matrixcodec.java

VHDL制作的ann的code

/*
 * Encog Neural Network and Bot Library for Java v1.x
 * http://www.heatonresearch.com/encog/
 * http://code.google.com/p/encog-java/
 * 
 * Copyright 2008, Heaton Research Inc., and individual contributors.
 * See the copyright.txt in the distribution for a full listing of 
 * individual contributors.
 *
 * This is free software; you can redistribute it and/or modify it
 * under the terms of the GNU Lesser General Public License as
 * published by the Free Software Foundation; either version 2.1 of
 * the License, or (at your option) any later version.
 *
 * This software is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
 * Lesser General Public License for more details.
 *
 * You should have received a copy of the GNU Lesser General Public
 * License along with this software; if not, write to the Free
 * Software Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
 * 02110-1301 USA, or see the FSF site: http://www.fsf.org.
 */
package org.encog.matrix;

import org.encog.neural.networks.BasicNetwork;
import org.encog.neural.networks.Layer;

/**
 * MatrixCODEC: The matrix CODEC can encode or decode a matrix to/from an array
 * of doubles. This is very useful when the neural network must be looked at as
 * an array of doubles for genetic algorithms and simulated annealing.
 */
public final class MatrixCODEC {

	/**
	 * Private constructor.
	 */
	private MatrixCODEC() {
		
	}
	
	/**
	 * Use an array to populate the memory of the neural network.
	 * 
	 * @param array
	 *            An array of doubles.
	 * @param network The network to encode.
	 */
	public static void arrayToNetwork(final Double[] array,
			final BasicNetwork network) {

		// copy data to array
		int index = 0;

		for (final Layer layer : network.getLayers()) {

			// now the weight matrix(if it exists)
			if (layer.getNext() != null) {
				index = layer.getMatrix().fromPackedArray(array, index);
			}
		}
	}

	/**
	 * Convert to an array. This is used with some training algorithms that
	 * require that the "memory" of the neuron(the weight and threshold values)
	 * be expressed as a linear array.
	 * @param network The network to encode.
	 * @return The memory of the neuron.
	 */
	public static Double[] networkToArray(final BasicNetwork network) {
		int size = 0;

		// first determine size
		for (final Layer layer : network.getLayers()) {
			// count the size of the weight matrix
			if (layer.hasMatrix()) {
				size += layer.getMatrixSize();
			}
		}

		// allocate an array to hold
		final Double[] result = new Double[size];

		// copy data to array
		int index = 0;

		for (final Layer layer : network.getLayers()) {

			// now the weight matrix(if it exists)
			if (layer.getNext() != null) {

				final Double[] matrix = layer.getMatrix().toPackedArray();
				for (int i = 0; i < matrix.length; i++) {
					result[index++] = matrix[i];
				}
			}
		}

		return result;
	}

}