/* 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) 2013 Thales group */ /* Authors: Johann Dréo */ #ifndef _edoSamplerBinomialMulti_h #define _edoSamplerBinomialMulti_h #include #include "edoSampler.h" #include "edoBinomialMulti.h" #ifdef WITH_EIGEN #include /** A sampler for an edoBinomialMulti distribution. * * @ingroup Samplers * @ingroup Binomial */ template< class EOT, class D = edoBinomialMulti > class edoSamplerBinomialMulti : public edoSampler { public: typedef typename EOT::AtomType AtomType; /** Called if the sampler draw the item at (i,j) * * The default implementation is to push back a true boolean. * If you have a more complex data structure, you can just overload this. */ virtual void make_true( AtomType & atom, unsigned int i, unsigned int j ) { atom.push_back( 1 ); } /** @see make_true */ virtual void make_false( AtomType & atom, unsigned int i, unsigned int j ) { atom.push_back( 0 ); } EOT sample( D& distrib ) { unsigned int rows = distrib.rows(); unsigned int cols = distrib.cols(); assert(rows > 0); assert(cols > 0); // The point we want to draw // X = {x1, x2, ..., xn} // with xn a container of booleans EOT solution; // Sampling all dimensions for( unsigned int i = 0; i < rows; ++i ) { AtomType atom; for( unsigned int j = 0; j < cols; ++j ) { // Toss a coin, biased by the proba of being 1. if( rng.flip( distrib(i,j) ) ) { make_true( atom, i, j ); } else { make_false( atom, i, j ); } } solution.push_back( atom ); } return solution; } }; #endif // WITH_EIGEN #endif // !_edoSamplerBinomialMulti_h