/// <summary>
/// Create a MateWorker.
/// </summary>
/// <param name="mother">The mother.</param>
/// <param name="father">The father.</param>
/// <param name="child1">The first child.</param>
/// <param name="child2">The second child.</param>
public MateWorker(IGenome mother, IGenome father,
IGenome child1, IGenome child2, GATracker.MatedElement matedElement)
{
this.mother = mother;
this.father = father;
this.child1 = child1;
this.child2 = child2;
this.matedElement = matedElement;
}
/// <summary>
/// Mate two genomes. Will loop over all chromosomes.
/// </summary>
/// <param name="father">The father.</param>
/// <param name="child1">The first child.</param>
/// <param name="child2">The second child.</param>
public void Mate(IGenome father, IGenome child1, IGenome child2, GATracker.MatedElement matedElement)
{
int motherChromosomes = Chromosomes.Count;
int fatherChromosomes = father.Chromosomes.Count;
if (motherChromosomes != fatherChromosomes)
{
throw new GeneticError(
"Mother and father must have same chromosome count, Mother:"
+ motherChromosomes + ",Father:"
+ fatherChromosomes);
}
for (int i = 0; i < fatherChromosomes; i++)
{
Chromosome motherChromosome = chromosomes[i];
Chromosome fatherChromosome = father.Chromosomes[i];
Chromosome offspring1Chromosome = child1.Chromosomes[i];
Chromosome offspring2Chromosome = child2.Chromosomes[i];
//This splices the chromosomes together, using a random number to decide splice points
GA.Crossover.Mate(motherChromosome, fatherChromosome, offspring1Chromosome, offspring2Chromosome);
//Set the gene number
if (matedElement != null)
{
matedElement.SetNumChildGenes(offspring1Chromosome.Genes.Count, 1);
matedElement.SetNumChildGenes(offspring2Chromosome.Genes.Count, 2);
}
//Now we potentially mutate the children
if (ThreadSafeRandom.NextDouble() < GA.MutationPercent)
{
if (matedElement != null)
{
matedElement.Child1Mutated = true;
}
GA.Mutate.PerformMutation(offspring1Chromosome, matedElement, 1);
}
//Now we potentially mutate the children
if (ThreadSafeRandom.NextDouble() < GA.MutationPercent)
{
if (matedElement != null)
{
matedElement.Child2Mutated = true;
}
GA.Mutate.PerformMutation(offspring2Chromosome, matedElement, 2);
}
}
child1.Decode();
child2.Decode();
GA.PerformScoreCalculation(child1);
GA.PerformScoreCalculation(child2);
}
/// <summary>
/// Perform a perturb mutation on the specified chromosome.
/// </summary>
/// <param name="chromosome">The chromosome to mutate.</param>
public void PerformMutation(Chromosome chromosome, GATracker.MatedElement mutatedElement, int childIndex)
{
bool usePertubAmount1 = ThreadSafeRandom.NextDouble() <= percentageUsePerturbAmount1;
foreach (IGene gene in chromosome.Genes)
{
if (gene is DoubleGene)
{
if (usePertubAmount1)
{
if (ThreadSafeRandom.NextDouble() < percentageGenesToPerturb1)
{
DoubleGene doubleGene = (DoubleGene)gene;
double value = doubleGene.Value;
double peturbAmount = (perturbAmount1 - (ThreadSafeRandom.NextDouble()) * perturbAmount1 * 2);
mutatedElement.AddChildMutation(new GATracker.MutationRecord(perturbAmount1, peturbAmount), childIndex);
value += peturbAmount;
doubleGene.Value = value;
}
}
else
{
//if (ThreadSafeRandom.NextDouble() < percentageGenesToPerturb1)
//{
// DoubleGene doubleGene = (DoubleGene)gene;
// double value = doubleGene.Value;
// double peturbAmount = (perturbAmount1 - (ThreadSafeRandom.NextDouble()) * perturbAmount1 * 2);
// mutatedElement.AddChildMutation(new GATracker.MutationRecord(perturbAmount1, peturbAmount), childIndex);
// value += peturbAmount;
// doubleGene.Value = value;
//}
if (ThreadSafeRandom.NextDouble() < percentageGenesToPerturb2)
{
DoubleGene doubleGene = (DoubleGene)gene;
double value = doubleGene.Value;
double peturbAmount = (perturbAmount2 - (ThreadSafeRandom.NextDouble()) * perturbAmount2 * 2);
mutatedElement.AddChildMutation(new GATracker.MutationRecord(perturbAmount2, peturbAmount), childIndex);
value += peturbAmount;
doubleGene.Value = value;
}
}
}
}
}
/// <summary>
/// Perform one generation.
/// </summary>
public virtual void Iteration(GATracker gaTracker)
{
int countToMate = (int)(Population.Genomes.Count * PercentToMate);
int matingPopulationSize = (int)(Population.Genomes.Count * MatingPopulation);
//The only individuals we want to preserve is the mating population.
//i.e. everything but the mating population gets replaced.
int newOffspringCount = Population.Genomes.Count - matingPopulationSize;
int newOffspringIndex = Population.Genomes.Count - newOffspringCount;
int offspringCount = countToMate * 2;
//int offspringIndex = Population.Genomes.Count - offspringCount;
//TaskGroup group = EngineConcurrency.Instance.CreateTaskGroup();
// mate and form the next generation
//20 < 80
while (newOffspringIndex < newOffspringCount + matingPopulationSize)
{
for (int i = 0; i < countToMate; i++)
{
IGenome mother = Population.Genomes[i];
int fatherInt = (int)(ThreadSafeRandom.NextDouble() * matingPopulationSize);
IGenome father = Population.Genomes[fatherInt];
IGenome child1 = Population.Genomes[newOffspringIndex];
IGenome child2 = Population.Genomes[newOffspringIndex + 1];
GATracker.MatedElement matedElement = new GATracker.MatedElement(i, fatherInt, newOffspringIndex, newOffspringIndex + 1);
MateWorker worker = new MateWorker(mother, father, child1, child2, matedElement);
//EngineConcurrency.Instance.ProcessTask(worker, group);
worker.Run();
//Add the matedElement to the GATracker
gaTracker.AddMatedElement(matedElement);
newOffspringIndex += 2;
}
}
//group.WaitForComplete();
// sort the next generation
Population.Sort();
}
public void PerformMutation(Chromosome chromosome, GATracker.MatedElement matedElement, int childIndex)
{
throw new NotImplementedException();
}
