static public NetworkModel DecodeToNetworkModel(NeatGenome.NeatGenome g)
{
ModelNeuronList masterNeuronList = new ModelNeuronList();
// loop all neurons and build a table keyed on id.
HybridDictionary neuronTable = new HybridDictionary(g.NeuronGeneList.Count);
foreach (NeuronGene neuronGene in g.NeuronGeneList)
{
ModelNeuron modelNeuron = new ModelNeuron(neuronGene.NeuronType, neuronGene.InnovationId, neuronGene.ActivationFunction);
neuronTable.Add(modelNeuron.Id, modelNeuron);
masterNeuronList.Add(modelNeuron);
}
// Loop through all of the connections.
// Now we have a neuron table keyed on id we can attach the connections
// to their source and target neurons.
foreach (ConnectionGene connectionGene in g.ConnectionGeneList)
{
ModelConnection modelConnection = new ModelConnection();
modelConnection.Weight = connectionGene.Weight;
modelConnection.SourceNeuron = (ModelNeuron)neuronTable[connectionGene.SourceNeuronId];
modelConnection.TargetNeuron = (ModelNeuron)neuronTable[connectionGene.TargetNeuronId];
modelConnection.SourceNeuron.OutConnectionList.Add(modelConnection);
modelConnection.TargetNeuron.InConnectionList.Add(modelConnection);
}
return(new NetworkModel(masterNeuronList));
}
static public NetworkModel DecodeToNetworkModel(ConcurrentNetwork network)
{
ModelNeuronList masterNeuronList = new ModelNeuronList();
// loop all neurons and build a table keyed on id.
Hashtable neuronTable = new Hashtable(network.MasterNeuronList.Count);
foreach (Neuron neuron in network.MasterNeuronList)
{
ModelNeuron modelNeuron = new ModelNeuron(neuron.NeuronType, neuron.Id, ActivationFunctionFactory.GetActivationFunction("NullFn"));
neuronTable.Add(modelNeuron.Id, modelNeuron);
masterNeuronList.Add(modelNeuron);
}
// Loop through all of the connections (within the neurons)
// Now we have a neuron table keyed on id we can attach the connections
// to their source and target neurons.
foreach (Neuron neuron in network.MasterNeuronList)
{
foreach (Connection connection in neuron.ConnectionList)
{
ModelConnection modelConnection = new ModelConnection();
modelConnection.Weight = connection.Weight;
modelConnection.SourceNeuron = (ModelNeuron)neuronTable[connection.SourceNeuronId];
modelConnection.TargetNeuron = (ModelNeuron)neuronTable[connection.TargetNeuronId];
modelConnection.SourceNeuron.OutConnectionList.Add(modelConnection);
modelConnection.TargetNeuron.InConnectionList.Add(modelConnection);
}
}
return(new NetworkModel(masterNeuronList));
}
public NetworkModel(ModelNeuronList masterNeuronList)
{
bounds = new Size(0, 0);
this.masterNeuronList = masterNeuronList;
foreach (ModelNeuron modelNeuron in masterNeuronList)
{
// Build the various lists.
switch (modelNeuron.NeuronType)
{
case NeuronType.Bias:
case NeuronType.Input:
inputNeuronList.Add(modelNeuron);
break;
case NeuronType.Hidden:
hiddenNeuronList.Add(modelNeuron);
break;
case NeuronType.Output:
outputNeuronList.Add(modelNeuron);
break;
}
}
}
static public NetworkModel DecodeToNetworkModel(NeatGenome.NeatGenome g)
{
ModelNeuronList masterNeuronList = new ModelNeuronList();
// loop all neurons and build a table keyed on id.
HybridDictionary neuronTable = new HybridDictionary(g.NeuronGeneList.Count);
foreach(NeuronGene neuronGene in g.NeuronGeneList)
{
ModelNeuron modelNeuron = new ModelNeuron(neuronGene.NeuronType, neuronGene.InnovationId,neuronGene.ActivationFunction);
neuronTable.Add(modelNeuron.Id, modelNeuron);
masterNeuronList.Add(modelNeuron);
}
// Loop through all of the connections.
// Now we have a neuron table keyed on id we can attach the connections
// to their source and target neurons.
foreach(ConnectionGene connectionGene in g.ConnectionGeneList)
{
ModelConnection modelConnection = new ModelConnection();
modelConnection.Weight = connectionGene.Weight;
modelConnection.SourceNeuron = (ModelNeuron)neuronTable[connectionGene.SourceNeuronId];
modelConnection.TargetNeuron = (ModelNeuron)neuronTable[connectionGene.TargetNeuronId];
modelConnection.SourceNeuron.OutConnectionList.Add(modelConnection);
modelConnection.TargetNeuron.InConnectionList.Add(modelConnection);
}
//Sebastian. Build Model connections
foreach (ModuleGene mg in g.ModuleGeneList)
{
foreach (uint sourceID in mg.InputIds)
{
foreach (uint targetID in mg.OutputIds)
{
ModelConnection modelConnection = new ModelConnection();
modelConnection.Weight = 1.0; //TODO connectionGene.Weight;
modelConnection.SourceNeuron = (ModelNeuron)neuronTable[sourceID];
modelConnection.TargetNeuron = (ModelNeuron)neuronTable[targetID];
modelConnection.SourceNeuron.OutConnectionList.Add(modelConnection);
modelConnection.TargetNeuron.InConnectionList.Add(modelConnection);
}
}
}
return new NetworkModel(masterNeuronList);
}
static public NetworkModel DecodeToNetworkModel(ConcurrentNetwork network)
{
ModelNeuronList masterNeuronList = new ModelNeuronList();
// loop all neurons and build a table keyed on id.
Hashtable neuronTable = new Hashtable(network.MasterNeuronList.Count);
foreach(Neuron neuron in network.MasterNeuronList)
{
ModelNeuron modelNeuron = new ModelNeuron(neuron.NeuronType, neuron.Id,ActivationFunctionFactory.GetActivationFunction("NullFn"));
neuronTable.Add(modelNeuron.Id, modelNeuron);
masterNeuronList.Add(modelNeuron);
}
// Loop through all of the connections (within the neurons)
// Now we have a neuron table keyed on id we can attach the connections
// to their source and target neurons.
foreach(Neuron neuron in network.MasterNeuronList)
{
foreach(Connection connection in neuron.ConnectionList)
{
ModelConnection modelConnection = new ModelConnection();
modelConnection.Weight = connection.Weight;
modelConnection.SourceNeuron = (ModelNeuron)neuronTable[connection.SourceNeuronId];
modelConnection.TargetNeuron = (ModelNeuron)neuronTable[connection.TargetNeuronId];
modelConnection.SourceNeuron.OutConnectionList.Add(modelConnection);
modelConnection.TargetNeuron.InConnectionList.Add(modelConnection);
}
}
return new NetworkModel(masterNeuronList);
}