public void VerifyNeatPopulationStats()
{
IRandomSource rng = RandomDefaults.CreateRandomSource(0);
// Create test population and apply speciation strategy.
NeatPopulation <double> neatPop = CreateNeatPopulation(30, 10.0, rng);
// Loop the species; assign the same fitness to genomes within each species.
for (int i = 0; i < neatPop.SpeciesArray.Length; i++)
{
double fitness = (i + 1) * 10.0;
neatPop.SpeciesArray[i].GenomeList.ForEach(x => x.FitnessInfo = new FitnessInfo(fitness));
}
// Calc NeatPopulation statistics.
neatPop.UpdateStats(PrimaryFitnessInfoComparer.Singleton, rng);
// Validate expected mean fitness for each species.
for (int i = 0; i < neatPop.SpeciesArray.Length; i++)
{
double expectedMeanFitness = (i + 1) * 10.0;
Assert.Equal(expectedMeanFitness, neatPop.SpeciesArray[i].Stats.MeanFitness);
}
// Validate SumSpeciesMeanFitness.
double expectedSumSpeciesMeanFitness = 10.0 + 20.0 + 30.0;
Assert.Equal(expectedSumSpeciesMeanFitness, neatPop.NeatPopulationStats.SumSpeciesMeanFitness);
// Validate BestGenomeSpeciesIdx.
Assert.Equal(2, neatPop.NeatPopulationStats.BestGenomeSpeciesIdx);
// Assign a high fitness to one of the genomes, and check that BestGenomeSpeciesIdx is updated accordingly.
neatPop.SpeciesArray[0].GenomeList[2].FitnessInfo = new FitnessInfo(100.0);
// Note. The species must be re-initialised in order for the fit genome to be sorted correctly within its
// containing species.
InitialiseSpecies(neatPop);
neatPop.UpdateStats(PrimaryFitnessInfoComparer.Singleton, rng);
Assert.Equal(0, neatPop.NeatPopulationStats.BestGenomeSpeciesIdx);
// Perform the same test again with the best genome in the second species.
neatPop.SpeciesArray[1].GenomeList[3].FitnessInfo = new FitnessInfo(200.0);
InitialiseSpecies(neatPop);
neatPop.UpdateStats(PrimaryFitnessInfoComparer.Singleton, rng);
Assert.Equal(1, neatPop.NeatPopulationStats.BestGenomeSpeciesIdx);
}
public void VerifyPopulationStats()
{
IRandomSource rng = RandomDefaults.CreateRandomSource(0);
// Create a test population.
NeatPopulation <double> pop = CreateNeatPopulation(100, 10.0, rng);
// Modify a few genome fitnesses.
pop.GenomeList[10].FitnessInfo = new FitnessInfo(100.0);
pop.GenomeList[20].FitnessInfo = new FitnessInfo(0.0);
// Initialise the NEAT population species; the wider population stats are dependent on this occurring.
InitialiseSpecies(pop);
// Calc/update stats.
pop.UpdateStats(PrimaryFitnessInfoComparer.Singleton, rng);
// Validate stats.
// Fitness stats.
PopulationStatistics stats = pop.Stats;
Assert.Equal(10, stats.BestGenomeIndex);
Assert.Equal(100.0, stats.BestFitness.PrimaryFitness);
Assert.Equal(10.8, stats.MeanFitness);
Assert.Equal(1, stats.BestFitnessHistory.Length);
Assert.Equal(100.0, stats.BestFitnessHistory.Total);
// Complexity stats.
Assert.Equal(6.0, stats.BestComplexity);
Assert.Equal(6.0, stats.MeanComplexity);
Assert.Equal(1, stats.MeanComplexityHistory.Length);
Assert.Equal(6.0, stats.MeanComplexityHistory.Total);
}
public void UpdateSpeciesAllocationSizes()
{
IRandomSource rng = RandomDefaults.CreateRandomSource(0);
NeatEvolutionAlgorithmSettings eaSettings = new()
{
SpeciesCount = 4
};
// Create population.
NeatPopulation <double> neatPop = CreateNeatPopulation(100, eaSettings.SpeciesCount, 2, 2, 1.0);
// Manually set-up some species.
var speciesArr = neatPop.SpeciesArray;
speciesArr[0].GenomeList.AddRange(neatPop.GenomeList.Take(25));
speciesArr[1].GenomeList.AddRange(neatPop.GenomeList.Skip(25).Take(25));
speciesArr[2].GenomeList.AddRange(neatPop.GenomeList.Skip(50).Take(25));
speciesArr[3].GenomeList.AddRange(neatPop.GenomeList.Skip(75).Take(25));
// Manually assign fitness scores to the genomes.
speciesArr[0].GenomeList.ForEach(x => x.FitnessInfo = new FitnessInfo(100.0));
speciesArr[1].GenomeList.ForEach(x => x.FitnessInfo = new FitnessInfo(200.0));
speciesArr[2].GenomeList.ForEach(x => x.FitnessInfo = new FitnessInfo(400.0));
speciesArr[3].GenomeList.ForEach(x => x.FitnessInfo = new FitnessInfo(800.0));
// Invoke species target size calcs.
neatPop.UpdateStats(PrimaryFitnessInfoComparer.Singleton, rng);
SpeciesAllocationCalcs <double> .UpdateSpeciesAllocationSizes(
neatPop, eaSettings, RandomDefaults.CreateRandomSource());
// Species target sizes should be relative to the species mean fitness.
double totalMeanFitness = 1500.0;
double popSize = 100.0;
Assert.Equal((100.0 / totalMeanFitness) * popSize, speciesArr[0].Stats.TargetSizeReal);
Assert.Equal((200.0 / totalMeanFitness) * popSize, speciesArr[1].Stats.TargetSizeReal);
Assert.Equal((400.0 / totalMeanFitness) * popSize, speciesArr[2].Stats.TargetSizeReal);
Assert.Equal((800.0 / totalMeanFitness) * popSize, speciesArr[3].Stats.TargetSizeReal);
// Note. Discretized target sizes will generally be equal to ceil(TargetSizeReal) or floor(TargetSizeReal),
// but may not be due to the target size adjustment logic that is used to ensure that sum(TargetSizeInt) is equal
// to the required population size.
// Check that sum(TargetSizeInt) is equal to the required population size.
Assert.Equal(speciesArr.Sum(x => x.Stats.TargetSizeInt), neatPop.GenomeList.Count);
}