/// <summary>
/// To display the image, create a Bitmap (easist way to render to a winforms picturebox)
/// Write our image data pixel by pixel to the new bitmap.
/// </summary>
/// <param name="colorData"></param>
/// <param name="header"></param>
/// <returns></returns>
public Bitmap GetImageFromColorData(Individual individual, int width, int height)
{
Bitmap image = new Bitmap(width, height);
var colorData = individual.Genome;
for (int x = image.Width - 1; x > 0; x--)
{
for (int y = image.Height - 1; y > 0; y--)
{
int index = TranslateXYToListIndex(x, y, image.Width);
if (index >= colorData.Length)
index = colorData.Length - 1;
Color color = Color.FromArgb(colorData[index].R, colorData[index].G, colorData[index].B);
image.SetPixel(x, y, color);
}
}
//Flip the bmp to display it on screen
image.RotateFlip(RotateFlipType.Rotate270FlipX);
return image;
}
/// <summary>
/// Choose a child to survive.
/// (ideally this would be done via a gladiator match between the two children. (pay per view is not out of the question))
/// </summary>
/// <param name="childOne"></param>
/// <param name="childTwo"></param>
/// <returns></returns>
private Individual ChooseRandomChild(Individual childOne, Individual childTwo)
{
int randomChild = RNG.Next(0, 2);
if (randomChild == 0)
return childOne;
else
return childTwo;
}
/// <summary>
/// Creates the initial population of individuals, each with a random starting genome.
/// </summary>
protected override void CreateInitialPopulation()
{
var configuration = (_configuration as ImageConfiguration);
for (int index = 0; index < _configuration.PopulationSize; index++)
{
Individual individual = new Individual( configuration.Width * configuration.Height );
_currentGeneration.Add(individual);
}
}
/// <summary>
/// Create a child using crossover reproduction between the two parents.
/// </summary>
/// <param name="one"></param>
/// <param name="two"></param>
/// <returns></returns>
private Individual GenerateChild(Individual one, Individual two)
{
//StringBuilder genome = new StringBuilder(one.Genome.Length);
RGB[] genome = new RGB[one.Genome.Length];
int crossoverPoint = one.Genome.Length / 2;
GetFirstParentGenome(one, genome, crossoverPoint);
GetSecondParentGenome(two, genome, crossoverPoint);
return new Individual(genome);
}
/// <summary>
/// Iterate over each allele, each has a random probability of being mutated to a new color value.
/// </summary>
/// <param name="toMutate"></param>
private void ChangeGenome(Individual toMutate)
{
double probabilityOfMutation = _configuration.MutationRate;
for (int index = 0; index < toMutate.Genome.Length; index++)
{
if (RNG.NextDouble() < probabilityOfMutation)
{
var newAllele = GetNewRandomAllele();
toMutate.Genome[index] = newAllele;
}
}
}
/// <summary>
/// Give the child the second parents genomes.
/// </summary>
/// <param name="parentTwo"></param>
/// <param name="childCoins"></param>
/// <param name="crossoverPoint"></param>
private void GetSecondParentGenome(Individual two, RGB[] genome, int crossoverPoint)
{
for (int index = crossoverPoint; index < two.Genome.Length; index++)
genome[index] = (two.Genome[index]);
}
/// <summary>
/// give the child the first parents genome.
/// </summary>
/// <param name="parentOne"></param>
/// <param name="childCoins"></param>
/// <param name="crossoverPoint"></param>
private void GetFirstParentGenome(Individual one, RGB[] genome, int crossoverPoint)
{
for (int index = 0; index < crossoverPoint; index++)
genome[index] = (one.Genome[index]);
}
