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1 | // random number generation -*- C++ -*- |
2 | ||
95fe602e | 3 | // Copyright (C) 2009 Free Software Foundation, Inc. |
8e79468d BK |
4 | // |
5 | // This file is part of the GNU ISO C++ Library. This library is free | |
6 | // software; you can redistribute it and/or modify it under the | |
7 | // terms of the GNU General Public License as published by the | |
8 | // Free Software Foundation; either version 2, 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 | // You should have received a copy of the GNU General Public License along | |
17 | // with this library; see the file COPYING. If not, write to the Free | |
18 | // Software Foundation, 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, | |
19 | // USA. | |
20 | ||
21 | // As a special exception, you may use this file as part of a free software | |
22 | // library without restriction. Specifically, if other files instantiate | |
23 | // templates or use macros or inline functions from this file, or you compile | |
24 | // this file and link it with other files to produce an executable, this | |
25 | // file does not by itself cause the resulting executable to be covered by | |
26 | // the GNU General Public License. This exception does not however | |
27 | // invalidate any other reasons why the executable file might be covered by | |
28 | // the GNU General Public License. | |
29 | ||
30 | /** | |
31 | * @file bits/random.h | |
32 | * This is an internal header file, included by other library headers. | |
33 | * You should not attempt to use it directly. | |
34 | */ | |
35 | ||
36 | #include <vector> | |
37 | ||
38 | namespace std | |
39 | { | |
40 | ||
41 | // [26.4] Random number generation | |
42 | ||
43 | /** | |
44 | * @addtogroup std_random Random Number Generation | |
45 | * A facility for generating random numbers on selected distributions. | |
46 | * @{ | |
47 | */ | |
48 | ||
49 | /** | |
50 | * @brief A function template for converting the output of a (integral) | |
51 | * uniform random number generator to a floatng point result in the range | |
52 | * [0-1). | |
53 | */ | |
54 | template<typename _RealType, size_t __bits, | |
55 | typename _UniformRandomNumberGenerator> | |
56 | _RealType | |
57 | generate_canonical(_UniformRandomNumberGenerator& __g); | |
58 | ||
59 | class seed_seq; | |
60 | ||
61 | /* | |
62 | * Implementation-space details. | |
63 | */ | |
64 | namespace __detail | |
65 | { | |
66 | template<typename _UIntType, size_t __w, | |
95fe602e PC |
67 | bool = __w < static_cast<size_t> |
68 | (std::numeric_limits<_UIntType>::digits)> | |
8e79468d BK |
69 | struct _Shift |
70 | { static const _UIntType __value = 0; }; | |
71 | ||
72 | template<typename _UIntType, size_t __w> | |
73 | struct _Shift<_UIntType, __w, true> | |
74 | { static const _UIntType __value = _UIntType(1) << __w; }; | |
75 | ||
76 | // XXX need constexpr | |
77 | template<typename _UIntType, size_t __w, | |
95fe602e PC |
78 | bool = __w <static_cast<size_t> |
79 | (std::numeric_limits<_UIntType>::digits)> | |
8e79468d | 80 | struct _ShiftMin1 |
42a73304 | 81 | { |
95fe602e | 82 | static const _UIntType __value = |
42a73304 | 83 | __gnu_cxx::__numeric_traits<_UIntType>::__max; |
95fe602e | 84 | }; |
8e79468d BK |
85 | |
86 | template<typename _UIntType, size_t __w> | |
87 | struct _ShiftMin1<_UIntType, __w, true> | |
42a73304 PC |
88 | { |
89 | static const _UIntType __value = | |
90 | (_UIntType(1) << __w) - _UIntType(1); | |
91 | }; | |
8e79468d BK |
92 | |
93 | template<typename _Tp, _Tp __a, _Tp __c, _Tp __m, bool> | |
94 | struct _Mod; | |
95 | ||
96 | // Dispatch based on modulus value to prevent divide-by-zero compile-time | |
97 | // errors when m == 0. | |
98 | template<typename _Tp, _Tp __a, _Tp __c, _Tp __m> | |
99 | inline _Tp | |
100 | __mod(_Tp __x) | |
101 | { return _Mod<_Tp, __a, __c, __m, __m == 0>::__calc(__x); } | |
102 | ||
103 | typedef __gnu_cxx::__conditional_type<(sizeof(unsigned) == 4), | |
104 | unsigned, unsigned long>::__type _UInt32Type; | |
105 | ||
106 | /* | |
107 | * An adaptor class for converting the output of any Generator into | |
108 | * the input for a specific Distribution. | |
109 | */ | |
110 | template<typename _Engine, typename _DInputType> | |
111 | struct _Adaptor | |
112 | { | |
113 | ||
114 | public: | |
115 | _Adaptor(_Engine& __g) | |
116 | : _M_g(__g) { } | |
117 | ||
118 | _DInputType | |
119 | min() const | |
120 | { | |
121 | if (is_integral<_DInputType>::value) | |
122 | return _M_g.min(); | |
123 | else | |
124 | return _DInputType(0); | |
125 | } | |
126 | ||
127 | _DInputType | |
128 | max() const | |
129 | { | |
130 | if (is_integral<_DInputType>::value) | |
131 | return _M_g.max(); | |
132 | else | |
133 | return _DInputType(1); | |
134 | } | |
135 | ||
136 | /* | |
137 | * Converts a value generated by the adapted random number generator | |
138 | * into a value in the input domain for the dependent random number | |
139 | * distribution. | |
140 | * | |
141 | * Because the type traits are compile time constants only the | |
142 | * appropriate clause of the if statements will actually be emitted | |
143 | * by the compiler. | |
144 | */ | |
145 | _DInputType | |
146 | operator()() | |
147 | { | |
148 | if (is_integral<_DInputType>::value) | |
149 | return _M_g(); | |
150 | else | |
151 | return generate_canonical<_DInputType, | |
152 | numeric_limits<_DInputType>::digits, | |
153 | _Engine>(_M_g); | |
154 | } | |
155 | ||
156 | private: | |
157 | _Engine& _M_g; | |
158 | }; | |
159 | } // namespace __detail | |
160 | ||
161 | /** | |
162 | * @addtogroup std_random_generators Random Number Generators | |
163 | * @ingroup std_random | |
164 | * | |
165 | * These classes define objects which provide random or pseudorandom | |
166 | * numbers, either from a discrete or a continuous interval. The | |
167 | * random number generator supplied as a part of this library are | |
168 | * all uniform random number generators which provide a sequence of | |
169 | * random number uniformly distributed over their range. | |
170 | * | |
171 | * A number generator is a function object with an operator() that | |
172 | * takes zero arguments and returns a number. | |
173 | * | |
174 | * A compliant random number generator must satisfy the following | |
175 | * requirements. <table border=1 cellpadding=10 cellspacing=0> | |
176 | * <caption align=top>Random Number Generator Requirements</caption> | |
177 | * <tr><td>To be documented.</td></tr> </table> | |
178 | * | |
179 | * @{ | |
180 | */ | |
181 | ||
182 | /** | |
183 | * @brief A model of a linear congruential random number generator. | |
184 | * | |
185 | * A random number generator that produces pseudorandom numbers using the | |
186 | * linear function @f$x_{i+1}\leftarrow(ax_{i} + c) \bmod m @f$. | |
187 | * | |
188 | * The template parameter @p _UIntType must be an unsigned integral type | |
189 | * large enough to store values up to (__m-1). If the template parameter | |
190 | * @p __m is 0, the modulus @p __m used is | |
191 | * std::numeric_limits<_UIntType>::max() plus 1. Otherwise, the template | |
192 | * parameters @p __a and @p __c must be less than @p __m. | |
193 | * | |
194 | * The size of the state is @f$ 1 @f$. | |
195 | */ | |
196 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m> | |
197 | class linear_congruential_engine | |
198 | { | |
199 | __glibcxx_class_requires(_UIntType, _UnsignedIntegerConcept) | |
200 | static_assert(__m == 0 || (__a < __m && __c < __m), | |
201 | "template arguments out of bounds" | |
202 | " in linear_congruential_engine"); | |
203 | ||
204 | public: | |
205 | /** The type of the generated random value. */ | |
206 | typedef _UIntType result_type; | |
207 | ||
208 | /** The multiplier. */ | |
209 | static const result_type multiplier = __a; | |
210 | /** An increment. */ | |
211 | static const result_type increment = __c; | |
212 | /** The modulus. */ | |
213 | static const result_type modulus = __m; | |
214 | static const result_type default_seed = 1UL; | |
215 | ||
216 | /** | |
217 | * @brief Constructs a %linear_congruential_engine random number | |
218 | * generator engine with seed @p __s. The default seed value | |
219 | * is 1. | |
220 | * | |
221 | * @param __s The initial seed value. | |
222 | */ | |
223 | explicit | |
224 | linear_congruential_engine(result_type __s = default_seed) | |
225 | { this->seed(__s); } | |
226 | ||
227 | /** | |
228 | * @brief Constructs a %linear_congruential_engine random number | |
229 | * generator engine seeded from the seed sequence @p __q. | |
230 | * | |
231 | * @param __q the seed sequence. | |
232 | */ | |
233 | explicit | |
234 | linear_congruential_engine(seed_seq& __q) | |
235 | { this->seed(__q); } | |
236 | ||
237 | /** | |
238 | * @brief Reseeds the %linear_congruential_engine random number generator | |
239 | * engine sequence to the seed @g __s. | |
240 | * | |
241 | * @param __s The new seed. | |
242 | */ | |
243 | void | |
244 | seed(result_type __s = default_seed); | |
245 | ||
246 | /** | |
247 | * @brief Reseeds the %linear_congruential_engine random number generator | |
248 | * engine | |
249 | * sequence using values from the seed sequence @p __q. | |
250 | * | |
251 | * @param __q the seed sequence. | |
252 | */ | |
253 | void | |
254 | seed(seed_seq& __q); | |
255 | ||
256 | /** | |
257 | * @brief Gets the smallest possible value in the output range. | |
258 | * | |
259 | * The minimum depends on the @p __c parameter: if it is zero, the | |
260 | * minimum generated must be > 0, otherwise 0 is allowed. | |
261 | * | |
262 | * @todo This should be constexpr. | |
263 | */ | |
264 | result_type | |
265 | min() const | |
266 | { return (__detail::__mod<_UIntType, 1, 0, __m>(__c) == 0) ? 1 : 0; } | |
267 | ||
268 | /** | |
269 | * @brief Gets the largest possible value in the output range. | |
270 | * | |
271 | * @todo This should be constexpr. | |
272 | */ | |
273 | result_type | |
274 | max() const | |
275 | { return __m - 1; } | |
276 | ||
277 | /** | |
278 | * @brief Discard a sequence of random numbers. | |
279 | * | |
280 | * @todo Look for a faster way to do discard. | |
281 | */ | |
282 | void | |
283 | discard(unsigned long long __z) | |
284 | { | |
285 | for (; __z != 0ULL; --__z) | |
286 | (*this)(); | |
287 | } | |
288 | ||
289 | /** | |
290 | * @brief Gets the next random number in the sequence. | |
291 | */ | |
292 | result_type | |
293 | operator()(); | |
294 | ||
295 | /** | |
296 | * @brief Compares two linear congruential random number generator | |
297 | * objects of the same type for equality. | |
298 | * | |
299 | * @param __lhs A linear congruential random number generator object. | |
300 | * @param __rhs Another linear congruential random number generator | |
301 | * object. | |
302 | * | |
303 | * @returns true if the two objects are equal, false otherwise. | |
304 | */ | |
305 | friend bool | |
306 | operator==(const linear_congruential_engine& __lhs, | |
307 | const linear_congruential_engine& __rhs) | |
308 | { return __lhs._M_x == __rhs._M_x; } | |
309 | ||
310 | /** | |
311 | * @brief Writes the textual representation of the state x(i) of x to | |
312 | * @p __os. | |
313 | * | |
314 | * @param __os The output stream. | |
315 | * @param __lcr A % linear_congruential_engine random number generator. | |
316 | * @returns __os. | |
317 | */ | |
318 | template<typename _UIntType1, _UIntType1 __a1, _UIntType1 __c1, | |
319 | _UIntType1 __m1, | |
320 | typename _CharT, typename _Traits> | |
321 | friend std::basic_ostream<_CharT, _Traits>& | |
94986f6d PC |
322 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
323 | const std::linear_congruential_engine<_UIntType1, | |
324 | __a1, __c1, __m1>&); | |
8e79468d BK |
325 | |
326 | /** | |
327 | * @brief Sets the state of the engine by reading its textual | |
328 | * representation from @p __is. | |
329 | * | |
330 | * The textual representation must have been previously written using | |
331 | * an output stream whose imbued locale and whose type's template | |
332 | * specialization arguments _CharT and _Traits were the same as those | |
333 | * of @p __is. | |
334 | * | |
335 | * @param __is The input stream. | |
336 | * @param __lcr A % linear_congruential_engine random number generator. | |
337 | * @returns __is. | |
338 | */ | |
339 | template<typename _UIntType1, _UIntType1 __a1, _UIntType1 __c1, | |
340 | _UIntType1 __m1, | |
341 | typename _CharT, typename _Traits> | |
342 | friend std::basic_istream<_CharT, _Traits>& | |
94986f6d PC |
343 | operator>>(std::basic_istream<_CharT, _Traits>&, |
344 | std::linear_congruential_engine<_UIntType1, __a1, | |
345 | __c1, __m1>&); | |
8e79468d BK |
346 | |
347 | private: | |
348 | template<typename _Gen> | |
349 | void | |
350 | seed(_Gen& __g, true_type) | |
351 | { return seed(static_cast<unsigned long>(__g)); } | |
352 | ||
353 | template<typename _Gen> | |
354 | void | |
355 | seed(_Gen& __g, false_type); | |
356 | ||
357 | _UIntType _M_x; | |
358 | }; | |
359 | ||
360 | ||
361 | /** | |
362 | * A generalized feedback shift register discrete random number generator. | |
363 | * | |
364 | * This algorithm avoids multiplication and division and is designed to be | |
365 | * friendly to a pipelined architecture. If the parameters are chosen | |
366 | * correctly, this generator will produce numbers with a very long period and | |
367 | * fairly good apparent entropy, although still not cryptographically strong. | |
368 | * | |
369 | * The best way to use this generator is with the predefined mt19937 class. | |
370 | * | |
371 | * This algorithm was originally invented by Makoto Matsumoto and | |
372 | * Takuji Nishimura. | |
373 | * | |
374 | * @var word_size The number of bits in each element of the state vector. | |
375 | * @var state_size The degree of recursion. | |
376 | * @var shift_size The period parameter. | |
377 | * @var mask_bits The separation point bit index. | |
378 | * @var parameter_a The last row of the twist matrix. | |
379 | * @var output_u The first right-shift tempering matrix parameter. | |
380 | * @var output_s The first left-shift tempering matrix parameter. | |
381 | * @var output_b The first left-shift tempering matrix mask. | |
382 | * @var output_t The second left-shift tempering matrix parameter. | |
383 | * @var output_c The second left-shift tempering matrix mask. | |
384 | * @var output_l The second right-shift tempering matrix parameter. | |
385 | */ | |
386 | template<typename _UIntType, size_t __w, | |
387 | size_t __n, size_t __m, size_t __r, | |
388 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, | |
389 | _UIntType __b, size_t __t, | |
390 | _UIntType __c, size_t __l, _UIntType __f> | |
391 | class mersenne_twister_engine | |
392 | { | |
393 | __glibcxx_class_requires(_UIntType, _UnsignedIntegerConcept) | |
394 | ||
395 | static_assert(__m >= 1U, | |
396 | "mersenne_twister_engine template arguments out of bounds"); | |
397 | static_assert(__n >= __m, | |
398 | "mersenne_twister_engine template arguments out of bounds"); | |
399 | static_assert(__w >= __r, | |
400 | "mersenne_twister_engine template arguments out of bounds"); | |
401 | static_assert(__w >= __u, | |
402 | "mersenne_twister_engine template arguments out of bounds"); | |
403 | static_assert(__w >= __s, | |
404 | "mersenne_twister_engine template arguments out of bounds"); | |
405 | static_assert(__w >= __t, | |
406 | "mersenne_twister_engine template arguments out of bounds"); | |
407 | static_assert(__w >= __l, | |
408 | "mersenne_twister_engine template arguments out of bounds"); | |
94986f6d PC |
409 | static_assert(__w <= |
410 | static_cast<size_t>(numeric_limits<_UIntType>::digits), | |
8e79468d | 411 | "mersenne_twister_engine template arguments out of bounds"); |
8e79468d BK |
412 | static_assert(__a <= __detail::_ShiftMin1<_UIntType, __w>::__value, |
413 | "mersenne_twister_engine template arguments out of bounds"); | |
414 | static_assert(__b <= __detail::_ShiftMin1<_UIntType, __w>::__value, | |
415 | "mersenne_twister_engine template arguments out of bounds"); | |
416 | static_assert(__c <= __detail::_ShiftMin1<_UIntType, __w>::__value, | |
417 | "mersenne_twister_engine template arguments out of bounds"); | |
8e79468d BK |
418 | |
419 | public: | |
420 | /** The type of the generated random value. */ | |
421 | typedef _UIntType result_type; | |
422 | ||
423 | // parameter values | |
424 | static const size_t word_size = __w; | |
425 | static const size_t state_size = __n; | |
426 | static const size_t shift_size = __m; | |
427 | static const size_t mask_bits = __r; | |
428 | static const result_type xor_mask = __a; | |
429 | static const size_t tempering_u = __u; | |
430 | static const result_type tempering_d = __d; | |
431 | static const size_t tempering_s = __s; | |
432 | static const result_type tempering_b = __b; | |
433 | static const size_t tempering_t = __t; | |
434 | static const result_type tempering_c = __c; | |
435 | static const size_t tempering_l = __l; | |
436 | static const size_t initialization_multiplier = __f; | |
437 | static const result_type default_seed = 5489UL; | |
438 | ||
439 | // constructors and member function | |
440 | explicit | |
441 | mersenne_twister_engine(result_type __sd = default_seed) | |
442 | { seed(__sd); } | |
443 | ||
444 | /** | |
445 | * @brief Constructs a %mersenne_twister_engine random number generator | |
446 | * engine seeded from the seed sequence @p __q. | |
447 | * | |
448 | * @param __q the seed sequence. | |
449 | */ | |
450 | explicit | |
451 | mersenne_twister_engine(seed_seq& __q) | |
452 | { seed(__q); } | |
453 | ||
454 | void | |
455 | seed(result_type __sd = default_seed); | |
456 | ||
457 | void | |
458 | seed(seed_seq& __q); | |
459 | ||
460 | /** | |
461 | * @brief Gets the smallest possible value in the output range. | |
462 | * | |
463 | * @todo This should be constexpr. | |
464 | */ | |
465 | result_type | |
466 | min() const | |
467 | { return 0; }; | |
468 | ||
469 | /** | |
470 | * @brief Gets the largest possible value in the output range. | |
471 | * | |
472 | * @todo This should be constexpr. | |
473 | */ | |
474 | result_type | |
475 | max() const | |
476 | { return __detail::_ShiftMin1<_UIntType, __w>::__value; } | |
477 | ||
478 | /** | |
479 | * @brief Discard a sequence of random numbers. | |
480 | * | |
481 | * @todo Look for a faster way to do discard. | |
482 | */ | |
483 | void | |
484 | discard(unsigned long long __z) | |
485 | { | |
486 | for (; __z != 0ULL; --__z) | |
487 | (*this)(); | |
488 | } | |
489 | ||
490 | result_type | |
491 | operator()(); | |
492 | ||
493 | /** | |
494 | * @brief Compares two % mersenne_twister_engine random number generator | |
495 | * objects of the same type for equality. | |
496 | * | |
497 | * @param __lhs A % mersenne_twister_engine random number generator | |
498 | * object. | |
499 | * @param __rhs Another % mersenne_twister_engine random number | |
500 | * generator object. | |
501 | * | |
502 | * @returns true if the two objects are equal, false otherwise. | |
503 | */ | |
504 | friend bool | |
505 | operator==(const mersenne_twister_engine& __lhs, | |
506 | const mersenne_twister_engine& __rhs) | |
507 | { return std::equal(__lhs._M_x, __lhs._M_x + state_size, __rhs._M_x); } | |
508 | ||
509 | /** | |
510 | * @brief Inserts the current state of a % mersenne_twister_engine | |
511 | * random number generator engine @p __x into the output stream | |
512 | * @p __os. | |
513 | * | |
514 | * @param __os An output stream. | |
515 | * @param __x A % mersenne_twister_engine random number generator | |
516 | * engine. | |
517 | * | |
518 | * @returns The output stream with the state of @p __x inserted or in | |
519 | * an error state. | |
520 | */ | |
521 | template<typename _UIntType1, | |
522 | size_t __w1, size_t __n1, | |
523 | size_t __m1, size_t __r1, | |
524 | _UIntType1 __a1, size_t __u1, | |
525 | _UIntType1 __d1, size_t __s1, | |
526 | _UIntType1 __b1, size_t __t1, | |
527 | _UIntType1 __c1, size_t __l1, _UIntType1 __f1, | |
528 | typename _CharT, typename _Traits> | |
529 | friend std::basic_ostream<_CharT, _Traits>& | |
94986f6d PC |
530 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
531 | const std::mersenne_twister_engine<_UIntType1, __w1, __n1, | |
532 | __m1, __r1, __a1, __u1, __d1, __s1, __b1, __t1, __c1, | |
533 | __l1, __f1>&); | |
8e79468d BK |
534 | |
535 | /** | |
536 | * @brief Extracts the current state of a % mersenne_twister_engine | |
537 | * random number generator engine @p __x from the input stream | |
538 | * @p __is. | |
539 | * | |
540 | * @param __is An input stream. | |
541 | * @param __x A % mersenne_twister_engine random number generator | |
542 | * engine. | |
543 | * | |
544 | * @returns The input stream with the state of @p __x extracted or in | |
545 | * an error state. | |
546 | */ | |
547 | template<typename _UIntType1, | |
548 | size_t __w1, size_t __n1, | |
549 | size_t __m1, size_t __r1, | |
550 | _UIntType1 __a1, size_t __u1, | |
551 | _UIntType1 __d1, size_t __s1, | |
552 | _UIntType1 __b1, size_t __t1, | |
553 | _UIntType1 __c1, size_t __l1, _UIntType1 __f1, | |
554 | typename _CharT, typename _Traits> | |
555 | friend std::basic_istream<_CharT, _Traits>& | |
94986f6d PC |
556 | operator>>(std::basic_istream<_CharT, _Traits>&, |
557 | std::mersenne_twister_engine<_UIntType1, __w1, __n1, __m1, | |
558 | __r1, __a1, __u1, __d1, __s1, __b1, __t1, __c1, | |
559 | __l1, __f1>&); | |
8e79468d BK |
560 | |
561 | private: | |
562 | template<typename _Gen> | |
563 | void | |
564 | seed(_Gen& __g, true_type) | |
565 | { return seed(static_cast<unsigned long>(__g)); } | |
566 | ||
567 | template<typename _Gen> | |
568 | void | |
569 | seed(_Gen& __g, false_type); | |
570 | ||
571 | _UIntType _M_x[state_size]; | |
572 | size_t _M_p; | |
573 | }; | |
574 | ||
575 | /** | |
576 | * @brief The Marsaglia-Zaman generator. | |
577 | * | |
578 | * This is a model of a Generalized Fibonacci discrete random number | |
579 | * generator, sometimes referred to as the SWC generator. | |
580 | * | |
581 | * A discrete random number generator that produces pseudorandom | |
582 | * numbers using @f$x_{i}\leftarrow(x_{i - s} - x_{i - r} - | |
583 | * carry_{i-1}) \bmod m @f$. | |
584 | * | |
585 | * The size of the state is @f$ r @f$ | |
586 | * and the maximum period of the generator is @f$ m^r - m^s - 1 @f$. | |
587 | * | |
588 | * @var _M_x The state of the generator. This is a ring buffer. | |
589 | * @var _M_carry The carry. | |
590 | * @var _M_p Current index of x(i - r). | |
591 | */ | |
592 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> | |
593 | class subtract_with_carry_engine | |
594 | { | |
595 | __glibcxx_class_requires(_UIntType, _UnsignedIntegerConcept) | |
596 | static_assert(__s > 0U && __r > __s | |
597 | && __w > 0U | |
598 | && __w <= static_cast<size_t>(numeric_limits<_UIntType>::digits), | |
599 | "template arguments out of bounds" | |
600 | " in subtract_with_carry_engine"); | |
601 | ||
602 | public: | |
603 | /** The type of the generated random value. */ | |
604 | typedef _UIntType result_type; | |
605 | ||
606 | // parameter values | |
607 | static const size_t word_size = __w; | |
608 | static const size_t short_lag = __s; | |
609 | static const size_t long_lag = __r; | |
610 | static const result_type default_seed = 19780503; | |
611 | ||
612 | /** | |
613 | * @brief Constructs an explicitly seeded % subtract_with_carry_engine | |
614 | * random number generator. | |
615 | */ | |
616 | explicit | |
617 | subtract_with_carry_engine(result_type __sd = default_seed) | |
618 | { this->seed(__sd); } | |
619 | ||
620 | /** | |
621 | * @brief Constructs a %subtract_with_carry_engine random number engine | |
622 | * seeded from the seed sequence @p __q. | |
623 | * | |
624 | * @param __q the seed sequence. | |
625 | */ | |
626 | explicit | |
627 | subtract_with_carry_engine(seed_seq& __q) | |
628 | { this->seed(__q); } | |
629 | ||
630 | /** | |
631 | * @brief Seeds the initial state @f$ x_0 @f$ of the random number | |
632 | * generator. | |
633 | * | |
634 | * N1688[4.19] modifies this as follows. If @p __value == 0, | |
635 | * sets value to 19780503. In any case, with a linear | |
636 | * congruential generator lcg(i) having parameters @f$ m_{lcg} = | |
637 | * 2147483563, a_{lcg} = 40014, c_{lcg} = 0, and lcg(0) = value | |
638 | * @f$, sets @f$ x_{-r} \dots x_{-1} @f$ to @f$ lcg(1) \bmod m | |
639 | * \dots lcg(r) \bmod m @f$ respectively. If @f$ x_{-1} = 0 @f$ | |
640 | * set carry to 1, otherwise sets carry to 0. | |
641 | */ | |
642 | void | |
643 | seed(result_type __sd = default_seed); | |
644 | ||
645 | /** | |
646 | * @brief Seeds the initial state @f$ x_0 @f$ of the | |
647 | * % subtract_with_carry_engine random number generator. | |
648 | */ | |
649 | void | |
650 | seed(seed_seq& __q); | |
651 | ||
652 | /** | |
653 | * @brief Gets the inclusive minimum value of the range of random | |
654 | * integers returned by this generator. | |
655 | * | |
656 | * @todo This should be constexpr. | |
657 | */ | |
658 | result_type | |
659 | min() const | |
660 | { return 0; } | |
661 | ||
662 | /** | |
663 | * @brief Gets the inclusive maximum value of the range of random | |
664 | * integers returned by this generator. | |
665 | * | |
666 | * @todo This should be constexpr. | |
667 | */ | |
668 | result_type | |
669 | max() const | |
670 | { return _S_modulus - 1U; } | |
671 | ||
672 | /** | |
673 | * @brief Discard a sequence of random numbers. | |
674 | * | |
675 | * @todo Look for a faster way to do discard. | |
676 | */ | |
677 | void | |
678 | discard(unsigned long long __z) | |
679 | { | |
680 | for (; __z != 0ULL; --__z) | |
681 | (*this)(); | |
682 | } | |
683 | ||
684 | /** | |
685 | * @brief Gets the next random number in the sequence. | |
686 | */ | |
687 | result_type | |
688 | operator()(); | |
689 | ||
690 | /** | |
691 | * @brief Compares two % subtract_with_carry_engine random number | |
692 | * generator objects of the same type for equality. | |
693 | * | |
694 | * @param __lhs A % subtract_with_carry_engine random number generator | |
695 | * object. | |
696 | * @param __rhs Another % subtract_with_carry_engine random number | |
697 | * generator object. | |
698 | * | |
699 | * @returns true if the two objects are equal, false otherwise. | |
700 | */ | |
701 | friend bool | |
702 | operator==(const subtract_with_carry_engine& __lhs, | |
703 | const subtract_with_carry_engine& __rhs) | |
704 | { return std::equal(__lhs._M_x, __lhs._M_x + long_lag, __rhs._M_x); } | |
705 | ||
706 | /** | |
707 | * @brief Inserts the current state of a % subtract_with_carry_engine | |
708 | * random number generator engine @p __x into the output stream | |
709 | * @p __os. | |
710 | * | |
711 | * @param __os An output stream. | |
712 | * @param __x A % subtract_with_carry_engine random number generator | |
713 | * engine. | |
714 | * | |
715 | * @returns The output stream with the state of @p __x inserted or in | |
716 | * an error state. | |
717 | */ | |
718 | template<typename _UIntType1, size_t __w1, size_t __s1, size_t __r1, | |
719 | typename _CharT, typename _Traits> | |
720 | friend std::basic_ostream<_CharT, _Traits>& | |
94986f6d PC |
721 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
722 | const std::subtract_with_carry_engine<_UIntType1, __w1, | |
723 | __s1, __r1>&); | |
8e79468d BK |
724 | |
725 | /** | |
726 | * @brief Extracts the current state of a % subtract_with_carry_engine | |
727 | * random number generator engine @p __x from the input stream | |
728 | * @p __is. | |
729 | * | |
730 | * @param __is An input stream. | |
731 | * @param __x A % subtract_with_carry_engine random number generator engine. | |
732 | * | |
733 | * @returns The input stream with the state of @p __x extracted or in | |
734 | * an error state. | |
735 | */ | |
736 | template<typename _UIntType1, size_t __w1, size_t __s1, size_t __r1, | |
737 | typename _CharT, typename _Traits> | |
738 | friend std::basic_istream<_CharT, _Traits>& | |
94986f6d PC |
739 | operator>>(std::basic_istream<_CharT, _Traits>&, |
740 | std::subtract_with_carry_engine<_UIntType1, __w1, | |
741 | __s1, __r1>&); | |
8e79468d BK |
742 | |
743 | private: | |
744 | template<typename _Gen> | |
745 | void | |
746 | seed(_Gen& __g, true_type) | |
747 | { return seed(static_cast<unsigned long>(__g)); } | |
748 | ||
749 | template<typename _Gen> | |
750 | void | |
751 | seed(_Gen& __g, false_type); | |
752 | ||
753 | static const size_t _S_modulus | |
754 | = __detail::_Shift<_UIntType, __w>::__value; | |
755 | ||
756 | _UIntType _M_x[long_lag]; | |
757 | _UIntType _M_carry; | |
758 | size_t _M_p; | |
759 | }; | |
760 | ||
761 | /** | |
762 | * Produces random numbers from some base engine by discarding blocks of | |
763 | * data. | |
764 | * | |
765 | * 0 <= @p __r <= @p __p | |
766 | */ | |
767 | template<typename _RandomNumberEngine, size_t __p, size_t __r> | |
768 | class discard_block_engine | |
769 | { | |
770 | static_assert(__r >= 1U && __p >= __r, | |
771 | "template arguments out of bounds" | |
772 | " in discard_block_engine"); | |
773 | ||
774 | public: | |
775 | /** The type of the generated random value. */ | |
776 | typedef typename _RandomNumberEngine::result_type result_type; | |
777 | ||
778 | // parameter values | |
779 | static const size_t block_size = __p; | |
780 | static const size_t used_block = __r; | |
781 | ||
782 | /** | |
783 | * @brief Constructs a default %discard_block_engine engine. | |
784 | * | |
785 | * The underlying engine is default constructed as well. | |
786 | */ | |
787 | discard_block_engine() | |
788 | : _M_b(), _M_n(0) { } | |
789 | ||
790 | /** | |
791 | * @brief Copy constructs a %discard_block_engine engine. | |
792 | * | |
793 | * Copies an existing base class random number generator. | |
794 | * @param rng An existing (base class) engine object. | |
795 | */ | |
796 | explicit | |
797 | discard_block_engine(const _RandomNumberEngine& __rne) | |
798 | : _M_b(__rne), _M_n(0) { } | |
799 | ||
800 | /** | |
801 | * @brief Move constructs a %discard_block_engine engine. | |
802 | * | |
803 | * Copies an existing base class random number generator. | |
804 | * @param rng An existing (base class) engine object. | |
805 | */ | |
806 | explicit | |
807 | discard_block_engine(_RandomNumberEngine&& __rne) | |
808 | : _M_b(std::move(__rne)), _M_n(0) { } | |
809 | ||
810 | /** | |
811 | * @brief Seed constructs a %discard_block_engine engine. | |
812 | * | |
813 | * Constructs the underlying generator engine seeded with @p __s. | |
814 | * @param __s A seed value for the base class engine. | |
815 | */ | |
816 | explicit | |
817 | discard_block_engine(result_type __s) | |
818 | : _M_b(__s), _M_n(0) { } | |
819 | ||
820 | /** | |
821 | * @brief Generator construct a %discard_block_engine engine. | |
822 | * | |
823 | * @param __q A seed sequence. | |
824 | */ | |
825 | explicit | |
826 | discard_block_engine(seed_seq& __q) | |
827 | : _M_b(__q), _M_n(0) | |
828 | { } | |
829 | ||
830 | /** | |
831 | * @brief Reseeds the %discard_block_engine object with the default | |
832 | * seed for the underlying base class generator engine. | |
833 | */ | |
834 | void | |
835 | seed() | |
836 | { | |
837 | _M_b.seed(); | |
838 | _M_n = 0; | |
839 | } | |
840 | ||
841 | /** | |
842 | * @brief Reseeds the %discard_block_engine object with the default | |
843 | * seed for the underlying base class generator engine. | |
844 | */ | |
845 | void | |
846 | seed(result_type __s) | |
847 | { | |
848 | _M_b.seed(__s); | |
849 | _M_n = 0; | |
850 | } | |
851 | ||
852 | /** | |
853 | * @brief Reseeds the %discard_block_engine object with the given seed | |
854 | * sequence. | |
855 | * @param __q A seed generator function. | |
856 | */ | |
857 | void | |
858 | seed(seed_seq& __q) | |
859 | { | |
860 | _M_b.seed(__q); | |
861 | _M_n = 0; | |
862 | } | |
863 | ||
864 | /** | |
865 | * @brief Gets a const reference to the underlying generator engine | |
866 | * object. | |
867 | */ | |
868 | const _RandomNumberEngine& | |
869 | base() const | |
870 | { return _M_b; } | |
871 | ||
872 | /** | |
873 | * @brief Gets the minimum value in the generated random number range. | |
874 | * | |
875 | * @todo This should be constexpr. | |
876 | */ | |
877 | result_type | |
878 | min() const | |
879 | { return _M_b.min(); } | |
880 | ||
881 | /** | |
882 | * @brief Gets the maximum value in the generated random number range. | |
883 | * | |
884 | * @todo This should be constexpr. | |
885 | */ | |
886 | result_type | |
887 | max() const | |
888 | { return _M_b.max(); } | |
889 | ||
890 | /** | |
891 | * @brief Discard a sequence of random numbers. | |
892 | * | |
893 | * @todo Look for a faster way to do discard. | |
894 | */ | |
895 | void | |
896 | discard(unsigned long long __z) | |
897 | { | |
898 | for (; __z != 0ULL; --__z) | |
899 | (*this)(); | |
900 | } | |
901 | ||
902 | /** | |
903 | * @brief Gets the next value in the generated random number sequence. | |
904 | */ | |
905 | result_type | |
906 | operator()(); | |
907 | ||
908 | /** | |
909 | * @brief Compares two %discard_block_engine random number generator | |
910 | * objects of the same type for equality. | |
911 | * | |
912 | * @param __lhs A %discard_block_engine random number generator object. | |
913 | * @param __rhs Another %discard_block_engine random number generator | |
914 | * object. | |
915 | * | |
916 | * @returns true if the two objects are equal, false otherwise. | |
917 | */ | |
918 | friend bool | |
919 | operator==(const discard_block_engine& __lhs, | |
920 | const discard_block_engine& __rhs) | |
921 | { return (__lhs._M_b == __rhs._M_b) && (__lhs._M_n == __rhs._M_n); } | |
922 | ||
923 | /** | |
924 | * @brief Inserts the current state of a %discard_block_engine random | |
925 | * number generator engine @p __x into the output stream | |
926 | * @p __os. | |
927 | * | |
928 | * @param __os An output stream. | |
929 | * @param __x A %discard_block_engine random number generator engine. | |
930 | * | |
931 | * @returns The output stream with the state of @p __x inserted or in | |
932 | * an error state. | |
933 | */ | |
934 | template<typename _RandomNumberEngine1, size_t __p1, size_t __r1, | |
935 | typename _CharT, typename _Traits> | |
936 | friend std::basic_ostream<_CharT, _Traits>& | |
94986f6d PC |
937 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
938 | const std::discard_block_engine<_RandomNumberEngine1, | |
939 | __p1, __r1>&); | |
8e79468d BK |
940 | |
941 | /** | |
942 | * @brief Extracts the current state of a % subtract_with_carry_engine | |
943 | * random number generator engine @p __x from the input stream | |
944 | * @p __is. | |
945 | * | |
946 | * @param __is An input stream. | |
947 | * @param __x A %discard_block_engine random number generator engine. | |
948 | * | |
949 | * @returns The input stream with the state of @p __x extracted or in | |
950 | * an error state. | |
951 | */ | |
952 | template<typename _RandomNumberEngine1, size_t __p1, size_t __r1, | |
953 | typename _CharT, typename _Traits> | |
954 | friend std::basic_istream<_CharT, _Traits>& | |
94986f6d PC |
955 | operator>>(std::basic_istream<_CharT, _Traits>&, |
956 | std::discard_block_engine<_RandomNumberEngine1, | |
957 | __p1, __r1>&); | |
8e79468d BK |
958 | |
959 | private: | |
960 | _RandomNumberEngine _M_b; | |
961 | size_t _M_n; | |
962 | }; | |
963 | ||
964 | /** | |
965 | * Produces random numbers by combining random numbers from some base | |
966 | * engine to produce random numbers with a specifies number of bits @p __w. | |
967 | */ | |
968 | template<typename _RandomNumberEngine, size_t __w, typename _UIntType> | |
969 | class independent_bits_engine | |
970 | { | |
971 | static_assert(__w > 0U | |
94986f6d PC |
972 | && __w <= |
973 | static_cast<size_t>(numeric_limits<_UIntType>::digits), | |
974 | "template arguments out of bounds " | |
975 | "in independent_bits_engine"); | |
8e79468d BK |
976 | |
977 | public: | |
978 | /** The type of the generated random value. */ | |
979 | typedef _UIntType result_type; | |
980 | ||
981 | /** | |
982 | * @brief Constructs a default %independent_bits_engine engine. | |
983 | * | |
984 | * The underlying engine is default constructed as well. | |
985 | */ | |
986 | independent_bits_engine() | |
987 | : _M_b() { } | |
988 | ||
989 | /** | |
990 | * @brief Copy constructs a %independent_bits_engine engine. | |
991 | * | |
992 | * Copies an existing base class random number generator. | |
993 | * @param rng An existing (base class) engine object. | |
994 | */ | |
995 | explicit | |
996 | independent_bits_engine(const _RandomNumberEngine& __rne) | |
997 | : _M_b(__rne) { } | |
998 | ||
999 | /** | |
1000 | * @brief Move constructs a %independent_bits_engine engine. | |
1001 | * | |
1002 | * Copies an existing base class random number generator. | |
1003 | * @param rng An existing (base class) engine object. | |
1004 | */ | |
1005 | explicit | |
1006 | independent_bits_engine(_RandomNumberEngine&& __rne) | |
1007 | : _M_b(std::move(__rne)) { } | |
1008 | ||
1009 | /** | |
1010 | * @brief Seed constructs a %independent_bits_engine engine. | |
1011 | * | |
1012 | * Constructs the underlying generator engine seeded with @p __s. | |
1013 | * @param __s A seed value for the base class engine. | |
1014 | */ | |
1015 | explicit | |
1016 | independent_bits_engine(result_type __s) | |
1017 | : _M_b(__s) { } | |
1018 | ||
1019 | /** | |
1020 | * @brief Generator construct a %independent_bits_engine engine. | |
1021 | * | |
1022 | * @param __q A seed sequence. | |
1023 | */ | |
1024 | explicit | |
1025 | independent_bits_engine(seed_seq& __q) | |
1026 | : _M_b(__q) | |
1027 | { } | |
1028 | ||
1029 | /** | |
1030 | * @brief Reseeds the %independent_bits_engine object with the default | |
1031 | * seed for the underlying base class generator engine. | |
1032 | */ | |
1033 | void | |
1034 | seed() | |
1035 | { _M_b.seed(); } | |
1036 | ||
1037 | /** | |
1038 | * @brief Reseeds the %independent_bits_engine object with the default | |
1039 | * seed for the underlying base class generator engine. | |
1040 | */ | |
1041 | void | |
1042 | seed(result_type __s) | |
1043 | { _M_b.seed(__s); } | |
1044 | ||
1045 | /** | |
1046 | * @brief Reseeds the %independent_bits_engine object with the given | |
1047 | * seed sequence. | |
1048 | * @param __q A seed generator function. | |
1049 | */ | |
1050 | void | |
1051 | seed(seed_seq& __q) | |
1052 | { _M_b.seed(__q); } | |
1053 | ||
1054 | /** | |
1055 | * @brief Gets a const reference to the underlying generator engine | |
1056 | * object. | |
1057 | */ | |
1058 | const _RandomNumberEngine& | |
1059 | base() const | |
1060 | { return _M_b; } | |
1061 | ||
1062 | /** | |
1063 | * @brief Gets the minimum value in the generated random number range. | |
1064 | * | |
1065 | * @todo This should be constexpr. | |
1066 | */ | |
1067 | result_type | |
1068 | min() const | |
1069 | { return 0U; } | |
1070 | ||
1071 | /** | |
1072 | * @brief Gets the maximum value in the generated random number range. | |
1073 | * | |
1074 | * @todo This should be constexpr. | |
1075 | */ | |
1076 | result_type | |
1077 | max() const | |
1078 | { return __detail::_ShiftMin1<_UIntType, __w>::__value; } | |
1079 | ||
1080 | /** | |
1081 | * @brief Discard a sequence of random numbers. | |
1082 | * | |
1083 | * @todo Look for a faster way to do discard. | |
1084 | */ | |
1085 | void | |
1086 | discard(unsigned long long __z) | |
1087 | { | |
1088 | for (; __z != 0ULL; --__z) | |
1089 | (*this)(); | |
1090 | } | |
1091 | ||
1092 | /** | |
1093 | * @brief Gets the next value in the generated random number sequence. | |
1094 | */ | |
1095 | result_type | |
1096 | operator()(); | |
1097 | ||
1098 | /** | |
1099 | * @brief Compares two %independent_bits_engine random number generator | |
1100 | * objects of the same type for equality. | |
1101 | * | |
1102 | * @param __lhs A %independent_bits_engine random number generator | |
1103 | * object. | |
1104 | * @param __rhs Another %independent_bits_engine random number generator | |
1105 | * object. | |
1106 | * | |
1107 | * @returns true if the two objects are equal, false otherwise. | |
1108 | */ | |
1109 | friend bool | |
1110 | operator==(const independent_bits_engine& __lhs, | |
1111 | const independent_bits_engine& __rhs) | |
1112 | { return __lhs._M_b == __rhs._M_b; } | |
1113 | ||
1114 | /** | |
1115 | * @brief Extracts the current state of a % subtract_with_carry_engine | |
1116 | * random number generator engine @p __x from the input stream | |
1117 | * @p __is. | |
1118 | * | |
1119 | * @param __is An input stream. | |
1120 | * @param __x A %independent_bits_engine random number generator | |
1121 | * engine. | |
1122 | * | |
1123 | * @returns The input stream with the state of @p __x extracted or in | |
1124 | * an error state. | |
1125 | */ | |
1126 | template<typename _CharT, typename _Traits> | |
1127 | friend std::basic_istream<_CharT, _Traits>& | |
1128 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
94986f6d | 1129 | std::independent_bits_engine<_RandomNumberEngine, |
8e79468d BK |
1130 | __w, _UIntType>& __x) |
1131 | { | |
1132 | __is >> __x._M_b; | |
1133 | return __is; | |
1134 | } | |
1135 | ||
1136 | private: | |
1137 | _RandomNumberEngine _M_b; | |
1138 | }; | |
1139 | ||
1140 | /** | |
1141 | * @brief Inserts the current state of a %independent_bits_engine random | |
1142 | * number generator engine @p __x into the output stream @p __os. | |
1143 | * | |
1144 | * @param __os An output stream. | |
1145 | * @param __x A %independent_bits_engine random number generator engine. | |
1146 | * | |
1147 | * @returns The output stream with the state of @p __x inserted or in | |
1148 | * an error state. | |
1149 | */ | |
1150 | template<typename _RandomNumberEngine, size_t __w, typename _UIntType, | |
1151 | typename _CharT, typename _Traits> | |
1152 | std::basic_ostream<_CharT, _Traits>& | |
1153 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
94986f6d | 1154 | const std::independent_bits_engine<_RandomNumberEngine, |
8e79468d BK |
1155 | __w, _UIntType>& __x) |
1156 | { | |
1157 | __os << __x.base(); | |
1158 | return __os; | |
1159 | } | |
1160 | ||
1161 | /** | |
1162 | * @brief Produces random numbers by combining random numbers from some | |
1163 | * base engine to produce random numbers with a specifies number of bits | |
1164 | * @p __w. | |
1165 | */ | |
1166 | template<typename _RandomNumberEngine, size_t __k> | |
1167 | class shuffle_order_engine | |
1168 | { | |
1169 | static_assert(__k >= 1U, | |
1170 | "template arguments out of bounds" | |
1171 | " in shuffle_order_engine"); | |
1172 | ||
1173 | public: | |
1174 | /** The type of the generated random value. */ | |
1175 | typedef typename _RandomNumberEngine::result_type result_type; | |
1176 | ||
1177 | static const size_t table_size = __k; | |
1178 | ||
1179 | /** | |
1180 | * @brief Constructs a default %shuffle_order_engine engine. | |
1181 | * | |
1182 | * The underlying engine is default constructed as well. | |
1183 | */ | |
1184 | shuffle_order_engine() | |
1185 | : _M_b() | |
1186 | { _M_initialize(); } | |
1187 | ||
1188 | /** | |
1189 | * @brief Copy constructs a %shuffle_order_engine engine. | |
1190 | * | |
1191 | * Copies an existing base class random number generator. | |
1192 | * @param rng An existing (base class) engine object. | |
1193 | */ | |
1194 | explicit | |
1195 | shuffle_order_engine(const _RandomNumberEngine& __rne) | |
1196 | : _M_b(__rne) | |
1197 | { _M_initialize(); } | |
1198 | ||
1199 | /** | |
1200 | * @brief Move constructs a %shuffle_order_engine engine. | |
1201 | * | |
1202 | * Copies an existing base class random number generator. | |
1203 | * @param rng An existing (base class) engine object. | |
1204 | */ | |
1205 | explicit | |
1206 | shuffle_order_engine(_RandomNumberEngine&& __rne) | |
1207 | : _M_b(std::move(__rne)) | |
1208 | { _M_initialize(); } | |
1209 | ||
1210 | /** | |
1211 | * @brief Seed constructs a %shuffle_order_engine engine. | |
1212 | * | |
1213 | * Constructs the underlying generator engine seeded with @p __s. | |
1214 | * @param __s A seed value for the base class engine. | |
1215 | */ | |
1216 | explicit | |
1217 | shuffle_order_engine(result_type __s) | |
1218 | : _M_b(__s) | |
1219 | { _M_initialize(); } | |
1220 | ||
1221 | /** | |
1222 | * @brief Generator construct a %shuffle_order_engine engine. | |
1223 | * | |
1224 | * @param __q A seed sequence. | |
1225 | */ | |
1226 | explicit | |
1227 | shuffle_order_engine(seed_seq& __q) | |
1228 | : _M_b(__q) | |
1229 | { _M_initialize(); } | |
1230 | ||
1231 | /** | |
94986f6d PC |
1232 | * @brief Reseeds the %shuffle_order_engine object with the default seed |
1233 | for the underlying base class generator engine. | |
8e79468d BK |
1234 | */ |
1235 | void | |
1236 | seed() | |
1237 | { | |
1238 | _M_b.seed(); | |
1239 | _M_initialize(); | |
1240 | } | |
1241 | ||
1242 | /** | |
1243 | * @brief Reseeds the %shuffle_order_engine object with the default seed | |
1244 | * for the underlying base class generator engine. | |
1245 | */ | |
1246 | void | |
1247 | seed(result_type __s) | |
1248 | { | |
1249 | _M_b.seed(__s); | |
1250 | _M_initialize(); | |
1251 | } | |
1252 | ||
1253 | /** | |
1254 | * @brief Reseeds the %shuffle_order_engine object with the given seed | |
1255 | * sequence. | |
1256 | * @param __q A seed generator function. | |
1257 | */ | |
1258 | void | |
1259 | seed(seed_seq& __q) | |
1260 | { | |
1261 | _M_b.seed(__q); | |
1262 | _M_initialize(); | |
1263 | } | |
1264 | ||
1265 | /** | |
1266 | * Gets a const reference to the underlying generator engine object. | |
1267 | */ | |
1268 | const _RandomNumberEngine& | |
1269 | base() const | |
1270 | { return _M_b; } | |
1271 | ||
1272 | /** | |
1273 | * Gets the minimum value in the generated random number range. | |
1274 | * | |
1275 | * @todo This should be constexpr. | |
1276 | */ | |
1277 | result_type | |
1278 | min() const | |
1279 | { return _M_b.min(); } | |
1280 | ||
1281 | /** | |
1282 | * Gets the maximum value in the generated random number range. | |
1283 | * | |
1284 | * @todo This should be constexpr. | |
1285 | */ | |
1286 | result_type | |
1287 | max() const | |
1288 | { return _M_b.max(); } | |
1289 | ||
1290 | /** | |
1291 | * Discard a sequence of random numbers. | |
1292 | * | |
1293 | * @todo Look for a faster way to do discard. | |
1294 | */ | |
1295 | void | |
1296 | discard(unsigned long long __z) | |
1297 | { | |
1298 | for (; __z != 0ULL; --__z) | |
1299 | (*this)(); | |
1300 | } | |
1301 | ||
1302 | /** | |
1303 | * Gets the next value in the generated random number sequence. | |
1304 | */ | |
1305 | result_type | |
1306 | operator()(); | |
1307 | ||
1308 | /** | |
1309 | * Compares two %shuffle_order_engine random number generator objects | |
1310 | * of the same type for equality. | |
1311 | * | |
1312 | * @param __lhs A %shuffle_order_engine random number generator object. | |
1313 | * @param __rhs Another %shuffle_order_engine random number generator | |
1314 | * object. | |
1315 | * | |
1316 | * @returns true if the two objects are equal, false otherwise. | |
1317 | */ | |
1318 | friend bool | |
1319 | operator==(const shuffle_order_engine& __lhs, | |
1320 | const shuffle_order_engine& __rhs) | |
1321 | { return __lhs._M_b == __rhs._M_b; } | |
1322 | ||
1323 | /** | |
1324 | * @brief Inserts the current state of a %shuffle_order_engine random | |
1325 | * number generator engine @p __x into the output stream | |
1326 | @p __os. | |
1327 | * | |
1328 | * @param __os An output stream. | |
1329 | * @param __x A %shuffle_order_engine random number generator engine. | |
1330 | * | |
1331 | * @returns The output stream with the state of @p __x inserted or in | |
1332 | * an error state. | |
1333 | */ | |
1334 | template<typename _RandomNumberEngine1, size_t __k1, | |
1335 | typename _CharT, typename _Traits> | |
1336 | friend std::basic_ostream<_CharT, _Traits>& | |
94986f6d PC |
1337 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
1338 | const std::shuffle_order_engine<_RandomNumberEngine1, | |
1339 | __k1>&); | |
8e79468d BK |
1340 | |
1341 | /** | |
1342 | * @brief Extracts the current state of a % subtract_with_carry_engine | |
1343 | * random number generator engine @p __x from the input stream | |
1344 | * @p __is. | |
1345 | * | |
1346 | * @param __is An input stream. | |
1347 | * @param __x A %shuffle_order_engine random number generator engine. | |
1348 | * | |
1349 | * @returns The input stream with the state of @p __x extracted or in | |
1350 | * an error state. | |
1351 | */ | |
1352 | template<typename _RandomNumberEngine1, size_t __k1, | |
1353 | typename _CharT, typename _Traits> | |
1354 | friend std::basic_istream<_CharT, _Traits>& | |
94986f6d PC |
1355 | operator>>(std::basic_istream<_CharT, _Traits>&, |
1356 | std::shuffle_order_engine<_RandomNumberEngine1, __k1>&); | |
8e79468d BK |
1357 | |
1358 | private: | |
1359 | void _M_initialize() | |
1360 | { | |
1361 | for (size_t __i = 0; __i < __k; ++__i) | |
1362 | _M_v[__i] = _M_b(); | |
1363 | _M_y = _M_b(); | |
1364 | } | |
1365 | ||
1366 | _RandomNumberEngine _M_b; | |
1367 | result_type _M_v[__k]; | |
1368 | result_type _M_y; | |
1369 | }; | |
1370 | ||
1371 | /** | |
1372 | * The classic Minimum Standard rand0 of Lewis, Goodman, and Miller. | |
1373 | */ | |
1374 | typedef linear_congruential_engine<uint_fast32_t, 16807UL, 0UL, 2147483647UL> | |
1375 | minstd_rand0; | |
1376 | ||
1377 | /** | |
1378 | * An alternative LCR (Lehmer Generator function) . | |
1379 | */ | |
1380 | typedef linear_congruential_engine<uint_fast32_t, 48271UL, 0UL, 2147483647UL> | |
1381 | minstd_rand; | |
1382 | ||
1383 | /** | |
1384 | * The classic Mersenne Twister. | |
1385 | * | |
1386 | * Reference: | |
1387 | * M. Matsumoto and T. Nishimura, "Mersenne Twister: A 623-Dimensionally | |
1388 | * Equidistributed Uniform Pseudo-Random Number Generator", ACM Transactions | |
1389 | * on Modeling and Computer Simulation, Vol. 8, No. 1, January 1998, pp 3-30. | |
1390 | */ | |
1391 | typedef mersenne_twister_engine< | |
1392 | uint_fast32_t, | |
1393 | 32, 624, 397, 31, | |
1394 | 0x9908b0dfUL, 11, | |
1395 | 0xffffffffUL, 7, | |
1396 | 0x9d2c5680UL, 15, | |
1397 | 0xefc60000UL, 18, 1812433253UL> mt19937; | |
1398 | ||
1399 | /** | |
1400 | * An alternative Mersenne Twister. | |
1401 | */ | |
1402 | typedef mersenne_twister_engine< | |
1403 | uint_fast64_t, | |
1404 | 64, 312, 156, 31, | |
1405 | 0xb5026f5aa96619e9ULL, 29, | |
1406 | 0x5555555555555555ULL, 17, | |
1407 | 0x71d67fffeda60000ULL, 37, | |
1408 | 0xfff7eee000000000ULL, 43, | |
1409 | 6364136223846793005ULL> mt19937_64; | |
1410 | ||
1411 | /** | |
1412 | * . | |
1413 | */ | |
1414 | typedef subtract_with_carry_engine<uint_fast32_t, 24, 10, 24> | |
1415 | ranlux24_base; | |
1416 | ||
1417 | typedef discard_block_engine<ranlux24_base, 223, 23> ranlux24; | |
1418 | ||
1419 | typedef subtract_with_carry_engine<uint_fast64_t, 48, 5, 12> | |
1420 | ranlux48_base; | |
1421 | ||
1422 | typedef discard_block_engine<ranlux48_base, 389, 11> ranlux48; | |
1423 | ||
1424 | /** | |
1425 | * . | |
1426 | */ | |
1427 | typedef shuffle_order_engine<minstd_rand0, 256> knuth_b; | |
1428 | ||
1429 | /** | |
1430 | * . | |
1431 | */ | |
1432 | typedef minstd_rand0 default_random_engine; | |
1433 | ||
1434 | /** | |
1435 | * A standard interface to a platform-specific non-deterministic | |
1436 | * random number generator (if any are available). | |
1437 | */ | |
1438 | class random_device | |
1439 | { | |
1440 | public: | |
1441 | /** The type of the generated random value. */ | |
1442 | typedef unsigned int result_type; | |
1443 | ||
1444 | // constructors, destructors and member functions | |
1445 | ||
1446 | #ifdef _GLIBCXX_USE_RANDOM_TR1 | |
1447 | ||
1448 | explicit | |
1449 | random_device(const std::string& __token = "/dev/urandom") | |
1450 | { | |
1451 | if ((__token != "/dev/urandom" && __token != "/dev/random") | |
1452 | || !(_M_file = std::fopen(__token.c_str(), "rb"))) | |
1453 | std::__throw_runtime_error(__N("random_device::" | |
1454 | "random_device(const std::string&)")); | |
1455 | } | |
1456 | ||
1457 | ~random_device() | |
1458 | { std::fclose(_M_file); } | |
1459 | ||
1460 | #else | |
1461 | ||
1462 | explicit | |
1463 | random_device(const std::string& __token = "mt19937") | |
1464 | : _M_mt(_M_strtoul(__token)) { } | |
1465 | ||
1466 | private: | |
1467 | static unsigned long | |
1468 | _M_strtoul(const std::string& __str) | |
1469 | { | |
1470 | unsigned long __ret = 5489UL; | |
1471 | if (__str != "mt19937") | |
1472 | { | |
1473 | const char* __nptr = __str.c_str(); | |
1474 | char* __endptr; | |
1475 | __ret = std::strtoul(__nptr, &__endptr, 0); | |
1476 | if (*__nptr == '\0' || *__endptr != '\0') | |
1477 | std::__throw_runtime_error(__N("random_device::_M_strtoul" | |
1478 | "(const std::string&)")); | |
1479 | } | |
1480 | return __ret; | |
1481 | } | |
1482 | ||
1483 | public: | |
1484 | ||
1485 | #endif | |
1486 | ||
1487 | result_type | |
1488 | min() const | |
1489 | { return std::numeric_limits<result_type>::min(); } | |
1490 | ||
1491 | result_type | |
1492 | max() const | |
1493 | { return std::numeric_limits<result_type>::max(); } | |
1494 | ||
1495 | double | |
1496 | entropy() const | |
1497 | { return 0.0; } | |
1498 | ||
1499 | result_type | |
1500 | operator()() | |
1501 | { | |
1502 | #ifdef _GLIBCXX_USE_RANDOM_TR1 | |
1503 | result_type __ret; | |
1504 | std::fread(reinterpret_cast<void*>(&__ret), sizeof(result_type), | |
1505 | 1, _M_file); | |
1506 | return __ret; | |
1507 | #else | |
1508 | return _M_mt(); | |
1509 | #endif | |
1510 | } | |
1511 | ||
1512 | // No copy functions. | |
1513 | random_device(const random_device&) = delete; | |
1514 | void operator=(const random_device&) = delete; | |
1515 | ||
1516 | private: | |
1517 | ||
1518 | #ifdef _GLIBCXX_USE_RANDOM_TR1 | |
1519 | FILE* _M_file; | |
1520 | #else | |
1521 | mt19937 _M_mt; | |
1522 | #endif | |
1523 | }; | |
1524 | ||
1525 | /* @} */ // group std_random_generators | |
1526 | ||
1527 | /** | |
1528 | * @addtogroup std_random_distributions Random Number Distributions | |
1529 | * @ingroup std_random | |
1530 | * @{ | |
1531 | */ | |
1532 | ||
1533 | /** | |
1534 | * @addtogroup std_random_distributions_uniform Uniform Distributions | |
1535 | * @ingroup std_random_distributions | |
1536 | * @{ | |
1537 | */ | |
1538 | ||
1539 | /** | |
1540 | * @brief Uniform discrete distribution for random numbers. | |
1541 | * A discrete random distribution on the range @f$[min, max]@f$ with equal | |
1542 | * probability throughout the range. | |
1543 | */ | |
1544 | template<typename _IntType = int> | |
1545 | class uniform_int_distribution | |
1546 | { | |
1547 | __glibcxx_class_requires(_IntType, _IntegerConcept) | |
1548 | ||
1549 | public: | |
1550 | /** The type of the range of the distribution. */ | |
1551 | typedef _IntType result_type; | |
1552 | /** Parameter type. */ | |
1553 | struct param_type | |
1554 | { | |
1555 | typedef uniform_int_distribution<_IntType> distribution_type; | |
1556 | ||
1557 | explicit | |
1558 | param_type(_IntType __a = 0, _IntType __b = 9) | |
1559 | : _M_a(__a), _M_b(__b) | |
1560 | { | |
1561 | _GLIBCXX_DEBUG_ASSERT(_M_a <= _M_b); | |
1562 | } | |
1563 | ||
1564 | result_type | |
1565 | a() const | |
1566 | { return _M_a; } | |
1567 | ||
1568 | result_type | |
1569 | b() const | |
1570 | { return _M_b; } | |
1571 | ||
1572 | friend bool | |
1573 | operator==(const param_type& __p1, const param_type& __p2) | |
1574 | { return (__p1._M_a == __p2._M_a) && (__p1._M_b == __p2._M_b); } | |
1575 | ||
1576 | private: | |
1577 | _IntType _M_a; | |
1578 | _IntType _M_b; | |
1579 | }; | |
1580 | ||
1581 | public: | |
1582 | /** | |
1583 | * @brief Constructs a uniform distribution object. | |
1584 | */ | |
1585 | explicit | |
1586 | uniform_int_distribution(_IntType __a = 0, _IntType __b = 9) | |
1587 | : _M_param(__a, __b) | |
1588 | { } | |
1589 | ||
1590 | explicit | |
1591 | uniform_int_distribution(const param_type& __p) | |
1592 | : _M_param(__p) | |
1593 | { } | |
1594 | ||
1595 | /** | |
1596 | * @brief Resets the distribution state. | |
1597 | * | |
1598 | * Does nothing for the uniform integer distribution. | |
1599 | */ | |
1600 | void | |
1601 | reset() { } | |
1602 | ||
1603 | result_type | |
1604 | a() const | |
1605 | { return _M_param.a(); } | |
1606 | ||
1607 | result_type | |
1608 | b() const | |
1609 | { return _M_param.b(); } | |
1610 | ||
1611 | /** | |
1612 | * @brief Returns the inclusive lower bound of the distribution range. | |
1613 | */ | |
1614 | result_type | |
1615 | min() const | |
1616 | { return this->a(); } | |
1617 | ||
1618 | /** | |
1619 | * @brief Returns the inclusive upper bound of the distribution range. | |
1620 | */ | |
1621 | result_type | |
1622 | max() const | |
1623 | { return this->b(); } | |
1624 | ||
1625 | /** | |
1626 | * @brief Returns the parameter set of the distribution. | |
1627 | */ | |
1628 | param_type | |
1629 | param() const | |
1630 | { return _M_param; } | |
1631 | ||
1632 | /** | |
1633 | * @brief Sets the parameter set of the distribution. | |
1634 | * @param __param The new parameter set of the distribution. | |
1635 | */ | |
1636 | void | |
1637 | param(const param_type& __param) | |
1638 | { _M_param = __param; } | |
1639 | ||
1640 | /** | |
1641 | * Gets a uniformly distributed random number in the range | |
1642 | * @f$(min, max)@f$. | |
1643 | */ | |
1644 | template<typename _UniformRandomNumberGenerator> | |
1645 | result_type | |
1646 | operator()(_UniformRandomNumberGenerator& __urng) | |
1647 | { | |
1648 | typedef typename _UniformRandomNumberGenerator::result_type | |
1649 | _UResult_type; | |
1650 | return _M_call(__urng, this->a(), this->b(), | |
1651 | typename is_integral<_UResult_type>::type()); | |
1652 | } | |
1653 | ||
1654 | /** | |
1655 | * Gets a uniform random number in the range @f$[0, n)@f$. | |
1656 | * | |
1657 | * This function is aimed at use with std::random_shuffle. | |
1658 | */ | |
1659 | template<typename _UniformRandomNumberGenerator> | |
1660 | result_type | |
1661 | operator()(_UniformRandomNumberGenerator& __urng, | |
1662 | const param_type& __p) | |
1663 | { | |
1664 | typedef typename _UniformRandomNumberGenerator::result_type | |
1665 | _UResult_type; | |
1666 | return _M_call(__urng, __p.a(), __p.b(), | |
1667 | typename is_integral<_UResult_type>::type()); | |
1668 | } | |
1669 | ||
1670 | private: | |
1671 | template<typename _UniformRandomNumberGenerator> | |
1672 | result_type | |
1673 | _M_call(_UniformRandomNumberGenerator& __urng, | |
1674 | result_type __min, result_type __max, true_type); | |
1675 | ||
1676 | template<typename _UniformRandomNumberGenerator> | |
1677 | result_type | |
1678 | _M_call(_UniformRandomNumberGenerator& __urng, | |
1679 | result_type __min, result_type __max, false_type) | |
1680 | { | |
1681 | return result_type((__urng() - __urng.min()) | |
1682 | / (__urng.max() - __urng.min()) | |
1683 | * (__max - __min + 1)) + __min; | |
1684 | } | |
1685 | ||
1686 | param_type _M_param; | |
1687 | }; | |
1688 | ||
1689 | /** | |
1690 | * @brief Return true if two uniform integer distributions have | |
1691 | * the same parameters. | |
1692 | */ | |
1693 | template<typename _IntType> | |
94986f6d PC |
1694 | inline bool |
1695 | operator==(const std::uniform_int_distribution<_IntType>& __d1, | |
1696 | const std::uniform_int_distribution<_IntType>& __d2) | |
8e79468d BK |
1697 | { return __d1.param() == __d2.param(); } |
1698 | ||
1699 | /** | |
1700 | * @brief Inserts a %uniform_int_distribution random number | |
1701 | * distribution @p __x into the output stream @p os. | |
1702 | * | |
1703 | * @param __os An output stream. | |
1704 | * @param __x A %uniform_int_distribution random number distribution. | |
1705 | * | |
1706 | * @returns The output stream with the state of @p __x inserted or in | |
1707 | * an error state. | |
1708 | */ | |
1709 | template<typename _IntType, typename _CharT, typename _Traits> | |
1710 | std::basic_ostream<_CharT, _Traits>& | |
94986f6d PC |
1711 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
1712 | const std::uniform_int_distribution<_IntType>&); | |
8e79468d BK |
1713 | |
1714 | /** | |
1715 | * @brief Extracts a %uniform_int_distribution random number distribution | |
1716 | * @p __x from the input stream @p __is. | |
1717 | * | |
1718 | * @param __is An input stream. | |
1719 | * @param __x A %uniform_int_distribution random number generator engine. | |
1720 | * | |
1721 | * @returns The input stream with @p __x extracted or in an error state. | |
1722 | */ | |
1723 | template<typename _IntType, typename _CharT, typename _Traits> | |
1724 | std::basic_istream<_CharT, _Traits>& | |
94986f6d PC |
1725 | operator>>(std::basic_istream<_CharT, _Traits>&, |
1726 | std::uniform_int_distribution<_IntType>&); | |
8e79468d BK |
1727 | |
1728 | ||
1729 | /** | |
1730 | * @brief Uniform continuous distribution for random numbers. | |
1731 | * | |
1732 | * A continuous random distribution on the range [min, max) with equal | |
1733 | * probability throughout the range. The URNG should be real-valued and | |
1734 | * deliver number in the range [0, 1). | |
1735 | */ | |
1736 | template<typename _RealType = double> | |
1737 | class uniform_real_distribution | |
1738 | { | |
1739 | public: | |
1740 | /** The type of the range of the distribution. */ | |
1741 | typedef _RealType result_type; | |
1742 | /** Parameter type. */ | |
1743 | struct param_type | |
1744 | { | |
1745 | typedef uniform_real_distribution<_RealType> distribution_type; | |
1746 | ||
1747 | explicit | |
1748 | param_type(_RealType __a = _RealType(0), | |
1749 | _RealType __b = _RealType(1)) | |
1750 | : _M_a(__a), _M_b(__b) | |
1751 | { | |
1752 | _GLIBCXX_DEBUG_ASSERT(_M_a <= _M_b); | |
1753 | } | |
1754 | ||
1755 | result_type | |
1756 | a() const | |
1757 | { return _M_a; } | |
1758 | ||
1759 | result_type | |
1760 | b() const | |
1761 | { return _M_b; } | |
1762 | ||
1763 | friend bool | |
1764 | operator==(const param_type& __p1, const param_type& __p2) | |
1765 | { return (__p1._M_a == __p2._M_a) && (__p1._M_b == __p2._M_b); } | |
1766 | ||
1767 | private: | |
1768 | _RealType _M_a; | |
1769 | _RealType _M_b; | |
1770 | }; | |
1771 | ||
1772 | public: | |
1773 | /** | |
1774 | * @brief Constructs a uniform_real_distribution object. | |
1775 | * | |
1776 | * @param __min [IN] The lower bound of the distribution. | |
1777 | * @param __max [IN] The upper bound of the distribution. | |
1778 | */ | |
1779 | explicit | |
1780 | uniform_real_distribution(_RealType __a = _RealType(0), | |
1781 | _RealType __b = _RealType(1)) | |
1782 | : _M_param(__a, __b) | |
1783 | { } | |
1784 | ||
1785 | explicit | |
1786 | uniform_real_distribution(const param_type& __p) | |
1787 | : _M_param(__p) | |
1788 | { } | |
1789 | ||
1790 | /** | |
1791 | * @brief Resets the distribution state. | |
1792 | * | |
1793 | * Does nothing for the uniform real distribution. | |
1794 | */ | |
1795 | void | |
1796 | reset() { } | |
1797 | ||
1798 | result_type | |
1799 | a() const | |
1800 | { return _M_param.a(); } | |
1801 | ||
1802 | result_type | |
1803 | b() const | |
1804 | { return _M_param.b(); } | |
1805 | ||
1806 | /** | |
1807 | * @brief Returns the inclusive lower bound of the distribution range. | |
1808 | */ | |
1809 | result_type | |
1810 | min() const | |
1811 | { return this->a(); } | |
1812 | ||
1813 | /** | |
1814 | * @brief Returns the inclusive upper bound of the distribution range. | |
1815 | */ | |
1816 | result_type | |
1817 | max() const | |
1818 | { return this->b(); } | |
1819 | ||
1820 | /** | |
1821 | * @brief Returns the parameter set of the distribution. | |
1822 | */ | |
1823 | param_type | |
1824 | param() const | |
1825 | { return _M_param; } | |
1826 | ||
1827 | /** | |
1828 | * @brief Sets the parameter set of the distribution. | |
1829 | * @param __param The new parameter set of the distribution. | |
1830 | */ | |
1831 | void | |
1832 | param(const param_type& __param) | |
1833 | { _M_param = __param; } | |
1834 | ||
1835 | template<typename _UniformRandomNumberGenerator> | |
1836 | result_type | |
1837 | operator()(_UniformRandomNumberGenerator& __urng) | |
1838 | { | |
1839 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
1840 | __aurng(__urng); | |
1841 | return (__aurng() * (this->b() - this->a())) + this->a(); | |
1842 | } | |
1843 | ||
1844 | template<typename _UniformRandomNumberGenerator> | |
1845 | result_type | |
1846 | operator()(_UniformRandomNumberGenerator& __urng, | |
1847 | const param_type& __p) | |
1848 | { | |
1849 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
1850 | __aurng(__urng); | |
1851 | return (__aurng() * (__p.b() - __p.a())) + __p.a(); | |
1852 | } | |
1853 | ||
1854 | private: | |
1855 | param_type _M_param; | |
1856 | }; | |
1857 | ||
1858 | /** | |
1859 | * @brief Return true if two uniform real distributions have | |
1860 | * the same parameters. | |
1861 | */ | |
1862 | template<typename _IntType> | |
94986f6d PC |
1863 | inline bool |
1864 | operator==(const std::uniform_real_distribution<_IntType>& __d1, | |
1865 | const std::uniform_real_distribution<_IntType>& __d2) | |
8e79468d BK |
1866 | { return __d1.param() == __d2.param(); } |
1867 | ||
1868 | /** | |
1869 | * @brief Inserts a %uniform_real_distribution random number | |
1870 | * distribution @p __x into the output stream @p __os. | |
1871 | * | |
1872 | * @param __os An output stream. | |
1873 | * @param __x A %uniform_real_distribution random number distribution. | |
1874 | * | |
1875 | * @returns The output stream with the state of @p __x inserted or in | |
1876 | * an error state. | |
1877 | */ | |
1878 | template<typename _RealType, typename _CharT, typename _Traits> | |
1879 | std::basic_ostream<_CharT, _Traits>& | |
94986f6d PC |
1880 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
1881 | const std::uniform_real_distribution<_RealType>&); | |
8e79468d BK |
1882 | |
1883 | /** | |
1884 | * @brief Extracts a %uniform_real_distribution random number distribution | |
1885 | * @p __x from the input stream @p __is. | |
1886 | * | |
1887 | * @param __is An input stream. | |
1888 | * @param __x A %uniform_real_distribution random number generator engine. | |
1889 | * | |
1890 | * @returns The input stream with @p __x extracted or in an error state. | |
1891 | */ | |
1892 | template<typename _RealType, typename _CharT, typename _Traits> | |
1893 | std::basic_istream<_CharT, _Traits>& | |
94986f6d PC |
1894 | operator>>(std::basic_istream<_CharT, _Traits>&, |
1895 | std::uniform_real_distribution<_RealType>&); | |
8e79468d BK |
1896 | |
1897 | /* @} */ // group std_random_distributions_uniform | |
1898 | ||
1899 | /** | |
1900 | * @addtogroup std_random_distributions_normal Normal Distributions | |
1901 | * @ingroup std_random_distributions | |
1902 | * @{ | |
1903 | */ | |
1904 | ||
1905 | /** | |
1906 | * @brief A normal continuous distribution for random numbers. | |
1907 | * | |
1908 | * The formula for the normal probability density function is | |
1909 | * @f$ p(x|\mu,\sigma) = \frac{1}{\sigma \sqrt{2 \pi}} | |
1910 | * e^{- \frac{{x - \mu}^ {2}}{2 \sigma ^ {2}} } @f$. | |
1911 | */ | |
1912 | template<typename _RealType = double> | |
1913 | class normal_distribution | |
1914 | { | |
1915 | public: | |
1916 | /** The type of the range of the distribution. */ | |
1917 | typedef _RealType result_type; | |
1918 | /** Parameter type. */ | |
1919 | struct param_type | |
1920 | { | |
1921 | typedef normal_distribution<_RealType> distribution_type; | |
1922 | ||
1923 | explicit | |
1924 | param_type(_RealType __mean = _RealType(0), | |
1925 | _RealType __stddev = _RealType(1)) | |
1926 | : _M_mean(__mean), _M_stddev(__stddev) | |
1927 | { | |
1928 | _GLIBCXX_DEBUG_ASSERT(_M_stddev > _RealType(0)); | |
1929 | } | |
1930 | ||
1931 | _RealType | |
1932 | mean() const | |
1933 | { return _M_mean; } | |
1934 | ||
1935 | _RealType | |
1936 | stddev() const | |
1937 | { return _M_stddev; } | |
1938 | ||
1939 | friend bool | |
1940 | operator==(const param_type& __p1, const param_type& __p2) | |
1941 | { return (__p1._M_mean == __p2._M_mean) | |
1942 | && (__p1._M_stddev == __p2._M_stddev); } | |
1943 | ||
1944 | private: | |
1945 | _RealType _M_mean; | |
1946 | _RealType _M_stddev; | |
1947 | }; | |
1948 | ||
1949 | public: | |
1950 | /** | |
1951 | * Constructs a normal distribution with parameters @f$ mean @f$ and | |
1952 | * standard deviation. | |
1953 | */ | |
1954 | explicit | |
1955 | normal_distribution(result_type __mean = result_type(0), | |
1956 | result_type __stddev = result_type(1)) | |
1957 | : _M_param(__mean, __stddev), _M_saved_available(false) | |
1958 | { } | |
1959 | ||
1960 | explicit | |
1961 | normal_distribution(const param_type& __p) | |
1962 | : _M_param(__p), _M_saved_available(false) | |
1963 | { } | |
1964 | ||
1965 | /** | |
1966 | * @brief Resets the distribution state. | |
1967 | */ | |
1968 | void | |
1969 | reset() | |
1970 | { _M_saved_available = false; } | |
1971 | ||
1972 | /** | |
1973 | * @brief Returns the mean of the distribution. | |
1974 | */ | |
1975 | _RealType | |
1976 | mean() const | |
1977 | { return _M_param.mean(); } | |
1978 | ||
1979 | /** | |
1980 | * @brief Returns the standard deviation of the distribution. | |
1981 | */ | |
1982 | _RealType | |
1983 | stddev() const | |
1984 | { return _M_param.stddev(); } | |
1985 | ||
1986 | /** | |
1987 | * @brief Returns the parameter set of the distribution. | |
1988 | */ | |
1989 | param_type | |
1990 | param() const | |
1991 | { return _M_param; } | |
1992 | ||
1993 | /** | |
1994 | * @brief Sets the parameter set of the distribution. | |
1995 | * @param __param The new parameter set of the distribution. | |
1996 | */ | |
1997 | void | |
1998 | param(const param_type& __param) | |
1999 | { _M_param = __param; } | |
2000 | ||
2001 | /** | |
2002 | * @brief Returns the greatest lower bound value of the distribution. | |
2003 | */ | |
2004 | result_type | |
2005 | min() const | |
2006 | { return std::numeric_limits<result_type>::min(); } | |
2007 | ||
2008 | /** | |
2009 | * @brief Returns the least upper bound value of the distribution. | |
2010 | */ | |
2011 | result_type | |
2012 | max() const | |
2013 | { return std::numeric_limits<result_type>::max(); } | |
2014 | ||
2015 | template<typename _UniformRandomNumberGenerator> | |
2016 | result_type | |
2017 | operator()(_UniformRandomNumberGenerator& __urng) | |
2018 | { return this->operator()(__urng, this->param()); } | |
2019 | ||
2020 | template<typename _UniformRandomNumberGenerator> | |
2021 | result_type | |
2022 | operator()(_UniformRandomNumberGenerator& __urng, | |
2023 | const param_type& __p); | |
2024 | ||
2025 | /** | |
2026 | * @brief Return true if two normal distributions have | |
2027 | * the same parameters. | |
2028 | */ | |
2029 | template<typename _RealType1> | |
2030 | friend bool | |
94986f6d PC |
2031 | operator==(const std::normal_distribution<_RealType1>& __d1, |
2032 | const std::normal_distribution<_RealType1>& __d2); | |
8e79468d BK |
2033 | |
2034 | /** | |
2035 | * @brief Inserts a %normal_distribution random number distribution | |
2036 | * @p __x into the output stream @p __os. | |
2037 | * | |
2038 | * @param __os An output stream. | |
2039 | * @param __x A %normal_distribution random number distribution. | |
2040 | * | |
2041 | * @returns The output stream with the state of @p __x inserted or in | |
2042 | * an error state. | |
2043 | */ | |
2044 | template<typename _RealType1, typename _CharT, typename _Traits> | |
2045 | friend std::basic_ostream<_CharT, _Traits>& | |
94986f6d PC |
2046 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
2047 | const std::normal_distribution<_RealType1>&); | |
8e79468d BK |
2048 | |
2049 | /** | |
2050 | * @brief Extracts a %normal_distribution random number distribution | |
2051 | * @p __x from the input stream @p __is. | |
2052 | * | |
2053 | * @param __is An input stream. | |
2054 | * @param __x A %normal_distribution random number generator engine. | |
2055 | * | |
2056 | * @returns The input stream with @p __x extracted or in an error | |
2057 | * state. | |
2058 | */ | |
2059 | template<typename _RealType1, typename _CharT, typename _Traits> | |
2060 | friend std::basic_istream<_CharT, _Traits>& | |
94986f6d PC |
2061 | operator>>(std::basic_istream<_CharT, _Traits>&, |
2062 | std::normal_distribution<_RealType1>&); | |
8e79468d BK |
2063 | |
2064 | private: | |
2065 | param_type _M_param; | |
2066 | result_type _M_saved; | |
2067 | bool _M_saved_available; | |
2068 | }; | |
2069 | ||
2070 | ||
2071 | /** | |
2072 | * @brief A lognormal_distribution random number distribution. | |
2073 | * | |
2074 | * The formula for the normal probability mass function is | |
2075 | * @f$ p(x|m,s) = \frac{1}{sx\sqrt{2\pi}} | |
2076 | * \exp{-\frac{(\ln{x} - m)^2}{2s^2}} @f$ | |
2077 | */ | |
2078 | template<typename _RealType = double> | |
2079 | class lognormal_distribution | |
2080 | { | |
2081 | public: | |
2082 | /** The type of the range of the distribution. */ | |
2083 | typedef _RealType result_type; | |
2084 | /** Parameter type. */ | |
2085 | struct param_type | |
2086 | { | |
2087 | typedef lognormal_distribution<_RealType> distribution_type; | |
2088 | ||
2089 | explicit | |
2090 | param_type(_RealType __m = _RealType(0), | |
2091 | _RealType __s = _RealType(1)) | |
2092 | : _M_m(__m), _M_s(__s) | |
2093 | { } | |
2094 | ||
2095 | _RealType | |
2096 | m() const | |
2097 | { return _M_m; } | |
2098 | ||
2099 | _RealType | |
2100 | s() const | |
2101 | { return _M_s; } | |
2102 | ||
2103 | friend bool | |
2104 | operator==(const param_type& __p1, const param_type& __p2) | |
2105 | { return (__p1._M_m == __p2._M_m) && (__p1._M_s == __p2._M_s); } | |
2106 | ||
2107 | private: | |
2108 | _RealType _M_m; | |
2109 | _RealType _M_s; | |
2110 | }; | |
2111 | ||
2112 | explicit | |
2113 | lognormal_distribution(_RealType __m = _RealType(0), | |
2114 | _RealType __s = _RealType(1)) | |
2115 | : _M_param(__m, __s) | |
2116 | { } | |
2117 | ||
2118 | explicit | |
2119 | lognormal_distribution(const param_type& __p) | |
2120 | : _M_param(__p) | |
2121 | { } | |
2122 | ||
2123 | /** | |
2124 | * Resets the distribution state. | |
2125 | */ | |
2126 | void | |
2127 | reset() | |
2128 | { } | |
2129 | ||
2130 | /** | |
2131 | * | |
2132 | */ | |
2133 | _RealType | |
2134 | m() const | |
2135 | { return _M_param.m(); } | |
2136 | ||
2137 | _RealType | |
2138 | s() const | |
2139 | { return _M_param.s(); } | |
2140 | ||
2141 | /** | |
2142 | * @brief Returns the parameter set of the distribution. | |
2143 | */ | |
2144 | param_type | |
2145 | param() const | |
2146 | { return _M_param; } | |
2147 | ||
2148 | /** | |
2149 | * @brief Sets the parameter set of the distribution. | |
2150 | * @param __param The new parameter set of the distribution. | |
2151 | */ | |
2152 | void | |
2153 | param(const param_type& __param) | |
2154 | { _M_param = __param; } | |
2155 | ||
2156 | /** | |
2157 | * @brief Returns the greatest lower bound value of the distribution. | |
2158 | */ | |
2159 | result_type | |
2160 | min() const | |
2161 | { return result_type(0); } | |
2162 | ||
2163 | /** | |
2164 | * @brief Returns the least upper bound value of the distribution. | |
2165 | */ | |
2166 | result_type | |
2167 | max() const | |
2168 | { return std::numeric_limits<result_type>::max(); } | |
2169 | ||
2170 | template<typename _UniformRandomNumberGenerator> | |
2171 | result_type | |
2172 | operator()(_UniformRandomNumberGenerator& __urng) | |
2173 | { return this->operator()(__urng, this->param()); } | |
2174 | ||
2175 | template<typename _UniformRandomNumberGenerator> | |
2176 | result_type | |
2177 | operator()(_UniformRandomNumberGenerator& __urng, | |
2178 | const param_type& __p); | |
2179 | ||
2180 | private: | |
2181 | param_type _M_param; | |
2182 | }; | |
2183 | ||
2184 | /** | |
2185 | * @brief Return true if two lognormal distributions have | |
2186 | * the same parameters. | |
2187 | */ | |
2188 | template<typename _RealType> | |
94986f6d PC |
2189 | inline bool |
2190 | operator==(const std::lognormal_distribution<_RealType>& __d1, | |
2191 | const std::lognormal_distribution<_RealType>& __d2) | |
8e79468d BK |
2192 | { return __d1.param() == __d2.param(); } |
2193 | ||
2194 | /** | |
2195 | * @brief Inserts a %lognormal_distribution random number distribution | |
2196 | * @p __x into the output stream @p __os. | |
2197 | * | |
2198 | * @param __os An output stream. | |
2199 | * @param __x A %lognormal_distribution random number distribution. | |
2200 | * | |
2201 | * @returns The output stream with the state of @p __x inserted or in | |
2202 | * an error state. | |
2203 | */ | |
2204 | template<typename _RealType, typename _CharT, typename _Traits> | |
2205 | std::basic_ostream<_CharT, _Traits>& | |
94986f6d PC |
2206 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
2207 | const std::lognormal_distribution<_RealType>&); | |
8e79468d BK |
2208 | |
2209 | /** | |
2210 | * @brief Extracts a %lognormal_distribution random number distribution | |
2211 | * @p __x from the input stream @p __is. | |
2212 | * | |
2213 | * @param __is An input stream. | |
2214 | * @param __x A %lognormal_distribution random number | |
2215 | * generator engine. | |
2216 | * | |
2217 | * @returns The input stream with @p __x extracted or in an error state. | |
2218 | */ | |
2219 | template<typename _RealType, typename _CharT, typename _Traits> | |
2220 | std::basic_istream<_CharT, _Traits>& | |
94986f6d PC |
2221 | operator>>(std::basic_istream<_CharT, _Traits>&, |
2222 | std::lognormal_distribution<_RealType>&); | |
8e79468d BK |
2223 | |
2224 | ||
2225 | /** | |
2226 | * @brief A chi_squared_distribution random number distribution. | |
2227 | * | |
2228 | * The formula for the normal probability mass function is | |
2229 | * @f$ p(x|n) = \frac{x^{(n/2) - 1}e^{-x/2}}{\Gamma(n/2) 2^{n/2}} @f$ | |
2230 | */ | |
2231 | template<typename _RealType = double> | |
2232 | class chi_squared_distribution | |
2233 | { | |
2234 | public: | |
2235 | /** The type of the range of the distribution. */ | |
2236 | typedef _RealType result_type; | |
2237 | /** Parameter type. */ | |
2238 | struct param_type | |
2239 | { | |
2240 | typedef chi_squared_distribution<_RealType> distribution_type; | |
2241 | ||
2242 | explicit | |
2243 | param_type(_RealType __n = _RealType(1)) | |
2244 | : _M_n(__n) | |
2245 | { } | |
2246 | ||
2247 | _RealType | |
2248 | n() const | |
2249 | { return _M_n; } | |
2250 | ||
2251 | friend bool | |
2252 | operator==(const param_type& __p1, const param_type& __p2) | |
2253 | { return __p1._M_n == __p2._M_n; } | |
2254 | ||
2255 | private: | |
2256 | _RealType _M_n; | |
2257 | }; | |
2258 | ||
2259 | explicit | |
2260 | chi_squared_distribution(_RealType __n = _RealType(1)) | |
2261 | : _M_param(__n) | |
2262 | { } | |
2263 | ||
2264 | explicit | |
2265 | chi_squared_distribution(const param_type& __p) | |
2266 | : _M_param(__p) | |
2267 | { } | |
2268 | ||
2269 | /** | |
2270 | * @brief Resets the distribution state. | |
2271 | */ | |
2272 | void | |
2273 | reset() | |
2274 | { } | |
2275 | ||
2276 | /** | |
2277 | * | |
2278 | */ | |
2279 | _RealType | |
2280 | n() const | |
2281 | { return _M_param.n(); } | |
2282 | ||
2283 | /** | |
2284 | * @brief Returns the parameter set of the distribution. | |
2285 | */ | |
2286 | param_type | |
2287 | param() const | |
2288 | { return _M_param; } | |
2289 | ||
2290 | /** | |
2291 | * @brief Sets the parameter set of the distribution. | |
2292 | * @param __param The new parameter set of the distribution. | |
2293 | */ | |
2294 | void | |
2295 | param(const param_type& __param) | |
2296 | { _M_param = __param; } | |
2297 | ||
2298 | /** | |
2299 | * @brief Returns the greatest lower bound value of the distribution. | |
2300 | */ | |
2301 | result_type | |
2302 | min() const | |
2303 | { return result_type(0); } | |
2304 | ||
2305 | /** | |
2306 | * @brief Returns the least upper bound value of the distribution. | |
2307 | */ | |
2308 | result_type | |
2309 | max() const | |
2310 | { return std::numeric_limits<result_type>::max(); } | |
2311 | ||
2312 | template<typename _UniformRandomNumberGenerator> | |
2313 | result_type | |
2314 | operator()(_UniformRandomNumberGenerator& __urng) | |
2315 | { return this->operator()(__urng, this->param()); } | |
2316 | ||
2317 | template<typename _UniformRandomNumberGenerator> | |
2318 | result_type | |
2319 | operator()(_UniformRandomNumberGenerator& __urng, | |
2320 | const param_type& __p); | |
2321 | ||
2322 | private: | |
2323 | param_type _M_param; | |
2324 | }; | |
2325 | ||
2326 | /** | |
2327 | * @brief Return true if two Chi-squared distributions have | |
2328 | * the same parameters. | |
2329 | */ | |
2330 | template<typename _RealType> | |
94986f6d PC |
2331 | inline bool |
2332 | operator==(const std::chi_squared_distribution<_RealType>& __d1, | |
2333 | const std::chi_squared_distribution<_RealType>& __d2) | |
8e79468d BK |
2334 | { return __d1.param() == __d2.param(); } |
2335 | ||
2336 | /** | |
2337 | * @brief Inserts a %chi_squared_distribution random number distribution | |
2338 | * @p __x into the output stream @p __os. | |
2339 | * | |
2340 | * @param __os An output stream. | |
2341 | * @param __x A %chi_squared_distribution random number distribution. | |
2342 | * | |
2343 | * @returns The output stream with the state of @p __x inserted or in | |
2344 | * an error state. | |
2345 | */ | |
2346 | template<typename _RealType, typename _CharT, typename _Traits> | |
2347 | std::basic_ostream<_CharT, _Traits>& | |
94986f6d PC |
2348 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
2349 | const std::chi_squared_distribution<_RealType>&); | |
8e79468d BK |
2350 | |
2351 | /** | |
2352 | * @brief Extracts a %chi_squared_distribution random number distribution | |
2353 | * @p __x from the input stream @p __is. | |
2354 | * | |
2355 | * @param __is An input stream. | |
2356 | * @param __x A %chi_squared_distribution random number | |
2357 | * generator engine. | |
2358 | * | |
2359 | * @returns The input stream with @p __x extracted or in an error state. | |
2360 | */ | |
2361 | template<typename _RealType, typename _CharT, typename _Traits> | |
2362 | std::basic_istream<_CharT, _Traits>& | |
94986f6d PC |
2363 | operator>>(std::basic_istream<_CharT, _Traits>&, |
2364 | std::chi_squared_distribution<_RealType>&); | |
8e79468d BK |
2365 | |
2366 | ||
2367 | /** | |
2368 | * @brief A cauchy_distribution random number distribution. | |
2369 | * | |
2370 | * The formula for the normal probability mass function is | |
2371 | * @f$ p(x|a,b) = \( \pi b \( 1 + \( \frac{x-a}{b} \)^2 \) \)^{-1} @f$ | |
2372 | */ | |
2373 | template<typename _RealType = double> | |
2374 | class cauchy_distribution | |
2375 | { | |
2376 | public: | |
2377 | /** The type of the range of the distribution. */ | |
2378 | typedef _RealType result_type; | |
2379 | /** Parameter type. */ | |
2380 | struct param_type | |
2381 | { | |
2382 | typedef cauchy_distribution<_RealType> distribution_type; | |
2383 | ||
2384 | explicit | |
2385 | param_type(_RealType __a = _RealType(0), | |
2386 | _RealType __b = _RealType(1)) | |
2387 | : _M_a(__a), _M_b(__b) | |
2388 | { } | |
2389 | ||
2390 | _RealType | |
2391 | a() const | |
2392 | { return _M_a; } | |
2393 | ||
2394 | _RealType | |
2395 | b() const | |
2396 | { return _M_b; } | |
2397 | ||
2398 | friend bool | |
2399 | operator==(const param_type& __p1, const param_type& __p2) | |
2400 | { return (__p1._M_a == __p2._M_a) && (__p1._M_b == __p2._M_b); } | |
2401 | ||
2402 | private: | |
2403 | _RealType _M_a; | |
2404 | _RealType _M_b; | |
2405 | }; | |
2406 | ||
2407 | explicit | |
2408 | cauchy_distribution(_RealType __a = _RealType(0), | |
2409 | _RealType __b = _RealType(1)) | |
2410 | : _M_param(__a, __b) | |
2411 | { } | |
2412 | ||
2413 | explicit | |
2414 | cauchy_distribution(const param_type& __p) | |
2415 | : _M_param(__p) | |
2416 | { } | |
2417 | ||
2418 | /** | |
2419 | * @brief Resets the distribution state. | |
2420 | */ | |
2421 | void | |
2422 | reset() | |
2423 | { } | |
2424 | ||
2425 | /** | |
2426 | * | |
2427 | */ | |
2428 | _RealType | |
2429 | a() const | |
2430 | { return _M_param.a(); } | |
2431 | ||
2432 | _RealType | |
2433 | b() const | |
2434 | { return _M_param.b(); } | |
2435 | ||
2436 | /** | |
2437 | * @brief Returns the parameter set of the distribution. | |
2438 | */ | |
2439 | param_type | |
2440 | param() const | |
2441 | { return _M_param; } | |
2442 | ||
2443 | /** | |
2444 | * @brief Sets the parameter set of the distribution. | |
2445 | * @param __param The new parameter set of the distribution. | |
2446 | */ | |
2447 | void | |
2448 | param(const param_type& __param) | |
2449 | { _M_param = __param; } | |
2450 | ||
2451 | /** | |
2452 | * @brief Returns the greatest lower bound value of the distribution. | |
2453 | */ | |
2454 | result_type | |
2455 | min() const | |
2456 | { return std::numeric_limits<result_type>::min(); } | |
2457 | ||
2458 | /** | |
2459 | * @brief Returns the least upper bound value of the distribution. | |
2460 | */ | |
2461 | result_type | |
2462 | max() const | |
2463 | { return std::numeric_limits<result_type>::max(); } | |
2464 | ||
2465 | template<typename _UniformRandomNumberGenerator> | |
2466 | result_type | |
2467 | operator()(_UniformRandomNumberGenerator& __urng) | |
2468 | { return this->operator()(__urng, this->param()); } | |
2469 | ||
2470 | template<typename _UniformRandomNumberGenerator> | |
2471 | result_type | |
2472 | operator()(_UniformRandomNumberGenerator& __urng, | |
2473 | const param_type& __p); | |
2474 | ||
2475 | private: | |
2476 | param_type _M_param; | |
2477 | }; | |
2478 | ||
2479 | /** | |
2480 | * @brief Return true if two Cauchy distributions have | |
2481 | * the same parameters. | |
2482 | */ | |
2483 | template<typename _RealType> | |
94986f6d PC |
2484 | inline bool |
2485 | operator==(const std::cauchy_distribution<_RealType>& __d1, | |
2486 | const std::cauchy_distribution<_RealType>& __d2) | |
8e79468d BK |
2487 | { return __d1.param() == __d2.param(); } |
2488 | ||
2489 | /** | |
2490 | * @brief Inserts a %cauchy_distribution random number distribution | |
2491 | * @p __x into the output stream @p __os. | |
2492 | * | |
2493 | * @param __os An output stream. | |
2494 | * @param __x A %cauchy_distribution random number distribution. | |
2495 | * | |
2496 | * @returns The output stream with the state of @p __x inserted or in | |
2497 | * an error state. | |
2498 | */ | |
2499 | template<typename _RealType, typename _CharT, typename _Traits> | |
2500 | std::basic_ostream<_CharT, _Traits>& | |
94986f6d PC |
2501 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
2502 | const std::cauchy_distribution<_RealType>&); | |
8e79468d BK |
2503 | |
2504 | /** | |
2505 | * @brief Extracts a %cauchy_distribution random number distribution | |
2506 | * @p __x from the input stream @p __is. | |
2507 | * | |
2508 | * @param __is An input stream. | |
2509 | * @param __x A %cauchy_distribution random number | |
2510 | * generator engine. | |
2511 | * | |
2512 | * @returns The input stream with @p __x extracted or in an error state. | |
2513 | */ | |
2514 | template<typename _RealType, typename _CharT, typename _Traits> | |
2515 | std::basic_istream<_CharT, _Traits>& | |
94986f6d PC |
2516 | operator>>(std::basic_istream<_CharT, _Traits>&, |
2517 | std::cauchy_distribution<_RealType>&); | |
8e79468d BK |
2518 | |
2519 | ||
2520 | /** | |
2521 | * @brief A fisher_f_distribution random number distribution. | |
2522 | * | |
2523 | * The formula for the normal probability mass function is | |
2524 | * @f$ p(x|m,n) = \frac{\Gamma((m+n)/2)}{\Gamma(m/2)\Gamma(n/2)} | |
2525 | * \(\frac{m}{n}\)^{m/2} x^{(m/2)-1} | |
2526 | * \( 1 + \frac{mx}{n} \)^{-(m+n)/2} @f$ | |
2527 | */ | |
2528 | template<typename _RealType = double> | |
2529 | class fisher_f_distribution | |
2530 | { | |
2531 | public: | |
2532 | /** The type of the range of the distribution. */ | |
2533 | typedef _RealType result_type; | |
2534 | /** Parameter type. */ | |
2535 | struct param_type | |
2536 | { | |
2537 | typedef fisher_f_distribution<_RealType> distribution_type; | |
2538 | ||
2539 | explicit | |
2540 | param_type(_RealType __m = _RealType(1), | |
2541 | _RealType __n = _RealType(1)) | |
2542 | : _M_m(__m), _M_n(__n) | |
2543 | { } | |
2544 | ||
2545 | _RealType | |
2546 | m() const | |
2547 | { return _M_m; } | |
2548 | ||
2549 | _RealType | |
2550 | n() const | |
2551 | { return _M_n; } | |
2552 | ||
2553 | friend bool | |
2554 | operator==(const param_type& __p1, const param_type& __p2) | |
2555 | { return (__p1._M_m == __p2._M_m) && (__p1._M_n == __p2._M_n); } | |
2556 | ||
2557 | private: | |
2558 | _RealType _M_m; | |
2559 | _RealType _M_n; | |
2560 | }; | |
2561 | ||
2562 | explicit | |
2563 | fisher_f_distribution(_RealType __m = _RealType(1), | |
2564 | _RealType __n = _RealType(1)) | |
2565 | : _M_param(__m, __n) | |
2566 | { } | |
2567 | ||
2568 | explicit | |
2569 | fisher_f_distribution(const param_type& __p) | |
2570 | : _M_param(__p) | |
2571 | { } | |
2572 | ||
2573 | /** | |
2574 | * @brief Resets the distribution state. | |
2575 | */ | |
2576 | void | |
2577 | reset() | |
2578 | { } | |
2579 | ||
2580 | /** | |
2581 | * | |
2582 | */ | |
2583 | _RealType | |
2584 | m() const | |
2585 | { return _M_param.m(); } | |
2586 | ||
2587 | _RealType | |
2588 | n() const | |
2589 | { return _M_param.n(); } | |
2590 | ||
2591 | /** | |
2592 | * @brief Returns the parameter set of the distribution. | |
2593 | */ | |
2594 | param_type | |
2595 | param() const | |
2596 | { return _M_param; } | |
2597 | ||
2598 | /** | |
2599 | * @brief Sets the parameter set of the distribution. | |
2600 | * @param __param The new parameter set of the distribution. | |
2601 | */ | |
2602 | void | |
2603 | param(const param_type& __param) | |
2604 | { _M_param = __param; } | |
2605 | ||
2606 | /** | |
2607 | * @brief Returns the greatest lower bound value of the distribution. | |
2608 | */ | |
2609 | result_type | |
2610 | min() const | |
2611 | { return result_type(0); } | |
2612 | ||
2613 | /** | |
2614 | * @brief Returns the least upper bound value of the distribution. | |
2615 | */ | |
2616 | result_type | |
2617 | max() const | |
2618 | { return std::numeric_limits<result_type>::max(); } | |
2619 | ||
2620 | template<typename _UniformRandomNumberGenerator> | |
2621 | result_type | |
2622 | operator()(_UniformRandomNumberGenerator& __urng) | |
2623 | { return this->operator()(__urng, this->param()); } | |
2624 | ||
2625 | template<typename _UniformRandomNumberGenerator> | |
2626 | result_type | |
2627 | operator()(_UniformRandomNumberGenerator& __urng, | |
2628 | const param_type& __p); | |
2629 | ||
2630 | private: | |
2631 | param_type _M_param; | |
2632 | }; | |
2633 | ||
2634 | /** | |
2635 | * @brief Return true if two Fisher f distributions have | |
2636 | * the same parameters. | |
2637 | */ | |
2638 | template<typename _RealType> | |
94986f6d PC |
2639 | inline bool |
2640 | operator==(const std::fisher_f_distribution<_RealType>& __d1, | |
2641 | const std::fisher_f_distribution<_RealType>& __d2) | |
8e79468d BK |
2642 | { return __d1.param() == __d2.param(); } |
2643 | ||
2644 | /** | |
2645 | * @brief Inserts a %fisher_f_distribution random number distribution | |
2646 | * @p __x into the output stream @p __os. | |
2647 | * | |
2648 | * @param __os An output stream. | |
2649 | * @param __x A %fisher_f_distribution random number distribution. | |
2650 | * | |
2651 | * @returns The output stream with the state of @p __x inserted or in | |
2652 | * an error state. | |
2653 | */ | |
2654 | template<typename _RealType, typename _CharT, typename _Traits> | |
2655 | std::basic_ostream<_CharT, _Traits>& | |
94986f6d PC |
2656 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
2657 | const std::fisher_f_distribution<_RealType>&); | |
8e79468d BK |
2658 | |
2659 | /** | |
2660 | * @brief Extracts a %fisher_f_distribution random number distribution | |
2661 | * @p __x from the input stream @p __is. | |
2662 | * | |
2663 | * @param __is An input stream. | |
2664 | * @param __x A %fisher_f_distribution random number | |
2665 | * generator engine. | |
2666 | * | |
2667 | * @returns The input stream with @p __x extracted or in an error state. | |
2668 | */ | |
2669 | template<typename _RealType, typename _CharT, typename _Traits> | |
2670 | std::basic_istream<_CharT, _Traits>& | |
94986f6d PC |
2671 | operator>>(std::basic_istream<_CharT, _Traits>&, |
2672 | std::fisher_f_distribution<_RealType>&); | |
8e79468d BK |
2673 | |
2674 | ||
2675 | /** | |
2676 | * @brief A student_t_distribution random number distribution. | |
2677 | * | |
2678 | * The formula for the normal probability mass function is | |
2679 | * @f$ p(x|n) = \frac{1}{\sqrt(n\pi)} \frac{\Gamma((n+1)/2)}{\Gamma(n/2)} | |
2680 | * \( 1 + \frac{x^2}{n} \) ^{-(n+1)/2} @f$ | |
2681 | */ | |
2682 | template<typename _RealType = double> | |
2683 | class student_t_distribution | |
2684 | { | |
2685 | public: | |
2686 | /** The type of the range of the distribution. */ | |
2687 | typedef _RealType result_type; | |
2688 | /** Parameter type. */ | |
2689 | struct param_type | |
2690 | { | |
2691 | typedef student_t_distribution<_RealType> distribution_type; | |
2692 | ||
2693 | explicit | |
2694 | param_type(_RealType __n = _RealType(1)) | |
2695 | : _M_n(__n) | |
2696 | { } | |
2697 | ||
2698 | _RealType | |
2699 | n() const | |
2700 | { return _M_n; } | |
2701 | ||
2702 | friend bool | |
2703 | operator==(const param_type& __p1, const param_type& __p2) | |
2704 | { return __p1._M_n == __p2._M_n; } | |
2705 | ||
2706 | private: | |
2707 | _RealType _M_n; | |
2708 | }; | |
2709 | ||
2710 | explicit | |
2711 | student_t_distribution(_RealType __n = _RealType(1)) | |
2712 | : _M_param(__n) | |
2713 | { } | |
2714 | ||
2715 | explicit | |
2716 | student_t_distribution(const param_type& __p) | |
2717 | : _M_param(__p) | |
2718 | { } | |
2719 | ||
2720 | /** | |
2721 | * @brief Resets the distribution state. | |
2722 | */ | |
2723 | void | |
2724 | reset() | |
2725 | { } | |
2726 | ||
2727 | /** | |
2728 | * | |
2729 | */ | |
2730 | _RealType | |
2731 | n() const | |
2732 | { return _M_param.n(); } | |
2733 | ||
2734 | /** | |
2735 | * @brief Returns the parameter set of the distribution. | |
2736 | */ | |
2737 | param_type | |
2738 | param() const | |
2739 | { return _M_param; } | |
2740 | ||
2741 | /** | |
2742 | * @brief Sets the parameter set of the distribution. | |
2743 | * @param __param The new parameter set of the distribution. | |
2744 | */ | |
2745 | void | |
2746 | param(const param_type& __param) | |
2747 | { _M_param = __param; } | |
2748 | ||
2749 | /** | |
2750 | * @brief Returns the greatest lower bound value of the distribution. | |
2751 | */ | |
2752 | result_type | |
2753 | min() const | |
2754 | { return std::numeric_limits<result_type>::min(); } | |
2755 | ||
2756 | /** | |
2757 | * @brief Returns the least upper bound value of the distribution. | |
2758 | */ | |
2759 | result_type | |
2760 | max() const | |
2761 | { return std::numeric_limits<result_type>::max(); } | |
2762 | ||
2763 | template<typename _UniformRandomNumberGenerator> | |
2764 | result_type | |
2765 | operator()(_UniformRandomNumberGenerator& __urng) | |
2766 | { return this->operator()(__urng, this->param()); } | |
2767 | ||
2768 | template<typename _UniformRandomNumberGenerator> | |
2769 | result_type | |
2770 | operator()(_UniformRandomNumberGenerator& __urng, | |
2771 | const param_type& __p); | |
2772 | ||
2773 | private: | |
2774 | template<typename _UniformRandomNumberGenerator> | |
2775 | result_type | |
2776 | _M_gaussian(_UniformRandomNumberGenerator& __urng, | |
2777 | const result_type __sigma); | |
2778 | ||
2779 | param_type _M_param; | |
2780 | }; | |
2781 | ||
2782 | /** | |
2783 | * @brief Return true if two Student t distributions have | |
2784 | * the same parameters. | |
2785 | */ | |
2786 | template<typename _RealType> | |
94986f6d PC |
2787 | inline bool |
2788 | operator==(const std::student_t_distribution<_RealType>& __d1, | |
2789 | const std::student_t_distribution<_RealType>& __d2) | |
8e79468d BK |
2790 | { return __d1.param() == __d2.param(); } |
2791 | ||
2792 | /** | |
2793 | * @brief Inserts a %student_t_distribution random number distribution | |
2794 | * @p __x into the output stream @p __os. | |
2795 | * | |
2796 | * @param __os An output stream. | |
2797 | * @param __x A %student_t_distribution random number distribution. | |
2798 | * | |
2799 | * @returns The output stream with the state of @p __x inserted or in | |
2800 | * an error state. | |
2801 | */ | |
2802 | template<typename _RealType, typename _CharT, typename _Traits> | |
2803 | std::basic_ostream<_CharT, _Traits>& | |
94986f6d PC |
2804 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
2805 | const std::student_t_distribution<_RealType>&); | |
8e79468d BK |
2806 | |
2807 | /** | |
2808 | * @brief Extracts a %student_t_distribution random number distribution | |
2809 | * @p __x from the input stream @p __is. | |
2810 | * | |
2811 | * @param __is An input stream. | |
2812 | * @param __x A %student_t_distribution random number | |
2813 | * generator engine. | |
2814 | * | |
2815 | * @returns The input stream with @p __x extracted or in an error state. | |
2816 | */ | |
2817 | template<typename _RealType, typename _CharT, typename _Traits> | |
2818 | std::basic_istream<_CharT, _Traits>& | |
94986f6d PC |
2819 | operator>>(std::basic_istream<_CharT, _Traits>&, |
2820 | std::student_t_distribution<_RealType>&); | |
8e79468d BK |
2821 | |
2822 | /* @} */ // group std_random_distributions_normal | |
2823 | ||
2824 | /** | |
2825 | * @addtogroup std_random_distributions_bernoulli Bernoulli Distributions | |
2826 | * @ingroup std_random_distributions | |
2827 | * @{ | |
2828 | */ | |
2829 | ||
2830 | /** | |
2831 | * @brief A Bernoulli random number distribution. | |
2832 | * | |
2833 | * Generates a sequence of true and false values with likelihood @f$ p @f$ | |
2834 | * that true will come up and @f$ (1 - p) @f$ that false will appear. | |
2835 | */ | |
2836 | class bernoulli_distribution | |
2837 | { | |
2838 | public: | |
2839 | /** The type of the range of the distribution. */ | |
2840 | typedef bool result_type; | |
2841 | /** Parameter type. */ | |
2842 | struct param_type | |
2843 | { | |
2844 | typedef bernoulli_distribution distribution_type; | |
2845 | ||
2846 | explicit | |
2847 | param_type(double __p = 0.5) | |
2848 | : _M_p(__p) | |
2849 | { | |
2850 | _GLIBCXX_DEBUG_ASSERT((_M_p >= 0.0) && (_M_p <= 1.0)); | |
2851 | } | |
2852 | ||
2853 | double | |
2854 | p() const | |
2855 | { return _M_p; } | |
2856 | ||
2857 | friend bool | |
2858 | operator==(const param_type& __p1, const param_type& __p2) | |
2859 | { return __p1._M_p == __p2._M_p; } | |
2860 | ||
2861 | private: | |
2862 | double _M_p; | |
2863 | }; | |
2864 | ||
2865 | public: | |
2866 | /** | |
2867 | * @brief Constructs a Bernoulli distribution with likelihood @p p. | |
2868 | * | |
2869 | * @param __p [IN] The likelihood of a true result being returned. | |
2870 | * Must be in the interval @f$ [0, 1] @f$. | |
2871 | */ | |
2872 | explicit | |
2873 | bernoulli_distribution(double __p = 0.5) | |
2874 | : _M_param(__p) | |
2875 | { } | |
2876 | ||
2877 | explicit | |
2878 | bernoulli_distribution(const param_type& __p) | |
2879 | : _M_param(__p) | |
2880 | { } | |
2881 | ||
2882 | /** | |
2883 | * @brief Resets the distribution state. | |
2884 | * | |
2885 | * Does nothing for a Bernoulli distribution. | |
2886 | */ | |
2887 | void | |
2888 | reset() { } | |
2889 | ||
2890 | /** | |
2891 | * @brief Returns the @p p parameter of the distribution. | |
2892 | */ | |
2893 | double | |
2894 | p() const | |
2895 | { return _M_param.p(); } | |
2896 | ||
2897 | /** | |
2898 | * @brief Returns the parameter set of the distribution. | |
2899 | */ | |
2900 | param_type | |
2901 | param() const | |
2902 | { return _M_param; } | |
2903 | ||
2904 | /** | |
2905 | * @brief Sets the parameter set of the distribution. | |
2906 | * @param __param The new parameter set of the distribution. | |
2907 | */ | |
2908 | void | |
2909 | param(const param_type& __param) | |
2910 | { _M_param = __param; } | |
2911 | ||
2912 | /** | |
2913 | * @brief Returns the greatest lower bound value of the distribution. | |
2914 | */ | |
2915 | result_type | |
2916 | min() const | |
2917 | { return std::numeric_limits<result_type>::min(); } | |
2918 | ||
2919 | /** | |
2920 | * @brief Returns the least upper bound value of the distribution. | |
2921 | */ | |
2922 | result_type | |
2923 | max() const | |
2924 | { return std::numeric_limits<result_type>::max(); } | |
2925 | ||
2926 | /** | |
2927 | * @brief Returns the next value in the Bernoullian sequence. | |
2928 | */ | |
2929 | template<typename _UniformRandomNumberGenerator> | |
2930 | result_type | |
2931 | operator()(_UniformRandomNumberGenerator& __urng) | |
2932 | { | |
2933 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
2934 | __aurng(__urng); | |
2935 | if ((__aurng() - __aurng.min()) | |
2936 | < this->p() * (__aurng.max() - __aurng.min())) | |
2937 | return true; | |
2938 | return false; | |
2939 | } | |
2940 | ||
2941 | template<typename _UniformRandomNumberGenerator> | |
2942 | result_type | |
2943 | operator()(_UniformRandomNumberGenerator& __urng, | |
2944 | const param_type& __p) | |
2945 | { | |
2946 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> | |
2947 | __aurng(__urng); | |
2948 | if ((__aurng() - __aurng.min()) | |
2949 | < __p.p() * (__aurng.max() - __aurng.min())) | |
2950 | return true; | |
2951 | return false; | |
2952 | } | |
2953 | ||
2954 | private: | |
2955 | param_type _M_param; | |
2956 | }; | |
2957 | ||
2958 | /** | |
2959 | * @brief Return true if two Bernoulli distributions have | |
2960 | * the same parameters. | |
2961 | */ | |
94986f6d PC |
2962 | inline bool |
2963 | operator==(const std::bernoulli_distribution& __d1, | |
2964 | const std::bernoulli_distribution& __d2) | |
8e79468d BK |
2965 | { return __d1.param() == __d2.param(); } |
2966 | ||
2967 | /** | |
2968 | * @brief Inserts a %bernoulli_distribution random number distribution | |
2969 | * @p __x into the output stream @p __os. | |
2970 | * | |
2971 | * @param __os An output stream. | |
2972 | * @param __x A %bernoulli_distribution random number distribution. | |
2973 | * | |
2974 | * @returns The output stream with the state of @p __x inserted or in | |
2975 | * an error state. | |
2976 | */ | |
2977 | template<typename _CharT, typename _Traits> | |
2978 | std::basic_ostream<_CharT, _Traits>& | |
94986f6d PC |
2979 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
2980 | const std::bernoulli_distribution&); | |
8e79468d BK |
2981 | |
2982 | /** | |
2983 | * @brief Extracts a %bernoulli_distribution random number distribution | |
2984 | * @p __x from the input stream @p __is. | |
2985 | * | |
2986 | * @param __is An input stream. | |
2987 | * @param __x A %bernoulli_distribution random number generator engine. | |
2988 | * | |
2989 | * @returns The input stream with @p __x extracted or in an error state. | |
2990 | */ | |
2991 | template<typename _CharT, typename _Traits> | |
2992 | std::basic_istream<_CharT, _Traits>& | |
2993 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
94986f6d | 2994 | std::bernoulli_distribution& __x) |
8e79468d BK |
2995 | { |
2996 | double __p; | |
2997 | __is >> __p; | |
2998 | __x.param(bernoulli_distribution::param_type(__p)); | |
2999 | return __is; | |
3000 | } | |
3001 | ||
3002 | ||
3003 | /** | |
3004 | * @brief A discrete binomial random number distribution. | |
3005 | * | |
3006 | * The formula for the binomial probability density function is | |
3007 | * @f$ p(i|t,p) = \binom{n}{i} p^i (1 - p)^{t - i} @f$ where @f$ t @f$ | |
3008 | * and @f$ p @f$ are the parameters of the distribution. | |
3009 | */ | |
3010 | template<typename _IntType = int> | |
3011 | class binomial_distribution | |
3012 | { | |
3013 | __glibcxx_class_requires(_IntType, _IntegerConcept) | |
3014 | ||
3015 | public: | |
3016 | /** The type of the range of the distribution. */ | |
3017 | typedef _IntType result_type; | |
3018 | /** Parameter type. */ | |
3019 | struct param_type | |
3020 | { | |
3021 | typedef binomial_distribution<_IntType> distribution_type; | |
3022 | friend class binomial_distribution<_IntType>; | |
3023 | ||
3024 | explicit | |
3025 | param_type(_IntType __t = _IntType(1), double __p = 0.5) | |
3026 | : _M_t(__t), _M_p(__p) | |
3027 | { | |
3028 | _GLIBCXX_DEBUG_ASSERT((_M_t >= _IntType(0)) | |
94986f6d PC |
3029 | && (_M_p >= 0.0) |
3030 | && (_M_p <= 1.0)); | |
8e79468d BK |
3031 | _M_initialize(); |
3032 | } | |
3033 | ||
3034 | _IntType | |
3035 | t() const | |
3036 | { return _M_t; } | |
3037 | ||
3038 | double | |
3039 | p() const | |
3040 | { return _M_p; } | |
3041 | ||
3042 | friend bool | |
3043 | operator==(const param_type& __p1, const param_type& __p2) | |
3044 | { return (__p1._M_t == __p2._M_t) && (__p1._M_p == __p2._M_p); } | |
3045 | ||
3046 | private: | |
3047 | void | |
3048 | _M_initialize(); | |
3049 | ||
3050 | _IntType _M_t; | |
3051 | double _M_p; | |
3052 | ||
3053 | double _M_q; | |
3054 | #if _GLIBCXX_USE_C99_MATH_TR1 | |
3055 | double _M_d1, _M_d2, _M_s1, _M_s2, _M_c, | |
3056 | _M_a1, _M_a123, _M_s, _M_lf, _M_lp1p; | |
3057 | #endif | |
3058 | bool _M_easy; | |
3059 | }; | |
3060 | ||
3061 | // constructors and member function | |
3062 | explicit | |
3063 | binomial_distribution(_IntType __t = _IntType(1), | |
3064 | double __p = 0.5) | |
3065 | : _M_param(__t, __p), _M_nd() | |
3066 | { } | |
3067 | ||
3068 | explicit | |
3069 | binomial_distribution(const param_type& __p) | |
3070 | : _M_param(__p), _M_nd() | |
3071 | { } | |
3072 | ||
3073 | /** | |
3074 | * @brief Resets the distribution state. | |
3075 | */ | |
3076 | void | |
3077 | reset() | |
3078 | { _M_nd.reset(); } | |
3079 | ||
3080 | /** | |
3081 | * @brief Returns the distribution @p t parameter. | |
3082 | */ | |
3083 | _IntType | |
3084 | t() const | |
3085 | { return _M_param.t(); } | |
3086 | ||
3087 | /** | |
3088 | * @brief Returns the distribution @p p parameter. | |
3089 | */ | |
3090 | double | |
3091 | p() const | |
3092 | { return _M_param.p(); } | |
3093 | ||
3094 | /** | |
3095 | * @brief Returns the parameter set of the distribution. | |
3096 | */ | |
3097 | param_type | |
3098 | param() const | |
3099 | { return _M_param; } | |
3100 | ||
3101 | /** | |
3102 | * @brief Sets the parameter set of the distribution. | |
3103 | * @param __param The new parameter set of the distribution. | |
3104 | */ | |
3105 | void | |
3106 | param(const param_type& __param) | |
3107 | { _M_param = __param; } | |
3108 | ||
3109 | /** | |
3110 | * @brief Returns the greatest lower bound value of the distribution. | |
3111 | */ | |
3112 | result_type | |
3113 | min() const | |
3114 | { return 0; } | |
3115 | ||
3116 | /** | |
3117 | * @brief Returns the least upper bound value of the distribution. | |
3118 | */ | |
3119 | result_type | |
3120 | max() const | |
3121 | { return _M_param.t(); } | |
3122 | ||
3123 | /** | |
3124 | * @brief Return true if two binomial distributions have | |
3125 | * the same parameters. | |
3126 | */ | |
3127 | template<typename _IntType1> | |
3128 | friend bool | |
94986f6d PC |
3129 | operator==(const std::binomial_distribution<_IntType1>& __d1, |
3130 | const std::binomial_distribution<_IntType1>& __d2) | |
3131 | { return ((__d1.param() == __d2.param()) | |
3132 | && (__d1._M_nd == __d2._M_nd)); } | |
8e79468d BK |
3133 | |
3134 | template<typename _UniformRandomNumberGenerator> | |
3135 | result_type | |
3136 | operator()(_UniformRandomNumberGenerator& __urng) | |
3137 | { return this->operator()(__urng, this->param()); } | |
3138 | ||
3139 | template<typename _UniformRandomNumberGenerator> | |
3140 | result_type | |
3141 | operator()(_UniformRandomNumberGenerator& __urng, | |
3142 | const param_type& __p); | |
3143 | ||
3144 | /** | |
3145 | * @brief Inserts a %binomial_distribution random number distribution | |
3146 | * @p __x into the output stream @p __os. | |
3147 | * | |
3148 | * @param __os An output stream. | |
3149 | * @param __x A %binomial_distribution random number distribution. | |
3150 | * | |
3151 | * @returns The output stream with the state of @p __x inserted or in | |
3152 | * an error state. | |
3153 | */ | |
3154 | template<typename _IntType1, | |
3155 | typename _CharT, typename _Traits> | |
3156 | friend std::basic_ostream<_CharT, _Traits>& | |
94986f6d PC |
3157 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
3158 | const std::binomial_distribution<_IntType1>&); | |
8e79468d BK |
3159 | |
3160 | /** | |
3161 | * @brief Extracts a %binomial_distribution random number distribution | |
3162 | * @p __x from the input stream @p __is. | |
3163 | * | |
3164 | * @param __is An input stream. | |
3165 | * @param __x A %binomial_distribution random number generator engine. | |
3166 | * | |
3167 | * @returns The input stream with @p __x extracted or in an error | |
3168 | * state. | |
3169 | */ | |
3170 | template<typename _IntType1, | |
3171 | typename _CharT, typename _Traits> | |
3172 | friend std::basic_istream<_CharT, _Traits>& | |
94986f6d PC |
3173 | operator>>(std::basic_istream<_CharT, _Traits>&, |
3174 | std::binomial_distribution<_IntType1>&); | |
8e79468d BK |
3175 | |
3176 | private: | |
3177 | template<typename _UniformRandomNumberGenerator> | |
3178 | result_type | |
3179 | _M_waiting(_UniformRandomNumberGenerator& __urng, _IntType __t); | |
3180 | ||
3181 | param_type _M_param; | |
3182 | ||
3183 | // NB: Unused when _GLIBCXX_USE_C99_MATH_TR1 is undefined. | |
3184 | normal_distribution<double> _M_nd; | |
3185 | }; | |
3186 | ||
3187 | ||
3188 | /** | |
3189 | * @brief A discrete geometric random number distribution. | |
3190 | * | |
3191 | * The formula for the geometric probability density function is | |
3192 | * @f$ p(i|p) = (1 - p)p^{i-1} @f$ where @f$ p @f$ is the parameter of the | |
3193 | * distribution. | |
3194 | */ | |
3195 | template<typename _IntType = int> | |
3196 | class geometric_distribution | |
3197 | { | |
3198 | __glibcxx_class_requires(_IntType, _IntegerConcept) | |
3199 | ||
3200 | public: | |
3201 | /** The type of the range of the distribution. */ | |
3202 | typedef _IntType result_type; | |
3203 | /** Parameter type. */ | |
3204 | struct param_type | |
3205 | { | |
3206 | typedef geometric_distribution<_IntType> distribution_type; | |
3207 | friend class geometric_distribution<_IntType>; | |
3208 | ||
3209 | explicit | |
3210 | param_type(double __p = 0.5) | |
3211 | : _M_p(__p) | |
3212 | { | |
3213 | _GLIBCXX_DEBUG_ASSERT((_M_p >= 0.0) | |
3214 | && (_M_p <= 1.0)); | |
3215 | _M_initialize(); | |
3216 | } | |
3217 | ||
3218 | double | |
3219 | p() const | |
3220 | { return _M_p; } | |
3221 | ||
3222 | friend bool | |
3223 | operator==(const param_type& __p1, const param_type& __p2) | |
3224 | { return __p1._M_p == __p2._M_p; } | |
3225 | ||
3226 | private: | |
3227 | void | |
3228 | _M_initialize() | |
3229 | { _M_log_p = std::log(_M_p); } | |
3230 | ||
3231 | double _M_p; | |
3232 | ||
3233 | double _M_log_p; | |
3234 | }; | |
3235 | ||
3236 | // constructors and member function | |
3237 | explicit | |
3238 | geometric_distribution(double __p = 0.5) | |
3239 | : _M_param(__p) | |
3240 | { } | |
3241 | ||
3242 | explicit | |
3243 | geometric_distribution(const param_type& __p) | |
3244 | : _M_param(__p) | |
3245 | { } | |
3246 | ||
3247 | /** | |
3248 | * @brief Resets the distribution state. | |
3249 | * | |
3250 | * Does nothing for the geometric distribution. | |
3251 | */ | |
3252 | void | |
3253 | reset() { } | |
3254 | ||
3255 | /** | |
3256 | * @brief Returns the distribution parameter @p p. | |
3257 | */ | |
3258 | double | |
3259 | p() const | |
3260 | { return _M_param.p(); } | |
3261 | ||
3262 | /** | |
3263 | * @brief Returns the parameter set of the distribution. | |
3264 | */ | |
3265 | param_type | |
3266 | param() const | |
3267 | { return _M_param; } | |
3268 | ||
3269 | /** | |
3270 | * @brief Sets the parameter set of the distribution. | |
3271 | * @param __param The new parameter set of the distribution. | |
3272 | */ | |
3273 | void | |
3274 | param(const param_type& __param) | |
3275 | { _M_param = __param; } | |
3276 | ||
3277 | /** | |
3278 | * @brief Returns the greatest lower bound value of the distribution. | |
3279 | */ | |
3280 | result_type | |
3281 | min() const | |
3282 | { return 0; } | |
3283 | ||
3284 | /** | |
3285 | * @brief Returns the least upper bound value of the distribution. | |
3286 | */ | |
3287 | result_type | |
3288 | max() const | |
3289 | { return std::numeric_limits<result_type>::max(); } | |
3290 | ||
3291 | template<typename _UniformRandomNumberGenerator> | |
3292 | result_type | |
3293 | operator()(_UniformRandomNumberGenerator& __urng) | |
3294 | { return this->operator()(__urng, this->param()); } | |
3295 | ||
3296 | template<typename _UniformRandomNumberGenerator> | |
3297 | result_type | |
3298 | operator()(_UniformRandomNumberGenerator& __urng, | |
3299 | const param_type& __p); | |
3300 | ||
3301 | private: | |
3302 | param_type _M_param; | |
3303 | }; | |
3304 | ||
3305 | /** | |
3306 | * @brief Return true if two geometric distributions have | |
3307 | * the same parameters. | |
3308 | */ | |
3309 | template<typename _IntType> | |
94986f6d | 3310 | inline bool |
8e79468d BK |
3311 | operator==(const geometric_distribution<_IntType>& __d1, |
3312 | const geometric_distribution<_IntType>& __d2) | |
3313 | { return __d1.param() == __d2.param(); } | |
3314 | ||
3315 | /** | |
3316 | * @brief Inserts a %geometric_distribution random number distribution | |
3317 | * @p __x into the output stream @p __os. | |
3318 | * | |
3319 | * @param __os An output stream. | |
3320 | * @param __x A %geometric_distribution random number distribution. | |
3321 | * | |
3322 | * @returns The output stream with the state of @p __x inserted or in | |
3323 | * an error state. | |
3324 | */ | |
3325 | template<typename _IntType, | |
3326 | typename _CharT, typename _Traits> | |
3327 | std::basic_ostream<_CharT, _Traits>& | |
94986f6d PC |
3328 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
3329 | const std::geometric_distribution<_IntType>&); | |
8e79468d BK |
3330 | |
3331 | /** | |
3332 | * @brief Extracts a %geometric_distribution random number distribution | |
3333 | * @p __x from the input stream @p __is. | |
3334 | * | |
3335 | * @param __is An input stream. | |
3336 | * @param __x A %geometric_distribution random number generator engine. | |
3337 | * | |
3338 | * @returns The input stream with @p __x extracted or in an error state. | |
3339 | */ | |
3340 | template<typename _IntType, | |
3341 | typename _CharT, typename _Traits> | |
3342 | std::basic_istream<_CharT, _Traits>& | |
94986f6d PC |
3343 | operator>>(std::basic_istream<_CharT, _Traits>&, |
3344 | std::geometric_distribution<_IntType>&); | |
8e79468d BK |
3345 | |
3346 | ||
3347 | /** | |
3348 | * @brief A negative_binomial_distribution random number distribution. | |
3349 | * | |
3350 | * The formula for the negative binomial probability mass function is | |
3351 | * @f$ p(i) = \binom{n}{i} p^i (1 - p)^{t - i} @f$ where @f$ t @f$ | |
3352 | * and @f$ p @f$ are the parameters of the distribution. | |
3353 | */ | |
3354 | template<typename _IntType = int> | |
3355 | class negative_binomial_distribution | |
3356 | { | |
3357 | __glibcxx_class_requires(_IntType, _IntegerConcept) | |
3358 | ||
3359 | public: | |
3360 | /** The type of the range of the distribution. */ | |
3361 | typedef _IntType result_type; | |
3362 | /** Parameter type. */ | |
3363 | struct param_type | |
3364 | { | |
3365 | typedef negative_binomial_distribution<_IntType> distribution_type; | |
3366 | ||
3367 | explicit | |
3368 | param_type(_IntType __k = 1, double __p = 0.5) | |
3369 | : _M_k(__k), _M_p(__p) | |
3370 | { } | |
3371 | ||
3372 | _IntType | |
3373 | k() const | |
3374 | { return _M_k; } | |
3375 | ||
3376 | double | |
3377 | p() const | |
3378 | { return _M_p; } | |
3379 | ||
3380 | friend bool | |
3381 | operator==(const param_type& __p1, const param_type& __p2) | |
3382 | { return (__p1._M_k == __p2._M_k) && (__p1._M_p == __p2._M_p); } | |
3383 | ||
3384 | private: | |
3385 | _IntType _M_k; | |
3386 | double _M_p; | |
3387 | }; | |
3388 | ||
3389 | explicit | |
3390 | negative_binomial_distribution(_IntType __k = 1, double __p = 0.5) | |
3391 | : _M_param(__k, __p) | |
3392 | { } | |
3393 | ||
3394 | explicit | |
3395 | negative_binomial_distribution(const param_type& __p) | |
3396 | : _M_param(__p) | |
3397 | { } | |
3398 | ||
3399 | /** | |
3400 | * @brief Resets the distribution state. | |
3401 | */ | |
3402 | void | |
3403 | reset() | |
3404 | { } | |
3405 | ||
3406 | /** | |
3407 | * @brief Return the @f$ k @f$ parameter of the distribution. | |
3408 | */ | |
3409 | _IntType | |
3410 | k() const | |
3411 | { return _M_param.k(); } | |
3412 | ||
3413 | /** | |
3414 | * @brief Return the @f$ p @f$ parameter of the distribution. | |
3415 | */ | |
3416 | double | |
3417 | p() const | |
3418 | { return _M_param.p(); } | |
3419 | ||
3420 | /** | |
3421 | * @brief Returns the parameter set of the distribution. | |
3422 | */ | |
3423 | param_type | |
3424 | param() const | |
3425 | { return _M_param; } | |
3426 | ||
3427 | /** | |
3428 | * @brief Sets the parameter set of the distribution. | |
3429 | * @param __param The new parameter set of the distribution. | |
3430 | */ | |
3431 | void | |
3432 | param(const param_type& __param) | |
3433 | { _M_param = __param; } | |
3434 | ||
3435 | /** | |
3436 | * @brief Returns the greatest lower bound value of the distribution. | |
3437 | */ | |
3438 | result_type | |
3439 | min() const | |
3440 | { return result_type(0); } | |
3441 | ||
3442 | /** | |
3443 | * @brief Returns the least upper bound value of the distribution. | |
3444 | */ | |
3445 | result_type | |
3446 | max() const | |
3447 | { return std::numeric_limits<result_type>::max(); } | |
3448 | ||
3449 | template<typename _UniformRandomNumberGenerator> | |
3450 | result_type | |
3451 | operator()(_UniformRandomNumberGenerator& __urng) | |
3452 | { return this->operator()(__urng, this->param()); } | |
3453 | ||
3454 | template<typename _UniformRandomNumberGenerator> | |
3455 | result_type | |
3456 | operator()(_UniformRandomNumberGenerator& __urng, | |
3457 | const param_type& __p); | |
3458 | ||
3459 | private: | |
3460 | param_type _M_param; | |
3461 | }; | |
3462 | ||
3463 | /** | |
3464 | * @brief Return true if two negative binomial distributions have | |
3465 | * the same parameters. | |
3466 | */ | |
3467 | template<typename _IntType> | |
94986f6d PC |
3468 | inline bool |
3469 | operator==(const std::negative_binomial_distribution<_IntType>& __d1, | |
3470 | const std::negative_binomial_distribution<_IntType>& __d2) | |
8e79468d BK |
3471 | { return __d1.param() == __d2.param(); } |
3472 | ||
3473 | /** | |
3474 | * @brief Inserts a %negative_binomial_distribution random | |
3475 | * number distribution @p __x into the output stream @p __os. | |
3476 | * | |
3477 | * @param __os An output stream. | |
3478 | * @param __x A %negative_binomial_distribution random number | |
3479 | * distribution. | |
3480 | * | |
3481 | * @returns The output stream with the state of @p __x inserted or in | |
3482 | * an error state. | |
3483 | */ | |
3484 | template<typename _IntType, typename _CharT, typename _Traits> | |
3485 | std::basic_ostream<_CharT, _Traits>& | |
94986f6d PC |
3486 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
3487 | const std::negative_binomial_distribution<_IntType>&); | |
8e79468d BK |
3488 | |
3489 | /** | |
3490 | * @brief Extracts a %negative_binomial_distribution random number | |
3491 | * distribution @p __x from the input stream @p __is. | |
3492 | * | |
3493 | * @param __is An input stream. | |
3494 | * @param __x A %negative_binomial_distribution random number | |
3495 | * generator engine. | |
3496 | * | |
3497 | * @returns The input stream with @p __x extracted or in an error state. | |
3498 | */ | |
3499 | template<typename _IntType, typename _CharT, typename _Traits> | |
3500 | std::basic_istream<_CharT, _Traits>& | |
94986f6d PC |
3501 | operator>>(std::basic_istream<_CharT, _Traits>&, |
3502 | std::negative_binomial_distribution<_IntType>&); | |
8e79468d BK |
3503 | |
3504 | /* @} */ // group std_random_distributions_bernoulli | |
3505 | ||
3506 | /** | |
3507 | * @addtogroup std_random_distributions_poisson Poisson Distributions | |
3508 | * @ingroup std_random_distributions | |
3509 | * @{ | |
3510 | */ | |
3511 | ||
3512 | /** | |
3513 | * @brief A discrete Poisson random number distribution. | |
3514 | * | |
3515 | * The formula for the Poisson probability density function is | |
3516 | * @f$ p(i|\mu) = \frac{\mu^i}{i!} e^{-\mu} @f$ where @f$ \mu @f$ is the | |
3517 | * parameter of the distribution. | |
3518 | */ | |
3519 | template<typename _IntType = int> | |
3520 | class poisson_distribution | |
3521 | { | |
3522 | __glibcxx_class_requires(_IntType, _IntegerConcept) | |
3523 | ||
3524 | public: | |
3525 | /** The type of the range of the distribution. */ | |
3526 | typedef _IntType result_type; | |
3527 | /** Parameter type. */ | |
3528 | struct param_type | |
3529 | { | |
3530 | typedef poisson_distribution<_IntType> distribution_type; | |
3531 | friend class poisson_distribution<_IntType>; | |
3532 | ||
3533 | explicit | |
3534 | param_type(double __mean = 1.0) | |
3535 | : _M_mean(__mean) | |
3536 | { | |
3537 | _GLIBCXX_DEBUG_ASSERT(_M_mean > 0.0); | |
3538 | _M_initialize(); | |
3539 | } | |
3540 | ||
3541 | double | |
3542 | mean() const | |
3543 | { return _M_mean; } | |
3544 | ||
3545 | friend bool | |
3546 | operator==(const param_type& __p1, const param_type& __p2) | |
3547 | { return __p1._M_mean == __p2._M_mean; } | |
3548 | ||
3549 | private: | |
3550 | // Hosts either log(mean) or the threshold of the simple method. | |
3551 | void | |
3552 | _M_initialize(); | |
3553 | ||
3554 | double _M_mean; | |
3555 | ||
3556 | double _M_lm_thr; | |
3557 | #if _GLIBCXX_USE_C99_MATH_TR1 | |
3558 | double _M_lfm, _M_sm, _M_d, _M_scx, _M_1cx, _M_c2b, _M_cb; | |
3559 | #endif | |
3560 | }; | |
3561 | ||
3562 | // constructors and member function | |
3563 | explicit | |
3564 | poisson_distribution(double __mean = 1.0) | |
3565 | : _M_param(__mean), _M_nd() | |
3566 | { } | |
3567 | ||
3568 | explicit | |
3569 | poisson_distribution(const param_type& __p) | |
3570 | : _M_param(__p), _M_nd() | |
3571 | { } | |
3572 | ||
3573 | /** | |
3574 | * @brief Resets the distribution state. | |
3575 | */ | |
3576 | void | |
3577 | reset() | |
3578 | { _M_nd.reset(); } | |
3579 | ||
3580 | /** | |
3581 | * @brief Returns the distribution parameter @p mean. | |
3582 | */ | |
3583 | double | |
3584 | mean() const | |
3585 | { return _M_param.mean(); } | |
3586 | ||
3587 | /** | |
3588 | * @brief Returns the parameter set of the distribution. | |
3589 | */ | |
3590 | param_type | |
3591 | param() const | |
3592 | { return _M_param; } | |
3593 | ||
3594 | /** | |
3595 | * @brief Sets the parameter set of the distribution. | |
3596 | * @param __param The new parameter set of the distribution. | |
3597 | */ | |
3598 | void | |
3599 | param(const param_type& __param) | |
3600 | { _M_param = __param; } | |
3601 | ||
3602 | /** | |
3603 | * @brief Returns the greatest lower bound value of the distribution. | |
3604 | */ | |
3605 | result_type | |
3606 | min() const | |
3607 | { return 0; } | |
3608 | ||
3609 | /** | |
3610 | * @brief Returns the least upper bound value of the distribution. | |
3611 | */ | |
3612 | result_type | |
3613 | max() const | |
3614 | { return std::numeric_limits<result_type>::max(); } | |
3615 | ||
3616 | template<typename _UniformRandomNumberGenerator> | |
3617 | result_type | |
3618 | operator()(_UniformRandomNumberGenerator& __urng) | |
3619 | { return this->operator()(__urng, this->param()); } | |
3620 | ||
3621 | template<typename _UniformRandomNumberGenerator> | |
3622 | result_type | |
3623 | operator()(_UniformRandomNumberGenerator& __urng, | |
3624 | const param_type& __p); | |
3625 | ||
3626 | /** | |
3627 | * @brief Return true if two Poisson distributions have the same | |
3628 | * parameters. | |
3629 | */ | |
3630 | template<typename _IntType1> | |
3631 | friend bool | |
94986f6d PC |
3632 | operator==(const std::poisson_distribution<_IntType1>& __d1, |
3633 | const std::poisson_distribution<_IntType1>& __d2) | |
3634 | { return ((__d1.param() == __d2.param()) | |
3635 | && (__d1._M_nd == __d2._M_nd)); } | |
8e79468d BK |
3636 | |
3637 | /** | |
3638 | * @brief Inserts a %poisson_distribution random number distribution | |
3639 | * @p __x into the output stream @p __os. | |
3640 | * | |
3641 | * @param __os An output stream. | |
3642 | * @param __x A %poisson_distribution random number distribution. | |
3643 | * | |
3644 | * @returns The output stream with the state of @p __x inserted or in | |
3645 | * an error state. | |
3646 | */ | |
3647 | template<typename _IntType1, typename _CharT, typename _Traits> | |
3648 | friend std::basic_ostream<_CharT, _Traits>& | |
94986f6d PC |
3649 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
3650 | const std::poisson_distribution<_IntType1>&); | |
8e79468d BK |
3651 | |
3652 | /** | |
3653 | * @brief Extracts a %poisson_distribution random number distribution | |
3654 | * @p __x from the input stream @p __is. | |
3655 | * | |
3656 | * @param __is An input stream. | |
3657 | * @param __x A %poisson_distribution random number generator engine. | |
3658 | * | |
3659 | * @returns The input stream with @p __x extracted or in an error | |
3660 | * state. | |
3661 | */ | |
3662 | template<typename _IntType1, typename _CharT, typename _Traits> | |
3663 | friend std::basic_istream<_CharT, _Traits>& | |
94986f6d PC |
3664 | operator>>(std::basic_istream<_CharT, _Traits>&, |
3665 | std::poisson_distribution<_IntType1>&); | |
8e79468d BK |
3666 | |
3667 | private: | |
3668 | param_type _M_param; | |
3669 | ||
3670 | // NB: Unused when _GLIBCXX_USE_C99_MATH_TR1 is undefined. | |
3671 | normal_distribution<double> _M_nd; | |
3672 | }; | |
3673 | ||
3674 | /** | |
3675 | * @brief An exponential continuous distribution for random numbers. | |
3676 | * | |
3677 | * The formula for the exponential probability density function is | |
3678 | * @f$ p(x|\lambda) = \lambda e^{-\lambda x} @f$. | |
3679 | * | |
3680 | * <table border=1 cellpadding=10 cellspacing=0> | |
3681 | * <caption align=top>Distribution Statistics</caption> | |
3682 | * <tr><td>Mean</td><td>@f$ \frac{1}{\lambda} @f$</td></tr> | |
3683 | * <tr><td>Median</td><td>@f$ \frac{\ln 2}{\lambda} @f$</td></tr> | |
3684 | * <tr><td>Mode</td><td>@f$ zero @f$</td></tr> | |
3685 | * <tr><td>Range</td><td>@f$[0, \infty]@f$</td></tr> | |
3686 | * <tr><td>Standard Deviation</td><td>@f$ \frac{1}{\lambda} @f$</td></tr> | |
3687 | * </table> | |
3688 | */ | |
3689 | template<typename _RealType = double> | |
3690 | class exponential_distribution | |
3691 | { | |
3692 | public: | |
3693 | /** The type of the range of the distribution. */ | |
3694 | typedef _RealType result_type; | |
3695 | /** Parameter type. */ | |
3696 | struct param_type | |
3697 | { | |
3698 | typedef exponential_distribution<_RealType> distribution_type; | |
3699 | ||
3700 | explicit | |
3701 | param_type(_RealType __lambda = _RealType(1)) | |
3702 | : _M_lambda(__lambda) | |
3703 | { | |
3704 | _GLIBCXX_DEBUG_ASSERT(_M_lambda > _RealType(0)); | |
3705 | } | |
3706 | ||
3707 | _RealType | |
3708 | lambda() const | |
3709 | { return _M_lambda; } | |
3710 | ||
3711 | friend bool | |
3712 | operator==(const param_type& __p1, const param_type& __p2) | |
3713 | { return __p1._M_lambda == __p2._M_lambda; } | |
3714 | ||
3715 | private: | |
3716 | _RealType _M_lambda; | |
3717 | }; | |
3718 | ||
3719 | public: | |
3720 | /** | |
3721 | * @brief Constructs an exponential distribution with inverse scale | |
3722 | * parameter @f$ \lambda @f$. | |
3723 | */ | |
3724 | explicit | |
3725 | exponential_distribution(const result_type& __lambda = result_type(1)) | |
3726 | : _M_param(__lambda) | |
3727 | { } | |
3728 | ||
3729 | explicit | |
3730 | exponential_distribution(const param_type& __p) | |
3731 | : _M_param(__p) | |
3732 | { } | |
3733 | ||
3734 | /** | |
3735 | * @brief Resets the distribution state. | |
3736 | * | |
3737 | * Has no effect on exponential distributions. | |
3738 | */ | |
3739 | void | |
3740 | reset() { } | |
3741 | ||
3742 | /** | |
3743 | * @brief Returns the inverse scale parameter of the distribution. | |
3744 | */ | |
3745 | _RealType | |
3746 | lambda() const | |
3747 | { return _M_param.lambda(); } | |
3748 | ||
3749 | /** | |
3750 | * @brief Returns the parameter set of the distribution. | |
3751 | */ | |
3752 | param_type | |
3753 | param() const | |
3754 | { return _M_param; } | |
3755 | ||
3756 | /** | |
3757 | * @brief Sets the parameter set of the distribution. | |
3758 | * @param __param The new parameter set of the distribution. | |
3759 | */ | |
3760 | void | |
3761 | param(const param_type& __param) | |
3762 | { _M_param = __param; } | |
3763 | ||
3764 | /** | |
3765 | * @brief Returns the greatest lower bound value of the distribution. | |
3766 | */ | |
3767 | result_type | |
3768 | min() const | |
3769 | { return result_type(0); } | |
3770 | ||
3771 | /** | |
3772 | * @brief Returns the least upper bound value of the distribution. | |
3773 | */ | |
3774 | result_type | |
3775 | max() const | |
3776 | { return std::numeric_limits<result_type>::max(); } | |
3777 | ||
3778 | template<typename _UniformRandomNumberGenerator> | |
3779 | result_type | |
3780 | operator()(_UniformRandomNumberGenerator& __urng) | |
3781 | { | |
3782 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
3783 | __aurng(__urng); | |
3784 | return -std::log(__aurng()) / this->lambda(); | |
3785 | } | |
3786 | ||
3787 | template<typename _UniformRandomNumberGenerator> | |
3788 | result_type | |
3789 | operator()(_UniformRandomNumberGenerator& __urng, | |
3790 | const param_type& __p) | |
3791 | { | |
3792 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
3793 | __aurng(__urng); | |
3794 | return -std::log(__aurng()) / __p.lambda(); | |
3795 | } | |
3796 | ||
3797 | private: | |
3798 | param_type _M_param; | |
3799 | }; | |
3800 | ||
3801 | /** | |
3802 | * @brief Return true if two exponential distributions have the same | |
3803 | * parameters. | |
3804 | */ | |
3805 | template<typename _RealType> | |
94986f6d PC |
3806 | inline bool |
3807 | operator==(const std::exponential_distribution<_RealType>& __d1, | |
3808 | const std::exponential_distribution<_RealType>& __d2) | |
8e79468d BK |
3809 | { return __d1.param() == __d2.param(); } |
3810 | ||
3811 | /** | |
3812 | * @brief Inserts a %exponential_distribution random number distribution | |
3813 | * @p __x into the output stream @p __os. | |
3814 | * | |
3815 | * @param __os An output stream. | |
3816 | * @param __x A %exponential_distribution random number distribution. | |
3817 | * | |
3818 | * @returns The output stream with the state of @p __x inserted or in | |
3819 | * an error state. | |
3820 | */ | |
3821 | template<typename _RealType, typename _CharT, typename _Traits> | |
3822 | std::basic_ostream<_CharT, _Traits>& | |
94986f6d PC |
3823 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
3824 | const std::exponential_distribution<_RealType>&); | |
8e79468d BK |
3825 | |
3826 | /** | |
3827 | * @brief Extracts a %exponential_distribution random number distribution | |
3828 | * @p __x from the input stream @p __is. | |
3829 | * | |
3830 | * @param __is An input stream. | |
3831 | * @param __x A %exponential_distribution random number | |
3832 | * generator engine. | |
3833 | * | |
3834 | * @returns The input stream with @p __x extracted or in an error state. | |
3835 | */ | |
3836 | template<typename _RealType, typename _CharT, typename _Traits> | |
3837 | std::basic_istream<_CharT, _Traits>& | |
94986f6d PC |
3838 | operator>>(std::basic_istream<_CharT, _Traits>&, |
3839 | std::exponential_distribution<_RealType>&); | |
8e79468d BK |
3840 | |
3841 | ||
3842 | /** | |
3843 | * @brief A gamma continuous distribution for random numbers. | |
3844 | * | |
3845 | * The formula for the gamma probability density function is | |
3846 | * @f$ p(x|\alpha,\beta) = \frac{1}{\beta\Gamma(\alpha)} | |
3847 | * (x/\beta)^{\alpha - 1} e^{-x/\beta} @f$. | |
3848 | */ | |
3849 | template<typename _RealType = double> | |
3850 | class gamma_distribution | |
3851 | { | |
3852 | public: | |
3853 | /** The type of the range of the distribution. */ | |
3854 | typedef _RealType result_type; | |
3855 | /** Parameter type. */ | |
3856 | struct param_type | |
3857 | { | |
3858 | typedef gamma_distribution<_RealType> distribution_type; | |
3859 | friend class gamma_distribution<_RealType>; | |
3860 | ||
3861 | explicit | |
3862 | param_type(_RealType __alpha = _RealType(1), | |
3863 | _RealType __beta = _RealType(1)) | |
3864 | : _M_alpha(__alpha), _M_beta(__beta) | |
3865 | { | |
3866 | _GLIBCXX_DEBUG_ASSERT(_M_alpha > _RealType(0)); | |
3867 | _M_initialize(); | |
3868 | } | |
3869 | ||
3870 | _RealType | |
3871 | alpha() const | |
3872 | { return _M_alpha; } | |
3873 | ||
3874 | _RealType | |
3875 | beta() const | |
3876 | { return _M_beta; } | |
3877 | ||
3878 | friend bool | |
3879 | operator==(const param_type& __p1, const param_type& __p2) | |
94986f6d PC |
3880 | { return ((__p1._M_alpha == __p2._M_alpha) |
3881 | && (__p1._M_beta == __p2._M_beta)); } | |
8e79468d BK |
3882 | |
3883 | private: | |
3884 | void | |
3885 | _M_initialize(); | |
3886 | ||
3887 | _RealType _M_alpha; | |
3888 | _RealType _M_beta; | |
3889 | ||
3890 | // Hosts either lambda of GB or d of modified Vaduva's. | |
3891 | _RealType _M_l_d; | |
3892 | }; | |
3893 | ||
3894 | public: | |
3895 | /** | |
3896 | * @brief Constructs a gamma distribution with parameters | |
3897 | * @f$ \alpha @f$ and @f$ \beta @f$. | |
3898 | */ | |
3899 | explicit | |
3900 | gamma_distribution(_RealType __alpha = _RealType(1), | |
3901 | _RealType __beta = _RealType(1)) | |
3902 | : _M_param(__alpha, __beta) | |
3903 | { } | |
3904 | ||
3905 | explicit | |
3906 | gamma_distribution(const param_type& __p) | |
3907 | : _M_param(__p) | |
3908 | { } | |
3909 | ||
3910 | /** | |
3911 | * @brief Resets the distribution state. | |
3912 | * | |
3913 | * Does nothing for the gamma distribution. | |
3914 | */ | |
3915 | void | |
3916 | reset() { } | |
3917 | ||
3918 | /** | |
3919 | * @brief Returns the @f$ \alpha @f$ of the distribution. | |
3920 | */ | |
3921 | _RealType | |
3922 | alpha() const | |
3923 | { return _M_param.alpha(); } | |
3924 | ||
3925 | /** | |
3926 | * @brief Returns the @f$ \beta @f$ of the distribution. | |
3927 | */ | |
3928 | _RealType | |
3929 | beta() const | |
3930 | { return _M_param.beta(); } | |
3931 | ||
3932 | /** | |
3933 | * @brief Returns the parameter set of the distribution. | |
3934 | */ | |
3935 | param_type | |
3936 | param() const | |
3937 | { return _M_param; } | |
3938 | ||
3939 | /** | |
3940 | * @brief Sets the parameter set of the distribution. | |
3941 | * @param __param The new parameter set of the distribution. | |
3942 | */ | |
3943 | void | |
3944 | param(const param_type& __param) | |
3945 | { _M_param = __param; } | |
3946 | ||
3947 | /** | |
3948 | * @brief Returns the greatest lower bound value of the distribution. | |
3949 | */ | |
3950 | result_type | |
3951 | min() const | |
3952 | { return result_type(0); } | |
3953 | ||
3954 | /** | |
3955 | * @brief Returns the least upper bound value of the distribution. | |
3956 | */ | |
3957 | result_type | |
3958 | max() const | |
3959 | { return std::numeric_limits<result_type>::max(); } | |
3960 | ||
3961 | template<typename _UniformRandomNumberGenerator> | |
3962 | result_type | |
3963 | operator()(_UniformRandomNumberGenerator& __urng) | |
3964 | { return this->operator()(__urng, this->param()); } | |
3965 | ||
3966 | template<typename _UniformRandomNumberGenerator> | |
3967 | result_type | |
3968 | operator()(_UniformRandomNumberGenerator& __urng, | |
3969 | const param_type& __p); | |
3970 | ||
3971 | private: | |
3972 | param_type _M_param; | |
3973 | }; | |
3974 | ||
3975 | /** | |
3976 | * @brief Return true if two gamma distributions have the same | |
3977 | * parameters. | |
3978 | */ | |
3979 | template<typename _RealType> | |
94986f6d PC |
3980 | inline bool |
3981 | operator==(const std::gamma_distribution<_RealType>& __d1, | |
3982 | const std::gamma_distribution<_RealType>& __d2) | |
8e79468d BK |
3983 | { return __d1.param() == __d2.param(); } |
3984 | ||
3985 | /** | |
3986 | * @brief Inserts a %gamma_distribution random number distribution | |
3987 | * @p __x into the output stream @p __os. | |
3988 | * | |
3989 | * @param __os An output stream. | |
3990 | * @param __x A %gamma_distribution random number distribution. | |
3991 | * | |
3992 | * @returns The output stream with the state of @p __x inserted or in | |
3993 | * an error state. | |
3994 | */ | |
3995 | template<typename _RealType, typename _CharT, typename _Traits> | |
3996 | std::basic_ostream<_CharT, _Traits>& | |
94986f6d PC |
3997 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
3998 | const std::gamma_distribution<_RealType>&); | |
8e79468d BK |
3999 | |
4000 | /** | |
4001 | * @brief Extracts a %gamma_distribution random number distribution | |
4002 | * @p __x from the input stream @p __is. | |
4003 | * | |
4004 | * @param __is An input stream. | |
4005 | * @param __x A %gamma_distribution random number generator engine. | |
4006 | * | |
4007 | * @returns The input stream with @p __x extracted or in an error state. | |
4008 | */ | |
4009 | template<typename _RealType, typename _CharT, typename _Traits> | |
4010 | std::basic_istream<_CharT, _Traits>& | |
94986f6d PC |
4011 | operator>>(std::basic_istream<_CharT, _Traits>&, |
4012 | std::gamma_distribution<_RealType>&); | |
8e79468d BK |
4013 | |
4014 | ||
4015 | /** | |
4016 | * @brief A weibull_distribution random number distribution. | |
4017 | * | |
4018 | * The formula for the normal probability density function is | |
4019 | * @f$ p(x|\alpha,\beta) = \frac{a}{b} (frac{x}{b})^{a-1} | |
4020 | * \exp{(-(frac{x}{b})^a)} @f$. | |
4021 | */ | |
4022 | template<typename _RealType = double> | |
4023 | class weibull_distribution | |
4024 | { | |
4025 | public: | |
4026 | /** The type of the range of the distribution. */ | |
4027 | typedef _RealType result_type; | |
4028 | /** Parameter type. */ | |
4029 | struct param_type | |
4030 | { | |
4031 | typedef weibull_distribution<_RealType> distribution_type; | |
4032 | ||
4033 | explicit | |
4034 | param_type(_RealType __a = _RealType(1), | |
4035 | _RealType __b = _RealType(1)) | |
4036 | : _M_a(__a), _M_b(__b) | |
4037 | { } | |
4038 | ||
4039 | _RealType | |
4040 | a() const | |
4041 | { return _M_a; } | |
4042 | ||
4043 | _RealType | |
4044 | b() const | |
4045 | { return _M_b; } | |
4046 | ||
4047 | friend bool | |
4048 | operator==(const param_type& __p1, const param_type& __p2) | |
4049 | { return (__p1._M_a == __p2._M_a) && (__p1._M_b == __p2._M_b); } | |
4050 | ||
4051 | private: | |
4052 | _RealType _M_a; | |
4053 | _RealType _M_b; | |
4054 | }; | |
4055 | ||
4056 | explicit | |
4057 | weibull_distribution(_RealType __a = _RealType(1), | |
4058 | _RealType __b = _RealType(1)) | |
4059 | : _M_param(__a, __b) | |
4060 | { } | |
4061 | ||
4062 | explicit | |
4063 | weibull_distribution(const param_type& __p) | |
4064 | : _M_param(__p) | |
4065 | { } | |
4066 | ||
4067 | /** | |
4068 | * @brief Resets the distribution state. | |
4069 | */ | |
4070 | void | |
4071 | reset() | |
4072 | { } | |
4073 | ||
4074 | /** | |
4075 | * @brief Return the @f$ a @f$ parameter of the distribution. | |
4076 | */ | |
4077 | _RealType | |
4078 | a() const | |
4079 | { return _M_param.a(); } | |
4080 | ||
4081 | /** | |
4082 | * @brief Return the @f$ b @f$ parameter of the distribution. | |
4083 | */ | |
4084 | _RealType | |
4085 | b() const | |
4086 | { return _M_param.b(); } | |
4087 | ||
4088 | /** | |
4089 | * @brief Returns the parameter set of the distribution. | |
4090 | */ | |
4091 | param_type | |
4092 | param() const | |
4093 | { return _M_param; } | |
4094 | ||
4095 | /** | |
4096 | * @brief Sets the parameter set of the distribution. | |
4097 | * @param __param The new parameter set of the distribution. | |
4098 | */ | |
4099 | void | |
4100 | param(const param_type& __param) | |
4101 | { _M_param = __param; } | |
4102 | ||
4103 | /** | |
4104 | * @brief Returns the greatest lower bound value of the distribution. | |
4105 | */ | |
4106 | result_type | |
4107 | min() const | |
4108 | { return result_type(0); } | |
4109 | ||
4110 | /** | |
4111 | * @brief Returns the least upper bound value of the distribution. | |
4112 | */ | |
4113 | result_type | |
4114 | max() const | |
4115 | { return std::numeric_limits<result_type>::max(); } | |
4116 | ||
4117 | template<typename _UniformRandomNumberGenerator> | |
4118 | result_type | |
4119 | operator()(_UniformRandomNumberGenerator& __urng) | |
4120 | { return this->operator()(__urng, this->param()); } | |
4121 | ||
4122 | template<typename _UniformRandomNumberGenerator> | |
4123 | result_type | |
4124 | operator()(_UniformRandomNumberGenerator& __urng, | |
4125 | const param_type& __p) | |
4126 | { | |
4127 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
4128 | __aurng(__urng); | |
4129 | return __p.b() * std::pow(-std::log(__aurng()), | |
4130 | result_type(1) / __p.a()); | |
4131 | } | |
4132 | ||
4133 | private: | |
4134 | param_type _M_param; | |
4135 | }; | |
4136 | ||
4137 | /** | |
4138 | * @brief Return true if two Weibull distributions have the same | |
4139 | * parameters. | |
4140 | */ | |
4141 | template<typename _RealType> | |
94986f6d PC |
4142 | inline bool |
4143 | operator==(const std::weibull_distribution<_RealType>& __d1, | |
4144 | const std::weibull_distribution<_RealType>& __d2) | |
8e79468d BK |
4145 | { return __d1.param() == __d2.param(); } |
4146 | ||
4147 | /** | |
4148 | * @brief Inserts a %weibull_distribution random number distribution | |
4149 | * @p __x into the output stream @p __os. | |
4150 | * | |
4151 | * @param __os An output stream. | |
4152 | * @param __x A %weibull_distribution random number distribution. | |
4153 | * | |
4154 | * @returns The output stream with the state of @p __x inserted or in | |
4155 | * an error state. | |
4156 | */ | |
4157 | template<typename _RealType, typename _CharT, typename _Traits> | |
4158 | std::basic_ostream<_CharT, _Traits>& | |
94986f6d PC |
4159 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
4160 | const std::weibull_distribution<_RealType>&); | |
8e79468d BK |
4161 | |
4162 | /** | |
4163 | * @brief Extracts a %weibull_distribution random number distribution | |
4164 | * @p __x from the input stream @p __is. | |
4165 | * | |
4166 | * @param __is An input stream. | |
4167 | * @param __x A %weibull_distribution random number | |
4168 | * generator engine. | |
4169 | * | |
4170 | * @returns The input stream with @p __x extracted or in an error state. | |
4171 | */ | |
4172 | template<typename _RealType, typename _CharT, typename _Traits> | |
4173 | std::basic_istream<_CharT, _Traits>& | |
94986f6d PC |
4174 | operator>>(std::basic_istream<_CharT, _Traits>&, |
4175 | std::weibull_distribution<_RealType>&); | |
8e79468d BK |
4176 | |
4177 | ||
4178 | /** | |
4179 | * @brief A extreme_value_distribution random number distribution. | |
4180 | * | |
4181 | * The formula for the normal probability mass function is | |
4182 | * @f$ p(x|a,b) = \frac{1}{b} | |
4183 | * \exp( \frac{a-x}{b} - \exp(\frac{a-x}{b})) @f$ | |
4184 | */ | |
4185 | template<typename _RealType = double> | |
4186 | class extreme_value_distribution | |
4187 | { | |
4188 | public: | |
4189 | /** The type of the range of the distribution. */ | |
4190 | typedef _RealType result_type; | |
4191 | /** Parameter type. */ | |
4192 | struct param_type | |
4193 | { | |
4194 | typedef extreme_value_distribution<_RealType> distribution_type; | |
4195 | ||
4196 | explicit | |
4197 | param_type(_RealType __a = _RealType(0), | |
4198 | _RealType __b = _RealType(1)) | |
4199 | : _M_a(__a), _M_b(__b) | |
4200 | { } | |
4201 | ||
4202 | _RealType | |
4203 | a() const | |
4204 | { return _M_a; } | |
4205 | ||
4206 | _RealType | |
4207 | b() const | |
4208 | { return _M_b; } | |
4209 | ||
4210 | friend bool | |
4211 | operator==(const param_type& __p1, const param_type& __p2) | |
4212 | { return (__p1._M_a == __p2._M_a) && (__p1._M_b == __p2._M_b); } | |
4213 | ||
4214 | private: | |
4215 | _RealType _M_a; | |
4216 | _RealType _M_b; | |
4217 | }; | |
4218 | ||
4219 | explicit | |
4220 | extreme_value_distribution(_RealType __a = _RealType(0), | |
4221 | _RealType __b = _RealType(1)) | |
4222 | : _M_param(__a, __b) | |
4223 | { } | |
4224 | ||
4225 | explicit | |
4226 | extreme_value_distribution(const param_type& __p) | |
4227 | : _M_param(__p) | |
4228 | { } | |
4229 | ||
4230 | /** | |
4231 | * @brief Resets the distribution state. | |
4232 | */ | |
4233 | void | |
4234 | reset() | |
4235 | { } | |
4236 | ||
4237 | /** | |
4238 | * @brief Return the @f$ a @f$ parameter of the distribution. | |
4239 | */ | |
4240 | _RealType | |
4241 | a() const | |
4242 | { return _M_param.a(); } | |
4243 | ||
4244 | /** | |
4245 | * @brief Return the @f$ b @f$ parameter of the distribution. | |
4246 | */ | |
4247 | _RealType | |
4248 | b() const | |
4249 | { return _M_param.b(); } | |
4250 | ||
4251 | /** | |
4252 | * @brief Returns the parameter set of the distribution. | |
4253 | */ | |
4254 | param_type | |
4255 | param() const | |
4256 | { return _M_param; } | |
4257 | ||
4258 | /** | |
4259 | * @brief Sets the parameter set of the distribution. | |
4260 | * @param __param The new parameter set of the distribution. | |
4261 | */ | |
4262 | void | |
4263 | param(const param_type& __param) | |
4264 | { _M_param = __param; } | |
4265 | ||
4266 | /** | |
4267 | * @brief Returns the greatest lower bound value of the distribution. | |
4268 | */ | |
4269 | result_type | |
4270 | min() const | |
4271 | { return std::numeric_limits<result_type>::min(); } | |
4272 | ||
4273 | /** | |
4274 | * @brief Returns the least upper bound value of the distribution. | |
4275 | */ | |
4276 | result_type | |
4277 | max() const | |
4278 | { return std::numeric_limits<result_type>::max(); } | |
4279 | ||
4280 | template<typename _UniformRandomNumberGenerator> | |
4281 | result_type | |
4282 | operator()(_UniformRandomNumberGenerator& __urng) | |
4283 | { return this->operator()(__urng, this->param()); } | |
4284 | ||
4285 | template<typename _UniformRandomNumberGenerator> | |
4286 | result_type | |
4287 | operator()(_UniformRandomNumberGenerator& __urng, | |
4288 | const param_type& __p); | |
4289 | ||
4290 | private: | |
4291 | param_type _M_param; | |
4292 | }; | |
4293 | ||
4294 | /** | |
4295 | * | |
4296 | */ | |
4297 | template<typename _RealType> | |
94986f6d PC |
4298 | inline bool |
4299 | operator==(const std::extreme_value_distribution<_RealType>& __d1, | |
4300 | const std::extreme_value_distribution<_RealType>& __d2) | |
8e79468d BK |
4301 | { return __d1.param() == __d2.param(); } |
4302 | ||
4303 | /** | |
4304 | * @brief Inserts a %extreme_value_distribution random number distribution | |
4305 | * @p __x into the output stream @p __os. | |
4306 | * | |
4307 | * @param __os An output stream. | |
4308 | * @param __x A %extreme_value_distribution random number distribution. | |
4309 | * | |
4310 | * @returns The output stream with the state of @p __x inserted or in | |
4311 | * an error state. | |
4312 | */ | |
4313 | template<typename _RealType, typename _CharT, typename _Traits> | |
4314 | std::basic_ostream<_CharT, _Traits>& | |
94986f6d PC |
4315 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
4316 | const std::extreme_value_distribution<_RealType>&); | |
8e79468d BK |
4317 | |
4318 | /** | |
4319 | * @brief Extracts a %extreme_value_distribution random number | |
4320 | * distribution @p __x from the input stream @p __is. | |
4321 | * | |
4322 | * @param __is An input stream. | |
4323 | * @param __x A %extreme_value_distribution random number | |
4324 | * generator engine. | |
4325 | * | |
4326 | * @returns The input stream with @p __x extracted or in an error state. | |
4327 | */ | |
4328 | template<typename _RealType, typename _CharT, typename _Traits> | |
4329 | std::basic_istream<_CharT, _Traits>& | |
94986f6d PC |
4330 | operator>>(std::basic_istream<_CharT, _Traits>&, |
4331 | std::extreme_value_distribution<_RealType>&); | |
8e79468d BK |
4332 | |
4333 | ||
4334 | /** | |
4335 | * @brief A discrete_distribution random number distribution. | |
4336 | * | |
4337 | * The formula for the discrete probability mass function is | |
4338 | * | |
4339 | */ | |
4340 | template<typename _IntType = int> | |
4341 | class discrete_distribution | |
4342 | { | |
4343 | __glibcxx_class_requires(_IntType, _IntegerConcept) | |
4344 | ||
4345 | public: | |
4346 | /** The type of the range of the distribution. */ | |
4347 | typedef _IntType result_type; | |
4348 | /** Parameter type. */ | |
4349 | struct param_type | |
4350 | { | |
4351 | typedef discrete_distribution<_IntType> distribution_type; | |
4352 | friend class discrete_distribution<_IntType>; | |
4353 | ||
4354 | param_type() | |
4355 | : _M_prob(), _M_cp() | |
4356 | { _M_initialize(); } | |
4357 | ||
4358 | template<typename _InputIterator> | |
4359 | param_type(_InputIterator __wbegin, | |
4360 | _InputIterator __wend) | |
4361 | : _M_prob(__wbegin, __wend), _M_cp() | |
4362 | { _M_initialize(); } | |
4363 | ||
4364 | param_type(initializer_list<double> __wil) | |
4365 | : _M_prob(__wil.begin(), __wil.end()), _M_cp() | |
4366 | { _M_initialize(); } | |
4367 | ||
4368 | template<typename _Func> | |
4369 | param_type(size_t __nw, double __xmin, double __xmax, | |
4370 | _Func __fw); | |
4371 | ||
4372 | std::vector<double> | |
4373 | probabilities() const | |
4374 | { return _M_prob; } | |
4375 | ||
4376 | friend bool | |
4377 | operator==(const param_type& __p1, const param_type& __p2) | |
4378 | { return __p1._M_prob == __p2._M_prob; } | |
4379 | ||
4380 | private: | |
4381 | void | |
4382 | _M_initialize(); | |
4383 | ||
4384 | std::vector<double> _M_prob; | |
4385 | std::vector<double> _M_cp; | |
4386 | }; | |
4387 | ||
4388 | discrete_distribution() | |
4389 | : _M_param() | |
4390 | { } | |
4391 | ||
4392 | template<typename _InputIterator> | |
4393 | discrete_distribution(_InputIterator __wbegin, | |
4394 | _InputIterator __wend) | |
4395 | : _M_param(__wbegin, __wend) | |
4396 | { } | |
4397 | ||
4398 | discrete_distribution(initializer_list<double> __wil) | |
4399 | : _M_param(__wil) | |
4400 | { } | |
4401 | ||
4402 | template<typename _Func> | |
4403 | discrete_distribution(size_t __nw, double __xmin, double __xmax, | |
4404 | _Func __fw) | |
4405 | : _M_param(__nw, __xmin, __xmax, __fw) | |
4406 | { } | |
4407 | ||
4408 | explicit | |
4409 | discrete_distribution(const param_type& __p) | |
4410 | : _M_param(__p) | |
4411 | { } | |
4412 | ||
4413 | /** | |
4414 | * @brief Resets the distribution state. | |
4415 | */ | |
4416 | void | |
4417 | reset() | |
4418 | { } | |
4419 | ||
4420 | /** | |
4421 | * @brief Returns the probabilities of the distribution. | |
4422 | */ | |
4423 | std::vector<double> | |
4424 | probabilities() const | |
4425 | { return _M_param.probabilities(); } | |
4426 | ||
4427 | /** | |
4428 | * @brief Returns the parameter set of the distribution. | |
4429 | */ | |
4430 | param_type | |
4431 | param() const | |
4432 | { return _M_param; } | |
4433 | ||
4434 | /** | |
4435 | * @brief Sets the parameter set of the distribution. | |
4436 | * @param __param The new parameter set of the distribution. | |
4437 | */ | |
4438 | void | |
4439 | param(const param_type& __param) | |
4440 | { _M_param = __param; } | |
4441 | ||
4442 | /** | |
4443 | * @brief Returns the greatest lower bound value of the distribution. | |
4444 | */ | |
4445 | result_type | |
4446 | min() const | |
4447 | { return result_type(0); } | |
4448 | ||
4449 | /** | |
4450 | * @brief Returns the least upper bound value of the distribution. | |
4451 | */ | |
4452 | result_type | |
4453 | max() const | |
4454 | { return this->_M_param._M_prob.size() - 1; } | |
4455 | ||
4456 | template<typename _UniformRandomNumberGenerator> | |
4457 | result_type | |
4458 | operator()(_UniformRandomNumberGenerator& __urng) | |
4459 | { return this->operator()(__urng, this->param()); } | |
4460 | ||
4461 | template<typename _UniformRandomNumberGenerator> | |
4462 | result_type | |
4463 | operator()(_UniformRandomNumberGenerator& __urng, | |
4464 | const param_type& __p); | |
4465 | ||
4466 | /** | |
4467 | * @brief Inserts a %discrete_distribution random number distribution | |
4468 | * @p __x into the output stream @p __os. | |
4469 | * | |
4470 | * @param __os An output stream. | |
4471 | * @param __x A %discrete_distribution random number distribution. | |
4472 | * | |
4473 | * @returns The output stream with the state of @p __x inserted or in | |
4474 | * an error state. | |
4475 | */ | |
4476 | template<typename _IntType1, typename _CharT, typename _Traits> | |
4477 | friend std::basic_ostream<_CharT, _Traits>& | |
94986f6d PC |
4478 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
4479 | const std::discrete_distribution<_IntType1>&); | |
8e79468d BK |
4480 | |
4481 | /** | |
4482 | * @brief Extracts a %discrete_distribution random number distribution | |
4483 | * @p __x from the input stream @p __is. | |
4484 | * | |
4485 | * @param __is An input stream. | |
4486 | * @param __x A %discrete_distribution random number | |
4487 | * generator engine. | |
4488 | * | |
4489 | * @returns The input stream with @p __x extracted or in an error | |
4490 | * state. | |
4491 | */ | |
4492 | template<typename _IntType1, typename _CharT, typename _Traits> | |
4493 | friend std::basic_istream<_CharT, _Traits>& | |
94986f6d PC |
4494 | operator>>(std::basic_istream<_CharT, _Traits>&, |
4495 | std::discrete_distribution<_IntType1>&); | |
8e79468d BK |
4496 | |
4497 | private: | |
4498 | param_type _M_param; | |
4499 | }; | |
4500 | ||
4501 | /** | |
4502 | * | |
4503 | */ | |
4504 | template<typename _IntType> | |
94986f6d PC |
4505 | inline bool |
4506 | operator==(const std::discrete_distribution<_IntType>& __d1, | |
4507 | const std::discrete_distribution<_IntType>& __d2) | |
8e79468d BK |
4508 | { return __d1.param() == __d2.param(); } |
4509 | ||
4510 | ||
4511 | /** | |
4512 | * @brief A piecewise_constant_distribution random number distribution. | |
4513 | * | |
4514 | * The formula for the piecewise constant probability mass function is | |
4515 | * | |
4516 | */ | |
4517 | template<typename _RealType = double> | |
4518 | class piecewise_constant_distribution | |
4519 | { | |
4520 | public: | |
4521 | /** The type of the range of the distribution. */ | |
4522 | typedef _RealType result_type; | |
4523 | /** Parameter type. */ | |
4524 | struct param_type | |
4525 | { | |
4526 | typedef piecewise_constant_distribution<_RealType> distribution_type; | |
4527 | friend class piecewise_constant_distribution<_RealType>; | |
4528 | ||
4529 | param_type(); | |
4530 | ||
4531 | template<typename _InputIteratorB, typename _InputIteratorW> | |
4532 | param_type(_InputIteratorB __bfirst, | |
4533 | _InputIteratorB __bend, | |
4534 | _InputIteratorW __wbegin); | |
4535 | ||
4536 | template<typename _Func> | |
4537 | param_type(initializer_list<_RealType> __bil, _Func __fw); | |
4538 | ||
4539 | template<typename _Func> | |
4540 | param_type(size_t __nw, _RealType __xmin, _RealType __xmax, | |
4541 | _Func __fw); | |
4542 | ||
4543 | std::vector<_RealType> | |
4544 | intervals() const | |
4545 | { return _M_int; } | |
4546 | ||
4547 | std::vector<double> | |
4548 | densities() const | |
4549 | { return _M_den; } | |
4550 | ||
4551 | friend bool | |
4552 | operator==(const param_type& __p1, const param_type& __p2) | |
94986f6d PC |
4553 | { return ((__p1._M_int == __p2._M_int) |
4554 | && (__p1._M_den == __p2._M_den)); } | |
8e79468d BK |
4555 | |
4556 | private: | |
4557 | void | |
4558 | _M_initialize(); | |
4559 | ||
4560 | std::vector<_RealType> _M_int; | |
4561 | std::vector<double> _M_den; | |
4562 | std::vector<double> _M_cp; | |
4563 | }; | |
4564 | ||
4565 | explicit | |
4566 | piecewise_constant_distribution() | |
4567 | : _M_param() | |
4568 | { } | |
4569 | ||
4570 | template<typename _InputIteratorB, typename _InputIteratorW> | |
4571 | piecewise_constant_distribution(_InputIteratorB __bfirst, | |
4572 | _InputIteratorB __bend, | |
4573 | _InputIteratorW __wbegin) | |
4574 | : _M_param(__bfirst, __bend, __wbegin) | |
4575 | { } | |
4576 | ||
4577 | template<typename _Func> | |
4578 | piecewise_constant_distribution(initializer_list<_RealType> __bil, | |
4579 | _Func __fw) | |
4580 | : _M_param(__bil, __fw) | |
4581 | { } | |
4582 | ||
4583 | template<typename _Func> | |
4584 | piecewise_constant_distribution(size_t __nw, | |
4585 | _RealType __xmin, _RealType __xmax, | |
4586 | _Func __fw) | |
4587 | : _M_param(__nw, __xmin, __xmax, __fw) | |
4588 | { } | |
4589 | ||
4590 | explicit | |
4591 | piecewise_constant_distribution(const param_type& __p) | |
4592 | : _M_param(__p) | |
4593 | { } | |
4594 | ||
4595 | /** | |
4596 | * @brief Resets the distribution state. | |
4597 | */ | |
4598 | void | |
4599 | reset() | |
4600 | { } | |
4601 | ||
4602 | /** | |
4603 | * @brief Returns a vector of the intervals. | |
4604 | */ | |
4605 | std::vector<_RealType> | |
4606 | intervals() const | |
4607 | { return _M_param.intervals(); } | |
4608 | ||
4609 | /** | |
4610 | * @brief Returns a vector of the probability densities. | |
4611 | */ | |
4612 | std::vector<double> | |
4613 | densities() const | |
4614 | { return _M_param.densities(); } | |
4615 | ||
4616 | /** | |
4617 | * @brief Returns the parameter set of the distribution. | |
4618 | */ | |
4619 | param_type | |
4620 | param() const | |
4621 | { return _M_param; } | |
4622 | ||
4623 | /** | |
4624 | * @brief Sets the parameter set of the distribution. | |
4625 | * @param __param The new parameter set of the distribution. | |
4626 | */ | |
4627 | void | |
4628 | param(const param_type& __param) | |
4629 | { _M_param = __param; } | |
4630 | ||
4631 | /** | |
4632 | * @brief Returns the greatest lower bound value of the distribution. | |
4633 | */ | |
4634 | result_type | |
4635 | min() const | |
4636 | { return this->_M_param._M_int.front(); } | |
4637 | ||
4638 | /** | |
4639 | * @brief Returns the least upper bound value of the distribution. | |
4640 | */ | |
4641 | result_type | |
4642 | max() const | |
4643 | { return this->_M_param._M_int.back(); } | |
4644 | ||
4645 | template<typename _UniformRandomNumberGenerator> | |
4646 | result_type | |
4647 | operator()(_UniformRandomNumberGenerator& __urng) | |
4648 | { return this->operator()(__urng, this->param()); } | |
4649 | ||
4650 | template<typename _UniformRandomNumberGenerator> | |
4651 | result_type | |
4652 | operator()(_UniformRandomNumberGenerator& __urng, | |
4653 | const param_type& __p); | |
4654 | ||
4655 | /** | |
4656 | * @brief Inserts a %piecewise_constan_distribution random | |
4657 | * number distribution @p __x into the output stream @p __os. | |
4658 | * | |
4659 | * @param __os An output stream. | |
4660 | * @param __x A %piecewise_constan_distribution random number | |
4661 | * distribution. | |
4662 | * | |
4663 | * @returns The output stream with the state of @p __x inserted or in | |
4664 | * an error state. | |
4665 | */ | |
4666 | template<typename _RealType1, typename _CharT, typename _Traits> | |
4667 | friend std::basic_ostream<_CharT, _Traits>& | |
94986f6d PC |
4668 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
4669 | const std::piecewise_constant_distribution<_RealType1>&); | |
8e79468d BK |
4670 | |
4671 | /** | |
4672 | * @brief Extracts a %piecewise_constan_distribution random | |
4673 | * number distribution @p __x from the input stream @p __is. | |
4674 | * | |
4675 | * @param __is An input stream. | |
4676 | * @param __x A %piecewise_constan_distribution random number | |
4677 | * generator engine. | |
4678 | * | |
4679 | * @returns The input stream with @p __x extracted or in an error | |
4680 | * state. | |
4681 | */ | |
4682 | template<typename _RealType1, typename _CharT, typename _Traits> | |
4683 | friend std::basic_istream<_CharT, _Traits>& | |
94986f6d PC |
4684 | operator>>(std::basic_istream<_CharT, _Traits>&, |
4685 | std::piecewise_constant_distribution<_RealType1>&); | |
8e79468d BK |
4686 | |
4687 | private: | |
4688 | param_type _M_param; | |
4689 | }; | |
4690 | ||
4691 | /** | |
4692 | * | |
4693 | */ | |
4694 | template<typename _RealType> | |
94986f6d PC |
4695 | inline bool |
4696 | operator==(const std::piecewise_constant_distribution<_RealType>& __d1, | |
4697 | const std::piecewise_constant_distribution<_RealType>& __d2) | |
8e79468d BK |
4698 | { return __d1.param() == __d2.param(); } |
4699 | ||
4700 | ||
4701 | /** | |
4702 | * @brief A piecewise_linear_distribution random number distribution. | |
4703 | * | |
4704 | * The formula for the piecewise linear probability mass function is | |
4705 | * | |
4706 | */ | |
4707 | template<typename _RealType = double> | |
4708 | class piecewise_linear_distribution | |
4709 | { | |
4710 | public: | |
4711 | /** The type of the range of the distribution. */ | |
4712 | typedef _RealType result_type; | |
4713 | /** Parameter type. */ | |
4714 | struct param_type | |
4715 | { | |
4716 | typedef piecewise_linear_distribution<_RealType> distribution_type; | |
4717 | friend class piecewise_linear_distribution<_RealType>; | |
4718 | ||
4719 | param_type(); | |
4720 | ||
4721 | template<typename _InputIteratorB, typename _InputIteratorW> | |
4722 | param_type(_InputIteratorB __bfirst, | |
4723 | _InputIteratorB __bend, | |
4724 | _InputIteratorW __wbegin); | |
4725 | ||
4726 | template<typename _Func> | |
4727 | param_type(initializer_list<_RealType> __bil, _Func __fw); | |
4728 | ||
4729 | template<typename _Func> | |
4730 | param_type(size_t __nw, _RealType __xmin, _RealType __xmax, | |
4731 | _Func __fw); | |
4732 | ||
4733 | std::vector<_RealType> | |
4734 | intervals() const | |
4735 | { return _M_int; } | |
4736 | ||
4737 | std::vector<double> | |
4738 | densities() const | |
4739 | { return _M_den; } | |
4740 | ||
4741 | friend bool | |
4742 | operator==(const param_type& __p1, const param_type& __p2) | |
94986f6d PC |
4743 | { return ((__p1._M_int == __p2._M_int) |
4744 | && (__p1._M_den == __p2._M_den)); } | |
8e79468d BK |
4745 | |
4746 | private: | |
4747 | void | |
4748 | _M_initialize(); | |
4749 | ||
4750 | std::vector<_RealType> _M_int; | |
4751 | std::vector<double> _M_den; | |
4752 | std::vector<double> _M_cp; | |
4753 | std::vector<double> _M_m; | |
4754 | }; | |
4755 | ||
4756 | explicit | |
4757 | piecewise_linear_distribution() | |
4758 | : _M_param() | |
4759 | { } | |
4760 | ||
4761 | template<typename _InputIteratorB, typename _InputIteratorW> | |
4762 | piecewise_linear_distribution(_InputIteratorB __bfirst, | |
4763 | _InputIteratorB __bend, | |
4764 | _InputIteratorW __wbegin) | |
4765 | : _M_param(__bfirst, __bend, __wbegin) | |
4766 | { } | |
4767 | ||
4768 | template<typename _Func> | |
4769 | piecewise_linear_distribution(initializer_list<_RealType> __bil, | |
4770 | _Func __fw) | |
4771 | : _M_param(__bil, __fw) | |
4772 | { } | |
4773 | ||
4774 | template<typename _Func> | |
4775 | piecewise_linear_distribution(size_t __nw, | |
4776 | _RealType __xmin, _RealType __xmax, | |
4777 | _Func __fw) | |
4778 | : _M_param(__nw, __xmin, __xmax, __fw) | |
4779 | { } | |
4780 | ||
4781 | explicit | |
4782 | piecewise_linear_distribution(const param_type& __p) | |
4783 | : _M_param(__p) | |
4784 | { } | |
4785 | ||
4786 | /** | |
4787 | * Resets the distribution state. | |
4788 | */ | |
4789 | void | |
4790 | reset() | |
4791 | { } | |
4792 | ||
4793 | /** | |
4794 | * @brief Return the intervals of the distribution. | |
4795 | */ | |
4796 | std::vector<_RealType> | |
4797 | intervals() const | |
4798 | { return _M_param.intervals(); } | |
4799 | ||
4800 | /** | |
4801 | * @brief Return a vector of the probability densities of the | |
4802 | * distribution. | |
4803 | */ | |
4804 | std::vector<double> | |
4805 | densities() const | |
4806 | { return _M_param.densities(); } | |
4807 | ||
4808 | /** | |
4809 | * @brief Returns the parameter set of the distribution. | |
4810 | */ | |
4811 | param_type | |
4812 | param() const | |
4813 | { return _M_param; } | |
4814 | ||
4815 | /** | |
4816 | * @brief Sets the parameter set of the distribution. | |
4817 | * @param __param The new parameter set of the distribution. | |
4818 | */ | |
4819 | void | |
4820 | param(const param_type& __param) | |
4821 | { _M_param = __param; } | |
4822 | ||
4823 | /** | |
4824 | * @brief Returns the greatest lower bound value of the distribution. | |
4825 | */ | |
4826 | result_type | |
4827 | min() const | |
4828 | { return this->_M_param._M_int.front(); } | |
4829 | ||
4830 | /** | |
4831 | * @brief Returns the least upper bound value of the distribution. | |
4832 | */ | |
4833 | result_type | |
4834 | max() const | |
4835 | { return this->_M_param._M_int.back(); } | |
4836 | ||
4837 | template<typename _UniformRandomNumberGenerator> | |
4838 | result_type | |
4839 | operator()(_UniformRandomNumberGenerator& __urng) | |
4840 | { return this->operator()(__urng, this->param()); } | |
4841 | ||
4842 | template<typename _UniformRandomNumberGenerator> | |
4843 | result_type | |
4844 | operator()(_UniformRandomNumberGenerator& __urng, | |
4845 | const param_type& __p); | |
4846 | ||
4847 | /** | |
4848 | * @brief Inserts a %piecewise_linear_distribution random number | |
4849 | * distribution @p __x into the output stream @p __os. | |
4850 | * | |
4851 | * @param __os An output stream. | |
4852 | * @param __x A %piecewise_linear_distribution random number | |
4853 | * distribution. | |
4854 | * | |
4855 | * @returns The output stream with the state of @p __x inserted or in | |
4856 | * an error state. | |
4857 | */ | |
4858 | template<typename _RealType1, typename _CharT, typename _Traits> | |
4859 | friend std::basic_ostream<_CharT, _Traits>& | |
94986f6d PC |
4860 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
4861 | const std::piecewise_linear_distribution<_RealType1>&); | |
8e79468d BK |
4862 | |
4863 | /** | |
4864 | * @brief Extracts a %piecewise_linear_distribution random number | |
4865 | * distribution @p __x from the input stream @p __is. | |
4866 | * | |
4867 | * @param __is An input stream. | |
4868 | * @param __x A %piecewise_linear_distribution random number | |
4869 | * generator engine. | |
4870 | * | |
4871 | * @returns The input stream with @p __x extracted or in an error | |
4872 | * state. | |
4873 | */ | |
4874 | template<typename _RealType1, typename _CharT, typename _Traits> | |
4875 | friend std::basic_istream<_CharT, _Traits>& | |
94986f6d PC |
4876 | operator>>(std::basic_istream<_CharT, _Traits>&, |
4877 | std::piecewise_linear_distribution<_RealType1>&); | |
8e79468d BK |
4878 | |
4879 | private: | |
4880 | param_type _M_param; | |
4881 | }; | |
4882 | ||
4883 | /** | |
4884 | * | |
4885 | */ | |
4886 | template<typename _RealType> | |
94986f6d PC |
4887 | inline bool |
4888 | operator==(const std::piecewise_linear_distribution<_RealType>& __d1, | |
4889 | const std::piecewise_linear_distribution<_RealType>& __d2) | |
8e79468d BK |
4890 | { return __d1.param() == __d2.param(); } |
4891 | ||
4892 | /* @} */ // group std_random_distributions_poisson | |
4893 | ||
4894 | /* @} */ // group std_random_distributions | |
4895 | ||
4896 | /** | |
4897 | * @addtogroup std_random_utilities Random Number Utilities | |
4898 | * @ingroup std_random | |
4899 | * @{ | |
4900 | */ | |
4901 | ||
4902 | /** | |
4903 | * @brief The seed_seq class generates sequences of seeds for random | |
4904 | * number generators. | |
4905 | */ | |
4906 | class seed_seq | |
4907 | { | |
4908 | ||
4909 | public: | |
4910 | /** The type of the seed vales. */ | |
4911 | typedef uint_least32_t result_type; | |
4912 | ||
4913 | /** Default constructor. */ | |
4914 | seed_seq() | |
4915 | : _M_v() | |
4916 | { } | |
4917 | ||
4918 | template<typename _IntType> | |
4919 | seed_seq(std::initializer_list<_IntType> il); | |
4920 | ||
4921 | template<typename _InputIterator> | |
4922 | seed_seq(_InputIterator __begin, _InputIterator __end); | |
4923 | ||
4924 | // generating functions | |
4925 | template<typename _RandomAccessIterator> | |
4926 | void | |
4927 | generate(_RandomAccessIterator __begin, _RandomAccessIterator __end); | |
4928 | ||
4929 | // property functions | |
4930 | size_t size() const | |
4931 | { return _M_v.size(); } | |
4932 | ||
4933 | template<typename OutputIterator> | |
4934 | void | |
4935 | param(OutputIterator __dest) const | |
4936 | { std::copy(_M_v.begin(), _M_v.end(), __dest); } | |
4937 | ||
4938 | private: | |
4939 | /// | |
94986f6d | 4940 | std::vector<result_type> _M_v; |
8e79468d BK |
4941 | }; |
4942 | ||
4943 | /* @} */ // group std_random_utilities | |
4944 | ||
4945 | /* @} */ // group std_random | |
4946 | ||
4947 | } | |
4948 |