3067f3f8e4
Refactor distribution, sampler and estimator related to the multi-binomial distribution. This introduce tomic methods which may be overloaded for data structures more complex than eoReal of vector of bool (the default implentation).
97 lines
2.8 KiB
C++
97 lines
2.8 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) 2013 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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*/
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#ifndef _edoSamplerBinomialMulti_h
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#define _edoSamplerBinomialMulti_h
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#include <utils/eoRNG.h>
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#include "edoSampler.h"
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#include "edoBinomialMulti.h"
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#ifdef WITH_EIGEN
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#include <Eigen/Dense>
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/** A sampler for an edoBinomialMulti distribution.
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*
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* @ingroup Samplers
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* @ingroup Binomial
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*/
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template< class EOT, class D = edoBinomialMulti<EOT> >
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class edoSamplerBinomialMulti : public edoSampler<D>
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{
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public:
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typedef typename EOT::AtomType AtomType;
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/** Called if the sampler draw the item at (i,j)
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*
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* The default implementation is to push back a true boolean.
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* If you have a more complex data structure, you can just overload this.
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*/
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virtual void make_true( AtomType & atom, unsigned int i, unsigned int j )
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{
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atom.push_back( 1 );
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}
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/** @see make_true */
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virtual void make_false( AtomType & atom, unsigned int i, unsigned int j )
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{
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atom.push_back( 0 );
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}
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EOT sample( D& distrib )
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{
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unsigned int rows = distrib.rows();
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unsigned int cols = distrib.cols();
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assert(rows > 0);
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assert(cols > 0);
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// The point we want to draw
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// X = {x1, x2, ..., xn}
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// with xn a container of booleans
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EOT solution;
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// Sampling all dimensions
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for( unsigned int i = 0; i < rows; ++i ) {
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AtomType atom;
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for( unsigned int j = 0; j < cols; ++j ) {
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// Toss a coin, biased by the proba of being 1.
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if( rng.flip( distrib(i,j) ) ) {
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make_true( atom, i, j );
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} else {
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make_false( atom, i, j );
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}
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}
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solution.push_back( atom );
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}
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return solution;
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}
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};
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#endif // WITH_EIGEN
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#endif // !_edoSamplerBinomialMulti_h
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