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 NGramGraphChainRetriever(NGramGraphMarkovChain <T> a)
{
a.NullCheck();
this.graph = a;
this.NodeDepthBeforeGreedy = 100;
this.Max = int.MaxValue;
}
public float Distance(NGramGraphMarkovChain <T> left, NGramGraphMarkovChain <T> right, NGramGraphDistanceType type = NGramGraphDistanceType.CompleteGraph)
{
left.NullCheck();
right.NullCheck();
switch (type)
{
case NGramGraphDistanceType.CompleteGraph:
return((this.DistanceCompleteWithRespectToLeft(left, right) + this.DistanceCompleteWithRespectToLeft(right, left)) / 2F);
case NGramGraphDistanceType.SubGraph:
if (left.Count() > right.Count())
{
return(this.DistanceCompleteWithRespectToLeft(right, left));
}
return(this.DistanceCompleteWithRespectToLeft(left, right));
}
throw new NotImplementedException();
}
public void LoadGraph(NGramGraphMarkovChain <T> graph)
{
graph.NullCheck();
this.Graph = graph;
}