src/gromacs/random/uniformrealdistribution.h

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  35
  36 /*! \file
  37  * \brief The uniform real distribution
  38  *
  39  * Portable version of the uniform real 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_UNIFORMREALDISTRIBUTION_H
  49 #define GMX_RANDOM_UNIFORMREALDISTRIBUTION_H
  50
  51 #include <cmath>
  52
  53 #include <algorithm>
  54 #include <limits>
  55 #include <type_traits>
  56
  57 #include "gromacs/math/functions.h"
  58 #include "gromacs/utility/basedefinitions.h"
  59 #include "gromacs/utility/classhelpers.h"
  60 #include "gromacs/utility/gmxassert.h"
  61 #include "gromacs/utility/real.h"
  62
  63 /*
  64  * The portable version of the uniform real distribution (to make sure we get
  65  * the same values on all platforms) has been modified from the LLVM libcxx
  66  * headers, distributed under the MIT license:
  67  *
  68  * Copyright (c) The LLVM compiler infrastructure
  69  *
  70  * Permission is hereby granted, free of charge, to any person obtaining a copy
  71  * of this software and associated documentation files (the "Software"), to deal
  72  * in the Software without restriction, including without limitation the rights
  73  * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
  74  * copies of the Software, and to permit persons to whom the Software is
  75  * furnished to do so, subject to the following conditions:
  76  *
  77  * The above copyright notice and this permission notice shall be included in
  78  * all copies or substantial portions of the Software.
  79  *
  80  * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
  81  * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
  82  * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
  83  * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
  84  * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
  85  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
  86  * THE SOFTWARE.
  87  */
  88
  89 namespace gmx
  90 {
  91
  92 /*! \brief Generate a floating-point value with specified number of random bits
  93  *
  94  * \tparam RealType  Floating-point type to generate
  95  * \tparam Bits      Number of random bits to generate
  96  * \tparam Rng       Random number generator class
  97  *
  98  * \param  g         Random number generator to use
  99  *
 100  * This implementation avoids the bug in libc++ and stdlibc++ (which is due
 101  * to the C++ standard being unclear) where 1.0 can be returned occasionally.
 102  *
 103  */
 104 template<class RealType = real, unsigned int Bits, class Rng>
 105 RealType generateCanonical(Rng& g)
 106 {
 107     // No point in using more bits than fit in RealType
 108     const uint64_t digits   = std::numeric_limits<RealType>::digits;
 109     const uint64_t realBits = std::min(digits, static_cast<uint64_t>(Bits));
 110     const uint64_t range    = Rng::max() - Rng::min() + uint64_t(1);
 111     uint64_t       log2R    = (range == 0) ? std::numeric_limits<uint64_t>::digits : log2I(range);
 112     uint64_t       k        = realBits / log2R + (realBits % log2R != 0) + (realBits == 0);
 113     // Note that Rng::max and Rng::min are typically an integer type.
 114     // Only unsigned integer types can express the range using the
 115     // same type. Converting to RealType before computing the range
 116     // would work but we have no need for that.
 117     static_assert(std::is_unsigned<decltype(Rng::max())>::value
 118                           && std::is_unsigned<decltype(Rng::min())>::value,
 119                   "Rng::max and Rng::min must be unsigned");
 120     RealType r    = RealType(Rng::max() - Rng::min()) + RealType(1);
 121     RealType s    = g() - Rng::min();
 122     RealType base = r;
 123     RealType result;
 124
 125     for (uint64_t i = 1; i < k; ++i)
 126     {
 127         s += RealType(g() - Rng::min()) * base;
 128         base *= r;
 129     }
 130     result = s / base;
 131
 132     // This implementation is specified by the C++ standard, but unfortunately it
 133     // has a bug where 1.0 can be generated occasionally due to the limited
 134     // precision of floating point, while 0.0 is only generated half as often as
 135     // it should. We "solve" both these issues by swapping 1.0 for 0.0 when it happens.
 136     //
 137     // See:
 138     // https://llvm.org/bugs/show_bug.cgi?id=18767
 139     // https://gcc.gnu.org/bugzilla/show_bug.cgi?id=63176
 140     //
 141     // Note that we prefer not to use the gcc 'fix' of looping until the result
 142     // is smaller than 1.0, since that breaks the strict specification of the
 143     // number of times the rng will be called.
 144     //
 145     // This can only happen when we ask for the same number of bits that fit
 146     // in RealType, so by checking for that we avoid the extra code in all other
 147     // cases. If you are worried about it: Use RealType=double with 32 bits.
 148     //
 149     if (realBits == digits && result == 1.0)
 150     {
 151         result = 0.0;
 152     }
 153     return result;
 154 }
 155
 156
 157 /*! \brief Uniform real distribution
 158  *
 159  *  The C++ standard library does provide this distribution, but even
 160  *  though they all sample from the correct distribution different standard
 161  *  library implementations appear to return different sequences of numbers
 162  *  for the same random number generator. To make it easier to use GROMACS
 163  *  unit tests that depend on random numbers we have our own implementation.
 164  *
 165  * \tparam RealType Floating-point type, real by default in GROMACS.
 166  */
 167 template<class RealType = real>
 168 class UniformRealDistribution
 169 {
 170 public:
 171     /*! \brief Type of values returned */
 172     typedef RealType result_type;
 173
 174     /*! \brief Uniform real distribution parameters */
 175     class param_type
 176     {
 177         /*! \brief Lower end of range (inclusive) */
 178         result_type a_;
 179         /*! \brief Upper end of range (exclusive) */
 180         result_type b_;
 181
 182     public:
 183         /*! \brief Reference back to the distribution class */
 184         typedef UniformRealDistribution distribution_type;
 185
 186         /*! \brief Construct parameter block
 187          *
 188          * \param a   Lower end of range (inclusive)
 189          * \param b   Upper end of range (exclusive)
 190          */
 191         explicit param_type(result_type a = 0.0, result_type b = 1.0) : a_(a), b_(b)
 192         {
 193             GMX_RELEASE_ASSERT(a < b, "The uniform real distribution requires a<b");
 194         }
 195
 196         /*! \brief Return first parameter */
 197         result_type a() const { return a_; }
 198         /*! \brief Return second parameter */
 199         result_type b() const { return b_; }
 200
 201         /*! \brief True if two parameter sets will return the same uniform real distribution.
 202          *
 203          * \param x  Instance to compare with.
 204          */
 205         bool operator==(const param_type& x) const { return a_ == x.a_ && b_ == x.b_; }
 206
 207         /*! \brief True if two parameter sets will return different uniform real distributions
 208          *
 209          * \param x  Instance to compare with.
 210          */
 211         bool operator!=(const param_type& x) const { return !operator==(x); }
 212     };
 213
 214 public:
 215     /*! \brief Construct new distribution with given floating-point parameters.
 216      *
 217      * \param a   Lower end of range (inclusive)
 218      * \param b   Upper end of range (exclusive)
 219      */
 220     explicit UniformRealDistribution(result_type a = 0.0, result_type b = 1.0) :
 221         param_(param_type(a, b))
 222     {
 223     }
 224
 225     /*! \brief Construct new distribution from parameter class
 226      *
 227      * \param param  Parameter class as defined inside gmx::UniformRealDistribution.
 228      */
 229     explicit UniformRealDistribution(const param_type& param) : param_(param) {}
 230
 231     /*! \brief Flush all internal saved values  */
 232     void reset() {}
 233
 234     /*! \brief Return values from uniform real distribution with internal parameters
 235      *
 236      * \tparam Rng  Random engine class
 237      *
 238      * \param  g    Random engine
 239      */
 240     template<class Rng>
 241     result_type operator()(Rng& g)
 242     {
 243         return (*this)(g, param_);
 244     }
 245
 246     /*! \brief Return value from uniform real distribution with given parameters
 247      *
 248      * \tparam Rng   Random engine class
 249      *
 250      * \param  g     Random engine
 251      * \param  param Parameters to use
 252      */
 253     template<class Rng>
 254     result_type operator()(Rng& g, const param_type& param)
 255     {
 256         result_type r = generateCanonical<RealType, std::numeric_limits<RealType>::digits>(g);
 257         return (param.b() - param.a()) * r + param.a();
 258     }
 259
 260     /*! \brief Return the lower range uniform real distribution */
 261     result_type a() const { return param_.a(); }
 262
 263     /*! \brief Return the upper range of the uniform real distribution */
 264     result_type b() const { return param_.b(); }
 265
 266     /*! \brief Return the full parameter class of the uniform real distribution */
 267     param_type param() const { return param_; }
 268
 269     /*! \brief Smallest value that can be returned from uniform real distribution */
 270     result_type min() const { return a(); }
 271
 272     /*! \brief Largest value that can be returned from uniform real distribution */
 273     result_type max() const { return b(); }
 274
 275     /*! \brief True if two uniform real distributions will produce the same values.
 276      *
 277      * \param  x     Instance to compare with.
 278      */
 279     bool operator==(const UniformRealDistribution& x) const { return param_ == x.param_; }
 280
 281     /*! \brief True if two uniform real distributions will produce different values.
 282      *
 283      * \param  x     Instance to compare with.
 284      */
 285     bool operator!=(const UniformRealDistribution& x) const { return !operator==(x); }
 286
 287 private:
 288     /*! \brief Internal value for parameters, can be overridden at generation time. */
 289     param_type param_;
 290
 291     GMX_DISALLOW_COPY_AND_ASSIGN(UniformRealDistribution);
 292 };
 293
 294 } // namespace gmx
 295
 296 #endif // GMX_RANDOM_UNIFORMREALDISTRIBUTION_H