## Series Introduction

My objective is to create a simple AI library that covers couple of advanced AI topics such as Genetic algorithms, ANN, Fuzzy logics and other evolutionary algorithms. The only challenge to complete this series would be having enough time working on code and articles.

Having the code itself might not be the main target however, understanding these algorithms is. wish it will be useful to someone someday.

Series will be published in couple of parts, am not sure how many yet. Anyways, each part will focus on single key topic trying to cover for good.

Please, feel free to comment and ask for any clarifications or hopefully suggest better approaches.

## Article Introduction - Part 1 "Basics"

This is Part 1 of multi-parts series, have dedicated it to cover basic library called "CommonLib" that contains fundamental classes as:

- Graphics wrapper class called "
*Canvas*" - Math wrapper classes to handle "
*Vector*" & "*Matrix*" operations and other math operations - Random generator class "
*RandomFactory*"

each of above classes shall be explained in details below

## 1- Graphics wrap class Canvas

Graphics shall be used to test AI libraries will build and hence, had to create one wrap class to contain all common graphics operations and make it easier than creating Graphics objects

Canvas class wraps some graphics operations as DrawLine, DrawBox (Square), DrawCircle, DrawText & Clear

Mainly it contains one internal graphics object *g* and bitmap object *bmp*

# Constructor

Public Sub New(_width As Integer, _height As Integer)
Me._Width = _width
Me._Height = _height
Me._bmp = New Bitmap(_width, _height)
g = Graphics.FromImage(_bmp)
g.SmoothingMode = SmoothingMode.HighQuality
End Sub

Width & Height are mandatory integers to create Canvas object which represents drawing area.

Here is an example of declaring canvas object and how to use

Imports CommonLib.CommonLib
Public Class Form1
Private myCanvas As Canvas
Private Sub Form1_Load(sender As Object, e As EventArgs) Handles MyBase.Load
myCanvas = New Canvas(PictureBox1.Width, PictureBox1.Height)
Draw()
End Sub
Private Sub Draw()
With myCanvas
.DrawBox(50, 25, 25, Color.Black)
.FillBox(50, 100, 25, Color.Red)
.DrawCircle(50, 100, 200, Color.Blue)
.FillCircle(50, 200, 200, Color.Green)
.DrawText("Test String", 250, 200, Color.Red)
End With
PictureBox1.Image = myCanvas.Image
End Sub
Private Sub Clear()
myCanvas.Clear()
PictureBox1.Image = myCanvas.Image
End Sub
End Class

and here is the result of above code

## 2- Math Classes

# MathFunctions

This class wraps some useful math functions

Constraint Function

Public Function Constraint(Value As Single, min As Single, max As Single) As Single
If Value <= min Then
Return min
ElseIf Value >= max Then
Return max
End If
Return Value
End Function

Map Function

Public Shared Function Map(ByVal value As Single, ByVal start1 As Single, ByVal stop1 As Single, ByVal start2 As Single, ByVal stop2 As Single) As Single
Dim Output As Single = start2 + (stop2 - start2) * ((value - start1) / (stop1 - start1))
Dim errMessage As String = Nothing
If Output <> Output Then
errMessage = "NaN (not a number)"
Throw New Exception(errMessage)
ElseIf Output = Single.NegativeInfinity OrElse Output = Single.PositiveInfinity Then
errMessage = "infinity"
Throw New Exception(errMessage)
End If
Return Output
End Function

Norm Function

Public Shared Function Norm(ByVal value As Single, ByVal start As Single, ByVal [stop] As Single) As Single
Return (value - start) / ([stop] - start)
End Function

GetBitArray Function

Public Function GetBitArray(Value As Integer) As Integer()
Dim Result(7) As Integer
Dim sValue As String
Dim cValue() As Char
Value = Constraint(Value, 0, 255)
sValue = Convert.ToString(Value, 2).PadLeft(8, "0"c)
cValue = sValue.ToArray
For i As Integer = 0 To cValue.Count - 1
If cValue(i) = "1"c Then
Result(i) = 1
Else
Result(i) = 0
End If
Next
Return Result
End Function

# Matrix Operations

Matrix operations are very important (especially for ANN later) and hence it worths to create separate class(s) to handle different cases of matrix functions. Namely, Vector and Matrix1D

Lots of resources are available to describe matrices and its functions and hence will not spend much time on that.

Just need to mention that, 2 special matrices are only considered so far in CommonLib; Matrix1D and Vector

# Matrix1D

is single column-matrix

Later, this class will help simplifying neural network creation. This class implements IMatrix Interface

`Size `

- Size or Capacity of Matrix - Simply Number of Stored Elements in Values Array `Product `

- Implement Matrix Product function between 2 metrics m1 and m2 or matrix and scalar `Add `

- Implement Matrix addition method between 2 metrics m1 and m2 or matrix and scalar `Sub `

- Implement Matrix subtraction method between 2 metrics m1 and m2 or matrix and scalar `Divide `

- Implement Matrix divide method between 2 metrics m1 and m2 or matrix and scalar `Sum `

- Sum of all matrix elements a_{1}+a_{2}+a_{3}+...........+a_{n} `RandomizeValues `

- Randomize matrix elements between min and max values `Copy `

- Copy contents of one matrix into object starting from given starting index `ForceValues `

- Forces all elements of matrix to ForcedValue `GetValue `

- Return index element of matrix Index starts with 0 `SetValue `

- Set value of matrix element at position Index 0 indexed positions

# Vector

`Vector `

is special matrix with 1 row and multiple columns (in our case, only 2 and 3 columns are considered not higher). This is one way to think about vectors, however the most efficient way is to consider a `vector `

as "Magnitude plus Direction" object. This is very powerful object and yet so much simple; just by giving 2 numbers we may extract magnitude and direction.

vectors play very important rule in math and physics and maybe will have separate article to cover vectors only. for now, you may visit **this link **to get more info about vectors and vectors operations

Note: only 2D and 3D vectors are considered in CommonLib, for higher dimensional vectors, matrix shall be used

many vector operations have been implemented in CommonLib such as:

`Randomize`

- Randomize X, Y and Z components of vector between 0 and 1 `Magnitude `

- Calculates the Euclidean magnitude (length) of the vector and returns the result = SQRT (X^{2}+Y^{2}+Z^{2}) `Add `

- Adds x, y, and z components to a vector, adds one vector to another, or adds two independent vectors together. here is graphical representation of vector addition from Wikipedia

`Sub `

- Perform vector subtraction with other vectors or scalar values

`Mult `

- implement vector scalar multiplication `Div `

- is scalar divide implementation `Distance `

- Calculates the Euclidean distance between two vectors = SQRT (dX^{2}+dY^{2}+dZ^{2}) `Dot `

- implements vectors dot product. more at **this link** `Cross `

- implements vectors cross product. here is **the link **explaining math behind it `Normalize `

- Normalize the vector to length 1 (make it a unit vector) `Limit `

- Limit the magnitude of this vector to the value passed as max parameter `SetMag `

- Set the magnitude of this vector to the value passed as len parameter `Heading `

- Calculate the angle of rotation for this vector `Rotate `

- Rotate the vector by an angle, magnitude remains the same `AngleBetween `

- Calculates and returns the angle (in radians) between two vectors

## 3- RandomFactory

This class is very important for both initialization of different AI objects and for test purposes. It extends .NET Random class and adds further methods

It can provide different random functions in addition to numbers (integer, Single and Double), as Random Color, Random Character, Random Boolean.

In addition, it has an implementation for `Gaussian`

random function using Box-Muller transform

Public Function NextGaussian(Optional ByVal Mean As Double = 0, Optional ByVal StdDeviation As Double = 1) As Double
Dim X1 = _Gen.NextDouble()
Dim X2 = _Gen.NextDouble()
Dim StdDistribution = Math.Sqrt(-2.0 * Math.Log(X1)) * Math.Sin(2.0 * Math.PI * X2)
Dim GaussianRnd = Mean + StdDeviation * StdDistribution
Return GaussianRnd
End Function

Also, it implements `Triangle `

distribution random generation (you may check **this wiki article**)

Public Function NextTriangular(ByVal min As Double, ByVal max As Double, ByVal mode As Double) As Double
Dim u = _Gen.NextDouble()
If (u < (mode - min) / (max - min)) Then
Return min + Math.Sqrt(u * (max - min) * (mode - min))
Else
Return max - Math.Sqrt((1 - u) * (max - min) * (max - mode))
End If
End Function

`Shuffle `

method provide random shuffle implementation for a list by using the Fisher-Yates/Knuth algorithm

Public Sub Shuffle(ByVal list As IList)
For i = 0 To list.Count - 1
Dim j = _Gen.Next(0, i + 1)
Dim temp = list(j)
list(j) = list(i)
list(i) = temp
Next i
End Sub

To get efficient result of RandomFactory class, a global or form level object shall be created and used through out the code

## What is Next

Next article will be about Genetic Algorithms (might be fuzzy controller!) depends on which code shall be ready first

## To Do List

- Add 2D Matrix operations implementation, 1D matrix is good for now however extend library to include 2D shall add more efficiency or practicality. wish to complete this task before starting ANN library

## History

CommonLib has been built to act as supporting class library for different projects hence it shall be kept as separate solution and only add references.

Version1 of this library is completed by August 2017, expecting further versions to follow.