/*

     dsh-evolve  Framework for evolutionary algorithms.

     Copyright (c) 2005-2012 held jointly by the individual authors.

     This library is free software; you can redistribute it and/or modify it

     under the terms of the GNU Lesser General Public License as published

     by the Free Software Foundation; either version 3 of the License, or (at

     your option) any later version.

     This library is distributed in the hope that it will be useful, but WITHOUT

     ANY WARRANTY; with out even the implied warranty of MERCHANTABILITY or

     FITNESS FOR A PARTICULAR PURPOSE.  See the GNU Lesser General Public

     License for more details.

     You should have received a copy of the GNU Lesser General Public License

     along with this library;  if not, write to the Free Software Foundation,

     Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307  USA.

     > http://www.fsf.org/licensing/licenses/lgpl.html

     > http://www.opensource.org/licenses/lgpl-license.php

 */

 package org.dishevelled.evolve.exit;

 import java.util.Collection;

 import org.dishevelled.weighted.WeightedMap;

 import org.dishevelled.evolve.ExitStrategy;

 /**

  * Fitness threshold exit strategy.  Exits as soon as

  * at least one individual has a fitness score above a

  * set threshold.

  *

  * @param <I> individual type

  * @author  Michael Heuer

  * @version $Revision: 1059 $ $Date: 2012-01-03 14:03:02 -0600 (Tue, 03 Jan 2012) $

  */

 public final class FitnessThresholdExitStrategy<I>

     implements ExitStrategy<I>

 {

     /** Threshold for this fitness threshold exit strategy. */

     private final double threshold;

     /**

      * Create a new fitness threshold exit strategy with the specified threshold.

      *

      * @param threshold threshold for this fitness threshold exit strategy

      */

     public FitnessThresholdExitStrategy(final double threshold)

     {

         this.threshold = threshold;

     }

     /** {@inheritDoc} */

     public boolean evaluate(final Collection<I> population, final WeightedMap<I> scores, final int time)

     {

         for (Double fitness : scores.values())

         {

             if (fitness > threshold)

             {

                 return true;

             }

         }

         return false;

     }

 }