redline.ipynb

{
 "metadata": {
  "name": "",
  "signature": "sha256:bfe44d29fc5947024b7335e62798789170c8276f28732b4058ab8dd4959ebf0f"
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 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from __future__ import print_function, division\n",
      "\n",
      "import numpy as np\n",
      "import thinkstats2\n",
      "import thinkplot\n",
      "\n",
      "import redline\n",
      "\n",
      "%matplotlib inline\n",
      "formats = ['png', 'pdf']"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "gap_times = np.array(redline.OBSERVED_GAP_TIMES)\n",
      "len(gap_times), min(gap_times), max(gap_times)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 45,
       "text": [
        "(70, 143.0, 901.0)"
       ]
      }
     ],
     "prompt_number": 45
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pmf_z = thinkstats2.Pmf(gap_times, label='actual')\n",
      "cdf_z = pmf_z.MakeCdf()\n",
      "\n",
      "pmf_zb = redline.BiasPmf(pmf_z, label='biased')\n",
      "cdf_zb = pmf_zb.MakeCdf()\n",
      "\n",
      "pmf_y = redline.PmfOfWaitTime(pmf_z)\n",
      "cdf_y = pmf_y.MakeCdf()\n",
      "\n",
      "pmf_yb = redline.PmfOfWaitTime(pmf_zb)\n",
      "cdf_yb = pmf_yb.MakeCdf()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 46
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pmf_z.Mean() / 60, pmf_y.Mean() / 60"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 58,
       "text": [
        "(7.7680952380952384, 3.919047619047618)"
       ]
      }
     ],
     "prompt_number": 58
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pmf_zb.Mean() / 60, pmf_yb.Mean() / 60"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 52,
       "text": [
        "(8.7205184004577116, 4.3937886961319181)"
       ]
      }
     ],
     "prompt_number": 52
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "thinkplot.PrePlot(2)\n",
      "thinkplot.Plot(cdf_z.xs/60, cdf_z.ps, label=cdf_z.label)\n",
      "thinkplot.Config(xlabel='time between trains (minutes)', ylabel='CDF', loc='lower right')\n",
      "thinkplot.Save('redline1', formats=formats)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Writing redline1.png\n",
        "Writing"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " redline1.pdf\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<matplotlib.figure.Figure at 0x7f6283fe2c90>"
       ]
      }
     ],
     "prompt_number": 55
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "thinkplot.PrePlot(2)\n",
      "thinkplot.Plot(cdf_z.xs/60, cdf_z.ps, label=cdf_z.label)\n",
      "thinkplot.Plot(cdf_zb.xs/60, cdf_zb.ps, label=cdf_zb.label)\n",
      "thinkplot.Config(xlabel='time between trains (minutes)', ylabel='CDF', \n",
      "                 ylim=[0, 1], loc='lower right')\n",
      "thinkplot.Save('redline2', formats=formats)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Writing redline2.png\n",
        "Writing"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " redline2.pdf\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<matplotlib.figure.Figure at 0x7f6284027b50>"
       ]
      }
     ],
     "prompt_number": 56
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    }
   ],
   "metadata": {}
  }
 ]
}