move edo stuff, that was in the wriong place after the merge, in the edo directory
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Johann Dreo
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174
edo/src/edoSamplerNormalMulti.h
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174
edo/src/edoSamplerNormalMulti.h
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/*
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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 _edoSamplerNormalMulti_h
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#define _edoSamplerNormalMulti_h
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#include <edoSampler.h>
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#include <boost/numeric/ublas/lu.hpp>
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#include <boost/numeric/ublas/symmetric.hpp>
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template< class EOT >
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class edoSamplerNormalMulti : public edoSampler< edoNormalMulti< EOT > >
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{
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public:
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typedef typename EOT::AtomType AtomType;
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class Cholesky
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{
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public:
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Cholesky( const ublas::symmetric_matrix< AtomType, ublas::lower >& V)
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{
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unsigned int Vl = V.size1();
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assert(Vl > 0);
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unsigned int Vc = V.size2();
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assert(Vc > 0);
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assert( Vl == Vc );
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_L.resize(Vl, Vc);
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unsigned int i,j,k;
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// first column
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i=0;
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// diagonal
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j=0;
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_L(0, 0) = sqrt( V(0, 0) );
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// end of the column
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for ( j = 1; j < Vc; ++j )
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{
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_L(j, 0) = V(0, j) / _L(0, 0);
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}
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// end of the matrix
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for ( i = 1; i < Vl; ++i ) // each column
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{
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// diagonal
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double sum = 0.0;
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for ( k = 0; k < i; ++k)
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{
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sum += _L(i, k) * _L(i, k);
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}
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_L(i,i) = sqrt( fabs( V(i,i) - sum) );
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for ( j = i + 1; j < Vl; ++j ) // rows
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{
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// one element
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sum = 0.0;
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for ( k = 0; k < i; ++k )
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{
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sum += _L(j, k) * _L(i, k);
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}
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_L(j, i) = (V(j, i) - sum) / _L(i, i);
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}
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}
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}
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const ublas::symmetric_matrix< AtomType, ublas::lower >& get_L() const {return _L;}
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private:
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ublas::symmetric_matrix< AtomType, ublas::lower > _L;
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};
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edoSamplerNormalMulti( edoBounder< EOT > & bounder )
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: edoSampler< edoNormalMulti< EOT > >( bounder )
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{}
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EOT sample( edoNormalMulti< EOT >& 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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// Cholesky factorisation gererating matrix L from covariance
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// matrix V.
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// We must use cholesky.get_L() to get the resulting matrix.
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//
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// L = cholesky decomposition of varcovar
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//-------------------------------------------------------------
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Cholesky cholesky( distrib.varcovar() );
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ublas::symmetric_matrix< AtomType, ublas::lower > L = cholesky.get_L();
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//-------------------------------------------------------------
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//-------------------------------------------------------------
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// T = vector of size elements drawn in N(0,1) rng.normal(1.0)
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//-------------------------------------------------------------
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ublas::vector< AtomType > T( size );
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for ( unsigned int i = 0; i < size; ++i )
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{
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T( i ) = rng.normal( 1.0 );
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}
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//-------------------------------------------------------------
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//-------------------------------------------------------------
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// LT = prod( L, T )
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//-------------------------------------------------------------
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ublas::vector< AtomType > LT = ublas::prod( L, T );
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//-------------------------------------------------------------
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//-------------------------------------------------------------
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// solution = means + LT
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//-------------------------------------------------------------
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ublas::vector< AtomType > mean = distrib.mean();
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ublas::vector< AtomType > ublas_solution = mean + LT;
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EOT solution( size );
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std::copy( ublas_solution.begin(), ublas_solution.end(), solution.begin() );
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//-------------------------------------------------------------
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return solution;
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}
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};
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#endif // !_edoSamplerNormalMulti_h
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