :</span></dt><dd>Pete Peterson</dd><dt><span>creator_email :</span></dt><dd>pete@geog.ucsb.edu</dd><dt><span>institution :</span></dt><dd>Climate Hazards Group.  University of California at Santa Barbara</dd><dt><span>documentation :</span></dt><dd>http://pubs.usgs.gov/ds/832/</dd><dt><span>reference :</span></dt><dd>Funk, C.C., Peterson, P.J., Landsfeld, M.F., Pedreros, D.H., Verdin, J.P., Rowland, J.D., Romero, B.E., Husak, G.J., Michaelsen, J.C., and Verdin, A.P., 2014, A quasi-global precipitation time series for drought monitoring: U.S. Geological Survey Data Series 832, 4 p., http://dx.doi.org/110.3133/ds832. </dd><dt><span>comments :</span></dt><dd> time variable denotes the first day of the given month.</dd><dt><span>acknowledgements :</span></dt><dd>The Climate Hazards Group InfraRed Precipitation with Stations development process was carried out through U.S. Geological Survey (USGS) cooperative agreement #G09AC000001 &quot;Monitoring and Forecasting Climate, Water and Land Use for Food Production in the Developing World&quot; with funding from: U.S. Agency for International Development Office of Food for Peace, award #AID-FFP-P-10-00002 for &quot;Famine Early Warning Systems Network Support,&quot; the National Aeronautics and Space Administration Applied Sciences Program, Decisions award #NN10AN26I for &quot;A Land Data Assimilation System for Famine Early Warning,&quot; SERVIR award #NNH12AU22I for &quot;A Long Time-Series Indicator of Agricultural Drought for the Greater Horn of Africa,&quot; The National Oceanic and Atmospheric Administration award NA11OAR4310151 for &quot;A Global Standardized Precipitation Index supporting the US Drought Portal and the Famine Early Warning System Network,&quot; and the USGS Land Change Science Program.</dd><dt><span>ftp_url :</span></dt><dd>ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-latest/</dd><dt><span>website :</span></dt><dd>http://chg.geog.ucsb.edu/data/chirps/index.html</dd><dt><span>faq :</span></dt><dd>http://chg-wiki.geog.ucsb.edu/wiki/CHIRPS_FAQ</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (time: 100, latitude: 40, longitude: 32)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1981-06-01 1981-07-01 ... 2005-09-01\n",
       "  * longitude  (longitude) float64 86.12 86.38 86.62 86.88 ... 93.38 93.62 93.88\n",
       "  * latitude   (latitude) float64 18.12 18.38 18.62 18.88 ... 27.38 27.62 27.88\n",
       "Data variables:\n",
       "    precip     (time, latitude, longitude) float64 nan nan nan ... 230.4 188.8\n",
       "Attributes: (12/15)\n",
       "    Conventions:       CF-1.6\n",
       "    title:             CHIRPS Version 2.0\n",
       "    history:           created by Climate Hazards Group\n",
       "    version:           Version 2.0\n",
       "    date_created:      2022-05-16\n",
       "    creator_name:      Pete Peterson\n",
       "    ...                ...\n",
       "    reference:         Funk, C.C., Peterson, P.J., Landsfeld, M.F., Pedreros,...\n",
       "    comments:           time variable denotes the first day of the given month.\n",
       "    acknowledgements:  The Climate Hazards Group InfraRed Precipitation with ...\n",
       "    ftp_url:           ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CH...\n",
       "    website:           http://chg.geog.ucsb.edu/data/chirps/index.html\n",
       "    faq:               http://chg-wiki.geog.ucsb.edu/wiki/CHIRPS_FAQ"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#interpolating to low resolution \n",
    "new_lon=np.arange(86.125,94,0.25)\n",
    "new_lat=np.arange(18.125,28,0.25)\n",
    "jjas_data = jjas_data.interp(longitude=new_lon,latitude=new_lat)\n",
    "jjas_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "82d6b5d0",
   "metadata": {},
   "outputs": [
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       "\n",
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       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
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       "  padding-right: 10px;\n",
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       "\n",
       ".xr-attrs dd {\n",
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       "\n",
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       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;precip&#x27; (latitude: 40, longitude: 32)&gt;\n",
       "array([[         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       ...,\n",
       "       [248.97755746, 275.25243237, 338.84412051, ..., 204.03614269,\n",
       "        273.31148617, 398.09106593],\n",
       "       [313.03271648, 304.99211103, 340.83162938, ..., 159.18378847,\n",
       "        245.99790446, 286.82859665],\n",
       "       [300.33862553, 273.78465937, 231.7827732 , ..., 220.4120115 ,\n",
       "        251.78057764, 284.67563868]])\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float64 86.12 86.38 86.62 86.88 ... 93.38 93.62 93.88\n",
       "  * latitude   (latitude) float64 18.12 18.38 18.62 18.88 ... 27.38 27.62 27.88</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'precip'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>latitude</span>: 40</li><li><span class='xr-has-index'>longitude</span>: 32</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-8cde3d9d-be7c-47cd-88b0-5389d897f506' class='xr-array-in' type='checkbox' checked><label for='section-8cde3d9d-be7c-47cd-88b0-5389d897f506' 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>nan nan nan nan nan nan nan ... 74.31 103.7 151.5 220.4 251.8 284.7</span></div><div class='xr-array-data'><pre>array([[         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       ...,\n",
       "       [248.97755746, 275.25243237, 338.84412051, ..., 204.03614269,\n",
       "        273.31148617, 398.09106593],\n",
       "       [313.03271648, 304.99211103, 340.83162938, ..., 159.18378847,\n",
       "        245.99790446, 286.82859665],\n",
       "       [300.33862553, 273.78465937, 231.7827732 , ..., 220.4120115 ,\n",
       "        251.78057764, 284.67563868]])</pre></div></div></li><li class='xr-section-item'><input id='section-f014250d-a136-4256-acdb-01c14415e08a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f014250d-a136-4256-acdb-01c14415e08a' class='xr-section-summary' >Coordinates: <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 class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>86.12 86.38 86.62 ... 93.62 93.88</div><input id='attrs-701b50e9-691a-401b-a3fc-353b4f915287' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-701b50e9-691a-401b-a3fc-353b4f915287' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-feba456e-50a9-49ef-ba15-3f31e1adf6dd' class='xr-var-data-in' type='checkbox'><label for='data-feba456e-50a9-49ef-ba15-3f31e1adf6dd' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([86.125, 86.375, 86.625, 86.875, 87.125, 87.375, 87.625, 87.875, 88.125,\n",
       "       88.375, 88.625, 88.875, 89.125, 89.375, 89.625, 89.875, 90.125, 90.375,\n",
       "       90.625, 90.875, 91.125, 91.375, 91.625, 91.875, 92.125, 92.375, 92.625,\n",
       "       92.875, 93.125, 93.375, 93.625, 93.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>18.12 18.38 18.62 ... 27.62 27.88</div><input id='attrs-a058935b-751e-4683-9418-0e6bd82d1b04' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a058935b-751e-4683-9418-0e6bd82d1b04' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec818755-89b1-4b08-8121-d930f3134d2b' class='xr-var-data-in' type='checkbox'><label for='data-ec818755-89b1-4b08-8121-d930f3134d2b' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([18.125, 18.375, 18.625, 18.875, 19.125, 19.375, 19.625, 19.875, 20.125,\n",
       "       20.375, 20.625, 20.875, 21.125, 21.375, 21.625, 21.875, 22.125, 22.375,\n",
       "       22.625, 22.875, 23.125, 23.375, 23.625, 23.875, 24.125, 24.375, 24.625,\n",
       "       24.875, 25.125, 25.375, 25.625, 25.875, 26.125, 26.375, 26.625, 26.875,\n",
       "       27.125, 27.375, 27.625, 27.875])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6a888f3f-848d-4ca6-bf4e-0f775b108aeb' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6a888f3f-848d-4ca6-bf4e-0f775b108aeb' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'precip' (latitude: 40, longitude: 32)>\n",
       "array([[         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       ...,\n",
       "       [248.97755746, 275.25243237, 338.84412051, ..., 204.03614269,\n",
       "        273.31148617, 398.09106593],\n",
       "       [313.03271648, 304.99211103, 340.83162938, ..., 159.18378847,\n",
       "        245.99790446, 286.82859665],\n",
       "       [300.33862553, 273.78465937, 231.7827732 , ..., 220.4120115 ,\n",
       "        251.78057764, 284.67563868]])\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float64 86.12 86.38 86.62 86.88 ... 93.38 93.62 93.88\n",
       "  * latitude   (latitude) float64 18.12 18.38 18.62 18.88 ... 27.38 27.62 27.88"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#getting the mean for JJAS data\n",
    "jjas_mean = jjas_data.precip.mean('time')\n",
    " \n",
    "jjas_mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6d00cba7",
   "metadata": {},
   "outputs": [],
   "source": [
    "#changing unit from mm/month to mm/day\n",
    "pr_mm = jjas_mean/30.4167\n",
    "\n",
    "\n",
    "\n",
    "chirps = pr_mm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b6d9b2b3",
   "metadata": {},
   "outputs": [
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       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (time: 1872, bnds: 2, longitude: 32, latitude: 40)\n",
       "Coordinates:\n",
       "  * time       (time) object 1850-01-16 12:00:00 ... 2005-12-16 12:00:00\n",
       "  * longitude  (longitude) float32 86.12 86.38 86.62 86.88 ... 93.38 93.62 93.88\n",
       "  * latitude   (latitude) float32 18.12 18.38 18.62 18.88 ... 27.38 27.62 27.88\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1850-01-01 00:00:00 ... 2006-01-01 00:00:00\n",
       "    pr         (time, latitude, longitude) float32 ...\n",
       "Attributes: (12/29)\n",
       "    CDI:                    Climate Data Interface version 1.9.9rc1 (https://...\n",
       "    Conventions:            CF-1.4\n",
       "    history:                Fri Jul 22 11:51:46 2022: cdo remapnn,grid.des gc...\n",
       "    source:                 MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); oce...\n",
       "    institution:            AORI (Atmosphere and Ocean Research Institute, Th...\n",
       "    institute_id:           MIROC\n",
       "    ...                     ...\n",
       "    title:                  MIROC5 model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.5.6\n",
       "    CDO:                    Climate Data Operators version 1.9.9rc1 (https://...</pre><div class='xr-wrap' style='display:none'><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-a3ee2f9a-b2ce-491b-85f6-09fa881a6fb5' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a3ee2f9a-b2ce-491b-85f6-09fa881a6fb5' 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'>time</span>: 1872</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>longitude</span>: 32</li><li><span class='xr-has-index'>latitude</span>: 40</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-9e7bd983-0afc-485d-92ba-6818cfc091e1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9e7bd983-0afc-485d-92ba-6818cfc091e1' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-16 12:00:00 ... 2005-12-...</div><input id='attrs-b32ea52d-ed70-4a6b-b559-670c8acba6c0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b32ea52d-ed70-4a6b-b559-670c8acba6c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c94c0827-d821-4bb5-b473-87c7c0c304ea' class='xr-var-data-in' type='checkbox'><label for='data-c94c0827-d821-4bb5-b473-87c7c0c304ea' 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>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1850, 1, 16, 12, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(1850, 2, 15, 0, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(1850, 3, 16, 12, 0, 0, 0, has_year_zero=True),\n",
       "       ...,\n",
       "       cftime.DatetimeNoLeap(2005, 10, 16, 12, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2005, 11, 16, 0, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2005, 12, 16, 12, 0, 0, 0, has_year_zero=True)],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>86.12 86.38 86.62 ... 93.62 93.88</div><input id='attrs-57649878-cb0c-452c-9027-87c62262e403' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-57649878-cb0c-452c-9027-87c62262e403' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-57d68fe0-152a-4afc-b237-582d1296d1ed' class='xr-var-data-in' type='checkbox'><label for='data-57d68fe0-152a-4afc-b237-582d1296d1ed' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([86.125, 86.375, 86.625, 86.875, 87.125, 87.375, 87.625, 87.875, 88.125,\n",
       "       88.375, 88.625, 88.875, 89.125, 89.375, 89.625, 89.875, 90.125, 90.375,\n",
       "       90.625, 90.875, 91.125, 91.375, 91.625, 91.875, 92.125, 92.375, 92.625,\n",
       "       92.875, 93.125, 93.375, 93.625, 93.875], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>18.12 18.38 18.62 ... 27.62 27.88</div><input id='attrs-98cc107a-3fda-42e1-849e-2294ac66c7d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-98cc107a-3fda-42e1-849e-2294ac66c7d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2f8b7af6-ac8c-41bc-ad60-4be1f6c4e109' class='xr-var-data-in' type='checkbox'><label for='data-2f8b7af6-ac8c-41bc-ad60-4be1f6c4e109' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([18.125, 18.375, 18.625, 18.875, 19.125, 19.375, 19.625, 19.875, 20.125,\n",
       "       20.375, 20.625, 20.875, 21.125, 21.375, 21.625, 21.875, 22.125, 22.375,\n",
       "       22.625, 22.875, 23.125, 23.375, 23.625, 23.875, 24.125, 24.375, 24.625,\n",
       "       24.875, 25.125, 25.375, 25.625, 25.875, 26.125, 26.375, 26.625, 26.875,\n",
       "       27.125, 27.375, 27.625, 27.875], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-35c16913-7fc8-4445-bdd1-a58b4d6ca025' class='xr-section-summary-in' type='checkbox'  checked><label for='section-35c16913-7fc8-4445-bdd1-a58b4d6ca025' 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, bnds)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-57062464-7214-4242-a7b2-2b0ad22850a9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-57062464-7214-4242-a7b2-2b0ad22850a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-39633e56-e282-4432-9706-0f2d57a647bf' class='xr-var-data-in' type='checkbox'><label for='data-39633e56-e282-4432-9706-0f2d57a647bf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[cftime.DatetimeNoLeap(1850, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1850, 2, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1850, 2, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1850, 3, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1850, 3, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1850, 4, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       ...,\n",
       "       [cftime.DatetimeNoLeap(2005, 10, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 11, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 11, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 12, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 12, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2006, 1, 1, 0, 0, 0, 0, has_year_zero=True)]],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pr</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8d84ebea-f24a-4281-b13d-4ea531e04c19' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8d84ebea-f24a-4281-b13d-4ea531e04c19' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-683db47f-b396-4cd5-9b9d-6dae2bb2f277' class='xr-var-data-in' type='checkbox'><label for='data-683db47f-b396-4cd5-9b9d-6dae2bb2f277' 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>standard_name :</span></dt><dd>precipitation_flux</dd><dt><span>long_name :</span></dt><dd>Precipitation</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>comment :</span></dt><dd>at surface; includes both liquid and solid phases from all types of clouds (both large-scale and convective)</dd><dt><span>original_name :</span></dt><dd>PRCP</dd><dt><span>original_units :</span></dt><dd>kg/m**2/s</dd><dt><span>history :</span></dt><dd>2011-04-23T09:11:46Z altered by CMOR: Converted units from &#x27;kg/m**2/s&#x27; to &#x27;kg m-2 s-1&#x27;. 2011-04-23T09:11:46Z altered by CMOR: replaced missing value flag (-999) with standard missing value (1e+20). 2011-04-23T09:11:46Z altered by CMOR: Inverted axis: lat.</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>associated_files :</span></dt><dd>baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_MIROC5_historical_r0i0p0.nc areacella: areacella_fx_MIROC5_historical_r0i0p0.nc</dd></dl></div><div class='xr-var-data'><pre>[2396160 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7ba253f4-2cf6-49cc-b92e-573b55d22758' class='xr-section-summary-in' type='checkbox'  ><label for='section-7ba253f4-2cf6-49cc-b92e-573b55d22758' class='xr-section-summary' >Attributes: <span>(29)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 1.9.9rc1 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>history :</span></dt><dd>Fri Jul 22 11:51:46 2022: cdo remapnn,grid.des gcmensemble.nc gcmensemble_remap1.nc\n",
       "Fri Jul 22 11:00:06 2022: cdo divc,3 final.nc gcmensemble.nc\n",
       "Fri Jul 22 10:53:46 2022: cdo -add gcm_miroc_remap1.nc -add gcm_mpi_remap.nc gcm_noresm_remap.nc final.nc\n",
       "Fri Jul 22 10:53:11 2022: cdo selyear,1850/2005 gcm_miroc_remap.nc gcm_miroc_remap1.nc\n",
       "Thu Jul 07 18:16:03 2022: cdo remapnn,grid1.des pr_Amon_MIROC5_historical_r1i1p1_185001-201212.nc gcm_miroc_remap.nc\n",
       "2011-04-23T09:11:46Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.</dd><dt><span>source :</span></dt><dd>MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); ocean: COCO (COCO4.5, 256x224 L50); sea ice: COCO (COCO4.5); land: MATSIRO (MATSIRO, L6); aerosols: SPRINTARS (SPRINTARS 5.00, T85L40)</dd><dt><span>institution :</span></dt><dd>AORI (Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba, Japan), NIES (National Institute for Environmental Studies, Ibaraki, Japan), JAMSTEC (Japan Agency for Marine-Earth Science and Technology, Kanagawa, Japan)</dd><dt><span>institute_id :</span></dt><dd>MIROC</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>model_id :</span></dt><dd>MIROC5</dd><dt><span>forcing :</span></dt><dd>GHG, SA, Oz, LU, Sl, Vl, SS, Ds, BC, MD, OC (GHG includes CO2, N2O, methane, and fluorocarbons; Oz includes OH and H2O2; LU excludes change in lake fraction)</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_experiment_rip :</span></dt><dd>r1i1p1</dd><dt><span>branch_time :</span></dt><dd>150015.0</dd><dt><span>contact :</span></dt><dd>Masahiro Watanabe (hiro@aori.u-tokyo.ac.jp), Seita Emori (emori@nies.go.jp), Masayoshi Ishii (ism@jamstec.go.jp), Masahide Kimoto (kimoto@aori.u-tokyo.ac.jp)</dd><dt><span>references :</span></dt><dd>Watanabe et al., 2010: Improved climate simulation by MIROC5: Mean states, variability, and climate sensitivity. J. Climate, 23, 6312-6335</dd><dt><span>initialization_method :</span></dt><dd>1</dd><dt><span>physics_version :</span></dt><dd>1</dd><dt><span>tracking_id :</span></dt><dd>a906be44-c850-4f0c-b8c4-2b165051669a</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>experiment :</span></dt><dd>historical</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>creation_date :</span></dt><dd>2011-04-23T09:11:46Z</dd><dt><span>project_id :</span></dt><dd>CMIP5</dd><dt><span>table_id :</span></dt><dd>Table Amon (31 January 2011) 53b766a395ac41696af40aab76a49ae5</dd><dt><span>title :</span></dt><dd>MIROC5 model output prepared for CMIP5 historical</dd><dt><span>parent_experiment :</span></dt><dd>pre-industrial control</dd><dt><span>modeling_realm :</span></dt><dd>atmos</dd><dt><span>realization :</span></dt><dd>1</dd><dt><span>cmor_version :</span></dt><dd>2.5.6</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 1.9.9rc1 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
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       "    pr         (time, latitude, longitude) float32 ...\n",
       "Attributes: (12/29)\n",
       "    CDI:                    Climate Data Interface version 1.9.9rc1 (https://...\n",
       "    Conventions:            CF-1.4\n",
       "    history:                Fri Jul 22 11:51:46 2022: cdo remapnn,grid.des gc...\n",
       "    source:                 MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); oce...\n",
       "    institution:            AORI (Atmosphere and Ocean Research Institute, Th...\n",
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     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#opening gcm miroc5 data\n",
    "\n",
    "data = xr.open_dataset('/home/mkibria/Academic/pr_of_thesis/GCM/ensemble-average/gcmensemble_remap1.nc')\n",
    "\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "5cbdbd2f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/mkibria/miniconda3/envs/esp-sp/lib/python3.9/site-packages/xarray/coding/times.py:351: FutureWarning: Index.ravel returning ndarray is deprecated; in a future version this will return a view on self.\n",
      "  sample = dates.ravel()[0]\n",
      "/tmp/ipykernel_9728/3137857967.py:3: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, 'noleap', to a pandas.DatetimeIndex, which uses dates from the standard calendar.  This may lead to subtle errors in operations that depend on the length of time between dates.\n",
      "  datetimeindex = data.indexes['time'].to_datetimeindex()\n"
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       "Dimensions:    (time: 1872, bnds: 2, longitude: 32, latitude: 40)\n",
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       "Attributes: (12/29)\n",
       "    CDI:                    Climate Data Interface version 1.9.9rc1 (https://...\n",
       "    Conventions:            CF-1.4\n",
       "    history:                Fri Jul 22 11:51:46 2022: cdo remapnn,grid.des gc...\n",
       "    source:                 MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); oce...\n",
       "    institution:            AORI (Atmosphere and Ocean Research Institute, Th...\n",
       "    institute_id:           MIROC\n",
       "    ...                     ...\n",
       "    title:                  MIROC5 model output prepared for CMIP5 historical\n",
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       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.5.6\n",
       "    CDO:                    Climate Data Operators version 1.9.9rc1 (https://...</pre><div class='xr-wrap' style='display:none'><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-50e2c348-fd80-4bc5-9822-b8cd52c819f0' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-50e2c348-fd80-4bc5-9822-b8cd52c819f0' 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'>time</span>: 1872</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>longitude</span>: 32</li><li><span class='xr-has-index'>latitude</span>: 40</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-c6856551-159d-4471-a292-766f39ae52df' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c6856551-159d-4471-a292-766f39ae52df' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1850-01-16T12:00:00 ... 2005-12-...</div><input id='attrs-aa2dbd78-0f26-442c-8759-306290059fef' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-aa2dbd78-0f26-442c-8759-306290059fef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a1f2cbea-92ff-4d9c-84c5-dc9acb202717' class='xr-var-data-in' type='checkbox'><label for='data-a1f2cbea-92ff-4d9c-84c5-dc9acb202717' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1850-01-16T12:00:00.000000000&#x27;, &#x27;1850-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;1850-03-16T12:00:00.000000000&#x27;, ..., &#x27;2005-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2005-11-16T00:00:00.000000000&#x27;, &#x27;2005-12-16T12:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>86.12 86.38 86.62 ... 93.62 93.88</div><input id='attrs-43ed0074-3ae1-4f53-826b-0197bb773046' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-43ed0074-3ae1-4f53-826b-0197bb773046' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4123d6f4-93fb-4a06-b7d4-422ede9becba' class='xr-var-data-in' type='checkbox'><label for='data-4123d6f4-93fb-4a06-b7d4-422ede9becba' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([86.125, 86.375, 86.625, 86.875, 87.125, 87.375, 87.625, 87.875, 88.125,\n",
       "       88.375, 88.625, 88.875, 89.125, 89.375, 89.625, 89.875, 90.125, 90.375,\n",
       "       90.625, 90.875, 91.125, 91.375, 91.625, 91.875, 92.125, 92.375, 92.625,\n",
       "       92.875, 93.125, 93.375, 93.625, 93.875], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>18.12 18.38 18.62 ... 27.62 27.88</div><input id='attrs-388f1249-4b37-4309-a5ca-5b6a0795263d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-388f1249-4b37-4309-a5ca-5b6a0795263d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ea335c6d-b9e2-4224-a579-e275884a0d5a' class='xr-var-data-in' type='checkbox'><label for='data-ea335c6d-b9e2-4224-a579-e275884a0d5a' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([18.125, 18.375, 18.625, 18.875, 19.125, 19.375, 19.625, 19.875, 20.125,\n",
       "       20.375, 20.625, 20.875, 21.125, 21.375, 21.625, 21.875, 22.125, 22.375,\n",
       "       22.625, 22.875, 23.125, 23.375, 23.625, 23.875, 24.125, 24.375, 24.625,\n",
       "       24.875, 25.125, 25.375, 25.625, 25.875, 26.125, 26.375, 26.625, 26.875,\n",
       "       27.125, 27.375, 27.625, 27.875], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-16682e28-2ad9-4e6d-81fb-007a3c35c631' class='xr-section-summary-in' type='checkbox'  checked><label for='section-16682e28-2ad9-4e6d-81fb-007a3c35c631' 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, bnds)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-01 00:00:00 ... 2006-01-...</div><input id='attrs-2bf2dbb5-27e1-4977-b937-a5cb9b6354f3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2bf2dbb5-27e1-4977-b937-a5cb9b6354f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab3eb866-390b-401e-bcc4-f0116cb6faea' class='xr-var-data-in' type='checkbox'><label for='data-ab3eb866-390b-401e-bcc4-f0116cb6faea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[cftime.DatetimeNoLeap(1850, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1850, 2, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1850, 2, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1850, 3, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1850, 3, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1850, 4, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       ...,\n",
       "       [cftime.DatetimeNoLeap(2005, 10, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 11, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 11, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 12, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 12, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2006, 1, 1, 0, 0, 0, 0, has_year_zero=True)]],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pr</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a57f9f04-df45-4c0d-94df-5fc6ee3de056' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a57f9f04-df45-4c0d-94df-5fc6ee3de056' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-41fc39e0-7636-4a72-90f7-d3fd5421275e' class='xr-var-data-in' type='checkbox'><label for='data-41fc39e0-7636-4a72-90f7-d3fd5421275e' 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>standard_name :</span></dt><dd>precipitation_flux</dd><dt><span>long_name :</span></dt><dd>Precipitation</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>comment :</span></dt><dd>at surface; includes both liquid and solid phases from all types of clouds (both large-scale and convective)</dd><dt><span>original_name :</span></dt><dd>PRCP</dd><dt><span>original_units :</span></dt><dd>kg/m**2/s</dd><dt><span>history :</span></dt><dd>2011-04-23T09:11:46Z altered by CMOR: Converted units from &#x27;kg/m**2/s&#x27; to &#x27;kg m-2 s-1&#x27;. 2011-04-23T09:11:46Z altered by CMOR: replaced missing value flag (-999) with standard missing value (1e+20). 2011-04-23T09:11:46Z altered by CMOR: Inverted axis: lat.</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>associated_files :</span></dt><dd>baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_MIROC5_historical_r0i0p0.nc areacella: areacella_fx_MIROC5_historical_r0i0p0.nc</dd></dl></div><div class='xr-var-data'><pre>[2396160 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5a213d83-a5f3-4e1e-b4b8-e2b48769d76c' class='xr-section-summary-in' type='checkbox'  ><label for='section-5a213d83-a5f3-4e1e-b4b8-e2b48769d76c' class='xr-section-summary' >Attributes: <span>(29)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 1.9.9rc1 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>history :</span></dt><dd>Fri Jul 22 11:51:46 2022: cdo remapnn,grid.des gcmensemble.nc gcmensemble_remap1.nc\n",
       "Fri Jul 22 11:00:06 2022: cdo divc,3 final.nc gcmensemble.nc\n",
       "Fri Jul 22 10:53:46 2022: cdo -add gcm_miroc_remap1.nc -add gcm_mpi_remap.nc gcm_noresm_remap.nc final.nc\n",
       "Fri Jul 22 10:53:11 2022: cdo selyear,1850/2005 gcm_miroc_remap.nc gcm_miroc_remap1.nc\n",
       "Thu Jul 07 18:16:03 2022: cdo remapnn,grid1.des pr_Amon_MIROC5_historical_r1i1p1_185001-201212.nc gcm_miroc_remap.nc\n",
       "2011-04-23T09:11:46Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.</dd><dt><span>source :</span></dt><dd>MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); ocean: COCO (COCO4.5, 256x224 L50); sea ice: COCO (COCO4.5); land: MATSIRO (MATSIRO, L6); aerosols: SPRINTARS (SPRINTARS 5.00, T85L40)</dd><dt><span>institution :</span></dt><dd>AORI (Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba, Japan), NIES (National Institute for Environmental Studies, Ibaraki, Japan), JAMSTEC (Japan Agency for Marine-Earth Science and Technology, Kanagawa, Japan)</dd><dt><span>institute_id :</span></dt><dd>MIROC</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>model_id :</span></dt><dd>MIROC5</dd><dt><span>forcing :</span></dt><dd>GHG, SA, Oz, LU, Sl, Vl, SS, Ds, BC, MD, OC (GHG includes CO2, N2O, methane, and fluorocarbons; Oz includes OH and H2O2; LU excludes change in lake fraction)</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_experiment_rip :</span></dt><dd>r1i1p1</dd><dt><span>branch_time :</span></dt><dd>150015.0</dd><dt><span>contact :</span></dt><dd>Masahiro Watanabe (hiro@aori.u-tokyo.ac.jp), Seita Emori (emori@nies.go.jp), Masayoshi Ishii (ism@jamstec.go.jp), Masahide Kimoto (kimoto@aori.u-tokyo.ac.jp)</dd><dt><span>references :</span></dt><dd>Watanabe et al., 2010: Improved climate simulation by MIROC5: Mean states, variability, and climate sensitivity. J. Climate, 23, 6312-6335</dd><dt><span>initialization_method :</span></dt><dd>1</dd><dt><span>physics_version :</span></dt><dd>1</dd><dt><span>tracking_id :</span></dt><dd>a906be44-c850-4f0c-b8c4-2b165051669a</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>experiment :</span></dt><dd>historical</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>creation_date :</span></dt><dd>2011-04-23T09:11:46Z</dd><dt><span>project_id :</span></dt><dd>CMIP5</dd><dt><span>table_id :</span></dt><dd>Table Amon (31 January 2011) 53b766a395ac41696af40aab76a49ae5</dd><dt><span>title :</span></dt><dd>MIROC5 model output prepared for CMIP5 historical</dd><dt><span>parent_experiment :</span></dt><dd>pre-industrial control</dd><dt><span>modeling_realm :</span></dt><dd>atmos</dd><dt><span>realization :</span></dt><dd>1</dd><dt><span>cmor_version :</span></dt><dd>2.5.6</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 1.9.9rc1 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (time: 1872, bnds: 2, longitude: 32, latitude: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1850-01-16T12:00:00 ... 2005-12-16T12:00:00\n",
       "  * longitude  (longitude) float32 86.12 86.38 86.62 86.88 ... 93.38 93.62 93.88\n",
       "  * latitude   (latitude) float32 18.12 18.38 18.62 18.88 ... 27.38 27.62 27.88\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1850-01-01 00:00:00 ... 2006-01-01 00:00:00\n",
       "    pr         (time, latitude, longitude) float32 ...\n",
       "Attributes: (12/29)\n",
       "    CDI:                    Climate Data Interface version 1.9.9rc1 (https://...\n",
       "    Conventions:            CF-1.4\n",
       "    history:                Fri Jul 22 11:51:46 2022: cdo remapnn,grid.des gc...\n",
       "    source:                 MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); oce...\n",
       "    institution:            AORI (Atmosphere and Ocean Research Institute, Th...\n",
       "    institute_id:           MIROC\n",
       "    ...                     ...\n",
       "    title:                  MIROC5 model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.5.6\n",
       "    CDO:                    Climate Data Operators version 1.9.9rc1 (https://..."
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#changing time dim to datetime64[ns] dtype\n",
    "\n",
    "datetimeindex = data.indexes['time'].to_datetimeindex()\n",
    "data['time']=datetimeindex\n",
    "data\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "cafd5692",
   "metadata": {},
   "outputs": [
    {
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       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (time: 299, bnds: 2, longitude: 32, latitude: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1981-01-16T12:00:00 ... 2005-11-16\n",
       "  * longitude  (longitude) float32 86.12 86.38 86.62 86.88 ... 93.38 93.62 93.88\n",
       "  * latitude   (latitude) float32 18.12 18.38 18.62 18.88 ... 27.38 27.62 27.88\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1981-01-01 00:00:00 ... 2005-12-01 00:00:00\n",
       "    pr         (time, latitude, longitude) float32 ...\n",
       "Attributes: (12/29)\n",
       "    CDI:                    Climate Data Interface version 1.9.9rc1 (https://...\n",
       "    Conventions:            CF-1.4\n",
       "    history:                Fri Jul 22 11:51:46 2022: cdo remapnn,grid.des gc...\n",
       "    source:                 MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); oce...\n",
       "    institution:            AORI (Atmosphere and Ocean Research Institute, Th...\n",
       "    institute_id:           MIROC\n",
       "    ...                     ...\n",
       "    title:                  MIROC5 model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.5.6\n",
       "    CDO:                    Climate Data Operators version 1.9.9rc1 (https://...</pre><div class='xr-wrap' style='display:none'><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-9899c75b-b5a4-464b-a834-e9250fe48dbc' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9899c75b-b5a4-464b-a834-e9250fe48dbc' 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'>time</span>: 299</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>longitude</span>: 32</li><li><span class='xr-has-index'>latitude</span>: 40</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-3592a418-fb7d-43bb-b4ab-88c62a6277e3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3592a418-fb7d-43bb-b4ab-88c62a6277e3' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1981-01-16T12:00:00 ... 2005-11-16</div><input id='attrs-2b0cb478-dc7a-4687-a7cb-94f32c9cdafa' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2b0cb478-dc7a-4687-a7cb-94f32c9cdafa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-312080f0-4e2a-4f83-8a88-33dd11d0f870' class='xr-var-data-in' type='checkbox'><label for='data-312080f0-4e2a-4f83-8a88-33dd11d0f870' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-01-16T12:00:00.000000000&#x27;, &#x27;1981-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;1981-03-16T12:00:00.000000000&#x27;, ..., &#x27;2005-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-10-16T12:00:00.000000000&#x27;, &#x27;2005-11-16T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>86.12 86.38 86.62 ... 93.62 93.88</div><input id='attrs-e7acb084-0b01-4170-a68c-66561b74edb5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e7acb084-0b01-4170-a68c-66561b74edb5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-78b4daa3-6114-423f-b121-1ad6e4e08644' class='xr-var-data-in' type='checkbox'><label for='data-78b4daa3-6114-423f-b121-1ad6e4e08644' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([86.125, 86.375, 86.625, 86.875, 87.125, 87.375, 87.625, 87.875, 88.125,\n",
       "       88.375, 88.625, 88.875, 89.125, 89.375, 89.625, 89.875, 90.125, 90.375,\n",
       "       90.625, 90.875, 91.125, 91.375, 91.625, 91.875, 92.125, 92.375, 92.625,\n",
       "       92.875, 93.125, 93.375, 93.625, 93.875], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>18.12 18.38 18.62 ... 27.62 27.88</div><input id='attrs-96220a4c-8634-4826-b722-f7443cb78ee0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-96220a4c-8634-4826-b722-f7443cb78ee0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-024852c3-fdec-4586-9396-c955236eb3c0' class='xr-var-data-in' type='checkbox'><label for='data-024852c3-fdec-4586-9396-c955236eb3c0' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([18.125, 18.375, 18.625, 18.875, 19.125, 19.375, 19.625, 19.875, 20.125,\n",
       "       20.375, 20.625, 20.875, 21.125, 21.375, 21.625, 21.875, 22.125, 22.375,\n",
       "       22.625, 22.875, 23.125, 23.375, 23.625, 23.875, 24.125, 24.375, 24.625,\n",
       "       24.875, 25.125, 25.375, 25.625, 25.875, 26.125, 26.375, 26.625, 26.875,\n",
       "       27.125, 27.375, 27.625, 27.875], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2a457c82-50ab-4bf2-945e-7938216eb801' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2a457c82-50ab-4bf2-945e-7938216eb801' 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, bnds)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1981-01-01 00:00:00 ... 2005-12-...</div><input id='attrs-2877a839-6861-4973-9545-da2ecd3af4a8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2877a839-6861-4973-9545-da2ecd3af4a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-df25cd78-228b-4083-bcf1-ded8bfe965ed' class='xr-var-data-in' type='checkbox'><label for='data-df25cd78-228b-4083-bcf1-ded8bfe965ed' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[cftime.DatetimeNoLeap(1981, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1981, 2, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1981, 2, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1981, 3, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1981, 3, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1981, 4, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       ...,\n",
       "       [cftime.DatetimeNoLeap(2005, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 10, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 11, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 11, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 12, 1, 0, 0, 0, 0, has_year_zero=True)]],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pr</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-407a6613-ef1a-4862-8094-1036e614d3d9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-407a6613-ef1a-4862-8094-1036e614d3d9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b927077-8b4c-4b65-892f-b8ff7d34c19f' class='xr-var-data-in' type='checkbox'><label for='data-4b927077-8b4c-4b65-892f-b8ff7d34c19f' 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>standard_name :</span></dt><dd>precipitation_flux</dd><dt><span>long_name :</span></dt><dd>Precipitation</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>comment :</span></dt><dd>at surface; includes both liquid and solid phases from all types of clouds (both large-scale and convective)</dd><dt><span>original_name :</span></dt><dd>PRCP</dd><dt><span>original_units :</span></dt><dd>kg/m**2/s</dd><dt><span>history :</span></dt><dd>2011-04-23T09:11:46Z altered by CMOR: Converted units from &#x27;kg/m**2/s&#x27; to &#x27;kg m-2 s-1&#x27;. 2011-04-23T09:11:46Z altered by CMOR: replaced missing value flag (-999) with standard missing value (1e+20). 2011-04-23T09:11:46Z altered by CMOR: Inverted axis: lat.</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>associated_files :</span></dt><dd>baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_MIROC5_historical_r0i0p0.nc areacella: areacella_fx_MIROC5_historical_r0i0p0.nc</dd></dl></div><div class='xr-var-data'><pre>[382720 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e83e9d72-7577-4537-9313-340a4f99ac91' class='xr-section-summary-in' type='checkbox'  ><label for='section-e83e9d72-7577-4537-9313-340a4f99ac91' class='xr-section-summary' >Attributes: <span>(29)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 1.9.9rc1 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>history :</span></dt><dd>Fri Jul 22 11:51:46 2022: cdo remapnn,grid.des gcmensemble.nc gcmensemble_remap1.nc\n",
       "Fri Jul 22 11:00:06 2022: cdo divc,3 final.nc gcmensemble.nc\n",
       "Fri Jul 22 10:53:46 2022: cdo -add gcm_miroc_remap1.nc -add gcm_mpi_remap.nc gcm_noresm_remap.nc final.nc\n",
       "Fri Jul 22 10:53:11 2022: cdo selyear,1850/2005 gcm_miroc_remap.nc gcm_miroc_remap1.nc\n",
       "Thu Jul 07 18:16:03 2022: cdo remapnn,grid1.des pr_Amon_MIROC5_historical_r1i1p1_185001-201212.nc gcm_miroc_remap.nc\n",
       "2011-04-23T09:11:46Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.</dd><dt><span>source :</span></dt><dd>MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); ocean: COCO (COCO4.5, 256x224 L50); sea ice: COCO (COCO4.5); land: MATSIRO (MATSIRO, L6); aerosols: SPRINTARS (SPRINTARS 5.00, T85L40)</dd><dt><span>institution :</span></dt><dd>AORI (Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba, Japan), NIES (National Institute for Environmental Studies, Ibaraki, Japan), JAMSTEC (Japan Agency for Marine-Earth Science and Technology, Kanagawa, Japan)</dd><dt><span>institute_id :</span></dt><dd>MIROC</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>model_id :</span></dt><dd>MIROC5</dd><dt><span>forcing :</span></dt><dd>GHG, SA, Oz, LU, Sl, Vl, SS, Ds, BC, MD, OC (GHG includes CO2, N2O, methane, and fluorocarbons; Oz includes OH and H2O2; LU excludes change in lake fraction)</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_experiment_rip :</span></dt><dd>r1i1p1</dd><dt><span>branch_time :</span></dt><dd>150015.0</dd><dt><span>contact :</span></dt><dd>Masahiro Watanabe (hiro@aori.u-tokyo.ac.jp), Seita Emori (emori@nies.go.jp), Masayoshi Ishii (ism@jamstec.go.jp), Masahide Kimoto (kimoto@aori.u-tokyo.ac.jp)</dd><dt><span>references :</span></dt><dd>Watanabe et al., 2010: Improved climate simulation by MIROC5: Mean states, variability, and climate sensitivity. J. Climate, 23, 6312-6335</dd><dt><span>initialization_method :</span></dt><dd>1</dd><dt><span>physics_version :</span></dt><dd>1</dd><dt><span>tracking_id :</span></dt><dd>a906be44-c850-4f0c-b8c4-2b165051669a</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>experiment :</span></dt><dd>historical</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>creation_date :</span></dt><dd>2011-04-23T09:11:46Z</dd><dt><span>project_id :</span></dt><dd>CMIP5</dd><dt><span>table_id :</span></dt><dd>Table Amon (31 January 2011) 53b766a395ac41696af40aab76a49ae5</dd><dt><span>title :</span></dt><dd>MIROC5 model output prepared for CMIP5 historical</dd><dt><span>parent_experiment :</span></dt><dd>pre-industrial control</dd><dt><span>modeling_realm :</span></dt><dd>atmos</dd><dt><span>realization :</span></dt><dd>1</dd><dt><span>cmor_version :</span></dt><dd>2.5.6</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 1.9.9rc1 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
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       "<xarray.Dataset>\n",
       "Dimensions:    (time: 299, bnds: 2, longitude: 32, latitude: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1981-01-16T12:00:00 ... 2005-11-16\n",
       "  * longitude  (longitude) float32 86.12 86.38 86.62 86.88 ... 93.38 93.62 93.88\n",
       "  * latitude   (latitude) float32 18.12 18.38 18.62 18.88 ... 27.38 27.62 27.88\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1981-01-01 00:00:00 ... 2005-12-01 00:00:00\n",
       "    pr         (time, latitude, longitude) float32 ...\n",
       "Attributes: (12/29)\n",
       "    CDI:                    Climate Data Interface version 1.9.9rc1 (https://...\n",
       "    Conventions:            CF-1.4\n",
       "    history:                Fri Jul 22 11:51:46 2022: cdo remapnn,grid.des gc...\n",
       "    source:                 MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); oce...\n",
       "    institution:            AORI (Atmosphere and Ocean Research Institute, Th...\n",
       "    institute_id:           MIROC\n",
       "    ...                     ...\n",
       "    title:                  MIROC5 model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.5.6\n",
       "    CDO:                    Climate Data Operators version 1.9.9rc1 (https://..."
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#to select the year from 1980 to 2015\n",
    "data = data.sel(time=slice('1981-01-16T12:00:00.000000000','2005-12-16T00:00:00.000000000'))\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c811b0f2",
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (time: 100, bnds: 2, longitude: 32, latitude: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1981-06-16 ... 2005-09-16\n",
       "  * longitude  (longitude) float32 86.12 86.38 86.62 86.88 ... 93.38 93.62 93.88\n",
       "  * latitude   (latitude) float32 18.12 18.38 18.62 18.88 ... 27.38 27.62 27.88\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1981-06-01 00:00:00 ... 2005-10-01 00:00:00\n",
       "    pr         (time, latitude, longitude) float32 ...\n",
       "Attributes: (12/29)\n",
       "    CDI:                    Climate Data Interface version 1.9.9rc1 (https://...\n",
       "    Conventions:            CF-1.4\n",
       "    history:                Fri Jul 22 11:51:46 2022: cdo remapnn,grid.des gc...\n",
       "    source:                 MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); oce...\n",
       "    institution:            AORI (Atmosphere and Ocean Research Institute, Th...\n",
       "    institute_id:           MIROC\n",
       "    ...                     ...\n",
       "    title:                  MIROC5 model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.5.6\n",
       "    CDO:                    Climate Data Operators version 1.9.9rc1 (https://...</pre><div class='xr-wrap' style='display:none'><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-9c0b780c-0016-4f67-a132-fa9ab0f311be' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9c0b780c-0016-4f67-a132-fa9ab0f311be' 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'>time</span>: 100</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>longitude</span>: 32</li><li><span class='xr-has-index'>latitude</span>: 40</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-ffba40e4-897b-49ee-b07d-4602c071a1b0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ffba40e4-897b-49ee-b07d-4602c071a1b0' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1981-06-16 ... 2005-09-16</div><input id='attrs-7840df5f-0cbd-46c8-8901-a9783ab7a5ac' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7840df5f-0cbd-46c8-8901-a9783ab7a5ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8f7bf0b3-d732-4447-b0c5-02b57ddd9b07' class='xr-var-data-in' type='checkbox'><label for='data-8f7bf0b3-d732-4447-b0c5-02b57ddd9b07' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-06-16T00:00:00.000000000&#x27;, &#x27;1981-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1981-08-16T12:00:00.000000000&#x27;, &#x27;1981-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1982-06-16T00:00:00.000000000&#x27;, &#x27;1982-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1982-08-16T12:00:00.000000000&#x27;, &#x27;1982-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1983-06-16T00:00:00.000000000&#x27;, &#x27;1983-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1983-08-16T12:00:00.000000000&#x27;, &#x27;1983-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1984-06-16T00:00:00.000000000&#x27;, &#x27;1984-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1984-08-16T12:00:00.000000000&#x27;, &#x27;1984-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1985-06-16T00:00:00.000000000&#x27;, &#x27;1985-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1985-08-16T12:00:00.000000000&#x27;, &#x27;1985-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1986-06-16T00:00:00.000000000&#x27;, &#x27;1986-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1986-08-16T12:00:00.000000000&#x27;, &#x27;1986-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1987-06-16T00:00:00.000000000&#x27;, &#x27;1987-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1987-08-16T12:00:00.000000000&#x27;, &#x27;1987-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1988-06-16T00:00:00.000000000&#x27;, &#x27;1988-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1988-08-16T12:00:00.000000000&#x27;, &#x27;1988-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1989-06-16T00:00:00.000000000&#x27;, &#x27;1989-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1989-08-16T12:00:00.000000000&#x27;, &#x27;1989-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1990-06-16T00:00:00.000000000&#x27;, &#x27;1990-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1990-08-16T12:00:00.000000000&#x27;, &#x27;1990-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1991-06-16T00:00:00.000000000&#x27;, &#x27;1991-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1991-08-16T12:00:00.000000000&#x27;, &#x27;1991-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1992-06-16T00:00:00.000000000&#x27;, &#x27;1992-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1992-08-16T12:00:00.000000000&#x27;, &#x27;1992-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1993-06-16T00:00:00.000000000&#x27;, &#x27;1993-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1993-08-16T12:00:00.000000000&#x27;, &#x27;1993-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1994-06-16T00:00:00.000000000&#x27;, &#x27;1994-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1994-08-16T12:00:00.000000000&#x27;, &#x27;1994-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1995-06-16T00:00:00.000000000&#x27;, &#x27;1995-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1995-08-16T12:00:00.000000000&#x27;, &#x27;1995-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1996-06-16T00:00:00.000000000&#x27;, &#x27;1996-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1996-08-16T12:00:00.000000000&#x27;, &#x27;1996-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1997-06-16T00:00:00.000000000&#x27;, &#x27;1997-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1997-08-16T12:00:00.000000000&#x27;, &#x27;1997-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-06-16T00:00:00.000000000&#x27;, &#x27;1998-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1998-08-16T12:00:00.000000000&#x27;, &#x27;1998-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-06-16T00:00:00.000000000&#x27;, &#x27;1999-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1999-08-16T12:00:00.000000000&#x27;, &#x27;1999-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-06-16T00:00:00.000000000&#x27;, &#x27;2000-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2000-08-16T12:00:00.000000000&#x27;, &#x27;2000-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-06-16T00:00:00.000000000&#x27;, &#x27;2001-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2001-08-16T12:00:00.000000000&#x27;, &#x27;2001-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-06-16T00:00:00.000000000&#x27;, &#x27;2002-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2002-08-16T12:00:00.000000000&#x27;, &#x27;2002-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-06-16T00:00:00.000000000&#x27;, &#x27;2003-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2003-08-16T12:00:00.000000000&#x27;, &#x27;2003-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-06-16T00:00:00.000000000&#x27;, &#x27;2004-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2004-08-16T12:00:00.000000000&#x27;, &#x27;2004-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-06-16T00:00:00.000000000&#x27;, &#x27;2005-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2005-08-16T12:00:00.000000000&#x27;, &#x27;2005-09-16T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>86.12 86.38 86.62 ... 93.62 93.88</div><input id='attrs-ccb1b3be-0444-49f8-bb7d-d19fd1fe854f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ccb1b3be-0444-49f8-bb7d-d19fd1fe854f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cbd63ad0-c0c2-4a56-8e26-396b3da5ca1c' class='xr-var-data-in' type='checkbox'><label for='data-cbd63ad0-c0c2-4a56-8e26-396b3da5ca1c' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([86.125, 86.375, 86.625, 86.875, 87.125, 87.375, 87.625, 87.875, 88.125,\n",
       "       88.375, 88.625, 88.875, 89.125, 89.375, 89.625, 89.875, 90.125, 90.375,\n",
       "       90.625, 90.875, 91.125, 91.375, 91.625, 91.875, 92.125, 92.375, 92.625,\n",
       "       92.875, 93.125, 93.375, 93.625, 93.875], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>18.12 18.38 18.62 ... 27.62 27.88</div><input id='attrs-9c81f369-891a-46d7-8cac-3772cf0afe2f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9c81f369-891a-46d7-8cac-3772cf0afe2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba205709-f066-443b-89d9-a9493bfe6b4a' class='xr-var-data-in' type='checkbox'><label for='data-ba205709-f066-443b-89d9-a9493bfe6b4a' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([18.125, 18.375, 18.625, 18.875, 19.125, 19.375, 19.625, 19.875, 20.125,\n",
       "       20.375, 20.625, 20.875, 21.125, 21.375, 21.625, 21.875, 22.125, 22.375,\n",
       "       22.625, 22.875, 23.125, 23.375, 23.625, 23.875, 24.125, 24.375, 24.625,\n",
       "       24.875, 25.125, 25.375, 25.625, 25.875, 26.125, 26.375, 26.625, 26.875,\n",
       "       27.125, 27.375, 27.625, 27.875], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2d9295d3-08d8-4268-99b1-091fafc0e7d8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2d9295d3-08d8-4268-99b1-091fafc0e7d8' 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, bnds)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1981-06-01 00:00:00 ... 2005-10-...</div><input id='attrs-a37a6e25-5f92-42c4-b556-3030ad35e3f3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a37a6e25-5f92-42c4-b556-3030ad35e3f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0ed6810f-f78c-4f20-b98a-fd95f8f66dae' class='xr-var-data-in' type='checkbox'><label for='data-0ed6810f-f78c-4f20-b98a-fd95f8f66dae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[cftime.DatetimeNoLeap(1981, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1981, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1981, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1981, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1981, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1981, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1981, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1981, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1982, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1982, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1982, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1982, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1982, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1982, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1982, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1982, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1983, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1983, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1983, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1983, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1983, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1983, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1983, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1983, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1984, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1984, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1984, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1984, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1984, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1984, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1984, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1984, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1985, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1985, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1985, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1985, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1985, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1985, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1985, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1985, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1986, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1986, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1986, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1986, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1986, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1986, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1986, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1986, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1987, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1987, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1987, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1987, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1987, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1987, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1987, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1987, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1988, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1988, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1988, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1988, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1988, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1988, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1988, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1988, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1989, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1989, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1989, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1989, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1989, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1989, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1989, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1989, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1990, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1990, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1990, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1990, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1990, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1990, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1990, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1990, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1991, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1991, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1991, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1991, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1991, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1991, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1991, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1991, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1992, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1992, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1992, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1992, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1992, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1992, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1992, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1992, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1993, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1993, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1993, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1993, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1993, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1993, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1993, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1993, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1994, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1994, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1994, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1994, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1994, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1994, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1994, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1994, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1995, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1995, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1995, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1995, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1995, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1995, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1995, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1995, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1996, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1996, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1996, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1996, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1996, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1996, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1996, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1996, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1997, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1997, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1997, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1997, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1997, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1997, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1997, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1997, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1998, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1998, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1998, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1998, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1998, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1998, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1998, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1998, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1999, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1999, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1999, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1999, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1999, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1999, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1999, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1999, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2000, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2000, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2000, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2000, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2000, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2000, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2000, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2000, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2001, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2001, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2001, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2001, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2001, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2001, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2001, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2001, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2002, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2002, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2002, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2002, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2002, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2002, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2002, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2002, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2003, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2003, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2003, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2003, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2003, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2003, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2003, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2003, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2004, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2004, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2004, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2004, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2004, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2004, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2004, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2004, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 10, 1, 0, 0, 0, 0, has_year_zero=True)]],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pr</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fb0a792b-cd86-497f-afc9-42938cdeed4d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fb0a792b-cd86-497f-afc9-42938cdeed4d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-90a86b39-d9b9-4d68-a832-7e3fe34dc258' class='xr-var-data-in' type='checkbox'><label for='data-90a86b39-d9b9-4d68-a832-7e3fe34dc258' 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>standard_name :</span></dt><dd>precipitation_flux</dd><dt><span>long_name :</span></dt><dd>Precipitation</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>comment :</span></dt><dd>at surface; includes both liquid and solid phases from all types of clouds (both large-scale and convective)</dd><dt><span>original_name :</span></dt><dd>PRCP</dd><dt><span>original_units :</span></dt><dd>kg/m**2/s</dd><dt><span>history :</span></dt><dd>2011-04-23T09:11:46Z altered by CMOR: Converted units from &#x27;kg/m**2/s&#x27; to &#x27;kg m-2 s-1&#x27;. 2011-04-23T09:11:46Z altered by CMOR: replaced missing value flag (-999) with standard missing value (1e+20). 2011-04-23T09:11:46Z altered by CMOR: Inverted axis: lat.</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>associated_files :</span></dt><dd>baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_MIROC5_historical_r0i0p0.nc areacella: areacella_fx_MIROC5_historical_r0i0p0.nc</dd></dl></div><div class='xr-var-data'><pre>[128000 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0ae5818f-badd-49a2-9b6a-54a51b57ef33' class='xr-section-summary-in' type='checkbox'  ><label for='section-0ae5818f-badd-49a2-9b6a-54a51b57ef33' class='xr-section-summary' >Attributes: <span>(29)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 1.9.9rc1 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>history :</span></dt><dd>Fri Jul 22 11:51:46 2022: cdo remapnn,grid.des gcmensemble.nc gcmensemble_remap1.nc\n",
       "Fri Jul 22 11:00:06 2022: cdo divc,3 final.nc gcmensemble.nc\n",
       "Fri Jul 22 10:53:46 2022: cdo -add gcm_miroc_remap1.nc -add gcm_mpi_remap.nc gcm_noresm_remap.nc final.nc\n",
       "Fri Jul 22 10:53:11 2022: cdo selyear,1850/2005 gcm_miroc_remap.nc gcm_miroc_remap1.nc\n",
       "Thu Jul 07 18:16:03 2022: cdo remapnn,grid1.des pr_Amon_MIROC5_historical_r1i1p1_185001-201212.nc gcm_miroc_remap.nc\n",
       "2011-04-23T09:11:46Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.</dd><dt><span>source :</span></dt><dd>MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); ocean: COCO (COCO4.5, 256x224 L50); sea ice: COCO (COCO4.5); land: MATSIRO (MATSIRO, L6); aerosols: SPRINTARS (SPRINTARS 5.00, T85L40)</dd><dt><span>institution :</span></dt><dd>AORI (Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba, Japan), NIES (National Institute for Environmental Studies, Ibaraki, Japan), JAMSTEC (Japan Agency for Marine-Earth Science and Technology, Kanagawa, Japan)</dd><dt><span>institute_id :</span></dt><dd>MIROC</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>model_id :</span></dt><dd>MIROC5</dd><dt><span>forcing :</span></dt><dd>GHG, SA, Oz, LU, Sl, Vl, SS, Ds, BC, MD, OC (GHG includes CO2, N2O, methane, and fluorocarbons; Oz includes OH and H2O2; LU excludes change in lake fraction)</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_experiment_rip :</span></dt><dd>r1i1p1</dd><dt><span>branch_time :</span></dt><dd>150015.0</dd><dt><span>contact :</span></dt><dd>Masahiro Watanabe (hiro@aori.u-tokyo.ac.jp), Seita Emori (emori@nies.go.jp), Masayoshi Ishii (ism@jamstec.go.jp), Masahide Kimoto (kimoto@aori.u-tokyo.ac.jp)</dd><dt><span>references :</span></dt><dd>Watanabe et al., 2010: Improved climate simulation by MIROC5: Mean states, variability, and climate sensitivity. J. Climate, 23, 6312-6335</dd><dt><span>initialization_method :</span></dt><dd>1</dd><dt><span>physics_version :</span></dt><dd>1</dd><dt><span>tracking_id :</span></dt><dd>a906be44-c850-4f0c-b8c4-2b165051669a</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>experiment :</span></dt><dd>historical</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>creation_date :</span></dt><dd>2011-04-23T09:11:46Z</dd><dt><span>project_id :</span></dt><dd>CMIP5</dd><dt><span>table_id :</span></dt><dd>Table Amon (31 January 2011) 53b766a395ac41696af40aab76a49ae5</dd><dt><span>title :</span></dt><dd>MIROC5 model output prepared for CMIP5 historical</dd><dt><span>parent_experiment :</span></dt><dd>pre-industrial control</dd><dt><span>modeling_realm :</span></dt><dd>atmos</dd><dt><span>realization :</span></dt><dd>1</dd><dt><span>cmor_version :</span></dt><dd>2.5.6</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 1.9.9rc1 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (time: 100, bnds: 2, longitude: 32, latitude: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1981-06-16 ... 2005-09-16\n",
       "  * longitude  (longitude) float32 86.12 86.38 86.62 86.88 ... 93.38 93.62 93.88\n",
       "  * latitude   (latitude) float32 18.12 18.38 18.62 18.88 ... 27.38 27.62 27.88\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1981-06-01 00:00:00 ... 2005-10-01 00:00:00\n",
       "    pr         (time, latitude, longitude) float32 ...\n",
       "Attributes: (12/29)\n",
       "    CDI:                    Climate Data Interface version 1.9.9rc1 (https://...\n",
       "    Conventions:            CF-1.4\n",
       "    history:                Fri Jul 22 11:51:46 2022: cdo remapnn,grid.des gc...\n",
       "    source:                 MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); oce...\n",
       "    institution:            AORI (Atmosphere and Ocean Research Institute, Th...\n",
       "    institute_id:           MIROC\n",
       "    ...                     ...\n",
       "    title:                  MIROC5 model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.5.6\n",
       "    CDO:                    Climate Data Operators version 1.9.9rc1 (https://..."
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#selecting only JJAS months\n",
    "\n",
    "def is_jjas(month):\n",
    "    return (month >= 6) & (month <= 9)\n",
    "\n",
    "jjas_data = data.sel(time=is_jjas(data['time.month']))\n",
    "\n",
    "jjas_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "be94f5d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "#jjas_data.x.values\n",
    "#jjas_data.y.values\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "a41e4a60",
   "metadata": {},
   "outputs": [],
   "source": [
    "#to select the x and y coordinates\n",
    "#jjas_data = jjas_data.sel(x=slice(1000000.,5275000.),y=slice(2000000.,4175000.))\n",
    "#jjas_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "18269e45",
   "metadata": {},
   "outputs": [
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       "\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;pr&#x27; (latitude: 40, longitude: 32)&gt;\n",
       "array([[0.00011733, 0.0001171 , 0.00011552, ..., 0.00014856, 0.00015397,\n",
       "        0.00015701],\n",
       "       [0.00012046, 0.00012023, 0.00012027, ..., 0.00016522, 0.00014499,\n",
       "        0.00014804],\n",
       "       [0.00012046, 0.00012023, 0.00012027, ..., 0.00016522, 0.00014499,\n",
       "        0.00014804],\n",
       "       ...,\n",
       "       [0.00024819, 0.00027803, 0.00028471, ..., 0.0002209 , 0.00022877,\n",
       "        0.00020397],\n",
       "       [0.00024819, 0.00027803, 0.00028471, ..., 0.0002209 , 0.00022877,\n",
       "        0.00020397],\n",
       "       [0.00024819, 0.00027803, 0.00028471, ..., 0.0002209 , 0.00022877,\n",
       "        0.00020397]], dtype=float32)\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float32 86.12 86.38 86.62 86.88 ... 93.38 93.62 93.88\n",
       "  * latitude   (latitude) float32 18.12 18.38 18.62 18.88 ... 27.38 27.62 27.88</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'pr'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>latitude</span>: 40</li><li><span class='xr-has-index'>longitude</span>: 32</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-e733944b-4ab9-454e-90bc-e67dd2f7581f' class='xr-array-in' type='checkbox' checked><label for='section-e733944b-4ab9-454e-90bc-e67dd2f7581f' 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>0.0001173 0.0001171 0.0001155 ... 0.0002209 0.0002288 0.000204</span></div><div class='xr-array-data'><pre>array([[0.00011733, 0.0001171 , 0.00011552, ..., 0.00014856, 0.00015397,\n",
       "        0.00015701],\n",
       "       [0.00012046, 0.00012023, 0.00012027, ..., 0.00016522, 0.00014499,\n",
       "        0.00014804],\n",
       "       [0.00012046, 0.00012023, 0.00012027, ..., 0.00016522, 0.00014499,\n",
       "        0.00014804],\n",
       "       ...,\n",
       "       [0.00024819, 0.00027803, 0.00028471, ..., 0.0002209 , 0.00022877,\n",
       "        0.00020397],\n",
       "       [0.00024819, 0.00027803, 0.00028471, ..., 0.0002209 , 0.00022877,\n",
       "        0.00020397],\n",
       "       [0.00024819, 0.00027803, 0.00028471, ..., 0.0002209 , 0.00022877,\n",
       "        0.00020397]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-0d655756-cc8a-45e7-8e8a-350b1c8de3e5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0d655756-cc8a-45e7-8e8a-350b1c8de3e5' class='xr-section-summary' >Coordinates: <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 class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>86.12 86.38 86.62 ... 93.62 93.88</div><input id='attrs-55175649-4ac1-4f3a-9ad0-b2fc8fdd0444' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-55175649-4ac1-4f3a-9ad0-b2fc8fdd0444' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53b79be9-8074-417c-92e9-df479846de6f' class='xr-var-data-in' type='checkbox'><label for='data-53b79be9-8074-417c-92e9-df479846de6f' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([86.125, 86.375, 86.625, 86.875, 87.125, 87.375, 87.625, 87.875, 88.125,\n",
       "       88.375, 88.625, 88.875, 89.125, 89.375, 89.625, 89.875, 90.125, 90.375,\n",
       "       90.625, 90.875, 91.125, 91.375, 91.625, 91.875, 92.125, 92.375, 92.625,\n",
       "       92.875, 93.125, 93.375, 93.625, 93.875], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>18.12 18.38 18.62 ... 27.62 27.88</div><input id='attrs-a73e772f-c7f6-481d-b7cb-05a308baa468' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a73e772f-c7f6-481d-b7cb-05a308baa468' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a9dee57-7b87-4d0d-9926-9ee8a18e3ab9' class='xr-var-data-in' type='checkbox'><label for='data-5a9dee57-7b87-4d0d-9926-9ee8a18e3ab9' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([18.125, 18.375, 18.625, 18.875, 19.125, 19.375, 19.625, 19.875, 20.125,\n",
       "       20.375, 20.625, 20.875, 21.125, 21.375, 21.625, 21.875, 22.125, 22.375,\n",
       "       22.625, 22.875, 23.125, 23.375, 23.625, 23.875, 24.125, 24.375, 24.625,\n",
       "       24.875, 25.125, 25.375, 25.625, 25.875, 26.125, 26.375, 26.625, 26.875,\n",
       "       27.125, 27.375, 27.625, 27.875], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7fb3b7ec-3e90-4557-a0d9-c0cb4468f4b0' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7fb3b7ec-3e90-4557-a0d9-c0cb4468f4b0' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'pr' (latitude: 40, longitude: 32)>\n",
       "array([[0.00011733, 0.0001171 , 0.00011552, ..., 0.00014856, 0.00015397,\n",
       "        0.00015701],\n",
       "       [0.00012046, 0.00012023, 0.00012027, ..., 0.00016522, 0.00014499,\n",
       "        0.00014804],\n",
       "       [0.00012046, 0.00012023, 0.00012027, ..., 0.00016522, 0.00014499,\n",
       "        0.00014804],\n",
       "       ...,\n",
       "       [0.00024819, 0.00027803, 0.00028471, ..., 0.0002209 , 0.00022877,\n",
       "        0.00020397],\n",
       "       [0.00024819, 0.00027803, 0.00028471, ..., 0.0002209 , 0.00022877,\n",
       "        0.00020397],\n",
       "       [0.00024819, 0.00027803, 0.00028471, ..., 0.0002209 , 0.00022877,\n",
       "        0.00020397]], dtype=float32)\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float32 86.12 86.38 86.62 86.88 ... 93.38 93.62 93.88\n",
       "  * latitude   (latitude) float32 18.12 18.38 18.62 18.88 ... 27.38 27.62 27.88"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#getting the mean for JJAS data\n",
    "jjas_mean = jjas_data.pr.mean('time')\n",
    " \n",
    "jjas_mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "6f88bd72",
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;pr&#x27; (latitude: 40, longitude: 32)&gt;\n",
       "array([[10.13700748, 10.11715934,  9.98064454, ..., 12.83584619,\n",
       "        13.30275424, 13.56588146],\n",
       "       [10.40811595, 10.38825964, 10.39161345, ..., 14.27526204,\n",
       "        12.52745795, 12.79058391],\n",
       "       [10.40811595, 10.38825964, 10.39161345, ..., 14.27526204,\n",
       "        12.52745795, 12.79058391],\n",
       "       ...,\n",
       "       [21.44322759, 24.02177174, 24.5989915 , ..., 19.08538481,\n",
       "        19.76553979, 17.62266895],\n",
       "       [21.44322759, 24.02177174, 24.5989915 , ..., 19.08538481,\n",
       "        19.76553979, 17.62266895],\n",
       "       [21.44322759, 24.02177174, 24.5989915 , ..., 19.08538481,\n",
       "        19.76553979, 17.62266895]])\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float32 86.12 86.38 86.62 86.88 ... 93.38 93.62 93.88\n",
       "  * latitude   (latitude) float32 18.12 18.38 18.62 18.88 ... 27.38 27.62 27.88</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'pr'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>latitude</span>: 40</li><li><span class='xr-has-index'>longitude</span>: 32</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-cf8adfaf-42f7-4699-8c0f-6aea03179464' class='xr-array-in' type='checkbox' checked><label for='section-cf8adfaf-42f7-4699-8c0f-6aea03179464' 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>10.14 10.12 9.981 9.981 9.981 10.68 ... 19.09 19.09 19.09 19.77 17.62</span></div><div class='xr-array-data'><pre>array([[10.13700748, 10.11715934,  9.98064454, ..., 12.83584619,\n",
       "        13.30275424, 13.56588146],\n",
       "       [10.40811595, 10.38825964, 10.39161345, ..., 14.27526204,\n",
       "        12.52745795, 12.79058391],\n",
       "       [10.40811595, 10.38825964, 10.39161345, ..., 14.27526204,\n",
       "        12.52745795, 12.79058391],\n",
       "       ...,\n",
       "       [21.44322759, 24.02177174, 24.5989915 , ..., 19.08538481,\n",
       "        19.76553979, 17.62266895],\n",
       "       [21.44322759, 24.02177174, 24.5989915 , ..., 19.08538481,\n",
       "        19.76553979, 17.62266895],\n",
       "       [21.44322759, 24.02177174, 24.5989915 , ..., 19.08538481,\n",
       "        19.76553979, 17.62266895]])</pre></div></div></li><li class='xr-section-item'><input id='section-3c32d417-3945-413a-b175-83ddd40509fe' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3c32d417-3945-413a-b175-83ddd40509fe' class='xr-section-summary' >Coordinates: <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 class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>86.12 86.38 86.62 ... 93.62 93.88</div><input id='attrs-5c3f6826-c061-4767-bcec-4b9f2ef5fb74' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5c3f6826-c061-4767-bcec-4b9f2ef5fb74' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c6218fd-2d70-4d88-b614-ae5373a4d507' class='xr-var-data-in' type='checkbox'><label for='data-5c6218fd-2d70-4d88-b614-ae5373a4d507' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([86.125, 86.375, 86.625, 86.875, 87.125, 87.375, 87.625, 87.875, 88.125,\n",
       "       88.375, 88.625, 88.875, 89.125, 89.375, 89.625, 89.875, 90.125, 90.375,\n",
       "       90.625, 90.875, 91.125, 91.375, 91.625, 91.875, 92.125, 92.375, 92.625,\n",
       "       92.875, 93.125, 93.375, 93.625, 93.875], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>18.12 18.38 18.62 ... 27.62 27.88</div><input id='attrs-addbefd2-22d1-4300-b054-d747fa1a228b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-addbefd2-22d1-4300-b054-d747fa1a228b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-761b0444-0c29-47e7-b0c5-b0b4d4a188e2' class='xr-var-data-in' type='checkbox'><label for='data-761b0444-0c29-47e7-b0c5-b0b4d4a188e2' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([18.125, 18.375, 18.625, 18.875, 19.125, 19.375, 19.625, 19.875, 20.125,\n",
       "       20.375, 20.625, 20.875, 21.125, 21.375, 21.625, 21.875, 22.125, 22.375,\n",
       "       22.625, 22.875, 23.125, 23.375, 23.625, 23.875, 24.125, 24.375, 24.625,\n",
       "       24.875, 25.125, 25.375, 25.625, 25.875, 26.125, 26.375, 26.625, 26.875,\n",
       "       27.125, 27.375, 27.625, 27.875], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-17c0ef16-1ef4-4346-a802-91b4cd82b85a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-17c0ef16-1ef4-4346-a802-91b4cd82b85a' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'pr' (latitude: 40, longitude: 32)>\n",
       "array([[10.13700748, 10.11715934,  9.98064454, ..., 12.83584619,\n",
       "        13.30275424, 13.56588146],\n",
       "       [10.40811595, 10.38825964, 10.39161345, ..., 14.27526204,\n",
       "        12.52745795, 12.79058391],\n",
       "       [10.40811595, 10.38825964, 10.39161345, ..., 14.27526204,\n",
       "        12.52745795, 12.79058391],\n",
       "       ...,\n",
       "       [21.44322759, 24.02177174, 24.5989915 , ..., 19.08538481,\n",
       "        19.76553979, 17.62266895],\n",
       "       [21.44322759, 24.02177174, 24.5989915 , ..., 19.08538481,\n",
       "        19.76553979, 17.62266895],\n",
       "       [21.44322759, 24.02177174, 24.5989915 , ..., 19.08538481,\n",
       "        19.76553979, 17.62266895]])\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float32 86.12 86.38 86.62 86.88 ... 93.38 93.62 93.88\n",
       "  * latitude   (latitude) float32 18.12 18.38 18.62 18.88 ... 27.38 27.62 27.88"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "miroc = jjas_mean*86400\n",
    "miroc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "6c5c5811",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "\n",
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       "\n",
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       "\n",
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       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
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       "  padding-right: 10px;\n",
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       "}\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",
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       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
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       "  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 (latitude: 40, longitude: 32)&gt;\n",
       "array([[        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       ...,\n",
       "       [13.25767302, 14.97238662, 13.45892303, ..., 12.3773546 ,\n",
       "        10.77996653,  4.53475784],\n",
       "       [11.15175229, 13.99464483, 13.39358035, ..., 13.85195093,\n",
       "        11.67794632,  8.19269802],\n",
       "       [11.56909181, 15.02064211, 16.97874429, ..., 11.83897046,\n",
       "        11.48783124,  8.26348012]])\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float32 86.12 86.38 86.62 86.88 ... 93.38 93.62 93.88\n",
       "  * latitude   (latitude) float32 18.12 18.38 18.62 18.88 ... 27.38 27.62 27.88</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>latitude</span>: 40</li><li><span class='xr-has-index'>longitude</span>: 32</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-78a02642-7406-4063-8b00-603f03652b32' class='xr-array-in' type='checkbox' checked><label for='section-78a02642-7406-4063-8b00-603f03652b32' 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>nan nan nan nan nan nan nan ... 19.1 15.68 14.11 11.84 11.49 8.263</span></div><div class='xr-array-data'><pre>array([[        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       ...,\n",
       "       [13.25767302, 14.97238662, 13.45892303, ..., 12.3773546 ,\n",
       "        10.77996653,  4.53475784],\n",
       "       [11.15175229, 13.99464483, 13.39358035, ..., 13.85195093,\n",
       "        11.67794632,  8.19269802],\n",
       "       [11.56909181, 15.02064211, 16.97874429, ..., 11.83897046,\n",
       "        11.48783124,  8.26348012]])</pre></div></div></li><li class='xr-section-item'><input id='section-b92cb01a-33af-49a5-b223-bfc578fd8dee' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b92cb01a-33af-49a5-b223-bfc578fd8dee' class='xr-section-summary' >Coordinates: <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 class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>86.12 86.38 86.62 ... 93.62 93.88</div><input id='attrs-bbad1658-3d21-4b79-a78d-c067b6d0cedc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bbad1658-3d21-4b79-a78d-c067b6d0cedc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bfacb45b-1cfa-43b7-bb97-9479f43e08d9' class='xr-var-data-in' type='checkbox'><label for='data-bfacb45b-1cfa-43b7-bb97-9479f43e08d9' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([86.125, 86.375, 86.625, 86.875, 87.125, 87.375, 87.625, 87.875, 88.125,\n",
       "       88.375, 88.625, 88.875, 89.125, 89.375, 89.625, 89.875, 90.125, 90.375,\n",
       "       90.625, 90.875, 91.125, 91.375, 91.625, 91.875, 92.125, 92.375, 92.625,\n",
       "       92.875, 93.125, 93.375, 93.625, 93.875], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>18.12 18.38 18.62 ... 27.62 27.88</div><input id='attrs-d3d6e712-7569-40a8-8c47-e196b9a16416' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d3d6e712-7569-40a8-8c47-e196b9a16416' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ddadeb83-dc1c-4f39-8772-3a70bc15fff1' class='xr-var-data-in' type='checkbox'><label for='data-ddadeb83-dc1c-4f39-8772-3a70bc15fff1' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([18.125, 18.375, 18.625, 18.875, 19.125, 19.375, 19.625, 19.875, 20.125,\n",
       "       20.375, 20.625, 20.875, 21.125, 21.375, 21.625, 21.875, 22.125, 22.375,\n",
       "       22.625, 22.875, 23.125, 23.375, 23.625, 23.875, 24.125, 24.375, 24.625,\n",
       "       24.875, 25.125, 25.375, 25.625, 25.875, 26.125, 26.375, 26.625, 26.875,\n",
       "       27.125, 27.375, 27.625, 27.875], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6a221770-62bf-4258-8b65-654c147bdbe2' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6a221770-62bf-4258-8b65-654c147bdbe2' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (latitude: 40, longitude: 32)>\n",
       "array([[        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       ...,\n",
       "       [13.25767302, 14.97238662, 13.45892303, ..., 12.3773546 ,\n",
       "        10.77996653,  4.53475784],\n",
       "       [11.15175229, 13.99464483, 13.39358035, ..., 13.85195093,\n",
       "        11.67794632,  8.19269802],\n",
       "       [11.56909181, 15.02064211, 16.97874429, ..., 11.83897046,\n",
       "        11.48783124,  8.26348012]])\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float32 86.12 86.38 86.62 86.88 ... 93.38 93.62 93.88\n",
       "  * latitude   (latitude) float32 18.12 18.38 18.62 18.88 ... 27.38 27.62 27.88"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bias = miroc - chirps\n",
    "bias"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "445388ed",
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (latitude: 40, longitude: 32)&gt;\n",
       "array([[         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       ...,\n",
       "       [161.96426182, 165.45197733, 120.81544268, ..., 184.5154866 ,\n",
       "        119.96971392,  34.64844616],\n",
       "       [108.35912228, 139.56784387, 119.52779032, ..., 264.68187484,\n",
       "        144.39333967,  86.87935612],\n",
       "       [117.16561409, 166.87507841, 222.81093818, ..., 163.37694587,\n",
       "        138.78033003,  88.29269588]])\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float32 86.12 86.38 86.62 86.88 ... 93.38 93.62 93.88\n",
       "  * latitude   (latitude) float32 18.12 18.38 18.62 18.88 ... 27.38 27.62 27.88</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>latitude</span>: 40</li><li><span class='xr-has-index'>longitude</span>: 32</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-ca6fa2ae-c675-442a-9819-8755dc99a910' class='xr-array-in' type='checkbox' checked><label for='section-ca6fa2ae-c675-442a-9819-8755dc99a910' 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>nan nan nan nan nan nan nan ... 781.8 459.9 283.3 163.4 138.8 88.29</span></div><div class='xr-array-data'><pre>array([[         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       ...,\n",
       "       [161.96426182, 165.45197733, 120.81544268, ..., 184.5154866 ,\n",
       "        119.96971392,  34.64844616],\n",
       "       [108.35912228, 139.56784387, 119.52779032, ..., 264.68187484,\n",
       "        144.39333967,  86.87935612],\n",
       "       [117.16561409, 166.87507841, 222.81093818, ..., 163.37694587,\n",
       "        138.78033003,  88.29269588]])</pre></div></div></li><li class='xr-section-item'><input id='section-59b6644e-6193-4d63-bacc-fbf94693611c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-59b6644e-6193-4d63-bacc-fbf94693611c' class='xr-section-summary' >Coordinates: <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 class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>86.12 86.38 86.62 ... 93.62 93.88</div><input id='attrs-2afface5-bf88-490e-95e1-6797a2b8426c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2afface5-bf88-490e-95e1-6797a2b8426c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8417a12b-ea09-489d-897b-8f3717609353' class='xr-var-data-in' type='checkbox'><label for='data-8417a12b-ea09-489d-897b-8f3717609353' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([86.125, 86.375, 86.625, 86.875, 87.125, 87.375, 87.625, 87.875, 88.125,\n",
       "       88.375, 88.625, 88.875, 89.125, 89.375, 89.625, 89.875, 90.125, 90.375,\n",
       "       90.625, 90.875, 91.125, 91.375, 91.625, 91.875, 92.125, 92.375, 92.625,\n",
       "       92.875, 93.125, 93.375, 93.625, 93.875], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>18.12 18.38 18.62 ... 27.62 27.88</div><input id='attrs-2ea7af43-462c-4791-84fd-9d1f49042508' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2ea7af43-462c-4791-84fd-9d1f49042508' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-301b6bc2-0b41-47c4-85db-25a5e728d5c7' class='xr-var-data-in' type='checkbox'><label for='data-301b6bc2-0b41-47c4-85db-25a5e728d5c7' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([18.125, 18.375, 18.625, 18.875, 19.125, 19.375, 19.625, 19.875, 20.125,\n",
       "       20.375, 20.625, 20.875, 21.125, 21.375, 21.625, 21.875, 22.125, 22.375,\n",
       "       22.625, 22.875, 23.125, 23.375, 23.625, 23.875, 24.125, 24.375, 24.625,\n",
       "       24.875, 25.125, 25.375, 25.625, 25.875, 26.125, 26.375, 26.625, 26.875,\n",
       "       27.125, 27.375, 27.625, 27.875], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d81845e5-79e2-4722-b19b-d1ebd1d81bcb' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d81845e5-79e2-4722-b19b-d1ebd1d81bcb' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (latitude: 40, longitude: 32)>\n",
       "array([[         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       ...,\n",
       "       [161.96426182, 165.45197733, 120.81544268, ..., 184.5154866 ,\n",
       "        119.96971392,  34.64844616],\n",
       "       [108.35912228, 139.56784387, 119.52779032, ..., 264.68187484,\n",
       "        144.39333967,  86.87935612],\n",
       "       [117.16561409, 166.87507841, 222.81093818, ..., 163.37694587,\n",
       "        138.78033003,  88.29269588]])\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float32 86.12 86.38 86.62 86.88 ... 93.38 93.62 93.88\n",
       "  * latitude   (latitude) float32 18.12 18.38 18.62 18.88 ... 27.38 27.62 27.88"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bias_percentage = ((miroc - chirps)/chirps)*100\n",
    "bias_percentage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "08ba09cb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x684 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting annual_pr_mean\n",
    "\n",
    "#plotting with cartopy\n",
    "import cartopy.feature as cfeature\n",
    "\n",
    "plt.rcParams['font.size'] = '16'\n",
    "\n",
    "fig = plt.figure(figsize=(12,9.5))\n",
    "\n",
    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
    "ax.set_extent([88,93,20,27])\n",
    "\n",
    "\n",
    "m1 = ax.contourf(bias['longitude'], bias['latitude'],bias[:,:],\n",
    "               levels=np.arange(-15,15+3,3),  transform = ccrs.PlateCarree(),cmap='BrBG',extend='both')\n",
    "\n",
    " \n",
    "# Define the xticks for longitude\n",
    "ax.set_xticks(np.arange(87,94,1), crs=ccrs.PlateCarree())\n",
    "lon_formatter = cticker.LongitudeFormatter()\n",
    "ax.xaxis.set_major_formatter(lon_formatter)\n",
    "\n",
    "# Define the yticks for latitude\n",
    "ax.set_yticks(np.arange(20,28,1), crs=ccrs.PlateCarree())\n",
    "lat_formatter = cticker.LatitudeFormatter()\n",
    "ax.yaxis.set_major_formatter(lat_formatter)\n",
    "\n",
    "\n",
    "plt.colorbar(m1,ticks=np.arange(-15,15+3,3), orientation = 'horizontal',shrink=0.5, fraction = 0.04 , label = 'mm/day')\n",
    "ax.coastlines(linewidth=3)\n",
    "ax.add_feature(cfeature.BORDERS,linewidth=3)\n",
    "\n",
    "\n",
    "\n",
    "plt.title('Seasonal Bias(GCM ensemble avg-CHIRPS)',fontsize=17)\n",
    "plt.savefig(\"/home/mkibria/Academic/pr_of_thesis/figures/Seasonal Bias(gcm ensemble avg-chirps).png\")\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "9003db92",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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uXxzaP/lAM2XZhNT61B0QQtyGdjPeK4R4z1g4GuKga9uWohu7kF/RXj6GXGdCnBlSWE9G6T7mCDVaNxXnqrLu+1wp5Rgf97Yy8oWieR8LMVU3CvtFGdcNswghnkb7Z3oRrY/NWbR/p6BdV8N6U9h532QneSHEZaPkwnMrfHiaw/CaZqKJT1NcQKsjNdCaKQ2PP6RwWWhBQg2v52W0F160ECLQzJ+hMpFSpgshpgE3CiF+RhNTj9lQVCRa/8S6lKy7hhjXNbD8d7fk3in8fdpQJBgsskNKmWa0nqcTlGnGeQ3sMxXbrURd0lH4rDR+Jhpi6z1bDN2fysI/w9vQvI9JaN60trqyjZ+fU9D6kN0ETNb1+bsZ7R417Khv7T3TF9N1YhVF74lyDVSyI59KKR/TnXtttPp2N1qLw81m9tklpWxr6QGklAfQWhcAEEL0Rnu/9Ub74/+R0S6Fzw5zQtAt8BohZoyU8qIQ4lY0t34rIUS0lPIyRQ+GRlLKoxYU9T+0psTusngnYoxH0OiOexWt0/9zQojGaH3WHkbzthR2qiy0wVyg2cJ0Uw+xMhFCdEITYYuA4YaeEp3NZb3kbUb3AN6J5h1rS1EncFPY/dpKKX/BhhFrJii89ndLKX+wYj9pIq3wZWnKA2DuuAOliZFAjkQI4Yf28DwHtDH0uAktKLLxC+GK7jvGKB3d4IRoiovPwnN7S0r5ooVmFcZDMsUGNPHSFyMhVhq6OroF7R914Z8BW/kZuAOtI3ouBp2yraDwuqyXUvYshy1msfK5NEVKeYsj7LCAEnVJhyXPRFvvWWNGoT27vpNS3mu4QQjxLKZF3ly0+2ECWj+77mh/er+UxQeKWHXPSClfRWu2M0WhB62DECJMSnnFTD6nIrU2wVPAPUKIusBNQoiZUhu9bO9jrRFCvAT8hDb4w1iIFY5GNyfw3QJvCF9RGtkUuXoL/f2bdd+WRn9vAFw2IRSq6raZRUp5WEr5NdpoRdD+MYHWDJYFdBWmI7n31n0bu/stpdCu+Saaq3rYWKY1FFb+suqXI66tvbC2nphF9xI8ADQRQtRx1nFLoQDTXrIqaB6HDbLk6C9T9aawfnY3sa0jJT0eW9CEqjXntgeI0I22NOZn3fcTuqZ4ayjc9zlhoi2wEKFh9g+r1AJOHkHzSswzcd3KRPcCPYjWHG0yWr89KeXeOYAmFDoJISz2otqZdrqmWj1CmxWhM9oz81Ap+9rr3il89sw1sc3k81Nqo5JnoY1Sbo3pZkmw/p4xi9RGD05DazYttYXHhvvDXjyO9ryZ7MA6dVX3beo+bqz7Ntec7RZ4vBATQtwjhGhvZvNDaH2jDhk8IH9G++HeFaZjVUWI4tMrnAKidG3ThXkC0PqG+BvtGyO0KMfGFP6bywTQNYX8jdbP4HGjMiagdTpdZUF/InMU7lfsoSG0qYfusbFMi9D10eqF1vxQVjRju19beyGl3IT2YL9dCDHSeLsQwl/XtGopX6N5/74wFt9Ci6tV+AL+B61f4HNCF4fJKG+wEMK4H4a1JGG6OeMi2nVsL4pPiVIdLV6RMWvROlGPEwYxwHQP3NeNM0stOv0MoL8Q4n7j7UKLo2XcZLlW913iWkgpl6C9/FoCM4RRjDVdmQLTzVm/onnUBgDfGL/8dfs2RGueNTlFiwHj0fovPVVGvtL4HK0J+ythIuaREKKFsHGeTSueS3loI34bA2+aenEKIbqYulZ2JIqS1/FhtPo6XRaFFSqBHe9Zc8/PMUCJcg0oFF2T0OrEMVkyortV94wFPI/W1P6K7l1YQowIIfphZTgVeyGl3A9MR+uXZ655slSEEKFCiOeFEFEmthmK0HUmdi98bqyx5djOwhuaJocB3wohDqF1gExAe6B1RQsil4VBp3Fdk+UENCG0TwixAO0fbShap8w+aA/p+3S7fIEWmXi9EOJvNIExAE0o7KJ4X4qawBYhxG60TrQJaGERrkPrX2AYB+gZ3bHe0d0o29EegNeh3VglXlRWsAnNbX2j0AInbtGd27VoQ8evL0fZhtyoE16giYz6aB3l/YFXpZRl9Yly1LW1FzejjUD7VwixFi1OXR5ac1gvNEFjqgO1Kb5Eaw4aBRwSWgDIDLRrNhStiWynlDJbaJ3lFwIbhRBL0OJK+aE1dfRBExBDShzBclaivQj+Rhutl482iuuUEOIbtD8HO4QQ89FejIXx6JoYFiKlzNcJqn/QfsM/0eruUF2Z5ygZg+t+tGv2lRDiLrQX51W0cCvd0AZsGAqRf9FGUw5AGwpvzETd9xggXgixHM1rko9WP/qgXbejGPTJ1HUAH4UW9+oetGm5DKc4aof2m2RRhsjXdc7fWVoeC/gazUtyK9BXCLECrQ9QdbT+rW3Rro/JuTbLwJp752U0z8xzwHW6ep+EJkY7oj2jquO4PjfrgCeFFktvB1ocsWt1Nv/Pgv3tcc/ORasHzwohWqB5K1ug3XOz0a6bKVbo7HwI7Rn2pXEGG+8Zs+ju2aG68r5Fm5Jrha7MKLQ63JIyBic4mDfQhOmLQoipRgNELMEfrQn9VaHFbNuN1pe4BkUBn3eg/Zkx5hq05+pJW413CrYMtXSnD9rL4Rm0YHgn0B6cGWgP42+BJmb2a47Wl+g02ui8S2hi6B2gqVHe8RTFgzmv268quqHbBvki0PrRrEG7IbPRbuiZQBcTNsSiiZFTOhvOo/U1MRXDJh4zw5pNbdPZ9wvajZ2B1ul0AkVDjV81yi8pX/iKArSH3FK0jvDm9unrjGtrge2jLcwfjdbnYz/aCzkNrQnnR3RhCyy9hmjNgfejCeN0NAGyH63zdIRR3jq6unFMd67JaO71z4FOBvniMAorUdY2tAfYDLSHdYHh74ImqF9GEy5ZuuO/qks3eX5oYnqD7vokonmdo3XXapeJ/KFo/+R3GFyHI2gDbcaYyL8crR6XiCVmkGewbv94nR2FAWxnob2cS4SF0O3no9s+T1evcnR2b0XzUFQ38RvvtLDuWJzXYJ8JaEIi2aCOL9bVG8N4X7/oyo8zUUaxbVj/XPJDi9W0UXctMtHiLv6DJnz9DPKuwuA+teR+wMQzyLCuoonOJbpjp6LVVVPPRHPlW3zPlvI7NEATXYlozbVrdXVsEmbChuj2+4iiZ2KjUsq36p6xwN4wtPfgOrTncC7aO22Fru4Embj+n5RS3mOmzhMr4ogZ5Zmuy2MYh9Ci+wPtHh2KNqJ9G9ofqly0e+Q/tOgIwSb266Y7Ron4bu72KQxEaBYhxFi0kSAd0YTDKbSH29tS1zlQlByVZMghKaX+H4jQhuN+g/Yy+BN4WOrczUKbxuKELmt/KeUKI1vWAXlSyr6lGq1QKFyK0KZWOorWnDS+nGUNRxNKo2TxieQVCq/BnveMAoQQ36N5yutJo1G97oYlfcSeQnOZPo/mmv0aTWEvFdooD9Bcj92MPjfptukfnEKbkmEa2hQs16G5/811MnzLmhNRKBTORwhRybiDua5jcGGIhDnlPYaUcj5aOIGXyluWQuFqnHHPVHSENijqNrQR2m4twsCyPmIjZfHJdFcLIZLQ+lH1RZuK5xhaE4YeIcRA3eKvBsnNgNNSyg91ed5A65/xvtExlwCDhBAjpZSmRq4oFAr3oCmwQte/6gTaiNlrKJoz8C87HedBtH5tsVIL7qhQeCrOumcqMnXQHEQl+um5I2UKMSMRVsgW3XdpgeQmok27s88g7RTQUNc8uQct+rWpqNkz0DrgvSmEmCfLaj9VKBSu4jRaX5reaB1nfdD6E70GvCut75hrEt1zZF+ZGRUK98cp90xFRmphZUyNonRLbB012Uf3fcDURiFED7TJZx8xTJfaiMUX0Tp0+6F1iDU1DY5ECyy5AG0qGvUPQaFwQ6SUF3BggGCFwttQ94zCGKvjiAkhaqKNJlompTQ3JHYi2qiGP403SCk/R+v03whtxI7xlA6F+RaiKdrXRSkBFRUKhUKhUCg8FasEjq6D4Ry0uCy3m8kTiBaSwGyUaSllMkWTcZbG82hDriehzVdliY33UBi0NCSwAz4eH7O2OL6O06Q+gSXiSJZOQT4FSclQoGs5DgggtLq5WZssIyzY3LSCjudKpm0xYQtycslM0KZ9E/5+BEVHk5OaSkFuHhQU4BdWiYCIymRmGs9Hax8Ksu1Qbn5e2XkUCoVjkEBmlsGz1B8CXOh/KOM9Y827IjjYsrz2ePafP3h4sTSYZ9ZTsPiX1kV7/hdd0FMp5RkzWUehxa351cx2i5FSrhVCLAJeFkL8buE+3wHfAYiwEEnbJqXvEBEFKUnlNdU5RJQILGxXQhqVca1MkH/mHJnTdYN8cnKoPXww0e3aWF1O71bNys7kJNbsMdnibpbcq+lsfvw5AGRuHlmJicj8opiMualpVO/Xm9rDBxfbb9f+/eU31gxXj5Q2E4yFeMp9oVB4A+cvw9HT2nJwILRq6Bo7SnnPVLLyHdGmefMy89jz2T+56wBTU6G5PRYJMaHN9TUTbbqAAVLK0uZtug0tkJypKNi28AJaX7L7yspYJuYqmCeJMQdy9cghq28031o18GvVnLw9mqg4/tdMIlo0wzfA1BSaJXEnAVaIoU2WiDK/0BB8AgMpyM4GKCbCCjn1zzzC6scR0azo+pp6SNlLnJn6Ha0WZ6buF3WfKBSOIcpgJq7Uq5CXB35O9oqZeUda+14A54swT6bMX1kXK2wK2vQsw2XJubMM81ZFm0j2Kyllrrl81iCl3C6EmInWTHkOLdKyZfj6We5Fcncx5mBvWHkI7NkFEX+K3CtXyUlKJnHTVqr1MjWnbRGecgNaIsqEEPj4++uFGECluDrUn3ADJ/6awZVjWoziS1t3FBNipjB+eNnTa2b8MLXJa6bEmULhGAL8oVIwXNV1kUi+AjGRzjm2kwUYeM47wBlYIre/BMahBVhNF9rE0YWcMWqinKArs9zNkka8BOxF6+S/2s5lF+HuYsxNadu+PWcvpRA/fTYACStWU7VnN0zMPwt47g1YmigLb1CPpF2aozggKpKWTz+Kb0AAVXt20wuxvPR0q49p7qFmD4Fm7iFrF8+ZPVH3pKKiEBluIMTSnCPETNy/tggwUCLMViwRYkN13y/oPoa8hjYPXSG3AXullNvLb1oRUsqDuj5ik+xZrkncUYw50RtmS/MkQNWeXTk1Zz4FOTlknDlH6qEjRDRtXCyPN918hedSKMhqDOxH2rETBMVUoekDd+mbZvMNvGSZ5y+QevgoF9b+R/LeA+RnZuIXEkyVzh2o1rsHITWqW3z80h545RVpdhNo9sLe9d/d7m+FopDgwKLlHLs0KpWO0b3liD5ghnjTO8CelDnXpCcjIsIlvTrZtrM7Payd3Cxpzc1oeCMe++Nvzq/WYuiF1Y+j1bOPI3x8KszNt3rXPhCimCcw9dAR9n7wmUX7x/bsRr1x1+EX4piRo44YHOAyceZq3On5oPAe4s/BGd3EETVioH5pMdPLwIr3hqXPfGuFlyHOeA9M7jpgm5Syo8MPZGcqdHwuw8pX4oXiLp4xN+4bZkzNwf25sH4jMi+PK8fjObdsJTc9+ZCrzXIafdq00C8XesrCGzekSucOXNq8rcz9L67bQMq+AzS99w7CGtSzu32O8KLZ2oRhjMcJusL7MisbEhLhUhIUFEBIMISGQJVICK9Uehn2xh2eV4rykWbQfSE81Hw+O70Xyrp/yyO8DKkof8ZtpcJ5xEqreCZfBq5+uLlIiFnygjV1k56cPZczC5YA4OPry63ff0qN5k3tbp8nUZCXz84589m/bBUZySnE1I+j9Ygh1GnfmjO79rFl2iyOrd+kz+8TGEiLxx4gvGF9F1qt4cgQG+6AzQJQSjidAPuOQL6ZGWnq1oSmDcDfTf/vuvrZBrY/39zBdnMkX4GLSVrTYuVKUDUKAi0YRR4SBsvWa4IeYEAPCAosfZ8ycHRToyU4U4R5qkeswggxSyukW4kxF3rDbP2nVJCXx573PuHqiZMARNSszt1Tf8TPkgdRBebA8tUsfu9TMlPTAAgKD+O+6b8SXDm8jD01rI19Zg+8XaSZQ0pJzur/yN2xu+zMQYHQqglUNR3eyNoXpcd5Du1JTi6cOQ9XrmpC2M8P/Hy10YaRlSEiHIwHCDn72X0lHXYdKZ7m4wMtG0OdGub3y8yCTTvhaoa2HhwE/UsfeW4Pb7QjhFchrvCCKSHmhvhWjZUhE8ZavZ/biDEPFGIAraIq8/PE+8hO1x4q/R68m6633mBX+7yRSydOMuWBJ8lITgGgy4RxXPPwvXY9Rm5WFivWbSIoNsbsqFZH4ykCTkoJubmA0F74QlBwIZGctRvIP3NOn09EVCagfWtEaCgFKanknzxN/qni8a79GjckoG8PfEJDnHwWxfFYIZdwEfYcKr0De0wUdGqNw2dTycmBtKua6MovgGoxUEn3u567ANvNzE1fu7omyHx9i9LyCyA1DbbthewcfXLgkP74N2tsohDrcaTYMoejRViPGnVNpo+o00gJMXfDViEGbiDGXNw3rDQhVtqNXXgDbpsxhyUffA5oXrH7Z1o0MYJDMHfTFrL+3EknWVI2B5av5p8X3gDAN8Cf+2f+TliM9cGi8/PyOL1jN2kXLgKCSydOcnrXHs4fPEJBXh7Vmzdl6HOPUbVxUfRuV3jVnImlAjD/YiI56zaRf+as9qIsRAjNE2OAb6P6BA2+BuHvr0+TUpJ3+Cg5K9chDae1CgwksE93/Jo3cZkILi8uEXKJSZq3yBLq14HmDopIn50DB49pTdLG1KmhNUPv3A8XDaZPDgvVBFshgQH41Y+j4MpVZEoq8qpRSBsfHwIHX4N/00Y2megK0WUOZ3nEDJ/vSoi5IeURYuBCMebhIgwgPzeXjwaMIk/3L+/h+dOoFF3+8ypLVJUHdxBkUkp+vfMhEvZrda/3PZPoccctVpWRdOoM/7z4BhcOHys1n/D1ofON19PzrokEGM3z5u2izBS5V66y/eff9bNElIoQ+HduT0DXjggzHhiZmUX26vXkHThcLN23Ti0C+/fGJ6KyPcx2Cxwm0PLzYdUmrekOtKbeuFpac2RevhZ9/lIyJKVo24WAfl21QRP2oqAA4s/A4RPaMS0lOlLz0O05BGfPl50/wJ+gkUPwq1PLZlPdSYgVovqIlY0SYmXgVDFWhgCzS2T0MrBVhEHJG+7nSQ9w/qD2Err1+8+o1ap8DwlHijBjXCnK9i1Zwb8vvw1AQEgIo996kbhO7fEtY7qT/Lw8jv23iYWTP9Y3b5pC+PoUm4YpvFosg556hEY9u5rMXxFEWUFuLrveep+Ms8W9HT4B/oCgIDdX84YFBeEXVwf/dq3wrRZrUdl5J0+TvWw1Mu1KUaIQ+DVpiH/HdvjGRNvxTNwXm55Xp87B7oPasr8f9OlSsgO7lLBhOyTpJl2pXR3a2Onln5gE+w4X9d0qpHKYNio2KRXSM0zv262dJsYKB3YcOl6s+RHQwt2EVcInJpqA7p3xrVK+uuCOQgycJ8Y8VYi56XAe96FSoybOCW1hpQgzlwa2CzR7ijCA0OiiqNAZSck22VSIM0WY4fFcIcia9O1JeLVY0s5fJCcjg2mPP09ASDDVmzcluHIYASEhBISEEBgagswvID05mZRz5zm39wC5WUVNYT5+fjTq2RW/oCBCIyOo3bYVtdq0JDM1jUXvfsKp7bsASDt/kRlPvUjjPj3oeddEqjZqUMwe4+C13silbTuLibCIls2oN34MIdWrAZqnUublIfz8ymxWNG4C9atbG9+JN5Dz3xatg7+UICV5B4+Qd/AIvnG1NUFWq4bHNllagtUDEw7uh6PxRQkN6poeRSgENKkPG3Zo62fOa3kL+23l5WvhRdIzNe9WpRBNIAX4lywLtN8nMQlOnNa+DQkNgRaNIFYnmHJyYcla0+VERRTZV6cG1KxGkF8gMj0DUTkcn8rhiPAwhGGfMS9lzZ4DKoRFKSghZiv2FGM2iDBb85sTafYWYQChUUVCLD25fELMVbhCkPkFBDDugzeZ8sCTZOm8KDkZmZzcusPiMoLCwxj34VsmvZAhEZW5+csP2LtwKcs//UY/UvPw6vUcXr2eel070rh3DzKSU7hyMZEriZe4kniZnMxMIqpXI6pOLZL9/AmrV5dK9eqabZrzJM6vXKNfrjVsEHVGjygmioQQxfqBlYbZ+6VNG66cOMnJmXNIPVQ0si4//jT58aepVK8utYYMJKptK7PX1NUDHaSU5J8+S+6ufdqAhPw8kICfHz6VQhFhlRABAciCAk305OdDQQGyoAAREIBP1Rh8q8biW6MaIjio1OP4nb5IXobuj0VgAKH9+iCCAk0/w6Ijtdhtl5I1IbV5J9SqDqlXNDFVUFByn8ph2j5BgZqgysrWmkDTMyAzu3heX19oXA/q1So+GCDAXxNnprxiBQXFO+b7+uDnwJA07uoNK0SJMfOopkkLMetlKq8Ys7MIsze2ijCAVV/9wIbf/gKgx5230vvu22yywdnesNJwpiBLOnWGDb/9SfzWHaSdv2jRPpWrV6Nhz670uH1CMSFsjoyUVFZ+8R275y22ycbwarFUat2KmC4dqFSntk1luJqrJ0+z6833ABC+vnR873UCwi0LG2IrV06c5OyiZVzesavEAIDgarHUHDSAmK4d8bFA/DlanEkpkRmZ5B06Qu7ufcjk1PIX6uuDf5tWBHRpjwgqLsjyLyWRs3p9sZGngQP64G+ma4P+2ZycCuvLDpxsNbWqaR3xzcX0OpMAO428xVGVoXuHYkmOfpa7uxAzxFGCzFObJpUQswK7ijE3F2BQPhEGsGfhUua99i4A9bt15oaP37baBncSYYY4u8ky5VwCl+JPkZOeoX0yMsnO0P6Fh0ZFUik6impNGxFe1bJ+S8YkHDjExj/+5tDKdZo3wwZaDRtEyNCB+AWZ93S4I0d+mcLF9RsBiOnSkcZ32faHwRYyz1/k7JLlXNywGZmXV2ybX6VKBFeLJaByOAERlQmoXFn7jqisT/MNDjbZnCkLCti1axcyJxdycpE5Odpybg4yOweZW5RebHuOtq0oXUtzGIEB+Ldshk9EZU3snTpDgVE/Pb/GDQkcNsCiZtucLTvIWbex5IawUM1rJoQm2FLSSi/Izxdq14C4mprHqywOHIXjpzVRHRig9Q+rVDwyvhJixXGEGFNCzA2xtxADO4mxCiDCQPPofDt+EqA1lT22aKbVzVjuKsQKcYeRlvYk6fRZds1ZwNWkJMKqRBMWG0NYTBUqxUQTEBxM8plzJJ06zcWjxzm6fpO+6bSQiFo1GPvua8Q4YIomsH8/tSvH49n7wWdaZ3yg1XNPEO4g20sjJyWVc8tXcX71OvINQ16UgU+APwGVNUGWn51NflYW+VlZFBh3CrcnAQH4N2+MX6vm+EREgABycrWQDFeuan3pfH20JjwfH/D1Rfj4UHD1KgXnL5J/+iwFiZfLOoo2MrV9GwJ6drHquZF/5hx5R46DABEeRo5PQUkxlZMLl1O0GF65edpAgOAgzesVHAShwcWbFS06cAFkZ2tCzMS+SoiVxN5iTAkxN8QRQgzKOZLSA0QYWB6mojSklHw65Hp9H6R7/v6Z6LqWN1+5uwgzxttEWVnk5+ZyYst2ds1ZyGHdZO8Atdu24pZvPnahZUWYE245aWlc2rKD+Bn/6D1RoXVq0ebFZ1zaYT4vI5Pza9ZzbtlKclPL8No4Ez8/fKKj8G/VDL8mjRDmOrpbgJSS/KPHyV63CZlioplTCHzrxxHQtSO+sdbH0CsLVwW1VULMNPYUY54qxFRnfRuweSRlKSLM2rkdHdkvxB4iDLQOzrEN63Ny204AUhPOWyzEPE2EgWtHWroCX39/GnbvQsPuXdj810yWf/I1oM0Q4EoK8vPJSrtCenIKdbKzyEhOIT0phYzkZK5eTuLc3gMlbAwKD2Pca//jSJ5tzbL2wi8kmFpDBlBzYD8yEy+Rm5pGTkoqOamp2ndKKjmFaSmpFJTSbOgTGIhfcBC+QYH4BgbhW7gcFKT7BBp9a8snEhIgIAAR4I8ICIAAf7sOyBBC4NeoAb7147RZCOJPIfMLEP5++MTG4FunFj6VSpnwupwYPmudJcrc5Q+2O1L4Z6kid+RXQsxGrBJjdvCCGYsjU2LJHuLMXiKskKCwSvrlbOMo0l6Ko0SkOwu8kIgI/XLhS7sgP5+LR46Tl5tLYGgIUXVqlRkLrXC/LX/NIn7Ldhr27Er7MSNNCgFZUMDFYyc4vXMPZ3bu4VL8SdKTUshMTbOqn1tMgziuf+91ImvWoLoF+Z0RxkP4+hJSrSpUq2o2j5SS/KwsclJSyc/KLhJUwUH4BgTYLJ4iWxS/zx31p0/4+uJXPw6/+nEOKd8STD7HFS6hIo+qVEKsHFgkxhwgwqzJZ81D1N4iDCA7I1O/HBBi2Tx7nugNcwa2XBdniLfcrCxWffWDfj22QT1Wff0jexcu48rFRH16SGQErUcMps21w4iqXdNseRv/+JvVX/8EwPGNW1j99Y/UatOSuh3aERgaonm19h/k7O59ZF25apPNPn5+1GzZjPrdOtFx3HUEWBGJ3ZJ7wSliTQj8goPxC7bcdltw1J8+d6HwGezJgsxTmyWNqahiTPURswO23MD2FGC2YPwgdYQIA/j6+ltJ0Y2Cuv3Xr6nWpPQ51JQIcw3lEWyntu9iygNPWrVPXMd2tBw2kNiG9QmOqAxSIgskPn6+TH/yhTKnZyqLoPAwQiIjCI2MIET3CY2MIDQqksjaNanVugX+Lhrd6Y2Bcb1JmDl7xhJ74C1CrBBb3zmqj1gFxlr3tqtFmDXll0eEpV9O1oswHz8/qtRTIstdMSeALRFoMQ3rExZThSuJl0psC46oTESN6qSdv0C6wewK8Vt3EG9FgFpzhEZFUrtdK2q3aUWNFs0Ii6lCSGRlfC0MvuoKzN1TnizQ7PG8chcxZ+/mStU/zHoqWr8xJcScjDuIMEsp702wb8ly/XKNFk3xCwgoNb/yhrkfpf0mhSItODyMST9/ycovv+fMrr0IH19iG9Wn5dABNOjWGV9/fwry8jn23yZ2zlnAsQ2bLerDVa1ZYyb99CUp5xI4sWkbF48cIz83l5CICKLq1qJ2m1ZE1q7pNdMClXa/ebJIsxRLnnvOEmve0FzpDVSUpkrVNGlHyrppyxJh7iLAoPwiTErJj7fcQ+KxEwAM/d8TtB01zGx+JcK8h7K8aGkXLrJn/hLO7jtA8umz5GRmIoQPwkeQlXaFnIxMgiuHM/7jt6nRvKmTrPZcKoJIM4WzRFl5xZgzPGLu8O4w/D3sbY+l7yPVNKkw69K2pxesd6tmDn/w2uMfyPmDh/UizC8wkGYD+pS7TIVnUKaorlGXoe06mdyUnZVF/MFDxDVtQqCNfbjceXSpI6ionrTCZ6ajBZnyjpWOqeu/a/9+u4oxb2+qVELMzhiLMXuJMMMKaFwZ7fmwtVdF3/jH3/rlpv17ExhqPi6Q8oYpCgkMCqJJ2zblKsPW+uSNAs4b+6MZ46z4irb0HfP2/mGlXW97izHwXkGmhJgDsPTms1eHeVPbXfmgPb1zDweXr9Gvtx9zrdm8SoQp3AVr6qKnizZH/plzJY4WZco7VoQl19cRYgy8T5ApIeYiHD1q0ZYHrT0qtSwoYNmnX+vXmw3sR82Wpsu15sUnpeS/hYs5ffQY/ceOIaaGJaE3FQrHYEnd9SSx5o3CzJFNl+4UCNbZ/cOsvZ6F+ZUgM48SYi7A2qZIe1CW18xex9u7eDnnDxwGwC8wgH4P3FXuMqWU/PTWu8z+7kcAZn37A+/PmkbdMmKSKRSuxFiseaow83RR5igvWUX0jpXn+jnKOwaeX0eVEHMizojdZQ32Pk5OZmaxCOudbxxL5eqmp2ixxhu2+M9pehEGkHHlKsdWrGFkp67sTrtsu8EKhRPxVGHmjaLMGYLMG0dLtmne3OZr52hbe7dqxnqHHsFxVFgh5uyYNa7wgjmbTX9M42qiJoxCo6PoOvFGk/msEWGXEhL45a13SqYnalPntA6PLrFNiTOFJ2B4HyhR5lwcKcicgSvDVVh77Rxpq6e/MwvxbiFWkE/m3MUUJFwgrGZ1Gt9xK4HRpc/9aEhpFcjeldDTK9SVxEts/GOafr3PvbcTGFp8bklbOuYv+uI7rpqYTzA/P9/sPkqcKTyNwnvDUwQZFD2zvEGQgftE9jeHO8QKM6Ssa+cIez39PWkOrxZiBUkpcEmbgDvt8FHOLl1B/RvtE+DVXpXMWyrW7nmLycvOBqBq4wa0Gj6o2HZbRFidfB9m/PmXfr3vgP6sWqZF6w+yMsaUEmcKT0B5yVyHs+KSWYO7iS9zKK9X+fBqIYbRNCrpp8+6yBDTWFvB3LmPyYFlq/TLnW8ej4+vr37dFhHWOjya6VP/JC8vD4A27dszcswYvRA7eSK+XPYWHsMeuLugs9d5WoK7XwtPwtNFmTGeItJcLcg8RXw5moogwArxbiFmRE5yiqtNAMovwEpLd8UD+9KJkwZR9ANo1Kubfpu1IsxQNCyaO0+/PHz0tTRuVjTdzbJFi7j9hpvoO6A/vfr1pX7DhjZaX34cLXQMxY0zRZUtKNHnGNzlXi8Pljz33EmsOVuQKQFWscSXIV4txISfHy2feIg9730CQF5GBlJKl04SbE1Fs8WT5IoH9oHlq/XLDbp34ZpGtt1Mhi/x9KtXWbNihX59yIgR1K1Xj2sGDWTFkqUALF+8mOWLFwPQtkN7HnrySQYNG2rTsd0ZdxdfrsLa6+Jtws3c88HTBJoh7jgTgCMFmavEl7v176uoAqwQrxZiwdViCWtQD9/gIPIzs8hLzyAr8RLBsTFOt8VeXjBbKI84K8sOKSV/rCoaNHzduHHWGafD+KW6ctkysnV9zpq1aEFc/foAfPXzTzx4x116AVbIzm3buevmCUz+5CMmTJpkkw0K78YS4eYNYs0bvGfGuINwsFfHfleIL3PvH1f376voAqwQrxZiwtcX4eNDWIN6pOzVKlmN7Cxa2fDjl6eSOtoLZgv2Os7Z4yc4ffQYAEEhIXTs39fqMky9IGf9VTQCc8jIEfrlkNBQfvprKsePHmXtylWsXbmKNStW6EXb/x57glPxJ3nmpRfxNeinplBYgjmx5ukCzVvEmTsIMnCvEA7msFbkOFOUKQFWHK8WYmHBwfRu1QzfHl1ZoxNiO2bPp9WwQWXsWRJb+je4owCzN5fOJeiX6zVrSlBwsMX7mnvpLZ43n2WLFunXh107sth2IQQNGjWiQaNGTLrnbs4nJHDHjTezd9cuAL7+5FMSL1zk/S8+U2JMYRdK86Z5qkjzxMEAhXiKIHOmALOnuHHElFdKfJnHq4VYIbXbtNQvn92zz2H9xGypaJ4qwAqJrlYUOf/s8RMW72fuxZafn8+7r79eLO2FJ5+mc/du3HjrrdSJK3m9qlWvzpTZM3nk7ntYvVzrVzbjzz85n3COtz/6UN+sqVA4Am8IjeKJcczA/QSZM3GmsCmPt0wJsLIRUkpX2+AwqjdrIm//5StkQQHvdC/ygk36+UuqN3NeFGRzuFqESSnJz8vDz9/f5jKO79vPI0NHARBbqyY//beqzH1K8y5sWv8f44aPMLs9rn59mjZvTpPmzWjaojnNW7Ykrn59hBAUFBTw3GOP89dvv+vzBwYGMmzUKEaPu56oKlUAaNioEaGVKll4hgpF+fA0UVaIp4kycL0gcyTuKmjMXXNH2mvu3TmiTqNtUsqODjuwg6gQHjHh40PTa3pzcMUaAPYvWelSIeZqAXb+1Gl+ffdDdq5dT2Z6OsNvu4W7XvqfTV7Co3v36ZcbtmpRZv6yOkxfvnSp1O3xx48Tf/w4i+YVhbZo0aoVk+65m1HjxvLOJx9TJSaGLz/6GCkl2dnZzJ42jdnTivqchYSGcv+jj/DI00+5dAStomJgWOc9SZR5opfMXTxk9sJdxZchjrbR1e9LZ+DjagOcResRQ/TLu/5dQGbaFafb0KNGXadUqrTkZL55+XXu6N6X+68Zwi+T3+f8yVMAbFqynEeHjWbt3PlcSUkhLzeXOT/8zIs3T+JcvPUP3CO79uiXG7Q0L8Rah0dbNGqtWo3qJtP79L/GbH+vfXv28PTDjzBm0BAyMzJ45qUX+XfFMtp17GAyf0Z6Oh++PZnpU6aWaY9CYU8K7wNPCklS+NzypBdi71bNPELEmMPT7bcHnlbnykOFaJoEKMjP5/ub7yLp5GkAet41kedefqnEPo7699ejRl2klOTl5OAXEOBQT8xHjz/Dipmzi6X5+PgQGRvD5fMXzO4XHhnJR3NnUq1ObYuOc/7kKR4YMIwc3YjFN/74mXa9e5bIZ81LJz8/nyG9enNof9E/2sbNmrJsw39kZWVx9NBhDu7fz6H9+zmwbx+bN2wkKzNTn/f2e+/htXe1ScKllOzdtZvpU/9k947t5ObmcfL4cdLS0gCIqVqVlZs3EV453GL7bGHjuvV898WXHNi7l+atWvHCG6+5NACtwj3xJG+ZJ3nJwDM8ZBVdeBVSHvHlqU2TXi/EflgyX7++ctYcPnzsKQBCw8P4dP4/VKtbp1zHMPdAyrp6lZNbdpB98Bh7Nmzi8vkLZKanU5CfT2h4GHUbNyauWRMGjL+exm1aW33cc/En2bh4KZcSztO6e1c6D7gGHx8fcrKymdCuC5np6aXuH1OzBg+/+yb/LVzCoilF8zkOGDeGxz58t8zjSyl5ddLdbFupBXOt36IZH8+dha9f8dZuW/75b9+yhbsn3ErixYv4+vry+Y/fM2L0aJN5U5KT+eazz/nq408AbUTlgtWraNG6lcn8Genp9O7QiYvnzwPQsHEjHn3mGXr06U2VGPvGlysoKOD9N9/iy48+LpYeGRXF+59/xqDhw+x6PIX34CmizJMEmTuKMSW+NOzl+VJCzA1p1LqV/GR+kWcoPy+PBwYM04/uq9OoIe/PnkZoeJjJ/aWUnDl6jOzMLBq0amGRFysrI4N/fviZmd98T+bV0sVQIV0G9mfCE49Qv0XZI29Sk5L4+oVXWTd/YbH0hq1a8uSnH7BjzTq+e/VNAPwC/Pnm55/59YcfWLtylT7vgCFD+PCrL4iMigLggzff4rMPPgS0/lOb9+8r00s0759/eGDSHYAmfuYsW0LbDqabAm0hLy+PA3v3ERYeVuaoRyklE8eO04+YvPXOO3jrww/M5p87ezYP3n5nifRGTZvw0Vdf0qZ9+/IZr+Pjd97l43fMi9oeffrw5gfv0aBRI7scryyiSbNpv8s41mOoKB0lyuyLOwgyJcA07N30qISYG2IsxAAObNvB/26YQF5OLgB1mzRm2K0306xDO1IuXybpwkWSLlzk3Il4dqxdr2/K6z/2Oh557+0SHh9DDm7fwVt3P0hyYqLZPD6+vhTk55vc1mPYEG5+/BHqNin5Ym4dHs3yxUt45uFHSLx4scxzB3j8uWd5/LlnATh98hSXLyUSERVFXL16xfJJKRnQrTtHDh7S7OjTh29+/YXKEZVNlnvm1GlGDxqs9ypNvOtO3vzgfYtschQb161n/Agt3ljliAi2HjpAYGCg2fy///Qzb730MhlGnsMbxo/mp+8+Kbc989ft4YaR11J4f/Xpfw2DR4zgk3ff0183gJjYWP6e9y8NGze26Ti2iitnoUSc/XF3YeYpgqwQZwkzJb6KcFTfLyXE3BBTQgxg5ew5fPjoU1aXN+l/TzP2/ntMbruUkMCjw0aTejlJn1azfj16DBtC6+5dqde8KSGVKuHn78/lCxc4efAwy6bPYu3c+cXKEULQe9QIBowdw7h+AwgMCmLl0mX88fPPrFi8pFje3tf0IygomFXLlpGTk1NsW2RUFKu2btZ7vcrC0MMFmkB47NlnuHHirfgbhLc4cewYN40azbkzZ7V8VauyYtNGs6LNWRQUFNCrbXtOn9IGJXz9688MHzWqRD5D4XL+wkV++nkqb73ziT6tbp1a7N6+Cr9SBLclDBgylg0btwLQu1c35s7+HT8/P5KSU3jhpbf5fcp0vUiLiozgsUfv5Zq+vWjdqlmFC0KrxFr5cFdh5mmCzBzOmlWlIuDozvdKiLkh5oQYwD8//Mwvk98nLzfX4vIiY2L4bs1SgkNDS2x7+96H+G+hNv9heGQkk55/mv7XX1eqBw3gxIGDTPnoMzYuXlpim5+fH5UjIkqEdIipWpX3P/+MawYNBGDX9u288uxz7Nm5i/z8fK4ZNIjnXn2Zxk2bWnxuUko+mvwOn75X3LNVv2FDPv7mK9p17Mih/fu5+brrSbygeQkDAgL4Yeof9B0wwOLjOJIP356st7//4MH8/PefQNleozHjb2fxkpX69Ucfvoe333jeZjv27T9E5+6DAfD392fvjtXUqlWjWJ516zcxZvztpKdnFEuvUiWa9ya/zA3jSorIiowSa9bhbuLMW0SZKUwJNSXAinDmyEclxNyQ0oQYaGEe1s5dwJp/55GalERUbCxRVWOJio0lumosjdu2oV6LZtzTawBJuubA5p06cu9rLxYL1XB0914eG3Gdfv3tv/+gdbcuFtlY2Jl9986dfPT2ZFYsKSnIDLn2+jG8/t67REWX7ARfUFBAXl4eAQEBFh3bFPPnzOH1518g4ey5Yulh4WGkX02noKAAgKDgYH6Y8ju9r7nG5mOVl32793A+IYHe1/TD39+f+BMn6N1O66fm6+vL+dN7CQkpe8qlZSvWMGrMRP161y4dWL54ps12zZ23mBtvuReAJo0bsH3zcpP5Nm/ZzoTbHuDcufMlti1ZMI0e3TvbbIPCerxZ7LmLMPNmQeYu2Cp87P3buCL0hBJibogpIWbtKL7daZdZMfMfPnr86WLpjdu2ZsiEG+k9cjiv33Efu//bAED3oYN5/tsvSi2zNBu2b9nC7GnT2bh+vT6EQ3SVKoybcDM33zbRKdP1ZGVm8vN33/Plhx/pQz0YUimsEj///TddundzuC3m+O2HH3nxKe03qdegAa3atiH++Al279ihz7Nnx2rq17PsYfDXtH+4857H9Ot33TGBxx+5j7g4y0J5GLJu/SYGD79Bv/7tVx8w4abrTQ72uHo1ndlzFrBs+WpmzCoKUjvhpuv57usPrT62wn54szAD14ozJcgsw1PiaBn+nva22Zp5XpUQc0PMecSsEWO70y4jpeSnt95l9nc/lppXCMGXS+dTp3HZo+AssSHp8mXOn0ugQeNGpXY8dxTxx48zafyNHD96VJ/Wsk0bJn/yEW3atXO6PYXs37OX6wZrwVtLY9Wy2XTqaJmdV6+m06Jtby5dKrqxQ0KC+fyTydw4frRV9uXn59O993D27juoT6tTuybDhw5k0m030rKF6SbjN9/+iMnvfaZf//6bj+jTqxs1a5oOcqtwHN4uwkAJMU/AU4SYI7HkXVlYlz1ViFWYyPq2UPjjCiG488Xn+GT+P/QZNQK/ANNzMw66cbxFIsxSoqKjad6qpUtEGGjzOi5at4Z5q1awftdOjl48z4LVK10mwlJTUnnzxZcYeU3/MkVYSGgodeta7s2qVCmUf2f9Rru2RfHHMjIyue/Bpzl2PN4qO319fZn7zx/FBNep02f5+rtf6NJjCGPG315MpBVSu3atYut33/cEjVt04857Hi8xGEPhGC4TXiFEmML9USLMcjxttgpjlEesFMz9Y0xNSmL59Fks+Xs6Z44eB2D4xAnc9dL/8LdCNHlyxXEmeXl5/Pnb73z41tskXS76TYJDQvjpz6mkpaaSkZFBbLWq+Pn6cT4hgdbt2tKgUSOrwztIKVm9ZgPDR92sT/vi08ncfttNVtudlJzCiy9P5p85C0g1mlKratUYDu5ZX6w/35UrV5l4x0MsWbqqRFnvTX6ZB++/o0S6wn5UNAGmPGLuixJhGta+I+tERHmkR6xCCjEo+we29CF1NSWVnOxsoqrGWm2fEmJlk3T5Mvffdjsb1q0rlt6hS2fefP99sxH0jbFGkJ08eZqO3QaRkaFNnfTn799w7cghZexlnpycHNb9t5kff5rCnLmL9GEr/pn5KwP79ymWNyMjk5gaJUdcjb52KFN++9pmGxSlU9FEWCFKjLkfSoQVUVGEmGqaLCeVIirbJMIUZZOSksL1Q4YVE2G1atfmi59+YNaihRaLMLDsRZuQcIGXX3uXrr2G6UVYndo16dSxHX/+PZs//57N5aRkq88jICCAa/r2ZMpvXxfzaj33/BtMmHg/142bxOnTWly2Xbv3mSwj3MzsD4ryoZoiFQqFqylf1EovxVn/EnenXVZeMTMUFBTw2D33cuzIEX3aI089yUNPPkFQcNkhKUxxmXCTnrHU1DSef+ltpvw5k1yjuHKnTp+lScvu5OtmQ/Dz86P/Nb2447abGDF8kMnjpKSkcvVqOjVrVi8xUvK6UcP44itt0MfBQ0c5eEgbCDH1r1k8+/TD+PmVDObap3d3Xnr+CetPWGEWJb4U7ojyhlVMKqxHzF3i6ihMs3Du3GIx1T797lueevEFm0VYIcYv4IKCAsbeeCe//PZXCRFWSL7BlFR5eXksXrKSGybcw/c//l4s38XES9xz/5PUjGtDk5bdqV6nFdeOubVYx/wundszeFC/Esf46NNv2LJ1ByEhIfq0yIjKnD+9lwX/TqVGjWo2na+iiELvlxJhCndEibDiVCQnRYUVYuZwtkBTgtA0q5Yu0y/fPOk2rhs/zm5lG76MLyZe4r8NW8rcp1vXjnTuVHy06OtvfkiarhP+uXPn6d57OFP+LAoEe+XKVZavWMvAoeNYu24joI3A/eOXr/jfM48UK+vq1XT6DriOv6bN1kfhT05J5bc/ptl+ogolvhRmcYfJvwtRIqxio4SYwi1JOFcU2f+aQaabAMvLZcKpGhvDnbffXGKbEILu3Trx/juvcGT/RpYtmsHKpbPZsWU5oaGa1yopOYUZs+YCmkcrIeGCfn/DPl1paVcYdf1E5vy7CNDik734/BMs+HcqgYHFZ0H46eep3GEwQvOV19+zOnxGRUeJL0VZFIowdxJjiopLhRZixt4o5Z1yH0JCiubztGY+UGtJEpV55eMvmPLr17Rq2YxePbrwwbuvcmT/RpYunM4D991erFmwcaMGvPJi0YTx73/4Jbv37Oeb737Vp3339YecO7mbdavmUrVqDADZ2TlMuO1+Pv/yB/38kl06t+fj998oZk9Kahr9r+lF8+ZNAMjMzOLBh5/Fm0c32wMlvjwPV3mB3E18KW9YSSpSsyRU4PAVhRj+4K4UYhWt4pXFvRNvY+G/Om/T118x9qYbXWxREclJSfRo05arV66W2NaieVM2rV+o76QfH3+aUddP5OixE/o8gYEBNG7UgIOHjpbolxYWVokdW1Zw/vwF+vQfre+fNvefP7imb08HnlX5ycnJ4d95i1mwaDnx8aeIi6vDsCH9GTtmpEOOp0SXfahoISzcaZJuJcJMY+v7UIWv8HCUN8x9WL96DSsWL9GvG3Zgdwcio6J4+a23TG6765FHSRKV9SIhLq42yxbPoH271vo82dk57Nl7oIQIa9O6BQvn/kX1arG0a9uKOyYVNVG6e1+x9PQMBg4dx213PMzf0/5h0+bt/D3tH26742FWrFpXdgEWojxfivLgTt4wJcIUhVR4IeYuAsxd7HAFBQUFbN20ibdfeZV+nbpw06jRZGdnA1CtRnX6DRzgYgtLcuPEW/n8h+9p1qIFALXr1OGZl18qNqigUDDEVIlm4dw/ef7ZR2nWrHGxcho3qs+tE8bx0/efsmbFHNq1banfNn7sKP3yoUNHcWf+mDqDrdt2mdz26+9/l7t8Jb4UjsSdBJqi4qHiiFGxRZArkFJy+MABtm7ezM6t21ixZCmJFy+WyBcUHMz7n39GsJt5xAoZNfZ6rr1+DHl5efj5+ZWIGVbIZcKhUjgv/O9xXvjf48THn+bU6TM0b96EKtFRZstv2LCefvlE/CmklGaP4WoMm17j6tZm3Nhref/DLwE4fPhYucpWAkxhD9xJbClvmHkqYjcdJcQUTuVU/EkevONOdm3fbjZPcEgII68bzZPP/4/qNWs60TrrEULg7296EnhjDJsr4+LKnpA8pko0lSqFcvVqOleuXOXS5SRiqrjnQyokpCi+29jrRzJsSH+9EAsIsOz6GKMEmMKZrNlzwCl9xZQIUxijhJgb4e2R9s+cOs0NI0Zy9syZEtuqxMQwYMhgBg4bRq++fcoduNWdKRQYZc1/KYSgXlwd9uzV/smfOHHS7YTYmrUbePb5N9i9Z78+beGiFQy4prd+3XBic0tRIkxhT9zFG6ZEmMIUSogpHE5OTg6/ff8Dn7z7Hmlpmvjw8fFh8PBhtOnQgc7dutKuY0d8fUtO7+PNWCLI6terqxdi+/YfonOn9k6xzRK2bN3ByOtuJS8vr1j6vv0HiT95Wr/+34YtjLvxLpKSk4mMiODuu25h8MCSswsUokRYxaFHjboOHzlpjQhzlldMYRpvdkSUhhJiboa3ecU2/beB5x59rNickf7+/vww9Q/6DRzoQsvch9IEWceObZkzVwsE+/W3v3LzjWMIDAx0qn2myM/P5/GnXi4hwgBq16pJdFRksbQFi4pmSli4eDlvv/ECjz58d4l9lQhTeCvKG6YwR4UfNalwHEcOHeKWMdcXE2H1Gzbk73n/KhFmAlMjA2+5eay+aW/f/oP06T+aP/+eTWZmlitM1LNt+y527NyjX1849082rV/Ej999woolMxk6pD8P3n9HiZkDCnntzfdJSk4plqZEmGvwpj9+xtjSJOmIZkwlwhSloYSYwmG8+eJLZGdpgiEkNJSX3nyDJf+to2OXLi62zL0xFGSxMVV4/rlH9dv27D3AXfc+TsOmnXny6Vf0zZbOpnbtWsUGKQwdeRN9B4xm2/ZdVK9eFSEE701+mSMHNjH9zx/4649vmT3jF6pXrwposdT+mbNAv78SYQpvRYkwRVkoIeaGeEM4jUuJiaxevkK/Pn3+PO5+6EGbOm5XVArFyVOPP8CL/3u8WB+6lNQ0vvn+V7r2HEqf/qNYtmKNU22rXi2WJx+7v1haZmYWX33zM8dPFPX5iY6KZNjQAYwcMZhBA/ry6ENFzZELFi4HlAhTKBTe7ZktiwrdR8zUD6+mObIPC/+dS0FBAQCdunWlVds2LrbIczDuKyaE4H/PPsqk227ij6nT+fW3vzkRf0q/feu2XYwaM5F7757Ih++95rRYY7l5JecA7dC+DbVqVje7z6CBfXnuhTcBra/YilXrik3dpESZa3DlVG/GHiN7dt4v7HhvaXOjvTrqKy+Y5XjTe89WKsxck+X5sR31YPLWCiilZEjP3hzYtw+AN95/j9vuvsvFVrkvZYWxMKagoIA1azfyy+9/MeffReTk5Oi3vfv2Szz0wJ32NtEkteu1LdHP64nH7uP1V54tVQxOvP1BZs6eD0CVKtFsWDO/2MTqxihx5jrcxTtv75GVhsJMiS/n46h3n6fONenVQqx1u3Zy/qoVZWe0EWsfUt4qvIy5lJhI+0ZN9OtbDu6najXzL9qKiLXiyxznL1zk4Uef149KrFIlmuOHNjslFEj9Jp24cCGxRPovP37GuOuvNbtfQsIFuvUeTmLiJQCefvJBXn3paauOrcSZa/BWYWYLzhJervRW2hNnvP+UEHNDHC3EzFF4s1QU4WVMVlYWLWrX1U9q3XdAf36dPs1tp+dxBvYSXqbIzs6mcYvuXLqk1btXX3qaxx65x+KI/7by7fe/8ezzb5SYvLx3z64snPdXqft++vn3PP+SNnH6mNHD+f2XL+1ikxJozsVdhIGzhJkrxJe1uMtvAs5/B3qqECuzs74QYqwQYqYQ4qQQIlMIcUgIMVkIEWYib1chxCIhRIoQIl0IsUcIcaNRnr5CiINCiDQhxLdCiACDbXFCCKn7XGOi/HVCiFU2nqvTaB0eXWFFGEBQUBA33TZRv75q2XI2b9joQoucTzRpxT6OJDAwkHHXj9Svv/rG+zRr3ZO33/mES5eTHHbce++eyIE963n7jReKpRvOkWmOAlmgX46Ojiwlp3UYX3dn/QYVlcJnnaufdz1q1NV/HFWuo0WYva6lYTnmPo7CWcfxNizprP8UcAp4HjgDtANeBfoJIbpLqT1RhRDDgdnAVOBmIAdoDgQVFiSECAWmAe8CO4HJwKPA+yaO+xbQzYZzUrgBr737DovnL+BCQgIAZ0+fxlt+Tnd8qf/v2UdZsXIth3QTbCckXOCtdz7h59/+YsmCadSLq+OQ4y5fsYY33v5Qv+7n58fjj95X5n6GnnhneUot/d2UV802zL14Pa3zvyd4vTz52IqSWCLERkopDTuCrBZCJAG/An2BFTrv2M/AV1LKxwzyLqM4zYDTUsoPAYQQbwD3UFKILQEGCSFGSinnWnoyCvdh3ux/SL5c9ABu2aa1C62xHHcUWZYQHRXJ8iWz+PyLH/j5tz+5eFHrf3Xu3HlGjJrA0oXTS+0Qby05OTk88vgL/D5luj4tODiIb758n/r1yn6R1aldNJn79Bn/8shDdztMLFqLveqAEnQarhZoZQkzZ3ayVwJIYQqb+ogJIZoB+4GJUsrfhRB3AD8CdaSUp0vZLxY4AowC9gBfAWeklE/qtscBJ9DE2X1oQrGt1BkphFgH5Ekp+1pip6v6iFVk8vPzefaRR5k2Zao+rW2H9vy73FiTuwZPFVrWkJOTw4xZ83j4sf+RlZUNaNMOffLRmwwZpM3xKKXkux9+59PPvyM5JZXR1w7li08nW9zJ/70PvuC1Nz/Qrzdt0pDff/mK5s0aW7R/enoGHboM5PSZswA0adyAFUtmERFR2ZpT9TiUOCsbd+rjVF6U8HIuntpHzNY4Yn1034VjgHsCSUArIcQCNM9XAvAD8KaUMh9ASnlRCPEisFR37K3AAybKl8CLwALgBqD0nr8KqzEnSMr7ovjthx+LibC69erx4Vf26YhtKRVBbJVGQEAAN984hqjICG6YcA95eXmcPnOW68ffTru2rRg4oA+bt+xg1er1+n1++2MaNapXY/SooZw5c45Ll5O4nJTM5ctJ5Obm0bFDG0aNHKIfAPDn37P0+44fN4rPP36bSpVCLbYxNDSEX3/6jKEjbyI7O4dDh49x34NP88lHb7Jz51569+pGSEiw/S6Km2CqbipxVhxXe9DKixJfCmux2iMmhKgJ7AB2SSkH6tIWoYmzbOANYBswAHgO+FxK+bhRGZFANHC8sI+ZLj0OzSN2t5TyByHEWqAq0FxKmac8YtZjD1Fi6Ysi6fJlerfvSFpqKgCjxl7P5I8/olJYiXEd5aKiCy1rmL9gKfc9+HSJeF+2MHRwf6b9+T1Hj52gXaf+gCaoTh7dTnBwUBl7m2bajDncftejJdLrxdVhxdJZxMZUKZfNnooSZ5ahAnArDKkQHjEhRCVgDpAH3G6wyQetU/4LUsqPdGmrhBDRwINCiFellKmFmaWUyUCyBYd8HlgDTELzrlli4z1oTZvUrF3Lkl28BkcJFEu9Zx9NfkcvwurWq8cHX35BYGBguY+jsJ3hwwayfctyXnvjA6b+NZPs7KLgr0IIJtx0Pbt277NozsqFi5fz+x/TiYkpegG1a9PSZhEGMH7sKJavWMsfU2cUSz8Rf4obJ9zD0oXTnRITzd2w5l6oyKLNWd4zJboUjsRij5gQIgitqbAt0EdKucdg25/AjUBro/TrgFlADynlfxYcIw4Dj5gubSHQAmgELEd5xAD3Ey1paVeIa9RB/6L/YeoUBg0bqt/ubvZWRJKSU5j9z3wOHzmOn58fN91wHS1bNOVi4iUefvR/rFy9nuDgYC5dusyN468jOjqS6KhINm7expKlqwCIqBzOzTddz1ff/AxA717dWDj3z3LZlXjpMr37Xcup02dLbFuxZCZdOncoV/kK2/A2gWeJOFOCy7Pxao+YEMIfmAl0BgYYii0d+3TfxqqucFx6AbbzAlpfsrLHxHshniJgFi1ZoRdhLVs05cah3REeYntFISoygjtvn1AiPTamCn9P/d7sfhkZmXTqNoj4k6dJSU3TizCAFs2amN3PUmKqRLN21VxuvuU+1m/YXGxbjepqRgZXUdazx9OEmieLrGjSPO56W4u31TdrKFOICSF8gClAf2C4lNJUZM5/0PqGDQH2GqQPBrKM0qxCSrldCDETrZnyHJBaxi4eiacILnPM+XeRfnnM6OEVOoq+txESEswvP37G4OE3FGvaDAoK5I7bb7bLMT7+9NsSIqxD+zbUqlXDLuUr7I8lzyxvfnk6gtKuaXneEe7yO5TnHLxZjFriEfsSGIcWYDVdCNHVYNsZKeUZKeVeIcQvwOs64bYdrbP+XcAbUsqr5bTzJTQxFwusLmdZgPUVwl4VwNMFlynS0zNYvHSlfn3UtUNLya3wRDp1bMe8f6bwyuvvsX//IZo0acirLz1tcbiKsjhy5FiJtN179rN12046dWxnl2MonI/q62YeZ74LHHGs0n4vR/ZX9sZ6YokQK3yrvqD7GPIaWpR9gHuBs8DDaCMd44EnpJSfltdIKeVBIcTvaJ32rcYelcIbBZS9mDl7HpmZWQA0a9qIpk0autgihSPo3q0TSxdOLzujDbw3+RXOJVxgx86iXg+5ubm898GXTP/LonE6Cg/HW2c+8NZ3h6vOq/C4nlYPSqNMISaljLOkICllDlrsrxdtNUZKGU9RvzLjbbdTfKRmmfiR77U3gbuwect2Hnuy6CcfrbxhChuIi6vNmhVzmDN3EbfcVhRaMDzcvqFPFJ6POzWJqveL6/Am75itAV0VCgD+/Hu2vt+Qv78/d991q4stUngqPj4+jBo5hG5dO7Jh41YAWrZs6mKrFJ6IEkgVA2/xjvm42gCFZ+PrUxTj6dYJY6kaG+NCaxSezq+//60XYX5+fowcPsjFFikUCnfH04W3EmKKctG8eVFn7StX011oicLTuXAxkRdfnqxff/zRe2nYoJ4LLVIoFJ6CJ4sxJcQU5aJF86I4Uvv2H3KhJQpP57kX3iQlVXuY1ourw7NPPexiixQKhcLxKCGmKBfNmjbWxwzbv/8Qh02EIVAoymLp8tVMmz5Hv/7px2+Va+okhUKh8BSUEFOUi/DwMHr1LAot9++8xS60RuGJZGdn8/iTL+nXbxg/mv79ernQIoVCoXAeatSkotw0a9qINWs3AFg0ebRCYcja9Zs4EX8KgMiIyrzzls0RcBQuIi/ZeNY7Db/IVk62RKHwPJQQU5SbuLp19MszZ83jxnGjGTqkvwstUngSBw8e0S+PunYosTFVXGiNojTMCS5b8yuhplAoIaawAxNvGcdvf/zNgYNHkFLy8OPPs7fvaoKCivr45Ofns3vPflauXs/KVevZvn0XNWvW4MH7buemG68jICDAhWegcCWnz5zTL9etU8uFligMsVZ02fsYSqQpKgpKiCnKTUREZebNmUL33sO5cCGRhIQLzF+4jOuvG0F2dja//j6N9z78goSEC8X2S0lN44FHnuXNdz7mzdf+xw3jRrnoDBSupLbBxN5Hj51woSUVE2cILlswZZcSZwpvRAkxhV2oVjWWOyfdzNvvalOLTrz9If6dt5hVq9Zz6XJSqfueO3eeO+5+lOzsbCbeMt4Z5irciPbtWuuXt+90T1Hgbbir+CoLQ7uVKFN4C0JK6WobHEb7dq3lulVzXW1GheHkydO069xfP+WRMVWio+jfvzf9+vSgc6d2zF+4jC+++pELFxIBbYqbX3/6nDGjhzvTbIWLSU/PoFrtlhQUFODj40PCqT1UqhTqarO8Dk8VX5agRJkCIDQibpuUsqOr7bAWJcQUdmX+gqXcMulBcnKKxFjtWjW5797buPeuiSViQ6WkpDJ05E3s3rMf0Ka1+Xvq9wwZ1M+pditcS6fug9mvCwi8ZME0enTv7GKLrMNdRw16s/gqDVdfd4Vr8FQhppomFXZl+LCBrFo2m1Wr/yMwMIDGjRvQp1c3fH19TeaPiKjMv7N/Z/Cw8Rw6fIy8vDwmTLyP2dN/oXevbk62XuEq2rdtpRdi27bvdnshZqnAcVVTWkUVYIWoJkyFJ6GEmMLutGndgjatW1icP6ZKNHNn/8HAoeM4eeoMWVnZjLvpLub98wedOrZzoKUKd6FD+zb8MXUGANt37naxNSWxh7AxLsPeAqGiiy9zKFGmcHdUZH2FW1CzZnXm/zuVatViAbh6NZ2hI2/ig4+/KtbMqfBO2rcrekFu3boTV3eZyEveU+zjrsdwtI3ehrpeCndECTGF21Avrg7z/plCdFQkAJmZWbzy2nt07z2ctes22v14lwnXfxSupWWLpgQFBQJwIv4UGzZuderxnSG8rLHBHvkUpaOun8JdUEJM4VY0a9qIBXP/pGWLpvq0AwePMGTEjdx93xNcTLxkl+MYiy8lxlxLUFAQN46/Tr/+2RffO+W47ipojIWhEl8KhfeihJjC7WjZoinrV89j8psvFgtjMPWvWbTreA0///qnzU1XpXnAlHfMtTz0wJ365XkLljo8uKsSNQpPqQOeYqfCNpQQU7glfn5+PPLQXWzftIzrRg3Tp6ekpvHQo//jrckfW1WeNSJLiTHX0KxpIwYN7AuAlJIvv/7JYcdSLzZFIe5eFwrtc3c7FbajhJjCralZszp//PoVs2f8Qr24osnFJ7/3Ge+891mZ+9vq5VLeMdfwyEN365enTZ9Dfn6+3Y+hXmgKT0U1T3snSogpPIJBA/qyZcMSvccE4I23P2L+gqUm89tLSClB5lz69u6uHzmbkprGrt377Fq+eokpTOFp9cLT7HUGnvycVkJM4TEEBwfx5+/f0K9vT33anLmLiuVxlHDy5JvckxBC0Kd3d/36qjX/2a1s9fJSlIY71o/SbFLeMe9BCTGFRxEUFMR9d0/UryclpQDO8Vwp75hz6NOrSIht2FD+MBbqhaWwFE+sJ55os6I4SogpPI7IyAj98sWUK04XR0qMOZawsKKRsuUN7KpeUoqKgKrnno0SYgqPw1CIpSYnu8QGJcYcx4n4U/rlevXqlJJTobA/7iJqrLVDeX49FzXXpMLjiIqK0C8fPXyE3Nxc/P39nW7HZcKJJs3px/V24g2FWJwSYgrnk5e8x2XzUpZXTDl6TlN3xZOfxcojpvA4oiIjCAwM1K+PHzGS1cuXu2R+QuUZsz8n4k/rl5UQU7gKV3iXHHFMNSuD+6OEmMLjuBJQhbsefEC/vm3TZm69fhxDe/Vh6cJFpeyp8AQMPWJxSogpXIizBIyzj6NEmXuhhJjCoyj0QD3z0os8/tyz+PgUVeH9e/dy180TWLNihUtscmcMJzg39XEX8vPzOXX6rH69bp1aLrRGodBwpHBx5STzCvdACTGFx2AoGIQQPP7cs6zZvo1J99xDcEgIoI2ym/zKa6Rfveoy25xNWSLLEtvcRZBlZWXro+mHhAQTEhLsYosUCg17Cxd38Ey5gw0KEK7oV+MsWrdrJzeu+sfVZlQ4XPFCP3fmDH06diY7KwuAuPr1+eTbr2nfqZPTbHBUZ1FXXE9XdXxNTkmlVlwbACIqh3P25O5yl6leNAp7Yo/O7+5YJ72hU39oRNw2KWVHV9thLV7vEXOHf/kVCVdd7xq1avHIU0/q1+OPH+f6IcNYt3p1ucvOzc1l3+49ZXrZ7DmlkqubDV113OzsbP2yf0CAS2xQKEqjPCLKnT1Q7mybt+P1QgyUGKsoPPTkE3z09VdUCqsEaP2Nnn/8Sc4nJJSr3HtvvY2hvfvQvnFTHr7r7lJHaFpb19xBdJnDFTbl5uTqlwMDlRBTuCe2iBZPETmeYqc34fVNk/NXFXXc9uQ4I56AuwiJY0eOMLzvNWSkp+vTqlavTmhoKIGBgQQFB9GoSRMm3n0Xrdu2NVlG/PHj/DN9BllZWXz18Scltl83fjwffPm5yfhl5uqZu1wfW3HG/XPseDyt2/cFoH69uuzZUX6PpnqxKBxJWU16nlz/PK250lObJitUQFcVgNNxuJPIaNCoES+88TovPFHUVHnByCu2Y+s2pk2ZSt8B/Xll8ts0aNRIv23eP//wxP0PkpWZafYYs6dNA+DDr77Az6/4bVRYz9zpmtiDwvNx5D2UY+ARCwhwfpBehcJaSgv+6skiDFwb2LYiUSGaJg3xtpejO+CO1/TWO27ns++/o3nLliWEkiGrli1nUPeevPXyK+zeuZPpU6byyF33mBRhMbGxjB43Vr8+e9o0bhs3nsyMjBJ53fGa2AtHNlkeOnRUvxwRUdkhx1Ao7I2x4PKm/lbedC7uSoXyiBWiPGMVg9HjxjJ63FhycnK4eP4C2dlZZGVmkZycxLQ/pjBnxkyklOTm5vLtZ5/z7WefF9u/Tlwcw0ePIic7mxatWzNyzHUEBAQQEhrK1F9+BWDtylW8/sKLTP74I1ecoktxhIds4eLl+uW+vXvYrVyFwtF4u1hR3jHHUaH6iJnCni8RYy9BRRB7nuz52btrNy8/+yxbN24qsa1OXBwzFsyjWo0aJbYVFBTwwVtv88WHReJr8/69JvNWJMpb3wsKCqjXuBOXLl0GYNWy2XTq2K7cdnn7C1KhcDbuKsg8tY9YhWuaNMaaYJfWBs10x5Fw9sTTz61lm9bMXLiAL376gWGjrqVW7dpUr1mDG26ZwOwli8wKKx8fH55+8QXqN2yoTzsZf9JZZrst5a3v27bv0ouwKlWi6dC+jb1MUygUdkT9ubEvFbJp0hhHCwpndHJW2IYQgmvHjOHaMWOs3tdw4vHMjPRSclYsbG36X7R4pX558MC+xaavKg9+ka3Ui0OhsDOF95S7esc8iQrvEXMm3uQh85bzsJX1a9ZwYN8+QBNkLdso740httQPw/5hQ4f0t6c5CoXCQag/OeVHCTEX4OmCzJNttxdffFDUP2z8LROoEhPjQmvcE2vqyeWkZHbt1oStn58f/fv1cpRZCoXCzqiRleVDCTEX4omCzNPsdQTJSUn8t3atfn3g0CEutMY7OHLkuH65ebPGhIeHudAahUJhC0qQ2YYSYm6AJwqyikxAQECxiPqfvPueC61xbyyt10eOFgmxRg3rOcochULhBJQgsw4lxNwIdxdk7mybMwmtVImPvv5Kv759y1bSUtVADHNYUm+OHY/XLzdsUN+B1igUCmehBJllKCGmUNjAqLHXFwtfMXf2LBda4/nk5eXpl9Vk3wqFd6EEWemo8BVugKeEtSi0U3nGNIZeO5IvP/oYgFeeeY4GDRvRtaeKBm+IpXW7erWq+uWE8xfsaoN6AXgeicfW2KWcmAa97VKOwj4Y34sq9IWGEmIuwlPElymUINO475FHWDx/PkcPHSYnJ4e7bp7AS2+9SVz9+tSqU4eatWu52kSXYEvdrl69SIidOZNQSk7LUQLMvbGX2CrvMZRYcx1KmGlU+CmOnIUnC6/SqOhi7Myp04waOIjECyW9ODfcMoG3PvqQgADvbmqzR93eu+8gXXpoo0+rVIkm/shWhBA2l6dEmPvgDMFlL5Qocz+sEWeeOsWREmJ4r0hyJt4qyCypG7t272Pk6Fu4nJRcYtuA/r2ZeMt4/KJqkpmRSUZ6OhkZ6fj5+TNi9CiCQ0IcYbbDcNS9UlBQQN0G7UlKTgFg68alNGvayKaylAhzHZ4kuspCiTL3whJBpoSYG+LsSb8VrhFk7vAbnjt3nh9/nsrO3Xs5evQER4+dKHOfzp3asXDun6QHxTrBQutx9nW96ZZ7+XfeYgBeev4JnnnqIdas3ciff89i247dmpDNzKSgQNKze2duvWU8A/v3xtfXF1ACzJV4kwAzhRJl7kNpgkwJMTekNCHmDi9vb8WcGKso11xKyZtvf8w7739WZt4vPp3M7bfdZHa7s4StO/w2v/4+jQcefka/XqlSKFevlj6HZ40a1Zhw0/XcPLIN9etWd7SJCiO8XYCZQoky98FYlCkh5oaYEmLu8MJRVAyWrVjD4iUrOXnyNFeuXCU0NJTQ0GBmzJqnz3P3nbfwyYdvutBK9yEvL4/uvUewb/9Bm/bv2aUlt44fyLVDuxMSHGRn6xSFVETxZQ4lytyDQkGmhJgbYijElABTuBopJTNmzeXhx57nypWrALzz1os8/OBdLrbMfdi2fRejxkwkOSUVgOioSMaPHcWY64ZTrVoswUFBXE5KZupfs5g6dRqJl1NKlBEeFsKYEb2YOH4Q7ds0Klenf0URSoCVjhJlrqdyvZFKiLkbrdu1kxtX/eNqMxQKLlxM5PEnX2LO3EX6tNjYKmzduJToqEgXWuZ+ZGdnc+jwMTIyMmnfrpXJUad5yXvIzc1j8cot/DFtGUtWbSU/v6BEvmaN63Dr+IHcMLofVaIrO8N8r0KJL8ehhJv9UULMDWnfrrVct2quq81QVHAOHT7K4OE3kph4SZ9Wq1YNpvz6FR07tHWdYR6KqU75CRcu89fslfwxbRlHT5wtsd3f348h/TsxcfwgrunVDj8/X2eY6rEoAeZ+KOFWNkqIuSFKiClcjZSSbr2GsWfvAX3aHZNu4q3Xnyc8PMyFlnkeloyKlFKycet+/pi+jFnz1pKRmV0iT/WqUdx8fX8mjBtAg7gajjDVI1Hiy3NQosw0Soi5IUqIKVxNfPxpWrTtpV+fNf1nBg/s50KLPA9bw1JcuZrB7Pnr+H3aUjZvNz0AoHunFvTu3pp2rRrStlVDqsVGlcdUj0QJMM9GibIilBBzQ5QQqxhIKTl/IZFjx05QuXI4LZo3wcfH/Hz2+fn5JCRcwNfXl4DAAEKCgwm2YZTd+QsXWbpsNVGREQzo35vAwMASefbsPUDXnkMBqF2rJgf3rrf6OBURe8cEO3T0NH9MX8afM1eY7OBfSPWqUbRt2ZB2rRtq360aEhvjfX34XCG+4s8k88P0zWzefYbAAD9GD2zOjcPbEBrs3TNPOJOKLsqUEHNDlBDzbs5fuMj9Dz3Dpk3bSE27ok+Pioxg1LVDuXH8aLp361RMlP09fQ7PvfAGFy9eKlZWndo1admiGZ06tuW60cNo1LB+qcfesHEro8fepo9zVb16VUZfO5TR1w6lW9eO+Pr6sv/AYe65/0l27NREha+vL2mXj9nr9L0OZwRkzc3NY8nKrfwxfRmLV24x2cHfmBrVojWPmYFAi6kS4XBb7YWjRFdKWibxZ5O1zxnt+8SZZE4npFBQIAkM8NN9fJES4s+WnHkiIiyI28Z04NZR7YgID3aIne5IYtJVjp9OJjDAl+BAf6pEhRIdYd9ZNiqiKFNCzA1RQsy7MYzEbo5q1WLp1bMrPbt3JjHxMm9O/tiistu0bsH1Y0Yw9roR1K1bu9i2vLw82na8hhPxp0zuW6VKNCOHD2Lm7HmkGQjEFs2bsvm/RSb3qai4Mhr+hcRkVq7dwc69x9i55yi79h0z2afMFK2a1ePW8QMZN7ovURG29fXLzc0DtIEE5pBScjw+gfjT5wkOCqR1i/pUCjUtWHJz80jPzCLn4ja7hexIz8zRi6wisZXEybMpJKdl2uUYACFB/vTpXJ9eneLo1bEe1WPco/9kfn4BKWmZhIYEEBToX2LbpeQMzl1MIyHxCgmJaSRcvELCxTQuXL5K5bAg6taIpE6NCOrWiCA4yJ/120+yevNx9h+9WOJYtatVpl3zGvToEMegno0ICy3pYbeViiLKlBBzQ5QQ81527tpLjz4j9Ov+/v40a9qI8xculvB2mcLf35+oqAhyc3JJu3KVvLw8s3mbNG5AjRrVqRobQ2xsFfbuO8iKlWv12yuHhxXzyJnjmy/f59YJ48rM5+2461RE+fn5HDl+lh27j7Jz71F27DnKnv3HSxVngQH+jBjcjVvHD6RP99Zmm8Svpmey98AJdu09xq59x9i19xgHjpwiP7+AymGhVImurH2iwomOqkxUZBjH4xPYuHU/Fy+l6MsJCPBj+MCu3DFhKB3aNCY0JIjEY2v4eeZWPvp5HZlZuUSEBTFuaCvuv7kr4ZWsa3LPzy/gwPFEFq89zJJ1hzl2Ksmq/UtDCOjVsR4Trm1LwsUr/Dh9C6fPp5rM27BuNL06aqKsc+taJUSQJWRk5rBmywkysnKpUz2CDi1rWixQU9IyefGTJSxbf5Q8ndc0NNifqMohVA4PIjk1kwuXruq32ZugQD+G9GrMM3f3ITa6kl3L9mZRpoSYG6KEmPcybcYcbr/rUQC6dunAskUzEEIgpWTT5u38+fcsZs2er59E2pB2bVvx7+zfiYqMACAnJ4fDR46zc9de5s1fwuKlq8jJybHIjheee4ynn3yQtes3Meffhfw7b7FZIViRhZi7iq+yyMvL5/CxM5ow0wm0XXuPkZ2TWyJvnVqxjL22D7FVIggI8Ofq1Ux279dE19ET53DEs7ZGbDgR4UEmPSxVoyvx/H39GNizEQH+WriO/PwCLly+ytkLaZw5n8rZC6mcOZ+m+04l4eIVi8VFUKAfcTUjqVszknq1IonTfdetGUmgvx9ZOblk5+STnZNHfoGkZtXwYv3B8vILWLDqIN/8uYnD8eb/PAUG+NGpVS29t6xR3egyBdXqzcd55r2FXE7J0Kf169qAL18Zpb8Whpy/dIUv/9jA+UtXadEwlhUbj5m8pvbCz9eH5g1jEUKQnpnDqXMp5OTml8hXLSaMOV9PtHuzJXinIFNCzA1RQsx7WbBwGeNu0iLSDx3cnxl//1giT35+Prv37Gf12g2sWLmWwIBA+vXtwR2TbiIoyLynIDU1jXkLljJz9jyWr1hr1ltWv15d1qz8l8iIokCh+fn5bN6ygzlzF7F4yQoOHzmOEIIWzZsw958/iI2pUs4z9xw8VXyVRWpaOjPmruH3aUvYsftoucry8fGhoKB04RNeKZCm9WNJScssVbCYQwiIja5EgJ8vCYmWCy0Afz8falePIM5AaMXVjCSuVhRVoyvh41P+JlApJUfiL7Fmazxrt55gy+4zJkVJIVWrVKJXhzjaNq9B9Zgw7dz8fdmy+wzrtsdzJP4yx05dNrnvAzd35Yk7epVMf/Uflqw7YnKf0JAAsrPzTF63yMrBVI8Jo0ZsONVjwqgeqy3HRlciJS2Tk2dTOHkumZPnUkhKyaB10+r061Kfbu3qFmt6zMnN58Cxi2zadYo5y/Zz6ETR79y5dW1uHd2OZg1iqVM9gvyCAvztGAfPmwSZEmJuiBJi3svqNf8x7NqbAejVowuL5v/tkOOkpV3hRPwpLlxM5MKFRC4mXuLChUSqV6/KpIk3FhNh5pBSeu00O94qtixl74ET/D5tKX//s4rkFPPN0z4+PjRtVJs2LRpQv6qkRaOqNGsQS0iQP6lXs0hKySQpNYOklAwup2SQnJZJVOUQOrasScO6VfSC5+Dxi0z9dycbdp7i1LkU8guKnt9Dejfm/WeGsXzDUV7/cgVJBt4ga6gSGUKPDnEM6dWYXh3jbGoWLA+ZWbls3n2GtVtPsHbriXI1j1aJDCG8UhDHTxeVMbR3E/p1rU94pSB8fQT7j17k41/Wmdz/2mua8dHzI5BSciU9m6SUTFKuZFI5LIhqVcIIDnLMtZm/8iCPvlXy3eXv50N+gaRnhzjefnIw1arYry+dNwgyJcTcECXEvJdt23fR+5pRgNbUqH5n+1LRBZa1ZGXnsGDpJrbvPkLKxXhycvPx9fWhSb0qtGhUlSb1Yuz+0s7Jzed0QgrnE69QLSaMBnWi9duSUjP4bfZ2Zi7eS0JicYFYJTKEmlUrU6taZWpWDadm1XDdcmVqxIYR4mbhJM5dSGPN1hOs3RrPf9tPciW97AEVvj6CAT0a8fqjA4kIC2L8o1PZdTDBouN1b1eH3YfO06dzfd58fJBdO81bw4c/reXrqRvNbq9XK5Lpn02w62hTTxdjSoi5IUqIeS8HDh6hY9eBADRuVJ8dW1Y49HjWChO/yFYOssQ+KKHlGNwxOGp2Tp6+Y3n1GMd5cZxBXn4Buw8msH77SU6dS+Hi5atcuHyVrOw86teOonenerRtVp1GcVWK9UdLu5rF/z5czOK1h82WHVk5mN/eG0+zBrHOOJUykVKyctNxlq4/wp5D5zl4PLFEno4ta/L1a9cRWdm+oT88VZApIeaGKCHmvfy3YQsDh2od393JI1YocNxdiIESY47CHcWYQhM2m3efYcPOk5w4nUxGZg45eflUrxJGXK0oxgxqYfcRivbk5LlkCgok+49cLNZsWbNqOK88PIC+nevbpc8eKCHmbMwHsFEo3Jj4k6f1y3FGcb5ciScIsEL8IlspMeYACl9iSpC5F0IIurSpTZc27vO8sIa6NbQZHurViuL85StM/mYVAGcvpHHPi7OoHhNG5za1aVAnmloGzc0xUaF2E2gKx6CEmMIjOXXqjH7ZOOCqQuEOGHoVlChT2JM7x3aiTvUInvtgEalXsgBISLzCnGX7S+StVa0yrz0ygD6dS58tROE6zE/Ip1C4McU9YrVcaIln40kePE8mpkFvj23uUbgnA3s0YslPd3Dbde1LHVBw5nwq97w4iy17zpjNo3AtZQoxIcRYIcRMIcRJIUSmEOKQEGKyECLMIE+cEEKa+UQYlddXCHFQCJEmhPhWCBFgppxrTNiyTgixqnynrPAGThp4xOrUUUKsPCgx5jwKBZkSZQp7EB0ZyksP9mfTjAeZ8fkEXnm4P3eO68jgXo1p2bgqfr7aKz6/QPLIG/8yf+VBsnPMzyKicA2WNE0+BZwCngfOAO2AV4F+QojuUkrDKHeTgX+N9tePnRZChALTgHeBnbr8jwLvmzjuW0A3S05CUbFIT8/QT6QNWmBVRflQ/cWcj+pLprAXAf6+tG1Wg7bNahRLP3shldEP/E5yaiaJSek8+tZcIsODmTSmA7df38HtQpVUVCxpmhwppRwvpZwipVwtpfwEeAToAvQ1yntcSrnR6GMYIrkZcFpK+aGUcjnwBmDqr+ESoKsQYqTVZ6TwembMmseVK1cBLXRFwwb1XGyRd+AX2Up5x1yA8pIpHEXNqpX57KVri4UsSU7L5ONf1jFg0g8s+698M0Mo7EOZQkxKWTJ4CWzRfde08ningIa65slo4BbAVGCXGcB24E3hrSHJFTZxMfES733wuX590sSbvDZqvatQYsx1KFGmsDfd2tZhyc938uhtPagRG65Pv3g5nSffma+aKt0AWzvr99F9HzBKnyyEyBNCpAoh/hVCFHuiSykvAi8CS4FLQH3gbRPlS12+1sANNtqo8DIyMjIZf9Nd+o76lSqFcvNNY1xslXeixJjrUYJMYS+qx4Tx8K3dWfH73bz1xGB9enpGDvuOXHChZQqwQYgJIWoCrwPLpJRbdcnZwLfAvUA/tH5lrYD/hBDNDPeXUn4OxAKNgC5SSpOzs0opFwLrgNeFECrMhoJX33ifLVt3AtrcfT999wkxVaJL30lhM0qMuQdKkCnshZ+vDzcMa82wPk30aeMfncrzHy7mso1zkyrKj1VCTAhRCZgD5AG3F6ZLKROklPdJKWdJKddKKb9H6/slgReMy5FSJkspjxp19DfF82iCbZIVNt4jhNgqhNh66bLtk8Uq3I9Fi4umMXrnrRcZPmygC62pGCgx5j4oQaawF13b1im2Pm3hbnre9A3HTpn0iygcjMVCTAgRhDYisj4wWEpZalASKeVpNI9WJ1uNk1KuBRYBLwshLJp5VUr5nZSyo5SyY5XoKFsPrXAzCgoKOHP2nH594i3jXWhNxUKJMfdCiTFFebl+cEvuuaFzsbTc3Hyuve83vvt7ExmZWS6yrGJikRATQvgDM4HOwDAppaXj3AWaV6w8vADUAu4rZzkKF3LmzDl27d5HwvmL2DK/6YKFy8jOzgGgSnQUYWHuOyecN6LEmHuhvGOK8hAY4Mczd/fhyNKnuPfGLvj7aVIgOyeP975fQ49hj3DpcqqLraw4WBLQ1QeYAvQHRkkpN1pSsBCiDtAD2FQeA6WU29FE4PNAaHnKUjiXrKwsvv3+N7r2HEqTlt3p3ns4DZt2pkefEWzctM3icjIzs3j1jaJQc+PHjXKEuYoyUGLM/VCCTFEehBA8fVdv/vlqIs0axOjTj8cn0G/0E1xNz3ShdRUHSzxiXwLjgA+AdCFEV4NPLQAhxIdCiI+FEOOFEP2EEPcBa4ECTI+KtJaXgGigrR3KUjiYrKwsvv72F1q268MTT7/Mnr3FB9fu2r2PAUPGMvWvWWWWJaXkvoee5sDBIwCEhobw9JMPOsRuRdkoMeaeKDGmKA9N6sfwxwc3Fks7deYifUY+zplzpiJYKeyJJUJsqO77BWCD0ecu3bZ9QE+0kZNL0SLvr0cbFXmovEZKKQ8Cv5e3HIXjmfrXLFq07c1Tz75KQkLRsOiAgACaNW1EUJDW1U9KyQMPP1umZ+yd9z5jxsy5+vU3X/sfsTFVHGO8wiKUGHNPlHdMUR4qhwXxwv39CA0uCv569MRZHnr2MxdaVTFmnhC29NfxFNq3ay3XrZpbdkaFXTh2PJ7W7fsWS6tWLZYnHr2PWyeMIzw8jFOnzjD2xrvYt/8gAC1bNGXjuoUmg7LOnD2Pibc/pF+/+85b+PiDN1QAVzdBTYnkvlSEl5eiOIeOJ7Jj/zlqVgunc+vaBAbYFvUpPTOH+Zuu8vybP+rTVs/9mLYtG9rLVIswrsOW/MmoXG/kNillR0fZ5ChUfC6F3bh6Nb3Yet8+PZjx148EBwfp0+rUqcWMv36gY7dBpKdnsHffQZatWMPA/n2K7Xv69Fnuf+gZ/Xq/vj15/51XlAhzI9T8lO6LmseyYiClZOGaw/w8cys79heNKg8NCaB3x3pc278ZA7o3tOq5GRocwIN3jmbrzsPMmrcWgJXrdjpNiJmrs4nH1nitx9fWyPoKRQlat2rODeNHF0szFGGF1KlTi1tuHqtfH339baxdt5GsrKIh008/9xrp6VqAwYYN6vH7L1/i7+9foiyFa1HNlO6Naq70btZti+eRN/4tJsJAi5i/cM0h7n/lH8Y9MoVte0uNNmWS1i3q65ePnjhXSk77kHhsTZl/HCzJ44koIaawG0II3njlWXx8tGq1es1/nDpl+gHQtEmjYutDRtxIjbqtGTxsPIOGjmfu/CX6bV9/8R6REZUdZ7iiXCgx5v4oMeadzFm2v9h63871qV2t+LNy54EEbnjsTx58bQ7xZ5MtKjcnJ5eZc9fq12tVd1y/XFvElbeJMdU0qbArNWtW55p+PVm2fA1SSqb8OZP/PftoiXw9uncukZadncO6/zYXS7vt1hvo3s3mmMAKJ6GaKd2fmAa9ve4FVtE5ahAJ/43HBnLTiLZIKTly8jIzF+/ht392kJubD8DitYdZ/t9RJlzblodv7U5EeHCxso6fTmL15uNs2XOG7Qe+08cRCwjwY/yovna3vbx10ZuaKpVHTGF3Jtx0vX551er1JvO0aN6EjesW8s5bL3L7bTfRqGH9EnnatW3FW2887zA7FfZDiTCFwvnUr1U0e0za1WxAa5loHFeF/93bj6U/38nIfkXTPeflF/Dr7O2Mf3QquXn5bN1zhne/W8XAST8w6PYfeevrlSxZd6RYMNdXnr6NBvVq2NVue/0h8JY/FsojprA7MQbhJY4cO2E2X6uWzWjVsughcf7CRbZs2cH5CxeJjYlh6JBrCAgIcKitivKjRJjnoLxi3kWPDnH8u0KL0zht4W7uHt8ZH5+ijvm1qlXm4xdGMOn6Drzz7Sq27NG6ihw/nUSzIR+VWnZEWBD33j6aB+641nEnoACUEFPYmfj40zzyWJEXK6ZKtMX7Vqsay8gRgx1hlsIBKAGmULiWob0b8+ZXK7iSns3Jsyn8t+MkPTvElcjXpml1pn50I7c89Tebdp02WVZwkD89O9SlV8d6dGxVi4Z1oqnaqI/JvOXB3n8EvKGJUgkxhd3Iysri2jG3cvzESQD8/f358rN3XGyVwhEoEaZQuJ6Q4ADGDGrBr7O3A7Bw9SGTQgy0JstvXr+OVz5dyvxVB8kvkMREhdK/WwP6d2tIt3Z1CAosPjLdG0SOJ6CEmKLcSCl59Y33+eCjr/RpgYEB/PLDZ3Ts0NZ1hinsjhJgCoV70bNDnF6InTlf+kTdYaGBfPT8CN5+cjApV7KIjapUrCnTFPYUY45qFvd0wag66yvKzax/5hcTYQBvvPoc144c4iKLFI5AiTDvwJNfWIqShIUG6pczs3Mt2ico0J9qVcLKFGEK56CEmKLc/DtvcbH1zp3acdcdE1xkjcIRKBGmULgnyWmZ+uWQIMcMbrKHJ8vRg0Q8eRCKEmIKm5FSsmv3vmKTcv/+y5csWzSDwMDAUvZUeAp5yXuUCFMo3BjDqPr1a0eVkrN8eLLQcXeUEFPYxPkLF+nTfzTdew/Xp/n4+NC7Vzd8fX1daJnCXigB5r2o5knvIDcvn9lL9+nXe3So69Dj2SrGlIgrHdVZX2ETU/6cybbtu4ql3XPnrVSJdtw/MoVzUAJMofAMVm06TmJSOgCx0aH06VwyMLbC/amQQqy0F42aN88yTpw4VWz9q8/f49YJY83kVngKSoQpFJ7DtIVF9+v1g1vh5+v4Ri5rRygqb1jZVAghZs3LpTCvEmSlcy7hvH757ynfMWL4IBdao7AHSoRVLFSUfc/m/KUrrN58XL8+dkhLpx3bUjGm6pdleLUQk/mZNr9cDPdToqw4Ukri44s8YjVrVnehNYryogSYQuF5zFq8l4ICCUC3dnWoWyPSxRYpbMWrhZi9UF6y4nz3w+8cOnwMAF9fX+rWre1ii9wDY0HjCfVFiTCFwvMoKJBMN2iWHD+0tdNtKMsrprxhlqNGTVqBGsoPSckpvPRq0bRFd90xgajICNcZ5GIK64SpeuHudcXd7VMoFKbZuPMUp3VR9CuHBTGoZyOX2KHEln1QQswGSnv5ejs//jyF9PQMAJo2acjbbzxfxh7eheFvb8nv7651xF3tUjgXFcbCM5m2cLd+eVT/5gQGuK5xy5QYUwLNOlTTZDmpaM2WS5eu1i8//uh9BAUFudAa51Be0ZKXvMet6ocSYQqF55KcmsnidUf06+OHuc+zRWEbSojZCWs799vzZeisl7yUkr37DujXmzV1njvcmYLXEULFXcSYEmEKhWczZ/l+cnPzAWjdpBpN68e62KLi/cWUN8x6lBBzAM5+2Zk7nr1f/BcTL5GadkW/3nfAdQwa2JdPP3yTWrVqWFWWPUaz2oK5a+KM38yV3lMlwBQK72DuiqI/w67opG8Oa+OLKYpQQsyLsbdAqxIdRY0a1Th3ToshVlBQwKLFKxh1/Ab+W/i5R0xt5A6CxNneMXc4Z4X7ouKJeQ5XM3LYc1h7/goBQ/s0cbFFxVH1yDaUEKuAlOfFvGbO+/w+fSnLVm1j/WZtjrODR07z1+yVTBg7wF4mej3OEmNKhCkU3sO2vWf1scOa1o+lcpj399GtCKhRkwqriKkSwRP3j2PB3+/w4J2j9OmPPv8l85dsdKFlCoXCVmIa9FbNSh7Alj2n9cudW9dyoSUKe6KEmMJmnnnkRurWrgpAbm4e9z/1CekZWS62SmGIOwwQUHgOSoy5N0dPXtYvt21mXb9chfuihFgFxi+ylcmPpUSEV2LBX5OpFBoMQOqVdA4dPV3GXgqFwp1R3jH35XRCin65bo0Il9mhsC+qj1gFpCyxZWq7ub5GtWrE0LhBLbbv1uLaSF3/BYVC4dmoTvzuRW5ePqcSUvXrtatHuM4YhV1RQqyCUN4mKmvEmadQeE6efh5l4RfZyuvPUeEYlBhzH5asO0JmVi4A1WPCiAhXHfW9BSXEvBxH9hEqLFv4hTjsGI7A+JoooaJQmEcF6nQ9ew6d59XPl+nXR/RrihDChRYp7IkSYl6IsztoGz4Pth++Qpd+Rcd3J4FT2nVxthhTnegVnobyjjmf1CtZfP77f0z5dwe5eQUAxESFctf4zi62TGFPVGd9L8Lazvb2onWr5vrll197l4OHjrrcJmMsscEd7HQU3nxuCuehOvI7jzPnU7n+oT/4ZdY2vQirFBLAJy+MJDrCs1ohFKWjhJgX4Gqx89ILT1K/Xl0AMjIyGTLiRlJT04rlcZWNrr42CoU3osSY43ly8nzizybr1zu2rMmcbybSpU1tF1qlcARKiHkotoSbcBSxMVWY+vs3+PlpLd2JiZeoUbc1HboM4PMvfyA9PUOf11k223ocd7ieCoUnoLxjjuPi5ats23dWv/7Bc8P48+ObqFsj0oVWKRyFEmIOwlyMrvLG7nIX8WVMq5bNuOXmscXSDh46ynMvvEmzVj149/3PSUkpGnrtqPOwR7nueH3tgbeel8K1KDFmfwrnkwTNEzZ6QAvVOd+LUZ31HUBF9cS89sozBAcFse6/Tew/cJj8/HwALicl8/pbH/LJ599xz1238uD9dxAbUwUoft7l6SzvSdfPk2xVKCxBjay0L4EBRa9mPz9fF1qicAbKI6awG1Wio/jgvVfZuG4h50/v5ZMP36BO7Zr67WlpV/jgo69o3ronTz37KmfPJhTb352aE71VLHnreSncA+Udsw+GnfEvp2SUklPhDSghZmfUi04jJCSYu++8ld3bV/Hd1x/SpHED/bbMzCy+/vYXWrTtzYOPPMex4/HF9rVUkDm6mVb9lgqF9ai+Y+VHCbGKhRJiCofi7+/PhJuuZ8uGJfzx61e0ad1Cvy03N5dffvuLth2vYdJdj7Bv/6Fi+5oTWs7sJ6fEmEJhG4WCTIky64msHKxfTk7NJCquh7qOXowSYgqn4Ovry3WjhrF+9TxmTf+Zbl076rcVFBQwfca/dO4+mBtuvput23YW29fWgQ0K06hrqHA2SpRZR40m/YioXAkAKSXJKVcB5W30VpQQsyPqBVc2QggGD+zH0oXTWTTvL/pf06vY9nkLltKn/2hGjL6FNWs3IKXrJxFXv6tCYT+UKCudmAa9ycvL52p6pj4tJCSwRB51/bwHNWpS4RKEEPTq2ZVePbuybfsu3v/wS+bOX6LfvnLVOlauWkfXLh14+okHGTyon0uHb9trCiQl6hSKIgzFhKNGXFoqWFw94tPQzsPHzpCXp406j60SQUiw6Qm+1WhV70C4g8fBUbRr3Uiu/vdjpxxLvWDLz/4Dh/ng46+YPuNfCgoKim1r3ao5Tz/5IKNGDsHX1zXDub1NiLnTPKAKhSG2CAt7eoicLWwMbc/MymbQ2GfYve84AP16tuWf39+wqJyKLMhiGvSmcr2R26SUHcvO7V4oIWYn3OkF6+kcP3GSjz/9hj+mziQnJ6fYtsaN6vPEY/dz4/jR+Pv7O9228ooXd6onSogpPAFjceHsJrnyipv0zBy++2szpxNSiKwcrH3Cg4msHEK9Zl2IjgxHCEFScho79x7jxykLOB6vhfbx9/djwV+T6dy+qVNt9kSUEHNTnCXE3Onl6k2cO3eeTz7/jp9+mUpmZlaxbc2bN+HXHz+nebPGTrfLWwLPKiGmUFiOreLm27828f4Ptu370ZsPcOeEoTbtCxVLkHmyEFOd9cuJO71YvY0aNarx3uSXObBnPc889RDh4WH6bfv3H6JXv5H8+PMUt+jQr1AoFMbk5Rdw6ESi1ftVDgvl9edu546bh9h87IomwjwZ5RErB0qEOZfU1DS+/f433v3gc7KysvXpo68dyhefvUNkRGWbyz5z5hwzZs+jSnQUHTu0pUnjBiYHB9jLi+TKuqM8YQqFdVgjapJTM/lxxhZWbDjG4fhLJbaP7NeMkGB/ktMyuZodwKUkbQ7eqMgwqkRHMLBPB8aN6kNoiOkO+va219MxFGGe6hFTQswGlABzLfsPHOa2Ox9mv0EA2Fq1avDz95/SvVsnq8vLy8ujU7dBHD5yXJ/Wo1tn3nn7Rdq3a12Uz84Cxtn1SAkwhadSKCxc4fmwVtTc/eIsVm48ZnZ7t3Z1+O298fo/evY+p4oqwsBzhZhqmrQSJcJcT/NmjVmzfA733HWrPu3MmXMMHn4DTz/3GvMXLGXX7n0cPXaChIQLpKamkZuba7a8mbPnFxNhAOs3bKZXv2u5+74nSElJdYiIyUve4xRx5KzjKBSOJvHYGv3HWceyhvz8AjbuPFVqng07TnH4RJGnzJ7nUpFFmCejPGJWoESY+/Hv3EU88PCzJKeklpk3LKwSfXt3Z8TwQQwZfA1VoqO4ejWdbr2GcfzESX0+Pz8/8vLy9Os9Ordgzh9v4u/vuLB7jqhbSnwpvIWyBIa7eJUuJ6fTZdxX+vV3nhrC+z+sKTFf5E+Tx9K7U71iaeU5h4okwMD8tVIeMS9HiTD35NqRQ9iwdgE9unUuM++VK1eZO38J9z7wFPUadaT/4Ou5ZtD1ehEWHh7GqeM72LpxCSOGDdTvt37zPp57/XuHnQPY12ulPGAKb8ISkWFPL1l5yomsHFJsnsiWjauy+Kc7uGVUO0JDAgAICfKnaf0Yux1XiTDPR3nEykAJMM8gLy+PefOX8t/GLezZe4CkpGQyMjJJz8jQvtMzSgSJNeb7bz7i5hvH6NfffetlXn//N/36H988z8jB3Rx2DoXYWueU+FJ4I7YKDVte2PYQNY+88S8LVmv9V5+/rx93jNUcNFnZuew4kECtquHUrh5hdn9r7K5oIgxKvz6e6hFTUxyVghJhnoOfnx+jRw1l9CjTMXeklBw5epx5C5Yyf8FSNm3eXizsxYSbruemG67Tr+cl7+GJ+8eyZ/9xZs9fB8DMuWucIsQKBZWl9U8JMIWiJIYipSxxY09B071dXb0Q27z7tF6IBQX6061tnTL3Tzy2xiIxpkSY96CEmBmUCPMuhBA0btSAJx5twBOP3seFi4ls376bgMAAYmOq0KJ5E/0opkJhI4Tgvkkj9ULsxKnzTrU5L3lPqfVQCTCFwjJKG3Vpb0FTs1q4fjkz2/wgodIoTYxVRAEG3ivCQAkxkygR5v1UjY1h6JD+JdKNxU39utX1yyfiE5BSOnXycVPeMSXAFBUFe4sOZ4iYS0np+uVKwQE2l2NKjCkR5p0oIWaAEmAVG1MCJ6ZKBJVCg7manknqlXSOxyfQoF4Nt7BNoVA4jnXb4pm1eC/VYsJo2bgaLRtVpXb1ymX+Edu854x+uVnD2HLZYCjGlAjzXpQQ06FEWMXGnNARQtC5fVNWrN0BwJYdB10ixBQKhf0x5+Hee+QCd784i9zc/GLplcOCaNEwljo1IujTuT4DezQqsa9hHLGubcruE1YWFVWAQcUQYeDlQkz4BiuBpSgVSzxNIQZTjWzcdoAbx1zjSJMUCgWOFSDTFu7mlU+XUiUylMdv78mYQS2Lbf9qyoYSIgwg9UoW/+04xX87TvH3gt1M/2wCbZsV/TE7dyGN0wlaTMPgIH9aN61eogyFZVQUEQYqjpiigmJprK3ESyksXblVv167ZvmaGhQKhWvJzMrl7a9XkptXQELiFf73wSLOXUwrlufCpav65eiIEHq0r0vlsOJzP0oJqzYXn5Fj464ib1j7FjUI8Pd1wBl4PxVJhIESYooKiKX9rQ4eOcWgcc+QnaONfKoSXZmJ4weWsZdCoXBndh44x9WMHP16foHkjzk7iuWpWzNCv3zvjV349b3xbJ31ECt/v5subWrrtyWlZBbbz97NkhWRiibCQAkxRQXCUi/YjLlr6DH0YboMepDj8Qn69M/efoiYKhEOtFChUIBjmyUPx18qkfb3gt1kZBaJs86tisTWCt0E3kIIaleP4OaRbfXblm84qp++SErJxp2n9du6WhAzTFGciijCQAkxRQXAmil/PvtuFnc+8j57D8YXSx/UryNDB5Q9jZJCoXBvjpgQYqlXspi2sOgZ0bNjnH7ZWLh1bFkLf12T44VLV7nxsamcvZDKkfhL+ibO0GB/Wjau6gDrvZeKKsLAyzvrKyo21oZ8SLhwmdc/+F2/Hhjgz+BrOnHHhKH07dHGqfHDFAqFYzAUVv261GflJq2f13vfr6Z6TBh9u9Rn54Fz+jzGnfarVqnEa48M4IWPFiMlnDiTzIh7fuVKerY+T69O9fD3U/3DLKUiizBQQkzhhdgac2vpqm3k5uYB0Kh+TZbMeI+oyPAy9lIoFJ6ClJIj8Zf16y8+eA1HT13mdEIqObn5PPjanBL7dG9Xsolx/NDWhIcG8vjk+eTm5hcTYQATDJovFaVT0UUYqKZJj6GweU0F9jRPea+P4dyTLZrGKRGmULgAR/YPO3k2RS+aKoUEUKd6BB88O6zEiMhCoiJCePmhASa3DendhJ8mj6V6TJg+zddH8OhtPejWrq79jfdClAjTUB4xN8eUsDBMU3HS7Bd1vlXz+vrlrTsP2aVMhULhPsxdeUC/3KlVLYQQdGhZi6W/3MmXf2xg+YZjnLuYRkiQP4N6NuLBW7pRtUols+V1a1uH1VPu5Uj8JeLPJtOsgRbsVVE2SoQVoYSYwmOxt3cwrnZR59qk5Ct2LVuhUFjPmfOp7D18nqTUTJJTM7mSnk3NauG0bFSNZg1iCAr0t7isA8cu8tOMopiAowe00C9HVQ7hpQf789KD/cnLL8DXR1jcJ9THR9CkfgxN6sdYfmIVHCXCiqOEmJtT6PFSXjDHs3n7Qf1yXJ1qLrREoVDsOpjAjY9NJTevwOR2Xx9Bw7rRtGxcjRaNqtKobjRRlUOICA/G11dw/tJVLly6wsmzKfy3/STrt8fry6pdvTIDejQ0Wa6fr+qx40iUCCuJEmIeghJfjmfJqqJ/ywP7dnShJQqF4uOf15kVYaAFYj104hKHTlxi5uK9Fpcb4O/LB88OIzBAvf4U7oGqiQqFjvhTF/TLlcNDXWiJQlGx2XvkAuu2xQNa09/1g1sSVTmEkCB/jp26zN4jFzhxJgmD8TUW0bFlTV5+qD/NG6oYX65AecNMo4SYQqGjZbN6LF+zHYDJn0wlJroyE28Y5GKrFIqKx3/b4/XLg3s2ZvKTQ0rkuZqRw/6jF9h7+AJ7j5wn4eIVklIzSUnLJC+/gKrRlagWE0bVKpVo2agqvTrWUx3pXYgSYeYpU4gJIcYCNwEdgVjgFDALeFtKabJHsxDiW+AeYIqU8hajbX2Bb4AawJ/Aw1LKHN22OOCELmt/KeUKo33XAXlSyr4WnZ1CYQX33z6SqTOWk3g5hdzcPB5+7nN8fX24fmRvggIDXG2eQlFhSM/I1S83ios2madSSACdW9emc+vaJrcr3AclwkrHkl6JTwH5wPPAEOBr4H5gqRCixP5CiO7ABCDNxLZQYBrwPXAd0A541Mxx37LANoXCblSvGs3yfz4gJjpCn/bA05/Squed7D1wwvyOCoXCrmRmFwmxkCDLR0YqFJ6IJUJspJRyvJRyipRytZTyE+ARoAvQ1zCjEMIf+A5NRCWbKKsZcFpK+aGUcjnwBmBKKi8BugohRlp8JgqFHahbqyrvvnpPsbSLl1L4a/ZKF1mkUFQsYhr0Jjk1U78erISYR6O8YWVTphCTUiaaSN6i+65plP404At8aKa4U0BDIURfIUQ0cAtw2ES+GcB24E2hJvhTmMCRMwyMGd6TN5+/o1ha5TDVeV+hcBbb9p3VLzepp+JzeSpKhFmGrZ31++i+9WGKhRANgBeB4VLKHFP6SUp5UQjxIrBUd+ytwAMmype6shYANwB/2WinQmETazfu1i9XjYnk1hsGutAahcJ7yc/P578t+0m8lEKdmrFUjY3k1LkUAIIC/WjVRMX080SUCLMcq4WYEKIm8DqwTEq51WDTN8AsKWWpbThSys+FEH8A0cBxKaXJQDFSyoW6zvmvCyFmSCnzrLVVobCFdZv2snhFUdX+5YtnqRYb5UKLFArv5PdpS3n74ymcO3/Z5Pb2zWuoeF8eiBJh1mFVDRdCVALmAHnA7QbptwCdgKaWlCOlTMZ0HzJjngfWAJOAHyy08R60EZvUrm3ccqpQlE1q2tVi6y2b1XORJQqFdyKl5MW3fuKLH/8pNd/Ano2cY5BC4UIsnstBCBEE/AvUBwZLKc/o0isBHwHvAllCiAghRISubH/duk29LaWUa4FFwMtCiEAL9/lOStlRStmxSrTrvBiO7MOkcCyD+3WiYb0iEW8YcV+hUJSfH35fUEyERUWGcU2vdvpAykLAbde1Z8LIdi6yUGEryhtmPRZ5xHRCaibQGRggpTRUGVWAGOBt3ceQ2sB4tFAV/9ho4wtofcnus3F/hcIq/P39uGF0X976eAoAy1dvY+xI9XBRKOzB8ZMJvPDWj/r1EYO78d1HTxAaEkROTi7xp88j0vYTER7sQisVtqBEmG1YEtDVB5gC9EfriL/RKMt5oJ+JXf8C9qCFsrB8IjAjpJTbhRAz0ZopzwGptpblbPKS96g5Ij2ULh2b6ZePxSe40BKFwnuQUvL0K9+QnaPFCWvVvD4/fvqUPmByQIA/jRvUJvGYitvnaSgRZjuWeMS+BMahCap0IURXg21ndE2Uq4x3EkJkAReklCW22cBLaGIuFlhth/IcimqWdCzOuL5VYyL1yxcSLenOqFAoymLOwv9YtlqbRkwIwWeTH1KzVngBSoSVD0v6iA3Vfb8AbDD63OUgu4ohpTwI/O6MY9kbJco8k4XLN+uXa1Wv4kJLFArv4MrVDP73xvf69btuGUb71qozvqejRFj5KdMjJqWMs6VgW/aTUsYDJgO4Silvx2CkpkLhKKbOXM4bHxTp/m6dWrjQGoXCO3jn0z/1YSpiq0Tw4lO3mM0b06A3icfWOMs0hY0oEWYfLB41qbAMUx4w5RXzDKSUfPT1dO5/6hPy87Xwds2b1OWRe8a42DKFwrPJzs7l178W69ffeuFOIsIrudAiRXlRIsx+qEh5CgWQl5fPC2/9yDe/zNWntWpWjxm/vEp4WIgLLVMoPJ89+49z5ao2f2StGlUYN6pPGXso3BUlwOyPEmKKCkVWdg7T56zm8LEzZGXlEB4Wgo+PYMHSTew9GK/P16trK6Z8+4I+rpFCobAdwynvBAIpJWoaYc9DiTDHoISYnSkMV6FCVzgOw2tsDcdPJjDx/snsOVD60PhRQ3vw/cdPEhhoUxxihUJhROOGtQgNCSI9I4vT5xJZuGwzwwd1LXtHhaICoPqIOQglwhyPX2Qri6+zlJIJ975Vqgjz9fXhxSdu4efPn1YiTKGwI2GVQrjzlmH69a9+mlNqftVRX1GRUB4xhcdjKMbMeckOHzvD/kMn9euP3Xc91WKjSE1LJys7h6YNa9OjS0tq14x1uL0KRUXkwTtH8dl3swBYv3kfV65mEFapZP9LJcLcl8Rja1TzpANQQkzhVVgiyqpEV+a1Zyc5ySKFQgEQHRmOEFr/MFN9xJQAU1RUlBBTeC2Goqx+3Tz98qXLqWRmZRMcZNE88v9n76yjovj6MP4M3R0iIKWEiiIWKiZ2d3d3x2t3+7O7uwssDFAUxRYbJUQEFelu5v1jYWaH3YUlliXu5xyPM3fuzNxdYOfZbxIIhBLg1btvoGkaAGBspAc1VbaXJBFh5QdiFSt5SIwYoVJw+2kYs62prgpFBRIDRiCUJueuejLbHdo0ZLaJCCNUdogQI1R4/vz9h1lzljL7w4cPgoJuXZJQQSCUEimpabh+25vZH9S7DQAiwsor5OdWshDXJKHCs2LVJkRF8xp3Gxsb4X/zpjHHiloKg0AgiM/tBy8Rn5AMALA0N4K5RjgiAv9JeVUEQtmAWMQIFZrU1FRcvOzG7O/bvQlaWpoC8wpTCoNAIIgPTdM4evo2s9+9lSUp5loBIFaxkoNYxAgVmuSUVKSnpzP79RzyF1vEQkYgFB+apvEzNBx//kbhoqsXvF98AgDIyFDo2baWlFdHIJQtiBAjVGh0tLVQq6YtPn/xAwCcOXsZ06aMLfA8IsgIhKKx/5gb9h2/geCQvwLHhvd0hEkVQYs0oXxCMihLBiLECBWe/v26Y/lKnhD76udfqHOJICMQxMf7+UcsWHVI6LFGdUwxc6RzKa9IemRkZuHdl9+IS0iFnZVBkQRoSmoGvN8E4+6T73jyOhjamsrYv7IXzE20JbBigrQgQoxQ4QkL+8NsG1etUqRrEEFGIBTMlj0XOft1bY1Q1UADfTvao0VD80oVGzZv423cfMj7AqikKIdjG/qhob2JWOdmZ9PYcuQxTl5/i9Q0tgZiVGwyZqy9gUs7h0BBXhYAkJqWgdNuvnjhG4LWTlbo06E2FBVK79FOrGLFhwgxQoXnmc8rZtvJqUGxrkUEGaG8U9gg68I8ZF/7fmO2XfcNR60ahoW6V0XhS0A4I8IAIDUtE+OXXMX1fcNgVjV/axZN01i+8z7O3Xwv9Phn/3BsP+6N+eNaIiw8DkPmXEDo3zgAwMMXQdh/7gX2r+qJmtUr53tfHiFZk4QKTVxcPD5/4T0cZGRk0KhBvRK5LsmyJJQ3IgIfFynTLfe8gv4BvIr5uazb/xAf/P4w1fQrEz6+IQJjCUlp+N9md2Rn5/9+7Dv7nCPCrKrpYNJgJ4wf0IgZO3zpFf5GJuCMmy8jwnL5/S8eB86/LOYrKBwkg7J4ECFGqNC8fP2OeRDY17aDurpaiV6fCDJCWSavUJL0vWpbaTH7L97/Qu+ppzFx2fVKJ8b+RSUy2x2ca0BWhueSffUxFCt3PxD5fni/Cca242zh2x5ta+LO4dGYM7o55o5pgbq2RgB4rsunb37iyetgodcJ+R1bMi+EUCoQIUao0Pj4vGa2mzQunlsyP4ggI5QVSlN85WX6sKaoX8uYM+bhE4Dn73+V+lqkSUpKBrPtVK8aJg12YvbPuPli0yEvATH2Ozwes9beRO5wwzom2DC3I2RyRJyMDIX2zjWY+W4eX/A1pyiunKwMjm3oyxxLSEor8ddUEMQqVnSIECNUaHxesELMyam+xO+XK8iIKCOUNtISX/xUNdTAqhnt0LqxJWf8wdPCZSuXd5SU2F62aWmZmDasKbq2tmXGDl18hV2nnjH7sfEpmLLSFTHxKQAAA11V7FzSDfJyspzrNnM0Y7afvv3JbNerWRVfAthOBfbWRUtKIkgHEqxPqLBkZGTg9RtfZr+pU0PRkyVAXjFGAvwJJY20hVde/IL+oev4EwLjdlYGUliN9FBWZIVYSlomZGVlsHlBZ6SmZeLBswAAwM6TzxAcFgNLUx1cufsJv/7wYr3kZGWwc0l36OsIhlHYWRnAQFcV/6KSOOPNG1rA+00ws+/cwLzkXxRBYhCLGKHCEh4egeTkFGb/4JFTiIyKltp6+K1lxGJGKCrSdD0WxONXPwTGqpvpome7ylVNX11VgdkOj0wAAMjLyWLHkm5ozieS3Dy+Yvvxp4wIA4Alk9uggYgyF7KyMlg5vR1nrFpVLfTtUBuvP4UxY871zSENyuLvZHmACDFChUVfXxdKSorM/pate9Gl++AyEzhMhBmhMJRV8cXPz7BYZltVRQFThzXB0XV9ISdbuR41/KUjfL+ydQwVFeSwd0VPNKtvJnCOipI8di/rjqE98s/sbtesBv43viVkZCg0qmOKSzsGQ0FeFhkZWQAAVWV5GOqVbFISQbIQ1yShwqKoqIj1a5bgf4tXIy2N12/y02c/pKamQVlZScqrE4TUKCPwE/TzDwJ/hCE7m0Z13RioqyqW+YKoWXylGSYObMwJUq9M1LE1gowMhexsGt9+RCAhMQ3qarwvhcpK8ji2vh88fAJw+9E3yMnJoH5tY7RxsoKBrngCamz/RhjZpwFkZShQFO8+sjIUsrJpJKVkIC09s1SLuhKKB/lJESo048cOQxVDfQwaNhEAICsrC2VlJdA0XSYfakSEVW5i4xNx5cYTnL54H28/cAPcmzmaYd/KnlBRVhBxtvSpX8sYl915v8PX7n/G2P4NBQLOKwNqKgqwtdTHl4B/oGnA1+83mjewYI7LyFBo16wG2jWrkc9V8offyigjQ0FbUxmRMckAgPDIRFSrqlXkaxNKl8plLyZUShQUWfdkVlYWDE1qQV3HEg2bdoDX42f5nFm6EBFW8cnKysIDrzf4FiBYzuH+o9eo2WQUZi/ZKyDCAF6W3Bk331JYZdFp27Q6VFV4QjHoVzROXX8n5RVJD0e+Mh5vP/+W+P2szdliuo9eBEn8fqIo6+7zsggRYoQKj0trZ9SsacPsJyYmgaZpfPnyDb36jcQDT+l/cBARVjnYuPM8+oxcgUbtJqNDv/n4FxHDHDt96QGSklPzPV9FWT7f49JGW1MZ04Y2YfZ3nXqGqJikfM6ouDjWrMpsv/0Sls/MkqFjC/Yz7s7jb/nMJJQ1iBAjVHjk5eVx8/ppdO7YVsAdmZaWjuEjpyD8X4SUVkdEWGUinE94PX/9FTUaDUfXQYswZOI6XL/9NN9zV89sh8HdHADw+hGmpGYgKSW9zCSf5DK8V32YG/P6KSYkpXEqxVcm6tdmLWK+X/8gKytbovfr4FyDKf76+lMo/uZkaxLKPkSIESoFhgb6uHT+MH798EWA30v4vvaEiQnvG2tcfAKWLt8glXUREVa5GDmoo8DYk+cfcfOuj8hzundsiphAVwzq6gCKovDB7w+aDtgH+67bUbfbDjgP2l+mLCAK8rJYPKk1s3/h9gcEh8bkc0bFpKqBBgxzgu+TktPxPThSovfT1VaFU11TAABNA3effJfo/fKDuCcLBxFihEqFtpYmjKoYoEZ1S+zesZ4ZP3PuCp75vCrVtRARVvmoZ18d86cNKNQ529ZMhowM+1G958xzRESz7r7wyETMXn9LoPmzNGnV2JIp0UDTwMnrb6W8otKHoijUq8Xnnvwsefdk55Zs9f7bj8qOOCfkDxFihEpLO5eW6Nm9E7M/cco8/Pn7L58zSg4iwiovi2cPxdkDi2FnXa3AuVWr6EJPVxMAoG/VAgBgaqQpMC8jIwu3HvmV7EKLAUVRGNe/EbPv/uRbmXOhlgb8fTfflIIQa8fXYPzN5zD8iSDuyfIAEWKESs3GdUuhqqoCAAgMCkanrgPxzveTRO9JRBihS3sn+Ljvho/7buzbMhMLpg/E1LE94ViHW84gMSkFySm8AH6apnH3yXe8/hQq9JrBYWXL/dfEoRrUVXkZy/+ikvCjEron+TMZS0MU6WqpwKkeK/CJe7J8QOqIESo1JiZVcWjfVgwbNQVZWVnwDwhCizbdMWXSaCxaMAMaGurM3IDAHzCqYsgIt6JARBghF4qiUNPGDDVt2CrrAUFhqO8ykdmPT0jGum1nISsrg1v3nsM/SLRVpazV65KVlUGjOqbw8OH1Vnz86gcsTXWkvKrSJZMvQF+plAqsdm5pi6dveA3Bb3v5YWTv+qVyX0LRIRYxQqWnR/eOOHVsD9MOKTs7G7v2HIZ1rSa4fecBomNiMXDIeNSt3xo17BrD1c29SPchIoxQEPJCHta7Dl3D9v1X8hVhAC9Ivqzh3IAVmQfOv0BEdKIUV1P6JKdmMNvKSqVTeqR9M9Y9+fbzb/z+F18q9yUUHSLECATwxNiLp+5o2aIpM5aQkIiRY6ejTbveuHHrHgBehuWQEZPwzrdwooqIMII4KMgX3Wqio6lcgispGXq3rw19HVUAQER0EjqPPY5zN30rTbyY10u2CXqum1bSaGsqo0k9VgA/e/uzVO4rDOKeFA8ixAiEHKpbWeCW6xkcPrANsrI860JSUjL8A7hVqmmaxnd/8StXExFWvvkTHoVdh67h1TvJB8MXVYg1czTDwK51S3g1xUdVWQErprVl6lvFxKdg6fb7OHyxdDOUpYHPu59MuycA6NjcutTubW9ThdkODS872bQE4ZAYMQKBD4qiMGhALygrKWHIiEki51Ux1C/wWkSAVQzGTN+Mpy8/AwAG9mqN1QtHwUBfWyL3kpcX7b6yMq8KLU01ZKTGg6YBGjSq6KljZO/6cHIoOANTWnRobo3Da/tg2Y77TImN7SeeYmCXukwj7IpGfGIqFm+7x+x3aG6N1k5WpXb/qgZsbOuffyRzsqxDhBiBIIQe3TvCpU1zeHg+AQA0buSIFy95tZBkZWVhZ5f/t1siwioOb96zfR/PX3uIOw9eYuywzujdtTlq2ZqXaPN4BREB3f+tnoQxQzox9ypvLp8WDS1w+9BIdJt4Aj/DYpGWnok3n8PQqrGltJdW4vyJSMDUla4I+R0LgOeSXD7VpVTXUNWALXEi7RixiMDHTOkVgnCIa5JAEAJFUbh07jDcrp3CZ98nqO/Iun26dGoLA329fM4mVCSqGuly9uMSkvDf3kto1nk6GrWbjPkrDuDE+bt44/u9wF6RBeHz6ovAmElVPY4IK6+oKCugeQMLZv9LQLgUV1Py/Pwdg82HH6PTmKN47/eHGV85vS0McirslxZVDVmLWFBIdKWJySuvEIsYgSACRUVFuLRujuTkFJw9d4UZHzN6iBRXRShtTu5ZiM4D/4f4hGSBY98DQ/E9kK3rRVEULM2MUMvWnPPP3NSQUx1fGAmJyZgwe6vAeBUD3XIvwnKpWd2A2X79SfIFTiVNekYWHjwLwIVb7/E0T1A8RQErprVFd5eapb4uc2NtaKorIS4hFeFRibjn7Y8OpRijRigcRIgRCAVw6coNxMbxzPuWFmZo08pZyisilCb2NS3wyG0blq0/hpv3nuc7l6ZpBAb/RmDwb7i5P2PGVVWUcmqGmaN2jjiraWsObU3WUrLvqBunKXguwuqD6Vu1KHfuSQBoypfN5+MbgoSktFLLJixpXn0Mxax1N/FXSKFWc2NtrJ/bEQ3tTaSwMt7vTKcW1jh/6wMAYMaaG9i5tBvaO0tHjBH3ZP4QIUYgFMCRY2eY7TGjhxRo2SDxYRUPK/OqOHNgMbyff8SS9Ufx7kOA0HkyMjLIzs4WGE9KTsWrd9/w6h23/59JVT3Y21miR6dmOHr2DjM+sFdrnL/2EAAgV4ySFmUNkyqasLMywNfAf8jIyMLjlz/QpbVtwSeWMdw8vmD+pjucgq0yMhRaNrTAgC510aqxJeRkpRv5M2ukM7xe/sCfiARkZmVjwWZ3NLQ3hXYZLHNS2ak4f+EEggR45/sRb96+BwAoKipg6OC+Ul4RQZo4O9nD89p/uHLjMVZuOolfvyM4xxs4WGNY/3aQlZXBZ79g+H4KxLsP/khOSRN6vdDfkQj9HYk7Hi+ZMQ11FXTv2JQRYmWtYn5xae9cA18DeT1dbz/+Vu6E2Lsvv7FgizsjwrQ1lDG0Rz3062iPqoYaUl4di662Ki7sGIwBM87iT0QCEpLS8OT1D6m4Sgn5Q4L1CYR8OHyUtYb16tEFerqVq0ULQRAZGRn069EKrzz2YcWCEdBQZ1tevXzrh+kLd+OJz0fMmNAH1lYmQkWYooI8U1srL/Z2FlBUVGD2MzKzSv5FSBH+WKX7T/3x2b/8BO1HRCdi6kpXZGTwfibVzXThum84ZoxoVqZEWC5VDTTgyNd4PD1Der9L5dGVXloQIUYgiCAuLh4XL7sy+2PFCNInbsnKg7KSImZN7It3Dw9i3LAukM1xRdE0jXNXPdG8ywzccPcRem5aegays2koKsijUX1bmBqzQezOTvaoZsLWqQsK/i006628xtxYm+uhRUNe9mR2No0hc85zaoyVVbKzaUxfcwPhUbw2TZrqSji4uneZFGCiuHL3E6LjBJNOCNKFCDECQQRnz19FcnIKAKBWTVs4NSbNcwmC6OlqYsuqiXh+dzc6t23MjIdHxCA6lhvIraOtDlUVJWY/LT0DL9/44e+/aHR0aYR9W2ZgwfSBMDetwswL+xMJP/8QgfuWZwvD7NHNIS/He/wkJqfj7A1fjF9ytUyXWbhw+z1efeBlyMrIUNixpBuqVdWS7qLEoH2zGsz2q4+hGDb3Aie2jSB9iBAjEISQnJyCvfuPMfvjxgypMCUECJLB2soU5w4twZXjK6GnyyuomZ2dzYnxSkpKxZ5NM3Bs13w42FdnxjMyMuHu8RLL1p/AXc/XUFCQR7tWrPC/fvtp6b2QUqB2DUMc3dCPM/Y9OBIx8SlSWlH+RMYkYfNhVvhOHNgYzvXNpbegQtC5lQ3GD2jE7H/7EYnXH0PzOUNylOcvD5KECDECQQgrVm9G0A9eXSANDXUM6NdTrPPktO0luCpCeaBtS0fcPr8eKsq8sgwZmVlQVuJtp6VnYOzMLQiPiMHD6//h2K75nHMjomIxaPwaTFmwE21bskJsx4ErWLDyIFr1mIUO/eYj5LNH6b0gCaGqxG3n1LCOCXQ0VUTMli7r9j1EfCIv1q9aVS1MHuIk5RWJD0VRmD+uJRrUZmPF4hKKV3i4OBAxJgjJmiQQ8vD4iQ/27DvK7K9fsxgaGur5nEEgcLGpbopJo7rjv72XAAApqWzAfmZmFv636hCOnrnDKQbLz+mL9xETEw9rKxN8DwxFSmo69h+/wRzvOTkcd4+OkeyLkDCn3d4x23KyMti6sKsUVyOaF+9/wc3zK7O/cnpbKCmK7glaVomJZ8WXSRXNfGYSShtiESMQ+MjMzMTUGQuZ/fbtWmHEsAFSXBGhvDJv2gA0bVhL5HFRIiyXW/dfYOOycdBUVxU4Js3st5LCUI/9cqOuqogqeqXbBkhcTl57w2x3bW3LadNUnkhNy2C2lRSla4MhVjEuRIgRCHxcuXYLgUHBAABNDXXs3bmRxIYRioSykiJcT6/G3s0zMKx/O9jbFf4B/vZjAC4fX4E2zetxxicOKj+uMVEM6e4AVWWeZSkmPgXvvv6W8ooEiYpJgodPILM/bVhTKa6meFiYsKV3vN8ES28hBAGIECMQ+Lh02Y3Znjp5DIyMDKW4GkJ5R0FBHkP6tsXujdPhfXsnnt/djcF92kBOzCKtKsqKaORoi2snV8HOii1xERVb/ksQVNFTh0sTNmHhW1BEPrOlw3WPL0yGoWOtqrCqplvAGWWXds3Y9zq39ZE0IVYxFiLECAQ+UlLZOAonpwZSXAmhImJnbYZ9W2bB/9Up7N8yC9PH90b/Hq3QvEkdVLcwhqICN/YoJSUdAO+hNbynIzN+5NIrJCQJr9ZfnrCsxlppgsME+2wCQEJiGoJ+ReN7cGSpll2gaRqX3T8x+/061im1e0uCzi3ZDgYBPyORnS39UiFEjPEgwfoEAh9qqmzW1pu370mDb4JE0NFSx6A+bYQeW7n5JLbmBPmv33EWjpY0altXQc92NbHwP3cAvKy3B0/90at97VJbsyQwN9ZmtoNDYwWO5+3paKirho3zO5VK6YjE5HT4B0cCAGRlKHRqaSPxe0qSN5/DmG1DPXWRnR0IpQ+xiBEIfHTswD4cN27eBbcb7sjKEh0YnZmZidjYuDJdiJJQvlg0czAaOPAe+hkZmZi17iZS0zIEek6mpmdKY3klCkeI5bGIfQuKwML/7nKsYOFRiRj1v0s4evm1xNemoiQPeXnee56VTZfrv3GapnHg/Atmv3sbOymuhguxihEhRiBwGDq4LywtzAAAKSmpGDRsIiytG2LcxNm4ev0W4uLiAQCBQcHoM2A09IzsYGxeFxbWDTF42EScu3ANsfGJ0nwJhHKOvLwcDm2fwwSy/wiNwT1vf9A0DVMjtuwAf/B1ecWsKivEQv7EIotPdB2/9gZpfGJTQ41Xi42mgfUHHuKphAPOZWVlUI3v/Q75HSvR+0mSRy+C8O4LLxlCXl4WQ7vXK+CM0qWyizEixAgEPuTl5XHq+B4YGrK9/iKjonH2/FUMGzkF1awc0aZ9bzg5d4L7XU9kZPBSwiMiIuF6wx1jJ8yCVf1h6D1iOY6ddce/COFxLwRCfmTHfER6JitKnr0LgefzQPz6w+vHqKIkj5rVDUSdXm5QV1OEjhYvHCAjIwt/ItiWUG8+sa6001sG4N6xMahXsyoAnhgbseAS/jv6RKKWqmpGWsz218B/EruPJKFpGttPsJ0ZBnWpW676Y1YGiBAjEPLgULc2nni6YcyowRxBBvBckS9evmV6UAKAnJycwByPx28xc/EeWDcegZ7DlmLnwavYuu8Sdh68ih8hf0vldRDKJxGBj7H+wCNk8NUK8w+OxIYDj5j9fp3soaGmJOTs8oe5sRazneueTEvPRNCvaAC8+Kx6NatCT1sVe1f0gKqKAjN/39nnuPXIT2JryxV+AHDi2tty6Z70/xmFz/7hAHj1wyYOalzAGdKhMlvFiBAjEIRgbGyEndvWIeDrCzz2dMXC+dPhUJcbGG1hXg1eHtcR8+87Xvncw4pl81DfsS5nDk3TeOjti6Xrj2HlppNYuv4Ymnacio9ffpTmyyGUE3IfRrF5ei6+9/uDH6E8kaKuqojJQ5qU+tokBTdgn/ca+ePCFBTkoKjA+7Kjr6OGCXx9EwFIVIgN7FqXKX76NfBfuay/9eYTWzi4ZSNLGOiWzcK5lRkixAiEfJCRkUF9x7pYsmg2nnrdhP+X57h66Rju3roA39eeaFDfATIyMqhpZ415s6fgsacr/D4+xcZl4+DcuDZkZAT/xJJT0nD7wXMpvBpCWYbfImBvXUXkvEFd60JXq2z2ZCwK/ELs52+eEOPP58trhZo02AkGumy3gftPA5j4p5JGR1MF/TuxZSuuP/gikftIksSkdGbbpErZdklWVqsYEWIEQiGoWrUKOrRrDedmjQVckrmYmhpj4qjuuHV+Pd49OoA1i0ajfWtuTTJ9Pa1SWC2hvJD3AWSXT/xXM0czSS+nVDHjZE7GAgCnm0VebyBFUbi0cwhjJQOAcYuvICklHZKguwubYehbBqv/F0RGJuvizpt5WxapjGKMCDECQYKYm1aBmakhnr9mv0lra6mjT9cWUlwVoSwh7MGjraHM2VeQZx+gVfQrVgN6jkUsJ0ZMTk6GqXOVnpGJxGSuyDI21MTB1b2Y/diEVPhKyCpmZ2XAlLH4GRaL6Ljy1dUggy/pozwIscoIEWIEgoSgaRpr/juNYZPWIz6B9+GtqCCPk3v/B00N1rUip20v9j9CxULUt39+IWZaRZPjipR2w+aSht8i9utPLDKzsiEvJwtrcz0APIvYB78/Auc1q2+OVo0smX1J9apUVJBDLT4L5fuvgmspy+SWQQHKT2usymYVI0KMQJAAslq1sWzrDWzefYEZM6tmggd3r6BN5yFEXBHyfdhoa7JCLDo+hVO8VUlRXtgp5RY1FQXo6/C+mGRkZuN3OK9WH3/GoqgYsC6t2Gr3958GSCyrkX8tvuVMiFlbsJnfZbGfpygqkxgjQoxAKGFomsb8hauwc/chZqx9u1Z4+vgWHOuV7351hJKhoIcMf4mGpOR0xMTxsijlZGWgrqoo0bVJA3MT1ir28TuvvIs4QqxlY0smVuyzfzi+/4iUyPoc7PjXEpbPzLKHrSUrxPx+RJTLEhwVHSLECIQShKZpzJ2/Anv3H2PGenTriItnD0FbSzOfMwmVBVEijKZp+H79jY/f/iIsPE7onOpmupx4sYpC47qmzLbHswAAea1Qv4UKCB1NFbRtWp3Zv//MXyLrq8cnxF59CkNkTJJE7iMJ9HVUGQtrUnI6wnIsjuWBymIVI0KMUOnJjPko8K8oZGdnY9bcpdh/6AQz1rtnF5w4ugvy8hXLnUQoGvk9WNbue4i+086g15RTcBl+WOgcO6vyX01fGO2b1WC2H74IQnpGFsyNtZlYudiEVKaOWl7aNWOF2D1vyQixqoYajDDMyMjCxdsfJHIfSUBRFNcqVo7ck5UFIsQIlZb8RJcwcVbQv11b1+LQkdPMNXp3bY5Dm8eBSvQrsrgjVA6OXn6N41ffFDjP1kq/wDnlETsrA5hU4VmME5LScO3+Z1AUBQc7I2aOSPdkI0smq/FLwD+R1sTiMrQH25/x7M33yM4uPy4+m3IaJwZUDqtYxUq/IRDEpKSFUUxcIjbuPM/s9+vREvu3zIIcX7p4Ue5JgvkrDsGfHuDxqx+IjU+Bgrwc5OVk8DcyAZ4+gXj9SXjcUYfm1gj9G8e0qKlZQS1iFEWhSytbHDj/AgCwarcHalU3QM3qhnj4IggAEBgSJfRcdVVFNK1XDV4ved0q7j8NwMje9Ut8jR2bW2PO+lsAgL8RCfj2I6LcWCiJRaxsQ4QYoVIhKcvU/mNuiIvnxY1YmBlh76YZHBFWVIglrWLg/fwjBozZJ1APKz/MjLWwYU5HuIxk3ZQWpjqSWF6ZYNJgJ3j4BCDgZxTS0jMxZtEVTvaojqayyHPbNa3BCLF73v4lKsQyMrNw/2kAHjzluj3LUxkRfiH27QcRYmUN4pokVBokKWqev/7KbM+b2h8KCiQmjMCyeNXuQokwVWV57FraHepqilBRYn+XostJHaiioKaigP0rezFZoVGxyQj4yVrBjPRFt+dp26w6covxv/4UWqj3uiCmrHTF9NVucPNk/8ab1TeDhUn5EcXVzXSZArnBYTFISc2Q8ooI/BQoxCiK6ktR1BWKon5SFJVCUdQ3iqLWUxSlzjenPkVR7hRFhVEUlUpR1F+Kom5TFCXQmZaiqFYURflRFBVPUdQBiqIU+I6ZUxRF5/xrI+Rcb4qiHhXj9RIqIcUJwBeXhET2AVnD0kSi9yKUL/4FeOHj9/xrTzVzNMP942MwebAT+neqg/PbB6NmdUMA3L6TN/jEQEXE3EQbu5Z1h5a6ksAxy2qihY+etioTB5WdTePJ6x8lsp6YuBR4+gRyxuytq2Dnku4lcv3SQklRHhY5JUKys2mOwCVIH3EsYnMBZAFYBKAjgH0AJgG4T1FU7vlaAAIAzAHQAcC0nDEviqIa5V6IoihVABcBHALQC0A9ADNE3Hdt4V4KgSBIabn2EpNSmG01VdEuFELlg6YBedn83dQ1qxtAT0sVFEXhb2QCFmy+g4nLruGTfzh6t6/FzLvs/gkJiWmSXrJUca5vjsdnJ+D4xn6YPNgJLRpaYObIZgXGY9WuYchsT1/tBp93P4u9lrM3fDn7c8e0wKktA6ApRCiWdfgD9stbnFhFD9gXx8ndjaZp/p+aF0VR0QBOAGgFwJOmaQ8AHvwnURTlDiASwDAAL3OG7QD8omn6v5w5qwGMB7A5zz3vAWhPUVQ3mqZvFO4lEQilH1tFhBhBGBGBjyEjQ6FmDQO8/Sw868/WUh/NG1qgx+STCPkdy4x/CfiHJ6+DsWp6WxgbaiAsPB4x8SmYu/E29q3sybiaKiIqygpwrm8O5/rmYp/TzrkGLt/9BIAnfo9dfYMm9YreIP3tlzDsOvWM2Z8xohkmDmpc5OtJG1tLfdz2+gYA8Av6J+XVEPgp0CKWR4Tl8irnf+N8Tk0CkAaA3xkdAqB6jntSF8BQAN+FnHsZwFsAayiKqrifNgSJUNoiLCU1DVHRbJFEDQ2VfGYTKgv83+Lr2BgJnVPX1gh9OtTCmEVXOCIsl7T0TCzY4o7mDSyYMQ+fAOw961Pi6y3vuDSpjjH9GjD7UTFFj6fzevkDo/53GZlZvIbZDnZGmDTYqdhrlCZGfM3iY+JT8plJKG2KGqzfMud/TsACRVEyFEXJUxRVDcDunGEm5Yem6X8AlgC4D561zBLAOiHXp3Pm1QEwoIhrJFQySiMWTBgej98iNY0XHFzdwhhaGmqlvgZC2aZXu1oCY6ZGmhjczQFr9z1CRkYWAF5ro9Uz2+H4xn6obqbLzL105wOncOmOE0/x8HmgwDUrO73b1Wa2E5KK5sK9cvcTxi25gqScgH9tTWVsXdgVcrLlO7eNv+yZrEz5fi0VjUL/NCiKMgawCsADmqZf5zl8EUA6gJ8A+gDoTNP0F/4JNE3vAmAAoAaAxjRNC40apGn6DgBvAKsoiio/ecIEqSDNMg+37j1ntnt2bia1dRDKDnljWmrVMERdWzboXkWJlxW59dgTZszOygCue4djUFcHONc3x6WdQ1ArJ+4pK5vG0zc/YW/DuwZNA7PX30KwiGrzlRV9XVUmezLoVzSu3fsktDVSeGQivN8E43d4PBKT03HrkR/W7PVEr8mnsGDzHaZYq5G+Ok5vHoBqVbVK8VVIhqzsbGZbtgK7tcsjhRI4FEWpAXAFkAlglJAp8wFsBGAKYAqAmxRFtc0r2GiajgEgzifIIgCPAYwEn2WtgDWOBy/uDKam+XlOCRWBslBn61cY671v1rh2PjMJlQFRgcVThzbFuCVXAQDJqRk4eOElwiMTAQC6Wio4nScIXF1VEYfX9kbfaWcQFh6P5NQMhIXHQV9HFRHRSUhISsOkFddxedcQqCorCL1nZUNHUwVtnKrDw4fXr3LepjvYcvQJHGyNMLRHPTSpZ4Yzbu+wcrdHgZXxbS31cWxDX+jrVAwLd3YW+3plyqFFLCLwMfStWkh7GRJB7J8GRVFKANzAcyd2oGk6NO8cmqaDaJp+RdP0VQCdAPwDsKaoi6Np+gkAdwDLKIpSFPOcgzRNN6BpuoGebvmp80IoPGVBhAFAZmYWs81fxoJA4KdVY0u0amTJ7Ls/ZsNjxw9sxIiwzKxsnHJ9i2Xb7+HRix/Yv6oXcyw6NgVxCamMRcM/OBILt7gLtfpUVtbMaseUagB41q+73v4YNu8iVux6gNV7PPMVYRQF9O1QG6e3DKgwIgzIYxGTJRaxsoRYFjGKouQBXAHQCEBbmqYLfALSNJ1OUdQHAA7FWiGwGMBrABOLeR1CBaGsCLBc7Gtawuc1zwO/fOMJODeuDV0dTSmviiAN8kuzpygKK6a3RccxR5GalolsPvG0fv8j3Pf2R1Y2jdC/cYiI5nVpwM33sLHQQ2paJjM3PSOLc93bXt9gb10F4wY0AgHQ11HD2a0DseXIE7g//oakFDZf7LTrO85cBXlZpGdkwdZSHy5NqqOObRXUtTWCnrZqaS9b4mTxiU+SA1e2KFCI5dQKOwPABUAXmqafF3BK7nkqABoA+FacBdI0/ZaiqCvguSl/A5BMR1dCmaesCbBcxg3vjFMX7yElNR0/fv7B0InrcePs2hJpcUSoWJhU0cT/xrfCil0PBI6J6jf57UekwFi/Tvb4F5XItPXZfOQxatUwRFPHopdrqEjo66hh47xOWDOrPQJ+RqHvtDNIS8/kzDm8tg+aOpohIzOrUrh2dTXZbO6fYSS2sCwhjmtyD4B+ALYASKIoyonvnwkA5FTIX09RVB+KolpSFDUcwCMARiiGa5KPpQB0UXzrGqEckZsFKa1sSHGxtjLFoe1zmW+Zz159xo6DV6W8KkJpI27RySHdHTCwS51856gqy8Oqmq7I4/raqti3shfq1+LFwWZn01i7z5O4KPMgLycLOysDDOjMfb9H9HJEy0YWUJCXrRQiDAAcarIlVHy//kZWVnY+swmlCVXQHy5FUcEARH3NWknT9AqKokYDGAvABoAqgDAALwCsF8eNyXcvcwA/AIyjafpwnmPHwAva96JpupU413OsV4f2fkTqwZYXyrLYEofNuy5gzdbTAAAlRQV88j4CfT0t6S6KUGoUpvp3SmoG7LtuZ/ZnDG+GRnVNIStDQV1VEeYm2lCQl8W4xVfx6GWQ0GvcOzYGaioKcBlxmOkdePvwKFib6xXrdVREomKSsHbfQ6SlZ2J4r/poXNdU2ksqdWiahvPA/QiP4iWI7FjcDV1a20p5VYUnv4B9TYtub2iabiByQhlFnIKu5jRNUyL+rciZc5Sm6aY0TevSNK1E07QVTdODCyPCcq4TnHNdgQxJmqZH5RxrVZhrEsou5cXiJS6zJvWFfU1eMHZqWjoOn74t5RURSovCtmBRUpTjZEjuOPkUHj4BcKxlDBtLfSgqyIGiKKya0Y5TiJOfF+9DYKCrhob2bG/TyupyOnL5FfrPOIOVux4IuCABQFdbFVsXdcWeFT0rpQgDeHFh7ZxrMPtLd9wj5U/KCOUvh5VQbqlowisvcnKymD2pL7N/6NQtJKekSnFFhLJIekYWwqMSMWukM2f86OXXuHrvE2esqqEGruweipG968POSh8qSvIAeLFmLRvyRL+pEZsY8vaz8Dizioxf0D+s3/8Ibz//xinXd/AkhW5FMnuUM4wNNQAA8YlpaD/6CEb97xLuPvlO3NpShBRKJUiMiii2CqJ7x6aoZmyAkLB/iIqOx9krnhg7tLO0l0WQIIWxht166IcVux8gJi4FFAXIy8syVfUBYM0+T+w/9wLZNA0ZikKtGoYY0LkOlkxuw8zJyMyCnKwME5PYvIEFzrj5AgDO3/qAcQMaQUez8rTZeveF28MzMSldSisp+2ioKWHrwi4YPPs8srJpZGfTePI6GE9eB2N4T0csndKGZFRKAWIRI0iEyijCAJ5VbPKYHsz+qk0nce2WN9LSMvI5i1BeKYwIe/b2J2avv4mYOF6fP5oGR4QBPBERHBaDkN+xCA6Lwa1Hfhg+/yKOX33DzJGXk+U8LFs3toS5Ma9uVkJSGrYefYLKxNO3Pzn78vLksZYf9Wub4MSm/mhSrxpn/OT1t7hw64OUViU+hQ0DKA+Q31gCoYQZ2q8tDPV5D8a4hCSMnLoRFo6DMW/5ASLIKin/ohIxecV1Ti2nwrBmryc2HnyEyJgkgWOysjJYNKk1s3/l7if8jUwo8lrLE8kp6ZzCuABQ08pASqspPzg5VMOpzQPgdWY8p4fpkcuvpLiqygsRYoQSp7Jaw3JRV1PBuYNLoKLMNoNISk7FwZM3MXTSOhKLUQm58fArEpMLdplNHdYE946NwYPjY3Fp5xDUtWVLDhy6+Ao7TjzF41c/BM5r42SFBrV5pSwyMrNx9e4ngTkVkbzvRW1rQ1hb6EtpNeUPY0NNbJrPhk6E/o0rsPWTtKmIbY5IjBiBIAHqO1jj8Y3tOHr2Dm7ee46Q0H8AgHsPX+PtB3/Ur2st5RUSikthXCTer4M5+51a2KBvR3sEhETi1584aGsow7FWVTRvYMHMMYc2Tmzqj/FLruLlh18AANcHX3D57iccXd8XTRy4rqX+neswRWHffubGTVVUbj7y4+z36UB6vRYWdVVFaKkrITYhFRmZ2YiKTapQrZ3KA8QiRiBIiBpWJli/dBw+PD6MenVY879/oECbVkIFJiU1Ay8/cH/mY/o1QMtGFhjTtyFWTGuLGSOacUQYwHO7yVDAiU39sG1RV95YagYyMrIwefl1/PoTy5lfr2ZVZvu9358KbXl9+eEXFm+9K+CW7NbaTkorKt9U4SuR8jciUYorqZwQixiBIGEoioJxFT28+xAAAFBWFqt/PaGC4OrxRaC2lbamssj5ySnpWLL9Hm499ENWNg2KAlSVFaCtqcwE+ickpWHuhts4s3Ug5GR536fNjbWhqa6EuIRUxMSn4L3fHzjYVRV5n/LK+gMPceTSa4HxurZG0NIQ/b4SRGOkrw6/oAgAwJ+IeNjbVJHyiioXxCJGKFEqe3yYKH78/Mts5wbyEyo2j14EYeF/7th6zFvgWGam8PYy/6ISMXjOebh5fGUC+2kaSExOZ0RYLm8+h3FcnhRFoXVjS2afP9OyonDpzkehIgwAHOyMhI4TCoZYxKQLEWIEgoRJTEqBX0AIAN7DsqaNuXQXRCg2BcWH3X/qj7GLr+DSnY+Ijk0GAMjwlZwIj+Q+7OITU7H16BN0GX8cn76HM+MK8qIbx1MUoKvFrRc2qg/b3eWO1zdECcmyLM/sPv2M2ZbP8960a1Yj73SCmPB3b/gTES/FlVROiGuSQJAwF64/Yhrs1rIxg4Z65Sm2WRl58ykUk5ZfFxi3MNVBYEgUACAqR5wBQER0IobPvwT/4EhmTEaGgoWxNgJ/RQu9x9h+DdGtjR1q1TDkjNeqYYhaNQzx2T8cWdk0nr//hS6tyl8/wfd+f7Dr5DMkp2ZAXVURVtV0YGqkibBwnkhQUZLHuAGNsOPEUwBA26bV4ZQneYEgPqZGWsz218AI6S2kACpixiRAhBiBIFECgsKwYuNxZr9nF2fRkwnlmsysbKzc9QDnbr4XOFbdTBc/+ETV5bsf0aReNehpq2LWulscEaahpoiU1AyRIgwADHTVBERYLk0cquGzP8+qtm7fQzjVNYWutmpRX5ZUWL//IZMBCgAePtzjNpb6UFdlYy0fPAvA/af+xCpWRPjduu++/kZWVjZkZYnDrLQg7zShxCDxYVzi4pPQe+RyxCfwrB8WZkaYNKq7lFdFkBSX3T8KFWEAEPAzilPM9embn+gw+ih8fEPw3JfntpaRobB0ShsY6asjIyeGTEaGgnN9cyyc2AqdW9ow59/KU7aBn9F9GzDJAOFRiVi7/2GxX1tpU1DC58/fsaidR4hOWn5doN0RQTxMqmjCUJdXsiIpOR1nb/pKd0GVDCLECAQJsefIdfz8xbNMqCgr4ujOeVBTJVldFRUD3cLVXopLSMWc9TeZfSN9dTR1NMO3HzzrmIK8LK7uGYbjG/thTN+GWDWjHZMh+d7vj0CcGf86tixgi3S6eXxl6pCVRZJT0rH16BNUb7sZ1u23YPDs83hTQPNyBXlZ1K9tDMda3KzQTYe9mDAAgvhQFIVubdjSH6v3eOLwxZcVugRKWYIIMQJBQty8+5zZXvW/UXCsQ9wmFQFRgfptnKywaX4nKCmKH/HxL4oNpo9LSMUTvkrxrRpbcqw+WhrKaFjHhNn38AkQed2WjSxR25o9d/Ds81i6/V6pV00P+R2LJdvuYsaaG5i9/ibmb7qNTYe8cMOT7TRwyf0j9p7l/a1kZ9NCRaOtpT6eXZiE7m3soKWuhNF9GoCiKBxc3RstG7H11159CMW244JZqoSCmTmyGePuzs6mseGgF2avuyVQeoVQ8pAYMQJBQigpKTDb1tVN8plJqCj0bl8brRpb4v7TADx4FgDv1z8YNyMAWJvr4TtfPBg/icnpuP+UFVfNHM0E5rRtWh0+73iuzHve/hjczUHkWuaPbYkxiy4z9z938z0caxmjV7taRXlpRWLVbg88ehkk9Jiulgqu7hmKakZaoCjh7kg5WRm0drLE2tkdoKOpgq2LuoKmaabpuZaGMo6s64vtx72x+zQvkGz/uRdISErDnNHNoaGmJLHXVtFQUpTHkXV9MGWFK2ORvPHwK3S0lLF0iouUV1dxA/UBYhEjlBAkPkwQ2xqmzDa/dYxQsdHRVMGAznVwaE1vPDw9HhMHNUZ3Fzt4nByLK7uHwtZSeC9EIwN1fPrO1ptzbmAuMKdtU7ZDw9O3wfgRKjqgv6mjGdwOjOAEYt/w/FqEV1R0EpPTRB6Lik3GhgNeaFTXFJd2DoGpkabAnHeu07FvZS/oaLKZxhRfGZBcpg1riuZ879cZN1849duLGWtuwPcriRsTFz1tVZzaMgADu9Rhxk5ce4u3X/J3FROKBxFiBIKEGNCrNbN97qoHEpNS8plNqIhU0VPH3DEtsHVhV5hV1YaykjymDG3CHM+N+VJUkMOUwU2QksZzA5lW0YRZVcHCv8aGmmjtZAWAZ0E6dll4cdNcapjpYceSbsz+41c/8PB5IB4+D0RQPlmZJcGL97/wNk/wvGkVrti68/gbHLrvwNhFVziWQwCwszKAspK8WPeSlZXBvpU9OaU60jOycOuRHwbMOAvvN8FFexGVEAV5Waye2R6tGrHFgW8/+ibFFVV8iBAjECREiyZ1UMPSGACQkJgCd4+XUl4RobgUptG3KKxMdZhtQ101TBrshLNbB+L3P7aQpjBrWC6j+7JFWy/f/YTf4fkX4DQ21ERdW9YqNm7JVYxbchXtRx3B+KVXkVlAcHvI71jMWnsTDfvsxoj5FwUq/Iti+c77AjFpGupKmDeW62KiaSA2IRV/IxI445OHOIl1n1yUFOWxbVFXrJ3dgVPaIyubxqx1NznvLyF/KIrCsJ6OzD7JRpUsRIgRCBKCoij069GS2X/sQ9y3BKCqIWsV+heThKlDm6CurRGevv3JjAuLD8vFqa4pI6zSM7Kw8+TTAu/Zu73wuDBPn0A85ksQEMasdTdx4+FXxMSl4Onbn5i6ylWsbDphcz77h2PzYVbMWvKJUgCQlaFQr2ZVnNzUH51a2OQ9vUBkZCgM6FwHrvuG48aBETDQ5dVPi4lLwbRVbkjPyCr0NSsrZsZazHZkBevQUNYgQoxQbEh8mGga16/JbH/8IjxomVC5UFNRYB5yGRlZuP/UHwA4RV0b1jEVdioAnsDntypdvf9ZZAJALoO6OmBUn/qwqqbDsY4B4PSrFIZ2nkbaL97/wueAf/meAwDzx7WEokL++WAaaop4fGYCruweipsHR+Ct63Rc2jkETfMRouJiZ2WAHUu6Q1aGF1P23u8PNhx4VOzrVhb0ddgiwBHRSVItZVGRA/UBIsQIBIlib2fObL//HAg//xDpLYZQZuDPXLzs/gnpGVlITs0AwLMK6WjmX2/OyaEaE5yenU1j1W6PfB+UMjIUFk9qg7tHx+DK7qE4vrEfc+zO4/x7Uq6b0wHVzXQ5Y9fufcp3fQDg0qQ6Pt2aiYenxmHz/E7o36kOrKpxLWC+X//gzA1f1LU1gq2lAVSVFURcrWg0tDfBvHGsVfrk9belnrBQXlFVVmBi9NIzspCYlC7lFVVciBAjECSIro4mWjarCwDIysrGwtWHpbwiQlEpifiwXHq3q43c5L9n734iPJKNj9JQUxKaGZiX/41vxVh7nvuG4JK7+JbphvYmTPX9iOgkzFh7U6SQM9BVw+5lPThjJ6695fTLFAVFUTA10kKv9rWxbk4H3D06BveOjcHgrnWZOceuvEZKjgiVBGP6NkAHZ7aG36Ktd+H/M38LIoGHnjabrRpB3JMSgwgxAkHCrFs8BjIyvD81zyfv8C2g7FY5J5QOVQ01YJwTK5adTSM8iq2Sny2mC8jGUp8TUL1s+32xswMVFeSweX5nRgw+9w3Bk3xclNXNdNGhuTVnbM0ezyK5qyxNdbBwIptRnJ6RhdiE1EJfR1woisKGeZ1gbszLQk1JzcDUla5MQVmCaPT4epSSODHJQYQYgSBhattZoEv7xsz+mcseUlwNoajoW7Vg/pUEVfTYlkhpaZlQkJcFwKuwn5Akuv4WPzNHOsPGQg8Ar+n4rLU383Uz8tOqsSX6drRn9qetcsVl948ixVX/Tvac/RsPv+L8LeG9NQvi5PW3zLaRvjrnvZAE6qqK2LO8B9P1IDAkGov+cyctfAqAP04sMqZgC6hE1lDB48MAIsQIJYCctj3ktO0LnliJGdq3LbN958ELKa6EUBLwi7K8/8QhMysbMfGsFSguMQ0mfDW2Wg45IFZ/SDUVBRxe15dp2BwTn4JlOx+ILTCmDW0KVRVeXFZSSgb+t8UdU1e5CS1p0dDeBPI5YjEXUU3O84OmaVy4/YHZnzCwsViu2OJiY6mP1TPbM/u3vb5xBCFBEEV5NtkiI7P0Mk5L+ktPWYcIMUKJQcSYaJo3YStVBwb/RlqaYExMrqAt6B+hbCNKmKWkZuDwxZfoNuEEbDv8h8CQKOZYRHQiJyA+PjENg2efx6rdHkhOyd+FZqSvjvVzOzL7d598h19QhFhrrWqogRMb+6FaVS3O+edu+nLmZWZl49uPSGTkKf/wNfCf2HXFcgn6FY2Q37EAABUlefTrlP/vtJXLJli5bBJ67M2nUPj4hiArK1usOLNe7Wpx4tPW73+EtwU0GK/MpKaz76lSARmwxaEoX2YqEqTXJKFEkdO2r/DlLIoihjS1AROTqggN/Y2srGz8itOArU31gk8U4/4V/f0u7+hbtUBaWgYGDPgf3rz/LnTO6j2eqF3DEDYW+vj2gxVRJ6+/xcPngVg3tyOaOFQTeY8WDS3Q2skKD58HAuDV67KzMhBrfQ52VXHr4EjM2XAL97x5pTRW7vLAqevvoKmuhLiEVIT8jhVqJaNp4OWHXwLxY/nB30/TuYF5viUu+AWYlcsmBHrMB8CLK5u17ibuPvmOKvrqsLHQg7ycLPau6AkZmfyta4snt8HH7+H4+P0vMrOyMW2VG9z2D4cuXzwUgUdKKtvwuzDN7AuiMoqt/CBCjFDi8AuFsiwSStO6FBcXj/Bw9gGrrS3YV6+oEGFW9rlxz0ekCMvlk384ZGQo9O1YG5HRyUyz7F9/4zBs7gUM7uaARRNbQUlReNufWjUMGCFW2PZFykryWD+nI95//cMkDoh7DVePL2jvXEMs9+Kdx9+wg68AbZucdk3CEGYFyxVj52+9x90nvPfzb0QCU5V/+3FvzB7dPN81KCrIYdey7ug56SRiE1IRHpWImetu4viGfpCVJU4iftLSWSFWUE24/CDCK3+IECNIFHHEjiSEQ1ly4Xk9foZBQycgI4Nn5q9Z0waGBsIbP5cEwl47EWfSxe3OM4GxjcvGoaqRHh4/+4Bj59yRmZmF7Gwal90/Yf7YFujaxhar93giLiej8OwNX3z6/hcHVveCvo5gcLuVKevaLEofSU11JVzYMRiz19/E28+CLW0M9dTQxKEaxvRriJS0DPSffhYAcM/bH9fuf0bv9rVFXjsrKxu7Tj/DntM+yA1fM9JXF2lJE+WKBADzVutxbJiu0GN7zz5HgyYt0Kdr/mJM3wo4vNMI/UavAk3T8HkXgu0nnmJOASKuspGaVjQhRoRX4SBCjCB1ChJNwkREWRJa+REdE4v+g8chMZHNZKNAISsrC7KysvmcWbIQq5l08Xn1mbMf8OoU9PW0AADdOzbFuOFdMH/FQTx66gsA2HX6OZ7f24NuvQZg6uzVjDvvw7e/mLP+Fk5uHiBwD/52QX5BEaBputBB8CZVNHFxxxD8Do9HXGIqkpLToawkD3MTbYFiq/062ePSHd7v0eJt9+D75TdG92sIc2NtpKRmwC8oAl8CwvHmcxie+4bgXxT7N2Bhoo1jG/pBXVVRYA35iTAAuH79On79iQMAaGmq4eOTIxg1bSMeePEC76fM2w5LMyPUs8/f9d+uVQPMnzYAG3eeBwDsO/scrdq0Q31zyZXSKG9o8xUWjs4wIAJLQlAVOX3XsV4d2vvRDWkvg1CJSUhIhJVtIyQlcVO/W7ZoimuXjkFRUfBBVB4hwk40kVFxsGowlDP24+0Z6GhrcMYyMjLRusdsfPzK6/3YuW1jnDu0BDRN49DJW1iw6hCys3lxWhe2D0L92iac89PSM9Gw926mQv/5bYPQwJ47pyRJTklHz8mnONY3igKqVdXCrz9xAg2/c2lSrxp2LOkGHU0VgWMFiTAAaNq0KXx8fAAAcyb3w7J5wxEbn4i2vebCP4gXeG9spIeHrlthqK+d77WysrLQd9RKeD55BwDQ1FDFW88D0NNlQwdKspBvaVISomnTzvNYu+0MAKCTSyOcP7y02NeUJJoW3d7QNN1A2usoLESIEQgS5sPHL/hv215cvnqTM7518ypMGDdcSqsqX5RnoXf/0Wv0HbWSM+bjvhs1bQT7Kb55/x0uveYy1qyvPsdgZMhzw02et52pQde9Y1NsndtM4Pwl2+7i/C1eaYhOLWywc2k3iZaG+BEajVnrbuLT9/AC5yrIy2JUn/qYPaq50FgscUSYv78/rK157kwFBQUEBwdDNe0NACAgKAxtes5BXALP8tawng1unVsPRRExdblERcehRbeZCP3Nq7Y/cWQ3bFw+XuT80hZm0rRCBf74Dcc2EwAAMjIy+PD4EEyNxUsCkQblVYiRyEQCQcLUsa+JE0d34/fPD+jauR0z/vCRtxRXVb4oz+U8Xr714+zLysqgioFwS039utZo3oT3mmiaxmU39qE/aRTbZsjn1RfoWTYXeEgP7OrAbN95/A3r9j+UaNFSCxMdXNszDKc290fLRhbMOEXxiqjyZzCmZ2Th9ccwoVmN4ogwAEhOZi3LxsbGMDIygoZ5VwBAdUtjHN01n+li8erdN8xasqfA16+ro4lNyycw+4dP30ZgsGCMXC4lVWohv1p0ZaWUg5VFVbRq5gAAyM7OxrkrnlJdT0WFCDECoZTQ1NTAimXzmf1nPq8YVxOh6PCLMlrNFvvPvcTOk0+RlFw2Yn227LnE2R8zpLOAW5Kf/j1aMdtnr7DNvGvZmkFNNac/ZFQs/v7juQT5H9i1axiiYws2AP7YlTeYusoN6RmSK8ZJURSa1DPD9kXdMKSbAzTUFEHTPOGV1z355nMYk+2Yi7giDABsbW0hJ8cLbf7x4wfi4+MBgBFjbVs6Ys2iUcz8M5c9sOeIa4HX7dyuMZo0qAkAyMzMwuotp8ReU17RVB4EVmHo1cWZ2f4WSNqzSQIixAiEUsTWpjr0dHlB1VHRMXj9xle6C6pAPH/xBlr6NbBg0WosXb4BW488LBMWtGaN2WzCGpbG2LBsbL7zu3dsyrgTv3z7CXePVwCA177fkZ7BFtj88DmIc17uA/7kwQ2cbMS7T75jxIKLiI6TbIua5Tvv48wNX8Qn8toz5ZY+sDDhWv+evv3JbBdGhAGAoqIibG1tmX0vLy9mO1eMTR7dA0P7sZ0slq4/hgdeb/K9LkVRWM0n4K7d8sbrd98KtTagYmYLVjNhXZGhv8UrFEwoHESIEQilCEVR6NCebXi8c/dhKa6m4rDvwHG4dOjDGdPV0RE6t7TF2f+mD4SmuioszY1w7/KmArNlk1NSOe60JeuOgqZp7D58Hel8dZ1ei6hLpqgoj7NHN2HSqO7M2KsPoegz9TQCfkYJPae4xCWk4g6fpctIXx2zRjrD/chobF7QGTpabGC+U11eYdrCirBcOnXqxGzv3buXc0zDvCsoisLO3XvQuBGvIXp2djZmLjkEWa3a+f7cG9azRY9ObNzd0vXHSC9KANZWbMLH128h5D2RAESIEQilzLQprEXkutsdBAYFS28x5RyaprFpy27MXbBC4NikCSPEvo4kRZmzkz2+vzqJt54H8nVJ5vLQ25ezH/AjDJ++BuNTTjZlLvc8X4u8hpycLNYvHYuVC0Yy1rVff+LQd9ppvPoYWvgXUQB3vb8z7Y+MjfRw/ugqNGvpggNXv6Pf9LOIjuVZ46oY6KB98xpFFmEAMHHiROY1ubu74/t3riDVMO8KRUVFnD21H+rqvHprv0LDEBb2R+BaeX/my+cNh5wcTyg/e/UZdx68LPI6KwrGRnrQ1OB1HYhLSELYn0gpr6jiQYQYgVDK2Ne2Q7u2LQHwhMTuvUekvKLyCU3TWLZyI1au2SJwLObfd8jL558tJwpJWMuUFBXEzl7MEtJKaP7KA0hM4vZ09P0UAO/norNJKYrCzIl9cHr/Qqgo88qkJCanY8LSq5w+l+KSX7xTfCZrfQz7E4mW3Wah76iVuHbLm7GgKCspYMe6KbDt8F+h782PpaUlunbtyuyvXLlSYI6KphmqGBrAvrYdM/b5q2hXY+7P2sqiKkYPZi1uyzceR2YpNrsui1AUhVo25sz+Z79gqa2lokKEGIEhIyMDGRkZxPRcCvBbxR4+eprPTIIoVq39D1u37xcYHzViEBQUFIScUTRKO74s1/rAz7OXnxEeESMwfuTMnQKv17V9E9y9vImpqRWfmIbxy28hPpFNZihucPnoIZ1gZy26F2aHNg3w/N4e9B+zqsD1isOMGTOY7bNnz+LEiRMCc1Q0zVDTjo2V++rnX+B15bTtsWD6QKir8ZIivgeG4tTF+4VaW1ZWFrKzsytUIk4tW3Nm+/O3YKmto6JChBgBALBx8y7oGdlBS78GTC0c8N/2fUSQSZAmjRswFpLAoGAkJ6cUcEblJfxfBA4cOolv39lm0RcuuWLTlt0CcxUVFTB9av7B8MWhNGLLWjs7QElRPCGZkZlZ8CQAdWpa4sKRZYxl7OevcPh8lymxDD5DfW08ubkDG5aNg4N9ddSyMUcjR1uMG9YFT2/vxMUjy1Gnecn9XFxcXDBiBOt6njx5Mvz8/ATmWVjVZLZ/hYSJde0q1Z0xZ9ZUZn/99rMC1khRnLp4H2YOg6Bt1QOmdQbi+Lm7Yp1X1qlpy9a8IxaxkocIMQIAYN/BE8jM+VCPiY3DshUbsXrtVimvquIS/i+CEbrZ2dlIS08XOTcKGmL9q6gMGjoBs+ctQ/3G7bBz92FkZ2dj5erNQuduXLcU1jVEN5IuaSQhytTVVDCgZyux5tatKf5rrWdfHXbW7ANVVC2zoiIvL4dJo7rDy20bnrnvwv0rm7Fl1UTUtrNgMhpLkt27d8PGxgYAr75Yly5d4ObmxvkC+erVK2bbxib/lkf8TJk0GkZGhgCA8IgY7D58XazzNuw4i4REnmhLTErB6UuFs6aVVWrbsjXiiBAreYgQIwAAalS3EBjbtvMA4uMTpLCaig9/XFN9x7rQ1tIUOq8wAquiCraAAF6QOk3TWLhkDXSr2OJniGDAea8enTF29FCB8dKiJEXZ4jlDoawk3Cqmr6vFbCeIaakBgPT0DHz8ypa8cKxTo8jryyUrKwvBv/4iIjJW5BxJiDAAUFNTw8WLF5k2YUFBQejRowfq1q0LR0dHGBgY4Pr168z85s5OYl9bRUUZSxfNYfYPnb6LrKz8Y8Vi4xOZ6vy58Lv0yjP8bmf/oDCkpWXkM5tQWIgQIwAANq1fDsU87pD09HR4PiTV3yWBp+cTZnv9msUCxyUpmsQVbJL4VxQoGe7HVLoQ66G5mSl271gv0XY+haG4osxQXxtzpvQXeiwiKpbZfv76i9jX/OQXzJS/sDAzEiuDMz/OX/WERb0hqNtiHKo3HIbB49cI1N6SlAjLpU6dOjh58iRUVdm4uo8fP+Ldu3eIiGBrXhkZGcGxkUuhrj10cB8YGOgBACIjo/D+R3a+P0+fl4I/C/5yGOUZdTUVmJnyLISZmVn4HljymbeVGSLECACAeg61sXzJPIHx4BBSSVkSJCQmMdt17Nk4lvJqtRKXooi3Fi5t872mnJwcThzdBS0RVkVpU1RRNnVsTyZoXBSvfb8hNj5RrOu94as7Vr9u8a1ha7eeYfo6AsCt+y/g0nsuegxdipDQfxIXYbn0798fQUFBmDFjhkCShoyMDKysrLBnzx5QFAUVTTOxvxzIysqiY/s2zP6du7z2PqJ+lnkzWLU01dDcqey34BKX2nzWvS8kYL9EIUKMwNC/b3eBsaioaCmspOJjZWXObPu+/wSgcG7IykSnbuwDXU5ODjY17TjHV6/4HxrUdyjlVRWNwogyZSVFNHK0y3dOVlY2foWKV+38LUeIWeczk+dyXLbhOHoOW4pX7wSD4Gmaxu9w4SUwHj31ReteCzhV7yWNgYEBtm/fjuDgYNy8eRM+Pj4IDQ1FWloaAgIC0KtXL2auqSY3Ni4/QdapAyvEPB8+4RzL+zM8e9WDs9+1vRPk5eWK9HrKIjX5Slh8KoNxYuWh76woiBAjMBgZGcKxXh3O2LdvASJmE4pD44aOzPbzl/m3X6ns1HWsx2xnZmYi/M9fZr9TBxdMmzJGGssqFpkxout/8VNQQL26mjKqW1YV61pv3rPlGwqKDzt08hZ2HLiCh96+6DF0KYJ+couhJiSmMPW1VJQV8fzubgzs1RqysrxHSmRkJLy8vBATI1hyQ5IYGRmhS5cucHJygrGxMdOXMi95xZgu4oXOa9y4PrP97XugyEzyy25eiI7hxtN279i0MEsv89QiFjGJQYQYgQP/N0AAeOz9nJRWkAC57VcA4OXLd1JcScnyJywMJw8fQcB34e13ikJ0HqtsbM7D3djYCAf2bSkzcWHiIq4IA4QXd+XHwb4GlJUUC7xOXHwSE9cjKyuDOrUsRc5NSEzG6v9OM/tJyak4cuo2Z05MHCs6tLXUYWdthgNbZ+P2+fXM+KZNm7B+/XqUVfKKMWEY6OtBU0MdAJCQkIjwf1zrY1x8EjbsOIexM7lFaimKQqtmDiW21rJArTJewqIwf1dlDSLECBz445UA3ofPzdv3pLSaigu/EHvx8g2ysrJEfisvL3jeu4/GteyxZO48DOjaHWlpaSVy3fOnTguMycrK4vjhndDVKdkSDJKmsA+LHyF/8z0uKyPeR/jX7z8Za05NazOoKCuJnOvz6otA3Sy3u884+/zWHx0tdWbbqUFNHDhwAACQlJSE8+fP488fwdZCZYWCxBhFUahenRWt/v68rNOsrCwsW7kR1eoOxPrtZwUsZTMn9oGiYtE6O5RVLM2qMvXt/oRHIzqmfH9elSWIECNwqFFD8Jvy2fNXpbCSik2N6pbQ09MFAERFx+C6W8EV0ssyP4ODMbL/AGY/Pj6+yC2G+AkKCMDpo0cFxpcsnIWmTRoW+/qlSVG+sQcFC4qYBg42hb5OWjpbbkCLTzgJ49mrzwJjIaH/8I+vsj//Q1hbm3u94cOHQ12dN/br1y80a9YM8fFl96FdkBirwS/EAoJwzfU2qlnWw3/b9gmdX83EAPOmDhB6rDwjJycLmxqmzP7nbz+luJqKBRFiBA4W5tUgKyvLGfN67FNgDR1C4ZCRkcHI4eyH9cIla5GQIF72W2mSnZ3NFPrNj3VLl3H223XqCBkxrTX5XnfZCoH7GxkZYtaMCcW+dmlSFBH2+28Up1RFLro6rPAR1yvL/7OgC2i9I0z8ATwxlktMHPu7qq3JFWJKSkrYs2cPc88fP37g4sWL4i1USqhomok8xl9jcfGy9Rg6YjJi44QLyz7dWuD2+fVQVRFtcSzPcDIny6B7srxChBiBg4KCAszNTDlj6enp+BEcIqUVVVxmTBvPbIeF/cGGzbvKlHvyxTMfNKpZG3bGpti9dZvIeV8+fsKdGzc5Y2v/E2zEXVh8nnjj3u3bAuPjxwwrEWubpMjKysI119u47noH/yIiixy7cuI82x5HgS/7rmXTuoW+lgyfYiuodVl0rPAizsmprKs5ic91KazExrBhw7B69Wpm/+7dst/qR5QY4/cSCCtw7VinBhbNGoxXD/bi6M55MDU2kNgapU1Zz5wsrxAhRhBAmHvSPaeGDqHkyGtlfPiobBXPPbhrN/79/Yu0tDRsWrUaoUJqykVHRWHmhImcsSbOztDW0SnWvbOzs7F6yVKBcUVFBYwaOahY15Y0W7buxdARkzFkxCRY1GiAKzefFHxSHjIyMjl9ChfPHoKObRpi/dKxUOILztfTFa92Gn9CQ3Z2AUIsWviXAT0d9l5ZfFa1vBb0XLp3Z8vhPHjwQCzLqrQRJsb4XZN5cbCvDs/r/2HB9EGwtjIVOa+iwM2cJK7JkoIIMYIAwj54NmzaibCwsht0Wx75+ZMrbEYOHyillQgn+EcQZ//4wYMCcxbNngO/L9yK4rXr1hGYV1iuXriIT+/fC4z37tkV+jmxdWWVvO2Xdh4sfIzlzXvP8fcfL1vUUF8bU8b0xIUjyzB5dA+85qvrVdNGtEuNHxkZPiGWj0UsKysLoX8E65KpKCvCproJ3zx+ISb8MVKrVi0YGvKqscfGxuLHjx9irVXa5BVjVpbmIuf6fgyAgW1vjqu2IlOL7/ft6/efyC7AzU0QDyLECALUcxAsjBcTG4e+A8cgNjZOCiuqmNSxr4mqVasw+2WpeC5N0wIWsJc+PgLzPO4KZtRWNTERGCssp44cETre1qVFsa8taexrc4uwBgSFFfoah0/dYrZHDurAFAZNSk7FHQ+2kXXLJuK5KfljxPJ7eF6/8wxx8UkC4451anCukZXJWnP5Mzf5i2pSFAU9PT1mPzU1Vay1lgX4xZiqqgpMTETXaktPz8SMhbtLY1lSx0Bfm+l1mpSciuBf4dJdUAWBCDGCAJ07ukBZSHr7h49f0GfAaCQlJXPG3777gGc+rwqMPSFwUVBQwLTJY5n9Neu34eate2UiTiw6Kgopydyfc7yQAGX+B20uuRlzxaGaubnQcVWV/Fv+lAXCf33l7Jvn9OgTl6/ff8L7Ba/bgqysDEYO6sgcO3bWHTE5MVzVjA1Qr051sa4pI4ZrMik5FUvWChfA3i8+wfUOW8KC3zUpp6IvsluAsjL78yrLmZPC4Bdjtjbs+9zWpYVAmZ87Hi8qzedfzTJeT6w8QoQYQQB1dTUsXDBD6LHnL96gVbteuPfgEZ4+e4kBg8eheevuaNepH65cuyn0HIJoJk0YgRbOTsz+mAmz8OmzYEuZ0ubXT8H4D1k5bixQakoKwkK5bjiKotDAqXGx7q2LeKxaOFVoQP5Dr6fFunZp8OItV4jlVzxVGPuO3WC2u7RzQtUqPFdsckoqdhy4whybOamv2JmpFMc1KdwidsfjJX7/Fd62CAA+ff3BCC5akRWXomLEAMDCgs04DAgof106csXYxHEjmLEHHo/x4SPXHZ+RkcU0VK/okJ6TJQ8RYgShzJw2Hq1aNhN67MuXb+jVdyTad+6Pm7fvM+P82wTxkJeXx6kTe5lM1cTEJAwYPA7RUaIfiKXBrxDBLNkqRkbMdsS/f+gmpBl3p+7dYFldPCtNXnQRz1gDq1tZoHevLgJzjp88j+/+gUW6fmmQGuGLt3ythABAXU1F7POfvviEkxdYd++44ex7cOL8PfyLjAUAGBvpYWjf/Juh88N1TQq33Ph9zz8zOo2vHyN/vKh2Ps3Wa9RgWyl9+/atwHWWRVQ0zdCpowuGDeknck7ThjUrXAFXUXAyJ78GS20dFQkixAhCkZWVxZkTewXiXfLjuusdTJ62oEw/KEURH5+Aq9dv4fzF6/B5/rpU3Qx6ujq4dP4I1NRUAQDBP39h+ohhUq3dlpoiGM+TK8RomsaC6TPx7QvX8qNvYIAVGwrf0oZfgPGTt90WAKSlpWPC5LllMkg4M+YjQv9ECFSlv+PxUqyfZXxCMibN28787rVt6YjmTjx3X2paOrbvZ61hsyb2LdSDnz9YX9TvtrKyArMtzMplVIW1gn3kswiJ+oygaRpPnrAZowoKCkLnlQdUNM2wZeMKDOjfE5YW3GD+KgY62L5uipRWVvqQzMmShwgxgki0tDRx/coJgQ8eUWRkZODEqQtwbNQWnboNwoFDJ/HnT/kI5hw6cjKGjZyCMeNnom3HvtiydW+p3r+mnTWOHdrBlBl47P0cN69dL9U18KOpKWjlMMwRYs+9n+KBuzvnmKKiIo6cO8OxmuVHrvjKLx6urUtLoYLg5at3ePHyrVj3KS47dh2CS4c+uO/hJdZ8/hIPuYSE/oPHY9H9RL2evUePoUthWX8IfuYEP2tqqGLXhunM78PJ8/eYLEojQx0MG9CuUK+Dv3wFncciJqdtD1mt2rh04zkzJkw45hY2pWma45qrW6eW0Hu6u7szQkxOTg7Dhw8v1JrLGgbGNXH04HZcOHuIGVNQkMOdixsqRemKXGxrmDIW1sDg30gW8qWNUDiIECPkSxVDA9xyPYOGDRzEPoemaTx+4oPZ85ahRk0nuHTog7Pnr5bZ6vzZ2dnwfvqCM3bNVbCQqKTp3Kktp2L83m3bS30NuWhqaQmMJeYUs/zuJxjDNm/JYjjUr1/gdQsSX/xoa2nC1oZ1bfEXGvZ9/0msaxSHN2/fY9HStXj+4g0WLl6T79zcoq1qqsro0k4wRu6B1xuBMf/AUHQdtAjdhyzBo6e+yMhgY4w2r5jAxIalpWVg2/7LzLGZE/owPf/EJW+wfm6sV26A/fsPn/HVz1/U6dDQUEfLFk0B8Cy2cTm/CzraWjA2FhTfqampmD17NrM/YcIEWFoWLlauLKKiaYZfoWwWbEMHG1iaifflo6KgrKQIK3PWOu7nL1hfkFA4iBAjFEi1aibwuHsF27asRssWTaGurib2uTRN4/mLNxg3cTYaN+sItxvuZS67yPORN9LS0jljQT+kY3KfPXMSU7Dz6+fPCPsVWsAZkkGYEPN56g2apmFqJmghffHMR6S7UBzrlyhq1rRmttPS2Z/Rv4jIQl+rsOzZf4zZ/urnL/L15a2cv2/LLHRsw+2Dqamhytl/+8EfbXrNwZPn3HNrWBrjv9WT0L9nKwC8v5+Lro+YIHpDfW2MGNSh0K+FEyMmIyji7t57mO/5w4b0g0pOxurlq2wyQb169hxrWy5btmyBX45gV1dXx5IlSwq95rKKjj6bgFBQcdyKCn+cGMmcLD5EiBHEQlZWFuPHDsNtt7P4++sTosO/Iej7Kzx56IZd29dh1IhBsBZSkZ+fr37+GDRsIrbu2F9Kqy6YjIwMjJ0wW2A8v7pBkkRbSxPNmjZi9oXV7ioNNIUEYH/78hWPPT3Rok1r2NXiuqPu37mD00ePccaKKr74qWXHNriOimKbTuctmpof/gFBWL9xB1q364X+g8YKbVOTl9jYONy4yW3LI674U1NVgkqeXoP8Dy4AWLj6EOITeOVB5ORkMWJgB3x4chivPfZj7NDOiIiMxZT5O2BaZwDmLGObS08a3R3KfJX1xYU/G1JeTk7guPezl0LPu3f7IoYP7Y+Vy+YDAEJDf2Pbdvbvd9CA3gLnREREYNOmTcz++vXrUaVKFYF55RX+ki2Bwb/L3BfL0oA/c7IgIVYZ35/CIvgXSSCIgaKiIgwN9GFooA/HenUweiRv/KufP1zd7mDfgeOIFFGg9L+tezF10mgoKhb+gVLSXLzshgghD9hhg0VnSEkaW5sa8PDkxdb8C/8rlTUIs4gBwIFdu9HSxQVrt25B7w6dOMfWL1+O/p2chbqqikpNO9Yixl/B/dUr0TFX/Bw+ehozZnOtMa433PPNgAOA02cvIzmZDbqXl5eHhpD6aHmtYTRNY/zsrbiap61Ry6Zst4H4hGQ8f80mOty7tAn1HdjX6R8Yil7Dl+HXb8EK953bFq00yK1HrDu5OV+5FIDnmn/5SnjMnZ2dNfbt3sTMmzh1PuOWtDCvht49Owucs2bNGiQk8ObY2tpiwoTy1aC9IOzs7KCjo4Po6Gj8i4yFx+O3OH/tIRISkjF1XC8mwaIiw99PMzJaeJHvj19+4NFTX8TEJsDT+x3aONfD+BFdUcWgeO3PKiLEIkYoUexsa+B/86fD+9ENONStzYwbGupDLuebeFx8AnyeC8bMlDZZWVlYs26rwLixsRGGDRV8UGdmZkq0X96JUxexYtVmPPNhK6fHSamTgbKKitA6Xt6PvBD6wQcdGtthxLABnGNJSck4cPhkia6jZk3WIiYvL89k3gX9+FmgherN2/cCIgwAavFdUxgJCYnYsm0fZ6xJ4/qMay4XYc281207g8tujzljMyb0gY42W/rB8wkrImvZmDMiLDomHrOX7kWDtpOEirAqBjqwtip814JvfxRw5hybcdmzO1dAJyUlIzGRV01fRUUZWpoaEMbSFRuZfqgUReHgvv84X6Zomsbe/cewZ88eZmzDhg3M331FQUZGBi4uLsx+n5ErcMnVC+6er9B10CKk8DVHr2j4B4Zi6oKdmDh3GzMmrDxLalo6Bo1bjSXrjuLabW+8+xCA//ZeglOHqQJfUghEiBEkhKmpMe7cOAfFnKDi8PAING3Cxs18/PRF1KmlxqfPfgj5xW0/07xZY3jevQIdbS0AvHpJcxesgKqWOTT1qsOomj3OX7xe4mvxef4ak6fNx+ate/DOl33AuzQpft/GokBRFDRFPJB37j4MAJg9c6LAseMnzpeoWDWrZsKIr/j4BNhYWzHHCrKKde4+WGCsR7eOcKwn+J5mZmbi46evuHHzLvoNHCNgJe3YwUXgnLzwCq4K9pWcOYF132VlZWHrvkvMftcOPOtUTFwiug9diiOn74i8fkpKGuISBNsP5Ue2qg3GjJ/JxEA61K0Np8bcpIoUvtZDyckpiM3poCArKwtlJZ6Lddeew9i+8wD7mqaPZ/6es7Oz4fv+E/oPGod5/1vJJOU0b96c0/i7IjFmzBiRx56++FyKKyk93n0MQJtec3DqIrdeZBUDbYG5b9/7M18mgoLZmnMxsQkYNW0TxszYjOjYgkMEKgtEiBEkhoaGOtq0as7sBwezBSOlXT2epmls3LxLYHzHtrVMfNjNW/dQr5EL9h04zhxPTk7BxcuuJb4e/jpPucyZOQnt27Yq8XvlhT+Ynv+fqEKdl6/eQGjob1S3shCwnkRFxyAgMLjE1iYjIwN1NTbQ3awaaxH6G/5P5HkRkVGMlSeXndvW4vQJblkSmqZx4ZIrNPWqw8m5EwYOnYAneTJoLS3MMGYUV9QJs4b5B4UhLT2DMzZv6gCONezwqdt4/4lXZ09JUQHDB7RHfEIy+oxYjo9fuE3W8xKXkITTFx/kO4cfOW17rN2wHR8/8dygiooKOHxgm0A1fmUlJaFlQlo0bwJlZSW43XDH//iyRrt0aosVS+cBAKJjYtGxy0A0a9kVt93ZtTVo0ADnzp0TGshfEWjfvj1q164t9FhutmtFY/8xNyauMZdGjrYYPqC9wNwYPpHl1MAOx3bNRzU+d+Zlt8do2nEqPB6XThmasg4RYgSJ0qplU2Y7PYN9SOU+HKSFz/PXcL3BrYXVupUzbKx5VeGvXLuJgUMnCPTVBIAJ40q+HpKammAmaudOBVthioo4mYxaWsItYpmZmUxGobyQIp3+JVzQV5nPJcifpZY305Uftzw/25uuZzBm1BCOCKFpGnPmL8foccLbeQE8y+DhA1uZYruAcBEGAL//CHZDGM9XGf/vv2is2Xqa2Z88ujvuPXqN5l1n4M377yLXwGm2rWgGdbMuuPIwAsu2P0CqSiNomHcV+u/tx1/YyhdYv3HjJtRv3BYqmmacf4YmtTB06FCB+w4dNgoqmmY4cOQ8Z/zSFTdo6FpBSd0U/1uyGU99uIH+U6ZMgbe3N4yNjUW+pvIORVH477//BMYXzRqMmjbi1V0sb1iac2M/n97eiXuXN8HIUFB4mhjrM9uxcYno3bU5nt7ZhaH92G4Qf8Kj0XvEcixYeRCZmcUrbfT0xSf0Gr6sWNeQJkSIESQKf+HNnt3Y2JSvfv6cYOjS5tnzVwJjA/r1AMDLsps4ZZ5Ato+ujjbu37mEDu1al/h6+K1uuaSmihYapYGqqqrIY8dOnMOXr9+FJjqoFaK8iTik8sXcKPFlDKamiY7F2fwf1/LlzJeJCrAi7MAh0TFtBgZ6uHj2EBo34rnyMmM+ihRhAPDzl2BiRWDwb2Z74erDjEXBpKo+jp+7i1mL9yI4hD1v7FDB4PfcshlVqlTB1KlTMWTIEIwePRo7duzAsmXCHz4JCQkYPnw4c66LiwumTZsmcu3btm1DvXr1AAA2NjZYuHAhU4DV3p4bfN6+fXv0798fjRs3xpkzZ5jxZs2a4dmzZ9i9e3eZSMSRNO3bt8eMGVwRL27vz/JIry7OzLaSogLMTA1FWjxNjPSgosz7Hfjzl5e0paGugj2bZuDsgcXQ02Wt7fuP38CQCWuLXBj2xl0fdB28mBN7Wd6oWFGUhDKF7/tPuHWHjScYM3oIPB4+gX9AENLT03H+4jWMHikYx1MaCHPFpOfUqdqwaZeASKxdyxaXzx+BqalkvuU/8xEsH8BfwFQa9O7ZGY9ENNlOSEhEwyaCLgk5OTk0alCvSPf79NkP3k9fgKIoWFmZo3FDR1xzvY3ISJ6lSVlZCVZW5sz8NBFB0b7vP3GKbgLgJB7QNI2581cIiDBFRQWsXbUIz1+8hqGhAf43fzo08Ctf8cV/zZv3nguMd+z/PzSsZwN1NRXOgyI7O5sTI6OlqYb1S8ciMZH7eydDUcjO+UKwc+dO/Pr1C+fOnWOOh4eznStomoaXlxeys7Nx9uxZ/PjxAwCvS8KxY8fyFQna2tp48+YNUlNToazMTUqYPn06jh49iqQknqvX29tb4PzBgwdzRFllYfv27bCwsMDMmTMBAN7PP2He1AH5n1ROsbYyRW1bc3zyC0ZqWjruer5C3+4tBeZ9/PID0/63E9VMDBEU/BuamtwvdF3aO6GRoy1mLNqNW/d5YQDunq/QbfASXDyyFLpCulOIIjklFfOW7y+TLc8KAxFiBIkQGRWNQUMnMO6jBvXroqadNYYN7YdlKzYC4JUIkJYQExb/9Nj7OYYP7Y+r129xxs3NTHH7xjno6ggGpZYUUdGxnH1ZWVmYmEi3YveYUUPQoL4DYmLiEPb7D8ZPmlPgOe1cWkJVVfwm17n4fQtA42Yd853TpVNbJngc4BZ4zeXN2/fo1XckZ0xGRgaZmZmQk5MDTdOYt2Al9h86IXDumRP70KmjCyZNGJkjvsSvGH7x+iOB4qy5vHrHbXbd0MEGr3x5Y2qqyujbvQUio+LwxOcDkpLThM4zNTVFhw4dBFpPrVq1CgBPhM2fPx9btmwRuP/evXthalqwqKcoSkCEAUD16tXh5eWFyZMn4+VL7hcGeXl5zJs3T6RlrjLQq1cvRoi9ePMF6ekZUFComA3Ae3ZxxqecumHXbnkLFWLuni/x7mMAAKC2nTkmjhRM2NDX08KZA4uxasspbN3LS1557fsN7fsuwJUTK2BuKl7duT1HXPEnnGdx09PVRGSUdLLMi0vFtaMSpEZsbBwGD53IZCRqaKjj0P6tyM7Oxu07bECvlohg8NKgRnXB4rNfvn7H37//GMtYLtnZ2VAQUsqhJKlpW4Ozr6mpUSbS/uvWqYVWLZuivmPdAufKy8tj3ZpFRbqPqDpWuejr62HD2qVQ5HdN5rGIPfJ6hs7dByMqOibv6cjOzuaJsP+txL6DxznH5OTkcOLoLrRrbFCg+1EYP0PDMXc5G4s1clAHfPI+goG9WkNenvszbO5kDx0dth5ZYlIKjp+7i5v3nuPsFU+43mEtkDqG5sz2iBEjBFyLVlZWsLe3R0ZGBqZPny5UhPXv3x+DBg0q1OsRRv369fHixQv8/v0bt2/fxrlz53Dy5En4+/tj7dq1lcIVKYpq1aox7ZtSUtPx9oPoVlHlnV6dWffk/UdvBIL3AXBc7aMGd8Kw/sL7olIUheXzhmPzigmMizPgRxja95mP958LjjONT0jGjgNsWZalc4aJ/TrKGgUKMYqi+lIUdYWiqJ8URaVQFPWNoqj1FEWp881xoSjqNEVRgTlzAimK2kdRlIGQ67WiKMqPoqh4iqIOUBSlwHfMnKIoOudfGyHnelMU9agYr5cgYYKDf8GlQx9OAO+RA9tgXcMKGzfvwvMXvPph8vLyWL3if9JaJho1rCfQqunn9jr8FQAAfkdJREFUz1/Q1dXhxCEBQMivMNjUaoKDh08hI4ObFVdS9OrZhbMfHR2DiEjB4G9pce/+owLnzJw+HtY1rAqcJ4wWzk1EZmmOHjkITx/dgJGRITQ1WBETwlddPyDwB/oNGiOQKQkA1jUsoaCggP+27xOIxdPV0cbdixvQs7V5kdYdGRWHviNXMA8kVRUlXLvlDQ11VezZNAPjh3WBspICzE2rYP9/M+F6ejVevv0m8nq6OmyCREwMKyj9/f1x8iTXlXrt2jUkJSWhWbNm2L17t8C1unTpgsOHD5do5qKRkRE6deqEgQMHYtiwYTAT0u6qMtK6NRs3KsoyWhGobmkMeztei6e09Ay8fCuYdMUf9pGdVbDLcPyIrji+ewEUc6yI4REx6DxgIZ6/zr/E0dsP/kjIceWbmRpyEgHKG+JYxOYCyAKwCEBHAPsATAJwn6Ko3PMnAtAFsCZnznoA3QE8pyiKedpRFKUK4CKAQwB6AagHQFTK0trCvhiC9MjKysKZc1fQsm1P+H0LYMbXrV6Mzp3a4vLVG1izni0COHvGxAILa0oSiqIEgvGTkpIRFRWNSRNGCsyPi0/ArLlL0X/wOInEI4wcPgBVjbjm+NHjZki9UXpSUjImTJ6LhUu4Ta9z66zlUrVqFcybPaXI9zE3N8Wr5/exbPEcVKnC/f5Wx74mU60/N3AeAO57eDHtio6dOC8y+WPOrMn4+fMXVq3hZrnZ2lTHI9ctaFCv6L+HU+bvwPdAniCkKApJyamIi09iaiXtOeqKlNR0BP/6i92HriMiKo6T2p+XqGheFqu2tjYn/uvChQucefPmzYO9vT1WrFiBV6/YxBNTU1O0b98emzdvhqurK9SFdAMglDytWrVitr2fS74hvTRpXN+O2c51QfJjZmrIbAcLSWARRs/OzXDt5CpoqvPiyRKTUjB04nqE/RFdtDmer6ZeNWMDyMkJxv2WF8QRYt1omu5P0/QZmqa9aJreDmA6gMYAWuXMmUzTdCeapo/lzDkMYBAACwD9+a5lB+AXTdP/0TTtAWA1gBZC7nkPgBNFUd2K9rIIkua+hxcGD5uIrj2HomvPoajfuB3GT5rDBFYrKCjg2OEdmDFtHF6+esuJL2rTujkWLpguraUDAC5duSHUevLU5xWWLZ6DzRuWw9JC8Nv+vfuP8OjxsxJfj4KCgsB74vnQG+s37ijxexWGa663cfrsZYHxzDwCsXuXDkWKDePHqIoBFsybBt9XnujXl40r2bhlNyOa7WxroFZNWwC8mm5Xrt0EAMTHC5bhMDUxxrlT+zF4YG+cOXeFI2oVFBRw7fgSVDMRMNqLTUxcIu4+fM3s8wt7j8dv4XqH+3vyyS8YPYcuFXotTQ1VuLRwZPZbt24tMq5LWVkZy5cvx7t377BtG/vlZu7cufjx4wfu3r2LuXPnCk1IIUiGli3ZWKkXb74gLU0ylvOygIN9dWbb9xPXhZialg5fPnFWmKbozRrXhvuljUxGZURULIZP3sB88fV69h6T523Hr98ROHTqFuysqzHn+rz+IrboK4sUKMRomhbstQHkfgUzFndODiEAque4J3UBDAUgrIDOZQBvAayhKmpFwHLMVz9/9Ok/Gq433PHwkTcePvKGfwBbjNLAQA+3XM+gf98eCAkJRf/B45mgfRtrK5w6tlto+5zS4rt/IGbOEWx9AwB//oZDQUEBkyeOwrw5wi08Z85eETpeXJybCfYR3PTfHkRGCPvzKh34G23zk7dxdsOGRcuUFIa6uhr2797E1O768yccf//yirdSFIUhg/owc3Nb7giz/Fw6fxjdu3VEdEwsjhw/yznWyaVhsQtv3rzrw4gvZSXBemrCmh1/9Q+BhjpXsGppqmHrmsl4/oZ1Wbq4uKB3b8GG2gAwc+ZMREdHo0+fPoy4bNOmDTZt2kTEl5QwNTWFlRXPLc+LExNdF66841CbFWLvc0TX9dtP4dxlBgxt+8DNnf0C0sjRtlDXrmljhhO7FzB9ZV/7foPPqy/wefUZ3YcswZnLHliw4gDmLtuPEZM3opEjz5qdmZmFA8dvFPelSY2iBuvnyv/8qnIKzKFp+h+AJQDuA4gEYAlgnZBz6Zx5dQBUzFzgckzY7z9CXWZqaqpYtGAG3r9+iKZNGiI9PR39B49jak3p6mjj8oWjUg3SB4B5/1vJWMMszKuhalXWJWigrweAV8riP75+g/wFPXMbGpc01YSUxsjKysKt6yVfyV9cunVtL5ZotrSoVuCcwqCkpMQU1wUAv+/st+yWLZow254PvZGRkQENIbXLcpMd5i5YwQi5XOxrWhRrfWlpGdi4gy0jkZKn5pssX6kIPV1NHNw6mykfEZ+QzLHExcYlYvbSg0x5CFNTUwwZMgTjx49H+/btYWDAtdpt2bIFVlZWTHkKRUVF7N+/v8JWsS8v8MeJPX1ZMdscAYBtDVMmnuvX7wicvnQfI6ZsEOgM0cDBBj06NRV2iXxxdrLHkL5svNeDx29x8sI9Zv+OBy/++PO3YNA0+zv/xKf8xuYVWohRFGUMYBWABzRNvxYxRx3AdvBE2HX+YzRN7wJgAKAGgMY0TQuNSKZp+g4AbwCrKIqSfvoYgaFunVqcmkRHDm7HTdcz8Pv0DIsXzoJGTkD11u37mQr6CgoKOH/moFB3X2mSkpIKr8c+zL5jPXv8/s0zaaupqaJ71w4AgD37jyEg8Aczj9+N6eTUQOx7TZg8Fw2atEfbjn3xxFuwzhQ/SkpKMDIyFBh/6eMjZHbpYGlhhkEDehU4z6KEf640TePPXzZGij8mrW6dWkzMWExsHOb9byUio6IFrtHAqR3MrBxxQUhv0PatxfsZiuLY2TtMLz1hsSlZfHGEMbEJGNCrNQ5uncX83YSE/uMIp7g4Xtq9jo4O3N3d4enpibS0NNy9exfh4eFYvXo1MzcjI4OTNLJ69WrUqMHNuiWUPjY2bKxhTEzF7aMoLy+H2nbsF5mZi/ZwjptU1cPk0d1x+fiKIltoO7Rh/z7vP3rDqdHXuS3rOXj1jm2Vl5xSfputF0qI5QTeuwLIBDBKxBw5AOfAc0kOpGlaoAMwTdMxNE0H0DRdUNTzIvAE28hCrHE8RVGvKYp6LezDmVB89PV0OVYk46pV0LplM07WW3JyCnbvPcLsr121kNP0W1r8DAnlPMRcb9xltqdNHgN1dTX8Df+HDZt2Cj1fV0eb4xrLj/+27cXps5fx9et3+Dx/jQmT5wp1V/HD30sxl4LOKSwP79/HlOn/w/6DJ8S69uSJQv/UGdTUVKGnq1NSywPAqyuWK5C1NDU4iR0URWH8WDZV/dCR00I7EwAQKtBaNK2DOjUFy5eIC03T2HGQbe5dUHsWNVVeba5+PVph2jhW1BrmaZZsamqKEydOYPHixejduzfMzc1x+fJlREZGYvjw4VDiq6EGAI0bN8alS5cwb968Ir8WQslRmSySjnVY4Z+R8/tvYWaEz0+P4vPTY1i/dBy0NYveYcPZie3m8PV7MJOVbGZqiNP7F2H88K4AAEN99m+oScOaRb6ftBFbiFEUpQTADTx3YgeapkOFzJEBcAJAWwA9aZr+UJzF0TT9BIA7gGUURYlVqIam6YM0TTegabpBST8cCDxOn72M0FC2dYswl9rjJz6IieV9yzc3M5VIf8aioKjIjeXJzOR9T2jYwAEL5vHqNF285CY0kF9bSxPXr5yAoYG+wLG8ZGVlYfe+o5yxnyGhePU6/zYcZkKq6SsolFyNpqCAAIwZNATHT57HnPnLcemKW4Hn2Ne2Q49uooutmlUzLfGHUBSfgKpSxUCgptrsGRM5Af25aGioY9/uTYxlMy+mVfWxb/PMYq038Mdv/P7LM+SrqigVMJt3z1wmjOjKbP8Nj8aLFy9w6NAheHl5YcGCBRgyZAiuX78OgOcC79evH169eoVq1arhwYMHmD59OmbNmoXHjx/Dx8cHffv2LfLrIEiOvMksFY0WTeugXav6kMuxeFW3MIbr6dUwqVrwZ6M4aGmowaQqL0wkM5O11/Ts7AyKorBuyRgM7dcWwwfyunt0aNMAqxeNLpF7SwOxhBhFUfIArgBoBKAzTdOinLH7wYvpGpiTFVkSLAZgAl6JDIKUCQkJ5QS6Dx7YmxEPX/38sfm/Pbh42RWv3vgyc9q1bVlqQcTXXG/DuVU3rFi9WaAwK8BrkyOMubMmI/jnL7zz/YSr128KHHesVwc+T27DsV4dsdaRkJCIhIREgfHXb97ne56wWKfadcW7pzhcOH2GEZ8AcOPmvXxms6xe+T+OeFm9kq0Bl7doaUlQo4Yl8zvj9y0Arm7cJt4yMjI4uHcLFv9vJmOdtbOzxmNPVwwf2h/nTh/AyOEDOecM7tMGT27vLPbD4j1fLEydWgXXTXNpyZbc+BbAVus3MzNDw4YN4ezsjMWLF2Pq1KlCsz+vXuVZ35o1a4YdO3Zg69ataN68eaWywJQHdHTYL/7Xbz/Nt/RCeaeKgQ7uP3qDzKwsaGmqwevGNpiZCIZVFIe6Qv62cmPO5OXlsGfTDCyYNhCBr0/j4pHl0NEqv6VaxCnoKgPgDAAXAD1omhYa6EJR1H8AxgIYRdP09ZJaIE3Tb8ETgYsAiO5CTCgVtu86iJSc5qy2NtWxbQsvduXmrXto3pongEaNnYFDR04x55Rmc++Vq7fgne9HbP5vD+rWb40/eYK0VYS0cAGAAUPGw6FBGzi36opXr305xxQUFHD5QuH6TGppacLK0lxgfNN/e3D7zgOOSzAjIwMJCYnIzs7G5y+CxT6bNm8u9n0L4u/v35x9t5t3ObFworC0MOOIxPp8gjRvBmVJYGigz3EBT5+9mLGw5qKgoIBF/5uJb5+e4ZPvY7zwvsN0TIiIjML5i9eYuQf+m4V9W2Zx3CXxCclISi58o+HQMDaLlV/UCkNVRYmxgj15/hGL17Lu+h49euD+/fuoV68ep3+jtbU1+vXrx+yfP3+eCeQnlF2aNWsGNVXeF72//6IxdOK6Eg8rKCs41LZiMoVj4xKRkChYYb+4zJ8+EOpqylg6dxi0tdQxdmhn1K9rzZkjLy/HaSBeXhHHIrYHQD8AWwAkURTlxPfPBAAoiloAYDaAYwD888wpWqltLkvBKxjrUALXIhSR8H8ROHGKLSy5cf0yqKmpIjT0N0aNm8EINIBb9iC3mn5pkJuhCfAq4i9fuZFzPDml8KLQwtxULHdkXtq5CPZhi4iIRL9BY9Gt1zCEhIRi4+ZdMDSphSqmtaGuY4lnPq8483W0tWBbq+RiH2rX4VrXMjMzmd6f+REW9gdxOYJLS1MDtnwtmYQJscdPfLByzRaEhf0p8lrXr1nMWLsiI6Nw/OR5ofNkZGRgYV6NY3V98+Y90wLJ3s4CA3q15pxz9eYT1Go2CmYOg/D6nehK98II/c0KsR8/869dNGFkNxgb6eHgiZvoOmgRvnz7yRzr3r07hg8fjtRU3t+NnJwcFi9ejNevX+PdO9aFnZiYCB8pJmwQCmb//v2oU6cOp27W2w/+nJ93RUJBQR4NHNi4TZ9X+VfBLwoOtavj3cODmDulP57c3I4tqyquU0wcIdYp5//FAHzy/BubZ85oIXOEVzAsBDRN+wE4VeBEgkTZu/8Y83BzqFsbLq15lpoVq7fka/UKDAoWsExJgne+nxAbx3Xt5G0T9IbPNWhna43mzZyEuk319NgaUyoqRStUOm/uFJFtex4+8oZdHWesWvsfU2NNGI0aOXIyVItL74EDoKrGdX+63nDHm7f5u0w/f2XFSs2aNpxWQ3HxCZxv/v4BQejeezg2bdmNdp36ITaPJUtctLQ0sWThbGZ/2/b9+PlTvEbccXzisIaVCceNFxUdh1HTNiE+IRkZGZl4IaRNS34E/WStipHRgq+N/xu6kXoSjh0+gPkrDzBjSkpK2LZtGzIyMpjq+QYGBnj9+jUiIyOhoaGBgAC2XIeWlhbs7Nhq5oSyxfHjxzFp0iSkpaUhOSWNUyfOL0C839fyiFMD9guiJIQYwGsODgCmxgYV2hUvTkFXc5qmKRH/VuTMaZXPnJHiLoam6eCccw4LOTYq51irQrw+QgkRFxePg4dZLTxv9hRQFIWwsD+cgO+brmegpakhcP4zvt6TkiApKRn9Bo0RGM/brPv4Sdail5aejidPnwvURGvRvAlOHNnF7ItyZxZEFUMDbPtvdcET88G8mvDq6kVFV08PbTsKBrK73/XM97z7972Y7Vo1baCoqMjUF8vIyOA04F6/aSeTmfozJBQzZi8u8nr79+0OQ0OeNTIqOgbTZonXVDwxkY3Py81azOXw6ducfRURcYPCyMrKwsu3fvnOsTRmReq8jbcxc+1N5OpUJycn+Pv7Y+bMmfj1i31IN2nSBJGRkThw4ADnWs7OzggICICxsfhucULp4e7ujjFjuJ87iYnsl9LfFThOjD9LsSI3Oi8NSu6rNqFCc/DIKcYFZV3DEt278R7mFy67MnEyzZs1Rq2aNoxVit+S8yM4RKLru+3+AH/+hAuMN3d2YrZDQ3/D/R4rOIKCgoVe69evMMZdBAAqqkUTYgDQr093uF07BesaRSuXkCiB2CAZGUEL4Ftf4fk3mZmZWL12Kw4cZhtOO9arA4qiODFjcTlB5n7fAnDxErcA7eWrN/E3vGgWUWVlJZw8yja09vB8ItbvUiJfzIq6GvvzS0vLwOFTXCEWnU/vx4jAx5x/j+9dYVLpRX0/nzKkCYR9ebezs8PNmzdhYsIrUfLgwQPmmKurKzZt2sSZr62tjStXrkBXt3gdAAiSIT09HZMnTxboPZvNZx3+/TcS2dnZCI+IQUZG/vGE5Q0LMyNmO/wfKRVVHIgQIxRISkoq9uw7xuzPmjGREVmPn7CxK4MH9cGVq2zGoaIiW3bB1ESy3+jd7z4UGNPR1uJkzp08fZH50OQ3c0+fOg57dm5g9qtVM+EE7OvrFe9B6NK6Od6+9IDPk9vo06tLoc598bJk4+vOHD+O65cuCYwL65SQmJiEfoPGYsPmncz7Vt+xLvr37Y7k5BRGcFMUhQw1I0RBAys27hEaoJyWWvhii79+hWHR0nVYsnw9Z1ycAOjYf6xrj98idsnNC/8iYzlzlbP/CQiu3H95efw6mF2HkPvWtTVCs/rmWDC+FWRl2N+xZs2a4e7duxxRFRvLXce9e2wG67x58/Ds2TOBqvqEsoOXlxfT3UBbWxszZ84UmLP3qBv0bXrDutFw1Go2mhNfWN4xyHEbAkB4ZEyFTUwoDYgQIxTIydMXmSB4Y2MjDOzfkznm58c+8DTU1bF0BSto+DPKHniwri1JQAt5LI4bM4xpTZSVlYXjfIkGuR8aDRs4YOWyedi6fT9zzKV1c467tWvn9sVeH0VRqGNfEyeP7cGp43uY7gMAmL5qwvAP+IEgvnih4uB25QoWzpwt9APTxLiqwNjUmQtx7/4jZr95s8a4cvEokpQMcPDcLUa8WVnXgIqqKr59/Yqb164LXKe+Y11UE1KoNj+eeD9Hs5ZdsWPXQY4obuHsJFZ3hnd8jYdNjQ2QlpaBtVtPY/rCXZx5etoq6NzKJu/pQsnMysZl9/zbqLg04eUmje3XEAGBQdi9ezd8fHzg7e3NaeIdHx/PiQPjZ8aMGdi0aRNsbQvXp49Qurx6xSbWDBgwAJMmTRI6L7fgb3hEDB49zT8WszzB/7mVlZVNhFgxIEKMkC8ZGRnYvpONW5kxdRwUFNiiqNExbHbk2ImzOJmT/BXsz124VmAx0+JQw0qwd6DbTXemMOv9B14CGXxycnLYvWMD7j/wQmCOm1JLUwMNGzgw+xoa6ujQvlWJrrV3zy546nWTqUaflZV/g4kHd9zzPS4OwUFBmDNlGrNfz8Gek5BQz6E2956ej3HpMitG582Zgts3zkFGzwJvXr7E6iVsDk7/IYMBAJ737gv9MO7SqW2hAm1PnbmErj2HIiqa23Dczs4amzYsL/D81AhfTvDwpp3n0WPoEmzadUHgvd67oidUlQUbduclO5vGun0PEfI7FgCgpiL8HJcmvP6YVi6bYG5ujilTpsDJyUlg3q1btxAUFCQw3qhRIwEXJaFswv/5pq6uDmtrtrSCqC9XlnzuvPLO7z9sIlRVQ90STSqqbJAejuUIFU3J9GlMjhOdYr1zz2GE/AoDwGvvk7dIpra2FpKSeDEz/CIsLzRNY9bcZfDyuC6R4q49e3TGmvXbOGNf/fwx738rsW/3JqGlD8aNGYratWxx7DjbvHnE8IG47c7WIu7Wpb1Aa5mSwNLCDFs2rcDIMdMLnHv/jjvGT5sKU03tAueKYva6DUjLiXuzsbHBosXLmFpV6urqGDlmGlTUWSvdVVf2Pejfvz82beHFaUX8+IHRAwYhNacMiIWFBRbOmgM1NTX06tQZ65evELj3idOX0bvfMNStW5cZy8rKwsGDB3HixAlERERg0aJFGDNmDB48eIDJ0xYwrlBDQ0Ps2LEDTk5OqFatmliCTk7ZCOkZrKs1JOwfQsKEx6jp1BoNKxeXfK8XFxeHYcOG4caNt8zY1OmzsWHDBs48CwsLdBp7VKw1amlpCYzZ2dnhxo0bnC86hLKLlRVbmSkoKIjjalZUkOf0PlRQkMPh7XPRtFGt0lyiRPnF52Y1zqmCTygaRMKWEyQlwkRdOzY2Dlu27cXyley382lTx0JVlVvKYeigvlBQUEB9x7qc8SpV2NiW3AfTO9+POHbiHCSBnW0NtG7lLDB+8vRFvH33AS9eveWMy8rKYsbUcQCAp3wZnS5tmuO66x1mX1gbnZKib+9uaNG8CWdMWUiG5qvnz6GSmb/VLD+CgoKY6uwAcPr0ady8ycbyjRw5Eurq3KrUUVHst90+fdjCqtOmTUNMjhVUX18fd+/ehVpOOYyGDRti7NixyMvPnz/h4OCAevXqYcKECVi4cCEaNmyIyZMn48WLFwgKCsLYsWPh4uKCzp07MyKsbt26ePXqFQYMGAAzMzOxrWoKCgo4f/48mjRpku88LS0tjhVDGF+/fkWjRo1w48YNZqxHjx6YNm2awNx169aJvcb27dtj3bp1aN26NVq2bIlt27bh48ePJCasHMHfaN3f3x/bt29n9nW1uZnjQ/q2RY9OzUpraaVC2B9WiJVUa6PKChFi5QBJirC896BpGidOXoBdHWcsX7mJcTU1buSImdPGC5y36H8z8MD9EiZNHMmMURSFc6f2M/0B+d1VK1ZtFqjtVVJMGj9C6PisuUvx7x83jbx1q2ZMpXz+bMtaNW047labGiVRj1g4FEWhhTPXbaWkJNhXMjs7G3fu3BEY9/Pzg7+/6LTxEydOoHbt2rCysmLETfv27VG/fn3O9YYOHSpwLn88U+49oqOjcevWLWbc1dWV8zACgC1btqB69epC1+Pr64uDBw9iw4YNnIKluXh6ejLuHlVVVVy9epWzjsLQq1cvPHv2DHfv3kXXrl3Rtm1bgVpcNWvWxKFDh/Dtm/CCrtevX0ejRo3w/ft3Zmzu3Lm4fPkyjIyM0KULL/FCWVkZe/bswcCBA4VeRxiysrJYuHAhPD098ejRI8ycObPU2oARSgb+3/MPHz5g8+bNzH5ENDcTt6a15D/DS5uw3+xnqrEREWLFgQixMk5piLBc4pIV0HfgGEyevoBTLd3Ozhonj+5m6kbxIysrizr2NbFpMxsEPWLYADRq6AhbG/aDKtdCFhMbx7GylSSiAsKF9Xd84PGYaZmTwFdzSkNdHQ3qOzD7N2/fL9lF5qF2LW5AtrBm4wCvaGRu8kNKSgoGDhwIOzs72NjY4OzZs0LPmTNnDj5//swZmzVrFhISEvDvH89Vp6SkhAYNGgicy+9GzA0q549psrOzE2px0tTUxJUrV4Ra9vKiqKgIS0vBsh7NmjWDl5eX0GOFpX379rhx4wbu378PNzc3jth59uwZVq9eDVtbWzg7O+Pw4cP4+PEj3r17h8mTJ6NXr15MPTJlZWWcPXsWmzdvhpycHCiKgpubG16+fImfP39i8uTJxV4roXyhoaHBiYtKTuaFaBgaGjLlb6pW0cWRnfMwbnjhsqXLA6F8NdJMjIhrsjiQGLEyTGmJsIyMDKxcuRK7d+9GXBxbKdzK0hxTJ4/BqBEDhYqwXC5duYHv/ryHtIaGOpYtmQOAV33/02de8ctOHVwYt+SJUxcweeIo1K5liyfez7FwyVpkZGRg4IBemDF1XJGCPj0feaNbT9ayIysrC+OqVZj4NmGYmNdF0yYNmcr2srKyUFZWQluXFvB6/AwA4PX4GSZPHFXo9YiLfW1u+yL+AGB+PDw80KxZM6xYsQJ79+5lXIs0TWPLli0YPHiwwDn87kUAqFWrFjp06ICfP9mYQD09PaHvd26tKwAIC+O9h/wxMGp5qvPzU6dOHZw+fRr9+/fnlMWoU6cO+vTpg9TUVOjp6WHIkCEwMDDA0aNH4eXlBQsLC/Tr1w+1a9cWee3iUL16dTx69AgLFizAs2fPOMeePn2Kp0+fCj3P3Nwc169f54hTgFcnr2HDhhJZK6Hs8+XLF4EaYgC3E8fa9VvQykERD719ER0Tj+iYBETHJkBWVgajBnUs130S+V2TxkSIFQsixMoopWkJW7JkiUCm1qQJI7Fq+QKoqBRs2TjJVxZi5rTxTF9Gh7q1cfrsZQBAWloa2rq0wAMPXm2mM+euYP2axdi4ZTfe5RQTXbJsPcJC/2DzxuWFbmexcvVmzn49h9qcfpe5UBTFcZXy93ZUV1MFRVFQ4qt/pqNT9AB5cahWzRjq6mpISEgscO7Lly/RuXNngfGQkBDQNC3wnmloaCA+nm35tHv3blAUxcR4AYCOjo7Qe/E/YHK369Wrx7x/b968QUxMDLS1hb8/vXv3xoULFzBw4EDGkvfhwwdoa2vj/v37HGE/ZswYgerkksLZ2Rne3t4IDAzE69evcfHiRdy4cUNk8+4uXbrgxIkTpKgqQQBh7nWA+7czYcIEZGZmChVsvp8CcWa/eJ0iyiL8NdFMjIlrsjgQ12QZpDRFGE3TOHHiBLNvaGgIDw8P7N1/TCwRFvTjJ548fQGAZ1EaPmwAc8yhLmvZ8P3wmdOf8N27DwAAeXnud4F9B4/jyLEzhXoNMbFxePuOre/Ur293tGjehKnAzi9QaJpGFUPhHxq5ouvbd7a+k61NDaFzhUHTNAKDgsUSVbnIyMgIuCcLS1RUFF6+FGwhxR/DcuDAAbRq1QoAOEJMlJD68OEDs21jw6uzpaury1iAsrOz4eHhIfTcXPr06YM7d+6gDl+jcS8vL7i7F78cR3GgKArVq1fHwIEDcfXqVYSGhmLLli3o3LkzLC0tYWVlhd69e+PSpUu4ceMGEWEEoQgTYnJychzRlZ6eLlSEAcCfv5KJlS0twohrssQgQqyMUZoiLCsrCxMmTGAaDwPAt2/f0KZNG7HXcvrMZWa7XduWMOLLlrSvbceIoG/fAvDxE9tcuW6OSDMxFqyrs2b9dqYkhjjs3nOE+bBzrFcH69csweGjrJibN2cKZ/7fcMHq1ioqypg1YwIA4OtXNgDe1lZ44HleaJpG34FjUMexFcxr1C9UzbSiCLGWLVtyshmPHTsmMMeFrywDf6wYvytSWN2vlJQU7Nu3j9mvX78+s92+PVvc1tOT1y4qIyMDmzZtQpcuXWBmZgZ1dXXUq1ePyVycP38+5/plrW+ioaEh5syZg1u3biEwMBABAQG4cuUK+vbtW6EbDROKhzAh1rZtW7EzX11a1CvpJZUacfFJSMjpqamkqAAdbcH+wgTxIUKsDFGaIiwqKgp9+vTBoUOHmLGxY8dCU5Mbs5DfmrKysnD6HCvEhg/pzzmupqaKajmZiVlZWZwCovr6vO3GjeojLxERkbj34JFYryM2Ng7bd7EFZ8eNGYoDh04wyQbVrSwwb/YUKCpyazPljXlbu2ohRo8cDJqm8dWPzZKzE9Mi9iM4hGmcnZqahm07DhRwBgt/ckBejIyMMH36dGhosB90jo6OePjwIWbMmMGMnT9/HikpKZxz+YXYw4dsCyj+n3HeODKapjF27FgmLszQ0JCTDcgfOxYRwRO0W7ZswYIFC3D79m2EhIQgMTERvr6+GDRoEDQ0NDhZmd27d4ejo6PI10sglAeys7Ph6+srMO7u7o43b8RrSxYcItgbt7zAbw0zNtIjX1iKCRFiZYTSEmE0TePChQuws7ODqyvbnHn48OHYu3dvodbm+cibqVavp6uDTh3bCMzJ4Iu96dypHbPtkRMr1rlTW6Fp+2/eitcK5In3c6Tm9DG0s7PGkEF9cOHideZ4bpzbts2r0cSpAbp37YA1qxbi+xcfbNm4gpn3+MlzAEBEZBSiY2IBAKqqKjAxEWz9I4zXb3w5+3fvP0R6erpY53bu1FZkMsSfP3/g5eUFNze2yv3nz5+RkZEBZ2dnxv0YFxeHa9eucc6tVq0as82fhGFqasp8cH7+/Jn5Zp+YmIj+/ftzsjBXr17NCT7m59GjR0hMTBQIfOeH3y1TrVo17NixQ+RcAqG8EBQUhIQE0c3ixUFHW73gSWUUEh9WshAhVgYoLRH2+PFjtG/fHgMHDmSsGQCvzMGxY8fyzYwUtsZTpy8y2wMH9BJaETwujg0W11BnM+1yXWI62lpwbtZY4LzQsD9IT08vsH+Z73vW5dahXWtERccwmZKKigro2KE1AGDE8AF44H4Z504fwKzpE2Cgr8ep2ZXboNzPj3VL2lhXFzuD8/ARblxbamoafoX+FutcE/O66NChg8jj79+/Z+K7AF7iQ1BQECiKwsiRI5nxvO7JT58+Mdu5cV4AL1OS31rWpUsXPHjwAE2bNsXly6yFc+LEiQIFWrt27cpY5yIjIzFz5kx07NiRMyc4OBjz58/nZD9OmDABHz9+hLm5ucjXSSCUF/i/2BSFtm3bYvFswfp95YVQ/mKuJD6s2BAhJmUkLcJomoa7uzuaN2+Oli1b4sGDB8wxY2Nj3LhxA1u2bBFLcPCvNSo6BjdusTW2hg/tLzA/MzOTifWSkZHBpcusBc7FpQWz3aNbR4FzL112g7aBNfoNHMspgZCXGL6SCsZVq0BHW4sRlGlp6UhPF14OAuBmTNaozutV6feNDdS3sxXPLen7/hOnOn8uP0NCCzw39z0dMmSIWPcCeO7BXEEzfPhwxrrl4eGBkJAQZt7+/Wwj83r1uPEomzZtYkpQ/PnzB+3atcPHj2zCw9SpU7Fr1y4Bl4OxsTH27NnD7B85ckTAohkTE4ONGzfi48ePiIqKwu/fv7F//36Oe5VAKM/Y29tzLM65zJ49O98vtACwc+dO3Lp1Cyb2/fHY5wPWbz+L8AjBDO+yTApf+yY11YKTugj5Q4SYFJGkCMvOzsbVq1fRsGFDdOrUCd7e3swxGRkZTJw4EV++fEHXrl0Ldd3cNV+85Mq43uo71kWtmjYCc/lreCkpKjLZlTIyMujVgy3D0K1Le4Fzc7lz1wOXr/JqZoWEhOL2nQcICPzBHM+t3g8AScnJkJOTQ3Urc2bs8xdu1XSPh09gZ98MqlrmOHuebfvTrm1LAIDfN/5AffGE2Hk+Vyg/IQUIMf6ff79+/QQsS7nktTQeP36c6X9pamqKdu14Ll+apnHmDM8y9/TpUyaYXlZWFhMmTOBco169erh586ZAH00FBQUcPXoUu3bt4ry3/AwZMoQTNzZp0iTOcf46ZTo6OjAyqjiNjgkEgPd3smXLFoHxfv36iawFmMvSpUsxcuRIhISEoNvgxdiw4xz6jV5ZoPW/LKGpwXo34hPET6wiCIcIMSkhSRHm6ekJe3t79OnThxM4Ki8vjzFjxsDPzw/79u0rsoVCRdMMT7yfMwHwA/r14BynaRoXLrmiZRt2PC2d/QY1dfIYVLeyYParVq2CBvW5xTL5mf+/lRg2cgrs6jij36CxaNK8M4KDfwFgLVkAcPceLyDdsR5bLuGa623OtfbtPy5Q5NXczJQ55yufa7KgQP1DR06hz4DR2H+QLf9RozpbDT4kRHQx2bw/f1lZWVy7do0jjHOtUenp6XBwcMC0adPg5ubGcSvSNI0fP1hhmmsR27lzJzM2YMAAoVXqW7ZsiWvXrjF9Jm1sbODl5YVRo/IvYEtRFPbt2yfUzejo6Jivm5VAqCj069cPL168YPbl5eVx+zb380ZYi664uDicO3cOTk5se7P3nwI5AfBlHQ11Nm40Ll54NxCC+BAhJgUkJcJSU1Mxe/ZsuLi44MuXL8y4kpISpk2bhsDAQBw+fFigP2BhSUhIwK07D5iK9L17ca1qh46cxuhxM5igdwDIyuIFbRsZGWLJwlkC1+zWVfTDOzIqGlevsz0Ok5NT8C8nxq1TBxfGFeDz/DWeeD/HgP49mbkXLrlyinWq5jGjy8nJYc/OjYzoiY1lYz+0tbVErsk/IAiz5i6D+11Pzjdg/tprolyTon7+SkpKuHLlCiwseOKSv0irr68v2rVrh27dunHOuXr1KqffpLMzr/H5nz9/mLGzZ89yEjP46dixI8LDwxEZGYmvX79yHg75oaWlhWfPnnEq+jdp0gQeHh4CVjYCoaLCbzW2tLTEwYMHOccvXrzIqaPHD//fKIBylXmoqaHKbMcnECFWXIgQK2UkJcJ8fX3RoEEDbNu2jRlTV1fHggULEBwcjJ07dxa5gXJeXrx4wYib2rVsObXDAODZczb2ytBQHy5tmjP7E8ePgKqqYBZe93yEWF50tLVQz8EeAGBiUhVDBrH1tHbsOoRWLZrCyMgQAK8UxgPPJ8xxY2NuFuS1y8fRqmVTZp/fUpc3E5KfG7fuCXUlvP/AJg/8DPklcLygn7+CggL+97//Mfv8ombRokUC8XL8MX9OTk4YNGgQAG7pCoDXBJu/RRE/ysrK0NXVLfSDwMjICGfOnMG7d+9w6dIlPHz4EFpaWoW6BoFQnuH/ff/16xfHDf+///0PTk5OHOt0/hcTTFoqq/ALMWIRKz5EiJUiRRVhNE0jMDAQ165dw+HDh7Fv3z6cOnUK165dw/Xr1zFjxgw0atSIU7SzU6dO+P79OzZs2ABDQ8OSegkAwHGF1XMU7LXXoV1rZpuiKJjxNeNWEdEM2rqGlcCYsrJwy0qvnp05AbEzp49ntr2ePANN0xjIZxU7d/4Ks23KV45i9MhBaNPKmXNt/gzOXXuPIC0tjXM8ISERcxeswNLlG4SujZ83bz/gxcs3jHgS9+c/YsQIJpA+JSWFaaD96dMnnDt3jjM3MpJ1ZwwYMAAyMjKIj48XiCvT09MTmtVaEjg4OKBv375M5imBUFmwtLSErS2vIHNycjI6duyIbt26Yf/+/Vi/fj0AXghAXku2MBYvXgwN88LF7EoL/hgxIsSKDxFipURhRVhoaChOnTqFUaNGwdzcHNWrV0fv3r0xbtw4TJ48GcOHD0fv3r3Rq1cv7Ny5k3GPKSsrY9++fbh16xaqVKkiiZfCqSvl6emJsH/pCA39jZgct16fXl1gYMBLaf779x8nqy63mXZByMjIYMHcaUKP5e3/aMJn5UpJSUVmZiZHqD32fs43l/3GGhrGdQ0AwLAh/aCvz1t7aOhvpldmLrPmLsO+A8cFztPQEKwJlJ6ejjbt+8DAuCaateqJJUuWICmp4A8tRUVFODg4MPt9+/ZltpctW8ZxtTZvzlob58yZg7p168LIyAiLFrE97BQUFHD58mWR9cAIBELR6dWrF7P9588fuLm5CSTHbNiwocDM9Nwkl/IgxohFrGQhQqwUEEeE/fv3DxcvXsTEiRNhbW0NU1NTDB8+HMePH+eUJMiPhg0bwtfXFxMnTpRovIGLiwvjMgsLC4O1tTVsajeFiXldtGrbE3v2H+P0W7Tic/fd9/BCZFS0wDX5640BvKr8ogqiZmRwGzTfvH2P2bauYQklJSWmuTjAtdDxF2gVJsRUVJQ5FrbN/+1l1pGdnY3rbrcFzlFWVsK5U9xK+vziMzU1Db6+vli7di3q1q2LJ0+ecObSNI3Vq1ejffv2THFV/v6Gbdu2hY6ODlq0aIHTp09z4lIGDBgAfX19Zn0fPnxAcjKbxWRnZ4enT5+iRQu2XAiBQCg5+IWYqAbyNWvWxIgRI/K9TmpqKrNd1sWYhhr7pS4+MVlkP02CeBAhJmFEibDY2Fi4ublh5syZqFOnDgwNDTFgwAAcOHCAE3ydi5qaGtq1a4eRI0di/PjxGDJkCHr06IH27dtjxowZuHXrFp49ewZra2tJvyRUqVIFCxYsEHrs1WtfLFm2Hikp7IdKy+ZNmJiutLR07N13DMnJ3HY8h46e5uyrqalyrFH8mZC5QiM9PR3XXe9g2kzW+tO5U1skJSXjnS+vJpaMjAzWruYdP3HqIpxbsS6ChHjhzbnHjR7KtGP6FRqGM+d4rs2MjAzO62LeD0MDTJnOvh+WFma4fuUE2rq0ELBKBgYGomXLlpg5cyZjHduzZw+WLVuG+/fvo2/fvqBpmtP/Mzs7G+/evcOjR4/QtGlTzvUMDQ3x8OFDpoRFLrVq1cKuXbvw9u1bNGjQQOjrJBAIxad+/fpM/9To6Gg8fvxY6Lzhw4cz2yoqKgJfjlq3bs3ZL8tiTE5OlqkfRtM003eSUDSo8lS7pLD8v737jo+qSv84/nlS6L1KESJEV0E6q2DBAohd7HUFbKjrT13FXsCyUsSylrWBIsrqriiKBRUpIgoiIqiIIkjvkNAhGHJ+f9zJMJlMkpmQzM2E7/v1mlfm3jn33mcehsmTe889p2OHtm761A99O354EbZr1y7GjRvHyJEjmTp1aqF/RVSqVIljjz2Wk08+mZNPPplOnToVOVBgPDnneOmllxgxYgTr1q3DOcfatWvzdSY/56xT+c8bL/LuuI+4st9NeV7rdcpJjHz5aWrXqknnLj3zDB0Rqm6d2jw5/GH6XOVdqjzs0BZc1fcyhgx7hs0hZ9IaNKjHD7MmsWHjJtp39qZbSmt+MPPneWegWrc7nqXL9nWg737y8Yx/742Ix3zyXy8G+4E1b9aUed9PITU1lSPaHJtv+Itwzz79GFf1vSz475+RkcG4ceO4/fbb84zI3aBBA/r3788jjzySZ/saNWqwdeu+9/X9999HNT/jwoUL2bx5M02aNKFx48YJdReWSCK76aabggMd33PPPTz22GP52uzYsYOaNWsGvyOvuOIK3nxz3x+g3333XcQ/mrYu/aiUot4/rY7pFxxy46evRtKsaXSTncdqw+Jp1G8Z3Rn9moec9b1zLuH+8lQhRumPbv/DDz8wcuRIxowZU+CdaykpKXTp0oWTTz6Zk046iS5duiTcMACbNm1i/PjxfP7556xfv55u3bpx5513UrlyZfbu3Uvr1q357be8A6x26NCBmTNn0qRJkzwdz0P985//5NZbb6VevXr5JrbOVb16dcaOHcspp5zCZ599FhwctX379sHLfdWqVcvTR+uuu+5iyJDIne63b9/OQQcdFGw/efJkTjrpJK655hpGjhxZaB4aN27M1VdfzYABA/KM1bZy5Uquu+46JkyYUOj2oY488kh+/PFHFVUiZdjo0aODlx4vvvhi3n777YjtOnfuHBzb8cgjjwxOQ9a7d+98c8XmKquFWNdTb+KX37x+bdM/foY2rQ4pYovYbVjsnV0s74XYAX9psrSKsMzMTJ5//nkuv/xyOnbsyPPPP5+nCDMzOnfuzJ133smnn35KZmYmX331FQ899BAnnnhiwhVh4PVr6tevH2+99RaTJk1i4MCBwTv+kpOT83Qgz/XDDz8wfvz4Ai+fXXHFFdxxxx1UqVIl3+U38AZMvPvuu1m8eDGnnHIKCxcuzNMXo3Xr1sHnoZ3VmzRpwt///vcC38vPP/8cLMKSk5ODY6/ddtttefpo3XbbbfnuRly9ejWPPPIIzZs3Z/To0cFhLpo2bcrHH3/MqFGjChxKJLdDb2pqKldccQXjx49XESZSxoUObhx6V3m40P/LoTNQFDTWWFlWs3poh/3I3Tz2R24RFv68PIo8h8kBoqSLsJycHCZPnsyrr77Ke++9R1ZWFg0bNsTMgr+MW7RowVVXXUXfvn2D/QoOFH/7299YunQpv/76KytWrAhOu/Tqq68ydOhQZs6cmadY/fDDDznjjDOCX14PPfQQ8+fPZ/HixVSrVo2///3vPPzww3kKoSuvvDJP/6ovv/ySXr16MWLEiDyxzJkzhwYNCj6V/vjjjwefX3bZZTRt6g3B0apVK7p3785nn30GeEVXbmf+evXqkZycTKVKlVi2bBmbN2+mT58+ZGZmcssttwDeF3GfPn245JJLeO2115g2bRp169blqKOO4tJLLyUzM5MVK1bQvHnzPB32RaTsyh2EGQouxJxz/PHHH8Hlbdu2Ad4fX9EMb1HW1KgR0mG/hKc5ilR4xXKJMtEcsIVYNEVYTk4Oy5YtIzs7m507dzJ27Fjmzp3LoYceSteuXWnbti1Lly7lxx9/5Mcff2TatGn57nBct24dxxxzDGlpaVxzzTWccMIJUU2wXR6ZGQ8++CDgdVpPT08HYMKECTzzzDO0bNkyeNq+YcOG+ebBbN++PYsWLQoO1RHeZ27JkiV5phxp3rw5y5YtY+XKlZx88slsCIzGH40FCxYEn8+YMYMhQ4bQrFkzFixYECzCgDx3KPbq1YtXXnmF0aNHM3To0OAX8p133snZZ5+d58u6YsWKXH/99Vx//fV5jlu/fv3gXZAikhjq1KkTfJ5bYIVbtGgRGRn57xi///77E/KGmprVNZZYSTkgC7GiirANGzYwfPhwRowYEfE/DpBnBPuCdOrUiauuuopLLrkkz39U8c4MhnZKD592KfSSYriCblr4+ON90yCdfvrpeeZ9W7RoUfB57dq1izzbNHDgQC677DJycnJYtGgR99xzT742ycnJ9O7dm/HjxwPeyNqVK1emf//+XHbZZRx99NEsWLCAPXv28MknnxR6KVREElfoTUqhXRdCzZgxI9+6QYMGBf84TTR5xxIruUuThV2GLK9nxQ64UzOFFWEbNmzgrrvuIi0tjWHDhhVYhBWmTp063HLLLcydO5fZs2dz4403qgiLwMwKnNewZ8+ejBo1KuZ9hv57HXzwwQV+Id5www15xvmK5OKLL+bdd98tsK9ebv+v0KmEfvrpJ5xzOOeoUKECl1xySfC10EsSIlK+hM7lWtAZ7ZkzZ+ZZbtKkCQMHDkzYPqB5CrESmm8ymr5g5bG/2AF1RqygImzDhg088cQTPPfcc/lGPq9Xrx61atUiKSmJww47jA4dOpCdnc2MGTP47bffSEtLo23btsHHX//6V031EqXXXnuNf/zjH8yYMQMzo0WLFvTt25crr7yyWF9OoWNsvfrqq/kGVuzevTs9e/YM9tcqSu/evVmwYAHvv/8+y5cvZ/ny5ZgZF198Mb179yYlJQXnXPDMXmZmJp06dWLdunWsXr06z75KepopESkbli5dyk037RuaJ7xLRa7Qs/LgnUVzziVsIVYjpLP+1q3730esPBZY0TpgCrFIRdjGjRsZPnx4xAKsbdu2DBw4kN69ex+wfbpKW+PGjfnvf/9bYvs77rjjqFOnDhkZGcF+ZLmSk5MZN24c1avnn4qoMGlpadx6660Fvp579+vkyZMBgkNlhDvvvPNiOq6IJIYXX3wx2MWiadOmPPTQQ/z+++8sWbKEqlWrcsQRR1CrVq18Q/esXbuW2bNn89e/5p+vNxGEnhHbvJ9nxGItwsrbJcpyXWFk411+Ci/CnHOMGjWK9PR0hg4dmqcIa9OmDe+++y4//PAD5513noqwBFKpUiUmTpyYb/T5Xr16MXHixJiLsGg98cQTBX6Z1q1bl8GDBwdvTBCR8mX79n39o7p06UKvXr047LDD6NWrF8cddxx169YlOTk5eCNXaLeIvn37RpwSKRGUVh+xaJWnM2jl/oxYeBG2atUqrrvuujwducErwAYOHMi5556r4iuBdezYkenTp/Pdd9+RkZHBMccck2dQ1dLQvn17Zs2axcKFC5k2bRqNGjWiZ8+eZGVlUa1atYS99CAiRTvttNOCo+qPHTu2iNZQuXLlYPH2yy+/cNFFF/Hee++VaoyloaQm/i5PBVVxletCrELIXx7OOUaPHs0tt9ySZ5qZli1bMnToUBVg5YiZcdRRR8X9uIcddlieuT7DB3oVkfKnW7dupKSkRDyz1bhxYzIyMti9ezcpKSlUqVIlz/RlAOPGjWPNmjU0atQoXiGXiFo19w1fkZkZeciOouxvEVZeLlEeEJWHc47777+fvn375inCbr75ZubNm8f555+vIkxERGJWvXp1brjhhnzrk5KSWLBgATt27GDPnj08+eST+YowM6NXr16lfjNPTk4OGZlbi24Ygwb1agWfr9uQGfP2JXUmrDycUTsgqo+BAwfmmYS1RYsWfPnll/zrX/+iatWqhWwpIiJSuOHDh3PjjTcG+381btyYt99+mxo1ajB//nzS09O5+eabg+0HDRqEc46cnBw+/fTTUjsRsGt3FoOGvc43s+aT/te/ceZl9/HKGx+zZ8+fRW9chIb1awe7XWzYtIUdO3dHvW15KJ5KUrme9Ltz587urLPOYtCgQcF1Z555Jm+//bYKMBERKVFbtmxhw4YNpKWlBccxvOOOOxg+fHiwTaNGjViyZEnUwxwVd9LvvXv3cuWNQ/jo85k0rF87z1mrk45rz9jXBpGSUvh4ikU5+pQb+fX3FQB8+r8hdP1rwQNx5yqtIqx+y26a9LssWrNmTZ4i7PTTT2fs2LEqwkREpMTVrFmT9PT0PINJh/f9uvnmm0t9rEnnHHcOepmPPvcGkQ2/dDhl+lwee2rMfh+nU7t9fWK/n/f7fu9vfyTyWbZyXYiFDqp56qmn8u6772qwVRERiZvjjz8+z3L//v1L/Biz5vzKoGGv8/SLY7nyxiEcf8YtjHhz38gAN13Tm9++fZ3+ffYNNvvS6x/x55/7N3RGxzyF2MIi2ydysVSaynUhluuUU05h3LhxBU5XIyIiUho6d+7M4YcfHly+8sorycyMvXN7Qeb8+DunXXw3T70wlknTfuCDCV/z04Il1Krh3dV4/lndeOSefhzUoA5DHryWgxp4U+5t37GLeT8v3q9jh54Rmzn7F3JycgpsqyKsYOW+EOvRowfvv/++ijAREYk7M+OBBx4ILn/00UccddRR+aZBK8iGxdMKLGKcc9zzyCtkZ3uTjq9aszH42qC7+tD30l688PitwZsBkpKSOLrTEcE2i5asivn9hDry8DTq1PYGyl69dhMzvvulwPcgBSvX44hVr16dDz74gMqVK/sdioiIHKAuvfRSPvvsM0aPHg14805eeumlTJ06NeoBnyMVM4sz6zFz9oLg8nlnHkerv6Sxd+9euv61Nf0uOzXfNumHNA4+/3Tyd1xy3smxvp2g1NQUep9+HK+OmQDA/z6YyrFHH1lk3JJXuT4jlp6eTpUqVfwOQ0REDmBmxqhRo3j11VeDQ1xMmzZtv+fa/e9/3wk+v+DUNvTv3Zzjj3BceM6JNG1cP+I255x+bPD5uI+n84/7/82cH38n0ggKu7P2sGXrDnZn7SkwhovOOSH4/P1Pvs4zNIaKsOiU6zNiGqRVRETKAjOjX79+/Pzzzzz55JMADBgwgLPOOqtYd/I75/h8+r47FU/r9pfg80gFUO4I9O1at+TEY9sz9eu5ALw6ZgKvjplAndrVadywLg3q16ZypQqsWL2BX35bRv8+Z/LS6x9x5BGH8LeLenLNFafn2e/RnY6gWZMGLF+1ns1btjNx6veccUqXmN/PgUyVioiISJwMHDgwOJL+qlWrGDx4cKHtW3YfFnH93AVrWLnWmymmWpUKdO3QrND95PY127B4Gk/ecTzHhLXPyNzGz78uZfJXP7BoyWp+nP8H2dl7mTH7F7Kz9zL3p0Xc/sALzPhufp7tkpKSOP/sfdMMvTP+y+DxJDoqxEREROKkRo0aDBkyJLj8+OOPs3hx4XcvhhdjO3ft4e7hnwaXT+7akgqp0Q/OWqNaJV4fdhGvDbmAc3u2pka1vMM6pTU7KPh806a8UyMNf/5/+fZ30TknBp9P+GIWW7ftjDoWOQBG1p89e7bfYYiIiATl5OTQtWtXZs2aBcA555zD+++/X+R2iyfdCcDdj09g7Gc/A1C5Uirv//tvtGxWt9jxZO/NYUPGDjZm7GBj5g5qVq9EpXqtaHdkS2rVqMavvy+n66n/FxyeYsoHT9Kx7aF59nHsaf/Hz78uBWDYnadx3ilHhh+m1KX3eFwj64uIiEjhkpKSePbZZ4PLH3zwAZ9//nmR27XsPoyPp/waLMIABt7Ufb+KMICU5CQa1a9Om78cxEldWtKxdRNaNdzCnxvmsGHxNOomLeW8M48Ltn/qhbH59nFhyFmxDyZFHsZCIlMhJiIiEmdHHXUU/fr1Cy7fcsst/Pln0ZNxv/bxiuDzc3q04vxe8Tnz1OeMQ4LPp07/Pt9dlheE9BObNW8FfwbGNpOiqRATERHxweDBg6lRowYAv/76K6+//nqh7VevXs3cuXMBSE1JYuBN3aMeh2x/Hd6iPjWrewOjb92exQ9ff5hnsNmmjetTpbLX1+zP7ByWrCy52QPKOxViIiIiPmjYsCF33313cHn8+PGFtg8djb/1kW2pUS1+M8aYGa3SGwSXf1m0Pvh8w+JpfDxuDDt3ZQXXVatcIW6xJToVYiIiIj654IILgs+nT59eaNvQy4HOuQKHtigtoYXY7J9X7nv+00quve/d4HL3ruk0blgjrrElMhViIiIiPmnZsmVw8PHMzEz27Cl4FPvmzZsHn//+++/k5OTEtRg7psO+43/wxS8sWLyeoS9P5YoB/2XHLq9/W51aVbjvhpPiFlN5oEJMRETEJ0lJSdSsWTO4vGXLlgLbNmjQgAYNvLNSO3fu5I8//gAKHvS1pB3TsTm1a3pzN2ds2cVZ/V/nlf99R/Zeb1iLerWrMOaJi2nWuFZc4ikvVIiJiIj4JCsri82bNwNeUVarVq1C27dt2zb4/Keffgo+j0cxlpqSzD39TwTg2I7N87z217ZN+e+/LuPQ5vVKPY7yplzPNSkiIlKWLVu2LNj3q2nTpqSmphbaPveMGMC2bdvyvNay+7DgoK+l5bxTjqR541ps27GHP1Zk0KhBdS49sz29e7SK2x2c5Y0KMREREZ8sWbIk+PyQQw4ppKVn06ZNwee1a9fO93o8irFORzYF4Ku3ri/V4xwodGlSRETEJ7EWYqGXI9PT0yO2iffdlLJ/VIiJiIj4JJZCbMOGDcGxxCpXrsxhhx1WYFsVY4lDhZiIiIhPduzYEXweevdkJN99913weZs2bUhOTi60vYqxxKBCTERExCeh/bxWrlxZSEuCw1UANGrUKKr9qxgr+1SIiYiI+OTII/dN2j169Gg2btxYYNvQoSu++eYbdu7cGdUxVIyVbSrEREREfNK7d28aNmwIwPr16znjjDPyXK4Mdeyxx9KkSRPA6y/Wv39/srOzozqOirGyS4WYiIiITypWrMgLL7wQHINr1qxZXHjhhfz555/52iYnJ/Pggw8Gl998803OPvvsAgu3cCrGyiYVYiIiIj4699xzee6554LLEyZM4OqrryYnJydf22uuuYY+ffrkaXvvvfdGfSwVY2WPCjERERGf3XjjjTzwwAPB5TfeeIP7778/X7ukpCRee+017rrrruC6V155hYyMjKiPpWKsbFEhJiIiUgY89NBDXHvttcHlwYMHM2nSpHztzIzBgwfTrl07AHbt2sXQoUPjFqeULBViIiIiZYCZ8e9//5tevXoF1/Xv3589e/ZEbNu/f//g8rBhw7jpppsitpWyTYWYiIhIGZGSksKoUaOC44stXryYF154IWLbK6+8MnhWDOD555+nS5cuLF68OC6xSslQISYiIlKGHHTQQXn6iz388MOsXbs2X7uqVavy1Vdfcf755wfX/fDDD5x44ols3749LrHK/iuyEDOzC8zsXTNbZma7zOw3MxtsZtVD2lQ3s+FmNtXMtpqZM7MTC9jfiWb2a6DdS2ZWIeS1tMC2zsxOjrDtdDObWqx3KiIikiBuvPFGWrRoAUBGRgbnnXceGzZsyNeuevXqvPPOOwwbtq8D/sqVK3nmmWfiFqvsn2jOiA0A9gL3AqcCLwA3ABPNLHf7usBVQDYwsaAdmVlV4H/AK8C5QAfglgKa/zOK2ERERMqdihUr8uKLLwbHF5sxYwadO3dmzpw5+dqaGdddd12edd9++21c4pT9F00hdpZz7iLn3Bjn3JfOuaeBm4GjgRMDbZY55+o453rgFWoFOQJY4Zx7wjk3CXgE6Bah3edAFzM7K9o3IiIiUp707NmTJ598Mri8fPlyjj32WMaMGZOv7fz58/Msr1mzptTjk5JRZCHmnMt/LhRyp4BvEmjjojzeciA9cHmyLnAFsDBCu7HAHOBRy/1zQERE5ABz6623Mn78eGrUqAHA7t27ueKKK/jHP/6RZ8DX33//Pc92y5cvj2ucUnzF7ax/QuDnglg2cs6tB+7Hu3y5EWgBPBapaaBdW+DiYsYoIiKS8M466yxmzZrF4YcfHlz39NNPM2TIkOByeOf8devWsXv37rjFKMUXcyFmZk2Ah4EvnHOzY93eOfcs0AA4FDjaObepgHYTgOnAw2aWEkN815nZbDObHaljo4iISKL5y1/+wrfffstZZ+3rsfPPf/6TnTt3At6gruFWrlwZt/ik+GIqxMysGvABXqf8fsU9qHMu0zm3yDmXfyKtvO7FK9j6xrDvl51znZ1znevXr1/cEEVERMqUGjVq8N577wXvpty5cydff/01ELkQ0+XJxBB1IWZmlYDxeJcTeznnSr3Uds59BXwKPGhmFUv7eCIiImVZSkoKZ5xxRnA5dwqkChUq5GurQiwxRFWImVkq8C5wFHC6c+6nUo0qr/uApsD1cTymiIhImdS9e/fg88mTJwPQpEmTfO3C76SUsimaAV2TgDFAd+Ac59zMUo8qhHNuDl4ReC9QNZ7HFhERKWtOOOEEkpK8X9/ff/89mzdvpmnTpvnavf7662zZsiXe4UmMojkj9jxwITAc2GFmXUIewX95MzvNzC4Ajg+sOiEwKv9pJRDnA3iDxrYvgX2JiIgkrFq1atGpUycAcnJymDRpEgcffHC+dhs2bGDAgAHxDk9iFE0hlltI3QfMCHtcE9LuBeAd4MHA8qDAcmEDvEbFOfcr8Mb+7kdERKQ86NGjR/D5o48+SvPmzWnQoEG+diNGjGDixAInvJEyIJoBXdOcc1bAY1AU7dKiDcY5tzSwzYgIr/ULvHZitPsTEREpj66//noqV64MwNy5cxk5ciSnnnpqxLbDhw+PZ2gSo+IO6CoiIiI+adasGXfffXdw+b777qNr164R237xxResXr06XqFJjFSIiYiIJKA77riD5s2bA7Bp0yZmzZpFo0aN8rXLycnhP//5T7zDkyipEBMREUlAlStXzjMp+OjRo7ntttsitn399deJflpoiScVYiIiIgnq3HPPDY4rtnfvXj755BNuvPHGfO1+/vln5s2bF+/wJAoqxERERBKUmfGvf/2L5ORkAKZMmcLRRx/NYYcdlq/t6NGjg89bdh8WtxilcCrEREREEljr1q256aabgssPPPBAxLNi//nPf8jOzg4uqxgrG1SIiYiIJLhBgwZRr149wJtjcvz48fnarFu3Lt+YYirG/KdCTEREJMHVqlWLwYMHB5dz56AMF3p5MpeKMX+pEBMRESkH+vXrF5z6qCDvv/9+xPknVYz5R4WYiIhIOZCcnMyDDz5YaJvdu3czduzYiK+pGPOHCjEREZFy4swzzyQ9Pb3QNpEuT+ZSMRZ/KsRERETKiaSkJG699dZC20ybNo2lS5cW+LqKsfhSISYiIlKO9OnTh1q1ahXaZtKkSYW+rmIsfsp1IbZjxw6/QxAREYmratWqce+99xba5ptvvilyPyrG4qNcF2IrV670OwQREZG4GzBgANdff32Br8+YMSOq/agYK33luhDbvn07a9eu9TsMERGRuDIznn/+eW688UbMjLS0NL755htSUlIAWLBgAevXr49qXyrGSle5LsQANm/ezOLFi5kwYQJ79+71OxwREZG4SEpK4vnnn2fr1q0sXLiQrl27ctRRRwVfHz58OM65qPYVTTH28+/r+Pr7peTkRLdP8ZTrQqxSpUrcfvvtpKenc/rppzNo0CC/QxIREYmratWqkZqaCsDNN98cXP/4449z3HHHMWrUKHJycorcT2HF2M8L19L7htH0uesdDjtlOMtWZ+5/4AeIcl2I7d69m08++SS4vGnTJh+jERER8dcFF1xAx44dg8vffPMN/fr1o0ePHvz0009FniErqBjL2LIrz3L3K0fw8dRf9z/gA0C5LsTC/eMf//A7BBEREd8kJyfz2Wefcf311wf7iwFMmTKFtm3bUqNGDW666Sb27NlT4D4iFWPHdGyeb92dwyawfPXmEom7PDtgCrFvvvmGQw891O8wREREfFWvXj1eeOEFli1bxoABA0hK2lcKbN++neeff54HHnig0H2EF2MpyUk8P/CcPOuy9mTz0HNfRN0P7UB1QBRi3377LV27dvU7DBERkTKjcePGPP7443z99df07t07zxmy5557jt9++63Q7cOLsVOOO5T2RzTKs+7LWUv47KuFJRd0OVSuC7HU1FR+/PHHPHeJiIiIyD5dunRh3LhxZGVlccQRRwCwc+dOTjrpJH7++edCtw0txsyMu687MV+bR/49me07C77UeaAr14VYq1ataNOmjd9hiIiIlHlJSUmMGTOGSpUqAbBmzRq6devGt99+W+h2ocVY5zZNubJ3xzyvr9u4nadHTS/5gMuJcl2IhZ5mFRERkcJ16NCBzz77jOrVqwOQmZlJ9+7dmT698EIqtBi789pupDevm+f1Ue99z7TvlpR8wOVAuS7EREREJDbdunVjypQp1KtXD/Dmbb7sssvYunVrodvlFmOVKqby5D1nkJqSt8S47bGPWLVuS+kEncBUiImIiEgenTp14quvvqJuXe/M1ooVK3jwwQeL3C63GGuV3pDbrzo+z2ubt+1mwNBPdBdlGBViIiIiks/hhx/Oc889F1x+5513otoutxi76oK/0qV9szyvfffjSibNWFxyQZYDKsREREQkogsvvJDKlSsDsHr1atauXRvVdi27DyMpyRhw9fH5Xnt8xJfs3Vv0lEoHChViIiIiElFycjLt27cPLs+ZMyfqbVt2H0bLg+vmW794eQY//hZdQXcgUCEmIiIiBerUqVPw+ddffx3Ttu3OfpqqlVPzrf9jRcZ+x1VeqBATERGRAoXOTPPUU08xd+7cqLc1Mw5u3jLfehVi+6gQExERkQKdf/75HHnkkQDs2rWLbt268fnnn0e9fdOmTfOtm/frmuDzjC072bY964C9m1KFmIiIiBSoYsWKvPnmm9SoUQOAbdu2ccYZZ/Daa69Ftf3BBx+cb93sn1aydftu7hj6CUed/zwdej9D+3Oe4enXp5OTc2AVZCrEREREpFDt2rVj+vTpwbNb2dnZXHXVVQwcOLDIM1mRzohl781hwNBPGDdxfnDdjp17eO6NGQx5eWqJxl7WqRATERGRIrVp04aZM2fSrl274LqHH36Yvn37smdPwZN6h951GWpyAeOJjRk/l91Zf+5XrIlEhZiIiIhEpUmTJkybNo1evXoF140ePZrTTjuNzZs3R9zm9NNPp1atWlEfI2tPNj8sWFN0w3JChZiIiIhErUaNGnz44Ydcc801wXWTJ0/muOOOY/ny5fnaV6pUiYsvvrjQfbZsVofTuv0luLx2feHzWpYnKsREREQkJqmpqbz88ss8+uijwXXz58+nS5cuLFu2LF/7Pn36FLq/AVd3o3HD6sHldZt2lFywZZwKMREREYmZmXHffffxxhtvkJrqDdq6Zs0aLr/8crKzs/O07dKlC+np6cHlChUqANCsWTPefPNNeh57KPXrVAu+vn7T9ji8g7JBhZiIiIgU2xVXXMEnn3xCcnIy4I2+//DDD+dpY2Z06NAhuPzqq6/yxx9/sGjRIi6//HJadh9Gw7ohhViGCjERERGRqPTo0SNP8fXYY4/l6y8W2pm/WrVqHHLIIcEzaQAdThkQfK4zYiIiIiIxuOuuuzjmmGMA2Lt3LyNHjszz+oIFC4LPDz/88HzbN27cOPh8vfqIiYiIiEQvOTmZ2267Lbg8YsSIYF+xbdu2sXLlSgBSUlJo0aJFvu0bNWoUfL52wzb27s0p5YjLBhViIiIiUiLOPvtsGjZsCMDq1av55JNPAPj999+DbdLT0/NcksxVrVq14LbZe3N4fdycOETsPxViIiIiUiJSU1Pp169fcPnll18GyDMNUsWKFQvc/rrrrgs+f+zFKQwfOY3scn5mTIWYiIiIlJjQgV4nTJjA8uXLqVevXnDdxo0bC9z2zjvvpFOnTsHlF9/6lr53vcO2HVmlE2wZoEJMRERESkzLli3p0aMHADk5OYwcOTJfIVbQROHVqlVj4sSJeaZQmjl3Obc99lGRk4snKhViIiIiUqL69+8ffD5y5EgqVqxIpUqVAMjKymLHjoLviqxduzYff/wxgwYNCq6b8u0fHNpzOIf2fJz0Ho/z0tvflpvO/CrEREREpESdffbZNGjQAIBVq1YxYcKEqC9PgncH5sCBAznzzDPzrM89Kfb4iGm88NbM4PoVazaXTOA+UCEmIiIiJapChQp5Ou0/++yzMRViEyZM4JxzzuGjjz4qsM3mrbuDzx8fMW0/ovWXCjEREREpcddeey1mBsDEiROZO3du8LWCCrH169dz6aWXcvrppzN+/PgC993v/E7cftXxAMyZv4pPvvyt5AKPMxViIiIiUuJatmzJ1VdfHfG18ELMOccbb7xBq1atePvtt/O8VrlyZbp06cLdd9/Nt99+y969e3l17GwqV0pl1+4/eeDpz0vtPcRDit8BiIiISPk0ZMgQPvvsM1asWJFn/bZt24LPly1bxvXXX8+nn36ap83f/vY37rrrLg4//PDghOKhWpw8lN49WvPbksIvc5Z1KsRERESkVNStW5f333+fo446ir179wbXd+7cGYAvv/ySM888k+3b903y3bx5c1588UVOPfXUQvf97LPPMn7ygkLbJAJdmhQREZFS07FjR5599tngcrt27ejcuTPz5s3jjDPOCBZhZsYtt9zCzz//XGQR9tVXX3H77bcHlwNd0RKSzoiJiIhIqbruuutYvnw5s2bN4umnn8Y5x3XXXRccT6xRo0a8++67dO3atch9rV69mgsvvDA4oXjVqlULHZesrFMhJiIiIqUqOTmZwYMHB5cnTZrErFmzAG+oi4kTJ9K6desi97Nnzx4uuOAC1q1bB0C9evU477zzgnNaJiJdmhQREZG4+vjjj4PPr7766qiKMIB7772XGTNmAJCUlMR///tfFi5cWCoxxosKMREREYmr0OKpWbNmUW2zYsUKnnnmmeDy0KFD6dKlC998802JxxdPKsREREQkriykd/1jjz3GxIkTi9xmyJAh/PnnnwAcc8wx3H777XzzzTfs2bOn1OKMBxViIiIiElcPPfQQVatWBbwxxXr16sU999wTLLTCrVq1ihEjRgSXBw4ciJkxb968uMRbmlSIiYiISFx17NiRCRMm0LBhQ8AbWX/IkCF069aNJUuW5Gs/bNiw4JmvLl260LNnTwBq1KgRv6BLiQoxERERibvjjz+eefPmccoppwTXzZw5kw4dOvDOO+8E161ZsybPXZEPPvhg8NLmQQcdFL+AS4kKMREREfFFw4YNmTBhAsOGDSMlxRtRa8uWLVx00UW89tprgHcZc/fu3YA3In/oYK9paWlxj7mkqRATERER3yQlJXHHHXcwffr0PIXVDTfcwDnnnMNLL70UXBd6Nuyuu+6ibdu28Q63xJlzzu8YSk3nzp3d7Nmz/Q5DREREopCZmUmXLl0ijg127LHH8tVXXwULsfT0dBYvXhza5HvnXOf4RFpydEZMREREyoTatWvzzjvvULt27Tzre/bsyYcffphn2It27drFO7xSoSmOREREpMxo27YtCxYs4J133iErK4uOHTvSqVMnHnvsMTIzM/n73/9O27Zt81zGPP/883n33Xf9C3o/qBATERGRMqVhw4bcdNNNweULL7yQsWPHAvDGG2/w1FNP5Rm6ok6dOnGPsaSoj5iIiIiUWRkZGdSrV4/weqVTp058//33gNfhPycnR33EREREREpSZmZmviIM4Pvvv6dBgwYA5OTkxDusElNkIWZmF5jZu2a2zMx2mdlvZjbYzKqHtattZiPMbKOZ7TCzL8ysTYT9nWhmv5rZVjN7ycwqhLyWZmYu8Dg5wrbTzWxqMd+riIiIJJi0tDTS09MjvrZx40ZatmwZ54hKVjRnxAYAe4F7gVOBF4AbgIlmlgRg3m0M4wOv/x9wPpAKTDGzprk7MrOqwP+AV4BzgQ7ALQUc95/FeD8iIiJSjiQnJzN27FiSkvaVLC1atAC8M2HnnnsulStX9iu8/RZNIXaWc+4i59wY59yXzrmngZuBo4ETA23OBo4D/uace8s592lgXRJwZ8i+jgBWOOeecM5NAh4BukU45udAFzM7qzhvSkRERMqPdu3a0a3bvnJhx44dVKlSBYBly5bxzDPP+BXafiuyEHPObYiw+rvAzyaBn2cDq51zU0K22wJ8CJwTst1yID1webIucAWQf9Q2GAvMAR610EFDRERE5IDUp0+f4PN169axc+dOACZPnszll1/uV1j7rbid9U8I/FwQ+Nka+DlCu/lAMzOrBuCcWw/cD0wENgItgMcibOcC7doCFxczRhERESknrrzySjp06JBv/aZNm3jvvfd8iKhkxDyOmJk1AR4GvnDO5Y4NUQdYGqF5RuBnbWA7gHPuWTN7E6gL/OGci3irg3NugplNBx42s7HOuewo47sOuC73+Ga2JJrtJCr18ApoKTnKaclTTkueclrylNMSdMUVVwBU8juO4oipEAuc2foAyAb6hb6EdxYr3yaR9uOcywQyozjkvcA0oC8wIpoYnXMvAy8H4p2diGOKlFXKZ8lTTkueclrylNOSp5yWPDNLyIFDo740aWaV8O6MbAH0cs6tDHk5A++sWLjcyaKiKbrycc59BXwKPGhmFYuzDxEREZGyKqpCzMxSgXeBo4DTnXM/hTWZj9dPLFwrYLlzbvt+xHgf0BS4fj/2ISIiIlLmRDOgaxIwBugOnOOcmxmh2XigiZmdELJdDeCswGvF5pybg1cE3gtUjXHzl/fn2JKP8lnylNOSp5yWPOW05CmnJS8hc1rkXJNm9gLe2ah/Ah+FvbzSObcyUKxNBw4G7sC7FHkP3l2P7ZxzK6IKxiwNWAJc65wbEbL+cLy7MpOBL51zJ0azPxEREZGyLJpLk6cFft4HzAh7XAMQuPPxTLxhKf4NjMMbjf+kaIuwwjjnfgXe2N/9iIiIiJQlRZ4RExEREZHSUdwBXUudmR1rZp+b2frABOFzzOyqkNdHhUwQHv74NWxf0U40HunRPo5vu9QUlc9Am9Zm9p6ZrQ5M3D7fzG43s5Swdgd8PiHqnLY3s0/NbHugzXgzyzd7rXLqMbOTzGy6me0yswwze8PMGkZoV9vMRpjZxsBn9QszaxOh3QGf12hyambVzWy4mU0N5MqZ2YkF7E85jS6n3c3sTTNbHGi32MxeMLMGEfannEaX006B79NVZrbbzNaa2Sdm1jXC/hInp865MvfA61u2C5iCN0VST+AlvLHKbgi0aQl0CXtcEmgzLGRfVYH1wO14NxzMAu4IeT0tsM1jEfbXBajidz7ilM/GwAZgLnARcDJev8AcYKjyWaycHgpsw7uMfw5wPvAjsBpooJzmy+nxwJ94fVFPB/4GLMPrH1oxpJ0BXwErgUuBU4Ev8QbHbKq8FiunaXjDEH2Bd3OUA06MsD/lNPqcvgNMwBtz8wS8rjyrgD+AasppsXLaHXgO73f9CcCFwDfAHuCoRM2p7/8ABfyjPBZIbLWw9TOBGYVs90Agua1D1nUGvg9ZPgv4MMI/yDV+v28/84k3G4EDDgtr8zawRvksVk5HAJuBWiGvNwV2k/ePBeXUe59fAIuAlJB1fw289xtD1p0TWHdSyLqaeIXEM8prsXJqIc97UHAhppxGn9P6EbbtFmh3lXIae04L2LY6kAU8m6g5LauXJivgVce7wtZvpvDLqVfiJX9+yLpoJxovz6LJZ+5p262FtAHlM1c0Oe2CV5Rtzn3ReQMh/wycG7KNcurpAkx0IdOZOee+AzaRN19nA6udc1NC2m0BPsQr0nIpr1Hm1AV+O0VBOY0+pxsibPtd4GeTkHXKafT/9yPZgVeI/RmyLqFyWlYLsVGBn8+YWWMzq2Vm1+KdYnwq0gZmdiyQDrweut5FP9F4kpmlhD2SS+bt+G5U4Gdh+XwHLz/PmdkhZlbDzM7FO0X8RO6OlM+gUYGfheV0L95Zs3BZQEvzZqtQTvcpLF9Hhiy3xitmw80Hmpk3FZvy6ok2p1FRToH9y2nuWJsLclcop0CMOTWzJDNLNbNmeJcqIWQaxITLqd+n5Ao53fhXvD4gLvDYA1xdSPuXAm3qFfB6bbxCLSlsfVrIMcIf2/3OQzzzGcjP/JA2OcCDymfxcgr8L/B6asi66nhnzRzQSDnN8z5nAd+GrWse+BxmhaxbCLwdYftrAjk5WHmNLadhrxd4aVI5LV5OA22qA78CvxByCU45jT2nwNiQHKwDjitgvwmR05gm/Y4XMzsUr8PofLzBZHfhXXJ40cx2O+fGhLWviNfB/CPnXMTZ7F3RE40/ijeheai9xXsHZUs0+TSz+sB7eKd5L8A7JXwycL+ZZTnnhobu80DOJ0T9Gf0XXmfSF83sQSAF7+xitcBuckL3eaDnFC9fb5rZo8AzePPXvoyXp9BcGd4XZjiLtNMDPK/R5jQmymlsOTXvzvO38C5JHutCLsHlUk5jyumdwFC8QeT/DnxkZj2cc3km/U6YnPpdCRdQxb4DLCbkTEJg/Ri804zh1e1FeF/M5xTjWGmUoU57fuUTeByvf1jtsDb/pJAzjQdiPqPNaWD5RmAL+/7a+gIYiXfKPTXKYx0QOQ2810fwitrcM7Jv4U2T9kdIm2+BzyJse2dgu2pRHuuAyGs0OQ1rX+QZMeU0+pwGvl/H4N2k01053f+chm1XAe8s+aeJmtOy2kesDTDPOfdn2PpZQF0gfByWPni//D6JQ2yJKJp8tgEWOe8viPA2qXind2WfqD6jzrl/B54fCTRzzvXAGyrk2wjbHvCccw8A9fCGB2nknLsUbxiQ6SHN5uP1EwvXCljunNte6oEmkChzKjGIMacvAhcDlzjnJsUvysRS3M+pc24P3rBACfs7qqwWYmuB9qEDsAUcjfdXRUbuisCAb6cA/9EvtgJFk8+1eHeZ1I7QBrzxb2SfqD+jzrks59x859wK8wYd7QG8EL9QE4tzbodz7ifn3DozOxU4HO+XWa7xQBMzOyF3hZnVwLtFfXx8o00MUeRUYhRNTs3sCby+i/2cc+/7EGZCKc7n1Myq4A1XsTgeMZaGMtlHDO8uiHeAD83s33inK8/GG7zxqUAFnOtyvPfxer69xKaFmXWJsH6hcy4jwvpEUmQ+zexFvFx+bmaP4/UROxEYAIxzsc8ZWp7zCdHltClwA96Ag1lAJ+Be4D3n3FvFOGa5zqmZdcCb23ZOYNVxwB14Y659E9J0PN4guW+a2R14fUDuwesjNqwYhy63eY0hp5jZaXgDYebOUHCCmdUDdjjnJsR46AM+p2Z2F3Ab8Crwe1g+NjjnYi0clFOzl/D+yJ2NdxWsOXAT0AjvDv9YlY2c+n1ttJBruKcBU/FGe9+GN+L7jUByWLt5wE/7cZw0Cr57wgEX+J2LeOUTbyyXT4A1eJ325+PdAlxZ+Yw9p0BDvD5hG/EKsV/wRnrOd8eUcurAu9w4He+u0l14X8r9CmhbB+8XXAawE5gEtFNe9yunSwvIw1LlNPacBr4bCsrDKOW0WDm9Cu8P2014Vx4WA/8B2sR4vDKVU036LSIiIuKTstpHTERERKTcUyEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+USEmIiIi4hMVYiIiIiI+SfE7gKKYWZXWByXtWLPVkZxgZWPlCokVcOXKFf0OIWapVav7HUJMUiomVrwAllzZ7xBikk2y3yHEbNfebL9DiMn2P/f4HULMtu3a5XcIMdm1a7ffIcQsJyvBYs7ZCwc3hF+WJDnnnF9hlNlCzMySOx2cnF2zEqQkw4UdUklOMr/Dikm7tGp+hxCTI45I8zuEmDU+6mS/Q4hJ/Zbd/A4hZim12/gdQkw2UcPvEGL249ZNfocQk69XL/M7hJhN+2mB3yHEZN4vv/gdQsy2//6b3yHEZt1aWLYWalXLMbPOzrnv/QijzJ2yMTM7rmWKq13FsrdlOU5IT+HQ+skJV4SJiIhIGVaxAhzWDNKaQO3qs61BHWdmafEOo0wVYmbWoUF1y1mRmUPXtGTaNk6mQooKMBERESkl1SpD65bQoDZUq7LEmjZwZlY7XocvE5cmzaxZs9q2rEF1o02jZGpXUfElIiIicVS7BtSqDuszoWqlDGvRBJasruScyyrNw/paiJlZzb80SNpcu4pxcO0kDqpumKkIExERER+YQcM6UK8WrN4AVSvvtsPT4Ldlpdah35dCzMwqtGuSlFWzElSraBzZKEkFmIiIiJQNyUneHZUH1YXla6FG1RwzO8E5N62kDxXXQszMrEtack6typC9F046NIWUZBVgIiIiUgalpkDLprArC5au/tLq1oSMrUc4534tqUPErRA76dAUV6+qsWG747gWKVRKVQEmIiIiCaByRTjiENi6A7L3LrBG9WDtpkbOubX7u+tSL8TM7LDGNe03gE4HJ1O9kgowERERSUA1qkKbdNi0BbbtXGPNG8HytdWcczuKu8tSK8TMrEHLeknr6lY1Dq2fRP1qZWqkDBEREZHYmXmd+evUhLUboUql7XZoM1i0IsU5tzfW3ZV4IZY7JVGtylCvqtG+iTrii4iISDmTZNC4PjSoAyvXQbUq2da6JfzyR0x3WJZYIWZmyZ1DpiQ6+dAUkjQavoiIiJRnKcmQ1hiy9sCyNblTJnVyzs2JavP9Pb6Z2XEtknNqVzG2BqYk0mj4IiIickCpWAEOaw7bd8Gy1d9bgzqwITPNOVfo5Kz71XHLzNIbVrec5ZqSSERERCR8yqSlgSmTUgtqvl+F2Anpyb/v3OOoVzWJSgUeQkREROQAU7WyV5Rt3QGFXIHcr0Js6u/Zti2LWjv2OKYs3MvqLTmU0gwAIiIiImXf3hxvNP75f3hzV27bmeSc21VQ8/3uI+ac24LXVazpqi05KxZtgDaNNXG3iIiIHECcg3UZ3hyVDevCjl0V3YIle4rarMTumnTOrcQryNr9vGbv3AopcORByVStqIJMREREyinnIHObdxasZjXYubu2+2Pl5mg3L/FxxJxz8wA7vmWKm7lsL/WqGkc0TFInfhERESlftu+EpWu8OSm372zutu1YHusuSm1k/a8WZ5uZJbesl5T95aJsmtdJomW9JJI1tpiIiIgkst2BMcP+zIbN2zo6534o7q5Kda7JwFD/ZmaVcxw7Jy/M5i8Nkzm4lmm0fREREUks2dmwYj1s2QbNGsU8in4kpT7pN0DgbgEzs/qbdrj1izfmcGQjzT8pIiIiCSAnB9ZsgnWbvGmNVq1PcfMXxzyvZCRxKcRyOec24BVkhy3akPPbwvU5tGmcTI1KOjsmIiIiZYxzsHEzrFwPdWvCzt3V3O/Ld5TkIeJaiOVyzi0E7KTDUtycFXupUclodVASlVJVkImIiEgZsGW71w+samXYsesgt33nutI4jC+FWK4pC7PNzCy9flLO9D+yaVwzicPqJ5GSrIJMREREfLBzt3cnJMDWHYe7Ldt/K83D+VqIAQQ6uZmZVUirQ9aU37NpWT+ZtDpGkjr0i4iISDzs+dMbC2znbti6o5tz7qt4HNb3QiyXc24PXkFWc0eW2zxlYQ5HHJREoxq6w1JERERKyd4cWLUeNm2Bpg1g7ab9vhMyFmWmEMsVMmXSwas25yzPnTKpQXW/IxMREZFyI9KURL8uLXJKopJmZX2SbjNr37C6/VA51ahSwe9oYlOnWqrfIcSkdu3Eq3ar1G/sdwgxqVSjkd8hxCypYh2/Q4jJbhLr/x1Axp4sv0OIybqd2/wOIWZrMjb7HUJMNmVm+h1CzLK3bvE7hNhkbPamJFq1vrZzbrNfYZT5QiyXmQ0EPvI7jhidC4zzO4gYJFq8kHgxJ1q8kHgxJ1q8kHgxJ1q8kHgxJ1q8kHgxn+ScG+53EIlUiM12znX2O45YJFrMiRYvJF7MiRYvJF7MiRYvJF7MiRYvJF7MiRYvJF7MZSVeDW0vIiIi4hMVYiIiIiI+SaRC7GW/AyiGRIs50eKFxIs50eKFxIs50eKFxIs50eKFxIs50eKFxIu5TMSbMH3ERERERMqbRDojJiIiIlKulKlCzMxuM7MPzWyNmTkzG1RAu6mB18Mft0Zo29vMfjCz3Wa2zMzuN7PkeMZsZo3MbLCZzTazLWa2wcwmmVm3CG1HFfDeno5XvCFtrzWzX80sy8x+M7PrC2hXqjmOcLy+BeQo93FQSNuoPyulycyWFhBH7whto8p7Kcd7mJn9y8x+NLPtgc/LeDNrF6Gt7zk2s4PNbGzg/9dWM3vPzJrF6/iFMbMLzOzdwP+NXYF/08FmVj2kTVohn+dacY73xALi2BzWrraZjTCzjWa2w8y+MLM28Yw1JJaCPoPOzD4NtPEtx2bW1MyeNbMZZrYzcMy0CO2iyqmZVTKzxwP/L3cF9pvv90lpxmtm3c3sTTNbHIhhsZm9YGYNIuyvoLy3j3PMUX8GSjvHocrayPrXAluB94Gifvn8CPQPW7c0dMHMegHvAiOB24AOwGNAdeCu/Y7WE03MnYCLgdeAmUAF4EZgqpmd7ZwLHx9tA3B22Lo1cYwXM7sWeAkYDHwBdAf+bWbmnHshpF08chzuY6BreMjAh8Afzrm1Ya8V+VmJk8+AQWHr8kwmG23e4+AU4CTgdWAOUAu4E/jWzI51zn0f1t63HJtZFWAykAX0ARzwKDDFzNo653bEI45CDACWA/cCK/H+jwwCTjKzY5xzOSFtBwPjw7b3a/TUm4HvQpazc5+YmeHFeQjwf0AmcA9ezts751bGM1C879MaYeu6Ak+SP59+5DgduAj4HvgK7/9XHjHmdCRwBnAH8Afwd+AzM+vqnJsbj3jxfn9Uw/u/9gdwKPAQ0Cvw/257WPtReN9toRaWQKyxxJwrms9Aaed4H+dcmXkASYGfKXhfpoMKaDcVmB7F/n4Avgxb9yCwBzgoXjHj/RJLCVuXgvdLeFrY+lHASj9zHHhtPfB62PpXgY1AajxzHOX7Oj7wfv5enM9KHOJbCrxZRJuo8x6HeOsR6EMasq4m3i+H0WUpx8AtwF4gPWTdIXiFw21l4N++foR1VwY+rycHltMCy9eUgXhPDMTSo5A25wTanBT2+cgAnvH7PQTiGYlXnNfxO8e537uB59cE4kgrTk6BdoF2/ULW5f4+GR/HeCN9rrsF2l4Vtt4Bj5aBHEf1GYhHjkMfZerSpMv7l+F+MbODgfbAm2EvvQGkAqeVxHGiidk5t9k5lx22LhuYCzQpiTiiFWWOuwL1iZy7usBxEL8cR6kPXvH3dhyPWdKiyns8OOc2usC3T8i6LXh/wcb1MxuFs4GZzrlFuSucc0uAr/F+ufnKObchwurcM01lLZfROhtY7Zybkrsi8Pn4kDKQczOrDFwIfOicy/A7nii/d6PN6dnAn8B/Q9pl43339TKzivGIt6x9rkuyfiAOOQ5VpgqxGHUwrz/In+b1Y7k67PXWgZ8/h64MfEHvBFrFI8iCmFkFvF+8CyK83CDQRyDbzBaa2V1Win2uIoiYO2B+4GerwtrFO8chX7ofOec2RWhS1GclXs4K9F3IMrOZlr9/WLR594WZ1QGOJPJn1s8ctyZ/zsDLm685K8QJgZ/huRwc+H+/xbw+eb70uQoYY2Z7zWyTmf3H8va5KyznzcysWnxCLNB5eN0jXo/wWlnKcahoc9oaWOKc2xmhXQW8S3R+KehzDXBD4Ltvp5lNNrPj4xlYmKI+A3HNcVnrIxatacAYvL/Oa+Gd5h9hZo2cc48G2uTOVBxp5tTMkNf9MghoClwetn4u3jXu+UAlvLm7BuNdf78mTrEVlLuMsNfLSo574/UPifSlG81nJR4+xPtrcQnQELgJGGdmf3PO5Z4BizbvfnkWry/e02Hr/c5xHSJ/BjOA2nE4fkzMrAnwMPCFc252YHUWXv+Zz/H6iB6O16fsGzM7yjkX6RdbadkCPAF8ideftEMglhlm1sE5tx4v50sjbJv7Wa0NhPcRiqcr8S7zTwhZV5ZyHEm0OS3s8567n7gz7+aTp/GKsPfDXn4Tb67o1UBzvH5Xk82sp3NuavyijPozEN8cl+L12h5411iLekyNsG2hfcQKON44YBdQLbB8eWAff4nQdhUw0q+YgcuAHOChKN/bU4F9HxqPeIH7Aq9VLGCbB4qb45L+rAS2/xTvSzclyuPl+azE87Mdso9kvMJsRax59yNmvE7D+fp+lFaOY3xve4DBEdb/E8gu7ePHGGs1YDbeL6SmRbQ9GK8QKrRvYZzi7ojX5+7RwPLvwFsR2l0b+Jwc7GOsjfH6DD4ZRdu455iC+y9FlVNgIjAjQruegXbHxyPesDYpeIXWNqBtFPusDiyjlPqWRhNzYZ+BeOe4NM+IfQMcEUW78FN/xfUW3pmRNsAMCq9ca4W8HqrUYzazs/A65I90zg2McrO3gFuBznj/WXOVVryhuQu9W7NO2OvFyXEkxX4fZtYIr8h41oX1wytE+GclVvudd+fcXjN7BxgaOHO0hujzXhz7k+Pr8e6Evd8592qUx9vfHMcik8ifwdpE/qvWF2ZWCe9OrRbACa6IOwudcyvMbDrw13jEV0Qsc8xsYUgsGRScc/A371fgdbuJdIY8j7KUY6LPaQYQaWiW2iGvx42Z5ea6B3CGc+7HorZxzm0zs48Bv7qJhMYS6TMQ1xyXWiHmvGurv5bW/iOw3EMHfub2q2lNyC+CwLgiVYBfwndQ2jGbWXfgHbyzBeG3+he6aeCnC11ZivGG5i60IMjtb/NLhHZR5TiS/XwfV+CdXSrySzdExHxGqwTzXthntrC8x6y4MZvZ34B/A0845/4Zy6a5h471mMUwn33960K1Yj9yVpLMLBVvmJej8O5G/CnaTYlPDqMRGst8Ig8P0ApY7vIPXRBPVwLznHPzomxfVnIcbU7nA+eaWRWXtw9TK7yzw4vCd1DKXsQbnukC59ykGLYrK3mH/LHENceJ3Fk/3GV4l0J+AnDOLQfmkb8P1hV4d0NMII7MrCvwATAJuMLFdofHZXgfku+KalhCZuANlxApdxl4d6OVlRxfCfzoYhvXJc9nxQ9mloJ3g8Fyt2/cs6jyHi9mdi7e2HcjnHMDYtw8njkeD3Qxsxa5KwJ/DBxL/rGC4i5wxmAM3phw5zjnZka5XTO89/BtKYYXFTPrDBwWEst4oImZnRDSpgZwFj7mPBBna6L8w6ws5Zjoczoe7670C0PapeAVQ58757LiEy6Y2RN4lwH7Oefej2G7GnhjdPme9wI+A3HNcZnqrB/4T5TGvgKxlZldEHj+iXNuZ+BOi7uB9/A6NtbEG7rgbOBul3fwxnuBj8zsJbxLJR2A+4F/ufyDfpZmzIfjDUK6EXgc6OSN3efJ/WI2s+Z4QxW8jVdxV8TrrN8XeMk5tzge8Trn/jSzB/AGEl2FN7DoycBVwP855/aE7LLUc1zIe+mIdxff7QW8HstnpTTjvBTv9vNPgBV4nfX/jjfQ76W57WLMe2nH3A3v3/NHYJSZdQl5Ocs590OgXVnI8St4Nz98YGb34/3R8ghersMHkPTD83hf6P8EdoTlcqVzbmXgF1oSXjG+AfgLXr+8HLzLwnFjZmPwbiqZA2zG+z99D16/z2cDzcYHYn3TzO5g3+CjBgyLZ7xhrsTry/af8Bf8znHI92ynwM/TzGwDsME59yVR5tQ5N9fM/gs8HTjTugS4AW/svPA/4kotXjO7C28Q71eB38M+1xtyf1+Z2QC8XE9hX2f9AcBBJRlvlDFH9RmIV46DSqOj3H50sBtFwZ2I0wJt0vHOtKzCuwNiO17/l0sL2Od5eGdtsvBGt34QSI5zzH0LaeNC9lUH726TZcBuvDMKc/B+ySTFK96Qtv3x7oTLwuubdqMfOS7kvfwL78xbwwJej+mzUopxdsEb+X1dIN4teEVWrwLaR5X3Uo55UCGfk6VlMMfN8C79bcXrMPx++OfZrwdegVpQLgcF2lyFd8Y7E6+QWItXTOS7ESYO8d6DV4BvCXxeVwAvA43C2tXB+yWcgde3cBLQzsc8p+L9cv2wgNd9zXEhn4GpseYUqIw3a8BavN8V3wInxjNevIGcC2ozKmQ/Z+Gdzd8Y+Dxtwis6j4p3jmP5DMQjx7kPCxxQREREROKsPPURExEREUkoKsREREREfKJCTERERMQnKsREREREfKJCTERERMQnKsREREREfKJCTEQOSGaWZmaDQkfkFxGJNxViInKgSgMG4k3CLSLiCxViIuIrM6vodwwiIn5RISYihQpcvnNm1sbMppjZTjNbY2YPBya0zm1Xz8xeMLNVZpZlZr+a2XVh++ob2Fc3M3vHzDYTmGzXzFLM7C4z+8XMdpvZBjP7NDBXa3GO0cXMxpjZVjNbbWbPmFmlQJsT8ea+A5gYaO8C6zGzS8xsciCG7Wb2g5n1iZCb+mb2VuAYmWb2mpmdHbqvkLbnmdnMQP42B95/s+L9q4hIeVGmJv0WkTLtfbx58AYDvYAH8CbLHWRmNfDmk6uMN0/lkkCbF8ysonPu2bB9jcGbVPwC9n0PvQ30Bp7Gm4uzEtANaAT8WoxjvBE4xnlA18A2mXiXI+fgTbz+PHAz3vxzAL8EfrYAxgJDAu+xGzDCzCo7514MOcZ7QBu8+RkXAeezb2LsIDO7HngBeA14GKgeiOdLM2vrnNsWvo2IHCDiMdmpHnrokbgP9k0AfnfY+lfwJtiuhVeU7QYOjdBmI5ASWO4b2NdTYe1ODqy/uZA4Yj3GQ2HtPgIWhiyfGGjXo4j3n4RXLL4CzAtZf0pg+4vC2o8PrD8xsFwNbwLtV8PapQF7gFv9/jfWQw89/Hvo0qSIROt/Yctv4xUZRwKn4l1iXBK4xJhiZinAZ0BdoFXYtuPClnOLmlcKOX6sx/g4bPknIKpLgWZ2aOCS4yrgz8DjGuAvIc26AHsjvJexYctdgRrAmLC4VwK/4p1tE5EDlC5Niki01hWw3ARoAKTjFSyR1A1bXhPh9Qzn3K5Cjh/rMTLClrOAIm8MMLNqwERgJ3A3sBjvzNUNwFUhTRsBmc658HjC89Qg8POLAg6ZWVRMIlJ+qRATkWg1BP4IWwZYBWwC1gO3FLDtb2HLLmx5I1An0AeroGIs1mMUV1egOXC8c2567srAWaxQa4DaZpYaVow1DGu3KfCzLzA/wvHUP0zkAKZCTESidRFe5/VclwDbgZ+BT4H/A5Y759YXY9+f4519uoYInd0D9vcY4bICPyuHra8S+BksrsysNnBOWLuZQDJwLnkv214Y1u4bvGIr3Tn3+v4ELCLljwoxEYnWtYHhKr7Du1vxGmCQc26zmT0FXAx8FXj+G1AVOBzvzFJ4EZOHc26Kmb0LPGlmBwOTgVS8/lMfO+emAvt1jAgWAtnAVWaWgVeY/YZXOG0FnjezgYFj3I931q5mSMyfm9l04GUzq4d31+QFQLtAk5xAu61mdkdgf/WBCXid95sAJwBTnXP/iTF2ESkn1FlfRKJ1DtAT767AK4BHgUcAnHNbgGOAT4C78DrQvxrYZkqknUVwCd4dmr0Dx3gVaE2gP1kJHSPIObcJuAmvcPoSr8Ds5JzbgHeWKxmv4/1gYATwZoTdnId3pm4o3lmxSnh3d4JXbOUe6yXgbLzO/m/gFWMP4f0xPDfW2EWk/DDnwrtqiIjsY2aD8MbeSnXOZfscTplnZs/j9Qer45zLKqK5iBzgdGlSRKSYzKwv3uXK+UAFvCE2rgceVxEmItFQISYiUnw7gFuBlnhDYywB7gUe9zEmEUkgujQpIiIi4hN11hcRERHxiQoxEREREZ+oEBMRERHxiQoxEREREZ+oEBMRERHxiQoxEREREZ/8P+Acp4uqox2SAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1152x972 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting bias percentage \n",
    "\n",
    "#plotting with cartopy\n",
    "import cartopy.feature as cfeature\n",
    "\n",
    "\n",
    "fig = plt.figure(figsize=(16,13.5))\n",
    "\n",
    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
    "ax.set_extent([88,93,20,27])\n",
    "\n",
    "\n",
    "m1 = ax.contourf(bias_percentage['longitude'], bias_percentage['latitude'],bias_percentage[:,:],\n",
    "               levels=np.arange(-150,150+25,25),  transform = ccrs.PlateCarree(),cmap='BrBG',extend='both')\n",
    "\n",
    " \n",
    "# Define the xticks for longitude\n",
    "ax.set_xticks(np.arange(87,94,1), crs=ccrs.PlateCarree())\n",
    "lon_formatter = cticker.LongitudeFormatter()\n",
    "ax.xaxis.set_major_formatter(lon_formatter)\n",
    "\n",
    "# Define the yticks for latitude\n",
    "ax.set_yticks(np.arange(20,28,1), crs=ccrs.PlateCarree())\n",
    "lat_formatter = cticker.LatitudeFormatter()\n",
    "ax.yaxis.set_major_formatter(lat_formatter)\n",
    "\n",
    "\n",
    "plt.colorbar(m1,ticks=np.arange(-150,150+25,25), orientation = 'horizontal',shrink=0.7, fraction = 0.04 , label = 'percentage')\n",
    "ax.coastlines(linewidth=3)\n",
    "ax.add_feature(cfeature.BORDERS,linewidth=3)\n",
    "\n",
    "\n",
    "plt.title('Seasonal Bias-Percentage(GCM ensemble avg-CHIRPS)')\n",
    "plt.savefig(\"/home/mkibria/Academic/pr_of_thesis/figures/Seasonal Bias_percentage(gcm ensemble avg-chirps).png\")\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "220503a1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Colormap CET_D1A is not recognized. Possible values are: Accent, Accent_r, Blues, Blues_r, \\nBrBG, BrBG_r, BuGn, BuGn_r, BuPu, BuPu_r, CMRmap, CMRmap_r, Dark2, Dark2_r, GnBu, GnBu_r, Greens,\\nGreens_r, Greys, Greys_r, OrRd, OrRd_r, Oranges, Oranges_r, PRGn, PRGn_r, Paired, Paired_r, Pastel1, Pastel1_r, Pastel2, \\nPastel2_r, PiYG, PiYG_r, PuBu, PuBuGn, PuBuGn_r, PuBu_r, PuOr, PuOr_r, PuRd, PuRd_r, Purples, Purples_r, RdBu, RdBu_r, RdGy,\\nRdGy_r, RdPu, RdPu_r, RdYlBu, RdYlBu_r, RdYlGn, RdYlGn_r, Reds, Reds_r, Set1, Set1_r, Set2, Set2_r, Set3, Set3_r, Spectral, \\nSpectral_r, Wistia, Wistia_r, YlGn, YlGnBu, YlGnBu_r, YlGn_r, YlOrBr, YlOrBr_r, YlOrRd, YlOrRd_r, afmhot, afmhot_r, autumn,\\nautumn_r, binary, binary_r, bone, bone_r, brg, brg_r, bwr, bwr_r, cividis, cividis_r, cool, cool_r, coolwarm, coolwarm_r, \\ncopper, copper_r, cubehelix, cubehelix_r, flag, flag_r, gist_earth, gist_earth_r, gist_gray, gist_gray_r, gist_heat,\\ngist_heat_r, gist_ncar, gist_ncar_r, gist_rainbow, gist_rainbow_r, gist_stern, gist_stern_r, gist_yarg, gist_yarg_r,\\ngnuplot, gnuplot2, gnuplot2_r, gnuplot_r, gray, gray_r, hot, hot_r, hsv, hsv_r, inferno, inferno_r, jet, jet_r, magma,\\nmagma_r, nipy_spectral, nipy_spectral_r, ocean, ocean_r, pink, pink_r, plasma, plasma_r, prism, prism_r, rainbow, rainbow_r, \\nseismic, seismic_r, spring, spring_r, summer, summer_r, tab10, tab10_r, tab20, tab20_r, tab20b, tab20b_r, tab20c, tab20c_r, \\nter'"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#cma colors\n",
    "'''Colormap CET_D1A is not recognized. Possible values are: Accent, Accent_r, Blues, Blues_r, \n",
    "BrBG, BrBG_r, BuGn, BuGn_r, BuPu, BuPu_r, CMRmap, CMRmap_r, Dark2, Dark2_r, GnBu, GnBu_r, Greens,\n",
    "Greens_r, Greys, Greys_r, OrRd, OrRd_r, Oranges, Oranges_r, PRGn, PRGn_r, Paired, Paired_r, Pastel1, Pastel1_r, Pastel2, \n",
    "Pastel2_r, PiYG, PiYG_r, PuBu, PuBuGn, PuBuGn_r, PuBu_r, PuOr, PuOr_r, PuRd, PuRd_r, Purples, Purples_r, RdBu, RdBu_r, RdGy,\n",
    "RdGy_r, RdPu, RdPu_r, RdYlBu, RdYlBu_r, RdYlGn, RdYlGn_r, Reds, Reds_r, Set1, Set1_r, Set2, Set2_r, Set3, Set3_r, Spectral, \n",
    "Spectral_r, Wistia, Wistia_r, YlGn, YlGnBu, YlGnBu_r, YlGn_r, YlOrBr, YlOrBr_r, YlOrRd, YlOrRd_r, afmhot, afmhot_r, autumn,\n",
    "autumn_r, binary, binary_r, bone, bone_r, brg, brg_r, bwr, bwr_r, cividis, cividis_r, cool, cool_r, coolwarm, coolwarm_r, \n",
    "copper, copper_r, cubehelix, cubehelix_r, flag, flag_r, gist_earth, gist_earth_r, gist_gray, gist_gray_r, gist_heat,\n",
    "gist_heat_r, gist_ncar, gist_ncar_r, gist_rainbow, gist_rainbow_r, gist_stern, gist_stern_r, gist_yarg, gist_yarg_r,\n",
    "gnuplot, gnuplot2, gnuplot2_r, gnuplot_r, gray, gray_r, hot, hot_r, hsv, hsv_r, inferno, inferno_r, jet, jet_r, magma,\n",
    "magma_r, nipy_spectral, nipy_spectral_r, ocean, ocean_r, pink, pink_r, plasma, plasma_r, prism, prism_r, rainbow, rainbow_r, \n",
    "seismic, seismic_r, spring, spring_r, summer, summer_r, tab10, tab10_r, tab20, tab20_r, tab20b, tab20b_r, tab20c, tab20c_r, \n",
    "ter'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "87f4ea28",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "20e38f40",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "21be7cc5",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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