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), stddev_(stddev) {}
 129
 130                 /*! \brief Return first parameter */
 131                 result_type mean() const { return mean_; }
 132                 /*! \brief Return second parameter */
 133                 result_type stddev()  const { return stddev_; }
 134
 135                 /*! \brief True if two parameter sets will return the same normal distribution.
 136                  *
 137                  * \param x  Instance to compare with.
 138                  */
 139                 bool
 140                 operator==(const param_type &x) const
 141                 {
 142                     return mean_ == x.mean_ && stddev_ == x.stddev_;
 143                 }
 144
 145                 /*! \brief True if two parameter sets will return different normal distributions
 146                  *
 147                  * \param x  Instance to compare with.
 148                  */
 149                 bool
 150                 operator!=(const param_type &x) const { return !operator==(x); }
 151         };
 152
 153     public:
 154
 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)), hot_(false), saved_(0) {}
 162
 163         /*! \brief Construct new distribution from parameter class
 164          *
 165          * \param param  Parameter class as defined inside gmx::NormalDistribution.
 166          */
 167         explicit NormalDistribution(const param_type &param)
 168             : param_(param), hot_(false), saved_(0) {}
 169
 170         /*! \brief Flush all internal saved values  */
 171         void
 172         reset() { hot_ = false; }
 173
 174         /*! \brief Return values from normal distribution with internal parameters
 175          *
 176          *  \tparam Rng   Random engine class
 177          *
 178          *  \param  g     Random engine
 179          */
 180         template<class Rng>
 181         result_type
 182         operator()(Rng &g) { return (*this)(g, param_); }
 183
 184         /*! \brief Return value from normal distribution with given parameters
 185          *
 186          *  \tparam Rng   Random engine class
 187          *
 188          *  \param  g     Random engine
 189          *  \param  param Parameters to use
 190          */
 191         template<class Rng>
 192         result_type
 193         operator()(Rng &g, const param_type &param)
 194         {
 195             result_type result;
 196
 197             if (hot_)
 198             {
 199                 hot_   = false;
 200                 result = saved_;
 201             }
 202             else
 203             {
 204                 UniformRealDistribution<result_type> uniformDist(-1.0, 1.0);
 205                 result_type u;
 206                 result_type v;
 207                 result_type s;
 208
 209                 do
 210                 {
 211                     u = uniformDist(g);
 212                     v = uniformDist(g);
 213                     s = u * u + v * v;
 214                 }
 215                 while (s > 1.0 || s == 0.0);
 216
 217                 s      = std::sqrt(-2.0 * std::log(s) / s);
 218                 saved_ = v * s;
 219                 hot_   = true;
 220                 result = u * s;
 221             }
 222             return result * param.stddev() + param.mean();
 223         }
 224
 225         /*! \brief Return the mean of the normal distribution */
 226         result_type
 227         mean() const { return param_.mean(); }
 228
 229         /*! \brief Return the standard deviation of the normal distribution */
 230         result_type
 231         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
 238         min() const { return -std::numeric_limits<result_type>::infinity(); }
 239
 240         /*! \brief Largest value that can be returned from normal distribution */
 241         result_type
 242         max() const { return std::numeric_limits<result_type>::infinity(); }
 243
 244         /*! \brief True if two normal distributions will produce the same values.
 245          *
 246          * \param  x     Instance to compare with.
 247          */
 248         bool
 249         operator==(const NormalDistribution &x) const
 250         {
 251             /* Equal if: Params are identical, and saved-state is identical,
 252              * and if we have something saved, it must be identical.
 253              */
 254             return param_ == x.param_ && hot_ == x.hot_ && (!hot_ || saved_ == x.saved_);
 255         }
 256
 257         /*! \brief True if two normal distributions will produce different values.
 258          *
 259          * \param  x     Instance to compare with.
 260          */
 261         bool
 262         operator!=(const NormalDistribution &x) const
 263         { return !operator==(x); }
 264
 265     private:
 266         /*! \brief Internal value for parameters, can be overridden at generation time. */
 267         param_type  param_;
 268         /*! \brief True if there is a saved result to return */
 269         bool        hot_;
 270         /*! \brief The saved result to return - only valid if hot_ is true */
 271         result_type saved_;
 272
 273         GMX_DISALLOW_COPY_AND_ASSIGN(NormalDistribution);
 274 };
 275
 276
 277 }      // namespace gmx
 278
 279 #endif // GMX_RANDOM_NORMALDISTRIBUTION_H