/*
 * Encog(tm) Core v3.2 - Java Version
 * http://www.heatonresearch.com/encog/
 * https://github.com/encog/encog-java-core
 
 * Copyright 2008-2013 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.neural.neat.training;

import java.io.Serializable;

import org.encog.engine.network.activation.ActivationFunction;
import org.encog.neural.neat.NEATNeuronType;

/**
 * Implements a NEAT neuron gene.
 * 
 * NeuroEvolution of Augmenting Topologies (NEAT) is a genetic algorithm for the
 * generation of evolving artificial neural networks. It was developed by Ken
 * Stanley while at The University of Texas at Austin.
 * 
 * -----------------------------------------------------------------------------
 * http://www.cs.ucf.edu/~kstanley/ Encog's NEAT implementation was drawn from
 * the following three Journal Articles. For more complete BibTeX sources, see
 * NEATNetwork.java.
 * 
 * Evolving Neural Networks Through Augmenting Topologies
 * 
 * Generating Large-Scale Neural Networks Through Discovering Geometric
 * Regularities
 * 
 * Automatic feature selection in neuroevolution
 * 
 */
public class NEATNeuronGene extends NEATBaseGene implements Serializable {

	/**
	 * Serial id.
	 */
	private static final long serialVersionUID = 1L;
	
	/**
	 * The neuron type.
	 */
	private NEATNeuronType neuronType;
	
	/**
	 * The activation function.
	 */
	private ActivationFunction activationFunction;

	/**
	 * The default constructor.
	 */
	public NEATNeuronGene() {

	}

	/**
	 * Construct a neuron gene.
	 * @param type The neuron type.
	 * @param theActivationFunction The activation function.
	 * @param id The neuron id.
	 * @param innovationID The innovation id.
	 */
	public NEATNeuronGene(final NEATNeuronType type, ActivationFunction theActivationFunction, final long id, final long innovationID) {
		this.neuronType = type;
		this.setInnovationId(innovationID);
		setId(id);
		this.activationFunction = theActivationFunction;
	}
	
	/**
	 * Construct this gene by comping another.
	 * @param other The other gene to copy.
	 */
	public NEATNeuronGene(NEATNeuronGene other) {
		copy(other);
	}

	/**
	 * Copy another gene to this one.
	 * 
	 * @param gene
	 *            The other gene.
	 */
	public void copy(final NEATNeuronGene gene) {
		final NEATNeuronGene other = gene;
		setId(other.getId());
		this.neuronType = other.neuronType;
		this.activationFunction = other.activationFunction;
		this.setInnovationId(other.getInnovationId());
	}
	
	/**
	 * @return The type for this neuron.
	 */
	public NEATNeuronType getNeuronType() {
		return this.neuronType;
	}

	/**
	 * Set the neuron type.
	 * 
	 * @param neuronType
	 *            The neuron type.
	 */
	public void setNeuronType(final NEATNeuronType neuronType) {
		this.neuronType = neuronType;
	}

	/**
	 * @return the activationFunction
	 */
	public ActivationFunction getActivationFunction() {
		return activationFunction;
	}

	/**
	 * @param activationFunction the activationFunction to set
	 */
	public void setActivationFunction(ActivationFunction activationFunction) {
		this.activationFunction = activationFunction;
	}

	/**
	 * {@inheritDoc}
	 */
	@Override
	public String toString() {
		StringBuilder result = new StringBuilder();
		result.append("[NEATNeuronGene: id=");
		result.append(this.getId());
		result.append(", type=");
		result.append(this.getNeuronType());
		result.append("]");
		return result.toString();
	}
}
