public override Neuron NameCopy()
{
InputNeuron clone = new InputNeuron();
clone.SetName(GetName());
return(clone);
}
public void AddInputNeuronAndMesh(InputNeuron neuron)
{
InputNeurons.Add(neuron);
foreach (WorkingNeuron wn in FirstHiddenLayer)
{
wn.AddNeuronConnection(new Connection(neuron, 0));
}
}
public void AddInputNeuronAndMesh(InputNeuron neuron)
{
inputNeurons.Add(neuron);
foreach (WorkingNeuron wn in hiddenNeurons)
{
wn.AddNeuronConnection(new Connection(neuron, 0));
}
}
public void Deserialize(BinaryReader reader)
{
fullMeshGenerated = reader.ReadBoolean();
int inputCount = reader.ReadInt32();
for (int currentIndex = 0; currentIndex < inputCount; currentIndex++)
{
InputNeuron newNeuron = new InputNeuron();
newNeuron.Deserialize(reader);
inputNeurons.Add(newNeuron);
}
int hiddenCount = reader.ReadInt32();
for (int currentIndex = 0; currentIndex < hiddenCount; currentIndex++)
{
WorkingNeuron newNeuron = new WorkingNeuron();
newNeuron.Deserialize(reader);
hiddenNeurons.Add(newNeuron);
int connectionCount = reader.ReadInt32();
for (int connectionIndex = 0; connectionIndex < connectionCount; connectionIndex++)
{
// Todo get rid of this covariance cast
Connection connection = Connection.Deserialize(reader, inputNeurons.Cast <Neuron>());
newNeuron.AddNeuronConnection(connection);
}
}
int outputCount = reader.ReadInt32();
for (int currentIndex = 0; currentIndex < outputCount; currentIndex++)
{
WorkingNeuron newNeuron = new WorkingNeuron();
newNeuron.Deserialize(reader);
outputNeurons.Add(newNeuron);
int connectionCount = reader.ReadInt32();
for (int connectionIndex = 0; connectionIndex < connectionCount; connectionIndex++)
{
// Todo get rid of this covariance cast
Connection connection = Connection.Deserialize(reader, hiddenNeurons.Cast <Neuron>());
newNeuron.AddNeuronConnection(connection);
}
}
Invalidate();
}
public void RemoveInputNeuron(InputNeuron neuron)
{
InputNeurons.Remove(neuron);
foreach (WorkingNeuron wn in neurons[1])
{
List <Connection> connectionsToRemove = new List <Connection>();
foreach (Connection c in wn.GetConnections())
{
if (c.entryNeuron == neuron)
{
connectionsToRemove.Add(c);
}
}
foreach (Connection c in connectionsToRemove)
{
wn.GetConnections().Remove(c);
}
}
}
public static void Test()
{
Console.WriteLine("Begin NN Test!");
NeuronalNetwork nn = new NeuronalNetwork();
InputNeuron in1 = new InputNeuron();
InputNeuron in2 = new InputNeuron();
InputNeuron in3 = new InputNeuron();
WorkingNeuron out1 = new WorkingNeuron(0);
WorkingNeuron out2 = new WorkingNeuron(0);
WorkingNeuron out3 = new WorkingNeuron(0);
nn.AddInputNeuron(in1);
nn.AddInputNeuron(in2);
nn.AddInputNeuron(in3);
nn.GenerateHiddenNeurons(3, 1);
nn.AddOutputNeuron(out1);
nn.AddOutputNeuron(out2);
nn.AddOutputNeuron(out3);
nn.GenerateFullMesh();
nn.RandomizeAllWeights();
NeuronalNetwork nn2 = nn.CloneFullMesh();
for (int i = 0; i < 3; i++)
{
Debug.Assert(nn2.GetOutputNeuronFromIndex(i).GetValue() == nn.GetOutputNeuronFromIndex(i).GetValue());
}
Console.WriteLine("NN Test success! <(^.^)>");
}
public void AddInputNeuron(InputNeuron neuron)
{
inputNeurons.Add(neuron);
}
