/**
* Construct a network analyze class. Analyze the specified network.
*
* @param network The network to analyze.
*/
public AnalyzeNetwork(final BasicNetwork network) {
final int assignDisabled = 0;
final int assignedTotal = 0;
final List<Double> biasList = new ArrayList<Double>();
final List<Double> weightList = new ArrayList<Double>();
final List<Double> allList = new ArrayList<Double>();
for (int layerNumber = 0; layerNumber < network.getLayerCount() - 1; layerNumber++) {
final int fromCount = network.getLayerNeuronCount(layerNumber);
final int fromBiasCount = network.getLayerTotalNeuronCount(layerNumber);
final int toCount = network.getLayerNeuronCount(layerNumber + 1);
// weights
for (int fromNeuron = 0; fromNeuron < fromCount; fromNeuron++) {
for (int toNeuron = 0; toNeuron < toCount; toNeuron++) {
final double v = network.getWeight(layerNumber, fromNeuron, toNeuron);
weightList.add(v);
allList.add(v);
}
}
// bias
if (fromCount != fromBiasCount) {
final int biasNeuron = fromCount;
for (int toNeuron = 0; toNeuron < toCount; toNeuron++) {
final double v = network.getWeight(layerNumber, biasNeuron, toNeuron);
biasList.add(v);
allList.add(v);
}
}
}
for (final Layer layer : network.getStructure().getLayers()) {
if (layer.hasBias()) {
for (int i = 0; i < layer.getNeuronCount(); i++) {}
}
}
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);
}
