131 lines
3.6 KiB
C++
131 lines
3.6 KiB
C++
/** -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
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-----------------------------------------------------------------------------
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eoSharing.h
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(c) Maarten Keijzer, Marc Schoenauer, 2001
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This library is free software; you can redistribute it and/or
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modify it under the terms of the GNU Lesser General Public
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License as published by the Free Software Foundation; either
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version 2 of the License, or (at your option) any later version.
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This library is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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Lesser General Public License for more details.
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You should have received a copy of the GNU Lesser General Public
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License along with this library; if not, write to the Free Software
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Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
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Contact: Marc.Schoenauer@inria.fr
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mkeijzer@dhi.dk
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*/
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//-----------------------------------------------------------------------------
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#ifndef eoSharing_h
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#define eoPerf2Worth_h
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#include <eoPerf2Worth.h>
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#include <utils/eoDistance.h>
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/** Sharing is a perf2worth class that implements
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* Goldberg and Richardson's basic sharing
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*/
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// template <class EOT, class Dist = eoQuadDistance<EOT> >
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template <class EOT>
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class eoSharing : public eoPerf2Worth<EOT, double>
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{
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public:
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/** Ctor with only nicheSize: will use the default eoQuadDistance */
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eoSharing(double _nicheSize) : eoPerf2Worth("Sharing"),
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nicheSize(_nicheSize),
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dist(repDist)
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{}
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eoSharing(double _nicheSize, Dist _dist) : eoPerf2Worth("Sharing"),
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nicheSize(_nicheSize),
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dist(_dist)
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{}
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/** Computes shared fitnesses
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*/
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void operator()(const eoPop<EOT>& _pop)
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{
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unsigned i, j,
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pSize=_pop.size();
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if (pSize <= 1)
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throw runtime_error("Apptempt to do sharing with population of size 1");
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value.resize(pSize);
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vector<double> sim(pSize); // to hold the similarities
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vector<double> distMatrix(pSize*(pSize-1)/2); // to hold the distances
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// compute the distances
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distMatrix(0,0)=0;
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for (i=1; i<pSize; i++)
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{
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distMatrix(i,i)=0;
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for (j=0; j<i; j++)
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{
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distMatrix(i,j) = distMatrix(j,i) = dist(_pop[i], _pop[j]);
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}
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}
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// compute the similarities
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for (i=0; i<pSize; i++)
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{
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double sum=0.0;
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for (j=0; j<pSize; j++)
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sum += distMatrix(i,j);
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sim[i] = sum;
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}
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// now set the worthes values
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for (i = 0; i < _pop.size(); ++i)
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value()[i]=_pop[i].fitness()/sim[i];
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}
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// helper class to hold distances
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class dMatrix : public vector<double>
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{
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public:
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// Ctor : sets size
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dMatrix(unsigned _s) : vector<double>(_s*(_s-1)), rSize(_s) {}
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/** simple accessor */
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double operator()(unsigned _i, unsigned _j) const
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{
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return this->operator[](_i*rSize + _j);
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}
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/** reference - to set values */
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double & operator()(unsigned _i, unsigned _j)
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{
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return this->operator[](_i*rSize + _j);
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}
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/** just in case */
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void printOn(ostream & _os)
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{
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unsigned index=0;
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for (unsigned i=0; i<rSize; i++)
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{
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for (unsigned j=0; j<rSize; j++)
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_os << this->operator[](index++) << " " ;
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_os << endl;
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}
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_os << endl;
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}
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private:
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unsigned rSize; // row size (== number of columns!)
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};
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// private data of class eoSharing
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private:
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double nicheSize;
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eoQuadDistance<EOT> repDist; // default distance
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eoDistance & dist; // allows to pass a specific distance
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};
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#endif
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