public Network(byte[] genes) : base(genes)
{
_genePointer = 0;
inputLayer = new Node[4];
hiddenLayer = new Node[5];
outputLayer = new Node[3];
connections = new List <Connection>();
for (int i = 0; i < inputLayer.Length; i++)
{
inputLayer[i] = new InputNode(this);
}
for (int i = 0; i < hiddenLayer.Length; i++)
{
hiddenLayer[i] = new Node(this);
}
for (int i = 0; i < outputLayer.Length; i++)
{
outputLayer[i] = new Node(this);
}
ConnectLayers();
}
public FeedForwardNet(ref FeedForwardNet copyNet)
{
AbstractNode abNode;
InputNode inNode = copyNet.InputNode;
this.InputNode = new InputNode(ref inNode);
abNode = (AbstractNode)this.InputNode;
//original layer
LayerOfNeurons curOrgLayer = (LayerOfNeurons)inNode.OutputNode;
//copy layer
LayerOfNeurons curCpyLayer = new LayerOfNeurons(ref curOrgLayer, ref abNode);
while (curOrgLayer.OutputNode.GetType() == typeof(LayerOfNeurons))
{
curOrgLayer = (LayerOfNeurons)curOrgLayer.OutputNode;
abNode = (AbstractNode)curCpyLayer;
curCpyLayer = new LayerOfNeurons(ref curOrgLayer, ref abNode);
}
abNode = (AbstractNode)curCpyLayer;
this.OutputNode = new OutputNode(ref abNode);
}
private void CreateBias()
{
Bias = new InputNode(Host);
Bias.SetValue(1.0);
Bias.ConnectTo(this, Host.GetNextGene());
}
