private void populateNeuralNet(ArrayList Structure, float [] Weights, float [] Biases)
{
//short[] neurons = structure;
net.initNeuralNet(Structure);
float[] w = Weights;
// create links
int totalLinks = 0;
// calculate total number of links
for (int i = 0; i < Structure.Count - 1; i++)
{
totalLinks += ((short[, ])(Structure[i]))[0, 0] * ((short[, ])(Structure[i + 1]))[0, 0];
}
// initialize WeightsCollection
WeightsMatrix weights = new WeightsMatrix(totalLinks);
for (int i = 0; i < totalLinks; i++)
{
weights.addWeight(w[i], i);
}
// initialize Links
int linkcount = 0;
for (short layerCount = 0; layerCount + 1 < Structure.Count; layerCount++)
{
// get adjacent layers
NeuralNet.Layer layerOne = net.getLayer(layerCount);
NeuralNet.Layer layerTwo = net.getLayer(layerCount + 1);
// traverse nerons of second layer
for (int toNeuronCount = 0; toNeuronCount < layerTwo.getNeuronCount(); toNeuronCount++)
{
// traverse all neurons of first layer
for (int fromNeuronCount = 0; fromNeuronCount < layerOne.getNeuronCount(); fromNeuronCount++)
{
// create a link
NeuralNet.Link link = new NeuralNet.Link(layerOne.getNeuron(fromNeuronCount), layerTwo.getNeuron(toNeuronCount));
link.setWeight(weights.getWeight(linkcount++));
}
}
}
// biases
float[] biases = Biases;
// initialize neurons with biases
int count = 0;
for (short layerCount = 1; layerCount < net.layers.Count; layerCount++)
{
for (int neuronCount = 0; neuronCount < net.getLayer(layerCount).getNeuronCount(); neuronCount++)
{
net.getLayer(layerCount).getNeuron(neuronCount).setBias(biases[count++]);
}
}
}
ArrayList fromLinks; // coming in
public void addFromLink(NeuralNet.Link fromlink)
{
fromLinks.Add(fromlink);
}
ArrayList toLinks; // going out
public void addToLink(NeuralNet.Link tolink)
{
toLinks.Add(tolink);
}