VILLASnode/tests/benchmarks/evaluate_logs.ipynb

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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Benchmark"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Settings\n",
    "root_dir = '/home/dennis/VILLASnode/tests'\n",
    "benchmark_dir = 'benchmarks_20180730_17-16-39'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load all files\n",
    "Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loaded /home/dennis/VILLASnode/tests/benchmarks_20180730_17-16-39/0_TCP-3-10-300.log\n",
      "Loaded /home/dennis/VILLASnode/tests/benchmarks_20180730_17-16-39/1_TCP-3-100-300.log\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import os\n",
    "\n",
    "# Initialize arrays\n",
    "result_files = []\n",
    "result_paths = []\n",
    "result_array = []\n",
    "\n",
    "# Save complete path of files in an array\n",
    "for subdir, dirs, files in os.walk(root_dir+'/'+benchmark_dir):\n",
    "    for file in files:\n",
    "        result_paths.append(os.path.join(subdir, file))\n",
    "        \n",
    "    result_files = files\n",
    "\n",
    "# Loop through array with files and save the comma separated data into a new array\n",
    "for file in result_paths:\n",
    "    print(\"Loaded {}\".format(file))\n",
    "    \n",
    "    # Load file \n",
    "    result_array.append(np.genfromtxt(file, delimiter=','))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Save characteristics of tests\n",
    "All important settings are contained in the name of the file. We will save them in a separate array. The structure of the name is as follows:\n",
    "\n",
    "```bash\n",
    "root_dir/benchmarks_${DATE}/${ID}_${MODE}-${VALUES IN SMP}-${RATE}-${SENT SMPS}\n",
    "```\n",
    "\n",
    "Thus, we will structure it in the settings_array as follows:\n",
    "\n",
    "* `settings_array[*][0] = ID`\n",
    "* `settings_array[*][1] = MODE`\n",
    "* `settings_array[*][2] = VALUES IN SAMPLE`\n",
    "* `settings_array[*][3] = RATE`\n",
    "* `settings_array[*][4] = TOTAL NUMBER OF SAMPLES`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import re\n",
    "\n",
    "# Initialize arrays\n",
    "settings_array = []\n",
    "\n",
    "for file in result_files:\n",
    "    settings = []\n",
    "    \n",
    "    matchObj = re.match( r'(\\d*)_(\\w*)-(\\d*)-(\\d*)-(\\d*).log', file, re.M|re.I)\n",
    "\n",
    "    # Fill values to array\n",
    "    for i in range(0,4):\n",
    "        settings.append(matchObj.group(i))\n",
    "    \n",
    "    # Append array to big array\n",
    "    settings_array.append(settings)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Process data\n",
    "\n",
    "### Number of samples\n",
    "* First number which appears in `result_array[*][3]` will be the first sample in the benchmark. Ignore all missing samples before that entry.\n",
    "* After that, check how many samples are missing."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "###"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "###"
   ]
  }
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