/*
* <moeoFrontByFrontCrowdingDiversityAssignment.h>
* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2007
* (C) OPAC Team, LIFL, 2002-2007
*
* Arnaud Liefooghe
*
* This software is governed by the CeCILL license under French law and
* abiding by the rules of distribution of free software.  You can  use,
* modify and/ or redistribute the software under the terms of the CeCILL
* license as circulated by CEA, CNRS and INRIA at the following URL
* "http://www.cecill.info".
*
* As a counterpart to the access to the source code and  rights to copy,
* modify and redistribute granted by the license, users are provided only
* with a limited warranty  and the software's author,  the holder of the
* economic rights,  and the successive licensors  have only  limited liability.
*
* In this respect, the user's attention is drawn to the risks associated
* with loading,  using,  modifying and/or developing or reproducing the
* software by the user in light of its specific status of free software,
* that may mean  that it is complicated to manipulate,  and  that  also
* therefore means  that it is reserved for developers  and  experienced
* professionals having in-depth computer knowledge. Users are therefore
* encouraged to load and test the software's suitability as regards their
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* data to be ensured and,  more generally, to use and operate it in the
* same conditions as regards security.
* The fact that you are presently reading this means that you have had
* knowledge of the CeCILL license and that you accept its terms.
*
* ParadisEO WebSite : http://paradiseo.gforge.inria.fr
* Contact: paradiseo-help@lists.gforge.inria.fr
*
*/
//-----------------------------------------------------------------------------

#ifndef MOEOFRONTBYFRONTCROWDINGDIVERSITYASSIGNMENT2_H_
#define MOEOFRONTBYFRONTCROWDINGDIVERSITYASSIGNMENT2_H_

#include <diversity/moeoCrowdingDiversityAssignment.h>
#include <comparator/moeoFitnessThenDiversityComparator.h>
#include <PhyloMOEA/moeoPtrComparator.h>


/**
 * Diversity assignment sheme based on crowding proposed in:
 * K. Deb, A. Pratap, S. Agarwal, T. Meyarivan, "A Fast and Elitist Multi-Objective Genetic Algorithm: NSGA-II", IEEE Transactions on Evolutionary Computation, vol. 6, no. 2 (2002).
 * Tis strategy assigns diversity values FRONT BY FRONT. It is, for instance, used in NSGA-II.
 */
template < class MOEOT >
class moeoFrontByFrontCrowdingDiversityAssignment2 : public moeoCrowdingDiversityAssignment < MOEOT >
  {
  public:

    /** the objective vector type of the solutions */
    typedef typename MOEOT::ObjectiveVector ObjectiveVector;


    /**
     * @warning NOT IMPLEMENTED, DO NOTHING !
     * Updates the diversity values of the whole population _pop by taking the deletion of the objective vector _objVec into account.
     * @param _pop the population
     * @param _objVec the objective vector
     * @warning NOT IMPLEMENTED, DO NOTHING !
     */
    void updateByDeleting(eoPop < MOEOT > & _pop, ObjectiveVector & _objVec)
    {
      std::cout << "WARNING : updateByDeleting not implemented in moeoFrontByFrontCrowdingDistanceDiversityAssignment" << std::endl;
    }

  private:

    using moeoCrowdingDiversityAssignment < MOEOT >::inf;
    using moeoCrowdingDiversityAssignment < MOEOT >::tiny;

    /**
     * Sets the distance values
     * @param _pop the population
     */

    void setDistances (eoPop <MOEOT> & _pop)
    {
      unsigned int a,b;
      double min, max, distance;
      unsigned int nObjectives = MOEOT::ObjectiveVector::nObjectives();
      // set diversity to 0 for every individual
      for (unsigned int i=0; i<_pop.size(); i++)
        {
          _pop[i].diversity(0.0);
        }
      // sort the whole pop according to fitness values
      moeoFitnessThenDiversityComparator < MOEOT > fitnessComparator;
	  std::vector<const MOEOT *> sortedptrpop;
	  sortedptrpop.resize(_pop.size());
	  // due to intensive sort operations for this diversity assignment,
	  // it is more efficient to perform sorts using only pointers to the
      // population members in order to avoid copy of individuals
	  std::transform( _pop.begin(), _pop.end(), sortedptrpop.begin(), typename eoPop<MOEOT>::Ref());	
      //sort the pointers to population members 
	  moeoPtrComparator<MOEOT> cmp2( fitnessComparator);
	  std::sort(sortedptrpop.begin(), sortedptrpop.end(), cmp2);
      // compute the crowding distance values for every individual "front" by "front" (front : from a to b)
      a = 0;	        			// the front starts at a
      while (a < _pop.size())
        {
		  b = lastIndex(sortedptrpop,a);	// the front ends at b
          //b = lastIndex(_pop,a);	// the front ends at b
          // if there is less than 2 individuals in the front...
          if ((b-a) < 2)
            {
              for (unsigned int i=a; i<=b; i++)
                {
					((MOEOT *)sortedptrpop[i])->diversity(inf());
                  //_pop[i].diversity(inf());
                }
            }
          // else...
          else
            {
              // for each objective
              for (unsigned int obj=0; obj<nObjectives; obj++)
                {
                  // sort in the descending order using the values of the objective 'obj'
                  moeoOneObjectiveComparator < MOEOT > objComp(obj);
				  moeoPtrComparator<MOEOT> cmp2( objComp );
				  std::sort(sortedptrpop.begin(), sortedptrpop.end(), cmp2);
                  // min & max
                  min = (sortedptrpop[b])->objectiveVector()[obj];
                  max = (sortedptrpop[a])->objectiveVector()[obj];
	
                  // avoid extreme case
                  if (min == max)
                    {
                      min -= tiny();
                      max += tiny();
                    }
                  // set the diversity value to infiny for min and max
                  ((MOEOT *)sortedptrpop[a])->diversity(inf());
                  ((MOEOT *)sortedptrpop[b])->diversity(inf());
                  // set the diversity values for the other individuals
                  for (unsigned int i=a+1; i<b; i++)
                    {
                        distance = ( (sortedptrpop[i-1])->objectiveVector()[obj] - (sortedptrpop[i+1])->objectiveVector()[obj]) / (max-min);
                        ((MOEOT *)sortedptrpop[i])->diversity(sortedptrpop[i]->diversity() + distance);
                    }
                }
            }
          // go to the next front
          a = b+1;
        }
    }



    /**
     * Returns the index of the last individual having the same fitness value than _pop[_start]
     * @param _pop the vector of pointers to population individuals
     * @param _start the index to start from
     */

    unsigned int lastIndex (std::vector<const MOEOT *> & _pop, unsigned int _start)
    {
      unsigned int i=_start;
      while ( (i<_pop.size()-1) && (_pop[i]->fitness()==_pop[i+1]->fitness()) )
        {
          i++;
        }
      return i;
    }


  };

#endif /*MOEOFRONTBYFRONTCROWDINGDIVERSITYASSIGNMENT_H_*/