NegExponential.h

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/*!
 * 
 *
 * \brief       Implements the negative exponential distribution
 * 
 * 
 *
 * \author      O. Krause
 * \date        2010-01-01
 *
 *
 * \par Copyright 1995-2017 Shark Development Team
 * 
 * <BR><HR>
 * This file is part of Shark.
 * <http://shark-ml.org/>
 * 
 * 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_NEGEXPONENTIAL_H
#define SHARK_RNG_NEGEXPONENTIAL_H




#include <boost/random/exponential_distribution.hpp>

#include <cmath>

namespace shark{

    ///\brief Implements the Negative exponential distribution.
    ///
    /// It's propability distribution is defined as
    /// \f[ p(x) = e^{-\lambda x}\f]
    /// Instead of lambda, we define the exponential distribution using the mean 
    /// \f[ \mu = 1.0/\lambda \f]
    template<typename RngType = shark::DefaultRngType>
    class NegExponential:public boost::variate_generator<RngType*,boost::exponential_distribution<> >
    {
    private:
        typedef boost::variate_generator<RngType*,boost::exponential_distribution<> > Base;
    public:
    
        NegExponential( RngType & rng, double mean = 0 )
            :Base(&rng,boost::exponential_distribution<>(1.0/mean))
        {}

        using Base::operator();

        ///\brief Draws a random number from the negative exponential distribution with the mean defined in the argument
        ///
        ///\param mean: the mean of the distribution from which the number is drawn
        double operator()(double mean)
        {
            boost::exponential_distribution<> dist(1.0/mean);
            return dist(Base::engine());
        }

        ///\brief Returns the mean of the negative exponential distribution
        double mean()const
        {
            return 1.0/Base::distribution().lambda();
        }
        ///\brief Sets the mean of the negative exponential distribution
        ///
        ///\param newMean the new Mean value
        void mean(double newMean)
        {
            Base::distribution()=boost::exponential_distribution<>(1.0/newMean);
        }

        double p(double x)
        {
            return x >= 0 ? Base::distribution().lambda() * exp(- Base::distribution().lambda() * x) : 0.;
        }

    };
}
#endif