1 | // Random number extensions -*- C++ -*- |
2 | |
3 | // Copyright (C) 2012-2018 Free Software Foundation, Inc. |
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 |
8 | // Free Software Foundation; either version 3, or (at your option) |
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 | |
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. |
19 | |
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/>. |
24 | |
25 | /** @file ext/random.tcc |
26 | * This is an internal header file, included by other library headers. |
27 | * Do not attempt to use it directly. @headername{ext/random} |
28 | */ |
29 | |
30 | #ifndef _EXT_RANDOM_TCC |
31 | #define _EXT_RANDOM_TCC 1 |
32 | |
33 | #pragma GCC system_header |
34 | |
35 | namespace __gnu_cxx _GLIBCXX_VISIBILITY(default) |
36 | { |
37 | _GLIBCXX_BEGIN_NAMESPACE_VERSION |
38 | |
39 | #if __BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__ |
40 | |
41 | template<typename _UIntType, size_t __m, |
42 | size_t __pos1, size_t __sl1, size_t __sl2, |
43 | size_t __sr1, size_t __sr2, |
44 | uint32_t __msk1, uint32_t __msk2, |
45 | uint32_t __msk3, uint32_t __msk4, |
46 | uint32_t __parity1, uint32_t __parity2, |
47 | uint32_t __parity3, uint32_t __parity4> |
48 | void simd_fast_mersenne_twister_engine<_UIntType, __m, |
49 | __pos1, __sl1, __sl2, __sr1, __sr2, |
50 | __msk1, __msk2, __msk3, __msk4, |
51 | __parity1, __parity2, __parity3, |
52 | __parity4>:: |
53 | seed(_UIntType __seed) |
54 | { |
55 | _M_state32[0] = static_cast<uint32_t>(__seed); |
56 | for (size_t __i = 1; __i < _M_nstate32; ++__i) |
57 | _M_state32[__i] = (1812433253UL |
58 | * (_M_state32[__i - 1] ^ (_M_state32[__i - 1] >> 30)) |
59 | + __i); |
60 | _M_pos = state_size; |
61 | _M_period_certification(); |
62 | } |
63 | |
64 | |
65 | namespace { |
66 | |
67 | inline uint32_t _Func1(uint32_t __x) |
68 | { |
69 | return (__x ^ (__x >> 27)) * UINT32_C(1664525); |
70 | } |
71 | |
72 | inline uint32_t _Func2(uint32_t __x) |
73 | { |
74 | return (__x ^ (__x >> 27)) * UINT32_C(1566083941); |
75 | } |
76 | |
77 | } |
78 | |
79 | |
80 | template<typename _UIntType, size_t __m, |
81 | size_t __pos1, size_t __sl1, size_t __sl2, |
82 | size_t __sr1, size_t __sr2, |
83 | uint32_t __msk1, uint32_t __msk2, |
84 | uint32_t __msk3, uint32_t __msk4, |
85 | uint32_t __parity1, uint32_t __parity2, |
86 | uint32_t __parity3, uint32_t __parity4> |
87 | template<typename _Sseq> |
88 | typename std::enable_if<std::is_class<_Sseq>::value>::type |
89 | simd_fast_mersenne_twister_engine<_UIntType, __m, |
90 | __pos1, __sl1, __sl2, __sr1, __sr2, |
91 | __msk1, __msk2, __msk3, __msk4, |
92 | __parity1, __parity2, __parity3, |
93 | __parity4>:: |
94 | seed(_Sseq& __q) |
95 | { |
96 | size_t __lag; |
97 | |
98 | if (_M_nstate32 >= 623) |
99 | __lag = 11; |
100 | else if (_M_nstate32 >= 68) |
101 | __lag = 7; |
102 | else if (_M_nstate32 >= 39) |
103 | __lag = 5; |
104 | else |
105 | __lag = 3; |
106 | const size_t __mid = (_M_nstate32 - __lag) / 2; |
107 | |
108 | std::fill(_M_state32, _M_state32 + _M_nstate32, UINT32_C(0x8b8b8b8b)); |
109 | uint32_t __arr[_M_nstate32]; |
110 | __q.generate(__arr + 0, __arr + _M_nstate32); |
111 | |
112 | uint32_t __r = _Func1(_M_state32[0] ^ _M_state32[__mid] |
113 | ^ _M_state32[_M_nstate32 - 1]); |
114 | _M_state32[__mid] += __r; |
115 | __r += _M_nstate32; |
116 | _M_state32[__mid + __lag] += __r; |
117 | _M_state32[0] = __r; |
118 | |
119 | for (size_t __i = 1, __j = 0; __j < _M_nstate32; ++__j) |
120 | { |
121 | __r = _Func1(_M_state32[__i] |
122 | ^ _M_state32[(__i + __mid) % _M_nstate32] |
123 | ^ _M_state32[(__i + _M_nstate32 - 1) % _M_nstate32]); |
124 | _M_state32[(__i + __mid) % _M_nstate32] += __r; |
125 | __r += __arr[__j] + __i; |
126 | _M_state32[(__i + __mid + __lag) % _M_nstate32] += __r; |
127 | _M_state32[__i] = __r; |
128 | __i = (__i + 1) % _M_nstate32; |
129 | } |
130 | for (size_t __j = 0; __j < _M_nstate32; ++__j) |
131 | { |
132 | const size_t __i = (__j + 1) % _M_nstate32; |
133 | __r = _Func2(_M_state32[__i] |
134 | + _M_state32[(__i + __mid) % _M_nstate32] |
135 | + _M_state32[(__i + _M_nstate32 - 1) % _M_nstate32]); |
136 | _M_state32[(__i + __mid) % _M_nstate32] ^= __r; |
137 | __r -= __i; |
138 | _M_state32[(__i + __mid + __lag) % _M_nstate32] ^= __r; |
139 | _M_state32[__i] = __r; |
140 | } |
141 | |
142 | _M_pos = state_size; |
143 | _M_period_certification(); |
144 | } |
145 | |
146 | |
147 | template<typename _UIntType, size_t __m, |
148 | size_t __pos1, size_t __sl1, size_t __sl2, |
149 | size_t __sr1, size_t __sr2, |
150 | uint32_t __msk1, uint32_t __msk2, |
151 | uint32_t __msk3, uint32_t __msk4, |
152 | uint32_t __parity1, uint32_t __parity2, |
153 | uint32_t __parity3, uint32_t __parity4> |
154 | void simd_fast_mersenne_twister_engine<_UIntType, __m, |
155 | __pos1, __sl1, __sl2, __sr1, __sr2, |
156 | __msk1, __msk2, __msk3, __msk4, |
157 | __parity1, __parity2, __parity3, |
158 | __parity4>:: |
159 | _M_period_certification(void) |
160 | { |
161 | static const uint32_t __parity[4] = { __parity1, __parity2, |
162 | __parity3, __parity4 }; |
163 | uint32_t __inner = 0; |
164 | for (size_t __i = 0; __i < 4; ++__i) |
165 | if (__parity[__i] != 0) |
166 | __inner ^= _M_state32[__i] & __parity[__i]; |
167 | |
168 | if (__builtin_parity(__inner) & 1) |
169 | return; |
170 | for (size_t __i = 0; __i < 4; ++__i) |
171 | if (__parity[__i] != 0) |
172 | { |
173 | _M_state32[__i] ^= 1 << (__builtin_ffs(__parity[__i]) - 1); |
174 | return; |
175 | } |
176 | __builtin_unreachable(); |
177 | } |
178 | |
179 | |
180 | template<typename _UIntType, size_t __m, |
181 | size_t __pos1, size_t __sl1, size_t __sl2, |
182 | size_t __sr1, size_t __sr2, |
183 | uint32_t __msk1, uint32_t __msk2, |
184 | uint32_t __msk3, uint32_t __msk4, |
185 | uint32_t __parity1, uint32_t __parity2, |
186 | uint32_t __parity3, uint32_t __parity4> |
187 | void simd_fast_mersenne_twister_engine<_UIntType, __m, |
188 | __pos1, __sl1, __sl2, __sr1, __sr2, |
189 | __msk1, __msk2, __msk3, __msk4, |
190 | __parity1, __parity2, __parity3, |
191 | __parity4>:: |
192 | discard(unsigned long long __z) |
193 | { |
194 | while (__z > state_size - _M_pos) |
195 | { |
196 | __z -= state_size - _M_pos; |
197 | |
198 | _M_gen_rand(); |
199 | } |
200 | |
201 | _M_pos += __z; |
202 | } |
203 | |
204 | |
205 | #ifndef _GLIBCXX_OPT_HAVE_RANDOM_SFMT_GEN_READ |
206 | |
207 | namespace { |
208 | |
209 | template<size_t __shift> |
210 | inline void __rshift(uint32_t *__out, const uint32_t *__in) |
211 | { |
212 | uint64_t __th = ((static_cast<uint64_t>(__in[3]) << 32) |
213 | | static_cast<uint64_t>(__in[2])); |
214 | uint64_t __tl = ((static_cast<uint64_t>(__in[1]) << 32) |
215 | | static_cast<uint64_t>(__in[0])); |
216 | |
217 | uint64_t __oh = __th >> (__shift * 8); |
218 | uint64_t __ol = __tl >> (__shift * 8); |
219 | __ol |= __th << (64 - __shift * 8); |
220 | __out[1] = static_cast<uint32_t>(__ol >> 32); |
221 | __out[0] = static_cast<uint32_t>(__ol); |
222 | __out[3] = static_cast<uint32_t>(__oh >> 32); |
223 | __out[2] = static_cast<uint32_t>(__oh); |
224 | } |
225 | |
226 | |
227 | template<size_t __shift> |
228 | inline void __lshift(uint32_t *__out, const uint32_t *__in) |
229 | { |
230 | uint64_t __th = ((static_cast<uint64_t>(__in[3]) << 32) |
231 | | static_cast<uint64_t>(__in[2])); |
232 | uint64_t __tl = ((static_cast<uint64_t>(__in[1]) << 32) |
233 | | static_cast<uint64_t>(__in[0])); |
234 | |
235 | uint64_t __oh = __th << (__shift * 8); |
236 | uint64_t __ol = __tl << (__shift * 8); |
237 | __oh |= __tl >> (64 - __shift * 8); |
238 | __out[1] = static_cast<uint32_t>(__ol >> 32); |
239 | __out[0] = static_cast<uint32_t>(__ol); |
240 | __out[3] = static_cast<uint32_t>(__oh >> 32); |
241 | __out[2] = static_cast<uint32_t>(__oh); |
242 | } |
243 | |
244 | |
245 | template<size_t __sl1, size_t __sl2, size_t __sr1, size_t __sr2, |
246 | uint32_t __msk1, uint32_t __msk2, uint32_t __msk3, uint32_t __msk4> |
247 | inline void __recursion(uint32_t *__r, |
248 | const uint32_t *__a, const uint32_t *__b, |
249 | const uint32_t *__c, const uint32_t *__d) |
250 | { |
251 | uint32_t __x[4]; |
252 | uint32_t __y[4]; |
253 | |
254 | __lshift<__sl2>(__x, __a); |
255 | __rshift<__sr2>(__y, __c); |
256 | __r[0] = (__a[0] ^ __x[0] ^ ((__b[0] >> __sr1) & __msk1) |
257 | ^ __y[0] ^ (__d[0] << __sl1)); |
258 | __r[1] = (__a[1] ^ __x[1] ^ ((__b[1] >> __sr1) & __msk2) |
259 | ^ __y[1] ^ (__d[1] << __sl1)); |
260 | __r[2] = (__a[2] ^ __x[2] ^ ((__b[2] >> __sr1) & __msk3) |
261 | ^ __y[2] ^ (__d[2] << __sl1)); |
262 | __r[3] = (__a[3] ^ __x[3] ^ ((__b[3] >> __sr1) & __msk4) |
263 | ^ __y[3] ^ (__d[3] << __sl1)); |
264 | } |
265 | |
266 | } |
267 | |
268 | |
269 | template<typename _UIntType, size_t __m, |
270 | size_t __pos1, size_t __sl1, size_t __sl2, |
271 | size_t __sr1, size_t __sr2, |
272 | uint32_t __msk1, uint32_t __msk2, |
273 | uint32_t __msk3, uint32_t __msk4, |
274 | uint32_t __parity1, uint32_t __parity2, |
275 | uint32_t __parity3, uint32_t __parity4> |
276 | void simd_fast_mersenne_twister_engine<_UIntType, __m, |
277 | __pos1, __sl1, __sl2, __sr1, __sr2, |
278 | __msk1, __msk2, __msk3, __msk4, |
279 | __parity1, __parity2, __parity3, |
280 | __parity4>:: |
281 | _M_gen_rand(void) |
282 | { |
283 | const uint32_t *__r1 = &_M_state32[_M_nstate32 - 8]; |
284 | const uint32_t *__r2 = &_M_state32[_M_nstate32 - 4]; |
285 | static constexpr size_t __pos1_32 = __pos1 * 4; |
286 | |
287 | size_t __i; |
288 | for (__i = 0; __i < _M_nstate32 - __pos1_32; __i += 4) |
289 | { |
290 | __recursion<__sl1, __sl2, __sr1, __sr2, |
291 | __msk1, __msk2, __msk3, __msk4> |
292 | (&_M_state32[__i], &_M_state32[__i], |
293 | &_M_state32[__i + __pos1_32], __r1, __r2); |
294 | __r1 = __r2; |
295 | __r2 = &_M_state32[__i]; |
296 | } |
297 | |
298 | for (; __i < _M_nstate32; __i += 4) |
299 | { |
300 | __recursion<__sl1, __sl2, __sr1, __sr2, |
301 | __msk1, __msk2, __msk3, __msk4> |
302 | (&_M_state32[__i], &_M_state32[__i], |
303 | &_M_state32[__i + __pos1_32 - _M_nstate32], __r1, __r2); |
304 | __r1 = __r2; |
305 | __r2 = &_M_state32[__i]; |
306 | } |
307 | |
308 | _M_pos = 0; |
309 | } |
310 | |
311 | #endif |
312 | |
313 | #ifndef _GLIBCXX_OPT_HAVE_RANDOM_SFMT_OPERATOREQUAL |
314 | template<typename _UIntType, size_t __m, |
315 | size_t __pos1, size_t __sl1, size_t __sl2, |
316 | size_t __sr1, size_t __sr2, |
317 | uint32_t __msk1, uint32_t __msk2, |
318 | uint32_t __msk3, uint32_t __msk4, |
319 | uint32_t __parity1, uint32_t __parity2, |
320 | uint32_t __parity3, uint32_t __parity4> |
321 | bool |
322 | operator==(const __gnu_cxx::simd_fast_mersenne_twister_engine<_UIntType, |
323 | __m, __pos1, __sl1, __sl2, __sr1, __sr2, |
324 | __msk1, __msk2, __msk3, __msk4, |
325 | __parity1, __parity2, __parity3, __parity4>& __lhs, |
326 | const __gnu_cxx::simd_fast_mersenne_twister_engine<_UIntType, |
327 | __m, __pos1, __sl1, __sl2, __sr1, __sr2, |
328 | __msk1, __msk2, __msk3, __msk4, |
329 | __parity1, __parity2, __parity3, __parity4>& __rhs) |
330 | { |
331 | typedef __gnu_cxx::simd_fast_mersenne_twister_engine<_UIntType, |
332 | __m, __pos1, __sl1, __sl2, __sr1, __sr2, |
333 | __msk1, __msk2, __msk3, __msk4, |
334 | __parity1, __parity2, __parity3, __parity4> __engine; |
335 | return (std::equal(__lhs._M_stateT, |
336 | __lhs._M_stateT + __engine::state_size, |
337 | __rhs._M_stateT) |
338 | && __lhs._M_pos == __rhs._M_pos); |
339 | } |
340 | #endif |
341 | |
342 | template<typename _UIntType, size_t __m, |
343 | size_t __pos1, size_t __sl1, size_t __sl2, |
344 | size_t __sr1, size_t __sr2, |
345 | uint32_t __msk1, uint32_t __msk2, |
346 | uint32_t __msk3, uint32_t __msk4, |
347 | uint32_t __parity1, uint32_t __parity2, |
348 | uint32_t __parity3, uint32_t __parity4, |
349 | typename _CharT, typename _Traits> |
350 | std::basic_ostream<_CharT, _Traits>& |
351 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
352 | const __gnu_cxx::simd_fast_mersenne_twister_engine<_UIntType, |
353 | __m, __pos1, __sl1, __sl2, __sr1, __sr2, |
354 | __msk1, __msk2, __msk3, __msk4, |
355 | __parity1, __parity2, __parity3, __parity4>& __x) |
356 | { |
357 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; |
358 | typedef typename __ostream_type::ios_base __ios_base; |
359 | |
360 | const typename __ios_base::fmtflags __flags = __os.flags(); |
361 | const _CharT __fill = __os.fill(); |
362 | const _CharT __space = __os.widen(' '); |
363 | __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left); |
364 | __os.fill(__space); |
365 | |
366 | for (size_t __i = 0; __i < __x._M_nstate32; ++__i) |
367 | __os << __x._M_state32[__i] << __space; |
368 | __os << __x._M_pos; |
369 | |
370 | __os.flags(__flags); |
371 | __os.fill(__fill); |
372 | return __os; |
373 | } |
374 | |
375 | |
376 | template<typename _UIntType, size_t __m, |
377 | size_t __pos1, size_t __sl1, size_t __sl2, |
378 | size_t __sr1, size_t __sr2, |
379 | uint32_t __msk1, uint32_t __msk2, |
380 | uint32_t __msk3, uint32_t __msk4, |
381 | uint32_t __parity1, uint32_t __parity2, |
382 | uint32_t __parity3, uint32_t __parity4, |
383 | typename _CharT, typename _Traits> |
384 | std::basic_istream<_CharT, _Traits>& |
385 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
386 | __gnu_cxx::simd_fast_mersenne_twister_engine<_UIntType, |
387 | __m, __pos1, __sl1, __sl2, __sr1, __sr2, |
388 | __msk1, __msk2, __msk3, __msk4, |
389 | __parity1, __parity2, __parity3, __parity4>& __x) |
390 | { |
391 | typedef std::basic_istream<_CharT, _Traits> __istream_type; |
392 | typedef typename __istream_type::ios_base __ios_base; |
393 | |
394 | const typename __ios_base::fmtflags __flags = __is.flags(); |
395 | __is.flags(__ios_base::dec | __ios_base::skipws); |
396 | |
397 | for (size_t __i = 0; __i < __x._M_nstate32; ++__i) |
398 | __is >> __x._M_state32[__i]; |
399 | __is >> __x._M_pos; |
400 | |
401 | __is.flags(__flags); |
402 | return __is; |
403 | } |
404 | |
405 | #endif // __BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__ |
406 | |
407 | /** |
408 | * Iteration method due to M.D. J<o:>hnk. |
409 | * |
410 | * M.D. J<o:>hnk, Erzeugung von betaverteilten und gammaverteilten |
411 | * Zufallszahlen, Metrika, Volume 8, 1964 |
412 | */ |
413 | template<typename _RealType> |
414 | template<typename _UniformRandomNumberGenerator> |
415 | typename beta_distribution<_RealType>::result_type |
416 | beta_distribution<_RealType>:: |
417 | operator()(_UniformRandomNumberGenerator& __urng, |
418 | const param_type& __param) |
419 | { |
420 | std::__detail::_Adaptor<_UniformRandomNumberGenerator, result_type> |
421 | __aurng(__urng); |
422 | |
423 | result_type __x, __y; |
424 | do |
425 | { |
426 | __x = std::exp(std::log(__aurng()) / __param.alpha()); |
427 | __y = std::exp(std::log(__aurng()) / __param.beta()); |
428 | } |
429 | while (__x + __y > result_type(1)); |
430 | |
431 | return __x / (__x + __y); |
432 | } |
433 | |
434 | template<typename _RealType> |
435 | template<typename _OutputIterator, |
436 | typename _UniformRandomNumberGenerator> |
437 | void |
438 | beta_distribution<_RealType>:: |
439 | __generate_impl(_OutputIterator __f, _OutputIterator __t, |
440 | _UniformRandomNumberGenerator& __urng, |
441 | const param_type& __param) |
442 | { |
443 | __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator, |
444 | result_type>) |
445 | |
446 | std::__detail::_Adaptor<_UniformRandomNumberGenerator, result_type> |
447 | __aurng(__urng); |
448 | |
449 | while (__f != __t) |
450 | { |
451 | result_type __x, __y; |
452 | do |
453 | { |
454 | __x = std::exp(std::log(__aurng()) / __param.alpha()); |
455 | __y = std::exp(std::log(__aurng()) / __param.beta()); |
456 | } |
457 | while (__x + __y > result_type(1)); |
458 | |
459 | *__f++ = __x / (__x + __y); |
460 | } |
461 | } |
462 | |
463 | template<typename _RealType, typename _CharT, typename _Traits> |
464 | std::basic_ostream<_CharT, _Traits>& |
465 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
466 | const __gnu_cxx::beta_distribution<_RealType>& __x) |
467 | { |
468 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; |
469 | typedef typename __ostream_type::ios_base __ios_base; |
470 | |
471 | const typename __ios_base::fmtflags __flags = __os.flags(); |
472 | const _CharT __fill = __os.fill(); |
473 | const std::streamsize __precision = __os.precision(); |
474 | const _CharT __space = __os.widen(' '); |
475 | __os.flags(__ios_base::scientific | __ios_base::left); |
476 | __os.fill(__space); |
477 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
478 | |
479 | __os << __x.alpha() << __space << __x.beta(); |
480 | |
481 | __os.flags(__flags); |
482 | __os.fill(__fill); |
483 | __os.precision(__precision); |
484 | return __os; |
485 | } |
486 | |
487 | template<typename _RealType, typename _CharT, typename _Traits> |
488 | std::basic_istream<_CharT, _Traits>& |
489 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
490 | __gnu_cxx::beta_distribution<_RealType>& __x) |
491 | { |
492 | typedef std::basic_istream<_CharT, _Traits> __istream_type; |
493 | typedef typename __istream_type::ios_base __ios_base; |
494 | |
495 | const typename __ios_base::fmtflags __flags = __is.flags(); |
496 | __is.flags(__ios_base::dec | __ios_base::skipws); |
497 | |
498 | _RealType __alpha_val, __beta_val; |
499 | __is >> __alpha_val >> __beta_val; |
500 | __x.param(typename __gnu_cxx::beta_distribution<_RealType>:: |
501 | param_type(__alpha_val, __beta_val)); |
502 | |
503 | __is.flags(__flags); |
504 | return __is; |
505 | } |
506 | |
507 | |
508 | template<std::size_t _Dimen, typename _RealType> |
509 | template<typename _InputIterator1, typename _InputIterator2> |
510 | void |
511 | normal_mv_distribution<_Dimen, _RealType>::param_type:: |
512 | _M_init_full(_InputIterator1 __meanbegin, _InputIterator1 __meanend, |
513 | _InputIterator2 __varcovbegin, _InputIterator2 __varcovend) |
514 | { |
515 | __glibcxx_function_requires(_InputIteratorConcept<_InputIterator1>) |
516 | __glibcxx_function_requires(_InputIteratorConcept<_InputIterator2>) |
517 | std::fill(std::copy(__meanbegin, __meanend, _M_mean.begin()), |
518 | _M_mean.end(), _RealType(0)); |
519 | |
520 | // Perform the Cholesky decomposition |
521 | auto __w = _M_t.begin(); |
522 | for (size_t __j = 0; __j < _Dimen; ++__j) |
523 | { |
524 | _RealType __sum = _RealType(0); |
525 | |
526 | auto __slitbegin = __w; |
527 | auto __cit = _M_t.begin(); |
528 | for (size_t __i = 0; __i < __j; ++__i) |
529 | { |
530 | auto __slit = __slitbegin; |
531 | _RealType __s = *__varcovbegin++; |
532 | for (size_t __k = 0; __k < __i; ++__k) |
533 | __s -= *__slit++ * *__cit++; |
534 | |
535 | *__w++ = __s /= *__cit++; |
536 | __sum += __s * __s; |
537 | } |
538 | |
539 | __sum = *__varcovbegin - __sum; |
540 | if (__builtin_expect(__sum <= _RealType(0), 0)) |
541 | std::__throw_runtime_error(__N("normal_mv_distribution::" |
542 | "param_type::_M_init_full" )); |
543 | *__w++ = std::sqrt(__sum); |
544 | |
545 | std::advance(__varcovbegin, _Dimen - __j); |
546 | } |
547 | } |
548 | |
549 | template<std::size_t _Dimen, typename _RealType> |
550 | template<typename _InputIterator1, typename _InputIterator2> |
551 | void |
552 | normal_mv_distribution<_Dimen, _RealType>::param_type:: |
553 | _M_init_lower(_InputIterator1 __meanbegin, _InputIterator1 __meanend, |
554 | _InputIterator2 __varcovbegin, _InputIterator2 __varcovend) |
555 | { |
556 | __glibcxx_function_requires(_InputIteratorConcept<_InputIterator1>) |
557 | __glibcxx_function_requires(_InputIteratorConcept<_InputIterator2>) |
558 | std::fill(std::copy(__meanbegin, __meanend, _M_mean.begin()), |
559 | _M_mean.end(), _RealType(0)); |
560 | |
561 | // Perform the Cholesky decomposition |
562 | auto __w = _M_t.begin(); |
563 | for (size_t __j = 0; __j < _Dimen; ++__j) |
564 | { |
565 | _RealType __sum = _RealType(0); |
566 | |
567 | auto __slitbegin = __w; |
568 | auto __cit = _M_t.begin(); |
569 | for (size_t __i = 0; __i < __j; ++__i) |
570 | { |
571 | auto __slit = __slitbegin; |
572 | _RealType __s = *__varcovbegin++; |
573 | for (size_t __k = 0; __k < __i; ++__k) |
574 | __s -= *__slit++ * *__cit++; |
575 | |
576 | *__w++ = __s /= *__cit++; |
577 | __sum += __s * __s; |
578 | } |
579 | |
580 | __sum = *__varcovbegin++ - __sum; |
581 | if (__builtin_expect(__sum <= _RealType(0), 0)) |
582 | std::__throw_runtime_error(__N("normal_mv_distribution::" |
583 | "param_type::_M_init_full" )); |
584 | *__w++ = std::sqrt(__sum); |
585 | } |
586 | } |
587 | |
588 | template<std::size_t _Dimen, typename _RealType> |
589 | template<typename _InputIterator1, typename _InputIterator2> |
590 | void |
591 | normal_mv_distribution<_Dimen, _RealType>::param_type:: |
592 | _M_init_diagonal(_InputIterator1 __meanbegin, _InputIterator1 __meanend, |
593 | _InputIterator2 __varbegin, _InputIterator2 __varend) |
594 | { |
595 | __glibcxx_function_requires(_InputIteratorConcept<_InputIterator1>) |
596 | __glibcxx_function_requires(_InputIteratorConcept<_InputIterator2>) |
597 | std::fill(std::copy(__meanbegin, __meanend, _M_mean.begin()), |
598 | _M_mean.end(), _RealType(0)); |
599 | |
600 | auto __w = _M_t.begin(); |
601 | size_t __step = 0; |
602 | while (__varbegin != __varend) |
603 | { |
604 | std::fill_n(__w, __step, _RealType(0)); |
605 | __w += __step++; |
606 | if (__builtin_expect(*__varbegin < _RealType(0), 0)) |
607 | std::__throw_runtime_error(__N("normal_mv_distribution::" |
608 | "param_type::_M_init_diagonal" )); |
609 | *__w++ = std::sqrt(*__varbegin++); |
610 | } |
611 | } |
612 | |
613 | template<std::size_t _Dimen, typename _RealType> |
614 | template<typename _UniformRandomNumberGenerator> |
615 | typename normal_mv_distribution<_Dimen, _RealType>::result_type |
616 | normal_mv_distribution<_Dimen, _RealType>:: |
617 | operator()(_UniformRandomNumberGenerator& __urng, |
618 | const param_type& __param) |
619 | { |
620 | result_type __ret; |
621 | |
622 | _M_nd.__generate(__ret.begin(), __ret.end(), __urng); |
623 | |
624 | auto __t_it = __param._M_t.crbegin(); |
625 | for (size_t __i = _Dimen; __i > 0; --__i) |
626 | { |
627 | _RealType __sum = _RealType(0); |
628 | for (size_t __j = __i; __j > 0; --__j) |
629 | __sum += __ret[__j - 1] * *__t_it++; |
630 | __ret[__i - 1] = __sum; |
631 | } |
632 | |
633 | return __ret; |
634 | } |
635 | |
636 | template<std::size_t _Dimen, typename _RealType> |
637 | template<typename _ForwardIterator, typename _UniformRandomNumberGenerator> |
638 | void |
639 | normal_mv_distribution<_Dimen, _RealType>:: |
640 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
641 | _UniformRandomNumberGenerator& __urng, |
642 | const param_type& __param) |
643 | { |
644 | __glibcxx_function_requires(_Mutable_ForwardIteratorConcept< |
645 | _ForwardIterator>) |
646 | while (__f != __t) |
647 | *__f++ = this->operator()(__urng, __param); |
648 | } |
649 | |
650 | template<size_t _Dimen, typename _RealType> |
651 | bool |
652 | operator==(const __gnu_cxx::normal_mv_distribution<_Dimen, _RealType>& |
653 | __d1, |
654 | const __gnu_cxx::normal_mv_distribution<_Dimen, _RealType>& |
655 | __d2) |
656 | { |
657 | return __d1._M_param == __d2._M_param && __d1._M_nd == __d2._M_nd; |
658 | } |
659 | |
660 | template<size_t _Dimen, typename _RealType, typename _CharT, typename _Traits> |
661 | std::basic_ostream<_CharT, _Traits>& |
662 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
663 | const __gnu_cxx::normal_mv_distribution<_Dimen, _RealType>& __x) |
664 | { |
665 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; |
666 | typedef typename __ostream_type::ios_base __ios_base; |
667 | |
668 | const typename __ios_base::fmtflags __flags = __os.flags(); |
669 | const _CharT __fill = __os.fill(); |
670 | const std::streamsize __precision = __os.precision(); |
671 | const _CharT __space = __os.widen(' '); |
672 | __os.flags(__ios_base::scientific | __ios_base::left); |
673 | __os.fill(__space); |
674 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
675 | |
676 | auto __mean = __x._M_param.mean(); |
677 | for (auto __it : __mean) |
678 | __os << __it << __space; |
679 | auto __t = __x._M_param.varcov(); |
680 | for (auto __it : __t) |
681 | __os << __it << __space; |
682 | |
683 | __os << __x._M_nd; |
684 | |
685 | __os.flags(__flags); |
686 | __os.fill(__fill); |
687 | __os.precision(__precision); |
688 | return __os; |
689 | } |
690 | |
691 | template<size_t _Dimen, typename _RealType, typename _CharT, typename _Traits> |
692 | std::basic_istream<_CharT, _Traits>& |
693 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
694 | __gnu_cxx::normal_mv_distribution<_Dimen, _RealType>& __x) |
695 | { |
696 | typedef std::basic_istream<_CharT, _Traits> __istream_type; |
697 | typedef typename __istream_type::ios_base __ios_base; |
698 | |
699 | const typename __ios_base::fmtflags __flags = __is.flags(); |
700 | __is.flags(__ios_base::dec | __ios_base::skipws); |
701 | |
702 | std::array<_RealType, _Dimen> __mean; |
703 | for (auto& __it : __mean) |
704 | __is >> __it; |
705 | std::array<_RealType, _Dimen * (_Dimen + 1) / 2> __varcov; |
706 | for (auto& __it : __varcov) |
707 | __is >> __it; |
708 | |
709 | __is >> __x._M_nd; |
710 | |
711 | __x.param(typename normal_mv_distribution<_Dimen, _RealType>:: |
712 | param_type(__mean.begin(), __mean.end(), |
713 | __varcov.begin(), __varcov.end())); |
714 | |
715 | __is.flags(__flags); |
716 | return __is; |
717 | } |
718 | |
719 | |
720 | template<typename _RealType> |
721 | template<typename _OutputIterator, |
722 | typename _UniformRandomNumberGenerator> |
723 | void |
724 | rice_distribution<_RealType>:: |
725 | __generate_impl(_OutputIterator __f, _OutputIterator __t, |
726 | _UniformRandomNumberGenerator& __urng, |
727 | const param_type& __p) |
728 | { |
729 | __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator, |
730 | result_type>) |
731 | |
732 | while (__f != __t) |
733 | { |
734 | typename std::normal_distribution<result_type>::param_type |
735 | __px(__p.nu(), __p.sigma()), __py(result_type(0), __p.sigma()); |
736 | result_type __x = this->_M_ndx(__px, __urng); |
737 | result_type __y = this->_M_ndy(__py, __urng); |
738 | #if _GLIBCXX_USE_C99_MATH_TR1 |
739 | *__f++ = std::hypot(__x, __y); |
740 | #else |
741 | *__f++ = std::sqrt(__x * __x + __y * __y); |
742 | #endif |
743 | } |
744 | } |
745 | |
746 | template<typename _RealType, typename _CharT, typename _Traits> |
747 | std::basic_ostream<_CharT, _Traits>& |
748 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
749 | const rice_distribution<_RealType>& __x) |
750 | { |
751 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; |
752 | typedef typename __ostream_type::ios_base __ios_base; |
753 | |
754 | const typename __ios_base::fmtflags __flags = __os.flags(); |
755 | const _CharT __fill = __os.fill(); |
756 | const std::streamsize __precision = __os.precision(); |
757 | const _CharT __space = __os.widen(' '); |
758 | __os.flags(__ios_base::scientific | __ios_base::left); |
759 | __os.fill(__space); |
760 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
761 | |
762 | __os << __x.nu() << __space << __x.sigma(); |
763 | __os << __space << __x._M_ndx; |
764 | __os << __space << __x._M_ndy; |
765 | |
766 | __os.flags(__flags); |
767 | __os.fill(__fill); |
768 | __os.precision(__precision); |
769 | return __os; |
770 | } |
771 | |
772 | template<typename _RealType, typename _CharT, typename _Traits> |
773 | std::basic_istream<_CharT, _Traits>& |
774 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
775 | rice_distribution<_RealType>& __x) |
776 | { |
777 | typedef std::basic_istream<_CharT, _Traits> __istream_type; |
778 | typedef typename __istream_type::ios_base __ios_base; |
779 | |
780 | const typename __ios_base::fmtflags __flags = __is.flags(); |
781 | __is.flags(__ios_base::dec | __ios_base::skipws); |
782 | |
783 | _RealType __nu_val, __sigma_val; |
784 | __is >> __nu_val >> __sigma_val; |
785 | __is >> __x._M_ndx; |
786 | __is >> __x._M_ndy; |
787 | __x.param(typename rice_distribution<_RealType>:: |
788 | param_type(__nu_val, __sigma_val)); |
789 | |
790 | __is.flags(__flags); |
791 | return __is; |
792 | } |
793 | |
794 | |
795 | template<typename _RealType> |
796 | template<typename _OutputIterator, |
797 | typename _UniformRandomNumberGenerator> |
798 | void |
799 | nakagami_distribution<_RealType>:: |
800 | __generate_impl(_OutputIterator __f, _OutputIterator __t, |
801 | _UniformRandomNumberGenerator& __urng, |
802 | const param_type& __p) |
803 | { |
804 | __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator, |
805 | result_type>) |
806 | |
807 | typename std::gamma_distribution<result_type>::param_type |
808 | __pg(__p.mu(), __p.omega() / __p.mu()); |
809 | while (__f != __t) |
810 | *__f++ = std::sqrt(this->_M_gd(__pg, __urng)); |
811 | } |
812 | |
813 | template<typename _RealType, typename _CharT, typename _Traits> |
814 | std::basic_ostream<_CharT, _Traits>& |
815 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
816 | const nakagami_distribution<_RealType>& __x) |
817 | { |
818 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; |
819 | typedef typename __ostream_type::ios_base __ios_base; |
820 | |
821 | const typename __ios_base::fmtflags __flags = __os.flags(); |
822 | const _CharT __fill = __os.fill(); |
823 | const std::streamsize __precision = __os.precision(); |
824 | const _CharT __space = __os.widen(' '); |
825 | __os.flags(__ios_base::scientific | __ios_base::left); |
826 | __os.fill(__space); |
827 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
828 | |
829 | __os << __x.mu() << __space << __x.omega(); |
830 | __os << __space << __x._M_gd; |
831 | |
832 | __os.flags(__flags); |
833 | __os.fill(__fill); |
834 | __os.precision(__precision); |
835 | return __os; |
836 | } |
837 | |
838 | template<typename _RealType, typename _CharT, typename _Traits> |
839 | std::basic_istream<_CharT, _Traits>& |
840 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
841 | nakagami_distribution<_RealType>& __x) |
842 | { |
843 | typedef std::basic_istream<_CharT, _Traits> __istream_type; |
844 | typedef typename __istream_type::ios_base __ios_base; |
845 | |
846 | const typename __ios_base::fmtflags __flags = __is.flags(); |
847 | __is.flags(__ios_base::dec | __ios_base::skipws); |
848 | |
849 | _RealType __mu_val, __omega_val; |
850 | __is >> __mu_val >> __omega_val; |
851 | __is >> __x._M_gd; |
852 | __x.param(typename nakagami_distribution<_RealType>:: |
853 | param_type(__mu_val, __omega_val)); |
854 | |
855 | __is.flags(__flags); |
856 | return __is; |
857 | } |
858 | |
859 | |
860 | template<typename _RealType> |
861 | template<typename _OutputIterator, |
862 | typename _UniformRandomNumberGenerator> |
863 | void |
864 | pareto_distribution<_RealType>:: |
865 | __generate_impl(_OutputIterator __f, _OutputIterator __t, |
866 | _UniformRandomNumberGenerator& __urng, |
867 | const param_type& __p) |
868 | { |
869 | __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator, |
870 | result_type>) |
871 | |
872 | result_type __mu_val = __p.mu(); |
873 | result_type __malphinv = -result_type(1) / __p.alpha(); |
874 | while (__f != __t) |
875 | *__f++ = __mu_val * std::pow(this->_M_ud(__urng), __malphinv); |
876 | } |
877 | |
878 | template<typename _RealType, typename _CharT, typename _Traits> |
879 | std::basic_ostream<_CharT, _Traits>& |
880 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
881 | const pareto_distribution<_RealType>& __x) |
882 | { |
883 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; |
884 | typedef typename __ostream_type::ios_base __ios_base; |
885 | |
886 | const typename __ios_base::fmtflags __flags = __os.flags(); |
887 | const _CharT __fill = __os.fill(); |
888 | const std::streamsize __precision = __os.precision(); |
889 | const _CharT __space = __os.widen(' '); |
890 | __os.flags(__ios_base::scientific | __ios_base::left); |
891 | __os.fill(__space); |
892 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
893 | |
894 | __os << __x.alpha() << __space << __x.mu(); |
895 | __os << __space << __x._M_ud; |
896 | |
897 | __os.flags(__flags); |
898 | __os.fill(__fill); |
899 | __os.precision(__precision); |
900 | return __os; |
901 | } |
902 | |
903 | template<typename _RealType, typename _CharT, typename _Traits> |
904 | std::basic_istream<_CharT, _Traits>& |
905 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
906 | pareto_distribution<_RealType>& __x) |
907 | { |
908 | typedef std::basic_istream<_CharT, _Traits> __istream_type; |
909 | typedef typename __istream_type::ios_base __ios_base; |
910 | |
911 | const typename __ios_base::fmtflags __flags = __is.flags(); |
912 | __is.flags(__ios_base::dec | __ios_base::skipws); |
913 | |
914 | _RealType __alpha_val, __mu_val; |
915 | __is >> __alpha_val >> __mu_val; |
916 | __is >> __x._M_ud; |
917 | __x.param(typename pareto_distribution<_RealType>:: |
918 | param_type(__alpha_val, __mu_val)); |
919 | |
920 | __is.flags(__flags); |
921 | return __is; |
922 | } |
923 | |
924 | |
925 | template<typename _RealType> |
926 | template<typename _UniformRandomNumberGenerator> |
927 | typename k_distribution<_RealType>::result_type |
928 | k_distribution<_RealType>:: |
929 | operator()(_UniformRandomNumberGenerator& __urng) |
930 | { |
931 | result_type __x = this->_M_gd1(__urng); |
932 | result_type __y = this->_M_gd2(__urng); |
933 | return std::sqrt(__x * __y); |
934 | } |
935 | |
936 | template<typename _RealType> |
937 | template<typename _UniformRandomNumberGenerator> |
938 | typename k_distribution<_RealType>::result_type |
939 | k_distribution<_RealType>:: |
940 | operator()(_UniformRandomNumberGenerator& __urng, |
941 | const param_type& __p) |
942 | { |
943 | typename std::gamma_distribution<result_type>::param_type |
944 | __p1(__p.lambda(), result_type(1) / __p.lambda()), |
945 | __p2(__p.nu(), __p.mu() / __p.nu()); |
946 | result_type __x = this->_M_gd1(__p1, __urng); |
947 | result_type __y = this->_M_gd2(__p2, __urng); |
948 | return std::sqrt(__x * __y); |
949 | } |
950 | |
951 | template<typename _RealType> |
952 | template<typename _OutputIterator, |
953 | typename _UniformRandomNumberGenerator> |
954 | void |
955 | k_distribution<_RealType>:: |
956 | __generate_impl(_OutputIterator __f, _OutputIterator __t, |
957 | _UniformRandomNumberGenerator& __urng, |
958 | const param_type& __p) |
959 | { |
960 | __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator, |
961 | result_type>) |
962 | |
963 | typename std::gamma_distribution<result_type>::param_type |
964 | __p1(__p.lambda(), result_type(1) / __p.lambda()), |
965 | __p2(__p.nu(), __p.mu() / __p.nu()); |
966 | while (__f != __t) |
967 | { |
968 | result_type __x = this->_M_gd1(__p1, __urng); |
969 | result_type __y = this->_M_gd2(__p2, __urng); |
970 | *__f++ = std::sqrt(__x * __y); |
971 | } |
972 | } |
973 | |
974 | template<typename _RealType, typename _CharT, typename _Traits> |
975 | std::basic_ostream<_CharT, _Traits>& |
976 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
977 | const k_distribution<_RealType>& __x) |
978 | { |
979 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; |
980 | typedef typename __ostream_type::ios_base __ios_base; |
981 | |
982 | const typename __ios_base::fmtflags __flags = __os.flags(); |
983 | const _CharT __fill = __os.fill(); |
984 | const std::streamsize __precision = __os.precision(); |
985 | const _CharT __space = __os.widen(' '); |
986 | __os.flags(__ios_base::scientific | __ios_base::left); |
987 | __os.fill(__space); |
988 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
989 | |
990 | __os << __x.lambda() << __space << __x.mu() << __space << __x.nu(); |
991 | __os << __space << __x._M_gd1; |
992 | __os << __space << __x._M_gd2; |
993 | |
994 | __os.flags(__flags); |
995 | __os.fill(__fill); |
996 | __os.precision(__precision); |
997 | return __os; |
998 | } |
999 | |
1000 | template<typename _RealType, typename _CharT, typename _Traits> |
1001 | std::basic_istream<_CharT, _Traits>& |
1002 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
1003 | k_distribution<_RealType>& __x) |
1004 | { |
1005 | typedef std::basic_istream<_CharT, _Traits> __istream_type; |
1006 | typedef typename __istream_type::ios_base __ios_base; |
1007 | |
1008 | const typename __ios_base::fmtflags __flags = __is.flags(); |
1009 | __is.flags(__ios_base::dec | __ios_base::skipws); |
1010 | |
1011 | _RealType __lambda_val, __mu_val, __nu_val; |
1012 | __is >> __lambda_val >> __mu_val >> __nu_val; |
1013 | __is >> __x._M_gd1; |
1014 | __is >> __x._M_gd2; |
1015 | __x.param(typename k_distribution<_RealType>:: |
1016 | param_type(__lambda_val, __mu_val, __nu_val)); |
1017 | |
1018 | __is.flags(__flags); |
1019 | return __is; |
1020 | } |
1021 | |
1022 | |
1023 | template<typename _RealType> |
1024 | template<typename _OutputIterator, |
1025 | typename _UniformRandomNumberGenerator> |
1026 | void |
1027 | arcsine_distribution<_RealType>:: |
1028 | __generate_impl(_OutputIterator __f, _OutputIterator __t, |
1029 | _UniformRandomNumberGenerator& __urng, |
1030 | const param_type& __p) |
1031 | { |
1032 | __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator, |
1033 | result_type>) |
1034 | |
1035 | result_type __dif = __p.b() - __p.a(); |
1036 | result_type __sum = __p.a() + __p.b(); |
1037 | while (__f != __t) |
1038 | { |
1039 | result_type __x = std::sin(this->_M_ud(__urng)); |
1040 | *__f++ = (__x * __dif + __sum) / result_type(2); |
1041 | } |
1042 | } |
1043 | |
1044 | template<typename _RealType, typename _CharT, typename _Traits> |
1045 | std::basic_ostream<_CharT, _Traits>& |
1046 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
1047 | const arcsine_distribution<_RealType>& __x) |
1048 | { |
1049 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; |
1050 | typedef typename __ostream_type::ios_base __ios_base; |
1051 | |
1052 | const typename __ios_base::fmtflags __flags = __os.flags(); |
1053 | const _CharT __fill = __os.fill(); |
1054 | const std::streamsize __precision = __os.precision(); |
1055 | const _CharT __space = __os.widen(' '); |
1056 | __os.flags(__ios_base::scientific | __ios_base::left); |
1057 | __os.fill(__space); |
1058 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
1059 | |
1060 | __os << __x.a() << __space << __x.b(); |
1061 | __os << __space << __x._M_ud; |
1062 | |
1063 | __os.flags(__flags); |
1064 | __os.fill(__fill); |
1065 | __os.precision(__precision); |
1066 | return __os; |
1067 | } |
1068 | |
1069 | template<typename _RealType, typename _CharT, typename _Traits> |
1070 | std::basic_istream<_CharT, _Traits>& |
1071 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
1072 | arcsine_distribution<_RealType>& __x) |
1073 | { |
1074 | typedef std::basic_istream<_CharT, _Traits> __istream_type; |
1075 | typedef typename __istream_type::ios_base __ios_base; |
1076 | |
1077 | const typename __ios_base::fmtflags __flags = __is.flags(); |
1078 | __is.flags(__ios_base::dec | __ios_base::skipws); |
1079 | |
1080 | _RealType __a, __b; |
1081 | __is >> __a >> __b; |
1082 | __is >> __x._M_ud; |
1083 | __x.param(typename arcsine_distribution<_RealType>:: |
1084 | param_type(__a, __b)); |
1085 | |
1086 | __is.flags(__flags); |
1087 | return __is; |
1088 | } |
1089 | |
1090 | |
1091 | template<typename _RealType> |
1092 | template<typename _UniformRandomNumberGenerator> |
1093 | typename hoyt_distribution<_RealType>::result_type |
1094 | hoyt_distribution<_RealType>:: |
1095 | operator()(_UniformRandomNumberGenerator& __urng) |
1096 | { |
1097 | result_type __x = this->_M_ad(__urng); |
1098 | result_type __y = this->_M_ed(__urng); |
1099 | return (result_type(2) * this->q() |
1100 | / (result_type(1) + this->q() * this->q())) |
1101 | * std::sqrt(this->omega() * __x * __y); |
1102 | } |
1103 | |
1104 | template<typename _RealType> |
1105 | template<typename _UniformRandomNumberGenerator> |
1106 | typename hoyt_distribution<_RealType>::result_type |
1107 | hoyt_distribution<_RealType>:: |
1108 | operator()(_UniformRandomNumberGenerator& __urng, |
1109 | const param_type& __p) |
1110 | { |
1111 | result_type __q2 = __p.q() * __p.q(); |
1112 | result_type __num = result_type(0.5L) * (result_type(1) + __q2); |
1113 | typename __gnu_cxx::arcsine_distribution<result_type>::param_type |
1114 | __pa(__num, __num / __q2); |
1115 | result_type __x = this->_M_ad(__pa, __urng); |
1116 | result_type __y = this->_M_ed(__urng); |
1117 | return (result_type(2) * __p.q() / (result_type(1) + __q2)) |
1118 | * std::sqrt(__p.omega() * __x * __y); |
1119 | } |
1120 | |
1121 | template<typename _RealType> |
1122 | template<typename _OutputIterator, |
1123 | typename _UniformRandomNumberGenerator> |
1124 | void |
1125 | hoyt_distribution<_RealType>:: |
1126 | __generate_impl(_OutputIterator __f, _OutputIterator __t, |
1127 | _UniformRandomNumberGenerator& __urng, |
1128 | const param_type& __p) |
1129 | { |
1130 | __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator, |
1131 | result_type>) |
1132 | |
1133 | result_type __2q = result_type(2) * __p.q(); |
1134 | result_type __q2 = __p.q() * __p.q(); |
1135 | result_type __q2p1 = result_type(1) + __q2; |
1136 | result_type __num = result_type(0.5L) * __q2p1; |
1137 | result_type __omega = __p.omega(); |
1138 | typename __gnu_cxx::arcsine_distribution<result_type>::param_type |
1139 | __pa(__num, __num / __q2); |
1140 | while (__f != __t) |
1141 | { |
1142 | result_type __x = this->_M_ad(__pa, __urng); |
1143 | result_type __y = this->_M_ed(__urng); |
1144 | *__f++ = (__2q / __q2p1) * std::sqrt(__omega * __x * __y); |
1145 | } |
1146 | } |
1147 | |
1148 | template<typename _RealType, typename _CharT, typename _Traits> |
1149 | std::basic_ostream<_CharT, _Traits>& |
1150 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
1151 | const hoyt_distribution<_RealType>& __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 | const _CharT __space = __os.widen(' '); |
1160 | __os.flags(__ios_base::scientific | __ios_base::left); |
1161 | __os.fill(__space); |
1162 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
1163 | |
1164 | __os << __x.q() << __space << __x.omega(); |
1165 | __os << __space << __x._M_ad; |
1166 | __os << __space << __x._M_ed; |
1167 | |
1168 | __os.flags(__flags); |
1169 | __os.fill(__fill); |
1170 | __os.precision(__precision); |
1171 | return __os; |
1172 | } |
1173 | |
1174 | template<typename _RealType, typename _CharT, typename _Traits> |
1175 | std::basic_istream<_CharT, _Traits>& |
1176 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
1177 | hoyt_distribution<_RealType>& __x) |
1178 | { |
1179 | typedef std::basic_istream<_CharT, _Traits> __istream_type; |
1180 | typedef typename __istream_type::ios_base __ios_base; |
1181 | |
1182 | const typename __ios_base::fmtflags __flags = __is.flags(); |
1183 | __is.flags(__ios_base::dec | __ios_base::skipws); |
1184 | |
1185 | _RealType __q, __omega; |
1186 | __is >> __q >> __omega; |
1187 | __is >> __x._M_ad; |
1188 | __is >> __x._M_ed; |
1189 | __x.param(typename hoyt_distribution<_RealType>:: |
1190 | param_type(__q, __omega)); |
1191 | |
1192 | __is.flags(__flags); |
1193 | return __is; |
1194 | } |
1195 | |
1196 | |
1197 | template<typename _RealType> |
1198 | template<typename _OutputIterator, |
1199 | typename _UniformRandomNumberGenerator> |
1200 | void |
1201 | triangular_distribution<_RealType>:: |
1202 | __generate_impl(_OutputIterator __f, _OutputIterator __t, |
1203 | _UniformRandomNumberGenerator& __urng, |
1204 | const param_type& __param) |
1205 | { |
1206 | __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator, |
1207 | result_type>) |
1208 | |
1209 | while (__f != __t) |
1210 | *__f++ = this->operator()(__urng, __param); |
1211 | } |
1212 | |
1213 | template<typename _RealType, typename _CharT, typename _Traits> |
1214 | std::basic_ostream<_CharT, _Traits>& |
1215 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
1216 | const __gnu_cxx::triangular_distribution<_RealType>& __x) |
1217 | { |
1218 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; |
1219 | typedef typename __ostream_type::ios_base __ios_base; |
1220 | |
1221 | const typename __ios_base::fmtflags __flags = __os.flags(); |
1222 | const _CharT __fill = __os.fill(); |
1223 | const std::streamsize __precision = __os.precision(); |
1224 | const _CharT __space = __os.widen(' '); |
1225 | __os.flags(__ios_base::scientific | __ios_base::left); |
1226 | __os.fill(__space); |
1227 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
1228 | |
1229 | __os << __x.a() << __space << __x.b() << __space << __x.c(); |
1230 | |
1231 | __os.flags(__flags); |
1232 | __os.fill(__fill); |
1233 | __os.precision(__precision); |
1234 | return __os; |
1235 | } |
1236 | |
1237 | template<typename _RealType, typename _CharT, typename _Traits> |
1238 | std::basic_istream<_CharT, _Traits>& |
1239 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
1240 | __gnu_cxx::triangular_distribution<_RealType>& __x) |
1241 | { |
1242 | typedef std::basic_istream<_CharT, _Traits> __istream_type; |
1243 | typedef typename __istream_type::ios_base __ios_base; |
1244 | |
1245 | const typename __ios_base::fmtflags __flags = __is.flags(); |
1246 | __is.flags(__ios_base::dec | __ios_base::skipws); |
1247 | |
1248 | _RealType __a, __b, __c; |
1249 | __is >> __a >> __b >> __c; |
1250 | __x.param(typename __gnu_cxx::triangular_distribution<_RealType>:: |
1251 | param_type(__a, __b, __c)); |
1252 | |
1253 | __is.flags(__flags); |
1254 | return __is; |
1255 | } |
1256 | |
1257 | |
1258 | template<typename _RealType> |
1259 | template<typename _UniformRandomNumberGenerator> |
1260 | typename von_mises_distribution<_RealType>::result_type |
1261 | von_mises_distribution<_RealType>:: |
1262 | operator()(_UniformRandomNumberGenerator& __urng, |
1263 | const param_type& __p) |
1264 | { |
1265 | const result_type __pi |
1266 | = __gnu_cxx::__math_constants<result_type>::__pi; |
1267 | std::__detail::_Adaptor<_UniformRandomNumberGenerator, result_type> |
1268 | __aurng(__urng); |
1269 | |
1270 | result_type __f; |
1271 | while (1) |
1272 | { |
1273 | result_type __rnd = std::cos(__pi * __aurng()); |
1274 | __f = (result_type(1) + __p._M_r * __rnd) / (__p._M_r + __rnd); |
1275 | result_type __c = __p._M_kappa * (__p._M_r - __f); |
1276 | |
1277 | result_type __rnd2 = __aurng(); |
1278 | if (__c * (result_type(2) - __c) > __rnd2) |
1279 | break; |
1280 | if (std::log(__c / __rnd2) >= __c - result_type(1)) |
1281 | break; |
1282 | } |
1283 | |
1284 | result_type __res = std::acos(__f); |
1285 | #if _GLIBCXX_USE_C99_MATH_TR1 |
1286 | __res = std::copysign(__res, __aurng() - result_type(0.5)); |
1287 | #else |
1288 | if (__aurng() < result_type(0.5)) |
1289 | __res = -__res; |
1290 | #endif |
1291 | __res += __p._M_mu; |
1292 | if (__res > __pi) |
1293 | __res -= result_type(2) * __pi; |
1294 | else if (__res < -__pi) |
1295 | __res += result_type(2) * __pi; |
1296 | return __res; |
1297 | } |
1298 | |
1299 | template<typename _RealType> |
1300 | template<typename _OutputIterator, |
1301 | typename _UniformRandomNumberGenerator> |
1302 | void |
1303 | von_mises_distribution<_RealType>:: |
1304 | __generate_impl(_OutputIterator __f, _OutputIterator __t, |
1305 | _UniformRandomNumberGenerator& __urng, |
1306 | const param_type& __param) |
1307 | { |
1308 | __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator, |
1309 | result_type>) |
1310 | |
1311 | while (__f != __t) |
1312 | *__f++ = this->operator()(__urng, __param); |
1313 | } |
1314 | |
1315 | template<typename _RealType, typename _CharT, typename _Traits> |
1316 | std::basic_ostream<_CharT, _Traits>& |
1317 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
1318 | const __gnu_cxx::von_mises_distribution<_RealType>& __x) |
1319 | { |
1320 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; |
1321 | typedef typename __ostream_type::ios_base __ios_base; |
1322 | |
1323 | const typename __ios_base::fmtflags __flags = __os.flags(); |
1324 | const _CharT __fill = __os.fill(); |
1325 | const std::streamsize __precision = __os.precision(); |
1326 | const _CharT __space = __os.widen(' '); |
1327 | __os.flags(__ios_base::scientific | __ios_base::left); |
1328 | __os.fill(__space); |
1329 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
1330 | |
1331 | __os << __x.mu() << __space << __x.kappa(); |
1332 | |
1333 | __os.flags(__flags); |
1334 | __os.fill(__fill); |
1335 | __os.precision(__precision); |
1336 | return __os; |
1337 | } |
1338 | |
1339 | template<typename _RealType, typename _CharT, typename _Traits> |
1340 | std::basic_istream<_CharT, _Traits>& |
1341 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
1342 | __gnu_cxx::von_mises_distribution<_RealType>& __x) |
1343 | { |
1344 | typedef std::basic_istream<_CharT, _Traits> __istream_type; |
1345 | typedef typename __istream_type::ios_base __ios_base; |
1346 | |
1347 | const typename __ios_base::fmtflags __flags = __is.flags(); |
1348 | __is.flags(__ios_base::dec | __ios_base::skipws); |
1349 | |
1350 | _RealType __mu, __kappa; |
1351 | __is >> __mu >> __kappa; |
1352 | __x.param(typename __gnu_cxx::von_mises_distribution<_RealType>:: |
1353 | param_type(__mu, __kappa)); |
1354 | |
1355 | __is.flags(__flags); |
1356 | return __is; |
1357 | } |
1358 | |
1359 | |
1360 | template<typename _UIntType> |
1361 | template<typename _UniformRandomNumberGenerator> |
1362 | typename hypergeometric_distribution<_UIntType>::result_type |
1363 | hypergeometric_distribution<_UIntType>:: |
1364 | operator()(_UniformRandomNumberGenerator& __urng, |
1365 | const param_type& __param) |
1366 | { |
1367 | std::__detail::_Adaptor<_UniformRandomNumberGenerator, double> |
1368 | __aurng(__urng); |
1369 | |
1370 | result_type __a = __param.successful_size(); |
1371 | result_type __b = __param.total_size(); |
1372 | result_type __k = 0; |
1373 | |
1374 | if (__param.total_draws() < __param.total_size() / 2) |
1375 | { |
1376 | for (result_type __i = 0; __i < __param.total_draws(); ++__i) |
1377 | { |
1378 | if (__b * __aurng() < __a) |
1379 | { |
1380 | ++__k; |
1381 | if (__k == __param.successful_size()) |
1382 | return __k; |
1383 | --__a; |
1384 | } |
1385 | --__b; |
1386 | } |
1387 | return __k; |
1388 | } |
1389 | else |
1390 | { |
1391 | for (result_type __i = 0; __i < __param.unsuccessful_size(); ++__i) |
1392 | { |
1393 | if (__b * __aurng() < __a) |
1394 | { |
1395 | ++__k; |
1396 | if (__k == __param.successful_size()) |
1397 | return __param.successful_size() - __k; |
1398 | --__a; |
1399 | } |
1400 | --__b; |
1401 | } |
1402 | return __param.successful_size() - __k; |
1403 | } |
1404 | } |
1405 | |
1406 | template<typename _UIntType> |
1407 | template<typename _OutputIterator, |
1408 | typename _UniformRandomNumberGenerator> |
1409 | void |
1410 | hypergeometric_distribution<_UIntType>:: |
1411 | __generate_impl(_OutputIterator __f, _OutputIterator __t, |
1412 | _UniformRandomNumberGenerator& __urng, |
1413 | const param_type& __param) |
1414 | { |
1415 | __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator, |
1416 | result_type>) |
1417 | |
1418 | while (__f != __t) |
1419 | *__f++ = this->operator()(__urng); |
1420 | } |
1421 | |
1422 | template<typename _UIntType, typename _CharT, typename _Traits> |
1423 | std::basic_ostream<_CharT, _Traits>& |
1424 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
1425 | const __gnu_cxx::hypergeometric_distribution<_UIntType>& __x) |
1426 | { |
1427 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; |
1428 | typedef typename __ostream_type::ios_base __ios_base; |
1429 | |
1430 | const typename __ios_base::fmtflags __flags = __os.flags(); |
1431 | const _CharT __fill = __os.fill(); |
1432 | const std::streamsize __precision = __os.precision(); |
1433 | const _CharT __space = __os.widen(' '); |
1434 | __os.flags(__ios_base::scientific | __ios_base::left); |
1435 | __os.fill(__space); |
1436 | __os.precision(std::numeric_limits<_UIntType>::max_digits10); |
1437 | |
1438 | __os << __x.total_size() << __space << __x.successful_size() << __space |
1439 | << __x.total_draws(); |
1440 | |
1441 | __os.flags(__flags); |
1442 | __os.fill(__fill); |
1443 | __os.precision(__precision); |
1444 | return __os; |
1445 | } |
1446 | |
1447 | template<typename _UIntType, typename _CharT, typename _Traits> |
1448 | std::basic_istream<_CharT, _Traits>& |
1449 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
1450 | __gnu_cxx::hypergeometric_distribution<_UIntType>& __x) |
1451 | { |
1452 | typedef std::basic_istream<_CharT, _Traits> __istream_type; |
1453 | typedef typename __istream_type::ios_base __ios_base; |
1454 | |
1455 | const typename __ios_base::fmtflags __flags = __is.flags(); |
1456 | __is.flags(__ios_base::dec | __ios_base::skipws); |
1457 | |
1458 | _UIntType __total_size, __successful_size, __total_draws; |
1459 | __is >> __total_size >> __successful_size >> __total_draws; |
1460 | __x.param(typename __gnu_cxx::hypergeometric_distribution<_UIntType>:: |
1461 | param_type(__total_size, __successful_size, __total_draws)); |
1462 | |
1463 | __is.flags(__flags); |
1464 | return __is; |
1465 | } |
1466 | |
1467 | |
1468 | template<typename _RealType> |
1469 | template<typename _UniformRandomNumberGenerator> |
1470 | typename logistic_distribution<_RealType>::result_type |
1471 | logistic_distribution<_RealType>:: |
1472 | operator()(_UniformRandomNumberGenerator& __urng, |
1473 | const param_type& __p) |
1474 | { |
1475 | std::__detail::_Adaptor<_UniformRandomNumberGenerator, result_type> |
1476 | __aurng(__urng); |
1477 | |
1478 | result_type __arg = result_type(1); |
1479 | while (__arg == result_type(1) || __arg == result_type(0)) |
1480 | __arg = __aurng(); |
1481 | return __p.a() |
1482 | + __p.b() * std::log(__arg / (result_type(1) - __arg)); |
1483 | } |
1484 | |
1485 | template<typename _RealType> |
1486 | template<typename _OutputIterator, |
1487 | typename _UniformRandomNumberGenerator> |
1488 | void |
1489 | logistic_distribution<_RealType>:: |
1490 | __generate_impl(_OutputIterator __f, _OutputIterator __t, |
1491 | _UniformRandomNumberGenerator& __urng, |
1492 | const param_type& __p) |
1493 | { |
1494 | __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator, |
1495 | result_type>) |
1496 | |
1497 | std::__detail::_Adaptor<_UniformRandomNumberGenerator, result_type> |
1498 | __aurng(__urng); |
1499 | |
1500 | while (__f != __t) |
1501 | { |
1502 | result_type __arg = result_type(1); |
1503 | while (__arg == result_type(1) || __arg == result_type(0)) |
1504 | __arg = __aurng(); |
1505 | *__f++ = __p.a() |
1506 | + __p.b() * std::log(__arg / (result_type(1) - __arg)); |
1507 | } |
1508 | } |
1509 | |
1510 | template<typename _RealType, typename _CharT, typename _Traits> |
1511 | std::basic_ostream<_CharT, _Traits>& |
1512 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
1513 | const logistic_distribution<_RealType>& __x) |
1514 | { |
1515 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; |
1516 | typedef typename __ostream_type::ios_base __ios_base; |
1517 | |
1518 | const typename __ios_base::fmtflags __flags = __os.flags(); |
1519 | const _CharT __fill = __os.fill(); |
1520 | const std::streamsize __precision = __os.precision(); |
1521 | const _CharT __space = __os.widen(' '); |
1522 | __os.flags(__ios_base::scientific | __ios_base::left); |
1523 | __os.fill(__space); |
1524 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
1525 | |
1526 | __os << __x.a() << __space << __x.b(); |
1527 | |
1528 | __os.flags(__flags); |
1529 | __os.fill(__fill); |
1530 | __os.precision(__precision); |
1531 | return __os; |
1532 | } |
1533 | |
1534 | template<typename _RealType, typename _CharT, typename _Traits> |
1535 | std::basic_istream<_CharT, _Traits>& |
1536 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
1537 | logistic_distribution<_RealType>& __x) |
1538 | { |
1539 | typedef std::basic_istream<_CharT, _Traits> __istream_type; |
1540 | typedef typename __istream_type::ios_base __ios_base; |
1541 | |
1542 | const typename __ios_base::fmtflags __flags = __is.flags(); |
1543 | __is.flags(__ios_base::dec | __ios_base::skipws); |
1544 | |
1545 | _RealType __a, __b; |
1546 | __is >> __a >> __b; |
1547 | __x.param(typename logistic_distribution<_RealType>:: |
1548 | param_type(__a, __b)); |
1549 | |
1550 | __is.flags(__flags); |
1551 | return __is; |
1552 | } |
1553 | |
1554 | |
1555 | namespace { |
1556 | |
1557 | // Helper class for the uniform_on_sphere_distribution generation |
1558 | // function. |
1559 | template<std::size_t _Dimen, typename _RealType> |
1560 | class uniform_on_sphere_helper |
1561 | { |
1562 | typedef typename uniform_on_sphere_distribution<_Dimen, _RealType>:: |
1563 | result_type result_type; |
1564 | |
1565 | public: |
1566 | template<typename _NormalDistribution, |
1567 | typename _UniformRandomNumberGenerator> |
1568 | result_type operator()(_NormalDistribution& __nd, |
1569 | _UniformRandomNumberGenerator& __urng) |
1570 | { |
1571 | result_type __ret; |
1572 | typename result_type::value_type __norm; |
1573 | |
1574 | do |
1575 | { |
1576 | auto __sum = _RealType(0); |
1577 | |
1578 | std::generate(__ret.begin(), __ret.end(), |
1579 | [&__nd, &__urng, &__sum](){ |
1580 | _RealType __t = __nd(__urng); |
1581 | __sum += __t * __t; |
1582 | return __t; }); |
1583 | __norm = std::sqrt(__sum); |
1584 | } |
1585 | while (__norm == _RealType(0) || ! __builtin_isfinite(__norm)); |
1586 | |
1587 | std::transform(__ret.begin(), __ret.end(), __ret.begin(), |
1588 | [__norm](_RealType __val){ return __val / __norm; }); |
1589 | |
1590 | return __ret; |
1591 | } |
1592 | }; |
1593 | |
1594 | |
1595 | template<typename _RealType> |
1596 | class uniform_on_sphere_helper<2, _RealType> |
1597 | { |
1598 | typedef typename uniform_on_sphere_distribution<2, _RealType>:: |
1599 | result_type result_type; |
1600 | |
1601 | public: |
1602 | template<typename _NormalDistribution, |
1603 | typename _UniformRandomNumberGenerator> |
1604 | result_type operator()(_NormalDistribution&, |
1605 | _UniformRandomNumberGenerator& __urng) |
1606 | { |
1607 | result_type __ret; |
1608 | _RealType __sq; |
1609 | std::__detail::_Adaptor<_UniformRandomNumberGenerator, |
1610 | _RealType> __aurng(__urng); |
1611 | |
1612 | do |
1613 | { |
1614 | __ret[0] = _RealType(2) * __aurng() - _RealType(1); |
1615 | __ret[1] = _RealType(2) * __aurng() - _RealType(1); |
1616 | |
1617 | __sq = __ret[0] * __ret[0] + __ret[1] * __ret[1]; |
1618 | } |
1619 | while (__sq == _RealType(0) || __sq > _RealType(1)); |
1620 | |
1621 | #if _GLIBCXX_USE_C99_MATH_TR1 |
1622 | // Yes, we do not just use sqrt(__sq) because hypot() is more |
1623 | // accurate. |
1624 | auto __norm = std::hypot(__ret[0], __ret[1]); |
1625 | #else |
1626 | auto __norm = std::sqrt(__sq); |
1627 | #endif |
1628 | __ret[0] /= __norm; |
1629 | __ret[1] /= __norm; |
1630 | |
1631 | return __ret; |
1632 | } |
1633 | }; |
1634 | |
1635 | } |
1636 | |
1637 | |
1638 | template<std::size_t _Dimen, typename _RealType> |
1639 | template<typename _UniformRandomNumberGenerator> |
1640 | typename uniform_on_sphere_distribution<_Dimen, _RealType>::result_type |
1641 | uniform_on_sphere_distribution<_Dimen, _RealType>:: |
1642 | operator()(_UniformRandomNumberGenerator& __urng, |
1643 | const param_type& __p) |
1644 | { |
1645 | uniform_on_sphere_helper<_Dimen, _RealType> __helper; |
1646 | return __helper(_M_nd, __urng); |
1647 | } |
1648 | |
1649 | template<std::size_t _Dimen, typename _RealType> |
1650 | template<typename _OutputIterator, |
1651 | typename _UniformRandomNumberGenerator> |
1652 | void |
1653 | uniform_on_sphere_distribution<_Dimen, _RealType>:: |
1654 | __generate_impl(_OutputIterator __f, _OutputIterator __t, |
1655 | _UniformRandomNumberGenerator& __urng, |
1656 | const param_type& __param) |
1657 | { |
1658 | __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator, |
1659 | result_type>) |
1660 | |
1661 | while (__f != __t) |
1662 | *__f++ = this->operator()(__urng, __param); |
1663 | } |
1664 | |
1665 | template<std::size_t _Dimen, typename _RealType, typename _CharT, |
1666 | typename _Traits> |
1667 | std::basic_ostream<_CharT, _Traits>& |
1668 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
1669 | const __gnu_cxx::uniform_on_sphere_distribution<_Dimen, |
1670 | _RealType>& __x) |
1671 | { |
1672 | return __os << __x._M_nd; |
1673 | } |
1674 | |
1675 | template<std::size_t _Dimen, typename _RealType, typename _CharT, |
1676 | typename _Traits> |
1677 | std::basic_istream<_CharT, _Traits>& |
1678 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
1679 | __gnu_cxx::uniform_on_sphere_distribution<_Dimen, |
1680 | _RealType>& __x) |
1681 | { |
1682 | return __is >> __x._M_nd; |
1683 | } |
1684 | |
1685 | |
1686 | namespace { |
1687 | |
1688 | // Helper class for the uniform_inside_sphere_distribution generation |
1689 | // function. |
1690 | template<std::size_t _Dimen, bool _SmallDimen, typename _RealType> |
1691 | class uniform_inside_sphere_helper; |
1692 | |
1693 | template<std::size_t _Dimen, typename _RealType> |
1694 | class uniform_inside_sphere_helper<_Dimen, false, _RealType> |
1695 | { |
1696 | using result_type |
1697 | = typename uniform_inside_sphere_distribution<_Dimen, _RealType>:: |
1698 | result_type; |
1699 | |
1700 | public: |
1701 | template<typename _UniformOnSphereDistribution, |
1702 | typename _UniformRandomNumberGenerator> |
1703 | result_type |
1704 | operator()(_UniformOnSphereDistribution& __uosd, |
1705 | _UniformRandomNumberGenerator& __urng, |
1706 | _RealType __radius) |
1707 | { |
1708 | std::__detail::_Adaptor<_UniformRandomNumberGenerator, |
1709 | _RealType> __aurng(__urng); |
1710 | |
1711 | _RealType __pow = 1 / _RealType(_Dimen); |
1712 | _RealType __urt = __radius * std::pow(__aurng(), __pow); |
1713 | result_type __ret = __uosd(__aurng); |
1714 | |
1715 | std::transform(__ret.begin(), __ret.end(), __ret.begin(), |
1716 | [__urt](_RealType __val) |
1717 | { return __val * __urt; }); |
1718 | |
1719 | return __ret; |
1720 | } |
1721 | }; |
1722 | |
1723 | // Helper class for the uniform_inside_sphere_distribution generation |
1724 | // function specialized for small dimensions. |
1725 | template<std::size_t _Dimen, typename _RealType> |
1726 | class uniform_inside_sphere_helper<_Dimen, true, _RealType> |
1727 | { |
1728 | using result_type |
1729 | = typename uniform_inside_sphere_distribution<_Dimen, _RealType>:: |
1730 | result_type; |
1731 | |
1732 | public: |
1733 | template<typename _UniformOnSphereDistribution, |
1734 | typename _UniformRandomNumberGenerator> |
1735 | result_type |
1736 | operator()(_UniformOnSphereDistribution&, |
1737 | _UniformRandomNumberGenerator& __urng, |
1738 | _RealType __radius) |
1739 | { |
1740 | result_type __ret; |
1741 | _RealType __sq; |
1742 | _RealType __radsq = __radius * __radius; |
1743 | std::__detail::_Adaptor<_UniformRandomNumberGenerator, |
1744 | _RealType> __aurng(__urng); |
1745 | |
1746 | do |
1747 | { |
1748 | __sq = _RealType(0); |
1749 | for (int i = 0; i < _Dimen; ++i) |
1750 | { |
1751 | __ret[i] = _RealType(2) * __aurng() - _RealType(1); |
1752 | __sq += __ret[i] * __ret[i]; |
1753 | } |
1754 | } |
1755 | while (__sq > _RealType(1)); |
1756 | |
1757 | for (int i = 0; i < _Dimen; ++i) |
1758 | __ret[i] *= __radius; |
1759 | |
1760 | return __ret; |
1761 | } |
1762 | }; |
1763 | } // namespace |
1764 | |
1765 | // |
1766 | // Experiments have shown that rejection is more efficient than transform |
1767 | // for dimensions less than 8. |
1768 | // |
1769 | template<std::size_t _Dimen, typename _RealType> |
1770 | template<typename _UniformRandomNumberGenerator> |
1771 | typename uniform_inside_sphere_distribution<_Dimen, _RealType>::result_type |
1772 | uniform_inside_sphere_distribution<_Dimen, _RealType>:: |
1773 | operator()(_UniformRandomNumberGenerator& __urng, |
1774 | const param_type& __p) |
1775 | { |
1776 | uniform_inside_sphere_helper<_Dimen, _Dimen < 8, _RealType> __helper; |
1777 | return __helper(_M_uosd, __urng, __p.radius()); |
1778 | } |
1779 | |
1780 | template<std::size_t _Dimen, typename _RealType> |
1781 | template<typename _OutputIterator, |
1782 | typename _UniformRandomNumberGenerator> |
1783 | void |
1784 | uniform_inside_sphere_distribution<_Dimen, _RealType>:: |
1785 | __generate_impl(_OutputIterator __f, _OutputIterator __t, |
1786 | _UniformRandomNumberGenerator& __urng, |
1787 | const param_type& __param) |
1788 | { |
1789 | __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator, |
1790 | result_type>) |
1791 | |
1792 | while (__f != __t) |
1793 | *__f++ = this->operator()(__urng, __param); |
1794 | } |
1795 | |
1796 | template<std::size_t _Dimen, typename _RealType, typename _CharT, |
1797 | typename _Traits> |
1798 | std::basic_ostream<_CharT, _Traits>& |
1799 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
1800 | const __gnu_cxx::uniform_inside_sphere_distribution<_Dimen, |
1801 | _RealType>& __x) |
1802 | { |
1803 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; |
1804 | typedef typename __ostream_type::ios_base __ios_base; |
1805 | |
1806 | const typename __ios_base::fmtflags __flags = __os.flags(); |
1807 | const _CharT __fill = __os.fill(); |
1808 | const std::streamsize __precision = __os.precision(); |
1809 | const _CharT __space = __os.widen(' '); |
1810 | __os.flags(__ios_base::scientific | __ios_base::left); |
1811 | __os.fill(__space); |
1812 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
1813 | |
1814 | __os << __x.radius() << __space << __x._M_uosd; |
1815 | |
1816 | __os.flags(__flags); |
1817 | __os.fill(__fill); |
1818 | __os.precision(__precision); |
1819 | |
1820 | return __os; |
1821 | } |
1822 | |
1823 | template<std::size_t _Dimen, typename _RealType, typename _CharT, |
1824 | typename _Traits> |
1825 | std::basic_istream<_CharT, _Traits>& |
1826 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
1827 | __gnu_cxx::uniform_inside_sphere_distribution<_Dimen, |
1828 | _RealType>& __x) |
1829 | { |
1830 | typedef std::basic_istream<_CharT, _Traits> __istream_type; |
1831 | typedef typename __istream_type::ios_base __ios_base; |
1832 | |
1833 | const typename __ios_base::fmtflags __flags = __is.flags(); |
1834 | __is.flags(__ios_base::dec | __ios_base::skipws); |
1835 | |
1836 | _RealType __radius_val; |
1837 | __is >> __radius_val >> __x._M_uosd; |
1838 | __x.param(typename uniform_inside_sphere_distribution<_Dimen, _RealType>:: |
1839 | param_type(__radius_val)); |
1840 | |
1841 | __is.flags(__flags); |
1842 | |
1843 | return __is; |
1844 | } |
1845 | |
1846 | _GLIBCXX_END_NAMESPACE_VERSION |
1847 | } // namespace __gnu_cxx |
1848 | |
1849 | |
1850 | #endif // _EXT_RANDOM_TCC |
1851 | |