/*

     dsh-evolve  Framework for evolutionary algorithms.

     Copyright (c) 2005-2013 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.select;

 import java.util.ArrayList;

 import java.util.Collection;

 import java.util.List;

 import org.dishevelled.weighted.WeightedMap;

 import org.dishevelled.weighted.HashWeightedMap;

 import org.dishevelled.evolve.Selection;

 /**

  * Rank-based selection function.

  *

  * @param <I> individual type

  * @author  Michael Heuer

  */

 public final class RankBasedSelection<I>

     implements Selection<I>

 {

     /** Rank. */

     private final int rank;

     /**

      * Create a new rank based selection function with

      * the specified rank.

      *

      * @param rank rank for this rank based selection function,

      *    must be <code>&gt;= 1</code>

      */

     public RankBasedSelection(final int rank)

     {

         if (rank < 1)

         {

             throw new IllegalArgumentException("rank must be greater than or equal to one");

         }

         this.rank = rank;

     }

     /**

      * Return the rank for this rank based selection function.

      *

      * @return the rank for this rank based selection function

      */

     public int getRank()

     {

         return rank;

     }

     /** {@inheritDoc} */

     public Collection<I> select(final Collection<I> population,

                                 final WeightedMap<I> scores)

     {

         if (scores.totalWeight() == 0.0d)

         {

             throw new IllegalStateException("scores total weight must be greater than zero");

         }

         int size = population.size();

         List<I> selected = new ArrayList<I>(size);

         // create intermediate map of those ranked at or above rank

         WeightedMap<I> intermediate = new HashWeightedMap<I>();

         for (I i : scores.keySet())

         {

             if (scores.rank(i) <= rank)

             {

                 // temporarily set fitness score to 0.0d

                 intermediate.put(i, Double.valueOf(0.0d));

             }

         }

         // update fitness based on size of intermediate map

         int intermediateSize = intermediate.size();

         for (I i : intermediate.keySet())

         {

             intermediate.put(i, Double.valueOf((double) rank / (double) intermediateSize));

         }

         // fitness proportional selection on intermediate map

         for (int i = 0; i < size; i++)

         {

             selected.add(intermediate.sample());

         }

         intermediate = null;

         return selected;

     }

 }