public ArrayList Evaluate(ArrayList ANNInput)
{
ArrayList ANNOutput = new ArrayList();
for (int layer = 0; layer < Layers; layer++)
{
for (int neuron = 0; neuron < NeuronsPerLayer[layer]; neuron++)
{
int neuronindex = NeuronIndex(layer, neuron);
if (layer == 0)
{
sNeuron Neuron = ((sNeuron)Neurons[neuronindex]);
Neuron.Value = ((double)ANNInput[neuronindex]) + Neuron.Bias;
Neuron.Output = ActivationFn(Neuron.Value, ActivationFunction[layer]);
Neurons[neuronindex] = Neuron;
}
else
{
double sum = 0;
for (int neuron0 = 0; neuron0 < NeuronsPerLayer[layer - 1]; neuron0++)
{
int n0index = NeuronIndex(layer - 1, neuron0);
int weigthindex = WeigthIndex(layer - 1, neuron0, neuron);
sum += ((sNeuron)Neurons[n0index]).Output * ((double)Weigths[weigthindex]);
}
sNeuron Neuron = ((sNeuron)Neurons[neuronindex]);
Neuron.Value = sum + Neuron.Bias;
Neuron.Output = ActivationFn(Neuron.Value, ActivationFunction[layer]);
Neurons[neuronindex] = Neuron;
if (layer == (Layers - 1))
{
ANNOutput.Add(((sNeuron)Neurons[neuronindex]).Output);
}
}
}
}
return(ANNOutput);
}
public oANN(string pFileName)
{
int linenumber = 0;
System.IO.TextReader tr = null;
String line;
ArrayList Parameters = new ArrayList();
NeuronsPerLayer = new int[5];
ActivationFunction = new int[5];
AFParameters = new int[20];
Neurons = new ArrayList();
Weigths = new ArrayList();
// how to code this differently with a FSM?
try
{
tr = new System.IO.StreamReader(pFileName);
while ((line = tr.ReadLine()) != null)
{
Parameters.Add(double.Parse(line));
linenumber++;
}
tr.Close();
for (int i = 0; i < 20; i++)
{
AFParameters[i] = (int)((double)Parameters[i]);
}
for (int i = 0; i < 5; i++)
{
NeuronsPerLayer[i] = (int)((double)Parameters[20 + i]);
}
int NumBiases = NeuronsPerLayer[0] + NeuronsPerLayer[1]
+ NeuronsPerLayer[2] + NeuronsPerLayer[3]
+ NeuronsPerLayer[4];
int NumWeigths = (NeuronsPerLayer[0] * NeuronsPerLayer[1])
+ (NeuronsPerLayer[1] * NeuronsPerLayer[2])
+ (NeuronsPerLayer[3] * NeuronsPerLayer[4]);
Layers = 5;
if (NeuronsPerLayer[4] == 0)
{
Layers = 4;
}
if (NeuronsPerLayer[3] == 0)
{
Layers = 3;
}
if (NeuronsPerLayer[2] == 0)
{
Layers = 2;
}
if (NeuronsPerLayer[1] == 0)
{
Layers = 1;
}
for (int i = 0; i < 5; i++)
{
ActivationFunction[i] = (int)((double)Parameters[25 + i]);
}
for (int i = 0; i < NumBiases; i++)
{
sNeuron Neuron = new sNeuron();
Neuron.Bias = (double)Parameters[30 + i];
Neuron.Value = 0;
Neuron.Output = 0;
Neurons.Add(Neuron);
}
for (int i = 0; i < NumWeigths; i++)
{
Weigths.Add(Parameters[30 + NumBiases + i]);
}
}
catch (Exception exc)
{
linenumber = 0;
Framework.Logger(99, "An error ocurred: " + exc.Message);
}
finally
{
if (tr != null)
{
tr.Close();
}
}
}