Merge branch release-2016

[gromacs.git] / src / gromacs / random / gammadistribution.h

/*
 * This file is part of the GROMACS molecular simulation package.
 *
 * Copyright (c) 2015,2016, by the GROMACS development team, led by
 * Mark Abraham, David van der Spoel, Berk Hess, and Erik Lindahl,
 * and including many others, as listed in the AUTHORS file in the
 * top-level source directory and at http://www.gromacs.org.
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/*! \file
 * \brief The gamma distribution
 *
 * Portable version of the gamma distribution that generates the same sequence
 * on all platforms.
 *
 * \note The gamma distribution is broken in some standard library headers
 * (including those shipped with gcc-4.9), and it is not guaranteed to
 * generate the same result on stdlibc++ and libc++. Use this one instead so
 * our unit tests produce the same values on all platforms.
 *
 * \author Erik Lindahl <erik.lindahl@gmail.com>
 * \inpublicapi
 * \ingroup module_random
 */

#ifndef GMX_RANDOM_GAMMADISTRIBUTION_H
#define GMX_RANDOM_GAMMADISTRIBUTION_H

#include <cmath>

#include <limits>

#include "gromacs/random/exponentialdistribution.h"
#include "gromacs/random/uniformrealdistribution.h"
#include "gromacs/utility/classhelpers.h"

/*
 * The workaround implementation for the broken std::gamma_distribution in the
 * gcc-4.6 headers has been modified from the LLVM libcxx headers, distributed
 * under the MIT license:
 *
 * Copyright (c) The LLVM compiler infrastructure
 *
 * Permission is hereby granted, free of charge, to any person obtaining a copy
 * of this software and associated documentation files (the "Software"), to deal
 * in the Software without restriction, including without limitation the rights
 * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 * copies of the Software, and to permit persons to whom the Software is
 * furnished to do so, subject to the following conditions:
 *
 * The above copyright notice and this permission notice shall be included in
 * all copies or substantial portions of the Software.
 *
 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
 * THE SOFTWARE.
 */

namespace gmx
{

/*! \brief Gamma distribution
 *
 *  The C++ standard library does provide a gamma distribution, but when
 *  using libstdc++-4.4.7 with at least gcc-4.6 or icc-14.0 the headers
 *  produce errors. Even for newer compilers, libstdc++ and libc++ appear to
 *  use different algorithms to generate it, which means their values differ
 *  in contrast to the uniform and normal distributions where they are
 *  identical. To avoid both compiler bugs and make it easier to use
 *  GROMACS unit tests that depend on random numbers, we have our
 *  own implementation.
 *
 *  Be warned that the gamma distribution works like the standard
 *  normal distribution and keeps drawing values from the random engine
 *  in a loop, so you want to make sure you use a random stream with a
 *  very large margin to make sure you do not run out of random numbers
 *  in an unlucky case (which will lead to an exception with the GROMACS
 *  default random engine).
 *
 *  The gamma distribution is defined as
 *
 * \f[
 *     p(x|\alpha,\beta) = \frac{1}{\Gamma(\alpha)\beta^{alpha}} x^{\alpha - 1} e^{-\frac{x}{\beta}}, x\geq 0
 * \f]
 *
 * \tparam RealType Floating-point type, real by default in GROMACS.
 */
template<class RealType = real>
class GammaDistribution
{
    public:
        /*! \brief Type of values returned */
        typedef RealType result_type;

        /*! \brief Gamma distribution parameters */
        class param_type
        {
            /*! \brief First parameter of gamma distribution */
            result_type  alpha_;
            /*! \brief Second parameter of gamma distribution */
            result_type  beta_;

            public:
                /*! \brief Reference back to the distribution class */
                typedef GammaDistribution distribution_type;

                /*! \brief Construct parameter block
                 *
                 * \param alpha  First parameter of gamma distribution
                 * \param beta   Second parameter of gamma distribution
                 */
                explicit param_type(result_type alpha = 1.0, result_type beta = 1.0)
                    : alpha_(alpha), beta_(beta) {}

                /*! \brief Return first parameter */
                result_type alpha() const { return alpha_; }
                /*! \brief Return second parameter */
                result_type beta()  const { return beta_; }

                /*! \brief True if two parameter sets will return the same distribution.
                 *
                 * \param x  Instance to compare with.
                 */
                bool
                operator==(const param_type &x) const
                {
                    return alpha_ == x.alpha_ && beta_ == x.beta_;
                }

                /*! \brief True if two parameter sets will return different distributions
                 *
                 * \param x  Instance to compare with.
                 */
                bool
                operator!=(const param_type &x) const { return !operator==(x); }
        };

    public:

        /*! \brief Construct new distribution with given floating-point parameters.
         *
         * \param alpha  First parameter of gamma distribution
         * \param beta   Second parameter of gamma distribution
         */
        explicit GammaDistribution(result_type alpha = 1.0, result_type beta = 1.0)
            : param_(param_type(alpha, beta)) {}

        /*! \brief Construct new distribution from parameter class
         *
         * \param param  Parameter class as defined inside gmx::GammaDistribution.
         */
        explicit GammaDistribution(const param_type &param) : param_(param) {}

        /*! \brief Flush all internal saved values  */
        void
        reset() {}

        /*! \brief Return values from gamma distribution with internal parameters
         *
         *  \tparam Rng   Random engine class
         *
         *  \param  g     Random engine
         */
        template<class Rng>
        result_type
        operator()(Rng &g) { return (*this)(g, param_); }

        /*! \brief Return value from gamma distribution with given parameters
         *
         *  \tparam Rng   Random engine class
         *
         *  \param  g     Random engine
         *  \param  param Parameters to use
         */
        template<class Rng>
        result_type
        operator()(Rng &g, const param_type &param)
        {
            result_type                            alpha = param.alpha();
            UniformRealDistribution<result_type>   uniformDist(0, 1);
            ExponentialDistribution<result_type>   expDist;

            result_type x;

            if (alpha == 1.0)
            {
                x = expDist(g);
            }
            else if (alpha > 1.0)
            {
                const result_type b = alpha - 1.0;
                const result_type c = 3.0 * alpha - result_type(0.75);

                while (true)
                {
                    const result_type u = uniformDist(g);
                    const result_type v = uniformDist(g);
                    const result_type w = u * (1 - u);

                    if (w != 0)
                    {
                        const result_type y = std::sqrt(c / w) *
                            (u - result_type(0.5));
                        x = b + y;

                        if (x >= 0)
                        {
                            const result_type z = 64 * w * w * w * v * v;

                            if (z <= 1.0 - 2.0 * y * y / x)
                            {
                                break;
                            }
                            if (std::log(z) <= 2.0 * (b * std::log(x / b) - y))
                            {
                                break;
                            }
                        }
                    }
                }
            }
            else  // __a < 1
            {
                while (true)
                {
                    const result_type u  = uniformDist(g);
                    const result_type es = expDist(g);

                    if (u <= 1.0 - alpha)
                    {
                        x = std::pow(u, 1.0 / alpha);

                        if (x <= es)
                        {
                            break;
                        }
                    }
                    else
                    {
                        const result_type e = -std::log((1.0 - u)/alpha);
                        x = std::pow(1.0 - alpha + alpha * e, 1.0 / alpha);

                        if (x <= e + es)
                        {
                            break;
                        }
                    }
                }
            }
            return x * param.beta();
        }

        /*! \brief Return the first parameter of gamma distribution */
        result_type
        alpha() const { return param_.alpha(); }

        /*! \brief Return the second parameter of gamma distribution */
        result_type
        beta() const { return param_.beta(); }

        /*! \brief Return the full parameter class of gamma distribution */
        param_type param() const { return param_; }

        /*! \brief Smallest value that can be returned from gamma distribution */
        result_type
        min() const { return 0; }

        /*! \brief Largest value that can be returned from gamma distribution */
        result_type
        max() const { return std::numeric_limits<result_type>::infinity(); }

        /*! \brief True if two gamma distributions will produce the same values.
         *
         * \param  x     Instance to compare with.
         */
        bool
        operator==(const GammaDistribution &x) const
        { return param_ == x.param_; }

        /*! \brief True if two gamma distributions will produce different values.
         *
         * \param  x     Instance to compare with.
         */
        bool
        operator!=(const GammaDistribution &x) const
        { return !operator==(x); }

    private:
        /*! \brief Internal value for parameters, can be overridden at generation time. */
        param_type param_;

        GMX_DISALLOW_COPY_AND_ASSIGN(GammaDistribution);
};

}      // namespace gmx

#endif // GMX_RANDOM_GAMMADISTRIBUTION_H