public void Calculate()
{
for (int layer = 0; layer < TotalLayers; layer++)
{
Neurons.FindAll(n => n.NetworkLevel == layer).ForEach(n => n.Calculate());
}
}
private void WireUpInputNeuronValuePointersToInputBuffer()
{
Neurons.FindAll(n => n.NetworkLevel == 0).ForEach(n =>
{
n.InputValues.Add(nameof(InputBuffer.DealerValueShowing), latestInput.DealerValueShowing);
n.InputValues.Add(nameof(InputBuffer.PlayerPointsShowing), latestInput.PlayerPointsShowing);
n.InputValues.Add(nameof(InputBuffer.Softness), latestInput.Softness);
});
}
public void WireUpOutputNeuronOutputPointersToOutputBuffer()
{
var fields = typeof(OutputBuffer).GetFields().ToList();
List <Neuron> outputNeurons = Neurons.FindAll(n => n.NetworkLevel == TotalLayers - 1);
for (int i = 0; i < fields.Count; i++)
{
fields[i].SetValue(latestOutput, outputNeurons[i].OutputPointer);
}
}
private void WireUpNeuronInputsToPreviousLayerOutputPointers()
{
for (int layer = 1; layer < TotalLayers; layer++)
{
List <Neuron> previousLayer = Neurons.FindAll(n => n.NetworkLevel == layer - 1);
List <Neuron> currentLayer = Neurons.FindAll(n => n.NetworkLevel == layer);
currentLayer.ForEach(n =>
{
previousLayer.ForEach(p =>
{
n.InputValues.Add(p.ID.ToString(), p.OutputPointer);
});
});
}
}
