public ChordChainGeneticFunction(
DiscreteNeuralNetworkByChord dnn,
NGramGraphMarkovChain <Chord> chord,
INGramWeightAssigner <Chord> assigner,
ChordRandomFunctionType type = ChordRandomFunctionType.NoRandomSelection,
ChordCrossFunctionType cross = ChordCrossFunctionType.DiscreteChoice)
{
dnn.NullCheck();
chord.NullCheck();
assigner.NullCheck();
this.NeuralNetwork = dnn;
this.NGramGraph = chord;
this.RandomFunctionType = type;
this.CrossFunctionType = cross;
this.ChordDepth = this.NeuralNetwork.InputsCount * 2;
this.NGramDepth = 10;
this.MutateCoefficient = 0.05D;
this.Assigner = assigner;
this.random = new Random();
switch (type)
{
case ChordRandomFunctionType.AllowRandomSelection:
this.RandomSelectionCoefficient = .05D;
return;
}
}
public double Fitness(NGram <Chord>[] t)
{
var training = t.SelectMany(x => x.SelectMany(y => DiscreteNeuralNetworkByChord.ConvertChordIntoTrainingInput(y))).ToList();
if (training.Count < this.NeuralNetwork.InputsCount)
{
training.AddRange(Enumerable.Repeat(-2D, this.NeuralNetwork.InputsCount - training.Count));
return(this.NeuralNetwork.Compute(training.ToArray()));
}
var data = this.Partition(training);
var query = data.Where(x => x.Length == this.NeuralNetwork.InputsCount).ToList();
var error = query.Select(x => this.NeuralNetwork.Compute(x)).Sum();
if (data.Count != query.Count)
{
int count = data.Last().Length;
float percent = (float)count / (float)query.Count * (float)this.NeuralNetwork.InputsCount;
error *= percent;
}
return(error);
}
private void trainingButton_Click(object sender, EventArgs e)
{
PianoNoteRetriever retriever = new PianoNoteRetriever();
var midiEvents = new InstrumentMidiEventProducer(this.files.Select(x => new Sequence(x)));
var midi = midiEvents.GetOrderedMessages(GeneralMidiInstrument.AcousticGrandPiano);
Chord.AllowForComplexSimplification = this.checkBox.Checked;
var accords = Chord.RetrieveChords(midi, retriever);
DiscreteDataRetriever data = new DiscreteDataRetriever(accords.ToList());
DiscreteNeuralNetworkByChord.OkayWeight = (double)this.okayWeight.Value;
DiscreteNeuralNetworkByChord.HiddenLayerSize = (int)hiddelLayerSize.Value;
if (this.okayFiles != null)
{
var midiEvents1 = new InstrumentMidiEventProducer(this.okayFiles.Select(x => new Sequence(x)));
var midi1 = midiEvents1.GetOrderedMessages(GeneralMidiInstrument.AcousticGrandPiano);
Chord.AllowForComplexSimplification = this.checkBox.Checked;
var accords1 = Chord.RetrieveChords(midi1, retriever);
DiscreteDataRetriever data1 = new DiscreteDataRetriever(accords1.ToList());
this.nnByChord = new DiscreteNeuralNetworkByChord(data.Good, data1.Good, data.Bad.Union(data1.Bad).Take(data.Bad.Count).ToList(),
new AForge.Neuro.BipolarSigmoidFunction());
}
else
{
this.nnByChord = new DiscreteNeuralNetworkByChord(data.Good, data.Okay, data.Bad, new AForge.Neuro.SigmoidFunction());
}
foreach (var item in this.Controls.OfType<Control>())
{
item.Enabled = false;
}
threadTrain = new Thread(Start);
threadTrain.Start();
}