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).
66 lines
1.9 KiB
C++
66 lines
1.9 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 _edoBinomialMulti_h
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#define _edoBinomialMulti_h
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#include "edoBinomial.h"
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#ifdef WITH_EIGEN // FIXME: provide an uBLAS implementation
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#include <Eigen/Dense>
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/** A 2D binomial distribution modeled as a matrix.
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*
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* i.e. a container of binomial distribution.
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*
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* @ingroup Distributions
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* @ingroup Binomial
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*/
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template<class EOT, class T=Eigen::MatrixXd>
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class edoBinomialMulti : public edoDistrib<EOT>, public T
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{
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public:
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/** This constructor takes an initial matrix of probabilities.
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* Use it if you have prior knowledge.
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*/
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edoBinomialMulti( T initial_probas )
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: T(initial_probas) {}
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/** Initialize all the probabilities to a constant
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*
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* 0.5 by default
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*/
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edoBinomialMulti( unsigned int rows, unsigned int cols, double proba=0.5 )
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: T::Constant(rows,cols,proba) {}
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/** Constructor without any assumption.
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*/
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edoBinomialMulti() {}
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};
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#endif // WITH_EIGEN
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#endif // !_edoBinomialMulti_h
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