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move edo stuff, that was in the wriong place after the merge, in the edo directory

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Johann Dreo 2011-01-27 11:58:21 +01:00
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src/edoSamplerNormalMono.h
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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
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 2.1 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., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoSamplerNormalMono_h
#define _edoSamplerNormalMono_h
#include <utils/eoRNG.h>
#include "edoSampler.h"
#include "edoNormalMono.h"
#include "edoBounder.h"
/**
* edoSamplerNormalMono
* This class uses the NormalMono distribution parameters (bounds) to return
* a random position used for population sampling.
*/
template < typename EOT >
class edoSamplerNormalMono : public edoSampler< edoNormalMono< EOT > >
{
public:
typedef typename EOT::AtomType AtomType;
edoSamplerNormalMono( edoBounder< EOT > & bounder )
: edoSampler< edoNormalMono< EOT > >( bounder )
{}
EOT sample( edoNormalMono< EOT >& distrib )
{
unsigned int size = distrib.size();
assert(size > 0);
//-------------------------------------------------------------
// Point we want to sample to get higher a set of points
// (coordinates in n dimension)
// x = {x1, x2, ..., xn}
//-------------------------------------------------------------
EOT solution;
//-------------------------------------------------------------
//-------------------------------------------------------------
// Sampling all dimensions
//-------------------------------------------------------------
for (unsigned int i = 0; i < size; ++i)
{
AtomType mean = distrib.mean()[i];
AtomType variance = distrib.variance()[i];
AtomType random = rng.normal(mean, variance);
assert(variance >= 0);
solution.push_back(random);
}
//-------------------------------------------------------------
return solution;
}
};
#endif // !_edoSamplerNormalMono_h