public BestOfSampling(ICandidateFactory <TSysConfig> innerSamplingFactory, int poolSize, int bestPoints,
IObjectiveEvaluator <TSysConfig> evaluator, IFitnessAssignment <double> fitAssignment = null)
{
if (fitAssignment == null)
{
fitAssignment = new DefaultFitnessAssignment();
}
if (poolSize < bestPoints)
{
throw new ArgumentOutOfRangeException("poolSize", poolSize, String.Format("poolSize must be >= bestPoints({0})", bestPoints));
}
this.HcFactory = (IHyperCubeOperationsFactory)innerSamplingFactory;
this.innerSamplingFactory = innerSamplingFactory;
var tmp = new IObjectiveScores[poolSize];
for (int i = 0; i < poolSize; i++)
{
tmp[i] = evaluator.EvaluateScore(innerSamplingFactory.CreateRandomCandidate());
}
var points = fitAssignment.AssignFitness(tmp);
Array.Sort(points);
candidates = new FitnessAssignedScores <double> [bestPoints];
for (int i = 0; i < bestPoints; i++)
{
candidates[i] = points[i];
}
}
private T[] initialisePopulation()
{
T[] result = new T[numShuffle];
for (int i = 0; i < result.Length; i++)
{
result[i] = populationInitializer.CreateRandomCandidate();
}
return(result);
}
public TSysConfig CreateRandomCandidate()
{
if (this.seeds != null && (counterSeeds < this.seeds.Length))
{
counterSeeds++;
return(this.seeds[counterSeeds - 1]);
}
else
{
return(uniformRandomSamplingFactory.CreateRandomCandidate());
}
}
