private static Chromosome SingleMutation(Chromosome chromosome)
{
Chromosome newChromosome = chromosome.GetClone();
newChromosome[GrammaticalEvolution.random.Next(chromosome.Count)] = (byte)GrammaticalEvolution.random.Next(0, 256);
return(newChromosome);
}
public Tuple <List <double>, List <double> > ExecuteTest(int testnumber, int testSize, int mutatedIndividuals, int initialChromosomeSize, double failureFitnessValue, bool useGE1ForBase, bool includeFailedCorrections)
{
List <double> localityResults1 = new List <double>();
List <double> localityResults2 = new List <double>();
for (int i = 0; i < testSize; i++)
{
Chromosome baseChromosome = null;
double baseFitness = failureFitnessValue;
while (baseFitness == failureFitnessValue)//Check that it is a correct individual
{
baseChromosome = new Chromosome(initialChromosomeSize, 64);
GrammaticalEvolution baseGE = (useGE1ForBase ? GE1 : GE2).GetClone();
baseFitness = Evaluate(baseChromosome, true, baseGE).Item1;
}
for (int j = 0; j < mutatedIndividuals; j++)//TODO: Perché le differenze del 2 è di 1?.
{
Chromosome mutatedChromosome1 = SingleMutation(baseChromosome);
mutatedChromosome1.BackupCodons = baseChromosome.ToList();
Chromosome mutatedChromosome2 = mutatedChromosome1.GetClone();
Tuple <double, bool> result1 = Evaluate(mutatedChromosome1, false, GE1);
Tuple <double, bool> result2 = Evaluate(mutatedChromosome2, false, GE2);
double minDistance = (double)1 / 64;
localityResults1.Add(Math.Abs(result1.Item1 - baseFitness - minDistance));
double secondResult = result2.Item2 ? baseFitness : result2.Item1;
localityResults2.Add(Math.Abs(secondResult - baseFitness - minDistance));
}
Console.WriteLine(i + " out of " + testSize);
}
Console.WriteLine("Media 1:" + localityResults1.Average());
Console.WriteLine("Media 2:" + localityResults2.Average());
Console.WriteLine("Miglioramento:" + ((localityResults1.Average() - localityResults2.Average()) / localityResults1.Average()));
return(new Tuple <List <double>, List <double> >(localityResults1, localityResults2));
/*string percorso = @"C:\Users\Samuele\Documents\BetterPECLE\v3\Studio località\";
* //string avviso = "ATTENZIONE: QUESTI RISULTATI SONO STATI DEFINITI PREVENTIVAMENTE COME TEST.\n" +
* // "AL FINE DI RISPETTARE L'ETICA SCIENTIFICA, NON USARE QUESTI DATI IN NESSUNA PUBBLICAZIONE.\n\n";
*
* double miglioramento = ((localityResults1.Average() - localityResults2.Average()) / localityResults1.Average());
*
* string spiegazione = "I seguenti dati indicano la differenza di fitness medio per mutazione. Più la differenza\n" +
* "è bassa, più la rappresentazione è locale.\n\n";
* File.WriteAllText(percorso + "Studio" + testnumber + ".txt",
* spiegazione + "Media default: " + localityResults1.Average() +
* "\nDeviazione Standard: " + StdDev(localityResults1) +
* "\nMedia PECLE: " + localityResults2.Average() +
* "\nDeviazione Standard: " + StdDev(localityResults2) +
* "\nMiglioramento: " + miglioramento);*/
}
public GenerationStats GetClone()
{
GenerationStats stats = new GenerationStats();
stats.bestChromosome = bestChromosome.GetClone();
stats.compilationErrors = compilationErrors;
stats.executedEvaluations = executedEvaluations;
stats.executionExceptions = executionExceptions;
stats.failedErrorChecks = failedErrorChecks;
stats.failedErrorCorrections = failedErrorCorrections;
stats.fitnessValues = fitnessValues.ToList();
stats.generationErrors = generationErrors;
stats.passedErrorChecks = passedErrorChecks;
stats.successfulErrorCorrections = successfulErrorCorrections;
return(stats);
}
public override Tuple <Chromosome, Chromosome> Cross(Chromosome parent1, Chromosome parent2, double crossoverProbability)
{
if (GrammaticalEvolution.random.NextDouble() < crossoverProbability)
{
int crossoverPoint = GrammaticalEvolution.random.Next(0, Math.Min(parent1.Count, parent2.Count));
Chromosome child1 = new Chromosome(0, parent1.MaximumSize);
Chromosome child2 = new Chromosome(0, parent2.MaximumSize);
for (int i = 0; i < crossoverPoint; i++)
{
child1.Add(parent1[i]);
child2.Add(parent2[i]);
}
for (int j = crossoverPoint; j < parent2.Count; j++)
{
child1.Add(parent2[j]);
}
for (int k = crossoverPoint; k < parent1.Count; k++)
{
child2.Add(parent1[k]);
}
if (GrammaticalEvolution.random.NextDouble() > 0.5)
{
child1.BackupCodons = parent1.BackupCodons == null ? null : parent1.BackupCodons.ToList();
child2.BackupCodons = parent2.BackupCodons == null ? null : parent2.BackupCodons.ToList();
}
else
{
child1.BackupCodons = parent2.BackupCodons == null ? null : parent2.BackupCodons.ToList();
child2.BackupCodons = parent1.BackupCodons == null ? null : parent1.BackupCodons.ToList();
}
return(new Tuple <Chromosome, Chromosome>(child1, child2));
}
else
{
return(new Tuple <Chromosome, Chromosome>(parent1.GetClone(), parent2.GetClone()));
}
}
