Merge pull request #27 from akkoyun/01.04.15

01.04.15 - Regresion model updated, R2 function added.
akkoyun · Mar 10, 2022 · 8cb5470 · 8cb5470
2 parents 6d8f97b + dd19ff0
commit 8cb5470
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Showing 11 changed files with 245 additions and 142 deletions.
diff --git a/.DS_Store b/.DS_Store
diff --git a/README.md b/README.md
@@ -3,7 +3,7 @@
 ![GitHub release (latest by date)](https://img.shields.io/github/v/release/akkoyun/Statistical) ![arduino-library-badge](https://www.ardu-badge.com/badge/Statistical.svg?) ![Visits Badge](https://badges.pufler.dev/visits/akkoyun/Statistical) ![GitHub stars](https://img.shields.io/github/stars/akkoyun/Statistical?style=flat&logo=github) ![Updated Badge](https://badges.pufler.dev/updated/akkoyun/Statistical) ![PlatformIO Registry](https://badges.registry.platformio.org/packages/akkoyun/library/Statistical.svg) 
 [![Check Arduino](https://github.com/akkoyun/Statistical/actions/workflows/check-arduino.yml/badge.svg)](https://github.com/akkoyun/Statistical/actions/workflows/check-arduino.yml) [![Compile Examples](https://github.com/akkoyun/Statistical/actions/workflows/compile-examples.yml/badge.svg)](https://github.com/akkoyun/Statistical/actions/workflows/compile-examples.yml) [![Spell Check](https://github.com/akkoyun/Statistical/actions/workflows/spell-check.yml/badge.svg)](https://github.com/akkoyun/Statistical/actions/workflows/spell-check.yml)
 
-	Build - 01.04.14
+	Build - 01.04.15
 
 ---
 
@@ -60,6 +60,7 @@ Library calculate listed statistical parameters for fixed size arrays.
 
 	* Slope
 	* Offset
+	* R2
 
 </details>
 
@@ -72,7 +73,8 @@ Library calculate listed statistical parameters for data stream. User set the re
 	* Precision
 	* Slope
 	* Offset
-
+	* R2
+
 </details>
 
 <details>

diff --git a/examples/.DS_Store b/examples/.DS_Store
diff --git a/examples/Linear_Regression/Linear_Regression.ino b/examples/Linear_Regression/Linear_Regression.ino
@@ -0,0 +1,53 @@
+#include <Statistical.h>
+
+Statistical DataSet;
+
+void setup() {
+
+	// Start Serial
+    Serial.begin(115200);
+
+}
+
+void loop() {
+
+	// Set Data
+    Serial.println("Learning Data...");
+
+    // Set Precision
+    uint8_t Linear_Regression_Precision = 5;
+
+    // Set Array
+    float Data[Linear_Regression_Precision][2];
+
+    // Learn Data
+    DataSet.Array_FILO(Data, Linear_Regression_Precision, 1, 220.14);
+    DataSet.Array_FILO(Data, Linear_Regression_Precision, 2, 221.36);
+    DataSet.Array_FILO(Data, Linear_Regression_Precision, 3, 218.21);
+    DataSet.Array_FILO(Data, Linear_Regression_Precision, 4, 217.06);
+    DataSet.Array_FILO(Data, Linear_Regression_Precision, 5, 220.14);
+    DataSet.Array_FILO(Data, Linear_Regression_Precision, 6, 222.14);
+    DataSet.Array_FILO(Data, Linear_Regression_Precision, 7, 225.14);
+
+    // Print FILO Array
+    Serial.print("Regression Data Array : ");
+    for (uint8_t i = 0; i < Linear_Regression_Precision; i++) {
+        Serial.print("[");        
+        Serial.print(Data[i][0]);
+        Serial.print(",");
+        Serial.print(Data[i][1]);
+        Serial.print("] ");
+    }
+    Serial.println("");
+
+	// Print Calculated Data
+    Serial.print("Regression Data Count : "); Serial.println(Linear_Regression_Precision);
+    Serial.print("Regression Slope      : "); Serial.println(DataSet.Linear_Regression_Slope(Data, Linear_Regression_Precision), 4);
+    Serial.print("Regression Offset     : "); Serial.println(DataSet.Linear_Regression_Offset(Data, Linear_Regression_Precision), 4);
+    Serial.print("Regression R2         : "); Serial.println(DataSet.Linear_Regression_R2(Data, Linear_Regression_Precision), 4);
+    Serial.println("------------------------");
+
+    delay(10000);
+
+}
+
diff --git a/examples/Regression/Regression.ino b/examples/Regression/Regression.ino
diff --git a/examples/Stream/Stream.ino b/examples/Stream/Stream.ino
@@ -20,14 +20,14 @@ void loop() {
 	DataSet.Stream_Statistic(132.2);
 
     // Print Calculations
-    Serial.print("Stream Data Count : "); Serial.println(DataSet.Stream_Data_Count_Avg);
+    Serial.print("Stream Data Count : "); Serial.println(DataSet.Stream_Data_Count);
     Serial.print("Stream Avg Value  : "); Serial.println(DataSet.Stream_Average);
     Serial.print("Stream Min Value  : "); Serial.println(DataSet.Stream_Minimum);
     Serial.print("Stream Max Value  : "); Serial.println(DataSet.Stream_Maximum);
     Serial.println("----------------");
 
 	// Reset
-    DataSet.Stream_Clear();
+    DataSet.Stream_Data_Clear();
 
     delay(1000);
 

diff --git a/keywords.txt b/keywords.txt
@@ -34,7 +34,7 @@ LinearRegression                KEYWORD2
 # Constants (LITERAL1)
 #######################################
 
-Data_Count						LITERAL1
+Stream_Data_Count				LITERAL1
 Stream_Average					LITERAL1
 Stream_Minimum					LITERAL1
 Stream_Maximum					LITERAL1

diff --git a/library.json b/library.json
@@ -1,6 +1,6 @@
 {
 	"name": "Statistical",
-	"version": "1.4.14",
+	"version": "1.4.15",
 	"keywords": "Statistical, Max, Min, Average, Regression, Data, Sensor, Slope, Offset",
 	"description": "Function calculates statistical parameters of data stream and array",
 	"authors":
@@ -31,10 +31,10 @@
 			]
 		},
 		{
-			"name": "Regression",
-			"base": "examples/Regression/",
+			"name": "Linear Regression",
+			"base": "examples/Linear_Regression/",
 			"files": [
-				"Regression.ino"
+				"Linear_Regression.ino"
 			]
 		},
 		{

diff --git a/library.properties b/library.properties
@@ -1,5 +1,5 @@
 name=Statistical
-version=1.4.14
+version=1.4.15
 author=Gunce Akkoyun <[email protected]>
 maintainer=Gunce Akkoyun <[email protected]>
 sentence=Statistic, Sum, Max, Min, Sq_Sum, Arithmetic Average, Geometric Average, RMS Average, Ext RMS Average, Bubble Sort, Median, Standard Deviation, Standard Deviation Error, Coefficient Factor, Average, Stream, Regression, Slope, Data, Analyse