/// <summary>
/// Initializes a new instance of the IndividualRriangles.
/// </summary>
/// <param name="width">The width.</param>
/// <param name="height">The height.</param>
/// <param name="init">Initilaization genes.</param>
public IndividualTriangles(int width, int height, int numberOfShapes, bool init = true)
: base(width, height, numberOfShapes * size)
{
geneSize = size;
this.numberOfShapes = numberOfShapes;
// Init
if (init)
{
for (int i = 0; i < numberOfShapes; i++)
{
//1. vertex
genes[(i * geneSize)] = FastRandom.GetInt(0, Width);
genes[(i * geneSize) + 1] = FastRandom.GetInt(0, Height);
// 2. vertex
genes[(i * geneSize) + 2] = FastRandom.GetInt(0, Width);
genes[(i * geneSize) + 3] = FastRandom.GetInt(0, Height);
// 3. vertex
genes[(i * geneSize) + 4] = FastRandom.GetInt(0, Width);
genes[(i * geneSize) + 5] = FastRandom.GetInt(0, Height);
// color
genes[(i * geneSize) + 6] = FastRandom.GetDouble() * 255;
genes[(i * geneSize) + 7] = FastRandom.GetDouble() * 255;
genes[(i * geneSize) + 8] = FastRandom.GetDouble() * 255;
}
}
}
/// <summary>
/// Initializes a new instance of the IndividualRectangles.
/// </summary>
/// <param name="width">The width.</param>
/// <param name="height">The height.</param>
/// <param name="init">Initilaization genes.</param>
public IndividualRectangles(int width, int height, int numberOfShapes, bool init = true)
: base(width, height, numberOfShapes * size)
{
geneSize = size;
this.numberOfShapes = numberOfShapes;
// Init
if (init)
{
for (int i = 0; i < numberOfShapes; i++)
{
//left corner
genes[(i * geneSize)] = FastRandom.GetInt(0, Width);
genes[(i * geneSize) + 1] = FastRandom.GetInt(0, Height);
// width
genes[(i * geneSize) + 2] = FastRandom.GetInt(0, maxWidth);
// height
genes[(i * geneSize) + 3] = FastRandom.GetInt(0, maxHeight);
// color
genes[(i * geneSize) + 4] = FastRandom.GetDouble() * 255;
genes[(i * geneSize) + 5] = FastRandom.GetDouble() * 255;
genes[(i * geneSize) + 6] = FastRandom.GetDouble() * 255;
}
}
}
/// <summary>
/// Initializes a new instance of the IndividualBitmap.
/// </summary>
/// <param name="width">The width.</param>
/// <param name="height">The height.</param>
/// <param name="init">Initilaization genes.</param>
public IndividualBitmap(int width, int height, bool init = true, Color[] initColors = null)
: base(width, height, width * height * 3)
{
// Init
if (init)
{
if (initColors == null)
{
for (int i = 0; i < Length; i++)
{
ReplaceGene(i, GenerateGene(i));
}
}
else
{
int indexR = 0;
int indexG = 1;
int indexB = 2;
for (int i = 0; i < width * height; i++)
{
Color c = initColors[FastRandom.GetInt(0, initColors.Length)];
genes[indexR] = c.R;
genes[indexG] = c.G;
genes[indexB] = c.B;
indexR += 3;
indexG += 3;
indexB += 3;
}
}
}
}
/// <summary>
/// Evolved one generation.
/// </summary>
/// <param name="population">Curr. pop</param>
/// <returns>New generation</returns>
protected override IPopulation EvolvedOneGeneration(IPopulation population)
{
List <IIndividual> newGeneration = new List <IIndividual>();
foreach (var orginal in population.Individuals)
{
// generate unique random numbers
var randomValues = FastRandom.GetUniqueInts(3, 0, population.Size);
int a = randomValues[0];
int b = randomValues[1];
int c = randomValues[2];
// choose random individuals (agents) from population
IIndividual individual1 = population.Individuals[a];
IIndividual individual2 = population.Individuals[b];
IIndividual individual3 = population.Individuals[c];
int i = 0;
int R = FastRandom.GetInt(0, population.Size);
var candidate = population.CreateEmptyIndividual();
foreach (var orginalElement in orginal.GetGenes())
{
double probXover = FastRandom.GetDouble();
if (probXover < XoverProbability || i == R)
{
// simple mutation
double newElement = individual1.GetGene(i) + F * (individual2.GetGene(i) - individual3.GetGene(i));
candidate.ReplaceGene(i, newElement);
}
else
{
candidate.ReplaceGene(i, orginalElement);
}
i++;
}
var fit = fitness.Evaluate(candidate);
if (fit < orginal.Fitness)
{
newGeneration.Add(candidate);
}
else
{
newGeneration.Add(orginal);
}
}
CurrentGenerationsNumber++;
population.Individuals = newGeneration;
return(population);
}
/// <summary>
/// Initializes a new instance of the IndividualBitmap.
/// </summary>
/// <param name="width">The width.</param>
/// <param name="height">The height.</param>
/// <param name="init">Initilaization genes.</param>
public IndividualLines(int width, int height, int numberOfLines, bool init = true)
: base(width, height, numberOfLines * 4)
{
this.numberOfLines = numberOfLines;
// Init
if (init)
{
int indexX1 = 0;
int indexY1 = 1;
int indexX2 = 2;
int indexY2 = 3;
for (int i = 0; i < numberOfLines; i++)
{
var sX = FastRandom.GetInt(0, width);
var sY = FastRandom.GetInt(0, height);
var shifts = FastRandom.GetInts(2, 0, 30);
genes[indexX1] = sX;
genes[indexY1] = sY;
genes[indexX2] = sX + shifts[0];
genes[indexY2] = sY + shifts[1];
indexX1 += 4;
indexY1 += 4;
indexX2 += 4;
indexY2 += 4;
}
}
}
/// <summary>
/// Mutate the specified individual.
/// Shifted line
/// </summary>
/// <param name="individual">The individual.</param>
/// <param name="mutation_probabilty">The probability to mutate each indiviudal.</param>
public override void Mutate(IIndividual individual, float mutation_probabilty)
{
var indexes = FastRandom.GetInts(mutateRate, 0, individual.Length);
foreach (var index in indexes)
{
var oldGene = individual.GetGene(index);
// line endPoints shift
var currShift = FastRandom.GetInt(-shift, shift);
// sets new gene
individual.ReplaceGene(index, oldGene + currShift);
}
}
/// <summary>
/// Generates the gene.
/// </summary>
/// <param name="geneIndex">Index of the gene.</param>
/// <returns>The new Gene.</returns>
public override double GenerateGene(int geneIndex)
{
var colorIndex = FastRandom.GetInt(0, colorsDomain.Length);
var color = colorsDomain[colorIndex];
if (geneIndex % 3 == 0)
{
return(color.R);
}
if (geneIndex % 3 == 1)
{
return(color.G);
}
return(color.B);
}
/// <summary>
/// Cross the specified parents generating the children.
/// </summary>
/// <param name="parents">The parents</param>
/// <returns>The offspring (children) of the parents.</returns>
public override IList <IIndividual> Cross(IList <IIndividual> parents)
{
// same length
if (parents[0].Length != parents[1].Length)
{
return(parents);
}
int swapPoint = FastRandom.GetInt(1, parents[0].Length - 2);
var firstChild = CreateChild(parents[0], parents[1], swapPoint);
var secondChild = CreateChild(parents[1], parents[0], swapPoint);
return(new List <IIndividual>()
{
firstChild, secondChild
});
}
/// <summary>
/// Initializes a new instance of the IndividualCircles.
/// </summary>
/// <param name="width">The width.</param>
/// <param name="height">The height.</param>
/// <param name="init">Initilaization genes.</param>
public IndividualCircles(int width, int height, int numberOfShapes, bool init = true)
: base(width, height, numberOfShapes * size)
{
geneSize = size;
this.numberOfShapes = numberOfShapes;
// Init
if (init)
{
for (int i = 0; i < numberOfShapes; i++)
{
genes[(i * geneSize)] = FastRandom.GetInt(0, Width);
genes[(i * geneSize) + 1] = FastRandom.GetInt(0, Height);
genes[(i * geneSize) + 2] = FastRandom.GetInt(0, maxRadius);
genes[(i * geneSize) + 3] = FastRandom.GetDouble() * 255;
genes[(i * geneSize) + 4] = FastRandom.GetDouble() * 255;
genes[(i * geneSize) + 5] = FastRandom.GetDouble() * 255;
}
}
}