/// <summary>
/// Initializes a new instance of the <see cref="GPTreeChromosome"/> class.
/// </summary>
///
/// <param name="ancestor">A gene, which is used as generator for the genetic tree.</param>
///
/// <remarks><para>This constructor creates a randomly generated genetic tree,
/// which has all genes of the same type and properties as the specified <paramref name="ancestor"/>.
/// </para></remarks>
///
public GPCustomTree(NoteGene ancestor)
{
// make the ancestor gene to be as temporary root of the tree
root.Gene = ancestor.Clone();
// call tree regeneration function
Generate();
}
public MelodySequence Generate()
{
NoteGene baseGene = new NoteGene(GPGeneType.Function);
baseGene.Function = NoteGene.FunctionTypes.Concatenation;
GPCustomTree tree = new GPCustomTree(baseGene);
if (base_seq != null)
{
tree.Generate(base_seq.ToArray());
tree.Mutate();
tree.Crossover(tree);
int length = base_seq.Length;
int depth = (int)Math.Ceiling(Math.Log(length, 2));
GPCustomTree.MaxInitialLevel = depth - 2;
GPCustomTree.MaxLevel = depth + 5;
}
var selection = new EliteSelection();
pop = new Population(30, tree, fitnessFunction, selection);
pop.AutoShuffling = true;
pop.CrossoverRate = 0.9;
pop.MutationRate = 0.1;
int percentage = MaxGenerations / 100;
for (int i = 0; i < MaxGenerations; i++)
{
if(i>percentage)
{
if (OnPercentage != null)
OnPercentage(this, i, pop.FitnessAvg);
percentage += MaxGenerations / 100;
}
pop.RunEpoch();
if ((int)(i) % 100 == 0)
Console.WriteLine(i / (float)MaxGenerations * 100 + "% : " + pop.FitnessAvg);
}
GPCustomTree best = pop.BestChromosome as GPCustomTree;
var notes = best.GenerateNotes();
return new MelodySequence(notes);
}
