/*
* 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.ml.prg.opp;
import java.util.ArrayList;
import java.util.List;
import java.util.Random;
import org.encog.ml.ea.genome.Genome;
import org.encog.ml.ea.opp.EvolutionaryOperator;
import org.encog.ml.ea.train.EvolutionaryAlgorithm;
import org.encog.ml.prg.EncogProgram;
import org.encog.ml.prg.EncogProgramContext;
import org.encog.ml.prg.ProgramNode;
import org.encog.ml.prg.expvalue.ValueType;
/**
* Perform a type-safe subtree crossover. The crossover points will be chosen
* randomly but must be type-safe. The first parent will be cloned to produce
* the child. The tree formed from the crossover point of the second child will
* be copied and grafted into the parent's clone and its crossover point.
*/
public class SubtreeCrossover implements EvolutionaryOperator {
/**
* This method is called reflexivly as we iterate downward. Once we reach
* the desired point (when current level drops to zero), the operation is
* performed.
*
* @param rnd
* A random number generator.
* @param parentNode
* The parent node.
* @param types
* The desired node
* @param holder
* The level holder.
*/
private void findNode(final Random rnd, final ProgramNode parentNode,
final List<ValueType> types, final LevelHolder holder) {
if (holder.getCurrentLevel() == 0) {
holder.decreaseLevel();
holder.setTypes(types);
holder.setNodeFound(parentNode);
} else {
holder.decreaseLevel();
for (int i = 0; i < parentNode.getTemplate().getChildNodeCount(); i++) {
final ProgramNode childNode = parentNode.getChildNode(i);
final List<ValueType> childTypes = parentNode.getTemplate()
.getParams().get(i).determineArgumentTypes(types);
findNode(rnd, childNode, childTypes, holder);
}
}
}
/**
* {@inheritDoc}
*/
@Override
public void init(final EvolutionaryAlgorithm theOwner) {
// TODO Auto-generated method stub
}
/**
* @return Returns the number of offspring produced. In this case, one.
*/
@Override
public int offspringProduced() {
return 1;
}
/**
* @return Returns the number of parents needed. In this case, two.
*/
@Override
public int parentsNeeded() {
return 2;
}
/**
* {@inheritDoc}
*/
@Override
public void performOperation(final Random rnd, final Genome[] parents,
final int parentIndex, final Genome[] offspring,
final int offspringIndex) {
final EncogProgram parent1 = (EncogProgram) parents[0];
final EncogProgram parent2 = (EncogProgram) parents[1];
offspring[0] = null;
final EncogProgramContext context = parent1.getContext();
final int size1 = parent1.getRootNode().size();
final int size2 = parent2.getRootNode().size();
boolean done = false;
int tries = 100;
while (!done) {
final int p1Index = rnd.nextInt(size1);
final int p2Index = rnd.nextInt(size2);
final LevelHolder holder1 = new LevelHolder(p1Index);
final LevelHolder holder2 = new LevelHolder(p2Index);
final List<ValueType> types = new ArrayList<ValueType>();
types.add(context.getResult().getVariableType());
findNode(rnd, parent1.getRootNode(), types, holder1);
findNode(rnd, parent2.getRootNode(), types, holder2);
if (LevelHolder.compatibleTypes(holder1.getTypes(),
holder2.getTypes())) {
final EncogProgram result = context.cloneProgram(parent1);
final ProgramNode resultNode = parent1.findNode(p1Index);
final ProgramNode p2Node = parent2.findNode(p2Index);
final ProgramNode newInsert = context.cloneBranch(result,
p2Node);
result.replaceNode(resultNode, newInsert);
offspring[0] = result;
done = true;
} else {
tries--;
if (tries < 0) {
done = true;
}
}
}
}
}