public NeuralNetwork DoSexyTimeWith(NeuralNetwork other)
{
if (Array.Equals(other.Layers, Layers))
{
NeuralNetwork newNet = new NeuralNetwork(Layers, activationFunction);
for (int layer = Layers.Length - 2; layer >= 0; layer--)
{
for (int neuron = Layers[layer + 1] - 1; neuron >= 0; neuron--)
{
double[] factors = calculatedNeurons[layer][neuron].GetFactors();
double[] otherFactors = other.calculatedNeurons[layer][neuron].GetFactors();
for (int i = 0; i < factors.Length; i++)
{
if (RandomValues.RandomDouble() > 0.5)
{
factors[i] = otherFactors[i];
}
else if (RandomValues.RandomDouble() <= 0.25)
{
factors[i] = (otherFactors[i] + factors[i]) / 2.0;
}
}
newNet.calculatedNeurons[layer][neuron].SetFactors(factors);
}
}
return(newNet);
}
else
{
throw new ArgumentException("Cannot breed between different networks");
}
}
private void CreateLayers(int[] layers)
{
this.Layers = layers;
List <Neuron> lastLayer = new List <Neuron>();
for (int i = 0; i < layers.Length; i++)
{
List <Neuron> currentLayer = new List <Neuron>();
if (i == 0)
{
for (int i2 = 0; i2 < layers[i]; i2++)
{
inputNeurons.Add(new InputNeuron());
}
currentLayer.AddRange(inputNeurons);
}
else
{
for (int i2 = 0; i2 < layers[i]; i2++)
{
CalculatedNeuron neuron = new CalculatedNeuron(activationFunction);
foreach (Neuron lastNeuron in lastLayer)
{
neuron.AddConnection(new NeuronConnection(lastNeuron, RandomValues.RandomDouble().Map(0, 1, -1, 1)));
}
currentLayer.Add(neuron);
}
calculatedNeurons.Add(currentLayer.Cast <CalculatedNeuron>().ToArray());
}
lastLayer = currentLayer;
}
}
double[] RandomDoubles()
{
double[] inp = new double[evolver.InputCount];
for (int i = 0; i < inp.Length; i++)
{
inp[i] = RandomValues.RandomDouble() > 0.5 ? 1 : 0;
}
return(inp);
}
public void Mutate(double probability, double factor)
{
calculatedNeurons.SelectMany(n => n).ToList().ForEach(n =>
{
n.NeuronConnections.ToList().ForEach(c =>
{
double val = RandomValues.RandomDouble();
if (val <= probability / 2)
{
double mutationFactor = 1 + factor * RandomValues.RandomDouble().Map(0, 1, -1, 1);
c.factor = c.factor * mutationFactor;
}
else if (val <= probability)
{
double mutationFactor = factor * RandomValues.RandomDouble().Map(0, 1, -1, 1);
c.factor = c.factor + mutationFactor;
}
});
});
}
