{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import time\n",
    "from datetime import datetime\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib qt5\n",
    "\n",
    "def unpack_line(str):\n",
    "    time_format = \"%d.%m.%Y %H:%M:%S.%f\"\n",
    "    index_1 = str.find(';')\n",
    "    index_2 = str.find(';',index_1+1)\n",
    "    index_3 = str.find(';',index_2+1)\n",
    "    index_4 = str.find(';',index_3+1)\n",
    "    index_5 = str.find(';',index_4+1)\n",
    "    parameter   = str[0:index_1]\n",
    "    value       = float(str[index_2+1:index_3])\n",
    "    timestamp   = time.mktime(datetime.strptime(str[index_5+1:-2],time_format).timetuple())\n",
    "    return parameter,value,timestamp\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "M1_LA_df    = pd.DataFrame(columns=['Timestamp','M1-LA'])\n",
    "M2_LA_df    = pd.DataFrame(columns=['Timestamp','M2-LA'])\n",
    "M1_Druck_df = pd.DataFrame(columns=['Timestamp','M1-Druck'])\n",
    "M2_Druck_df = pd.DataFrame(columns=['Timestamp','M2-Druck'])\n",
    "\n",
    "\n",
    "parameter_old    = ''\n",
    "value_list      = []\n",
    "timestamp_list  = []\n",
    "with open('Juni_1_22.txt') as txt_file:\n",
    "    for line in txt_file:\n",
    "        parameter_new, value_new, timestamp_new = unpack_line(line)\n",
    "        if parameter_new != parameter_old:\n",
    "            if 'M1' in parameter_old and 'Stell_Leitapparat' in parameter_old:\n",
    "                M1_LA_df['Timestamp']       = timestamp_list[:]\n",
    "                M1_LA_df['M1-LA']           = value_list[:]\n",
    "            if 'M1' in parameter_old and 'Spiraldruck' in parameter_old:\n",
    "                M1_Druck_df['Timestamp']    = timestamp_list[:]\n",
    "                M1_Druck_df['M1-Druck']     = value_list[:]\n",
    "            if 'M2' in parameter_old and 'Stell_Leitapparat' in parameter_old:\n",
    "                M2_LA_df['Timestamp']       = timestamp_list[:]\n",
    "                M2_LA_df['M2-LA']           = value_list[:]\n",
    "            if 'M2' in parameter_old and 'Spiraldruck' in parameter_old:\n",
    "                M2_Druck_df['Timestamp']    = timestamp_list[:]\n",
    "                M2_Druck_df['M2-Druck']     = value_list[:]\n",
    "            \n",
    "            value_list      = []\n",
    "            timestamp_list  = []\n",
    "            value_list.append(value_new)\n",
    "            timestamp_list.append(timestamp_new)\n",
    "\n",
    "            parameter_old   = parameter_new\n",
    "        else:\n",
    "            if value_new != value_list[-1]:\n",
    "                value_list.append(value_new)\n",
    "                timestamp_list.append(timestamp_new) \n",
    "\n",
    "    if 'M1' in parameter_old and 'Stell_Leitapparat' in parameter_old:\n",
    "        M1_LA_df['Timestamp']       = timestamp_list[:]\n",
    "        M1_LA_df['M1-LA']           = value_list[:]\n",
    "    if 'M1' in parameter_old and 'Spiraldruck' in parameter_old:\n",
    "        M1_Druck_df['Timestamp']    = timestamp_list[:]\n",
    "        M1_Druck_df['M1-Druck']     = value_list[:]\n",
    "    if 'M2' in parameter_old and 'Stell_Leitapparat' in parameter_old:\n",
    "        M2_LA_df['Timestamp']       = timestamp_list[:]\n",
    "        M2_LA_df['M2-LA']           = value_list[:]\n",
    "    if 'M2' in parameter_old and 'Spiraldruck' in parameter_old:\n",
    "        M2_Druck_df['Timestamp']    = timestamp_list[:]\n",
    "        M2_Druck_df['M2-Druck']     = value_list[:]\n",
    "\n",
    "M1_LA_df.set_index(['Timestamp'],inplace=True)\n",
    "M1_Druck_df.set_index(['Timestamp'],inplace=True)\n",
    "M2_LA_df.set_index(['Timestamp'],inplace=True)\n",
    "M2_Druck_df.set_index(['Timestamp'],inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2e6c96b7430>]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig1=plt.figure()\n",
    "plt.plot(M1_LA_df['M1-LA'])\n",
    "fig2=plt.figure()\n",
    "plt.plot(M1_Druck_df['M1-Druck'])\n",
    "fig3=plt.figure()\n",
    "plt.plot(M2_LA_df['M2-LA'])\n",
    "fig4=plt.figure()\n",
    "plt.plot(M2_Druck_df['M2-Druck'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = M1_LA_df.join([M2_LA_df,M1_Druck_df,M2_Druck_df],how='outer')\n",
    "df.sort_index(axis=0,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2e6c8733c10>]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig1=plt.figure()\n",
    "plt.plot(df['M1-LA'])\n",
    "fig2=plt.figure()\n",
    "plt.plot(df['M1-Druck'])\n",
    "fig3=plt.figure()\n",
    "plt.plot(df['M2-LA'])\n",
    "fig4=plt.figure()\n",
    "plt.plot(df['M2-Druck'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "t_vec = df.index.to_numpy()\n",
    "M1_LA = df['M1-LA'].to_numpy() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2e6c8563340>]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig5=plt.figure()\n",
    "plt.plot(t_vec,M1_LA)"
   ]
  }
 ],
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