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8e79468d BK |
1 | // random number generation (out of line) -*- C++ -*- |
2 | ||
7adcbafe | 3 | // Copyright (C) 2009-2022 Free Software Foundation, Inc. |
8e79468d BK |
4 | // |
5 | // This file is part of the GNU ISO C++ Library. This library is free | |
6 | // software; you can redistribute it and/or modify it under the | |
7 | // terms of the GNU General Public License as published by the | |
748086b7 | 8 | // Free Software Foundation; either version 3, or (at your option) |
8e79468d BK |
9 | // any later version. |
10 | ||
11 | // This library is distributed in the hope that it will be useful, | |
12 | // but WITHOUT ANY WARRANTY; without even the implied warranty of | |
13 | // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the | |
14 | // GNU General Public License for more details. | |
15 | ||
748086b7 JJ |
16 | // Under Section 7 of GPL version 3, you are granted additional |
17 | // permissions described in the GCC Runtime Library Exception, version | |
18 | // 3.1, as published by the Free Software Foundation. | |
8e79468d | 19 | |
748086b7 JJ |
20 | // You should have received a copy of the GNU General Public License and |
21 | // a copy of the GCC Runtime Library Exception along with this program; | |
22 | // see the files COPYING3 and COPYING.RUNTIME respectively. If not, see | |
23 | // <http://www.gnu.org/licenses/>. | |
8e79468d BK |
24 | |
25 | /** @file bits/random.tcc | |
26 | * This is an internal header file, included by other library headers. | |
f910786b | 27 | * Do not attempt to use it directly. @headername{random} |
8e79468d BK |
28 | */ |
29 | ||
06f29237 PC |
30 | #ifndef _RANDOM_TCC |
31 | #define _RANDOM_TCC 1 | |
32 | ||
247d8075 | 33 | #include <numeric> // std::accumulate and std::partial_sum |
8e79468d | 34 | |
12ffa228 BK |
35 | namespace std _GLIBCXX_VISIBILITY(default) |
36 | { | |
4a15d842 FD |
37 | _GLIBCXX_BEGIN_NAMESPACE_VERSION |
38 | ||
6963c3b9 JW |
39 | /// @cond undocumented |
40 | // (Further) implementation-space details. | |
8e79468d BK |
41 | namespace __detail |
42 | { | |
cf48c255 MG |
43 | // General case for x = (ax + c) mod m -- use Schrage's algorithm |
44 | // to avoid integer overflow. | |
8e79468d BK |
45 | // |
46 | // Preconditions: a > 0, m > 0. | |
47 | // | |
cf48c255 | 48 | // Note: only works correctly for __m % __a < __m / __a. |
b94f4bef | 49 | template<typename _Tp, _Tp __m, _Tp __a, _Tp __c> |
cf48c255 MG |
50 | _Tp |
51 | _Mod<_Tp, __m, __a, __c, false, true>:: | |
52 | __calc(_Tp __x) | |
8e79468d | 53 | { |
cf48c255 MG |
54 | if (__a == 1) |
55 | __x %= __m; | |
56 | else | |
57 | { | |
58 | static const _Tp __q = __m / __a; | |
59 | static const _Tp __r = __m % __a; | |
60 | ||
61 | _Tp __t1 = __a * (__x % __q); | |
62 | _Tp __t2 = __r * (__x / __q); | |
63 | if (__t1 >= __t2) | |
64 | __x = __t1 - __t2; | |
65 | else | |
66 | __x = __m - __t2 + __t1; | |
67 | } | |
68 | ||
69 | if (__c != 0) | |
70 | { | |
71 | const _Tp __d = __m - __x; | |
72 | if (__d > __c) | |
73 | __x += __c; | |
74 | else | |
75 | __x = __c - __d; | |
76 | } | |
77 | return __x; | |
78 | } | |
247d8075 | 79 | |
afcd05a7 | 80 | template<typename _InputIterator, typename _OutputIterator, |
60f3a59f | 81 | typename _Tp> |
afcd05a7 | 82 | _OutputIterator |
60f3a59f PC |
83 | __normalize(_InputIterator __first, _InputIterator __last, |
84 | _OutputIterator __result, const _Tp& __factor) | |
afcd05a7 PC |
85 | { |
86 | for (; __first != __last; ++__first, ++__result) | |
60f3a59f | 87 | *__result = *__first / __factor; |
afcd05a7 PC |
88 | return __result; |
89 | } | |
12ffa228 | 90 | |
8e79468d | 91 | } // namespace __detail |
6963c3b9 | 92 | /// @endcond |
8e79468d | 93 | |
a77a46d9 | 94 | #if ! __cpp_inline_variables |
300ea283 | 95 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m> |
94a86be0 | 96 | constexpr _UIntType |
300ea283 PC |
97 | linear_congruential_engine<_UIntType, __a, __c, __m>::multiplier; |
98 | ||
99 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m> | |
94a86be0 | 100 | constexpr _UIntType |
300ea283 PC |
101 | linear_congruential_engine<_UIntType, __a, __c, __m>::increment; |
102 | ||
103 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m> | |
94a86be0 | 104 | constexpr _UIntType |
300ea283 PC |
105 | linear_congruential_engine<_UIntType, __a, __c, __m>::modulus; |
106 | ||
107 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m> | |
94a86be0 | 108 | constexpr _UIntType |
300ea283 | 109 | linear_congruential_engine<_UIntType, __a, __c, __m>::default_seed; |
a77a46d9 | 110 | #endif |
300ea283 | 111 | |
8e79468d | 112 | /** |
96a9203b | 113 | * Seeds the LCR with integral value @p __s, adjusted so that the |
8e79468d BK |
114 | * ring identity is never a member of the convergence set. |
115 | */ | |
116 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m> | |
117 | void | |
118 | linear_congruential_engine<_UIntType, __a, __c, __m>:: | |
96a9203b | 119 | seed(result_type __s) |
8e79468d | 120 | { |
b94f4bef PC |
121 | if ((__detail::__mod<_UIntType, __m>(__c) == 0) |
122 | && (__detail::__mod<_UIntType, __m>(__s) == 0)) | |
123 | _M_x = 1; | |
8e79468d | 124 | else |
b94f4bef | 125 | _M_x = __detail::__mod<_UIntType, __m>(__s); |
8e79468d BK |
126 | } |
127 | ||
128 | /** | |
96a9203b | 129 | * Seeds the LCR engine with a value generated by @p __q. |
8e79468d BK |
130 | */ |
131 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m> | |
05eeebfe | 132 | template<typename _Sseq> |
5a7960da | 133 | auto |
15ecdcc6 PC |
134 | linear_congruential_engine<_UIntType, __a, __c, __m>:: |
135 | seed(_Sseq& __q) | |
5a7960da | 136 | -> _If_seed_seq<_Sseq> |
15ecdcc6 PC |
137 | { |
138 | const _UIntType __k0 = __m == 0 ? std::numeric_limits<_UIntType>::digits | |
139 | : std::__lg(__m); | |
140 | const _UIntType __k = (__k0 + 31) / 32; | |
141 | uint_least32_t __arr[__k + 3]; | |
142 | __q.generate(__arr + 0, __arr + __k + 3); | |
143 | _UIntType __factor = 1u; | |
144 | _UIntType __sum = 0u; | |
145 | for (size_t __j = 0; __j < __k; ++__j) | |
146 | { | |
147 | __sum += __arr[__j + 3] * __factor; | |
148 | __factor *= __detail::_Shift<_UIntType, 32>::__value; | |
149 | } | |
150 | seed(__sum); | |
151 | } | |
8e79468d | 152 | |
8e79468d BK |
153 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m, |
154 | typename _CharT, typename _Traits> | |
155 | std::basic_ostream<_CharT, _Traits>& | |
156 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
157 | const linear_congruential_engine<_UIntType, | |
158 | __a, __c, __m>& __lcr) | |
159 | { | |
160e95dc | 160 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
161 | |
162 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
163 | const _CharT __fill = __os.fill(); | |
95fe602e | 164 | __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left); |
8e79468d BK |
165 | __os.fill(__os.widen(' ')); |
166 | ||
167 | __os << __lcr._M_x; | |
168 | ||
169 | __os.flags(__flags); | |
170 | __os.fill(__fill); | |
171 | return __os; | |
172 | } | |
173 | ||
174 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m, | |
175 | typename _CharT, typename _Traits> | |
176 | std::basic_istream<_CharT, _Traits>& | |
177 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
178 | linear_congruential_engine<_UIntType, __a, __c, __m>& __lcr) | |
179 | { | |
160e95dc | 180 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; |
8e79468d BK |
181 | |
182 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
183 | __is.flags(__ios_base::dec); | |
184 | ||
185 | __is >> __lcr._M_x; | |
186 | ||
187 | __is.flags(__flags); | |
188 | return __is; | |
189 | } | |
190 | ||
996be6b6 | 191 | #if ! __cpp_inline_variables |
300ea283 PC |
192 | template<typename _UIntType, |
193 | size_t __w, size_t __n, size_t __m, size_t __r, | |
194 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
195 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
196 | _UIntType __f> | |
94a86be0 | 197 | constexpr size_t |
300ea283 PC |
198 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
199 | __s, __b, __t, __c, __l, __f>::word_size; | |
200 | ||
201 | template<typename _UIntType, | |
202 | size_t __w, size_t __n, size_t __m, size_t __r, | |
203 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
204 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
205 | _UIntType __f> | |
94a86be0 | 206 | constexpr size_t |
300ea283 PC |
207 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
208 | __s, __b, __t, __c, __l, __f>::state_size; | |
209 | ||
210 | template<typename _UIntType, | |
211 | size_t __w, size_t __n, size_t __m, size_t __r, | |
212 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
213 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
214 | _UIntType __f> | |
94a86be0 | 215 | constexpr size_t |
300ea283 PC |
216 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
217 | __s, __b, __t, __c, __l, __f>::shift_size; | |
218 | ||
219 | template<typename _UIntType, | |
220 | size_t __w, size_t __n, size_t __m, size_t __r, | |
221 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
222 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
223 | _UIntType __f> | |
94a86be0 | 224 | constexpr size_t |
300ea283 PC |
225 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
226 | __s, __b, __t, __c, __l, __f>::mask_bits; | |
227 | ||
228 | template<typename _UIntType, | |
229 | size_t __w, size_t __n, size_t __m, size_t __r, | |
230 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
231 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
232 | _UIntType __f> | |
94a86be0 | 233 | constexpr _UIntType |
300ea283 PC |
234 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
235 | __s, __b, __t, __c, __l, __f>::xor_mask; | |
236 | ||
237 | template<typename _UIntType, | |
238 | size_t __w, size_t __n, size_t __m, size_t __r, | |
239 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
240 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
241 | _UIntType __f> | |
94a86be0 | 242 | constexpr size_t |
300ea283 PC |
243 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
244 | __s, __b, __t, __c, __l, __f>::tempering_u; | |
245 | ||
246 | template<typename _UIntType, | |
247 | size_t __w, size_t __n, size_t __m, size_t __r, | |
248 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
249 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
250 | _UIntType __f> | |
94a86be0 | 251 | constexpr _UIntType |
300ea283 PC |
252 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
253 | __s, __b, __t, __c, __l, __f>::tempering_d; | |
254 | ||
255 | template<typename _UIntType, | |
256 | size_t __w, size_t __n, size_t __m, size_t __r, | |
257 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
258 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
259 | _UIntType __f> | |
94a86be0 | 260 | constexpr size_t |
300ea283 PC |
261 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
262 | __s, __b, __t, __c, __l, __f>::tempering_s; | |
263 | ||
264 | template<typename _UIntType, | |
265 | size_t __w, size_t __n, size_t __m, size_t __r, | |
266 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
267 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
268 | _UIntType __f> | |
94a86be0 | 269 | constexpr _UIntType |
300ea283 PC |
270 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
271 | __s, __b, __t, __c, __l, __f>::tempering_b; | |
272 | ||
273 | template<typename _UIntType, | |
274 | size_t __w, size_t __n, size_t __m, size_t __r, | |
275 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
276 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
277 | _UIntType __f> | |
94a86be0 | 278 | constexpr size_t |
300ea283 PC |
279 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
280 | __s, __b, __t, __c, __l, __f>::tempering_t; | |
281 | ||
282 | template<typename _UIntType, | |
283 | size_t __w, size_t __n, size_t __m, size_t __r, | |
284 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
285 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
286 | _UIntType __f> | |
94a86be0 | 287 | constexpr _UIntType |
300ea283 PC |
288 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
289 | __s, __b, __t, __c, __l, __f>::tempering_c; | |
290 | ||
291 | template<typename _UIntType, | |
292 | size_t __w, size_t __n, size_t __m, size_t __r, | |
293 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
294 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
295 | _UIntType __f> | |
94a86be0 | 296 | constexpr size_t |
300ea283 PC |
297 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
298 | __s, __b, __t, __c, __l, __f>::tempering_l; | |
299 | ||
300 | template<typename _UIntType, | |
301 | size_t __w, size_t __n, size_t __m, size_t __r, | |
302 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
303 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
304 | _UIntType __f> | |
94a86be0 | 305 | constexpr _UIntType |
300ea283 PC |
306 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
307 | __s, __b, __t, __c, __l, __f>:: | |
308 | initialization_multiplier; | |
309 | ||
310 | template<typename _UIntType, | |
311 | size_t __w, size_t __n, size_t __m, size_t __r, | |
312 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
313 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
314 | _UIntType __f> | |
94a86be0 | 315 | constexpr _UIntType |
300ea283 PC |
316 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
317 | __s, __b, __t, __c, __l, __f>::default_seed; | |
996be6b6 | 318 | #endif |
300ea283 | 319 | |
8e79468d BK |
320 | template<typename _UIntType, |
321 | size_t __w, size_t __n, size_t __m, size_t __r, | |
322 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
323 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
324 | _UIntType __f> | |
325 | void | |
326 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, | |
327 | __s, __b, __t, __c, __l, __f>:: | |
328 | seed(result_type __sd) | |
329 | { | |
b94f4bef | 330 | _M_x[0] = __detail::__mod<_UIntType, |
8e79468d BK |
331 | __detail::_Shift<_UIntType, __w>::__value>(__sd); |
332 | ||
333 | for (size_t __i = 1; __i < state_size; ++__i) | |
334 | { | |
335 | _UIntType __x = _M_x[__i - 1]; | |
336 | __x ^= __x >> (__w - 2); | |
337 | __x *= __f; | |
b94f4bef PC |
338 | __x += __detail::__mod<_UIntType, __n>(__i); |
339 | _M_x[__i] = __detail::__mod<_UIntType, | |
8e79468d BK |
340 | __detail::_Shift<_UIntType, __w>::__value>(__x); |
341 | } | |
342 | _M_p = state_size; | |
343 | } | |
344 | ||
345 | template<typename _UIntType, | |
346 | size_t __w, size_t __n, size_t __m, size_t __r, | |
347 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
348 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
349 | _UIntType __f> | |
05eeebfe | 350 | template<typename _Sseq> |
5a7960da | 351 | auto |
15ecdcc6 | 352 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
8e79468d | 353 | __s, __b, __t, __c, __l, __f>:: |
15ecdcc6 | 354 | seed(_Sseq& __q) |
5a7960da | 355 | -> _If_seed_seq<_Sseq> |
15ecdcc6 PC |
356 | { |
357 | const _UIntType __upper_mask = (~_UIntType()) << __r; | |
358 | const size_t __k = (__w + 31) / 32; | |
359 | uint_least32_t __arr[__n * __k]; | |
360 | __q.generate(__arr + 0, __arr + __n * __k); | |
361 | ||
362 | bool __zero = true; | |
363 | for (size_t __i = 0; __i < state_size; ++__i) | |
364 | { | |
365 | _UIntType __factor = 1u; | |
366 | _UIntType __sum = 0u; | |
367 | for (size_t __j = 0; __j < __k; ++__j) | |
368 | { | |
369 | __sum += __arr[__k * __i + __j] * __factor; | |
370 | __factor *= __detail::_Shift<_UIntType, 32>::__value; | |
371 | } | |
372 | _M_x[__i] = __detail::__mod<_UIntType, | |
373 | __detail::_Shift<_UIntType, __w>::__value>(__sum); | |
374 | ||
375 | if (__zero) | |
376 | { | |
377 | if (__i == 0) | |
378 | { | |
379 | if ((_M_x[0] & __upper_mask) != 0u) | |
380 | __zero = false; | |
381 | } | |
382 | else if (_M_x[__i] != 0u) | |
383 | __zero = false; | |
384 | } | |
385 | } | |
8e79468d | 386 | if (__zero) |
b94f4bef | 387 | _M_x[0] = __detail::_Shift<_UIntType, __w - 1>::__value; |
935ec36f | 388 | _M_p = state_size; |
15ecdcc6 | 389 | } |
8e79468d | 390 | |
b668e41a UD |
391 | template<typename _UIntType, size_t __w, |
392 | size_t __n, size_t __m, size_t __r, | |
393 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
394 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
395 | _UIntType __f> | |
396 | void | |
397 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, | |
398 | __s, __b, __t, __c, __l, __f>:: | |
399 | _M_gen_rand(void) | |
400 | { | |
401 | const _UIntType __upper_mask = (~_UIntType()) << __r; | |
402 | const _UIntType __lower_mask = ~__upper_mask; | |
403 | ||
404 | for (size_t __k = 0; __k < (__n - __m); ++__k) | |
405 | { | |
406 | _UIntType __y = ((_M_x[__k] & __upper_mask) | |
407 | | (_M_x[__k + 1] & __lower_mask)); | |
408 | _M_x[__k] = (_M_x[__k + __m] ^ (__y >> 1) | |
409 | ^ ((__y & 0x01) ? __a : 0)); | |
410 | } | |
411 | ||
412 | for (size_t __k = (__n - __m); __k < (__n - 1); ++__k) | |
413 | { | |
414 | _UIntType __y = ((_M_x[__k] & __upper_mask) | |
415 | | (_M_x[__k + 1] & __lower_mask)); | |
416 | _M_x[__k] = (_M_x[__k + (__m - __n)] ^ (__y >> 1) | |
417 | ^ ((__y & 0x01) ? __a : 0)); | |
418 | } | |
419 | ||
420 | _UIntType __y = ((_M_x[__n - 1] & __upper_mask) | |
421 | | (_M_x[0] & __lower_mask)); | |
422 | _M_x[__n - 1] = (_M_x[__m - 1] ^ (__y >> 1) | |
423 | ^ ((__y & 0x01) ? __a : 0)); | |
424 | _M_p = 0; | |
425 | } | |
426 | ||
427 | template<typename _UIntType, size_t __w, | |
428 | size_t __n, size_t __m, size_t __r, | |
429 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
430 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
431 | _UIntType __f> | |
432 | void | |
433 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, | |
434 | __s, __b, __t, __c, __l, __f>:: | |
435 | discard(unsigned long long __z) | |
436 | { | |
437 | while (__z > state_size - _M_p) | |
438 | { | |
439 | __z -= state_size - _M_p; | |
440 | _M_gen_rand(); | |
441 | } | |
442 | _M_p += __z; | |
443 | } | |
444 | ||
8e79468d BK |
445 | template<typename _UIntType, size_t __w, |
446 | size_t __n, size_t __m, size_t __r, | |
447 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
448 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
449 | _UIntType __f> | |
450 | typename | |
451 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, | |
452 | __s, __b, __t, __c, __l, __f>::result_type | |
453 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, | |
454 | __s, __b, __t, __c, __l, __f>:: | |
455 | operator()() | |
456 | { | |
457 | // Reload the vector - cost is O(n) amortized over n calls. | |
458 | if (_M_p >= state_size) | |
b668e41a | 459 | _M_gen_rand(); |
8e79468d BK |
460 | |
461 | // Calculate o(x(i)). | |
462 | result_type __z = _M_x[_M_p++]; | |
463 | __z ^= (__z >> __u) & __d; | |
464 | __z ^= (__z << __s) & __b; | |
465 | __z ^= (__z << __t) & __c; | |
466 | __z ^= (__z >> __l); | |
467 | ||
468 | return __z; | |
469 | } | |
470 | ||
471 | template<typename _UIntType, size_t __w, | |
472 | size_t __n, size_t __m, size_t __r, | |
473 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
474 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
475 | _UIntType __f, typename _CharT, typename _Traits> | |
476 | std::basic_ostream<_CharT, _Traits>& | |
477 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
478 | const mersenne_twister_engine<_UIntType, __w, __n, __m, | |
479 | __r, __a, __u, __d, __s, __b, __t, __c, __l, __f>& __x) | |
480 | { | |
160e95dc | 481 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
482 | |
483 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
484 | const _CharT __fill = __os.fill(); | |
485 | const _CharT __space = __os.widen(' '); | |
95fe602e | 486 | __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left); |
8e79468d BK |
487 | __os.fill(__space); |
488 | ||
31645179 | 489 | for (size_t __i = 0; __i < __n; ++__i) |
8e79468d | 490 | __os << __x._M_x[__i] << __space; |
31645179 | 491 | __os << __x._M_p; |
8e79468d BK |
492 | |
493 | __os.flags(__flags); | |
494 | __os.fill(__fill); | |
495 | return __os; | |
496 | } | |
497 | ||
498 | template<typename _UIntType, size_t __w, | |
499 | size_t __n, size_t __m, size_t __r, | |
500 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
501 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
502 | _UIntType __f, typename _CharT, typename _Traits> | |
503 | std::basic_istream<_CharT, _Traits>& | |
504 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
505 | mersenne_twister_engine<_UIntType, __w, __n, __m, | |
506 | __r, __a, __u, __d, __s, __b, __t, __c, __l, __f>& __x) | |
507 | { | |
160e95dc | 508 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; |
8e79468d BK |
509 | |
510 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
511 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
512 | ||
513 | for (size_t __i = 0; __i < __n; ++__i) | |
514 | __is >> __x._M_x[__i]; | |
31645179 | 515 | __is >> __x._M_p; |
8e79468d BK |
516 | |
517 | __is.flags(__flags); | |
518 | return __is; | |
519 | } | |
520 | ||
996be6b6 | 521 | #if ! __cpp_inline_variables |
300ea283 | 522 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> |
94a86be0 | 523 | constexpr size_t |
300ea283 PC |
524 | subtract_with_carry_engine<_UIntType, __w, __s, __r>::word_size; |
525 | ||
526 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> | |
94a86be0 | 527 | constexpr size_t |
300ea283 PC |
528 | subtract_with_carry_engine<_UIntType, __w, __s, __r>::short_lag; |
529 | ||
530 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> | |
94a86be0 | 531 | constexpr size_t |
300ea283 PC |
532 | subtract_with_carry_engine<_UIntType, __w, __s, __r>::long_lag; |
533 | ||
534 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> | |
94a86be0 | 535 | constexpr _UIntType |
300ea283 | 536 | subtract_with_carry_engine<_UIntType, __w, __s, __r>::default_seed; |
996be6b6 | 537 | #endif |
300ea283 | 538 | |
8e79468d BK |
539 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> |
540 | void | |
541 | subtract_with_carry_engine<_UIntType, __w, __s, __r>:: | |
542 | seed(result_type __value) | |
543 | { | |
b94f4bef PC |
544 | std::linear_congruential_engine<result_type, 40014u, 0u, 2147483563u> |
545 | __lcg(__value == 0u ? default_seed : __value); | |
8e79468d | 546 | |
b94f4bef | 547 | const size_t __n = (__w + 31) / 32; |
8e79468d BK |
548 | |
549 | for (size_t __i = 0; __i < long_lag; ++__i) | |
550 | { | |
b94f4bef PC |
551 | _UIntType __sum = 0u; |
552 | _UIntType __factor = 1u; | |
8e79468d BK |
553 | for (size_t __j = 0; __j < __n; ++__j) |
554 | { | |
b94f4bef PC |
555 | __sum += __detail::__mod<uint_least32_t, |
556 | __detail::_Shift<uint_least32_t, 32>::__value> | |
8e79468d BK |
557 | (__lcg()) * __factor; |
558 | __factor *= __detail::_Shift<_UIntType, 32>::__value; | |
559 | } | |
b94f4bef | 560 | _M_x[__i] = __detail::__mod<_UIntType, |
96a9203b | 561 | __detail::_Shift<_UIntType, __w>::__value>(__sum); |
8e79468d BK |
562 | } |
563 | _M_carry = (_M_x[long_lag - 1] == 0) ? 1 : 0; | |
564 | _M_p = 0; | |
565 | } | |
566 | ||
567 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> | |
05eeebfe | 568 | template<typename _Sseq> |
5a7960da | 569 | auto |
15ecdcc6 PC |
570 | subtract_with_carry_engine<_UIntType, __w, __s, __r>:: |
571 | seed(_Sseq& __q) | |
5a7960da | 572 | -> _If_seed_seq<_Sseq> |
15ecdcc6 PC |
573 | { |
574 | const size_t __k = (__w + 31) / 32; | |
575 | uint_least32_t __arr[__r * __k]; | |
576 | __q.generate(__arr + 0, __arr + __r * __k); | |
577 | ||
578 | for (size_t __i = 0; __i < long_lag; ++__i) | |
579 | { | |
580 | _UIntType __sum = 0u; | |
581 | _UIntType __factor = 1u; | |
582 | for (size_t __j = 0; __j < __k; ++__j) | |
583 | { | |
584 | __sum += __arr[__k * __i + __j] * __factor; | |
585 | __factor *= __detail::_Shift<_UIntType, 32>::__value; | |
586 | } | |
587 | _M_x[__i] = __detail::__mod<_UIntType, | |
588 | __detail::_Shift<_UIntType, __w>::__value>(__sum); | |
589 | } | |
590 | _M_carry = (_M_x[long_lag - 1] == 0) ? 1 : 0; | |
591 | _M_p = 0; | |
592 | } | |
8e79468d BK |
593 | |
594 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> | |
595 | typename subtract_with_carry_engine<_UIntType, __w, __s, __r>:: | |
596 | result_type | |
597 | subtract_with_carry_engine<_UIntType, __w, __s, __r>:: | |
598 | operator()() | |
599 | { | |
600 | // Derive short lag index from current index. | |
601 | long __ps = _M_p - short_lag; | |
602 | if (__ps < 0) | |
603 | __ps += long_lag; | |
604 | ||
605 | // Calculate new x(i) without overflow or division. | |
606 | // NB: Thanks to the requirements for _UIntType, _M_x[_M_p] + _M_carry | |
607 | // cannot overflow. | |
608 | _UIntType __xi; | |
609 | if (_M_x[__ps] >= _M_x[_M_p] + _M_carry) | |
610 | { | |
611 | __xi = _M_x[__ps] - _M_x[_M_p] - _M_carry; | |
612 | _M_carry = 0; | |
613 | } | |
614 | else | |
615 | { | |
96a9203b PC |
616 | __xi = (__detail::_Shift<_UIntType, __w>::__value |
617 | - _M_x[_M_p] - _M_carry + _M_x[__ps]); | |
8e79468d BK |
618 | _M_carry = 1; |
619 | } | |
620 | _M_x[_M_p] = __xi; | |
621 | ||
622 | // Adjust current index to loop around in ring buffer. | |
623 | if (++_M_p >= long_lag) | |
624 | _M_p = 0; | |
625 | ||
626 | return __xi; | |
627 | } | |
628 | ||
629 | template<typename _UIntType, size_t __w, size_t __s, size_t __r, | |
630 | typename _CharT, typename _Traits> | |
631 | std::basic_ostream<_CharT, _Traits>& | |
632 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
633 | const subtract_with_carry_engine<_UIntType, | |
634 | __w, __s, __r>& __x) | |
635 | { | |
160e95dc | 636 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
637 | |
638 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
639 | const _CharT __fill = __os.fill(); | |
640 | const _CharT __space = __os.widen(' '); | |
95fe602e | 641 | __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left); |
8e79468d BK |
642 | __os.fill(__space); |
643 | ||
644 | for (size_t __i = 0; __i < __r; ++__i) | |
645 | __os << __x._M_x[__i] << __space; | |
31645179 | 646 | __os << __x._M_carry << __space << __x._M_p; |
8e79468d BK |
647 | |
648 | __os.flags(__flags); | |
649 | __os.fill(__fill); | |
650 | return __os; | |
651 | } | |
652 | ||
653 | template<typename _UIntType, size_t __w, size_t __s, size_t __r, | |
654 | typename _CharT, typename _Traits> | |
655 | std::basic_istream<_CharT, _Traits>& | |
656 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
657 | subtract_with_carry_engine<_UIntType, __w, __s, __r>& __x) | |
658 | { | |
160e95dc | 659 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; |
8e79468d BK |
660 | |
661 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
662 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
663 | ||
664 | for (size_t __i = 0; __i < __r; ++__i) | |
665 | __is >> __x._M_x[__i]; | |
666 | __is >> __x._M_carry; | |
31645179 | 667 | __is >> __x._M_p; |
8e79468d BK |
668 | |
669 | __is.flags(__flags); | |
670 | return __is; | |
671 | } | |
672 | ||
996be6b6 | 673 | #if ! __cpp_inline_variables |
300ea283 | 674 | template<typename _RandomNumberEngine, size_t __p, size_t __r> |
94a86be0 | 675 | constexpr size_t |
300ea283 PC |
676 | discard_block_engine<_RandomNumberEngine, __p, __r>::block_size; |
677 | ||
678 | template<typename _RandomNumberEngine, size_t __p, size_t __r> | |
94a86be0 | 679 | constexpr size_t |
300ea283 | 680 | discard_block_engine<_RandomNumberEngine, __p, __r>::used_block; |
996be6b6 | 681 | #endif |
300ea283 | 682 | |
8e79468d BK |
683 | template<typename _RandomNumberEngine, size_t __p, size_t __r> |
684 | typename discard_block_engine<_RandomNumberEngine, | |
685 | __p, __r>::result_type | |
686 | discard_block_engine<_RandomNumberEngine, __p, __r>:: | |
687 | operator()() | |
688 | { | |
689 | if (_M_n >= used_block) | |
690 | { | |
691 | _M_b.discard(block_size - _M_n); | |
692 | _M_n = 0; | |
693 | } | |
694 | ++_M_n; | |
695 | return _M_b(); | |
696 | } | |
697 | ||
698 | template<typename _RandomNumberEngine, size_t __p, size_t __r, | |
699 | typename _CharT, typename _Traits> | |
700 | std::basic_ostream<_CharT, _Traits>& | |
701 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
702 | const discard_block_engine<_RandomNumberEngine, | |
703 | __p, __r>& __x) | |
704 | { | |
160e95dc | 705 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
706 | |
707 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
708 | const _CharT __fill = __os.fill(); | |
709 | const _CharT __space = __os.widen(' '); | |
95fe602e | 710 | __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left); |
8e79468d BK |
711 | __os.fill(__space); |
712 | ||
713 | __os << __x.base() << __space << __x._M_n; | |
714 | ||
715 | __os.flags(__flags); | |
716 | __os.fill(__fill); | |
717 | return __os; | |
718 | } | |
719 | ||
720 | template<typename _RandomNumberEngine, size_t __p, size_t __r, | |
721 | typename _CharT, typename _Traits> | |
722 | std::basic_istream<_CharT, _Traits>& | |
723 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
724 | discard_block_engine<_RandomNumberEngine, __p, __r>& __x) | |
725 | { | |
160e95dc | 726 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; |
8e79468d BK |
727 | |
728 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
729 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
730 | ||
731 | __is >> __x._M_b >> __x._M_n; | |
732 | ||
733 | __is.flags(__flags); | |
734 | return __is; | |
735 | } | |
736 | ||
737 | ||
738 | template<typename _RandomNumberEngine, size_t __w, typename _UIntType> | |
739 | typename independent_bits_engine<_RandomNumberEngine, __w, _UIntType>:: | |
740 | result_type | |
741 | independent_bits_engine<_RandomNumberEngine, __w, _UIntType>:: | |
742 | operator()() | |
743 | { | |
f84ca6e7 PC |
744 | typedef typename _RandomNumberEngine::result_type _Eresult_type; |
745 | const _Eresult_type __r | |
746 | = (_M_b.max() - _M_b.min() < std::numeric_limits<_Eresult_type>::max() | |
747 | ? _M_b.max() - _M_b.min() + 1 : 0); | |
748 | const unsigned __edig = std::numeric_limits<_Eresult_type>::digits; | |
749 | const unsigned __m = __r ? std::__lg(__r) : __edig; | |
750 | ||
751 | typedef typename std::common_type<_Eresult_type, result_type>::type | |
752 | __ctype; | |
753 | const unsigned __cdig = std::numeric_limits<__ctype>::digits; | |
754 | ||
755 | unsigned __n, __n0; | |
756 | __ctype __s0, __s1, __y0, __y1; | |
757 | ||
8e79468d BK |
758 | for (size_t __i = 0; __i < 2; ++__i) |
759 | { | |
760 | __n = (__w + __m - 1) / __m + __i; | |
761 | __n0 = __n - __w % __n; | |
f84ca6e7 PC |
762 | const unsigned __w0 = __w / __n; // __w0 <= __m |
763 | ||
764 | __s0 = 0; | |
765 | __s1 = 0; | |
766 | if (__w0 < __cdig) | |
767 | { | |
768 | __s0 = __ctype(1) << __w0; | |
769 | __s1 = __s0 << 1; | |
770 | } | |
771 | ||
772 | __y0 = 0; | |
773 | __y1 = 0; | |
774 | if (__r) | |
775 | { | |
776 | __y0 = __s0 * (__r / __s0); | |
777 | if (__s1) | |
778 | __y1 = __s1 * (__r / __s1); | |
779 | ||
780 | if (__r - __y0 <= __y0 / __n) | |
781 | break; | |
782 | } | |
783 | else | |
8e79468d BK |
784 | break; |
785 | } | |
786 | ||
787 | result_type __sum = 0; | |
788 | for (size_t __k = 0; __k < __n0; ++__k) | |
789 | { | |
f84ca6e7 | 790 | __ctype __u; |
8e79468d | 791 | do |
6855fe45 | 792 | __u = _M_b() - _M_b.min(); |
f84ca6e7 PC |
793 | while (__y0 && __u >= __y0); |
794 | __sum = __s0 * __sum + (__s0 ? __u % __s0 : __u); | |
8e79468d BK |
795 | } |
796 | for (size_t __k = __n0; __k < __n; ++__k) | |
797 | { | |
f84ca6e7 | 798 | __ctype __u; |
8e79468d | 799 | do |
6855fe45 | 800 | __u = _M_b() - _M_b.min(); |
f84ca6e7 PC |
801 | while (__y1 && __u >= __y1); |
802 | __sum = __s1 * __sum + (__s1 ? __u % __s1 : __u); | |
8e79468d BK |
803 | } |
804 | return __sum; | |
805 | } | |
806 | ||
996be6b6 | 807 | #if ! __cpp_inline_variables |
300ea283 | 808 | template<typename _RandomNumberEngine, size_t __k> |
94a86be0 | 809 | constexpr size_t |
300ea283 | 810 | shuffle_order_engine<_RandomNumberEngine, __k>::table_size; |
996be6b6 | 811 | #endif |
300ea283 | 812 | |
60d9f254 JW |
813 | namespace __detail |
814 | { | |
815 | // Determine whether an integer is representable as double. | |
816 | template<typename _Tp> | |
817 | constexpr bool | |
818 | __representable_as_double(_Tp __x) noexcept | |
819 | { | |
64ba45c7 JW |
820 | static_assert(numeric_limits<_Tp>::is_integer, ""); |
821 | static_assert(!numeric_limits<_Tp>::is_signed, ""); | |
60d9f254 JW |
822 | // All integers <= 2^53 are representable. |
823 | return (__x <= (1ull << __DBL_MANT_DIG__)) | |
824 | // Between 2^53 and 2^54 only even numbers are representable. | |
825 | || (!(__x & 1) && __detail::__representable_as_double(__x >> 1)); | |
826 | } | |
827 | ||
828 | // Determine whether x+1 is representable as double. | |
829 | template<typename _Tp> | |
830 | constexpr bool | |
831 | __p1_representable_as_double(_Tp __x) noexcept | |
832 | { | |
64ba45c7 JW |
833 | static_assert(numeric_limits<_Tp>::is_integer, ""); |
834 | static_assert(!numeric_limits<_Tp>::is_signed, ""); | |
60d9f254 JW |
835 | return numeric_limits<_Tp>::digits < __DBL_MANT_DIG__ |
836 | || (bool(__x + 1u) // return false if x+1 wraps around to zero | |
837 | && __detail::__representable_as_double(__x + 1u)); | |
838 | } | |
839 | } | |
840 | ||
8e79468d BK |
841 | template<typename _RandomNumberEngine, size_t __k> |
842 | typename shuffle_order_engine<_RandomNumberEngine, __k>::result_type | |
843 | shuffle_order_engine<_RandomNumberEngine, __k>:: | |
844 | operator()() | |
845 | { | |
60d9f254 JW |
846 | constexpr result_type __range = max() - min(); |
847 | size_t __j = __k; | |
848 | const result_type __y = _M_y - min(); | |
849 | // Avoid using slower long double arithmetic if possible. | |
850 | if _GLIBCXX17_CONSTEXPR (__detail::__p1_representable_as_double(__range)) | |
851 | __j *= __y / (__range + 1.0); | |
852 | else | |
853 | __j *= __y / (__range + 1.0L); | |
8e79468d BK |
854 | _M_y = _M_v[__j]; |
855 | _M_v[__j] = _M_b(); | |
856 | ||
857 | return _M_y; | |
858 | } | |
859 | ||
860 | template<typename _RandomNumberEngine, size_t __k, | |
861 | typename _CharT, typename _Traits> | |
862 | std::basic_ostream<_CharT, _Traits>& | |
863 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
864 | const shuffle_order_engine<_RandomNumberEngine, __k>& __x) | |
865 | { | |
160e95dc | 866 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
867 | |
868 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
869 | const _CharT __fill = __os.fill(); | |
870 | const _CharT __space = __os.widen(' '); | |
95fe602e | 871 | __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left); |
8e79468d BK |
872 | __os.fill(__space); |
873 | ||
874 | __os << __x.base(); | |
875 | for (size_t __i = 0; __i < __k; ++__i) | |
876 | __os << __space << __x._M_v[__i]; | |
877 | __os << __space << __x._M_y; | |
878 | ||
879 | __os.flags(__flags); | |
880 | __os.fill(__fill); | |
881 | return __os; | |
882 | } | |
883 | ||
884 | template<typename _RandomNumberEngine, size_t __k, | |
885 | typename _CharT, typename _Traits> | |
886 | std::basic_istream<_CharT, _Traits>& | |
887 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
888 | shuffle_order_engine<_RandomNumberEngine, __k>& __x) | |
889 | { | |
160e95dc | 890 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; |
8e79468d BK |
891 | |
892 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
893 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
894 | ||
895 | __is >> __x._M_b; | |
896 | for (size_t __i = 0; __i < __k; ++__i) | |
897 | __is >> __x._M_v[__i]; | |
898 | __is >> __x._M_y; | |
899 | ||
900 | __is.flags(__flags); | |
901 | return __is; | |
902 | } | |
903 | ||
904 | ||
8e79468d BK |
905 | template<typename _IntType, typename _CharT, typename _Traits> |
906 | std::basic_ostream<_CharT, _Traits>& | |
907 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
908 | const uniform_int_distribution<_IntType>& __x) | |
909 | { | |
160e95dc | 910 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
911 | |
912 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
913 | const _CharT __fill = __os.fill(); | |
914 | const _CharT __space = __os.widen(' '); | |
915 | __os.flags(__ios_base::scientific | __ios_base::left); | |
916 | __os.fill(__space); | |
917 | ||
918 | __os << __x.a() << __space << __x.b(); | |
919 | ||
920 | __os.flags(__flags); | |
921 | __os.fill(__fill); | |
922 | return __os; | |
923 | } | |
924 | ||
925 | template<typename _IntType, typename _CharT, typename _Traits> | |
926 | std::basic_istream<_CharT, _Traits>& | |
927 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
928 | uniform_int_distribution<_IntType>& __x) | |
929 | { | |
160e95dc JW |
930 | using param_type |
931 | = typename uniform_int_distribution<_IntType>::param_type; | |
932 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
933 | |
934 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
935 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
936 | ||
937 | _IntType __a, __b; | |
160e95dc JW |
938 | if (__is >> __a >> __b) |
939 | __x.param(param_type(__a, __b)); | |
8e79468d BK |
940 | |
941 | __is.flags(__flags); | |
942 | return __is; | |
943 | } | |
944 | ||
945 | ||
7b93bdde UD |
946 | template<typename _RealType> |
947 | template<typename _ForwardIterator, | |
948 | typename _UniformRandomNumberGenerator> | |
949 | void | |
950 | uniform_real_distribution<_RealType>:: | |
951 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
952 | _UniformRandomNumberGenerator& __urng, | |
953 | const param_type& __p) | |
954 | { | |
955 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
956 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
957 | __aurng(__urng); | |
958 | auto __range = __p.b() - __p.a(); | |
959 | while (__f != __t) | |
960 | *__f++ = __aurng() * __range + __p.a(); | |
961 | } | |
962 | ||
8e79468d BK |
963 | template<typename _RealType, typename _CharT, typename _Traits> |
964 | std::basic_ostream<_CharT, _Traits>& | |
965 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
966 | const uniform_real_distribution<_RealType>& __x) | |
967 | { | |
160e95dc | 968 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
969 | |
970 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
971 | const _CharT __fill = __os.fill(); | |
972 | const std::streamsize __precision = __os.precision(); | |
973 | const _CharT __space = __os.widen(' '); | |
974 | __os.flags(__ios_base::scientific | __ios_base::left); | |
975 | __os.fill(__space); | |
7703dc47 | 976 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d BK |
977 | |
978 | __os << __x.a() << __space << __x.b(); | |
979 | ||
980 | __os.flags(__flags); | |
981 | __os.fill(__fill); | |
982 | __os.precision(__precision); | |
983 | return __os; | |
984 | } | |
985 | ||
986 | template<typename _RealType, typename _CharT, typename _Traits> | |
987 | std::basic_istream<_CharT, _Traits>& | |
988 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
989 | uniform_real_distribution<_RealType>& __x) | |
990 | { | |
160e95dc JW |
991 | using param_type |
992 | = typename uniform_real_distribution<_RealType>::param_type; | |
993 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
994 | |
995 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
996 | __is.flags(__ios_base::skipws); | |
997 | ||
998 | _RealType __a, __b; | |
160e95dc JW |
999 | if (__is >> __a >> __b) |
1000 | __x.param(param_type(__a, __b)); | |
8e79468d BK |
1001 | |
1002 | __is.flags(__flags); | |
1003 | return __is; | |
1004 | } | |
1005 | ||
1006 | ||
7b93bdde UD |
1007 | template<typename _ForwardIterator, |
1008 | typename _UniformRandomNumberGenerator> | |
1009 | void | |
1010 | std::bernoulli_distribution:: | |
1011 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1012 | _UniformRandomNumberGenerator& __urng, | |
1013 | const param_type& __p) | |
1014 | { | |
1015 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1016 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
1017 | __aurng(__urng); | |
1018 | auto __limit = __p.p() * (__aurng.max() - __aurng.min()); | |
1019 | ||
1020 | while (__f != __t) | |
1021 | *__f++ = (__aurng() - __aurng.min()) < __limit; | |
1022 | } | |
1023 | ||
8e79468d BK |
1024 | template<typename _CharT, typename _Traits> |
1025 | std::basic_ostream<_CharT, _Traits>& | |
1026 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1027 | const bernoulli_distribution& __x) | |
1028 | { | |
160e95dc | 1029 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
1030 | |
1031 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1032 | const _CharT __fill = __os.fill(); | |
1033 | const std::streamsize __precision = __os.precision(); | |
1034 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1035 | __os.fill(__os.widen(' ')); | |
7703dc47 | 1036 | __os.precision(std::numeric_limits<double>::max_digits10); |
8e79468d BK |
1037 | |
1038 | __os << __x.p(); | |
1039 | ||
1040 | __os.flags(__flags); | |
1041 | __os.fill(__fill); | |
1042 | __os.precision(__precision); | |
1043 | return __os; | |
1044 | } | |
1045 | ||
1046 | ||
1047 | template<typename _IntType> | |
1048 | template<typename _UniformRandomNumberGenerator> | |
1049 | typename geometric_distribution<_IntType>::result_type | |
1050 | geometric_distribution<_IntType>:: | |
1051 | operator()(_UniformRandomNumberGenerator& __urng, | |
1052 | const param_type& __param) | |
1053 | { | |
1054 | // About the epsilon thing see this thread: | |
1055 | // http://gcc.gnu.org/ml/gcc-patches/2006-10/msg00971.html | |
1056 | const double __naf = | |
1057 | (1 - std::numeric_limits<double>::epsilon()) / 2; | |
1058 | // The largest _RealType convertible to _IntType. | |
1059 | const double __thr = | |
1060 | std::numeric_limits<_IntType>::max() + __naf; | |
9b88236b | 1061 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> |
8e79468d BK |
1062 | __aurng(__urng); |
1063 | ||
1064 | double __cand; | |
1065 | do | |
c2d9083d | 1066 | __cand = std::floor(std::log(1.0 - __aurng()) / __param._M_log_1_p); |
8e79468d BK |
1067 | while (__cand >= __thr); |
1068 | ||
1069 | return result_type(__cand + __naf); | |
1070 | } | |
1071 | ||
7b93bdde UD |
1072 | template<typename _IntType> |
1073 | template<typename _ForwardIterator, | |
1074 | typename _UniformRandomNumberGenerator> | |
1075 | void | |
1076 | geometric_distribution<_IntType>:: | |
1077 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1078 | _UniformRandomNumberGenerator& __urng, | |
1079 | const param_type& __param) | |
1080 | { | |
1081 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1082 | // About the epsilon thing see this thread: | |
1083 | // http://gcc.gnu.org/ml/gcc-patches/2006-10/msg00971.html | |
1084 | const double __naf = | |
1085 | (1 - std::numeric_limits<double>::epsilon()) / 2; | |
1086 | // The largest _RealType convertible to _IntType. | |
1087 | const double __thr = | |
1088 | std::numeric_limits<_IntType>::max() + __naf; | |
1089 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
1090 | __aurng(__urng); | |
1091 | ||
1092 | while (__f != __t) | |
1093 | { | |
1094 | double __cand; | |
1095 | do | |
c2d9083d HY |
1096 | __cand = std::floor(std::log(1.0 - __aurng()) |
1097 | / __param._M_log_1_p); | |
7b93bdde UD |
1098 | while (__cand >= __thr); |
1099 | ||
1100 | *__f++ = __cand + __naf; | |
1101 | } | |
1102 | } | |
1103 | ||
8e79468d BK |
1104 | template<typename _IntType, |
1105 | typename _CharT, typename _Traits> | |
1106 | std::basic_ostream<_CharT, _Traits>& | |
1107 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1108 | const geometric_distribution<_IntType>& __x) | |
1109 | { | |
160e95dc | 1110 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
1111 | |
1112 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1113 | const _CharT __fill = __os.fill(); | |
1114 | const std::streamsize __precision = __os.precision(); | |
1115 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1116 | __os.fill(__os.widen(' ')); | |
7703dc47 | 1117 | __os.precision(std::numeric_limits<double>::max_digits10); |
8e79468d BK |
1118 | |
1119 | __os << __x.p(); | |
1120 | ||
1121 | __os.flags(__flags); | |
1122 | __os.fill(__fill); | |
1123 | __os.precision(__precision); | |
1124 | return __os; | |
1125 | } | |
1126 | ||
1127 | template<typename _IntType, | |
1128 | typename _CharT, typename _Traits> | |
1129 | std::basic_istream<_CharT, _Traits>& | |
1130 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
1131 | geometric_distribution<_IntType>& __x) | |
1132 | { | |
160e95dc JW |
1133 | using param_type = typename geometric_distribution<_IntType>::param_type; |
1134 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
1135 | |
1136 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
1137 | __is.flags(__ios_base::skipws); | |
1138 | ||
1139 | double __p; | |
160e95dc JW |
1140 | if (__is >> __p) |
1141 | __x.param(param_type(__p)); | |
8e79468d BK |
1142 | |
1143 | __is.flags(__flags); | |
1144 | return __is; | |
1145 | } | |
1146 | ||
ff2e697a | 1147 | // This is Leger's algorithm, also in Devroye, Ch. X, Example 1.5. |
f9b09dec PC |
1148 | template<typename _IntType> |
1149 | template<typename _UniformRandomNumberGenerator> | |
1150 | typename negative_binomial_distribution<_IntType>::result_type | |
1151 | negative_binomial_distribution<_IntType>:: | |
1152 | operator()(_UniformRandomNumberGenerator& __urng) | |
1153 | { | |
1154 | const double __y = _M_gd(__urng); | |
1155 | ||
1156 | // XXX Is the constructor too slow? | |
ff2e697a | 1157 | std::poisson_distribution<result_type> __poisson(__y); |
f9b09dec PC |
1158 | return __poisson(__urng); |
1159 | } | |
1160 | ||
8e79468d BK |
1161 | template<typename _IntType> |
1162 | template<typename _UniformRandomNumberGenerator> | |
1163 | typename negative_binomial_distribution<_IntType>::result_type | |
1164 | negative_binomial_distribution<_IntType>:: | |
1165 | operator()(_UniformRandomNumberGenerator& __urng, | |
1166 | const param_type& __p) | |
1167 | { | |
e5fbc9fc | 1168 | typedef typename std::gamma_distribution<double>::param_type |
f9b09dec PC |
1169 | param_type; |
1170 | ||
ff2e697a PC |
1171 | const double __y = |
1172 | _M_gd(__urng, param_type(__p.k(), (1.0 - __p.p()) / __p.p())); | |
8e79468d | 1173 | |
ff2e697a | 1174 | std::poisson_distribution<result_type> __poisson(__y); |
b01630bb | 1175 | return __poisson(__urng); |
8e79468d BK |
1176 | } |
1177 | ||
7b93bdde UD |
1178 | template<typename _IntType> |
1179 | template<typename _ForwardIterator, | |
1180 | typename _UniformRandomNumberGenerator> | |
1181 | void | |
1182 | negative_binomial_distribution<_IntType>:: | |
1183 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1184 | _UniformRandomNumberGenerator& __urng) | |
1185 | { | |
1186 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1187 | while (__f != __t) | |
1188 | { | |
1189 | const double __y = _M_gd(__urng); | |
1190 | ||
1191 | // XXX Is the constructor too slow? | |
1192 | std::poisson_distribution<result_type> __poisson(__y); | |
1193 | *__f++ = __poisson(__urng); | |
1194 | } | |
1195 | } | |
1196 | ||
1197 | template<typename _IntType> | |
1198 | template<typename _ForwardIterator, | |
1199 | typename _UniformRandomNumberGenerator> | |
1200 | void | |
1201 | negative_binomial_distribution<_IntType>:: | |
1202 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1203 | _UniformRandomNumberGenerator& __urng, | |
1204 | const param_type& __p) | |
1205 | { | |
1206 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1207 | typename std::gamma_distribution<result_type>::param_type | |
1208 | __p2(__p.k(), (1.0 - __p.p()) / __p.p()); | |
1209 | ||
1210 | while (__f != __t) | |
1211 | { | |
1212 | const double __y = _M_gd(__urng, __p2); | |
1213 | ||
1214 | std::poisson_distribution<result_type> __poisson(__y); | |
1215 | *__f++ = __poisson(__urng); | |
1216 | } | |
1217 | } | |
1218 | ||
8e79468d BK |
1219 | template<typename _IntType, typename _CharT, typename _Traits> |
1220 | std::basic_ostream<_CharT, _Traits>& | |
1221 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1222 | const negative_binomial_distribution<_IntType>& __x) | |
1223 | { | |
160e95dc | 1224 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
1225 | |
1226 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1227 | const _CharT __fill = __os.fill(); | |
1228 | const std::streamsize __precision = __os.precision(); | |
1229 | const _CharT __space = __os.widen(' '); | |
1230 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1231 | __os.fill(__os.widen(' ')); | |
7703dc47 | 1232 | __os.precision(std::numeric_limits<double>::max_digits10); |
8e79468d | 1233 | |
f9b09dec PC |
1234 | __os << __x.k() << __space << __x.p() |
1235 | << __space << __x._M_gd; | |
8e79468d BK |
1236 | |
1237 | __os.flags(__flags); | |
1238 | __os.fill(__fill); | |
1239 | __os.precision(__precision); | |
1240 | return __os; | |
1241 | } | |
1242 | ||
1243 | template<typename _IntType, typename _CharT, typename _Traits> | |
1244 | std::basic_istream<_CharT, _Traits>& | |
1245 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
1246 | negative_binomial_distribution<_IntType>& __x) | |
1247 | { | |
160e95dc JW |
1248 | using param_type |
1249 | = typename negative_binomial_distribution<_IntType>::param_type; | |
1250 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
1251 | |
1252 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
1253 | __is.flags(__ios_base::skipws); | |
1254 | ||
1255 | _IntType __k; | |
1256 | double __p; | |
160e95dc JW |
1257 | if (__is >> __k >> __p >> __x._M_gd) |
1258 | __x.param(param_type(__k, __p)); | |
8e79468d BK |
1259 | |
1260 | __is.flags(__flags); | |
1261 | return __is; | |
1262 | } | |
1263 | ||
1264 | ||
1265 | template<typename _IntType> | |
1266 | void | |
1267 | poisson_distribution<_IntType>::param_type:: | |
1268 | _M_initialize() | |
1269 | { | |
1270 | #if _GLIBCXX_USE_C99_MATH_TR1 | |
1271 | if (_M_mean >= 12) | |
1272 | { | |
1273 | const double __m = std::floor(_M_mean); | |
1274 | _M_lm_thr = std::log(_M_mean); | |
1275 | _M_lfm = std::lgamma(__m + 1); | |
1276 | _M_sm = std::sqrt(__m); | |
1277 | ||
1278 | const double __pi_4 = 0.7853981633974483096156608458198757L; | |
1279 | const double __dx = std::sqrt(2 * __m * std::log(32 * __m | |
1280 | / __pi_4)); | |
3af7efb7 | 1281 | _M_d = std::round(std::max<double>(6.0, std::min(__m, __dx))); |
8e79468d BK |
1282 | const double __cx = 2 * __m + _M_d; |
1283 | _M_scx = std::sqrt(__cx / 2); | |
1284 | _M_1cx = 1 / __cx; | |
1285 | ||
1286 | _M_c2b = std::sqrt(__pi_4 * __cx) * std::exp(_M_1cx); | |
1287 | _M_cb = 2 * __cx * std::exp(-_M_d * _M_1cx * (1 + _M_d / 2)) | |
1288 | / _M_d; | |
1289 | } | |
1290 | else | |
1291 | #endif | |
1292 | _M_lm_thr = std::exp(-_M_mean); | |
1293 | } | |
1294 | ||
1295 | /** | |
1296 | * A rejection algorithm when mean >= 12 and a simple method based | |
1297 | * upon the multiplication of uniform random variates otherwise. | |
1298 | * NB: The former is available only if _GLIBCXX_USE_C99_MATH_TR1 | |
1299 | * is defined. | |
1300 | * | |
1301 | * Reference: | |
2a60a9f6 | 1302 | * Devroye, L. Non-Uniform Random Variates Generation. Springer-Verlag, |
8e79468d BK |
1303 | * New York, 1986, Ch. X, Sects. 3.3 & 3.4 (+ Errata!). |
1304 | */ | |
1305 | template<typename _IntType> | |
1306 | template<typename _UniformRandomNumberGenerator> | |
1307 | typename poisson_distribution<_IntType>::result_type | |
1308 | poisson_distribution<_IntType>:: | |
1309 | operator()(_UniformRandomNumberGenerator& __urng, | |
1310 | const param_type& __param) | |
1311 | { | |
1312 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
1313 | __aurng(__urng); | |
1314 | #if _GLIBCXX_USE_C99_MATH_TR1 | |
1315 | if (__param.mean() >= 12) | |
1316 | { | |
1317 | double __x; | |
1318 | ||
1319 | // See comments above... | |
1320 | const double __naf = | |
1321 | (1 - std::numeric_limits<double>::epsilon()) / 2; | |
1322 | const double __thr = | |
1323 | std::numeric_limits<_IntType>::max() + __naf; | |
1324 | ||
1325 | const double __m = std::floor(__param.mean()); | |
1326 | // sqrt(pi / 2) | |
1327 | const double __spi_2 = 1.2533141373155002512078826424055226L; | |
1328 | const double __c1 = __param._M_sm * __spi_2; | |
1329 | const double __c2 = __param._M_c2b + __c1; | |
1330 | const double __c3 = __c2 + 1; | |
1331 | const double __c4 = __c3 + 1; | |
73986c31 MP |
1332 | // 1 / 78 |
1333 | const double __178 = 0.0128205128205128205128205128205128L; | |
8e79468d BK |
1334 | // e^(1 / 78) |
1335 | const double __e178 = 1.0129030479320018583185514777512983L; | |
1336 | const double __c5 = __c4 + __e178; | |
1337 | const double __c = __param._M_cb + __c5; | |
1338 | const double __2cx = 2 * (2 * __m + __param._M_d); | |
1339 | ||
1340 | bool __reject = true; | |
1341 | do | |
1342 | { | |
1343 | const double __u = __c * __aurng(); | |
c2d9083d | 1344 | const double __e = -std::log(1.0 - __aurng()); |
8e79468d BK |
1345 | |
1346 | double __w = 0.0; | |
1347 | ||
1348 | if (__u <= __c1) | |
1349 | { | |
1350 | const double __n = _M_nd(__urng); | |
1351 | const double __y = -std::abs(__n) * __param._M_sm - 1; | |
1352 | __x = std::floor(__y); | |
1353 | __w = -__n * __n / 2; | |
1354 | if (__x < -__m) | |
1355 | continue; | |
1356 | } | |
1357 | else if (__u <= __c2) | |
1358 | { | |
1359 | const double __n = _M_nd(__urng); | |
1360 | const double __y = 1 + std::abs(__n) * __param._M_scx; | |
1361 | __x = std::ceil(__y); | |
1362 | __w = __y * (2 - __y) * __param._M_1cx; | |
1363 | if (__x > __param._M_d) | |
1364 | continue; | |
1365 | } | |
1366 | else if (__u <= __c3) | |
1367 | // NB: This case not in the book, nor in the Errata, | |
1368 | // but should be ok... | |
1369 | __x = -1; | |
1370 | else if (__u <= __c4) | |
1371 | __x = 0; | |
1372 | else if (__u <= __c5) | |
73986c31 MP |
1373 | { |
1374 | __x = 1; | |
1375 | // Only in the Errata, see libstdc++/83237. | |
1376 | __w = __178; | |
1377 | } | |
8e79468d BK |
1378 | else |
1379 | { | |
c2d9083d | 1380 | const double __v = -std::log(1.0 - __aurng()); |
8e79468d BK |
1381 | const double __y = __param._M_d |
1382 | + __v * __2cx / __param._M_d; | |
1383 | __x = std::ceil(__y); | |
1384 | __w = -__param._M_d * __param._M_1cx * (1 + __y / 2); | |
1385 | } | |
1386 | ||
1387 | __reject = (__w - __e - __x * __param._M_lm_thr | |
1388 | > __param._M_lfm - std::lgamma(__x + __m + 1)); | |
1389 | ||
1390 | __reject |= __x + __m >= __thr; | |
1391 | ||
1392 | } while (__reject); | |
1393 | ||
1394 | return result_type(__x + __m + __naf); | |
1395 | } | |
1396 | else | |
1397 | #endif | |
1398 | { | |
1399 | _IntType __x = 0; | |
1400 | double __prod = 1.0; | |
1401 | ||
1402 | do | |
1403 | { | |
1404 | __prod *= __aurng(); | |
1405 | __x += 1; | |
1406 | } | |
1407 | while (__prod > __param._M_lm_thr); | |
1408 | ||
1409 | return __x - 1; | |
1410 | } | |
1411 | } | |
1412 | ||
7b93bdde UD |
1413 | template<typename _IntType> |
1414 | template<typename _ForwardIterator, | |
1415 | typename _UniformRandomNumberGenerator> | |
1416 | void | |
1417 | poisson_distribution<_IntType>:: | |
1418 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1419 | _UniformRandomNumberGenerator& __urng, | |
1420 | const param_type& __param) | |
1421 | { | |
1422 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1423 | // We could duplicate everything from operator()... | |
1424 | while (__f != __t) | |
1425 | *__f++ = this->operator()(__urng, __param); | |
1426 | } | |
1427 | ||
8e79468d BK |
1428 | template<typename _IntType, |
1429 | typename _CharT, typename _Traits> | |
1430 | std::basic_ostream<_CharT, _Traits>& | |
1431 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1432 | const poisson_distribution<_IntType>& __x) | |
1433 | { | |
160e95dc | 1434 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
1435 | |
1436 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1437 | const _CharT __fill = __os.fill(); | |
1438 | const std::streamsize __precision = __os.precision(); | |
1439 | const _CharT __space = __os.widen(' '); | |
1440 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1441 | __os.fill(__space); | |
7703dc47 | 1442 | __os.precision(std::numeric_limits<double>::max_digits10); |
8e79468d BK |
1443 | |
1444 | __os << __x.mean() << __space << __x._M_nd; | |
1445 | ||
1446 | __os.flags(__flags); | |
1447 | __os.fill(__fill); | |
1448 | __os.precision(__precision); | |
1449 | return __os; | |
1450 | } | |
1451 | ||
1452 | template<typename _IntType, | |
1453 | typename _CharT, typename _Traits> | |
1454 | std::basic_istream<_CharT, _Traits>& | |
1455 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
1456 | poisson_distribution<_IntType>& __x) | |
1457 | { | |
160e95dc JW |
1458 | using param_type = typename poisson_distribution<_IntType>::param_type; |
1459 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
1460 | |
1461 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
1462 | __is.flags(__ios_base::skipws); | |
1463 | ||
1464 | double __mean; | |
160e95dc JW |
1465 | if (__is >> __mean >> __x._M_nd) |
1466 | __x.param(param_type(__mean)); | |
8e79468d BK |
1467 | |
1468 | __is.flags(__flags); | |
1469 | return __is; | |
1470 | } | |
1471 | ||
1472 | ||
1473 | template<typename _IntType> | |
1474 | void | |
1475 | binomial_distribution<_IntType>::param_type:: | |
1476 | _M_initialize() | |
1477 | { | |
1478 | const double __p12 = _M_p <= 0.5 ? _M_p : 1.0 - _M_p; | |
1479 | ||
1480 | _M_easy = true; | |
1481 | ||
1482 | #if _GLIBCXX_USE_C99_MATH_TR1 | |
1483 | if (_M_t * __p12 >= 8) | |
1484 | { | |
1485 | _M_easy = false; | |
1486 | const double __np = std::floor(_M_t * __p12); | |
1487 | const double __pa = __np / _M_t; | |
1488 | const double __1p = 1 - __pa; | |
1489 | ||
1490 | const double __pi_4 = 0.7853981633974483096156608458198757L; | |
1491 | const double __d1x = | |
1492 | std::sqrt(__np * __1p * std::log(32 * __np | |
1493 | / (81 * __pi_4 * __1p))); | |
3af7efb7 | 1494 | _M_d1 = std::round(std::max<double>(1.0, __d1x)); |
8e79468d BK |
1495 | const double __d2x = |
1496 | std::sqrt(__np * __1p * std::log(32 * _M_t * __1p | |
1497 | / (__pi_4 * __pa))); | |
3af7efb7 | 1498 | _M_d2 = std::round(std::max<double>(1.0, __d2x)); |
8e79468d BK |
1499 | |
1500 | // sqrt(pi / 2) | |
1501 | const double __spi_2 = 1.2533141373155002512078826424055226L; | |
1502 | _M_s1 = std::sqrt(__np * __1p) * (1 + _M_d1 / (4 * __np)); | |
1503 | _M_s2 = std::sqrt(__np * __1p) * (1 + _M_d2 / (4 * _M_t * __1p)); | |
1504 | _M_c = 2 * _M_d1 / __np; | |
1505 | _M_a1 = std::exp(_M_c) * _M_s1 * __spi_2; | |
1506 | const double __a12 = _M_a1 + _M_s2 * __spi_2; | |
1507 | const double __s1s = _M_s1 * _M_s1; | |
1508 | _M_a123 = __a12 + (std::exp(_M_d1 / (_M_t * __1p)) | |
1509 | * 2 * __s1s / _M_d1 | |
1510 | * std::exp(-_M_d1 * _M_d1 / (2 * __s1s))); | |
1511 | const double __s2s = _M_s2 * _M_s2; | |
1512 | _M_s = (_M_a123 + 2 * __s2s / _M_d2 | |
1513 | * std::exp(-_M_d2 * _M_d2 / (2 * __s2s))); | |
1514 | _M_lf = (std::lgamma(__np + 1) | |
1515 | + std::lgamma(_M_t - __np + 1)); | |
1516 | _M_lp1p = std::log(__pa / __1p); | |
1517 | ||
1518 | _M_q = -std::log(1 - (__p12 - __pa) / __1p); | |
1519 | } | |
1520 | else | |
1521 | #endif | |
1522 | _M_q = -std::log(1 - __p12); | |
1523 | } | |
1524 | ||
1525 | template<typename _IntType> | |
1526 | template<typename _UniformRandomNumberGenerator> | |
1527 | typename binomial_distribution<_IntType>::result_type | |
1528 | binomial_distribution<_IntType>:: | |
07bba3b1 PC |
1529 | _M_waiting(_UniformRandomNumberGenerator& __urng, |
1530 | _IntType __t, double __q) | |
8e79468d BK |
1531 | { |
1532 | _IntType __x = 0; | |
1533 | double __sum = 0.0; | |
1534 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
1535 | __aurng(__urng); | |
1536 | ||
1537 | do | |
1538 | { | |
85018f40 | 1539 | if (__t == __x) |
9ea146e6 MLI |
1540 | return __x; |
1541 | const double __e = -std::log(1.0 - __aurng()); | |
8e79468d BK |
1542 | __sum += __e / (__t - __x); |
1543 | __x += 1; | |
1544 | } | |
07bba3b1 | 1545 | while (__sum <= __q); |
8e79468d BK |
1546 | |
1547 | return __x - 1; | |
1548 | } | |
1549 | ||
1550 | /** | |
1551 | * A rejection algorithm when t * p >= 8 and a simple waiting time | |
1552 | * method - the second in the referenced book - otherwise. | |
1553 | * NB: The former is available only if _GLIBCXX_USE_C99_MATH_TR1 | |
1554 | * is defined. | |
1555 | * | |
1556 | * Reference: | |
2a60a9f6 | 1557 | * Devroye, L. Non-Uniform Random Variates Generation. Springer-Verlag, |
8e79468d BK |
1558 | * New York, 1986, Ch. X, Sect. 4 (+ Errata!). |
1559 | */ | |
1560 | template<typename _IntType> | |
1561 | template<typename _UniformRandomNumberGenerator> | |
1562 | typename binomial_distribution<_IntType>::result_type | |
1563 | binomial_distribution<_IntType>:: | |
1564 | operator()(_UniformRandomNumberGenerator& __urng, | |
1565 | const param_type& __param) | |
1566 | { | |
1567 | result_type __ret; | |
1568 | const _IntType __t = __param.t(); | |
d8d4db33 | 1569 | const double __p = __param.p(); |
8e79468d BK |
1570 | const double __p12 = __p <= 0.5 ? __p : 1.0 - __p; |
1571 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
1572 | __aurng(__urng); | |
1573 | ||
1574 | #if _GLIBCXX_USE_C99_MATH_TR1 | |
1575 | if (!__param._M_easy) | |
1576 | { | |
1577 | double __x; | |
1578 | ||
1579 | // See comments above... | |
1580 | const double __naf = | |
1581 | (1 - std::numeric_limits<double>::epsilon()) / 2; | |
1582 | const double __thr = | |
1583 | std::numeric_limits<_IntType>::max() + __naf; | |
1584 | ||
1585 | const double __np = std::floor(__t * __p12); | |
1586 | ||
1587 | // sqrt(pi / 2) | |
1588 | const double __spi_2 = 1.2533141373155002512078826424055226L; | |
1589 | const double __a1 = __param._M_a1; | |
1590 | const double __a12 = __a1 + __param._M_s2 * __spi_2; | |
1591 | const double __a123 = __param._M_a123; | |
1592 | const double __s1s = __param._M_s1 * __param._M_s1; | |
1593 | const double __s2s = __param._M_s2 * __param._M_s2; | |
1594 | ||
1595 | bool __reject; | |
1596 | do | |
1597 | { | |
1598 | const double __u = __param._M_s * __aurng(); | |
1599 | ||
1600 | double __v; | |
1601 | ||
1602 | if (__u <= __a1) | |
1603 | { | |
1604 | const double __n = _M_nd(__urng); | |
1605 | const double __y = __param._M_s1 * std::abs(__n); | |
1606 | __reject = __y >= __param._M_d1; | |
1607 | if (!__reject) | |
1608 | { | |
c2d9083d | 1609 | const double __e = -std::log(1.0 - __aurng()); |
8e79468d BK |
1610 | __x = std::floor(__y); |
1611 | __v = -__e - __n * __n / 2 + __param._M_c; | |
1612 | } | |
1613 | } | |
1614 | else if (__u <= __a12) | |
1615 | { | |
1616 | const double __n = _M_nd(__urng); | |
1617 | const double __y = __param._M_s2 * std::abs(__n); | |
1618 | __reject = __y >= __param._M_d2; | |
1619 | if (!__reject) | |
1620 | { | |
c2d9083d | 1621 | const double __e = -std::log(1.0 - __aurng()); |
8e79468d BK |
1622 | __x = std::floor(-__y); |
1623 | __v = -__e - __n * __n / 2; | |
1624 | } | |
1625 | } | |
1626 | else if (__u <= __a123) | |
1627 | { | |
c2d9083d HY |
1628 | const double __e1 = -std::log(1.0 - __aurng()); |
1629 | const double __e2 = -std::log(1.0 - __aurng()); | |
8e79468d BK |
1630 | |
1631 | const double __y = __param._M_d1 | |
1632 | + 2 * __s1s * __e1 / __param._M_d1; | |
1633 | __x = std::floor(__y); | |
1634 | __v = (-__e2 + __param._M_d1 * (1 / (__t - __np) | |
1635 | -__y / (2 * __s1s))); | |
1636 | __reject = false; | |
1637 | } | |
1638 | else | |
1639 | { | |
c2d9083d HY |
1640 | const double __e1 = -std::log(1.0 - __aurng()); |
1641 | const double __e2 = -std::log(1.0 - __aurng()); | |
8e79468d BK |
1642 | |
1643 | const double __y = __param._M_d2 | |
1644 | + 2 * __s2s * __e1 / __param._M_d2; | |
1645 | __x = std::floor(-__y); | |
1646 | __v = -__e2 - __param._M_d2 * __y / (2 * __s2s); | |
1647 | __reject = false; | |
1648 | } | |
1649 | ||
1650 | __reject = __reject || __x < -__np || __x > __t - __np; | |
1651 | if (!__reject) | |
1652 | { | |
1653 | const double __lfx = | |
1654 | std::lgamma(__np + __x + 1) | |
1655 | + std::lgamma(__t - (__np + __x) + 1); | |
1656 | __reject = __v > __param._M_lf - __lfx | |
1657 | + __x * __param._M_lp1p; | |
1658 | } | |
1659 | ||
1660 | __reject |= __x + __np >= __thr; | |
1661 | } | |
1662 | while (__reject); | |
1663 | ||
1664 | __x += __np + __naf; | |
1665 | ||
07bba3b1 PC |
1666 | const _IntType __z = _M_waiting(__urng, __t - _IntType(__x), |
1667 | __param._M_q); | |
8e79468d BK |
1668 | __ret = _IntType(__x) + __z; |
1669 | } | |
1670 | else | |
1671 | #endif | |
07bba3b1 | 1672 | __ret = _M_waiting(__urng, __t, __param._M_q); |
8e79468d BK |
1673 | |
1674 | if (__p12 != __p) | |
1675 | __ret = __t - __ret; | |
1676 | return __ret; | |
1677 | } | |
1678 | ||
7b93bdde UD |
1679 | template<typename _IntType> |
1680 | template<typename _ForwardIterator, | |
1681 | typename _UniformRandomNumberGenerator> | |
1682 | void | |
1683 | binomial_distribution<_IntType>:: | |
1684 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1685 | _UniformRandomNumberGenerator& __urng, | |
1686 | const param_type& __param) | |
1687 | { | |
1688 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1689 | // We could duplicate everything from operator()... | |
1690 | while (__f != __t) | |
1691 | *__f++ = this->operator()(__urng, __param); | |
1692 | } | |
1693 | ||
8e79468d BK |
1694 | template<typename _IntType, |
1695 | typename _CharT, typename _Traits> | |
1696 | std::basic_ostream<_CharT, _Traits>& | |
1697 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1698 | const binomial_distribution<_IntType>& __x) | |
1699 | { | |
160e95dc | 1700 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
1701 | |
1702 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1703 | const _CharT __fill = __os.fill(); | |
1704 | const std::streamsize __precision = __os.precision(); | |
1705 | const _CharT __space = __os.widen(' '); | |
1706 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1707 | __os.fill(__space); | |
7703dc47 | 1708 | __os.precision(std::numeric_limits<double>::max_digits10); |
8e79468d BK |
1709 | |
1710 | __os << __x.t() << __space << __x.p() | |
1711 | << __space << __x._M_nd; | |
1712 | ||
1713 | __os.flags(__flags); | |
1714 | __os.fill(__fill); | |
1715 | __os.precision(__precision); | |
1716 | return __os; | |
1717 | } | |
1718 | ||
1719 | template<typename _IntType, | |
1720 | typename _CharT, typename _Traits> | |
1721 | std::basic_istream<_CharT, _Traits>& | |
1722 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
1723 | binomial_distribution<_IntType>& __x) | |
1724 | { | |
160e95dc JW |
1725 | using param_type = typename binomial_distribution<_IntType>::param_type; |
1726 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
1727 | |
1728 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
1729 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
1730 | ||
1731 | _IntType __t; | |
1732 | double __p; | |
160e95dc JW |
1733 | if (__is >> __t >> __p >> __x._M_nd) |
1734 | __x.param(param_type(__t, __p)); | |
8e79468d BK |
1735 | |
1736 | __is.flags(__flags); | |
1737 | return __is; | |
1738 | } | |
1739 | ||
1740 | ||
7b93bdde UD |
1741 | template<typename _RealType> |
1742 | template<typename _ForwardIterator, | |
1743 | typename _UniformRandomNumberGenerator> | |
1744 | void | |
1745 | std::exponential_distribution<_RealType>:: | |
1746 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1747 | _UniformRandomNumberGenerator& __urng, | |
1748 | const param_type& __p) | |
1749 | { | |
1750 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1751 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
1752 | __aurng(__urng); | |
1753 | while (__f != __t) | |
c2d9083d | 1754 | *__f++ = -std::log(result_type(1) - __aurng()) / __p.lambda(); |
7b93bdde UD |
1755 | } |
1756 | ||
8e79468d BK |
1757 | template<typename _RealType, typename _CharT, typename _Traits> |
1758 | std::basic_ostream<_CharT, _Traits>& | |
1759 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1760 | const exponential_distribution<_RealType>& __x) | |
1761 | { | |
160e95dc | 1762 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
1763 | |
1764 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1765 | const _CharT __fill = __os.fill(); | |
1766 | const std::streamsize __precision = __os.precision(); | |
1767 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1768 | __os.fill(__os.widen(' ')); | |
7703dc47 | 1769 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d BK |
1770 | |
1771 | __os << __x.lambda(); | |
1772 | ||
1773 | __os.flags(__flags); | |
1774 | __os.fill(__fill); | |
1775 | __os.precision(__precision); | |
1776 | return __os; | |
1777 | } | |
1778 | ||
1779 | template<typename _RealType, typename _CharT, typename _Traits> | |
1780 | std::basic_istream<_CharT, _Traits>& | |
1781 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
1782 | exponential_distribution<_RealType>& __x) | |
1783 | { | |
160e95dc JW |
1784 | using param_type |
1785 | = typename exponential_distribution<_RealType>::param_type; | |
1786 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
1787 | |
1788 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
1789 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
1790 | ||
1791 | _RealType __lambda; | |
160e95dc JW |
1792 | if (__is >> __lambda) |
1793 | __x.param(param_type(__lambda)); | |
8e79468d BK |
1794 | |
1795 | __is.flags(__flags); | |
1796 | return __is; | |
1797 | } | |
1798 | ||
1799 | ||
8e79468d BK |
1800 | /** |
1801 | * Polar method due to Marsaglia. | |
1802 | * | |
2a60a9f6 | 1803 | * Devroye, L. Non-Uniform Random Variates Generation. Springer-Verlag, |
8e79468d BK |
1804 | * New York, 1986, Ch. V, Sect. 4.4. |
1805 | */ | |
1806 | template<typename _RealType> | |
1807 | template<typename _UniformRandomNumberGenerator> | |
1808 | typename normal_distribution<_RealType>::result_type | |
1809 | normal_distribution<_RealType>:: | |
1810 | operator()(_UniformRandomNumberGenerator& __urng, | |
1811 | const param_type& __param) | |
1812 | { | |
1813 | result_type __ret; | |
1814 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
1815 | __aurng(__urng); | |
1816 | ||
1817 | if (_M_saved_available) | |
1818 | { | |
1819 | _M_saved_available = false; | |
1820 | __ret = _M_saved; | |
1821 | } | |
1822 | else | |
1823 | { | |
1824 | result_type __x, __y, __r2; | |
1825 | do | |
1826 | { | |
1827 | __x = result_type(2.0) * __aurng() - 1.0; | |
1828 | __y = result_type(2.0) * __aurng() - 1.0; | |
1829 | __r2 = __x * __x + __y * __y; | |
1830 | } | |
1831 | while (__r2 > 1.0 || __r2 == 0.0); | |
1832 | ||
1833 | const result_type __mult = std::sqrt(-2 * std::log(__r2) / __r2); | |
1834 | _M_saved = __x * __mult; | |
1835 | _M_saved_available = true; | |
1836 | __ret = __y * __mult; | |
1837 | } | |
1838 | ||
1839 | __ret = __ret * __param.stddev() + __param.mean(); | |
1840 | return __ret; | |
1841 | } | |
1842 | ||
7b93bdde UD |
1843 | template<typename _RealType> |
1844 | template<typename _ForwardIterator, | |
1845 | typename _UniformRandomNumberGenerator> | |
1846 | void | |
1847 | normal_distribution<_RealType>:: | |
1848 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1849 | _UniformRandomNumberGenerator& __urng, | |
1850 | const param_type& __param) | |
1851 | { | |
1852 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1853 | ||
1854 | if (__f == __t) | |
1855 | return; | |
1856 | ||
1857 | if (_M_saved_available) | |
1858 | { | |
1859 | _M_saved_available = false; | |
1860 | *__f++ = _M_saved * __param.stddev() + __param.mean(); | |
1861 | ||
1862 | if (__f == __t) | |
1863 | return; | |
1864 | } | |
1865 | ||
1866 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
1867 | __aurng(__urng); | |
1868 | ||
1869 | while (__f + 1 < __t) | |
1870 | { | |
1871 | result_type __x, __y, __r2; | |
1872 | do | |
1873 | { | |
1874 | __x = result_type(2.0) * __aurng() - 1.0; | |
1875 | __y = result_type(2.0) * __aurng() - 1.0; | |
1876 | __r2 = __x * __x + __y * __y; | |
1877 | } | |
1878 | while (__r2 > 1.0 || __r2 == 0.0); | |
1879 | ||
1880 | const result_type __mult = std::sqrt(-2 * std::log(__r2) / __r2); | |
1881 | *__f++ = __y * __mult * __param.stddev() + __param.mean(); | |
1882 | *__f++ = __x * __mult * __param.stddev() + __param.mean(); | |
1883 | } | |
1884 | ||
1885 | if (__f != __t) | |
1886 | { | |
1887 | result_type __x, __y, __r2; | |
1888 | do | |
1889 | { | |
1890 | __x = result_type(2.0) * __aurng() - 1.0; | |
1891 | __y = result_type(2.0) * __aurng() - 1.0; | |
1892 | __r2 = __x * __x + __y * __y; | |
1893 | } | |
1894 | while (__r2 > 1.0 || __r2 == 0.0); | |
1895 | ||
1896 | const result_type __mult = std::sqrt(-2 * std::log(__r2) / __r2); | |
1897 | _M_saved = __x * __mult; | |
1898 | _M_saved_available = true; | |
1899 | *__f = __y * __mult * __param.stddev() + __param.mean(); | |
1900 | } | |
1901 | } | |
1902 | ||
fc05e1ba PC |
1903 | template<typename _RealType> |
1904 | bool | |
1905 | operator==(const std::normal_distribution<_RealType>& __d1, | |
1906 | const std::normal_distribution<_RealType>& __d2) | |
1907 | { | |
1908 | if (__d1._M_param == __d2._M_param | |
1909 | && __d1._M_saved_available == __d2._M_saved_available) | |
1910 | { | |
1911 | if (__d1._M_saved_available | |
1912 | && __d1._M_saved == __d2._M_saved) | |
1913 | return true; | |
1914 | else if(!__d1._M_saved_available) | |
1915 | return true; | |
1916 | else | |
1917 | return false; | |
1918 | } | |
1919 | else | |
1920 | return false; | |
1921 | } | |
1922 | ||
8e79468d BK |
1923 | template<typename _RealType, typename _CharT, typename _Traits> |
1924 | std::basic_ostream<_CharT, _Traits>& | |
1925 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1926 | const normal_distribution<_RealType>& __x) | |
1927 | { | |
160e95dc | 1928 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
1929 | |
1930 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1931 | const _CharT __fill = __os.fill(); | |
1932 | const std::streamsize __precision = __os.precision(); | |
1933 | const _CharT __space = __os.widen(' '); | |
1934 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1935 | __os.fill(__space); | |
7703dc47 | 1936 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d BK |
1937 | |
1938 | __os << __x.mean() << __space << __x.stddev() | |
1939 | << __space << __x._M_saved_available; | |
1940 | if (__x._M_saved_available) | |
1941 | __os << __space << __x._M_saved; | |
1942 | ||
1943 | __os.flags(__flags); | |
1944 | __os.fill(__fill); | |
1945 | __os.precision(__precision); | |
1946 | return __os; | |
1947 | } | |
1948 | ||
1949 | template<typename _RealType, typename _CharT, typename _Traits> | |
1950 | std::basic_istream<_CharT, _Traits>& | |
1951 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
1952 | normal_distribution<_RealType>& __x) | |
1953 | { | |
160e95dc JW |
1954 | using param_type = typename normal_distribution<_RealType>::param_type; |
1955 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
1956 | |
1957 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
1958 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
1959 | ||
1960 | double __mean, __stddev; | |
160e95dc JW |
1961 | bool __saved_avail; |
1962 | if (__is >> __mean >> __stddev >> __saved_avail) | |
1963 | { | |
909ef4e2 | 1964 | if (!__saved_avail || (__is >> __x._M_saved)) |
160e95dc JW |
1965 | { |
1966 | __x._M_saved_available = __saved_avail; | |
1967 | __x.param(param_type(__mean, __stddev)); | |
1968 | } | |
1969 | } | |
8e79468d BK |
1970 | |
1971 | __is.flags(__flags); | |
1972 | return __is; | |
1973 | } | |
1974 | ||
1975 | ||
7b93bdde UD |
1976 | template<typename _RealType> |
1977 | template<typename _ForwardIterator, | |
1978 | typename _UniformRandomNumberGenerator> | |
1979 | void | |
1980 | lognormal_distribution<_RealType>:: | |
1981 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1982 | _UniformRandomNumberGenerator& __urng, | |
1983 | const param_type& __p) | |
1984 | { | |
1985 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1986 | while (__f != __t) | |
1987 | *__f++ = std::exp(__p.s() * _M_nd(__urng) + __p.m()); | |
1988 | } | |
1989 | ||
8e79468d BK |
1990 | template<typename _RealType, typename _CharT, typename _Traits> |
1991 | std::basic_ostream<_CharT, _Traits>& | |
1992 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1993 | const lognormal_distribution<_RealType>& __x) | |
1994 | { | |
160e95dc | 1995 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
1996 | |
1997 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1998 | const _CharT __fill = __os.fill(); | |
1999 | const std::streamsize __precision = __os.precision(); | |
2000 | const _CharT __space = __os.widen(' '); | |
2001 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2002 | __os.fill(__space); | |
7703dc47 | 2003 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d | 2004 | |
b01630bb PC |
2005 | __os << __x.m() << __space << __x.s() |
2006 | << __space << __x._M_nd; | |
8e79468d BK |
2007 | |
2008 | __os.flags(__flags); | |
2009 | __os.fill(__fill); | |
2010 | __os.precision(__precision); | |
2011 | return __os; | |
2012 | } | |
2013 | ||
2014 | template<typename _RealType, typename _CharT, typename _Traits> | |
2015 | std::basic_istream<_CharT, _Traits>& | |
2016 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2017 | lognormal_distribution<_RealType>& __x) | |
2018 | { | |
160e95dc JW |
2019 | using param_type |
2020 | = typename lognormal_distribution<_RealType>::param_type; | |
2021 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
2022 | |
2023 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2024 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2025 | ||
2026 | _RealType __m, __s; | |
160e95dc JW |
2027 | if (__is >> __m >> __s >> __x._M_nd) |
2028 | __x.param(param_type(__m, __s)); | |
8e79468d BK |
2029 | |
2030 | __is.flags(__flags); | |
2031 | return __is; | |
2032 | } | |
2033 | ||
5bcb3b4d PC |
2034 | template<typename _RealType> |
2035 | template<typename _ForwardIterator, | |
2036 | typename _UniformRandomNumberGenerator> | |
2037 | void | |
2038 | std::chi_squared_distribution<_RealType>:: | |
2039 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2040 | _UniformRandomNumberGenerator& __urng) | |
2041 | { | |
2042 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2043 | while (__f != __t) | |
2044 | *__f++ = 2 * _M_gd(__urng); | |
2045 | } | |
8e79468d | 2046 | |
7b93bdde UD |
2047 | template<typename _RealType> |
2048 | template<typename _ForwardIterator, | |
2049 | typename _UniformRandomNumberGenerator> | |
2050 | void | |
2051 | std::chi_squared_distribution<_RealType>:: | |
2052 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2053 | _UniformRandomNumberGenerator& __urng, | |
5bcb3b4d PC |
2054 | const typename |
2055 | std::gamma_distribution<result_type>::param_type& __p) | |
7b93bdde UD |
2056 | { |
2057 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2058 | while (__f != __t) | |
2059 | *__f++ = 2 * _M_gd(__urng, __p); | |
2060 | } | |
2061 | ||
8e79468d BK |
2062 | template<typename _RealType, typename _CharT, typename _Traits> |
2063 | std::basic_ostream<_CharT, _Traits>& | |
2064 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2065 | const chi_squared_distribution<_RealType>& __x) | |
2066 | { | |
160e95dc | 2067 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
2068 | |
2069 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2070 | const _CharT __fill = __os.fill(); | |
2071 | const std::streamsize __precision = __os.precision(); | |
2072 | const _CharT __space = __os.widen(' '); | |
2073 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2074 | __os.fill(__space); | |
7703dc47 | 2075 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d | 2076 | |
f9b09dec | 2077 | __os << __x.n() << __space << __x._M_gd; |
8e79468d BK |
2078 | |
2079 | __os.flags(__flags); | |
2080 | __os.fill(__fill); | |
2081 | __os.precision(__precision); | |
2082 | return __os; | |
2083 | } | |
2084 | ||
2085 | template<typename _RealType, typename _CharT, typename _Traits> | |
2086 | std::basic_istream<_CharT, _Traits>& | |
2087 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2088 | chi_squared_distribution<_RealType>& __x) | |
2089 | { | |
160e95dc JW |
2090 | using param_type |
2091 | = typename chi_squared_distribution<_RealType>::param_type; | |
2092 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
2093 | |
2094 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2095 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2096 | ||
2097 | _RealType __n; | |
160e95dc JW |
2098 | if (__is >> __n >> __x._M_gd) |
2099 | __x.param(param_type(__n)); | |
8e79468d BK |
2100 | |
2101 | __is.flags(__flags); | |
2102 | return __is; | |
2103 | } | |
2104 | ||
2105 | ||
2106 | template<typename _RealType> | |
2107 | template<typename _UniformRandomNumberGenerator> | |
2108 | typename cauchy_distribution<_RealType>::result_type | |
2109 | cauchy_distribution<_RealType>:: | |
2110 | operator()(_UniformRandomNumberGenerator& __urng, | |
2111 | const param_type& __p) | |
2112 | { | |
2113 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
2114 | __aurng(__urng); | |
2115 | _RealType __u; | |
2116 | do | |
e1a02963 | 2117 | __u = __aurng(); |
8e79468d BK |
2118 | while (__u == 0.5); |
2119 | ||
e1a02963 PC |
2120 | const _RealType __pi = 3.1415926535897932384626433832795029L; |
2121 | return __p.a() + __p.b() * std::tan(__pi * __u); | |
8e79468d BK |
2122 | } |
2123 | ||
7b93bdde UD |
2124 | template<typename _RealType> |
2125 | template<typename _ForwardIterator, | |
2126 | typename _UniformRandomNumberGenerator> | |
2127 | void | |
2128 | cauchy_distribution<_RealType>:: | |
2129 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2130 | _UniformRandomNumberGenerator& __urng, | |
2131 | const param_type& __p) | |
2132 | { | |
2133 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2134 | const _RealType __pi = 3.1415926535897932384626433832795029L; | |
2135 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
2136 | __aurng(__urng); | |
2137 | while (__f != __t) | |
2138 | { | |
2139 | _RealType __u; | |
2140 | do | |
2141 | __u = __aurng(); | |
2142 | while (__u == 0.5); | |
2143 | ||
2144 | *__f++ = __p.a() + __p.b() * std::tan(__pi * __u); | |
2145 | } | |
2146 | } | |
2147 | ||
8e79468d BK |
2148 | template<typename _RealType, typename _CharT, typename _Traits> |
2149 | std::basic_ostream<_CharT, _Traits>& | |
2150 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2151 | const cauchy_distribution<_RealType>& __x) | |
2152 | { | |
160e95dc | 2153 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
2154 | |
2155 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2156 | const _CharT __fill = __os.fill(); | |
2157 | const std::streamsize __precision = __os.precision(); | |
2158 | const _CharT __space = __os.widen(' '); | |
2159 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2160 | __os.fill(__space); | |
7703dc47 | 2161 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d BK |
2162 | |
2163 | __os << __x.a() << __space << __x.b(); | |
2164 | ||
2165 | __os.flags(__flags); | |
2166 | __os.fill(__fill); | |
2167 | __os.precision(__precision); | |
2168 | return __os; | |
2169 | } | |
2170 | ||
2171 | template<typename _RealType, typename _CharT, typename _Traits> | |
2172 | std::basic_istream<_CharT, _Traits>& | |
2173 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2174 | cauchy_distribution<_RealType>& __x) | |
2175 | { | |
160e95dc JW |
2176 | using param_type = typename cauchy_distribution<_RealType>::param_type; |
2177 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
2178 | |
2179 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2180 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2181 | ||
2182 | _RealType __a, __b; | |
160e95dc JW |
2183 | if (__is >> __a >> __b) |
2184 | __x.param(param_type(__a, __b)); | |
8e79468d BK |
2185 | |
2186 | __is.flags(__flags); | |
2187 | return __is; | |
2188 | } | |
2189 | ||
2190 | ||
7b93bdde UD |
2191 | template<typename _RealType> |
2192 | template<typename _ForwardIterator, | |
2193 | typename _UniformRandomNumberGenerator> | |
2194 | void | |
2195 | std::fisher_f_distribution<_RealType>:: | |
2196 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2197 | _UniformRandomNumberGenerator& __urng) | |
2198 | { | |
2199 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2200 | while (__f != __t) | |
2201 | *__f++ = ((_M_gd_x(__urng) * n()) / (_M_gd_y(__urng) * m())); | |
2202 | } | |
2203 | ||
2204 | template<typename _RealType> | |
2205 | template<typename _ForwardIterator, | |
2206 | typename _UniformRandomNumberGenerator> | |
2207 | void | |
2208 | std::fisher_f_distribution<_RealType>:: | |
2209 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2210 | _UniformRandomNumberGenerator& __urng, | |
2211 | const param_type& __p) | |
2212 | { | |
2213 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2214 | typedef typename std::gamma_distribution<result_type>::param_type | |
2215 | param_type; | |
2216 | param_type __p1(__p.m() / 2); | |
2217 | param_type __p2(__p.n() / 2); | |
2218 | while (__f != __t) | |
2219 | *__f++ = ((_M_gd_x(__urng, __p1) * n()) | |
2220 | / (_M_gd_y(__urng, __p2) * m())); | |
2221 | } | |
2222 | ||
8e79468d BK |
2223 | template<typename _RealType, typename _CharT, typename _Traits> |
2224 | std::basic_ostream<_CharT, _Traits>& | |
2225 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2226 | const fisher_f_distribution<_RealType>& __x) | |
2227 | { | |
160e95dc | 2228 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
2229 | |
2230 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2231 | const _CharT __fill = __os.fill(); | |
2232 | const std::streamsize __precision = __os.precision(); | |
2233 | const _CharT __space = __os.widen(' '); | |
2234 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2235 | __os.fill(__space); | |
7703dc47 | 2236 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d | 2237 | |
f9b09dec PC |
2238 | __os << __x.m() << __space << __x.n() |
2239 | << __space << __x._M_gd_x << __space << __x._M_gd_y; | |
8e79468d BK |
2240 | |
2241 | __os.flags(__flags); | |
2242 | __os.fill(__fill); | |
2243 | __os.precision(__precision); | |
2244 | return __os; | |
2245 | } | |
2246 | ||
2247 | template<typename _RealType, typename _CharT, typename _Traits> | |
2248 | std::basic_istream<_CharT, _Traits>& | |
2249 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2250 | fisher_f_distribution<_RealType>& __x) | |
2251 | { | |
160e95dc JW |
2252 | using param_type |
2253 | = typename fisher_f_distribution<_RealType>::param_type; | |
2254 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
2255 | |
2256 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2257 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2258 | ||
2259 | _RealType __m, __n; | |
160e95dc JW |
2260 | if (__is >> __m >> __n >> __x._M_gd_x >> __x._M_gd_y) |
2261 | __x.param(param_type(__m, __n)); | |
8e79468d BK |
2262 | |
2263 | __is.flags(__flags); | |
2264 | return __is; | |
2265 | } | |
2266 | ||
2267 | ||
7b93bdde UD |
2268 | template<typename _RealType> |
2269 | template<typename _ForwardIterator, | |
2270 | typename _UniformRandomNumberGenerator> | |
2271 | void | |
2272 | std::student_t_distribution<_RealType>:: | |
2273 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2274 | _UniformRandomNumberGenerator& __urng) | |
2275 | { | |
2276 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2277 | while (__f != __t) | |
2278 | *__f++ = _M_nd(__urng) * std::sqrt(n() / _M_gd(__urng)); | |
2279 | } | |
2280 | ||
2281 | template<typename _RealType> | |
2282 | template<typename _ForwardIterator, | |
2283 | typename _UniformRandomNumberGenerator> | |
2284 | void | |
2285 | std::student_t_distribution<_RealType>:: | |
2286 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2287 | _UniformRandomNumberGenerator& __urng, | |
2288 | const param_type& __p) | |
2289 | { | |
2290 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2291 | typename std::gamma_distribution<result_type>::param_type | |
2292 | __p2(__p.n() / 2, 2); | |
2293 | while (__f != __t) | |
2294 | *__f++ = _M_nd(__urng) * std::sqrt(__p.n() / _M_gd(__urng, __p2)); | |
2295 | } | |
2296 | ||
8e79468d BK |
2297 | template<typename _RealType, typename _CharT, typename _Traits> |
2298 | std::basic_ostream<_CharT, _Traits>& | |
2299 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2300 | const student_t_distribution<_RealType>& __x) | |
2301 | { | |
160e95dc | 2302 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
2303 | |
2304 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2305 | const _CharT __fill = __os.fill(); | |
2306 | const std::streamsize __precision = __os.precision(); | |
2307 | const _CharT __space = __os.widen(' '); | |
2308 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2309 | __os.fill(__space); | |
7703dc47 | 2310 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d | 2311 | |
f9b09dec | 2312 | __os << __x.n() << __space << __x._M_nd << __space << __x._M_gd; |
8e79468d BK |
2313 | |
2314 | __os.flags(__flags); | |
2315 | __os.fill(__fill); | |
2316 | __os.precision(__precision); | |
2317 | return __os; | |
2318 | } | |
2319 | ||
2320 | template<typename _RealType, typename _CharT, typename _Traits> | |
2321 | std::basic_istream<_CharT, _Traits>& | |
2322 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2323 | student_t_distribution<_RealType>& __x) | |
2324 | { | |
160e95dc JW |
2325 | using param_type |
2326 | = typename student_t_distribution<_RealType>::param_type; | |
2327 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
2328 | |
2329 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2330 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2331 | ||
2332 | _RealType __n; | |
160e95dc JW |
2333 | if (__is >> __n >> __x._M_nd >> __x._M_gd) |
2334 | __x.param(param_type(__n)); | |
8e79468d BK |
2335 | |
2336 | __is.flags(__flags); | |
2337 | return __is; | |
2338 | } | |
2339 | ||
2340 | ||
2341 | template<typename _RealType> | |
2342 | void | |
2343 | gamma_distribution<_RealType>::param_type:: | |
2344 | _M_initialize() | |
2345 | { | |
b01630bb PC |
2346 | _M_malpha = _M_alpha < 1.0 ? _M_alpha + _RealType(1.0) : _M_alpha; |
2347 | ||
2348 | const _RealType __a1 = _M_malpha - _RealType(1.0) / _RealType(3.0); | |
2349 | _M_a2 = _RealType(1.0) / std::sqrt(_RealType(9.0) * __a1); | |
8e79468d BK |
2350 | } |
2351 | ||
2352 | /** | |
b01630bb PC |
2353 | * Marsaglia, G. and Tsang, W. W. |
2354 | * "A Simple Method for Generating Gamma Variables" | |
2355 | * ACM Transactions on Mathematical Software, 26, 3, 363-372, 2000. | |
8e79468d BK |
2356 | */ |
2357 | template<typename _RealType> | |
2358 | template<typename _UniformRandomNumberGenerator> | |
2359 | typename gamma_distribution<_RealType>::result_type | |
2360 | gamma_distribution<_RealType>:: | |
2361 | operator()(_UniformRandomNumberGenerator& __urng, | |
2362 | const param_type& __param) | |
2363 | { | |
8e79468d BK |
2364 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> |
2365 | __aurng(__urng); | |
2366 | ||
b01630bb PC |
2367 | result_type __u, __v, __n; |
2368 | const result_type __a1 = (__param._M_malpha | |
2369 | - _RealType(1.0) / _RealType(3.0)); | |
8e79468d | 2370 | |
b01630bb PC |
2371 | do |
2372 | { | |
8e79468d BK |
2373 | do |
2374 | { | |
b01630bb PC |
2375 | __n = _M_nd(__urng); |
2376 | __v = result_type(1.0) + __param._M_a2 * __n; | |
8e79468d | 2377 | } |
b01630bb PC |
2378 | while (__v <= 0.0); |
2379 | ||
2380 | __v = __v * __v * __v; | |
2381 | __u = __aurng(); | |
8e79468d | 2382 | } |
957221f5 | 2383 | while (__u > result_type(1.0) - 0.0331 * __n * __n * __n * __n |
b01630bb PC |
2384 | && (std::log(__u) > (0.5 * __n * __n + __a1 |
2385 | * (1.0 - __v + std::log(__v))))); | |
2386 | ||
2387 | if (__param.alpha() == __param._M_malpha) | |
2388 | return __a1 * __v * __param.beta(); | |
8e79468d BK |
2389 | else |
2390 | { | |
8e79468d | 2391 | do |
b01630bb PC |
2392 | __u = __aurng(); |
2393 | while (__u == 0.0); | |
2394 | ||
2395 | return (std::pow(__u, result_type(1.0) / __param.alpha()) | |
2396 | * __a1 * __v * __param.beta()); | |
8e79468d | 2397 | } |
8e79468d BK |
2398 | } |
2399 | ||
7b93bdde UD |
2400 | template<typename _RealType> |
2401 | template<typename _ForwardIterator, | |
2402 | typename _UniformRandomNumberGenerator> | |
2403 | void | |
2404 | gamma_distribution<_RealType>:: | |
2405 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2406 | _UniformRandomNumberGenerator& __urng, | |
2407 | const param_type& __param) | |
2408 | { | |
2409 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2410 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
2411 | __aurng(__urng); | |
2412 | ||
2413 | result_type __u, __v, __n; | |
2414 | const result_type __a1 = (__param._M_malpha | |
2415 | - _RealType(1.0) / _RealType(3.0)); | |
2416 | ||
2417 | if (__param.alpha() == __param._M_malpha) | |
2418 | while (__f != __t) | |
2419 | { | |
2420 | do | |
2421 | { | |
2422 | do | |
2423 | { | |
2424 | __n = _M_nd(__urng); | |
2425 | __v = result_type(1.0) + __param._M_a2 * __n; | |
2426 | } | |
2427 | while (__v <= 0.0); | |
2428 | ||
2429 | __v = __v * __v * __v; | |
2430 | __u = __aurng(); | |
2431 | } | |
6fa8c51f | 2432 | while (__u > result_type(1.0) - 0.0331 * __n * __n * __n * __n |
7b93bdde UD |
2433 | && (std::log(__u) > (0.5 * __n * __n + __a1 |
2434 | * (1.0 - __v + std::log(__v))))); | |
2435 | ||
2436 | *__f++ = __a1 * __v * __param.beta(); | |
2437 | } | |
2438 | else | |
2439 | while (__f != __t) | |
2440 | { | |
2441 | do | |
2442 | { | |
2443 | do | |
2444 | { | |
2445 | __n = _M_nd(__urng); | |
2446 | __v = result_type(1.0) + __param._M_a2 * __n; | |
2447 | } | |
2448 | while (__v <= 0.0); | |
2449 | ||
2450 | __v = __v * __v * __v; | |
2451 | __u = __aurng(); | |
2452 | } | |
6fa8c51f | 2453 | while (__u > result_type(1.0) - 0.0331 * __n * __n * __n * __n |
7b93bdde UD |
2454 | && (std::log(__u) > (0.5 * __n * __n + __a1 |
2455 | * (1.0 - __v + std::log(__v))))); | |
2456 | ||
2457 | do | |
2458 | __u = __aurng(); | |
2459 | while (__u == 0.0); | |
2460 | ||
2461 | *__f++ = (std::pow(__u, result_type(1.0) / __param.alpha()) | |
2462 | * __a1 * __v * __param.beta()); | |
2463 | } | |
2464 | } | |
2465 | ||
8e79468d BK |
2466 | template<typename _RealType, typename _CharT, typename _Traits> |
2467 | std::basic_ostream<_CharT, _Traits>& | |
2468 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2469 | const gamma_distribution<_RealType>& __x) | |
2470 | { | |
160e95dc | 2471 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
2472 | |
2473 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2474 | const _CharT __fill = __os.fill(); | |
2475 | const std::streamsize __precision = __os.precision(); | |
2476 | const _CharT __space = __os.widen(' '); | |
2477 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2478 | __os.fill(__space); | |
7703dc47 | 2479 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d | 2480 | |
b01630bb PC |
2481 | __os << __x.alpha() << __space << __x.beta() |
2482 | << __space << __x._M_nd; | |
8e79468d BK |
2483 | |
2484 | __os.flags(__flags); | |
2485 | __os.fill(__fill); | |
2486 | __os.precision(__precision); | |
2487 | return __os; | |
2488 | } | |
2489 | ||
2490 | template<typename _RealType, typename _CharT, typename _Traits> | |
2491 | std::basic_istream<_CharT, _Traits>& | |
2492 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2493 | gamma_distribution<_RealType>& __x) | |
2494 | { | |
160e95dc JW |
2495 | using param_type = typename gamma_distribution<_RealType>::param_type; |
2496 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
2497 | |
2498 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2499 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2500 | ||
ed2807f4 | 2501 | _RealType __alpha_val, __beta_val; |
160e95dc JW |
2502 | if (__is >> __alpha_val >> __beta_val >> __x._M_nd) |
2503 | __x.param(param_type(__alpha_val, __beta_val)); | |
8e79468d BK |
2504 | |
2505 | __is.flags(__flags); | |
2506 | return __is; | |
2507 | } | |
2508 | ||
2509 | ||
b01630bb PC |
2510 | template<typename _RealType> |
2511 | template<typename _UniformRandomNumberGenerator> | |
2512 | typename weibull_distribution<_RealType>::result_type | |
2513 | weibull_distribution<_RealType>:: | |
2514 | operator()(_UniformRandomNumberGenerator& __urng, | |
2515 | const param_type& __p) | |
2516 | { | |
2517 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
2518 | __aurng(__urng); | |
c2d9083d | 2519 | return __p.b() * std::pow(-std::log(result_type(1) - __aurng()), |
b01630bb PC |
2520 | result_type(1) / __p.a()); |
2521 | } | |
2522 | ||
7b93bdde UD |
2523 | template<typename _RealType> |
2524 | template<typename _ForwardIterator, | |
2525 | typename _UniformRandomNumberGenerator> | |
2526 | void | |
2527 | weibull_distribution<_RealType>:: | |
2528 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2529 | _UniformRandomNumberGenerator& __urng, | |
2530 | const param_type& __p) | |
2531 | { | |
2532 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2533 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
2534 | __aurng(__urng); | |
c2d9083d | 2535 | auto __inv_a = result_type(1) / __p.a(); |
7b93bdde UD |
2536 | |
2537 | while (__f != __t) | |
c2d9083d HY |
2538 | *__f++ = __p.b() * std::pow(-std::log(result_type(1) - __aurng()), |
2539 | __inv_a); | |
7b93bdde UD |
2540 | } |
2541 | ||
8e79468d BK |
2542 | template<typename _RealType, typename _CharT, typename _Traits> |
2543 | std::basic_ostream<_CharT, _Traits>& | |
2544 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2545 | const weibull_distribution<_RealType>& __x) | |
2546 | { | |
160e95dc | 2547 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
2548 | |
2549 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2550 | const _CharT __fill = __os.fill(); | |
2551 | const std::streamsize __precision = __os.precision(); | |
2552 | const _CharT __space = __os.widen(' '); | |
2553 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2554 | __os.fill(__space); | |
7703dc47 | 2555 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d BK |
2556 | |
2557 | __os << __x.a() << __space << __x.b(); | |
2558 | ||
2559 | __os.flags(__flags); | |
2560 | __os.fill(__fill); | |
2561 | __os.precision(__precision); | |
2562 | return __os; | |
2563 | } | |
2564 | ||
2565 | template<typename _RealType, typename _CharT, typename _Traits> | |
2566 | std::basic_istream<_CharT, _Traits>& | |
2567 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2568 | weibull_distribution<_RealType>& __x) | |
2569 | { | |
160e95dc JW |
2570 | using param_type = typename weibull_distribution<_RealType>::param_type; |
2571 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
2572 | |
2573 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2574 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2575 | ||
2576 | _RealType __a, __b; | |
160e95dc JW |
2577 | if (__is >> __a >> __b) |
2578 | __x.param(param_type(__a, __b)); | |
8e79468d BK |
2579 | |
2580 | __is.flags(__flags); | |
2581 | return __is; | |
2582 | } | |
2583 | ||
2584 | ||
2585 | template<typename _RealType> | |
2586 | template<typename _UniformRandomNumberGenerator> | |
2587 | typename extreme_value_distribution<_RealType>::result_type | |
2588 | extreme_value_distribution<_RealType>:: | |
2589 | operator()(_UniformRandomNumberGenerator& __urng, | |
2590 | const param_type& __p) | |
2591 | { | |
2592 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
2593 | __aurng(__urng); | |
c2d9083d HY |
2594 | return __p.a() - __p.b() * std::log(-std::log(result_type(1) |
2595 | - __aurng())); | |
8e79468d BK |
2596 | } |
2597 | ||
7b93bdde UD |
2598 | template<typename _RealType> |
2599 | template<typename _ForwardIterator, | |
2600 | typename _UniformRandomNumberGenerator> | |
2601 | void | |
2602 | extreme_value_distribution<_RealType>:: | |
2603 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2604 | _UniformRandomNumberGenerator& __urng, | |
2605 | const param_type& __p) | |
2606 | { | |
2607 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2608 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
2609 | __aurng(__urng); | |
2610 | ||
2611 | while (__f != __t) | |
c2d9083d HY |
2612 | *__f++ = __p.a() - __p.b() * std::log(-std::log(result_type(1) |
2613 | - __aurng())); | |
7b93bdde UD |
2614 | } |
2615 | ||
8e79468d BK |
2616 | template<typename _RealType, typename _CharT, typename _Traits> |
2617 | std::basic_ostream<_CharT, _Traits>& | |
2618 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2619 | const extreme_value_distribution<_RealType>& __x) | |
2620 | { | |
160e95dc | 2621 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
2622 | |
2623 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2624 | const _CharT __fill = __os.fill(); | |
2625 | const std::streamsize __precision = __os.precision(); | |
2626 | const _CharT __space = __os.widen(' '); | |
2627 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2628 | __os.fill(__space); | |
7703dc47 | 2629 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d BK |
2630 | |
2631 | __os << __x.a() << __space << __x.b(); | |
2632 | ||
2633 | __os.flags(__flags); | |
2634 | __os.fill(__fill); | |
2635 | __os.precision(__precision); | |
2636 | return __os; | |
2637 | } | |
2638 | ||
2639 | template<typename _RealType, typename _CharT, typename _Traits> | |
2640 | std::basic_istream<_CharT, _Traits>& | |
2641 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2642 | extreme_value_distribution<_RealType>& __x) | |
2643 | { | |
160e95dc JW |
2644 | using param_type |
2645 | = typename extreme_value_distribution<_RealType>::param_type; | |
2646 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
2647 | |
2648 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2649 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2650 | ||
2651 | _RealType __a, __b; | |
160e95dc JW |
2652 | if (__is >> __a >> __b) |
2653 | __x.param(param_type(__a, __b)); | |
8e79468d BK |
2654 | |
2655 | __is.flags(__flags); | |
2656 | return __is; | |
2657 | } | |
2658 | ||
2659 | ||
2660 | template<typename _IntType> | |
2661 | void | |
2662 | discrete_distribution<_IntType>::param_type:: | |
2663 | _M_initialize() | |
2664 | { | |
2665 | if (_M_prob.size() < 2) | |
2666 | { | |
2667 | _M_prob.clear(); | |
8e79468d BK |
2668 | return; |
2669 | } | |
2670 | ||
f8dd9e0d PC |
2671 | const double __sum = std::accumulate(_M_prob.begin(), |
2672 | _M_prob.end(), 0.0); | |
b2a96bf9 | 2673 | __glibcxx_assert(__sum > 0); |
f8dd9e0d | 2674 | // Now normalize the probabilites. |
60f3a59f PC |
2675 | __detail::__normalize(_M_prob.begin(), _M_prob.end(), _M_prob.begin(), |
2676 | __sum); | |
f8dd9e0d PC |
2677 | // Accumulate partial sums. |
2678 | _M_cp.reserve(_M_prob.size()); | |
8e79468d BK |
2679 | std::partial_sum(_M_prob.begin(), _M_prob.end(), |
2680 | std::back_inserter(_M_cp)); | |
f8dd9e0d | 2681 | // Make sure the last cumulative probability is one. |
8e79468d BK |
2682 | _M_cp[_M_cp.size() - 1] = 1.0; |
2683 | } | |
2684 | ||
2685 | template<typename _IntType> | |
2686 | template<typename _Func> | |
2687 | discrete_distribution<_IntType>::param_type:: | |
f8dd9e0d | 2688 | param_type(size_t __nw, double __xmin, double __xmax, _Func __fw) |
8e79468d BK |
2689 | : _M_prob(), _M_cp() |
2690 | { | |
f8dd9e0d PC |
2691 | const size_t __n = __nw == 0 ? 1 : __nw; |
2692 | const double __delta = (__xmax - __xmin) / __n; | |
2693 | ||
2694 | _M_prob.reserve(__n); | |
2695 | for (size_t __k = 0; __k < __nw; ++__k) | |
2696 | _M_prob.push_back(__fw(__xmin + __k * __delta + 0.5 * __delta)); | |
8e79468d BK |
2697 | |
2698 | _M_initialize(); | |
2699 | } | |
2700 | ||
2701 | template<typename _IntType> | |
2702 | template<typename _UniformRandomNumberGenerator> | |
2703 | typename discrete_distribution<_IntType>::result_type | |
2704 | discrete_distribution<_IntType>:: | |
2705 | operator()(_UniformRandomNumberGenerator& __urng, | |
2706 | const param_type& __param) | |
2707 | { | |
879b9073 PC |
2708 | if (__param._M_cp.empty()) |
2709 | return result_type(0); | |
2710 | ||
9b88236b | 2711 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> |
8e79468d BK |
2712 | __aurng(__urng); |
2713 | ||
2714 | const double __p = __aurng(); | |
2715 | auto __pos = std::lower_bound(__param._M_cp.begin(), | |
2716 | __param._M_cp.end(), __p); | |
8e79468d | 2717 | |
f8dd9e0d | 2718 | return __pos - __param._M_cp.begin(); |
8e79468d BK |
2719 | } |
2720 | ||
7b93bdde UD |
2721 | template<typename _IntType> |
2722 | template<typename _ForwardIterator, | |
2723 | typename _UniformRandomNumberGenerator> | |
2724 | void | |
2725 | discrete_distribution<_IntType>:: | |
2726 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2727 | _UniformRandomNumberGenerator& __urng, | |
2728 | const param_type& __param) | |
2729 | { | |
2730 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2731 | ||
2732 | if (__param._M_cp.empty()) | |
2733 | { | |
2734 | while (__f != __t) | |
2735 | *__f++ = result_type(0); | |
2736 | return; | |
2737 | } | |
2738 | ||
2739 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
2740 | __aurng(__urng); | |
2741 | ||
2742 | while (__f != __t) | |
2743 | { | |
2744 | const double __p = __aurng(); | |
2745 | auto __pos = std::lower_bound(__param._M_cp.begin(), | |
2746 | __param._M_cp.end(), __p); | |
2747 | ||
2748 | *__f++ = __pos - __param._M_cp.begin(); | |
2749 | } | |
2750 | } | |
2751 | ||
8e79468d BK |
2752 | template<typename _IntType, typename _CharT, typename _Traits> |
2753 | std::basic_ostream<_CharT, _Traits>& | |
2754 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2755 | const discrete_distribution<_IntType>& __x) | |
2756 | { | |
160e95dc | 2757 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
2758 | |
2759 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2760 | const _CharT __fill = __os.fill(); | |
2761 | const std::streamsize __precision = __os.precision(); | |
2762 | const _CharT __space = __os.widen(' '); | |
2763 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2764 | __os.fill(__space); | |
7703dc47 | 2765 | __os.precision(std::numeric_limits<double>::max_digits10); |
8e79468d BK |
2766 | |
2767 | std::vector<double> __prob = __x.probabilities(); | |
2768 | __os << __prob.size(); | |
2769 | for (auto __dit = __prob.begin(); __dit != __prob.end(); ++__dit) | |
2770 | __os << __space << *__dit; | |
2771 | ||
2772 | __os.flags(__flags); | |
2773 | __os.fill(__fill); | |
2774 | __os.precision(__precision); | |
2775 | return __os; | |
2776 | } | |
2777 | ||
160e95dc JW |
2778 | namespace __detail |
2779 | { | |
2780 | template<typename _ValT, typename _CharT, typename _Traits> | |
2781 | basic_istream<_CharT, _Traits>& | |
2782 | __extract_params(basic_istream<_CharT, _Traits>& __is, | |
2783 | vector<_ValT>& __vals, size_t __n) | |
2784 | { | |
2785 | __vals.reserve(__n); | |
2786 | while (__n--) | |
2787 | { | |
2788 | _ValT __val; | |
2789 | if (__is >> __val) | |
2790 | __vals.push_back(__val); | |
2791 | else | |
2792 | break; | |
2793 | } | |
2794 | return __is; | |
2795 | } | |
2796 | } // namespace __detail | |
2797 | ||
8e79468d BK |
2798 | template<typename _IntType, typename _CharT, typename _Traits> |
2799 | std::basic_istream<_CharT, _Traits>& | |
2800 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2801 | discrete_distribution<_IntType>& __x) | |
2802 | { | |
160e95dc | 2803 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; |
8e79468d BK |
2804 | |
2805 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2806 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2807 | ||
2808 | size_t __n; | |
160e95dc | 2809 | if (__is >> __n) |
8e79468d | 2810 | { |
160e95dc JW |
2811 | std::vector<double> __prob_vec; |
2812 | if (__detail::__extract_params(__is, __prob_vec, __n)) | |
2813 | __x.param({__prob_vec.begin(), __prob_vec.end()}); | |
8e79468d BK |
2814 | } |
2815 | ||
8e79468d BK |
2816 | __is.flags(__flags); |
2817 | return __is; | |
2818 | } | |
2819 | ||
2820 | ||
2821 | template<typename _RealType> | |
2822 | void | |
2823 | piecewise_constant_distribution<_RealType>::param_type:: | |
2824 | _M_initialize() | |
2825 | { | |
879b9073 PC |
2826 | if (_M_int.size() < 2 |
2827 | || (_M_int.size() == 2 | |
2828 | && _M_int[0] == _RealType(0) | |
2829 | && _M_int[1] == _RealType(1))) | |
8e79468d BK |
2830 | { |
2831 | _M_int.clear(); | |
8e79468d | 2832 | _M_den.clear(); |
8e79468d BK |
2833 | return; |
2834 | } | |
2835 | ||
f8dd9e0d PC |
2836 | const double __sum = std::accumulate(_M_den.begin(), |
2837 | _M_den.end(), 0.0); | |
b2a96bf9 | 2838 | __glibcxx_assert(__sum > 0); |
8e79468d | 2839 | |
60f3a59f PC |
2840 | __detail::__normalize(_M_den.begin(), _M_den.end(), _M_den.begin(), |
2841 | __sum); | |
f8dd9e0d PC |
2842 | |
2843 | _M_cp.reserve(_M_den.size()); | |
2844 | std::partial_sum(_M_den.begin(), _M_den.end(), | |
2845 | std::back_inserter(_M_cp)); | |
2846 | ||
2847 | // Make sure the last cumulative probability is one. | |
8e79468d | 2848 | _M_cp[_M_cp.size() - 1] = 1.0; |
f8dd9e0d PC |
2849 | |
2850 | for (size_t __k = 0; __k < _M_den.size(); ++__k) | |
2851 | _M_den[__k] /= _M_int[__k + 1] - _M_int[__k]; | |
8e79468d BK |
2852 | } |
2853 | ||
8e79468d BK |
2854 | template<typename _RealType> |
2855 | template<typename _InputIteratorB, typename _InputIteratorW> | |
2856 | piecewise_constant_distribution<_RealType>::param_type:: | |
2857 | param_type(_InputIteratorB __bbegin, | |
2858 | _InputIteratorB __bend, | |
2859 | _InputIteratorW __wbegin) | |
2860 | : _M_int(), _M_den(), _M_cp() | |
2861 | { | |
f8dd9e0d | 2862 | if (__bbegin != __bend) |
8e79468d | 2863 | { |
f8dd9e0d | 2864 | for (;;) |
8e79468d | 2865 | { |
f8dd9e0d PC |
2866 | _M_int.push_back(*__bbegin); |
2867 | ++__bbegin; | |
2868 | if (__bbegin == __bend) | |
2869 | break; | |
2870 | ||
8e79468d BK |
2871 | _M_den.push_back(*__wbegin); |
2872 | ++__wbegin; | |
2873 | } | |
2874 | } | |
8e79468d BK |
2875 | |
2876 | _M_initialize(); | |
2877 | } | |
2878 | ||
2879 | template<typename _RealType> | |
2880 | template<typename _Func> | |
2881 | piecewise_constant_distribution<_RealType>::param_type:: | |
f8dd9e0d | 2882 | param_type(initializer_list<_RealType> __bl, _Func __fw) |
8e79468d BK |
2883 | : _M_int(), _M_den(), _M_cp() |
2884 | { | |
f8dd9e0d PC |
2885 | _M_int.reserve(__bl.size()); |
2886 | for (auto __biter = __bl.begin(); __biter != __bl.end(); ++__biter) | |
8e79468d BK |
2887 | _M_int.push_back(*__biter); |
2888 | ||
f8dd9e0d PC |
2889 | _M_den.reserve(_M_int.size() - 1); |
2890 | for (size_t __k = 0; __k < _M_int.size() - 1; ++__k) | |
2891 | _M_den.push_back(__fw(0.5 * (_M_int[__k + 1] + _M_int[__k]))); | |
8e79468d BK |
2892 | |
2893 | _M_initialize(); | |
2894 | } | |
2895 | ||
2896 | template<typename _RealType> | |
2897 | template<typename _Func> | |
2898 | piecewise_constant_distribution<_RealType>::param_type:: | |
b01630bb | 2899 | param_type(size_t __nw, _RealType __xmin, _RealType __xmax, _Func __fw) |
8e79468d BK |
2900 | : _M_int(), _M_den(), _M_cp() |
2901 | { | |
f8dd9e0d PC |
2902 | const size_t __n = __nw == 0 ? 1 : __nw; |
2903 | const _RealType __delta = (__xmax - __xmin) / __n; | |
2904 | ||
2905 | _M_int.reserve(__n + 1); | |
2906 | for (size_t __k = 0; __k <= __nw; ++__k) | |
2907 | _M_int.push_back(__xmin + __k * __delta); | |
2908 | ||
2909 | _M_den.reserve(__n); | |
2910 | for (size_t __k = 0; __k < __nw; ++__k) | |
2911 | _M_den.push_back(__fw(_M_int[__k] + 0.5 * __delta)); | |
8e79468d BK |
2912 | |
2913 | _M_initialize(); | |
2914 | } | |
2915 | ||
2916 | template<typename _RealType> | |
2917 | template<typename _UniformRandomNumberGenerator> | |
2918 | typename piecewise_constant_distribution<_RealType>::result_type | |
2919 | piecewise_constant_distribution<_RealType>:: | |
2920 | operator()(_UniformRandomNumberGenerator& __urng, | |
2921 | const param_type& __param) | |
2922 | { | |
9b88236b | 2923 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> |
8e79468d BK |
2924 | __aurng(__urng); |
2925 | ||
2926 | const double __p = __aurng(); | |
879b9073 PC |
2927 | if (__param._M_cp.empty()) |
2928 | return __p; | |
2929 | ||
8e79468d BK |
2930 | auto __pos = std::lower_bound(__param._M_cp.begin(), |
2931 | __param._M_cp.end(), __p); | |
2932 | const size_t __i = __pos - __param._M_cp.begin(); | |
2933 | ||
f8dd9e0d PC |
2934 | const double __pref = __i > 0 ? __param._M_cp[__i - 1] : 0.0; |
2935 | ||
2936 | return __param._M_int[__i] + (__p - __pref) / __param._M_den[__i]; | |
8e79468d BK |
2937 | } |
2938 | ||
7b93bdde UD |
2939 | template<typename _RealType> |
2940 | template<typename _ForwardIterator, | |
2941 | typename _UniformRandomNumberGenerator> | |
2942 | void | |
2943 | piecewise_constant_distribution<_RealType>:: | |
2944 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2945 | _UniformRandomNumberGenerator& __urng, | |
2946 | const param_type& __param) | |
2947 | { | |
2948 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2949 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
2950 | __aurng(__urng); | |
2951 | ||
2952 | if (__param._M_cp.empty()) | |
2953 | { | |
2954 | while (__f != __t) | |
2955 | *__f++ = __aurng(); | |
2956 | return; | |
2957 | } | |
2958 | ||
2959 | while (__f != __t) | |
2960 | { | |
2961 | const double __p = __aurng(); | |
2962 | ||
2963 | auto __pos = std::lower_bound(__param._M_cp.begin(), | |
2964 | __param._M_cp.end(), __p); | |
2965 | const size_t __i = __pos - __param._M_cp.begin(); | |
2966 | ||
2967 | const double __pref = __i > 0 ? __param._M_cp[__i - 1] : 0.0; | |
2968 | ||
2969 | *__f++ = (__param._M_int[__i] | |
2970 | + (__p - __pref) / __param._M_den[__i]); | |
2971 | } | |
2972 | } | |
2973 | ||
8e79468d BK |
2974 | template<typename _RealType, typename _CharT, typename _Traits> |
2975 | std::basic_ostream<_CharT, _Traits>& | |
2976 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2977 | const piecewise_constant_distribution<_RealType>& __x) | |
2978 | { | |
160e95dc | 2979 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
2980 | |
2981 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2982 | const _CharT __fill = __os.fill(); | |
2983 | const std::streamsize __precision = __os.precision(); | |
2984 | const _CharT __space = __os.widen(' '); | |
2985 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2986 | __os.fill(__space); | |
7703dc47 | 2987 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d BK |
2988 | |
2989 | std::vector<_RealType> __int = __x.intervals(); | |
2990 | __os << __int.size() - 1; | |
2991 | ||
2992 | for (auto __xit = __int.begin(); __xit != __int.end(); ++__xit) | |
2993 | __os << __space << *__xit; | |
2994 | ||
2995 | std::vector<double> __den = __x.densities(); | |
2996 | for (auto __dit = __den.begin(); __dit != __den.end(); ++__dit) | |
2997 | __os << __space << *__dit; | |
2998 | ||
2999 | __os.flags(__flags); | |
3000 | __os.fill(__fill); | |
3001 | __os.precision(__precision); | |
3002 | return __os; | |
3003 | } | |
3004 | ||
3005 | template<typename _RealType, typename _CharT, typename _Traits> | |
3006 | std::basic_istream<_CharT, _Traits>& | |
3007 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
3008 | piecewise_constant_distribution<_RealType>& __x) | |
3009 | { | |
160e95dc | 3010 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; |
8e79468d BK |
3011 | |
3012 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
3013 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
3014 | ||
3015 | size_t __n; | |
160e95dc | 3016 | if (__is >> __n) |
8e79468d | 3017 | { |
160e95dc JW |
3018 | std::vector<_RealType> __int_vec; |
3019 | if (__detail::__extract_params(__is, __int_vec, __n + 1)) | |
3020 | { | |
3021 | std::vector<double> __den_vec; | |
3022 | if (__detail::__extract_params(__is, __den_vec, __n)) | |
3023 | { | |
3024 | __x.param({ __int_vec.begin(), __int_vec.end(), | |
3025 | __den_vec.begin() }); | |
3026 | } | |
3027 | } | |
8e79468d BK |
3028 | } |
3029 | ||
8e79468d BK |
3030 | __is.flags(__flags); |
3031 | return __is; | |
3032 | } | |
3033 | ||
3034 | ||
3035 | template<typename _RealType> | |
3036 | void | |
3037 | piecewise_linear_distribution<_RealType>::param_type:: | |
3038 | _M_initialize() | |
3039 | { | |
879b9073 PC |
3040 | if (_M_int.size() < 2 |
3041 | || (_M_int.size() == 2 | |
3042 | && _M_int[0] == _RealType(0) | |
3043 | && _M_int[1] == _RealType(1) | |
3044 | && _M_den[0] == _M_den[1])) | |
8e79468d BK |
3045 | { |
3046 | _M_int.clear(); | |
8e79468d | 3047 | _M_den.clear(); |
8e79468d BK |
3048 | return; |
3049 | } | |
3050 | ||
3051 | double __sum = 0.0; | |
f8dd9e0d PC |
3052 | _M_cp.reserve(_M_int.size() - 1); |
3053 | _M_m.reserve(_M_int.size() - 1); | |
3054 | for (size_t __k = 0; __k < _M_int.size() - 1; ++__k) | |
8e79468d | 3055 | { |
f8dd9e0d PC |
3056 | const _RealType __delta = _M_int[__k + 1] - _M_int[__k]; |
3057 | __sum += 0.5 * (_M_den[__k + 1] + _M_den[__k]) * __delta; | |
8e79468d | 3058 | _M_cp.push_back(__sum); |
f8dd9e0d | 3059 | _M_m.push_back((_M_den[__k + 1] - _M_den[__k]) / __delta); |
8e79468d | 3060 | } |
b2a96bf9 | 3061 | __glibcxx_assert(__sum > 0); |
8e79468d BK |
3062 | |
3063 | // Now normalize the densities... | |
60f3a59f PC |
3064 | __detail::__normalize(_M_den.begin(), _M_den.end(), _M_den.begin(), |
3065 | __sum); | |
8e79468d | 3066 | // ... and partial sums... |
60f3a59f | 3067 | __detail::__normalize(_M_cp.begin(), _M_cp.end(), _M_cp.begin(), __sum); |
8e79468d | 3068 | // ... and slopes. |
60f3a59f PC |
3069 | __detail::__normalize(_M_m.begin(), _M_m.end(), _M_m.begin(), __sum); |
3070 | ||
8e79468d BK |
3071 | // Make sure the last cumulative probablility is one. |
3072 | _M_cp[_M_cp.size() - 1] = 1.0; | |
f8dd9e0d | 3073 | } |
8e79468d BK |
3074 | |
3075 | template<typename _RealType> | |
3076 | template<typename _InputIteratorB, typename _InputIteratorW> | |
3077 | piecewise_linear_distribution<_RealType>::param_type:: | |
3078 | param_type(_InputIteratorB __bbegin, | |
3079 | _InputIteratorB __bend, | |
3080 | _InputIteratorW __wbegin) | |
3081 | : _M_int(), _M_den(), _M_cp(), _M_m() | |
3082 | { | |
3083 | for (; __bbegin != __bend; ++__bbegin, ++__wbegin) | |
3084 | { | |
3085 | _M_int.push_back(*__bbegin); | |
3086 | _M_den.push_back(*__wbegin); | |
3087 | } | |
3088 | ||
3089 | _M_initialize(); | |
3090 | } | |
3091 | ||
3092 | template<typename _RealType> | |
3093 | template<typename _Func> | |
3094 | piecewise_linear_distribution<_RealType>::param_type:: | |
f8dd9e0d | 3095 | param_type(initializer_list<_RealType> __bl, _Func __fw) |
8e79468d BK |
3096 | : _M_int(), _M_den(), _M_cp(), _M_m() |
3097 | { | |
f8dd9e0d PC |
3098 | _M_int.reserve(__bl.size()); |
3099 | _M_den.reserve(__bl.size()); | |
3100 | for (auto __biter = __bl.begin(); __biter != __bl.end(); ++__biter) | |
8e79468d BK |
3101 | { |
3102 | _M_int.push_back(*__biter); | |
3103 | _M_den.push_back(__fw(*__biter)); | |
3104 | } | |
3105 | ||
3106 | _M_initialize(); | |
3107 | } | |
3108 | ||
3109 | template<typename _RealType> | |
3110 | template<typename _Func> | |
3111 | piecewise_linear_distribution<_RealType>::param_type:: | |
f8dd9e0d | 3112 | param_type(size_t __nw, _RealType __xmin, _RealType __xmax, _Func __fw) |
8e79468d BK |
3113 | : _M_int(), _M_den(), _M_cp(), _M_m() |
3114 | { | |
f8dd9e0d PC |
3115 | const size_t __n = __nw == 0 ? 1 : __nw; |
3116 | const _RealType __delta = (__xmax - __xmin) / __n; | |
3117 | ||
3118 | _M_int.reserve(__n + 1); | |
3119 | _M_den.reserve(__n + 1); | |
3120 | for (size_t __k = 0; __k <= __nw; ++__k) | |
8e79468d | 3121 | { |
f8dd9e0d PC |
3122 | _M_int.push_back(__xmin + __k * __delta); |
3123 | _M_den.push_back(__fw(_M_int[__k] + __delta)); | |
8e79468d BK |
3124 | } |
3125 | ||
3126 | _M_initialize(); | |
3127 | } | |
3128 | ||
3129 | template<typename _RealType> | |
3130 | template<typename _UniformRandomNumberGenerator> | |
3131 | typename piecewise_linear_distribution<_RealType>::result_type | |
3132 | piecewise_linear_distribution<_RealType>:: | |
3133 | operator()(_UniformRandomNumberGenerator& __urng, | |
3134 | const param_type& __param) | |
3135 | { | |
9b88236b | 3136 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> |
8e79468d BK |
3137 | __aurng(__urng); |
3138 | ||
3139 | const double __p = __aurng(); | |
879b9073 | 3140 | if (__param._M_cp.empty()) |
d3a73504 PC |
3141 | return __p; |
3142 | ||
8e79468d BK |
3143 | auto __pos = std::lower_bound(__param._M_cp.begin(), |
3144 | __param._M_cp.end(), __p); | |
3145 | const size_t __i = __pos - __param._M_cp.begin(); | |
f8dd9e0d PC |
3146 | |
3147 | const double __pref = __i > 0 ? __param._M_cp[__i - 1] : 0.0; | |
3148 | ||
8e79468d BK |
3149 | const double __a = 0.5 * __param._M_m[__i]; |
3150 | const double __b = __param._M_den[__i]; | |
f8dd9e0d PC |
3151 | const double __cm = __p - __pref; |
3152 | ||
3153 | _RealType __x = __param._M_int[__i]; | |
3154 | if (__a == 0) | |
3155 | __x += __cm / __b; | |
3156 | else | |
3157 | { | |
3158 | const double __d = __b * __b + 4.0 * __a * __cm; | |
3159 | __x += 0.5 * (std::sqrt(__d) - __b) / __a; | |
3160 | } | |
8e79468d | 3161 | |
f8dd9e0d | 3162 | return __x; |
8e79468d BK |
3163 | } |
3164 | ||
7b93bdde UD |
3165 | template<typename _RealType> |
3166 | template<typename _ForwardIterator, | |
3167 | typename _UniformRandomNumberGenerator> | |
3168 | void | |
3169 | piecewise_linear_distribution<_RealType>:: | |
3170 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
3171 | _UniformRandomNumberGenerator& __urng, | |
3172 | const param_type& __param) | |
3173 | { | |
3174 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
3175 | // We could duplicate everything from operator()... | |
3176 | while (__f != __t) | |
3177 | *__f++ = this->operator()(__urng, __param); | |
3178 | } | |
3179 | ||
8e79468d BK |
3180 | template<typename _RealType, typename _CharT, typename _Traits> |
3181 | std::basic_ostream<_CharT, _Traits>& | |
3182 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
3183 | const piecewise_linear_distribution<_RealType>& __x) | |
3184 | { | |
160e95dc | 3185 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
3186 | |
3187 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
3188 | const _CharT __fill = __os.fill(); | |
3189 | const std::streamsize __precision = __os.precision(); | |
3190 | const _CharT __space = __os.widen(' '); | |
3191 | __os.flags(__ios_base::scientific | __ios_base::left); | |
3192 | __os.fill(__space); | |
7703dc47 | 3193 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d BK |
3194 | |
3195 | std::vector<_RealType> __int = __x.intervals(); | |
3196 | __os << __int.size() - 1; | |
3197 | ||
3198 | for (auto __xit = __int.begin(); __xit != __int.end(); ++__xit) | |
3199 | __os << __space << *__xit; | |
3200 | ||
3201 | std::vector<double> __den = __x.densities(); | |
3202 | for (auto __dit = __den.begin(); __dit != __den.end(); ++__dit) | |
3203 | __os << __space << *__dit; | |
3204 | ||
3205 | __os.flags(__flags); | |
3206 | __os.fill(__fill); | |
3207 | __os.precision(__precision); | |
3208 | return __os; | |
3209 | } | |
3210 | ||
3211 | template<typename _RealType, typename _CharT, typename _Traits> | |
3212 | std::basic_istream<_CharT, _Traits>& | |
3213 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
3214 | piecewise_linear_distribution<_RealType>& __x) | |
3215 | { | |
160e95dc | 3216 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; |
8e79468d BK |
3217 | |
3218 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
3219 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
3220 | ||
3221 | size_t __n; | |
160e95dc | 3222 | if (__is >> __n) |
8e79468d | 3223 | { |
160e95dc JW |
3224 | vector<_RealType> __int_vec; |
3225 | if (__detail::__extract_params(__is, __int_vec, __n + 1)) | |
3226 | { | |
3227 | vector<double> __den_vec; | |
3228 | if (__detail::__extract_params(__is, __den_vec, __n + 1)) | |
3229 | { | |
3230 | __x.param({ __int_vec.begin(), __int_vec.end(), | |
3231 | __den_vec.begin() }); | |
3232 | } | |
3233 | } | |
8e79468d | 3234 | } |
8e79468d BK |
3235 | __is.flags(__flags); |
3236 | return __is; | |
3237 | } | |
3238 | ||
3239 | ||
6c63cb23 | 3240 | template<typename _IntType, typename> |
8e79468d BK |
3241 | seed_seq::seed_seq(std::initializer_list<_IntType> __il) |
3242 | { | |
174f9257 | 3243 | _M_v.reserve(__il.size()); |
8e79468d | 3244 | for (auto __iter = __il.begin(); __iter != __il.end(); ++__iter) |
b94f4bef | 3245 | _M_v.push_back(__detail::__mod<result_type, |
8e79468d BK |
3246 | __detail::_Shift<result_type, 32>::__value>(*__iter)); |
3247 | } | |
3248 | ||
3249 | template<typename _InputIterator> | |
3250 | seed_seq::seed_seq(_InputIterator __begin, _InputIterator __end) | |
3251 | { | |
174f9257 AP |
3252 | if _GLIBCXX17_CONSTEXPR (__is_random_access_iter<_InputIterator>::value) |
3253 | _M_v.reserve(std::distance(__begin, __end)); | |
3254 | ||
8e79468d | 3255 | for (_InputIterator __iter = __begin; __iter != __end; ++__iter) |
b94f4bef | 3256 | _M_v.push_back(__detail::__mod<result_type, |
8e79468d BK |
3257 | __detail::_Shift<result_type, 32>::__value>(*__iter)); |
3258 | } | |
3259 | ||
3260 | template<typename _RandomAccessIterator> | |
3261 | void | |
3262 | seed_seq::generate(_RandomAccessIterator __begin, | |
3263 | _RandomAccessIterator __end) | |
3264 | { | |
3265 | typedef typename iterator_traits<_RandomAccessIterator>::value_type | |
6855fe45 | 3266 | _Type; |
8e79468d BK |
3267 | |
3268 | if (__begin == __end) | |
3269 | return; | |
3270 | ||
b94f4bef | 3271 | std::fill(__begin, __end, _Type(0x8b8b8b8bu)); |
8e79468d BK |
3272 | |
3273 | const size_t __n = __end - __begin; | |
3274 | const size_t __s = _M_v.size(); | |
3275 | const size_t __t = (__n >= 623) ? 11 | |
3276 | : (__n >= 68) ? 7 | |
3277 | : (__n >= 39) ? 5 | |
3278 | : (__n >= 7) ? 3 | |
3279 | : (__n - 1) / 2; | |
3280 | const size_t __p = (__n - __t) / 2; | |
3281 | const size_t __q = __p + __t; | |
58651854 | 3282 | const size_t __m = std::max(size_t(__s + 1), __n); |
8e79468d | 3283 | |
3ee44d4c JW |
3284 | #ifndef __UINT32_TYPE__ |
3285 | struct _Up | |
3286 | { | |
3287 | _Up(uint_least32_t v) : _M_v(v & 0xffffffffu) { } | |
3288 | ||
3289 | operator uint_least32_t() const { return _M_v; } | |
3290 | ||
3291 | uint_least32_t _M_v; | |
3292 | }; | |
3293 | using uint32_t = _Up; | |
3294 | #endif | |
3295 | ||
3296 | // k == 0, every element in [begin,end) equals 0x8b8b8b8bu | |
8e79468d | 3297 | { |
3ee44d4c JW |
3298 | uint32_t __r1 = 1371501266u; |
3299 | uint32_t __r2 = __r1 + __s; | |
3300 | __begin[__p] += __r1; | |
3301 | __begin[__q] = (uint32_t)__begin[__q] + __r2; | |
3302 | __begin[0] = __r2; | |
3303 | } | |
3304 | ||
3305 | for (size_t __k = 1; __k <= __s; ++__k) | |
3306 | { | |
3307 | const size_t __kn = __k % __n; | |
3308 | const size_t __kpn = (__k + __p) % __n; | |
3309 | const size_t __kqn = (__k + __q) % __n; | |
3310 | uint32_t __arg = (__begin[__kn] | |
3311 | ^ __begin[__kpn] | |
3312 | ^ __begin[(__k - 1) % __n]); | |
3313 | uint32_t __r1 = 1664525u * (__arg ^ (__arg >> 27)); | |
3314 | uint32_t __r2 = __r1 + (uint32_t)__kn + _M_v[__k - 1]; | |
3315 | __begin[__kpn] = (uint32_t)__begin[__kpn] + __r1; | |
3316 | __begin[__kqn] = (uint32_t)__begin[__kqn] + __r2; | |
3317 | __begin[__kn] = __r2; | |
3318 | } | |
3319 | ||
3320 | for (size_t __k = __s + 1; __k < __m; ++__k) | |
3321 | { | |
3322 | const size_t __kn = __k % __n; | |
3323 | const size_t __kpn = (__k + __p) % __n; | |
3324 | const size_t __kqn = (__k + __q) % __n; | |
3325 | uint32_t __arg = (__begin[__kn] | |
3326 | ^ __begin[__kpn] | |
3327 | ^ __begin[(__k - 1) % __n]); | |
3328 | uint32_t __r1 = 1664525u * (__arg ^ (__arg >> 27)); | |
3329 | uint32_t __r2 = __r1 + (uint32_t)__kn; | |
3330 | __begin[__kpn] = (uint32_t)__begin[__kpn] + __r1; | |
3331 | __begin[__kqn] = (uint32_t)__begin[__kqn] + __r2; | |
3332 | __begin[__kn] = __r2; | |
8e79468d BK |
3333 | } |
3334 | ||
3335 | for (size_t __k = __m; __k < __m + __n; ++__k) | |
3336 | { | |
3ee44d4c JW |
3337 | const size_t __kn = __k % __n; |
3338 | const size_t __kpn = (__k + __p) % __n; | |
3339 | const size_t __kqn = (__k + __q) % __n; | |
3340 | uint32_t __arg = (__begin[__kn] | |
3341 | + __begin[__kpn] | |
3342 | + __begin[(__k - 1) % __n]); | |
3343 | uint32_t __r3 = 1566083941u * (__arg ^ (__arg >> 27)); | |
3344 | uint32_t __r4 = __r3 - __kn; | |
3345 | __begin[__kpn] ^= __r3; | |
3346 | __begin[__kqn] ^= __r4; | |
3347 | __begin[__kn] = __r4; | |
8e79468d BK |
3348 | } |
3349 | } | |
3350 | ||
3351 | template<typename _RealType, size_t __bits, | |
3352 | typename _UniformRandomNumberGenerator> | |
3353 | _RealType | |
3354 | generate_canonical(_UniformRandomNumberGenerator& __urng) | |
3355 | { | |
1c4ff014 | 3356 | static_assert(std::is_floating_point<_RealType>::value, |
0cded43d | 3357 | "template argument must be a floating point type"); |
1c4ff014 | 3358 | |
8e79468d BK |
3359 | const size_t __b |
3360 | = std::min(static_cast<size_t>(std::numeric_limits<_RealType>::digits), | |
3361 | __bits); | |
3362 | const long double __r = static_cast<long double>(__urng.max()) | |
3363 | - static_cast<long double>(__urng.min()) + 1.0L; | |
b01630bb | 3364 | const size_t __log2r = std::log(__r) / std::log(2.0L); |
33df19a7 ESR |
3365 | const size_t __m = std::max<size_t>(1UL, |
3366 | (__b + __log2r - 1UL) / __log2r); | |
3367 | _RealType __ret; | |
92d85953 JW |
3368 | _RealType __sum = _RealType(0); |
3369 | _RealType __tmp = _RealType(1); | |
3370 | for (size_t __k = __m; __k != 0; --__k) | |
8e79468d | 3371 | { |
92d85953 JW |
3372 | __sum += _RealType(__urng() - __urng.min()) * __tmp; |
3373 | __tmp *= __r; | |
3374 | } | |
3375 | __ret = __sum / __tmp; | |
3376 | if (__builtin_expect(__ret >= _RealType(1), 0)) | |
3377 | { | |
3378 | #if _GLIBCXX_USE_C99_MATH_TR1 | |
3379 | __ret = std::nextafter(_RealType(1), _RealType(0)); | |
3380 | #else | |
3381 | __ret = _RealType(1) | |
3382 | - std::numeric_limits<_RealType>::epsilon() / _RealType(2); | |
3383 | #endif | |
8e79468d | 3384 | } |
33df19a7 | 3385 | return __ret; |
8e79468d | 3386 | } |
12ffa228 BK |
3387 | |
3388 | _GLIBCXX_END_NAMESPACE_VERSION | |
3389 | } // namespace | |
06f29237 PC |
3390 | |
3391 | #endif |