public WeightSynapse(INeuron presynapticneuron, double weight)
{
this.id = Guid.NewGuid();
this.presynapticneuron = presynapticneuron;
this.weight = weight;
type = SynapseType.WeightSynapse;
}
/// <summary>
/// Add a layer to the neural network. If there are no layers added this
/// layer will become the input layer. This function automatically updates
/// both the input and output layer references.
/// </summary>
/// <param name="layer">The layer to be added to the network.</param>
/// <param name="type">What sort of synapse should connect this layer to the last.</param>
public void AddLayer(ILayer layer, SynapseType type)
{
// is this the first layer? If so, mark as the input layer.
if (this.layerTags.Count == 0)
{
this.TagLayer(BasicNetwork.TAG_INPUT, layer);
this.TagLayer(BasicNetwork.TAG_OUTPUT, layer);
}
else
{
// add the layer to any previous layers
ILayer outputLayer = this.GetLayer(BasicNetwork.TAG_OUTPUT);
outputLayer.AddNext(layer, type);
this.TagLayer(BasicNetwork.TAG_OUTPUT, layer);
}
}
/// <summary>
/// Add a "next" layer.
/// </summary>
/// <param name="next">The next layer to add.</param>
/// <param name="type">The synapse type to use for this layer.</param>
public void AddNext(ILayer next, SynapseType type)
{
ISynapse synapse = null;
switch (type)
{
case SynapseType.OneToOne:
synapse = new OneToOneSynapse(this, next);
break;
case SynapseType.Weighted:
synapse = new WeightedSynapse(this, next);
break;
case SynapseType.Weightless:
synapse = new WeightlessSynapse(this, next);
break;
case SynapseType.Direct:
synapse = new DirectSynapse(this, next);
break;
case SynapseType.NEAT:
synapse = new NEATSynapse(this, next);
break;
default:
throw new NeuralNetworkError("Unknown synapse type");
}
if (synapse == null)
{
String str = "Unknown synapse type.";
#if logging
if (BasicLayer.logger.IsErrorEnabled)
{
BasicLayer.logger.Error(str);
}
#endif
throw new NeuralNetworkError(str);
}
else
{
this.next.Add(synapse);
}
}
/// <summary>
/// Add a layer to the neural network. If there are no layers added this
/// layer will become the input layer. This function automatically updates
/// both the input and output layer references.
/// </summary>
/// <param name="layer">The layer to be added to the network.</param>
/// <param name="type">What sort of synapse should connect this layer to the last.</param>
public void AddLayer(ILayer layer, SynapseType type)
{
// is this the first layer? If so, mark as the input layer.
if (this.layerTags.Count == 0)
{
this.TagLayer(BasicNetwork.TAG_INPUT, layer);
this.TagLayer(BasicNetwork.TAG_OUTPUT, layer);
}
else
{
// add the layer to any previous layers
ILayer outputLayer = this.GetLayer(BasicNetwork.TAG_OUTPUT);
outputLayer.AddNext(layer, type);
this.TagLayer(BasicNetwork.TAG_OUTPUT, layer);
}
}
/// <summary>
/// Add a "next" layer.
/// </summary>
/// <param name="next">The next layer to add.</param>
/// <param name="type">The synapse type to use for this layer.</param>
public void AddNext(ILayer next, SynapseType type)
{
ISynapse synapse = null;
switch (type)
{
case SynapseType.OneToOne:
synapse = new OneToOneSynapse(this, next);
break;
case SynapseType.Weighted:
synapse = new WeightedSynapse(this, next);
break;
case SynapseType.Weightless:
synapse = new WeightlessSynapse(this, next);
break;
case SynapseType.Direct:
synapse = new DirectSynapse(this, next);
break;
case SynapseType.NEAT:
synapse = new NEATSynapse(this, next);
break;
default:
throw new NeuralNetworkError("Unknown synapse type");
}
if (synapse == null)
{
String str = "Unknown synapse type.";
#if logging
if (BasicLayer.logger.IsErrorEnabled)
{
BasicLayer.logger.Error(str);
}
#endif
throw new NeuralNetworkError(str);
}
else
{
this.next.Add(synapse);
}
}
