Click here to Skip to main content
15,881,248 members
Articles / Artificial Intelligence

AForge.NET open source framework

Rate me:
Please Sign up or sign in to vote.
4.97/5 (150 votes)
16 May 2007GPL311 min read 826.9K   48.3K   346  
The article describes an open source C# framework for researchers in the areas of Computer Vision and Artificial Intelligence - image processing, neural networks, genetic algorithms, etc.
// AForge Genetic Library
//
// Copyright � Andrew Kirillov, 2006
// andrew.kirillov@gmail.com
//

namespace AForge.Genetic
{
	using System;
	using System.Text;

	/// <summary>
	/// Short Array Chromosome is a chromosome, which is represented
	/// by array of unsigned short values. Array length is in the
	/// range of [2, 65536]
	/// </summary>
	public class ShortArrayChromosome : IChromosome
	{
		protected int		length;			// chromosome's length
		protected int		maxValue;		// max value of chromosome's gene
		protected ushort[]	val = null;		// chromosome's value 
		protected double	fitness = 0;	// chromosome's fitness

		// random number generator for chromosoms generation
		protected static Random	rand = new Random( (int) DateTime.Now.Ticks );

		/// <summary>
		/// Chromosome's maximum length
		/// </summary>
		public const int MaxLength = 65536;

		/// <summary>
		/// Chromosome's length
		/// </summary>
		public int Length
		{
			get { return length; }
		}

		/// <summary>
		/// Chromosome's value
		/// </summary>
		public ushort[] Value
		{
			get { return val; }
		}

		/// <summary>
		/// Max possible value of single chromosomes element - gene 
		/// </summary>
		public int MaxValue
		{
			get { return maxValue; }
		}

		/// <summary>
		/// Chromosome's fintess value
		/// </summary>
		public double Fitness
		{
			get { return fitness; }
		}
		

		/// <summary>
		/// Constructor
		/// </summary>
		public ShortArrayChromosome( int length ) : this( length, ushort.MaxValue ) { }

		/// <summary>
		/// Constructor
		/// </summary>
		public ShortArrayChromosome( int length, int maxValue )
		{
			// save parameters
			this.length		= Math.Max( 2, Math.Min( MaxLength, length ) );
			this.maxValue	= Math.Max( 1, Math.Min( ushort.MaxValue, maxValue ) );

			// allocate array
			val = new ushort[this.length];

			// generate random chromosome
			Generate( );
		}

		/// <summary>
		/// Copy constructor
		/// </summary>
		protected ShortArrayChromosome( ShortArrayChromosome source )
		{
			// copy all properties
			length		= source.length;
			maxValue	= source.maxValue;
			val			= (ushort[]) source.val.Clone( );
			fitness		= source.fitness;
		}

		/// <summary>
		/// Get string representation of the chromosome
		/// </summary>
		public override string ToString( )
		{
			StringBuilder sb = new StringBuilder( );

			// append first gene
			sb.Append( val[0] );
			// append all other genes
			for ( int i = 1; i < length; i++ )
			{
				sb.Append( ' ' );
				sb.Append( val[i] );
			}

			return sb.ToString( );
		}

		/// <summary>
		/// Compare two chromosomes
		/// </summary>
		public int CompareTo( object o )
		{
			double f = ((ShortArrayChromosome) o).fitness;

			return ( fitness == f ) ? 0 : ( fitness < f ) ? 1 : -1;
		}

		/// <summary>
		/// Generate random chromosome value
		/// </summary>
		public virtual void Generate( )
		{
			int max = maxValue + 1;

			for ( int i = 0; i < length; i++ )
			{
				// generate next value
				val[i] = (ushort) rand.Next( max );
			}
		}

		/// <summary>
		/// Create new random chromosome (factory method)
		/// </summary>
		public virtual IChromosome CreateOffspring( )
		{
			return new ShortArrayChromosome( length, maxValue );
		}

		/// <summary>
		/// Clone the chromosome
		/// </summary>
		public virtual IChromosome Clone( )
		{
			return new ShortArrayChromosome( this );
		}

		/// <summary>
		/// Mutation operator
		/// </summary>
		public virtual void Mutate( )
		{
			// get random index
			int i = rand.Next( length );
			// randomize the gene
			val[i] = (ushort) rand.Next( maxValue + 1 );
		}

		/// <summary>
		/// Crossover operator
		/// </summary>
		public virtual void Crossover( IChromosome pair )
		{
			ShortArrayChromosome p = (ShortArrayChromosome) pair;

			// check for correct pair
			if ( ( p != null ) && ( p.length == length ) )
			{
				// crossover point
				int crossOverPoint = rand.Next( length - 1 ) + 1;
				// length of chromosome to be crossed
				int crossOverLength = length - crossOverPoint;
				// temporary array
				ushort[] temp = new ushort[crossOverLength];

				// copy part of first (this) chromosome to temp
				Array.Copy( val, crossOverPoint, temp, 0, crossOverLength );
				// copy part of second (pair) chromosome to the first
				Array.Copy( p.val, crossOverPoint, val, crossOverPoint, crossOverLength );
				// copy temp to the second
				Array.Copy( temp, 0, p.val, crossOverPoint, crossOverLength );
			}
		}

		/// <summary>
		/// Evaluate chromosome with specified fitness function
		/// </summary>
		public void Evaluate( IFitnessFunction function )
		{
			fitness = function.Evaluate( this );
		}
	}
}

By viewing downloads associated with this article you agree to the Terms of Service and the article's licence.

If a file you wish to view isn't highlighted, and is a text file (not binary), please let us know and we'll add colourisation support for it.

License

This article, along with any associated source code and files, is licensed under The GNU General Public License (GPLv3)


Written By
Software Developer IBM
United Kingdom United Kingdom
Started software development at about 15 years old and it seems like now it lasts most part of my life. Fortunately did not spend too much time with Z80 and BK0010 and switched to 8086 and further. Similar with programming languages – luckily managed to get away from BASIC and Pascal to things like Assembler, C, C++ and then C#. Apart from daily programming for food, do it also for hobby, where mostly enjoy areas like Computer Vision, Robotics and AI. This led to some open source stuff like AForge.NET, Computer Vision Sandbox, cam2web, ANNT, etc.

Comments and Discussions