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*
*
* \brief Provides a function for estimating the entropy of a distribution.
*
*
*
* \author O. Krause
* \date 2010-01-01
*
*
* \par Copyright 1995-2015 Shark Development Team
*
* <BR><HR>
* This file is part of Shark.
* <http://image.diku.dk/shark/>
*
* Shark 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 3 of the License, or
* (at your option) any later version.
*
* Shark 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 Shark. If not, see <http://www.gnu.org/licenses/>.
*
*/
#ifndef SHARK_RNG_ENTROPY_H
#define SHARK_RNG_ENTROPY_H
#include <shark/Core/Exception.h>
namespace shark {
/**
* \brief Estimates the entropy of a distribution. The more trials the better is the estimate, but good estimates are slow.
*
* \tparam Distribution The type of distribution, needs to provide operator()() for sampling purposes.
* \param [in,out] d Distribution instance to sample from.
* \param [in] trials The number of samples drawn from the distribution. Needs to be larger than 0.
* \throws shark::Exception if trials == 0.
*/
template<typename Distribution>
double entropy( Distribution & d, std::size_t trials = 10000 ) {
if( trials == 0 )
throw( shark::Exception( "entropy: Trial count needs to be larger than 0.", __FILE__, __LINE__ ) );
double t = 0;
for ( unsigned int i = 0; i < trials; i++ ) {
t += ::log( d.p( d() ) );
}
return( -t / trials );
}
}
#endif
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