{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## TEST K 20190410"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import serial\n",
    "import time\n",
    "import datetime\n",
    "import pandas as pd\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('seaborn-deep')\n",
    "import numpy as np\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Test Notes\n",
    "\n",
    "### Configuration ###\n",
    "\n",
    "* Test: `K`\n",
    "* NAL Power: `Internal 12VDC`\n",
    "* NAL Serial GND: `Connected to 12VDC GND`\n",
    "* CPF Power: `On, 12/5 Enabled`\n",
    "* CPF Electronics: `In Housing`\n",
    "* Motherboard: `Modified`\n",
    "### Log\n",
    "\n",
    "* `2019-04-10T09:30` Test started this is the first test running the motherboard with modified DCDC power stages. \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "filename = '20190410T093000_cpflog.csv'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "date,time,csq\n",
      "01-Jan-2007,00:03:20.639,2\n",
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      "01-Jan-2007,00:42:58.905,5\n"
     ]
    }
   ],
   "source": [
    "!echo date,time,csq> 20190410T093000_cpflog.csv\n",
    "!grep '+CSQ' 20190410T093000_cpflog.txt | awk '{print $2\",\"$3\",\"$7}' | sed 's/+CSQ://g'>>20190410T093000_cpflog.csv\n",
    "!cat 20190404T083000_cpflog.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = pd.read_csv(filename)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 361 entries, 0 to 360\n",
      "Data columns (total 3 columns):\n",
      "date    361 non-null object\n",
      "time    361 non-null object\n",
      "csq     361 non-null int64\n",
      "dtypes: int64(1), object(2)\n",
      "memory usage: 8.5+ KB\n"
     ]
    }
   ],
   "source": [
    "df2.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>time</th>\n",
       "      <th>csq</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>01-Jan-2007</td>\n",
       "      <td>00:03:20.639</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>01-Jan-2007</td>\n",
       "      <td>00:03:39.072</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>01-Jan-2007</td>\n",
       "      <td>00:03:40.964</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>01-Jan-2007</td>\n",
       "      <td>00:03:56.335</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>01-Jan-2007</td>\n",
       "      <td>00:04:00.741</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          date          time  csq\n",
       "0  01-Jan-2007  00:03:20.639    2\n",
       "1  01-Jan-2007  00:03:39.072    5\n",
       "2  01-Jan-2007  00:03:40.964    5\n",
       "3  01-Jan-2007  00:03:56.335    4\n",
       "4  01-Jan-2007  00:04:00.741    0"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['date', 'time', 'csq'], dtype='object')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## \n",
    "df2.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'Test K: Housing Closed, CPF On, 5V On, 12V On, CPF connected to NAL')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bins = np.arange(7)-0.5\n",
    "\n",
    "fig = df2.csq.hist(figsize=(10,5), align='mid', bins=bins, edgecolor=\"black\")\n",
    "bins = np.arange(7)-0.5\n",
    "fig.set_xlabel(\"CSQ REPLY (RSSI)\")\n",
    "fig.set_ylabel(\"COUNT\")\n",
    "fig.set_title(\"Test K: Housing Closed, CPF On, 5V On, 12V On, CPF connected to NAL\")\n",
    "#Determine Test Length\n",
    "#date_str = f\"Test Start: {df2.date[0]}\\nTest End: {df2.date.iloc[-1]} \"\n",
    "#plt.text(0,150,date_str);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,0,'Time')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plot CSQ over time\n",
    "import matplotlib.dates as mdates\n",
    "ax = df2.plot(kind='line',x='time',y='csq', figsize=(10,5))\n",
    "#ax.xaxis.set_major_locator(plt.MaxNLocator(4))\n",
    "ax.set_title(\"Test K Time Series\")\n",
    "ax.set_ylabel(\"CSQ (RSSI)\")\n",
    "ax.set_xlabel(\"Time\")"
   ]
  },
  {
   "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": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}