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1//===----------------------------------------------------------------------===//2//3// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.4// See https://llvm.org/LICENSE.txt for license information.5// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception6//7//===----------------------------------------------------------------------===//8 9#ifndef _LIBCPP___CXX03___RANDOM_POISSON_DISTRIBUTION_H10#define _LIBCPP___CXX03___RANDOM_POISSON_DISTRIBUTION_H11 12#include <__cxx03/__config>13#include <__cxx03/__random/clamp_to_integral.h>14#include <__cxx03/__random/exponential_distribution.h>15#include <__cxx03/__random/is_valid.h>16#include <__cxx03/__random/normal_distribution.h>17#include <__cxx03/__random/uniform_real_distribution.h>18#include <__cxx03/cmath>19#include <__cxx03/iosfwd>20#include <__cxx03/limits>21 22#if !defined(_LIBCPP_HAS_NO_PRAGMA_SYSTEM_HEADER)23# pragma GCC system_header24#endif25 26_LIBCPP_PUSH_MACROS27#include <__cxx03/__undef_macros>28 29_LIBCPP_BEGIN_NAMESPACE_STD30 31template <class _IntType = int>32class _LIBCPP_TEMPLATE_VIS poisson_distribution {33 static_assert(__libcpp_random_is_valid_inttype<_IntType>::value, "IntType must be a supported integer type");34 35public:36 // types37 typedef _IntType result_type;38 39 class _LIBCPP_TEMPLATE_VIS param_type {40 double __mean_;41 double __s_;42 double __d_;43 double __l_;44 double __omega_;45 double __c0_;46 double __c1_;47 double __c2_;48 double __c3_;49 double __c_;50 51 public:52 typedef poisson_distribution distribution_type;53 54 _LIBCPP_HIDE_FROM_ABI explicit param_type(double __mean = 1.0);55 56 _LIBCPP_HIDE_FROM_ABI double mean() const { return __mean_; }57 58 friend _LIBCPP_HIDE_FROM_ABI bool operator==(const param_type& __x, const param_type& __y) {59 return __x.__mean_ == __y.__mean_;60 }61 friend _LIBCPP_HIDE_FROM_ABI bool operator!=(const param_type& __x, const param_type& __y) { return !(__x == __y); }62 63 friend class poisson_distribution;64 };65 66private:67 param_type __p_;68 69public:70 // constructors and reset functions71 _LIBCPP_HIDE_FROM_ABI explicit poisson_distribution(double __mean = 1.0) : __p_(__mean) {}72 _LIBCPP_HIDE_FROM_ABI explicit poisson_distribution(const param_type& __p) : __p_(__p) {}73 _LIBCPP_HIDE_FROM_ABI void reset() {}74 75 // generating functions76 template <class _URNG>77 _LIBCPP_HIDE_FROM_ABI result_type operator()(_URNG& __g) {78 return (*this)(__g, __p_);79 }80 template <class _URNG>81 _LIBCPP_HIDE_FROM_ABI result_type operator()(_URNG& __g, const param_type& __p);82 83 // property functions84 _LIBCPP_HIDE_FROM_ABI double mean() const { return __p_.mean(); }85 86 _LIBCPP_HIDE_FROM_ABI param_type param() const { return __p_; }87 _LIBCPP_HIDE_FROM_ABI void param(const param_type& __p) { __p_ = __p; }88 89 _LIBCPP_HIDE_FROM_ABI result_type min() const { return 0; }90 _LIBCPP_HIDE_FROM_ABI result_type max() const { return numeric_limits<result_type>::max(); }91 92 friend _LIBCPP_HIDE_FROM_ABI bool operator==(const poisson_distribution& __x, const poisson_distribution& __y) {93 return __x.__p_ == __y.__p_;94 }95 friend _LIBCPP_HIDE_FROM_ABI bool operator!=(const poisson_distribution& __x, const poisson_distribution& __y) {96 return !(__x == __y);97 }98};99 100template <class _IntType>101poisson_distribution<_IntType>::param_type::param_type(double __mean)102 // According to the standard `inf` is a valid input, but it causes the103 // distribution to hang, so we replace it with the maximum representable104 // mean.105 : __mean_(isinf(__mean) ? numeric_limits<double>::max() : __mean) {106 if (__mean_ < 10) {107 __s_ = 0;108 __d_ = 0;109 __l_ = std::exp(-__mean_);110 __omega_ = 0;111 __c3_ = 0;112 __c2_ = 0;113 __c1_ = 0;114 __c0_ = 0;115 __c_ = 0;116 } else {117 __s_ = std::sqrt(__mean_);118 __d_ = 6 * __mean_ * __mean_;119 __l_ = std::trunc(__mean_ - 1.1484);120 __omega_ = .3989423 / __s_;121 double __b1 = .4166667E-1 / __mean_;122 double __b2 = .3 * __b1 * __b1;123 __c3_ = .1428571 * __b1 * __b2;124 __c2_ = __b2 - 15. * __c3_;125 __c1_ = __b1 - 6. * __b2 + 45. * __c3_;126 __c0_ = 1. - __b1 + 3. * __b2 - 15. * __c3_;127 __c_ = .1069 / __mean_;128 }129}130 131template <class _IntType>132template <class _URNG>133_IntType poisson_distribution<_IntType>::operator()(_URNG& __urng, const param_type& __pr) {134 static_assert(__libcpp_random_is_valid_urng<_URNG>::value, "");135 double __tx;136 uniform_real_distribution<double> __urd;137 if (__pr.__mean_ < 10) {138 __tx = 0;139 for (double __p = __urd(__urng); __p > __pr.__l_; ++__tx)140 __p *= __urd(__urng);141 } else {142 double __difmuk;143 double __g = __pr.__mean_ + __pr.__s_ * normal_distribution<double>()(__urng);144 double __u;145 if (__g > 0) {146 __tx = std::trunc(__g);147 if (__tx >= __pr.__l_)148 return std::__clamp_to_integral<result_type>(__tx);149 __difmuk = __pr.__mean_ - __tx;150 __u = __urd(__urng);151 if (__pr.__d_ * __u >= __difmuk * __difmuk * __difmuk)152 return std::__clamp_to_integral<result_type>(__tx);153 }154 exponential_distribution<double> __edist;155 for (bool __using_exp_dist = false; true; __using_exp_dist = true) {156 double __e;157 if (__using_exp_dist || __g <= 0) {158 double __t;159 do {160 __e = __edist(__urng);161 __u = __urd(__urng);162 __u += __u - 1;163 __t = 1.8 + (__u < 0 ? -__e : __e);164 } while (__t <= -.6744);165 __tx = std::trunc(__pr.__mean_ + __pr.__s_ * __t);166 __difmuk = __pr.__mean_ - __tx;167 __using_exp_dist = true;168 }169 double __px;170 double __py;171 if (__tx < 10 && __tx >= 0) {172 const double __fac[] = {1, 1, 2, 6, 24, 120, 720, 5040, 40320, 362880};173 __px = -__pr.__mean_;174 __py = std::pow(__pr.__mean_, (double)__tx) / __fac[static_cast<int>(__tx)];175 } else {176 double __del = .8333333E-1 / __tx;177 __del -= 4.8 * __del * __del * __del;178 double __v = __difmuk / __tx;179 if (std::abs(__v) > 0.25)180 __px = __tx * std::log(1 + __v) - __difmuk - __del;181 else182 __px = __tx * __v * __v *183 (((((((.1250060 * __v + -.1384794) * __v + .1421878) * __v + -.1661269) * __v + .2000118) * __v +184 -.2500068) *185 __v +186 .3333333) *187 __v +188 -.5) -189 __del;190 __py = .3989423 / std::sqrt(__tx);191 }192 double __r = (0.5 - __difmuk) / __pr.__s_;193 double __r2 = __r * __r;194 double __fx = -0.5 * __r2;195 double __fy = __pr.__omega_ * (((__pr.__c3_ * __r2 + __pr.__c2_) * __r2 + __pr.__c1_) * __r2 + __pr.__c0_);196 if (__using_exp_dist) {197 if (__pr.__c_ * std::abs(__u) <= __py * std::exp(__px + __e) - __fy * std::exp(__fx + __e))198 break;199 } else {200 if (__fy - __u * __fy <= __py * std::exp(__px - __fx))201 break;202 }203 }204 }205 return std::__clamp_to_integral<result_type>(__tx);206}207 208template <class _CharT, class _Traits, class _IntType>209_LIBCPP_HIDE_FROM_ABI basic_ostream<_CharT, _Traits>&210operator<<(basic_ostream<_CharT, _Traits>& __os, const poisson_distribution<_IntType>& __x) {211 __save_flags<_CharT, _Traits> __lx(__os);212 typedef basic_ostream<_CharT, _Traits> _OStream;213 __os.flags(_OStream::dec | _OStream::left | _OStream::fixed | _OStream::scientific);214 return __os << __x.mean();215}216 217template <class _CharT, class _Traits, class _IntType>218_LIBCPP_HIDE_FROM_ABI basic_istream<_CharT, _Traits>&219operator>>(basic_istream<_CharT, _Traits>& __is, poisson_distribution<_IntType>& __x) {220 typedef poisson_distribution<_IntType> _Eng;221 typedef typename _Eng::param_type param_type;222 __save_flags<_CharT, _Traits> __lx(__is);223 typedef basic_istream<_CharT, _Traits> _Istream;224 __is.flags(_Istream::dec | _Istream::skipws);225 double __mean;226 __is >> __mean;227 if (!__is.fail())228 __x.param(param_type(__mean));229 return __is;230}231 232_LIBCPP_END_NAMESPACE_STD233 234_LIBCPP_POP_MACROS235 236#endif // _LIBCPP___CXX03___RANDOM_POISSON_DISTRIBUTION_H237