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8e79468d BK |
1 | // random number generation (out of line) -*- C++ -*- |
2 | ||
85ec4feb | 3 | // Copyright (C) 2009-2018 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 PC |
130 | template<typename _Sseq> |
131 | typename std::enable_if<std::is_class<_Sseq>::value>::type | |
15ecdcc6 PC |
132 | linear_congruential_engine<_UIntType, __a, __c, __m>:: |
133 | seed(_Sseq& __q) | |
134 | { | |
135 | const _UIntType __k0 = __m == 0 ? std::numeric_limits<_UIntType>::digits | |
136 | : std::__lg(__m); | |
137 | const _UIntType __k = (__k0 + 31) / 32; | |
138 | uint_least32_t __arr[__k + 3]; | |
139 | __q.generate(__arr + 0, __arr + __k + 3); | |
140 | _UIntType __factor = 1u; | |
141 | _UIntType __sum = 0u; | |
142 | for (size_t __j = 0; __j < __k; ++__j) | |
143 | { | |
144 | __sum += __arr[__j + 3] * __factor; | |
145 | __factor *= __detail::_Shift<_UIntType, 32>::__value; | |
146 | } | |
147 | seed(__sum); | |
148 | } | |
8e79468d | 149 | |
8e79468d BK |
150 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m, |
151 | typename _CharT, typename _Traits> | |
152 | std::basic_ostream<_CharT, _Traits>& | |
153 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
154 | const linear_congruential_engine<_UIntType, | |
155 | __a, __c, __m>& __lcr) | |
156 | { | |
157 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
158 | typedef typename __ostream_type::ios_base __ios_base; | |
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 | { | |
178 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
179 | typedef typename __istream_type::ios_base __ios_base; | |
180 | ||
181 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
182 | __is.flags(__ios_base::dec); | |
183 | ||
184 | __is >> __lcr._M_x; | |
185 | ||
186 | __is.flags(__flags); | |
187 | return __is; | |
188 | } | |
189 | ||
190 | ||
300ea283 PC |
191 | template<typename _UIntType, |
192 | size_t __w, size_t __n, size_t __m, size_t __r, | |
193 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
194 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
195 | _UIntType __f> | |
94a86be0 | 196 | constexpr size_t |
300ea283 PC |
197 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
198 | __s, __b, __t, __c, __l, __f>::word_size; | |
199 | ||
200 | template<typename _UIntType, | |
201 | size_t __w, size_t __n, size_t __m, size_t __r, | |
202 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
203 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
204 | _UIntType __f> | |
94a86be0 | 205 | constexpr size_t |
300ea283 PC |
206 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
207 | __s, __b, __t, __c, __l, __f>::state_size; | |
208 | ||
209 | template<typename _UIntType, | |
210 | size_t __w, size_t __n, size_t __m, size_t __r, | |
211 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
212 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
213 | _UIntType __f> | |
94a86be0 | 214 | constexpr size_t |
300ea283 PC |
215 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
216 | __s, __b, __t, __c, __l, __f>::shift_size; | |
217 | ||
218 | template<typename _UIntType, | |
219 | size_t __w, size_t __n, size_t __m, size_t __r, | |
220 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
221 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
222 | _UIntType __f> | |
94a86be0 | 223 | constexpr size_t |
300ea283 PC |
224 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
225 | __s, __b, __t, __c, __l, __f>::mask_bits; | |
226 | ||
227 | template<typename _UIntType, | |
228 | size_t __w, size_t __n, size_t __m, size_t __r, | |
229 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
230 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
231 | _UIntType __f> | |
94a86be0 | 232 | constexpr _UIntType |
300ea283 PC |
233 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
234 | __s, __b, __t, __c, __l, __f>::xor_mask; | |
235 | ||
236 | template<typename _UIntType, | |
237 | size_t __w, size_t __n, size_t __m, size_t __r, | |
238 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
239 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
240 | _UIntType __f> | |
94a86be0 | 241 | constexpr size_t |
300ea283 PC |
242 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
243 | __s, __b, __t, __c, __l, __f>::tempering_u; | |
244 | ||
245 | template<typename _UIntType, | |
246 | size_t __w, size_t __n, size_t __m, size_t __r, | |
247 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
248 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
249 | _UIntType __f> | |
94a86be0 | 250 | constexpr _UIntType |
300ea283 PC |
251 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
252 | __s, __b, __t, __c, __l, __f>::tempering_d; | |
253 | ||
254 | template<typename _UIntType, | |
255 | size_t __w, size_t __n, size_t __m, size_t __r, | |
256 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
257 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
258 | _UIntType __f> | |
94a86be0 | 259 | constexpr size_t |
300ea283 PC |
260 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
261 | __s, __b, __t, __c, __l, __f>::tempering_s; | |
262 | ||
263 | template<typename _UIntType, | |
264 | size_t __w, size_t __n, size_t __m, size_t __r, | |
265 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
266 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
267 | _UIntType __f> | |
94a86be0 | 268 | constexpr _UIntType |
300ea283 PC |
269 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
270 | __s, __b, __t, __c, __l, __f>::tempering_b; | |
271 | ||
272 | template<typename _UIntType, | |
273 | size_t __w, size_t __n, size_t __m, size_t __r, | |
274 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
275 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
276 | _UIntType __f> | |
94a86be0 | 277 | constexpr size_t |
300ea283 PC |
278 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
279 | __s, __b, __t, __c, __l, __f>::tempering_t; | |
280 | ||
281 | template<typename _UIntType, | |
282 | size_t __w, size_t __n, size_t __m, size_t __r, | |
283 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
284 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
285 | _UIntType __f> | |
94a86be0 | 286 | constexpr _UIntType |
300ea283 PC |
287 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
288 | __s, __b, __t, __c, __l, __f>::tempering_c; | |
289 | ||
290 | template<typename _UIntType, | |
291 | size_t __w, size_t __n, size_t __m, size_t __r, | |
292 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
293 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
294 | _UIntType __f> | |
94a86be0 | 295 | constexpr size_t |
300ea283 PC |
296 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
297 | __s, __b, __t, __c, __l, __f>::tempering_l; | |
298 | ||
299 | template<typename _UIntType, | |
300 | size_t __w, size_t __n, size_t __m, size_t __r, | |
301 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
302 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
303 | _UIntType __f> | |
94a86be0 | 304 | constexpr _UIntType |
300ea283 PC |
305 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
306 | __s, __b, __t, __c, __l, __f>:: | |
307 | initialization_multiplier; | |
308 | ||
309 | template<typename _UIntType, | |
310 | size_t __w, size_t __n, size_t __m, size_t __r, | |
311 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
312 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
313 | _UIntType __f> | |
94a86be0 | 314 | constexpr _UIntType |
300ea283 PC |
315 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
316 | __s, __b, __t, __c, __l, __f>::default_seed; | |
317 | ||
8e79468d BK |
318 | template<typename _UIntType, |
319 | size_t __w, size_t __n, size_t __m, size_t __r, | |
320 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
321 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
322 | _UIntType __f> | |
323 | void | |
324 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, | |
325 | __s, __b, __t, __c, __l, __f>:: | |
326 | seed(result_type __sd) | |
327 | { | |
b94f4bef | 328 | _M_x[0] = __detail::__mod<_UIntType, |
8e79468d BK |
329 | __detail::_Shift<_UIntType, __w>::__value>(__sd); |
330 | ||
331 | for (size_t __i = 1; __i < state_size; ++__i) | |
332 | { | |
333 | _UIntType __x = _M_x[__i - 1]; | |
334 | __x ^= __x >> (__w - 2); | |
335 | __x *= __f; | |
b94f4bef PC |
336 | __x += __detail::__mod<_UIntType, __n>(__i); |
337 | _M_x[__i] = __detail::__mod<_UIntType, | |
8e79468d BK |
338 | __detail::_Shift<_UIntType, __w>::__value>(__x); |
339 | } | |
340 | _M_p = state_size; | |
341 | } | |
342 | ||
343 | template<typename _UIntType, | |
344 | size_t __w, size_t __n, size_t __m, size_t __r, | |
345 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
346 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
347 | _UIntType __f> | |
05eeebfe PC |
348 | template<typename _Sseq> |
349 | typename std::enable_if<std::is_class<_Sseq>::value>::type | |
15ecdcc6 | 350 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
8e79468d | 351 | __s, __b, __t, __c, __l, __f>:: |
15ecdcc6 PC |
352 | seed(_Sseq& __q) |
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 | { | |
478 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
479 | typedef typename __ostream_type::ios_base __ios_base; | |
480 | ||
481 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
482 | const _CharT __fill = __os.fill(); | |
483 | const _CharT __space = __os.widen(' '); | |
95fe602e | 484 | __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left); |
8e79468d BK |
485 | __os.fill(__space); |
486 | ||
31645179 | 487 | for (size_t __i = 0; __i < __n; ++__i) |
8e79468d | 488 | __os << __x._M_x[__i] << __space; |
31645179 | 489 | __os << __x._M_p; |
8e79468d BK |
490 | |
491 | __os.flags(__flags); | |
492 | __os.fill(__fill); | |
493 | return __os; | |
494 | } | |
495 | ||
496 | template<typename _UIntType, size_t __w, | |
497 | size_t __n, size_t __m, size_t __r, | |
498 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
499 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
500 | _UIntType __f, typename _CharT, typename _Traits> | |
501 | std::basic_istream<_CharT, _Traits>& | |
502 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
503 | mersenne_twister_engine<_UIntType, __w, __n, __m, | |
504 | __r, __a, __u, __d, __s, __b, __t, __c, __l, __f>& __x) | |
505 | { | |
506 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
507 | typedef typename __istream_type::ios_base __ios_base; | |
508 | ||
509 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
510 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
511 | ||
512 | for (size_t __i = 0; __i < __n; ++__i) | |
513 | __is >> __x._M_x[__i]; | |
31645179 | 514 | __is >> __x._M_p; |
8e79468d BK |
515 | |
516 | __is.flags(__flags); | |
517 | return __is; | |
518 | } | |
519 | ||
520 | ||
300ea283 | 521 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> |
94a86be0 | 522 | constexpr size_t |
300ea283 PC |
523 | subtract_with_carry_engine<_UIntType, __w, __s, __r>::word_size; |
524 | ||
525 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> | |
94a86be0 | 526 | constexpr size_t |
300ea283 PC |
527 | subtract_with_carry_engine<_UIntType, __w, __s, __r>::short_lag; |
528 | ||
529 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> | |
94a86be0 | 530 | constexpr size_t |
300ea283 PC |
531 | subtract_with_carry_engine<_UIntType, __w, __s, __r>::long_lag; |
532 | ||
533 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> | |
94a86be0 | 534 | constexpr _UIntType |
300ea283 PC |
535 | subtract_with_carry_engine<_UIntType, __w, __s, __r>::default_seed; |
536 | ||
8e79468d BK |
537 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> |
538 | void | |
539 | subtract_with_carry_engine<_UIntType, __w, __s, __r>:: | |
540 | seed(result_type __value) | |
541 | { | |
b94f4bef PC |
542 | std::linear_congruential_engine<result_type, 40014u, 0u, 2147483563u> |
543 | __lcg(__value == 0u ? default_seed : __value); | |
8e79468d | 544 | |
b94f4bef | 545 | const size_t __n = (__w + 31) / 32; |
8e79468d BK |
546 | |
547 | for (size_t __i = 0; __i < long_lag; ++__i) | |
548 | { | |
b94f4bef PC |
549 | _UIntType __sum = 0u; |
550 | _UIntType __factor = 1u; | |
8e79468d BK |
551 | for (size_t __j = 0; __j < __n; ++__j) |
552 | { | |
b94f4bef PC |
553 | __sum += __detail::__mod<uint_least32_t, |
554 | __detail::_Shift<uint_least32_t, 32>::__value> | |
8e79468d BK |
555 | (__lcg()) * __factor; |
556 | __factor *= __detail::_Shift<_UIntType, 32>::__value; | |
557 | } | |
b94f4bef | 558 | _M_x[__i] = __detail::__mod<_UIntType, |
96a9203b | 559 | __detail::_Shift<_UIntType, __w>::__value>(__sum); |
8e79468d BK |
560 | } |
561 | _M_carry = (_M_x[long_lag - 1] == 0) ? 1 : 0; | |
562 | _M_p = 0; | |
563 | } | |
564 | ||
565 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> | |
05eeebfe PC |
566 | template<typename _Sseq> |
567 | typename std::enable_if<std::is_class<_Sseq>::value>::type | |
15ecdcc6 PC |
568 | subtract_with_carry_engine<_UIntType, __w, __s, __r>:: |
569 | seed(_Sseq& __q) | |
570 | { | |
571 | const size_t __k = (__w + 31) / 32; | |
572 | uint_least32_t __arr[__r * __k]; | |
573 | __q.generate(__arr + 0, __arr + __r * __k); | |
574 | ||
575 | for (size_t __i = 0; __i < long_lag; ++__i) | |
576 | { | |
577 | _UIntType __sum = 0u; | |
578 | _UIntType __factor = 1u; | |
579 | for (size_t __j = 0; __j < __k; ++__j) | |
580 | { | |
581 | __sum += __arr[__k * __i + __j] * __factor; | |
582 | __factor *= __detail::_Shift<_UIntType, 32>::__value; | |
583 | } | |
584 | _M_x[__i] = __detail::__mod<_UIntType, | |
585 | __detail::_Shift<_UIntType, __w>::__value>(__sum); | |
586 | } | |
587 | _M_carry = (_M_x[long_lag - 1] == 0) ? 1 : 0; | |
588 | _M_p = 0; | |
589 | } | |
8e79468d BK |
590 | |
591 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> | |
592 | typename subtract_with_carry_engine<_UIntType, __w, __s, __r>:: | |
593 | result_type | |
594 | subtract_with_carry_engine<_UIntType, __w, __s, __r>:: | |
595 | operator()() | |
596 | { | |
597 | // Derive short lag index from current index. | |
598 | long __ps = _M_p - short_lag; | |
599 | if (__ps < 0) | |
600 | __ps += long_lag; | |
601 | ||
602 | // Calculate new x(i) without overflow or division. | |
603 | // NB: Thanks to the requirements for _UIntType, _M_x[_M_p] + _M_carry | |
604 | // cannot overflow. | |
605 | _UIntType __xi; | |
606 | if (_M_x[__ps] >= _M_x[_M_p] + _M_carry) | |
607 | { | |
608 | __xi = _M_x[__ps] - _M_x[_M_p] - _M_carry; | |
609 | _M_carry = 0; | |
610 | } | |
611 | else | |
612 | { | |
96a9203b PC |
613 | __xi = (__detail::_Shift<_UIntType, __w>::__value |
614 | - _M_x[_M_p] - _M_carry + _M_x[__ps]); | |
8e79468d BK |
615 | _M_carry = 1; |
616 | } | |
617 | _M_x[_M_p] = __xi; | |
618 | ||
619 | // Adjust current index to loop around in ring buffer. | |
620 | if (++_M_p >= long_lag) | |
621 | _M_p = 0; | |
622 | ||
623 | return __xi; | |
624 | } | |
625 | ||
626 | template<typename _UIntType, size_t __w, size_t __s, size_t __r, | |
627 | typename _CharT, typename _Traits> | |
628 | std::basic_ostream<_CharT, _Traits>& | |
629 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
630 | const subtract_with_carry_engine<_UIntType, | |
631 | __w, __s, __r>& __x) | |
632 | { | |
633 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
634 | typedef typename __ostream_type::ios_base __ios_base; | |
635 | ||
636 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
637 | const _CharT __fill = __os.fill(); | |
638 | const _CharT __space = __os.widen(' '); | |
95fe602e | 639 | __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left); |
8e79468d BK |
640 | __os.fill(__space); |
641 | ||
642 | for (size_t __i = 0; __i < __r; ++__i) | |
643 | __os << __x._M_x[__i] << __space; | |
31645179 | 644 | __os << __x._M_carry << __space << __x._M_p; |
8e79468d BK |
645 | |
646 | __os.flags(__flags); | |
647 | __os.fill(__fill); | |
648 | return __os; | |
649 | } | |
650 | ||
651 | template<typename _UIntType, size_t __w, size_t __s, size_t __r, | |
652 | typename _CharT, typename _Traits> | |
653 | std::basic_istream<_CharT, _Traits>& | |
654 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
655 | subtract_with_carry_engine<_UIntType, __w, __s, __r>& __x) | |
656 | { | |
657 | typedef std::basic_ostream<_CharT, _Traits> __istream_type; | |
658 | typedef typename __istream_type::ios_base __ios_base; | |
659 | ||
660 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
661 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
662 | ||
663 | for (size_t __i = 0; __i < __r; ++__i) | |
664 | __is >> __x._M_x[__i]; | |
665 | __is >> __x._M_carry; | |
31645179 | 666 | __is >> __x._M_p; |
8e79468d BK |
667 | |
668 | __is.flags(__flags); | |
669 | return __is; | |
670 | } | |
671 | ||
672 | ||
300ea283 | 673 | template<typename _RandomNumberEngine, size_t __p, size_t __r> |
94a86be0 | 674 | constexpr size_t |
300ea283 PC |
675 | discard_block_engine<_RandomNumberEngine, __p, __r>::block_size; |
676 | ||
677 | template<typename _RandomNumberEngine, size_t __p, size_t __r> | |
94a86be0 | 678 | constexpr size_t |
300ea283 PC |
679 | discard_block_engine<_RandomNumberEngine, __p, __r>::used_block; |
680 | ||
8e79468d BK |
681 | template<typename _RandomNumberEngine, size_t __p, size_t __r> |
682 | typename discard_block_engine<_RandomNumberEngine, | |
683 | __p, __r>::result_type | |
684 | discard_block_engine<_RandomNumberEngine, __p, __r>:: | |
685 | operator()() | |
686 | { | |
687 | if (_M_n >= used_block) | |
688 | { | |
689 | _M_b.discard(block_size - _M_n); | |
690 | _M_n = 0; | |
691 | } | |
692 | ++_M_n; | |
693 | return _M_b(); | |
694 | } | |
695 | ||
696 | template<typename _RandomNumberEngine, size_t __p, size_t __r, | |
697 | typename _CharT, typename _Traits> | |
698 | std::basic_ostream<_CharT, _Traits>& | |
699 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
700 | const discard_block_engine<_RandomNumberEngine, | |
701 | __p, __r>& __x) | |
702 | { | |
703 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
704 | typedef typename __ostream_type::ios_base __ios_base; | |
705 | ||
706 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
707 | const _CharT __fill = __os.fill(); | |
708 | const _CharT __space = __os.widen(' '); | |
95fe602e | 709 | __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left); |
8e79468d BK |
710 | __os.fill(__space); |
711 | ||
712 | __os << __x.base() << __space << __x._M_n; | |
713 | ||
714 | __os.flags(__flags); | |
715 | __os.fill(__fill); | |
716 | return __os; | |
717 | } | |
718 | ||
719 | template<typename _RandomNumberEngine, size_t __p, size_t __r, | |
720 | typename _CharT, typename _Traits> | |
721 | std::basic_istream<_CharT, _Traits>& | |
722 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
723 | discard_block_engine<_RandomNumberEngine, __p, __r>& __x) | |
724 | { | |
725 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
726 | typedef typename __istream_type::ios_base __ios_base; | |
727 | ||
728 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
729 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
730 | ||
731 | __is >> __x._M_b >> __x._M_n; | |
732 | ||
733 | __is.flags(__flags); | |
734 | return __is; | |
735 | } | |
736 | ||
737 | ||
738 | template<typename _RandomNumberEngine, size_t __w, typename _UIntType> | |
739 | typename independent_bits_engine<_RandomNumberEngine, __w, _UIntType>:: | |
740 | result_type | |
741 | independent_bits_engine<_RandomNumberEngine, __w, _UIntType>:: | |
742 | operator()() | |
743 | { | |
f84ca6e7 PC |
744 | typedef typename _RandomNumberEngine::result_type _Eresult_type; |
745 | const _Eresult_type __r | |
746 | = (_M_b.max() - _M_b.min() < std::numeric_limits<_Eresult_type>::max() | |
747 | ? _M_b.max() - _M_b.min() + 1 : 0); | |
748 | const unsigned __edig = std::numeric_limits<_Eresult_type>::digits; | |
749 | const unsigned __m = __r ? std::__lg(__r) : __edig; | |
750 | ||
751 | typedef typename std::common_type<_Eresult_type, result_type>::type | |
752 | __ctype; | |
753 | const unsigned __cdig = std::numeric_limits<__ctype>::digits; | |
754 | ||
755 | unsigned __n, __n0; | |
756 | __ctype __s0, __s1, __y0, __y1; | |
757 | ||
8e79468d BK |
758 | for (size_t __i = 0; __i < 2; ++__i) |
759 | { | |
760 | __n = (__w + __m - 1) / __m + __i; | |
761 | __n0 = __n - __w % __n; | |
f84ca6e7 PC |
762 | const unsigned __w0 = __w / __n; // __w0 <= __m |
763 | ||
764 | __s0 = 0; | |
765 | __s1 = 0; | |
766 | if (__w0 < __cdig) | |
767 | { | |
768 | __s0 = __ctype(1) << __w0; | |
769 | __s1 = __s0 << 1; | |
770 | } | |
771 | ||
772 | __y0 = 0; | |
773 | __y1 = 0; | |
774 | if (__r) | |
775 | { | |
776 | __y0 = __s0 * (__r / __s0); | |
777 | if (__s1) | |
778 | __y1 = __s1 * (__r / __s1); | |
779 | ||
780 | if (__r - __y0 <= __y0 / __n) | |
781 | break; | |
782 | } | |
783 | else | |
8e79468d BK |
784 | break; |
785 | } | |
786 | ||
787 | result_type __sum = 0; | |
788 | for (size_t __k = 0; __k < __n0; ++__k) | |
789 | { | |
f84ca6e7 | 790 | __ctype __u; |
8e79468d | 791 | do |
6855fe45 | 792 | __u = _M_b() - _M_b.min(); |
f84ca6e7 PC |
793 | while (__y0 && __u >= __y0); |
794 | __sum = __s0 * __sum + (__s0 ? __u % __s0 : __u); | |
8e79468d BK |
795 | } |
796 | for (size_t __k = __n0; __k < __n; ++__k) | |
797 | { | |
f84ca6e7 | 798 | __ctype __u; |
8e79468d | 799 | do |
6855fe45 | 800 | __u = _M_b() - _M_b.min(); |
f84ca6e7 PC |
801 | while (__y1 && __u >= __y1); |
802 | __sum = __s1 * __sum + (__s1 ? __u % __s1 : __u); | |
8e79468d BK |
803 | } |
804 | return __sum; | |
805 | } | |
806 | ||
807 | ||
300ea283 | 808 | template<typename _RandomNumberEngine, size_t __k> |
94a86be0 | 809 | constexpr size_t |
300ea283 PC |
810 | shuffle_order_engine<_RandomNumberEngine, __k>::table_size; |
811 | ||
8e79468d BK |
812 | template<typename _RandomNumberEngine, size_t __k> |
813 | typename shuffle_order_engine<_RandomNumberEngine, __k>::result_type | |
814 | shuffle_order_engine<_RandomNumberEngine, __k>:: | |
815 | operator()() | |
816 | { | |
96a9203b PC |
817 | size_t __j = __k * ((_M_y - _M_b.min()) |
818 | / (_M_b.max() - _M_b.min() + 1.0L)); | |
8e79468d BK |
819 | _M_y = _M_v[__j]; |
820 | _M_v[__j] = _M_b(); | |
821 | ||
822 | return _M_y; | |
823 | } | |
824 | ||
825 | template<typename _RandomNumberEngine, size_t __k, | |
826 | typename _CharT, typename _Traits> | |
827 | std::basic_ostream<_CharT, _Traits>& | |
828 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
829 | const shuffle_order_engine<_RandomNumberEngine, __k>& __x) | |
830 | { | |
831 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
832 | typedef typename __ostream_type::ios_base __ios_base; | |
833 | ||
834 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
835 | const _CharT __fill = __os.fill(); | |
836 | const _CharT __space = __os.widen(' '); | |
95fe602e | 837 | __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left); |
8e79468d BK |
838 | __os.fill(__space); |
839 | ||
840 | __os << __x.base(); | |
841 | for (size_t __i = 0; __i < __k; ++__i) | |
842 | __os << __space << __x._M_v[__i]; | |
843 | __os << __space << __x._M_y; | |
844 | ||
845 | __os.flags(__flags); | |
846 | __os.fill(__fill); | |
847 | return __os; | |
848 | } | |
849 | ||
850 | template<typename _RandomNumberEngine, size_t __k, | |
851 | typename _CharT, typename _Traits> | |
852 | std::basic_istream<_CharT, _Traits>& | |
853 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
854 | shuffle_order_engine<_RandomNumberEngine, __k>& __x) | |
855 | { | |
856 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
857 | typedef typename __istream_type::ios_base __ios_base; | |
858 | ||
859 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
860 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
861 | ||
862 | __is >> __x._M_b; | |
863 | for (size_t __i = 0; __i < __k; ++__i) | |
864 | __is >> __x._M_v[__i]; | |
865 | __is >> __x._M_y; | |
866 | ||
867 | __is.flags(__flags); | |
868 | return __is; | |
869 | } | |
870 | ||
871 | ||
8e79468d BK |
872 | template<typename _IntType, typename _CharT, typename _Traits> |
873 | std::basic_ostream<_CharT, _Traits>& | |
874 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
875 | const uniform_int_distribution<_IntType>& __x) | |
876 | { | |
877 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
878 | typedef typename __ostream_type::ios_base __ios_base; | |
879 | ||
880 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
881 | const _CharT __fill = __os.fill(); | |
882 | const _CharT __space = __os.widen(' '); | |
883 | __os.flags(__ios_base::scientific | __ios_base::left); | |
884 | __os.fill(__space); | |
885 | ||
886 | __os << __x.a() << __space << __x.b(); | |
887 | ||
888 | __os.flags(__flags); | |
889 | __os.fill(__fill); | |
890 | return __os; | |
891 | } | |
892 | ||
893 | template<typename _IntType, typename _CharT, typename _Traits> | |
894 | std::basic_istream<_CharT, _Traits>& | |
895 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
896 | uniform_int_distribution<_IntType>& __x) | |
897 | { | |
898 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
899 | typedef typename __istream_type::ios_base __ios_base; | |
900 | ||
901 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
902 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
903 | ||
904 | _IntType __a, __b; | |
905 | __is >> __a >> __b; | |
906 | __x.param(typename uniform_int_distribution<_IntType>:: | |
907 | param_type(__a, __b)); | |
908 | ||
909 | __is.flags(__flags); | |
910 | return __is; | |
911 | } | |
912 | ||
913 | ||
7b93bdde UD |
914 | template<typename _RealType> |
915 | template<typename _ForwardIterator, | |
916 | typename _UniformRandomNumberGenerator> | |
917 | void | |
918 | uniform_real_distribution<_RealType>:: | |
919 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
920 | _UniformRandomNumberGenerator& __urng, | |
921 | const param_type& __p) | |
922 | { | |
923 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
924 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
925 | __aurng(__urng); | |
926 | auto __range = __p.b() - __p.a(); | |
927 | while (__f != __t) | |
928 | *__f++ = __aurng() * __range + __p.a(); | |
929 | } | |
930 | ||
8e79468d BK |
931 | template<typename _RealType, typename _CharT, typename _Traits> |
932 | std::basic_ostream<_CharT, _Traits>& | |
933 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
934 | const uniform_real_distribution<_RealType>& __x) | |
935 | { | |
936 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
937 | typedef typename __ostream_type::ios_base __ios_base; | |
938 | ||
939 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
940 | const _CharT __fill = __os.fill(); | |
941 | const std::streamsize __precision = __os.precision(); | |
942 | const _CharT __space = __os.widen(' '); | |
943 | __os.flags(__ios_base::scientific | __ios_base::left); | |
944 | __os.fill(__space); | |
7703dc47 | 945 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d BK |
946 | |
947 | __os << __x.a() << __space << __x.b(); | |
948 | ||
949 | __os.flags(__flags); | |
950 | __os.fill(__fill); | |
951 | __os.precision(__precision); | |
952 | return __os; | |
953 | } | |
954 | ||
955 | template<typename _RealType, typename _CharT, typename _Traits> | |
956 | std::basic_istream<_CharT, _Traits>& | |
957 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
958 | uniform_real_distribution<_RealType>& __x) | |
959 | { | |
960 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
961 | typedef typename __istream_type::ios_base __ios_base; | |
962 | ||
963 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
964 | __is.flags(__ios_base::skipws); | |
965 | ||
966 | _RealType __a, __b; | |
967 | __is >> __a >> __b; | |
968 | __x.param(typename uniform_real_distribution<_RealType>:: | |
969 | param_type(__a, __b)); | |
970 | ||
971 | __is.flags(__flags); | |
972 | return __is; | |
973 | } | |
974 | ||
975 | ||
7b93bdde UD |
976 | template<typename _ForwardIterator, |
977 | typename _UniformRandomNumberGenerator> | |
978 | void | |
979 | std::bernoulli_distribution:: | |
980 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
981 | _UniformRandomNumberGenerator& __urng, | |
982 | const param_type& __p) | |
983 | { | |
984 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
985 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
986 | __aurng(__urng); | |
987 | auto __limit = __p.p() * (__aurng.max() - __aurng.min()); | |
988 | ||
989 | while (__f != __t) | |
990 | *__f++ = (__aurng() - __aurng.min()) < __limit; | |
991 | } | |
992 | ||
8e79468d BK |
993 | template<typename _CharT, typename _Traits> |
994 | std::basic_ostream<_CharT, _Traits>& | |
995 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
996 | const bernoulli_distribution& __x) | |
997 | { | |
998 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
999 | typedef typename __ostream_type::ios_base __ios_base; | |
1000 | ||
1001 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1002 | const _CharT __fill = __os.fill(); | |
1003 | const std::streamsize __precision = __os.precision(); | |
1004 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1005 | __os.fill(__os.widen(' ')); | |
7703dc47 | 1006 | __os.precision(std::numeric_limits<double>::max_digits10); |
8e79468d BK |
1007 | |
1008 | __os << __x.p(); | |
1009 | ||
1010 | __os.flags(__flags); | |
1011 | __os.fill(__fill); | |
1012 | __os.precision(__precision); | |
1013 | return __os; | |
1014 | } | |
1015 | ||
1016 | ||
1017 | template<typename _IntType> | |
1018 | template<typename _UniformRandomNumberGenerator> | |
1019 | typename geometric_distribution<_IntType>::result_type | |
1020 | geometric_distribution<_IntType>:: | |
1021 | operator()(_UniformRandomNumberGenerator& __urng, | |
1022 | const param_type& __param) | |
1023 | { | |
1024 | // About the epsilon thing see this thread: | |
1025 | // http://gcc.gnu.org/ml/gcc-patches/2006-10/msg00971.html | |
1026 | const double __naf = | |
1027 | (1 - std::numeric_limits<double>::epsilon()) / 2; | |
1028 | // The largest _RealType convertible to _IntType. | |
1029 | const double __thr = | |
1030 | std::numeric_limits<_IntType>::max() + __naf; | |
9b88236b | 1031 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> |
8e79468d BK |
1032 | __aurng(__urng); |
1033 | ||
1034 | double __cand; | |
1035 | do | |
c2d9083d | 1036 | __cand = std::floor(std::log(1.0 - __aurng()) / __param._M_log_1_p); |
8e79468d BK |
1037 | while (__cand >= __thr); |
1038 | ||
1039 | return result_type(__cand + __naf); | |
1040 | } | |
1041 | ||
7b93bdde UD |
1042 | template<typename _IntType> |
1043 | template<typename _ForwardIterator, | |
1044 | typename _UniformRandomNumberGenerator> | |
1045 | void | |
1046 | geometric_distribution<_IntType>:: | |
1047 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1048 | _UniformRandomNumberGenerator& __urng, | |
1049 | const param_type& __param) | |
1050 | { | |
1051 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1052 | // About the epsilon thing see this thread: | |
1053 | // http://gcc.gnu.org/ml/gcc-patches/2006-10/msg00971.html | |
1054 | const double __naf = | |
1055 | (1 - std::numeric_limits<double>::epsilon()) / 2; | |
1056 | // The largest _RealType convertible to _IntType. | |
1057 | const double __thr = | |
1058 | std::numeric_limits<_IntType>::max() + __naf; | |
1059 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
1060 | __aurng(__urng); | |
1061 | ||
1062 | while (__f != __t) | |
1063 | { | |
1064 | double __cand; | |
1065 | do | |
c2d9083d HY |
1066 | __cand = std::floor(std::log(1.0 - __aurng()) |
1067 | / __param._M_log_1_p); | |
7b93bdde UD |
1068 | while (__cand >= __thr); |
1069 | ||
1070 | *__f++ = __cand + __naf; | |
1071 | } | |
1072 | } | |
1073 | ||
8e79468d BK |
1074 | template<typename _IntType, |
1075 | typename _CharT, typename _Traits> | |
1076 | std::basic_ostream<_CharT, _Traits>& | |
1077 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1078 | const geometric_distribution<_IntType>& __x) | |
1079 | { | |
1080 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
1081 | typedef typename __ostream_type::ios_base __ios_base; | |
1082 | ||
1083 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1084 | const _CharT __fill = __os.fill(); | |
1085 | const std::streamsize __precision = __os.precision(); | |
1086 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1087 | __os.fill(__os.widen(' ')); | |
7703dc47 | 1088 | __os.precision(std::numeric_limits<double>::max_digits10); |
8e79468d BK |
1089 | |
1090 | __os << __x.p(); | |
1091 | ||
1092 | __os.flags(__flags); | |
1093 | __os.fill(__fill); | |
1094 | __os.precision(__precision); | |
1095 | return __os; | |
1096 | } | |
1097 | ||
1098 | template<typename _IntType, | |
1099 | typename _CharT, typename _Traits> | |
1100 | std::basic_istream<_CharT, _Traits>& | |
1101 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
1102 | geometric_distribution<_IntType>& __x) | |
1103 | { | |
1104 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
1105 | typedef typename __istream_type::ios_base __ios_base; | |
1106 | ||
1107 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
1108 | __is.flags(__ios_base::skipws); | |
1109 | ||
1110 | double __p; | |
1111 | __is >> __p; | |
1112 | __x.param(typename geometric_distribution<_IntType>::param_type(__p)); | |
1113 | ||
1114 | __is.flags(__flags); | |
1115 | return __is; | |
1116 | } | |
1117 | ||
ff2e697a | 1118 | // This is Leger's algorithm, also in Devroye, Ch. X, Example 1.5. |
f9b09dec PC |
1119 | template<typename _IntType> |
1120 | template<typename _UniformRandomNumberGenerator> | |
1121 | typename negative_binomial_distribution<_IntType>::result_type | |
1122 | negative_binomial_distribution<_IntType>:: | |
1123 | operator()(_UniformRandomNumberGenerator& __urng) | |
1124 | { | |
1125 | const double __y = _M_gd(__urng); | |
1126 | ||
1127 | // XXX Is the constructor too slow? | |
ff2e697a | 1128 | std::poisson_distribution<result_type> __poisson(__y); |
f9b09dec PC |
1129 | return __poisson(__urng); |
1130 | } | |
1131 | ||
8e79468d BK |
1132 | template<typename _IntType> |
1133 | template<typename _UniformRandomNumberGenerator> | |
1134 | typename negative_binomial_distribution<_IntType>::result_type | |
1135 | negative_binomial_distribution<_IntType>:: | |
1136 | operator()(_UniformRandomNumberGenerator& __urng, | |
1137 | const param_type& __p) | |
1138 | { | |
e5fbc9fc | 1139 | typedef typename std::gamma_distribution<double>::param_type |
f9b09dec PC |
1140 | param_type; |
1141 | ||
ff2e697a PC |
1142 | const double __y = |
1143 | _M_gd(__urng, param_type(__p.k(), (1.0 - __p.p()) / __p.p())); | |
8e79468d | 1144 | |
ff2e697a | 1145 | std::poisson_distribution<result_type> __poisson(__y); |
b01630bb | 1146 | return __poisson(__urng); |
8e79468d BK |
1147 | } |
1148 | ||
7b93bdde UD |
1149 | template<typename _IntType> |
1150 | template<typename _ForwardIterator, | |
1151 | typename _UniformRandomNumberGenerator> | |
1152 | void | |
1153 | negative_binomial_distribution<_IntType>:: | |
1154 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1155 | _UniformRandomNumberGenerator& __urng) | |
1156 | { | |
1157 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1158 | while (__f != __t) | |
1159 | { | |
1160 | const double __y = _M_gd(__urng); | |
1161 | ||
1162 | // XXX Is the constructor too slow? | |
1163 | std::poisson_distribution<result_type> __poisson(__y); | |
1164 | *__f++ = __poisson(__urng); | |
1165 | } | |
1166 | } | |
1167 | ||
1168 | template<typename _IntType> | |
1169 | template<typename _ForwardIterator, | |
1170 | typename _UniformRandomNumberGenerator> | |
1171 | void | |
1172 | negative_binomial_distribution<_IntType>:: | |
1173 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1174 | _UniformRandomNumberGenerator& __urng, | |
1175 | const param_type& __p) | |
1176 | { | |
1177 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1178 | typename std::gamma_distribution<result_type>::param_type | |
1179 | __p2(__p.k(), (1.0 - __p.p()) / __p.p()); | |
1180 | ||
1181 | while (__f != __t) | |
1182 | { | |
1183 | const double __y = _M_gd(__urng, __p2); | |
1184 | ||
1185 | std::poisson_distribution<result_type> __poisson(__y); | |
1186 | *__f++ = __poisson(__urng); | |
1187 | } | |
1188 | } | |
1189 | ||
8e79468d BK |
1190 | template<typename _IntType, typename _CharT, typename _Traits> |
1191 | std::basic_ostream<_CharT, _Traits>& | |
1192 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1193 | const negative_binomial_distribution<_IntType>& __x) | |
1194 | { | |
1195 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
1196 | typedef typename __ostream_type::ios_base __ios_base; | |
1197 | ||
1198 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1199 | const _CharT __fill = __os.fill(); | |
1200 | const std::streamsize __precision = __os.precision(); | |
1201 | const _CharT __space = __os.widen(' '); | |
1202 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1203 | __os.fill(__os.widen(' ')); | |
7703dc47 | 1204 | __os.precision(std::numeric_limits<double>::max_digits10); |
8e79468d | 1205 | |
f9b09dec PC |
1206 | __os << __x.k() << __space << __x.p() |
1207 | << __space << __x._M_gd; | |
8e79468d BK |
1208 | |
1209 | __os.flags(__flags); | |
1210 | __os.fill(__fill); | |
1211 | __os.precision(__precision); | |
1212 | return __os; | |
1213 | } | |
1214 | ||
1215 | template<typename _IntType, typename _CharT, typename _Traits> | |
1216 | std::basic_istream<_CharT, _Traits>& | |
1217 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
1218 | negative_binomial_distribution<_IntType>& __x) | |
1219 | { | |
1220 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
1221 | typedef typename __istream_type::ios_base __ios_base; | |
1222 | ||
1223 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
1224 | __is.flags(__ios_base::skipws); | |
1225 | ||
1226 | _IntType __k; | |
1227 | double __p; | |
f9b09dec | 1228 | __is >> __k >> __p >> __x._M_gd; |
8e79468d BK |
1229 | __x.param(typename negative_binomial_distribution<_IntType>:: |
1230 | param_type(__k, __p)); | |
1231 | ||
1232 | __is.flags(__flags); | |
1233 | return __is; | |
1234 | } | |
1235 | ||
1236 | ||
1237 | template<typename _IntType> | |
1238 | void | |
1239 | poisson_distribution<_IntType>::param_type:: | |
1240 | _M_initialize() | |
1241 | { | |
1242 | #if _GLIBCXX_USE_C99_MATH_TR1 | |
1243 | if (_M_mean >= 12) | |
1244 | { | |
1245 | const double __m = std::floor(_M_mean); | |
1246 | _M_lm_thr = std::log(_M_mean); | |
1247 | _M_lfm = std::lgamma(__m + 1); | |
1248 | _M_sm = std::sqrt(__m); | |
1249 | ||
1250 | const double __pi_4 = 0.7853981633974483096156608458198757L; | |
1251 | const double __dx = std::sqrt(2 * __m * std::log(32 * __m | |
1252 | / __pi_4)); | |
3af7efb7 | 1253 | _M_d = std::round(std::max<double>(6.0, std::min(__m, __dx))); |
8e79468d BK |
1254 | const double __cx = 2 * __m + _M_d; |
1255 | _M_scx = std::sqrt(__cx / 2); | |
1256 | _M_1cx = 1 / __cx; | |
1257 | ||
1258 | _M_c2b = std::sqrt(__pi_4 * __cx) * std::exp(_M_1cx); | |
1259 | _M_cb = 2 * __cx * std::exp(-_M_d * _M_1cx * (1 + _M_d / 2)) | |
1260 | / _M_d; | |
1261 | } | |
1262 | else | |
1263 | #endif | |
1264 | _M_lm_thr = std::exp(-_M_mean); | |
1265 | } | |
1266 | ||
1267 | /** | |
1268 | * A rejection algorithm when mean >= 12 and a simple method based | |
1269 | * upon the multiplication of uniform random variates otherwise. | |
1270 | * NB: The former is available only if _GLIBCXX_USE_C99_MATH_TR1 | |
1271 | * is defined. | |
1272 | * | |
1273 | * Reference: | |
2a60a9f6 | 1274 | * Devroye, L. Non-Uniform Random Variates Generation. Springer-Verlag, |
8e79468d BK |
1275 | * New York, 1986, Ch. X, Sects. 3.3 & 3.4 (+ Errata!). |
1276 | */ | |
1277 | template<typename _IntType> | |
1278 | template<typename _UniformRandomNumberGenerator> | |
1279 | typename poisson_distribution<_IntType>::result_type | |
1280 | poisson_distribution<_IntType>:: | |
1281 | operator()(_UniformRandomNumberGenerator& __urng, | |
1282 | const param_type& __param) | |
1283 | { | |
1284 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
1285 | __aurng(__urng); | |
1286 | #if _GLIBCXX_USE_C99_MATH_TR1 | |
1287 | if (__param.mean() >= 12) | |
1288 | { | |
1289 | double __x; | |
1290 | ||
1291 | // See comments above... | |
1292 | const double __naf = | |
1293 | (1 - std::numeric_limits<double>::epsilon()) / 2; | |
1294 | const double __thr = | |
1295 | std::numeric_limits<_IntType>::max() + __naf; | |
1296 | ||
1297 | const double __m = std::floor(__param.mean()); | |
1298 | // sqrt(pi / 2) | |
1299 | const double __spi_2 = 1.2533141373155002512078826424055226L; | |
1300 | const double __c1 = __param._M_sm * __spi_2; | |
1301 | const double __c2 = __param._M_c2b + __c1; | |
1302 | const double __c3 = __c2 + 1; | |
1303 | const double __c4 = __c3 + 1; | |
73986c31 MP |
1304 | // 1 / 78 |
1305 | const double __178 = 0.0128205128205128205128205128205128L; | |
8e79468d BK |
1306 | // e^(1 / 78) |
1307 | const double __e178 = 1.0129030479320018583185514777512983L; | |
1308 | const double __c5 = __c4 + __e178; | |
1309 | const double __c = __param._M_cb + __c5; | |
1310 | const double __2cx = 2 * (2 * __m + __param._M_d); | |
1311 | ||
1312 | bool __reject = true; | |
1313 | do | |
1314 | { | |
1315 | const double __u = __c * __aurng(); | |
c2d9083d | 1316 | const double __e = -std::log(1.0 - __aurng()); |
8e79468d BK |
1317 | |
1318 | double __w = 0.0; | |
1319 | ||
1320 | if (__u <= __c1) | |
1321 | { | |
1322 | const double __n = _M_nd(__urng); | |
1323 | const double __y = -std::abs(__n) * __param._M_sm - 1; | |
1324 | __x = std::floor(__y); | |
1325 | __w = -__n * __n / 2; | |
1326 | if (__x < -__m) | |
1327 | continue; | |
1328 | } | |
1329 | else if (__u <= __c2) | |
1330 | { | |
1331 | const double __n = _M_nd(__urng); | |
1332 | const double __y = 1 + std::abs(__n) * __param._M_scx; | |
1333 | __x = std::ceil(__y); | |
1334 | __w = __y * (2 - __y) * __param._M_1cx; | |
1335 | if (__x > __param._M_d) | |
1336 | continue; | |
1337 | } | |
1338 | else if (__u <= __c3) | |
1339 | // NB: This case not in the book, nor in the Errata, | |
1340 | // but should be ok... | |
1341 | __x = -1; | |
1342 | else if (__u <= __c4) | |
1343 | __x = 0; | |
1344 | else if (__u <= __c5) | |
73986c31 MP |
1345 | { |
1346 | __x = 1; | |
1347 | // Only in the Errata, see libstdc++/83237. | |
1348 | __w = __178; | |
1349 | } | |
8e79468d BK |
1350 | else |
1351 | { | |
c2d9083d | 1352 | const double __v = -std::log(1.0 - __aurng()); |
8e79468d BK |
1353 | const double __y = __param._M_d |
1354 | + __v * __2cx / __param._M_d; | |
1355 | __x = std::ceil(__y); | |
1356 | __w = -__param._M_d * __param._M_1cx * (1 + __y / 2); | |
1357 | } | |
1358 | ||
1359 | __reject = (__w - __e - __x * __param._M_lm_thr | |
1360 | > __param._M_lfm - std::lgamma(__x + __m + 1)); | |
1361 | ||
1362 | __reject |= __x + __m >= __thr; | |
1363 | ||
1364 | } while (__reject); | |
1365 | ||
1366 | return result_type(__x + __m + __naf); | |
1367 | } | |
1368 | else | |
1369 | #endif | |
1370 | { | |
1371 | _IntType __x = 0; | |
1372 | double __prod = 1.0; | |
1373 | ||
1374 | do | |
1375 | { | |
1376 | __prod *= __aurng(); | |
1377 | __x += 1; | |
1378 | } | |
1379 | while (__prod > __param._M_lm_thr); | |
1380 | ||
1381 | return __x - 1; | |
1382 | } | |
1383 | } | |
1384 | ||
7b93bdde UD |
1385 | template<typename _IntType> |
1386 | template<typename _ForwardIterator, | |
1387 | typename _UniformRandomNumberGenerator> | |
1388 | void | |
1389 | poisson_distribution<_IntType>:: | |
1390 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1391 | _UniformRandomNumberGenerator& __urng, | |
1392 | const param_type& __param) | |
1393 | { | |
1394 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1395 | // We could duplicate everything from operator()... | |
1396 | while (__f != __t) | |
1397 | *__f++ = this->operator()(__urng, __param); | |
1398 | } | |
1399 | ||
8e79468d BK |
1400 | template<typename _IntType, |
1401 | typename _CharT, typename _Traits> | |
1402 | std::basic_ostream<_CharT, _Traits>& | |
1403 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1404 | const poisson_distribution<_IntType>& __x) | |
1405 | { | |
1406 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
1407 | typedef typename __ostream_type::ios_base __ios_base; | |
1408 | ||
1409 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1410 | const _CharT __fill = __os.fill(); | |
1411 | const std::streamsize __precision = __os.precision(); | |
1412 | const _CharT __space = __os.widen(' '); | |
1413 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1414 | __os.fill(__space); | |
7703dc47 | 1415 | __os.precision(std::numeric_limits<double>::max_digits10); |
8e79468d BK |
1416 | |
1417 | __os << __x.mean() << __space << __x._M_nd; | |
1418 | ||
1419 | __os.flags(__flags); | |
1420 | __os.fill(__fill); | |
1421 | __os.precision(__precision); | |
1422 | return __os; | |
1423 | } | |
1424 | ||
1425 | template<typename _IntType, | |
1426 | typename _CharT, typename _Traits> | |
1427 | std::basic_istream<_CharT, _Traits>& | |
1428 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
1429 | poisson_distribution<_IntType>& __x) | |
1430 | { | |
1431 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
1432 | typedef typename __istream_type::ios_base __ios_base; | |
1433 | ||
1434 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
1435 | __is.flags(__ios_base::skipws); | |
1436 | ||
1437 | double __mean; | |
1438 | __is >> __mean >> __x._M_nd; | |
1439 | __x.param(typename poisson_distribution<_IntType>::param_type(__mean)); | |
1440 | ||
1441 | __is.flags(__flags); | |
1442 | return __is; | |
1443 | } | |
1444 | ||
1445 | ||
1446 | template<typename _IntType> | |
1447 | void | |
1448 | binomial_distribution<_IntType>::param_type:: | |
1449 | _M_initialize() | |
1450 | { | |
1451 | const double __p12 = _M_p <= 0.5 ? _M_p : 1.0 - _M_p; | |
1452 | ||
1453 | _M_easy = true; | |
1454 | ||
1455 | #if _GLIBCXX_USE_C99_MATH_TR1 | |
1456 | if (_M_t * __p12 >= 8) | |
1457 | { | |
1458 | _M_easy = false; | |
1459 | const double __np = std::floor(_M_t * __p12); | |
1460 | const double __pa = __np / _M_t; | |
1461 | const double __1p = 1 - __pa; | |
1462 | ||
1463 | const double __pi_4 = 0.7853981633974483096156608458198757L; | |
1464 | const double __d1x = | |
1465 | std::sqrt(__np * __1p * std::log(32 * __np | |
1466 | / (81 * __pi_4 * __1p))); | |
3af7efb7 | 1467 | _M_d1 = std::round(std::max<double>(1.0, __d1x)); |
8e79468d BK |
1468 | const double __d2x = |
1469 | std::sqrt(__np * __1p * std::log(32 * _M_t * __1p | |
1470 | / (__pi_4 * __pa))); | |
3af7efb7 | 1471 | _M_d2 = std::round(std::max<double>(1.0, __d2x)); |
8e79468d BK |
1472 | |
1473 | // sqrt(pi / 2) | |
1474 | const double __spi_2 = 1.2533141373155002512078826424055226L; | |
1475 | _M_s1 = std::sqrt(__np * __1p) * (1 + _M_d1 / (4 * __np)); | |
1476 | _M_s2 = std::sqrt(__np * __1p) * (1 + _M_d2 / (4 * _M_t * __1p)); | |
1477 | _M_c = 2 * _M_d1 / __np; | |
1478 | _M_a1 = std::exp(_M_c) * _M_s1 * __spi_2; | |
1479 | const double __a12 = _M_a1 + _M_s2 * __spi_2; | |
1480 | const double __s1s = _M_s1 * _M_s1; | |
1481 | _M_a123 = __a12 + (std::exp(_M_d1 / (_M_t * __1p)) | |
1482 | * 2 * __s1s / _M_d1 | |
1483 | * std::exp(-_M_d1 * _M_d1 / (2 * __s1s))); | |
1484 | const double __s2s = _M_s2 * _M_s2; | |
1485 | _M_s = (_M_a123 + 2 * __s2s / _M_d2 | |
1486 | * std::exp(-_M_d2 * _M_d2 / (2 * __s2s))); | |
1487 | _M_lf = (std::lgamma(__np + 1) | |
1488 | + std::lgamma(_M_t - __np + 1)); | |
1489 | _M_lp1p = std::log(__pa / __1p); | |
1490 | ||
1491 | _M_q = -std::log(1 - (__p12 - __pa) / __1p); | |
1492 | } | |
1493 | else | |
1494 | #endif | |
1495 | _M_q = -std::log(1 - __p12); | |
1496 | } | |
1497 | ||
1498 | template<typename _IntType> | |
1499 | template<typename _UniformRandomNumberGenerator> | |
1500 | typename binomial_distribution<_IntType>::result_type | |
1501 | binomial_distribution<_IntType>:: | |
07bba3b1 PC |
1502 | _M_waiting(_UniformRandomNumberGenerator& __urng, |
1503 | _IntType __t, double __q) | |
8e79468d BK |
1504 | { |
1505 | _IntType __x = 0; | |
1506 | double __sum = 0.0; | |
1507 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
1508 | __aurng(__urng); | |
1509 | ||
1510 | do | |
1511 | { | |
85018f40 | 1512 | if (__t == __x) |
9ea146e6 MLI |
1513 | return __x; |
1514 | const double __e = -std::log(1.0 - __aurng()); | |
8e79468d BK |
1515 | __sum += __e / (__t - __x); |
1516 | __x += 1; | |
1517 | } | |
07bba3b1 | 1518 | while (__sum <= __q); |
8e79468d BK |
1519 | |
1520 | return __x - 1; | |
1521 | } | |
1522 | ||
1523 | /** | |
1524 | * A rejection algorithm when t * p >= 8 and a simple waiting time | |
1525 | * method - the second in the referenced book - otherwise. | |
1526 | * NB: The former is available only if _GLIBCXX_USE_C99_MATH_TR1 | |
1527 | * is defined. | |
1528 | * | |
1529 | * Reference: | |
2a60a9f6 | 1530 | * Devroye, L. Non-Uniform Random Variates Generation. Springer-Verlag, |
8e79468d BK |
1531 | * New York, 1986, Ch. X, Sect. 4 (+ Errata!). |
1532 | */ | |
1533 | template<typename _IntType> | |
1534 | template<typename _UniformRandomNumberGenerator> | |
1535 | typename binomial_distribution<_IntType>::result_type | |
1536 | binomial_distribution<_IntType>:: | |
1537 | operator()(_UniformRandomNumberGenerator& __urng, | |
1538 | const param_type& __param) | |
1539 | { | |
1540 | result_type __ret; | |
1541 | const _IntType __t = __param.t(); | |
d8d4db33 | 1542 | const double __p = __param.p(); |
8e79468d BK |
1543 | const double __p12 = __p <= 0.5 ? __p : 1.0 - __p; |
1544 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
1545 | __aurng(__urng); | |
1546 | ||
1547 | #if _GLIBCXX_USE_C99_MATH_TR1 | |
1548 | if (!__param._M_easy) | |
1549 | { | |
1550 | double __x; | |
1551 | ||
1552 | // See comments above... | |
1553 | const double __naf = | |
1554 | (1 - std::numeric_limits<double>::epsilon()) / 2; | |
1555 | const double __thr = | |
1556 | std::numeric_limits<_IntType>::max() + __naf; | |
1557 | ||
1558 | const double __np = std::floor(__t * __p12); | |
1559 | ||
1560 | // sqrt(pi / 2) | |
1561 | const double __spi_2 = 1.2533141373155002512078826424055226L; | |
1562 | const double __a1 = __param._M_a1; | |
1563 | const double __a12 = __a1 + __param._M_s2 * __spi_2; | |
1564 | const double __a123 = __param._M_a123; | |
1565 | const double __s1s = __param._M_s1 * __param._M_s1; | |
1566 | const double __s2s = __param._M_s2 * __param._M_s2; | |
1567 | ||
1568 | bool __reject; | |
1569 | do | |
1570 | { | |
1571 | const double __u = __param._M_s * __aurng(); | |
1572 | ||
1573 | double __v; | |
1574 | ||
1575 | if (__u <= __a1) | |
1576 | { | |
1577 | const double __n = _M_nd(__urng); | |
1578 | const double __y = __param._M_s1 * std::abs(__n); | |
1579 | __reject = __y >= __param._M_d1; | |
1580 | if (!__reject) | |
1581 | { | |
c2d9083d | 1582 | const double __e = -std::log(1.0 - __aurng()); |
8e79468d BK |
1583 | __x = std::floor(__y); |
1584 | __v = -__e - __n * __n / 2 + __param._M_c; | |
1585 | } | |
1586 | } | |
1587 | else if (__u <= __a12) | |
1588 | { | |
1589 | const double __n = _M_nd(__urng); | |
1590 | const double __y = __param._M_s2 * std::abs(__n); | |
1591 | __reject = __y >= __param._M_d2; | |
1592 | if (!__reject) | |
1593 | { | |
c2d9083d | 1594 | const double __e = -std::log(1.0 - __aurng()); |
8e79468d BK |
1595 | __x = std::floor(-__y); |
1596 | __v = -__e - __n * __n / 2; | |
1597 | } | |
1598 | } | |
1599 | else if (__u <= __a123) | |
1600 | { | |
c2d9083d HY |
1601 | const double __e1 = -std::log(1.0 - __aurng()); |
1602 | const double __e2 = -std::log(1.0 - __aurng()); | |
8e79468d BK |
1603 | |
1604 | const double __y = __param._M_d1 | |
1605 | + 2 * __s1s * __e1 / __param._M_d1; | |
1606 | __x = std::floor(__y); | |
1607 | __v = (-__e2 + __param._M_d1 * (1 / (__t - __np) | |
1608 | -__y / (2 * __s1s))); | |
1609 | __reject = false; | |
1610 | } | |
1611 | else | |
1612 | { | |
c2d9083d HY |
1613 | const double __e1 = -std::log(1.0 - __aurng()); |
1614 | const double __e2 = -std::log(1.0 - __aurng()); | |
8e79468d BK |
1615 | |
1616 | const double __y = __param._M_d2 | |
1617 | + 2 * __s2s * __e1 / __param._M_d2; | |
1618 | __x = std::floor(-__y); | |
1619 | __v = -__e2 - __param._M_d2 * __y / (2 * __s2s); | |
1620 | __reject = false; | |
1621 | } | |
1622 | ||
1623 | __reject = __reject || __x < -__np || __x > __t - __np; | |
1624 | if (!__reject) | |
1625 | { | |
1626 | const double __lfx = | |
1627 | std::lgamma(__np + __x + 1) | |
1628 | + std::lgamma(__t - (__np + __x) + 1); | |
1629 | __reject = __v > __param._M_lf - __lfx | |
1630 | + __x * __param._M_lp1p; | |
1631 | } | |
1632 | ||
1633 | __reject |= __x + __np >= __thr; | |
1634 | } | |
1635 | while (__reject); | |
1636 | ||
1637 | __x += __np + __naf; | |
1638 | ||
07bba3b1 PC |
1639 | const _IntType __z = _M_waiting(__urng, __t - _IntType(__x), |
1640 | __param._M_q); | |
8e79468d BK |
1641 | __ret = _IntType(__x) + __z; |
1642 | } | |
1643 | else | |
1644 | #endif | |
07bba3b1 | 1645 | __ret = _M_waiting(__urng, __t, __param._M_q); |
8e79468d BK |
1646 | |
1647 | if (__p12 != __p) | |
1648 | __ret = __t - __ret; | |
1649 | return __ret; | |
1650 | } | |
1651 | ||
7b93bdde UD |
1652 | template<typename _IntType> |
1653 | template<typename _ForwardIterator, | |
1654 | typename _UniformRandomNumberGenerator> | |
1655 | void | |
1656 | binomial_distribution<_IntType>:: | |
1657 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1658 | _UniformRandomNumberGenerator& __urng, | |
1659 | const param_type& __param) | |
1660 | { | |
1661 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1662 | // We could duplicate everything from operator()... | |
1663 | while (__f != __t) | |
1664 | *__f++ = this->operator()(__urng, __param); | |
1665 | } | |
1666 | ||
8e79468d BK |
1667 | template<typename _IntType, |
1668 | typename _CharT, typename _Traits> | |
1669 | std::basic_ostream<_CharT, _Traits>& | |
1670 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1671 | const binomial_distribution<_IntType>& __x) | |
1672 | { | |
1673 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
1674 | typedef typename __ostream_type::ios_base __ios_base; | |
1675 | ||
1676 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1677 | const _CharT __fill = __os.fill(); | |
1678 | const std::streamsize __precision = __os.precision(); | |
1679 | const _CharT __space = __os.widen(' '); | |
1680 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1681 | __os.fill(__space); | |
7703dc47 | 1682 | __os.precision(std::numeric_limits<double>::max_digits10); |
8e79468d BK |
1683 | |
1684 | __os << __x.t() << __space << __x.p() | |
1685 | << __space << __x._M_nd; | |
1686 | ||
1687 | __os.flags(__flags); | |
1688 | __os.fill(__fill); | |
1689 | __os.precision(__precision); | |
1690 | return __os; | |
1691 | } | |
1692 | ||
1693 | template<typename _IntType, | |
1694 | typename _CharT, typename _Traits> | |
1695 | std::basic_istream<_CharT, _Traits>& | |
1696 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
1697 | binomial_distribution<_IntType>& __x) | |
1698 | { | |
1699 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
1700 | typedef typename __istream_type::ios_base __ios_base; | |
1701 | ||
1702 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
1703 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
1704 | ||
1705 | _IntType __t; | |
1706 | double __p; | |
1707 | __is >> __t >> __p >> __x._M_nd; | |
1708 | __x.param(typename binomial_distribution<_IntType>:: | |
1709 | param_type(__t, __p)); | |
1710 | ||
1711 | __is.flags(__flags); | |
1712 | return __is; | |
1713 | } | |
1714 | ||
1715 | ||
7b93bdde UD |
1716 | template<typename _RealType> |
1717 | template<typename _ForwardIterator, | |
1718 | typename _UniformRandomNumberGenerator> | |
1719 | void | |
1720 | std::exponential_distribution<_RealType>:: | |
1721 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1722 | _UniformRandomNumberGenerator& __urng, | |
1723 | const param_type& __p) | |
1724 | { | |
1725 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1726 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
1727 | __aurng(__urng); | |
1728 | while (__f != __t) | |
c2d9083d | 1729 | *__f++ = -std::log(result_type(1) - __aurng()) / __p.lambda(); |
7b93bdde UD |
1730 | } |
1731 | ||
8e79468d BK |
1732 | template<typename _RealType, typename _CharT, typename _Traits> |
1733 | std::basic_ostream<_CharT, _Traits>& | |
1734 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1735 | const exponential_distribution<_RealType>& __x) | |
1736 | { | |
1737 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
1738 | typedef typename __ostream_type::ios_base __ios_base; | |
1739 | ||
1740 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1741 | const _CharT __fill = __os.fill(); | |
1742 | const std::streamsize __precision = __os.precision(); | |
1743 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1744 | __os.fill(__os.widen(' ')); | |
7703dc47 | 1745 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d BK |
1746 | |
1747 | __os << __x.lambda(); | |
1748 | ||
1749 | __os.flags(__flags); | |
1750 | __os.fill(__fill); | |
1751 | __os.precision(__precision); | |
1752 | return __os; | |
1753 | } | |
1754 | ||
1755 | template<typename _RealType, typename _CharT, typename _Traits> | |
1756 | std::basic_istream<_CharT, _Traits>& | |
1757 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
1758 | exponential_distribution<_RealType>& __x) | |
1759 | { | |
1760 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
1761 | typedef typename __istream_type::ios_base __ios_base; | |
1762 | ||
1763 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
1764 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
1765 | ||
1766 | _RealType __lambda; | |
1767 | __is >> __lambda; | |
1768 | __x.param(typename exponential_distribution<_RealType>:: | |
1769 | param_type(__lambda)); | |
1770 | ||
1771 | __is.flags(__flags); | |
1772 | return __is; | |
1773 | } | |
1774 | ||
1775 | ||
8e79468d BK |
1776 | /** |
1777 | * Polar method due to Marsaglia. | |
1778 | * | |
2a60a9f6 | 1779 | * Devroye, L. Non-Uniform Random Variates Generation. Springer-Verlag, |
8e79468d BK |
1780 | * New York, 1986, Ch. V, Sect. 4.4. |
1781 | */ | |
1782 | template<typename _RealType> | |
1783 | template<typename _UniformRandomNumberGenerator> | |
1784 | typename normal_distribution<_RealType>::result_type | |
1785 | normal_distribution<_RealType>:: | |
1786 | operator()(_UniformRandomNumberGenerator& __urng, | |
1787 | const param_type& __param) | |
1788 | { | |
1789 | result_type __ret; | |
1790 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
1791 | __aurng(__urng); | |
1792 | ||
1793 | if (_M_saved_available) | |
1794 | { | |
1795 | _M_saved_available = false; | |
1796 | __ret = _M_saved; | |
1797 | } | |
1798 | else | |
1799 | { | |
1800 | result_type __x, __y, __r2; | |
1801 | do | |
1802 | { | |
1803 | __x = result_type(2.0) * __aurng() - 1.0; | |
1804 | __y = result_type(2.0) * __aurng() - 1.0; | |
1805 | __r2 = __x * __x + __y * __y; | |
1806 | } | |
1807 | while (__r2 > 1.0 || __r2 == 0.0); | |
1808 | ||
1809 | const result_type __mult = std::sqrt(-2 * std::log(__r2) / __r2); | |
1810 | _M_saved = __x * __mult; | |
1811 | _M_saved_available = true; | |
1812 | __ret = __y * __mult; | |
1813 | } | |
1814 | ||
1815 | __ret = __ret * __param.stddev() + __param.mean(); | |
1816 | return __ret; | |
1817 | } | |
1818 | ||
7b93bdde UD |
1819 | template<typename _RealType> |
1820 | template<typename _ForwardIterator, | |
1821 | typename _UniformRandomNumberGenerator> | |
1822 | void | |
1823 | normal_distribution<_RealType>:: | |
1824 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1825 | _UniformRandomNumberGenerator& __urng, | |
1826 | const param_type& __param) | |
1827 | { | |
1828 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1829 | ||
1830 | if (__f == __t) | |
1831 | return; | |
1832 | ||
1833 | if (_M_saved_available) | |
1834 | { | |
1835 | _M_saved_available = false; | |
1836 | *__f++ = _M_saved * __param.stddev() + __param.mean(); | |
1837 | ||
1838 | if (__f == __t) | |
1839 | return; | |
1840 | } | |
1841 | ||
1842 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
1843 | __aurng(__urng); | |
1844 | ||
1845 | while (__f + 1 < __t) | |
1846 | { | |
1847 | result_type __x, __y, __r2; | |
1848 | do | |
1849 | { | |
1850 | __x = result_type(2.0) * __aurng() - 1.0; | |
1851 | __y = result_type(2.0) * __aurng() - 1.0; | |
1852 | __r2 = __x * __x + __y * __y; | |
1853 | } | |
1854 | while (__r2 > 1.0 || __r2 == 0.0); | |
1855 | ||
1856 | const result_type __mult = std::sqrt(-2 * std::log(__r2) / __r2); | |
1857 | *__f++ = __y * __mult * __param.stddev() + __param.mean(); | |
1858 | *__f++ = __x * __mult * __param.stddev() + __param.mean(); | |
1859 | } | |
1860 | ||
1861 | if (__f != __t) | |
1862 | { | |
1863 | result_type __x, __y, __r2; | |
1864 | do | |
1865 | { | |
1866 | __x = result_type(2.0) * __aurng() - 1.0; | |
1867 | __y = result_type(2.0) * __aurng() - 1.0; | |
1868 | __r2 = __x * __x + __y * __y; | |
1869 | } | |
1870 | while (__r2 > 1.0 || __r2 == 0.0); | |
1871 | ||
1872 | const result_type __mult = std::sqrt(-2 * std::log(__r2) / __r2); | |
1873 | _M_saved = __x * __mult; | |
1874 | _M_saved_available = true; | |
1875 | *__f = __y * __mult * __param.stddev() + __param.mean(); | |
1876 | } | |
1877 | } | |
1878 | ||
fc05e1ba PC |
1879 | template<typename _RealType> |
1880 | bool | |
1881 | operator==(const std::normal_distribution<_RealType>& __d1, | |
1882 | const std::normal_distribution<_RealType>& __d2) | |
1883 | { | |
1884 | if (__d1._M_param == __d2._M_param | |
1885 | && __d1._M_saved_available == __d2._M_saved_available) | |
1886 | { | |
1887 | if (__d1._M_saved_available | |
1888 | && __d1._M_saved == __d2._M_saved) | |
1889 | return true; | |
1890 | else if(!__d1._M_saved_available) | |
1891 | return true; | |
1892 | else | |
1893 | return false; | |
1894 | } | |
1895 | else | |
1896 | return false; | |
1897 | } | |
1898 | ||
8e79468d BK |
1899 | template<typename _RealType, typename _CharT, typename _Traits> |
1900 | std::basic_ostream<_CharT, _Traits>& | |
1901 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1902 | const normal_distribution<_RealType>& __x) | |
1903 | { | |
1904 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
1905 | typedef typename __ostream_type::ios_base __ios_base; | |
1906 | ||
1907 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1908 | const _CharT __fill = __os.fill(); | |
1909 | const std::streamsize __precision = __os.precision(); | |
1910 | const _CharT __space = __os.widen(' '); | |
1911 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1912 | __os.fill(__space); | |
7703dc47 | 1913 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d BK |
1914 | |
1915 | __os << __x.mean() << __space << __x.stddev() | |
1916 | << __space << __x._M_saved_available; | |
1917 | if (__x._M_saved_available) | |
1918 | __os << __space << __x._M_saved; | |
1919 | ||
1920 | __os.flags(__flags); | |
1921 | __os.fill(__fill); | |
1922 | __os.precision(__precision); | |
1923 | return __os; | |
1924 | } | |
1925 | ||
1926 | template<typename _RealType, typename _CharT, typename _Traits> | |
1927 | std::basic_istream<_CharT, _Traits>& | |
1928 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
1929 | normal_distribution<_RealType>& __x) | |
1930 | { | |
1931 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
1932 | typedef typename __istream_type::ios_base __ios_base; | |
1933 | ||
1934 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
1935 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
1936 | ||
1937 | double __mean, __stddev; | |
1938 | __is >> __mean >> __stddev | |
1939 | >> __x._M_saved_available; | |
1940 | if (__x._M_saved_available) | |
1941 | __is >> __x._M_saved; | |
1942 | __x.param(typename normal_distribution<_RealType>:: | |
1943 | param_type(__mean, __stddev)); | |
1944 | ||
1945 | __is.flags(__flags); | |
1946 | return __is; | |
1947 | } | |
1948 | ||
1949 | ||
7b93bdde UD |
1950 | template<typename _RealType> |
1951 | template<typename _ForwardIterator, | |
1952 | typename _UniformRandomNumberGenerator> | |
1953 | void | |
1954 | lognormal_distribution<_RealType>:: | |
1955 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1956 | _UniformRandomNumberGenerator& __urng, | |
1957 | const param_type& __p) | |
1958 | { | |
1959 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1960 | while (__f != __t) | |
1961 | *__f++ = std::exp(__p.s() * _M_nd(__urng) + __p.m()); | |
1962 | } | |
1963 | ||
8e79468d BK |
1964 | template<typename _RealType, typename _CharT, typename _Traits> |
1965 | std::basic_ostream<_CharT, _Traits>& | |
1966 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1967 | const lognormal_distribution<_RealType>& __x) | |
1968 | { | |
1969 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
1970 | typedef typename __ostream_type::ios_base __ios_base; | |
1971 | ||
1972 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1973 | const _CharT __fill = __os.fill(); | |
1974 | const std::streamsize __precision = __os.precision(); | |
1975 | const _CharT __space = __os.widen(' '); | |
1976 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1977 | __os.fill(__space); | |
7703dc47 | 1978 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d | 1979 | |
b01630bb PC |
1980 | __os << __x.m() << __space << __x.s() |
1981 | << __space << __x._M_nd; | |
8e79468d BK |
1982 | |
1983 | __os.flags(__flags); | |
1984 | __os.fill(__fill); | |
1985 | __os.precision(__precision); | |
1986 | return __os; | |
1987 | } | |
1988 | ||
1989 | template<typename _RealType, typename _CharT, typename _Traits> | |
1990 | std::basic_istream<_CharT, _Traits>& | |
1991 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
1992 | lognormal_distribution<_RealType>& __x) | |
1993 | { | |
1994 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
1995 | typedef typename __istream_type::ios_base __ios_base; | |
1996 | ||
1997 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
1998 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
1999 | ||
2000 | _RealType __m, __s; | |
b01630bb | 2001 | __is >> __m >> __s >> __x._M_nd; |
8e79468d BK |
2002 | __x.param(typename lognormal_distribution<_RealType>:: |
2003 | param_type(__m, __s)); | |
2004 | ||
2005 | __is.flags(__flags); | |
2006 | return __is; | |
2007 | } | |
2008 | ||
5bcb3b4d PC |
2009 | template<typename _RealType> |
2010 | template<typename _ForwardIterator, | |
2011 | typename _UniformRandomNumberGenerator> | |
2012 | void | |
2013 | std::chi_squared_distribution<_RealType>:: | |
2014 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2015 | _UniformRandomNumberGenerator& __urng) | |
2016 | { | |
2017 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2018 | while (__f != __t) | |
2019 | *__f++ = 2 * _M_gd(__urng); | |
2020 | } | |
8e79468d | 2021 | |
7b93bdde UD |
2022 | template<typename _RealType> |
2023 | template<typename _ForwardIterator, | |
2024 | typename _UniformRandomNumberGenerator> | |
2025 | void | |
2026 | std::chi_squared_distribution<_RealType>:: | |
2027 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2028 | _UniformRandomNumberGenerator& __urng, | |
5bcb3b4d PC |
2029 | const typename |
2030 | std::gamma_distribution<result_type>::param_type& __p) | |
7b93bdde UD |
2031 | { |
2032 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2033 | while (__f != __t) | |
2034 | *__f++ = 2 * _M_gd(__urng, __p); | |
2035 | } | |
2036 | ||
8e79468d BK |
2037 | template<typename _RealType, typename _CharT, typename _Traits> |
2038 | std::basic_ostream<_CharT, _Traits>& | |
2039 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2040 | const chi_squared_distribution<_RealType>& __x) | |
2041 | { | |
2042 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
2043 | typedef typename __ostream_type::ios_base __ios_base; | |
2044 | ||
2045 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2046 | const _CharT __fill = __os.fill(); | |
2047 | const std::streamsize __precision = __os.precision(); | |
2048 | const _CharT __space = __os.widen(' '); | |
2049 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2050 | __os.fill(__space); | |
7703dc47 | 2051 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d | 2052 | |
f9b09dec | 2053 | __os << __x.n() << __space << __x._M_gd; |
8e79468d BK |
2054 | |
2055 | __os.flags(__flags); | |
2056 | __os.fill(__fill); | |
2057 | __os.precision(__precision); | |
2058 | return __os; | |
2059 | } | |
2060 | ||
2061 | template<typename _RealType, typename _CharT, typename _Traits> | |
2062 | std::basic_istream<_CharT, _Traits>& | |
2063 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2064 | chi_squared_distribution<_RealType>& __x) | |
2065 | { | |
2066 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
2067 | typedef typename __istream_type::ios_base __ios_base; | |
2068 | ||
2069 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2070 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2071 | ||
2072 | _RealType __n; | |
f9b09dec | 2073 | __is >> __n >> __x._M_gd; |
8e79468d BK |
2074 | __x.param(typename chi_squared_distribution<_RealType>:: |
2075 | param_type(__n)); | |
2076 | ||
2077 | __is.flags(__flags); | |
2078 | return __is; | |
2079 | } | |
2080 | ||
2081 | ||
2082 | template<typename _RealType> | |
2083 | template<typename _UniformRandomNumberGenerator> | |
2084 | typename cauchy_distribution<_RealType>::result_type | |
2085 | cauchy_distribution<_RealType>:: | |
2086 | operator()(_UniformRandomNumberGenerator& __urng, | |
2087 | const param_type& __p) | |
2088 | { | |
2089 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
2090 | __aurng(__urng); | |
2091 | _RealType __u; | |
2092 | do | |
e1a02963 | 2093 | __u = __aurng(); |
8e79468d BK |
2094 | while (__u == 0.5); |
2095 | ||
e1a02963 PC |
2096 | const _RealType __pi = 3.1415926535897932384626433832795029L; |
2097 | return __p.a() + __p.b() * std::tan(__pi * __u); | |
8e79468d BK |
2098 | } |
2099 | ||
7b93bdde UD |
2100 | template<typename _RealType> |
2101 | template<typename _ForwardIterator, | |
2102 | typename _UniformRandomNumberGenerator> | |
2103 | void | |
2104 | cauchy_distribution<_RealType>:: | |
2105 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2106 | _UniformRandomNumberGenerator& __urng, | |
2107 | const param_type& __p) | |
2108 | { | |
2109 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2110 | const _RealType __pi = 3.1415926535897932384626433832795029L; | |
2111 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
2112 | __aurng(__urng); | |
2113 | while (__f != __t) | |
2114 | { | |
2115 | _RealType __u; | |
2116 | do | |
2117 | __u = __aurng(); | |
2118 | while (__u == 0.5); | |
2119 | ||
2120 | *__f++ = __p.a() + __p.b() * std::tan(__pi * __u); | |
2121 | } | |
2122 | } | |
2123 | ||
8e79468d BK |
2124 | template<typename _RealType, typename _CharT, typename _Traits> |
2125 | std::basic_ostream<_CharT, _Traits>& | |
2126 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2127 | const cauchy_distribution<_RealType>& __x) | |
2128 | { | |
2129 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
2130 | typedef typename __ostream_type::ios_base __ios_base; | |
2131 | ||
2132 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2133 | const _CharT __fill = __os.fill(); | |
2134 | const std::streamsize __precision = __os.precision(); | |
2135 | const _CharT __space = __os.widen(' '); | |
2136 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2137 | __os.fill(__space); | |
7703dc47 | 2138 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d BK |
2139 | |
2140 | __os << __x.a() << __space << __x.b(); | |
2141 | ||
2142 | __os.flags(__flags); | |
2143 | __os.fill(__fill); | |
2144 | __os.precision(__precision); | |
2145 | return __os; | |
2146 | } | |
2147 | ||
2148 | template<typename _RealType, typename _CharT, typename _Traits> | |
2149 | std::basic_istream<_CharT, _Traits>& | |
2150 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2151 | cauchy_distribution<_RealType>& __x) | |
2152 | { | |
2153 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
2154 | typedef typename __istream_type::ios_base __ios_base; | |
2155 | ||
2156 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2157 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2158 | ||
2159 | _RealType __a, __b; | |
2160 | __is >> __a >> __b; | |
2161 | __x.param(typename cauchy_distribution<_RealType>:: | |
2162 | param_type(__a, __b)); | |
2163 | ||
2164 | __is.flags(__flags); | |
2165 | return __is; | |
2166 | } | |
2167 | ||
2168 | ||
7b93bdde UD |
2169 | template<typename _RealType> |
2170 | template<typename _ForwardIterator, | |
2171 | typename _UniformRandomNumberGenerator> | |
2172 | void | |
2173 | std::fisher_f_distribution<_RealType>:: | |
2174 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2175 | _UniformRandomNumberGenerator& __urng) | |
2176 | { | |
2177 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2178 | while (__f != __t) | |
2179 | *__f++ = ((_M_gd_x(__urng) * n()) / (_M_gd_y(__urng) * m())); | |
2180 | } | |
2181 | ||
2182 | template<typename _RealType> | |
2183 | template<typename _ForwardIterator, | |
2184 | typename _UniformRandomNumberGenerator> | |
2185 | void | |
2186 | std::fisher_f_distribution<_RealType>:: | |
2187 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2188 | _UniformRandomNumberGenerator& __urng, | |
2189 | const param_type& __p) | |
2190 | { | |
2191 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2192 | typedef typename std::gamma_distribution<result_type>::param_type | |
2193 | param_type; | |
2194 | param_type __p1(__p.m() / 2); | |
2195 | param_type __p2(__p.n() / 2); | |
2196 | while (__f != __t) | |
2197 | *__f++ = ((_M_gd_x(__urng, __p1) * n()) | |
2198 | / (_M_gd_y(__urng, __p2) * m())); | |
2199 | } | |
2200 | ||
8e79468d BK |
2201 | template<typename _RealType, typename _CharT, typename _Traits> |
2202 | std::basic_ostream<_CharT, _Traits>& | |
2203 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2204 | const fisher_f_distribution<_RealType>& __x) | |
2205 | { | |
2206 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
2207 | typedef typename __ostream_type::ios_base __ios_base; | |
2208 | ||
2209 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2210 | const _CharT __fill = __os.fill(); | |
2211 | const std::streamsize __precision = __os.precision(); | |
2212 | const _CharT __space = __os.widen(' '); | |
2213 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2214 | __os.fill(__space); | |
7703dc47 | 2215 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d | 2216 | |
f9b09dec PC |
2217 | __os << __x.m() << __space << __x.n() |
2218 | << __space << __x._M_gd_x << __space << __x._M_gd_y; | |
8e79468d BK |
2219 | |
2220 | __os.flags(__flags); | |
2221 | __os.fill(__fill); | |
2222 | __os.precision(__precision); | |
2223 | return __os; | |
2224 | } | |
2225 | ||
2226 | template<typename _RealType, typename _CharT, typename _Traits> | |
2227 | std::basic_istream<_CharT, _Traits>& | |
2228 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2229 | fisher_f_distribution<_RealType>& __x) | |
2230 | { | |
2231 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
2232 | typedef typename __istream_type::ios_base __ios_base; | |
2233 | ||
2234 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2235 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2236 | ||
2237 | _RealType __m, __n; | |
f9b09dec | 2238 | __is >> __m >> __n >> __x._M_gd_x >> __x._M_gd_y; |
8e79468d BK |
2239 | __x.param(typename fisher_f_distribution<_RealType>:: |
2240 | param_type(__m, __n)); | |
2241 | ||
2242 | __is.flags(__flags); | |
2243 | return __is; | |
2244 | } | |
2245 | ||
2246 | ||
7b93bdde UD |
2247 | template<typename _RealType> |
2248 | template<typename _ForwardIterator, | |
2249 | typename _UniformRandomNumberGenerator> | |
2250 | void | |
2251 | std::student_t_distribution<_RealType>:: | |
2252 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2253 | _UniformRandomNumberGenerator& __urng) | |
2254 | { | |
2255 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2256 | while (__f != __t) | |
2257 | *__f++ = _M_nd(__urng) * std::sqrt(n() / _M_gd(__urng)); | |
2258 | } | |
2259 | ||
2260 | template<typename _RealType> | |
2261 | template<typename _ForwardIterator, | |
2262 | typename _UniformRandomNumberGenerator> | |
2263 | void | |
2264 | std::student_t_distribution<_RealType>:: | |
2265 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2266 | _UniformRandomNumberGenerator& __urng, | |
2267 | const param_type& __p) | |
2268 | { | |
2269 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2270 | typename std::gamma_distribution<result_type>::param_type | |
2271 | __p2(__p.n() / 2, 2); | |
2272 | while (__f != __t) | |
2273 | *__f++ = _M_nd(__urng) * std::sqrt(__p.n() / _M_gd(__urng, __p2)); | |
2274 | } | |
2275 | ||
8e79468d BK |
2276 | template<typename _RealType, typename _CharT, typename _Traits> |
2277 | std::basic_ostream<_CharT, _Traits>& | |
2278 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2279 | const student_t_distribution<_RealType>& __x) | |
2280 | { | |
2281 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
2282 | typedef typename __ostream_type::ios_base __ios_base; | |
2283 | ||
2284 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2285 | const _CharT __fill = __os.fill(); | |
2286 | const std::streamsize __precision = __os.precision(); | |
2287 | const _CharT __space = __os.widen(' '); | |
2288 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2289 | __os.fill(__space); | |
7703dc47 | 2290 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d | 2291 | |
f9b09dec | 2292 | __os << __x.n() << __space << __x._M_nd << __space << __x._M_gd; |
8e79468d BK |
2293 | |
2294 | __os.flags(__flags); | |
2295 | __os.fill(__fill); | |
2296 | __os.precision(__precision); | |
2297 | return __os; | |
2298 | } | |
2299 | ||
2300 | template<typename _RealType, typename _CharT, typename _Traits> | |
2301 | std::basic_istream<_CharT, _Traits>& | |
2302 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2303 | student_t_distribution<_RealType>& __x) | |
2304 | { | |
2305 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
2306 | typedef typename __istream_type::ios_base __ios_base; | |
2307 | ||
2308 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2309 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2310 | ||
2311 | _RealType __n; | |
f9b09dec | 2312 | __is >> __n >> __x._M_nd >> __x._M_gd; |
8e79468d BK |
2313 | __x.param(typename student_t_distribution<_RealType>::param_type(__n)); |
2314 | ||
2315 | __is.flags(__flags); | |
2316 | return __is; | |
2317 | } | |
2318 | ||
2319 | ||
2320 | template<typename _RealType> | |
2321 | void | |
2322 | gamma_distribution<_RealType>::param_type:: | |
2323 | _M_initialize() | |
2324 | { | |
b01630bb PC |
2325 | _M_malpha = _M_alpha < 1.0 ? _M_alpha + _RealType(1.0) : _M_alpha; |
2326 | ||
2327 | const _RealType __a1 = _M_malpha - _RealType(1.0) / _RealType(3.0); | |
2328 | _M_a2 = _RealType(1.0) / std::sqrt(_RealType(9.0) * __a1); | |
8e79468d BK |
2329 | } |
2330 | ||
2331 | /** | |
b01630bb PC |
2332 | * Marsaglia, G. and Tsang, W. W. |
2333 | * "A Simple Method for Generating Gamma Variables" | |
2334 | * ACM Transactions on Mathematical Software, 26, 3, 363-372, 2000. | |
8e79468d BK |
2335 | */ |
2336 | template<typename _RealType> | |
2337 | template<typename _UniformRandomNumberGenerator> | |
2338 | typename gamma_distribution<_RealType>::result_type | |
2339 | gamma_distribution<_RealType>:: | |
2340 | operator()(_UniformRandomNumberGenerator& __urng, | |
2341 | const param_type& __param) | |
2342 | { | |
8e79468d BK |
2343 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> |
2344 | __aurng(__urng); | |
2345 | ||
b01630bb PC |
2346 | result_type __u, __v, __n; |
2347 | const result_type __a1 = (__param._M_malpha | |
2348 | - _RealType(1.0) / _RealType(3.0)); | |
8e79468d | 2349 | |
b01630bb PC |
2350 | do |
2351 | { | |
8e79468d BK |
2352 | do |
2353 | { | |
b01630bb PC |
2354 | __n = _M_nd(__urng); |
2355 | __v = result_type(1.0) + __param._M_a2 * __n; | |
8e79468d | 2356 | } |
b01630bb PC |
2357 | while (__v <= 0.0); |
2358 | ||
2359 | __v = __v * __v * __v; | |
2360 | __u = __aurng(); | |
8e79468d | 2361 | } |
957221f5 | 2362 | while (__u > result_type(1.0) - 0.0331 * __n * __n * __n * __n |
b01630bb PC |
2363 | && (std::log(__u) > (0.5 * __n * __n + __a1 |
2364 | * (1.0 - __v + std::log(__v))))); | |
2365 | ||
2366 | if (__param.alpha() == __param._M_malpha) | |
2367 | return __a1 * __v * __param.beta(); | |
8e79468d BK |
2368 | else |
2369 | { | |
8e79468d | 2370 | do |
b01630bb PC |
2371 | __u = __aurng(); |
2372 | while (__u == 0.0); | |
2373 | ||
2374 | return (std::pow(__u, result_type(1.0) / __param.alpha()) | |
2375 | * __a1 * __v * __param.beta()); | |
8e79468d | 2376 | } |
8e79468d BK |
2377 | } |
2378 | ||
7b93bdde UD |
2379 | template<typename _RealType> |
2380 | template<typename _ForwardIterator, | |
2381 | typename _UniformRandomNumberGenerator> | |
2382 | void | |
2383 | gamma_distribution<_RealType>:: | |
2384 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2385 | _UniformRandomNumberGenerator& __urng, | |
2386 | const param_type& __param) | |
2387 | { | |
2388 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2389 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
2390 | __aurng(__urng); | |
2391 | ||
2392 | result_type __u, __v, __n; | |
2393 | const result_type __a1 = (__param._M_malpha | |
2394 | - _RealType(1.0) / _RealType(3.0)); | |
2395 | ||
2396 | if (__param.alpha() == __param._M_malpha) | |
2397 | while (__f != __t) | |
2398 | { | |
2399 | do | |
2400 | { | |
2401 | do | |
2402 | { | |
2403 | __n = _M_nd(__urng); | |
2404 | __v = result_type(1.0) + __param._M_a2 * __n; | |
2405 | } | |
2406 | while (__v <= 0.0); | |
2407 | ||
2408 | __v = __v * __v * __v; | |
2409 | __u = __aurng(); | |
2410 | } | |
eda0ab6e | 2411 | while (__u > result_type(1.0) - 0.331 * __n * __n * __n * __n |
7b93bdde UD |
2412 | && (std::log(__u) > (0.5 * __n * __n + __a1 |
2413 | * (1.0 - __v + std::log(__v))))); | |
2414 | ||
2415 | *__f++ = __a1 * __v * __param.beta(); | |
2416 | } | |
2417 | else | |
2418 | while (__f != __t) | |
2419 | { | |
2420 | do | |
2421 | { | |
2422 | do | |
2423 | { | |
2424 | __n = _M_nd(__urng); | |
2425 | __v = result_type(1.0) + __param._M_a2 * __n; | |
2426 | } | |
2427 | while (__v <= 0.0); | |
2428 | ||
2429 | __v = __v * __v * __v; | |
2430 | __u = __aurng(); | |
2431 | } | |
eda0ab6e | 2432 | while (__u > result_type(1.0) - 0.331 * __n * __n * __n * __n |
7b93bdde UD |
2433 | && (std::log(__u) > (0.5 * __n * __n + __a1 |
2434 | * (1.0 - __v + std::log(__v))))); | |
2435 | ||
2436 | do | |
2437 | __u = __aurng(); | |
2438 | while (__u == 0.0); | |
2439 | ||
2440 | *__f++ = (std::pow(__u, result_type(1.0) / __param.alpha()) | |
2441 | * __a1 * __v * __param.beta()); | |
2442 | } | |
2443 | } | |
2444 | ||
8e79468d BK |
2445 | template<typename _RealType, typename _CharT, typename _Traits> |
2446 | std::basic_ostream<_CharT, _Traits>& | |
2447 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2448 | const gamma_distribution<_RealType>& __x) | |
2449 | { | |
2450 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
2451 | typedef typename __ostream_type::ios_base __ios_base; | |
2452 | ||
2453 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2454 | const _CharT __fill = __os.fill(); | |
2455 | const std::streamsize __precision = __os.precision(); | |
2456 | const _CharT __space = __os.widen(' '); | |
2457 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2458 | __os.fill(__space); | |
7703dc47 | 2459 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d | 2460 | |
b01630bb PC |
2461 | __os << __x.alpha() << __space << __x.beta() |
2462 | << __space << __x._M_nd; | |
8e79468d BK |
2463 | |
2464 | __os.flags(__flags); | |
2465 | __os.fill(__fill); | |
2466 | __os.precision(__precision); | |
2467 | return __os; | |
2468 | } | |
2469 | ||
2470 | template<typename _RealType, typename _CharT, typename _Traits> | |
2471 | std::basic_istream<_CharT, _Traits>& | |
2472 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2473 | gamma_distribution<_RealType>& __x) | |
2474 | { | |
2475 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
2476 | typedef typename __istream_type::ios_base __ios_base; | |
2477 | ||
2478 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2479 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2480 | ||
ed2807f4 | 2481 | _RealType __alpha_val, __beta_val; |
b01630bb | 2482 | __is >> __alpha_val >> __beta_val >> __x._M_nd; |
8e79468d | 2483 | __x.param(typename gamma_distribution<_RealType>:: |
ed2807f4 | 2484 | param_type(__alpha_val, __beta_val)); |
8e79468d BK |
2485 | |
2486 | __is.flags(__flags); | |
2487 | return __is; | |
2488 | } | |
2489 | ||
2490 | ||
b01630bb PC |
2491 | template<typename _RealType> |
2492 | template<typename _UniformRandomNumberGenerator> | |
2493 | typename weibull_distribution<_RealType>::result_type | |
2494 | weibull_distribution<_RealType>:: | |
2495 | operator()(_UniformRandomNumberGenerator& __urng, | |
2496 | const param_type& __p) | |
2497 | { | |
2498 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
2499 | __aurng(__urng); | |
c2d9083d | 2500 | return __p.b() * std::pow(-std::log(result_type(1) - __aurng()), |
b01630bb PC |
2501 | result_type(1) / __p.a()); |
2502 | } | |
2503 | ||
7b93bdde UD |
2504 | template<typename _RealType> |
2505 | template<typename _ForwardIterator, | |
2506 | typename _UniformRandomNumberGenerator> | |
2507 | void | |
2508 | weibull_distribution<_RealType>:: | |
2509 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2510 | _UniformRandomNumberGenerator& __urng, | |
2511 | const param_type& __p) | |
2512 | { | |
2513 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2514 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
2515 | __aurng(__urng); | |
c2d9083d | 2516 | auto __inv_a = result_type(1) / __p.a(); |
7b93bdde UD |
2517 | |
2518 | while (__f != __t) | |
c2d9083d HY |
2519 | *__f++ = __p.b() * std::pow(-std::log(result_type(1) - __aurng()), |
2520 | __inv_a); | |
7b93bdde UD |
2521 | } |
2522 | ||
8e79468d BK |
2523 | template<typename _RealType, typename _CharT, typename _Traits> |
2524 | std::basic_ostream<_CharT, _Traits>& | |
2525 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2526 | const weibull_distribution<_RealType>& __x) | |
2527 | { | |
2528 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
2529 | typedef typename __ostream_type::ios_base __ios_base; | |
2530 | ||
2531 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2532 | const _CharT __fill = __os.fill(); | |
2533 | const std::streamsize __precision = __os.precision(); | |
2534 | const _CharT __space = __os.widen(' '); | |
2535 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2536 | __os.fill(__space); | |
7703dc47 | 2537 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d BK |
2538 | |
2539 | __os << __x.a() << __space << __x.b(); | |
2540 | ||
2541 | __os.flags(__flags); | |
2542 | __os.fill(__fill); | |
2543 | __os.precision(__precision); | |
2544 | return __os; | |
2545 | } | |
2546 | ||
2547 | template<typename _RealType, typename _CharT, typename _Traits> | |
2548 | std::basic_istream<_CharT, _Traits>& | |
2549 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2550 | weibull_distribution<_RealType>& __x) | |
2551 | { | |
2552 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
2553 | typedef typename __istream_type::ios_base __ios_base; | |
2554 | ||
2555 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2556 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2557 | ||
2558 | _RealType __a, __b; | |
2559 | __is >> __a >> __b; | |
2560 | __x.param(typename weibull_distribution<_RealType>:: | |
2561 | param_type(__a, __b)); | |
2562 | ||
2563 | __is.flags(__flags); | |
2564 | return __is; | |
2565 | } | |
2566 | ||
2567 | ||
2568 | template<typename _RealType> | |
2569 | template<typename _UniformRandomNumberGenerator> | |
2570 | typename extreme_value_distribution<_RealType>::result_type | |
2571 | extreme_value_distribution<_RealType>:: | |
2572 | operator()(_UniformRandomNumberGenerator& __urng, | |
2573 | const param_type& __p) | |
2574 | { | |
2575 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
2576 | __aurng(__urng); | |
c2d9083d HY |
2577 | return __p.a() - __p.b() * std::log(-std::log(result_type(1) |
2578 | - __aurng())); | |
8e79468d BK |
2579 | } |
2580 | ||
7b93bdde UD |
2581 | template<typename _RealType> |
2582 | template<typename _ForwardIterator, | |
2583 | typename _UniformRandomNumberGenerator> | |
2584 | void | |
2585 | extreme_value_distribution<_RealType>:: | |
2586 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2587 | _UniformRandomNumberGenerator& __urng, | |
2588 | const param_type& __p) | |
2589 | { | |
2590 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2591 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
2592 | __aurng(__urng); | |
2593 | ||
2594 | while (__f != __t) | |
c2d9083d HY |
2595 | *__f++ = __p.a() - __p.b() * std::log(-std::log(result_type(1) |
2596 | - __aurng())); | |
7b93bdde UD |
2597 | } |
2598 | ||
8e79468d BK |
2599 | template<typename _RealType, typename _CharT, typename _Traits> |
2600 | std::basic_ostream<_CharT, _Traits>& | |
2601 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2602 | const extreme_value_distribution<_RealType>& __x) | |
2603 | { | |
2604 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
2605 | typedef typename __ostream_type::ios_base __ios_base; | |
2606 | ||
2607 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2608 | const _CharT __fill = __os.fill(); | |
2609 | const std::streamsize __precision = __os.precision(); | |
2610 | const _CharT __space = __os.widen(' '); | |
2611 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2612 | __os.fill(__space); | |
7703dc47 | 2613 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d BK |
2614 | |
2615 | __os << __x.a() << __space << __x.b(); | |
2616 | ||
2617 | __os.flags(__flags); | |
2618 | __os.fill(__fill); | |
2619 | __os.precision(__precision); | |
2620 | return __os; | |
2621 | } | |
2622 | ||
2623 | template<typename _RealType, typename _CharT, typename _Traits> | |
2624 | std::basic_istream<_CharT, _Traits>& | |
2625 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2626 | extreme_value_distribution<_RealType>& __x) | |
2627 | { | |
2628 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
2629 | typedef typename __istream_type::ios_base __ios_base; | |
2630 | ||
2631 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2632 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2633 | ||
2634 | _RealType __a, __b; | |
2635 | __is >> __a >> __b; | |
2636 | __x.param(typename extreme_value_distribution<_RealType>:: | |
2637 | param_type(__a, __b)); | |
2638 | ||
2639 | __is.flags(__flags); | |
2640 | return __is; | |
2641 | } | |
2642 | ||
2643 | ||
2644 | template<typename _IntType> | |
2645 | void | |
2646 | discrete_distribution<_IntType>::param_type:: | |
2647 | _M_initialize() | |
2648 | { | |
2649 | if (_M_prob.size() < 2) | |
2650 | { | |
2651 | _M_prob.clear(); | |
8e79468d BK |
2652 | return; |
2653 | } | |
2654 | ||
f8dd9e0d PC |
2655 | const double __sum = std::accumulate(_M_prob.begin(), |
2656 | _M_prob.end(), 0.0); | |
2657 | // Now normalize the probabilites. | |
60f3a59f PC |
2658 | __detail::__normalize(_M_prob.begin(), _M_prob.end(), _M_prob.begin(), |
2659 | __sum); | |
f8dd9e0d PC |
2660 | // Accumulate partial sums. |
2661 | _M_cp.reserve(_M_prob.size()); | |
8e79468d BK |
2662 | std::partial_sum(_M_prob.begin(), _M_prob.end(), |
2663 | std::back_inserter(_M_cp)); | |
f8dd9e0d | 2664 | // Make sure the last cumulative probability is one. |
8e79468d BK |
2665 | _M_cp[_M_cp.size() - 1] = 1.0; |
2666 | } | |
2667 | ||
2668 | template<typename _IntType> | |
2669 | template<typename _Func> | |
2670 | discrete_distribution<_IntType>::param_type:: | |
f8dd9e0d | 2671 | param_type(size_t __nw, double __xmin, double __xmax, _Func __fw) |
8e79468d BK |
2672 | : _M_prob(), _M_cp() |
2673 | { | |
f8dd9e0d PC |
2674 | const size_t __n = __nw == 0 ? 1 : __nw; |
2675 | const double __delta = (__xmax - __xmin) / __n; | |
2676 | ||
2677 | _M_prob.reserve(__n); | |
2678 | for (size_t __k = 0; __k < __nw; ++__k) | |
2679 | _M_prob.push_back(__fw(__xmin + __k * __delta + 0.5 * __delta)); | |
8e79468d BK |
2680 | |
2681 | _M_initialize(); | |
2682 | } | |
2683 | ||
2684 | template<typename _IntType> | |
2685 | template<typename _UniformRandomNumberGenerator> | |
2686 | typename discrete_distribution<_IntType>::result_type | |
2687 | discrete_distribution<_IntType>:: | |
2688 | operator()(_UniformRandomNumberGenerator& __urng, | |
2689 | const param_type& __param) | |
2690 | { | |
879b9073 PC |
2691 | if (__param._M_cp.empty()) |
2692 | return result_type(0); | |
2693 | ||
9b88236b | 2694 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> |
8e79468d BK |
2695 | __aurng(__urng); |
2696 | ||
2697 | const double __p = __aurng(); | |
2698 | auto __pos = std::lower_bound(__param._M_cp.begin(), | |
2699 | __param._M_cp.end(), __p); | |
8e79468d | 2700 | |
f8dd9e0d | 2701 | return __pos - __param._M_cp.begin(); |
8e79468d BK |
2702 | } |
2703 | ||
7b93bdde UD |
2704 | template<typename _IntType> |
2705 | template<typename _ForwardIterator, | |
2706 | typename _UniformRandomNumberGenerator> | |
2707 | void | |
2708 | discrete_distribution<_IntType>:: | |
2709 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2710 | _UniformRandomNumberGenerator& __urng, | |
2711 | const param_type& __param) | |
2712 | { | |
2713 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2714 | ||
2715 | if (__param._M_cp.empty()) | |
2716 | { | |
2717 | while (__f != __t) | |
2718 | *__f++ = result_type(0); | |
2719 | return; | |
2720 | } | |
2721 | ||
2722 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
2723 | __aurng(__urng); | |
2724 | ||
2725 | while (__f != __t) | |
2726 | { | |
2727 | const double __p = __aurng(); | |
2728 | auto __pos = std::lower_bound(__param._M_cp.begin(), | |
2729 | __param._M_cp.end(), __p); | |
2730 | ||
2731 | *__f++ = __pos - __param._M_cp.begin(); | |
2732 | } | |
2733 | } | |
2734 | ||
8e79468d BK |
2735 | template<typename _IntType, typename _CharT, typename _Traits> |
2736 | std::basic_ostream<_CharT, _Traits>& | |
2737 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2738 | const discrete_distribution<_IntType>& __x) | |
2739 | { | |
2740 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
2741 | typedef typename __ostream_type::ios_base __ios_base; | |
2742 | ||
2743 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2744 | const _CharT __fill = __os.fill(); | |
2745 | const std::streamsize __precision = __os.precision(); | |
2746 | const _CharT __space = __os.widen(' '); | |
2747 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2748 | __os.fill(__space); | |
7703dc47 | 2749 | __os.precision(std::numeric_limits<double>::max_digits10); |
8e79468d BK |
2750 | |
2751 | std::vector<double> __prob = __x.probabilities(); | |
2752 | __os << __prob.size(); | |
2753 | for (auto __dit = __prob.begin(); __dit != __prob.end(); ++__dit) | |
2754 | __os << __space << *__dit; | |
2755 | ||
2756 | __os.flags(__flags); | |
2757 | __os.fill(__fill); | |
2758 | __os.precision(__precision); | |
2759 | return __os; | |
2760 | } | |
2761 | ||
2762 | template<typename _IntType, typename _CharT, typename _Traits> | |
2763 | std::basic_istream<_CharT, _Traits>& | |
2764 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2765 | discrete_distribution<_IntType>& __x) | |
2766 | { | |
2767 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
2768 | typedef typename __istream_type::ios_base __ios_base; | |
2769 | ||
2770 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2771 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2772 | ||
2773 | size_t __n; | |
2774 | __is >> __n; | |
2775 | ||
2776 | std::vector<double> __prob_vec; | |
f8dd9e0d | 2777 | __prob_vec.reserve(__n); |
8e79468d BK |
2778 | for (; __n != 0; --__n) |
2779 | { | |
2780 | double __prob; | |
2781 | __is >> __prob; | |
2782 | __prob_vec.push_back(__prob); | |
2783 | } | |
2784 | ||
2785 | __x.param(typename discrete_distribution<_IntType>:: | |
2786 | param_type(__prob_vec.begin(), __prob_vec.end())); | |
2787 | ||
2788 | __is.flags(__flags); | |
2789 | return __is; | |
2790 | } | |
2791 | ||
2792 | ||
2793 | template<typename _RealType> | |
2794 | void | |
2795 | piecewise_constant_distribution<_RealType>::param_type:: | |
2796 | _M_initialize() | |
2797 | { | |
879b9073 PC |
2798 | if (_M_int.size() < 2 |
2799 | || (_M_int.size() == 2 | |
2800 | && _M_int[0] == _RealType(0) | |
2801 | && _M_int[1] == _RealType(1))) | |
8e79468d BK |
2802 | { |
2803 | _M_int.clear(); | |
8e79468d | 2804 | _M_den.clear(); |
8e79468d BK |
2805 | return; |
2806 | } | |
2807 | ||
f8dd9e0d PC |
2808 | const double __sum = std::accumulate(_M_den.begin(), |
2809 | _M_den.end(), 0.0); | |
8e79468d | 2810 | |
60f3a59f PC |
2811 | __detail::__normalize(_M_den.begin(), _M_den.end(), _M_den.begin(), |
2812 | __sum); | |
f8dd9e0d PC |
2813 | |
2814 | _M_cp.reserve(_M_den.size()); | |
2815 | std::partial_sum(_M_den.begin(), _M_den.end(), | |
2816 | std::back_inserter(_M_cp)); | |
2817 | ||
2818 | // Make sure the last cumulative probability is one. | |
8e79468d | 2819 | _M_cp[_M_cp.size() - 1] = 1.0; |
f8dd9e0d PC |
2820 | |
2821 | for (size_t __k = 0; __k < _M_den.size(); ++__k) | |
2822 | _M_den[__k] /= _M_int[__k + 1] - _M_int[__k]; | |
8e79468d BK |
2823 | } |
2824 | ||
8e79468d BK |
2825 | template<typename _RealType> |
2826 | template<typename _InputIteratorB, typename _InputIteratorW> | |
2827 | piecewise_constant_distribution<_RealType>::param_type:: | |
2828 | param_type(_InputIteratorB __bbegin, | |
2829 | _InputIteratorB __bend, | |
2830 | _InputIteratorW __wbegin) | |
2831 | : _M_int(), _M_den(), _M_cp() | |
2832 | { | |
f8dd9e0d | 2833 | if (__bbegin != __bend) |
8e79468d | 2834 | { |
f8dd9e0d | 2835 | for (;;) |
8e79468d | 2836 | { |
f8dd9e0d PC |
2837 | _M_int.push_back(*__bbegin); |
2838 | ++__bbegin; | |
2839 | if (__bbegin == __bend) | |
2840 | break; | |
2841 | ||
8e79468d BK |
2842 | _M_den.push_back(*__wbegin); |
2843 | ++__wbegin; | |
2844 | } | |
2845 | } | |
8e79468d BK |
2846 | |
2847 | _M_initialize(); | |
2848 | } | |
2849 | ||
2850 | template<typename _RealType> | |
2851 | template<typename _Func> | |
2852 | piecewise_constant_distribution<_RealType>::param_type:: | |
f8dd9e0d | 2853 | param_type(initializer_list<_RealType> __bl, _Func __fw) |
8e79468d BK |
2854 | : _M_int(), _M_den(), _M_cp() |
2855 | { | |
f8dd9e0d PC |
2856 | _M_int.reserve(__bl.size()); |
2857 | for (auto __biter = __bl.begin(); __biter != __bl.end(); ++__biter) | |
8e79468d BK |
2858 | _M_int.push_back(*__biter); |
2859 | ||
f8dd9e0d PC |
2860 | _M_den.reserve(_M_int.size() - 1); |
2861 | for (size_t __k = 0; __k < _M_int.size() - 1; ++__k) | |
2862 | _M_den.push_back(__fw(0.5 * (_M_int[__k + 1] + _M_int[__k]))); | |
8e79468d BK |
2863 | |
2864 | _M_initialize(); | |
2865 | } | |
2866 | ||
2867 | template<typename _RealType> | |
2868 | template<typename _Func> | |
2869 | piecewise_constant_distribution<_RealType>::param_type:: | |
b01630bb | 2870 | param_type(size_t __nw, _RealType __xmin, _RealType __xmax, _Func __fw) |
8e79468d BK |
2871 | : _M_int(), _M_den(), _M_cp() |
2872 | { | |
f8dd9e0d PC |
2873 | const size_t __n = __nw == 0 ? 1 : __nw; |
2874 | const _RealType __delta = (__xmax - __xmin) / __n; | |
2875 | ||
2876 | _M_int.reserve(__n + 1); | |
2877 | for (size_t __k = 0; __k <= __nw; ++__k) | |
2878 | _M_int.push_back(__xmin + __k * __delta); | |
2879 | ||
2880 | _M_den.reserve(__n); | |
2881 | for (size_t __k = 0; __k < __nw; ++__k) | |
2882 | _M_den.push_back(__fw(_M_int[__k] + 0.5 * __delta)); | |
8e79468d BK |
2883 | |
2884 | _M_initialize(); | |
2885 | } | |
2886 | ||
2887 | template<typename _RealType> | |
2888 | template<typename _UniformRandomNumberGenerator> | |
2889 | typename piecewise_constant_distribution<_RealType>::result_type | |
2890 | piecewise_constant_distribution<_RealType>:: | |
2891 | operator()(_UniformRandomNumberGenerator& __urng, | |
2892 | const param_type& __param) | |
2893 | { | |
9b88236b | 2894 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> |
8e79468d BK |
2895 | __aurng(__urng); |
2896 | ||
2897 | const double __p = __aurng(); | |
879b9073 PC |
2898 | if (__param._M_cp.empty()) |
2899 | return __p; | |
2900 | ||
8e79468d BK |
2901 | auto __pos = std::lower_bound(__param._M_cp.begin(), |
2902 | __param._M_cp.end(), __p); | |
2903 | const size_t __i = __pos - __param._M_cp.begin(); | |
2904 | ||
f8dd9e0d PC |
2905 | const double __pref = __i > 0 ? __param._M_cp[__i - 1] : 0.0; |
2906 | ||
2907 | return __param._M_int[__i] + (__p - __pref) / __param._M_den[__i]; | |
8e79468d BK |
2908 | } |
2909 | ||
7b93bdde UD |
2910 | template<typename _RealType> |
2911 | template<typename _ForwardIterator, | |
2912 | typename _UniformRandomNumberGenerator> | |
2913 | void | |
2914 | piecewise_constant_distribution<_RealType>:: | |
2915 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2916 | _UniformRandomNumberGenerator& __urng, | |
2917 | const param_type& __param) | |
2918 | { | |
2919 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2920 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
2921 | __aurng(__urng); | |
2922 | ||
2923 | if (__param._M_cp.empty()) | |
2924 | { | |
2925 | while (__f != __t) | |
2926 | *__f++ = __aurng(); | |
2927 | return; | |
2928 | } | |
2929 | ||
2930 | while (__f != __t) | |
2931 | { | |
2932 | const double __p = __aurng(); | |
2933 | ||
2934 | auto __pos = std::lower_bound(__param._M_cp.begin(), | |
2935 | __param._M_cp.end(), __p); | |
2936 | const size_t __i = __pos - __param._M_cp.begin(); | |
2937 | ||
2938 | const double __pref = __i > 0 ? __param._M_cp[__i - 1] : 0.0; | |
2939 | ||
2940 | *__f++ = (__param._M_int[__i] | |
2941 | + (__p - __pref) / __param._M_den[__i]); | |
2942 | } | |
2943 | } | |
2944 | ||
8e79468d BK |
2945 | template<typename _RealType, typename _CharT, typename _Traits> |
2946 | std::basic_ostream<_CharT, _Traits>& | |
2947 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2948 | const piecewise_constant_distribution<_RealType>& __x) | |
2949 | { | |
2950 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
2951 | typedef typename __ostream_type::ios_base __ios_base; | |
2952 | ||
2953 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2954 | const _CharT __fill = __os.fill(); | |
2955 | const std::streamsize __precision = __os.precision(); | |
2956 | const _CharT __space = __os.widen(' '); | |
2957 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2958 | __os.fill(__space); | |
7703dc47 | 2959 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d BK |
2960 | |
2961 | std::vector<_RealType> __int = __x.intervals(); | |
2962 | __os << __int.size() - 1; | |
2963 | ||
2964 | for (auto __xit = __int.begin(); __xit != __int.end(); ++__xit) | |
2965 | __os << __space << *__xit; | |
2966 | ||
2967 | std::vector<double> __den = __x.densities(); | |
2968 | for (auto __dit = __den.begin(); __dit != __den.end(); ++__dit) | |
2969 | __os << __space << *__dit; | |
2970 | ||
2971 | __os.flags(__flags); | |
2972 | __os.fill(__fill); | |
2973 | __os.precision(__precision); | |
2974 | return __os; | |
2975 | } | |
2976 | ||
2977 | template<typename _RealType, typename _CharT, typename _Traits> | |
2978 | std::basic_istream<_CharT, _Traits>& | |
2979 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2980 | piecewise_constant_distribution<_RealType>& __x) | |
2981 | { | |
2982 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
2983 | typedef typename __istream_type::ios_base __ios_base; | |
2984 | ||
2985 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2986 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2987 | ||
2988 | size_t __n; | |
2989 | __is >> __n; | |
2990 | ||
2991 | std::vector<_RealType> __int_vec; | |
f8dd9e0d | 2992 | __int_vec.reserve(__n + 1); |
8e79468d BK |
2993 | for (size_t __i = 0; __i <= __n; ++__i) |
2994 | { | |
2995 | _RealType __int; | |
2996 | __is >> __int; | |
2997 | __int_vec.push_back(__int); | |
2998 | } | |
2999 | ||
3000 | std::vector<double> __den_vec; | |
f8dd9e0d | 3001 | __den_vec.reserve(__n); |
8e79468d BK |
3002 | for (size_t __i = 0; __i < __n; ++__i) |
3003 | { | |
3004 | double __den; | |
3005 | __is >> __den; | |
3006 | __den_vec.push_back(__den); | |
3007 | } | |
3008 | ||
3009 | __x.param(typename piecewise_constant_distribution<_RealType>:: | |
3010 | param_type(__int_vec.begin(), __int_vec.end(), __den_vec.begin())); | |
3011 | ||
3012 | __is.flags(__flags); | |
3013 | return __is; | |
3014 | } | |
3015 | ||
3016 | ||
3017 | template<typename _RealType> | |
3018 | void | |
3019 | piecewise_linear_distribution<_RealType>::param_type:: | |
3020 | _M_initialize() | |
3021 | { | |
879b9073 PC |
3022 | if (_M_int.size() < 2 |
3023 | || (_M_int.size() == 2 | |
3024 | && _M_int[0] == _RealType(0) | |
3025 | && _M_int[1] == _RealType(1) | |
3026 | && _M_den[0] == _M_den[1])) | |
8e79468d BK |
3027 | { |
3028 | _M_int.clear(); | |
8e79468d | 3029 | _M_den.clear(); |
8e79468d BK |
3030 | return; |
3031 | } | |
3032 | ||
3033 | double __sum = 0.0; | |
f8dd9e0d PC |
3034 | _M_cp.reserve(_M_int.size() - 1); |
3035 | _M_m.reserve(_M_int.size() - 1); | |
3036 | for (size_t __k = 0; __k < _M_int.size() - 1; ++__k) | |
8e79468d | 3037 | { |
f8dd9e0d PC |
3038 | const _RealType __delta = _M_int[__k + 1] - _M_int[__k]; |
3039 | __sum += 0.5 * (_M_den[__k + 1] + _M_den[__k]) * __delta; | |
8e79468d | 3040 | _M_cp.push_back(__sum); |
f8dd9e0d | 3041 | _M_m.push_back((_M_den[__k + 1] - _M_den[__k]) / __delta); |
8e79468d BK |
3042 | } |
3043 | ||
3044 | // Now normalize the densities... | |
60f3a59f PC |
3045 | __detail::__normalize(_M_den.begin(), _M_den.end(), _M_den.begin(), |
3046 | __sum); | |
8e79468d | 3047 | // ... and partial sums... |
60f3a59f | 3048 | __detail::__normalize(_M_cp.begin(), _M_cp.end(), _M_cp.begin(), __sum); |
8e79468d | 3049 | // ... and slopes. |
60f3a59f PC |
3050 | __detail::__normalize(_M_m.begin(), _M_m.end(), _M_m.begin(), __sum); |
3051 | ||
8e79468d BK |
3052 | // Make sure the last cumulative probablility is one. |
3053 | _M_cp[_M_cp.size() - 1] = 1.0; | |
f8dd9e0d | 3054 | } |
8e79468d BK |
3055 | |
3056 | template<typename _RealType> | |
3057 | template<typename _InputIteratorB, typename _InputIteratorW> | |
3058 | piecewise_linear_distribution<_RealType>::param_type:: | |
3059 | param_type(_InputIteratorB __bbegin, | |
3060 | _InputIteratorB __bend, | |
3061 | _InputIteratorW __wbegin) | |
3062 | : _M_int(), _M_den(), _M_cp(), _M_m() | |
3063 | { | |
3064 | for (; __bbegin != __bend; ++__bbegin, ++__wbegin) | |
3065 | { | |
3066 | _M_int.push_back(*__bbegin); | |
3067 | _M_den.push_back(*__wbegin); | |
3068 | } | |
3069 | ||
3070 | _M_initialize(); | |
3071 | } | |
3072 | ||
3073 | template<typename _RealType> | |
3074 | template<typename _Func> | |
3075 | piecewise_linear_distribution<_RealType>::param_type:: | |
f8dd9e0d | 3076 | param_type(initializer_list<_RealType> __bl, _Func __fw) |
8e79468d BK |
3077 | : _M_int(), _M_den(), _M_cp(), _M_m() |
3078 | { | |
f8dd9e0d PC |
3079 | _M_int.reserve(__bl.size()); |
3080 | _M_den.reserve(__bl.size()); | |
3081 | for (auto __biter = __bl.begin(); __biter != __bl.end(); ++__biter) | |
8e79468d BK |
3082 | { |
3083 | _M_int.push_back(*__biter); | |
3084 | _M_den.push_back(__fw(*__biter)); | |
3085 | } | |
3086 | ||
3087 | _M_initialize(); | |
3088 | } | |
3089 | ||
3090 | template<typename _RealType> | |
3091 | template<typename _Func> | |
3092 | piecewise_linear_distribution<_RealType>::param_type:: | |
f8dd9e0d | 3093 | param_type(size_t __nw, _RealType __xmin, _RealType __xmax, _Func __fw) |
8e79468d BK |
3094 | : _M_int(), _M_den(), _M_cp(), _M_m() |
3095 | { | |
f8dd9e0d PC |
3096 | const size_t __n = __nw == 0 ? 1 : __nw; |
3097 | const _RealType __delta = (__xmax - __xmin) / __n; | |
3098 | ||
3099 | _M_int.reserve(__n + 1); | |
3100 | _M_den.reserve(__n + 1); | |
3101 | for (size_t __k = 0; __k <= __nw; ++__k) | |
8e79468d | 3102 | { |
f8dd9e0d PC |
3103 | _M_int.push_back(__xmin + __k * __delta); |
3104 | _M_den.push_back(__fw(_M_int[__k] + __delta)); | |
8e79468d BK |
3105 | } |
3106 | ||
3107 | _M_initialize(); | |
3108 | } | |
3109 | ||
3110 | template<typename _RealType> | |
3111 | template<typename _UniformRandomNumberGenerator> | |
3112 | typename piecewise_linear_distribution<_RealType>::result_type | |
3113 | piecewise_linear_distribution<_RealType>:: | |
3114 | operator()(_UniformRandomNumberGenerator& __urng, | |
3115 | const param_type& __param) | |
3116 | { | |
9b88236b | 3117 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> |
8e79468d BK |
3118 | __aurng(__urng); |
3119 | ||
3120 | const double __p = __aurng(); | |
879b9073 | 3121 | if (__param._M_cp.empty()) |
d3a73504 PC |
3122 | return __p; |
3123 | ||
8e79468d BK |
3124 | auto __pos = std::lower_bound(__param._M_cp.begin(), |
3125 | __param._M_cp.end(), __p); | |
3126 | const size_t __i = __pos - __param._M_cp.begin(); | |
f8dd9e0d PC |
3127 | |
3128 | const double __pref = __i > 0 ? __param._M_cp[__i - 1] : 0.0; | |
3129 | ||
8e79468d BK |
3130 | const double __a = 0.5 * __param._M_m[__i]; |
3131 | const double __b = __param._M_den[__i]; | |
f8dd9e0d PC |
3132 | const double __cm = __p - __pref; |
3133 | ||
3134 | _RealType __x = __param._M_int[__i]; | |
3135 | if (__a == 0) | |
3136 | __x += __cm / __b; | |
3137 | else | |
3138 | { | |
3139 | const double __d = __b * __b + 4.0 * __a * __cm; | |
3140 | __x += 0.5 * (std::sqrt(__d) - __b) / __a; | |
3141 | } | |
8e79468d | 3142 | |
f8dd9e0d | 3143 | return __x; |
8e79468d BK |
3144 | } |
3145 | ||
7b93bdde UD |
3146 | template<typename _RealType> |
3147 | template<typename _ForwardIterator, | |
3148 | typename _UniformRandomNumberGenerator> | |
3149 | void | |
3150 | piecewise_linear_distribution<_RealType>:: | |
3151 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
3152 | _UniformRandomNumberGenerator& __urng, | |
3153 | const param_type& __param) | |
3154 | { | |
3155 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
3156 | // We could duplicate everything from operator()... | |
3157 | while (__f != __t) | |
3158 | *__f++ = this->operator()(__urng, __param); | |
3159 | } | |
3160 | ||
8e79468d BK |
3161 | template<typename _RealType, typename _CharT, typename _Traits> |
3162 | std::basic_ostream<_CharT, _Traits>& | |
3163 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
3164 | const piecewise_linear_distribution<_RealType>& __x) | |
3165 | { | |
3166 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
3167 | typedef typename __ostream_type::ios_base __ios_base; | |
3168 | ||
3169 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
3170 | const _CharT __fill = __os.fill(); | |
3171 | const std::streamsize __precision = __os.precision(); | |
3172 | const _CharT __space = __os.widen(' '); | |
3173 | __os.flags(__ios_base::scientific | __ios_base::left); | |
3174 | __os.fill(__space); | |
7703dc47 | 3175 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
8e79468d BK |
3176 | |
3177 | std::vector<_RealType> __int = __x.intervals(); | |
3178 | __os << __int.size() - 1; | |
3179 | ||
3180 | for (auto __xit = __int.begin(); __xit != __int.end(); ++__xit) | |
3181 | __os << __space << *__xit; | |
3182 | ||
3183 | std::vector<double> __den = __x.densities(); | |
3184 | for (auto __dit = __den.begin(); __dit != __den.end(); ++__dit) | |
3185 | __os << __space << *__dit; | |
3186 | ||
3187 | __os.flags(__flags); | |
3188 | __os.fill(__fill); | |
3189 | __os.precision(__precision); | |
3190 | return __os; | |
3191 | } | |
3192 | ||
3193 | template<typename _RealType, typename _CharT, typename _Traits> | |
3194 | std::basic_istream<_CharT, _Traits>& | |
3195 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
3196 | piecewise_linear_distribution<_RealType>& __x) | |
3197 | { | |
3198 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
3199 | typedef typename __istream_type::ios_base __ios_base; | |
3200 | ||
3201 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
3202 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
3203 | ||
3204 | size_t __n; | |
3205 | __is >> __n; | |
3206 | ||
3207 | std::vector<_RealType> __int_vec; | |
f8dd9e0d | 3208 | __int_vec.reserve(__n + 1); |
8e79468d BK |
3209 | for (size_t __i = 0; __i <= __n; ++__i) |
3210 | { | |
3211 | _RealType __int; | |
3212 | __is >> __int; | |
3213 | __int_vec.push_back(__int); | |
3214 | } | |
3215 | ||
3216 | std::vector<double> __den_vec; | |
f8dd9e0d | 3217 | __den_vec.reserve(__n + 1); |
8e79468d BK |
3218 | for (size_t __i = 0; __i <= __n; ++__i) |
3219 | { | |
3220 | double __den; | |
3221 | __is >> __den; | |
3222 | __den_vec.push_back(__den); | |
3223 | } | |
3224 | ||
3225 | __x.param(typename piecewise_linear_distribution<_RealType>:: | |
3226 | param_type(__int_vec.begin(), __int_vec.end(), __den_vec.begin())); | |
3227 | ||
3228 | __is.flags(__flags); | |
3229 | return __is; | |
3230 | } | |
3231 | ||
3232 | ||
3233 | template<typename _IntType> | |
3234 | seed_seq::seed_seq(std::initializer_list<_IntType> __il) | |
3235 | { | |
3236 | for (auto __iter = __il.begin(); __iter != __il.end(); ++__iter) | |
b94f4bef | 3237 | _M_v.push_back(__detail::__mod<result_type, |
8e79468d BK |
3238 | __detail::_Shift<result_type, 32>::__value>(*__iter)); |
3239 | } | |
3240 | ||
3241 | template<typename _InputIterator> | |
3242 | seed_seq::seed_seq(_InputIterator __begin, _InputIterator __end) | |
3243 | { | |
3244 | for (_InputIterator __iter = __begin; __iter != __end; ++__iter) | |
b94f4bef | 3245 | _M_v.push_back(__detail::__mod<result_type, |
8e79468d BK |
3246 | __detail::_Shift<result_type, 32>::__value>(*__iter)); |
3247 | } | |
3248 | ||
3249 | template<typename _RandomAccessIterator> | |
3250 | void | |
3251 | seed_seq::generate(_RandomAccessIterator __begin, | |
3252 | _RandomAccessIterator __end) | |
3253 | { | |
3254 | typedef typename iterator_traits<_RandomAccessIterator>::value_type | |
6855fe45 | 3255 | _Type; |
8e79468d BK |
3256 | |
3257 | if (__begin == __end) | |
3258 | return; | |
3259 | ||
b94f4bef | 3260 | std::fill(__begin, __end, _Type(0x8b8b8b8bu)); |
8e79468d BK |
3261 | |
3262 | const size_t __n = __end - __begin; | |
3263 | const size_t __s = _M_v.size(); | |
3264 | const size_t __t = (__n >= 623) ? 11 | |
3265 | : (__n >= 68) ? 7 | |
3266 | : (__n >= 39) ? 5 | |
3267 | : (__n >= 7) ? 3 | |
3268 | : (__n - 1) / 2; | |
3269 | const size_t __p = (__n - __t) / 2; | |
3270 | const size_t __q = __p + __t; | |
58651854 | 3271 | const size_t __m = std::max(size_t(__s + 1), __n); |
8e79468d BK |
3272 | |
3273 | for (size_t __k = 0; __k < __m; ++__k) | |
3274 | { | |
6855fe45 PC |
3275 | _Type __arg = (__begin[__k % __n] |
3276 | ^ __begin[(__k + __p) % __n] | |
3277 | ^ __begin[(__k - 1) % __n]); | |
9d1f3ce6 | 3278 | _Type __r1 = __arg ^ (__arg >> 27); |
d9c257a7 PC |
3279 | __r1 = __detail::__mod<_Type, |
3280 | __detail::_Shift<_Type, 32>::__value>(1664525u * __r1); | |
6855fe45 | 3281 | _Type __r2 = __r1; |
8e79468d BK |
3282 | if (__k == 0) |
3283 | __r2 += __s; | |
3284 | else if (__k <= __s) | |
3285 | __r2 += __k % __n + _M_v[__k - 1]; | |
3286 | else | |
3287 | __r2 += __k % __n; | |
b94f4bef PC |
3288 | __r2 = __detail::__mod<_Type, |
3289 | __detail::_Shift<_Type, 32>::__value>(__r2); | |
8e79468d BK |
3290 | __begin[(__k + __p) % __n] += __r1; |
3291 | __begin[(__k + __q) % __n] += __r2; | |
3292 | __begin[__k % __n] = __r2; | |
3293 | } | |
3294 | ||
3295 | for (size_t __k = __m; __k < __m + __n; ++__k) | |
3296 | { | |
6855fe45 PC |
3297 | _Type __arg = (__begin[__k % __n] |
3298 | + __begin[(__k + __p) % __n] | |
3299 | + __begin[(__k - 1) % __n]); | |
9d1f3ce6 | 3300 | _Type __r3 = __arg ^ (__arg >> 27); |
d9c257a7 PC |
3301 | __r3 = __detail::__mod<_Type, |
3302 | __detail::_Shift<_Type, 32>::__value>(1566083941u * __r3); | |
6855fe45 | 3303 | _Type __r4 = __r3 - __k % __n; |
b94f4bef PC |
3304 | __r4 = __detail::__mod<_Type, |
3305 | __detail::_Shift<_Type, 32>::__value>(__r4); | |
82582df6 JS |
3306 | __begin[(__k + __p) % __n] ^= __r3; |
3307 | __begin[(__k + __q) % __n] ^= __r4; | |
8e79468d BK |
3308 | __begin[__k % __n] = __r4; |
3309 | } | |
3310 | } | |
3311 | ||
3312 | template<typename _RealType, size_t __bits, | |
3313 | typename _UniformRandomNumberGenerator> | |
3314 | _RealType | |
3315 | generate_canonical(_UniformRandomNumberGenerator& __urng) | |
3316 | { | |
1c4ff014 | 3317 | static_assert(std::is_floating_point<_RealType>::value, |
0cded43d | 3318 | "template argument must be a floating point type"); |
1c4ff014 | 3319 | |
8e79468d BK |
3320 | const size_t __b |
3321 | = std::min(static_cast<size_t>(std::numeric_limits<_RealType>::digits), | |
3322 | __bits); | |
3323 | const long double __r = static_cast<long double>(__urng.max()) | |
3324 | - static_cast<long double>(__urng.min()) + 1.0L; | |
b01630bb | 3325 | const size_t __log2r = std::log(__r) / std::log(2.0L); |
33df19a7 ESR |
3326 | const size_t __m = std::max<size_t>(1UL, |
3327 | (__b + __log2r - 1UL) / __log2r); | |
3328 | _RealType __ret; | |
92d85953 JW |
3329 | _RealType __sum = _RealType(0); |
3330 | _RealType __tmp = _RealType(1); | |
3331 | for (size_t __k = __m; __k != 0; --__k) | |
8e79468d | 3332 | { |
92d85953 JW |
3333 | __sum += _RealType(__urng() - __urng.min()) * __tmp; |
3334 | __tmp *= __r; | |
3335 | } | |
3336 | __ret = __sum / __tmp; | |
3337 | if (__builtin_expect(__ret >= _RealType(1), 0)) | |
3338 | { | |
3339 | #if _GLIBCXX_USE_C99_MATH_TR1 | |
3340 | __ret = std::nextafter(_RealType(1), _RealType(0)); | |
3341 | #else | |
3342 | __ret = _RealType(1) | |
3343 | - std::numeric_limits<_RealType>::epsilon() / _RealType(2); | |
3344 | #endif | |
8e79468d | 3345 | } |
33df19a7 | 3346 | return __ret; |
8e79468d | 3347 | } |
12ffa228 BK |
3348 | |
3349 | _GLIBCXX_END_NAMESPACE_VERSION | |
3350 | } // namespace | |
06f29237 PC |
3351 | |
3352 | #endif |