/*
* RapidMiner
*
* Copyright (C) 2001-2008 by Rapid-I and the contributors
*
* Complete list of developers available at our web site:
*
* http://rapid-i.com
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU Affero General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU Affero General Public License for more details.
*
* You should have received a copy of the GNU Affero General Public License
* along with this program. If not, see http://www.gnu.org/licenses/.
*/
package com.rapidminer.operator.features.aggregation;
import java.util.ArrayList;
import java.util.Iterator;
import java.util.List;
import com.rapidminer.tools.RandomGenerator;
/**
* Performs an aggregation mutation on integer arrays. Each feature value is
* mutated with probability 1/n. Mutation is done by randomly selecting a new
* value between -1 and max(values).
*
* @author Ingo Mierswa
* @version $Id: AggregationMutation.java,v 1.4 2006/04/05 08:57:23 ingomierswa
* Exp $
*/
public class AggregationMutation {
private RandomGenerator random;
public AggregationMutation(RandomGenerator random) {
this.random = random;
}
/** Checks if at least one feature was selected. */
private boolean isValid(int[] individual) {
for (int i = 0; i < individual.length; i++) {
if (individual[i] >= 0)
return true;
}
return false;
}
/**
* Invokes the method mutate(int[]) for each individual. The parents are
* kept.
*/
public void mutate(List<AggregationIndividual> population) {
List<AggregationIndividual> children = new ArrayList<AggregationIndividual>();
Iterator<AggregationIndividual> i = population.iterator();
while (i.hasNext()) {
AggregationIndividual individual = i.next();
int[] parent = individual.getIndividual();
int[] child = new int[parent.length];
for (int j = 0; j < child.length; j++)
child[j] = parent[j];
mutate(child);
if (isValid(child)) {
children.add(new AggregationIndividual(child));
}
}
population.addAll(children);
}
/**
* Changes the individual (each gene with probability 1 / n). Make clone if
* original individual should be kept.
*/
private void mutate(int[] individual) {
double prob = 1.0d / individual.length;
int max = -1;
for (int i = 0; i < individual.length; i++) {
if (individual[i] > max)
max = individual[i];
}
for (int i = 0; i < individual.length; i++) {
if (random.nextDouble() < prob) {
individual[i] = random.nextIntInRange(-1, max + 1);
}
}
}
}