public void WriteParamValues(int iteration, double fitness, Gene gene)
{
Write(iteration + ",");
for (var index = 0; index < gene.Chromosomes.Count; index++)
{
Write(gene.Chromosomes[index] + ",");
}
WriteLine(fitness.ToString("N3"));
}
public bool Valid(Gene gene)
{
var valid = !_seenGenes.ContainsKey(gene);
if (valid)
{
_seenGenes.Add(gene, true);
}
return(valid);
}
public bool Valid(Gene gene)
{
var valid = !_seenGenes.ContainsKey(gene);
if (valid)
{
_seenGenes.Add(gene, true);
}
return valid;
}
public bool Valid(Gene gene)
{
foreach (var validator in _geneValidators)
{
if (!validator.Valid(gene))
{
return(false);
}
}
return(true);
}
public GeneScore Evaluate(Gene gene)
{
for (var i = 0; i < gene.Chromosomes.Count; i++)
{
// NT needs everything to be doubles
_strategy.Parameters[_strategyParameterIndices[i]].Value = Convert.ToDouble(gene.Chromosomes[i]);
}
_strategy.RunIteration();
return new GeneScore(gene, FitnessFunctionWrapper.LastPerformanceValue);
}
public bool Valid(Gene gene)
{
foreach (var validator in _geneValidators)
{
if (!validator.Valid(gene))
{
return false;
}
}
return true;
}
private Gene Reproduce(double mutationRate, params Gene[] parents)
{
var child = new Gene();
for (var i = 0; i < _chromosomeTypes.Count; i++)
{
var chromosome = parents[_random.Next(parents.Length)].Chromosomes[i];
if (_random.NextDouble() < mutationRate)
{
chromosome = _chromosomeTypes[i].Mutate(chromosome, _random);
}
child.Chromosomes.Add(chromosome);
}
return(child);
}
private Gene Reproduce(double mutationRate, params Gene[] parents)
{
var child = new Gene();
for (var i = 0; i < _chromosomeTypes.Count; i++)
{
var chromosome = parents[_random.Next(parents.Length)].Chromosomes[i];
if (_random.NextDouble() < mutationRate)
{
chromosome = _chromosomeTypes[i].Mutate(chromosome, _random);
}
child.Chromosomes.Add(chromosome);
}
return child;
}
private Gene CreateNew()
{
var gene = new Gene();
foreach (var chromosomeType in _chromosomeTypes)
{
gene.Chromosomes.Add(chromosomeType.GetRandomValue(_random));
}
return gene;
}
