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📄 eoproportionalselect.h

📁 这是linux下的进化计算的源代码。 === === === === === === === === === === === ===== check latest news at http:
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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-//-----------------------------------------------------------------------------// eoProportionalSelect.h// (c) GeNeura Team, 1998 - EEAAX 1999, Maarten Keijzer 2000/*     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 2 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; without 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    Contact: todos@geneura.ugr.es, http://geneura.ugr.es             Marc.Schoenauer@polytechnique.fr             mak@dhi.dk *///-----------------------------------------------------------------------------#ifndef eoProportionalSelect_h#define eoProportionalSelect_h//-----------------------------------------------------------------------------#include <utils/eoRNG.h>#include <utils/selectors.h>#include <eoSelectOne.h>#include <eoPop.h>//-----------------------------------------------------------------------------/** eoProportionalSelect: select an individual proportional to her stored fitness    value         Changed the algorithm to make use of a cumulative array of fitness scores,     This changes the algorithm from O(n) per call to  O(log n) per call. (MK)*///-----------------------------------------------------------------------------template <class EOT> class eoProportionalSelect: public eoSelectOne<EOT> {public:  /// Sanity check  eoProportionalSelect(const eoPop<EOT>& pop = eoPop<EOT>())   {    if (minimizing_fitness<EOT>())      throw std::logic_error("eoProportionalSelect: minimizing fitness");  }  void setup(const eoPop<EOT>& _pop)  {      if (_pop.size() == 0) return;            cumulative.resize(_pop.size());      cumulative[0] = _pop[0].fitness();      for (unsigned i = 1; i < _pop.size(); ++i)       {	  cumulative[i] = _pop[i].fitness() + cumulative[i-1];      }  }      /** do the selection,     */  const EOT& operator()(const eoPop<EOT>& _pop)   {      if (cumulative.size() == 0) setup(_pop);            double fortune = rng.uniform() * cumulative.back();       typename FitVec::iterator result = std::upper_bound(cumulative.begin(), cumulative.end(), fortune);      return _pop[result - cumulative.begin()];  }private :  typedef std::vector<typename EOT::Fitness> FitVec;  FitVec cumulative;};#endif

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