/** Sets default input and output neurons for network (first layer as input, last as output) */
public static void setDefaultIO(NeuralNetwork nnet) {
ArrayList<Neuron> inputNeuronsList = new ArrayList<Neuron>();
Layer firstLayer = nnet.getLayerAt(0);
for (Neuron neuron : firstLayer.getNeurons()) {
if (!(neuron instanceof BiasNeuron)) { // dont set input to bias
// neurons
inputNeuronsList.add(neuron);
}
}
Neuron[] inputNeurons = new Neuron[inputNeuronsList.size()];
inputNeurons = inputNeuronsList.toArray(inputNeurons);
Neuron[] outputNeurons = ((Layer) nnet.getLayerAt(nnet.getLayersCount() - 1)).getNeurons();
nnet.setInputNeurons(inputNeurons);
nnet.setOutputNeurons(outputNeurons);
}
private void fillAttributes() {
int layerIdx = nnet.getLayersCount() - 1; // output layerIdx by default
Attribute attr1;
Attribute attr2 = null;
if (layerCombo.isEnabled()) {
layerIdx = (Integer) layerCombo.getSelectedItem() - 1;
}
attr1 = new Attribute(layerIdx, false, "Layer");
if (attributeTxtField.isEnabled()) {
attribute = Integer.parseInt(attributeTxtField.getText());
attr2 = new Attribute(attribute, false, "Input");
}
graphBuilder.setAttribute1(attr1);
graphBuilder.setAttribute2(attr2);
outputNeuronCount = nnet.getLayerAt(layerIdx).getNeuronsCount();
}
@Override
public void setNeuralNetwork(NeuralNetwork neuralNetwork) {
super.setNeuralNetwork(neuralNetwork);
int neuronsNum = neuralNetwork.getLayerAt(1).getNeuronsCount();
mapSize = (int) Math.sqrt(neuronsNum);
}
