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8e79468d BK |
1 | // random number generation (out of line) -*- C++ -*- |
2 | ||
8d9254fc | 3 | // Copyright (C) 2009-2020 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 | ||
8e79468d BK |
39 | /* |
40 | * (Further) implementation-space details. | |
41 | */ | |
42 | namespace __detail | |
43 | { | |
cf48c255 MG |
44 | // General case for x = (ax + c) mod m -- use Schrage's algorithm |
45 | // to avoid integer overflow. | |
8e79468d BK |
46 | // |
47 | // Preconditions: a > 0, m > 0. | |
48 | // | |
cf48c255 | 49 | // Note: only works correctly for __m % __a < __m / __a. |
b94f4bef | 50 | template<typename _Tp, _Tp __m, _Tp __a, _Tp __c> |
cf48c255 MG |
51 | _Tp |
52 | _Mod<_Tp, __m, __a, __c, false, true>:: | |
53 | __calc(_Tp __x) | |
8e79468d | 54 | { |
cf48c255 MG |
55 | if (__a == 1) |
56 | __x %= __m; | |
57 | else | |
58 | { | |
59 | static const _Tp __q = __m / __a; | |
60 | static const _Tp __r = __m % __a; | |
61 | ||
62 | _Tp __t1 = __a * (__x % __q); | |
63 | _Tp __t2 = __r * (__x / __q); | |
64 | if (__t1 >= __t2) | |
65 | __x = __t1 - __t2; | |
66 | else | |
67 | __x = __m - __t2 + __t1; | |
68 | } | |
69 | ||
70 | if (__c != 0) | |
71 | { | |
72 | const _Tp __d = __m - __x; | |
73 | if (__d > __c) | |
74 | __x += __c; | |
75 | else | |
76 | __x = __c - __d; | |
77 | } | |
78 | return __x; | |
79 | } | |
247d8075 | 80 | |
afcd05a7 | 81 | template<typename _InputIterator, typename _OutputIterator, |
60f3a59f | 82 | typename _Tp> |
afcd05a7 | 83 | _OutputIterator |
60f3a59f PC |
84 | __normalize(_InputIterator __first, _InputIterator __last, |
85 | _OutputIterator __result, const _Tp& __factor) | |
afcd05a7 PC |
86 | { |
87 | for (; __first != __last; ++__first, ++__result) | |
60f3a59f | 88 | *__result = *__first / __factor; |
afcd05a7 PC |
89 | return __result; |
90 | } | |
12ffa228 | 91 | |
8e79468d BK |
92 | } // namespace __detail |
93 | ||
300ea283 | 94 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m> |
94a86be0 | 95 | constexpr _UIntType |
300ea283 PC |
96 | linear_congruential_engine<_UIntType, __a, __c, __m>::multiplier; |
97 | ||
98 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m> | |
94a86be0 | 99 | constexpr _UIntType |
300ea283 PC |
100 | linear_congruential_engine<_UIntType, __a, __c, __m>::increment; |
101 | ||
102 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m> | |
94a86be0 | 103 | constexpr _UIntType |
300ea283 PC |
104 | linear_congruential_engine<_UIntType, __a, __c, __m>::modulus; |
105 | ||
106 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m> | |
94a86be0 | 107 | constexpr _UIntType |
300ea283 PC |
108 | linear_congruential_engine<_UIntType, __a, __c, __m>::default_seed; |
109 | ||
8e79468d | 110 | /** |
96a9203b | 111 | * Seeds the LCR with integral value @p __s, adjusted so that the |
8e79468d BK |
112 | * ring identity is never a member of the convergence set. |
113 | */ | |
114 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m> | |
115 | void | |
116 | linear_congruential_engine<_UIntType, __a, __c, __m>:: | |
96a9203b | 117 | seed(result_type __s) |
8e79468d | 118 | { |
b94f4bef PC |
119 | if ((__detail::__mod<_UIntType, __m>(__c) == 0) |
120 | && (__detail::__mod<_UIntType, __m>(__s) == 0)) | |
121 | _M_x = 1; | |
8e79468d | 122 | else |
b94f4bef | 123 | _M_x = __detail::__mod<_UIntType, __m>(__s); |
8e79468d BK |
124 | } |
125 | ||
126 | /** | |
96a9203b | 127 | * Seeds the LCR engine with a value generated by @p __q. |
8e79468d BK |
128 | */ |
129 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m> | |
05eeebfe | 130 | template<typename _Sseq> |
5a7960da | 131 | auto |
15ecdcc6 PC |
132 | linear_congruential_engine<_UIntType, __a, __c, __m>:: |
133 | seed(_Sseq& __q) | |
5a7960da | 134 | -> _If_seed_seq<_Sseq> |
15ecdcc6 PC |
135 | { |
136 | const _UIntType __k0 = __m == 0 ? std::numeric_limits<_UIntType>::digits | |
137 | : std::__lg(__m); | |
138 | const _UIntType __k = (__k0 + 31) / 32; | |
139 | uint_least32_t __arr[__k + 3]; | |
140 | __q.generate(__arr + 0, __arr + __k + 3); | |
141 | _UIntType __factor = 1u; | |
142 | _UIntType __sum = 0u; | |
143 | for (size_t __j = 0; __j < __k; ++__j) | |
144 | { | |
145 | __sum += __arr[__j + 3] * __factor; | |
146 | __factor *= __detail::_Shift<_UIntType, 32>::__value; | |
147 | } | |
148 | seed(__sum); | |
149 | } | |
8e79468d | 150 | |
8e79468d BK |
151 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m, |
152 | typename _CharT, typename _Traits> | |
153 | std::basic_ostream<_CharT, _Traits>& | |
154 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
155 | const linear_congruential_engine<_UIntType, | |
156 | __a, __c, __m>& __lcr) | |
157 | { | |
160e95dc | 158 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
159 | |
160 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
161 | const _CharT __fill = __os.fill(); | |
95fe602e | 162 | __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left); |
8e79468d BK |
163 | __os.fill(__os.widen(' ')); |
164 | ||
165 | __os << __lcr._M_x; | |
166 | ||
167 | __os.flags(__flags); | |
168 | __os.fill(__fill); | |
169 | return __os; | |
170 | } | |
171 | ||
172 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m, | |
173 | typename _CharT, typename _Traits> | |
174 | std::basic_istream<_CharT, _Traits>& | |
175 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
176 | linear_congruential_engine<_UIntType, __a, __c, __m>& __lcr) | |
177 | { | |
160e95dc | 178 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; |
8e79468d BK |
179 | |
180 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
181 | __is.flags(__ios_base::dec); | |
182 | ||
183 | __is >> __lcr._M_x; | |
184 | ||
185 | __is.flags(__flags); | |
186 | return __is; | |
187 | } | |
188 | ||
189 | ||
300ea283 PC |
190 | template<typename _UIntType, |
191 | size_t __w, size_t __n, size_t __m, size_t __r, | |
192 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
193 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
194 | _UIntType __f> | |
94a86be0 | 195 | constexpr size_t |
300ea283 PC |
196 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
197 | __s, __b, __t, __c, __l, __f>::word_size; | |
198 | ||
199 | template<typename _UIntType, | |
200 | size_t __w, size_t __n, size_t __m, size_t __r, | |
201 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
202 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
203 | _UIntType __f> | |
94a86be0 | 204 | constexpr size_t |
300ea283 PC |
205 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
206 | __s, __b, __t, __c, __l, __f>::state_size; | |
207 | ||
208 | template<typename _UIntType, | |
209 | size_t __w, size_t __n, size_t __m, size_t __r, | |
210 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
211 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
212 | _UIntType __f> | |
94a86be0 | 213 | constexpr size_t |
300ea283 PC |
214 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
215 | __s, __b, __t, __c, __l, __f>::shift_size; | |
216 | ||
217 | template<typename _UIntType, | |
218 | size_t __w, size_t __n, size_t __m, size_t __r, | |
219 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
220 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
221 | _UIntType __f> | |
94a86be0 | 222 | constexpr size_t |
300ea283 PC |
223 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
224 | __s, __b, __t, __c, __l, __f>::mask_bits; | |
225 | ||
226 | template<typename _UIntType, | |
227 | size_t __w, size_t __n, size_t __m, size_t __r, | |
228 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
229 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
230 | _UIntType __f> | |
94a86be0 | 231 | constexpr _UIntType |
300ea283 PC |
232 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
233 | __s, __b, __t, __c, __l, __f>::xor_mask; | |
234 | ||
235 | template<typename _UIntType, | |
236 | size_t __w, size_t __n, size_t __m, size_t __r, | |
237 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
238 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
239 | _UIntType __f> | |
94a86be0 | 240 | constexpr size_t |
300ea283 PC |
241 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
242 | __s, __b, __t, __c, __l, __f>::tempering_u; | |
243 | ||
244 | template<typename _UIntType, | |
245 | size_t __w, size_t __n, size_t __m, size_t __r, | |
246 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
247 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
248 | _UIntType __f> | |
94a86be0 | 249 | constexpr _UIntType |
300ea283 PC |
250 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
251 | __s, __b, __t, __c, __l, __f>::tempering_d; | |
252 | ||
253 | template<typename _UIntType, | |
254 | size_t __w, size_t __n, size_t __m, size_t __r, | |
255 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
256 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
257 | _UIntType __f> | |
94a86be0 | 258 | constexpr size_t |
300ea283 PC |
259 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
260 | __s, __b, __t, __c, __l, __f>::tempering_s; | |
261 | ||
262 | template<typename _UIntType, | |
263 | size_t __w, size_t __n, size_t __m, size_t __r, | |
264 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
265 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
266 | _UIntType __f> | |
94a86be0 | 267 | constexpr _UIntType |
300ea283 PC |
268 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
269 | __s, __b, __t, __c, __l, __f>::tempering_b; | |
270 | ||
271 | template<typename _UIntType, | |
272 | size_t __w, size_t __n, size_t __m, size_t __r, | |
273 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
274 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
275 | _UIntType __f> | |
94a86be0 | 276 | constexpr size_t |
300ea283 PC |
277 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
278 | __s, __b, __t, __c, __l, __f>::tempering_t; | |
279 | ||
280 | template<typename _UIntType, | |
281 | size_t __w, size_t __n, size_t __m, size_t __r, | |
282 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
283 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
284 | _UIntType __f> | |
94a86be0 | 285 | constexpr _UIntType |
300ea283 PC |
286 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
287 | __s, __b, __t, __c, __l, __f>::tempering_c; | |
288 | ||
289 | template<typename _UIntType, | |
290 | size_t __w, size_t __n, size_t __m, size_t __r, | |
291 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
292 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
293 | _UIntType __f> | |
94a86be0 | 294 | constexpr size_t |
300ea283 PC |
295 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
296 | __s, __b, __t, __c, __l, __f>::tempering_l; | |
297 | ||
298 | template<typename _UIntType, | |
299 | size_t __w, size_t __n, size_t __m, size_t __r, | |
300 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
301 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
302 | _UIntType __f> | |
94a86be0 | 303 | constexpr _UIntType |
300ea283 PC |
304 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
305 | __s, __b, __t, __c, __l, __f>:: | |
306 | initialization_multiplier; | |
307 | ||
308 | template<typename _UIntType, | |
309 | size_t __w, size_t __n, size_t __m, size_t __r, | |
310 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
311 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
312 | _UIntType __f> | |
94a86be0 | 313 | constexpr _UIntType |
300ea283 PC |
314 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
315 | __s, __b, __t, __c, __l, __f>::default_seed; | |
316 | ||
8e79468d BK |
317 | template<typename _UIntType, |
318 | size_t __w, size_t __n, size_t __m, size_t __r, | |
319 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
320 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
321 | _UIntType __f> | |
322 | void | |
323 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, | |
324 | __s, __b, __t, __c, __l, __f>:: | |
325 | seed(result_type __sd) | |
326 | { | |
b94f4bef | 327 | _M_x[0] = __detail::__mod<_UIntType, |
8e79468d BK |
328 | __detail::_Shift<_UIntType, __w>::__value>(__sd); |
329 | ||
330 | for (size_t __i = 1; __i < state_size; ++__i) | |
331 | { | |
332 | _UIntType __x = _M_x[__i - 1]; | |
333 | __x ^= __x >> (__w - 2); | |
334 | __x *= __f; | |
b94f4bef PC |
335 | __x += __detail::__mod<_UIntType, __n>(__i); |
336 | _M_x[__i] = __detail::__mod<_UIntType, | |
8e79468d BK |
337 | __detail::_Shift<_UIntType, __w>::__value>(__x); |
338 | } | |
339 | _M_p = state_size; | |
340 | } | |
341 | ||
342 | template<typename _UIntType, | |
343 | size_t __w, size_t __n, size_t __m, size_t __r, | |
344 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
345 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
346 | _UIntType __f> | |
05eeebfe | 347 | template<typename _Sseq> |
5a7960da | 348 | auto |
15ecdcc6 | 349 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
8e79468d | 350 | __s, __b, __t, __c, __l, __f>:: |
15ecdcc6 | 351 | seed(_Sseq& __q) |
5a7960da | 352 | -> _If_seed_seq<_Sseq> |
15ecdcc6 PC |
353 | { |
354 | const _UIntType __upper_mask = (~_UIntType()) << __r; | |
355 | const size_t __k = (__w + 31) / 32; | |
356 | uint_least32_t __arr[__n * __k]; | |
357 | __q.generate(__arr + 0, __arr + __n * __k); | |
358 | ||
359 | bool __zero = true; | |
360 | for (size_t __i = 0; __i < state_size; ++__i) | |
361 | { | |
362 | _UIntType __factor = 1u; | |
363 | _UIntType __sum = 0u; | |
364 | for (size_t __j = 0; __j < __k; ++__j) | |
365 | { | |
366 | __sum += __arr[__k * __i + __j] * __factor; | |
367 | __factor *= __detail::_Shift<_UIntType, 32>::__value; | |
368 | } | |
369 | _M_x[__i] = __detail::__mod<_UIntType, | |
370 | __detail::_Shift<_UIntType, __w>::__value>(__sum); | |
371 | ||
372 | if (__zero) | |
373 | { | |
374 | if (__i == 0) | |
375 | { | |
376 | if ((_M_x[0] & __upper_mask) != 0u) | |
377 | __zero = false; | |
378 | } | |
379 | else if (_M_x[__i] != 0u) | |
380 | __zero = false; | |
381 | } | |
382 | } | |
8e79468d | 383 | if (__zero) |
b94f4bef | 384 | _M_x[0] = __detail::_Shift<_UIntType, __w - 1>::__value; |
935ec36f | 385 | _M_p = state_size; |
15ecdcc6 | 386 | } |
8e79468d | 387 | |
b668e41a UD |
388 | template<typename _UIntType, size_t __w, |
389 | size_t __n, size_t __m, size_t __r, | |
390 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
391 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
392 | _UIntType __f> | |
393 | void | |
394 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, | |
395 | __s, __b, __t, __c, __l, __f>:: | |
396 | _M_gen_rand(void) | |
397 | { | |
398 | const _UIntType __upper_mask = (~_UIntType()) << __r; | |
399 | const _UIntType __lower_mask = ~__upper_mask; | |
400 | ||
401 | for (size_t __k = 0; __k < (__n - __m); ++__k) | |
402 | { | |
403 | _UIntType __y = ((_M_x[__k] & __upper_mask) | |
404 | | (_M_x[__k + 1] & __lower_mask)); | |
405 | _M_x[__k] = (_M_x[__k + __m] ^ (__y >> 1) | |
406 | ^ ((__y & 0x01) ? __a : 0)); | |
407 | } | |
408 | ||
409 | for (size_t __k = (__n - __m); __k < (__n - 1); ++__k) | |
410 | { | |
411 | _UIntType __y = ((_M_x[__k] & __upper_mask) | |
412 | | (_M_x[__k + 1] & __lower_mask)); | |
413 | _M_x[__k] = (_M_x[__k + (__m - __n)] ^ (__y >> 1) | |
414 | ^ ((__y & 0x01) ? __a : 0)); | |
415 | } | |
416 | ||
417 | _UIntType __y = ((_M_x[__n - 1] & __upper_mask) | |
418 | | (_M_x[0] & __lower_mask)); | |
419 | _M_x[__n - 1] = (_M_x[__m - 1] ^ (__y >> 1) | |
420 | ^ ((__y & 0x01) ? __a : 0)); | |
421 | _M_p = 0; | |
422 | } | |
423 | ||
424 | template<typename _UIntType, size_t __w, | |
425 | size_t __n, size_t __m, size_t __r, | |
426 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
427 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
428 | _UIntType __f> | |
429 | void | |
430 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, | |
431 | __s, __b, __t, __c, __l, __f>:: | |
432 | discard(unsigned long long __z) | |
433 | { | |
434 | while (__z > state_size - _M_p) | |
435 | { | |
436 | __z -= state_size - _M_p; | |
437 | _M_gen_rand(); | |
438 | } | |
439 | _M_p += __z; | |
440 | } | |
441 | ||
8e79468d BK |
442 | template<typename _UIntType, size_t __w, |
443 | size_t __n, size_t __m, size_t __r, | |
444 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
445 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
446 | _UIntType __f> | |
447 | typename | |
448 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, | |
449 | __s, __b, __t, __c, __l, __f>::result_type | |
450 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, | |
451 | __s, __b, __t, __c, __l, __f>:: | |
452 | operator()() | |
453 | { | |
454 | // Reload the vector - cost is O(n) amortized over n calls. | |
455 | if (_M_p >= state_size) | |
b668e41a | 456 | _M_gen_rand(); |
8e79468d BK |
457 | |
458 | // Calculate o(x(i)). | |
459 | result_type __z = _M_x[_M_p++]; | |
460 | __z ^= (__z >> __u) & __d; | |
461 | __z ^= (__z << __s) & __b; | |
462 | __z ^= (__z << __t) & __c; | |
463 | __z ^= (__z >> __l); | |
464 | ||
465 | return __z; | |
466 | } | |
467 | ||
468 | template<typename _UIntType, size_t __w, | |
469 | size_t __n, size_t __m, size_t __r, | |
470 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
471 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
472 | _UIntType __f, typename _CharT, typename _Traits> | |
473 | std::basic_ostream<_CharT, _Traits>& | |
474 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
475 | const mersenne_twister_engine<_UIntType, __w, __n, __m, | |
476 | __r, __a, __u, __d, __s, __b, __t, __c, __l, __f>& __x) | |
477 | { | |
160e95dc | 478 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
479 | |
480 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
481 | const _CharT __fill = __os.fill(); | |
482 | const _CharT __space = __os.widen(' '); | |
95fe602e | 483 | __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left); |
8e79468d BK |
484 | __os.fill(__space); |
485 | ||
31645179 | 486 | for (size_t __i = 0; __i < __n; ++__i) |
8e79468d | 487 | __os << __x._M_x[__i] << __space; |
31645179 | 488 | __os << __x._M_p; |
8e79468d BK |
489 | |
490 | __os.flags(__flags); | |
491 | __os.fill(__fill); | |
492 | return __os; | |
493 | } | |
494 | ||
495 | template<typename _UIntType, size_t __w, | |
496 | size_t __n, size_t __m, size_t __r, | |
497 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
498 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
499 | _UIntType __f, typename _CharT, typename _Traits> | |
500 | std::basic_istream<_CharT, _Traits>& | |
501 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
502 | mersenne_twister_engine<_UIntType, __w, __n, __m, | |
503 | __r, __a, __u, __d, __s, __b, __t, __c, __l, __f>& __x) | |
504 | { | |
160e95dc | 505 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; |
8e79468d BK |
506 | |
507 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
508 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
509 | ||
510 | for (size_t __i = 0; __i < __n; ++__i) | |
511 | __is >> __x._M_x[__i]; | |
31645179 | 512 | __is >> __x._M_p; |
8e79468d BK |
513 | |
514 | __is.flags(__flags); | |
515 | return __is; | |
516 | } | |
517 | ||
518 | ||
300ea283 | 519 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> |
94a86be0 | 520 | constexpr size_t |
300ea283 PC |
521 | subtract_with_carry_engine<_UIntType, __w, __s, __r>::word_size; |
522 | ||
523 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> | |
94a86be0 | 524 | constexpr size_t |
300ea283 PC |
525 | subtract_with_carry_engine<_UIntType, __w, __s, __r>::short_lag; |
526 | ||
527 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> | |
94a86be0 | 528 | constexpr size_t |
300ea283 PC |
529 | subtract_with_carry_engine<_UIntType, __w, __s, __r>::long_lag; |
530 | ||
531 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> | |
94a86be0 | 532 | constexpr _UIntType |
300ea283 PC |
533 | subtract_with_carry_engine<_UIntType, __w, __s, __r>::default_seed; |
534 | ||
8e79468d BK |
535 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> |
536 | void | |
537 | subtract_with_carry_engine<_UIntType, __w, __s, __r>:: | |
538 | seed(result_type __value) | |
539 | { | |
b94f4bef PC |
540 | std::linear_congruential_engine<result_type, 40014u, 0u, 2147483563u> |
541 | __lcg(__value == 0u ? default_seed : __value); | |
8e79468d | 542 | |
b94f4bef | 543 | const size_t __n = (__w + 31) / 32; |
8e79468d BK |
544 | |
545 | for (size_t __i = 0; __i < long_lag; ++__i) | |
546 | { | |
b94f4bef PC |
547 | _UIntType __sum = 0u; |
548 | _UIntType __factor = 1u; | |
8e79468d BK |
549 | for (size_t __j = 0; __j < __n; ++__j) |
550 | { | |
b94f4bef PC |
551 | __sum += __detail::__mod<uint_least32_t, |
552 | __detail::_Shift<uint_least32_t, 32>::__value> | |
8e79468d BK |
553 | (__lcg()) * __factor; |
554 | __factor *= __detail::_Shift<_UIntType, 32>::__value; | |
555 | } | |
b94f4bef | 556 | _M_x[__i] = __detail::__mod<_UIntType, |
96a9203b | 557 | __detail::_Shift<_UIntType, __w>::__value>(__sum); |
8e79468d BK |
558 | } |
559 | _M_carry = (_M_x[long_lag - 1] == 0) ? 1 : 0; | |
560 | _M_p = 0; | |
561 | } | |
562 | ||
563 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> | |
05eeebfe | 564 | template<typename _Sseq> |
5a7960da | 565 | auto |
15ecdcc6 PC |
566 | subtract_with_carry_engine<_UIntType, __w, __s, __r>:: |
567 | seed(_Sseq& __q) | |
5a7960da | 568 | -> _If_seed_seq<_Sseq> |
15ecdcc6 PC |
569 | { |
570 | const size_t __k = (__w + 31) / 32; | |
571 | uint_least32_t __arr[__r * __k]; | |
572 | __q.generate(__arr + 0, __arr + __r * __k); | |
573 | ||
574 | for (size_t __i = 0; __i < long_lag; ++__i) | |
575 | { | |
576 | _UIntType __sum = 0u; | |
577 | _UIntType __factor = 1u; | |
578 | for (size_t __j = 0; __j < __k; ++__j) | |
579 | { | |
580 | __sum += __arr[__k * __i + __j] * __factor; | |
581 | __factor *= __detail::_Shift<_UIntType, 32>::__value; | |
582 | } | |
583 | _M_x[__i] = __detail::__mod<_UIntType, | |
584 | __detail::_Shift<_UIntType, __w>::__value>(__sum); | |
585 | } | |
586 | _M_carry = (_M_x[long_lag - 1] == 0) ? 1 : 0; | |
587 | _M_p = 0; | |
588 | } | |
8e79468d BK |
589 | |
590 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> | |
591 | typename subtract_with_carry_engine<_UIntType, __w, __s, __r>:: | |
592 | result_type | |
593 | subtract_with_carry_engine<_UIntType, __w, __s, __r>:: | |
594 | operator()() | |
595 | { | |
596 | // Derive short lag index from current index. | |
597 | long __ps = _M_p - short_lag; | |
598 | if (__ps < 0) | |
599 | __ps += long_lag; | |
600 | ||
601 | // Calculate new x(i) without overflow or division. | |
602 | // NB: Thanks to the requirements for _UIntType, _M_x[_M_p] + _M_carry | |
603 | // cannot overflow. | |
604 | _UIntType __xi; | |
605 | if (_M_x[__ps] >= _M_x[_M_p] + _M_carry) | |
606 | { | |
607 | __xi = _M_x[__ps] - _M_x[_M_p] - _M_carry; | |
608 | _M_carry = 0; | |
609 | } | |
610 | else | |
611 | { | |
96a9203b PC |
612 | __xi = (__detail::_Shift<_UIntType, __w>::__value |
613 | - _M_x[_M_p] - _M_carry + _M_x[__ps]); | |
8e79468d BK |
614 | _M_carry = 1; |
615 | } | |
616 | _M_x[_M_p] = __xi; | |
617 | ||
618 | // Adjust current index to loop around in ring buffer. | |
619 | if (++_M_p >= long_lag) | |
620 | _M_p = 0; | |
621 | ||
622 | return __xi; | |
623 | } | |
624 | ||
625 | template<typename _UIntType, size_t __w, size_t __s, size_t __r, | |
626 | typename _CharT, typename _Traits> | |
627 | std::basic_ostream<_CharT, _Traits>& | |
628 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
629 | const subtract_with_carry_engine<_UIntType, | |
630 | __w, __s, __r>& __x) | |
631 | { | |
160e95dc | 632 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
633 | |
634 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
635 | const _CharT __fill = __os.fill(); | |
636 | const _CharT __space = __os.widen(' '); | |
95fe602e | 637 | __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left); |
8e79468d BK |
638 | __os.fill(__space); |
639 | ||
640 | for (size_t __i = 0; __i < __r; ++__i) | |
641 | __os << __x._M_x[__i] << __space; | |
31645179 | 642 | __os << __x._M_carry << __space << __x._M_p; |
8e79468d BK |
643 | |
644 | __os.flags(__flags); | |
645 | __os.fill(__fill); | |
646 | return __os; | |
647 | } | |
648 | ||
649 | template<typename _UIntType, size_t __w, size_t __s, size_t __r, | |
650 | typename _CharT, typename _Traits> | |
651 | std::basic_istream<_CharT, _Traits>& | |
652 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
653 | subtract_with_carry_engine<_UIntType, __w, __s, __r>& __x) | |
654 | { | |
160e95dc | 655 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; |
8e79468d BK |
656 | |
657 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
658 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
659 | ||
660 | for (size_t __i = 0; __i < __r; ++__i) | |
661 | __is >> __x._M_x[__i]; | |
662 | __is >> __x._M_carry; | |
31645179 | 663 | __is >> __x._M_p; |
8e79468d BK |
664 | |
665 | __is.flags(__flags); | |
666 | return __is; | |
667 | } | |
668 | ||
669 | ||
300ea283 | 670 | template<typename _RandomNumberEngine, size_t __p, size_t __r> |
94a86be0 | 671 | constexpr size_t |
300ea283 PC |
672 | discard_block_engine<_RandomNumberEngine, __p, __r>::block_size; |
673 | ||
674 | template<typename _RandomNumberEngine, size_t __p, size_t __r> | |
94a86be0 | 675 | constexpr size_t |
300ea283 PC |
676 | discard_block_engine<_RandomNumberEngine, __p, __r>::used_block; |
677 | ||
8e79468d BK |
678 | template<typename _RandomNumberEngine, size_t __p, size_t __r> |
679 | typename discard_block_engine<_RandomNumberEngine, | |
680 | __p, __r>::result_type | |
681 | discard_block_engine<_RandomNumberEngine, __p, __r>:: | |
682 | operator()() | |
683 | { | |
684 | if (_M_n >= used_block) | |
685 | { | |
686 | _M_b.discard(block_size - _M_n); | |
687 | _M_n = 0; | |
688 | } | |
689 | ++_M_n; | |
690 | return _M_b(); | |
691 | } | |
692 | ||
693 | template<typename _RandomNumberEngine, size_t __p, size_t __r, | |
694 | typename _CharT, typename _Traits> | |
695 | std::basic_ostream<_CharT, _Traits>& | |
696 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
697 | const discard_block_engine<_RandomNumberEngine, | |
698 | __p, __r>& __x) | |
699 | { | |
160e95dc | 700 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
701 | |
702 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
703 | const _CharT __fill = __os.fill(); | |
704 | const _CharT __space = __os.widen(' '); | |
95fe602e | 705 | __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left); |
8e79468d BK |
706 | __os.fill(__space); |
707 | ||
708 | __os << __x.base() << __space << __x._M_n; | |
709 | ||
710 | __os.flags(__flags); | |
711 | __os.fill(__fill); | |
712 | return __os; | |
713 | } | |
714 | ||
715 | template<typename _RandomNumberEngine, size_t __p, size_t __r, | |
716 | typename _CharT, typename _Traits> | |
717 | std::basic_istream<_CharT, _Traits>& | |
718 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
719 | discard_block_engine<_RandomNumberEngine, __p, __r>& __x) | |
720 | { | |
160e95dc | 721 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; |
8e79468d BK |
722 | |
723 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
724 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
725 | ||
726 | __is >> __x._M_b >> __x._M_n; | |
727 | ||
728 | __is.flags(__flags); | |
729 | return __is; | |
730 | } | |
731 | ||
732 | ||
733 | template<typename _RandomNumberEngine, size_t __w, typename _UIntType> | |
734 | typename independent_bits_engine<_RandomNumberEngine, __w, _UIntType>:: | |
735 | result_type | |
736 | independent_bits_engine<_RandomNumberEngine, __w, _UIntType>:: | |
737 | operator()() | |
738 | { | |
f84ca6e7 PC |
739 | typedef typename _RandomNumberEngine::result_type _Eresult_type; |
740 | const _Eresult_type __r | |
741 | = (_M_b.max() - _M_b.min() < std::numeric_limits<_Eresult_type>::max() | |
742 | ? _M_b.max() - _M_b.min() + 1 : 0); | |
743 | const unsigned __edig = std::numeric_limits<_Eresult_type>::digits; | |
744 | const unsigned __m = __r ? std::__lg(__r) : __edig; | |
745 | ||
746 | typedef typename std::common_type<_Eresult_type, result_type>::type | |
747 | __ctype; | |
748 | const unsigned __cdig = std::numeric_limits<__ctype>::digits; | |
749 | ||
750 | unsigned __n, __n0; | |
751 | __ctype __s0, __s1, __y0, __y1; | |
752 | ||
8e79468d BK |
753 | for (size_t __i = 0; __i < 2; ++__i) |
754 | { | |
755 | __n = (__w + __m - 1) / __m + __i; | |
756 | __n0 = __n - __w % __n; | |
f84ca6e7 PC |
757 | const unsigned __w0 = __w / __n; // __w0 <= __m |
758 | ||
759 | __s0 = 0; | |
760 | __s1 = 0; | |
761 | if (__w0 < __cdig) | |
762 | { | |
763 | __s0 = __ctype(1) << __w0; | |
764 | __s1 = __s0 << 1; | |
765 | } | |
766 | ||
767 | __y0 = 0; | |
768 | __y1 = 0; | |
769 | if (__r) | |
770 | { | |
771 | __y0 = __s0 * (__r / __s0); | |
772 | if (__s1) | |
773 | __y1 = __s1 * (__r / __s1); | |
774 | ||
775 | if (__r - __y0 <= __y0 / __n) | |
776 | break; | |
777 | } | |
778 | else | |
8e79468d BK |
779 | break; |
780 | } | |
781 | ||
782 | result_type __sum = 0; | |
783 | for (size_t __k = 0; __k < __n0; ++__k) | |
784 | { | |
f84ca6e7 | 785 | __ctype __u; |
8e79468d | 786 | do |
6855fe45 | 787 | __u = _M_b() - _M_b.min(); |
f84ca6e7 PC |
788 | while (__y0 && __u >= __y0); |
789 | __sum = __s0 * __sum + (__s0 ? __u % __s0 : __u); | |
8e79468d BK |
790 | } |
791 | for (size_t __k = __n0; __k < __n; ++__k) | |
792 | { | |
f84ca6e7 | 793 | __ctype __u; |
8e79468d | 794 | do |
6855fe45 | 795 | __u = _M_b() - _M_b.min(); |
f84ca6e7 PC |
796 | while (__y1 && __u >= __y1); |
797 | __sum = __s1 * __sum + (__s1 ? __u % __s1 : __u); | |
8e79468d BK |
798 | } |
799 | return __sum; | |
800 | } | |
801 | ||
802 | ||
300ea283 | 803 | template<typename _RandomNumberEngine, size_t __k> |
94a86be0 | 804 | constexpr size_t |
300ea283 PC |
805 | shuffle_order_engine<_RandomNumberEngine, __k>::table_size; |
806 | ||
60d9f254 JW |
807 | namespace __detail |
808 | { | |
809 | // Determine whether an integer is representable as double. | |
810 | template<typename _Tp> | |
811 | constexpr bool | |
812 | __representable_as_double(_Tp __x) noexcept | |
813 | { | |
814 | static_assert(numeric_limits<_Tp>::is_integer); | |
815 | static_assert(!numeric_limits<_Tp>::is_signed); | |
816 | // All integers <= 2^53 are representable. | |
817 | return (__x <= (1ull << __DBL_MANT_DIG__)) | |
818 | // Between 2^53 and 2^54 only even numbers are representable. | |
819 | || (!(__x & 1) && __detail::__representable_as_double(__x >> 1)); | |
820 | } | |
821 | ||
822 | // Determine whether x+1 is representable as double. | |
823 | template<typename _Tp> | |
824 | constexpr bool | |
825 | __p1_representable_as_double(_Tp __x) noexcept | |
826 | { | |
827 | static_assert(numeric_limits<_Tp>::is_integer); | |
828 | static_assert(!numeric_limits<_Tp>::is_signed); | |
829 | return numeric_limits<_Tp>::digits < __DBL_MANT_DIG__ | |
830 | || (bool(__x + 1u) // return false if x+1 wraps around to zero | |
831 | && __detail::__representable_as_double(__x + 1u)); | |
832 | } | |
833 | } | |
834 | ||
8e79468d BK |
835 | template<typename _RandomNumberEngine, size_t __k> |
836 | typename shuffle_order_engine<_RandomNumberEngine, __k>::result_type | |
837 | shuffle_order_engine<_RandomNumberEngine, __k>:: | |
838 | operator()() | |
839 | { | |
60d9f254 JW |
840 | constexpr result_type __range = max() - min(); |
841 | size_t __j = __k; | |
842 | const result_type __y = _M_y - min(); | |
843 | // Avoid using slower long double arithmetic if possible. | |
844 | if _GLIBCXX17_CONSTEXPR (__detail::__p1_representable_as_double(__range)) | |
845 | __j *= __y / (__range + 1.0); | |
846 | else | |
847 | __j *= __y / (__range + 1.0L); | |
8e79468d BK |
848 | _M_y = _M_v[__j]; |
849 | _M_v[__j] = _M_b(); | |
850 | ||
851 | return _M_y; | |
852 | } | |
853 | ||
854 | template<typename _RandomNumberEngine, size_t __k, | |
855 | typename _CharT, typename _Traits> | |
856 | std::basic_ostream<_CharT, _Traits>& | |
857 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
858 | const shuffle_order_engine<_RandomNumberEngine, __k>& __x) | |
859 | { | |
160e95dc | 860 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
861 | |
862 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
863 | const _CharT __fill = __os.fill(); | |
864 | const _CharT __space = __os.widen(' '); | |
95fe602e | 865 | __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left); |
8e79468d BK |
866 | __os.fill(__space); |
867 | ||
868 | __os << __x.base(); | |
869 | for (size_t __i = 0; __i < __k; ++__i) | |
870 | __os << __space << __x._M_v[__i]; | |
871 | __os << __space << __x._M_y; | |
872 | ||
873 | __os.flags(__flags); | |
874 | __os.fill(__fill); | |
875 | return __os; | |
876 | } | |
877 | ||
878 | template<typename _RandomNumberEngine, size_t __k, | |
879 | typename _CharT, typename _Traits> | |
880 | std::basic_istream<_CharT, _Traits>& | |
881 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
882 | shuffle_order_engine<_RandomNumberEngine, __k>& __x) | |
883 | { | |
160e95dc | 884 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; |
8e79468d BK |
885 | |
886 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
887 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
888 | ||
889 | __is >> __x._M_b; | |
890 | for (size_t __i = 0; __i < __k; ++__i) | |
891 | __is >> __x._M_v[__i]; | |
892 | __is >> __x._M_y; | |
893 | ||
894 | __is.flags(__flags); | |
895 | return __is; | |
896 | } | |
897 | ||
898 | ||
8e79468d BK |
899 | template<typename _IntType, typename _CharT, typename _Traits> |
900 | std::basic_ostream<_CharT, _Traits>& | |
901 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
902 | const uniform_int_distribution<_IntType>& __x) | |
903 | { | |
160e95dc | 904 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
905 | |
906 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
907 | const _CharT __fill = __os.fill(); | |
908 | const _CharT __space = __os.widen(' '); | |
909 | __os.flags(__ios_base::scientific | __ios_base::left); | |
910 | __os.fill(__space); | |
911 | ||
912 | __os << __x.a() << __space << __x.b(); | |
913 | ||
914 | __os.flags(__flags); | |
915 | __os.fill(__fill); | |
916 | return __os; | |
917 | } | |
918 | ||
919 | template<typename _IntType, typename _CharT, typename _Traits> | |
920 | std::basic_istream<_CharT, _Traits>& | |
921 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
922 | uniform_int_distribution<_IntType>& __x) | |
923 | { | |
160e95dc JW |
924 | using param_type |
925 | = typename uniform_int_distribution<_IntType>::param_type; | |
926 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
927 | |
928 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
929 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
930 | ||
931 | _IntType __a, __b; | |
160e95dc JW |
932 | if (__is >> __a >> __b) |
933 | __x.param(param_type(__a, __b)); | |
8e79468d BK |
934 | |
935 | __is.flags(__flags); | |
936 | return __is; | |
937 | } | |
938 | ||
939 | ||
7b93bdde UD |
940 | template<typename _RealType> |
941 | template<typename _ForwardIterator, | |
942 | typename _UniformRandomNumberGenerator> | |
943 | void | |
944 | uniform_real_distribution<_RealType>:: | |
945 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
946 | _UniformRandomNumberGenerator& __urng, | |
947 | const param_type& __p) | |
948 | { | |
949 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
950 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
951 | __aurng(__urng); | |
952 | auto __range = __p.b() - __p.a(); | |
953 | while (__f != __t) | |
954 | *__f++ = __aurng() * __range + __p.a(); | |
955 | } | |
956 | ||
8e79468d BK |
957 | template<typename _RealType, typename _CharT, typename _Traits> |
958 | std::basic_ostream<_CharT, _Traits>& | |
959 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
960 | const uniform_real_distribution<_RealType>& __x) | |
961 | { | |
160e95dc | 962 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
963 | |
964 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
965 | const _CharT __fill = __os.fill(); | |
966 | const std::streamsize __precision = __os.precision(); | |
967 | const _CharT __space = __os.widen(' '); | |
968 | __os.flags(__ios_base::scientific | __ios_base::left); | |
969 | __os.fill(__space); | |
7703dc47 | 970 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d BK |
971 | |
972 | __os << __x.a() << __space << __x.b(); | |
973 | ||
974 | __os.flags(__flags); | |
975 | __os.fill(__fill); | |
976 | __os.precision(__precision); | |
977 | return __os; | |
978 | } | |
979 | ||
980 | template<typename _RealType, typename _CharT, typename _Traits> | |
981 | std::basic_istream<_CharT, _Traits>& | |
982 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
983 | uniform_real_distribution<_RealType>& __x) | |
984 | { | |
160e95dc JW |
985 | using param_type |
986 | = typename uniform_real_distribution<_RealType>::param_type; | |
987 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
988 | |
989 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
990 | __is.flags(__ios_base::skipws); | |
991 | ||
992 | _RealType __a, __b; | |
160e95dc JW |
993 | if (__is >> __a >> __b) |
994 | __x.param(param_type(__a, __b)); | |
8e79468d BK |
995 | |
996 | __is.flags(__flags); | |
997 | return __is; | |
998 | } | |
999 | ||
1000 | ||
7b93bdde UD |
1001 | template<typename _ForwardIterator, |
1002 | typename _UniformRandomNumberGenerator> | |
1003 | void | |
1004 | std::bernoulli_distribution:: | |
1005 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1006 | _UniformRandomNumberGenerator& __urng, | |
1007 | const param_type& __p) | |
1008 | { | |
1009 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1010 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
1011 | __aurng(__urng); | |
1012 | auto __limit = __p.p() * (__aurng.max() - __aurng.min()); | |
1013 | ||
1014 | while (__f != __t) | |
1015 | *__f++ = (__aurng() - __aurng.min()) < __limit; | |
1016 | } | |
1017 | ||
8e79468d BK |
1018 | template<typename _CharT, typename _Traits> |
1019 | std::basic_ostream<_CharT, _Traits>& | |
1020 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1021 | const bernoulli_distribution& __x) | |
1022 | { | |
160e95dc | 1023 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
1024 | |
1025 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1026 | const _CharT __fill = __os.fill(); | |
1027 | const std::streamsize __precision = __os.precision(); | |
1028 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1029 | __os.fill(__os.widen(' ')); | |
7703dc47 | 1030 | __os.precision(std::numeric_limits<double>::max_digits10); |
8e79468d BK |
1031 | |
1032 | __os << __x.p(); | |
1033 | ||
1034 | __os.flags(__flags); | |
1035 | __os.fill(__fill); | |
1036 | __os.precision(__precision); | |
1037 | return __os; | |
1038 | } | |
1039 | ||
1040 | ||
1041 | template<typename _IntType> | |
1042 | template<typename _UniformRandomNumberGenerator> | |
1043 | typename geometric_distribution<_IntType>::result_type | |
1044 | geometric_distribution<_IntType>:: | |
1045 | operator()(_UniformRandomNumberGenerator& __urng, | |
1046 | const param_type& __param) | |
1047 | { | |
1048 | // About the epsilon thing see this thread: | |
1049 | // http://gcc.gnu.org/ml/gcc-patches/2006-10/msg00971.html | |
1050 | const double __naf = | |
1051 | (1 - std::numeric_limits<double>::epsilon()) / 2; | |
1052 | // The largest _RealType convertible to _IntType. | |
1053 | const double __thr = | |
1054 | std::numeric_limits<_IntType>::max() + __naf; | |
9b88236b | 1055 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> |
8e79468d BK |
1056 | __aurng(__urng); |
1057 | ||
1058 | double __cand; | |
1059 | do | |
c2d9083d | 1060 | __cand = std::floor(std::log(1.0 - __aurng()) / __param._M_log_1_p); |
8e79468d BK |
1061 | while (__cand >= __thr); |
1062 | ||
1063 | return result_type(__cand + __naf); | |
1064 | } | |
1065 | ||
7b93bdde UD |
1066 | template<typename _IntType> |
1067 | template<typename _ForwardIterator, | |
1068 | typename _UniformRandomNumberGenerator> | |
1069 | void | |
1070 | geometric_distribution<_IntType>:: | |
1071 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1072 | _UniformRandomNumberGenerator& __urng, | |
1073 | const param_type& __param) | |
1074 | { | |
1075 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1076 | // About the epsilon thing see this thread: | |
1077 | // http://gcc.gnu.org/ml/gcc-patches/2006-10/msg00971.html | |
1078 | const double __naf = | |
1079 | (1 - std::numeric_limits<double>::epsilon()) / 2; | |
1080 | // The largest _RealType convertible to _IntType. | |
1081 | const double __thr = | |
1082 | std::numeric_limits<_IntType>::max() + __naf; | |
1083 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
1084 | __aurng(__urng); | |
1085 | ||
1086 | while (__f != __t) | |
1087 | { | |
1088 | double __cand; | |
1089 | do | |
c2d9083d HY |
1090 | __cand = std::floor(std::log(1.0 - __aurng()) |
1091 | / __param._M_log_1_p); | |
7b93bdde UD |
1092 | while (__cand >= __thr); |
1093 | ||
1094 | *__f++ = __cand + __naf; | |
1095 | } | |
1096 | } | |
1097 | ||
8e79468d BK |
1098 | template<typename _IntType, |
1099 | typename _CharT, typename _Traits> | |
1100 | std::basic_ostream<_CharT, _Traits>& | |
1101 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1102 | const geometric_distribution<_IntType>& __x) | |
1103 | { | |
160e95dc | 1104 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
1105 | |
1106 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1107 | const _CharT __fill = __os.fill(); | |
1108 | const std::streamsize __precision = __os.precision(); | |
1109 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1110 | __os.fill(__os.widen(' ')); | |
7703dc47 | 1111 | __os.precision(std::numeric_limits<double>::max_digits10); |
8e79468d BK |
1112 | |
1113 | __os << __x.p(); | |
1114 | ||
1115 | __os.flags(__flags); | |
1116 | __os.fill(__fill); | |
1117 | __os.precision(__precision); | |
1118 | return __os; | |
1119 | } | |
1120 | ||
1121 | template<typename _IntType, | |
1122 | typename _CharT, typename _Traits> | |
1123 | std::basic_istream<_CharT, _Traits>& | |
1124 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
1125 | geometric_distribution<_IntType>& __x) | |
1126 | { | |
160e95dc JW |
1127 | using param_type = typename geometric_distribution<_IntType>::param_type; |
1128 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
1129 | |
1130 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
1131 | __is.flags(__ios_base::skipws); | |
1132 | ||
1133 | double __p; | |
160e95dc JW |
1134 | if (__is >> __p) |
1135 | __x.param(param_type(__p)); | |
8e79468d BK |
1136 | |
1137 | __is.flags(__flags); | |
1138 | return __is; | |
1139 | } | |
1140 | ||
ff2e697a | 1141 | // This is Leger's algorithm, also in Devroye, Ch. X, Example 1.5. |
f9b09dec PC |
1142 | template<typename _IntType> |
1143 | template<typename _UniformRandomNumberGenerator> | |
1144 | typename negative_binomial_distribution<_IntType>::result_type | |
1145 | negative_binomial_distribution<_IntType>:: | |
1146 | operator()(_UniformRandomNumberGenerator& __urng) | |
1147 | { | |
1148 | const double __y = _M_gd(__urng); | |
1149 | ||
1150 | // XXX Is the constructor too slow? | |
ff2e697a | 1151 | std::poisson_distribution<result_type> __poisson(__y); |
f9b09dec PC |
1152 | return __poisson(__urng); |
1153 | } | |
1154 | ||
8e79468d BK |
1155 | template<typename _IntType> |
1156 | template<typename _UniformRandomNumberGenerator> | |
1157 | typename negative_binomial_distribution<_IntType>::result_type | |
1158 | negative_binomial_distribution<_IntType>:: | |
1159 | operator()(_UniformRandomNumberGenerator& __urng, | |
1160 | const param_type& __p) | |
1161 | { | |
e5fbc9fc | 1162 | typedef typename std::gamma_distribution<double>::param_type |
f9b09dec PC |
1163 | param_type; |
1164 | ||
ff2e697a PC |
1165 | const double __y = |
1166 | _M_gd(__urng, param_type(__p.k(), (1.0 - __p.p()) / __p.p())); | |
8e79468d | 1167 | |
ff2e697a | 1168 | std::poisson_distribution<result_type> __poisson(__y); |
b01630bb | 1169 | return __poisson(__urng); |
8e79468d BK |
1170 | } |
1171 | ||
7b93bdde UD |
1172 | template<typename _IntType> |
1173 | template<typename _ForwardIterator, | |
1174 | typename _UniformRandomNumberGenerator> | |
1175 | void | |
1176 | negative_binomial_distribution<_IntType>:: | |
1177 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1178 | _UniformRandomNumberGenerator& __urng) | |
1179 | { | |
1180 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1181 | while (__f != __t) | |
1182 | { | |
1183 | const double __y = _M_gd(__urng); | |
1184 | ||
1185 | // XXX Is the constructor too slow? | |
1186 | std::poisson_distribution<result_type> __poisson(__y); | |
1187 | *__f++ = __poisson(__urng); | |
1188 | } | |
1189 | } | |
1190 | ||
1191 | template<typename _IntType> | |
1192 | template<typename _ForwardIterator, | |
1193 | typename _UniformRandomNumberGenerator> | |
1194 | void | |
1195 | negative_binomial_distribution<_IntType>:: | |
1196 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1197 | _UniformRandomNumberGenerator& __urng, | |
1198 | const param_type& __p) | |
1199 | { | |
1200 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1201 | typename std::gamma_distribution<result_type>::param_type | |
1202 | __p2(__p.k(), (1.0 - __p.p()) / __p.p()); | |
1203 | ||
1204 | while (__f != __t) | |
1205 | { | |
1206 | const double __y = _M_gd(__urng, __p2); | |
1207 | ||
1208 | std::poisson_distribution<result_type> __poisson(__y); | |
1209 | *__f++ = __poisson(__urng); | |
1210 | } | |
1211 | } | |
1212 | ||
8e79468d BK |
1213 | template<typename _IntType, typename _CharT, typename _Traits> |
1214 | std::basic_ostream<_CharT, _Traits>& | |
1215 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1216 | const negative_binomial_distribution<_IntType>& __x) | |
1217 | { | |
160e95dc | 1218 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
1219 | |
1220 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1221 | const _CharT __fill = __os.fill(); | |
1222 | const std::streamsize __precision = __os.precision(); | |
1223 | const _CharT __space = __os.widen(' '); | |
1224 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1225 | __os.fill(__os.widen(' ')); | |
7703dc47 | 1226 | __os.precision(std::numeric_limits<double>::max_digits10); |
8e79468d | 1227 | |
f9b09dec PC |
1228 | __os << __x.k() << __space << __x.p() |
1229 | << __space << __x._M_gd; | |
8e79468d BK |
1230 | |
1231 | __os.flags(__flags); | |
1232 | __os.fill(__fill); | |
1233 | __os.precision(__precision); | |
1234 | return __os; | |
1235 | } | |
1236 | ||
1237 | template<typename _IntType, typename _CharT, typename _Traits> | |
1238 | std::basic_istream<_CharT, _Traits>& | |
1239 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
1240 | negative_binomial_distribution<_IntType>& __x) | |
1241 | { | |
160e95dc JW |
1242 | using param_type |
1243 | = typename negative_binomial_distribution<_IntType>::param_type; | |
1244 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
1245 | |
1246 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
1247 | __is.flags(__ios_base::skipws); | |
1248 | ||
1249 | _IntType __k; | |
1250 | double __p; | |
160e95dc JW |
1251 | if (__is >> __k >> __p >> __x._M_gd) |
1252 | __x.param(param_type(__k, __p)); | |
8e79468d BK |
1253 | |
1254 | __is.flags(__flags); | |
1255 | return __is; | |
1256 | } | |
1257 | ||
1258 | ||
1259 | template<typename _IntType> | |
1260 | void | |
1261 | poisson_distribution<_IntType>::param_type:: | |
1262 | _M_initialize() | |
1263 | { | |
1264 | #if _GLIBCXX_USE_C99_MATH_TR1 | |
1265 | if (_M_mean >= 12) | |
1266 | { | |
1267 | const double __m = std::floor(_M_mean); | |
1268 | _M_lm_thr = std::log(_M_mean); | |
1269 | _M_lfm = std::lgamma(__m + 1); | |
1270 | _M_sm = std::sqrt(__m); | |
1271 | ||
1272 | const double __pi_4 = 0.7853981633974483096156608458198757L; | |
1273 | const double __dx = std::sqrt(2 * __m * std::log(32 * __m | |
1274 | / __pi_4)); | |
3af7efb7 | 1275 | _M_d = std::round(std::max<double>(6.0, std::min(__m, __dx))); |
8e79468d BK |
1276 | const double __cx = 2 * __m + _M_d; |
1277 | _M_scx = std::sqrt(__cx / 2); | |
1278 | _M_1cx = 1 / __cx; | |
1279 | ||
1280 | _M_c2b = std::sqrt(__pi_4 * __cx) * std::exp(_M_1cx); | |
1281 | _M_cb = 2 * __cx * std::exp(-_M_d * _M_1cx * (1 + _M_d / 2)) | |
1282 | / _M_d; | |
1283 | } | |
1284 | else | |
1285 | #endif | |
1286 | _M_lm_thr = std::exp(-_M_mean); | |
1287 | } | |
1288 | ||
1289 | /** | |
1290 | * A rejection algorithm when mean >= 12 and a simple method based | |
1291 | * upon the multiplication of uniform random variates otherwise. | |
1292 | * NB: The former is available only if _GLIBCXX_USE_C99_MATH_TR1 | |
1293 | * is defined. | |
1294 | * | |
1295 | * Reference: | |
2a60a9f6 | 1296 | * Devroye, L. Non-Uniform Random Variates Generation. Springer-Verlag, |
8e79468d BK |
1297 | * New York, 1986, Ch. X, Sects. 3.3 & 3.4 (+ Errata!). |
1298 | */ | |
1299 | template<typename _IntType> | |
1300 | template<typename _UniformRandomNumberGenerator> | |
1301 | typename poisson_distribution<_IntType>::result_type | |
1302 | poisson_distribution<_IntType>:: | |
1303 | operator()(_UniformRandomNumberGenerator& __urng, | |
1304 | const param_type& __param) | |
1305 | { | |
1306 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
1307 | __aurng(__urng); | |
1308 | #if _GLIBCXX_USE_C99_MATH_TR1 | |
1309 | if (__param.mean() >= 12) | |
1310 | { | |
1311 | double __x; | |
1312 | ||
1313 | // See comments above... | |
1314 | const double __naf = | |
1315 | (1 - std::numeric_limits<double>::epsilon()) / 2; | |
1316 | const double __thr = | |
1317 | std::numeric_limits<_IntType>::max() + __naf; | |
1318 | ||
1319 | const double __m = std::floor(__param.mean()); | |
1320 | // sqrt(pi / 2) | |
1321 | const double __spi_2 = 1.2533141373155002512078826424055226L; | |
1322 | const double __c1 = __param._M_sm * __spi_2; | |
1323 | const double __c2 = __param._M_c2b + __c1; | |
1324 | const double __c3 = __c2 + 1; | |
1325 | const double __c4 = __c3 + 1; | |
73986c31 MP |
1326 | // 1 / 78 |
1327 | const double __178 = 0.0128205128205128205128205128205128L; | |
8e79468d BK |
1328 | // e^(1 / 78) |
1329 | const double __e178 = 1.0129030479320018583185514777512983L; | |
1330 | const double __c5 = __c4 + __e178; | |
1331 | const double __c = __param._M_cb + __c5; | |
1332 | const double __2cx = 2 * (2 * __m + __param._M_d); | |
1333 | ||
1334 | bool __reject = true; | |
1335 | do | |
1336 | { | |
1337 | const double __u = __c * __aurng(); | |
c2d9083d | 1338 | const double __e = -std::log(1.0 - __aurng()); |
8e79468d BK |
1339 | |
1340 | double __w = 0.0; | |
1341 | ||
1342 | if (__u <= __c1) | |
1343 | { | |
1344 | const double __n = _M_nd(__urng); | |
1345 | const double __y = -std::abs(__n) * __param._M_sm - 1; | |
1346 | __x = std::floor(__y); | |
1347 | __w = -__n * __n / 2; | |
1348 | if (__x < -__m) | |
1349 | continue; | |
1350 | } | |
1351 | else if (__u <= __c2) | |
1352 | { | |
1353 | const double __n = _M_nd(__urng); | |
1354 | const double __y = 1 + std::abs(__n) * __param._M_scx; | |
1355 | __x = std::ceil(__y); | |
1356 | __w = __y * (2 - __y) * __param._M_1cx; | |
1357 | if (__x > __param._M_d) | |
1358 | continue; | |
1359 | } | |
1360 | else if (__u <= __c3) | |
1361 | // NB: This case not in the book, nor in the Errata, | |
1362 | // but should be ok... | |
1363 | __x = -1; | |
1364 | else if (__u <= __c4) | |
1365 | __x = 0; | |
1366 | else if (__u <= __c5) | |
73986c31 MP |
1367 | { |
1368 | __x = 1; | |
1369 | // Only in the Errata, see libstdc++/83237. | |
1370 | __w = __178; | |
1371 | } | |
8e79468d BK |
1372 | else |
1373 | { | |
c2d9083d | 1374 | const double __v = -std::log(1.0 - __aurng()); |
8e79468d BK |
1375 | const double __y = __param._M_d |
1376 | + __v * __2cx / __param._M_d; | |
1377 | __x = std::ceil(__y); | |
1378 | __w = -__param._M_d * __param._M_1cx * (1 + __y / 2); | |
1379 | } | |
1380 | ||
1381 | __reject = (__w - __e - __x * __param._M_lm_thr | |
1382 | > __param._M_lfm - std::lgamma(__x + __m + 1)); | |
1383 | ||
1384 | __reject |= __x + __m >= __thr; | |
1385 | ||
1386 | } while (__reject); | |
1387 | ||
1388 | return result_type(__x + __m + __naf); | |
1389 | } | |
1390 | else | |
1391 | #endif | |
1392 | { | |
1393 | _IntType __x = 0; | |
1394 | double __prod = 1.0; | |
1395 | ||
1396 | do | |
1397 | { | |
1398 | __prod *= __aurng(); | |
1399 | __x += 1; | |
1400 | } | |
1401 | while (__prod > __param._M_lm_thr); | |
1402 | ||
1403 | return __x - 1; | |
1404 | } | |
1405 | } | |
1406 | ||
7b93bdde UD |
1407 | template<typename _IntType> |
1408 | template<typename _ForwardIterator, | |
1409 | typename _UniformRandomNumberGenerator> | |
1410 | void | |
1411 | poisson_distribution<_IntType>:: | |
1412 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1413 | _UniformRandomNumberGenerator& __urng, | |
1414 | const param_type& __param) | |
1415 | { | |
1416 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1417 | // We could duplicate everything from operator()... | |
1418 | while (__f != __t) | |
1419 | *__f++ = this->operator()(__urng, __param); | |
1420 | } | |
1421 | ||
8e79468d BK |
1422 | template<typename _IntType, |
1423 | typename _CharT, typename _Traits> | |
1424 | std::basic_ostream<_CharT, _Traits>& | |
1425 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1426 | const poisson_distribution<_IntType>& __x) | |
1427 | { | |
160e95dc | 1428 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
1429 | |
1430 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1431 | const _CharT __fill = __os.fill(); | |
1432 | const std::streamsize __precision = __os.precision(); | |
1433 | const _CharT __space = __os.widen(' '); | |
1434 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1435 | __os.fill(__space); | |
7703dc47 | 1436 | __os.precision(std::numeric_limits<double>::max_digits10); |
8e79468d BK |
1437 | |
1438 | __os << __x.mean() << __space << __x._M_nd; | |
1439 | ||
1440 | __os.flags(__flags); | |
1441 | __os.fill(__fill); | |
1442 | __os.precision(__precision); | |
1443 | return __os; | |
1444 | } | |
1445 | ||
1446 | template<typename _IntType, | |
1447 | typename _CharT, typename _Traits> | |
1448 | std::basic_istream<_CharT, _Traits>& | |
1449 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
1450 | poisson_distribution<_IntType>& __x) | |
1451 | { | |
160e95dc JW |
1452 | using param_type = typename poisson_distribution<_IntType>::param_type; |
1453 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
1454 | |
1455 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
1456 | __is.flags(__ios_base::skipws); | |
1457 | ||
1458 | double __mean; | |
160e95dc JW |
1459 | if (__is >> __mean >> __x._M_nd) |
1460 | __x.param(param_type(__mean)); | |
8e79468d BK |
1461 | |
1462 | __is.flags(__flags); | |
1463 | return __is; | |
1464 | } | |
1465 | ||
1466 | ||
1467 | template<typename _IntType> | |
1468 | void | |
1469 | binomial_distribution<_IntType>::param_type:: | |
1470 | _M_initialize() | |
1471 | { | |
1472 | const double __p12 = _M_p <= 0.5 ? _M_p : 1.0 - _M_p; | |
1473 | ||
1474 | _M_easy = true; | |
1475 | ||
1476 | #if _GLIBCXX_USE_C99_MATH_TR1 | |
1477 | if (_M_t * __p12 >= 8) | |
1478 | { | |
1479 | _M_easy = false; | |
1480 | const double __np = std::floor(_M_t * __p12); | |
1481 | const double __pa = __np / _M_t; | |
1482 | const double __1p = 1 - __pa; | |
1483 | ||
1484 | const double __pi_4 = 0.7853981633974483096156608458198757L; | |
1485 | const double __d1x = | |
1486 | std::sqrt(__np * __1p * std::log(32 * __np | |
1487 | / (81 * __pi_4 * __1p))); | |
3af7efb7 | 1488 | _M_d1 = std::round(std::max<double>(1.0, __d1x)); |
8e79468d BK |
1489 | const double __d2x = |
1490 | std::sqrt(__np * __1p * std::log(32 * _M_t * __1p | |
1491 | / (__pi_4 * __pa))); | |
3af7efb7 | 1492 | _M_d2 = std::round(std::max<double>(1.0, __d2x)); |
8e79468d BK |
1493 | |
1494 | // sqrt(pi / 2) | |
1495 | const double __spi_2 = 1.2533141373155002512078826424055226L; | |
1496 | _M_s1 = std::sqrt(__np * __1p) * (1 + _M_d1 / (4 * __np)); | |
1497 | _M_s2 = std::sqrt(__np * __1p) * (1 + _M_d2 / (4 * _M_t * __1p)); | |
1498 | _M_c = 2 * _M_d1 / __np; | |
1499 | _M_a1 = std::exp(_M_c) * _M_s1 * __spi_2; | |
1500 | const double __a12 = _M_a1 + _M_s2 * __spi_2; | |
1501 | const double __s1s = _M_s1 * _M_s1; | |
1502 | _M_a123 = __a12 + (std::exp(_M_d1 / (_M_t * __1p)) | |
1503 | * 2 * __s1s / _M_d1 | |
1504 | * std::exp(-_M_d1 * _M_d1 / (2 * __s1s))); | |
1505 | const double __s2s = _M_s2 * _M_s2; | |
1506 | _M_s = (_M_a123 + 2 * __s2s / _M_d2 | |
1507 | * std::exp(-_M_d2 * _M_d2 / (2 * __s2s))); | |
1508 | _M_lf = (std::lgamma(__np + 1) | |
1509 | + std::lgamma(_M_t - __np + 1)); | |
1510 | _M_lp1p = std::log(__pa / __1p); | |
1511 | ||
1512 | _M_q = -std::log(1 - (__p12 - __pa) / __1p); | |
1513 | } | |
1514 | else | |
1515 | #endif | |
1516 | _M_q = -std::log(1 - __p12); | |
1517 | } | |
1518 | ||
1519 | template<typename _IntType> | |
1520 | template<typename _UniformRandomNumberGenerator> | |
1521 | typename binomial_distribution<_IntType>::result_type | |
1522 | binomial_distribution<_IntType>:: | |
07bba3b1 PC |
1523 | _M_waiting(_UniformRandomNumberGenerator& __urng, |
1524 | _IntType __t, double __q) | |
8e79468d BK |
1525 | { |
1526 | _IntType __x = 0; | |
1527 | double __sum = 0.0; | |
1528 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
1529 | __aurng(__urng); | |
1530 | ||
1531 | do | |
1532 | { | |
85018f40 | 1533 | if (__t == __x) |
9ea146e6 MLI |
1534 | return __x; |
1535 | const double __e = -std::log(1.0 - __aurng()); | |
8e79468d BK |
1536 | __sum += __e / (__t - __x); |
1537 | __x += 1; | |
1538 | } | |
07bba3b1 | 1539 | while (__sum <= __q); |
8e79468d BK |
1540 | |
1541 | return __x - 1; | |
1542 | } | |
1543 | ||
1544 | /** | |
1545 | * A rejection algorithm when t * p >= 8 and a simple waiting time | |
1546 | * method - the second in the referenced book - otherwise. | |
1547 | * NB: The former is available only if _GLIBCXX_USE_C99_MATH_TR1 | |
1548 | * is defined. | |
1549 | * | |
1550 | * Reference: | |
2a60a9f6 | 1551 | * Devroye, L. Non-Uniform Random Variates Generation. Springer-Verlag, |
8e79468d BK |
1552 | * New York, 1986, Ch. X, Sect. 4 (+ Errata!). |
1553 | */ | |
1554 | template<typename _IntType> | |
1555 | template<typename _UniformRandomNumberGenerator> | |
1556 | typename binomial_distribution<_IntType>::result_type | |
1557 | binomial_distribution<_IntType>:: | |
1558 | operator()(_UniformRandomNumberGenerator& __urng, | |
1559 | const param_type& __param) | |
1560 | { | |
1561 | result_type __ret; | |
1562 | const _IntType __t = __param.t(); | |
d8d4db33 | 1563 | const double __p = __param.p(); |
8e79468d BK |
1564 | const double __p12 = __p <= 0.5 ? __p : 1.0 - __p; |
1565 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
1566 | __aurng(__urng); | |
1567 | ||
1568 | #if _GLIBCXX_USE_C99_MATH_TR1 | |
1569 | if (!__param._M_easy) | |
1570 | { | |
1571 | double __x; | |
1572 | ||
1573 | // See comments above... | |
1574 | const double __naf = | |
1575 | (1 - std::numeric_limits<double>::epsilon()) / 2; | |
1576 | const double __thr = | |
1577 | std::numeric_limits<_IntType>::max() + __naf; | |
1578 | ||
1579 | const double __np = std::floor(__t * __p12); | |
1580 | ||
1581 | // sqrt(pi / 2) | |
1582 | const double __spi_2 = 1.2533141373155002512078826424055226L; | |
1583 | const double __a1 = __param._M_a1; | |
1584 | const double __a12 = __a1 + __param._M_s2 * __spi_2; | |
1585 | const double __a123 = __param._M_a123; | |
1586 | const double __s1s = __param._M_s1 * __param._M_s1; | |
1587 | const double __s2s = __param._M_s2 * __param._M_s2; | |
1588 | ||
1589 | bool __reject; | |
1590 | do | |
1591 | { | |
1592 | const double __u = __param._M_s * __aurng(); | |
1593 | ||
1594 | double __v; | |
1595 | ||
1596 | if (__u <= __a1) | |
1597 | { | |
1598 | const double __n = _M_nd(__urng); | |
1599 | const double __y = __param._M_s1 * std::abs(__n); | |
1600 | __reject = __y >= __param._M_d1; | |
1601 | if (!__reject) | |
1602 | { | |
c2d9083d | 1603 | const double __e = -std::log(1.0 - __aurng()); |
8e79468d BK |
1604 | __x = std::floor(__y); |
1605 | __v = -__e - __n * __n / 2 + __param._M_c; | |
1606 | } | |
1607 | } | |
1608 | else if (__u <= __a12) | |
1609 | { | |
1610 | const double __n = _M_nd(__urng); | |
1611 | const double __y = __param._M_s2 * std::abs(__n); | |
1612 | __reject = __y >= __param._M_d2; | |
1613 | if (!__reject) | |
1614 | { | |
c2d9083d | 1615 | const double __e = -std::log(1.0 - __aurng()); |
8e79468d BK |
1616 | __x = std::floor(-__y); |
1617 | __v = -__e - __n * __n / 2; | |
1618 | } | |
1619 | } | |
1620 | else if (__u <= __a123) | |
1621 | { | |
c2d9083d HY |
1622 | const double __e1 = -std::log(1.0 - __aurng()); |
1623 | const double __e2 = -std::log(1.0 - __aurng()); | |
8e79468d BK |
1624 | |
1625 | const double __y = __param._M_d1 | |
1626 | + 2 * __s1s * __e1 / __param._M_d1; | |
1627 | __x = std::floor(__y); | |
1628 | __v = (-__e2 + __param._M_d1 * (1 / (__t - __np) | |
1629 | -__y / (2 * __s1s))); | |
1630 | __reject = false; | |
1631 | } | |
1632 | else | |
1633 | { | |
c2d9083d HY |
1634 | const double __e1 = -std::log(1.0 - __aurng()); |
1635 | const double __e2 = -std::log(1.0 - __aurng()); | |
8e79468d BK |
1636 | |
1637 | const double __y = __param._M_d2 | |
1638 | + 2 * __s2s * __e1 / __param._M_d2; | |
1639 | __x = std::floor(-__y); | |
1640 | __v = -__e2 - __param._M_d2 * __y / (2 * __s2s); | |
1641 | __reject = false; | |
1642 | } | |
1643 | ||
1644 | __reject = __reject || __x < -__np || __x > __t - __np; | |
1645 | if (!__reject) | |
1646 | { | |
1647 | const double __lfx = | |
1648 | std::lgamma(__np + __x + 1) | |
1649 | + std::lgamma(__t - (__np + __x) + 1); | |
1650 | __reject = __v > __param._M_lf - __lfx | |
1651 | + __x * __param._M_lp1p; | |
1652 | } | |
1653 | ||
1654 | __reject |= __x + __np >= __thr; | |
1655 | } | |
1656 | while (__reject); | |
1657 | ||
1658 | __x += __np + __naf; | |
1659 | ||
07bba3b1 PC |
1660 | const _IntType __z = _M_waiting(__urng, __t - _IntType(__x), |
1661 | __param._M_q); | |
8e79468d BK |
1662 | __ret = _IntType(__x) + __z; |
1663 | } | |
1664 | else | |
1665 | #endif | |
07bba3b1 | 1666 | __ret = _M_waiting(__urng, __t, __param._M_q); |
8e79468d BK |
1667 | |
1668 | if (__p12 != __p) | |
1669 | __ret = __t - __ret; | |
1670 | return __ret; | |
1671 | } | |
1672 | ||
7b93bdde UD |
1673 | template<typename _IntType> |
1674 | template<typename _ForwardIterator, | |
1675 | typename _UniformRandomNumberGenerator> | |
1676 | void | |
1677 | binomial_distribution<_IntType>:: | |
1678 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1679 | _UniformRandomNumberGenerator& __urng, | |
1680 | const param_type& __param) | |
1681 | { | |
1682 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1683 | // We could duplicate everything from operator()... | |
1684 | while (__f != __t) | |
1685 | *__f++ = this->operator()(__urng, __param); | |
1686 | } | |
1687 | ||
8e79468d BK |
1688 | template<typename _IntType, |
1689 | typename _CharT, typename _Traits> | |
1690 | std::basic_ostream<_CharT, _Traits>& | |
1691 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1692 | const binomial_distribution<_IntType>& __x) | |
1693 | { | |
160e95dc | 1694 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
1695 | |
1696 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1697 | const _CharT __fill = __os.fill(); | |
1698 | const std::streamsize __precision = __os.precision(); | |
1699 | const _CharT __space = __os.widen(' '); | |
1700 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1701 | __os.fill(__space); | |
7703dc47 | 1702 | __os.precision(std::numeric_limits<double>::max_digits10); |
8e79468d BK |
1703 | |
1704 | __os << __x.t() << __space << __x.p() | |
1705 | << __space << __x._M_nd; | |
1706 | ||
1707 | __os.flags(__flags); | |
1708 | __os.fill(__fill); | |
1709 | __os.precision(__precision); | |
1710 | return __os; | |
1711 | } | |
1712 | ||
1713 | template<typename _IntType, | |
1714 | typename _CharT, typename _Traits> | |
1715 | std::basic_istream<_CharT, _Traits>& | |
1716 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
1717 | binomial_distribution<_IntType>& __x) | |
1718 | { | |
160e95dc JW |
1719 | using param_type = typename binomial_distribution<_IntType>::param_type; |
1720 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
1721 | |
1722 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
1723 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
1724 | ||
1725 | _IntType __t; | |
1726 | double __p; | |
160e95dc JW |
1727 | if (__is >> __t >> __p >> __x._M_nd) |
1728 | __x.param(param_type(__t, __p)); | |
8e79468d BK |
1729 | |
1730 | __is.flags(__flags); | |
1731 | return __is; | |
1732 | } | |
1733 | ||
1734 | ||
7b93bdde UD |
1735 | template<typename _RealType> |
1736 | template<typename _ForwardIterator, | |
1737 | typename _UniformRandomNumberGenerator> | |
1738 | void | |
1739 | std::exponential_distribution<_RealType>:: | |
1740 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1741 | _UniformRandomNumberGenerator& __urng, | |
1742 | const param_type& __p) | |
1743 | { | |
1744 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1745 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
1746 | __aurng(__urng); | |
1747 | while (__f != __t) | |
c2d9083d | 1748 | *__f++ = -std::log(result_type(1) - __aurng()) / __p.lambda(); |
7b93bdde UD |
1749 | } |
1750 | ||
8e79468d BK |
1751 | template<typename _RealType, typename _CharT, typename _Traits> |
1752 | std::basic_ostream<_CharT, _Traits>& | |
1753 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1754 | const exponential_distribution<_RealType>& __x) | |
1755 | { | |
160e95dc | 1756 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
1757 | |
1758 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1759 | const _CharT __fill = __os.fill(); | |
1760 | const std::streamsize __precision = __os.precision(); | |
1761 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1762 | __os.fill(__os.widen(' ')); | |
7703dc47 | 1763 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d BK |
1764 | |
1765 | __os << __x.lambda(); | |
1766 | ||
1767 | __os.flags(__flags); | |
1768 | __os.fill(__fill); | |
1769 | __os.precision(__precision); | |
1770 | return __os; | |
1771 | } | |
1772 | ||
1773 | template<typename _RealType, typename _CharT, typename _Traits> | |
1774 | std::basic_istream<_CharT, _Traits>& | |
1775 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
1776 | exponential_distribution<_RealType>& __x) | |
1777 | { | |
160e95dc JW |
1778 | using param_type |
1779 | = typename exponential_distribution<_RealType>::param_type; | |
1780 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
1781 | |
1782 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
1783 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
1784 | ||
1785 | _RealType __lambda; | |
160e95dc JW |
1786 | if (__is >> __lambda) |
1787 | __x.param(param_type(__lambda)); | |
8e79468d BK |
1788 | |
1789 | __is.flags(__flags); | |
1790 | return __is; | |
1791 | } | |
1792 | ||
1793 | ||
8e79468d BK |
1794 | /** |
1795 | * Polar method due to Marsaglia. | |
1796 | * | |
2a60a9f6 | 1797 | * Devroye, L. Non-Uniform Random Variates Generation. Springer-Verlag, |
8e79468d BK |
1798 | * New York, 1986, Ch. V, Sect. 4.4. |
1799 | */ | |
1800 | template<typename _RealType> | |
1801 | template<typename _UniformRandomNumberGenerator> | |
1802 | typename normal_distribution<_RealType>::result_type | |
1803 | normal_distribution<_RealType>:: | |
1804 | operator()(_UniformRandomNumberGenerator& __urng, | |
1805 | const param_type& __param) | |
1806 | { | |
1807 | result_type __ret; | |
1808 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
1809 | __aurng(__urng); | |
1810 | ||
1811 | if (_M_saved_available) | |
1812 | { | |
1813 | _M_saved_available = false; | |
1814 | __ret = _M_saved; | |
1815 | } | |
1816 | else | |
1817 | { | |
1818 | result_type __x, __y, __r2; | |
1819 | do | |
1820 | { | |
1821 | __x = result_type(2.0) * __aurng() - 1.0; | |
1822 | __y = result_type(2.0) * __aurng() - 1.0; | |
1823 | __r2 = __x * __x + __y * __y; | |
1824 | } | |
1825 | while (__r2 > 1.0 || __r2 == 0.0); | |
1826 | ||
1827 | const result_type __mult = std::sqrt(-2 * std::log(__r2) / __r2); | |
1828 | _M_saved = __x * __mult; | |
1829 | _M_saved_available = true; | |
1830 | __ret = __y * __mult; | |
1831 | } | |
1832 | ||
1833 | __ret = __ret * __param.stddev() + __param.mean(); | |
1834 | return __ret; | |
1835 | } | |
1836 | ||
7b93bdde UD |
1837 | template<typename _RealType> |
1838 | template<typename _ForwardIterator, | |
1839 | typename _UniformRandomNumberGenerator> | |
1840 | void | |
1841 | normal_distribution<_RealType>:: | |
1842 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1843 | _UniformRandomNumberGenerator& __urng, | |
1844 | const param_type& __param) | |
1845 | { | |
1846 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1847 | ||
1848 | if (__f == __t) | |
1849 | return; | |
1850 | ||
1851 | if (_M_saved_available) | |
1852 | { | |
1853 | _M_saved_available = false; | |
1854 | *__f++ = _M_saved * __param.stddev() + __param.mean(); | |
1855 | ||
1856 | if (__f == __t) | |
1857 | return; | |
1858 | } | |
1859 | ||
1860 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
1861 | __aurng(__urng); | |
1862 | ||
1863 | while (__f + 1 < __t) | |
1864 | { | |
1865 | result_type __x, __y, __r2; | |
1866 | do | |
1867 | { | |
1868 | __x = result_type(2.0) * __aurng() - 1.0; | |
1869 | __y = result_type(2.0) * __aurng() - 1.0; | |
1870 | __r2 = __x * __x + __y * __y; | |
1871 | } | |
1872 | while (__r2 > 1.0 || __r2 == 0.0); | |
1873 | ||
1874 | const result_type __mult = std::sqrt(-2 * std::log(__r2) / __r2); | |
1875 | *__f++ = __y * __mult * __param.stddev() + __param.mean(); | |
1876 | *__f++ = __x * __mult * __param.stddev() + __param.mean(); | |
1877 | } | |
1878 | ||
1879 | if (__f != __t) | |
1880 | { | |
1881 | result_type __x, __y, __r2; | |
1882 | do | |
1883 | { | |
1884 | __x = result_type(2.0) * __aurng() - 1.0; | |
1885 | __y = result_type(2.0) * __aurng() - 1.0; | |
1886 | __r2 = __x * __x + __y * __y; | |
1887 | } | |
1888 | while (__r2 > 1.0 || __r2 == 0.0); | |
1889 | ||
1890 | const result_type __mult = std::sqrt(-2 * std::log(__r2) / __r2); | |
1891 | _M_saved = __x * __mult; | |
1892 | _M_saved_available = true; | |
1893 | *__f = __y * __mult * __param.stddev() + __param.mean(); | |
1894 | } | |
1895 | } | |
1896 | ||
fc05e1ba PC |
1897 | template<typename _RealType> |
1898 | bool | |
1899 | operator==(const std::normal_distribution<_RealType>& __d1, | |
1900 | const std::normal_distribution<_RealType>& __d2) | |
1901 | { | |
1902 | if (__d1._M_param == __d2._M_param | |
1903 | && __d1._M_saved_available == __d2._M_saved_available) | |
1904 | { | |
1905 | if (__d1._M_saved_available | |
1906 | && __d1._M_saved == __d2._M_saved) | |
1907 | return true; | |
1908 | else if(!__d1._M_saved_available) | |
1909 | return true; | |
1910 | else | |
1911 | return false; | |
1912 | } | |
1913 | else | |
1914 | return false; | |
1915 | } | |
1916 | ||
8e79468d BK |
1917 | template<typename _RealType, typename _CharT, typename _Traits> |
1918 | std::basic_ostream<_CharT, _Traits>& | |
1919 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1920 | const normal_distribution<_RealType>& __x) | |
1921 | { | |
160e95dc | 1922 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
1923 | |
1924 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1925 | const _CharT __fill = __os.fill(); | |
1926 | const std::streamsize __precision = __os.precision(); | |
1927 | const _CharT __space = __os.widen(' '); | |
1928 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1929 | __os.fill(__space); | |
7703dc47 | 1930 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d BK |
1931 | |
1932 | __os << __x.mean() << __space << __x.stddev() | |
1933 | << __space << __x._M_saved_available; | |
1934 | if (__x._M_saved_available) | |
1935 | __os << __space << __x._M_saved; | |
1936 | ||
1937 | __os.flags(__flags); | |
1938 | __os.fill(__fill); | |
1939 | __os.precision(__precision); | |
1940 | return __os; | |
1941 | } | |
1942 | ||
1943 | template<typename _RealType, typename _CharT, typename _Traits> | |
1944 | std::basic_istream<_CharT, _Traits>& | |
1945 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
1946 | normal_distribution<_RealType>& __x) | |
1947 | { | |
160e95dc JW |
1948 | using param_type = typename normal_distribution<_RealType>::param_type; |
1949 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
1950 | |
1951 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
1952 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
1953 | ||
1954 | double __mean, __stddev; | |
160e95dc JW |
1955 | bool __saved_avail; |
1956 | if (__is >> __mean >> __stddev >> __saved_avail) | |
1957 | { | |
1958 | if (__saved_avail && (__is >> __x._M_saved)) | |
1959 | { | |
1960 | __x._M_saved_available = __saved_avail; | |
1961 | __x.param(param_type(__mean, __stddev)); | |
1962 | } | |
1963 | } | |
8e79468d BK |
1964 | |
1965 | __is.flags(__flags); | |
1966 | return __is; | |
1967 | } | |
1968 | ||
1969 | ||
7b93bdde UD |
1970 | template<typename _RealType> |
1971 | template<typename _ForwardIterator, | |
1972 | typename _UniformRandomNumberGenerator> | |
1973 | void | |
1974 | lognormal_distribution<_RealType>:: | |
1975 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1976 | _UniformRandomNumberGenerator& __urng, | |
1977 | const param_type& __p) | |
1978 | { | |
1979 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1980 | while (__f != __t) | |
1981 | *__f++ = std::exp(__p.s() * _M_nd(__urng) + __p.m()); | |
1982 | } | |
1983 | ||
8e79468d BK |
1984 | template<typename _RealType, typename _CharT, typename _Traits> |
1985 | std::basic_ostream<_CharT, _Traits>& | |
1986 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1987 | const lognormal_distribution<_RealType>& __x) | |
1988 | { | |
160e95dc | 1989 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
1990 | |
1991 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1992 | const _CharT __fill = __os.fill(); | |
1993 | const std::streamsize __precision = __os.precision(); | |
1994 | const _CharT __space = __os.widen(' '); | |
1995 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1996 | __os.fill(__space); | |
7703dc47 | 1997 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d | 1998 | |
b01630bb PC |
1999 | __os << __x.m() << __space << __x.s() |
2000 | << __space << __x._M_nd; | |
8e79468d BK |
2001 | |
2002 | __os.flags(__flags); | |
2003 | __os.fill(__fill); | |
2004 | __os.precision(__precision); | |
2005 | return __os; | |
2006 | } | |
2007 | ||
2008 | template<typename _RealType, typename _CharT, typename _Traits> | |
2009 | std::basic_istream<_CharT, _Traits>& | |
2010 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2011 | lognormal_distribution<_RealType>& __x) | |
2012 | { | |
160e95dc JW |
2013 | using param_type |
2014 | = typename lognormal_distribution<_RealType>::param_type; | |
2015 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
2016 | |
2017 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2018 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2019 | ||
2020 | _RealType __m, __s; | |
160e95dc JW |
2021 | if (__is >> __m >> __s >> __x._M_nd) |
2022 | __x.param(param_type(__m, __s)); | |
8e79468d BK |
2023 | |
2024 | __is.flags(__flags); | |
2025 | return __is; | |
2026 | } | |
2027 | ||
5bcb3b4d PC |
2028 | template<typename _RealType> |
2029 | template<typename _ForwardIterator, | |
2030 | typename _UniformRandomNumberGenerator> | |
2031 | void | |
2032 | std::chi_squared_distribution<_RealType>:: | |
2033 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2034 | _UniformRandomNumberGenerator& __urng) | |
2035 | { | |
2036 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2037 | while (__f != __t) | |
2038 | *__f++ = 2 * _M_gd(__urng); | |
2039 | } | |
8e79468d | 2040 | |
7b93bdde UD |
2041 | template<typename _RealType> |
2042 | template<typename _ForwardIterator, | |
2043 | typename _UniformRandomNumberGenerator> | |
2044 | void | |
2045 | std::chi_squared_distribution<_RealType>:: | |
2046 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2047 | _UniformRandomNumberGenerator& __urng, | |
5bcb3b4d PC |
2048 | const typename |
2049 | std::gamma_distribution<result_type>::param_type& __p) | |
7b93bdde UD |
2050 | { |
2051 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2052 | while (__f != __t) | |
2053 | *__f++ = 2 * _M_gd(__urng, __p); | |
2054 | } | |
2055 | ||
8e79468d BK |
2056 | template<typename _RealType, typename _CharT, typename _Traits> |
2057 | std::basic_ostream<_CharT, _Traits>& | |
2058 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2059 | const chi_squared_distribution<_RealType>& __x) | |
2060 | { | |
160e95dc | 2061 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
2062 | |
2063 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2064 | const _CharT __fill = __os.fill(); | |
2065 | const std::streamsize __precision = __os.precision(); | |
2066 | const _CharT __space = __os.widen(' '); | |
2067 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2068 | __os.fill(__space); | |
7703dc47 | 2069 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d | 2070 | |
f9b09dec | 2071 | __os << __x.n() << __space << __x._M_gd; |
8e79468d BK |
2072 | |
2073 | __os.flags(__flags); | |
2074 | __os.fill(__fill); | |
2075 | __os.precision(__precision); | |
2076 | return __os; | |
2077 | } | |
2078 | ||
2079 | template<typename _RealType, typename _CharT, typename _Traits> | |
2080 | std::basic_istream<_CharT, _Traits>& | |
2081 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2082 | chi_squared_distribution<_RealType>& __x) | |
2083 | { | |
160e95dc JW |
2084 | using param_type |
2085 | = typename chi_squared_distribution<_RealType>::param_type; | |
2086 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
2087 | |
2088 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2089 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2090 | ||
2091 | _RealType __n; | |
160e95dc JW |
2092 | if (__is >> __n >> __x._M_gd) |
2093 | __x.param(param_type(__n)); | |
8e79468d BK |
2094 | |
2095 | __is.flags(__flags); | |
2096 | return __is; | |
2097 | } | |
2098 | ||
2099 | ||
2100 | template<typename _RealType> | |
2101 | template<typename _UniformRandomNumberGenerator> | |
2102 | typename cauchy_distribution<_RealType>::result_type | |
2103 | cauchy_distribution<_RealType>:: | |
2104 | operator()(_UniformRandomNumberGenerator& __urng, | |
2105 | const param_type& __p) | |
2106 | { | |
2107 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
2108 | __aurng(__urng); | |
2109 | _RealType __u; | |
2110 | do | |
e1a02963 | 2111 | __u = __aurng(); |
8e79468d BK |
2112 | while (__u == 0.5); |
2113 | ||
e1a02963 PC |
2114 | const _RealType __pi = 3.1415926535897932384626433832795029L; |
2115 | return __p.a() + __p.b() * std::tan(__pi * __u); | |
8e79468d BK |
2116 | } |
2117 | ||
7b93bdde UD |
2118 | template<typename _RealType> |
2119 | template<typename _ForwardIterator, | |
2120 | typename _UniformRandomNumberGenerator> | |
2121 | void | |
2122 | cauchy_distribution<_RealType>:: | |
2123 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2124 | _UniformRandomNumberGenerator& __urng, | |
2125 | const param_type& __p) | |
2126 | { | |
2127 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2128 | const _RealType __pi = 3.1415926535897932384626433832795029L; | |
2129 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
2130 | __aurng(__urng); | |
2131 | while (__f != __t) | |
2132 | { | |
2133 | _RealType __u; | |
2134 | do | |
2135 | __u = __aurng(); | |
2136 | while (__u == 0.5); | |
2137 | ||
2138 | *__f++ = __p.a() + __p.b() * std::tan(__pi * __u); | |
2139 | } | |
2140 | } | |
2141 | ||
8e79468d BK |
2142 | template<typename _RealType, typename _CharT, typename _Traits> |
2143 | std::basic_ostream<_CharT, _Traits>& | |
2144 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2145 | const cauchy_distribution<_RealType>& __x) | |
2146 | { | |
160e95dc | 2147 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
2148 | |
2149 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2150 | const _CharT __fill = __os.fill(); | |
2151 | const std::streamsize __precision = __os.precision(); | |
2152 | const _CharT __space = __os.widen(' '); | |
2153 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2154 | __os.fill(__space); | |
7703dc47 | 2155 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d BK |
2156 | |
2157 | __os << __x.a() << __space << __x.b(); | |
2158 | ||
2159 | __os.flags(__flags); | |
2160 | __os.fill(__fill); | |
2161 | __os.precision(__precision); | |
2162 | return __os; | |
2163 | } | |
2164 | ||
2165 | template<typename _RealType, typename _CharT, typename _Traits> | |
2166 | std::basic_istream<_CharT, _Traits>& | |
2167 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2168 | cauchy_distribution<_RealType>& __x) | |
2169 | { | |
160e95dc JW |
2170 | using param_type = typename cauchy_distribution<_RealType>::param_type; |
2171 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
2172 | |
2173 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2174 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2175 | ||
2176 | _RealType __a, __b; | |
160e95dc JW |
2177 | if (__is >> __a >> __b) |
2178 | __x.param(param_type(__a, __b)); | |
8e79468d BK |
2179 | |
2180 | __is.flags(__flags); | |
2181 | return __is; | |
2182 | } | |
2183 | ||
2184 | ||
7b93bdde UD |
2185 | template<typename _RealType> |
2186 | template<typename _ForwardIterator, | |
2187 | typename _UniformRandomNumberGenerator> | |
2188 | void | |
2189 | std::fisher_f_distribution<_RealType>:: | |
2190 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2191 | _UniformRandomNumberGenerator& __urng) | |
2192 | { | |
2193 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2194 | while (__f != __t) | |
2195 | *__f++ = ((_M_gd_x(__urng) * n()) / (_M_gd_y(__urng) * m())); | |
2196 | } | |
2197 | ||
2198 | template<typename _RealType> | |
2199 | template<typename _ForwardIterator, | |
2200 | typename _UniformRandomNumberGenerator> | |
2201 | void | |
2202 | std::fisher_f_distribution<_RealType>:: | |
2203 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2204 | _UniformRandomNumberGenerator& __urng, | |
2205 | const param_type& __p) | |
2206 | { | |
2207 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2208 | typedef typename std::gamma_distribution<result_type>::param_type | |
2209 | param_type; | |
2210 | param_type __p1(__p.m() / 2); | |
2211 | param_type __p2(__p.n() / 2); | |
2212 | while (__f != __t) | |
2213 | *__f++ = ((_M_gd_x(__urng, __p1) * n()) | |
2214 | / (_M_gd_y(__urng, __p2) * m())); | |
2215 | } | |
2216 | ||
8e79468d BK |
2217 | template<typename _RealType, typename _CharT, typename _Traits> |
2218 | std::basic_ostream<_CharT, _Traits>& | |
2219 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2220 | const fisher_f_distribution<_RealType>& __x) | |
2221 | { | |
160e95dc | 2222 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
2223 | |
2224 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2225 | const _CharT __fill = __os.fill(); | |
2226 | const std::streamsize __precision = __os.precision(); | |
2227 | const _CharT __space = __os.widen(' '); | |
2228 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2229 | __os.fill(__space); | |
7703dc47 | 2230 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d | 2231 | |
f9b09dec PC |
2232 | __os << __x.m() << __space << __x.n() |
2233 | << __space << __x._M_gd_x << __space << __x._M_gd_y; | |
8e79468d BK |
2234 | |
2235 | __os.flags(__flags); | |
2236 | __os.fill(__fill); | |
2237 | __os.precision(__precision); | |
2238 | return __os; | |
2239 | } | |
2240 | ||
2241 | template<typename _RealType, typename _CharT, typename _Traits> | |
2242 | std::basic_istream<_CharT, _Traits>& | |
2243 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2244 | fisher_f_distribution<_RealType>& __x) | |
2245 | { | |
160e95dc JW |
2246 | using param_type |
2247 | = typename fisher_f_distribution<_RealType>::param_type; | |
2248 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
2249 | |
2250 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2251 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2252 | ||
2253 | _RealType __m, __n; | |
160e95dc JW |
2254 | if (__is >> __m >> __n >> __x._M_gd_x >> __x._M_gd_y) |
2255 | __x.param(param_type(__m, __n)); | |
8e79468d BK |
2256 | |
2257 | __is.flags(__flags); | |
2258 | return __is; | |
2259 | } | |
2260 | ||
2261 | ||
7b93bdde UD |
2262 | template<typename _RealType> |
2263 | template<typename _ForwardIterator, | |
2264 | typename _UniformRandomNumberGenerator> | |
2265 | void | |
2266 | std::student_t_distribution<_RealType>:: | |
2267 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2268 | _UniformRandomNumberGenerator& __urng) | |
2269 | { | |
2270 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2271 | while (__f != __t) | |
2272 | *__f++ = _M_nd(__urng) * std::sqrt(n() / _M_gd(__urng)); | |
2273 | } | |
2274 | ||
2275 | template<typename _RealType> | |
2276 | template<typename _ForwardIterator, | |
2277 | typename _UniformRandomNumberGenerator> | |
2278 | void | |
2279 | std::student_t_distribution<_RealType>:: | |
2280 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2281 | _UniformRandomNumberGenerator& __urng, | |
2282 | const param_type& __p) | |
2283 | { | |
2284 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2285 | typename std::gamma_distribution<result_type>::param_type | |
2286 | __p2(__p.n() / 2, 2); | |
2287 | while (__f != __t) | |
2288 | *__f++ = _M_nd(__urng) * std::sqrt(__p.n() / _M_gd(__urng, __p2)); | |
2289 | } | |
2290 | ||
8e79468d BK |
2291 | template<typename _RealType, typename _CharT, typename _Traits> |
2292 | std::basic_ostream<_CharT, _Traits>& | |
2293 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2294 | const student_t_distribution<_RealType>& __x) | |
2295 | { | |
160e95dc | 2296 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
2297 | |
2298 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2299 | const _CharT __fill = __os.fill(); | |
2300 | const std::streamsize __precision = __os.precision(); | |
2301 | const _CharT __space = __os.widen(' '); | |
2302 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2303 | __os.fill(__space); | |
7703dc47 | 2304 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d | 2305 | |
f9b09dec | 2306 | __os << __x.n() << __space << __x._M_nd << __space << __x._M_gd; |
8e79468d BK |
2307 | |
2308 | __os.flags(__flags); | |
2309 | __os.fill(__fill); | |
2310 | __os.precision(__precision); | |
2311 | return __os; | |
2312 | } | |
2313 | ||
2314 | template<typename _RealType, typename _CharT, typename _Traits> | |
2315 | std::basic_istream<_CharT, _Traits>& | |
2316 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2317 | student_t_distribution<_RealType>& __x) | |
2318 | { | |
160e95dc JW |
2319 | using param_type |
2320 | = typename student_t_distribution<_RealType>::param_type; | |
2321 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
2322 | |
2323 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2324 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2325 | ||
2326 | _RealType __n; | |
160e95dc JW |
2327 | if (__is >> __n >> __x._M_nd >> __x._M_gd) |
2328 | __x.param(param_type(__n)); | |
8e79468d BK |
2329 | |
2330 | __is.flags(__flags); | |
2331 | return __is; | |
2332 | } | |
2333 | ||
2334 | ||
2335 | template<typename _RealType> | |
2336 | void | |
2337 | gamma_distribution<_RealType>::param_type:: | |
2338 | _M_initialize() | |
2339 | { | |
b01630bb PC |
2340 | _M_malpha = _M_alpha < 1.0 ? _M_alpha + _RealType(1.0) : _M_alpha; |
2341 | ||
2342 | const _RealType __a1 = _M_malpha - _RealType(1.0) / _RealType(3.0); | |
2343 | _M_a2 = _RealType(1.0) / std::sqrt(_RealType(9.0) * __a1); | |
8e79468d BK |
2344 | } |
2345 | ||
2346 | /** | |
b01630bb PC |
2347 | * Marsaglia, G. and Tsang, W. W. |
2348 | * "A Simple Method for Generating Gamma Variables" | |
2349 | * ACM Transactions on Mathematical Software, 26, 3, 363-372, 2000. | |
8e79468d BK |
2350 | */ |
2351 | template<typename _RealType> | |
2352 | template<typename _UniformRandomNumberGenerator> | |
2353 | typename gamma_distribution<_RealType>::result_type | |
2354 | gamma_distribution<_RealType>:: | |
2355 | operator()(_UniformRandomNumberGenerator& __urng, | |
2356 | const param_type& __param) | |
2357 | { | |
8e79468d BK |
2358 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> |
2359 | __aurng(__urng); | |
2360 | ||
b01630bb PC |
2361 | result_type __u, __v, __n; |
2362 | const result_type __a1 = (__param._M_malpha | |
2363 | - _RealType(1.0) / _RealType(3.0)); | |
8e79468d | 2364 | |
b01630bb PC |
2365 | do |
2366 | { | |
8e79468d BK |
2367 | do |
2368 | { | |
b01630bb PC |
2369 | __n = _M_nd(__urng); |
2370 | __v = result_type(1.0) + __param._M_a2 * __n; | |
8e79468d | 2371 | } |
b01630bb PC |
2372 | while (__v <= 0.0); |
2373 | ||
2374 | __v = __v * __v * __v; | |
2375 | __u = __aurng(); | |
8e79468d | 2376 | } |
957221f5 | 2377 | while (__u > result_type(1.0) - 0.0331 * __n * __n * __n * __n |
b01630bb PC |
2378 | && (std::log(__u) > (0.5 * __n * __n + __a1 |
2379 | * (1.0 - __v + std::log(__v))))); | |
2380 | ||
2381 | if (__param.alpha() == __param._M_malpha) | |
2382 | return __a1 * __v * __param.beta(); | |
8e79468d BK |
2383 | else |
2384 | { | |
8e79468d | 2385 | do |
b01630bb PC |
2386 | __u = __aurng(); |
2387 | while (__u == 0.0); | |
2388 | ||
2389 | return (std::pow(__u, result_type(1.0) / __param.alpha()) | |
2390 | * __a1 * __v * __param.beta()); | |
8e79468d | 2391 | } |
8e79468d BK |
2392 | } |
2393 | ||
7b93bdde UD |
2394 | template<typename _RealType> |
2395 | template<typename _ForwardIterator, | |
2396 | typename _UniformRandomNumberGenerator> | |
2397 | void | |
2398 | gamma_distribution<_RealType>:: | |
2399 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2400 | _UniformRandomNumberGenerator& __urng, | |
2401 | const param_type& __param) | |
2402 | { | |
2403 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2404 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
2405 | __aurng(__urng); | |
2406 | ||
2407 | result_type __u, __v, __n; | |
2408 | const result_type __a1 = (__param._M_malpha | |
2409 | - _RealType(1.0) / _RealType(3.0)); | |
2410 | ||
2411 | if (__param.alpha() == __param._M_malpha) | |
2412 | while (__f != __t) | |
2413 | { | |
2414 | do | |
2415 | { | |
2416 | do | |
2417 | { | |
2418 | __n = _M_nd(__urng); | |
2419 | __v = result_type(1.0) + __param._M_a2 * __n; | |
2420 | } | |
2421 | while (__v <= 0.0); | |
2422 | ||
2423 | __v = __v * __v * __v; | |
2424 | __u = __aurng(); | |
2425 | } | |
6fa8c51f | 2426 | while (__u > result_type(1.0) - 0.0331 * __n * __n * __n * __n |
7b93bdde UD |
2427 | && (std::log(__u) > (0.5 * __n * __n + __a1 |
2428 | * (1.0 - __v + std::log(__v))))); | |
2429 | ||
2430 | *__f++ = __a1 * __v * __param.beta(); | |
2431 | } | |
2432 | else | |
2433 | while (__f != __t) | |
2434 | { | |
2435 | do | |
2436 | { | |
2437 | do | |
2438 | { | |
2439 | __n = _M_nd(__urng); | |
2440 | __v = result_type(1.0) + __param._M_a2 * __n; | |
2441 | } | |
2442 | while (__v <= 0.0); | |
2443 | ||
2444 | __v = __v * __v * __v; | |
2445 | __u = __aurng(); | |
2446 | } | |
6fa8c51f | 2447 | while (__u > result_type(1.0) - 0.0331 * __n * __n * __n * __n |
7b93bdde UD |
2448 | && (std::log(__u) > (0.5 * __n * __n + __a1 |
2449 | * (1.0 - __v + std::log(__v))))); | |
2450 | ||
2451 | do | |
2452 | __u = __aurng(); | |
2453 | while (__u == 0.0); | |
2454 | ||
2455 | *__f++ = (std::pow(__u, result_type(1.0) / __param.alpha()) | |
2456 | * __a1 * __v * __param.beta()); | |
2457 | } | |
2458 | } | |
2459 | ||
8e79468d BK |
2460 | template<typename _RealType, typename _CharT, typename _Traits> |
2461 | std::basic_ostream<_CharT, _Traits>& | |
2462 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2463 | const gamma_distribution<_RealType>& __x) | |
2464 | { | |
160e95dc | 2465 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
2466 | |
2467 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2468 | const _CharT __fill = __os.fill(); | |
2469 | const std::streamsize __precision = __os.precision(); | |
2470 | const _CharT __space = __os.widen(' '); | |
2471 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2472 | __os.fill(__space); | |
7703dc47 | 2473 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d | 2474 | |
b01630bb PC |
2475 | __os << __x.alpha() << __space << __x.beta() |
2476 | << __space << __x._M_nd; | |
8e79468d BK |
2477 | |
2478 | __os.flags(__flags); | |
2479 | __os.fill(__fill); | |
2480 | __os.precision(__precision); | |
2481 | return __os; | |
2482 | } | |
2483 | ||
2484 | template<typename _RealType, typename _CharT, typename _Traits> | |
2485 | std::basic_istream<_CharT, _Traits>& | |
2486 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2487 | gamma_distribution<_RealType>& __x) | |
2488 | { | |
160e95dc JW |
2489 | using param_type = typename gamma_distribution<_RealType>::param_type; |
2490 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
2491 | |
2492 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2493 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2494 | ||
ed2807f4 | 2495 | _RealType __alpha_val, __beta_val; |
160e95dc JW |
2496 | if (__is >> __alpha_val >> __beta_val >> __x._M_nd) |
2497 | __x.param(param_type(__alpha_val, __beta_val)); | |
8e79468d BK |
2498 | |
2499 | __is.flags(__flags); | |
2500 | return __is; | |
2501 | } | |
2502 | ||
2503 | ||
b01630bb PC |
2504 | template<typename _RealType> |
2505 | template<typename _UniformRandomNumberGenerator> | |
2506 | typename weibull_distribution<_RealType>::result_type | |
2507 | weibull_distribution<_RealType>:: | |
2508 | operator()(_UniformRandomNumberGenerator& __urng, | |
2509 | const param_type& __p) | |
2510 | { | |
2511 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
2512 | __aurng(__urng); | |
c2d9083d | 2513 | return __p.b() * std::pow(-std::log(result_type(1) - __aurng()), |
b01630bb PC |
2514 | result_type(1) / __p.a()); |
2515 | } | |
2516 | ||
7b93bdde UD |
2517 | template<typename _RealType> |
2518 | template<typename _ForwardIterator, | |
2519 | typename _UniformRandomNumberGenerator> | |
2520 | void | |
2521 | weibull_distribution<_RealType>:: | |
2522 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2523 | _UniformRandomNumberGenerator& __urng, | |
2524 | const param_type& __p) | |
2525 | { | |
2526 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2527 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
2528 | __aurng(__urng); | |
c2d9083d | 2529 | auto __inv_a = result_type(1) / __p.a(); |
7b93bdde UD |
2530 | |
2531 | while (__f != __t) | |
c2d9083d HY |
2532 | *__f++ = __p.b() * std::pow(-std::log(result_type(1) - __aurng()), |
2533 | __inv_a); | |
7b93bdde UD |
2534 | } |
2535 | ||
8e79468d BK |
2536 | template<typename _RealType, typename _CharT, typename _Traits> |
2537 | std::basic_ostream<_CharT, _Traits>& | |
2538 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2539 | const weibull_distribution<_RealType>& __x) | |
2540 | { | |
160e95dc | 2541 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
2542 | |
2543 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2544 | const _CharT __fill = __os.fill(); | |
2545 | const std::streamsize __precision = __os.precision(); | |
2546 | const _CharT __space = __os.widen(' '); | |
2547 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2548 | __os.fill(__space); | |
7703dc47 | 2549 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d BK |
2550 | |
2551 | __os << __x.a() << __space << __x.b(); | |
2552 | ||
2553 | __os.flags(__flags); | |
2554 | __os.fill(__fill); | |
2555 | __os.precision(__precision); | |
2556 | return __os; | |
2557 | } | |
2558 | ||
2559 | template<typename _RealType, typename _CharT, typename _Traits> | |
2560 | std::basic_istream<_CharT, _Traits>& | |
2561 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2562 | weibull_distribution<_RealType>& __x) | |
2563 | { | |
160e95dc JW |
2564 | using param_type = typename weibull_distribution<_RealType>::param_type; |
2565 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
2566 | |
2567 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2568 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2569 | ||
2570 | _RealType __a, __b; | |
160e95dc JW |
2571 | if (__is >> __a >> __b) |
2572 | __x.param(param_type(__a, __b)); | |
8e79468d BK |
2573 | |
2574 | __is.flags(__flags); | |
2575 | return __is; | |
2576 | } | |
2577 | ||
2578 | ||
2579 | template<typename _RealType> | |
2580 | template<typename _UniformRandomNumberGenerator> | |
2581 | typename extreme_value_distribution<_RealType>::result_type | |
2582 | extreme_value_distribution<_RealType>:: | |
2583 | operator()(_UniformRandomNumberGenerator& __urng, | |
2584 | const param_type& __p) | |
2585 | { | |
2586 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
2587 | __aurng(__urng); | |
c2d9083d HY |
2588 | return __p.a() - __p.b() * std::log(-std::log(result_type(1) |
2589 | - __aurng())); | |
8e79468d BK |
2590 | } |
2591 | ||
7b93bdde UD |
2592 | template<typename _RealType> |
2593 | template<typename _ForwardIterator, | |
2594 | typename _UniformRandomNumberGenerator> | |
2595 | void | |
2596 | extreme_value_distribution<_RealType>:: | |
2597 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2598 | _UniformRandomNumberGenerator& __urng, | |
2599 | const param_type& __p) | |
2600 | { | |
2601 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2602 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
2603 | __aurng(__urng); | |
2604 | ||
2605 | while (__f != __t) | |
c2d9083d HY |
2606 | *__f++ = __p.a() - __p.b() * std::log(-std::log(result_type(1) |
2607 | - __aurng())); | |
7b93bdde UD |
2608 | } |
2609 | ||
8e79468d BK |
2610 | template<typename _RealType, typename _CharT, typename _Traits> |
2611 | std::basic_ostream<_CharT, _Traits>& | |
2612 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2613 | const extreme_value_distribution<_RealType>& __x) | |
2614 | { | |
160e95dc | 2615 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
2616 | |
2617 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2618 | const _CharT __fill = __os.fill(); | |
2619 | const std::streamsize __precision = __os.precision(); | |
2620 | const _CharT __space = __os.widen(' '); | |
2621 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2622 | __os.fill(__space); | |
7703dc47 | 2623 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d BK |
2624 | |
2625 | __os << __x.a() << __space << __x.b(); | |
2626 | ||
2627 | __os.flags(__flags); | |
2628 | __os.fill(__fill); | |
2629 | __os.precision(__precision); | |
2630 | return __os; | |
2631 | } | |
2632 | ||
2633 | template<typename _RealType, typename _CharT, typename _Traits> | |
2634 | std::basic_istream<_CharT, _Traits>& | |
2635 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2636 | extreme_value_distribution<_RealType>& __x) | |
2637 | { | |
160e95dc JW |
2638 | using param_type |
2639 | = typename extreme_value_distribution<_RealType>::param_type; | |
2640 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; | |
8e79468d BK |
2641 | |
2642 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2643 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2644 | ||
2645 | _RealType __a, __b; | |
160e95dc JW |
2646 | if (__is >> __a >> __b) |
2647 | __x.param(param_type(__a, __b)); | |
8e79468d BK |
2648 | |
2649 | __is.flags(__flags); | |
2650 | return __is; | |
2651 | } | |
2652 | ||
2653 | ||
2654 | template<typename _IntType> | |
2655 | void | |
2656 | discrete_distribution<_IntType>::param_type:: | |
2657 | _M_initialize() | |
2658 | { | |
2659 | if (_M_prob.size() < 2) | |
2660 | { | |
2661 | _M_prob.clear(); | |
8e79468d BK |
2662 | return; |
2663 | } | |
2664 | ||
f8dd9e0d PC |
2665 | const double __sum = std::accumulate(_M_prob.begin(), |
2666 | _M_prob.end(), 0.0); | |
b2a96bf9 | 2667 | __glibcxx_assert(__sum > 0); |
f8dd9e0d | 2668 | // Now normalize the probabilites. |
60f3a59f PC |
2669 | __detail::__normalize(_M_prob.begin(), _M_prob.end(), _M_prob.begin(), |
2670 | __sum); | |
f8dd9e0d PC |
2671 | // Accumulate partial sums. |
2672 | _M_cp.reserve(_M_prob.size()); | |
8e79468d BK |
2673 | std::partial_sum(_M_prob.begin(), _M_prob.end(), |
2674 | std::back_inserter(_M_cp)); | |
f8dd9e0d | 2675 | // Make sure the last cumulative probability is one. |
8e79468d BK |
2676 | _M_cp[_M_cp.size() - 1] = 1.0; |
2677 | } | |
2678 | ||
2679 | template<typename _IntType> | |
2680 | template<typename _Func> | |
2681 | discrete_distribution<_IntType>::param_type:: | |
f8dd9e0d | 2682 | param_type(size_t __nw, double __xmin, double __xmax, _Func __fw) |
8e79468d BK |
2683 | : _M_prob(), _M_cp() |
2684 | { | |
f8dd9e0d PC |
2685 | const size_t __n = __nw == 0 ? 1 : __nw; |
2686 | const double __delta = (__xmax - __xmin) / __n; | |
2687 | ||
2688 | _M_prob.reserve(__n); | |
2689 | for (size_t __k = 0; __k < __nw; ++__k) | |
2690 | _M_prob.push_back(__fw(__xmin + __k * __delta + 0.5 * __delta)); | |
8e79468d BK |
2691 | |
2692 | _M_initialize(); | |
2693 | } | |
2694 | ||
2695 | template<typename _IntType> | |
2696 | template<typename _UniformRandomNumberGenerator> | |
2697 | typename discrete_distribution<_IntType>::result_type | |
2698 | discrete_distribution<_IntType>:: | |
2699 | operator()(_UniformRandomNumberGenerator& __urng, | |
2700 | const param_type& __param) | |
2701 | { | |
879b9073 PC |
2702 | if (__param._M_cp.empty()) |
2703 | return result_type(0); | |
2704 | ||
9b88236b | 2705 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> |
8e79468d BK |
2706 | __aurng(__urng); |
2707 | ||
2708 | const double __p = __aurng(); | |
2709 | auto __pos = std::lower_bound(__param._M_cp.begin(), | |
2710 | __param._M_cp.end(), __p); | |
8e79468d | 2711 | |
f8dd9e0d | 2712 | return __pos - __param._M_cp.begin(); |
8e79468d BK |
2713 | } |
2714 | ||
7b93bdde UD |
2715 | template<typename _IntType> |
2716 | template<typename _ForwardIterator, | |
2717 | typename _UniformRandomNumberGenerator> | |
2718 | void | |
2719 | discrete_distribution<_IntType>:: | |
2720 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2721 | _UniformRandomNumberGenerator& __urng, | |
2722 | const param_type& __param) | |
2723 | { | |
2724 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2725 | ||
2726 | if (__param._M_cp.empty()) | |
2727 | { | |
2728 | while (__f != __t) | |
2729 | *__f++ = result_type(0); | |
2730 | return; | |
2731 | } | |
2732 | ||
2733 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
2734 | __aurng(__urng); | |
2735 | ||
2736 | while (__f != __t) | |
2737 | { | |
2738 | const double __p = __aurng(); | |
2739 | auto __pos = std::lower_bound(__param._M_cp.begin(), | |
2740 | __param._M_cp.end(), __p); | |
2741 | ||
2742 | *__f++ = __pos - __param._M_cp.begin(); | |
2743 | } | |
2744 | } | |
2745 | ||
8e79468d BK |
2746 | template<typename _IntType, typename _CharT, typename _Traits> |
2747 | std::basic_ostream<_CharT, _Traits>& | |
2748 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2749 | const discrete_distribution<_IntType>& __x) | |
2750 | { | |
160e95dc | 2751 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
2752 | |
2753 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2754 | const _CharT __fill = __os.fill(); | |
2755 | const std::streamsize __precision = __os.precision(); | |
2756 | const _CharT __space = __os.widen(' '); | |
2757 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2758 | __os.fill(__space); | |
7703dc47 | 2759 | __os.precision(std::numeric_limits<double>::max_digits10); |
8e79468d BK |
2760 | |
2761 | std::vector<double> __prob = __x.probabilities(); | |
2762 | __os << __prob.size(); | |
2763 | for (auto __dit = __prob.begin(); __dit != __prob.end(); ++__dit) | |
2764 | __os << __space << *__dit; | |
2765 | ||
2766 | __os.flags(__flags); | |
2767 | __os.fill(__fill); | |
2768 | __os.precision(__precision); | |
2769 | return __os; | |
2770 | } | |
2771 | ||
160e95dc JW |
2772 | namespace __detail |
2773 | { | |
2774 | template<typename _ValT, typename _CharT, typename _Traits> | |
2775 | basic_istream<_CharT, _Traits>& | |
2776 | __extract_params(basic_istream<_CharT, _Traits>& __is, | |
2777 | vector<_ValT>& __vals, size_t __n) | |
2778 | { | |
2779 | __vals.reserve(__n); | |
2780 | while (__n--) | |
2781 | { | |
2782 | _ValT __val; | |
2783 | if (__is >> __val) | |
2784 | __vals.push_back(__val); | |
2785 | else | |
2786 | break; | |
2787 | } | |
2788 | return __is; | |
2789 | } | |
2790 | } // namespace __detail | |
2791 | ||
8e79468d BK |
2792 | template<typename _IntType, typename _CharT, typename _Traits> |
2793 | std::basic_istream<_CharT, _Traits>& | |
2794 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2795 | discrete_distribution<_IntType>& __x) | |
2796 | { | |
160e95dc | 2797 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; |
8e79468d BK |
2798 | |
2799 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2800 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2801 | ||
2802 | size_t __n; | |
160e95dc | 2803 | if (__is >> __n) |
8e79468d | 2804 | { |
160e95dc JW |
2805 | std::vector<double> __prob_vec; |
2806 | if (__detail::__extract_params(__is, __prob_vec, __n)) | |
2807 | __x.param({__prob_vec.begin(), __prob_vec.end()}); | |
8e79468d BK |
2808 | } |
2809 | ||
8e79468d BK |
2810 | __is.flags(__flags); |
2811 | return __is; | |
2812 | } | |
2813 | ||
2814 | ||
2815 | template<typename _RealType> | |
2816 | void | |
2817 | piecewise_constant_distribution<_RealType>::param_type:: | |
2818 | _M_initialize() | |
2819 | { | |
879b9073 PC |
2820 | if (_M_int.size() < 2 |
2821 | || (_M_int.size() == 2 | |
2822 | && _M_int[0] == _RealType(0) | |
2823 | && _M_int[1] == _RealType(1))) | |
8e79468d BK |
2824 | { |
2825 | _M_int.clear(); | |
8e79468d | 2826 | _M_den.clear(); |
8e79468d BK |
2827 | return; |
2828 | } | |
2829 | ||
f8dd9e0d PC |
2830 | const double __sum = std::accumulate(_M_den.begin(), |
2831 | _M_den.end(), 0.0); | |
b2a96bf9 | 2832 | __glibcxx_assert(__sum > 0); |
8e79468d | 2833 | |
60f3a59f PC |
2834 | __detail::__normalize(_M_den.begin(), _M_den.end(), _M_den.begin(), |
2835 | __sum); | |
f8dd9e0d PC |
2836 | |
2837 | _M_cp.reserve(_M_den.size()); | |
2838 | std::partial_sum(_M_den.begin(), _M_den.end(), | |
2839 | std::back_inserter(_M_cp)); | |
2840 | ||
2841 | // Make sure the last cumulative probability is one. | |
8e79468d | 2842 | _M_cp[_M_cp.size() - 1] = 1.0; |
f8dd9e0d PC |
2843 | |
2844 | for (size_t __k = 0; __k < _M_den.size(); ++__k) | |
2845 | _M_den[__k] /= _M_int[__k + 1] - _M_int[__k]; | |
8e79468d BK |
2846 | } |
2847 | ||
8e79468d BK |
2848 | template<typename _RealType> |
2849 | template<typename _InputIteratorB, typename _InputIteratorW> | |
2850 | piecewise_constant_distribution<_RealType>::param_type:: | |
2851 | param_type(_InputIteratorB __bbegin, | |
2852 | _InputIteratorB __bend, | |
2853 | _InputIteratorW __wbegin) | |
2854 | : _M_int(), _M_den(), _M_cp() | |
2855 | { | |
f8dd9e0d | 2856 | if (__bbegin != __bend) |
8e79468d | 2857 | { |
f8dd9e0d | 2858 | for (;;) |
8e79468d | 2859 | { |
f8dd9e0d PC |
2860 | _M_int.push_back(*__bbegin); |
2861 | ++__bbegin; | |
2862 | if (__bbegin == __bend) | |
2863 | break; | |
2864 | ||
8e79468d BK |
2865 | _M_den.push_back(*__wbegin); |
2866 | ++__wbegin; | |
2867 | } | |
2868 | } | |
8e79468d BK |
2869 | |
2870 | _M_initialize(); | |
2871 | } | |
2872 | ||
2873 | template<typename _RealType> | |
2874 | template<typename _Func> | |
2875 | piecewise_constant_distribution<_RealType>::param_type:: | |
f8dd9e0d | 2876 | param_type(initializer_list<_RealType> __bl, _Func __fw) |
8e79468d BK |
2877 | : _M_int(), _M_den(), _M_cp() |
2878 | { | |
f8dd9e0d PC |
2879 | _M_int.reserve(__bl.size()); |
2880 | for (auto __biter = __bl.begin(); __biter != __bl.end(); ++__biter) | |
8e79468d BK |
2881 | _M_int.push_back(*__biter); |
2882 | ||
f8dd9e0d PC |
2883 | _M_den.reserve(_M_int.size() - 1); |
2884 | for (size_t __k = 0; __k < _M_int.size() - 1; ++__k) | |
2885 | _M_den.push_back(__fw(0.5 * (_M_int[__k + 1] + _M_int[__k]))); | |
8e79468d BK |
2886 | |
2887 | _M_initialize(); | |
2888 | } | |
2889 | ||
2890 | template<typename _RealType> | |
2891 | template<typename _Func> | |
2892 | piecewise_constant_distribution<_RealType>::param_type:: | |
b01630bb | 2893 | param_type(size_t __nw, _RealType __xmin, _RealType __xmax, _Func __fw) |
8e79468d BK |
2894 | : _M_int(), _M_den(), _M_cp() |
2895 | { | |
f8dd9e0d PC |
2896 | const size_t __n = __nw == 0 ? 1 : __nw; |
2897 | const _RealType __delta = (__xmax - __xmin) / __n; | |
2898 | ||
2899 | _M_int.reserve(__n + 1); | |
2900 | for (size_t __k = 0; __k <= __nw; ++__k) | |
2901 | _M_int.push_back(__xmin + __k * __delta); | |
2902 | ||
2903 | _M_den.reserve(__n); | |
2904 | for (size_t __k = 0; __k < __nw; ++__k) | |
2905 | _M_den.push_back(__fw(_M_int[__k] + 0.5 * __delta)); | |
8e79468d BK |
2906 | |
2907 | _M_initialize(); | |
2908 | } | |
2909 | ||
2910 | template<typename _RealType> | |
2911 | template<typename _UniformRandomNumberGenerator> | |
2912 | typename piecewise_constant_distribution<_RealType>::result_type | |
2913 | piecewise_constant_distribution<_RealType>:: | |
2914 | operator()(_UniformRandomNumberGenerator& __urng, | |
2915 | const param_type& __param) | |
2916 | { | |
9b88236b | 2917 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> |
8e79468d BK |
2918 | __aurng(__urng); |
2919 | ||
2920 | const double __p = __aurng(); | |
879b9073 PC |
2921 | if (__param._M_cp.empty()) |
2922 | return __p; | |
2923 | ||
8e79468d BK |
2924 | auto __pos = std::lower_bound(__param._M_cp.begin(), |
2925 | __param._M_cp.end(), __p); | |
2926 | const size_t __i = __pos - __param._M_cp.begin(); | |
2927 | ||
f8dd9e0d PC |
2928 | const double __pref = __i > 0 ? __param._M_cp[__i - 1] : 0.0; |
2929 | ||
2930 | return __param._M_int[__i] + (__p - __pref) / __param._M_den[__i]; | |
8e79468d BK |
2931 | } |
2932 | ||
7b93bdde UD |
2933 | template<typename _RealType> |
2934 | template<typename _ForwardIterator, | |
2935 | typename _UniformRandomNumberGenerator> | |
2936 | void | |
2937 | piecewise_constant_distribution<_RealType>:: | |
2938 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2939 | _UniformRandomNumberGenerator& __urng, | |
2940 | const param_type& __param) | |
2941 | { | |
2942 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2943 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
2944 | __aurng(__urng); | |
2945 | ||
2946 | if (__param._M_cp.empty()) | |
2947 | { | |
2948 | while (__f != __t) | |
2949 | *__f++ = __aurng(); | |
2950 | return; | |
2951 | } | |
2952 | ||
2953 | while (__f != __t) | |
2954 | { | |
2955 | const double __p = __aurng(); | |
2956 | ||
2957 | auto __pos = std::lower_bound(__param._M_cp.begin(), | |
2958 | __param._M_cp.end(), __p); | |
2959 | const size_t __i = __pos - __param._M_cp.begin(); | |
2960 | ||
2961 | const double __pref = __i > 0 ? __param._M_cp[__i - 1] : 0.0; | |
2962 | ||
2963 | *__f++ = (__param._M_int[__i] | |
2964 | + (__p - __pref) / __param._M_den[__i]); | |
2965 | } | |
2966 | } | |
2967 | ||
8e79468d BK |
2968 | template<typename _RealType, typename _CharT, typename _Traits> |
2969 | std::basic_ostream<_CharT, _Traits>& | |
2970 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2971 | const piecewise_constant_distribution<_RealType>& __x) | |
2972 | { | |
160e95dc | 2973 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
2974 | |
2975 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2976 | const _CharT __fill = __os.fill(); | |
2977 | const std::streamsize __precision = __os.precision(); | |
2978 | const _CharT __space = __os.widen(' '); | |
2979 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2980 | __os.fill(__space); | |
7703dc47 | 2981 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d BK |
2982 | |
2983 | std::vector<_RealType> __int = __x.intervals(); | |
2984 | __os << __int.size() - 1; | |
2985 | ||
2986 | for (auto __xit = __int.begin(); __xit != __int.end(); ++__xit) | |
2987 | __os << __space << *__xit; | |
2988 | ||
2989 | std::vector<double> __den = __x.densities(); | |
2990 | for (auto __dit = __den.begin(); __dit != __den.end(); ++__dit) | |
2991 | __os << __space << *__dit; | |
2992 | ||
2993 | __os.flags(__flags); | |
2994 | __os.fill(__fill); | |
2995 | __os.precision(__precision); | |
2996 | return __os; | |
2997 | } | |
2998 | ||
2999 | template<typename _RealType, typename _CharT, typename _Traits> | |
3000 | std::basic_istream<_CharT, _Traits>& | |
3001 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
3002 | piecewise_constant_distribution<_RealType>& __x) | |
3003 | { | |
160e95dc | 3004 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; |
8e79468d BK |
3005 | |
3006 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
3007 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
3008 | ||
3009 | size_t __n; | |
160e95dc | 3010 | if (__is >> __n) |
8e79468d | 3011 | { |
160e95dc JW |
3012 | std::vector<_RealType> __int_vec; |
3013 | if (__detail::__extract_params(__is, __int_vec, __n + 1)) | |
3014 | { | |
3015 | std::vector<double> __den_vec; | |
3016 | if (__detail::__extract_params(__is, __den_vec, __n)) | |
3017 | { | |
3018 | __x.param({ __int_vec.begin(), __int_vec.end(), | |
3019 | __den_vec.begin() }); | |
3020 | } | |
3021 | } | |
8e79468d BK |
3022 | } |
3023 | ||
8e79468d BK |
3024 | __is.flags(__flags); |
3025 | return __is; | |
3026 | } | |
3027 | ||
3028 | ||
3029 | template<typename _RealType> | |
3030 | void | |
3031 | piecewise_linear_distribution<_RealType>::param_type:: | |
3032 | _M_initialize() | |
3033 | { | |
879b9073 PC |
3034 | if (_M_int.size() < 2 |
3035 | || (_M_int.size() == 2 | |
3036 | && _M_int[0] == _RealType(0) | |
3037 | && _M_int[1] == _RealType(1) | |
3038 | && _M_den[0] == _M_den[1])) | |
8e79468d BK |
3039 | { |
3040 | _M_int.clear(); | |
8e79468d | 3041 | _M_den.clear(); |
8e79468d BK |
3042 | return; |
3043 | } | |
3044 | ||
3045 | double __sum = 0.0; | |
f8dd9e0d PC |
3046 | _M_cp.reserve(_M_int.size() - 1); |
3047 | _M_m.reserve(_M_int.size() - 1); | |
3048 | for (size_t __k = 0; __k < _M_int.size() - 1; ++__k) | |
8e79468d | 3049 | { |
f8dd9e0d PC |
3050 | const _RealType __delta = _M_int[__k + 1] - _M_int[__k]; |
3051 | __sum += 0.5 * (_M_den[__k + 1] + _M_den[__k]) * __delta; | |
8e79468d | 3052 | _M_cp.push_back(__sum); |
f8dd9e0d | 3053 | _M_m.push_back((_M_den[__k + 1] - _M_den[__k]) / __delta); |
8e79468d | 3054 | } |
b2a96bf9 | 3055 | __glibcxx_assert(__sum > 0); |
8e79468d BK |
3056 | |
3057 | // Now normalize the densities... | |
60f3a59f PC |
3058 | __detail::__normalize(_M_den.begin(), _M_den.end(), _M_den.begin(), |
3059 | __sum); | |
8e79468d | 3060 | // ... and partial sums... |
60f3a59f | 3061 | __detail::__normalize(_M_cp.begin(), _M_cp.end(), _M_cp.begin(), __sum); |
8e79468d | 3062 | // ... and slopes. |
60f3a59f PC |
3063 | __detail::__normalize(_M_m.begin(), _M_m.end(), _M_m.begin(), __sum); |
3064 | ||
8e79468d BK |
3065 | // Make sure the last cumulative probablility is one. |
3066 | _M_cp[_M_cp.size() - 1] = 1.0; | |
f8dd9e0d | 3067 | } |
8e79468d BK |
3068 | |
3069 | template<typename _RealType> | |
3070 | template<typename _InputIteratorB, typename _InputIteratorW> | |
3071 | piecewise_linear_distribution<_RealType>::param_type:: | |
3072 | param_type(_InputIteratorB __bbegin, | |
3073 | _InputIteratorB __bend, | |
3074 | _InputIteratorW __wbegin) | |
3075 | : _M_int(), _M_den(), _M_cp(), _M_m() | |
3076 | { | |
3077 | for (; __bbegin != __bend; ++__bbegin, ++__wbegin) | |
3078 | { | |
3079 | _M_int.push_back(*__bbegin); | |
3080 | _M_den.push_back(*__wbegin); | |
3081 | } | |
3082 | ||
3083 | _M_initialize(); | |
3084 | } | |
3085 | ||
3086 | template<typename _RealType> | |
3087 | template<typename _Func> | |
3088 | piecewise_linear_distribution<_RealType>::param_type:: | |
f8dd9e0d | 3089 | param_type(initializer_list<_RealType> __bl, _Func __fw) |
8e79468d BK |
3090 | : _M_int(), _M_den(), _M_cp(), _M_m() |
3091 | { | |
f8dd9e0d PC |
3092 | _M_int.reserve(__bl.size()); |
3093 | _M_den.reserve(__bl.size()); | |
3094 | for (auto __biter = __bl.begin(); __biter != __bl.end(); ++__biter) | |
8e79468d BK |
3095 | { |
3096 | _M_int.push_back(*__biter); | |
3097 | _M_den.push_back(__fw(*__biter)); | |
3098 | } | |
3099 | ||
3100 | _M_initialize(); | |
3101 | } | |
3102 | ||
3103 | template<typename _RealType> | |
3104 | template<typename _Func> | |
3105 | piecewise_linear_distribution<_RealType>::param_type:: | |
f8dd9e0d | 3106 | param_type(size_t __nw, _RealType __xmin, _RealType __xmax, _Func __fw) |
8e79468d BK |
3107 | : _M_int(), _M_den(), _M_cp(), _M_m() |
3108 | { | |
f8dd9e0d PC |
3109 | const size_t __n = __nw == 0 ? 1 : __nw; |
3110 | const _RealType __delta = (__xmax - __xmin) / __n; | |
3111 | ||
3112 | _M_int.reserve(__n + 1); | |
3113 | _M_den.reserve(__n + 1); | |
3114 | for (size_t __k = 0; __k <= __nw; ++__k) | |
8e79468d | 3115 | { |
f8dd9e0d PC |
3116 | _M_int.push_back(__xmin + __k * __delta); |
3117 | _M_den.push_back(__fw(_M_int[__k] + __delta)); | |
8e79468d BK |
3118 | } |
3119 | ||
3120 | _M_initialize(); | |
3121 | } | |
3122 | ||
3123 | template<typename _RealType> | |
3124 | template<typename _UniformRandomNumberGenerator> | |
3125 | typename piecewise_linear_distribution<_RealType>::result_type | |
3126 | piecewise_linear_distribution<_RealType>:: | |
3127 | operator()(_UniformRandomNumberGenerator& __urng, | |
3128 | const param_type& __param) | |
3129 | { | |
9b88236b | 3130 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> |
8e79468d BK |
3131 | __aurng(__urng); |
3132 | ||
3133 | const double __p = __aurng(); | |
879b9073 | 3134 | if (__param._M_cp.empty()) |
d3a73504 PC |
3135 | return __p; |
3136 | ||
8e79468d BK |
3137 | auto __pos = std::lower_bound(__param._M_cp.begin(), |
3138 | __param._M_cp.end(), __p); | |
3139 | const size_t __i = __pos - __param._M_cp.begin(); | |
f8dd9e0d PC |
3140 | |
3141 | const double __pref = __i > 0 ? __param._M_cp[__i - 1] : 0.0; | |
3142 | ||
8e79468d BK |
3143 | const double __a = 0.5 * __param._M_m[__i]; |
3144 | const double __b = __param._M_den[__i]; | |
f8dd9e0d PC |
3145 | const double __cm = __p - __pref; |
3146 | ||
3147 | _RealType __x = __param._M_int[__i]; | |
3148 | if (__a == 0) | |
3149 | __x += __cm / __b; | |
3150 | else | |
3151 | { | |
3152 | const double __d = __b * __b + 4.0 * __a * __cm; | |
3153 | __x += 0.5 * (std::sqrt(__d) - __b) / __a; | |
3154 | } | |
8e79468d | 3155 | |
f8dd9e0d | 3156 | return __x; |
8e79468d BK |
3157 | } |
3158 | ||
7b93bdde UD |
3159 | template<typename _RealType> |
3160 | template<typename _ForwardIterator, | |
3161 | typename _UniformRandomNumberGenerator> | |
3162 | void | |
3163 | piecewise_linear_distribution<_RealType>:: | |
3164 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
3165 | _UniformRandomNumberGenerator& __urng, | |
3166 | const param_type& __param) | |
3167 | { | |
3168 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
3169 | // We could duplicate everything from operator()... | |
3170 | while (__f != __t) | |
3171 | *__f++ = this->operator()(__urng, __param); | |
3172 | } | |
3173 | ||
8e79468d BK |
3174 | template<typename _RealType, typename _CharT, typename _Traits> |
3175 | std::basic_ostream<_CharT, _Traits>& | |
3176 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
3177 | const piecewise_linear_distribution<_RealType>& __x) | |
3178 | { | |
160e95dc | 3179 | using __ios_base = typename basic_ostream<_CharT, _Traits>::ios_base; |
8e79468d BK |
3180 | |
3181 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
3182 | const _CharT __fill = __os.fill(); | |
3183 | const std::streamsize __precision = __os.precision(); | |
3184 | const _CharT __space = __os.widen(' '); | |
3185 | __os.flags(__ios_base::scientific | __ios_base::left); | |
3186 | __os.fill(__space); | |
7703dc47 | 3187 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d BK |
3188 | |
3189 | std::vector<_RealType> __int = __x.intervals(); | |
3190 | __os << __int.size() - 1; | |
3191 | ||
3192 | for (auto __xit = __int.begin(); __xit != __int.end(); ++__xit) | |
3193 | __os << __space << *__xit; | |
3194 | ||
3195 | std::vector<double> __den = __x.densities(); | |
3196 | for (auto __dit = __den.begin(); __dit != __den.end(); ++__dit) | |
3197 | __os << __space << *__dit; | |
3198 | ||
3199 | __os.flags(__flags); | |
3200 | __os.fill(__fill); | |
3201 | __os.precision(__precision); | |
3202 | return __os; | |
3203 | } | |
3204 | ||
3205 | template<typename _RealType, typename _CharT, typename _Traits> | |
3206 | std::basic_istream<_CharT, _Traits>& | |
3207 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
3208 | piecewise_linear_distribution<_RealType>& __x) | |
3209 | { | |
160e95dc | 3210 | using __ios_base = typename basic_istream<_CharT, _Traits>::ios_base; |
8e79468d BK |
3211 | |
3212 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
3213 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
3214 | ||
3215 | size_t __n; | |
160e95dc | 3216 | if (__is >> __n) |
8e79468d | 3217 | { |
160e95dc JW |
3218 | vector<_RealType> __int_vec; |
3219 | if (__detail::__extract_params(__is, __int_vec, __n + 1)) | |
3220 | { | |
3221 | vector<double> __den_vec; | |
3222 | if (__detail::__extract_params(__is, __den_vec, __n + 1)) | |
3223 | { | |
3224 | __x.param({ __int_vec.begin(), __int_vec.end(), | |
3225 | __den_vec.begin() }); | |
3226 | } | |
3227 | } | |
8e79468d | 3228 | } |
8e79468d BK |
3229 | __is.flags(__flags); |
3230 | return __is; | |
3231 | } | |
3232 | ||
3233 | ||
3234 | template<typename _IntType> | |
3235 | seed_seq::seed_seq(std::initializer_list<_IntType> __il) | |
3236 | { | |
3237 | for (auto __iter = __il.begin(); __iter != __il.end(); ++__iter) | |
b94f4bef | 3238 | _M_v.push_back(__detail::__mod<result_type, |
8e79468d BK |
3239 | __detail::_Shift<result_type, 32>::__value>(*__iter)); |
3240 | } | |
3241 | ||
3242 | template<typename _InputIterator> | |
3243 | seed_seq::seed_seq(_InputIterator __begin, _InputIterator __end) | |
3244 | { | |
3245 | for (_InputIterator __iter = __begin; __iter != __end; ++__iter) | |
b94f4bef | 3246 | _M_v.push_back(__detail::__mod<result_type, |
8e79468d BK |
3247 | __detail::_Shift<result_type, 32>::__value>(*__iter)); |
3248 | } | |
3249 | ||
3250 | template<typename _RandomAccessIterator> | |
3251 | void | |
3252 | seed_seq::generate(_RandomAccessIterator __begin, | |
3253 | _RandomAccessIterator __end) | |
3254 | { | |
3255 | typedef typename iterator_traits<_RandomAccessIterator>::value_type | |
6855fe45 | 3256 | _Type; |
8e79468d BK |
3257 | |
3258 | if (__begin == __end) | |
3259 | return; | |
3260 | ||
b94f4bef | 3261 | std::fill(__begin, __end, _Type(0x8b8b8b8bu)); |
8e79468d BK |
3262 | |
3263 | const size_t __n = __end - __begin; | |
3264 | const size_t __s = _M_v.size(); | |
3265 | const size_t __t = (__n >= 623) ? 11 | |
3266 | : (__n >= 68) ? 7 | |
3267 | : (__n >= 39) ? 5 | |
3268 | : (__n >= 7) ? 3 | |
3269 | : (__n - 1) / 2; | |
3270 | const size_t __p = (__n - __t) / 2; | |
3271 | const size_t __q = __p + __t; | |
58651854 | 3272 | const size_t __m = std::max(size_t(__s + 1), __n); |
8e79468d | 3273 | |
3ee44d4c JW |
3274 | #ifndef __UINT32_TYPE__ |
3275 | struct _Up | |
3276 | { | |
3277 | _Up(uint_least32_t v) : _M_v(v & 0xffffffffu) { } | |
3278 | ||
3279 | operator uint_least32_t() const { return _M_v; } | |
3280 | ||
3281 | uint_least32_t _M_v; | |
3282 | }; | |
3283 | using uint32_t = _Up; | |
3284 | #endif | |
3285 | ||
3286 | // k == 0, every element in [begin,end) equals 0x8b8b8b8bu | |
8e79468d | 3287 | { |
3ee44d4c JW |
3288 | uint32_t __r1 = 1371501266u; |
3289 | uint32_t __r2 = __r1 + __s; | |
3290 | __begin[__p] += __r1; | |
3291 | __begin[__q] = (uint32_t)__begin[__q] + __r2; | |
3292 | __begin[0] = __r2; | |
3293 | } | |
3294 | ||
3295 | for (size_t __k = 1; __k <= __s; ++__k) | |
3296 | { | |
3297 | const size_t __kn = __k % __n; | |
3298 | const size_t __kpn = (__k + __p) % __n; | |
3299 | const size_t __kqn = (__k + __q) % __n; | |
3300 | uint32_t __arg = (__begin[__kn] | |
3301 | ^ __begin[__kpn] | |
3302 | ^ __begin[(__k - 1) % __n]); | |
3303 | uint32_t __r1 = 1664525u * (__arg ^ (__arg >> 27)); | |
3304 | uint32_t __r2 = __r1 + (uint32_t)__kn + _M_v[__k - 1]; | |
3305 | __begin[__kpn] = (uint32_t)__begin[__kpn] + __r1; | |
3306 | __begin[__kqn] = (uint32_t)__begin[__kqn] + __r2; | |
3307 | __begin[__kn] = __r2; | |
3308 | } | |
3309 | ||
3310 | for (size_t __k = __s + 1; __k < __m; ++__k) | |
3311 | { | |
3312 | const size_t __kn = __k % __n; | |
3313 | const size_t __kpn = (__k + __p) % __n; | |
3314 | const size_t __kqn = (__k + __q) % __n; | |
3315 | uint32_t __arg = (__begin[__kn] | |
3316 | ^ __begin[__kpn] | |
3317 | ^ __begin[(__k - 1) % __n]); | |
3318 | uint32_t __r1 = 1664525u * (__arg ^ (__arg >> 27)); | |
3319 | uint32_t __r2 = __r1 + (uint32_t)__kn; | |
3320 | __begin[__kpn] = (uint32_t)__begin[__kpn] + __r1; | |
3321 | __begin[__kqn] = (uint32_t)__begin[__kqn] + __r2; | |
3322 | __begin[__kn] = __r2; | |
8e79468d BK |
3323 | } |
3324 | ||
3325 | for (size_t __k = __m; __k < __m + __n; ++__k) | |
3326 | { | |
3ee44d4c JW |
3327 | const size_t __kn = __k % __n; |
3328 | const size_t __kpn = (__k + __p) % __n; | |
3329 | const size_t __kqn = (__k + __q) % __n; | |
3330 | uint32_t __arg = (__begin[__kn] | |
3331 | + __begin[__kpn] | |
3332 | + __begin[(__k - 1) % __n]); | |
3333 | uint32_t __r3 = 1566083941u * (__arg ^ (__arg >> 27)); | |
3334 | uint32_t __r4 = __r3 - __kn; | |
3335 | __begin[__kpn] ^= __r3; | |
3336 | __begin[__kqn] ^= __r4; | |
3337 | __begin[__kn] = __r4; | |
8e79468d BK |
3338 | } |
3339 | } | |
3340 | ||
3341 | template<typename _RealType, size_t __bits, | |
3342 | typename _UniformRandomNumberGenerator> | |
3343 | _RealType | |
3344 | generate_canonical(_UniformRandomNumberGenerator& __urng) | |
3345 | { | |
1c4ff014 | 3346 | static_assert(std::is_floating_point<_RealType>::value, |
0cded43d | 3347 | "template argument must be a floating point type"); |
1c4ff014 | 3348 | |
8e79468d BK |
3349 | const size_t __b |
3350 | = std::min(static_cast<size_t>(std::numeric_limits<_RealType>::digits), | |
3351 | __bits); | |
3352 | const long double __r = static_cast<long double>(__urng.max()) | |
3353 | - static_cast<long double>(__urng.min()) + 1.0L; | |
b01630bb | 3354 | const size_t __log2r = std::log(__r) / std::log(2.0L); |
33df19a7 ESR |
3355 | const size_t __m = std::max<size_t>(1UL, |
3356 | (__b + __log2r - 1UL) / __log2r); | |
3357 | _RealType __ret; | |
92d85953 JW |
3358 | _RealType __sum = _RealType(0); |
3359 | _RealType __tmp = _RealType(1); | |
3360 | for (size_t __k = __m; __k != 0; --__k) | |
8e79468d | 3361 | { |
92d85953 JW |
3362 | __sum += _RealType(__urng() - __urng.min()) * __tmp; |
3363 | __tmp *= __r; | |
3364 | } | |
3365 | __ret = __sum / __tmp; | |
3366 | if (__builtin_expect(__ret >= _RealType(1), 0)) | |
3367 | { | |
3368 | #if _GLIBCXX_USE_C99_MATH_TR1 | |
3369 | __ret = std::nextafter(_RealType(1), _RealType(0)); | |
3370 | #else | |
3371 | __ret = _RealType(1) | |
3372 | - std::numeric_limits<_RealType>::epsilon() / _RealType(2); | |
3373 | #endif | |
8e79468d | 3374 | } |
33df19a7 | 3375 | return __ret; |
8e79468d | 3376 | } |
12ffa228 BK |
3377 | |
3378 | _GLIBCXX_END_NAMESPACE_VERSION | |
3379 | } // namespace | |
06f29237 PC |
3380 | |
3381 | #endif |