/// <summary>
/// Create a population with random genomes.
/// </summary>
private void Populate()
{
for (int i = 0; i < GenomeCount; i++)
{
Genomes.Add(new Genome(InputCount, OutputCount, Config.weightInitRandomValue));
}
}
//constructor
public Population(int size, int inputDims)
{
_inputDims = inputDims;
AddedConnections = new Dictionary <string, int>();
for (int i = 0; i < size; i++)
{
Genomes.Add(new Genome(inputDims));
}
}
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);
}
}
/// <summary>
/// Create a population of a set number of genes, with a crossover type, and the ideal path ends
/// </summary>
/// <param name="numberOfGenomes"></param>
/// <param name="crossOver"></param>
/// <param name="originPosition"></param>
/// <param name="destinationPosition"></param>
public Population(int numberOfGenomes, CrossOver crossOver, Coordinate originPosition, Coordinate destinationPosition, float mutationStrength)
{
NumberOfGenomes = numberOfGenomes;
CrossOver = crossOver;
OriginPosition = originPosition;
DestinationPosition = destinationPosition;
MutationStrength = (int)(mutationStrength * 100);
for (int i = 0; i < NumberOfGenomes; i++)
{
Genomes.Add(new Genome(OriginPosition));
}
}
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;
}
/// <summary>
/// Add Genome to Species and Update it's ID
/// </summary>
public void Add(Genome genome)
{
Genomes.Add(genome);
genome.SpeciesID = this.ID;
}
