/*
 * Encog(tm) Core v3.4 - Java Version
 * http://www.heatonresearch.com/encog/
 * https://github.com/encog/encog-java-core
 
 * Copyright 2008-2016 Heaton Research, Inc.
 *
 * 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.
 *   
 * For more information on Heaton Research copyrights, licenses 
 * and trademarks visit:
 * http://www.heatonresearch.com/copyright
 */
package org.encog.ml.genetic;

import org.encog.ml.MLEncodable;
import org.encog.ml.genetic.genome.DoubleArrayGenome;

/**
 * Implements a genome that allows a feedforward neural network to be trained
 * using a genetic algorithm. The chromosome for a feed forward neural network
 * is the weight and bias matrix.
 */
public class MLMethodGenome extends DoubleArrayGenome {

	/**
	 * Serial id.
	 */
	private static final long serialVersionUID = 1L;

	/**
	 * The phenome.
	 */
	private MLEncodable phenotype;

	/**
	 * Construct a neural genome.
	 * 
	 * @param thePhenotype
	 *            The phenotype to use.
	 */
	public MLMethodGenome(final MLEncodable thePhenotype) {
		super(thePhenotype.encodedArrayLength());
		this.phenotype = thePhenotype;
		this.phenotype.encodeToArray(getData());
	}

	/**
	 * Decode the phenotype.
	 */
	public void decode() {
		this.phenotype.decodeFromArray(getData());
	}

	/**
	 * @return the phenotype
	 */
	public MLEncodable getPhenotype() {
		return this.phenotype;
	}

	/**
	 * @param phenotype
	 *            the phenotype to set
	 */
	public void setPhenotype(final MLEncodable phenotype) {
		this.phenotype = phenotype;
	}
}