/// <summary>
/// Set the networks current training data
/// </summary>
/// <remarks>
/// Teh traing data should have the same order as teh output data it corilates to.
/// </remarks>
/// <param name="TrainingToSet">Trainging data</param>
public void SetTraining(double[] TrainingToSet)
{
IEnumerator NeuronEnum = this.NeuronsOwned.GetEnumerator();
int Lcv = 0;
while ((NeuronEnum.MoveNext()) && (TrainingToSet.Length > Lcv))
{
if (NeuronEnum.Current is OutputNeuron)
{
OutputNeuron CurrentNeuron = NeuronEnum.Current as OutputNeuron;
CurrentNeuron.SetTrainingData(TrainingToSet[Lcv]);
}
else
{
throw new Exception("NeuronsOwned should only contain OutputNeuron");
}
Lcv++;
}
}
protected Brain(SerializationInfo info, StreamingContext context)
{
//Get brains attributes
this.LayerCount = info.GetInt32("LayerCount");
// Input layer and output layer must be set later
//Get all the layers
Layer LastLayer = null;
for (int LayerLcv = this.LayerCount - 1; LayerLcv >= 0; LayerLcv--)
{
string LayerIdName = "Layer" + LayerLcv;
uint LayerUid = info.GetUInt32(LayerIdName + "Uid");
bool UseByteRes = info.GetBoolean(LayerIdName + "UseByteRes");
bool IsInput = info.GetBoolean(LayerIdName + "IsInput");
bool IsOutput = info.GetBoolean(LayerIdName + "IsOutput");
int NeuronCount = info.GetInt32(LayerIdName + "NeuronCount");
if (IsInput)
{
Layer NewLayer = new InputLayer(this, UseByteRes, LayerUid);
this.InLayer = (NewLayer as InputLayer);
NewLayer.DestinationLayer = LastLayer;
LastLayer.SourceLayer = NewLayer;
LastLayer = NewLayer;
}
else if (IsOutput)
{
LastLayer = new OutputLayer(this, UseByteRes, LayerUid);
this.OutLayer = (LastLayer as OutputLayer);
}
else
{
Layer NewLayer = new Layer(this, UseByteRes, LayerUid);
NewLayer.DestinationLayer = LastLayer;
LastLayer.SourceLayer = NewLayer;
LastLayer = NewLayer;
}
//Get all of this layers neurons
for (int NeuronLcv = 0; NeuronLcv < NeuronCount; NeuronLcv++)
{
string NeuronIdName = LayerIdName + "Neuron" + NeuronLcv;
double BiasWeight = info.GetDouble(NeuronIdName + "BiasWeight");
bool UseByte = info.GetBoolean(NeuronIdName + "UseByteResolution");
int OutConCount = info.GetInt32(NeuronIdName + "OutConCount");
uint NeuronUid = info.GetUInt32(NeuronIdName + "Uid");
Neuron NewNeuron = null;
if (IsInput)
{
NewNeuron = new InputNeuron(LastLayer, UseByte, BiasWeight, NeuronUid);
}
else if (IsOutput)
{
NewNeuron = new OutputNeuron(LastLayer, UseByte, BiasWeight, NeuronUid);
}
else
{
NewNeuron = new Neuron(LastLayer, UseByte, BiasWeight, NeuronUid);
}
LastLayer.AddNeuron(NewNeuron);
//Connect the new neuron to all its destinations
for (int SynapseLcv = 0; SynapseLcv < OutConCount; SynapseLcv++)
{
string SynapseIdName = NeuronIdName + "Synapse" + SynapseLcv;
uint ToUid = info.GetUInt32(SynapseIdName + "ToUid");
double Weight = info.GetDouble(SynapseIdName + "Weight");
Neuron ToConnectTo = this.FindNeuron(LastLayer, ToUid);
NewNeuron.ConnectToNeuron(ToConnectTo, Weight);
}
}
}
}
