public static void TestSpeciateAdd(
int popSize,
int inputNodeCount,
int outputNodeCount,
double connectionsProportion,
IDistanceMetric <double> distanceMetric,
ISpeciationStrategy <NeatGenome <double>, double> speciationStrategy,
IRandomSource rng,
bool validateNearestSpecies = true)
{
// Create population.
NeatPopulation <double> neatPop = CreateNeatPopulation(popSize, inputNodeCount, outputNodeCount, connectionsProportion);
// Split the population into three.
int popSize1 = popSize / 3;
int popSize2 = popSize / 3;
int popSize3 = popSize - (popSize1 + popSize2);
var genomeList1 = neatPop.GenomeList.GetRange(0, popSize1);
var genomeList2 = neatPop.GenomeList.GetRange(popSize1, popSize2);
var genomeList3 = neatPop.GenomeList.GetRange(popSize1 + popSize2, popSize3);
for (int i = 0; i < 6; i++)
{
int speciesCount = rng.Next(1, (neatPop.GenomeList.Count / 4) + 1);
var fullGenomeList = new List <NeatGenome <double> >(genomeList1);
// Invoke speciation strategy, and run tests
var speciesArr = speciationStrategy.SpeciateAll(genomeList1, speciesCount, rng);
ValidationTests(speciesArr, distanceMetric, speciesCount, fullGenomeList, validateNearestSpecies);
// Add second batch of genomes, and re-run tests.
speciationStrategy.SpeciateAdd(genomeList2, speciesArr, rng);
fullGenomeList.AddRange(genomeList2);
ValidationTests(speciesArr, distanceMetric, speciesCount, fullGenomeList, validateNearestSpecies);
// Add third batch of genomes, and re-run tests.
speciationStrategy.SpeciateAdd(genomeList3, speciesArr, rng);
fullGenomeList.AddRange(genomeList3);
ValidationTests(speciesArr, distanceMetric, speciesCount, fullGenomeList, validateNearestSpecies);
}
}
/// <summary>
/// Initialise (or re-initialise) the population species.
/// </summary>
/// <param name="speciationStrategy">The speciation strategy to use.</param>
/// <param name="speciesCount">The required number of species.</param>
/// <param name="rng">Random source.</param>
public void InitialiseSpecies(
ISpeciationStrategy <NeatGenome <T>, T> speciationStrategy,
int speciesCount,
IRandomSource rng)
{
// Allocate the genomes to species.
Species <T>[] speciesArr = speciationStrategy.SpeciateAll(this.GenomeList, speciesCount, rng);
if (null == speciesArr || speciesArr.Length != speciesCount)
{
throw new Exception("Species array is null or has incorrect length.");
}
this.SpeciesArray = speciesArr;
// Sort the genomes in each species. Highest fitness first, then secondary sorted by youngest genomes first.
foreach (Species <T> species in speciesArr)
{
SortUtils.SortUnstable(species.GenomeList, GenomeFitnessAndAgeComparer <T> .Singleton, rng);
}
}
/// <summary>
/// Initialise the strategy.
/// </summary>
public void Initialise(Population <NeatGenome <T> > population)
{
// Check for expected population type.
var neatPop = population as NeatPopulation <T>;
if (null == neatPop)
{
throw new ArgumentException("Invalid population type; expected NeatPopulation<T>.", "population");
}
// Initialise species.
var speciesArr = _speciationStrategy.SpeciateAll(population.GenomeList, _speciesCount);
if (null == speciesArr || speciesArr.Length != _speciesCount)
{
throw new Exception("Species array is null or has incorrect length.");
}
neatPop.SpeciesArray = speciesArr;
}
/// <summary>
/// Initialise (or re-initialise) the population species.
/// </summary>
/// <param name="speciationStrategy">The speciation strategy to use.</param>
/// <param name="speciesCount">The required number of species.</param>
/// <param name="genomeComparerDescending">A genome comparer for sorting by fitness in descending order.</param>
/// <param name="rng">Random source.</param>
public void InitialiseSpecies(
ISpeciationStrategy <NeatGenome <T>, T> speciationStrategy,
int speciesCount,
IComparer <NeatGenome <T> > genomeComparerDescending,
IRandomSource rng)
{
// Allocate the genomes to species.
Species <T>[] speciesArr = speciationStrategy.SpeciateAll(this.GenomeList, speciesCount, rng);
if (speciesArr is null || speciesArr.Length != speciesCount)
{
throw new Exception("Species array is null or has incorrect length.");
}
this.SpeciesArray = speciesArr;
// Sort the genomes in each species by primary fitness, highest fitness first.
// We use an unstable sort; this ensures that the order of equally fit genomes is randomized, which in turn
// randomizes which genomes are in the subset if elite genomes that are preserved for the next generation - if lots
// of genomes have equally high fitness.
foreach (var species in speciesArr)
{
SortUtils.SortUnstable(species.GenomeList, genomeComparerDescending, rng);
}
}
public static void TestSpeciateAll(
int popSize,
int inputNodeCount,
int outputNodeCount,
double connectionsProportion,
IDistanceMetric <double> distanceMetric,
ISpeciationStrategy <NeatGenome <double>, double> speciationStrategy,
IRandomSource rng,
bool validateNearestSpecies = true)
{
// Create population.
NeatPopulation <double> neatPop = CreateNeatPopulation(popSize, inputNodeCount, outputNodeCount, connectionsProportion);
for (int i = 0; i < 6; i++)
{
int speciesCount = rng.Next(1, (neatPop.GenomeList.Count / 4) + 1);
// Invoke speciation strategy.
var speciesArr = speciationStrategy.SpeciateAll(neatPop.GenomeList, speciesCount, rng);
// Perform tests.
ValidationTests(speciesArr, distanceMetric, speciesCount, neatPop.GenomeList, validateNearestSpecies);
}
}
