/// <summary>
/// Construct a network analyze class. Analyze the specified network.
/// </summary>
/// <param name="network">The network to analyze.</param>
public AnalyzeNetwork(BasicNetwork network)
{
int assignDisabled = 0;
int assignedTotal = 0;
IList <double> biasList = new List <double>();
IList <double> weightList = new List <double>();
IList <double> allList = new List <double>();
foreach (ILayer layer in network.Structure.Layers)
{
if (layer.HasBias)
{
for (int i = 0; i < layer.NeuronCount; i++)
{
biasList.Add(layer.BiasWeights[i]);
allList.Add(layer.BiasWeights[i]);
}
}
}
foreach (ISynapse synapse in network.Structure.Synapses)
{
if (synapse.MatrixSize > 0)
{
for (int from = 0; from < synapse.FromNeuronCount; from++)
{
for (int to = 0; to < synapse.ToNeuronCount; to++)
{
if (network.IsConnected(synapse, from, to))
{
double d = synapse.WeightMatrix[from, to];
weightList.Add(d);
allList.Add(d);
}
else
{
assignDisabled++;
}
assignedTotal++;
}
}
}
}
this.disabledConnections = assignDisabled;
this.totalConnections = assignedTotal;
this.weights = new NumericRange(weightList);
this.bias = new NumericRange(biasList);
this.weightsAndBias = new NumericRange(allList);
this.weightValues = EngineArray.ListToDouble(weightList);
this.allValues = EngineArray.ListToDouble(allList);
this.biasValues = EngineArray.ListToDouble(biasList);
}
/// <summary>
/// Construct a network analyze class. Analyze the specified network.
/// </summary>
///
/// <param name="network">The network to analyze.</param>
public AnalyzeNetwork(BasicNetwork network)
{
int assignDisabled = 0;
int assignedTotal = 0;
IList <Double> biasList = new List <Double>();
IList <Double> weightList = new List <Double>();
IList <Double> allList = new List <Double>();
for (int layerNumber = 0; layerNumber < network.LayerCount - 1; layerNumber++)
{
int fromCount = network.GetLayerNeuronCount(layerNumber);
int fromBiasCount = network
.GetLayerTotalNeuronCount(layerNumber);
int toCount = network.GetLayerNeuronCount(layerNumber + 1);
// weights
for (int fromNeuron = 0; fromNeuron < fromCount; fromNeuron++)
{
for (int toNeuron = 0; toNeuron < toCount; toNeuron++)
{
double v = network.GetWeight(layerNumber, fromNeuron,
toNeuron);
if (network.Structure.ConnectionLimited)
{
if (Math.Abs(v) < network.Structure.ConnectionLimit)
{
assignDisabled++;
}
}
weightList.Add(v);
allList.Add(v);
assignedTotal++;
}
}
// bias
if (fromCount != fromBiasCount)
{
int biasNeuron = fromCount;
for (int toNeuron = 0; toNeuron < toCount; toNeuron++)
{
double v = network.GetWeight(layerNumber, biasNeuron,
toNeuron);
if (network.Structure.ConnectionLimited)
{
if (Math.Abs(v) < network.Structure.ConnectionLimit)
{
assignDisabled++;
}
}
biasList.Add(v);
allList.Add(v);
assignedTotal++;
}
}
}
_disabledConnections = assignDisabled;
_totalConnections = assignedTotal;
_weights = new NumericRange(weightList);
_bias = new NumericRange(biasList);
_weightsAndBias = new NumericRange(allList);
_weightValues = EngineArray.ListToDouble(weightList);
_allValues = EngineArray.ListToDouble(allList);
_biasValues = EngineArray.ListToDouble(biasList);
}