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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___RANDOM_POISSON_DISTRIBUTION_H10#define _LIBCPP___RANDOM_POISSON_DISTRIBUTION_H11 12#include <__config>13#include <__random/clamp_to_integral.h>14#include <__random/exponential_distribution.h>15#include <__random/is_valid.h>16#include <__random/normal_distribution.h>17#include <__random/uniform_real_distribution.h>18#include <cmath>19#include <iosfwd>20#include <limits>21 22#if !defined(_LIBCPP_HAS_NO_PRAGMA_SYSTEM_HEADER)23# pragma GCC system_header24#endif25 26_LIBCPP_PUSH_MACROS27#include <__undef_macros>28 29_LIBCPP_BEGIN_NAMESPACE_STD30 31template <class _IntType = int>32class 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 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#ifndef _LIBCPP_CXX03_LANG72 _LIBCPP_HIDE_FROM_ABI poisson_distribution() : poisson_distribution(1.0) {}73 _LIBCPP_HIDE_FROM_ABI explicit poisson_distribution(double __mean) : __p_(__mean) {}74#else75 _LIBCPP_HIDE_FROM_ABI explicit poisson_distribution(double __mean = 1.0) : __p_(__mean) {}76#endif77 _LIBCPP_HIDE_FROM_ABI explicit poisson_distribution(const param_type& __p) : __p_(__p) {}78 _LIBCPP_HIDE_FROM_ABI void reset() {}79 80 // generating functions81 template <class _URNG>82 _LIBCPP_HIDE_FROM_ABI result_type operator()(_URNG& __g) {83 return (*this)(__g, __p_);84 }85 template <class _URNG>86 _LIBCPP_HIDE_FROM_ABI result_type operator()(_URNG& __g, const param_type& __p);87 88 // property functions89 _LIBCPP_HIDE_FROM_ABI double mean() const { return __p_.mean(); }90 91 _LIBCPP_HIDE_FROM_ABI param_type param() const { return __p_; }92 _LIBCPP_HIDE_FROM_ABI void param(const param_type& __p) { __p_ = __p; }93 94 _LIBCPP_HIDE_FROM_ABI result_type min() const { return 0; }95 _LIBCPP_HIDE_FROM_ABI result_type max() const { return numeric_limits<result_type>::max(); }96 97 friend _LIBCPP_HIDE_FROM_ABI bool operator==(const poisson_distribution& __x, const poisson_distribution& __y) {98 return __x.__p_ == __y.__p_;99 }100 friend _LIBCPP_HIDE_FROM_ABI bool operator!=(const poisson_distribution& __x, const poisson_distribution& __y) {101 return !(__x == __y);102 }103};104 105template <class _IntType>106poisson_distribution<_IntType>::param_type::param_type(double __mean)107 // According to the standard `inf` is a valid input, but it causes the108 // distribution to hang, so we replace it with the maximum representable109 // mean.110 : __mean_(isinf(__mean) ? numeric_limits<double>::max() : __mean) {111 if (__mean_ < 10) {112 __s_ = 0;113 __d_ = 0;114 __l_ = std::exp(-__mean_);115 __omega_ = 0;116 __c3_ = 0;117 __c2_ = 0;118 __c1_ = 0;119 __c0_ = 0;120 __c_ = 0;121 } else {122 __s_ = std::sqrt(__mean_);123 __d_ = 6 * __mean_ * __mean_;124 __l_ = std::trunc(__mean_ - 1.1484);125 __omega_ = .3989423 / __s_;126 double __b1 = .4166667E-1 / __mean_;127 double __b2 = .3 * __b1 * __b1;128 __c3_ = .1428571 * __b1 * __b2;129 __c2_ = __b2 - 15. * __c3_;130 __c1_ = __b1 - 6. * __b2 + 45. * __c3_;131 __c0_ = 1. - __b1 + 3. * __b2 - 15. * __c3_;132 __c_ = .1069 / __mean_;133 }134}135 136template <class _IntType>137template <class _URNG>138_IntType poisson_distribution<_IntType>::operator()(_URNG& __urng, const param_type& __pr) {139 static_assert(__libcpp_random_is_valid_urng<_URNG>::value, "");140 double __tx;141 uniform_real_distribution<double> __urd;142 if (__pr.__mean_ < 10) {143 __tx = 0;144 for (double __p = __urd(__urng); __p > __pr.__l_; ++__tx)145 __p *= __urd(__urng);146 } else {147 double __difmuk;148 double __g = __pr.__mean_ + __pr.__s_ * normal_distribution<double>()(__urng);149 double __u;150 if (__g > 0) {151 __tx = std::trunc(__g);152 if (__tx >= __pr.__l_)153 return std::__clamp_to_integral<result_type>(__tx);154 __difmuk = __pr.__mean_ - __tx;155 __u = __urd(__urng);156 if (__pr.__d_ * __u >= __difmuk * __difmuk * __difmuk)157 return std::__clamp_to_integral<result_type>(__tx);158 }159 exponential_distribution<double> __edist;160 for (bool __using_exp_dist = false; true; __using_exp_dist = true) {161 double __e;162 if (__using_exp_dist || __g <= 0) {163 double __t;164 do {165 __e = __edist(__urng);166 __u = __urd(__urng);167 __u += __u - 1;168 __t = 1.8 + (__u < 0 ? -__e : __e);169 } while (__t <= -.6744);170 __tx = std::trunc(__pr.__mean_ + __pr.__s_ * __t);171 __difmuk = __pr.__mean_ - __tx;172 __using_exp_dist = true;173 }174 double __px;175 double __py;176 if (__tx < 10 && __tx >= 0) {177 const double __fac[] = {1, 1, 2, 6, 24, 120, 720, 5040, 40320, 362880};178 __px = -__pr.__mean_;179 __py = std::pow(__pr.__mean_, (double)__tx) / __fac[static_cast<int>(__tx)];180 } else {181 double __del = .8333333E-1 / __tx;182 __del -= 4.8 * __del * __del * __del;183 double __v = __difmuk / __tx;184 if (std::abs(__v) > 0.25)185 __px = __tx * std::log(1 + __v) - __difmuk - __del;186 else187 __px = __tx * __v * __v *188 (((((((.1250060 * __v + -.1384794) * __v + .1421878) * __v + -.1661269) * __v + .2000118) * __v +189 -.2500068) *190 __v +191 .3333333) *192 __v +193 -.5) -194 __del;195 __py = .3989423 / std::sqrt(__tx);196 }197 double __r = (0.5 - __difmuk) / __pr.__s_;198 double __r2 = __r * __r;199 double __fx = -0.5 * __r2;200 double __fy = __pr.__omega_ * (((__pr.__c3_ * __r2 + __pr.__c2_) * __r2 + __pr.__c1_) * __r2 + __pr.__c0_);201 if (__using_exp_dist) {202 if (__pr.__c_ * std::abs(__u) <= __py * std::exp(__px + __e) - __fy * std::exp(__fx + __e))203 break;204 } else {205 if (__fy - __u * __fy <= __py * std::exp(__px - __fx))206 break;207 }208 }209 }210 return std::__clamp_to_integral<result_type>(__tx);211}212 213template <class _CharT, class _Traits, class _IntType>214_LIBCPP_HIDE_FROM_ABI basic_ostream<_CharT, _Traits>&215operator<<(basic_ostream<_CharT, _Traits>& __os, const poisson_distribution<_IntType>& __x) {216 __save_flags<_CharT, _Traits> __lx(__os);217 typedef basic_ostream<_CharT, _Traits> _OStream;218 __os.flags(_OStream::dec | _OStream::left | _OStream::fixed | _OStream::scientific);219 return __os << __x.mean();220}221 222template <class _CharT, class _Traits, class _IntType>223_LIBCPP_HIDE_FROM_ABI basic_istream<_CharT, _Traits>&224operator>>(basic_istream<_CharT, _Traits>& __is, poisson_distribution<_IntType>& __x) {225 typedef poisson_distribution<_IntType> _Eng;226 typedef typename _Eng::param_type param_type;227 __save_flags<_CharT, _Traits> __lx(__is);228 typedef basic_istream<_CharT, _Traits> _Istream;229 __is.flags(_Istream::dec | _Istream::skipws);230 double __mean;231 __is >> __mean;232 if (!__is.fail())233 __x.param(param_type(__mean));234 return __is;235}236 237_LIBCPP_END_NAMESPACE_STD238 239_LIBCPP_POP_MACROS240 241#endif // _LIBCPP___RANDOM_POISSON_DISTRIBUTION_H242