public static Connection Create(double weight, Node fromNode, Node toNode)
{
var con = new Connection(weight, fromNode, toNode);
fromNode.AddOutgoingConnection(con);
toNode.AddIncommingConnection(con);
return con;
}
public void FillNetwork(int nrInputs, int nrOutputs, params int[] hiddenLayerHeights)
{
//Creation of outputs is similar to creating hidden layers
var nonInputLayers = hiddenLayerHeights.ToList();
nonInputLayers.Add(nrOutputs);
//Init array
Nodes = new Node[nonInputLayers.Count + 1][];
//Inputs
Nodes[0] = CreateInputs(nrInputs).ToArray();
//Hidden & out
for(int layerIndex = 1; layerIndex <= nonInputLayers.Count; layerIndex++) {
int height = nonInputLayers[layerIndex - 1];
var curLayer = new List<Perceptron>(height);
for(int percNr = 0; percNr < height; percNr++) {
//Create perceptron
string name = layerIndex == Nodes.Length - 1 ? $"Output {percNr}" : $"Hidden #{layerIndex - 1}.{percNr}";
var newPerceptron = new Perceptron(TransferFunction, name);
//Create input connections
foreach(var inp in Nodes[layerIndex - 1]) {
double weight = 0;
if(layerIndex - 1 == 0) { //Input --> 1st hidden
weight = MathHelper.GuassianRandom(Math.Sqrt(1.0 / 3.0), 0);
}
Connection.Create(weight, inp, newPerceptron);
}
if(Bias != null) {
Connection.Create(0.5, Bias, newPerceptron);
}
curLayer.Add(newPerceptron);
}
Nodes[layerIndex] = curLayer.ToArray();
}
}
private Connection(double weight, Node fromNode, Node toNode)
{
Weight = weight;
FromNode = fromNode;
ToNode = toNode;
}
