static void Main()
{
Network xorNet = new Network("res/mininet.txt");
Console.WriteLine(xorNet.output.ToString());
double[][] testMatrix = new double[][]{
new double[] { 0.0, 0.0 },
new double[] { 0.0, 1.0 },
new double[] { 1.0, 0.0 },
new double[] { 1.0, 1.0 }
};
foreach(double[] sample in testMatrix){
xorNet.computeNetwork(sample);
Console.WriteLine(string.Format("Input {0}, output {1}",sample.ToString(), xorNet.output.ToString()));
}
//myANN.doFeedForward();
/*double []v = new double[2];
v[0] = 0;
v[1] = 0;
myANN.computeNetwork(v);
Console.WriteLine(myANN.output.ToString());
* */
Console.Read();
}
public Network(Network n)
{
this.actionList = new List<IAction>();
foreach(IAction ac in n.actionList){
if (ac.GetType() == typeof(Layer))
{
Layer acLayer = (Layer)ac;
Layer aux = new Layer(acLayer);
this.actionList.Add(aux);
if (acLayer == n.input)
{
this.input = aux;
}
else if (acLayer == n.output)
{
this.output = aux;
}
}
else
{
this.actionList.Add(ac);
}
}
}
public static Network fromDescription(string description)
{
Network network = new Network();
string[] desc = description.Split();
int idx = 0;
Layer ant = null;
while (idx < desc.Length)
{
int nNeurons = Int32.Parse(desc[idx++]);
string sAct = desc[idx++];
ActivationFunction fAct = Layer.stringToActivation(sAct);
if (ant == null)
{
network.input = new Layer(nNeurons, fAct);
ant = network.input;
continue;
}
Layer newLayer = new Layer(nNeurons, fAct);
Connections newConnection = new Connections(ant, newLayer);
network.actionList.Add(newConnection);
network.actionList.Add(newLayer);
ant = newLayer;
}
network.output = ant;
return network;
}
