{
 "metadata": {
  "name": "",
  "signature": "sha256:1aae17bbf83989324e5ea2689394d9c4668379c714534666e2d0ae76787cb304"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%pylab inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Populating the interactive namespace from numpy and matplotlib\n"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pickle \n",
      "\n",
      "# get the file here: https://github.com/poppy-project/pypot/releases/download/2.4.0/data.pickle",
      "with open('data.pickle') as f:\n",
      "    data = pickle.load(f)\n",
      "    \n",
      "packets = data['packet']"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "to_plot = (('dell', '2.7.8'),\n",
      "           ('dell', 'pypy-2.3.1'),\n",
      "\n",
      "           ('odroid', '2.7.8'),\n",
      "           ('odroid', 'pypy-2.3.1'),\n",
      "           \n",
      "           ('pi', '2.7.8'),\n",
      "           ('pi', 'pypy-2.3.1'))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "indices = array([0.5, 1.0, \n",
      "                 2.0, 2.5,\n",
      "                 3.5, 4.0])\n",
      "\n",
      "color = {'serial': 'b',\n",
      "         'forged': 'r',\n",
      "         'pypot': 'g'}\n",
      "\n",
      "width = 0.4\n",
      "\n",
      "with xkcd():\n",
      "    fig = plt.figure()\n",
      "    ax = fig.add_axes((0.1, 0.2, 0.8, 0.7))\n",
      "    \n",
      "    for s in ['pypot', 'forged', 'serial']:\n",
      "        x = [mean(packets[s][b][p]) * 1000 for b, p in to_plot]\n",
      "        ax.bar(indices, x, width, color=color[s])\n",
      "    \n",
      "    ax.spines['right'].set_color('none')\n",
      "    ax.spines['top'].set_color('none')\n",
      "    ax.xaxis.set_ticks_position('bottom')\n",
      "    ax.yaxis.set_ticks_position('left')\n",
      "\n",
      "    ax.set_xticks(indices + width/2)\n",
      "    \n",
      "    ax.set_xticklabels(['2.7.8\\n               PC',\n",
      "                        'PyPy',\n",
      "                        '2.7.8\\n             Odroid',\n",
      "                        'PyPy',\n",
      "                        '2.7.8\\n                Raspberry pi',\n",
      "                        'PyPy'])\n",
      "\n",
      "    plt.ylabel('time (ms)')\n",
      "    plt.title(\"BOARDS COMPARISON\")\n",
      "    legend(['pypot', 'preforged-packet', 'raw serial'], loc='best')\n",
      "    savefig('packet.png')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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pBAIZEGIOkCAzajC1ARl1ldFoFIOheVsxldWsotLWqD6FtqW6ujoZIZhuZNAZ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\nBkOGiQKDwWAwZJgoMBgMBkPm/wMiMeNTdgPRqgAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10bd0f610>"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}
