001/* 002 * Java Genetic Algorithm Library (jenetics-7.2.0). 003 * Copyright (c) 2007-2023 Franz Wilhelmstötter 004 * 005 * Licensed under the Apache License, Version 2.0 (the "License"); 006 * you may not use this file except in compliance with the License. 007 * You may obtain a copy of the License at 008 * 009 * http://www.apache.org/licenses/LICENSE-2.0 010 * 011 * Unless required by applicable law or agreed to in writing, software 012 * distributed under the License is distributed on an "AS IS" BASIS, 013 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 014 * See the License for the specific language governing permissions and 015 * limitations under the License. 016 * 017 * Author: 018 * Franz Wilhelmstötter (franz.wilhelmstoetter@gmail.com) 019 */ 020package io.jenetics.ext; 021 022import java.util.random.RandomGenerator; 023 024import io.jenetics.Chromosome; 025import io.jenetics.Mutator; 026import io.jenetics.MutatorResult; 027import io.jenetics.internal.math.Probabilities; 028 029import io.jenetics.ext.util.FlatTreeNode; 030import io.jenetics.ext.util.TreeNode; 031 032/** 033 * Abstract class for mutating tree chromosomes. 034 * 035 * @author <a href="mailto:franz.wilhelmstoetter@gmail.com">Franz Wilhelmstötter</a> 036 * @version 4.1 037 * @since 4.1 038 */ 039public abstract class TreeMutator< 040 A, 041 G extends TreeGene<A, G>, 042 C extends Comparable<? super C> 043> 044 extends Mutator<G, C> 045{ 046 047 public TreeMutator() { 048 this(DEFAULT_ALTER_PROBABILITY); 049 } 050 051 public TreeMutator(final double probability) { 052 super(probability); 053 } 054 055 056 /** 057 * Mutates the given chromosome. 058 * 059 * @param chromosome the chromosome to mutate 060 * @param p the mutation probability for the underlying genetic objects 061 * @param random the random engine used for the genotype mutation 062 * @return the mutation result 063 */ 064 @Override 065 protected MutatorResult<Chromosome<G>> mutate( 066 final Chromosome<G> chromosome, 067 final double p, 068 final RandomGenerator random 069 ) { 070 final int P = Probabilities.toInt(p); 071 return random.nextInt() < P 072 ? mutate(chromosome) 073 : new MutatorResult<>(chromosome, 0); 074 } 075 076 private MutatorResult<Chromosome<G>> mutate(final Chromosome<G> chromosome) { 077 final TreeNode<A> tree = TreeNode.ofTree(chromosome.gene()); 078 mutate(tree); 079 080 final var flat = FlatTreeNode.ofTree(tree); 081 final var genes = flat.map(t -> chromosome.gene().newInstance(t)); 082 return new MutatorResult<>(chromosome.newInstance(genes), 1); 083 } 084 085 /** 086 * This method does the actual mutating, in place. 087 * 088 * @param tree the mutable tree to mutate 089 */ 090 protected abstract void mutate(final TreeNode<A> tree); 091 092}