eoSharing.h

//-----------------------------------------------------------------------------

#ifndef eoSharing_h
#define eoSharing_h

#include <eoPerf2Worth.h>
#include <utils/eoDistance.h>

class dMatrix : public std::vector<double>
  {
  public:
    // Ctor : sets size
    dMatrix(unsigned _s) : std::vector<double>(_s*_s), rSize(_s) {}

    double operator()(unsigned _i, unsigned _j) const
    {
      return this->operator[](_i*rSize + _j);
    }

    double & operator()(unsigned _i, unsigned _j)
    {
      return this->operator[](_i*rSize + _j);
    }

    void printOn(std::ostream & _os)
    {
      unsigned index=0;
      for (unsigned i=0; i<rSize; i++)
        {
          for (unsigned j=0; j<rSize; j++)
            _os << this->operator[](index++) << " " ;
          _os << std::endl;
        }
      _os << std::endl;
    }

    private:
      unsigned rSize;              // row size (== number of columns!)
  };


template <class EOT>
class eoSharing : public eoPerf2Worth<EOT>
{
public:

    using eoPerf2Worth<EOT>::value;


  /* Ctor requires a distance - cannot have a default distance! */
  eoSharing(double _nicheSize, eoDistance<EOT> & _dist) : eoPerf2Worth<EOT>("Sharing"),
                                             nicheSize(_nicheSize),
                                             dist(_dist)
  {}

    void operator()(const eoPop<EOT>& _pop)
    {
      unsigned i, j,
        pSize=_pop.size();
      if (pSize <= 1)
        throw std::runtime_error("Apptempt to do sharing with population of size 1");
      value().resize(pSize);
      std::vector<double> sim(pSize);      // to hold the similarities
      dMatrix distMatrix(pSize); // to hold the distances

      // compute the similarities (wrong name for distMatrix, I know)
      distMatrix(0,0)=1;
      for (i=1; i<pSize; i++)
        {
          distMatrix(i,i)=1;
          for (j=0; j<i; j++)
            {
              double d =  dist(_pop[i], _pop[j]);
              distMatrix(i,j) =
                distMatrix(j,i) = ( d>nicheSize ? 0 : 1-(d/nicheSize) );
            }
        }

      for (i=0; i<pSize; i++)
        {
          double sum=0.0;
          for (j=0; j<pSize; j++)
            sum += distMatrix(i,j);
          sim[i] = sum;
        }

      // now set the worthes values
      for (i = 0; i < _pop.size(); ++i)
        value()[i]=_pop[i].fitness()/sim[i];
    }
    // private data of class eoSharing
private:
  double nicheSize;
  eoDistance<EOT> & dist;            // specific distance
};



#endif