{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# pvsystem tutorial"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This tutorial explores the ``pvlib.pvsystem`` module. The module has functions for importing PV module and inverter data and functions for modeling module and inverter performance.\n",
    "\n",
    "1. [systemdef](#systemdef)\n",
    "2. [Angle of Incidence Modifiers](#Angle-of-Incidence-Modifiers)\n",
    "2. [Sandia Cell Temp correction](#Sandia-Cell-Temp-correction)\n",
    "2. [Sandia Inverter Model](#snlinverter)\n",
    "2. [Sandia Array Performance Model](#SAPM)\n",
    "    1. [SAPM IV curves](#SAPM-IV-curves)\n",
    "2. [DeSoto Model](#desoto)\n",
    "2. [Single Diode Model](#Single-diode-model)\n",
    "\n",
    "This tutorial has been tested against the following package versions:\n",
    "* pvlib 0.4.5\n",
    "* Python 3.6.2\n",
    "* IPython 6.0\n",
    "* Pandas 0.20.1\n",
    "\n",
    "It should work with other Python and Pandas versions. It requires pvlib >= 0.4.0 and IPython >= 3.0.\n",
    "\n",
    "Authors:\n",
    "* Will Holmgren (@wholmgren), University of Arizona. 2015, March 2016, November 2016, May 2017."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# built-in python modules\n",
    "import os\n",
    "import inspect\n",
    "import datetime\n",
    "\n",
    "# scientific python add-ons\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "# plotting stuff\n",
    "# first line makes the plots appear in the notebook\n",
    "%matplotlib inline \n",
    "import matplotlib.pyplot as plt\n",
    "# seaborn makes your plots look better\n",
    "try:\n",
    "    import seaborn as sns\n",
    "    sns.set(rc={\"figure.figsize\": (12, 6)})\n",
    "except ImportError:\n",
    "    print('We suggest you install seaborn using conda or pip and rerun this cell')\n",
    "\n",
    "# finally, we import the pvlib library\n",
    "import pvlib"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### systemdef"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pvlib\n",
    "from pvlib import pvsystem"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "``pvlib`` can import TMY2 and TMY3 data. Here, we import the example files."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "pvlib_abspath = os.path.dirname(os.path.abspath(inspect.getfile(pvlib)))\n",
    "\n",
    "tmy3_data, tmy3_metadata = pvlib.tmy.readtmy3(os.path.join(pvlib_abspath, 'data', '703165TY.csv'))\n",
    "tmy2_data, tmy2_metadata = pvlib.tmy.readtmy2(os.path.join(pvlib_abspath, 'data', '12839.tm2'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'albedo': 0.1,\n",
       " 'altitude': 7.0,\n",
       " 'latitude': 55.317,\n",
       " 'longitude': -160.517,\n",
       " 'modules_per_string': 5,\n",
       " 'name': '\"SAND POINT\"',\n",
       " 'strings_per_inverter': 5,\n",
       " 'surface_azimuth': 0,\n",
       " 'surface_tilt': 0,\n",
       " 'tz': -9.0}"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pvlib.pvsystem.systemdef(tmy3_metadata, 0, 0, .1, 5, 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'albedo': 0.1,\n",
       " 'altitude': 2.0,\n",
       " 'latitude': 25.8,\n",
       " 'longitude': -80.26666666666667,\n",
       " 'modules_per_string': 5,\n",
       " 'name': 'MIAMI',\n",
       " 'strings_per_inverter': 5,\n",
       " 'surface_azimuth': 0,\n",
       " 'surface_tilt': 0,\n",
       " 'tz': -5}"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pvlib.pvsystem.systemdef(tmy2_metadata, 0, 0, .1, 5, 5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Angle of Incidence Modifiers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,0,'input angle (deg)')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1ef3d545278>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "angles = np.linspace(-180,180,3601)\n",
    "ashraeiam = pd.Series(pvsystem.ashraeiam(angles, .05), index=angles)\n",
    "\n",
    "ashraeiam.plot()\n",
    "plt.ylabel('ASHRAE modifier')\n",
    "plt.xlabel('input angle (deg)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,0,'input index')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1ef40470860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "angles = np.linspace(-180,180,3601)\n",
    "physicaliam = pd.Series(pvsystem.physicaliam(angles), index=angles)\n",
    "\n",
    "physicaliam.plot()\n",
    "plt.ylabel('physical modifier')\n",
    "plt.xlabel('input index')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1ef51a8acc0>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1ef51aa3128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "ashraeiam.plot(label='ASHRAE')\n",
    "physicaliam.plot(label='physical')\n",
    "plt.ylabel('modifier')\n",
    "plt.xlabel('input angle (deg)')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sandia Cell Temp correction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "PV system efficiency can vary by up to 0.5% per degree C, so it's important to accurately model cell and module temperature. The ``sapm_celltemp`` function uses plane of array irradiance, ambient temperature, wind speed, and module and racking type to calculate cell and module temperatures. From King et. al. (2004):\n",
    "\n",
    "$$T_m = E e^{a+b*WS} + T_a$$\n",
    "\n",
    "$$T_c = T_m + \\frac{E}{E_0} \\Delta T$$\n",
    "\n",
    "The $a$, $b$, and $\\Delta T$ parameters depend on the module and racking type. The default parameter set is ``open_rack_cell_glassback``."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "``sapm_celltemp`` works with either scalar or vector inputs, but always returns a pandas DataFrame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>temp_cell</th>\n",
       "      <th>temp_module</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>43.509191</td>\n",
       "      <td>40.809191</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   temp_cell  temp_module\n",
       "0  43.509191    40.809191"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# scalar inputs\n",
    "pvsystem.sapm_celltemp(900, 5, 20) # irrad, wind, temp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1ef51ca3f98>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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9Z8AH+ItSaptSahvwFvB3pdQewBmofoG/EPVkzY7jHDqVTUQ3f0bc0qHGbVYlb0DLSibUvxcPdB7WqPV19+nKixHTcXdy46tDK/np1PZat23p6cIbEyMIbOnGht0nWLdTAlzUnZznLexW7JEMPlh1gMCWbvzX1H419i3ZdeY3vtZW0cajNa/2nYXrVa6AbEipBWl8GPsx2SU5DA8ewqjOw2tdFrmQW8z/fhVNRk4x4wZ1ZtTtHRu3WNGoZHq8aFbOWxtOORn1zBoXUmNwH8k6xvLDq/Fwcmd62FSbBTdAkEcrXomcib+bH5tPbuWbw2swmWu+/MHX25U3JkXg5+3K6l+PsXHvyUauVjQFEt7C7pSVVzB/dQKFJeVMGdadDq2qN5yqaaiCrfm5+fJK5Czaegbx65k9fJ60vNaOhP4t3HhjUgS+3i58u+0om/edauRqhaOT8BZ256sfj3AyLY87w4K4M6xNtcevNlTB1lq4ePFSxHQ6eQezPy2WRfFLKa0oq3HbgJZuvD4xAh8vF1ZsTebH/acbuVrhyCS8hV3ZFZ/Kr3Fn6RDoyeR7qzecMplNLL00VOG2Gocq2Jq7kzsvRDxDT9/uJGQeZF7cJxSVF9e4bSsfd16fGEELT2eW/XSErdEpjVytcFQS3sJunD6fz9LNGm4uRmY9GIqzU/ULu74//iNxGYl0b9mF8d1G26DK6+NicGZ62FQiAkI5kn2MOTELySvNr3Hb1r7uvDExAm8PZ77ccphtsWcauVrhiCS8hV0oLLY0nCorN/H0Az0JbOlWbZuotFg2nfjZMlQhdMo1hyrYmpPeyLSQydwe1J/TeWd4L3oBWcXZNW4b5OfB6xP64OXuxNJNGjviau+bIgRIeAs7YDab+fSHg5zPKmLkgA5EdKvecOpUbgpfHPwGV4MLM8Km4ulUc09te6PX6ZnUYzxD2w8irfA8/4max/nC9Bq3bRvgyesTIvB0c+KzjYfYFZ/ayNUKRyLhLWxu877TRB1Op0eHljw4qHrDqcpDFab2nnjDQxVsTafTMa7r/YzqPIKskmxmR83ndC0dCdsFevLahD64uxpZ8v1B9iSea+RqhaOQ8BY2pZ3KYuW2o7TwdGb66N7V5j6WVZSxKH4p2SU5jO4yglD/2htA2TOdTseIjkN4tPtY8ssKmBOzgKPZJ2rctkMrL16bEIGbi5GPNySx72Ba4xYrHIKEt7CZnPwSFqxNBGDmmBBaeLpUefzKoQr3dhhsgyrr16B2t/NErwmUVJQyN3YxiZlajdsFt/bi1Ql9cHU2sGhdEvsPnW/kSoW9k/AWNlFhMrFgbSI5BaWMH9yF7u2rjxVriKEK9qB/6wieDX0cMLPwwGdEpcXVuF2nIG9eeaQPzk56Fq5LJPpwzWvlonmS8BY28d2vx9BOZ9O3ewDDb2lf7fGGHKpgD0L9e/Fc+FM46Y18mvg1u878VuN2Xdq24OVHwjEa9Mxfk0BsckYjVyrslYS3aHQxR9LZuPcUgT5uPHlfz2pH1OcK0vg0cRlGvYHpYU/QwsXbRpU2rG4+XS51JPxaW8WPJ7fVvF27lrz0cBgGg455q+M5cDSzcQsVdknCWzSq81mFfLzhIM5GPc+NC8XdteoM7IKyQuYf+IziimIm93iYYO/qR+VNSQfvdrwSOZOWLi1Yc/QH1h7dWOOoNNXBhxfHh6PX6fjwu3gSjkuAN3cS3qLRlJZVMG91AkUl5Tw2XNE+0LPK45WHKgwLvpv+jTRUwdZae7TilchZBLj5seXkLyw/vLrGjoQ9g314YXwYOh3MXRVP0okLNqhW2AsJb9FovvrxMKfO5zMovA13hAZVe7zyUIVRnYfboELb8XPz4ZW+lo6EO8/s5bPEZTV2JOzd0ZcXHgzFbDbzwcoDaKeybFCtsAcS3qJR7Dhwlh0HUglu5cXke7tVe3zXmd/YnrKLNh6tmdprAnpd8/uv6e3sxUsRM+jcoiNR5+NYGP85pRWl1bYL6ezHc+NCqTCZef/bAxw+XfMl96Jpa37fIaLRnUrL48sth3F3MTJrXAhOxqo9SexpqIKtuTu58Xyfp+nlq0jMPMSHsZ9QVF5Ubbvwrv7MGhdCeYWJ976NIzklxwbVCluS8BYNqrC4jHmrEywNp0b1IuCKhlOVhyo8bSdDFWzN0pHwCSICwziac5w50TV3JIzoFsCMMb0pKzMx+5tYjp6VAG9OJLxFgzGbzXzy/UHOZxdx/23B9OnqX+Xx4vKSSkMVxtDdjoYq2JpRb2Ra70nc0eYWTuefZXb0PC4UV1/f7qsCmT6mN6VlJmaviON4aq4NqhW2IOEtGsym304RcySDHh1aMvbOTlUeswxVWF5pqMJtNqrSful1eiaqh7i3w2DOF2YwO2o+aTV0JOzfI5CnR/WkuLSc/yyP5eQ5GdbdHEh4iwahncpi5fajtPR0ZvqYkGoNpxxlqIKt6XQ6xna9jzGdR1o7Es7jdF71YQ0DerXmqft7UlRSzrvLYziVJgHe1El4i3qXnV/C/LWJ6HU6Zo4NoYWHc5XHLw1VcPV1iKEK9mBYx7uZoMZRUFbI+9ELSc4+Xm2b20OCePK+nhQWl/Pu8lhS0mue3COaBglvUa8uNpzKLSjl4cFd6NauasOpykMVpjvQUAV7cGfb25jaawKlplI+jP2YhIyD1bYZGBbEEyN7kF9UxrvLYjibUWCDSkVjkPAW9WrV9mMcPp1NPxXAvf2rXtqeU5JXZahCG8/WNqrScfVrHcH00CcAMwvjPycqLbbaNoPC2/DYcEVuYRnvLIshNVMCvCmS8Bb1JvpwOpt+O0UrX/dqDafKKspYHP+5ww9VsAch/j15vs8zOOud+TRxGTvO7K22zd0RbZl8b3dyCkp5e1kMaRcKbVCpaEgS3qJepGUV8sn3SZaGU2NDcHO53HDKbDazTPuO401oqIKtdW3ZiRcjn8XDyZ3l2ndsOfFLtW2G9m3HhKHdyMm3BPj57OoX+wjHJeEtbtrlhlMVPD5C0e6KhlM/n/6V385FNbmhCrbWwcvSkdDHpSVrj21kTfIP1ToSDuvfnkfu7kpWXgnvfB1NhgR4kyHhLW7al1sOc/p8PoP7tOH2kKoNpyoPVXg29PEmN1TB1lp5BPJK35kEuvvz46ltLNO+q9aRcMStHXjors5k5pbw9rIYMnOKbVStqE8S3uKm/Bp3lp3xqQS39mLiPVUbTl05VKGlSwsbVdm0+br68ErkLNp5tmHX2d/4LHEZ5abyKtvcf1tHxt7ZiYycYt5eFs2FXAlwRyfhLers5DlLwykPVyPPja3acKqgrJAFzWiogq15OXvyYsR0ulylI+HoOzox+o6OpGcX886yGLLySmxUragPEt6iTgqKy/hodTzlFSaefqAX/pUaTlWYKliS8BXpzWyogq1d6kjop0jK1Jgb+zGFZVXXuMcM7MT9twWTllXEO8tiyMmXAHdUEt7ihpnMZj7ZcJCMnGIeuD2Y8CsaTq1K3sChrCOE+vdsdkMVbM3Z4Mz00CfoGxjOsZwTzIlZSG7p5UvldTodDw7qzIhbO3DuQiFvL4sht6B6z3Bh/yS8xQ3buPcksckZ9Az2YezAzlUeuzhUIcijFVN7TWyWQxVszag3MrX3RAa2uZWU/LO8FzW/SkdCnU7Hw4O7MKx/e1IzC3lneQx5hRLgjka+s8QNOXgyi+9+PYaPlwvTx/RGr7982l/loQozmvlQBVvT6/RMUA8yLPhuzhdl8J+oeZwrOH/pcZ1Ox6NDujK0bzvOpBfw7vJY8ovKbFixuFHXFd5KqVuVUtusH0cqpc4opbZZ/z3aoBUKu5GVV8LCtQmXGk55u19uOFV9qIKfrcoUVjqdjjFdRjKmy0iyS3J4L3o+p/JSqjw+6Z5u3B3RltPn83l3eQwFxRLgjuKa4a2UegP4GLh4GBUJzNY0bbD134qGLFDYh/IKEwvWJpBbWMYjd3ela9vLp/0Vl5ewMP5zGapgp4YF381E9SAFZYXMiV7Ikaxjlx7T6XRMHtadQeFtOJWWz3+Wx1IoAe4QrufI+yjwYKXbfYH7lVK/KqU+UUp5NUxpwp6s2n6UIyk59O8RyD392l26/+JQhTP5qTJUwY4NbDuAJ3tPpMxUzkdxVTsS6nU6Hh+hGBgaxIlzecz+Jo6ikvKrPJuwB7orL6etiVKqI7Bc07QBSqkngQOapkUppd4EfDRNe+1q+5eXV5iNRunZ7Kh2HzjLvz//nbYBnsx+aRDurpevklwev47vkjbSO7A7b971B4zSm9uuxaYm8u6uhVSYKnju1qkMDO5/6bEKk5k5y6P5JSqFnh19+dszA6p8rYVN1NpLwljbA1exWtO07IsfA3OvtUNW1s11NAsI8CI9XSaD2ELahULeXx6Ns5OeGaN7UZBXTEGe5eq8qLRYvkvaiL+rL4+riWRlSuc6e9fW2IHnwp9mftynzN37KWkXshjU7vJvS5OHdqOoqIy9SWn8Zf4uXn6kDy7O8gP5ZtQlvy7uExBQ+8JGXc422ayUusX68VAgqg7PIRxASVkFH62Op6ikgidG9KBtwOWGU6fyUvji4LcyVMEBdW3ZiZcip+Ph5M6Kw6vZfGLrpYZWer2Opx7oSf8egRxOyWHOyjhKyipsXLGoSV3CeybwvvXskzuAf9ZrRcIumM1mvtyskZJewN0Rbbmt9+XBCTkleSw88DnlpnIZquCg2nu15ZW+s/Bxacm6Y5tYc/RyR0KDXs8zo3rRt3sAh05lM3fVAUolwO3Oda1536z09LybehFZNml822PP8PkmjU5BXvxpcl+cjJaf82UVZcyJWcjx3FOM6TKSYcF327hScTOyirOZG7uYtMJ0bg+6hYk9Hrx0YVV5hYn5axKIOZJBSCdfXngotEr/GnF9bnLZpNY1b7lIR1Rz4lwuX/1oaTg1c2zIpeCuOlQhQoYqNAE+ri15OXIm7b3asjt1H0sSv6bM2pHQaNAzY0wIYV38SDh+gY9WJ1BWbrrGM4rGIuEtqsgvKmPe6gQqKsw8M6o3/i0uN5y6NFTBqz2TeoyXoQpNhKUj4bN0bdmJmPMHWHjgM0qsHQmdjHqeGxdCSGdfDhzNZP6aBMorJMDtgYS3uMRkNvPxhiQycooZdUdHwrpcvkoyMfPQ5aEKYY/jLEMVmhQ3oxvPhT9NiF8PDl44zIexiykss5w95GQ08Py4UHp39CE2OYMFaxMlwO2AhLe45Ic9JzlwNJPenXwZfUenS/efK0hjScLXMlShiXM2OPFs6BP0a9WHYzkneb9SR0JnJwPPPxRGjw4tiT6czqL1SVSYJMBtScJbAJB04gKrd1gaTj07qtelhlMyVKF5MegNPNFrAgPbDuBMfiqzo+aRWWTpSOjiZODF8eF0b9+S/YfOs1gC3KYkvIWl4dS6RPQ6HbPGhuBlbTglQxWaJ71Oz4Tu4xgWfDfpRZnMjp7HuYI0AFycDbz0cBhd27Vg38HzLPn+ICZTw5+xJqqT8G7myitMzF+bQF5hGY8O6UqXSg2nvpOhCs3WxY6EY7vcR3ZJDrOj53My9zQArs5GXn44nC5tvNmTmManGw9iaoRTjkVVEt7N3MptR0lOyeGWnoEM7Xu54dSus7+xTYYqNHv3Bg9mUo+HKCwr4oOYRRzOOgqAm4uRlx/pQ6cgL3bFn2PppkMS4I1MviObsf2HzrPl99ME+bkzdWSPS6f+JWcfZ4W2RoYqCADuaHMr00ImWzsSfkJ8RhIA7q5GXn20D8GtvPg1LpUvN2s0xkV/wkLCu5k6d6GQJT8cxMXJwKxxobg6W3qUZRZdYHH8UsyYZaiCuCQyMIwZYVPRoWNR/FL2nYsGwN3ViVcn9KFDoCfbYs/y1Y+HJcAbiYR3M1RSamk4VVxawRMjFW39LU2lKg9VeLibDFUQVfXyU7zQ5xlcDM58nrSc7Sm7AfB0swR4uwAPtkafYdnPRyTAG4GEdzNjNptZuvkQZ9ILGBLZlgG9LE2lTGYTSw+u4Ex+Kne2va1Km1AhLurSsiMvRczAy8mTbw6vYdOJnzGbzXi5O/PahAja+Hvw0/4UvvklWQK8gUl4NzPbYs+yJzGNTkHePDqk26X7fzj+I3HpCXRv2YWHu422YYXC3rXzasNBenTzAAAgAElEQVQrfWfi49KS9cc2szr5e8xmM94ezrw+MYIgP3c27zvNqu3HJMAbkIR3M3I8NZdlPx3G082JWZUaTkWlxbHxxM/4u/ryVOgUDDINR1xDoHsAr/adRSv3QH4+/StfHVqJyWyihTXAW/m688Pek6zZcdzWpTZZEt7NROWGU8+O6oVfC8sZJJahCt/gYnCWoQrihlg6Es6gg1db9qT+zicJX1FmKqelpwtvTIwgsKUb63efYN1OCfCGIOHdDJjMZhavTyIzt5jRAzsR0tlyBknloQpP9p4kQxXEDfNy9uQPEdPp1rIzsenxLIj7lJKKUny8XHhjUgT+LVxZs/M4G3afsHWpTY6EdzPw/e4TxB/LJKSTL6Pu6AhAmamcxfGfk12Sw+jOIwj172XbIoXDcjO6Miv8KUL8enIo6whzYywdCX29XXljUgR+3q589+sxNu49aetSmxQJ7yYu8cQF1uw4jq+3C8+M6oVep7MMVTi06vJQheDBti5TODhLR8LH6d8qguO5J3kvegE5JXn4t3Dj9UkR+Hi58O22o2zZd8rWpTYZEt5N2IXcYhauTUSv1zFrbOilhlMyVEE0BIPewOO9HmVQ29s5W3CO2dHzyCi6QGBLN96YFEFLT2eWb03mp/2nbV1qkyDh3URdbDiVX1TGhKHd6NzGG6g8VMFLhiqIeqfX6Xmk+xhGdBxKRlEms6PmkVqQRisfd96YFEkLD2e+/ukIW6NTbF2qw5PwbqK++SWZo2dyubVXK4ZEtgUuD1Uw6A08K0MVRAPR6XSM6jycB7s+QE5pLu9ZOxK29nXnjUkReLs78eWWw2yLPWPrUh2ahHcTtO9gGj/tTyHIz50nRih0Oh2FlYYqTOnxMB29O9i6TNHEDe0wiMk9HqawrIg5MQs5nJVMkJ8Hr0+MwNPNiaWbNHbEnbV1mQ5LwruJSc0s4NONh3BxMvCcteFUhamCT2SogrCB29v0Z1rIZMpNFXwUt4QD6Ym0DfDk9YkReLga+WzjIXbFp9q6TIck4d2EFJeW89HqBEpKK3jyvh60sTackqEKwpYiA8OYGfYkenQsTviC31KjaB/oyWsTInB3NbLk+4PsTTxn6zIdjoR3E2E2m1m6SeNsRgFD+7bjlp6tgKpDFZ6QoQrCRnr6deeFiGdxMbiw9OAKtp3eRXBrL16d0AdXFyOLNySx72Carct0KPKd3ET8EnOGvUlpdGnjzaNDugKVhioYLUMV3GSogrChzi2CeTlyBl7Onnx7ZC0bj/9EcCsvXn20D67OBhatS2L/ofO2LtNhSHg3AcfO5rLspyN4ujkxc2wIRoOezKKsy0MVQqfIUAVhF9p6BvFK5Cz8XH3YcHwLq5LX0zHIk5cf6YOTk56F6xKJOZxu6zIdgoS3g8svKmP+mnhMJjPTR/fG19vVOlThs0pDFbraukwhLgl09+eVvrNo7R7IL6d38tXBlXQK8uTlh8MxGvTMW5NAbHKGrcu0exLeDsxkNrNofSKZuSWMubMTvTv5ylAF4RBaurTg5ciZdPBqx95z+/kk8Ss6tfXkpYfDMOh1zFsdz4GjmbYu065JeDuwDbtOkHDsAqGd/Xjg9o7A5aEK3Vp2lqEKwq55Onvwh4hn6dayM3HpCSyI+5TgNu68OD4MnU7Hh9/Fk3BcArw2Et4OKuF4Jmt3HsevUsOpi0MV/Fx9eTrkMRmqIOyem9GV58KfItS/l6UjYexiOrR15Q8PhQEwd1U8B09csHGV9knC2wFdyC1m0bokDAYds8aF4unmVGWowoywqXg6y1AF4RicDE48E/IY/VtFciL3FO9HL6BdGyMvPBSK2WxmzsoDaKeybF2m3ZHwdjDlFSbmrbE0nJo4tBudgrxlqIJweJaOhI9wVztrR8KoeQQFwaxxoVSYzLz/7QEOn862dZl2RcLbwazYmsyxs7kM6N2KwRFtrUMVlspQBeHw9Do9D3cbw8iO95BRfIHZUfMIbF3OrLEhlFeYeO/bOJLP5Ni6TLsh4e1AfktK4+eoFNr6e/DE8B4A1qEKJ+nXqo8MVRAOT6fT8UDnYTzUbRQ5pXm8H72Alq2KmD66N2VlJmaviOXoWQlwuM7wVkrdqpTaZv24q1Jqp1Jqh1JqvlJKfgA0grMZBXy28RAuzgZmjQvBxdlQZajC5B4Py1AF0WQMaX8nU3o8TGF5ER/ELsIzMIdnR/eipKyC2SviOJ6aa+sSbe6awauUegP4GLh4bfVs4C1N0+4EdMCYhitPwMWGU/GUlFUw7b6eBPl5yFAF0eTd1qY/T4dMwWSqYH7cElz803nmgV4Ul5Yze0UsJ8/l2bpEmzJexzZHgQeBL6y3+wLbrR9vBIYBq6/2BD4+7hiNN3faWkCA103t76jMZjPvfhlFamYhowd15r47u3Am9xyfJn2NUW/gj4Nm0dWvna3LFKJB3BtwO638fHhn10IWJ3zBzP6P8dKESN5fHs3sb2L518w76NTG/oeK1CW/rrWPzmw2X/NJlFIdgeWapg1QSp3VNK2N9f4hwDRN06Zcbf/09Lxrv8hVBAR4kZ7ePH/K/hyVwlc/HqZr2xa8MSmCUlMx7+z/kPNFGUztNVF6c4tm4XjOSebFLaGwvIjx3UZjzOrMpz8cwtPNiTcmRdAuwNPWJdaqLvl1cZ+AAK9a10Lrsl5tqvSxFyDn7zSQo2dyWP7zEbzcLQ2ndDoznyR8xfmiDBmqIJqVTi2CeSlyBt7OXqw8so5cr0QeH96d/KIy3l0Ww9mMAluX2OjqEt4xSqnB1o9HAjvqrxxxUV5hKfPXJmAyWxpO+Xi5XBqqEOInQxVE83O5I6EvPxz/kXSPKKbc243cwjLeWRZDambzCvC6hPerwN+VUnsAZ2Bl/ZYkTCYzi9YncSG3hLF3dqZXR98qQxWm9pahCqJ5CnD345W+M2nt0YptKbtIcdvNhKFdyCko5Z1lMaRlFdq6xEZzXWveN0vWvG/Mmh3HWLfrBGFd/PjD+DCO5Zzgg5hFuBpceKP/C9KbWzR7+WUFzItbwsnc04T796Z90Z18+8sJfLxc+OPkSAJbutm6xEvsac1bNKD4Y5ms33UC/xauPP1AL7KKs2WoghBX8HTy4A99nqG7T1fiMhI57PwT4wa3JyuvhHe+jiYju8jWJTY4CW87kplTzKJ1iRgMOstEHCeTDFUQohauRldmhT1JuH9vDmclc9C4iVGD2pCZW8Lby2LIzCm2dYkNSsLbTpSVWxpOFRSXM+me7gS39rw0VGFg2wEyVEGIGjgZnHgqZAq3tu7LydzTJBq+Z8QdgWTkFPPOshgu5DbdAJfwthMrth7heGout/VuzV192lQZqvBIN7mIVYjaGPQGpvR8mMHt7iC1II0EwwaG3ubD+ewi3lkWQ1Zeia1LbBAS3nZgb+I5tkafoW2AB4+PUESfPyBDFYS4AXqdnvHdRnNfp3vJLL5AgmEDdw3wIi2riHeXx5CT3/QCXMLbxs6k5/PZpkO4Oht4blwoacWpMlRBiDrQ6XTc3+lexncbTW5pHgn6Ddx+iwupmYW8szyW3IJSW5dYryS8baiopJyPVidQWmZi2n09cfOokKEKQtyku9sP5LGej1BcUUKiYSP9++k5m1HAu8tjyCtsOgEu4W0jZrOZzzYe4tyFQob1b094d99LQxVGdR4uQxWEuAkDgvpd6kh4yLCZPn3LSEkv4N3lseQXldm6vHoh4W0jP0Wl8Puh83Rr14KH7upcZajCsOC7bV2eEA4vPCCEmeHT0OsNHDZspXdkAafP5/Of5bEUFDt+gEt420DymRy+2ZqMt7sTM8aE8OvZXTJUQYgG0MO3Gy9GPIu70Y1jxh10j7zAybQ8Zq+IpbC43Nbl3RQJ70aWW1jK/DXWhlNjQjhbepzVyd/LUAUhGkhH7w68FDmDFs5enDbuo1NEKsdTc3nvm1iKShw3wCW8G5HJZGbRukSy8kp4cFBnfPzLWJLwNQa9gWfDnqCli/03lRfCEbXxbM0rfWfh7+rLOac42kec4ujZHN77Js5hA1zCuxGt3XmcpBNZhHfx466+ASw88BnFFcVM7jGejt4dbF2eEE2av5sfr/SdRRuP1mQ4HSQo4gjJZ7OY820cJaUVti7vhkl4N5IDRzNZv9vScOrJBxSfJn7N+aIM7u0wmFtaR9q6PCGahRYu3rwUOYOO3h3IdjpGYJ8kDp+5wJyVcZSUOVaAS3g3goycIhavT8Ro0PPcuFC2nN5yaajC6C4jbF2eEM2Kh5M7L/R5BuXTlTynFPz6HOBQSgZzVx2g1IECXMK7gZWVm5i32tJwavK93ThjOsgvKTtlqIIQNuRqdGFm+DTCA0IodErDp080SSlpfPhdPGXljhHgkhwNbPnPRzhxLo87QlrTNriE5dpqPIzuTA+dipvR1dblCdFsOemNPNV7MgNa96PYeIEWYVEkpJzlo9UJlJWbrv0ENibh3YD2JJzjl5gztAvw5L67Almc8AVmzDwVMoUAdxmqIIStGfQGJvccz93tB1JqzMEr7HfiU04xf00C5RX2HeAS3g0kJT2fzzcdws3FwDOju/HpwS+sQxVGo3xlqIIQ9kKv0/NQ11E80GkY5YYCPEJ+J+7McRasTbTrAJfwbgCXGk6Vm3hyZE82nltfaajC7bYuTwhxBZ1Ox8hO9/BwtzFUGIpx772P2LOHWbQ+iQqTfQa4hHc9M5vNfPrDQdIuFDLilg6cc46VoQpCOIjB7e/g8Z6Pgr4C1x77iT6bxGI7DXAJ73r24/4U9mvpdG/Xgs698tl44icZqiCEA7k1qC9Phz6GwaDDRUWz/9wBlnx/EJPJbOvSqpDwrkdHUrL59pdkvD2cGXWvL18e+laGKgjhgMIDevNcn2m4GIy4dI1jX1oUn248iMlsPwEu4V1PcgsuN5x67L5gvk7+mnJTOVN7TZShCkI4oO4+XXkxcjruTq44d07gt/Q9LN10yG4CXMK7HphMZhauSyQ7v5SxgzryS9a6S0MVwgJ627o8IUQdBXu355W+s/B29sKpg8bujO18sUXDbAcBLuFdD9bsPMbBk1mEd/Ujq8XvMlRBiCYkyKMVr/Z9Dj8XX5zaHmP3hZ/46sfDNg9wCe+bFJecwYbdJwlo6Ur3yAv8di6KDl7tZKiCEE2Iv5svr/abRWv3VhhbnWJH9g98/bNtA1zC+yZkZBfx8YYkjAY9I4a68f2JTbRw9mJ62BMyVEGIJqaFizev9p1JB8/2GP1T2ZGzjuW/2G4JRcK7jsrKK/hojaXh1Oih/mw4u1qGKgjRxLk7ufNS3+l09e6CwSed7bmrWbHtkE0CXMK7jr7+6Qgnz+UxINSXqJIfZKiCEM2Ei8GZ5yOfordPLwzeWWzPX8U3vyY1eh0S3nWwKz6V7bFnaRfoTlHQPhmqIEQz46Q3Mj38MSL9I9F75LItfyXf7Ihv1BokvG9Qyvl8vtis4eZipGv/MxzOTpahCkI0Qwa9gWmhj3J74O3o3Qr4Jf9bVuyMbbTXl/C+AYXF5Xy0Op7SchN3Di7jt/TfaC1DFYRotnQ6HZN6j2FI0BD0LsVsz1/Jit1RjfLakjjX6VLDqawibrvFmd3ZP+FhdGeGDFUQolnT6XQ81HMEI9vfh865lO35q1i257cGf11jXXdUSsUAOdabxzVNe7J+SrJPW34/TdThdLp0dCLZ6WfM5TJUQQhx2QPdBuOqc2X1ydXsyF+NaW8ZkwcMbLDXq1N4K6VcATRNG1yv1dipw6ez+faXo3h76TF3/J38wgIe7T5WhioIIaq4p+sAnPTOfHPsG3blr8e0t4xXRo1ukNeq67JJOOCulNqilNqqlBpQn0XZk5yCUuavTQDMdOh3lNTCczJUQQhRq7s6RzKl62PozAb2FGxk0bZNDfI6urqcXK6UCgUGAB8D3YCNgNI0rbym7cvLK8xGo+P1sq6oMPFfi/ZwIDmDfoOzSSzcS6+Abrw1+EWM0ptbCHEVOw8n8cHvC/HTt2f+xNfq+jS19tioa3i7AHpN04qst/cBD2madrqm7dPT827q8qOAAC/S0/Nu5inqZNX2o3y/5yRdehVw1nMHfq6+vNHvBenNLYS4LgUlxbQN8iX7QuEN7Xcx8wICvGoN77oum0wD/gOglGoDeAOpdXwuuxR7JIPv95zEr1UJ6d57ZaiCEOKGebi44mRomN/S6xrenwAtlVI7gRXAtNqWTBzR+ewiFm9Iwsm1DEPXKBmqIISwO3U620TTtFJgUj3XYhfKyiuYtzqeotJS2t2WRGZZLqM7j5ChCkIIuyIX6Vzhqx8Pcyotj/aRx8gsT5WhCkIIuyThXcnOA6n8GpeKf9dUMgzJMlRBCGG3JLytTqXl8cUWDTf/CxT6xstQBSGEXZPwxtJwat6aBMqNuTh3iZOhCkIIu9fsw9tsNvPJ90mcz83FJyyeUnOJDFUQQti9Zh/em/edJubIeXxCEigiR4YqCCEcQrMOb+1UFiu3HcWjSzLFLmmE+PWQoQpCCIfQbMM7J7+EBWsT0fufxuR3zDpUYZIMVRBCOIRmmVQVJhML1iaSp0vDuVOSDFUQQjicZhne3/16jMNpqbj3iEWnQ4YqCCEcTrML75jD6Wzcdwz3nrFU6EsY3220DFUQQjicZhXe57MK+fj7JFy7xGNyyWFgm1sZ1PY2W5clhBA3rNmEd2lZBR+tTqDM/xA6nzS6tezMI93HyqXvQgiH1GzC+8sfD3OmLBmntkfxc/Xl6ZDHMMg0HCGEg2oW4b0j7iy7kjVcusTLUAUhRJPQ5MP7VFoeX/4Sj2v3aNCbeEKGKgghmoAmHd6FxWV8uCYWXacocC5mVOfhhMtQBSFEE9Bkw9tsNvPx90nktIzG4JVNv1Z9GC5DFYQQTUSTDe9Nv50iPjcKY8AZGaoghGhymmR4a6ey+C5mL84dDuHl5ClDFYQQTU6TC+/s/BLmbfwNJ+tQhelhU2WoghCiyWlS4V1eYWLe2mhK2+9FZyxnSs+H6dRChioIIZqeJhXeq7Ync8r9V/SuhdzT4S4ZqiCEaLKaTHhHaelsPfcjhhaZ9PRRjOky0tYlCSFEg2kS4Z12oZAlezdjbH0SPxd/ngqdLEMVhBBNmsMnXElZBe//sA1z23icdS48HzFNhioIIZo8hw5vs9nMJz9GkROwG50OZoQ/QaC7v63LEkKIBufQ4b017iTxFZvROZXykAxVEEI0Iw4b3idSc1l59Dv0Hnn08+/H3e1vt3VJQgjRaBwyvAuKy3h/x7fofc4R5NKex0IelEvfhRDNisOFt8ls5v3Nmyjz13DFi5f6T8OoN9q6LCGEaFQOF97Ld+/njPsudCYjL/d7SoYqCCGaJYcK76ijKezMXY9Ob2JKj0dp593G1iUJIYRNOEx4p+cU8GnSF+hcirkjYDAD2oXbuiQhhLAZhwjvsvIK3t6xFLNHFm2N3ZgYKpe+CyGatzr9pU8ppQfmAeFACfC0pmnJ9VlYZf9Yt4xC9+O4Vvjx6qDH5cwSIUSzV9cj77GAq6ZptwF/Av5TfyVVtTb2Nw6V7kJX7sLrtz6Ni9GloV5KCCEcRl3DeyCwCUDTtL1Av3qrqJKTmelsTl8LZj2Pq8m09vZriJcRQgiHU9cTpL2BnEq3K5RSRk3Tymva2MfHHaPRcMMvciIvDZ3JyPDgEdzfr38dSxVCCNsKCPCq933qGt65QOVn1tcW3ABZWYV1epGOXq34aPg/CAjwIj09r07PIYQQtlSX/Lq4z9UCvK7LJruA+wCUUgOA+Do+jxBCiDqo65H3auBepdRuQAc8WX8lCSGEuJY6hbemaSZgRj3XIoQQ4jo5xEU6QgghqpLwFkIIByThLYQQDkjCWwghHJCEtxBCOCCd2Wy2dQ1CCCFukBx5CyGEA5LwFkIIByThLYQQDkjGrldS05AJIAh4FzADP2ia9o8r9nEDvgQCgTzgCU3T0pVSo4D/AsqBJZqmLa7nugAWAM7W+yZompZpB3V1Bv4PKAA2aZr2zyv28Qe+BtyAs8CTmqYVKqWeAaZb6/qnpmkb6lqX9XVuBf5P07TBSqk+wFygwlrn45qmpV3t89A0Ldnat2eOtaYtmqb9/WZqqqGuSGA9cMT68HxN01ZU2rbBv4a11NUHy/+tcuAwlvfDVGnbRnm/lFJOwBKgI+CC5f/FOutj7wGapmkLrtin0b6WtiZH3lXVNGTifSzBOAC4WykVccU+M4F4TdPuBJYCb1n/070HDAPuAp5VSrWu57oWAW9pmjYIyzdadzuo6z3gY+AhTdMGAj2UUgOv2Oe/gK+tdcUA0601/AG4AxgO/FspVeepG0qpN6x1uFrvmgO8oGnaYOA74I/X+DwuDhdZAEzC0r/+VmvY1lkNdUUCszVNG2z9t+KKXRrja1hTXX8F/mH9GroA91+xS6O8X8AUINP6+Y8EPlRKBSilNgKja9mnsWqzOQnvqmoaMnGrpmnHlVKeQAsgE0AptUUp5Vx5H2AjcA/QE0jWNC1L07RSYCdwZz3WNRDL0dgopdQ2YACwzw7qugfI0jTtmPXxXcBApZSvUuq7K/epVNctwC5N00o0TcsBkoGwm6jrKPBgpdsTNE2LtX5sBIoBlFJLlVIdavg8+imlvAEXTdOOappmBjYDQ2+ipprq6gvcr5T6VSn1iVLKy1pXY34Na6orBvBVSumwtH4us9bV2O/Xt8BfKt0uBzyBvwFfVN7QBrXZnIR3VdWGTMCltrcJwDkgHUDTtGHWb57K++RhCfgrn+fi/fVVlzfQG/gJuBvwBZ6wg7oyAG+lVA+llAFL22APTdMuaJr2YA37NEhdmqatwho41tupAEqp24HnsRy5omna45qmnarh9Sus9+XWV0011YXlB+7r1t+ejmE54m3sr2FNdR0BPgAOAq2AbdbtGvv9ytc0Lc/6Q20llt80j2ua9lsN2zZqbfbAJmvetayV+nOVNalGWiutbcjEXqCjUuqfWH4V+2st+3gB2TU8z8X766uuXMBJ07RfAJRSG4B7sawP2rIuHTARy6+oWYCGJdBr2qeoAeuqRin1KPAmcL+maem11HSRvjFqAlZrmnbxOVdjWZevra5Ge6+wfB/eqWlaolLqOSxLD8/VUhc04PullGqP5b2Zp2na19exS4PXZi/5Zasj75rWpa61JtXga6XUMGRCKbVDKeVjfTwPMNW2D5Z1uR1Yjli6WZcLnIFBwJ56rGsfcFgpdfHX5UFAoh3UFW99rfux/BreBctvB9eqax9wp1LKVSnVAsvSQMJN1FWFUmoKliPuwZWWdK76eWialguUKqW6WJcPhltrrU+blVK3WD8eCkTVVhcN9zWsyQUuH6meBXyueLxR3i+lVCtgC/BHTdOWXGv7RqzNLvLLVmebVFmXUkoNAs5pmnYUQCm1GRiqlDoBfGz9lXsg8D/W/TdaPz6Kda0UKFFKXVwr/b2OddU0ZEIBG5VSJUAq1jM9lFJbgAeA+cDnSqmdQCkwSdO0MqXUK1jW1vRYzgg4U8eaaqvLBfhIKWUEjmP9I5wd1HUnlm+gIuAr69GbL5e/jv+01vUMlqPySZqmFSilPsDyDaUH3tQ0rfgm6rrEunzzAXAK+E4pBbBd07S/KqWWAm/V8nmApWf9V4ABy9FUtV/Xb9JMLH+EK8WyJPestebG/BrW5GlguVKq3Pq6z1jrauz3689YfnD8RSl1ce17pKZpRVdu2Mi12UV+2eTyeKXUx8AqTdM2Wm+bgBhN0/pab08DOmua9lalfZKBUE3TipRSnbH89X2B9b6LwbUUWKpp2pVHe0IIUS/sJb9stWxy5RpUNpa1oItqWpOy1fqfEEJUZhf5ZavwvnJd6jeuvSbV6GulQghRA7vIL1stm1z8a20Yl9elWmK5IObimtSblddKrX+8+BzLT6fKa6XPYFkr1AP/Yz3tSQghGoS95Je0hBVCCAckF+kIIYQDkvAWQggH1Gjnedd0VZJm6fZlAFZgWRvadJX9BwMzNE2b0Bj1CiHERbVcVRmM5bqFMuA8lm6VhbXsP5h6zq/GPPKudlWSUqoLsB3o34h1CCHEjarpqsp5wFhrb5ojXG7V3Cga8wrLK69K6oelQ9gzVG/ReVVKqeexXH7thKUJzYNYLk29D3DHcln2/2ma9ll9FS+EaNZqyq9+2uW+8Je6VV5LfeVXYx5519TtK1HTtIM38iTWX1/8gHusfQKcuHzk3kLTtAew9Pr9082XLIQQQM35lQ6glBqHpbvn0ms9SX3mV2MeedfWsa8K60+l8dabk4F8a49nALOmaSZrL4hlSql8oB2WNwDgYs/m01xuLC+EEDerxvxSSr2MJa9GaJpW3Jj51ZhH3jV1oKtG07QPNetkESx9qtdZH2oDnFdKhWFZZ3oUeAHL56CzbiMnrQshGkJNHUffxNKI7R5N0zKgcfOrMY+8a+v2VStN0+KVUseVUruwrCdNxTLJpkAptR/LX31TsbwxQgjRUK7Mrz8BPwLRWLqOAqzQNG3+xR0aOr/kCkshhHBAcpGOEEI4IAlvIYRwQLaapINSygnLzMWOWKbC/BNIAj7DsnCfADynaZrJun1XYI2maSHW277AYS63UFytadqcRvwUhBDCZmwW3sAUIFPTtMeUUn5Y5rrFYpkQvU0ptQAYA6xWSj0GvIhlyOdFkcAyTdNeaOzChRDC1my5bPIt8JdKt8uBvlgulwfLnLd7rB9nAXddsX9fIFIptV0p9a1SKqghixVCCHtis/DWNC1f07Q8pZQXsBLL8FCdpmkXT3/JA1pYt92gaVrBFU9xCPirpml3AWuAuY1UuhBC2JxN/2CplGoP/AJ8oWna14Cp0sPXmue21bovWM7BjGiQIoUQwg7ZLLytY4G2AH/UNG2J9e4Ya+tEuDznrTYfAw9ZPx4KRDVEnUIIYY9s+QfLPwM+wF+UUhfXvl8EPlBKOQMHsSyn1OZPwBKl1Ktd14cAAABJSURBVCyggEZuxyiEELYkV1gKIYQDkot0hBDCAUl4CyGEA5LwFkIIByThLYQQDkjCWwghHJCEtxBCOCAJbyGEcEAS3kII4YD+P6V2cfEiM7cQAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1ef51ca3908>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# vector inputs\n",
    "times = pd.DatetimeIndex(start='2015-01-01', end='2015-01-02', freq='12H')\n",
    "temps = pd.Series([0, 10, 5], index=times)\n",
    "irrads = pd.Series([0, 500, 0], index=times)\n",
    "winds = pd.Series([10, 5, 0], index=times)\n",
    "\n",
    "pvtemps = pvsystem.sapm_celltemp(irrads, winds, temps)\n",
    "pvtemps.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Cell and module temperature as a function of wind speed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'temperature (deg C)')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1ef51cd07b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wind = np.linspace(0,20,21)\n",
    "temps = pd.DataFrame(pvsystem.sapm_celltemp(900, wind, 20), index=wind)\n",
    "\n",
    "temps.plot()\n",
    "plt.legend()\n",
    "plt.xlabel('wind speed (m/s)')\n",
    "plt.ylabel('temperature (deg C)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Cell and module temperature as a function of ambient temperature."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'temperature (deg C)')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1ef5215b828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "atemp = np.linspace(-20,50,71)\n",
    "temps = pvsystem.sapm_celltemp(900, 2, atemp).set_index(atemp)\n",
    "\n",
    "temps.plot()\n",
    "plt.legend()\n",
    "plt.xlabel('ambient temperature (deg C)')\n",
    "plt.ylabel('temperature (deg C)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Cell and module temperature as a function of incident irradiance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'temperature (deg C)')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1ef521e1518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "irrad = np.linspace(0,1000,101)\n",
    "temps = pvsystem.sapm_celltemp(irrad, 2, 20).set_index(irrad)\n",
    "\n",
    "temps.plot()\n",
    "plt.legend()\n",
    "plt.xlabel('incident irradiance (W/m**2)')\n",
    "plt.ylabel('temperature (deg C)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Cell and module temperature for different module and racking types."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'temperature (deg C)')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1ef5223fb38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "models = ['open_rack_cell_glassback',\n",
    "          'roof_mount_cell_glassback',\n",
    "          'open_rack_cell_polymerback',\n",
    "          'insulated_back_polymerback',\n",
    "          'open_rack_polymer_thinfilm_steel',\n",
    "          '22x_concentrator_tracker']\n",
    "\n",
    "temps = pd.DataFrame(index=['temp_cell','temp_module'])\n",
    "\n",
    "for model in models:\n",
    "    temps[model] = pd.Series(pvsystem.sapm_celltemp(1000, 5, 20, model=model).iloc[0])\n",
    "\n",
    "temps.T.plot(kind='bar') # try removing the transpose operation and replotting\n",
    "plt.legend()\n",
    "plt.ylabel('temperature (deg C)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### snlinverter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>ABB__MICRO_0_25_I_OUTD_US_208_208V__CEC_2014_</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",
       "      <th>ABB__MICRO_0_3_I_OUTD_US_208__208V__208V__CEC_2018_</th>\n",
       "      <th>ABB__MICRO_0_3_I_OUTD_US_240_240V__CEC_2014_</th>\n",
       "      <th>ABB__MICRO_0_3_I_OUTD_US_240__240V__240V__CEC_2018_</th>\n",
       "      <th>ABB__MICRO_0_3HV_I_OUTD_US_208_208V__CEC_2014_</th>\n",
       "      <th>ABB__MICRO_0_3HV_I_OUTD_US_208__208V__208V__CEC_2018_</th>\n",
       "      <th>...</th>\n",
       "      <th>i_Energy_Corporation__GT260_240V__CEC_2013_</th>\n",
       "      <th>i_Energy__GT260__240V__240V__CEC_2018_</th>\n",
       "      <th>iPower__SHO_1_1__120V__120V__CEC_2018_</th>\n",
       "      <th>iPower__SHO_2_0__240V__240V__CEC_2018_</th>\n",
       "      <th>iPower__SHO_2_5__240V__240V__CEC_2018_</th>\n",
       "      <th>iPower__SHO_3_0__240V__240V__CEC_2018_</th>\n",
       "      <th>iPower__SHO_3_5__240V__240V__CEC_2018_</th>\n",
       "      <th>iPower__SHO_4_6__208V__208V__CEC_2018_</th>\n",
       "      <th>iPower__SHO_4_8__240V__240V__CEC_2018_</th>\n",
       "      <th>iPower__SHO_5_2__240V__240V__CEC_2018_</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Vac</th>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>240.000000</td>\n",
       "      <td>240.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>240.000000</td>\n",
       "      <td>240.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>240.000000</td>\n",
       "      <td>240.000000</td>\n",
       "      <td>120.000000</td>\n",
       "      <td>240.000000</td>\n",
       "      <td>240.000000</td>\n",
       "      <td>240.000000</td>\n",
       "      <td>240.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>240.000000</td>\n",
       "      <td>240.000000</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>250.000000</td>\n",
       "      <td>300.000000</td>\n",
       "      <td>300.000000</td>\n",
       "      <td>300.000000</td>\n",
       "      <td>300.000000</td>\n",
       "      <td>300.000000</td>\n",
       "      <td>300.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>230.000000</td>\n",
       "      <td>230.000000</td>\n",
       "      <td>1100.000000</td>\n",
       "      <td>2000.000000</td>\n",
       "      <td>2500.000000</td>\n",
       "      <td>3000.000000</td>\n",
       "      <td>3500.000000</td>\n",
       "      <td>4600.000000</td>\n",
       "      <td>4800.000000</td>\n",
       "      <td>5200.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pdco</th>\n",
       "      <td>259.522050</td>\n",
       "      <td>259.589000</td>\n",
       "      <td>259.552697</td>\n",
       "      <td>259.492000</td>\n",
       "      <td>311.714554</td>\n",
       "      <td>311.669000</td>\n",
       "      <td>311.504961</td>\n",
       "      <td>311.581000</td>\n",
       "      <td>312.523347</td>\n",
       "      <td>312.423000</td>\n",
       "      <td>...</td>\n",
       "      <td>245.790658</td>\n",
       "      <td>245.630000</td>\n",
       "      <td>1194.090000</td>\n",
       "      <td>2161.880000</td>\n",
       "      <td>2632.840000</td>\n",
       "      <td>3205.930000</td>\n",
       "      <td>3641.830000</td>\n",
       "      <td>4797.810000</td>\n",
       "      <td>4968.030000</td>\n",
       "      <td>5382.860000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vdco</th>\n",
       "      <td>40.242603</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>39.982246</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.227111</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.136095</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>45.259429</td>\n",
       "      <td>45.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>40.709524</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>182.000000</td>\n",
       "      <td>199.000000</td>\n",
       "      <td>218.000000</td>\n",
       "      <td>222.500000</td>\n",
       "      <td>263.000000</td>\n",
       "      <td>254.000000</td>\n",
       "      <td>263.000000</td>\n",
       "      <td>280.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pso</th>\n",
       "      <td>1.771614</td>\n",
       "      <td>2.089610</td>\n",
       "      <td>1.931194</td>\n",
       "      <td>2.240410</td>\n",
       "      <td>1.971053</td>\n",
       "      <td>1.846510</td>\n",
       "      <td>1.991342</td>\n",
       "      <td>1.950540</td>\n",
       "      <td>1.882620</td>\n",
       "      <td>1.762100</td>\n",
       "      <td>...</td>\n",
       "      <td>2.511675</td>\n",
       "      <td>2.530100</td>\n",
       "      <td>22.095400</td>\n",
       "      <td>24.465800</td>\n",
       "      <td>42.776500</td>\n",
       "      <td>31.682000</td>\n",
       "      <td>64.768100</td>\n",
       "      <td>54.570100</td>\n",
       "      <td>85.145700</td>\n",
       "      <td>62.486700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C0</th>\n",
       "      <td>-0.000025</td>\n",
       "      <td>-0.000041</td>\n",
       "      <td>-0.000027</td>\n",
       "      <td>-0.000039</td>\n",
       "      <td>-0.000036</td>\n",
       "      <td>-0.000033</td>\n",
       "      <td>-0.000031</td>\n",
       "      <td>-0.000034</td>\n",
       "      <td>-0.000049</td>\n",
       "      <td>-0.000045</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000048</td>\n",
       "      <td>0.000062</td>\n",
       "      <td>-0.000021</td>\n",
       "      <td>-0.000013</td>\n",
       "      <td>-0.000014</td>\n",
       "      <td>-0.000008</td>\n",
       "      <td>-0.000009</td>\n",
       "      <td>-0.000006</td>\n",
       "      <td>-0.000006</td>\n",
       "      <td>-0.000005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C1</th>\n",
       "      <td>-0.000090</td>\n",
       "      <td>-0.000091</td>\n",
       "      <td>-0.000158</td>\n",
       "      <td>-0.000132</td>\n",
       "      <td>-0.000256</td>\n",
       "      <td>-0.000192</td>\n",
       "      <td>-0.000289</td>\n",
       "      <td>-0.000256</td>\n",
       "      <td>-0.000241</td>\n",
       "      <td>-0.000198</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000086</td>\n",
       "      <td>-0.000098</td>\n",
       "      <td>0.000057</td>\n",
       "      <td>0.000055</td>\n",
       "      <td>0.000061</td>\n",
       "      <td>0.000036</td>\n",
       "      <td>0.000035</td>\n",
       "      <td>0.000028</td>\n",
       "      <td>0.000034</td>\n",
       "      <td>0.000044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C2</th>\n",
       "      <td>0.000669</td>\n",
       "      <td>0.000494</td>\n",
       "      <td>0.001480</td>\n",
       "      <td>0.002418</td>\n",
       "      <td>-0.000833</td>\n",
       "      <td>0.000907</td>\n",
       "      <td>-0.002110</td>\n",
       "      <td>0.002453</td>\n",
       "      <td>0.000975</td>\n",
       "      <td>0.002208</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.002590</td>\n",
       "      <td>0.000231</td>\n",
       "      <td>0.002001</td>\n",
       "      <td>0.001703</td>\n",
       "      <td>0.002053</td>\n",
       "      <td>0.001708</td>\n",
       "      <td>0.001417</td>\n",
       "      <td>0.001381</td>\n",
       "      <td>0.000586</td>\n",
       "      <td>0.001260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C3</th>\n",
       "      <td>-0.018900</td>\n",
       "      <td>-0.013171</td>\n",
       "      <td>-0.034600</td>\n",
       "      <td>-0.014926</td>\n",
       "      <td>-0.039100</td>\n",
       "      <td>-0.031742</td>\n",
       "      <td>-0.049500</td>\n",
       "      <td>-0.028223</td>\n",
       "      <td>-0.027600</td>\n",
       "      <td>-0.023681</td>\n",
       "      <td>...</td>\n",
       "      <td>0.157676</td>\n",
       "      <td>0.121032</td>\n",
       "      <td>0.000623</td>\n",
       "      <td>0.000315</td>\n",
       "      <td>0.001530</td>\n",
       "      <td>0.000860</td>\n",
       "      <td>0.001218</td>\n",
       "      <td>0.000889</td>\n",
       "      <td>0.000195</td>\n",
       "      <td>0.000367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pnt</th>\n",
       "      <td>0.020000</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>0.050000</td>\n",
       "      <td>0.050000</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>0.050000</td>\n",
       "      <td>0.050000</td>\n",
       "      <td>0.060000</td>\n",
       "      <td>0.060000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.150000</td>\n",
       "      <td>0.150000</td>\n",
       "      <td>3.600000</td>\n",
       "      <td>3.600000</td>\n",
       "      <td>3.900000</td>\n",
       "      <td>3.630000</td>\n",
       "      <td>3.860000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>4.100000</td>\n",
       "      <td>4.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vdcmax</th>\n",
       "      <td>65.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>79.000000</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>59.000000</td>\n",
       "      <td>49.000000</td>\n",
       "      <td>380.000000</td>\n",
       "      <td>380.000000</td>\n",
       "      <td>400.000000</td>\n",
       "      <td>380.000000</td>\n",
       "      <td>400.000000</td>\n",
       "      <td>400.000000</td>\n",
       "      <td>400.000000</td>\n",
       "      <td>400.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Idcmax</th>\n",
       "      <td>10.000000</td>\n",
       "      <td>6.489710</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>6.487300</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>7.791730</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>7.789520</td>\n",
       "      <td>10.500000</td>\n",
       "      <td>6.942740</td>\n",
       "      <td>...</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>6.140760</td>\n",
       "      <td>6.560960</td>\n",
       "      <td>10.863700</td>\n",
       "      <td>12.077200</td>\n",
       "      <td>14.408700</td>\n",
       "      <td>13.847300</td>\n",
       "      <td>18.889000</td>\n",
       "      <td>18.889800</td>\n",
       "      <td>19.224500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mppt_low</th>\n",
       "      <td>20.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>240.000000</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",
       "      <td>50.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>75.000000</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>49.000000</td>\n",
       "      <td>380.000000</td>\n",
       "      <td>380.000000</td>\n",
       "      <td>400.000000</td>\n",
       "      <td>380.000000</td>\n",
       "      <td>400.000000</td>\n",
       "      <td>400.000000</td>\n",
       "      <td>400.000000</td>\n",
       "      <td>400.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>14 rows × 5100 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           ABB__MICRO_0_25_I_OUTD_US_208_208V__CEC_2014_  \\\n",
       "Vac                                           208.000000   \n",
       "Paco                                          250.000000   \n",
       "Pdco                                          259.522050   \n",
       "Vdco                                           40.242603   \n",
       "Pso                                             1.771614   \n",
       "C0                                             -0.000025   \n",
       "C1                                             -0.000090   \n",
       "C2                                              0.000669   \n",
       "C3                                             -0.018900   \n",
       "Pnt                                             0.020000   \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_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   \n",
       "\n",
       "           ABB__MICRO_0_3_I_OUTD_US_208__208V__208V__CEC_2018_  \\\n",
       "Vac                                               208.000000     \n",
       "Paco                                              300.000000     \n",
       "Pdco                                              311.669000     \n",
       "Vdco                                               40.000000     \n",
       "Pso                                                 1.846510     \n",
       "C0                                                 -0.000033     \n",
       "C1                                                 -0.000192     \n",
       "C2                                                  0.000907     \n",
       "C3                                                 -0.031742     \n",
       "Pnt                                                 0.020000     \n",
       "Vdcmax                                             50.000000     \n",
       "Idcmax                                              7.791730     \n",
       "Mppt_low                                           30.000000     \n",
       "Mppt_high                                          50.000000     \n",
       "\n",
       "           ABB__MICRO_0_3_I_OUTD_US_240_240V__CEC_2014_  \\\n",
       "Vac                                          240.000000   \n",
       "Paco                                         300.000000   \n",
       "Pdco                                         311.504961   \n",
       "Vdco                                          40.136095   \n",
       "Pso                                            1.991342   \n",
       "C0                                            -0.000031   \n",
       "C1                                            -0.000289   \n",
       "C2                                            -0.002110   \n",
       "C3                                            -0.049500   \n",
       "Pnt                                            0.050000   \n",
       "Vdcmax                                        65.000000   \n",
       "Idcmax                                        10.000000   \n",
       "Mppt_low                                      30.000000   \n",
       "Mppt_high                                     50.000000   \n",
       "\n",
       "           ABB__MICRO_0_3_I_OUTD_US_240__240V__240V__CEC_2018_  \\\n",
       "Vac                                               240.000000     \n",
       "Paco                                              300.000000     \n",
       "Pdco                                              311.581000     \n",
       "Vdco                                               40.000000     \n",
       "Pso                                                 1.950540     \n",
       "C0                                                 -0.000034     \n",
       "C1                                                 -0.000256     \n",
       "C2                                                  0.002453     \n",
       "C3                                                 -0.028223     \n",
       "Pnt                                                 0.050000     \n",
       "Vdcmax                                             50.000000     \n",
       "Idcmax                                              7.789520     \n",
       "Mppt_low                                           30.000000     \n",
       "Mppt_high                                          50.000000     \n",
       "\n",
       "           ABB__MICRO_0_3HV_I_OUTD_US_208_208V__CEC_2014_  \\\n",
       "Vac                                            208.000000   \n",
       "Paco                                           300.000000   \n",
       "Pdco                                           312.523347   \n",
       "Vdco                                            45.259429   \n",
       "Pso                                              1.882620   \n",
       "C0                                              -0.000049   \n",
       "C1                                              -0.000241   \n",
       "C2                                               0.000975   \n",
       "C3                                              -0.027600   \n",
       "Pnt                                              0.060000   \n",
       "Vdcmax                                          79.000000   \n",
       "Idcmax                                          10.500000   \n",
       "Mppt_low                                        30.000000   \n",
       "Mppt_high                                       75.000000   \n",
       "\n",
       "           ABB__MICRO_0_3HV_I_OUTD_US_208__208V__208V__CEC_2018_  \\\n",
       "Vac                                               208.000000       \n",
       "Paco                                              300.000000       \n",
       "Pdco                                              312.423000       \n",
       "Vdco                                               45.000000       \n",
       "Pso                                                 1.762100       \n",
       "C0                                                 -0.000045       \n",
       "C1                                                 -0.000198       \n",
       "C2                                                  0.002208       \n",
       "C3                                                 -0.023681       \n",
       "Pnt                                                 0.060000       \n",
       "Vdcmax                                             60.000000       \n",
       "Idcmax                                              6.942740       \n",
       "Mppt_low                                           30.000000       \n",
       "Mppt_high                                          60.000000       \n",
       "\n",
       "                            ...                    \\\n",
       "Vac                         ...                     \n",
       "Paco                        ...                     \n",
       "Pdco                        ...                     \n",
       "Vdco                        ...                     \n",
       "Pso                         ...                     \n",
       "C0                          ...                     \n",
       "C1                          ...                     \n",
       "C2                          ...                     \n",
       "C3                          ...                     \n",
       "Pnt                         ...                     \n",
       "Vdcmax                      ...                     \n",
       "Idcmax                      ...                     \n",
       "Mppt_low                    ...                     \n",
       "Mppt_high                   ...                     \n",
       "\n",
       "           i_Energy_Corporation__GT260_240V__CEC_2013_  \\\n",
       "Vac                                         240.000000   \n",
       "Paco                                        230.000000   \n",
       "Pdco                                        245.790658   \n",
       "Vdco                                         40.709524   \n",
       "Pso                                           2.511675   \n",
       "C0                                            0.000048   \n",
       "C1                                           -0.000086   \n",
       "C2                                           -0.002590   \n",
       "C3                                            0.157676   \n",
       "Pnt                                           0.150000   \n",
       "Vdcmax                                       59.000000   \n",
       "Idcmax                                       10.000000   \n",
       "Mppt_low                                     30.000000   \n",
       "Mppt_high                                    50.000000   \n",
       "\n",
       "           i_Energy__GT260__240V__240V__CEC_2018_  \\\n",
       "Vac                                    240.000000   \n",
       "Paco                                   230.000000   \n",
       "Pdco                                   245.630000   \n",
       "Vdco                                    40.000000   \n",
       "Pso                                      2.530100   \n",
       "C0                                       0.000062   \n",
       "C1                                      -0.000098   \n",
       "C2                                       0.000231   \n",
       "C3                                       0.121032   \n",
       "Pnt                                      0.150000   \n",
       "Vdcmax                                  49.000000   \n",
       "Idcmax                                   6.140760   \n",
       "Mppt_low                                30.000000   \n",
       "Mppt_high                               49.000000   \n",
       "\n",
       "           iPower__SHO_1_1__120V__120V__CEC_2018_  \\\n",
       "Vac                                    120.000000   \n",
       "Paco                                  1100.000000   \n",
       "Pdco                                  1194.090000   \n",
       "Vdco                                   182.000000   \n",
       "Pso                                     22.095400   \n",
       "C0                                      -0.000021   \n",
       "C1                                       0.000057   \n",
       "C2                                       0.002001   \n",
       "C3                                       0.000623   \n",
       "Pnt                                      3.600000   \n",
       "Vdcmax                                 380.000000   \n",
       "Idcmax                                   6.560960   \n",
       "Mppt_low                               100.000000   \n",
       "Mppt_high                              380.000000   \n",
       "\n",
       "           iPower__SHO_2_0__240V__240V__CEC_2018_  \\\n",
       "Vac                                    240.000000   \n",
       "Paco                                  2000.000000   \n",
       "Pdco                                  2161.880000   \n",
       "Vdco                                   199.000000   \n",
       "Pso                                     24.465800   \n",
       "C0                                      -0.000013   \n",
       "C1                                       0.000055   \n",
       "C2                                       0.001703   \n",
       "C3                                       0.000315   \n",
       "Pnt                                      3.600000   \n",
       "Vdcmax                                 380.000000   \n",
       "Idcmax                                  10.863700   \n",
       "Mppt_low                               100.000000   \n",
       "Mppt_high                              380.000000   \n",
       "\n",
       "           iPower__SHO_2_5__240V__240V__CEC_2018_  \\\n",
       "Vac                                    240.000000   \n",
       "Paco                                  2500.000000   \n",
       "Pdco                                  2632.840000   \n",
       "Vdco                                   218.000000   \n",
       "Pso                                     42.776500   \n",
       "C0                                      -0.000014   \n",
       "C1                                       0.000061   \n",
       "C2                                       0.002053   \n",
       "C3                                       0.001530   \n",
       "Pnt                                      3.900000   \n",
       "Vdcmax                                 400.000000   \n",
       "Idcmax                                  12.077200   \n",
       "Mppt_low                               100.000000   \n",
       "Mppt_high                              400.000000   \n",
       "\n",
       "           iPower__SHO_3_0__240V__240V__CEC_2018_  \\\n",
       "Vac                                    240.000000   \n",
       "Paco                                  3000.000000   \n",
       "Pdco                                  3205.930000   \n",
       "Vdco                                   222.500000   \n",
       "Pso                                     31.682000   \n",
       "C0                                      -0.000008   \n",
       "C1                                       0.000036   \n",
       "C2                                       0.001708   \n",
       "C3                                       0.000860   \n",
       "Pnt                                      3.630000   \n",
       "Vdcmax                                 380.000000   \n",
       "Idcmax                                  14.408700   \n",
       "Mppt_low                               100.000000   \n",
       "Mppt_high                              380.000000   \n",
       "\n",
       "           iPower__SHO_3_5__240V__240V__CEC_2018_  \\\n",
       "Vac                                    240.000000   \n",
       "Paco                                  3500.000000   \n",
       "Pdco                                  3641.830000   \n",
       "Vdco                                   263.000000   \n",
       "Pso                                     64.768100   \n",
       "C0                                      -0.000009   \n",
       "C1                                       0.000035   \n",
       "C2                                       0.001417   \n",
       "C3                                       0.001218   \n",
       "Pnt                                      3.860000   \n",
       "Vdcmax                                 400.000000   \n",
       "Idcmax                                  13.847300   \n",
       "Mppt_low                               100.000000   \n",
       "Mppt_high                              400.000000   \n",
       "\n",
       "           iPower__SHO_4_6__208V__208V__CEC_2018_  \\\n",
       "Vac                                    208.000000   \n",
       "Paco                                  4600.000000   \n",
       "Pdco                                  4797.810000   \n",
       "Vdco                                   254.000000   \n",
       "Pso                                     54.570100   \n",
       "C0                                      -0.000006   \n",
       "C1                                       0.000028   \n",
       "C2                                       0.001381   \n",
       "C3                                       0.000889   \n",
       "Pnt                                      4.000000   \n",
       "Vdcmax                                 400.000000   \n",
       "Idcmax                                  18.889000   \n",
       "Mppt_low                               100.000000   \n",
       "Mppt_high                              400.000000   \n",
       "\n",
       "           iPower__SHO_4_8__240V__240V__CEC_2018_  \\\n",
       "Vac                                    240.000000   \n",
       "Paco                                  4800.000000   \n",
       "Pdco                                  4968.030000   \n",
       "Vdco                                   263.000000   \n",
       "Pso                                     85.145700   \n",
       "C0                                      -0.000006   \n",
       "C1                                       0.000034   \n",
       "C2                                       0.000586   \n",
       "C3                                       0.000195   \n",
       "Pnt                                      4.100000   \n",
       "Vdcmax                                 400.000000   \n",
       "Idcmax                                  18.889800   \n",
       "Mppt_low                               100.000000   \n",
       "Mppt_high                              400.000000   \n",
       "\n",
       "           iPower__SHO_5_2__240V__240V__CEC_2018_  \n",
       "Vac                                    240.000000  \n",
       "Paco                                  5200.000000  \n",
       "Pdco                                  5382.860000  \n",
       "Vdco                                   280.000000  \n",
       "Pso                                     62.486700  \n",
       "C0                                      -0.000005  \n",
       "C1                                       0.000044  \n",
       "C2                                       0.001260  \n",
       "C3                                       0.000367  \n",
       "Pnt                                      4.000000  \n",
       "Vdcmax                                 400.000000  \n",
       "Idcmax                                  19.224500  \n",
       "Mppt_low                               240.000000  \n",
       "Mppt_high                              400.000000  \n",
       "\n",
       "[14 rows x 5100 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "inverters = pvsystem.retrieve_sam('sandiainverter')\n",
    "inverters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\cliff\\Anaconda3\\lib\\site-packages\\pvlib\\pvsystem.py:2200: RuntimeWarning: invalid value encountered in minimum\n",
      "  ac_power = np.minimum(Paco, ac_power)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5,0,'dc power')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1ef52291e80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vdcs = pd.Series(np.linspace(0,50,51))\n",
    "idcs = pd.Series(np.linspace(0,11,110))\n",
    "pdcs = idcs * vdcs\n",
    "\n",
    "pacs = pvsystem.snlinverter(vdcs, pdcs, inverters['ABB__MICRO_0_25_I_OUTD_US_208_208V__CEC_2014_'])\n",
    "#pacs.plot()\n",
    "plt.plot(pacs, pdcs)\n",
    "plt.ylabel('ac power')\n",
    "plt.xlabel('dc power')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Need to put more effort into describing this function."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### DC model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This example shows use of the Desoto module performance model and the Sandia Array Performance Model (SAPM). Both models reuire a set of parameter values which can be read from SAM databases for modules.\n",
    "\n",
    "Foe the Desoto model, the database content is returned by supplying the keyword `cecmod` to `pvsystem.retrievesam`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>1Soltech_1STH_215_P</th>\n",
       "      <th>1Soltech_1STH_220_P</th>\n",
       "      <th>1Soltech_1STH_225_P</th>\n",
       "      <th>1Soltech_1STH_230_P</th>\n",
       "      <th>1Soltech_1STH_235_WH</th>\n",
       "      <th>1Soltech_1STH_240_P</th>\n",
       "      <th>1Soltech_1STH_240_WH</th>\n",
       "      <th>1Soltech_1STH_245_P</th>\n",
       "      <th>1Soltech_1STH_245_WH</th>\n",
       "      <th>1Soltech_1STH_250_P</th>\n",
       "      <th>...</th>\n",
       "      <th>iTek_iT_240</th>\n",
       "      <th>iTek_iT_260_HE</th>\n",
       "      <th>iTek_iT_265_HE</th>\n",
       "      <th>iTek_iT_270_HE</th>\n",
       "      <th>iTek_iT_275_HE</th>\n",
       "      <th>iTek_iT_280_HE</th>\n",
       "      <th>iTek_iT_285_HE</th>\n",
       "      <th>iTek_iT_290_HE</th>\n",
       "      <th>iTek_iT_295_HE</th>\n",
       "      <th>iTek_iT_300_HE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>BIPV</th>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>...</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <td>10/7/2010</td>\n",
       "      <td>10/4/2010</td>\n",
       "      <td>10/4/2010</td>\n",
       "      <td>10/4/2010</td>\n",
       "      <td>3/4/2010</td>\n",
       "      <td>4/2/2014</td>\n",
       "      <td>3/4/2010</td>\n",
       "      <td>4/2/2014</td>\n",
       "      <td>3/4/2010</td>\n",
       "      <td>4/2/2014</td>\n",
       "      <td>...</td>\n",
       "      <td>10/26/2011</td>\n",
       "      <td>2/2/2015</td>\n",
       "      <td>2/2/2015</td>\n",
       "      <td>2/2/2015</td>\n",
       "      <td>2/2/2015</td>\n",
       "      <td>2/2/2015</td>\n",
       "      <td>5/29/2015</td>\n",
       "      <td>5/29/2015</td>\n",
       "      <td>5/29/2015</td>\n",
       "      <td>5/29/2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T_NOCT</th>\n",
       "      <td>47.4</td>\n",
       "      <td>47.4</td>\n",
       "      <td>47.4</td>\n",
       "      <td>47.4</td>\n",
       "      <td>49.9</td>\n",
       "      <td>43</td>\n",
       "      <td>49.9</td>\n",
       "      <td>43</td>\n",
       "      <td>49.9</td>\n",
       "      <td>43</td>\n",
       "      <td>...</td>\n",
       "      <td>48.2</td>\n",
       "      <td>44.5</td>\n",
       "      <td>44.5</td>\n",
       "      <td>44.5</td>\n",
       "      <td>44.5</td>\n",
       "      <td>44.5</td>\n",
       "      <td>48.8</td>\n",
       "      <td>48.8</td>\n",
       "      <td>48.7</td>\n",
       "      <td>48.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A_c</th>\n",
       "      <td>1.567</td>\n",
       "      <td>1.567</td>\n",
       "      <td>1.567</td>\n",
       "      <td>1.567</td>\n",
       "      <td>1.635</td>\n",
       "      <td>1.561</td>\n",
       "      <td>1.635</td>\n",
       "      <td>1.561</td>\n",
       "      <td>1.635</td>\n",
       "      <td>1.561</td>\n",
       "      <td>...</td>\n",
       "      <td>1.637</td>\n",
       "      <td>1.634</td>\n",
       "      <td>1.634</td>\n",
       "      <td>1.634</td>\n",
       "      <td>1.634</td>\n",
       "      <td>1.634</td>\n",
       "      <td>1.62</td>\n",
       "      <td>1.62</td>\n",
       "      <td>1.62</td>\n",
       "      <td>1.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N_s</th>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "      <td>...</td>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>I_sc_ref</th>\n",
       "      <td>7.84</td>\n",
       "      <td>7.97</td>\n",
       "      <td>8.09</td>\n",
       "      <td>8.18</td>\n",
       "      <td>8.54</td>\n",
       "      <td>8.62</td>\n",
       "      <td>8.58</td>\n",
       "      <td>8.65</td>\n",
       "      <td>8.62</td>\n",
       "      <td>8.69</td>\n",
       "      <td>...</td>\n",
       "      <td>8.7</td>\n",
       "      <td>8.9</td>\n",
       "      <td>9</td>\n",
       "      <td>9.1</td>\n",
       "      <td>9.2</td>\n",
       "      <td>9.3</td>\n",
       "      <td>10.05</td>\n",
       "      <td>10.08</td>\n",
       "      <td>9.9</td>\n",
       "      <td>10.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>V_oc_ref</th>\n",
       "      <td>36.3</td>\n",
       "      <td>36.6</td>\n",
       "      <td>36.9</td>\n",
       "      <td>37.1</td>\n",
       "      <td>37</td>\n",
       "      <td>36.9</td>\n",
       "      <td>37.1</td>\n",
       "      <td>37.1</td>\n",
       "      <td>37.2</td>\n",
       "      <td>37.3</td>\n",
       "      <td>...</td>\n",
       "      <td>38</td>\n",
       "      <td>38.6</td>\n",
       "      <td>38.7</td>\n",
       "      <td>38.9</td>\n",
       "      <td>39</td>\n",
       "      <td>39.2</td>\n",
       "      <td>40.9</td>\n",
       "      <td>41.2</td>\n",
       "      <td>41.2</td>\n",
       "      <td>41.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>I_mp_ref</th>\n",
       "      <td>7.35</td>\n",
       "      <td>7.47</td>\n",
       "      <td>7.58</td>\n",
       "      <td>7.65</td>\n",
       "      <td>8.02</td>\n",
       "      <td>8.08</td>\n",
       "      <td>8.07</td>\n",
       "      <td>8.14</td>\n",
       "      <td>8.1</td>\n",
       "      <td>8.25</td>\n",
       "      <td>...</td>\n",
       "      <td>8.2</td>\n",
       "      <td>8.2</td>\n",
       "      <td>8.3</td>\n",
       "      <td>8.4</td>\n",
       "      <td>8.5</td>\n",
       "      <td>8.6</td>\n",
       "      <td>9.53</td>\n",
       "      <td>9.57</td>\n",
       "      <td>9.43</td>\n",
       "      <td>9.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>V_mp_ref</th>\n",
       "      <td>29</td>\n",
       "      <td>29.3</td>\n",
       "      <td>29.6</td>\n",
       "      <td>29.9</td>\n",
       "      <td>29.3</td>\n",
       "      <td>29.7</td>\n",
       "      <td>29.7</td>\n",
       "      <td>30.1</td>\n",
       "      <td>30.2</td>\n",
       "      <td>30.3</td>\n",
       "      <td>...</td>\n",
       "      <td>30</td>\n",
       "      <td>31.7</td>\n",
       "      <td>31.8</td>\n",
       "      <td>32</td>\n",
       "      <td>32.1</td>\n",
       "      <td>32.3</td>\n",
       "      <td>33.6</td>\n",
       "      <td>34</td>\n",
       "      <td>34.5</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>alpha_sc</th>\n",
       "      <td>0.007997</td>\n",
       "      <td>0.008129</td>\n",
       "      <td>0.008252</td>\n",
       "      <td>0.008344</td>\n",
       "      <td>0.00743</td>\n",
       "      <td>0.010085</td>\n",
       "      <td>0.007465</td>\n",
       "      <td>0.010121</td>\n",
       "      <td>0.007499</td>\n",
       "      <td>0.010167</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00348</td>\n",
       "      <td>0.00356</td>\n",
       "      <td>0.0036</td>\n",
       "      <td>0.00364</td>\n",
       "      <td>0.00368</td>\n",
       "      <td>0.00372</td>\n",
       "      <td>0.00376</td>\n",
       "      <td>0.0038</td>\n",
       "      <td>0.00384</td>\n",
       "      <td>0.00388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beta_oc</th>\n",
       "      <td>-0.13104</td>\n",
       "      <td>-0.13213</td>\n",
       "      <td>-0.13321</td>\n",
       "      <td>-0.13393</td>\n",
       "      <td>-0.13653</td>\n",
       "      <td>-0.13432</td>\n",
       "      <td>-0.1369</td>\n",
       "      <td>-0.13504</td>\n",
       "      <td>-0.13727</td>\n",
       "      <td>-0.13577</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1292</td>\n",
       "      <td>-0.10808</td>\n",
       "      <td>-0.10836</td>\n",
       "      <td>-0.10892</td>\n",
       "      <td>-0.1092</td>\n",
       "      <td>-0.10976</td>\n",
       "      <td>-0.11397</td>\n",
       "      <td>-0.11455</td>\n",
       "      <td>-0.11513</td>\n",
       "      <td>-0.11542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>a_ref</th>\n",
       "      <td>1.6413</td>\n",
       "      <td>1.6572</td>\n",
       "      <td>1.6732</td>\n",
       "      <td>1.6888</td>\n",
       "      <td>1.6292</td>\n",
       "      <td>1.6068</td>\n",
       "      <td>1.6425</td>\n",
       "      <td>1.6195</td>\n",
       "      <td>1.6617</td>\n",
       "      <td>1.629</td>\n",
       "      <td>...</td>\n",
       "      <td>1.6204</td>\n",
       "      <td>1.527</td>\n",
       "      <td>1.5306</td>\n",
       "      <td>1.5386</td>\n",
       "      <td>1.5422</td>\n",
       "      <td>1.5503</td>\n",
       "      <td>1.5904</td>\n",
       "      <td>1.5986</td>\n",
       "      <td>1.6069</td>\n",
       "      <td>1.6107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>I_L_ref</th>\n",
       "      <td>7.843</td>\n",
       "      <td>7.974</td>\n",
       "      <td>8.094</td>\n",
       "      <td>8.185</td>\n",
       "      <td>8.543</td>\n",
       "      <td>8.626</td>\n",
       "      <td>8.582</td>\n",
       "      <td>8.653</td>\n",
       "      <td>8.623</td>\n",
       "      <td>8.781</td>\n",
       "      <td>...</td>\n",
       "      <td>8.7</td>\n",
       "      <td>8.923</td>\n",
       "      <td>9.022</td>\n",
       "      <td>9.121</td>\n",
       "      <td>9.221</td>\n",
       "      <td>9.32</td>\n",
       "      <td>9.418</td>\n",
       "      <td>9.517</td>\n",
       "      <td>9.617</td>\n",
       "      <td>9.716</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>I_o_ref</th>\n",
       "      <td>1.936e-09</td>\n",
       "      <td>2.03e-09</td>\n",
       "      <td>2.126e-09</td>\n",
       "      <td>2.332e-09</td>\n",
       "      <td>1.166e-09</td>\n",
       "      <td>9.08e-10</td>\n",
       "      <td>1.325e-09</td>\n",
       "      <td>9.68e-10</td>\n",
       "      <td>1.623e-09</td>\n",
       "      <td>9.92e-10</td>\n",
       "      <td>...</td>\n",
       "      <td>5.68e-10</td>\n",
       "      <td>9e-11</td>\n",
       "      <td>9.06e-11</td>\n",
       "      <td>9.19e-11</td>\n",
       "      <td>9.25e-11</td>\n",
       "      <td>9.39e-11</td>\n",
       "      <td>1.69e-10</td>\n",
       "      <td>1.71e-10</td>\n",
       "      <td>1.74e-10</td>\n",
       "      <td>1.75e-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R_s</th>\n",
       "      <td>0.359</td>\n",
       "      <td>0.346</td>\n",
       "      <td>0.334</td>\n",
       "      <td>0.311</td>\n",
       "      <td>0.383</td>\n",
       "      <td>0.316</td>\n",
       "      <td>0.335</td>\n",
       "      <td>0.282</td>\n",
       "      <td>0.272</td>\n",
       "      <td>0.275</td>\n",
       "      <td>...</td>\n",
       "      <td>0.411</td>\n",
       "      <td>0.276</td>\n",
       "      <td>0.271</td>\n",
       "      <td>0.265</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.254</td>\n",
       "      <td>0.241</td>\n",
       "      <td>0.235</td>\n",
       "      <td>0.229</td>\n",
       "      <td>0.225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R_sh_ref</th>\n",
       "      <td>839.4</td>\n",
       "      <td>751.03</td>\n",
       "      <td>670.65</td>\n",
       "      <td>462.56</td>\n",
       "      <td>1257.84</td>\n",
       "      <td>452.56</td>\n",
       "      <td>1463.82</td>\n",
       "      <td>790.96</td>\n",
       "      <td>724.06</td>\n",
       "      <td>600.38</td>\n",
       "      <td>...</td>\n",
       "      <td>25925.1</td>\n",
       "      <td>109.16</td>\n",
       "      <td>111.38</td>\n",
       "      <td>113.85</td>\n",
       "      <td>116.21</td>\n",
       "      <td>118.83</td>\n",
       "      <td>125.87</td>\n",
       "      <td>128.9</td>\n",
       "      <td>132.03</td>\n",
       "      <td>135.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adjust</th>\n",
       "      <td>16.5</td>\n",
       "      <td>16.8</td>\n",
       "      <td>17.1</td>\n",
       "      <td>17.9</td>\n",
       "      <td>8.7</td>\n",
       "      <td>7.736</td>\n",
       "      <td>9.8</td>\n",
       "      <td>8.259</td>\n",
       "      <td>11.6</td>\n",
       "      <td>8.361</td>\n",
       "      <td>...</td>\n",
       "      <td>11.88</td>\n",
       "      <td>17.19</td>\n",
       "      <td>17.14</td>\n",
       "      <td>17.17</td>\n",
       "      <td>17.12</td>\n",
       "      <td>17.15</td>\n",
       "      <td>18.44</td>\n",
       "      <td>18.47</td>\n",
       "      <td>18.5</td>\n",
       "      <td>18.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gamma_r</th>\n",
       "      <td>-0.495</td>\n",
       "      <td>-0.495</td>\n",
       "      <td>-0.495</td>\n",
       "      <td>-0.495</td>\n",
       "      <td>-0.482</td>\n",
       "      <td>-0.43</td>\n",
       "      <td>-0.482</td>\n",
       "      <td>-0.43</td>\n",
       "      <td>-0.482</td>\n",
       "      <td>-0.43</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.5</td>\n",
       "      <td>-0.4</td>\n",
       "      <td>-0.4</td>\n",
       "      <td>-0.4</td>\n",
       "      <td>-0.4</td>\n",
       "      <td>-0.4</td>\n",
       "      <td>-0.42</td>\n",
       "      <td>-0.42</td>\n",
       "      <td>-0.42</td>\n",
       "      <td>-0.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Version</th>\n",
       "      <td>MM107</td>\n",
       "      <td>MM107</td>\n",
       "      <td>MM107</td>\n",
       "      <td>MM107</td>\n",
       "      <td>MM107</td>\n",
       "      <td>NRELv1</td>\n",
       "      <td>MM107</td>\n",
       "      <td>NRELv1</td>\n",
       "      <td>MM107</td>\n",
       "      <td>NRELv1</td>\n",
       "      <td>...</td>\n",
       "      <td>NRELv1</td>\n",
       "      <td>NRELv1</td>\n",
       "      <td>NRELv1</td>\n",
       "      <td>NRELv1</td>\n",
       "      <td>NRELv1</td>\n",
       "      <td>NRELv1</td>\n",
       "      <td>NRELv1</td>\n",
       "      <td>NRELv1</td>\n",
       "      <td>NRELv1</td>\n",
       "      <td>NRELv1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTC</th>\n",
       "      <td>189.4</td>\n",
       "      <td>194</td>\n",
       "      <td>198.5</td>\n",
       "      <td>203.1</td>\n",
       "      <td>205.1</td>\n",
       "      <td>220.6</td>\n",
       "      <td>209.6</td>\n",
       "      <td>225.3</td>\n",
       "      <td>214.1</td>\n",
       "      <td>230</td>\n",
       "      <td>...</td>\n",
       "      <td>210.6</td>\n",
       "      <td>239</td>\n",
       "      <td>243.7</td>\n",
       "      <td>248.4</td>\n",
       "      <td>253.1</td>\n",
       "      <td>257.8</td>\n",
       "      <td>292.1</td>\n",
       "      <td>296.8</td>\n",
       "      <td>296.9</td>\n",
       "      <td>296.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Technology</th>\n",
       "      <td>Multi-c-Si</td>\n",
       "      <td>Multi-c-Si</td>\n",
       "      <td>Multi-c-Si</td>\n",
       "      <td>Multi-c-Si</td>\n",
       "      <td>Mono-c-Si</td>\n",
       "      <td>Multi-c-Si</td>\n",
       "      <td>Mono-c-Si</td>\n",
       "      <td>Multi-c-Si</td>\n",
       "      <td>Mono-c-Si</td>\n",
       "      <td>Multi-c-Si</td>\n",
       "      <td>...</td>\n",
       "      <td>Mono-c-Si</td>\n",
       "      <td>Mono-c-Si</td>\n",
       "      <td>Mono-c-Si</td>\n",
       "      <td>Mono-c-Si</td>\n",
       "      <td>Mono-c-Si</td>\n",
       "      <td>Mono-c-Si</td>\n",
       "      <td>Mono-c-Si</td>\n",
       "      <td>Mono-c-Si</td>\n",
       "      <td>Mono-c-Si</td>\n",
       "      <td>Mono-c-Si</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>21 rows × 19254 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           1Soltech_1STH_215_P 1Soltech_1STH_220_P 1Soltech_1STH_225_P  \\\n",
       "BIPV                         N                   N                   N   \n",
       "Date                 10/7/2010           10/4/2010           10/4/2010   \n",
       "T_NOCT                    47.4                47.4                47.4   \n",
       "A_c                      1.567               1.567               1.567   \n",
       "N_s                         60                  60                  60   \n",
       "I_sc_ref                  7.84                7.97                8.09   \n",
       "V_oc_ref                  36.3                36.6                36.9   \n",
       "I_mp_ref                  7.35                7.47                7.58   \n",
       "V_mp_ref                    29                29.3                29.6   \n",
       "alpha_sc              0.007997            0.008129            0.008252   \n",
       "beta_oc               -0.13104            -0.13213            -0.13321   \n",
       "a_ref                   1.6413              1.6572              1.6732   \n",
       "I_L_ref                  7.843               7.974               8.094   \n",
       "I_o_ref              1.936e-09            2.03e-09           2.126e-09   \n",
       "R_s                      0.359               0.346               0.334   \n",
       "R_sh_ref                 839.4              751.03              670.65   \n",
       "Adjust                    16.5                16.8                17.1   \n",
       "gamma_r                 -0.495              -0.495              -0.495   \n",
       "Version                  MM107               MM107               MM107   \n",
       "PTC                      189.4                 194               198.5   \n",
       "Technology          Multi-c-Si          Multi-c-Si          Multi-c-Si   \n",
       "\n",
       "           1Soltech_1STH_230_P 1Soltech_1STH_235_WH 1Soltech_1STH_240_P  \\\n",
       "BIPV                         N                    N                   N   \n",
       "Date                 10/4/2010             3/4/2010            4/2/2014   \n",
       "T_NOCT                    47.4                 49.9                  43   \n",
       "A_c                      1.567                1.635               1.561   \n",
       "N_s                         60                   60                  60   \n",
       "I_sc_ref                  8.18                 8.54                8.62   \n",
       "V_oc_ref                  37.1                   37                36.9   \n",
       "I_mp_ref                  7.65                 8.02                8.08   \n",
       "V_mp_ref                  29.9                 29.3                29.7   \n",
       "alpha_sc              0.008344              0.00743            0.010085   \n",
       "beta_oc               -0.13393             -0.13653            -0.13432   \n",
       "a_ref                   1.6888               1.6292              1.6068   \n",
       "I_L_ref                  8.185                8.543               8.626   \n",
       "I_o_ref              2.332e-09            1.166e-09            9.08e-10   \n",
       "R_s                      0.311                0.383               0.316   \n",
       "R_sh_ref                462.56              1257.84              452.56   \n",
       "Adjust                    17.9                  8.7               7.736   \n",
       "gamma_r                 -0.495               -0.482               -0.43   \n",
       "Version                  MM107                MM107              NRELv1   \n",
       "PTC                      203.1                205.1               220.6   \n",
       "Technology          Multi-c-Si            Mono-c-Si          Multi-c-Si   \n",
       "\n",
       "           1Soltech_1STH_240_WH 1Soltech_1STH_245_P 1Soltech_1STH_245_WH  \\\n",
       "BIPV                          N                   N                    N   \n",
       "Date                   3/4/2010            4/2/2014             3/4/2010   \n",
       "T_NOCT                     49.9                  43                 49.9   \n",
       "A_c                       1.635               1.561                1.635   \n",
       "N_s                          60                  60                   60   \n",
       "I_sc_ref                   8.58                8.65                 8.62   \n",
       "V_oc_ref                   37.1                37.1                 37.2   \n",
       "I_mp_ref                   8.07                8.14                  8.1   \n",
       "V_mp_ref                   29.7                30.1                 30.2   \n",
       "alpha_sc               0.007465            0.010121             0.007499   \n",
       "beta_oc                 -0.1369            -0.13504             -0.13727   \n",
       "a_ref                    1.6425              1.6195               1.6617   \n",
       "I_L_ref                   8.582               8.653                8.623   \n",
       "I_o_ref               1.325e-09            9.68e-10            1.623e-09   \n",
       "R_s                       0.335               0.282                0.272   \n",
       "R_sh_ref                1463.82              790.96               724.06   \n",
       "Adjust                      9.8               8.259                 11.6   \n",
       "gamma_r                  -0.482               -0.43               -0.482   \n",
       "Version                   MM107              NRELv1                MM107   \n",
       "PTC                       209.6               225.3                214.1   \n",
       "Technology            Mono-c-Si          Multi-c-Si            Mono-c-Si   \n",
       "\n",
       "           1Soltech_1STH_250_P      ...       iTek_iT_240 iTek_iT_260_HE  \\\n",
       "BIPV                         N      ...                 N              N   \n",
       "Date                  4/2/2014      ...        10/26/2011       2/2/2015   \n",
       "T_NOCT                      43      ...              48.2           44.5   \n",
       "A_c                      1.561      ...             1.637          1.634   \n",
       "N_s                         60      ...                60             60   \n",
       "I_sc_ref                  8.69      ...               8.7            8.9   \n",
       "V_oc_ref                  37.3      ...                38           38.6   \n",
       "I_mp_ref                  8.25      ...               8.2            8.2   \n",
       "V_mp_ref                  30.3      ...                30           31.7   \n",
       "alpha_sc              0.010167      ...           0.00348        0.00356   \n",
       "beta_oc               -0.13577      ...           -0.1292       -0.10808   \n",
       "a_ref                    1.629      ...            1.6204          1.527   \n",
       "I_L_ref                  8.781      ...               8.7          8.923   \n",
       "I_o_ref               9.92e-10      ...          5.68e-10          9e-11   \n",
       "R_s                      0.275      ...             0.411          0.276   \n",
       "R_sh_ref                600.38      ...           25925.1         109.16   \n",
       "Adjust                   8.361      ...             11.88          17.19   \n",
       "gamma_r                  -0.43      ...              -0.5           -0.4   \n",
       "Version                 NRELv1      ...            NRELv1         NRELv1   \n",
       "PTC                        230      ...             210.6            239   \n",
       "Technology          Multi-c-Si      ...         Mono-c-Si      Mono-c-Si   \n",
       "\n",
       "           iTek_iT_265_HE iTek_iT_270_HE iTek_iT_275_HE iTek_iT_280_HE  \\\n",
       "BIPV                    N              N              N              N   \n",
       "Date             2/2/2015       2/2/2015       2/2/2015       2/2/2015   \n",
       "T_NOCT               44.5           44.5           44.5           44.5   \n",
       "A_c                 1.634          1.634          1.634          1.634   \n",
       "N_s                    60             60             60             60   \n",
       "I_sc_ref                9            9.1            9.2            9.3   \n",
       "V_oc_ref             38.7           38.9             39           39.2   \n",
       "I_mp_ref              8.3            8.4            8.5            8.6   \n",
       "V_mp_ref             31.8             32           32.1           32.3   \n",
       "alpha_sc           0.0036        0.00364        0.00368        0.00372   \n",
       "beta_oc          -0.10836       -0.10892        -0.1092       -0.10976   \n",
       "a_ref              1.5306         1.5386         1.5422         1.5503   \n",
       "I_L_ref             9.022          9.121          9.221           9.32   \n",
       "I_o_ref          9.06e-11       9.19e-11       9.25e-11       9.39e-11   \n",
       "R_s                 0.271          0.265           0.26          0.254   \n",
       "R_sh_ref           111.38         113.85         116.21         118.83   \n",
       "Adjust              17.14          17.17          17.12          17.15   \n",
       "gamma_r              -0.4           -0.4           -0.4           -0.4   \n",
       "Version            NRELv1         NRELv1         NRELv1         NRELv1   \n",
       "PTC                 243.7          248.4          253.1          257.8   \n",
       "Technology      Mono-c-Si      Mono-c-Si      Mono-c-Si      Mono-c-Si   \n",
       "\n",
       "           iTek_iT_285_HE iTek_iT_290_HE iTek_iT_295_HE iTek_iT_300_HE  \n",
       "BIPV                    N              N              N              N  \n",
       "Date            5/29/2015      5/29/2015      5/29/2015      5/29/2015  \n",
       "T_NOCT               48.8           48.8           48.7           48.8  \n",
       "A_c                  1.62           1.62           1.62           1.62  \n",
       "N_s                    60             60             60             60  \n",
       "I_sc_ref            10.05          10.08            9.9          10.08  \n",
       "V_oc_ref             40.9           41.2           41.2           41.2  \n",
       "I_mp_ref             9.53           9.57           9.43           9.57  \n",
       "V_mp_ref             33.6             34           34.5             34  \n",
       "alpha_sc          0.00376         0.0038        0.00384        0.00388  \n",
       "beta_oc          -0.11397       -0.11455       -0.11513       -0.11542  \n",
       "a_ref              1.5904         1.5986         1.6069         1.6107  \n",
       "I_L_ref             9.418          9.517          9.617          9.716  \n",
       "I_o_ref          1.69e-10       1.71e-10       1.74e-10       1.75e-10  \n",
       "R_s                 0.241          0.235          0.229          0.225  \n",
       "R_sh_ref           125.87          128.9         132.03          135.1  \n",
       "Adjust              18.44          18.47           18.5          18.47  \n",
       "gamma_r             -0.42          -0.42          -0.42          -0.42  \n",
       "Version            NRELv1         NRELv1         NRELv1         NRELv1  \n",
       "PTC                 292.1          296.8          296.9          296.8  \n",
       "Technology      Mono-c-Si      Mono-c-Si      Mono-c-Si      Mono-c-Si  \n",
       "\n",
       "[21 rows x 19254 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cec_modules = pvsystem.retrieve_sam('cecmod')\n",
    "cec_modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "BIPV                   Y\n",
       "Date           4/28/2008\n",
       "T_NOCT                65\n",
       "A_c                 0.67\n",
       "N_s                   18\n",
       "I_sc_ref             7.5\n",
       "V_oc_ref            10.4\n",
       "I_mp_ref             6.6\n",
       "V_mp_ref             8.4\n",
       "alpha_sc           0.003\n",
       "beta_oc            -0.04\n",
       "a_ref              0.473\n",
       "I_L_ref            7.545\n",
       "I_o_ref         1.94e-09\n",
       "R_s                0.094\n",
       "R_sh_ref           15.72\n",
       "Adjust              10.6\n",
       "gamma_r             -0.5\n",
       "Version            MM105\n",
       "PTC                 48.9\n",
       "Technology    Multi-c-Si\n",
       "Name: Example_Module, dtype: object"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cecmodule = cec_modules.Example_Module \n",
    "cecmodule"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Sandia module database is read by the same function with the keyword `SandiaMod`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Advent_Solar_AS160___2006_</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",
       "      <th>Aleo_S16_165__2007__E__</th>\n",
       "      <th>Aleo_S16_170__2007__E__</th>\n",
       "      <th>Aleo_S16_175__2007__E__</th>\n",
       "      <th>Aleo_S16_180__2007__E__</th>\n",
       "      <th>Aleo_S16_185__2007__E__</th>\n",
       "      <th>...</th>\n",
       "      <th>Panasonic_VBHN235SA06B__2013_</th>\n",
       "      <th>Trina_TSM_240PA05__2013_</th>\n",
       "      <th>Hanwha_HSL60P6_PA_4_250T__2013_</th>\n",
       "      <th>Suniva_OPT300_72_4_100__2013_</th>\n",
       "      <th>Canadian_Solar_CS6X_300M__2013_</th>\n",
       "      <th>LG_LG290N1C_G3__2013_</th>\n",
       "      <th>Sharp_NDQ235F4__2013_</th>\n",
       "      <th>Solar_Frontier_SF_160S__2013_</th>\n",
       "      <th>SolarWorld_Sunmodule_250_Poly__2013_</th>\n",
       "      <th>Silevo_Triex_U300_Black__2014_</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Vintage</th>\n",
       "      <td>2006</td>\n",
       "      <td>2008</td>\n",
       "      <td>2009</td>\n",
       "      <td>2007 (E)</td>\n",
       "      <td>2007 (E)</td>\n",
       "      <td>2007 (E)</td>\n",
       "      <td>2007 (E)</td>\n",
       "      <td>2007 (E)</td>\n",
       "      <td>2007 (E)</td>\n",
       "      <td>2007 (E)</td>\n",
       "      <td>...</td>\n",
       "      <td>2013</td>\n",
       "      <td>2013</td>\n",
       "      <td>2013</td>\n",
       "      <td>2013</td>\n",
       "      <td>2013</td>\n",
       "      <td>2013</td>\n",
       "      <td>2013</td>\n",
       "      <td>2013</td>\n",
       "      <td>2013</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Area</th>\n",
       "      <td>1.312</td>\n",
       "      <td>1.646</td>\n",
       "      <td>1.646</td>\n",
       "      <td>1.28</td>\n",
       "      <td>1.28</td>\n",
       "      <td>1.378</td>\n",
       "      <td>1.378</td>\n",
       "      <td>1.378</td>\n",
       "      <td>1.378</td>\n",
       "      <td>1.378</td>\n",
       "      <td>...</td>\n",
       "      <td>1.26</td>\n",
       "      <td>1.63</td>\n",
       "      <td>1.65</td>\n",
       "      <td>1.93</td>\n",
       "      <td>1.91</td>\n",
       "      <td>1.64</td>\n",
       "      <td>1.56</td>\n",
       "      <td>1.22</td>\n",
       "      <td>1.68</td>\n",
       "      <td>1.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Material</th>\n",
       "      <td>mc-Si</td>\n",
       "      <td>mc-Si</td>\n",
       "      <td>mc-Si</td>\n",
       "      <td>c-Si</td>\n",
       "      <td>c-Si</td>\n",
       "      <td>mc-Si</td>\n",
       "      <td>mc-Si</td>\n",
       "      <td>mc-Si</td>\n",
       "      <td>mc-Si</td>\n",
       "      <td>mc-Si</td>\n",
       "      <td>...</td>\n",
       "      <td>a-Si / mono-Si</td>\n",
       "      <td>mc-Si</td>\n",
       "      <td>mc-Si</td>\n",
       "      <td>c-Si</td>\n",
       "      <td>c-Si</td>\n",
       "      <td>c-Si</td>\n",
       "      <td>mc-Si</td>\n",
       "      <td>CIS</td>\n",
       "      <td>mc-Si</td>\n",
       "      <td>c-Si</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cells_in_Series</th>\n",
       "      <td>72</td>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>...</td>\n",
       "      <td>72</td>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "      <td>172</td>\n",
       "      <td>60</td>\n",
       "      <td>96</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",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\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>5.564</td>\n",
       "      <td>8.34</td>\n",
       "      <td>8.49</td>\n",
       "      <td>5.1</td>\n",
       "      <td>5.2</td>\n",
       "      <td>7.9</td>\n",
       "      <td>7.95</td>\n",
       "      <td>8.1</td>\n",
       "      <td>8.15</td>\n",
       "      <td>8.2</td>\n",
       "      <td>...</td>\n",
       "      <td>5.8738</td>\n",
       "      <td>8.8449</td>\n",
       "      <td>8.5935</td>\n",
       "      <td>8.5753</td>\n",
       "      <td>8.6388</td>\n",
       "      <td>9.8525</td>\n",
       "      <td>8.6739</td>\n",
       "      <td>2.0259</td>\n",
       "      <td>8.3768</td>\n",
       "      <td>5.771</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Voco</th>\n",
       "      <td>42.832</td>\n",
       "      <td>35.31</td>\n",
       "      <td>35.92</td>\n",
       "      <td>43.5</td>\n",
       "      <td>43.6</td>\n",
       "      <td>30</td>\n",
       "      <td>30.1</td>\n",
       "      <td>30.2</td>\n",
       "      <td>30.3</td>\n",
       "      <td>30.5</td>\n",
       "      <td>...</td>\n",
       "      <td>52.0042</td>\n",
       "      <td>36.8926</td>\n",
       "      <td>36.8075</td>\n",
       "      <td>44.2921</td>\n",
       "      <td>43.5918</td>\n",
       "      <td>39.6117</td>\n",
       "      <td>36.8276</td>\n",
       "      <td>112.505</td>\n",
       "      <td>36.3806</td>\n",
       "      <td>68.5983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Impo</th>\n",
       "      <td>5.028</td>\n",
       "      <td>7.49</td>\n",
       "      <td>7.74</td>\n",
       "      <td>4.55</td>\n",
       "      <td>4.65</td>\n",
       "      <td>7.08</td>\n",
       "      <td>7.23</td>\n",
       "      <td>7.38</td>\n",
       "      <td>7.53</td>\n",
       "      <td>7.67</td>\n",
       "      <td>...</td>\n",
       "      <td>5.5383</td>\n",
       "      <td>8.2955</td>\n",
       "      <td>8.0822</td>\n",
       "      <td>7.963</td>\n",
       "      <td>8.1359</td>\n",
       "      <td>9.2473</td>\n",
       "      <td>8.1243</td>\n",
       "      <td>1.8356</td>\n",
       "      <td>7.6921</td>\n",
       "      <td>5.383</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vmpo</th>\n",
       "      <td>32.41</td>\n",
       "      <td>27.61</td>\n",
       "      <td>27.92</td>\n",
       "      <td>35.6</td>\n",
       "      <td>35.8</td>\n",
       "      <td>23.3</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.7</td>\n",
       "      <td>23.9</td>\n",
       "      <td>24.1</td>\n",
       "      <td>...</td>\n",
       "      <td>43.1204</td>\n",
       "      <td>29.066</td>\n",
       "      <td>29.2011</td>\n",
       "      <td>35.0837</td>\n",
       "      <td>34.9531</td>\n",
       "      <td>31.2921</td>\n",
       "      <td>29.1988</td>\n",
       "      <td>86.6752</td>\n",
       "      <td>28.348</td>\n",
       "      <td>55.4547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aisc</th>\n",
       "      <td>0.000537</td>\n",
       "      <td>0.00077</td>\n",
       "      <td>0.00082</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>0.0008</td>\n",
       "      <td>0.0008</td>\n",
       "      <td>0.0008</td>\n",
       "      <td>0.0008</td>\n",
       "      <td>0.0008</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0005</td>\n",
       "      <td>0.0004</td>\n",
       "      <td>0.0004</td>\n",
       "      <td>0.0006</td>\n",
       "      <td>0.0005</td>\n",
       "      <td>0.0002</td>\n",
       "      <td>0.0006</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>0.0006</td>\n",
       "      <td>0.0003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aimp</th>\n",
       "      <td>-0.000491</td>\n",
       "      <td>-0.00015</td>\n",
       "      <td>-0.00013</td>\n",
       "      <td>-0.00025</td>\n",
       "      <td>-0.00025</td>\n",
       "      <td>-0.0003</td>\n",
       "      <td>-0.0003</td>\n",
       "      <td>-0.0003</td>\n",
       "      <td>-0.0003</td>\n",
       "      <td>-0.0003</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0001</td>\n",
       "      <td>-0.0003</td>\n",
       "      <td>-0.0003</td>\n",
       "      <td>-0.0002</td>\n",
       "      <td>-0.0001</td>\n",
       "      <td>-0.0004</td>\n",
       "      <td>-0.0002</td>\n",
       "      <td>-0.0003</td>\n",
       "      <td>-0.0001</td>\n",
       "      <td>-0.0003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C0</th>\n",
       "      <td>1.0233</td>\n",
       "      <td>0.937</td>\n",
       "      <td>1.015</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0015</td>\n",
       "      <td>1.0116</td>\n",
       "      <td>1.0061</td>\n",
       "      <td>0.999</td>\n",
       "      <td>1.0121</td>\n",
       "      <td>1.0145</td>\n",
       "      <td>1.0049</td>\n",
       "      <td>1.0096</td>\n",
       "      <td>1.0158</td>\n",
       "      <td>0.995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C1</th>\n",
       "      <td>-0.0233</td>\n",
       "      <td>0.063</td>\n",
       "      <td>-0.015</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0015</td>\n",
       "      <td>-0.0116</td>\n",
       "      <td>-0.0061</td>\n",
       "      <td>0.001</td>\n",
       "      <td>-0.0121</td>\n",
       "      <td>-0.0145</td>\n",
       "      <td>-0.0049</td>\n",
       "      <td>-0.0096</td>\n",
       "      <td>-0.0158</td>\n",
       "      <td>0.005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bvoco</th>\n",
       "      <td>-0.1703</td>\n",
       "      <td>-0.133</td>\n",
       "      <td>-0.135</td>\n",
       "      <td>-0.152</td>\n",
       "      <td>-0.152</td>\n",
       "      <td>-0.11</td>\n",
       "      <td>-0.11</td>\n",
       "      <td>-0.11</td>\n",
       "      <td>-0.11</td>\n",
       "      <td>-0.11</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1411</td>\n",
       "      <td>-0.137</td>\n",
       "      <td>-0.1263</td>\n",
       "      <td>-0.155</td>\n",
       "      <td>-0.1532</td>\n",
       "      <td>-0.1205</td>\n",
       "      <td>-0.1279</td>\n",
       "      <td>-0.3044</td>\n",
       "      <td>-0.1393</td>\n",
       "      <td>-0.1913</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",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\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>-0.1731</td>\n",
       "      <td>-0.135</td>\n",
       "      <td>-0.136</td>\n",
       "      <td>-0.158</td>\n",
       "      <td>-0.158</td>\n",
       "      <td>-0.115</td>\n",
       "      <td>-0.115</td>\n",
       "      <td>-0.115</td>\n",
       "      <td>-0.115</td>\n",
       "      <td>-0.115</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1366</td>\n",
       "      <td>-0.1441</td>\n",
       "      <td>-0.1314</td>\n",
       "      <td>-0.1669</td>\n",
       "      <td>-0.1634</td>\n",
       "      <td>-0.1337</td>\n",
       "      <td>-0.1348</td>\n",
       "      <td>-0.2339</td>\n",
       "      <td>-0.1449</td>\n",
       "      <td>-0.184</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",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\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>1.174</td>\n",
       "      <td>1.495</td>\n",
       "      <td>1.373</td>\n",
       "      <td>1.25</td>\n",
       "      <td>1.25</td>\n",
       "      <td>1.35</td>\n",
       "      <td>1.35</td>\n",
       "      <td>1.35</td>\n",
       "      <td>1.35</td>\n",
       "      <td>1.35</td>\n",
       "      <td>...</td>\n",
       "      <td>1.029</td>\n",
       "      <td>1.2073</td>\n",
       "      <td>1.0686</td>\n",
       "      <td>1.0771</td>\n",
       "      <td>1.0025</td>\n",
       "      <td>1.0925</td>\n",
       "      <td>1.0695</td>\n",
       "      <td>1.2066</td>\n",
       "      <td>1.226</td>\n",
       "      <td>1.345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C2</th>\n",
       "      <td>-0.76444</td>\n",
       "      <td>0.0182</td>\n",
       "      <td>0.0036</td>\n",
       "      <td>-0.15</td>\n",
       "      <td>-0.15</td>\n",
       "      <td>-0.12</td>\n",
       "      <td>-0.12</td>\n",
       "      <td>-0.12</td>\n",
       "      <td>-0.12</td>\n",
       "      <td>-0.12</td>\n",
       "      <td>...</td>\n",
       "      <td>0.2859</td>\n",
       "      <td>-0.07993</td>\n",
       "      <td>-0.2585</td>\n",
       "      <td>-0.355</td>\n",
       "      <td>-0.171</td>\n",
       "      <td>-0.4647</td>\n",
       "      <td>-0.2718</td>\n",
       "      <td>-0.5426</td>\n",
       "      <td>-0.09677</td>\n",
       "      <td>0.3221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C3</th>\n",
       "      <td>-15.5087</td>\n",
       "      <td>-10.758</td>\n",
       "      <td>-7.2509</td>\n",
       "      <td>-8.96</td>\n",
       "      <td>-8.96</td>\n",
       "      <td>-11.08</td>\n",
       "      <td>-11.08</td>\n",
       "      <td>-11.08</td>\n",
       "      <td>-11.08</td>\n",
       "      <td>-11.08</td>\n",
       "      <td>...</td>\n",
       "      <td>-5.48455</td>\n",
       "      <td>-7.27624</td>\n",
       "      <td>-9.85905</td>\n",
       "      <td>-13.0643</td>\n",
       "      <td>-9.39745</td>\n",
       "      <td>-11.9008</td>\n",
       "      <td>-11.4033</td>\n",
       "      <td>-15.2598</td>\n",
       "      <td>-8.51148</td>\n",
       "      <td>-6.7178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A0</th>\n",
       "      <td>0.9281</td>\n",
       "      <td>0.9067</td>\n",
       "      <td>0.9323</td>\n",
       "      <td>0.938</td>\n",
       "      <td>0.938</td>\n",
       "      <td>0.924</td>\n",
       "      <td>0.924</td>\n",
       "      <td>0.924</td>\n",
       "      <td>0.924</td>\n",
       "      <td>0.924</td>\n",
       "      <td>...</td>\n",
       "      <td>0.9161</td>\n",
       "      <td>0.9645</td>\n",
       "      <td>0.9428</td>\n",
       "      <td>0.9327</td>\n",
       "      <td>0.9371</td>\n",
       "      <td>0.9731</td>\n",
       "      <td>0.9436</td>\n",
       "      <td>0.9354</td>\n",
       "      <td>0.9288</td>\n",
       "      <td>0.9191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A1</th>\n",
       "      <td>0.06615</td>\n",
       "      <td>0.09573</td>\n",
       "      <td>0.06526</td>\n",
       "      <td>0.05422</td>\n",
       "      <td>0.05422</td>\n",
       "      <td>0.06749</td>\n",
       "      <td>0.06749</td>\n",
       "      <td>0.06749</td>\n",
       "      <td>0.06749</td>\n",
       "      <td>0.06749</td>\n",
       "      <td>...</td>\n",
       "      <td>0.07968</td>\n",
       "      <td>0.02753</td>\n",
       "      <td>0.0536</td>\n",
       "      <td>0.07283</td>\n",
       "      <td>0.06262</td>\n",
       "      <td>0.02966</td>\n",
       "      <td>0.04765</td>\n",
       "      <td>0.06809</td>\n",
       "      <td>0.07201</td>\n",
       "      <td>0.09988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A2</th>\n",
       "      <td>-0.01384</td>\n",
       "      <td>-0.0266</td>\n",
       "      <td>-0.01567</td>\n",
       "      <td>-0.009903</td>\n",
       "      <td>-0.009903</td>\n",
       "      <td>-0.012549</td>\n",
       "      <td>-0.012549</td>\n",
       "      <td>-0.012549</td>\n",
       "      <td>-0.012549</td>\n",
       "      <td>-0.012549</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.01866</td>\n",
       "      <td>-0.002848</td>\n",
       "      <td>-0.01281</td>\n",
       "      <td>-0.02402</td>\n",
       "      <td>-0.01667</td>\n",
       "      <td>-0.01024</td>\n",
       "      <td>-0.007405</td>\n",
       "      <td>-0.02094</td>\n",
       "      <td>-0.02065</td>\n",
       "      <td>-0.04273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A3</th>\n",
       "      <td>0.001298</td>\n",
       "      <td>0.00343</td>\n",
       "      <td>0.00193</td>\n",
       "      <td>0.0007297</td>\n",
       "      <td>0.0007297</td>\n",
       "      <td>0.0010049</td>\n",
       "      <td>0.0010049</td>\n",
       "      <td>0.0010049</td>\n",
       "      <td>0.0010049</td>\n",
       "      <td>0.0010049</td>\n",
       "      <td>...</td>\n",
       "      <td>0.002278</td>\n",
       "      <td>-0.0001439</td>\n",
       "      <td>0.001826</td>\n",
       "      <td>0.003819</td>\n",
       "      <td>0.002168</td>\n",
       "      <td>0.001793</td>\n",
       "      <td>0.0003818</td>\n",
       "      <td>0.00293</td>\n",
       "      <td>0.002862</td>\n",
       "      <td>0.00937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A4</th>\n",
       "      <td>-4.6e-05</td>\n",
       "      <td>-0.0001794</td>\n",
       "      <td>-9.81e-05</td>\n",
       "      <td>-1.907e-05</td>\n",
       "      <td>-1.907e-05</td>\n",
       "      <td>-2.8797e-05</td>\n",
       "      <td>-2.8797e-05</td>\n",
       "      <td>-2.8797e-05</td>\n",
       "      <td>-2.8797e-05</td>\n",
       "      <td>-2.8797e-05</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0001118</td>\n",
       "      <td>2.219e-05</td>\n",
       "      <td>-0.0001048</td>\n",
       "      <td>-0.000235</td>\n",
       "      <td>-0.0001087</td>\n",
       "      <td>-0.0001286</td>\n",
       "      <td>-1.101e-05</td>\n",
       "      <td>-0.0001564</td>\n",
       "      <td>-0.0001544</td>\n",
       "      <td>-0.0007643</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",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\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",
       "      <td>-0.002438</td>\n",
       "      <td>-0.002438</td>\n",
       "      <td>-0.002438</td>\n",
       "      <td>-0.002438</td>\n",
       "      <td>-0.002438</td>\n",
       "      <td>-0.002438</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.01053</td>\n",
       "      <td>-0.00261</td>\n",
       "      <td>-0.007861</td>\n",
       "      <td>-0.006801</td>\n",
       "      <td>-0.00789</td>\n",
       "      <td>-0.0154</td>\n",
       "      <td>-0.00464</td>\n",
       "      <td>-0.0152</td>\n",
       "      <td>-0.00308</td>\n",
       "      <td>-0.006498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B2</th>\n",
       "      <td>0.0003103</td>\n",
       "      <td>0.00031</td>\n",
       "      <td>0.00031</td>\n",
       "      <td>0.0003103</td>\n",
       "      <td>0.0003103</td>\n",
       "      <td>0.0003103</td>\n",
       "      <td>0.0003103</td>\n",
       "      <td>0.0003103</td>\n",
       "      <td>0.0003103</td>\n",
       "      <td>0.0003103</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001149</td>\n",
       "      <td>0.0003279</td>\n",
       "      <td>0.0009058</td>\n",
       "      <td>0.0007968</td>\n",
       "      <td>0.0008656</td>\n",
       "      <td>0.001572</td>\n",
       "      <td>0.000559</td>\n",
       "      <td>0.001598</td>\n",
       "      <td>0.0004053</td>\n",
       "      <td>0.0006908</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",
       "      <td>-1.246e-05</td>\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",
       "      <td>-1.246e-05</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.268e-05</td>\n",
       "      <td>-1.458e-05</td>\n",
       "      <td>-3.496e-05</td>\n",
       "      <td>-3.095e-05</td>\n",
       "      <td>-3.298e-05</td>\n",
       "      <td>-5.525e-05</td>\n",
       "      <td>-2.249e-05</td>\n",
       "      <td>-5.682e-05</td>\n",
       "      <td>-1.729e-05</td>\n",
       "      <td>-2.678e-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",
       "      <td>2.11e-07</td>\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",
       "      <td>2.11e-07</td>\n",
       "      <td>...</td>\n",
       "      <td>6.517e-07</td>\n",
       "      <td>2.654e-07</td>\n",
       "      <td>5.473e-07</td>\n",
       "      <td>4.896e-07</td>\n",
       "      <td>5.178e-07</td>\n",
       "      <td>8.04e-07</td>\n",
       "      <td>3.673e-07</td>\n",
       "      <td>8.326e-07</td>\n",
       "      <td>2.997e-07</td>\n",
       "      <td>4.322e-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",
       "      <td>-1.36e-09</td>\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",
       "      <td>-1.36e-09</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.556e-09</td>\n",
       "      <td>-1.732e-09</td>\n",
       "      <td>-3.058e-09</td>\n",
       "      <td>-2.78e-09</td>\n",
       "      <td>-2.918e-09</td>\n",
       "      <td>-4.202e-09</td>\n",
       "      <td>-2.144e-09</td>\n",
       "      <td>-4.363e-09</td>\n",
       "      <td>-1.878e-09</td>\n",
       "      <td>-2.508e-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",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>2.03</td>\n",
       "      <td>3.03</td>\n",
       "      <td>2.55</td>\n",
       "      <td>2.58</td>\n",
       "      <td>3.2</td>\n",
       "      <td>3.05</td>\n",
       "      <td>3.27</td>\n",
       "      <td>3.29</td>\n",
       "      <td>3.19</td>\n",
       "      <td>3.13</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",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\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>-3.35</td>\n",
       "      <td>-3.45</td>\n",
       "      <td>-3.47</td>\n",
       "      <td>-3.56</td>\n",
       "      <td>-3.56</td>\n",
       "      <td>-3.56</td>\n",
       "      <td>-3.56</td>\n",
       "      <td>-3.56</td>\n",
       "      <td>-3.56</td>\n",
       "      <td>-3.56</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.7489</td>\n",
       "      <td>-3.5924</td>\n",
       "      <td>-3.5578</td>\n",
       "      <td>-3.7566</td>\n",
       "      <td>-3.6024</td>\n",
       "      <td>-3.4247</td>\n",
       "      <td>-3.7445</td>\n",
       "      <td>-3.6836</td>\n",
       "      <td>-3.73</td>\n",
       "      <td>-3.6866</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>-0.1161</td>\n",
       "      <td>-0.077</td>\n",
       "      <td>-0.087</td>\n",
       "      <td>-0.075</td>\n",
       "      <td>-0.075</td>\n",
       "      <td>-0.075</td>\n",
       "      <td>-0.075</td>\n",
       "      <td>-0.075</td>\n",
       "      <td>-0.075</td>\n",
       "      <td>-0.075</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1287</td>\n",
       "      <td>-0.1319</td>\n",
       "      <td>-0.1766</td>\n",
       "      <td>-0.156</td>\n",
       "      <td>-0.2106</td>\n",
       "      <td>-0.0951</td>\n",
       "      <td>-0.149</td>\n",
       "      <td>-0.1483</td>\n",
       "      <td>-0.1483</td>\n",
       "      <td>-0.104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C4</th>\n",
       "      <td>0.9974</td>\n",
       "      <td>0.972</td>\n",
       "      <td>0.989</td>\n",
       "      <td>0.995</td>\n",
       "      <td>0.995</td>\n",
       "      <td>0.995</td>\n",
       "      <td>0.995</td>\n",
       "      <td>0.995</td>\n",
       "      <td>0.995</td>\n",
       "      <td>0.995</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C5</th>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.028</td>\n",
       "      <td>0.012</td>\n",
       "      <td>0.005</td>\n",
       "      <td>0.005</td>\n",
       "      <td>0.005</td>\n",
       "      <td>0.005</td>\n",
       "      <td>0.005</td>\n",
       "      <td>0.005</td>\n",
       "      <td>0.005</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IXO</th>\n",
       "      <td>5.54</td>\n",
       "      <td>8.25</td>\n",
       "      <td>8.49</td>\n",
       "      <td>5.04</td>\n",
       "      <td>5.14</td>\n",
       "      <td>7.8</td>\n",
       "      <td>7.85</td>\n",
       "      <td>8</td>\n",
       "      <td>8.05</td>\n",
       "      <td>8.1</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IXXO</th>\n",
       "      <td>3.56</td>\n",
       "      <td>5.2</td>\n",
       "      <td>5.45</td>\n",
       "      <td>3.16</td>\n",
       "      <td>3.25</td>\n",
       "      <td>4.92</td>\n",
       "      <td>5.08</td>\n",
       "      <td>5.18</td>\n",
       "      <td>5.39</td>\n",
       "      <td>5.54</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C6</th>\n",
       "      <td>1.173</td>\n",
       "      <td>1.067</td>\n",
       "      <td>1.137</td>\n",
       "      <td>1.15</td>\n",
       "      <td>1.15</td>\n",
       "      <td>1.15</td>\n",
       "      <td>1.15</td>\n",
       "      <td>1.15</td>\n",
       "      <td>1.15</td>\n",
       "      <td>1.15</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C7</th>\n",
       "      <td>-0.173</td>\n",
       "      <td>-0.067</td>\n",
       "      <td>-0.137</td>\n",
       "      <td>-0.15</td>\n",
       "      <td>-0.15</td>\n",
       "      <td>-0.15</td>\n",
       "      <td>-0.15</td>\n",
       "      <td>-0.15</td>\n",
       "      <td>-0.15</td>\n",
       "      <td>-0.15</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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",
       "      <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",
       "      <td>Source: Sandia National Laboratories Updated 9...</td>\n",
       "      <td>Source: Sandia National Laboratories Updated 9...</td>\n",
       "      <td>...</td>\n",
       "      <td>Source:  CFV Solar Test Lab.  Tested 2013.  Mo...</td>\n",
       "      <td>Source:  CFV Solar Test Lab.  Tested 2013.  Mo...</td>\n",
       "      <td>Source:  CFV Solar Test Lab.  Tested 2013.  Mo...</td>\n",
       "      <td>Source:  CFV Solar Test Lab.  Tested 2013.  Mo...</td>\n",
       "      <td>Source:  CFV Solar Test Lab.  Tested 2013.  Mo...</td>\n",
       "      <td>Source:  CFV Solar Test Lab.  Tested 2013.  Mo...</td>\n",
       "      <td>Source:  CFV Solar Test Lab.  Tested 2013.  Mo...</td>\n",
       "      <td>Source:  CFV Solar Test Lab.  Tested 2013.  Mo...</td>\n",
       "      <td>Source:  CFV Solar Test Lab.  Tested 2013.  Mo...</td>\n",
       "      <td>Source:  CFV Solar Test Lab.  Tested 2014.  Mo...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>42 rows × 523 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         Advent_Solar_AS160___2006_  \\\n",
       "Vintage                                                        2006   \n",
       "Area                                                          1.312   \n",
       "Material                                                      mc-Si   \n",
       "Cells_in_Series                                                  72   \n",
       "Parallel_Strings                                                  1   \n",
       "Isco                                                          5.564   \n",
       "Voco                                                         42.832   \n",
       "Impo                                                          5.028   \n",
       "Vmpo                                                          32.41   \n",
       "Aisc                                                       0.000537   \n",
       "Aimp                                                      -0.000491   \n",
       "C0                                                           1.0233   \n",
       "C1                                                          -0.0233   \n",
       "Bvoco                                                       -0.1703   \n",
       "Mbvoc                                                             0   \n",
       "Bvmpo                                                       -0.1731   \n",
       "Mbvmp                                                             0   \n",
       "N                                                             1.174   \n",
       "C2                                                         -0.76444   \n",
       "C3                                                         -15.5087   \n",
       "A0                                                           0.9281   \n",
       "A1                                                          0.06615   \n",
       "A2                                                         -0.01384   \n",
       "A3                                                         0.001298   \n",
       "A4                                                         -4.6e-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                                                             -3.35   \n",
       "B                                                           -0.1161   \n",
       "C4                                                           0.9974   \n",
       "C5                                                           0.0026   \n",
       "IXO                                                            5.54   \n",
       "IXXO                                                           3.56   \n",
       "C6                                                            1.173   \n",
       "C7                                                           -0.173   \n",
       "Notes             Source: Sandia National Laboratories Updated 9...   \n",
       "\n",
       "                                   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...   \n",
       "\n",
       "                                            Aleo_S16_165__2007__E__  \\\n",
       "Vintage                                                    2007 (E)   \n",
       "Area                                                          1.378   \n",
       "Material                                                      mc-Si   \n",
       "Cells_in_Series                                                  50   \n",
       "Parallel_Strings                                                  1   \n",
       "Isco                                                            7.9   \n",
       "Voco                                                             30   \n",
       "Impo                                                           7.08   \n",
       "Vmpo                                                           23.3   \n",
       "Aisc                                                         0.0008   \n",
       "Aimp                                                        -0.0003   \n",
       "C0                                                             0.99   \n",
       "C1                                                             0.01   \n",
       "Bvoco                                                         -0.11   \n",
       "Mbvoc                                                             0   \n",
       "Bvmpo                                                        -0.115   \n",
       "Mbvmp                                                             0   \n",
       "N                                                              1.35   \n",
       "C2                                                            -0.12   \n",
       "C3                                                           -11.08   \n",
       "A0                                                            0.924   \n",
       "A1                                                          0.06749   \n",
       "A2                                                        -0.012549   \n",
       "A3                                                        0.0010049   \n",
       "A4                                                      -2.8797e-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                                                             7.8   \n",
       "IXXO                                                           4.92   \n",
       "C6                                                             1.15   \n",
       "C7                                                            -0.15   \n",
       "Notes             Source: Sandia National Laboratories Updated 9...   \n",
       "\n",
       "                                            Aleo_S16_170__2007__E__  \\\n",
       "Vintage                                                    2007 (E)   \n",
       "Area                                                          1.378   \n",
       "Material                                                      mc-Si   \n",
       "Cells_in_Series                                                  50   \n",
       "Parallel_Strings                                                  1   \n",
       "Isco                                                           7.95   \n",
       "Voco                                                           30.1   \n",
       "Impo                                                           7.23   \n",
       "Vmpo                                                           23.5   \n",
       "Aisc                                                         0.0008   \n",
       "Aimp                                                        -0.0003   \n",
       "C0                                                             0.99   \n",
       "C1                                                             0.01   \n",
       "Bvoco                                                         -0.11   \n",
       "Mbvoc                                                             0   \n",
       "Bvmpo                                                        -0.115   \n",
       "Mbvmp                                                             0   \n",
       "N                                                              1.35   \n",
       "C2                                                            -0.12   \n",
       "C3                                                           -11.08   \n",
       "A0                                                            0.924   \n",
       "A1                                                          0.06749   \n",
       "A2                                                        -0.012549   \n",
       "A3                                                        0.0010049   \n",
       "A4                                                      -2.8797e-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                                                            7.85   \n",
       "IXXO                                                           5.08   \n",
       "C6                                                             1.15   \n",
       "C7                                                            -0.15   \n",
       "Notes             Source: Sandia National Laboratories Updated 9...   \n",
       "\n",
       "                                            Aleo_S16_175__2007__E__  \\\n",
       "Vintage                                                    2007 (E)   \n",
       "Area                                                          1.378   \n",
       "Material                                                      mc-Si   \n",
       "Cells_in_Series                                                  50   \n",
       "Parallel_Strings                                                  1   \n",
       "Isco                                                            8.1   \n",
       "Voco                                                           30.2   \n",
       "Impo                                                           7.38   \n",
       "Vmpo                                                           23.7   \n",
       "Aisc                                                         0.0008   \n",
       "Aimp                                                        -0.0003   \n",
       "C0                                                             0.99   \n",
       "C1                                                             0.01   \n",
       "Bvoco                                                         -0.11   \n",
       "Mbvoc                                                             0   \n",
       "Bvmpo                                                        -0.115   \n",
       "Mbvmp                                                             0   \n",
       "N                                                              1.35   \n",
       "C2                                                            -0.12   \n",
       "C3                                                           -11.08   \n",
       "A0                                                            0.924   \n",
       "A1                                                          0.06749   \n",
       "A2                                                        -0.012549   \n",
       "A3                                                        0.0010049   \n",
       "A4                                                      -2.8797e-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                                                               8   \n",
       "IXXO                                                           5.18   \n",
       "C6                                                             1.15   \n",
       "C7                                                            -0.15   \n",
       "Notes             Source: Sandia National Laboratories Updated 9...   \n",
       "\n",
       "                                            Aleo_S16_180__2007__E__  \\\n",
       "Vintage                                                    2007 (E)   \n",
       "Area                                                          1.378   \n",
       "Material                                                      mc-Si   \n",
       "Cells_in_Series                                                  50   \n",
       "Parallel_Strings                                                  1   \n",
       "Isco                                                           8.15   \n",
       "Voco                                                           30.3   \n",
       "Impo                                                           7.53   \n",
       "Vmpo                                                           23.9   \n",
       "Aisc                                                         0.0008   \n",
       "Aimp                                                        -0.0003   \n",
       "C0                                                             0.99   \n",
       "C1                                                             0.01   \n",
       "Bvoco                                                         -0.11   \n",
       "Mbvoc                                                             0   \n",
       "Bvmpo                                                        -0.115   \n",
       "Mbvmp                                                             0   \n",
       "N                                                              1.35   \n",
       "C2                                                            -0.12   \n",
       "C3                                                           -11.08   \n",
       "A0                                                            0.924   \n",
       "A1                                                          0.06749   \n",
       "A2                                                        -0.012549   \n",
       "A3                                                        0.0010049   \n",
       "A4                                                      -2.8797e-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                                                            8.05   \n",
       "IXXO                                                           5.39   \n",
       "C6                                                             1.15   \n",
       "C7                                                            -0.15   \n",
       "Notes             Source: Sandia National Laboratories Updated 9...   \n",
       "\n",
       "                                            Aleo_S16_185__2007__E__  \\\n",
       "Vintage                                                    2007 (E)   \n",
       "Area                                                          1.378   \n",
       "Material                                                      mc-Si   \n",
       "Cells_in_Series                                                  50   \n",
       "Parallel_Strings                                                  1   \n",
       "Isco                                                            8.2   \n",
       "Voco                                                           30.5   \n",
       "Impo                                                           7.67   \n",
       "Vmpo                                                           24.1   \n",
       "Aisc                                                         0.0008   \n",
       "Aimp                                                        -0.0003   \n",
       "C0                                                             0.99   \n",
       "C1                                                             0.01   \n",
       "Bvoco                                                         -0.11   \n",
       "Mbvoc                                                             0   \n",
       "Bvmpo                                                        -0.115   \n",
       "Mbvmp                                                             0   \n",
       "N                                                              1.35   \n",
       "C2                                                            -0.12   \n",
       "C3                                                           -11.08   \n",
       "A0                                                            0.924   \n",
       "A1                                                          0.06749   \n",
       "A2                                                        -0.012549   \n",
       "A3                                                        0.0010049   \n",
       "A4                                                      -2.8797e-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                                                             8.1   \n",
       "IXXO                                                           5.54   \n",
       "C6                                                             1.15   \n",
       "C7                                                            -0.15   \n",
       "Notes             Source: Sandia National Laboratories Updated 9...   \n",
       "\n",
       "                                        ...                          \\\n",
       "Vintage                                 ...                           \n",
       "Area                                    ...                           \n",
       "Material                                ...                           \n",
       "Cells_in_Series                         ...                           \n",
       "Parallel_Strings                        ...                           \n",
       "Isco                                    ...                           \n",
       "Voco                                    ...                           \n",
       "Impo                                    ...                           \n",
       "Vmpo                                    ...                           \n",
       "Aisc                                    ...                           \n",
       "Aimp                                    ...                           \n",
       "C0                                      ...                           \n",
       "C1                                      ...                           \n",
       "Bvoco                                   ...                           \n",
       "Mbvoc                                   ...                           \n",
       "Bvmpo                                   ...                           \n",
       "Mbvmp                                   ...                           \n",
       "N                                       ...                           \n",
       "C2                                      ...                           \n",
       "C3                                      ...                           \n",
       "A0                                      ...                           \n",
       "A1                                      ...                           \n",
       "A2                                      ...                           \n",
       "A3                                      ...                           \n",
       "A4                                      ...                           \n",
       "B0                                      ...                           \n",
       "B1                                      ...                           \n",
       "B2                                      ...                           \n",
       "B3                                      ...                           \n",
       "B4                                      ...                           \n",
       "B5                                      ...                           \n",
       "DTC                                     ...                           \n",
       "FD                                      ...                           \n",
       "A                                       ...                           \n",
       "B                                       ...                           \n",
       "C4                                      ...                           \n",
       "C5                                      ...                           \n",
       "IXO                                     ...                           \n",
       "IXXO                                    ...                           \n",
       "C6                                      ...                           \n",
       "C7                                      ...                           \n",
       "Notes                                   ...                           \n",
       "\n",
       "                                      Panasonic_VBHN235SA06B__2013_  \\\n",
       "Vintage                                                        2013   \n",
       "Area                                                           1.26   \n",
       "Material                                             a-Si / mono-Si   \n",
       "Cells_in_Series                                                  72   \n",
       "Parallel_Strings                                                  1   \n",
       "Isco                                                         5.8738   \n",
       "Voco                                                        52.0042   \n",
       "Impo                                                         5.5383   \n",
       "Vmpo                                                        43.1204   \n",
       "Aisc                                                         0.0005   \n",
       "Aimp                                                        -0.0001   \n",
       "C0                                                           1.0015   \n",
       "C1                                                          -0.0015   \n",
       "Bvoco                                                       -0.1411   \n",
       "Mbvoc                                                             0   \n",
       "Bvmpo                                                       -0.1366   \n",
       "Mbvmp                                                             0   \n",
       "N                                                             1.029   \n",
       "C2                                                           0.2859   \n",
       "C3                                                         -5.48455   \n",
       "A0                                                           0.9161   \n",
       "A1                                                          0.07968   \n",
       "A2                                                         -0.01866   \n",
       "A3                                                         0.002278   \n",
       "A4                                                       -0.0001118   \n",
       "B0                                                                1   \n",
       "B1                                                         -0.01053   \n",
       "B2                                                         0.001149   \n",
       "B3                                                       -4.268e-05   \n",
       "B4                                                        6.517e-07   \n",
       "B5                                                       -3.556e-09   \n",
       "DTC                                                            2.03   \n",
       "FD                                                                1   \n",
       "A                                                           -3.7489   \n",
       "B                                                           -0.1287   \n",
       "C4                                                              NaN   \n",
       "C5                                                              NaN   \n",
       "IXO                                                             NaN   \n",
       "IXXO                                                            NaN   \n",
       "C6                                                              NaN   \n",
       "C7                                                              NaN   \n",
       "Notes             Source:  CFV Solar Test Lab.  Tested 2013.  Mo...   \n",
       "\n",
       "                                           Trina_TSM_240PA05__2013_  \\\n",
       "Vintage                                                        2013   \n",
       "Area                                                           1.63   \n",
       "Material                                                      mc-Si   \n",
       "Cells_in_Series                                                  60   \n",
       "Parallel_Strings                                                  1   \n",
       "Isco                                                         8.8449   \n",
       "Voco                                                        36.8926   \n",
       "Impo                                                         8.2955   \n",
       "Vmpo                                                         29.066   \n",
       "Aisc                                                         0.0004   \n",
       "Aimp                                                        -0.0003   \n",
       "C0                                                           1.0116   \n",
       "C1                                                          -0.0116   \n",
       "Bvoco                                                        -0.137   \n",
       "Mbvoc                                                             0   \n",
       "Bvmpo                                                       -0.1441   \n",
       "Mbvmp                                                             0   \n",
       "N                                                            1.2073   \n",
       "C2                                                         -0.07993   \n",
       "C3                                                         -7.27624   \n",
       "A0                                                           0.9645   \n",
       "A1                                                          0.02753   \n",
       "A2                                                        -0.002848   \n",
       "A3                                                       -0.0001439   \n",
       "A4                                                        2.219e-05   \n",
       "B0                                                                1   \n",
       "B1                                                         -0.00261   \n",
       "B2                                                        0.0003279   \n",
       "B3                                                       -1.458e-05   \n",
       "B4                                                        2.654e-07   \n",
       "B5                                                       -1.732e-09   \n",
       "DTC                                                            3.03   \n",
       "FD                                                                1   \n",
       "A                                                           -3.5924   \n",
       "B                                                           -0.1319   \n",
       "C4                                                              NaN   \n",
       "C5                                                              NaN   \n",
       "IXO                                                             NaN   \n",
       "IXXO                                                            NaN   \n",
       "C6                                                              NaN   \n",
       "C7                                                              NaN   \n",
       "Notes             Source:  CFV Solar Test Lab.  Tested 2013.  Mo...   \n",
       "\n",
       "                                    Hanwha_HSL60P6_PA_4_250T__2013_  \\\n",
       "Vintage                                                        2013   \n",
       "Area                                                           1.65   \n",
       "Material                                                      mc-Si   \n",
       "Cells_in_Series                                                  60   \n",
       "Parallel_Strings                                                  1   \n",
       "Isco                                                         8.5935   \n",
       "Voco                                                        36.8075   \n",
       "Impo                                                         8.0822   \n",
       "Vmpo                                                        29.2011   \n",
       "Aisc                                                         0.0004   \n",
       "Aimp                                                        -0.0003   \n",
       "C0                                                           1.0061   \n",
       "C1                                                          -0.0061   \n",
       "Bvoco                                                       -0.1263   \n",
       "Mbvoc                                                             0   \n",
       "Bvmpo                                                       -0.1314   \n",
       "Mbvmp                                                             0   \n",
       "N                                                            1.0686   \n",
       "C2                                                          -0.2585   \n",
       "C3                                                         -9.85905   \n",
       "A0                                                           0.9428   \n",
       "A1                                                           0.0536   \n",
       "A2                                                         -0.01281   \n",
       "A3                                                         0.001826   \n",
       "A4                                                       -0.0001048   \n",
       "B0                                                                1   \n",
       "B1                                                        -0.007861   \n",
       "B2                                                        0.0009058   \n",
       "B3                                                       -3.496e-05   \n",
       "B4                                                        5.473e-07   \n",
       "B5                                                       -3.058e-09   \n",
       "DTC                                                            2.55   \n",
       "FD                                                                1   \n",
       "A                                                           -3.5578   \n",
       "B                                                           -0.1766   \n",
       "C4                                                              NaN   \n",
       "C5                                                              NaN   \n",
       "IXO                                                             NaN   \n",
       "IXXO                                                            NaN   \n",
       "C6                                                              NaN   \n",
       "C7                                                              NaN   \n",
       "Notes             Source:  CFV Solar Test Lab.  Tested 2013.  Mo...   \n",
       "\n",
       "                                      Suniva_OPT300_72_4_100__2013_  \\\n",
       "Vintage                                                        2013   \n",
       "Area                                                           1.93   \n",
       "Material                                                       c-Si   \n",
       "Cells_in_Series                                                  72   \n",
       "Parallel_Strings                                                  1   \n",
       "Isco                                                         8.5753   \n",
       "Voco                                                        44.2921   \n",
       "Impo                                                          7.963   \n",
       "Vmpo                                                        35.0837   \n",
       "Aisc                                                         0.0006   \n",
       "Aimp                                                        -0.0002   \n",
       "C0                                                            0.999   \n",
       "C1                                                            0.001   \n",
       "Bvoco                                                        -0.155   \n",
       "Mbvoc                                                             0   \n",
       "Bvmpo                                                       -0.1669   \n",
       "Mbvmp                                                             0   \n",
       "N                                                            1.0771   \n",
       "C2                                                           -0.355   \n",
       "C3                                                         -13.0643   \n",
       "A0                                                           0.9327   \n",
       "A1                                                          0.07283   \n",
       "A2                                                         -0.02402   \n",
       "A3                                                         0.003819   \n",
       "A4                                                        -0.000235   \n",
       "B0                                                                1   \n",
       "B1                                                        -0.006801   \n",
       "B2                                                        0.0007968   \n",
       "B3                                                       -3.095e-05   \n",
       "B4                                                        4.896e-07   \n",
       "B5                                                        -2.78e-09   \n",
       "DTC                                                            2.58   \n",
       "FD                                                                1   \n",
       "A                                                           -3.7566   \n",
       "B                                                            -0.156   \n",
       "C4                                                              NaN   \n",
       "C5                                                              NaN   \n",
       "IXO                                                             NaN   \n",
       "IXXO                                                            NaN   \n",
       "C6                                                              NaN   \n",
       "C7                                                              NaN   \n",
       "Notes             Source:  CFV Solar Test Lab.  Tested 2013.  Mo...   \n",
       "\n",
       "                                    Canadian_Solar_CS6X_300M__2013_  \\\n",
       "Vintage                                                        2013   \n",
       "Area                                                           1.91   \n",
       "Material                                                       c-Si   \n",
       "Cells_in_Series                                                  72   \n",
       "Parallel_Strings                                                  1   \n",
       "Isco                                                         8.6388   \n",
       "Voco                                                        43.5918   \n",
       "Impo                                                         8.1359   \n",
       "Vmpo                                                        34.9531   \n",
       "Aisc                                                         0.0005   \n",
       "Aimp                                                        -0.0001   \n",
       "C0                                                           1.0121   \n",
       "C1                                                          -0.0121   \n",
       "Bvoco                                                       -0.1532   \n",
       "Mbvoc                                                             0   \n",
       "Bvmpo                                                       -0.1634   \n",
       "Mbvmp                                                             0   \n",
       "N                                                            1.0025   \n",
       "C2                                                           -0.171   \n",
       "C3                                                         -9.39745   \n",
       "A0                                                           0.9371   \n",
       "A1                                                          0.06262   \n",
       "A2                                                         -0.01667   \n",
       "A3                                                         0.002168   \n",
       "A4                                                       -0.0001087   \n",
       "B0                                                                1   \n",
       "B1                                                         -0.00789   \n",
       "B2                                                        0.0008656   \n",
       "B3                                                       -3.298e-05   \n",
       "B4                                                        5.178e-07   \n",
       "B5                                                       -2.918e-09   \n",
       "DTC                                                             3.2   \n",
       "FD                                                                1   \n",
       "A                                                           -3.6024   \n",
       "B                                                           -0.2106   \n",
       "C4                                                              NaN   \n",
       "C5                                                              NaN   \n",
       "IXO                                                             NaN   \n",
       "IXXO                                                            NaN   \n",
       "C6                                                              NaN   \n",
       "C7                                                              NaN   \n",
       "Notes             Source:  CFV Solar Test Lab.  Tested 2013.  Mo...   \n",
       "\n",
       "                                              LG_LG290N1C_G3__2013_  \\\n",
       "Vintage                                                        2013   \n",
       "Area                                                           1.64   \n",
       "Material                                                       c-Si   \n",
       "Cells_in_Series                                                  60   \n",
       "Parallel_Strings                                                  1   \n",
       "Isco                                                         9.8525   \n",
       "Voco                                                        39.6117   \n",
       "Impo                                                         9.2473   \n",
       "Vmpo                                                        31.2921   \n",
       "Aisc                                                         0.0002   \n",
       "Aimp                                                        -0.0004   \n",
       "C0                                                           1.0145   \n",
       "C1                                                          -0.0145   \n",
       "Bvoco                                                       -0.1205   \n",
       "Mbvoc                                                             0   \n",
       "Bvmpo                                                       -0.1337   \n",
       "Mbvmp                                                             0   \n",
       "N                                                            1.0925   \n",
       "C2                                                          -0.4647   \n",
       "C3                                                         -11.9008   \n",
       "A0                                                           0.9731   \n",
       "A1                                                          0.02966   \n",
       "A2                                                         -0.01024   \n",
       "A3                                                         0.001793   \n",
       "A4                                                       -0.0001286   \n",
       "B0                                                                1   \n",
       "B1                                                          -0.0154   \n",
       "B2                                                         0.001572   \n",
       "B3                                                       -5.525e-05   \n",
       "B4                                                         8.04e-07   \n",
       "B5                                                       -4.202e-09   \n",
       "DTC                                                            3.05   \n",
       "FD                                                                1   \n",
       "A                                                           -3.4247   \n",
       "B                                                           -0.0951   \n",
       "C4                                                              NaN   \n",
       "C5                                                              NaN   \n",
       "IXO                                                             NaN   \n",
       "IXXO                                                            NaN   \n",
       "C6                                                              NaN   \n",
       "C7                                                              NaN   \n",
       "Notes             Source:  CFV Solar Test Lab.  Tested 2013.  Mo...   \n",
       "\n",
       "                                              Sharp_NDQ235F4__2013_  \\\n",
       "Vintage                                                        2013   \n",
       "Area                                                           1.56   \n",
       "Material                                                      mc-Si   \n",
       "Cells_in_Series                                                  60   \n",
       "Parallel_Strings                                                  1   \n",
       "Isco                                                         8.6739   \n",
       "Voco                                                        36.8276   \n",
       "Impo                                                         8.1243   \n",
       "Vmpo                                                        29.1988   \n",
       "Aisc                                                         0.0006   \n",
       "Aimp                                                        -0.0002   \n",
       "C0                                                           1.0049   \n",
       "C1                                                          -0.0049   \n",
       "Bvoco                                                       -0.1279   \n",
       "Mbvoc                                                             0   \n",
       "Bvmpo                                                       -0.1348   \n",
       "Mbvmp                                                             0   \n",
       "N                                                            1.0695   \n",
       "C2                                                          -0.2718   \n",
       "C3                                                         -11.4033   \n",
       "A0                                                           0.9436   \n",
       "A1                                                          0.04765   \n",
       "A2                                                        -0.007405   \n",
       "A3                                                        0.0003818   \n",
       "A4                                                       -1.101e-05   \n",
       "B0                                                                1   \n",
       "B1                                                         -0.00464   \n",
       "B2                                                         0.000559   \n",
       "B3                                                       -2.249e-05   \n",
       "B4                                                        3.673e-07   \n",
       "B5                                                       -2.144e-09   \n",
       "DTC                                                            3.27   \n",
       "FD                                                                1   \n",
       "A                                                           -3.7445   \n",
       "B                                                            -0.149   \n",
       "C4                                                              NaN   \n",
       "C5                                                              NaN   \n",
       "IXO                                                             NaN   \n",
       "IXXO                                                            NaN   \n",
       "C6                                                              NaN   \n",
       "C7                                                              NaN   \n",
       "Notes             Source:  CFV Solar Test Lab.  Tested 2013.  Mo...   \n",
       "\n",
       "                                      Solar_Frontier_SF_160S__2013_  \\\n",
       "Vintage                                                        2013   \n",
       "Area                                                           1.22   \n",
       "Material                                                        CIS   \n",
       "Cells_in_Series                                                 172   \n",
       "Parallel_Strings                                                  1   \n",
       "Isco                                                         2.0259   \n",
       "Voco                                                        112.505   \n",
       "Impo                                                         1.8356   \n",
       "Vmpo                                                        86.6752   \n",
       "Aisc                                                         0.0001   \n",
       "Aimp                                                        -0.0003   \n",
       "C0                                                           1.0096   \n",
       "C1                                                          -0.0096   \n",
       "Bvoco                                                       -0.3044   \n",
       "Mbvoc                                                             0   \n",
       "Bvmpo                                                       -0.2339   \n",
       "Mbvmp                                                             0   \n",
       "N                                                            1.2066   \n",
       "C2                                                          -0.5426   \n",
       "C3                                                         -15.2598   \n",
       "A0                                                           0.9354   \n",
       "A1                                                          0.06809   \n",
       "A2                                                         -0.02094   \n",
       "A3                                                          0.00293   \n",
       "A4                                                       -0.0001564   \n",
       "B0                                                                1   \n",
       "B1                                                          -0.0152   \n",
       "B2                                                         0.001598   \n",
       "B3                                                       -5.682e-05   \n",
       "B4                                                        8.326e-07   \n",
       "B5                                                       -4.363e-09   \n",
       "DTC                                                            3.29   \n",
       "FD                                                                1   \n",
       "A                                                           -3.6836   \n",
       "B                                                           -0.1483   \n",
       "C4                                                              NaN   \n",
       "C5                                                              NaN   \n",
       "IXO                                                             NaN   \n",
       "IXXO                                                            NaN   \n",
       "C6                                                              NaN   \n",
       "C7                                                              NaN   \n",
       "Notes             Source:  CFV Solar Test Lab.  Tested 2013.  Mo...   \n",
       "\n",
       "                               SolarWorld_Sunmodule_250_Poly__2013_  \\\n",
       "Vintage                                                        2013   \n",
       "Area                                                           1.68   \n",
       "Material                                                      mc-Si   \n",
       "Cells_in_Series                                                  60   \n",
       "Parallel_Strings                                                  1   \n",
       "Isco                                                         8.3768   \n",
       "Voco                                                        36.3806   \n",
       "Impo                                                         7.6921   \n",
       "Vmpo                                                         28.348   \n",
       "Aisc                                                         0.0006   \n",
       "Aimp                                                        -0.0001   \n",
       "C0                                                           1.0158   \n",
       "C1                                                          -0.0158   \n",
       "Bvoco                                                       -0.1393   \n",
       "Mbvoc                                                             0   \n",
       "Bvmpo                                                       -0.1449   \n",
       "Mbvmp                                                             0   \n",
       "N                                                             1.226   \n",
       "C2                                                         -0.09677   \n",
       "C3                                                         -8.51148   \n",
       "A0                                                           0.9288   \n",
       "A1                                                          0.07201   \n",
       "A2                                                         -0.02065   \n",
       "A3                                                         0.002862   \n",
       "A4                                                       -0.0001544   \n",
       "B0                                                                1   \n",
       "B1                                                         -0.00308   \n",
       "B2                                                        0.0004053   \n",
       "B3                                                       -1.729e-05   \n",
       "B4                                                        2.997e-07   \n",
       "B5                                                       -1.878e-09   \n",
       "DTC                                                            3.19   \n",
       "FD                                                                1   \n",
       "A                                                             -3.73   \n",
       "B                                                           -0.1483   \n",
       "C4                                                              NaN   \n",
       "C5                                                              NaN   \n",
       "IXO                                                             NaN   \n",
       "IXXO                                                            NaN   \n",
       "C6                                                              NaN   \n",
       "C7                                                              NaN   \n",
       "Notes             Source:  CFV Solar Test Lab.  Tested 2013.  Mo...   \n",
       "\n",
       "                                     Silevo_Triex_U300_Black__2014_  \n",
       "Vintage                                                        2014  \n",
       "Area                                                           1.68  \n",
       "Material                                                       c-Si  \n",
       "Cells_in_Series                                                  96  \n",
       "Parallel_Strings                                                  1  \n",
       "Isco                                                          5.771  \n",
       "Voco                                                        68.5983  \n",
       "Impo                                                          5.383  \n",
       "Vmpo                                                        55.4547  \n",
       "Aisc                                                         0.0003  \n",
       "Aimp                                                        -0.0003  \n",
       "C0                                                            0.995  \n",
       "C1                                                            0.005  \n",
       "Bvoco                                                       -0.1913  \n",
       "Mbvoc                                                             0  \n",
       "Bvmpo                                                        -0.184  \n",
       "Mbvmp                                                             0  \n",
       "N                                                             1.345  \n",
       "C2                                                           0.3221  \n",
       "C3                                                          -6.7178  \n",
       "A0                                                           0.9191  \n",
       "A1                                                          0.09988  \n",
       "A2                                                         -0.04273  \n",
       "A3                                                          0.00937  \n",
       "A4                                                       -0.0007643  \n",
       "B0                                                                1  \n",
       "B1                                                        -0.006498  \n",
       "B2                                                        0.0006908  \n",
       "B3                                                       -2.678e-05  \n",
       "B4                                                        4.322e-07  \n",
       "B5                                                       -2.508e-09  \n",
       "DTC                                                            3.13  \n",
       "FD                                                                1  \n",
       "A                                                           -3.6866  \n",
       "B                                                            -0.104  \n",
       "C4                                                              NaN  \n",
       "C5                                                              NaN  \n",
       "IXO                                                             NaN  \n",
       "IXXO                                                            NaN  \n",
       "C6                                                              NaN  \n",
       "C7                                                              NaN  \n",
       "Notes             Source:  CFV Solar Test Lab.  Tested 2014.  Mo...  \n",
       "\n",
       "[42 rows x 523 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sandia_modules = pvsystem.retrieve_sam(name='SandiaMod')\n",
    "sandia_modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Vintage                                                          2009\n",
       "Area                                                            1.701\n",
       "Material                                                         c-Si\n",
       "Cells_in_Series                                                    96\n",
       "Parallel_Strings                                                    1\n",
       "Isco                                                          5.09115\n",
       "Voco                                                          59.2608\n",
       "Impo                                                          4.54629\n",
       "Vmpo                                                          48.3156\n",
       "Aisc                                                         0.000397\n",
       "Aimp                                                         0.000181\n",
       "C0                                                            1.01284\n",
       "C1                                                         -0.0128398\n",
       "Bvoco                                                        -0.21696\n",
       "Mbvoc                                                               0\n",
       "Bvmpo                                                       -0.235488\n",
       "Mbvmp                                                               0\n",
       "N                                                              1.4032\n",
       "C2                                                           0.279317\n",
       "C3                                                           -7.24463\n",
       "A0                                                           0.928385\n",
       "A1                                                           0.068093\n",
       "A2                                                         -0.0157738\n",
       "A3                                                          0.0016606\n",
       "A4                                                          -6.93e-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                                                            -3.40641\n",
       "B                                                          -0.0842075\n",
       "C4                                                           0.996446\n",
       "C5                                                           0.003554\n",
       "IXO                                                           4.97599\n",
       "IXXO                                                          3.18803\n",
       "C6                                                            1.15535\n",
       "C7                                                          -0.155353\n",
       "Notes               Source: Sandia National Laboratories Updated 9...\n",
       "Name: Canadian_Solar_CS5P_220M___2009_, dtype: object"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sandia_module = sandia_modules.Canadian_Solar_CS5P_220M___2009_\n",
    "sandia_module"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Generate some irradiance data for modeling."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pvlib import clearsky\n",
    "from pvlib import irradiance\n",
    "from pvlib import atmosphere\n",
    "from pvlib.location import Location\n",
    "\n",
    "tus = Location(32.2, -111, 'US/Arizona', 700, 'Tucson')\n",
    "\n",
    "times_loc = pd.date_range(start=datetime.datetime(2014,4,1), end=datetime.datetime(2014,4,2), freq='30s', tz=tus.tz)\n",
    "solpos = pvlib.solarposition.get_solarposition(times_loc, tus.latitude, tus.longitude)\n",
    "dni_extra = pvlib.irradiance.extraradiation(times_loc)\n",
    "airmass = pvlib.atmosphere.relativeairmass(solpos['apparent_zenith'])\n",
    "pressure = pvlib.atmosphere.alt2pres(tus.altitude)\n",
    "am_abs = pvlib.atmosphere.absoluteairmass(airmass, pressure)\n",
    "cs = tus.get_clearsky(times_loc)\n",
    "\n",
    "surface_tilt = tus.latitude\n",
    "surface_azimuth = 180  # pointing south\n",
    "\n",
    "aoi = pvlib.irradiance.aoi(surface_tilt, surface_azimuth,\n",
    "                           solpos['apparent_zenith'], solpos['azimuth'])\n",
    "total_irrad = pvlib.irradiance.total_irrad(surface_tilt,\n",
    "                                           surface_azimuth,\n",
    "                                           solpos['apparent_zenith'],\n",
    "                                           solpos['azimuth'],\n",
    "                                           cs['dni'], cs['ghi'], cs['dhi'],\n",
    "                                           dni_extra=dni_extra,\n",
    "                                           model='haydavies')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can run the module parameters and the irradiance data through the SAPM functions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\cliff\\Anaconda3\\lib\\site-packages\\pvlib\\pvsystem.py:1479: RuntimeWarning: invalid value encountered in maximum\n",
      "  spectral_loss = np.maximum(0, np.polyval(am_coeff, airmass_absolute))\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1ef526a50f0>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1ef52800a90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "module = sandia_module\n",
    "\n",
    "# a sunny, calm, and hot day in the desert\n",
    "temps = pvsystem.sapm_celltemp(total_irrad['poa_global'], 0, 30)\n",
    "\n",
    "effective_irradiance = pvlib.pvsystem.sapm_effective_irradiance(\n",
    "    total_irrad['poa_direct'], total_irrad['poa_diffuse'],\n",
    "    am_abs, aoi, module)\n",
    "\n",
    "sapm_1 = pvlib.pvsystem.sapm(effective_irradiance, temps['temp_cell'], module)\n",
    "\n",
    "sapm_1.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_sapm(sapm_data, effective_irradiance):\n",
    "    \"\"\"\n",
    "    Makes a nice figure with the SAPM data.\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    sapm_data : DataFrame\n",
    "        The output of ``pvsystem.sapm``\n",
    "    \"\"\"\n",
    "    fig, axes = plt.subplots(2, 3, figsize=(16,10), sharex=False, sharey=False, squeeze=False)\n",
    "    plt.subplots_adjust(wspace=.2, hspace=.3)\n",
    "\n",
    "    ax = axes[0,0]\n",
    "    sapm_data.filter(like='i_').plot(ax=ax)\n",
    "    ax.set_ylabel('Current (A)')\n",
    "\n",
    "    ax = axes[0,1]\n",
    "    sapm_data.filter(like='v_').plot(ax=ax)\n",
    "    ax.set_ylabel('Voltage (V)')\n",
    "\n",
    "    ax = axes[0,2]\n",
    "    sapm_data.filter(like='p_').plot(ax=ax)\n",
    "    ax.set_ylabel('Power (W)')\n",
    "\n",
    "    ax = axes[1,0]\n",
    "    [ax.plot(effective_irradiance, current, label=name) for name, current in\n",
    "     sapm_data.filter(like='i_').iteritems()]\n",
    "    ax.set_ylabel('Current (A)')\n",
    "    ax.set_xlabel('Effective Irradiance')\n",
    "    ax.legend(loc=2)\n",
    "\n",
    "    ax = axes[1,1]\n",
    "    [ax.plot(effective_irradiance, voltage, label=name) for name, voltage in\n",
    "     sapm_data.filter(like='v_').iteritems()]\n",
    "    ax.set_ylabel('Voltage (V)')\n",
    "    ax.set_xlabel('Effective Irradiance')\n",
    "    ax.legend(loc=4)\n",
    "\n",
    "    ax = axes[1,2]\n",
    "    ax.plot(effective_irradiance, sapm_data['p_mp'], label='p_mp')\n",
    "    ax.set_ylabel('Power (W)')\n",
    "    ax.set_xlabel('Effective Irradiance')\n",
    "    ax.legend(loc=2)\n",
    "\n",
    "    # needed to show the time ticks\n",
    "    for ax in axes.flatten():\n",
    "        for tk in ax.get_xticklabels():\n",
    "            tk.set_visible(True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1ef55853cc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_sapm(sapm_1, effective_irradiance)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For comparison, here's the SAPM for a sunny, windy, cold version of the same day."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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rgN+/UUiQ1cx9183capXTiaIofP6ybBraetm4v5FF82NYlhNvdFgnrbGxkR/96PtHbS8oWMqdd95jQERCBLY/rD1Ai2uAK86ax4K0GL+/v8Vs4t5rFvC9327hxQ/KWJgeI0WdJuCTnRF33HE3d9xx92m910svve6PkI4gCawISC+vK6Onf4ibz5+P/soLDJSW4Fi2nIQ7v4hyGmPwFYuFhDvuwmS10fnRh5j/+BtuPO8mnn2nlBfeKeb/fFqq3vrTY4/9zOgQhAB81S5feKeYAbeHOy7LJmkC862Ef1ktJr54VR6P/GErz7+tkZsaPW0eLiQkJIwNlRNCHF9xjYu3N1eR5Azl6nPSJq2dyLAgbrkwi9+sPcizbxbxHzfnT1pbwlhSxEkEnNIaFx/vbSDZGUpB4y56dmwnJEsl/o67Tit5HaWYTMTd9llC8wvoKzxAdvEG1JRIdpe2cqCy3Y9nIIQIFDuLW9ld2kr23EjOWTTH6HDEJyRE27l2VTq9A8P846Nyo8MRQviZx+vlj29rKAp87tJsLObJTT1W5MWzaH4MhVUd7CxumdS2hHEkgRUBRdd1fvPqPnTgM1kWOl5/FUt0DIlf/iom68SfzCsmE3Pu/hK2hDm4/v0ONyT71qh68YNSvN4TL/4shJg+PF4vL60rw2xSuP0SVYp6BKgLliYzJ8bOh7vrqGnuMTocIYQfrd/bQH1rLxcvn0dGUsSkt6coCjdfkInZpPD3D0oZGvZMepti6kkCKwLKgcp2Dla0szQ1gqB//QWAhLu+iDkszG9tmIKCmHPPvSgWC/o//8I5GRFUN/Xw0e46v7UhhDDexn2NNLX3sWrRHL8WDBH+ZTGbuOn8THQdXttQYXQ4Qgg/GRzy8OqGCmxWE7dcMnWFfhKi7Zy/JJkW1wBr5ZoyI0kCKwKGruu8tqESgEvdRQy3thJ1yWXYs1S/txWUMpeYq6/F093F+a7dmE0Kf31Hk15YP9i8eSOvvvqK0WGIWW7Y4+W1jyuwmE1cefbkzbkS/rEwPZr0xHB2FLdIL6wQM8S/t9fQ2ePm4jNTprxY5pVnpxISZOHlD0oYdEsv7EwjCawIGIVVHZTWdXLeXCuej9/HEh1DzJVXT1p7URddgi0xCffm9Vyc6KGupUfmS/jBihUr/bJItRATsbO4hbauQVYvTiTK4b+158TkUBSFq85OBeD1jZWGxiKEmLhBt4e3tlQTGmzh0mXzprz9sBArFy5NprPHzToZYTfjSBViETDWjty0rGrcitvjIe4zt2Dy46LHn6RYLMTf/jlqfvIYSyo38pblbN7YXMVS1Slz5SbgjTdep6qqctzFr3/3u1/R2tpIU1Mr3d2dXHvtDXz44fvU1FTx8MM/JCYmhu9979vExMTQ0tLM8uUrueee+ww4CzHdvbutBgW48ExZC3C6WJgew9z4MHZozbS6+okNsCUwHnrom9xww80UFCylsPAAzz33u3GXBvvKV75IRkYWtbWVWCw2Fi0qYOvWTfT09PDEE0+zYcM61q9fR19fLy6XizvuuIs1ay4w4IyEmDwf7a2nd2CYq85OxR5sTLpx0Zkp/HtHDW9uqWZNQRI26+kXAhWBJSASWFVVdwGji0ZWaJomK33PMtVN3RRVuzgnsg/39n2EZOcQmr9k0tsNycwiNL+A3t27uOKsAtY2KhRWdZCbGj3pbU+2V0rXsqt53zH3m00KnlMcMl0Qt5DrMj41obiCg4N54omneP75Z9m06WN++tMn+de/XuO9997hxhs/Q2NjPU888RShoWF8+ct3oWlFqOrUL5Itpq+yuk7K6rvIz4glPspudDjiJCmKwkVnpPC7fxXy/s46bjw/45jHnuj6driTvdad6Pp25ZXX8OabaykoWMobb6zlyiuvPeaxubl5PProD7n99s8THBzMf//3L/nRj37A7t07Aejv7+PJJ3+By9XB3Xd/jnPOWY3FEhC3ZEJM2LDHyztbq7FZTFyw1LiHiGEhVi5fmcbLH5Ty8f5GzitIMiwW4V+GDyFWVTUYQNO0NSM/krzOQu/tqAVd56wm35d77DXXTVkvaOy1nwZFYXHlZhTd64tFTJrc3FwAHI4wUlPTRn4Px+32VYSePz+L8PAIzGYzubkLqK6uNCpUMU29u70GgIvOkN7X6WZZTjzhoTY+2lMfcPPWli8/i8LCA3R1dbJ37y5WrFh5zGOzsnwP3Y51ncvPX4LJZCI6OgaHIxyXyzX5JyDEFNlW2Exb1yCrFiXisNsMjeXqc+djNin8e3sNui51TmaKQHjctxiwq6r6Dr54HtI0bbPBMYkp1NM/xOaDTSwyt2OuKSdq6RJCMjKnrP2gpCTCz1pJ18aPOTu7lY9LTbR1DhATMbUFB/ztuoxPHbc3wel00NLSPYUR+ZzowURVVQUDAwNYrVYOHtzP5ZdfOUWRiZmgvWuA7UUtJDtDyZ4XZXQ44hRZLSbW5Cfy2seVbNzfwHlLxn8IcaLr2+H8da0zmUycd96F/Pznj7Nq1RrMx1mX/ETXOU0rAqC9vY3e3l6iouTfqpg53t1eg6LAxctSjA6FqPBgzsyJY/OBJg5WdZA3A0bYicBIYPuAnwO/BTKBN1VVVTVNGx7v4KgoOxaL70vD6XRMWZCHk3b9a937JQwNe7lwqBiAlM/chGOKzzX01hvZtWkjK7sOsiHEybaSVm6/LGfK2p9Jn63DEYzdbhv3vUNDg8baDQsLZmAgCKfTQURECMHBVqKjQwkKsvGf//kwra2tXHrppaxcudTvMYqZ6/2ddXh1nYvOSJG57NPUeQVJ/GtTFf/eUcuagqSA+hyvuOIqbrzxav76139M6H3a29u4//576enp4Rvf+NZxk2EhppOKhi4qG7vJz4jFGSDz2C9cmsLmA028t71WEtgZIhAS2GKgVNM0HShWVbUNmAPUjHdwR0cfYFzvkbTrX15d542Py0kc7sRWVUKImo0jM+Ok2vTqXgrbi9nbepDSjnLaBzrQgajgCNIjUlkcm0deTDZm00ncGARFEL3sTNq3bCUzrZW3NgVxYUEiFvPkj7KfaZ/tqlUXsWoV4773zTd/fqzdCy/09Z60tHSzePFyFi9eTkNDPRERUTz66H+NveZkYzTqIYAIHINDHtbtriMsxMqKvHijwxGnKSIsaKzHRKt2BVRPenx8AuvWbTnuMU8//eux33/4wx+P/X7//d8AfIXu8vOXjFvoTojp7sNdvoq/5y0JnPmm6YnhpCeGs6e0lWZXP3EBkliL0xcICewXgIXAl1VVTQTCgQZjQxJTpaTGRYtrgM97ygDf0jYnMuwdZkP9Ft6r/oj2gQ4Ags1BxNt91YNb+tvY3LCdzQ3bcdjCuHDuas5NWonNbD3u+yZffy3tW7Zy4WAx/9vrZHdJK2dkx038JGehhx76Jl1dnUdsCwsLG7dipxD+svVgE70Dw3xqZSpWi/RoTWdr8pPYfKCJdXvqAyqBHdXY2MiPfvT9o7YXFCzlzjvvMSAiIYzXNzDElsImYiOCyUsLrJ7O8wqSKK/vYsPeBq47N93ocMQEBUIC+zvgWVVVNwA68IVjDR8WM8+GfQ2EDvcRX1eINSGB0EWLj3t8qauCPxW+SHN/KzazjbMTl7M8YSmp4SljPa1e3UtNdx1bGneypWEH/yj9Fx/WfMytOZ8mJzrrmO/tULMIzsiE0hIi5y1i4/5GSWBP02OP/ey0XjdnTiK//vWz/g1GzBof7a1HAVYvTjQ6FDFBmckRzImxs0Nrprsv0/BCMJ+UkJBwRE/rqZB5/WKm2nSgCfeQl9X5iZgCaOg/wBnZcfzp3WI+3tfANeekYTIFVnzi1BiewGqa5gZuMToOMfUG3MNsL2phlbsSxesh6sKLUUzjD9nVdZ23Kt/jXxXvAnBu0kouT7sQhy3sqGNNiol54SnMC0/hirSLeLfqQ96r+Yind/+WC+aeyzXzL8ekjN9O5JrzaCwtYfVwJWvLw+nqdRMeGlg3TkKIozW09VJW18WC9OhpX4BN+IogrV6cyF/fL2Xj/kYuWTbX6JCEECewfm89ZpPCqkWB9xAxyGpmWU48H+2p52BVOwvSYowOSUyA4cvoiNlrW1Ezg+5hFnWWoAQFEb7irHGP83g9vFD0Imsr3iEqOJIHltzLTeo14yavnxRqtXNNxuV884yvEG938l71R/x23/MMecfv5A9beibmMAdZbRoMD7OlsGlC5yiEmBp7y9oAWJYtc19nipUL52A2KWyV67AQAa+upYfqph4WpscE7IP/VYvmALBhr8xUnO4kgRWG2bivkbS+emy9nTiWLccUfPSkeq/u5fnCF9ncsJ25jmQePOOrzI9MPeW25jqS+Y+l95EVlcGe1gP8fv+f8HiPXmPQZLUSfs4qzAN95PRWsXFf4+mcmhBiihVV+ebDB9q8K3H6wkKspCWGU9XYQ/+gzCwSIpBtOuB70BTIBfTSE8OZE2NnZ3ELPf1DRocjJkASWGGIju5BimtcnD1cBUDEqjXjHvfPsjfY1rSTtPC53F9wz0n1uh6L3Wrny4vuQI3KYG/rAf6ivTLuotYRq9eAorBysJyqpm7qWnpOu00hxNSob+sl3G4lyhFkdCjCj+YnhuPVdepae40OZVZTVdWqqurzqqquV1V1q6qqV6mqmqGq6oaRbf+rqqpp5NgfjByzUVXVZUbHLiafV9fZfLCRkCAz+RmxRodzTIqicM7COQx7dHZozUaHIyZAElhhiB1aMyHD/SS1VWBLSiY4Le2oY7Y37uK96o+It8fxpcV3EGyZ+I2p1WzlnkWfZ64jiU0N21hft+moY2zOOELUbKJd9UQMdbOtSC5y4tSpqrpLVdUPR37+oKrqClVVt6iq+rGqqj8wOr6ZZGjYQ2vnAAnRdqNDEX4WP/KZNrX3GRzJrHcb0KZp2irgMuBp4AnguyPbFOBqVVWXAKuB5cDNwC8MildMoeJqF+1dgyxV47BZA7sC/Jk5vuKcWwvl3m46kwRWGGJrUTMLuitQvB4iVq0+aqH6pt5m/qy9TJDZxj2LPkeYNdRvbQeZbdy98LOEWUN5seQ1qrtrjzom/KyVACzqrZAE9hRt3ryRV199xegwDKWqajCApmlrRn7uAJ7BV7DuHGD5yI2e8IP2rkF0HZxRsrbfTDO6XmOLq9/gSGa9F4HvHfbnYWApsG7kz28CF+K7vr2jaZquaVo1YFFV1TmlkYopt+mAb7rVWXkJBkdyYrERIcxPCqeouoPOnkGjwxGnSRJYMeXauwYore2kwF0NZjPhy1ccsd/r9fJc4d8Y9Li5Rb2eeLv/v/uig6P4fN5n8Ope/njwb0cVdXIsPQPFZiO/r5KG1l4ZRnwKVqxYydVXX2d0GEZbDNhVVX1HVdX3VVU9FwjSNK1M0zQdeBu4wNgQZ46eAd9cJkdIYBYOEacvfGT5HJmvZixN03o0TetWVdUBvAR8F1BGrmcA3UAEEA4cvgj46HYxQw17vOwsbiHKEYQ6N9LocE7Kspx4dB22ay1GhyJOk+HL6IjZZ7vWQpS7i6juZkIXLsLscByx/63SD6nqquGM+HzOSCiYtDhyorNYlXQW6+s28WbFv7kz/oaxfabgEMIKlqBv2UziYCvbippJcp7+/FsjtLz4V7q3bzvm/iqzCY/He0rv6TjjTJw33HzcY95443Wqqiq5996vHrXvF7/4H8LD7dx665088MB93HTTraxcec4pxTBN9AE/B34LZOLrnXAdtr8bOO5K6lFRdiwW31Asp9NxvEMnzXRpt7rNN7zUGRM6oZidTgfDnmGGvcPo+EZrmI6xtJc/GfH3PFlt6rrOsHcYt2eIIEsQFtORwwlPtV1zkBUAt0ef8GdrBKPanQyqqqYA/wB+qWnan1VV/elhux34rnFdI79/cvsxybVuere7U2umd2CY885IIT4ufMraPRWfbPfSs9P563sl7Cxp5eZLc6akzakyW9qVBFZMuW2FTeT1VADgWHZk72vHgIu/7HsNuyWET2deNemxXDP/cg60FfFe9Touz1uNhUNDEMPPWkn3ls0s6ilnu5bKNauOm2+Ik3DPPfdx//33UFlZTU5O3kxNXgGKgdKR3oliVVU7gcPL457wpq6jYyQpczpoaenkRwOBAAAgAElEQVSerDiPaTq1W9/Y5fvF6z3l1zb2NrOjaTdVfdVUd9TTPXRotIWCQqjVTrjNQZzdSYLdSZzdSbIjkQR7HGbTxOd6GfH3PNE2dV2n091FbXc9tT31NPa20D7QTttAB13ubrz6oQdjQWYb8fY4UsNTWJO5DKcy55jrcI9neOQhW5ur/7Rjnk7/lk/2faeaqqrxwDvAVzRNe29k8y5VVddomvYhvnmxHwClwE9VVf05kAyYNE1rPd57y7Vuerf73hZfMc68uZHHfd9AO181JZLCyna0shaiw/27dnignet0bfd41zpJYMWU6ugepKyuk8sGqlBsNsIKjuxhfbXsTQaHB7k1+4YJVRw+WcGWIK7NuILf7X+B53a/xJ3Zt4/ts+fkYQ4PJ7e3irdbuqlr7SUp1n9zcSeb84abj9tbasSFzmKx8LnPfY4HH3yQl19eO6VtT7EvAAuBL6uqmgjYgV5VVecD5cAlwA8NjG9G6R3wTQEIDT75r7Sm3mZeLl3LgbYiwJesxgRHkRCajs1sQwH6hwfpGeqhbaCd+t4jl9SymqwkhyUyNzyJuY5k5jqSSQiNO6XkbDrQdR3XYCeVXTVUd9dS011HbfeRiT74/v4igyKY50ghyGzDarYw6Bmix91DfU8D1d21fFS3iQR7HFfPv4xFzryTat9iNmE2KQwOHb3smZhSDwFRwPdUVR2dC3s/8P9UVbUBhcBLmqZ5VFVdD2zCN03tPkOiFVPC69XZVdJCuN1KZvL0GD48allOPEXVLrYXNXPxsrlGhyNOkSSwYkrtKW0lfrCdsD4XoWcsO2Lt15ruOrY17SI1MpkVc5ZOWUwFzoVkRqazs34fZzk1cmNUABSzmbClZ+D54H3m9jexU2smKfboasni5HV1dfHMM8/w1a8+wE9+8ig//emTRoc0WX4HPKuq6gZAx5fQeoE/AWZ8RU62GBjfjDLg9iWwwbaT+0rb0rCDP2svM+wdJiMyjVVJZ7Eqawn9neMPqR/tcWzua6Gxt5ma7nqqu2up6q6hoqtq7DibyUqKI4m54cljSW2cPXZaJbW9Q31UddX4frprqOyqodt9ZLIaHRzF4og8khyJpIQlkhiWQFRQ5DF7pIe9w5R3VrG7Yw/rq7byq33PsXLOMm5Sr8FiOvFnFmQ1SwJrME3T7seXsH7S6nGOfQR4ZJJDEgGguMZFd98Qq/MTMZmUE78ggBRkxvL82xq7SlolgZ2GJIEVU2p3aSu5I8OHP1m86Z+lbwBw6+Jrp/SGT1EUrs+8ise3/Tdry98hJzprrCqyY+mZdH7wPtm9VewuVbnybElgJ+Lxx/+Tu+66i5Urz6eoqJAXX/wrN5xgTu10pGmaG1/F4U9aMc42MUEej6+OjMV84huo92vW83LJ64RYgvl87mfIdy5AURTCbKH0M/6IBEXx9S5GBkWQFZUxtn3IM0RdbwPVXbVUddVS3V1LeWcVZZ2VY8cEm4N8Sa0jmbnhyaQ4kogNjvbL8OOJ0HWd9gEX9b0N1Pc0UtfTQFV3La39bUccFxUUSb5zAfPCU5jr8MUfaj215YosJgtZUfM5OyufVfFn89yBv7CxYSvdQ93cueB2rCdIYoNsZgbdksAKEWh2jBRBWjoNC01HhAWRnhhOca2Lnv4hwkKsRockToEksGLKDLiHOVjRzpf6azAFB2NfsHBsX0lHGUUdJWRHZbI4IXfKh7amOBJZkbyEzbU7OdBWxIJY36T+kCwVs8NBTl8N79S76OwZJCJs4uvRzmSXX37lMfc99tjPxoYuP/zwI1MXlJjRhr2+BNZ8gh6Anc17ebnkdSJsDu5f8qUJVzi3mq2khs8lNfzQ03u3x01tT/1YQlvdVUupq4ISV/nYMRbFjNMeS4I9jjRnMg4iiA2JJjIogghbuN+SW13X6R/up6W/jdb+dlr722jtb6NtbzvVrjr6hweOOD7UYicnOovU8JSRhDWFiCD/zrecExrP15fex6/2Psu+1kJeLH6VW7KvP+5rbBYTA5LAChFQvLrOjuJmQoMtZM+NMjqc05KfGUtZfRd7Sls5e+Eco8MRp0ASWDFlDlR0EN3fRthgN6HLlmOyHnra9XbVBwB8Kv1io8Lj03mXs6V2F2sr3iEvJhtFUVBMJsKWLMWz7kNS+pvZU9bGuYsTDYtxunjooW/S1dV5xLawsDAef/wJgyISM5nH6xv6azYfe+RGx4CLPxe9jM1k5b78uyZleS4Am9lGekQq6RGpY9sGhgeo7WmguquGmp56mnpbaOprpqG3iV0t+454vYJCRFA4kUER2K0hhJiDCbGGYLeEYDVZMCkmTJjGRokMeYdwe4Zwe4dwe9z0DvXR7e6my91Nl7uHIe/Ry88oikJ8iJOc6CySwuaQGJpAYtgcYoKjjlqTezLYzFbuWfR5/mvHL/i4fgtZkenHrThvNpvwfGKpMyGEsSobunH1uFm5IAHLca69gWxJlpOX15Wzu0QS2OlGElgxZXaXtpDVUw1AWMGhOa7VXbUUtheTFTmftIh5RoXH3MgklsQtYkfzniN6YcOWnknnug9Re6vYU9oqCexJeOyxnxkdgphFRocQH68H9m/F/6R/uJ9b1OtJCpvaG5VgSzAZkWlkRB6agjA6r3bA2oNWX0X7QAeuwU46BjpxDbqo6a7Do59er6NJMRFuc5AQGkeEzUFMSAzOkBhiQ6JxhsSgpsyjs33gxG80iWxmK3ctuJ1Htz7BSyWvkxuTjd0aMu6xJkXB49XH3SeEMMbeMl9x6fyMWIMjOX1zYkKJj7azr6IN95AHm9XYqR3i5EkCK6aE16uzp7SNm/trwWIhdOGh4cOjva8Xp55nVHhjLpp3Hjua9/B+zfqxBNauZmMKCyOnr4ZfVbTKRU6IAHNoDuz4vQClrgr2tR4kIzKNlYnLpjK0YxqdV+t0JpNgSjpqv67ruL1D9A/30z88QN9QP0PeIXRdx4sXXdfR0bGarNjMNl/lX5OFUGsodkvIcXtSbWYrYGwCC+C0x3BZ6gW8Vv4Wb1W9x3UZnxr3OLNZGetlF0IEhj1lbZhNCrmp0Sc+OIAVZMby1pZqDlZ1TOtkfLaRBFZMibL6Tsxd7cQOtBO6cNFY9eHmvhb2tOxnriOZ7KhMg6P0zYXNispA6yiltrueZEeirxpx/hK8Gz4ipqeFwqoOFstFToiAMTaE+Bg9sK+XvwXANfOvmJIhsv6gKApBI4lpZFCE0eFMmvPnnstHdZtYX7eZi+edR5j16KXKLCYFr/TAChEwXD2DVDV2kzMvCvspLF8WiEYT2N0lLZLATiPTc9C6mHb2lLaR1VMDHDl8+KO6TejoXDj33IC5sbwgZRXgq1Y6KmxxPgAZvbXsKT3umuxCiCk2VsRpnCrENd11lLoqyInOIi1ClkoINFaThQvmnovb42ZdzcfjHmMyKWO97EII4+0r81UrXzQ/xuBIJm5+YgRhIVb2lbej63KdmS4kgRVTYn95G2pfNSgKofm+Yh2DHjebG7YTbnOw2LnA4AgPyY1RSbDHsb1pN52DvmrI9tw8FIuFrP5a9pa3yUVOiAByvDmwH9b6kqLzUs6Z0pjEyTs7cTnB5iA2NmzDqx89VNhsUtBBemGFCBB7Z1ACazIpLEiLpqN7kLqWXqPDESdJElgx6Tp73bTWt5DU30xIRiaW8HAAtjfuon94gLMTl5/UYvZTxaSYWJ28Eo/uYXPDNt+2oCBCsnOJHehguK2NhrY+g6MMXJs3b+TVV18xOgwxixwaQnzkV9qgx83Opj3EBkeTE51lRGjiJASZbSyNz8c12Elhe8lR+0cfTEghJyGMN+zxsr+ynbjIEBKiT21N6EC1IN03j3dfRdsJjhSBQhJYMekOVLSR3lePAoSODMXVdZ11dRsxKSbOSVpubIDjODOhAJvJysf1W8d6BEaHEc/vq+VARbuR4QW0FStWcvXV1xkdhphFDhVxOrIHdn9rIW7vEGckFGBS5OsukK1MPBOALQ3bj9o3ujySFHISwnhajYtBt4dF82MCZurXROWl+XqS95fLvd10ETjdXmLG2l/RTnpfHQChCxcDUNFVRV1PAwXOhQFZoCTEEsLS+Hw2NWxDay8lJyaL0EWL4U++ebD7K9q56MwUo8M8ro3vl1Fe1HzM/SazCa/n1G4I07PjWHn+/OMe88Ybr1NVVcm99371qH2/+MX/EB5u59Zb7+SBB+7jpptuZdeuHVgsFu6++96xbStXynBPcfJGe+Y+2QO7o3kPAEvjFk95TOLUzHOkEBsczYG2Ioa8w1gPG5VjGrlJliHEQhhvbP5rxvQfPjwqItTGvHgHxTUuBtzDBNskPQp08khaTCqvrnOwvJX0/gYs0dHYEn1rqG6q9w3NPSdphZHhHdfZib6e4Q31WwCwxsQQlJJCan8j5ZXNDA1Lb8Cpuuee+9i8eTOPPvoDcnLyWLnyHO655z527Nh2xDYhTsWhBPZQb8Cgx82BtiLmhMaTGJZgVGjiJCmKwmLnAgY8gxR3lH1in++/kr4KYbwDle1YLSbUlEijQ/GrhfOj8Xh1Cqs6jA5FnAR5xCAmVU1TD472BoI9g4QuOAtFUXB73Oxs3ktUUCRZUcfvzTNSangKSWFz2Nt6gC53N+E2B6GL8hmsqSGxq46SWldAr3+28vz5x+0tdTodtLR0T2FEYLFY+NznPseDDz7Iyy+vHdt2442f4Uc/+sHYNiFOy2Gj2Uo6yhj2DrMwNte4eMQpWeTM472aj9jTsp+8GPWo/VI7TwhjuXp8hY7y0qKxWsxGh+NXC9JiWLuxiv3l7RRkOo0OR5yA9MCKSbW/ou2w4cOLANjdsp8BzyDLE5YE9Lw0RVFYOWcZXt3L9qbdwKE5vDIP9vR0dXXxzDPP8NWvPsBPfvLo2Lbnn//DEduEmKiD7cUA5ErxpmkjPWIeoVY7B9u0Iyq9z5R5dkJMd4WVvt7J3NQogyPxv/lJ4YQEWdgnK01MC4GbPYgZ4UBFO/P76sBsxp6TA8CWhh0ALJuz9HgvDQhL4xdjUkxsa9wJQHBqGqbQUNL7GthfLtXqTtXjj/8nd911F9dffxMRERG8+OJfefzx/+SWWz57xDYhToU+zuDSwjaNILONtIh5BkQkTodJMZEVOZ+OQRct/Yeur2NDiOWmUghDHaz0PbjPC+DRZ6fLbDKRmxpFa+cAzR39RocjTkCGEItJM+Aepr6ykYTBdkKyczAFh9Ax4ELrKCUtfB7x9sAfouGwhZEbncX+tiIae5tICI3HnpOHd/tWeuvq6ewZJCIsyOgwA8rll195zH2PPfazsaHLDz/8CAA33HDz2P7RbUKcjtF+utb+dpr7W1kUmxdQS3SJE8uKymBXyz6KO0qJs8cChz5XyV+FMI6u6xys6iAsxEpyXJjR4UyK3HlR7NBaKKzqIH6GLBE0U8k3u5g0WrWLuT1HDh/e2rgTHZ0V06D3ddSZCUvY31bE1sZdXDX/UkLz8ujZvpW0vnoOVLazcsEco0MMOA899E26ujqP2BYWFsbjjz9hUERiNilxlQOgRmUYHIk4VWq07zPTOkoPFfkb6YKV/FUI4zS09dHRPciynLixyuAzTc5Iz3JhVQdrCpIMjkYcT8AksKqqxgE7gIs0TSsyOh4xcYVVHUfNf93etBuLYmbJNFrWYlFsLsHmILY17eJT6Rdjz10AQFpfPUVVLklgx/HYYz8zOgQxi5W7KgCYH5lqbCDilMWFxBIZFEFxRxm6rqMoyqHaXNIFK4RhRocPB3LxyomKjwohyhFEUXUHXl2fsYn6TBAQc2BVVbUCvwJk0PkMUlTVTlpfA+aoaGxzEmnobaK+t5HcmGzs1hCjwztpNrONfOdC2gc6KHNVYo2JwZowh3n9TRRXthodnhDiE3lNWWcVweYgEkNl+ZzpRlEUMiPT6RnqpbmvZWSbb5+kr0IY5+AMLuA0SlEUsudG0d03RH1Lr9HhiOMIiAQW+DnwDFBvdCDCP3r6h3BXVxPiHSQ0Nw9FUdjZvBeAJXGLDI7u1J2R4Ks+PHoOoQsWYNWHCW6qocUlz12ECASKAj3uXpr6mkmLmIfZNLOWeZgt0kcKb5V3Vh2xXTpghTDGsMdLUXUH8VEhxEZMnw6I05Ezz5egy3qwgc3wIcSqqn4eaNE07W1VVb9zouOjouxYRtaecjodkxzd+KTdEyvd18Dc/gYA4pctwel0sHf7fqwmC+dlLyPEGuz3Nv3hWO1Gx+Tz3MFQ9rbt58uxt2I+60xc/36XtL566tr7yc2Mm5R2J9tsa1fMfOWdlcChJEhMP2kRqYAvgT0r8UxZRkcIg1U2djPg9rAib+YOHx51eAJ70ZkpBkcjjsXwBBb4AqCrqnohkA/8UVXVqzRNaxzv4I6OPoCxSqZTTdo9OVv31ZPa7/sIPUlp7KkoobargcXOBfS4huhhyO9tTtSJ2l0Yk8fGhq1sKd1PesI8MJtJ669n24EG8tNP/6IeqOc73dqVpHj2OrxjrmwkgZ0fkWZILGLiEkPjCTLbKO/y9cAeqkIsXbBCGEGr9vVGjiZ3M1lMRDBxUSFoNR14vF7MpkAZrCoOZ/inomnauZqmrdY0bQ2wG/jssZJXMX0UV7aS0t+MNTEJS2Qku6bx8OFRBXELAdjdvA9TUBAhGZkkDLZTWdYgN1ZCBASF8s5KTIqJ1Ii5RgcjTpPZZCY1fC6NvU30DfUdymCFEIbQalwAZKVEGhzJ1MiZF0X/oIeqxh6jQxHHYHgCK2aerj43em0lVn2Y0JxcdF1nZ/NerCYLC2JyjA7vtKlRGdgtIexq2YdX9xKa56tGHNFSJYteCxEAhrxDVHfVkhyWSJDZZnQ4YgJGh4BXdFXLOrBCGMjj9VJa20lCtJ2I0NlxXT00jLjd4EjEsQRUAqtp2hpZQmf6K652kdrn60S35+TS0NtEY18zeTE5BFuCDI7u9JlNZhbF5uEa7KSqq4YQNRuAef1NFFbLZH8hDDOS2dT3NDKse0gNl97X6e7webDK2DqwksEKMdWqm3oYcHtmTe8rQPZcXwJbVO0yOBJxLIEwB1bMMIXVHczrbwDFREiWyvqmTQAUOBcYHNnEFcQtZHPjdnY17+PatEvBFsTc/kb2VHWwJl8WvRaHHL62NTAMPItvuuZ+4D5N07zGRTcz1fTUAjAvPNngSMREpY08hKjorCIUXyEV6YEVYuoVjwwfVufOngQ2PNRGQrSd0rpOmQcboOQTEX5XVtZE4kArQalpmO129rUexKSYyI3JNjq0CVOjMwk2B7OrZR+YzdizsogZ6qK6rE7mwYox46xt/QTwXU3TVuGb0Xe1UbHNZNXdvgR2rkMS2OnObg3BGRJDTXcduuK7tsoVVoipp430QqqzqAcWICslgkG3h9pmWQ82EEkCK/yqs9eNtb4SEzqhubm+4bbdNWRGpmO3Tv+1w6wmC3kxKu0DHdT3NmLP9s3pjW6roaGtz+DoRAD55NrWS4F1I7+/CVxoRFAzXU1PLTaTlYTQiS1rJQJDsiOJvuF+hpSRa6s8JBRiSnl1nZJaF7ERwUSHH3/5w5kmM9mXsI/2QIvAIgms8KuSGhepfb71X+05uexrLQRgYWyukWH51ei57GstHEtg5/Y3UlrXaWRYIkAcvrb1YZsVTdNG7767gYgpD2wG0wEUD429zSQ7kjAp8tU2E6SEJQLQb2oDpAdWiKlW39JL78DwrOt9BcgcOefiWklgA5HMgRV+VVLbydz+RrBYCZ4/n30HXwBg0QxKYPNiVEyKiX2tB7lkyRoIDmFefxP7alycuzjR6PCE8Y5a2xo4vEvQAZzwGzEqyo7FYgaMW+N2urRrs1pQgvvQ0UmPTTntuKfL+U7XNk+13QXDGbxWDm6bC4gjOioUpzNs0tv1J1mfWkxnY8vnzKL5r6OcEcFEhtkoqXGh6/pYMTkRGCSBFX5VWdnEEncHwVkqbkVH6yglKWwOMSHRRofmN3arnfkRqZS6Kuge7sWuqrBnN/XltcDMSdTF6dE07dzR31VV/RD4EvAzVVXXaJr2IXAZ8MGJ3qejwzds0ul00NLSPSmxHs90atc9NIwS7Jun5FDCTyvu6XS+07HN02k3zOO7ae7xtAFxtLf3Yj2Nftjpcr6n8r5CTIXRBHY29sAqikJWSiRbC5tp7ugnPtpudEjiMDLOSvjNgHsYvboCBbCr2RS1FzPsHZ5Rw4dHLYzNRUdnf2sRoapvGHFYYxUd3YMGRyYC1DeAH6qqugmwAS8ZHM+MoutgCvYl/HEhsQZHI/wl3ObAZrIyqEx98inEbKfrOsU1LiLDbDgjp38Nk9Mh82ADl/TACr8pr+8ieXT91yyVva37gJk1fHjUwtgcXildy/7WgyzJXgMcmgd7ZrYUkBE+mqatOeyPq42KYzZQgkYSWLsksDOFoihEh0TT0uNbZ1vmwAoxdZpd/XT1ulmWEzdrh89mJvvKVRTXulglU8QCiiSwwm9KajtJ6W9CN5mwpaWxf9vfibCFk+KYeeujxtmdxNudFLYXY8q5GYLtzO1vorjGJQmsEAZQrL7RDxFB4QZHIvwpNjiKxt4mMA0bHYoAVFVdDvxE07Q1qqouAV4HSkZ2/6+maX9TVfUHwBX41r/+mqZpWw0KV0xA2UhhyvmJs7fmYLIzjJAgCyU1UqQz0MgQYuE35ZXNJAy2YZubSs1gC71DfeTFZM/YiqALYnNwe4co7izHrqpEDvdQV1ZjdFhCzEqK1Y1ZMRNsnl1LPcx0DptvvufoAwphHFVVHwR+C4z+T7YEeELTtDUjP38bSWpXA8uBm4FfGBOtmKiyui4AMpJnbwJrMilkJkfQ7OrH1SPXoEAyMzMLMeU8Xi8D5eWY0QnLzuZguwb4KvbOVAtjfEOjD7QVEar6ztNUU0H/oPQUCDHlLG7CrKGzdqjbTBVmDfX9YhlCl3VgjVYGXHfYn5cCV6iq+pGqqr9TVdUBnAO8o2marmlaNWBRVdVpRLBiYkrrOrFaTKTEnV7l75lidBhxaa30wgYSvw8hVlU1EkgHvECFpmnyic8CNc09JHT71n8NycqisG0DJsWEGp1hcGSTJz1iHsHmYA62F3NVxg0AJPc3U1bfyYK0GIOjE/6gqupq4CogE981rRR4VdO09YYGJo6iWN2EWWdfpcyZLtTqq/ypWN0GRyI0TXtZVdXUwzZtBX6radoOVVUfBn6Ab4mwtsOOGV33umXKAhUT1j84TG1LDxlJEVjMs7uvKyPJl8CW1XdyhkwRCxh+S2BVVb0M+Ba+dURq8c19SFZVtRD4uaZpb/qrLRF4SmpG5r+i4J2XROWOGtIjUgmxzNzKdWaTGTU6gz0t++lyhqJbrCQPNFNcIwnsdKeqaj7w30AzsB5Yh++algr8H1VVH8U3t2unYUGKMToeFLOH0NHeOjFjjPbAKhZJYAPQPzRNGy3P+g/gKeBVfGtdjzrhutey5nXgtbunpAVdh0WZTr/GGKjnezyO8BBMyi6qm3tP6X2m47lOp3b9ksCqqvos0Ajcp2nagU/sWwB8QVXV2zRNu9Uf7YnAU1rVyurBFiyJSZQM1KGjkzuDhw+PyonOYk/Lfoo6y5iXno6zWGNbRSOcm250aGJibgOu1zStbZx9v1RVNQ74DiAJbADwMARAsCXI4EiEvwVbRqZbmmVqhr+oqpoGfIojR5a8rmla1Sm+1duqqn51pEjTBcAO4GPgp6qq/hxIBkyaprUe701kzevAa3fHAd+IujlRIX6LMZDP90SSnWGU1rpoaOw8qR7p6XyugdTu8ZJif/XAPqxpWt14OzRN2w98XVXVZD+1JQKMrut0lZRh0b04crLZ2FYMQG5M1qS16R4cpqG2k4baTlobu+lyDdDf53tCHxxixRERjDPBQUJyBIkpkQQFT07B7dxo3zkWtmvkZam4izXcFeUMe1bM+mE309yzx0heAdA0rRl4YArjEcehKx4AbGabwZEIfxv9TBWTx+BIpj9VVefgG1kyD1+iWcqhkSV/V1W1EviGpmm1J/mW9wJPq6rqxteJ8UVN07pUVV0PbMJXZ+U+f56DmBpl9b4CTvOTZm8Bp8OlJ0VQ3dxDbUsPqQlS6T4Q+OWufrzkVVXVIOAm4Euapq08hQuimGZaXP1Ed/j+CQRnqhxsfwuHNYzkMP+umaXrOtVl7RTta6CqrB3PsHdsX7DdSlh4MArQ3zdEXZWLuioXbKnBZFaYmxaNujCB1MxYTCb/FXmJCYkmzh5LcUcZtvm+ebDxvY1ykZv+XlVVtRX4PfAXTdO6jA5IHJuu+HrnrCZZGW6mCRp9KCEJrD88DjyiaVrheDtVVV0M/Bi4/VhvoGlaJbBi5PedwMpxjnkEeGTC0QpDeHWdsrpOnJHBRITKQ0GA+YnhfLirjrK6Lrm3CxCTUcQpG7gH+CzQDvyPv9sQgaWsvovkgSYAOhPD6SrqZlnCEr8tn6PrOuVaK9s/rqS9pReAyBg7aVmxJKZEEp8YflQP65B7mKb6bhpqXFQUt1JZ2kZlaRsRUSEsPXseWXnxfqtWmhOtsq72YxpjreiKQkp/s1zkpjlN0+arqnoOvhu576uq+h7wO03T1hkcmhiH9MDOXDazFQDF7EGKEE/Y90YqA49L07Q9HCd5FbNDU3sfvQPDLJwvtTxGpSf67ufK6zu5YKkMKA0E/poDawU+DXwJWAysBdxAlqZp8pUzw5XXdbJwoAWiYykcqgcgN9o/81+7XP189HYxNRUdKApk5cWz6MxkYuPDjpuAWm0WklOjSE6N4sxVabS39LJ3ey3a/kbeX1vEwd0NrLksi6iYiRd9yY3OYl3txxT2VZE3J5k5DXVsrGkDuchNa5qmbQA2qKpqw1eJ+Ouqqv4S+JOmaY8ZG5043FgCa7IaHInwtyCT9MD60SZVVXuAd4B3gfc1TesxOCYRYErrfIuHzE+U4cOj4qPt2IMsY0OrhdPitNUAACAASURBVPH8NUmvDrgR39yKBE3TbgP6JXmdHVpLKwn2DhGWlcXBNg0FhezozAm/b0VxCy/+YTs1FR2kpEVx893LuODKHJwJjlPuPY12hrLmMpVbvrictKxYGms7eenZHRTvb5xwnJlR87EoZgrbNBzZKhbdS1dp+YTfVwQGTdPcmqa9BPwE2AJ83eCQxCd4R4YQSwI789hkCLHfaJqWBFyOr9jSNcC2kTVcv6eq6gpjoxOBoqzOl6RlyPzXMSZFIT0xnOaO/v/P3p3HSXrVhf7/PLX23l2979ss35lMJsmEhCRkIQQFIiDCFVCRq3j5of4QN7woygXxXn/Xy4+LVxEFUUEQEQwgAoYAIQkEsmeSzGQyp2d637t637equn88VTM9me7p7al6avm+X69+dXd1VZ1vbaef73PO+R7mFrUiejpwagrx54E3Y+/1VS0i9zh0vyrNra1HsAZ7AAi0t9E1832aiuspDux94+tYLMbTj/Ty2EPd+HweXvFTghyvdWTKb3FpHq9509V0nh3jwXsN93/zLJPjC9z08r1XDQ56A7SXtdExdR7aTgBQGO5nbnGV4gKd0pjJROQY8DbsE3RdwGewC5eoNJIYgfV7NYHNNr74umbLE0XPiO+fMaYT6AQ+KyJlwBuA9wIfALSMt6JraJaAz0NjtW5LtlF7fQmnuyfpGprl2oOVboeT85wq4vReEXkf8FrgHcDHAETkZ7H3CdNTp1mqd3SeukV7f/JwdT6RsQgS2vvoaywW47vfOMNjD3VTVBLkp372OBXVe0+Gt3LgSDWVNUV868unOPloP0uLa/zs22/Y8/1dVX6Yjqnz9FVYlAJNS2PayWUwEfl97MS1EPgscNeV1o4pd0WJJ7A6Apt1vIlaCpamr/slIj7gNuA1wKuBfOB7wAeB77sYmkoTK2sRhsYXaG8owevRnRQ2SlRk7tRju7TgWBGneJL678C/i0gVdiGA/4ZdxKnBqXZUeukanKFhOUwsEMQE7L3KJXRwz/f32ENdnHy0n1BFAa976zUUleQ5FeplSkMFvPHtJ/jWl09x9rkR7v3qKW68o3VPI71SfhA6wURGubGsgobZMToHZ7STy1xXA79ljHnA7UDU9rSIU/byWF77B01gnTAF/Bi4B3hjvKKwUhf0jc4RjcVo0yKUl2mrs5+T7qEZlyNR4NAaWBG5JMswxoSNMR8zxlyLXfzksuuo7NDbM0rl2gz+llbMTBdey0t7Weue7uvZx/s5+Wg/FVWFvOFt1yU1eU3ILwjw+p+7hsrqIp56pJfHf9C9p/tpLKqnwJdPx9R5Cg4dIj+6ytj5HmeDVan0OPCDrf4oIl4ReU8K41FXZG+p5fN4XY5DOc2beE2tKFqGeN8+BVQDvwK8Q0RuFREdZlMX9AzPAdBaV+xyJOmnKN9PbXkBXcOzRLUvcp1TI7BfEJFvA/9ijJl70d86ROTdwE8Ab3SoPZUmFjs7Acg/2E7/3NMcKGu9uG/fLvScG+fH3++ksCjA2951M2uR1M06D+b5ee1br+EbX3yWpx/pI1RZyOFjNbu6D4/l4VDoAM+GT2O1HoMnYL23m2g05ui+sypleoAfiMhD2InsALAGtAJ3Aa8A/tSt4NSlYvHROQ/6Wcs2OoXYOcaY3wMQkTrsKcS/AfyjiJwC7jPGfNLN+JT7ukfsAk6J0UZ1qba6Yh55fpGxqSVqywvcDienOXXm7c1AALui3aMico+IfFFEHgWeBqz4dVQWmZ5foWRyEIDxmnxixDi8h+nD05OL3P/NF/D6PPzUm49T5kKnUFAY4Of+y0sJBL08eK8hPPLi8zDbOxw6AMBghT1iUDk/xvDEgqNxqtQwxnwDO0k9h72v9b9gT7v7VcAAtxtjvu5ehGqjWLy8j+XQ3tMqfXgsD8QsewRWOcIYMwz8M/BXwN8Ch7DXwaoc1z08R37QS3Uo3+1Q0lJrfGp1z7Bup+M2p4o4RYFPAJ8QkWuxO8MYcD6+MbbKQl1DszQs2wWcOkpWYHz361/X1iLc97XnWV2JcNdrj1BZ4960lcrqIl75+qPce89p7vva87zlV24gENz5RyTx2M8GprnZ66NhOUzn0CwNVc4XoVLJZ4xZxa46/Bm3Y1HbiY/AagKblSw8WDoCu28i8tPArdiFnNqBR7GLN73VGPO8m7Ep9y0urzM6ucjRlhAeB3Z9yEYttfYxas/IHDcfq3U5mtzmWBGnhHjCuuOkVUS8wKcBASLAO+Jl3lWa6xqYRpbHiVXWcGapj4DHT2tJ067u47EHu5gML3DViXrkuPudQevBSq6/pZmnH+nj4e+d567XHtnxbWsLqikOFGFmu3hZQzNVfd083hfmjmvrkxixUioxOqcJbHby4CFi6TY6DvgN7IT1t4Gn4oMPSgHQG58+rOtft9ZcU4Rl2Qmsclc6/Ld/PYAx5lbsKSwfczcctVPj57oIxtYJtLcysjDKgbK2C3v27cRg7xSnnhqkrDyfW+86kMRId+eG21qpqi3CnBqh82x4x7ezLIvDZQeYWZ3D196Ahxgz57qSGKlSCuzttwAdNchSFh5dA+uMjxtj/swY88RWyWt8lFbloO54UqYViLeWF/BRX1FIb7xas3KP4yOwu2WM+TcR+Wb81xZg1M141M5EozFi/T0AzNbbU2R3M314dWWdB751FsuCu153FJ8/faqHer0eXvn6o9zzmaf4wX2G+uZS8gt2VphKQgd5auxZxqryCAHB0X6WVtbJ38VUZKXULlk6hTib2QmsDhY6oFVEvoO9nn+z4nRvBb7mWnTKVYl1nToCe2UttcUMji8wOrlIXUWh2+HkLEf/24vIxze57B+3u50xZj1+vY9jd6wqzQ2OL1CzYJ9rOF+2BuwugX3ihz3Mza5w4uZmaurT72xfqKKQG29vY3lpnUcf3PkoaqKIlSleBKB+OUzfqE41yVQi0iIi3xWRcyJSJyLfF5FWt+NSL6YJbDa7MAKrAx77Yoz5OPCLQAPwRWAEGIv/XIu9FvYv3ItQual7eI7iAj8VKdjCMJO1JtbBDuuxnZscGRYSkb/DLghwg4gc2/AnP1C6k/swxvySiPw+8JiIXGWM2bR8ayhUgM9nj9ZVVblzlkjbhac7J6lfDhML5vG8L0xhLJ8TbYLHs/0B5OjQLKeeHqS8spDXvOHqTUdf0+GxvvLuI3SZMGefG+Gm29tpaa/Y9vaVsSIqnyvnzPoQNxWXUr84Tnh2hdu2eTzp8Hhzod09+BTw/wN/hn2w90Xgc8AdbgalLhWL7wPrSYtVMcppdgKbuq3VspkxZgz4UPxLKQBmF1eZmF3meHsFli7FuKJEJeLukVluudr92i25yql5jf8DewrKXwAf3nD5OvDClW4oIm8HGo0x/xNYxN6Rfsv/VFNT9shWVVUx4XDqz35ou7YXzvRx49oc0fYDjC5OcLzyKiZ2sGVMLBbj6196hlg0xi13tTM1vbjjNpNts3Zf9soDfO3zJ/n3Lz3Dm99xA17v9gfIB0vaeXTkSaKNdRS9cJZnT3URvkInl06PN5PbTVJSXGmM+Y6I/C9jTAz4dHxfa5VGLuwDqwdeWcnC0irESiVRYjSxTacPb6spXsipVws5ucqR09XGmB5jzIPGmGuBk0AX0A30A9vtIfJV4ISI/AC4D/htY8yyE3Gp5Fk4bxeKXmkMAXCwrG1Htzv3/CgjAzO0Ha6keQcjmm6rbSjlquvqmBpf5IVnhnd0m4OhdgDmG+yzdKs9Wsgpgy2JSCPxyYsichuw4m5I6nK6D2w2s7C4uNuvUsppF9e/pt+SrnQT9HtpqIwXcopqr+QWRyvLiMj7gfcDExsujmFPL95UfKrwW5yMQyXXeiSKd3QAgKFy+4DxQOn2Cez6WoRHH+rG6/Nw6yt3t1+sm268vY1zZ8Z44uEeDh2rIZh35Y/Nwfhz0R2KcB1QOD7IwvIahXn+FESrHPa7wDeBAyLyDFDODvqrzbYHAyzgs9h94mng3bqNhTMSqY1XE9jspYPrjhGR1xpjvuV2HCp99MZrdbTU6AjsTrTUFjMQXmB4YoGGqu3G6VQyOP3f/p3AAWNM24avLZNXlZkGwwvULI0D8HzBLAGPn+bihm1vd+rpQRbmVrjmhgaKSzOnSEBBYYATNzezvLTGycf6tr1+ZX45pYFingtOErMs6lfGdapJhjLGPAHcCNwM/GfgoDHm0R3cdLPtwT4GfMAYczv24fgbkhJ0LtIqxFnOHoFVjvmI2wGo9NI3Ok9JgZ+yop3tuJDrEutgdT9Y9zi9t0cfMOnwfao00zMyS93yOOuFxXQziZQexOu58jY4K8trnHykj2CejxM3N6coUudcc2Mjz58c4rknBjh2Xf0VE3DLsjhQ1sbTY8+xVllNbThMz+AUV7WWpzBi5QQR+YcXXRQTkSXstf2fNsasbna7LbYHey3wUPyye4FXoVtWOCJ2YQqxDtNlIwsLrIv7/ap964z3bY8BS4kLjTGfcy8k5Zb5pTUmZpe5uq1c+9AdSmw11DMyx63H61yOJjc5fbr6HPCwiPx/IvLBxJfDbSiXDXUPURxZYrW+EtjZ+teTj/azsrzOiVuaCWbgVFq/38tL72gjsh7lqR/3bnv9A/HnZKWxHB9RJs51JztElRwR7Erq/xb/ygeqgcPAJ690w022B7PihaAA5thhhXa1E4kpxOmzn7RymiavDprAHta+GXhF/OtONwNS7ukfmwfs4kRqZ5qqivBYls6uc5HTI7CD8S/QFStZa6HTLko0U1sALGybwC7Or3DqyQEKi4Mcv377qcbp6vCxGp5+pBdzaoTrb2mmpCx/y+seKrNnzocrfRQDq709qQlSOe06Y8yNiV9E5BvAY8aYt4jIs9vdeOP2YNjJb0IxMH2l2+qWYTuX2L2roryIqtK9x5wpjzdT29xrux6PByJQXl6457gz6fEmmzHmHQAiEjLGTLkdj3JXn65/3bWA30tdRQH94XmisZhWwHeBowmsMebDIlIIHMAuUpK/1X6uKjOtrUcJjNkFnLpKVvFaXlpLrjwl+NknBlhfj/KylzVvuudrpvB4LG64tZX7v/ECTz/Sx513y5bXrSusId+Xz9nCedqB4pkRZhdXKSnQ9SUZpkhEao0xI/Hfq7mYiG7Zf26xPdiTInKnMeZB4G7ggSs1rFuG7VwkZu+8Nj21RN7q3mLOpMebiW3up91YFLBiTE4uUOTf/cSxTHu8O7nf/RCRa4EvAQUicjPwA+AtxpinHQhPZZi+UXsEtlkT2F1pqilicHyB8PQSNaECt8PJOY5OIRaRu4Bnga9jH+j1isirnGxDuWsgPH+xgFP+DM3FjQS8Wydly0trnH56kMKiAEeyYJ3AwaPVlJbnY06NMDu9tOX1PJaHA6UtdObNE/X6qFue0KkmmelDwFMi8q8i8lXgCeCDIvLHwHevcLvLtgcD3g18WEQeAQLY04qVI7SIk1K78HHgjcCEMWYI+HW2WRKhslff2BxBv5fq0NazytTlmqvthL8/fgJApZbTU4j/J3AbcK8xZkRE7gC+CHzH4XaUS3qHZ6hbmWCltJSlwPbrX597YoD1tSg33dGM15f5B5e7GYU9UNbG6YmzLFWVUzkSprN/guMZsPetusgY82UR+T5wO/Z62HcZY8ZF5CFjzJYF666wPdjLkxRqjtMENptZuiLJaQXGmBdE7P9fxpjvishHXY5JuWBtPcLw+CLt9SU6DXaXEmuG+8bmuOFItcvR5B6n/9t7Nky1wxhzxuH7Vy4bOd9HXnSV+XgJ8SslsCvL65x6aoC8Aj9Hr8v80deEg0erKQ3lY06PsDC/svX14s/NXG0hXmJMnutKVYjKISJSBbwduBq4DniPiHzuSsmrSr1YfBsdTXSylQVWDC1C7JjJ+DTiGICIvA3dQSInDYQXiMZiNGsBp11rqo4nsDoC6wqnE9gBEXkd9lYTZSLyR9hb66gssdxtV9MdqfBgYdFe2rrldU8/PcjqSoRrb2zEn8FrX1/M47G49qVNRCMxTj01uOX1mosb8Xt89JWtA7A+oB+FDPQl7MT1F4FC4Gex17MqpVLE0n1gnfbrwCeAYyIyjb3E4VfdDUm5IVHASde/7l5JQYBQcfBCFWeVWk4nsL8KvA1oAjqxD/ze5XAbyiVr6xECYTthM0Xz1BfVUuDffM1EZD3K6acGCQS9XJ3BlYe3IlfXkFfg5/mnh1hbXd/0Oj6Pj9aSZjoK7WI8pTOjTF9hxFalpXpjzC8B38Be13oHcMLdkJRSal/KjDG3AeVAszHmRmNMh9tBqdTrG0sUcNIR2L1oqi5iam6FucVNt4RXSeR0AvubxpifN8ZUGWMqjDFvNsYMO9yGcslAeIHa5XGilsVwmYe20pYtr3v+7BiLC6scvbaOQNDppdbu8/m9HL++gdWVdV54dmTL6x0oa2Oy2EPE56N2ZeLC2U6VMRJbTBjgWmPMhJvBqC3EB+d0CVd2srB0Yz5n/amIdAL/B3iFiGgJ1RzVNzqHx7JoqCx0O5SMlJhGrKOwqed0Avt6EdF/M1mqZ2CKmpVJFkOlrPssWoubNr1eLBbjuScGsCyycvQ14dj19fh8Hp57op9odPNZpW0lzcQ8FvNVpVSsztA3oPlPhvm+iPwrdiG694rIJ4Gty08rpZJEpxA7xRjzGuAY9qySVwKnReQ/3I1KpVo0GmNgbIH6ygL8vuxZ5pVKianXug429ZxOYCeAsyLyRRH5h8SXw20ol4yd68YfizBbY5+paynZPIEd7p9hfHSetsOVlJRlb1n2/IIAck0tc7MrdHeMb3qdxCj1RFUADzFmzmshp0xijPkj4A+MMb3AL2CPxL7R3ajUVrSIU7aydHTdQfHidK8DXotdGX0S0KKbOWZ0apGVtYiuf92H5gsjsDq7LtWcntv5jw7fn0ojq329AAyVxwh6A9QWbl42/LknBwC45sbNE9xscvwljTz/9BCnnxrkwCZl1Av9BdQUVNFdMkw7ENFCThlFRL5ijPlPAMaYp7D3hL0fe9RCpYmYjs5ltcSJiWhM66c5ZDT+9X+AO40xU9tcX2WhxLTXRBKmdq8qlE/Q772wlliljtMJ7C8YY17t8H2qNLAeieIft5czdxYu01Ism+65ODu9RHfHOFW1xdQ2lKQ6zJQLVRTQ2BpioGeKyfAC5VWXryNpK2nhbJn93BVNjbC4vE5BXvatC84mIvJV7GJN9SKycdjcB/S7E5VSucpOYPVEhWOOAHcBrwAeEJEzwAPGmE+7G5ZKpV6tQLxvHsuiqbqIrqFZ1tYjOhU7hZyeQpwvItk/7JaDhicWqV6eIGpZhMu8W04fPvPMEADHb2jAypE5X8dO1ANw+uTmW+q0lTYzXexlze+nbmVCp5pkhl/GPrj7dvx74usW7Cl3Kp3kRleTsxIvryawzjDGdBhjPgn8KfB54EbgfTu5rYjcJCIPxn8+KCIPi8gPReRvRMQTv/xDIvK4iPxYRF6apIeh9ikxAtukFYj3pammiGgsxuD4gtuh5BSnE9hqoEdEhkWkS0S6XzR6oTJU3/AM1StTLJYVE/FZtG6SwEYiUc4+N0Iwz8eBI1UuROmO1kMVFBYH6Tg9yurK5VvqtJW2gGUxU1lIxdosff2br5dVaeU6oBn430DLhq8DwMtcjEtdQa6cNMs58dc1pvmrI0TkX0SkH/gY9r7WrzPGHNrB7d4H/B2QF7/oY8AHjDG3Y59neIOIXI99ku8m4Oew95tVaWgwvECoOEhhnt/tUDJaYgq2FnJKLafnMer04Sw11tVHVWydsUr7/9ZmI7A958ZZWlzjmhsb8eXQNAqPx8Ox6+p4/Ic9dDw/elnl5brCGvK8QUYrIlQOw0zHebh122MF5a4PX+FvMezpdypdaGKT1RJrYGOawTrly8A7sZNOrzFmeoe36wTehD1qC/AS4KH4z/cCr8IudPcdY0wM6BMRn4hUGWPCjkWv9m1heY2puRWOt1e4HUrGS0zB7tcENqWcTmC3mlr3OYfbUSm21N0DwGAoSmmglLJg6WXXOfOMvc7zqmvrUhlaWjh6bR1P/qiX008PcuxE/SUjQR7LQ0tJE72lpzkGrA3oEsp0Z4x5xcbfRaSY3R3oKaUcplOIHfMs8H3sGSWWiPQCbzXGdFzpRsaYr4hI64aLrHiiCjAHlAIl2DtS8KLLNYFNIwPx6cONm9TtULvTUFmIZWkl4lRzOoHdeNDnB24HfoAmsBktFovhGbXXd/aVrNNS0nzZVL2ZqSUGeqaoaywllIMbYhcUBWk9VEmXCTM2PEdN/aUFrNpKW3g0dBaA/MkR1taj+H1Oz+BXThORduBfuPRA7y3GmHPuRqZU7rC0iJPTPgl8xBhzD4CIvAX4W+DOXd7PxrLQxcA0MBv/+cWXbykUKrgwa6uqyp2CQrnW7sySvdzp6IHKlMaQrc9zfWUhgxOLVFYWXTg+ztbHmi7tOprAGmPesfF3ESkHvuRkGyr1JmdXqFi0122Oh3zcsMn04ReejY++Xpd7o68JR66ppcuEOXtq5PIEtqSZbxd7WfN5qVqZYHB8ntba7K/SnAU+xeUHep9m9wd6KqnsxEb3gc1W8ddVpxA7pTLRpwEYY74sIh/Yw/2cFJE7jTEPAncDDwDngY+IyEeBRsBjjLli4YepqUXAPgAOh1M/ipWL7Z7ttgfJS4LelMWQzc9zbXkBg+EFOrrGKS/Jy+rHmsp2r5QUJ3sIaB5oTXIbKsn6RmepWZlkvriAVb/nsvWvkUiUs6eGCeb5aJfcKd70Yk1t5RQWBTh/ZpT1tcglf0sUcpoO5VOxOkvfwKRLUapduuxADyh3MR6lco5WIXbcSrzYEgAi8hJgcQ/3817gwyLyCBAA7onvl/1D4BHgK8C7HYhXOWwgvIDHsqiryL0Zc8nQWGUXchoIayXiVHF0BFZEHuBiOQ0LaAe+5WQbKvVGOgc4EF2lLz41uKWk8ZK/93dPsrSwxvGXNODz507xphfzeCwOH6/l5CN9dHWMc/hYzYW/FfoLqCmoYqS8l6pwjPFzXXBDq3vBqp1aEZHrjTFPw74O9FQy6cBrlrNf4Kjmr075beArIjKJ/eSWA2/dyQ2NMT3AzfGfO9ik9okx5o+BP3YmVOW0WCzG4Pg8tRUFupTJIQ3x4+PB8DzXHNDCWKng9BrYP97wcwwYN8accbgNlWJzXd0ADJVFqSmoJt+Xf8nfO06PAnD46prLbptrjsQTWHNq5JIEFqC1pJmRsj6OAyt9fe4EqHZrzwd6yg2ayWY3zWCdYIx5VEQOA4exZ+IZY8yqy2GpFAlPLbG0EuF4u46+OqWxWkdgU82xBFZEQsDzibUOIvJytOpcVogNDwAwXHb5/q8ry2v0nBunrKKAqlp3Fo6nk7LyAmobSxnomWJuZpni0rwLf2srbeF75Y8C4A8PEY3G8Hj0gDsdiUi5MWZSD/Qyg26votT2RKQe+ChwDPgx8H6trJ57ekZmAWiIT3tV+1ddlk/A52EwrFvppIojcwdE5ARwBrhhw8WvAp4RkWucaEO5Y35pjZLZMQDGQr7L1r92mjCRSAy5uuayysS56ug1tQCY0yOXXN5W0sxkiY+IZVG5NMHolM5ETWMdIvIlEXk1sG6Med4Yc0qT1/SmXVB2ShTniuoI7H59BhgC/hDIA/7c3XCUG3qH7QRWt9BxjsdjUVdZyNDEIpFodPsbqH1zavL7R4GfN8Z8O3GBMeaPgF8BPuZQG8oF3YPT1K5MsFAQZDnPc9kIbMcpe/rwoat0+nBCu1Th9Xk4d2bskpGhusIavP4A02UBqlan6RuecTFKtY1m4BvA7wJdIvInItLmckxKKbUfDcaY3zPGfAt4F/BStwNSqddzIYHVEVgnNVYVsh6JMjq55HYoOcGpBDYUL6N+CWPMfUDllW4oIn4R+byI/FBEHheRn3YoJuWAno5+CiPLTFQE8VleGooubpMzO73E8MAM9c1ll0yVzXWBoI+WAxVMTywyMXZxOonX46WpuIGRkIU/FmHsXI97QaorMsYsGmP+yRjzauBl2Hsbfk1E7heRX3A5PLUF3UYn2+kI7D5dmEFijFnb+LvKHb3DswQDXir0uM1RFysR6zTiVHAqgfWLyGX3Fb8ssM1tfxGYMMbcjr2P2F85FJNywPgL5wAYCkVpLG7A57m4bPrc8/boq2jxpsscuqoagHNnxi65vKWkkbGQ/Rwu9vSkOiy1B8aYYWPMR4HXAR3Y0/BUOtG8NTdo/uo0fUZzzHokysDYPI2VhXh0zYWjdCud1HKqiNNDwIfiXxt9AHhym9v+K3DPht/XHYpJOWC1txeAsZD3kvWvsViMjjNjeH2enN77dSvNB8oJBL2cf2GMm+9sv7A+uLW4ibPl9sfOGh3U4jNpTkTKgDcDbwNqgM8BOpVYKTdod7lfx0Ska8PvDfHfLSBmjGl3KS6VIiMTi0SiMS3glASJNcVayCk1nEpg3w/8h4j8EvAMsAxcD4wBV5wSbIyZBxCRYuxE9gMOxaT2aT0SJTgxBNgFnO7YkMBOhheYnlikXSoJBJ3ejSnz+Xxe2g9XcfbUiD3NuqkMgOaSJsbLfMSA8vlxpudXqa52N1Z1ORF5C/bskJcBXwf+mzHmh+5GpVSu0pEihxx2OwDlrv54cqUFnJxXUhigKN+vU4hTxJHMwxgzJyJ3AK8ATgBR4BM7PeATkSbga8BfG2P++UrXDYUK8Pm8AFRVubNtS6602z00Q/XyJEt5fhbyPZxoPUJVsR3D6acGAThxY3NS4sqG5/glt7Ry9tQIg91TXHu9nfxXxooIFBYxUzxD9cIkM8vrjre7G7nW7i68B/gH7OJ0Oh8o3cVnMuga2OyUeFW1CvH+GGN63Y5BuWvgQgKrI7BOsyyLxqpCzvZNs7Sik0mTzbGhM2NMDPh+/GvHRKQG+A7wG8aY+7e7/lR865GqqmLCAiCpzwAAIABJREFU4bk9RLo/udTucye7qFxfoL+6gHx/Ad6lPMLLc8RiMU49NYDP5yFUXeB4XNnyHBeVBcgv8HP65CDX39qC12svE28uamQ0NIzMrXD2KcONV9VmxeN1u10nk+L4mvw9ERE/dvLbCgSB/4G9zdhnsSdBngbebYzRWvtK7YiemFDKCYPx9ZmN1ZrAJkNDVRFn+6bpG5mlvMDvdjhZzakiTvvxh0AI+G8i8mD8K9/toBRMdthLZYZD0FLciMey3y6T4QWmJ5doPlCBP6DTh7fi8Xg4cKSa5aV1Bnsv7hXfUtJEOL4Odr6r263wVPJsVpjuY8AH4pdZwBtcjC97aZ6jlFJbGgjPU14SpChfk6tkSEzN7hlO/eBArnE9+zDG/BbwW27HoS632m/PNgqHfBwsbb5weefZMAAHjmjxpu0cOFLF6acH6e4I09xeDtgnA86E7H8e0eEBN8NTybFZYbqXYBe7A7gXeBX2sgnlAJ1Ymt0sC32RldqnxeU1JmdXOHFYj92SJTE1u29klusPlLscTXZzPYFV6SkWi+EbHwbsBPYn4gWcYrEY58+O4fN5aDlQ4WaIGaG2sZS8Aj/dHePc/qrDeDwWLSVNF7bSKZoZY3F5zeUolZO2KEz30fgyC4A5oHS7+9H1/jsXnxxCZUURxcG9T43LlMebqW3utV2v1wPrUFKSv+e4M+nxKpUMie1dWupKXI4ke9VXJkZgZ12OJPtpAqs2NTG7TOXiBKs+DzNFXpqL7QR2MrzAzOQS7VKFP+B1Ocr05/FYtB2q5IVnhxkZtKsRlwZLyCsNMV8wRc3KJN1Ds1QXb7ddssokLy5MJyIf2fDnYmB681tepOv9dy6xHdXExALL/r0N1WXS483ENvfTbiRiLxefmVnc0+0z7fHu5H6V2q3E9i5t9ZrAJkt+0EdlaR69I5rAJls6rIFVaah/YJLytVnGQ35CeSFKg/Y/zPNnxwA4eFSnoOxUu1QC0G3GL1zWWtLEWMhLcWSJnnM6jTibbChM9/vGmH+IX3xSRO6M/3w3oFvyOEmnlyql1BVdGIGt1QQ2mRqripiZX2VmYdXtULKaJrBqU2Md3XiIMRby0Lph/9eecxN4vdaF9Zxqew0tIQJBL10d4QsjRS3FTYTj04jDZ865GZ5y3mWF6bCnEX9YRB4BAly6RlY5RGs4ZSv7lY3pmQql9mwgPI/Hsmiq0RH8ZGqstqcR636wyaVTiNWmFnt6AHv96+F4Ajs7vcRkeIGWA+VafXgXvF4PrQcr6Xh+lPDIHNV1JbSUNHEqXshpubfH3QCVo65QmO7lqY4lZ2jmqpRSW4rFYgyEF6gpzyfg1+VfyZQo5DQ4Ns+xVh3sSRYdgVWb8owOAnYCmxiB7T5nT4FtPVTpWlyZqu2w/Zx1ddjPYXNJw4WtdALjw6xHdEtQpfZPM9lslHhVdQRWqb2ZmlthaWWdhird/zXZEs9xYsq2Sg5NYNVlFpfXKZkLE7FgqsxPU3EjYE8fBmg9qNWHd6upvRyf30OXsbcgyvflU1BZy3LAomp5gpGJRZcjVEqpdBWfQqz5q1J7kpjO2hivkquSpyaUj8/r0SnESaYJrLrMwOgs1atTTJb6qA81kOcLsry0xnD/NNX1xRQUBd0OMeP4/V6aWsuZmVxietJOVltK7e10ytfm6O8PuxyhUpnMzmwsHYBVSqnLDMZHA3UENvl8Xg9NNUUMjS8QjepZt2TRBFZdZqijB38sQjjk42B5CwB9nRPEYtCm04f3rCU+ct173h7JbilpIlxur4Od6OhyLS6llFJKZa8LI7DVOgKbCi11JayuRwlPL7kdStbSBFZdZq6rG7DXvx6saAWg53xi+rAmsHvVcsBezJ94LjdWIl7u63UtLqUy3cWppToEm81iOodYqT0ZDC8Q8HmoKs13O5Sc0BrfqkinESePJrDqMtEhe19SewS2lch6lL6uSUrK8ghVFrgcXeYqKApSXVfMyMAMK8trNBbVMV4eAMAfHtKDM6WU2oSlJyaU2rNINMrQxCL1lYV4PPpZSoWWukQCq4WckkUTWHWJSDRK/tQoANMV+TSV1jPYN83aaoS2Q5VYushsX1oOVBCNxujvnsLv9VNY18ia16JicZzJ2RW3w1MqM2m3pJRSmxqbWmI9EqWhSqcPp0prnY7AJpsmsOoSwxOLVK1MMFPoobaiCa/HS8953T7HKS9eB9tc1sx4mZeK1Rn6BqfcDE2pjKd5bHaLxXS7MaV2KzEK2FCpBZxSpaI0j4KgT0dgk0gTWHWJwa4hCiMrhEN+WkqaiMVi9HVOEgj6qG0scTu8jFdZU0RhUYC+rgmi0RitxXYhJy8xxrSQk1J7pNPvlVJqM4NawCnlLMuisaqQsalFVtciboeTlTSBVZeYOtcJ2OtfW0uamAgvMDezTFNbCI9H3y77ZVkWLQcrWF5aZ3RolpYSeysdgIWeHneDUyrj6RhsdorvA+tyFEplokEdgXVFQ3URsRgMTegobDJoRqIusdrfD9gJbEtJM51nxwBoait3M6ys0nLg4jTi2sJqpqvswliekUE3w1JKqbSkpyWU2ruB8DyFeT7KigJuh5JTGuN77g6MaQKbDJrAqkv4x4cAWKwuoSIvxHkTT2DbNYF1SkNrCK/PQ2/nBB7LQ2lrOxELSudHWVheczs8pTKWFpnLdjoGq9RurK5FGJtaoqGqSPvHFGuMF83SQk7JoQmsumBmfoXyxXGWAhaVtfb2Ob3nJ6ioKqSoOOh2eFnD7/fS0FzGZHiB+dll2qvbmCz1UbU6Tf/wrNvhKaWUUioLDE0sEONiMqVSJzFle1AT2KTQBFZd0N8/Tmht3p4+XNrMUP806+tRHX1NgsSU7P7uKQ6WtxIO+QhEIwyf63E3MKUykj0yp+ML2S2qA7BK7cqF9a9Vuv411QryfFSUBLUScZJoAqsuCJuNBZya6euaBKBZE1jHJU4K9HdPcrC8hXC8kNNsZ7ebYSmlVNqx9NSEUnuSmL6qI7DuaKgqYmZhlbnFVbdDyTqawKoLFnt6AeJb6DTS1zVJIOiltrHU5ciyT1l5PsUlQfq7p6jICzEfPzsaGxpwOTKlMpkmOtlNh2CV2o2LFYg1gXXDhUJOOgrrOJ/bAag0MmonT+t1lUQXPMxMLiHHavB69TyH0yzLoqm9nDPPDDPUP0N+axswQuHsMGvrUfw+fc6VUgoAy4KYpq/pSkROAjPxX7uBTwF/AawD3zHGfNit2HLdQHie8pIgBXl+t0PJSRsLOR1tCbkcTXbRo2QFwNp6hJK5Uda9EGpqvzB9+MCRapcjy16JqdmdJkxjRRvTRV6qlyd1wb9Se6Tjr0qllojkARhj7ox/vQP4JPALwG3ATSJyvZsx5qr5pTWm51d1/1cXJUZg9bjOeZrAKgAGRmaoWJlhvNRHS1kL/YkEVjSBTZaGlhAej8V5M0ZrSRNj5T7yI2sMnu93OzSlMoqOzGW3xImJmL7S6ehaoEBEviMi3xeRO4CgMabTGBMD7gNe6W6IuSmRNDXo+lfX1FYU4PVYOoU4CTSBVQAMn+3CF4sRDvloLmxkoHeKsvJ8QhUFboeWtQJBHzUNJQz1T1Prr7tQyGn6fJfLkSmVaTSxyQn6MqejReCjwKuBXwM+E78sYQ7QQhouGBy3kyYt4OQen9dDbUUBg+EFojHtwJyka2AVALPnu6gEwuUBfNNFrK9FaW6vcDusrNfcXs5w/wxTgyssVZcBC6wN9LkdllKZydJJxNlNDwDTUAdwPj7a2iEiM8DGrQuKgekr3UEoVIDP5wWgqqo4WXFeUTa2OzFnV769+lD1Ze1k4+NNt3YTbR5oLGMwPEjM66WqIvknE3LlOdYEVgEQHewBINZYy3DvLIDu/5oCTW3lPPZQN/1dkxS2tAGDBKcGicZiePRgXCmlVHr7FeA48P+KSD1QACyIyAGgC3tk9opFnKam7AHbqqpiwuG55Ea7iWxt91z/FJYF+V4uaSdbH286tbuxzaqSIADPnR3Fe7gqZe2mUrLavVJSnDZTiEXkJhF50O04clEkGqVoZoiIB0ItB+nrmsTr81DfpLN+kq2ypojCogD93VPU1R5kPt9D1dIE49NLboemVMbRUz7Zyn5ldQZeWvp7oExEHga+hJ3QvhP4AvA4cNIY85iL8eWkaCxG/9g8dRWF+OOj28odDRe20tFCTk5KixFYEXkf8HZAVzm7YGh0lsqlGcZDPuryWjkTXqCpvRyfXzu9ZLMsi3ap4tRTg1Ss1xAO+WgbWqG/e5TqUJvb4SmllFJbMsasYlccfrGbUx2Lumh8eomV1QjN1VqB2G0Xt9LRFMdJ6TIC2wm8ye0gctXQmU58sRhj5T6Ck/aoa7NOH06Zg/FKz5HRwIVCTuMd590MSTlg46wSETkoIg+LyA9F5G9EJF363qxi6RhsVtIqxErtTt+oPdrXVKMJrNsqSvLID3p1BNZhaXEQZYz5CrDmdhy5avpcJwCTFfnMDNovgyawqdMu9pqI4d45VmrtwlnLfT0uRqT2Kz6r5O+AvPhFHwM+YIy5Hft4/A1uxaZUptL0Vamd6Ruzk6XmancK+qiLLMuiobKI0ckl1tajboeTNdJiCvFuaLU658VGegDIa29l8NQ0ZeX5HDxcjRUvIuRm9bZcabeusZSRwRmqXi5wfz/+if6UxJJrz3MKJWaVfD7++0uAh+I/3wu8CviaC3FlKU1tspuOrCu1G/2jdkGdJp1CnBYaqwo5PzjD8MQCzTVZf/yTEhmXwGq1OmdFozEKpgZZ90BBgTC2vM7Bo9WMj88ntd0rybbneCft1jeXMTwwQ2C9hWW/RflCmM7eCUoKAkltN5ue53RKio0xXxGR1g0XWfFtJkD3RVRqVzR9VWp3+sbmKSsKUFKYvGMItXOJQk79Y/OawDok4xJY5ayhsVkqF2eZCPkIzlQAC7p9jgua28t56se9MF7IWIWP5pEl+ntGOXZVk9uhKWdsnDe07b6IoLNNdiWe4VRXleDx7H1lTMY83gxtc6/t+vxeWIGiouCe486kx6vUfswtrjI1t8I1ByrcDkXFtcST1t7ROW49XudyNNkhbRJYY0wPWrUu5YbOnKcsXsApMhzD47FoaC5zO6ycU11fTCDoY2pgBcoDNI+sET5jQBPYbHFSRO40xjwI3A08sN0NdLbJziW2VwmPz+Gx9pbAZtLjzcQ299Puenzd2Nzc8p5un2mPdyf3q9RW+uPrX3X6cPpoqinCsqB3JPX9ULZKiyJOyj3T5+xqt7MVVUyMLlLbWEogmDbnNXKGx+OhqS3E/OwKK9WtACx3d7oblHLSe4EPi8gjQAC4x+V4lFJKZaFEBWKdqpo+gn4v9RWF9I3OE41qzQYnaKaS4yID5wDwlB6FCa0+7Kbm9nI6z4YJFh4Bnsc/1u12SGofNs4qMcZ0AC93NSClMtTFbXS0gqdS2+kfs0f5dA/Y9NJaW8zg+AIjk4vUVxa6HU7G0xHYHLYeiVI2Pcyqz8IXbQA0gXVT4rn3zIaYKfRQOTfO3OKqy1EppZRSKlP0js4T9HupCuW7HYraoKU2vg5WpxE7QhPYHNbXO0bF0gLDFT6WRz0UFAUor9KzQm4pKApSWVPE/FiEocp88tfX6Xm+y+2wlMoA9pQsS+vVZin7ddWJd0pd2dLKOsPjC7TUFuOxtD9MJ621JQD0aALrCE1gc9jQM2cAGK6oZXUpQnNb+YW9X5U7mtvLiUZiTJS1ADB2+gWXI1JKqTShGaxSV9Q7MkcMaK8rcTsU9SKJQk49I7Nuh5IVNIHNYXOddnK0VnwYQLfPSQMXXoP8QwCs9BsXo1Eqs+gJuOykr6pSO9MdT47a6jWBTTdayMlZmsDmsEC8SJAnVo9lQWNryOWIVG1DCYGgl+hSiHUPFE0OakenlFJKqW11D8UT2DqtQJyOWmqLWVmLMDK56HYoGU8T2Bw1PbdM9ewUY6X5rEx5qa4vIS/f73ZYOc/j8dDYWs7aAgxUlFO1MMfg4KTbYSmV5vQkT3a7WIdYKbW17uFZSgr8VJTkuR2K2kSikJNOI94/TWBzVM9zHQQjEfoqWojFoPVghdshqbhENeLh8ha8MRg4ecrliJRSyn2aviq1tZn5FSZmV2irK9HlFGnqYEMpAOcHNYHdL01gc9TYs88AsJDfDkDroUo3w1EbJBLYlWArADNnn3MxGqUygIVmNzlAX2KlttY9bFe31fWv6aupuoiA38O5gWm3Q8l4msDmKKv/BaJ4iKxXUlKWR6iiwO2QVFxhsb2dTmSphBVvgPyRTmIxPXRTSuUmHU1SanvnBu2kqF0T2LTl83porythKLzAwvKa2+FkNE1gc9Dcwgo1U2MMhOqJRTy0HqrUA4Q00364EmIW3dXNVM/NMDqqZ+uUUrlNT+QptbWOvmk8lnVhmqpKTwcby4gBnYMzboeS0TSBzUHnnzpD3nqEwfJWQNe/pqN2qQIgXNSONwadjz3jckRKpTHNa5RSOWxlNULPyBytdcXkBXxuh6Ou4HCjfYLh3IAmsPuhCWwOGn32CWLAkq+JYJ6P2kY9W5duQpWFlFUUsEotEcvH9AtPuh2SUmlOZ5FkK31llbqyzqEZItEYh5vK3A5FbaO9vhQLTWD3SxPYHBToP8t0Xg2xSJC2w5V4vfo2SEf2NGIPY0X1lA93E9Xpc0ptztLPRnazU9hYLOpyHEqlJ9NnLzPSBDb9FeT5aKopomtohpXViNvhZCzNXHLM8OAEdVOT9FQeAODQVdUuR6S2kphG3FvRTsXCIp3Pd7sckVLpSdNXpVQuO9MziceyLkxPVenteHsF65EYZ/um3A4lY2kCm2PMgw9jxSym8lrIL/RT3xxyOyS1hcqaIkpD+Sz4mli3/HT98Aduh6SUUkqpNDK3uErX0CwHG0ooyPO7HY7agavb7O0ST3dNuhxJ5tIENsesmMeZLKgnRpADUo3Ho6uL0pVlWcjVNYCX0eJWfN3PahVOpVTO0t5Pqcud7pokBlxzsNLtUNQOHWgoJS/g5VT3hNuhZCxNYHPIRHiGhtFhessPAyDHa1yOSG3n8NW1APSVH6JhcoqBziGXI1JKqdS6cJpVT+ApdZlnO8cBuKZdd5TIFD6vh6tayxmbWmJofMHtcDKSJrA55Jlvf4cYQabzmqisKaKqttjtkNQ2ikvzaGwNseirZslfypn7vuV2SEoplWI6U0ipzSyvrvPM+XGqyvJoqCp0Oxy1CzccseucPHZm1OVIMpMmsDkiGovhee5HDJYcBjwcO1GPZelBQSa46ro6AHpDV1HScZLVtXWXI1Iq3cQgpv1ZttPxV6UudbJjnNW1KLccq9Vjugxz4mAVAb+Hx86M6vKwPdAENkc8+8OnqZmep7f8KoJ5Pq0+nEHaDldRXJbHcPFBipbhqXsfcDskpZRSSrns4VPDANx8rNblSNRuBQNerj9Uxdj0Eh39026Hk3E0gc0B0ViMiW9/iYGyo0StINe+tAl/wOd2WGqHPB6L617aBJaX3tDVrP7gG6yt695hSqnckBhZ0jEKpS7qHZnjhd4pjraEqC0vcDsctQd3Xd8IwLcf63M5ksyjCWwOePir36J6cp6u8msI5Hm5+voGt0NSu3T0mjqKy4L0lx6leMHiR1/6qtshKaVUauk0O6Uu+PrD9t7wr7mp2eVI1F4dbCzlYGMpz3ZO0DMy63Y4GUUT2Cw3PTlL/oP/zpnq24hZfm696yDBPB19zTRen4fbXnkILA/P195OyY++w3RYy68rpZRSueZkR5hnzo8jTWUX9hRVmemNt7cD8Pn7DNGonqTbKU1gs9yPPvNJhouuZ6qgnuYD5chxXSeRqVoPVXLkeC3zwUr6yl7K43/7F26HpJRSSWehU4iVSlhZjfCF73Xg9Vi8/dWixZsy3NGWEDddVUP38BwPPjPodjgZQxPYLDY1OU1gOMJg6RFKygP85E9fpR1dhrv9VYcIVeUzXHIIz2QRHc+dcjskpZRKEU1hlbr3sV4mZ1d4zU3N1Ffq1jnZ4OfuOkhB0MdXHupkam7F7XAygutzSUXEA/w1cC2wArzTGHPe3aiywyP/8U36y2/EYo2ffuvNBIKuv9xqn3x+L69787V84ZMPc67yBubuf4DD1xx3Oyy1A9rXJVMM3Ss0+8U0gc0I2tclTywW44fPDVOY5+O1t7S4HY5ySGlRkDe9vJ1/+k4HD54c5I13tLsdUtpLhxHYnwHyjDG3AH8A/G+X48kaMwOLRD0+Gtq9FJfmuR2OckhRSR4vvasZLA+Lc8Vuh6N2Tvs6pVQu0L4uSQbCC0zNrXD8QAV5uptEVrn16jqCAa/uC7tD6fDuvw34NoAx5lERucGpO37wvgcZPO1saWrL2lAIcZs3WGzjiMA+34weyyK6y/tYW6sGP9z88mv21bZKP9e95BBP3XeOBV8DX/jY5/Z0H3t5Tzlhp+0eue0YL3npS1IQUcokra87PdjL/Z1POjpCFfD7WF1bd+z+ktlu1LucpGhUOkj8J/3R4JOcndz9QF66v5dva7mWG1oOpSCilElaXzc5u8yjZ0aJOFjsprAwwMLCqmP3l8x2e4btSrXH2yuSEZJyUTDg5Xh7BU+eHeOeBzvJ28OsyXR/Lx9pLuNQY5kjbaZDAlsCzGz4PSIiPmPMpr1+KFSAz+cFoKrqyqNPfU8Ms+DL4fLifshbn+Kqq9v2dTfbPc/J4EabmdZugXeMGdqYXc3O9/gLDzzPa157p9thOClpfd2/PfAAw7EzTsVpS/3x/t7bDYB3vWDfn99M+vxnYpt7bbeypIxzEzDp72ByL++PNH8vhzvGuPuG65MbS2olra+7/5kh7nmw06k4M1LA5+HlNzRTWhTc831k0uc/U9vdS5s/cVMLT54d494s3Rf2aGs5H3nP7Y7cVzoksLPAxlfZs1UnBzA1tQjYb4xweO6Kd3znL97GqcefYdO1UVssl7Kszf+UGE0NBn2srEa2u5tdFUva8robLg8GfaysrL/44hff4LJLjpx46bbP05Xs5Hl2mhttZmK7d7/rZ3j0/h/teRQ1EPCxuurCqMRO2rUsbrnr9bt6Xtz6x7gLSevr3nPzm3mk2+BkkZvCwiALC6kvJrHXdo/WNmVcX+dWu5n2WN967Cdo6KpjZX1v/VW6v5dvbD6kfR07e3/ccXUt9aF8R7cbKS3NZ2ZmybH7S3a75SVBVpdWCS/tbaQt0z7/mdjuXts8VFvEH779JZfkGbuR7u/lxuoix/q6dEhgfwS8HviyiNwMOFZWtbm1iebWJqfuDsitD6BKb6HyEHe/+XV7vr2+l1MuaX1daX4hr7nK2REcfX+odOH3+XjF4Wv3fHt9L6dc0vo6v8/D0ZaQU3cH6PtDpQ/LsjjYULrn2+fSezkdEtivAT8pIj/GHkJ8h8vxKKVUMmhfp5TKBdrXKaWSyvUE1hgTBX7N7TiUUiqZtK9TSuUC7euUUsmWDtvoKKWUUkoppZRS29IEVimllFJKKaVURtAEVimllFJKKaVURtAEVimllFJKKaVURtAEVimllFJKKaVURrBiMec2g1ZKKaWUUkoppZJFR2CVUkoppZRSSmUETWCVUkoppZRSSmUETWCVUkoppZRSSmUETWCVUkoppZRSSmUETWCVUkoppZRSSmUETWCVUkoppZRSSmUETWDTjIg0ux2DSg4ReZnbMSiVLrSvy17a1yl1kfZ12Uv7Ovek7T6wItIO/DHwI+CkMeZxEfEYY6JJbrcV+BDwOPCEMebJZLa3od024APAHPBBY8xsCtpsBX4H+AbwgjFmUEQsY0zS3hQiYsV//O/APxpjziWrrS3a/zTwXWPMl1PYZivwm8BvA7cYYx5LUbttwPuA7wLPG2NMij5DbcD7gfuAM8aYF5L9vspk2tclv6+Lt9tKCvs77eu0r1OX0r5O+7okta99XQ72dWk5Aisih4C/wu7kVoBPAqTgBXoV8AXgCWAN+Gwy29vQ7n8GHgQ+B/xOipLX1wD/AkwAdwK/B5DsN2P8/suANwC/lsy2NhIRX/zH48DPikhNCtq0ROQ9wD9h/wP7e+C5ZLcbb/uGeHsdQE08hlR8hm4EPgO8ADRj/0NL+vsqU2lfl7IDupT3d9rXaV+nLtK+Tvs6p2lfl9t9XVolsPEzGgDFQKEx5lPA14FTIlKXxHbz4z82AP9mjPlr7BfraREpT0G7LwCngDzgmyLyZyLyy/HrOPoabWizBHjIGPMnwEPYnV3iOkl7X8Q7nP8HeBS4TkTuTlZbGxlj1kXECzyD/f56RQqarQDGgJ8yxnwIaAJak9mgiNTGf/QBfcaYPzfG/A0QFpEPxq/j+Ou7od1SoN8Y8+fAD4EeESmMX8fa6va5Rvu65Pd1L2o35f2d9nXa1ynt69C+Lmm0r8vtvi4tphCLyG3AbwEFwLeAh7E/dMPYZ5LagDDwp8aYHznY7suBXwcGgE8AJ4DnjDHnReQm7KkubzDGrDrV5ibt/gMwCnwUqAf+K1CJfWblGmPMeBLa/BtAgDuACHA3MB6P43ccbNNjjImKyKeAvzbGPBu//E7gLHAb8E5jzGucaG8H7f4kUA38GLgHGALebYzpc7jdvwU+kWg3/rcG4MPAe40xM06096K278D+DEWBf8Y+OXUC+CdjzNn42e/7geuMMZNJavcL2O+hQWAE+B7gBeaBXzPGdDvVbqbSvi75fd0m7Sa9v9O+Tvs6tK+7hPZ12tftt60dtqt9XY72da6PwIpIEfYUh08BHwQOA5XGmMH4sPifGGNuxD6z84sOtlsDvBf4O6AP+CNg1hhzPn6Vnwf+wxizKiIlSWq3J/7zrdgd/EeMMc8ZY76PvXbhXUlosw/4A+zO7bPYHdzfGGNehf1m/SMn2gR7WoOIBID/BPySiOTF//SQMWYE+zHPiIijU06u0O4ccA12Z18GrDnVyb2o3Tf5o7btAAAgAElEQVTF2w1u+NsgcBR4GTh71kpEGoHfB/4Se7rST2EfKNTZf5aS+JqUbwFvS2K7bwLCxpi++MHBfzXG3Ap0Ar/rVLuZSvu65Pd1m7Sbkv5O+zrt67Svu0j7Ou3rtK/bH+3rtud6AgtcB9QYY75njHkKOPCiv1sbvhsH220DquPt/iXwPHCLiByM/z0I/KuI/CZwj4hUJKHdv4q3exR7usn3N0ypWcBeLO10m38Zb+tG4Pp4+/8Wv94A9pQTR8Q/zK8HvoT9Ot8KF+fNG2OWsM+Q/o6IhJLdLnBV/PIz2GtDmuNnZJPV7m3xyxOfs08DN4PjaweOASFjzEPGmG8A7dj/zL4djyExrcYCHkliu3XYU00S+uPfxx1uN1NpX5f8vu7F7aakv9O+Tvu6+Hft62za12lfp33d/mhftw1XEtgNLzzGmIeB/xK/PAgsEl8QHX8Tvk9EHsB+8T7nYLuPAqMi8rr4Rd8FQkBIRMqAXwb+HbuD+CVjzAR7tIN2a7DXLbwf+AsReQgoZB8d+zZtfi9+/8Px339fRB7EfqM+sNc2N2k3BvQYY96NPQ3hnSKy8YOAMeYHwJ8C60ls913x99bngduNMZ81xvQDf4I95SVZ7b5TRMrMxQX2c0CRiDTtp81N2r2Pi5+hGmAK6MWeTvM48GYRuR97Kte+Dha2aXcS+x8oIvIm4L/H38tNwH/sp91MpX1d8vu6HbSblP5O+zrt6+K/a1+H9nWbtKt9nfZ1+2lX+7ptpGQNbPzJ8QB/C/yuMWZaNin7HP8Qvt0Y81ax53Zb2HOva4wxHXto1wICwP8iXsI80a6I+LGnk7wCeJcxZk1E/h57Hv2T2PPaP2yMOZmCdj8D3G+M+ScROQLkGWOeSXKb/wh8xxjzBRE5AXjiZ0qdeKwXSmuLiM8Ysx7/+WvAV40xn99tOw60+zVjzOfiv/uNMWspavfC442fhfWbPUxvudLr+6LrvQu43hjza2KXPV/A/idSZYzZdSe3x3YTe95Fsc/kndptu5lK+7rk93V7bHff/Z32ddrXbdKu9nXa12lfp32d9nUuSMkIbPxJKQJ+BntPrEvIxXnjh4CzIvIHwMeBEmPMzF46uXi7Mf4ve/cdHkW1PnD8m82mFwgQkCY9BwUEQQRBir2LV8VeuaJSrCgqqGBDBAQbCGJBvfrTaxfLtVJEOiJKO0jvpBCSQHp2fn/MZpJASN3NbHk/z5Mne2Zm530nhmPenTnnQAt33OJxB8WPORQAv2L+Ejzl3hcCHNRar9FaX1GTTq6GcV1Arnv/xpp0cjWIWVgq5uqaFK8VxC29v3iWOIAZwL3KHPheKzWIO7I4bk07uRrGvbdU3H016eQqiGt9+qRKPkFrCqxSSo3FfIynodb6YE06uVrEnYk52+RuX+jk6pL0dZXGrXVfV8O4te7vpK+rNK70dUFE+rpK40pf5/240tfVXVyf6+u8WsCqkmmWw4FbMT+pu0Ypdbr706NQMH+Y7k+S/g1ch/kP8DJdw8WmlTmBAEqpaMypvb8BrlBKdXHHcrrj7sZc3Lq5UuonIANzeveaXm9N42YCn9sQ8wsvXmvpRxKK3N9/AiZizhJX13FfsClunVyv+99TJDDS/ZWHOdPiBn+K66+kr/N+X+eBuDXq73z93345caWv84O4/kr6Ounr3HGlr/NyXOnrKuaVR4iVUv8Cbsb8D/yO1nqVUupcrfXPypyZ7GZtzmJVfHyI+4d3BzBPa72lFnFvxBxcPENr/ZdS6mzMBaz/DZyutb6h1PGlH8OI1Fpn+Utcf7nWUu+zHseQuJ6Pq8xPux2YU59/qbXe6k9x/ZX0dYEb11/+7QdbXOnr7CF9XeDG9Zd/+8EWV/q6inm8gFVKNQbexfxEaCDmmlc3KaUitNZ57mP+AKZqc2yA9Wy5B+K+g7nG12mAAn7TWn/m3t8IcwD2q1rrb5RSocWfqPhb3GC6Volbpbh2/RvySFx/JX1d4MYNpmv1s7jS19lA+rrAjRtM1+pncaWvq4Q3HiHuh7nu1nLMKbyTlFLtgMhSxzyC+Tw1HvxBdQVcWusVmItIL8ecPl2546S6tz/jbtf6F9LGuMF0rRK38rh2/Rvyi07Oi6SvC9y4wXSt/hRX+jp7SF8XuHGD6Vr9Ka70dZXwSAGrSi3e667qhypzfMSjmI+bjAIeKHXMT8AopVRY6ffWIG7p59N/AloopQa4PxH8EziMOV16sS8wpzN3+lvcYLpWiRv4cf2V9HWBGzeYrlXiSl9XGenrAjduMF2rxA3gvs4wjBp9JSUl9UpKShqUlJQUXWqb86hj6rm/X52UlDTW/TqspjHd729XfC5325GUlBTufn1HUlLSN6X2TU9KSrrB/TrE3+IG07VK3MCP669f0tcFbtxgulaJK31dFX5e0tcFaNxgulaJGxx9XbXvwCqlQpRSLwMvAoOAF5Q5eLx4qumWytQI6KHMWa+uwH23V9diqmu3y4EblVKXuM/n0lrnK3ONop8Ah1JqtDIXrW4EFM8cVtvBvnbEDaZrlbiBH9evSF8XFHGD6VolrvR15ZK+LijiBtO1Stwg6Otq8ghxI6CF1vpMrfUQ4AygPoAyZ5v7AXN9oURgCPAdsEJr/YxnUgb3OW9U7tvk7rg/Y65ZNApoiDlO4w+t9cd+HjeYrlXiBn5cfyJ9XXDEDaZrlbjS15VH+rrgiBtM1ypxA7yvq9IsxEqp24COmD+cRcAE4AngAszBv1Mwn6nejTm7Vbr7feFAqNY6pybJlYr7k9b6F/e2/wDPY64rlggsw1z36tfiuO7jrNnx/CFuMF2rxA38uP5K+rrAjRtM1ypxpa+rjPR1gRs3mK5V4gZvX1fhHVhlPlbyJHApsBRzlrmRWutHtfnISAFwFXAIOBVYrrVOVyULWefXpJMrJ+69SqlH3LsPAAbmrHiXADu11p+VjuuOXZN/9HUeN5iuVeIGflx/JX1d4MYNpmuVuNLXVUb6usCNG0zXKnGlr6v0DqxSajLmp29fK6VOBr4Humut05RSUVrrHKVUf2Cw1voeTyV2VNxOwDdAX8zb33nAbKAx0Mrf4wbTtUrcwI/rr6SvC9y4wXStElf6uspIXxe4cYPpWiVucPd1ld2BdWDego5XSsVprddj/rCmKPMxkm+VUuOAZ4G17vfUegrmcuKuc8d9A7gF6K+1fg/4BVhQ23h2xg2ma5W4gR/XX0lfF7hxg+laJa70dZWRvi5w4wbTtUpc6esqLGC11i7gV6Ab0NK9eQyg3K/HYo6PuFFrPcv9nlrPaHWcuGMxJxXYVyrGn1rrT2sbz864wXStEjfw4/or6esCN24wXavElb6uMtLXBW7cYLpWiSt9XVVmIV6MOd3ypUqpRKA98Jc2x0Es0Vq/pbXe5YXcjo7bwR03o/gAT3SqPhI3mK5V4gZ+XH8lfV3gxg2ma5W40tdVRvq6wI0bTNcqcYO4r6u0gHX/ICYDIcA7wEvA717O63hxlwRi3GC6Vokb+HH9lfR1gRs3mK5V4kpfVxnp6wI3bjBdq8QN7r6uSsvoFFNKdQf+1rVftLpagiluMF2rxA38uP4q2P47BVPcYLpWiSsqE2z/nYIpbjBdq8QNPtUqYIUQQgghhBBCCLtUZQysEEIIIYQQQghhOylghRBCCCGEEEL4BSlghRBCCCGEEEL4BSlghRBCCCGEEEL4BSlghRBCCCGEEEL4BSlghRBCCCGEEEL4BSlghRBCCCGEEEL4BSlghRBCCCGEEEL4BSlghRBCCCGEEEL4BSlghRBCCCGEEEL4BSlghRBCCCGEEEL4BSlghRBCCCGEEEL4BSlghRBCCCGEEEL4BSlghRBCCCGEEEL4BSlghRBCCCGEEEL4BSlghRBCCCGEEEL4BSlghRBCCCGEEEL4BSlghRBCCCGEEEL4BSlghRBCCCGEEEL4BSlghRBCCCGEEEL4BSlghRBCCCGEEEL4BSlghRBCCCGEEEL4BSlghRBCCCGEEEL4BSlghRBCCCGEEEL4BSlghRBCCCGEEEL4BSlghRBCCCGEEEL4BSlghRBCCCGEEEL4BSlghRBCCCGEEEL4BSlghRBCCCGEEEL4BSlghRBCCCGEEEL4BafdCVRXSkqWUZ3jExKiSU/P9lY6Hif5eo8/5QqSb3UlJsaF2BbcC6Sv8y2Sr/f4U65gf77S18nvizdJvt7jT7mC/flW1NcF/B1YpzPU7hSqRfL1Hn/KFSRfUT3+9vOXfL3Ln/L1p1zB//INNP7285d8vcuf8vWnXMG38w34AlYIIYQQQgghRGCQAlYIIYQQQgghhF/wuzGwQgjh65RSjwGXA+HADGABMAcwgLXACK21y7YEhRBCCCH8lNyBFUIID1JKDQT6AH2BAUBLYCrwuNa6HxACDLItQSGEEEIIPyYFrBBCeNYFwN/AF8Bc4BugB+ZdWIDvgXPtSU0IIYQQwr/JI8RCCOFZjYBWwKVAG+BrwKG1Ll4qIguoV9lJEhKiqz0DYGJiXPUytZnk613+lK8/5Qr+l68QQgQSKWCFED5n/8FsEuIiiAjz3SncK5AGbNRa5wNaKZWL+RhxsTjgUGUnqe7aa4mJcaSkZFXrPXaSfL3r6HyLXC7yC1wUFJpfhUUuCopcFBUZuAyDoiKDIpeLIpdR8mXtK9nuKr3f5cLlMjAMc3C3YbhfG+ZnNSEh5hJ+1kJ+IRzVNl/FxkRw5EhecZOS3SGEuL87QiDEEYIjJASHw2w7HCE4HQ7ze2gIoe7XoaEhOB0h7u0OQt2vQx0hhIY6cJZ67QhxHx9qnjvk6CSq8LOta1I8CyH8TXpWHg5HCPViwj1yPilghRA+w2UYjJi6kLyCIs7t0YIbzkuyO6WaWATcp5SaCjQFYoBflFIDtdbzgYuAeTbmJ+pQXkERGUfyyTicR+aRAg7n5JOdW8iR3EKycws47P5e3C7eJwJLuNNBVISTqAgn0ZFO63V8dBhX9GtLbFSY3SkKIYTHGYbB03NWsuNAFs0TY3jm3708cl4pYD1k6dLFHDiwn0GDrrQ7FSH8UlZ2Pve9sshqn9KuoY3Z1JzW+hulVH9gOeY8AyOAbcBspVQ4sAH41MYURRXk5BWSciiH1IxcUg7lcCSviJ37M0k5lENaRi75hTKJtKi6/EIX+YX5ZBzJP2ZfZnYBw6/obENWQgjhPfsPZjPmjaVWu0dSosfOHXAF7H9/3cyKjclWOzQ0hKIio4J3VK5nx8Zcc3b7Co/p3btPrWIIEcz+2X2I5//zh9V+esjptGgca2NGtaO1Hl3O5gF1nogAzGJ0T+oR9qQcZk/KEfN16hEyyykm6kqoI4SYSCcxUWFERzqJjggjJspJjPt7dGQYMZHm3bqYyOJjnESGhxIeFkqoo+LHXe1+zLU6/ClXMPNNTs6kyGVQWGQ+mp1XUGR+5Zvfc/OLyMkrLPVVRHapdvFrgEF9W9t7QT7Orr/rvvtuLr/9toDs7CMcOnSI22+/g4EDzznmuD/+WMl//jOHsLAwkpMPMGjQVfzxx0o2b97E4MHXc+edt3PTTYM55ZRubNu2lfj4eMaPn0BUVFStrkEIX/bZgi18u2SH1R57cw/aNa90+o8qC7gC1i7ffTeXHTu2M2zYPcfs++uvP3nttZdwOp3ExcUxbtyzhIaGMmHCU+zfv5/CwkIeeOBhOnc+xYbMhbDXt0u289mCrVZ7xoP9iQyXrklULju3kG37MtmyN4OtezPZujeTwzkFXokVE+mkYb1IEutH0TA+koS4COrFhlM/xv09NoLI8NAqjaEU/i8kxBw36wx1EOmZIV3CB+XkZDNt2nQOHUpn6NBbOfPMATidx/7/KTk5mTlzPmTjxg08+eSjfPzxl6SkJDNmzMPceeft5Obmcv75F9GtW3dmzHiZr776jOuuu8mGKxLCu3LzCxk+daHVjopw8vK9Z+IM9ezCNwH3V+I1Z7cv86maL3yy+9tvCxgw4Cyuv/5mFi1aSGZmFgsW/MIJJzTjqaeeZ+vWzaxcuVwKWBF0nnl3Jdv2ZQLQtGE0z97Ri4wF89j5n/dofOMt1D/rbJszFHY6nFPA+u0HWb89nfXbD5KakVvrc0aEh9K8UYz5lRhL80YxNGkQRYO4SByOwLijKUQgsfPvum7duuNwOGjQoCFxcfEcOnSIRo0aHXNc27btrJsUzZo1JywsjLi4ePLz8wBwOp1069YdgM6du7J06e91kr8QdWn1Pym8+tnfVvum85M4u3sLr8QKuALWF9188+28997b3HffMBITG3PyyZ3ZuXOH9dhx27btadu24kdZhAgk+QVF3P3iAqt9WZ/W/Kt/W3a/OInsDesBcOXm2JWeqEMFhS7WbT/Iqo3JrNyUQl5+UY3O0yIxhrbN4mnbrB5tmsbTrFE0oQ5Z6lwIUXNabwTg4ME0jhw5QkJCQrnHVfbgRWFhIf/8s4kOHZL4++81tGnTztOpCmEbl2Ew4f1VbN2baW2bOrIv9WMjvBZTCtg68NNP33PxxZcycuT9vP/+O3z99ee0atWGDRvW06/fQPbs2c3s2a8zfvxzdqcqhNftSzvC2NnLrPZD13WjY7NYNt1xm7Wt/tnn0uCiS2zITniLYRhs25fFwjV7+P3v/RS5qj6GLSbSyUmtG9CpdQIntUogsX6UPKorhPC6gwfTuO++YRw+fJhRox4hNLTmS7t98MG7HDiwnyZNTmDo0GEezFII+yQfyuHRmUus9mkqkWFXdPb6/6OlgK0DHTt24tlnxxMdHY3T6WT06LE0bNiI559/mpEj76SoqIj77htld5pCeN3Sdft5Y+56qz1tZF8iM1PZPPxBa1vz+x4kpos8Tu/vdicf5scVu1j0974qHR8T6eS0jo05tUMiHU+sT7h/rgEshAgg3bp1L3duk9K6dz+N7t1PA6BVq9a89tobAMTFxfHhh59Zxz322JNERHjvjpQQde27pTv4dP4Wq/3ojd1Jalm/TmJLAeshF1982XH3derUmbff/s8x2+WOqwgms+euZ8m6/Vb7zdFnkbVoITvee8fa1nbKNJz1y39ES/guwzBYvyOdbxdvZ+POQxUeG+Z0cOYpTbngjDY0ig3DIXdShRB+4J13ZrNq1Ypjto8ZM45mzZrbkJEQ9igscjHsxQXWk1QhITBz1EDCnHU3bEcKWA8aM+ZhMjMzymyLjY1l4sSpNmUkhP1cLoOhk+ZR/MBo705NuPOyTux+6UWy15qD/UPCwmg/fRYhMmbRb2QczuOzhVtZ9Nfx77CGOR2c3b05/bs2o2nDmDL7ZFIkIYQvO/rGxO23D+X224fW6FyffjrXEykJYbstezJ47v1VVvvK/m25tE/rOs9DClgPmjBhst0pCOFTMg7n8cBrJbMtDr30ZHqpBmXGu9YbcBZNbr7VhuxEde1JOcysr9ezO+VwufsbJ0RxyRmtOKPTCR6fMl8IIYQQ9nnr2/X8/nfJk3QT7+pN44RoW3KRAlYI4RUbdqQz+f9WW+3nhvaiYX4Gm4fdaW1rds/9xHbtZkd6oooyjuTz+pdr2bSr/EeDB5/VjnN7tKzTR4eEEEIIUTeO5BZwz0u/We0TG8cy7vaetk6mKAWsEMLjvvxtK1//vt1qvz5qALnLFrN9zlvWtjaTpxF2nCUJhP2WrNvP7FITbhVrEB/B3YM60755PRuyEkIIIURdWbExmde/XGu17x7UidNPamJjRiYpYIUQHmMYBk++tZw9qUcAaHVCHE/eehp7X32JI3+tMQ8KDaXD67NlvKsPMgyDzxZs5bulO47Z9/B13TipdQMbshJCCCFEXTIMg/unzWfL7pK5fV65rx+xUWE2ZlVCClgPWbp0MQcO7GfQoCvtTkUIW+TkFfLvF+ZZ7Sv7t+Xins34Z+jt1rZ6/QfQ5Jbby3u7sNnnC7fyzeLtZbadeUpTbj5fyePBQgghRJBIy8jl4dcXW+0+nU/gjktPtjGjY0kB6yG9e/exOwUhbLM75TBPTvzVaj96Y3dah+WUHe868j5iu51qR3qiAmu3pTH14zVltt1ygWLgqbIshBBCCBFM5q/ew3s/aKs95qYetG/he0OGfKKAVUqtBorvUW/TWtf4Fs3nm79hdfLfVjvUEWKtU1RTpzbuwpXtL63wmO++m8uOHdvLXfD6rbdmsWfPbg4dOkRWVgb/+tdg5s//lV27djB27FM0bNiQJ554lIYNG5KenkaPHr24664RtcpZiLry2197eee7jVb7pXvPxPhjWdnxrpOmEtZAHj/1JYVFLh6asZjMI/nWtlsuVAzsJoWrEEIIEUwMw2DM7GUcOJhtbfts4qVkHMqu4F32sb2AVUpFAmitB9qcildFREQwdeqrvP/+HJYs+Z1Jk6bx7bdf88svP3LNNdezf/9epk59ldatmzJ48LVovRGlOtqdthAVmvHF36zUKQBEhIcy/YH+7Cs93tXhoMPMN2W8q485eh23Uzs0YsSVXXDYOKOgEEIIIepeakYOo19fYrUvOL0l157dgfCwUBuzqpjtBSzQFYhWSv2Imc8YrfXSmp7syvaXlrlbmpgYR0pKVu2zrKWkJLMYjYuLpXXrNu7X8eTn5wHQrl0S8fH1CA0N5eSTO7Nz53YpYIXPKnK5GDppvtXud0pTHrrhVJZcfZ21Tca7+qb/LdvJf+dtttrP3tGLZo1ibMxICCGEEHZY8Oce3v1fySPDT9x6Gm2axtuYUdX4QgGbDUwB3gQ6AN8rpZTWutDetDyrshsbO3ZsIzc3l6KiaNavX8vFF19WN4kJUU3pWXmMmv671b57UCe6JbjKFK8y3tU3vfnNehavNRchb1w/iufv6m3rOm5CCCGEqHuGYfD4m8vYl1byiPCshwb6zaSNvlDAbgI2a60NYJNSKg1oCuwq7+CEhGiczurd0k5MjKt1kpWJi4skOjq83FgxMRHExkaSmBhHbGwkubkRJCbGUa9eFJGRYTRoEENERDjPPDOW1NRULrzwQvr06eH1nD2lLn6+nuJPuYLv5fvHxmTGzS55zGTWY+cQumY5mx+fbm077a03iGjUsFZx9mbup2F0AyKc4bU6jygx86u1LN+QDMBFvU5k8Fntbc5ICCGEEHXtYGYuD80omWX4/J4tue6cDjZmVH2+UMAOAboAw5VSzYB4YN/xDk5Pr95g4rp6hLhfv/Po149yY1133W2Aue/ccy+1Xnft2ouuXXuxb99e6tVL4LnnXrTy9YXHnqvCVx7Rrgp/yhV8L99P5m/m+6U7rfashwaQ/Mo0jqz509zgHu+aaTighnnnFuYyauGTAAxs0ZfBSYOq/F5fK/Z9yVeLtlnF6zVntefCXifanJEQQggh6trCNXuZ833JxJuP33IabZv5/iPDR/OFAvYtYI5SahFgAEP89fHhMWMeJjMzo8y22NhYJk6calNGQtSeYRg8MnMJqRm5AHRoUY/R13Rhy93/to6p138AnUfdW6uCe03KOt74+12r3TWxc82TFpYN2w/y1aJtAFzet7UUr0IIIUSQMQyDJ99azp7UI9a2WQ8NIKyaT7X6CtsLWK11PnCD3Xl4woQJk2v0vqZNm/HGG3M8m4wQHpCdW8jIlxZa7WvOas/ZrcLYMtxz67sahsHkla+xI6tk1MDzZz5BfLjcUa2twiIXkz8y75C3bRbPFf3a2pyREEIIIerS0Y8Mn9ujBTecl2RjRrVnewErhPBNO/Zn8dScFVZ77M09aLT9L7Y/7rn1XZOzU3lq6SSr3aNxV4Z0vrHG5xNlPTarZLzy2Jv9Z1y9EEIIIWrvtzV7eafUI8Njb+lBu2b1bMzIM6SAFUIcY94fu3n/x01W+5X7+pHx5nQOFI93DQmhw6y3arW+67dbf+S77T9b7VE9htO2Xusan0+UtS/tCGmZ5jJdzw3tJbMNCyGEEEHCMAyemrOCnQcOW9v8+ZHho0kBK4QoY+p//2Tt1oMAxEaFMW1YL7YMH2rtj+/XnxNuHVLj8+cX5fPAgsetdnhoOJP7jcfpkO7Ik8bOXgZAYv1ImjaUdV6FEEKIYJBxJJ8HXl1ktc/p3oIbz/fvR4aPJn8xCiEAc7zknZPnW+1zurdg8ClxZce7jriX2FO71zjG+jTN9DUljyBf3eFyzmp5Zo3PJ8p3MDPXej3+9tNtzEQIEQiUUmHA20BrIAJ4FlgPzMGcgHMtMEJr7VJKjQMuAQqB+7XWy+3IWYhgtHJjMjO+XGu1H7upOx1a1LcxI++QAlYIQcqhHB6ZWTJe8p6rutA2WbP98QnWtjaTXiSsQc3WdzUMg1dWv8GmQ1usbc/1HUv9CP8fh3E8SqnVQPG05NuAWcDLmH/U/ai1fspbsSd9uBqAqIhQoiKkmxdC1NpNQJrW+malVENgNfAn8LjWer5SaiYwSCm1AxgA9AJaAp8BPe1KWohg8tIna/hrS5rVfv3BAUSEB8Yjw0eTv2w8ZOnSxRw4sJ9Bg660OxUhqmWVTmH6F39b7UnDziDv/Tc48KdZBNV2vGtaTjpPLnneandu2JFhXWv+CLI/UEpFAmitB5ba9idwFbAV+FYp1V1r/YenYxuGQfKhHADG3nyap08vhAhOnwCflmoXAj2ABe7298D5gMb8gM4AdiqlnEqpRK11Sp1mK0QQyckrZMS0khUjep3chLsu72RjRt4XcAVsyicfkbWyZObUHaEOiopctTpn3Gk9SRx8XYXH9O7dp1YxhLDD+z9o5q3eY7Vn3d+XbSPvstq1He/60475fLnlO6t936l3kpTQvsbn8yNdgWil1I+Y/ex4IEJrvQVAKfUDcA7g8QL2j02p1utmjWTsqxCi9rTWhwGUUnGYhezjwBR3oQqQBdQD4oG0Um8t3i4FrBBeoHem84L7qSuA+64+ha7tG9mYUd0IuALWLt99N5cdO7YzbNg9x+ybPv1lnE4nQ4cO44EHRnDttTfSp4+M+xP2cRkG97y0kJy8It/liz0AACAASURBVABOadeQ4f2alCleazPetcBVyP3zx5TZ9tKA5wgLDat50v4lG5gCvAl0wLw7cajU/iygwkVZExKicVZztsDExDhmTZ4HQPeOjUlM9O21dH01P8MwKHAVklOQQ05BLtkFuRw4sJdsdzunMJe8wnyKjCKKXEUUGUUUuly4XEUUWttc5nf3NpdhfpAaGhKKIyTE/d2Bw+Ewv5faFmptM7+cjlDCQ8MIDw0n0hlBhDOciNAIIpxh7u/hRDjDiXS/Lp4QzVd/vuXxp1zB//L1BKVUS+ALYIbW+kOl1KRSu+Mw+7hM9+ujtx9XTfs6fyL5epc/5evJXGd9/hff/L7Nav/nqQupFxvhsfOD7/5sA66ATRx8XZm7pYmJcaSkZNmYEdx11wiGD7+D5OT9nHRSJyleha2ysvO575WS2eluuUBxavZWtj8+zdpWm/Gum9K38PLqWVZ7UNuLOL/1WTVP2D9tAja7705sUkplAKUXzK30j7r09OxqBSzu6wqLzBsiN5zd3va+ryLe6JvzivJJzk5xf6VyIDuVlJxU0nPTycj33Z+Fr4p2RplfYVFElXodExZDTFg0Mc5oYsNjiA2LJS7c/Ap3hFV7ySZf+P90ddidrx1/UCqlmgA/AiO11r+4N69WSg3UWs8HLgLmAZuBSUqpKUALwKG1Ti3vnMVq2tf5C8nXu/wpX0/levSkm22bxTP25h7k5+STkpNf6/MXs/tnW1FfF3AFrC9yOp1cc831PPvsOD777Bu70xFBbNOuQ0z8oOSp1fG39yT0v295bH3XWX+9y1+p66z202c8SsOoBhW8I2ANAboAw5VSzYBo4IhSqh3mGNgLAI9P4nQ4p8B63SA+0tOnt4VhGKTkpLI9cxc7MnexI3M3O7J2WXc0fUEIIYQ6QgkNceAIMb+X3E0NJdS9zcDAZRi4jCL3d1fJF65y9xkYlSfgJdmFOWQX5kBu5cfWVExYNPWj4ol2RBMbHkt8eJz1VS+i5HVceCyOkJqvOy1qbQyQADyhlHrCve0+4BWlVDiwAfhUa12klPoNWAI4gBG2ZCtEgNqTcpgn3iqZ2Pv2izrSr2szGzOyhxSwdSAzM5P333+He+55gBdeeI5Jk6ZV/iYhPOzbJdv5bMFWq/3ayDPYff8wqx1/Zn9OuK1m410P5WUw4uPRVrtD/bbcd+pd1b4TE0DeAuYopRZhLjExBHABHwChmJOcLPN00J9X7vL0KeuEy3CxNWMHa1M3sPHgJnYd3uuR8zaITKBxVCMaRCZQLyLe/AqPo15EvFUYhTqq9uii3Z9EV1dl+RqGQV5RPtmF2eQU5pJdkG0WrAU5VuGaXZBDTqnX5vZssgtyKDKKPJLnkYJsjhRU7w5cRcIcTuqFx5f8946Ip154PPUj6lEvIp76EfHEh8cTERoezP1TtWmt78MsWI82oJxjx2OO+xdCeND3y3bwybyS1RxeuPsMEutH2ZiRfaSArQMTJz7DDTfcwgUXXMzGjRv45JOPGFzJpFBCeIphGDzz7kq27zf/mG3aMJonL23FjlLFa23Gu87f/TufbPrKag/vOoRODTvWLmk/p7XOB24oZ1dvb8b9dskOAPp2OcGbYWrlUF4GS/etZOWK1ezLSq7We8MdYbSKb8mJ8S1oFdeSVvEtaRiZIIVIDYSEhBDpjCDS6dnxUuUxDIPswhyy8g9zuOAIWfmHycrPstr5IXmkZKWTVZBFVv4RcgpzahyrwFVIau5BUnMP1irnEEJoGJlAw6gGpb43oGFUAs7YEylyGVX+8EMIIWrDZRiMfn0xBzPzAIiNCuOle87E4Qje//dJAeshF1982XH3TZgw2Xo9duz4OshGCFNeQRHDXlxgtS/v25qzHHvZ8cRj1raajnctchXx8G/jyCsqGW8xdcCzRISG1y5pUWNFLvNx0/N7nmhzJiaX4WJNyjp+2jGfHVlVuzvcMaEDHRt04OSGimYxJ0hxGgBCQkLMMbNh0eXur+nd7QJXIZl5mWTkZ3IoL5MM99ehvAzzdb75unQfVVUGxvEL4VWVvz8uLJbE6EY0jmpEYnRDEkt9jwyNkN9rIUSVHMzM5aEZi632FWe24fIz29iYkW+QAtaDxox5mMzMjDLbYmNjmThxqk0ZiWC2J/UIT7xZ8pTqw9d1I/6b9z2yvuvWjB28uGq61b6o9Tnc3utqv3rEMpC1bBxrW+wdmbv4YvO3/HNoa4XHndq0E6ckdOGURicT6QyM8bqiboU5nOadUQ+Msy9wFXIoN4ODuemk5R4kLccsXtNy0jmYe7Dak4BlFRwmK+MwWzO2V3rsvzvfRPfGp9QwcyFEoFq6bj9vzF1vtcfd1pNWJ/jmrMB1TQpYDyp9p1UIO/3+9z7e+naD1Z46rBfJo0ZwxN2uzXjXd9Z9yMoDf1rtcb0fpnF0Ym3SFR6QcTjPlriGYfBX6jreXvchha7Cco9pGduMs0/sT/fGp5RZ4kU+8BC+IszhNO+QRlf+NMrRv7suw0V2YQ4ZeZmk5qSRnJ1KSk4aKdmpJOekcigvo4KzweZDW6WAFUKUMeWj1azfnm61Zz00gLBqLjcVyKSAFSLAvP7lWlZsNMcWhjpCePXmjuwcVTIRZLMR9xB7ao9qnzcr/zCPLnraap8Y15zRp90rj8L5iBXrD9RpvD2H9/Hqn7PJyj98zL6EiPr8q/0lnNq4i8wcKwKeI8RBbFgMsWExNI9tWq33FrgKCXPIn2JCCFNOXiEjpi202md2acqQS06yMSPfJL2mEAGiyOVi6KT5Vrtv5xMY3CCdnR4Y77p473I+2Pip1R7a5Ra6JXauVb7CszZsN8fqxUWHeS2GYRj8uGMeX2/93zH7TmqQxA0dr6JBZILX4gsRaKR4FUIUO3qpwwev6UrnttX/my0YSM8pRABIz8pj1PTfrfZdl3eixa8fsf/L1da2DrPeIiS0eo+fFLmKeGLxhDLjv6b0f5ooGbPoc/QOs4Bt2zTe4+d2GS4+0p/z+97lZbY3iU7k7lNup3F0I4/HFEIIIYLFf+dt5n/LdlrtV+7rR2yU9z6Q9ndSwArh59ZuTWPqf9dY7QlDepA55r5aj3fdmbWbF1a8YrXPbtmPqzocf7ZtYa8d7mWS2jav59Hz/m/7L8zd+kOZbZe1vZALWp0lj48LIYQQteByGYx4aSF5+eba2ic2iWXcbT3l/6+VkALWQ5YuXcyBA/sZNOhKu1MRQeSTeZv5vtQndq/drNg9pmSt+ZqOd/1w42f8vrdkBuOxpz9Is1jfXVtUlGjXzDN3YLdl7GBKqZmmAYZ0upEeTbp65PxCCCFEMDt6iZwbz0vinB4tbMzIfwRcAbv41y1sdU9gA+AIdeAqctXqnG07NqbP2e0qPKZ37z61iiFEdRiGwejXl5CWmQtAhxb1GNE2l93jxlrH1GS865GCbEb/Nt5qN4lO5PFeo2QiHj/S+oTaFbCGYfDiqulsyyz5YGRw0iAGtuhb29SEEEIIASzfcICZX62z2s/c0YvmjWJszMi/BFwBa5fvvpvLjh3bGTbsnmP2TZ/+Mk6nk6FDh/HAAyO49tobWb161THb+vQ504bMhb/Jzi1k5EslM9Rdd3Z7Oi3/gv1v126864r9q5mz/v+s9m0nX0/PE06tfcKiTkVH1rxbP5ibzhOLn7fabeJP5MEew+UDDCGEEMJDXv3sL1b/k2q1Zz00kDCn/H+2OgKugO1zdrsyd0t9Ya3Bu+4awfDhd5CcvJ+TTupEnz5ncvrpvY/ZJkRltu3L5Jl3V1rtsTd0pejpUaXGu/bjhNv+Xa1zugwXzyybQnJ2SWc6qd94YsKiPZGy8BNrUtbxxt/vWu1RPYbTtl5r+xISQgghAkheQRFDJv5qtXt3asKdl3WyMSP/FXAFrC9yOp1cc831PPvsOD777JvjbhOiIj+t3MX//fyP1Z52QxIHnh5ltWsy3nXv4f08t3yq1e7brBc3dLyq9skKv/LzzgV8sflbq/3SwAmyvIcQQgjhITsPZDG+VPF6z5VdODUp0caM/Jvcr64DmZmZvP/+O9xzzwO88MJzx90mxPFM/r/VVvFaPzacaf3COfD049b+NpNerHbx+tk/c8sUr4/0vFeK1yA0d+sPVvGalNCe6WdPkuJVCCGE8JDvl+1g/DsrrPbUkX2leK0l+SulDkyc+Aw33HALF1xwMRs3buCTTz5i9epVx2wbPPg6u1MVPqag0MVdU+Zb7fN7tqTf+m858M6f1rbqjnfNKczloYVPWu164XE802cMoY7qjZkVvsMwjBq9b96uRfxv+y+A3H0XQgghPMkwDMbMXsaBg9kANIiPYNKwPjhkiZxakwLWQy6++PjrY06YMNl6PXbseIAyxWrxNiFK25d6pEzxet8VJxE15bFare969DjHGzpeRd9mvTyQrbBTYQ1mWl+fpvn0n68B6NO0pxSvQgghhIdkZudz/yuLrPblfVsz9Mquts/LEyh8poBVSjUGVgHnaa032p1PTYwZ8zCZmRlltsXGxjJx4tTjvEOI8q3cmMyML9da7YlXteXQC49Z7WYj7iX21O5VPp9hGExe9Ro7MneVnPPMJ4kLj/VMwsJWR3ILq3V8Vv5hpq95C4BW8S258aTB3khLCCGECDprt6Yx9b9rrPbYW3rQrlk9GzMKPD5RwCqlwoBZQI7dudRG6TutQtTUnO83sHDNPqs9pU8oqS+Mt9ptJk0lrEGDKp8vOTuVp5ZOsto9GndlSOcbPZKr8A3VLWAfXfS09Xr0accu/SWEEEKI6nv/B8281Xus9owH+xMZ7hPlVkDxlZ/oFGAm8FhlBwoRqFyGwfAXF5BfaD4OekaXply06VtS3zPvxIY4nbSf8QYhjqrPvfbdtp/4dttPVvvB7sNpV7+1R/MW9supRgH73vqPrdcv9n/GG+kIIYQQQaXI5eLOyfMpnpKi44n1GX1D1Z+UE9VjewGrlLoNSNFa/6CUkgJWBKXMI/nc/2rJWInbz2tHk9fHke1u1xtwFk1uvrXK58svKuCBBWOtdpjDyZT+T+OU2WUD0pHcgiodl557iGX7VwFwZ5dbiHRGeDMtIYQQIuClZuQw+vUlVvu2izrSv2szGzMKfL7w1+wQwFBKnQt0A95TSl2utd5f3sEJCdE4ndWbLTUxMa72WdYhydd7fDHXtVtSeWzG71bbXN+1ZImck54YQ4PTqr5Ezl/7N/Dsgles9i3druZSdY5nkq2EL/58g0F2Fe/APr54AgChIaF0TezszZSEEEKIgLdiYzKvl5qz5LmhvWjaMMbGjIKD7QWs1rp/8Wul1Hzg7uMVrwDp6dnH21WuxMQ4v5rxS/L1Hl/M9evft/Hlb9us9qTTXGWK17ZTXqKofv0q5W0YBjPWvM36g9ra9myfMSREVu39tWX3zzeYi+fsvMoL2E3pm63XE898soIjhRBCCFGZN75ex9L1B6z2rIcGEuas+jAvUXO2F7BCBCPDMBj39nJ2p5iL4rRsHMu/U37m4EebAHBERdH7w/dITTtS0Wks6bmHrLtrACc1SGJE138TImuNBYWqPEL88uo3AOjcsCPRYVHeTkkIIYQISIVF5njXYj07NmbYFfJUU13yqQJWaz3Q7hyE8Lbc/EKGT11ota/s3Zyk/zxPrrtd/9zzaXzdDVWerOnXXb/x2T9zrfbIbndwUoMkT6YsfFzxI8QRYeUPr9h8qOQu/51dqj6WWgghhBAlUg7l8MjMkvGud13eiV4nN7Exo+DkUwWsEIFud8phnnxrudV+5KxEQmY/b7WbP/AQMZ2q9ileoauQhxaOo8BVcvdt2oDnCA8N81zCwi8UF7DRkeV36dP+eB2ADvXbEuqo3hwCQgghhIDlGw4w86t1Vnvi3WfQuL480WQHKWCFqCO/rdnLO99vtNrPdc4ha/aLVrvttFdwxsVX6VxbM7bz4qoZVvviNudxSZvzPJesqDWlVGNgFXAeUAjMAQxgLTBCa+3yVKziR4hjyilgswtK5g24+5TbPBVSCCGECBozv1rL8g3JVvuNhwfiDJXxrnaRAlaIOvDa53/zx6YUACKcDh7N/pWsL3cC4ExIoM2kqVUer/r22g9YlbzGao/rPZrG0Y08n7SoMaVUGDALyHFvmgo8rrWer5SaCQwCvvBUvJI7sMfefX+31Lqvkc5IT4UUQgghAt7R411PP6kxdw+S8a52kwJWCC86uuM76+QG9Pr6JfLc7QaXXEajf11VpXNl5R/m0UVPW+1W8S15uMdImajJN00BZgLFa1v3ABa4X38PnI8HC9gj7gK2vDuwa9M2AHL3VQghhKiO5EM5PFpqvOvdgzpx+kky3tUXSAErhJcczMzloRmLrfY9p8cR8+FLVrvF6MeITlJVOtfivcv5YOOnVvvOLrfIOp4+Sil1G5Citf5BKVVcwIZorQ336yygnidjZueZjxAfPQY2OTvVet2l0cmeDCmEEEIErKXr9/PG1+ut9gt3n0GijHf1GVLACuEFf21J5aVP/rLa49ulk/vhe1a73cvTCY2pfKFrl+Hi8d8nkJGfaW2b0v9pouRRUF82BDCUUucC3YD3gMal9scBhyo7SUJCNE5n1SZcyssvMt9TL6rMergz578FQHRYlE+uk+uLOVVE8vUef8oV/C9fIUTVvf7lWlZslPGuvkwKWCE87KNf/uHHFbvMhmHweOYP5P5gdoThJzSl1TMTqvTY77b0XTwyr2Rt17Nb9uOqDpd5JWfhOVrr/sWvlVLzgbuByUqpgVrr+cBFwLzKzpOenl3ZIZb8QnM+qMKCIlJSsqztfx/QAFyvriqz3RckJsb5XE4VkXy9x59yBfvzleJZCO84ethX75ObcOflnexLSByXFLBCeIhhGDz42u9kHMkHoGvzKC5aMItC9/6G/7qKhpdUrQD9SH/Bb3tKxl2MPf1BmsWe4OmURd0ZBcxWSoUDG4BPKzm+WgrdBWzpT4gLXYXW61MTu3gynBBCCBFQktOzeXTWUqst4119mxSwQnjAkdwC7nnpN6s9pFMYjb+aZbVbjnmSqLZtKz1PdkEOD/82zmo3jmrEE70fwhEij674I631wFLNAd6KUzy4NsxZ8nuyeO8K67VM9CWEEEKU7+j1XSfdfQaNZLyrT5MCVoha2rI3g+feW2W1xzTbi+urn612u1dfJzSq8o5w1YE/eXvdh1Z7ZK/bOClGJt4RVRdW6g7s/7abv4OdG3a0Kx0hRIBRSvUCXtBaD1RKdQfmAv+4d7+utf5YKTUOuARz/ev7tdbLbUpXiErNnruOJesOWG0Z7+ofpIAVohZ+XL6Tj37dbDYMgzHJX+LabI6NimjdhlaPj6vg3SaX4WLC8mnsO1LSgb7Qbxxtmp3gV+PChP2coSV3WjPyzd+d81qdZVc6QogAopQaDdwMHHFv6g5M1Vq/WOqY7phPm/QCWgKfAT3rOFUhKlXkcjF00nyrLeu7+hcpYIWooef/s4p/dmcA0CLa4Ka/3sfl3pd47fUknHdBpefYfySZZ5ZNsdpnNO3JTScN9ka6Igg43Y8QG4ZhbWtXr7VN2QghAswW4ErgfXe7B6CUUoMw78LeD5wJ/OheNmynUsqplErUWqfYkrEQ5Th6mcOhl53MGZ1knhF/4vECVilVH2gLuIBtWusMT8cQwk4FhUXcNWWB1R58YgHtfv0/q33ik08ReWKrSs/z1Zbv+XFHyWS0o0+7h1bxLT2brKgVpdQA4HKgA2afthn4Smv9W4VvtEnxI8RbMrZb22T8qxDCE7TWnymlWpfatBx4U2u9Sik1FhiHuURYWqljite9lgJW+IS/tqTx0idrrPbzd/amSYNoGzMSNeGxAlYpdRHwCHAysBtz7EMLpdQGYIrW+ntPxRLCLgcOZvPYGyWz1D2csI3QX0tqmfbTZ+GIiKjwHLmFeYxa+ITVjgmL5vm+TxDqqNqan8L7lFLdgJeAZOA3YAFmn9YauFcp9Rzm2K4/bEuyHMXjdpa4J3CKDK34d1EIEXyUUm2ASyn7wdxcrfWOap7qC6118ZrWXwCvAl9hrnVdrNJ1r6uz5nUxf1tKSPL1rqrm+9bXa/lywRar/fkLlxJWzd+92grUn21d80gBq5SaA+wHRmit1x21rzMwRCl1k9b6Rk/EE8IOy9YfYNbX5q93iOHikZ0fw+YCAKI6nkTLhx6p9BxrUzfw+l/vWO3r1L/o1/wM7yTsxw6mHiG+XiTOMNuK+puAq7TWaeXsm6GUagw8BvhkAbvywGoATj+hu53pCCF8iFKqKeYHc62A3zEL1+IP5v6rlNoOjNJa767iKX9QSt3jnqTpHGCV+7yTlFJTgBaAQ2udWtFJqrPmNdi/Dm91Sb7eVZV8DcPgoRmLSc/KA6DjifUZfUN3DlXzd6+2AvFn6+34x+OpO7BjtdZ7ytuhtV4LPKiUauGhWELUube+Wc/va/cDEFuYzcjtJct4Nr75VuoPqHiiHMMwmPbHTLZkbLO2Tej7BPUifPOTLTsUFBTxy9wNbNtk/q1zSs8W9D2nvV3pzDlO8QqA1joZeKAO86mS4kmcCo0iAHo06WZnOkII3zIRGK+13lDeTqVUV+B5zImaqmIY8JpSKh/zJsadWutMpdRvwBLAAYyofdpC1Fx2bgEjSy1zeP25HTjvNBmu5e88UsCWV7wqpSKAa4G7tdZ9qvGJnhA+w+UyGDp5HsVz4lyckMkpK7609rd6+jkimjWv8BypOQcZt2Si1e6a2Jk7u9zilXz9UVryYT6dswqXyyizXXW2dUKFr5RSqcDbwP9prTPtTKaqHI6y413b1qt8LLYQImg8obXeebydWus1VFK8aq23A73dr/8A+pRzzHhgfC3yFMIjtu3L5Jl3V1rtJ249jTZN423MSHiKNyZx6gjcBdwCHARe9nQMIepCxuE8Hnjtd6t9f8R6IleUdITtX38DR1h4hef4YfuvfL31fyXnOPUuOiS083yyfsYwDNb+sYdFP20+Zt/FV3ehVfuGNmRVQmvdTil1JuYfc08qpX4B3tJaL6jkrbYrKCqwXjtCZC07IYRliVLqMPAj8BPwq9b6sM05CeEVP63Yxf/98o/Vfu3+fkRHhtmYkfAkT42BDQOuBu4GugLfAPlAknsqdSH8yobtB5n80Z+Ae7zrlv9Y+2K6dqP5PfdX+P6CogLuXzDWaocQwrSBzxHmCO6VqwryC/nxq/Xs3HKwzPaERtFcdm1XYuJ8Z9IhrfUiYJFSKhxzJuIHlVIzgA+01hPsze74dPqxHwoIIYTWurlSqh3QD7gCeEEplYJZzP6ktV5a4QmE8BOTPvyDjTvNucMaxEcweVgfmZE/wHjqr+k9mAP3XwK+11rnKqW2SvEq/NEXC7cyd/F2AOoVHGbYjs+tfScMGUp8n74Vvn9T+hZeXj3Lal/R7mLOazXQG6n6jbTkw3zyzkqMo3qEbr1a0mtA22MeffUlWut84FOl1F7gDuBBwGcL2HVpGoBwh3zSLIQoS2u9BXM91znuZQ8HAaOAxwHf+QRRiBo4epnDC08/kWvOtm0uDeFFnipg3wcGY6711Vgp9WklxwvhcwzDYMzsZRw4aM5K19+5nz6bf7T2t37uBcKbNKnwHLP+epe/Uksm4n76jMdoGJXgnYR9nGEYrP9zLwt/+OeYfZdddwotWjewIavqUUp1Am4ErgG2Au9gTlzik0IouQOrGsj/tIUQJZRSTuBM4ELgAiAK+Bl4EvjVxtSEqLUD6dk8NqvkIYIHrulKl7b2DkcS3uOpSZxGKaVGA5cAtwNTAZRSV2OuE1bkiThCeEtOXiEjpi202iOKVhG3uaQQ7TDzTUKcx//ncigvg7G/P2e1k+q3495T7wzKR1YKCor45esNbPun7MoJDRJjuOzaU4iO9f0P+ZVSj2AWrjHAHODsiiY/8SUHspMBSEqQAlYIUUY6sBj4FPiXe0ImIfze8g0HmPlVyd9sL47oS4IPDUkSnuexAXnuIvVr4GulVCLm5CdPYE7iVPE0rULYaMf+LJ6aswIAh1HE6C0fWPviTu9F0zsrvuG2YPdi/rupZGbi4V2H0KlhR+8k68NS9mfxxrSFFBW6ymzvenoLeg9s59OPCZejM3Cf1nqe3YnUlJICVghR1izM9VqHAC2UUj8CS7TWrorfJoTveuXj1fy0vOTz5dmjBxLqkAkMA52nJnGK1FrnFre11imYd2GnKqV6lHeMEL7g55W7+PBn8xHXhPxM7tpZUog2vXs4caedftz3FrmKeGTRU+QUlvxaTx3wLBGhFc9MHGg2rNnH/O/1MdsvHtyFVu389vGd5cDC4+1USoUCw7XWr9ZdSlVQ6jOCpjEVP+4uhAguWuuHAJRSTTEfIR4JvKuU+hv4QWs90878hKgOl2EwfOoC8gvMz19OU4kM/1cXm7MSdcVTd2A/UEr9D/hIa5111L5NSqkRwLnAvzwUT4haKz1L3el52zl7V0m90uaFKYQ1bHTc927P3Mnkla9Z7Qtbnc1l7S70XrI+prCwiF+/2ciWjSllttdLiOLyG7oR6/+P7mwHFiqlFmAWsruBAqA1cDZwFvDc8d7sC2QJHSFEebTW+5RSHwL/AH0xlz3sBUgBK/zC4ZwC7n35N6t9+8Ud6XdKMxszEnXNUwXsYMyJTVYopQ5R8sdeG6Ah5mPEgz0US4haOXqWumHZi6m3t2TpkQ6z3iIkNPS4739v/ccs27/Kaj/Z6yGaxDT2TrI+Jj0tm8/fW0V+Xtlh7V16NGfQtd1IO3jEpsw8S2s9Vyn1A+Y42LuADoCB+QffN8CTWus8G1MsV5FLphsQQpRPKXU5ZsF6JtAWWIo5edO1Wut1Fb1XCF+xZU8Gz71f8jfYqw+dRYzTr4YoCQ/w1CROLmA6MF0p1ZWSP/Y2a63XeCKGEJ6wL+0IY2cvAyDUVcTDW0vGu8b3688Jtw457nsP5x/hkUVPWe3msU15rOf9QCUJ7gAAIABJREFUQTFR0z/rD/Dz1xuO2X7hVZ1p08G8U+0IDaw7fu7lc95xf/mFgwUplR8khAhWIzEL1vuBVTL2VfibH5fv5KNfS244TH+gPyc2jScl5eiHP0Wg89gkTsXcBWuVi1b3WLLZgAKKgNvd65QJ4VHzVu1i6od/ANAw/xBDd35t7Ws28j5iu5163Pcu27eK9zZ8bLX/3fkmujc+xXvJ+gCXy2DxL5v5e9WeMtvj6kUy6IZuxNWLtCkzcTyp+cl2pyCE8F2vaq3nVnSAUupyrfXXFR0jhB2mfLSa9dvTAUisH8nEu84IihsIonweL2Br4DIArXVfpdRAzMmfBtmakQg4M79ay/IN5h/33TI0F6Yss/a1nTINZ/3y12p1GS7GL3mBtNx0a9uU/k8R5YzybsI2ysst4JuP/yJ5X9lPNE/q2pR+53cgNMDutAaStPwDAESGyocLQohjtHbPPPwp5Y/tvxb4wrbshChHYZGLOyfPt9oXnn4i15wts+wHO9sLWK31l0qpb9zNVsABO/MRgaXI5WLopPlW++70edRP2wWAIzKSdq/MIOQ4063vObyPCcunWe3+zftwrbrCq/naKS35MP99e+Ux2wdepDipa1MbMhLVVXwHtkWc/PcSQpSltX5VKfUxMAL4P8zhXkXAFmAu5lhY+RtM+Iz0rDxGTf/dat979Sl0a3/8CTZF8PBoAauUelVrfc9R297VWt9a0fu01oVKqXcxZym+2pM5ieB1MDOXh2YsBiDMVcCorf9n7at/7nk0vu7G4773001fM2/3Iqv9WM/7aREXmDPcbVp3gF/mHju+9apbu9O4abwNGfkOpVQr4E3MOxT9gQ+AIVrr7TamdVypee4CNjYwf1eFELWjtU4Gxrm/hPBZG7YfZPJHf1rtF+4+g8T6gfv0m6geT60D+ybmjHanKaU6ldoVBtSryjm01rcqpR4BlimlTtZalzudaUJCNE7n8WeILU9iYly1jreb5Ft7y9fv55m3zMeEm+Slcfuub619nZ56kvrdupb7vuyCHG77/EGr3Si6Aa9d8gwOmxbF9tbP1uUy+PGrdSxftK3M9sZN47j57jOIia3ZMji++LtQS7OAycBEYD/mXYv3MItZn1Ng5APQXApYIYQQfmru4u18sXCr1Z710ADCqvm3vwhsnroD+yzmHYqXgadKbS8Ejr21U4pS6maghdb6eSAbcGE+0lKu9PTsaiWWmBjnV7OTSb6198GPm/jlj90A9Dy0nnNSSx6LbTv1FQriy5+x7s/kv5m99n2rfdNJ13BG09NIS7NnaRhv/GyPN7715G7m+FaHw0F2Tj7ZOfnVPrfdvwteKp4baa1/VEq9oLU2gNnuda19WtMgWdZJCCFEYJnw/io278kA4MQmsYy//XSbMxK+yFPL6GwHtgNdlVLxmHddi6cGiwUOVvD2z4F3lFILMe/Y3q+1zvVEXiK4uAyDe176jZy8QjAM7k7+gfpZ5iOVofXq0+vdN0lNPXzM+wzD4IWVr7Arq2S23YlnPklceGyd5e5tqQcO88k7Mr61BnKUUi0wlwVDKXUm4HPrvx6tUVRDu1MQQvgopdQlWutvKz9SiLpz9GRNl/dtzRX92tqXkPBpnh4D+xjwGJBWarOB+XhxudyPCl/jyTxE8MnMzuf+V8wxq+GufB7c+pG1r8HFl9LoyqvLnW49OTuFp5ZOtto9m3Tntk7XeT/hOiLjW2vtQeAboJ1S6k+gAVXor8pbHgzzQ705mH3iWmCEt9ZhjA2L8cZphRCBYRIgBazwGWkZuTz8+mKr/eC1XencRj6IFcfn6VmI7wDaaa1TPHxeIY5L70znhQ9XA9AsN4Vbdn9v7Wsx+jGik1S57/tm6498v/1nq/1QjxG0qdfKu8nWAcMwWLZgG6uX7iyzvUFiDJdf35Wo6HCbMvM/WusVSqmeQBIQCmzUWlfl+erylgcLAR7XWs9XSs3EXC7MK0tWyNp4QogKbFFKvQ0sA3KKN2qt37MvJRGs1m5NY+p/11jtKcP70CBeloITFfN0AbuTih8XFsKjvlq0ja/cExH1OfgX/Q+WzFjX7qXXCI099jHg/KJ8HljwuNWODI1gUr/xhDr8e4KAwoIifvxyPTu2pJXZXnp8q6ge9x95pRlKqRzMsf2zj1fMHmd5sEuABe5t3wPnI2suCiHqXhrmB2q9S20zMCeoE6LOfL5wK98s3m6133h4IE5Za15UgacL2H+ARUqpeYA1jlVr/bSH44ggZxgGj7+5jH1p2WAYjNz9FbF5mQCEn9CUVs9MKPcu1IaDm3jtzzet9uAOgxjYsm+d5e0N2Yfz+Pz91WRllB063u/8DnTu3tymrAJGEeZjw++629cBce7tM4Ehx3tjOcuDXeqeCAogi0pmaK/+jOuG9cpfZoP2lzyLSb7e40+5gv/lW5rW+nYApVSC1jrd7nxE8DEMg/HvrGBXsjkvSfsW9RhzUw+bsxL+xNMF7B73F5RM4iSER+XkFTJi2kIAoopyuW/bf619ja68mgYXX1ru+55fOJ3V+9Za7ef6jqV+RJVWefJJqQey+OSdVcdsv+y6U2jRuoENGQWkblrrnsUNpdRcYJnW+hql1JoK3geUXR4MKL2AXRxwqKL3VnfGdUILrZe+NjN4eeyetbq6JF/v8adcwf58a1s8K6W6Ah8D0Uqp3sBC4Bqt9R8eSE+IChUUFnHXlAVW+6oBbbnkjNb2JST8kkcLWK31U0qpGKAd5iQlUcdbz1WImtixP4un5qwAoFX2Pq7f+5O178SxTxLZ5tj5wg7lZTD29+es9kkNkhjZ7Q7vJ+sl2zal8L/P15XZ5nCEcM2/e5LQMNqmrAJWrFLqBK31fne7MSWF6HH7z+MsD7ZSKTVQaz0fuAiY58lEQyJyKj9ICCHgVcwnQz7UWu9VSg3DfKJE1isRXpV6KIfRM5dY7dHXn0rHVgk2ZiT8ladnIT4beANzspMzgLVKqRu01j96Mo4ITj+v/P/27js6qmrt4/g3lU4oCR2kbwSkVxHBhmJFUayoKPbGK4rY8epVQRQsIBbU6xVULNgQy5UuiEivG+lFSugBkpAy7x8znGSAhITM5Mwkv89aLLP3ac/EZGee2W0z4//3NwDn7vqLDvtWOMcavvU2kSVLHXfNjC1z+Hx11jTD+1v25/TKjYMfbIB5PB4W/rGJudPX+9XHVynLZde3pGSpGJciK/KeBeYbY2bjbdfaAQ8ZY4YAv+Zy3XHbg+GbN2uMifV9/WUgA1UCKyJ5VNpau9IY7wKH1tpfjTHDXY5Jiril63YzIttiTa/e14WK5Uq4GJGEs0APIX4JOAuYbK3dbow5G/gUUAIrBTJs/AJWbdoHHg8Pr/+M2Mw0AEo2aEidx5867vyMzAye+P0FDqZlDQD4b+/XObA35Lfw9JORkcnUSav4e8VOv/rGzarS/WJDlBY7CCpr7QRjzBSgK955r3daa3cZY6Zba3NcsC6X7cG6BSlUImK0fbaI5Mke3zDio/tb34gW4JQg+mbmOr77fYNT1mJNUlCBTmAjfYkrANbaFUe/FjkV2edKlE0/zP0bsjqtqtxwExXOPf+4azYlbWHovDecco/TzuGKBj0pER0LhEcCm5KcxjvDp7Nj2wG/+o7d6tG6Ux1tk1JIjDEJwE1AWbzz+tsaY+pZa292N7LjRUSnuR2CiISHe/AuTNfMGLMP7wKcN7obkhRVL3z8F+v+8b6XaVQrjse1WJMEQKAT2C3GmEvxbjVRAbgP79Y6Ivm2fc9hnnj3DwAaHdxE7+3TnGOnPfcCJWrWOu6az+xEZm7Nml/xdMeBVCtTNeixBsq+PYf5/P15ZGZ6/OovuqoZ9RonuBRVsfY5sBnvdhPfAJcC81yNKAcRMd4dfUpHHz+UXkQkmwrW2rN8a5ZEWWsPnPQKkXxKz8jkzlemOeUru9bjsi713AtIipRAJ7B3Aa8DtYG1wBTgzgA/Q4qBOcu2894P3jmul+z4nTOS1jrHGr79LpExsX7nJ6cn88iMZ51y1dIJPNVxIJER4TFEZfvW/Uz878Lj6q/p15b4quG7XUMRUMNae65vftjXwDC87Vro8fXAlo0p43IgIhLi/m2MaYS3LfvBGPOrtTafy56L5GxvUioDR/3ulAde24pm9bQ7ggROoBPYB6211wf4nlLMvP3NMuat2kmkJ5NBaz9x6su0ak3N+x867vxFO5fy3rL/OuVbml5Hh2ptCiXWglq/ehc/fb3Mr65s+RJcdXMb6taLD6utJYqoo3skWqCltXZuqE6LiIj29sCWidFK1CKSM2vtRcaYksA5eFdEH2GMWWWtvdjl0KQIWL15Hy+Py9qR6ZV7zqRyXEkXI5KiKNAJ7GXGmKettZ6TnyriLyMzkzuGTQOgwpED3L3pG+dYtTvuonzHzn7nezweXvnrLTYmbXbqhp71LGVjQ78HatmCrcz85W+/umq14ri0zxnExAb611IKYIox5gvgEeAXY0wbICSX+z06B7aMemBFJBe+uf3dgO54F6jbA6zI7RqRvMi+WwTAO490IyY6ysWIpKgK9Dvl3cAqY8wCsr3Js9beFuDnSBGz50AKj4yeDcAZB9Zwyc7ZzrF6L71CTIL//M9dybt5ds5Qp9y+amtubRbanf8ej4e509ex8I/NfvWNmlXhnIubaEXhEGStfdIY08Bau9EYcwNwNvCc23GdkK8HVkOIReQkdvj+jQS6W2v3nuR8kZMa9fVS5q9OBKBqpdK8eEdHLTgpQRPoBPY/Ab6fFAOL1uzijS+XANBn66/UT97mHGv0zlgiovw/vft5wxS+W/eTUx7Y9l7qx9UtlFhPRUZGJlMmrWLNMVvhtO5ch45n11MDH8KMMV9Za3sDWGvn490T9jfgPHcjO57TAxurIcQikqsmwLl4hxBPNcasAKZaa99zNywJR5keD3e9Mo0M3+KT57etxQ0XNHY5KinqAp3A3mCtvTDA95QibNwvq/ltwRaiM9N5ZN14pz7u7O5UvflWv3PTMtMZMO0JpxwZEcmIbi8QHRmaQ26PpKYzacIStm/1X+Dx7Asb0ax1TZeikrwwxnwNtAZqGGPWZTsUjXdV4pATEZUBQNlo9cCKSM6stauB1caY2cAFwN1Ae0AJrOTL4ZR07h85wynffUUzOpwePjs/SPgK9Dv/UsaY2tbakHyDJ6Ej0+PhwZEzOZyaTpXUPdy2+QfnWI0H/4+yLVr6nb9m33pGLHjbKfdqcDEXnNa9sMLNl8MHU/nyPws4lOS/52zP3s2p2yjepagkn24FKuFdVf3BbPXpeIfehSwt4iQiuTHGfAZ0wbs43STgUmutzeO1HYGh1truxpiGwEeAB1gG3GetzTTGPAtcgre9HGCt/TMIL0NctjXxIE+Pzfpf+6/bO1AroayLEUlxEugEtgqwwRizE+8c2AjAY62tH+DnSBhLOnyEh96YBUD7vSs4b/dfzrH6r75OdFyc3/ljl33Cgp1LnPK/Og+mcqnQW4597+7DfPbe8X+nr7q5DVVrlHchIimAVr7/vgqcdsyxBsAMQlSZMFjETERcNQHoj/c9WpS1dl9eLjLGDAL6Aod8Va8BT1lrpxljxgBXGGM24l0gqiPeLRW/wtu7K0XInyt3MObb5U75rQFdKV0yxsWIpLgJdAKr4cOSK7tpL0PHLwSPh9s2f0+VI96/m1FxcdR/ZQQRkVkLGSUdOcjgWf9yyvXj6vJwm3tCbs7oifZwjYyM4Lo72hNXUb1hYSq3hZo8eOePhaQy0fqZE5FcLca7B2wDIMKXdF7rG1qcm7XAVcDRfevaAtN9X08GeuDt1f3FtxvFJmNMtDEmwVqbGOgXIe4Y/7/V/O+vLQBERUbwzqPdiQyx92VS9AU6ge2WQ/3HAX6OhKFvZ63n21nrKZGRyv+t/9ypr3TJZcRf2dvv3Dnb/uKTlROc8p1n3ELLhGaFFmtebNmwh+8/W+JXV75CSa66uQ2lSse6FJUEgrX2nOxlY0w58tFT4aZw2EZKRFw1Bhhmrf0SwBjTB3gX77Y6ObLWfmWMqZutKiLbtolJQBxQHu+OFBxTn2MCW7FiaaLzudVKQkK5fJ3vtqIQr8fj4Z6hv7E10dsB3/mM6jxxa4fCDu2Ewun7G06xQujGG+gENvubvhi8+4vNQAlssebxeHjq/bls232YWsk7uGnrz86x2o89SalGjZxypieTIXOGsjsla1X/4Wf/i1LRobMJ9jqbyM8Tl/vVVa8VxyV9WhATq/3OihJjTH3gM/x7KvpYa//O/Ur3aA6siJxE/NHkFcBaO8EY89Qp3Ccz29flgH3AAd/Xx9bnaO/ew/l6aEJCORITk/J1jZuKQrxp6RncNXy6U77+/EZc0K52SLyucPr+hlOs4H68uSXPAU1grbX9speNMZWAz3M4XYqB5NR07hvhnS7YbdcCOu9b5hxr8MYookpn9Rb9c3A7//7zNafcrVYX+jS+ovCCPYlVS7Yx9Uf/dS7qNYrngl5NtYdr0fUOx/dUvMdJeircVDq6lNshiEhoSzXGtLHWLgAwxrQF8pdFei00xnS31k4DegJTgTXAMGPMcKAWEGmt3RWguMUFew6k8Mjo2U558I1taFy7gosRiQS+B/ZYB4G6QX6GhKiN25N47qN54PHw4PoJlM70rspbos5p1Hl6iN9c1olrJvG/TVmf7g1uP4Da5WoUeswnsnjeZmb/ttavrkmLanS7yBAZqXkfRVygeioKTahuKyUiIWMA8JUxZg/ehZwqAdeewn0GAu8ZY2KBlcCX1toMY8xMYA4QCdwXoJjFBas27mXYp1lrfLx6XxcqlivhYkQiXgF9p2OMmYp3gRPwNor18S7RLsXM//7azPj//U2Z9GQe2PCFU59w7fVUvCBrra/UjCM8PD0rH4iLLccLXZ4kMsLdHk2Px8O8WRuY//tGv/qW7WvR+dwGIbeQlARNoHoqRERCgrX2D2NMY6Ax3iTTWmuP5PHaDUAn39erOcHaJ9baIcCQAIUrLvll3mY++y1rtsy7j3YnWqPNJEQE+qP6Idm+9gC7rLUrAvwMCXHDxi9g1aZ9NDi0hWu2TXHqT3v2X5SoXccpL9+9itGLP3DK15urOKtmp0KN9Vgej4dZv65h2YKtfvUdzq5H2zOP3U1FioFA9VSIiLjKGFMDGA40A2YDj4fDwnRS+EZ9vZT5q73rbtWML8Pz/Tu6HJGIv4AlsMaYisDyo3MdjDHdyGXVOSl6sk/yv2jnbFodWOMcazjqHSJLeIedeDwe3lz0HnZv1vEXuzxNXAn3VjrLzMxkyqRV/L18p1991wsa0bxtTZeiErcYYypZa/cUpKdCRCTEfAgsBcYBVwMjgH65XiHFisfjofdj33Mk3bs+1/ntanHD+Y1djkrkeAFJYI0xrYEf8TaEP/mqewDjjTE9rbVLcrxYioRtuw/x5HtzifRkMmjtJ0596eYtqDXgYae8N2UfT81+0SmfEd+Uu1vcWpih+slIz+SnicvYtHaPX/15lzahcfNqLkUlIWC1MeY34AO8exouP9kFIiIhrqa19kIAY8wvwCKX45EQkn3RTYA7L29Kp6Z6HyShKVA9sMOB630r0QFgrX3SGDMDeA04P0DPkRA0Z9l23vthBXFpSdyzcaJTX+22Oyh/ZhenPHXzLL78+zun/GCrOzGVGhZqrEelHcng+88Xs2PrAb/6i3o3p16jeFdikpBSB7gKeBgYY4z5L/ChtXa9u2GJiJwyZ/SItTbNGKPRJALA9j2HeeLdP5zyc7d1oHaVsi5GJJK7QCWwFbMnr0dZa382xgzN7UJjTAzeXo66QAngBWvtd7ldI6Fj2H//YuairTRLWsdlO2Y59XVfHEZslSoAZGRm8OjMZ0nNyPpbOaLbv4mNiin0eNOOpPPNuEXs2nHQr/7y61tS87SKhR6PhCZr7WHgE+ATY0x14EZgojFmNzDWWjve1QBFRArOc/JTpKhbvGYXr3+ZNVBy/PM9STmU6mJEIicXqAQ2xhgTaa3Nvqk1xphIIPYk194E7LbW9jXGVAYWAkpgQ1xGZiZ3DJsGwNX/TKHh4S3OsUZj3ici2vujtfHAZob99aZzrGfd87m0fo9CjRXgSGo67wyfzo5t/j2uvW9pQ5Xq5Qs9Hgkf1tptwHBjzGfAk3jnkSmBFZFw08wYsy5buaavHAF4rLX1XYpLXPL97A1MnJH1I/H+oHMoVzpWCayEvEAlsNOBZ33/snsK+Osk134BfJmtnB6gmCRIjm5qHZ2ZziPrst7Hl+/SlWr9bnfK41Z+wext85zyM50epWrphEKNNTUlnYmfLGDvLv+dT67p15b4qu4tGiXhwRhTAbgGbw9sVeBjoJ6rQYmInBqtxiOO1z5fxLL13vU/GteKY/BNbV2OSCTvApXAPg78aIy5Be+iAClAG2AncHluF1prDwIYY8rhTWSfyu38ihVLEx0dla/gEhLCK1EJ5Xj/XLGd58fOJSF1L7dv/t6pb/LEYCp3bA/AwSOHuG3iI86xOnE1eeXCJwt179SU5DTGvj6T3YmH/OrvGtiNqjXCp8c1lH8WTiTc4s2JMaYP3tEhZwLfAk9ba2e6G5WIyKmz1m48+VlS1GV6PPQfOtUpX3rmaVx1dgMXIxLJv4AksNbaJGPM2cA5QGsgExiV1zd8xpjawERg9Mnmlu3dezi3w8dJSChHYmJSvq5xUyjHO+6X1fy2YAtt963kgl1ZPav1h48gs0JFEhOTmL9jMR8sH+ccu63ZDbSt2opduw6e6JYBl5Kcxlf/mc+BfSl+9dfe3h7TtBqJiUkh+/09Vij/LJyI2/EGOHl+AO/c/OuttYdOdnJ2J5rXD6wAPsI752wZcN+xUy5ERESC6diVhu+7sjltTRUXIxI5NQHbB9Za6wGm+P7lmTGmKvALcL+19rdAxSOBk+nx8ODImRxOSeOWLT9SPXU3AJFlytDpk4/YtfsQHo+Hl+aNZOvBbc51w7oOoUxM6UKJMSU5jS8+/IuDB/znbVzXvz0V48sUSgxSdFhruxbg8hPN618EPGWtnWaMGQNcgfdDOxERkaA7dqXhf93egVoJWmlYwlPAEtgCeAKoCDxtjHnaV9fTWpvsYkzik3T4CA+9MYsSGUcYvP4zp77iRReTcHUfIiIj2Xk4kef+eMU51ql6O/qe3qdQ4ks+fIQvPviLQwf9dwO47o4OVKxcOMmzyDFONK+/Ld61AgAm490nWwmsiIgE3ZK1uxn5xWKn/OaArpQpWfg7QYgEiusJrLX2IeAht+OQ49lNexk6fiE1k3fSd+tPTn2tQY9TurEB4ItlP/DF8knOsUfb3U/d8nWCHtvhQ0eYMHYeyYfT/Oqvv7MDFSopcRX35DCvf7hvlApAEhDnUngiIlKMTJqzga+m+680HBlZeGuSiASD6wmshKZvZ63n21nr6bp7EV32Zu0P1uD1UUSVKcORjDT+b/qTTn2JqFhe6focUZH5W2Arvw4fTOXzsfNISfZfrPqGuzoSV7FUUJ8tklfHzus3xgzLdrgcsO9k9ziVBesgvBbSCqdYQfEGUzjFCuEXrxRPI79YzJK13mlfDWvF8YRWGpYiQgms+PF4PDz1/ly27TrEfRu+pFyGdyR3bI2anPbcC0RERLB671peX/iOc03vRpdxbu2CTBk8ucOHjvDZe3+SmuKfuN54d0fKV1DiKqEjh3n9C40x3a2104CewNScrj8qfwvWeZyvwmXhL7cX/covxRs84RQruB+vkmc5mUyPhzuHTSPT4/3bcEnn0+jdTSsNS9GhBFYcR1enK52ezOANXzj18Vf3odJFFwPw7pL/sHjXcufY6Mv+jedQ8OZRpCSn8fnYeRzONsc1IgJuvLsT5eJKBu25IgVwonn9DwFvGGNigZX4z5ENAM/JTxERkSLv2JWG7+3VnHZNtNKwFC1KYAWAjduTeO6jedQ7tJVrt2UtBl3n6SGUPK0u+1OTeOL35536xhUa8GDrO4kvXZ7EQ4H/JDo1JY0vPzp+O5yb7lHiKqEtl3n93YL2UE1nEhEp9nbsOczjWmlYigElsMJv87cw7tfV9Nj5B20OrHbqG456h8gSJfj9n7mMX/WVU39Pi340jz89KLEcSU1n4icL2ZPov/Wm5riK5CJCW8qKiBRny9bt5rUJWSsNv/FQV8qW0krDUjQpgS3mho1fgN24h8fWfuJ04pRu2oxaDz9KpieTJ2a9wP4jB5zzXz37eUpGlwh4HGlpGXw3fhE7t/n35mo7HJE8iNAQYhGR4mry3I18MXWtU35vUHeiIiNdjEgkuJTAFlNp6RncNXw6cWkHeWzj10591VtvI+6ss9l6cBsv/jnCqT+v9tlc1ejSgMeRnp7BpM+X8M/m/X71fW5rR+UqGvYikifqgRURKZZGfb2U+asTAahfozxP3dzO5YhEgk8JbDG0bfchnnxvLqcnreeKHTOd+rovvExstWp8ufo7pm6Z5dQ/2eFhapStFtAYMjIy+emrZWxat8ev/upb25JQTSssiuSLemBFRIoVj8fD/SNnkpzq3Z3hog516HNuQ5ejEikcSmCLmd+XbmPspJVcuW0a5tAmp77RmPdJJZ37pgxy6iqXrMiQzo8RGRG4YSiZmZn8+u0K1tldfvVX9m1NtZpxAXuOSHESEakeWBGR4uJIWgZ3vzrdKd95eVM6NQ1sR4NIKFMCW4yMnriUhSu3M3jdOKeuXMfOVL/jLpbuWsGYJR859Tc1uYbONdoH7Nkej4cpP6xi9fIdfvVX3NCKGnUqBOw5IsWShhCLiBQLew6k8Mjo2U75mVvbUbdaeRcjEil8SmCLgfSMTO58ZRrxqft4dPN3Tn31ex+gbOs2vDZ/NGv3b3DqXz7rGcrFBmb+qcfjYcbPq1mxaJtf/aXXtqB2vUoBeYZIsachxCIiRd7qzft4edwCpzzigbOIKxPrYkQi7lDcWOkfAAAgAElEQVQCW8Ql7kvmsTFzaLNvFT12/enU1xv2GgdKRXD/1MecutZVWtC/+U0Bea7H42Hu9HUs/GOzX33P3s2p2yg+IM8QER/1wIqIFGnTF23lPz9Zp/zuo92JjtJKw1I8KYEtwv5atZPR3yyj7+YfqZnqnXMaUaIkDd8czW9bZjJx0STn3AGt76ZRxfoBee7iPzcze8pav7oevZrSoEmVgNxfRI6hHlgRkSLro8mrmLH4HwASKpRk6N1nuhyRiLuUwBZRYyet4K9Fmxi8/jOnrmKPi6h49dUMmP4k6Z4Mp35kt38TE1Xwza5XLd3O1Emr/Oq69zSc3rJ6ge8tIjnTIk4iIkWPx+Ph8Xf/YOfeZADOalGd2y4+3eWoRNynBLaIycz00H/YVGom7+T/tv7k1Nd65DG2Vy/NkGlPOHWX1b+Qi+qeV+Bnblizi8lfLvOr69S9Pq071SnwvUUkD9QDKyJSpBxdv+Sovhcazmld072AREKIEtgiZG9SKgNH/U7X3YvosneJU99g5FuM2zSJufPnO3VDOj1GQunKBXrets37ePvlaX51LdvXovO5DYiIiCjQvUUkHzQHVkSkyDhw+AgD3pjllB+7oTWmTkUXIxIJLUpgi4gla3cxcsJi7t/wBWUzUgCIrVmLhCcf58FZzznn1SlXk0HtHixQgrl750EmfPCXX12jZlU479LTlbiKuEE9sCIiRcKmHUkM+XCeU37lnjOpHFfSxYhEQo8S2CJg3K+r+WPu3wze8IVTF3/NtWxoXZNXsiWvtze/iTZVWpzycw7sS2bcmLl+dfUbx3P+FU2J0kp4Iu5RD6yISNg7uvjmUW8P7EaJmCgXIxIJTUpgw1imx8MDI2dQY89GHtg2xamv8/RzjNz5DZuXTXXqXuk6hNIxpU/pOYcPHWHcmD9IT8t6k1w5oQxX9m1DjZoVSExMOvUXISIFFqEEVkQkrH09Yx0/zN4AQGx0JG8P7KZRbSI5UAIbpg4cOsKAN2fRc8dsWiatceorvvoSA+ePcMqdqrWjb9M+p/SM1JR0vvjwL5L2pzh1pcrEcF3/DpQsVfBVi0UkQDSEWEQkbA0bv4BVm/YB0KJBZQZc09LliERCmxLYMLRywx5e/XQBg9d+4tSVbt6CFVe25vVsyevAtvdRP+60fN8/PT2D78YvZsc/B/zq+97bibLlNQ9DJORoGx0RkbCT6fHQf2jWaLkru9bjsi71XIxIJDwogQ0zX01fy+zpSxm06RunLuG223kmdRKZaycDEBURxWvdnic6Mn//ezMzPfz67QrW2US/+uvuaE/FymUKHryIBId6YEXEJcaYhcB+X3E98A7wOpAO/GKtfS6na4uz5NR07hsxwyk/cNUZtG6c4GJEIuFDCWyY8Hg8PPr2bGptXsZdiXOc+ugnBvDUhvFO+Yr6PelR95x83/+P6etYOGeTX13vW9pQpXr5Uw9aRAqH5sCKiAuMMSUBrLXds9UtAnoD64BJxpg21toF7kQYmnbuS2bwmKz3cv+6vQO1Esq6GJFIeFECGwYOpaTxwMiZ3LDlZ+qk7PBWRkQwd8CF/JEteT2VvV1XLPqH6T+t9qu7pM8Z1KlfsD1iRaTwRKgHVkTc0RIobYz5Be97yiFACWvtWgBjzM/AeYASWJ+VG/fyyqcLnfIbD3WlrNYVEckXJbAhbs2W/Qz/+A8Gr/vUqStz9tm8WGsV7PD+PahdtgaPtX8oX6vVbVq3m0kTlvrVdbuoMU1b1QhM4CJSeNQDKyLuOAwMB94HGgGTgX3ZjicB9XO7QcWKpYmOzt9WMQkJ5fIXpcuOxjtp1jrGTMx67/XNsMtCchvCcP3+hoNwihVCN14lsCHs+9kb+OOXuTy8ZbJTl9yvN6+nznTKtzW7kbZV875a3a4dSXzx4Xy/ujad69CxW65/X0QklGkRJxFxx2pgjbXWA6w2xuwHKmU7Xg7/hPY4e/ceztcDExLKhdX2fUfjHfvDCn5fth2AmvFleL5/R/bsOeRydMcL1+9vOAinWMH9eHNLnpXAhiCPx8MzH/xJvVW/c8veJU79pJtbsCZb8jqs6xDK5HFv16T9KXzy9h9+dQ2aJHDBFU21z5hIuPMNIY5Av8siUqhuA84A7jXG1ABKA4eMMQ3wzoG9ECjWizh5PB4eHT2b3Qe8WxKe07omfS80LkclEt5CJoE1xnQEhmZfCKA4OpySxu0vT+G+DV9SLiMZgMgqCYw4D0j3fnLXoVobbml6XZ7ul5qSzudj/+RQ0hGnLr5qWa68qTXRMfkbsiMiIcqXwEZF6HdaRArVWOAjY8wswIM3oc0ExgFReFchnutifK5Kz8jk8ke+c8q39mzC2S01VUukoEIigTXGDAL6AqE3lqIQbdh+gFdfmMTgDV84dXvPa8fHVbNWB364zb00qFD3pPfKyMjkh8+X8M+mrJE7sSWiuOGujpQqHRvQuEXEXRG+ObBKYEWkMFlrjwA3nOBQp8KOJdQcOHSEAW/OcsqP39SGRrUquBiRSNEREgkssBa4Cviv24G45dd5m/nzu6k8sG2KUzfh4gS2VfAmrxFEMKL7v4k5yd6uHo+HaZMtq5Zs96u/4a4OxFXM23BjESm47KNKjDENgY/w9lAsA+6z1gZu4qp6YEVEQsbG7Uk899E8pzz83jOpVL6kixGJFC0hkcBaa78yxtTNy7lFcbW6QW/OpN7c77kmaa1TN6pPAunR3vls151xOVc17XnS+/w+ZQ2/TVrpV9fvgS7UrlsphysCI9S/v9mFU6ygeMPVCUaVvAY8Za2dZowZA1wBTAzYA309sJERobeapYhIcfLnyh2M+Xa5U/7ipUtI2p/sYkQiRU9IJLD5UZRWq0tNy+C+4VMYtHacU3egYVU+7JC1p+OznQZRpXR8rq9h7aqd/PLNCr+6Hr2a0aBJAkBQX38of3+PFU6xguI9leeHkGNHlbQFpvu+ngz0IAgJrHpgRUTc89X0tUyasxGAEjFRjH74bErGRhM+f8lFwkPYJbBFxZbEg4x4+38M2vSNU/dT5/LYet7ktWbZ6jzefkCuKwQnbk/iy4/8t8Q589wGtOxQOzhBi0ienGBUSYRvmwnw7osYF9AHRvqGEEcqgRURccPLn8xn9Zb9ALRsUJmHrsn7Focikj9KYF0wfdFWFn3+PXclZm1r8+HllTlQ1vvms1/T62lXrXWO1x86mMrHb83xq2vaqjpnX9hYW+KIhKbs811Pui8i5G+6xNFFnGKiY0KtJzpX4RQrKN5gCqdYIfzileDJ9HjoP3SqU77q7PpcemZd9wISKQZCJoG11m6gGKxa99qERbSY8Sk9U3YAkBkZwVt94vFEehPPsb1eIeWA54TXpqdl8PXHC9idmLVYc5Xq5eh1Y2uiojX3TSSELTTGdLfWTgN6AlNPcn7+pksc3Qc2MyJshp27PeQ8vxRv8IRTrOB+vEqeQ0dyajr3jZjhlB+8ugWtGsa7GJFI8RAyCWxRl5aeyQPDfuHhdZ85dYsal2J6O+8fonZVW9Gv2Q2UK1GWlGNmS3g8HqZOWoVdtsOpi4yMoO99nSldRlviiISBgcB7xphYYCXwZUDvrkWcREQK1Y49h3n83ayRdC/070iN+DIuRiRSfCiBLQQ79hzmzde/5+Gtk526r8+twOZq3uTz/9rcQ8MK9U547eJ5m5n921q/umv6tSO+atngBSwiBZZ9VIm1djXQLWgP0zY6IiKFZtm63bw2YbFTfnNAV8qUjHExIpHiRQlskM1Zvp1VH43n5r1LnLp3eseTUsLbUzKy+4sn3Nt107rdTJqw1K/uoquaU6+xhqaIyDGcHlglsCIiwfTT3E1MmLrGKb8/6BwiI7X+iEhhUgIbRG9PXErHn0bRJSMFgN3lo/jkkkoQEcGl9XrQs975x12TuCOJt4dN86vr2K0ebTqfVhghi0g4cnpgNYRYRCRYRk1cynybCEC96uV4+pb2LkckUjwpgQ2C9IxM/u+lH3lgQ9Y0t5mtyrCgqXduxLOdHqVK6QS/a1KS0/jk7T9IO5Lh1DVoksAFVzTVysIikquISO0DKyISLB6Phwdfn8mhlHQAerSvzXXnNXI5KpHiSwlsgO3an8y7wyfwwLasRUbHX1SRxEoxVCtTlac6POyXkGZkZPL9p4vZ5ts7DCCuYimu6deOmFi9GRWRPIhQAisiEgxH0jK4+9XpTvmOS5vSuXk1FyMSESWwATTf7mTDmDFcnbTOqRvVJ4H06AhuaXodHaq1ceo9Hg+//7aGpX9t9bvHQ0+dx5H0DERE8kyLOImIBNyeAyk8Mnq2U376lnbUq17exYhEBJTABsxHPyzjzG+Gc4avvK5mLN93qwDA0LOepWxs1tLqq5fv4LfvV/pdf2Xf1lSrGUdcxdJhtR+eiIQALeIkIhJQf2/Zx0ufLHDKI+7vQlzZEi5GJCJHKYEtoMxMD4Nf/Jb+G75x6n46szy2bknaVmnJbc1vdOp37TjIFx/+5Xf9eZc2obGGoohIQRztgY1UAisiUlDTFm7l45+tU37nke7ERGuRPJFQoQS2APYmpfLxix/SPzFrI+sPLq9MUtkoBrS+m0YV6wPeBZr+O3oO6WmZznlntK1Jl/MbaoEmESmwCM2BFREJiLGTVvD70u0AxMeVZOjdnfVeTSTEKIE9RUvW7iZxxFB6puwEICPSO9/VExnByG7/JiYqhsxMD5O/XMqmdXuc6ypXKcNVN7chOlpvNEUkQCK1jY4ULxOmrGHeqp0BvWf7JlXoc27DgN5TwofH4+HRt2ez50AqAF1bVKffxae7HJWInIgS2FPw2eSltPnqVWr7ygsbl2JGu3JcXPd8LqnfA4AFczYyd/p6v+v63tuJsuVLFnK0IlLkqQdWJOieeOJRrrnmOnr06M7Klcv5z3/G8vLLrx133urVqxgx4hWioqKIjY1l0KCnqFatGh999D4zZ04nIyODXr1606tXbxdehZxIWnoGdw3PWmn41p5NOLtlDRcjEpHcKIHNh0yPh5de+pJr1k1y6r4+twKbq8XyTMdHqFqmCpvX7+GHz5f4XXf59S2peVrFwg5XRIoLLeIkxUyfcxsWem/pZZf1YvLkH+jRozs//vgDl1125QnPGzr03wwe/BSNGhlmzpzGW2+9xs0338bcubN5992PSEtLY8yYt/B4PBqaGgL2JqUycNTvTvmJvm1pWDPOxYhE5GSUwObRgcNH+OrZN7lm71Kn7p3e8cRVrMqbHQdycH8qb788ze+aM89rQMv2tRERCaoIDSEWCbaOHTszevTr7Nu3jyVLFjJgwCMnPG/XrkQaNTIAtGzZhjFj3mLTpo2cfnozoqKiiIqKyvFaKVxrtuznxU/mO+VX7+tCxXJaaVgk1CmBzYNVG3aT/NKTdMlIAWB3XBSfXFyJm5teR5v4Vnz23jz270l2zq9v4unRq5k+WRWRQnG0qdEQYpHgiYyM5JxzzmfIkCF07dqdqKgT/77FxyewZs3fNGzYiEWLFlC7dh1OO60u33zzFZmZmWRmZvLIIw8ybNhIYmNjC/lVyFHTFm3l45+00rBIOFICexLf/bSYJl+O4OgurjNbl2XB6aV5qcvTLJjyD+8vnumcW7JUDDfc1ZESJfVtFZHCp210RILrkksu59pre/Hpp1/neM5jjz3JiBHD8Hg8REVFMXjw09SsWYuOHTtzzz23k5mZyZVXXq3k1UUfTFrJrKXbAK00LBKOlGnlwOPxMOrlT+mx9henblzPitRu3IYHPOczbsR8v/Ov7d+eSvFljr2NiEihUQ+sSHBVrVqN5cuXk5iYlOM5jRs3YdSo946r79u3H3379gtmeHISHo+H/3tzFgcOpwFaaVgkXCmBPYFDKWn8/PhL9Eha59S91SeBm+vexryvdzCVrCEnPXo1o0GTBDfCFBHxowRWpHBs376dF1545rj61q3bcvvtd7kQkZxMcmo6942Y4ZS10rBI+FICe4y/N+7G8/xAmvvKa2vG8mOXeFosvYh5C3Y457XqWJvO5zRwJ0gRkRNQAitSOKpVq8Zbb73rdhiSR1sTD/L02D+d8tO3tKNe9fIuRiQiBaEENptfJs+j7lejnPLkzuWJK3kFTRdEkY53m4oq1cvR66bWREVpor+IhBYlsCIi/uYs3857369wym881JWypWJcjEhECkoJLN45EeNe+pAO67KGlnx+divi/2lFcrbz+t7bibLlSxZ+gCIieaBFnEREsnzw40pmLfEu1hQVGcE7j3YnUos1iYS9Yp/AJqemM2fgYDqk7AJgX4kKzK/di/h/ss65pM8Z1Klf2aUIRUTyRvvAioh4OybuHzmT5NR0ADo2rcpdlzdzOSoRCZRincBu2LCTIy8MohaQHhHNjAZX4yGrh7V1pzp06l7fvQBFRPJBQ4hFpLg7nJLG/SOztjjs17MJXbVYk0iRUmwT2Bnfz6Lat+/jAVZWOZNt5Rs7xyollKH3LW2IjtabQREJH0pgRaQ4W7t1P//+b9Y2h0P6tadO1XIuRiQiwVAsE9hvXhhB0w2L2V62HsurdfM7duPdHSlfoZRLkYmInLqoyGLZpEsx9PWaH1i4c2lA79m6yhlc1fDSHI8/8cSjXHPNdfTo0Z2VK5fzn/+M5eWXXzvuvPvvv5OGDRuzfv1aSpUqRYsWrfnzzzkcPHiQ1157i1mzpjNz5nQOHz7Evn376NevP927nxfQ11IcfT1jHT/M3uCU3xrQldIltViTSFFUrCZMpaamsfju/py2dT2/NbzVL3m96Kpm3DO4u5JXEQlbmgMrEjyXXdaLyZN/AODHH3/gssuuzPHcpk2b8frrb3PkSBolS5Zk5MjR1K1bj0WLFgCQnHyYESNGMWLEW7z55gjS09ML5TUURZkeDw+9MdNJXqtXLs3Yx85R8ipShBWbj+s3rdnMoaFDWFCnFykxWcNJzmhbk7MuaORiZCIigRGpIcRSTFzV8NJce0uDoWPHzowe/Tr79u1jyZKFDBjwSI7nNm7cBIBy5cpSt24939flOXIkFYBWrdoQGRlJpUqVKVeuPPv27SM+Pj74L6KI2ZuUysBRvzvlPuc05KKOdVyMSEQKg+sJrDEmEhgNtARSgf7W2jWBfMaUCV9yaMFOtjTo69SViyvJtf3bExOjN3wiEnyF0dZFK4EVCZrIyEjOOed8hgwZQteu3YmKyvn3LeIkW7VYuwqAPXt2c+jQISpWrBjQWN1UGG0dwP/+2sz4//3tlDXfVaT4cD2BBXoBJa21nY0xnYBXgSsCdfN3H3iW7bHtoELWJ5vX3dGeipXLBOoRIiJ5EdS2DrQPrEiwXXLJ5Vx7bS8+/fTrAt1nz57dPPTQPRw8eJCBAx/LNRkOQ0Ft6w4cOsJtL0/xqxszsBux6pAQKTZCIYE9C/gJwFr7hzGmXaBu/OHz35ISm3W7cy9rgmlWLVC3FxHJj6C1dUdFag6sSFBVrVqN5cuXk5iYlOM5b731rvP1c8+95Hz90EMDAfjxx+9p1aoN99zzQPACdVfQ2rrvf1/PxJnrnfLlXerSq6u2OxQpbkIhgS0P7M9WzjDGRFtrT7iiQcWKpfO8vU1KTJz3AXEHeejp6046pCdUJCSE1xCYcIo3nGIFxVvEBK2t82RGEhGZSZuGDShTouTJLwgR4fbzoniDJ5xiBUhLS+Kxxx47rr59+/Y8+OCDuV5brlxJSpeODbvXnA9Ba+tWbc667dgnL6BKpdIFibPQhNv/a8UbPOEUK4RuvKGQwB4Asn93InNq5AD27j2c5xvfM7g7CQnlSExMYteugwUIsfAcjTdchFO84RQrKN5TeX6IC1pbN/r8l53v/2HSChBi4XH75yW/FG/whFOs4I03JqYcr702+oTHT/Zauna9gK5dT35ebs8PcUFr6x69rlXWz0tGRlj83ITjz7fiDY5wihXcjze3ti4Uxpv9DlwM4JsrEdiN3UREQoPaOhEpDtTWiUhQhUIP7ETgAmPMbCAC6OdyPCIiwaC2TkSKA7V1IhJUriew1tpM4G634xARCSa1dSJSHKitE5FgC4UhxCIiIiIiIiInpQRWREREREREwoISWBEREREREQkLSmBFREREREQkLCiBFRERERERkbAQ4fF43I5BRERERERE5KTUAysiIiIiIiJhQQmsiIiIiIiIhAUlsCIiIiIiIhIWlMCKiIiIiIhIWFACKyIiIiIiImFBCayIiIiIiIiEhWi3AwgUY0wkMBpoCaQC/a21a7IdvwO4C0gHXrDW/uBKoOQp1v8DrvMVf7TWPlf4UWY5WbzZzpkEfGutHVP4UR4XS27f357As77iAuA+a61r+0nlId5HgOuBTOBFa+1EVwLNxhjTERhqre1+TP1lwDN4f88+sNa+50J4RZrauuBRWxdcauskP8KprfPFEzbtndq64FJbF3xFqQe2F1DSWtsZGAy8evSAMaYa8CDQBbgQeMkYU8KVKL1yi7U+cCNwJtAZ6GGMaeFKlFlyjDebF4BKhRpVznL7/pYDXgEutdZ2AjYA8W4EmU1u8VbA+7PbGegBjHQlwmyMMYOA94GSx9THACPwxtkNuNP3uyeBpbYueNTWBZfaOsmPcGrrILzaO7V1waW2LsiKUgJ7FvATgLX2D6BdtmMdgN+ttanW2v3AGsDNhiO3WDcDF1lrM6y1mUAMkFL4IfrJLV6MMVfj/RRpcuGHdkK5xXsmsBR41RgzE9hhrU0s/BD95BbvIWAjUMb3L7PQozveWuCqE9SfDqyx1u611h4BZgFdCzWy4kFtXfCorQsutXWSH+HU1kF4tXdq64JLbV2QFaUEtjywP1s5wxgTncOxJCCusAI7gRxjtdamWWt3GWMijDHDgYXW2tWuRJklx3iNMc2BG/AOLwgVuf0sxAPnAI8BPYEBxpjGhRzfsXKLF7x/+FbgHRbzRmEGdiLW2q+AtBMcCrXfs6JKbV3wqK0LLrV1kh/h1NZBeLV3auuCS21dkBWlBPYAUC5bOdJam57DsXLAvsIK7ARyixVjTElgnO+cews5thPJLd6bgZrAFOBW4GFjzEWFG95xcot3NzDPWrvdWnsQmAG0KuwAj5FbvD2B6kA9oA7QyxjToZDjy6tQ+z0rqtTWBY/auuBSWyf5EU5tHYRXe6e2LrjU1gVZUUpgfwcuBjDGdMI7nOCoP4GuxpiSxpg4vF3iywo/REeOsRpjIoBvgcXW2rustRnuhOgnx3ittYOstR19k74/Al6z1v7kRpDZ5PazMB9oboyJ930a1gnvp2Buyi3evUAykGqtTcHbcFQo9AjzZiXQyBhTyRgTC5wNzHE5pqJIbV3wqK0LLrV1kh/h1NZBeLV3auuCS21dkBWZVYiBicAFxpjZQATQzxjzMN6x298ZY94AZuJN2p/0/dCEXKxAFN6J0iV8q6oBPG6tdfMHJtfvrYtx5eRkPwuPAz/7zp1grXX7j97J4j0f+MMYk4l3/sGvLsZ6HGPMDUBZa+27vrh/xvt79oG1dqu70RVJauuCR21dcKmtk/wIp7YOwqu9U1sXXGrrgizC43FtlWkRERERERGRPCtKQ4hFRERERESkCFMCKyIiIiIiImFBCayIiIiIiIiEBSWwIiIiIiIiEhaUwIqIiIiIiEhYKErb6MgpMMbUBVZz/J5Z71lrRxlj7gCGAOOBqcB7wHRr7Q35fM5Ua+05vq8XWWsLtMm0MeYjYJq19qOC3OfY+wG/AO9bay8OxH1FJDSorfO/H2rrRIoktXX+90NtXZGkBFYA/sml4bke6Get/cUY8wHwnLX23VN4RvejXxS0kQsma+0/+DafFpEiR22dj9o6kSJNbZ2P2rqiSQms5MgY8wzQARjt2zC8F3C+b+PlacDbQGXgMPCAtXahMeY04EOgiq++v+8fxpi51tqOxhgPEANsAlpba3cYYyoBy4DTgPOAf/nOWQ/cYa3dnUucG4C5QCugL/AxsAtIBnoDY4FaQA3gf0fjAV4FLgX+wbvJ+DTfJ5fTrLV1jTHNgTeBsr7X85K1dowxZghQE2jki/d9a+2/jTElgVHAWUAa8Ly19nNjTHtgBFDaF9dd1tr1efzfICJBprZObZ1IcaC2Tm1dUaE5sAJQwxiz6Jh/Z1hr/wX8BfS31r4BfAc8Y619H/gPMMha2wa4E/jMd6/RwFfW2uZ4h6g8Za19EMBa2/HoA6216cAXwDW+qt7ARKAC8DJwobW2NfAzMDQPr2GytdYAOwED3GStvQC4BFhkre2Mt2HqBrTxPa810MwXQ8MT3LM/8IK1tj1wDvBKtmMtgB5AR2CwMaYC8ADeRvF04HzgGWNMLPA+cIPve/Uq3uE6IlL41NaprRMpDtTWqa0r0tQDK5D7UJPjGGPKAu2BD40xR6vLGmMq421Irgew1v4I/JjLrT7B+wnWW75rnsTbcNQBpvruHQXsyUNYc7N9vdNau8EXw6fGmA7GmAF4G6DKeBuj7sDX1to0INEYc6I4BwIXGWMeB87wXXfUVGvtEWCnMWYPEOd77e9aazOB7UAz36d9DYDvsn2vyufh9YhI4KmtU1snUhyorVNbV6QpgZVTEQWkZG8cjTG18DZIadnqIoDTrbXHLiQAgLV2njGmkm8oRi1r7RxjzBXALGvt5b57lMS/gclJ8om+NsY8AFwNvIt3mElzIALw+P57VPoJ7jkB2At8j/eTyOuzHUvJ9vXRe6X5vj767IZ4v1frjn6vjDFRQNU8vB4RcZ/aOrV1IsWB2jq1dWFFQ4gl36y1+4G/jTE3ARhjLgBm+A7PAK7zfX0+3gYGIMMYc6IPTMYB7wCf+spzgc7GmMa+8tPA8AKEewHwjrV2HFAS73yKKLyNXh9jTAljTEXgohyufcZa+y3QE5yGKiczgGuNMRHGmCrAdGADUMkY09V3zm14V/4TkRCnti5HautEihC1dTlSWxei1AMr4JsrcUzdjKNzHHJwIx/OfWQAAADvSURBVDDGGDMIOAJca631GGPuB943xtxL1mR/gG+BxcaYtsfc5xPgeeBaAGvtdmPMbcAEX6OyBbipAK9tJPC2b7jIfmA2UM9a+77vE8JleIeFnOjTxCHALGNMCrAYb6NVL5dnjQbe8J0L3gUQ9htjrgFe933qeAC4pQCvR0ROndo6tXUixYHaOrV1RVqEx+M5+VkiIiIiIiIiLtMQYhEREREREQkLSmBFREREREQkLCiBFRERERERkbCgBFZERERERETCghJYERERERERCQtKYEVERERERCQsKIEVERERERGRsKAEVkRERERERMLC/wPq6hWZ0wMLHAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1ef52441860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "temps = pvsystem.sapm_celltemp(total_irrad['poa_global'], 10, 5)\n",
    "\n",
    "sapm_2 = pvlib.pvsystem.sapm(effective_irradiance, temps['temp_cell'], module)\n",
    "\n",
    "plot_sapm(sapm_2, effective_irradiance)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'Comparison of a hot, calm day and a cold, windy day')"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1ef55d8da90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sapm_1['p_mp'].plot(label='30 C,  0 m/s')\n",
    "sapm_2['p_mp'].plot(label=' 5 C, 10 m/s')\n",
    "plt.legend()\n",
    "plt.ylabel('Pmp')\n",
    "plt.title('Comparison of a hot, calm day and a cold, windy day')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### SAPM IV curves"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The IV curve function only calculates the 5 points of the SAPM. We will add arbitrary points in a future release, but for now we just interpolate between the 5 SAPM points."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.simplefilter('ignore', np.RankWarning)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "def sapm_to_ivframe(sapm_row):\n",
    "    pnt = sapm_row\n",
    "\n",
    "    ivframe = {'Isc': (pnt['i_sc'], 0),\n",
    "              'Pmp': (pnt['i_mp'], pnt['v_mp']),\n",
    "              'Ix': (pnt['i_x'], 0.5*pnt['v_oc']),\n",
    "              'Ixx': (pnt['i_xx'], 0.5*(pnt['v_oc']+pnt['v_mp'])),\n",
    "              'Voc': (0, pnt['v_oc'])}\n",
    "    ivframe = pd.DataFrame(ivframe, index=['current', 'voltage']).T\n",
    "    ivframe = ivframe.sort_values(by='voltage')\n",
    "    \n",
    "    return ivframe\n",
    "\n",
    "def ivframe_to_ivcurve(ivframe, points=100):\n",
    "    ivfit_coefs = np.polyfit(ivframe['voltage'], ivframe['current'], 30)\n",
    "    fit_voltages = np.linspace(0, ivframe.loc['Voc', 'voltage'], points)\n",
    "    fit_currents = np.polyval(ivfit_coefs, fit_voltages)\n",
    "    \n",
    "    return fit_voltages, fit_currents"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1ef55d9cc18>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1ef55e04390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "times = ['2014-04-01 07:00:00', '2014-04-01 08:00:00', '2014-04-01 09:00:00', \n",
    "         '2014-04-01 10:00:00', '2014-04-01 11:00:00', '2014-04-01 12:00:00']\n",
    "times.reverse()\n",
    "\n",
    "fig, ax = plt.subplots(1, 1, figsize=(12,8))\n",
    "\n",
    "for time in times:\n",
    "    ivframe = sapm_to_ivframe(sapm_1.loc[time])\n",
    "\n",
    "    fit_voltages, fit_currents = ivframe_to_ivcurve(ivframe)\n",
    "\n",
    "    ax.plot(fit_voltages, fit_currents, label=time)\n",
    "    ax.plot(ivframe['voltage'], ivframe['current'], 'ko')\n",
    "    \n",
    "ax.set_xlabel('Voltage (V)')\n",
    "ax.set_ylabel('Current (A)')\n",
    "ax.set_ylim(0, None)\n",
    "ax.set_title('IV curves at multiple times')\n",
    "ax.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### desoto"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The same weather data run through the Desoto model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "calcparams_desoto() got an unexpected keyword argument 'alpha_sc'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-33-3b8f2876ffe0>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      7\u001b[0m                                \u001b[0mI_o_ref\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mcecmodule\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'I_o_ref'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      8\u001b[0m                                \u001b[0mR_sh_ref\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mcecmodule\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'R_sh_ref'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 9\u001b[1;33m                                R_s=cecmodule['R_s']) )\n\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m: calcparams_desoto() got an unexpected keyword argument 'alpha_sc'"
     ]
    }
   ],
   "source": [
    "photocurrent, saturation_current, resistance_series, resistance_shunt, nNsVth = (\n",
    "    pvsystem.calcparams_desoto(total_irrad['poa_global'],\n",
    "                               temp_cell=temps['temp_cell'],\n",
    "                               alpha_sc=cecmodule['alpha_sc'],\n",
    "                               a_ref=cecmodule['a_ref'],\n",
    "                               I_L_ref=cecmodule['I_L_ref'],\n",
    "                               I_o_ref=cecmodule['I_o_ref'],\n",
    "                               R_sh_ref=cecmodule['R_sh_ref'],\n",
    "                               R_s=cecmodule['R_s']) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'photocurrent' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-34-216ea8098a3e>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mphotocurrent\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      2\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mylabel\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Light current I_L (A)'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'photocurrent' is not defined"
     ]
    }
   ],
   "source": [
    "photocurrent.plot()\n",
    "plt.ylabel('Light current I_L (A)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'saturation_current' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-35-34fefecf2a4a>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0msaturation_current\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      2\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mylabel\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Saturation current I_0 (A)'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'saturation_current' is not defined"
     ]
    }
   ],
   "source": [
    "saturation_current.plot()\n",
    "plt.ylabel('Saturation current I_0 (A)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.094"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "resistance_series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 100)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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wd9kwIDlM6ihEPuVWkW5ubsaGDRu8nYWIfCDqvJM7WKSJyBMaWrg+mgKTW0s7Ro8ejR07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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x113dc9748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "resistance_shunt.plot()\n",
    "plt.ylabel('Shunt resistance (ohms)')\n",
    "plt.ylim(0,100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x11479d160>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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p1Yg/H+ZVI4nowVi0iYgeweHMMhRXtuCx8QGIjtCLjkMW9tTUMAwP8sS3V6pxsbBOdBwi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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115e0f710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nNsVth.plot()\n",
    "plt.ylabel('nNsVth')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Single diode model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/holmgren/git_repos/pvlib2/pvlib-python/pvlib/pvsystem.py:1943: RuntimeWarning: invalid value encountered in true_divide\n",
      "  I = -V/(Rs + Rsh) - (nNsVth/Rs)*lambertwterm + Rsh*(IL + I0)/(Rs + Rsh)\n"
     ]
    }
   ],
   "source": [
    "single_diode_out = pvsystem.singlediode(photocurrent, saturation_current,\n",
    "                                        resistance_series, resistance_shunt, nNsVth)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x116445a20>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ffFIpKSmX/X0NDTxQ4Q8pKTHM0o+Y5/vtPdmomsZOXTcxQ33dfWrovvKvnZmn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\nkAYAgA4MaQAA6MCQBgCADt4AQb364/ZbducAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114b59438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "single_diode_out['i_sc'].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x113d9aef0>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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tJkgDGNp8I9JVzJNGCCBIAyHgMCPSAIaJbHf/yh3ccIhQQJAGQkBVff+KHenJ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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114b6b5c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "single_diode_out['v_oc'].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1151764a8>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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FLMvYdqAekgRclRkpOg6Ry1k8IwIqpQLbD9bByq3wiOyCRZqI7KK8vgc1LX3I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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114b671d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "single_diode_out['p_mp'].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "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": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}