public void Reset(Random r)
{
Genome = Genomes[r.Next(Genomes.Count)];
Genomes.Clear();
FitnessPop.Clear();
TotalAdjustedFitness = 0f;
}
public MasterMindPopulation(int numberOfGenomes)
{
Genomes.Clear();
for (int i = 0; i < numberOfGenomes; i++)
{
MastermindGenome aGenome = new MastermindGenome(kLength, 1, 9);
aGenome.SetCrossoverPoint(kCrossover);
aGenome.CalculateFitness();
Genomes.Add(aGenome);
}
}
private void CreateStartPopulation(int genomes, int numChromosoneBits, int numGeneBits)
{
//clear existing population
Genomes.Clear();
for (int i = 0; i < genomes; i++)
{
var genome = new TGenome();
genome.Initialize(numChromosoneBits, numGeneBits);
Genomes.Add(genome);
}
//reset all variables
Generation = 0;
TotalFitnessScore = 0;
}
private void CreateStartPopulation(int genomes, Action <TGenome> genomeCreationMethod)
{
//clear existing population
Genomes.Clear();
for (int i = 0; i < genomes; i++)
{
var genome = new TGenome();
genomeCreationMethod(genome);
Genomes.Add(genome);
}
//reset all variables
Generation = 0;
TotalFitnessScore = 0;
GeneLength = -1;
ChromosoneLength = Genomes.First().Genes.Sum(g => g.Length);
}
public void CreateStartPopulation()
{
// clear existing population
Genomes.Clear();
//Parallel.For(0, _settings.PopulationSize, (i) =>
for (int i = 0; i < _settings.PopulationSize; i++)
{
var genome = new Genome <TMainModel, TCombinationModel>(_settings);
// Make sure all genomes are initially different
int initPasses = 0;
do
{
genome.Initialize();
initPasses++;
lock (Genomes)
{
if (!Genomes.AsParallel().Any(g => g.GetUniqueGenesString().Equals(genome.GetUniqueGenesString())))
{
break; // we are all good
}
if (initPasses > 10)
{
throw new InvalidOperationException("No more combinations possible, reduce population size!");
}
}
} while (true);
lock (Genomes)
{
Genomes.Add(genome);
}
//Debug.WriteLineIf(initPasses>1, $"# Re-initialized because of duplicate genome ({initPasses})");
}
;
//reset all variables
Generation = 0;
TotalFitnessScore = 0;
}
public void NextGen(List <Species> speciesList)
{
//var speciesList = _speciesList.Where(x => (x.Stagnant == false)).ToList();
var popSize = Genomes.Count;
Genomes.Clear();
var totalFitness = speciesList.Select(x => (1.0 / x.MinFitness)).Sum();
//var expSum = speciesList.Select(x => Math.Exp(1.0/ x.Fitness)).Sum();
var remainder = popSize;
var count = speciesList.Count;
foreach (var species in speciesList)
{
//var newProp = Math.Exp((1.0/species.Fitness)) / expSum * popSize; ;
var proportion = (1.0 / species.MinFitness) / totalFitness * popSize;
//var proportion = newProp;
var decimalPart = proportion - Math.Truncate(proportion);
//ensures the total adds up at the end
int numChildren = decimalPart < 0.5 ? (int)Math.Floor(proportion) : (int)Math.Ceiling(proportion);
if (count == 1)
{
numChildren = remainder;
}
numChildren = numChildren < 0 ? 0 : numChildren;
remainder -= numChildren;
NextGeneration(species, numChildren);
count--;
}
}