{
 "metadata": {
  "name": "",
  "signature": "sha256:c99e2b20fedbcf3c0a9288eeba51f01082263fb209ae55f3c30ac2dd6241e4d6"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%matplotlib inline\n",
      "\n",
      "import pandas as pd\n",
      "\n",
      "import matplotlib.pyplot as plt\n",
      "import seaborn as sns\n",
      "\n",
      "import logging\n",
      "logging.getLogger('pvlib').setLevel(logging.DEBUG)\n",
      "\n",
      "import pvlib"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "times = pd.date_range('2014-01-01', '2015-01-01', freq='1D')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pvlib.irradiance.extraradiation(300, method='asce')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "DEBUG:pvlib:irradiance.extraradiation()\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "DEBUG:pvlib:Calculating ET rad using ASCE method\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 3,
       "text": [
        "1385.7848051831807"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pvlib.irradiance.extraradiation(300, method='spencer')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "DEBUG:pvlib:irradiance.extraradiation()\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "DEBUG:pvlib:Calculating ET rad using Spencer method\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 4,
       "text": [
        "1384.3999948908033"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pvlib.irradiance.extraradiation(300, method='pyephem')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "DEBUG:pvlib:irradiance.extraradiation()\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "DEBUG:pvlib:Calculating ET rad using pyephem method\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "DEBUG:pvlib:solarposition.pyephem_earthsun_distance()\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 5,
       "text": [
        "2014-10-27    1382.618665\n",
        "dtype: float64"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "spencer = pd.Series(pvlib.irradiance.extraradiation(times.dayofyear, method='spencer'), times)\n",
      "asce = pd.Series(pvlib.irradiance.extraradiation(times.dayofyear, method='asce'), times)\n",
      "ephem = pvlib.irradiance.extraradiation(times, method='pyephem')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "DEBUG:pvlib:irradiance.extraradiation()\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "DEBUG:pvlib:Calculating ET rad using Spencer method\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "DEBUG:pvlib:irradiance.extraradiation()\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "DEBUG:pvlib:Calculating ET rad using ASCE method\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "DEBUG:pvlib:irradiance.extraradiation()\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "DEBUG:pvlib:Calculating ET rad using pyephem method\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "DEBUG:pvlib:solarposition.pyephem_earthsun_distance()\n"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.figure(figsize=(12,6))\n",
      "spencer.plot(label='spencer')\n",
      "asce.plot(label='asce')\n",
      "ephem.plot(label='pyephem')\n",
      "plt.legend()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 7,
       "text": [
        "<matplotlib.legend.Legend at 0x5bfd1d0>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAtYAAAF+CAYAAACmt13YAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x5b15050>"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "logging.getLogger('pvlib').setLevel(logging.WARNING)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%timeit\n",
      "\n",
      "spencer = pd.Series(pvlib.irradiance.extraradiation(times.dayofyear, method='spencer'), times)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "1000 loops, best of 3: 174 \u00b5s per loop\n"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%timeit\n",
      "\n",
      "asce = pd.Series(pvlib.irradiance.extraradiation(times.dayofyear, method='asce'), times)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "10000 loops, best of 3: 114 \u00b5s per loop\n"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%timeit\n",
      "\n",
      "ephem = pvlib.irradiance.extraradiation(times, method='pyephem')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "100 loops, best of 3: 19.4 ms per loop\n"
       ]
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 11
    }
   ],
   "metadata": {}
  }
 ]
}