{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "source": [
    "# YouTube energy comparison for turning off iowait boost\n",
    "\n",
    "Test: Run YouTube video for 30 seconds, and collect energy 15 times (total test time 7.5 minutes)\n",
    "Wifi was turned off and video played back with youtube red"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false,
    "run_control": {
     "frozen": false,
     "marked": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "%pylab inline\n",
    "\n",
    "import pandas as pd\n",
    "import sqlite3\n",
    "import matplotlib.cm as cm\n",
    "import os, json\n",
    "from collections import namedtuple\n",
    "\n",
    "# Provide the root path where your test folders are stored\n",
    "results_dir = '/home/joelaf/repo/lisa/results/wifi-off/'\n",
    "\n",
    "# Provide the names of the results folders you want compared\n",
    "all_test_dirs = [\n",
    "                 \"yt_schedutil_energy_1.2_30s_run1\",\n",
    "                 \"yt_schedutil_energy_1.2_30s_noiowaitboost_run2\",\n",
    "                 \"yt_schedutil_energy_1.2_bigsoff\"\n",
    "                ]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "source": [
    "# Plot histograms of energy consumed for tests"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false,
    "run_control": {
     "frozen": false,
     "read_only": false
    },
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       schedutil_energy_1.2_30s_run1\n",
      "count                      15.000000\n",
      "mean                        8.042533\n",
      "std                         0.039394\n",
      "min                         7.966584\n",
      "25%                         8.014455\n",
      "50%                         8.051294\n",
      "75%                         8.058296\n",
      "max                         8.110917\n",
      "       schedutil_energy_1.2_30s_noiowaitboost_run2\n",
      "count                                    15.000000\n",
      "mean                                      7.948377\n",
      "std                                       0.039497\n",
      "min                                       7.897061\n",
      "25%                                       7.910292\n",
      "50%                                       7.957902\n",
      "75%                                       7.977662\n",
      "max                                       8.005220\n",
      "       schedutil_energy_1.2_bigsoff\n",
      "count                     15.000000\n",
      "mean                       7.580664\n",
      "std                        0.037787\n",
      "min                        7.532140\n",
      "25%                        7.547024\n",
      "50%                        7.573458\n",
      "75%                        7.611389\n",
      "max                        7.641877\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAlYAAAF2CAYAAACs4da0AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nIgsQAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f38d8630d50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA7sAAAE/CAYAAACHJNQRAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f38d882ffd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA8EAAAE/CAYAAABmT8FAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nq6DI/dG6r/0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f38d8c11fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA8EAAAE/CAYAAABmT8FAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nJEnqDEOwJEmSJKkzDMGSJEmSpM74/+feTXHLqC4WAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f38d81b07d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot a box plot\n",
    "fig, axes = plt.subplots()\n",
    "df_all = []\n",
    "for test in all_test_dirs:\n",
    "    test_dir = results_dir + \"/\" + test\n",
    "    with open(test_dir + \"/energy_all_runs.json\") as f:\n",
    "        samples = json.load(f)['energy_samples']\n",
    "    df = pd.DataFrame(samples, columns=[test[3:]])\n",
    "    print df.describe()\n",
    "    df_all.append(df)\n",
    "\n",
    "df_box = pd.concat(df_all, axis=1)\n",
    "axes = df_box.plot.box(figsize=(10, 6), ax=axes, ylim=(7.4,8.2), title=\"Box plot comparing energy samples\")\n",
    "\n",
    "# Plot a histogram of energy values collected\n",
    "def plot_energy(test):\n",
    "    test_dir = results_dir + \"/\" + test\n",
    "    with open(test_dir + \"/energy_all_runs.json\") as f:\n",
    "        samples = json.load(f)['energy_samples']\n",
    "    df = pd.DataFrame(samples, columns=['energy'])\n",
    "    fig, axes = plt.subplots()\n",
    "    # print axes\n",
    "    df.plot(kind='hist', bins=32, xlim=(6,10), title=test, figsize=(16,5), ax=axes)\n",
    "\n",
    "for t in all_test_dirs:\n",
    "    plot_energy(t)\n"
   ]
  }
 ],
 "metadata": {
  "hide_input": false,
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.13"
  },
  "toc": {
   "colors": {
    "hover_highlight": "#DAA520",
    "running_highlight": "#FF0000",
    "selected_highlight": "#FFD700"
   },
   "moveMenuLeft": true,
   "nav_menu": {
    "height": "189px",
    "width": "252px"
   },
   "navigate_menu": true,
   "number_sections": true,
   "sideBar": true,
   "threshold": 4,
   "toc_cell": false,
   "toc_number_sections": true,
   "toc_section_display": "block",
   "toc_threshold": 6,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}