/// <summary>
/// compare the fitnesses of the two networks, save the best genes
/// </summary>
private void CalculateFitness()
{
fitnessSum = 0;
DNA best = Population[0];
for (int i = 0; i < Population.Count; i++)
{
fitnessSum += Population[i].CalculateFitness(i);
if (Generation > 1 && Population[i].Fitness >= 0 && !float.IsNaN(Population[i].Fitness) && !Population[i].Equals(null) && Generation > 1 && Population[i].Fitness <= 1)
{
Console.WriteLine("Current Fitness: {0},", Population[i].Fitness);
FitnessList.Add(Population[i].Fitness);
}
if (Population[i].Fitness >= best.Fitness && Generation > 1)
{
best = Population[i];
best.Genes.minifiedPrint();
best.Genes.OutputSet.ForEach(x => Console.Write("{0}\t", x));
Console.WriteLine("\nCurrent best fitness: {0}", best.Fitness);
// FitnessList.Add(best.Fitness);
}
}
BestFitness = best.Fitness;
BestGenes = ReflectionCloner.DeepFieldClone(best.Genes);
}
/// <summary>
/// Execute a step in the network
/// </summary>
/// <param name="networkRef">Network which will be executed</param>
public void Spike(Network networkRef)
{
/*
* Run through removing all of the spikes and recording an output
* then run through adding all of the spikes that are recorded to have a spike go out to their network
* Check if each spike sends spike across all axons or if it determines which to go through randomly.
* Add needs to be done on a copy of the network BEFORE the removal happens (original network)
*/
List <Neuron> NeuronCopy = new List <Neuron>(this.Neurons);
List <Neuron> NeuronAdditionCopy = ReflectionCloner.DeepFieldClone(this.Neurons);
Parallel.ForEach(NeuronCopy, neuron =>
{
if (neuron.RemoveSpikes(networkRef) == true)
{
if (neuron.IsOutput == true && this.IsEngaged == true)
{
this.OutputSet.Add(++this.CurrentOutput);
this.IsClear = true;
}
else if (neuron.IsOutput == true && this.IsEngaged == false)
{
this.IsEngaged = true;
}
}
else
{
if (neuron.IsOutput == true)
{
this.CurrentOutput++;
}
}
});
Parallel.ForEach(NeuronAdditionCopy, neuron =>
{
if (neuron.ActiveDelay == 0)
{
neuron.FireSpike(networkRef, neuron.Connections);
}
});
this.GlobalTimer++;
}
public object Reflection()
{
return(ReflectionCloner.Copy(Original));
}
