/* 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 Caner Candan */ #ifndef _edoNormalMono_h #define _edoNormalMono_h #include "edoDistrib.h" /** @defgroup Mononormal Normal * A normal (Gaussian) distribution that only model variances of variables. * * @ingroup Distributions */ /** A normal (Gaussian) distribution that only model variances of variables. * * This is basically a mean vector and a variances vector. Do not model co-variances. * * @ingroup Distributions * @ingroup Mononormal */ template < typename EOT > class edoNormalMono : public edoDistrib< EOT > { public: edoNormalMono() : _mean(EOT(1,0)), _variance(EOT(1,1)) {} edoNormalMono( const EOT& mean, const EOT& variance ) : _mean(mean), _variance(variance) { assert(_mean.size() > 0); assert(_mean.size() == _variance.size()); } unsigned int size() { assert(_mean.size() == _variance.size()); return _mean.size(); } EOT mean(){return _mean;} EOT variance(){return _variance;} private: EOT _mean; EOT _variance; }; #endif // !_edoNormalMono_h