Merge pull request #11 from akkoyun/01.03.03

01.03.03 - Readme update

README.md

@@ -1,47 +1,57 @@
-# Statistical 
-> version 1.3.0
+# Statistical Library <sup>V1</sup>
 
-Descriptive statistics for Arduino float arrays
+![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)
+
+	Library - 01.03.03
+
+---
+
+**Abstract**
+
+ 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
+**Array Statistics**
+
+Library calculate listed statistical parameters for fixed size arrays.
+
+	* Sum
+	* Maximum
+	* Minimum
+	* Square Sum
+	* Aritmetic Average
+	* Geometric Average
+	* RMS Average
+	* 1 Sigma RMS Average
+	* Bubble Sort
+	* Median
+	* Standart Deviation
+	* Standart Deviation Error
+	* Coefficient Factor
+
+**Stream Statistics**
+
+Library calculate listed statistical parameters for data streams.
+
+	* Data Count
+	* Aritmetic Average
+	* Minimum
+	* Maximum
+
+**Array Linear Regression**
+
+Library calculate listed statistical parameters for fixed size arrays.
+
+	* Slope
+	* Offset
+
+**Working on**
+
+Still working on data stream regression functions.
+
+---
 
+[![Support me](https://img.shields.io/badge/Support-PATREON-GREEN.svg)](https://www.patreon.com/bePatron?u=62967889) ![Twitter Follow](https://img.shields.io/twitter/follow/gunceakkoyun?style=social) ![YouTube Channel Views](https://img.shields.io/youtube/channel/views/UCIguQGdaBT1GnnVMz5qAZ2Q?style=social) ![Repos Badge](https://badges.pufler.dev/repos/akkoyun) [![E-Mail](https://img.shields.io/badge/E_Mail-Mehmet_Gunce_Akkoyun-blue.svg)](mailto:akkoyun@me.com) ![GitHub](https://img.shields.io/github/license/akkoyun/Statistical) 

src/Statistical.cpp

@@ -86,8 +86,11 @@ void Statistical::Data_Clear(void) {
 
 }
 
-// Array Statistics
+// TODO: Stream statistic
+
+// TODO: Stream regression function
 
+// Array Statistics
 float Statistical::Array_Sum(float _Data[], uint16_t _Data_Count) {
 
 	// Declare Variable