FactoryIO_JenksNaturalBreakTestingData.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#SCREENSHOT OF RUNNING SCENE IN FACTORY IO"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![title](images/Conveyor.PNG)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1>Testing the ideal range obatined on a corrupted data<h1>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Importing the csv file from factory io\n",
    "\n",
    "#Commenting out block of code for local machine usage\n",
    "#data = pd.read_csv('C:/Users/a.sethu/Desktop/Python/moving2.csv')\n",
    "#df = pd.DataFrame(data)\n",
    "\n",
    "#Importing the csv file created in factory io\n",
    "#File currently contains 6 Columns and 682,211 Rows\n",
    "data = pd.read_csv('data/moving2.zip')\n",
    "df = pd.DataFrame(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Importing the csv file from factory io\n",
    "\n",
    "#Commenting out block of code for local machine usage\n",
    "#data = pd.read_csv('C:/Users/a.sethu/Desktop/Python/normal.csv')\n",
    "#df = pd.DataFrame(data)\n",
    "\n",
    "#Importing the csv file created in factory io\n",
    "#File currently contains 6 Columns and 682,211 Rows\n",
    "import zipfile\n",
    "from zipfile import ZipFile\n",
    "file_name = \"data/moving2.zip\"\n",
    "with ZipFile(file_name, 'r') as zip:\n",
    "    # printing all the contents of the zip file\n",
    "    zip.printdir()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Subseting all Light Array Emitter data\n",
    "filteredLAE = df[df[' Name']=='Light Array Emitter 1 (Value)']\n",
    "#using a copy to prevent index warning\n",
    "filteredLAE = filteredLAE.copy()\n",
    "#converting the current value column to numeric\n",
    "filteredLAE[' Current Value'] = pd.to_numeric(filteredLAE[' Current Value'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sensor/Actuator</th>\n",
       "      <th>Data Type</th>\n",
       "      <th>Name</th>\n",
       "      <th>Address</th>\n",
       "      <th>Current Value</th>\n",
       "      <th>Time Elapsed</th>\n",
       "      <th>Sensor Value Difference</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6.783351</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6.883351</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6.975019</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.066686</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.166686</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>682130</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>192</td>\n",
       "      <td>4014.250000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>682147</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>192</td>\n",
       "      <td>4014.341000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>682164</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>192</td>\n",
       "      <td>4014.457000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>682181</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>192</td>\n",
       "      <td>4014.548000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>682198</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>192</td>\n",
       "      <td>4014.656000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>40130 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Sensor/Actuator  Data Type                           Name   Address  \\\n",
       "5               Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "22              Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "39              Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "56              Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "73              Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "...                ...        ...                            ...       ...   \n",
       "682130          Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "682147          Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "682164          Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "682181          Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "682198          Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "\n",
       "         Current Value   Time Elapsed   Sensor Value Difference  \n",
       "5                    0       6.783351                       NaN  \n",
       "22                   0       6.883351                       0.0  \n",
       "39                   0       6.975019                       0.0  \n",
       "56                   0       7.066686                       0.0  \n",
       "73                   0       7.166686                       0.0  \n",
       "...                ...            ...                       ...  \n",
       "682130             192    4014.250000                       0.0  \n",
       "682147             192    4014.341000                       0.0  \n",
       "682164             192    4014.457000                       0.0  \n",
       "682181             192    4014.548000                       0.0  \n",
       "682198             192    4014.656000                       0.0  \n",
       "\n",
       "[40130 rows x 7 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#using a copy to prevent index warning\n",
    "filteredLAE = filteredLAE.copy()\n",
    "filteredLAE[' Sensor Value Difference'] = filteredLAE[' Current Value'].diff()\n",
    "filteredLAE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sensor/Actuator</th>\n",
       "      <th>Data Type</th>\n",
       "      <th>Name</th>\n",
       "      <th>Address</th>\n",
       "      <th>Current Value</th>\n",
       "      <th>Time Elapsed</th>\n",
       "      <th>Sensor Value Difference</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1909</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>192</td>\n",
       "      <td>17.96656</td>\n",
       "      <td>64.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2266</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>20.07486</td>\n",
       "      <td>-192.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2538</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>192</td>\n",
       "      <td>21.68317</td>\n",
       "      <td>192.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2912</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23.88313</td>\n",
       "      <td>-192.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3694</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>192</td>\n",
       "      <td>28.46640</td>\n",
       "      <td>128.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>679869</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>192</td>\n",
       "      <td>4000.99300</td>\n",
       "      <td>192.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>680226</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4003.09300</td>\n",
       "      <td>-192.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>681076</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>192</td>\n",
       "      <td>4008.08200</td>\n",
       "      <td>192.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>681450</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4010.25700</td>\n",
       "      <td>-192.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>681994</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>192</td>\n",
       "      <td>4013.46100</td>\n",
       "      <td>192.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "<p>1297 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Sensor/Actuator  Data Type                           Name   Address  \\\n",
       "1909            Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "2266            Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "2538            Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "2912            Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "3694            Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "...                ...        ...                            ...       ...   \n",
       "679869          Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "680226          Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "681076          Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "681450          Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "681994          Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "\n",
       "         Current Value   Time Elapsed   Sensor Value Difference  \n",
       "1909               192       17.96656                      64.0  \n",
       "2266                 0       20.07486                    -192.0  \n",
       "2538               192       21.68317                     192.0  \n",
       "2912                 0       23.88313                    -192.0  \n",
       "3694               192       28.46640                     128.0  \n",
       "...                ...            ...                       ...  \n",
       "679869             192     4000.99300                     192.0  \n",
       "680226               0     4003.09300                    -192.0  \n",
       "681076             192     4008.08200                     192.0  \n",
       "681450               0     4010.25700                    -192.0  \n",
       "681994             192     4013.46100                     192.0  \n",
       "\n",
       "[1297 rows x 7 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Filtering sensor trigger data points from the data by removing \n",
    "#all all data with current value = 0\n",
    "filteredLAE = filteredLAE[filteredLAE[' Sensor Value Difference'] != 0]\n",
    "filteredLAE = filteredLAE[filteredLAE[' Current Value']!=128 ]\n",
    "filteredLAE = filteredLAE[filteredLAE[' Current Value']!=64 ]\n",
    "#Dropping al NaN values\n",
    "filteredLAE.dropna(subset = [' Sensor Value Difference'], inplace=True)\n",
    "filteredLAE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "filteredLAE[filteredLAE[' Sensor Value Difference'] > 0]\n",
    "filteredLAE['Trigger Status']=\"Off\"\n",
    "filteredLAE['Trigger Status'] = filteredLAE.apply(lambda x: 'On' if x[' Sensor Value Difference']>0 else 'Off',axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "filteredLAE['Trigger Interval'] = filteredLAE[\" Time Elapsed\"].diff(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "preprocessedDF = filteredLAE[filteredLAE['Trigger Status']=='On']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sensor/Actuator</th>\n",
       "      <th>Data Type</th>\n",
       "      <th>Name</th>\n",
       "      <th>Address</th>\n",
       "      <th>Current Value</th>\n",
       "      <th>Time Elapsed</th>\n",
       "      <th>Sensor Value Difference</th>\n",
       "      <th>Trigger Status</th>\n",
       "      <th>Trigger Interval</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2538</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>192</td>\n",
       "      <td>21.68317</td>\n",
       "      <td>192.0</td>\n",
       "      <td>On</td>\n",
       "      <td>3.71661</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3694</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>192</td>\n",
       "      <td>28.46640</td>\n",
       "      <td>128.0</td>\n",
       "      <td>On</td>\n",
       "      <td>6.78323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4731</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>192</td>\n",
       "      <td>34.56642</td>\n",
       "      <td>192.0</td>\n",
       "      <td>On</td>\n",
       "      <td>6.10002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6312</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>192</td>\n",
       "      <td>43.86673</td>\n",
       "      <td>192.0</td>\n",
       "      <td>On</td>\n",
       "      <td>9.30031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7094</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>192</td>\n",
       "      <td>48.47523</td>\n",
       "      <td>192.0</td>\n",
       "      <td>On</td>\n",
       "      <td>4.60850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>678611</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>192</td>\n",
       "      <td>3993.63800</td>\n",
       "      <td>192.0</td>\n",
       "      <td>On</td>\n",
       "      <td>6.09300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>679393</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>192</td>\n",
       "      <td>3998.21200</td>\n",
       "      <td>192.0</td>\n",
       "      <td>On</td>\n",
       "      <td>4.57400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>679869</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>192</td>\n",
       "      <td>4000.99300</td>\n",
       "      <td>192.0</td>\n",
       "      <td>On</td>\n",
       "      <td>2.78100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>681076</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>192</td>\n",
       "      <td>4008.08200</td>\n",
       "      <td>192.0</td>\n",
       "      <td>On</td>\n",
       "      <td>7.08900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>681994</th>\n",
       "      <td>Sensor</td>\n",
       "      <td>Int</td>\n",
       "      <td>Light Array Emitter 1 (Value)</td>\n",
       "      <td>0</td>\n",
       "      <td>192</td>\n",
       "      <td>4013.46100</td>\n",
       "      <td>192.0</td>\n",
       "      <td>On</td>\n",
       "      <td>5.37900</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>648 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Sensor/Actuator  Data Type                           Name   Address  \\\n",
       "2538            Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "3694            Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "4731            Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "6312            Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "7094            Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "...                ...        ...                            ...       ...   \n",
       "678611          Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "679393          Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "679869          Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "681076          Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "681994          Sensor        Int  Light Array Emitter 1 (Value)         0   \n",
       "\n",
       "         Current Value   Time Elapsed   Sensor Value Difference  \\\n",
       "2538               192       21.68317                     192.0   \n",
       "3694               192       28.46640                     128.0   \n",
       "4731               192       34.56642                     192.0   \n",
       "6312               192       43.86673                     192.0   \n",
       "7094               192       48.47523                     192.0   \n",
       "...                ...            ...                       ...   \n",
       "678611             192     3993.63800                     192.0   \n",
       "679393             192     3998.21200                     192.0   \n",
       "679869             192     4000.99300                     192.0   \n",
       "681076             192     4008.08200                     192.0   \n",
       "681994             192     4013.46100                     192.0   \n",
       "\n",
       "       Trigger Status  Trigger Interval  \n",
       "2538               On           3.71661  \n",
       "3694               On           6.78323  \n",
       "4731               On           6.10002  \n",
       "6312               On           9.30031  \n",
       "7094               On           4.60850  \n",
       "...               ...               ...  \n",
       "678611             On           6.09300  \n",
       "679393             On           4.57400  \n",
       "679869             On           2.78100  \n",
       "681076             On           7.08900  \n",
       "681994             On           5.37900  \n",
       "\n",
       "[648 rows x 9 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#using a copy to prevent index warning\n",
    "preprocessedDF = preprocessedDF.copy()\n",
    "preprocessedDF['Trigger Interval'] = preprocessedDF[\" Time Elapsed\"].diff(1)\n",
    "preprocessedDF.dropna(subset = ['Trigger Interval'], inplace=True)\n",
    "preprocessedDF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([], [])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "preprocessedDF=preprocessedDF.reset_index(drop=True)\n",
    "plt.figure(figsize=(12,8)) #Plotting the data points on the plot\n",
    "sns.stripplot(x='Trigger Interval',data = preprocessedDF,jitter= True,edgecolor = 'None')\n",
    "sns.despine\n",
    "locs,labels = plt.xticks()\n",
    "plt.yticks([])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1>Loading the JNOB(Jenks Natural Optimzation Breaks) obatined from ideal parameters<h1>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "import jenkspy\n",
    "#Finding the breaks using the Jenks natural breaks optimzation method\n",
    "# load the model from disk\n",
    "import pickle\n",
    "breaks = pickle.load(open('data/finalized_model.sav', 'rb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[3.201000000000022, 4.515600000000006, 5.8250000000000455, 7.231999999999971]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "breaks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#seaborn library for plotting\n",
    "import seaborn as sns\n",
    "plt.figure(figsize=(12,8)) #Plotting the data points on the plot\n",
    "sns.stripplot(x='Trigger Interval',data = preprocessedDF,jitter= True,edgecolor = 'None')\n",
    "sns.despine\n",
    "locs,labels = plt.xticks()\n",
    "plt.yticks([])\n",
    "#Drawing vertical lines usng the data points as x values\n",
    "for b in breaks:\n",
    "    plt.vlines(b,ymin= -0.2,ymax=0.2,color='k')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b><i>According to the box plot obtained in ideal paramters it was shown that the ideal range lies between 4.2 to 6.2. Taking this into account the valid range is the class obtained in the center of the plot</i></b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Trigger Interval'>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Box plot\n",
    "import numpy as np\n",
    "sns.boxplot(x='Trigger Interval', data=preprocessedDF, whis=np.inf)"
   ]
  },
  {
   "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": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}