1 | // random number generation -*- C++ -*- |
2 | |
3 | // Copyright (C) 2009-2024 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 | /** |
26 | * @file bits/random.h |
27 | * This is an internal header file, included by other library headers. |
28 | * Do not attempt to use it directly. @headername{random} |
29 | */ |
30 | |
31 | #ifndef _RANDOM_H |
32 | #define _RANDOM_H 1 |
33 | |
34 | #include <vector> |
35 | #include <bits/uniform_int_dist.h> |
36 | |
37 | namespace std _GLIBCXX_VISIBILITY(default) |
38 | { |
39 | _GLIBCXX_BEGIN_NAMESPACE_VERSION |
40 | |
41 | // [26.4] Random number generation |
42 | |
43 | /** |
44 | * @defgroup random Random Number Generation |
45 | * @ingroup numerics |
46 | * |
47 | * A facility for generating random numbers on selected distributions. |
48 | * @{ |
49 | */ |
50 | |
51 | // std::uniform_random_bit_generator is defined in <bits/uniform_int_dist.h> |
52 | |
53 | /** |
54 | * @brief A function template for converting the output of a (integral) |
55 | * uniform random number generator to a floatng point result in the range |
56 | * [0-1). |
57 | */ |
58 | template<typename _RealType, size_t __bits, |
59 | typename _UniformRandomNumberGenerator> |
60 | _RealType |
61 | generate_canonical(_UniformRandomNumberGenerator& __g); |
62 | |
63 | /// @cond undocumented |
64 | // Implementation-space details. |
65 | namespace __detail |
66 | { |
67 | #pragma GCC diagnostic push |
68 | #pragma GCC diagnostic ignored "-Wc++17-extensions" |
69 | |
70 | template<typename _UIntType, size_t __w, |
71 | bool = __w < static_cast<size_t> |
72 | (std::numeric_limits<_UIntType>::digits)> |
73 | struct _Shift |
74 | { static constexpr _UIntType __value = 0; }; |
75 | |
76 | template<typename _UIntType, size_t __w> |
77 | struct _Shift<_UIntType, __w, true> |
78 | { static constexpr _UIntType __value = _UIntType(1) << __w; }; |
79 | |
80 | template<int __s, |
81 | int __which = ((__s <= __CHAR_BIT__ * sizeof (int)) |
82 | + (__s <= __CHAR_BIT__ * sizeof (long)) |
83 | + (__s <= __CHAR_BIT__ * sizeof (long long)) |
84 | /* assume long long no bigger than __int128 */ |
85 | + (__s <= 128))> |
86 | struct _Select_uint_least_t |
87 | { |
88 | static_assert(__which < 0, /* needs to be dependent */ |
89 | "sorry, would be too much trouble for a slow result" ); |
90 | }; |
91 | |
92 | template<int __s> |
93 | struct _Select_uint_least_t<__s, 4> |
94 | { using type = unsigned int; }; |
95 | |
96 | template<int __s> |
97 | struct _Select_uint_least_t<__s, 3> |
98 | { using type = unsigned long; }; |
99 | |
100 | template<int __s> |
101 | struct _Select_uint_least_t<__s, 2> |
102 | { using type = unsigned long long; }; |
103 | |
104 | #if __SIZEOF_INT128__ > __SIZEOF_LONG_LONG__ |
105 | template<int __s> |
106 | struct _Select_uint_least_t<__s, 1> |
107 | { __extension__ using type = unsigned __int128; }; |
108 | #elif __has_builtin(__builtin_add_overflow) \ |
109 | && __has_builtin(__builtin_sub_overflow) \ |
110 | && defined __UINT64_TYPE__ |
111 | template<int __s> |
112 | struct _Select_uint_least_t<__s, 1> |
113 | { |
114 | // This is NOT a general-purpose 128-bit integer type. |
115 | // It only supports (type(a) * x + c) % m as needed by __mod. |
116 | struct type |
117 | { |
118 | explicit |
119 | type(uint64_t __a) noexcept : _M_lo(__a), _M_hi(0) { } |
120 | |
121 | // pre: __l._M_hi == 0 |
122 | friend type |
123 | operator*(type __l, uint64_t __x) noexcept |
124 | { |
125 | // Split 64-bit values __l._M_lo and __x into high and low 32-bit |
126 | // limbs and multiply those individually. |
127 | // l * x = (l0 + l1) * (x0 + x1) = l0x0 + l0x1 + l1x0 + l1x1 |
128 | |
129 | constexpr uint64_t __mask = 0xffffffff; |
130 | uint64_t __ll[2] = { __l._M_lo >> 32, __l._M_lo & __mask }; |
131 | uint64_t __xx[2] = { __x >> 32, __x & __mask }; |
132 | uint64_t __l0x0 = __ll[0] * __xx[0]; |
133 | uint64_t __l0x1 = __ll[0] * __xx[1]; |
134 | uint64_t __l1x0 = __ll[1] * __xx[0]; |
135 | uint64_t __l1x1 = __ll[1] * __xx[1]; |
136 | // These bits are the low half of __l._M_hi |
137 | // and the high half of __l._M_lo. |
138 | uint64_t __mid |
139 | = (__l0x1 & __mask) + (__l1x0 & __mask) + (__l1x1 >> 32); |
140 | __l._M_hi = __l0x0 + (__l0x1 >> 32) + (__l1x0 >> 32) + (__mid >> 32); |
141 | __l._M_lo = (__mid << 32) + (__l1x1 & __mask); |
142 | return __l; |
143 | } |
144 | |
145 | friend type |
146 | operator+(type __l, uint64_t __c) noexcept |
147 | { |
148 | __l._M_hi += __builtin_add_overflow(__l._M_lo, __c, &__l._M_lo); |
149 | return __l; |
150 | } |
151 | |
152 | friend type |
153 | operator%(type __l, uint64_t __m) noexcept |
154 | { |
155 | if (__builtin_expect(__l._M_hi == 0, 0)) |
156 | { |
157 | __l._M_lo %= __m; |
158 | return __l; |
159 | } |
160 | |
161 | int __shift = __builtin_clzll(__m) + 64 |
162 | - __builtin_clzll(__l._M_hi); |
163 | type __x(0); |
164 | if (__shift >= 64) |
165 | { |
166 | __x._M_hi = __m << (__shift - 64); |
167 | __x._M_lo = 0; |
168 | } |
169 | else |
170 | { |
171 | __x._M_hi = __m >> (64 - __shift); |
172 | __x._M_lo = __m << __shift; |
173 | } |
174 | |
175 | while (__l._M_hi != 0 || __l._M_lo >= __m) |
176 | { |
177 | if (__x <= __l) |
178 | { |
179 | __l._M_hi -= __x._M_hi; |
180 | __l._M_hi -= __builtin_sub_overflow(__l._M_lo, __x._M_lo, |
181 | &__l._M_lo); |
182 | } |
183 | __x._M_lo = (__x._M_lo >> 1) | (__x._M_hi << 63); |
184 | __x._M_hi >>= 1; |
185 | } |
186 | return __l; |
187 | } |
188 | |
189 | // pre: __l._M_hi == 0 |
190 | explicit operator uint64_t() const noexcept |
191 | { return _M_lo; } |
192 | |
193 | friend bool operator<(const type& __l, const type& __r) noexcept |
194 | { |
195 | if (__l._M_hi < __r._M_hi) |
196 | return true; |
197 | else if (__l._M_hi == __r._M_hi) |
198 | return __l._M_lo < __r._M_lo; |
199 | else |
200 | return false; |
201 | } |
202 | |
203 | friend bool operator<=(const type& __l, const type& __r) noexcept |
204 | { return !(__r < __l); } |
205 | |
206 | uint64_t _M_lo; |
207 | uint64_t _M_hi; |
208 | }; |
209 | }; |
210 | #endif |
211 | |
212 | // Assume a != 0, a < m, c < m, x < m. |
213 | template<typename _Tp, _Tp __m, _Tp __a, _Tp __c, |
214 | bool __big_enough = (!(__m & (__m - 1)) |
215 | || (_Tp(-1) - __c) / __a >= __m - 1), |
216 | bool __schrage_ok = __m % __a < __m / __a> |
217 | struct _Mod |
218 | { |
219 | static _Tp |
220 | __calc(_Tp __x) |
221 | { |
222 | using _Tp2 |
223 | = typename _Select_uint_least_t<std::__lg(__a) |
224 | + std::__lg(__m) + 2>::type; |
225 | return static_cast<_Tp>((_Tp2(__a) * __x + __c) % __m); |
226 | } |
227 | }; |
228 | |
229 | // Schrage. |
230 | template<typename _Tp, _Tp __m, _Tp __a, _Tp __c> |
231 | struct _Mod<_Tp, __m, __a, __c, false, true> |
232 | { |
233 | static _Tp |
234 | __calc(_Tp __x); |
235 | }; |
236 | |
237 | // Special cases: |
238 | // - for m == 2^n or m == 0, unsigned integer overflow is safe. |
239 | // - a * (m - 1) + c fits in _Tp, there is no overflow. |
240 | template<typename _Tp, _Tp __m, _Tp __a, _Tp __c, bool __s> |
241 | struct _Mod<_Tp, __m, __a, __c, true, __s> |
242 | { |
243 | static _Tp |
244 | __calc(_Tp __x) |
245 | { |
246 | _Tp __res = __a * __x + __c; |
247 | if (__m) |
248 | __res %= __m; |
249 | return __res; |
250 | } |
251 | }; |
252 | |
253 | template<typename _Tp, _Tp __m, _Tp __a = 1, _Tp __c = 0> |
254 | inline _Tp |
255 | __mod(_Tp __x) |
256 | { |
257 | if constexpr (__a == 0) |
258 | return __c; |
259 | else // N.B. _Mod must not be instantiated with a == 0 |
260 | return _Mod<_Tp, __m, __a, __c>::__calc(__x); |
261 | } |
262 | |
263 | /* |
264 | * An adaptor class for converting the output of any Generator into |
265 | * the input for a specific Distribution. |
266 | */ |
267 | template<typename _Engine, typename _DInputType> |
268 | struct _Adaptor |
269 | { |
270 | static_assert(std::is_floating_point<_DInputType>::value, |
271 | "template argument must be a floating point type" ); |
272 | |
273 | public: |
274 | _Adaptor(_Engine& __g) |
275 | : _M_g(__g) { } |
276 | |
277 | _DInputType |
278 | min() const |
279 | { return _DInputType(0); } |
280 | |
281 | _DInputType |
282 | max() const |
283 | { return _DInputType(1); } |
284 | |
285 | /* |
286 | * Converts a value generated by the adapted random number generator |
287 | * into a value in the input domain for the dependent random number |
288 | * distribution. |
289 | */ |
290 | _DInputType |
291 | operator()() |
292 | { |
293 | return std::generate_canonical<_DInputType, |
294 | std::numeric_limits<_DInputType>::digits, |
295 | _Engine>(_M_g); |
296 | } |
297 | |
298 | private: |
299 | _Engine& _M_g; |
300 | }; |
301 | |
302 | // Detect whether a template argument _Sseq is a valid seed sequence for |
303 | // a random number engine _Engine with result type _Res. |
304 | // Used to constrain _Engine::_Engine(_Sseq&) and _Engine::seed(_Sseq&) |
305 | // as required by [rand.eng.general]. |
306 | |
307 | template<typename _Sseq> |
308 | using __seed_seq_generate_t = decltype( |
309 | std::declval<_Sseq&>().generate(std::declval<uint_least32_t*>(), |
310 | std::declval<uint_least32_t*>())); |
311 | |
312 | template<typename _Sseq, typename _Engine, typename _Res, |
313 | typename _GenerateCheck = __seed_seq_generate_t<_Sseq>> |
314 | using _If_seed_seq_for = _Require< |
315 | __not_<is_same<__remove_cvref_t<_Sseq>, _Engine>>, |
316 | is_unsigned<typename _Sseq::result_type>, |
317 | __not_<is_convertible<_Sseq, _Res>> |
318 | >; |
319 | |
320 | #pragma GCC diagnostic pop |
321 | } // namespace __detail |
322 | /// @endcond |
323 | |
324 | /** |
325 | * @addtogroup random_generators Random Number Generators |
326 | * @ingroup random |
327 | * |
328 | * These classes define objects which provide random or pseudorandom |
329 | * numbers, either from a discrete or a continuous interval. The |
330 | * random number generator supplied as a part of this library are |
331 | * all uniform random number generators which provide a sequence of |
332 | * random number uniformly distributed over their range. |
333 | * |
334 | * A number generator is a function object with an operator() that |
335 | * takes zero arguments and returns a number. |
336 | * |
337 | * A compliant random number generator must satisfy the following |
338 | * requirements. <table border=1 cellpadding=10 cellspacing=0> |
339 | * <caption align=top>Random Number Generator Requirements</caption> |
340 | * <tr><td>To be documented.</td></tr> </table> |
341 | * |
342 | * @{ |
343 | */ |
344 | |
345 | /** |
346 | * @brief A model of a linear congruential random number generator. |
347 | * |
348 | * A random number generator that produces pseudorandom numbers via |
349 | * linear function: |
350 | * @f[ |
351 | * x_{i+1}\leftarrow(ax_{i} + c) \bmod m |
352 | * @f] |
353 | * |
354 | * The template parameter @p _UIntType must be an unsigned integral type |
355 | * large enough to store values up to (__m-1). If the template parameter |
356 | * @p __m is 0, the modulus @p __m used is |
357 | * std::numeric_limits<_UIntType>::max() plus 1. Otherwise, the template |
358 | * parameters @p __a and @p __c must be less than @p __m. |
359 | * |
360 | * The size of the state is @f$1@f$. |
361 | * |
362 | * @headerfile random |
363 | * @since C++11 |
364 | */ |
365 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m> |
366 | class linear_congruential_engine |
367 | { |
368 | static_assert(std::is_unsigned<_UIntType>::value, |
369 | "result_type must be an unsigned integral type" ); |
370 | static_assert(__m == 0u || (__a < __m && __c < __m), |
371 | "template argument substituting __m out of bounds" ); |
372 | |
373 | template<typename _Sseq> |
374 | using _If_seed_seq |
375 | = __detail::_If_seed_seq_for<_Sseq, linear_congruential_engine, |
376 | _UIntType>; |
377 | |
378 | public: |
379 | /** The type of the generated random value. */ |
380 | typedef _UIntType result_type; |
381 | |
382 | /** The multiplier. */ |
383 | static constexpr result_type multiplier = __a; |
384 | /** An increment. */ |
385 | static constexpr result_type increment = __c; |
386 | /** The modulus. */ |
387 | static constexpr result_type modulus = __m; |
388 | static constexpr result_type default_seed = 1u; |
389 | |
390 | /** |
391 | * @brief Constructs a %linear_congruential_engine random number |
392 | * generator engine with seed 1. |
393 | */ |
394 | linear_congruential_engine() : linear_congruential_engine(default_seed) |
395 | { } |
396 | |
397 | /** |
398 | * @brief Constructs a %linear_congruential_engine random number |
399 | * generator engine with seed @p __s. The default seed value |
400 | * is 1. |
401 | * |
402 | * @param __s The initial seed value. |
403 | */ |
404 | explicit |
405 | linear_congruential_engine(result_type __s) |
406 | { seed(__s); } |
407 | |
408 | /** |
409 | * @brief Constructs a %linear_congruential_engine random number |
410 | * generator engine seeded from the seed sequence @p __q. |
411 | * |
412 | * @param __q the seed sequence. |
413 | */ |
414 | template<typename _Sseq, typename = _If_seed_seq<_Sseq>> |
415 | explicit |
416 | linear_congruential_engine(_Sseq& __q) |
417 | { seed(__q); } |
418 | |
419 | /** |
420 | * @brief Reseeds the %linear_congruential_engine random number generator |
421 | * engine sequence to the seed @p __s. |
422 | * |
423 | * @param __s The new seed. |
424 | */ |
425 | void |
426 | seed(result_type __s = default_seed); |
427 | |
428 | /** |
429 | * @brief Reseeds the %linear_congruential_engine random number generator |
430 | * engine |
431 | * sequence using values from the seed sequence @p __q. |
432 | * |
433 | * @param __q the seed sequence. |
434 | */ |
435 | template<typename _Sseq> |
436 | _If_seed_seq<_Sseq> |
437 | seed(_Sseq& __q); |
438 | |
439 | /** |
440 | * @brief Gets the smallest possible value in the output range. |
441 | * |
442 | * The minimum depends on the @p __c parameter: if it is zero, the |
443 | * minimum generated must be > 0, otherwise 0 is allowed. |
444 | */ |
445 | static constexpr result_type |
446 | min() |
447 | { return __c == 0u ? 1u : 0u; } |
448 | |
449 | /** |
450 | * @brief Gets the largest possible value in the output range. |
451 | */ |
452 | static constexpr result_type |
453 | max() |
454 | { return __m - 1u; } |
455 | |
456 | /** |
457 | * @brief Discard a sequence of random numbers. |
458 | */ |
459 | void |
460 | discard(unsigned long long __z) |
461 | { |
462 | for (; __z != 0ULL; --__z) |
463 | (*this)(); |
464 | } |
465 | |
466 | /** |
467 | * @brief Gets the next random number in the sequence. |
468 | */ |
469 | result_type |
470 | operator()() |
471 | { |
472 | _M_x = __detail::__mod<_UIntType, __m, __a, __c>(_M_x); |
473 | return _M_x; |
474 | } |
475 | |
476 | /** |
477 | * @brief Compares two linear congruential random number generator |
478 | * objects of the same type for equality. |
479 | * |
480 | * @param __lhs A linear congruential random number generator object. |
481 | * @param __rhs Another linear congruential random number generator |
482 | * object. |
483 | * |
484 | * @returns true if the infinite sequences of generated values |
485 | * would be equal, false otherwise. |
486 | */ |
487 | friend bool |
488 | operator==(const linear_congruential_engine& __lhs, |
489 | const linear_congruential_engine& __rhs) |
490 | { return __lhs._M_x == __rhs._M_x; } |
491 | |
492 | /** |
493 | * @brief Writes the textual representation of the state x(i) of x to |
494 | * @p __os. |
495 | * |
496 | * @param __os The output stream. |
497 | * @param __lcr A % linear_congruential_engine random number generator. |
498 | * @returns __os. |
499 | */ |
500 | template<typename _UIntType1, _UIntType1 __a1, _UIntType1 __c1, |
501 | _UIntType1 __m1, typename _CharT, typename _Traits> |
502 | friend std::basic_ostream<_CharT, _Traits>& |
503 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
504 | const std::linear_congruential_engine<_UIntType1, |
505 | __a1, __c1, __m1>& __lcr); |
506 | |
507 | /** |
508 | * @brief Sets the state of the engine by reading its textual |
509 | * representation from @p __is. |
510 | * |
511 | * The textual representation must have been previously written using |
512 | * an output stream whose imbued locale and whose type's template |
513 | * specialization arguments _CharT and _Traits were the same as those |
514 | * of @p __is. |
515 | * |
516 | * @param __is The input stream. |
517 | * @param __lcr A % linear_congruential_engine random number generator. |
518 | * @returns __is. |
519 | */ |
520 | template<typename _UIntType1, _UIntType1 __a1, _UIntType1 __c1, |
521 | _UIntType1 __m1, typename _CharT, typename _Traits> |
522 | friend std::basic_istream<_CharT, _Traits>& |
523 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
524 | std::linear_congruential_engine<_UIntType1, __a1, |
525 | __c1, __m1>& __lcr); |
526 | |
527 | private: |
528 | _UIntType _M_x; |
529 | }; |
530 | |
531 | #if __cpp_impl_three_way_comparison < 201907L |
532 | /** |
533 | * @brief Compares two linear congruential random number generator |
534 | * objects of the same type for inequality. |
535 | * |
536 | * @param __lhs A linear congruential random number generator object. |
537 | * @param __rhs Another linear congruential random number generator |
538 | * object. |
539 | * |
540 | * @returns true if the infinite sequences of generated values |
541 | * would be different, false otherwise. |
542 | */ |
543 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m> |
544 | inline bool |
545 | operator!=(const std::linear_congruential_engine<_UIntType, __a, |
546 | __c, __m>& __lhs, |
547 | const std::linear_congruential_engine<_UIntType, __a, |
548 | __c, __m>& __rhs) |
549 | { return !(__lhs == __rhs); } |
550 | #endif |
551 | |
552 | /** |
553 | * A generalized feedback shift register discrete random number generator. |
554 | * |
555 | * This algorithm avoids multiplication and division and is designed to be |
556 | * friendly to a pipelined architecture. If the parameters are chosen |
557 | * correctly, this generator will produce numbers with a very long period and |
558 | * fairly good apparent entropy, although still not cryptographically strong. |
559 | * |
560 | * The best way to use this generator is with the predefined mt19937 class. |
561 | * |
562 | * This algorithm was originally invented by Makoto Matsumoto and |
563 | * Takuji Nishimura. |
564 | * |
565 | * @tparam __w Word size, the number of bits in each element of |
566 | * the state vector. |
567 | * @tparam __n The degree of recursion. |
568 | * @tparam __m The period parameter. |
569 | * @tparam __r The separation point bit index. |
570 | * @tparam __a The last row of the twist matrix. |
571 | * @tparam __u The first right-shift tempering matrix parameter. |
572 | * @tparam __d The first right-shift tempering matrix mask. |
573 | * @tparam __s The first left-shift tempering matrix parameter. |
574 | * @tparam __b The first left-shift tempering matrix mask. |
575 | * @tparam __t The second left-shift tempering matrix parameter. |
576 | * @tparam __c The second left-shift tempering matrix mask. |
577 | * @tparam __l The second right-shift tempering matrix parameter. |
578 | * @tparam __f Initialization multiplier. |
579 | * |
580 | * @headerfile random |
581 | * @since C++11 |
582 | */ |
583 | template<typename _UIntType, size_t __w, |
584 | size_t __n, size_t __m, size_t __r, |
585 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, |
586 | _UIntType __b, size_t __t, |
587 | _UIntType __c, size_t __l, _UIntType __f> |
588 | class mersenne_twister_engine |
589 | { |
590 | static_assert(std::is_unsigned<_UIntType>::value, |
591 | "result_type must be an unsigned integral type" ); |
592 | static_assert(1u <= __m && __m <= __n, |
593 | "template argument substituting __m out of bounds" ); |
594 | static_assert(__r <= __w, "template argument substituting " |
595 | "__r out of bound" ); |
596 | static_assert(__u <= __w, "template argument substituting " |
597 | "__u out of bound" ); |
598 | static_assert(__s <= __w, "template argument substituting " |
599 | "__s out of bound" ); |
600 | static_assert(__t <= __w, "template argument substituting " |
601 | "__t out of bound" ); |
602 | static_assert(__l <= __w, "template argument substituting " |
603 | "__l out of bound" ); |
604 | static_assert(__w <= std::numeric_limits<_UIntType>::digits, |
605 | "template argument substituting __w out of bound" ); |
606 | static_assert(__a <= (__detail::_Shift<_UIntType, __w>::__value - 1), |
607 | "template argument substituting __a out of bound" ); |
608 | static_assert(__b <= (__detail::_Shift<_UIntType, __w>::__value - 1), |
609 | "template argument substituting __b out of bound" ); |
610 | static_assert(__c <= (__detail::_Shift<_UIntType, __w>::__value - 1), |
611 | "template argument substituting __c out of bound" ); |
612 | static_assert(__d <= (__detail::_Shift<_UIntType, __w>::__value - 1), |
613 | "template argument substituting __d out of bound" ); |
614 | static_assert(__f <= (__detail::_Shift<_UIntType, __w>::__value - 1), |
615 | "template argument substituting __f out of bound" ); |
616 | |
617 | template<typename _Sseq> |
618 | using _If_seed_seq |
619 | = __detail::_If_seed_seq_for<_Sseq, mersenne_twister_engine, |
620 | _UIntType>; |
621 | |
622 | public: |
623 | /** The type of the generated random value. */ |
624 | typedef _UIntType result_type; |
625 | |
626 | // parameter values |
627 | static constexpr size_t word_size = __w; |
628 | static constexpr size_t state_size = __n; |
629 | static constexpr size_t shift_size = __m; |
630 | static constexpr size_t mask_bits = __r; |
631 | static constexpr result_type xor_mask = __a; |
632 | static constexpr size_t tempering_u = __u; |
633 | static constexpr result_type tempering_d = __d; |
634 | static constexpr size_t tempering_s = __s; |
635 | static constexpr result_type tempering_b = __b; |
636 | static constexpr size_t tempering_t = __t; |
637 | static constexpr result_type tempering_c = __c; |
638 | static constexpr size_t tempering_l = __l; |
639 | static constexpr result_type initialization_multiplier = __f; |
640 | static constexpr result_type default_seed = 5489u; |
641 | |
642 | // constructors and member functions |
643 | |
644 | mersenne_twister_engine() : mersenne_twister_engine(default_seed) { } |
645 | |
646 | explicit |
647 | mersenne_twister_engine(result_type __sd) |
648 | { seed(__sd); } |
649 | |
650 | /** |
651 | * @brief Constructs a %mersenne_twister_engine random number generator |
652 | * engine seeded from the seed sequence @p __q. |
653 | * |
654 | * @param __q the seed sequence. |
655 | */ |
656 | template<typename _Sseq, typename = _If_seed_seq<_Sseq>> |
657 | explicit |
658 | mersenne_twister_engine(_Sseq& __q) |
659 | { seed(__q); } |
660 | |
661 | void |
662 | seed(result_type __sd = default_seed); |
663 | |
664 | template<typename _Sseq> |
665 | _If_seed_seq<_Sseq> |
666 | seed(_Sseq& __q); |
667 | |
668 | /** |
669 | * @brief Gets the smallest possible value in the output range. |
670 | */ |
671 | static constexpr result_type |
672 | min() |
673 | { return 0; } |
674 | |
675 | /** |
676 | * @brief Gets the largest possible value in the output range. |
677 | */ |
678 | static constexpr result_type |
679 | max() |
680 | { return __detail::_Shift<_UIntType, __w>::__value - 1; } |
681 | |
682 | /** |
683 | * @brief Discard a sequence of random numbers. |
684 | */ |
685 | void |
686 | discard(unsigned long long __z); |
687 | |
688 | result_type |
689 | operator()(); |
690 | |
691 | /** |
692 | * @brief Compares two % mersenne_twister_engine random number generator |
693 | * objects of the same type for equality. |
694 | * |
695 | * @param __lhs A % mersenne_twister_engine random number generator |
696 | * object. |
697 | * @param __rhs Another % mersenne_twister_engine random number |
698 | * generator object. |
699 | * |
700 | * @returns true if the infinite sequences of generated values |
701 | * would be equal, false otherwise. |
702 | */ |
703 | friend bool |
704 | operator==(const mersenne_twister_engine& __lhs, |
705 | const mersenne_twister_engine& __rhs) |
706 | { return (std::equal(__lhs._M_x, __lhs._M_x + state_size, __rhs._M_x) |
707 | && __lhs._M_p == __rhs._M_p); } |
708 | |
709 | /** |
710 | * @brief Inserts the current state of a % mersenne_twister_engine |
711 | * random number generator engine @p __x into the output stream |
712 | * @p __os. |
713 | * |
714 | * @param __os An output stream. |
715 | * @param __x A % mersenne_twister_engine random number generator |
716 | * engine. |
717 | * |
718 | * @returns The output stream with the state of @p __x inserted or in |
719 | * an error state. |
720 | */ |
721 | template<typename _UIntType1, |
722 | size_t __w1, size_t __n1, |
723 | size_t __m1, size_t __r1, |
724 | _UIntType1 __a1, size_t __u1, |
725 | _UIntType1 __d1, size_t __s1, |
726 | _UIntType1 __b1, size_t __t1, |
727 | _UIntType1 __c1, size_t __l1, _UIntType1 __f1, |
728 | typename _CharT, typename _Traits> |
729 | friend std::basic_ostream<_CharT, _Traits>& |
730 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
731 | const std::mersenne_twister_engine<_UIntType1, __w1, __n1, |
732 | __m1, __r1, __a1, __u1, __d1, __s1, __b1, __t1, __c1, |
733 | __l1, __f1>& __x); |
734 | |
735 | /** |
736 | * @brief Extracts the current state of a % mersenne_twister_engine |
737 | * random number generator engine @p __x from the input stream |
738 | * @p __is. |
739 | * |
740 | * @param __is An input stream. |
741 | * @param __x A % mersenne_twister_engine random number generator |
742 | * engine. |
743 | * |
744 | * @returns The input stream with the state of @p __x extracted or in |
745 | * an error state. |
746 | */ |
747 | template<typename _UIntType1, |
748 | size_t __w1, size_t __n1, |
749 | size_t __m1, size_t __r1, |
750 | _UIntType1 __a1, size_t __u1, |
751 | _UIntType1 __d1, size_t __s1, |
752 | _UIntType1 __b1, size_t __t1, |
753 | _UIntType1 __c1, size_t __l1, _UIntType1 __f1, |
754 | typename _CharT, typename _Traits> |
755 | friend std::basic_istream<_CharT, _Traits>& |
756 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
757 | std::mersenne_twister_engine<_UIntType1, __w1, __n1, __m1, |
758 | __r1, __a1, __u1, __d1, __s1, __b1, __t1, __c1, |
759 | __l1, __f1>& __x); |
760 | |
761 | private: |
762 | void _M_gen_rand(); |
763 | |
764 | _UIntType _M_x[state_size]; |
765 | size_t _M_p; |
766 | }; |
767 | |
768 | #if __cpp_impl_three_way_comparison < 201907L |
769 | /** |
770 | * @brief Compares two % mersenne_twister_engine random number generator |
771 | * objects of the same type for inequality. |
772 | * |
773 | * @param __lhs A % mersenne_twister_engine random number generator |
774 | * object. |
775 | * @param __rhs Another % mersenne_twister_engine random number |
776 | * generator object. |
777 | * |
778 | * @returns true if the infinite sequences of generated values |
779 | * would be different, false otherwise. |
780 | */ |
781 | template<typename _UIntType, size_t __w, |
782 | size_t __n, size_t __m, size_t __r, |
783 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, |
784 | _UIntType __b, size_t __t, |
785 | _UIntType __c, size_t __l, _UIntType __f> |
786 | inline bool |
787 | operator!=(const std::mersenne_twister_engine<_UIntType, __w, __n, __m, |
788 | __r, __a, __u, __d, __s, __b, __t, __c, __l, __f>& __lhs, |
789 | const std::mersenne_twister_engine<_UIntType, __w, __n, __m, |
790 | __r, __a, __u, __d, __s, __b, __t, __c, __l, __f>& __rhs) |
791 | { return !(__lhs == __rhs); } |
792 | #endif |
793 | |
794 | /** |
795 | * @brief The Marsaglia-Zaman generator. |
796 | * |
797 | * This is a model of a Generalized Fibonacci discrete random number |
798 | * generator, sometimes referred to as the SWC generator. |
799 | * |
800 | * A discrete random number generator that produces pseudorandom |
801 | * numbers using: |
802 | * @f[ |
803 | * x_{i}\leftarrow(x_{i - s} - x_{i - r} - carry_{i-1}) \bmod m |
804 | * @f] |
805 | * |
806 | * The size of the state is @f$r@f$ |
807 | * and the maximum period of the generator is @f$(m^r - m^s - 1)@f$. |
808 | * |
809 | * @headerfile random |
810 | * @since C++11 |
811 | */ |
812 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> |
813 | class subtract_with_carry_engine |
814 | { |
815 | static_assert(std::is_unsigned<_UIntType>::value, |
816 | "result_type must be an unsigned integral type" ); |
817 | static_assert(0u < __s && __s < __r, |
818 | "0 < s < r" ); |
819 | static_assert(0u < __w && __w <= std::numeric_limits<_UIntType>::digits, |
820 | "template argument substituting __w out of bounds" ); |
821 | |
822 | template<typename _Sseq> |
823 | using _If_seed_seq |
824 | = __detail::_If_seed_seq_for<_Sseq, subtract_with_carry_engine, |
825 | _UIntType>; |
826 | |
827 | public: |
828 | /** The type of the generated random value. */ |
829 | typedef _UIntType result_type; |
830 | |
831 | // parameter values |
832 | static constexpr size_t word_size = __w; |
833 | static constexpr size_t short_lag = __s; |
834 | static constexpr size_t long_lag = __r; |
835 | static constexpr uint_least32_t default_seed = 19780503u; |
836 | |
837 | subtract_with_carry_engine() : subtract_with_carry_engine(0u) |
838 | { } |
839 | |
840 | /** |
841 | * @brief Constructs an explicitly seeded %subtract_with_carry_engine |
842 | * random number generator. |
843 | */ |
844 | explicit |
845 | subtract_with_carry_engine(result_type __sd) |
846 | { seed(__sd); } |
847 | |
848 | /** |
849 | * @brief Constructs a %subtract_with_carry_engine random number engine |
850 | * seeded from the seed sequence @p __q. |
851 | * |
852 | * @param __q the seed sequence. |
853 | */ |
854 | template<typename _Sseq, typename = _If_seed_seq<_Sseq>> |
855 | explicit |
856 | subtract_with_carry_engine(_Sseq& __q) |
857 | { seed(__q); } |
858 | |
859 | /** |
860 | * @brief Seeds the initial state @f$x_0@f$ of the random number |
861 | * generator. |
862 | * |
863 | * N1688[4.19] modifies this as follows. If @p __value == 0, |
864 | * sets value to 19780503. In any case, with a linear |
865 | * congruential generator lcg(i) having parameters @f$ m_{lcg} = |
866 | * 2147483563, a_{lcg} = 40014, c_{lcg} = 0, and lcg(0) = value |
867 | * @f$, sets @f$ x_{-r} \dots x_{-1} @f$ to @f$ lcg(1) \bmod m |
868 | * \dots lcg(r) \bmod m @f$ respectively. If @f$ x_{-1} = 0 @f$ |
869 | * set carry to 1, otherwise sets carry to 0. |
870 | */ |
871 | void |
872 | seed(result_type __sd = 0u); |
873 | |
874 | /** |
875 | * @brief Seeds the initial state @f$x_0@f$ of the |
876 | * % subtract_with_carry_engine random number generator. |
877 | */ |
878 | template<typename _Sseq> |
879 | _If_seed_seq<_Sseq> |
880 | seed(_Sseq& __q); |
881 | |
882 | /** |
883 | * @brief Gets the inclusive minimum value of the range of random |
884 | * integers returned by this generator. |
885 | */ |
886 | static constexpr result_type |
887 | min() |
888 | { return 0; } |
889 | |
890 | /** |
891 | * @brief Gets the inclusive maximum value of the range of random |
892 | * integers returned by this generator. |
893 | */ |
894 | static constexpr result_type |
895 | max() |
896 | { return __detail::_Shift<_UIntType, __w>::__value - 1; } |
897 | |
898 | /** |
899 | * @brief Discard a sequence of random numbers. |
900 | */ |
901 | void |
902 | discard(unsigned long long __z) |
903 | { |
904 | for (; __z != 0ULL; --__z) |
905 | (*this)(); |
906 | } |
907 | |
908 | /** |
909 | * @brief Gets the next random number in the sequence. |
910 | */ |
911 | result_type |
912 | operator()(); |
913 | |
914 | /** |
915 | * @brief Compares two % subtract_with_carry_engine random number |
916 | * generator objects of the same type for equality. |
917 | * |
918 | * @param __lhs A % subtract_with_carry_engine random number generator |
919 | * object. |
920 | * @param __rhs Another % subtract_with_carry_engine random number |
921 | * generator object. |
922 | * |
923 | * @returns true if the infinite sequences of generated values |
924 | * would be equal, false otherwise. |
925 | */ |
926 | friend bool |
927 | operator==(const subtract_with_carry_engine& __lhs, |
928 | const subtract_with_carry_engine& __rhs) |
929 | { return (std::equal(__lhs._M_x, __lhs._M_x + long_lag, __rhs._M_x) |
930 | && __lhs._M_carry == __rhs._M_carry |
931 | && __lhs._M_p == __rhs._M_p); } |
932 | |
933 | /** |
934 | * @brief Inserts the current state of a % subtract_with_carry_engine |
935 | * random number generator engine @p __x into the output stream |
936 | * @p __os. |
937 | * |
938 | * @param __os An output stream. |
939 | * @param __x A % subtract_with_carry_engine random number generator |
940 | * engine. |
941 | * |
942 | * @returns The output stream with the state of @p __x inserted or in |
943 | * an error state. |
944 | */ |
945 | template<typename _UIntType1, size_t __w1, size_t __s1, size_t __r1, |
946 | typename _CharT, typename _Traits> |
947 | friend std::basic_ostream<_CharT, _Traits>& |
948 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
949 | const std::subtract_with_carry_engine<_UIntType1, __w1, |
950 | __s1, __r1>& __x); |
951 | |
952 | /** |
953 | * @brief Extracts the current state of a % subtract_with_carry_engine |
954 | * random number generator engine @p __x from the input stream |
955 | * @p __is. |
956 | * |
957 | * @param __is An input stream. |
958 | * @param __x A % subtract_with_carry_engine random number generator |
959 | * engine. |
960 | * |
961 | * @returns The input stream with the state of @p __x extracted or in |
962 | * an error state. |
963 | */ |
964 | template<typename _UIntType1, size_t __w1, size_t __s1, size_t __r1, |
965 | typename _CharT, typename _Traits> |
966 | friend std::basic_istream<_CharT, _Traits>& |
967 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
968 | std::subtract_with_carry_engine<_UIntType1, __w1, |
969 | __s1, __r1>& __x); |
970 | |
971 | private: |
972 | /// The state of the generator. This is a ring buffer. |
973 | _UIntType _M_x[long_lag]; |
974 | _UIntType _M_carry; ///< The carry |
975 | size_t _M_p; ///< Current index of x(i - r). |
976 | }; |
977 | |
978 | #if __cpp_impl_three_way_comparison < 201907L |
979 | /** |
980 | * @brief Compares two % subtract_with_carry_engine random number |
981 | * generator objects of the same type for inequality. |
982 | * |
983 | * @param __lhs A % subtract_with_carry_engine random number generator |
984 | * object. |
985 | * @param __rhs Another % subtract_with_carry_engine random number |
986 | * generator object. |
987 | * |
988 | * @returns true if the infinite sequences of generated values |
989 | * would be different, false otherwise. |
990 | */ |
991 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> |
992 | inline bool |
993 | operator!=(const std::subtract_with_carry_engine<_UIntType, __w, |
994 | __s, __r>& __lhs, |
995 | const std::subtract_with_carry_engine<_UIntType, __w, |
996 | __s, __r>& __rhs) |
997 | { return !(__lhs == __rhs); } |
998 | #endif |
999 | |
1000 | /** |
1001 | * Produces random numbers from some base engine by discarding blocks of |
1002 | * data. |
1003 | * |
1004 | * @pre @f$ 0 \leq r \leq p @f$ |
1005 | * |
1006 | * @headerfile random |
1007 | * @since C++11 |
1008 | */ |
1009 | template<typename _RandomNumberEngine, size_t __p, size_t __r> |
1010 | class discard_block_engine |
1011 | { |
1012 | static_assert(1 <= __r && __r <= __p, |
1013 | "template argument substituting __r out of bounds" ); |
1014 | |
1015 | public: |
1016 | /** The type of the generated random value. */ |
1017 | typedef typename _RandomNumberEngine::result_type result_type; |
1018 | |
1019 | template<typename _Sseq> |
1020 | using _If_seed_seq |
1021 | = __detail::_If_seed_seq_for<_Sseq, discard_block_engine, |
1022 | result_type>; |
1023 | |
1024 | // parameter values |
1025 | static constexpr size_t block_size = __p; |
1026 | static constexpr size_t used_block = __r; |
1027 | |
1028 | /** |
1029 | * @brief Constructs a default %discard_block_engine engine. |
1030 | * |
1031 | * The underlying engine is default constructed as well. |
1032 | */ |
1033 | discard_block_engine() |
1034 | : _M_b(), _M_n(0) { } |
1035 | |
1036 | /** |
1037 | * @brief Copy constructs a %discard_block_engine engine. |
1038 | * |
1039 | * Copies an existing base class random number generator. |
1040 | * @param __rng An existing (base class) engine object. |
1041 | */ |
1042 | explicit |
1043 | discard_block_engine(const _RandomNumberEngine& __rng) |
1044 | : _M_b(__rng), _M_n(0) { } |
1045 | |
1046 | /** |
1047 | * @brief Move constructs a %discard_block_engine engine. |
1048 | * |
1049 | * Copies an existing base class random number generator. |
1050 | * @param __rng An existing (base class) engine object. |
1051 | */ |
1052 | explicit |
1053 | discard_block_engine(_RandomNumberEngine&& __rng) |
1054 | : _M_b(std::move(__rng)), _M_n(0) { } |
1055 | |
1056 | /** |
1057 | * @brief Seed constructs a %discard_block_engine engine. |
1058 | * |
1059 | * Constructs the underlying generator engine seeded with @p __s. |
1060 | * @param __s A seed value for the base class engine. |
1061 | */ |
1062 | explicit |
1063 | discard_block_engine(result_type __s) |
1064 | : _M_b(__s), _M_n(0) { } |
1065 | |
1066 | /** |
1067 | * @brief Generator construct a %discard_block_engine engine. |
1068 | * |
1069 | * @param __q A seed sequence. |
1070 | */ |
1071 | template<typename _Sseq, typename = _If_seed_seq<_Sseq>> |
1072 | explicit |
1073 | discard_block_engine(_Sseq& __q) |
1074 | : _M_b(__q), _M_n(0) |
1075 | { } |
1076 | |
1077 | /** |
1078 | * @brief Reseeds the %discard_block_engine object with the default |
1079 | * seed for the underlying base class generator engine. |
1080 | */ |
1081 | void |
1082 | seed() |
1083 | { |
1084 | _M_b.seed(); |
1085 | _M_n = 0; |
1086 | } |
1087 | |
1088 | /** |
1089 | * @brief Reseeds the %discard_block_engine object with the default |
1090 | * seed for the underlying base class generator engine. |
1091 | */ |
1092 | void |
1093 | seed(result_type __s) |
1094 | { |
1095 | _M_b.seed(__s); |
1096 | _M_n = 0; |
1097 | } |
1098 | |
1099 | /** |
1100 | * @brief Reseeds the %discard_block_engine object with the given seed |
1101 | * sequence. |
1102 | * @param __q A seed generator function. |
1103 | */ |
1104 | template<typename _Sseq> |
1105 | _If_seed_seq<_Sseq> |
1106 | seed(_Sseq& __q) |
1107 | { |
1108 | _M_b.seed(__q); |
1109 | _M_n = 0; |
1110 | } |
1111 | |
1112 | /** |
1113 | * @brief Gets a const reference to the underlying generator engine |
1114 | * object. |
1115 | */ |
1116 | const _RandomNumberEngine& |
1117 | base() const noexcept |
1118 | { return _M_b; } |
1119 | |
1120 | /** |
1121 | * @brief Gets the minimum value in the generated random number range. |
1122 | */ |
1123 | static constexpr result_type |
1124 | min() |
1125 | { return _RandomNumberEngine::min(); } |
1126 | |
1127 | /** |
1128 | * @brief Gets the maximum value in the generated random number range. |
1129 | */ |
1130 | static constexpr result_type |
1131 | max() |
1132 | { return _RandomNumberEngine::max(); } |
1133 | |
1134 | /** |
1135 | * @brief Discard a sequence of random numbers. |
1136 | */ |
1137 | void |
1138 | discard(unsigned long long __z) |
1139 | { |
1140 | for (; __z != 0ULL; --__z) |
1141 | (*this)(); |
1142 | } |
1143 | |
1144 | /** |
1145 | * @brief Gets the next value in the generated random number sequence. |
1146 | */ |
1147 | result_type |
1148 | operator()(); |
1149 | |
1150 | /** |
1151 | * @brief Compares two %discard_block_engine random number generator |
1152 | * objects of the same type for equality. |
1153 | * |
1154 | * @param __lhs A %discard_block_engine random number generator object. |
1155 | * @param __rhs Another %discard_block_engine random number generator |
1156 | * object. |
1157 | * |
1158 | * @returns true if the infinite sequences of generated values |
1159 | * would be equal, false otherwise. |
1160 | */ |
1161 | friend bool |
1162 | operator==(const discard_block_engine& __lhs, |
1163 | const discard_block_engine& __rhs) |
1164 | { return __lhs._M_b == __rhs._M_b && __lhs._M_n == __rhs._M_n; } |
1165 | |
1166 | /** |
1167 | * @brief Inserts the current state of a %discard_block_engine random |
1168 | * number generator engine @p __x into the output stream |
1169 | * @p __os. |
1170 | * |
1171 | * @param __os An output stream. |
1172 | * @param __x A %discard_block_engine random number generator engine. |
1173 | * |
1174 | * @returns The output stream with the state of @p __x inserted or in |
1175 | * an error state. |
1176 | */ |
1177 | template<typename _RandomNumberEngine1, size_t __p1, size_t __r1, |
1178 | typename _CharT, typename _Traits> |
1179 | friend std::basic_ostream<_CharT, _Traits>& |
1180 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
1181 | const std::discard_block_engine<_RandomNumberEngine1, |
1182 | __p1, __r1>& __x); |
1183 | |
1184 | /** |
1185 | * @brief Extracts the current state of a % subtract_with_carry_engine |
1186 | * random number generator engine @p __x from the input stream |
1187 | * @p __is. |
1188 | * |
1189 | * @param __is An input stream. |
1190 | * @param __x A %discard_block_engine random number generator engine. |
1191 | * |
1192 | * @returns The input stream with the state of @p __x extracted or in |
1193 | * an error state. |
1194 | */ |
1195 | template<typename _RandomNumberEngine1, size_t __p1, size_t __r1, |
1196 | typename _CharT, typename _Traits> |
1197 | friend std::basic_istream<_CharT, _Traits>& |
1198 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
1199 | std::discard_block_engine<_RandomNumberEngine1, |
1200 | __p1, __r1>& __x); |
1201 | |
1202 | private: |
1203 | _RandomNumberEngine _M_b; |
1204 | size_t _M_n; |
1205 | }; |
1206 | |
1207 | #if __cpp_impl_three_way_comparison < 201907L |
1208 | /** |
1209 | * @brief Compares two %discard_block_engine random number generator |
1210 | * objects of the same type for inequality. |
1211 | * |
1212 | * @param __lhs A %discard_block_engine random number generator object. |
1213 | * @param __rhs Another %discard_block_engine random number generator |
1214 | * object. |
1215 | * |
1216 | * @returns true if the infinite sequences of generated values |
1217 | * would be different, false otherwise. |
1218 | */ |
1219 | template<typename _RandomNumberEngine, size_t __p, size_t __r> |
1220 | inline bool |
1221 | operator!=(const std::discard_block_engine<_RandomNumberEngine, __p, |
1222 | __r>& __lhs, |
1223 | const std::discard_block_engine<_RandomNumberEngine, __p, |
1224 | __r>& __rhs) |
1225 | { return !(__lhs == __rhs); } |
1226 | #endif |
1227 | |
1228 | /** |
1229 | * Produces random numbers by combining random numbers from some base |
1230 | * engine to produce random numbers with a specified number of bits @p __w. |
1231 | * |
1232 | * @headerfile random |
1233 | * @since C++11 |
1234 | */ |
1235 | template<typename _RandomNumberEngine, size_t __w, typename _UIntType> |
1236 | class independent_bits_engine |
1237 | { |
1238 | static_assert(std::is_unsigned<_UIntType>::value, |
1239 | "result_type must be an unsigned integral type" ); |
1240 | static_assert(0u < __w && __w <= std::numeric_limits<_UIntType>::digits, |
1241 | "template argument substituting __w out of bounds" ); |
1242 | |
1243 | template<typename _Sseq> |
1244 | using _If_seed_seq |
1245 | = __detail::_If_seed_seq_for<_Sseq, independent_bits_engine, |
1246 | _UIntType>; |
1247 | |
1248 | public: |
1249 | /** The type of the generated random value. */ |
1250 | typedef _UIntType result_type; |
1251 | |
1252 | /** |
1253 | * @brief Constructs a default %independent_bits_engine engine. |
1254 | * |
1255 | * The underlying engine is default constructed as well. |
1256 | */ |
1257 | independent_bits_engine() |
1258 | : _M_b() { } |
1259 | |
1260 | /** |
1261 | * @brief Copy constructs a %independent_bits_engine engine. |
1262 | * |
1263 | * Copies an existing base class random number generator. |
1264 | * @param __rng An existing (base class) engine object. |
1265 | */ |
1266 | explicit |
1267 | independent_bits_engine(const _RandomNumberEngine& __rng) |
1268 | : _M_b(__rng) { } |
1269 | |
1270 | /** |
1271 | * @brief Move constructs a %independent_bits_engine engine. |
1272 | * |
1273 | * Copies an existing base class random number generator. |
1274 | * @param __rng An existing (base class) engine object. |
1275 | */ |
1276 | explicit |
1277 | independent_bits_engine(_RandomNumberEngine&& __rng) |
1278 | : _M_b(std::move(__rng)) { } |
1279 | |
1280 | /** |
1281 | * @brief Seed constructs a %independent_bits_engine engine. |
1282 | * |
1283 | * Constructs the underlying generator engine seeded with @p __s. |
1284 | * @param __s A seed value for the base class engine. |
1285 | */ |
1286 | explicit |
1287 | independent_bits_engine(result_type __s) |
1288 | : _M_b(__s) { } |
1289 | |
1290 | /** |
1291 | * @brief Generator construct a %independent_bits_engine engine. |
1292 | * |
1293 | * @param __q A seed sequence. |
1294 | */ |
1295 | template<typename _Sseq, typename = _If_seed_seq<_Sseq>> |
1296 | explicit |
1297 | independent_bits_engine(_Sseq& __q) |
1298 | : _M_b(__q) |
1299 | { } |
1300 | |
1301 | /** |
1302 | * @brief Reseeds the %independent_bits_engine object with the default |
1303 | * seed for the underlying base class generator engine. |
1304 | */ |
1305 | void |
1306 | seed() |
1307 | { _M_b.seed(); } |
1308 | |
1309 | /** |
1310 | * @brief Reseeds the %independent_bits_engine object with the default |
1311 | * seed for the underlying base class generator engine. |
1312 | */ |
1313 | void |
1314 | seed(result_type __s) |
1315 | { _M_b.seed(__s); } |
1316 | |
1317 | /** |
1318 | * @brief Reseeds the %independent_bits_engine object with the given |
1319 | * seed sequence. |
1320 | * @param __q A seed generator function. |
1321 | */ |
1322 | template<typename _Sseq> |
1323 | _If_seed_seq<_Sseq> |
1324 | seed(_Sseq& __q) |
1325 | { _M_b.seed(__q); } |
1326 | |
1327 | /** |
1328 | * @brief Gets a const reference to the underlying generator engine |
1329 | * object. |
1330 | */ |
1331 | const _RandomNumberEngine& |
1332 | base() const noexcept |
1333 | { return _M_b; } |
1334 | |
1335 | /** |
1336 | * @brief Gets the minimum value in the generated random number range. |
1337 | */ |
1338 | static constexpr result_type |
1339 | min() |
1340 | { return 0U; } |
1341 | |
1342 | /** |
1343 | * @brief Gets the maximum value in the generated random number range. |
1344 | */ |
1345 | static constexpr result_type |
1346 | max() |
1347 | { return __detail::_Shift<_UIntType, __w>::__value - 1; } |
1348 | |
1349 | /** |
1350 | * @brief Discard a sequence of random numbers. |
1351 | */ |
1352 | void |
1353 | discard(unsigned long long __z) |
1354 | { |
1355 | for (; __z != 0ULL; --__z) |
1356 | (*this)(); |
1357 | } |
1358 | |
1359 | /** |
1360 | * @brief Gets the next value in the generated random number sequence. |
1361 | */ |
1362 | result_type |
1363 | operator()(); |
1364 | |
1365 | /** |
1366 | * @brief Compares two %independent_bits_engine random number generator |
1367 | * objects of the same type for equality. |
1368 | * |
1369 | * @param __lhs A %independent_bits_engine random number generator |
1370 | * object. |
1371 | * @param __rhs Another %independent_bits_engine random number generator |
1372 | * object. |
1373 | * |
1374 | * @returns true if the infinite sequences of generated values |
1375 | * would be equal, false otherwise. |
1376 | */ |
1377 | friend bool |
1378 | operator==(const independent_bits_engine& __lhs, |
1379 | const independent_bits_engine& __rhs) |
1380 | { return __lhs._M_b == __rhs._M_b; } |
1381 | |
1382 | /** |
1383 | * @brief Extracts the current state of a % subtract_with_carry_engine |
1384 | * random number generator engine @p __x from the input stream |
1385 | * @p __is. |
1386 | * |
1387 | * @param __is An input stream. |
1388 | * @param __x A %independent_bits_engine random number generator |
1389 | * engine. |
1390 | * |
1391 | * @returns The input stream with the state of @p __x extracted or in |
1392 | * an error state. |
1393 | */ |
1394 | template<typename _CharT, typename _Traits> |
1395 | friend std::basic_istream<_CharT, _Traits>& |
1396 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
1397 | std::independent_bits_engine<_RandomNumberEngine, |
1398 | __w, _UIntType>& __x) |
1399 | { |
1400 | __is >> __x._M_b; |
1401 | return __is; |
1402 | } |
1403 | |
1404 | private: |
1405 | _RandomNumberEngine _M_b; |
1406 | }; |
1407 | |
1408 | #if __cpp_impl_three_way_comparison < 201907L |
1409 | /** |
1410 | * @brief Compares two %independent_bits_engine random number generator |
1411 | * objects of the same type for inequality. |
1412 | * |
1413 | * @param __lhs A %independent_bits_engine random number generator |
1414 | * object. |
1415 | * @param __rhs Another %independent_bits_engine random number generator |
1416 | * object. |
1417 | * |
1418 | * @returns true if the infinite sequences of generated values |
1419 | * would be different, false otherwise. |
1420 | */ |
1421 | template<typename _RandomNumberEngine, size_t __w, typename _UIntType> |
1422 | inline bool |
1423 | operator!=(const std::independent_bits_engine<_RandomNumberEngine, __w, |
1424 | _UIntType>& __lhs, |
1425 | const std::independent_bits_engine<_RandomNumberEngine, __w, |
1426 | _UIntType>& __rhs) |
1427 | { return !(__lhs == __rhs); } |
1428 | #endif |
1429 | |
1430 | /** |
1431 | * @brief Inserts the current state of a %independent_bits_engine random |
1432 | * number generator engine @p __x into the output stream @p __os. |
1433 | * |
1434 | * @param __os An output stream. |
1435 | * @param __x A %independent_bits_engine random number generator engine. |
1436 | * |
1437 | * @returns The output stream with the state of @p __x inserted or in |
1438 | * an error state. |
1439 | */ |
1440 | template<typename _RandomNumberEngine, size_t __w, typename _UIntType, |
1441 | typename _CharT, typename _Traits> |
1442 | std::basic_ostream<_CharT, _Traits>& |
1443 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
1444 | const std::independent_bits_engine<_RandomNumberEngine, |
1445 | __w, _UIntType>& __x) |
1446 | { |
1447 | __os << __x.base(); |
1448 | return __os; |
1449 | } |
1450 | |
1451 | |
1452 | /** |
1453 | * @brief Produces random numbers by reordering random numbers from some |
1454 | * base engine. |
1455 | * |
1456 | * The values from the base engine are stored in a sequence of size @p __k |
1457 | * and shuffled by an algorithm that depends on those values. |
1458 | * |
1459 | * @headerfile random |
1460 | * @since C++11 |
1461 | */ |
1462 | template<typename _RandomNumberEngine, size_t __k> |
1463 | class shuffle_order_engine |
1464 | { |
1465 | static_assert(1u <= __k, "template argument substituting " |
1466 | "__k out of bound" ); |
1467 | |
1468 | public: |
1469 | /** The type of the generated random value. */ |
1470 | typedef typename _RandomNumberEngine::result_type result_type; |
1471 | |
1472 | template<typename _Sseq> |
1473 | using _If_seed_seq |
1474 | = __detail::_If_seed_seq_for<_Sseq, shuffle_order_engine, |
1475 | result_type>; |
1476 | |
1477 | static constexpr size_t table_size = __k; |
1478 | |
1479 | /** |
1480 | * @brief Constructs a default %shuffle_order_engine engine. |
1481 | * |
1482 | * The underlying engine is default constructed as well. |
1483 | */ |
1484 | shuffle_order_engine() |
1485 | : _M_b() |
1486 | { _M_initialize(); } |
1487 | |
1488 | /** |
1489 | * @brief Copy constructs a %shuffle_order_engine engine. |
1490 | * |
1491 | * Copies an existing base class random number generator. |
1492 | * @param __rng An existing (base class) engine object. |
1493 | */ |
1494 | explicit |
1495 | shuffle_order_engine(const _RandomNumberEngine& __rng) |
1496 | : _M_b(__rng) |
1497 | { _M_initialize(); } |
1498 | |
1499 | /** |
1500 | * @brief Move constructs a %shuffle_order_engine engine. |
1501 | * |
1502 | * Copies an existing base class random number generator. |
1503 | * @param __rng An existing (base class) engine object. |
1504 | */ |
1505 | explicit |
1506 | shuffle_order_engine(_RandomNumberEngine&& __rng) |
1507 | : _M_b(std::move(__rng)) |
1508 | { _M_initialize(); } |
1509 | |
1510 | /** |
1511 | * @brief Seed constructs a %shuffle_order_engine engine. |
1512 | * |
1513 | * Constructs the underlying generator engine seeded with @p __s. |
1514 | * @param __s A seed value for the base class engine. |
1515 | */ |
1516 | explicit |
1517 | shuffle_order_engine(result_type __s) |
1518 | : _M_b(__s) |
1519 | { _M_initialize(); } |
1520 | |
1521 | /** |
1522 | * @brief Generator construct a %shuffle_order_engine engine. |
1523 | * |
1524 | * @param __q A seed sequence. |
1525 | */ |
1526 | template<typename _Sseq, typename = _If_seed_seq<_Sseq>> |
1527 | explicit |
1528 | shuffle_order_engine(_Sseq& __q) |
1529 | : _M_b(__q) |
1530 | { _M_initialize(); } |
1531 | |
1532 | /** |
1533 | * @brief Reseeds the %shuffle_order_engine object with the default seed |
1534 | for the underlying base class generator engine. |
1535 | */ |
1536 | void |
1537 | seed() |
1538 | { |
1539 | _M_b.seed(); |
1540 | _M_initialize(); |
1541 | } |
1542 | |
1543 | /** |
1544 | * @brief Reseeds the %shuffle_order_engine object with the default seed |
1545 | * for the underlying base class generator engine. |
1546 | */ |
1547 | void |
1548 | seed(result_type __s) |
1549 | { |
1550 | _M_b.seed(__s); |
1551 | _M_initialize(); |
1552 | } |
1553 | |
1554 | /** |
1555 | * @brief Reseeds the %shuffle_order_engine object with the given seed |
1556 | * sequence. |
1557 | * @param __q A seed generator function. |
1558 | */ |
1559 | template<typename _Sseq> |
1560 | _If_seed_seq<_Sseq> |
1561 | seed(_Sseq& __q) |
1562 | { |
1563 | _M_b.seed(__q); |
1564 | _M_initialize(); |
1565 | } |
1566 | |
1567 | /** |
1568 | * Gets a const reference to the underlying generator engine object. |
1569 | */ |
1570 | const _RandomNumberEngine& |
1571 | base() const noexcept |
1572 | { return _M_b; } |
1573 | |
1574 | /** |
1575 | * Gets the minimum value in the generated random number range. |
1576 | */ |
1577 | static constexpr result_type |
1578 | min() |
1579 | { return _RandomNumberEngine::min(); } |
1580 | |
1581 | /** |
1582 | * Gets the maximum value in the generated random number range. |
1583 | */ |
1584 | static constexpr result_type |
1585 | max() |
1586 | { return _RandomNumberEngine::max(); } |
1587 | |
1588 | /** |
1589 | * Discard a sequence of random numbers. |
1590 | */ |
1591 | void |
1592 | discard(unsigned long long __z) |
1593 | { |
1594 | for (; __z != 0ULL; --__z) |
1595 | (*this)(); |
1596 | } |
1597 | |
1598 | /** |
1599 | * Gets the next value in the generated random number sequence. |
1600 | */ |
1601 | result_type |
1602 | operator()(); |
1603 | |
1604 | /** |
1605 | * Compares two %shuffle_order_engine random number generator objects |
1606 | * of the same type for equality. |
1607 | * |
1608 | * @param __lhs A %shuffle_order_engine random number generator object. |
1609 | * @param __rhs Another %shuffle_order_engine random number generator |
1610 | * object. |
1611 | * |
1612 | * @returns true if the infinite sequences of generated values |
1613 | * would be equal, false otherwise. |
1614 | */ |
1615 | friend bool |
1616 | operator==(const shuffle_order_engine& __lhs, |
1617 | const shuffle_order_engine& __rhs) |
1618 | { return (__lhs._M_b == __rhs._M_b |
1619 | && std::equal(__lhs._M_v, __lhs._M_v + __k, __rhs._M_v) |
1620 | && __lhs._M_y == __rhs._M_y); } |
1621 | |
1622 | /** |
1623 | * @brief Inserts the current state of a %shuffle_order_engine random |
1624 | * number generator engine @p __x into the output stream |
1625 | @p __os. |
1626 | * |
1627 | * @param __os An output stream. |
1628 | * @param __x A %shuffle_order_engine random number generator engine. |
1629 | * |
1630 | * @returns The output stream with the state of @p __x inserted or in |
1631 | * an error state. |
1632 | */ |
1633 | template<typename _RandomNumberEngine1, size_t __k1, |
1634 | typename _CharT, typename _Traits> |
1635 | friend std::basic_ostream<_CharT, _Traits>& |
1636 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
1637 | const std::shuffle_order_engine<_RandomNumberEngine1, |
1638 | __k1>& __x); |
1639 | |
1640 | /** |
1641 | * @brief Extracts the current state of a % subtract_with_carry_engine |
1642 | * random number generator engine @p __x from the input stream |
1643 | * @p __is. |
1644 | * |
1645 | * @param __is An input stream. |
1646 | * @param __x A %shuffle_order_engine random number generator engine. |
1647 | * |
1648 | * @returns The input stream with the state of @p __x extracted or in |
1649 | * an error state. |
1650 | */ |
1651 | template<typename _RandomNumberEngine1, size_t __k1, |
1652 | typename _CharT, typename _Traits> |
1653 | friend std::basic_istream<_CharT, _Traits>& |
1654 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
1655 | std::shuffle_order_engine<_RandomNumberEngine1, __k1>& __x); |
1656 | |
1657 | private: |
1658 | void _M_initialize() |
1659 | { |
1660 | for (size_t __i = 0; __i < __k; ++__i) |
1661 | _M_v[__i] = _M_b(); |
1662 | _M_y = _M_b(); |
1663 | } |
1664 | |
1665 | _RandomNumberEngine _M_b; |
1666 | result_type _M_v[__k]; |
1667 | result_type _M_y; |
1668 | }; |
1669 | |
1670 | #if __cpp_impl_three_way_comparison < 201907L |
1671 | /** |
1672 | * Compares two %shuffle_order_engine random number generator objects |
1673 | * of the same type for inequality. |
1674 | * |
1675 | * @param __lhs A %shuffle_order_engine random number generator object. |
1676 | * @param __rhs Another %shuffle_order_engine random number generator |
1677 | * object. |
1678 | * |
1679 | * @returns true if the infinite sequences of generated values |
1680 | * would be different, false otherwise. |
1681 | */ |
1682 | template<typename _RandomNumberEngine, size_t __k> |
1683 | inline bool |
1684 | operator!=(const std::shuffle_order_engine<_RandomNumberEngine, |
1685 | __k>& __lhs, |
1686 | const std::shuffle_order_engine<_RandomNumberEngine, |
1687 | __k>& __rhs) |
1688 | { return !(__lhs == __rhs); } |
1689 | #endif |
1690 | |
1691 | /** |
1692 | * The classic Minimum Standard rand0 of Lewis, Goodman, and Miller. |
1693 | */ |
1694 | typedef linear_congruential_engine<uint_fast32_t, 16807UL, 0UL, 2147483647UL> |
1695 | minstd_rand0; |
1696 | |
1697 | /** |
1698 | * An alternative LCR (Lehmer Generator function). |
1699 | */ |
1700 | typedef linear_congruential_engine<uint_fast32_t, 48271UL, 0UL, 2147483647UL> |
1701 | minstd_rand; |
1702 | |
1703 | /** |
1704 | * The classic Mersenne Twister. |
1705 | * |
1706 | * Reference: |
1707 | * M. Matsumoto and T. Nishimura, Mersenne Twister: A 623-Dimensionally |
1708 | * Equidistributed Uniform Pseudo-Random Number Generator, ACM Transactions |
1709 | * on Modeling and Computer Simulation, Vol. 8, No. 1, January 1998, pp 3-30. |
1710 | */ |
1711 | typedef mersenne_twister_engine< |
1712 | uint_fast32_t, |
1713 | 32, 624, 397, 31, |
1714 | 0x9908b0dfUL, 11, |
1715 | 0xffffffffUL, 7, |
1716 | 0x9d2c5680UL, 15, |
1717 | 0xefc60000UL, 18, 1812433253UL> mt19937; |
1718 | |
1719 | /** |
1720 | * An alternative Mersenne Twister. |
1721 | */ |
1722 | typedef mersenne_twister_engine< |
1723 | uint_fast64_t, |
1724 | 64, 312, 156, 31, |
1725 | 0xb5026f5aa96619e9ULL, 29, |
1726 | 0x5555555555555555ULL, 17, |
1727 | 0x71d67fffeda60000ULL, 37, |
1728 | 0xfff7eee000000000ULL, 43, |
1729 | 6364136223846793005ULL> mt19937_64; |
1730 | |
1731 | typedef subtract_with_carry_engine<uint_fast32_t, 24, 10, 24> |
1732 | ranlux24_base; |
1733 | |
1734 | typedef subtract_with_carry_engine<uint_fast64_t, 48, 5, 12> |
1735 | ranlux48_base; |
1736 | |
1737 | typedef discard_block_engine<ranlux24_base, 223, 23> ranlux24; |
1738 | |
1739 | typedef discard_block_engine<ranlux48_base, 389, 11> ranlux48; |
1740 | |
1741 | typedef shuffle_order_engine<minstd_rand0, 256> knuth_b; |
1742 | |
1743 | typedef minstd_rand0 default_random_engine; |
1744 | |
1745 | /** |
1746 | * A standard interface to a platform-specific non-deterministic |
1747 | * random number generator (if any are available). |
1748 | * |
1749 | * @headerfile random |
1750 | * @since C++11 |
1751 | */ |
1752 | class random_device |
1753 | { |
1754 | public: |
1755 | /** The type of the generated random value. */ |
1756 | typedef unsigned int result_type; |
1757 | |
1758 | // constructors, destructors and member functions |
1759 | |
1760 | random_device() { _M_init(token: "default" ); } |
1761 | |
1762 | explicit |
1763 | random_device(const std::string& __token) { _M_init(__token); } |
1764 | |
1765 | ~random_device() |
1766 | { _M_fini(); } |
1767 | |
1768 | static constexpr result_type |
1769 | min() |
1770 | { return std::numeric_limits<result_type>::min(); } |
1771 | |
1772 | static constexpr result_type |
1773 | max() |
1774 | { return std::numeric_limits<result_type>::max(); } |
1775 | |
1776 | double |
1777 | entropy() const noexcept |
1778 | { return this->_M_getentropy(); } |
1779 | |
1780 | result_type |
1781 | operator()() |
1782 | { return this->_M_getval(); } |
1783 | |
1784 | // No copy functions. |
1785 | random_device(const random_device&) = delete; |
1786 | void operator=(const random_device&) = delete; |
1787 | |
1788 | private: |
1789 | |
1790 | void _M_init(const std::string& __token); |
1791 | void _M_init_pretr1(const std::string& __token); |
1792 | void _M_fini(); |
1793 | |
1794 | result_type _M_getval(); |
1795 | result_type _M_getval_pretr1(); |
1796 | double _M_getentropy() const noexcept; |
1797 | |
1798 | void _M_init(const char*, size_t); // not exported from the shared library |
1799 | |
1800 | __extension__ union |
1801 | { |
1802 | struct |
1803 | { |
1804 | void* _M_file; |
1805 | result_type (*_M_func)(void*); |
1806 | int _M_fd; |
1807 | }; |
1808 | mt19937 _M_mt; |
1809 | }; |
1810 | }; |
1811 | |
1812 | /// @} group random_generators |
1813 | |
1814 | /** |
1815 | * @addtogroup random_distributions Random Number Distributions |
1816 | * @ingroup random |
1817 | * @{ |
1818 | */ |
1819 | |
1820 | /** |
1821 | * @addtogroup random_distributions_uniform Uniform Distributions |
1822 | * @ingroup random_distributions |
1823 | * @{ |
1824 | */ |
1825 | |
1826 | // std::uniform_int_distribution is defined in <bits/uniform_int_dist.h> |
1827 | |
1828 | #if __cpp_impl_three_way_comparison < 201907L |
1829 | /** |
1830 | * @brief Return true if two uniform integer distributions have |
1831 | * different parameters. |
1832 | */ |
1833 | template<typename _IntType> |
1834 | inline bool |
1835 | operator!=(const std::uniform_int_distribution<_IntType>& __d1, |
1836 | const std::uniform_int_distribution<_IntType>& __d2) |
1837 | { return !(__d1 == __d2); } |
1838 | #endif |
1839 | |
1840 | /** |
1841 | * @brief Inserts a %uniform_int_distribution random number |
1842 | * distribution @p __x into the output stream @p os. |
1843 | * |
1844 | * @param __os An output stream. |
1845 | * @param __x A %uniform_int_distribution random number distribution. |
1846 | * |
1847 | * @returns The output stream with the state of @p __x inserted or in |
1848 | * an error state. |
1849 | */ |
1850 | template<typename _IntType, typename _CharT, typename _Traits> |
1851 | std::basic_ostream<_CharT, _Traits>& |
1852 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
1853 | const std::uniform_int_distribution<_IntType>&); |
1854 | |
1855 | /** |
1856 | * @brief Extracts a %uniform_int_distribution random number distribution |
1857 | * @p __x from the input stream @p __is. |
1858 | * |
1859 | * @param __is An input stream. |
1860 | * @param __x A %uniform_int_distribution random number generator engine. |
1861 | * |
1862 | * @returns The input stream with @p __x extracted or in an error state. |
1863 | */ |
1864 | template<typename _IntType, typename _CharT, typename _Traits> |
1865 | std::basic_istream<_CharT, _Traits>& |
1866 | operator>>(std::basic_istream<_CharT, _Traits>&, |
1867 | std::uniform_int_distribution<_IntType>&); |
1868 | |
1869 | |
1870 | /** |
1871 | * @brief Uniform continuous distribution for random numbers. |
1872 | * |
1873 | * A continuous random distribution on the range [min, max) with equal |
1874 | * probability throughout the range. The URNG should be real-valued and |
1875 | * deliver number in the range [0, 1). |
1876 | * |
1877 | * @headerfile random |
1878 | * @since C++11 |
1879 | */ |
1880 | template<typename _RealType = double> |
1881 | class uniform_real_distribution |
1882 | { |
1883 | static_assert(std::is_floating_point<_RealType>::value, |
1884 | "result_type must be a floating point type" ); |
1885 | |
1886 | public: |
1887 | /** The type of the range of the distribution. */ |
1888 | typedef _RealType result_type; |
1889 | |
1890 | /** Parameter type. */ |
1891 | struct param_type |
1892 | { |
1893 | typedef uniform_real_distribution<_RealType> distribution_type; |
1894 | |
1895 | param_type() : param_type(0) { } |
1896 | |
1897 | explicit |
1898 | param_type(_RealType __a, _RealType __b = _RealType(1)) |
1899 | : _M_a(__a), _M_b(__b) |
1900 | { |
1901 | __glibcxx_assert(_M_a <= _M_b); |
1902 | } |
1903 | |
1904 | result_type |
1905 | a() const |
1906 | { return _M_a; } |
1907 | |
1908 | result_type |
1909 | b() const |
1910 | { return _M_b; } |
1911 | |
1912 | friend bool |
1913 | operator==(const param_type& __p1, const param_type& __p2) |
1914 | { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; } |
1915 | |
1916 | #if __cpp_impl_three_way_comparison < 201907L |
1917 | friend bool |
1918 | operator!=(const param_type& __p1, const param_type& __p2) |
1919 | { return !(__p1 == __p2); } |
1920 | #endif |
1921 | |
1922 | private: |
1923 | _RealType _M_a; |
1924 | _RealType _M_b; |
1925 | }; |
1926 | |
1927 | public: |
1928 | /** |
1929 | * @brief Constructs a uniform_real_distribution object. |
1930 | * |
1931 | * The lower bound is set to 0.0 and the upper bound to 1.0 |
1932 | */ |
1933 | uniform_real_distribution() : uniform_real_distribution(0.0) { } |
1934 | |
1935 | /** |
1936 | * @brief Constructs a uniform_real_distribution object. |
1937 | * |
1938 | * @param __a [IN] The lower bound of the distribution. |
1939 | * @param __b [IN] The upper bound of the distribution. |
1940 | */ |
1941 | explicit |
1942 | uniform_real_distribution(_RealType __a, _RealType __b = _RealType(1)) |
1943 | : _M_param(__a, __b) |
1944 | { } |
1945 | |
1946 | explicit |
1947 | uniform_real_distribution(const param_type& __p) |
1948 | : _M_param(__p) |
1949 | { } |
1950 | |
1951 | /** |
1952 | * @brief Resets the distribution state. |
1953 | * |
1954 | * Does nothing for the uniform real distribution. |
1955 | */ |
1956 | void |
1957 | reset() { } |
1958 | |
1959 | result_type |
1960 | a() const |
1961 | { return _M_param.a(); } |
1962 | |
1963 | result_type |
1964 | b() const |
1965 | { return _M_param.b(); } |
1966 | |
1967 | /** |
1968 | * @brief Returns the parameter set of the distribution. |
1969 | */ |
1970 | param_type |
1971 | param() const |
1972 | { return _M_param; } |
1973 | |
1974 | /** |
1975 | * @brief Sets the parameter set of the distribution. |
1976 | * @param __param The new parameter set of the distribution. |
1977 | */ |
1978 | void |
1979 | param(const param_type& __param) |
1980 | { _M_param = __param; } |
1981 | |
1982 | /** |
1983 | * @brief Returns the inclusive lower bound of the distribution range. |
1984 | */ |
1985 | result_type |
1986 | min() const |
1987 | { return this->a(); } |
1988 | |
1989 | /** |
1990 | * @brief Returns the inclusive upper bound of the distribution range. |
1991 | */ |
1992 | result_type |
1993 | max() const |
1994 | { return this->b(); } |
1995 | |
1996 | /** |
1997 | * @brief Generating functions. |
1998 | */ |
1999 | template<typename _UniformRandomNumberGenerator> |
2000 | result_type |
2001 | operator()(_UniformRandomNumberGenerator& __urng) |
2002 | { return this->operator()(__urng, _M_param); } |
2003 | |
2004 | template<typename _UniformRandomNumberGenerator> |
2005 | result_type |
2006 | operator()(_UniformRandomNumberGenerator& __urng, |
2007 | const param_type& __p) |
2008 | { |
2009 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> |
2010 | __aurng(__urng); |
2011 | return (__aurng() * (__p.b() - __p.a())) + __p.a(); |
2012 | } |
2013 | |
2014 | template<typename _ForwardIterator, |
2015 | typename _UniformRandomNumberGenerator> |
2016 | void |
2017 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
2018 | _UniformRandomNumberGenerator& __urng) |
2019 | { this->__generate(__f, __t, __urng, _M_param); } |
2020 | |
2021 | template<typename _ForwardIterator, |
2022 | typename _UniformRandomNumberGenerator> |
2023 | void |
2024 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
2025 | _UniformRandomNumberGenerator& __urng, |
2026 | const param_type& __p) |
2027 | { this->__generate_impl(__f, __t, __urng, __p); } |
2028 | |
2029 | template<typename _UniformRandomNumberGenerator> |
2030 | void |
2031 | __generate(result_type* __f, result_type* __t, |
2032 | _UniformRandomNumberGenerator& __urng, |
2033 | const param_type& __p) |
2034 | { this->__generate_impl(__f, __t, __urng, __p); } |
2035 | |
2036 | /** |
2037 | * @brief Return true if two uniform real distributions have |
2038 | * the same parameters. |
2039 | */ |
2040 | friend bool |
2041 | operator==(const uniform_real_distribution& __d1, |
2042 | const uniform_real_distribution& __d2) |
2043 | { return __d1._M_param == __d2._M_param; } |
2044 | |
2045 | private: |
2046 | template<typename _ForwardIterator, |
2047 | typename _UniformRandomNumberGenerator> |
2048 | void |
2049 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
2050 | _UniformRandomNumberGenerator& __urng, |
2051 | const param_type& __p); |
2052 | |
2053 | param_type _M_param; |
2054 | }; |
2055 | |
2056 | #if __cpp_impl_three_way_comparison < 201907L |
2057 | /** |
2058 | * @brief Return true if two uniform real distributions have |
2059 | * different parameters. |
2060 | */ |
2061 | template<typename _IntType> |
2062 | inline bool |
2063 | operator!=(const std::uniform_real_distribution<_IntType>& __d1, |
2064 | const std::uniform_real_distribution<_IntType>& __d2) |
2065 | { return !(__d1 == __d2); } |
2066 | #endif |
2067 | |
2068 | /** |
2069 | * @brief Inserts a %uniform_real_distribution random number |
2070 | * distribution @p __x into the output stream @p __os. |
2071 | * |
2072 | * @param __os An output stream. |
2073 | * @param __x A %uniform_real_distribution random number distribution. |
2074 | * |
2075 | * @returns The output stream with the state of @p __x inserted or in |
2076 | * an error state. |
2077 | */ |
2078 | template<typename _RealType, typename _CharT, typename _Traits> |
2079 | std::basic_ostream<_CharT, _Traits>& |
2080 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
2081 | const std::uniform_real_distribution<_RealType>&); |
2082 | |
2083 | /** |
2084 | * @brief Extracts a %uniform_real_distribution random number distribution |
2085 | * @p __x from the input stream @p __is. |
2086 | * |
2087 | * @param __is An input stream. |
2088 | * @param __x A %uniform_real_distribution random number generator engine. |
2089 | * |
2090 | * @returns The input stream with @p __x extracted or in an error state. |
2091 | */ |
2092 | template<typename _RealType, typename _CharT, typename _Traits> |
2093 | std::basic_istream<_CharT, _Traits>& |
2094 | operator>>(std::basic_istream<_CharT, _Traits>&, |
2095 | std::uniform_real_distribution<_RealType>&); |
2096 | |
2097 | /// @} group random_distributions_uniform |
2098 | |
2099 | /** |
2100 | * @addtogroup random_distributions_normal Normal Distributions |
2101 | * @ingroup random_distributions |
2102 | * @{ |
2103 | */ |
2104 | |
2105 | /** |
2106 | * @brief A normal continuous distribution for random numbers. |
2107 | * |
2108 | * The formula for the normal probability density function is |
2109 | * @f[ |
2110 | * p(x|\mu,\sigma) = \frac{1}{\sigma \sqrt{2 \pi}} |
2111 | * e^{- \frac{{x - \mu}^ {2}}{2 \sigma ^ {2}} } |
2112 | * @f] |
2113 | * |
2114 | * @headerfile random |
2115 | * @since C++11 |
2116 | */ |
2117 | template<typename _RealType = double> |
2118 | class normal_distribution |
2119 | { |
2120 | static_assert(std::is_floating_point<_RealType>::value, |
2121 | "result_type must be a floating point type" ); |
2122 | |
2123 | public: |
2124 | /** The type of the range of the distribution. */ |
2125 | typedef _RealType result_type; |
2126 | |
2127 | /** Parameter type. */ |
2128 | struct param_type |
2129 | { |
2130 | typedef normal_distribution<_RealType> distribution_type; |
2131 | |
2132 | param_type() : param_type(0.0) { } |
2133 | |
2134 | explicit |
2135 | param_type(_RealType __mean, _RealType __stddev = _RealType(1)) |
2136 | : _M_mean(__mean), _M_stddev(__stddev) |
2137 | { |
2138 | __glibcxx_assert(_M_stddev > _RealType(0)); |
2139 | } |
2140 | |
2141 | _RealType |
2142 | mean() const |
2143 | { return _M_mean; } |
2144 | |
2145 | _RealType |
2146 | stddev() const |
2147 | { return _M_stddev; } |
2148 | |
2149 | friend bool |
2150 | operator==(const param_type& __p1, const param_type& __p2) |
2151 | { return (__p1._M_mean == __p2._M_mean |
2152 | && __p1._M_stddev == __p2._M_stddev); } |
2153 | |
2154 | #if __cpp_impl_three_way_comparison < 201907L |
2155 | friend bool |
2156 | operator!=(const param_type& __p1, const param_type& __p2) |
2157 | { return !(__p1 == __p2); } |
2158 | #endif |
2159 | |
2160 | private: |
2161 | _RealType _M_mean; |
2162 | _RealType _M_stddev; |
2163 | }; |
2164 | |
2165 | public: |
2166 | normal_distribution() : normal_distribution(0.0) { } |
2167 | |
2168 | /** |
2169 | * Constructs a normal distribution with parameters @f$mean@f$ and |
2170 | * standard deviation. |
2171 | */ |
2172 | explicit |
2173 | normal_distribution(result_type __mean, |
2174 | result_type __stddev = result_type(1)) |
2175 | : _M_param(__mean, __stddev) |
2176 | { } |
2177 | |
2178 | explicit |
2179 | normal_distribution(const param_type& __p) |
2180 | : _M_param(__p) |
2181 | { } |
2182 | |
2183 | /** |
2184 | * @brief Resets the distribution state. |
2185 | */ |
2186 | void |
2187 | reset() |
2188 | { _M_saved_available = false; } |
2189 | |
2190 | /** |
2191 | * @brief Returns the mean of the distribution. |
2192 | */ |
2193 | _RealType |
2194 | mean() const |
2195 | { return _M_param.mean(); } |
2196 | |
2197 | /** |
2198 | * @brief Returns the standard deviation of the distribution. |
2199 | */ |
2200 | _RealType |
2201 | stddev() const |
2202 | { return _M_param.stddev(); } |
2203 | |
2204 | /** |
2205 | * @brief Returns the parameter set of the distribution. |
2206 | */ |
2207 | param_type |
2208 | param() const |
2209 | { return _M_param; } |
2210 | |
2211 | /** |
2212 | * @brief Sets the parameter set of the distribution. |
2213 | * @param __param The new parameter set of the distribution. |
2214 | */ |
2215 | void |
2216 | param(const param_type& __param) |
2217 | { _M_param = __param; } |
2218 | |
2219 | /** |
2220 | * @brief Returns the greatest lower bound value of the distribution. |
2221 | */ |
2222 | result_type |
2223 | min() const |
2224 | { return std::numeric_limits<result_type>::lowest(); } |
2225 | |
2226 | /** |
2227 | * @brief Returns the least upper bound value of the distribution. |
2228 | */ |
2229 | result_type |
2230 | max() const |
2231 | { return std::numeric_limits<result_type>::max(); } |
2232 | |
2233 | /** |
2234 | * @brief Generating functions. |
2235 | */ |
2236 | template<typename _UniformRandomNumberGenerator> |
2237 | result_type |
2238 | operator()(_UniformRandomNumberGenerator& __urng) |
2239 | { return this->operator()(__urng, _M_param); } |
2240 | |
2241 | template<typename _UniformRandomNumberGenerator> |
2242 | result_type |
2243 | operator()(_UniformRandomNumberGenerator& __urng, |
2244 | const param_type& __p); |
2245 | |
2246 | template<typename _ForwardIterator, |
2247 | typename _UniformRandomNumberGenerator> |
2248 | void |
2249 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
2250 | _UniformRandomNumberGenerator& __urng) |
2251 | { this->__generate(__f, __t, __urng, _M_param); } |
2252 | |
2253 | template<typename _ForwardIterator, |
2254 | typename _UniformRandomNumberGenerator> |
2255 | void |
2256 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
2257 | _UniformRandomNumberGenerator& __urng, |
2258 | const param_type& __p) |
2259 | { this->__generate_impl(__f, __t, __urng, __p); } |
2260 | |
2261 | template<typename _UniformRandomNumberGenerator> |
2262 | void |
2263 | __generate(result_type* __f, result_type* __t, |
2264 | _UniformRandomNumberGenerator& __urng, |
2265 | const param_type& __p) |
2266 | { this->__generate_impl(__f, __t, __urng, __p); } |
2267 | |
2268 | /** |
2269 | * @brief Return true if two normal distributions have |
2270 | * the same parameters and the sequences that would |
2271 | * be generated are equal. |
2272 | */ |
2273 | template<typename _RealType1> |
2274 | friend bool |
2275 | operator==(const std::normal_distribution<_RealType1>& __d1, |
2276 | const std::normal_distribution<_RealType1>& __d2); |
2277 | |
2278 | /** |
2279 | * @brief Inserts a %normal_distribution random number distribution |
2280 | * @p __x into the output stream @p __os. |
2281 | * |
2282 | * @param __os An output stream. |
2283 | * @param __x A %normal_distribution random number distribution. |
2284 | * |
2285 | * @returns The output stream with the state of @p __x inserted or in |
2286 | * an error state. |
2287 | */ |
2288 | template<typename _RealType1, typename _CharT, typename _Traits> |
2289 | friend std::basic_ostream<_CharT, _Traits>& |
2290 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
2291 | const std::normal_distribution<_RealType1>& __x); |
2292 | |
2293 | /** |
2294 | * @brief Extracts a %normal_distribution random number distribution |
2295 | * @p __x from the input stream @p __is. |
2296 | * |
2297 | * @param __is An input stream. |
2298 | * @param __x A %normal_distribution random number generator engine. |
2299 | * |
2300 | * @returns The input stream with @p __x extracted or in an error |
2301 | * state. |
2302 | */ |
2303 | template<typename _RealType1, typename _CharT, typename _Traits> |
2304 | friend std::basic_istream<_CharT, _Traits>& |
2305 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
2306 | std::normal_distribution<_RealType1>& __x); |
2307 | |
2308 | private: |
2309 | template<typename _ForwardIterator, |
2310 | typename _UniformRandomNumberGenerator> |
2311 | void |
2312 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
2313 | _UniformRandomNumberGenerator& __urng, |
2314 | const param_type& __p); |
2315 | |
2316 | param_type _M_param; |
2317 | result_type _M_saved = 0; |
2318 | bool _M_saved_available = false; |
2319 | }; |
2320 | |
2321 | #if __cpp_impl_three_way_comparison < 201907L |
2322 | /** |
2323 | * @brief Return true if two normal distributions are different. |
2324 | */ |
2325 | template<typename _RealType> |
2326 | inline bool |
2327 | operator!=(const std::normal_distribution<_RealType>& __d1, |
2328 | const std::normal_distribution<_RealType>& __d2) |
2329 | { return !(__d1 == __d2); } |
2330 | #endif |
2331 | |
2332 | /** |
2333 | * @brief A lognormal_distribution random number distribution. |
2334 | * |
2335 | * The formula for the normal probability mass function is |
2336 | * @f[ |
2337 | * p(x|m,s) = \frac{1}{sx\sqrt{2\pi}} |
2338 | * \exp{-\frac{(\ln{x} - m)^2}{2s^2}} |
2339 | * @f] |
2340 | * |
2341 | * @headerfile random |
2342 | * @since C++11 |
2343 | */ |
2344 | template<typename _RealType = double> |
2345 | class lognormal_distribution |
2346 | { |
2347 | static_assert(std::is_floating_point<_RealType>::value, |
2348 | "result_type must be a floating point type" ); |
2349 | |
2350 | public: |
2351 | /** The type of the range of the distribution. */ |
2352 | typedef _RealType result_type; |
2353 | |
2354 | /** Parameter type. */ |
2355 | struct param_type |
2356 | { |
2357 | typedef lognormal_distribution<_RealType> distribution_type; |
2358 | |
2359 | param_type() : param_type(0.0) { } |
2360 | |
2361 | explicit |
2362 | param_type(_RealType __m, _RealType __s = _RealType(1)) |
2363 | : _M_m(__m), _M_s(__s) |
2364 | { } |
2365 | |
2366 | _RealType |
2367 | m() const |
2368 | { return _M_m; } |
2369 | |
2370 | _RealType |
2371 | s() const |
2372 | { return _M_s; } |
2373 | |
2374 | friend bool |
2375 | operator==(const param_type& __p1, const param_type& __p2) |
2376 | { return __p1._M_m == __p2._M_m && __p1._M_s == __p2._M_s; } |
2377 | |
2378 | #if __cpp_impl_three_way_comparison < 201907L |
2379 | friend bool |
2380 | operator!=(const param_type& __p1, const param_type& __p2) |
2381 | { return !(__p1 == __p2); } |
2382 | #endif |
2383 | |
2384 | private: |
2385 | _RealType _M_m; |
2386 | _RealType _M_s; |
2387 | }; |
2388 | |
2389 | lognormal_distribution() : lognormal_distribution(0.0) { } |
2390 | |
2391 | explicit |
2392 | lognormal_distribution(_RealType __m, _RealType __s = _RealType(1)) |
2393 | : _M_param(__m, __s), _M_nd() |
2394 | { } |
2395 | |
2396 | explicit |
2397 | lognormal_distribution(const param_type& __p) |
2398 | : _M_param(__p), _M_nd() |
2399 | { } |
2400 | |
2401 | /** |
2402 | * Resets the distribution state. |
2403 | */ |
2404 | void |
2405 | reset() |
2406 | { _M_nd.reset(); } |
2407 | |
2408 | /** |
2409 | * |
2410 | */ |
2411 | _RealType |
2412 | m() const |
2413 | { return _M_param.m(); } |
2414 | |
2415 | _RealType |
2416 | s() const |
2417 | { return _M_param.s(); } |
2418 | |
2419 | /** |
2420 | * @brief Returns the parameter set of the distribution. |
2421 | */ |
2422 | param_type |
2423 | param() const |
2424 | { return _M_param; } |
2425 | |
2426 | /** |
2427 | * @brief Sets the parameter set of the distribution. |
2428 | * @param __param The new parameter set of the distribution. |
2429 | */ |
2430 | void |
2431 | param(const param_type& __param) |
2432 | { _M_param = __param; } |
2433 | |
2434 | /** |
2435 | * @brief Returns the greatest lower bound value of the distribution. |
2436 | */ |
2437 | result_type |
2438 | min() const |
2439 | { return result_type(0); } |
2440 | |
2441 | /** |
2442 | * @brief Returns the least upper bound value of the distribution. |
2443 | */ |
2444 | result_type |
2445 | max() const |
2446 | { return std::numeric_limits<result_type>::max(); } |
2447 | |
2448 | /** |
2449 | * @brief Generating functions. |
2450 | */ |
2451 | template<typename _UniformRandomNumberGenerator> |
2452 | result_type |
2453 | operator()(_UniformRandomNumberGenerator& __urng) |
2454 | { return this->operator()(__urng, _M_param); } |
2455 | |
2456 | template<typename _UniformRandomNumberGenerator> |
2457 | result_type |
2458 | operator()(_UniformRandomNumberGenerator& __urng, |
2459 | const param_type& __p) |
2460 | { return std::exp(__p.s() * _M_nd(__urng) + __p.m()); } |
2461 | |
2462 | template<typename _ForwardIterator, |
2463 | typename _UniformRandomNumberGenerator> |
2464 | void |
2465 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
2466 | _UniformRandomNumberGenerator& __urng) |
2467 | { this->__generate(__f, __t, __urng, _M_param); } |
2468 | |
2469 | template<typename _ForwardIterator, |
2470 | typename _UniformRandomNumberGenerator> |
2471 | void |
2472 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
2473 | _UniformRandomNumberGenerator& __urng, |
2474 | const param_type& __p) |
2475 | { this->__generate_impl(__f, __t, __urng, __p); } |
2476 | |
2477 | template<typename _UniformRandomNumberGenerator> |
2478 | void |
2479 | __generate(result_type* __f, result_type* __t, |
2480 | _UniformRandomNumberGenerator& __urng, |
2481 | const param_type& __p) |
2482 | { this->__generate_impl(__f, __t, __urng, __p); } |
2483 | |
2484 | /** |
2485 | * @brief Return true if two lognormal distributions have |
2486 | * the same parameters and the sequences that would |
2487 | * be generated are equal. |
2488 | */ |
2489 | friend bool |
2490 | operator==(const lognormal_distribution& __d1, |
2491 | const lognormal_distribution& __d2) |
2492 | { return (__d1._M_param == __d2._M_param |
2493 | && __d1._M_nd == __d2._M_nd); } |
2494 | |
2495 | /** |
2496 | * @brief Inserts a %lognormal_distribution random number distribution |
2497 | * @p __x into the output stream @p __os. |
2498 | * |
2499 | * @param __os An output stream. |
2500 | * @param __x A %lognormal_distribution random number distribution. |
2501 | * |
2502 | * @returns The output stream with the state of @p __x inserted or in |
2503 | * an error state. |
2504 | */ |
2505 | template<typename _RealType1, typename _CharT, typename _Traits> |
2506 | friend std::basic_ostream<_CharT, _Traits>& |
2507 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
2508 | const std::lognormal_distribution<_RealType1>& __x); |
2509 | |
2510 | /** |
2511 | * @brief Extracts a %lognormal_distribution random number distribution |
2512 | * @p __x from the input stream @p __is. |
2513 | * |
2514 | * @param __is An input stream. |
2515 | * @param __x A %lognormal_distribution random number |
2516 | * generator engine. |
2517 | * |
2518 | * @returns The input stream with @p __x extracted or in an error state. |
2519 | */ |
2520 | template<typename _RealType1, typename _CharT, typename _Traits> |
2521 | friend std::basic_istream<_CharT, _Traits>& |
2522 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
2523 | std::lognormal_distribution<_RealType1>& __x); |
2524 | |
2525 | private: |
2526 | template<typename _ForwardIterator, |
2527 | typename _UniformRandomNumberGenerator> |
2528 | void |
2529 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
2530 | _UniformRandomNumberGenerator& __urng, |
2531 | const param_type& __p); |
2532 | |
2533 | param_type _M_param; |
2534 | |
2535 | std::normal_distribution<result_type> _M_nd; |
2536 | }; |
2537 | |
2538 | #if __cpp_impl_three_way_comparison < 201907L |
2539 | /** |
2540 | * @brief Return true if two lognormal distributions are different. |
2541 | */ |
2542 | template<typename _RealType> |
2543 | inline bool |
2544 | operator!=(const std::lognormal_distribution<_RealType>& __d1, |
2545 | const std::lognormal_distribution<_RealType>& __d2) |
2546 | { return !(__d1 == __d2); } |
2547 | #endif |
2548 | |
2549 | /// @} group random_distributions_normal |
2550 | |
2551 | /** |
2552 | * @addtogroup random_distributions_poisson Poisson Distributions |
2553 | * @ingroup random_distributions |
2554 | * @{ |
2555 | */ |
2556 | |
2557 | /** |
2558 | * @brief A gamma continuous distribution for random numbers. |
2559 | * |
2560 | * The formula for the gamma probability density function is: |
2561 | * @f[ |
2562 | * p(x|\alpha,\beta) = \frac{1}{\beta\Gamma(\alpha)} |
2563 | * (x/\beta)^{\alpha - 1} e^{-x/\beta} |
2564 | * @f] |
2565 | * |
2566 | * @headerfile random |
2567 | * @since C++11 |
2568 | */ |
2569 | template<typename _RealType = double> |
2570 | class gamma_distribution |
2571 | { |
2572 | static_assert(std::is_floating_point<_RealType>::value, |
2573 | "result_type must be a floating point type" ); |
2574 | |
2575 | public: |
2576 | /** The type of the range of the distribution. */ |
2577 | typedef _RealType result_type; |
2578 | |
2579 | /** Parameter type. */ |
2580 | struct param_type |
2581 | { |
2582 | typedef gamma_distribution<_RealType> distribution_type; |
2583 | friend class gamma_distribution<_RealType>; |
2584 | |
2585 | param_type() : param_type(1.0) { } |
2586 | |
2587 | explicit |
2588 | param_type(_RealType __alpha_val, _RealType __beta_val = _RealType(1)) |
2589 | : _M_alpha(__alpha_val), _M_beta(__beta_val) |
2590 | { |
2591 | __glibcxx_assert(_M_alpha > _RealType(0)); |
2592 | _M_initialize(); |
2593 | } |
2594 | |
2595 | _RealType |
2596 | alpha() const |
2597 | { return _M_alpha; } |
2598 | |
2599 | _RealType |
2600 | beta() const |
2601 | { return _M_beta; } |
2602 | |
2603 | friend bool |
2604 | operator==(const param_type& __p1, const param_type& __p2) |
2605 | { return (__p1._M_alpha == __p2._M_alpha |
2606 | && __p1._M_beta == __p2._M_beta); } |
2607 | |
2608 | #if __cpp_impl_three_way_comparison < 201907L |
2609 | friend bool |
2610 | operator!=(const param_type& __p1, const param_type& __p2) |
2611 | { return !(__p1 == __p2); } |
2612 | #endif |
2613 | |
2614 | private: |
2615 | void |
2616 | _M_initialize(); |
2617 | |
2618 | _RealType _M_alpha; |
2619 | _RealType _M_beta; |
2620 | |
2621 | _RealType _M_malpha, _M_a2; |
2622 | }; |
2623 | |
2624 | public: |
2625 | /** |
2626 | * @brief Constructs a gamma distribution with parameters 1 and 1. |
2627 | */ |
2628 | gamma_distribution() : gamma_distribution(1.0) { } |
2629 | |
2630 | /** |
2631 | * @brief Constructs a gamma distribution with parameters |
2632 | * @f$\alpha@f$ and @f$\beta@f$. |
2633 | */ |
2634 | explicit |
2635 | gamma_distribution(_RealType __alpha_val, |
2636 | _RealType __beta_val = _RealType(1)) |
2637 | : _M_param(__alpha_val, __beta_val), _M_nd() |
2638 | { } |
2639 | |
2640 | explicit |
2641 | gamma_distribution(const param_type& __p) |
2642 | : _M_param(__p), _M_nd() |
2643 | { } |
2644 | |
2645 | /** |
2646 | * @brief Resets the distribution state. |
2647 | */ |
2648 | void |
2649 | reset() |
2650 | { _M_nd.reset(); } |
2651 | |
2652 | /** |
2653 | * @brief Returns the @f$\alpha@f$ of the distribution. |
2654 | */ |
2655 | _RealType |
2656 | alpha() const |
2657 | { return _M_param.alpha(); } |
2658 | |
2659 | /** |
2660 | * @brief Returns the @f$\beta@f$ of the distribution. |
2661 | */ |
2662 | _RealType |
2663 | beta() const |
2664 | { return _M_param.beta(); } |
2665 | |
2666 | /** |
2667 | * @brief Returns the parameter set of the distribution. |
2668 | */ |
2669 | param_type |
2670 | param() const |
2671 | { return _M_param; } |
2672 | |
2673 | /** |
2674 | * @brief Sets the parameter set of the distribution. |
2675 | * @param __param The new parameter set of the distribution. |
2676 | */ |
2677 | void |
2678 | param(const param_type& __param) |
2679 | { _M_param = __param; } |
2680 | |
2681 | /** |
2682 | * @brief Returns the greatest lower bound value of the distribution. |
2683 | */ |
2684 | result_type |
2685 | min() const |
2686 | { return result_type(0); } |
2687 | |
2688 | /** |
2689 | * @brief Returns the least upper bound value of the distribution. |
2690 | */ |
2691 | result_type |
2692 | max() const |
2693 | { return std::numeric_limits<result_type>::max(); } |
2694 | |
2695 | /** |
2696 | * @brief Generating functions. |
2697 | */ |
2698 | template<typename _UniformRandomNumberGenerator> |
2699 | result_type |
2700 | operator()(_UniformRandomNumberGenerator& __urng) |
2701 | { return this->operator()(__urng, _M_param); } |
2702 | |
2703 | template<typename _UniformRandomNumberGenerator> |
2704 | result_type |
2705 | operator()(_UniformRandomNumberGenerator& __urng, |
2706 | const param_type& __p); |
2707 | |
2708 | template<typename _ForwardIterator, |
2709 | typename _UniformRandomNumberGenerator> |
2710 | void |
2711 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
2712 | _UniformRandomNumberGenerator& __urng) |
2713 | { this->__generate(__f, __t, __urng, _M_param); } |
2714 | |
2715 | template<typename _ForwardIterator, |
2716 | typename _UniformRandomNumberGenerator> |
2717 | void |
2718 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
2719 | _UniformRandomNumberGenerator& __urng, |
2720 | const param_type& __p) |
2721 | { this->__generate_impl(__f, __t, __urng, __p); } |
2722 | |
2723 | template<typename _UniformRandomNumberGenerator> |
2724 | void |
2725 | __generate(result_type* __f, result_type* __t, |
2726 | _UniformRandomNumberGenerator& __urng, |
2727 | const param_type& __p) |
2728 | { this->__generate_impl(__f, __t, __urng, __p); } |
2729 | |
2730 | /** |
2731 | * @brief Return true if two gamma distributions have the same |
2732 | * parameters and the sequences that would be generated |
2733 | * are equal. |
2734 | */ |
2735 | friend bool |
2736 | operator==(const gamma_distribution& __d1, |
2737 | const gamma_distribution& __d2) |
2738 | { return (__d1._M_param == __d2._M_param |
2739 | && __d1._M_nd == __d2._M_nd); } |
2740 | |
2741 | /** |
2742 | * @brief Inserts a %gamma_distribution random number distribution |
2743 | * @p __x into the output stream @p __os. |
2744 | * |
2745 | * @param __os An output stream. |
2746 | * @param __x A %gamma_distribution random number distribution. |
2747 | * |
2748 | * @returns The output stream with the state of @p __x inserted or in |
2749 | * an error state. |
2750 | */ |
2751 | template<typename _RealType1, typename _CharT, typename _Traits> |
2752 | friend std::basic_ostream<_CharT, _Traits>& |
2753 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
2754 | const std::gamma_distribution<_RealType1>& __x); |
2755 | |
2756 | /** |
2757 | * @brief Extracts a %gamma_distribution random number distribution |
2758 | * @p __x from the input stream @p __is. |
2759 | * |
2760 | * @param __is An input stream. |
2761 | * @param __x A %gamma_distribution random number generator engine. |
2762 | * |
2763 | * @returns The input stream with @p __x extracted or in an error state. |
2764 | */ |
2765 | template<typename _RealType1, typename _CharT, typename _Traits> |
2766 | friend std::basic_istream<_CharT, _Traits>& |
2767 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
2768 | std::gamma_distribution<_RealType1>& __x); |
2769 | |
2770 | private: |
2771 | template<typename _ForwardIterator, |
2772 | typename _UniformRandomNumberGenerator> |
2773 | void |
2774 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
2775 | _UniformRandomNumberGenerator& __urng, |
2776 | const param_type& __p); |
2777 | |
2778 | param_type _M_param; |
2779 | |
2780 | std::normal_distribution<result_type> _M_nd; |
2781 | }; |
2782 | |
2783 | #if __cpp_impl_three_way_comparison < 201907L |
2784 | /** |
2785 | * @brief Return true if two gamma distributions are different. |
2786 | */ |
2787 | template<typename _RealType> |
2788 | inline bool |
2789 | operator!=(const std::gamma_distribution<_RealType>& __d1, |
2790 | const std::gamma_distribution<_RealType>& __d2) |
2791 | { return !(__d1 == __d2); } |
2792 | #endif |
2793 | |
2794 | /// @} group random_distributions_poisson |
2795 | |
2796 | /** |
2797 | * @addtogroup random_distributions_normal Normal Distributions |
2798 | * @ingroup random_distributions |
2799 | * @{ |
2800 | */ |
2801 | |
2802 | /** |
2803 | * @brief A chi_squared_distribution random number distribution. |
2804 | * |
2805 | * The formula for the normal probability mass function is |
2806 | * @f$p(x|n) = \frac{x^{(n/2) - 1}e^{-x/2}}{\Gamma(n/2) 2^{n/2}}@f$ |
2807 | * |
2808 | * @headerfile random |
2809 | * @since C++11 |
2810 | */ |
2811 | template<typename _RealType = double> |
2812 | class chi_squared_distribution |
2813 | { |
2814 | static_assert(std::is_floating_point<_RealType>::value, |
2815 | "result_type must be a floating point type" ); |
2816 | |
2817 | public: |
2818 | /** The type of the range of the distribution. */ |
2819 | typedef _RealType result_type; |
2820 | |
2821 | /** Parameter type. */ |
2822 | struct param_type |
2823 | { |
2824 | typedef chi_squared_distribution<_RealType> distribution_type; |
2825 | |
2826 | param_type() : param_type(1) { } |
2827 | |
2828 | explicit |
2829 | param_type(_RealType __n) |
2830 | : _M_n(__n) |
2831 | { } |
2832 | |
2833 | _RealType |
2834 | n() const |
2835 | { return _M_n; } |
2836 | |
2837 | friend bool |
2838 | operator==(const param_type& __p1, const param_type& __p2) |
2839 | { return __p1._M_n == __p2._M_n; } |
2840 | |
2841 | #if __cpp_impl_three_way_comparison < 201907L |
2842 | friend bool |
2843 | operator!=(const param_type& __p1, const param_type& __p2) |
2844 | { return !(__p1 == __p2); } |
2845 | #endif |
2846 | |
2847 | private: |
2848 | _RealType _M_n; |
2849 | }; |
2850 | |
2851 | chi_squared_distribution() : chi_squared_distribution(1) { } |
2852 | |
2853 | explicit |
2854 | chi_squared_distribution(_RealType __n) |
2855 | : _M_param(__n), _M_gd(__n / 2) |
2856 | { } |
2857 | |
2858 | explicit |
2859 | chi_squared_distribution(const param_type& __p) |
2860 | : _M_param(__p), _M_gd(__p.n() / 2) |
2861 | { } |
2862 | |
2863 | /** |
2864 | * @brief Resets the distribution state. |
2865 | */ |
2866 | void |
2867 | reset() |
2868 | { _M_gd.reset(); } |
2869 | |
2870 | /** |
2871 | * |
2872 | */ |
2873 | _RealType |
2874 | n() const |
2875 | { return _M_param.n(); } |
2876 | |
2877 | /** |
2878 | * @brief Returns the parameter set of the distribution. |
2879 | */ |
2880 | param_type |
2881 | param() const |
2882 | { return _M_param; } |
2883 | |
2884 | /** |
2885 | * @brief Sets the parameter set of the distribution. |
2886 | * @param __param The new parameter set of the distribution. |
2887 | */ |
2888 | void |
2889 | param(const param_type& __param) |
2890 | { |
2891 | _M_param = __param; |
2892 | typedef typename std::gamma_distribution<result_type>::param_type |
2893 | param_type; |
2894 | _M_gd.param(param_type{__param.n() / 2}); |
2895 | } |
2896 | |
2897 | /** |
2898 | * @brief Returns the greatest lower bound value of the distribution. |
2899 | */ |
2900 | result_type |
2901 | min() const |
2902 | { return result_type(0); } |
2903 | |
2904 | /** |
2905 | * @brief Returns the least upper bound value of the distribution. |
2906 | */ |
2907 | result_type |
2908 | max() const |
2909 | { return std::numeric_limits<result_type>::max(); } |
2910 | |
2911 | /** |
2912 | * @brief Generating functions. |
2913 | */ |
2914 | template<typename _UniformRandomNumberGenerator> |
2915 | result_type |
2916 | operator()(_UniformRandomNumberGenerator& __urng) |
2917 | { return 2 * _M_gd(__urng); } |
2918 | |
2919 | template<typename _UniformRandomNumberGenerator> |
2920 | result_type |
2921 | operator()(_UniformRandomNumberGenerator& __urng, |
2922 | const param_type& __p) |
2923 | { |
2924 | typedef typename std::gamma_distribution<result_type>::param_type |
2925 | param_type; |
2926 | return 2 * _M_gd(__urng, param_type(__p.n() / 2)); |
2927 | } |
2928 | |
2929 | template<typename _ForwardIterator, |
2930 | typename _UniformRandomNumberGenerator> |
2931 | void |
2932 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
2933 | _UniformRandomNumberGenerator& __urng) |
2934 | { this->__generate_impl(__f, __t, __urng); } |
2935 | |
2936 | template<typename _ForwardIterator, |
2937 | typename _UniformRandomNumberGenerator> |
2938 | void |
2939 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
2940 | _UniformRandomNumberGenerator& __urng, |
2941 | const param_type& __p) |
2942 | { typename std::gamma_distribution<result_type>::param_type |
2943 | __p2(__p.n() / 2); |
2944 | this->__generate_impl(__f, __t, __urng, __p2); } |
2945 | |
2946 | template<typename _UniformRandomNumberGenerator> |
2947 | void |
2948 | __generate(result_type* __f, result_type* __t, |
2949 | _UniformRandomNumberGenerator& __urng) |
2950 | { this->__generate_impl(__f, __t, __urng); } |
2951 | |
2952 | template<typename _UniformRandomNumberGenerator> |
2953 | void |
2954 | __generate(result_type* __f, result_type* __t, |
2955 | _UniformRandomNumberGenerator& __urng, |
2956 | const param_type& __p) |
2957 | { typename std::gamma_distribution<result_type>::param_type |
2958 | __p2(__p.n() / 2); |
2959 | this->__generate_impl(__f, __t, __urng, __p2); } |
2960 | |
2961 | /** |
2962 | * @brief Return true if two Chi-squared distributions have |
2963 | * the same parameters and the sequences that would be |
2964 | * generated are equal. |
2965 | */ |
2966 | friend bool |
2967 | operator==(const chi_squared_distribution& __d1, |
2968 | const chi_squared_distribution& __d2) |
2969 | { return __d1._M_param == __d2._M_param && __d1._M_gd == __d2._M_gd; } |
2970 | |
2971 | /** |
2972 | * @brief Inserts a %chi_squared_distribution random number distribution |
2973 | * @p __x into the output stream @p __os. |
2974 | * |
2975 | * @param __os An output stream. |
2976 | * @param __x A %chi_squared_distribution random number distribution. |
2977 | * |
2978 | * @returns The output stream with the state of @p __x inserted or in |
2979 | * an error state. |
2980 | */ |
2981 | template<typename _RealType1, typename _CharT, typename _Traits> |
2982 | friend std::basic_ostream<_CharT, _Traits>& |
2983 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
2984 | const std::chi_squared_distribution<_RealType1>& __x); |
2985 | |
2986 | /** |
2987 | * @brief Extracts a %chi_squared_distribution random number distribution |
2988 | * @p __x from the input stream @p __is. |
2989 | * |
2990 | * @param __is An input stream. |
2991 | * @param __x A %chi_squared_distribution random number |
2992 | * generator engine. |
2993 | * |
2994 | * @returns The input stream with @p __x extracted or in an error state. |
2995 | */ |
2996 | template<typename _RealType1, typename _CharT, typename _Traits> |
2997 | friend std::basic_istream<_CharT, _Traits>& |
2998 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
2999 | std::chi_squared_distribution<_RealType1>& __x); |
3000 | |
3001 | private: |
3002 | template<typename _ForwardIterator, |
3003 | typename _UniformRandomNumberGenerator> |
3004 | void |
3005 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
3006 | _UniformRandomNumberGenerator& __urng); |
3007 | |
3008 | template<typename _ForwardIterator, |
3009 | typename _UniformRandomNumberGenerator> |
3010 | void |
3011 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
3012 | _UniformRandomNumberGenerator& __urng, |
3013 | const typename |
3014 | std::gamma_distribution<result_type>::param_type& __p); |
3015 | |
3016 | param_type _M_param; |
3017 | |
3018 | std::gamma_distribution<result_type> _M_gd; |
3019 | }; |
3020 | |
3021 | #if __cpp_impl_three_way_comparison < 201907L |
3022 | /** |
3023 | * @brief Return true if two Chi-squared distributions are different. |
3024 | */ |
3025 | template<typename _RealType> |
3026 | inline bool |
3027 | operator!=(const std::chi_squared_distribution<_RealType>& __d1, |
3028 | const std::chi_squared_distribution<_RealType>& __d2) |
3029 | { return !(__d1 == __d2); } |
3030 | #endif |
3031 | |
3032 | /** |
3033 | * @brief A cauchy_distribution random number distribution. |
3034 | * |
3035 | * The formula for the normal probability mass function is |
3036 | * @f$p(x|a,b) = (\pi b (1 + (\frac{x-a}{b})^2))^{-1}@f$ |
3037 | * |
3038 | * @headerfile random |
3039 | * @since C++11 |
3040 | */ |
3041 | template<typename _RealType = double> |
3042 | class cauchy_distribution |
3043 | { |
3044 | static_assert(std::is_floating_point<_RealType>::value, |
3045 | "result_type must be a floating point type" ); |
3046 | |
3047 | public: |
3048 | /** The type of the range of the distribution. */ |
3049 | typedef _RealType result_type; |
3050 | |
3051 | /** Parameter type. */ |
3052 | struct param_type |
3053 | { |
3054 | typedef cauchy_distribution<_RealType> distribution_type; |
3055 | |
3056 | param_type() : param_type(0) { } |
3057 | |
3058 | explicit |
3059 | param_type(_RealType __a, _RealType __b = _RealType(1)) |
3060 | : _M_a(__a), _M_b(__b) |
3061 | { } |
3062 | |
3063 | _RealType |
3064 | a() const |
3065 | { return _M_a; } |
3066 | |
3067 | _RealType |
3068 | b() const |
3069 | { return _M_b; } |
3070 | |
3071 | friend bool |
3072 | operator==(const param_type& __p1, const param_type& __p2) |
3073 | { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; } |
3074 | |
3075 | #if __cpp_impl_three_way_comparison < 201907L |
3076 | friend bool |
3077 | operator!=(const param_type& __p1, const param_type& __p2) |
3078 | { return !(__p1 == __p2); } |
3079 | #endif |
3080 | |
3081 | private: |
3082 | _RealType _M_a; |
3083 | _RealType _M_b; |
3084 | }; |
3085 | |
3086 | cauchy_distribution() : cauchy_distribution(0.0) { } |
3087 | |
3088 | explicit |
3089 | cauchy_distribution(_RealType __a, _RealType __b = 1.0) |
3090 | : _M_param(__a, __b) |
3091 | { } |
3092 | |
3093 | explicit |
3094 | cauchy_distribution(const param_type& __p) |
3095 | : _M_param(__p) |
3096 | { } |
3097 | |
3098 | /** |
3099 | * @brief Resets the distribution state. |
3100 | */ |
3101 | void |
3102 | reset() |
3103 | { } |
3104 | |
3105 | /** |
3106 | * |
3107 | */ |
3108 | _RealType |
3109 | a() const |
3110 | { return _M_param.a(); } |
3111 | |
3112 | _RealType |
3113 | b() const |
3114 | { return _M_param.b(); } |
3115 | |
3116 | /** |
3117 | * @brief Returns the parameter set of the distribution. |
3118 | */ |
3119 | param_type |
3120 | param() const |
3121 | { return _M_param; } |
3122 | |
3123 | /** |
3124 | * @brief Sets the parameter set of the distribution. |
3125 | * @param __param The new parameter set of the distribution. |
3126 | */ |
3127 | void |
3128 | param(const param_type& __param) |
3129 | { _M_param = __param; } |
3130 | |
3131 | /** |
3132 | * @brief Returns the greatest lower bound value of the distribution. |
3133 | */ |
3134 | result_type |
3135 | min() const |
3136 | { return std::numeric_limits<result_type>::lowest(); } |
3137 | |
3138 | /** |
3139 | * @brief Returns the least upper bound value of the distribution. |
3140 | */ |
3141 | result_type |
3142 | max() const |
3143 | { return std::numeric_limits<result_type>::max(); } |
3144 | |
3145 | /** |
3146 | * @brief Generating functions. |
3147 | */ |
3148 | template<typename _UniformRandomNumberGenerator> |
3149 | result_type |
3150 | operator()(_UniformRandomNumberGenerator& __urng) |
3151 | { return this->operator()(__urng, _M_param); } |
3152 | |
3153 | template<typename _UniformRandomNumberGenerator> |
3154 | result_type |
3155 | operator()(_UniformRandomNumberGenerator& __urng, |
3156 | const param_type& __p); |
3157 | |
3158 | template<typename _ForwardIterator, |
3159 | typename _UniformRandomNumberGenerator> |
3160 | void |
3161 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
3162 | _UniformRandomNumberGenerator& __urng) |
3163 | { this->__generate(__f, __t, __urng, _M_param); } |
3164 | |
3165 | template<typename _ForwardIterator, |
3166 | typename _UniformRandomNumberGenerator> |
3167 | void |
3168 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
3169 | _UniformRandomNumberGenerator& __urng, |
3170 | const param_type& __p) |
3171 | { this->__generate_impl(__f, __t, __urng, __p); } |
3172 | |
3173 | template<typename _UniformRandomNumberGenerator> |
3174 | void |
3175 | __generate(result_type* __f, result_type* __t, |
3176 | _UniformRandomNumberGenerator& __urng, |
3177 | const param_type& __p) |
3178 | { this->__generate_impl(__f, __t, __urng, __p); } |
3179 | |
3180 | /** |
3181 | * @brief Return true if two Cauchy distributions have |
3182 | * the same parameters. |
3183 | */ |
3184 | friend bool |
3185 | operator==(const cauchy_distribution& __d1, |
3186 | const cauchy_distribution& __d2) |
3187 | { return __d1._M_param == __d2._M_param; } |
3188 | |
3189 | private: |
3190 | template<typename _ForwardIterator, |
3191 | typename _UniformRandomNumberGenerator> |
3192 | void |
3193 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
3194 | _UniformRandomNumberGenerator& __urng, |
3195 | const param_type& __p); |
3196 | |
3197 | param_type _M_param; |
3198 | }; |
3199 | |
3200 | #if __cpp_impl_three_way_comparison < 201907L |
3201 | /** |
3202 | * @brief Return true if two Cauchy distributions have |
3203 | * different parameters. |
3204 | */ |
3205 | template<typename _RealType> |
3206 | inline bool |
3207 | operator!=(const std::cauchy_distribution<_RealType>& __d1, |
3208 | const std::cauchy_distribution<_RealType>& __d2) |
3209 | { return !(__d1 == __d2); } |
3210 | #endif |
3211 | |
3212 | /** |
3213 | * @brief Inserts a %cauchy_distribution random number distribution |
3214 | * @p __x into the output stream @p __os. |
3215 | * |
3216 | * @param __os An output stream. |
3217 | * @param __x A %cauchy_distribution random number distribution. |
3218 | * |
3219 | * @returns The output stream with the state of @p __x inserted or in |
3220 | * an error state. |
3221 | */ |
3222 | template<typename _RealType, typename _CharT, typename _Traits> |
3223 | std::basic_ostream<_CharT, _Traits>& |
3224 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
3225 | const std::cauchy_distribution<_RealType>& __x); |
3226 | |
3227 | /** |
3228 | * @brief Extracts a %cauchy_distribution random number distribution |
3229 | * @p __x from the input stream @p __is. |
3230 | * |
3231 | * @param __is An input stream. |
3232 | * @param __x A %cauchy_distribution random number |
3233 | * generator engine. |
3234 | * |
3235 | * @returns The input stream with @p __x extracted or in an error state. |
3236 | */ |
3237 | template<typename _RealType, typename _CharT, typename _Traits> |
3238 | std::basic_istream<_CharT, _Traits>& |
3239 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
3240 | std::cauchy_distribution<_RealType>& __x); |
3241 | |
3242 | |
3243 | /** |
3244 | * @brief A fisher_f_distribution random number distribution. |
3245 | * |
3246 | * The formula for the normal probability mass function is |
3247 | * @f[ |
3248 | * p(x|m,n) = \frac{\Gamma((m+n)/2)}{\Gamma(m/2)\Gamma(n/2)} |
3249 | * (\frac{m}{n})^{m/2} x^{(m/2)-1} |
3250 | * (1 + \frac{mx}{n})^{-(m+n)/2} |
3251 | * @f] |
3252 | * |
3253 | * @headerfile random |
3254 | * @since C++11 |
3255 | */ |
3256 | template<typename _RealType = double> |
3257 | class fisher_f_distribution |
3258 | { |
3259 | static_assert(std::is_floating_point<_RealType>::value, |
3260 | "result_type must be a floating point type" ); |
3261 | |
3262 | public: |
3263 | /** The type of the range of the distribution. */ |
3264 | typedef _RealType result_type; |
3265 | |
3266 | /** Parameter type. */ |
3267 | struct param_type |
3268 | { |
3269 | typedef fisher_f_distribution<_RealType> distribution_type; |
3270 | |
3271 | param_type() : param_type(1) { } |
3272 | |
3273 | explicit |
3274 | param_type(_RealType __m, _RealType __n = _RealType(1)) |
3275 | : _M_m(__m), _M_n(__n) |
3276 | { } |
3277 | |
3278 | _RealType |
3279 | m() const |
3280 | { return _M_m; } |
3281 | |
3282 | _RealType |
3283 | n() const |
3284 | { return _M_n; } |
3285 | |
3286 | friend bool |
3287 | operator==(const param_type& __p1, const param_type& __p2) |
3288 | { return __p1._M_m == __p2._M_m && __p1._M_n == __p2._M_n; } |
3289 | |
3290 | #if __cpp_impl_three_way_comparison < 201907L |
3291 | friend bool |
3292 | operator!=(const param_type& __p1, const param_type& __p2) |
3293 | { return !(__p1 == __p2); } |
3294 | #endif |
3295 | |
3296 | private: |
3297 | _RealType _M_m; |
3298 | _RealType _M_n; |
3299 | }; |
3300 | |
3301 | fisher_f_distribution() : fisher_f_distribution(1.0) { } |
3302 | |
3303 | explicit |
3304 | fisher_f_distribution(_RealType __m, |
3305 | _RealType __n = _RealType(1)) |
3306 | : _M_param(__m, __n), _M_gd_x(__m / 2), _M_gd_y(__n / 2) |
3307 | { } |
3308 | |
3309 | explicit |
3310 | fisher_f_distribution(const param_type& __p) |
3311 | : _M_param(__p), _M_gd_x(__p.m() / 2), _M_gd_y(__p.n() / 2) |
3312 | { } |
3313 | |
3314 | /** |
3315 | * @brief Resets the distribution state. |
3316 | */ |
3317 | void |
3318 | reset() |
3319 | { |
3320 | _M_gd_x.reset(); |
3321 | _M_gd_y.reset(); |
3322 | } |
3323 | |
3324 | /** |
3325 | * |
3326 | */ |
3327 | _RealType |
3328 | m() const |
3329 | { return _M_param.m(); } |
3330 | |
3331 | _RealType |
3332 | n() const |
3333 | { return _M_param.n(); } |
3334 | |
3335 | /** |
3336 | * @brief Returns the parameter set of the distribution. |
3337 | */ |
3338 | param_type |
3339 | param() const |
3340 | { return _M_param; } |
3341 | |
3342 | /** |
3343 | * @brief Sets the parameter set of the distribution. |
3344 | * @param __param The new parameter set of the distribution. |
3345 | */ |
3346 | void |
3347 | param(const param_type& __param) |
3348 | { _M_param = __param; } |
3349 | |
3350 | /** |
3351 | * @brief Returns the greatest lower bound value of the distribution. |
3352 | */ |
3353 | result_type |
3354 | min() const |
3355 | { return result_type(0); } |
3356 | |
3357 | /** |
3358 | * @brief Returns the least upper bound value of the distribution. |
3359 | */ |
3360 | result_type |
3361 | max() const |
3362 | { return std::numeric_limits<result_type>::max(); } |
3363 | |
3364 | /** |
3365 | * @brief Generating functions. |
3366 | */ |
3367 | template<typename _UniformRandomNumberGenerator> |
3368 | result_type |
3369 | operator()(_UniformRandomNumberGenerator& __urng) |
3370 | { return (_M_gd_x(__urng) * n()) / (_M_gd_y(__urng) * m()); } |
3371 | |
3372 | template<typename _UniformRandomNumberGenerator> |
3373 | result_type |
3374 | operator()(_UniformRandomNumberGenerator& __urng, |
3375 | const param_type& __p) |
3376 | { |
3377 | typedef typename std::gamma_distribution<result_type>::param_type |
3378 | param_type; |
3379 | return ((_M_gd_x(__urng, param_type(__p.m() / 2)) * n()) |
3380 | / (_M_gd_y(__urng, param_type(__p.n() / 2)) * m())); |
3381 | } |
3382 | |
3383 | template<typename _ForwardIterator, |
3384 | typename _UniformRandomNumberGenerator> |
3385 | void |
3386 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
3387 | _UniformRandomNumberGenerator& __urng) |
3388 | { this->__generate_impl(__f, __t, __urng); } |
3389 | |
3390 | template<typename _ForwardIterator, |
3391 | typename _UniformRandomNumberGenerator> |
3392 | void |
3393 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
3394 | _UniformRandomNumberGenerator& __urng, |
3395 | const param_type& __p) |
3396 | { this->__generate_impl(__f, __t, __urng, __p); } |
3397 | |
3398 | template<typename _UniformRandomNumberGenerator> |
3399 | void |
3400 | __generate(result_type* __f, result_type* __t, |
3401 | _UniformRandomNumberGenerator& __urng) |
3402 | { this->__generate_impl(__f, __t, __urng); } |
3403 | |
3404 | template<typename _UniformRandomNumberGenerator> |
3405 | void |
3406 | __generate(result_type* __f, result_type* __t, |
3407 | _UniformRandomNumberGenerator& __urng, |
3408 | const param_type& __p) |
3409 | { this->__generate_impl(__f, __t, __urng, __p); } |
3410 | |
3411 | /** |
3412 | * @brief Return true if two Fisher f distributions have |
3413 | * the same parameters and the sequences that would |
3414 | * be generated are equal. |
3415 | */ |
3416 | friend bool |
3417 | operator==(const fisher_f_distribution& __d1, |
3418 | const fisher_f_distribution& __d2) |
3419 | { return (__d1._M_param == __d2._M_param |
3420 | && __d1._M_gd_x == __d2._M_gd_x |
3421 | && __d1._M_gd_y == __d2._M_gd_y); } |
3422 | |
3423 | /** |
3424 | * @brief Inserts a %fisher_f_distribution random number distribution |
3425 | * @p __x into the output stream @p __os. |
3426 | * |
3427 | * @param __os An output stream. |
3428 | * @param __x A %fisher_f_distribution random number distribution. |
3429 | * |
3430 | * @returns The output stream with the state of @p __x inserted or in |
3431 | * an error state. |
3432 | */ |
3433 | template<typename _RealType1, typename _CharT, typename _Traits> |
3434 | friend std::basic_ostream<_CharT, _Traits>& |
3435 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
3436 | const std::fisher_f_distribution<_RealType1>& __x); |
3437 | |
3438 | /** |
3439 | * @brief Extracts a %fisher_f_distribution random number distribution |
3440 | * @p __x from the input stream @p __is. |
3441 | * |
3442 | * @param __is An input stream. |
3443 | * @param __x A %fisher_f_distribution random number |
3444 | * generator engine. |
3445 | * |
3446 | * @returns The input stream with @p __x extracted or in an error state. |
3447 | */ |
3448 | template<typename _RealType1, typename _CharT, typename _Traits> |
3449 | friend std::basic_istream<_CharT, _Traits>& |
3450 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
3451 | std::fisher_f_distribution<_RealType1>& __x); |
3452 | |
3453 | private: |
3454 | template<typename _ForwardIterator, |
3455 | typename _UniformRandomNumberGenerator> |
3456 | void |
3457 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
3458 | _UniformRandomNumberGenerator& __urng); |
3459 | |
3460 | template<typename _ForwardIterator, |
3461 | typename _UniformRandomNumberGenerator> |
3462 | void |
3463 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
3464 | _UniformRandomNumberGenerator& __urng, |
3465 | const param_type& __p); |
3466 | |
3467 | param_type _M_param; |
3468 | |
3469 | std::gamma_distribution<result_type> _M_gd_x, _M_gd_y; |
3470 | }; |
3471 | |
3472 | #if __cpp_impl_three_way_comparison < 201907L |
3473 | /** |
3474 | * @brief Return true if two Fisher f distributions are different. |
3475 | */ |
3476 | template<typename _RealType> |
3477 | inline bool |
3478 | operator!=(const std::fisher_f_distribution<_RealType>& __d1, |
3479 | const std::fisher_f_distribution<_RealType>& __d2) |
3480 | { return !(__d1 == __d2); } |
3481 | #endif |
3482 | |
3483 | /** |
3484 | * @brief A student_t_distribution random number distribution. |
3485 | * |
3486 | * The formula for the normal probability mass function is: |
3487 | * @f[ |
3488 | * p(x|n) = \frac{1}{\sqrt(n\pi)} \frac{\Gamma((n+1)/2)}{\Gamma(n/2)} |
3489 | * (1 + \frac{x^2}{n}) ^{-(n+1)/2} |
3490 | * @f] |
3491 | * |
3492 | * @headerfile random |
3493 | * @since C++11 |
3494 | */ |
3495 | template<typename _RealType = double> |
3496 | class student_t_distribution |
3497 | { |
3498 | static_assert(std::is_floating_point<_RealType>::value, |
3499 | "result_type must be a floating point type" ); |
3500 | |
3501 | public: |
3502 | /** The type of the range of the distribution. */ |
3503 | typedef _RealType result_type; |
3504 | |
3505 | /** Parameter type. */ |
3506 | struct param_type |
3507 | { |
3508 | typedef student_t_distribution<_RealType> distribution_type; |
3509 | |
3510 | param_type() : param_type(1) { } |
3511 | |
3512 | explicit |
3513 | param_type(_RealType __n) |
3514 | : _M_n(__n) |
3515 | { } |
3516 | |
3517 | _RealType |
3518 | n() const |
3519 | { return _M_n; } |
3520 | |
3521 | friend bool |
3522 | operator==(const param_type& __p1, const param_type& __p2) |
3523 | { return __p1._M_n == __p2._M_n; } |
3524 | |
3525 | #if __cpp_impl_three_way_comparison < 201907L |
3526 | friend bool |
3527 | operator!=(const param_type& __p1, const param_type& __p2) |
3528 | { return !(__p1 == __p2); } |
3529 | #endif |
3530 | |
3531 | private: |
3532 | _RealType _M_n; |
3533 | }; |
3534 | |
3535 | student_t_distribution() : student_t_distribution(1.0) { } |
3536 | |
3537 | explicit |
3538 | student_t_distribution(_RealType __n) |
3539 | : _M_param(__n), _M_nd(), _M_gd(__n / 2, 2) |
3540 | { } |
3541 | |
3542 | explicit |
3543 | student_t_distribution(const param_type& __p) |
3544 | : _M_param(__p), _M_nd(), _M_gd(__p.n() / 2, 2) |
3545 | { } |
3546 | |
3547 | /** |
3548 | * @brief Resets the distribution state. |
3549 | */ |
3550 | void |
3551 | reset() |
3552 | { |
3553 | _M_nd.reset(); |
3554 | _M_gd.reset(); |
3555 | } |
3556 | |
3557 | /** |
3558 | * |
3559 | */ |
3560 | _RealType |
3561 | n() const |
3562 | { return _M_param.n(); } |
3563 | |
3564 | /** |
3565 | * @brief Returns the parameter set of the distribution. |
3566 | */ |
3567 | param_type |
3568 | param() const |
3569 | { return _M_param; } |
3570 | |
3571 | /** |
3572 | * @brief Sets the parameter set of the distribution. |
3573 | * @param __param The new parameter set of the distribution. |
3574 | */ |
3575 | void |
3576 | param(const param_type& __param) |
3577 | { _M_param = __param; } |
3578 | |
3579 | /** |
3580 | * @brief Returns the greatest lower bound value of the distribution. |
3581 | */ |
3582 | result_type |
3583 | min() const |
3584 | { return std::numeric_limits<result_type>::lowest(); } |
3585 | |
3586 | /** |
3587 | * @brief Returns the least upper bound value of the distribution. |
3588 | */ |
3589 | result_type |
3590 | max() const |
3591 | { return std::numeric_limits<result_type>::max(); } |
3592 | |
3593 | /** |
3594 | * @brief Generating functions. |
3595 | */ |
3596 | template<typename _UniformRandomNumberGenerator> |
3597 | result_type |
3598 | operator()(_UniformRandomNumberGenerator& __urng) |
3599 | { return _M_nd(__urng) * std::sqrt(n() / _M_gd(__urng)); } |
3600 | |
3601 | template<typename _UniformRandomNumberGenerator> |
3602 | result_type |
3603 | operator()(_UniformRandomNumberGenerator& __urng, |
3604 | const param_type& __p) |
3605 | { |
3606 | typedef typename std::gamma_distribution<result_type>::param_type |
3607 | param_type; |
3608 | |
3609 | const result_type __g = _M_gd(__urng, param_type(__p.n() / 2, 2)); |
3610 | return _M_nd(__urng) * std::sqrt(__p.n() / __g); |
3611 | } |
3612 | |
3613 | template<typename _ForwardIterator, |
3614 | typename _UniformRandomNumberGenerator> |
3615 | void |
3616 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
3617 | _UniformRandomNumberGenerator& __urng) |
3618 | { this->__generate_impl(__f, __t, __urng); } |
3619 | |
3620 | template<typename _ForwardIterator, |
3621 | typename _UniformRandomNumberGenerator> |
3622 | void |
3623 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
3624 | _UniformRandomNumberGenerator& __urng, |
3625 | const param_type& __p) |
3626 | { this->__generate_impl(__f, __t, __urng, __p); } |
3627 | |
3628 | template<typename _UniformRandomNumberGenerator> |
3629 | void |
3630 | __generate(result_type* __f, result_type* __t, |
3631 | _UniformRandomNumberGenerator& __urng) |
3632 | { this->__generate_impl(__f, __t, __urng); } |
3633 | |
3634 | template<typename _UniformRandomNumberGenerator> |
3635 | void |
3636 | __generate(result_type* __f, result_type* __t, |
3637 | _UniformRandomNumberGenerator& __urng, |
3638 | const param_type& __p) |
3639 | { this->__generate_impl(__f, __t, __urng, __p); } |
3640 | |
3641 | /** |
3642 | * @brief Return true if two Student t distributions have |
3643 | * the same parameters and the sequences that would |
3644 | * be generated are equal. |
3645 | */ |
3646 | friend bool |
3647 | operator==(const student_t_distribution& __d1, |
3648 | const student_t_distribution& __d2) |
3649 | { return (__d1._M_param == __d2._M_param |
3650 | && __d1._M_nd == __d2._M_nd && __d1._M_gd == __d2._M_gd); } |
3651 | |
3652 | /** |
3653 | * @brief Inserts a %student_t_distribution random number distribution |
3654 | * @p __x into the output stream @p __os. |
3655 | * |
3656 | * @param __os An output stream. |
3657 | * @param __x A %student_t_distribution random number distribution. |
3658 | * |
3659 | * @returns The output stream with the state of @p __x inserted or in |
3660 | * an error state. |
3661 | */ |
3662 | template<typename _RealType1, typename _CharT, typename _Traits> |
3663 | friend std::basic_ostream<_CharT, _Traits>& |
3664 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
3665 | const std::student_t_distribution<_RealType1>& __x); |
3666 | |
3667 | /** |
3668 | * @brief Extracts a %student_t_distribution random number distribution |
3669 | * @p __x from the input stream @p __is. |
3670 | * |
3671 | * @param __is An input stream. |
3672 | * @param __x A %student_t_distribution random number |
3673 | * generator engine. |
3674 | * |
3675 | * @returns The input stream with @p __x extracted or in an error state. |
3676 | */ |
3677 | template<typename _RealType1, typename _CharT, typename _Traits> |
3678 | friend std::basic_istream<_CharT, _Traits>& |
3679 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
3680 | std::student_t_distribution<_RealType1>& __x); |
3681 | |
3682 | private: |
3683 | template<typename _ForwardIterator, |
3684 | typename _UniformRandomNumberGenerator> |
3685 | void |
3686 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
3687 | _UniformRandomNumberGenerator& __urng); |
3688 | template<typename _ForwardIterator, |
3689 | typename _UniformRandomNumberGenerator> |
3690 | void |
3691 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
3692 | _UniformRandomNumberGenerator& __urng, |
3693 | const param_type& __p); |
3694 | |
3695 | param_type _M_param; |
3696 | |
3697 | std::normal_distribution<result_type> _M_nd; |
3698 | std::gamma_distribution<result_type> _M_gd; |
3699 | }; |
3700 | |
3701 | #if __cpp_impl_three_way_comparison < 201907L |
3702 | /** |
3703 | * @brief Return true if two Student t distributions are different. |
3704 | */ |
3705 | template<typename _RealType> |
3706 | inline bool |
3707 | operator!=(const std::student_t_distribution<_RealType>& __d1, |
3708 | const std::student_t_distribution<_RealType>& __d2) |
3709 | { return !(__d1 == __d2); } |
3710 | #endif |
3711 | |
3712 | /// @} group random_distributions_normal |
3713 | |
3714 | /** |
3715 | * @addtogroup random_distributions_bernoulli Bernoulli Distributions |
3716 | * @ingroup random_distributions |
3717 | * @{ |
3718 | */ |
3719 | |
3720 | /** |
3721 | * @brief A Bernoulli random number distribution. |
3722 | * |
3723 | * Generates a sequence of true and false values with likelihood @f$p@f$ |
3724 | * that true will come up and @f$(1 - p)@f$ that false will appear. |
3725 | * |
3726 | * @headerfile random |
3727 | * @since C++11 |
3728 | */ |
3729 | class bernoulli_distribution |
3730 | { |
3731 | public: |
3732 | /** The type of the range of the distribution. */ |
3733 | typedef bool result_type; |
3734 | |
3735 | /** Parameter type. */ |
3736 | struct param_type |
3737 | { |
3738 | typedef bernoulli_distribution distribution_type; |
3739 | |
3740 | param_type() : param_type(0.5) { } |
3741 | |
3742 | explicit |
3743 | param_type(double __p) |
3744 | : _M_p(__p) |
3745 | { |
3746 | __glibcxx_assert((_M_p >= 0.0) && (_M_p <= 1.0)); |
3747 | } |
3748 | |
3749 | double |
3750 | p() const |
3751 | { return _M_p; } |
3752 | |
3753 | friend bool |
3754 | operator==(const param_type& __p1, const param_type& __p2) |
3755 | { return __p1._M_p == __p2._M_p; } |
3756 | |
3757 | #if __cpp_impl_three_way_comparison < 201907L |
3758 | friend bool |
3759 | operator!=(const param_type& __p1, const param_type& __p2) |
3760 | { return !(__p1 == __p2); } |
3761 | #endif |
3762 | |
3763 | private: |
3764 | double _M_p; |
3765 | }; |
3766 | |
3767 | public: |
3768 | /** |
3769 | * @brief Constructs a Bernoulli distribution with likelihood 0.5. |
3770 | */ |
3771 | bernoulli_distribution() : bernoulli_distribution(0.5) { } |
3772 | |
3773 | /** |
3774 | * @brief Constructs a Bernoulli distribution with likelihood @p p. |
3775 | * |
3776 | * @param __p [IN] The likelihood of a true result being returned. |
3777 | * Must be in the interval @f$[0, 1]@f$. |
3778 | */ |
3779 | explicit |
3780 | bernoulli_distribution(double __p) |
3781 | : _M_param(__p) |
3782 | { } |
3783 | |
3784 | explicit |
3785 | bernoulli_distribution(const param_type& __p) |
3786 | : _M_param(__p) |
3787 | { } |
3788 | |
3789 | /** |
3790 | * @brief Resets the distribution state. |
3791 | * |
3792 | * Does nothing for a Bernoulli distribution. |
3793 | */ |
3794 | void |
3795 | reset() { } |
3796 | |
3797 | /** |
3798 | * @brief Returns the @p p parameter of the distribution. |
3799 | */ |
3800 | double |
3801 | p() const |
3802 | { return _M_param.p(); } |
3803 | |
3804 | /** |
3805 | * @brief Returns the parameter set of the distribution. |
3806 | */ |
3807 | param_type |
3808 | param() const |
3809 | { return _M_param; } |
3810 | |
3811 | /** |
3812 | * @brief Sets the parameter set of the distribution. |
3813 | * @param __param The new parameter set of the distribution. |
3814 | */ |
3815 | void |
3816 | param(const param_type& __param) |
3817 | { _M_param = __param; } |
3818 | |
3819 | /** |
3820 | * @brief Returns the greatest lower bound value of the distribution. |
3821 | */ |
3822 | result_type |
3823 | min() const |
3824 | { return std::numeric_limits<result_type>::min(); } |
3825 | |
3826 | /** |
3827 | * @brief Returns the least upper bound value of the distribution. |
3828 | */ |
3829 | result_type |
3830 | max() const |
3831 | { return std::numeric_limits<result_type>::max(); } |
3832 | |
3833 | /** |
3834 | * @brief Generating functions. |
3835 | */ |
3836 | template<typename _UniformRandomNumberGenerator> |
3837 | result_type |
3838 | operator()(_UniformRandomNumberGenerator& __urng) |
3839 | { return this->operator()(__urng, _M_param); } |
3840 | |
3841 | template<typename _UniformRandomNumberGenerator> |
3842 | result_type |
3843 | operator()(_UniformRandomNumberGenerator& __urng, |
3844 | const param_type& __p) |
3845 | { |
3846 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> |
3847 | __aurng(__urng); |
3848 | if ((__aurng() - __aurng.min()) |
3849 | < __p.p() * (__aurng.max() - __aurng.min())) |
3850 | return true; |
3851 | return false; |
3852 | } |
3853 | |
3854 | template<typename _ForwardIterator, |
3855 | typename _UniformRandomNumberGenerator> |
3856 | void |
3857 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
3858 | _UniformRandomNumberGenerator& __urng) |
3859 | { this->__generate(__f, __t, __urng, _M_param); } |
3860 | |
3861 | template<typename _ForwardIterator, |
3862 | typename _UniformRandomNumberGenerator> |
3863 | void |
3864 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
3865 | _UniformRandomNumberGenerator& __urng, const param_type& __p) |
3866 | { this->__generate_impl(__f, __t, __urng, __p); } |
3867 | |
3868 | template<typename _UniformRandomNumberGenerator> |
3869 | void |
3870 | __generate(result_type* __f, result_type* __t, |
3871 | _UniformRandomNumberGenerator& __urng, |
3872 | const param_type& __p) |
3873 | { this->__generate_impl(__f, __t, __urng, __p); } |
3874 | |
3875 | /** |
3876 | * @brief Return true if two Bernoulli distributions have |
3877 | * the same parameters. |
3878 | */ |
3879 | friend bool |
3880 | operator==(const bernoulli_distribution& __d1, |
3881 | const bernoulli_distribution& __d2) |
3882 | { return __d1._M_param == __d2._M_param; } |
3883 | |
3884 | private: |
3885 | template<typename _ForwardIterator, |
3886 | typename _UniformRandomNumberGenerator> |
3887 | void |
3888 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
3889 | _UniformRandomNumberGenerator& __urng, |
3890 | const param_type& __p); |
3891 | |
3892 | param_type _M_param; |
3893 | }; |
3894 | |
3895 | #if __cpp_impl_three_way_comparison < 201907L |
3896 | /** |
3897 | * @brief Return true if two Bernoulli distributions have |
3898 | * different parameters. |
3899 | */ |
3900 | inline bool |
3901 | operator!=(const std::bernoulli_distribution& __d1, |
3902 | const std::bernoulli_distribution& __d2) |
3903 | { return !(__d1 == __d2); } |
3904 | #endif |
3905 | |
3906 | /** |
3907 | * @brief Inserts a %bernoulli_distribution random number distribution |
3908 | * @p __x into the output stream @p __os. |
3909 | * |
3910 | * @param __os An output stream. |
3911 | * @param __x A %bernoulli_distribution random number distribution. |
3912 | * |
3913 | * @returns The output stream with the state of @p __x inserted or in |
3914 | * an error state. |
3915 | */ |
3916 | template<typename _CharT, typename _Traits> |
3917 | std::basic_ostream<_CharT, _Traits>& |
3918 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
3919 | const std::bernoulli_distribution& __x); |
3920 | |
3921 | /** |
3922 | * @brief Extracts a %bernoulli_distribution random number distribution |
3923 | * @p __x from the input stream @p __is. |
3924 | * |
3925 | * @param __is An input stream. |
3926 | * @param __x A %bernoulli_distribution random number generator engine. |
3927 | * |
3928 | * @returns The input stream with @p __x extracted or in an error state. |
3929 | */ |
3930 | template<typename _CharT, typename _Traits> |
3931 | inline std::basic_istream<_CharT, _Traits>& |
3932 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
3933 | std::bernoulli_distribution& __x) |
3934 | { |
3935 | double __p; |
3936 | if (__is >> __p) |
3937 | __x.param(param: bernoulli_distribution::param_type(__p)); |
3938 | return __is; |
3939 | } |
3940 | |
3941 | |
3942 | /** |
3943 | * @brief A discrete binomial random number distribution. |
3944 | * |
3945 | * The formula for the binomial probability density function is |
3946 | * @f$p(i|t,p) = \binom{t}{i} p^i (1 - p)^{t - i}@f$ where @f$t@f$ |
3947 | * and @f$p@f$ are the parameters of the distribution. |
3948 | * |
3949 | * @headerfile random |
3950 | * @since C++11 |
3951 | */ |
3952 | template<typename _IntType = int> |
3953 | class binomial_distribution |
3954 | { |
3955 | static_assert(std::is_integral<_IntType>::value, |
3956 | "result_type must be an integral type" ); |
3957 | |
3958 | public: |
3959 | /** The type of the range of the distribution. */ |
3960 | typedef _IntType result_type; |
3961 | |
3962 | /** Parameter type. */ |
3963 | struct param_type |
3964 | { |
3965 | typedef binomial_distribution<_IntType> distribution_type; |
3966 | friend class binomial_distribution<_IntType>; |
3967 | |
3968 | param_type() : param_type(1) { } |
3969 | |
3970 | explicit |
3971 | param_type(_IntType __t, double __p = 0.5) |
3972 | : _M_t(__t), _M_p(__p) |
3973 | { |
3974 | __glibcxx_assert((_M_t >= _IntType(0)) |
3975 | && (_M_p >= 0.0) |
3976 | && (_M_p <= 1.0)); |
3977 | _M_initialize(); |
3978 | } |
3979 | |
3980 | _IntType |
3981 | t() const |
3982 | { return _M_t; } |
3983 | |
3984 | double |
3985 | p() const |
3986 | { return _M_p; } |
3987 | |
3988 | friend bool |
3989 | operator==(const param_type& __p1, const param_type& __p2) |
3990 | { return __p1._M_t == __p2._M_t && __p1._M_p == __p2._M_p; } |
3991 | |
3992 | #if __cpp_impl_three_way_comparison < 201907L |
3993 | friend bool |
3994 | operator!=(const param_type& __p1, const param_type& __p2) |
3995 | { return !(__p1 == __p2); } |
3996 | #endif |
3997 | |
3998 | private: |
3999 | void |
4000 | _M_initialize(); |
4001 | |
4002 | _IntType _M_t; |
4003 | double _M_p; |
4004 | |
4005 | double _M_q; |
4006 | #if _GLIBCXX_USE_C99_MATH_FUNCS |
4007 | double _M_d1, _M_d2, _M_s1, _M_s2, _M_c, |
4008 | _M_a1, _M_a123, _M_s, _M_lf, _M_lp1p; |
4009 | #endif |
4010 | bool _M_easy; |
4011 | }; |
4012 | |
4013 | // constructors and member functions |
4014 | |
4015 | binomial_distribution() : binomial_distribution(1) { } |
4016 | |
4017 | explicit |
4018 | binomial_distribution(_IntType __t, double __p = 0.5) |
4019 | : _M_param(__t, __p), _M_nd() |
4020 | { } |
4021 | |
4022 | explicit |
4023 | binomial_distribution(const param_type& __p) |
4024 | : _M_param(__p), _M_nd() |
4025 | { } |
4026 | |
4027 | /** |
4028 | * @brief Resets the distribution state. |
4029 | */ |
4030 | void |
4031 | reset() |
4032 | { _M_nd.reset(); } |
4033 | |
4034 | /** |
4035 | * @brief Returns the distribution @p t parameter. |
4036 | */ |
4037 | _IntType |
4038 | t() const |
4039 | { return _M_param.t(); } |
4040 | |
4041 | /** |
4042 | * @brief Returns the distribution @p p parameter. |
4043 | */ |
4044 | double |
4045 | p() const |
4046 | { return _M_param.p(); } |
4047 | |
4048 | /** |
4049 | * @brief Returns the parameter set of the distribution. |
4050 | */ |
4051 | param_type |
4052 | param() const |
4053 | { return _M_param; } |
4054 | |
4055 | /** |
4056 | * @brief Sets the parameter set of the distribution. |
4057 | * @param __param The new parameter set of the distribution. |
4058 | */ |
4059 | void |
4060 | param(const param_type& __param) |
4061 | { _M_param = __param; } |
4062 | |
4063 | /** |
4064 | * @brief Returns the greatest lower bound value of the distribution. |
4065 | */ |
4066 | result_type |
4067 | min() const |
4068 | { return 0; } |
4069 | |
4070 | /** |
4071 | * @brief Returns the least upper bound value of the distribution. |
4072 | */ |
4073 | result_type |
4074 | max() const |
4075 | { return _M_param.t(); } |
4076 | |
4077 | /** |
4078 | * @brief Generating functions. |
4079 | */ |
4080 | template<typename _UniformRandomNumberGenerator> |
4081 | result_type |
4082 | operator()(_UniformRandomNumberGenerator& __urng) |
4083 | { return this->operator()(__urng, _M_param); } |
4084 | |
4085 | template<typename _UniformRandomNumberGenerator> |
4086 | result_type |
4087 | operator()(_UniformRandomNumberGenerator& __urng, |
4088 | const param_type& __p); |
4089 | |
4090 | template<typename _ForwardIterator, |
4091 | typename _UniformRandomNumberGenerator> |
4092 | void |
4093 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
4094 | _UniformRandomNumberGenerator& __urng) |
4095 | { this->__generate(__f, __t, __urng, _M_param); } |
4096 | |
4097 | template<typename _ForwardIterator, |
4098 | typename _UniformRandomNumberGenerator> |
4099 | void |
4100 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
4101 | _UniformRandomNumberGenerator& __urng, |
4102 | const param_type& __p) |
4103 | { this->__generate_impl(__f, __t, __urng, __p); } |
4104 | |
4105 | template<typename _UniformRandomNumberGenerator> |
4106 | void |
4107 | __generate(result_type* __f, result_type* __t, |
4108 | _UniformRandomNumberGenerator& __urng, |
4109 | const param_type& __p) |
4110 | { this->__generate_impl(__f, __t, __urng, __p); } |
4111 | |
4112 | /** |
4113 | * @brief Return true if two binomial distributions have |
4114 | * the same parameters and the sequences that would |
4115 | * be generated are equal. |
4116 | */ |
4117 | friend bool |
4118 | operator==(const binomial_distribution& __d1, |
4119 | const binomial_distribution& __d2) |
4120 | #ifdef _GLIBCXX_USE_C99_MATH_FUNCS |
4121 | { return __d1._M_param == __d2._M_param && __d1._M_nd == __d2._M_nd; } |
4122 | #else |
4123 | { return __d1._M_param == __d2._M_param; } |
4124 | #endif |
4125 | |
4126 | /** |
4127 | * @brief Inserts a %binomial_distribution random number distribution |
4128 | * @p __x into the output stream @p __os. |
4129 | * |
4130 | * @param __os An output stream. |
4131 | * @param __x A %binomial_distribution random number distribution. |
4132 | * |
4133 | * @returns The output stream with the state of @p __x inserted or in |
4134 | * an error state. |
4135 | */ |
4136 | template<typename _IntType1, |
4137 | typename _CharT, typename _Traits> |
4138 | friend std::basic_ostream<_CharT, _Traits>& |
4139 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
4140 | const std::binomial_distribution<_IntType1>& __x); |
4141 | |
4142 | /** |
4143 | * @brief Extracts a %binomial_distribution random number distribution |
4144 | * @p __x from the input stream @p __is. |
4145 | * |
4146 | * @param __is An input stream. |
4147 | * @param __x A %binomial_distribution random number generator engine. |
4148 | * |
4149 | * @returns The input stream with @p __x extracted or in an error |
4150 | * state. |
4151 | */ |
4152 | template<typename _IntType1, |
4153 | typename _CharT, typename _Traits> |
4154 | friend std::basic_istream<_CharT, _Traits>& |
4155 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
4156 | std::binomial_distribution<_IntType1>& __x); |
4157 | |
4158 | private: |
4159 | template<typename _ForwardIterator, |
4160 | typename _UniformRandomNumberGenerator> |
4161 | void |
4162 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
4163 | _UniformRandomNumberGenerator& __urng, |
4164 | const param_type& __p); |
4165 | |
4166 | template<typename _UniformRandomNumberGenerator> |
4167 | result_type |
4168 | _M_waiting(_UniformRandomNumberGenerator& __urng, |
4169 | _IntType __t, double __q); |
4170 | |
4171 | param_type _M_param; |
4172 | |
4173 | // NB: Unused when _GLIBCXX_USE_C99_MATH_FUNCS is undefined. |
4174 | std::normal_distribution<double> _M_nd; |
4175 | }; |
4176 | |
4177 | #if __cpp_impl_three_way_comparison < 201907L |
4178 | /** |
4179 | * @brief Return true if two binomial distributions are different. |
4180 | */ |
4181 | template<typename _IntType> |
4182 | inline bool |
4183 | operator!=(const std::binomial_distribution<_IntType>& __d1, |
4184 | const std::binomial_distribution<_IntType>& __d2) |
4185 | { return !(__d1 == __d2); } |
4186 | #endif |
4187 | |
4188 | /** |
4189 | * @brief A discrete geometric random number distribution. |
4190 | * |
4191 | * The formula for the geometric probability density function is |
4192 | * @f$p(i|p) = p(1 - p)^{i}@f$ where @f$p@f$ is the parameter of the |
4193 | * distribution. |
4194 | * |
4195 | * @headerfile random |
4196 | * @since C++11 |
4197 | */ |
4198 | template<typename _IntType = int> |
4199 | class geometric_distribution |
4200 | { |
4201 | static_assert(std::is_integral<_IntType>::value, |
4202 | "result_type must be an integral type" ); |
4203 | |
4204 | public: |
4205 | /** The type of the range of the distribution. */ |
4206 | typedef _IntType result_type; |
4207 | |
4208 | /** Parameter type. */ |
4209 | struct param_type |
4210 | { |
4211 | typedef geometric_distribution<_IntType> distribution_type; |
4212 | friend class geometric_distribution<_IntType>; |
4213 | |
4214 | param_type() : param_type(0.5) { } |
4215 | |
4216 | explicit |
4217 | param_type(double __p) |
4218 | : _M_p(__p) |
4219 | { |
4220 | __glibcxx_assert((_M_p > 0.0) && (_M_p < 1.0)); |
4221 | _M_initialize(); |
4222 | } |
4223 | |
4224 | double |
4225 | p() const |
4226 | { return _M_p; } |
4227 | |
4228 | friend bool |
4229 | operator==(const param_type& __p1, const param_type& __p2) |
4230 | { return __p1._M_p == __p2._M_p; } |
4231 | |
4232 | #if __cpp_impl_three_way_comparison < 201907L |
4233 | friend bool |
4234 | operator!=(const param_type& __p1, const param_type& __p2) |
4235 | { return !(__p1 == __p2); } |
4236 | #endif |
4237 | |
4238 | private: |
4239 | void |
4240 | _M_initialize() |
4241 | { _M_log_1_p = std::log(x: 1.0 - _M_p); } |
4242 | |
4243 | double _M_p; |
4244 | |
4245 | double _M_log_1_p; |
4246 | }; |
4247 | |
4248 | // constructors and member functions |
4249 | |
4250 | geometric_distribution() : geometric_distribution(0.5) { } |
4251 | |
4252 | explicit |
4253 | geometric_distribution(double __p) |
4254 | : _M_param(__p) |
4255 | { } |
4256 | |
4257 | explicit |
4258 | geometric_distribution(const param_type& __p) |
4259 | : _M_param(__p) |
4260 | { } |
4261 | |
4262 | /** |
4263 | * @brief Resets the distribution state. |
4264 | * |
4265 | * Does nothing for the geometric distribution. |
4266 | */ |
4267 | void |
4268 | reset() { } |
4269 | |
4270 | /** |
4271 | * @brief Returns the distribution parameter @p p. |
4272 | */ |
4273 | double |
4274 | p() const |
4275 | { return _M_param.p(); } |
4276 | |
4277 | /** |
4278 | * @brief Returns the parameter set of the distribution. |
4279 | */ |
4280 | param_type |
4281 | param() const |
4282 | { return _M_param; } |
4283 | |
4284 | /** |
4285 | * @brief Sets the parameter set of the distribution. |
4286 | * @param __param The new parameter set of the distribution. |
4287 | */ |
4288 | void |
4289 | param(const param_type& __param) |
4290 | { _M_param = __param; } |
4291 | |
4292 | /** |
4293 | * @brief Returns the greatest lower bound value of the distribution. |
4294 | */ |
4295 | result_type |
4296 | min() const |
4297 | { return 0; } |
4298 | |
4299 | /** |
4300 | * @brief Returns the least upper bound value of the distribution. |
4301 | */ |
4302 | result_type |
4303 | max() const |
4304 | { return std::numeric_limits<result_type>::max(); } |
4305 | |
4306 | /** |
4307 | * @brief Generating functions. |
4308 | */ |
4309 | template<typename _UniformRandomNumberGenerator> |
4310 | result_type |
4311 | operator()(_UniformRandomNumberGenerator& __urng) |
4312 | { return this->operator()(__urng, _M_param); } |
4313 | |
4314 | template<typename _UniformRandomNumberGenerator> |
4315 | result_type |
4316 | operator()(_UniformRandomNumberGenerator& __urng, |
4317 | const param_type& __p); |
4318 | |
4319 | template<typename _ForwardIterator, |
4320 | typename _UniformRandomNumberGenerator> |
4321 | void |
4322 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
4323 | _UniformRandomNumberGenerator& __urng) |
4324 | { this->__generate(__f, __t, __urng, _M_param); } |
4325 | |
4326 | template<typename _ForwardIterator, |
4327 | typename _UniformRandomNumberGenerator> |
4328 | void |
4329 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
4330 | _UniformRandomNumberGenerator& __urng, |
4331 | const param_type& __p) |
4332 | { this->__generate_impl(__f, __t, __urng, __p); } |
4333 | |
4334 | template<typename _UniformRandomNumberGenerator> |
4335 | void |
4336 | __generate(result_type* __f, result_type* __t, |
4337 | _UniformRandomNumberGenerator& __urng, |
4338 | const param_type& __p) |
4339 | { this->__generate_impl(__f, __t, __urng, __p); } |
4340 | |
4341 | /** |
4342 | * @brief Return true if two geometric distributions have |
4343 | * the same parameters. |
4344 | */ |
4345 | friend bool |
4346 | operator==(const geometric_distribution& __d1, |
4347 | const geometric_distribution& __d2) |
4348 | { return __d1._M_param == __d2._M_param; } |
4349 | |
4350 | private: |
4351 | template<typename _ForwardIterator, |
4352 | typename _UniformRandomNumberGenerator> |
4353 | void |
4354 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
4355 | _UniformRandomNumberGenerator& __urng, |
4356 | const param_type& __p); |
4357 | |
4358 | param_type _M_param; |
4359 | }; |
4360 | |
4361 | #if __cpp_impl_three_way_comparison < 201907L |
4362 | /** |
4363 | * @brief Return true if two geometric distributions have |
4364 | * different parameters. |
4365 | */ |
4366 | template<typename _IntType> |
4367 | inline bool |
4368 | operator!=(const std::geometric_distribution<_IntType>& __d1, |
4369 | const std::geometric_distribution<_IntType>& __d2) |
4370 | { return !(__d1 == __d2); } |
4371 | #endif |
4372 | |
4373 | /** |
4374 | * @brief Inserts a %geometric_distribution random number distribution |
4375 | * @p __x into the output stream @p __os. |
4376 | * |
4377 | * @param __os An output stream. |
4378 | * @param __x A %geometric_distribution random number distribution. |
4379 | * |
4380 | * @returns The output stream with the state of @p __x inserted or in |
4381 | * an error state. |
4382 | */ |
4383 | template<typename _IntType, |
4384 | typename _CharT, typename _Traits> |
4385 | std::basic_ostream<_CharT, _Traits>& |
4386 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
4387 | const std::geometric_distribution<_IntType>& __x); |
4388 | |
4389 | /** |
4390 | * @brief Extracts a %geometric_distribution random number distribution |
4391 | * @p __x from the input stream @p __is. |
4392 | * |
4393 | * @param __is An input stream. |
4394 | * @param __x A %geometric_distribution random number generator engine. |
4395 | * |
4396 | * @returns The input stream with @p __x extracted or in an error state. |
4397 | */ |
4398 | template<typename _IntType, |
4399 | typename _CharT, typename _Traits> |
4400 | std::basic_istream<_CharT, _Traits>& |
4401 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
4402 | std::geometric_distribution<_IntType>& __x); |
4403 | |
4404 | |
4405 | /** |
4406 | * @brief A negative_binomial_distribution random number distribution. |
4407 | * |
4408 | * The formula for the negative binomial probability mass function is |
4409 | * @f$p(i) = \binom{n}{i} p^i (1 - p)^{t - i}@f$ where @f$t@f$ |
4410 | * and @f$p@f$ are the parameters of the distribution. |
4411 | * |
4412 | * @headerfile random |
4413 | * @since C++11 |
4414 | */ |
4415 | template<typename _IntType = int> |
4416 | class negative_binomial_distribution |
4417 | { |
4418 | static_assert(std::is_integral<_IntType>::value, |
4419 | "result_type must be an integral type" ); |
4420 | |
4421 | public: |
4422 | /** The type of the range of the distribution. */ |
4423 | typedef _IntType result_type; |
4424 | |
4425 | /** Parameter type. */ |
4426 | struct param_type |
4427 | { |
4428 | typedef negative_binomial_distribution<_IntType> distribution_type; |
4429 | |
4430 | param_type() : param_type(1) { } |
4431 | |
4432 | explicit |
4433 | param_type(_IntType __k, double __p = 0.5) |
4434 | : _M_k(__k), _M_p(__p) |
4435 | { |
4436 | __glibcxx_assert((_M_k > 0) && (_M_p > 0.0) && (_M_p <= 1.0)); |
4437 | } |
4438 | |
4439 | _IntType |
4440 | k() const |
4441 | { return _M_k; } |
4442 | |
4443 | double |
4444 | p() const |
4445 | { return _M_p; } |
4446 | |
4447 | friend bool |
4448 | operator==(const param_type& __p1, const param_type& __p2) |
4449 | { return __p1._M_k == __p2._M_k && __p1._M_p == __p2._M_p; } |
4450 | |
4451 | #if __cpp_impl_three_way_comparison < 201907L |
4452 | friend bool |
4453 | operator!=(const param_type& __p1, const param_type& __p2) |
4454 | { return !(__p1 == __p2); } |
4455 | #endif |
4456 | |
4457 | private: |
4458 | _IntType _M_k; |
4459 | double _M_p; |
4460 | }; |
4461 | |
4462 | negative_binomial_distribution() : negative_binomial_distribution(1) { } |
4463 | |
4464 | explicit |
4465 | negative_binomial_distribution(_IntType __k, double __p = 0.5) |
4466 | : _M_param(__k, __p), _M_gd(__k, (1.0 - __p) / __p) |
4467 | { } |
4468 | |
4469 | explicit |
4470 | negative_binomial_distribution(const param_type& __p) |
4471 | : _M_param(__p), _M_gd(__p.k(), (1.0 - __p.p()) / __p.p()) |
4472 | { } |
4473 | |
4474 | /** |
4475 | * @brief Resets the distribution state. |
4476 | */ |
4477 | void |
4478 | reset() |
4479 | { _M_gd.reset(); } |
4480 | |
4481 | /** |
4482 | * @brief Return the @f$k@f$ parameter of the distribution. |
4483 | */ |
4484 | _IntType |
4485 | k() const |
4486 | { return _M_param.k(); } |
4487 | |
4488 | /** |
4489 | * @brief Return the @f$p@f$ parameter of the distribution. |
4490 | */ |
4491 | double |
4492 | p() const |
4493 | { return _M_param.p(); } |
4494 | |
4495 | /** |
4496 | * @brief Returns the parameter set of the distribution. |
4497 | */ |
4498 | param_type |
4499 | param() const |
4500 | { return _M_param; } |
4501 | |
4502 | /** |
4503 | * @brief Sets the parameter set of the distribution. |
4504 | * @param __param The new parameter set of the distribution. |
4505 | */ |
4506 | void |
4507 | param(const param_type& __param) |
4508 | { _M_param = __param; } |
4509 | |
4510 | /** |
4511 | * @brief Returns the greatest lower bound value of the distribution. |
4512 | */ |
4513 | result_type |
4514 | min() const |
4515 | { return result_type(0); } |
4516 | |
4517 | /** |
4518 | * @brief Returns the least upper bound value of the distribution. |
4519 | */ |
4520 | result_type |
4521 | max() const |
4522 | { return std::numeric_limits<result_type>::max(); } |
4523 | |
4524 | /** |
4525 | * @brief Generating functions. |
4526 | */ |
4527 | template<typename _UniformRandomNumberGenerator> |
4528 | result_type |
4529 | operator()(_UniformRandomNumberGenerator& __urng); |
4530 | |
4531 | template<typename _UniformRandomNumberGenerator> |
4532 | result_type |
4533 | operator()(_UniformRandomNumberGenerator& __urng, |
4534 | const param_type& __p); |
4535 | |
4536 | template<typename _ForwardIterator, |
4537 | typename _UniformRandomNumberGenerator> |
4538 | void |
4539 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
4540 | _UniformRandomNumberGenerator& __urng) |
4541 | { this->__generate_impl(__f, __t, __urng); } |
4542 | |
4543 | template<typename _ForwardIterator, |
4544 | typename _UniformRandomNumberGenerator> |
4545 | void |
4546 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
4547 | _UniformRandomNumberGenerator& __urng, |
4548 | const param_type& __p) |
4549 | { this->__generate_impl(__f, __t, __urng, __p); } |
4550 | |
4551 | template<typename _UniformRandomNumberGenerator> |
4552 | void |
4553 | __generate(result_type* __f, result_type* __t, |
4554 | _UniformRandomNumberGenerator& __urng) |
4555 | { this->__generate_impl(__f, __t, __urng); } |
4556 | |
4557 | template<typename _UniformRandomNumberGenerator> |
4558 | void |
4559 | __generate(result_type* __f, result_type* __t, |
4560 | _UniformRandomNumberGenerator& __urng, |
4561 | const param_type& __p) |
4562 | { this->__generate_impl(__f, __t, __urng, __p); } |
4563 | |
4564 | /** |
4565 | * @brief Return true if two negative binomial distributions have |
4566 | * the same parameters and the sequences that would be |
4567 | * generated are equal. |
4568 | */ |
4569 | friend bool |
4570 | operator==(const negative_binomial_distribution& __d1, |
4571 | const negative_binomial_distribution& __d2) |
4572 | { return __d1._M_param == __d2._M_param && __d1._M_gd == __d2._M_gd; } |
4573 | |
4574 | /** |
4575 | * @brief Inserts a %negative_binomial_distribution random |
4576 | * number distribution @p __x into the output stream @p __os. |
4577 | * |
4578 | * @param __os An output stream. |
4579 | * @param __x A %negative_binomial_distribution random number |
4580 | * distribution. |
4581 | * |
4582 | * @returns The output stream with the state of @p __x inserted or in |
4583 | * an error state. |
4584 | */ |
4585 | template<typename _IntType1, typename _CharT, typename _Traits> |
4586 | friend std::basic_ostream<_CharT, _Traits>& |
4587 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
4588 | const std::negative_binomial_distribution<_IntType1>& __x); |
4589 | |
4590 | /** |
4591 | * @brief Extracts a %negative_binomial_distribution random number |
4592 | * distribution @p __x from the input stream @p __is. |
4593 | * |
4594 | * @param __is An input stream. |
4595 | * @param __x A %negative_binomial_distribution random number |
4596 | * generator engine. |
4597 | * |
4598 | * @returns The input stream with @p __x extracted or in an error state. |
4599 | */ |
4600 | template<typename _IntType1, typename _CharT, typename _Traits> |
4601 | friend std::basic_istream<_CharT, _Traits>& |
4602 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
4603 | std::negative_binomial_distribution<_IntType1>& __x); |
4604 | |
4605 | private: |
4606 | template<typename _ForwardIterator, |
4607 | typename _UniformRandomNumberGenerator> |
4608 | void |
4609 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
4610 | _UniformRandomNumberGenerator& __urng); |
4611 | template<typename _ForwardIterator, |
4612 | typename _UniformRandomNumberGenerator> |
4613 | void |
4614 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
4615 | _UniformRandomNumberGenerator& __urng, |
4616 | const param_type& __p); |
4617 | |
4618 | param_type _M_param; |
4619 | |
4620 | std::gamma_distribution<double> _M_gd; |
4621 | }; |
4622 | |
4623 | #if __cpp_impl_three_way_comparison < 201907L |
4624 | /** |
4625 | * @brief Return true if two negative binomial distributions are different. |
4626 | */ |
4627 | template<typename _IntType> |
4628 | inline bool |
4629 | operator!=(const std::negative_binomial_distribution<_IntType>& __d1, |
4630 | const std::negative_binomial_distribution<_IntType>& __d2) |
4631 | { return !(__d1 == __d2); } |
4632 | #endif |
4633 | |
4634 | /// @} group random_distributions_bernoulli |
4635 | |
4636 | /** |
4637 | * @addtogroup random_distributions_poisson Poisson Distributions |
4638 | * @ingroup random_distributions |
4639 | * @{ |
4640 | */ |
4641 | |
4642 | /** |
4643 | * @brief A discrete Poisson random number distribution. |
4644 | * |
4645 | * The formula for the Poisson probability density function is |
4646 | * @f$p(i|\mu) = \frac{\mu^i}{i!} e^{-\mu}@f$ where @f$\mu@f$ is the |
4647 | * parameter of the distribution. |
4648 | * |
4649 | * @headerfile random |
4650 | * @since C++11 |
4651 | */ |
4652 | template<typename _IntType = int> |
4653 | class poisson_distribution |
4654 | { |
4655 | static_assert(std::is_integral<_IntType>::value, |
4656 | "result_type must be an integral type" ); |
4657 | |
4658 | public: |
4659 | /** The type of the range of the distribution. */ |
4660 | typedef _IntType result_type; |
4661 | |
4662 | /** Parameter type. */ |
4663 | struct param_type |
4664 | { |
4665 | typedef poisson_distribution<_IntType> distribution_type; |
4666 | friend class poisson_distribution<_IntType>; |
4667 | |
4668 | param_type() : param_type(1.0) { } |
4669 | |
4670 | explicit |
4671 | param_type(double __mean) |
4672 | : _M_mean(__mean) |
4673 | { |
4674 | __glibcxx_assert(_M_mean > 0.0); |
4675 | _M_initialize(); |
4676 | } |
4677 | |
4678 | double |
4679 | mean() const |
4680 | { return _M_mean; } |
4681 | |
4682 | friend bool |
4683 | operator==(const param_type& __p1, const param_type& __p2) |
4684 | { return __p1._M_mean == __p2._M_mean; } |
4685 | |
4686 | #if __cpp_impl_three_way_comparison < 201907L |
4687 | friend bool |
4688 | operator!=(const param_type& __p1, const param_type& __p2) |
4689 | { return !(__p1 == __p2); } |
4690 | #endif |
4691 | |
4692 | private: |
4693 | // Hosts either log(mean) or the threshold of the simple method. |
4694 | void |
4695 | _M_initialize(); |
4696 | |
4697 | double _M_mean; |
4698 | |
4699 | double _M_lm_thr; |
4700 | #if _GLIBCXX_USE_C99_MATH_FUNCS |
4701 | double _M_lfm, _M_sm, _M_d, _M_scx, _M_1cx, _M_c2b, _M_cb; |
4702 | #endif |
4703 | }; |
4704 | |
4705 | // constructors and member functions |
4706 | |
4707 | poisson_distribution() : poisson_distribution(1.0) { } |
4708 | |
4709 | explicit |
4710 | poisson_distribution(double __mean) |
4711 | : _M_param(__mean), _M_nd() |
4712 | { } |
4713 | |
4714 | explicit |
4715 | poisson_distribution(const param_type& __p) |
4716 | : _M_param(__p), _M_nd() |
4717 | { } |
4718 | |
4719 | /** |
4720 | * @brief Resets the distribution state. |
4721 | */ |
4722 | void |
4723 | reset() |
4724 | { _M_nd.reset(); } |
4725 | |
4726 | /** |
4727 | * @brief Returns the distribution parameter @p mean. |
4728 | */ |
4729 | double |
4730 | mean() const |
4731 | { return _M_param.mean(); } |
4732 | |
4733 | /** |
4734 | * @brief Returns the parameter set of the distribution. |
4735 | */ |
4736 | param_type |
4737 | param() const |
4738 | { return _M_param; } |
4739 | |
4740 | /** |
4741 | * @brief Sets the parameter set of the distribution. |
4742 | * @param __param The new parameter set of the distribution. |
4743 | */ |
4744 | void |
4745 | param(const param_type& __param) |
4746 | { _M_param = __param; } |
4747 | |
4748 | /** |
4749 | * @brief Returns the greatest lower bound value of the distribution. |
4750 | */ |
4751 | result_type |
4752 | min() const |
4753 | { return 0; } |
4754 | |
4755 | /** |
4756 | * @brief Returns the least upper bound value of the distribution. |
4757 | */ |
4758 | result_type |
4759 | max() const |
4760 | { return std::numeric_limits<result_type>::max(); } |
4761 | |
4762 | /** |
4763 | * @brief Generating functions. |
4764 | */ |
4765 | template<typename _UniformRandomNumberGenerator> |
4766 | result_type |
4767 | operator()(_UniformRandomNumberGenerator& __urng) |
4768 | { return this->operator()(__urng, _M_param); } |
4769 | |
4770 | template<typename _UniformRandomNumberGenerator> |
4771 | result_type |
4772 | operator()(_UniformRandomNumberGenerator& __urng, |
4773 | const param_type& __p); |
4774 | |
4775 | template<typename _ForwardIterator, |
4776 | typename _UniformRandomNumberGenerator> |
4777 | void |
4778 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
4779 | _UniformRandomNumberGenerator& __urng) |
4780 | { this->__generate(__f, __t, __urng, _M_param); } |
4781 | |
4782 | template<typename _ForwardIterator, |
4783 | typename _UniformRandomNumberGenerator> |
4784 | void |
4785 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
4786 | _UniformRandomNumberGenerator& __urng, |
4787 | const param_type& __p) |
4788 | { this->__generate_impl(__f, __t, __urng, __p); } |
4789 | |
4790 | template<typename _UniformRandomNumberGenerator> |
4791 | void |
4792 | __generate(result_type* __f, result_type* __t, |
4793 | _UniformRandomNumberGenerator& __urng, |
4794 | const param_type& __p) |
4795 | { this->__generate_impl(__f, __t, __urng, __p); } |
4796 | |
4797 | /** |
4798 | * @brief Return true if two Poisson distributions have the same |
4799 | * parameters and the sequences that would be generated |
4800 | * are equal. |
4801 | */ |
4802 | friend bool |
4803 | operator==(const poisson_distribution& __d1, |
4804 | const poisson_distribution& __d2) |
4805 | #ifdef _GLIBCXX_USE_C99_MATH_FUNCS |
4806 | { return __d1._M_param == __d2._M_param && __d1._M_nd == __d2._M_nd; } |
4807 | #else |
4808 | { return __d1._M_param == __d2._M_param; } |
4809 | #endif |
4810 | |
4811 | /** |
4812 | * @brief Inserts a %poisson_distribution random number distribution |
4813 | * @p __x into the output stream @p __os. |
4814 | * |
4815 | * @param __os An output stream. |
4816 | * @param __x A %poisson_distribution random number distribution. |
4817 | * |
4818 | * @returns The output stream with the state of @p __x inserted or in |
4819 | * an error state. |
4820 | */ |
4821 | template<typename _IntType1, typename _CharT, typename _Traits> |
4822 | friend std::basic_ostream<_CharT, _Traits>& |
4823 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
4824 | const std::poisson_distribution<_IntType1>& __x); |
4825 | |
4826 | /** |
4827 | * @brief Extracts a %poisson_distribution random number distribution |
4828 | * @p __x from the input stream @p __is. |
4829 | * |
4830 | * @param __is An input stream. |
4831 | * @param __x A %poisson_distribution random number generator engine. |
4832 | * |
4833 | * @returns The input stream with @p __x extracted or in an error |
4834 | * state. |
4835 | */ |
4836 | template<typename _IntType1, typename _CharT, typename _Traits> |
4837 | friend std::basic_istream<_CharT, _Traits>& |
4838 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
4839 | std::poisson_distribution<_IntType1>& __x); |
4840 | |
4841 | private: |
4842 | template<typename _ForwardIterator, |
4843 | typename _UniformRandomNumberGenerator> |
4844 | void |
4845 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
4846 | _UniformRandomNumberGenerator& __urng, |
4847 | const param_type& __p); |
4848 | |
4849 | param_type _M_param; |
4850 | |
4851 | // NB: Unused when _GLIBCXX_USE_C99_MATH_FUNCS is undefined. |
4852 | std::normal_distribution<double> _M_nd; |
4853 | }; |
4854 | |
4855 | #if __cpp_impl_three_way_comparison < 201907L |
4856 | /** |
4857 | * @brief Return true if two Poisson distributions are different. |
4858 | */ |
4859 | template<typename _IntType> |
4860 | inline bool |
4861 | operator!=(const std::poisson_distribution<_IntType>& __d1, |
4862 | const std::poisson_distribution<_IntType>& __d2) |
4863 | { return !(__d1 == __d2); } |
4864 | #endif |
4865 | |
4866 | /** |
4867 | * @brief An exponential continuous distribution for random numbers. |
4868 | * |
4869 | * The formula for the exponential probability density function is |
4870 | * @f$p(x|\lambda) = \lambda e^{-\lambda x}@f$. |
4871 | * |
4872 | * <table border=1 cellpadding=10 cellspacing=0> |
4873 | * <caption align=top>Distribution Statistics</caption> |
4874 | * <tr><td>Mean</td><td>@f$\frac{1}{\lambda}@f$</td></tr> |
4875 | * <tr><td>Median</td><td>@f$\frac{\ln 2}{\lambda}@f$</td></tr> |
4876 | * <tr><td>Mode</td><td>@f$zero@f$</td></tr> |
4877 | * <tr><td>Range</td><td>@f$[0, \infty]@f$</td></tr> |
4878 | * <tr><td>Standard Deviation</td><td>@f$\frac{1}{\lambda}@f$</td></tr> |
4879 | * </table> |
4880 | * |
4881 | * @headerfile random |
4882 | * @since C++11 |
4883 | */ |
4884 | template<typename _RealType = double> |
4885 | class exponential_distribution |
4886 | { |
4887 | static_assert(std::is_floating_point<_RealType>::value, |
4888 | "result_type must be a floating point type" ); |
4889 | |
4890 | public: |
4891 | /** The type of the range of the distribution. */ |
4892 | typedef _RealType result_type; |
4893 | |
4894 | /** Parameter type. */ |
4895 | struct param_type |
4896 | { |
4897 | typedef exponential_distribution<_RealType> distribution_type; |
4898 | |
4899 | param_type() : param_type(1.0) { } |
4900 | |
4901 | explicit |
4902 | param_type(_RealType __lambda) |
4903 | : _M_lambda(__lambda) |
4904 | { |
4905 | __glibcxx_assert(_M_lambda > _RealType(0)); |
4906 | } |
4907 | |
4908 | _RealType |
4909 | lambda() const |
4910 | { return _M_lambda; } |
4911 | |
4912 | friend bool |
4913 | operator==(const param_type& __p1, const param_type& __p2) |
4914 | { return __p1._M_lambda == __p2._M_lambda; } |
4915 | |
4916 | #if __cpp_impl_three_way_comparison < 201907L |
4917 | friend bool |
4918 | operator!=(const param_type& __p1, const param_type& __p2) |
4919 | { return !(__p1 == __p2); } |
4920 | #endif |
4921 | |
4922 | private: |
4923 | _RealType _M_lambda; |
4924 | }; |
4925 | |
4926 | public: |
4927 | /** |
4928 | * @brief Constructs an exponential distribution with inverse scale |
4929 | * parameter 1.0 |
4930 | */ |
4931 | exponential_distribution() : exponential_distribution(1.0) { } |
4932 | |
4933 | /** |
4934 | * @brief Constructs an exponential distribution with inverse scale |
4935 | * parameter @f$\lambda@f$. |
4936 | */ |
4937 | explicit |
4938 | exponential_distribution(_RealType __lambda) |
4939 | : _M_param(__lambda) |
4940 | { } |
4941 | |
4942 | explicit |
4943 | exponential_distribution(const param_type& __p) |
4944 | : _M_param(__p) |
4945 | { } |
4946 | |
4947 | /** |
4948 | * @brief Resets the distribution state. |
4949 | * |
4950 | * Has no effect on exponential distributions. |
4951 | */ |
4952 | void |
4953 | reset() { } |
4954 | |
4955 | /** |
4956 | * @brief Returns the inverse scale parameter of the distribution. |
4957 | */ |
4958 | _RealType |
4959 | lambda() const |
4960 | { return _M_param.lambda(); } |
4961 | |
4962 | /** |
4963 | * @brief Returns the parameter set of the distribution. |
4964 | */ |
4965 | param_type |
4966 | param() const |
4967 | { return _M_param; } |
4968 | |
4969 | /** |
4970 | * @brief Sets the parameter set of the distribution. |
4971 | * @param __param The new parameter set of the distribution. |
4972 | */ |
4973 | void |
4974 | param(const param_type& __param) |
4975 | { _M_param = __param; } |
4976 | |
4977 | /** |
4978 | * @brief Returns the greatest lower bound value of the distribution. |
4979 | */ |
4980 | result_type |
4981 | min() const |
4982 | { return result_type(0); } |
4983 | |
4984 | /** |
4985 | * @brief Returns the least upper bound value of the distribution. |
4986 | */ |
4987 | result_type |
4988 | max() const |
4989 | { return std::numeric_limits<result_type>::max(); } |
4990 | |
4991 | /** |
4992 | * @brief Generating functions. |
4993 | */ |
4994 | template<typename _UniformRandomNumberGenerator> |
4995 | result_type |
4996 | operator()(_UniformRandomNumberGenerator& __urng) |
4997 | { return this->operator()(__urng, _M_param); } |
4998 | |
4999 | template<typename _UniformRandomNumberGenerator> |
5000 | result_type |
5001 | operator()(_UniformRandomNumberGenerator& __urng, |
5002 | const param_type& __p) |
5003 | { |
5004 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> |
5005 | __aurng(__urng); |
5006 | return -std::log(result_type(1) - __aurng()) / __p.lambda(); |
5007 | } |
5008 | |
5009 | template<typename _ForwardIterator, |
5010 | typename _UniformRandomNumberGenerator> |
5011 | void |
5012 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
5013 | _UniformRandomNumberGenerator& __urng) |
5014 | { this->__generate(__f, __t, __urng, _M_param); } |
5015 | |
5016 | template<typename _ForwardIterator, |
5017 | typename _UniformRandomNumberGenerator> |
5018 | void |
5019 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
5020 | _UniformRandomNumberGenerator& __urng, |
5021 | const param_type& __p) |
5022 | { this->__generate_impl(__f, __t, __urng, __p); } |
5023 | |
5024 | template<typename _UniformRandomNumberGenerator> |
5025 | void |
5026 | __generate(result_type* __f, result_type* __t, |
5027 | _UniformRandomNumberGenerator& __urng, |
5028 | const param_type& __p) |
5029 | { this->__generate_impl(__f, __t, __urng, __p); } |
5030 | |
5031 | /** |
5032 | * @brief Return true if two exponential distributions have the same |
5033 | * parameters. |
5034 | */ |
5035 | friend bool |
5036 | operator==(const exponential_distribution& __d1, |
5037 | const exponential_distribution& __d2) |
5038 | { return __d1._M_param == __d2._M_param; } |
5039 | |
5040 | private: |
5041 | template<typename _ForwardIterator, |
5042 | typename _UniformRandomNumberGenerator> |
5043 | void |
5044 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
5045 | _UniformRandomNumberGenerator& __urng, |
5046 | const param_type& __p); |
5047 | |
5048 | param_type _M_param; |
5049 | }; |
5050 | |
5051 | #if __cpp_impl_three_way_comparison < 201907L |
5052 | /** |
5053 | * @brief Return true if two exponential distributions have different |
5054 | * parameters. |
5055 | */ |
5056 | template<typename _RealType> |
5057 | inline bool |
5058 | operator!=(const std::exponential_distribution<_RealType>& __d1, |
5059 | const std::exponential_distribution<_RealType>& __d2) |
5060 | { return !(__d1 == __d2); } |
5061 | #endif |
5062 | |
5063 | /** |
5064 | * @brief Inserts a %exponential_distribution random number distribution |
5065 | * @p __x into the output stream @p __os. |
5066 | * |
5067 | * @param __os An output stream. |
5068 | * @param __x A %exponential_distribution random number distribution. |
5069 | * |
5070 | * @returns The output stream with the state of @p __x inserted or in |
5071 | * an error state. |
5072 | */ |
5073 | template<typename _RealType, typename _CharT, typename _Traits> |
5074 | std::basic_ostream<_CharT, _Traits>& |
5075 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
5076 | const std::exponential_distribution<_RealType>& __x); |
5077 | |
5078 | /** |
5079 | * @brief Extracts a %exponential_distribution random number distribution |
5080 | * @p __x from the input stream @p __is. |
5081 | * |
5082 | * @param __is An input stream. |
5083 | * @param __x A %exponential_distribution random number |
5084 | * generator engine. |
5085 | * |
5086 | * @returns The input stream with @p __x extracted or in an error state. |
5087 | */ |
5088 | template<typename _RealType, typename _CharT, typename _Traits> |
5089 | std::basic_istream<_CharT, _Traits>& |
5090 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
5091 | std::exponential_distribution<_RealType>& __x); |
5092 | |
5093 | |
5094 | /** |
5095 | * @brief A weibull_distribution random number distribution. |
5096 | * |
5097 | * The formula for the normal probability density function is: |
5098 | * @f[ |
5099 | * p(x|\alpha,\beta) = \frac{\alpha}{\beta} (\frac{x}{\beta})^{\alpha-1} |
5100 | * \exp{(-(\frac{x}{\beta})^\alpha)} |
5101 | * @f] |
5102 | * |
5103 | * @headerfile random |
5104 | * @since C++11 |
5105 | */ |
5106 | template<typename _RealType = double> |
5107 | class weibull_distribution |
5108 | { |
5109 | static_assert(std::is_floating_point<_RealType>::value, |
5110 | "result_type must be a floating point type" ); |
5111 | |
5112 | public: |
5113 | /** The type of the range of the distribution. */ |
5114 | typedef _RealType result_type; |
5115 | |
5116 | /** Parameter type. */ |
5117 | struct param_type |
5118 | { |
5119 | typedef weibull_distribution<_RealType> distribution_type; |
5120 | |
5121 | param_type() : param_type(1.0) { } |
5122 | |
5123 | explicit |
5124 | param_type(_RealType __a, _RealType __b = _RealType(1.0)) |
5125 | : _M_a(__a), _M_b(__b) |
5126 | { } |
5127 | |
5128 | _RealType |
5129 | a() const |
5130 | { return _M_a; } |
5131 | |
5132 | _RealType |
5133 | b() const |
5134 | { return _M_b; } |
5135 | |
5136 | friend bool |
5137 | operator==(const param_type& __p1, const param_type& __p2) |
5138 | { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; } |
5139 | |
5140 | #if __cpp_impl_three_way_comparison < 201907L |
5141 | friend bool |
5142 | operator!=(const param_type& __p1, const param_type& __p2) |
5143 | { return !(__p1 == __p2); } |
5144 | #endif |
5145 | |
5146 | private: |
5147 | _RealType _M_a; |
5148 | _RealType _M_b; |
5149 | }; |
5150 | |
5151 | weibull_distribution() : weibull_distribution(1.0) { } |
5152 | |
5153 | explicit |
5154 | weibull_distribution(_RealType __a, _RealType __b = _RealType(1)) |
5155 | : _M_param(__a, __b) |
5156 | { } |
5157 | |
5158 | explicit |
5159 | weibull_distribution(const param_type& __p) |
5160 | : _M_param(__p) |
5161 | { } |
5162 | |
5163 | /** |
5164 | * @brief Resets the distribution state. |
5165 | */ |
5166 | void |
5167 | reset() |
5168 | { } |
5169 | |
5170 | /** |
5171 | * @brief Return the @f$a@f$ parameter of the distribution. |
5172 | */ |
5173 | _RealType |
5174 | a() const |
5175 | { return _M_param.a(); } |
5176 | |
5177 | /** |
5178 | * @brief Return the @f$b@f$ parameter of the distribution. |
5179 | */ |
5180 | _RealType |
5181 | b() const |
5182 | { return _M_param.b(); } |
5183 | |
5184 | /** |
5185 | * @brief Returns the parameter set of the distribution. |
5186 | */ |
5187 | param_type |
5188 | param() const |
5189 | { return _M_param; } |
5190 | |
5191 | /** |
5192 | * @brief Sets the parameter set of the distribution. |
5193 | * @param __param The new parameter set of the distribution. |
5194 | */ |
5195 | void |
5196 | param(const param_type& __param) |
5197 | { _M_param = __param; } |
5198 | |
5199 | /** |
5200 | * @brief Returns the greatest lower bound value of the distribution. |
5201 | */ |
5202 | result_type |
5203 | min() const |
5204 | { return result_type(0); } |
5205 | |
5206 | /** |
5207 | * @brief Returns the least upper bound value of the distribution. |
5208 | */ |
5209 | result_type |
5210 | max() const |
5211 | { return std::numeric_limits<result_type>::max(); } |
5212 | |
5213 | /** |
5214 | * @brief Generating functions. |
5215 | */ |
5216 | template<typename _UniformRandomNumberGenerator> |
5217 | result_type |
5218 | operator()(_UniformRandomNumberGenerator& __urng) |
5219 | { return this->operator()(__urng, _M_param); } |
5220 | |
5221 | template<typename _UniformRandomNumberGenerator> |
5222 | result_type |
5223 | operator()(_UniformRandomNumberGenerator& __urng, |
5224 | const param_type& __p); |
5225 | |
5226 | template<typename _ForwardIterator, |
5227 | typename _UniformRandomNumberGenerator> |
5228 | void |
5229 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
5230 | _UniformRandomNumberGenerator& __urng) |
5231 | { this->__generate(__f, __t, __urng, _M_param); } |
5232 | |
5233 | template<typename _ForwardIterator, |
5234 | typename _UniformRandomNumberGenerator> |
5235 | void |
5236 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
5237 | _UniformRandomNumberGenerator& __urng, |
5238 | const param_type& __p) |
5239 | { this->__generate_impl(__f, __t, __urng, __p); } |
5240 | |
5241 | template<typename _UniformRandomNumberGenerator> |
5242 | void |
5243 | __generate(result_type* __f, result_type* __t, |
5244 | _UniformRandomNumberGenerator& __urng, |
5245 | const param_type& __p) |
5246 | { this->__generate_impl(__f, __t, __urng, __p); } |
5247 | |
5248 | /** |
5249 | * @brief Return true if two Weibull distributions have the same |
5250 | * parameters. |
5251 | */ |
5252 | friend bool |
5253 | operator==(const weibull_distribution& __d1, |
5254 | const weibull_distribution& __d2) |
5255 | { return __d1._M_param == __d2._M_param; } |
5256 | |
5257 | private: |
5258 | template<typename _ForwardIterator, |
5259 | typename _UniformRandomNumberGenerator> |
5260 | void |
5261 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
5262 | _UniformRandomNumberGenerator& __urng, |
5263 | const param_type& __p); |
5264 | |
5265 | param_type _M_param; |
5266 | }; |
5267 | |
5268 | #if __cpp_impl_three_way_comparison < 201907L |
5269 | /** |
5270 | * @brief Return true if two Weibull distributions have different |
5271 | * parameters. |
5272 | */ |
5273 | template<typename _RealType> |
5274 | inline bool |
5275 | operator!=(const std::weibull_distribution<_RealType>& __d1, |
5276 | const std::weibull_distribution<_RealType>& __d2) |
5277 | { return !(__d1 == __d2); } |
5278 | #endif |
5279 | |
5280 | /** |
5281 | * @brief Inserts a %weibull_distribution random number distribution |
5282 | * @p __x into the output stream @p __os. |
5283 | * |
5284 | * @param __os An output stream. |
5285 | * @param __x A %weibull_distribution random number distribution. |
5286 | * |
5287 | * @returns The output stream with the state of @p __x inserted or in |
5288 | * an error state. |
5289 | */ |
5290 | template<typename _RealType, typename _CharT, typename _Traits> |
5291 | std::basic_ostream<_CharT, _Traits>& |
5292 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
5293 | const std::weibull_distribution<_RealType>& __x); |
5294 | |
5295 | /** |
5296 | * @brief Extracts a %weibull_distribution random number distribution |
5297 | * @p __x from the input stream @p __is. |
5298 | * |
5299 | * @param __is An input stream. |
5300 | * @param __x A %weibull_distribution random number |
5301 | * generator engine. |
5302 | * |
5303 | * @returns The input stream with @p __x extracted or in an error state. |
5304 | */ |
5305 | template<typename _RealType, typename _CharT, typename _Traits> |
5306 | std::basic_istream<_CharT, _Traits>& |
5307 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
5308 | std::weibull_distribution<_RealType>& __x); |
5309 | |
5310 | |
5311 | /** |
5312 | * @brief A extreme_value_distribution random number distribution. |
5313 | * |
5314 | * The formula for the normal probability mass function is |
5315 | * @f[ |
5316 | * p(x|a,b) = \frac{1}{b} |
5317 | * \exp( \frac{a-x}{b} - \exp(\frac{a-x}{b})) |
5318 | * @f] |
5319 | * |
5320 | * @headerfile random |
5321 | * @since C++11 |
5322 | */ |
5323 | template<typename _RealType = double> |
5324 | class extreme_value_distribution |
5325 | { |
5326 | static_assert(std::is_floating_point<_RealType>::value, |
5327 | "result_type must be a floating point type" ); |
5328 | |
5329 | public: |
5330 | /** The type of the range of the distribution. */ |
5331 | typedef _RealType result_type; |
5332 | |
5333 | /** Parameter type. */ |
5334 | struct param_type |
5335 | { |
5336 | typedef extreme_value_distribution<_RealType> distribution_type; |
5337 | |
5338 | param_type() : param_type(0.0) { } |
5339 | |
5340 | explicit |
5341 | param_type(_RealType __a, _RealType __b = _RealType(1.0)) |
5342 | : _M_a(__a), _M_b(__b) |
5343 | { } |
5344 | |
5345 | _RealType |
5346 | a() const |
5347 | { return _M_a; } |
5348 | |
5349 | _RealType |
5350 | b() const |
5351 | { return _M_b; } |
5352 | |
5353 | friend bool |
5354 | operator==(const param_type& __p1, const param_type& __p2) |
5355 | { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; } |
5356 | |
5357 | #if __cpp_impl_three_way_comparison < 201907L |
5358 | friend bool |
5359 | operator!=(const param_type& __p1, const param_type& __p2) |
5360 | { return !(__p1 == __p2); } |
5361 | #endif |
5362 | |
5363 | private: |
5364 | _RealType _M_a; |
5365 | _RealType _M_b; |
5366 | }; |
5367 | |
5368 | extreme_value_distribution() : extreme_value_distribution(0.0) { } |
5369 | |
5370 | explicit |
5371 | extreme_value_distribution(_RealType __a, _RealType __b = _RealType(1)) |
5372 | : _M_param(__a, __b) |
5373 | { } |
5374 | |
5375 | explicit |
5376 | extreme_value_distribution(const param_type& __p) |
5377 | : _M_param(__p) |
5378 | { } |
5379 | |
5380 | /** |
5381 | * @brief Resets the distribution state. |
5382 | */ |
5383 | void |
5384 | reset() |
5385 | { } |
5386 | |
5387 | /** |
5388 | * @brief Return the @f$a@f$ parameter of the distribution. |
5389 | */ |
5390 | _RealType |
5391 | a() const |
5392 | { return _M_param.a(); } |
5393 | |
5394 | /** |
5395 | * @brief Return the @f$b@f$ parameter of the distribution. |
5396 | */ |
5397 | _RealType |
5398 | b() const |
5399 | { return _M_param.b(); } |
5400 | |
5401 | /** |
5402 | * @brief Returns the parameter set of the distribution. |
5403 | */ |
5404 | param_type |
5405 | param() const |
5406 | { return _M_param; } |
5407 | |
5408 | /** |
5409 | * @brief Sets the parameter set of the distribution. |
5410 | * @param __param The new parameter set of the distribution. |
5411 | */ |
5412 | void |
5413 | param(const param_type& __param) |
5414 | { _M_param = __param; } |
5415 | |
5416 | /** |
5417 | * @brief Returns the greatest lower bound value of the distribution. |
5418 | */ |
5419 | result_type |
5420 | min() const |
5421 | { return std::numeric_limits<result_type>::lowest(); } |
5422 | |
5423 | /** |
5424 | * @brief Returns the least upper bound value of the distribution. |
5425 | */ |
5426 | result_type |
5427 | max() const |
5428 | { return std::numeric_limits<result_type>::max(); } |
5429 | |
5430 | /** |
5431 | * @brief Generating functions. |
5432 | */ |
5433 | template<typename _UniformRandomNumberGenerator> |
5434 | result_type |
5435 | operator()(_UniformRandomNumberGenerator& __urng) |
5436 | { return this->operator()(__urng, _M_param); } |
5437 | |
5438 | template<typename _UniformRandomNumberGenerator> |
5439 | result_type |
5440 | operator()(_UniformRandomNumberGenerator& __urng, |
5441 | const param_type& __p); |
5442 | |
5443 | template<typename _ForwardIterator, |
5444 | typename _UniformRandomNumberGenerator> |
5445 | void |
5446 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
5447 | _UniformRandomNumberGenerator& __urng) |
5448 | { this->__generate(__f, __t, __urng, _M_param); } |
5449 | |
5450 | template<typename _ForwardIterator, |
5451 | typename _UniformRandomNumberGenerator> |
5452 | void |
5453 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
5454 | _UniformRandomNumberGenerator& __urng, |
5455 | const param_type& __p) |
5456 | { this->__generate_impl(__f, __t, __urng, __p); } |
5457 | |
5458 | template<typename _UniformRandomNumberGenerator> |
5459 | void |
5460 | __generate(result_type* __f, result_type* __t, |
5461 | _UniformRandomNumberGenerator& __urng, |
5462 | const param_type& __p) |
5463 | { this->__generate_impl(__f, __t, __urng, __p); } |
5464 | |
5465 | /** |
5466 | * @brief Return true if two extreme value distributions have the same |
5467 | * parameters. |
5468 | */ |
5469 | friend bool |
5470 | operator==(const extreme_value_distribution& __d1, |
5471 | const extreme_value_distribution& __d2) |
5472 | { return __d1._M_param == __d2._M_param; } |
5473 | |
5474 | private: |
5475 | template<typename _ForwardIterator, |
5476 | typename _UniformRandomNumberGenerator> |
5477 | void |
5478 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
5479 | _UniformRandomNumberGenerator& __urng, |
5480 | const param_type& __p); |
5481 | |
5482 | param_type _M_param; |
5483 | }; |
5484 | |
5485 | #if __cpp_impl_three_way_comparison < 201907L |
5486 | /** |
5487 | * @brief Return true if two extreme value distributions have different |
5488 | * parameters. |
5489 | */ |
5490 | template<typename _RealType> |
5491 | inline bool |
5492 | operator!=(const std::extreme_value_distribution<_RealType>& __d1, |
5493 | const std::extreme_value_distribution<_RealType>& __d2) |
5494 | { return !(__d1 == __d2); } |
5495 | #endif |
5496 | |
5497 | /** |
5498 | * @brief Inserts a %extreme_value_distribution random number distribution |
5499 | * @p __x into the output stream @p __os. |
5500 | * |
5501 | * @param __os An output stream. |
5502 | * @param __x A %extreme_value_distribution random number distribution. |
5503 | * |
5504 | * @returns The output stream with the state of @p __x inserted or in |
5505 | * an error state. |
5506 | */ |
5507 | template<typename _RealType, typename _CharT, typename _Traits> |
5508 | std::basic_ostream<_CharT, _Traits>& |
5509 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
5510 | const std::extreme_value_distribution<_RealType>& __x); |
5511 | |
5512 | /** |
5513 | * @brief Extracts a %extreme_value_distribution random number |
5514 | * distribution @p __x from the input stream @p __is. |
5515 | * |
5516 | * @param __is An input stream. |
5517 | * @param __x A %extreme_value_distribution random number |
5518 | * generator engine. |
5519 | * |
5520 | * @returns The input stream with @p __x extracted or in an error state. |
5521 | */ |
5522 | template<typename _RealType, typename _CharT, typename _Traits> |
5523 | std::basic_istream<_CharT, _Traits>& |
5524 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
5525 | std::extreme_value_distribution<_RealType>& __x); |
5526 | |
5527 | /// @} group random_distributions_poisson |
5528 | |
5529 | /** |
5530 | * @addtogroup random_distributions_sampling Sampling Distributions |
5531 | * @ingroup random_distributions |
5532 | * @{ |
5533 | */ |
5534 | |
5535 | /** |
5536 | * @brief A discrete_distribution random number distribution. |
5537 | * |
5538 | * This distribution produces random numbers @f$ i, 0 \leq i < n @f$, |
5539 | * distributed according to the probability mass function |
5540 | * @f$ p(i | p_0, ..., p_{n-1}) = p_i @f$. |
5541 | * |
5542 | * @headerfile random |
5543 | * @since C++11 |
5544 | */ |
5545 | template<typename _IntType = int> |
5546 | class discrete_distribution |
5547 | { |
5548 | static_assert(std::is_integral<_IntType>::value, |
5549 | "result_type must be an integral type" ); |
5550 | |
5551 | public: |
5552 | /** The type of the range of the distribution. */ |
5553 | typedef _IntType result_type; |
5554 | |
5555 | /** Parameter type. */ |
5556 | struct param_type |
5557 | { |
5558 | typedef discrete_distribution<_IntType> distribution_type; |
5559 | friend class discrete_distribution<_IntType>; |
5560 | |
5561 | param_type() |
5562 | : _M_prob(), _M_cp() |
5563 | { } |
5564 | |
5565 | template<typename _InputIterator> |
5566 | param_type(_InputIterator __wbegin, |
5567 | _InputIterator __wend) |
5568 | : _M_prob(__wbegin, __wend), _M_cp() |
5569 | { _M_initialize(); } |
5570 | |
5571 | param_type(initializer_list<double> __wil) |
5572 | : _M_prob(__wil.begin(), __wil.end()), _M_cp() |
5573 | { _M_initialize(); } |
5574 | |
5575 | template<typename _Func> |
5576 | param_type(size_t __nw, double __xmin, double __xmax, |
5577 | _Func __fw); |
5578 | |
5579 | // See: http://cpp-next.com/archive/2010/10/implicit-move-must-go/ |
5580 | param_type(const param_type&) = default; |
5581 | param_type& operator=(const param_type&) = default; |
5582 | |
5583 | std::vector<double> |
5584 | probabilities() const |
5585 | { return _M_prob.empty() ? std::vector<double>(1, 1.0) : _M_prob; } |
5586 | |
5587 | friend bool |
5588 | operator==(const param_type& __p1, const param_type& __p2) |
5589 | { return __p1._M_prob == __p2._M_prob; } |
5590 | |
5591 | #if __cpp_impl_three_way_comparison < 201907L |
5592 | friend bool |
5593 | operator!=(const param_type& __p1, const param_type& __p2) |
5594 | { return !(__p1 == __p2); } |
5595 | #endif |
5596 | |
5597 | private: |
5598 | void |
5599 | _M_initialize(); |
5600 | |
5601 | std::vector<double> _M_prob; |
5602 | std::vector<double> _M_cp; |
5603 | }; |
5604 | |
5605 | discrete_distribution() |
5606 | : _M_param() |
5607 | { } |
5608 | |
5609 | template<typename _InputIterator> |
5610 | discrete_distribution(_InputIterator __wbegin, |
5611 | _InputIterator __wend) |
5612 | : _M_param(__wbegin, __wend) |
5613 | { } |
5614 | |
5615 | discrete_distribution(initializer_list<double> __wl) |
5616 | : _M_param(__wl) |
5617 | { } |
5618 | |
5619 | template<typename _Func> |
5620 | discrete_distribution(size_t __nw, double __xmin, double __xmax, |
5621 | _Func __fw) |
5622 | : _M_param(__nw, __xmin, __xmax, __fw) |
5623 | { } |
5624 | |
5625 | explicit |
5626 | discrete_distribution(const param_type& __p) |
5627 | : _M_param(__p) |
5628 | { } |
5629 | |
5630 | /** |
5631 | * @brief Resets the distribution state. |
5632 | */ |
5633 | void |
5634 | reset() |
5635 | { } |
5636 | |
5637 | /** |
5638 | * @brief Returns the probabilities of the distribution. |
5639 | */ |
5640 | std::vector<double> |
5641 | probabilities() const |
5642 | { |
5643 | return _M_param._M_prob.empty() |
5644 | ? std::vector<double>(1, 1.0) : _M_param._M_prob; |
5645 | } |
5646 | |
5647 | /** |
5648 | * @brief Returns the parameter set of the distribution. |
5649 | */ |
5650 | param_type |
5651 | param() const |
5652 | { return _M_param; } |
5653 | |
5654 | /** |
5655 | * @brief Sets the parameter set of the distribution. |
5656 | * @param __param The new parameter set of the distribution. |
5657 | */ |
5658 | void |
5659 | param(const param_type& __param) |
5660 | { _M_param = __param; } |
5661 | |
5662 | /** |
5663 | * @brief Returns the greatest lower bound value of the distribution. |
5664 | */ |
5665 | result_type |
5666 | min() const |
5667 | { return result_type(0); } |
5668 | |
5669 | /** |
5670 | * @brief Returns the least upper bound value of the distribution. |
5671 | */ |
5672 | result_type |
5673 | max() const |
5674 | { |
5675 | return _M_param._M_prob.empty() |
5676 | ? result_type(0) : result_type(_M_param._M_prob.size() - 1); |
5677 | } |
5678 | |
5679 | /** |
5680 | * @brief Generating functions. |
5681 | */ |
5682 | template<typename _UniformRandomNumberGenerator> |
5683 | result_type |
5684 | operator()(_UniformRandomNumberGenerator& __urng) |
5685 | { return this->operator()(__urng, _M_param); } |
5686 | |
5687 | template<typename _UniformRandomNumberGenerator> |
5688 | result_type |
5689 | operator()(_UniformRandomNumberGenerator& __urng, |
5690 | const param_type& __p); |
5691 | |
5692 | template<typename _ForwardIterator, |
5693 | typename _UniformRandomNumberGenerator> |
5694 | void |
5695 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
5696 | _UniformRandomNumberGenerator& __urng) |
5697 | { this->__generate(__f, __t, __urng, _M_param); } |
5698 | |
5699 | template<typename _ForwardIterator, |
5700 | typename _UniformRandomNumberGenerator> |
5701 | void |
5702 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
5703 | _UniformRandomNumberGenerator& __urng, |
5704 | const param_type& __p) |
5705 | { this->__generate_impl(__f, __t, __urng, __p); } |
5706 | |
5707 | template<typename _UniformRandomNumberGenerator> |
5708 | void |
5709 | __generate(result_type* __f, result_type* __t, |
5710 | _UniformRandomNumberGenerator& __urng, |
5711 | const param_type& __p) |
5712 | { this->__generate_impl(__f, __t, __urng, __p); } |
5713 | |
5714 | /** |
5715 | * @brief Return true if two discrete distributions have the same |
5716 | * parameters. |
5717 | */ |
5718 | friend bool |
5719 | operator==(const discrete_distribution& __d1, |
5720 | const discrete_distribution& __d2) |
5721 | { return __d1._M_param == __d2._M_param; } |
5722 | |
5723 | /** |
5724 | * @brief Inserts a %discrete_distribution random number distribution |
5725 | * @p __x into the output stream @p __os. |
5726 | * |
5727 | * @param __os An output stream. |
5728 | * @param __x A %discrete_distribution random number distribution. |
5729 | * |
5730 | * @returns The output stream with the state of @p __x inserted or in |
5731 | * an error state. |
5732 | */ |
5733 | template<typename _IntType1, typename _CharT, typename _Traits> |
5734 | friend std::basic_ostream<_CharT, _Traits>& |
5735 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
5736 | const std::discrete_distribution<_IntType1>& __x); |
5737 | |
5738 | /** |
5739 | * @brief Extracts a %discrete_distribution random number distribution |
5740 | * @p __x from the input stream @p __is. |
5741 | * |
5742 | * @param __is An input stream. |
5743 | * @param __x A %discrete_distribution random number |
5744 | * generator engine. |
5745 | * |
5746 | * @returns The input stream with @p __x extracted or in an error |
5747 | * state. |
5748 | */ |
5749 | template<typename _IntType1, typename _CharT, typename _Traits> |
5750 | friend std::basic_istream<_CharT, _Traits>& |
5751 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
5752 | std::discrete_distribution<_IntType1>& __x); |
5753 | |
5754 | private: |
5755 | template<typename _ForwardIterator, |
5756 | typename _UniformRandomNumberGenerator> |
5757 | void |
5758 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
5759 | _UniformRandomNumberGenerator& __urng, |
5760 | const param_type& __p); |
5761 | |
5762 | param_type _M_param; |
5763 | }; |
5764 | |
5765 | #if __cpp_impl_three_way_comparison < 201907L |
5766 | /** |
5767 | * @brief Return true if two discrete distributions have different |
5768 | * parameters. |
5769 | */ |
5770 | template<typename _IntType> |
5771 | inline bool |
5772 | operator!=(const std::discrete_distribution<_IntType>& __d1, |
5773 | const std::discrete_distribution<_IntType>& __d2) |
5774 | { return !(__d1 == __d2); } |
5775 | #endif |
5776 | |
5777 | /** |
5778 | * @brief A piecewise_constant_distribution random number distribution. |
5779 | * |
5780 | * This distribution produces random numbers @f$ x, b_0 \leq x < b_n @f$, |
5781 | * uniformly distributed over each subinterval @f$ [b_i, b_{i+1}) @f$ |
5782 | * according to the probability mass function |
5783 | * @f[ |
5784 | * p(x | b_0, ..., b_n, \rho_0, ..., \rho_{n-1}) |
5785 | * = \rho_i \cdot \frac{b_{i+1} - x}{b_{i+1} - b_i} |
5786 | * + \rho_{i+1} \cdot \frac{ x - b_i}{b_{i+1} - b_i} |
5787 | * @f] |
5788 | * for @f$ b_i \leq x < b_{i+1} @f$. |
5789 | * |
5790 | * @headerfile random |
5791 | * @since C++11 |
5792 | */ |
5793 | template<typename _RealType = double> |
5794 | class piecewise_constant_distribution |
5795 | { |
5796 | static_assert(std::is_floating_point<_RealType>::value, |
5797 | "result_type must be a floating point type" ); |
5798 | |
5799 | public: |
5800 | /** The type of the range of the distribution. */ |
5801 | typedef _RealType result_type; |
5802 | |
5803 | /** Parameter type. */ |
5804 | struct param_type |
5805 | { |
5806 | typedef piecewise_constant_distribution<_RealType> distribution_type; |
5807 | friend class piecewise_constant_distribution<_RealType>; |
5808 | |
5809 | param_type() |
5810 | : _M_int(), _M_den(), _M_cp() |
5811 | { } |
5812 | |
5813 | template<typename _InputIteratorB, typename _InputIteratorW> |
5814 | param_type(_InputIteratorB __bfirst, |
5815 | _InputIteratorB __bend, |
5816 | _InputIteratorW __wbegin); |
5817 | |
5818 | template<typename _Func> |
5819 | param_type(initializer_list<_RealType> __bi, _Func __fw); |
5820 | |
5821 | template<typename _Func> |
5822 | param_type(size_t __nw, _RealType __xmin, _RealType __xmax, |
5823 | _Func __fw); |
5824 | |
5825 | // See: http://cpp-next.com/archive/2010/10/implicit-move-must-go/ |
5826 | param_type(const param_type&) = default; |
5827 | param_type& operator=(const param_type&) = default; |
5828 | |
5829 | std::vector<_RealType> |
5830 | intervals() const |
5831 | { |
5832 | if (_M_int.empty()) |
5833 | { |
5834 | std::vector<_RealType> __tmp(2); |
5835 | __tmp[1] = _RealType(1); |
5836 | return __tmp; |
5837 | } |
5838 | else |
5839 | return _M_int; |
5840 | } |
5841 | |
5842 | std::vector<double> |
5843 | densities() const |
5844 | { return _M_den.empty() ? std::vector<double>(1, 1.0) : _M_den; } |
5845 | |
5846 | friend bool |
5847 | operator==(const param_type& __p1, const param_type& __p2) |
5848 | { return __p1._M_int == __p2._M_int && __p1._M_den == __p2._M_den; } |
5849 | |
5850 | #if __cpp_impl_three_way_comparison < 201907L |
5851 | friend bool |
5852 | operator!=(const param_type& __p1, const param_type& __p2) |
5853 | { return !(__p1 == __p2); } |
5854 | #endif |
5855 | |
5856 | private: |
5857 | void |
5858 | _M_initialize(); |
5859 | |
5860 | std::vector<_RealType> _M_int; |
5861 | std::vector<double> _M_den; |
5862 | std::vector<double> _M_cp; |
5863 | }; |
5864 | |
5865 | piecewise_constant_distribution() |
5866 | : _M_param() |
5867 | { } |
5868 | |
5869 | template<typename _InputIteratorB, typename _InputIteratorW> |
5870 | piecewise_constant_distribution(_InputIteratorB __bfirst, |
5871 | _InputIteratorB __bend, |
5872 | _InputIteratorW __wbegin) |
5873 | : _M_param(__bfirst, __bend, __wbegin) |
5874 | { } |
5875 | |
5876 | template<typename _Func> |
5877 | piecewise_constant_distribution(initializer_list<_RealType> __bl, |
5878 | _Func __fw) |
5879 | : _M_param(__bl, __fw) |
5880 | { } |
5881 | |
5882 | template<typename _Func> |
5883 | piecewise_constant_distribution(size_t __nw, |
5884 | _RealType __xmin, _RealType __xmax, |
5885 | _Func __fw) |
5886 | : _M_param(__nw, __xmin, __xmax, __fw) |
5887 | { } |
5888 | |
5889 | explicit |
5890 | piecewise_constant_distribution(const param_type& __p) |
5891 | : _M_param(__p) |
5892 | { } |
5893 | |
5894 | /** |
5895 | * @brief Resets the distribution state. |
5896 | */ |
5897 | void |
5898 | reset() |
5899 | { } |
5900 | |
5901 | /** |
5902 | * @brief Returns a vector of the intervals. |
5903 | */ |
5904 | std::vector<_RealType> |
5905 | intervals() const |
5906 | { |
5907 | if (_M_param._M_int.empty()) |
5908 | { |
5909 | std::vector<_RealType> __tmp(2); |
5910 | __tmp[1] = _RealType(1); |
5911 | return __tmp; |
5912 | } |
5913 | else |
5914 | return _M_param._M_int; |
5915 | } |
5916 | |
5917 | /** |
5918 | * @brief Returns a vector of the probability densities. |
5919 | */ |
5920 | std::vector<double> |
5921 | densities() const |
5922 | { |
5923 | return _M_param._M_den.empty() |
5924 | ? std::vector<double>(1, 1.0) : _M_param._M_den; |
5925 | } |
5926 | |
5927 | /** |
5928 | * @brief Returns the parameter set of the distribution. |
5929 | */ |
5930 | param_type |
5931 | param() const |
5932 | { return _M_param; } |
5933 | |
5934 | /** |
5935 | * @brief Sets the parameter set of the distribution. |
5936 | * @param __param The new parameter set of the distribution. |
5937 | */ |
5938 | void |
5939 | param(const param_type& __param) |
5940 | { _M_param = __param; } |
5941 | |
5942 | /** |
5943 | * @brief Returns the greatest lower bound value of the distribution. |
5944 | */ |
5945 | result_type |
5946 | min() const |
5947 | { |
5948 | return _M_param._M_int.empty() |
5949 | ? result_type(0) : _M_param._M_int.front(); |
5950 | } |
5951 | |
5952 | /** |
5953 | * @brief Returns the least upper bound value of the distribution. |
5954 | */ |
5955 | result_type |
5956 | max() const |
5957 | { |
5958 | return _M_param._M_int.empty() |
5959 | ? result_type(1) : _M_param._M_int.back(); |
5960 | } |
5961 | |
5962 | /** |
5963 | * @brief Generating functions. |
5964 | */ |
5965 | template<typename _UniformRandomNumberGenerator> |
5966 | result_type |
5967 | operator()(_UniformRandomNumberGenerator& __urng) |
5968 | { return this->operator()(__urng, _M_param); } |
5969 | |
5970 | template<typename _UniformRandomNumberGenerator> |
5971 | result_type |
5972 | operator()(_UniformRandomNumberGenerator& __urng, |
5973 | const param_type& __p); |
5974 | |
5975 | template<typename _ForwardIterator, |
5976 | typename _UniformRandomNumberGenerator> |
5977 | void |
5978 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
5979 | _UniformRandomNumberGenerator& __urng) |
5980 | { this->__generate(__f, __t, __urng, _M_param); } |
5981 | |
5982 | template<typename _ForwardIterator, |
5983 | typename _UniformRandomNumberGenerator> |
5984 | void |
5985 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
5986 | _UniformRandomNumberGenerator& __urng, |
5987 | const param_type& __p) |
5988 | { this->__generate_impl(__f, __t, __urng, __p); } |
5989 | |
5990 | template<typename _UniformRandomNumberGenerator> |
5991 | void |
5992 | __generate(result_type* __f, result_type* __t, |
5993 | _UniformRandomNumberGenerator& __urng, |
5994 | const param_type& __p) |
5995 | { this->__generate_impl(__f, __t, __urng, __p); } |
5996 | |
5997 | /** |
5998 | * @brief Return true if two piecewise constant distributions have the |
5999 | * same parameters. |
6000 | */ |
6001 | friend bool |
6002 | operator==(const piecewise_constant_distribution& __d1, |
6003 | const piecewise_constant_distribution& __d2) |
6004 | { return __d1._M_param == __d2._M_param; } |
6005 | |
6006 | /** |
6007 | * @brief Inserts a %piecewise_constant_distribution random |
6008 | * number distribution @p __x into the output stream @p __os. |
6009 | * |
6010 | * @param __os An output stream. |
6011 | * @param __x A %piecewise_constant_distribution random number |
6012 | * distribution. |
6013 | * |
6014 | * @returns The output stream with the state of @p __x inserted or in |
6015 | * an error state. |
6016 | */ |
6017 | template<typename _RealType1, typename _CharT, typename _Traits> |
6018 | friend std::basic_ostream<_CharT, _Traits>& |
6019 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
6020 | const std::piecewise_constant_distribution<_RealType1>& __x); |
6021 | |
6022 | /** |
6023 | * @brief Extracts a %piecewise_constant_distribution random |
6024 | * number distribution @p __x from the input stream @p __is. |
6025 | * |
6026 | * @param __is An input stream. |
6027 | * @param __x A %piecewise_constant_distribution random number |
6028 | * generator engine. |
6029 | * |
6030 | * @returns The input stream with @p __x extracted or in an error |
6031 | * state. |
6032 | */ |
6033 | template<typename _RealType1, typename _CharT, typename _Traits> |
6034 | friend std::basic_istream<_CharT, _Traits>& |
6035 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
6036 | std::piecewise_constant_distribution<_RealType1>& __x); |
6037 | |
6038 | private: |
6039 | template<typename _ForwardIterator, |
6040 | typename _UniformRandomNumberGenerator> |
6041 | void |
6042 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
6043 | _UniformRandomNumberGenerator& __urng, |
6044 | const param_type& __p); |
6045 | |
6046 | param_type _M_param; |
6047 | }; |
6048 | |
6049 | #if __cpp_impl_three_way_comparison < 201907L |
6050 | /** |
6051 | * @brief Return true if two piecewise constant distributions have |
6052 | * different parameters. |
6053 | */ |
6054 | template<typename _RealType> |
6055 | inline bool |
6056 | operator!=(const std::piecewise_constant_distribution<_RealType>& __d1, |
6057 | const std::piecewise_constant_distribution<_RealType>& __d2) |
6058 | { return !(__d1 == __d2); } |
6059 | #endif |
6060 | |
6061 | /** |
6062 | * @brief A piecewise_linear_distribution random number distribution. |
6063 | * |
6064 | * This distribution produces random numbers @f$ x, b_0 \leq x < b_n @f$, |
6065 | * distributed over each subinterval @f$ [b_i, b_{i+1}) @f$ |
6066 | * according to the probability mass function |
6067 | * @f$ p(x | b_0, ..., b_n, \rho_0, ..., \rho_n) = \rho_i @f$, |
6068 | * for @f$ b_i \leq x < b_{i+1} @f$. |
6069 | * |
6070 | * @headerfile random |
6071 | * @since C++11 |
6072 | */ |
6073 | template<typename _RealType = double> |
6074 | class piecewise_linear_distribution |
6075 | { |
6076 | static_assert(std::is_floating_point<_RealType>::value, |
6077 | "result_type must be a floating point type" ); |
6078 | |
6079 | public: |
6080 | /** The type of the range of the distribution. */ |
6081 | typedef _RealType result_type; |
6082 | |
6083 | /** Parameter type. */ |
6084 | struct param_type |
6085 | { |
6086 | typedef piecewise_linear_distribution<_RealType> distribution_type; |
6087 | friend class piecewise_linear_distribution<_RealType>; |
6088 | |
6089 | param_type() |
6090 | : _M_int(), _M_den(), _M_cp(), _M_m() |
6091 | { } |
6092 | |
6093 | template<typename _InputIteratorB, typename _InputIteratorW> |
6094 | param_type(_InputIteratorB __bfirst, |
6095 | _InputIteratorB __bend, |
6096 | _InputIteratorW __wbegin); |
6097 | |
6098 | template<typename _Func> |
6099 | param_type(initializer_list<_RealType> __bl, _Func __fw); |
6100 | |
6101 | template<typename _Func> |
6102 | param_type(size_t __nw, _RealType __xmin, _RealType __xmax, |
6103 | _Func __fw); |
6104 | |
6105 | // See: http://cpp-next.com/archive/2010/10/implicit-move-must-go/ |
6106 | param_type(const param_type&) = default; |
6107 | param_type& operator=(const param_type&) = default; |
6108 | |
6109 | std::vector<_RealType> |
6110 | intervals() const |
6111 | { |
6112 | if (_M_int.empty()) |
6113 | { |
6114 | std::vector<_RealType> __tmp(2); |
6115 | __tmp[1] = _RealType(1); |
6116 | return __tmp; |
6117 | } |
6118 | else |
6119 | return _M_int; |
6120 | } |
6121 | |
6122 | std::vector<double> |
6123 | densities() const |
6124 | { return _M_den.empty() ? std::vector<double>(2, 1.0) : _M_den; } |
6125 | |
6126 | friend bool |
6127 | operator==(const param_type& __p1, const param_type& __p2) |
6128 | { return __p1._M_int == __p2._M_int && __p1._M_den == __p2._M_den; } |
6129 | |
6130 | #if __cpp_impl_three_way_comparison < 201907L |
6131 | friend bool |
6132 | operator!=(const param_type& __p1, const param_type& __p2) |
6133 | { return !(__p1 == __p2); } |
6134 | #endif |
6135 | |
6136 | private: |
6137 | void |
6138 | _M_initialize(); |
6139 | |
6140 | std::vector<_RealType> _M_int; |
6141 | std::vector<double> _M_den; |
6142 | std::vector<double> _M_cp; |
6143 | std::vector<double> _M_m; |
6144 | }; |
6145 | |
6146 | piecewise_linear_distribution() |
6147 | : _M_param() |
6148 | { } |
6149 | |
6150 | template<typename _InputIteratorB, typename _InputIteratorW> |
6151 | piecewise_linear_distribution(_InputIteratorB __bfirst, |
6152 | _InputIteratorB __bend, |
6153 | _InputIteratorW __wbegin) |
6154 | : _M_param(__bfirst, __bend, __wbegin) |
6155 | { } |
6156 | |
6157 | template<typename _Func> |
6158 | piecewise_linear_distribution(initializer_list<_RealType> __bl, |
6159 | _Func __fw) |
6160 | : _M_param(__bl, __fw) |
6161 | { } |
6162 | |
6163 | template<typename _Func> |
6164 | piecewise_linear_distribution(size_t __nw, |
6165 | _RealType __xmin, _RealType __xmax, |
6166 | _Func __fw) |
6167 | : _M_param(__nw, __xmin, __xmax, __fw) |
6168 | { } |
6169 | |
6170 | explicit |
6171 | piecewise_linear_distribution(const param_type& __p) |
6172 | : _M_param(__p) |
6173 | { } |
6174 | |
6175 | /** |
6176 | * Resets the distribution state. |
6177 | */ |
6178 | void |
6179 | reset() |
6180 | { } |
6181 | |
6182 | /** |
6183 | * @brief Return the intervals of the distribution. |
6184 | */ |
6185 | std::vector<_RealType> |
6186 | intervals() const |
6187 | { |
6188 | if (_M_param._M_int.empty()) |
6189 | { |
6190 | std::vector<_RealType> __tmp(2); |
6191 | __tmp[1] = _RealType(1); |
6192 | return __tmp; |
6193 | } |
6194 | else |
6195 | return _M_param._M_int; |
6196 | } |
6197 | |
6198 | /** |
6199 | * @brief Return a vector of the probability densities of the |
6200 | * distribution. |
6201 | */ |
6202 | std::vector<double> |
6203 | densities() const |
6204 | { |
6205 | return _M_param._M_den.empty() |
6206 | ? std::vector<double>(2, 1.0) : _M_param._M_den; |
6207 | } |
6208 | |
6209 | /** |
6210 | * @brief Returns the parameter set of the distribution. |
6211 | */ |
6212 | param_type |
6213 | param() const |
6214 | { return _M_param; } |
6215 | |
6216 | /** |
6217 | * @brief Sets the parameter set of the distribution. |
6218 | * @param __param The new parameter set of the distribution. |
6219 | */ |
6220 | void |
6221 | param(const param_type& __param) |
6222 | { _M_param = __param; } |
6223 | |
6224 | /** |
6225 | * @brief Returns the greatest lower bound value of the distribution. |
6226 | */ |
6227 | result_type |
6228 | min() const |
6229 | { |
6230 | return _M_param._M_int.empty() |
6231 | ? result_type(0) : _M_param._M_int.front(); |
6232 | } |
6233 | |
6234 | /** |
6235 | * @brief Returns the least upper bound value of the distribution. |
6236 | */ |
6237 | result_type |
6238 | max() const |
6239 | { |
6240 | return _M_param._M_int.empty() |
6241 | ? result_type(1) : _M_param._M_int.back(); |
6242 | } |
6243 | |
6244 | /** |
6245 | * @brief Generating functions. |
6246 | */ |
6247 | template<typename _UniformRandomNumberGenerator> |
6248 | result_type |
6249 | operator()(_UniformRandomNumberGenerator& __urng) |
6250 | { return this->operator()(__urng, _M_param); } |
6251 | |
6252 | template<typename _UniformRandomNumberGenerator> |
6253 | result_type |
6254 | operator()(_UniformRandomNumberGenerator& __urng, |
6255 | const param_type& __p); |
6256 | |
6257 | template<typename _ForwardIterator, |
6258 | typename _UniformRandomNumberGenerator> |
6259 | void |
6260 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
6261 | _UniformRandomNumberGenerator& __urng) |
6262 | { this->__generate(__f, __t, __urng, _M_param); } |
6263 | |
6264 | template<typename _ForwardIterator, |
6265 | typename _UniformRandomNumberGenerator> |
6266 | void |
6267 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
6268 | _UniformRandomNumberGenerator& __urng, |
6269 | const param_type& __p) |
6270 | { this->__generate_impl(__f, __t, __urng, __p); } |
6271 | |
6272 | template<typename _UniformRandomNumberGenerator> |
6273 | void |
6274 | __generate(result_type* __f, result_type* __t, |
6275 | _UniformRandomNumberGenerator& __urng, |
6276 | const param_type& __p) |
6277 | { this->__generate_impl(__f, __t, __urng, __p); } |
6278 | |
6279 | /** |
6280 | * @brief Return true if two piecewise linear distributions have the |
6281 | * same parameters. |
6282 | */ |
6283 | friend bool |
6284 | operator==(const piecewise_linear_distribution& __d1, |
6285 | const piecewise_linear_distribution& __d2) |
6286 | { return __d1._M_param == __d2._M_param; } |
6287 | |
6288 | /** |
6289 | * @brief Inserts a %piecewise_linear_distribution random number |
6290 | * distribution @p __x into the output stream @p __os. |
6291 | * |
6292 | * @param __os An output stream. |
6293 | * @param __x A %piecewise_linear_distribution random number |
6294 | * distribution. |
6295 | * |
6296 | * @returns The output stream with the state of @p __x inserted or in |
6297 | * an error state. |
6298 | */ |
6299 | template<typename _RealType1, typename _CharT, typename _Traits> |
6300 | friend std::basic_ostream<_CharT, _Traits>& |
6301 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
6302 | const std::piecewise_linear_distribution<_RealType1>& __x); |
6303 | |
6304 | /** |
6305 | * @brief Extracts a %piecewise_linear_distribution random number |
6306 | * distribution @p __x from the input stream @p __is. |
6307 | * |
6308 | * @param __is An input stream. |
6309 | * @param __x A %piecewise_linear_distribution random number |
6310 | * generator engine. |
6311 | * |
6312 | * @returns The input stream with @p __x extracted or in an error |
6313 | * state. |
6314 | */ |
6315 | template<typename _RealType1, typename _CharT, typename _Traits> |
6316 | friend std::basic_istream<_CharT, _Traits>& |
6317 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
6318 | std::piecewise_linear_distribution<_RealType1>& __x); |
6319 | |
6320 | private: |
6321 | template<typename _ForwardIterator, |
6322 | typename _UniformRandomNumberGenerator> |
6323 | void |
6324 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
6325 | _UniformRandomNumberGenerator& __urng, |
6326 | const param_type& __p); |
6327 | |
6328 | param_type _M_param; |
6329 | }; |
6330 | |
6331 | #if __cpp_impl_three_way_comparison < 201907L |
6332 | /** |
6333 | * @brief Return true if two piecewise linear distributions have |
6334 | * different parameters. |
6335 | */ |
6336 | template<typename _RealType> |
6337 | inline bool |
6338 | operator!=(const std::piecewise_linear_distribution<_RealType>& __d1, |
6339 | const std::piecewise_linear_distribution<_RealType>& __d2) |
6340 | { return !(__d1 == __d2); } |
6341 | #endif |
6342 | |
6343 | /// @} group random_distributions_sampling |
6344 | |
6345 | /// @} *group random_distributions |
6346 | |
6347 | /** |
6348 | * @addtogroup random_utilities Random Number Utilities |
6349 | * @ingroup random |
6350 | * @{ |
6351 | */ |
6352 | |
6353 | /** |
6354 | * @brief The seed_seq class generates sequences of seeds for random |
6355 | * number generators. |
6356 | * |
6357 | * @headerfile random |
6358 | * @since C++11 |
6359 | */ |
6360 | class seed_seq |
6361 | { |
6362 | public: |
6363 | /** The type of the seed vales. */ |
6364 | typedef uint_least32_t result_type; |
6365 | |
6366 | /** Default constructor. */ |
6367 | seed_seq() noexcept |
6368 | : _M_v() |
6369 | { } |
6370 | |
6371 | template<typename _IntType, typename = _Require<is_integral<_IntType>>> |
6372 | seed_seq(std::initializer_list<_IntType> __il); |
6373 | |
6374 | template<typename _InputIterator> |
6375 | seed_seq(_InputIterator __begin, _InputIterator __end); |
6376 | |
6377 | // generating functions |
6378 | template<typename _RandomAccessIterator> |
6379 | void |
6380 | generate(_RandomAccessIterator __begin, _RandomAccessIterator __end); |
6381 | |
6382 | // property functions |
6383 | size_t size() const noexcept |
6384 | { return _M_v.size(); } |
6385 | |
6386 | template<typename _OutputIterator> |
6387 | void |
6388 | param(_OutputIterator __dest) const |
6389 | { std::copy(_M_v.begin(), _M_v.end(), __dest); } |
6390 | |
6391 | // no copy functions |
6392 | seed_seq(const seed_seq&) = delete; |
6393 | seed_seq& operator=(const seed_seq&) = delete; |
6394 | |
6395 | private: |
6396 | std::vector<result_type> _M_v; |
6397 | }; |
6398 | |
6399 | /// @} group random_utilities |
6400 | |
6401 | /// @} group random |
6402 | |
6403 | _GLIBCXX_END_NAMESPACE_VERSION |
6404 | } // namespace std |
6405 | |
6406 | #endif |
6407 | |