public void InitBrain(BrainConfiguration configuration)
{
Brain = new Brain();
Brain.InitBrain(configuration);
BrainControl.Brain = Brain;
//BrainCharts.Brain = Brain;
}
//[JsonRequired]
//public BrainConfiguration Configuration { get; set; }
public void InitLayers(BrainConfiguration configuration)
{
//Configuration = configuration;
foreach (IBrainLayer layer in this)
{
layer.InitLayer(configuration);
layer.InitFiredNeurons();
}
globals.CachedNeuronCount = HiddenLayers.Sum(l => l.Count);
}
public override void AfterDeserialization(BrainConfiguration configuration)
{
base.AfterDeserialization(configuration);
for (int i = 0; i < configuration.NumInputClasses; i++)
{
List <Neuron> NeuronClass = new List <Neuron> ();
Classes.Add(NeuronClass);
for (int k = 0; k < configuration.NumInputClassNeurons; k++)
{
Neuron n = m_Neurons[(i * configuration.NumInputClassNeurons) + k];
NeuronClass.Add(n);
}
}
}
public override void InitLayer(BrainConfiguration configuration)
{
for (int i = 0; i < configuration.NumInputClasses; i++)
{
List <Neuron> NeuronClass = new List <Neuron> ();
Classes.Add(NeuronClass);
for (int k = 0; k < configuration.NumInputClassNeurons; k++)
{
Neuron n = new Neuron(LayerIndex, i, configuration.NumInputClasses, NeuronTypes.Perceptron, ConnectionTypes.None);
m_Neurons.Add(n);
NeuronClass.Add(n);
}
}
}
public override void InitLayer(BrainConfiguration configuration)
{
for (int i = 0; i < configuration.NumOutputClasses; i++)
{
List <Neuron> NeuronClass = new List <Neuron> ();
Classes.Add(NeuronClass);
for (int k = 0; k < configuration.NumOutputClassNeurons; k++)
{
int length = (int)(ThreadSafeRandom.NextDouble() * configuration.NumInputClasses) + 1;
Neuron n = new Neuron(LayerIndex, i, length, NeuronTypes.MirrorNeuron, ConnectionTypes.PreviousLayer, configuration.OutputLayerMaxSynapses);
m_Neurons.Add(n);
NeuronClass.Add(n);
}
}
}
public void InitBrain(BrainConfiguration configuration)
{
Configuration = configuration;
int layerIndex = 0;
Layers.Add(new InputLayer(layerIndex++));
for (int i = 0; i < configuration.NumHiddenLayers; i++)
{
Layers.Add(new HiddenLayer(layerIndex++));
}
Layers.Add(new OutputLayer(layerIndex++));
Layers.InitLayers(configuration);
CalcConnectionCount();
CalcTotalEmphasis();
}
public override void InitLayer(BrainConfiguration configuration)
{
int neuronsPerColumn = configuration.NeuronsPerHiddenLayer / configuration.NumInputClasses;
for (int i = 0; i < configuration.NumInputClasses; i++)
{
for (int k = 0; k < neuronsPerColumn; k++)
{
int length = (int)(ThreadSafeRandom.NextDouble() * configuration.NumInputClasses) + 1;
m_Neurons.Add(new Neuron(LayerIndex, i, length, NeuronTypes.PyramidCell, ConnectionTypes.LocalLayer, configuration.HiddenLayerMaxSynapses));
m_Neurons.Add(new Neuron(LayerIndex, i, length / 2 + 1, NeuronTypes.Interneuron, ConnectionTypes.LocalLayer, configuration.HiddenLayerMaxSynapses));
}
}
/***
* for (int i = 0; i < configuration.NeuronsPerHiddenLayer; i++) {
* m_Neurons.Add (new Neuron (LayerIndex, NeuronTypes.PyramidCell, ConnectionTypes.LocalLayer, configuration.HiddenLayerMaxSynapses));
* m_Neurons.Add (new Neuron (LayerIndex, NeuronTypes.Interneuron, ConnectionTypes.LocalLayer, configuration.HiddenLayerMaxSynapses));
* }
***/
}
public override void AfterDeserialization(BrainConfiguration configuration)
{
base.AfterDeserialization(configuration);
}
