Normal.h

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/*!
 * 
 *
 * \brief       Implements a univariate normal 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_NORMAL_H
#define SHARK_RNG_NORMAL_H

#include "shark/Core/Math.h"
#include "shark/Rng/AbstractDistribution.h"
#include "shark/Rng/Rng.h"

#include <boost/math/special_functions.hpp>
#include <boost/random.hpp>

#include <cmath>

namespace shark {

/// \brief Implements a univariate normal (Gaussian) distribution.
///
/// For backwards compatibility with older shark versions
/// instead of the standard deviation sigma the
/// variance=sigma^2 is used as argument.
template<typename RngType = DefaultRngType>
class Normal
:
    public AbstractDistribution,
    public boost::variate_generator<RngType*, boost::normal_distribution<> >
{
private:
    typedef boost::variate_generator<RngType*, boost::normal_distribution<> > Base;

public:
    /// constructor
    /// \param rng: random number generator
    /// \param mean: mean of distribution
    /// \param variance: variance of distribution
    Normal( RngType & rng, double mean = 0., double variance =1. )
        :Base(&rng,boost::normal_distribution<>(mean,std::sqrt(variance)))
    {}

    using Base::operator();

    double operator()(double mean,double variance)
    {
        boost::normal_distribution<> dist(mean,std::sqrt(variance));
        return dist(Base::engine());
    }

    double mean()const
    {
        return Base::distribution().mean();
    }

    double variance()const
    {
        return Base::distribution().sigma() * Base::distribution().sigma();
    }

    void mean(double newMean)
    {
        Base::distribution() = boost::normal_distribution<>(newMean, Base::distribution().sigma());
    }

    void variance(double newVariance)
    {
        Base::distribution() = boost::normal_distribution<>(mean(), std::sqrt(newVariance));
    }

    double p(double x) const
    {
        const double standardDeviation = Base::distribution().sigma();
        return std::exp(-sqr((x - mean()) / standardDeviation) / 2.0) / (SQRT_2_PI * standardDeviation);
    }

    double logP(double x) const
    {
        const double standardDeviation = Base::distribution().sigma();
        return (-sqr((x - mean()) / standardDeviation) / 2.0) - safeLog(SQRT_2_PI * standardDeviation);
    }
};

///\brief Draws a number from the normal distribution with given mean and variance by drawing random numbers from rng.
template<class RngType>
double gauss(RngType& rng, double mean, double variance){
    Normal<RngType> dist(rng, mean, variance);
    return dist();
}


} // namespace shark {

#endif // SHARK_RNG_NORMAL_H