95 lines
2.5 KiB
C++
95 lines
2.5 KiB
C++
/*
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The Evolving Distribution Objects framework (EDO) is a template-based,
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ANSI-C++ evolutionary computation library which helps you to write your
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own estimation of distribution algorithms.
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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 2.1 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., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
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Copyright (C) 2010 Thales group
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*/
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/*
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Authors:
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Johann Dréo <johann.dreo@thalesgroup.com>
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Caner Candan <caner.candan@thalesgroup.com>
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*/
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#ifndef _edoSampler_h
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#define _edoSampler_h
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#include <eoFunctor.h>
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#include "edoBounder.h"
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#include "edoBounderNo.h"
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template < typename D >
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class edoSampler : public eoUF< D&, typename D::EOType >
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{
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public:
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typedef typename D::EOType EOType;
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edoSampler(edoBounder< EOType > & bounder)
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: /*_dummy_bounder(),*/ _bounder(bounder)
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{}
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/*
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edoSampler()
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: _dummy_bounder(), _bounder( _dummy_bounder )
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{}
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*/
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// virtual EOType operator()( D& ) = 0 (provided by eoUF< A1, R >)
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virtual EOType sample( D& ) = 0;
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EOType operator()( D& distrib )
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{
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unsigned int size = distrib.size();
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assert(size > 0);
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//-------------------------------------------------------------
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// Point we want to sample to get higher a set of points
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// (coordinates in n dimension)
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// x = {x1, x2, ..., xn}
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// the sample method is implemented in the derivated class
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//-------------------------------------------------------------
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EOType solution(sample(distrib));
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//-------------------------------------------------------------
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//-------------------------------------------------------------
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// Now we are bounding the distribution thanks to min and max
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// parameters.
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//-------------------------------------------------------------
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_bounder(solution);
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//-------------------------------------------------------------
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return solution;
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}
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private:
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//edoBounderNo<EOType> _dummy_bounder;
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//! Bounder functor
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edoBounder< EOType > & _bounder;
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};
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#endif // !_edoSampler_h
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