/*
 *  RapidMiner
 *
 *  Copyright (C) 2001-2011 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.selection;

import java.util.LinkedList;
import java.util.List;
import java.util.Random;

import com.rapidminer.operator.features.Individual;
import com.rapidminer.operator.features.IndividualOperator;

/**
 * Inverts the used bit for every feature of every example set with a given
 * fixed probability.
 * 
 * @author Simon Fischer, Ingo Mierswa
 *          Exp $
 */
public class SelectionMutation extends IndividualOperator {

	private double probability;

    private Random random;
    
    private int minNumber;
    
    private int maxNumber;
    
    private int exactNumber;
    
    
	public SelectionMutation(double probability, Random random, int minNumber, int maxNumber, int exactNumber) {
		this.probability = probability;
        this.random      = random;
        this.minNumber   = minNumber;
        this.maxNumber   = maxNumber;
        this.exactNumber = exactNumber;
	}

	@Override
	public List<Individual> operate(Individual individual) {
		List<Individual> l = new LinkedList<Individual>();
		double[] weights = individual.getWeightsClone();

		double prob = probability < 0 ? 1.0d / weights.length : probability;
		for (int i = 0; i < weights.length; i++) {
			if (random.nextDouble() < prob) {
				if (weights[i] > 0)
					weights[i] = 0;
				else
					weights[i] = 1;
			}
		}
		
		Individual newIndividual = new Individual(weights);
		int numberOfFeatures = newIndividual.getNumberOfUsedAttributes(); 
		if (numberOfFeatures > 0) {
			if (exactNumber > 0) {
				if (numberOfFeatures == exactNumber) {
					l.add(newIndividual);
				}
			} else {
				if (((maxNumber < 1) || (numberOfFeatures <= maxNumber)) && (numberOfFeatures >= minNumber)) {
					l.add(newIndividual);
				}
			}
		}

		// add also original ES
		l.add(individual);
		return l;
	}
}