/*
 *  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.selection;

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

import com.rapidminer.operator.features.Individual;
import com.rapidminer.operator.features.Population;
import com.rapidminer.operator.features.PopulationOperator;


/**
 * Performs tournaments with k participants. The winner of each tournament is
 * added to the next population. This will be repeated until the desired
 * population size is reached. The tournament size k represents the selection
 * pressure. For small sizes (like 2) relatively bad individuals have a good
 * chance to survive. If k reaches the population size, only the best individual
 * will survive.
 * 
 * @author Ingo Mierswa
 * @version $Id: TournamentSelection.java,v 1.1 2006/04/14 07:47:17 ingomierswa
 *          Exp $
 */
public class TournamentSelection implements PopulationOperator {

	private int popSize;

	private double tournamentFraction;

	private double delta = 0.0d;

	private boolean keepBest = false;

    private Random random;
    
    
	public TournamentSelection(int popSize, double tournamentFraction, int maxGenerations, boolean dynamic, boolean keepBest, Random random) {
		this.popSize = popSize;
		this.keepBest = keepBest;
		this.tournamentFraction = tournamentFraction;
		if (dynamic)
			delta = (1.0d - this.tournamentFraction) / (maxGenerations + 1);
        this.random = random;
	}

	public boolean performOperation(int generation) {
		return true;
	}

	public void operate(Population population) {
		List<Individual> newGeneration = new LinkedList<Individual>();
		int tournamentSize = Math.max((int) Math.round(population.getNumberOfIndividuals() * tournamentFraction), 1);

		if (keepBest) {
			newGeneration.add(population.getBestIndividualEver());
		}

		while (newGeneration.size() < popSize) {
			Individual winner = null;
			for (int k = 0; k < tournamentSize; k++) {
				Individual current = population.get(random.nextInt(population.getNumberOfIndividuals()));
				if ((winner == null) || (current.getPerformance().getMainCriterion().getFitness() > (winner.getPerformance().getMainCriterion().getFitness())))
					winner = current;
			}
			newGeneration.add(winner);
		}

		population.clear();
		population.addAllIndividuals(newGeneration);
		this.tournamentFraction += delta;
	}
}