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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-exception
6//
7//===----------------------------------------------------------------------===//
8
9#ifndef _LIBCPP___CXX03___RANDOM_POISSON_DISTRIBUTION_H
10#define _LIBCPP___CXX03___RANDOM_POISSON_DISTRIBUTION_H
11
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_header
24#endif
25
26_LIBCPP_PUSH_MACROS
27#include <__cxx03/__undef_macros>
28
29_LIBCPP_BEGIN_NAMESPACE_STD
30
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 // types
37 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 functions
71 _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 functions
76 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 functions
84 _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 the
103 // distribution to hang, so we replace it with the maximum representable
104 // 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 else
182 __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_STD
233
234_LIBCPP_POP_MACROS
235
236#endif // _LIBCPP___CXX03___RANDOM_POISSON_DISTRIBUTION_H
237

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source code of libcxx/include/__cxx03/__random/poisson_distribution.h