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fca66f47 | 1 | // random number generation (out of line) -*- C++ -*- |
2 | ||
f1717362 | 3 | // Copyright (C) 2009-2016 Free Software Foundation, Inc. |
fca66f47 | 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 | |
6bc9506f | 8 | // Free Software Foundation; either version 3, or (at your option) |
fca66f47 | 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 | ||
6bc9506f | 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. | |
fca66f47 | 19 | |
6bc9506f | 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/>. | |
fca66f47 | 24 | |
25 | /** @file bits/random.tcc | |
26 | * This is an internal header file, included by other library headers. | |
5846aeac | 27 | * Do not attempt to use it directly. @headername{random} |
fca66f47 | 28 | */ |
29 | ||
22688974 | 30 | #ifndef _RANDOM_TCC |
31 | #define _RANDOM_TCC 1 | |
32 | ||
5f94d8fe | 33 | #include <numeric> // std::accumulate and std::partial_sum |
fca66f47 | 34 | |
2948dd21 | 35 | namespace std _GLIBCXX_VISIBILITY(default) |
36 | { | |
fca66f47 | 37 | /* |
38 | * (Further) implementation-space details. | |
39 | */ | |
40 | namespace __detail | |
41 | { | |
2948dd21 | 42 | _GLIBCXX_BEGIN_NAMESPACE_VERSION |
43 | ||
1a5394ea | 44 | // General case for x = (ax + c) mod m -- use Schrage's algorithm |
45 | // to avoid integer overflow. | |
fca66f47 | 46 | // |
47 | // Preconditions: a > 0, m > 0. | |
48 | // | |
1a5394ea | 49 | // Note: only works correctly for __m % __a < __m / __a. |
ccb188ea | 50 | template<typename _Tp, _Tp __m, _Tp __a, _Tp __c> |
1a5394ea | 51 | _Tp |
52 | _Mod<_Tp, __m, __a, __c, false, true>:: | |
53 | __calc(_Tp __x) | |
fca66f47 | 54 | { |
1a5394ea | 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 | } | |
5f94d8fe | 80 | |
3ec419bf | 81 | template<typename _InputIterator, typename _OutputIterator, |
8ffda4f4 | 82 | typename _Tp> |
3ec419bf | 83 | _OutputIterator |
8ffda4f4 | 84 | __normalize(_InputIterator __first, _InputIterator __last, |
85 | _OutputIterator __result, const _Tp& __factor) | |
3ec419bf | 86 | { |
87 | for (; __first != __last; ++__first, ++__result) | |
8ffda4f4 | 88 | *__result = *__first / __factor; |
3ec419bf | 89 | return __result; |
90 | } | |
2948dd21 | 91 | |
92 | _GLIBCXX_END_NAMESPACE_VERSION | |
fca66f47 | 93 | } // namespace __detail |
94 | ||
2948dd21 | 95 | _GLIBCXX_BEGIN_NAMESPACE_VERSION |
8f1349db | 96 | |
97 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m> | |
c0000147 | 98 | constexpr _UIntType |
8f1349db | 99 | linear_congruential_engine<_UIntType, __a, __c, __m>::multiplier; |
100 | ||
101 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m> | |
c0000147 | 102 | constexpr _UIntType |
8f1349db | 103 | linear_congruential_engine<_UIntType, __a, __c, __m>::increment; |
104 | ||
105 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m> | |
c0000147 | 106 | constexpr _UIntType |
8f1349db | 107 | linear_congruential_engine<_UIntType, __a, __c, __m>::modulus; |
108 | ||
109 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m> | |
c0000147 | 110 | constexpr _UIntType |
8f1349db | 111 | linear_congruential_engine<_UIntType, __a, __c, __m>::default_seed; |
112 | ||
fca66f47 | 113 | /** |
6a0ebfd6 | 114 | * Seeds the LCR with integral value @p __s, adjusted so that the |
fca66f47 | 115 | * ring identity is never a member of the convergence set. |
116 | */ | |
117 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m> | |
118 | void | |
119 | linear_congruential_engine<_UIntType, __a, __c, __m>:: | |
6a0ebfd6 | 120 | seed(result_type __s) |
fca66f47 | 121 | { |
ccb188ea | 122 | if ((__detail::__mod<_UIntType, __m>(__c) == 0) |
123 | && (__detail::__mod<_UIntType, __m>(__s) == 0)) | |
124 | _M_x = 1; | |
fca66f47 | 125 | else |
ccb188ea | 126 | _M_x = __detail::__mod<_UIntType, __m>(__s); |
fca66f47 | 127 | } |
128 | ||
129 | /** | |
6a0ebfd6 | 130 | * Seeds the LCR engine with a value generated by @p __q. |
fca66f47 | 131 | */ |
132 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m> | |
0d1addb7 | 133 | template<typename _Sseq> |
134 | typename std::enable_if<std::is_class<_Sseq>::value>::type | |
79a27af7 | 135 | linear_congruential_engine<_UIntType, __a, __c, __m>:: |
136 | seed(_Sseq& __q) | |
137 | { | |
138 | const _UIntType __k0 = __m == 0 ? std::numeric_limits<_UIntType>::digits | |
139 | : std::__lg(__m); | |
140 | const _UIntType __k = (__k0 + 31) / 32; | |
141 | uint_least32_t __arr[__k + 3]; | |
142 | __q.generate(__arr + 0, __arr + __k + 3); | |
143 | _UIntType __factor = 1u; | |
144 | _UIntType __sum = 0u; | |
145 | for (size_t __j = 0; __j < __k; ++__j) | |
146 | { | |
147 | __sum += __arr[__j + 3] * __factor; | |
148 | __factor *= __detail::_Shift<_UIntType, 32>::__value; | |
149 | } | |
150 | seed(__sum); | |
151 | } | |
fca66f47 | 152 | |
fca66f47 | 153 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m, |
154 | typename _CharT, typename _Traits> | |
155 | std::basic_ostream<_CharT, _Traits>& | |
156 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
157 | const linear_congruential_engine<_UIntType, | |
158 | __a, __c, __m>& __lcr) | |
159 | { | |
160 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
161 | typedef typename __ostream_type::ios_base __ios_base; | |
162 | ||
163 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
164 | const _CharT __fill = __os.fill(); | |
5c5d5311 | 165 | __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left); |
fca66f47 | 166 | __os.fill(__os.widen(' ')); |
167 | ||
168 | __os << __lcr._M_x; | |
169 | ||
170 | __os.flags(__flags); | |
171 | __os.fill(__fill); | |
172 | return __os; | |
173 | } | |
174 | ||
175 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m, | |
176 | typename _CharT, typename _Traits> | |
177 | std::basic_istream<_CharT, _Traits>& | |
178 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
179 | linear_congruential_engine<_UIntType, __a, __c, __m>& __lcr) | |
180 | { | |
181 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
182 | typedef typename __istream_type::ios_base __ios_base; | |
183 | ||
184 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
185 | __is.flags(__ios_base::dec); | |
186 | ||
187 | __is >> __lcr._M_x; | |
188 | ||
189 | __is.flags(__flags); | |
190 | return __is; | |
191 | } | |
192 | ||
193 | ||
8f1349db | 194 | template<typename _UIntType, |
195 | size_t __w, size_t __n, size_t __m, size_t __r, | |
196 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
197 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
198 | _UIntType __f> | |
c0000147 | 199 | constexpr size_t |
8f1349db | 200 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
201 | __s, __b, __t, __c, __l, __f>::word_size; | |
202 | ||
203 | template<typename _UIntType, | |
204 | size_t __w, size_t __n, size_t __m, size_t __r, | |
205 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
206 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
207 | _UIntType __f> | |
c0000147 | 208 | constexpr size_t |
8f1349db | 209 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
210 | __s, __b, __t, __c, __l, __f>::state_size; | |
211 | ||
212 | template<typename _UIntType, | |
213 | size_t __w, size_t __n, size_t __m, size_t __r, | |
214 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
215 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
216 | _UIntType __f> | |
c0000147 | 217 | constexpr size_t |
8f1349db | 218 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
219 | __s, __b, __t, __c, __l, __f>::shift_size; | |
220 | ||
221 | template<typename _UIntType, | |
222 | size_t __w, size_t __n, size_t __m, size_t __r, | |
223 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
224 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
225 | _UIntType __f> | |
c0000147 | 226 | constexpr size_t |
8f1349db | 227 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
228 | __s, __b, __t, __c, __l, __f>::mask_bits; | |
229 | ||
230 | template<typename _UIntType, | |
231 | size_t __w, size_t __n, size_t __m, size_t __r, | |
232 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
233 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
234 | _UIntType __f> | |
c0000147 | 235 | constexpr _UIntType |
8f1349db | 236 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
237 | __s, __b, __t, __c, __l, __f>::xor_mask; | |
238 | ||
239 | template<typename _UIntType, | |
240 | size_t __w, size_t __n, size_t __m, size_t __r, | |
241 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
242 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
243 | _UIntType __f> | |
c0000147 | 244 | constexpr size_t |
8f1349db | 245 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
246 | __s, __b, __t, __c, __l, __f>::tempering_u; | |
247 | ||
248 | template<typename _UIntType, | |
249 | size_t __w, size_t __n, size_t __m, size_t __r, | |
250 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
251 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
252 | _UIntType __f> | |
c0000147 | 253 | constexpr _UIntType |
8f1349db | 254 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
255 | __s, __b, __t, __c, __l, __f>::tempering_d; | |
256 | ||
257 | template<typename _UIntType, | |
258 | size_t __w, size_t __n, size_t __m, size_t __r, | |
259 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
260 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
261 | _UIntType __f> | |
c0000147 | 262 | constexpr size_t |
8f1349db | 263 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
264 | __s, __b, __t, __c, __l, __f>::tempering_s; | |
265 | ||
266 | template<typename _UIntType, | |
267 | size_t __w, size_t __n, size_t __m, size_t __r, | |
268 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
269 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
270 | _UIntType __f> | |
c0000147 | 271 | constexpr _UIntType |
8f1349db | 272 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
273 | __s, __b, __t, __c, __l, __f>::tempering_b; | |
274 | ||
275 | template<typename _UIntType, | |
276 | size_t __w, size_t __n, size_t __m, size_t __r, | |
277 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
278 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
279 | _UIntType __f> | |
c0000147 | 280 | constexpr size_t |
8f1349db | 281 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
282 | __s, __b, __t, __c, __l, __f>::tempering_t; | |
283 | ||
284 | template<typename _UIntType, | |
285 | size_t __w, size_t __n, size_t __m, size_t __r, | |
286 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
287 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
288 | _UIntType __f> | |
c0000147 | 289 | constexpr _UIntType |
8f1349db | 290 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
291 | __s, __b, __t, __c, __l, __f>::tempering_c; | |
292 | ||
293 | template<typename _UIntType, | |
294 | size_t __w, size_t __n, size_t __m, size_t __r, | |
295 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
296 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
297 | _UIntType __f> | |
c0000147 | 298 | constexpr size_t |
8f1349db | 299 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
300 | __s, __b, __t, __c, __l, __f>::tempering_l; | |
301 | ||
302 | template<typename _UIntType, | |
303 | size_t __w, size_t __n, size_t __m, size_t __r, | |
304 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
305 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
306 | _UIntType __f> | |
c0000147 | 307 | constexpr _UIntType |
8f1349db | 308 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
309 | __s, __b, __t, __c, __l, __f>:: | |
310 | initialization_multiplier; | |
311 | ||
312 | template<typename _UIntType, | |
313 | size_t __w, size_t __n, size_t __m, size_t __r, | |
314 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
315 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
316 | _UIntType __f> | |
c0000147 | 317 | constexpr _UIntType |
8f1349db | 318 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
319 | __s, __b, __t, __c, __l, __f>::default_seed; | |
320 | ||
fca66f47 | 321 | template<typename _UIntType, |
322 | size_t __w, size_t __n, size_t __m, size_t __r, | |
323 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
324 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
325 | _UIntType __f> | |
326 | void | |
327 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, | |
328 | __s, __b, __t, __c, __l, __f>:: | |
329 | seed(result_type __sd) | |
330 | { | |
ccb188ea | 331 | _M_x[0] = __detail::__mod<_UIntType, |
fca66f47 | 332 | __detail::_Shift<_UIntType, __w>::__value>(__sd); |
333 | ||
334 | for (size_t __i = 1; __i < state_size; ++__i) | |
335 | { | |
336 | _UIntType __x = _M_x[__i - 1]; | |
337 | __x ^= __x >> (__w - 2); | |
338 | __x *= __f; | |
ccb188ea | 339 | __x += __detail::__mod<_UIntType, __n>(__i); |
340 | _M_x[__i] = __detail::__mod<_UIntType, | |
fca66f47 | 341 | __detail::_Shift<_UIntType, __w>::__value>(__x); |
342 | } | |
343 | _M_p = state_size; | |
344 | } | |
345 | ||
346 | template<typename _UIntType, | |
347 | size_t __w, size_t __n, size_t __m, size_t __r, | |
348 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
349 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
350 | _UIntType __f> | |
0d1addb7 | 351 | template<typename _Sseq> |
352 | typename std::enable_if<std::is_class<_Sseq>::value>::type | |
79a27af7 | 353 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, |
fca66f47 | 354 | __s, __b, __t, __c, __l, __f>:: |
79a27af7 | 355 | seed(_Sseq& __q) |
356 | { | |
357 | const _UIntType __upper_mask = (~_UIntType()) << __r; | |
358 | const size_t __k = (__w + 31) / 32; | |
359 | uint_least32_t __arr[__n * __k]; | |
360 | __q.generate(__arr + 0, __arr + __n * __k); | |
361 | ||
362 | bool __zero = true; | |
363 | for (size_t __i = 0; __i < state_size; ++__i) | |
364 | { | |
365 | _UIntType __factor = 1u; | |
366 | _UIntType __sum = 0u; | |
367 | for (size_t __j = 0; __j < __k; ++__j) | |
368 | { | |
369 | __sum += __arr[__k * __i + __j] * __factor; | |
370 | __factor *= __detail::_Shift<_UIntType, 32>::__value; | |
371 | } | |
372 | _M_x[__i] = __detail::__mod<_UIntType, | |
373 | __detail::_Shift<_UIntType, __w>::__value>(__sum); | |
374 | ||
375 | if (__zero) | |
376 | { | |
377 | if (__i == 0) | |
378 | { | |
379 | if ((_M_x[0] & __upper_mask) != 0u) | |
380 | __zero = false; | |
381 | } | |
382 | else if (_M_x[__i] != 0u) | |
383 | __zero = false; | |
384 | } | |
385 | } | |
fca66f47 | 386 | if (__zero) |
ccb188ea | 387 | _M_x[0] = __detail::_Shift<_UIntType, __w - 1>::__value; |
673f2c6a | 388 | _M_p = state_size; |
79a27af7 | 389 | } |
fca66f47 | 390 | |
fbeec1b3 | 391 | template<typename _UIntType, size_t __w, |
392 | size_t __n, size_t __m, size_t __r, | |
393 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
394 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
395 | _UIntType __f> | |
396 | void | |
397 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, | |
398 | __s, __b, __t, __c, __l, __f>:: | |
399 | _M_gen_rand(void) | |
400 | { | |
401 | const _UIntType __upper_mask = (~_UIntType()) << __r; | |
402 | const _UIntType __lower_mask = ~__upper_mask; | |
403 | ||
404 | for (size_t __k = 0; __k < (__n - __m); ++__k) | |
405 | { | |
406 | _UIntType __y = ((_M_x[__k] & __upper_mask) | |
407 | | (_M_x[__k + 1] & __lower_mask)); | |
408 | _M_x[__k] = (_M_x[__k + __m] ^ (__y >> 1) | |
409 | ^ ((__y & 0x01) ? __a : 0)); | |
410 | } | |
411 | ||
412 | for (size_t __k = (__n - __m); __k < (__n - 1); ++__k) | |
413 | { | |
414 | _UIntType __y = ((_M_x[__k] & __upper_mask) | |
415 | | (_M_x[__k + 1] & __lower_mask)); | |
416 | _M_x[__k] = (_M_x[__k + (__m - __n)] ^ (__y >> 1) | |
417 | ^ ((__y & 0x01) ? __a : 0)); | |
418 | } | |
419 | ||
420 | _UIntType __y = ((_M_x[__n - 1] & __upper_mask) | |
421 | | (_M_x[0] & __lower_mask)); | |
422 | _M_x[__n - 1] = (_M_x[__m - 1] ^ (__y >> 1) | |
423 | ^ ((__y & 0x01) ? __a : 0)); | |
424 | _M_p = 0; | |
425 | } | |
426 | ||
427 | template<typename _UIntType, size_t __w, | |
428 | size_t __n, size_t __m, size_t __r, | |
429 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
430 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
431 | _UIntType __f> | |
432 | void | |
433 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, | |
434 | __s, __b, __t, __c, __l, __f>:: | |
435 | discard(unsigned long long __z) | |
436 | { | |
437 | while (__z > state_size - _M_p) | |
438 | { | |
439 | __z -= state_size - _M_p; | |
440 | _M_gen_rand(); | |
441 | } | |
442 | _M_p += __z; | |
443 | } | |
444 | ||
fca66f47 | 445 | template<typename _UIntType, size_t __w, |
446 | size_t __n, size_t __m, size_t __r, | |
447 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
448 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
449 | _UIntType __f> | |
450 | typename | |
451 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, | |
452 | __s, __b, __t, __c, __l, __f>::result_type | |
453 | mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, | |
454 | __s, __b, __t, __c, __l, __f>:: | |
455 | operator()() | |
456 | { | |
457 | // Reload the vector - cost is O(n) amortized over n calls. | |
458 | if (_M_p >= state_size) | |
fbeec1b3 | 459 | _M_gen_rand(); |
fca66f47 | 460 | |
461 | // Calculate o(x(i)). | |
462 | result_type __z = _M_x[_M_p++]; | |
463 | __z ^= (__z >> __u) & __d; | |
464 | __z ^= (__z << __s) & __b; | |
465 | __z ^= (__z << __t) & __c; | |
466 | __z ^= (__z >> __l); | |
467 | ||
468 | return __z; | |
469 | } | |
470 | ||
471 | template<typename _UIntType, size_t __w, | |
472 | size_t __n, size_t __m, size_t __r, | |
473 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
474 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
475 | _UIntType __f, typename _CharT, typename _Traits> | |
476 | std::basic_ostream<_CharT, _Traits>& | |
477 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
478 | const mersenne_twister_engine<_UIntType, __w, __n, __m, | |
479 | __r, __a, __u, __d, __s, __b, __t, __c, __l, __f>& __x) | |
480 | { | |
481 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
482 | typedef typename __ostream_type::ios_base __ios_base; | |
483 | ||
484 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
485 | const _CharT __fill = __os.fill(); | |
486 | const _CharT __space = __os.widen(' '); | |
5c5d5311 | 487 | __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left); |
fca66f47 | 488 | __os.fill(__space); |
489 | ||
2350caac | 490 | for (size_t __i = 0; __i < __n; ++__i) |
fca66f47 | 491 | __os << __x._M_x[__i] << __space; |
2350caac | 492 | __os << __x._M_p; |
fca66f47 | 493 | |
494 | __os.flags(__flags); | |
495 | __os.fill(__fill); | |
496 | return __os; | |
497 | } | |
498 | ||
499 | template<typename _UIntType, size_t __w, | |
500 | size_t __n, size_t __m, size_t __r, | |
501 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
502 | _UIntType __b, size_t __t, _UIntType __c, size_t __l, | |
503 | _UIntType __f, typename _CharT, typename _Traits> | |
504 | std::basic_istream<_CharT, _Traits>& | |
505 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
506 | mersenne_twister_engine<_UIntType, __w, __n, __m, | |
507 | __r, __a, __u, __d, __s, __b, __t, __c, __l, __f>& __x) | |
508 | { | |
509 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
510 | typedef typename __istream_type::ios_base __ios_base; | |
511 | ||
512 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
513 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
514 | ||
515 | for (size_t __i = 0; __i < __n; ++__i) | |
516 | __is >> __x._M_x[__i]; | |
2350caac | 517 | __is >> __x._M_p; |
fca66f47 | 518 | |
519 | __is.flags(__flags); | |
520 | return __is; | |
521 | } | |
522 | ||
523 | ||
8f1349db | 524 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> |
c0000147 | 525 | constexpr size_t |
8f1349db | 526 | subtract_with_carry_engine<_UIntType, __w, __s, __r>::word_size; |
527 | ||
528 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> | |
c0000147 | 529 | constexpr size_t |
8f1349db | 530 | subtract_with_carry_engine<_UIntType, __w, __s, __r>::short_lag; |
531 | ||
532 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> | |
c0000147 | 533 | constexpr size_t |
8f1349db | 534 | subtract_with_carry_engine<_UIntType, __w, __s, __r>::long_lag; |
535 | ||
536 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> | |
c0000147 | 537 | constexpr _UIntType |
8f1349db | 538 | subtract_with_carry_engine<_UIntType, __w, __s, __r>::default_seed; |
539 | ||
fca66f47 | 540 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> |
541 | void | |
542 | subtract_with_carry_engine<_UIntType, __w, __s, __r>:: | |
543 | seed(result_type __value) | |
544 | { | |
ccb188ea | 545 | std::linear_congruential_engine<result_type, 40014u, 0u, 2147483563u> |
546 | __lcg(__value == 0u ? default_seed : __value); | |
fca66f47 | 547 | |
ccb188ea | 548 | const size_t __n = (__w + 31) / 32; |
fca66f47 | 549 | |
550 | for (size_t __i = 0; __i < long_lag; ++__i) | |
551 | { | |
ccb188ea | 552 | _UIntType __sum = 0u; |
553 | _UIntType __factor = 1u; | |
fca66f47 | 554 | for (size_t __j = 0; __j < __n; ++__j) |
555 | { | |
ccb188ea | 556 | __sum += __detail::__mod<uint_least32_t, |
557 | __detail::_Shift<uint_least32_t, 32>::__value> | |
fca66f47 | 558 | (__lcg()) * __factor; |
559 | __factor *= __detail::_Shift<_UIntType, 32>::__value; | |
560 | } | |
ccb188ea | 561 | _M_x[__i] = __detail::__mod<_UIntType, |
6a0ebfd6 | 562 | __detail::_Shift<_UIntType, __w>::__value>(__sum); |
fca66f47 | 563 | } |
564 | _M_carry = (_M_x[long_lag - 1] == 0) ? 1 : 0; | |
565 | _M_p = 0; | |
566 | } | |
567 | ||
568 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> | |
0d1addb7 | 569 | template<typename _Sseq> |
570 | typename std::enable_if<std::is_class<_Sseq>::value>::type | |
79a27af7 | 571 | subtract_with_carry_engine<_UIntType, __w, __s, __r>:: |
572 | seed(_Sseq& __q) | |
573 | { | |
574 | const size_t __k = (__w + 31) / 32; | |
575 | uint_least32_t __arr[__r * __k]; | |
576 | __q.generate(__arr + 0, __arr + __r * __k); | |
577 | ||
578 | for (size_t __i = 0; __i < long_lag; ++__i) | |
579 | { | |
580 | _UIntType __sum = 0u; | |
581 | _UIntType __factor = 1u; | |
582 | for (size_t __j = 0; __j < __k; ++__j) | |
583 | { | |
584 | __sum += __arr[__k * __i + __j] * __factor; | |
585 | __factor *= __detail::_Shift<_UIntType, 32>::__value; | |
586 | } | |
587 | _M_x[__i] = __detail::__mod<_UIntType, | |
588 | __detail::_Shift<_UIntType, __w>::__value>(__sum); | |
589 | } | |
590 | _M_carry = (_M_x[long_lag - 1] == 0) ? 1 : 0; | |
591 | _M_p = 0; | |
592 | } | |
fca66f47 | 593 | |
594 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> | |
595 | typename subtract_with_carry_engine<_UIntType, __w, __s, __r>:: | |
596 | result_type | |
597 | subtract_with_carry_engine<_UIntType, __w, __s, __r>:: | |
598 | operator()() | |
599 | { | |
600 | // Derive short lag index from current index. | |
601 | long __ps = _M_p - short_lag; | |
602 | if (__ps < 0) | |
603 | __ps += long_lag; | |
604 | ||
605 | // Calculate new x(i) without overflow or division. | |
606 | // NB: Thanks to the requirements for _UIntType, _M_x[_M_p] + _M_carry | |
607 | // cannot overflow. | |
608 | _UIntType __xi; | |
609 | if (_M_x[__ps] >= _M_x[_M_p] + _M_carry) | |
610 | { | |
611 | __xi = _M_x[__ps] - _M_x[_M_p] - _M_carry; | |
612 | _M_carry = 0; | |
613 | } | |
614 | else | |
615 | { | |
6a0ebfd6 | 616 | __xi = (__detail::_Shift<_UIntType, __w>::__value |
617 | - _M_x[_M_p] - _M_carry + _M_x[__ps]); | |
fca66f47 | 618 | _M_carry = 1; |
619 | } | |
620 | _M_x[_M_p] = __xi; | |
621 | ||
622 | // Adjust current index to loop around in ring buffer. | |
623 | if (++_M_p >= long_lag) | |
624 | _M_p = 0; | |
625 | ||
626 | return __xi; | |
627 | } | |
628 | ||
629 | template<typename _UIntType, size_t __w, size_t __s, size_t __r, | |
630 | typename _CharT, typename _Traits> | |
631 | std::basic_ostream<_CharT, _Traits>& | |
632 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
633 | const subtract_with_carry_engine<_UIntType, | |
634 | __w, __s, __r>& __x) | |
635 | { | |
636 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
637 | typedef typename __ostream_type::ios_base __ios_base; | |
638 | ||
639 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
640 | const _CharT __fill = __os.fill(); | |
641 | const _CharT __space = __os.widen(' '); | |
5c5d5311 | 642 | __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left); |
fca66f47 | 643 | __os.fill(__space); |
644 | ||
645 | for (size_t __i = 0; __i < __r; ++__i) | |
646 | __os << __x._M_x[__i] << __space; | |
2350caac | 647 | __os << __x._M_carry << __space << __x._M_p; |
fca66f47 | 648 | |
649 | __os.flags(__flags); | |
650 | __os.fill(__fill); | |
651 | return __os; | |
652 | } | |
653 | ||
654 | template<typename _UIntType, size_t __w, size_t __s, size_t __r, | |
655 | typename _CharT, typename _Traits> | |
656 | std::basic_istream<_CharT, _Traits>& | |
657 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
658 | subtract_with_carry_engine<_UIntType, __w, __s, __r>& __x) | |
659 | { | |
660 | typedef std::basic_ostream<_CharT, _Traits> __istream_type; | |
661 | typedef typename __istream_type::ios_base __ios_base; | |
662 | ||
663 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
664 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
665 | ||
666 | for (size_t __i = 0; __i < __r; ++__i) | |
667 | __is >> __x._M_x[__i]; | |
668 | __is >> __x._M_carry; | |
2350caac | 669 | __is >> __x._M_p; |
fca66f47 | 670 | |
671 | __is.flags(__flags); | |
672 | return __is; | |
673 | } | |
674 | ||
675 | ||
8f1349db | 676 | template<typename _RandomNumberEngine, size_t __p, size_t __r> |
c0000147 | 677 | constexpr size_t |
8f1349db | 678 | discard_block_engine<_RandomNumberEngine, __p, __r>::block_size; |
679 | ||
680 | template<typename _RandomNumberEngine, size_t __p, size_t __r> | |
c0000147 | 681 | constexpr size_t |
8f1349db | 682 | discard_block_engine<_RandomNumberEngine, __p, __r>::used_block; |
683 | ||
fca66f47 | 684 | template<typename _RandomNumberEngine, size_t __p, size_t __r> |
685 | typename discard_block_engine<_RandomNumberEngine, | |
686 | __p, __r>::result_type | |
687 | discard_block_engine<_RandomNumberEngine, __p, __r>:: | |
688 | operator()() | |
689 | { | |
690 | if (_M_n >= used_block) | |
691 | { | |
692 | _M_b.discard(block_size - _M_n); | |
693 | _M_n = 0; | |
694 | } | |
695 | ++_M_n; | |
696 | return _M_b(); | |
697 | } | |
698 | ||
699 | template<typename _RandomNumberEngine, size_t __p, size_t __r, | |
700 | typename _CharT, typename _Traits> | |
701 | std::basic_ostream<_CharT, _Traits>& | |
702 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
703 | const discard_block_engine<_RandomNumberEngine, | |
704 | __p, __r>& __x) | |
705 | { | |
706 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
707 | typedef typename __ostream_type::ios_base __ios_base; | |
708 | ||
709 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
710 | const _CharT __fill = __os.fill(); | |
711 | const _CharT __space = __os.widen(' '); | |
5c5d5311 | 712 | __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left); |
fca66f47 | 713 | __os.fill(__space); |
714 | ||
715 | __os << __x.base() << __space << __x._M_n; | |
716 | ||
717 | __os.flags(__flags); | |
718 | __os.fill(__fill); | |
719 | return __os; | |
720 | } | |
721 | ||
722 | template<typename _RandomNumberEngine, size_t __p, size_t __r, | |
723 | typename _CharT, typename _Traits> | |
724 | std::basic_istream<_CharT, _Traits>& | |
725 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
726 | discard_block_engine<_RandomNumberEngine, __p, __r>& __x) | |
727 | { | |
728 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
729 | typedef typename __istream_type::ios_base __ios_base; | |
730 | ||
731 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
732 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
733 | ||
734 | __is >> __x._M_b >> __x._M_n; | |
735 | ||
736 | __is.flags(__flags); | |
737 | return __is; | |
738 | } | |
739 | ||
740 | ||
741 | template<typename _RandomNumberEngine, size_t __w, typename _UIntType> | |
742 | typename independent_bits_engine<_RandomNumberEngine, __w, _UIntType>:: | |
743 | result_type | |
744 | independent_bits_engine<_RandomNumberEngine, __w, _UIntType>:: | |
745 | operator()() | |
746 | { | |
672db419 | 747 | typedef typename _RandomNumberEngine::result_type _Eresult_type; |
748 | const _Eresult_type __r | |
749 | = (_M_b.max() - _M_b.min() < std::numeric_limits<_Eresult_type>::max() | |
750 | ? _M_b.max() - _M_b.min() + 1 : 0); | |
751 | const unsigned __edig = std::numeric_limits<_Eresult_type>::digits; | |
752 | const unsigned __m = __r ? std::__lg(__r) : __edig; | |
753 | ||
754 | typedef typename std::common_type<_Eresult_type, result_type>::type | |
755 | __ctype; | |
756 | const unsigned __cdig = std::numeric_limits<__ctype>::digits; | |
757 | ||
758 | unsigned __n, __n0; | |
759 | __ctype __s0, __s1, __y0, __y1; | |
760 | ||
fca66f47 | 761 | for (size_t __i = 0; __i < 2; ++__i) |
762 | { | |
763 | __n = (__w + __m - 1) / __m + __i; | |
764 | __n0 = __n - __w % __n; | |
672db419 | 765 | const unsigned __w0 = __w / __n; // __w0 <= __m |
766 | ||
767 | __s0 = 0; | |
768 | __s1 = 0; | |
769 | if (__w0 < __cdig) | |
770 | { | |
771 | __s0 = __ctype(1) << __w0; | |
772 | __s1 = __s0 << 1; | |
773 | } | |
774 | ||
775 | __y0 = 0; | |
776 | __y1 = 0; | |
777 | if (__r) | |
778 | { | |
779 | __y0 = __s0 * (__r / __s0); | |
780 | if (__s1) | |
781 | __y1 = __s1 * (__r / __s1); | |
782 | ||
783 | if (__r - __y0 <= __y0 / __n) | |
784 | break; | |
785 | } | |
786 | else | |
fca66f47 | 787 | break; |
788 | } | |
789 | ||
790 | result_type __sum = 0; | |
791 | for (size_t __k = 0; __k < __n0; ++__k) | |
792 | { | |
672db419 | 793 | __ctype __u; |
fca66f47 | 794 | do |
f3922893 | 795 | __u = _M_b() - _M_b.min(); |
672db419 | 796 | while (__y0 && __u >= __y0); |
797 | __sum = __s0 * __sum + (__s0 ? __u % __s0 : __u); | |
fca66f47 | 798 | } |
799 | for (size_t __k = __n0; __k < __n; ++__k) | |
800 | { | |
672db419 | 801 | __ctype __u; |
fca66f47 | 802 | do |
f3922893 | 803 | __u = _M_b() - _M_b.min(); |
672db419 | 804 | while (__y1 && __u >= __y1); |
805 | __sum = __s1 * __sum + (__s1 ? __u % __s1 : __u); | |
fca66f47 | 806 | } |
807 | return __sum; | |
808 | } | |
809 | ||
810 | ||
8f1349db | 811 | template<typename _RandomNumberEngine, size_t __k> |
c0000147 | 812 | constexpr size_t |
8f1349db | 813 | shuffle_order_engine<_RandomNumberEngine, __k>::table_size; |
814 | ||
fca66f47 | 815 | template<typename _RandomNumberEngine, size_t __k> |
816 | typename shuffle_order_engine<_RandomNumberEngine, __k>::result_type | |
817 | shuffle_order_engine<_RandomNumberEngine, __k>:: | |
818 | operator()() | |
819 | { | |
6a0ebfd6 | 820 | size_t __j = __k * ((_M_y - _M_b.min()) |
821 | / (_M_b.max() - _M_b.min() + 1.0L)); | |
fca66f47 | 822 | _M_y = _M_v[__j]; |
823 | _M_v[__j] = _M_b(); | |
824 | ||
825 | return _M_y; | |
826 | } | |
827 | ||
828 | template<typename _RandomNumberEngine, size_t __k, | |
829 | typename _CharT, typename _Traits> | |
830 | std::basic_ostream<_CharT, _Traits>& | |
831 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
832 | const shuffle_order_engine<_RandomNumberEngine, __k>& __x) | |
833 | { | |
834 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
835 | typedef typename __ostream_type::ios_base __ios_base; | |
836 | ||
837 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
838 | const _CharT __fill = __os.fill(); | |
839 | const _CharT __space = __os.widen(' '); | |
5c5d5311 | 840 | __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left); |
fca66f47 | 841 | __os.fill(__space); |
842 | ||
843 | __os << __x.base(); | |
844 | for (size_t __i = 0; __i < __k; ++__i) | |
845 | __os << __space << __x._M_v[__i]; | |
846 | __os << __space << __x._M_y; | |
847 | ||
848 | __os.flags(__flags); | |
849 | __os.fill(__fill); | |
850 | return __os; | |
851 | } | |
852 | ||
853 | template<typename _RandomNumberEngine, size_t __k, | |
854 | typename _CharT, typename _Traits> | |
855 | std::basic_istream<_CharT, _Traits>& | |
856 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
857 | shuffle_order_engine<_RandomNumberEngine, __k>& __x) | |
858 | { | |
859 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
860 | typedef typename __istream_type::ios_base __ios_base; | |
861 | ||
862 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
863 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
864 | ||
865 | __is >> __x._M_b; | |
866 | for (size_t __i = 0; __i < __k; ++__i) | |
867 | __is >> __x._M_v[__i]; | |
868 | __is >> __x._M_y; | |
869 | ||
870 | __is.flags(__flags); | |
871 | return __is; | |
872 | } | |
873 | ||
874 | ||
875 | template<typename _IntType> | |
876 | template<typename _UniformRandomNumberGenerator> | |
877 | typename uniform_int_distribution<_IntType>::result_type | |
878 | uniform_int_distribution<_IntType>:: | |
010799ab | 879 | operator()(_UniformRandomNumberGenerator& __urng, |
880 | const param_type& __param) | |
fca66f47 | 881 | { |
672db419 | 882 | typedef typename _UniformRandomNumberGenerator::result_type |
883 | _Gresult_type; | |
113bf78b | 884 | typedef typename std::make_unsigned<result_type>::type __utype; |
672db419 | 885 | typedef typename std::common_type<_Gresult_type, __utype>::type |
886 | __uctype; | |
e9d6048a | 887 | |
888 | const __uctype __urngmin = __urng.min(); | |
889 | const __uctype __urngmax = __urng.max(); | |
890 | const __uctype __urngrange = __urngmax - __urngmin; | |
891 | const __uctype __urange | |
892 | = __uctype(__param.b()) - __uctype(__param.a()); | |
893 | ||
894 | __uctype __ret; | |
895 | ||
896 | if (__urngrange > __urange) | |
897 | { | |
898 | // downscaling | |
899 | const __uctype __uerange = __urange + 1; // __urange can be zero | |
900 | const __uctype __scaling = __urngrange / __uerange; | |
901 | const __uctype __past = __uerange * __scaling; | |
902 | do | |
903 | __ret = __uctype(__urng()) - __urngmin; | |
904 | while (__ret >= __past); | |
905 | __ret /= __scaling; | |
906 | } | |
907 | else if (__urngrange < __urange) | |
908 | { | |
909 | // upscaling | |
910 | /* | |
911 | Note that every value in [0, urange] | |
912 | can be written uniquely as | |
913 | ||
914 | (urngrange + 1) * high + low | |
915 | ||
916 | where | |
917 | ||
918 | high in [0, urange / (urngrange + 1)] | |
919 | ||
920 | and | |
921 | ||
922 | low in [0, urngrange]. | |
923 | */ | |
924 | __uctype __tmp; // wraparound control | |
925 | do | |
926 | { | |
927 | const __uctype __uerngrange = __urngrange + 1; | |
928 | __tmp = (__uerngrange * operator() | |
929 | (__urng, param_type(0, __urange / __uerngrange))); | |
930 | __ret = __tmp + (__uctype(__urng()) - __urngmin); | |
931 | } | |
932 | while (__ret > __urange || __ret < __tmp); | |
933 | } | |
934 | else | |
935 | __ret = __uctype(__urng()) - __urngmin; | |
fca66f47 | 936 | |
010799ab | 937 | return __ret + __param.a(); |
fca66f47 | 938 | } |
939 | ||
308b344d | 940 | |
941 | template<typename _IntType> | |
942 | template<typename _ForwardIterator, | |
943 | typename _UniformRandomNumberGenerator> | |
944 | void | |
945 | uniform_int_distribution<_IntType>:: | |
946 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
947 | _UniformRandomNumberGenerator& __urng, | |
948 | const param_type& __param) | |
949 | { | |
950 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
951 | typedef typename _UniformRandomNumberGenerator::result_type | |
952 | _Gresult_type; | |
953 | typedef typename std::make_unsigned<result_type>::type __utype; | |
954 | typedef typename std::common_type<_Gresult_type, __utype>::type | |
955 | __uctype; | |
956 | ||
957 | const __uctype __urngmin = __urng.min(); | |
958 | const __uctype __urngmax = __urng.max(); | |
959 | const __uctype __urngrange = __urngmax - __urngmin; | |
960 | const __uctype __urange | |
961 | = __uctype(__param.b()) - __uctype(__param.a()); | |
962 | ||
963 | __uctype __ret; | |
964 | ||
965 | if (__urngrange > __urange) | |
966 | { | |
967 | if (__detail::_Power_of_2(__urngrange + 1) | |
968 | && __detail::_Power_of_2(__urange + 1)) | |
969 | { | |
970 | while (__f != __t) | |
971 | { | |
972 | __ret = __uctype(__urng()) - __urngmin; | |
973 | *__f++ = (__ret & __urange) + __param.a(); | |
974 | } | |
975 | } | |
976 | else | |
977 | { | |
978 | // downscaling | |
979 | const __uctype __uerange = __urange + 1; // __urange can be zero | |
980 | const __uctype __scaling = __urngrange / __uerange; | |
981 | const __uctype __past = __uerange * __scaling; | |
982 | while (__f != __t) | |
983 | { | |
984 | do | |
985 | __ret = __uctype(__urng()) - __urngmin; | |
986 | while (__ret >= __past); | |
987 | *__f++ = __ret / __scaling + __param.a(); | |
988 | } | |
989 | } | |
990 | } | |
991 | else if (__urngrange < __urange) | |
992 | { | |
993 | // upscaling | |
994 | /* | |
995 | Note that every value in [0, urange] | |
996 | can be written uniquely as | |
997 | ||
998 | (urngrange + 1) * high + low | |
999 | ||
1000 | where | |
1001 | ||
1002 | high in [0, urange / (urngrange + 1)] | |
1003 | ||
1004 | and | |
1005 | ||
1006 | low in [0, urngrange]. | |
1007 | */ | |
1008 | __uctype __tmp; // wraparound control | |
1009 | while (__f != __t) | |
1010 | { | |
1011 | do | |
1012 | { | |
1013 | const __uctype __uerngrange = __urngrange + 1; | |
1014 | __tmp = (__uerngrange * operator() | |
1015 | (__urng, param_type(0, __urange / __uerngrange))); | |
1016 | __ret = __tmp + (__uctype(__urng()) - __urngmin); | |
1017 | } | |
1018 | while (__ret > __urange || __ret < __tmp); | |
1019 | *__f++ = __ret; | |
1020 | } | |
1021 | } | |
1022 | else | |
1023 | while (__f != __t) | |
1024 | *__f++ = __uctype(__urng()) - __urngmin + __param.a(); | |
1025 | } | |
1026 | ||
fca66f47 | 1027 | template<typename _IntType, typename _CharT, typename _Traits> |
1028 | std::basic_ostream<_CharT, _Traits>& | |
1029 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1030 | const uniform_int_distribution<_IntType>& __x) | |
1031 | { | |
1032 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
1033 | typedef typename __ostream_type::ios_base __ios_base; | |
1034 | ||
1035 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1036 | const _CharT __fill = __os.fill(); | |
1037 | const _CharT __space = __os.widen(' '); | |
1038 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1039 | __os.fill(__space); | |
1040 | ||
1041 | __os << __x.a() << __space << __x.b(); | |
1042 | ||
1043 | __os.flags(__flags); | |
1044 | __os.fill(__fill); | |
1045 | return __os; | |
1046 | } | |
1047 | ||
1048 | template<typename _IntType, typename _CharT, typename _Traits> | |
1049 | std::basic_istream<_CharT, _Traits>& | |
1050 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
1051 | uniform_int_distribution<_IntType>& __x) | |
1052 | { | |
1053 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
1054 | typedef typename __istream_type::ios_base __ios_base; | |
1055 | ||
1056 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
1057 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
1058 | ||
1059 | _IntType __a, __b; | |
1060 | __is >> __a >> __b; | |
1061 | __x.param(typename uniform_int_distribution<_IntType>:: | |
1062 | param_type(__a, __b)); | |
1063 | ||
1064 | __is.flags(__flags); | |
1065 | return __is; | |
1066 | } | |
1067 | ||
1068 | ||
308b344d | 1069 | template<typename _RealType> |
1070 | template<typename _ForwardIterator, | |
1071 | typename _UniformRandomNumberGenerator> | |
1072 | void | |
1073 | uniform_real_distribution<_RealType>:: | |
1074 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1075 | _UniformRandomNumberGenerator& __urng, | |
1076 | const param_type& __p) | |
1077 | { | |
1078 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1079 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
1080 | __aurng(__urng); | |
1081 | auto __range = __p.b() - __p.a(); | |
1082 | while (__f != __t) | |
1083 | *__f++ = __aurng() * __range + __p.a(); | |
1084 | } | |
1085 | ||
fca66f47 | 1086 | template<typename _RealType, typename _CharT, typename _Traits> |
1087 | std::basic_ostream<_CharT, _Traits>& | |
1088 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1089 | const uniform_real_distribution<_RealType>& __x) | |
1090 | { | |
1091 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
1092 | typedef typename __ostream_type::ios_base __ios_base; | |
1093 | ||
1094 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1095 | const _CharT __fill = __os.fill(); | |
1096 | const std::streamsize __precision = __os.precision(); | |
1097 | const _CharT __space = __os.widen(' '); | |
1098 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1099 | __os.fill(__space); | |
245c5a20 | 1100 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
fca66f47 | 1101 | |
1102 | __os << __x.a() << __space << __x.b(); | |
1103 | ||
1104 | __os.flags(__flags); | |
1105 | __os.fill(__fill); | |
1106 | __os.precision(__precision); | |
1107 | return __os; | |
1108 | } | |
1109 | ||
1110 | template<typename _RealType, typename _CharT, typename _Traits> | |
1111 | std::basic_istream<_CharT, _Traits>& | |
1112 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
1113 | uniform_real_distribution<_RealType>& __x) | |
1114 | { | |
1115 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
1116 | typedef typename __istream_type::ios_base __ios_base; | |
1117 | ||
1118 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
1119 | __is.flags(__ios_base::skipws); | |
1120 | ||
1121 | _RealType __a, __b; | |
1122 | __is >> __a >> __b; | |
1123 | __x.param(typename uniform_real_distribution<_RealType>:: | |
1124 | param_type(__a, __b)); | |
1125 | ||
1126 | __is.flags(__flags); | |
1127 | return __is; | |
1128 | } | |
1129 | ||
1130 | ||
308b344d | 1131 | template<typename _ForwardIterator, |
1132 | typename _UniformRandomNumberGenerator> | |
1133 | void | |
1134 | std::bernoulli_distribution:: | |
1135 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1136 | _UniformRandomNumberGenerator& __urng, | |
1137 | const param_type& __p) | |
1138 | { | |
1139 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1140 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
1141 | __aurng(__urng); | |
1142 | auto __limit = __p.p() * (__aurng.max() - __aurng.min()); | |
1143 | ||
1144 | while (__f != __t) | |
1145 | *__f++ = (__aurng() - __aurng.min()) < __limit; | |
1146 | } | |
1147 | ||
fca66f47 | 1148 | template<typename _CharT, typename _Traits> |
1149 | std::basic_ostream<_CharT, _Traits>& | |
1150 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1151 | const bernoulli_distribution& __x) | |
1152 | { | |
1153 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
1154 | typedef typename __ostream_type::ios_base __ios_base; | |
1155 | ||
1156 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1157 | const _CharT __fill = __os.fill(); | |
1158 | const std::streamsize __precision = __os.precision(); | |
1159 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1160 | __os.fill(__os.widen(' ')); | |
245c5a20 | 1161 | __os.precision(std::numeric_limits<double>::max_digits10); |
fca66f47 | 1162 | |
1163 | __os << __x.p(); | |
1164 | ||
1165 | __os.flags(__flags); | |
1166 | __os.fill(__fill); | |
1167 | __os.precision(__precision); | |
1168 | return __os; | |
1169 | } | |
1170 | ||
1171 | ||
1172 | template<typename _IntType> | |
1173 | template<typename _UniformRandomNumberGenerator> | |
1174 | typename geometric_distribution<_IntType>::result_type | |
1175 | geometric_distribution<_IntType>:: | |
1176 | operator()(_UniformRandomNumberGenerator& __urng, | |
1177 | const param_type& __param) | |
1178 | { | |
1179 | // About the epsilon thing see this thread: | |
1180 | // http://gcc.gnu.org/ml/gcc-patches/2006-10/msg00971.html | |
1181 | const double __naf = | |
1182 | (1 - std::numeric_limits<double>::epsilon()) / 2; | |
1183 | // The largest _RealType convertible to _IntType. | |
1184 | const double __thr = | |
1185 | std::numeric_limits<_IntType>::max() + __naf; | |
010799ab | 1186 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> |
fca66f47 | 1187 | __aurng(__urng); |
1188 | ||
1189 | double __cand; | |
1190 | do | |
c279067a | 1191 | __cand = std::floor(std::log(1.0 - __aurng()) / __param._M_log_1_p); |
fca66f47 | 1192 | while (__cand >= __thr); |
1193 | ||
1194 | return result_type(__cand + __naf); | |
1195 | } | |
1196 | ||
308b344d | 1197 | template<typename _IntType> |
1198 | template<typename _ForwardIterator, | |
1199 | typename _UniformRandomNumberGenerator> | |
1200 | void | |
1201 | geometric_distribution<_IntType>:: | |
1202 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1203 | _UniformRandomNumberGenerator& __urng, | |
1204 | const param_type& __param) | |
1205 | { | |
1206 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1207 | // About the epsilon thing see this thread: | |
1208 | // http://gcc.gnu.org/ml/gcc-patches/2006-10/msg00971.html | |
1209 | const double __naf = | |
1210 | (1 - std::numeric_limits<double>::epsilon()) / 2; | |
1211 | // The largest _RealType convertible to _IntType. | |
1212 | const double __thr = | |
1213 | std::numeric_limits<_IntType>::max() + __naf; | |
1214 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
1215 | __aurng(__urng); | |
1216 | ||
1217 | while (__f != __t) | |
1218 | { | |
1219 | double __cand; | |
1220 | do | |
c279067a | 1221 | __cand = std::floor(std::log(1.0 - __aurng()) |
1222 | / __param._M_log_1_p); | |
308b344d | 1223 | while (__cand >= __thr); |
1224 | ||
1225 | *__f++ = __cand + __naf; | |
1226 | } | |
1227 | } | |
1228 | ||
fca66f47 | 1229 | template<typename _IntType, |
1230 | typename _CharT, typename _Traits> | |
1231 | std::basic_ostream<_CharT, _Traits>& | |
1232 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1233 | const geometric_distribution<_IntType>& __x) | |
1234 | { | |
1235 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
1236 | typedef typename __ostream_type::ios_base __ios_base; | |
1237 | ||
1238 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1239 | const _CharT __fill = __os.fill(); | |
1240 | const std::streamsize __precision = __os.precision(); | |
1241 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1242 | __os.fill(__os.widen(' ')); | |
245c5a20 | 1243 | __os.precision(std::numeric_limits<double>::max_digits10); |
fca66f47 | 1244 | |
1245 | __os << __x.p(); | |
1246 | ||
1247 | __os.flags(__flags); | |
1248 | __os.fill(__fill); | |
1249 | __os.precision(__precision); | |
1250 | return __os; | |
1251 | } | |
1252 | ||
1253 | template<typename _IntType, | |
1254 | typename _CharT, typename _Traits> | |
1255 | std::basic_istream<_CharT, _Traits>& | |
1256 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
1257 | geometric_distribution<_IntType>& __x) | |
1258 | { | |
1259 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
1260 | typedef typename __istream_type::ios_base __ios_base; | |
1261 | ||
1262 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
1263 | __is.flags(__ios_base::skipws); | |
1264 | ||
1265 | double __p; | |
1266 | __is >> __p; | |
1267 | __x.param(typename geometric_distribution<_IntType>::param_type(__p)); | |
1268 | ||
1269 | __is.flags(__flags); | |
1270 | return __is; | |
1271 | } | |
1272 | ||
b74d57a5 | 1273 | // This is Leger's algorithm, also in Devroye, Ch. X, Example 1.5. |
520d23b7 | 1274 | template<typename _IntType> |
1275 | template<typename _UniformRandomNumberGenerator> | |
1276 | typename negative_binomial_distribution<_IntType>::result_type | |
1277 | negative_binomial_distribution<_IntType>:: | |
1278 | operator()(_UniformRandomNumberGenerator& __urng) | |
1279 | { | |
1280 | const double __y = _M_gd(__urng); | |
1281 | ||
1282 | // XXX Is the constructor too slow? | |
b74d57a5 | 1283 | std::poisson_distribution<result_type> __poisson(__y); |
520d23b7 | 1284 | return __poisson(__urng); |
1285 | } | |
1286 | ||
fca66f47 | 1287 | template<typename _IntType> |
1288 | template<typename _UniformRandomNumberGenerator> | |
1289 | typename negative_binomial_distribution<_IntType>::result_type | |
1290 | negative_binomial_distribution<_IntType>:: | |
1291 | operator()(_UniformRandomNumberGenerator& __urng, | |
1292 | const param_type& __p) | |
1293 | { | |
8961a83d | 1294 | typedef typename std::gamma_distribution<double>::param_type |
520d23b7 | 1295 | param_type; |
1296 | ||
b74d57a5 | 1297 | const double __y = |
1298 | _M_gd(__urng, param_type(__p.k(), (1.0 - __p.p()) / __p.p())); | |
fca66f47 | 1299 | |
b74d57a5 | 1300 | std::poisson_distribution<result_type> __poisson(__y); |
d37c6500 | 1301 | return __poisson(__urng); |
fca66f47 | 1302 | } |
1303 | ||
308b344d | 1304 | template<typename _IntType> |
1305 | template<typename _ForwardIterator, | |
1306 | typename _UniformRandomNumberGenerator> | |
1307 | void | |
1308 | negative_binomial_distribution<_IntType>:: | |
1309 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1310 | _UniformRandomNumberGenerator& __urng) | |
1311 | { | |
1312 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1313 | while (__f != __t) | |
1314 | { | |
1315 | const double __y = _M_gd(__urng); | |
1316 | ||
1317 | // XXX Is the constructor too slow? | |
1318 | std::poisson_distribution<result_type> __poisson(__y); | |
1319 | *__f++ = __poisson(__urng); | |
1320 | } | |
1321 | } | |
1322 | ||
1323 | template<typename _IntType> | |
1324 | template<typename _ForwardIterator, | |
1325 | typename _UniformRandomNumberGenerator> | |
1326 | void | |
1327 | negative_binomial_distribution<_IntType>:: | |
1328 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1329 | _UniformRandomNumberGenerator& __urng, | |
1330 | const param_type& __p) | |
1331 | { | |
1332 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1333 | typename std::gamma_distribution<result_type>::param_type | |
1334 | __p2(__p.k(), (1.0 - __p.p()) / __p.p()); | |
1335 | ||
1336 | while (__f != __t) | |
1337 | { | |
1338 | const double __y = _M_gd(__urng, __p2); | |
1339 | ||
1340 | std::poisson_distribution<result_type> __poisson(__y); | |
1341 | *__f++ = __poisson(__urng); | |
1342 | } | |
1343 | } | |
1344 | ||
fca66f47 | 1345 | template<typename _IntType, typename _CharT, typename _Traits> |
1346 | std::basic_ostream<_CharT, _Traits>& | |
1347 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1348 | const negative_binomial_distribution<_IntType>& __x) | |
1349 | { | |
1350 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
1351 | typedef typename __ostream_type::ios_base __ios_base; | |
1352 | ||
1353 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1354 | const _CharT __fill = __os.fill(); | |
1355 | const std::streamsize __precision = __os.precision(); | |
1356 | const _CharT __space = __os.widen(' '); | |
1357 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1358 | __os.fill(__os.widen(' ')); | |
245c5a20 | 1359 | __os.precision(std::numeric_limits<double>::max_digits10); |
fca66f47 | 1360 | |
520d23b7 | 1361 | __os << __x.k() << __space << __x.p() |
1362 | << __space << __x._M_gd; | |
fca66f47 | 1363 | |
1364 | __os.flags(__flags); | |
1365 | __os.fill(__fill); | |
1366 | __os.precision(__precision); | |
1367 | return __os; | |
1368 | } | |
1369 | ||
1370 | template<typename _IntType, typename _CharT, typename _Traits> | |
1371 | std::basic_istream<_CharT, _Traits>& | |
1372 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
1373 | negative_binomial_distribution<_IntType>& __x) | |
1374 | { | |
1375 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
1376 | typedef typename __istream_type::ios_base __ios_base; | |
1377 | ||
1378 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
1379 | __is.flags(__ios_base::skipws); | |
1380 | ||
1381 | _IntType __k; | |
1382 | double __p; | |
520d23b7 | 1383 | __is >> __k >> __p >> __x._M_gd; |
fca66f47 | 1384 | __x.param(typename negative_binomial_distribution<_IntType>:: |
1385 | param_type(__k, __p)); | |
1386 | ||
1387 | __is.flags(__flags); | |
1388 | return __is; | |
1389 | } | |
1390 | ||
1391 | ||
1392 | template<typename _IntType> | |
1393 | void | |
1394 | poisson_distribution<_IntType>::param_type:: | |
1395 | _M_initialize() | |
1396 | { | |
1397 | #if _GLIBCXX_USE_C99_MATH_TR1 | |
1398 | if (_M_mean >= 12) | |
1399 | { | |
1400 | const double __m = std::floor(_M_mean); | |
1401 | _M_lm_thr = std::log(_M_mean); | |
1402 | _M_lfm = std::lgamma(__m + 1); | |
1403 | _M_sm = std::sqrt(__m); | |
1404 | ||
1405 | const double __pi_4 = 0.7853981633974483096156608458198757L; | |
1406 | const double __dx = std::sqrt(2 * __m * std::log(32 * __m | |
1407 | / __pi_4)); | |
b16ebdf3 | 1408 | _M_d = std::round(std::max<double>(6.0, std::min(__m, __dx))); |
fca66f47 | 1409 | const double __cx = 2 * __m + _M_d; |
1410 | _M_scx = std::sqrt(__cx / 2); | |
1411 | _M_1cx = 1 / __cx; | |
1412 | ||
1413 | _M_c2b = std::sqrt(__pi_4 * __cx) * std::exp(_M_1cx); | |
1414 | _M_cb = 2 * __cx * std::exp(-_M_d * _M_1cx * (1 + _M_d / 2)) | |
1415 | / _M_d; | |
1416 | } | |
1417 | else | |
1418 | #endif | |
1419 | _M_lm_thr = std::exp(-_M_mean); | |
1420 | } | |
1421 | ||
1422 | /** | |
1423 | * A rejection algorithm when mean >= 12 and a simple method based | |
1424 | * upon the multiplication of uniform random variates otherwise. | |
1425 | * NB: The former is available only if _GLIBCXX_USE_C99_MATH_TR1 | |
1426 | * is defined. | |
1427 | * | |
1428 | * Reference: | |
72117d76 | 1429 | * Devroye, L. Non-Uniform Random Variates Generation. Springer-Verlag, |
fca66f47 | 1430 | * New York, 1986, Ch. X, Sects. 3.3 & 3.4 (+ Errata!). |
1431 | */ | |
1432 | template<typename _IntType> | |
1433 | template<typename _UniformRandomNumberGenerator> | |
1434 | typename poisson_distribution<_IntType>::result_type | |
1435 | poisson_distribution<_IntType>:: | |
1436 | operator()(_UniformRandomNumberGenerator& __urng, | |
1437 | const param_type& __param) | |
1438 | { | |
1439 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
1440 | __aurng(__urng); | |
1441 | #if _GLIBCXX_USE_C99_MATH_TR1 | |
1442 | if (__param.mean() >= 12) | |
1443 | { | |
1444 | double __x; | |
1445 | ||
1446 | // See comments above... | |
1447 | const double __naf = | |
1448 | (1 - std::numeric_limits<double>::epsilon()) / 2; | |
1449 | const double __thr = | |
1450 | std::numeric_limits<_IntType>::max() + __naf; | |
1451 | ||
1452 | const double __m = std::floor(__param.mean()); | |
1453 | // sqrt(pi / 2) | |
1454 | const double __spi_2 = 1.2533141373155002512078826424055226L; | |
1455 | const double __c1 = __param._M_sm * __spi_2; | |
1456 | const double __c2 = __param._M_c2b + __c1; | |
1457 | const double __c3 = __c2 + 1; | |
1458 | const double __c4 = __c3 + 1; | |
1459 | // e^(1 / 78) | |
1460 | const double __e178 = 1.0129030479320018583185514777512983L; | |
1461 | const double __c5 = __c4 + __e178; | |
1462 | const double __c = __param._M_cb + __c5; | |
1463 | const double __2cx = 2 * (2 * __m + __param._M_d); | |
1464 | ||
1465 | bool __reject = true; | |
1466 | do | |
1467 | { | |
1468 | const double __u = __c * __aurng(); | |
c279067a | 1469 | const double __e = -std::log(1.0 - __aurng()); |
fca66f47 | 1470 | |
1471 | double __w = 0.0; | |
1472 | ||
1473 | if (__u <= __c1) | |
1474 | { | |
1475 | const double __n = _M_nd(__urng); | |
1476 | const double __y = -std::abs(__n) * __param._M_sm - 1; | |
1477 | __x = std::floor(__y); | |
1478 | __w = -__n * __n / 2; | |
1479 | if (__x < -__m) | |
1480 | continue; | |
1481 | } | |
1482 | else if (__u <= __c2) | |
1483 | { | |
1484 | const double __n = _M_nd(__urng); | |
1485 | const double __y = 1 + std::abs(__n) * __param._M_scx; | |
1486 | __x = std::ceil(__y); | |
1487 | __w = __y * (2 - __y) * __param._M_1cx; | |
1488 | if (__x > __param._M_d) | |
1489 | continue; | |
1490 | } | |
1491 | else if (__u <= __c3) | |
1492 | // NB: This case not in the book, nor in the Errata, | |
1493 | // but should be ok... | |
1494 | __x = -1; | |
1495 | else if (__u <= __c4) | |
1496 | __x = 0; | |
1497 | else if (__u <= __c5) | |
1498 | __x = 1; | |
1499 | else | |
1500 | { | |
c279067a | 1501 | const double __v = -std::log(1.0 - __aurng()); |
fca66f47 | 1502 | const double __y = __param._M_d |
1503 | + __v * __2cx / __param._M_d; | |
1504 | __x = std::ceil(__y); | |
1505 | __w = -__param._M_d * __param._M_1cx * (1 + __y / 2); | |
1506 | } | |
1507 | ||
1508 | __reject = (__w - __e - __x * __param._M_lm_thr | |
1509 | > __param._M_lfm - std::lgamma(__x + __m + 1)); | |
1510 | ||
1511 | __reject |= __x + __m >= __thr; | |
1512 | ||
1513 | } while (__reject); | |
1514 | ||
1515 | return result_type(__x + __m + __naf); | |
1516 | } | |
1517 | else | |
1518 | #endif | |
1519 | { | |
1520 | _IntType __x = 0; | |
1521 | double __prod = 1.0; | |
1522 | ||
1523 | do | |
1524 | { | |
1525 | __prod *= __aurng(); | |
1526 | __x += 1; | |
1527 | } | |
1528 | while (__prod > __param._M_lm_thr); | |
1529 | ||
1530 | return __x - 1; | |
1531 | } | |
1532 | } | |
1533 | ||
308b344d | 1534 | template<typename _IntType> |
1535 | template<typename _ForwardIterator, | |
1536 | typename _UniformRandomNumberGenerator> | |
1537 | void | |
1538 | poisson_distribution<_IntType>:: | |
1539 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1540 | _UniformRandomNumberGenerator& __urng, | |
1541 | const param_type& __param) | |
1542 | { | |
1543 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1544 | // We could duplicate everything from operator()... | |
1545 | while (__f != __t) | |
1546 | *__f++ = this->operator()(__urng, __param); | |
1547 | } | |
1548 | ||
fca66f47 | 1549 | template<typename _IntType, |
1550 | typename _CharT, typename _Traits> | |
1551 | std::basic_ostream<_CharT, _Traits>& | |
1552 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1553 | const poisson_distribution<_IntType>& __x) | |
1554 | { | |
1555 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
1556 | typedef typename __ostream_type::ios_base __ios_base; | |
1557 | ||
1558 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1559 | const _CharT __fill = __os.fill(); | |
1560 | const std::streamsize __precision = __os.precision(); | |
1561 | const _CharT __space = __os.widen(' '); | |
1562 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1563 | __os.fill(__space); | |
245c5a20 | 1564 | __os.precision(std::numeric_limits<double>::max_digits10); |
fca66f47 | 1565 | |
1566 | __os << __x.mean() << __space << __x._M_nd; | |
1567 | ||
1568 | __os.flags(__flags); | |
1569 | __os.fill(__fill); | |
1570 | __os.precision(__precision); | |
1571 | return __os; | |
1572 | } | |
1573 | ||
1574 | template<typename _IntType, | |
1575 | typename _CharT, typename _Traits> | |
1576 | std::basic_istream<_CharT, _Traits>& | |
1577 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
1578 | poisson_distribution<_IntType>& __x) | |
1579 | { | |
1580 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
1581 | typedef typename __istream_type::ios_base __ios_base; | |
1582 | ||
1583 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
1584 | __is.flags(__ios_base::skipws); | |
1585 | ||
1586 | double __mean; | |
1587 | __is >> __mean >> __x._M_nd; | |
1588 | __x.param(typename poisson_distribution<_IntType>::param_type(__mean)); | |
1589 | ||
1590 | __is.flags(__flags); | |
1591 | return __is; | |
1592 | } | |
1593 | ||
1594 | ||
1595 | template<typename _IntType> | |
1596 | void | |
1597 | binomial_distribution<_IntType>::param_type:: | |
1598 | _M_initialize() | |
1599 | { | |
1600 | const double __p12 = _M_p <= 0.5 ? _M_p : 1.0 - _M_p; | |
1601 | ||
1602 | _M_easy = true; | |
1603 | ||
1604 | #if _GLIBCXX_USE_C99_MATH_TR1 | |
1605 | if (_M_t * __p12 >= 8) | |
1606 | { | |
1607 | _M_easy = false; | |
1608 | const double __np = std::floor(_M_t * __p12); | |
1609 | const double __pa = __np / _M_t; | |
1610 | const double __1p = 1 - __pa; | |
1611 | ||
1612 | const double __pi_4 = 0.7853981633974483096156608458198757L; | |
1613 | const double __d1x = | |
1614 | std::sqrt(__np * __1p * std::log(32 * __np | |
1615 | / (81 * __pi_4 * __1p))); | |
b16ebdf3 | 1616 | _M_d1 = std::round(std::max<double>(1.0, __d1x)); |
fca66f47 | 1617 | const double __d2x = |
1618 | std::sqrt(__np * __1p * std::log(32 * _M_t * __1p | |
1619 | / (__pi_4 * __pa))); | |
b16ebdf3 | 1620 | _M_d2 = std::round(std::max<double>(1.0, __d2x)); |
fca66f47 | 1621 | |
1622 | // sqrt(pi / 2) | |
1623 | const double __spi_2 = 1.2533141373155002512078826424055226L; | |
1624 | _M_s1 = std::sqrt(__np * __1p) * (1 + _M_d1 / (4 * __np)); | |
1625 | _M_s2 = std::sqrt(__np * __1p) * (1 + _M_d2 / (4 * _M_t * __1p)); | |
1626 | _M_c = 2 * _M_d1 / __np; | |
1627 | _M_a1 = std::exp(_M_c) * _M_s1 * __spi_2; | |
1628 | const double __a12 = _M_a1 + _M_s2 * __spi_2; | |
1629 | const double __s1s = _M_s1 * _M_s1; | |
1630 | _M_a123 = __a12 + (std::exp(_M_d1 / (_M_t * __1p)) | |
1631 | * 2 * __s1s / _M_d1 | |
1632 | * std::exp(-_M_d1 * _M_d1 / (2 * __s1s))); | |
1633 | const double __s2s = _M_s2 * _M_s2; | |
1634 | _M_s = (_M_a123 + 2 * __s2s / _M_d2 | |
1635 | * std::exp(-_M_d2 * _M_d2 / (2 * __s2s))); | |
1636 | _M_lf = (std::lgamma(__np + 1) | |
1637 | + std::lgamma(_M_t - __np + 1)); | |
1638 | _M_lp1p = std::log(__pa / __1p); | |
1639 | ||
1640 | _M_q = -std::log(1 - (__p12 - __pa) / __1p); | |
1641 | } | |
1642 | else | |
1643 | #endif | |
1644 | _M_q = -std::log(1 - __p12); | |
1645 | } | |
1646 | ||
1647 | template<typename _IntType> | |
1648 | template<typename _UniformRandomNumberGenerator> | |
1649 | typename binomial_distribution<_IntType>::result_type | |
1650 | binomial_distribution<_IntType>:: | |
503700a9 | 1651 | _M_waiting(_UniformRandomNumberGenerator& __urng, |
1652 | _IntType __t, double __q) | |
fca66f47 | 1653 | { |
1654 | _IntType __x = 0; | |
1655 | double __sum = 0.0; | |
1656 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
1657 | __aurng(__urng); | |
1658 | ||
1659 | do | |
1660 | { | |
32eabe8a | 1661 | if (__t == __x) |
3c9cd0e9 | 1662 | return __x; |
1663 | const double __e = -std::log(1.0 - __aurng()); | |
fca66f47 | 1664 | __sum += __e / (__t - __x); |
1665 | __x += 1; | |
1666 | } | |
503700a9 | 1667 | while (__sum <= __q); |
fca66f47 | 1668 | |
1669 | return __x - 1; | |
1670 | } | |
1671 | ||
1672 | /** | |
1673 | * A rejection algorithm when t * p >= 8 and a simple waiting time | |
1674 | * method - the second in the referenced book - otherwise. | |
1675 | * NB: The former is available only if _GLIBCXX_USE_C99_MATH_TR1 | |
1676 | * is defined. | |
1677 | * | |
1678 | * Reference: | |
72117d76 | 1679 | * Devroye, L. Non-Uniform Random Variates Generation. Springer-Verlag, |
fca66f47 | 1680 | * New York, 1986, Ch. X, Sect. 4 (+ Errata!). |
1681 | */ | |
1682 | template<typename _IntType> | |
1683 | template<typename _UniformRandomNumberGenerator> | |
1684 | typename binomial_distribution<_IntType>::result_type | |
1685 | binomial_distribution<_IntType>:: | |
1686 | operator()(_UniformRandomNumberGenerator& __urng, | |
1687 | const param_type& __param) | |
1688 | { | |
1689 | result_type __ret; | |
1690 | const _IntType __t = __param.t(); | |
a872aebe | 1691 | const double __p = __param.p(); |
fca66f47 | 1692 | const double __p12 = __p <= 0.5 ? __p : 1.0 - __p; |
1693 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
1694 | __aurng(__urng); | |
1695 | ||
1696 | #if _GLIBCXX_USE_C99_MATH_TR1 | |
1697 | if (!__param._M_easy) | |
1698 | { | |
1699 | double __x; | |
1700 | ||
1701 | // See comments above... | |
1702 | const double __naf = | |
1703 | (1 - std::numeric_limits<double>::epsilon()) / 2; | |
1704 | const double __thr = | |
1705 | std::numeric_limits<_IntType>::max() + __naf; | |
1706 | ||
1707 | const double __np = std::floor(__t * __p12); | |
1708 | ||
1709 | // sqrt(pi / 2) | |
1710 | const double __spi_2 = 1.2533141373155002512078826424055226L; | |
1711 | const double __a1 = __param._M_a1; | |
1712 | const double __a12 = __a1 + __param._M_s2 * __spi_2; | |
1713 | const double __a123 = __param._M_a123; | |
1714 | const double __s1s = __param._M_s1 * __param._M_s1; | |
1715 | const double __s2s = __param._M_s2 * __param._M_s2; | |
1716 | ||
1717 | bool __reject; | |
1718 | do | |
1719 | { | |
1720 | const double __u = __param._M_s * __aurng(); | |
1721 | ||
1722 | double __v; | |
1723 | ||
1724 | if (__u <= __a1) | |
1725 | { | |
1726 | const double __n = _M_nd(__urng); | |
1727 | const double __y = __param._M_s1 * std::abs(__n); | |
1728 | __reject = __y >= __param._M_d1; | |
1729 | if (!__reject) | |
1730 | { | |
c279067a | 1731 | const double __e = -std::log(1.0 - __aurng()); |
fca66f47 | 1732 | __x = std::floor(__y); |
1733 | __v = -__e - __n * __n / 2 + __param._M_c; | |
1734 | } | |
1735 | } | |
1736 | else if (__u <= __a12) | |
1737 | { | |
1738 | const double __n = _M_nd(__urng); | |
1739 | const double __y = __param._M_s2 * std::abs(__n); | |
1740 | __reject = __y >= __param._M_d2; | |
1741 | if (!__reject) | |
1742 | { | |
c279067a | 1743 | const double __e = -std::log(1.0 - __aurng()); |
fca66f47 | 1744 | __x = std::floor(-__y); |
1745 | __v = -__e - __n * __n / 2; | |
1746 | } | |
1747 | } | |
1748 | else if (__u <= __a123) | |
1749 | { | |
c279067a | 1750 | const double __e1 = -std::log(1.0 - __aurng()); |
1751 | const double __e2 = -std::log(1.0 - __aurng()); | |
fca66f47 | 1752 | |
1753 | const double __y = __param._M_d1 | |
1754 | + 2 * __s1s * __e1 / __param._M_d1; | |
1755 | __x = std::floor(__y); | |
1756 | __v = (-__e2 + __param._M_d1 * (1 / (__t - __np) | |
1757 | -__y / (2 * __s1s))); | |
1758 | __reject = false; | |
1759 | } | |
1760 | else | |
1761 | { | |
c279067a | 1762 | const double __e1 = -std::log(1.0 - __aurng()); |
1763 | const double __e2 = -std::log(1.0 - __aurng()); | |
fca66f47 | 1764 | |
1765 | const double __y = __param._M_d2 | |
1766 | + 2 * __s2s * __e1 / __param._M_d2; | |
1767 | __x = std::floor(-__y); | |
1768 | __v = -__e2 - __param._M_d2 * __y / (2 * __s2s); | |
1769 | __reject = false; | |
1770 | } | |
1771 | ||
1772 | __reject = __reject || __x < -__np || __x > __t - __np; | |
1773 | if (!__reject) | |
1774 | { | |
1775 | const double __lfx = | |
1776 | std::lgamma(__np + __x + 1) | |
1777 | + std::lgamma(__t - (__np + __x) + 1); | |
1778 | __reject = __v > __param._M_lf - __lfx | |
1779 | + __x * __param._M_lp1p; | |
1780 | } | |
1781 | ||
1782 | __reject |= __x + __np >= __thr; | |
1783 | } | |
1784 | while (__reject); | |
1785 | ||
1786 | __x += __np + __naf; | |
1787 | ||
503700a9 | 1788 | const _IntType __z = _M_waiting(__urng, __t - _IntType(__x), |
1789 | __param._M_q); | |
fca66f47 | 1790 | __ret = _IntType(__x) + __z; |
1791 | } | |
1792 | else | |
1793 | #endif | |
503700a9 | 1794 | __ret = _M_waiting(__urng, __t, __param._M_q); |
fca66f47 | 1795 | |
1796 | if (__p12 != __p) | |
1797 | __ret = __t - __ret; | |
1798 | return __ret; | |
1799 | } | |
1800 | ||
308b344d | 1801 | template<typename _IntType> |
1802 | template<typename _ForwardIterator, | |
1803 | typename _UniformRandomNumberGenerator> | |
1804 | void | |
1805 | binomial_distribution<_IntType>:: | |
1806 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1807 | _UniformRandomNumberGenerator& __urng, | |
1808 | const param_type& __param) | |
1809 | { | |
1810 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1811 | // We could duplicate everything from operator()... | |
1812 | while (__f != __t) | |
1813 | *__f++ = this->operator()(__urng, __param); | |
1814 | } | |
1815 | ||
fca66f47 | 1816 | template<typename _IntType, |
1817 | typename _CharT, typename _Traits> | |
1818 | std::basic_ostream<_CharT, _Traits>& | |
1819 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1820 | const binomial_distribution<_IntType>& __x) | |
1821 | { | |
1822 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
1823 | typedef typename __ostream_type::ios_base __ios_base; | |
1824 | ||
1825 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1826 | const _CharT __fill = __os.fill(); | |
1827 | const std::streamsize __precision = __os.precision(); | |
1828 | const _CharT __space = __os.widen(' '); | |
1829 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1830 | __os.fill(__space); | |
245c5a20 | 1831 | __os.precision(std::numeric_limits<double>::max_digits10); |
fca66f47 | 1832 | |
1833 | __os << __x.t() << __space << __x.p() | |
1834 | << __space << __x._M_nd; | |
1835 | ||
1836 | __os.flags(__flags); | |
1837 | __os.fill(__fill); | |
1838 | __os.precision(__precision); | |
1839 | return __os; | |
1840 | } | |
1841 | ||
1842 | template<typename _IntType, | |
1843 | typename _CharT, typename _Traits> | |
1844 | std::basic_istream<_CharT, _Traits>& | |
1845 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
1846 | binomial_distribution<_IntType>& __x) | |
1847 | { | |
1848 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
1849 | typedef typename __istream_type::ios_base __ios_base; | |
1850 | ||
1851 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
1852 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
1853 | ||
1854 | _IntType __t; | |
1855 | double __p; | |
1856 | __is >> __t >> __p >> __x._M_nd; | |
1857 | __x.param(typename binomial_distribution<_IntType>:: | |
1858 | param_type(__t, __p)); | |
1859 | ||
1860 | __is.flags(__flags); | |
1861 | return __is; | |
1862 | } | |
1863 | ||
1864 | ||
308b344d | 1865 | template<typename _RealType> |
1866 | template<typename _ForwardIterator, | |
1867 | typename _UniformRandomNumberGenerator> | |
1868 | void | |
1869 | std::exponential_distribution<_RealType>:: | |
1870 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1871 | _UniformRandomNumberGenerator& __urng, | |
1872 | const param_type& __p) | |
1873 | { | |
1874 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1875 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
1876 | __aurng(__urng); | |
1877 | while (__f != __t) | |
c279067a | 1878 | *__f++ = -std::log(result_type(1) - __aurng()) / __p.lambda(); |
308b344d | 1879 | } |
1880 | ||
fca66f47 | 1881 | template<typename _RealType, typename _CharT, typename _Traits> |
1882 | std::basic_ostream<_CharT, _Traits>& | |
1883 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
1884 | const exponential_distribution<_RealType>& __x) | |
1885 | { | |
1886 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
1887 | typedef typename __ostream_type::ios_base __ios_base; | |
1888 | ||
1889 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
1890 | const _CharT __fill = __os.fill(); | |
1891 | const std::streamsize __precision = __os.precision(); | |
1892 | __os.flags(__ios_base::scientific | __ios_base::left); | |
1893 | __os.fill(__os.widen(' ')); | |
245c5a20 | 1894 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
fca66f47 | 1895 | |
1896 | __os << __x.lambda(); | |
1897 | ||
1898 | __os.flags(__flags); | |
1899 | __os.fill(__fill); | |
1900 | __os.precision(__precision); | |
1901 | return __os; | |
1902 | } | |
1903 | ||
1904 | template<typename _RealType, typename _CharT, typename _Traits> | |
1905 | std::basic_istream<_CharT, _Traits>& | |
1906 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
1907 | exponential_distribution<_RealType>& __x) | |
1908 | { | |
1909 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
1910 | typedef typename __istream_type::ios_base __ios_base; | |
1911 | ||
1912 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
1913 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
1914 | ||
1915 | _RealType __lambda; | |
1916 | __is >> __lambda; | |
1917 | __x.param(typename exponential_distribution<_RealType>:: | |
1918 | param_type(__lambda)); | |
1919 | ||
1920 | __is.flags(__flags); | |
1921 | return __is; | |
1922 | } | |
1923 | ||
1924 | ||
fca66f47 | 1925 | /** |
1926 | * Polar method due to Marsaglia. | |
1927 | * | |
72117d76 | 1928 | * Devroye, L. Non-Uniform Random Variates Generation. Springer-Verlag, |
fca66f47 | 1929 | * New York, 1986, Ch. V, Sect. 4.4. |
1930 | */ | |
1931 | template<typename _RealType> | |
1932 | template<typename _UniformRandomNumberGenerator> | |
1933 | typename normal_distribution<_RealType>::result_type | |
1934 | normal_distribution<_RealType>:: | |
1935 | operator()(_UniformRandomNumberGenerator& __urng, | |
1936 | const param_type& __param) | |
1937 | { | |
1938 | result_type __ret; | |
1939 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
1940 | __aurng(__urng); | |
1941 | ||
1942 | if (_M_saved_available) | |
1943 | { | |
1944 | _M_saved_available = false; | |
1945 | __ret = _M_saved; | |
1946 | } | |
1947 | else | |
1948 | { | |
1949 | result_type __x, __y, __r2; | |
1950 | do | |
1951 | { | |
1952 | __x = result_type(2.0) * __aurng() - 1.0; | |
1953 | __y = result_type(2.0) * __aurng() - 1.0; | |
1954 | __r2 = __x * __x + __y * __y; | |
1955 | } | |
1956 | while (__r2 > 1.0 || __r2 == 0.0); | |
1957 | ||
1958 | const result_type __mult = std::sqrt(-2 * std::log(__r2) / __r2); | |
1959 | _M_saved = __x * __mult; | |
1960 | _M_saved_available = true; | |
1961 | __ret = __y * __mult; | |
1962 | } | |
1963 | ||
1964 | __ret = __ret * __param.stddev() + __param.mean(); | |
1965 | return __ret; | |
1966 | } | |
1967 | ||
308b344d | 1968 | template<typename _RealType> |
1969 | template<typename _ForwardIterator, | |
1970 | typename _UniformRandomNumberGenerator> | |
1971 | void | |
1972 | normal_distribution<_RealType>:: | |
1973 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1974 | _UniformRandomNumberGenerator& __urng, | |
1975 | const param_type& __param) | |
1976 | { | |
1977 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
1978 | ||
1979 | if (__f == __t) | |
1980 | return; | |
1981 | ||
1982 | if (_M_saved_available) | |
1983 | { | |
1984 | _M_saved_available = false; | |
1985 | *__f++ = _M_saved * __param.stddev() + __param.mean(); | |
1986 | ||
1987 | if (__f == __t) | |
1988 | return; | |
1989 | } | |
1990 | ||
1991 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
1992 | __aurng(__urng); | |
1993 | ||
1994 | while (__f + 1 < __t) | |
1995 | { | |
1996 | result_type __x, __y, __r2; | |
1997 | do | |
1998 | { | |
1999 | __x = result_type(2.0) * __aurng() - 1.0; | |
2000 | __y = result_type(2.0) * __aurng() - 1.0; | |
2001 | __r2 = __x * __x + __y * __y; | |
2002 | } | |
2003 | while (__r2 > 1.0 || __r2 == 0.0); | |
2004 | ||
2005 | const result_type __mult = std::sqrt(-2 * std::log(__r2) / __r2); | |
2006 | *__f++ = __y * __mult * __param.stddev() + __param.mean(); | |
2007 | *__f++ = __x * __mult * __param.stddev() + __param.mean(); | |
2008 | } | |
2009 | ||
2010 | if (__f != __t) | |
2011 | { | |
2012 | result_type __x, __y, __r2; | |
2013 | do | |
2014 | { | |
2015 | __x = result_type(2.0) * __aurng() - 1.0; | |
2016 | __y = result_type(2.0) * __aurng() - 1.0; | |
2017 | __r2 = __x * __x + __y * __y; | |
2018 | } | |
2019 | while (__r2 > 1.0 || __r2 == 0.0); | |
2020 | ||
2021 | const result_type __mult = std::sqrt(-2 * std::log(__r2) / __r2); | |
2022 | _M_saved = __x * __mult; | |
2023 | _M_saved_available = true; | |
2024 | *__f = __y * __mult * __param.stddev() + __param.mean(); | |
2025 | } | |
2026 | } | |
2027 | ||
6d2e94ab | 2028 | template<typename _RealType> |
2029 | bool | |
2030 | operator==(const std::normal_distribution<_RealType>& __d1, | |
2031 | const std::normal_distribution<_RealType>& __d2) | |
2032 | { | |
2033 | if (__d1._M_param == __d2._M_param | |
2034 | && __d1._M_saved_available == __d2._M_saved_available) | |
2035 | { | |
2036 | if (__d1._M_saved_available | |
2037 | && __d1._M_saved == __d2._M_saved) | |
2038 | return true; | |
2039 | else if(!__d1._M_saved_available) | |
2040 | return true; | |
2041 | else | |
2042 | return false; | |
2043 | } | |
2044 | else | |
2045 | return false; | |
2046 | } | |
2047 | ||
fca66f47 | 2048 | template<typename _RealType, typename _CharT, typename _Traits> |
2049 | std::basic_ostream<_CharT, _Traits>& | |
2050 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2051 | const normal_distribution<_RealType>& __x) | |
2052 | { | |
2053 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
2054 | typedef typename __ostream_type::ios_base __ios_base; | |
2055 | ||
2056 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2057 | const _CharT __fill = __os.fill(); | |
2058 | const std::streamsize __precision = __os.precision(); | |
2059 | const _CharT __space = __os.widen(' '); | |
2060 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2061 | __os.fill(__space); | |
245c5a20 | 2062 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
fca66f47 | 2063 | |
2064 | __os << __x.mean() << __space << __x.stddev() | |
2065 | << __space << __x._M_saved_available; | |
2066 | if (__x._M_saved_available) | |
2067 | __os << __space << __x._M_saved; | |
2068 | ||
2069 | __os.flags(__flags); | |
2070 | __os.fill(__fill); | |
2071 | __os.precision(__precision); | |
2072 | return __os; | |
2073 | } | |
2074 | ||
2075 | template<typename _RealType, typename _CharT, typename _Traits> | |
2076 | std::basic_istream<_CharT, _Traits>& | |
2077 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2078 | normal_distribution<_RealType>& __x) | |
2079 | { | |
2080 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
2081 | typedef typename __istream_type::ios_base __ios_base; | |
2082 | ||
2083 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2084 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2085 | ||
2086 | double __mean, __stddev; | |
2087 | __is >> __mean >> __stddev | |
2088 | >> __x._M_saved_available; | |
2089 | if (__x._M_saved_available) | |
2090 | __is >> __x._M_saved; | |
2091 | __x.param(typename normal_distribution<_RealType>:: | |
2092 | param_type(__mean, __stddev)); | |
2093 | ||
2094 | __is.flags(__flags); | |
2095 | return __is; | |
2096 | } | |
2097 | ||
2098 | ||
308b344d | 2099 | template<typename _RealType> |
2100 | template<typename _ForwardIterator, | |
2101 | typename _UniformRandomNumberGenerator> | |
2102 | void | |
2103 | lognormal_distribution<_RealType>:: | |
2104 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2105 | _UniformRandomNumberGenerator& __urng, | |
2106 | const param_type& __p) | |
2107 | { | |
2108 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2109 | while (__f != __t) | |
2110 | *__f++ = std::exp(__p.s() * _M_nd(__urng) + __p.m()); | |
2111 | } | |
2112 | ||
fca66f47 | 2113 | template<typename _RealType, typename _CharT, typename _Traits> |
2114 | std::basic_ostream<_CharT, _Traits>& | |
2115 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2116 | const lognormal_distribution<_RealType>& __x) | |
2117 | { | |
2118 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
2119 | typedef typename __ostream_type::ios_base __ios_base; | |
2120 | ||
2121 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2122 | const _CharT __fill = __os.fill(); | |
2123 | const std::streamsize __precision = __os.precision(); | |
2124 | const _CharT __space = __os.widen(' '); | |
2125 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2126 | __os.fill(__space); | |
245c5a20 | 2127 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
fca66f47 | 2128 | |
d37c6500 | 2129 | __os << __x.m() << __space << __x.s() |
2130 | << __space << __x._M_nd; | |
fca66f47 | 2131 | |
2132 | __os.flags(__flags); | |
2133 | __os.fill(__fill); | |
2134 | __os.precision(__precision); | |
2135 | return __os; | |
2136 | } | |
2137 | ||
2138 | template<typename _RealType, typename _CharT, typename _Traits> | |
2139 | std::basic_istream<_CharT, _Traits>& | |
2140 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2141 | lognormal_distribution<_RealType>& __x) | |
2142 | { | |
2143 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
2144 | typedef typename __istream_type::ios_base __ios_base; | |
2145 | ||
2146 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2147 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2148 | ||
2149 | _RealType __m, __s; | |
d37c6500 | 2150 | __is >> __m >> __s >> __x._M_nd; |
fca66f47 | 2151 | __x.param(typename lognormal_distribution<_RealType>:: |
2152 | param_type(__m, __s)); | |
2153 | ||
2154 | __is.flags(__flags); | |
2155 | return __is; | |
2156 | } | |
2157 | ||
71aa0c9f | 2158 | template<typename _RealType> |
2159 | template<typename _ForwardIterator, | |
2160 | typename _UniformRandomNumberGenerator> | |
2161 | void | |
2162 | std::chi_squared_distribution<_RealType>:: | |
2163 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2164 | _UniformRandomNumberGenerator& __urng) | |
2165 | { | |
2166 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2167 | while (__f != __t) | |
2168 | *__f++ = 2 * _M_gd(__urng); | |
2169 | } | |
fca66f47 | 2170 | |
308b344d | 2171 | template<typename _RealType> |
2172 | template<typename _ForwardIterator, | |
2173 | typename _UniformRandomNumberGenerator> | |
2174 | void | |
2175 | std::chi_squared_distribution<_RealType>:: | |
2176 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2177 | _UniformRandomNumberGenerator& __urng, | |
71aa0c9f | 2178 | const typename |
2179 | std::gamma_distribution<result_type>::param_type& __p) | |
308b344d | 2180 | { |
2181 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2182 | while (__f != __t) | |
2183 | *__f++ = 2 * _M_gd(__urng, __p); | |
2184 | } | |
2185 | ||
fca66f47 | 2186 | template<typename _RealType, typename _CharT, typename _Traits> |
2187 | std::basic_ostream<_CharT, _Traits>& | |
2188 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2189 | const chi_squared_distribution<_RealType>& __x) | |
2190 | { | |
2191 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
2192 | typedef typename __ostream_type::ios_base __ios_base; | |
2193 | ||
2194 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2195 | const _CharT __fill = __os.fill(); | |
2196 | const std::streamsize __precision = __os.precision(); | |
2197 | const _CharT __space = __os.widen(' '); | |
2198 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2199 | __os.fill(__space); | |
245c5a20 | 2200 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
fca66f47 | 2201 | |
520d23b7 | 2202 | __os << __x.n() << __space << __x._M_gd; |
fca66f47 | 2203 | |
2204 | __os.flags(__flags); | |
2205 | __os.fill(__fill); | |
2206 | __os.precision(__precision); | |
2207 | return __os; | |
2208 | } | |
2209 | ||
2210 | template<typename _RealType, typename _CharT, typename _Traits> | |
2211 | std::basic_istream<_CharT, _Traits>& | |
2212 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2213 | chi_squared_distribution<_RealType>& __x) | |
2214 | { | |
2215 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
2216 | typedef typename __istream_type::ios_base __ios_base; | |
2217 | ||
2218 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2219 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2220 | ||
2221 | _RealType __n; | |
520d23b7 | 2222 | __is >> __n >> __x._M_gd; |
fca66f47 | 2223 | __x.param(typename chi_squared_distribution<_RealType>:: |
2224 | param_type(__n)); | |
2225 | ||
2226 | __is.flags(__flags); | |
2227 | return __is; | |
2228 | } | |
2229 | ||
2230 | ||
2231 | template<typename _RealType> | |
2232 | template<typename _UniformRandomNumberGenerator> | |
2233 | typename cauchy_distribution<_RealType>::result_type | |
2234 | cauchy_distribution<_RealType>:: | |
2235 | operator()(_UniformRandomNumberGenerator& __urng, | |
2236 | const param_type& __p) | |
2237 | { | |
2238 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
2239 | __aurng(__urng); | |
2240 | _RealType __u; | |
2241 | do | |
d900e4f3 | 2242 | __u = __aurng(); |
fca66f47 | 2243 | while (__u == 0.5); |
2244 | ||
d900e4f3 | 2245 | const _RealType __pi = 3.1415926535897932384626433832795029L; |
2246 | return __p.a() + __p.b() * std::tan(__pi * __u); | |
fca66f47 | 2247 | } |
2248 | ||
308b344d | 2249 | template<typename _RealType> |
2250 | template<typename _ForwardIterator, | |
2251 | typename _UniformRandomNumberGenerator> | |
2252 | void | |
2253 | cauchy_distribution<_RealType>:: | |
2254 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2255 | _UniformRandomNumberGenerator& __urng, | |
2256 | const param_type& __p) | |
2257 | { | |
2258 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2259 | const _RealType __pi = 3.1415926535897932384626433832795029L; | |
2260 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
2261 | __aurng(__urng); | |
2262 | while (__f != __t) | |
2263 | { | |
2264 | _RealType __u; | |
2265 | do | |
2266 | __u = __aurng(); | |
2267 | while (__u == 0.5); | |
2268 | ||
2269 | *__f++ = __p.a() + __p.b() * std::tan(__pi * __u); | |
2270 | } | |
2271 | } | |
2272 | ||
fca66f47 | 2273 | template<typename _RealType, typename _CharT, typename _Traits> |
2274 | std::basic_ostream<_CharT, _Traits>& | |
2275 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2276 | const cauchy_distribution<_RealType>& __x) | |
2277 | { | |
2278 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
2279 | typedef typename __ostream_type::ios_base __ios_base; | |
2280 | ||
2281 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2282 | const _CharT __fill = __os.fill(); | |
2283 | const std::streamsize __precision = __os.precision(); | |
2284 | const _CharT __space = __os.widen(' '); | |
2285 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2286 | __os.fill(__space); | |
245c5a20 | 2287 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
fca66f47 | 2288 | |
2289 | __os << __x.a() << __space << __x.b(); | |
2290 | ||
2291 | __os.flags(__flags); | |
2292 | __os.fill(__fill); | |
2293 | __os.precision(__precision); | |
2294 | return __os; | |
2295 | } | |
2296 | ||
2297 | template<typename _RealType, typename _CharT, typename _Traits> | |
2298 | std::basic_istream<_CharT, _Traits>& | |
2299 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2300 | cauchy_distribution<_RealType>& __x) | |
2301 | { | |
2302 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
2303 | typedef typename __istream_type::ios_base __ios_base; | |
2304 | ||
2305 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2306 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2307 | ||
2308 | _RealType __a, __b; | |
2309 | __is >> __a >> __b; | |
2310 | __x.param(typename cauchy_distribution<_RealType>:: | |
2311 | param_type(__a, __b)); | |
2312 | ||
2313 | __is.flags(__flags); | |
2314 | return __is; | |
2315 | } | |
2316 | ||
2317 | ||
308b344d | 2318 | template<typename _RealType> |
2319 | template<typename _ForwardIterator, | |
2320 | typename _UniformRandomNumberGenerator> | |
2321 | void | |
2322 | std::fisher_f_distribution<_RealType>:: | |
2323 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2324 | _UniformRandomNumberGenerator& __urng) | |
2325 | { | |
2326 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2327 | while (__f != __t) | |
2328 | *__f++ = ((_M_gd_x(__urng) * n()) / (_M_gd_y(__urng) * m())); | |
2329 | } | |
2330 | ||
2331 | template<typename _RealType> | |
2332 | template<typename _ForwardIterator, | |
2333 | typename _UniformRandomNumberGenerator> | |
2334 | void | |
2335 | std::fisher_f_distribution<_RealType>:: | |
2336 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2337 | _UniformRandomNumberGenerator& __urng, | |
2338 | const param_type& __p) | |
2339 | { | |
2340 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2341 | typedef typename std::gamma_distribution<result_type>::param_type | |
2342 | param_type; | |
2343 | param_type __p1(__p.m() / 2); | |
2344 | param_type __p2(__p.n() / 2); | |
2345 | while (__f != __t) | |
2346 | *__f++ = ((_M_gd_x(__urng, __p1) * n()) | |
2347 | / (_M_gd_y(__urng, __p2) * m())); | |
2348 | } | |
2349 | ||
fca66f47 | 2350 | template<typename _RealType, typename _CharT, typename _Traits> |
2351 | std::basic_ostream<_CharT, _Traits>& | |
2352 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2353 | const fisher_f_distribution<_RealType>& __x) | |
2354 | { | |
2355 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
2356 | typedef typename __ostream_type::ios_base __ios_base; | |
2357 | ||
2358 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2359 | const _CharT __fill = __os.fill(); | |
2360 | const std::streamsize __precision = __os.precision(); | |
2361 | const _CharT __space = __os.widen(' '); | |
2362 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2363 | __os.fill(__space); | |
245c5a20 | 2364 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
fca66f47 | 2365 | |
520d23b7 | 2366 | __os << __x.m() << __space << __x.n() |
2367 | << __space << __x._M_gd_x << __space << __x._M_gd_y; | |
fca66f47 | 2368 | |
2369 | __os.flags(__flags); | |
2370 | __os.fill(__fill); | |
2371 | __os.precision(__precision); | |
2372 | return __os; | |
2373 | } | |
2374 | ||
2375 | template<typename _RealType, typename _CharT, typename _Traits> | |
2376 | std::basic_istream<_CharT, _Traits>& | |
2377 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2378 | fisher_f_distribution<_RealType>& __x) | |
2379 | { | |
2380 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
2381 | typedef typename __istream_type::ios_base __ios_base; | |
2382 | ||
2383 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2384 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2385 | ||
2386 | _RealType __m, __n; | |
520d23b7 | 2387 | __is >> __m >> __n >> __x._M_gd_x >> __x._M_gd_y; |
fca66f47 | 2388 | __x.param(typename fisher_f_distribution<_RealType>:: |
2389 | param_type(__m, __n)); | |
2390 | ||
2391 | __is.flags(__flags); | |
2392 | return __is; | |
2393 | } | |
2394 | ||
2395 | ||
308b344d | 2396 | template<typename _RealType> |
2397 | template<typename _ForwardIterator, | |
2398 | typename _UniformRandomNumberGenerator> | |
2399 | void | |
2400 | std::student_t_distribution<_RealType>:: | |
2401 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2402 | _UniformRandomNumberGenerator& __urng) | |
2403 | { | |
2404 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2405 | while (__f != __t) | |
2406 | *__f++ = _M_nd(__urng) * std::sqrt(n() / _M_gd(__urng)); | |
2407 | } | |
2408 | ||
2409 | template<typename _RealType> | |
2410 | template<typename _ForwardIterator, | |
2411 | typename _UniformRandomNumberGenerator> | |
2412 | void | |
2413 | std::student_t_distribution<_RealType>:: | |
2414 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2415 | _UniformRandomNumberGenerator& __urng, | |
2416 | const param_type& __p) | |
2417 | { | |
2418 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2419 | typename std::gamma_distribution<result_type>::param_type | |
2420 | __p2(__p.n() / 2, 2); | |
2421 | while (__f != __t) | |
2422 | *__f++ = _M_nd(__urng) * std::sqrt(__p.n() / _M_gd(__urng, __p2)); | |
2423 | } | |
2424 | ||
fca66f47 | 2425 | template<typename _RealType, typename _CharT, typename _Traits> |
2426 | std::basic_ostream<_CharT, _Traits>& | |
2427 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2428 | const student_t_distribution<_RealType>& __x) | |
2429 | { | |
2430 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
2431 | typedef typename __ostream_type::ios_base __ios_base; | |
2432 | ||
2433 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2434 | const _CharT __fill = __os.fill(); | |
2435 | const std::streamsize __precision = __os.precision(); | |
2436 | const _CharT __space = __os.widen(' '); | |
2437 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2438 | __os.fill(__space); | |
245c5a20 | 2439 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
fca66f47 | 2440 | |
520d23b7 | 2441 | __os << __x.n() << __space << __x._M_nd << __space << __x._M_gd; |
fca66f47 | 2442 | |
2443 | __os.flags(__flags); | |
2444 | __os.fill(__fill); | |
2445 | __os.precision(__precision); | |
2446 | return __os; | |
2447 | } | |
2448 | ||
2449 | template<typename _RealType, typename _CharT, typename _Traits> | |
2450 | std::basic_istream<_CharT, _Traits>& | |
2451 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2452 | student_t_distribution<_RealType>& __x) | |
2453 | { | |
2454 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
2455 | typedef typename __istream_type::ios_base __ios_base; | |
2456 | ||
2457 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2458 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2459 | ||
2460 | _RealType __n; | |
520d23b7 | 2461 | __is >> __n >> __x._M_nd >> __x._M_gd; |
fca66f47 | 2462 | __x.param(typename student_t_distribution<_RealType>::param_type(__n)); |
2463 | ||
2464 | __is.flags(__flags); | |
2465 | return __is; | |
2466 | } | |
2467 | ||
2468 | ||
2469 | template<typename _RealType> | |
2470 | void | |
2471 | gamma_distribution<_RealType>::param_type:: | |
2472 | _M_initialize() | |
2473 | { | |
d37c6500 | 2474 | _M_malpha = _M_alpha < 1.0 ? _M_alpha + _RealType(1.0) : _M_alpha; |
2475 | ||
2476 | const _RealType __a1 = _M_malpha - _RealType(1.0) / _RealType(3.0); | |
2477 | _M_a2 = _RealType(1.0) / std::sqrt(_RealType(9.0) * __a1); | |
fca66f47 | 2478 | } |
2479 | ||
2480 | /** | |
d37c6500 | 2481 | * Marsaglia, G. and Tsang, W. W. |
2482 | * "A Simple Method for Generating Gamma Variables" | |
2483 | * ACM Transactions on Mathematical Software, 26, 3, 363-372, 2000. | |
fca66f47 | 2484 | */ |
2485 | template<typename _RealType> | |
2486 | template<typename _UniformRandomNumberGenerator> | |
2487 | typename gamma_distribution<_RealType>::result_type | |
2488 | gamma_distribution<_RealType>:: | |
2489 | operator()(_UniformRandomNumberGenerator& __urng, | |
2490 | const param_type& __param) | |
2491 | { | |
fca66f47 | 2492 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> |
2493 | __aurng(__urng); | |
2494 | ||
d37c6500 | 2495 | result_type __u, __v, __n; |
2496 | const result_type __a1 = (__param._M_malpha | |
2497 | - _RealType(1.0) / _RealType(3.0)); | |
fca66f47 | 2498 | |
d37c6500 | 2499 | do |
2500 | { | |
fca66f47 | 2501 | do |
2502 | { | |
d37c6500 | 2503 | __n = _M_nd(__urng); |
2504 | __v = result_type(1.0) + __param._M_a2 * __n; | |
fca66f47 | 2505 | } |
d37c6500 | 2506 | while (__v <= 0.0); |
2507 | ||
2508 | __v = __v * __v * __v; | |
2509 | __u = __aurng(); | |
fca66f47 | 2510 | } |
d37c6500 | 2511 | while (__u > result_type(1.0) - 0.331 * __n * __n * __n * __n |
2512 | && (std::log(__u) > (0.5 * __n * __n + __a1 | |
2513 | * (1.0 - __v + std::log(__v))))); | |
2514 | ||
2515 | if (__param.alpha() == __param._M_malpha) | |
2516 | return __a1 * __v * __param.beta(); | |
fca66f47 | 2517 | else |
2518 | { | |
fca66f47 | 2519 | do |
d37c6500 | 2520 | __u = __aurng(); |
2521 | while (__u == 0.0); | |
2522 | ||
2523 | return (std::pow(__u, result_type(1.0) / __param.alpha()) | |
2524 | * __a1 * __v * __param.beta()); | |
fca66f47 | 2525 | } |
fca66f47 | 2526 | } |
2527 | ||
308b344d | 2528 | template<typename _RealType> |
2529 | template<typename _ForwardIterator, | |
2530 | typename _UniformRandomNumberGenerator> | |
2531 | void | |
2532 | gamma_distribution<_RealType>:: | |
2533 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2534 | _UniformRandomNumberGenerator& __urng, | |
2535 | const param_type& __param) | |
2536 | { | |
2537 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2538 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
2539 | __aurng(__urng); | |
2540 | ||
2541 | result_type __u, __v, __n; | |
2542 | const result_type __a1 = (__param._M_malpha | |
2543 | - _RealType(1.0) / _RealType(3.0)); | |
2544 | ||
2545 | if (__param.alpha() == __param._M_malpha) | |
2546 | while (__f != __t) | |
2547 | { | |
2548 | do | |
2549 | { | |
2550 | do | |
2551 | { | |
2552 | __n = _M_nd(__urng); | |
2553 | __v = result_type(1.0) + __param._M_a2 * __n; | |
2554 | } | |
2555 | while (__v <= 0.0); | |
2556 | ||
2557 | __v = __v * __v * __v; | |
2558 | __u = __aurng(); | |
2559 | } | |
2560 | while (__u > result_type(1.0) - 0.331 * __n * __n * __n * __n | |
2561 | && (std::log(__u) > (0.5 * __n * __n + __a1 | |
2562 | * (1.0 - __v + std::log(__v))))); | |
2563 | ||
2564 | *__f++ = __a1 * __v * __param.beta(); | |
2565 | } | |
2566 | else | |
2567 | while (__f != __t) | |
2568 | { | |
2569 | do | |
2570 | { | |
2571 | do | |
2572 | { | |
2573 | __n = _M_nd(__urng); | |
2574 | __v = result_type(1.0) + __param._M_a2 * __n; | |
2575 | } | |
2576 | while (__v <= 0.0); | |
2577 | ||
2578 | __v = __v * __v * __v; | |
2579 | __u = __aurng(); | |
2580 | } | |
2581 | while (__u > result_type(1.0) - 0.331 * __n * __n * __n * __n | |
2582 | && (std::log(__u) > (0.5 * __n * __n + __a1 | |
2583 | * (1.0 - __v + std::log(__v))))); | |
2584 | ||
2585 | do | |
2586 | __u = __aurng(); | |
2587 | while (__u == 0.0); | |
2588 | ||
2589 | *__f++ = (std::pow(__u, result_type(1.0) / __param.alpha()) | |
2590 | * __a1 * __v * __param.beta()); | |
2591 | } | |
2592 | } | |
2593 | ||
fca66f47 | 2594 | template<typename _RealType, typename _CharT, typename _Traits> |
2595 | std::basic_ostream<_CharT, _Traits>& | |
2596 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2597 | const gamma_distribution<_RealType>& __x) | |
2598 | { | |
2599 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
2600 | typedef typename __ostream_type::ios_base __ios_base; | |
2601 | ||
2602 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2603 | const _CharT __fill = __os.fill(); | |
2604 | const std::streamsize __precision = __os.precision(); | |
2605 | const _CharT __space = __os.widen(' '); | |
2606 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2607 | __os.fill(__space); | |
245c5a20 | 2608 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
fca66f47 | 2609 | |
d37c6500 | 2610 | __os << __x.alpha() << __space << __x.beta() |
2611 | << __space << __x._M_nd; | |
fca66f47 | 2612 | |
2613 | __os.flags(__flags); | |
2614 | __os.fill(__fill); | |
2615 | __os.precision(__precision); | |
2616 | return __os; | |
2617 | } | |
2618 | ||
2619 | template<typename _RealType, typename _CharT, typename _Traits> | |
2620 | std::basic_istream<_CharT, _Traits>& | |
2621 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2622 | gamma_distribution<_RealType>& __x) | |
2623 | { | |
2624 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
2625 | typedef typename __istream_type::ios_base __ios_base; | |
2626 | ||
2627 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2628 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2629 | ||
fc0a5a49 | 2630 | _RealType __alpha_val, __beta_val; |
d37c6500 | 2631 | __is >> __alpha_val >> __beta_val >> __x._M_nd; |
fca66f47 | 2632 | __x.param(typename gamma_distribution<_RealType>:: |
fc0a5a49 | 2633 | param_type(__alpha_val, __beta_val)); |
fca66f47 | 2634 | |
2635 | __is.flags(__flags); | |
2636 | return __is; | |
2637 | } | |
2638 | ||
2639 | ||
d37c6500 | 2640 | template<typename _RealType> |
2641 | template<typename _UniformRandomNumberGenerator> | |
2642 | typename weibull_distribution<_RealType>::result_type | |
2643 | weibull_distribution<_RealType>:: | |
2644 | operator()(_UniformRandomNumberGenerator& __urng, | |
2645 | const param_type& __p) | |
2646 | { | |
2647 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
2648 | __aurng(__urng); | |
c279067a | 2649 | return __p.b() * std::pow(-std::log(result_type(1) - __aurng()), |
d37c6500 | 2650 | result_type(1) / __p.a()); |
2651 | } | |
2652 | ||
308b344d | 2653 | template<typename _RealType> |
2654 | template<typename _ForwardIterator, | |
2655 | typename _UniformRandomNumberGenerator> | |
2656 | void | |
2657 | weibull_distribution<_RealType>:: | |
2658 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2659 | _UniformRandomNumberGenerator& __urng, | |
2660 | const param_type& __p) | |
2661 | { | |
2662 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2663 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
2664 | __aurng(__urng); | |
c279067a | 2665 | auto __inv_a = result_type(1) / __p.a(); |
308b344d | 2666 | |
2667 | while (__f != __t) | |
c279067a | 2668 | *__f++ = __p.b() * std::pow(-std::log(result_type(1) - __aurng()), |
2669 | __inv_a); | |
308b344d | 2670 | } |
2671 | ||
fca66f47 | 2672 | template<typename _RealType, typename _CharT, typename _Traits> |
2673 | std::basic_ostream<_CharT, _Traits>& | |
2674 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2675 | const weibull_distribution<_RealType>& __x) | |
2676 | { | |
2677 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
2678 | typedef typename __ostream_type::ios_base __ios_base; | |
2679 | ||
2680 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2681 | const _CharT __fill = __os.fill(); | |
2682 | const std::streamsize __precision = __os.precision(); | |
2683 | const _CharT __space = __os.widen(' '); | |
2684 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2685 | __os.fill(__space); | |
245c5a20 | 2686 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
fca66f47 | 2687 | |
2688 | __os << __x.a() << __space << __x.b(); | |
2689 | ||
2690 | __os.flags(__flags); | |
2691 | __os.fill(__fill); | |
2692 | __os.precision(__precision); | |
2693 | return __os; | |
2694 | } | |
2695 | ||
2696 | template<typename _RealType, typename _CharT, typename _Traits> | |
2697 | std::basic_istream<_CharT, _Traits>& | |
2698 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2699 | weibull_distribution<_RealType>& __x) | |
2700 | { | |
2701 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
2702 | typedef typename __istream_type::ios_base __ios_base; | |
2703 | ||
2704 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2705 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2706 | ||
2707 | _RealType __a, __b; | |
2708 | __is >> __a >> __b; | |
2709 | __x.param(typename weibull_distribution<_RealType>:: | |
2710 | param_type(__a, __b)); | |
2711 | ||
2712 | __is.flags(__flags); | |
2713 | return __is; | |
2714 | } | |
2715 | ||
2716 | ||
2717 | template<typename _RealType> | |
2718 | template<typename _UniformRandomNumberGenerator> | |
2719 | typename extreme_value_distribution<_RealType>::result_type | |
2720 | extreme_value_distribution<_RealType>:: | |
2721 | operator()(_UniformRandomNumberGenerator& __urng, | |
2722 | const param_type& __p) | |
2723 | { | |
2724 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
2725 | __aurng(__urng); | |
c279067a | 2726 | return __p.a() - __p.b() * std::log(-std::log(result_type(1) |
2727 | - __aurng())); | |
fca66f47 | 2728 | } |
2729 | ||
308b344d | 2730 | template<typename _RealType> |
2731 | template<typename _ForwardIterator, | |
2732 | typename _UniformRandomNumberGenerator> | |
2733 | void | |
2734 | extreme_value_distribution<_RealType>:: | |
2735 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2736 | _UniformRandomNumberGenerator& __urng, | |
2737 | const param_type& __p) | |
2738 | { | |
2739 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2740 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
2741 | __aurng(__urng); | |
2742 | ||
2743 | while (__f != __t) | |
c279067a | 2744 | *__f++ = __p.a() - __p.b() * std::log(-std::log(result_type(1) |
2745 | - __aurng())); | |
308b344d | 2746 | } |
2747 | ||
fca66f47 | 2748 | template<typename _RealType, typename _CharT, typename _Traits> |
2749 | std::basic_ostream<_CharT, _Traits>& | |
2750 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2751 | const extreme_value_distribution<_RealType>& __x) | |
2752 | { | |
2753 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
2754 | typedef typename __ostream_type::ios_base __ios_base; | |
2755 | ||
2756 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2757 | const _CharT __fill = __os.fill(); | |
2758 | const std::streamsize __precision = __os.precision(); | |
2759 | const _CharT __space = __os.widen(' '); | |
2760 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2761 | __os.fill(__space); | |
245c5a20 | 2762 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
fca66f47 | 2763 | |
2764 | __os << __x.a() << __space << __x.b(); | |
2765 | ||
2766 | __os.flags(__flags); | |
2767 | __os.fill(__fill); | |
2768 | __os.precision(__precision); | |
2769 | return __os; | |
2770 | } | |
2771 | ||
2772 | template<typename _RealType, typename _CharT, typename _Traits> | |
2773 | std::basic_istream<_CharT, _Traits>& | |
2774 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2775 | extreme_value_distribution<_RealType>& __x) | |
2776 | { | |
2777 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
2778 | typedef typename __istream_type::ios_base __ios_base; | |
2779 | ||
2780 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2781 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2782 | ||
2783 | _RealType __a, __b; | |
2784 | __is >> __a >> __b; | |
2785 | __x.param(typename extreme_value_distribution<_RealType>:: | |
2786 | param_type(__a, __b)); | |
2787 | ||
2788 | __is.flags(__flags); | |
2789 | return __is; | |
2790 | } | |
2791 | ||
2792 | ||
2793 | template<typename _IntType> | |
2794 | void | |
2795 | discrete_distribution<_IntType>::param_type:: | |
2796 | _M_initialize() | |
2797 | { | |
2798 | if (_M_prob.size() < 2) | |
2799 | { | |
2800 | _M_prob.clear(); | |
fca66f47 | 2801 | return; |
2802 | } | |
2803 | ||
985855e9 | 2804 | const double __sum = std::accumulate(_M_prob.begin(), |
2805 | _M_prob.end(), 0.0); | |
2806 | // Now normalize the probabilites. | |
8ffda4f4 | 2807 | __detail::__normalize(_M_prob.begin(), _M_prob.end(), _M_prob.begin(), |
2808 | __sum); | |
985855e9 | 2809 | // Accumulate partial sums. |
2810 | _M_cp.reserve(_M_prob.size()); | |
fca66f47 | 2811 | std::partial_sum(_M_prob.begin(), _M_prob.end(), |
2812 | std::back_inserter(_M_cp)); | |
985855e9 | 2813 | // Make sure the last cumulative probability is one. |
fca66f47 | 2814 | _M_cp[_M_cp.size() - 1] = 1.0; |
2815 | } | |
2816 | ||
2817 | template<typename _IntType> | |
2818 | template<typename _Func> | |
2819 | discrete_distribution<_IntType>::param_type:: | |
985855e9 | 2820 | param_type(size_t __nw, double __xmin, double __xmax, _Func __fw) |
fca66f47 | 2821 | : _M_prob(), _M_cp() |
2822 | { | |
985855e9 | 2823 | const size_t __n = __nw == 0 ? 1 : __nw; |
2824 | const double __delta = (__xmax - __xmin) / __n; | |
2825 | ||
2826 | _M_prob.reserve(__n); | |
2827 | for (size_t __k = 0; __k < __nw; ++__k) | |
2828 | _M_prob.push_back(__fw(__xmin + __k * __delta + 0.5 * __delta)); | |
fca66f47 | 2829 | |
2830 | _M_initialize(); | |
2831 | } | |
2832 | ||
2833 | template<typename _IntType> | |
2834 | template<typename _UniformRandomNumberGenerator> | |
2835 | typename discrete_distribution<_IntType>::result_type | |
2836 | discrete_distribution<_IntType>:: | |
2837 | operator()(_UniformRandomNumberGenerator& __urng, | |
2838 | const param_type& __param) | |
2839 | { | |
184886d6 | 2840 | if (__param._M_cp.empty()) |
2841 | return result_type(0); | |
2842 | ||
010799ab | 2843 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> |
fca66f47 | 2844 | __aurng(__urng); |
2845 | ||
2846 | const double __p = __aurng(); | |
2847 | auto __pos = std::lower_bound(__param._M_cp.begin(), | |
2848 | __param._M_cp.end(), __p); | |
fca66f47 | 2849 | |
985855e9 | 2850 | return __pos - __param._M_cp.begin(); |
fca66f47 | 2851 | } |
2852 | ||
308b344d | 2853 | template<typename _IntType> |
2854 | template<typename _ForwardIterator, | |
2855 | typename _UniformRandomNumberGenerator> | |
2856 | void | |
2857 | discrete_distribution<_IntType>:: | |
2858 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2859 | _UniformRandomNumberGenerator& __urng, | |
2860 | const param_type& __param) | |
2861 | { | |
2862 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
2863 | ||
2864 | if (__param._M_cp.empty()) | |
2865 | { | |
2866 | while (__f != __t) | |
2867 | *__f++ = result_type(0); | |
2868 | return; | |
2869 | } | |
2870 | ||
2871 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
2872 | __aurng(__urng); | |
2873 | ||
2874 | while (__f != __t) | |
2875 | { | |
2876 | const double __p = __aurng(); | |
2877 | auto __pos = std::lower_bound(__param._M_cp.begin(), | |
2878 | __param._M_cp.end(), __p); | |
2879 | ||
2880 | *__f++ = __pos - __param._M_cp.begin(); | |
2881 | } | |
2882 | } | |
2883 | ||
fca66f47 | 2884 | template<typename _IntType, typename _CharT, typename _Traits> |
2885 | std::basic_ostream<_CharT, _Traits>& | |
2886 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2887 | const discrete_distribution<_IntType>& __x) | |
2888 | { | |
2889 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
2890 | typedef typename __ostream_type::ios_base __ios_base; | |
2891 | ||
2892 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
2893 | const _CharT __fill = __os.fill(); | |
2894 | const std::streamsize __precision = __os.precision(); | |
2895 | const _CharT __space = __os.widen(' '); | |
2896 | __os.flags(__ios_base::scientific | __ios_base::left); | |
2897 | __os.fill(__space); | |
245c5a20 | 2898 | __os.precision(std::numeric_limits<double>::max_digits10); |
fca66f47 | 2899 | |
2900 | std::vector<double> __prob = __x.probabilities(); | |
2901 | __os << __prob.size(); | |
2902 | for (auto __dit = __prob.begin(); __dit != __prob.end(); ++__dit) | |
2903 | __os << __space << *__dit; | |
2904 | ||
2905 | __os.flags(__flags); | |
2906 | __os.fill(__fill); | |
2907 | __os.precision(__precision); | |
2908 | return __os; | |
2909 | } | |
2910 | ||
2911 | template<typename _IntType, typename _CharT, typename _Traits> | |
2912 | std::basic_istream<_CharT, _Traits>& | |
2913 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2914 | discrete_distribution<_IntType>& __x) | |
2915 | { | |
2916 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
2917 | typedef typename __istream_type::ios_base __ios_base; | |
2918 | ||
2919 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
2920 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
2921 | ||
2922 | size_t __n; | |
2923 | __is >> __n; | |
2924 | ||
2925 | std::vector<double> __prob_vec; | |
985855e9 | 2926 | __prob_vec.reserve(__n); |
fca66f47 | 2927 | for (; __n != 0; --__n) |
2928 | { | |
2929 | double __prob; | |
2930 | __is >> __prob; | |
2931 | __prob_vec.push_back(__prob); | |
2932 | } | |
2933 | ||
2934 | __x.param(typename discrete_distribution<_IntType>:: | |
2935 | param_type(__prob_vec.begin(), __prob_vec.end())); | |
2936 | ||
2937 | __is.flags(__flags); | |
2938 | return __is; | |
2939 | } | |
2940 | ||
2941 | ||
2942 | template<typename _RealType> | |
2943 | void | |
2944 | piecewise_constant_distribution<_RealType>::param_type:: | |
2945 | _M_initialize() | |
2946 | { | |
184886d6 | 2947 | if (_M_int.size() < 2 |
2948 | || (_M_int.size() == 2 | |
2949 | && _M_int[0] == _RealType(0) | |
2950 | && _M_int[1] == _RealType(1))) | |
fca66f47 | 2951 | { |
2952 | _M_int.clear(); | |
fca66f47 | 2953 | _M_den.clear(); |
fca66f47 | 2954 | return; |
2955 | } | |
2956 | ||
985855e9 | 2957 | const double __sum = std::accumulate(_M_den.begin(), |
2958 | _M_den.end(), 0.0); | |
fca66f47 | 2959 | |
8ffda4f4 | 2960 | __detail::__normalize(_M_den.begin(), _M_den.end(), _M_den.begin(), |
2961 | __sum); | |
985855e9 | 2962 | |
2963 | _M_cp.reserve(_M_den.size()); | |
2964 | std::partial_sum(_M_den.begin(), _M_den.end(), | |
2965 | std::back_inserter(_M_cp)); | |
2966 | ||
2967 | // Make sure the last cumulative probability is one. | |
fca66f47 | 2968 | _M_cp[_M_cp.size() - 1] = 1.0; |
985855e9 | 2969 | |
2970 | for (size_t __k = 0; __k < _M_den.size(); ++__k) | |
2971 | _M_den[__k] /= _M_int[__k + 1] - _M_int[__k]; | |
fca66f47 | 2972 | } |
2973 | ||
fca66f47 | 2974 | template<typename _RealType> |
2975 | template<typename _InputIteratorB, typename _InputIteratorW> | |
2976 | piecewise_constant_distribution<_RealType>::param_type:: | |
2977 | param_type(_InputIteratorB __bbegin, | |
2978 | _InputIteratorB __bend, | |
2979 | _InputIteratorW __wbegin) | |
2980 | : _M_int(), _M_den(), _M_cp() | |
2981 | { | |
985855e9 | 2982 | if (__bbegin != __bend) |
fca66f47 | 2983 | { |
985855e9 | 2984 | for (;;) |
fca66f47 | 2985 | { |
985855e9 | 2986 | _M_int.push_back(*__bbegin); |
2987 | ++__bbegin; | |
2988 | if (__bbegin == __bend) | |
2989 | break; | |
2990 | ||
fca66f47 | 2991 | _M_den.push_back(*__wbegin); |
2992 | ++__wbegin; | |
2993 | } | |
2994 | } | |
fca66f47 | 2995 | |
2996 | _M_initialize(); | |
2997 | } | |
2998 | ||
2999 | template<typename _RealType> | |
3000 | template<typename _Func> | |
3001 | piecewise_constant_distribution<_RealType>::param_type:: | |
985855e9 | 3002 | param_type(initializer_list<_RealType> __bl, _Func __fw) |
fca66f47 | 3003 | : _M_int(), _M_den(), _M_cp() |
3004 | { | |
985855e9 | 3005 | _M_int.reserve(__bl.size()); |
3006 | for (auto __biter = __bl.begin(); __biter != __bl.end(); ++__biter) | |
fca66f47 | 3007 | _M_int.push_back(*__biter); |
3008 | ||
985855e9 | 3009 | _M_den.reserve(_M_int.size() - 1); |
3010 | for (size_t __k = 0; __k < _M_int.size() - 1; ++__k) | |
3011 | _M_den.push_back(__fw(0.5 * (_M_int[__k + 1] + _M_int[__k]))); | |
fca66f47 | 3012 | |
3013 | _M_initialize(); | |
3014 | } | |
3015 | ||
3016 | template<typename _RealType> | |
3017 | template<typename _Func> | |
3018 | piecewise_constant_distribution<_RealType>::param_type:: | |
d37c6500 | 3019 | param_type(size_t __nw, _RealType __xmin, _RealType __xmax, _Func __fw) |
fca66f47 | 3020 | : _M_int(), _M_den(), _M_cp() |
3021 | { | |
985855e9 | 3022 | const size_t __n = __nw == 0 ? 1 : __nw; |
3023 | const _RealType __delta = (__xmax - __xmin) / __n; | |
3024 | ||
3025 | _M_int.reserve(__n + 1); | |
3026 | for (size_t __k = 0; __k <= __nw; ++__k) | |
3027 | _M_int.push_back(__xmin + __k * __delta); | |
3028 | ||
3029 | _M_den.reserve(__n); | |
3030 | for (size_t __k = 0; __k < __nw; ++__k) | |
3031 | _M_den.push_back(__fw(_M_int[__k] + 0.5 * __delta)); | |
fca66f47 | 3032 | |
3033 | _M_initialize(); | |
3034 | } | |
3035 | ||
3036 | template<typename _RealType> | |
3037 | template<typename _UniformRandomNumberGenerator> | |
3038 | typename piecewise_constant_distribution<_RealType>::result_type | |
3039 | piecewise_constant_distribution<_RealType>:: | |
3040 | operator()(_UniformRandomNumberGenerator& __urng, | |
3041 | const param_type& __param) | |
3042 | { | |
010799ab | 3043 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> |
fca66f47 | 3044 | __aurng(__urng); |
3045 | ||
3046 | const double __p = __aurng(); | |
184886d6 | 3047 | if (__param._M_cp.empty()) |
3048 | return __p; | |
3049 | ||
fca66f47 | 3050 | auto __pos = std::lower_bound(__param._M_cp.begin(), |
3051 | __param._M_cp.end(), __p); | |
3052 | const size_t __i = __pos - __param._M_cp.begin(); | |
3053 | ||
985855e9 | 3054 | const double __pref = __i > 0 ? __param._M_cp[__i - 1] : 0.0; |
3055 | ||
3056 | return __param._M_int[__i] + (__p - __pref) / __param._M_den[__i]; | |
fca66f47 | 3057 | } |
3058 | ||
308b344d | 3059 | template<typename _RealType> |
3060 | template<typename _ForwardIterator, | |
3061 | typename _UniformRandomNumberGenerator> | |
3062 | void | |
3063 | piecewise_constant_distribution<_RealType>:: | |
3064 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
3065 | _UniformRandomNumberGenerator& __urng, | |
3066 | const param_type& __param) | |
3067 | { | |
3068 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
3069 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
3070 | __aurng(__urng); | |
3071 | ||
3072 | if (__param._M_cp.empty()) | |
3073 | { | |
3074 | while (__f != __t) | |
3075 | *__f++ = __aurng(); | |
3076 | return; | |
3077 | } | |
3078 | ||
3079 | while (__f != __t) | |
3080 | { | |
3081 | const double __p = __aurng(); | |
3082 | ||
3083 | auto __pos = std::lower_bound(__param._M_cp.begin(), | |
3084 | __param._M_cp.end(), __p); | |
3085 | const size_t __i = __pos - __param._M_cp.begin(); | |
3086 | ||
3087 | const double __pref = __i > 0 ? __param._M_cp[__i - 1] : 0.0; | |
3088 | ||
3089 | *__f++ = (__param._M_int[__i] | |
3090 | + (__p - __pref) / __param._M_den[__i]); | |
3091 | } | |
3092 | } | |
3093 | ||
fca66f47 | 3094 | template<typename _RealType, typename _CharT, typename _Traits> |
3095 | std::basic_ostream<_CharT, _Traits>& | |
3096 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
3097 | const piecewise_constant_distribution<_RealType>& __x) | |
3098 | { | |
3099 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
3100 | typedef typename __ostream_type::ios_base __ios_base; | |
3101 | ||
3102 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
3103 | const _CharT __fill = __os.fill(); | |
3104 | const std::streamsize __precision = __os.precision(); | |
3105 | const _CharT __space = __os.widen(' '); | |
3106 | __os.flags(__ios_base::scientific | __ios_base::left); | |
3107 | __os.fill(__space); | |
245c5a20 | 3108 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
fca66f47 | 3109 | |
3110 | std::vector<_RealType> __int = __x.intervals(); | |
3111 | __os << __int.size() - 1; | |
3112 | ||
3113 | for (auto __xit = __int.begin(); __xit != __int.end(); ++__xit) | |
3114 | __os << __space << *__xit; | |
3115 | ||
3116 | std::vector<double> __den = __x.densities(); | |
3117 | for (auto __dit = __den.begin(); __dit != __den.end(); ++__dit) | |
3118 | __os << __space << *__dit; | |
3119 | ||
3120 | __os.flags(__flags); | |
3121 | __os.fill(__fill); | |
3122 | __os.precision(__precision); | |
3123 | return __os; | |
3124 | } | |
3125 | ||
3126 | template<typename _RealType, typename _CharT, typename _Traits> | |
3127 | std::basic_istream<_CharT, _Traits>& | |
3128 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
3129 | piecewise_constant_distribution<_RealType>& __x) | |
3130 | { | |
3131 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
3132 | typedef typename __istream_type::ios_base __ios_base; | |
3133 | ||
3134 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
3135 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
3136 | ||
3137 | size_t __n; | |
3138 | __is >> __n; | |
3139 | ||
3140 | std::vector<_RealType> __int_vec; | |
985855e9 | 3141 | __int_vec.reserve(__n + 1); |
fca66f47 | 3142 | for (size_t __i = 0; __i <= __n; ++__i) |
3143 | { | |
3144 | _RealType __int; | |
3145 | __is >> __int; | |
3146 | __int_vec.push_back(__int); | |
3147 | } | |
3148 | ||
3149 | std::vector<double> __den_vec; | |
985855e9 | 3150 | __den_vec.reserve(__n); |
fca66f47 | 3151 | for (size_t __i = 0; __i < __n; ++__i) |
3152 | { | |
3153 | double __den; | |
3154 | __is >> __den; | |
3155 | __den_vec.push_back(__den); | |
3156 | } | |
3157 | ||
3158 | __x.param(typename piecewise_constant_distribution<_RealType>:: | |
3159 | param_type(__int_vec.begin(), __int_vec.end(), __den_vec.begin())); | |
3160 | ||
3161 | __is.flags(__flags); | |
3162 | return __is; | |
3163 | } | |
3164 | ||
3165 | ||
3166 | template<typename _RealType> | |
3167 | void | |
3168 | piecewise_linear_distribution<_RealType>::param_type:: | |
3169 | _M_initialize() | |
3170 | { | |
184886d6 | 3171 | if (_M_int.size() < 2 |
3172 | || (_M_int.size() == 2 | |
3173 | && _M_int[0] == _RealType(0) | |
3174 | && _M_int[1] == _RealType(1) | |
3175 | && _M_den[0] == _M_den[1])) | |
fca66f47 | 3176 | { |
3177 | _M_int.clear(); | |
fca66f47 | 3178 | _M_den.clear(); |
fca66f47 | 3179 | return; |
3180 | } | |
3181 | ||
3182 | double __sum = 0.0; | |
985855e9 | 3183 | _M_cp.reserve(_M_int.size() - 1); |
3184 | _M_m.reserve(_M_int.size() - 1); | |
3185 | for (size_t __k = 0; __k < _M_int.size() - 1; ++__k) | |
fca66f47 | 3186 | { |
985855e9 | 3187 | const _RealType __delta = _M_int[__k + 1] - _M_int[__k]; |
3188 | __sum += 0.5 * (_M_den[__k + 1] + _M_den[__k]) * __delta; | |
fca66f47 | 3189 | _M_cp.push_back(__sum); |
985855e9 | 3190 | _M_m.push_back((_M_den[__k + 1] - _M_den[__k]) / __delta); |
fca66f47 | 3191 | } |
3192 | ||
3193 | // Now normalize the densities... | |
8ffda4f4 | 3194 | __detail::__normalize(_M_den.begin(), _M_den.end(), _M_den.begin(), |
3195 | __sum); | |
fca66f47 | 3196 | // ... and partial sums... |
8ffda4f4 | 3197 | __detail::__normalize(_M_cp.begin(), _M_cp.end(), _M_cp.begin(), __sum); |
fca66f47 | 3198 | // ... and slopes. |
8ffda4f4 | 3199 | __detail::__normalize(_M_m.begin(), _M_m.end(), _M_m.begin(), __sum); |
3200 | ||
fca66f47 | 3201 | // Make sure the last cumulative probablility is one. |
3202 | _M_cp[_M_cp.size() - 1] = 1.0; | |
985855e9 | 3203 | } |
fca66f47 | 3204 | |
3205 | template<typename _RealType> | |
3206 | template<typename _InputIteratorB, typename _InputIteratorW> | |
3207 | piecewise_linear_distribution<_RealType>::param_type:: | |
3208 | param_type(_InputIteratorB __bbegin, | |
3209 | _InputIteratorB __bend, | |
3210 | _InputIteratorW __wbegin) | |
3211 | : _M_int(), _M_den(), _M_cp(), _M_m() | |
3212 | { | |
3213 | for (; __bbegin != __bend; ++__bbegin, ++__wbegin) | |
3214 | { | |
3215 | _M_int.push_back(*__bbegin); | |
3216 | _M_den.push_back(*__wbegin); | |
3217 | } | |
3218 | ||
3219 | _M_initialize(); | |
3220 | } | |
3221 | ||
3222 | template<typename _RealType> | |
3223 | template<typename _Func> | |
3224 | piecewise_linear_distribution<_RealType>::param_type:: | |
985855e9 | 3225 | param_type(initializer_list<_RealType> __bl, _Func __fw) |
fca66f47 | 3226 | : _M_int(), _M_den(), _M_cp(), _M_m() |
3227 | { | |
985855e9 | 3228 | _M_int.reserve(__bl.size()); |
3229 | _M_den.reserve(__bl.size()); | |
3230 | for (auto __biter = __bl.begin(); __biter != __bl.end(); ++__biter) | |
fca66f47 | 3231 | { |
3232 | _M_int.push_back(*__biter); | |
3233 | _M_den.push_back(__fw(*__biter)); | |
3234 | } | |
3235 | ||
3236 | _M_initialize(); | |
3237 | } | |
3238 | ||
3239 | template<typename _RealType> | |
3240 | template<typename _Func> | |
3241 | piecewise_linear_distribution<_RealType>::param_type:: | |
985855e9 | 3242 | param_type(size_t __nw, _RealType __xmin, _RealType __xmax, _Func __fw) |
fca66f47 | 3243 | : _M_int(), _M_den(), _M_cp(), _M_m() |
3244 | { | |
985855e9 | 3245 | const size_t __n = __nw == 0 ? 1 : __nw; |
3246 | const _RealType __delta = (__xmax - __xmin) / __n; | |
3247 | ||
3248 | _M_int.reserve(__n + 1); | |
3249 | _M_den.reserve(__n + 1); | |
3250 | for (size_t __k = 0; __k <= __nw; ++__k) | |
fca66f47 | 3251 | { |
985855e9 | 3252 | _M_int.push_back(__xmin + __k * __delta); |
3253 | _M_den.push_back(__fw(_M_int[__k] + __delta)); | |
fca66f47 | 3254 | } |
3255 | ||
3256 | _M_initialize(); | |
3257 | } | |
3258 | ||
3259 | template<typename _RealType> | |
3260 | template<typename _UniformRandomNumberGenerator> | |
3261 | typename piecewise_linear_distribution<_RealType>::result_type | |
3262 | piecewise_linear_distribution<_RealType>:: | |
3263 | operator()(_UniformRandomNumberGenerator& __urng, | |
3264 | const param_type& __param) | |
3265 | { | |
010799ab | 3266 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> |
fca66f47 | 3267 | __aurng(__urng); |
3268 | ||
3269 | const double __p = __aurng(); | |
184886d6 | 3270 | if (__param._M_cp.empty()) |
b89d5905 | 3271 | return __p; |
3272 | ||
fca66f47 | 3273 | auto __pos = std::lower_bound(__param._M_cp.begin(), |
3274 | __param._M_cp.end(), __p); | |
3275 | const size_t __i = __pos - __param._M_cp.begin(); | |
985855e9 | 3276 | |
3277 | const double __pref = __i > 0 ? __param._M_cp[__i - 1] : 0.0; | |
3278 | ||
fca66f47 | 3279 | const double __a = 0.5 * __param._M_m[__i]; |
3280 | const double __b = __param._M_den[__i]; | |
985855e9 | 3281 | const double __cm = __p - __pref; |
3282 | ||
3283 | _RealType __x = __param._M_int[__i]; | |
3284 | if (__a == 0) | |
3285 | __x += __cm / __b; | |
3286 | else | |
3287 | { | |
3288 | const double __d = __b * __b + 4.0 * __a * __cm; | |
3289 | __x += 0.5 * (std::sqrt(__d) - __b) / __a; | |
3290 | } | |
fca66f47 | 3291 | |
985855e9 | 3292 | return __x; |
fca66f47 | 3293 | } |
3294 | ||
308b344d | 3295 | template<typename _RealType> |
3296 | template<typename _ForwardIterator, | |
3297 | typename _UniformRandomNumberGenerator> | |
3298 | void | |
3299 | piecewise_linear_distribution<_RealType>:: | |
3300 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
3301 | _UniformRandomNumberGenerator& __urng, | |
3302 | const param_type& __param) | |
3303 | { | |
3304 | __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>) | |
3305 | // We could duplicate everything from operator()... | |
3306 | while (__f != __t) | |
3307 | *__f++ = this->operator()(__urng, __param); | |
3308 | } | |
3309 | ||
fca66f47 | 3310 | template<typename _RealType, typename _CharT, typename _Traits> |
3311 | std::basic_ostream<_CharT, _Traits>& | |
3312 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
3313 | const piecewise_linear_distribution<_RealType>& __x) | |
3314 | { | |
3315 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; | |
3316 | typedef typename __ostream_type::ios_base __ios_base; | |
3317 | ||
3318 | const typename __ios_base::fmtflags __flags = __os.flags(); | |
3319 | const _CharT __fill = __os.fill(); | |
3320 | const std::streamsize __precision = __os.precision(); | |
3321 | const _CharT __space = __os.widen(' '); | |
3322 | __os.flags(__ios_base::scientific | __ios_base::left); | |
3323 | __os.fill(__space); | |
245c5a20 | 3324 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
fca66f47 | 3325 | |
3326 | std::vector<_RealType> __int = __x.intervals(); | |
3327 | __os << __int.size() - 1; | |
3328 | ||
3329 | for (auto __xit = __int.begin(); __xit != __int.end(); ++__xit) | |
3330 | __os << __space << *__xit; | |
3331 | ||
3332 | std::vector<double> __den = __x.densities(); | |
3333 | for (auto __dit = __den.begin(); __dit != __den.end(); ++__dit) | |
3334 | __os << __space << *__dit; | |
3335 | ||
3336 | __os.flags(__flags); | |
3337 | __os.fill(__fill); | |
3338 | __os.precision(__precision); | |
3339 | return __os; | |
3340 | } | |
3341 | ||
3342 | template<typename _RealType, typename _CharT, typename _Traits> | |
3343 | std::basic_istream<_CharT, _Traits>& | |
3344 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
3345 | piecewise_linear_distribution<_RealType>& __x) | |
3346 | { | |
3347 | typedef std::basic_istream<_CharT, _Traits> __istream_type; | |
3348 | typedef typename __istream_type::ios_base __ios_base; | |
3349 | ||
3350 | const typename __ios_base::fmtflags __flags = __is.flags(); | |
3351 | __is.flags(__ios_base::dec | __ios_base::skipws); | |
3352 | ||
3353 | size_t __n; | |
3354 | __is >> __n; | |
3355 | ||
3356 | std::vector<_RealType> __int_vec; | |
985855e9 | 3357 | __int_vec.reserve(__n + 1); |
fca66f47 | 3358 | for (size_t __i = 0; __i <= __n; ++__i) |
3359 | { | |
3360 | _RealType __int; | |
3361 | __is >> __int; | |
3362 | __int_vec.push_back(__int); | |
3363 | } | |
3364 | ||
3365 | std::vector<double> __den_vec; | |
985855e9 | 3366 | __den_vec.reserve(__n + 1); |
fca66f47 | 3367 | for (size_t __i = 0; __i <= __n; ++__i) |
3368 | { | |
3369 | double __den; | |
3370 | __is >> __den; | |
3371 | __den_vec.push_back(__den); | |
3372 | } | |
3373 | ||
3374 | __x.param(typename piecewise_linear_distribution<_RealType>:: | |
3375 | param_type(__int_vec.begin(), __int_vec.end(), __den_vec.begin())); | |
3376 | ||
3377 | __is.flags(__flags); | |
3378 | return __is; | |
3379 | } | |
3380 | ||
3381 | ||
3382 | template<typename _IntType> | |
3383 | seed_seq::seed_seq(std::initializer_list<_IntType> __il) | |
3384 | { | |
3385 | for (auto __iter = __il.begin(); __iter != __il.end(); ++__iter) | |
ccb188ea | 3386 | _M_v.push_back(__detail::__mod<result_type, |
fca66f47 | 3387 | __detail::_Shift<result_type, 32>::__value>(*__iter)); |
3388 | } | |
3389 | ||
3390 | template<typename _InputIterator> | |
3391 | seed_seq::seed_seq(_InputIterator __begin, _InputIterator __end) | |
3392 | { | |
3393 | for (_InputIterator __iter = __begin; __iter != __end; ++__iter) | |
ccb188ea | 3394 | _M_v.push_back(__detail::__mod<result_type, |
fca66f47 | 3395 | __detail::_Shift<result_type, 32>::__value>(*__iter)); |
3396 | } | |
3397 | ||
3398 | template<typename _RandomAccessIterator> | |
3399 | void | |
3400 | seed_seq::generate(_RandomAccessIterator __begin, | |
3401 | _RandomAccessIterator __end) | |
3402 | { | |
3403 | typedef typename iterator_traits<_RandomAccessIterator>::value_type | |
f3922893 | 3404 | _Type; |
fca66f47 | 3405 | |
3406 | if (__begin == __end) | |
3407 | return; | |
3408 | ||
ccb188ea | 3409 | std::fill(__begin, __end, _Type(0x8b8b8b8bu)); |
fca66f47 | 3410 | |
3411 | const size_t __n = __end - __begin; | |
3412 | const size_t __s = _M_v.size(); | |
3413 | const size_t __t = (__n >= 623) ? 11 | |
3414 | : (__n >= 68) ? 7 | |
3415 | : (__n >= 39) ? 5 | |
3416 | : (__n >= 7) ? 3 | |
3417 | : (__n - 1) / 2; | |
3418 | const size_t __p = (__n - __t) / 2; | |
3419 | const size_t __q = __p + __t; | |
91d963c4 | 3420 | const size_t __m = std::max(size_t(__s + 1), __n); |
fca66f47 | 3421 | |
3422 | for (size_t __k = 0; __k < __m; ++__k) | |
3423 | { | |
f3922893 | 3424 | _Type __arg = (__begin[__k % __n] |
3425 | ^ __begin[(__k + __p) % __n] | |
3426 | ^ __begin[(__k - 1) % __n]); | |
e279f95b | 3427 | _Type __r1 = __arg ^ (__arg >> 27); |
d39cfbd4 | 3428 | __r1 = __detail::__mod<_Type, |
3429 | __detail::_Shift<_Type, 32>::__value>(1664525u * __r1); | |
f3922893 | 3430 | _Type __r2 = __r1; |
fca66f47 | 3431 | if (__k == 0) |
3432 | __r2 += __s; | |
3433 | else if (__k <= __s) | |
3434 | __r2 += __k % __n + _M_v[__k - 1]; | |
3435 | else | |
3436 | __r2 += __k % __n; | |
ccb188ea | 3437 | __r2 = __detail::__mod<_Type, |
3438 | __detail::_Shift<_Type, 32>::__value>(__r2); | |
fca66f47 | 3439 | __begin[(__k + __p) % __n] += __r1; |
3440 | __begin[(__k + __q) % __n] += __r2; | |
3441 | __begin[__k % __n] = __r2; | |
3442 | } | |
3443 | ||
3444 | for (size_t __k = __m; __k < __m + __n; ++__k) | |
3445 | { | |
f3922893 | 3446 | _Type __arg = (__begin[__k % __n] |
3447 | + __begin[(__k + __p) % __n] | |
3448 | + __begin[(__k - 1) % __n]); | |
e279f95b | 3449 | _Type __r3 = __arg ^ (__arg >> 27); |
d39cfbd4 | 3450 | __r3 = __detail::__mod<_Type, |
3451 | __detail::_Shift<_Type, 32>::__value>(1566083941u * __r3); | |
f3922893 | 3452 | _Type __r4 = __r3 - __k % __n; |
ccb188ea | 3453 | __r4 = __detail::__mod<_Type, |
3454 | __detail::_Shift<_Type, 32>::__value>(__r4); | |
09223d2c | 3455 | __begin[(__k + __p) % __n] ^= __r3; |
3456 | __begin[(__k + __q) % __n] ^= __r4; | |
fca66f47 | 3457 | __begin[__k % __n] = __r4; |
3458 | } | |
3459 | } | |
3460 | ||
3461 | template<typename _RealType, size_t __bits, | |
3462 | typename _UniformRandomNumberGenerator> | |
3463 | _RealType | |
3464 | generate_canonical(_UniformRandomNumberGenerator& __urng) | |
3465 | { | |
85448703 | 3466 | static_assert(std::is_floating_point<_RealType>::value, |
3467 | "template argument not a floating point type"); | |
3468 | ||
fca66f47 | 3469 | const size_t __b |
3470 | = std::min(static_cast<size_t>(std::numeric_limits<_RealType>::digits), | |
3471 | __bits); | |
3472 | const long double __r = static_cast<long double>(__urng.max()) | |
3473 | - static_cast<long double>(__urng.min()) + 1.0L; | |
d37c6500 | 3474 | const size_t __log2r = std::log(__r) / std::log(2.0L); |
42c1c978 | 3475 | const size_t __m = std::max<size_t>(1UL, |
3476 | (__b + __log2r - 1UL) / __log2r); | |
3477 | _RealType __ret; | |
3478 | do | |
fca66f47 | 3479 | { |
42c1c978 | 3480 | _RealType __sum = _RealType(0); |
3481 | _RealType __tmp = _RealType(1); | |
3482 | for (size_t __k = __m; __k != 0; --__k) | |
3483 | { | |
3484 | __sum += _RealType(__urng() - __urng.min()) * __tmp; | |
3485 | __tmp *= __r; | |
3486 | } | |
3487 | __ret = __sum / __tmp; | |
fca66f47 | 3488 | } |
42c1c978 | 3489 | while (__builtin_expect(__ret >= _RealType(1), 0)); |
3490 | return __ret; | |
fca66f47 | 3491 | } |
2948dd21 | 3492 | |
3493 | _GLIBCXX_END_NAMESPACE_VERSION | |
3494 | } // namespace | |
22688974 | 3495 | |
3496 | #endif |