src/gromacs/random/normaldistribution.h

   1 /*
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  35
  36 /*! \file
  37  * \brief The normal distribution
  38  *
  39  * Portable version of the normal distribution that generates the same sequence
  40  * on all platforms. Since stdlibc++ and libc++ provide different sequences
  41  * we prefer this one so unit tests produce the same values on all platforms.
  42  *
  43  * \author Erik Lindahl <erik.lindahl@gmail.com>
  44  * \inpublicapi
  45  * \ingroup module_random
  46  */
  47
  48 #ifndef GMX_RANDOM_NORMALDISTRIBUTION_H
  49 #define GMX_RANDOM_NORMALDISTRIBUTION_H
  50
  51 #include <cmath>
  52
  53 #include <limits>
  54
  55 #include "gromacs/random/uniformrealdistribution.h"
  56 #include "gromacs/utility/classhelpers.h"
  57
  58 /*
  59  * The portable version of the normal distribution (to make sure we get the same
  60  * values on all platforms) has been modified from the LLVM libcxx headers,
  61  * distributed under the MIT license:
  62  *
  63  * Copyright (c) The LLVM compiler infrastructure
  64  *
  65  * Permission is hereby granted, free of charge, to any person obtaining a copy
  66  * of this software and associated documentation files (the "Software"), to deal
  67  * in the Software without restriction, including without limitation the rights
  68  * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
  69  * copies of the Software, and to permit persons to whom the Software is
  70  * furnished to do so, subject to the following conditions:
  71  *
  72  * The above copyright notice and this permission notice shall be included in
  73  * all copies or substantial portions of the Software.
  74  *
  75  * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
  76  * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
  77  * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
  78  * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
  79  * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
  80  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
  81  * THE SOFTWARE.
  82  */
  83
  84 namespace gmx
  85 {
  86
  87 /*! \brief Normal distribution
  88  *
  89  *  The C++ standard library does provide a normal distribution, but even
  90  *  though they all sample from the normal distribution different standard
  91  *  library implementations appear to return different sequences of numbers
  92  *  for the same random number generator. To make it easier to use GROMACS
  93  *  unit tests that depend on random numbers we have our own implementation.
  94  *
  95  *  Be warned that the normal distribution draws values from the random engine
  96  *  in a loop, so you want to make sure you use a random stream with a
  97  *  very large margin to make sure you do not run out of random numbers
  98  *  in an unlucky case (which will lead to an exception with the GROMACS
  99  *  default random engine).
 100  *
 101  * \tparam RealType Floating-point type, real by default in GROMACS.
 102  */
 103 template<class RealType = real>
 104 class NormalDistribution
 105 {
 106 public:
 107     /*! \brief Type of values returned */
 108     typedef RealType result_type;
 109
 110     /*! \brief Normal distribution parameters */
 111     class param_type
 112     {
 113         /*! \brief Mean of normal distribution */
 114         result_type mean_;
 115         /*! \brief Standard deviation of distribution */
 116         result_type stddev_;
 117
 118     public:
 119         /*! \brief Reference back to the distribution class */
 120         typedef NormalDistribution distribution_type;
 121
 122         /*! \brief Construct parameter block
 123          *
 124          * \param mean     Mean of normal distribution
 125          * \param stddev   Standard deviation of normal distribution
 126          */
 127         explicit param_type(result_type mean = 0.0, result_type stddev = 1.0) :
 128             mean_(mean),
 129             stddev_(stddev)
 130         {
 131         }
 132
 133         /*! \brief Return first parameter */
 134         result_type mean() const { return mean_; }
 135         /*! \brief Return second parameter */
 136         result_type stddev() const { return stddev_; }
 137
 138         /*! \brief True if two parameter sets will return the same normal distribution.
 139          *
 140          * \param x  Instance to compare with.
 141          */
 142         bool operator==(const param_type& x) const
 143         {
 144             return mean_ == x.mean_ && stddev_ == x.stddev_;
 145         }
 146
 147         /*! \brief True if two parameter sets will return different normal distributions
 148          *
 149          * \param x  Instance to compare with.
 150          */
 151         bool operator!=(const param_type& x) const { return !operator==(x); }
 152     };
 153
 154 public:
 155     /*! \brief Construct new distribution with given floating-point parameters.
 156      *
 157      * \param mean     Mean of normal distribution
 158      * \param stddev   Standard deviation of normal distribution
 159      */
 160     explicit NormalDistribution(result_type mean = 0.0, result_type stddev = 1.0) :
 161         param_(param_type(mean, stddev)),
 162         hot_(false),
 163         saved_(0)
 164     {
 165     }
 166
 167     /*! \brief Construct new distribution from parameter class
 168      *
 169      * \param param  Parameter class as defined inside gmx::NormalDistribution.
 170      */
 171     explicit NormalDistribution(const param_type& param) : param_(param), hot_(false), saved_(0) {}
 172
 173     /*! \brief Flush all internal saved values  */
 174     void reset() { hot_ = false; }
 175
 176     /*! \brief Return values from normal distribution with internal parameters
 177      *
 178      *  \tparam Rng   Random engine class
 179      *
 180      *  \param  g     Random engine
 181      */
 182     template<class Rng>
 183     result_type operator()(Rng& g)
 184     {
 185         return (*this)(g, param_);
 186     }
 187
 188     /*! \brief Return value from normal distribution with given parameters
 189      *
 190      *  \tparam Rng   Random engine class
 191      *
 192      *  \param  g     Random engine
 193      *  \param  param Parameters to use
 194      */
 195     template<class Rng>
 196     result_type operator()(Rng& g, const param_type& param)
 197     {
 198         result_type result;
 199
 200         if (hot_)
 201         {
 202             hot_   = false;
 203             result = saved_;
 204         }
 205         else
 206         {
 207             UniformRealDistribution<result_type> uniformDist(-1.0, 1.0);
 208             result_type                          u;
 209             result_type                          v;
 210             result_type                          s;
 211
 212             do
 213             {
 214                 u = uniformDist(g);
 215                 v = uniformDist(g);
 216                 s = u * u + v * v;
 217             } while (s > 1.0 || s == 0.0);
 218
 219             s      = std::sqrt(-2.0 * std::log(s) / s);
 220             saved_ = v * s;
 221             hot_   = true;
 222             result = u * s;
 223         }
 224         return result * param.stddev() + param.mean();
 225     }
 226
 227     /*! \brief Return the mean of the normal distribution */
 228     result_type mean() const { return param_.mean(); }
 229
 230     /*! \brief Return the standard deviation of the normal distribution */
 231     result_type stddev() const { return param_.stddev(); }
 232
 233     /*! \brief Return the full parameter class of the normal distribution */
 234     param_type param() const { return param_; }
 235
 236     /*! \brief Smallest value that can be returned from normal distribution */
 237     result_type min() const { return -std::numeric_limits<result_type>::infinity(); }
 238
 239     /*! \brief Largest value that can be returned from normal distribution */
 240     result_type max() const { return std::numeric_limits<result_type>::infinity(); }
 241
 242     /*! \brief True if two normal distributions will produce the same values.
 243      *
 244      * \param  x     Instance to compare with.
 245      */
 246     bool operator==(const NormalDistribution& x) const
 247     {
 248         /* Equal if: Params are identical, and saved-state is identical,
 249          * and if we have something saved, it must be identical.
 250          */
 251         return param_ == x.param_ && hot_ == x.hot_ && (!hot_ || saved_ == x.saved_);
 252     }
 253
 254     /*! \brief True if two normal distributions will produce different values.
 255      *
 256      * \param  x     Instance to compare with.
 257      */
 258     bool operator!=(const NormalDistribution& x) const { return !operator==(x); }
 259
 260 private:
 261     /*! \brief Internal value for parameters, can be overridden at generation time. */
 262     param_type param_;
 263     /*! \brief True if there is a saved result to return */
 264     bool hot_;
 265     /*! \brief The saved result to return - only valid if hot_ is true */
 266     result_type saved_;
 267
 268     GMX_DISALLOW_COPY_AND_ASSIGN(NormalDistribution);
 269 };
 270
 271
 272 } // namespace gmx
 273
 274 #endif // GMX_RANDOM_NORMALDISTRIBUTION_H