01.03.00 Initial update

README.md

@@ -1,2 +1,47 @@
-# Data Stream Statistical Library
+# Statistical 
+> version 1.3.0
+
+Descriptive statistics for Arduino float arrays
+
+We developed this library to help quickly accomplish median and mode filtering when collecting sensor data. Functions in this library operate on an array of float variables, of dimension "m", and return the corresponding statistic. This library was originally created for a data smoothing strategy for float variables. Using a median or mode filtering strategy (opposed to mean filtering) is better at removing spikes from aberrant readings. 
+
+A bubble sort algorithm is also contained in this library which was necessary to calculate median and mode.
+
+### Array Statistics
+
+    Array_Sum
+    Array_Max
+    Array_Min
+    Array_Sq_Sum
+    Array_Aritmetic_Average
+    Array_Geometric_Average
+    Array_RMS_Average
+    Array_Ext_RMS_Average
+    Array_Bubble_Sort
+    Array_Median
+    Array_Standart_Deviation
+    Array_Standart_Deviation_Error
+    Array_Coefficient_Factor
+    Array_Average
+
+### Stream Statistics
+
+	Stream_Statistic
+	Data_Clear
+	LinearRegression
+
+	Stream_Average
+	Stream_Minimum
+	Stream_Maximum
+
+	Linear_Regression_MeanX
+	Linear_Regression_MeanX2
+	Linear_Regression_VarianceX
+	Linear_Regression_MeanY
+	Linear_Regression_MeanY2
+	Linear_Regression_MeanXY
+	Linear_Regression_VarianceY
+	Linear_Regression_CovarianceXY
+	Linear_Regression_a
+	Linear_Regression_b
 

examples/Array/Array.ino

@@ -13,16 +13,11 @@ void loop() {
 	// Set Data
 	Serial.println("Learning Data...");
 	float Data_Array[] = {220.14, 221.36, 218.21, 217.6, 215.7, 225.8, 220.14 };
-	int Data_Size = 7;
+	uint8_t Data_Size = 7;
 
 	// Print Array
 	Serial.print("Data Array : ");
-	for (uint8_t i = 0; i < sizeof(Data_Array); i++) {
-        Serial.print("[");
-        Serial.print(Data_Array[i]);
-        Serial.print("] ");
-	}
-	Serial.println("");
+	for (uint8_t i = 0; i < Data_Size; i++) {Serial.print("["); Serial.print(Data_Array[i]); Serial.print("] ");} Serial.println("");
 
 	// Print Stats
 	Serial.print("Array Sum                      : "); Serial.println(Stats.Array_Sum(Data_Array, Data_Size));
@@ -39,12 +34,7 @@ void loop() {
 	Serial.print("Array Coefficient Factor       : "); Serial.println(Stats.Array_Coefficient_Factor(Data_Array, Data_Size));
 
 	Serial.print("Sorted Data Array              : ");
-	for (uint8_t i = 0; i < sizeof(Data_Array); i++) {
-        Serial.print("[");
-        Serial.print(Data_Array[i]);
-        Serial.print("] ");
-	}
-	Serial.println("");
+	for (uint8_t i = 0; i < Data_Size; i++) {Serial.print("["); Serial.print(Data_Array[i]); Serial.print("] ");} Serial.println("");
 
 	Serial.println("--------------------------------------------------");
 

library.json

@@ -1,6 +1,6 @@
 {
 	"name": "Statistical",
-	"version": "1.2.0",
+	"version": "1.3.0",
 	"keywords": "Statistical, Max, Min, Average, Regression, Data, Sensor, Slope, Offset",
 	"description": "Function calculates statistical parameters of data stream and array",
 	"authors":

library.properties

@@ -1,10 +1,9 @@
 name=Statistical
-version=1.2.0
+version=1.3.0
 author=Gunce Akkoyun <akkoyun@me.com>
 maintainer=Gunce Akkoyun <akkoyun@me.com>
-sentence=Statistic, Max, Min, Average, Stream, Regression, Slope, Data, Analyse
+sentence=Statistic, Sum, Max, Min, Sq_Sum, Aritmetic Average, Geometric Average, RMS Average, Ext RMS Average, Bubble Sort, Median, Standart Deviation, Standart Deviation Error, Coefficient Factor, Average, Stream, Regression, Slope, Data, Analyse
 paragraph=Function calculates statistical parameters of data stream and array.
-category=Other
+category=Data Processing
 url=https://github.com/akkoyun/Statistical
-architectures=*
-
+architectures=*

src/Statistical.cpp

@@ -1,11 +1,9 @@
 /* *******************************************************************************
- *  Copyright (C) 2014-2021 Mehmet Gunce Akkoyun Can not be copied and/or
+ *  Copyright (C) 2014-2022 Mehmet Gunce Akkoyun Can not be copied and/or
  *	distributed without the express permission of Mehmet Gunce Akkoyun.
  *
- *	Library				: Data Stream Statistical Library
+ *	Library				: Data Statistical Library
  *	Code Developer		: Mehmet Gunce Akkoyun (akkoyun@me.com)
- *	Revision			: 01.01.02
- *
  *********************************************************************************/
 
 #include "Statistical.h"
@@ -103,7 +101,7 @@ float Statistical::Array_Sum(float _Data[], uint16_t _Data_Count) {
 	} 
 
 	// End Function
-	return(_Sum)
+	return(_Sum);
 
 }
 float Statistical::Array_Max(float _Data[], uint16_t _Data_Count) {
@@ -119,7 +117,7 @@ float Statistical::Array_Max(float _Data[], uint16_t _Data_Count) {
 	}
 
 	// End Function
-	return(_Max)
+	return(_Max);
 
 }
 float Statistical::Array_Min(float _Data[], uint16_t _Data_Count) {
@@ -135,7 +133,7 @@ float Statistical::Array_Min(float _Data[], uint16_t _Data_Count) {
 	}
 
 	// End Function
-	return(_Min)
+	return(_Min);
 
 }
 float Statistical::Array_Sq_Sum(float _Data[], uint16_t _Data_Count) {
@@ -151,7 +149,7 @@ float Statistical::Array_Sq_Sum(float _Data[], uint16_t _Data_Count) {
 	}
 
 	// End Function
-	return(_Sq_Sum)
+	return(_Sq_Sum);
 
 }
 float Statistical::Array_Aritmetic_Average(float _Data[], uint16_t _Data_Count) {
@@ -166,7 +164,7 @@ float Statistical::Array_Aritmetic_Average(float _Data[], uint16_t _Data_Count)
 	float _Average = _Sum / _Data_Count;
 
 	// End Function
-	return(_Average)
+	return(_Average);
 
 }
 float Statistical::Array_Geometric_Average(float _Data[], uint16_t _Data_Count) {
@@ -185,7 +183,7 @@ float Statistical::Array_Geometric_Average(float _Data[], uint16_t _Data_Count)
 	float _GAvg = exp(_GAvg_Sum);
 
 	// End Function
-	return(_GAvg)
+	return(_GAvg);
 
 }
 float Statistical::Array_RMS_Average(float _Data[], uint16_t _Data_Count) {
@@ -194,10 +192,10 @@ float Statistical::Array_RMS_Average(float _Data[], uint16_t _Data_Count) {
 	float _Sum = Array_Sq_Sum(_Data, _Data_Count);
 
 	// Calculate RSM Average
-	float _RMS_Avg = (sqrt(Array_Sq_Sum / _Data_Count));
+	float _RMS_Avg = (sqrt(_Sum / _Data_Count));
 
 	// End Function
-	return(_RMS_Avg)
+	return(_RMS_Avg);
 
 }
 float Statistical::Array_Ext_RMS_Average(float _Data[], uint16_t _Data_Count) {
@@ -219,13 +217,14 @@ float Statistical::Array_Ext_RMS_Average(float _Data[], uint16_t _Data_Count) {
 	float _Ext_RMS_Avg = (sqrt(_Sum / _Data_Count));
 
 	// End Function
-	return(_Ext_RMS_Avg)
+	return(_Ext_RMS_Avg);
 
 }
 void Statistical::Array_Bubble_Sort(float _Data[], uint16_t _Data_Count) {
 
 	// Declare Buffer Variables
 	uint16_t _New_n;
+	uint16_t _n = _Data_Count;
 	float _Temp = 0;
 
 	// Sort Array
@@ -249,10 +248,10 @@ void Statistical::Array_Bubble_Sort(float _Data[], uint16_t _Data_Count) {
 
 		}
 
-	} while (_Data_Count > 1);
+	} while (_New_n > 1);
 
 }
-void Statistical::Array_Median(float _Data[], uint16_t _Data_Count) {
+float Statistical::Array_Median(float _Data[], uint16_t _Data_Count) {
 
 	// Sort Array
 	Array_Bubble_Sort(_Data, _Data_Count);
@@ -272,7 +271,7 @@ void Statistical::Array_Median(float _Data[], uint16_t _Data_Count) {
 	}
 
 	// End Function
-	return(_Median)
+	return(_Median);
 
 }
 float Statistical::Array_Standart_Deviation(float _Data[], uint16_t _Data_Count) {

src/Statistical.h

@@ -1,8 +1,8 @@
 /* *******************************************************************************
- *  Copyright (C) 2014-2020 Mehmet Gunce Akkoyun Can not be copied and/or
+ *  Copyright (C) 2014-2022 Mehmet Gunce Akkoyun Can not be copied and/or
  *	distributed without the express permission of Mehmet Gunce Akkoyun.
  *
- *	Library				: Linear Regression Library
+ *	Library				: Data Statistical Library
  *	Code Developer		: Mehmet Gunce Akkoyun (akkoyun@me.com)
  *********************************************************************************/
 
@@ -46,8 +46,8 @@ class Statistical {
 	// Public Functions
 	// ************************************************************
 	void Stream_Statistic(float _Data);
-	void Data_Clear(void);
 	void LinearRegression(float _X, float _Y);
+	void Data_Clear(void);
 
 	/**
 	 * @brief Calculate the array sum.