/// <summary>
/// Mutates a gene by bitwise mutation.
/// </summary>
/// <param name="gene"></param>
/// <returns></returns>
public static Gene Mutate(Gene gene)
{
if (gene is BinaryGene)
{
BinaryGene g = (BinaryGene)gene.Clone();
g.Value = !(BinaryGene)gene;
return(g);
}
else if (gene is DoubleGene)
{
DoubleGene g = (DoubleGene)gene.Clone();
byte[] bytes = BitConverter.GetBytes(g.Value);
BitArray ba = new BitArray(bytes);
int p = Utils.Rand.Next(ba.Length);
ba.Set(p, !ba[p]);
ba.CopyTo(bytes, 0);
g.Value = BitConverter.ToDouble(bytes, 0);
return(g);
}
else if (gene is IntegerGene)
{
IntegerGene g = (IntegerGene)gene.Clone();
byte[] bytes = BitConverter.GetBytes(g.Value);
BitArray ba = new BitArray(bytes);
int p = Utils.Rand.Next(ba.Length);
ba.Set(p, !ba[p]);
ba.CopyTo(bytes, 0);
g.Value = BitConverter.ToInt32(bytes, 0);
return(g);
}
return((Gene)gene.Clone()); // default
}
public void Clone_Gene_ClonedGene()
{
var representation = new [] { 1.2m, 1.3m, 1.4m, 1.5m };
var probability = 0.1m;
var gene = new Gene <decimal>(representation, probability);
var cloned = (Gene <decimal>)gene.Clone();
Assert.AreEqual(cloned.Representation[0], representation[0]);
Assert.AreEqual(cloned.Representation[1], representation[1]);
Assert.AreEqual(cloned.Representation[2], representation[2]);
Assert.AreEqual(cloned.Representation[3], representation[3]);
Assert.AreEqual(cloned.MutationProbability, probability);
}
private Gene CrossOverGenes(Gene a, Gene b)
{
double mutationProb = 0.5f;
Gene c = a.Clone();
for (int i = 0; i < a.collection.Count; i++)
{
if (random.NextDouble() > mutationProb)
{
c.collection[i] = b.collection[i].Clone();
}
}
return(c);
}
private void Crossbreed(Individual child)
{
var rnd = new Random();
var swopIndex = rnd.Next(0, child.Genes.Length);
//todo: enhance per category e.g. breakfast, snack, lunch, supper
for (int i = 0; i < swopIndex; i++)
{
//todo: check for duplicate genes
child.Genes[i] = Gene.Clone(Best.Genes[i]);
}
//todo: enhance per category e.g. breakfast, snack, lunch, supper
for (int i = swopIndex; i < child.Genes.Length; i++)
{
//todo: check for duplicate genes
child.Genes[i] = Gene.Clone(SecondBest.Genes[i]);
}
}
public void Run(object obj_iterations)
{
int nrOfIterations = (int)obj_iterations;
double referenceNegativeIndex = double.MaxValue;
double referenceComeback = NrOfPolygons;
bool nrOfMutationsTryChanged = false;
int limit = 0;
int shakeTheImageCounter = 0;
double currentNegativeFitness = workingGene.NegativeFitness;
for (int i = 0; i < nrOfIterations; i++)
{
if (CommandChannel.GetCommand() == 1)
{
break;
}
List <int> mutationsList = retrieveMutationsList();
for (int mi = 0; mi < mutationsList.Count; mi++)
{
int mutationStep = mutationsList[mi];
switch (mutationStep)
{
case 1: performAddPolygon(workingGene); break;
case 2: performMutateColor(workingGene); break;
case 3: performMutatePolygon(workingGene); break;
case 4: performMutatePolygonAndColor(workingGene); break;
case 5: performMutateColorParam(workingGene); break;
case 6: performMutatePolygonPoint(workingGene); break;
}
}
#region check if the gene had evolved in the last 250 iterations; comment this region if you don't one to have momentum in your app
if (currentNegativeFitness != workingGene.NegativeFitness)
{
currentNegativeFitness = workingGene.NegativeFitness;
shakeTheImageCounter = 0;
}
else
{
//that means the in the last 250 iterations nothing changed in the gene fitness.
if (shakeTheImageCounter > 250)
{
int nrOfPolysToBeRemoved = workingGene.NrOfPolygons / 10;
for (int ix = 0; ix < nrOfPolysToBeRemoved; ix++)
{
randomlyRemovePolygons(workingGene);
}
referenceComeback = workingGene.Polygons.Count + 1;
}
shakeTheImageCounter++;
}
#endregion
//if gene is more fit, we added to the container;
Console.WriteLine("Negative fitness: {0} , {1}", workingGene.NegativeFitness, workingGene.Polygons.Count);
if (workingGene.NegativeFitness < referenceNegativeIndex)
{
GeneContainer.Instance.AddGene(workingGene.Clone());
referenceNegativeIndex = workingGene.NegativeFitness;
}
#region every 100 iterations we increase the number of polygons, till we reach 50
if (workingGene.Polygons.Count < 50 && this.NrOfPolygons < 50)
{
if (i % 100 == 0 && i != 0)
{
this.NrOfPolygons++;
workingGene.NrOfPolygons++;
}
}
#endregion
//if every time the number of polygons in the gene reaches the max number of polygons, then we increase the nr of polygons and
//we remove the less fit individuals
if (workingGene.Polygons.Count < 50)
{
if (workingGene.Polygons.Count == referenceComeback)
{
limit = workingGene.Polygons.Count / 10;
for (int ix = 0; ix < limit; ix++)
{
removeLessFitPolys(workingGene);
}
Console.WriteLine("-------- [ReferenceComeback] :" + referenceComeback);
referenceComeback++;
}
}
// when 50 poly are reached, we double the nr of mutations tries;
// and we remove a larger number of less fit individuals;
else if (workingGene.Polygons.Count >= 50)
{
if (nrOfMutationsTryChanged == false)
{
NrOfMutationsTries = NrOfMutationsTries * 2;
nrOfMutationsTryChanged = true;
}
limit = workingGene.Polygons.Count / 8;
for (int ix = 0; ix < limit; ix++)
{
removeLessFitPolys(workingGene);
}
}
}
CommandChannel.SetCommand(2); //tell timer to stop
}
