@Test(expected=UnsupportedOperationException.class) public void testGetLayerUnitsUnmodifiableRemove(){ List<Neuron> layer = neuralNet.getLayerUnits(0); layer.remove(0); }
public List<Neuron> getLayerUnits(int layerIndex) { return Collections.unmodifiableList(layers.get(layerIndex)); }
BasicNeuralNet implements NeuralNet, Serializable { public List<Neuron> getLayerUnits(int layerIndex) { return Collections.unmodifiableList(layers.get(layerIndex)); } }
BasicNeuralNet implements NeuralNet, Serializable { public List<Neuron> getLayerUnits(int layerIndex) { return Collections.unmodifiableList(layers.get(layerIndex)); } BasicNeuralNet(int[] netTopology, double biasInput,
            Class<? extends ActivationFunction> activationFunction, Random random); }
BasicNeuralNet implements NeuralNet, Serializable { public List<Neuron> getLayerUnits(int layerIndex) { return Collections.unmodifiableList(layers.get(layerIndex)); } BasicNeuralNet(int[] netTopology, double biasInput,
            Class<? extends ActivationFunction> activationFunction, Random random); List<Neuron> getLayerUnits(int layerIndex); int getLayersCount(); double[] feedForward(final double[] inputPattern); double[] getOutput(); void reset(); int getNetInputSize(); int getNetOutputSize(); }
BasicNeuralNet implements NeuralNet, Serializable { public List<Neuron> getLayerUnits(int layerIndex) { return Collections.unmodifiableList(layers.get(layerIndex)); } BasicNeuralNet(int[] netTopology, double biasInput,
            Class<? extends ActivationFunction> activationFunction, Random random); List<Neuron> getLayerUnits(int layerIndex); int getLayersCount(); double[] feedForward(final double[] inputPattern); double[] getOutput(); void reset(); int getNetInputSize(); int getNetOutputSize();  }