/*
* Artificial Intelligence for Humans
* Volume 2: Nature Inspired Algorithms
* Java Version
* http://www.aifh.org
* http://www.jeffheaton.com
*
* Code repository:
* https://github.com/jeffheaton/aifh
*
* Copyright 2014 by Jeff Heaton
*
* 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 com.heatonresearch.aifh.genetic.trees;
import com.heatonresearch.aifh.evolutionary.genome.Genome;
import com.heatonresearch.aifh.evolutionary.opp.EvolutionaryOperator;
import com.heatonresearch.aifh.evolutionary.train.EvolutionaryAlgorithm;
import com.heatonresearch.aifh.randomize.GenerateRandom;
/**
* Create a child tree as a mutation of the parent. Do not modify the parent.
*/
public class MutateTree implements EvolutionaryOperator {
/**
* The owner.
*/
private EvolutionaryAlgorithm owner;
/**
* The maximum length of a branch to graft.
*/
private int maxGraftLength;
/**
* Construct the tree mutation object.
* @param theMaxGraftLength The maximum graft length.
*/
public MutateTree(int theMaxGraftLength) {
this.maxGraftLength = Math.max(1, theMaxGraftLength);
}
/**
* {@inheritDoc}
*/
@Override
public void init(final EvolutionaryAlgorithm theOwner) {
this.owner = theOwner;
}
/**
* {@inheritDoc}
*/
@Override
public int offspringProduced() {
return 1;
}
/**
* {@inheritDoc}
*/
@Override
public int parentsNeeded() {
return 1;
}
/**
* {@inheritDoc}
*/
@Override
public void performOperation(final GenerateRandom rnd, final Genome[] parents, final int parentIndex, final Genome[] offspring, final int offspringIndex) {
TreeGenome parent1 = (TreeGenome) parents[parentIndex];
EvaluateTree eval = parent1.getEvaluator();
TreeGenome off1 = (TreeGenome) this.owner.getPopulation().getGenomeFactory().factor(parent1);
RandomNodeResult off1Point = eval.sampleRandomNode(rnd, off1.getRoot());
int len = rnd.nextInt(1, this.maxGraftLength + 1);
TreeGenomeNode randomSequence = eval.grow(rnd, len);
if (off1Point.getParent() == null) {
off1.setRoot(randomSequence);
} else {
int idx = off1Point.getParent().getChildren().indexOf(off1Point.getChild());
off1Point.getParent().getChildren().set(idx, randomSequence);
}
offspring[0] = off1;
}
}