{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Example for using the Pvlib model\n",
    "\n",
    "The `Pvlib` model can be used to determine the feed-in of a photovoltaic module using the pvlib.\n",
    "The [pvlib](https://github.com/pvlib/pvlib-python) is a python library for simulating the performance of photovoltaic energy systems. For more information check out the [documentation of the pvlib](https://pvlib-python.readthedocs.io/en/stable/).\n",
    "\n",
    "The following example shows you how to use the `Pvlib` model.\n",
    "\n",
    "* [Set up Photovoltaic object](#photovoltaic_object)\n",
    "* [Get weather data](#weather_data)\n",
    "* [Calculate feed-in](#feedin)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Set up Photovoltaic object <a class=\"anchor\" id=\"photovoltaic_object\"></a>\n",
    "\n",
    "To calculate the feed-in using the `Pvlib` model you have to set up a `Photovoltaic` object. You can import it as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from feedinlib import Photovoltaic"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To set up a Photovoltaic system you have to provide all PV system parameters required by the `PVlib` model. The required parameters can be looked up in the [model's documentation](https://feedinlib.readthedocs.io/en/features-design-skeleton/temp/feedinlib.models.Pvlib.html#feedinlib.models.Pvlib.power_plant_requires).\n",
    "For the `Pvlib` model these are the **azimuth** and **tilt** of the module as well as the **albedo or surface type**. Furthermore, the **name of the module and inverter** are needed to obtain technical parameters from the provided module and inverter databases. For an overview of the provided modules and inverters you can use the function `get_power_plant_data()`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from feedinlib import get_power_plant_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Advent_Solar_Ventura_210___2008_</th>\n",
       "      <th>Advent_Solar_Ventura_215___2009_</th>\n",
       "      <th>Aleo_S03_160__2007__E__</th>\n",
       "      <th>Aleo_S03_165__2007__E__</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Vintage</th>\n",
       "      <td>2008</td>\n",
       "      <td>2009</td>\n",
       "      <td>2007 (E)</td>\n",
       "      <td>2007 (E)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Area</th>\n",
       "      <td>1.646</td>\n",
       "      <td>1.646</td>\n",
       "      <td>1.28</td>\n",
       "      <td>1.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Material</th>\n",
       "      <td>mc-Si</td>\n",
       "      <td>mc-Si</td>\n",
       "      <td>c-Si</td>\n",
       "      <td>c-Si</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cells_in_Series</th>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Parallel_Strings</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Isco</th>\n",
       "      <td>8.34</td>\n",
       "      <td>8.49</td>\n",
       "      <td>5.1</td>\n",
       "      <td>5.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Voco</th>\n",
       "      <td>35.31</td>\n",
       "      <td>35.92</td>\n",
       "      <td>43.5</td>\n",
       "      <td>43.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Impo</th>\n",
       "      <td>7.49</td>\n",
       "      <td>7.74</td>\n",
       "      <td>4.55</td>\n",
       "      <td>4.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vmpo</th>\n",
       "      <td>27.61</td>\n",
       "      <td>27.92</td>\n",
       "      <td>35.6</td>\n",
       "      <td>35.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aisc</th>\n",
       "      <td>0.00077</td>\n",
       "      <td>0.00082</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>0.0003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aimp</th>\n",
       "      <td>-0.00015</td>\n",
       "      <td>-0.00013</td>\n",
       "      <td>-0.00025</td>\n",
       "      <td>-0.00025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C0</th>\n",
       "      <td>0.937</td>\n",
       "      <td>1.015</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C1</th>\n",
       "      <td>0.063</td>\n",
       "      <td>-0.015</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bvoco</th>\n",
       "      <td>-0.133</td>\n",
       "      <td>-0.135</td>\n",
       "      <td>-0.152</td>\n",
       "      <td>-0.152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mbvoc</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bvmpo</th>\n",
       "      <td>-0.135</td>\n",
       "      <td>-0.136</td>\n",
       "      <td>-0.158</td>\n",
       "      <td>-0.158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mbvmp</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N</th>\n",
       "      <td>1.495</td>\n",
       "      <td>1.373</td>\n",
       "      <td>1.25</td>\n",
       "      <td>1.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C2</th>\n",
       "      <td>0.0182</td>\n",
       "      <td>0.0036</td>\n",
       "      <td>-0.15</td>\n",
       "      <td>-0.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C3</th>\n",
       "      <td>-10.758</td>\n",
       "      <td>-7.2509</td>\n",
       "      <td>-8.96</td>\n",
       "      <td>-8.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A0</th>\n",
       "      <td>0.9067</td>\n",
       "      <td>0.9323</td>\n",
       "      <td>0.938</td>\n",
       "      <td>0.938</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A1</th>\n",
       "      <td>0.09573</td>\n",
       "      <td>0.06526</td>\n",
       "      <td>0.05422</td>\n",
       "      <td>0.05422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A2</th>\n",
       "      <td>-0.0266</td>\n",
       "      <td>-0.01567</td>\n",
       "      <td>-0.009903</td>\n",
       "      <td>-0.009903</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A3</th>\n",
       "      <td>0.00343</td>\n",
       "      <td>0.00193</td>\n",
       "      <td>0.0007297</td>\n",
       "      <td>0.0007297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A4</th>\n",
       "      <td>-0.0001794</td>\n",
       "      <td>-9.81e-05</td>\n",
       "      <td>-1.907e-05</td>\n",
       "      <td>-1.907e-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B1</th>\n",
       "      <td>-0.002438</td>\n",
       "      <td>-0.002438</td>\n",
       "      <td>-0.002438</td>\n",
       "      <td>-0.002438</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B2</th>\n",
       "      <td>0.00031</td>\n",
       "      <td>0.00031</td>\n",
       "      <td>0.0003103</td>\n",
       "      <td>0.0003103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B3</th>\n",
       "      <td>-1.246e-05</td>\n",
       "      <td>-1.246e-05</td>\n",
       "      <td>-1.246e-05</td>\n",
       "      <td>-1.246e-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B4</th>\n",
       "      <td>2.11e-07</td>\n",
       "      <td>2.11e-07</td>\n",
       "      <td>2.11e-07</td>\n",
       "      <td>2.11e-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B5</th>\n",
       "      <td>-1.36e-09</td>\n",
       "      <td>-1.36e-09</td>\n",
       "      <td>-1.36e-09</td>\n",
       "      <td>-1.36e-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DTC</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FD</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>-3.45</td>\n",
       "      <td>-3.47</td>\n",
       "      <td>-3.56</td>\n",
       "      <td>-3.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>-0.077</td>\n",
       "      <td>-0.087</td>\n",
       "      <td>-0.075</td>\n",
       "      <td>-0.075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C4</th>\n",
       "      <td>0.972</td>\n",
       "      <td>0.989</td>\n",
       "      <td>0.995</td>\n",
       "      <td>0.995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C5</th>\n",
       "      <td>0.028</td>\n",
       "      <td>0.012</td>\n",
       "      <td>0.005</td>\n",
       "      <td>0.005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IXO</th>\n",
       "      <td>8.25</td>\n",
       "      <td>8.49</td>\n",
       "      <td>5.04</td>\n",
       "      <td>5.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IXXO</th>\n",
       "      <td>5.2</td>\n",
       "      <td>5.45</td>\n",
       "      <td>3.16</td>\n",
       "      <td>3.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C6</th>\n",
       "      <td>1.067</td>\n",
       "      <td>1.137</td>\n",
       "      <td>1.15</td>\n",
       "      <td>1.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C7</th>\n",
       "      <td>-0.067</td>\n",
       "      <td>-0.137</td>\n",
       "      <td>-0.15</td>\n",
       "      <td>-0.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Notes</th>\n",
       "      <td>Source: Sandia National Laboratories Updated 9...</td>\n",
       "      <td>Source: Sandia National Laboratories Updated 9...</td>\n",
       "      <td>Source: Sandia National Laboratories Updated 9...</td>\n",
       "      <td>Source: Sandia National Laboratories Updated 9...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   Advent_Solar_Ventura_210___2008_  \\\n",
       "Vintage                                                        2008   \n",
       "Area                                                          1.646   \n",
       "Material                                                      mc-Si   \n",
       "Cells_in_Series                                                  60   \n",
       "Parallel_Strings                                                  1   \n",
       "Isco                                                           8.34   \n",
       "Voco                                                          35.31   \n",
       "Impo                                                           7.49   \n",
       "Vmpo                                                          27.61   \n",
       "Aisc                                                        0.00077   \n",
       "Aimp                                                       -0.00015   \n",
       "C0                                                            0.937   \n",
       "C1                                                            0.063   \n",
       "Bvoco                                                        -0.133   \n",
       "Mbvoc                                                             0   \n",
       "Bvmpo                                                        -0.135   \n",
       "Mbvmp                                                             0   \n",
       "N                                                             1.495   \n",
       "C2                                                           0.0182   \n",
       "C3                                                          -10.758   \n",
       "A0                                                           0.9067   \n",
       "A1                                                          0.09573   \n",
       "A2                                                          -0.0266   \n",
       "A3                                                          0.00343   \n",
       "A4                                                       -0.0001794   \n",
       "B0                                                                1   \n",
       "B1                                                        -0.002438   \n",
       "B2                                                          0.00031   \n",
       "B3                                                       -1.246e-05   \n",
       "B4                                                         2.11e-07   \n",
       "B5                                                        -1.36e-09   \n",
       "DTC                                                               3   \n",
       "FD                                                                1   \n",
       "A                                                             -3.45   \n",
       "B                                                            -0.077   \n",
       "C4                                                            0.972   \n",
       "C5                                                            0.028   \n",
       "IXO                                                            8.25   \n",
       "IXXO                                                            5.2   \n",
       "C6                                                            1.067   \n",
       "C7                                                           -0.067   \n",
       "Notes             Source: Sandia National Laboratories Updated 9...   \n",
       "\n",
       "                                   Advent_Solar_Ventura_215___2009_  \\\n",
       "Vintage                                                        2009   \n",
       "Area                                                          1.646   \n",
       "Material                                                      mc-Si   \n",
       "Cells_in_Series                                                  60   \n",
       "Parallel_Strings                                                  1   \n",
       "Isco                                                           8.49   \n",
       "Voco                                                          35.92   \n",
       "Impo                                                           7.74   \n",
       "Vmpo                                                          27.92   \n",
       "Aisc                                                        0.00082   \n",
       "Aimp                                                       -0.00013   \n",
       "C0                                                            1.015   \n",
       "C1                                                           -0.015   \n",
       "Bvoco                                                        -0.135   \n",
       "Mbvoc                                                             0   \n",
       "Bvmpo                                                        -0.136   \n",
       "Mbvmp                                                             0   \n",
       "N                                                             1.373   \n",
       "C2                                                           0.0036   \n",
       "C3                                                          -7.2509   \n",
       "A0                                                           0.9323   \n",
       "A1                                                          0.06526   \n",
       "A2                                                         -0.01567   \n",
       "A3                                                          0.00193   \n",
       "A4                                                        -9.81e-05   \n",
       "B0                                                                1   \n",
       "B1                                                        -0.002438   \n",
       "B2                                                          0.00031   \n",
       "B3                                                       -1.246e-05   \n",
       "B4                                                         2.11e-07   \n",
       "B5                                                        -1.36e-09   \n",
       "DTC                                                               3   \n",
       "FD                                                                1   \n",
       "A                                                             -3.47   \n",
       "B                                                            -0.087   \n",
       "C4                                                            0.989   \n",
       "C5                                                            0.012   \n",
       "IXO                                                            8.49   \n",
       "IXXO                                                           5.45   \n",
       "C6                                                            1.137   \n",
       "C7                                                           -0.137   \n",
       "Notes             Source: Sandia National Laboratories Updated 9...   \n",
       "\n",
       "                                            Aleo_S03_160__2007__E__  \\\n",
       "Vintage                                                    2007 (E)   \n",
       "Area                                                           1.28   \n",
       "Material                                                       c-Si   \n",
       "Cells_in_Series                                                  72   \n",
       "Parallel_Strings                                                  1   \n",
       "Isco                                                            5.1   \n",
       "Voco                                                           43.5   \n",
       "Impo                                                           4.55   \n",
       "Vmpo                                                           35.6   \n",
       "Aisc                                                         0.0003   \n",
       "Aimp                                                       -0.00025   \n",
       "C0                                                             0.99   \n",
       "C1                                                             0.01   \n",
       "Bvoco                                                        -0.152   \n",
       "Mbvoc                                                             0   \n",
       "Bvmpo                                                        -0.158   \n",
       "Mbvmp                                                             0   \n",
       "N                                                              1.25   \n",
       "C2                                                            -0.15   \n",
       "C3                                                            -8.96   \n",
       "A0                                                            0.938   \n",
       "A1                                                          0.05422   \n",
       "A2                                                        -0.009903   \n",
       "A3                                                        0.0007297   \n",
       "A4                                                       -1.907e-05   \n",
       "B0                                                                1   \n",
       "B1                                                        -0.002438   \n",
       "B2                                                        0.0003103   \n",
       "B3                                                       -1.246e-05   \n",
       "B4                                                         2.11e-07   \n",
       "B5                                                        -1.36e-09   \n",
       "DTC                                                               3   \n",
       "FD                                                                1   \n",
       "A                                                             -3.56   \n",
       "B                                                            -0.075   \n",
       "C4                                                            0.995   \n",
       "C5                                                            0.005   \n",
       "IXO                                                            5.04   \n",
       "IXXO                                                           3.16   \n",
       "C6                                                             1.15   \n",
       "C7                                                            -0.15   \n",
       "Notes             Source: Sandia National Laboratories Updated 9...   \n",
       "\n",
       "                                            Aleo_S03_165__2007__E__  \n",
       "Vintage                                                    2007 (E)  \n",
       "Area                                                           1.28  \n",
       "Material                                                       c-Si  \n",
       "Cells_in_Series                                                  72  \n",
       "Parallel_Strings                                                  1  \n",
       "Isco                                                            5.2  \n",
       "Voco                                                           43.6  \n",
       "Impo                                                           4.65  \n",
       "Vmpo                                                           35.8  \n",
       "Aisc                                                         0.0003  \n",
       "Aimp                                                       -0.00025  \n",
       "C0                                                             0.99  \n",
       "C1                                                             0.01  \n",
       "Bvoco                                                        -0.152  \n",
       "Mbvoc                                                             0  \n",
       "Bvmpo                                                        -0.158  \n",
       "Mbvmp                                                             0  \n",
       "N                                                              1.25  \n",
       "C2                                                            -0.15  \n",
       "C3                                                            -8.96  \n",
       "A0                                                            0.938  \n",
       "A1                                                          0.05422  \n",
       "A2                                                        -0.009903  \n",
       "A3                                                        0.0007297  \n",
       "A4                                                       -1.907e-05  \n",
       "B0                                                                1  \n",
       "B1                                                        -0.002438  \n",
       "B2                                                        0.0003103  \n",
       "B3                                                       -1.246e-05  \n",
       "B4                                                         2.11e-07  \n",
       "B5                                                        -1.36e-09  \n",
       "DTC                                                               3  \n",
       "FD                                                                1  \n",
       "A                                                             -3.56  \n",
       "B                                                            -0.075  \n",
       "C4                                                            0.995  \n",
       "C5                                                            0.005  \n",
       "IXO                                                            5.14  \n",
       "IXXO                                                           3.25  \n",
       "C6                                                             1.15  \n",
       "C7                                                            -0.15  \n",
       "Notes             Source: Sandia National Laboratories Updated 9...  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get modules\n",
    "module_df = get_power_plant_data(dataset='sandiamod')\n",
    "# print the first four modules\n",
    "module_df.iloc[:, 1:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>ABB__MICRO_0_25_I_OUTD_US_208__208V__208V__CEC_2018_</th>\n",
       "      <th>ABB__MICRO_0_25_I_OUTD_US_240_240V__CEC_2014_</th>\n",
       "      <th>ABB__MICRO_0_25_I_OUTD_US_240__240V__240V__CEC_2018_</th>\n",
       "      <th>ABB__MICRO_0_3_I_OUTD_US_208_208V__CEC_2014_</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Vac</th>\n",
       "      <td>208.000000</td>\n",
       "      <td>240.000000</td>\n",
       "      <td>240.000000</td>\n",
       "      <td>208.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Paco</th>\n",
       "      <td>250.000000</td>\n",
       "      <td>250.000000</td>\n",
       "      <td>250.000000</td>\n",
       "      <td>300.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pdco</th>\n",
       "      <td>259.589000</td>\n",
       "      <td>259.552697</td>\n",
       "      <td>259.492000</td>\n",
       "      <td>311.714554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vdco</th>\n",
       "      <td>40.000000</td>\n",
       "      <td>39.982246</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.227111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pso</th>\n",
       "      <td>2.089610</td>\n",
       "      <td>1.931194</td>\n",
       "      <td>2.240410</td>\n",
       "      <td>1.971053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C0</th>\n",
       "      <td>-0.000041</td>\n",
       "      <td>-0.000027</td>\n",
       "      <td>-0.000039</td>\n",
       "      <td>-0.000036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C1</th>\n",
       "      <td>-0.000091</td>\n",
       "      <td>-0.000158</td>\n",
       "      <td>-0.000132</td>\n",
       "      <td>-0.000256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C2</th>\n",
       "      <td>0.000494</td>\n",
       "      <td>0.001480</td>\n",
       "      <td>0.002418</td>\n",
       "      <td>-0.000833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C3</th>\n",
       "      <td>-0.013171</td>\n",
       "      <td>-0.034600</td>\n",
       "      <td>-0.014926</td>\n",
       "      <td>-0.039100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pnt</th>\n",
       "      <td>0.020000</td>\n",
       "      <td>0.050000</td>\n",
       "      <td>0.050000</td>\n",
       "      <td>0.020000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vdcmax</th>\n",
       "      <td>50.000000</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>65.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Idcmax</th>\n",
       "      <td>6.489710</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>6.487300</td>\n",
       "      <td>10.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mppt_low</th>\n",
       "      <td>30.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>30.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mppt_high</th>\n",
       "      <td>50.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>50.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           ABB__MICRO_0_25_I_OUTD_US_208__208V__208V__CEC_2018_  \\\n",
       "Vac                                               208.000000      \n",
       "Paco                                              250.000000      \n",
       "Pdco                                              259.589000      \n",
       "Vdco                                               40.000000      \n",
       "Pso                                                 2.089610      \n",
       "C0                                                 -0.000041      \n",
       "C1                                                 -0.000091      \n",
       "C2                                                  0.000494      \n",
       "C3                                                 -0.013171      \n",
       "Pnt                                                 0.020000      \n",
       "Vdcmax                                             50.000000      \n",
       "Idcmax                                              6.489710      \n",
       "Mppt_low                                           30.000000      \n",
       "Mppt_high                                          50.000000      \n",
       "\n",
       "           ABB__MICRO_0_25_I_OUTD_US_240_240V__CEC_2014_  \\\n",
       "Vac                                           240.000000   \n",
       "Paco                                          250.000000   \n",
       "Pdco                                          259.552697   \n",
       "Vdco                                           39.982246   \n",
       "Pso                                             1.931194   \n",
       "C0                                             -0.000027   \n",
       "C1                                             -0.000158   \n",
       "C2                                              0.001480   \n",
       "C3                                             -0.034600   \n",
       "Pnt                                             0.050000   \n",
       "Vdcmax                                         65.000000   \n",
       "Idcmax                                         10.000000   \n",
       "Mppt_low                                       20.000000   \n",
       "Mppt_high                                      50.000000   \n",
       "\n",
       "           ABB__MICRO_0_25_I_OUTD_US_240__240V__240V__CEC_2018_  \\\n",
       "Vac                                               240.000000      \n",
       "Paco                                              250.000000      \n",
       "Pdco                                              259.492000      \n",
       "Vdco                                               40.000000      \n",
       "Pso                                                 2.240410      \n",
       "C0                                                 -0.000039      \n",
       "C1                                                 -0.000132      \n",
       "C2                                                  0.002418      \n",
       "C3                                                 -0.014926      \n",
       "Pnt                                                 0.050000      \n",
       "Vdcmax                                             50.000000      \n",
       "Idcmax                                              6.487300      \n",
       "Mppt_low                                           30.000000      \n",
       "Mppt_high                                          50.000000      \n",
       "\n",
       "           ABB__MICRO_0_3_I_OUTD_US_208_208V__CEC_2014_  \n",
       "Vac                                          208.000000  \n",
       "Paco                                         300.000000  \n",
       "Pdco                                         311.714554  \n",
       "Vdco                                          40.227111  \n",
       "Pso                                            1.971053  \n",
       "C0                                            -0.000036  \n",
       "C1                                            -0.000256  \n",
       "C2                                            -0.000833  \n",
       "C3                                            -0.039100  \n",
       "Pnt                                            0.020000  \n",
       "Vdcmax                                        65.000000  \n",
       "Idcmax                                        10.000000  \n",
       "Mppt_low                                      30.000000  \n",
       "Mppt_high                                     50.000000  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get inverter data\n",
    "inverter_df = get_power_plant_data(dataset='cecinverter')\n",
    "# print the first four inverters\n",
    "inverter_df.iloc[:, 1:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now you can set up a PV system to calculate feed-in for, using for example the first module and converter in the databases:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "system_data = {\n",
    "    'module_name': 'Advent_Solar_Ventura_210___2008_',  # module name as in database\n",
    "    'inverter_name': 'ABB__MICRO_0_25_I_OUTD_US_208__208V__208V__CEC_2018_',  # inverter name as in database\n",
    "    'azimuth': 180,\n",
    "    'tilt': 30,\n",
    "    'albedo': 0.2}\n",
    "pv_system = Photovoltaic(**system_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Optional power plant parameters**\n",
    "\n",
    "Besides the required PV system parameters you can provide optional parameters such as the number of modules per string, etc. Optional PV system parameters are specific to the used model and how to find out about the possible optional parameters is documented in the model's `feedin` method under `power_plant_parameters`. In case of the `Pvlib` model see [here](https://feedinlib.readthedocs.io/en/features-design-skeleton/temp/feedinlib.models.Pvlib.html#feedinlib.models.Pvlib.feedin). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "system_data['modules_per_string'] = 2\n",
    "pv_system_with_optional_parameters = Photovoltaic(**system_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Get weather data <a class=\"anchor\" id=\"weather_data\"></a>\n",
    "\n",
    "Besides setting up your PV system you have to provide weather data the feed-in is calculated with.\n",
    "This example uses open_FRED weather data. For more information on the data and download see the [load_open_fred_weather_data Notebook](load_open_fred_weather_data.ipynb)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from feedinlib.db import Weather\n",
    "from feedinlib.db import defaultdb\n",
    "from shapely.geometry import Point"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# specify latitude and longitude of PV system location\n",
    "lat = 52.4\n",
    "lon = 13.5\n",
    "location = Point(lon, lat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# download weather data for June 2017\n",
    "open_FRED_weather_data = Weather(\n",
    "    start='2017-06-01', stop='2017-07-01', \n",
    "    locations=[location],\n",
    "    variables=\"pvlib\",\n",
    "    **defaultdb())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/birgit/virtualenvs/feedinlib/lib/python3.6/site-packages/pandas/core/sorting.py:257: FutureWarning: Converting timezone-aware DatetimeArray to timezone-naive ndarray with 'datetime64[ns]' dtype. In the future, this will return an ndarray with 'object' dtype where each element is a 'pandas.Timestamp' with the correct 'tz'.\n",
      "\tTo accept the future behavior, pass 'dtype=object'.\n",
      "\tTo keep the old behavior, pass 'dtype=\"datetime64[ns]\"'.\n",
      "  items = np.asanyarray(items)\n"
     ]
    }
   ],
   "source": [
    "# get weather data in pvlib format\n",
    "weather_df = open_FRED_weather_data.df(location=location, lib=\"pvlib\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot irradiance\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "weather_df.loc[:, ['dhi', 'ghi']].plot(title='Irradiance')\n",
    "plt.xlabel('Time')\n",
    "plt.ylabel('Irradiance in $W/m^2$');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Calculate feed-in <a class=\"anchor\" id=\"feedin\"></a>\n",
    "\n",
    "The feed-in can be calculated by calling the `Photovoltaic`'s `feedin` method with the weather data. For the `Pvlib` model you also have to provide the location of the PV system."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "feedin = pv_system.feedin(\n",
    "    weather=weather_df,\n",
    "    location=(lat, lon))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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M42mPfEjpVUKiFDq65v58iJwHtKCgfVI3b3VnKffjBCsmNLNs0AdhOqk9m5Ep3DSdbKmfi66HQRRh493S/+7vJGMttV8XyliVXq3OuH7fulBjW+1hGCXbugjA85jj/6yUOiP7uwQAiOgxSDvNnZZ95wO6BWko4kSh26Fc2nFJVrkPIiDrepQwJeXF4IPQZpR8IwhgrDq7dqVHhY6Vyjeicd0KLc295TdOBQCcvHalODZOFBIVlndTF+a68GlT5dLgjZFQmltr5RL0hjjRjRBR2L14xYeuwqP/+ptBdHzux3fh2e+9cqyh4Oaa9K3Pe7OeIoD/XiyAIDQnRsYglFLfAxDaNvQlAD6nlJpVSt0J4BcAnlLnfP1YoRNFQRpEvxLFNCYfRM3WkuOGXuy5DyJgI9CX6NOQlAKiaNwaRHo9qwNqdM3lzLL5bPw6mdSj1EL1c+LVIAxNo9uJgkxMP7s7vDjd2796E+7YeaC08R5qhJqYduydwefX353/71sXC73fxzgMX28gouszE5Tu63gcgLuNMVuyYxUQ0blEtJ6I1u/cuTM/HicJeiUNooaJaQH4IBaDBqE3xRWT4b4bfVk+VTtRKv/txlWXKq8InDFAl8SqN8E62lQozLXwwStvd441bdxNbzZ6fXqT9bLPux3CRCdq/HkqhL4xahCG2OK6zXYhPx/NC/2pP9QM4oMATgZwBoCtAN5bdwKl1AVKqXVKqXVr167Njw/idIPpRlH+vwQ7zLWNYgpDwSDCNQgN3/XFiRp7wbI8eCFbF64Ntx+XNYgmAx3q7IN1u8/df2AOj3v7Zfjk1Zu9Y/VzEuxojSL0OtT486Svapy+71ANwi6Z4VsXC71I5yFlEEqp7UqpWCmVAPgICjPSPQBOMIYenx0Lhg5z7XT8GkTFxDRGDUJvigvdFgkYm2INxqolL59UqRQKJ/WYfRBTAeGaNoNo1MRU4wbUNTFdv2U39s0O8Nf/daN37MBy2kvQ59UmJt+62OEJmxXpGacGUWIQ8jjbHOejWc+1UBnFIWUQRHSM8e/LAOhV+lUAryKiSSJ6OIBTAPy4ztypkzrMBxEvkES5OFF5Yt9iMDENU1Ih1AdRMjGNSfEuSrD4tVCtTeW1vxrcvOr4o0omJg8JSaJwzsfXh8+tTUxeDaJsYvJFtz3lPZcH02BinEJU2cTk2lvKn/k1iPnRNWqMLDuDiD4L4JkAjiSiLQDeDuCZRHQGUq1xE4A/BACl1E1E9J8AbgYwAPAnSqlaMXA6zDUkikn/aJPdCBQYdTEKpAwiwkw/WRQmJk2jLiwWIjXrEb4NNE4UdLDMuDUIzQCDNIgR+LHqrAVTuvcJGXum+xWzpsusd3/Wf9x3bZqB9DoRomh0jtfFoEHY1x4iGC1kjIxBKKVezRz+qGP8uwG8e9jz6TDXsDyIIjmlF0Vjq8UUK4WJzGa5UFVMEwWDCM8fCdcgkPuPQu7EpvsOBIyqB7sroUvI0FJyzkyaTJSrsRbMbHbfPbaji/pxgk4kR5PvnUkdrt+6eTvOevIJ4rgiHJYQEY1sLY9zMzXP7KLD/sy3Lhb6c78w0/eGQD9Jw1yDopiMqIteh8ZsYvJnfi8U5F37enVoDvVBGP6YgIfmpR/4YcC562GuRsmIOdsH0eDvV8fE1K8RxTRr9V73lQfR47+zcbtzI9MCVq9DIDSfj1EIGc3OW4+GsGAAm0aviWleVI0eS4ZBxEmCnhnFFOCk7kVR5lQbn5Nal5dYDD6IigZRK8zV56xTtZzUuw+66+wPg9xJnW36seP6hskJCUUtDaKGk1q3An3KSUek3/XQbDpcXSQNjCimiGhkm954w1yN944LtH8D77rPxi/Ux3/JMIh+Fuaq7djuPAhtYqKRhOWFwnRSL4YoJr3YJ3t+JqyR+yB8NYXU+Pvy6nUx1Q3wQWTS98qAnIm60Gv3hCOW4aGHuVuK1jExaY1h5ZSf5iRR2G90RnNJzQPDxASqZwr6ynXhwYpjdVKXfBDhJibful/ohoMlwyC0uSYkD0JLXd2I0AsIyxsVUg0ik1ZHIEIopfDVn92L3QfnGplPP6C5k7rGE+vbQE0TU4hdlkbAS7SJSSdcujZcbWLSDGIU1VzXrpxEr+splFfDxGTnsbh+k/sPzpXLSzjmHeT3LdUg6qgQb/zcdcFj6zCT5mGamORRVR9Ea2JaEBhkjWy0EOqsxZRFPBGl5cHHlkmtFCYC+lcMi9t27MeffvZa/O3Xb25kvkKDqGNiSsf4NtBEqaLURsCtiEbAIfpxmo1PlDKIkIKPerMNKTynlML1W/wlJvSeP9GNnGaulOZwE9OspfW4BKO9VkawW4MoNPKopgZRB1/YsGUk84bAvLVuH0T62f/5jVNBFJBJnc21UIv2LR0GkSXKEaWRTL5+ELpvRDeKxmb/N0tcj8JJrSXEW7fta2Q+O8w1hGY9Ys7TejFOjGJ9AbSMwhg1iJM8aKAbkafgY0rlyhoM4r+uuwcv/o8f4tIbtjrHaWGh14m8Zry5ITSIw6b8Ws+M5dB2+yAKnx6BGmcQC2HzLBfr85uYHnvc6jRCcpHnQSwZBmHGdHcicm76g1jlpqiIxtfgJFZGFFPgSvnWTduwc99s0FgtZTfFfAY5gwgvcqgvK8QWG+qkvvnevSP5zfpxwaQ6ETlp1vdU16X65k3bvPPftSstNnfTvZ4y4kZ/Ba/jueSDcJ+/YmJyfGHGYuhOBpHR2+kQiMa/6SWJCg4fvfv+g/ijT23wMvhyFJPj3NlnESGzTvg154WMJcMgyloBOVXzQZKUNYgxmZgGRphriIlpei7GuZ/cgNddGJZkHhLyWweJrUHUSJTzVfhUykiU80iMH/n+Hd7zDoO5OMk1uq7HB6EZui7Wd/Ud/sLF2jm8f3bgHKfDS5dPdLyMsNS2NlDbWBnQEdAOiXXXpdIaRKrBj9vx+oi3XYL/88Xrg8a+82s349Ibt+HKW3c6x5mXFGJi6gRYMtK5gsgcG5YMg0gSlUvMPvtx39AgfNrGKJGYDCKAhK/97F4AwF276iWJNa9BpDSHJBhqyStOlHvDTYrfxPdz+MpPDwvTxNSJIqf9WJufNEMJwcpM2/gvj7PVrBTrExx0BQHAL43+fHtqasyjmGpoECGbYrcTZT7A8e96Xwz0VxzImPWqKXfOcHAmdfZhFBgAsxDMZy4sGQYRG1Ew3U7kDXPV4aW+aJVRIlYKE93wWkxvuTiViuqaV5pigOZG4LPRc3CGVarwfhBa+2sa/bjQQqd6UcUOb0I/93pzftLD1ohjNbS24cvhqKdBqLy4oG8d/8t3bgNgtAZ1ahCWiclJQ2ZiilITk4uM+WYON515rJmkj9GH1mLS196JwgJgFriFaQkxiKRItPJGoBjmKN/YUSG1kyIvtVEniik0gCe0kmooBob6HHrfzAfAtSEppRARMhu2e95R5Uv0DQ1i+UQHB+dkU5BmjlFEeMwxh2HN8p53/sOyRkQ6U1vC7CDOQ7BDfBBao/NpEPq8a1dOAnD7hTRzfPVTTgQAKIcsoNdBr5OW2gjJmagDc7pRJbV6V5SpQQSYHiNKzdc+P12bKHeIkCRFmKRPuu3HCXpRYWseRzc3vZAORamNphxh+j51sppXdRmPS5OJVWoiJISYmEazbPtxkjPsZRNdTDs0iLxcS+TPmdDQjO/EI5Y7x+lNvxP5tT/Tb+LD75x5IlZMdPCQlRMA3CGYs5mJSZtegkxMUQQiqpVpHAIzpDmkW90oUPZByONyExPpMj4eDaIB2kaJJcMgYhWuQZilpaOIxpLCrx+UYUpthA4tylw0q0Houv9hYa7FGNf4JEGmQZDXLjs6H0SxLnoeISNnllGYNtWPE3zr5u0A/Hbn2UGCyV4HHY80rufVa8j3a+hIv7ygZYAGUad5UjfStZj8YzUesXaFh+qyxjiuvtTmNQU5qbNnJKTEDNBqECNHnMDSIFw+CMNfMSYfRJyr5fVNTHWpbUpDys0qWYRGnZ7UgL9EQagGEY2IQZh+rI5HQ7LNbb6N/N8uvw2fueYuAP6AhNlBjIlOIY07C+UNEqMisHveomeKv1SKDvvU1WpdUw/i1DwYGYmqLhpM6LImLphzjqr6qW/W0NPqdVA8I+4v6tuxUJ3VS4ZBpFpB+j5EgzAjnsbBIAbz0iDCxo5Wgwg1qxTvXeOVSh+qkEoNo6rYFBuRcN2Oew3lkmJAWQ4AuGf3dP7eW3V1kGCyF+W0uKbuG8mWvjs30BpER2sQMoPfM91HNyKsmAjQIJIE3ezho5o+iGNWu2tNAWUNoulHNXQtlU1M7r0F0CamyF8p+sGqQRDRhUS0g4huNI79IxHdQkTXE9GXiejw7PhJRDRNRNdlfx+qez7TSe3Lbagk1Y3JSQ0M56Su66hrToMwfRD+LF8g3MQUZ3kQBLcNe5Qws7k7nusz49075F9DZGxFvuszfRCAvCEppTAXF05qvwaRpPH5GYNwhSnvnu7j8OW9oPInsZFgGHkS5WytbM2KCTfRSJmOxrgk7dBEOc0PQk2PuQbxYGMQAC4C8Dzr2LcBPFYpdTqAnwP4S+Oz25VSZ2R/59U9memk9v0wsSqbo8YRxTRfJ3VIAb48iqlhBqEdsyF9NOqamEABm8CIVIjYWEM+H4RZwTREmzLNJCEaxEQ3yjdGaW4tKIT7IFJ6e3lBS0cYb5YrpLUYJ4Mw/H9+DSK8hEcxxhg0po00VIPQz3UnQqCTWnnnHCdGxiCUUt8DcL917FtKKR07eDWA45s6n7lI0wfW7WAsJJ4x+yC6fjMCB1eMfuVcDS0+vSlGushhkAZh0BFiYrK/xIBGxCHMnhQ+H0RiMMuQNWSGJvt+jtlBjMlux6huy4/Tm60WMnyIswoCnY6b8aRzq1LxSydzT1Q+p69hkH3OEI3A/M7YMo9NHuWgQTOztCZciJNavz7IGEQAfh/Apcb/Dyeia4nou0T0dOlLRHQuEa0novU7dxbp8bbZyJ0HkVjMZHwMIjcx1VwgIX5aPWVT12dqEMFhroEaRGr/R5APYlQw15BvXZgaREg2vhmqGVJUb7Ib5b+xNHepDwP8jGeQmWG1BuEyVepIP82MfX4F/Tz5yn3b5wzTIIz34zIxmeW+A02P3U6Ik1prEA0QOQKMhUEQ0f8FMADw6ezQVgAnKqWeAODNAD5DRIdx31VKXaCUWqeUWrd27dr8uFku2heZlCTI6/50xlTNtRLmWnOFmHZZDgfnBvjYDzcNNbeEUgjfUD4IeZz+/UJ6Go+iFwRQNj36fBBJnthHXm0DAB4wTIJ+DUIzCPfmXGgxYX3N9aYf4qTWGoS+166pzWePPOW+KxpEwLNXNu94hw8FHxmmIhCiIXWyREdvCH3ug1iYHOKQMwgiOhvAiwD8rsruilJqVim1K3u/AcDtAB5VZ946mdSlcEYaTz9oO8y1LpPybZLvuWQjLv5pWD2aPdP9oGYscb5pkNeMJ31fgmliGpc0lSQKuopH15MfM0jMNeQPc73spu35e99mMNtPfRC5/V8gw9ToAL/mpcO79XiXkzrJTUwBPghLg3DRUfFBeGgGygyn6Y00vCoBT09lXPZRFKhltxqEASJ6HoC3AHixUuqgcXwtEXWy948AcAqA4JKdSqlSLZ9u5E7iMsMZO1E0loZBA4tB1I008jXMqdOz+e8u2Yg3fu46bNjsrkg6qMGENULDXAsTkz+KaZRhrqX8mNBIuJpmSp8woH0QPhNT7hDthJmYSgzeE2SgzbB6mbm1gsLM5dMg7Gct1MR0RBbtNC5BWwUyKbPURkixvkWbB0FELyWio4admIg+C+AqAKcS0RYiOgfAfwBYBeDbVjjrMwBcT0TXAfgigPOUUv76yRlsScqrQRhO6m5AktMooM9ZmJjqfb/JTXLfTBo3cO/uGee4OEmMTOMwxmqOcG2Mhc17fA+L7YPwr6Gs8mvNQAff0CLM1W1iyrXQXINwTxyrcr8LN8NGWYNwzGtWJvAxePuehtw1BRWkycwHPs0k1MxVCn8OCKHXp12oPeldNW5fA+D9RHQQwI8A/BDAj5RSNzq+k0Mp9Wrm8EeFsRcDuDhkXg5FaFlYLSZzI4jGFeZqPdx1TUxNUqyre057mqbEic2EQ8I7ZqXXAAAgAElEQVRcTR+Ei0FkfhVPHD0wSh9EeH6M1niAbL3VSnR0f26HuUrapaYvNLO8FMbbcXc708JAiAZhmtseODCHG+7Z46TBRIhwlqgiKGNUwoNvVpPMO++Ty+3niXJRXSf1ItMglFK/pZQ6DsCvAbgMwOkAPk5EO4nokkNFYAj0PqWljMgXomhkUo+71IYOJWy6YGCd2aZ66TLwddWKkyQ3Z9QJcw3ZZHKnbxjJI4HZU6Qbuc0DumwFkK63Ok2nvD6IQZKZmNwh0Hrdd4vd04mS5txxM3jtsKdccnf7KzQJmjlI4ytmrTAVwtCmAsYPAf/+XAz4hqNlbGJoEL2AMNe8J/XC5A9ODQIAoJTaRERTAJZlf/r9goGZnAL4nYYLIZO66K0QFiZpo0lnXWiynumDCGWsSiGvSePWILJaTCFRTCNiI3U0iIHpx6J6v19QmGvPn0mtNx/NqHwUmJJ+19MvOU6SLMcj/f+27fvxyKNWCWMLc5vGTD/J6zjZNJgI0QjKJqZRaRBhpiAf9C3Nc4UCq7kuOg2CiN5GRF8joquRZjxPIPUhnK6UetahIjAEuaodWF8pVuWs63HWYorIX0OfQ5MUh/auTkobqL8hO5DSmUt/nqiZ0FpMo4IdCef0mRjSeOqkDj+P056fFOUzfJnUes3kUUyBTmr9Ha8ZlgofxB99+qfyWON50jgg9NKohrm6adZj8lwP//Dh4Jk49LxaQ+p0wjrKLXQTk0uDeB2AAwC+htQHcY1SSjYujhFm6WUgVY19jiTTST2Oct/Fw52GMzbek6LGdCHZskAagaLvWy8gzPVnd+8GlJYuE+eGa4a5jutZMcu1pL+JPNYOc60T8utixGaHsw65N36z7g8Q4KROFDq6D4pHutVaQYiuls5bPibNbW+YIb+1KZg0HuaaJwL6aQjBbFaOfKob1epJvUD5g8wglFKPJqIjAPwygGcCeCsRrQTwM6TO6o8dGhL9sJ3UvtyGUtx25N4IRgX9AEVRukHX5Q++BVXHmafvm08KjpOipIIvOeyym7bhDz+5AQBwWNZ0xqvV6TBXD+2mk7rJ3hBmlI/P8WxGdNXVQl2/nW43Otnt5MmcciZ10YfBN29Ks8ngI2ceRJwoTHbJm5Cpx3ascZLQNYyT2vRjjSyKqSET00w/zvuldDv+SD897wLlD24fRBZq+nUi+iaAJyENR/1DpGUyFgyDMLs4AZnT0GfOWCAahFbj6y78JqM59L3wahDGRpBmicrjNxmRHt0AH4eWEqOAKCYTvnyQOjCjfPQaUkqxm2SsEBwyasMlBecaRIfgz6RGdv6wdCbTb+LLg9DmqBD+a0r4Nm0cDSaCfNSq+J194+tqGPo58gtcYZjpF9V1Q/aWwkm9MFmEyCCI6MVItYenATgNwE1IQ13/HKnJacGgqkF4nNSqbGtOFMSNYFTIeyt0yJtcNAzqTNcJ9EFUG+rIi9/cMLqRf/48zBVu8yAw4kQ5w/Gs6eowJ4yTpFzapZaT2vWZ1izJ65jV5wzNpDb9Jl1fmKsqkup8MH0bNm026lZzVYYgBYzOVt8U45nux1g2kW6r3U66lk2BtDpvHSoPPVwaxNlIGcJbAGxQSvnrS48JZnIKEJgE1ClvBGnY4qFjEKbWExK5U0GDCytUfdcloAF/mXRTsu8GaCg6VDL9Wg1pvMEbUY5uqx6zx3YtbSMULprNtVwED3jGBtrnB4ZZzO+kRrAGYWomxff5uasmF5nmmX6Md39jI4BCyx1XolwopucGWJ5Fb+nowH6SYDLiO+flLUcbOXvzcPkgXn4oCZkP8jyIYCd1Uc1VM4pBoiB1P9zywEGsXTWJyYD2iKEosr/Tqp11JZhRLCifsFgKk/SUlzA3lqK8tDx3KZPad3FmA5kQJ2eiQOQvcJiosplS08WhxEwazKQ2k998Ya5FPa8wDaJepnhSYlIuJInZ1U5/X6bBhOv3+8KGLfjk1ZsBwHsvQuabz/dC5z04F+cMwuz9PSnstAvdSb0kWo7aeRCRx2RjP9z6GIeZfoxf+fsr8JYvXt8gxUaYa4SgMNerbt/V6PlN6FP7toK4JIG6Q/hMlVprHe5SG+kGTjV9ECFDH/G2S/DHjjBNDTMax7cuTGapBZLwVrBuX4w+vy/MtdAgMqJ9GqBhIuwFJAJ2OhRkzzPn1ZBs77Zj3LXuzSlHXWrDh1BNNTUxZQyioxszyd/NfSALVIdYGgzCzoPwSHSmpJhH8AgrTzsNL9+4ozF6UxoKDSLtwuUef/UdZQbRlMRj0uITFmNllzMJMzH58iAKc1vWctQXxWS8D92UL71xm3eMnR+jj7FjGSEjVIkI0SDMOkhzwkZeyYPwhbnGlgbhK0ZYQ4MIdVLH1rVccetO7Nw3y47tGc730GCEYbfZpqKYTA1Ca3Z9hykvj2JamPxhaTCIXOoyJTpfmGt25bkDVXhYdKnlpqMMimYvWZMcn+pc+V8e/+M778c3b/JviDZ8JhidXQukZiNXmCTng5BMGmWpudmHpZbpJyl3GtTHpHkLn5f7XPZvG9T0PiLs2JcWT7zmDr5upd0wyAc7OMNXEt/MpHbBjG4zv++i2cSt2/axY3W3RU0vMEIntWfa0GWkK/EC/jWUzrtAOUMGL4MgoqcR0beJ6OdEdAcR3UlEwaW4DwUqTmpP6YNUJc4qcXo2L60qN/0zmk7qkNDOjVv3Bs991oevqkVL6LUN4vCmTGbilFeDyA5H2gfhocPci3xjL/rRJs+IAnY5c8Bt3jEFEsARjmoddv3WefIbEZ70sDUAgGMPn+LnNSLhfPPquc1ifc5aTLEceVOdtxh74dnrsmOCk5q5n7b/QqNT0iDS19Cop1CEDg+dN05QCiUG3KbVha5BeGsxIa3A+mcANgBwV3MbE+yqliGVOHNbc+Ru+akXdJwo/Pct2/GsU49qJBw2D3PVmdSeFfIdy8TV5IIKlWISZUYxRc48AWI0COlBMU1cIf0gTPjGainch8RaQ5GH5jhRmOwV5b71MXbuGhdUmJiAqUwS9TmpQ1uOpoEA6XtfMxszadCHxBg70elktAnzMvdIepzMw76ckPmiqTyIxNhb9BryFQ5dyAgxMe1RSl2qlNqhlNql/0ZOWQ2YJgpAOw399lXAb/7Qx2cHCX7/ovW45Ib6phuWZsNJTaifSX3/gUMfdWzX8gHk+2aaHHzSeG5WyZOhmntoTFPXhs0PiONiaw35cjdKxfo8GsQw/qCIKJ9XylcohIzwKCbN4H11gkytwIdygmFxjAN3TmkDNRlHaC2m4X0QzUxsOuxDwrsLDWJhMooQBnEFEf0jEf0PInqi/guZnIguJKIdRHSjceyIzGR1W/a6JjtORPRvRPQLIro+9BxAVZJyOaklSVEyf9jJYPft5x1qdVEkOUW1pWYA+O0P1TMjORG6+Ethku7s6HKinHusPtwhSjcYDz11qrmaUvBlDr9MRQsN0Ar03EXfBn7u4TQI8lbZNQMdAOAPPrHeqznn5g9PmLLO8wghvSxwuWnmjofcn1FFMYVOFyq0JIzg4PL1FFFMCxMhJqYzs9d1xjEF4NkB370IaQXYTxjH3grgcqXU+UT01uz/vwDwfKStRk/JzvlB49xOmI49/Sr9JpKk6NMgNEKlKh9KYa5RfQnC19ynDvJkHQ8NnHTUj5O84ZCJUr2kjn+z1d8hDFHZVjBzAWUNIii8tCI48OMHsRnFlB6TzFF1Lic21nK+wQiSvlkyXmP/7ACrl/XE8YVp1d3MRmtIIaSXM+zL12GjHytMdKJSZJZ0f8z1UiTKyRT93SUbsXVPmEnRhjdIJPA3HCTlrn2Ap4LAAu0kpxHSD+JZw06ulPoeEZ1kHX4J0uJ/APBxAFciZRAvAfAJlf5SVxPR4UR0jFJK7s6RwXTsma9cinsuoXUsW3Ng5qcdrTEscgdjFAVtik8+aQ1+skk2kTSBICdnoBPX1CB8JphyVnk9JzUAvOsbG/HXL3oMOzbUjl7Nxs+OO/wmncCNoA7DKzWc0WGSwkZuMzUg7SUhwQzj9QUZmBFdfpoNxuqN/krQ7RDmAuSbN37uuvy95oGuO/nh7w0fO9OU6co0t4WUmAmtBTUuuGoxvUYp9SkiejP3uVLqfUOe82hj098G4Ojs/XEA7jbGbcmOlRgEEZ0L4FwAOPHEEwEUkUacFGMXLLY3guJH5Im1Iz3sssbDYmDQEZJJvXbVZDMnZhC6OE0HXM/IQPfBbypJX3UmtQ/2mI/+4E6RQYRqfEXhu/JGF5ooBzh8EMyxnftm2d/UDF31MR4tvJgbucuvkFhRWiFtREM0W87EJK2LflzNmQgx34SEjA6DUM091OeXGKHEIX1W9EeLMVFuRfa6SvibNzJtodadUUpdoJRap5Rat3btWgDVh9uVgVop7JebmMI0iKaqh5pO6iggUW5UXdQOzA7w/35wJ4AAJ2dJanZniZrXo5mJL4opNJSxzk8QmiNQFTLcm77ZW2GYKKY3ff5afizjg5ASrYq1XDzGPg3CfEZ8+Rh18itCndQxo5mE7NG5iSmIovpw0TA3SPCPl90aNI9dzkQfk8+7SDUIpdSHs9d3NnzO7dp0RETHANDxm/cAOMEYd3x2zItKy1HHw22XBg8pqWCi15AKYYa5hlRzHVWh2Yt/uiV/7w2TNDbFbsfNWE3JLHdoS8wk0T6IrHBhGOlBMPciZ/6B5cfyrYtSsT5PCKZibtG+GaHjmiHA5BqE576ZG+6Hvns7zn/F6exYpcrr3iWUmBqSD7ZvA3CHjXeHeIZ8zZPmD3liKZOdQ6LKTacAj5M61yAWJsaRSf1VAL+Xvf89AF8xjr8ui2Z6KtLwWq//Aai36VcinjymEnuO0IfGh8KxrmP/3Uukyb4HwyJNJEvfm4XIOJgbRM+bB5G+BpuYatyL0PuWWH6swjclr4tKYb8aUUy+KJ+IqAgE8AgvppP6cz+5mx1rlwaPyKHxGMwkZOMyw2d9QR9moUyNkHOMqqNcyGwmtS9/wnGYcDA4ztwWkjm/UBESxTQ0iOizSB3SRxLRFgBvB3A+gP8konMAbAZwVjb8EgAvAPALAAcBvD70PPam73pguZDYdKxk5y1P0lQHs0o11wbNKsMipGWlXatILJ9h3LY8GdGbB5HR0eBDE8pMKlqoRyswNQifQ/tmJgteEipNx7Omfe903zvWBzuM15UrVGImAT+FGdrp8xWkGkT9xax/xnGYmEz4aC9n2KfH3Ily9c5/qOFkEEQUAfgtpdR/DjO5UurVwkfPYcYqAH8yzHly80CuQZSPc2NDI1BCnLDDIA9zpbBqrvaybIhP1U7iMjvKAfJ9M49GlGW3ezKCKY1zHZmJyYWKFurRLAdJ1ZQg3YvXX/STyjGxCZClyQBpuZB3vPg0ZmwhZGgcd/gydt5KGC/J9cpsZuJDrKompno+CP8vPvJaTI7P7IQ9t0ZgltrwaxCKedcUrrh1B3bum8VZ607wDxbgNDEppRKkDYMWNBJbK3AsUq65kDQWQKXMd53OYS7oCph5kpVnWttUMorHxB/mWg3tlKJmzIdC29MlU64e2qHmXfGlPAjHuLqaZalwYWAYb+mYh1mGdBG1aQaA5z/2oe6xpSgm97yh2rLJLEMELpvxBJmYRuyDCJ3XJ8yV/THpq9sHoWqdvw5e/7GfzLtNQYgP4jtE9L+J6IQsC/oIIjpiXmdtGLZW4EqqsZsL+co6b9tbTrypUx3UBbMwXFBPautZHcWC8k1pRrb0PBEa5r0noiy73c1M8k2xwWtbIXVqsWBXRq1TrM9njuI2COn3syX95RMdnH78apEGoLyR+0x+et0TyWvefJ5Cwi/NnAnf81Qnv8KEFqSaXvYhz5E5xsVYgXJEVyfPKneEHmsG4SdjLAh5el6ZvZrmHwXgEc2TMxy4fhCA28RUJ9vRRFMqrrnZhmRSjyrMtQ4GCRPmKm76xfvcxORx4ubtV339IGrcCrNS6Ed/cCdeesZxeByz4XImGMCxiSblkFF9LBTeAnzZnI89brVoJrMFI0D+PYoKAsjnl9acqZGHLPdSGfGg/BFLLg04R2hHubpQ+WuIGajsLOf8W6W+354cq3SeWuQecng1CKXUw5m/BcMcALlMAm9iSkpjfAu6+v350aphlmoIyaRuyufghIeGUi2fGlFMuqS5XA678EE0fZn2Jvib//EDdpxkehQb36iq1FynbILPSa3X50QnkjOpmSgmX3RUJ9tpI0e9sjp9JvKIpxqaV8UHUSNRblSitmvpm2vI1xzKtgwAgRpEw5xCKs9SFyH9IJYT0V8R0QXZ/6cQ0YsaOXtDkEttBIytq0E0ZGJKlMo3/ZBgkUMR5uo1MZlJQJ77Zh4ufBDusaF25lFoU9WS8dlxh6QfOpZDqAbR7ZDo5zFzaTQkZmLP66pXVkeDsGubDeODCEGRKNcwh6i5MQflWEXFbwe4hco8iqkWFX40FVwT4oP4GIA5AL+c/X8PgHc1cvaGYGYlm6+siSlf/Mhe60VHhG4C9+yedjb5GSRJnjAU0nJ0AaRBlIv15e0UQ3wQqUkqJJOaqFm1O3SuSsn4kHDNwCgm1/lsDFWZ2FgbYmE/K4xXf4e7PrMMzGFC4b8KvVZtM5fDPjST+rm/dFT+3iX0NQHXL2d+5ro+m1kWiXIuG1P2skBNTSEM4mSl1D8A6AOAUuogglqZHzpUnNSOB9buPRBSkrd0rsBxTzv/v/H8f/2+Y56ChjQPojm7ex2Y5/Ut0qTULcvtgDM3nrS3gSsjOH1No1yb9UGESpyVjdkhCWuzSmhZDg6+pDozX0E012RmLtMWLjupy+velf1t3ounPNwdj2IzVn8fjSQ42dTWQiV6m4Dr+Ss5qR1arq2FhvSDGJWJqSmEMIg5IlqGjNcR0ckAmmmK0BBE+7Fj8WsJuK7015iTOin3E1gIGZW+zXTAhHbKlUaL9xHB2Qa25INomBGGSpyVjTkg0GFYM6VrLGcudUVH2eYaySckMUCODC58VkIlSdVTXqJOLSbzHh25cgIAsH1fs1tP0C9mrmWXiUnIsXIlyo3qqW9qOwmJYnoHgG8COIGIPg3gaQDObub0zcB+uF2O54ElSYVw+dK5mgxzzR8q/w86bv6hlEqTgCr2VcHEZLyPiFKbt+fehTaFqcNDQm+bXRm1cDw7JOyOrU3xZ+t1qr0XxA3UCvl1+m4yh6h5P7xRTEaYK+AxldRgEJXueg7T3FTPdlLzMGnTpq7pOb6G1ShhCk4uJ7Uddhyi9YwqzLUpX01IP4hvEdEGAE9F+my+USl1XyNnbwicAw5ojsuXztXQL2mGuYZoEIeCQbjOYTuSfWWdTZVZN7/xahD6uzVo9iG42bxgenT6sQLNlEcfNoWnnHQEvnRtUXtSDA+u4UyOE12SozjmMzGF5G4Mo0FogcEVYq7pqFMEUEPXP3I1OZoP3FFMxXtXuK3ELF3m6/yjhi/rkGkQRPQpAN8F8H2l1C3NnLZZVCJQnFFM4cyEP1czXjJTgyD4M6kPRb141xls534R5urPpC7yICRmko2L6hXiC0HoXavTD8KWsAu7u1TZtnpdoaagbkSyVpDZ800dQpp3YK971/VZkrALNmP1tvBlTUxuwQEo8llmHeXMh0HdjVTncHAVekUznuvhHpkG0QxCfBAfBXAMgH8nojuI6GIiemND528EklbASTGVUDRPMks3olILx6byINICZ+n7iMj7i47bxFQx49UIc43yTGqfBhFoYhqBjalOyfhYMEdJm3OaVFU+Jm36urS03hDTmkkyzbYGIYXEcsX6ALepRG/6f/qcU/LrsGEzVv3eGR4cWDamXPCRMlPdaMKYwhPlMtoCTHOaGYdoEI1XqW1ovhAT0xVE9D0ATwbwLADnATgNwL82QkEDsB17rkS5gSUd+ZJZBkn54W7KmZw6fLNNIBqd6lwHrkuzpUpvOGMpzNWdB6HyccDGrXuxceteZ5/pUMz0Y3xhA1/+ukKvbR4gWXCwE8lC/DG2MC4xE93wR5tUOpHboW1vtj4mXGgQ2XGXBpH7WApmYhcztRst6XPIHRrDq7naTGaiEzkbIs0HoYlyodFfQOGjcgUvjKP4YB2EmJguR9pd7ioA3wfwZKXUDve3Di3sWj5O+2oNSThvZGN+vyEndZwYdXECMqntT59w4uHsuP++ZfvQNLmkKNu579pAgWpooKvImX4ATYawb3aAw6b4GPzQRLl//s7Pg/t4V0vGp8ddfixbCxXt/0pVaJbGzg7iEh1O3w1jrpHyUuQoJlmIqtrSE3SijkVD+mpWn02FAdnHYpfaCIliiojQ6zbPIEJMt2UNwq95hYb8AsW1N25iamjCEBPT9UgT5R4L4HQAj83CXhcMtDRWaBDpcdemXwlR5H7w7C4/41Fri3M1xCASZYa5+heI+YM//oTDxc3zXV/fWIuOcBs9v4G6Ni+NYB+EsdftbCCc8f79YX2EATmXxpVIVpiYPKXPVXq/TjjC/9i8/4rbARTM0lWWW/uxSk5qj0+oKNbnMMMqfX2FmQsQfHpMxJOr7hbng5BQ1kJ12ZFxaBDFe7MWkw27IGJIR7kiD6IOtQE4VAxCKfVnSqlnAHg5gF1IM6t3D3tCIjqViK4z/vYS0ZuI6B1EdI9x/AWhc9Z5uOWEqOrC02NPfegqbDr/hWk9oQbDXM2FVMdJHVGYaac2XCYmwb4qNwEq3usoJlnCTl9NKfsBR5P4UMtTrxsi/6QQ14XLj2XXpXJeHw1VIsQX/WU79uvkVwD8xqQFriLUNpvDFbljbPqu9cn5IA7M8qGrJQYBwoRDg5ivzd317fKzJ2sQ2txmF+tz7RmFBtEsh2hqvpBaTG8gos8DuBbASwBcCOD5w55QKXWrUuoMpdQZAJ6EtHvcl7OP/1l/ppS6JHRO7fClilYgS0f2RscJJlWVMWpOg0jMUg0BC9zccEmukTMf8lxfrW6KnjBXYzbKNAifickULOv0AZZQp6x0JbqthpAROYSMFHp9+ul43HGr8axTC43VVVQvTTqLSmxHrttU9hXoW+OqNmBrEO6xtgbhorl8I/78Cz8TxhbvtQYhrQvudP8ptF/lEMpgnLWYBPO1sx8ERqNBHMpEuSkA7wOwQSnVdJbKcwDcrpTaPB+HZFr4zpRgXFy+hgZhayZRs05qvRkF5UEY730Smo2HH7liaDrzeZl7AQRqEN4opuyNsQRcTvvQn0Bkokk1A7lOlJYU5urSINIyIn6YZcT1OVyd32zG4+sHYTM1lw+iEtHFmdu0tmH7IISbP0hU7rz1wTZTujQI7nd6y8XX46wnu7upBa0l08TkdFKXxxC5qxin8wScfwg0NW2IiemfAMwAOC/TJh7f0LkB4FUAPmv8/wYiup6ILiSiNdwXiOhcIlpPROt37twJAKUmHUBYFmwlIYrTIGJ7I4gac1InSVma8yoQVlTQKExMLilqYN0Ll5Zmz9UhSpmr5NBGdZPpN+CMrHOPKslvuY2e+b6whqSNXKmqWcVFc+hmq5lJSB5EtVif7FeQri9EI9ffC+nE50P5fISeQ4OY73PpNjEVKJqRyTTYDD6oo1wwpWFoKsw1xMT0pwA+DeCo7O9TRPS/5ntiIpoA8GIAX8gOfRDAyQDOALAVwHu57ymlLlBKrVNKrVu7NlXFdckBDVepjWpjmPR4SP/qiJqLYjKLloVUc61qEPw4bvNrYrFI1U59YZVAKuF2HdVc9eEQUwkQbl+V7pG7yq9fQxpKg0BYEiCnQbiK9dmMx5ehXWz6mjZZg9AmJqc2ZWkb6ffcvSbqMEsNyjQIMc9jvmvc8XVz6jw8OGAN6fchPojGM6kbmifExPQ/AZyplDoAAET090hDXv99nud+PoCfKqW2A4B+zc7xEQBfD50oTiwJxulUS19NNVAKy+MkqcbCXJUZ5lpvE4+IHNEq1WOhM4fkQYRmidompsjppC6bdwC3DyL8VrkZkouGkFIbVS1U1iBCTagVbdjng+jYUUxu02MlU9zpeC5oMI/b9KbzFhzCVYG2TstRuyKwKw9i2OcyZC1xTmr3vSiOdcitQRS1mJrlEIcyzJUAxMb/MZop9/1qGOYlIjrG+OxlAG4MnchsvgO4Ny+7dwQgJ/ZU25PKUnBdlJ3U/sYsdqidz+Erfdf1mYsEsSBigBknojTBSjbBFOM0mkgc9JXUNlFJtnRpoZY931+XKvNBBDw1tjasazFxv2uccMX63CYmu9y3NC9gOKlDNIg6PoghTEyENCptzsMAh4Uzk9p69qTzFUw4Ko135kEw52gCh6xYH9Kw1muISEcavRRp+Y2hQUQrAPwagD80Dv8DEZ2B9J5tsj5zImGkLiDcZiptuEW4X6GWSz0N6sJUtUOc3+anLpMUr0HMn2YpW9236QPp/e04/DfFtRs+CKeJKQx1HPlcFVVA2EAtSdFfdiT9rc1t8fEn8ImOZlMmwHSKVrOY83Vf0iDcEna1zD1PQ3pdNg1+bUOPd2k9oQwi4aKYmtYg9Gvg13u6URazD3DMsttx+y1HVua/oWlDSm28j4iuBPAr2aHXK6Wunc9JM3PVQ6xjrx12vpiRuvTxylhLkgIyRxLzg1eboYxGg5iei3Hbjv3O8cqSyCWTFHfN8436MecNrbljMo7UjOcwwWSvZQ2iCSd1+PFKFdWA8OfQ/txm/2oAOGb1lNhjPEnKmkaeg8BsrIUGYTBWx8YMmAmi2fk4IcqShEOqDVS1Hv+9WLO8hwcO9tlxNm1EwGQ3wtwg9o6tgxDTrjmil1eVlfOmTGYZ+UxMSfUcTaCp+UQGQURTSOsuPRLADQA+MIIw10aQKDtRR5Z4bL9C+t4tHeVSl2OTqwvTSX3FrWk01vVbduP043nJUp/1ccetdibWcRJ9MINwLCuWQQimOYAJc3UwE67UhqukQjjDCzfDVW302fEALTSKUj+AlAcRJyobUzAfl7bBCZHVxJwAACAASURBVDvS+tTntq9DormSSc2FrtrM0kUDp5EL11d04ouw6fwX4md378ZL3v9Dll6bNiJi+2rYNA8L17fN9aLbBHPBALZACaTCQ0hybfPF+pqZx+WD+DiAdUiZw/MB/FMzp2weZmVUIDD5zfiCpAZWnJGOB7s2zQoViXD/jIP/KmDtqkl89tynji6T2gHOAecyjdmZ367QR84HsWdalixDUcfExG2gkeA3YU0JDie87SvodniNNR/LmUsFmk0a9DgnA6z4IKo05FqBVazPqU1FZabmLnKY/u9bqeVMancexHwrHIT66XqRbGLKo78MW6AvzHUxNwx6jFLqcQBARB8F8ONGzjgCxBWpK33lJZ70tTReUAMr5SUcUnBdcL15XWtcQWH1sh5WTnbr+yACaQ4xMZVMcw6Gac6168CccwPVh01TyW6H6WG+Ya7c8TrOVrtkfD6W1d5URcP1lT7ncnqkaKPJbrWARz9WmOhWGYc5X0iYq81MOKm5YO5lZslGBVoRT751WdUgHGGuDQluPuQaBGeS5p4Rh7kNMBhEw+QfCg0if0IXqmlJw86MdUUx5eYM06kWeSRFk0E05KROmFLNroWkVOGLdPoguCimoams0hYao29ey57pvjP0sTAxFcekeP46qJUox1yfpPVIZhWOAepDuqItgCzkV97obOEFkPIxUDJdmXNU6RBMTI57YTvsQxpw6XNwj0l9DaJ4H5Fbg5i/iSns+1o76Dtqt9VLlKtDZTiamtalQTyeiPZm7wnAsux/AqCUUoc1RMO8YbbvBNxRTLx5gHc+c2p5kxqEHQ/um1uT7LJhN23L1BCd1AEMgii9h/KGXYzTcDZ6D7xEaRyfTFilQbo+VpvyjO1ExdwdIsw4JGH7HpvzlK4jUehQNea8nyRYhnJZbn26PGTbFeaaDe7lTurseAAzSef2CVxag6gMKaEU6JAV65sN6GA4DMJNTLIGIVW2dZm/RqX4jLxhkFKqI3220BAry+ns0CBYSVFwPtubYrcT5nAyISVJmf0gzLHyPMV7V5QIb2Jy0Bd4/rrx7iYdBErt7uK9q264TRRFrHOP2OsTBAJOm+p2IrfjMjSRTFUZj0mfTbNd7hsQNq+MNjsPwuUrsMtWO6OYAgSHIr+i+jxwiC0hQ5f75p6pYftE6FO4VpupXWgNggsnlgI5XNqw+cw10SSrmKuRaYIS5RY8ZCd1oJ1QirqwfRCekDUOLinWflBcVhWFoumMK7GOtYMHKpyuUdzidzuelTHOPZbTIJoJcxXOFyAMABkjZsemr9UmOdVz2WYVQKvgPM3ppl/876uDFFG1jDi3IYmlRBwM0G6p6jTNWWYxjl5NVyEYuddlyQeBVNNXimfwTVT/lVDSIHITU5h1QloXAPCJqzZhl1HWflTmplkhNDgES4NBWCamPA+ClRTT15B4fq5AXV1VVho/iDkntVuDKExMfpX62NVTpe/OF3YnPsBjYrL6CbvDXNPXkgbhNDGFXZDspOY3xTTb2dzo3NpGNTnMERtPRpirI1y6UqzPIezk5qgQDUKV5wtpiGQKRi4a0mvym1USy8zlg/kzEZGztetsf54MwvXsGe/zrHlm15f9dDxtf/OVm8TzzBfm5Xzzxm1Dz7MkGEScVCtgAvziz511tq3ZYVM0a+64Ni4OrkiaelFMBUIaDHUNMTSUYte+yyZEOXwydohiiL/CvBtNmJgkRiJt+nbIqBjFJGwErJNaMDu4mwBx5lKG5mysvY6cETa245m7F5ZgpKXlS2/YytKrr0lDFLh0TwpHiG2JDsvE5DJ1zVeDcJqYMjr+5ZVnGCYmv0Cp3zfVQ6YODlnDoMUAUeoKlhSlcMb01SxPUNdJLWoQTJirzwehaU6Tstx0mHtdsFO3bqKcwwFnH3WGxGavZfur+16EQLpFUoa97RMSo5i4QAfBP2X6vPLpHeY2m1G5HMS6blPPqsHBmZjsCq2aFmcV44yOrbunAQAfv2ozQ6+ms47DPmMQlRH8eEALGTLNUlc6n7ZZZyMlMjKpHf1j7JDfUKtDkwEmrQ/CgB35oX8fKfvUlhSlh3tgOfaGcVJL4MJc3cxHGWGufhV9866Dpe9K+OnmB7xzAQ71OcCM89jjVjs1CC7MtYnbXKegoV0kD5A3Oq76rBjmWjIxIXsvhCOras6Er3poJ6I8skaDzenR7TCtWkzSM0JU0PErpxwJAHjaIx9SGcvmhAjCgF2ZwAX7OYsict4LKck0dB2FBnK4yqpw2mLksDrYlrZGTUwNzbMkGEQa+VH87zIxcZKiHMNe/sF9dVU47BJ6K3Nhrk4Tk6rng7C/y2GmH+MbhtnANaVtl87pEDf94v2vn/ZQp/+G80E4tSmOPtYmzH9fKgNva3SSxig7IzkhQ0vuIUERxefmvOlnvIarS6mb4Bz8OvPXrCCczsFfn0nv8WuWY+VkF49+aDWyvZCai2NSlJYdHuw0aVofajOlRPN8GwmFRhB2HbWYuN/apUHYEUtNOqntBmPDYokwCKGaq9Aty5YUpbDRSuz4EE7qp53/35VjnKSoj7sQkgfBQRppz+GasU7sP1B9wF22WM4HUVeDuH3ngcox0QfBrQulKhKdZEKrkxNiOnHNKDT3vAYNXid19Vp4RpVkIbHFWgYc/hhbiPKZjSwTryviST9PzrBqm0GQO6JL9jd5TExB60xruIU5zyVQ2g5737ovztKgiamheZYEg6hknzpDA6uqXVdQA+3YcWlcXej1UtUgwqRm3SMgFHWyriVIrSVD8iD0WKV4Wm64Z08+JqfZQQt3Sle4ZujYimYpmNC4jaDb8YRKG9dGxG/M3Ly+ysRc6WypTpC53jQ5ktZTMcNGfDy/EjZFdl7GiSuheipyaj11ItY4hKw3QuHD4VriSppliJbN/T8flCLA5jHP2BgEEW0iohuI6DoiWp8dO4KIvk1Et2WvbF9qG9LDLUlpnDPS2X3OUMubKIaXR3PYDMKVB6HMPIh6Di3x4bE+uPKWHeIcXOy/tCmm5ywf7zo2uo/9cBOAdNO67E3PANW8Pmneeg2DGM1SMKGxeRCC+dHUNkoaYKDpynXfkoRv38mZ2wZxmUHkjmLpXtjPSA0NQhJg6jip62oQdQozcgjxQaRO6pQGZx5Ex78uRo9mzjluDeJZSqkzlFLrsv/fCuBypdQpAC7P/vcitcWWj7myYDn1Oaj3sGNDrAO7I5l9Pg4KZRNTCKN631mPx8ufcJwjkqp8/N49Mw6a+cUfWvJDM2XXw0IEnPrQVXjCCYd7HljOxMDQHKjd6LG24NCN+OxotryEYH40tYI8yECo/cVqaY5NUdIgpI3cDH32tRztWrYrUctWZTrzsY77pmk+9ehVlTEa9r3sRZG77IgoBImnAFBvGyWkJrr0XoRrEIeqkKAJ8/atmgrpC8dj3AzCxkuQlhlH9vrSkC9xD4r0EErx7q7ID1ODaOLHtuPBNbxhrtn7kDwIAHj5E4/HmhUTcgZzjWuxK3wCnpIf1vPjcrbaiIiCW0Bq8HZp/vvBGkTEZ8FyOSHdKBLMlPpzyjm8L6yaLM3EPKdNM6dBcNJtP05K4bBFFFNlaKnbYU5H5K5sW82wr85raxBrVkzgccetxrMffZQ4r0avS0EVEirnbNDEpCGVjZFqMTWhxdSFOdViZRAKwLeIaAMRnZsdO1oppcNqtgE4OmQi7kFxRYqw5iiXiclw7DVRrE/SIJxRTEC+waQ27DA6Og5/RR3Vly/KVsNJ7Xi4NXJbL/klP9/5pGOAbDayfw8pAoUvyyE7hwGUWo6S4I8p8g+KY95ifYwGIZmY+CKATPRXUi0D05VMTIyPReoeKJYzcdxjjV7Hp0HM18Tk0t7Tz/Ql9iK+7HidulQA8MxT1wIA/uiZJ5fO0wTMy5mPTDtOBvErSqknIm1G9CdE9AzzQ5X+YpVLI6JziWg9Ea3fuXOnHlthEJFD4uGc1M5CZB2DQTSpQdRxUqtyHkQon3IxkzrXIrWW9CW/abge7vwceTSTR4Nw0Ocbl56HP7eVTpCV5XabjTSkisCmMPDEE1OX2pErJwBU74VU7wqoZ2LiaE6d1MUFagYgObQ5M6zLx2Kb21w+FpOOiGQHvImJTuTsbCctK2+iXMCDZDqpAbnhE6dldx1CJQE4/fjVOHxZr3SeJmA+P/OZd2wMQil1T/a6A8CXATwFwHYiOgYAsteK11QpdYFSap1Sat3atSkH5h4Ul8RTdUa6Y9hzDaIhExNX1wjwm3yGyYOoW9hPglSpMjQZLYxBpK+pkzqYNMd8xSRveu4peaKXGDJa0UJl0076eVlSdJsdgL98waNxyZ8+HSevXVn6zKaX723CXB+TbAkIZSCSpJSg1nM0vomZLP9uFLHlaPgWvlLiaXEvzLHcb20f63Uid/j6kJF6IcvM1GwBR+XepPr7uRLlEjW/CCMXyhrE8A/TWBgEEa0golX6PYBfB3AjgK8C+L1s2O8B+ErIfDHzoIhZsEwUkxjjbZlVmtIgpKJlvqlNDSKUDhczqWNikjYv2cRk0eFwtmroubwMInDBmzS86bmPwp8++5Ts67xWUNdJHVKUzcwf6XUiPObYw8REMZ7xlM9p08HlQbClNqwoprymEHt91bXpZYC2Y9bpryhrECEmpsOWdYt7wWmLI41i0h+m19iL+N7YkqAqt+VNzY361jWoQJSuZz7C1vDei/nhaABfzpxxXQCfUUp9k4h+AuA/iegcAJsBnBUymWIeFCnSh/sRfQtaq8SNm5jIZhAuE1PxPorCTUyuXIU618JliUqdw4D0Wnodwmf+4Kml74WcMyJCjPmXb5YiqUQTU8VMKUnuVam5Izm0ucik7K1kYuJKbdRxUksaRM94SHR5DnajS5Iqs+wIbUQZmqXil2ygg/ScZmOfd9pDMd2PsXyi6ywPMmwUk8a7L9mIP3jGI5xjShqEkEkdapoDtGm8aLXbaC2mkolp+HnHwiCUUncAeDxzfBeA59Sdj3VSSxqEqm7MvjIJZonkJn5CMczV5cBF0UwkxMT0zheflo0tHKIhrSklsJnUggkGSO/zaceuxpNPOiIbKzOI5zz6KFx+yw6cvHYFADmRTIP7SNr0TeQbc2AUUzeKMB1Xa+lzBeqkPsxShU+ODqkyqqbPRJ6gxjEIgY4SvY7GN7a2oemQNIjKpijmeVR9b5I2rO/Frz3maLziSceXvudzUj/yqJX4xY79OX1OBDwCXBQTFykm1fOSnxF1aDSIecyz0MJch4JUiVMKUbSfKTHiyXLA1bH9u2A7qc/71ZO936mGubrp0LfDVfdmKCd1oIlJS0c5PQ5b+tGrp3DkykmDAVJtqUeqVWTCXaCu6hOSnNRS/SFnPS9Lak7p4zUI01eg77c9t+0TuvDsdfirF/4SAEcmtaFBdD0lI9hNf54CVx7ya4bbRm4Tk+38BqREufR10/kvzIMA9LU0BU11L+I1CC4SzpUop1R5DTXppLbPMyyWBINQwiIV4925MFfHRqBNTNSQk9o2O7zh2Y8sHeegVKHiUkgeBJVtzJt2VWsVuVoh2pA6h7nKWdhlj815TNjMJP0+T4dSChf9aFP1fAGhj+5SDVUzpaQh6Ug4sq6vTt0m87OQsfa12H6QZz/6aLzsCcex8wKZicmYV5uYuFaddUwlqU+vfEwKXbWrI+v3LgZhRjy5NAhuDWn6JDxwYA533Fd9Lqpzp6/695aimPgk3ChAg2jeVb2ondRNI074QmuS45kzR4WE8HVq2P5dkDt2yd8ptxzNjjmI0Vd4+cY0EOwTTC3/OguHszW7+kwnSbl8d1FTiLNjlzcNcpjy1m9+APuY0s4cGfbluZLD+ATKKNys4tM2LN+N+ZmGVPlV02dC38YyE47YsUCqVdj5BynNvGO94myV+l2w0V9us1HJjyUIO1oL6nX890LPzZnbZhyd5q69O6zUfZ4Hkf3f7USsiYnr8dKJ5GCQShRTgxpEyQcxj3mWDoOomJgEVZRZ/L5kncIH0YzKatvzXfZgDaWQrybXRqehnxVN7z1Z0xcTdQoPxqpql3b2pEbZ5+ELUSwxE4KoF9sS70dety6nj6O5RK+nD3M1us2lQQRuilxkUq7JWPRyUT5eDcKgwdGSM05UyUkNuIpUcj4ImVlyprlEVQUYzh/ji2LqcvdCMF/p38Ts0b1nul8Zq2Gfds9Bfqwd5tqLpFIbXDQlnx+TTlw2p44uUe5BrkEkSmj2EqgGijkTlqTfVLG+2JIUdZbojKO5uMEfxCgYDh3nQ8Wr6hwGDBOWor/2zfRx9R33lzZzp3kAlgYBmfmZFPzorc/O7c28DyLcxCQ5qUWHNhvlE2Zi0m9tmutoEFzQQN7MhpNu46TSqKfXiUR/hb3RuZJJuecJqP6GUiIg99vpjm0dxh8jmSk5S80cE2RQfKf8/2d+fJc4FigYhCuEvspY5edUJ2de8L07AADf2SgXy6wL84zz6de9dBgE56RmpcpqAw2pEZA2XRWtPuuV2ZbAPSjLeh2nOpyeX7/yUmVpbLaVumogzTL2Z2lKNkJDkJo/cOXtAIDr7t5djPVEoJQ1CDmT2vztjj18mXvTty6mI2xcmi5OEg5NtpQds8ymKPogqlE+0n2TaiCZ85iwy30D2kQolNroVK9P1CCYe5GeM6mMBaqh0pwrTGsbvVLOhHsN6fOa5Li0ZPsTac3ZRyVhgPfdRIgTJebeEAg79s0CALbvlYtl1oV5vvM+tWHoeZYEg4iT6qYvOZ7TjQ5BY21bc0TNxCpzsfFTvQjTfVnaMVep/p6LlOc/9qEAivvCPSe3bt8n0maD7bjmccyacCV8mQ74lGY5fp3zNaV0V8fam4MkuWsaKnOTsBlx2pQkZDC/dUdg8JpeewPlxnLzFrkmFTKy0FXbxCRrEJ3KWCkRsGpWKZi2PVaVrikdy/8e2oTDRXRJeRCcD6KOxn/s6mXs8bwlbi508eY2rlyLpE0B5QrNTaMpY9WSYBBcBIpUA4U1D7giNCoRF/Onl7PFTnQitgmJBuek5hb/muU9vPapD8OaFanpRT9fHGM7/9JbAABnPvwI4zw82I5rgpbGPagdhwP19p37Le1JdlLbgoD+N6SAm0vz4h3PkaxBBEarsPkjdaKYBN8NW+IiSmPquY28n3AmJrlsNSdESc9IJfpLEAZs06q+Lj7CTuU05vPW8GPZ83C44taySeewZXxaWD6DNjEJgkPquynfDEmbSmlOfz8d5n7M6imR1rpoKmR26TAIW4qpEcUkh+UpK+KiISc1I/1NdCOxry5QlrJ9Dec5s4OL7o+e/eT8vauwH6dBcCRzD6pkS1dK4fote7AzU7NTmmVNrZLDkmtT/O8HAP/3Bb9UokG6b1VTibQRVJmgFNHl6vEg+iCsPAGA2WyZeQGHJiOamKQ1xGkQYeY2yRTEMcDvbNyOmX6C+/bPlsYWuUKhYa6Gk9ogx+Wn+8w1ZZ8Dp03puYHC/yUKDgkfTQnwGrH2m7z48ccCAJZPdERa66MZDrEkGEScVLOEpUJyipP+BFu6bZeWyjQPQy/AMAinBsH5IKrjbFXb1bLyub+U1uFfOVlITtKlcWaHjpDkZD8kKR1g6eDoIpLpsKd2VTtNEoXXPPXEvIRCLs3ViGGXI+GqdLiSw7goJpu5clFMUj8Irm5T+l1eqxvE1SZAvQ4vlMTc9QkRT1JtM45mO7zbxO6Dc6X/+4y5zefH4tZdnbwlroR3iszEpKMOHf4mbm8BeA1CMzX9czcl9Tc515JgEFLoqszlGX8Fs/Hbm4YrK7kOOLPDz7fvx6U3bhNDXe2Wo/oYNzfX9J6TYLpRVOnqtXXPDKbnqr4Q1pQgbIqsiUmyuwvfl53U/LlYH4TlWHdtMHwehDCWkZrFLmpsNA4ymgUNouRXiEqfaeR5EFxEHrOR2w2DADkjeJAkjL/CoUEIDEIyMXEMwiYjd1J3TA2iOKcNKQ+iDoPwhX3nGoTg3Hc57NmaXhlTCwlbr4vWB2FAqgfDdrVS1YdK2jg4ExMQZmbSUvlEt3qLOVusxgNCLLYpnXgTvkqx49lxLpSQCX181j9diddf9OPqvIIZj7O7c5mhUmkHSYOQHhZbi8l/E9E+HlZegoticuU28E2nqkyb0yDywIGAKKY8d8Mey+RB6O/KZiPGxMRqU4zpSnTM8lqMPqdNA1AdD1QlbP1/ydzmiFhLlBFtaOiZTWgQ9qPjCvnlor8A2QcBUNC+8mefvw7/eNktMvEemofFkmAQXASDlCUqRTEB1U204qR2RCTY0AyC0XqdkpQEk1npr8kSXfG/ywfRT6rJUwBw9R33V47VidxhTUzCw819nyDXYqp0qnNEtgwsrSeXxrluYGzoquB4dknNwkZud+LjaGbzIDzSOK8NC8KArRXUyAiWylZL68KksZjXpUFYY2uamKRSG65ifasmy05p0QeRveZ5EMK6tzXWEs2CuTv9OB3zke/fgZPe+g1Wg//ytffg/VfcLl4LN3cTWBoMgnEOSaWoWTuhQ+Ixx+rfPkSD0CYSVytM7kGRpJjYkE60pCSamKzIK4CXuvqDBBNcQwHu/Nym2KkTxeSWKk0QySpypYS3IzY+pTlcgwgtk8Cbo/i5Nb0hpi4pkYwbK60hMeM5qTqpxYzgmH9G5IinqmbJ0pzdY07DtGkuNAgmD8ITZBDqpH7R449hz2mjcFKnE4sh9Er2x7gc6/or12/ZAwA4MFctJVMXrYnJAG9iklRRvkwC4GcQdXwQeiopoQaoxyBMCVCK/efizF0SDGdikiA54Lh7zEly0gbKPZQ6GICDfTp9rdx42x/TE+z5+vvVCCnBSc1sBD2B+UjhqHoeE4XUXI3cCXVSiz6IpOqklkxMXFkVlw+ict8cGhJnXgKq15fXYmLWsmRi0kM3bC5qLLkYhP3TSkEieR5ENr8r+osrkw7IgRFEVYFKdpaHY9GamIjoBCK6gohuJqKbiOiN2fF3ENE9RHRd9veCkPmUUqUQNw0xHV4IcwWYxJ6Kkzp9/duv3xxEV3o+zi5dVZ/1e2mRmhqEZLPUC8s0G+kzcGsudVwGahCC1MxtoJyEKJmCeCe3rCJXy2dk81jjlVIVf0zxsPIORk6DCHVoT3bTEMVZK9lRf73cR0MLJNV5AcuhLUjNnDCQ0iyYPzgndSfKS1rYc1fmlcJ4Bd8GUDXZpI2IKlOUrsekN52LCXP1MO2DhommDoOYERJVcxOTQYck+Nl7i9bQuU1fIV0X9uPiimYMRVN1ncahQQwA/LlS6jEAngrgT4joMdln/6yUOiP7uyRkMu4B1P+Hlvsuatgk1bGMueaznpotQHnxyfbV4vb/+6ufkNFQpfmF//Z9bNp1MKdbSvhyOb+5Dbcf8z4IDmweRI2wX9EuzUhWBNnPYx+XpFU9zm4gD9QwGwWGPwPAZBaMYJcv0XSR6RcSQn6lrn1AlTFyfSYA3geRJIp1PNcp1lcniknaFPuxEk2aIf4KlwbBCYncvKXvWJsoVyW4BK1BSA575hnRQSpcOLGkQTTBIGz+4Ot3L+GQMwil1Fal1E+z9/sAbARw3LDzFXbb8nGpXkqiqlKXVH7ZlNoBXjKWYD6kYrgfV4iMofmme/cCKEwkkqkrZzzGzTj7aScBAB573OrKvFzoowTWNFfDr1BPg5DDXG1mlDNLgYZy0ln6/k6mBwAfmRSJc9vrbaqXahC2FKrJ5TSIqmZZjWLS/4eGjHJVAYqsZMZJHdw6M90UOW24IjXrTdHa6GYHCSa6fDKY7Sx3ZVKLZS6yob975okFfQ7hxf5or8Ag7HFizouDWXKbfmrWrGoQXI20urCpe8WHfjTUPGP1QRDRSQCeAOCa7NAbiOh6IrqQiNYI3zmXiNYT0fqdO3fmGw7bUU504paP5fVSrN8lraFfbrAeCnP9hEiKeiOzx5oP5GRPMwh9DsvElGgTUzHv009Zi8luhIesmICN2iYmyQFXsaVXF7hki2Udg8THjQOMBuHzxzBM/SvX3Vs5xhfg0zRam6KqSu5TPbcGYd66Ov0gAK3JlOmV1n1q/hBCRpnNi2MQnDYl1RTiEgx7ggYxN0hyTcuGvYHmJiam3Lco+GU037qtqDHG+WPM75jYNyOU+877QaTzuyr3ihoEyyDKeRAa9hqqE6orfefau3YLI90YG4MgopUALgbwJqXUXgAfBHAygDMAbAXwXu57SqkLlFLrlFLr1q5dazyAjKodGmkgZDvGSVnCrhOWam7e6zeVG5PwVTt5B6ppx9UPl5QHwZmu9Hn40McaJibGRCEVZdPXoM1m5lhpUzRBbHBwCqnPtF2qgasc6gLXcjTXIBiTjX0vtA/C1iA4E2idUhT6f3vT5/IrirHWGhqk/9s5Oc5SG4Hx/BwzkTbFuThh84IA3hwF8GGuUmSgJmOZUbLCpUHY83DhpQBwTRb2rXtLSD6IOvciPX+YD8L8X/KTVGhZzGGuRNRDyhw+rZT6EgAopbYrpWKlVALgIwCeEjKXWHJAiFXmmr1ITmpb1a7VGtA49b9efltlXiCs7r/ZI0IvNk1GZSNgKmACWiWukljHxBQL3bIAftOf6kX4zazGjElTJQ+CkfCcTurs+KfOORMAsHpZD0etmsTmXQfL9Ma8hC2BbTkqaRAcg8g0CLtke+6DMIZLG12xLqoMXnJo205fbvOaY4IX9HkkH0Ro8luSVGmQ7O5zg1j0QdgbX2q6siLyBOc+oKXx9PO3/+ZppXkk2J9Jpp2v/SzVOHXTLTlrPtw3BWRMDYwPgtG8NEICZADJT1OfaYwjiokAfBTARqXU+4zjZlDyywDcGDKfVHJALEXNmBKkfsn9OLHq0Ref+W62+fDb5+MkRekBNJt9aClVKlDH2W013VLy1HyimPRGZlehHcSqdN8A2X5cN5NaX8bKqSwRkQgPWTlZKZVeX4OoUXSO8cfkUUwD2wdR1XD9tZj8okDu8wAAIABJREFUv5/kpOZ8EFpwsDfnXodEHwTnpDZpNOkItbvPDWQNwt5A0+qzfGVUX9vatSsn8+NOBmHdU0k6f+3/eBgA4KVnHJvTkSg+cKBixnMwCMkHUfHdGE2PTPOZC9xlu4qBShiHBvE0AK8F8GwrpPUfiOgGIroewLMA/FnIZMWDUj4ulaLmTAlSv2QpD0J/5qbLnL/8GScpSj4Ic9H6TUxVuy2QOt++fO09FRoHNUxMnKSoN+n9s2XnXpwkFROFr4KpiS0PTGPb3hnckCUOlehgbPpc2Wot4UkaBFd3i6trBDAbAaNBTIkaBDJ6jXUkRTExZhWA1wrc5ihLg8g2nF7Xuj7GxFQ0IpI2Zz+zFDUIxsT0/t95IoBqeHAqZPC/h+Sk1mSsmuri6accydJb+k6gBqGZ6GQWiCCFHnNdFycdUUySD6LCIIw1FaoFcNc9THTUOKKYfqCUIqXU6WZIq1LqtUqpx2XHX6yU2hoyH9cUXv8v1Y3nis4BVYmuHyurFkzxmavOvD5P8b1wDcJWXc1FWzCI6jk0vUBVgwD43ryzcVLZNCRwERq6VIGd+dmvIYFyC/maO1Ob70U/2lT5jNtwuxFVYu71bbTpePOvPYo9L9tnWtiQuHshaRAcQ5MjupI07DEgiqkwXQX4IBwmJluDKMJLYY3l7wV331xOanttPuvRawFUN+e0RapVdytKs46lpDNNRxQRPnnOmVgx0allYpIS1PTGqjUjqff3gAnjneh0SnOUaU61ZfsJtNdQXcn/Fzv24fM/qYbi37u7fse6RZ9JzWWqAukCF5vTixtBVYMwNxjzYfSV2zA/XWnVfGHrzAjx/KYGoUMEpTyIIlrF/7PGicLcIMGyHh92yIV2hoYzxkz3MikChbPlLu/xmy3A2/R7TDRO3k9A2LxCNn2Xk9q+F3kUk6BBmGtHqo/FmXb0eDEPgmEm9rVJPogek0ldCC/VkFiA+a05E5PkpB4kOSPNx3Z4zUu6F92OXDTQXvYRcy/K3yk+O/PhR4hjcw0sYwySsJNWOwi7F0AaHZWW2qihQYhXU+A3/uX7uOLWnZXjL/vADwO+XcaiZxDu0EDeARdakrdvSTHm93btL9evt6GUwmufmtouTzu2nIPASYpSGKjLxGTzqDzyI8DxrOeVGAQXalep5SMlRHEObU/kTmne7Dr5+jVVgYBjEJJvSj/ktlRm2rBzmsUwV87ElEUxMT4Ie59zRTFxkXK8iSn7jPELSWUrbOmWy4OQfDeFCc12JlfvW3GPy3RM9+NKU5xuJ0I3osp9G8TVyqiartBii1KBwYL24rOjD5sStY3ZzHeimbwr4rBnmdAKHwQn7KSCg33/7HtsrtUQC5N0HQeFKC0XFj+DYJLDANlJndrd+Y2ATZQr+SCKz75183YnXYlKI2w6EWEuthY/Z4IR1FbT+erLgxgIkqJ5PRo5gxC6WNmLlHNo93KpsqpqV++xbLcF0lapGvrecNU1WRMTY0vnckKA4oG1Hev9pGr+kAodcptiHq3CRDGJAgmrQVR/Oy6nx5VUJzmpud/PTn6Tor+mchOazVirJttJwawy3Y9zRloazzTL6jM9KQBHe2BVNbc9cLCPn1gh5ibM5ZWaKXlTzuwgwaRxkbm5rRKam1T8JpOePAiicpY9ABy0GcQ8Eude/sShc5ABLAEGIW0EkpN6wEZHaImVUXMFDeK4w939Y7XTLI0U8UuKko13holiEp3UguPyRaenAWLmA6AZj37wX/aEdCGd/csnpecd+BmE5Izk73HGIOx7kf3/id8/Mz9WaEi8BpiOKY6lGkT4pph+bmyKSVrPq1oOW7I1J5iwfDdSJnWiGM3EEcUkaRBiMTuGEVfzIPhnpMesOVmD4K8vZazCurAZxFzCMoipXqcyLydkANrEJDt8bWzcurd6MIN+3s844XCxcCGQrm8tnKU08M/qwPWMCFFMEeODODhbvhem9hHmoi7wmsyKMSwWPYPQPypbitr6AZVSqRoomj+suZOyTdHMAuW0OKUUPvTd27Fj70wewtbrVKUjrqqlZJeeLvkgwvIg7AfrjBMOB1DeyPUDOZVpEO876/H44VufjdOPX519zjFLSxrvCNJ4zFS19CTKsTV3BB8SUJYWuXBNKSKIM4u58kdMGs3xXMe1iPhMajuMUWoCZK83jdRJjcpY83rMsTa9szrMtZIol5lKjMkHgmYi5XnwmiXln5mY6cesSXOyG7EmTY5Zis16GE3NhzhROPXoVfjcuU8VfRtAFp5rXKMO4eaS+yoVc6M0jFWqxcT5IOygj1ICX81chimhtEkouv4hCxuSY5bzQRT1eWxzVPnzfG5rozOlH86meOv2fTj/0lvw37fsAJBKBst6nUqG5nQ/rph2imY2fh+EmAchZFJzZpXpufS9fmCJCMcdvkyWFAfMRtDlNwJOkpKKznE1k6TseKCQxMzNo8u0zpQ1iKoPQsof6QpOaju6DUjvHycJK06DEMxtbh+EdX0D3t/U5bSNgfte9JMEy9DJr838TEPysXCSfrcTIaKy1KyUytZ9VSad6nWqeRBCjg4XsQbwPiQfkgRYs6KHqV5HTH4D0mfBfPZzDcKgQymVhvEy62KCERKBzCyGKt22BmEyjLoaxIrJ+TGIJaNBcIvUtq9KTtxubmJibMIdnkHYkpT5/R9nYZqTvQhrV01ix75yeNn+mQFWWJFNUuhcrTwIZrMFDF+BqUFkD/pUr7wEJGdk2n2O1yCqJiaHg9Ei+m++kuZDmhujJNEDwDu/lmaSmg9clzHjSfeCS+KS8kdyJzVTP4rLCOYkYa6ZlauyLatBMMJOX9AgImajy53UtgbBBEZMZ5vRsony+pwSypnbgRwaduBAP07Lr3MaxEQ3qpqYpDXU4ftox0pVbDVHHzZZWd/2d/S6k7LKgcJJbV5bek0FHZLwCaTXZ6+Lg3ODPPTc5mu2BnHAYBh16zJJQSihWPwMguk8BSDn5ObGkT9UwkbAFZ0zNw1zsdkPCodlvQ5WTHYr0QMHZgeV0Fcpm7vMILS0n/4vhblW7KC5KcjcCPgoJskZyWkFPWazBaoZ6BoRE8+/60AaDWZujO94cVoqYeVkDzb0sNXLis+4onOSBqG/Z+aFSFKzZPbjNAiAt6VzPgipIyBXAwngc3oKwai66QfnQeQmpmLyg9K6EE1MfAlve1PMfV6CD4LTIGo5qRkB5syHPwTHrl5WGathRjT2OrwG8c0bt+HbN28v0d3j9hbh9wDS59a+vvdf8Yt0/pu2VRiEbXE4YCSiSkxM4/4D5ehKKQglFIueQXCdpwDegToQNAhXv2RzrHmzuaxL+9iyXgfLmE1j/2xVg5Ds3T/dXFRhnLA0iFddcHVprF5I9sPdY+6F9MBOSiYmJrdBazQV6V3YQKUOdEBZg3jR6cfi+DXLKiW/r7t7d16S+aGriyCBZRNVM56kWR7GMAhJyJCc1NLmtazXqUSgcD4IKStZimLicnokLYtLqrPj+DUKE1MxfvvetOjhkSvL1X9F0yMT+w9kkUnGept1RM1NchqEoE1JzuS0blpVgHElmZllQtKWqtV5z/vUhpxGc970nIaGJATL6O/aQpTWCnbum/X6IA4Ya5tr8GTiuz/fUfqfY8h1sOgZhBTmmquBnCmBySgFuKgEywfRdTMIe5Evm0gZhF0naP/soNIwPdcgrAVtbpyHLUu/I9la78tyM446bLJ0XGtTXFVIewHJkiLfkSydt2qO4lRtSfpLP6tqPTbj+YsvXs9+d+VkF/vnBpY5kTcb6Th887eSHNoS0x7Eiq0ptHyyyqgUU8KjcNiXvy/6IDgTUy4YVTWIvhV2fDDbcJZP2Guu+ozszRjnEVZ5eL1BsuHPzL1YMdktNeDRzwBn8uA0CLsXi0lzaLvPia4cuqq/o38LziRt05jTwJiY9H2zBb+UjiqjMh9h+3mejwZhM6LQWmQSFj2D6Ce8JMVpEFpSsrUNyUkdWxudKf1whb3sGPjJbieVbvvVH1zyQVQiULLN93/+ysPzImTSb75vZoCJblTJVtWmmt3Thfop5UHoB8F2wrPRKqIGUY0HB/jIMg3Ob2JHR0l1lVb8/+2debxcRZXHv6e7374kLwtJSCAhZCEhGpRECCgR0AEFBRVxXBBwnxmBUccdRv3oODgqCIrjBqKiOPiRGRFcQFAQBIHILoQkJIEshOx5Ly9vP/NH3dt9l+r3Eki6+4bz/Xz6k773VXd+fW/dOlXnnKpqKKAanwhULt4U/t5dsbLDu+bSWWj+XnNzXaHYGIf4XExh3fzF/c/s1vf6JgKWy1hzjW0yyOmOkwHL0v3zxab89aInEXj2ZQWCWzBvc2QJ9uEMREMhl45teNJnIZzzkm70fXOLfOnPAA89s42f/nV1bPVVX8pv/LsiWXOeeTobO91vndieTn93Qer474vWieTV25kwENE65Yu/REn+3mi23/MxFtnPYhohndEbjCyTo+/bgOeFjiAa6/LFjKEQn4upUEZDd98gC6Z2cOGpc4vnyi077ottAEwd2wzA05u7OeZQd65sDMLjShgccltWlg34elJMfb2/lvpCLOAWJXX/PL2/cusKhtcyanjDRiTpHw9/b9RolwtohynA0cydYqPoEdNUn2drd9wHHN3pLCQ0EE8kVuYsN4Joqs+nFkQM67JvRndy9NfVO0AhJ6lr0RoYjOh3h59Npkf66kW5nepCzbERRF/5GESDZwRRzsW0dusuHl6zPZhkJpHyQ97kk2QnA+C0K0pLTkwb2wLEk0R8Xpk/PF5y3fgMa3gN2xr9I4jk7wvnZyjpIHVyBBHd6S45Oz3JcAZkpPXjfGR+BDFYJs3Vt4piuWCkb5Ja78AgqnHfY2MkRc+X5ppMARwuBpGsSOXcGd196ZTYch0BZ3jStXt8mxt5bIk0XuV6lY1FV0LpuoVGNjkyqfO4rsC/VDO4h6er179rV3pJjPSwvNxiY76GrpzrsdFjIEZ0R/X5GkWPAWzIpxISfDN8y2085XYw9Ae/k41GmFWW/O7GQo6egcGYq6Q7MJzJsr6AfVhXG+rSnai6vMTqRblrDO7aRTUPF6RuqsulDGD/4FAqpgClpIZ12+N1YdAXgyjIiAvd5YsjCPfZcpsGRfFlf4XGsLWMgUg+I39ZsRkoLfkdJRmD2N5duj8jJcf4jMCXTp9XfL+ne0Jk3kCEljnpEx5uQlSyJ+ULUodDxrBxDT939qKpgD/NNXmusS5HU32OXf2lB3ZgcIie/iFaUv7gMAaR9h8n168p18B09Q6kvheckSvkhK5IT6SzZ4C6vKQafV9PsTNo1JOV300ETPf0e/vjSxOEtDYUYg1B9HO+FUGT/taXHzw69Z1A8TdHRyc7ekKfcCIIX8ghEm/0S2mgCXdUcC2ijX5fmfrmyhfoTjR05Wb4JlFVbn9yIxt2pI1gc326k9HnmZcCrjeuGh/hdpYZWfoMRG//ICLxjlGIM1Sl3xe6PnyppM31hVhDN9zSLgeObmJjZ28qbXS4zax8Lqnd3VI1Svg7V212+5R//tePectF61543WPXOKhvbY3pzDtfkDrkc2+YmzqXnAcRdQ0n3dVJfJ6Ndx09lQtOnAns+cqwmTcQYYPTnmi8fP7jclbeNw8izOY4oK3kUxQRvnDaPKaPa0ndiL6BIT59/SOxc43BCGJwSIuNUNiIJTWUW1q6u28w1eiXC1KXczGJCK2N8cbZFwcJNUPc2IUBuOQ1BryTgDp7+r1D7dbGAlt3lhqjMPh20uETUrp9hqehTEZGmJkUde+s29ZDXV4Y1xIP2IuIyzaKNPrlHm6fO2p78VqkG4Lmen8Wk+9+HTtjbOw4TDAI611SR3Jk0tnT79VQjCFF7t/27n5GN6fLhtdtR3QEEewb7XNjjm6uixmT9UEvftKotN89mVmWnJgZJbz33YkRx3AZOMnr0d2bXgiwLp9jSNOxxSOnlra7D0dKYV1cstq/dtO1Hzi6+D687tGU0mLbsptB6tHNdbz5ZZM599hDUuX7BodiHYJt3f3FrLKZE9q8+kKi8YrXzp1QfB8+j76O7XDUnIEQkZNFZKmILBeRT41U/tntPeRzUqzsIR0t7ji6V/GzQe9sbKLRCHs1OyKblm8MJrclM4Ig8CkmGoLfPJLevqKloZByaXT1hRUpXpml6GKK38BdHhdTuQmj5Rp99/8VYiOInWVGG0VXQsRdtmar22px8uh0TnldId5L6+kfpLN3gI5EFgzAjPGtLN/YVRyphQ/ViXMmpMr6ArObu9KNJ8BBY1yMJdwSEmD99l1MHNXoDWw3JxIH1m8L60UitbM+HEGUrtuqTa6nOclzLZrLuJh8BmLRdGcgQuMaNlBvjGzTWtQRGIioe2Dttl2x0W2pbOAqiTYwu/wGwjeCKDcKBehormdrxN1RqhfNqbLNCaM2XJC6pWggStd5c1df6n5EibsTh9jR059qA8qtNhx9Du4OXD3hPfI1oBPaG2Ij7fFtDdTlJbbO03AGIpnG2z84xLbu/mK99bE5Yny2d/fzxvmTOeqQMd6OV5ToNY9qKZemPBI1ZSBEJA9cAbwOmAu8XUTSY7AIKzftZEpHU6q3EQafVm4q7VX81MYuRODQA1piZce11tPWUGBl8PCDfwQR4kvLS05QAfcwhKmFYW8qrJzlGvIr/rgidryzr/ycCYj7FDt7B7w+UHCVpTPyUHWVGW2AizVEK1Lo+5/c4TEQ+VwscLZq805UYfr41lTZg8c20zcwxKadvUUN4B+ZJL8XSm6/JGOaXUMSHUGs39bDpDKTpJI+/WXPddJQyBXrTEhbQ4FxrQ08sb4UTF4ZuCJmHpD+fc11BfoGhmKBwqGh9DwIiAfWodTAvMFjIGZOaKWrdyC27/by57qYPTHdm5w6xv2GpRtKmrd29zG6Od3YNhTyNNblYgZiW3ef17iDMyjbImVDg+yrF6ERDjsDxRiEZ6mNsOcfjq539g6wq3+Qsa1pAxgSbeSXbuikf1A5LHE9yi3tHjUuZy2aBpTih8kGtJATzjhySuxcU32ewya28/SW0v1whjXvdf92NNezZWe08+nq8QRPxlPI1qA96R8corN3gFFNdfx15ZbiKg0jfQ7i2VGh++2ZLd3sCbWWxfQKYLmqPgUgIj8HTgO8O3Vv2NHDjQ+v55hDx6b+NqalnrbGAjc+vI5tQcPx7T+tYEJbY8rvLiJMP6CVPy/bxNdvXgq4Xc3yOfH2YhoKOZY/11UsC3D1XasA18v+4umHc9mtyxnVVFdce+bbf3LHoY/Z1zjPmtDKkxu6uPi3T1CXF1RdjybZgEYNxGf+9xHGBQ/Sxh29LJzqv6VtjQUeX7+jqPmJZztTk6FCWhry/PCuVUWN967cQiEnXmNZn8/xwNNbi98bGtkZHgMRPhCX3rKMca31RReFb8Z0fT7Hhh09sWscGqq5k9pjZV22WI5bH3+u2PAve66TxbPGe39fe2MdD67ZVvzuPy3dyNSxzanRhojwksnt/GXF5lK9eGoLdXnxPtxhQ/fVm5cWXZyPrdvhHUGE7qzP//oxDh7TXGxsffViXrCfyCW3PMnUsc2oug7MVE8P9KUHubJX3rmS+1e5xmTD9p7iiCXJ6KZ6fnT36mIH65G125nU7jesHc31PLp2e/Fa/GXFZprq8rGl2ovXIvgdX715KYWc8OAzbsKndwQRdKJ+8OenGN/WUDSWvvp59bkLOeeH9/GLJc/w0Br3nWE2WNR1BKU40eV/WFYchavGR5qLZ7mtScPefFfvQPH3bezsZWBIU+0FuLr8UKQO3fPUZm/8wf2OBrbs7C2WXbahC4ADPCPAkCvvXMmUjqaiMYmOAN991b3MnzLK+7m/PV2aWBvtLIbX6Izv3M15J8wo+/8mqTUDMRmIJoevAY6KFhCRDwAfAKifOIPJAsfPPiD1RSLCcTPH89tH1/NQUDmHtLTFYZLFM8fxrT8uL06BB1g4bYzXRTFv8ijuW7UlVnZInV/5mvcehYhwwmHObXLo+Faa6/Ncc8/qYtm2xgLTx6Ub0EvOPIKzrvwr37ujNIpoKOSYf1A8ODsh4va69t5nikFQEWHe5HjjGfLSKaNZsnplTPMJh6WvG8Cxh47j+gfWxsoePX2st3c098B2bn18A09GeqyTRzcxfXxLuuykdtoaC7HtENsbC0wbl27o5kxq47ePro9pyOeES982nze9bEqq/JFTO7h7xWYeeNr5kEWEhYeM8f6+hdM6+Mk9q2PffXawzHmS42aN545lm2Jlj50xznstDpvURn0hx/fveCp23udCe9nBo2ltKHDDQ+uKPb1RTXXeazFzQiuTRjVy48Priuca63IsmJb+fe2NdSyY2sGdyzZy5zK3q1hOhPlT/AH+42aN4xdL1sR+3+vnTfKWPeKg0dz0SPyeLJ413huvmD3RXYvv3l6qy9PHtaQm6wFMH99CW0OB6yLzQprr88yZlK7LrzhkDJNGNXLL3zdwS2RPlvlTRqVcoDPGt9JQyHHVXSuL5xQ3sjjvhJms27aLQ4Ln8GOvnc1ND69n3bZdxd8Xhi4WJAyP09HBH5c+F7sWUZ9/lPkHjaaQy8XKjm2p5yWRRn7e5HYeXbuDL50+j0tueZJfPbi2qLe5Ps+CaR1MbG/k2R093PFk6d76+OBx0xnVXMfZwegI3HL+4Ra+UR0jIXua9rQvEZEzgJNV9X3B8VnAUar6YV/5BQsW6P33319JiYZhGJlHRJao6oKRytVUDAJYCxwUOZ4SnDMMwzAqTK0ZiPuAmSJyiIjUA/8I3FBlTYZhGC9KaioGoaoDIvJh4PdAHrhKVf0zVwzDMIx9Sk0ZCABV/Q3wm2rrMAzDeLFTay4mwzAMo0YwA2EYhmF4MQNhGIZheKmpeRB7iohsBFaPWLC2GAdsqraIPSRrmrOmF0xzJciaXth3mqeqqn/WcIRMG4gsIiL3784ElVoia5qzphdMcyXIml6ovmZzMRmGYRhezEAYhmEYXsxAVJ7vVVvA8yBrmrOmF0xzJciaXqiyZotBGIZhGF5sBGEYhmF4MQNhGIZheDEDYSC+HV8Mw3jRYwZiHyAiJ4hIeku12qW4n2FWjIWIjAv2MM+EZhH5ioi8Knhf83qzioi8WUTSW8DVKCLSFnlfc/XCDMReRETeKSJLgOOB/pHKVxsReXug9z9E5AIArfGsheAaPwh8DfgB1LbmQO9twPuDV03rBRCR94nIdaFBywIi8i4RuQd4JdBTbT0jISJnishjwMUi8l9Qm/Wi5pb7zhqB1S8AFwCfBV6nqvdUV9XIiMgC4DzgX4DlwK0i0qmqV4mI1FplFZEC8CHgrcCHgbuBp0RkkareXVVxHkSkGbgIWIirF/XAqSLSqqpdVRU3DCJyEvBR4HFgkYg8qqpba7ROCCDA2bjOwjGq+tfqqhoZEZmNe/bOVdV7ReROEblAVS+rtrYkNoJ4AYhIozr6gSeBnwKrRaReRN4iIgdWWWIMEWmMHM4BblXVe1R1E077l0VkVK01BOA2kwJuUtXFqnonbmva+4Hyu7dXEVXtBn6sqq8JDFgHsLgWjYOINEQOlwAnAt/Cbfm7GGqvdysiDcGzNwTcC/wP0CsiORE5W0TmVFlijMQ1ngI8BDwaHH8fuEhEXlZxYSNgBuJ5IiIXAb8TkfNFZBbwW+CZ4N+/AW8CfiQinw3KV/VaJ/QeBCwFXicic4MiQ8AO4CNB+arXDRH5goicEh6r6srg/ELgeqABZ9T+PThf7Wuc1Pt45P3/AU215rYRkU8D1wf14nBV3aSq64HbcfvBLxCRaUHZmvCRJzTPCXadvBm4EdfwLgKuEpH/DMpXu15E9U4D1gHTgNcG13QUsALXZlRdb5SaEZIlROQ9uF7WJ3GrLX41+PcGXEU9WVXfhWts/01ExgY9nVrR+y2cC+F64BNBHOIA4B04N0hLlfWOEZHvAefjDEDSFboGOFFVTwU+AZwnIgdWS/Nu6EVE2oHbgAmV1udD3L7vtwGH4+I5s4FzwqBpcC3/ALQBrwnOVXUUUUbzewJ33u+B7wKnq+qHgLNwv6ea9cKn98NBx+HXwOuBvwCzgA8AZ4rI6Go+eylU1V578ML5PD8HnBkctwJfxrkTABoT5a8FZteY3ouBK4PjUcARwftpwOW4rCapouYG4PXB+98Anwze58qU/yVwbA3qlUS5nwPnB+/z1dIbue8fjRyfhHMzNkZ14/z7/w6cA3yqBjX/DBffyQN1nnqxqMb0/jx4JnPBc3ZY8Lcc8B1gTDWfveTLRhB7iAZ3E3h3cNwFXArMEZFXq2oPgIjUicg3gXaquGdFGb1fB14qIieo6nZVfVBE6nFB1UFV7Y98ruKoai9wR3D4OeD9IjJJVYeibg4RaRSRS3H+/ceqIBUYVq+KIx/87Sbg7cFnBqsgFXCuIlXdjvN9hzyGi+vUhbqD8w/gjMTFFZYZYxjNU4AGVR1UFwtERJpE5Bu4xvbvlVc7rN4DgVZVHQqesydEpBU3+mlW1S3VfPaSmIEYBnHzGSZGjsOH5mJguogcFxxvAn4C/ENQ7nTc0HEQeGtoNGpQ74lBuZfj3B8An66E1ojGmOYQVe0KHrL7cP7wLwbnw0b3jcF5gFNVdVut6o0Yg2eBKyrtY05qDhsgVe2MFDsKeCY8F1zneuAbwJ+B6apaMSPxfDQHnzseuDU4PCVopGtZ7yE4dxPAByuhdU8wA+FBRI4Rl6N8Ds4lE/1bIegxXoGLPYSVYRDYEhR7AjhDVf9VXTZLrerdGhRbDbxFVd9bQWPm1Rw0/mG9DHvenwJeKSIzRWQRMA+4E3eNP1LNa7wbeo8ONAPcpqrXaIV8zLujORIvmYoL8CIii8QFrPuAN6nqOZW4xi9Q8zFBY/sgrlNW1WdvN/XOVpd4cYaqvl9Vd+1rvXtMtX1ctfbCPeQ/BN6ROJ+LvJ8U/HsxN117AAAGVklEQVQbrnf+SlyQ7BMZ0/vxWr7GuCF3eHwZLtPqQWCh6d1rmluD95cDX8ItL30zMDdjmm+ptOYsXuM9/o3VFlBrL5w/+2pgNC74dRYwgyD4DFyCcx9NA6bjJm/dDnzW9O5VzXfgJpkJcCqwkioY4Czq3UPNR+IyldbhUp8vMM37p97n83rRz6QWkfOBlwD3qOqVOLfbdGA+bkZpL+6B3yYiH8XNmj5FVUP3zHdE5Cp1w3HTu/c0nxZqFpGluEyrSvmTM6V3L2n+InCdqm42zfuH3r1CtS1UNV84v+E9wMm4XvWFQBPODbOcUmpoG7AZmB/5bMXTFLOmdy9oLpjefa653jTvf3r31uvFHqQ+EfiKqv4O+BguB/yfcXnfbcELdVkHPyOY5BRkq1QjTTFreuGFaR4wvbvFC9FcsZFkgqxpzprevcKL0kBEsk4ewA0JUdX7cZkxh+MCSx8HThKRN4jIhcCxBDnVGnQLTO/+ozlrek2z6a0ELwoDISLHisih4bGW0gzvAnJSmh/wKG49pSNV9ce4mY2vBA7G5dqvMb37h+as6TXNVi+qwX4dpBY3Aexi3IqUiyLnc8GNX4ab3fg2EblLVdeIyAHATABVvU1E/qSVy1vPlN4sas6aXtNs9aKa7JcjCHHLXHwXl298OS7n/9XB3/KRm9iJmyXaAHxNROpwqWvFJaQrccOzpjeLmrOm1zRbvagF9ksDgbuJdwCvUtUbcauWzhE3q3gQ3NLMuGDSdtwaRB24CrAd+JHp3e80Z02vaTa9VWe/cTGJyNHAFlV9Etipqj+N/DmPW4RuQEQEl8s8E7c65Yrg8+8BWjS+dorpzbDmrOk1zVYvag6tgVzbF/LCzWK8CTcEvBB34yBYUjd4PwPYAHSEf4t83ruEtOnNruas6TXNprdWX/uDi6kF5zc8L3h/HBRX0RwSl6a2KiizOPwbxAJQpnf/0pw1vabZ9NYkmTQQIvJuEVksIu2quhYXYLoO6AGOkmAvaBGR4KaG+8GGezUIVDRwlym9WdScNb2m2epFFsiMgRDHJBH5I24Dk3cC/y0i41S1R93Svn/ABZBOgOKa9nlV3Yn7rUeH501v9jVnTa9ptnqROXQv+ar25YtgHSHc3q3XhOeAbwLXJ8p+BLek7ijiyy9XbD2UrOnNouas6TXNpjeLr5oeQYhIXkS+jNsIfjFu0+9BKG7ZeAFwTPC3kO/jNu64BVgZDiG1AuuhZE1vFjVnTa9ptnqRZWrWQAQ3cgluGLgct4VjP3C8iLwCin7BzwevkFNwi2g9BLxEVdeZ3v1Dc9b0mmarF5mn2kOYci/gVcBZkeNvA/+EW3Z3SXAuB0zEBZ2mBedOA44zvfuf5qzpNc2mN+uvmh1B4HoE14lIuM/vXcDBqno1kBeR89T1CqbgJrasAlDVX6nqHaZ3t8ia5qzpBdNsejNMzRoIVe1W1V4t7WPwWkrrnpyLmw5/I3At8DcopaRVg6zphexpzppeMM2VIGt6s0TNL7UR9AoUtwHHDcHpTuAzwDxgpbr8ZlS16ilpWdML2dOcNb1gmitB1vRmgZodQUQYAuqATcBLg57ARcCQqt4Z3vAaImt6IXuas6YXTHMlyJre2qdawY89eeEmrQzhdnF6b7X17G96s6g5a3pNs+nN4kuCi1rTiMgU4CzgElXtrbaekciaXsie5qzpBdNcCbKmt9bJhIEwDMMwKk8WYhCGYRhGFTADYRiGYXgxA2EYhmF4MQNhGIZheDEDYRiGYXip+ZnUhlELiMhY4NbgcCJuKelwOYduVT2mKsIMYx9iaa6GsYeIyOeBLlX9WrW1GMa+xFxMhvECEZGu4N9Xi8jtIvIrEXlKRC4WkXeKyL0i8oiIHBqUGy8ivxSR+4LXsdX9BYbhxwyEYexd5gMfAubgZvTOUtVXAD8AzgvKXAZcqqoLgbcEfzOMmsNiEIaxd7lPVdcDiMgK4Obg/CPA8cH71wBzIytOt4tIq6p2VVSpYYyAGQjD2LtE1/8ZihwPUXrecsDRqtpTSWGGsaeYi8kwKs/NlNxNiMgRVdRiGGUxA2EYled8YIGIPCwif8fFLAyj5rA0V8MwDMOLjSAMwzAML2YgDMMwDC9mIAzDMAwvZiAMwzAML2YgDMMwDC9mIAzDMAwvZiAMwzAML/8PLwUF5yoVP0UAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot calculated feed-in\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "feedin.plot(title='PV feed-in')\n",
    "plt.xlabel('Time')\n",
    "plt.ylabel('Power in W');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Scaled feed-in**\n",
    "\n",
    "The PV feed-in can also be automatically scaled by the PV system's area or peak power. The following example shows how to scale feed-in by area."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "feedin_scaled = pv_system.feedin(\n",
    "    weather=weather_df,\n",
    "    location=(lat, lon),\n",
    "    scaling='area')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To scale by the peak power use `scaling=peak_power`.\n",
    "\n",
    "The PV system area and peak power can be retrieved as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.646"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pv_system.area"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "206.7989"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pv_system.peak_power"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot calculated feed-in\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "feedin_scaled.plot(title='Scaled PV feed-in')\n",
    "plt.xlabel('Time')\n",
    "plt.ylabel('Power in W');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Feed-in for PV system with optional parameters**\n",
    "\n",
    "In the following example the feed-in is calculated for the PV system with optional system parameters (with 2 modules per string, instead of 1, which is the default). It was chosen to demonstrate the importantance of choosing a suitable converter."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "feedin_ac = pv_system_with_optional_parameters.feedin(\n",
    "    weather=weather_df,\n",
    "    location=(lat, lon))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot calculated feed-in\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "feedin_ac.plot(title='PV feed-in')\n",
    "plt.xlabel('Time')\n",
    "plt.ylabel('Power in W');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As the above plot shows the feed-in is cut off at 250 W. That is because it is limited by the inverter. So while the area is as expected two times greater as for the PV system without optional parameters, the peak power is only around 1.2 times higher."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.208903915833208"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pv_system_with_optional_parameters.peak_power / pv_system.peak_power"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.0"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pv_system_with_optional_parameters.area / pv_system.area"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you are only interested in the modules power output without the inverter losses you can have the `Pvlib` model return the DC feed-in. This is done as follows: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "feedin_dc = pv_system_with_optional_parameters.feedin(\n",
    "    weather=weather_df,\n",
    "    location=(lat, lon),\n",
    "    mode='dc')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot calculated feed-in\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "feedin_dc.plot(label='DC', title='AC and DC PV feed-in', legend=True)\n",
    "feedin_ac.plot(label='AC', legend=True)\n",
    "plt.xlabel('Time')\n",
    "plt.ylabel('Power in W');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Feed-in with optional model parameters**\n",
    "\n",
    "In order to change the default calculation configurations of the `Pvlib` model to e.g. choose a different model to calculate losses or the solar position you can pass further parameters to the `feedin` method. An overview of which further parameters may be provided is documented under the [feedin method](https://feedinlib.readthedocs.io/en/features-design-skeleton/temp/feedinlib.models.Pvlib.html#feedinlib.models.Pvlib.feedin)'s kwargs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "feedin_no_loss = pv_system.feedin(\n",
    "    weather=weather_df,\n",
    "    location=(lat, lon),\n",
    "    aoi_model='no_loss')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot calculated feed-in\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "feedin_no_loss.iloc[0:96].plot(label='aoi_model = no_loss', legend=True)\n",
    "feedin.iloc[0:96].plot(label='aoi_model = sapm_aoi_loss', legend=True)\n",
    "plt.xlabel('Time')\n",
    "plt.ylabel('Power in W');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}