Trying options for version 1.10

Internal_design_documents/Experiments/.ipynb_checkpoints/LinearRegression-checkpoint.ipynb

@@ -1,6 +0,0 @@
-{
- "cells": [],
- "metadata": {},
- "nbformat": 4,
- "nbformat_minor": 2
-}

README.md

@@ -8,10 +8,33 @@ This is a unified library to use sensors MQ: 2, 3, 4, 5, 6, 7, 8, 9, 131, 135, 3
 ## Getting Started
 
 ```
-MQUnifiedsensor MQ4(pin, 4); //Example if sensor is MQ4, type = 4
+#define placa "Arduino UNO"
+#define Voltage_Resolution 5
+#define pin A0 //Analog input 0 of your arduino
+#define type "MQ-4" //MQ4
+#define ADC_Bit_Resolution 10 // For arduino UNO/MEGA/NANO
+MQUnifiedsensor MQ4(placa, Voltage_Resolution, ADC_Bit_Resolution, pin, type); //Example if sensor is MQ4 on Arduino UNO board
+MQ4.setRegressionMethod("Exponential"); //_PPM =  a*ratio^b
+MQ4.setA(1012.7); MQ4.setB(-2.786); // Configurate the ecuation values to get CH4 concentration
+MQ4.setR0(3.86018237);
+MQ4.init();
+MQ4.update();
 float ppmCH4 = MQ4.readSensor();
 ```
 
+## Wiring
+
+### Arduino
+![Arduino_Wiring_MQSensor](https://raw.githubusercontent.com/miguel5612/MQSensorsLib_Docs/master/static/img/MQ_Arduino.PNG)
+
+### ESP8266
+![ESP8266_Wiring_MQSensor](https://raw.githubusercontent.com/miguel5612/MQSensorsLib_Docs/master/static/img/MQ_ESP8266.PNG)
+
+### User Manual New!! 12.2019
+[Manual](https://drive.google.com/open?id=1BAFInlvqKR7h81zETtjz4_RC2EssvFWX)
+
+[Excel_Help_Spreadsheet (Fill only Volaje Between RL - RS - RL Values)](https://drive.google.com/open?id=1MKDcudQ7BHL_vLGi-lgPh9-pblvygRMq)
+
 ### Prerequisites
 
 You'll need Arduino desktop app 1.8.9 or later.
@@ -34,7 +57,7 @@ You'll need Arduino desktop app 1.8.9 or later.
 
 ### Info of datasheets 
 
-Review WPDigitalizer [folder](https://github.com/miguel5612/MQSensorsLib/tree/master/WPDigitalizer) [website](https://automeris.io/WebPlotDigitizer/)
+Review WPDigitalizer [folder](https://github.com/miguel5612/MQSensorsLib_Docs/tree/master/WPDigitalizer) [website](https://automeris.io/WebPlotDigitizer/)
 
 ### Installing
 
@@ -67,12 +90,12 @@ Examples/MQ-board.ino
 
 ## Built With
 
-* [Data sheets](https://github.com/miguel5612/MQSensorsLib/tree/master/Datasheets) - Curves and behavior for each sensor, using logarithmic graphs.
-* [Main purpose](https://github.com/miguel5612/MQSensorsLib/blob/master/static/img/bg.jpg) - Every sensor has high sensibility for a specific gas or material.
+* [Data sheets](https://github.com/miguel5612/MQSensorsLib_Docs/tree/master/Datasheets) - Curves and behavior for each sensor, using logarithmic graphs.
+* [Main purpose](https://github.com/miguel5612/MQSensorsLib_Docs/blob/master/static/img/bg.jpg) - Every sensor has high sensibility for a specific gas or material.
 
 ## Contributing
 
-Please read [CONTRIBUTING.md](https://github.com/miguel5612/MQSensorsLib/blob/NO_Functional/CONTRIBUTING.md) for details on our code of conduct, and the process for submitting pull requests to us.
+Please read [CONTRIBUTING.md](https://github.com/miguel5612/MQSensorsLib/blob/master/CONTRIBUTING.md) for details on our code of conduct, and the process for submitting pull requests to us.
 
 ## Authors
 

WPDigitalizer/MQ131/CL2.csv

@@ -1,5 +0,0 @@
-4.957713628975931; 5.970352865838375
-9.82303087255475; 3.890451449942809
-19.66936860744601; 2.365919697485761
-49.50200098710442; 0.9908319448927686
-99.17887133636847; 0.49659232145033677

WPDigitalizer/MQ131/NOx.csv

@@ -1,5 +0,0 @@
-5.004690736196025; 8.090958991783829
-9.81247228520288; 5.571857489319305
-19.63847609606165; 3.9994474976109777
-49.85956704514034; 2.8313919957993816
-98.7613064604988; 2.032357010936224

WPDigitalizer/MQ131/O3.csv

@@ -1,5 +0,0 @@
-5.015052099488824; 4.055085354483843
-9.839297042431014; 2.2387211385683425
-19.708460197689764; 1.2189895989248674
-50.120105449151986; 0.49659232145033727
-99.34721307419954; 0.2818382931264458

WPDigitalizer/MQ135/Acetona.csv

@@ -1,3 +0,0 @@
-10.038068731719024; 1.4367778871086752
-100.76282386271518; 0.7437057711666111
-199.67791490816478; 0.5858066785834567

WPDigitalizer/MQ135/Alcohol.csv

@@ -1,3 +0,0 @@
-10; 1.8980643862295867
-100.76282386271518; 0.9276207214357883
-199.67791490816478; 0.7371610501169261

WPDigitalizer/MQ135/CO.csv

@@ -1,3 +0,0 @@
-9.92429510870452; 2.850325339883499
-100.76282386271518; 1.5488850711364055
-199.67791490816478; 1.3446177759671738

WPDigitalizer/MQ135/CO2.csv

@@ -1,3 +0,0 @@
-10; 2.3054935712377356
-100.76282386271518; 1.049816136090719
-198.16625542394166; 0.8052859018667691

WPDigitalizer/MQ135/NH4.csv

@@ -1,3 +0,0 @@
-10; 2.563475521052897
-100.38068731719024; 1
-199.67791490816478; 0.7670732751979543

WPDigitalizer/MQ135/Tolueno.csv

@@ -1,3 +0,0 @@
-10; 1.5420548019516276
-100.38068731719024; 0.8017347542813508
-199.67791490816478; 0.6427786162225773

WPDigitalizer/MQ2/Alcohol.csv

@@ -1,9 +0,0 @@
-202,97159045689085; 2,870821251841819
-493,62843297110385; 2,120486081991352
-789,3018264543583; 1,722949305824931
-1013,5564768245204; 1,628558370192401
-1483,4109724050659; 1,4241031945513674
-2002,568136043121; 1,2616407836292618
-3045,8553406742876; 1,09372808300933
-4983,9913111605565; 0,8886628824162796
-10116,086432495827; 0,6593474448589979

WPDigitalizer/MQ2/CH4.csv

@@ -1,9 +0,0 @@
-200,6424043638923; 3,0628594206904824
-493,62843297110385; 2,262307524341795
-795,3985507023424; 1,9027463399615197
-1021,3853885815306; 1,760109364516406
-1466,3881949840988; 1,512822440016997
-2010,2873757128875; 1,3635579819828156
-3022,508881097584; 1,1618613226754184
-4945,78905312065; 0,9359079659557669
-10155,080609166793; 0,7034431020028873

WPDigitalizer/MQ2/CO.csv

@@ -1,9 +0,0 @@
-202,97159045689085; 5,230578600305607
-491,73296457790207; 4,06886745979215
-810,8471866516105; 3,4816976949280916
-994,2457296427418; 3,220835982615804
-1483,4109724050659; 2,8043001628397395
-2025,8152351174235; 2,505895099093425
-3045,8553406742876; 2,2293985477843727
-4983,9913111605565; 1,84294785992263
-10272,967317129345; 1,4525325413623644

WPDigitalizer/MQ2/H2.csv

@@ -1,9 +0,0 @@
-199,87196386572526; 2,0769753765580705
-495,5312077697903; 1,3831422575910868
-792,3443246647935; 1,1093808898233806
-998,0782190045875; 1,004327136273875
-1477,714868970752; 0,8303118686874813
-2033,6240846866745; 0,7167722606428578
-2976,351441631319; 0,5951498799327694
-4907,879615117585; 0,46313409452053067
-10038,546701761785; 0,33483775607304667

WPDigitalizer/MQ2/LPG.csv

@@ -1,9 +0,0 @@
-197,57834731787014; 1,5893603059497052
-497,4413171377462; 1,081492898685633
-798,4645497739094; 0,8636972212632283
-1005,7875736205846; 0,7785412443059092
-1455,1483398731953; 0,6691551077105506
-1964,4142809066307; 0,5776630257056471
-2964,922642745657; 0,4673698778126437
-4907,879615117585; 0,3636968635962981
-9961,601312513694; 0,2562263980512121