public void InitializeEvolution(Color[,] sourceIndividual)
{
if (AlgorithmInformation.Population < 4)
{
AlgorithmInformation.Population = 4;
}
if (AlgorithmInformation.Elite < 2)
{
AlgorithmInformation.Elite = 2;
}
_threads = new List <Thread>();
_populationForThread = new int[AlgorithmInformation.GetOptimalThreadAmount()];
_populationIndividuals = new Individual[AlgorithmInformation.Population];
_populationToPass = new Individual[AlgorithmInformation.Population];
_eliteIndividuals = new Individual[AlgorithmInformation.Elite];
_destinationIndividual = sourceIndividual;
_evolutionFitness = new EvolutionFitness(AlgorithmInformation.ImageWidth, AlgorithmInformation.ImageHeight);
Individual individual;
for (int i = 0; i < AlgorithmInformation.Population; i++)
{
individual = new Individual();
individual.Initialize();
_populationIndividuals[i] = individual;
}
}
public void SoftMutation()
{
var point = RandomMutation.RandomIntervalIntegerInclusive(0, 1);
switch (point)
{
case 0:
PositionX = RandomMutation.RandomPosition(PositionX - AlgorithmInformation.SmallDeltaValue(), PositionX + AlgorithmInformation.SmallDeltaValue());
break;
case 1:
PositionY = RandomMutation.RandomPosition(PositionY - AlgorithmInformation.SmallDeltaValue(), PositionY + AlgorithmInformation.SmallDeltaValue());
break;
}
FixPosition();
}
public void SoftMutation()
{
var colourMutation = RandomMutation.RandomIntervalIntegerInclusive(0, 4);
switch (colourMutation)
{
case 0:
RedColour = RandomMutation.RandomColour((byte)(RedColour - AlgorithmInformation.SmallDeltaValue()), (byte)(RedColour + AlgorithmInformation.SmallDeltaValue()));
break;
case 1:
GreenColour = RandomMutation.RandomColour((byte)(GreenColour - AlgorithmInformation.SmallDeltaValue()), (byte)(GreenColour + AlgorithmInformation.SmallDeltaValue()));
break;
case 2:
BlueColour = RandomMutation.RandomColour((byte)(BlueColour - AlgorithmInformation.SmallDeltaValue()), (byte)(BlueColour + AlgorithmInformation.SmallDeltaValue()));
break;
case 3:
AlphaColour = RandomMutation.RandomColour((byte)(BlueColour - AlgorithmInformation.SmallDeltaValue()), (byte)(BlueColour + AlgorithmInformation.SmallDeltaValue()));
break;
}
}
override public Individual Generate()
{
_generation++;
if (AlgorithmInformation.DynamicMutation && (_generation % 100 == 0))
{
AlgorithmInformation.MutationChance -= 1;
}
var oneThread = AlgorithmInformation.Population / AlgorithmInformation.GetOptimalThreadAmount();
if (oneThread * AlgorithmInformation.GetOptimalThreadAmount() != AlgorithmInformation.Population)
{
int delta = AlgorithmInformation.Population - (oneThread * (AlgorithmInformation.GetOptimalThreadAmount() - 1));
for (int j = 0; j < AlgorithmInformation.GetOptimalThreadAmount() - 1; j++)
{
_populationForThread[j] = oneThread;
}
_populationForThread[AlgorithmInformation.GetOptimalThreadAmount() - 1] = delta;
}
else
{
for (int j = 0; j < AlgorithmInformation.GetOptimalThreadAmount(); j++)
{
_populationForThread[j] = oneThread;
}
}
int from = 0;
int to = _populationForThread[0];
for (int j = 0; j < AlgorithmInformation.GetOptimalThreadAmount(); j++)
{
int[] coords = { from, to };
var th = new Thread(() =>
{
ComparePopulation(coords[0], coords[1]);
});
this._threads.Add(th);
if ((j + 1) < _populationForThread.Length)
{
from += _populationForThread[j];
to += _populationForThread[j + 1];
}
}
foreach (Thread th in _threads)
{
th.Start();
}
foreach (Thread th in _threads)
{
th.Join();
}
_populationIndividuals = _populationIndividuals.OrderByDescending(i => i.Adaptation).ToArray();
for (int j = 0; j < AlgorithmInformation.Population; j++)
{
_populationToPass[j] = _populationIndividuals[j].CloneIndividual();
}
for (int j = 0; j < AlgorithmInformation.Elite; j++)
{
_eliteIndividuals[j] = _populationIndividuals[j].CloneIndividual();
}
int mother = 0;
int father = 1;
for (int i = 0; i < AlgorithmInformation.Population; i++)
{
_populationIndividuals[i] = Reproduct(_eliteIndividuals[mother], _eliteIndividuals[father]);
mother++;
if (mother >= AlgorithmInformation.Elite)
{
father++;
mother = 0;
}
if (father >= AlgorithmInformation.Elite)
{
father = 0;
}
}
AlgorithmInformation.KilledChilds += AlgorithmInformation.Population - AlgorithmInformation.Elite;
OnIndividualCreated(_eliteIndividuals[0]);
_threads.Clear();
return(_eliteIndividuals[0]);
}
