{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, process the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[31mCompassTestAnalysis.ipynb\u001b[m\u001b[m     \u001b[31mtest_2_bootdiffs.png\u001b[m\u001b[m\r\n",
      "\u001b[31mMicrostrain_FaultTesting.html\u001b[m\u001b[m \u001b[31mtest_2_log.txt\u001b[m\u001b[m\r\n",
      "\u001b[31mMicrostrain_FaultTesting.txt\u001b[m\u001b[m  \u001b[31mtest_2_results.txt\u001b[m\u001b[m\r\n",
      "\u001b[31mplot_times.py\u001b[m\u001b[m                 \u001b[31mtest_2_times.txt\u001b[m\u001b[m\r\n",
      "\u001b[31mprocess_log.sh\u001b[m\u001b[m                \u001b[31mtest_3_bootdiffs.png\u001b[m\u001b[m\r\n",
      "\u001b[31mprocess_log_times.sh\u001b[m\u001b[m          \u001b[31mtest_3_log.txt\u001b[m\u001b[m\r\n",
      "\u001b[31mtest_1_bootdiffs.png\u001b[m\u001b[m          \u001b[31mtest_3_log_cleaned.txt\u001b[m\u001b[m\r\n",
      "\u001b[31mtest_1_log.txt\u001b[m\u001b[m                \u001b[31mtest_3_times.txt\u001b[m\u001b[m\r\n",
      "\u001b[31mtest_1_results.txt\u001b[m\u001b[m            \u001b[31mtest_4_log.txt\u001b[m\u001b[m\r\n",
      "\u001b[31mtest_1_times.txt\u001b[m\u001b[m\r\n"
     ]
    }
   ],
   "source": [
    "!ls\n",
    "!./process_log_times.sh test_1_log.txt > test_1_times.txt\n",
    "!./process_log_times.sh test_2_log.txt > test_2_times.txt\n",
    "!./process_log_times.sh test_3_log_cleaned.txt > test_3_times.txt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[31mtest_1_times.txt\u001b[m\u001b[m \u001b[31mtest_2_times.txt\u001b[m\u001b[m \u001b[31mtest_3_times.txt\u001b[m\u001b[m\r\n"
     ]
    }
   ],
   "source": [
    "!ls *times.txt*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import pandas as pd\n",
    "import matplotlib\n",
    "matplotlib.rcParams['figure.dpi'] = 200\n",
    "matplotlib.rcParams['text.usetex'] = True\n",
    "matplotlib.rcParams['text.latex.unicode'] = True\n",
    "import matplotlib.pyplot as plt\n",
    "import datetime\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_time_between_boots(fname):\n",
    "    data = pd.read_csv(fname, delimiter=',', header=None, names=['date'], parse_dates=['date'])\n",
    "    data2 = data.assign(delta = pd.to_timedelta(data.date).apply(pd.Timedelta.total_seconds).diff())\n",
    "    fig1 = plt.figure(figsize=(10,4))\n",
    "    ax1 = fig1.add_subplot(111)\n",
    "    ax1.plot(data.date,pd.to_timedelta(data.date).apply(pd.Timedelta.total_seconds).diff(),'.')\n",
    "    ax1.set_ylabel('Seconds Between Restarts')\n",
    "    \n",
    "    return ax1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processing File: test_1_log.txt\r\n",
      "SUCCESS rate is      241 detections for      241 tests.\r\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10debca58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "!./process_log.sh test_1_log.txt\n",
    "ax1 = plot_time_between_boots('test_1_times.txt')\n",
    "ax1.set_title('Test 1: Powered Through External PSU Windows Self-Rebooting')\n",
    "plt.savefig('test_1_bootdiffs.png', dpi=300)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processing File: test_2_log.txt\r\n",
      "SUCCESS rate is      426 detections for      426 tests.\r\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x11608e320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "!./process_log.sh test_2_log.txt\n",
    "ax2 = plot_time_between_boots('test_2_times.txt')\n",
    "ax2.set_title('Test 2: Powered Through Murata DC/DC Windows Self-Rebooting');\n",
    "ax2.text('07-16-19 17:20',400, '$\\leftarrow$ User intervention, test was paused.')\n",
    "plt.savefig('test_2_bootdiffs.png', dpi=300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processing File: test_3_log_cleaned.txt\r\n",
      "SUCCESS rate is      293 detections for      293 tests.\r\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10897c080>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "!./process_log.sh test_3_log_cleaned.txt\n",
    "ax3 = plot_time_between_boots('test_3_times.txt')\n",
    "ax3.set_title('Test 3: Powered Through Murata DC/DC, Using Relay to Fully Remove Power');\n",
    "ax3.text('07-18-19 05:00:00', 400, '${\\leftarrow}$ Higher variability could either be\\nfailed boots or jitter in system clock \\non power cycle.')\n",
    "plt.savefig('test_3_bootdiffs.png', dpi=300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processing File: test_4_log.txt\r\n",
      "SUCCESS rate is       38 detections for       38 tests.\r\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10898e780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "!./process_log.sh test_4_log.txt\n",
    "!./process_log_times.sh test_4_log.txt > test_4_times.txt\n",
    "ax4 = plot_time_between_boots('test_4_times.txt')\n",
    "ax4.set_title('Test 4: Powered Through Traco DC/DC (New), Self Restartings');\n",
    "ax4.set_ylim(0, 600)\n",
    "#ax3.text('07-18-19 05:00:00', 400, '${\\leftarrow}$ Higher variability could \n",
    "#either be\\nfailed boots or jitter in system clock \\non power cycle.')\n",
    "plt.savefig('test_4_bootdiffs.png', dpi=300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processing File: test_5_log.txt\r\n",
      "SUCCESS rate is      235 detections for      235 tests.\r\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10a0e6438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "!./process_log.sh test_5_log.txt\n",
    "!./process_log_times.sh test_5_log.txt > test_5_times.txt\n",
    "ax5= plot_time_between_boots('test_5_times.txt')\n",
    "ax5.set_title('Test 5: Powered Through Traco DC/DC (New), Using Relay to Fully Remove Power')\n",
    "ax5.set_ylim(0, 600)\n",
    "#ax3.text('07-18-19 05:00:00', 400, '${\\leftarrow}$ Higher variability could \n",
    "#either be\\nfailed boots or jitter in system clock \\non power cycle.')\n",
    "plt.savefig('test_5_bootdiffs.png', dpi=300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}