/**
* Copyright 2010 Neuroph Project http://neuroph.sourceforge.net
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.neuroph.util;
import org.neuroph.core.Connection;
import org.neuroph.core.Layer;
import org.neuroph.core.NeuralNetwork;
import org.neuroph.core.Neuron;
/**
* A CODEC encodes and decodes neural networks, much like the more standard
* definition of a CODEC encodes and decodes audio/video.
*
* This CODEC can encode a neural network to an array of doubles. It can also
* decode this array of doubles back into a neural network. This is very useful
* for both simulated annealing and genetic algorithms.
*
* @author Jeff Heaton (http://www.heatonresearch.com)
*/
public class NeuralNetworkCODEC {
/**
* Private constructor.
*/
private NeuralNetworkCODEC() {
}
/**
* Encode a network to an array.
* @param network The network to encode.
* @return The array encoded.
*/
public static void network2array(NeuralNetwork network, double[] array) {
int index = 0;
for (Layer layer : network.getLayers()) {
for (Neuron neuron : layer.getNeurons()) {
for (Connection connection : neuron.getOutConnections()) {
array[index++] = connection.getWeight().getValue();
}
}
}
}
/**
* Decode a network from an array.
* @param array The array used to decode.
* @param network The network to decode into.
*/
public static void array2network(double[] array, NeuralNetwork network) {
int index = 0;
for (Layer layer : network.getLayers()) {
for (Neuron neuron : layer.getNeurons()) {
for (Connection connection : neuron.getOutConnections()) {
connection.getWeight().setValue(array[index]);
//connection.getWeight().setPreviousValue(array[index++]);
}
}
}
}
/**
* Determine the array size for the given neural network.
* @param network The neural network to determine for.
* @return The size of the array necessary to hold that network.
*/
public static int determineArraySize(NeuralNetwork network) {
int result = 0;
for (Layer layer : network.getLayers()) {
for (Neuron neuron : layer.getNeurons()) {
result+=neuron.getOutConnections().size();
}
}
return result;
}
}