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The C and C++ Include Header Files
/usr/include/c++/13/tr1/random.h
$ cat -n /usr/include/c++/13/tr1/random.h 1 // random number generation -*- C++ -*- 2 3 // Copyright (C) 2009-2023 Free Software Foundation, Inc. 4 // 5 // This file is part of the GNU ISO C++ Library. This library is free 6 // software; you can redistribute it and/or modify it under the 7 // terms of the GNU General Public License as published by the 8 // Free Software Foundation; either version 3, or (at your option) 9 // any later version. 10 11 // This library is distributed in the hope that it will be useful, 12 // but WITHOUT ANY WARRANTY; without even the implied warranty of 13 // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 14 // GNU General Public License for more details. 15 16 // Under Section 7 of GPL version 3, you are granted additional 17 // permissions described in the GCC Runtime Library Exception, version 18 // 3.1, as published by the Free Software Foundation. 19 20 // You should have received a copy of the GNU General Public License and 21 // a copy of the GCC Runtime Library Exception along with this program; 22 // see the files COPYING3 and COPYING.RUNTIME respectively. If not, see 23 // <http://www.gnu.org/licenses/>. 24 25 /** 26 * @file tr1/random.h 27 * This is an internal header file, included by other library headers. 28 * Do not attempt to use it directly. @headername{tr1/random} 29 */ 30 31 #ifndef _GLIBCXX_TR1_RANDOM_H 32 #define _GLIBCXX_TR1_RANDOM_H 1 33 34 #pragma GCC system_header 35 36 namespace std _GLIBCXX_VISIBILITY(default) 37 { 38 _GLIBCXX_BEGIN_NAMESPACE_VERSION 39 40 namespace tr1 41 { 42 // [5.1] Random number generation 43 44 /** 45 * @addtogroup tr1_random Random Number Generation 46 * A facility for generating random numbers on selected distributions. 47 * @{ 48 */ 49 50 /* 51 * Implementation-space details. 52 */ 53 namespace __detail 54 { 55 template<typename _UIntType, int __w, 56 bool = __w < std::numeric_limits<_UIntType>::digits> 57 struct _Shift 58 { static const _UIntType __value = 0; }; 59 60 template<typename _UIntType, int __w> 61 struct _Shift<_UIntType, __w, true> 62 { static const _UIntType __value = _UIntType(1) << __w; }; 63 64 template<typename _Tp, _Tp __a, _Tp __c, _Tp __m, bool> 65 struct _Mod; 66 67 // Dispatch based on modulus value to prevent divide-by-zero compile-time 68 // errors when m == 0. 69 template<typename _Tp, _Tp __a, _Tp __c, _Tp __m> 70 inline _Tp 71 __mod(_Tp __x) 72 { return _Mod<_Tp, __a, __c, __m, __m == 0>::__calc(__x); } 73 74 typedef __gnu_cxx::__conditional_type<(sizeof(unsigned) == 4), 75 unsigned, unsigned long>::__type _UInt32Type; 76 77 /* 78 * An adaptor class for converting the output of any Generator into 79 * the input for a specific Distribution. 80 */ 81 template<typename _Engine, typename _Distribution> 82 struct _Adaptor 83 { 84 typedef typename _Engine::result_type _Engine_result_type; 85 typedef typename _Distribution::input_type result_type; 86 87 public: 88 _Adaptor(const _Engine& __g) 89 : _M_g(__g) { } 90 91 result_type 92 min() const 93 { 94 result_type __return_value; 95 if (is_integral<_Engine_result_type>::value 96 && is_integral<result_type>::value) 97 __return_value = _M_g.min(); 98 else 99 __return_value = result_type(0); 100 return __return_value; 101 } 102 103 result_type 104 max() const 105 { 106 result_type __return_value; 107 if (is_integral<_Engine_result_type>::value 108 && is_integral<result_type>::value) 109 __return_value = _M_g.max(); 110 else if (!is_integral<result_type>::value) 111 __return_value = result_type(1); 112 else 113 __return_value = std::numeric_limits<result_type>::max() - 1; 114 return __return_value; 115 } 116 117 /* 118 * Converts a value generated by the adapted random number generator 119 * into a value in the input domain for the dependent random number 120 * distribution. 121 * 122 * Because the type traits are compile time constants only the 123 * appropriate clause of the if statements will actually be emitted 124 * by the compiler. 125 */ 126 result_type 127 operator()() 128 { 129 result_type __return_value; 130 if (is_integral<_Engine_result_type>::value 131 && is_integral<result_type>::value) 132 __return_value = _M_g(); 133 else if (!is_integral<_Engine_result_type>::value 134 && !is_integral<result_type>::value) 135 __return_value = result_type(_M_g() - _M_g.min()) 136 / result_type(_M_g.max() - _M_g.min()); 137 else if (is_integral<_Engine_result_type>::value 138 && !is_integral<result_type>::value) 139 __return_value = result_type(_M_g() - _M_g.min()) 140 / result_type(_M_g.max() - _M_g.min() + result_type(1)); 141 else 142 __return_value = (((_M_g() - _M_g.min()) 143 / (_M_g.max() - _M_g.min())) 144 * std::numeric_limits<result_type>::max()); 145 return __return_value; 146 } 147 148 _Engine _M_g; 149 }; 150 } // namespace __detail 151 152 /** 153 * Produces random numbers on a given distribution function using a 154 * non-uniform random number generation engine. 155 * 156 * @todo the engine_value_type needs to be studied more carefully. 157 */ 158 template<typename _Engine, typename _Dist> 159 class variate_generator 160 { 161 template<typename _Eng> 162 struct _Value 163 { 164 typedef _Eng type; 165 166 static const _Eng& 167 _S_ref(const _Eng& __e) { return __e; } 168 }; 169 170 template<typename _Eng> 171 struct _Value<_Eng*> 172 { 173 typedef _Eng type; 174 175 __attribute__((__nonnull__)) 176 static const _Eng& 177 _S_ref(const _Eng* __e) { return *__e; } 178 }; 179 180 template<typename _Eng> 181 struct _Value<_Eng&> 182 { 183 typedef _Eng type; 184 185 static const _Eng& 186 _S_ref(const _Eng& __e) { return __e; } 187 }; 188 189 public: 190 typedef _Engine engine_type; 191 typedef typename _Value<_Engine>::type engine_value_type; 192 typedef _Dist distribution_type; 193 typedef typename _Dist::result_type result_type; 194 195 // Concept requirements. 196 __glibcxx_class_requires(engine_value_type, _CopyConstructibleConcept) 197 // __glibcxx_class_requires(_Engine, _EngineConcept) 198 // __glibcxx_class_requires(_Dist, _EngineConcept) 199 200 // tr1:5.1.1 table 5.1 requirement 201 typedef typename __gnu_cxx::__enable_if< 202 is_arithmetic<result_type>::value, result_type>::__type _IsValidType; 203 204 /** 205 * Constructs a variate generator with the uniform random number 206 * generator @p __eng for the random distribution @p __dist. 207 * 208 * @throws Any exceptions which may thrown by the copy constructors of 209 * the @p _Engine or @p _Dist objects. 210 */ 211 variate_generator(engine_type __eng, distribution_type __dist) 212 : _M_engine(_Value<_Engine>::_S_ref(__eng)), _M_dist(__dist) { } 213 214 /** 215 * Gets the next generated value on the distribution. 216 */ 217 result_type 218 operator()() 219 { return _M_dist(_M_engine); } 220 221 /** 222 * WTF? 223 */ 224 template<typename _Tp> 225 result_type 226 operator()(_Tp __value) 227 { return _M_dist(_M_engine, __value); } 228 229 /** 230 * Gets a reference to the underlying uniform random number generator 231 * object. 232 */ 233 engine_value_type& 234 engine() 235 { return _M_engine._M_g; } 236 237 /** 238 * Gets a const reference to the underlying uniform random number 239 * generator object. 240 */ 241 const engine_value_type& 242 engine() const 243 { return _M_engine._M_g; } 244 245 /** 246 * Gets a reference to the underlying random distribution. 247 */ 248 distribution_type& 249 distribution() 250 { return _M_dist; } 251 252 /** 253 * Gets a const reference to the underlying random distribution. 254 */ 255 const distribution_type& 256 distribution() const 257 { return _M_dist; } 258 259 /** 260 * Gets the closed lower bound of the distribution interval. 261 */ 262 result_type 263 min() const 264 { return this->distribution().min(); } 265 266 /** 267 * Gets the closed upper bound of the distribution interval. 268 */ 269 result_type 270 max() const 271 { return this->distribution().max(); } 272 273 private: 274 __detail::_Adaptor<engine_value_type, _Dist> _M_engine; 275 distribution_type _M_dist; 276 }; 277 278 279 /** 280 * @addtogroup tr1_random_generators Random Number Generators 281 * @ingroup tr1_random 282 * 283 * These classes define objects which provide random or pseudorandom 284 * numbers, either from a discrete or a continuous interval. The 285 * random number generator supplied as a part of this library are 286 * all uniform random number generators which provide a sequence of 287 * random number uniformly distributed over their range. 288 * 289 * A number generator is a function object with an operator() that 290 * takes zero arguments and returns a number. 291 * 292 * A compliant random number generator must satisfy the following 293 * requirements. <table border=1 cellpadding=10 cellspacing=0> 294 * <caption align=top>Random Number Generator Requirements</caption> 295 * <tr><td>To be documented.</td></tr> </table> 296 * 297 * @{ 298 */ 299 300 /** 301 * @brief A model of a linear congruential random number generator. 302 * 303 * A random number generator that produces pseudorandom numbers using the 304 * linear function @f$x_{i+1}\leftarrow(ax_{i} + c) \bmod m @f$. 305 * 306 * The template parameter @p _UIntType must be an unsigned integral type 307 * large enough to store values up to (__m-1). If the template parameter 308 * @p __m is 0, the modulus @p __m used is 309 * std::numeric_limits<_UIntType>::max() plus 1. Otherwise, the template 310 * parameters @p __a and @p __c must be less than @p __m. 311 * 312 * The size of the state is @f$ 1 @f$. 313 */ 314 template<class _UIntType, _UIntType __a, _UIntType __c, _UIntType __m> 315 class linear_congruential 316 { 317 __glibcxx_class_requires(_UIntType, _UnsignedIntegerConcept) 318 // __glibcpp_class_requires(__a < __m && __c < __m) 319 320 public: 321 /** The type of the generated random value. */ 322 typedef _UIntType result_type; 323 324 /** The multiplier. */ 325 static const _UIntType multiplier = __a; 326 /** An increment. */ 327 static const _UIntType increment = __c; 328 /** The modulus. */ 329 static const _UIntType modulus = __m; 330 331 /** 332 * Constructs a %linear_congruential random number generator engine with 333 * seed @p __s. The default seed value is 1. 334 * 335 * @param __s The initial seed value. 336 */ 337 explicit 338 linear_congruential(unsigned long __x0 = 1) 339 { this->seed(__x0); } 340 341 /** 342 * Constructs a %linear_congruential random number generator engine 343 * seeded from the generator function @p __g. 344 * 345 * @param __g The seed generator function. 346 */ 347 template<class _Gen> 348 linear_congruential(_Gen& __g) 349 { this->seed(__g); } 350 351 /** 352 * Reseeds the %linear_congruential random number generator engine 353 * sequence to the seed @g __s. 354 * 355 * @param __s The new seed. 356 */ 357 void 358 seed(unsigned long __s = 1); 359 360 /** 361 * Reseeds the %linear_congruential random number generator engine 362 * sequence using values from the generator function @p __g. 363 * 364 * @param __g the seed generator function. 365 */ 366 template<class _Gen> 367 void 368 seed(_Gen& __g) 369 { seed(__g, typename is_fundamental<_Gen>::type()); } 370 371 /** 372 * Gets the smallest possible value in the output range. 373 * 374 * The minimum depends on the @p __c parameter: if it is zero, the 375 * minimum generated must be > 0, otherwise 0 is allowed. 376 */ 377 result_type 378 min() const 379 { return (__detail::__mod<_UIntType, 1, 0, __m>(__c) == 0) ? 1 : 0; } 380 381 /** 382 * Gets the largest possible value in the output range. 383 */ 384 result_type 385 max() const 386 { return __m - 1; } 387 388 /** 389 * Gets the next random number in the sequence. 390 */ 391 result_type 392 operator()(); 393 394 /** 395 * Compares two linear congruential random number generator 396 * objects of the same type for equality. 397 * 398 * @param __lhs A linear congruential random number generator object. 399 * @param __rhs Another linear congruential random number generator obj. 400 * 401 * @returns true if the two objects are equal, false otherwise. 402 */ 403 friend bool 404 operator==(const linear_congruential& __lhs, 405 const linear_congruential& __rhs) 406 { return __lhs._M_x == __rhs._M_x; } 407 408 /** 409 * Compares two linear congruential random number generator 410 * objects of the same type for inequality. 411 * 412 * @param __lhs A linear congruential random number generator object. 413 * @param __rhs Another linear congruential random number generator obj. 414 * 415 * @returns true if the two objects are not equal, false otherwise. 416 */ 417 friend bool 418 operator!=(const linear_congruential& __lhs, 419 const linear_congruential& __rhs) 420 { return !(__lhs == __rhs); } 421 422 /** 423 * Writes the textual representation of the state x(i) of x to @p __os. 424 * 425 * @param __os The output stream. 426 * @param __lcr A % linear_congruential random number generator. 427 * @returns __os. 428 */ 429 template<class _UIntType1, _UIntType1 __a1, _UIntType1 __c1, 430 _UIntType1 __m1, 431 typename _CharT, typename _Traits> 432 friend std::basic_ostream<_CharT, _Traits>& 433 operator<<(std::basic_ostream<_CharT, _Traits>& __os, 434 const linear_congruential<_UIntType1, __a1, __c1, 435 __m1>& __lcr); 436 437 /** 438 * Sets the state of the engine by reading its textual 439 * representation from @p __is. 440 * 441 * The textual representation must have been previously written using an 442 * output stream whose imbued locale and whose type's template 443 * specialization arguments _CharT and _Traits were the same as those of 444 * @p __is. 445 * 446 * @param __is The input stream. 447 * @param __lcr A % linear_congruential random number generator. 448 * @returns __is. 449 */ 450 template<class _UIntType1, _UIntType1 __a1, _UIntType1 __c1, 451 _UIntType1 __m1, 452 typename _CharT, typename _Traits> 453 friend std::basic_istream<_CharT, _Traits>& 454 operator>>(std::basic_istream<_CharT, _Traits>& __is, 455 linear_congruential<_UIntType1, __a1, __c1, __m1>& __lcr); 456 457 private: 458 template<class _Gen> 459 void 460 seed(_Gen& __g, true_type) 461 { return seed(static_cast<unsigned long>(__g)); } 462 463 template<class _Gen> 464 void 465 seed(_Gen& __g, false_type); 466 467 _UIntType _M_x; 468 }; 469 470 /** 471 * The classic Minimum Standard rand0 of Lewis, Goodman, and Miller. 472 */ 473 typedef linear_congruential<unsigned long, 16807, 0, 2147483647> minstd_rand0; 474 475 /** 476 * An alternative LCR (Lehmer Generator function) . 477 */ 478 typedef linear_congruential<unsigned long, 48271, 0, 2147483647> minstd_rand; 479 480 481 /** 482 * A generalized feedback shift register discrete random number generator. 483 * 484 * This algorithm avoids multiplication and division and is designed to be 485 * friendly to a pipelined architecture. If the parameters are chosen 486 * correctly, this generator will produce numbers with a very long period and 487 * fairly good apparent entropy, although still not cryptographically strong. 488 * 489 * The best way to use this generator is with the predefined mt19937 class. 490 * 491 * This algorithm was originally invented by Makoto Matsumoto and 492 * Takuji Nishimura. 493 * 494 * @var word_size The number of bits in each element of the state vector. 495 * @var state_size The degree of recursion. 496 * @var shift_size The period parameter. 497 * @var mask_bits The separation point bit index. 498 * @var parameter_a The last row of the twist matrix. 499 * @var output_u The first right-shift tempering matrix parameter. 500 * @var output_s The first left-shift tempering matrix parameter. 501 * @var output_b The first left-shift tempering matrix mask. 502 * @var output_t The second left-shift tempering matrix parameter. 503 * @var output_c The second left-shift tempering matrix mask. 504 * @var output_l The second right-shift tempering matrix parameter. 505 */ 506 template<class _UIntType, int __w, int __n, int __m, int __r, 507 _UIntType __a, int __u, int __s, _UIntType __b, int __t, 508 _UIntType __c, int __l> 509 class mersenne_twister 510 { 511 __glibcxx_class_requires(_UIntType, _UnsignedIntegerConcept) 512 513 public: 514 // types 515 typedef _UIntType result_type; 516 517 // parameter values 518 static const int word_size = __w; 519 static const int state_size = __n; 520 static const int shift_size = __m; 521 static const int mask_bits = __r; 522 static const _UIntType parameter_a = __a; 523 static const int output_u = __u; 524 static const int output_s = __s; 525 static const _UIntType output_b = __b; 526 static const int output_t = __t; 527 static const _UIntType output_c = __c; 528 static const int output_l = __l; 529 530 // constructors and member function 531 mersenne_twister() 532 { seed(); } 533 534 explicit 535 mersenne_twister(unsigned long __value) 536 { seed(__value); } 537 538 template<class _Gen> 539 mersenne_twister(_Gen& __g) 540 { seed(__g); } 541 542 void 543 seed() 544 { seed(5489UL); } 545 546 void 547 seed(unsigned long __value); 548 549 template<class _Gen> 550 void 551 seed(_Gen& __g) 552 { seed(__g, typename is_fundamental<_Gen>::type()); } 553 554 result_type 555 min() const 556 { return 0; } 557 558 result_type 559 max() const 560 { return __detail::_Shift<_UIntType, __w>::__value - 1; } 561 562 result_type 563 operator()(); 564 565 /** 566 * Compares two % mersenne_twister random number generator objects of 567 * the same type for equality. 568 * 569 * @param __lhs A % mersenne_twister random number generator object. 570 * @param __rhs Another % mersenne_twister random number generator 571 * object. 572 * 573 * @returns true if the two objects are equal, false otherwise. 574 */ 575 friend bool 576 operator==(const mersenne_twister& __lhs, 577 const mersenne_twister& __rhs) 578 { return std::equal(__lhs._M_x, __lhs._M_x + state_size, __rhs._M_x); } 579 580 /** 581 * Compares two % mersenne_twister random number generator objects of 582 * the same type for inequality. 583 * 584 * @param __lhs A % mersenne_twister random number generator object. 585 * @param __rhs Another % mersenne_twister random number generator 586 * object. 587 * 588 * @returns true if the two objects are not equal, false otherwise. 589 */ 590 friend bool 591 operator!=(const mersenne_twister& __lhs, 592 const mersenne_twister& __rhs) 593 { return !(__lhs == __rhs); } 594 595 /** 596 * Inserts the current state of a % mersenne_twister random number 597 * generator engine @p __x into the output stream @p __os. 598 * 599 * @param __os An output stream. 600 * @param __x A % mersenne_twister random number generator engine. 601 * 602 * @returns The output stream with the state of @p __x inserted or in 603 * an error state. 604 */ 605 template<class _UIntType1, int __w1, int __n1, int __m1, int __r1, 606 _UIntType1 __a1, int __u1, int __s1, _UIntType1 __b1, int __t1, 607 _UIntType1 __c1, int __l1, 608 typename _CharT, typename _Traits> 609 friend std::basic_ostream<_CharT, _Traits>& 610 operator<<(std::basic_ostream<_CharT, _Traits>& __os, 611 const mersenne_twister<_UIntType1, __w1, __n1, __m1, __r1, 612 __a1, __u1, __s1, __b1, __t1, __c1, __l1>& __x); 613 614 /** 615 * Extracts the current state of a % mersenne_twister random number 616 * generator engine @p __x from the input stream @p __is. 617 * 618 * @param __is An input stream. 619 * @param __x A % mersenne_twister random number generator engine. 620 * 621 * @returns The input stream with the state of @p __x extracted or in 622 * an error state. 623 */ 624 template<class _UIntType1, int __w1, int __n1, int __m1, int __r1, 625 _UIntType1 __a1, int __u1, int __s1, _UIntType1 __b1, int __t1, 626 _UIntType1 __c1, int __l1, 627 typename _CharT, typename _Traits> 628 friend std::basic_istream<_CharT, _Traits>& 629 operator>>(std::basic_istream<_CharT, _Traits>& __is, 630 mersenne_twister<_UIntType1, __w1, __n1, __m1, __r1, 631 __a1, __u1, __s1, __b1, __t1, __c1, __l1>& __x); 632 633 private: 634 template<class _Gen> 635 void 636 seed(_Gen& __g, true_type) 637 { return seed(static_cast<unsigned long>(__g)); } 638 639 template<class _Gen> 640 void 641 seed(_Gen& __g, false_type); 642 643 _UIntType _M_x[state_size]; 644 int _M_p; 645 }; 646 647 /** 648 * The classic Mersenne Twister. 649 * 650 * Reference: 651 * M. Matsumoto and T. Nishimura, Mersenne Twister: A 623-Dimensionally 652 * Equidistributed Uniform Pseudo-Random Number Generator, ACM Transactions 653 * on Modeling and Computer Simulation, Vol. 8, No. 1, January 1998, pp 3-30. 654 */ 655 typedef mersenne_twister< 656 unsigned long, 32, 624, 397, 31, 657 0x9908b0dful, 11, 7, 658 0x9d2c5680ul, 15, 659 0xefc60000ul, 18 660 > mt19937; 661 662 663 /** 664 * @brief The Marsaglia-Zaman generator. 665 * 666 * This is a model of a Generalized Fibonacci discrete random number 667 * generator, sometimes referred to as the SWC generator. 668 * 669 * A discrete random number generator that produces pseudorandom 670 * numbers using @f$x_{i}\leftarrow(x_{i - s} - x_{i - r} - 671 * carry_{i-1}) \bmod m @f$. 672 * 673 * The size of the state is @f$ r @f$ 674 * and the maximum period of the generator is @f$ m^r - m^s -1 @f$. 675 * 676 * N1688[4.13] says <em>the template parameter _IntType shall denote 677 * an integral type large enough to store values up to m</em>. 678 * 679 * @var _M_x The state of the generator. This is a ring buffer. 680 * @var _M_carry The carry. 681 * @var _M_p Current index of x(i - r). 682 */ 683 template<typename _IntType, _IntType __m, int __s, int __r> 684 class subtract_with_carry 685 { 686 __glibcxx_class_requires(_IntType, _IntegerConcept) 687 688 public: 689 /** The type of the generated random value. */ 690 typedef _IntType result_type; 691 692 // parameter values 693 static const _IntType modulus = __m; 694 static const int long_lag = __r; 695 static const int short_lag = __s; 696 697 /** 698 * Constructs a default-initialized % subtract_with_carry random number 699 * generator. 700 */ 701 subtract_with_carry() 702 { this->seed(); } 703 704 /** 705 * Constructs an explicitly seeded % subtract_with_carry random number 706 * generator. 707 */ 708 explicit 709 subtract_with_carry(unsigned long __value) 710 { this->seed(__value); } 711 712 /** 713 * Constructs a %subtract_with_carry random number generator engine 714 * seeded from the generator function @p __g. 715 * 716 * @param __g The seed generator function. 717 */ 718 template<class _Gen> 719 subtract_with_carry(_Gen& __g) 720 { this->seed(__g); } 721 722 /** 723 * Seeds the initial state @f$ x_0 @f$ of the random number generator. 724 * 725 * N1688[4.19] modifies this as follows. If @p __value == 0, 726 * sets value to 19780503. In any case, with a linear 727 * congruential generator lcg(i) having parameters @f$ m_{lcg} = 728 * 2147483563, a_{lcg} = 40014, c_{lcg} = 0, and lcg(0) = value 729 * @f$, sets @f$ x_{-r} \dots x_{-1} @f$ to @f$ lcg(1) \bmod m 730 * \dots lcg(r) \bmod m @f$ respectively. If @f$ x_{-1} = 0 @f$ 731 * set carry to 1, otherwise sets carry to 0. 732 */ 733 void 734 seed(unsigned long __value = 19780503); 735 736 /** 737 * Seeds the initial state @f$ x_0 @f$ of the % subtract_with_carry 738 * random number generator. 739 */ 740 template<class _Gen> 741 void 742 seed(_Gen& __g) 743 { seed(__g, typename is_fundamental<_Gen>::type()); } 744 745 /** 746 * Gets the inclusive minimum value of the range of random integers 747 * returned by this generator. 748 */ 749 result_type 750 min() const 751 { return 0; } 752 753 /** 754 * Gets the inclusive maximum value of the range of random integers 755 * returned by this generator. 756 */ 757 result_type 758 max() const 759 { return this->modulus - 1; } 760 761 /** 762 * Gets the next random number in the sequence. 763 */ 764 result_type 765 operator()(); 766 767 /** 768 * Compares two % subtract_with_carry random number generator objects of 769 * the same type for equality. 770 * 771 * @param __lhs A % subtract_with_carry random number generator object. 772 * @param __rhs Another % subtract_with_carry random number generator 773 * object. 774 * 775 * @returns true if the two objects are equal, false otherwise. 776 */ 777 friend bool 778 operator==(const subtract_with_carry& __lhs, 779 const subtract_with_carry& __rhs) 780 { return std::equal(__lhs._M_x, __lhs._M_x + long_lag, __rhs._M_x); } 781 782 /** 783 * Compares two % subtract_with_carry random number generator objects of 784 * the same type for inequality. 785 * 786 * @param __lhs A % subtract_with_carry random number generator object. 787 * @param __rhs Another % subtract_with_carry random number generator 788 * object. 789 * 790 * @returns true if the two objects are not equal, false otherwise. 791 */ 792 friend bool 793 operator!=(const subtract_with_carry& __lhs, 794 const subtract_with_carry& __rhs) 795 { return !(__lhs == __rhs); } 796 797 /** 798 * Inserts the current state of a % subtract_with_carry random number 799 * generator engine @p __x into the output stream @p __os. 800 * 801 * @param __os An output stream. 802 * @param __x A % subtract_with_carry random number generator engine. 803 * 804 * @returns The output stream with the state of @p __x inserted or in 805 * an error state. 806 */ 807 template<typename _IntType1, _IntType1 __m1, int __s1, int __r1, 808 typename _CharT, typename _Traits> 809 friend std::basic_ostream<_CharT, _Traits>& 810 operator<<(std::basic_ostream<_CharT, _Traits>& __os, 811 const subtract_with_carry<_IntType1, __m1, __s1, 812 __r1>& __x); 813 814 /** 815 * Extracts the current state of a % subtract_with_carry random number 816 * generator engine @p __x from the input stream @p __is. 817 * 818 * @param __is An input stream. 819 * @param __x A % subtract_with_carry random number generator engine. 820 * 821 * @returns The input stream with the state of @p __x extracted or in 822 * an error state. 823 */ 824 template<typename _IntType1, _IntType1 __m1, int __s1, int __r1, 825 typename _CharT, typename _Traits> 826 friend std::basic_istream<_CharT, _Traits>& 827 operator>>(std::basic_istream<_CharT, _Traits>& __is, 828 subtract_with_carry<_IntType1, __m1, __s1, __r1>& __x); 829 830 private: 831 template<class _Gen> 832 void 833 seed(_Gen& __g, true_type) 834 { return seed(static_cast<unsigned long>(__g)); } 835 836 template<class _Gen> 837 void 838 seed(_Gen& __g, false_type); 839 840 typedef typename __gnu_cxx::__add_unsigned<_IntType>::__type _UIntType; 841 842 _UIntType _M_x[long_lag]; 843 _UIntType _M_carry; 844 int _M_p; 845 }; 846 847 848 /** 849 * @brief The Marsaglia-Zaman generator (floats version). 850 * 851 * @var _M_x The state of the generator. This is a ring buffer. 852 * @var _M_carry The carry. 853 * @var _M_p Current index of x(i - r). 854 * @var _M_npows Precomputed negative powers of 2. 855 */ 856 template<typename _RealType, int __w, int __s, int __r> 857 class subtract_with_carry_01 858 { 859 public: 860 /** The type of the generated random value. */ 861 typedef _RealType result_type; 862 863 // parameter values 864 static const int word_size = __w; 865 static const int long_lag = __r; 866 static const int short_lag = __s; 867 868 /** 869 * Constructs a default-initialized % subtract_with_carry_01 random 870 * number generator. 871 */ 872 subtract_with_carry_01() 873 { 874 this->seed(); 875 _M_initialize_npows(); 876 } 877 878 /** 879 * Constructs an explicitly seeded % subtract_with_carry_01 random number 880 * generator. 881 */ 882 explicit 883 subtract_with_carry_01(unsigned long __value) 884 { 885 this->seed(__value); 886 _M_initialize_npows(); 887 } 888 889 /** 890 * Constructs a % subtract_with_carry_01 random number generator engine 891 * seeded from the generator function @p __g. 892 * 893 * @param __g The seed generator function. 894 */ 895 template<class _Gen> 896 subtract_with_carry_01(_Gen& __g) 897 { 898 this->seed(__g); 899 _M_initialize_npows(); 900 } 901 902 /** 903 * Seeds the initial state @f$ x_0 @f$ of the random number generator. 904 */ 905 void 906 seed(unsigned long __value = 19780503); 907 908 /** 909 * Seeds the initial state @f$ x_0 @f$ of the % subtract_with_carry_01 910 * random number generator. 911 */ 912 template<class _Gen> 913 void 914 seed(_Gen& __g) 915 { seed(__g, typename is_fundamental<_Gen>::type()); } 916 917 /** 918 * Gets the minimum value of the range of random floats 919 * returned by this generator. 920 */ 921 result_type 922 min() const 923 { return 0.0; } 924 925 /** 926 * Gets the maximum value of the range of random floats 927 * returned by this generator. 928 */ 929 result_type 930 max() const 931 { return 1.0; } 932 933 /** 934 * Gets the next random number in the sequence. 935 */ 936 result_type 937 operator()(); 938 939 /** 940 * Compares two % subtract_with_carry_01 random number generator objects 941 * of the same type for equality. 942 * 943 * @param __lhs A % subtract_with_carry_01 random number 944 * generator object. 945 * @param __rhs Another % subtract_with_carry_01 random number generator 946 * object. 947 * 948 * @returns true if the two objects are equal, false otherwise. 949 */ 950 friend bool 951 operator==(const subtract_with_carry_01& __lhs, 952 const subtract_with_carry_01& __rhs) 953 { 954 for (int __i = 0; __i < long_lag; ++__i) 955 if (!std::equal(__lhs._M_x[__i], __lhs._M_x[__i] + __n, 956 __rhs._M_x[__i])) 957 return false; 958 return true; 959 } 960 961 /** 962 * Compares two % subtract_with_carry_01 random number generator objects 963 * of the same type for inequality. 964 * 965 * @param __lhs A % subtract_with_carry_01 random number 966 * generator object. 967 * 968 * @param __rhs Another % subtract_with_carry_01 random number generator 969 * object. 970 * 971 * @returns true if the two objects are not equal, false otherwise. 972 */ 973 friend bool 974 operator!=(const subtract_with_carry_01& __lhs, 975 const subtract_with_carry_01& __rhs) 976 { return !(__lhs == __rhs); } 977 978 /** 979 * Inserts the current state of a % subtract_with_carry_01 random number 980 * generator engine @p __x into the output stream @p __os. 981 * 982 * @param __os An output stream. 983 * @param __x A % subtract_with_carry_01 random number generator engine. 984 * 985 * @returns The output stream with the state of @p __x inserted or in 986 * an error state. 987 */ 988 template<typename _RealType1, int __w1, int __s1, int __r1, 989 typename _CharT, typename _Traits> 990 friend std::basic_ostream<_CharT, _Traits>& 991 operator<<(std::basic_ostream<_CharT, _Traits>& __os, 992 const subtract_with_carry_01<_RealType1, __w1, __s1, 993 __r1>& __x); 994 995 /** 996 * Extracts the current state of a % subtract_with_carry_01 random number 997 * generator engine @p __x from the input stream @p __is. 998 * 999 * @param __is An input stream. 1000 * @param __x A % subtract_with_carry_01 random number generator engine. 1001 * 1002 * @returns The input stream with the state of @p __x extracted or in 1003 * an error state. 1004 */ 1005 template<typename _RealType1, int __w1, int __s1, int __r1, 1006 typename _CharT, typename _Traits> 1007 friend std::basic_istream<_CharT, _Traits>& 1008 operator>>(std::basic_istream<_CharT, _Traits>& __is, 1009 subtract_with_carry_01<_RealType1, __w1, __s1, __r1>& __x); 1010 1011 private: 1012 template<class _Gen> 1013 void 1014 seed(_Gen& __g, true_type) 1015 { return seed(static_cast<unsigned long>(__g)); } 1016 1017 template<class _Gen> 1018 void 1019 seed(_Gen& __g, false_type); 1020 1021 void 1022 _M_initialize_npows(); 1023 1024 static const int __n = (__w + 31) / 32; 1025 1026 typedef __detail::_UInt32Type _UInt32Type; 1027 _UInt32Type _M_x[long_lag][__n]; 1028 _RealType _M_npows[__n]; 1029 _UInt32Type _M_carry; 1030 int _M_p; 1031 }; 1032 1033 typedef subtract_with_carry_01<float, 24, 10, 24> ranlux_base_01; 1034 1035 // _GLIBCXX_RESOLVE_LIB_DEFECTS 1036 // 508. Bad parameters for ranlux64_base_01. 1037 typedef subtract_with_carry_01<double, 48, 5, 12> ranlux64_base_01; 1038 1039 1040 /** 1041 * Produces random numbers from some base engine by discarding blocks of 1042 * data. 1043 * 1044 * 0 <= @p __r <= @p __p 1045 */ 1046 template<class _UniformRandomNumberGenerator, int __p, int __r> 1047 class discard_block 1048 { 1049 // __glibcxx_class_requires(typename base_type::result_type, 1050 // ArithmeticTypeConcept) 1051 1052 public: 1053 /** The type of the underlying generator engine. */ 1054 typedef _UniformRandomNumberGenerator base_type; 1055 /** The type of the generated random value. */ 1056 typedef typename base_type::result_type result_type; 1057 1058 // parameter values 1059 static const int block_size = __p; 1060 static const int used_block = __r; 1061 1062 /** 1063 * Constructs a default %discard_block engine. 1064 * 1065 * The underlying engine is default constructed as well. 1066 */ 1067 discard_block() 1068 : _M_n(0) { } 1069 1070 /** 1071 * Copy constructs a %discard_block engine. 1072 * 1073 * Copies an existing base class random number generator. 1074 * @param rng An existing (base class) engine object. 1075 */ 1076 explicit 1077 discard_block(const base_type& __rng) 1078 : _M_b(__rng), _M_n(0) { } 1079 1080 /** 1081 * Seed constructs a %discard_block engine. 1082 * 1083 * Constructs the underlying generator engine seeded with @p __s. 1084 * @param __s A seed value for the base class engine. 1085 */ 1086 explicit 1087 discard_block(unsigned long __s) 1088 : _M_b(__s), _M_n(0) { } 1089 1090 /** 1091 * Generator construct a %discard_block engine. 1092 * 1093 * @param __g A seed generator function. 1094 */ 1095 template<class _Gen> 1096 discard_block(_Gen& __g) 1097 : _M_b(__g), _M_n(0) { } 1098 1099 /** 1100 * Reseeds the %discard_block object with the default seed for the 1101 * underlying base class generator engine. 1102 */ 1103 void seed() 1104 { 1105 _M_b.seed(); 1106 _M_n = 0; 1107 } 1108 1109 /** 1110 * Reseeds the %discard_block object with the given seed generator 1111 * function. 1112 * @param __g A seed generator function. 1113 */ 1114 template<class _Gen> 1115 void seed(_Gen& __g) 1116 { 1117 _M_b.seed(__g); 1118 _M_n = 0; 1119 } 1120 1121 /** 1122 * Gets a const reference to the underlying generator engine object. 1123 */ 1124 const base_type& 1125 base() const 1126 { return _M_b; } 1127 1128 /** 1129 * Gets the minimum value in the generated random number range. 1130 */ 1131 result_type 1132 min() const 1133 { return _M_b.min(); } 1134 1135 /** 1136 * Gets the maximum value in the generated random number range. 1137 */ 1138 result_type 1139 max() const 1140 { return _M_b.max(); } 1141 1142 /** 1143 * Gets the next value in the generated random number sequence. 1144 */ 1145 result_type 1146 operator()(); 1147 1148 /** 1149 * Compares two %discard_block random number generator objects of 1150 * the same type for equality. 1151 * 1152 * @param __lhs A %discard_block random number generator object. 1153 * @param __rhs Another %discard_block random number generator 1154 * object. 1155 * 1156 * @returns true if the two objects are equal, false otherwise. 1157 */ 1158 friend bool 1159 operator==(const discard_block& __lhs, const discard_block& __rhs) 1160 { return (__lhs._M_b == __rhs._M_b) && (__lhs._M_n == __rhs._M_n); } 1161 1162 /** 1163 * Compares two %discard_block random number generator objects of 1164 * the same type for inequality. 1165 * 1166 * @param __lhs A %discard_block random number generator object. 1167 * @param __rhs Another %discard_block random number generator 1168 * object. 1169 * 1170 * @returns true if the two objects are not equal, false otherwise. 1171 */ 1172 friend bool 1173 operator!=(const discard_block& __lhs, const discard_block& __rhs) 1174 { return !(__lhs == __rhs); } 1175 1176 /** 1177 * Inserts the current state of a %discard_block random number 1178 * generator engine @p __x into the output stream @p __os. 1179 * 1180 * @param __os An output stream. 1181 * @param __x A %discard_block random number generator engine. 1182 * 1183 * @returns The output stream with the state of @p __x inserted or in 1184 * an error state. 1185 */ 1186 template<class _UniformRandomNumberGenerator1, int __p1, int __r1, 1187 typename _CharT, typename _Traits> 1188 friend std::basic_ostream<_CharT, _Traits>& 1189 operator<<(std::basic_ostream<_CharT, _Traits>& __os, 1190 const discard_block<_UniformRandomNumberGenerator1, 1191 __p1, __r1>& __x); 1192 1193 /** 1194 * Extracts the current state of a % subtract_with_carry random number 1195 * generator engine @p __x from the input stream @p __is. 1196 * 1197 * @param __is An input stream. 1198 * @param __x A %discard_block random number generator engine. 1199 * 1200 * @returns The input stream with the state of @p __x extracted or in 1201 * an error state. 1202 */ 1203 template<class _UniformRandomNumberGenerator1, int __p1, int __r1, 1204 typename _CharT, typename _Traits> 1205 friend std::basic_istream<_CharT, _Traits>& 1206 operator>>(std::basic_istream<_CharT, _Traits>& __is, 1207 discard_block<_UniformRandomNumberGenerator1, 1208 __p1, __r1>& __x); 1209 1210 private: 1211 base_type _M_b; 1212 int _M_n; 1213 }; 1214 1215 1216 /** 1217 * James's luxury-level-3 integer adaptation of Luescher's generator. 1218 */ 1219 typedef discard_block< 1220 subtract_with_carry<unsigned long, (1UL << 24), 10, 24>, 1221 223, 1222 24 1223 > ranlux3; 1224 1225 /** 1226 * James's luxury-level-4 integer adaptation of Luescher's generator. 1227 */ 1228 typedef discard_block< 1229 subtract_with_carry<unsigned long, (1UL << 24), 10, 24>, 1230 389, 1231 24 1232 > ranlux4; 1233 1234 typedef discard_block< 1235 subtract_with_carry_01<float, 24, 10, 24>, 1236 223, 1237 24 1238 > ranlux3_01; 1239 1240 typedef discard_block< 1241 subtract_with_carry_01<float, 24, 10, 24>, 1242 389, 1243 24 1244 > ranlux4_01; 1245 1246 1247 /** 1248 * A random number generator adaptor class that combines two random number 1249 * generator engines into a single output sequence. 1250 */ 1251 template<class _UniformRandomNumberGenerator1, int __s1, 1252 class _UniformRandomNumberGenerator2, int __s2> 1253 class xor_combine 1254 { 1255 // __glibcxx_class_requires(typename _UniformRandomNumberGenerator1:: 1256 // result_type, ArithmeticTypeConcept) 1257 // __glibcxx_class_requires(typename _UniformRandomNumberGenerator2:: 1258 // result_type, ArithmeticTypeConcept) 1259 1260 public: 1261 /** The type of the first underlying generator engine. */ 1262 typedef _UniformRandomNumberGenerator1 base1_type; 1263 /** The type of the second underlying generator engine. */ 1264 typedef _UniformRandomNumberGenerator2 base2_type; 1265 1266 private: 1267 typedef typename base1_type::result_type _Result_type1; 1268 typedef typename base2_type::result_type _Result_type2; 1269 1270 public: 1271 /** The type of the generated random value. */ 1272 typedef typename __gnu_cxx::__conditional_type<(sizeof(_Result_type1) 1273 > sizeof(_Result_type2)), 1274 _Result_type1, _Result_type2>::__type result_type; 1275 1276 // parameter values 1277 static const int shift1 = __s1; 1278 static const int shift2 = __s2; 1279 1280 // constructors and member function 1281 xor_combine() 1282 : _M_b1(), _M_b2() 1283 { _M_initialize_max(); } 1284 1285 xor_combine(const base1_type& __rng1, const base2_type& __rng2) 1286 : _M_b1(__rng1), _M_b2(__rng2) 1287 { _M_initialize_max(); } 1288 1289 xor_combine(unsigned long __s) 1290 : _M_b1(__s), _M_b2(__s + 1) 1291 { _M_initialize_max(); } 1292 1293 template<class _Gen> 1294 xor_combine(_Gen& __g) 1295 : _M_b1(__g), _M_b2(__g) 1296 { _M_initialize_max(); } 1297 1298 void 1299 seed() 1300 { 1301 _M_b1.seed(); 1302 _M_b2.seed(); 1303 } 1304 1305 template<class _Gen> 1306 void 1307 seed(_Gen& __g) 1308 { 1309 _M_b1.seed(__g); 1310 _M_b2.seed(__g); 1311 } 1312 1313 const base1_type& 1314 base1() const 1315 { return _M_b1; } 1316 1317 const base2_type& 1318 base2() const 1319 { return _M_b2; } 1320 1321 result_type 1322 min() const 1323 { return 0; } 1324 1325 result_type 1326 max() const 1327 { return _M_max; } 1328 1329 /** 1330 * Gets the next random number in the sequence. 1331 */ 1332 // NB: Not exactly the TR1 formula, per N2079 instead. 1333 result_type 1334 operator()() 1335 { 1336 return ((result_type(_M_b1() - _M_b1.min()) << shift1) 1337 ^ (result_type(_M_b2() - _M_b2.min()) << shift2)); 1338 } 1339 1340 /** 1341 * Compares two %xor_combine random number generator objects of 1342 * the same type for equality. 1343 * 1344 * @param __lhs A %xor_combine random number generator object. 1345 * @param __rhs Another %xor_combine random number generator 1346 * object. 1347 * 1348 * @returns true if the two objects are equal, false otherwise. 1349 */ 1350 friend bool 1351 operator==(const xor_combine& __lhs, const xor_combine& __rhs) 1352 { 1353 return (__lhs.base1() == __rhs.base1()) 1354 && (__lhs.base2() == __rhs.base2()); 1355 } 1356 1357 /** 1358 * Compares two %xor_combine random number generator objects of 1359 * the same type for inequality. 1360 * 1361 * @param __lhs A %xor_combine random number generator object. 1362 * @param __rhs Another %xor_combine random number generator 1363 * object. 1364 * 1365 * @returns true if the two objects are not equal, false otherwise. 1366 */ 1367 friend bool 1368 operator!=(const xor_combine& __lhs, const xor_combine& __rhs) 1369 { return !(__lhs == __rhs); } 1370 1371 /** 1372 * Inserts the current state of a %xor_combine random number 1373 * generator engine @p __x into the output stream @p __os. 1374 * 1375 * @param __os An output stream. 1376 * @param __x A %xor_combine random number generator engine. 1377 * 1378 * @returns The output stream with the state of @p __x inserted or in 1379 * an error state. 1380 */ 1381 template<class _UniformRandomNumberGenerator11, int __s11, 1382 class _UniformRandomNumberGenerator21, int __s21, 1383 typename _CharT, typename _Traits> 1384 friend std::basic_ostream<_CharT, _Traits>& 1385 operator<<(std::basic_ostream<_CharT, _Traits>& __os, 1386 const xor_combine<_UniformRandomNumberGenerator11, __s11, 1387 _UniformRandomNumberGenerator21, __s21>& __x); 1388 1389 /** 1390 * Extracts the current state of a %xor_combine random number 1391 * generator engine @p __x from the input stream @p __is. 1392 * 1393 * @param __is An input stream. 1394 * @param __x A %xor_combine random number generator engine. 1395 * 1396 * @returns The input stream with the state of @p __x extracted or in 1397 * an error state. 1398 */ 1399 template<class _UniformRandomNumberGenerator11, int __s11, 1400 class _UniformRandomNumberGenerator21, int __s21, 1401 typename _CharT, typename _Traits> 1402 friend std::basic_istream<_CharT, _Traits>& 1403 operator>>(std::basic_istream<_CharT, _Traits>& __is, 1404 xor_combine<_UniformRandomNumberGenerator11, __s11, 1405 _UniformRandomNumberGenerator21, __s21>& __x); 1406 1407 private: 1408 void 1409 _M_initialize_max(); 1410 1411 result_type 1412 _M_initialize_max_aux(result_type, result_type, int); 1413 1414 base1_type _M_b1; 1415 base2_type _M_b2; 1416 result_type _M_max; 1417 }; 1418 1419 1420 /** 1421 * A standard interface to a platform-specific non-deterministic 1422 * random number generator (if any are available). 1423 */ 1424 class random_device 1425 { 1426 public: 1427 // types 1428 typedef unsigned int result_type; 1429 1430 // constructors, destructors and member functions 1431 1432 #ifdef _GLIBCXX_USE_RANDOM_TR1 1433 1434 explicit 1435 random_device(const std::string& __token = "/dev/urandom") 1436 { 1437 if ((__token != "/dev/urandom" && __token != "/dev/random") 1438 || !(_M_file = std::fopen(__token.c_str(), "rb"))) 1439 std::__throw_runtime_error(__N("random_device::" 1440 "random_device(const std::string&)")); 1441 } 1442 1443 ~random_device() 1444 { std::fclose(_M_file); } 1445 1446 #else 1447 1448 explicit 1449 random_device(const std::string& __token = "mt19937") 1450 : _M_mt(_M_strtoul(__token)) { } 1451 1452 private: 1453 static unsigned long 1454 _M_strtoul(const std::string& __str) 1455 { 1456 unsigned long __ret = 5489UL; 1457 if (__str != "mt19937") 1458 { 1459 const char* __nptr = __str.c_str(); 1460 char* __endptr; 1461 __ret = std::strtoul(__nptr, &__endptr, 0); 1462 if (*__nptr == '\0' || *__endptr != '\0') 1463 std::__throw_runtime_error(__N("random_device::_M_strtoul" 1464 "(const std::string&)")); 1465 } 1466 return __ret; 1467 } 1468 1469 public: 1470 1471 #endif 1472 1473 result_type 1474 min() const 1475 { return std::numeric_limits<result_type>::min(); } 1476 1477 result_type 1478 max() const 1479 { return std::numeric_limits<result_type>::max(); } 1480 1481 double 1482 entropy() const 1483 { return 0.0; } 1484 1485 result_type 1486 operator()() 1487 { 1488 #ifdef _GLIBCXX_USE_RANDOM_TR1 1489 result_type __ret; 1490 std::fread(reinterpret_cast<void*>(&__ret), sizeof(result_type), 1491 1, _M_file); 1492 return __ret; 1493 #else 1494 return _M_mt(); 1495 #endif 1496 } 1497 1498 private: 1499 random_device(const random_device&); 1500 void operator=(const random_device&); 1501 1502 #ifdef _GLIBCXX_USE_RANDOM_TR1 1503 FILE* _M_file; 1504 #else 1505 mt19937 _M_mt; 1506 #endif 1507 }; 1508 1509 /// @} group tr1_random_generators 1510 1511 /** 1512 * @addtogroup tr1_random_distributions Random Number Distributions 1513 * @ingroup tr1_random 1514 * @{ 1515 */ 1516 1517 /** 1518 * @addtogroup tr1_random_distributions_discrete Discrete Distributions 1519 * @ingroup tr1_random_distributions 1520 * @{ 1521 */ 1522 1523 /** 1524 * @brief Uniform discrete distribution for random numbers. 1525 * A discrete random distribution on the range @f$[min, max]@f$ with equal 1526 * probability throughout the range. 1527 */ 1528 template<typename _IntType = int> 1529 class uniform_int 1530 { 1531 __glibcxx_class_requires(_IntType, _IntegerConcept) 1532 1533 public: 1534 /** The type of the parameters of the distribution. */ 1535 typedef _IntType input_type; 1536 /** The type of the range of the distribution. */ 1537 typedef _IntType result_type; 1538 1539 public: 1540 /** 1541 * Constructs a uniform distribution object. 1542 */ 1543 explicit 1544 uniform_int(_IntType __min = 0, _IntType __max = 9) 1545 : _M_min(__min), _M_max(__max) 1546 { 1547 _GLIBCXX_DEBUG_ASSERT(_M_min <= _M_max); 1548 } 1549 1550 /** 1551 * Gets the inclusive lower bound of the distribution range. 1552 */ 1553 result_type 1554 min() const 1555 { return _M_min; } 1556 1557 /** 1558 * Gets the inclusive upper bound of the distribution range. 1559 */ 1560 result_type 1561 max() const 1562 { return _M_max; } 1563 1564 /** 1565 * Resets the distribution state. 1566 * 1567 * Does nothing for the uniform integer distribution. 1568 */ 1569 void 1570 reset() { } 1571 1572 /** 1573 * Gets a uniformly distributed random number in the range 1574 * @f$(min, max)@f$. 1575 */ 1576 template<typename _UniformRandomNumberGenerator> 1577 result_type 1578 operator()(_UniformRandomNumberGenerator& __urng) 1579 { 1580 typedef typename _UniformRandomNumberGenerator::result_type 1581 _UResult_type; 1582 return _M_call(__urng, _M_min, _M_max, 1583 typename is_integral<_UResult_type>::type()); 1584 } 1585 1586 /** 1587 * Gets a uniform random number in the range @f$[0, n)@f$. 1588 * 1589 * This function is aimed at use with std::random_shuffle. 1590 */ 1591 template<typename _UniformRandomNumberGenerator> 1592 result_type 1593 operator()(_UniformRandomNumberGenerator& __urng, result_type __n) 1594 { 1595 typedef typename _UniformRandomNumberGenerator::result_type 1596 _UResult_type; 1597 return _M_call(__urng, 0, __n - 1, 1598 typename is_integral<_UResult_type>::type()); 1599 } 1600 1601 /** 1602 * Inserts a %uniform_int random number distribution @p __x into the 1603 * output stream @p os. 1604 * 1605 * @param __os An output stream. 1606 * @param __x A %uniform_int random number distribution. 1607 * 1608 * @returns The output stream with the state of @p __x inserted or in 1609 * an error state. 1610 */ 1611 template<typename _IntType1, typename _CharT, typename _Traits> 1612 friend std::basic_ostream<_CharT, _Traits>& 1613 operator<<(std::basic_ostream<_CharT, _Traits>& __os, 1614 const uniform_int<_IntType1>& __x); 1615 1616 /** 1617 * Extracts a %uniform_int random number distribution 1618 * @p __x from the input stream @p __is. 1619 * 1620 * @param __is An input stream. 1621 * @param __x A %uniform_int random number generator engine. 1622 * 1623 * @returns The input stream with @p __x extracted or in an error state. 1624 */ 1625 template<typename _IntType1, typename _CharT, typename _Traits> 1626 friend std::basic_istream<_CharT, _Traits>& 1627 operator>>(std::basic_istream<_CharT, _Traits>& __is, 1628 uniform_int<_IntType1>& __x); 1629 1630 private: 1631 template<typename _UniformRandomNumberGenerator> 1632 result_type 1633 _M_call(_UniformRandomNumberGenerator& __urng, 1634 result_type __min, result_type __max, true_type); 1635 1636 template<typename _UniformRandomNumberGenerator> 1637 result_type 1638 _M_call(_UniformRandomNumberGenerator& __urng, 1639 result_type __min, result_type __max, false_type) 1640 { 1641 return result_type((__urng() - __urng.min()) 1642 / (__urng.max() - __urng.min()) 1643 * (__max - __min + 1)) + __min; 1644 } 1645 1646 _IntType _M_min; 1647 _IntType _M_max; 1648 }; 1649 1650 1651 /** 1652 * @brief A Bernoulli random number distribution. 1653 * 1654 * Generates a sequence of true and false values with likelihood @f$ p @f$ 1655 * that true will come up and @f$ (1 - p) @f$ that false will appear. 1656 */ 1657 class bernoulli_distribution 1658 { 1659 public: 1660 typedef int input_type; 1661 typedef bool result_type; 1662 1663 public: 1664 /** 1665 * Constructs a Bernoulli distribution with likelihood @p p. 1666 * 1667 * @param __p [IN] The likelihood of a true result being returned. Must 1668 * be in the interval @f$ [0, 1] @f$. 1669 */ 1670 explicit 1671 bernoulli_distribution(double __p = 0.5) 1672 : _M_p(__p) 1673 { 1674 _GLIBCXX_DEBUG_ASSERT((_M_p >= 0.0) && (_M_p <= 1.0)); 1675 } 1676 1677 /** 1678 * Gets the @p p parameter of the distribution. 1679 */ 1680 double 1681 p() const 1682 { return _M_p; } 1683 1684 /** 1685 * Resets the distribution state. 1686 * 1687 * Does nothing for a Bernoulli distribution. 1688 */ 1689 void 1690 reset() { } 1691 1692 /** 1693 * Gets the next value in the Bernoullian sequence. 1694 */ 1695 template<class _UniformRandomNumberGenerator> 1696 result_type 1697 operator()(_UniformRandomNumberGenerator& __urng) 1698 { 1699 if ((__urng() - __urng.min()) < _M_p * (__urng.max() - __urng.min())) 1700 return true; 1701 return false; 1702 } 1703 1704 /** 1705 * Inserts a %bernoulli_distribution random number distribution 1706 * @p __x into the output stream @p __os. 1707 * 1708 * @param __os An output stream. 1709 * @param __x A %bernoulli_distribution random number distribution. 1710 * 1711 * @returns The output stream with the state of @p __x inserted or in 1712 * an error state. 1713 */ 1714 template<typename _CharT, typename _Traits> 1715 friend std::basic_ostream<_CharT, _Traits>& 1716 operator<<(std::basic_ostream<_CharT, _Traits>& __os, 1717 const bernoulli_distribution& __x); 1718 1719 /** 1720 * Extracts a %bernoulli_distribution random number distribution 1721 * @p __x from the input stream @p __is. 1722 * 1723 * @param __is An input stream. 1724 * @param __x A %bernoulli_distribution random number generator engine. 1725 * 1726 * @returns The input stream with @p __x extracted or in an error state. 1727 */ 1728 template<typename _CharT, typename _Traits> 1729 friend std::basic_istream<_CharT, _Traits>& 1730 operator>>(std::basic_istream<_CharT, _Traits>& __is, 1731 bernoulli_distribution& __x) 1732 { return __is >> __x._M_p; } 1733 1734 private: 1735 double _M_p; 1736 }; 1737 1738 1739 /** 1740 * @brief A discrete geometric random number distribution. 1741 * 1742 * The formula for the geometric probability mass function is 1743 * @f$ p(i) = (1 - p)p^{i-1} @f$ where @f$ p @f$ is the parameter of the 1744 * distribution. 1745 */ 1746 template<typename _IntType = int, typename _RealType = double> 1747 class geometric_distribution 1748 { 1749 public: 1750 // types 1751 typedef _RealType input_type; 1752 typedef _IntType result_type; 1753 1754 // constructors and member function 1755 explicit 1756 geometric_distribution(const _RealType& __p = _RealType(0.5)) 1757 : _M_p(__p) 1758 { 1759 _GLIBCXX_DEBUG_ASSERT((_M_p > 0.0) && (_M_p < 1.0)); 1760 _M_initialize(); 1761 } 1762 1763 /** 1764 * Gets the distribution parameter @p p. 1765 */ 1766 _RealType 1767 p() const 1768 { return _M_p; } 1769 1770 void 1771 reset() { } 1772 1773 template<class _UniformRandomNumberGenerator> 1774 result_type 1775 operator()(_UniformRandomNumberGenerator& __urng); 1776 1777 /** 1778 * Inserts a %geometric_distribution random number distribution 1779 * @p __x into the output stream @p __os. 1780 * 1781 * @param __os An output stream. 1782 * @param __x A %geometric_distribution random number distribution. 1783 * 1784 * @returns The output stream with the state of @p __x inserted or in 1785 * an error state. 1786 */ 1787 template<typename _IntType1, typename _RealType1, 1788 typename _CharT, typename _Traits> 1789 friend std::basic_ostream<_CharT, _Traits>& 1790 operator<<(std::basic_ostream<_CharT, _Traits>& __os, 1791 const geometric_distribution<_IntType1, _RealType1>& __x); 1792 1793 /** 1794 * Extracts a %geometric_distribution random number distribution 1795 * @p __x from the input stream @p __is. 1796 * 1797 * @param __is An input stream. 1798 * @param __x A %geometric_distribution random number generator engine. 1799 * 1800 * @returns The input stream with @p __x extracted or in an error state. 1801 */ 1802 template<typename _CharT, typename _Traits> 1803 friend std::basic_istream<_CharT, _Traits>& 1804 operator>>(std::basic_istream<_CharT, _Traits>& __is, 1805 geometric_distribution& __x) 1806 { 1807 __is >> __x._M_p; 1808 __x._M_initialize(); 1809 return __is; 1810 } 1811 1812 private: 1813 void 1814 _M_initialize() 1815 { _M_log_p = std::log(_M_p); } 1816 1817 _RealType _M_p; 1818 _RealType _M_log_p; 1819 }; 1820 1821 1822 template<typename _RealType> 1823 class normal_distribution; 1824 1825 /** 1826 * @brief A discrete Poisson random number distribution. 1827 * 1828 * The formula for the Poisson probability mass function is 1829 * @f$ p(i) = \frac{mean^i}{i!} e^{-mean} @f$ where @f$ mean @f$ is the 1830 * parameter of the distribution. 1831 */ 1832 template<typename _IntType = int, typename _RealType = double> 1833 class poisson_distribution 1834 { 1835 public: 1836 // types 1837 typedef _RealType input_type; 1838 typedef _IntType result_type; 1839 1840 // constructors and member function 1841 explicit 1842 poisson_distribution(const _RealType& __mean = _RealType(1)) 1843 : _M_mean(__mean), _M_nd() 1844 { 1845 _GLIBCXX_DEBUG_ASSERT(_M_mean > 0.0); 1846 _M_initialize(); 1847 } 1848 1849 /** 1850 * Gets the distribution parameter @p mean. 1851 */ 1852 _RealType 1853 mean() const 1854 { return _M_mean; } 1855 1856 void 1857 reset() 1858 { _M_nd.reset(); } 1859 1860 template<class _UniformRandomNumberGenerator> 1861 result_type 1862 operator()(_UniformRandomNumberGenerator& __urng); 1863 1864 /** 1865 * Inserts a %poisson_distribution random number distribution 1866 * @p __x into the output stream @p __os. 1867 * 1868 * @param __os An output stream. 1869 * @param __x A %poisson_distribution random number distribution. 1870 * 1871 * @returns The output stream with the state of @p __x inserted or in 1872 * an error state. 1873 */ 1874 template<typename _IntType1, typename _RealType1, 1875 typename _CharT, typename _Traits> 1876 friend std::basic_ostream<_CharT, _Traits>& 1877 operator<<(std::basic_ostream<_CharT, _Traits>& __os, 1878 const poisson_distribution<_IntType1, _RealType1>& __x); 1879 1880 /** 1881 * Extracts a %poisson_distribution random number distribution 1882 * @p __x from the input stream @p __is. 1883 * 1884 * @param __is An input stream. 1885 * @param __x A %poisson_distribution random number generator engine. 1886 * 1887 * @returns The input stream with @p __x extracted or in an error state. 1888 */ 1889 template<typename _IntType1, typename _RealType1, 1890 typename _CharT, typename _Traits> 1891 friend std::basic_istream<_CharT, _Traits>& 1892 operator>>(std::basic_istream<_CharT, _Traits>& __is, 1893 poisson_distribution<_IntType1, _RealType1>& __x); 1894 1895 private: 1896 void 1897 _M_initialize(); 1898 1899 // NB: Unused when _GLIBCXX_USE_C99_MATH_TR1 is undefined. 1900 normal_distribution<_RealType> _M_nd; 1901 1902 _RealType _M_mean; 1903 1904 // Hosts either log(mean) or the threshold of the simple method. 1905 _RealType _M_lm_thr; 1906 #if _GLIBCXX_USE_C99_MATH_TR1 1907 _RealType _M_lfm, _M_sm, _M_d, _M_scx, _M_1cx, _M_c2b, _M_cb; 1908 #endif 1909 }; 1910 1911 1912 /** 1913 * @brief A discrete binomial random number distribution. 1914 * 1915 * The formula for the binomial probability mass function is 1916 * @f$ p(i) = \binom{n}{i} p^i (1 - p)^{t - i} @f$ where @f$ t @f$ 1917 * and @f$ p @f$ are the parameters of the distribution. 1918 */ 1919 template<typename _IntType = int, typename _RealType = double> 1920 class binomial_distribution 1921 { 1922 public: 1923 // types 1924 typedef _RealType input_type; 1925 typedef _IntType result_type; 1926 1927 // constructors and member function 1928 explicit 1929 binomial_distribution(_IntType __t = 1, 1930 const _RealType& __p = _RealType(0.5)) 1931 : _M_t(__t), _M_p(__p), _M_nd() 1932 { 1933 _GLIBCXX_DEBUG_ASSERT((_M_t >= 0) && (_M_p >= 0.0) && (_M_p <= 1.0)); 1934 _M_initialize(); 1935 } 1936 1937 /** 1938 * Gets the distribution @p t parameter. 1939 */ 1940 _IntType 1941 t() const 1942 { return _M_t; } 1943 1944 /** 1945 * Gets the distribution @p p parameter. 1946 */ 1947 _RealType 1948 p() const 1949 { return _M_p; } 1950 1951 void 1952 reset() 1953 { _M_nd.reset(); } 1954 1955 template<class _UniformRandomNumberGenerator> 1956 result_type 1957 operator()(_UniformRandomNumberGenerator& __urng); 1958 1959 /** 1960 * Inserts a %binomial_distribution random number distribution 1961 * @p __x into the output stream @p __os. 1962 * 1963 * @param __os An output stream. 1964 * @param __x A %binomial_distribution random number distribution. 1965 * 1966 * @returns The output stream with the state of @p __x inserted or in 1967 * an error state. 1968 */ 1969 template<typename _IntType1, typename _RealType1, 1970 typename _CharT, typename _Traits> 1971 friend std::basic_ostream<_CharT, _Traits>& 1972 operator<<(std::basic_ostream<_CharT, _Traits>& __os, 1973 const binomial_distribution<_IntType1, _RealType1>& __x); 1974 1975 /** 1976 * Extracts a %binomial_distribution random number distribution 1977 * @p __x from the input stream @p __is. 1978 * 1979 * @param __is An input stream. 1980 * @param __x A %binomial_distribution random number generator engine. 1981 * 1982 * @returns The input stream with @p __x extracted or in an error state. 1983 */ 1984 template<typename _IntType1, typename _RealType1, 1985 typename _CharT, typename _Traits> 1986 friend std::basic_istream<_CharT, _Traits>& 1987 operator>>(std::basic_istream<_CharT, _Traits>& __is, 1988 binomial_distribution<_IntType1, _RealType1>& __x); 1989 1990 private: 1991 void 1992 _M_initialize(); 1993 1994 template<class _UniformRandomNumberGenerator> 1995 result_type 1996 _M_waiting(_UniformRandomNumberGenerator& __urng, _IntType __t); 1997 1998 // NB: Unused when _GLIBCXX_USE_C99_MATH_TR1 is undefined. 1999 normal_distribution<_RealType> _M_nd; 2000 2001 _RealType _M_q; 2002 #if _GLIBCXX_USE_C99_MATH_TR1 2003 _RealType _M_d1, _M_d2, _M_s1, _M_s2, _M_c, 2004 _M_a1, _M_a123, _M_s, _M_lf, _M_lp1p; 2005 #endif 2006 _RealType _M_p; 2007 _IntType _M_t; 2008 2009 bool _M_easy; 2010 }; 2011 2012 /// @} group tr1_random_distributions_discrete 2013 2014 /** 2015 * @addtogroup tr1_random_distributions_continuous Continuous Distributions 2016 * @ingroup tr1_random_distributions 2017 * @{ 2018 */ 2019 2020 /** 2021 * @brief Uniform continuous distribution for random numbers. 2022 * 2023 * A continuous random distribution on the range [min, max) with equal 2024 * probability throughout the range. The URNG should be real-valued and 2025 * deliver number in the range [0, 1). 2026 */ 2027 template<typename _RealType = double> 2028 class uniform_real 2029 { 2030 public: 2031 // types 2032 typedef _RealType input_type; 2033 typedef _RealType result_type; 2034 2035 public: 2036 /** 2037 * Constructs a uniform_real object. 2038 * 2039 * @param __min [IN] The lower bound of the distribution. 2040 * @param __max [IN] The upper bound of the distribution. 2041 */ 2042 explicit 2043 uniform_real(_RealType __min = _RealType(0), 2044 _RealType __max = _RealType(1)) 2045 : _M_min(__min), _M_max(__max) 2046 { 2047 _GLIBCXX_DEBUG_ASSERT(_M_min <= _M_max); 2048 } 2049 2050 result_type 2051 min() const 2052 { return _M_min; } 2053 2054 result_type 2055 max() const 2056 { return _M_max; } 2057 2058 void 2059 reset() { } 2060 2061 template<class _UniformRandomNumberGenerator> 2062 result_type 2063 operator()(_UniformRandomNumberGenerator& __urng) 2064 { return (__urng() * (_M_max - _M_min)) + _M_min; } 2065 2066 /** 2067 * Inserts a %uniform_real random number distribution @p __x into the 2068 * output stream @p __os. 2069 * 2070 * @param __os An output stream. 2071 * @param __x A %uniform_real random number distribution. 2072 * 2073 * @returns The output stream with the state of @p __x inserted or in 2074 * an error state. 2075 */ 2076 template<typename _RealType1, typename _CharT, typename _Traits> 2077 friend std::basic_ostream<_CharT, _Traits>& 2078 operator<<(std::basic_ostream<_CharT, _Traits>& __os, 2079 const uniform_real<_RealType1>& __x); 2080 2081 /** 2082 * Extracts a %uniform_real random number distribution 2083 * @p __x from the input stream @p __is. 2084 * 2085 * @param __is An input stream. 2086 * @param __x A %uniform_real random number generator engine. 2087 * 2088 * @returns The input stream with @p __x extracted or in an error state. 2089 */ 2090 template<typename _RealType1, typename _CharT, typename _Traits> 2091 friend std::basic_istream<_CharT, _Traits>& 2092 operator>>(std::basic_istream<_CharT, _Traits>& __is, 2093 uniform_real<_RealType1>& __x); 2094 2095 private: 2096 _RealType _M_min; 2097 _RealType _M_max; 2098 }; 2099 2100 2101 /** 2102 * @brief An exponential continuous distribution for random numbers. 2103 * 2104 * The formula for the exponential probability mass function is 2105 * @f$ p(x) = \lambda e^{-\lambda x} @f$. 2106 * 2107 * <table border=1 cellpadding=10 cellspacing=0> 2108 * <caption align=top>Distribution Statistics</caption> 2109 * <tr><td>Mean</td><td>@f$ \frac{1}{\lambda} @f$</td></tr> 2110 * <tr><td>Median</td><td>@f$ \frac{\ln 2}{\lambda} @f$</td></tr> 2111 * <tr><td>Mode</td><td>@f$ zero @f$</td></tr> 2112 * <tr><td>Range</td><td>@f$[0, \infty]@f$</td></tr> 2113 * <tr><td>Standard Deviation</td><td>@f$ \frac{1}{\lambda} @f$</td></tr> 2114 * </table> 2115 */ 2116 template<typename _RealType = double> 2117 class exponential_distribution 2118 { 2119 public: 2120 // types 2121 typedef _RealType input_type; 2122 typedef _RealType result_type; 2123 2124 public: 2125 /** 2126 * Constructs an exponential distribution with inverse scale parameter 2127 * @f$ \lambda @f$. 2128 */ 2129 explicit 2130 exponential_distribution(const result_type& __lambda = result_type(1)) 2131 : _M_lambda(__lambda) 2132 { 2133 _GLIBCXX_DEBUG_ASSERT(_M_lambda > 0); 2134 } 2135 2136 /** 2137 * Gets the inverse scale parameter of the distribution. 2138 */ 2139 _RealType 2140 lambda() const 2141 { return _M_lambda; } 2142 2143 /** 2144 * Resets the distribution. 2145 * 2146 * Has no effect on exponential distributions. 2147 */ 2148 void 2149 reset() { } 2150 2151 template<class _UniformRandomNumberGenerator> 2152 result_type 2153 operator()(_UniformRandomNumberGenerator& __urng) 2154 { return -std::log(__urng()) / _M_lambda; } 2155 2156 /** 2157 * Inserts a %exponential_distribution random number distribution 2158 * @p __x into the output stream @p __os. 2159 * 2160 * @param __os An output stream. 2161 * @param __x A %exponential_distribution random number distribution. 2162 * 2163 * @returns The output stream with the state of @p __x inserted or in 2164 * an error state. 2165 */ 2166 template<typename _RealType1, typename _CharT, typename _Traits> 2167 friend std::basic_ostream<_CharT, _Traits>& 2168 operator<<(std::basic_ostream<_CharT, _Traits>& __os, 2169 const exponential_distribution<_RealType1>& __x); 2170 2171 /** 2172 * Extracts a %exponential_distribution random number distribution 2173 * @p __x from the input stream @p __is. 2174 * 2175 * @param __is An input stream. 2176 * @param __x A %exponential_distribution random number 2177 * generator engine. 2178 * 2179 * @returns The input stream with @p __x extracted or in an error state. 2180 */ 2181 template<typename _CharT, typename _Traits> 2182 friend std::basic_istream<_CharT, _Traits>& 2183 operator>>(std::basic_istream<_CharT, _Traits>& __is, 2184 exponential_distribution& __x) 2185 { return __is >> __x._M_lambda; } 2186 2187 private: 2188 result_type _M_lambda; 2189 }; 2190 2191 2192 /** 2193 * @brief A normal continuous distribution for random numbers. 2194 * 2195 * The formula for the normal probability mass function is 2196 * @f$ p(x) = \frac{1}{\sigma \sqrt{2 \pi}} 2197 * e^{- \frac{{x - mean}^ {2}}{2 \sigma ^ {2}} } @f$. 2198 */ 2199 template<typename _RealType = double> 2200 class normal_distribution 2201 { 2202 public: 2203 // types 2204 typedef _RealType input_type; 2205 typedef _RealType result_type; 2206 2207 public: 2208 /** 2209 * Constructs a normal distribution with parameters @f$ mean @f$ and 2210 * @f$ \sigma @f$. 2211 */ 2212 explicit 2213 normal_distribution(const result_type& __mean = result_type(0), 2214 const result_type& __sigma = result_type(1)) 2215 : _M_mean(__mean), _M_sigma(__sigma), _M_saved_available(false) 2216 { 2217 _GLIBCXX_DEBUG_ASSERT(_M_sigma > 0); 2218 } 2219 2220 /** 2221 * Gets the mean of the distribution. 2222 */ 2223 _RealType 2224 mean() const 2225 { return _M_mean; } 2226 2227 /** 2228 * Gets the @f$ \sigma @f$ of the distribution. 2229 */ 2230 _RealType 2231 sigma() const 2232 { return _M_sigma; } 2233 2234 /** 2235 * Resets the distribution. 2236 */ 2237 void 2238 reset() 2239 { _M_saved_available = false; } 2240 2241 template<class _UniformRandomNumberGenerator> 2242 result_type 2243 operator()(_UniformRandomNumberGenerator& __urng); 2244 2245 /** 2246 * Inserts a %normal_distribution random number distribution 2247 * @p __x into the output stream @p __os. 2248 * 2249 * @param __os An output stream. 2250 * @param __x A %normal_distribution random number distribution. 2251 * 2252 * @returns The output stream with the state of @p __x inserted or in 2253 * an error state. 2254 */ 2255 template<typename _RealType1, typename _CharT, typename _Traits> 2256 friend std::basic_ostream<_CharT, _Traits>& 2257 operator<<(std::basic_ostream<_CharT, _Traits>& __os, 2258 const normal_distribution<_RealType1>& __x); 2259 2260 /** 2261 * Extracts a %normal_distribution random number distribution 2262 * @p __x from the input stream @p __is. 2263 * 2264 * @param __is An input stream. 2265 * @param __x A %normal_distribution random number generator engine. 2266 * 2267 * @returns The input stream with @p __x extracted or in an error state. 2268 */ 2269 template<typename _RealType1, typename _CharT, typename _Traits> 2270 friend std::basic_istream<_CharT, _Traits>& 2271 operator>>(std::basic_istream<_CharT, _Traits>& __is, 2272 normal_distribution<_RealType1>& __x); 2273 2274 private: 2275 result_type _M_mean; 2276 result_type _M_sigma; 2277 result_type _M_saved; 2278 bool _M_saved_available; 2279 }; 2280 2281 2282 /** 2283 * @brief A gamma continuous distribution for random numbers. 2284 * 2285 * The formula for the gamma probability mass function is 2286 * @f$ p(x) = \frac{1}{\Gamma(\alpha)} x^{\alpha - 1} e^{-x} @f$. 2287 */ 2288 template<typename _RealType = double> 2289 class gamma_distribution 2290 { 2291 public: 2292 // types 2293 typedef _RealType input_type; 2294 typedef _RealType result_type; 2295 2296 public: 2297 /** 2298 * Constructs a gamma distribution with parameters @f$ \alpha @f$. 2299 */ 2300 explicit 2301 gamma_distribution(const result_type& __alpha_val = result_type(1)) 2302 : _M_alpha(__alpha_val) 2303 { 2304 _GLIBCXX_DEBUG_ASSERT(_M_alpha > 0); 2305 _M_initialize(); 2306 } 2307 2308 /** 2309 * Gets the @f$ \alpha @f$ of the distribution. 2310 */ 2311 _RealType 2312 alpha() const 2313 { return _M_alpha; } 2314 2315 /** 2316 * Resets the distribution. 2317 */ 2318 void 2319 reset() { } 2320 2321 template<class _UniformRandomNumberGenerator> 2322 result_type 2323 operator()(_UniformRandomNumberGenerator& __urng); 2324 2325 /** 2326 * Inserts a %gamma_distribution random number distribution 2327 * @p __x into the output stream @p __os. 2328 * 2329 * @param __os An output stream. 2330 * @param __x A %gamma_distribution random number distribution. 2331 * 2332 * @returns The output stream with the state of @p __x inserted or in 2333 * an error state. 2334 */ 2335 template<typename _RealType1, typename _CharT, typename _Traits> 2336 friend std::basic_ostream<_CharT, _Traits>& 2337 operator<<(std::basic_ostream<_CharT, _Traits>& __os, 2338 const gamma_distribution<_RealType1>& __x); 2339 2340 /** 2341 * Extracts a %gamma_distribution random number distribution 2342 * @p __x from the input stream @p __is. 2343 * 2344 * @param __is An input stream. 2345 * @param __x A %gamma_distribution random number generator engine. 2346 * 2347 * @returns The input stream with @p __x extracted or in an error state. 2348 */ 2349 template<typename _CharT, typename _Traits> 2350 friend std::basic_istream<_CharT, _Traits>& 2351 operator>>(std::basic_istream<_CharT, _Traits>& __is, 2352 gamma_distribution& __x) 2353 { 2354 __is >> __x._M_alpha; 2355 __x._M_initialize(); 2356 return __is; 2357 } 2358 2359 private: 2360 void 2361 _M_initialize(); 2362 2363 result_type _M_alpha; 2364 2365 // Hosts either lambda of GB or d of modified Vaduva's. 2366 result_type _M_l_d; 2367 }; 2368 2369 /// @} group tr1_random_distributions_continuous 2370 /// @} group tr1_random_distributions 2371 /// @} group tr1_random 2372 } 2373 2374 _GLIBCXX_END_NAMESPACE_VERSION 2375 } 2376 2377 #endif // _GLIBCXX_TR1_RANDOM_H
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