/*
* Encog(tm) Core v3.3 - Java Version
* http://www.heatonresearch.com/encog/
* https://github.com/encog/encog-java-core
* Copyright 2008-2014 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.opp.links;
import java.util.ArrayList;
import java.util.List;
import java.util.Random;
import org.encog.ml.ea.train.EvolutionaryAlgorithm;
import org.encog.neural.neat.training.NEATGenome;
import org.encog.neural.neat.training.NEATLinkGene;
/**
* Select a random proportion of links to mutate.
*
* -----------------------------------------------------------------------------
* 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 SelectProportion implements SelectLinks {
/**
* The portion of the links to mutate. 0.0 for none, 1.0 for all.
*/
private double proportion;
/**
* The trainer.
*/
private EvolutionaryAlgorithm trainer;
/**
* Select based on proportion.
* @param theProportion The proportion to select from.
*/
public SelectProportion(double theProportion) {
this.proportion = theProportion;
}
/**
* {@inheritDoc}
*/
@Override
public void init(EvolutionaryAlgorithm theTrainer) {
this.trainer = theTrainer;
}
/**
* {@inheritDoc}
*/
@Override
public List<NEATLinkGene> selectLinks(Random rnd, NEATGenome genome) {
List<NEATLinkGene> result = new ArrayList<NEATLinkGene>();
boolean mutated = false;
for (final NEATLinkGene linkGene : genome.getLinksChromosome()) {
if (rnd.nextDouble() < this.proportion) {
mutated = true;
result.add(linkGene);
}
}
if( !mutated ) {
int idx = rnd.nextInt(genome.getLinksChromosome().size());
NEATLinkGene linkGene = genome.getLinksChromosome().get(idx);
result.add(linkGene);
}
return result;
}
/**
* {@inheritDoc}
*/
@Override
public EvolutionaryAlgorithm getTrainer() {
return trainer;
}
/**
* {@inheritDoc}
*/
@Override
public String toString() {
StringBuilder result = new StringBuilder();
result.append("[");
result.append(this.getClass().getSimpleName());
result.append(":proportion=");
result.append(this.proportion);
result.append("]");
return result.toString();
}
}