1 | // random number generation -*- C++ -*- |
2 | |
3 | // Copyright (C) 2009-2017 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 | /** |
52 | * @brief A function template for converting the output of a (integral) |
53 | * uniform random number generator to a floatng point result in the range |
54 | * [0-1). |
55 | */ |
56 | template<typename _RealType, size_t __bits, |
57 | typename _UniformRandomNumberGenerator> |
58 | _RealType |
59 | generate_canonical(_UniformRandomNumberGenerator& __g); |
60 | |
61 | _GLIBCXX_END_NAMESPACE_VERSION |
62 | |
63 | /* |
64 | * Implementation-space details. |
65 | */ |
66 | namespace __detail |
67 | { |
68 | _GLIBCXX_BEGIN_NAMESPACE_VERSION |
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 const _UIntType __value = 0; }; |
75 | |
76 | template<typename _UIntType, size_t __w> |
77 | struct _Shift<_UIntType, __w, true> |
78 | { static const _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 | { typedef unsigned int type; }; |
95 | |
96 | template<int __s> |
97 | struct _Select_uint_least_t<__s, 3> |
98 | { typedef unsigned long type; }; |
99 | |
100 | template<int __s> |
101 | struct _Select_uint_least_t<__s, 2> |
102 | { typedef unsigned long long type; }; |
103 | |
104 | #ifdef _GLIBCXX_USE_INT128 |
105 | template<int __s> |
106 | struct _Select_uint_least_t<__s, 1> |
107 | { typedef unsigned __int128 type; }; |
108 | #endif |
109 | |
110 | // Assume a != 0, a < m, c < m, x < m. |
111 | template<typename _Tp, _Tp __m, _Tp __a, _Tp __c, |
112 | bool __big_enough = (!(__m & (__m - 1)) |
113 | || (_Tp(-1) - __c) / __a >= __m - 1), |
114 | bool __schrage_ok = __m % __a < __m / __a> |
115 | struct _Mod |
116 | { |
117 | typedef typename _Select_uint_least_t<std::__lg(__a) |
118 | + std::__lg(__m) + 2>::type _Tp2; |
119 | static _Tp |
120 | __calc(_Tp __x) |
121 | { return static_cast<_Tp>((_Tp2(__a) * __x + __c) % __m); } |
122 | }; |
123 | |
124 | // Schrage. |
125 | template<typename _Tp, _Tp __m, _Tp __a, _Tp __c> |
126 | struct _Mod<_Tp, __m, __a, __c, false, true> |
127 | { |
128 | static _Tp |
129 | __calc(_Tp __x); |
130 | }; |
131 | |
132 | // Special cases: |
133 | // - for m == 2^n or m == 0, unsigned integer overflow is safe. |
134 | // - a * (m - 1) + c fits in _Tp, there is no overflow. |
135 | template<typename _Tp, _Tp __m, _Tp __a, _Tp __c, bool __s> |
136 | struct _Mod<_Tp, __m, __a, __c, true, __s> |
137 | { |
138 | static _Tp |
139 | __calc(_Tp __x) |
140 | { |
141 | _Tp __res = __a * __x + __c; |
142 | if (__m) |
143 | __res %= __m; |
144 | return __res; |
145 | } |
146 | }; |
147 | |
148 | template<typename _Tp, _Tp __m, _Tp __a = 1, _Tp __c = 0> |
149 | inline _Tp |
150 | __mod(_Tp __x) |
151 | { return _Mod<_Tp, __m, __a, __c>::__calc(__x); } |
152 | |
153 | /* |
154 | * An adaptor class for converting the output of any Generator into |
155 | * the input for a specific Distribution. |
156 | */ |
157 | template<typename _Engine, typename _DInputType> |
158 | struct _Adaptor |
159 | { |
160 | static_assert(std::is_floating_point<_DInputType>::value, |
161 | "template argument must be a floating point type" ); |
162 | |
163 | public: |
164 | _Adaptor(_Engine& __g) |
165 | : _M_g(__g) { } |
166 | |
167 | _DInputType |
168 | min() const |
169 | { return _DInputType(0); } |
170 | |
171 | _DInputType |
172 | max() const |
173 | { return _DInputType(1); } |
174 | |
175 | /* |
176 | * Converts a value generated by the adapted random number generator |
177 | * into a value in the input domain for the dependent random number |
178 | * distribution. |
179 | */ |
180 | _DInputType |
181 | operator()() |
182 | { |
183 | return std::generate_canonical<_DInputType, |
184 | std::numeric_limits<_DInputType>::digits, |
185 | _Engine>(_M_g); |
186 | } |
187 | |
188 | private: |
189 | _Engine& _M_g; |
190 | }; |
191 | |
192 | _GLIBCXX_END_NAMESPACE_VERSION |
193 | } // namespace __detail |
194 | |
195 | _GLIBCXX_BEGIN_NAMESPACE_VERSION |
196 | |
197 | /** |
198 | * @addtogroup random_generators Random Number Generators |
199 | * @ingroup random |
200 | * |
201 | * These classes define objects which provide random or pseudorandom |
202 | * numbers, either from a discrete or a continuous interval. The |
203 | * random number generator supplied as a part of this library are |
204 | * all uniform random number generators which provide a sequence of |
205 | * random number uniformly distributed over their range. |
206 | * |
207 | * A number generator is a function object with an operator() that |
208 | * takes zero arguments and returns a number. |
209 | * |
210 | * A compliant random number generator must satisfy the following |
211 | * requirements. <table border=1 cellpadding=10 cellspacing=0> |
212 | * <caption align=top>Random Number Generator Requirements</caption> |
213 | * <tr><td>To be documented.</td></tr> </table> |
214 | * |
215 | * @{ |
216 | */ |
217 | |
218 | /** |
219 | * @brief A model of a linear congruential random number generator. |
220 | * |
221 | * A random number generator that produces pseudorandom numbers via |
222 | * linear function: |
223 | * @f[ |
224 | * x_{i+1}\leftarrow(ax_{i} + c) \bmod m |
225 | * @f] |
226 | * |
227 | * The template parameter @p _UIntType must be an unsigned integral type |
228 | * large enough to store values up to (__m-1). If the template parameter |
229 | * @p __m is 0, the modulus @p __m used is |
230 | * std::numeric_limits<_UIntType>::max() plus 1. Otherwise, the template |
231 | * parameters @p __a and @p __c must be less than @p __m. |
232 | * |
233 | * The size of the state is @f$1@f$. |
234 | */ |
235 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m> |
236 | class linear_congruential_engine |
237 | { |
238 | static_assert(std::is_unsigned<_UIntType>::value, |
239 | "result_type must be an unsigned integral type" ); |
240 | static_assert(__m == 0u || (__a < __m && __c < __m), |
241 | "template argument substituting __m out of bounds" ); |
242 | |
243 | public: |
244 | /** The type of the generated random value. */ |
245 | typedef _UIntType result_type; |
246 | |
247 | /** The multiplier. */ |
248 | static constexpr result_type multiplier = __a; |
249 | /** An increment. */ |
250 | static constexpr result_type increment = __c; |
251 | /** The modulus. */ |
252 | static constexpr result_type modulus = __m; |
253 | static constexpr result_type default_seed = 1u; |
254 | |
255 | /** |
256 | * @brief Constructs a %linear_congruential_engine random number |
257 | * generator engine with seed @p __s. The default seed value |
258 | * is 1. |
259 | * |
260 | * @param __s The initial seed value. |
261 | */ |
262 | explicit |
263 | linear_congruential_engine(result_type __s = default_seed) |
264 | { seed(__s); } |
265 | |
266 | /** |
267 | * @brief Constructs a %linear_congruential_engine random number |
268 | * generator engine seeded from the seed sequence @p __q. |
269 | * |
270 | * @param __q the seed sequence. |
271 | */ |
272 | template<typename _Sseq, typename = typename |
273 | std::enable_if<!std::is_same<_Sseq, linear_congruential_engine>::value> |
274 | ::type> |
275 | explicit |
276 | linear_congruential_engine(_Sseq& __q) |
277 | { seed(__q); } |
278 | |
279 | /** |
280 | * @brief Reseeds the %linear_congruential_engine random number generator |
281 | * engine sequence to the seed @p __s. |
282 | * |
283 | * @param __s The new seed. |
284 | */ |
285 | void |
286 | seed(result_type __s = default_seed); |
287 | |
288 | /** |
289 | * @brief Reseeds the %linear_congruential_engine random number generator |
290 | * engine |
291 | * sequence using values from the seed sequence @p __q. |
292 | * |
293 | * @param __q the seed sequence. |
294 | */ |
295 | template<typename _Sseq> |
296 | typename std::enable_if<std::is_class<_Sseq>::value>::type |
297 | seed(_Sseq& __q); |
298 | |
299 | /** |
300 | * @brief Gets the smallest possible value in the output range. |
301 | * |
302 | * The minimum depends on the @p __c parameter: if it is zero, the |
303 | * minimum generated must be > 0, otherwise 0 is allowed. |
304 | */ |
305 | static constexpr result_type |
306 | min() |
307 | { return __c == 0u ? 1u : 0u; } |
308 | |
309 | /** |
310 | * @brief Gets the largest possible value in the output range. |
311 | */ |
312 | static constexpr result_type |
313 | max() |
314 | { return __m - 1u; } |
315 | |
316 | /** |
317 | * @brief Discard a sequence of random numbers. |
318 | */ |
319 | void |
320 | discard(unsigned long long __z) |
321 | { |
322 | for (; __z != 0ULL; --__z) |
323 | (*this)(); |
324 | } |
325 | |
326 | /** |
327 | * @brief Gets the next random number in the sequence. |
328 | */ |
329 | result_type |
330 | operator()() |
331 | { |
332 | _M_x = __detail::__mod<_UIntType, __m, __a, __c>(_M_x); |
333 | return _M_x; |
334 | } |
335 | |
336 | /** |
337 | * @brief Compares two linear congruential random number generator |
338 | * objects of the same type for equality. |
339 | * |
340 | * @param __lhs A linear congruential random number generator object. |
341 | * @param __rhs Another linear congruential random number generator |
342 | * object. |
343 | * |
344 | * @returns true if the infinite sequences of generated values |
345 | * would be equal, false otherwise. |
346 | */ |
347 | friend bool |
348 | operator==(const linear_congruential_engine& __lhs, |
349 | const linear_congruential_engine& __rhs) |
350 | { return __lhs._M_x == __rhs._M_x; } |
351 | |
352 | /** |
353 | * @brief Writes the textual representation of the state x(i) of x to |
354 | * @p __os. |
355 | * |
356 | * @param __os The output stream. |
357 | * @param __lcr A % linear_congruential_engine random number generator. |
358 | * @returns __os. |
359 | */ |
360 | template<typename _UIntType1, _UIntType1 __a1, _UIntType1 __c1, |
361 | _UIntType1 __m1, typename _CharT, typename _Traits> |
362 | friend std::basic_ostream<_CharT, _Traits>& |
363 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
364 | const std::linear_congruential_engine<_UIntType1, |
365 | __a1, __c1, __m1>& __lcr); |
366 | |
367 | /** |
368 | * @brief Sets the state of the engine by reading its textual |
369 | * representation from @p __is. |
370 | * |
371 | * The textual representation must have been previously written using |
372 | * an output stream whose imbued locale and whose type's template |
373 | * specialization arguments _CharT and _Traits were the same as those |
374 | * of @p __is. |
375 | * |
376 | * @param __is The input stream. |
377 | * @param __lcr A % linear_congruential_engine random number generator. |
378 | * @returns __is. |
379 | */ |
380 | template<typename _UIntType1, _UIntType1 __a1, _UIntType1 __c1, |
381 | _UIntType1 __m1, typename _CharT, typename _Traits> |
382 | friend std::basic_istream<_CharT, _Traits>& |
383 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
384 | std::linear_congruential_engine<_UIntType1, __a1, |
385 | __c1, __m1>& __lcr); |
386 | |
387 | private: |
388 | _UIntType _M_x; |
389 | }; |
390 | |
391 | /** |
392 | * @brief Compares two linear congruential random number generator |
393 | * objects of the same type for inequality. |
394 | * |
395 | * @param __lhs A linear congruential random number generator object. |
396 | * @param __rhs Another linear congruential random number generator |
397 | * object. |
398 | * |
399 | * @returns true if the infinite sequences of generated values |
400 | * would be different, false otherwise. |
401 | */ |
402 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m> |
403 | inline bool |
404 | operator!=(const std::linear_congruential_engine<_UIntType, __a, |
405 | __c, __m>& __lhs, |
406 | const std::linear_congruential_engine<_UIntType, __a, |
407 | __c, __m>& __rhs) |
408 | { return !(__lhs == __rhs); } |
409 | |
410 | |
411 | /** |
412 | * A generalized feedback shift register discrete random number generator. |
413 | * |
414 | * This algorithm avoids multiplication and division and is designed to be |
415 | * friendly to a pipelined architecture. If the parameters are chosen |
416 | * correctly, this generator will produce numbers with a very long period and |
417 | * fairly good apparent entropy, although still not cryptographically strong. |
418 | * |
419 | * The best way to use this generator is with the predefined mt19937 class. |
420 | * |
421 | * This algorithm was originally invented by Makoto Matsumoto and |
422 | * Takuji Nishimura. |
423 | * |
424 | * @tparam __w Word size, the number of bits in each element of |
425 | * the state vector. |
426 | * @tparam __n The degree of recursion. |
427 | * @tparam __m The period parameter. |
428 | * @tparam __r The separation point bit index. |
429 | * @tparam __a The last row of the twist matrix. |
430 | * @tparam __u The first right-shift tempering matrix parameter. |
431 | * @tparam __d The first right-shift tempering matrix mask. |
432 | * @tparam __s The first left-shift tempering matrix parameter. |
433 | * @tparam __b The first left-shift tempering matrix mask. |
434 | * @tparam __t The second left-shift tempering matrix parameter. |
435 | * @tparam __c The second left-shift tempering matrix mask. |
436 | * @tparam __l The second right-shift tempering matrix parameter. |
437 | * @tparam __f Initialization multiplier. |
438 | */ |
439 | template<typename _UIntType, size_t __w, |
440 | size_t __n, size_t __m, size_t __r, |
441 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, |
442 | _UIntType __b, size_t __t, |
443 | _UIntType __c, size_t __l, _UIntType __f> |
444 | class mersenne_twister_engine |
445 | { |
446 | static_assert(std::is_unsigned<_UIntType>::value, |
447 | "result_type must be an unsigned integral type" ); |
448 | static_assert(1u <= __m && __m <= __n, |
449 | "template argument substituting __m out of bounds" ); |
450 | static_assert(__r <= __w, "template argument substituting " |
451 | "__r out of bound" ); |
452 | static_assert(__u <= __w, "template argument substituting " |
453 | "__u out of bound" ); |
454 | static_assert(__s <= __w, "template argument substituting " |
455 | "__s out of bound" ); |
456 | static_assert(__t <= __w, "template argument substituting " |
457 | "__t out of bound" ); |
458 | static_assert(__l <= __w, "template argument substituting " |
459 | "__l out of bound" ); |
460 | static_assert(__w <= std::numeric_limits<_UIntType>::digits, |
461 | "template argument substituting __w out of bound" ); |
462 | static_assert(__a <= (__detail::_Shift<_UIntType, __w>::__value - 1), |
463 | "template argument substituting __a out of bound" ); |
464 | static_assert(__b <= (__detail::_Shift<_UIntType, __w>::__value - 1), |
465 | "template argument substituting __b out of bound" ); |
466 | static_assert(__c <= (__detail::_Shift<_UIntType, __w>::__value - 1), |
467 | "template argument substituting __c out of bound" ); |
468 | static_assert(__d <= (__detail::_Shift<_UIntType, __w>::__value - 1), |
469 | "template argument substituting __d out of bound" ); |
470 | static_assert(__f <= (__detail::_Shift<_UIntType, __w>::__value - 1), |
471 | "template argument substituting __f out of bound" ); |
472 | |
473 | public: |
474 | /** The type of the generated random value. */ |
475 | typedef _UIntType result_type; |
476 | |
477 | // parameter values |
478 | static constexpr size_t word_size = __w; |
479 | static constexpr size_t state_size = __n; |
480 | static constexpr size_t shift_size = __m; |
481 | static constexpr size_t mask_bits = __r; |
482 | static constexpr result_type xor_mask = __a; |
483 | static constexpr size_t tempering_u = __u; |
484 | static constexpr result_type tempering_d = __d; |
485 | static constexpr size_t tempering_s = __s; |
486 | static constexpr result_type tempering_b = __b; |
487 | static constexpr size_t tempering_t = __t; |
488 | static constexpr result_type tempering_c = __c; |
489 | static constexpr size_t tempering_l = __l; |
490 | static constexpr result_type initialization_multiplier = __f; |
491 | static constexpr result_type default_seed = 5489u; |
492 | |
493 | // constructors and member function |
494 | explicit |
495 | mersenne_twister_engine(result_type __sd = default_seed) |
496 | { seed(__sd); } |
497 | |
498 | /** |
499 | * @brief Constructs a %mersenne_twister_engine random number generator |
500 | * engine seeded from the seed sequence @p __q. |
501 | * |
502 | * @param __q the seed sequence. |
503 | */ |
504 | template<typename _Sseq, typename = typename |
505 | std::enable_if<!std::is_same<_Sseq, mersenne_twister_engine>::value> |
506 | ::type> |
507 | explicit |
508 | mersenne_twister_engine(_Sseq& __q) |
509 | { seed(__q); } |
510 | |
511 | void |
512 | seed(result_type __sd = default_seed); |
513 | |
514 | template<typename _Sseq> |
515 | typename std::enable_if<std::is_class<_Sseq>::value>::type |
516 | seed(_Sseq& __q); |
517 | |
518 | /** |
519 | * @brief Gets the smallest possible value in the output range. |
520 | */ |
521 | static constexpr result_type |
522 | min() |
523 | { return 0; }; |
524 | |
525 | /** |
526 | * @brief Gets the largest possible value in the output range. |
527 | */ |
528 | static constexpr result_type |
529 | max() |
530 | { return __detail::_Shift<_UIntType, __w>::__value - 1; } |
531 | |
532 | /** |
533 | * @brief Discard a sequence of random numbers. |
534 | */ |
535 | void |
536 | discard(unsigned long long __z); |
537 | |
538 | result_type |
539 | operator()(); |
540 | |
541 | /** |
542 | * @brief Compares two % mersenne_twister_engine random number generator |
543 | * objects of the same type for equality. |
544 | * |
545 | * @param __lhs A % mersenne_twister_engine random number generator |
546 | * object. |
547 | * @param __rhs Another % mersenne_twister_engine random number |
548 | * generator object. |
549 | * |
550 | * @returns true if the infinite sequences of generated values |
551 | * would be equal, false otherwise. |
552 | */ |
553 | friend bool |
554 | operator==(const mersenne_twister_engine& __lhs, |
555 | const mersenne_twister_engine& __rhs) |
556 | { return (std::equal(__lhs._M_x, __lhs._M_x + state_size, __rhs._M_x) |
557 | && __lhs._M_p == __rhs._M_p); } |
558 | |
559 | /** |
560 | * @brief Inserts the current state of a % mersenne_twister_engine |
561 | * random number generator engine @p __x into the output stream |
562 | * @p __os. |
563 | * |
564 | * @param __os An output stream. |
565 | * @param __x A % mersenne_twister_engine random number generator |
566 | * engine. |
567 | * |
568 | * @returns The output stream with the state of @p __x inserted or in |
569 | * an error state. |
570 | */ |
571 | template<typename _UIntType1, |
572 | size_t __w1, size_t __n1, |
573 | size_t __m1, size_t __r1, |
574 | _UIntType1 __a1, size_t __u1, |
575 | _UIntType1 __d1, size_t __s1, |
576 | _UIntType1 __b1, size_t __t1, |
577 | _UIntType1 __c1, size_t __l1, _UIntType1 __f1, |
578 | typename _CharT, typename _Traits> |
579 | friend std::basic_ostream<_CharT, _Traits>& |
580 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
581 | const std::mersenne_twister_engine<_UIntType1, __w1, __n1, |
582 | __m1, __r1, __a1, __u1, __d1, __s1, __b1, __t1, __c1, |
583 | __l1, __f1>& __x); |
584 | |
585 | /** |
586 | * @brief Extracts the current state of a % mersenne_twister_engine |
587 | * random number generator engine @p __x from the input stream |
588 | * @p __is. |
589 | * |
590 | * @param __is An input stream. |
591 | * @param __x A % mersenne_twister_engine random number generator |
592 | * engine. |
593 | * |
594 | * @returns The input stream with the state of @p __x extracted or in |
595 | * an error state. |
596 | */ |
597 | template<typename _UIntType1, |
598 | size_t __w1, size_t __n1, |
599 | size_t __m1, size_t __r1, |
600 | _UIntType1 __a1, size_t __u1, |
601 | _UIntType1 __d1, size_t __s1, |
602 | _UIntType1 __b1, size_t __t1, |
603 | _UIntType1 __c1, size_t __l1, _UIntType1 __f1, |
604 | typename _CharT, typename _Traits> |
605 | friend std::basic_istream<_CharT, _Traits>& |
606 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
607 | std::mersenne_twister_engine<_UIntType1, __w1, __n1, __m1, |
608 | __r1, __a1, __u1, __d1, __s1, __b1, __t1, __c1, |
609 | __l1, __f1>& __x); |
610 | |
611 | private: |
612 | void _M_gen_rand(); |
613 | |
614 | _UIntType _M_x[state_size]; |
615 | size_t _M_p; |
616 | }; |
617 | |
618 | /** |
619 | * @brief Compares two % mersenne_twister_engine random number generator |
620 | * objects of the same type for inequality. |
621 | * |
622 | * @param __lhs A % mersenne_twister_engine random number generator |
623 | * object. |
624 | * @param __rhs Another % mersenne_twister_engine random number |
625 | * generator object. |
626 | * |
627 | * @returns true if the infinite sequences of generated values |
628 | * would be different, false otherwise. |
629 | */ |
630 | template<typename _UIntType, size_t __w, |
631 | size_t __n, size_t __m, size_t __r, |
632 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, |
633 | _UIntType __b, size_t __t, |
634 | _UIntType __c, size_t __l, _UIntType __f> |
635 | inline bool |
636 | operator!=(const std::mersenne_twister_engine<_UIntType, __w, __n, __m, |
637 | __r, __a, __u, __d, __s, __b, __t, __c, __l, __f>& __lhs, |
638 | const std::mersenne_twister_engine<_UIntType, __w, __n, __m, |
639 | __r, __a, __u, __d, __s, __b, __t, __c, __l, __f>& __rhs) |
640 | { return !(__lhs == __rhs); } |
641 | |
642 | |
643 | /** |
644 | * @brief The Marsaglia-Zaman generator. |
645 | * |
646 | * This is a model of a Generalized Fibonacci discrete random number |
647 | * generator, sometimes referred to as the SWC generator. |
648 | * |
649 | * A discrete random number generator that produces pseudorandom |
650 | * numbers using: |
651 | * @f[ |
652 | * x_{i}\leftarrow(x_{i - s} - x_{i - r} - carry_{i-1}) \bmod m |
653 | * @f] |
654 | * |
655 | * The size of the state is @f$r@f$ |
656 | * and the maximum period of the generator is @f$(m^r - m^s - 1)@f$. |
657 | */ |
658 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> |
659 | class subtract_with_carry_engine |
660 | { |
661 | static_assert(std::is_unsigned<_UIntType>::value, |
662 | "result_type must be an unsigned integral type" ); |
663 | static_assert(0u < __s && __s < __r, |
664 | "0 < s < r" ); |
665 | static_assert(0u < __w && __w <= std::numeric_limits<_UIntType>::digits, |
666 | "template argument substituting __w out of bounds" ); |
667 | |
668 | public: |
669 | /** The type of the generated random value. */ |
670 | typedef _UIntType result_type; |
671 | |
672 | // parameter values |
673 | static constexpr size_t word_size = __w; |
674 | static constexpr size_t short_lag = __s; |
675 | static constexpr size_t long_lag = __r; |
676 | static constexpr result_type default_seed = 19780503u; |
677 | |
678 | /** |
679 | * @brief Constructs an explicitly seeded % subtract_with_carry_engine |
680 | * random number generator. |
681 | */ |
682 | explicit |
683 | subtract_with_carry_engine(result_type __sd = default_seed) |
684 | { seed(__sd); } |
685 | |
686 | /** |
687 | * @brief Constructs a %subtract_with_carry_engine random number engine |
688 | * seeded from the seed sequence @p __q. |
689 | * |
690 | * @param __q the seed sequence. |
691 | */ |
692 | template<typename _Sseq, typename = typename |
693 | std::enable_if<!std::is_same<_Sseq, subtract_with_carry_engine>::value> |
694 | ::type> |
695 | explicit |
696 | subtract_with_carry_engine(_Sseq& __q) |
697 | { seed(__q); } |
698 | |
699 | /** |
700 | * @brief Seeds the initial state @f$x_0@f$ of the random number |
701 | * generator. |
702 | * |
703 | * N1688[4.19] modifies this as follows. If @p __value == 0, |
704 | * sets value to 19780503. In any case, with a linear |
705 | * congruential generator lcg(i) having parameters @f$ m_{lcg} = |
706 | * 2147483563, a_{lcg} = 40014, c_{lcg} = 0, and lcg(0) = value |
707 | * @f$, sets @f$ x_{-r} \dots x_{-1} @f$ to @f$ lcg(1) \bmod m |
708 | * \dots lcg(r) \bmod m @f$ respectively. If @f$ x_{-1} = 0 @f$ |
709 | * set carry to 1, otherwise sets carry to 0. |
710 | */ |
711 | void |
712 | seed(result_type __sd = default_seed); |
713 | |
714 | /** |
715 | * @brief Seeds the initial state @f$x_0@f$ of the |
716 | * % subtract_with_carry_engine random number generator. |
717 | */ |
718 | template<typename _Sseq> |
719 | typename std::enable_if<std::is_class<_Sseq>::value>::type |
720 | seed(_Sseq& __q); |
721 | |
722 | /** |
723 | * @brief Gets the inclusive minimum value of the range of random |
724 | * integers returned by this generator. |
725 | */ |
726 | static constexpr result_type |
727 | min() |
728 | { return 0; } |
729 | |
730 | /** |
731 | * @brief Gets the inclusive maximum value of the range of random |
732 | * integers returned by this generator. |
733 | */ |
734 | static constexpr result_type |
735 | max() |
736 | { return __detail::_Shift<_UIntType, __w>::__value - 1; } |
737 | |
738 | /** |
739 | * @brief Discard a sequence of random numbers. |
740 | */ |
741 | void |
742 | discard(unsigned long long __z) |
743 | { |
744 | for (; __z != 0ULL; --__z) |
745 | (*this)(); |
746 | } |
747 | |
748 | /** |
749 | * @brief Gets the next random number in the sequence. |
750 | */ |
751 | result_type |
752 | operator()(); |
753 | |
754 | /** |
755 | * @brief Compares two % subtract_with_carry_engine random number |
756 | * generator objects of the same type for equality. |
757 | * |
758 | * @param __lhs A % subtract_with_carry_engine random number generator |
759 | * object. |
760 | * @param __rhs Another % subtract_with_carry_engine random number |
761 | * generator object. |
762 | * |
763 | * @returns true if the infinite sequences of generated values |
764 | * would be equal, false otherwise. |
765 | */ |
766 | friend bool |
767 | operator==(const subtract_with_carry_engine& __lhs, |
768 | const subtract_with_carry_engine& __rhs) |
769 | { return (std::equal(__lhs._M_x, __lhs._M_x + long_lag, __rhs._M_x) |
770 | && __lhs._M_carry == __rhs._M_carry |
771 | && __lhs._M_p == __rhs._M_p); } |
772 | |
773 | /** |
774 | * @brief Inserts the current state of a % subtract_with_carry_engine |
775 | * random number generator engine @p __x into the output stream |
776 | * @p __os. |
777 | * |
778 | * @param __os An output stream. |
779 | * @param __x A % subtract_with_carry_engine random number generator |
780 | * engine. |
781 | * |
782 | * @returns The output stream with the state of @p __x inserted or in |
783 | * an error state. |
784 | */ |
785 | template<typename _UIntType1, size_t __w1, size_t __s1, size_t __r1, |
786 | typename _CharT, typename _Traits> |
787 | friend std::basic_ostream<_CharT, _Traits>& |
788 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
789 | const std::subtract_with_carry_engine<_UIntType1, __w1, |
790 | __s1, __r1>& __x); |
791 | |
792 | /** |
793 | * @brief Extracts the current state of a % subtract_with_carry_engine |
794 | * random number generator engine @p __x from the input stream |
795 | * @p __is. |
796 | * |
797 | * @param __is An input stream. |
798 | * @param __x A % subtract_with_carry_engine random number generator |
799 | * engine. |
800 | * |
801 | * @returns The input stream with the state of @p __x extracted or in |
802 | * an error state. |
803 | */ |
804 | template<typename _UIntType1, size_t __w1, size_t __s1, size_t __r1, |
805 | typename _CharT, typename _Traits> |
806 | friend std::basic_istream<_CharT, _Traits>& |
807 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
808 | std::subtract_with_carry_engine<_UIntType1, __w1, |
809 | __s1, __r1>& __x); |
810 | |
811 | private: |
812 | /// The state of the generator. This is a ring buffer. |
813 | _UIntType _M_x[long_lag]; |
814 | _UIntType _M_carry; ///< The carry |
815 | size_t _M_p; ///< Current index of x(i - r). |
816 | }; |
817 | |
818 | /** |
819 | * @brief Compares two % subtract_with_carry_engine random number |
820 | * generator objects of the same type for inequality. |
821 | * |
822 | * @param __lhs A % subtract_with_carry_engine random number generator |
823 | * object. |
824 | * @param __rhs Another % subtract_with_carry_engine random number |
825 | * generator object. |
826 | * |
827 | * @returns true if the infinite sequences of generated values |
828 | * would be different, false otherwise. |
829 | */ |
830 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> |
831 | inline bool |
832 | operator!=(const std::subtract_with_carry_engine<_UIntType, __w, |
833 | __s, __r>& __lhs, |
834 | const std::subtract_with_carry_engine<_UIntType, __w, |
835 | __s, __r>& __rhs) |
836 | { return !(__lhs == __rhs); } |
837 | |
838 | |
839 | /** |
840 | * Produces random numbers from some base engine by discarding blocks of |
841 | * data. |
842 | * |
843 | * 0 <= @p __r <= @p __p |
844 | */ |
845 | template<typename _RandomNumberEngine, size_t __p, size_t __r> |
846 | class discard_block_engine |
847 | { |
848 | static_assert(1 <= __r && __r <= __p, |
849 | "template argument substituting __r out of bounds" ); |
850 | |
851 | public: |
852 | /** The type of the generated random value. */ |
853 | typedef typename _RandomNumberEngine::result_type result_type; |
854 | |
855 | // parameter values |
856 | static constexpr size_t block_size = __p; |
857 | static constexpr size_t used_block = __r; |
858 | |
859 | /** |
860 | * @brief Constructs a default %discard_block_engine engine. |
861 | * |
862 | * The underlying engine is default constructed as well. |
863 | */ |
864 | discard_block_engine() |
865 | : _M_b(), _M_n(0) { } |
866 | |
867 | /** |
868 | * @brief Copy constructs a %discard_block_engine engine. |
869 | * |
870 | * Copies an existing base class random number generator. |
871 | * @param __rng An existing (base class) engine object. |
872 | */ |
873 | explicit |
874 | discard_block_engine(const _RandomNumberEngine& __rng) |
875 | : _M_b(__rng), _M_n(0) { } |
876 | |
877 | /** |
878 | * @brief Move constructs a %discard_block_engine engine. |
879 | * |
880 | * Copies an existing base class random number generator. |
881 | * @param __rng An existing (base class) engine object. |
882 | */ |
883 | explicit |
884 | discard_block_engine(_RandomNumberEngine&& __rng) |
885 | : _M_b(std::move(__rng)), _M_n(0) { } |
886 | |
887 | /** |
888 | * @brief Seed constructs a %discard_block_engine engine. |
889 | * |
890 | * Constructs the underlying generator engine seeded with @p __s. |
891 | * @param __s A seed value for the base class engine. |
892 | */ |
893 | explicit |
894 | discard_block_engine(result_type __s) |
895 | : _M_b(__s), _M_n(0) { } |
896 | |
897 | /** |
898 | * @brief Generator construct a %discard_block_engine engine. |
899 | * |
900 | * @param __q A seed sequence. |
901 | */ |
902 | template<typename _Sseq, typename = typename |
903 | std::enable_if<!std::is_same<_Sseq, discard_block_engine>::value |
904 | && !std::is_same<_Sseq, _RandomNumberEngine>::value> |
905 | ::type> |
906 | explicit |
907 | discard_block_engine(_Sseq& __q) |
908 | : _M_b(__q), _M_n(0) |
909 | { } |
910 | |
911 | /** |
912 | * @brief Reseeds the %discard_block_engine object with the default |
913 | * seed for the underlying base class generator engine. |
914 | */ |
915 | void |
916 | seed() |
917 | { |
918 | _M_b.seed(); |
919 | _M_n = 0; |
920 | } |
921 | |
922 | /** |
923 | * @brief Reseeds the %discard_block_engine object with the default |
924 | * seed for the underlying base class generator engine. |
925 | */ |
926 | void |
927 | seed(result_type __s) |
928 | { |
929 | _M_b.seed(__s); |
930 | _M_n = 0; |
931 | } |
932 | |
933 | /** |
934 | * @brief Reseeds the %discard_block_engine object with the given seed |
935 | * sequence. |
936 | * @param __q A seed generator function. |
937 | */ |
938 | template<typename _Sseq> |
939 | void |
940 | seed(_Sseq& __q) |
941 | { |
942 | _M_b.seed(__q); |
943 | _M_n = 0; |
944 | } |
945 | |
946 | /** |
947 | * @brief Gets a const reference to the underlying generator engine |
948 | * object. |
949 | */ |
950 | const _RandomNumberEngine& |
951 | base() const noexcept |
952 | { return _M_b; } |
953 | |
954 | /** |
955 | * @brief Gets the minimum value in the generated random number range. |
956 | */ |
957 | static constexpr result_type |
958 | min() |
959 | { return _RandomNumberEngine::min(); } |
960 | |
961 | /** |
962 | * @brief Gets the maximum value in the generated random number range. |
963 | */ |
964 | static constexpr result_type |
965 | max() |
966 | { return _RandomNumberEngine::max(); } |
967 | |
968 | /** |
969 | * @brief Discard a sequence of random numbers. |
970 | */ |
971 | void |
972 | discard(unsigned long long __z) |
973 | { |
974 | for (; __z != 0ULL; --__z) |
975 | (*this)(); |
976 | } |
977 | |
978 | /** |
979 | * @brief Gets the next value in the generated random number sequence. |
980 | */ |
981 | result_type |
982 | operator()(); |
983 | |
984 | /** |
985 | * @brief Compares two %discard_block_engine random number generator |
986 | * objects of the same type for equality. |
987 | * |
988 | * @param __lhs A %discard_block_engine random number generator object. |
989 | * @param __rhs Another %discard_block_engine random number generator |
990 | * object. |
991 | * |
992 | * @returns true if the infinite sequences of generated values |
993 | * would be equal, false otherwise. |
994 | */ |
995 | friend bool |
996 | operator==(const discard_block_engine& __lhs, |
997 | const discard_block_engine& __rhs) |
998 | { return __lhs._M_b == __rhs._M_b && __lhs._M_n == __rhs._M_n; } |
999 | |
1000 | /** |
1001 | * @brief Inserts the current state of a %discard_block_engine random |
1002 | * number generator engine @p __x into the output stream |
1003 | * @p __os. |
1004 | * |
1005 | * @param __os An output stream. |
1006 | * @param __x A %discard_block_engine random number generator engine. |
1007 | * |
1008 | * @returns The output stream with the state of @p __x inserted or in |
1009 | * an error state. |
1010 | */ |
1011 | template<typename _RandomNumberEngine1, size_t __p1, size_t __r1, |
1012 | typename _CharT, typename _Traits> |
1013 | friend std::basic_ostream<_CharT, _Traits>& |
1014 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
1015 | const std::discard_block_engine<_RandomNumberEngine1, |
1016 | __p1, __r1>& __x); |
1017 | |
1018 | /** |
1019 | * @brief Extracts the current state of a % subtract_with_carry_engine |
1020 | * random number generator engine @p __x from the input stream |
1021 | * @p __is. |
1022 | * |
1023 | * @param __is An input stream. |
1024 | * @param __x A %discard_block_engine random number generator engine. |
1025 | * |
1026 | * @returns The input stream with the state of @p __x extracted or in |
1027 | * an error state. |
1028 | */ |
1029 | template<typename _RandomNumberEngine1, size_t __p1, size_t __r1, |
1030 | typename _CharT, typename _Traits> |
1031 | friend std::basic_istream<_CharT, _Traits>& |
1032 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
1033 | std::discard_block_engine<_RandomNumberEngine1, |
1034 | __p1, __r1>& __x); |
1035 | |
1036 | private: |
1037 | _RandomNumberEngine _M_b; |
1038 | size_t _M_n; |
1039 | }; |
1040 | |
1041 | /** |
1042 | * @brief Compares two %discard_block_engine random number generator |
1043 | * objects of the same type for inequality. |
1044 | * |
1045 | * @param __lhs A %discard_block_engine random number generator object. |
1046 | * @param __rhs Another %discard_block_engine random number generator |
1047 | * object. |
1048 | * |
1049 | * @returns true if the infinite sequences of generated values |
1050 | * would be different, false otherwise. |
1051 | */ |
1052 | template<typename _RandomNumberEngine, size_t __p, size_t __r> |
1053 | inline bool |
1054 | operator!=(const std::discard_block_engine<_RandomNumberEngine, __p, |
1055 | __r>& __lhs, |
1056 | const std::discard_block_engine<_RandomNumberEngine, __p, |
1057 | __r>& __rhs) |
1058 | { return !(__lhs == __rhs); } |
1059 | |
1060 | |
1061 | /** |
1062 | * Produces random numbers by combining random numbers from some base |
1063 | * engine to produce random numbers with a specifies number of bits @p __w. |
1064 | */ |
1065 | template<typename _RandomNumberEngine, size_t __w, typename _UIntType> |
1066 | class independent_bits_engine |
1067 | { |
1068 | static_assert(std::is_unsigned<_UIntType>::value, |
1069 | "result_type must be an unsigned integral type" ); |
1070 | static_assert(0u < __w && __w <= std::numeric_limits<_UIntType>::digits, |
1071 | "template argument substituting __w out of bounds" ); |
1072 | |
1073 | public: |
1074 | /** The type of the generated random value. */ |
1075 | typedef _UIntType result_type; |
1076 | |
1077 | /** |
1078 | * @brief Constructs a default %independent_bits_engine engine. |
1079 | * |
1080 | * The underlying engine is default constructed as well. |
1081 | */ |
1082 | independent_bits_engine() |
1083 | : _M_b() { } |
1084 | |
1085 | /** |
1086 | * @brief Copy constructs a %independent_bits_engine engine. |
1087 | * |
1088 | * Copies an existing base class random number generator. |
1089 | * @param __rng An existing (base class) engine object. |
1090 | */ |
1091 | explicit |
1092 | independent_bits_engine(const _RandomNumberEngine& __rng) |
1093 | : _M_b(__rng) { } |
1094 | |
1095 | /** |
1096 | * @brief Move constructs a %independent_bits_engine engine. |
1097 | * |
1098 | * Copies an existing base class random number generator. |
1099 | * @param __rng An existing (base class) engine object. |
1100 | */ |
1101 | explicit |
1102 | independent_bits_engine(_RandomNumberEngine&& __rng) |
1103 | : _M_b(std::move(__rng)) { } |
1104 | |
1105 | /** |
1106 | * @brief Seed constructs a %independent_bits_engine engine. |
1107 | * |
1108 | * Constructs the underlying generator engine seeded with @p __s. |
1109 | * @param __s A seed value for the base class engine. |
1110 | */ |
1111 | explicit |
1112 | independent_bits_engine(result_type __s) |
1113 | : _M_b(__s) { } |
1114 | |
1115 | /** |
1116 | * @brief Generator construct a %independent_bits_engine engine. |
1117 | * |
1118 | * @param __q A seed sequence. |
1119 | */ |
1120 | template<typename _Sseq, typename = typename |
1121 | std::enable_if<!std::is_same<_Sseq, independent_bits_engine>::value |
1122 | && !std::is_same<_Sseq, _RandomNumberEngine>::value> |
1123 | ::type> |
1124 | explicit |
1125 | independent_bits_engine(_Sseq& __q) |
1126 | : _M_b(__q) |
1127 | { } |
1128 | |
1129 | /** |
1130 | * @brief Reseeds the %independent_bits_engine object with the default |
1131 | * seed for the underlying base class generator engine. |
1132 | */ |
1133 | void |
1134 | seed() |
1135 | { _M_b.seed(); } |
1136 | |
1137 | /** |
1138 | * @brief Reseeds the %independent_bits_engine object with the default |
1139 | * seed for the underlying base class generator engine. |
1140 | */ |
1141 | void |
1142 | seed(result_type __s) |
1143 | { _M_b.seed(__s); } |
1144 | |
1145 | /** |
1146 | * @brief Reseeds the %independent_bits_engine object with the given |
1147 | * seed sequence. |
1148 | * @param __q A seed generator function. |
1149 | */ |
1150 | template<typename _Sseq> |
1151 | void |
1152 | seed(_Sseq& __q) |
1153 | { _M_b.seed(__q); } |
1154 | |
1155 | /** |
1156 | * @brief Gets a const reference to the underlying generator engine |
1157 | * object. |
1158 | */ |
1159 | const _RandomNumberEngine& |
1160 | base() const noexcept |
1161 | { return _M_b; } |
1162 | |
1163 | /** |
1164 | * @brief Gets the minimum value in the generated random number range. |
1165 | */ |
1166 | static constexpr result_type |
1167 | min() |
1168 | { return 0U; } |
1169 | |
1170 | /** |
1171 | * @brief Gets the maximum value in the generated random number range. |
1172 | */ |
1173 | static constexpr result_type |
1174 | max() |
1175 | { return __detail::_Shift<_UIntType, __w>::__value - 1; } |
1176 | |
1177 | /** |
1178 | * @brief Discard a sequence of random numbers. |
1179 | */ |
1180 | void |
1181 | discard(unsigned long long __z) |
1182 | { |
1183 | for (; __z != 0ULL; --__z) |
1184 | (*this)(); |
1185 | } |
1186 | |
1187 | /** |
1188 | * @brief Gets the next value in the generated random number sequence. |
1189 | */ |
1190 | result_type |
1191 | operator()(); |
1192 | |
1193 | /** |
1194 | * @brief Compares two %independent_bits_engine random number generator |
1195 | * objects of the same type for equality. |
1196 | * |
1197 | * @param __lhs A %independent_bits_engine random number generator |
1198 | * object. |
1199 | * @param __rhs Another %independent_bits_engine random number generator |
1200 | * object. |
1201 | * |
1202 | * @returns true if the infinite sequences of generated values |
1203 | * would be equal, false otherwise. |
1204 | */ |
1205 | friend bool |
1206 | operator==(const independent_bits_engine& __lhs, |
1207 | const independent_bits_engine& __rhs) |
1208 | { return __lhs._M_b == __rhs._M_b; } |
1209 | |
1210 | /** |
1211 | * @brief Extracts the current state of a % subtract_with_carry_engine |
1212 | * random number generator engine @p __x from the input stream |
1213 | * @p __is. |
1214 | * |
1215 | * @param __is An input stream. |
1216 | * @param __x A %independent_bits_engine random number generator |
1217 | * engine. |
1218 | * |
1219 | * @returns The input stream with the state of @p __x extracted or in |
1220 | * an error state. |
1221 | */ |
1222 | template<typename _CharT, typename _Traits> |
1223 | friend std::basic_istream<_CharT, _Traits>& |
1224 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
1225 | std::independent_bits_engine<_RandomNumberEngine, |
1226 | __w, _UIntType>& __x) |
1227 | { |
1228 | __is >> __x._M_b; |
1229 | return __is; |
1230 | } |
1231 | |
1232 | private: |
1233 | _RandomNumberEngine _M_b; |
1234 | }; |
1235 | |
1236 | /** |
1237 | * @brief Compares two %independent_bits_engine random number generator |
1238 | * objects of the same type for inequality. |
1239 | * |
1240 | * @param __lhs A %independent_bits_engine random number generator |
1241 | * object. |
1242 | * @param __rhs Another %independent_bits_engine random number generator |
1243 | * object. |
1244 | * |
1245 | * @returns true if the infinite sequences of generated values |
1246 | * would be different, false otherwise. |
1247 | */ |
1248 | template<typename _RandomNumberEngine, size_t __w, typename _UIntType> |
1249 | inline bool |
1250 | operator!=(const std::independent_bits_engine<_RandomNumberEngine, __w, |
1251 | _UIntType>& __lhs, |
1252 | const std::independent_bits_engine<_RandomNumberEngine, __w, |
1253 | _UIntType>& __rhs) |
1254 | { return !(__lhs == __rhs); } |
1255 | |
1256 | /** |
1257 | * @brief Inserts the current state of a %independent_bits_engine random |
1258 | * number generator engine @p __x into the output stream @p __os. |
1259 | * |
1260 | * @param __os An output stream. |
1261 | * @param __x A %independent_bits_engine random number generator engine. |
1262 | * |
1263 | * @returns The output stream with the state of @p __x inserted or in |
1264 | * an error state. |
1265 | */ |
1266 | template<typename _RandomNumberEngine, size_t __w, typename _UIntType, |
1267 | typename _CharT, typename _Traits> |
1268 | std::basic_ostream<_CharT, _Traits>& |
1269 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
1270 | const std::independent_bits_engine<_RandomNumberEngine, |
1271 | __w, _UIntType>& __x) |
1272 | { |
1273 | __os << __x.base(); |
1274 | return __os; |
1275 | } |
1276 | |
1277 | |
1278 | /** |
1279 | * @brief Produces random numbers by combining random numbers from some |
1280 | * base engine to produce random numbers with a specifies number of bits |
1281 | * @p __k. |
1282 | */ |
1283 | template<typename _RandomNumberEngine, size_t __k> |
1284 | class shuffle_order_engine |
1285 | { |
1286 | static_assert(1u <= __k, "template argument substituting " |
1287 | "__k out of bound" ); |
1288 | |
1289 | public: |
1290 | /** The type of the generated random value. */ |
1291 | typedef typename _RandomNumberEngine::result_type result_type; |
1292 | |
1293 | static constexpr size_t table_size = __k; |
1294 | |
1295 | /** |
1296 | * @brief Constructs a default %shuffle_order_engine engine. |
1297 | * |
1298 | * The underlying engine is default constructed as well. |
1299 | */ |
1300 | shuffle_order_engine() |
1301 | : _M_b() |
1302 | { _M_initialize(); } |
1303 | |
1304 | /** |
1305 | * @brief Copy constructs a %shuffle_order_engine engine. |
1306 | * |
1307 | * Copies an existing base class random number generator. |
1308 | * @param __rng An existing (base class) engine object. |
1309 | */ |
1310 | explicit |
1311 | shuffle_order_engine(const _RandomNumberEngine& __rng) |
1312 | : _M_b(__rng) |
1313 | { _M_initialize(); } |
1314 | |
1315 | /** |
1316 | * @brief Move constructs a %shuffle_order_engine engine. |
1317 | * |
1318 | * Copies an existing base class random number generator. |
1319 | * @param __rng An existing (base class) engine object. |
1320 | */ |
1321 | explicit |
1322 | shuffle_order_engine(_RandomNumberEngine&& __rng) |
1323 | : _M_b(std::move(__rng)) |
1324 | { _M_initialize(); } |
1325 | |
1326 | /** |
1327 | * @brief Seed constructs a %shuffle_order_engine engine. |
1328 | * |
1329 | * Constructs the underlying generator engine seeded with @p __s. |
1330 | * @param __s A seed value for the base class engine. |
1331 | */ |
1332 | explicit |
1333 | shuffle_order_engine(result_type __s) |
1334 | : _M_b(__s) |
1335 | { _M_initialize(); } |
1336 | |
1337 | /** |
1338 | * @brief Generator construct a %shuffle_order_engine engine. |
1339 | * |
1340 | * @param __q A seed sequence. |
1341 | */ |
1342 | template<typename _Sseq, typename = typename |
1343 | std::enable_if<!std::is_same<_Sseq, shuffle_order_engine>::value |
1344 | && !std::is_same<_Sseq, _RandomNumberEngine>::value> |
1345 | ::type> |
1346 | explicit |
1347 | shuffle_order_engine(_Sseq& __q) |
1348 | : _M_b(__q) |
1349 | { _M_initialize(); } |
1350 | |
1351 | /** |
1352 | * @brief Reseeds the %shuffle_order_engine object with the default seed |
1353 | for the underlying base class generator engine. |
1354 | */ |
1355 | void |
1356 | seed() |
1357 | { |
1358 | _M_b.seed(); |
1359 | _M_initialize(); |
1360 | } |
1361 | |
1362 | /** |
1363 | * @brief Reseeds the %shuffle_order_engine object with the default seed |
1364 | * for the underlying base class generator engine. |
1365 | */ |
1366 | void |
1367 | seed(result_type __s) |
1368 | { |
1369 | _M_b.seed(__s); |
1370 | _M_initialize(); |
1371 | } |
1372 | |
1373 | /** |
1374 | * @brief Reseeds the %shuffle_order_engine object with the given seed |
1375 | * sequence. |
1376 | * @param __q A seed generator function. |
1377 | */ |
1378 | template<typename _Sseq> |
1379 | void |
1380 | seed(_Sseq& __q) |
1381 | { |
1382 | _M_b.seed(__q); |
1383 | _M_initialize(); |
1384 | } |
1385 | |
1386 | /** |
1387 | * Gets a const reference to the underlying generator engine object. |
1388 | */ |
1389 | const _RandomNumberEngine& |
1390 | base() const noexcept |
1391 | { return _M_b; } |
1392 | |
1393 | /** |
1394 | * Gets the minimum value in the generated random number range. |
1395 | */ |
1396 | static constexpr result_type |
1397 | min() |
1398 | { return _RandomNumberEngine::min(); } |
1399 | |
1400 | /** |
1401 | * Gets the maximum value in the generated random number range. |
1402 | */ |
1403 | static constexpr result_type |
1404 | max() |
1405 | { return _RandomNumberEngine::max(); } |
1406 | |
1407 | /** |
1408 | * Discard a sequence of random numbers. |
1409 | */ |
1410 | void |
1411 | discard(unsigned long long __z) |
1412 | { |
1413 | for (; __z != 0ULL; --__z) |
1414 | (*this)(); |
1415 | } |
1416 | |
1417 | /** |
1418 | * Gets the next value in the generated random number sequence. |
1419 | */ |
1420 | result_type |
1421 | operator()(); |
1422 | |
1423 | /** |
1424 | * Compares two %shuffle_order_engine random number generator objects |
1425 | * of the same type for equality. |
1426 | * |
1427 | * @param __lhs A %shuffle_order_engine random number generator object. |
1428 | * @param __rhs Another %shuffle_order_engine random number generator |
1429 | * object. |
1430 | * |
1431 | * @returns true if the infinite sequences of generated values |
1432 | * would be equal, false otherwise. |
1433 | */ |
1434 | friend bool |
1435 | operator==(const shuffle_order_engine& __lhs, |
1436 | const shuffle_order_engine& __rhs) |
1437 | { return (__lhs._M_b == __rhs._M_b |
1438 | && std::equal(__lhs._M_v, __lhs._M_v + __k, __rhs._M_v) |
1439 | && __lhs._M_y == __rhs._M_y); } |
1440 | |
1441 | /** |
1442 | * @brief Inserts the current state of a %shuffle_order_engine random |
1443 | * number generator engine @p __x into the output stream |
1444 | @p __os. |
1445 | * |
1446 | * @param __os An output stream. |
1447 | * @param __x A %shuffle_order_engine random number generator engine. |
1448 | * |
1449 | * @returns The output stream with the state of @p __x inserted or in |
1450 | * an error state. |
1451 | */ |
1452 | template<typename _RandomNumberEngine1, size_t __k1, |
1453 | typename _CharT, typename _Traits> |
1454 | friend std::basic_ostream<_CharT, _Traits>& |
1455 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
1456 | const std::shuffle_order_engine<_RandomNumberEngine1, |
1457 | __k1>& __x); |
1458 | |
1459 | /** |
1460 | * @brief Extracts the current state of a % subtract_with_carry_engine |
1461 | * random number generator engine @p __x from the input stream |
1462 | * @p __is. |
1463 | * |
1464 | * @param __is An input stream. |
1465 | * @param __x A %shuffle_order_engine random number generator engine. |
1466 | * |
1467 | * @returns The input stream with the state of @p __x extracted or in |
1468 | * an error state. |
1469 | */ |
1470 | template<typename _RandomNumberEngine1, size_t __k1, |
1471 | typename _CharT, typename _Traits> |
1472 | friend std::basic_istream<_CharT, _Traits>& |
1473 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
1474 | std::shuffle_order_engine<_RandomNumberEngine1, __k1>& __x); |
1475 | |
1476 | private: |
1477 | void _M_initialize() |
1478 | { |
1479 | for (size_t __i = 0; __i < __k; ++__i) |
1480 | _M_v[__i] = _M_b(); |
1481 | _M_y = _M_b(); |
1482 | } |
1483 | |
1484 | _RandomNumberEngine _M_b; |
1485 | result_type _M_v[__k]; |
1486 | result_type _M_y; |
1487 | }; |
1488 | |
1489 | /** |
1490 | * Compares two %shuffle_order_engine random number generator objects |
1491 | * of the same type for inequality. |
1492 | * |
1493 | * @param __lhs A %shuffle_order_engine random number generator object. |
1494 | * @param __rhs Another %shuffle_order_engine random number generator |
1495 | * object. |
1496 | * |
1497 | * @returns true if the infinite sequences of generated values |
1498 | * would be different, false otherwise. |
1499 | */ |
1500 | template<typename _RandomNumberEngine, size_t __k> |
1501 | inline bool |
1502 | operator!=(const std::shuffle_order_engine<_RandomNumberEngine, |
1503 | __k>& __lhs, |
1504 | const std::shuffle_order_engine<_RandomNumberEngine, |
1505 | __k>& __rhs) |
1506 | { return !(__lhs == __rhs); } |
1507 | |
1508 | |
1509 | /** |
1510 | * The classic Minimum Standard rand0 of Lewis, Goodman, and Miller. |
1511 | */ |
1512 | typedef linear_congruential_engine<uint_fast32_t, 16807UL, 0UL, 2147483647UL> |
1513 | minstd_rand0; |
1514 | |
1515 | /** |
1516 | * An alternative LCR (Lehmer Generator function). |
1517 | */ |
1518 | typedef linear_congruential_engine<uint_fast32_t, 48271UL, 0UL, 2147483647UL> |
1519 | minstd_rand; |
1520 | |
1521 | /** |
1522 | * The classic Mersenne Twister. |
1523 | * |
1524 | * Reference: |
1525 | * M. Matsumoto and T. Nishimura, Mersenne Twister: A 623-Dimensionally |
1526 | * Equidistributed Uniform Pseudo-Random Number Generator, ACM Transactions |
1527 | * on Modeling and Computer Simulation, Vol. 8, No. 1, January 1998, pp 3-30. |
1528 | */ |
1529 | typedef mersenne_twister_engine< |
1530 | uint_fast32_t, |
1531 | 32, 624, 397, 31, |
1532 | 0x9908b0dfUL, 11, |
1533 | 0xffffffffUL, 7, |
1534 | 0x9d2c5680UL, 15, |
1535 | 0xefc60000UL, 18, 1812433253UL> mt19937; |
1536 | |
1537 | /** |
1538 | * An alternative Mersenne Twister. |
1539 | */ |
1540 | typedef mersenne_twister_engine< |
1541 | uint_fast64_t, |
1542 | 64, 312, 156, 31, |
1543 | 0xb5026f5aa96619e9ULL, 29, |
1544 | 0x5555555555555555ULL, 17, |
1545 | 0x71d67fffeda60000ULL, 37, |
1546 | 0xfff7eee000000000ULL, 43, |
1547 | 6364136223846793005ULL> mt19937_64; |
1548 | |
1549 | typedef subtract_with_carry_engine<uint_fast32_t, 24, 10, 24> |
1550 | ranlux24_base; |
1551 | |
1552 | typedef subtract_with_carry_engine<uint_fast64_t, 48, 5, 12> |
1553 | ranlux48_base; |
1554 | |
1555 | typedef discard_block_engine<ranlux24_base, 223, 23> ranlux24; |
1556 | |
1557 | typedef discard_block_engine<ranlux48_base, 389, 11> ranlux48; |
1558 | |
1559 | typedef shuffle_order_engine<minstd_rand0, 256> knuth_b; |
1560 | |
1561 | typedef minstd_rand0 default_random_engine; |
1562 | |
1563 | /** |
1564 | * A standard interface to a platform-specific non-deterministic |
1565 | * random number generator (if any are available). |
1566 | */ |
1567 | class random_device |
1568 | { |
1569 | public: |
1570 | /** The type of the generated random value. */ |
1571 | typedef unsigned int result_type; |
1572 | |
1573 | // constructors, destructors and member functions |
1574 | |
1575 | #ifdef _GLIBCXX_USE_RANDOM_TR1 |
1576 | |
1577 | explicit |
1578 | random_device(const std::string& __token = "default" ) |
1579 | { |
1580 | _M_init(__token); |
1581 | } |
1582 | |
1583 | ~random_device() |
1584 | { _M_fini(); } |
1585 | |
1586 | #else |
1587 | |
1588 | explicit |
1589 | random_device(const std::string& __token = "mt19937" ) |
1590 | { _M_init_pretr1(__token); } |
1591 | |
1592 | public: |
1593 | |
1594 | #endif |
1595 | |
1596 | static constexpr result_type |
1597 | min() |
1598 | { return std::numeric_limits<result_type>::min(); } |
1599 | |
1600 | static constexpr result_type |
1601 | max() |
1602 | { return std::numeric_limits<result_type>::max(); } |
1603 | |
1604 | double |
1605 | entropy() const noexcept |
1606 | { return 0.0; } |
1607 | |
1608 | result_type |
1609 | operator()() |
1610 | { |
1611 | #ifdef _GLIBCXX_USE_RANDOM_TR1 |
1612 | return this->_M_getval(); |
1613 | #else |
1614 | return this->_M_getval_pretr1(); |
1615 | #endif |
1616 | } |
1617 | |
1618 | // No copy functions. |
1619 | random_device(const random_device&) = delete; |
1620 | void operator=(const random_device&) = delete; |
1621 | |
1622 | private: |
1623 | |
1624 | void _M_init(const std::string& __token); |
1625 | void _M_init_pretr1(const std::string& __token); |
1626 | void _M_fini(); |
1627 | |
1628 | result_type _M_getval(); |
1629 | result_type _M_getval_pretr1(); |
1630 | |
1631 | union |
1632 | { |
1633 | void* _M_file; |
1634 | mt19937 _M_mt; |
1635 | }; |
1636 | }; |
1637 | |
1638 | /* @} */ // group random_generators |
1639 | |
1640 | /** |
1641 | * @addtogroup random_distributions Random Number Distributions |
1642 | * @ingroup random |
1643 | * @{ |
1644 | */ |
1645 | |
1646 | /** |
1647 | * @addtogroup random_distributions_uniform Uniform Distributions |
1648 | * @ingroup random_distributions |
1649 | * @{ |
1650 | */ |
1651 | |
1652 | // std::uniform_int_distribution is defined in <bits/uniform_int_dist.h> |
1653 | |
1654 | /** |
1655 | * @brief Return true if two uniform integer distributions have |
1656 | * different parameters. |
1657 | */ |
1658 | template<typename _IntType> |
1659 | inline bool |
1660 | operator!=(const std::uniform_int_distribution<_IntType>& __d1, |
1661 | const std::uniform_int_distribution<_IntType>& __d2) |
1662 | { return !(__d1 == __d2); } |
1663 | |
1664 | /** |
1665 | * @brief Inserts a %uniform_int_distribution random number |
1666 | * distribution @p __x into the output stream @p os. |
1667 | * |
1668 | * @param __os An output stream. |
1669 | * @param __x A %uniform_int_distribution random number distribution. |
1670 | * |
1671 | * @returns The output stream with the state of @p __x inserted or in |
1672 | * an error state. |
1673 | */ |
1674 | template<typename _IntType, typename _CharT, typename _Traits> |
1675 | std::basic_ostream<_CharT, _Traits>& |
1676 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
1677 | const std::uniform_int_distribution<_IntType>&); |
1678 | |
1679 | /** |
1680 | * @brief Extracts a %uniform_int_distribution random number distribution |
1681 | * @p __x from the input stream @p __is. |
1682 | * |
1683 | * @param __is An input stream. |
1684 | * @param __x A %uniform_int_distribution random number generator engine. |
1685 | * |
1686 | * @returns The input stream with @p __x extracted or in an error state. |
1687 | */ |
1688 | template<typename _IntType, typename _CharT, typename _Traits> |
1689 | std::basic_istream<_CharT, _Traits>& |
1690 | operator>>(std::basic_istream<_CharT, _Traits>&, |
1691 | std::uniform_int_distribution<_IntType>&); |
1692 | |
1693 | |
1694 | /** |
1695 | * @brief Uniform continuous distribution for random numbers. |
1696 | * |
1697 | * A continuous random distribution on the range [min, max) with equal |
1698 | * probability throughout the range. The URNG should be real-valued and |
1699 | * deliver number in the range [0, 1). |
1700 | */ |
1701 | template<typename _RealType = double> |
1702 | class uniform_real_distribution |
1703 | { |
1704 | static_assert(std::is_floating_point<_RealType>::value, |
1705 | "result_type must be a floating point type" ); |
1706 | |
1707 | public: |
1708 | /** The type of the range of the distribution. */ |
1709 | typedef _RealType result_type; |
1710 | |
1711 | /** Parameter type. */ |
1712 | struct param_type |
1713 | { |
1714 | typedef uniform_real_distribution<_RealType> distribution_type; |
1715 | |
1716 | explicit |
1717 | param_type(_RealType __a = _RealType(0), |
1718 | _RealType __b = _RealType(1)) |
1719 | : _M_a(__a), _M_b(__b) |
1720 | { |
1721 | __glibcxx_assert(_M_a <= _M_b); |
1722 | } |
1723 | |
1724 | result_type |
1725 | a() const |
1726 | { return _M_a; } |
1727 | |
1728 | result_type |
1729 | b() const |
1730 | { return _M_b; } |
1731 | |
1732 | friend bool |
1733 | operator==(const param_type& __p1, const param_type& __p2) |
1734 | { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; } |
1735 | |
1736 | friend bool |
1737 | operator!=(const param_type& __p1, const param_type& __p2) |
1738 | { return !(__p1 == __p2); } |
1739 | |
1740 | private: |
1741 | _RealType _M_a; |
1742 | _RealType _M_b; |
1743 | }; |
1744 | |
1745 | public: |
1746 | /** |
1747 | * @brief Constructs a uniform_real_distribution object. |
1748 | * |
1749 | * @param __a [IN] The lower bound of the distribution. |
1750 | * @param __b [IN] The upper bound of the distribution. |
1751 | */ |
1752 | explicit |
1753 | uniform_real_distribution(_RealType __a = _RealType(0), |
1754 | _RealType __b = _RealType(1)) |
1755 | : _M_param(__a, __b) |
1756 | { } |
1757 | |
1758 | explicit |
1759 | uniform_real_distribution(const param_type& __p) |
1760 | : _M_param(__p) |
1761 | { } |
1762 | |
1763 | /** |
1764 | * @brief Resets the distribution state. |
1765 | * |
1766 | * Does nothing for the uniform real distribution. |
1767 | */ |
1768 | void |
1769 | reset() { } |
1770 | |
1771 | result_type |
1772 | a() const |
1773 | { return _M_param.a(); } |
1774 | |
1775 | result_type |
1776 | b() const |
1777 | { return _M_param.b(); } |
1778 | |
1779 | /** |
1780 | * @brief Returns the parameter set of the distribution. |
1781 | */ |
1782 | param_type |
1783 | param() const |
1784 | { return _M_param; } |
1785 | |
1786 | /** |
1787 | * @brief Sets the parameter set of the distribution. |
1788 | * @param __param The new parameter set of the distribution. |
1789 | */ |
1790 | void |
1791 | param(const param_type& __param) |
1792 | { _M_param = __param; } |
1793 | |
1794 | /** |
1795 | * @brief Returns the inclusive lower bound of the distribution range. |
1796 | */ |
1797 | result_type |
1798 | min() const |
1799 | { return this->a(); } |
1800 | |
1801 | /** |
1802 | * @brief Returns the inclusive upper bound of the distribution range. |
1803 | */ |
1804 | result_type |
1805 | max() const |
1806 | { return this->b(); } |
1807 | |
1808 | /** |
1809 | * @brief Generating functions. |
1810 | */ |
1811 | template<typename _UniformRandomNumberGenerator> |
1812 | result_type |
1813 | operator()(_UniformRandomNumberGenerator& __urng) |
1814 | { return this->operator()(__urng, _M_param); } |
1815 | |
1816 | template<typename _UniformRandomNumberGenerator> |
1817 | result_type |
1818 | operator()(_UniformRandomNumberGenerator& __urng, |
1819 | const param_type& __p) |
1820 | { |
1821 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> |
1822 | __aurng(__urng); |
1823 | return (__aurng() * (__p.b() - __p.a())) + __p.a(); |
1824 | } |
1825 | |
1826 | template<typename _ForwardIterator, |
1827 | typename _UniformRandomNumberGenerator> |
1828 | void |
1829 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
1830 | _UniformRandomNumberGenerator& __urng) |
1831 | { this->__generate(__f, __t, __urng, _M_param); } |
1832 | |
1833 | template<typename _ForwardIterator, |
1834 | typename _UniformRandomNumberGenerator> |
1835 | void |
1836 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
1837 | _UniformRandomNumberGenerator& __urng, |
1838 | const param_type& __p) |
1839 | { this->__generate_impl(__f, __t, __urng, __p); } |
1840 | |
1841 | template<typename _UniformRandomNumberGenerator> |
1842 | void |
1843 | __generate(result_type* __f, result_type* __t, |
1844 | _UniformRandomNumberGenerator& __urng, |
1845 | const param_type& __p) |
1846 | { this->__generate_impl(__f, __t, __urng, __p); } |
1847 | |
1848 | /** |
1849 | * @brief Return true if two uniform real distributions have |
1850 | * the same parameters. |
1851 | */ |
1852 | friend bool |
1853 | operator==(const uniform_real_distribution& __d1, |
1854 | const uniform_real_distribution& __d2) |
1855 | { return __d1._M_param == __d2._M_param; } |
1856 | |
1857 | private: |
1858 | template<typename _ForwardIterator, |
1859 | typename _UniformRandomNumberGenerator> |
1860 | void |
1861 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
1862 | _UniformRandomNumberGenerator& __urng, |
1863 | const param_type& __p); |
1864 | |
1865 | param_type _M_param; |
1866 | }; |
1867 | |
1868 | /** |
1869 | * @brief Return true if two uniform real distributions have |
1870 | * different parameters. |
1871 | */ |
1872 | template<typename _IntType> |
1873 | inline bool |
1874 | operator!=(const std::uniform_real_distribution<_IntType>& __d1, |
1875 | const std::uniform_real_distribution<_IntType>& __d2) |
1876 | { return !(__d1 == __d2); } |
1877 | |
1878 | /** |
1879 | * @brief Inserts a %uniform_real_distribution random number |
1880 | * distribution @p __x into the output stream @p __os. |
1881 | * |
1882 | * @param __os An output stream. |
1883 | * @param __x A %uniform_real_distribution random number distribution. |
1884 | * |
1885 | * @returns The output stream with the state of @p __x inserted or in |
1886 | * an error state. |
1887 | */ |
1888 | template<typename _RealType, typename _CharT, typename _Traits> |
1889 | std::basic_ostream<_CharT, _Traits>& |
1890 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
1891 | const std::uniform_real_distribution<_RealType>&); |
1892 | |
1893 | /** |
1894 | * @brief Extracts a %uniform_real_distribution random number distribution |
1895 | * @p __x from the input stream @p __is. |
1896 | * |
1897 | * @param __is An input stream. |
1898 | * @param __x A %uniform_real_distribution random number generator engine. |
1899 | * |
1900 | * @returns The input stream with @p __x extracted or in an error state. |
1901 | */ |
1902 | template<typename _RealType, typename _CharT, typename _Traits> |
1903 | std::basic_istream<_CharT, _Traits>& |
1904 | operator>>(std::basic_istream<_CharT, _Traits>&, |
1905 | std::uniform_real_distribution<_RealType>&); |
1906 | |
1907 | /* @} */ // group random_distributions_uniform |
1908 | |
1909 | /** |
1910 | * @addtogroup random_distributions_normal Normal Distributions |
1911 | * @ingroup random_distributions |
1912 | * @{ |
1913 | */ |
1914 | |
1915 | /** |
1916 | * @brief A normal continuous distribution for random numbers. |
1917 | * |
1918 | * The formula for the normal probability density function is |
1919 | * @f[ |
1920 | * p(x|\mu,\sigma) = \frac{1}{\sigma \sqrt{2 \pi}} |
1921 | * e^{- \frac{{x - \mu}^ {2}}{2 \sigma ^ {2}} } |
1922 | * @f] |
1923 | */ |
1924 | template<typename _RealType = double> |
1925 | class normal_distribution |
1926 | { |
1927 | static_assert(std::is_floating_point<_RealType>::value, |
1928 | "result_type must be a floating point type" ); |
1929 | |
1930 | public: |
1931 | /** The type of the range of the distribution. */ |
1932 | typedef _RealType result_type; |
1933 | |
1934 | /** Parameter type. */ |
1935 | struct param_type |
1936 | { |
1937 | typedef normal_distribution<_RealType> distribution_type; |
1938 | |
1939 | explicit |
1940 | param_type(_RealType __mean = _RealType(0), |
1941 | _RealType __stddev = _RealType(1)) |
1942 | : _M_mean(__mean), _M_stddev(__stddev) |
1943 | { |
1944 | __glibcxx_assert(_M_stddev > _RealType(0)); |
1945 | } |
1946 | |
1947 | _RealType |
1948 | mean() const |
1949 | { return _M_mean; } |
1950 | |
1951 | _RealType |
1952 | stddev() const |
1953 | { return _M_stddev; } |
1954 | |
1955 | friend bool |
1956 | operator==(const param_type& __p1, const param_type& __p2) |
1957 | { return (__p1._M_mean == __p2._M_mean |
1958 | && __p1._M_stddev == __p2._M_stddev); } |
1959 | |
1960 | friend bool |
1961 | operator!=(const param_type& __p1, const param_type& __p2) |
1962 | { return !(__p1 == __p2); } |
1963 | |
1964 | private: |
1965 | _RealType _M_mean; |
1966 | _RealType _M_stddev; |
1967 | }; |
1968 | |
1969 | public: |
1970 | /** |
1971 | * Constructs a normal distribution with parameters @f$mean@f$ and |
1972 | * standard deviation. |
1973 | */ |
1974 | explicit |
1975 | normal_distribution(result_type __mean = result_type(0), |
1976 | result_type __stddev = result_type(1)) |
1977 | : _M_param(__mean, __stddev), _M_saved_available(false) |
1978 | { } |
1979 | |
1980 | explicit |
1981 | normal_distribution(const param_type& __p) |
1982 | : _M_param(__p), _M_saved_available(false) |
1983 | { } |
1984 | |
1985 | /** |
1986 | * @brief Resets the distribution state. |
1987 | */ |
1988 | void |
1989 | reset() |
1990 | { _M_saved_available = false; } |
1991 | |
1992 | /** |
1993 | * @brief Returns the mean of the distribution. |
1994 | */ |
1995 | _RealType |
1996 | mean() const |
1997 | { return _M_param.mean(); } |
1998 | |
1999 | /** |
2000 | * @brief Returns the standard deviation of the distribution. |
2001 | */ |
2002 | _RealType |
2003 | stddev() const |
2004 | { return _M_param.stddev(); } |
2005 | |
2006 | /** |
2007 | * @brief Returns the parameter set of the distribution. |
2008 | */ |
2009 | param_type |
2010 | param() const |
2011 | { return _M_param; } |
2012 | |
2013 | /** |
2014 | * @brief Sets the parameter set of the distribution. |
2015 | * @param __param The new parameter set of the distribution. |
2016 | */ |
2017 | void |
2018 | param(const param_type& __param) |
2019 | { _M_param = __param; } |
2020 | |
2021 | /** |
2022 | * @brief Returns the greatest lower bound value of the distribution. |
2023 | */ |
2024 | result_type |
2025 | min() const |
2026 | { return std::numeric_limits<result_type>::lowest(); } |
2027 | |
2028 | /** |
2029 | * @brief Returns the least upper bound value of the distribution. |
2030 | */ |
2031 | result_type |
2032 | max() const |
2033 | { return std::numeric_limits<result_type>::max(); } |
2034 | |
2035 | /** |
2036 | * @brief Generating functions. |
2037 | */ |
2038 | template<typename _UniformRandomNumberGenerator> |
2039 | result_type |
2040 | operator()(_UniformRandomNumberGenerator& __urng) |
2041 | { return this->operator()(__urng, _M_param); } |
2042 | |
2043 | template<typename _UniformRandomNumberGenerator> |
2044 | result_type |
2045 | operator()(_UniformRandomNumberGenerator& __urng, |
2046 | const param_type& __p); |
2047 | |
2048 | template<typename _ForwardIterator, |
2049 | typename _UniformRandomNumberGenerator> |
2050 | void |
2051 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
2052 | _UniformRandomNumberGenerator& __urng) |
2053 | { this->__generate(__f, __t, __urng, _M_param); } |
2054 | |
2055 | template<typename _ForwardIterator, |
2056 | typename _UniformRandomNumberGenerator> |
2057 | void |
2058 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
2059 | _UniformRandomNumberGenerator& __urng, |
2060 | const param_type& __p) |
2061 | { this->__generate_impl(__f, __t, __urng, __p); } |
2062 | |
2063 | template<typename _UniformRandomNumberGenerator> |
2064 | void |
2065 | __generate(result_type* __f, result_type* __t, |
2066 | _UniformRandomNumberGenerator& __urng, |
2067 | const param_type& __p) |
2068 | { this->__generate_impl(__f, __t, __urng, __p); } |
2069 | |
2070 | /** |
2071 | * @brief Return true if two normal distributions have |
2072 | * the same parameters and the sequences that would |
2073 | * be generated are equal. |
2074 | */ |
2075 | template<typename _RealType1> |
2076 | friend bool |
2077 | operator==(const std::normal_distribution<_RealType1>& __d1, |
2078 | const std::normal_distribution<_RealType1>& __d2); |
2079 | |
2080 | /** |
2081 | * @brief Inserts a %normal_distribution random number distribution |
2082 | * @p __x into the output stream @p __os. |
2083 | * |
2084 | * @param __os An output stream. |
2085 | * @param __x A %normal_distribution random number distribution. |
2086 | * |
2087 | * @returns The output stream with the state of @p __x inserted or in |
2088 | * an error state. |
2089 | */ |
2090 | template<typename _RealType1, typename _CharT, typename _Traits> |
2091 | friend std::basic_ostream<_CharT, _Traits>& |
2092 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
2093 | const std::normal_distribution<_RealType1>& __x); |
2094 | |
2095 | /** |
2096 | * @brief Extracts a %normal_distribution random number distribution |
2097 | * @p __x from the input stream @p __is. |
2098 | * |
2099 | * @param __is An input stream. |
2100 | * @param __x A %normal_distribution random number generator engine. |
2101 | * |
2102 | * @returns The input stream with @p __x extracted or in an error |
2103 | * state. |
2104 | */ |
2105 | template<typename _RealType1, typename _CharT, typename _Traits> |
2106 | friend std::basic_istream<_CharT, _Traits>& |
2107 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
2108 | std::normal_distribution<_RealType1>& __x); |
2109 | |
2110 | private: |
2111 | template<typename _ForwardIterator, |
2112 | typename _UniformRandomNumberGenerator> |
2113 | void |
2114 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
2115 | _UniformRandomNumberGenerator& __urng, |
2116 | const param_type& __p); |
2117 | |
2118 | param_type _M_param; |
2119 | result_type _M_saved; |
2120 | bool _M_saved_available; |
2121 | }; |
2122 | |
2123 | /** |
2124 | * @brief Return true if two normal distributions are different. |
2125 | */ |
2126 | template<typename _RealType> |
2127 | inline bool |
2128 | operator!=(const std::normal_distribution<_RealType>& __d1, |
2129 | const std::normal_distribution<_RealType>& __d2) |
2130 | { return !(__d1 == __d2); } |
2131 | |
2132 | |
2133 | /** |
2134 | * @brief A lognormal_distribution random number distribution. |
2135 | * |
2136 | * The formula for the normal probability mass function is |
2137 | * @f[ |
2138 | * p(x|m,s) = \frac{1}{sx\sqrt{2\pi}} |
2139 | * \exp{-\frac{(\ln{x} - m)^2}{2s^2}} |
2140 | * @f] |
2141 | */ |
2142 | template<typename _RealType = double> |
2143 | class lognormal_distribution |
2144 | { |
2145 | static_assert(std::is_floating_point<_RealType>::value, |
2146 | "result_type must be a floating point type" ); |
2147 | |
2148 | public: |
2149 | /** The type of the range of the distribution. */ |
2150 | typedef _RealType result_type; |
2151 | |
2152 | /** Parameter type. */ |
2153 | struct param_type |
2154 | { |
2155 | typedef lognormal_distribution<_RealType> distribution_type; |
2156 | |
2157 | explicit |
2158 | param_type(_RealType __m = _RealType(0), |
2159 | _RealType __s = _RealType(1)) |
2160 | : _M_m(__m), _M_s(__s) |
2161 | { } |
2162 | |
2163 | _RealType |
2164 | m() const |
2165 | { return _M_m; } |
2166 | |
2167 | _RealType |
2168 | s() const |
2169 | { return _M_s; } |
2170 | |
2171 | friend bool |
2172 | operator==(const param_type& __p1, const param_type& __p2) |
2173 | { return __p1._M_m == __p2._M_m && __p1._M_s == __p2._M_s; } |
2174 | |
2175 | friend bool |
2176 | operator!=(const param_type& __p1, const param_type& __p2) |
2177 | { return !(__p1 == __p2); } |
2178 | |
2179 | private: |
2180 | _RealType _M_m; |
2181 | _RealType _M_s; |
2182 | }; |
2183 | |
2184 | explicit |
2185 | lognormal_distribution(_RealType __m = _RealType(0), |
2186 | _RealType __s = _RealType(1)) |
2187 | : _M_param(__m, __s), _M_nd() |
2188 | { } |
2189 | |
2190 | explicit |
2191 | lognormal_distribution(const param_type& __p) |
2192 | : _M_param(__p), _M_nd() |
2193 | { } |
2194 | |
2195 | /** |
2196 | * Resets the distribution state. |
2197 | */ |
2198 | void |
2199 | reset() |
2200 | { _M_nd.reset(); } |
2201 | |
2202 | /** |
2203 | * |
2204 | */ |
2205 | _RealType |
2206 | m() const |
2207 | { return _M_param.m(); } |
2208 | |
2209 | _RealType |
2210 | s() const |
2211 | { return _M_param.s(); } |
2212 | |
2213 | /** |
2214 | * @brief Returns the parameter set of the distribution. |
2215 | */ |
2216 | param_type |
2217 | param() const |
2218 | { return _M_param; } |
2219 | |
2220 | /** |
2221 | * @brief Sets the parameter set of the distribution. |
2222 | * @param __param The new parameter set of the distribution. |
2223 | */ |
2224 | void |
2225 | param(const param_type& __param) |
2226 | { _M_param = __param; } |
2227 | |
2228 | /** |
2229 | * @brief Returns the greatest lower bound value of the distribution. |
2230 | */ |
2231 | result_type |
2232 | min() const |
2233 | { return result_type(0); } |
2234 | |
2235 | /** |
2236 | * @brief Returns the least upper bound value of the distribution. |
2237 | */ |
2238 | result_type |
2239 | max() const |
2240 | { return std::numeric_limits<result_type>::max(); } |
2241 | |
2242 | /** |
2243 | * @brief Generating functions. |
2244 | */ |
2245 | template<typename _UniformRandomNumberGenerator> |
2246 | result_type |
2247 | operator()(_UniformRandomNumberGenerator& __urng) |
2248 | { return this->operator()(__urng, _M_param); } |
2249 | |
2250 | template<typename _UniformRandomNumberGenerator> |
2251 | result_type |
2252 | operator()(_UniformRandomNumberGenerator& __urng, |
2253 | const param_type& __p) |
2254 | { return std::exp(__p.s() * _M_nd(__urng) + __p.m()); } |
2255 | |
2256 | template<typename _ForwardIterator, |
2257 | typename _UniformRandomNumberGenerator> |
2258 | void |
2259 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
2260 | _UniformRandomNumberGenerator& __urng) |
2261 | { this->__generate(__f, __t, __urng, _M_param); } |
2262 | |
2263 | template<typename _ForwardIterator, |
2264 | typename _UniformRandomNumberGenerator> |
2265 | void |
2266 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
2267 | _UniformRandomNumberGenerator& __urng, |
2268 | const param_type& __p) |
2269 | { this->__generate_impl(__f, __t, __urng, __p); } |
2270 | |
2271 | template<typename _UniformRandomNumberGenerator> |
2272 | void |
2273 | __generate(result_type* __f, result_type* __t, |
2274 | _UniformRandomNumberGenerator& __urng, |
2275 | const param_type& __p) |
2276 | { this->__generate_impl(__f, __t, __urng, __p); } |
2277 | |
2278 | /** |
2279 | * @brief Return true if two lognormal distributions have |
2280 | * the same parameters and the sequences that would |
2281 | * be generated are equal. |
2282 | */ |
2283 | friend bool |
2284 | operator==(const lognormal_distribution& __d1, |
2285 | const lognormal_distribution& __d2) |
2286 | { return (__d1._M_param == __d2._M_param |
2287 | && __d1._M_nd == __d2._M_nd); } |
2288 | |
2289 | /** |
2290 | * @brief Inserts a %lognormal_distribution random number distribution |
2291 | * @p __x into the output stream @p __os. |
2292 | * |
2293 | * @param __os An output stream. |
2294 | * @param __x A %lognormal_distribution random number distribution. |
2295 | * |
2296 | * @returns The output stream with the state of @p __x inserted or in |
2297 | * an error state. |
2298 | */ |
2299 | template<typename _RealType1, typename _CharT, typename _Traits> |
2300 | friend std::basic_ostream<_CharT, _Traits>& |
2301 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
2302 | const std::lognormal_distribution<_RealType1>& __x); |
2303 | |
2304 | /** |
2305 | * @brief Extracts a %lognormal_distribution random number distribution |
2306 | * @p __x from the input stream @p __is. |
2307 | * |
2308 | * @param __is An input stream. |
2309 | * @param __x A %lognormal_distribution random number |
2310 | * generator engine. |
2311 | * |
2312 | * @returns The input stream with @p __x extracted or in an error state. |
2313 | */ |
2314 | template<typename _RealType1, typename _CharT, typename _Traits> |
2315 | friend std::basic_istream<_CharT, _Traits>& |
2316 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
2317 | std::lognormal_distribution<_RealType1>& __x); |
2318 | |
2319 | private: |
2320 | template<typename _ForwardIterator, |
2321 | typename _UniformRandomNumberGenerator> |
2322 | void |
2323 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
2324 | _UniformRandomNumberGenerator& __urng, |
2325 | const param_type& __p); |
2326 | |
2327 | param_type _M_param; |
2328 | |
2329 | std::normal_distribution<result_type> _M_nd; |
2330 | }; |
2331 | |
2332 | /** |
2333 | * @brief Return true if two lognormal distributions are different. |
2334 | */ |
2335 | template<typename _RealType> |
2336 | inline bool |
2337 | operator!=(const std::lognormal_distribution<_RealType>& __d1, |
2338 | const std::lognormal_distribution<_RealType>& __d2) |
2339 | { return !(__d1 == __d2); } |
2340 | |
2341 | |
2342 | /** |
2343 | * @brief A gamma continuous distribution for random numbers. |
2344 | * |
2345 | * The formula for the gamma probability density function is: |
2346 | * @f[ |
2347 | * p(x|\alpha,\beta) = \frac{1}{\beta\Gamma(\alpha)} |
2348 | * (x/\beta)^{\alpha - 1} e^{-x/\beta} |
2349 | * @f] |
2350 | */ |
2351 | template<typename _RealType = double> |
2352 | class gamma_distribution |
2353 | { |
2354 | static_assert(std::is_floating_point<_RealType>::value, |
2355 | "result_type must be a floating point type" ); |
2356 | |
2357 | public: |
2358 | /** The type of the range of the distribution. */ |
2359 | typedef _RealType result_type; |
2360 | |
2361 | /** Parameter type. */ |
2362 | struct param_type |
2363 | { |
2364 | typedef gamma_distribution<_RealType> distribution_type; |
2365 | friend class gamma_distribution<_RealType>; |
2366 | |
2367 | explicit |
2368 | param_type(_RealType __alpha_val = _RealType(1), |
2369 | _RealType __beta_val = _RealType(1)) |
2370 | : _M_alpha(__alpha_val), _M_beta(__beta_val) |
2371 | { |
2372 | __glibcxx_assert(_M_alpha > _RealType(0)); |
2373 | _M_initialize(); |
2374 | } |
2375 | |
2376 | _RealType |
2377 | alpha() const |
2378 | { return _M_alpha; } |
2379 | |
2380 | _RealType |
2381 | beta() const |
2382 | { return _M_beta; } |
2383 | |
2384 | friend bool |
2385 | operator==(const param_type& __p1, const param_type& __p2) |
2386 | { return (__p1._M_alpha == __p2._M_alpha |
2387 | && __p1._M_beta == __p2._M_beta); } |
2388 | |
2389 | friend bool |
2390 | operator!=(const param_type& __p1, const param_type& __p2) |
2391 | { return !(__p1 == __p2); } |
2392 | |
2393 | private: |
2394 | void |
2395 | _M_initialize(); |
2396 | |
2397 | _RealType _M_alpha; |
2398 | _RealType _M_beta; |
2399 | |
2400 | _RealType _M_malpha, _M_a2; |
2401 | }; |
2402 | |
2403 | public: |
2404 | /** |
2405 | * @brief Constructs a gamma distribution with parameters |
2406 | * @f$\alpha@f$ and @f$\beta@f$. |
2407 | */ |
2408 | explicit |
2409 | gamma_distribution(_RealType __alpha_val = _RealType(1), |
2410 | _RealType __beta_val = _RealType(1)) |
2411 | : _M_param(__alpha_val, __beta_val), _M_nd() |
2412 | { } |
2413 | |
2414 | explicit |
2415 | gamma_distribution(const param_type& __p) |
2416 | : _M_param(__p), _M_nd() |
2417 | { } |
2418 | |
2419 | /** |
2420 | * @brief Resets the distribution state. |
2421 | */ |
2422 | void |
2423 | reset() |
2424 | { _M_nd.reset(); } |
2425 | |
2426 | /** |
2427 | * @brief Returns the @f$\alpha@f$ of the distribution. |
2428 | */ |
2429 | _RealType |
2430 | alpha() const |
2431 | { return _M_param.alpha(); } |
2432 | |
2433 | /** |
2434 | * @brief Returns the @f$\beta@f$ of the distribution. |
2435 | */ |
2436 | _RealType |
2437 | beta() const |
2438 | { return _M_param.beta(); } |
2439 | |
2440 | /** |
2441 | * @brief Returns the parameter set of the distribution. |
2442 | */ |
2443 | param_type |
2444 | param() const |
2445 | { return _M_param; } |
2446 | |
2447 | /** |
2448 | * @brief Sets the parameter set of the distribution. |
2449 | * @param __param The new parameter set of the distribution. |
2450 | */ |
2451 | void |
2452 | param(const param_type& __param) |
2453 | { _M_param = __param; } |
2454 | |
2455 | /** |
2456 | * @brief Returns the greatest lower bound value of the distribution. |
2457 | */ |
2458 | result_type |
2459 | min() const |
2460 | { return result_type(0); } |
2461 | |
2462 | /** |
2463 | * @brief Returns the least upper bound value of the distribution. |
2464 | */ |
2465 | result_type |
2466 | max() const |
2467 | { return std::numeric_limits<result_type>::max(); } |
2468 | |
2469 | /** |
2470 | * @brief Generating functions. |
2471 | */ |
2472 | template<typename _UniformRandomNumberGenerator> |
2473 | result_type |
2474 | operator()(_UniformRandomNumberGenerator& __urng) |
2475 | { return this->operator()(__urng, _M_param); } |
2476 | |
2477 | template<typename _UniformRandomNumberGenerator> |
2478 | result_type |
2479 | operator()(_UniformRandomNumberGenerator& __urng, |
2480 | const param_type& __p); |
2481 | |
2482 | template<typename _ForwardIterator, |
2483 | typename _UniformRandomNumberGenerator> |
2484 | void |
2485 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
2486 | _UniformRandomNumberGenerator& __urng) |
2487 | { this->__generate(__f, __t, __urng, _M_param); } |
2488 | |
2489 | template<typename _ForwardIterator, |
2490 | typename _UniformRandomNumberGenerator> |
2491 | void |
2492 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
2493 | _UniformRandomNumberGenerator& __urng, |
2494 | const param_type& __p) |
2495 | { this->__generate_impl(__f, __t, __urng, __p); } |
2496 | |
2497 | template<typename _UniformRandomNumberGenerator> |
2498 | void |
2499 | __generate(result_type* __f, result_type* __t, |
2500 | _UniformRandomNumberGenerator& __urng, |
2501 | const param_type& __p) |
2502 | { this->__generate_impl(__f, __t, __urng, __p); } |
2503 | |
2504 | /** |
2505 | * @brief Return true if two gamma distributions have the same |
2506 | * parameters and the sequences that would be generated |
2507 | * are equal. |
2508 | */ |
2509 | friend bool |
2510 | operator==(const gamma_distribution& __d1, |
2511 | const gamma_distribution& __d2) |
2512 | { return (__d1._M_param == __d2._M_param |
2513 | && __d1._M_nd == __d2._M_nd); } |
2514 | |
2515 | /** |
2516 | * @brief Inserts a %gamma_distribution random number distribution |
2517 | * @p __x into the output stream @p __os. |
2518 | * |
2519 | * @param __os An output stream. |
2520 | * @param __x A %gamma_distribution random number distribution. |
2521 | * |
2522 | * @returns The output stream with the state of @p __x inserted or in |
2523 | * an error state. |
2524 | */ |
2525 | template<typename _RealType1, typename _CharT, typename _Traits> |
2526 | friend std::basic_ostream<_CharT, _Traits>& |
2527 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
2528 | const std::gamma_distribution<_RealType1>& __x); |
2529 | |
2530 | /** |
2531 | * @brief Extracts a %gamma_distribution random number distribution |
2532 | * @p __x from the input stream @p __is. |
2533 | * |
2534 | * @param __is An input stream. |
2535 | * @param __x A %gamma_distribution random number generator engine. |
2536 | * |
2537 | * @returns The input stream with @p __x extracted or in an error state. |
2538 | */ |
2539 | template<typename _RealType1, typename _CharT, typename _Traits> |
2540 | friend std::basic_istream<_CharT, _Traits>& |
2541 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
2542 | std::gamma_distribution<_RealType1>& __x); |
2543 | |
2544 | private: |
2545 | template<typename _ForwardIterator, |
2546 | typename _UniformRandomNumberGenerator> |
2547 | void |
2548 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
2549 | _UniformRandomNumberGenerator& __urng, |
2550 | const param_type& __p); |
2551 | |
2552 | param_type _M_param; |
2553 | |
2554 | std::normal_distribution<result_type> _M_nd; |
2555 | }; |
2556 | |
2557 | /** |
2558 | * @brief Return true if two gamma distributions are different. |
2559 | */ |
2560 | template<typename _RealType> |
2561 | inline bool |
2562 | operator!=(const std::gamma_distribution<_RealType>& __d1, |
2563 | const std::gamma_distribution<_RealType>& __d2) |
2564 | { return !(__d1 == __d2); } |
2565 | |
2566 | |
2567 | /** |
2568 | * @brief A chi_squared_distribution random number distribution. |
2569 | * |
2570 | * The formula for the normal probability mass function is |
2571 | * @f$p(x|n) = \frac{x^{(n/2) - 1}e^{-x/2}}{\Gamma(n/2) 2^{n/2}}@f$ |
2572 | */ |
2573 | template<typename _RealType = double> |
2574 | class chi_squared_distribution |
2575 | { |
2576 | static_assert(std::is_floating_point<_RealType>::value, |
2577 | "result_type must be a floating point type" ); |
2578 | |
2579 | public: |
2580 | /** The type of the range of the distribution. */ |
2581 | typedef _RealType result_type; |
2582 | |
2583 | /** Parameter type. */ |
2584 | struct param_type |
2585 | { |
2586 | typedef chi_squared_distribution<_RealType> distribution_type; |
2587 | |
2588 | explicit |
2589 | param_type(_RealType __n = _RealType(1)) |
2590 | : _M_n(__n) |
2591 | { } |
2592 | |
2593 | _RealType |
2594 | n() const |
2595 | { return _M_n; } |
2596 | |
2597 | friend bool |
2598 | operator==(const param_type& __p1, const param_type& __p2) |
2599 | { return __p1._M_n == __p2._M_n; } |
2600 | |
2601 | friend bool |
2602 | operator!=(const param_type& __p1, const param_type& __p2) |
2603 | { return !(__p1 == __p2); } |
2604 | |
2605 | private: |
2606 | _RealType _M_n; |
2607 | }; |
2608 | |
2609 | explicit |
2610 | chi_squared_distribution(_RealType __n = _RealType(1)) |
2611 | : _M_param(__n), _M_gd(__n / 2) |
2612 | { } |
2613 | |
2614 | explicit |
2615 | chi_squared_distribution(const param_type& __p) |
2616 | : _M_param(__p), _M_gd(__p.n() / 2) |
2617 | { } |
2618 | |
2619 | /** |
2620 | * @brief Resets the distribution state. |
2621 | */ |
2622 | void |
2623 | reset() |
2624 | { _M_gd.reset(); } |
2625 | |
2626 | /** |
2627 | * |
2628 | */ |
2629 | _RealType |
2630 | n() const |
2631 | { return _M_param.n(); } |
2632 | |
2633 | /** |
2634 | * @brief Returns the parameter set of the distribution. |
2635 | */ |
2636 | param_type |
2637 | param() const |
2638 | { return _M_param; } |
2639 | |
2640 | /** |
2641 | * @brief Sets the parameter set of the distribution. |
2642 | * @param __param The new parameter set of the distribution. |
2643 | */ |
2644 | void |
2645 | param(const param_type& __param) |
2646 | { _M_param = __param; } |
2647 | |
2648 | /** |
2649 | * @brief Returns the greatest lower bound value of the distribution. |
2650 | */ |
2651 | result_type |
2652 | min() const |
2653 | { return result_type(0); } |
2654 | |
2655 | /** |
2656 | * @brief Returns the least upper bound value of the distribution. |
2657 | */ |
2658 | result_type |
2659 | max() const |
2660 | { return std::numeric_limits<result_type>::max(); } |
2661 | |
2662 | /** |
2663 | * @brief Generating functions. |
2664 | */ |
2665 | template<typename _UniformRandomNumberGenerator> |
2666 | result_type |
2667 | operator()(_UniformRandomNumberGenerator& __urng) |
2668 | { return 2 * _M_gd(__urng); } |
2669 | |
2670 | template<typename _UniformRandomNumberGenerator> |
2671 | result_type |
2672 | operator()(_UniformRandomNumberGenerator& __urng, |
2673 | const param_type& __p) |
2674 | { |
2675 | typedef typename std::gamma_distribution<result_type>::param_type |
2676 | param_type; |
2677 | return 2 * _M_gd(__urng, param_type(__p.n() / 2)); |
2678 | } |
2679 | |
2680 | template<typename _ForwardIterator, |
2681 | typename _UniformRandomNumberGenerator> |
2682 | void |
2683 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
2684 | _UniformRandomNumberGenerator& __urng) |
2685 | { this->__generate_impl(__f, __t, __urng); } |
2686 | |
2687 | template<typename _ForwardIterator, |
2688 | typename _UniformRandomNumberGenerator> |
2689 | void |
2690 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
2691 | _UniformRandomNumberGenerator& __urng, |
2692 | const param_type& __p) |
2693 | { typename std::gamma_distribution<result_type>::param_type |
2694 | __p2(__p.n() / 2); |
2695 | this->__generate_impl(__f, __t, __urng, __p2); } |
2696 | |
2697 | template<typename _UniformRandomNumberGenerator> |
2698 | void |
2699 | __generate(result_type* __f, result_type* __t, |
2700 | _UniformRandomNumberGenerator& __urng) |
2701 | { this->__generate_impl(__f, __t, __urng); } |
2702 | |
2703 | template<typename _UniformRandomNumberGenerator> |
2704 | void |
2705 | __generate(result_type* __f, result_type* __t, |
2706 | _UniformRandomNumberGenerator& __urng, |
2707 | const param_type& __p) |
2708 | { typename std::gamma_distribution<result_type>::param_type |
2709 | __p2(__p.n() / 2); |
2710 | this->__generate_impl(__f, __t, __urng, __p2); } |
2711 | |
2712 | /** |
2713 | * @brief Return true if two Chi-squared distributions have |
2714 | * the same parameters and the sequences that would be |
2715 | * generated are equal. |
2716 | */ |
2717 | friend bool |
2718 | operator==(const chi_squared_distribution& __d1, |
2719 | const chi_squared_distribution& __d2) |
2720 | { return __d1._M_param == __d2._M_param && __d1._M_gd == __d2._M_gd; } |
2721 | |
2722 | /** |
2723 | * @brief Inserts a %chi_squared_distribution random number distribution |
2724 | * @p __x into the output stream @p __os. |
2725 | * |
2726 | * @param __os An output stream. |
2727 | * @param __x A %chi_squared_distribution random number distribution. |
2728 | * |
2729 | * @returns The output stream with the state of @p __x inserted or in |
2730 | * an error state. |
2731 | */ |
2732 | template<typename _RealType1, typename _CharT, typename _Traits> |
2733 | friend std::basic_ostream<_CharT, _Traits>& |
2734 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
2735 | const std::chi_squared_distribution<_RealType1>& __x); |
2736 | |
2737 | /** |
2738 | * @brief Extracts a %chi_squared_distribution random number distribution |
2739 | * @p __x from the input stream @p __is. |
2740 | * |
2741 | * @param __is An input stream. |
2742 | * @param __x A %chi_squared_distribution random number |
2743 | * generator engine. |
2744 | * |
2745 | * @returns The input stream with @p __x extracted or in an error state. |
2746 | */ |
2747 | template<typename _RealType1, typename _CharT, typename _Traits> |
2748 | friend std::basic_istream<_CharT, _Traits>& |
2749 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
2750 | std::chi_squared_distribution<_RealType1>& __x); |
2751 | |
2752 | private: |
2753 | template<typename _ForwardIterator, |
2754 | typename _UniformRandomNumberGenerator> |
2755 | void |
2756 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
2757 | _UniformRandomNumberGenerator& __urng); |
2758 | |
2759 | template<typename _ForwardIterator, |
2760 | typename _UniformRandomNumberGenerator> |
2761 | void |
2762 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
2763 | _UniformRandomNumberGenerator& __urng, |
2764 | const typename |
2765 | std::gamma_distribution<result_type>::param_type& __p); |
2766 | |
2767 | param_type _M_param; |
2768 | |
2769 | std::gamma_distribution<result_type> _M_gd; |
2770 | }; |
2771 | |
2772 | /** |
2773 | * @brief Return true if two Chi-squared distributions are different. |
2774 | */ |
2775 | template<typename _RealType> |
2776 | inline bool |
2777 | operator!=(const std::chi_squared_distribution<_RealType>& __d1, |
2778 | const std::chi_squared_distribution<_RealType>& __d2) |
2779 | { return !(__d1 == __d2); } |
2780 | |
2781 | |
2782 | /** |
2783 | * @brief A cauchy_distribution random number distribution. |
2784 | * |
2785 | * The formula for the normal probability mass function is |
2786 | * @f$p(x|a,b) = (\pi b (1 + (\frac{x-a}{b})^2))^{-1}@f$ |
2787 | */ |
2788 | template<typename _RealType = double> |
2789 | class cauchy_distribution |
2790 | { |
2791 | static_assert(std::is_floating_point<_RealType>::value, |
2792 | "result_type must be a floating point type" ); |
2793 | |
2794 | public: |
2795 | /** The type of the range of the distribution. */ |
2796 | typedef _RealType result_type; |
2797 | |
2798 | /** Parameter type. */ |
2799 | struct param_type |
2800 | { |
2801 | typedef cauchy_distribution<_RealType> distribution_type; |
2802 | |
2803 | explicit |
2804 | param_type(_RealType __a = _RealType(0), |
2805 | _RealType __b = _RealType(1)) |
2806 | : _M_a(__a), _M_b(__b) |
2807 | { } |
2808 | |
2809 | _RealType |
2810 | a() const |
2811 | { return _M_a; } |
2812 | |
2813 | _RealType |
2814 | b() const |
2815 | { return _M_b; } |
2816 | |
2817 | friend bool |
2818 | operator==(const param_type& __p1, const param_type& __p2) |
2819 | { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; } |
2820 | |
2821 | friend bool |
2822 | operator!=(const param_type& __p1, const param_type& __p2) |
2823 | { return !(__p1 == __p2); } |
2824 | |
2825 | private: |
2826 | _RealType _M_a; |
2827 | _RealType _M_b; |
2828 | }; |
2829 | |
2830 | explicit |
2831 | cauchy_distribution(_RealType __a = _RealType(0), |
2832 | _RealType __b = _RealType(1)) |
2833 | : _M_param(__a, __b) |
2834 | { } |
2835 | |
2836 | explicit |
2837 | cauchy_distribution(const param_type& __p) |
2838 | : _M_param(__p) |
2839 | { } |
2840 | |
2841 | /** |
2842 | * @brief Resets the distribution state. |
2843 | */ |
2844 | void |
2845 | reset() |
2846 | { } |
2847 | |
2848 | /** |
2849 | * |
2850 | */ |
2851 | _RealType |
2852 | a() const |
2853 | { return _M_param.a(); } |
2854 | |
2855 | _RealType |
2856 | b() const |
2857 | { return _M_param.b(); } |
2858 | |
2859 | /** |
2860 | * @brief Returns the parameter set of the distribution. |
2861 | */ |
2862 | param_type |
2863 | param() const |
2864 | { return _M_param; } |
2865 | |
2866 | /** |
2867 | * @brief Sets the parameter set of the distribution. |
2868 | * @param __param The new parameter set of the distribution. |
2869 | */ |
2870 | void |
2871 | param(const param_type& __param) |
2872 | { _M_param = __param; } |
2873 | |
2874 | /** |
2875 | * @brief Returns the greatest lower bound value of the distribution. |
2876 | */ |
2877 | result_type |
2878 | min() const |
2879 | { return std::numeric_limits<result_type>::lowest(); } |
2880 | |
2881 | /** |
2882 | * @brief Returns the least upper bound value of the distribution. |
2883 | */ |
2884 | result_type |
2885 | max() const |
2886 | { return std::numeric_limits<result_type>::max(); } |
2887 | |
2888 | /** |
2889 | * @brief Generating functions. |
2890 | */ |
2891 | template<typename _UniformRandomNumberGenerator> |
2892 | result_type |
2893 | operator()(_UniformRandomNumberGenerator& __urng) |
2894 | { return this->operator()(__urng, _M_param); } |
2895 | |
2896 | template<typename _UniformRandomNumberGenerator> |
2897 | result_type |
2898 | operator()(_UniformRandomNumberGenerator& __urng, |
2899 | const param_type& __p); |
2900 | |
2901 | template<typename _ForwardIterator, |
2902 | typename _UniformRandomNumberGenerator> |
2903 | void |
2904 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
2905 | _UniformRandomNumberGenerator& __urng) |
2906 | { this->__generate(__f, __t, __urng, _M_param); } |
2907 | |
2908 | template<typename _ForwardIterator, |
2909 | typename _UniformRandomNumberGenerator> |
2910 | void |
2911 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
2912 | _UniformRandomNumberGenerator& __urng, |
2913 | const param_type& __p) |
2914 | { this->__generate_impl(__f, __t, __urng, __p); } |
2915 | |
2916 | template<typename _UniformRandomNumberGenerator> |
2917 | void |
2918 | __generate(result_type* __f, result_type* __t, |
2919 | _UniformRandomNumberGenerator& __urng, |
2920 | const param_type& __p) |
2921 | { this->__generate_impl(__f, __t, __urng, __p); } |
2922 | |
2923 | /** |
2924 | * @brief Return true if two Cauchy distributions have |
2925 | * the same parameters. |
2926 | */ |
2927 | friend bool |
2928 | operator==(const cauchy_distribution& __d1, |
2929 | const cauchy_distribution& __d2) |
2930 | { return __d1._M_param == __d2._M_param; } |
2931 | |
2932 | private: |
2933 | template<typename _ForwardIterator, |
2934 | typename _UniformRandomNumberGenerator> |
2935 | void |
2936 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
2937 | _UniformRandomNumberGenerator& __urng, |
2938 | const param_type& __p); |
2939 | |
2940 | param_type _M_param; |
2941 | }; |
2942 | |
2943 | /** |
2944 | * @brief Return true if two Cauchy distributions have |
2945 | * different parameters. |
2946 | */ |
2947 | template<typename _RealType> |
2948 | inline bool |
2949 | operator!=(const std::cauchy_distribution<_RealType>& __d1, |
2950 | const std::cauchy_distribution<_RealType>& __d2) |
2951 | { return !(__d1 == __d2); } |
2952 | |
2953 | /** |
2954 | * @brief Inserts a %cauchy_distribution random number distribution |
2955 | * @p __x into the output stream @p __os. |
2956 | * |
2957 | * @param __os An output stream. |
2958 | * @param __x A %cauchy_distribution random number distribution. |
2959 | * |
2960 | * @returns The output stream with the state of @p __x inserted or in |
2961 | * an error state. |
2962 | */ |
2963 | template<typename _RealType, typename _CharT, typename _Traits> |
2964 | std::basic_ostream<_CharT, _Traits>& |
2965 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
2966 | const std::cauchy_distribution<_RealType>& __x); |
2967 | |
2968 | /** |
2969 | * @brief Extracts a %cauchy_distribution random number distribution |
2970 | * @p __x from the input stream @p __is. |
2971 | * |
2972 | * @param __is An input stream. |
2973 | * @param __x A %cauchy_distribution random number |
2974 | * generator engine. |
2975 | * |
2976 | * @returns The input stream with @p __x extracted or in an error state. |
2977 | */ |
2978 | template<typename _RealType, typename _CharT, typename _Traits> |
2979 | std::basic_istream<_CharT, _Traits>& |
2980 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
2981 | std::cauchy_distribution<_RealType>& __x); |
2982 | |
2983 | |
2984 | /** |
2985 | * @brief A fisher_f_distribution random number distribution. |
2986 | * |
2987 | * The formula for the normal probability mass function is |
2988 | * @f[ |
2989 | * p(x|m,n) = \frac{\Gamma((m+n)/2)}{\Gamma(m/2)\Gamma(n/2)} |
2990 | * (\frac{m}{n})^{m/2} x^{(m/2)-1} |
2991 | * (1 + \frac{mx}{n})^{-(m+n)/2} |
2992 | * @f] |
2993 | */ |
2994 | template<typename _RealType = double> |
2995 | class fisher_f_distribution |
2996 | { |
2997 | static_assert(std::is_floating_point<_RealType>::value, |
2998 | "result_type must be a floating point type" ); |
2999 | |
3000 | public: |
3001 | /** The type of the range of the distribution. */ |
3002 | typedef _RealType result_type; |
3003 | |
3004 | /** Parameter type. */ |
3005 | struct param_type |
3006 | { |
3007 | typedef fisher_f_distribution<_RealType> distribution_type; |
3008 | |
3009 | explicit |
3010 | param_type(_RealType __m = _RealType(1), |
3011 | _RealType __n = _RealType(1)) |
3012 | : _M_m(__m), _M_n(__n) |
3013 | { } |
3014 | |
3015 | _RealType |
3016 | m() const |
3017 | { return _M_m; } |
3018 | |
3019 | _RealType |
3020 | n() const |
3021 | { return _M_n; } |
3022 | |
3023 | friend bool |
3024 | operator==(const param_type& __p1, const param_type& __p2) |
3025 | { return __p1._M_m == __p2._M_m && __p1._M_n == __p2._M_n; } |
3026 | |
3027 | friend bool |
3028 | operator!=(const param_type& __p1, const param_type& __p2) |
3029 | { return !(__p1 == __p2); } |
3030 | |
3031 | private: |
3032 | _RealType _M_m; |
3033 | _RealType _M_n; |
3034 | }; |
3035 | |
3036 | explicit |
3037 | fisher_f_distribution(_RealType __m = _RealType(1), |
3038 | _RealType __n = _RealType(1)) |
3039 | : _M_param(__m, __n), _M_gd_x(__m / 2), _M_gd_y(__n / 2) |
3040 | { } |
3041 | |
3042 | explicit |
3043 | fisher_f_distribution(const param_type& __p) |
3044 | : _M_param(__p), _M_gd_x(__p.m() / 2), _M_gd_y(__p.n() / 2) |
3045 | { } |
3046 | |
3047 | /** |
3048 | * @brief Resets the distribution state. |
3049 | */ |
3050 | void |
3051 | reset() |
3052 | { |
3053 | _M_gd_x.reset(); |
3054 | _M_gd_y.reset(); |
3055 | } |
3056 | |
3057 | /** |
3058 | * |
3059 | */ |
3060 | _RealType |
3061 | m() const |
3062 | { return _M_param.m(); } |
3063 | |
3064 | _RealType |
3065 | n() const |
3066 | { return _M_param.n(); } |
3067 | |
3068 | /** |
3069 | * @brief Returns the parameter set of the distribution. |
3070 | */ |
3071 | param_type |
3072 | param() const |
3073 | { return _M_param; } |
3074 | |
3075 | /** |
3076 | * @brief Sets the parameter set of the distribution. |
3077 | * @param __param The new parameter set of the distribution. |
3078 | */ |
3079 | void |
3080 | param(const param_type& __param) |
3081 | { _M_param = __param; } |
3082 | |
3083 | /** |
3084 | * @brief Returns the greatest lower bound value of the distribution. |
3085 | */ |
3086 | result_type |
3087 | min() const |
3088 | { return result_type(0); } |
3089 | |
3090 | /** |
3091 | * @brief Returns the least upper bound value of the distribution. |
3092 | */ |
3093 | result_type |
3094 | max() const |
3095 | { return std::numeric_limits<result_type>::max(); } |
3096 | |
3097 | /** |
3098 | * @brief Generating functions. |
3099 | */ |
3100 | template<typename _UniformRandomNumberGenerator> |
3101 | result_type |
3102 | operator()(_UniformRandomNumberGenerator& __urng) |
3103 | { return (_M_gd_x(__urng) * n()) / (_M_gd_y(__urng) * m()); } |
3104 | |
3105 | template<typename _UniformRandomNumberGenerator> |
3106 | result_type |
3107 | operator()(_UniformRandomNumberGenerator& __urng, |
3108 | const param_type& __p) |
3109 | { |
3110 | typedef typename std::gamma_distribution<result_type>::param_type |
3111 | param_type; |
3112 | return ((_M_gd_x(__urng, param_type(__p.m() / 2)) * n()) |
3113 | / (_M_gd_y(__urng, param_type(__p.n() / 2)) * m())); |
3114 | } |
3115 | |
3116 | template<typename _ForwardIterator, |
3117 | typename _UniformRandomNumberGenerator> |
3118 | void |
3119 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
3120 | _UniformRandomNumberGenerator& __urng) |
3121 | { this->__generate_impl(__f, __t, __urng); } |
3122 | |
3123 | template<typename _ForwardIterator, |
3124 | typename _UniformRandomNumberGenerator> |
3125 | void |
3126 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
3127 | _UniformRandomNumberGenerator& __urng, |
3128 | const param_type& __p) |
3129 | { this->__generate_impl(__f, __t, __urng, __p); } |
3130 | |
3131 | template<typename _UniformRandomNumberGenerator> |
3132 | void |
3133 | __generate(result_type* __f, result_type* __t, |
3134 | _UniformRandomNumberGenerator& __urng) |
3135 | { this->__generate_impl(__f, __t, __urng); } |
3136 | |
3137 | template<typename _UniformRandomNumberGenerator> |
3138 | void |
3139 | __generate(result_type* __f, result_type* __t, |
3140 | _UniformRandomNumberGenerator& __urng, |
3141 | const param_type& __p) |
3142 | { this->__generate_impl(__f, __t, __urng, __p); } |
3143 | |
3144 | /** |
3145 | * @brief Return true if two Fisher f distributions have |
3146 | * the same parameters and the sequences that would |
3147 | * be generated are equal. |
3148 | */ |
3149 | friend bool |
3150 | operator==(const fisher_f_distribution& __d1, |
3151 | const fisher_f_distribution& __d2) |
3152 | { return (__d1._M_param == __d2._M_param |
3153 | && __d1._M_gd_x == __d2._M_gd_x |
3154 | && __d1._M_gd_y == __d2._M_gd_y); } |
3155 | |
3156 | /** |
3157 | * @brief Inserts a %fisher_f_distribution random number distribution |
3158 | * @p __x into the output stream @p __os. |
3159 | * |
3160 | * @param __os An output stream. |
3161 | * @param __x A %fisher_f_distribution random number distribution. |
3162 | * |
3163 | * @returns The output stream with the state of @p __x inserted or in |
3164 | * an error state. |
3165 | */ |
3166 | template<typename _RealType1, typename _CharT, typename _Traits> |
3167 | friend std::basic_ostream<_CharT, _Traits>& |
3168 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
3169 | const std::fisher_f_distribution<_RealType1>& __x); |
3170 | |
3171 | /** |
3172 | * @brief Extracts a %fisher_f_distribution random number distribution |
3173 | * @p __x from the input stream @p __is. |
3174 | * |
3175 | * @param __is An input stream. |
3176 | * @param __x A %fisher_f_distribution random number |
3177 | * generator engine. |
3178 | * |
3179 | * @returns The input stream with @p __x extracted or in an error state. |
3180 | */ |
3181 | template<typename _RealType1, typename _CharT, typename _Traits> |
3182 | friend std::basic_istream<_CharT, _Traits>& |
3183 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
3184 | std::fisher_f_distribution<_RealType1>& __x); |
3185 | |
3186 | private: |
3187 | template<typename _ForwardIterator, |
3188 | typename _UniformRandomNumberGenerator> |
3189 | void |
3190 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
3191 | _UniformRandomNumberGenerator& __urng); |
3192 | |
3193 | template<typename _ForwardIterator, |
3194 | typename _UniformRandomNumberGenerator> |
3195 | void |
3196 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
3197 | _UniformRandomNumberGenerator& __urng, |
3198 | const param_type& __p); |
3199 | |
3200 | param_type _M_param; |
3201 | |
3202 | std::gamma_distribution<result_type> _M_gd_x, _M_gd_y; |
3203 | }; |
3204 | |
3205 | /** |
3206 | * @brief Return true if two Fisher f distributions are different. |
3207 | */ |
3208 | template<typename _RealType> |
3209 | inline bool |
3210 | operator!=(const std::fisher_f_distribution<_RealType>& __d1, |
3211 | const std::fisher_f_distribution<_RealType>& __d2) |
3212 | { return !(__d1 == __d2); } |
3213 | |
3214 | /** |
3215 | * @brief A student_t_distribution random number distribution. |
3216 | * |
3217 | * The formula for the normal probability mass function is: |
3218 | * @f[ |
3219 | * p(x|n) = \frac{1}{\sqrt(n\pi)} \frac{\Gamma((n+1)/2)}{\Gamma(n/2)} |
3220 | * (1 + \frac{x^2}{n}) ^{-(n+1)/2} |
3221 | * @f] |
3222 | */ |
3223 | template<typename _RealType = double> |
3224 | class student_t_distribution |
3225 | { |
3226 | static_assert(std::is_floating_point<_RealType>::value, |
3227 | "result_type must be a floating point type" ); |
3228 | |
3229 | public: |
3230 | /** The type of the range of the distribution. */ |
3231 | typedef _RealType result_type; |
3232 | |
3233 | /** Parameter type. */ |
3234 | struct param_type |
3235 | { |
3236 | typedef student_t_distribution<_RealType> distribution_type; |
3237 | |
3238 | explicit |
3239 | param_type(_RealType __n = _RealType(1)) |
3240 | : _M_n(__n) |
3241 | { } |
3242 | |
3243 | _RealType |
3244 | n() const |
3245 | { return _M_n; } |
3246 | |
3247 | friend bool |
3248 | operator==(const param_type& __p1, const param_type& __p2) |
3249 | { return __p1._M_n == __p2._M_n; } |
3250 | |
3251 | friend bool |
3252 | operator!=(const param_type& __p1, const param_type& __p2) |
3253 | { return !(__p1 == __p2); } |
3254 | |
3255 | private: |
3256 | _RealType _M_n; |
3257 | }; |
3258 | |
3259 | explicit |
3260 | student_t_distribution(_RealType __n = _RealType(1)) |
3261 | : _M_param(__n), _M_nd(), _M_gd(__n / 2, 2) |
3262 | { } |
3263 | |
3264 | explicit |
3265 | student_t_distribution(const param_type& __p) |
3266 | : _M_param(__p), _M_nd(), _M_gd(__p.n() / 2, 2) |
3267 | { } |
3268 | |
3269 | /** |
3270 | * @brief Resets the distribution state. |
3271 | */ |
3272 | void |
3273 | reset() |
3274 | { |
3275 | _M_nd.reset(); |
3276 | _M_gd.reset(); |
3277 | } |
3278 | |
3279 | /** |
3280 | * |
3281 | */ |
3282 | _RealType |
3283 | n() const |
3284 | { return _M_param.n(); } |
3285 | |
3286 | /** |
3287 | * @brief Returns the parameter set of the distribution. |
3288 | */ |
3289 | param_type |
3290 | param() const |
3291 | { return _M_param; } |
3292 | |
3293 | /** |
3294 | * @brief Sets the parameter set of the distribution. |
3295 | * @param __param The new parameter set of the distribution. |
3296 | */ |
3297 | void |
3298 | param(const param_type& __param) |
3299 | { _M_param = __param; } |
3300 | |
3301 | /** |
3302 | * @brief Returns the greatest lower bound value of the distribution. |
3303 | */ |
3304 | result_type |
3305 | min() const |
3306 | { return std::numeric_limits<result_type>::lowest(); } |
3307 | |
3308 | /** |
3309 | * @brief Returns the least upper bound value of the distribution. |
3310 | */ |
3311 | result_type |
3312 | max() const |
3313 | { return std::numeric_limits<result_type>::max(); } |
3314 | |
3315 | /** |
3316 | * @brief Generating functions. |
3317 | */ |
3318 | template<typename _UniformRandomNumberGenerator> |
3319 | result_type |
3320 | operator()(_UniformRandomNumberGenerator& __urng) |
3321 | { return _M_nd(__urng) * std::sqrt(n() / _M_gd(__urng)); } |
3322 | |
3323 | template<typename _UniformRandomNumberGenerator> |
3324 | result_type |
3325 | operator()(_UniformRandomNumberGenerator& __urng, |
3326 | const param_type& __p) |
3327 | { |
3328 | typedef typename std::gamma_distribution<result_type>::param_type |
3329 | param_type; |
3330 | |
3331 | const result_type __g = _M_gd(__urng, param_type(__p.n() / 2, 2)); |
3332 | return _M_nd(__urng) * std::sqrt(__p.n() / __g); |
3333 | } |
3334 | |
3335 | template<typename _ForwardIterator, |
3336 | typename _UniformRandomNumberGenerator> |
3337 | void |
3338 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
3339 | _UniformRandomNumberGenerator& __urng) |
3340 | { this->__generate_impl(__f, __t, __urng); } |
3341 | |
3342 | template<typename _ForwardIterator, |
3343 | typename _UniformRandomNumberGenerator> |
3344 | void |
3345 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
3346 | _UniformRandomNumberGenerator& __urng, |
3347 | const param_type& __p) |
3348 | { this->__generate_impl(__f, __t, __urng, __p); } |
3349 | |
3350 | template<typename _UniformRandomNumberGenerator> |
3351 | void |
3352 | __generate(result_type* __f, result_type* __t, |
3353 | _UniformRandomNumberGenerator& __urng) |
3354 | { this->__generate_impl(__f, __t, __urng); } |
3355 | |
3356 | template<typename _UniformRandomNumberGenerator> |
3357 | void |
3358 | __generate(result_type* __f, result_type* __t, |
3359 | _UniformRandomNumberGenerator& __urng, |
3360 | const param_type& __p) |
3361 | { this->__generate_impl(__f, __t, __urng, __p); } |
3362 | |
3363 | /** |
3364 | * @brief Return true if two Student t distributions have |
3365 | * the same parameters and the sequences that would |
3366 | * be generated are equal. |
3367 | */ |
3368 | friend bool |
3369 | operator==(const student_t_distribution& __d1, |
3370 | const student_t_distribution& __d2) |
3371 | { return (__d1._M_param == __d2._M_param |
3372 | && __d1._M_nd == __d2._M_nd && __d1._M_gd == __d2._M_gd); } |
3373 | |
3374 | /** |
3375 | * @brief Inserts a %student_t_distribution random number distribution |
3376 | * @p __x into the output stream @p __os. |
3377 | * |
3378 | * @param __os An output stream. |
3379 | * @param __x A %student_t_distribution random number distribution. |
3380 | * |
3381 | * @returns The output stream with the state of @p __x inserted or in |
3382 | * an error state. |
3383 | */ |
3384 | template<typename _RealType1, typename _CharT, typename _Traits> |
3385 | friend std::basic_ostream<_CharT, _Traits>& |
3386 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
3387 | const std::student_t_distribution<_RealType1>& __x); |
3388 | |
3389 | /** |
3390 | * @brief Extracts a %student_t_distribution random number distribution |
3391 | * @p __x from the input stream @p __is. |
3392 | * |
3393 | * @param __is An input stream. |
3394 | * @param __x A %student_t_distribution random number |
3395 | * generator engine. |
3396 | * |
3397 | * @returns The input stream with @p __x extracted or in an error state. |
3398 | */ |
3399 | template<typename _RealType1, typename _CharT, typename _Traits> |
3400 | friend std::basic_istream<_CharT, _Traits>& |
3401 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
3402 | std::student_t_distribution<_RealType1>& __x); |
3403 | |
3404 | private: |
3405 | template<typename _ForwardIterator, |
3406 | typename _UniformRandomNumberGenerator> |
3407 | void |
3408 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
3409 | _UniformRandomNumberGenerator& __urng); |
3410 | template<typename _ForwardIterator, |
3411 | typename _UniformRandomNumberGenerator> |
3412 | void |
3413 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
3414 | _UniformRandomNumberGenerator& __urng, |
3415 | const param_type& __p); |
3416 | |
3417 | param_type _M_param; |
3418 | |
3419 | std::normal_distribution<result_type> _M_nd; |
3420 | std::gamma_distribution<result_type> _M_gd; |
3421 | }; |
3422 | |
3423 | /** |
3424 | * @brief Return true if two Student t distributions are different. |
3425 | */ |
3426 | template<typename _RealType> |
3427 | inline bool |
3428 | operator!=(const std::student_t_distribution<_RealType>& __d1, |
3429 | const std::student_t_distribution<_RealType>& __d2) |
3430 | { return !(__d1 == __d2); } |
3431 | |
3432 | |
3433 | /* @} */ // group random_distributions_normal |
3434 | |
3435 | /** |
3436 | * @addtogroup random_distributions_bernoulli Bernoulli Distributions |
3437 | * @ingroup random_distributions |
3438 | * @{ |
3439 | */ |
3440 | |
3441 | /** |
3442 | * @brief A Bernoulli random number distribution. |
3443 | * |
3444 | * Generates a sequence of true and false values with likelihood @f$p@f$ |
3445 | * that true will come up and @f$(1 - p)@f$ that false will appear. |
3446 | */ |
3447 | class bernoulli_distribution |
3448 | { |
3449 | public: |
3450 | /** The type of the range of the distribution. */ |
3451 | typedef bool result_type; |
3452 | |
3453 | /** Parameter type. */ |
3454 | struct param_type |
3455 | { |
3456 | typedef bernoulli_distribution distribution_type; |
3457 | |
3458 | explicit |
3459 | param_type(double __p = 0.5) |
3460 | : _M_p(__p) |
3461 | { |
3462 | __glibcxx_assert((_M_p >= 0.0) && (_M_p <= 1.0)); |
3463 | } |
3464 | |
3465 | double |
3466 | p() const |
3467 | { return _M_p; } |
3468 | |
3469 | friend bool |
3470 | operator==(const param_type& __p1, const param_type& __p2) |
3471 | { return __p1._M_p == __p2._M_p; } |
3472 | |
3473 | friend bool |
3474 | operator!=(const param_type& __p1, const param_type& __p2) |
3475 | { return !(__p1 == __p2); } |
3476 | |
3477 | private: |
3478 | double _M_p; |
3479 | }; |
3480 | |
3481 | public: |
3482 | /** |
3483 | * @brief Constructs a Bernoulli distribution with likelihood @p p. |
3484 | * |
3485 | * @param __p [IN] The likelihood of a true result being returned. |
3486 | * Must be in the interval @f$[0, 1]@f$. |
3487 | */ |
3488 | explicit |
3489 | bernoulli_distribution(double __p = 0.5) |
3490 | : _M_param(__p) |
3491 | { } |
3492 | |
3493 | explicit |
3494 | bernoulli_distribution(const param_type& __p) |
3495 | : _M_param(__p) |
3496 | { } |
3497 | |
3498 | /** |
3499 | * @brief Resets the distribution state. |
3500 | * |
3501 | * Does nothing for a Bernoulli distribution. |
3502 | */ |
3503 | void |
3504 | reset() { } |
3505 | |
3506 | /** |
3507 | * @brief Returns the @p p parameter of the distribution. |
3508 | */ |
3509 | double |
3510 | p() const |
3511 | { return _M_param.p(); } |
3512 | |
3513 | /** |
3514 | * @brief Returns the parameter set of the distribution. |
3515 | */ |
3516 | param_type |
3517 | param() const |
3518 | { return _M_param; } |
3519 | |
3520 | /** |
3521 | * @brief Sets the parameter set of the distribution. |
3522 | * @param __param The new parameter set of the distribution. |
3523 | */ |
3524 | void |
3525 | param(const param_type& __param) |
3526 | { _M_param = __param; } |
3527 | |
3528 | /** |
3529 | * @brief Returns the greatest lower bound value of the distribution. |
3530 | */ |
3531 | result_type |
3532 | min() const |
3533 | { return std::numeric_limits<result_type>::min(); } |
3534 | |
3535 | /** |
3536 | * @brief Returns the least upper bound value of the distribution. |
3537 | */ |
3538 | result_type |
3539 | max() const |
3540 | { return std::numeric_limits<result_type>::max(); } |
3541 | |
3542 | /** |
3543 | * @brief Generating functions. |
3544 | */ |
3545 | template<typename _UniformRandomNumberGenerator> |
3546 | result_type |
3547 | operator()(_UniformRandomNumberGenerator& __urng) |
3548 | { return this->operator()(__urng, _M_param); } |
3549 | |
3550 | template<typename _UniformRandomNumberGenerator> |
3551 | result_type |
3552 | operator()(_UniformRandomNumberGenerator& __urng, |
3553 | const param_type& __p) |
3554 | { |
3555 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> |
3556 | __aurng(__urng); |
3557 | if ((__aurng() - __aurng.min()) |
3558 | < __p.p() * (__aurng.max() - __aurng.min())) |
3559 | return true; |
3560 | return false; |
3561 | } |
3562 | |
3563 | template<typename _ForwardIterator, |
3564 | typename _UniformRandomNumberGenerator> |
3565 | void |
3566 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
3567 | _UniformRandomNumberGenerator& __urng) |
3568 | { this->__generate(__f, __t, __urng, _M_param); } |
3569 | |
3570 | template<typename _ForwardIterator, |
3571 | typename _UniformRandomNumberGenerator> |
3572 | void |
3573 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
3574 | _UniformRandomNumberGenerator& __urng, const param_type& __p) |
3575 | { this->__generate_impl(__f, __t, __urng, __p); } |
3576 | |
3577 | template<typename _UniformRandomNumberGenerator> |
3578 | void |
3579 | __generate(result_type* __f, result_type* __t, |
3580 | _UniformRandomNumberGenerator& __urng, |
3581 | const param_type& __p) |
3582 | { this->__generate_impl(__f, __t, __urng, __p); } |
3583 | |
3584 | /** |
3585 | * @brief Return true if two Bernoulli distributions have |
3586 | * the same parameters. |
3587 | */ |
3588 | friend bool |
3589 | operator==(const bernoulli_distribution& __d1, |
3590 | const bernoulli_distribution& __d2) |
3591 | { return __d1._M_param == __d2._M_param; } |
3592 | |
3593 | private: |
3594 | template<typename _ForwardIterator, |
3595 | typename _UniformRandomNumberGenerator> |
3596 | void |
3597 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
3598 | _UniformRandomNumberGenerator& __urng, |
3599 | const param_type& __p); |
3600 | |
3601 | param_type _M_param; |
3602 | }; |
3603 | |
3604 | /** |
3605 | * @brief Return true if two Bernoulli distributions have |
3606 | * different parameters. |
3607 | */ |
3608 | inline bool |
3609 | operator!=(const std::bernoulli_distribution& __d1, |
3610 | const std::bernoulli_distribution& __d2) |
3611 | { return !(__d1 == __d2); } |
3612 | |
3613 | /** |
3614 | * @brief Inserts a %bernoulli_distribution random number distribution |
3615 | * @p __x into the output stream @p __os. |
3616 | * |
3617 | * @param __os An output stream. |
3618 | * @param __x A %bernoulli_distribution random number distribution. |
3619 | * |
3620 | * @returns The output stream with the state of @p __x inserted or in |
3621 | * an error state. |
3622 | */ |
3623 | template<typename _CharT, typename _Traits> |
3624 | std::basic_ostream<_CharT, _Traits>& |
3625 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
3626 | const std::bernoulli_distribution& __x); |
3627 | |
3628 | /** |
3629 | * @brief Extracts a %bernoulli_distribution random number distribution |
3630 | * @p __x from the input stream @p __is. |
3631 | * |
3632 | * @param __is An input stream. |
3633 | * @param __x A %bernoulli_distribution random number generator engine. |
3634 | * |
3635 | * @returns The input stream with @p __x extracted or in an error state. |
3636 | */ |
3637 | template<typename _CharT, typename _Traits> |
3638 | std::basic_istream<_CharT, _Traits>& |
3639 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
3640 | std::bernoulli_distribution& __x) |
3641 | { |
3642 | double __p; |
3643 | __is >> __p; |
3644 | __x.param(bernoulli_distribution::param_type(__p)); |
3645 | return __is; |
3646 | } |
3647 | |
3648 | |
3649 | /** |
3650 | * @brief A discrete binomial random number distribution. |
3651 | * |
3652 | * The formula for the binomial probability density function is |
3653 | * @f$p(i|t,p) = \binom{t}{i} p^i (1 - p)^{t - i}@f$ where @f$t@f$ |
3654 | * and @f$p@f$ are the parameters of the distribution. |
3655 | */ |
3656 | template<typename _IntType = int> |
3657 | class binomial_distribution |
3658 | { |
3659 | static_assert(std::is_integral<_IntType>::value, |
3660 | "result_type must be an integral type" ); |
3661 | |
3662 | public: |
3663 | /** The type of the range of the distribution. */ |
3664 | typedef _IntType result_type; |
3665 | |
3666 | /** Parameter type. */ |
3667 | struct param_type |
3668 | { |
3669 | typedef binomial_distribution<_IntType> distribution_type; |
3670 | friend class binomial_distribution<_IntType>; |
3671 | |
3672 | explicit |
3673 | param_type(_IntType __t = _IntType(1), double __p = 0.5) |
3674 | : _M_t(__t), _M_p(__p) |
3675 | { |
3676 | __glibcxx_assert((_M_t >= _IntType(0)) |
3677 | && (_M_p >= 0.0) |
3678 | && (_M_p <= 1.0)); |
3679 | _M_initialize(); |
3680 | } |
3681 | |
3682 | _IntType |
3683 | t() const |
3684 | { return _M_t; } |
3685 | |
3686 | double |
3687 | p() const |
3688 | { return _M_p; } |
3689 | |
3690 | friend bool |
3691 | operator==(const param_type& __p1, const param_type& __p2) |
3692 | { return __p1._M_t == __p2._M_t && __p1._M_p == __p2._M_p; } |
3693 | |
3694 | friend bool |
3695 | operator!=(const param_type& __p1, const param_type& __p2) |
3696 | { return !(__p1 == __p2); } |
3697 | |
3698 | private: |
3699 | void |
3700 | _M_initialize(); |
3701 | |
3702 | _IntType _M_t; |
3703 | double _M_p; |
3704 | |
3705 | double _M_q; |
3706 | #if _GLIBCXX_USE_C99_MATH_TR1 |
3707 | double _M_d1, _M_d2, _M_s1, _M_s2, _M_c, |
3708 | _M_a1, _M_a123, _M_s, _M_lf, _M_lp1p; |
3709 | #endif |
3710 | bool _M_easy; |
3711 | }; |
3712 | |
3713 | // constructors and member function |
3714 | explicit |
3715 | binomial_distribution(_IntType __t = _IntType(1), |
3716 | double __p = 0.5) |
3717 | : _M_param(__t, __p), _M_nd() |
3718 | { } |
3719 | |
3720 | explicit |
3721 | binomial_distribution(const param_type& __p) |
3722 | : _M_param(__p), _M_nd() |
3723 | { } |
3724 | |
3725 | /** |
3726 | * @brief Resets the distribution state. |
3727 | */ |
3728 | void |
3729 | reset() |
3730 | { _M_nd.reset(); } |
3731 | |
3732 | /** |
3733 | * @brief Returns the distribution @p t parameter. |
3734 | */ |
3735 | _IntType |
3736 | t() const |
3737 | { return _M_param.t(); } |
3738 | |
3739 | /** |
3740 | * @brief Returns the distribution @p p parameter. |
3741 | */ |
3742 | double |
3743 | p() const |
3744 | { return _M_param.p(); } |
3745 | |
3746 | /** |
3747 | * @brief Returns the parameter set of the distribution. |
3748 | */ |
3749 | param_type |
3750 | param() const |
3751 | { return _M_param; } |
3752 | |
3753 | /** |
3754 | * @brief Sets the parameter set of the distribution. |
3755 | * @param __param The new parameter set of the distribution. |
3756 | */ |
3757 | void |
3758 | param(const param_type& __param) |
3759 | { _M_param = __param; } |
3760 | |
3761 | /** |
3762 | * @brief Returns the greatest lower bound value of the distribution. |
3763 | */ |
3764 | result_type |
3765 | min() const |
3766 | { return 0; } |
3767 | |
3768 | /** |
3769 | * @brief Returns the least upper bound value of the distribution. |
3770 | */ |
3771 | result_type |
3772 | max() const |
3773 | { return _M_param.t(); } |
3774 | |
3775 | /** |
3776 | * @brief Generating functions. |
3777 | */ |
3778 | template<typename _UniformRandomNumberGenerator> |
3779 | result_type |
3780 | operator()(_UniformRandomNumberGenerator& __urng) |
3781 | { return this->operator()(__urng, _M_param); } |
3782 | |
3783 | template<typename _UniformRandomNumberGenerator> |
3784 | result_type |
3785 | operator()(_UniformRandomNumberGenerator& __urng, |
3786 | const param_type& __p); |
3787 | |
3788 | template<typename _ForwardIterator, |
3789 | typename _UniformRandomNumberGenerator> |
3790 | void |
3791 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
3792 | _UniformRandomNumberGenerator& __urng) |
3793 | { this->__generate(__f, __t, __urng, _M_param); } |
3794 | |
3795 | template<typename _ForwardIterator, |
3796 | typename _UniformRandomNumberGenerator> |
3797 | void |
3798 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
3799 | _UniformRandomNumberGenerator& __urng, |
3800 | const param_type& __p) |
3801 | { this->__generate_impl(__f, __t, __urng, __p); } |
3802 | |
3803 | template<typename _UniformRandomNumberGenerator> |
3804 | void |
3805 | __generate(result_type* __f, result_type* __t, |
3806 | _UniformRandomNumberGenerator& __urng, |
3807 | const param_type& __p) |
3808 | { this->__generate_impl(__f, __t, __urng, __p); } |
3809 | |
3810 | /** |
3811 | * @brief Return true if two binomial distributions have |
3812 | * the same parameters and the sequences that would |
3813 | * be generated are equal. |
3814 | */ |
3815 | friend bool |
3816 | operator==(const binomial_distribution& __d1, |
3817 | const binomial_distribution& __d2) |
3818 | #ifdef _GLIBCXX_USE_C99_MATH_TR1 |
3819 | { return __d1._M_param == __d2._M_param && __d1._M_nd == __d2._M_nd; } |
3820 | #else |
3821 | { return __d1._M_param == __d2._M_param; } |
3822 | #endif |
3823 | |
3824 | /** |
3825 | * @brief Inserts a %binomial_distribution random number distribution |
3826 | * @p __x into the output stream @p __os. |
3827 | * |
3828 | * @param __os An output stream. |
3829 | * @param __x A %binomial_distribution random number distribution. |
3830 | * |
3831 | * @returns The output stream with the state of @p __x inserted or in |
3832 | * an error state. |
3833 | */ |
3834 | template<typename _IntType1, |
3835 | typename _CharT, typename _Traits> |
3836 | friend std::basic_ostream<_CharT, _Traits>& |
3837 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
3838 | const std::binomial_distribution<_IntType1>& __x); |
3839 | |
3840 | /** |
3841 | * @brief Extracts a %binomial_distribution random number distribution |
3842 | * @p __x from the input stream @p __is. |
3843 | * |
3844 | * @param __is An input stream. |
3845 | * @param __x A %binomial_distribution random number generator engine. |
3846 | * |
3847 | * @returns The input stream with @p __x extracted or in an error |
3848 | * state. |
3849 | */ |
3850 | template<typename _IntType1, |
3851 | typename _CharT, typename _Traits> |
3852 | friend std::basic_istream<_CharT, _Traits>& |
3853 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
3854 | std::binomial_distribution<_IntType1>& __x); |
3855 | |
3856 | private: |
3857 | template<typename _ForwardIterator, |
3858 | typename _UniformRandomNumberGenerator> |
3859 | void |
3860 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
3861 | _UniformRandomNumberGenerator& __urng, |
3862 | const param_type& __p); |
3863 | |
3864 | template<typename _UniformRandomNumberGenerator> |
3865 | result_type |
3866 | _M_waiting(_UniformRandomNumberGenerator& __urng, |
3867 | _IntType __t, double __q); |
3868 | |
3869 | param_type _M_param; |
3870 | |
3871 | // NB: Unused when _GLIBCXX_USE_C99_MATH_TR1 is undefined. |
3872 | std::normal_distribution<double> _M_nd; |
3873 | }; |
3874 | |
3875 | /** |
3876 | * @brief Return true if two binomial distributions are different. |
3877 | */ |
3878 | template<typename _IntType> |
3879 | inline bool |
3880 | operator!=(const std::binomial_distribution<_IntType>& __d1, |
3881 | const std::binomial_distribution<_IntType>& __d2) |
3882 | { return !(__d1 == __d2); } |
3883 | |
3884 | |
3885 | /** |
3886 | * @brief A discrete geometric random number distribution. |
3887 | * |
3888 | * The formula for the geometric probability density function is |
3889 | * @f$p(i|p) = p(1 - p)^{i}@f$ where @f$p@f$ is the parameter of the |
3890 | * distribution. |
3891 | */ |
3892 | template<typename _IntType = int> |
3893 | class geometric_distribution |
3894 | { |
3895 | static_assert(std::is_integral<_IntType>::value, |
3896 | "result_type must be an integral type" ); |
3897 | |
3898 | public: |
3899 | /** The type of the range of the distribution. */ |
3900 | typedef _IntType result_type; |
3901 | |
3902 | /** Parameter type. */ |
3903 | struct param_type |
3904 | { |
3905 | typedef geometric_distribution<_IntType> distribution_type; |
3906 | friend class geometric_distribution<_IntType>; |
3907 | |
3908 | explicit |
3909 | param_type(double __p = 0.5) |
3910 | : _M_p(__p) |
3911 | { |
3912 | __glibcxx_assert((_M_p > 0.0) && (_M_p < 1.0)); |
3913 | _M_initialize(); |
3914 | } |
3915 | |
3916 | double |
3917 | p() const |
3918 | { return _M_p; } |
3919 | |
3920 | friend bool |
3921 | operator==(const param_type& __p1, const param_type& __p2) |
3922 | { return __p1._M_p == __p2._M_p; } |
3923 | |
3924 | friend bool |
3925 | operator!=(const param_type& __p1, const param_type& __p2) |
3926 | { return !(__p1 == __p2); } |
3927 | |
3928 | private: |
3929 | void |
3930 | _M_initialize() |
3931 | { _M_log_1_p = std::log(1.0 - _M_p); } |
3932 | |
3933 | double _M_p; |
3934 | |
3935 | double _M_log_1_p; |
3936 | }; |
3937 | |
3938 | // constructors and member function |
3939 | explicit |
3940 | geometric_distribution(double __p = 0.5) |
3941 | : _M_param(__p) |
3942 | { } |
3943 | |
3944 | explicit |
3945 | geometric_distribution(const param_type& __p) |
3946 | : _M_param(__p) |
3947 | { } |
3948 | |
3949 | /** |
3950 | * @brief Resets the distribution state. |
3951 | * |
3952 | * Does nothing for the geometric distribution. |
3953 | */ |
3954 | void |
3955 | reset() { } |
3956 | |
3957 | /** |
3958 | * @brief Returns the distribution parameter @p p. |
3959 | */ |
3960 | double |
3961 | p() const |
3962 | { return _M_param.p(); } |
3963 | |
3964 | /** |
3965 | * @brief Returns the parameter set of the distribution. |
3966 | */ |
3967 | param_type |
3968 | param() const |
3969 | { return _M_param; } |
3970 | |
3971 | /** |
3972 | * @brief Sets the parameter set of the distribution. |
3973 | * @param __param The new parameter set of the distribution. |
3974 | */ |
3975 | void |
3976 | param(const param_type& __param) |
3977 | { _M_param = __param; } |
3978 | |
3979 | /** |
3980 | * @brief Returns the greatest lower bound value of the distribution. |
3981 | */ |
3982 | result_type |
3983 | min() const |
3984 | { return 0; } |
3985 | |
3986 | /** |
3987 | * @brief Returns the least upper bound value of the distribution. |
3988 | */ |
3989 | result_type |
3990 | max() const |
3991 | { return std::numeric_limits<result_type>::max(); } |
3992 | |
3993 | /** |
3994 | * @brief Generating functions. |
3995 | */ |
3996 | template<typename _UniformRandomNumberGenerator> |
3997 | result_type |
3998 | operator()(_UniformRandomNumberGenerator& __urng) |
3999 | { return this->operator()(__urng, _M_param); } |
4000 | |
4001 | template<typename _UniformRandomNumberGenerator> |
4002 | result_type |
4003 | operator()(_UniformRandomNumberGenerator& __urng, |
4004 | const param_type& __p); |
4005 | |
4006 | template<typename _ForwardIterator, |
4007 | typename _UniformRandomNumberGenerator> |
4008 | void |
4009 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
4010 | _UniformRandomNumberGenerator& __urng) |
4011 | { this->__generate(__f, __t, __urng, _M_param); } |
4012 | |
4013 | template<typename _ForwardIterator, |
4014 | typename _UniformRandomNumberGenerator> |
4015 | void |
4016 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
4017 | _UniformRandomNumberGenerator& __urng, |
4018 | const param_type& __p) |
4019 | { this->__generate_impl(__f, __t, __urng, __p); } |
4020 | |
4021 | template<typename _UniformRandomNumberGenerator> |
4022 | void |
4023 | __generate(result_type* __f, result_type* __t, |
4024 | _UniformRandomNumberGenerator& __urng, |
4025 | const param_type& __p) |
4026 | { this->__generate_impl(__f, __t, __urng, __p); } |
4027 | |
4028 | /** |
4029 | * @brief Return true if two geometric distributions have |
4030 | * the same parameters. |
4031 | */ |
4032 | friend bool |
4033 | operator==(const geometric_distribution& __d1, |
4034 | const geometric_distribution& __d2) |
4035 | { return __d1._M_param == __d2._M_param; } |
4036 | |
4037 | private: |
4038 | template<typename _ForwardIterator, |
4039 | typename _UniformRandomNumberGenerator> |
4040 | void |
4041 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
4042 | _UniformRandomNumberGenerator& __urng, |
4043 | const param_type& __p); |
4044 | |
4045 | param_type _M_param; |
4046 | }; |
4047 | |
4048 | /** |
4049 | * @brief Return true if two geometric distributions have |
4050 | * different parameters. |
4051 | */ |
4052 | template<typename _IntType> |
4053 | inline bool |
4054 | operator!=(const std::geometric_distribution<_IntType>& __d1, |
4055 | const std::geometric_distribution<_IntType>& __d2) |
4056 | { return !(__d1 == __d2); } |
4057 | |
4058 | /** |
4059 | * @brief Inserts a %geometric_distribution random number distribution |
4060 | * @p __x into the output stream @p __os. |
4061 | * |
4062 | * @param __os An output stream. |
4063 | * @param __x A %geometric_distribution random number distribution. |
4064 | * |
4065 | * @returns The output stream with the state of @p __x inserted or in |
4066 | * an error state. |
4067 | */ |
4068 | template<typename _IntType, |
4069 | typename _CharT, typename _Traits> |
4070 | std::basic_ostream<_CharT, _Traits>& |
4071 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
4072 | const std::geometric_distribution<_IntType>& __x); |
4073 | |
4074 | /** |
4075 | * @brief Extracts a %geometric_distribution random number distribution |
4076 | * @p __x from the input stream @p __is. |
4077 | * |
4078 | * @param __is An input stream. |
4079 | * @param __x A %geometric_distribution random number generator engine. |
4080 | * |
4081 | * @returns The input stream with @p __x extracted or in an error state. |
4082 | */ |
4083 | template<typename _IntType, |
4084 | typename _CharT, typename _Traits> |
4085 | std::basic_istream<_CharT, _Traits>& |
4086 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
4087 | std::geometric_distribution<_IntType>& __x); |
4088 | |
4089 | |
4090 | /** |
4091 | * @brief A negative_binomial_distribution random number distribution. |
4092 | * |
4093 | * The formula for the negative binomial probability mass function is |
4094 | * @f$p(i) = \binom{n}{i} p^i (1 - p)^{t - i}@f$ where @f$t@f$ |
4095 | * and @f$p@f$ are the parameters of the distribution. |
4096 | */ |
4097 | template<typename _IntType = int> |
4098 | class negative_binomial_distribution |
4099 | { |
4100 | static_assert(std::is_integral<_IntType>::value, |
4101 | "result_type must be an integral type" ); |
4102 | |
4103 | public: |
4104 | /** The type of the range of the distribution. */ |
4105 | typedef _IntType result_type; |
4106 | |
4107 | /** Parameter type. */ |
4108 | struct param_type |
4109 | { |
4110 | typedef negative_binomial_distribution<_IntType> distribution_type; |
4111 | |
4112 | explicit |
4113 | param_type(_IntType __k = 1, double __p = 0.5) |
4114 | : _M_k(__k), _M_p(__p) |
4115 | { |
4116 | __glibcxx_assert((_M_k > 0) && (_M_p > 0.0) && (_M_p <= 1.0)); |
4117 | } |
4118 | |
4119 | _IntType |
4120 | k() const |
4121 | { return _M_k; } |
4122 | |
4123 | double |
4124 | p() const |
4125 | { return _M_p; } |
4126 | |
4127 | friend bool |
4128 | operator==(const param_type& __p1, const param_type& __p2) |
4129 | { return __p1._M_k == __p2._M_k && __p1._M_p == __p2._M_p; } |
4130 | |
4131 | friend bool |
4132 | operator!=(const param_type& __p1, const param_type& __p2) |
4133 | { return !(__p1 == __p2); } |
4134 | |
4135 | private: |
4136 | _IntType _M_k; |
4137 | double _M_p; |
4138 | }; |
4139 | |
4140 | explicit |
4141 | negative_binomial_distribution(_IntType __k = 1, double __p = 0.5) |
4142 | : _M_param(__k, __p), _M_gd(__k, (1.0 - __p) / __p) |
4143 | { } |
4144 | |
4145 | explicit |
4146 | negative_binomial_distribution(const param_type& __p) |
4147 | : _M_param(__p), _M_gd(__p.k(), (1.0 - __p.p()) / __p.p()) |
4148 | { } |
4149 | |
4150 | /** |
4151 | * @brief Resets the distribution state. |
4152 | */ |
4153 | void |
4154 | reset() |
4155 | { _M_gd.reset(); } |
4156 | |
4157 | /** |
4158 | * @brief Return the @f$k@f$ parameter of the distribution. |
4159 | */ |
4160 | _IntType |
4161 | k() const |
4162 | { return _M_param.k(); } |
4163 | |
4164 | /** |
4165 | * @brief Return the @f$p@f$ parameter of the distribution. |
4166 | */ |
4167 | double |
4168 | p() const |
4169 | { return _M_param.p(); } |
4170 | |
4171 | /** |
4172 | * @brief Returns the parameter set of the distribution. |
4173 | */ |
4174 | param_type |
4175 | param() const |
4176 | { return _M_param; } |
4177 | |
4178 | /** |
4179 | * @brief Sets the parameter set of the distribution. |
4180 | * @param __param The new parameter set of the distribution. |
4181 | */ |
4182 | void |
4183 | param(const param_type& __param) |
4184 | { _M_param = __param; } |
4185 | |
4186 | /** |
4187 | * @brief Returns the greatest lower bound value of the distribution. |
4188 | */ |
4189 | result_type |
4190 | min() const |
4191 | { return result_type(0); } |
4192 | |
4193 | /** |
4194 | * @brief Returns the least upper bound value of the distribution. |
4195 | */ |
4196 | result_type |
4197 | max() const |
4198 | { return std::numeric_limits<result_type>::max(); } |
4199 | |
4200 | /** |
4201 | * @brief Generating functions. |
4202 | */ |
4203 | template<typename _UniformRandomNumberGenerator> |
4204 | result_type |
4205 | operator()(_UniformRandomNumberGenerator& __urng); |
4206 | |
4207 | template<typename _UniformRandomNumberGenerator> |
4208 | result_type |
4209 | operator()(_UniformRandomNumberGenerator& __urng, |
4210 | const param_type& __p); |
4211 | |
4212 | template<typename _ForwardIterator, |
4213 | typename _UniformRandomNumberGenerator> |
4214 | void |
4215 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
4216 | _UniformRandomNumberGenerator& __urng) |
4217 | { this->__generate_impl(__f, __t, __urng); } |
4218 | |
4219 | template<typename _ForwardIterator, |
4220 | typename _UniformRandomNumberGenerator> |
4221 | void |
4222 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
4223 | _UniformRandomNumberGenerator& __urng, |
4224 | const param_type& __p) |
4225 | { this->__generate_impl(__f, __t, __urng, __p); } |
4226 | |
4227 | template<typename _UniformRandomNumberGenerator> |
4228 | void |
4229 | __generate(result_type* __f, result_type* __t, |
4230 | _UniformRandomNumberGenerator& __urng) |
4231 | { this->__generate_impl(__f, __t, __urng); } |
4232 | |
4233 | template<typename _UniformRandomNumberGenerator> |
4234 | void |
4235 | __generate(result_type* __f, result_type* __t, |
4236 | _UniformRandomNumberGenerator& __urng, |
4237 | const param_type& __p) |
4238 | { this->__generate_impl(__f, __t, __urng, __p); } |
4239 | |
4240 | /** |
4241 | * @brief Return true if two negative binomial distributions have |
4242 | * the same parameters and the sequences that would be |
4243 | * generated are equal. |
4244 | */ |
4245 | friend bool |
4246 | operator==(const negative_binomial_distribution& __d1, |
4247 | const negative_binomial_distribution& __d2) |
4248 | { return __d1._M_param == __d2._M_param && __d1._M_gd == __d2._M_gd; } |
4249 | |
4250 | /** |
4251 | * @brief Inserts a %negative_binomial_distribution random |
4252 | * number distribution @p __x into the output stream @p __os. |
4253 | * |
4254 | * @param __os An output stream. |
4255 | * @param __x A %negative_binomial_distribution random number |
4256 | * distribution. |
4257 | * |
4258 | * @returns The output stream with the state of @p __x inserted or in |
4259 | * an error state. |
4260 | */ |
4261 | template<typename _IntType1, typename _CharT, typename _Traits> |
4262 | friend std::basic_ostream<_CharT, _Traits>& |
4263 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
4264 | const std::negative_binomial_distribution<_IntType1>& __x); |
4265 | |
4266 | /** |
4267 | * @brief Extracts a %negative_binomial_distribution random number |
4268 | * distribution @p __x from the input stream @p __is. |
4269 | * |
4270 | * @param __is An input stream. |
4271 | * @param __x A %negative_binomial_distribution random number |
4272 | * generator engine. |
4273 | * |
4274 | * @returns The input stream with @p __x extracted or in an error state. |
4275 | */ |
4276 | template<typename _IntType1, typename _CharT, typename _Traits> |
4277 | friend std::basic_istream<_CharT, _Traits>& |
4278 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
4279 | std::negative_binomial_distribution<_IntType1>& __x); |
4280 | |
4281 | private: |
4282 | template<typename _ForwardIterator, |
4283 | typename _UniformRandomNumberGenerator> |
4284 | void |
4285 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
4286 | _UniformRandomNumberGenerator& __urng); |
4287 | template<typename _ForwardIterator, |
4288 | typename _UniformRandomNumberGenerator> |
4289 | void |
4290 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
4291 | _UniformRandomNumberGenerator& __urng, |
4292 | const param_type& __p); |
4293 | |
4294 | param_type _M_param; |
4295 | |
4296 | std::gamma_distribution<double> _M_gd; |
4297 | }; |
4298 | |
4299 | /** |
4300 | * @brief Return true if two negative binomial distributions are different. |
4301 | */ |
4302 | template<typename _IntType> |
4303 | inline bool |
4304 | operator!=(const std::negative_binomial_distribution<_IntType>& __d1, |
4305 | const std::negative_binomial_distribution<_IntType>& __d2) |
4306 | { return !(__d1 == __d2); } |
4307 | |
4308 | |
4309 | /* @} */ // group random_distributions_bernoulli |
4310 | |
4311 | /** |
4312 | * @addtogroup random_distributions_poisson Poisson Distributions |
4313 | * @ingroup random_distributions |
4314 | * @{ |
4315 | */ |
4316 | |
4317 | /** |
4318 | * @brief A discrete Poisson random number distribution. |
4319 | * |
4320 | * The formula for the Poisson probability density function is |
4321 | * @f$p(i|\mu) = \frac{\mu^i}{i!} e^{-\mu}@f$ where @f$\mu@f$ is the |
4322 | * parameter of the distribution. |
4323 | */ |
4324 | template<typename _IntType = int> |
4325 | class poisson_distribution |
4326 | { |
4327 | static_assert(std::is_integral<_IntType>::value, |
4328 | "result_type must be an integral type" ); |
4329 | |
4330 | public: |
4331 | /** The type of the range of the distribution. */ |
4332 | typedef _IntType result_type; |
4333 | |
4334 | /** Parameter type. */ |
4335 | struct param_type |
4336 | { |
4337 | typedef poisson_distribution<_IntType> distribution_type; |
4338 | friend class poisson_distribution<_IntType>; |
4339 | |
4340 | explicit |
4341 | param_type(double __mean = 1.0) |
4342 | : _M_mean(__mean) |
4343 | { |
4344 | __glibcxx_assert(_M_mean > 0.0); |
4345 | _M_initialize(); |
4346 | } |
4347 | |
4348 | double |
4349 | mean() const |
4350 | { return _M_mean; } |
4351 | |
4352 | friend bool |
4353 | operator==(const param_type& __p1, const param_type& __p2) |
4354 | { return __p1._M_mean == __p2._M_mean; } |
4355 | |
4356 | friend bool |
4357 | operator!=(const param_type& __p1, const param_type& __p2) |
4358 | { return !(__p1 == __p2); } |
4359 | |
4360 | private: |
4361 | // Hosts either log(mean) or the threshold of the simple method. |
4362 | void |
4363 | _M_initialize(); |
4364 | |
4365 | double _M_mean; |
4366 | |
4367 | double _M_lm_thr; |
4368 | #if _GLIBCXX_USE_C99_MATH_TR1 |
4369 | double _M_lfm, _M_sm, _M_d, _M_scx, _M_1cx, _M_c2b, _M_cb; |
4370 | #endif |
4371 | }; |
4372 | |
4373 | // constructors and member function |
4374 | explicit |
4375 | poisson_distribution(double __mean = 1.0) |
4376 | : _M_param(__mean), _M_nd() |
4377 | { } |
4378 | |
4379 | explicit |
4380 | poisson_distribution(const param_type& __p) |
4381 | : _M_param(__p), _M_nd() |
4382 | { } |
4383 | |
4384 | /** |
4385 | * @brief Resets the distribution state. |
4386 | */ |
4387 | void |
4388 | reset() |
4389 | { _M_nd.reset(); } |
4390 | |
4391 | /** |
4392 | * @brief Returns the distribution parameter @p mean. |
4393 | */ |
4394 | double |
4395 | mean() const |
4396 | { return _M_param.mean(); } |
4397 | |
4398 | /** |
4399 | * @brief Returns the parameter set of the distribution. |
4400 | */ |
4401 | param_type |
4402 | param() const |
4403 | { return _M_param; } |
4404 | |
4405 | /** |
4406 | * @brief Sets the parameter set of the distribution. |
4407 | * @param __param The new parameter set of the distribution. |
4408 | */ |
4409 | void |
4410 | param(const param_type& __param) |
4411 | { _M_param = __param; } |
4412 | |
4413 | /** |
4414 | * @brief Returns the greatest lower bound value of the distribution. |
4415 | */ |
4416 | result_type |
4417 | min() const |
4418 | { return 0; } |
4419 | |
4420 | /** |
4421 | * @brief Returns the least upper bound value of the distribution. |
4422 | */ |
4423 | result_type |
4424 | max() const |
4425 | { return std::numeric_limits<result_type>::max(); } |
4426 | |
4427 | /** |
4428 | * @brief Generating functions. |
4429 | */ |
4430 | template<typename _UniformRandomNumberGenerator> |
4431 | result_type |
4432 | operator()(_UniformRandomNumberGenerator& __urng) |
4433 | { return this->operator()(__urng, _M_param); } |
4434 | |
4435 | template<typename _UniformRandomNumberGenerator> |
4436 | result_type |
4437 | operator()(_UniformRandomNumberGenerator& __urng, |
4438 | const param_type& __p); |
4439 | |
4440 | template<typename _ForwardIterator, |
4441 | typename _UniformRandomNumberGenerator> |
4442 | void |
4443 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
4444 | _UniformRandomNumberGenerator& __urng) |
4445 | { this->__generate(__f, __t, __urng, _M_param); } |
4446 | |
4447 | template<typename _ForwardIterator, |
4448 | typename _UniformRandomNumberGenerator> |
4449 | void |
4450 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
4451 | _UniformRandomNumberGenerator& __urng, |
4452 | const param_type& __p) |
4453 | { this->__generate_impl(__f, __t, __urng, __p); } |
4454 | |
4455 | template<typename _UniformRandomNumberGenerator> |
4456 | void |
4457 | __generate(result_type* __f, result_type* __t, |
4458 | _UniformRandomNumberGenerator& __urng, |
4459 | const param_type& __p) |
4460 | { this->__generate_impl(__f, __t, __urng, __p); } |
4461 | |
4462 | /** |
4463 | * @brief Return true if two Poisson distributions have the same |
4464 | * parameters and the sequences that would be generated |
4465 | * are equal. |
4466 | */ |
4467 | friend bool |
4468 | operator==(const poisson_distribution& __d1, |
4469 | const poisson_distribution& __d2) |
4470 | #ifdef _GLIBCXX_USE_C99_MATH_TR1 |
4471 | { return __d1._M_param == __d2._M_param && __d1._M_nd == __d2._M_nd; } |
4472 | #else |
4473 | { return __d1._M_param == __d2._M_param; } |
4474 | #endif |
4475 | |
4476 | /** |
4477 | * @brief Inserts a %poisson_distribution random number distribution |
4478 | * @p __x into the output stream @p __os. |
4479 | * |
4480 | * @param __os An output stream. |
4481 | * @param __x A %poisson_distribution random number distribution. |
4482 | * |
4483 | * @returns The output stream with the state of @p __x inserted or in |
4484 | * an error state. |
4485 | */ |
4486 | template<typename _IntType1, typename _CharT, typename _Traits> |
4487 | friend std::basic_ostream<_CharT, _Traits>& |
4488 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
4489 | const std::poisson_distribution<_IntType1>& __x); |
4490 | |
4491 | /** |
4492 | * @brief Extracts a %poisson_distribution random number distribution |
4493 | * @p __x from the input stream @p __is. |
4494 | * |
4495 | * @param __is An input stream. |
4496 | * @param __x A %poisson_distribution random number generator engine. |
4497 | * |
4498 | * @returns The input stream with @p __x extracted or in an error |
4499 | * state. |
4500 | */ |
4501 | template<typename _IntType1, typename _CharT, typename _Traits> |
4502 | friend std::basic_istream<_CharT, _Traits>& |
4503 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
4504 | std::poisson_distribution<_IntType1>& __x); |
4505 | |
4506 | private: |
4507 | template<typename _ForwardIterator, |
4508 | typename _UniformRandomNumberGenerator> |
4509 | void |
4510 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
4511 | _UniformRandomNumberGenerator& __urng, |
4512 | const param_type& __p); |
4513 | |
4514 | param_type _M_param; |
4515 | |
4516 | // NB: Unused when _GLIBCXX_USE_C99_MATH_TR1 is undefined. |
4517 | std::normal_distribution<double> _M_nd; |
4518 | }; |
4519 | |
4520 | /** |
4521 | * @brief Return true if two Poisson distributions are different. |
4522 | */ |
4523 | template<typename _IntType> |
4524 | inline bool |
4525 | operator!=(const std::poisson_distribution<_IntType>& __d1, |
4526 | const std::poisson_distribution<_IntType>& __d2) |
4527 | { return !(__d1 == __d2); } |
4528 | |
4529 | |
4530 | /** |
4531 | * @brief An exponential continuous distribution for random numbers. |
4532 | * |
4533 | * The formula for the exponential probability density function is |
4534 | * @f$p(x|\lambda) = \lambda e^{-\lambda x}@f$. |
4535 | * |
4536 | * <table border=1 cellpadding=10 cellspacing=0> |
4537 | * <caption align=top>Distribution Statistics</caption> |
4538 | * <tr><td>Mean</td><td>@f$\frac{1}{\lambda}@f$</td></tr> |
4539 | * <tr><td>Median</td><td>@f$\frac{\ln 2}{\lambda}@f$</td></tr> |
4540 | * <tr><td>Mode</td><td>@f$zero@f$</td></tr> |
4541 | * <tr><td>Range</td><td>@f$[0, \infty]@f$</td></tr> |
4542 | * <tr><td>Standard Deviation</td><td>@f$\frac{1}{\lambda}@f$</td></tr> |
4543 | * </table> |
4544 | */ |
4545 | template<typename _RealType = double> |
4546 | class exponential_distribution |
4547 | { |
4548 | static_assert(std::is_floating_point<_RealType>::value, |
4549 | "result_type must be a floating point type" ); |
4550 | |
4551 | public: |
4552 | /** The type of the range of the distribution. */ |
4553 | typedef _RealType result_type; |
4554 | |
4555 | /** Parameter type. */ |
4556 | struct param_type |
4557 | { |
4558 | typedef exponential_distribution<_RealType> distribution_type; |
4559 | |
4560 | explicit |
4561 | param_type(_RealType __lambda = _RealType(1)) |
4562 | : _M_lambda(__lambda) |
4563 | { |
4564 | __glibcxx_assert(_M_lambda > _RealType(0)); |
4565 | } |
4566 | |
4567 | _RealType |
4568 | lambda() const |
4569 | { return _M_lambda; } |
4570 | |
4571 | friend bool |
4572 | operator==(const param_type& __p1, const param_type& __p2) |
4573 | { return __p1._M_lambda == __p2._M_lambda; } |
4574 | |
4575 | friend bool |
4576 | operator!=(const param_type& __p1, const param_type& __p2) |
4577 | { return !(__p1 == __p2); } |
4578 | |
4579 | private: |
4580 | _RealType _M_lambda; |
4581 | }; |
4582 | |
4583 | public: |
4584 | /** |
4585 | * @brief Constructs an exponential distribution with inverse scale |
4586 | * parameter @f$\lambda@f$. |
4587 | */ |
4588 | explicit |
4589 | exponential_distribution(const result_type& __lambda = result_type(1)) |
4590 | : _M_param(__lambda) |
4591 | { } |
4592 | |
4593 | explicit |
4594 | exponential_distribution(const param_type& __p) |
4595 | : _M_param(__p) |
4596 | { } |
4597 | |
4598 | /** |
4599 | * @brief Resets the distribution state. |
4600 | * |
4601 | * Has no effect on exponential distributions. |
4602 | */ |
4603 | void |
4604 | reset() { } |
4605 | |
4606 | /** |
4607 | * @brief Returns the inverse scale parameter of the distribution. |
4608 | */ |
4609 | _RealType |
4610 | lambda() const |
4611 | { return _M_param.lambda(); } |
4612 | |
4613 | /** |
4614 | * @brief Returns the parameter set of the distribution. |
4615 | */ |
4616 | param_type |
4617 | param() const |
4618 | { return _M_param; } |
4619 | |
4620 | /** |
4621 | * @brief Sets the parameter set of the distribution. |
4622 | * @param __param The new parameter set of the distribution. |
4623 | */ |
4624 | void |
4625 | param(const param_type& __param) |
4626 | { _M_param = __param; } |
4627 | |
4628 | /** |
4629 | * @brief Returns the greatest lower bound value of the distribution. |
4630 | */ |
4631 | result_type |
4632 | min() const |
4633 | { return result_type(0); } |
4634 | |
4635 | /** |
4636 | * @brief Returns the least upper bound value of the distribution. |
4637 | */ |
4638 | result_type |
4639 | max() const |
4640 | { return std::numeric_limits<result_type>::max(); } |
4641 | |
4642 | /** |
4643 | * @brief Generating functions. |
4644 | */ |
4645 | template<typename _UniformRandomNumberGenerator> |
4646 | result_type |
4647 | operator()(_UniformRandomNumberGenerator& __urng) |
4648 | { return this->operator()(__urng, _M_param); } |
4649 | |
4650 | template<typename _UniformRandomNumberGenerator> |
4651 | result_type |
4652 | operator()(_UniformRandomNumberGenerator& __urng, |
4653 | const param_type& __p) |
4654 | { |
4655 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> |
4656 | __aurng(__urng); |
4657 | return -std::log(result_type(1) - __aurng()) / __p.lambda(); |
4658 | } |
4659 | |
4660 | template<typename _ForwardIterator, |
4661 | typename _UniformRandomNumberGenerator> |
4662 | void |
4663 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
4664 | _UniformRandomNumberGenerator& __urng) |
4665 | { this->__generate(__f, __t, __urng, _M_param); } |
4666 | |
4667 | template<typename _ForwardIterator, |
4668 | typename _UniformRandomNumberGenerator> |
4669 | void |
4670 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
4671 | _UniformRandomNumberGenerator& __urng, |
4672 | const param_type& __p) |
4673 | { this->__generate_impl(__f, __t, __urng, __p); } |
4674 | |
4675 | template<typename _UniformRandomNumberGenerator> |
4676 | void |
4677 | __generate(result_type* __f, result_type* __t, |
4678 | _UniformRandomNumberGenerator& __urng, |
4679 | const param_type& __p) |
4680 | { this->__generate_impl(__f, __t, __urng, __p); } |
4681 | |
4682 | /** |
4683 | * @brief Return true if two exponential distributions have the same |
4684 | * parameters. |
4685 | */ |
4686 | friend bool |
4687 | operator==(const exponential_distribution& __d1, |
4688 | const exponential_distribution& __d2) |
4689 | { return __d1._M_param == __d2._M_param; } |
4690 | |
4691 | private: |
4692 | template<typename _ForwardIterator, |
4693 | typename _UniformRandomNumberGenerator> |
4694 | void |
4695 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
4696 | _UniformRandomNumberGenerator& __urng, |
4697 | const param_type& __p); |
4698 | |
4699 | param_type _M_param; |
4700 | }; |
4701 | |
4702 | /** |
4703 | * @brief Return true if two exponential distributions have different |
4704 | * parameters. |
4705 | */ |
4706 | template<typename _RealType> |
4707 | inline bool |
4708 | operator!=(const std::exponential_distribution<_RealType>& __d1, |
4709 | const std::exponential_distribution<_RealType>& __d2) |
4710 | { return !(__d1 == __d2); } |
4711 | |
4712 | /** |
4713 | * @brief Inserts a %exponential_distribution random number distribution |
4714 | * @p __x into the output stream @p __os. |
4715 | * |
4716 | * @param __os An output stream. |
4717 | * @param __x A %exponential_distribution random number distribution. |
4718 | * |
4719 | * @returns The output stream with the state of @p __x inserted or in |
4720 | * an error state. |
4721 | */ |
4722 | template<typename _RealType, typename _CharT, typename _Traits> |
4723 | std::basic_ostream<_CharT, _Traits>& |
4724 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
4725 | const std::exponential_distribution<_RealType>& __x); |
4726 | |
4727 | /** |
4728 | * @brief Extracts a %exponential_distribution random number distribution |
4729 | * @p __x from the input stream @p __is. |
4730 | * |
4731 | * @param __is An input stream. |
4732 | * @param __x A %exponential_distribution random number |
4733 | * generator engine. |
4734 | * |
4735 | * @returns The input stream with @p __x extracted or in an error state. |
4736 | */ |
4737 | template<typename _RealType, typename _CharT, typename _Traits> |
4738 | std::basic_istream<_CharT, _Traits>& |
4739 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
4740 | std::exponential_distribution<_RealType>& __x); |
4741 | |
4742 | |
4743 | /** |
4744 | * @brief A weibull_distribution random number distribution. |
4745 | * |
4746 | * The formula for the normal probability density function is: |
4747 | * @f[ |
4748 | * p(x|\alpha,\beta) = \frac{\alpha}{\beta} (\frac{x}{\beta})^{\alpha-1} |
4749 | * \exp{(-(\frac{x}{\beta})^\alpha)} |
4750 | * @f] |
4751 | */ |
4752 | template<typename _RealType = double> |
4753 | class weibull_distribution |
4754 | { |
4755 | static_assert(std::is_floating_point<_RealType>::value, |
4756 | "result_type must be a floating point type" ); |
4757 | |
4758 | public: |
4759 | /** The type of the range of the distribution. */ |
4760 | typedef _RealType result_type; |
4761 | |
4762 | /** Parameter type. */ |
4763 | struct param_type |
4764 | { |
4765 | typedef weibull_distribution<_RealType> distribution_type; |
4766 | |
4767 | explicit |
4768 | param_type(_RealType __a = _RealType(1), |
4769 | _RealType __b = _RealType(1)) |
4770 | : _M_a(__a), _M_b(__b) |
4771 | { } |
4772 | |
4773 | _RealType |
4774 | a() const |
4775 | { return _M_a; } |
4776 | |
4777 | _RealType |
4778 | b() const |
4779 | { return _M_b; } |
4780 | |
4781 | friend bool |
4782 | operator==(const param_type& __p1, const param_type& __p2) |
4783 | { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; } |
4784 | |
4785 | friend bool |
4786 | operator!=(const param_type& __p1, const param_type& __p2) |
4787 | { return !(__p1 == __p2); } |
4788 | |
4789 | private: |
4790 | _RealType _M_a; |
4791 | _RealType _M_b; |
4792 | }; |
4793 | |
4794 | explicit |
4795 | weibull_distribution(_RealType __a = _RealType(1), |
4796 | _RealType __b = _RealType(1)) |
4797 | : _M_param(__a, __b) |
4798 | { } |
4799 | |
4800 | explicit |
4801 | weibull_distribution(const param_type& __p) |
4802 | : _M_param(__p) |
4803 | { } |
4804 | |
4805 | /** |
4806 | * @brief Resets the distribution state. |
4807 | */ |
4808 | void |
4809 | reset() |
4810 | { } |
4811 | |
4812 | /** |
4813 | * @brief Return the @f$a@f$ parameter of the distribution. |
4814 | */ |
4815 | _RealType |
4816 | a() const |
4817 | { return _M_param.a(); } |
4818 | |
4819 | /** |
4820 | * @brief Return the @f$b@f$ parameter of the distribution. |
4821 | */ |
4822 | _RealType |
4823 | b() const |
4824 | { return _M_param.b(); } |
4825 | |
4826 | /** |
4827 | * @brief Returns the parameter set of the distribution. |
4828 | */ |
4829 | param_type |
4830 | param() const |
4831 | { return _M_param; } |
4832 | |
4833 | /** |
4834 | * @brief Sets the parameter set of the distribution. |
4835 | * @param __param The new parameter set of the distribution. |
4836 | */ |
4837 | void |
4838 | param(const param_type& __param) |
4839 | { _M_param = __param; } |
4840 | |
4841 | /** |
4842 | * @brief Returns the greatest lower bound value of the distribution. |
4843 | */ |
4844 | result_type |
4845 | min() const |
4846 | { return result_type(0); } |
4847 | |
4848 | /** |
4849 | * @brief Returns the least upper bound value of the distribution. |
4850 | */ |
4851 | result_type |
4852 | max() const |
4853 | { return std::numeric_limits<result_type>::max(); } |
4854 | |
4855 | /** |
4856 | * @brief Generating functions. |
4857 | */ |
4858 | template<typename _UniformRandomNumberGenerator> |
4859 | result_type |
4860 | operator()(_UniformRandomNumberGenerator& __urng) |
4861 | { return this->operator()(__urng, _M_param); } |
4862 | |
4863 | template<typename _UniformRandomNumberGenerator> |
4864 | result_type |
4865 | operator()(_UniformRandomNumberGenerator& __urng, |
4866 | const param_type& __p); |
4867 | |
4868 | template<typename _ForwardIterator, |
4869 | typename _UniformRandomNumberGenerator> |
4870 | void |
4871 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
4872 | _UniformRandomNumberGenerator& __urng) |
4873 | { this->__generate(__f, __t, __urng, _M_param); } |
4874 | |
4875 | template<typename _ForwardIterator, |
4876 | typename _UniformRandomNumberGenerator> |
4877 | void |
4878 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
4879 | _UniformRandomNumberGenerator& __urng, |
4880 | const param_type& __p) |
4881 | { this->__generate_impl(__f, __t, __urng, __p); } |
4882 | |
4883 | template<typename _UniformRandomNumberGenerator> |
4884 | void |
4885 | __generate(result_type* __f, result_type* __t, |
4886 | _UniformRandomNumberGenerator& __urng, |
4887 | const param_type& __p) |
4888 | { this->__generate_impl(__f, __t, __urng, __p); } |
4889 | |
4890 | /** |
4891 | * @brief Return true if two Weibull distributions have the same |
4892 | * parameters. |
4893 | */ |
4894 | friend bool |
4895 | operator==(const weibull_distribution& __d1, |
4896 | const weibull_distribution& __d2) |
4897 | { return __d1._M_param == __d2._M_param; } |
4898 | |
4899 | private: |
4900 | template<typename _ForwardIterator, |
4901 | typename _UniformRandomNumberGenerator> |
4902 | void |
4903 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
4904 | _UniformRandomNumberGenerator& __urng, |
4905 | const param_type& __p); |
4906 | |
4907 | param_type _M_param; |
4908 | }; |
4909 | |
4910 | /** |
4911 | * @brief Return true if two Weibull distributions have different |
4912 | * parameters. |
4913 | */ |
4914 | template<typename _RealType> |
4915 | inline bool |
4916 | operator!=(const std::weibull_distribution<_RealType>& __d1, |
4917 | const std::weibull_distribution<_RealType>& __d2) |
4918 | { return !(__d1 == __d2); } |
4919 | |
4920 | /** |
4921 | * @brief Inserts a %weibull_distribution random number distribution |
4922 | * @p __x into the output stream @p __os. |
4923 | * |
4924 | * @param __os An output stream. |
4925 | * @param __x A %weibull_distribution random number distribution. |
4926 | * |
4927 | * @returns The output stream with the state of @p __x inserted or in |
4928 | * an error state. |
4929 | */ |
4930 | template<typename _RealType, typename _CharT, typename _Traits> |
4931 | std::basic_ostream<_CharT, _Traits>& |
4932 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
4933 | const std::weibull_distribution<_RealType>& __x); |
4934 | |
4935 | /** |
4936 | * @brief Extracts a %weibull_distribution random number distribution |
4937 | * @p __x from the input stream @p __is. |
4938 | * |
4939 | * @param __is An input stream. |
4940 | * @param __x A %weibull_distribution random number |
4941 | * generator engine. |
4942 | * |
4943 | * @returns The input stream with @p __x extracted or in an error state. |
4944 | */ |
4945 | template<typename _RealType, typename _CharT, typename _Traits> |
4946 | std::basic_istream<_CharT, _Traits>& |
4947 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
4948 | std::weibull_distribution<_RealType>& __x); |
4949 | |
4950 | |
4951 | /** |
4952 | * @brief A extreme_value_distribution random number distribution. |
4953 | * |
4954 | * The formula for the normal probability mass function is |
4955 | * @f[ |
4956 | * p(x|a,b) = \frac{1}{b} |
4957 | * \exp( \frac{a-x}{b} - \exp(\frac{a-x}{b})) |
4958 | * @f] |
4959 | */ |
4960 | template<typename _RealType = double> |
4961 | class extreme_value_distribution |
4962 | { |
4963 | static_assert(std::is_floating_point<_RealType>::value, |
4964 | "result_type must be a floating point type" ); |
4965 | |
4966 | public: |
4967 | /** The type of the range of the distribution. */ |
4968 | typedef _RealType result_type; |
4969 | |
4970 | /** Parameter type. */ |
4971 | struct param_type |
4972 | { |
4973 | typedef extreme_value_distribution<_RealType> distribution_type; |
4974 | |
4975 | explicit |
4976 | param_type(_RealType __a = _RealType(0), |
4977 | _RealType __b = _RealType(1)) |
4978 | : _M_a(__a), _M_b(__b) |
4979 | { } |
4980 | |
4981 | _RealType |
4982 | a() const |
4983 | { return _M_a; } |
4984 | |
4985 | _RealType |
4986 | b() const |
4987 | { return _M_b; } |
4988 | |
4989 | friend bool |
4990 | operator==(const param_type& __p1, const param_type& __p2) |
4991 | { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; } |
4992 | |
4993 | friend bool |
4994 | operator!=(const param_type& __p1, const param_type& __p2) |
4995 | { return !(__p1 == __p2); } |
4996 | |
4997 | private: |
4998 | _RealType _M_a; |
4999 | _RealType _M_b; |
5000 | }; |
5001 | |
5002 | explicit |
5003 | extreme_value_distribution(_RealType __a = _RealType(0), |
5004 | _RealType __b = _RealType(1)) |
5005 | : _M_param(__a, __b) |
5006 | { } |
5007 | |
5008 | explicit |
5009 | extreme_value_distribution(const param_type& __p) |
5010 | : _M_param(__p) |
5011 | { } |
5012 | |
5013 | /** |
5014 | * @brief Resets the distribution state. |
5015 | */ |
5016 | void |
5017 | reset() |
5018 | { } |
5019 | |
5020 | /** |
5021 | * @brief Return the @f$a@f$ parameter of the distribution. |
5022 | */ |
5023 | _RealType |
5024 | a() const |
5025 | { return _M_param.a(); } |
5026 | |
5027 | /** |
5028 | * @brief Return the @f$b@f$ parameter of the distribution. |
5029 | */ |
5030 | _RealType |
5031 | b() const |
5032 | { return _M_param.b(); } |
5033 | |
5034 | /** |
5035 | * @brief Returns the parameter set of the distribution. |
5036 | */ |
5037 | param_type |
5038 | param() const |
5039 | { return _M_param; } |
5040 | |
5041 | /** |
5042 | * @brief Sets the parameter set of the distribution. |
5043 | * @param __param The new parameter set of the distribution. |
5044 | */ |
5045 | void |
5046 | param(const param_type& __param) |
5047 | { _M_param = __param; } |
5048 | |
5049 | /** |
5050 | * @brief Returns the greatest lower bound value of the distribution. |
5051 | */ |
5052 | result_type |
5053 | min() const |
5054 | { return std::numeric_limits<result_type>::lowest(); } |
5055 | |
5056 | /** |
5057 | * @brief Returns the least upper bound value of the distribution. |
5058 | */ |
5059 | result_type |
5060 | max() const |
5061 | { return std::numeric_limits<result_type>::max(); } |
5062 | |
5063 | /** |
5064 | * @brief Generating functions. |
5065 | */ |
5066 | template<typename _UniformRandomNumberGenerator> |
5067 | result_type |
5068 | operator()(_UniformRandomNumberGenerator& __urng) |
5069 | { return this->operator()(__urng, _M_param); } |
5070 | |
5071 | template<typename _UniformRandomNumberGenerator> |
5072 | result_type |
5073 | operator()(_UniformRandomNumberGenerator& __urng, |
5074 | const param_type& __p); |
5075 | |
5076 | template<typename _ForwardIterator, |
5077 | typename _UniformRandomNumberGenerator> |
5078 | void |
5079 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
5080 | _UniformRandomNumberGenerator& __urng) |
5081 | { this->__generate(__f, __t, __urng, _M_param); } |
5082 | |
5083 | template<typename _ForwardIterator, |
5084 | typename _UniformRandomNumberGenerator> |
5085 | void |
5086 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
5087 | _UniformRandomNumberGenerator& __urng, |
5088 | const param_type& __p) |
5089 | { this->__generate_impl(__f, __t, __urng, __p); } |
5090 | |
5091 | template<typename _UniformRandomNumberGenerator> |
5092 | void |
5093 | __generate(result_type* __f, result_type* __t, |
5094 | _UniformRandomNumberGenerator& __urng, |
5095 | const param_type& __p) |
5096 | { this->__generate_impl(__f, __t, __urng, __p); } |
5097 | |
5098 | /** |
5099 | * @brief Return true if two extreme value distributions have the same |
5100 | * parameters. |
5101 | */ |
5102 | friend bool |
5103 | operator==(const extreme_value_distribution& __d1, |
5104 | const extreme_value_distribution& __d2) |
5105 | { return __d1._M_param == __d2._M_param; } |
5106 | |
5107 | private: |
5108 | template<typename _ForwardIterator, |
5109 | typename _UniformRandomNumberGenerator> |
5110 | void |
5111 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
5112 | _UniformRandomNumberGenerator& __urng, |
5113 | const param_type& __p); |
5114 | |
5115 | param_type _M_param; |
5116 | }; |
5117 | |
5118 | /** |
5119 | * @brief Return true if two extreme value distributions have different |
5120 | * parameters. |
5121 | */ |
5122 | template<typename _RealType> |
5123 | inline bool |
5124 | operator!=(const std::extreme_value_distribution<_RealType>& __d1, |
5125 | const std::extreme_value_distribution<_RealType>& __d2) |
5126 | { return !(__d1 == __d2); } |
5127 | |
5128 | /** |
5129 | * @brief Inserts a %extreme_value_distribution random number distribution |
5130 | * @p __x into the output stream @p __os. |
5131 | * |
5132 | * @param __os An output stream. |
5133 | * @param __x A %extreme_value_distribution random number distribution. |
5134 | * |
5135 | * @returns The output stream with the state of @p __x inserted or in |
5136 | * an error state. |
5137 | */ |
5138 | template<typename _RealType, typename _CharT, typename _Traits> |
5139 | std::basic_ostream<_CharT, _Traits>& |
5140 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
5141 | const std::extreme_value_distribution<_RealType>& __x); |
5142 | |
5143 | /** |
5144 | * @brief Extracts a %extreme_value_distribution random number |
5145 | * distribution @p __x from the input stream @p __is. |
5146 | * |
5147 | * @param __is An input stream. |
5148 | * @param __x A %extreme_value_distribution random number |
5149 | * generator engine. |
5150 | * |
5151 | * @returns The input stream with @p __x extracted or in an error state. |
5152 | */ |
5153 | template<typename _RealType, typename _CharT, typename _Traits> |
5154 | std::basic_istream<_CharT, _Traits>& |
5155 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
5156 | std::extreme_value_distribution<_RealType>& __x); |
5157 | |
5158 | |
5159 | /** |
5160 | * @brief A discrete_distribution random number distribution. |
5161 | * |
5162 | * The formula for the discrete probability mass function is |
5163 | * |
5164 | */ |
5165 | template<typename _IntType = int> |
5166 | class discrete_distribution |
5167 | { |
5168 | static_assert(std::is_integral<_IntType>::value, |
5169 | "result_type must be an integral type" ); |
5170 | |
5171 | public: |
5172 | /** The type of the range of the distribution. */ |
5173 | typedef _IntType result_type; |
5174 | |
5175 | /** Parameter type. */ |
5176 | struct param_type |
5177 | { |
5178 | typedef discrete_distribution<_IntType> distribution_type; |
5179 | friend class discrete_distribution<_IntType>; |
5180 | |
5181 | param_type() |
5182 | : _M_prob(), _M_cp() |
5183 | { } |
5184 | |
5185 | template<typename _InputIterator> |
5186 | param_type(_InputIterator __wbegin, |
5187 | _InputIterator __wend) |
5188 | : _M_prob(__wbegin, __wend), _M_cp() |
5189 | { _M_initialize(); } |
5190 | |
5191 | param_type(initializer_list<double> __wil) |
5192 | : _M_prob(__wil.begin(), __wil.end()), _M_cp() |
5193 | { _M_initialize(); } |
5194 | |
5195 | template<typename _Func> |
5196 | param_type(size_t __nw, double __xmin, double __xmax, |
5197 | _Func __fw); |
5198 | |
5199 | // See: http://cpp-next.com/archive/2010/10/implicit-move-must-go/ |
5200 | param_type(const param_type&) = default; |
5201 | param_type& operator=(const param_type&) = default; |
5202 | |
5203 | std::vector<double> |
5204 | probabilities() const |
5205 | { return _M_prob.empty() ? std::vector<double>(1, 1.0) : _M_prob; } |
5206 | |
5207 | friend bool |
5208 | operator==(const param_type& __p1, const param_type& __p2) |
5209 | { return __p1._M_prob == __p2._M_prob; } |
5210 | |
5211 | friend bool |
5212 | operator!=(const param_type& __p1, const param_type& __p2) |
5213 | { return !(__p1 == __p2); } |
5214 | |
5215 | private: |
5216 | void |
5217 | _M_initialize(); |
5218 | |
5219 | std::vector<double> _M_prob; |
5220 | std::vector<double> _M_cp; |
5221 | }; |
5222 | |
5223 | discrete_distribution() |
5224 | : _M_param() |
5225 | { } |
5226 | |
5227 | template<typename _InputIterator> |
5228 | discrete_distribution(_InputIterator __wbegin, |
5229 | _InputIterator __wend) |
5230 | : _M_param(__wbegin, __wend) |
5231 | { } |
5232 | |
5233 | discrete_distribution(initializer_list<double> __wl) |
5234 | : _M_param(__wl) |
5235 | { } |
5236 | |
5237 | template<typename _Func> |
5238 | discrete_distribution(size_t __nw, double __xmin, double __xmax, |
5239 | _Func __fw) |
5240 | : _M_param(__nw, __xmin, __xmax, __fw) |
5241 | { } |
5242 | |
5243 | explicit |
5244 | discrete_distribution(const param_type& __p) |
5245 | : _M_param(__p) |
5246 | { } |
5247 | |
5248 | /** |
5249 | * @brief Resets the distribution state. |
5250 | */ |
5251 | void |
5252 | reset() |
5253 | { } |
5254 | |
5255 | /** |
5256 | * @brief Returns the probabilities of the distribution. |
5257 | */ |
5258 | std::vector<double> |
5259 | probabilities() const |
5260 | { |
5261 | return _M_param._M_prob.empty() |
5262 | ? std::vector<double>(1, 1.0) : _M_param._M_prob; |
5263 | } |
5264 | |
5265 | /** |
5266 | * @brief Returns the parameter set of the distribution. |
5267 | */ |
5268 | param_type |
5269 | param() const |
5270 | { return _M_param; } |
5271 | |
5272 | /** |
5273 | * @brief Sets the parameter set of the distribution. |
5274 | * @param __param The new parameter set of the distribution. |
5275 | */ |
5276 | void |
5277 | param(const param_type& __param) |
5278 | { _M_param = __param; } |
5279 | |
5280 | /** |
5281 | * @brief Returns the greatest lower bound value of the distribution. |
5282 | */ |
5283 | result_type |
5284 | min() const |
5285 | { return result_type(0); } |
5286 | |
5287 | /** |
5288 | * @brief Returns the least upper bound value of the distribution. |
5289 | */ |
5290 | result_type |
5291 | max() const |
5292 | { |
5293 | return _M_param._M_prob.empty() |
5294 | ? result_type(0) : result_type(_M_param._M_prob.size() - 1); |
5295 | } |
5296 | |
5297 | /** |
5298 | * @brief Generating functions. |
5299 | */ |
5300 | template<typename _UniformRandomNumberGenerator> |
5301 | result_type |
5302 | operator()(_UniformRandomNumberGenerator& __urng) |
5303 | { return this->operator()(__urng, _M_param); } |
5304 | |
5305 | template<typename _UniformRandomNumberGenerator> |
5306 | result_type |
5307 | operator()(_UniformRandomNumberGenerator& __urng, |
5308 | const param_type& __p); |
5309 | |
5310 | template<typename _ForwardIterator, |
5311 | typename _UniformRandomNumberGenerator> |
5312 | void |
5313 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
5314 | _UniformRandomNumberGenerator& __urng) |
5315 | { this->__generate(__f, __t, __urng, _M_param); } |
5316 | |
5317 | template<typename _ForwardIterator, |
5318 | typename _UniformRandomNumberGenerator> |
5319 | void |
5320 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
5321 | _UniformRandomNumberGenerator& __urng, |
5322 | const param_type& __p) |
5323 | { this->__generate_impl(__f, __t, __urng, __p); } |
5324 | |
5325 | template<typename _UniformRandomNumberGenerator> |
5326 | void |
5327 | __generate(result_type* __f, result_type* __t, |
5328 | _UniformRandomNumberGenerator& __urng, |
5329 | const param_type& __p) |
5330 | { this->__generate_impl(__f, __t, __urng, __p); } |
5331 | |
5332 | /** |
5333 | * @brief Return true if two discrete distributions have the same |
5334 | * parameters. |
5335 | */ |
5336 | friend bool |
5337 | operator==(const discrete_distribution& __d1, |
5338 | const discrete_distribution& __d2) |
5339 | { return __d1._M_param == __d2._M_param; } |
5340 | |
5341 | /** |
5342 | * @brief Inserts a %discrete_distribution random number distribution |
5343 | * @p __x into the output stream @p __os. |
5344 | * |
5345 | * @param __os An output stream. |
5346 | * @param __x A %discrete_distribution random number distribution. |
5347 | * |
5348 | * @returns The output stream with the state of @p __x inserted or in |
5349 | * an error state. |
5350 | */ |
5351 | template<typename _IntType1, typename _CharT, typename _Traits> |
5352 | friend std::basic_ostream<_CharT, _Traits>& |
5353 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
5354 | const std::discrete_distribution<_IntType1>& __x); |
5355 | |
5356 | /** |
5357 | * @brief Extracts a %discrete_distribution random number distribution |
5358 | * @p __x from the input stream @p __is. |
5359 | * |
5360 | * @param __is An input stream. |
5361 | * @param __x A %discrete_distribution random number |
5362 | * generator engine. |
5363 | * |
5364 | * @returns The input stream with @p __x extracted or in an error |
5365 | * state. |
5366 | */ |
5367 | template<typename _IntType1, typename _CharT, typename _Traits> |
5368 | friend std::basic_istream<_CharT, _Traits>& |
5369 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
5370 | std::discrete_distribution<_IntType1>& __x); |
5371 | |
5372 | private: |
5373 | template<typename _ForwardIterator, |
5374 | typename _UniformRandomNumberGenerator> |
5375 | void |
5376 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
5377 | _UniformRandomNumberGenerator& __urng, |
5378 | const param_type& __p); |
5379 | |
5380 | param_type _M_param; |
5381 | }; |
5382 | |
5383 | /** |
5384 | * @brief Return true if two discrete distributions have different |
5385 | * parameters. |
5386 | */ |
5387 | template<typename _IntType> |
5388 | inline bool |
5389 | operator!=(const std::discrete_distribution<_IntType>& __d1, |
5390 | const std::discrete_distribution<_IntType>& __d2) |
5391 | { return !(__d1 == __d2); } |
5392 | |
5393 | |
5394 | /** |
5395 | * @brief A piecewise_constant_distribution random number distribution. |
5396 | * |
5397 | * The formula for the piecewise constant probability mass function is |
5398 | * |
5399 | */ |
5400 | template<typename _RealType = double> |
5401 | class piecewise_constant_distribution |
5402 | { |
5403 | static_assert(std::is_floating_point<_RealType>::value, |
5404 | "result_type must be a floating point type" ); |
5405 | |
5406 | public: |
5407 | /** The type of the range of the distribution. */ |
5408 | typedef _RealType result_type; |
5409 | |
5410 | /** Parameter type. */ |
5411 | struct param_type |
5412 | { |
5413 | typedef piecewise_constant_distribution<_RealType> distribution_type; |
5414 | friend class piecewise_constant_distribution<_RealType>; |
5415 | |
5416 | param_type() |
5417 | : _M_int(), _M_den(), _M_cp() |
5418 | { } |
5419 | |
5420 | template<typename _InputIteratorB, typename _InputIteratorW> |
5421 | param_type(_InputIteratorB __bfirst, |
5422 | _InputIteratorB __bend, |
5423 | _InputIteratorW __wbegin); |
5424 | |
5425 | template<typename _Func> |
5426 | param_type(initializer_list<_RealType> __bi, _Func __fw); |
5427 | |
5428 | template<typename _Func> |
5429 | param_type(size_t __nw, _RealType __xmin, _RealType __xmax, |
5430 | _Func __fw); |
5431 | |
5432 | // See: http://cpp-next.com/archive/2010/10/implicit-move-must-go/ |
5433 | param_type(const param_type&) = default; |
5434 | param_type& operator=(const param_type&) = default; |
5435 | |
5436 | std::vector<_RealType> |
5437 | intervals() const |
5438 | { |
5439 | if (_M_int.empty()) |
5440 | { |
5441 | std::vector<_RealType> __tmp(2); |
5442 | __tmp[1] = _RealType(1); |
5443 | return __tmp; |
5444 | } |
5445 | else |
5446 | return _M_int; |
5447 | } |
5448 | |
5449 | std::vector<double> |
5450 | densities() const |
5451 | { return _M_den.empty() ? std::vector<double>(1, 1.0) : _M_den; } |
5452 | |
5453 | friend bool |
5454 | operator==(const param_type& __p1, const param_type& __p2) |
5455 | { return __p1._M_int == __p2._M_int && __p1._M_den == __p2._M_den; } |
5456 | |
5457 | friend bool |
5458 | operator!=(const param_type& __p1, const param_type& __p2) |
5459 | { return !(__p1 == __p2); } |
5460 | |
5461 | private: |
5462 | void |
5463 | _M_initialize(); |
5464 | |
5465 | std::vector<_RealType> _M_int; |
5466 | std::vector<double> _M_den; |
5467 | std::vector<double> _M_cp; |
5468 | }; |
5469 | |
5470 | explicit |
5471 | piecewise_constant_distribution() |
5472 | : _M_param() |
5473 | { } |
5474 | |
5475 | template<typename _InputIteratorB, typename _InputIteratorW> |
5476 | piecewise_constant_distribution(_InputIteratorB __bfirst, |
5477 | _InputIteratorB __bend, |
5478 | _InputIteratorW __wbegin) |
5479 | : _M_param(__bfirst, __bend, __wbegin) |
5480 | { } |
5481 | |
5482 | template<typename _Func> |
5483 | piecewise_constant_distribution(initializer_list<_RealType> __bl, |
5484 | _Func __fw) |
5485 | : _M_param(__bl, __fw) |
5486 | { } |
5487 | |
5488 | template<typename _Func> |
5489 | piecewise_constant_distribution(size_t __nw, |
5490 | _RealType __xmin, _RealType __xmax, |
5491 | _Func __fw) |
5492 | : _M_param(__nw, __xmin, __xmax, __fw) |
5493 | { } |
5494 | |
5495 | explicit |
5496 | piecewise_constant_distribution(const param_type& __p) |
5497 | : _M_param(__p) |
5498 | { } |
5499 | |
5500 | /** |
5501 | * @brief Resets the distribution state. |
5502 | */ |
5503 | void |
5504 | reset() |
5505 | { } |
5506 | |
5507 | /** |
5508 | * @brief Returns a vector of the intervals. |
5509 | */ |
5510 | std::vector<_RealType> |
5511 | intervals() const |
5512 | { |
5513 | if (_M_param._M_int.empty()) |
5514 | { |
5515 | std::vector<_RealType> __tmp(2); |
5516 | __tmp[1] = _RealType(1); |
5517 | return __tmp; |
5518 | } |
5519 | else |
5520 | return _M_param._M_int; |
5521 | } |
5522 | |
5523 | /** |
5524 | * @brief Returns a vector of the probability densities. |
5525 | */ |
5526 | std::vector<double> |
5527 | densities() const |
5528 | { |
5529 | return _M_param._M_den.empty() |
5530 | ? std::vector<double>(1, 1.0) : _M_param._M_den; |
5531 | } |
5532 | |
5533 | /** |
5534 | * @brief Returns the parameter set of the distribution. |
5535 | */ |
5536 | param_type |
5537 | param() const |
5538 | { return _M_param; } |
5539 | |
5540 | /** |
5541 | * @brief Sets the parameter set of the distribution. |
5542 | * @param __param The new parameter set of the distribution. |
5543 | */ |
5544 | void |
5545 | param(const param_type& __param) |
5546 | { _M_param = __param; } |
5547 | |
5548 | /** |
5549 | * @brief Returns the greatest lower bound value of the distribution. |
5550 | */ |
5551 | result_type |
5552 | min() const |
5553 | { |
5554 | return _M_param._M_int.empty() |
5555 | ? result_type(0) : _M_param._M_int.front(); |
5556 | } |
5557 | |
5558 | /** |
5559 | * @brief Returns the least upper bound value of the distribution. |
5560 | */ |
5561 | result_type |
5562 | max() const |
5563 | { |
5564 | return _M_param._M_int.empty() |
5565 | ? result_type(1) : _M_param._M_int.back(); |
5566 | } |
5567 | |
5568 | /** |
5569 | * @brief Generating functions. |
5570 | */ |
5571 | template<typename _UniformRandomNumberGenerator> |
5572 | result_type |
5573 | operator()(_UniformRandomNumberGenerator& __urng) |
5574 | { return this->operator()(__urng, _M_param); } |
5575 | |
5576 | template<typename _UniformRandomNumberGenerator> |
5577 | result_type |
5578 | operator()(_UniformRandomNumberGenerator& __urng, |
5579 | const param_type& __p); |
5580 | |
5581 | template<typename _ForwardIterator, |
5582 | typename _UniformRandomNumberGenerator> |
5583 | void |
5584 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
5585 | _UniformRandomNumberGenerator& __urng) |
5586 | { this->__generate(__f, __t, __urng, _M_param); } |
5587 | |
5588 | template<typename _ForwardIterator, |
5589 | typename _UniformRandomNumberGenerator> |
5590 | void |
5591 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
5592 | _UniformRandomNumberGenerator& __urng, |
5593 | const param_type& __p) |
5594 | { this->__generate_impl(__f, __t, __urng, __p); } |
5595 | |
5596 | template<typename _UniformRandomNumberGenerator> |
5597 | void |
5598 | __generate(result_type* __f, result_type* __t, |
5599 | _UniformRandomNumberGenerator& __urng, |
5600 | const param_type& __p) |
5601 | { this->__generate_impl(__f, __t, __urng, __p); } |
5602 | |
5603 | /** |
5604 | * @brief Return true if two piecewise constant distributions have the |
5605 | * same parameters. |
5606 | */ |
5607 | friend bool |
5608 | operator==(const piecewise_constant_distribution& __d1, |
5609 | const piecewise_constant_distribution& __d2) |
5610 | { return __d1._M_param == __d2._M_param; } |
5611 | |
5612 | /** |
5613 | * @brief Inserts a %piecewise_constant_distribution random |
5614 | * number distribution @p __x into the output stream @p __os. |
5615 | * |
5616 | * @param __os An output stream. |
5617 | * @param __x A %piecewise_constant_distribution random number |
5618 | * distribution. |
5619 | * |
5620 | * @returns The output stream with the state of @p __x inserted or in |
5621 | * an error state. |
5622 | */ |
5623 | template<typename _RealType1, typename _CharT, typename _Traits> |
5624 | friend std::basic_ostream<_CharT, _Traits>& |
5625 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
5626 | const std::piecewise_constant_distribution<_RealType1>& __x); |
5627 | |
5628 | /** |
5629 | * @brief Extracts a %piecewise_constant_distribution random |
5630 | * number distribution @p __x from the input stream @p __is. |
5631 | * |
5632 | * @param __is An input stream. |
5633 | * @param __x A %piecewise_constant_distribution random number |
5634 | * generator engine. |
5635 | * |
5636 | * @returns The input stream with @p __x extracted or in an error |
5637 | * state. |
5638 | */ |
5639 | template<typename _RealType1, typename _CharT, typename _Traits> |
5640 | friend std::basic_istream<_CharT, _Traits>& |
5641 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
5642 | std::piecewise_constant_distribution<_RealType1>& __x); |
5643 | |
5644 | private: |
5645 | template<typename _ForwardIterator, |
5646 | typename _UniformRandomNumberGenerator> |
5647 | void |
5648 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
5649 | _UniformRandomNumberGenerator& __urng, |
5650 | const param_type& __p); |
5651 | |
5652 | param_type _M_param; |
5653 | }; |
5654 | |
5655 | /** |
5656 | * @brief Return true if two piecewise constant distributions have |
5657 | * different parameters. |
5658 | */ |
5659 | template<typename _RealType> |
5660 | inline bool |
5661 | operator!=(const std::piecewise_constant_distribution<_RealType>& __d1, |
5662 | const std::piecewise_constant_distribution<_RealType>& __d2) |
5663 | { return !(__d1 == __d2); } |
5664 | |
5665 | |
5666 | /** |
5667 | * @brief A piecewise_linear_distribution random number distribution. |
5668 | * |
5669 | * The formula for the piecewise linear probability mass function is |
5670 | * |
5671 | */ |
5672 | template<typename _RealType = double> |
5673 | class piecewise_linear_distribution |
5674 | { |
5675 | static_assert(std::is_floating_point<_RealType>::value, |
5676 | "result_type must be a floating point type" ); |
5677 | |
5678 | public: |
5679 | /** The type of the range of the distribution. */ |
5680 | typedef _RealType result_type; |
5681 | |
5682 | /** Parameter type. */ |
5683 | struct param_type |
5684 | { |
5685 | typedef piecewise_linear_distribution<_RealType> distribution_type; |
5686 | friend class piecewise_linear_distribution<_RealType>; |
5687 | |
5688 | param_type() |
5689 | : _M_int(), _M_den(), _M_cp(), _M_m() |
5690 | { } |
5691 | |
5692 | template<typename _InputIteratorB, typename _InputIteratorW> |
5693 | param_type(_InputIteratorB __bfirst, |
5694 | _InputIteratorB __bend, |
5695 | _InputIteratorW __wbegin); |
5696 | |
5697 | template<typename _Func> |
5698 | param_type(initializer_list<_RealType> __bl, _Func __fw); |
5699 | |
5700 | template<typename _Func> |
5701 | param_type(size_t __nw, _RealType __xmin, _RealType __xmax, |
5702 | _Func __fw); |
5703 | |
5704 | // See: http://cpp-next.com/archive/2010/10/implicit-move-must-go/ |
5705 | param_type(const param_type&) = default; |
5706 | param_type& operator=(const param_type&) = default; |
5707 | |
5708 | std::vector<_RealType> |
5709 | intervals() const |
5710 | { |
5711 | if (_M_int.empty()) |
5712 | { |
5713 | std::vector<_RealType> __tmp(2); |
5714 | __tmp[1] = _RealType(1); |
5715 | return __tmp; |
5716 | } |
5717 | else |
5718 | return _M_int; |
5719 | } |
5720 | |
5721 | std::vector<double> |
5722 | densities() const |
5723 | { return _M_den.empty() ? std::vector<double>(2, 1.0) : _M_den; } |
5724 | |
5725 | friend bool |
5726 | operator==(const param_type& __p1, const param_type& __p2) |
5727 | { return __p1._M_int == __p2._M_int && __p1._M_den == __p2._M_den; } |
5728 | |
5729 | friend bool |
5730 | operator!=(const param_type& __p1, const param_type& __p2) |
5731 | { return !(__p1 == __p2); } |
5732 | |
5733 | private: |
5734 | void |
5735 | _M_initialize(); |
5736 | |
5737 | std::vector<_RealType> _M_int; |
5738 | std::vector<double> _M_den; |
5739 | std::vector<double> _M_cp; |
5740 | std::vector<double> _M_m; |
5741 | }; |
5742 | |
5743 | explicit |
5744 | piecewise_linear_distribution() |
5745 | : _M_param() |
5746 | { } |
5747 | |
5748 | template<typename _InputIteratorB, typename _InputIteratorW> |
5749 | piecewise_linear_distribution(_InputIteratorB __bfirst, |
5750 | _InputIteratorB __bend, |
5751 | _InputIteratorW __wbegin) |
5752 | : _M_param(__bfirst, __bend, __wbegin) |
5753 | { } |
5754 | |
5755 | template<typename _Func> |
5756 | piecewise_linear_distribution(initializer_list<_RealType> __bl, |
5757 | _Func __fw) |
5758 | : _M_param(__bl, __fw) |
5759 | { } |
5760 | |
5761 | template<typename _Func> |
5762 | piecewise_linear_distribution(size_t __nw, |
5763 | _RealType __xmin, _RealType __xmax, |
5764 | _Func __fw) |
5765 | : _M_param(__nw, __xmin, __xmax, __fw) |
5766 | { } |
5767 | |
5768 | explicit |
5769 | piecewise_linear_distribution(const param_type& __p) |
5770 | : _M_param(__p) |
5771 | { } |
5772 | |
5773 | /** |
5774 | * Resets the distribution state. |
5775 | */ |
5776 | void |
5777 | reset() |
5778 | { } |
5779 | |
5780 | /** |
5781 | * @brief Return the intervals of the distribution. |
5782 | */ |
5783 | std::vector<_RealType> |
5784 | intervals() const |
5785 | { |
5786 | if (_M_param._M_int.empty()) |
5787 | { |
5788 | std::vector<_RealType> __tmp(2); |
5789 | __tmp[1] = _RealType(1); |
5790 | return __tmp; |
5791 | } |
5792 | else |
5793 | return _M_param._M_int; |
5794 | } |
5795 | |
5796 | /** |
5797 | * @brief Return a vector of the probability densities of the |
5798 | * distribution. |
5799 | */ |
5800 | std::vector<double> |
5801 | densities() const |
5802 | { |
5803 | return _M_param._M_den.empty() |
5804 | ? std::vector<double>(2, 1.0) : _M_param._M_den; |
5805 | } |
5806 | |
5807 | /** |
5808 | * @brief Returns the parameter set of the distribution. |
5809 | */ |
5810 | param_type |
5811 | param() const |
5812 | { return _M_param; } |
5813 | |
5814 | /** |
5815 | * @brief Sets the parameter set of the distribution. |
5816 | * @param __param The new parameter set of the distribution. |
5817 | */ |
5818 | void |
5819 | param(const param_type& __param) |
5820 | { _M_param = __param; } |
5821 | |
5822 | /** |
5823 | * @brief Returns the greatest lower bound value of the distribution. |
5824 | */ |
5825 | result_type |
5826 | min() const |
5827 | { |
5828 | return _M_param._M_int.empty() |
5829 | ? result_type(0) : _M_param._M_int.front(); |
5830 | } |
5831 | |
5832 | /** |
5833 | * @brief Returns the least upper bound value of the distribution. |
5834 | */ |
5835 | result_type |
5836 | max() const |
5837 | { |
5838 | return _M_param._M_int.empty() |
5839 | ? result_type(1) : _M_param._M_int.back(); |
5840 | } |
5841 | |
5842 | /** |
5843 | * @brief Generating functions. |
5844 | */ |
5845 | template<typename _UniformRandomNumberGenerator> |
5846 | result_type |
5847 | operator()(_UniformRandomNumberGenerator& __urng) |
5848 | { return this->operator()(__urng, _M_param); } |
5849 | |
5850 | template<typename _UniformRandomNumberGenerator> |
5851 | result_type |
5852 | operator()(_UniformRandomNumberGenerator& __urng, |
5853 | const param_type& __p); |
5854 | |
5855 | template<typename _ForwardIterator, |
5856 | typename _UniformRandomNumberGenerator> |
5857 | void |
5858 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
5859 | _UniformRandomNumberGenerator& __urng) |
5860 | { this->__generate(__f, __t, __urng, _M_param); } |
5861 | |
5862 | template<typename _ForwardIterator, |
5863 | typename _UniformRandomNumberGenerator> |
5864 | void |
5865 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
5866 | _UniformRandomNumberGenerator& __urng, |
5867 | const param_type& __p) |
5868 | { this->__generate_impl(__f, __t, __urng, __p); } |
5869 | |
5870 | template<typename _UniformRandomNumberGenerator> |
5871 | void |
5872 | __generate(result_type* __f, result_type* __t, |
5873 | _UniformRandomNumberGenerator& __urng, |
5874 | const param_type& __p) |
5875 | { this->__generate_impl(__f, __t, __urng, __p); } |
5876 | |
5877 | /** |
5878 | * @brief Return true if two piecewise linear distributions have the |
5879 | * same parameters. |
5880 | */ |
5881 | friend bool |
5882 | operator==(const piecewise_linear_distribution& __d1, |
5883 | const piecewise_linear_distribution& __d2) |
5884 | { return __d1._M_param == __d2._M_param; } |
5885 | |
5886 | /** |
5887 | * @brief Inserts a %piecewise_linear_distribution random number |
5888 | * distribution @p __x into the output stream @p __os. |
5889 | * |
5890 | * @param __os An output stream. |
5891 | * @param __x A %piecewise_linear_distribution random number |
5892 | * distribution. |
5893 | * |
5894 | * @returns The output stream with the state of @p __x inserted or in |
5895 | * an error state. |
5896 | */ |
5897 | template<typename _RealType1, typename _CharT, typename _Traits> |
5898 | friend std::basic_ostream<_CharT, _Traits>& |
5899 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
5900 | const std::piecewise_linear_distribution<_RealType1>& __x); |
5901 | |
5902 | /** |
5903 | * @brief Extracts a %piecewise_linear_distribution random number |
5904 | * distribution @p __x from the input stream @p __is. |
5905 | * |
5906 | * @param __is An input stream. |
5907 | * @param __x A %piecewise_linear_distribution random number |
5908 | * generator engine. |
5909 | * |
5910 | * @returns The input stream with @p __x extracted or in an error |
5911 | * state. |
5912 | */ |
5913 | template<typename _RealType1, typename _CharT, typename _Traits> |
5914 | friend std::basic_istream<_CharT, _Traits>& |
5915 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
5916 | std::piecewise_linear_distribution<_RealType1>& __x); |
5917 | |
5918 | private: |
5919 | template<typename _ForwardIterator, |
5920 | typename _UniformRandomNumberGenerator> |
5921 | void |
5922 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
5923 | _UniformRandomNumberGenerator& __urng, |
5924 | const param_type& __p); |
5925 | |
5926 | param_type _M_param; |
5927 | }; |
5928 | |
5929 | /** |
5930 | * @brief Return true if two piecewise linear distributions have |
5931 | * different parameters. |
5932 | */ |
5933 | template<typename _RealType> |
5934 | inline bool |
5935 | operator!=(const std::piecewise_linear_distribution<_RealType>& __d1, |
5936 | const std::piecewise_linear_distribution<_RealType>& __d2) |
5937 | { return !(__d1 == __d2); } |
5938 | |
5939 | |
5940 | /* @} */ // group random_distributions_poisson |
5941 | |
5942 | /* @} */ // group random_distributions |
5943 | |
5944 | /** |
5945 | * @addtogroup random_utilities Random Number Utilities |
5946 | * @ingroup random |
5947 | * @{ |
5948 | */ |
5949 | |
5950 | /** |
5951 | * @brief The seed_seq class generates sequences of seeds for random |
5952 | * number generators. |
5953 | */ |
5954 | class seed_seq |
5955 | { |
5956 | public: |
5957 | /** The type of the seed vales. */ |
5958 | typedef uint_least32_t result_type; |
5959 | |
5960 | /** Default constructor. */ |
5961 | seed_seq() noexcept |
5962 | : _M_v() |
5963 | { } |
5964 | |
5965 | template<typename _IntType> |
5966 | seed_seq(std::initializer_list<_IntType> il); |
5967 | |
5968 | template<typename _InputIterator> |
5969 | seed_seq(_InputIterator __begin, _InputIterator __end); |
5970 | |
5971 | // generating functions |
5972 | template<typename _RandomAccessIterator> |
5973 | void |
5974 | generate(_RandomAccessIterator __begin, _RandomAccessIterator __end); |
5975 | |
5976 | // property functions |
5977 | size_t size() const noexcept |
5978 | { return _M_v.size(); } |
5979 | |
5980 | template<typename OutputIterator> |
5981 | void |
5982 | param(OutputIterator __dest) const |
5983 | { std::copy(_M_v.begin(), _M_v.end(), __dest); } |
5984 | |
5985 | // no copy functions |
5986 | seed_seq(const seed_seq&) = delete; |
5987 | seed_seq& operator=(const seed_seq&) = delete; |
5988 | |
5989 | private: |
5990 | std::vector<result_type> _M_v; |
5991 | }; |
5992 | |
5993 | /* @} */ // group random_utilities |
5994 | |
5995 | /* @} */ // group random |
5996 | |
5997 | _GLIBCXX_END_NAMESPACE_VERSION |
5998 | } // namespace std |
5999 | |
6000 | #endif |
6001 | |