public NeatBrainGenotype(NeatBrainGenotype other)
{
// Node name map does not need copying as it should remain the same between different genomes
this.NodeNameMap = other.NodeNameMap;
// The genome lists do need to be copied as we can end up doing mutable operations to them
this.ConnectionGenes = other.ConnectionGenes.ConvertAll(connectionGene => (ConnectionGene)connectionGene.Clone());
this.NodeGenes = other.NodeGenes.ConvertAll(nodeGene => (NodeGene)nodeGene.Clone());
}
/// <summary>
/// Compare the connection genes of this genotype to those of another.
///
/// </summary>
/// <param name="other"></param>
/// <returns>(Disjoint, excess, average weight difference)</returns>
public (int, int, double) CompareConnectionGenes(NeatBrainGenotype other)
{
// Calculate number of similar genes
int thisGenesCount = this.ConnectionGenes.Count;
int otherGenesCount = other.ConnectionGenes.Count;
int thisIndex = 0;
int otherIndex = 0;
int totalDisjointGenes = 0;
double totalWeightDiff = 0;
int totalSharedConnections = 0;
while (thisIndex < thisGenesCount && otherIndex < otherGenesCount)
{
ConnectionGene thisGene = this.ConnectionGenes[thisIndex];
ConnectionGene otherGene = other.ConnectionGenes[otherIndex];
if (thisGene.InnovationId == otherGene.InnovationId)
{
// genes match, progress both pointers
thisIndex += 1;
otherIndex += 1;
totalWeightDiff += Math.Abs(thisGene.Weight - otherGene.Weight);
totalSharedConnections += 1;
continue;
}
else if (thisGene.InnovationId > otherGene.InnovationId)
{
// If the thisGene (top genome) has a larger innovation number
// Progress otherIndex counter
otherIndex += 1;
totalDisjointGenes += 1;
continue;
}
// This will always happen, because otherGene.InnovationId must be larger if it is not equal or smaller to thisGene.InnovationId
else
{
// thisGene.innov_id < otherGene.innov_id
// If the otherGene (bottom genome) has a larger innovation number
// progress thisGene counter
thisIndex += 1;
totalDisjointGenes += 1;
continue;
}
}
// Once we've got here we know some of the genes don't match so lets count them
int totalExcessGenes = (thisGenesCount - (thisIndex + 1)) + (otherGenesCount - (otherIndex + 1));
// Max(1,...) to avoid divide by 0
return(totalDisjointGenes, totalExcessGenes, totalWeightDiff / Math.Max(1, totalSharedConnections));
}