public Population(int n, int[] m, float elitism, float mutationRate, GA_NN_Settings.SelectionMethod selectionMethod)
{
MutationRate = mutationRate;
Elitism = elitism;
GeneratePopulation(n, m);
recordSolution = Individuals[0];
nElite = (int)(Individuals.Length * Elitism);
tournamentGroupSize = (int)(Individuals.Length * 0.02f);
OnSelectionEvent += () => Individuals = Individuals.OrderByDescending(x => x.Fitness).ToArray();
switch (selectionMethod)
{
case GA_NN_Settings.SelectionMethod.Tournament:
{
SelectIndividual = SelectIndividualByTournament;
//System.Windows.MessageBox.Show("Metoda turniejowa");
} break;
case GA_NN_Settings.SelectionMethod.Ranking:
{
SelectIndividual = ChooseRandomIndividual;
OnSelectionEvent += CalculateFitnessBasedOnRanking;
//System.Windows.MessageBox.Show("Metoda Rankingowa");
}
break;
}
}
// Finds the fittest individual
public Individual GetFittest()
{
var fittest = Individuals.OrderByDescending(i => i.Fitness).First();
FitnessValue = fittest.Fitness;
return(fittest);
}
/// <summary>
/// Picks the given number of individuals with the best scores.
/// </summary>
/// <param name="WinnersCount"></param>
/// <returns>List of genomes</returns>
public IEnumerable <string> PickWinners(int WinnersCount)
{
var minScore = Individuals.Min(i => i.Score);
return(Individuals.OrderByDescending(i =>
{
var randomNumber = _rng.NextDouble();
return (1 + i.AverageScore - minScore) * randomNumber;
}).Take(WinnersCount).Select(i => i.Genome));
}
public IEvolvable FindMate(IEvolvable evolvable)
{
// return IndividualsSortedByFitness.Take(10).MaxElement(a => evolvable.DifferenceTo(a));
// sort by difference and then take the best out of the top 10! :D
return(Individuals.OrderByDescending(a => evolvable.DifferenceTo(a)).Take(10).OrderByDescending(a => a.Fitness).First());
//return IndividualsSortedByFitness.Take(3).MaxElement(a => evolvable.DifferenceTo(a));
//return Best;
//return IndividualsSortedByFitness.MaxElement(a => evolvable.DifferenceTo(a));
}
public Individual[] OrderByFitness()
{
return(Individuals.OrderByDescending(x => x.Fitness).ToArray());
}
public Melody BestIndividual()
{
return(Individuals.OrderByDescending(i => i.Fitness).FirstOrDefault());
}
/**
* Sort the individuals in this subspecies, the one with highest fitness
* comes first.
*/
public void SortIndividuals()
{
Individuals = Individuals
.OrderByDescending(x => ((NEATIndividual)x).AdjustedFitness)
.ToList();
}
public Individual TheBestInPopulation()
{
return(Individuals.OrderByDescending(q => q.FunctionValue).FirstOrDefault());
}
public Individual GetSecondFittest()
{
var nextFittest = Individuals.OrderByDescending(i => i.Fitness).Skip(1).First();
return(nextFittest);
}
