Global_latency_demo.ipynb

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 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from trace import Trace"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": [
    "import os"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Parse trace"
   ]
  },
  {
   "cell_type": "code",
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    "collapsed": true
   },
   "outputs": [],
   "source": [
    "d = \"{}/ipynb/tutorial/example_results/\".format(os.getenv('LISA_HOME'))\n",
    "with open(\"{}/platform.json\".format(d)) as f:\n",
    "    platform = json.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": [
    "trace = Trace(platform, '{}/trace.dat'.format(d), ['sched_switch', 'sched_wakeup'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Get DataFrame with `sched_switch` & `sched_wakeup`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "switch_in = trace.data_frame.trace_event('sched_switch')[['next_pid']]\n",
    "wake = trace.data_frame.trace_event('sched_wakeup')[['pid']]\n",
    "df = wake.join(switch_in, how='outer')\n",
    "df = df.rename(columns={'next_pid': 'switch_in_pid', 'pid': 'wake_pid'})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Find wakeup latencies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "wakeup_times = {}\n",
    "lats = []\n",
    "def f(row):\n",
    "    time = row.name\n",
    "    if not np.isnan(row.wake_pid):\n",
    "        wakeup_times[row.wake_pid] = time\n",
    "        lats.append(None)\n",
    "    else:\n",
    "        if row.switch_in_pid in wakeup_times:\n",
    "            lats.append(time - wakeup_times[row.switch_in_pid])\n",
    "        else:\n",
    "            lats.append(None)\n",
    "df.apply(f, axis=1)\n",
    "ldf = pd.DataFrame({'latency': lats, 'pid': df.switch_in_pid}).dropna()"
   ]
  }
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