public bool IsConnection(NeuronLocation input, NeuronLocation output)
{
int indexInput = getNeuronIndexInNet(input);
int indexOutput = getNeuronIndexInNet(output);
return(learned_net.ConnectionsOfNeurons[indexOutput, indexInput]);
}
public NeuronLocation[] GetOutputsOfNeuron(NeuronLocation neuronLocation)
{
int indexCurNeuron = getNeuronIndexInNet(neuronLocation);
Neuron neu = getNeuron(neuronLocation);
int k = 0;
for (int i = 0; i < learned_net.NeuronsCount; i++)
{
if (learned_net.ConnectionsOfNeurons[indexCurNeuron, i] == true)
{
k++;
}
}
NeuronLocation[] arr = new NeuronLocation[k];
k = 0;
for (int i = 0; i < learned_net.NeuronsCount; i++)
{
if (learned_net.ConnectionsOfNeurons[indexCurNeuron, i] == true)
{
arr[k] = getNeuronLocation(learned_net.GetNeuron(i));
}
}
return(arr);
}
public void DeleteConnection(NeuronLocation input, NeuronLocation output)
{
int indexIn = getNeuronIndexInNet(input);
int indexOut = getNeuronIndexInNet(output);
learned_net.DeleteConnection(indexIn, indexOut);
}
public double GetConnectionWeight(NeuronLocation input, NeuronLocation output)
{
int indexInput = getNeuronIndexInNet(input);
int indexOutput = getNeuronIndexInNet(output);
return(learned_net.WeightsOfConnections[indexOutput, indexInput]);
}
public void DeleteConnection(NeuronLocation input, NeuronLocation output)
{
int indexIn = getNeuronIndexInNet(input);
int indexOut = getNeuronIndexInNet(output);
learned_net.DeleteConnection(indexIn, indexOut);
}
public Tuple <double, NeuronLocation>[] GetInputsOfNeuronWithWeights(NeuronLocation location)
{
NeuronLocation[] loc = GetInputsOfNeuron(location);
Tuple <double, NeuronLocation>[] res = new Tuple <double, NeuronLocation> [loc.Length];
for (int i = 0; i < loc.Length; i++)
{
res[i] = new Tuple <double, NeuronLocation>(GetConnectionWeight(loc[i], location), loc[i]);
}
return(res);
}
public void ChangeConnectionWeight(NeuronLocation input, NeuronLocation output, double weight)
{
Neuron inp = getNeuron(input);
Neuron oup = getNeuron(output);
if (IsConnection(input, output) == true)
{
int indexOut = getNeuronIndexInNet(output);
inp.SetWeightValue(weight, indexOut);
}
else
{
throw new Exception("Связь между нейронами не найдена");
}
}
public void ChangeConnectionWeight(NeuronLocation input, NeuronLocation output, double weight)
{
Neuron inp = getNeuron(input);
Neuron oup = getNeuron(output);
if (IsConnection(input, output) == true)
{
int indexOut = getNeuronIndexInNet(output);
inp.SetWeightValue(weight, indexOut);
}
else
{
throw new Exception("Связь между нейронами не найдена");
}
}
public void SetNewConnection(NeuronLocation input, NeuronLocation output, double weight)
{
Neuron inp = getNeuron(input);
Neuron oup = getNeuron(output);
if (IsConnection(input, output) == true)
{
throw new Exception("Связь между нейронами уже существует");
}
else
{
int indexIn = getNeuronIndexInNet(input);
int indexOut = getNeuronIndexInNet(output);
learned_net.SetNewConnection(indexIn, indexOut, weight);
}
}
private int getNeuronIndexInNet(NeuronLocation location)
{
if (location.Layer < 1 || location.Layer > learned_net.NeuronsInLayers.GetLength(0))
{
throw new Exception("Invalid index of layer");
}
int index = 0;
for (int i = 0; i < location.Layer - 1; i++)
{
index += learned_net.NeuronsInLayers[i];
}
if (index + location.Number > learned_net.NeuronsCount ||
index + location.Number < 1)
{
throw new Exception("Invalid number of neuron in layer");
}
return(index + location.Number - 1);
}
//TODO:
public string GetNameOfAF(NeuronLocation neuron)
{
return null;
}
public Tuple<double, NeuronLocation>[] GetInputsOfNeuronWithWeights(NeuronLocation location)
{
NeuronLocation[] loc = GetInputsOfNeuron(location);
Tuple<double, NeuronLocation>[] res = new Tuple<double, NeuronLocation>[loc.Length];
for (int i = 0; i < loc.Length; i++)
{
res[i] = new Tuple<double, NeuronLocation>(GetConnectionWeight(loc[i], location), loc[i]);
}
return res;
}
public NeuronLocation[] GetOutputsOfNeuron(NeuronLocation neuronLocation)
{
int indexCurNeuron = getNeuronIndexInNet(neuronLocation);
Neuron neu = getNeuron(neuronLocation);
int k = 0;
for (int i = 0; i < learned_net.NeuronsCount; i++)
{
if (learned_net.ConnectionsOfNeurons[indexCurNeuron, i] == true)
{
k++;
}
}
NeuronLocation[] arr = new NeuronLocation[k];
k = 0;
for (int i = 0; i < learned_net.NeuronsCount; i++)
{
if (learned_net.ConnectionsOfNeurons[indexCurNeuron, i] == true)
{
arr[k] = getNeuronLocation(learned_net.GetNeuron(i));
}
}
return arr;
}
public string[] GetNamesOfParametersAF(NeuronLocation neuron)
{
return null;
}
public string[] GetNamesOfParametersAF(NeuronLocation neuron)
{
return(null);
}
public void SetValueOfParameterAF(NeuronLocation neuron, string parameterName, double value)
{
}
public double GetDerivativeAFValue(NeuronLocation neuron, double x)
{
return -1;
}
public bool HasAFContinuousDerivative(NeuronLocation neuron)
{
return(false);
}
public void SetValueOfParameterAF(NeuronLocation neuron, string parameterName, double value)
{
}
private Neuron getNeuron(NeuronLocation location)
{
return(learned_net.GetNeuron(getNeuronIndexInNet(location)));
}
public bool IsConnection(NeuronLocation input, NeuronLocation output)
{
int indexInput = getNeuronIndexInNet(input);
int indexOutput = getNeuronIndexInNet(output);
return learned_net.ConnectionsOfNeurons[indexOutput, indexInput];
}
private int getNeuronIndexInNet(NeuronLocation location)
{
if (location.Layer < 1 || location.Layer > learned_net.NeuronsInLayers.GetLength(0))
throw new Exception("Invalid index of layer");
int index = 0;
for (int i = 0; i < location.Layer - 1; i++)
{
index += learned_net.NeuronsInLayers[i];
}
if (index + location.Number > learned_net.NeuronsCount ||
index + location.Number < 1)
throw new Exception("Invalid number of neuron in layer");
return index + location.Number - 1;
}
private Neuron getNeuron(NeuronLocation location)
{
return learned_net.GetNeuron(getNeuronIndexInNet(location));
}
public double GetOutputValueOfNeuron(NeuronLocation neuron)
{
return(getNeuron(neuron).OutputValue);
}
public bool HasAFContinuousDerivative(NeuronLocation neuron)
{
return false;
}
//TODO:
public string GetNameOfAF(NeuronLocation neuron)
{
return(null);
}
public double GetValueOfParameterAF(NeuronLocation neuron, string parameterName)
{
return -1;
}
public int GetCountParametersAF(NeuronLocation neuron)
{
return(-1);
}
public double GetOutputValueOfNeuron(NeuronLocation neuron)
{
return getNeuron(neuron).OutputValue;
}
public double GetValueOfParameterAF(NeuronLocation neuron, string parameterName)
{
return(-1);
}
public void SetNewConnection(NeuronLocation input, NeuronLocation output, double weight)
{
Neuron inp = getNeuron(input);
Neuron oup = getNeuron(output);
if (IsConnection(input, output) == true)
{
throw new Exception("Связь между нейронами уже существует");
}
else
{
int indexIn = getNeuronIndexInNet(input);
int indexOut = getNeuronIndexInNet(output);
learned_net.SetNewConnection(indexIn, indexOut, weight);
}
}
public double GetDerivativeAFValue(NeuronLocation neuron, double x)
{
return(-1);
}
public double GetAFValue(NeuronLocation neuron, double x)
{
return -1;
}
public double GetConnectionWeight(NeuronLocation input, NeuronLocation output)
{
int indexInput = getNeuronIndexInNet(input);
int indexOutput = getNeuronIndexInNet(output);
return learned_net.WeightsOfConnections[indexOutput, indexInput];
}
public int GetCountParametersAF(NeuronLocation neuron)
{
return -1;
}
