Prematched_with_auxiliary.ipynb

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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pre-matched data with auxiliary data\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import modelskill as ms\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import mikeio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<mikeio.Dataset>\n",
       "dims: (time:67)\n",
       "time: 2017-10-27 00:00:00 - 2017-10-29 18:00:00 (67 records)\n",
       "geometry: GeometryUndefined()\n",
       "items:\n",
       "  0:  Hm0, model <Significant wave height> (meter)\n",
       "  1:  Hm0, obs <Significant wave height> (meter)\n",
       "  2:  Wind speed <Wind speed> (meter per sec)\n",
       "  3:  Wind Direction <Wind Direction> (degree)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fn = \"examples/metocean/eur_matched.dfs0\"\n",
    "mikeio.read(fn)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The function `from_matched()` takes a dataframe, a dfs0 or a mikeio.Dataset of already matched data and returns a Comparer object."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Wind speed', 'Wind Direction']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cmp = ms.from_matched(fn, obs_item=1, mod_items=0, aux_items=[2,3])\n",
    "cmp.aux_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# NOTE: we rename data_vars to avoid spaces in names\n",
    "cmp = cmp.rename({\"Wind speed\": \"wind_speed\", \"Wind Direction\": \"wind_dir\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['wind_speed', 'wind_dir']"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cmp.aux_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Comparer>\n",
       "Quantity: Significant wave height [m]\n",
       "Observation: Hm0, obs, n_points=67\n",
       "Model(s):\n",
       "0: Hm0, model\n",
       " Auxiliary: wind_speed\n",
       " Auxiliary: wind_dir"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cmp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:      (time: 67)\n",
       "Coordinates:\n",
       "  * time         (time) datetime64[ns] 2017-10-27 ... 2017-10-29T18:00:00\n",
       "    x            float64 nan\n",
       "    y            float64 nan\n",
       "    z            float64 nan\n",
       "Data variables:\n",
       "    Observation  (time) float64 0.92 1.03 1.24 1.34 1.55 ... 3.24 3.23 3.36 3.23\n",
       "    Hm0, model   (time) float64 1.43 1.655 1.789 1.834 ... 3.473 3.395 3.307\n",
       "    wind_speed   (time) float64 9.754 11.06 11.42 10.93 ... 13.54 13.06 12.87\n",
       "    wind_dir     (time) float64 327.4 331.5 333.3 330.2 ... 343.6 343.7 345.9\n",
       "Attributes:\n",
       "    name:                Hm0, obs\n",
       "    gtype:               track\n",
       "    weight:              1.0\n",
       "    modelskill_version:  1.1.dev0</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-3e48ea56-3c3a-4bb0-aba0-24a6f1b02907' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3e48ea56-3c3a-4bb0-aba0-24a6f1b02907' 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>: 67</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-22634a21-e884-429f-93bf-84a3f3d87dce' class='xr-section-summary-in' type='checkbox'  checked><label for='section-22634a21-e884-429f-93bf-84a3f3d87dce' class='xr-section-summary' >Coordinates: <span>(4)</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'>2017-10-27 ... 2017-10-29T18:00:00</div><input id='attrs-e6f7d3de-aaf5-481d-897d-3ce3d3cab039' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e6f7d3de-aaf5-481d-897d-3ce3d3cab039' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c2475489-ab9a-4bba-8672-eee07fc5175a' class='xr-var-data-in' type='checkbox'><label for='data-c2475489-ab9a-4bba-8672-eee07fc5175a' 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;2017-10-27T00:00:00.000000000&#x27;, &#x27;2017-10-27T01:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-27T02:00:00.000000000&#x27;, &#x27;2017-10-27T03:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-27T04:00:00.000000000&#x27;, &#x27;2017-10-27T05:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-27T06:00:00.000000000&#x27;, &#x27;2017-10-27T07:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-27T08:00:00.000000000&#x27;, &#x27;2017-10-27T09:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-27T10:00:00.000000000&#x27;, &#x27;2017-10-27T11:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-27T12:00:00.000000000&#x27;, &#x27;2017-10-27T13:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-27T14:00:00.000000000&#x27;, &#x27;2017-10-27T15:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-27T16:00:00.000000000&#x27;, &#x27;2017-10-27T17:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-27T18:00:00.000000000&#x27;, &#x27;2017-10-27T19:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-27T20:00:00.000000000&#x27;, &#x27;2017-10-27T21:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-27T22:00:00.000000000&#x27;, &#x27;2017-10-27T23:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-28T00:00:00.000000000&#x27;, &#x27;2017-10-28T01:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-28T02:00:00.000000000&#x27;, &#x27;2017-10-28T03:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-28T04:00:00.000000000&#x27;, &#x27;2017-10-28T05:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-28T06:00:00.000000000&#x27;, &#x27;2017-10-28T07:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-28T08:00:00.000000000&#x27;, &#x27;2017-10-28T09:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-28T10:00:00.000000000&#x27;, &#x27;2017-10-28T11:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-28T12:00:00.000000000&#x27;, &#x27;2017-10-28T13:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-28T14:00:00.000000000&#x27;, &#x27;2017-10-28T15:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-28T16:00:00.000000000&#x27;, &#x27;2017-10-28T17:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-28T18:00:00.000000000&#x27;, &#x27;2017-10-28T19:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-28T20:00:00.000000000&#x27;, &#x27;2017-10-28T21:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-28T22:00:00.000000000&#x27;, &#x27;2017-10-28T23:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-29T00:00:00.000000000&#x27;, &#x27;2017-10-29T01:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-29T02:00:00.000000000&#x27;, &#x27;2017-10-29T03:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-29T04:00:00.000000000&#x27;, &#x27;2017-10-29T05:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-29T06:00:00.000000000&#x27;, &#x27;2017-10-29T07:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-29T08:00:00.000000000&#x27;, &#x27;2017-10-29T09:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-29T10:00:00.000000000&#x27;, &#x27;2017-10-29T11:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-29T12:00:00.000000000&#x27;, &#x27;2017-10-29T13:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-29T14:00:00.000000000&#x27;, &#x27;2017-10-29T15:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-29T16:00:00.000000000&#x27;, &#x27;2017-10-29T17:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-29T18:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-b6c864e0-9d92-49ae-be5d-e018874699f0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b6c864e0-9d92-49ae-be5d-e018874699f0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6fffa5c0-d11e-4e64-8036-353024d09cb9' class='xr-var-data-in' type='checkbox'><label for='data-6fffa5c0-d11e-4e64-8036-353024d09cb9' 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(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-1b9c45e7-e25b-4f59-b341-718c3b3e404f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1b9c45e7-e25b-4f59-b341-718c3b3e404f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0fc91c7f-c1e0-4742-b05b-2c29e8df622e' class='xr-var-data-in' type='checkbox'><label for='data-0fc91c7f-c1e0-4742-b05b-2c29e8df622e' 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(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-ad8838e3-4494-4f81-a04c-fb6b6451128e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ad8838e3-4494-4f81-a04c-fb6b6451128e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f64a3cc8-83b4-44b3-a5e7-e35dd6c83674' class='xr-var-data-in' type='checkbox'><label for='data-f64a3cc8-83b4-44b3-a5e7-e35dd6c83674' 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(nan)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1272cccb-69f9-4ebc-a27d-ec9e243bc3ed' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1272cccb-69f9-4ebc-a27d-ec9e243bc3ed' class='xr-section-summary' >Data variables: <span>(4)</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>Observation</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.92 1.03 1.24 ... 3.23 3.36 3.23</div><input id='attrs-59c49d1c-6e8b-4ff6-9401-4b5a6da6aa8e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-59c49d1c-6e8b-4ff6-9401-4b5a6da6aa8e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6ca34e4-b3ed-446e-80a2-3f8cd335977b' class='xr-var-data-in' type='checkbox'><label for='data-a6ca34e4-b3ed-446e-80a2-3f8cd335977b' 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>kind :</span></dt><dd>observation</dd><dt><span>long_name :</span></dt><dd>Significant wave height</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>is_directional :</span></dt><dd>0</dd><dt><span>color :</span></dt><dd>black</dd></dl></div><div class='xr-var-data'><pre>array([0.92000002, 1.02999997, 1.24000001, 1.34000003, 1.54999995,\n",
       "       1.65999997, 1.79999995, 2.01999998, 2.07999992, 2.07999992,\n",
       "       2.1500001 , 2.20000005, 2.1500001 , 2.1500001 , 2.08999991,\n",
       "       2.01999998, 2.02999997, 1.88999999, 1.75      , 1.69000006,\n",
       "       1.76999998, 1.48000002, 1.5       , 1.58000004, 1.69000006,\n",
       "       1.82000005, 1.86000001, 2.1099999 , 2.27999997, 2.31999993,\n",
       "       2.32999992, 2.28999996, 2.43000007, 2.44000006, 2.42000008,\n",
       "       2.48000002, 2.46000004, 2.77999997, 2.72000003, 2.74000001,\n",
       "       2.61999989, 2.79999995, 2.99000001, 2.91000009, 2.96000004,\n",
       "       3.31999993, 2.86999989, 3.26999998, 3.3900001 , 3.3599999 ,\n",
       "       4.13000011, 4.07000017, 4.01000023, 4.26999998, 3.97000003,\n",
       "       4.15999985, 3.8900001 , 4.17999983, 3.63000011, 3.79999995,\n",
       "       3.47000003, 3.46000004, 3.36999989, 3.24000001, 3.23000002,\n",
       "       3.3599999 , 3.23000002])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Hm0, model</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.43 1.655 1.789 ... 3.395 3.307</div><input id='attrs-af88f4b1-6281-4d61-9075-f914781e41c1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-af88f4b1-6281-4d61-9075-f914781e41c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f566fd11-d964-4fdb-9805-67aba7d7f1e5' class='xr-var-data-in' type='checkbox'><label for='data-f566fd11-d964-4fdb-9805-67aba7d7f1e5' 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>kind :</span></dt><dd>model</dd></dl></div><div class='xr-var-data'><pre>array([1.43012357, 1.65531552, 1.78946149, 1.83432007, 1.85007548,\n",
       "       1.88810992, 1.91699803, 1.98814738, 2.03688717, 2.03490376,\n",
       "       2.01962423, 2.00415182, 1.94293642, 1.85048389, 1.77836597,\n",
       "       1.75923872, 1.75259233, 1.75367975, 1.72203565, 1.64668751,\n",
       "       1.57914627, 1.52860236, 1.50953329, 1.56580639, 1.64933288,\n",
       "       1.72945035, 1.84817863, 1.97161794, 2.1112957 , 2.19987416,\n",
       "       2.29758883, 2.36435962, 2.41646504, 2.47689247, 2.48058844,\n",
       "       2.45307708, 2.45904875, 2.47637129, 2.55487871, 2.68618751,\n",
       "       2.83624077, 2.96349311, 3.08343101, 3.14569426, 3.15837502,\n",
       "       3.20412183, 3.24757648, 3.30238676, 3.41156077, 3.52448201,\n",
       "       3.74735975, 3.9755125 , 4.14409924, 4.26423264, 4.30005264,\n",
       "       4.25883722, 4.15624857, 4.0532217 , 3.99341106, 3.97029829,\n",
       "       3.93167901, 3.77592611, 3.63365626, 3.53073692, 3.47268701,\n",
       "       3.39540291, 3.3068819 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wind_speed</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9.754 11.06 11.42 ... 13.06 12.87</div><input id='attrs-190f049d-0803-404d-97a3-d173089f38e2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-190f049d-0803-404d-97a3-d173089f38e2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8887e956-725f-4fbd-89eb-3b286cf58822' class='xr-var-data-in' type='checkbox'><label for='data-8887e956-725f-4fbd-89eb-3b286cf58822' 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>kind :</span></dt><dd>auxiliary</dd></dl></div><div class='xr-var-data'><pre>array([ 9.75422764, 11.05792618, 11.41961288, 10.93108845, 11.59212685,\n",
       "       11.50384808, 11.65175247, 12.03963852, 11.58486843, 11.15458775,\n",
       "       10.9690237 , 10.31010818,  9.36198521,  7.5320425 ,  7.88942194,\n",
       "        8.23822212,  8.55280876,  8.85723591,  8.33512497,  7.71903372,\n",
       "        7.88614607,  8.11098766,  9.22024536, 10.71835136, 11.26555157,\n",
       "       11.58329678, 12.29633713, 12.95066452, 13.37149906, 13.2597723 ,\n",
       "       13.52050114, 13.86180305, 13.53653717, 13.54683971, 13.14327049,\n",
       "       12.56189728, 12.56243896, 12.59917164, 13.45185947, 14.30421638,\n",
       "       15.24296665, 15.61402416, 16.41535378, 15.84278202, 15.97074413,\n",
       "       16.34448814, 16.65880013, 17.06884575, 17.3742485 , 17.63953781,\n",
       "       18.84160423, 18.75466156, 18.17855644, 17.60562897, 17.0172348 ,\n",
       "       16.37489319, 15.27303028, 15.21595955, 14.86328125, 15.18598461,\n",
       "       14.70676708, 13.52915859, 13.29970551, 13.29527473, 13.5355835 ,\n",
       "       13.06369305, 12.87180138])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wind_dir</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>327.4 331.5 333.3 ... 343.7 345.9</div><input id='attrs-c7ad7b65-b2ec-4045-8b47-38c79ca5f722' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c7ad7b65-b2ec-4045-8b47-38c79ca5f722' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b6c9951-a6b9-4434-882b-aefa09c7f149' class='xr-var-data-in' type='checkbox'><label for='data-9b6c9951-a6b9-4434-882b-aefa09c7f149' 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>kind :</span></dt><dd>auxiliary</dd></dl></div><div class='xr-var-data'><pre>array([327.40255737, 331.50585938, 333.26519775, 330.1819458 ,\n",
       "       329.84255981, 330.83706665, 332.21621704, 334.30059814,\n",
       "       339.52163696, 340.134552  , 346.37115479, 351.52597046,\n",
       "       352.15368652, 342.68927002, 335.25900269, 332.52694702,\n",
       "       331.50216675, 332.73135376, 323.90362549, 315.73312378,\n",
       "       303.58590698, 293.41372681, 283.28015137, 282.3427124 ,\n",
       "       281.49691772, 282.24893188, 284.72872925, 288.24108887,\n",
       "       288.14099121, 291.40057373, 293.46334839, 287.16912842,\n",
       "       287.4234314 , 286.82751465, 282.67053223, 281.55844116,\n",
       "       277.71987915, 274.09899902, 277.03219604, 278.20327759,\n",
       "       280.80819702, 284.3190918 , 287.29998779, 281.2434082 ,\n",
       "       281.49319458, 282.18078613, 282.68603516, 285.64093018,\n",
       "       286.8213501 , 290.25241089, 301.35461426, 312.87652588,\n",
       "       324.72293091, 336.34906006, 341.91207886, 340.01062012,\n",
       "       339.22665405, 342.81564331, 344.95181274, 346.12741089,\n",
       "       345.7918396 , 346.46191406, 342.99346924, 340.83685303,\n",
       "       343.58926392, 343.68731689, 345.85305786])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-614ec3e5-6cc0-4508-8ad3-dcd9ec5ed6a9' class='xr-section-summary-in' type='checkbox'  ><label for='section-614ec3e5-6cc0-4508-8ad3-dcd9ec5ed6a9' class='xr-section-summary' >Indexes: <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-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-76c4a113-7e55-4601-9517-13b2d079187f' class='xr-index-data-in' type='checkbox'/><label for='index-76c4a113-7e55-4601-9517-13b2d079187f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2017-10-27 00:00:00&#x27;, &#x27;2017-10-27 01:00:00&#x27;,\n",
       "               &#x27;2017-10-27 02:00:00&#x27;, &#x27;2017-10-27 03:00:00&#x27;,\n",
       "               &#x27;2017-10-27 04:00:00&#x27;, &#x27;2017-10-27 05:00:00&#x27;,\n",
       "               &#x27;2017-10-27 06:00:00&#x27;, &#x27;2017-10-27 07:00:00&#x27;,\n",
       "               &#x27;2017-10-27 08:00:00&#x27;, &#x27;2017-10-27 09:00:00&#x27;,\n",
       "               &#x27;2017-10-27 10:00:00&#x27;, &#x27;2017-10-27 11:00:00&#x27;,\n",
       "               &#x27;2017-10-27 12:00:00&#x27;, &#x27;2017-10-27 13:00:00&#x27;,\n",
       "               &#x27;2017-10-27 14:00:00&#x27;, &#x27;2017-10-27 15:00:00&#x27;,\n",
       "               &#x27;2017-10-27 16:00:00&#x27;, &#x27;2017-10-27 17:00:00&#x27;,\n",
       "               &#x27;2017-10-27 18:00:00&#x27;, &#x27;2017-10-27 19:00:00&#x27;,\n",
       "               &#x27;2017-10-27 20:00:00&#x27;, &#x27;2017-10-27 21:00:00&#x27;,\n",
       "               &#x27;2017-10-27 22:00:00&#x27;, &#x27;2017-10-27 23:00:00&#x27;,\n",
       "               &#x27;2017-10-28 00:00:00&#x27;, &#x27;2017-10-28 01:00:00&#x27;,\n",
       "               &#x27;2017-10-28 02:00:00&#x27;, &#x27;2017-10-28 03:00:00&#x27;,\n",
       "               &#x27;2017-10-28 04:00:00&#x27;, &#x27;2017-10-28 05:00:00&#x27;,\n",
       "               &#x27;2017-10-28 06:00:00&#x27;, &#x27;2017-10-28 07:00:00&#x27;,\n",
       "               &#x27;2017-10-28 08:00:00&#x27;, &#x27;2017-10-28 09:00:00&#x27;,\n",
       "               &#x27;2017-10-28 10:00:00&#x27;, &#x27;2017-10-28 11:00:00&#x27;,\n",
       "               &#x27;2017-10-28 12:00:00&#x27;, &#x27;2017-10-28 13:00:00&#x27;,\n",
       "               &#x27;2017-10-28 14:00:00&#x27;, &#x27;2017-10-28 15:00:00&#x27;,\n",
       "               &#x27;2017-10-28 16:00:00&#x27;, &#x27;2017-10-28 17:00:00&#x27;,\n",
       "               &#x27;2017-10-28 18:00:00&#x27;, &#x27;2017-10-28 19:00:00&#x27;,\n",
       "               &#x27;2017-10-28 20:00:00&#x27;, &#x27;2017-10-28 21:00:00&#x27;,\n",
       "               &#x27;2017-10-28 22:00:00&#x27;, &#x27;2017-10-28 23:00:00&#x27;,\n",
       "               &#x27;2017-10-29 00:00:00&#x27;, &#x27;2017-10-29 01:00:00&#x27;,\n",
       "               &#x27;2017-10-29 02:00:00&#x27;, &#x27;2017-10-29 03:00:00&#x27;,\n",
       "               &#x27;2017-10-29 04:00:00&#x27;, &#x27;2017-10-29 05:00:00&#x27;,\n",
       "               &#x27;2017-10-29 06:00:00&#x27;, &#x27;2017-10-29 07:00:00&#x27;,\n",
       "               &#x27;2017-10-29 08:00:00&#x27;, &#x27;2017-10-29 09:00:00&#x27;,\n",
       "               &#x27;2017-10-29 10:00:00&#x27;, &#x27;2017-10-29 11:00:00&#x27;,\n",
       "               &#x27;2017-10-29 12:00:00&#x27;, &#x27;2017-10-29 13:00:00&#x27;,\n",
       "               &#x27;2017-10-29 14:00:00&#x27;, &#x27;2017-10-29 15:00:00&#x27;,\n",
       "               &#x27;2017-10-29 16:00:00&#x27;, &#x27;2017-10-29 17:00:00&#x27;,\n",
       "               &#x27;2017-10-29 18:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=&#x27;H&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1ed9300a-adbd-450f-bb10-c1f392defc0e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1ed9300a-adbd-450f-bb10-c1f392defc0e' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>name :</span></dt><dd>Hm0, obs</dd><dt><span>gtype :</span></dt><dd>track</dd><dt><span>weight :</span></dt><dd>1.0</dd><dt><span>modelskill_version :</span></dt><dd>1.1.dev0</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:      (time: 67)\n",
       "Coordinates:\n",
       "  * time         (time) datetime64[ns] 2017-10-27 ... 2017-10-29T18:00:00\n",
       "    x            float64 nan\n",
       "    y            float64 nan\n",
       "    z            float64 nan\n",
       "Data variables:\n",
       "    Observation  (time) float64 0.92 1.03 1.24 1.34 1.55 ... 3.24 3.23 3.36 3.23\n",
       "    Hm0, model   (time) float64 1.43 1.655 1.789 1.834 ... 3.473 3.395 3.307\n",
       "    wind_speed   (time) float64 9.754 11.06 11.42 10.93 ... 13.54 13.06 12.87\n",
       "    wind_dir     (time) float64 327.4 331.5 333.3 330.2 ... 343.6 343.7 345.9\n",
       "Attributes:\n",
       "    name:                Hm0, obs\n",
       "    gtype:               track\n",
       "    weight:              1.0\n",
       "    modelskill_version:  1.1.dev0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cmp.data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>n</th>\n",
       "      <th>bias</th>\n",
       "      <th>rmse</th>\n",
       "      <th>urmse</th>\n",
       "      <th>mae</th>\n",
       "      <th>cc</th>\n",
       "      <th>si</th>\n",
       "      <th>r2</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>observation</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Hm0, obs</th>\n",
       "      <td>67</td>\n",
       "      <td>0.052239</td>\n",
       "      <td>0.22824</td>\n",
       "      <td>0.222181</td>\n",
       "      <td>0.174851</td>\n",
       "      <td>0.968321</td>\n",
       "      <td>0.085898</td>\n",
       "      <td>0.929767</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              n      bias     rmse     urmse       mae        cc        si  \\\n",
       "observation                                                                  \n",
       "Hm0, obs     67  0.052239  0.22824  0.222181  0.174851  0.968321  0.085898   \n",
       "\n",
       "                   r2  \n",
       "observation            \n",
       "Hm0, obs     0.929767  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cmp.skill()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cmp.plot.scatter(quantiles=0, figsize=(6,6));\n",
    "cmp.plot.timeseries();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Filter \n",
    "\n",
    "Filter on auxiliary data using `query()` or `where()`. Below, we consider only wave data when the wind speed is above 15 m/s."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Comparer>\n",
       "Quantity: Significant wave height [m]\n",
       "Observation: Hm0, obs, n_points=19\n",
       "Model(s):\n",
       "0: Hm0, model\n",
       " Auxiliary: wind_speed\n",
       " Auxiliary: wind_dir"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cmp.query(\"wind_speed > 15.0\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Comparer>\n",
       "Quantity: Significant wave height [m]\n",
       "Observation: Hm0, obs, n_points=19\n",
       "Model(s):\n",
       "0: Hm0, model\n",
       " Auxiliary: wind_speed\n",
       " Auxiliary: wind_dir"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cmp2 = cmp.where(cmp.data.wind_speed>15.0)\n",
    "cmp2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# notice that the model data is kept, but the observations are filtered\n",
    "cmp2.plot.timeseries();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "More auxiliary data can be added, e.g. as derived data from the original data. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "cmp.data[\"residual\"] = cmp.data[\"Hm0, model\"] - cmp.data[\"Observation\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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KbTYiosct+OsacotK0MbTEaM7eFX6OC3qOeCDfqUtzZ8fiMT1u1maKpGeQCJqWBtZdnY2HBwckJWVBXt7e5XXCgsLERcXBx8fH46eqYTAwEAEBgZi4cKFui5F43htENUsh2+kYtJPl2FqIsG+GV3QxNX+2W96CiEE3tp6CcdupqFBHRv8Nb0LbCwMoz+nvnja9/d/seWGNCInJwe3b9/GnDlzdF0KEVGV5BaVYMHe0uVlJnZtUOVgA5Te3v9qeCu42lsiNj0Pn+7l8jXaxHBDGmFnZ4fExMQy8+wQERmarw9HISWrEPWdrPFOLz+NHdfJxhzfvtoaJhJgV1gSdoeVHc1KmsFwQ0RE9K/wxEz8eDYeAPDFkOawVHO+sWfp4FMb7/RqBAD4+M9ruH0/V6PHp1IMN0RERACK5QrM3xMBIYAhrd3R1a+uVs4zvYcvOjWojXyZHDN2XEFhcdmZ5KlqGG6IiIgAbDodh8iUbDhameHjF5tp7TxSEwlWjmwNJxtz3EjJxpK/I7V2rpqK4YaIiIxCUlISgoODy52Z/VkSM/Kx4ugtAMCHA5qijq2FpstT4WJviW9eaQUA+PHsHRy6nqrV89U0DDdERGTwgoKC4OXlhZ49e8LLywtBQUFqvX/RvusoLFagYwMnvNLOQ0tVqurR2BmTupauqzd311UkZxZUy3lrAoYbIiIyaElJSZg0aZJyTbpHa8lVtAUnKjUHRyPTYCIB/je4RaUWBK6sOX0ao5WHA7IKivHOzisokSuq7dzGjOGGiIgMWnR0tDLYPCKXyxETE1Oh9288FQsA6OfvCl/n6p3OwtzUBN+91hZ2Fqa4dOchvj0WXa3nN1YMNzWQt7c3Vq5cqesyNCYkJAQSiQSZmZm6LoWIdMDPzw8mJqpfZ1KpFL6+vs98b1pOIf4MvwsAmNClgVbqe5b6Ttb44uUWAIDVITE4cztdJ3UYE4YbI5OYmIgJEybA3d0d5ubm8PLywjvvvIMHDx7oujSNCAwMxKxZs1S2de7cGSkpKXBwcNBNUUSkUx4eHli/fj2k0tI5aaRSKdatWwcPj2f3ndl69g5kcgXa1ndEO69a2i71iQa1csfIAE8IAcz6JRwPcot0VosxYLgxIrGxsQgICMCtW7ewY8cOxMTEYO3atTh27Bg6deqEjIwMndQll8vLNBlrkrm5OVxdXav1PjkR6ZcJEyYgPj4ewcHBiI+Px4QJE575ngKZXLlK98Suumm1edyCgc3g62yLtJwivPfbP1AoatTSjxrFcGNEpk2bBnNzcxw+fBjdu3dH/fr10b9/fxw9ehTJycn46KOPlPvm5ORg1KhRsLW1hbu7O7777juVYy1cuBD169eHhYUF3N3dMXPmTOVrMpkMc+fORb169WBjY4MOHTogJCRE+fqWLVvg6OiIffv2oVmzZrCwsMCGDRtgaWlZ5tbRzJkz0b17dwDAgwcP8Nprr8HDwwPW1tZo0aIFduzYodx3/PjxCA0NxbfffguJRAKJRIL4+Phyb0vt2rUL/v7+sLCwgLe3N7755huV83p7e2Px4sV48803YWdnh/r162P9+vWV/dETkR7w8PBAYGBghVpsAOD3sCRkFhSjvpM1+jRz1XJ1z2ZtborVr7WBuakJQm7dx6bTcbouyWAx3GhRVeZcUFdGRgYOHTqEqVOnwsrKSuU1V1dXjB49Gr/88gseLQL/1VdfoWXLlggLC8P8+fPx7rvv4siRIwCA33//HStWrMC6desQHR2NP/74Ay1atFAe74033sDp06exc+dOXL16Fa+88gr69euH6Oj/7wiXn5+PJUuWYOPGjbh+/Tpef/11ODo6YteuXcp95HI5fv31V4wePRpA6crb7dq1w759+3Dt2jVMmjQJY8aMwfnz5wEA3377LTp16oSJEyciJSUFKSkp8PT0LPOzuHz5MkaMGIFXX30VERERWLhwIT755BNs2bJFZb9vvvkGAQEBuHLlCqZOnYq3334bN2/erML/C0RkKBQKgU2nSsPDm897Q2qiHy2/TVzt8elLpRMILjt0E/8kZuq2IEMlapisrCwBQGRlZZV5raCgQNy4cUMUFBRU+TwbN24UJiYmAoAwMTERGzdurPIxn+bcuXMCgNizZ0+5ry9fvlwAEPfu3RNeXl6iX79+Kq+PHDlS9O/fXwghxDfffCMaNWokZDJZmePExMQIiUQikpOTVbb36tVLzJ8/XwghxObNmwUAER4errLPzJkzRc+ePZXPDx06JMzNzUVGRsYTP9eAAQPEe++9p3zevXt38c4776jsExwcLACIhw8fCiGEGDVqlOjdu7fKPu+//75o1qyZ8rmXl5d4/fXXlc8VCoVwdnYWa9asKbcOTV4bRKR7h6+nCq8P9okWCw+K3MJiXZejQqFQiCnbLgmvD/aJrl8eF9kFZX8X10RP+/7+L7bcaEFV51zQBvFvi82jfimdOnVSeb1Tp06IjCydAvyVV15BQUEBGjRogIkTJ2LPnj0oKSkBAISFhUEIgUaNGsHW1lb5CA0Nxe3bt5XHMzc3R8uWLVXOMXr0aISEhODu3dKRCT///DMGDBiAWrVKO/HJ5XJ88cUXaNmyJWrXrg1bW1scPnwYCQkJan3WyMhIPP/88yrbnn/+eURHR0Mu//81XB6vTyKRwNXVFWlpaWqdi4gM04Z/h3+P6uAFGwtTHVejSiKRYOnQlqjnaIWEjHxM33EF2YXFui7LoDDcaEFV51yoDF9fX0gkEty4caPc12/evIlatWqhTp06TzzGo+Dj6emJqKgofP/997CyssLUqVPRrVs3FBcXQ6FQQCqV4vLlywgPD1c+IiMj8e233yqPZWVlVaaD73PPPYeGDRti586dKCgowJ49e/D6668rX//mm2+wYsUKzJ07F8ePH0d4eDj69u0LmUym1s9CCFHm3I/C3ePMzMzKfH5tdnwmIv1wNSkTF+IyYGoiwfhO3roup1wOVmZY9Wpp/5vQW/cx5PvTiEnL0XVZBkNvws2SJUsgkUjKDPP9r9DQULRr1w6WlpZo0KAB1q5dWz0FqqEqcy5UVu3atdG7d2/88MMPKChQncI7NTUVP//8M0aOHKn80j937pzKPufOnUOTJk2Uz62srDBo0CCsWrUKISEhOHv2LCIiItCmTRvI5XKkpaXB19dX5eHq+uwOeaNGjcLPP/+Mv/76CyYmJnjxxReVr508eRKDBw/G66+/jlatWqFBgwYq/XiA0hahx1tfytOsWTOcOnVKZduZM2fQqFEj5VBRIqq5Npws7WszqJU7XB0sdVzNk7XzqoXfJnWCm4MlYtPzMPj70zh4LUXXZRkEvQg3Fy9exPr168vcxvivuLg4DBgwAF27dsWVK1fw4YcfYubMmSqdVPVBVeZcqIrVq1ejqKgIffv2xYkTJ5CYmIiDBw+id+/eqFevHr744gvlvqdPn8aXX36JW7du4fvvv8dvv/2Gd955B0DpaKegoCBcu3YNsbGx+Omnn2BlZQUvLy80atQIo0ePxtixY7F7927ExcXh4sWLWLZsGQ4cOPDMGkePHo2wsDB88cUXGD58OCwt//8Xi6+vL44cOYIzZ84gMjISkydPRmqq6mJy3t7eOH/+POLj45Genl5uS8t7772HY8eO4fPPP8etW7fw448/YvXq1ZgzZ05lf7REZCSSMwtw4N+AMKGLj46rebZWno74a3oXdGzghDyZHFN+DsOygzch5zDxp9Ny/59nysnJEX5+fuLIkSPldhZ93Ny5c0WTJk1Utk2ePFl07Nixwuerrg7FQgiRmJgogoODRWJiokaOVxHx8fFi/PjxwtXVVZiZmQlPT08xY8YMkZ6ertzHy8tLLFq0SIwYMUJYW1sLFxcXsXLlSuXre/bsER06dBD29vbCxsZGdOzYURw9elT5ukwmE59++qnw9vYWZmZmwtXVVbz88svi6tWrQojSDsUODg5PrLF9+/YCgDh+/LjK9gcPHojBgwcLW1tb4ezsLD7++GMxduxYMXjwYOU+UVFRomPHjsLKykoAEHFxcWU6FAshxO+//y6aNWsmzMzMRP369cVXX32lci4vLy+xYsUKlW2tWrUSCxYsKLdmdigmMg7/239deH2wT7y24ayuS1FLcYlcWbvXB/vE6xvPiYzcIl2XVa3U6VAsEaKczgjVaNy4cXBycsKKFSsQGBiI1q1bP3FpgG7duqFNmzYqfTv27NmDESNGID8/v0wfCgAoKipCUdH/z/SYnZ0NT09PZGVlwd7eXmXfwsJCxMXFwcfHR6VFgYjXBpHhyyksRuelx5FTVILN49qjRxNnXZektr3/3MW8XVdRUCyHRy0rrH29HZq714zZ2bOzs+Hg4FDu9/d/6fS21M6dOxEWFoYlS5ZUaP/U1FS4uLiobHNxcUFJSQnS08tfi2PJkiVwcHBQPsqbF4WIiIzfLxcTkVNUAl9nW3RvVFdjx63OOc0GtXLH7rc7w8vJGkkPC/DyD6cxbvMF/HTuDlKzCrV+fkOhs3CTmJiId955B9u2bVPrL+EnjYJ50tT78+fPR1ZWlvKRmJhY+aKJiMgglcgV2HwmHgDwVhcfmGho0r6goCB4eXmhZ8+e8PLyQlBQkEaO+zRN3eyxd3oXvNDUGcVygdBb9/HJn9fQcekxDFx9Ct8ei8b1u1nljhKtKXQ2uP/y5ctIS0tDu3btlNvkcjlOnDih7Bj735Etrq6uZTqYpqWlwdTUFLVr1y73PBYWFrCwsND8ByAiIoNxNPIekjMLUNvGHENa19PIMZ80p1nfvn21PoDEwcoMG8YE4Pb9XByJTMPRyHsIS3iIiOQsRCRnYcXRW6jnaIVhbethQpcGcLAq223DmOks3PTq1QsREREq29544w00adIE8+bNK3fIbqdOnfDXX3+pbDt8+DACAgLK7W9DREQEAH9dLR0hNbydByzNNDMlxNPmNNN2uAFK71j4OtvB19kOb3dviPTcIhy/mYYjkfdwMvo+kjMLsOp4DDaficfELg3wxvPesLOsGd+VOgs3dnZ2aN68uco2Gxsb1K5dW7l9/vz5SE5OxtatWwEAU6ZMwerVqzF79mxMnDgRZ8+eRVBQkMriippQk5vyqHy8JogMV4FMjuM3S2cff7GFm8aO+2hOs8cDjrbnNHuaOrYWGBHgiREBnigsluNo5D18dzwGUfdysPzoLWw6HYfJ3RtiXCcvWJvr16zMmqYX89w8SUpKisrU+z4+Pjhw4ABCQkLQunVrfP7551i1ahWGDRumkfM9av3Jz8/XyPHIeDy6JthCSGR4Qm6lKUcXtainuZFFuprTrCIszaR4qaU7/p7ZFd+91gYN69ogs6AYyw7eRNcvg7HxZCwKi58+Iaoh0/lQ8Or2rKFkKSkpyMzMhLOzM6ytrZ/YUZlqBiEE8vPzkZaWBkdHR7i5ae6vPiKqHtN3hGHf1RRM6toAHw5oqvHjJyUlISYmBr6+vnoRbMojVwj8GZ6Mb49F405G6R9rbg6W2DmxI7xq2+i4uopRZyi4cbdLVcKjJQS4gCI9ztHRsULLSxCRfiks/v9bUgM0eEvqcR4eHnobah6RmkgwtK0HBrZyx+6wJHx7LBp3swqx/MgtfPtqG12Xp3EMN/8hkUjg5uYGZ2dnFBdzFVYqvRXFNamIDFNIVBryZXLUc7RCK4+aMdnd05hJTTCyfX3413PAS9+dwl9X72LWC43gU8cwWm8qiuHmCaRSKb/QiIgM3P6I0ulDBrRwZTeDxzR3d0DPxs44HpWGNaEx+HJYK12XpFF63aGYiIioskpvSd0DAAxozv5y/zWtR+mort1hyUh6aFwDaRhuiIjIKIXeuo88mRzuDpZo7emo63L0TjuvWni+YW2UKATWnYjVdTkaxXBDRERG6UBE6cR9/Zu78ZbUE8zo6QcA+OVSIu5lG8/aVAw3RERkdAqL5Tim5VFSxqCDjxPae9eCrESB9UbUesNwQ0RERudE9H3kFpXAzcESbXhL6okkEgmm9yhtvfn5wh08yC3ScUWawXBDRERG5/FbUppaAdxYdfOrg5b1HFBYrEDQ6Thdl6MRDDdERGRUikrkOBr5aC0pTr75LBKJRNn3ZuvZO8gqMPw53hhuiIjIqJyMTkduUQlc7S3RxrOWrssxCL2aOKOJqx1yi0qw2QhabxhuiIjIqDy6JdWvuStvSVWQiYkE0/+d92bzmXjkFBp26w3DDRERGY2iEjmO3CiduO9FjpJSS//mbmhQ1wZZBcXYdj5B1+VUCcMNEREZjVPR6cgpKoGLvQXa1ectKXVITSSYHljaerPxZCwKZHIdV1R5DDdERGQ09j8aJeXPUVKVMaiVOzxrWeFBngzbLxhu6w3DDRERGYWiEjmORP67lhRvSVWKqdQEU/9tvVl74jbyZSU6rqhyGG6IiMgonIl5gJzCEjjbWSDAi7ekKmtYWw941rLC/ZwibDkTr+tyKoXhhoiIjML+a/+OkvLnKKmqMDc1wezejQAAa0NvG+S8Nww3RERk8GQlChy+ngqAt6Q0YVCremjiaofswhKsCb2t63LUxnBDREQG72T0fWQXlqCunQXaezvpuhyDJzWR4P0+jQEAm0/HITXLsFYMZ7ghIiKD92iU1IvN3SDlLSmN6NnEGQFetVBUosCq49G6LkctDDdERGTQCovlOPzvxH0vteQtKU2RSCSY168JAOCXS4mIS8/TcUUVx3BDREQGLfTWfeQWlcDNwRJtOXGfRrX3dkKvJs6QKwS+ORKl63IqjOGGiIgM2r6r/96SasGJ+7RhTp/GkEhKf87XkrN0XU6FMNwQEZHBKpDJcezmo1tS7jquxjg1dbPHkFb1AADLDt3UcTUVw3BDREQG63hUGvJlcnjUskIrDwddl2O03u3dCGZSCU5Gp+PM7XRdl/NMDDdERGSw9l+9C6D0lpREwltS2lLfyRqjnqsPAFh2MApCCB1X9HQMN0REZJDyikpwPCoNADCwBt6SSkpKQnBwMJKSkqrlfNN7+MHaXIp/kjJx6N/RafqK4YaIiAzS0ch7KCxWwLu2Nfzd7XVdTrUKCgqCl5cXevbsCS8vLwQFBWn9nHXtLDDheR8AwNeHo1AiV2j9nJXFcENERAZp378T973U0r1G3ZJKSkrCpEmToFCUhguFQoHJkydXSwvOxG4N4Ghlhpi0XL1eVJPhhoiIDE52YTFCo+4DqHkT90VHRyuDzSNyuRwxMTFaP7e9pRne71u6LMOyQzcRoadDwxluiIjI4By5cQ8yuQIN69qgsYudrsupVn5+fjAxUf36lkql8PX1rZbzj3quPvr5u6JYLjB9exhyCvVv1XCGGyIiMjj7r9bMW1IA4OHhgfXr10MqlQIoDTbr1q2Dh4dHtZxfIpFg2bCWqOdohTsZ+fj4j2t6N3qK4YaIiAxKVkExTsaU3pIaWMNuST0yYcIExMfHIzg4GPHx8ZgwYUK1nt/BygyrXm0NqYkEf/5zF7+HVc+IrYpiuCEiIoNy6HoqiuUCTVzt4Otcs25JPc7DwwOBgYHV1mLzX+28nDC7dyMAwKd/XkdMWq5O6igPww0RERmUv/6duK+mdSTWR293a4guvnVQUCzH9B1hKCyW67okAAw3RERkQB7kFuHM7QcAgBdb1LyJ+/SNiYkEy0e0Qh1bc9xMzcHiA5G6LgkAww0RERmQg9dTIVcI+Lvbw6eOja7LIQDOdpb45pXWAICt5+7g4PVU3RYEwLQiOzk5Oal1UIlEgrCwMHh5eVWqKCIiovLsf2ziPtIf3RvVxeRuDbDuRCzm/v4Pmrvbw6OWtc7qqVC4yczMxMqVK+Hg8OwVV4UQmDp1KuTyZ993W7NmDdasWYP4+HgAgL+/Pz799FP079+/3P1DQkLQo0ePMtsjIyPRpEmTZ56PiIgM1/2cIpyLLb0l9VIL9rfRN3P6NMb5uAyEJ2bira2XsGFMADyddBNwKhRuAODVV1+Fs7NzhfadMWNGhfbz8PDA0qVLlRMP/fjjjxg8eDCuXLkCf3//J74vKioK9vb/v45I3bp1K3Q+IiIyXBtPxUIhgFYejjr70qQnM5Oa4LtX22DwD6dxMzUHL60+hRUjWqFnE5dqr0Ui9GzmHScnJ3z11Vfljtl/1HLz8OFDODo6Vur42dnZcHBwQFZWlkpAIiIi/RWW8BDD156BQgDrx7RDn2auui6JniA5swBTfw7DP0mZAIBpgQ3x7guNYCqtWjdfdb6/9aZDsVwux86dO5GXl4dOnTo9dd82bdrAzc0NvXr1QnBw8FP3LSoqQnZ2tsqDiIgMR2GxHO///g8UAhjS2p3BRs/Vc7TCr5M7Ylyn0n6334fcxphNF3A/p6jaaqjwbanHJScn4/Tp00hLSyuzeNfMmTPVOlZERAQ6deqEwsJC2NraYs+ePWjWrFm5+7q5uWH9+vVo164dioqK8NNPP6FXr14ICQlBt27dyn3PkiVLsGjRIrVqIiIi/bHi6C3cvp+HunYWWDjwyV0WqOKSkpIQHR0NPz8/rUwCaGEqxaJBzdHOywkf7L6Ks7EP8OJ3J7H6tbZ4zke9QUqVofZtqc2bN2PKlCkwNzdH7dq1Vdb0kEgkiI2NVasAmUyGhIQEZGZmYteuXdi4cSNCQ0OfGHD+a+DAgZBIJNi7d2+5rxcVFaGo6P/TYnZ2Njw9PXlbiojIAFy+8xDD152BEMDGsQF4oWn1998wNkFBQZg0aRIUCgVMTEywfv36Ml1BNBl+YtJyMOXnMMSk5UJqIsG8vo0xsWsDtdcEU+e2lNrhxtPTE1OmTMH8+fPLrEqqCS+88AIaNmyIdevWVWj/L774Atu2bUNkZMUmDmKfGyIiw1BYLMeAVScRm56HoW3qYfmI1rouyeAlJSXBy8tL5a6LVCpFfHy8MsRUJPyoK6+oBB/uicCf/5TOLj2+szcWvNRMrYCj1T43+fn5ePXVV7USbIDSoeSPt7Q8y5UrV+DmxiGBRETG5uvDUYhNz4OznQUW8HaURkRHR5fpTiKXyxETEwOgNPw8CjYAoFAoMHnyZCQlVW1hTBsLU6wc2RoLB5beldlyJh6L/47U2mriave5mTBhAn777Td88MEHVT75hx9+iP79+8PT0xM5OTnYuXMnQkJCcPDgQQDA/PnzkZycjK1btwIAVq5cCW9vb/j7+0Mmk2Hbtm3YtWsXdu3aVeVaiIhIf1yKz0DQ6TgAwNKhLeBgZabjioyDn58fTExMyrTcPJqS5Wnhp6q3pyQSCcZ39oG5qRQf7onAhpNxMDUxwdy+jdW+RfUsaoebJUuW4KWXXsLBgwfRokULmJmpXnDLly+v8LHu3buHMWPGICUlBQ4ODmjZsiUOHjyI3r17AwBSUlKQkJCg3F8mk2HOnDlITk6GlZUV/P39sX//fgwYMEDdj0FERHqqQCbH+79fhRDA8HYeOpknxVh5eHhg/fr1mDx5MuRyOaRSKdatW6cMLs8KP5ow6rn6KJEr8One61gTehvmpiZ494VGGjs+UIk+N59//jkWLFiAxo0bw8XFpUyH4uPHj2u0QE1jnxsiIv322b4b2HQ6Dq72ljg0qxtbbbQgKSkJMTEx8PX1LdMiExQUVCb8VLXPTXk2norF//aX9ped06cRpvfwe+r+Wu1QXKtWLaxYsQLjx49X5216g+GGiEh/XYjLwMgNZyEEsHl8e/RoXLGZ8UmznhZ+NGlt6G0sPXgTAPBBvyaY0r3hE/dV5/tb7dtSFhYWeP7559V9GxER0VPlFZXg/d//gRDAiAAPBhsd8vDw0GqoeWRK94YoUSjw9eFbWHrwJkylErzVpUGVj6v2kKd33nkH3333XZVPTERE9LgvDkTiTkY+3B0s8fGLFZvrjAzf9B5+mNmz9JbU//ZHYuvZ+CofU+2WmwsXLuD48ePYt28f/P39y3Qo3r17d5WLIiKimiX4Zhq2XygdQPL1K61gb8l+NjXJuy/4oUShwA8ht7Hgr+twsbdEX//KL7OhdrhxdHTE0KFDK31CIiKix2XkyfD+rqsAgDef90HnhnV0XBFVN4lEgvf7NEZWQTF+Pp+AWb+E49fJndCinkPljqdvq4JrGzsUExHpDyEEpm4Pw9/XUuHrbIt907vA0kyq67JIR0rkCrzx40WcjE6Hs50F/pj6PNwdrQAY6KrgRERU8+y5koy/r6XC1ESClSNaM9jUcKZSE3w/qi0audgiLacIE7ZeQm5RidrHqVC4adu2LR4+fFjhg3bp0gXJyclqF0NERDVHcmYBFuy9DgCY9YIfmlfyFgQZF3tLM2wa1x51bC0QmZKNmTuuoESuePYbH1OhPjfh4eH4559/4ORUsWXKw8PD1VofioiIahaFQmDOb/8gp6gEbTwdMaXbk+c3oZrHo5Y1No4NwMj1Z3E8Kg3/OxCJ2d09K/z+Cnco7tWrV4UXuNL0GhFERGRcNp2Jw9nYB7Ayk2LFiNYwlbKXBKlq7emIFSNaY+r2MGw5Ew9Xy4q33lQo3MTFxaldVHVM/kNERIbn1r0cfHkoCgDw8YtN4V3HRscVkb4a0MIN8/o1wbKDN5UzGVdEhcKNl5dXpQsjIiJ6RFaiwKxfwiErUaBH47oY9Vx9XZdEem5KtwaIT8/DjtNRFX4P2wGJiKhaJD7Mx6sbzuJGSjZqWZth2dCW7MZAzySRSPC/Ic3Rwadi/X4BhhsiIqoGf129iwGrTiIsIRN2Fqb4dmQbONtb6rosMhBmUhMsH9G6wvurPUMxERFRReXLSrDwr+v49VISAKCNpyNWvdoGnk7WOq6MDI2DVcWX5GC4ISIirbh2Nwszd15B7P08SCTAtEBfvNPLD2YcGUVapvYV1qBBAzx48KDM9szMTDRoUPVlyomIyLAJIRB0Kg5DfziD2Pt5cLG3wM8TOmBOn8YMNlQt1G65iY+Ph1wuL7O9qKiIsxITEdVwMWk5WPTXDZyMSQcA9G7mgi+HtkQtG3MdV0Y1SYXDzd69e5X/fejQITg4/P802XK5HMeOHYO3t7dGiyMiIsOQmS/DymPR+OncHcgVAuamJvhkQFO83tGLI6Ko2lU43AwZMgRA6ZCscePGqbxmZmYGb29vfPPNNxotjoiI9FuJXIHtFxKw/MgtZBYUAyhtrfmoPyfnI92pcLhRKEqnPfbx8cHFixdRp04drRVFRET672T0fXy+/wZu3csFADR2scOnLzXD8778fiDdUrvPTWWWYiAiIuNx50EePt8fiaOR9wAAtazNMPuFRnjtufpcI4r0QqWGgh87dgzHjh1DWlqaskXnkU2bNmmkMCIi0i+FxXKsDb2NH0JvQ1aigNREgrEdvTDrhUZqzUFCpG1qh5tFixbhs88+Q0BAANzc3NhRjIioBgi+mYYFf11HQkY+AOD5hrWxaJA/fJ3tdFwZUVlqh5u1a9diy5YtGDNmjDbqISIiPZKcWYDP9l3Hoeult6Bc7C3w8YvN8FIL/nFL+kvtcCOTydC5c2dt1EJERHpCVqLAxlOx+O54DAqK5ZCaSPDm8954p1cj2FpwcnvSb2pfoW+99Ra2b9+OTz75RBv1EBFRNRJCICWrELfu5SA6LRe37uXg1r1cxKTlIE9WOmHrcz5O+HxQczR25S0oMgwVCjezZ89W/rdCocD69etx9OhRtGzZEmZmqp3Ili9frtkKiYhI4y7GZ+Crw1GIvJuNnKKScvepa2eB+f2a4OU29XgLigxKhcLNlStXVJ63bt0aAHDt2jWV7bz4iYj0386LCfjkz2solgsAgKmJBN51bNDI2RZ+LnZo5GKHRs628K5jw7WgyCBVKNwEBwdruw4iItKyErkC/zsQiS1n4gEAL7Zww8yefvCpYwNzU4YYMh7sFUZEVANkFRRj+vYw5YKWs19ohBk9fdniTkZJ7XDz8ssvl/uPQSKRwNLSEr6+vhg1ahQaN26skQKJiKhqYtJy8dbWi4h/kA8rMylWjGiFfs3ddF0Wkdao3Q7p4OCA48ePIywsTBlyrly5guPHj6OkpAS//PILWrVqhdOnT2u8WCIiUk9wVBpe/uE04h/ko56jFXa93ZnBhoye2i03rq6uGDVqFFavXg0Tk9JspFAo8M4778DOzg47d+7ElClTMG/ePJw6dUrjBRMRUcVsOROHz/bdgEIA7b1rYc3odqhja6Hrsoi0TiKEEOq8oW7dujh9+jQaNWqksv3WrVvo3Lkz0tPTERERga5duyIzM1OTtWpEdnY2HBwckJWVBXt7e12XQ0SkFZfiMzB83VkAwMgAT3w+uDk7DZNBU+f7W+0rvaSkBDdv3iyz/ebNm5DLSyd8srS0ZCc1IiIdkZUoMH9PBABgWFsPLB3agsGGahS1b0uNGTMGEyZMwIcffoj27dtDIpHgwoULWLx4McaOHQsACA0Nhb+/v8aLJSKiZ1t/8jai03LhZGOOjwc05R+bVOOoHW5WrFgBFxcXfPnll7h379+F1Fxc8O6772LevHkAgD59+qBfv36arZSIiJ4p9n4uVh2PAQB8+mIz1LIx13FFRNVP7T43j8vOzgYAg+q7wj43RGSshBAYtfE8zsY+QFe/Otj6xnNstSGjodU+N4+zt7evUkBYs2YNWrZsqTxOp06d8Pfffz/1PaGhoWjXrh0sLS3RoEEDrF27ttLnJyIyJrvCknE29gEsTE3wv8HNGWyoxqrQbam2bdvi2LFjqFWrFtq0afPUfzBhYWEVPrmHhweWLl0KX19fAMCPP/6IwYMH48qVK+X22YmLi8OAAQMwceJEbNu2DadPn8bUqVNRt25dDBs2rMLnJSIyNg9yi/DFgRsAgFkvNIJXbRsdV0SkOxUKN4MHD4aFRencCEOGDNHYyQcOHKjy/IsvvsCaNWtw7ty5csPN2rVrUb9+faxcuRIA0LRpU1y6dAlff/01ww0R1WhfHIjEw/xiNHG1w1tdfHRdDpFOVSjcLFiwoNz/1iS5XI7ffvsNeXl56NSpU7n7nD17Fn369FHZ1rdvXwQFBaG4uBhmZmZl3lNUVISioiLl80f9hIiIjMWpmHTsvpIMiQRY8nILruRNNV6l/gVkZmZi48aNmD9/PjIyMgCU3o5KTk5W+1gRERGwtbWFhYUFpkyZgj179qBZs2bl7puamgoXFxeVbS4uLigpKUF6enq571myZAkcHByUD09PT7VrJCLSV4XFcnz075w2Yzt6oU39WjquiEj31A43V69eRaNGjbBs2TJ8/fXXylmI9+zZg/nz56tdQOPGjREeHo5z587h7bffxrhx43Djxo0n7v/f/j6PBns9qR/Q/PnzkZWVpXwkJiaqXSMRkb5adTwadzLy4WpviTl9uGAxEVCJcDN79myMHz8e0dHRsLS0VG7v378/Tpw4oXYB5ubm8PX1RUBAAJYsWYJWrVrh22+/LXdfV1dXpKamqmxLS0uDqakpateuXe57LCwslKOxqjq6i4hIn0Sl5mD9iVgAwMJB/rCzLHtrnqgmUjvcXLx4EZMnTy6zvV69emWCR2UIIVT6yDyuU6dOOHLkiMq2w4cPIyAgoNz+NkRExkoIgU/+vIYShUDvZi7o5++q65KI9Iba4cbS0rLcTrlRUVGoW7euWsf68MMPcfLkScTHxyMiIgIfffQRQkJCMHr0aAClt5QeLekAAFOmTMGdO3cwe/ZsREZGYtOmTQgKCsKcOXPU/RhERAZt7z93cSE+A5ZmJlg4kMvdED1O7XAzePBgfPbZZyguLgZQ2tclISEBH3zwgdrDse/du4cxY8agcePG6NWrF86fP4+DBw+id+/eAICUlBQkJCQo9/fx8cGBAwcQEhKC1q1b4/PPP8eqVas4DJyIapTcohJ8cSASADC9hy/qOVrpuCIi/aL28gvZ2dkYMGAArl+/jpycHLi7uyM1NRWdOnXCgQMHYGOj3xNHcfkFIjJ0S/6OxLoTsfCubY1Ds7rBwlSq65KItE6d72+1F860t7fHqVOncPz4cYSFhUGhUKBt27Z44YUXKl0wERFVTExaLoJOxQEAFrzkz2BDVA61w80jPXv2RM+ePTVZCxERPYUQAgv/uo4ShcALTZ3Ro4mzrksi0kuVCjfHjh3DsWPHkJaWBoVCofLapk2bNFIYERGpOng9Fadi0mFuaoJPXix/slMiqkS4WbRoET777DMEBATAzc2Nq84SEVWDApkcn+8rneB0SrcGer0wZlJSEqKjo+Hn5wcPDw9dl0M1kNrhZu3atdiyZQvGjBmjjXqIiKgcP4TE4G5WIeo5WuHt7r66LueJgoKCMGnSJCgUCpiYmGD9+vWYMGGCrsuiGkbtoeAymQydO3fWRi1ERFSO+PQ8rPt3JuJPXmwKK3P97ESclJSkDDYAoFAoMHnyZCQlJem4Mqpp1A43b731FrZv366NWoiIqByf778BmVyBrn510FePZyKOjo4u0w9TLpcjJiZGRxVRTVWh21KzZ89W/rdCocD69etx9OhRtGzZssyyB8uXL9dshURENdixyHs4djMNZlIJFg701+t+jn5+fjAxMVEJOFKpFL6++nsbjYxThcLNlStXVJ63bt0aAHDt2jWV7fr8j46IyNDIShT47N9OxG8+74OGdW11XNHTeXh4YP369Zg8eTLkcjmkUinWrVvHTsVU7dSeodjQcYZiIjIUOy4kYP6eCNSxtUDInEDYWlR6arJqlZSUhJiYGPj6+jLYkMZodYZiIiLSPlmJAquDS/uqvN29ocEEG6C0BYehhnRJ7Q7FRESkfb9dTkRyZgGc7SwwukN9XZdDZFAYboiIqigpKQnBwcEaG/JcVCLH94+12lia6efQbyJ9xXBDRFQFQUFB8PLyQs+ePeHl5YWgoKAqH/PXS0m4m1UIF3sLvPYcW22I1MVwQ0RUSdqYtK6oRI4fQkpbbaZ292WrDVElVCrc/PTTT3j++efh7u6OO3fuAABWrlyJP//8U6PFERHpM21MWvfLxUSkZBXC1d4SI9t7VrVEohpJ7XCzZs0azJ49GwMGDEBmZibkcjkAwNHREStXrtR0fUREeuvRpHWPq8qkdYXFcnz/b6vNtED2tSGqLLXDzXfffYcNGzbgo48+glT6///wAgICEBERodHiiIj02aNJ6x79LqzqpHU7LybgXnYR3B0sMYKtNkSVpvbECXFxcWjTpk2Z7RYWFsjLy9NIUUREhmLChAno27dvlSetKyyW44eQ2wCAqT18YWHKVhuiylI73Pj4+CA8PBxeXl4q2//++280a9ZMY4URERkKTUxat/1CAtJyilDP0Qoj2rHVhqgq1A4377//PqZNm4bCwkIIIXDhwgXs2LEDS5YswcaNG7VRIxGRUSsslmNNaGmrzbQevjA35UBWoqpQO9y88cYbKCkpwdy5c5Gfn49Ro0ahXr16+Pbbb/Hqq69qo0YiIqO27fwd3P+31WZ4Wy5bQFRVlVqsZOLEiZg4cSLS09OhUCjg7Oys6bqIiGqEApkca0NjAQAzerLVhkgT1P5XtGjRIty+Xdp8WqdOHQYbIqIq2HouHum5RfCsZYVhbLUh0gi1w82uXbvQqFEjdOzYEatXr8b9+/e1URcRkdFLzy3C6uOl89q806sRzKRstSHSBLX/JV29ehVXr15Fz549sXz5ctSrVw8DBgzA9u3bkZ+fr40aiYiM0jeHo5BTVIIW9RwwtE09XZdDZDQkQghRlQOcPn0a27dvx2+//YbCwkJkZ2drqjatyM7OhoODA7KysmBvb6/rcoiohrp+NwsvrT4FIYDfJ3dCgLeTrksi0mvqfH9XuQ3UxsYGVlZWMDc3R3FxcVUPR0Rk9IQQWLTvBoQABrZ0Z7Ah0rBKhZu4uDh88cUXaNasGQICAhAWFoaFCxciNTVV0/URERmdv6+l4kJcBizNTPBB/ya6LofI6Kg9FLxTp064cOECWrRogTfeeEM5zw0RET1bYbEci/+OBABM7tYQ9RytdFwRkfFRO9z06NEDGzduhL+/vzbqISIyahtPxSLpYQHcHCwxpVtDXZdDZJTUDjeLFy/WRh1EREYvNatQuTjmB/2awMqci2MSaUOlZihOSkrC3r17kZCQAJlMpvLa8uXLNVIYEZGx+fLQTeTL5GjnVQuDWrnruhwio6V2uDl27BgGDRoEHx8fREVFoXnz5oiPj4cQAm3bttVGjUREBu9KwkPsvpIMAPj0xWaQSCQ6rojIeKk9Wmr+/Pl47733cO3aNVhaWmLXrl1ITExE9+7d8corr2ijRiIig6ZQlA79BoDh7TzQytNRtwURGTm1w01kZCTGjRsHADA1NUVBQQFsbW3x2WefYdmyZRovkIjI0P35TzLCEzNhYy7F3D6NdV0OkdFTO9zY2NigqKgIAODu7q5cRBMA0tPTNVcZEZERuJtZgCV/3wQATO3hC2d7Sx1XRGT81O5z07FjR5w+fRrNmjXDiy++iPfeew8RERHYvXs3OnbsqI0aiYgMUlp2IUZtPIe0nCI0rGuDCc/76LokohpB7XCzfPly5ObmAgAWLlyI3Nxc/PLLL/D19cWKFSs0XiARkSF6kFuE0UHnEf8gH/UcrfDTmx1gacah30TVQe3bUg0aNEDLli0BANbW1vjhhx9w9epV7N69G15eXmoda8mSJWjfvj3s7Ozg7OyMIUOGICoq6qnvCQkJgUQiKfO4efOmuh+FiEgrsgqKMWbTBUSn5cLV3hI7JnaEO2ciJqo2aoebjz76CEeOHEF+fn6VTx4aGopp06bh3LlzOHLkCEpKStCnTx/k5eU9871RUVFISUlRPvz8/KpcDxFRVeUUFmPspgu4kZKNOrbm+PmtDqjvZK3rsohqFLVvS12+fBnfffcdioqK0LZtWwQGBqJ79+7o0qULbG1t1TrWwYMHVZ5v3rwZzs7OuHz5Mrp16/bU9zo7O8PR0fGZ5ygqKlJ2gAZKl0wnItKGfFkJJvx4Cf8kZcLRygzbJnRAw7rq/V4koqpTu+Xm4MGDePjwIUJCQjB48GBcuXIFI0eOhJOTU5U7FGdlZQEAnJycnrlvmzZt4Obmhl69eiE4OPiJ+y1ZsgQODg7Kh6enZ5VqJCIqT2GxHJN+uowL8RmwszTFtgkd0MTVXtdlEdVIEiGEqOybo6KiEBISgqNHj+KPP/6Ao6Mj7t+/X6ljCSEwePBgPHz4ECdPnnzqOU+cOIF27dqhqKgIP/30E9auXYuQkJByW3vKa7nx9PREVlYW7O35i4fImBQWy3EhLgOZBcXIKypBnqwEeUVy5MtKkFtUgvwiOTydrDGktTsaaLBFJaewGO/sDMfxqDRYm0vx05sd0M6rlsaOT0Sl398ODg4V+v5WO9ysWbMGoaGhCA0NhVwuR9euXdG9e3cEBgYqOxpXxrRp07B//36cOnUKHh4ear134MCBkEgk2Lt37zP3VeeHQ0SGIyEjH5N+uoSbqTkV2r+VhyOGta2Hl1q6w8nGvMLnEUIg6WEBLt95iEt3MnA5IRNRqdlQCMDSzARbxj+Hjg1qV/ZjENETaDXcmJiYoG7dunjvvfcwZcoUjQSEGTNm4I8//sCJEyfg46P+PBBffPEFtm3bhsjIyGfuy3BDZHxO3LqPGTuvIKugGI5WZmjiZgdbC1NYm5vCxsIUNuZS2FiYwsLUBBfiMnAyJh1yRemvPlMTCQIbO2Nom3ro2cQZpiYSPMwvxsN8GTLyZHiYL8ODPBkycmW4mZqNS3ceIi2nqEwN3rWt8b8hLdDFt051f3yiGkGr4eZRCAkJCcGNGzfQqlUrBAYGIjAwEF27dlWrU7EQAjNmzMCePXsQEhJS6RFPw4cPR0ZGBo4fP/7MfRluiIyHEALrTsTiy0M3oRBAa09HrB3dDq4OT58F+H5OEfb+cxd7riTh2t3/H2RgJpWgWP7sX4mmJhL4uzsgwKsWArxroV39Wpx5mEjLtBpuHpeVlYWTJ0/i999/x/bt2yGRSFT6tzzL1KlTsX37dvz5559o3Pj/11txcHCAlVXpnBDz589HcnIytm7dCgBYuXIlvL294e/vD5lMhm3btmHp0qXYtWsXhg4d+sxzMtwQGYd8WQne//0q9kekAABGBnjis8H+sDBVb6K8W/dysOdKMv4IT0ZKVqFyu6OVGZxszFHLxhy1rM1R28Yc9WtbI8CrFlrWc4SVOSfkI6pO6nx/qz0UHAAyMjIQGhqKkJAQhISE4Nq1a6hduza6d++u1nHWrFkDAAgMDFTZvnnzZowfPx4AkJKSgoSEBOVrMpkMc+bMQXJyMqysrODv74/9+/djwIABlfkoRGSA7jzIw+Rtl3EzNQemJhIsGOiP1zvUh0QiUftYjVzsMK9fE7zfpzESH+bDxsIUjlZmMJWqPZiUiPSE2i03LVu2xI0bN+Dk5IRu3bopb0k1b95cWzVqFFtuiAxb6K37mPlv/5o6thZYM7ot2ns/e/oIIjJsWm25mTRpkkGFGSIyDoXFcnx9OApBp+Mg1OhfQ0Q1j9rhZvr06dqog4joia4lZ+HdX8MRnVa6aO+o5+pjwcBmavevIaKaoVJ9boiIqkOJXIE1obfx7bFolCgE6thaYNnQFujV1EXXpRGRHmO4ISK9FJeeh9m/huNKYiYAoJ+/K74Y0hy1bS10WxgR6T2GGyLSK0IIbDt3B4v/vomCYjnsLE3x2SB/DGldr1KjoYio5lE73CQkJMDT07PMLxkhBBITE1G/fn2NFUdENUthsRyzfw3HgWupAIDODWvj6+Gt4O5opePKiMiQqB1ufHx8kJKSAmdnZ5XtGRkZ8PHxgVwu11hxRFRzPMyTYeJPl3DpzkOYS03wQf8mGN/JGyYmbK0hIvWoHW6EEOU2Defm5sLSkkMyiUh9iRn5GLflAmLv58HO0hTrxwSgExefJKJKqnC4mT17NgBAIpHgk08+gbW1tfI1uVyO8+fPo3Xr1hovkIiMW0RyFt7YchHpuUVwd7DEljeeQyMXO12XRUQGrMLh5sqVKwBKW24iIiJgbm6ufM3c3BytWrXCnDlzNF8hERmtkKg0TN0ehnyZHE1c7bBl/HOclI+IqqzC4SY4OBgA8MYbb+Dbb7/l0gVEVCW/XkrE/D0RkCsEuvjWwZrRbWFnaabrsojICKjd52bz5s3aqIOIagghBFYdj8GKo7cAAEPb1MPSoS1hbsqFKolIM9QON3l5eVi6dCmOHTuGtLQ0KBQKlddjY2M1VhwRGZ8dFxOVwWZaYEPM6dOY89cQkUapHW7eeusthIaGYsyYMXBzc+MvJSKqsKtJmVi49zoAYE6fRpjew0/HFRGRMVI73Pz999/Yv38/nn/+eW3UQ0RG6mGeDG//HAaZXIE+zVwwLdBX1yURkZFS+yZ3rVq14OTkpI1aiMhIKRQCs34NR3JmAbxrW+PrV1qx1ZeItEbtcPP555/j008/RX5+vjbqISIj9F1wDEJv3YelmQnWjG4He46KIiItUvu21DfffIPbt2/DxcUF3t7eMDNT/SUVFhamseKIyPCF3rqPlcdKOxB/MaQFmrpxGgki0i61w82QIUO0UAYRGaOkh/l4Z+cVCAGMeq4+hrX10HVJRFQDqB1uFixYoI06iMjIFJXIMW17GDILitGyngM+famZrksiohqCs2YRkVZ8vu8G/knKgqOVGb4f3RaWZlJdl0RENYTaLTdyuRwrVqzAr7/+ioSEBMhkMpXXMzIyNFYcERmmXWFJ2HY+ARIJsHJka3jWsn72m4iINETtlptFixZh+fLlGDFiBLKysjB79mwMHToUJiYmWLhwoRZKJCJDcjE+A/N3RwAAZvTwQ2BjZx1XREQ1jdrh5ueff8aGDRswZ84cmJqa4rXXXsPGjRvx6aef4ty5c9qokYgMRHx6Hib9dAkyuQL9/F0xqxdnICai6qd2uElNTUWLFi0AALa2tsjKygIAvPTSS9i/f79mqyMig5GZL8ObP17Ew/zSDsQrRrSGiQkn6iOi6qd2uPHw8EBKSgoAwNfXF4cPHwYAXLx4ERYWFpqtjogMgqxEgSk/X0Zseh7cHSyxcWwArMzZgZiIdEPtcPPyyy/j2LFjAIB33nkHn3zyCfz8/DB27Fi8+eabGi+QiPSbEAIf/hGBc7EZsLUwRdC49nC2t9R1WURUg0mEEKIqBzh//jxOnz4NX19fDBo0SFN1aU12djYcHByQlZUFe3vOlEpUVd+HxOCrQ1EwkQBB49qjBzsQE5EWqPP9rfZQ8P/q0KEDOnToUNXDEJEB2nf1Lr46FAUAWDTQn8GGiPSC2rellixZgk2bNpXZvmnTJixbtkwjRRGR/gtLeIjZv/0DAHijszfGdPLWbUFERP9SO9ysW7cOTZo0KbPd398fa9eu1UhRRElJSQgODkZSUpKuS6FypOcWlQ75LlGgVxNnfPwil1YgIv1RqaHgbm5uZbbXrVtXOYqKqCqCgoLg5eWFnj17wsvLC0FBQbouif5j1bFopOfK0NjFDqtebQMph3wTkR5RO9x4enri9OnTZbafPn0a7u7uGimKaq6kpCRMmjQJCoUCAKBQKDB58mS24OiR+PQ8bL+QAABYMLAZbCyq3HWPiEij1P6t9NZbb2HWrFkoLi5Gz549AQDHjh3D3Llz8d5772m8QKpZoqOjlcHmEblcjpiYGHh4eOioKnrcV4ejUKIQCGxUF50b1tF1OUREZagdbubOnYuMjAxMnTpVuWimpaUl5s2bh/nz52u8QKpZ/Pz8YGJiohJwpFIpfH19dVgVPfJPYib2R6RAIgHm9Svb946ISB+ofVtKIpFg2bJluH//Ps6dO4d//vkHGRkZ+PTTT7VRH9UwHh4eWL9+PaTS0tltpVIp1q1bx1YbPSCEwNKDNwEAL7euh6ZunCeKiPRTlSfxMzScxM8wJCUlISYmBr6+vgw2eiIkKg3jt1yEuakJgt8LRD1HK12XREQ1iMYn8Rs6dCi2bNkCe3t7DB069Kn77t69u+KVktYlZuTjt8tJKFEoYCY1gbmpCSz+/d9Hz+vYWqBFPQc42ZjrulwlDw8Phho9Ilf8f6vNuE5eDDZEpNcqFG4cHBwgkZQO9bS3t1f+d1UtWbIEu3fvxs2bN2FlZYXOnTtj2bJlaNy48VPfFxoaitmzZ+P69etwd3fH3LlzMWXKFI3UZCzkCoHNZ+LwzeFbKCiWV+g99Ryt0NLDAS3q/f/D0Vp/Ag/pzp/hybiZmgM7S1NMC2T/JyLSbxUKNy+//DIsLUsXwtuyZYvGTh4aGopp06ahffv2KCkpwUcffYQ+ffrgxo0bsLGxKfc9cXFxGDBgACZOnIht27bh9OnTmDp1KurWrYthw4ZprDZDdjM1G/N2ReCfpEwAQHvvWmju7gCZXAFZiQLF//6vTC4gK1Eg6WE+YtPzkJxZgOTMAvx9LVV5rPpO1mhRzwEtPRzQ0sMRzd3tYWdppqNPRrpQWCzHN0duAQCmBvoy8BKR3qtQnxupVIrU1FTUrVsXUqkUKSkpcHbW/Boy9+/fh7OzM0JDQ9GtW7dy95k3bx727t2LyMhI5bYpU6bgn3/+wdmzZ595DmPuc1NUIsf3wTH4IeQ2ShQCdpam+LB/U4wM8ITJMyZZyy4sxvW72YhIysTV5CxEJGXhTkZ+mf0kEqBBHRu0rOeIlh4O6OpXB77Odtr6SKQHNp6Mxf8ORMLV3hIhcwJhaSbVdUlEVANpvM9N3bp1ce7cOQwcOBBCCI3dlvqvrKwsAICTk9MT9zl79iz69Omjsq1v374ICgpCcXExzMxUWxWKiopQVFSkfJ6dna3BivXH5TsZmLc7AjFpuQCAPs1c8Png5nCxt6zQ++0tzdCpQW10alBbuS0zX4Zrd7NxNSkTEclZuJqUheTMAty+n4fb9/OwJzwZUhMJPhrQFG909tbadUG6k1VQjNXBMQCA2b0bMdgQkUGoULiZMmUKBg8eDIlEAolEAldX1yfuK5dXrH/HfwkhMHv2bHTp0gXNmzd/4n6pqalwcXFR2ebi4oKSkhKkp6eXWRpiyZIlWLRoUaVqMgRyhcCSvyMRdDoOQgB1bC3w2SB/9G/uWuWw4Whtji6+ddDF9/8nakvPLULEvy07Z2Mf4GzsA3y27wau383GF0Oa88vPyKwJvY3MgmI0crHFsLbs4E1EhqFC4WbhwoV49dVXERMTg0GDBmHz5s1wdHTUaCHTp0/H1atXcerUqWfu+98v7Ud31sr7Mp8/fz5mz56tfJ6dnQ1PT88qVqsfZCUKvPtrOPZHlK7p9Uo7D3w0oKlW+0TUsbVAj8bO6NHYGTN6+mLT6Xh8ceAGdoUlISYtF+vHtKtwaxHpt5SsAmw+HQcAmNe3CdePIiKDUeEZips0aYImTZpgwYIFeOWVV2Btba2xImbMmIG9e/fixIkTzxz+6+rqitTUVJVtaWlpMDU1Re3atcvsb2FhAQsLC43Vqi8KZHK8/fNlhNy6DzOpBN+ObIMBLcouaKpNEokEE7r4oLGrHaZvD8M/SZl4afUprB3dDu28alVrLaR53xy5haISBZ7zdkLPJprvY0dEpC1qz1C8YMECjQUbIQSmT5+O3bt34/jx4/Dx8Xnmezp16oQjR46obDt8+DACAgLK9LcxVjmFxRi35QJCbt2HpZkJgsa2r/Zg87guvnWwd3oXNHaxw/2cIry24Rx+vZSos3qo6i7FZ+D3y6WLlc7v34T9qYjIoFRotFTbtm1x7Ngx1KpVC23atHnqL7qwsLAKn3zq1KnYvn07/vzzT5W5bRwcHGBlVTpJ2Pz585GcnIytW7cCKB0K3rx5c0yePBkTJ07E2bNnMWXKFOzYsaNCQ8ENfbRURp4M4zdfwNXkLNhZmGLz+PYI8H5yB+zqlFdUgjm//6McSj6ukxc+frEZzKRqZ2jSoWK5Ai99dwpR93LwantPLB3aUtclERFpfrTU4MGDlbd2hgwZUuUCH1mzZg0AIDAwUGX75s2bMX78eABASkoKEhISlK/5+PjgwIEDePfdd/H999/D3d0dq1atqhFz3NzLLsTrQecRnZYLJxtzbH3zOTR3d9B1WUo2Fqb4/rW2WB0cg+VHb+HHs3eQkVeMVa+25l/+BmTz6ThE3cuBk4055vXl4phEZHi4tpSBSMjIx+iN55D4sACu9pbYNqEDfJ1tdV3WEx26nopp28NQohB4v29jzmprIO5mFuCFFaHIl8nx5bCWGBFgHJ3vicjwqfP9Xen7BTKZDElJSUhISFB5kGbJShT4+1oKXll3BokPC+DlZI3fpnTS62ADAH39XbFokD8A4OvDUTgaeU/HFVFFfLbvBvJlcrT3roXhHPpNRAaqwqOlHrl16xYmTJiAM2fOqGx/NLlfZee5IVWRKdn47XIS/ghPRkaeDADQ2MUOP735HJwNZKj16A5eiEzJxrbzCZj1Szj2vN0Zfi6czVhfBd9Mw8HrqZCaSPD54ObPnNWaiEhfqR1u3njjDZiammLfvn1wc3NjXwoNyiooxt7wZPx6OQkRyVnK7S72FhjW1gOTuzWEg5VhjQhbMNAfMfdzcS42A29tvYQ/pz3PtYn0UIFMjk/3XgMATHjeB01cDeeWLRHRf6kdbsLDw3H58mU0acKOhppy+34uvg+Owb6IFMhKFAAAM6kELzR1wYh2nujqVwemBjriyExqgh9GtcOg70/hTkY+pu+4gi3j2xvs5zFW34fEIPFhAdwdLPFOLz9dl0NEVCVqh5tmzZohPT1dG7XUOLH3c/Hd8Rj8+U8yFP92627iaocRAZ4Y0roenGyMo4XDycYcG8YEYNjaMzgVk44vDkRiwUB/XZdF/4pJy8W6E7cBAJ8O9IeNhdq/FoiI9Irav8WWLVuGuXPnYvHixWjRokWZifMMaQSSrsSl5+G749H4I/z/Q03vZi6YFuiLVh4ORnmrr6mbPZa/0gpTfg7D5jPxaOpmz5E4ekAIgU/3XkOxXKBH47ro28zl2W8iItJzag8FNzEpvZ1Q3vpOhtChWJdDwePT8/BdcAz+CE+G/N9U80JTZ8zq1QjN6+nPfDXatPLoLaw8Fg0zqQQ7J3ZEOy/9mICwpvozPBnv/BIOC1MTHHm3O+o7aW5ZFSIiTdL4JH6PCw4OrnRhNYlcIRCdloOrSVkIT8zE1aRM3EjJVrbU9GrijHd6+aGlh6NO66xuM3v6IepeDv6+lorJ2y5jx1sdOYJKR7IKivH5/kgAwIyevgw2RGQ01A433bt310YdBk8IgZPR6TgRfR9Xk7Jw7W4W8mVlW7F6NK6LWb0aoZWnY/UXqQdMTCT4engr3HmQjxsp2Ri54ZzezbRcUyw9eBPpuUVoUNcGE7s20HU5REQao3a4uXr1arnbJRIJLC0tUb9+faNchftpbt/PxaK/buBE9H2V7TbmUrTwcEArD0e09HBEa09H1HO00lGV+sPGwhQ/T+iAsZsvICI5C69tOIct45/jSuLV6HzcA+y4UDrp5pKXW8DCVKrjioiINKdSfW6e1uHVzMwMI0eOxLp162BpqX+TzWmyz01uUQm+Ox6NTafjUCwXMJeaYGjbegjwckIrDwc0qGsLKSdCe6LswmK8ueUiLt15CGtzKTaODUDnhnV0XZbRKyyWY8B3JxF7Pw+vtffEEi6MSUQGQKvLL+zZswd+fn5Yv349wsPDceXKFaxfvx6NGzfG9u3bERQUhOPHj+Pjjz+u9AfQd0II/BmejF7LQ7DuRCyK5QI9Gzvj8KxuWDq0JYa384Cfix2DzTPYW5ph65vPoYtvHeTL5Hhjy0UE30zTdVlG74eQGMTez0NdOwt80L+prsshItI4tVtunnvuOXz++efo27evyvZDhw7hk08+wYULF/DHH3/gvffew+3btzVarCZUteUmMiUbC/66jgtxGQCA+k7WWPBSM/RqyiG0lVVYLMf0HWE4GpkGM6kEq15tg/7N3XRdllG6dS8HL353EsVygR9GtcWAFvw5E5Fh0GrLTUREBLy8vMps9/LyQkREBACgdevWSElJUffQem93WBJeWn0KF+IyYGlmgvd6N8LhWd0YbKrI0kyKNaPb4aWWbiiWC0zbHobdYUm6LsvoKBQCH+y+imK5wAtNXdC/uauuSyIi0gq1w02TJk2wdOlSyGQy5bbi4mIsXbpUuSRDcnIyXFyM6ws/M1+GRftuQK4Q6NPMBcdmB2JGTz9YmrEjpiaYSU3w7cg2eKWdBxQCeO/3fzBtexi2nb+D2/dzoWYDI5Vj2/k7CEvIhK2FKT4f7G+Uk0USEQGVGC31/fffY9CgQfDw8EDLli0hkUhw9epVyOVy7Nu3DwAQGxuLqVOnarxYXfrueAyyCorR2MUOP4xqy7WRtEBqIsGyoS1hY26KLWfjsT8iBfsjSlsAne0s0KlBbXRsUBudGtSGV21rfjmrISWrAF8eigIAzO3bGG4OHLVHRMZL7T43AJCbm4tt27bh1q1bEEKgSZMmGDVqFOzs9H8ytsr0uYlLz0OflaEolgv89OZz6OpXV8tV1mxCCIQlZOJUTDrOxqYjLCFTuaDoI45WZqhrZ4E6thaobWuOOrYWqPPv/zrZmMNEIoFcISBXCJQoBOQKBeQKQK5QwMnGAt0b1YW5ac0IqEIITPzpMo5G3kPb+o74fXJnmLCzOxEZGHW+vysVbgxZZcLNpJ8u4fCNe+jRuC42j39OyxXSfxUWy3ElMRNnbz/AudgHuJL4EMXyql22de0s8Fr7+hj1XH24OujflAWadCAiBVO3h8FMKsH+GV3RiDNCE5EB0vjyC3v37kX//v1hZmaGvXv3PnXfQYMGVbxSA3A29gEO37gHqYkEHw3gsFldsDSTotO/t6MAoEAmx52MPDzIlSE9twjpuTI8yCtCem4RHuTK8CBPBiEAU6kEUokEUhMJTE0kMDEpfR5xNwv3c4qw6ng0vg+JQd9mLhjTyRsdfZyM7lZXVkExFvx1HQDwdveGDDZEVCNUqOXGxMQEqampcHZ2Vi6cWe7BjGzhTLlCYND3p3D9bjbGdvTCZ4ObV1OVpE2yEgUO3UjFT2fv4EJ8hnJ7IxdbjOngheHtPGFlbvgdxRUKgVm/hmPvP3fRoK4NDszoyg7wRGSwNN5yo1Aoyv1vY7f7ShKu382GnaUp3unlp+tySEPMTU0wsKU7BrZ0R2RKNn46dwd7riTj1r1cfLL3On4PS8LWNzvAwcpM16VWmhACn+27gb3/3IXURIKlL7dksCGiGqNm9KishHxZCb76d3TJjB6+qG1bs9bLqimautlj8cstcP7DXljwUjM42Zjjn6QsjAk6j6yCYl2XV2nfHLmFLWfjAQBfD2+J53ycdFsQEVE1qnC4OX/+PP7++2+VbVu3boWPjw+cnZ0xadIkFBUVabxAXVkbGou0nCLUd7LGuM7eui6HtMze0gxvPO+D7W91gJONOa4mZ+F1Aw04a0NvY3VwDADg80H+eLmNh44rIiKqXhUONwsXLlRZETwiIgITJkzACy+8gA8++AB//fUXlixZopUiq1tKVgHWnyxdOmJ+/yZcMbkGaeJqjx1vdYSTjTkiDDDgbDt/B0sP3gQAzOvXBGM6eeu2ICIiHahwuAkPD0evXr2Uz3fu3IkOHTpgw4YNmD17NlatWoVff/1VK0VWt68ORaGwWIH23rXQz59T1Nc0jV3tsOOtjqj9b8AZvfEcMvNlz36jjv1xJRmf/HkNADA1sCHe7t5QxxUREelGhcPNw4cPVZZUCA0NRb9+/ZTP27dvj8TERM1WpwNXkzKx+0oyAODjAc2MbmgwVUxjVzts/zfgXLubjdFB5/U64By+kYr3fv8HQgBjO3rh/T6NdV0SEZHOVDjcuLi4IC4uDgAgk8kQFhaGTp06KV/PycmBmZnhji4BSkeY/G9/JADg5db10MrTUbcFkU41drXDjokdUcfWHNf1OOCciknH9O1XIFcIDG1TDwsHct0oIqrZKhxu+vXrhw8++AAnT57E/PnzYW1tja5duypfv3r1Kho2NOxm8KtJWbgQnwELUxO835d/+RLQyKX0FtWjgDNq43mk5+pPx/krCQ8x6adLkMkV6Ofvii+HteTSCkRU41U43Pzvf/+DVCpF9+7dsWHDBmzYsAHm5ubK1zdt2oQ+ffpopcjq8miRxt7NXODuyIUFqZTfYwHnRko2hq05gzsP8nRdFmLScvHmjxeRL5Ojq28dfPtqay7oSkSESqwtlZWVBVtbW0ilqiOIMjIyYGtrqxJ49NGTZjgUQqDLl8FIzizA2tFt0a+5mw6rJH0Uez8X4zZfQOLDAtS2Mcfm8e3R0sNRJ7WkZhVi2NozSM4sQCsPB2x/qyNsLCo0JycRkUFSZ4Zitf/Mc3BwKBNsAMDJyUnvg83ThCdmIjmzANbmUgQ2dtZ1OaSHGtS1xa63O8Pf3R4P8mR4dcM5BEelVXsdWQXFGLf5ApIzC+BT2wabxrVnsCEiegzbsP/16JbUC01dOE09PZGznSV+mdQJXX3rIF8mx1tbL+G3y9U3SrCwWI6JWy8h6l4OnO0ssHXCc5w9m4joPxhuULrA4IF/w82LLXg7ip7O1sIUQePa4+XW9SBXCLz/+1V8HxwDNe/wqq1ErsDMnVdwIT4Ddham+PGN5+BZy1qr5yQiMkQMNwCuJGbiblYhbMyl6N6orq7LIQNgbmqCb15phcndGgAAvjochU/3XodcoZ2AI4TAJ3uv4/CNezA3NcGGsQFo6vb0e85ERDUVww1UR0nxlhRVlImJBPP7N8WCl5pBIgF+OncH4zZfwN3MAo2fa8XRaOy4kAATCbBqZGt0bFBb4+cgIjIWNT7cqN6SctfaeZKSkhAcHIykpCStnYN0443nfbD6tbawMDXBqZh09F15Ar9cTNDIbSohBNaduI1Vx6MBAJ8Pbs6RfEREz1Djw01YwkOkZhfCzsIUXf3qaOUcQUFB8PLyQs+ePeHl5YWgoCCtnId058UWbjgwsyva1ndETlEJ5u2OwPgtF5GSVflWnKyCYkzdHoYlf5cuhDmrlx9Gd/DSVMlEREarxoebfVq+JZWUlIRJkyZBoVAAABQKBSZPnswWHCPUsK4tfpvcGR/2bwJzUxOE3rqPPitO4NdLiWq34oQnZuLF707i72upMJNK8MmLzfBOLz8tVU5EZFxqdLipjlFS0dHRymDziFwuR0xMjFbOR7olNZFgUreGODCjK1p7lrbizN11FW/+eBGpWYXPfL8QAhtPxeKVdWeQ9LAAnrWs8PvkzpjQxYfrRRERVZBOw82JEycwcOBAuLu7QyKR4I8//njq/iEhIZBIJGUeN2/erNT5L915iLScIthZmqKLlm5J+fn5wcRE9ccslUrh6+urlfORfvB1tsWuKZ3xQb/SVpzgqPvo/nUwXg86j++DY3D5TgaK5aqhNzNfhok/Xcb/9keiWC7Qv7kr9s3oygVciYjUpNNpTfPy8tCqVSu88cYbGDZsWIXfFxUVpTL1ct26lRu+vT/iLgCgTzNXWJhqZ5SUh4cH1q9fj8mTJ0Mul0MqlWLdunXw8PDQyvlIf0hNJJjSvSFeaOqMOb9fRXhiJk7FpONUTDoAwNpcigAvJ3Rs4IT6TtZYfCASd7MKYS41wScvNsXrHb3YWkNEVAk6DTf9+/dH//791X6fs7MzHB0dq3RuuULg72upAICXtDxx34QJE9C3b1/ExMTA19eXwaaG8XW2w563OyMmLRdnYx/gbOwDnIt9gIf5xTgRfR8nou8r9/WubY3Vo9qiubuDDismIjJsBrkgTZs2bVBYWIhmzZrh448/Ro8ePZ64b1FREYqKipTPs7OzAQBXEkpvSdlbmuJ5X+3cknqch4cHQ00NJpFI4OdiBz8XO4zt5A2FQuBWWg7O3n6Ac3EPcC05G8/71sanL/nDlutEERFViUH9FnVzc8P69evRrl07FBUV4aeffkKvXr0QEhKCbt26lfueJUuWYNGiRWW2H7pe2mrTx98V5qY1ul816YCJiQRNXO3RxNUebzzvo+tyiIiMikRoe0GcCpJIJNizZw+GDBmi1vsGDhwIiUSCvXv3lvt6eS03np6eaP3xH3hYYorN49ujB1cBJyIi0mvZ2dlwcHBAVlaWSr/b8hh8k0XHjh0RHR39xNctLCxgb2+v8gCAB3kyOFiZ4fmG2r8lRURERNXH4MPNlStX4OZWuQ7Bff1deEuKiIjIyOi0z01ubq7KZHZxcXEIDw+Hk5MT6tevj/nz5yM5ORlbt24FAKxcuRLe3t7w9/eHTCbDtm3bsGvXLuzatatS59fmWlJERESkGzoNN5cuXVIZ6TR79mwAwLhx47BlyxakpKQgISFB+bpMJsOcOXOQnJwMKysr+Pv7Y//+/RgwYIDa53awNEXnhlxZmYiIyNjoTYfi6vKoQ9Ksn05jxeuddV0OERERVUCN6lBcWX39XXVdAhEREWlBjQ03HXx4S4qIiMgY1dhwIzXhmj1ERETGqMaGGyIiIjJODDdERERkVBhuiIiIyKgw3GhQUlISgoODkZSUpOtSiIiIaiyGGw0JCgqCl5cXevbsCS8vLwQFBem6JCIiohqpxk7iV5FJgCoqKSkJXl5eUCgUym1SqRTx8fHw8PDQyDmIiIhqMk7iV82io6NVgg0AyOVylXWziIiIqHow3GiAn58fTExUf5RSqRS+vr46qoiIiKjmYrjRAA8PD6xfvx5SqRRAabBZt24db0kRERHpAPvcaFBSUhJiYmLg6+vLYENERKRB6nx/m1ZTTTWCh4cHQw0REZGO8bYUERERGRWGGyIiIjIqDDdq4AzERERE+o/hpoI4AzEREZFh4GipCuAMxERERLrFGYo1jDMQExERGQ6GmwrgDMRERESGg+GmAjgDMRERkeFgnxs1cAZiIiIi3eAMxVrCGYiJiIj0H29LERERkVFhuCEiIiKjwnBDRERERoXhhoiIiIwKww0REREZFYYbIiIiMioMN0RERGRUGG6IiIjIqDDcEBERkVFhuCEiIiKjwnBDRERERoXhhoiIiIwKww0REREZFYab/0hKSkJwcDCSkpJ0XQoRERFVAsPNY4KCguDl5YWePXvCy8sLQUFBui6JiIiI1KTTcHPixAkMHDgQ7u7ukEgk+OOPP575ntDQULRr1w6WlpZo0KAB1q5dq5FakpKSMGnSJCgUCgCAQqHA5MmT2YJDRERkYHQabvLy8tCqVSusXr26QvvHxcVhwIAB6Nq1K65cuYIPP/wQM2fOxK5du6pcS3R0tDLYPCKXyxETE1PlYxMREVH1MdXlyfv374/+/ftXeP+1a9eifv36WLlyJQCgadOmuHTpEr7++msMGzasSrX4+fnBxMREJeBIpVL4+vpW6bhERERUvQyqz83Zs2fRp08flW19+/bFpUuXUFxcXO57ioqKkJ2drfIoj4eHB9avXw+pVAqgNNisW7cOHh4emv0QREREpFUGFW5SU1Ph4uKiss3FxQUlJSVIT08v9z1LliyBg4OD8uHp6fnE40+YMAHx8fEIDg5GfHw8JkyYoNH6iYiISPsMKtwAgEQiUXkuhCh3+yPz589HVlaW8pGYmPjU43t4eCAwMJAtNkRERAZKp31u1OXq6orU1FSVbWlpaTA1NUXt2rXLfY+FhQUsLCyqozwiIiLSAwbVctOpUyccOXJEZdvhw4cREBAAMzMzHVVFRERE+kSn4SY3Nxfh4eEIDw8HUDrUOzw8HAkJCQBKbymNHTtWuf+UKVNw584dzJ49G5GRkdi0aROCgoIwZ84cXZRPREREekin4ebSpUto06YN2rRpAwCYPXs22rRpg08//RQAkJKSogw6AODj44MDBw4gJCQErVu3xueff45Vq1ZVahh4cnKyZj4EERER6RWJeNQjt4bIzs6Gg4MDJBIJNmzYwBFRREREBuDR93dWVhbs7e2fuq9B9bnRJCEEl1cgIiIyQjU23ABcXoGIiMgY1ehww+UViIiIjE+NDTcmJiZcXoGIiMgIGdQkfpp07do1NG3aVNdlEBERkYbV2JabevXq6boEIiIi0oIaG26IiIjIODHcEBERkVFhuCEiIiKjwnBDRERERoXhhoiIiIwKww0REREZFYYbIiIiMioMN0RERGRUGG6IiIjIqDDcEBERkVGpcWtLCSEAANnZ2TquhIiIiCrq0ff2o+/xp6lx4ebBgwcAAE9PTx1XQkREROp68OABHBwcnrpPjQs3Tk5OAICEhIRn/nCo6tq3b4+LFy/qugyjlp2dDU9PTyQmJsLe3l7X5Rg1Xs/ax+u5+hja9ZyVlYX69esrv8efpsaFGxOT0m5GDg4O/IdTDaRSKX/O1cTe3p4/ay3j9Vx9eD1rn6Fez4++x5+6TzXUQTXYtGnTdF0CkcbweiZjYszXs0RUpGeOEcnOzoaDgwOysrIMMrES/RevaTImvJ7pSdS5Nmpcy42FhQUWLFgACwsLXZdCpBG8psmY8HqmJ1Hn2qhxLTdERERk3Gpcyw0REREZN4YbIiIiMioMN1TGiRMnMHDgQLi7u0MikeCPP/5QvlZcXIx58+ahRYsWsLGxgbu7O8aOHYu7d+8+87gRERHo3r07rKysUK9ePXz22WdlZpoMDQ1Fu3btYGlpiQYNGmDt2rWa/nhUw/B6JmPDa/rZGG6ojLy8PLRq1QqrV68u81p+fj7CwsLwySefICwsDLt378atW7cwaNCgpx4zOzsbvXv3hru7Oy5evIjvvvsOX3/9NZYvX67cJy4uDgMGDEDXrl1x5coVfPjhh5g5cyZ27dql8c9INQevZzI2vKYrQBA9BQCxZ8+ep+5z4cIFAUDcuXPnifv88MMPwsHBQRQWFiq3LVmyRLi7uwuFQiGEEGLu3LmiSZMmKu+bPHmy6NixY+U/ANFjeD2TseE1XT6Da7n54Ycf4OPjA0tLS7Rr1w4nT55UviaEwMKFC+Hu7g4rKysEBgbi+vXrzzymMTXF6UJWVhYkEgkcHR2V28aPH4/AwEDl87Nnz6J79+4qQ/j69u2Lu3fvIj4+XrlPnz59VI7dt29fXLp0CcXFxdr8CDrFa1q/8HquGl7P+qcmXtMGFW5++eUXzJo1Cx999BGuXLmCrl27on///khISAAAfPnll1i+fDlWr16NixcvwtXVFb1790ZOTs4Tj2l0TXHVrLCwEB988AFGjRqlMqmSm5sb6tevr3yempoKFxcXlfc+ep6amvrUfUpKSpCenq6tj6BTvKb1C6/nquH1rH9q7DWty2YjdT333HNiypQpKtuaNGkiPvjgA6FQKISrq6tYunSp8rXCwkLh4OAg1q5d+8RjGltTnKbhKU2eMplMDB48WLRp00ZkZWU99Ti9e/cWkyZNUtmWlJQkAIizZ88KIYTw8/MTixcvVtnn1KlTAoBISUmp/IfQY7ymqxevZ+3i9Vz9eE2Xz2BabmQyGS5fvlymSaxPnz44c+YM4uLikJqaqvK6hYUFunfvjjNnzii3GXtTXHUpLi7GiBEjEBcXhyNHjjxzKmxXV1dl+n8kLS0NwP//dfCkfUxNTVG7dm0NVq8feE3rD17PVcfrWb/U9GvaYMJNeno65HJ5uU1iqampyh/4k15/xOib4qrBo3800dHROHr0aIUu6k6dOuHEiROQyWTKbYcPH4a7uzu8vb2V+xw5ckTlfYcPH0ZAQADMzMw0+hn0Aa9p/cDrWTN4PesPXtMGFG4ekUgkKs+FECrbnvX6kiVLsHXr1mce87/bK7KPscjNzUV4eDjCw8MBlN7PDg8PR0JCAkpKSjB8+HBcunQJP//8M+RyufIX1+P/KObPn4+xY8cqn48aNQoWFhYYP348rl27hj179mDx4sWYPXu28mc4ZcoU3LlzB7Nnz0ZkZCQ2bdqEoKAgzJkzp1o/f3XjNa1dvJ6rF69n7eM1XQG6uRumvqKiIiGVSsXu3btVts+cOVN069ZN3L59WwAQYWFhKq8PGjRIjB079onHHTNmjBg0aJDKtrCwMAFAxMbGCiGE6Nq1q5g5c6bKPrt37xampqZCJpNV5WPppeDgYAGgzGPcuHEiLi6u3NcAiODgYOUxxo0bJ7p3765y3KtXr4quXbsKCwsL4erqKhYuXKi8Z/5ISEiIaNOmjTA3Nxfe3t5izZo11fCJdYPXdPXg9Vw9eD1XH17Tz2Yw4UaI0s5qb7/9tsq2pk2bqnRWW7ZsmfK1oqKiCnVWc3R0FEVFRcptS5cuLdNZrWnTpirvmzJlSo3orEbaxWuajAmvZ9IXBhVudu7cKczMzERQUJC4ceOGmDVrlrCxsRHx8fFCiNIL3sHBQezevVtERESI1157Tbi5uYns7GzlMT744AMxZswY5fPMzEzh4uIiXnvtNRERESF2794t7O3txddff63cJzY2VlhbW4t3331X3LhxQwQFBQkzMzPx+++/V9+HJ6PEa5qMCa9n0hcGFW6EEOL7778XXl5ewtzcXLRt21aEhoYqX1MoFGLBggXC1dVVWFhYiG7duomIiAiV9xt7UxwZHl7TZEx4PZM+kAjxn2keiYiIiAyYwY2WIiIiInoahhsiIiIyKgw3REREZFQYboiIiMioMNwQERGRUdHrcLNkyRK0b98ednZ2cHZ2xpAhQxAVFaWyj0QiKffx1VdfPfP4iYmJmDBhAtzd3WFubg4vLy+88847ePDgQYVrDAkJgUQiQWZmprofj2qYilzPubm5mD59Ojw8PGBlZYWmTZtizZo1FTo+r2eqbhW5pu/du4fx48fD3d0d1tbW6NevH6Kjoyt0fF7TVFl6HW5CQ0Mxbdo0nDt3DkeOHEFJSQn69OmDvLw85T4pKSkqj02bNkEikWDYsGFPPXZsbCwCAgJw69Yt7NixAzExMVi7di2OHTuGTp06ISMjQ9sfj2qYilzP7777Lg4ePIht27YhMjIS7777LmbMmIE///zzqcfm9Uy68KxrWgiBIUOGIDY2Fn/++SeuXLkCLy8vvPDCCyrXfXl4TVOV6HieHbWkpaUJACqTQv3X4MGDRc+ePZ95rH79+gkPDw+Rn5+vsj0lJUVYW1uLKVOmKLcVFhaK999/X3h4eAhzc3Ph6+srNm7cWO4aHuPGjav056Oapbzr2d/fX3z22Wcq+7Vt21Z8/PHHTz0Wr2fSB/+9pqOiogQAce3aNeU+JSUlwsnJSWzYsOGpx+I1TVVhUOEmOjpaACgzo+UjqampwtTUVPz8889PPc6DBw+ERCIRixcvLvf1iRMnilq1ailnwBwxYoTw9PQUu3fvFrdv3xZHjx4VO3fuFCUlJWLXrl0CgIiKihIpKSkiMzOzah+SaozyrufJkyeLgIAAkZSUJBQKhTh+/LiwtbUVJ0+efOJxeD2TvvjvNX316lUBQMTExKjs5+rq+tSQwWuaqsq0GhuJqkQIgdmzZ6NLly5o3rx5ufv8+OOPsLOzw9ChQ596rOjoaAgh0LRp03Jfb9q0KR4+fIj79+8jMzMTv/76K44cOYIXXngBANCgQQPlvk5OTgAAZ2dnODo6VuKTUU30pOt51apVmDhxIjw8PGBqagoTExNs3LgRXbp0eeKxeD2TPijvmm7SpAm8vLwwf/58rFu3DjY2Nli+fDlSU1ORkpLyxGPxmqaq0us+N4+bPn06rl69ih07djxxn02bNmH06NGwtLRUbpsyZQpsbW2Vj4oQ/65IIZFIEB4eDqlUiu7du1ftAxA95knX86pVq3Du3Dns3bsXly9fxjfffIOpU6fi6NGjAHg9k/4q75o2MzPDrl27cOvWLTg5OcHa2hohISHo378/pFIpAF7TpB0GEW5mzJiBvXv3Ijg4GB4eHuXuc/LkSURFReGtt95S2f7ZZ58hPDxc+QAAX19fSCQS3Lhxo9xj3bx5E7Vq1UKdOnVgZWWl0c9C9KTruaCgAB9++CGWL1+OgQMHomXLlpg+fTpGjhyJr7/+GgCvZ9JPT/sd3a5dO4SHhyMzMxMpKSk4ePAgHjx4AB8fHwC8pklLdHZDrAIUCoWYNm2acHd3F7du3XrqvuPGjRPt2rWr8LH79Okj6tWr98zOanFxcUIikYgjR46Ue5zTp08LACI9Pb3C56aa6VnXc1ZWlgAgDhw4oLJ90qRJonfv3k89Nq9n0gV1fkc/cuvWLWFiYiIOHTr01P14TVNV6HW4efvtt4WDg4MICQkRKSkpysd/L/asrCxhbW2t1hL3t27dEnXq1BFdu3YVoaGhIiEhQfz999+iefPmws/PTzx48EC57/jx44Wnp6fYs2ePiI2NFcHBweKXX34RQgiRlJQkJBKJ2LJli0hLSxM5OTma+fBkdCpyPXfv3l34+/uL4OBgERsbKzZv3iwsLS3FDz/88NRj83omXajINf3rr7+K4OBgcfv2bfHHH38ILy8vMXTo0Gcem9c0VYVehxv8Zwjfo8fmzZtV9lu3bp2wsrJSuxd8fHy8GD9+vHB1dRVmZmbC09NTzJgxo0zCLygoEO+++65wc3NTDjPctGmT8vXPPvtMuLq6ColEwmGG9EQVuZ5TUlLE+PHjhbu7u7C0tBSNGzcW33zzjXJUyNPweqbqVpFr+ttvvxUeHh7CzMxM1K9fX3z88ceiqKioQsfnNU2VJRHi355ZREREREbAIDoUExEREVUUww0REREZFYYbIiIiMioMN0RERGRUGG6IiIjIqBhkuFmyZAnat28POzs7ODs7Y8iQIYiKilLZRwiBhQsXwt3dHVZWVggMDMT169dV9lm/fj0CAwNhb28PiUSCzMxMlddDQkIgkUjKfVy8eFHbH5OIiIgqwSDDTWhoKKZNm4Zz587hyJEjKCkpQZ8+fZCXl6fc58svv8Ty5cuxevVqXLx4Ea6urujduzdycnKU++Tn56Nfv3748MMPyz1P586dkZKSovJ466234O3tjYCAAK1/TiIiIlKfUcxzc//+fTg7OyM0NBTdunWDEALu7u6YNWsW5s2bBwAoKiqCi4sLli1bhsmTJ6u8PyQkBD169MDDhw+fumpscXExPDw8MH36dHzyySfa/EhERERUSQbZcvNfWVlZAP5/afu4uDikpqaiT58+yn0sLCzQvXt3nDlzptLn2bt3L9LT0zF+/Pgq1UtERETaY/DhRgiB2bNno0uXLmjevDkAIDU1FQDg4uKisq+Li4vytcoICgpC37594enpWfmCiYiISKtMdV1AVU2fPh1Xr17FqVOnyrwmkUhUngshymyrqKSkJBw6dAi//vprpd5PRERE1cOgW25mzJiBvXv3Ijg4GB4eHsrtrq6uAFCmlSYtLa1Ma05Fbd68GbVr18agQYMqXzARERFpnUGGGyEEpk+fjt27d+P48ePw8fFRed3Hxweurq44cuSIcptMJkNoaCg6d+5cqfNt3rwZY8eOhZmZWZXrJyIiIu0xyNtS06ZNw/bt2/Hnn3/Czs5O2ULj4OAAKysrSCQSzJo1C4sXL4afnx/8/PywePFiWFtbY9SoUcrjpKamIjU1FTExMQCAiIgI2NnZoX79+srOyQBw/PhxxMXFYcKECdX7QYmIiEhtBjkU/En9ZjZv3qwcySSEwKJFi7Bu3To8fPgQHTp0wPfff6/sdAwACxcuxKJFi556HAAYNWoU7ty5g9OnT2v0cxAREZHmGWS4ISIiInoSg+xzQ0RERPQkDDdERERkVBhuiIiIyKgw3BAREZFRYbghIiIio8JwQ0REREaF4YaIiIiMCsMNERERGRWGGyIyCCEhIZBIJMjMzNR1KUSk5zhDMRHppcDAQLRu3RorV64EULr4bUZGBlxcXJ64BAsREWCgC2cSUc1jbm4OV1dXXZdBRAaAt6WISO+MHz8eoaGh+PbbbyGRSCCRSLBlyxaV21JbtmyBo6Mj9u3bh8aNG8Pa2hrDhw9HXl4efvzxR3h7e6NWrVqYMWMG5HK58tgymQxz585FvXr1YGNjgw4dOiAkJEQ3H5SItIItN0Skd7799lvcunULzZs3x2effQYAuH79epn98vPzsWrVKuzcuRM5OTkYOnQohg4dCkdHRxw4cACxsbEYNmwYunTpgpEjRwIA3njjDcTHx2Pnzp1wd3fHnj170K9fP0RERMDPz69aPycRaQfDDRHpHQcHB5ibm8Pa2lp5K+rmzZtl9isuLsaaNWvQsGFDAMDw4cPx008/4d69e7C1tUWzZs3Qo0cPBAcHY+TIkbh9+zZ27NiBpKQkuLu7AwDmzJmDgwcPYvPmzVi8eHH1fUgi0hqGGyIyWNbW1spgAwAuLi7w9vaGra2tyra0tDQAQFhYGIQQaNSokcpxioqKULt27eopmoi0juGGiAyWmZmZynOJRFLuNoVCAQBQKBSQSqW4fPkypFKpyn6PByIiMmwMN0Skl8zNzVU6AmtCmzZtIJfLkZaWhq5du2r02ESkPzhaioj0kre3N86fP4/4+Hikp6crW1+qolGjRhg9ejTGjh2L3bt3Iy4uDhcvXsSyZctw4MABDVRNRPqA4YaI9NKcOXMglUrRrFkz1K1bFwkJCRo57ubNmzF27Fi89957aNy4MQYNGoTz58/D09NTI8cnIt3jDMVERERkVNhyQ0REREaF4YaIiIiMCsMNERERGRWGGyIiIjIqDDdERERkVBhuiIiIyKgw3BAREZFRYbghIiIio8JwQ0REREaF4YaIiIiMCsMNERERGZX/AwR8JdxPQkezAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "large_residuals = np.abs(cmp.data.residual)>0.3\n",
    "cmp3 = cmp.where(large_residuals)\n",
    "# cmp3.plot.scatter(figsize=(6,6));\n",
    "cmp3.plot.timeseries();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Data variables:\n",
       "    Observation  (time) float64 0.92 1.03 1.24 1.34 1.55 ... 3.97 3.63 3.47 3.46\n",
       "    Hm0, model   (time) float64 1.43 1.655 1.789 1.834 ... 4.3 3.993 3.932 3.776\n",
       "    wind_speed   (time) float64 9.754 11.06 11.42 10.93 ... 14.86 14.71 13.53\n",
       "    wind_dir     (time) float64 327.4 331.5 333.3 330.2 ... 345.0 345.8 346.5\n",
       "    residual     (time) float64 0.5101 0.6253 0.5495 ... 0.3634 0.4617 0.3159"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cmp3.data.data_vars"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.92000002, 1.02999997, 1.24000001, 1.34000003, 1.54999995,\n",
       "       2.08999991, 2.77999997, 2.86999989, 4.13000011, 3.97000003,\n",
       "       3.63000011, 3.47000003, 3.46000004])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cmp3.data.Observation.values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Aggregate"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's split the data based on wind direction sector and aggregate the skill calculation of the significant wave height predition for each sector."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Note: in this short example wind direction is between 274 and 353 degrees\n",
    "df = cmp.data.wind_dir.to_dataframe()\n",
    "cmp.data[\"windsector\"] = pd.cut(df.wind_dir, [255, 285, 315, 345, 360], labels=[\"W\", \"WNW\", \"NNW\", \"N\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th id=\"T_95166_level0_col6\" class=\"col_heading level0 col6\" >cc</th>\n",
       "      <th id=\"T_95166_level0_col7\" class=\"col_heading level0 col7\" >si</th>\n",
       "      <th id=\"T_95166_level0_col8\" class=\"col_heading level0 col8\" >r2</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >windsector</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "      <th class=\"blank col3\" >&nbsp;</th>\n",
       "      <th class=\"blank col4\" >&nbsp;</th>\n",
       "      <th class=\"blank col5\" >&nbsp;</th>\n",
       "      <th class=\"blank col6\" >&nbsp;</th>\n",
       "      <th class=\"blank col7\" >&nbsp;</th>\n",
       "      <th class=\"blank col8\" >&nbsp;</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_95166_level0_row0\" class=\"row_heading level0 row0\" >NNW</th>\n",
       "      <td id=\"T_95166_row0_col0\" class=\"data row0 col0\" >Hm0, obs</td>\n",
       "      <td id=\"T_95166_row0_col1\" class=\"data row0 col1\" >28</td>\n",
       "      <td id=\"T_95166_row0_col2\" class=\"data row0 col2\" >0.116</td>\n",
       "      <td id=\"T_95166_row0_col3\" class=\"data row0 col3\" >0.285</td>\n",
       "      <td id=\"T_95166_row0_col4\" class=\"data row0 col4\" >0.261</td>\n",
       "      <td id=\"T_95166_row0_col5\" class=\"data row0 col5\" >0.231</td>\n",
       "      <td id=\"T_95166_row0_col6\" class=\"data row0 col6\" >0.970</td>\n",
       "      <td id=\"T_95166_row0_col7\" class=\"data row0 col7\" >0.103</td>\n",
       "      <td id=\"T_95166_row0_col8\" class=\"data row0 col8\" >0.928</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_95166_level0_row1\" class=\"row_heading level0 row1\" >N</th>\n",
       "      <td id=\"T_95166_row1_col0\" class=\"data row1 col0\" >Hm0, obs</td>\n",
       "      <td id=\"T_95166_row1_col1\" class=\"data row1 col1\" >7</td>\n",
       "      <td id=\"T_95166_row1_col2\" class=\"data row1 col2\" >0.070</td>\n",
       "      <td id=\"T_95166_row1_col3\" class=\"data row1 col3\" >0.252</td>\n",
       "      <td id=\"T_95166_row1_col4\" class=\"data row1 col4\" >0.242</td>\n",
       "      <td id=\"T_95166_row1_col5\" class=\"data row1 col5\" >0.223</td>\n",
       "      <td id=\"T_95166_row1_col6\" class=\"data row1 col6\" >0.991</td>\n",
       "      <td id=\"T_95166_row1_col7\" class=\"data row1 col7\" >0.083</td>\n",
       "      <td id=\"T_95166_row1_col8\" class=\"data row1 col8\" >0.859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_95166_level0_row2\" class=\"row_heading level0 row2\" >WNW</th>\n",
       "      <td id=\"T_95166_row2_col0\" class=\"data row2 col0\" >Hm0, obs</td>\n",
       "      <td id=\"T_95166_row2_col1\" class=\"data row2 col1\" >15</td>\n",
       "      <td id=\"T_95166_row2_col2\" class=\"data row2 col2\" >-0.045</td>\n",
       "      <td id=\"T_95166_row2_col3\" class=\"data row2 col3\" >0.142</td>\n",
       "      <td id=\"T_95166_row2_col4\" class=\"data row2 col4\" >0.135</td>\n",
       "      <td id=\"T_95166_row2_col5\" class=\"data row2 col5\" >0.108</td>\n",
       "      <td id=\"T_95166_row2_col6\" class=\"data row2 col6\" >0.984</td>\n",
       "      <td id=\"T_95166_row2_col7\" class=\"data row2 col7\" >0.050</td>\n",
       "      <td id=\"T_95166_row2_col8\" class=\"data row2 col8\" >0.965</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_95166_level0_row3\" class=\"row_heading level0 row3\" >W</th>\n",
       "      <td id=\"T_95166_row3_col0\" class=\"data row3 col0\" >Hm0, obs</td>\n",
       "      <td id=\"T_95166_row3_col1\" class=\"data row3 col1\" >17</td>\n",
       "      <td id=\"T_95166_row3_col2\" class=\"data row3 col2\" >0.026</td>\n",
       "      <td id=\"T_95166_row3_col3\" class=\"data row3 col3\" >0.165</td>\n",
       "      <td id=\"T_95166_row3_col4\" class=\"data row3 col4\" >0.163</td>\n",
       "      <td id=\"T_95166_row3_col5\" class=\"data row3 col5\" >0.123</td>\n",
       "      <td id=\"T_95166_row3_col6\" class=\"data row3 col6\" >0.962</td>\n",
       "      <td id=\"T_95166_row3_col7\" class=\"data row3 col7\" >0.067</td>\n",
       "      <td id=\"T_95166_row3_col8\" class=\"data row3 col8\" >0.904</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1b5e9cefc10>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ss = cmp.skill(by=\"windsector\")\n",
    "ss.style()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ss[\"rmse\"].plot.bar(title=\"Hm0 RMSE by wind sector\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cmp.where(cmp.data.windsector==\"W\").plot.timeseries();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.12"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}