public float queryCPPNWeight(float x1, float y1, float x2, float y2)
{
coordinates[0] = x1;
coordinates[1] = y1;
coordinates[2] = x2;
coordinates[3] = y2;
genome.ClearSignals();
genome.SetInputSignals(coordinates);
genome.RecursiveActivation();
return(genome.GetOutputSignal(0));
}
public float queryCPPN(float x1, float y1, float x2, float y2, out float thrs)
{
coordinates[0] = x1;
coordinates[1] = y1;
coordinates[2] = x2;
coordinates[3] = y2;
genome.ClearSignals();
genome.SetInputSignals(coordinates);
genome.RecursiveActivation();
//genome.MultipleSteps(NETWORK_ITERATIONS); //TODO query CPPN based on depth
thrs = 0.0f;
return(genome.GetOutputSignal(0)); //use weight
}
float[] queryCPPNOutputs(ModularNetwork genome, float x1, float y1, float x2, float y2, float maxXDist, float minYDist)
{
float[] coordinates = new float[genome.InputNeuronCount];
coordinates[0] = x1;
coordinates[1] = y1;
coordinates[2] = x2;
coordinates[3] = y2;
//coordinates[4] = maxXDist;
//coordinates[5] = minYDist;
//Console.WriteLine("Coordinates: ({0}, {1} : {2}, {3})", x1, y1, x2, y2);
genome.ClearSignals();
genome.SetInputSignals(coordinates);
genome.RecursiveActivation();
float[] outs = new float[genome.OutputNeuronCount];
for (int i = 0; i < genome.OutputNeuronCount; i++)
{
outs[i] = genome.GetOutputSignal(i);
}
return(outs);
}