| { |
| "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": 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VksXA1sAtQ/MPAf65Ot8AdkjymIZ1StrMVNWMbrsffdaMl5WkDTVlsKqqm4EPAjcCtwLr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\n/ZcmuSTJE5McleS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|
| "text/plain": [ |
| "<matplotlib.figure.Figure at 0x7f38d8630d50>" |
| ] |
| }, |
| "metadata": {}, |
| "output_type": "display_data" |
| }, |
| { |
| "data": { |
| "image/png": 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vd9ttt/zTP/3TAlT0r2b6PbsAAACwEIRdAACAGVtqz0raGmb9MxF2AQAAZmjZsmW57rrr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\nrkJggg==\n", |
| "text/plain": [ |
| "<matplotlib.figure.Figure at 0x7f38d882ffd0>" |
| ] |
| }, |
| "metadata": {}, |
| "output_type": "display_data" |
| }, |
| { |
| "data": { |
| "image/png": 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NB1eSJEmSJEmD0W8IPjfJJ4Gtk/wFcCnwqcGVJUmSJEnS2Ov37tAfTnIQcC/w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\nq6DI/dG6r/0AAAAASUVORK5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|
| "text/plain": [ |
| "<matplotlib.figure.Figure at 0x7f38d8c11fd0>" |
| ] |
| }, |
| "metadata": {}, |
| "output_type": "display_data" |
| }, |
| { |
| "data": { |
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|
| "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 |
| } |
