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1//  (C) Copyright John Maddock 2005-2006.2//  Use, modification and distribution are subject to the3//  Boost Software License, Version 1.0. (See accompanying file4//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)5 6#ifndef BOOST_MATH_LOG1P_INCLUDED7#define BOOST_MATH_LOG1P_INCLUDED8 9#ifdef _MSC_VER10#pragma once11#pragma warning(push)12#pragma warning(disable:4702) // Unreachable code (release mode only warning)13#endif14 15#if defined __has_include16#  if ((__cplusplus > 202002L) || (defined(_MSVC_LANG) && (_MSVC_LANG > 202002L)))17#    if __has_include (<stdfloat>)18#    include <stdfloat>19#    endif20#  endif21#endif22 23#include <boost/math/tools/config.hpp>24#include <boost/math/tools/series.hpp>25#include <boost/math/tools/rational.hpp>26#include <boost/math/tools/big_constant.hpp>27#include <boost/math/tools/numeric_limits.hpp>28#include <boost/math/tools/cstdint.hpp>29#include <boost/math/tools/promotion.hpp>30#include <boost/math/tools/precision.hpp>31#include <boost/math/policies/error_handling.hpp>32#include <boost/math/special_functions/math_fwd.hpp>33#include <boost/math/tools/assert.hpp>34#include <boost/math/special_functions/fpclassify.hpp>35 36#if defined(__GNUC__) && defined(BOOST_MATH_USE_FLOAT128)37//38// This is the only way we can avoid39// warning: non-standard suffix on floating constant [-Wpedantic]40// when building with -Wall -pedantic.  Neither __extension__41// nor #pragma diagnostic ignored work :(42//43#pragma GCC system_header44#endif45 46namespace boost{ namespace math{47 48namespace detail49{50  // Functor log1p_series returns the next term in the Taylor series51  //   pow(-1, k-1)*pow(x, k) / k52  // each time that operator() is invoked.53  //54  template <class T>55  struct log1p_series56  {57     typedef T result_type;58 59     BOOST_MATH_GPU_ENABLED log1p_series(T x)60        : k(0), m_mult(-x), m_prod(-1){}61 62     BOOST_MATH_GPU_ENABLED T operator()()63     {64        m_prod *= m_mult;65        return m_prod / ++k;66     }67 68     BOOST_MATH_GPU_ENABLED int count()const69     {70        return k;71     }72 73  private:74     int k;75     const T m_mult;76     T m_prod;77     log1p_series(const log1p_series&) = delete;78     log1p_series& operator=(const log1p_series&) = delete;79  };80 81// Algorithm log1p is part of C99, but is not yet provided by many compilers.82//83// This version uses a Taylor series expansion for 0.5 > x > epsilon, which may84// require up to std::numeric_limits<T>::digits+1 terms to be calculated.85// It would be much more efficient to use the equivalence:86//   log(1+x) == (log(1+x) * x) / ((1-x) - 1)87// Unfortunately many optimizing compilers make such a mess of this, that88// it performs no better than log(1+x): which is to say not very well at all.89//90template <class T, class Policy>91BOOST_MATH_GPU_ENABLED T log1p_imp(T const & x, const Policy& pol, const boost::math::integral_constant<int, 0>&)92{ // The function returns the natural logarithm of 1 + x.93   typedef typename tools::promote_args<T>::type result_type;94   BOOST_MATH_STD_USING95 96   constexpr auto function = "boost::math::log1p<%1%>(%1%)";97 98   if((x < -1) || (boost::math::isnan)(x))99      return policies::raise_domain_error<T>(function, "log1p(x) requires x > -1, but got x = %1%.", x, pol);100   if(x == -1)101      return -policies::raise_overflow_error<T>(function, nullptr, pol);102 103   result_type a = abs(result_type(x));104   if(a > result_type(0.5f))105      return log(1 + result_type(x));106   // Note that without numeric_limits specialisation support,107   // epsilon just returns zero, and our "optimisation" will always fail:108   if(a < tools::epsilon<result_type>())109      return x;110   detail::log1p_series<result_type> s(x);111   boost::math::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();112 113   result_type result = tools::sum_series(s, policies::get_epsilon<result_type, Policy>(), max_iter);114 115   policies::check_series_iterations<T>(function, max_iter, pol);116   return result;117}118 119template <class T, class Policy>120BOOST_MATH_GPU_ENABLED T log1p_imp(T const& x, const Policy& pol, const boost::math::integral_constant<int, 53>&)121{ // The function returns the natural logarithm of 1 + x.122   BOOST_MATH_STD_USING123 124   constexpr auto function = "boost::math::log1p<%1%>(%1%)";125 126   if(x < -1)127      return policies::raise_domain_error<T>(function, "log1p(x) requires x > -1, but got x = %1%.", x, pol);128   if(x == -1)129      return -policies::raise_overflow_error<T>(function, nullptr, pol);130 131   T a = fabs(x);132   if(a > 0.5f)133      return log(1 + x);134   // Note that without numeric_limits specialisation support,135   // epsilon just returns zero, and our "optimisation" will always fail:136   if(a < tools::epsilon<T>())137      return x;138 139   // Maximum Deviation Found:                     1.846e-017140   // Expected Error Term:                         1.843e-017141   // Maximum Relative Change in Control Points:   8.138e-004142   // Max Error found at double precision =        3.250766e-016143   BOOST_MATH_STATIC const T P[] = {144       static_cast<T>(0.15141069795941984e-16L),145       static_cast<T>(0.35495104378055055e-15L),146       static_cast<T>(0.33333333333332835L),147       static_cast<T>(0.99249063543365859L),148       static_cast<T>(1.1143969784156509L),149       static_cast<T>(0.58052937949269651L),150       static_cast<T>(0.13703234928513215L),151       static_cast<T>(0.011294864812099712L)152     };153   BOOST_MATH_STATIC const T Q[] = {154       static_cast<T>(1L),155       static_cast<T>(3.7274719063011499L),156       static_cast<T>(5.5387948649720334L),157       static_cast<T>(4.159201143419005L),158       static_cast<T>(1.6423855110312755L),159       static_cast<T>(0.31706251443180914L),160       static_cast<T>(0.022665554431410243L),161       static_cast<T>(-0.29252538135177773e-5L)162     };163 164   T result = 1 - x / 2 + tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);165   result *= x;166 167   return result;168}169 170template <class T, class Policy>171BOOST_MATH_GPU_ENABLED T log1p_imp(T const& x, const Policy& pol, const boost::math::integral_constant<int, 64>&)172{ // The function returns the natural logarithm of 1 + x.173   BOOST_MATH_STD_USING174 175   constexpr auto function = "boost::math::log1p<%1%>(%1%)";176 177   if(x < -1)178      return policies::raise_domain_error<T>(function, "log1p(x) requires x > -1, but got x = %1%.", x, pol);179   if(x == -1)180      return -policies::raise_overflow_error<T>(function, nullptr, pol);181 182   T a = fabs(x);183   if(a > 0.5f)184      return log(1 + x);185   // Note that without numeric_limits specialisation support,186   // epsilon just returns zero, and our "optimisation" will always fail:187   if(a < tools::epsilon<T>())188      return x;189 190   // Maximum Deviation Found:                     8.089e-20191   // Expected Error Term:                         8.088e-20192   // Maximum Relative Change in Control Points:   9.648e-05193   // Max Error found at long double precision =   2.242324e-19194   BOOST_MATH_STATIC const T P[] = {195      BOOST_MATH_BIG_CONSTANT(T, 64, -0.807533446680736736712e-19),196      BOOST_MATH_BIG_CONSTANT(T, 64, -0.490881544804798926426e-18),197      BOOST_MATH_BIG_CONSTANT(T, 64, 0.333333333333333373941),198      BOOST_MATH_BIG_CONSTANT(T, 64, 1.17141290782087994162),199      BOOST_MATH_BIG_CONSTANT(T, 64, 1.62790522814926264694),200      BOOST_MATH_BIG_CONSTANT(T, 64, 1.13156411870766876113),201      BOOST_MATH_BIG_CONSTANT(T, 64, 0.408087379932853785336),202      BOOST_MATH_BIG_CONSTANT(T, 64, 0.0706537026422828914622),203      BOOST_MATH_BIG_CONSTANT(T, 64, 0.00441709903782239229447)204   };205   BOOST_MATH_STATIC const T Q[] = {206      BOOST_MATH_BIG_CONSTANT(T, 64, 1.0),207      BOOST_MATH_BIG_CONSTANT(T, 64, 4.26423872346263928361),208      BOOST_MATH_BIG_CONSTANT(T, 64, 7.48189472704477708962),209      BOOST_MATH_BIG_CONSTANT(T, 64, 6.94757016732904280913),210      BOOST_MATH_BIG_CONSTANT(T, 64, 3.6493508622280767304),211      BOOST_MATH_BIG_CONSTANT(T, 64, 1.06884863623790638317),212      BOOST_MATH_BIG_CONSTANT(T, 64, 0.158292216998514145947),213      BOOST_MATH_BIG_CONSTANT(T, 64, 0.00885295524069924328658),214      BOOST_MATH_BIG_CONSTANT(T, 64, -0.560026216133415663808e-6)215   };216 217   T result = 1 - x / 2 + tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);218   result *= x;219 220   return result;221}222 223template <class T, class Policy>224BOOST_MATH_GPU_ENABLED T log1p_imp(T const& x, const Policy& pol, const boost::math::integral_constant<int, 24>&)225{ // The function returns the natural logarithm of 1 + x.226   BOOST_MATH_STD_USING227 228   constexpr auto function = "boost::math::log1p<%1%>(%1%)";229 230   if(x < -1)231      return policies::raise_domain_error<T>(232         function, "log1p(x) requires x > -1, but got x = %1%.", x, pol);233   if(x == -1)234      return -policies::raise_overflow_error<T>(235         function, nullptr, pol);236 237   T a = fabs(x);238   if(a > 0.5f)239      return log(1 + x);240   // Note that without numeric_limits specialisation support,241   // epsilon just returns zero, and our "optimisation" will always fail:242   if(a < tools::epsilon<T>())243      return x;244 245   // Maximum Deviation Found:                     6.910e-08246   // Expected Error Term:                         6.910e-08247   // Maximum Relative Change in Control Points:   2.509e-04248   // Max Error found at double precision =        6.910422e-08249   // Max Error found at float precision =         8.357242e-08250   BOOST_MATH_STATIC const T P[] = {251      -0.671192866803148236519e-7L,252      0.119670999140731844725e-6L,253      0.333339469182083148598L,254      0.237827183019664122066L255   };256   BOOST_MATH_STATIC const T Q[] = {257      1L,258      1.46348272586988539733L,259      0.497859871350117338894L,260      -0.00471666268910169651936L261   };262 263   T result = 1 - x / 2 + tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);264   result *= x;265 266   return result;267}268 269} // namespace detail270 271template <class T, class Policy>272BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type log1p(T x, const Policy&)273{274   typedef typename tools::promote_args<T>::type result_type;275   typedef typename policies::evaluation<result_type, Policy>::type value_type;276   typedef typename policies::precision<result_type, Policy>::type precision_type;277   typedef typename policies::normalise<278      Policy,279      policies::promote_float<false>,280      policies::promote_double<false>,281      policies::discrete_quantile<>,282      policies::assert_undefined<> >::type forwarding_policy;283 284   typedef boost::math::integral_constant<int,285      precision_type::value <= 0 ? 0 :286      precision_type::value <= 53 ? 53 :287      precision_type::value <= 64 ? 64 : 0288   > tag_type;289 290   return policies::checked_narrowing_cast<result_type, forwarding_policy>(291      detail::log1p_imp(static_cast<value_type>(x), forwarding_policy(), tag_type()), "boost::math::log1p<%1%>(%1%)");292}293 294template <class Policy>295BOOST_MATH_GPU_ENABLED inline float log1p(float x, const Policy& pol)296{297   if(x < -1)298      return policies::raise_domain_error<float>("log1p<%1%>(%1%)", "log1p(x) requires x > -1, but got x = %1%.", x, pol);299   if(x == -1)300      return -policies::raise_overflow_error<float>("log1p<%1%>(%1%)", nullptr, pol);301   #ifndef BOOST_MATH_HAS_NVRTC302   return std::log1p(x);303   #else304   return ::log1pf(x);305   #endif306}307#ifndef BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS308template <class Policy>309BOOST_MATH_GPU_ENABLED inline long double log1p(long double x, const Policy& pol)310{311   if(x < -1)312      return policies::raise_domain_error<long double>("log1p<%1%>(%1%)", "log1p(x) requires x > -1, but got x = %1%.", x, pol);313   if(x == -1)314      return -policies::raise_overflow_error<long double>("log1p<%1%>(%1%)", nullptr, pol);315   return std::log1p(x);316}317#endif318template <class Policy>319BOOST_MATH_GPU_ENABLED inline double log1p(double x, const Policy& pol)320{321   if(x < -1)322      return policies::raise_domain_error<double>("log1p<%1%>(%1%)", "log1p(x) requires x > -1, but got x = %1%.", x, pol);323   if(x == -1)324      return -policies::raise_overflow_error<double>("log1p<%1%>(%1%)", nullptr, pol);325   #ifndef BOOST_MATH_HAS_NVRTC326   return std::log1p(x);327   #else328   return ::log1p(x);329   #endif330}331 332template <class T>333BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type log1p(T x)334{335   return boost::math::log1p(x, policies::policy<>());336}337//338// Compute log(1+x)-x:339//340template <class T, class Policy>341BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type342   log1pmx(T x, const Policy& pol)343{344   typedef typename tools::promote_args<T>::type result_type;345   BOOST_MATH_STD_USING346   constexpr auto function = "boost::math::log1pmx<%1%>(%1%)";347 348   if(x < -1)349      return policies::raise_domain_error<T>(function, "log1pmx(x) requires x > -1, but got x = %1%.", x, pol);350   if(x == -1)351      return -policies::raise_overflow_error<T>(function, nullptr, pol);352 353   result_type a = abs(result_type(x));354   if(a > result_type(0.95f))355      return log(1 + result_type(x)) - result_type(x);356   // Note that without numeric_limits specialisation support,357   // epsilon just returns zero, and our "optimisation" will always fail:358   if(a < tools::epsilon<result_type>())359      return -x * x / 2;360   boost::math::detail::log1p_series<T> s(x);361   s();362   boost::math::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();363 364   T result = boost::math::tools::sum_series(s, policies::get_epsilon<T, Policy>(), max_iter);365 366   policies::check_series_iterations<T>(function, max_iter, pol);367   return result;368}369 370template <class T>371BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type log1pmx(T x)372{373   return log1pmx(x, policies::policy<>());374}375 376//377// Specific width floating point types:378//379#ifdef __STDCPP_FLOAT32_T__380template <class Policy>381BOOST_MATH_GPU_ENABLED inline std::float32_t log1p(std::float32_t x, const Policy& pol)382{383   return boost::math::log1p(static_cast<float>(x), pol);384}385#endif386#ifdef __STDCPP_FLOAT64_T__387template <class Policy>388BOOST_MATH_GPU_ENABLED inline std::float64_t log1p(std::float64_t x, const Policy& pol)389{390   return boost::math::log1p(static_cast<double>(x), pol);391}392#endif393#ifdef __STDCPP_FLOAT128_T__394template <class Policy>395BOOST_MATH_GPU_ENABLED inline std::float128_t log1p(std::float128_t x, const Policy& pol)396{397   if constexpr (std::numeric_limits<long double>::digits == std::numeric_limits<std::float128_t>::digits)398   {399      return boost::math::log1p(static_cast<long double>(x), pol);400   }401   else402   {403      return boost::math::detail::log1p_imp(x, pol, boost::math::integral_constant<int, 0>());404   }405}406#endif407} // namespace math408} // namespace boost409 410#ifdef _MSC_VER411#pragma warning(pop)412#endif413 414#endif // BOOST_MATH_LOG1P_INCLUDED415 416 417 418