| 1 | // random number generation -*- C++ -*- |
|---|---|
| 2 | |
| 3 | // Copyright (C) 2009-2024 Free Software Foundation, Inc. |
| 4 | // |
| 5 | // This file is part of the GNU ISO C++ Library. This library is free |
| 6 | // software; you can redistribute it and/or modify it under the |
| 7 | // terms of the GNU General Public License as published by the |
| 8 | // Free Software Foundation; either version 3, or (at your option) |
| 9 | // any later version. |
| 10 | |
| 11 | // This library is distributed in the hope that it will be useful, |
| 12 | // but WITHOUT ANY WARRANTY; without even the implied warranty of |
| 13 | // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
| 14 | // GNU General Public License for more details. |
| 15 | |
| 16 | // Under Section 7 of GPL version 3, you are granted additional |
| 17 | // permissions described in the GCC Runtime Library Exception, version |
| 18 | // 3.1, as published by the Free Software Foundation. |
| 19 | |
| 20 | // You should have received a copy of the GNU General Public License and |
| 21 | // a copy of the GCC Runtime Library Exception along with this program; |
| 22 | // see the files COPYING3 and COPYING.RUNTIME respectively. If not, see |
| 23 | // <http://www.gnu.org/licenses/>. |
| 24 | |
| 25 | /** |
| 26 | * @file bits/random.h |
| 27 | * This is an internal header file, included by other library headers. |
| 28 | * Do not attempt to use it directly. @headername{random} |
| 29 | */ |
| 30 | |
| 31 | #ifndef _RANDOM_H |
| 32 | #define _RANDOM_H 1 |
| 33 | |
| 34 | #include <vector> |
| 35 | #include <bits/uniform_int_dist.h> |
| 36 | |
| 37 | namespace std _GLIBCXX_VISIBILITY(default) |
| 38 | { |
| 39 | _GLIBCXX_BEGIN_NAMESPACE_VERSION |
| 40 | |
| 41 | // [26.4] Random number generation |
| 42 | |
| 43 | /** |
| 44 | * @defgroup random Random Number Generation |
| 45 | * @ingroup numerics |
| 46 | * |
| 47 | * A facility for generating random numbers on selected distributions. |
| 48 | * @{ |
| 49 | */ |
| 50 | |
| 51 | // std::uniform_random_bit_generator is defined in <bits/uniform_int_dist.h> |
| 52 | |
| 53 | /** |
| 54 | * @brief A function template for converting the output of a (integral) |
| 55 | * uniform random number generator to a floatng point result in the range |
| 56 | * [0-1). |
| 57 | */ |
| 58 | template<typename _RealType, size_t __bits, |
| 59 | typename _UniformRandomNumberGenerator> |
| 60 | _RealType |
| 61 | generate_canonical(_UniformRandomNumberGenerator& __g); |
| 62 | |
| 63 | /// @cond undocumented |
| 64 | // Implementation-space details. |
| 65 | namespace __detail |
| 66 | { |
| 67 | #pragma GCC diagnostic push |
| 68 | #pragma GCC diagnostic ignored "-Wc++17-extensions" |
| 69 | |
| 70 | template<typename _UIntType, size_t __w, |
| 71 | bool = __w < static_cast<size_t> |
| 72 | (std::numeric_limits<_UIntType>::digits)> |
| 73 | struct _Shift |
| 74 | { static constexpr _UIntType __value = 0; }; |
| 75 | |
| 76 | template<typename _UIntType, size_t __w> |
| 77 | struct _Shift<_UIntType, __w, true> |
| 78 | { static constexpr _UIntType __value = _UIntType(1) << __w; }; |
| 79 | |
| 80 | template<int __s, |
| 81 | int __which = ((__s <= __CHAR_BIT__ * sizeof (int)) |
| 82 | + (__s <= __CHAR_BIT__ * sizeof (long)) |
| 83 | + (__s <= __CHAR_BIT__ * sizeof (long long)) |
| 84 | /* assume long long no bigger than __int128 */ |
| 85 | + (__s <= 128))> |
| 86 | struct _Select_uint_least_t |
| 87 | { |
| 88 | static_assert(__which < 0, /* needs to be dependent */ |
| 89 | "sorry, would be too much trouble for a slow result"); |
| 90 | }; |
| 91 | |
| 92 | template<int __s> |
| 93 | struct _Select_uint_least_t<__s, 4> |
| 94 | { using type = unsigned int; }; |
| 95 | |
| 96 | template<int __s> |
| 97 | struct _Select_uint_least_t<__s, 3> |
| 98 | { using type = unsigned long; }; |
| 99 | |
| 100 | template<int __s> |
| 101 | struct _Select_uint_least_t<__s, 2> |
| 102 | { using type = unsigned long long; }; |
| 103 | |
| 104 | #if __SIZEOF_INT128__ > __SIZEOF_LONG_LONG__ |
| 105 | template<int __s> |
| 106 | struct _Select_uint_least_t<__s, 1> |
| 107 | { __extension__ using type = unsigned __int128; }; |
| 108 | #elif __has_builtin(__builtin_add_overflow) \ |
| 109 | && __has_builtin(__builtin_sub_overflow) \ |
| 110 | && defined __UINT64_TYPE__ |
| 111 | template<int __s> |
| 112 | struct _Select_uint_least_t<__s, 1> |
| 113 | { |
| 114 | // This is NOT a general-purpose 128-bit integer type. |
| 115 | // It only supports (type(a) * x + c) % m as needed by __mod. |
| 116 | struct type |
| 117 | { |
| 118 | explicit |
| 119 | type(uint64_t __a) noexcept : _M_lo(__a), _M_hi(0) { } |
| 120 | |
| 121 | // pre: __l._M_hi == 0 |
| 122 | friend type |
| 123 | operator*(type __l, uint64_t __x) noexcept |
| 124 | { |
| 125 | // Split 64-bit values __l._M_lo and __x into high and low 32-bit |
| 126 | // limbs and multiply those individually. |
| 127 | // l * x = (l0 + l1) * (x0 + x1) = l0x0 + l0x1 + l1x0 + l1x1 |
| 128 | |
| 129 | constexpr uint64_t __mask = 0xffffffff; |
| 130 | uint64_t __ll[2] = { __l._M_lo >> 32, __l._M_lo & __mask }; |
| 131 | uint64_t __xx[2] = { __x >> 32, __x & __mask }; |
| 132 | uint64_t __l0x0 = __ll[0] * __xx[0]; |
| 133 | uint64_t __l0x1 = __ll[0] * __xx[1]; |
| 134 | uint64_t __l1x0 = __ll[1] * __xx[0]; |
| 135 | uint64_t __l1x1 = __ll[1] * __xx[1]; |
| 136 | // These bits are the low half of __l._M_hi |
| 137 | // and the high half of __l._M_lo. |
| 138 | uint64_t __mid |
| 139 | = (__l0x1 & __mask) + (__l1x0 & __mask) + (__l1x1 >> 32); |
| 140 | __l._M_hi = __l0x0 + (__l0x1 >> 32) + (__l1x0 >> 32) + (__mid >> 32); |
| 141 | __l._M_lo = (__mid << 32) + (__l1x1 & __mask); |
| 142 | return __l; |
| 143 | } |
| 144 | |
| 145 | friend type |
| 146 | operator+(type __l, uint64_t __c) noexcept |
| 147 | { |
| 148 | __l._M_hi += __builtin_add_overflow(__l._M_lo, __c, &__l._M_lo); |
| 149 | return __l; |
| 150 | } |
| 151 | |
| 152 | friend type |
| 153 | operator%(type __l, uint64_t __m) noexcept |
| 154 | { |
| 155 | if (__builtin_expect(__l._M_hi == 0, 0)) |
| 156 | { |
| 157 | __l._M_lo %= __m; |
| 158 | return __l; |
| 159 | } |
| 160 | |
| 161 | int __shift = __builtin_clzll(__m) + 64 |
| 162 | - __builtin_clzll(__l._M_hi); |
| 163 | type __x(0); |
| 164 | if (__shift >= 64) |
| 165 | { |
| 166 | __x._M_hi = __m << (__shift - 64); |
| 167 | __x._M_lo = 0; |
| 168 | } |
| 169 | else |
| 170 | { |
| 171 | __x._M_hi = __m >> (64 - __shift); |
| 172 | __x._M_lo = __m << __shift; |
| 173 | } |
| 174 | |
| 175 | while (__l._M_hi != 0 || __l._M_lo >= __m) |
| 176 | { |
| 177 | if (__x <= __l) |
| 178 | { |
| 179 | __l._M_hi -= __x._M_hi; |
| 180 | __l._M_hi -= __builtin_sub_overflow(__l._M_lo, __x._M_lo, |
| 181 | &__l._M_lo); |
| 182 | } |
| 183 | __x._M_lo = (__x._M_lo >> 1) | (__x._M_hi << 63); |
| 184 | __x._M_hi >>= 1; |
| 185 | } |
| 186 | return __l; |
| 187 | } |
| 188 | |
| 189 | // pre: __l._M_hi == 0 |
| 190 | explicit operator uint64_t() const noexcept |
| 191 | { return _M_lo; } |
| 192 | |
| 193 | friend bool operator<(const type& __l, const type& __r) noexcept |
| 194 | { |
| 195 | if (__l._M_hi < __r._M_hi) |
| 196 | return true; |
| 197 | else if (__l._M_hi == __r._M_hi) |
| 198 | return __l._M_lo < __r._M_lo; |
| 199 | else |
| 200 | return false; |
| 201 | } |
| 202 | |
| 203 | friend bool operator<=(const type& __l, const type& __r) noexcept |
| 204 | { return !(__r < __l); } |
| 205 | |
| 206 | uint64_t _M_lo; |
| 207 | uint64_t _M_hi; |
| 208 | }; |
| 209 | }; |
| 210 | #endif |
| 211 | |
| 212 | // Assume a != 0, a < m, c < m, x < m. |
| 213 | template<typename _Tp, _Tp __m, _Tp __a, _Tp __c, |
| 214 | bool __big_enough = (!(__m & (__m - 1)) |
| 215 | || (_Tp(-1) - __c) / __a >= __m - 1), |
| 216 | bool __schrage_ok = __m % __a < __m / __a> |
| 217 | struct _Mod |
| 218 | { |
| 219 | static _Tp |
| 220 | __calc(_Tp __x) |
| 221 | { |
| 222 | using _Tp2 |
| 223 | = typename _Select_uint_least_t<std::__lg(__a) |
| 224 | + std::__lg(__m) + 2>::type; |
| 225 | return static_cast<_Tp>((_Tp2(__a) * __x + __c) % __m); |
| 226 | } |
| 227 | }; |
| 228 | |
| 229 | // Schrage. |
| 230 | template<typename _Tp, _Tp __m, _Tp __a, _Tp __c> |
| 231 | struct _Mod<_Tp, __m, __a, __c, false, true> |
| 232 | { |
| 233 | static _Tp |
| 234 | __calc(_Tp __x); |
| 235 | }; |
| 236 | |
| 237 | // Special cases: |
| 238 | // - for m == 2^n or m == 0, unsigned integer overflow is safe. |
| 239 | // - a * (m - 1) + c fits in _Tp, there is no overflow. |
| 240 | template<typename _Tp, _Tp __m, _Tp __a, _Tp __c, bool __s> |
| 241 | struct _Mod<_Tp, __m, __a, __c, true, __s> |
| 242 | { |
| 243 | static _Tp |
| 244 | __calc(_Tp __x) |
| 245 | { |
| 246 | _Tp __res = __a * __x + __c; |
| 247 | if (__m) |
| 248 | __res %= __m; |
| 249 | return __res; |
| 250 | } |
| 251 | }; |
| 252 | |
| 253 | template<typename _Tp, _Tp __m, _Tp __a = 1, _Tp __c = 0> |
| 254 | inline _Tp |
| 255 | __mod(_Tp __x) |
| 256 | { |
| 257 | if constexpr (__a == 0) |
| 258 | return __c; |
| 259 | else // N.B. _Mod must not be instantiated with a == 0 |
| 260 | return _Mod<_Tp, __m, __a, __c>::__calc(__x); |
| 261 | } |
| 262 | |
| 263 | /* |
| 264 | * An adaptor class for converting the output of any Generator into |
| 265 | * the input for a specific Distribution. |
| 266 | */ |
| 267 | template<typename _Engine, typename _DInputType> |
| 268 | struct _Adaptor |
| 269 | { |
| 270 | static_assert(std::is_floating_point<_DInputType>::value, |
| 271 | "template argument must be a floating point type"); |
| 272 | |
| 273 | public: |
| 274 | _Adaptor(_Engine& __g) |
| 275 | : _M_g(__g) { } |
| 276 | |
| 277 | _DInputType |
| 278 | min() const |
| 279 | { return _DInputType(0); } |
| 280 | |
| 281 | _DInputType |
| 282 | max() const |
| 283 | { return _DInputType(1); } |
| 284 | |
| 285 | /* |
| 286 | * Converts a value generated by the adapted random number generator |
| 287 | * into a value in the input domain for the dependent random number |
| 288 | * distribution. |
| 289 | */ |
| 290 | _DInputType |
| 291 | operator()() |
| 292 | { |
| 293 | return std::generate_canonical<_DInputType, |
| 294 | std::numeric_limits<_DInputType>::digits, |
| 295 | _Engine>(_M_g); |
| 296 | } |
| 297 | |
| 298 | private: |
| 299 | _Engine& _M_g; |
| 300 | }; |
| 301 | |
| 302 | // Detect whether a template argument _Sseq is a valid seed sequence for |
| 303 | // a random number engine _Engine with result type _Res. |
| 304 | // Used to constrain _Engine::_Engine(_Sseq&) and _Engine::seed(_Sseq&) |
| 305 | // as required by [rand.eng.general]. |
| 306 | |
| 307 | template<typename _Sseq> |
| 308 | using __seed_seq_generate_t = decltype( |
| 309 | std::declval<_Sseq&>().generate(std::declval<uint_least32_t*>(), |
| 310 | std::declval<uint_least32_t*>())); |
| 311 | |
| 312 | template<typename _Sseq, typename _Engine, typename _Res, |
| 313 | typename _GenerateCheck = __seed_seq_generate_t<_Sseq>> |
| 314 | using _If_seed_seq_for = _Require< |
| 315 | __not_<is_same<__remove_cvref_t<_Sseq>, _Engine>>, |
| 316 | is_unsigned<typename _Sseq::result_type>, |
| 317 | __not_<is_convertible<_Sseq, _Res>> |
| 318 | >; |
| 319 | |
| 320 | #pragma GCC diagnostic pop |
| 321 | } // namespace __detail |
| 322 | /// @endcond |
| 323 | |
| 324 | /** |
| 325 | * @addtogroup random_generators Random Number Generators |
| 326 | * @ingroup random |
| 327 | * |
| 328 | * These classes define objects which provide random or pseudorandom |
| 329 | * numbers, either from a discrete or a continuous interval. The |
| 330 | * random number generator supplied as a part of this library are |
| 331 | * all uniform random number generators which provide a sequence of |
| 332 | * random number uniformly distributed over their range. |
| 333 | * |
| 334 | * A number generator is a function object with an operator() that |
| 335 | * takes zero arguments and returns a number. |
| 336 | * |
| 337 | * A compliant random number generator must satisfy the following |
| 338 | * requirements. <table border=1 cellpadding=10 cellspacing=0> |
| 339 | * <caption align=top>Random Number Generator Requirements</caption> |
| 340 | * <tr><td>To be documented.</td></tr> </table> |
| 341 | * |
| 342 | * @{ |
| 343 | */ |
| 344 | |
| 345 | /** |
| 346 | * @brief A model of a linear congruential random number generator. |
| 347 | * |
| 348 | * A random number generator that produces pseudorandom numbers via |
| 349 | * linear function: |
| 350 | * @f[ |
| 351 | * x_{i+1}\leftarrow(ax_{i} + c) \bmod m |
| 352 | * @f] |
| 353 | * |
| 354 | * The template parameter @p _UIntType must be an unsigned integral type |
| 355 | * large enough to store values up to (__m-1). If the template parameter |
| 356 | * @p __m is 0, the modulus @p __m used is |
| 357 | * std::numeric_limits<_UIntType>::max() plus 1. Otherwise, the template |
| 358 | * parameters @p __a and @p __c must be less than @p __m. |
| 359 | * |
| 360 | * The size of the state is @f$1@f$. |
| 361 | * |
| 362 | * @headerfile random |
| 363 | * @since C++11 |
| 364 | */ |
| 365 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m> |
| 366 | class linear_congruential_engine |
| 367 | { |
| 368 | static_assert(std::is_unsigned<_UIntType>::value, |
| 369 | "result_type must be an unsigned integral type"); |
| 370 | static_assert(__m == 0u || (__a < __m && __c < __m), |
| 371 | "template argument substituting __m out of bounds"); |
| 372 | |
| 373 | template<typename _Sseq> |
| 374 | using _If_seed_seq |
| 375 | = __detail::_If_seed_seq_for<_Sseq, linear_congruential_engine, |
| 376 | _UIntType>; |
| 377 | |
| 378 | public: |
| 379 | /** The type of the generated random value. */ |
| 380 | typedef _UIntType result_type; |
| 381 | |
| 382 | /** The multiplier. */ |
| 383 | static constexpr result_type multiplier = __a; |
| 384 | /** An increment. */ |
| 385 | static constexpr result_type increment = __c; |
| 386 | /** The modulus. */ |
| 387 | static constexpr result_type modulus = __m; |
| 388 | static constexpr result_type default_seed = 1u; |
| 389 | |
| 390 | /** |
| 391 | * @brief Constructs a %linear_congruential_engine random number |
| 392 | * generator engine with seed 1. |
| 393 | */ |
| 394 | linear_congruential_engine() : linear_congruential_engine(default_seed) |
| 395 | { } |
| 396 | |
| 397 | /** |
| 398 | * @brief Constructs a %linear_congruential_engine random number |
| 399 | * generator engine with seed @p __s. The default seed value |
| 400 | * is 1. |
| 401 | * |
| 402 | * @param __s The initial seed value. |
| 403 | */ |
| 404 | explicit |
| 405 | linear_congruential_engine(result_type __s) |
| 406 | { seed(__s); } |
| 407 | |
| 408 | /** |
| 409 | * @brief Constructs a %linear_congruential_engine random number |
| 410 | * generator engine seeded from the seed sequence @p __q. |
| 411 | * |
| 412 | * @param __q the seed sequence. |
| 413 | */ |
| 414 | template<typename _Sseq, typename = _If_seed_seq<_Sseq>> |
| 415 | explicit |
| 416 | linear_congruential_engine(_Sseq& __q) |
| 417 | { seed(__q); } |
| 418 | |
| 419 | /** |
| 420 | * @brief Reseeds the %linear_congruential_engine random number generator |
| 421 | * engine sequence to the seed @p __s. |
| 422 | * |
| 423 | * @param __s The new seed. |
| 424 | */ |
| 425 | void |
| 426 | seed(result_type __s = default_seed); |
| 427 | |
| 428 | /** |
| 429 | * @brief Reseeds the %linear_congruential_engine random number generator |
| 430 | * engine |
| 431 | * sequence using values from the seed sequence @p __q. |
| 432 | * |
| 433 | * @param __q the seed sequence. |
| 434 | */ |
| 435 | template<typename _Sseq> |
| 436 | _If_seed_seq<_Sseq> |
| 437 | seed(_Sseq& __q); |
| 438 | |
| 439 | /** |
| 440 | * @brief Gets the smallest possible value in the output range. |
| 441 | * |
| 442 | * The minimum depends on the @p __c parameter: if it is zero, the |
| 443 | * minimum generated must be > 0, otherwise 0 is allowed. |
| 444 | */ |
| 445 | static constexpr result_type |
| 446 | min() |
| 447 | { return __c == 0u ? 1u : 0u; } |
| 448 | |
| 449 | /** |
| 450 | * @brief Gets the largest possible value in the output range. |
| 451 | */ |
| 452 | static constexpr result_type |
| 453 | max() |
| 454 | { return __m - 1u; } |
| 455 | |
| 456 | /** |
| 457 | * @brief Discard a sequence of random numbers. |
| 458 | */ |
| 459 | void |
| 460 | discard(unsigned long long __z) |
| 461 | { |
| 462 | for (; __z != 0ULL; --__z) |
| 463 | (*this)(); |
| 464 | } |
| 465 | |
| 466 | /** |
| 467 | * @brief Gets the next random number in the sequence. |
| 468 | */ |
| 469 | result_type |
| 470 | operator()() |
| 471 | { |
| 472 | _M_x = __detail::__mod<_UIntType, __m, __a, __c>(_M_x); |
| 473 | return _M_x; |
| 474 | } |
| 475 | |
| 476 | /** |
| 477 | * @brief Compares two linear congruential random number generator |
| 478 | * objects of the same type for equality. |
| 479 | * |
| 480 | * @param __lhs A linear congruential random number generator object. |
| 481 | * @param __rhs Another linear congruential random number generator |
| 482 | * object. |
| 483 | * |
| 484 | * @returns true if the infinite sequences of generated values |
| 485 | * would be equal, false otherwise. |
| 486 | */ |
| 487 | friend bool |
| 488 | operator==(const linear_congruential_engine& __lhs, |
| 489 | const linear_congruential_engine& __rhs) |
| 490 | { return __lhs._M_x == __rhs._M_x; } |
| 491 | |
| 492 | /** |
| 493 | * @brief Writes the textual representation of the state x(i) of x to |
| 494 | * @p __os. |
| 495 | * |
| 496 | * @param __os The output stream. |
| 497 | * @param __lcr A % linear_congruential_engine random number generator. |
| 498 | * @returns __os. |
| 499 | */ |
| 500 | template<typename _UIntType1, _UIntType1 __a1, _UIntType1 __c1, |
| 501 | _UIntType1 __m1, typename _CharT, typename _Traits> |
| 502 | friend std::basic_ostream<_CharT, _Traits>& |
| 503 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 504 | const std::linear_congruential_engine<_UIntType1, |
| 505 | __a1, __c1, __m1>& __lcr); |
| 506 | |
| 507 | /** |
| 508 | * @brief Sets the state of the engine by reading its textual |
| 509 | * representation from @p __is. |
| 510 | * |
| 511 | * The textual representation must have been previously written using |
| 512 | * an output stream whose imbued locale and whose type's template |
| 513 | * specialization arguments _CharT and _Traits were the same as those |
| 514 | * of @p __is. |
| 515 | * |
| 516 | * @param __is The input stream. |
| 517 | * @param __lcr A % linear_congruential_engine random number generator. |
| 518 | * @returns __is. |
| 519 | */ |
| 520 | template<typename _UIntType1, _UIntType1 __a1, _UIntType1 __c1, |
| 521 | _UIntType1 __m1, typename _CharT, typename _Traits> |
| 522 | friend std::basic_istream<_CharT, _Traits>& |
| 523 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 524 | std::linear_congruential_engine<_UIntType1, __a1, |
| 525 | __c1, __m1>& __lcr); |
| 526 | |
| 527 | private: |
| 528 | _UIntType _M_x; |
| 529 | }; |
| 530 | |
| 531 | #if __cpp_impl_three_way_comparison < 201907L |
| 532 | /** |
| 533 | * @brief Compares two linear congruential random number generator |
| 534 | * objects of the same type for inequality. |
| 535 | * |
| 536 | * @param __lhs A linear congruential random number generator object. |
| 537 | * @param __rhs Another linear congruential random number generator |
| 538 | * object. |
| 539 | * |
| 540 | * @returns true if the infinite sequences of generated values |
| 541 | * would be different, false otherwise. |
| 542 | */ |
| 543 | template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m> |
| 544 | inline bool |
| 545 | operator!=(const std::linear_congruential_engine<_UIntType, __a, |
| 546 | __c, __m>& __lhs, |
| 547 | const std::linear_congruential_engine<_UIntType, __a, |
| 548 | __c, __m>& __rhs) |
| 549 | { return !(__lhs == __rhs); } |
| 550 | #endif |
| 551 | |
| 552 | /** |
| 553 | * A generalized feedback shift register discrete random number generator. |
| 554 | * |
| 555 | * This algorithm avoids multiplication and division and is designed to be |
| 556 | * friendly to a pipelined architecture. If the parameters are chosen |
| 557 | * correctly, this generator will produce numbers with a very long period and |
| 558 | * fairly good apparent entropy, although still not cryptographically strong. |
| 559 | * |
| 560 | * The best way to use this generator is with the predefined mt19937 class. |
| 561 | * |
| 562 | * This algorithm was originally invented by Makoto Matsumoto and |
| 563 | * Takuji Nishimura. |
| 564 | * |
| 565 | * @tparam __w Word size, the number of bits in each element of |
| 566 | * the state vector. |
| 567 | * @tparam __n The degree of recursion. |
| 568 | * @tparam __m The period parameter. |
| 569 | * @tparam __r The separation point bit index. |
| 570 | * @tparam __a The last row of the twist matrix. |
| 571 | * @tparam __u The first right-shift tempering matrix parameter. |
| 572 | * @tparam __d The first right-shift tempering matrix mask. |
| 573 | * @tparam __s The first left-shift tempering matrix parameter. |
| 574 | * @tparam __b The first left-shift tempering matrix mask. |
| 575 | * @tparam __t The second left-shift tempering matrix parameter. |
| 576 | * @tparam __c The second left-shift tempering matrix mask. |
| 577 | * @tparam __l The second right-shift tempering matrix parameter. |
| 578 | * @tparam __f Initialization multiplier. |
| 579 | * |
| 580 | * @headerfile random |
| 581 | * @since C++11 |
| 582 | */ |
| 583 | template<typename _UIntType, size_t __w, |
| 584 | size_t __n, size_t __m, size_t __r, |
| 585 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, |
| 586 | _UIntType __b, size_t __t, |
| 587 | _UIntType __c, size_t __l, _UIntType __f> |
| 588 | class mersenne_twister_engine |
| 589 | { |
| 590 | static_assert(std::is_unsigned<_UIntType>::value, |
| 591 | "result_type must be an unsigned integral type"); |
| 592 | static_assert(1u <= __m && __m <= __n, |
| 593 | "template argument substituting __m out of bounds"); |
| 594 | static_assert(__r <= __w, "template argument substituting " |
| 595 | "__r out of bound"); |
| 596 | static_assert(__u <= __w, "template argument substituting " |
| 597 | "__u out of bound"); |
| 598 | static_assert(__s <= __w, "template argument substituting " |
| 599 | "__s out of bound"); |
| 600 | static_assert(__t <= __w, "template argument substituting " |
| 601 | "__t out of bound"); |
| 602 | static_assert(__l <= __w, "template argument substituting " |
| 603 | "__l out of bound"); |
| 604 | static_assert(__w <= std::numeric_limits<_UIntType>::digits, |
| 605 | "template argument substituting __w out of bound"); |
| 606 | static_assert(__a <= (__detail::_Shift<_UIntType, __w>::__value - 1), |
| 607 | "template argument substituting __a out of bound"); |
| 608 | static_assert(__b <= (__detail::_Shift<_UIntType, __w>::__value - 1), |
| 609 | "template argument substituting __b out of bound"); |
| 610 | static_assert(__c <= (__detail::_Shift<_UIntType, __w>::__value - 1), |
| 611 | "template argument substituting __c out of bound"); |
| 612 | static_assert(__d <= (__detail::_Shift<_UIntType, __w>::__value - 1), |
| 613 | "template argument substituting __d out of bound"); |
| 614 | static_assert(__f <= (__detail::_Shift<_UIntType, __w>::__value - 1), |
| 615 | "template argument substituting __f out of bound"); |
| 616 | |
| 617 | template<typename _Sseq> |
| 618 | using _If_seed_seq |
| 619 | = __detail::_If_seed_seq_for<_Sseq, mersenne_twister_engine, |
| 620 | _UIntType>; |
| 621 | |
| 622 | public: |
| 623 | /** The type of the generated random value. */ |
| 624 | typedef _UIntType result_type; |
| 625 | |
| 626 | // parameter values |
| 627 | static constexpr size_t word_size = __w; |
| 628 | static constexpr size_t state_size = __n; |
| 629 | static constexpr size_t shift_size = __m; |
| 630 | static constexpr size_t mask_bits = __r; |
| 631 | static constexpr result_type xor_mask = __a; |
| 632 | static constexpr size_t tempering_u = __u; |
| 633 | static constexpr result_type tempering_d = __d; |
| 634 | static constexpr size_t tempering_s = __s; |
| 635 | static constexpr result_type tempering_b = __b; |
| 636 | static constexpr size_t tempering_t = __t; |
| 637 | static constexpr result_type tempering_c = __c; |
| 638 | static constexpr size_t tempering_l = __l; |
| 639 | static constexpr result_type initialization_multiplier = __f; |
| 640 | static constexpr result_type default_seed = 5489u; |
| 641 | |
| 642 | // constructors and member functions |
| 643 | |
| 644 | mersenne_twister_engine() : mersenne_twister_engine(default_seed) { } |
| 645 | |
| 646 | explicit |
| 647 | mersenne_twister_engine(result_type __sd) |
| 648 | { seed(__sd); } |
| 649 | |
| 650 | /** |
| 651 | * @brief Constructs a %mersenne_twister_engine random number generator |
| 652 | * engine seeded from the seed sequence @p __q. |
| 653 | * |
| 654 | * @param __q the seed sequence. |
| 655 | */ |
| 656 | template<typename _Sseq, typename = _If_seed_seq<_Sseq>> |
| 657 | explicit |
| 658 | mersenne_twister_engine(_Sseq& __q) |
| 659 | { seed(__q); } |
| 660 | |
| 661 | void |
| 662 | seed(result_type __sd = default_seed); |
| 663 | |
| 664 | template<typename _Sseq> |
| 665 | _If_seed_seq<_Sseq> |
| 666 | seed(_Sseq& __q); |
| 667 | |
| 668 | /** |
| 669 | * @brief Gets the smallest possible value in the output range. |
| 670 | */ |
| 671 | static constexpr result_type |
| 672 | min() |
| 673 | { return 0; } |
| 674 | |
| 675 | /** |
| 676 | * @brief Gets the largest possible value in the output range. |
| 677 | */ |
| 678 | static constexpr result_type |
| 679 | max() |
| 680 | { return __detail::_Shift<_UIntType, __w>::__value - 1; } |
| 681 | |
| 682 | /** |
| 683 | * @brief Discard a sequence of random numbers. |
| 684 | */ |
| 685 | void |
| 686 | discard(unsigned long long __z); |
| 687 | |
| 688 | result_type |
| 689 | operator()(); |
| 690 | |
| 691 | /** |
| 692 | * @brief Compares two % mersenne_twister_engine random number generator |
| 693 | * objects of the same type for equality. |
| 694 | * |
| 695 | * @param __lhs A % mersenne_twister_engine random number generator |
| 696 | * object. |
| 697 | * @param __rhs Another % mersenne_twister_engine random number |
| 698 | * generator object. |
| 699 | * |
| 700 | * @returns true if the infinite sequences of generated values |
| 701 | * would be equal, false otherwise. |
| 702 | */ |
| 703 | friend bool |
| 704 | operator==(const mersenne_twister_engine& __lhs, |
| 705 | const mersenne_twister_engine& __rhs) |
| 706 | { return (std::equal(__lhs._M_x, __lhs._M_x + state_size, __rhs._M_x) |
| 707 | && __lhs._M_p == __rhs._M_p); } |
| 708 | |
| 709 | /** |
| 710 | * @brief Inserts the current state of a % mersenne_twister_engine |
| 711 | * random number generator engine @p __x into the output stream |
| 712 | * @p __os. |
| 713 | * |
| 714 | * @param __os An output stream. |
| 715 | * @param __x A % mersenne_twister_engine random number generator |
| 716 | * engine. |
| 717 | * |
| 718 | * @returns The output stream with the state of @p __x inserted or in |
| 719 | * an error state. |
| 720 | */ |
| 721 | template<typename _UIntType1, |
| 722 | size_t __w1, size_t __n1, |
| 723 | size_t __m1, size_t __r1, |
| 724 | _UIntType1 __a1, size_t __u1, |
| 725 | _UIntType1 __d1, size_t __s1, |
| 726 | _UIntType1 __b1, size_t __t1, |
| 727 | _UIntType1 __c1, size_t __l1, _UIntType1 __f1, |
| 728 | typename _CharT, typename _Traits> |
| 729 | friend std::basic_ostream<_CharT, _Traits>& |
| 730 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 731 | const std::mersenne_twister_engine<_UIntType1, __w1, __n1, |
| 732 | __m1, __r1, __a1, __u1, __d1, __s1, __b1, __t1, __c1, |
| 733 | __l1, __f1>& __x); |
| 734 | |
| 735 | /** |
| 736 | * @brief Extracts the current state of a % mersenne_twister_engine |
| 737 | * random number generator engine @p __x from the input stream |
| 738 | * @p __is. |
| 739 | * |
| 740 | * @param __is An input stream. |
| 741 | * @param __x A % mersenne_twister_engine random number generator |
| 742 | * engine. |
| 743 | * |
| 744 | * @returns The input stream with the state of @p __x extracted or in |
| 745 | * an error state. |
| 746 | */ |
| 747 | template<typename _UIntType1, |
| 748 | size_t __w1, size_t __n1, |
| 749 | size_t __m1, size_t __r1, |
| 750 | _UIntType1 __a1, size_t __u1, |
| 751 | _UIntType1 __d1, size_t __s1, |
| 752 | _UIntType1 __b1, size_t __t1, |
| 753 | _UIntType1 __c1, size_t __l1, _UIntType1 __f1, |
| 754 | typename _CharT, typename _Traits> |
| 755 | friend std::basic_istream<_CharT, _Traits>& |
| 756 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 757 | std::mersenne_twister_engine<_UIntType1, __w1, __n1, __m1, |
| 758 | __r1, __a1, __u1, __d1, __s1, __b1, __t1, __c1, |
| 759 | __l1, __f1>& __x); |
| 760 | |
| 761 | private: |
| 762 | void _M_gen_rand(); |
| 763 | |
| 764 | _UIntType _M_x[state_size]; |
| 765 | size_t _M_p; |
| 766 | }; |
| 767 | |
| 768 | #if __cpp_impl_three_way_comparison < 201907L |
| 769 | /** |
| 770 | * @brief Compares two % mersenne_twister_engine random number generator |
| 771 | * objects of the same type for inequality. |
| 772 | * |
| 773 | * @param __lhs A % mersenne_twister_engine random number generator |
| 774 | * object. |
| 775 | * @param __rhs Another % mersenne_twister_engine random number |
| 776 | * generator object. |
| 777 | * |
| 778 | * @returns true if the infinite sequences of generated values |
| 779 | * would be different, false otherwise. |
| 780 | */ |
| 781 | template<typename _UIntType, size_t __w, |
| 782 | size_t __n, size_t __m, size_t __r, |
| 783 | _UIntType __a, size_t __u, _UIntType __d, size_t __s, |
| 784 | _UIntType __b, size_t __t, |
| 785 | _UIntType __c, size_t __l, _UIntType __f> |
| 786 | inline bool |
| 787 | operator!=(const std::mersenne_twister_engine<_UIntType, __w, __n, __m, |
| 788 | __r, __a, __u, __d, __s, __b, __t, __c, __l, __f>& __lhs, |
| 789 | const std::mersenne_twister_engine<_UIntType, __w, __n, __m, |
| 790 | __r, __a, __u, __d, __s, __b, __t, __c, __l, __f>& __rhs) |
| 791 | { return !(__lhs == __rhs); } |
| 792 | #endif |
| 793 | |
| 794 | /** |
| 795 | * @brief The Marsaglia-Zaman generator. |
| 796 | * |
| 797 | * This is a model of a Generalized Fibonacci discrete random number |
| 798 | * generator, sometimes referred to as the SWC generator. |
| 799 | * |
| 800 | * A discrete random number generator that produces pseudorandom |
| 801 | * numbers using: |
| 802 | * @f[ |
| 803 | * x_{i}\leftarrow(x_{i - s} - x_{i - r} - carry_{i-1}) \bmod m |
| 804 | * @f] |
| 805 | * |
| 806 | * The size of the state is @f$r@f$ |
| 807 | * and the maximum period of the generator is @f$(m^r - m^s - 1)@f$. |
| 808 | * |
| 809 | * @headerfile random |
| 810 | * @since C++11 |
| 811 | */ |
| 812 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> |
| 813 | class subtract_with_carry_engine |
| 814 | { |
| 815 | static_assert(std::is_unsigned<_UIntType>::value, |
| 816 | "result_type must be an unsigned integral type"); |
| 817 | static_assert(0u < __s && __s < __r, |
| 818 | "0 < s < r"); |
| 819 | static_assert(0u < __w && __w <= std::numeric_limits<_UIntType>::digits, |
| 820 | "template argument substituting __w out of bounds"); |
| 821 | |
| 822 | template<typename _Sseq> |
| 823 | using _If_seed_seq |
| 824 | = __detail::_If_seed_seq_for<_Sseq, subtract_with_carry_engine, |
| 825 | _UIntType>; |
| 826 | |
| 827 | public: |
| 828 | /** The type of the generated random value. */ |
| 829 | typedef _UIntType result_type; |
| 830 | |
| 831 | // parameter values |
| 832 | static constexpr size_t word_size = __w; |
| 833 | static constexpr size_t short_lag = __s; |
| 834 | static constexpr size_t long_lag = __r; |
| 835 | static constexpr uint_least32_t default_seed = 19780503u; |
| 836 | |
| 837 | subtract_with_carry_engine() : subtract_with_carry_engine(0u) |
| 838 | { } |
| 839 | |
| 840 | /** |
| 841 | * @brief Constructs an explicitly seeded %subtract_with_carry_engine |
| 842 | * random number generator. |
| 843 | */ |
| 844 | explicit |
| 845 | subtract_with_carry_engine(result_type __sd) |
| 846 | { seed(__sd); } |
| 847 | |
| 848 | /** |
| 849 | * @brief Constructs a %subtract_with_carry_engine random number engine |
| 850 | * seeded from the seed sequence @p __q. |
| 851 | * |
| 852 | * @param __q the seed sequence. |
| 853 | */ |
| 854 | template<typename _Sseq, typename = _If_seed_seq<_Sseq>> |
| 855 | explicit |
| 856 | subtract_with_carry_engine(_Sseq& __q) |
| 857 | { seed(__q); } |
| 858 | |
| 859 | /** |
| 860 | * @brief Seeds the initial state @f$x_0@f$ of the random number |
| 861 | * generator. |
| 862 | * |
| 863 | * N1688[4.19] modifies this as follows. If @p __value == 0, |
| 864 | * sets value to 19780503. In any case, with a linear |
| 865 | * congruential generator lcg(i) having parameters @f$ m_{lcg} = |
| 866 | * 2147483563, a_{lcg} = 40014, c_{lcg} = 0, and lcg(0) = value |
| 867 | * @f$, sets @f$ x_{-r} \dots x_{-1} @f$ to @f$ lcg(1) \bmod m |
| 868 | * \dots lcg(r) \bmod m @f$ respectively. If @f$ x_{-1} = 0 @f$ |
| 869 | * set carry to 1, otherwise sets carry to 0. |
| 870 | */ |
| 871 | void |
| 872 | seed(result_type __sd = 0u); |
| 873 | |
| 874 | /** |
| 875 | * @brief Seeds the initial state @f$x_0@f$ of the |
| 876 | * % subtract_with_carry_engine random number generator. |
| 877 | */ |
| 878 | template<typename _Sseq> |
| 879 | _If_seed_seq<_Sseq> |
| 880 | seed(_Sseq& __q); |
| 881 | |
| 882 | /** |
| 883 | * @brief Gets the inclusive minimum value of the range of random |
| 884 | * integers returned by this generator. |
| 885 | */ |
| 886 | static constexpr result_type |
| 887 | min() |
| 888 | { return 0; } |
| 889 | |
| 890 | /** |
| 891 | * @brief Gets the inclusive maximum value of the range of random |
| 892 | * integers returned by this generator. |
| 893 | */ |
| 894 | static constexpr result_type |
| 895 | max() |
| 896 | { return __detail::_Shift<_UIntType, __w>::__value - 1; } |
| 897 | |
| 898 | /** |
| 899 | * @brief Discard a sequence of random numbers. |
| 900 | */ |
| 901 | void |
| 902 | discard(unsigned long long __z) |
| 903 | { |
| 904 | for (; __z != 0ULL; --__z) |
| 905 | (*this)(); |
| 906 | } |
| 907 | |
| 908 | /** |
| 909 | * @brief Gets the next random number in the sequence. |
| 910 | */ |
| 911 | result_type |
| 912 | operator()(); |
| 913 | |
| 914 | /** |
| 915 | * @brief Compares two % subtract_with_carry_engine random number |
| 916 | * generator objects of the same type for equality. |
| 917 | * |
| 918 | * @param __lhs A % subtract_with_carry_engine random number generator |
| 919 | * object. |
| 920 | * @param __rhs Another % subtract_with_carry_engine random number |
| 921 | * generator object. |
| 922 | * |
| 923 | * @returns true if the infinite sequences of generated values |
| 924 | * would be equal, false otherwise. |
| 925 | */ |
| 926 | friend bool |
| 927 | operator==(const subtract_with_carry_engine& __lhs, |
| 928 | const subtract_with_carry_engine& __rhs) |
| 929 | { return (std::equal(__lhs._M_x, __lhs._M_x + long_lag, __rhs._M_x) |
| 930 | && __lhs._M_carry == __rhs._M_carry |
| 931 | && __lhs._M_p == __rhs._M_p); } |
| 932 | |
| 933 | /** |
| 934 | * @brief Inserts the current state of a % subtract_with_carry_engine |
| 935 | * random number generator engine @p __x into the output stream |
| 936 | * @p __os. |
| 937 | * |
| 938 | * @param __os An output stream. |
| 939 | * @param __x A % subtract_with_carry_engine random number generator |
| 940 | * engine. |
| 941 | * |
| 942 | * @returns The output stream with the state of @p __x inserted or in |
| 943 | * an error state. |
| 944 | */ |
| 945 | template<typename _UIntType1, size_t __w1, size_t __s1, size_t __r1, |
| 946 | typename _CharT, typename _Traits> |
| 947 | friend std::basic_ostream<_CharT, _Traits>& |
| 948 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 949 | const std::subtract_with_carry_engine<_UIntType1, __w1, |
| 950 | __s1, __r1>& __x); |
| 951 | |
| 952 | /** |
| 953 | * @brief Extracts the current state of a % subtract_with_carry_engine |
| 954 | * random number generator engine @p __x from the input stream |
| 955 | * @p __is. |
| 956 | * |
| 957 | * @param __is An input stream. |
| 958 | * @param __x A % subtract_with_carry_engine random number generator |
| 959 | * engine. |
| 960 | * |
| 961 | * @returns The input stream with the state of @p __x extracted or in |
| 962 | * an error state. |
| 963 | */ |
| 964 | template<typename _UIntType1, size_t __w1, size_t __s1, size_t __r1, |
| 965 | typename _CharT, typename _Traits> |
| 966 | friend std::basic_istream<_CharT, _Traits>& |
| 967 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 968 | std::subtract_with_carry_engine<_UIntType1, __w1, |
| 969 | __s1, __r1>& __x); |
| 970 | |
| 971 | private: |
| 972 | /// The state of the generator. This is a ring buffer. |
| 973 | _UIntType _M_x[long_lag]; |
| 974 | _UIntType _M_carry; ///< The carry |
| 975 | size_t _M_p; ///< Current index of x(i - r). |
| 976 | }; |
| 977 | |
| 978 | #if __cpp_impl_three_way_comparison < 201907L |
| 979 | /** |
| 980 | * @brief Compares two % subtract_with_carry_engine random number |
| 981 | * generator objects of the same type for inequality. |
| 982 | * |
| 983 | * @param __lhs A % subtract_with_carry_engine random number generator |
| 984 | * object. |
| 985 | * @param __rhs Another % subtract_with_carry_engine random number |
| 986 | * generator object. |
| 987 | * |
| 988 | * @returns true if the infinite sequences of generated values |
| 989 | * would be different, false otherwise. |
| 990 | */ |
| 991 | template<typename _UIntType, size_t __w, size_t __s, size_t __r> |
| 992 | inline bool |
| 993 | operator!=(const std::subtract_with_carry_engine<_UIntType, __w, |
| 994 | __s, __r>& __lhs, |
| 995 | const std::subtract_with_carry_engine<_UIntType, __w, |
| 996 | __s, __r>& __rhs) |
| 997 | { return !(__lhs == __rhs); } |
| 998 | #endif |
| 999 | |
| 1000 | /** |
| 1001 | * Produces random numbers from some base engine by discarding blocks of |
| 1002 | * data. |
| 1003 | * |
| 1004 | * @pre @f$ 0 \leq r \leq p @f$ |
| 1005 | * |
| 1006 | * @headerfile random |
| 1007 | * @since C++11 |
| 1008 | */ |
| 1009 | template<typename _RandomNumberEngine, size_t __p, size_t __r> |
| 1010 | class discard_block_engine |
| 1011 | { |
| 1012 | static_assert(1 <= __r && __r <= __p, |
| 1013 | "template argument substituting __r out of bounds"); |
| 1014 | |
| 1015 | public: |
| 1016 | /** The type of the generated random value. */ |
| 1017 | typedef typename _RandomNumberEngine::result_type result_type; |
| 1018 | |
| 1019 | template<typename _Sseq> |
| 1020 | using _If_seed_seq |
| 1021 | = __detail::_If_seed_seq_for<_Sseq, discard_block_engine, |
| 1022 | result_type>; |
| 1023 | |
| 1024 | // parameter values |
| 1025 | static constexpr size_t block_size = __p; |
| 1026 | static constexpr size_t used_block = __r; |
| 1027 | |
| 1028 | /** |
| 1029 | * @brief Constructs a default %discard_block_engine engine. |
| 1030 | * |
| 1031 | * The underlying engine is default constructed as well. |
| 1032 | */ |
| 1033 | discard_block_engine() |
| 1034 | : _M_b(), _M_n(0) { } |
| 1035 | |
| 1036 | /** |
| 1037 | * @brief Copy constructs a %discard_block_engine engine. |
| 1038 | * |
| 1039 | * Copies an existing base class random number generator. |
| 1040 | * @param __rng An existing (base class) engine object. |
| 1041 | */ |
| 1042 | explicit |
| 1043 | discard_block_engine(const _RandomNumberEngine& __rng) |
| 1044 | : _M_b(__rng), _M_n(0) { } |
| 1045 | |
| 1046 | /** |
| 1047 | * @brief Move constructs a %discard_block_engine engine. |
| 1048 | * |
| 1049 | * Copies an existing base class random number generator. |
| 1050 | * @param __rng An existing (base class) engine object. |
| 1051 | */ |
| 1052 | explicit |
| 1053 | discard_block_engine(_RandomNumberEngine&& __rng) |
| 1054 | : _M_b(std::move(__rng)), _M_n(0) { } |
| 1055 | |
| 1056 | /** |
| 1057 | * @brief Seed constructs a %discard_block_engine engine. |
| 1058 | * |
| 1059 | * Constructs the underlying generator engine seeded with @p __s. |
| 1060 | * @param __s A seed value for the base class engine. |
| 1061 | */ |
| 1062 | explicit |
| 1063 | discard_block_engine(result_type __s) |
| 1064 | : _M_b(__s), _M_n(0) { } |
| 1065 | |
| 1066 | /** |
| 1067 | * @brief Generator construct a %discard_block_engine engine. |
| 1068 | * |
| 1069 | * @param __q A seed sequence. |
| 1070 | */ |
| 1071 | template<typename _Sseq, typename = _If_seed_seq<_Sseq>> |
| 1072 | explicit |
| 1073 | discard_block_engine(_Sseq& __q) |
| 1074 | : _M_b(__q), _M_n(0) |
| 1075 | { } |
| 1076 | |
| 1077 | /** |
| 1078 | * @brief Reseeds the %discard_block_engine object with the default |
| 1079 | * seed for the underlying base class generator engine. |
| 1080 | */ |
| 1081 | void |
| 1082 | seed() |
| 1083 | { |
| 1084 | _M_b.seed(); |
| 1085 | _M_n = 0; |
| 1086 | } |
| 1087 | |
| 1088 | /** |
| 1089 | * @brief Reseeds the %discard_block_engine object with the default |
| 1090 | * seed for the underlying base class generator engine. |
| 1091 | */ |
| 1092 | void |
| 1093 | seed(result_type __s) |
| 1094 | { |
| 1095 | _M_b.seed(__s); |
| 1096 | _M_n = 0; |
| 1097 | } |
| 1098 | |
| 1099 | /** |
| 1100 | * @brief Reseeds the %discard_block_engine object with the given seed |
| 1101 | * sequence. |
| 1102 | * @param __q A seed generator function. |
| 1103 | */ |
| 1104 | template<typename _Sseq> |
| 1105 | _If_seed_seq<_Sseq> |
| 1106 | seed(_Sseq& __q) |
| 1107 | { |
| 1108 | _M_b.seed(__q); |
| 1109 | _M_n = 0; |
| 1110 | } |
| 1111 | |
| 1112 | /** |
| 1113 | * @brief Gets a const reference to the underlying generator engine |
| 1114 | * object. |
| 1115 | */ |
| 1116 | const _RandomNumberEngine& |
| 1117 | base() const noexcept |
| 1118 | { return _M_b; } |
| 1119 | |
| 1120 | /** |
| 1121 | * @brief Gets the minimum value in the generated random number range. |
| 1122 | */ |
| 1123 | static constexpr result_type |
| 1124 | min() |
| 1125 | { return _RandomNumberEngine::min(); } |
| 1126 | |
| 1127 | /** |
| 1128 | * @brief Gets the maximum value in the generated random number range. |
| 1129 | */ |
| 1130 | static constexpr result_type |
| 1131 | max() |
| 1132 | { return _RandomNumberEngine::max(); } |
| 1133 | |
| 1134 | /** |
| 1135 | * @brief Discard a sequence of random numbers. |
| 1136 | */ |
| 1137 | void |
| 1138 | discard(unsigned long long __z) |
| 1139 | { |
| 1140 | for (; __z != 0ULL; --__z) |
| 1141 | (*this)(); |
| 1142 | } |
| 1143 | |
| 1144 | /** |
| 1145 | * @brief Gets the next value in the generated random number sequence. |
| 1146 | */ |
| 1147 | result_type |
| 1148 | operator()(); |
| 1149 | |
| 1150 | /** |
| 1151 | * @brief Compares two %discard_block_engine random number generator |
| 1152 | * objects of the same type for equality. |
| 1153 | * |
| 1154 | * @param __lhs A %discard_block_engine random number generator object. |
| 1155 | * @param __rhs Another %discard_block_engine random number generator |
| 1156 | * object. |
| 1157 | * |
| 1158 | * @returns true if the infinite sequences of generated values |
| 1159 | * would be equal, false otherwise. |
| 1160 | */ |
| 1161 | friend bool |
| 1162 | operator==(const discard_block_engine& __lhs, |
| 1163 | const discard_block_engine& __rhs) |
| 1164 | { return __lhs._M_b == __rhs._M_b && __lhs._M_n == __rhs._M_n; } |
| 1165 | |
| 1166 | /** |
| 1167 | * @brief Inserts the current state of a %discard_block_engine random |
| 1168 | * number generator engine @p __x into the output stream |
| 1169 | * @p __os. |
| 1170 | * |
| 1171 | * @param __os An output stream. |
| 1172 | * @param __x A %discard_block_engine random number generator engine. |
| 1173 | * |
| 1174 | * @returns The output stream with the state of @p __x inserted or in |
| 1175 | * an error state. |
| 1176 | */ |
| 1177 | template<typename _RandomNumberEngine1, size_t __p1, size_t __r1, |
| 1178 | typename _CharT, typename _Traits> |
| 1179 | friend std::basic_ostream<_CharT, _Traits>& |
| 1180 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 1181 | const std::discard_block_engine<_RandomNumberEngine1, |
| 1182 | __p1, __r1>& __x); |
| 1183 | |
| 1184 | /** |
| 1185 | * @brief Extracts the current state of a % subtract_with_carry_engine |
| 1186 | * random number generator engine @p __x from the input stream |
| 1187 | * @p __is. |
| 1188 | * |
| 1189 | * @param __is An input stream. |
| 1190 | * @param __x A %discard_block_engine random number generator engine. |
| 1191 | * |
| 1192 | * @returns The input stream with the state of @p __x extracted or in |
| 1193 | * an error state. |
| 1194 | */ |
| 1195 | template<typename _RandomNumberEngine1, size_t __p1, size_t __r1, |
| 1196 | typename _CharT, typename _Traits> |
| 1197 | friend std::basic_istream<_CharT, _Traits>& |
| 1198 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 1199 | std::discard_block_engine<_RandomNumberEngine1, |
| 1200 | __p1, __r1>& __x); |
| 1201 | |
| 1202 | private: |
| 1203 | _RandomNumberEngine _M_b; |
| 1204 | size_t _M_n; |
| 1205 | }; |
| 1206 | |
| 1207 | #if __cpp_impl_three_way_comparison < 201907L |
| 1208 | /** |
| 1209 | * @brief Compares two %discard_block_engine random number generator |
| 1210 | * objects of the same type for inequality. |
| 1211 | * |
| 1212 | * @param __lhs A %discard_block_engine random number generator object. |
| 1213 | * @param __rhs Another %discard_block_engine random number generator |
| 1214 | * object. |
| 1215 | * |
| 1216 | * @returns true if the infinite sequences of generated values |
| 1217 | * would be different, false otherwise. |
| 1218 | */ |
| 1219 | template<typename _RandomNumberEngine, size_t __p, size_t __r> |
| 1220 | inline bool |
| 1221 | operator!=(const std::discard_block_engine<_RandomNumberEngine, __p, |
| 1222 | __r>& __lhs, |
| 1223 | const std::discard_block_engine<_RandomNumberEngine, __p, |
| 1224 | __r>& __rhs) |
| 1225 | { return !(__lhs == __rhs); } |
| 1226 | #endif |
| 1227 | |
| 1228 | /** |
| 1229 | * Produces random numbers by combining random numbers from some base |
| 1230 | * engine to produce random numbers with a specified number of bits @p __w. |
| 1231 | * |
| 1232 | * @headerfile random |
| 1233 | * @since C++11 |
| 1234 | */ |
| 1235 | template<typename _RandomNumberEngine, size_t __w, typename _UIntType> |
| 1236 | class independent_bits_engine |
| 1237 | { |
| 1238 | static_assert(std::is_unsigned<_UIntType>::value, |
| 1239 | "result_type must be an unsigned integral type"); |
| 1240 | static_assert(0u < __w && __w <= std::numeric_limits<_UIntType>::digits, |
| 1241 | "template argument substituting __w out of bounds"); |
| 1242 | |
| 1243 | template<typename _Sseq> |
| 1244 | using _If_seed_seq |
| 1245 | = __detail::_If_seed_seq_for<_Sseq, independent_bits_engine, |
| 1246 | _UIntType>; |
| 1247 | |
| 1248 | public: |
| 1249 | /** The type of the generated random value. */ |
| 1250 | typedef _UIntType result_type; |
| 1251 | |
| 1252 | /** |
| 1253 | * @brief Constructs a default %independent_bits_engine engine. |
| 1254 | * |
| 1255 | * The underlying engine is default constructed as well. |
| 1256 | */ |
| 1257 | independent_bits_engine() |
| 1258 | : _M_b() { } |
| 1259 | |
| 1260 | /** |
| 1261 | * @brief Copy constructs a %independent_bits_engine engine. |
| 1262 | * |
| 1263 | * Copies an existing base class random number generator. |
| 1264 | * @param __rng An existing (base class) engine object. |
| 1265 | */ |
| 1266 | explicit |
| 1267 | independent_bits_engine(const _RandomNumberEngine& __rng) |
| 1268 | : _M_b(__rng) { } |
| 1269 | |
| 1270 | /** |
| 1271 | * @brief Move constructs a %independent_bits_engine engine. |
| 1272 | * |
| 1273 | * Copies an existing base class random number generator. |
| 1274 | * @param __rng An existing (base class) engine object. |
| 1275 | */ |
| 1276 | explicit |
| 1277 | independent_bits_engine(_RandomNumberEngine&& __rng) |
| 1278 | : _M_b(std::move(__rng)) { } |
| 1279 | |
| 1280 | /** |
| 1281 | * @brief Seed constructs a %independent_bits_engine engine. |
| 1282 | * |
| 1283 | * Constructs the underlying generator engine seeded with @p __s. |
| 1284 | * @param __s A seed value for the base class engine. |
| 1285 | */ |
| 1286 | explicit |
| 1287 | independent_bits_engine(result_type __s) |
| 1288 | : _M_b(__s) { } |
| 1289 | |
| 1290 | /** |
| 1291 | * @brief Generator construct a %independent_bits_engine engine. |
| 1292 | * |
| 1293 | * @param __q A seed sequence. |
| 1294 | */ |
| 1295 | template<typename _Sseq, typename = _If_seed_seq<_Sseq>> |
| 1296 | explicit |
| 1297 | independent_bits_engine(_Sseq& __q) |
| 1298 | : _M_b(__q) |
| 1299 | { } |
| 1300 | |
| 1301 | /** |
| 1302 | * @brief Reseeds the %independent_bits_engine object with the default |
| 1303 | * seed for the underlying base class generator engine. |
| 1304 | */ |
| 1305 | void |
| 1306 | seed() |
| 1307 | { _M_b.seed(); } |
| 1308 | |
| 1309 | /** |
| 1310 | * @brief Reseeds the %independent_bits_engine object with the default |
| 1311 | * seed for the underlying base class generator engine. |
| 1312 | */ |
| 1313 | void |
| 1314 | seed(result_type __s) |
| 1315 | { _M_b.seed(__s); } |
| 1316 | |
| 1317 | /** |
| 1318 | * @brief Reseeds the %independent_bits_engine object with the given |
| 1319 | * seed sequence. |
| 1320 | * @param __q A seed generator function. |
| 1321 | */ |
| 1322 | template<typename _Sseq> |
| 1323 | _If_seed_seq<_Sseq> |
| 1324 | seed(_Sseq& __q) |
| 1325 | { _M_b.seed(__q); } |
| 1326 | |
| 1327 | /** |
| 1328 | * @brief Gets a const reference to the underlying generator engine |
| 1329 | * object. |
| 1330 | */ |
| 1331 | const _RandomNumberEngine& |
| 1332 | base() const noexcept |
| 1333 | { return _M_b; } |
| 1334 | |
| 1335 | /** |
| 1336 | * @brief Gets the minimum value in the generated random number range. |
| 1337 | */ |
| 1338 | static constexpr result_type |
| 1339 | min() |
| 1340 | { return 0U; } |
| 1341 | |
| 1342 | /** |
| 1343 | * @brief Gets the maximum value in the generated random number range. |
| 1344 | */ |
| 1345 | static constexpr result_type |
| 1346 | max() |
| 1347 | { return __detail::_Shift<_UIntType, __w>::__value - 1; } |
| 1348 | |
| 1349 | /** |
| 1350 | * @brief Discard a sequence of random numbers. |
| 1351 | */ |
| 1352 | void |
| 1353 | discard(unsigned long long __z) |
| 1354 | { |
| 1355 | for (; __z != 0ULL; --__z) |
| 1356 | (*this)(); |
| 1357 | } |
| 1358 | |
| 1359 | /** |
| 1360 | * @brief Gets the next value in the generated random number sequence. |
| 1361 | */ |
| 1362 | result_type |
| 1363 | operator()(); |
| 1364 | |
| 1365 | /** |
| 1366 | * @brief Compares two %independent_bits_engine random number generator |
| 1367 | * objects of the same type for equality. |
| 1368 | * |
| 1369 | * @param __lhs A %independent_bits_engine random number generator |
| 1370 | * object. |
| 1371 | * @param __rhs Another %independent_bits_engine random number generator |
| 1372 | * object. |
| 1373 | * |
| 1374 | * @returns true if the infinite sequences of generated values |
| 1375 | * would be equal, false otherwise. |
| 1376 | */ |
| 1377 | friend bool |
| 1378 | operator==(const independent_bits_engine& __lhs, |
| 1379 | const independent_bits_engine& __rhs) |
| 1380 | { return __lhs._M_b == __rhs._M_b; } |
| 1381 | |
| 1382 | /** |
| 1383 | * @brief Extracts the current state of a % subtract_with_carry_engine |
| 1384 | * random number generator engine @p __x from the input stream |
| 1385 | * @p __is. |
| 1386 | * |
| 1387 | * @param __is An input stream. |
| 1388 | * @param __x A %independent_bits_engine random number generator |
| 1389 | * engine. |
| 1390 | * |
| 1391 | * @returns The input stream with the state of @p __x extracted or in |
| 1392 | * an error state. |
| 1393 | */ |
| 1394 | template<typename _CharT, typename _Traits> |
| 1395 | friend std::basic_istream<_CharT, _Traits>& |
| 1396 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 1397 | std::independent_bits_engine<_RandomNumberEngine, |
| 1398 | __w, _UIntType>& __x) |
| 1399 | { |
| 1400 | __is >> __x._M_b; |
| 1401 | return __is; |
| 1402 | } |
| 1403 | |
| 1404 | private: |
| 1405 | _RandomNumberEngine _M_b; |
| 1406 | }; |
| 1407 | |
| 1408 | #if __cpp_impl_three_way_comparison < 201907L |
| 1409 | /** |
| 1410 | * @brief Compares two %independent_bits_engine random number generator |
| 1411 | * objects of the same type for inequality. |
| 1412 | * |
| 1413 | * @param __lhs A %independent_bits_engine random number generator |
| 1414 | * object. |
| 1415 | * @param __rhs Another %independent_bits_engine random number generator |
| 1416 | * object. |
| 1417 | * |
| 1418 | * @returns true if the infinite sequences of generated values |
| 1419 | * would be different, false otherwise. |
| 1420 | */ |
| 1421 | template<typename _RandomNumberEngine, size_t __w, typename _UIntType> |
| 1422 | inline bool |
| 1423 | operator!=(const std::independent_bits_engine<_RandomNumberEngine, __w, |
| 1424 | _UIntType>& __lhs, |
| 1425 | const std::independent_bits_engine<_RandomNumberEngine, __w, |
| 1426 | _UIntType>& __rhs) |
| 1427 | { return !(__lhs == __rhs); } |
| 1428 | #endif |
| 1429 | |
| 1430 | /** |
| 1431 | * @brief Inserts the current state of a %independent_bits_engine random |
| 1432 | * number generator engine @p __x into the output stream @p __os. |
| 1433 | * |
| 1434 | * @param __os An output stream. |
| 1435 | * @param __x A %independent_bits_engine random number generator engine. |
| 1436 | * |
| 1437 | * @returns The output stream with the state of @p __x inserted or in |
| 1438 | * an error state. |
| 1439 | */ |
| 1440 | template<typename _RandomNumberEngine, size_t __w, typename _UIntType, |
| 1441 | typename _CharT, typename _Traits> |
| 1442 | std::basic_ostream<_CharT, _Traits>& |
| 1443 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 1444 | const std::independent_bits_engine<_RandomNumberEngine, |
| 1445 | __w, _UIntType>& __x) |
| 1446 | { |
| 1447 | __os << __x.base(); |
| 1448 | return __os; |
| 1449 | } |
| 1450 | |
| 1451 | |
| 1452 | /** |
| 1453 | * @brief Produces random numbers by reordering random numbers from some |
| 1454 | * base engine. |
| 1455 | * |
| 1456 | * The values from the base engine are stored in a sequence of size @p __k |
| 1457 | * and shuffled by an algorithm that depends on those values. |
| 1458 | * |
| 1459 | * @headerfile random |
| 1460 | * @since C++11 |
| 1461 | */ |
| 1462 | template<typename _RandomNumberEngine, size_t __k> |
| 1463 | class shuffle_order_engine |
| 1464 | { |
| 1465 | static_assert(1u <= __k, "template argument substituting " |
| 1466 | "__k out of bound"); |
| 1467 | |
| 1468 | public: |
| 1469 | /** The type of the generated random value. */ |
| 1470 | typedef typename _RandomNumberEngine::result_type result_type; |
| 1471 | |
| 1472 | template<typename _Sseq> |
| 1473 | using _If_seed_seq |
| 1474 | = __detail::_If_seed_seq_for<_Sseq, shuffle_order_engine, |
| 1475 | result_type>; |
| 1476 | |
| 1477 | static constexpr size_t table_size = __k; |
| 1478 | |
| 1479 | /** |
| 1480 | * @brief Constructs a default %shuffle_order_engine engine. |
| 1481 | * |
| 1482 | * The underlying engine is default constructed as well. |
| 1483 | */ |
| 1484 | shuffle_order_engine() |
| 1485 | : _M_b() |
| 1486 | { _M_initialize(); } |
| 1487 | |
| 1488 | /** |
| 1489 | * @brief Copy constructs a %shuffle_order_engine engine. |
| 1490 | * |
| 1491 | * Copies an existing base class random number generator. |
| 1492 | * @param __rng An existing (base class) engine object. |
| 1493 | */ |
| 1494 | explicit |
| 1495 | shuffle_order_engine(const _RandomNumberEngine& __rng) |
| 1496 | : _M_b(__rng) |
| 1497 | { _M_initialize(); } |
| 1498 | |
| 1499 | /** |
| 1500 | * @brief Move constructs a %shuffle_order_engine engine. |
| 1501 | * |
| 1502 | * Copies an existing base class random number generator. |
| 1503 | * @param __rng An existing (base class) engine object. |
| 1504 | */ |
| 1505 | explicit |
| 1506 | shuffle_order_engine(_RandomNumberEngine&& __rng) |
| 1507 | : _M_b(std::move(__rng)) |
| 1508 | { _M_initialize(); } |
| 1509 | |
| 1510 | /** |
| 1511 | * @brief Seed constructs a %shuffle_order_engine engine. |
| 1512 | * |
| 1513 | * Constructs the underlying generator engine seeded with @p __s. |
| 1514 | * @param __s A seed value for the base class engine. |
| 1515 | */ |
| 1516 | explicit |
| 1517 | shuffle_order_engine(result_type __s) |
| 1518 | : _M_b(__s) |
| 1519 | { _M_initialize(); } |
| 1520 | |
| 1521 | /** |
| 1522 | * @brief Generator construct a %shuffle_order_engine engine. |
| 1523 | * |
| 1524 | * @param __q A seed sequence. |
| 1525 | */ |
| 1526 | template<typename _Sseq, typename = _If_seed_seq<_Sseq>> |
| 1527 | explicit |
| 1528 | shuffle_order_engine(_Sseq& __q) |
| 1529 | : _M_b(__q) |
| 1530 | { _M_initialize(); } |
| 1531 | |
| 1532 | /** |
| 1533 | * @brief Reseeds the %shuffle_order_engine object with the default seed |
| 1534 | for the underlying base class generator engine. |
| 1535 | */ |
| 1536 | void |
| 1537 | seed() |
| 1538 | { |
| 1539 | _M_b.seed(); |
| 1540 | _M_initialize(); |
| 1541 | } |
| 1542 | |
| 1543 | /** |
| 1544 | * @brief Reseeds the %shuffle_order_engine object with the default seed |
| 1545 | * for the underlying base class generator engine. |
| 1546 | */ |
| 1547 | void |
| 1548 | seed(result_type __s) |
| 1549 | { |
| 1550 | _M_b.seed(__s); |
| 1551 | _M_initialize(); |
| 1552 | } |
| 1553 | |
| 1554 | /** |
| 1555 | * @brief Reseeds the %shuffle_order_engine object with the given seed |
| 1556 | * sequence. |
| 1557 | * @param __q A seed generator function. |
| 1558 | */ |
| 1559 | template<typename _Sseq> |
| 1560 | _If_seed_seq<_Sseq> |
| 1561 | seed(_Sseq& __q) |
| 1562 | { |
| 1563 | _M_b.seed(__q); |
| 1564 | _M_initialize(); |
| 1565 | } |
| 1566 | |
| 1567 | /** |
| 1568 | * Gets a const reference to the underlying generator engine object. |
| 1569 | */ |
| 1570 | const _RandomNumberEngine& |
| 1571 | base() const noexcept |
| 1572 | { return _M_b; } |
| 1573 | |
| 1574 | /** |
| 1575 | * Gets the minimum value in the generated random number range. |
| 1576 | */ |
| 1577 | static constexpr result_type |
| 1578 | min() |
| 1579 | { return _RandomNumberEngine::min(); } |
| 1580 | |
| 1581 | /** |
| 1582 | * Gets the maximum value in the generated random number range. |
| 1583 | */ |
| 1584 | static constexpr result_type |
| 1585 | max() |
| 1586 | { return _RandomNumberEngine::max(); } |
| 1587 | |
| 1588 | /** |
| 1589 | * Discard a sequence of random numbers. |
| 1590 | */ |
| 1591 | void |
| 1592 | discard(unsigned long long __z) |
| 1593 | { |
| 1594 | for (; __z != 0ULL; --__z) |
| 1595 | (*this)(); |
| 1596 | } |
| 1597 | |
| 1598 | /** |
| 1599 | * Gets the next value in the generated random number sequence. |
| 1600 | */ |
| 1601 | result_type |
| 1602 | operator()(); |
| 1603 | |
| 1604 | /** |
| 1605 | * Compares two %shuffle_order_engine random number generator objects |
| 1606 | * of the same type for equality. |
| 1607 | * |
| 1608 | * @param __lhs A %shuffle_order_engine random number generator object. |
| 1609 | * @param __rhs Another %shuffle_order_engine random number generator |
| 1610 | * object. |
| 1611 | * |
| 1612 | * @returns true if the infinite sequences of generated values |
| 1613 | * would be equal, false otherwise. |
| 1614 | */ |
| 1615 | friend bool |
| 1616 | operator==(const shuffle_order_engine& __lhs, |
| 1617 | const shuffle_order_engine& __rhs) |
| 1618 | { return (__lhs._M_b == __rhs._M_b |
| 1619 | && std::equal(__lhs._M_v, __lhs._M_v + __k, __rhs._M_v) |
| 1620 | && __lhs._M_y == __rhs._M_y); } |
| 1621 | |
| 1622 | /** |
| 1623 | * @brief Inserts the current state of a %shuffle_order_engine random |
| 1624 | * number generator engine @p __x into the output stream |
| 1625 | @p __os. |
| 1626 | * |
| 1627 | * @param __os An output stream. |
| 1628 | * @param __x A %shuffle_order_engine random number generator engine. |
| 1629 | * |
| 1630 | * @returns The output stream with the state of @p __x inserted or in |
| 1631 | * an error state. |
| 1632 | */ |
| 1633 | template<typename _RandomNumberEngine1, size_t __k1, |
| 1634 | typename _CharT, typename _Traits> |
| 1635 | friend std::basic_ostream<_CharT, _Traits>& |
| 1636 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 1637 | const std::shuffle_order_engine<_RandomNumberEngine1, |
| 1638 | __k1>& __x); |
| 1639 | |
| 1640 | /** |
| 1641 | * @brief Extracts the current state of a % subtract_with_carry_engine |
| 1642 | * random number generator engine @p __x from the input stream |
| 1643 | * @p __is. |
| 1644 | * |
| 1645 | * @param __is An input stream. |
| 1646 | * @param __x A %shuffle_order_engine random number generator engine. |
| 1647 | * |
| 1648 | * @returns The input stream with the state of @p __x extracted or in |
| 1649 | * an error state. |
| 1650 | */ |
| 1651 | template<typename _RandomNumberEngine1, size_t __k1, |
| 1652 | typename _CharT, typename _Traits> |
| 1653 | friend std::basic_istream<_CharT, _Traits>& |
| 1654 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 1655 | std::shuffle_order_engine<_RandomNumberEngine1, __k1>& __x); |
| 1656 | |
| 1657 | private: |
| 1658 | void _M_initialize() |
| 1659 | { |
| 1660 | for (size_t __i = 0; __i < __k; ++__i) |
| 1661 | _M_v[__i] = _M_b(); |
| 1662 | _M_y = _M_b(); |
| 1663 | } |
| 1664 | |
| 1665 | _RandomNumberEngine _M_b; |
| 1666 | result_type _M_v[__k]; |
| 1667 | result_type _M_y; |
| 1668 | }; |
| 1669 | |
| 1670 | #if __cpp_impl_three_way_comparison < 201907L |
| 1671 | /** |
| 1672 | * Compares two %shuffle_order_engine random number generator objects |
| 1673 | * of the same type for inequality. |
| 1674 | * |
| 1675 | * @param __lhs A %shuffle_order_engine random number generator object. |
| 1676 | * @param __rhs Another %shuffle_order_engine random number generator |
| 1677 | * object. |
| 1678 | * |
| 1679 | * @returns true if the infinite sequences of generated values |
| 1680 | * would be different, false otherwise. |
| 1681 | */ |
| 1682 | template<typename _RandomNumberEngine, size_t __k> |
| 1683 | inline bool |
| 1684 | operator!=(const std::shuffle_order_engine<_RandomNumberEngine, |
| 1685 | __k>& __lhs, |
| 1686 | const std::shuffle_order_engine<_RandomNumberEngine, |
| 1687 | __k>& __rhs) |
| 1688 | { return !(__lhs == __rhs); } |
| 1689 | #endif |
| 1690 | |
| 1691 | /** |
| 1692 | * The classic Minimum Standard rand0 of Lewis, Goodman, and Miller. |
| 1693 | */ |
| 1694 | typedef linear_congruential_engine<uint_fast32_t, 16807UL, 0UL, 2147483647UL> |
| 1695 | minstd_rand0; |
| 1696 | |
| 1697 | /** |
| 1698 | * An alternative LCR (Lehmer Generator function). |
| 1699 | */ |
| 1700 | typedef linear_congruential_engine<uint_fast32_t, 48271UL, 0UL, 2147483647UL> |
| 1701 | minstd_rand; |
| 1702 | |
| 1703 | /** |
| 1704 | * The classic Mersenne Twister. |
| 1705 | * |
| 1706 | * Reference: |
| 1707 | * M. Matsumoto and T. Nishimura, Mersenne Twister: A 623-Dimensionally |
| 1708 | * Equidistributed Uniform Pseudo-Random Number Generator, ACM Transactions |
| 1709 | * on Modeling and Computer Simulation, Vol. 8, No. 1, January 1998, pp 3-30. |
| 1710 | */ |
| 1711 | typedef mersenne_twister_engine< |
| 1712 | uint_fast32_t, |
| 1713 | 32, 624, 397, 31, |
| 1714 | 0x9908b0dfUL, 11, |
| 1715 | 0xffffffffUL, 7, |
| 1716 | 0x9d2c5680UL, 15, |
| 1717 | 0xefc60000UL, 18, 1812433253UL> mt19937; |
| 1718 | |
| 1719 | /** |
| 1720 | * An alternative Mersenne Twister. |
| 1721 | */ |
| 1722 | typedef mersenne_twister_engine< |
| 1723 | uint_fast64_t, |
| 1724 | 64, 312, 156, 31, |
| 1725 | 0xb5026f5aa96619e9ULL, 29, |
| 1726 | 0x5555555555555555ULL, 17, |
| 1727 | 0x71d67fffeda60000ULL, 37, |
| 1728 | 0xfff7eee000000000ULL, 43, |
| 1729 | 6364136223846793005ULL> mt19937_64; |
| 1730 | |
| 1731 | typedef subtract_with_carry_engine<uint_fast32_t, 24, 10, 24> |
| 1732 | ranlux24_base; |
| 1733 | |
| 1734 | typedef subtract_with_carry_engine<uint_fast64_t, 48, 5, 12> |
| 1735 | ranlux48_base; |
| 1736 | |
| 1737 | typedef discard_block_engine<ranlux24_base, 223, 23> ranlux24; |
| 1738 | |
| 1739 | typedef discard_block_engine<ranlux48_base, 389, 11> ranlux48; |
| 1740 | |
| 1741 | typedef shuffle_order_engine<minstd_rand0, 256> knuth_b; |
| 1742 | |
| 1743 | typedef minstd_rand0 default_random_engine; |
| 1744 | |
| 1745 | /** |
| 1746 | * A standard interface to a platform-specific non-deterministic |
| 1747 | * random number generator (if any are available). |
| 1748 | * |
| 1749 | * @headerfile random |
| 1750 | * @since C++11 |
| 1751 | */ |
| 1752 | class random_device |
| 1753 | { |
| 1754 | public: |
| 1755 | /** The type of the generated random value. */ |
| 1756 | typedef unsigned int result_type; |
| 1757 | |
| 1758 | // constructors, destructors and member functions |
| 1759 | |
| 1760 | random_device() { _M_init(token: "default"); } |
| 1761 | |
| 1762 | explicit |
| 1763 | random_device(const std::string& __token) { _M_init(__token); } |
| 1764 | |
| 1765 | ~random_device() |
| 1766 | { _M_fini(); } |
| 1767 | |
| 1768 | static constexpr result_type |
| 1769 | min() |
| 1770 | { return std::numeric_limits<result_type>::min(); } |
| 1771 | |
| 1772 | static constexpr result_type |
| 1773 | max() |
| 1774 | { return std::numeric_limits<result_type>::max(); } |
| 1775 | |
| 1776 | double |
| 1777 | entropy() const noexcept |
| 1778 | { return this->_M_getentropy(); } |
| 1779 | |
| 1780 | result_type |
| 1781 | operator()() |
| 1782 | { return this->_M_getval(); } |
| 1783 | |
| 1784 | // No copy functions. |
| 1785 | random_device(const random_device&) = delete; |
| 1786 | void operator=(const random_device&) = delete; |
| 1787 | |
| 1788 | private: |
| 1789 | |
| 1790 | void _M_init(const std::string& __token); |
| 1791 | void _M_init_pretr1(const std::string& __token); |
| 1792 | void _M_fini(); |
| 1793 | |
| 1794 | result_type _M_getval(); |
| 1795 | result_type _M_getval_pretr1(); |
| 1796 | double _M_getentropy() const noexcept; |
| 1797 | |
| 1798 | void _M_init(const char*, size_t); // not exported from the shared library |
| 1799 | |
| 1800 | __extension__ union |
| 1801 | { |
| 1802 | struct |
| 1803 | { |
| 1804 | void* _M_file; |
| 1805 | result_type (*_M_func)(void*); |
| 1806 | int _M_fd; |
| 1807 | }; |
| 1808 | mt19937 _M_mt; |
| 1809 | }; |
| 1810 | }; |
| 1811 | |
| 1812 | /// @} group random_generators |
| 1813 | |
| 1814 | /** |
| 1815 | * @addtogroup random_distributions Random Number Distributions |
| 1816 | * @ingroup random |
| 1817 | * @{ |
| 1818 | */ |
| 1819 | |
| 1820 | /** |
| 1821 | * @addtogroup random_distributions_uniform Uniform Distributions |
| 1822 | * @ingroup random_distributions |
| 1823 | * @{ |
| 1824 | */ |
| 1825 | |
| 1826 | // std::uniform_int_distribution is defined in <bits/uniform_int_dist.h> |
| 1827 | |
| 1828 | #if __cpp_impl_three_way_comparison < 201907L |
| 1829 | /** |
| 1830 | * @brief Return true if two uniform integer distributions have |
| 1831 | * different parameters. |
| 1832 | */ |
| 1833 | template<typename _IntType> |
| 1834 | inline bool |
| 1835 | operator!=(const std::uniform_int_distribution<_IntType>& __d1, |
| 1836 | const std::uniform_int_distribution<_IntType>& __d2) |
| 1837 | { return !(__d1 == __d2); } |
| 1838 | #endif |
| 1839 | |
| 1840 | /** |
| 1841 | * @brief Inserts a %uniform_int_distribution random number |
| 1842 | * distribution @p __x into the output stream @p os. |
| 1843 | * |
| 1844 | * @param __os An output stream. |
| 1845 | * @param __x A %uniform_int_distribution random number distribution. |
| 1846 | * |
| 1847 | * @returns The output stream with the state of @p __x inserted or in |
| 1848 | * an error state. |
| 1849 | */ |
| 1850 | template<typename _IntType, typename _CharT, typename _Traits> |
| 1851 | std::basic_ostream<_CharT, _Traits>& |
| 1852 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
| 1853 | const std::uniform_int_distribution<_IntType>&); |
| 1854 | |
| 1855 | /** |
| 1856 | * @brief Extracts a %uniform_int_distribution random number distribution |
| 1857 | * @p __x from the input stream @p __is. |
| 1858 | * |
| 1859 | * @param __is An input stream. |
| 1860 | * @param __x A %uniform_int_distribution random number generator engine. |
| 1861 | * |
| 1862 | * @returns The input stream with @p __x extracted or in an error state. |
| 1863 | */ |
| 1864 | template<typename _IntType, typename _CharT, typename _Traits> |
| 1865 | std::basic_istream<_CharT, _Traits>& |
| 1866 | operator>>(std::basic_istream<_CharT, _Traits>&, |
| 1867 | std::uniform_int_distribution<_IntType>&); |
| 1868 | |
| 1869 | |
| 1870 | /** |
| 1871 | * @brief Uniform continuous distribution for random numbers. |
| 1872 | * |
| 1873 | * A continuous random distribution on the range [min, max) with equal |
| 1874 | * probability throughout the range. The URNG should be real-valued and |
| 1875 | * deliver number in the range [0, 1). |
| 1876 | * |
| 1877 | * @headerfile random |
| 1878 | * @since C++11 |
| 1879 | */ |
| 1880 | template<typename _RealType = double> |
| 1881 | class uniform_real_distribution |
| 1882 | { |
| 1883 | static_assert(std::is_floating_point<_RealType>::value, |
| 1884 | "result_type must be a floating point type"); |
| 1885 | |
| 1886 | public: |
| 1887 | /** The type of the range of the distribution. */ |
| 1888 | typedef _RealType result_type; |
| 1889 | |
| 1890 | /** Parameter type. */ |
| 1891 | struct param_type |
| 1892 | { |
| 1893 | typedef uniform_real_distribution<_RealType> distribution_type; |
| 1894 | |
| 1895 | param_type() : param_type(0) { } |
| 1896 | |
| 1897 | explicit |
| 1898 | param_type(_RealType __a, _RealType __b = _RealType(1)) |
| 1899 | : _M_a(__a), _M_b(__b) |
| 1900 | { |
| 1901 | __glibcxx_assert(_M_a <= _M_b); |
| 1902 | } |
| 1903 | |
| 1904 | result_type |
| 1905 | a() const |
| 1906 | { return _M_a; } |
| 1907 | |
| 1908 | result_type |
| 1909 | b() const |
| 1910 | { return _M_b; } |
| 1911 | |
| 1912 | friend bool |
| 1913 | operator==(const param_type& __p1, const param_type& __p2) |
| 1914 | { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; } |
| 1915 | |
| 1916 | #if __cpp_impl_three_way_comparison < 201907L |
| 1917 | friend bool |
| 1918 | operator!=(const param_type& __p1, const param_type& __p2) |
| 1919 | { return !(__p1 == __p2); } |
| 1920 | #endif |
| 1921 | |
| 1922 | private: |
| 1923 | _RealType _M_a; |
| 1924 | _RealType _M_b; |
| 1925 | }; |
| 1926 | |
| 1927 | public: |
| 1928 | /** |
| 1929 | * @brief Constructs a uniform_real_distribution object. |
| 1930 | * |
| 1931 | * The lower bound is set to 0.0 and the upper bound to 1.0 |
| 1932 | */ |
| 1933 | uniform_real_distribution() : uniform_real_distribution(0.0) { } |
| 1934 | |
| 1935 | /** |
| 1936 | * @brief Constructs a uniform_real_distribution object. |
| 1937 | * |
| 1938 | * @param __a [IN] The lower bound of the distribution. |
| 1939 | * @param __b [IN] The upper bound of the distribution. |
| 1940 | */ |
| 1941 | explicit |
| 1942 | uniform_real_distribution(_RealType __a, _RealType __b = _RealType(1)) |
| 1943 | : _M_param(__a, __b) |
| 1944 | { } |
| 1945 | |
| 1946 | explicit |
| 1947 | uniform_real_distribution(const param_type& __p) |
| 1948 | : _M_param(__p) |
| 1949 | { } |
| 1950 | |
| 1951 | /** |
| 1952 | * @brief Resets the distribution state. |
| 1953 | * |
| 1954 | * Does nothing for the uniform real distribution. |
| 1955 | */ |
| 1956 | void |
| 1957 | reset() { } |
| 1958 | |
| 1959 | result_type |
| 1960 | a() const |
| 1961 | { return _M_param.a(); } |
| 1962 | |
| 1963 | result_type |
| 1964 | b() const |
| 1965 | { return _M_param.b(); } |
| 1966 | |
| 1967 | /** |
| 1968 | * @brief Returns the parameter set of the distribution. |
| 1969 | */ |
| 1970 | param_type |
| 1971 | param() const |
| 1972 | { return _M_param; } |
| 1973 | |
| 1974 | /** |
| 1975 | * @brief Sets the parameter set of the distribution. |
| 1976 | * @param __param The new parameter set of the distribution. |
| 1977 | */ |
| 1978 | void |
| 1979 | param(const param_type& __param) |
| 1980 | { _M_param = __param; } |
| 1981 | |
| 1982 | /** |
| 1983 | * @brief Returns the inclusive lower bound of the distribution range. |
| 1984 | */ |
| 1985 | result_type |
| 1986 | min() const |
| 1987 | { return this->a(); } |
| 1988 | |
| 1989 | /** |
| 1990 | * @brief Returns the inclusive upper bound of the distribution range. |
| 1991 | */ |
| 1992 | result_type |
| 1993 | max() const |
| 1994 | { return this->b(); } |
| 1995 | |
| 1996 | /** |
| 1997 | * @brief Generating functions. |
| 1998 | */ |
| 1999 | template<typename _UniformRandomNumberGenerator> |
| 2000 | result_type |
| 2001 | operator()(_UniformRandomNumberGenerator& __urng) |
| 2002 | { return this->operator()(__urng, _M_param); } |
| 2003 | |
| 2004 | template<typename _UniformRandomNumberGenerator> |
| 2005 | result_type |
| 2006 | operator()(_UniformRandomNumberGenerator& __urng, |
| 2007 | const param_type& __p) |
| 2008 | { |
| 2009 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> |
| 2010 | __aurng(__urng); |
| 2011 | return (__aurng() * (__p.b() - __p.a())) + __p.a(); |
| 2012 | } |
| 2013 | |
| 2014 | template<typename _ForwardIterator, |
| 2015 | typename _UniformRandomNumberGenerator> |
| 2016 | void |
| 2017 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 2018 | _UniformRandomNumberGenerator& __urng) |
| 2019 | { this->__generate(__f, __t, __urng, _M_param); } |
| 2020 | |
| 2021 | template<typename _ForwardIterator, |
| 2022 | typename _UniformRandomNumberGenerator> |
| 2023 | void |
| 2024 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 2025 | _UniformRandomNumberGenerator& __urng, |
| 2026 | const param_type& __p) |
| 2027 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 2028 | |
| 2029 | template<typename _UniformRandomNumberGenerator> |
| 2030 | void |
| 2031 | __generate(result_type* __f, result_type* __t, |
| 2032 | _UniformRandomNumberGenerator& __urng, |
| 2033 | const param_type& __p) |
| 2034 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 2035 | |
| 2036 | /** |
| 2037 | * @brief Return true if two uniform real distributions have |
| 2038 | * the same parameters. |
| 2039 | */ |
| 2040 | friend bool |
| 2041 | operator==(const uniform_real_distribution& __d1, |
| 2042 | const uniform_real_distribution& __d2) |
| 2043 | { return __d1._M_param == __d2._M_param; } |
| 2044 | |
| 2045 | private: |
| 2046 | template<typename _ForwardIterator, |
| 2047 | typename _UniformRandomNumberGenerator> |
| 2048 | void |
| 2049 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
| 2050 | _UniformRandomNumberGenerator& __urng, |
| 2051 | const param_type& __p); |
| 2052 | |
| 2053 | param_type _M_param; |
| 2054 | }; |
| 2055 | |
| 2056 | #if __cpp_impl_three_way_comparison < 201907L |
| 2057 | /** |
| 2058 | * @brief Return true if two uniform real distributions have |
| 2059 | * different parameters. |
| 2060 | */ |
| 2061 | template<typename _IntType> |
| 2062 | inline bool |
| 2063 | operator!=(const std::uniform_real_distribution<_IntType>& __d1, |
| 2064 | const std::uniform_real_distribution<_IntType>& __d2) |
| 2065 | { return !(__d1 == __d2); } |
| 2066 | #endif |
| 2067 | |
| 2068 | /** |
| 2069 | * @brief Inserts a %uniform_real_distribution random number |
| 2070 | * distribution @p __x into the output stream @p __os. |
| 2071 | * |
| 2072 | * @param __os An output stream. |
| 2073 | * @param __x A %uniform_real_distribution random number distribution. |
| 2074 | * |
| 2075 | * @returns The output stream with the state of @p __x inserted or in |
| 2076 | * an error state. |
| 2077 | */ |
| 2078 | template<typename _RealType, typename _CharT, typename _Traits> |
| 2079 | std::basic_ostream<_CharT, _Traits>& |
| 2080 | operator<<(std::basic_ostream<_CharT, _Traits>&, |
| 2081 | const std::uniform_real_distribution<_RealType>&); |
| 2082 | |
| 2083 | /** |
| 2084 | * @brief Extracts a %uniform_real_distribution random number distribution |
| 2085 | * @p __x from the input stream @p __is. |
| 2086 | * |
| 2087 | * @param __is An input stream. |
| 2088 | * @param __x A %uniform_real_distribution random number generator engine. |
| 2089 | * |
| 2090 | * @returns The input stream with @p __x extracted or in an error state. |
| 2091 | */ |
| 2092 | template<typename _RealType, typename _CharT, typename _Traits> |
| 2093 | std::basic_istream<_CharT, _Traits>& |
| 2094 | operator>>(std::basic_istream<_CharT, _Traits>&, |
| 2095 | std::uniform_real_distribution<_RealType>&); |
| 2096 | |
| 2097 | /// @} group random_distributions_uniform |
| 2098 | |
| 2099 | /** |
| 2100 | * @addtogroup random_distributions_normal Normal Distributions |
| 2101 | * @ingroup random_distributions |
| 2102 | * @{ |
| 2103 | */ |
| 2104 | |
| 2105 | /** |
| 2106 | * @brief A normal continuous distribution for random numbers. |
| 2107 | * |
| 2108 | * The formula for the normal probability density function is |
| 2109 | * @f[ |
| 2110 | * p(x|\mu,\sigma) = \frac{1}{\sigma \sqrt{2 \pi}} |
| 2111 | * e^{- \frac{{x - \mu}^ {2}}{2 \sigma ^ {2}} } |
| 2112 | * @f] |
| 2113 | * |
| 2114 | * @headerfile random |
| 2115 | * @since C++11 |
| 2116 | */ |
| 2117 | template<typename _RealType = double> |
| 2118 | class normal_distribution |
| 2119 | { |
| 2120 | static_assert(std::is_floating_point<_RealType>::value, |
| 2121 | "result_type must be a floating point type"); |
| 2122 | |
| 2123 | public: |
| 2124 | /** The type of the range of the distribution. */ |
| 2125 | typedef _RealType result_type; |
| 2126 | |
| 2127 | /** Parameter type. */ |
| 2128 | struct param_type |
| 2129 | { |
| 2130 | typedef normal_distribution<_RealType> distribution_type; |
| 2131 | |
| 2132 | param_type() : param_type(0.0) { } |
| 2133 | |
| 2134 | explicit |
| 2135 | param_type(_RealType __mean, _RealType __stddev = _RealType(1)) |
| 2136 | : _M_mean(__mean), _M_stddev(__stddev) |
| 2137 | { |
| 2138 | __glibcxx_assert(_M_stddev > _RealType(0)); |
| 2139 | } |
| 2140 | |
| 2141 | _RealType |
| 2142 | mean() const |
| 2143 | { return _M_mean; } |
| 2144 | |
| 2145 | _RealType |
| 2146 | stddev() const |
| 2147 | { return _M_stddev; } |
| 2148 | |
| 2149 | friend bool |
| 2150 | operator==(const param_type& __p1, const param_type& __p2) |
| 2151 | { return (__p1._M_mean == __p2._M_mean |
| 2152 | && __p1._M_stddev == __p2._M_stddev); } |
| 2153 | |
| 2154 | #if __cpp_impl_three_way_comparison < 201907L |
| 2155 | friend bool |
| 2156 | operator!=(const param_type& __p1, const param_type& __p2) |
| 2157 | { return !(__p1 == __p2); } |
| 2158 | #endif |
| 2159 | |
| 2160 | private: |
| 2161 | _RealType _M_mean; |
| 2162 | _RealType _M_stddev; |
| 2163 | }; |
| 2164 | |
| 2165 | public: |
| 2166 | normal_distribution() : normal_distribution(0.0) { } |
| 2167 | |
| 2168 | /** |
| 2169 | * Constructs a normal distribution with parameters @f$mean@f$ and |
| 2170 | * standard deviation. |
| 2171 | */ |
| 2172 | explicit |
| 2173 | normal_distribution(result_type __mean, |
| 2174 | result_type __stddev = result_type(1)) |
| 2175 | : _M_param(__mean, __stddev) |
| 2176 | { } |
| 2177 | |
| 2178 | explicit |
| 2179 | normal_distribution(const param_type& __p) |
| 2180 | : _M_param(__p) |
| 2181 | { } |
| 2182 | |
| 2183 | /** |
| 2184 | * @brief Resets the distribution state. |
| 2185 | */ |
| 2186 | void |
| 2187 | reset() |
| 2188 | { _M_saved_available = false; } |
| 2189 | |
| 2190 | /** |
| 2191 | * @brief Returns the mean of the distribution. |
| 2192 | */ |
| 2193 | _RealType |
| 2194 | mean() const |
| 2195 | { return _M_param.mean(); } |
| 2196 | |
| 2197 | /** |
| 2198 | * @brief Returns the standard deviation of the distribution. |
| 2199 | */ |
| 2200 | _RealType |
| 2201 | stddev() const |
| 2202 | { return _M_param.stddev(); } |
| 2203 | |
| 2204 | /** |
| 2205 | * @brief Returns the parameter set of the distribution. |
| 2206 | */ |
| 2207 | param_type |
| 2208 | param() const |
| 2209 | { return _M_param; } |
| 2210 | |
| 2211 | /** |
| 2212 | * @brief Sets the parameter set of the distribution. |
| 2213 | * @param __param The new parameter set of the distribution. |
| 2214 | */ |
| 2215 | void |
| 2216 | param(const param_type& __param) |
| 2217 | { _M_param = __param; } |
| 2218 | |
| 2219 | /** |
| 2220 | * @brief Returns the greatest lower bound value of the distribution. |
| 2221 | */ |
| 2222 | result_type |
| 2223 | min() const |
| 2224 | { return std::numeric_limits<result_type>::lowest(); } |
| 2225 | |
| 2226 | /** |
| 2227 | * @brief Returns the least upper bound value of the distribution. |
| 2228 | */ |
| 2229 | result_type |
| 2230 | max() const |
| 2231 | { return std::numeric_limits<result_type>::max(); } |
| 2232 | |
| 2233 | /** |
| 2234 | * @brief Generating functions. |
| 2235 | */ |
| 2236 | template<typename _UniformRandomNumberGenerator> |
| 2237 | result_type |
| 2238 | operator()(_UniformRandomNumberGenerator& __urng) |
| 2239 | { return this->operator()(__urng, _M_param); } |
| 2240 | |
| 2241 | template<typename _UniformRandomNumberGenerator> |
| 2242 | result_type |
| 2243 | operator()(_UniformRandomNumberGenerator& __urng, |
| 2244 | const param_type& __p); |
| 2245 | |
| 2246 | template<typename _ForwardIterator, |
| 2247 | typename _UniformRandomNumberGenerator> |
| 2248 | void |
| 2249 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 2250 | _UniformRandomNumberGenerator& __urng) |
| 2251 | { this->__generate(__f, __t, __urng, _M_param); } |
| 2252 | |
| 2253 | template<typename _ForwardIterator, |
| 2254 | typename _UniformRandomNumberGenerator> |
| 2255 | void |
| 2256 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 2257 | _UniformRandomNumberGenerator& __urng, |
| 2258 | const param_type& __p) |
| 2259 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 2260 | |
| 2261 | template<typename _UniformRandomNumberGenerator> |
| 2262 | void |
| 2263 | __generate(result_type* __f, result_type* __t, |
| 2264 | _UniformRandomNumberGenerator& __urng, |
| 2265 | const param_type& __p) |
| 2266 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 2267 | |
| 2268 | /** |
| 2269 | * @brief Return true if two normal distributions have |
| 2270 | * the same parameters and the sequences that would |
| 2271 | * be generated are equal. |
| 2272 | */ |
| 2273 | template<typename _RealType1> |
| 2274 | friend bool |
| 2275 | operator==(const std::normal_distribution<_RealType1>& __d1, |
| 2276 | const std::normal_distribution<_RealType1>& __d2); |
| 2277 | |
| 2278 | /** |
| 2279 | * @brief Inserts a %normal_distribution random number distribution |
| 2280 | * @p __x into the output stream @p __os. |
| 2281 | * |
| 2282 | * @param __os An output stream. |
| 2283 | * @param __x A %normal_distribution random number distribution. |
| 2284 | * |
| 2285 | * @returns The output stream with the state of @p __x inserted or in |
| 2286 | * an error state. |
| 2287 | */ |
| 2288 | template<typename _RealType1, typename _CharT, typename _Traits> |
| 2289 | friend std::basic_ostream<_CharT, _Traits>& |
| 2290 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 2291 | const std::normal_distribution<_RealType1>& __x); |
| 2292 | |
| 2293 | /** |
| 2294 | * @brief Extracts a %normal_distribution random number distribution |
| 2295 | * @p __x from the input stream @p __is. |
| 2296 | * |
| 2297 | * @param __is An input stream. |
| 2298 | * @param __x A %normal_distribution random number generator engine. |
| 2299 | * |
| 2300 | * @returns The input stream with @p __x extracted or in an error |
| 2301 | * state. |
| 2302 | */ |
| 2303 | template<typename _RealType1, typename _CharT, typename _Traits> |
| 2304 | friend std::basic_istream<_CharT, _Traits>& |
| 2305 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 2306 | std::normal_distribution<_RealType1>& __x); |
| 2307 | |
| 2308 | private: |
| 2309 | template<typename _ForwardIterator, |
| 2310 | typename _UniformRandomNumberGenerator> |
| 2311 | void |
| 2312 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
| 2313 | _UniformRandomNumberGenerator& __urng, |
| 2314 | const param_type& __p); |
| 2315 | |
| 2316 | param_type _M_param; |
| 2317 | result_type _M_saved = 0; |
| 2318 | bool _M_saved_available = false; |
| 2319 | }; |
| 2320 | |
| 2321 | #if __cpp_impl_three_way_comparison < 201907L |
| 2322 | /** |
| 2323 | * @brief Return true if two normal distributions are different. |
| 2324 | */ |
| 2325 | template<typename _RealType> |
| 2326 | inline bool |
| 2327 | operator!=(const std::normal_distribution<_RealType>& __d1, |
| 2328 | const std::normal_distribution<_RealType>& __d2) |
| 2329 | { return !(__d1 == __d2); } |
| 2330 | #endif |
| 2331 | |
| 2332 | /** |
| 2333 | * @brief A lognormal_distribution random number distribution. |
| 2334 | * |
| 2335 | * The formula for the normal probability mass function is |
| 2336 | * @f[ |
| 2337 | * p(x|m,s) = \frac{1}{sx\sqrt{2\pi}} |
| 2338 | * \exp{-\frac{(\ln{x} - m)^2}{2s^2}} |
| 2339 | * @f] |
| 2340 | * |
| 2341 | * @headerfile random |
| 2342 | * @since C++11 |
| 2343 | */ |
| 2344 | template<typename _RealType = double> |
| 2345 | class lognormal_distribution |
| 2346 | { |
| 2347 | static_assert(std::is_floating_point<_RealType>::value, |
| 2348 | "result_type must be a floating point type"); |
| 2349 | |
| 2350 | public: |
| 2351 | /** The type of the range of the distribution. */ |
| 2352 | typedef _RealType result_type; |
| 2353 | |
| 2354 | /** Parameter type. */ |
| 2355 | struct param_type |
| 2356 | { |
| 2357 | typedef lognormal_distribution<_RealType> distribution_type; |
| 2358 | |
| 2359 | param_type() : param_type(0.0) { } |
| 2360 | |
| 2361 | explicit |
| 2362 | param_type(_RealType __m, _RealType __s = _RealType(1)) |
| 2363 | : _M_m(__m), _M_s(__s) |
| 2364 | { } |
| 2365 | |
| 2366 | _RealType |
| 2367 | m() const |
| 2368 | { return _M_m; } |
| 2369 | |
| 2370 | _RealType |
| 2371 | s() const |
| 2372 | { return _M_s; } |
| 2373 | |
| 2374 | friend bool |
| 2375 | operator==(const param_type& __p1, const param_type& __p2) |
| 2376 | { return __p1._M_m == __p2._M_m && __p1._M_s == __p2._M_s; } |
| 2377 | |
| 2378 | #if __cpp_impl_three_way_comparison < 201907L |
| 2379 | friend bool |
| 2380 | operator!=(const param_type& __p1, const param_type& __p2) |
| 2381 | { return !(__p1 == __p2); } |
| 2382 | #endif |
| 2383 | |
| 2384 | private: |
| 2385 | _RealType _M_m; |
| 2386 | _RealType _M_s; |
| 2387 | }; |
| 2388 | |
| 2389 | lognormal_distribution() : lognormal_distribution(0.0) { } |
| 2390 | |
| 2391 | explicit |
| 2392 | lognormal_distribution(_RealType __m, _RealType __s = _RealType(1)) |
| 2393 | : _M_param(__m, __s), _M_nd() |
| 2394 | { } |
| 2395 | |
| 2396 | explicit |
| 2397 | lognormal_distribution(const param_type& __p) |
| 2398 | : _M_param(__p), _M_nd() |
| 2399 | { } |
| 2400 | |
| 2401 | /** |
| 2402 | * Resets the distribution state. |
| 2403 | */ |
| 2404 | void |
| 2405 | reset() |
| 2406 | { _M_nd.reset(); } |
| 2407 | |
| 2408 | /** |
| 2409 | * |
| 2410 | */ |
| 2411 | _RealType |
| 2412 | m() const |
| 2413 | { return _M_param.m(); } |
| 2414 | |
| 2415 | _RealType |
| 2416 | s() const |
| 2417 | { return _M_param.s(); } |
| 2418 | |
| 2419 | /** |
| 2420 | * @brief Returns the parameter set of the distribution. |
| 2421 | */ |
| 2422 | param_type |
| 2423 | param() const |
| 2424 | { return _M_param; } |
| 2425 | |
| 2426 | /** |
| 2427 | * @brief Sets the parameter set of the distribution. |
| 2428 | * @param __param The new parameter set of the distribution. |
| 2429 | */ |
| 2430 | void |
| 2431 | param(const param_type& __param) |
| 2432 | { _M_param = __param; } |
| 2433 | |
| 2434 | /** |
| 2435 | * @brief Returns the greatest lower bound value of the distribution. |
| 2436 | */ |
| 2437 | result_type |
| 2438 | min() const |
| 2439 | { return result_type(0); } |
| 2440 | |
| 2441 | /** |
| 2442 | * @brief Returns the least upper bound value of the distribution. |
| 2443 | */ |
| 2444 | result_type |
| 2445 | max() const |
| 2446 | { return std::numeric_limits<result_type>::max(); } |
| 2447 | |
| 2448 | /** |
| 2449 | * @brief Generating functions. |
| 2450 | */ |
| 2451 | template<typename _UniformRandomNumberGenerator> |
| 2452 | result_type |
| 2453 | operator()(_UniformRandomNumberGenerator& __urng) |
| 2454 | { return this->operator()(__urng, _M_param); } |
| 2455 | |
| 2456 | template<typename _UniformRandomNumberGenerator> |
| 2457 | result_type |
| 2458 | operator()(_UniformRandomNumberGenerator& __urng, |
| 2459 | const param_type& __p) |
| 2460 | { return std::exp(__p.s() * _M_nd(__urng) + __p.m()); } |
| 2461 | |
| 2462 | template<typename _ForwardIterator, |
| 2463 | typename _UniformRandomNumberGenerator> |
| 2464 | void |
| 2465 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 2466 | _UniformRandomNumberGenerator& __urng) |
| 2467 | { this->__generate(__f, __t, __urng, _M_param); } |
| 2468 | |
| 2469 | template<typename _ForwardIterator, |
| 2470 | typename _UniformRandomNumberGenerator> |
| 2471 | void |
| 2472 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 2473 | _UniformRandomNumberGenerator& __urng, |
| 2474 | const param_type& __p) |
| 2475 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 2476 | |
| 2477 | template<typename _UniformRandomNumberGenerator> |
| 2478 | void |
| 2479 | __generate(result_type* __f, result_type* __t, |
| 2480 | _UniformRandomNumberGenerator& __urng, |
| 2481 | const param_type& __p) |
| 2482 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 2483 | |
| 2484 | /** |
| 2485 | * @brief Return true if two lognormal distributions have |
| 2486 | * the same parameters and the sequences that would |
| 2487 | * be generated are equal. |
| 2488 | */ |
| 2489 | friend bool |
| 2490 | operator==(const lognormal_distribution& __d1, |
| 2491 | const lognormal_distribution& __d2) |
| 2492 | { return (__d1._M_param == __d2._M_param |
| 2493 | && __d1._M_nd == __d2._M_nd); } |
| 2494 | |
| 2495 | /** |
| 2496 | * @brief Inserts a %lognormal_distribution random number distribution |
| 2497 | * @p __x into the output stream @p __os. |
| 2498 | * |
| 2499 | * @param __os An output stream. |
| 2500 | * @param __x A %lognormal_distribution random number distribution. |
| 2501 | * |
| 2502 | * @returns The output stream with the state of @p __x inserted or in |
| 2503 | * an error state. |
| 2504 | */ |
| 2505 | template<typename _RealType1, typename _CharT, typename _Traits> |
| 2506 | friend std::basic_ostream<_CharT, _Traits>& |
| 2507 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 2508 | const std::lognormal_distribution<_RealType1>& __x); |
| 2509 | |
| 2510 | /** |
| 2511 | * @brief Extracts a %lognormal_distribution random number distribution |
| 2512 | * @p __x from the input stream @p __is. |
| 2513 | * |
| 2514 | * @param __is An input stream. |
| 2515 | * @param __x A %lognormal_distribution random number |
| 2516 | * generator engine. |
| 2517 | * |
| 2518 | * @returns The input stream with @p __x extracted or in an error state. |
| 2519 | */ |
| 2520 | template<typename _RealType1, typename _CharT, typename _Traits> |
| 2521 | friend std::basic_istream<_CharT, _Traits>& |
| 2522 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 2523 | std::lognormal_distribution<_RealType1>& __x); |
| 2524 | |
| 2525 | private: |
| 2526 | template<typename _ForwardIterator, |
| 2527 | typename _UniformRandomNumberGenerator> |
| 2528 | void |
| 2529 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
| 2530 | _UniformRandomNumberGenerator& __urng, |
| 2531 | const param_type& __p); |
| 2532 | |
| 2533 | param_type _M_param; |
| 2534 | |
| 2535 | std::normal_distribution<result_type> _M_nd; |
| 2536 | }; |
| 2537 | |
| 2538 | #if __cpp_impl_three_way_comparison < 201907L |
| 2539 | /** |
| 2540 | * @brief Return true if two lognormal distributions are different. |
| 2541 | */ |
| 2542 | template<typename _RealType> |
| 2543 | inline bool |
| 2544 | operator!=(const std::lognormal_distribution<_RealType>& __d1, |
| 2545 | const std::lognormal_distribution<_RealType>& __d2) |
| 2546 | { return !(__d1 == __d2); } |
| 2547 | #endif |
| 2548 | |
| 2549 | /// @} group random_distributions_normal |
| 2550 | |
| 2551 | /** |
| 2552 | * @addtogroup random_distributions_poisson Poisson Distributions |
| 2553 | * @ingroup random_distributions |
| 2554 | * @{ |
| 2555 | */ |
| 2556 | |
| 2557 | /** |
| 2558 | * @brief A gamma continuous distribution for random numbers. |
| 2559 | * |
| 2560 | * The formula for the gamma probability density function is: |
| 2561 | * @f[ |
| 2562 | * p(x|\alpha,\beta) = \frac{1}{\beta\Gamma(\alpha)} |
| 2563 | * (x/\beta)^{\alpha - 1} e^{-x/\beta} |
| 2564 | * @f] |
| 2565 | * |
| 2566 | * @headerfile random |
| 2567 | * @since C++11 |
| 2568 | */ |
| 2569 | template<typename _RealType = double> |
| 2570 | class gamma_distribution |
| 2571 | { |
| 2572 | static_assert(std::is_floating_point<_RealType>::value, |
| 2573 | "result_type must be a floating point type"); |
| 2574 | |
| 2575 | public: |
| 2576 | /** The type of the range of the distribution. */ |
| 2577 | typedef _RealType result_type; |
| 2578 | |
| 2579 | /** Parameter type. */ |
| 2580 | struct param_type |
| 2581 | { |
| 2582 | typedef gamma_distribution<_RealType> distribution_type; |
| 2583 | friend class gamma_distribution<_RealType>; |
| 2584 | |
| 2585 | param_type() : param_type(1.0) { } |
| 2586 | |
| 2587 | explicit |
| 2588 | param_type(_RealType __alpha_val, _RealType __beta_val = _RealType(1)) |
| 2589 | : _M_alpha(__alpha_val), _M_beta(__beta_val) |
| 2590 | { |
| 2591 | __glibcxx_assert(_M_alpha > _RealType(0)); |
| 2592 | _M_initialize(); |
| 2593 | } |
| 2594 | |
| 2595 | _RealType |
| 2596 | alpha() const |
| 2597 | { return _M_alpha; } |
| 2598 | |
| 2599 | _RealType |
| 2600 | beta() const |
| 2601 | { return _M_beta; } |
| 2602 | |
| 2603 | friend bool |
| 2604 | operator==(const param_type& __p1, const param_type& __p2) |
| 2605 | { return (__p1._M_alpha == __p2._M_alpha |
| 2606 | && __p1._M_beta == __p2._M_beta); } |
| 2607 | |
| 2608 | #if __cpp_impl_three_way_comparison < 201907L |
| 2609 | friend bool |
| 2610 | operator!=(const param_type& __p1, const param_type& __p2) |
| 2611 | { return !(__p1 == __p2); } |
| 2612 | #endif |
| 2613 | |
| 2614 | private: |
| 2615 | void |
| 2616 | _M_initialize(); |
| 2617 | |
| 2618 | _RealType _M_alpha; |
| 2619 | _RealType _M_beta; |
| 2620 | |
| 2621 | _RealType _M_malpha, _M_a2; |
| 2622 | }; |
| 2623 | |
| 2624 | public: |
| 2625 | /** |
| 2626 | * @brief Constructs a gamma distribution with parameters 1 and 1. |
| 2627 | */ |
| 2628 | gamma_distribution() : gamma_distribution(1.0) { } |
| 2629 | |
| 2630 | /** |
| 2631 | * @brief Constructs a gamma distribution with parameters |
| 2632 | * @f$\alpha@f$ and @f$\beta@f$. |
| 2633 | */ |
| 2634 | explicit |
| 2635 | gamma_distribution(_RealType __alpha_val, |
| 2636 | _RealType __beta_val = _RealType(1)) |
| 2637 | : _M_param(__alpha_val, __beta_val), _M_nd() |
| 2638 | { } |
| 2639 | |
| 2640 | explicit |
| 2641 | gamma_distribution(const param_type& __p) |
| 2642 | : _M_param(__p), _M_nd() |
| 2643 | { } |
| 2644 | |
| 2645 | /** |
| 2646 | * @brief Resets the distribution state. |
| 2647 | */ |
| 2648 | void |
| 2649 | reset() |
| 2650 | { _M_nd.reset(); } |
| 2651 | |
| 2652 | /** |
| 2653 | * @brief Returns the @f$\alpha@f$ of the distribution. |
| 2654 | */ |
| 2655 | _RealType |
| 2656 | alpha() const |
| 2657 | { return _M_param.alpha(); } |
| 2658 | |
| 2659 | /** |
| 2660 | * @brief Returns the @f$\beta@f$ of the distribution. |
| 2661 | */ |
| 2662 | _RealType |
| 2663 | beta() const |
| 2664 | { return _M_param.beta(); } |
| 2665 | |
| 2666 | /** |
| 2667 | * @brief Returns the parameter set of the distribution. |
| 2668 | */ |
| 2669 | param_type |
| 2670 | param() const |
| 2671 | { return _M_param; } |
| 2672 | |
| 2673 | /** |
| 2674 | * @brief Sets the parameter set of the distribution. |
| 2675 | * @param __param The new parameter set of the distribution. |
| 2676 | */ |
| 2677 | void |
| 2678 | param(const param_type& __param) |
| 2679 | { _M_param = __param; } |
| 2680 | |
| 2681 | /** |
| 2682 | * @brief Returns the greatest lower bound value of the distribution. |
| 2683 | */ |
| 2684 | result_type |
| 2685 | min() const |
| 2686 | { return result_type(0); } |
| 2687 | |
| 2688 | /** |
| 2689 | * @brief Returns the least upper bound value of the distribution. |
| 2690 | */ |
| 2691 | result_type |
| 2692 | max() const |
| 2693 | { return std::numeric_limits<result_type>::max(); } |
| 2694 | |
| 2695 | /** |
| 2696 | * @brief Generating functions. |
| 2697 | */ |
| 2698 | template<typename _UniformRandomNumberGenerator> |
| 2699 | result_type |
| 2700 | operator()(_UniformRandomNumberGenerator& __urng) |
| 2701 | { return this->operator()(__urng, _M_param); } |
| 2702 | |
| 2703 | template<typename _UniformRandomNumberGenerator> |
| 2704 | result_type |
| 2705 | operator()(_UniformRandomNumberGenerator& __urng, |
| 2706 | const param_type& __p); |
| 2707 | |
| 2708 | template<typename _ForwardIterator, |
| 2709 | typename _UniformRandomNumberGenerator> |
| 2710 | void |
| 2711 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 2712 | _UniformRandomNumberGenerator& __urng) |
| 2713 | { this->__generate(__f, __t, __urng, _M_param); } |
| 2714 | |
| 2715 | template<typename _ForwardIterator, |
| 2716 | typename _UniformRandomNumberGenerator> |
| 2717 | void |
| 2718 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 2719 | _UniformRandomNumberGenerator& __urng, |
| 2720 | const param_type& __p) |
| 2721 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 2722 | |
| 2723 | template<typename _UniformRandomNumberGenerator> |
| 2724 | void |
| 2725 | __generate(result_type* __f, result_type* __t, |
| 2726 | _UniformRandomNumberGenerator& __urng, |
| 2727 | const param_type& __p) |
| 2728 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 2729 | |
| 2730 | /** |
| 2731 | * @brief Return true if two gamma distributions have the same |
| 2732 | * parameters and the sequences that would be generated |
| 2733 | * are equal. |
| 2734 | */ |
| 2735 | friend bool |
| 2736 | operator==(const gamma_distribution& __d1, |
| 2737 | const gamma_distribution& __d2) |
| 2738 | { return (__d1._M_param == __d2._M_param |
| 2739 | && __d1._M_nd == __d2._M_nd); } |
| 2740 | |
| 2741 | /** |
| 2742 | * @brief Inserts a %gamma_distribution random number distribution |
| 2743 | * @p __x into the output stream @p __os. |
| 2744 | * |
| 2745 | * @param __os An output stream. |
| 2746 | * @param __x A %gamma_distribution random number distribution. |
| 2747 | * |
| 2748 | * @returns The output stream with the state of @p __x inserted or in |
| 2749 | * an error state. |
| 2750 | */ |
| 2751 | template<typename _RealType1, typename _CharT, typename _Traits> |
| 2752 | friend std::basic_ostream<_CharT, _Traits>& |
| 2753 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 2754 | const std::gamma_distribution<_RealType1>& __x); |
| 2755 | |
| 2756 | /** |
| 2757 | * @brief Extracts a %gamma_distribution random number distribution |
| 2758 | * @p __x from the input stream @p __is. |
| 2759 | * |
| 2760 | * @param __is An input stream. |
| 2761 | * @param __x A %gamma_distribution random number generator engine. |
| 2762 | * |
| 2763 | * @returns The input stream with @p __x extracted or in an error state. |
| 2764 | */ |
| 2765 | template<typename _RealType1, typename _CharT, typename _Traits> |
| 2766 | friend std::basic_istream<_CharT, _Traits>& |
| 2767 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 2768 | std::gamma_distribution<_RealType1>& __x); |
| 2769 | |
| 2770 | private: |
| 2771 | template<typename _ForwardIterator, |
| 2772 | typename _UniformRandomNumberGenerator> |
| 2773 | void |
| 2774 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
| 2775 | _UniformRandomNumberGenerator& __urng, |
| 2776 | const param_type& __p); |
| 2777 | |
| 2778 | param_type _M_param; |
| 2779 | |
| 2780 | std::normal_distribution<result_type> _M_nd; |
| 2781 | }; |
| 2782 | |
| 2783 | #if __cpp_impl_three_way_comparison < 201907L |
| 2784 | /** |
| 2785 | * @brief Return true if two gamma distributions are different. |
| 2786 | */ |
| 2787 | template<typename _RealType> |
| 2788 | inline bool |
| 2789 | operator!=(const std::gamma_distribution<_RealType>& __d1, |
| 2790 | const std::gamma_distribution<_RealType>& __d2) |
| 2791 | { return !(__d1 == __d2); } |
| 2792 | #endif |
| 2793 | |
| 2794 | /// @} group random_distributions_poisson |
| 2795 | |
| 2796 | /** |
| 2797 | * @addtogroup random_distributions_normal Normal Distributions |
| 2798 | * @ingroup random_distributions |
| 2799 | * @{ |
| 2800 | */ |
| 2801 | |
| 2802 | /** |
| 2803 | * @brief A chi_squared_distribution random number distribution. |
| 2804 | * |
| 2805 | * The formula for the normal probability mass function is |
| 2806 | * @f$p(x|n) = \frac{x^{(n/2) - 1}e^{-x/2}}{\Gamma(n/2) 2^{n/2}}@f$ |
| 2807 | * |
| 2808 | * @headerfile random |
| 2809 | * @since C++11 |
| 2810 | */ |
| 2811 | template<typename _RealType = double> |
| 2812 | class chi_squared_distribution |
| 2813 | { |
| 2814 | static_assert(std::is_floating_point<_RealType>::value, |
| 2815 | "result_type must be a floating point type"); |
| 2816 | |
| 2817 | public: |
| 2818 | /** The type of the range of the distribution. */ |
| 2819 | typedef _RealType result_type; |
| 2820 | |
| 2821 | /** Parameter type. */ |
| 2822 | struct param_type |
| 2823 | { |
| 2824 | typedef chi_squared_distribution<_RealType> distribution_type; |
| 2825 | |
| 2826 | param_type() : param_type(1) { } |
| 2827 | |
| 2828 | explicit |
| 2829 | param_type(_RealType __n) |
| 2830 | : _M_n(__n) |
| 2831 | { } |
| 2832 | |
| 2833 | _RealType |
| 2834 | n() const |
| 2835 | { return _M_n; } |
| 2836 | |
| 2837 | friend bool |
| 2838 | operator==(const param_type& __p1, const param_type& __p2) |
| 2839 | { return __p1._M_n == __p2._M_n; } |
| 2840 | |
| 2841 | #if __cpp_impl_three_way_comparison < 201907L |
| 2842 | friend bool |
| 2843 | operator!=(const param_type& __p1, const param_type& __p2) |
| 2844 | { return !(__p1 == __p2); } |
| 2845 | #endif |
| 2846 | |
| 2847 | private: |
| 2848 | _RealType _M_n; |
| 2849 | }; |
| 2850 | |
| 2851 | chi_squared_distribution() : chi_squared_distribution(1) { } |
| 2852 | |
| 2853 | explicit |
| 2854 | chi_squared_distribution(_RealType __n) |
| 2855 | : _M_param(__n), _M_gd(__n / 2) |
| 2856 | { } |
| 2857 | |
| 2858 | explicit |
| 2859 | chi_squared_distribution(const param_type& __p) |
| 2860 | : _M_param(__p), _M_gd(__p.n() / 2) |
| 2861 | { } |
| 2862 | |
| 2863 | /** |
| 2864 | * @brief Resets the distribution state. |
| 2865 | */ |
| 2866 | void |
| 2867 | reset() |
| 2868 | { _M_gd.reset(); } |
| 2869 | |
| 2870 | /** |
| 2871 | * |
| 2872 | */ |
| 2873 | _RealType |
| 2874 | n() const |
| 2875 | { return _M_param.n(); } |
| 2876 | |
| 2877 | /** |
| 2878 | * @brief Returns the parameter set of the distribution. |
| 2879 | */ |
| 2880 | param_type |
| 2881 | param() const |
| 2882 | { return _M_param; } |
| 2883 | |
| 2884 | /** |
| 2885 | * @brief Sets the parameter set of the distribution. |
| 2886 | * @param __param The new parameter set of the distribution. |
| 2887 | */ |
| 2888 | void |
| 2889 | param(const param_type& __param) |
| 2890 | { |
| 2891 | _M_param = __param; |
| 2892 | typedef typename std::gamma_distribution<result_type>::param_type |
| 2893 | param_type; |
| 2894 | _M_gd.param(param_type{__param.n() / 2}); |
| 2895 | } |
| 2896 | |
| 2897 | /** |
| 2898 | * @brief Returns the greatest lower bound value of the distribution. |
| 2899 | */ |
| 2900 | result_type |
| 2901 | min() const |
| 2902 | { return result_type(0); } |
| 2903 | |
| 2904 | /** |
| 2905 | * @brief Returns the least upper bound value of the distribution. |
| 2906 | */ |
| 2907 | result_type |
| 2908 | max() const |
| 2909 | { return std::numeric_limits<result_type>::max(); } |
| 2910 | |
| 2911 | /** |
| 2912 | * @brief Generating functions. |
| 2913 | */ |
| 2914 | template<typename _UniformRandomNumberGenerator> |
| 2915 | result_type |
| 2916 | operator()(_UniformRandomNumberGenerator& __urng) |
| 2917 | { return 2 * _M_gd(__urng); } |
| 2918 | |
| 2919 | template<typename _UniformRandomNumberGenerator> |
| 2920 | result_type |
| 2921 | operator()(_UniformRandomNumberGenerator& __urng, |
| 2922 | const param_type& __p) |
| 2923 | { |
| 2924 | typedef typename std::gamma_distribution<result_type>::param_type |
| 2925 | param_type; |
| 2926 | return 2 * _M_gd(__urng, param_type(__p.n() / 2)); |
| 2927 | } |
| 2928 | |
| 2929 | template<typename _ForwardIterator, |
| 2930 | typename _UniformRandomNumberGenerator> |
| 2931 | void |
| 2932 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 2933 | _UniformRandomNumberGenerator& __urng) |
| 2934 | { this->__generate_impl(__f, __t, __urng); } |
| 2935 | |
| 2936 | template<typename _ForwardIterator, |
| 2937 | typename _UniformRandomNumberGenerator> |
| 2938 | void |
| 2939 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 2940 | _UniformRandomNumberGenerator& __urng, |
| 2941 | const param_type& __p) |
| 2942 | { typename std::gamma_distribution<result_type>::param_type |
| 2943 | __p2(__p.n() / 2); |
| 2944 | this->__generate_impl(__f, __t, __urng, __p2); } |
| 2945 | |
| 2946 | template<typename _UniformRandomNumberGenerator> |
| 2947 | void |
| 2948 | __generate(result_type* __f, result_type* __t, |
| 2949 | _UniformRandomNumberGenerator& __urng) |
| 2950 | { this->__generate_impl(__f, __t, __urng); } |
| 2951 | |
| 2952 | template<typename _UniformRandomNumberGenerator> |
| 2953 | void |
| 2954 | __generate(result_type* __f, result_type* __t, |
| 2955 | _UniformRandomNumberGenerator& __urng, |
| 2956 | const param_type& __p) |
| 2957 | { typename std::gamma_distribution<result_type>::param_type |
| 2958 | __p2(__p.n() / 2); |
| 2959 | this->__generate_impl(__f, __t, __urng, __p2); } |
| 2960 | |
| 2961 | /** |
| 2962 | * @brief Return true if two Chi-squared distributions have |
| 2963 | * the same parameters and the sequences that would be |
| 2964 | * generated are equal. |
| 2965 | */ |
| 2966 | friend bool |
| 2967 | operator==(const chi_squared_distribution& __d1, |
| 2968 | const chi_squared_distribution& __d2) |
| 2969 | { return __d1._M_param == __d2._M_param && __d1._M_gd == __d2._M_gd; } |
| 2970 | |
| 2971 | /** |
| 2972 | * @brief Inserts a %chi_squared_distribution random number distribution |
| 2973 | * @p __x into the output stream @p __os. |
| 2974 | * |
| 2975 | * @param __os An output stream. |
| 2976 | * @param __x A %chi_squared_distribution random number distribution. |
| 2977 | * |
| 2978 | * @returns The output stream with the state of @p __x inserted or in |
| 2979 | * an error state. |
| 2980 | */ |
| 2981 | template<typename _RealType1, typename _CharT, typename _Traits> |
| 2982 | friend std::basic_ostream<_CharT, _Traits>& |
| 2983 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 2984 | const std::chi_squared_distribution<_RealType1>& __x); |
| 2985 | |
| 2986 | /** |
| 2987 | * @brief Extracts a %chi_squared_distribution random number distribution |
| 2988 | * @p __x from the input stream @p __is. |
| 2989 | * |
| 2990 | * @param __is An input stream. |
| 2991 | * @param __x A %chi_squared_distribution random number |
| 2992 | * generator engine. |
| 2993 | * |
| 2994 | * @returns The input stream with @p __x extracted or in an error state. |
| 2995 | */ |
| 2996 | template<typename _RealType1, typename _CharT, typename _Traits> |
| 2997 | friend std::basic_istream<_CharT, _Traits>& |
| 2998 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 2999 | std::chi_squared_distribution<_RealType1>& __x); |
| 3000 | |
| 3001 | private: |
| 3002 | template<typename _ForwardIterator, |
| 3003 | typename _UniformRandomNumberGenerator> |
| 3004 | void |
| 3005 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
| 3006 | _UniformRandomNumberGenerator& __urng); |
| 3007 | |
| 3008 | template<typename _ForwardIterator, |
| 3009 | typename _UniformRandomNumberGenerator> |
| 3010 | void |
| 3011 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
| 3012 | _UniformRandomNumberGenerator& __urng, |
| 3013 | const typename |
| 3014 | std::gamma_distribution<result_type>::param_type& __p); |
| 3015 | |
| 3016 | param_type _M_param; |
| 3017 | |
| 3018 | std::gamma_distribution<result_type> _M_gd; |
| 3019 | }; |
| 3020 | |
| 3021 | #if __cpp_impl_three_way_comparison < 201907L |
| 3022 | /** |
| 3023 | * @brief Return true if two Chi-squared distributions are different. |
| 3024 | */ |
| 3025 | template<typename _RealType> |
| 3026 | inline bool |
| 3027 | operator!=(const std::chi_squared_distribution<_RealType>& __d1, |
| 3028 | const std::chi_squared_distribution<_RealType>& __d2) |
| 3029 | { return !(__d1 == __d2); } |
| 3030 | #endif |
| 3031 | |
| 3032 | /** |
| 3033 | * @brief A cauchy_distribution random number distribution. |
| 3034 | * |
| 3035 | * The formula for the normal probability mass function is |
| 3036 | * @f$p(x|a,b) = (\pi b (1 + (\frac{x-a}{b})^2))^{-1}@f$ |
| 3037 | * |
| 3038 | * @headerfile random |
| 3039 | * @since C++11 |
| 3040 | */ |
| 3041 | template<typename _RealType = double> |
| 3042 | class cauchy_distribution |
| 3043 | { |
| 3044 | static_assert(std::is_floating_point<_RealType>::value, |
| 3045 | "result_type must be a floating point type"); |
| 3046 | |
| 3047 | public: |
| 3048 | /** The type of the range of the distribution. */ |
| 3049 | typedef _RealType result_type; |
| 3050 | |
| 3051 | /** Parameter type. */ |
| 3052 | struct param_type |
| 3053 | { |
| 3054 | typedef cauchy_distribution<_RealType> distribution_type; |
| 3055 | |
| 3056 | param_type() : param_type(0) { } |
| 3057 | |
| 3058 | explicit |
| 3059 | param_type(_RealType __a, _RealType __b = _RealType(1)) |
| 3060 | : _M_a(__a), _M_b(__b) |
| 3061 | { } |
| 3062 | |
| 3063 | _RealType |
| 3064 | a() const |
| 3065 | { return _M_a; } |
| 3066 | |
| 3067 | _RealType |
| 3068 | b() const |
| 3069 | { return _M_b; } |
| 3070 | |
| 3071 | friend bool |
| 3072 | operator==(const param_type& __p1, const param_type& __p2) |
| 3073 | { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; } |
| 3074 | |
| 3075 | #if __cpp_impl_three_way_comparison < 201907L |
| 3076 | friend bool |
| 3077 | operator!=(const param_type& __p1, const param_type& __p2) |
| 3078 | { return !(__p1 == __p2); } |
| 3079 | #endif |
| 3080 | |
| 3081 | private: |
| 3082 | _RealType _M_a; |
| 3083 | _RealType _M_b; |
| 3084 | }; |
| 3085 | |
| 3086 | cauchy_distribution() : cauchy_distribution(0.0) { } |
| 3087 | |
| 3088 | explicit |
| 3089 | cauchy_distribution(_RealType __a, _RealType __b = 1.0) |
| 3090 | : _M_param(__a, __b) |
| 3091 | { } |
| 3092 | |
| 3093 | explicit |
| 3094 | cauchy_distribution(const param_type& __p) |
| 3095 | : _M_param(__p) |
| 3096 | { } |
| 3097 | |
| 3098 | /** |
| 3099 | * @brief Resets the distribution state. |
| 3100 | */ |
| 3101 | void |
| 3102 | reset() |
| 3103 | { } |
| 3104 | |
| 3105 | /** |
| 3106 | * |
| 3107 | */ |
| 3108 | _RealType |
| 3109 | a() const |
| 3110 | { return _M_param.a(); } |
| 3111 | |
| 3112 | _RealType |
| 3113 | b() const |
| 3114 | { return _M_param.b(); } |
| 3115 | |
| 3116 | /** |
| 3117 | * @brief Returns the parameter set of the distribution. |
| 3118 | */ |
| 3119 | param_type |
| 3120 | param() const |
| 3121 | { return _M_param; } |
| 3122 | |
| 3123 | /** |
| 3124 | * @brief Sets the parameter set of the distribution. |
| 3125 | * @param __param The new parameter set of the distribution. |
| 3126 | */ |
| 3127 | void |
| 3128 | param(const param_type& __param) |
| 3129 | { _M_param = __param; } |
| 3130 | |
| 3131 | /** |
| 3132 | * @brief Returns the greatest lower bound value of the distribution. |
| 3133 | */ |
| 3134 | result_type |
| 3135 | min() const |
| 3136 | { return std::numeric_limits<result_type>::lowest(); } |
| 3137 | |
| 3138 | /** |
| 3139 | * @brief Returns the least upper bound value of the distribution. |
| 3140 | */ |
| 3141 | result_type |
| 3142 | max() const |
| 3143 | { return std::numeric_limits<result_type>::max(); } |
| 3144 | |
| 3145 | /** |
| 3146 | * @brief Generating functions. |
| 3147 | */ |
| 3148 | template<typename _UniformRandomNumberGenerator> |
| 3149 | result_type |
| 3150 | operator()(_UniformRandomNumberGenerator& __urng) |
| 3151 | { return this->operator()(__urng, _M_param); } |
| 3152 | |
| 3153 | template<typename _UniformRandomNumberGenerator> |
| 3154 | result_type |
| 3155 | operator()(_UniformRandomNumberGenerator& __urng, |
| 3156 | const param_type& __p); |
| 3157 | |
| 3158 | template<typename _ForwardIterator, |
| 3159 | typename _UniformRandomNumberGenerator> |
| 3160 | void |
| 3161 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 3162 | _UniformRandomNumberGenerator& __urng) |
| 3163 | { this->__generate(__f, __t, __urng, _M_param); } |
| 3164 | |
| 3165 | template<typename _ForwardIterator, |
| 3166 | typename _UniformRandomNumberGenerator> |
| 3167 | void |
| 3168 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 3169 | _UniformRandomNumberGenerator& __urng, |
| 3170 | const param_type& __p) |
| 3171 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 3172 | |
| 3173 | template<typename _UniformRandomNumberGenerator> |
| 3174 | void |
| 3175 | __generate(result_type* __f, result_type* __t, |
| 3176 | _UniformRandomNumberGenerator& __urng, |
| 3177 | const param_type& __p) |
| 3178 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 3179 | |
| 3180 | /** |
| 3181 | * @brief Return true if two Cauchy distributions have |
| 3182 | * the same parameters. |
| 3183 | */ |
| 3184 | friend bool |
| 3185 | operator==(const cauchy_distribution& __d1, |
| 3186 | const cauchy_distribution& __d2) |
| 3187 | { return __d1._M_param == __d2._M_param; } |
| 3188 | |
| 3189 | private: |
| 3190 | template<typename _ForwardIterator, |
| 3191 | typename _UniformRandomNumberGenerator> |
| 3192 | void |
| 3193 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
| 3194 | _UniformRandomNumberGenerator& __urng, |
| 3195 | const param_type& __p); |
| 3196 | |
| 3197 | param_type _M_param; |
| 3198 | }; |
| 3199 | |
| 3200 | #if __cpp_impl_three_way_comparison < 201907L |
| 3201 | /** |
| 3202 | * @brief Return true if two Cauchy distributions have |
| 3203 | * different parameters. |
| 3204 | */ |
| 3205 | template<typename _RealType> |
| 3206 | inline bool |
| 3207 | operator!=(const std::cauchy_distribution<_RealType>& __d1, |
| 3208 | const std::cauchy_distribution<_RealType>& __d2) |
| 3209 | { return !(__d1 == __d2); } |
| 3210 | #endif |
| 3211 | |
| 3212 | /** |
| 3213 | * @brief Inserts a %cauchy_distribution random number distribution |
| 3214 | * @p __x into the output stream @p __os. |
| 3215 | * |
| 3216 | * @param __os An output stream. |
| 3217 | * @param __x A %cauchy_distribution random number distribution. |
| 3218 | * |
| 3219 | * @returns The output stream with the state of @p __x inserted or in |
| 3220 | * an error state. |
| 3221 | */ |
| 3222 | template<typename _RealType, typename _CharT, typename _Traits> |
| 3223 | std::basic_ostream<_CharT, _Traits>& |
| 3224 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 3225 | const std::cauchy_distribution<_RealType>& __x); |
| 3226 | |
| 3227 | /** |
| 3228 | * @brief Extracts a %cauchy_distribution random number distribution |
| 3229 | * @p __x from the input stream @p __is. |
| 3230 | * |
| 3231 | * @param __is An input stream. |
| 3232 | * @param __x A %cauchy_distribution random number |
| 3233 | * generator engine. |
| 3234 | * |
| 3235 | * @returns The input stream with @p __x extracted or in an error state. |
| 3236 | */ |
| 3237 | template<typename _RealType, typename _CharT, typename _Traits> |
| 3238 | std::basic_istream<_CharT, _Traits>& |
| 3239 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 3240 | std::cauchy_distribution<_RealType>& __x); |
| 3241 | |
| 3242 | |
| 3243 | /** |
| 3244 | * @brief A fisher_f_distribution random number distribution. |
| 3245 | * |
| 3246 | * The formula for the normal probability mass function is |
| 3247 | * @f[ |
| 3248 | * p(x|m,n) = \frac{\Gamma((m+n)/2)}{\Gamma(m/2)\Gamma(n/2)} |
| 3249 | * (\frac{m}{n})^{m/2} x^{(m/2)-1} |
| 3250 | * (1 + \frac{mx}{n})^{-(m+n)/2} |
| 3251 | * @f] |
| 3252 | * |
| 3253 | * @headerfile random |
| 3254 | * @since C++11 |
| 3255 | */ |
| 3256 | template<typename _RealType = double> |
| 3257 | class fisher_f_distribution |
| 3258 | { |
| 3259 | static_assert(std::is_floating_point<_RealType>::value, |
| 3260 | "result_type must be a floating point type"); |
| 3261 | |
| 3262 | public: |
| 3263 | /** The type of the range of the distribution. */ |
| 3264 | typedef _RealType result_type; |
| 3265 | |
| 3266 | /** Parameter type. */ |
| 3267 | struct param_type |
| 3268 | { |
| 3269 | typedef fisher_f_distribution<_RealType> distribution_type; |
| 3270 | |
| 3271 | param_type() : param_type(1) { } |
| 3272 | |
| 3273 | explicit |
| 3274 | param_type(_RealType __m, _RealType __n = _RealType(1)) |
| 3275 | : _M_m(__m), _M_n(__n) |
| 3276 | { } |
| 3277 | |
| 3278 | _RealType |
| 3279 | m() const |
| 3280 | { return _M_m; } |
| 3281 | |
| 3282 | _RealType |
| 3283 | n() const |
| 3284 | { return _M_n; } |
| 3285 | |
| 3286 | friend bool |
| 3287 | operator==(const param_type& __p1, const param_type& __p2) |
| 3288 | { return __p1._M_m == __p2._M_m && __p1._M_n == __p2._M_n; } |
| 3289 | |
| 3290 | #if __cpp_impl_three_way_comparison < 201907L |
| 3291 | friend bool |
| 3292 | operator!=(const param_type& __p1, const param_type& __p2) |
| 3293 | { return !(__p1 == __p2); } |
| 3294 | #endif |
| 3295 | |
| 3296 | private: |
| 3297 | _RealType _M_m; |
| 3298 | _RealType _M_n; |
| 3299 | }; |
| 3300 | |
| 3301 | fisher_f_distribution() : fisher_f_distribution(1.0) { } |
| 3302 | |
| 3303 | explicit |
| 3304 | fisher_f_distribution(_RealType __m, |
| 3305 | _RealType __n = _RealType(1)) |
| 3306 | : _M_param(__m, __n), _M_gd_x(__m / 2), _M_gd_y(__n / 2) |
| 3307 | { } |
| 3308 | |
| 3309 | explicit |
| 3310 | fisher_f_distribution(const param_type& __p) |
| 3311 | : _M_param(__p), _M_gd_x(__p.m() / 2), _M_gd_y(__p.n() / 2) |
| 3312 | { } |
| 3313 | |
| 3314 | /** |
| 3315 | * @brief Resets the distribution state. |
| 3316 | */ |
| 3317 | void |
| 3318 | reset() |
| 3319 | { |
| 3320 | _M_gd_x.reset(); |
| 3321 | _M_gd_y.reset(); |
| 3322 | } |
| 3323 | |
| 3324 | /** |
| 3325 | * |
| 3326 | */ |
| 3327 | _RealType |
| 3328 | m() const |
| 3329 | { return _M_param.m(); } |
| 3330 | |
| 3331 | _RealType |
| 3332 | n() const |
| 3333 | { return _M_param.n(); } |
| 3334 | |
| 3335 | /** |
| 3336 | * @brief Returns the parameter set of the distribution. |
| 3337 | */ |
| 3338 | param_type |
| 3339 | param() const |
| 3340 | { return _M_param; } |
| 3341 | |
| 3342 | /** |
| 3343 | * @brief Sets the parameter set of the distribution. |
| 3344 | * @param __param The new parameter set of the distribution. |
| 3345 | */ |
| 3346 | void |
| 3347 | param(const param_type& __param) |
| 3348 | { _M_param = __param; } |
| 3349 | |
| 3350 | /** |
| 3351 | * @brief Returns the greatest lower bound value of the distribution. |
| 3352 | */ |
| 3353 | result_type |
| 3354 | min() const |
| 3355 | { return result_type(0); } |
| 3356 | |
| 3357 | /** |
| 3358 | * @brief Returns the least upper bound value of the distribution. |
| 3359 | */ |
| 3360 | result_type |
| 3361 | max() const |
| 3362 | { return std::numeric_limits<result_type>::max(); } |
| 3363 | |
| 3364 | /** |
| 3365 | * @brief Generating functions. |
| 3366 | */ |
| 3367 | template<typename _UniformRandomNumberGenerator> |
| 3368 | result_type |
| 3369 | operator()(_UniformRandomNumberGenerator& __urng) |
| 3370 | { return (_M_gd_x(__urng) * n()) / (_M_gd_y(__urng) * m()); } |
| 3371 | |
| 3372 | template<typename _UniformRandomNumberGenerator> |
| 3373 | result_type |
| 3374 | operator()(_UniformRandomNumberGenerator& __urng, |
| 3375 | const param_type& __p) |
| 3376 | { |
| 3377 | typedef typename std::gamma_distribution<result_type>::param_type |
| 3378 | param_type; |
| 3379 | return ((_M_gd_x(__urng, param_type(__p.m() / 2)) * n()) |
| 3380 | / (_M_gd_y(__urng, param_type(__p.n() / 2)) * m())); |
| 3381 | } |
| 3382 | |
| 3383 | template<typename _ForwardIterator, |
| 3384 | typename _UniformRandomNumberGenerator> |
| 3385 | void |
| 3386 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 3387 | _UniformRandomNumberGenerator& __urng) |
| 3388 | { this->__generate_impl(__f, __t, __urng); } |
| 3389 | |
| 3390 | template<typename _ForwardIterator, |
| 3391 | typename _UniformRandomNumberGenerator> |
| 3392 | void |
| 3393 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 3394 | _UniformRandomNumberGenerator& __urng, |
| 3395 | const param_type& __p) |
| 3396 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 3397 | |
| 3398 | template<typename _UniformRandomNumberGenerator> |
| 3399 | void |
| 3400 | __generate(result_type* __f, result_type* __t, |
| 3401 | _UniformRandomNumberGenerator& __urng) |
| 3402 | { this->__generate_impl(__f, __t, __urng); } |
| 3403 | |
| 3404 | template<typename _UniformRandomNumberGenerator> |
| 3405 | void |
| 3406 | __generate(result_type* __f, result_type* __t, |
| 3407 | _UniformRandomNumberGenerator& __urng, |
| 3408 | const param_type& __p) |
| 3409 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 3410 | |
| 3411 | /** |
| 3412 | * @brief Return true if two Fisher f distributions have |
| 3413 | * the same parameters and the sequences that would |
| 3414 | * be generated are equal. |
| 3415 | */ |
| 3416 | friend bool |
| 3417 | operator==(const fisher_f_distribution& __d1, |
| 3418 | const fisher_f_distribution& __d2) |
| 3419 | { return (__d1._M_param == __d2._M_param |
| 3420 | && __d1._M_gd_x == __d2._M_gd_x |
| 3421 | && __d1._M_gd_y == __d2._M_gd_y); } |
| 3422 | |
| 3423 | /** |
| 3424 | * @brief Inserts a %fisher_f_distribution random number distribution |
| 3425 | * @p __x into the output stream @p __os. |
| 3426 | * |
| 3427 | * @param __os An output stream. |
| 3428 | * @param __x A %fisher_f_distribution random number distribution. |
| 3429 | * |
| 3430 | * @returns The output stream with the state of @p __x inserted or in |
| 3431 | * an error state. |
| 3432 | */ |
| 3433 | template<typename _RealType1, typename _CharT, typename _Traits> |
| 3434 | friend std::basic_ostream<_CharT, _Traits>& |
| 3435 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 3436 | const std::fisher_f_distribution<_RealType1>& __x); |
| 3437 | |
| 3438 | /** |
| 3439 | * @brief Extracts a %fisher_f_distribution random number distribution |
| 3440 | * @p __x from the input stream @p __is. |
| 3441 | * |
| 3442 | * @param __is An input stream. |
| 3443 | * @param __x A %fisher_f_distribution random number |
| 3444 | * generator engine. |
| 3445 | * |
| 3446 | * @returns The input stream with @p __x extracted or in an error state. |
| 3447 | */ |
| 3448 | template<typename _RealType1, typename _CharT, typename _Traits> |
| 3449 | friend std::basic_istream<_CharT, _Traits>& |
| 3450 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 3451 | std::fisher_f_distribution<_RealType1>& __x); |
| 3452 | |
| 3453 | private: |
| 3454 | template<typename _ForwardIterator, |
| 3455 | typename _UniformRandomNumberGenerator> |
| 3456 | void |
| 3457 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
| 3458 | _UniformRandomNumberGenerator& __urng); |
| 3459 | |
| 3460 | template<typename _ForwardIterator, |
| 3461 | typename _UniformRandomNumberGenerator> |
| 3462 | void |
| 3463 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
| 3464 | _UniformRandomNumberGenerator& __urng, |
| 3465 | const param_type& __p); |
| 3466 | |
| 3467 | param_type _M_param; |
| 3468 | |
| 3469 | std::gamma_distribution<result_type> _M_gd_x, _M_gd_y; |
| 3470 | }; |
| 3471 | |
| 3472 | #if __cpp_impl_three_way_comparison < 201907L |
| 3473 | /** |
| 3474 | * @brief Return true if two Fisher f distributions are different. |
| 3475 | */ |
| 3476 | template<typename _RealType> |
| 3477 | inline bool |
| 3478 | operator!=(const std::fisher_f_distribution<_RealType>& __d1, |
| 3479 | const std::fisher_f_distribution<_RealType>& __d2) |
| 3480 | { return !(__d1 == __d2); } |
| 3481 | #endif |
| 3482 | |
| 3483 | /** |
| 3484 | * @brief A student_t_distribution random number distribution. |
| 3485 | * |
| 3486 | * The formula for the normal probability mass function is: |
| 3487 | * @f[ |
| 3488 | * p(x|n) = \frac{1}{\sqrt(n\pi)} \frac{\Gamma((n+1)/2)}{\Gamma(n/2)} |
| 3489 | * (1 + \frac{x^2}{n}) ^{-(n+1)/2} |
| 3490 | * @f] |
| 3491 | * |
| 3492 | * @headerfile random |
| 3493 | * @since C++11 |
| 3494 | */ |
| 3495 | template<typename _RealType = double> |
| 3496 | class student_t_distribution |
| 3497 | { |
| 3498 | static_assert(std::is_floating_point<_RealType>::value, |
| 3499 | "result_type must be a floating point type"); |
| 3500 | |
| 3501 | public: |
| 3502 | /** The type of the range of the distribution. */ |
| 3503 | typedef _RealType result_type; |
| 3504 | |
| 3505 | /** Parameter type. */ |
| 3506 | struct param_type |
| 3507 | { |
| 3508 | typedef student_t_distribution<_RealType> distribution_type; |
| 3509 | |
| 3510 | param_type() : param_type(1) { } |
| 3511 | |
| 3512 | explicit |
| 3513 | param_type(_RealType __n) |
| 3514 | : _M_n(__n) |
| 3515 | { } |
| 3516 | |
| 3517 | _RealType |
| 3518 | n() const |
| 3519 | { return _M_n; } |
| 3520 | |
| 3521 | friend bool |
| 3522 | operator==(const param_type& __p1, const param_type& __p2) |
| 3523 | { return __p1._M_n == __p2._M_n; } |
| 3524 | |
| 3525 | #if __cpp_impl_three_way_comparison < 201907L |
| 3526 | friend bool |
| 3527 | operator!=(const param_type& __p1, const param_type& __p2) |
| 3528 | { return !(__p1 == __p2); } |
| 3529 | #endif |
| 3530 | |
| 3531 | private: |
| 3532 | _RealType _M_n; |
| 3533 | }; |
| 3534 | |
| 3535 | student_t_distribution() : student_t_distribution(1.0) { } |
| 3536 | |
| 3537 | explicit |
| 3538 | student_t_distribution(_RealType __n) |
| 3539 | : _M_param(__n), _M_nd(), _M_gd(__n / 2, 2) |
| 3540 | { } |
| 3541 | |
| 3542 | explicit |
| 3543 | student_t_distribution(const param_type& __p) |
| 3544 | : _M_param(__p), _M_nd(), _M_gd(__p.n() / 2, 2) |
| 3545 | { } |
| 3546 | |
| 3547 | /** |
| 3548 | * @brief Resets the distribution state. |
| 3549 | */ |
| 3550 | void |
| 3551 | reset() |
| 3552 | { |
| 3553 | _M_nd.reset(); |
| 3554 | _M_gd.reset(); |
| 3555 | } |
| 3556 | |
| 3557 | /** |
| 3558 | * |
| 3559 | */ |
| 3560 | _RealType |
| 3561 | n() const |
| 3562 | { return _M_param.n(); } |
| 3563 | |
| 3564 | /** |
| 3565 | * @brief Returns the parameter set of the distribution. |
| 3566 | */ |
| 3567 | param_type |
| 3568 | param() const |
| 3569 | { return _M_param; } |
| 3570 | |
| 3571 | /** |
| 3572 | * @brief Sets the parameter set of the distribution. |
| 3573 | * @param __param The new parameter set of the distribution. |
| 3574 | */ |
| 3575 | void |
| 3576 | param(const param_type& __param) |
| 3577 | { _M_param = __param; } |
| 3578 | |
| 3579 | /** |
| 3580 | * @brief Returns the greatest lower bound value of the distribution. |
| 3581 | */ |
| 3582 | result_type |
| 3583 | min() const |
| 3584 | { return std::numeric_limits<result_type>::lowest(); } |
| 3585 | |
| 3586 | /** |
| 3587 | * @brief Returns the least upper bound value of the distribution. |
| 3588 | */ |
| 3589 | result_type |
| 3590 | max() const |
| 3591 | { return std::numeric_limits<result_type>::max(); } |
| 3592 | |
| 3593 | /** |
| 3594 | * @brief Generating functions. |
| 3595 | */ |
| 3596 | template<typename _UniformRandomNumberGenerator> |
| 3597 | result_type |
| 3598 | operator()(_UniformRandomNumberGenerator& __urng) |
| 3599 | { return _M_nd(__urng) * std::sqrt(n() / _M_gd(__urng)); } |
| 3600 | |
| 3601 | template<typename _UniformRandomNumberGenerator> |
| 3602 | result_type |
| 3603 | operator()(_UniformRandomNumberGenerator& __urng, |
| 3604 | const param_type& __p) |
| 3605 | { |
| 3606 | typedef typename std::gamma_distribution<result_type>::param_type |
| 3607 | param_type; |
| 3608 | |
| 3609 | const result_type __g = _M_gd(__urng, param_type(__p.n() / 2, 2)); |
| 3610 | return _M_nd(__urng) * std::sqrt(__p.n() / __g); |
| 3611 | } |
| 3612 | |
| 3613 | template<typename _ForwardIterator, |
| 3614 | typename _UniformRandomNumberGenerator> |
| 3615 | void |
| 3616 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 3617 | _UniformRandomNumberGenerator& __urng) |
| 3618 | { this->__generate_impl(__f, __t, __urng); } |
| 3619 | |
| 3620 | template<typename _ForwardIterator, |
| 3621 | typename _UniformRandomNumberGenerator> |
| 3622 | void |
| 3623 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 3624 | _UniformRandomNumberGenerator& __urng, |
| 3625 | const param_type& __p) |
| 3626 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 3627 | |
| 3628 | template<typename _UniformRandomNumberGenerator> |
| 3629 | void |
| 3630 | __generate(result_type* __f, result_type* __t, |
| 3631 | _UniformRandomNumberGenerator& __urng) |
| 3632 | { this->__generate_impl(__f, __t, __urng); } |
| 3633 | |
| 3634 | template<typename _UniformRandomNumberGenerator> |
| 3635 | void |
| 3636 | __generate(result_type* __f, result_type* __t, |
| 3637 | _UniformRandomNumberGenerator& __urng, |
| 3638 | const param_type& __p) |
| 3639 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 3640 | |
| 3641 | /** |
| 3642 | * @brief Return true if two Student t distributions have |
| 3643 | * the same parameters and the sequences that would |
| 3644 | * be generated are equal. |
| 3645 | */ |
| 3646 | friend bool |
| 3647 | operator==(const student_t_distribution& __d1, |
| 3648 | const student_t_distribution& __d2) |
| 3649 | { return (__d1._M_param == __d2._M_param |
| 3650 | && __d1._M_nd == __d2._M_nd && __d1._M_gd == __d2._M_gd); } |
| 3651 | |
| 3652 | /** |
| 3653 | * @brief Inserts a %student_t_distribution random number distribution |
| 3654 | * @p __x into the output stream @p __os. |
| 3655 | * |
| 3656 | * @param __os An output stream. |
| 3657 | * @param __x A %student_t_distribution random number distribution. |
| 3658 | * |
| 3659 | * @returns The output stream with the state of @p __x inserted or in |
| 3660 | * an error state. |
| 3661 | */ |
| 3662 | template<typename _RealType1, typename _CharT, typename _Traits> |
| 3663 | friend std::basic_ostream<_CharT, _Traits>& |
| 3664 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 3665 | const std::student_t_distribution<_RealType1>& __x); |
| 3666 | |
| 3667 | /** |
| 3668 | * @brief Extracts a %student_t_distribution random number distribution |
| 3669 | * @p __x from the input stream @p __is. |
| 3670 | * |
| 3671 | * @param __is An input stream. |
| 3672 | * @param __x A %student_t_distribution random number |
| 3673 | * generator engine. |
| 3674 | * |
| 3675 | * @returns The input stream with @p __x extracted or in an error state. |
| 3676 | */ |
| 3677 | template<typename _RealType1, typename _CharT, typename _Traits> |
| 3678 | friend std::basic_istream<_CharT, _Traits>& |
| 3679 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 3680 | std::student_t_distribution<_RealType1>& __x); |
| 3681 | |
| 3682 | private: |
| 3683 | template<typename _ForwardIterator, |
| 3684 | typename _UniformRandomNumberGenerator> |
| 3685 | void |
| 3686 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
| 3687 | _UniformRandomNumberGenerator& __urng); |
| 3688 | template<typename _ForwardIterator, |
| 3689 | typename _UniformRandomNumberGenerator> |
| 3690 | void |
| 3691 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
| 3692 | _UniformRandomNumberGenerator& __urng, |
| 3693 | const param_type& __p); |
| 3694 | |
| 3695 | param_type _M_param; |
| 3696 | |
| 3697 | std::normal_distribution<result_type> _M_nd; |
| 3698 | std::gamma_distribution<result_type> _M_gd; |
| 3699 | }; |
| 3700 | |
| 3701 | #if __cpp_impl_three_way_comparison < 201907L |
| 3702 | /** |
| 3703 | * @brief Return true if two Student t distributions are different. |
| 3704 | */ |
| 3705 | template<typename _RealType> |
| 3706 | inline bool |
| 3707 | operator!=(const std::student_t_distribution<_RealType>& __d1, |
| 3708 | const std::student_t_distribution<_RealType>& __d2) |
| 3709 | { return !(__d1 == __d2); } |
| 3710 | #endif |
| 3711 | |
| 3712 | /// @} group random_distributions_normal |
| 3713 | |
| 3714 | /** |
| 3715 | * @addtogroup random_distributions_bernoulli Bernoulli Distributions |
| 3716 | * @ingroup random_distributions |
| 3717 | * @{ |
| 3718 | */ |
| 3719 | |
| 3720 | /** |
| 3721 | * @brief A Bernoulli random number distribution. |
| 3722 | * |
| 3723 | * Generates a sequence of true and false values with likelihood @f$p@f$ |
| 3724 | * that true will come up and @f$(1 - p)@f$ that false will appear. |
| 3725 | * |
| 3726 | * @headerfile random |
| 3727 | * @since C++11 |
| 3728 | */ |
| 3729 | class bernoulli_distribution |
| 3730 | { |
| 3731 | public: |
| 3732 | /** The type of the range of the distribution. */ |
| 3733 | typedef bool result_type; |
| 3734 | |
| 3735 | /** Parameter type. */ |
| 3736 | struct param_type |
| 3737 | { |
| 3738 | typedef bernoulli_distribution distribution_type; |
| 3739 | |
| 3740 | param_type() : param_type(0.5) { } |
| 3741 | |
| 3742 | explicit |
| 3743 | param_type(double __p) |
| 3744 | : _M_p(__p) |
| 3745 | { |
| 3746 | __glibcxx_assert((_M_p >= 0.0) && (_M_p <= 1.0)); |
| 3747 | } |
| 3748 | |
| 3749 | double |
| 3750 | p() const |
| 3751 | { return _M_p; } |
| 3752 | |
| 3753 | friend bool |
| 3754 | operator==(const param_type& __p1, const param_type& __p2) |
| 3755 | { return __p1._M_p == __p2._M_p; } |
| 3756 | |
| 3757 | #if __cpp_impl_three_way_comparison < 201907L |
| 3758 | friend bool |
| 3759 | operator!=(const param_type& __p1, const param_type& __p2) |
| 3760 | { return !(__p1 == __p2); } |
| 3761 | #endif |
| 3762 | |
| 3763 | private: |
| 3764 | double _M_p; |
| 3765 | }; |
| 3766 | |
| 3767 | public: |
| 3768 | /** |
| 3769 | * @brief Constructs a Bernoulli distribution with likelihood 0.5. |
| 3770 | */ |
| 3771 | bernoulli_distribution() : bernoulli_distribution(0.5) { } |
| 3772 | |
| 3773 | /** |
| 3774 | * @brief Constructs a Bernoulli distribution with likelihood @p p. |
| 3775 | * |
| 3776 | * @param __p [IN] The likelihood of a true result being returned. |
| 3777 | * Must be in the interval @f$[0, 1]@f$. |
| 3778 | */ |
| 3779 | explicit |
| 3780 | bernoulli_distribution(double __p) |
| 3781 | : _M_param(__p) |
| 3782 | { } |
| 3783 | |
| 3784 | explicit |
| 3785 | bernoulli_distribution(const param_type& __p) |
| 3786 | : _M_param(__p) |
| 3787 | { } |
| 3788 | |
| 3789 | /** |
| 3790 | * @brief Resets the distribution state. |
| 3791 | * |
| 3792 | * Does nothing for a Bernoulli distribution. |
| 3793 | */ |
| 3794 | void |
| 3795 | reset() { } |
| 3796 | |
| 3797 | /** |
| 3798 | * @brief Returns the @p p parameter of the distribution. |
| 3799 | */ |
| 3800 | double |
| 3801 | p() const |
| 3802 | { return _M_param.p(); } |
| 3803 | |
| 3804 | /** |
| 3805 | * @brief Returns the parameter set of the distribution. |
| 3806 | */ |
| 3807 | param_type |
| 3808 | param() const |
| 3809 | { return _M_param; } |
| 3810 | |
| 3811 | /** |
| 3812 | * @brief Sets the parameter set of the distribution. |
| 3813 | * @param __param The new parameter set of the distribution. |
| 3814 | */ |
| 3815 | void |
| 3816 | param(const param_type& __param) |
| 3817 | { _M_param = __param; } |
| 3818 | |
| 3819 | /** |
| 3820 | * @brief Returns the greatest lower bound value of the distribution. |
| 3821 | */ |
| 3822 | result_type |
| 3823 | min() const |
| 3824 | { return std::numeric_limits<result_type>::min(); } |
| 3825 | |
| 3826 | /** |
| 3827 | * @brief Returns the least upper bound value of the distribution. |
| 3828 | */ |
| 3829 | result_type |
| 3830 | max() const |
| 3831 | { return std::numeric_limits<result_type>::max(); } |
| 3832 | |
| 3833 | /** |
| 3834 | * @brief Generating functions. |
| 3835 | */ |
| 3836 | template<typename _UniformRandomNumberGenerator> |
| 3837 | result_type |
| 3838 | operator()(_UniformRandomNumberGenerator& __urng) |
| 3839 | { return this->operator()(__urng, _M_param); } |
| 3840 | |
| 3841 | template<typename _UniformRandomNumberGenerator> |
| 3842 | result_type |
| 3843 | operator()(_UniformRandomNumberGenerator& __urng, |
| 3844 | const param_type& __p) |
| 3845 | { |
| 3846 | __detail::_Adaptor<_UniformRandomNumberGenerator, double> |
| 3847 | __aurng(__urng); |
| 3848 | if ((__aurng() - __aurng.min()) |
| 3849 | < __p.p() * (__aurng.max() - __aurng.min())) |
| 3850 | return true; |
| 3851 | return false; |
| 3852 | } |
| 3853 | |
| 3854 | template<typename _ForwardIterator, |
| 3855 | typename _UniformRandomNumberGenerator> |
| 3856 | void |
| 3857 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 3858 | _UniformRandomNumberGenerator& __urng) |
| 3859 | { this->__generate(__f, __t, __urng, _M_param); } |
| 3860 | |
| 3861 | template<typename _ForwardIterator, |
| 3862 | typename _UniformRandomNumberGenerator> |
| 3863 | void |
| 3864 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 3865 | _UniformRandomNumberGenerator& __urng, const param_type& __p) |
| 3866 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 3867 | |
| 3868 | template<typename _UniformRandomNumberGenerator> |
| 3869 | void |
| 3870 | __generate(result_type* __f, result_type* __t, |
| 3871 | _UniformRandomNumberGenerator& __urng, |
| 3872 | const param_type& __p) |
| 3873 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 3874 | |
| 3875 | /** |
| 3876 | * @brief Return true if two Bernoulli distributions have |
| 3877 | * the same parameters. |
| 3878 | */ |
| 3879 | friend bool |
| 3880 | operator==(const bernoulli_distribution& __d1, |
| 3881 | const bernoulli_distribution& __d2) |
| 3882 | { return __d1._M_param == __d2._M_param; } |
| 3883 | |
| 3884 | private: |
| 3885 | template<typename _ForwardIterator, |
| 3886 | typename _UniformRandomNumberGenerator> |
| 3887 | void |
| 3888 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
| 3889 | _UniformRandomNumberGenerator& __urng, |
| 3890 | const param_type& __p); |
| 3891 | |
| 3892 | param_type _M_param; |
| 3893 | }; |
| 3894 | |
| 3895 | #if __cpp_impl_three_way_comparison < 201907L |
| 3896 | /** |
| 3897 | * @brief Return true if two Bernoulli distributions have |
| 3898 | * different parameters. |
| 3899 | */ |
| 3900 | inline bool |
| 3901 | operator!=(const std::bernoulli_distribution& __d1, |
| 3902 | const std::bernoulli_distribution& __d2) |
| 3903 | { return !(__d1 == __d2); } |
| 3904 | #endif |
| 3905 | |
| 3906 | /** |
| 3907 | * @brief Inserts a %bernoulli_distribution random number distribution |
| 3908 | * @p __x into the output stream @p __os. |
| 3909 | * |
| 3910 | * @param __os An output stream. |
| 3911 | * @param __x A %bernoulli_distribution random number distribution. |
| 3912 | * |
| 3913 | * @returns The output stream with the state of @p __x inserted or in |
| 3914 | * an error state. |
| 3915 | */ |
| 3916 | template<typename _CharT, typename _Traits> |
| 3917 | std::basic_ostream<_CharT, _Traits>& |
| 3918 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 3919 | const std::bernoulli_distribution& __x); |
| 3920 | |
| 3921 | /** |
| 3922 | * @brief Extracts a %bernoulli_distribution random number distribution |
| 3923 | * @p __x from the input stream @p __is. |
| 3924 | * |
| 3925 | * @param __is An input stream. |
| 3926 | * @param __x A %bernoulli_distribution random number generator engine. |
| 3927 | * |
| 3928 | * @returns The input stream with @p __x extracted or in an error state. |
| 3929 | */ |
| 3930 | template<typename _CharT, typename _Traits> |
| 3931 | inline std::basic_istream<_CharT, _Traits>& |
| 3932 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 3933 | std::bernoulli_distribution& __x) |
| 3934 | { |
| 3935 | double __p; |
| 3936 | if (__is >> __p) |
| 3937 | __x.param(param: bernoulli_distribution::param_type(__p)); |
| 3938 | return __is; |
| 3939 | } |
| 3940 | |
| 3941 | |
| 3942 | /** |
| 3943 | * @brief A discrete binomial random number distribution. |
| 3944 | * |
| 3945 | * The formula for the binomial probability density function is |
| 3946 | * @f$p(i|t,p) = \binom{t}{i} p^i (1 - p)^{t - i}@f$ where @f$t@f$ |
| 3947 | * and @f$p@f$ are the parameters of the distribution. |
| 3948 | * |
| 3949 | * @headerfile random |
| 3950 | * @since C++11 |
| 3951 | */ |
| 3952 | template<typename _IntType = int> |
| 3953 | class binomial_distribution |
| 3954 | { |
| 3955 | static_assert(std::is_integral<_IntType>::value, |
| 3956 | "result_type must be an integral type"); |
| 3957 | |
| 3958 | public: |
| 3959 | /** The type of the range of the distribution. */ |
| 3960 | typedef _IntType result_type; |
| 3961 | |
| 3962 | /** Parameter type. */ |
| 3963 | struct param_type |
| 3964 | { |
| 3965 | typedef binomial_distribution<_IntType> distribution_type; |
| 3966 | friend class binomial_distribution<_IntType>; |
| 3967 | |
| 3968 | param_type() : param_type(1) { } |
| 3969 | |
| 3970 | explicit |
| 3971 | param_type(_IntType __t, double __p = 0.5) |
| 3972 | : _M_t(__t), _M_p(__p) |
| 3973 | { |
| 3974 | __glibcxx_assert((_M_t >= _IntType(0)) |
| 3975 | && (_M_p >= 0.0) |
| 3976 | && (_M_p <= 1.0)); |
| 3977 | _M_initialize(); |
| 3978 | } |
| 3979 | |
| 3980 | _IntType |
| 3981 | t() const |
| 3982 | { return _M_t; } |
| 3983 | |
| 3984 | double |
| 3985 | p() const |
| 3986 | { return _M_p; } |
| 3987 | |
| 3988 | friend bool |
| 3989 | operator==(const param_type& __p1, const param_type& __p2) |
| 3990 | { return __p1._M_t == __p2._M_t && __p1._M_p == __p2._M_p; } |
| 3991 | |
| 3992 | #if __cpp_impl_three_way_comparison < 201907L |
| 3993 | friend bool |
| 3994 | operator!=(const param_type& __p1, const param_type& __p2) |
| 3995 | { return !(__p1 == __p2); } |
| 3996 | #endif |
| 3997 | |
| 3998 | private: |
| 3999 | void |
| 4000 | _M_initialize(); |
| 4001 | |
| 4002 | _IntType _M_t; |
| 4003 | double _M_p; |
| 4004 | |
| 4005 | double _M_q; |
| 4006 | #if _GLIBCXX_USE_C99_MATH_FUNCS |
| 4007 | double _M_d1, _M_d2, _M_s1, _M_s2, _M_c, |
| 4008 | _M_a1, _M_a123, _M_s, _M_lf, _M_lp1p; |
| 4009 | #endif |
| 4010 | bool _M_easy; |
| 4011 | }; |
| 4012 | |
| 4013 | // constructors and member functions |
| 4014 | |
| 4015 | binomial_distribution() : binomial_distribution(1) { } |
| 4016 | |
| 4017 | explicit |
| 4018 | binomial_distribution(_IntType __t, double __p = 0.5) |
| 4019 | : _M_param(__t, __p), _M_nd() |
| 4020 | { } |
| 4021 | |
| 4022 | explicit |
| 4023 | binomial_distribution(const param_type& __p) |
| 4024 | : _M_param(__p), _M_nd() |
| 4025 | { } |
| 4026 | |
| 4027 | /** |
| 4028 | * @brief Resets the distribution state. |
| 4029 | */ |
| 4030 | void |
| 4031 | reset() |
| 4032 | { _M_nd.reset(); } |
| 4033 | |
| 4034 | /** |
| 4035 | * @brief Returns the distribution @p t parameter. |
| 4036 | */ |
| 4037 | _IntType |
| 4038 | t() const |
| 4039 | { return _M_param.t(); } |
| 4040 | |
| 4041 | /** |
| 4042 | * @brief Returns the distribution @p p parameter. |
| 4043 | */ |
| 4044 | double |
| 4045 | p() const |
| 4046 | { return _M_param.p(); } |
| 4047 | |
| 4048 | /** |
| 4049 | * @brief Returns the parameter set of the distribution. |
| 4050 | */ |
| 4051 | param_type |
| 4052 | param() const |
| 4053 | { return _M_param; } |
| 4054 | |
| 4055 | /** |
| 4056 | * @brief Sets the parameter set of the distribution. |
| 4057 | * @param __param The new parameter set of the distribution. |
| 4058 | */ |
| 4059 | void |
| 4060 | param(const param_type& __param) |
| 4061 | { _M_param = __param; } |
| 4062 | |
| 4063 | /** |
| 4064 | * @brief Returns the greatest lower bound value of the distribution. |
| 4065 | */ |
| 4066 | result_type |
| 4067 | min() const |
| 4068 | { return 0; } |
| 4069 | |
| 4070 | /** |
| 4071 | * @brief Returns the least upper bound value of the distribution. |
| 4072 | */ |
| 4073 | result_type |
| 4074 | max() const |
| 4075 | { return _M_param.t(); } |
| 4076 | |
| 4077 | /** |
| 4078 | * @brief Generating functions. |
| 4079 | */ |
| 4080 | template<typename _UniformRandomNumberGenerator> |
| 4081 | result_type |
| 4082 | operator()(_UniformRandomNumberGenerator& __urng) |
| 4083 | { return this->operator()(__urng, _M_param); } |
| 4084 | |
| 4085 | template<typename _UniformRandomNumberGenerator> |
| 4086 | result_type |
| 4087 | operator()(_UniformRandomNumberGenerator& __urng, |
| 4088 | const param_type& __p); |
| 4089 | |
| 4090 | template<typename _ForwardIterator, |
| 4091 | typename _UniformRandomNumberGenerator> |
| 4092 | void |
| 4093 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 4094 | _UniformRandomNumberGenerator& __urng) |
| 4095 | { this->__generate(__f, __t, __urng, _M_param); } |
| 4096 | |
| 4097 | template<typename _ForwardIterator, |
| 4098 | typename _UniformRandomNumberGenerator> |
| 4099 | void |
| 4100 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 4101 | _UniformRandomNumberGenerator& __urng, |
| 4102 | const param_type& __p) |
| 4103 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 4104 | |
| 4105 | template<typename _UniformRandomNumberGenerator> |
| 4106 | void |
| 4107 | __generate(result_type* __f, result_type* __t, |
| 4108 | _UniformRandomNumberGenerator& __urng, |
| 4109 | const param_type& __p) |
| 4110 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 4111 | |
| 4112 | /** |
| 4113 | * @brief Return true if two binomial distributions have |
| 4114 | * the same parameters and the sequences that would |
| 4115 | * be generated are equal. |
| 4116 | */ |
| 4117 | friend bool |
| 4118 | operator==(const binomial_distribution& __d1, |
| 4119 | const binomial_distribution& __d2) |
| 4120 | #ifdef _GLIBCXX_USE_C99_MATH_FUNCS |
| 4121 | { return __d1._M_param == __d2._M_param && __d1._M_nd == __d2._M_nd; } |
| 4122 | #else |
| 4123 | { return __d1._M_param == __d2._M_param; } |
| 4124 | #endif |
| 4125 | |
| 4126 | /** |
| 4127 | * @brief Inserts a %binomial_distribution random number distribution |
| 4128 | * @p __x into the output stream @p __os. |
| 4129 | * |
| 4130 | * @param __os An output stream. |
| 4131 | * @param __x A %binomial_distribution random number distribution. |
| 4132 | * |
| 4133 | * @returns The output stream with the state of @p __x inserted or in |
| 4134 | * an error state. |
| 4135 | */ |
| 4136 | template<typename _IntType1, |
| 4137 | typename _CharT, typename _Traits> |
| 4138 | friend std::basic_ostream<_CharT, _Traits>& |
| 4139 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 4140 | const std::binomial_distribution<_IntType1>& __x); |
| 4141 | |
| 4142 | /** |
| 4143 | * @brief Extracts a %binomial_distribution random number distribution |
| 4144 | * @p __x from the input stream @p __is. |
| 4145 | * |
| 4146 | * @param __is An input stream. |
| 4147 | * @param __x A %binomial_distribution random number generator engine. |
| 4148 | * |
| 4149 | * @returns The input stream with @p __x extracted or in an error |
| 4150 | * state. |
| 4151 | */ |
| 4152 | template<typename _IntType1, |
| 4153 | typename _CharT, typename _Traits> |
| 4154 | friend std::basic_istream<_CharT, _Traits>& |
| 4155 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 4156 | std::binomial_distribution<_IntType1>& __x); |
| 4157 | |
| 4158 | private: |
| 4159 | template<typename _ForwardIterator, |
| 4160 | typename _UniformRandomNumberGenerator> |
| 4161 | void |
| 4162 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
| 4163 | _UniformRandomNumberGenerator& __urng, |
| 4164 | const param_type& __p); |
| 4165 | |
| 4166 | template<typename _UniformRandomNumberGenerator> |
| 4167 | result_type |
| 4168 | _M_waiting(_UniformRandomNumberGenerator& __urng, |
| 4169 | _IntType __t, double __q); |
| 4170 | |
| 4171 | param_type _M_param; |
| 4172 | |
| 4173 | // NB: Unused when _GLIBCXX_USE_C99_MATH_FUNCS is undefined. |
| 4174 | std::normal_distribution<double> _M_nd; |
| 4175 | }; |
| 4176 | |
| 4177 | #if __cpp_impl_three_way_comparison < 201907L |
| 4178 | /** |
| 4179 | * @brief Return true if two binomial distributions are different. |
| 4180 | */ |
| 4181 | template<typename _IntType> |
| 4182 | inline bool |
| 4183 | operator!=(const std::binomial_distribution<_IntType>& __d1, |
| 4184 | const std::binomial_distribution<_IntType>& __d2) |
| 4185 | { return !(__d1 == __d2); } |
| 4186 | #endif |
| 4187 | |
| 4188 | /** |
| 4189 | * @brief A discrete geometric random number distribution. |
| 4190 | * |
| 4191 | * The formula for the geometric probability density function is |
| 4192 | * @f$p(i|p) = p(1 - p)^{i}@f$ where @f$p@f$ is the parameter of the |
| 4193 | * distribution. |
| 4194 | * |
| 4195 | * @headerfile random |
| 4196 | * @since C++11 |
| 4197 | */ |
| 4198 | template<typename _IntType = int> |
| 4199 | class geometric_distribution |
| 4200 | { |
| 4201 | static_assert(std::is_integral<_IntType>::value, |
| 4202 | "result_type must be an integral type"); |
| 4203 | |
| 4204 | public: |
| 4205 | /** The type of the range of the distribution. */ |
| 4206 | typedef _IntType result_type; |
| 4207 | |
| 4208 | /** Parameter type. */ |
| 4209 | struct param_type |
| 4210 | { |
| 4211 | typedef geometric_distribution<_IntType> distribution_type; |
| 4212 | friend class geometric_distribution<_IntType>; |
| 4213 | |
| 4214 | param_type() : param_type(0.5) { } |
| 4215 | |
| 4216 | explicit |
| 4217 | param_type(double __p) |
| 4218 | : _M_p(__p) |
| 4219 | { |
| 4220 | __glibcxx_assert((_M_p > 0.0) && (_M_p < 1.0)); |
| 4221 | _M_initialize(); |
| 4222 | } |
| 4223 | |
| 4224 | double |
| 4225 | p() const |
| 4226 | { return _M_p; } |
| 4227 | |
| 4228 | friend bool |
| 4229 | operator==(const param_type& __p1, const param_type& __p2) |
| 4230 | { return __p1._M_p == __p2._M_p; } |
| 4231 | |
| 4232 | #if __cpp_impl_three_way_comparison < 201907L |
| 4233 | friend bool |
| 4234 | operator!=(const param_type& __p1, const param_type& __p2) |
| 4235 | { return !(__p1 == __p2); } |
| 4236 | #endif |
| 4237 | |
| 4238 | private: |
| 4239 | void |
| 4240 | _M_initialize() |
| 4241 | { _M_log_1_p = std::log(x: 1.0 - _M_p); } |
| 4242 | |
| 4243 | double _M_p; |
| 4244 | |
| 4245 | double _M_log_1_p; |
| 4246 | }; |
| 4247 | |
| 4248 | // constructors and member functions |
| 4249 | |
| 4250 | geometric_distribution() : geometric_distribution(0.5) { } |
| 4251 | |
| 4252 | explicit |
| 4253 | geometric_distribution(double __p) |
| 4254 | : _M_param(__p) |
| 4255 | { } |
| 4256 | |
| 4257 | explicit |
| 4258 | geometric_distribution(const param_type& __p) |
| 4259 | : _M_param(__p) |
| 4260 | { } |
| 4261 | |
| 4262 | /** |
| 4263 | * @brief Resets the distribution state. |
| 4264 | * |
| 4265 | * Does nothing for the geometric distribution. |
| 4266 | */ |
| 4267 | void |
| 4268 | reset() { } |
| 4269 | |
| 4270 | /** |
| 4271 | * @brief Returns the distribution parameter @p p. |
| 4272 | */ |
| 4273 | double |
| 4274 | p() const |
| 4275 | { return _M_param.p(); } |
| 4276 | |
| 4277 | /** |
| 4278 | * @brief Returns the parameter set of the distribution. |
| 4279 | */ |
| 4280 | param_type |
| 4281 | param() const |
| 4282 | { return _M_param; } |
| 4283 | |
| 4284 | /** |
| 4285 | * @brief Sets the parameter set of the distribution. |
| 4286 | * @param __param The new parameter set of the distribution. |
| 4287 | */ |
| 4288 | void |
| 4289 | param(const param_type& __param) |
| 4290 | { _M_param = __param; } |
| 4291 | |
| 4292 | /** |
| 4293 | * @brief Returns the greatest lower bound value of the distribution. |
| 4294 | */ |
| 4295 | result_type |
| 4296 | min() const |
| 4297 | { return 0; } |
| 4298 | |
| 4299 | /** |
| 4300 | * @brief Returns the least upper bound value of the distribution. |
| 4301 | */ |
| 4302 | result_type |
| 4303 | max() const |
| 4304 | { return std::numeric_limits<result_type>::max(); } |
| 4305 | |
| 4306 | /** |
| 4307 | * @brief Generating functions. |
| 4308 | */ |
| 4309 | template<typename _UniformRandomNumberGenerator> |
| 4310 | result_type |
| 4311 | operator()(_UniformRandomNumberGenerator& __urng) |
| 4312 | { return this->operator()(__urng, _M_param); } |
| 4313 | |
| 4314 | template<typename _UniformRandomNumberGenerator> |
| 4315 | result_type |
| 4316 | operator()(_UniformRandomNumberGenerator& __urng, |
| 4317 | const param_type& __p); |
| 4318 | |
| 4319 | template<typename _ForwardIterator, |
| 4320 | typename _UniformRandomNumberGenerator> |
| 4321 | void |
| 4322 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 4323 | _UniformRandomNumberGenerator& __urng) |
| 4324 | { this->__generate(__f, __t, __urng, _M_param); } |
| 4325 | |
| 4326 | template<typename _ForwardIterator, |
| 4327 | typename _UniformRandomNumberGenerator> |
| 4328 | void |
| 4329 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 4330 | _UniformRandomNumberGenerator& __urng, |
| 4331 | const param_type& __p) |
| 4332 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 4333 | |
| 4334 | template<typename _UniformRandomNumberGenerator> |
| 4335 | void |
| 4336 | __generate(result_type* __f, result_type* __t, |
| 4337 | _UniformRandomNumberGenerator& __urng, |
| 4338 | const param_type& __p) |
| 4339 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 4340 | |
| 4341 | /** |
| 4342 | * @brief Return true if two geometric distributions have |
| 4343 | * the same parameters. |
| 4344 | */ |
| 4345 | friend bool |
| 4346 | operator==(const geometric_distribution& __d1, |
| 4347 | const geometric_distribution& __d2) |
| 4348 | { return __d1._M_param == __d2._M_param; } |
| 4349 | |
| 4350 | private: |
| 4351 | template<typename _ForwardIterator, |
| 4352 | typename _UniformRandomNumberGenerator> |
| 4353 | void |
| 4354 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
| 4355 | _UniformRandomNumberGenerator& __urng, |
| 4356 | const param_type& __p); |
| 4357 | |
| 4358 | param_type _M_param; |
| 4359 | }; |
| 4360 | |
| 4361 | #if __cpp_impl_three_way_comparison < 201907L |
| 4362 | /** |
| 4363 | * @brief Return true if two geometric distributions have |
| 4364 | * different parameters. |
| 4365 | */ |
| 4366 | template<typename _IntType> |
| 4367 | inline bool |
| 4368 | operator!=(const std::geometric_distribution<_IntType>& __d1, |
| 4369 | const std::geometric_distribution<_IntType>& __d2) |
| 4370 | { return !(__d1 == __d2); } |
| 4371 | #endif |
| 4372 | |
| 4373 | /** |
| 4374 | * @brief Inserts a %geometric_distribution random number distribution |
| 4375 | * @p __x into the output stream @p __os. |
| 4376 | * |
| 4377 | * @param __os An output stream. |
| 4378 | * @param __x A %geometric_distribution random number distribution. |
| 4379 | * |
| 4380 | * @returns The output stream with the state of @p __x inserted or in |
| 4381 | * an error state. |
| 4382 | */ |
| 4383 | template<typename _IntType, |
| 4384 | typename _CharT, typename _Traits> |
| 4385 | std::basic_ostream<_CharT, _Traits>& |
| 4386 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 4387 | const std::geometric_distribution<_IntType>& __x); |
| 4388 | |
| 4389 | /** |
| 4390 | * @brief Extracts a %geometric_distribution random number distribution |
| 4391 | * @p __x from the input stream @p __is. |
| 4392 | * |
| 4393 | * @param __is An input stream. |
| 4394 | * @param __x A %geometric_distribution random number generator engine. |
| 4395 | * |
| 4396 | * @returns The input stream with @p __x extracted or in an error state. |
| 4397 | */ |
| 4398 | template<typename _IntType, |
| 4399 | typename _CharT, typename _Traits> |
| 4400 | std::basic_istream<_CharT, _Traits>& |
| 4401 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 4402 | std::geometric_distribution<_IntType>& __x); |
| 4403 | |
| 4404 | |
| 4405 | /** |
| 4406 | * @brief A negative_binomial_distribution random number distribution. |
| 4407 | * |
| 4408 | * The formula for the negative binomial probability mass function is |
| 4409 | * @f$p(i) = \binom{n}{i} p^i (1 - p)^{t - i}@f$ where @f$t@f$ |
| 4410 | * and @f$p@f$ are the parameters of the distribution. |
| 4411 | * |
| 4412 | * @headerfile random |
| 4413 | * @since C++11 |
| 4414 | */ |
| 4415 | template<typename _IntType = int> |
| 4416 | class negative_binomial_distribution |
| 4417 | { |
| 4418 | static_assert(std::is_integral<_IntType>::value, |
| 4419 | "result_type must be an integral type"); |
| 4420 | |
| 4421 | public: |
| 4422 | /** The type of the range of the distribution. */ |
| 4423 | typedef _IntType result_type; |
| 4424 | |
| 4425 | /** Parameter type. */ |
| 4426 | struct param_type |
| 4427 | { |
| 4428 | typedef negative_binomial_distribution<_IntType> distribution_type; |
| 4429 | |
| 4430 | param_type() : param_type(1) { } |
| 4431 | |
| 4432 | explicit |
| 4433 | param_type(_IntType __k, double __p = 0.5) |
| 4434 | : _M_k(__k), _M_p(__p) |
| 4435 | { |
| 4436 | __glibcxx_assert((_M_k > 0) && (_M_p > 0.0) && (_M_p <= 1.0)); |
| 4437 | } |
| 4438 | |
| 4439 | _IntType |
| 4440 | k() const |
| 4441 | { return _M_k; } |
| 4442 | |
| 4443 | double |
| 4444 | p() const |
| 4445 | { return _M_p; } |
| 4446 | |
| 4447 | friend bool |
| 4448 | operator==(const param_type& __p1, const param_type& __p2) |
| 4449 | { return __p1._M_k == __p2._M_k && __p1._M_p == __p2._M_p; } |
| 4450 | |
| 4451 | #if __cpp_impl_three_way_comparison < 201907L |
| 4452 | friend bool |
| 4453 | operator!=(const param_type& __p1, const param_type& __p2) |
| 4454 | { return !(__p1 == __p2); } |
| 4455 | #endif |
| 4456 | |
| 4457 | private: |
| 4458 | _IntType _M_k; |
| 4459 | double _M_p; |
| 4460 | }; |
| 4461 | |
| 4462 | negative_binomial_distribution() : negative_binomial_distribution(1) { } |
| 4463 | |
| 4464 | explicit |
| 4465 | negative_binomial_distribution(_IntType __k, double __p = 0.5) |
| 4466 | : _M_param(__k, __p), _M_gd(__k, (1.0 - __p) / __p) |
| 4467 | { } |
| 4468 | |
| 4469 | explicit |
| 4470 | negative_binomial_distribution(const param_type& __p) |
| 4471 | : _M_param(__p), _M_gd(__p.k(), (1.0 - __p.p()) / __p.p()) |
| 4472 | { } |
| 4473 | |
| 4474 | /** |
| 4475 | * @brief Resets the distribution state. |
| 4476 | */ |
| 4477 | void |
| 4478 | reset() |
| 4479 | { _M_gd.reset(); } |
| 4480 | |
| 4481 | /** |
| 4482 | * @brief Return the @f$k@f$ parameter of the distribution. |
| 4483 | */ |
| 4484 | _IntType |
| 4485 | k() const |
| 4486 | { return _M_param.k(); } |
| 4487 | |
| 4488 | /** |
| 4489 | * @brief Return the @f$p@f$ parameter of the distribution. |
| 4490 | */ |
| 4491 | double |
| 4492 | p() const |
| 4493 | { return _M_param.p(); } |
| 4494 | |
| 4495 | /** |
| 4496 | * @brief Returns the parameter set of the distribution. |
| 4497 | */ |
| 4498 | param_type |
| 4499 | param() const |
| 4500 | { return _M_param; } |
| 4501 | |
| 4502 | /** |
| 4503 | * @brief Sets the parameter set of the distribution. |
| 4504 | * @param __param The new parameter set of the distribution. |
| 4505 | */ |
| 4506 | void |
| 4507 | param(const param_type& __param) |
| 4508 | { _M_param = __param; } |
| 4509 | |
| 4510 | /** |
| 4511 | * @brief Returns the greatest lower bound value of the distribution. |
| 4512 | */ |
| 4513 | result_type |
| 4514 | min() const |
| 4515 | { return result_type(0); } |
| 4516 | |
| 4517 | /** |
| 4518 | * @brief Returns the least upper bound value of the distribution. |
| 4519 | */ |
| 4520 | result_type |
| 4521 | max() const |
| 4522 | { return std::numeric_limits<result_type>::max(); } |
| 4523 | |
| 4524 | /** |
| 4525 | * @brief Generating functions. |
| 4526 | */ |
| 4527 | template<typename _UniformRandomNumberGenerator> |
| 4528 | result_type |
| 4529 | operator()(_UniformRandomNumberGenerator& __urng); |
| 4530 | |
| 4531 | template<typename _UniformRandomNumberGenerator> |
| 4532 | result_type |
| 4533 | operator()(_UniformRandomNumberGenerator& __urng, |
| 4534 | const param_type& __p); |
| 4535 | |
| 4536 | template<typename _ForwardIterator, |
| 4537 | typename _UniformRandomNumberGenerator> |
| 4538 | void |
| 4539 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 4540 | _UniformRandomNumberGenerator& __urng) |
| 4541 | { this->__generate_impl(__f, __t, __urng); } |
| 4542 | |
| 4543 | template<typename _ForwardIterator, |
| 4544 | typename _UniformRandomNumberGenerator> |
| 4545 | void |
| 4546 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 4547 | _UniformRandomNumberGenerator& __urng, |
| 4548 | const param_type& __p) |
| 4549 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 4550 | |
| 4551 | template<typename _UniformRandomNumberGenerator> |
| 4552 | void |
| 4553 | __generate(result_type* __f, result_type* __t, |
| 4554 | _UniformRandomNumberGenerator& __urng) |
| 4555 | { this->__generate_impl(__f, __t, __urng); } |
| 4556 | |
| 4557 | template<typename _UniformRandomNumberGenerator> |
| 4558 | void |
| 4559 | __generate(result_type* __f, result_type* __t, |
| 4560 | _UniformRandomNumberGenerator& __urng, |
| 4561 | const param_type& __p) |
| 4562 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 4563 | |
| 4564 | /** |
| 4565 | * @brief Return true if two negative binomial distributions have |
| 4566 | * the same parameters and the sequences that would be |
| 4567 | * generated are equal. |
| 4568 | */ |
| 4569 | friend bool |
| 4570 | operator==(const negative_binomial_distribution& __d1, |
| 4571 | const negative_binomial_distribution& __d2) |
| 4572 | { return __d1._M_param == __d2._M_param && __d1._M_gd == __d2._M_gd; } |
| 4573 | |
| 4574 | /** |
| 4575 | * @brief Inserts a %negative_binomial_distribution random |
| 4576 | * number distribution @p __x into the output stream @p __os. |
| 4577 | * |
| 4578 | * @param __os An output stream. |
| 4579 | * @param __x A %negative_binomial_distribution random number |
| 4580 | * distribution. |
| 4581 | * |
| 4582 | * @returns The output stream with the state of @p __x inserted or in |
| 4583 | * an error state. |
| 4584 | */ |
| 4585 | template<typename _IntType1, typename _CharT, typename _Traits> |
| 4586 | friend std::basic_ostream<_CharT, _Traits>& |
| 4587 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 4588 | const std::negative_binomial_distribution<_IntType1>& __x); |
| 4589 | |
| 4590 | /** |
| 4591 | * @brief Extracts a %negative_binomial_distribution random number |
| 4592 | * distribution @p __x from the input stream @p __is. |
| 4593 | * |
| 4594 | * @param __is An input stream. |
| 4595 | * @param __x A %negative_binomial_distribution random number |
| 4596 | * generator engine. |
| 4597 | * |
| 4598 | * @returns The input stream with @p __x extracted or in an error state. |
| 4599 | */ |
| 4600 | template<typename _IntType1, typename _CharT, typename _Traits> |
| 4601 | friend std::basic_istream<_CharT, _Traits>& |
| 4602 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 4603 | std::negative_binomial_distribution<_IntType1>& __x); |
| 4604 | |
| 4605 | private: |
| 4606 | template<typename _ForwardIterator, |
| 4607 | typename _UniformRandomNumberGenerator> |
| 4608 | void |
| 4609 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
| 4610 | _UniformRandomNumberGenerator& __urng); |
| 4611 | template<typename _ForwardIterator, |
| 4612 | typename _UniformRandomNumberGenerator> |
| 4613 | void |
| 4614 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
| 4615 | _UniformRandomNumberGenerator& __urng, |
| 4616 | const param_type& __p); |
| 4617 | |
| 4618 | param_type _M_param; |
| 4619 | |
| 4620 | std::gamma_distribution<double> _M_gd; |
| 4621 | }; |
| 4622 | |
| 4623 | #if __cpp_impl_three_way_comparison < 201907L |
| 4624 | /** |
| 4625 | * @brief Return true if two negative binomial distributions are different. |
| 4626 | */ |
| 4627 | template<typename _IntType> |
| 4628 | inline bool |
| 4629 | operator!=(const std::negative_binomial_distribution<_IntType>& __d1, |
| 4630 | const std::negative_binomial_distribution<_IntType>& __d2) |
| 4631 | { return !(__d1 == __d2); } |
| 4632 | #endif |
| 4633 | |
| 4634 | /// @} group random_distributions_bernoulli |
| 4635 | |
| 4636 | /** |
| 4637 | * @addtogroup random_distributions_poisson Poisson Distributions |
| 4638 | * @ingroup random_distributions |
| 4639 | * @{ |
| 4640 | */ |
| 4641 | |
| 4642 | /** |
| 4643 | * @brief A discrete Poisson random number distribution. |
| 4644 | * |
| 4645 | * The formula for the Poisson probability density function is |
| 4646 | * @f$p(i|\mu) = \frac{\mu^i}{i!} e^{-\mu}@f$ where @f$\mu@f$ is the |
| 4647 | * parameter of the distribution. |
| 4648 | * |
| 4649 | * @headerfile random |
| 4650 | * @since C++11 |
| 4651 | */ |
| 4652 | template<typename _IntType = int> |
| 4653 | class poisson_distribution |
| 4654 | { |
| 4655 | static_assert(std::is_integral<_IntType>::value, |
| 4656 | "result_type must be an integral type"); |
| 4657 | |
| 4658 | public: |
| 4659 | /** The type of the range of the distribution. */ |
| 4660 | typedef _IntType result_type; |
| 4661 | |
| 4662 | /** Parameter type. */ |
| 4663 | struct param_type |
| 4664 | { |
| 4665 | typedef poisson_distribution<_IntType> distribution_type; |
| 4666 | friend class poisson_distribution<_IntType>; |
| 4667 | |
| 4668 | param_type() : param_type(1.0) { } |
| 4669 | |
| 4670 | explicit |
| 4671 | param_type(double __mean) |
| 4672 | : _M_mean(__mean) |
| 4673 | { |
| 4674 | __glibcxx_assert(_M_mean > 0.0); |
| 4675 | _M_initialize(); |
| 4676 | } |
| 4677 | |
| 4678 | double |
| 4679 | mean() const |
| 4680 | { return _M_mean; } |
| 4681 | |
| 4682 | friend bool |
| 4683 | operator==(const param_type& __p1, const param_type& __p2) |
| 4684 | { return __p1._M_mean == __p2._M_mean; } |
| 4685 | |
| 4686 | #if __cpp_impl_three_way_comparison < 201907L |
| 4687 | friend bool |
| 4688 | operator!=(const param_type& __p1, const param_type& __p2) |
| 4689 | { return !(__p1 == __p2); } |
| 4690 | #endif |
| 4691 | |
| 4692 | private: |
| 4693 | // Hosts either log(mean) or the threshold of the simple method. |
| 4694 | void |
| 4695 | _M_initialize(); |
| 4696 | |
| 4697 | double _M_mean; |
| 4698 | |
| 4699 | double _M_lm_thr; |
| 4700 | #if _GLIBCXX_USE_C99_MATH_FUNCS |
| 4701 | double _M_lfm, _M_sm, _M_d, _M_scx, _M_1cx, _M_c2b, _M_cb; |
| 4702 | #endif |
| 4703 | }; |
| 4704 | |
| 4705 | // constructors and member functions |
| 4706 | |
| 4707 | poisson_distribution() : poisson_distribution(1.0) { } |
| 4708 | |
| 4709 | explicit |
| 4710 | poisson_distribution(double __mean) |
| 4711 | : _M_param(__mean), _M_nd() |
| 4712 | { } |
| 4713 | |
| 4714 | explicit |
| 4715 | poisson_distribution(const param_type& __p) |
| 4716 | : _M_param(__p), _M_nd() |
| 4717 | { } |
| 4718 | |
| 4719 | /** |
| 4720 | * @brief Resets the distribution state. |
| 4721 | */ |
| 4722 | void |
| 4723 | reset() |
| 4724 | { _M_nd.reset(); } |
| 4725 | |
| 4726 | /** |
| 4727 | * @brief Returns the distribution parameter @p mean. |
| 4728 | */ |
| 4729 | double |
| 4730 | mean() const |
| 4731 | { return _M_param.mean(); } |
| 4732 | |
| 4733 | /** |
| 4734 | * @brief Returns the parameter set of the distribution. |
| 4735 | */ |
| 4736 | param_type |
| 4737 | param() const |
| 4738 | { return _M_param; } |
| 4739 | |
| 4740 | /** |
| 4741 | * @brief Sets the parameter set of the distribution. |
| 4742 | * @param __param The new parameter set of the distribution. |
| 4743 | */ |
| 4744 | void |
| 4745 | param(const param_type& __param) |
| 4746 | { _M_param = __param; } |
| 4747 | |
| 4748 | /** |
| 4749 | * @brief Returns the greatest lower bound value of the distribution. |
| 4750 | */ |
| 4751 | result_type |
| 4752 | min() const |
| 4753 | { return 0; } |
| 4754 | |
| 4755 | /** |
| 4756 | * @brief Returns the least upper bound value of the distribution. |
| 4757 | */ |
| 4758 | result_type |
| 4759 | max() const |
| 4760 | { return std::numeric_limits<result_type>::max(); } |
| 4761 | |
| 4762 | /** |
| 4763 | * @brief Generating functions. |
| 4764 | */ |
| 4765 | template<typename _UniformRandomNumberGenerator> |
| 4766 | result_type |
| 4767 | operator()(_UniformRandomNumberGenerator& __urng) |
| 4768 | { return this->operator()(__urng, _M_param); } |
| 4769 | |
| 4770 | template<typename _UniformRandomNumberGenerator> |
| 4771 | result_type |
| 4772 | operator()(_UniformRandomNumberGenerator& __urng, |
| 4773 | const param_type& __p); |
| 4774 | |
| 4775 | template<typename _ForwardIterator, |
| 4776 | typename _UniformRandomNumberGenerator> |
| 4777 | void |
| 4778 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 4779 | _UniformRandomNumberGenerator& __urng) |
| 4780 | { this->__generate(__f, __t, __urng, _M_param); } |
| 4781 | |
| 4782 | template<typename _ForwardIterator, |
| 4783 | typename _UniformRandomNumberGenerator> |
| 4784 | void |
| 4785 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 4786 | _UniformRandomNumberGenerator& __urng, |
| 4787 | const param_type& __p) |
| 4788 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 4789 | |
| 4790 | template<typename _UniformRandomNumberGenerator> |
| 4791 | void |
| 4792 | __generate(result_type* __f, result_type* __t, |
| 4793 | _UniformRandomNumberGenerator& __urng, |
| 4794 | const param_type& __p) |
| 4795 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 4796 | |
| 4797 | /** |
| 4798 | * @brief Return true if two Poisson distributions have the same |
| 4799 | * parameters and the sequences that would be generated |
| 4800 | * are equal. |
| 4801 | */ |
| 4802 | friend bool |
| 4803 | operator==(const poisson_distribution& __d1, |
| 4804 | const poisson_distribution& __d2) |
| 4805 | #ifdef _GLIBCXX_USE_C99_MATH_FUNCS |
| 4806 | { return __d1._M_param == __d2._M_param && __d1._M_nd == __d2._M_nd; } |
| 4807 | #else |
| 4808 | { return __d1._M_param == __d2._M_param; } |
| 4809 | #endif |
| 4810 | |
| 4811 | /** |
| 4812 | * @brief Inserts a %poisson_distribution random number distribution |
| 4813 | * @p __x into the output stream @p __os. |
| 4814 | * |
| 4815 | * @param __os An output stream. |
| 4816 | * @param __x A %poisson_distribution random number distribution. |
| 4817 | * |
| 4818 | * @returns The output stream with the state of @p __x inserted or in |
| 4819 | * an error state. |
| 4820 | */ |
| 4821 | template<typename _IntType1, typename _CharT, typename _Traits> |
| 4822 | friend std::basic_ostream<_CharT, _Traits>& |
| 4823 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 4824 | const std::poisson_distribution<_IntType1>& __x); |
| 4825 | |
| 4826 | /** |
| 4827 | * @brief Extracts a %poisson_distribution random number distribution |
| 4828 | * @p __x from the input stream @p __is. |
| 4829 | * |
| 4830 | * @param __is An input stream. |
| 4831 | * @param __x A %poisson_distribution random number generator engine. |
| 4832 | * |
| 4833 | * @returns The input stream with @p __x extracted or in an error |
| 4834 | * state. |
| 4835 | */ |
| 4836 | template<typename _IntType1, typename _CharT, typename _Traits> |
| 4837 | friend std::basic_istream<_CharT, _Traits>& |
| 4838 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 4839 | std::poisson_distribution<_IntType1>& __x); |
| 4840 | |
| 4841 | private: |
| 4842 | template<typename _ForwardIterator, |
| 4843 | typename _UniformRandomNumberGenerator> |
| 4844 | void |
| 4845 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
| 4846 | _UniformRandomNumberGenerator& __urng, |
| 4847 | const param_type& __p); |
| 4848 | |
| 4849 | param_type _M_param; |
| 4850 | |
| 4851 | // NB: Unused when _GLIBCXX_USE_C99_MATH_FUNCS is undefined. |
| 4852 | std::normal_distribution<double> _M_nd; |
| 4853 | }; |
| 4854 | |
| 4855 | #if __cpp_impl_three_way_comparison < 201907L |
| 4856 | /** |
| 4857 | * @brief Return true if two Poisson distributions are different. |
| 4858 | */ |
| 4859 | template<typename _IntType> |
| 4860 | inline bool |
| 4861 | operator!=(const std::poisson_distribution<_IntType>& __d1, |
| 4862 | const std::poisson_distribution<_IntType>& __d2) |
| 4863 | { return !(__d1 == __d2); } |
| 4864 | #endif |
| 4865 | |
| 4866 | /** |
| 4867 | * @brief An exponential continuous distribution for random numbers. |
| 4868 | * |
| 4869 | * The formula for the exponential probability density function is |
| 4870 | * @f$p(x|\lambda) = \lambda e^{-\lambda x}@f$. |
| 4871 | * |
| 4872 | * <table border=1 cellpadding=10 cellspacing=0> |
| 4873 | * <caption align=top>Distribution Statistics</caption> |
| 4874 | * <tr><td>Mean</td><td>@f$\frac{1}{\lambda}@f$</td></tr> |
| 4875 | * <tr><td>Median</td><td>@f$\frac{\ln 2}{\lambda}@f$</td></tr> |
| 4876 | * <tr><td>Mode</td><td>@f$zero@f$</td></tr> |
| 4877 | * <tr><td>Range</td><td>@f$[0, \infty]@f$</td></tr> |
| 4878 | * <tr><td>Standard Deviation</td><td>@f$\frac{1}{\lambda}@f$</td></tr> |
| 4879 | * </table> |
| 4880 | * |
| 4881 | * @headerfile random |
| 4882 | * @since C++11 |
| 4883 | */ |
| 4884 | template<typename _RealType = double> |
| 4885 | class exponential_distribution |
| 4886 | { |
| 4887 | static_assert(std::is_floating_point<_RealType>::value, |
| 4888 | "result_type must be a floating point type"); |
| 4889 | |
| 4890 | public: |
| 4891 | /** The type of the range of the distribution. */ |
| 4892 | typedef _RealType result_type; |
| 4893 | |
| 4894 | /** Parameter type. */ |
| 4895 | struct param_type |
| 4896 | { |
| 4897 | typedef exponential_distribution<_RealType> distribution_type; |
| 4898 | |
| 4899 | param_type() : param_type(1.0) { } |
| 4900 | |
| 4901 | explicit |
| 4902 | param_type(_RealType __lambda) |
| 4903 | : _M_lambda(__lambda) |
| 4904 | { |
| 4905 | __glibcxx_assert(_M_lambda > _RealType(0)); |
| 4906 | } |
| 4907 | |
| 4908 | _RealType |
| 4909 | lambda() const |
| 4910 | { return _M_lambda; } |
| 4911 | |
| 4912 | friend bool |
| 4913 | operator==(const param_type& __p1, const param_type& __p2) |
| 4914 | { return __p1._M_lambda == __p2._M_lambda; } |
| 4915 | |
| 4916 | #if __cpp_impl_three_way_comparison < 201907L |
| 4917 | friend bool |
| 4918 | operator!=(const param_type& __p1, const param_type& __p2) |
| 4919 | { return !(__p1 == __p2); } |
| 4920 | #endif |
| 4921 | |
| 4922 | private: |
| 4923 | _RealType _M_lambda; |
| 4924 | }; |
| 4925 | |
| 4926 | public: |
| 4927 | /** |
| 4928 | * @brief Constructs an exponential distribution with inverse scale |
| 4929 | * parameter 1.0 |
| 4930 | */ |
| 4931 | exponential_distribution() : exponential_distribution(1.0) { } |
| 4932 | |
| 4933 | /** |
| 4934 | * @brief Constructs an exponential distribution with inverse scale |
| 4935 | * parameter @f$\lambda@f$. |
| 4936 | */ |
| 4937 | explicit |
| 4938 | exponential_distribution(_RealType __lambda) |
| 4939 | : _M_param(__lambda) |
| 4940 | { } |
| 4941 | |
| 4942 | explicit |
| 4943 | exponential_distribution(const param_type& __p) |
| 4944 | : _M_param(__p) |
| 4945 | { } |
| 4946 | |
| 4947 | /** |
| 4948 | * @brief Resets the distribution state. |
| 4949 | * |
| 4950 | * Has no effect on exponential distributions. |
| 4951 | */ |
| 4952 | void |
| 4953 | reset() { } |
| 4954 | |
| 4955 | /** |
| 4956 | * @brief Returns the inverse scale parameter of the distribution. |
| 4957 | */ |
| 4958 | _RealType |
| 4959 | lambda() const |
| 4960 | { return _M_param.lambda(); } |
| 4961 | |
| 4962 | /** |
| 4963 | * @brief Returns the parameter set of the distribution. |
| 4964 | */ |
| 4965 | param_type |
| 4966 | param() const |
| 4967 | { return _M_param; } |
| 4968 | |
| 4969 | /** |
| 4970 | * @brief Sets the parameter set of the distribution. |
| 4971 | * @param __param The new parameter set of the distribution. |
| 4972 | */ |
| 4973 | void |
| 4974 | param(const param_type& __param) |
| 4975 | { _M_param = __param; } |
| 4976 | |
| 4977 | /** |
| 4978 | * @brief Returns the greatest lower bound value of the distribution. |
| 4979 | */ |
| 4980 | result_type |
| 4981 | min() const |
| 4982 | { return result_type(0); } |
| 4983 | |
| 4984 | /** |
| 4985 | * @brief Returns the least upper bound value of the distribution. |
| 4986 | */ |
| 4987 | result_type |
| 4988 | max() const |
| 4989 | { return std::numeric_limits<result_type>::max(); } |
| 4990 | |
| 4991 | /** |
| 4992 | * @brief Generating functions. |
| 4993 | */ |
| 4994 | template<typename _UniformRandomNumberGenerator> |
| 4995 | result_type |
| 4996 | operator()(_UniformRandomNumberGenerator& __urng) |
| 4997 | { return this->operator()(__urng, _M_param); } |
| 4998 | |
| 4999 | template<typename _UniformRandomNumberGenerator> |
| 5000 | result_type |
| 5001 | operator()(_UniformRandomNumberGenerator& __urng, |
| 5002 | const param_type& __p) |
| 5003 | { |
| 5004 | __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> |
| 5005 | __aurng(__urng); |
| 5006 | return -std::log(result_type(1) - __aurng()) / __p.lambda(); |
| 5007 | } |
| 5008 | |
| 5009 | template<typename _ForwardIterator, |
| 5010 | typename _UniformRandomNumberGenerator> |
| 5011 | void |
| 5012 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 5013 | _UniformRandomNumberGenerator& __urng) |
| 5014 | { this->__generate(__f, __t, __urng, _M_param); } |
| 5015 | |
| 5016 | template<typename _ForwardIterator, |
| 5017 | typename _UniformRandomNumberGenerator> |
| 5018 | void |
| 5019 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 5020 | _UniformRandomNumberGenerator& __urng, |
| 5021 | const param_type& __p) |
| 5022 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 5023 | |
| 5024 | template<typename _UniformRandomNumberGenerator> |
| 5025 | void |
| 5026 | __generate(result_type* __f, result_type* __t, |
| 5027 | _UniformRandomNumberGenerator& __urng, |
| 5028 | const param_type& __p) |
| 5029 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 5030 | |
| 5031 | /** |
| 5032 | * @brief Return true if two exponential distributions have the same |
| 5033 | * parameters. |
| 5034 | */ |
| 5035 | friend bool |
| 5036 | operator==(const exponential_distribution& __d1, |
| 5037 | const exponential_distribution& __d2) |
| 5038 | { return __d1._M_param == __d2._M_param; } |
| 5039 | |
| 5040 | private: |
| 5041 | template<typename _ForwardIterator, |
| 5042 | typename _UniformRandomNumberGenerator> |
| 5043 | void |
| 5044 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
| 5045 | _UniformRandomNumberGenerator& __urng, |
| 5046 | const param_type& __p); |
| 5047 | |
| 5048 | param_type _M_param; |
| 5049 | }; |
| 5050 | |
| 5051 | #if __cpp_impl_three_way_comparison < 201907L |
| 5052 | /** |
| 5053 | * @brief Return true if two exponential distributions have different |
| 5054 | * parameters. |
| 5055 | */ |
| 5056 | template<typename _RealType> |
| 5057 | inline bool |
| 5058 | operator!=(const std::exponential_distribution<_RealType>& __d1, |
| 5059 | const std::exponential_distribution<_RealType>& __d2) |
| 5060 | { return !(__d1 == __d2); } |
| 5061 | #endif |
| 5062 | |
| 5063 | /** |
| 5064 | * @brief Inserts a %exponential_distribution random number distribution |
| 5065 | * @p __x into the output stream @p __os. |
| 5066 | * |
| 5067 | * @param __os An output stream. |
| 5068 | * @param __x A %exponential_distribution random number distribution. |
| 5069 | * |
| 5070 | * @returns The output stream with the state of @p __x inserted or in |
| 5071 | * an error state. |
| 5072 | */ |
| 5073 | template<typename _RealType, typename _CharT, typename _Traits> |
| 5074 | std::basic_ostream<_CharT, _Traits>& |
| 5075 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 5076 | const std::exponential_distribution<_RealType>& __x); |
| 5077 | |
| 5078 | /** |
| 5079 | * @brief Extracts a %exponential_distribution random number distribution |
| 5080 | * @p __x from the input stream @p __is. |
| 5081 | * |
| 5082 | * @param __is An input stream. |
| 5083 | * @param __x A %exponential_distribution random number |
| 5084 | * generator engine. |
| 5085 | * |
| 5086 | * @returns The input stream with @p __x extracted or in an error state. |
| 5087 | */ |
| 5088 | template<typename _RealType, typename _CharT, typename _Traits> |
| 5089 | std::basic_istream<_CharT, _Traits>& |
| 5090 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 5091 | std::exponential_distribution<_RealType>& __x); |
| 5092 | |
| 5093 | |
| 5094 | /** |
| 5095 | * @brief A weibull_distribution random number distribution. |
| 5096 | * |
| 5097 | * The formula for the normal probability density function is: |
| 5098 | * @f[ |
| 5099 | * p(x|\alpha,\beta) = \frac{\alpha}{\beta} (\frac{x}{\beta})^{\alpha-1} |
| 5100 | * \exp{(-(\frac{x}{\beta})^\alpha)} |
| 5101 | * @f] |
| 5102 | * |
| 5103 | * @headerfile random |
| 5104 | * @since C++11 |
| 5105 | */ |
| 5106 | template<typename _RealType = double> |
| 5107 | class weibull_distribution |
| 5108 | { |
| 5109 | static_assert(std::is_floating_point<_RealType>::value, |
| 5110 | "result_type must be a floating point type"); |
| 5111 | |
| 5112 | public: |
| 5113 | /** The type of the range of the distribution. */ |
| 5114 | typedef _RealType result_type; |
| 5115 | |
| 5116 | /** Parameter type. */ |
| 5117 | struct param_type |
| 5118 | { |
| 5119 | typedef weibull_distribution<_RealType> distribution_type; |
| 5120 | |
| 5121 | param_type() : param_type(1.0) { } |
| 5122 | |
| 5123 | explicit |
| 5124 | param_type(_RealType __a, _RealType __b = _RealType(1.0)) |
| 5125 | : _M_a(__a), _M_b(__b) |
| 5126 | { } |
| 5127 | |
| 5128 | _RealType |
| 5129 | a() const |
| 5130 | { return _M_a; } |
| 5131 | |
| 5132 | _RealType |
| 5133 | b() const |
| 5134 | { return _M_b; } |
| 5135 | |
| 5136 | friend bool |
| 5137 | operator==(const param_type& __p1, const param_type& __p2) |
| 5138 | { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; } |
| 5139 | |
| 5140 | #if __cpp_impl_three_way_comparison < 201907L |
| 5141 | friend bool |
| 5142 | operator!=(const param_type& __p1, const param_type& __p2) |
| 5143 | { return !(__p1 == __p2); } |
| 5144 | #endif |
| 5145 | |
| 5146 | private: |
| 5147 | _RealType _M_a; |
| 5148 | _RealType _M_b; |
| 5149 | }; |
| 5150 | |
| 5151 | weibull_distribution() : weibull_distribution(1.0) { } |
| 5152 | |
| 5153 | explicit |
| 5154 | weibull_distribution(_RealType __a, _RealType __b = _RealType(1)) |
| 5155 | : _M_param(__a, __b) |
| 5156 | { } |
| 5157 | |
| 5158 | explicit |
| 5159 | weibull_distribution(const param_type& __p) |
| 5160 | : _M_param(__p) |
| 5161 | { } |
| 5162 | |
| 5163 | /** |
| 5164 | * @brief Resets the distribution state. |
| 5165 | */ |
| 5166 | void |
| 5167 | reset() |
| 5168 | { } |
| 5169 | |
| 5170 | /** |
| 5171 | * @brief Return the @f$a@f$ parameter of the distribution. |
| 5172 | */ |
| 5173 | _RealType |
| 5174 | a() const |
| 5175 | { return _M_param.a(); } |
| 5176 | |
| 5177 | /** |
| 5178 | * @brief Return the @f$b@f$ parameter of the distribution. |
| 5179 | */ |
| 5180 | _RealType |
| 5181 | b() const |
| 5182 | { return _M_param.b(); } |
| 5183 | |
| 5184 | /** |
| 5185 | * @brief Returns the parameter set of the distribution. |
| 5186 | */ |
| 5187 | param_type |
| 5188 | param() const |
| 5189 | { return _M_param; } |
| 5190 | |
| 5191 | /** |
| 5192 | * @brief Sets the parameter set of the distribution. |
| 5193 | * @param __param The new parameter set of the distribution. |
| 5194 | */ |
| 5195 | void |
| 5196 | param(const param_type& __param) |
| 5197 | { _M_param = __param; } |
| 5198 | |
| 5199 | /** |
| 5200 | * @brief Returns the greatest lower bound value of the distribution. |
| 5201 | */ |
| 5202 | result_type |
| 5203 | min() const |
| 5204 | { return result_type(0); } |
| 5205 | |
| 5206 | /** |
| 5207 | * @brief Returns the least upper bound value of the distribution. |
| 5208 | */ |
| 5209 | result_type |
| 5210 | max() const |
| 5211 | { return std::numeric_limits<result_type>::max(); } |
| 5212 | |
| 5213 | /** |
| 5214 | * @brief Generating functions. |
| 5215 | */ |
| 5216 | template<typename _UniformRandomNumberGenerator> |
| 5217 | result_type |
| 5218 | operator()(_UniformRandomNumberGenerator& __urng) |
| 5219 | { return this->operator()(__urng, _M_param); } |
| 5220 | |
| 5221 | template<typename _UniformRandomNumberGenerator> |
| 5222 | result_type |
| 5223 | operator()(_UniformRandomNumberGenerator& __urng, |
| 5224 | const param_type& __p); |
| 5225 | |
| 5226 | template<typename _ForwardIterator, |
| 5227 | typename _UniformRandomNumberGenerator> |
| 5228 | void |
| 5229 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 5230 | _UniformRandomNumberGenerator& __urng) |
| 5231 | { this->__generate(__f, __t, __urng, _M_param); } |
| 5232 | |
| 5233 | template<typename _ForwardIterator, |
| 5234 | typename _UniformRandomNumberGenerator> |
| 5235 | void |
| 5236 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 5237 | _UniformRandomNumberGenerator& __urng, |
| 5238 | const param_type& __p) |
| 5239 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 5240 | |
| 5241 | template<typename _UniformRandomNumberGenerator> |
| 5242 | void |
| 5243 | __generate(result_type* __f, result_type* __t, |
| 5244 | _UniformRandomNumberGenerator& __urng, |
| 5245 | const param_type& __p) |
| 5246 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 5247 | |
| 5248 | /** |
| 5249 | * @brief Return true if two Weibull distributions have the same |
| 5250 | * parameters. |
| 5251 | */ |
| 5252 | friend bool |
| 5253 | operator==(const weibull_distribution& __d1, |
| 5254 | const weibull_distribution& __d2) |
| 5255 | { return __d1._M_param == __d2._M_param; } |
| 5256 | |
| 5257 | private: |
| 5258 | template<typename _ForwardIterator, |
| 5259 | typename _UniformRandomNumberGenerator> |
| 5260 | void |
| 5261 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
| 5262 | _UniformRandomNumberGenerator& __urng, |
| 5263 | const param_type& __p); |
| 5264 | |
| 5265 | param_type _M_param; |
| 5266 | }; |
| 5267 | |
| 5268 | #if __cpp_impl_three_way_comparison < 201907L |
| 5269 | /** |
| 5270 | * @brief Return true if two Weibull distributions have different |
| 5271 | * parameters. |
| 5272 | */ |
| 5273 | template<typename _RealType> |
| 5274 | inline bool |
| 5275 | operator!=(const std::weibull_distribution<_RealType>& __d1, |
| 5276 | const std::weibull_distribution<_RealType>& __d2) |
| 5277 | { return !(__d1 == __d2); } |
| 5278 | #endif |
| 5279 | |
| 5280 | /** |
| 5281 | * @brief Inserts a %weibull_distribution random number distribution |
| 5282 | * @p __x into the output stream @p __os. |
| 5283 | * |
| 5284 | * @param __os An output stream. |
| 5285 | * @param __x A %weibull_distribution random number distribution. |
| 5286 | * |
| 5287 | * @returns The output stream with the state of @p __x inserted or in |
| 5288 | * an error state. |
| 5289 | */ |
| 5290 | template<typename _RealType, typename _CharT, typename _Traits> |
| 5291 | std::basic_ostream<_CharT, _Traits>& |
| 5292 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 5293 | const std::weibull_distribution<_RealType>& __x); |
| 5294 | |
| 5295 | /** |
| 5296 | * @brief Extracts a %weibull_distribution random number distribution |
| 5297 | * @p __x from the input stream @p __is. |
| 5298 | * |
| 5299 | * @param __is An input stream. |
| 5300 | * @param __x A %weibull_distribution random number |
| 5301 | * generator engine. |
| 5302 | * |
| 5303 | * @returns The input stream with @p __x extracted or in an error state. |
| 5304 | */ |
| 5305 | template<typename _RealType, typename _CharT, typename _Traits> |
| 5306 | std::basic_istream<_CharT, _Traits>& |
| 5307 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 5308 | std::weibull_distribution<_RealType>& __x); |
| 5309 | |
| 5310 | |
| 5311 | /** |
| 5312 | * @brief A extreme_value_distribution random number distribution. |
| 5313 | * |
| 5314 | * The formula for the normal probability mass function is |
| 5315 | * @f[ |
| 5316 | * p(x|a,b) = \frac{1}{b} |
| 5317 | * \exp( \frac{a-x}{b} - \exp(\frac{a-x}{b})) |
| 5318 | * @f] |
| 5319 | * |
| 5320 | * @headerfile random |
| 5321 | * @since C++11 |
| 5322 | */ |
| 5323 | template<typename _RealType = double> |
| 5324 | class extreme_value_distribution |
| 5325 | { |
| 5326 | static_assert(std::is_floating_point<_RealType>::value, |
| 5327 | "result_type must be a floating point type"); |
| 5328 | |
| 5329 | public: |
| 5330 | /** The type of the range of the distribution. */ |
| 5331 | typedef _RealType result_type; |
| 5332 | |
| 5333 | /** Parameter type. */ |
| 5334 | struct param_type |
| 5335 | { |
| 5336 | typedef extreme_value_distribution<_RealType> distribution_type; |
| 5337 | |
| 5338 | param_type() : param_type(0.0) { } |
| 5339 | |
| 5340 | explicit |
| 5341 | param_type(_RealType __a, _RealType __b = _RealType(1.0)) |
| 5342 | : _M_a(__a), _M_b(__b) |
| 5343 | { } |
| 5344 | |
| 5345 | _RealType |
| 5346 | a() const |
| 5347 | { return _M_a; } |
| 5348 | |
| 5349 | _RealType |
| 5350 | b() const |
| 5351 | { return _M_b; } |
| 5352 | |
| 5353 | friend bool |
| 5354 | operator==(const param_type& __p1, const param_type& __p2) |
| 5355 | { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; } |
| 5356 | |
| 5357 | #if __cpp_impl_three_way_comparison < 201907L |
| 5358 | friend bool |
| 5359 | operator!=(const param_type& __p1, const param_type& __p2) |
| 5360 | { return !(__p1 == __p2); } |
| 5361 | #endif |
| 5362 | |
| 5363 | private: |
| 5364 | _RealType _M_a; |
| 5365 | _RealType _M_b; |
| 5366 | }; |
| 5367 | |
| 5368 | extreme_value_distribution() : extreme_value_distribution(0.0) { } |
| 5369 | |
| 5370 | explicit |
| 5371 | extreme_value_distribution(_RealType __a, _RealType __b = _RealType(1)) |
| 5372 | : _M_param(__a, __b) |
| 5373 | { } |
| 5374 | |
| 5375 | explicit |
| 5376 | extreme_value_distribution(const param_type& __p) |
| 5377 | : _M_param(__p) |
| 5378 | { } |
| 5379 | |
| 5380 | /** |
| 5381 | * @brief Resets the distribution state. |
| 5382 | */ |
| 5383 | void |
| 5384 | reset() |
| 5385 | { } |
| 5386 | |
| 5387 | /** |
| 5388 | * @brief Return the @f$a@f$ parameter of the distribution. |
| 5389 | */ |
| 5390 | _RealType |
| 5391 | a() const |
| 5392 | { return _M_param.a(); } |
| 5393 | |
| 5394 | /** |
| 5395 | * @brief Return the @f$b@f$ parameter of the distribution. |
| 5396 | */ |
| 5397 | _RealType |
| 5398 | b() const |
| 5399 | { return _M_param.b(); } |
| 5400 | |
| 5401 | /** |
| 5402 | * @brief Returns the parameter set of the distribution. |
| 5403 | */ |
| 5404 | param_type |
| 5405 | param() const |
| 5406 | { return _M_param; } |
| 5407 | |
| 5408 | /** |
| 5409 | * @brief Sets the parameter set of the distribution. |
| 5410 | * @param __param The new parameter set of the distribution. |
| 5411 | */ |
| 5412 | void |
| 5413 | param(const param_type& __param) |
| 5414 | { _M_param = __param; } |
| 5415 | |
| 5416 | /** |
| 5417 | * @brief Returns the greatest lower bound value of the distribution. |
| 5418 | */ |
| 5419 | result_type |
| 5420 | min() const |
| 5421 | { return std::numeric_limits<result_type>::lowest(); } |
| 5422 | |
| 5423 | /** |
| 5424 | * @brief Returns the least upper bound value of the distribution. |
| 5425 | */ |
| 5426 | result_type |
| 5427 | max() const |
| 5428 | { return std::numeric_limits<result_type>::max(); } |
| 5429 | |
| 5430 | /** |
| 5431 | * @brief Generating functions. |
| 5432 | */ |
| 5433 | template<typename _UniformRandomNumberGenerator> |
| 5434 | result_type |
| 5435 | operator()(_UniformRandomNumberGenerator& __urng) |
| 5436 | { return this->operator()(__urng, _M_param); } |
| 5437 | |
| 5438 | template<typename _UniformRandomNumberGenerator> |
| 5439 | result_type |
| 5440 | operator()(_UniformRandomNumberGenerator& __urng, |
| 5441 | const param_type& __p); |
| 5442 | |
| 5443 | template<typename _ForwardIterator, |
| 5444 | typename _UniformRandomNumberGenerator> |
| 5445 | void |
| 5446 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 5447 | _UniformRandomNumberGenerator& __urng) |
| 5448 | { this->__generate(__f, __t, __urng, _M_param); } |
| 5449 | |
| 5450 | template<typename _ForwardIterator, |
| 5451 | typename _UniformRandomNumberGenerator> |
| 5452 | void |
| 5453 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 5454 | _UniformRandomNumberGenerator& __urng, |
| 5455 | const param_type& __p) |
| 5456 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 5457 | |
| 5458 | template<typename _UniformRandomNumberGenerator> |
| 5459 | void |
| 5460 | __generate(result_type* __f, result_type* __t, |
| 5461 | _UniformRandomNumberGenerator& __urng, |
| 5462 | const param_type& __p) |
| 5463 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 5464 | |
| 5465 | /** |
| 5466 | * @brief Return true if two extreme value distributions have the same |
| 5467 | * parameters. |
| 5468 | */ |
| 5469 | friend bool |
| 5470 | operator==(const extreme_value_distribution& __d1, |
| 5471 | const extreme_value_distribution& __d2) |
| 5472 | { return __d1._M_param == __d2._M_param; } |
| 5473 | |
| 5474 | private: |
| 5475 | template<typename _ForwardIterator, |
| 5476 | typename _UniformRandomNumberGenerator> |
| 5477 | void |
| 5478 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
| 5479 | _UniformRandomNumberGenerator& __urng, |
| 5480 | const param_type& __p); |
| 5481 | |
| 5482 | param_type _M_param; |
| 5483 | }; |
| 5484 | |
| 5485 | #if __cpp_impl_three_way_comparison < 201907L |
| 5486 | /** |
| 5487 | * @brief Return true if two extreme value distributions have different |
| 5488 | * parameters. |
| 5489 | */ |
| 5490 | template<typename _RealType> |
| 5491 | inline bool |
| 5492 | operator!=(const std::extreme_value_distribution<_RealType>& __d1, |
| 5493 | const std::extreme_value_distribution<_RealType>& __d2) |
| 5494 | { return !(__d1 == __d2); } |
| 5495 | #endif |
| 5496 | |
| 5497 | /** |
| 5498 | * @brief Inserts a %extreme_value_distribution random number distribution |
| 5499 | * @p __x into the output stream @p __os. |
| 5500 | * |
| 5501 | * @param __os An output stream. |
| 5502 | * @param __x A %extreme_value_distribution random number distribution. |
| 5503 | * |
| 5504 | * @returns The output stream with the state of @p __x inserted or in |
| 5505 | * an error state. |
| 5506 | */ |
| 5507 | template<typename _RealType, typename _CharT, typename _Traits> |
| 5508 | std::basic_ostream<_CharT, _Traits>& |
| 5509 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 5510 | const std::extreme_value_distribution<_RealType>& __x); |
| 5511 | |
| 5512 | /** |
| 5513 | * @brief Extracts a %extreme_value_distribution random number |
| 5514 | * distribution @p __x from the input stream @p __is. |
| 5515 | * |
| 5516 | * @param __is An input stream. |
| 5517 | * @param __x A %extreme_value_distribution random number |
| 5518 | * generator engine. |
| 5519 | * |
| 5520 | * @returns The input stream with @p __x extracted or in an error state. |
| 5521 | */ |
| 5522 | template<typename _RealType, typename _CharT, typename _Traits> |
| 5523 | std::basic_istream<_CharT, _Traits>& |
| 5524 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 5525 | std::extreme_value_distribution<_RealType>& __x); |
| 5526 | |
| 5527 | /// @} group random_distributions_poisson |
| 5528 | |
| 5529 | /** |
| 5530 | * @addtogroup random_distributions_sampling Sampling Distributions |
| 5531 | * @ingroup random_distributions |
| 5532 | * @{ |
| 5533 | */ |
| 5534 | |
| 5535 | /** |
| 5536 | * @brief A discrete_distribution random number distribution. |
| 5537 | * |
| 5538 | * This distribution produces random numbers @f$ i, 0 \leq i < n @f$, |
| 5539 | * distributed according to the probability mass function |
| 5540 | * @f$ p(i | p_0, ..., p_{n-1}) = p_i @f$. |
| 5541 | * |
| 5542 | * @headerfile random |
| 5543 | * @since C++11 |
| 5544 | */ |
| 5545 | template<typename _IntType = int> |
| 5546 | class discrete_distribution |
| 5547 | { |
| 5548 | static_assert(std::is_integral<_IntType>::value, |
| 5549 | "result_type must be an integral type"); |
| 5550 | |
| 5551 | public: |
| 5552 | /** The type of the range of the distribution. */ |
| 5553 | typedef _IntType result_type; |
| 5554 | |
| 5555 | /** Parameter type. */ |
| 5556 | struct param_type |
| 5557 | { |
| 5558 | typedef discrete_distribution<_IntType> distribution_type; |
| 5559 | friend class discrete_distribution<_IntType>; |
| 5560 | |
| 5561 | param_type() |
| 5562 | : _M_prob(), _M_cp() |
| 5563 | { } |
| 5564 | |
| 5565 | template<typename _InputIterator> |
| 5566 | param_type(_InputIterator __wbegin, |
| 5567 | _InputIterator __wend) |
| 5568 | : _M_prob(__wbegin, __wend), _M_cp() |
| 5569 | { _M_initialize(); } |
| 5570 | |
| 5571 | param_type(initializer_list<double> __wil) |
| 5572 | : _M_prob(__wil.begin(), __wil.end()), _M_cp() |
| 5573 | { _M_initialize(); } |
| 5574 | |
| 5575 | template<typename _Func> |
| 5576 | param_type(size_t __nw, double __xmin, double __xmax, |
| 5577 | _Func __fw); |
| 5578 | |
| 5579 | // See: http://cpp-next.com/archive/2010/10/implicit-move-must-go/ |
| 5580 | param_type(const param_type&) = default; |
| 5581 | param_type& operator=(const param_type&) = default; |
| 5582 | |
| 5583 | std::vector<double> |
| 5584 | probabilities() const |
| 5585 | { return _M_prob.empty() ? std::vector<double>(1, 1.0) : _M_prob; } |
| 5586 | |
| 5587 | friend bool |
| 5588 | operator==(const param_type& __p1, const param_type& __p2) |
| 5589 | { return __p1._M_prob == __p2._M_prob; } |
| 5590 | |
| 5591 | #if __cpp_impl_three_way_comparison < 201907L |
| 5592 | friend bool |
| 5593 | operator!=(const param_type& __p1, const param_type& __p2) |
| 5594 | { return !(__p1 == __p2); } |
| 5595 | #endif |
| 5596 | |
| 5597 | private: |
| 5598 | void |
| 5599 | _M_initialize(); |
| 5600 | |
| 5601 | std::vector<double> _M_prob; |
| 5602 | std::vector<double> _M_cp; |
| 5603 | }; |
| 5604 | |
| 5605 | discrete_distribution() |
| 5606 | : _M_param() |
| 5607 | { } |
| 5608 | |
| 5609 | template<typename _InputIterator> |
| 5610 | discrete_distribution(_InputIterator __wbegin, |
| 5611 | _InputIterator __wend) |
| 5612 | : _M_param(__wbegin, __wend) |
| 5613 | { } |
| 5614 | |
| 5615 | discrete_distribution(initializer_list<double> __wl) |
| 5616 | : _M_param(__wl) |
| 5617 | { } |
| 5618 | |
| 5619 | template<typename _Func> |
| 5620 | discrete_distribution(size_t __nw, double __xmin, double __xmax, |
| 5621 | _Func __fw) |
| 5622 | : _M_param(__nw, __xmin, __xmax, __fw) |
| 5623 | { } |
| 5624 | |
| 5625 | explicit |
| 5626 | discrete_distribution(const param_type& __p) |
| 5627 | : _M_param(__p) |
| 5628 | { } |
| 5629 | |
| 5630 | /** |
| 5631 | * @brief Resets the distribution state. |
| 5632 | */ |
| 5633 | void |
| 5634 | reset() |
| 5635 | { } |
| 5636 | |
| 5637 | /** |
| 5638 | * @brief Returns the probabilities of the distribution. |
| 5639 | */ |
| 5640 | std::vector<double> |
| 5641 | probabilities() const |
| 5642 | { |
| 5643 | return _M_param._M_prob.empty() |
| 5644 | ? std::vector<double>(1, 1.0) : _M_param._M_prob; |
| 5645 | } |
| 5646 | |
| 5647 | /** |
| 5648 | * @brief Returns the parameter set of the distribution. |
| 5649 | */ |
| 5650 | param_type |
| 5651 | param() const |
| 5652 | { return _M_param; } |
| 5653 | |
| 5654 | /** |
| 5655 | * @brief Sets the parameter set of the distribution. |
| 5656 | * @param __param The new parameter set of the distribution. |
| 5657 | */ |
| 5658 | void |
| 5659 | param(const param_type& __param) |
| 5660 | { _M_param = __param; } |
| 5661 | |
| 5662 | /** |
| 5663 | * @brief Returns the greatest lower bound value of the distribution. |
| 5664 | */ |
| 5665 | result_type |
| 5666 | min() const |
| 5667 | { return result_type(0); } |
| 5668 | |
| 5669 | /** |
| 5670 | * @brief Returns the least upper bound value of the distribution. |
| 5671 | */ |
| 5672 | result_type |
| 5673 | max() const |
| 5674 | { |
| 5675 | return _M_param._M_prob.empty() |
| 5676 | ? result_type(0) : result_type(_M_param._M_prob.size() - 1); |
| 5677 | } |
| 5678 | |
| 5679 | /** |
| 5680 | * @brief Generating functions. |
| 5681 | */ |
| 5682 | template<typename _UniformRandomNumberGenerator> |
| 5683 | result_type |
| 5684 | operator()(_UniformRandomNumberGenerator& __urng) |
| 5685 | { return this->operator()(__urng, _M_param); } |
| 5686 | |
| 5687 | template<typename _UniformRandomNumberGenerator> |
| 5688 | result_type |
| 5689 | operator()(_UniformRandomNumberGenerator& __urng, |
| 5690 | const param_type& __p); |
| 5691 | |
| 5692 | template<typename _ForwardIterator, |
| 5693 | typename _UniformRandomNumberGenerator> |
| 5694 | void |
| 5695 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 5696 | _UniformRandomNumberGenerator& __urng) |
| 5697 | { this->__generate(__f, __t, __urng, _M_param); } |
| 5698 | |
| 5699 | template<typename _ForwardIterator, |
| 5700 | typename _UniformRandomNumberGenerator> |
| 5701 | void |
| 5702 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 5703 | _UniformRandomNumberGenerator& __urng, |
| 5704 | const param_type& __p) |
| 5705 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 5706 | |
| 5707 | template<typename _UniformRandomNumberGenerator> |
| 5708 | void |
| 5709 | __generate(result_type* __f, result_type* __t, |
| 5710 | _UniformRandomNumberGenerator& __urng, |
| 5711 | const param_type& __p) |
| 5712 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 5713 | |
| 5714 | /** |
| 5715 | * @brief Return true if two discrete distributions have the same |
| 5716 | * parameters. |
| 5717 | */ |
| 5718 | friend bool |
| 5719 | operator==(const discrete_distribution& __d1, |
| 5720 | const discrete_distribution& __d2) |
| 5721 | { return __d1._M_param == __d2._M_param; } |
| 5722 | |
| 5723 | /** |
| 5724 | * @brief Inserts a %discrete_distribution random number distribution |
| 5725 | * @p __x into the output stream @p __os. |
| 5726 | * |
| 5727 | * @param __os An output stream. |
| 5728 | * @param __x A %discrete_distribution random number distribution. |
| 5729 | * |
| 5730 | * @returns The output stream with the state of @p __x inserted or in |
| 5731 | * an error state. |
| 5732 | */ |
| 5733 | template<typename _IntType1, typename _CharT, typename _Traits> |
| 5734 | friend std::basic_ostream<_CharT, _Traits>& |
| 5735 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 5736 | const std::discrete_distribution<_IntType1>& __x); |
| 5737 | |
| 5738 | /** |
| 5739 | * @brief Extracts a %discrete_distribution random number distribution |
| 5740 | * @p __x from the input stream @p __is. |
| 5741 | * |
| 5742 | * @param __is An input stream. |
| 5743 | * @param __x A %discrete_distribution random number |
| 5744 | * generator engine. |
| 5745 | * |
| 5746 | * @returns The input stream with @p __x extracted or in an error |
| 5747 | * state. |
| 5748 | */ |
| 5749 | template<typename _IntType1, typename _CharT, typename _Traits> |
| 5750 | friend std::basic_istream<_CharT, _Traits>& |
| 5751 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 5752 | std::discrete_distribution<_IntType1>& __x); |
| 5753 | |
| 5754 | private: |
| 5755 | template<typename _ForwardIterator, |
| 5756 | typename _UniformRandomNumberGenerator> |
| 5757 | void |
| 5758 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
| 5759 | _UniformRandomNumberGenerator& __urng, |
| 5760 | const param_type& __p); |
| 5761 | |
| 5762 | param_type _M_param; |
| 5763 | }; |
| 5764 | |
| 5765 | #if __cpp_impl_three_way_comparison < 201907L |
| 5766 | /** |
| 5767 | * @brief Return true if two discrete distributions have different |
| 5768 | * parameters. |
| 5769 | */ |
| 5770 | template<typename _IntType> |
| 5771 | inline bool |
| 5772 | operator!=(const std::discrete_distribution<_IntType>& __d1, |
| 5773 | const std::discrete_distribution<_IntType>& __d2) |
| 5774 | { return !(__d1 == __d2); } |
| 5775 | #endif |
| 5776 | |
| 5777 | /** |
| 5778 | * @brief A piecewise_constant_distribution random number distribution. |
| 5779 | * |
| 5780 | * This distribution produces random numbers @f$ x, b_0 \leq x < b_n @f$, |
| 5781 | * uniformly distributed over each subinterval @f$ [b_i, b_{i+1}) @f$ |
| 5782 | * according to the probability mass function |
| 5783 | * @f[ |
| 5784 | * p(x | b_0, ..., b_n, \rho_0, ..., \rho_{n-1}) |
| 5785 | * = \rho_i \cdot \frac{b_{i+1} - x}{b_{i+1} - b_i} |
| 5786 | * + \rho_{i+1} \cdot \frac{ x - b_i}{b_{i+1} - b_i} |
| 5787 | * @f] |
| 5788 | * for @f$ b_i \leq x < b_{i+1} @f$. |
| 5789 | * |
| 5790 | * @headerfile random |
| 5791 | * @since C++11 |
| 5792 | */ |
| 5793 | template<typename _RealType = double> |
| 5794 | class piecewise_constant_distribution |
| 5795 | { |
| 5796 | static_assert(std::is_floating_point<_RealType>::value, |
| 5797 | "result_type must be a floating point type"); |
| 5798 | |
| 5799 | public: |
| 5800 | /** The type of the range of the distribution. */ |
| 5801 | typedef _RealType result_type; |
| 5802 | |
| 5803 | /** Parameter type. */ |
| 5804 | struct param_type |
| 5805 | { |
| 5806 | typedef piecewise_constant_distribution<_RealType> distribution_type; |
| 5807 | friend class piecewise_constant_distribution<_RealType>; |
| 5808 | |
| 5809 | param_type() |
| 5810 | : _M_int(), _M_den(), _M_cp() |
| 5811 | { } |
| 5812 | |
| 5813 | template<typename _InputIteratorB, typename _InputIteratorW> |
| 5814 | param_type(_InputIteratorB __bfirst, |
| 5815 | _InputIteratorB __bend, |
| 5816 | _InputIteratorW __wbegin); |
| 5817 | |
| 5818 | template<typename _Func> |
| 5819 | param_type(initializer_list<_RealType> __bi, _Func __fw); |
| 5820 | |
| 5821 | template<typename _Func> |
| 5822 | param_type(size_t __nw, _RealType __xmin, _RealType __xmax, |
| 5823 | _Func __fw); |
| 5824 | |
| 5825 | // See: http://cpp-next.com/archive/2010/10/implicit-move-must-go/ |
| 5826 | param_type(const param_type&) = default; |
| 5827 | param_type& operator=(const param_type&) = default; |
| 5828 | |
| 5829 | std::vector<_RealType> |
| 5830 | intervals() const |
| 5831 | { |
| 5832 | if (_M_int.empty()) |
| 5833 | { |
| 5834 | std::vector<_RealType> __tmp(2); |
| 5835 | __tmp[1] = _RealType(1); |
| 5836 | return __tmp; |
| 5837 | } |
| 5838 | else |
| 5839 | return _M_int; |
| 5840 | } |
| 5841 | |
| 5842 | std::vector<double> |
| 5843 | densities() const |
| 5844 | { return _M_den.empty() ? std::vector<double>(1, 1.0) : _M_den; } |
| 5845 | |
| 5846 | friend bool |
| 5847 | operator==(const param_type& __p1, const param_type& __p2) |
| 5848 | { return __p1._M_int == __p2._M_int && __p1._M_den == __p2._M_den; } |
| 5849 | |
| 5850 | #if __cpp_impl_three_way_comparison < 201907L |
| 5851 | friend bool |
| 5852 | operator!=(const param_type& __p1, const param_type& __p2) |
| 5853 | { return !(__p1 == __p2); } |
| 5854 | #endif |
| 5855 | |
| 5856 | private: |
| 5857 | void |
| 5858 | _M_initialize(); |
| 5859 | |
| 5860 | std::vector<_RealType> _M_int; |
| 5861 | std::vector<double> _M_den; |
| 5862 | std::vector<double> _M_cp; |
| 5863 | }; |
| 5864 | |
| 5865 | piecewise_constant_distribution() |
| 5866 | : _M_param() |
| 5867 | { } |
| 5868 | |
| 5869 | template<typename _InputIteratorB, typename _InputIteratorW> |
| 5870 | piecewise_constant_distribution(_InputIteratorB __bfirst, |
| 5871 | _InputIteratorB __bend, |
| 5872 | _InputIteratorW __wbegin) |
| 5873 | : _M_param(__bfirst, __bend, __wbegin) |
| 5874 | { } |
| 5875 | |
| 5876 | template<typename _Func> |
| 5877 | piecewise_constant_distribution(initializer_list<_RealType> __bl, |
| 5878 | _Func __fw) |
| 5879 | : _M_param(__bl, __fw) |
| 5880 | { } |
| 5881 | |
| 5882 | template<typename _Func> |
| 5883 | piecewise_constant_distribution(size_t __nw, |
| 5884 | _RealType __xmin, _RealType __xmax, |
| 5885 | _Func __fw) |
| 5886 | : _M_param(__nw, __xmin, __xmax, __fw) |
| 5887 | { } |
| 5888 | |
| 5889 | explicit |
| 5890 | piecewise_constant_distribution(const param_type& __p) |
| 5891 | : _M_param(__p) |
| 5892 | { } |
| 5893 | |
| 5894 | /** |
| 5895 | * @brief Resets the distribution state. |
| 5896 | */ |
| 5897 | void |
| 5898 | reset() |
| 5899 | { } |
| 5900 | |
| 5901 | /** |
| 5902 | * @brief Returns a vector of the intervals. |
| 5903 | */ |
| 5904 | std::vector<_RealType> |
| 5905 | intervals() const |
| 5906 | { |
| 5907 | if (_M_param._M_int.empty()) |
| 5908 | { |
| 5909 | std::vector<_RealType> __tmp(2); |
| 5910 | __tmp[1] = _RealType(1); |
| 5911 | return __tmp; |
| 5912 | } |
| 5913 | else |
| 5914 | return _M_param._M_int; |
| 5915 | } |
| 5916 | |
| 5917 | /** |
| 5918 | * @brief Returns a vector of the probability densities. |
| 5919 | */ |
| 5920 | std::vector<double> |
| 5921 | densities() const |
| 5922 | { |
| 5923 | return _M_param._M_den.empty() |
| 5924 | ? std::vector<double>(1, 1.0) : _M_param._M_den; |
| 5925 | } |
| 5926 | |
| 5927 | /** |
| 5928 | * @brief Returns the parameter set of the distribution. |
| 5929 | */ |
| 5930 | param_type |
| 5931 | param() const |
| 5932 | { return _M_param; } |
| 5933 | |
| 5934 | /** |
| 5935 | * @brief Sets the parameter set of the distribution. |
| 5936 | * @param __param The new parameter set of the distribution. |
| 5937 | */ |
| 5938 | void |
| 5939 | param(const param_type& __param) |
| 5940 | { _M_param = __param; } |
| 5941 | |
| 5942 | /** |
| 5943 | * @brief Returns the greatest lower bound value of the distribution. |
| 5944 | */ |
| 5945 | result_type |
| 5946 | min() const |
| 5947 | { |
| 5948 | return _M_param._M_int.empty() |
| 5949 | ? result_type(0) : _M_param._M_int.front(); |
| 5950 | } |
| 5951 | |
| 5952 | /** |
| 5953 | * @brief Returns the least upper bound value of the distribution. |
| 5954 | */ |
| 5955 | result_type |
| 5956 | max() const |
| 5957 | { |
| 5958 | return _M_param._M_int.empty() |
| 5959 | ? result_type(1) : _M_param._M_int.back(); |
| 5960 | } |
| 5961 | |
| 5962 | /** |
| 5963 | * @brief Generating functions. |
| 5964 | */ |
| 5965 | template<typename _UniformRandomNumberGenerator> |
| 5966 | result_type |
| 5967 | operator()(_UniformRandomNumberGenerator& __urng) |
| 5968 | { return this->operator()(__urng, _M_param); } |
| 5969 | |
| 5970 | template<typename _UniformRandomNumberGenerator> |
| 5971 | result_type |
| 5972 | operator()(_UniformRandomNumberGenerator& __urng, |
| 5973 | const param_type& __p); |
| 5974 | |
| 5975 | template<typename _ForwardIterator, |
| 5976 | typename _UniformRandomNumberGenerator> |
| 5977 | void |
| 5978 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 5979 | _UniformRandomNumberGenerator& __urng) |
| 5980 | { this->__generate(__f, __t, __urng, _M_param); } |
| 5981 | |
| 5982 | template<typename _ForwardIterator, |
| 5983 | typename _UniformRandomNumberGenerator> |
| 5984 | void |
| 5985 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 5986 | _UniformRandomNumberGenerator& __urng, |
| 5987 | const param_type& __p) |
| 5988 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 5989 | |
| 5990 | template<typename _UniformRandomNumberGenerator> |
| 5991 | void |
| 5992 | __generate(result_type* __f, result_type* __t, |
| 5993 | _UniformRandomNumberGenerator& __urng, |
| 5994 | const param_type& __p) |
| 5995 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 5996 | |
| 5997 | /** |
| 5998 | * @brief Return true if two piecewise constant distributions have the |
| 5999 | * same parameters. |
| 6000 | */ |
| 6001 | friend bool |
| 6002 | operator==(const piecewise_constant_distribution& __d1, |
| 6003 | const piecewise_constant_distribution& __d2) |
| 6004 | { return __d1._M_param == __d2._M_param; } |
| 6005 | |
| 6006 | /** |
| 6007 | * @brief Inserts a %piecewise_constant_distribution random |
| 6008 | * number distribution @p __x into the output stream @p __os. |
| 6009 | * |
| 6010 | * @param __os An output stream. |
| 6011 | * @param __x A %piecewise_constant_distribution random number |
| 6012 | * distribution. |
| 6013 | * |
| 6014 | * @returns The output stream with the state of @p __x inserted or in |
| 6015 | * an error state. |
| 6016 | */ |
| 6017 | template<typename _RealType1, typename _CharT, typename _Traits> |
| 6018 | friend std::basic_ostream<_CharT, _Traits>& |
| 6019 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 6020 | const std::piecewise_constant_distribution<_RealType1>& __x); |
| 6021 | |
| 6022 | /** |
| 6023 | * @brief Extracts a %piecewise_constant_distribution random |
| 6024 | * number distribution @p __x from the input stream @p __is. |
| 6025 | * |
| 6026 | * @param __is An input stream. |
| 6027 | * @param __x A %piecewise_constant_distribution random number |
| 6028 | * generator engine. |
| 6029 | * |
| 6030 | * @returns The input stream with @p __x extracted or in an error |
| 6031 | * state. |
| 6032 | */ |
| 6033 | template<typename _RealType1, typename _CharT, typename _Traits> |
| 6034 | friend std::basic_istream<_CharT, _Traits>& |
| 6035 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 6036 | std::piecewise_constant_distribution<_RealType1>& __x); |
| 6037 | |
| 6038 | private: |
| 6039 | template<typename _ForwardIterator, |
| 6040 | typename _UniformRandomNumberGenerator> |
| 6041 | void |
| 6042 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
| 6043 | _UniformRandomNumberGenerator& __urng, |
| 6044 | const param_type& __p); |
| 6045 | |
| 6046 | param_type _M_param; |
| 6047 | }; |
| 6048 | |
| 6049 | #if __cpp_impl_three_way_comparison < 201907L |
| 6050 | /** |
| 6051 | * @brief Return true if two piecewise constant distributions have |
| 6052 | * different parameters. |
| 6053 | */ |
| 6054 | template<typename _RealType> |
| 6055 | inline bool |
| 6056 | operator!=(const std::piecewise_constant_distribution<_RealType>& __d1, |
| 6057 | const std::piecewise_constant_distribution<_RealType>& __d2) |
| 6058 | { return !(__d1 == __d2); } |
| 6059 | #endif |
| 6060 | |
| 6061 | /** |
| 6062 | * @brief A piecewise_linear_distribution random number distribution. |
| 6063 | * |
| 6064 | * This distribution produces random numbers @f$ x, b_0 \leq x < b_n @f$, |
| 6065 | * distributed over each subinterval @f$ [b_i, b_{i+1}) @f$ |
| 6066 | * according to the probability mass function |
| 6067 | * @f$ p(x | b_0, ..., b_n, \rho_0, ..., \rho_n) = \rho_i @f$, |
| 6068 | * for @f$ b_i \leq x < b_{i+1} @f$. |
| 6069 | * |
| 6070 | * @headerfile random |
| 6071 | * @since C++11 |
| 6072 | */ |
| 6073 | template<typename _RealType = double> |
| 6074 | class piecewise_linear_distribution |
| 6075 | { |
| 6076 | static_assert(std::is_floating_point<_RealType>::value, |
| 6077 | "result_type must be a floating point type"); |
| 6078 | |
| 6079 | public: |
| 6080 | /** The type of the range of the distribution. */ |
| 6081 | typedef _RealType result_type; |
| 6082 | |
| 6083 | /** Parameter type. */ |
| 6084 | struct param_type |
| 6085 | { |
| 6086 | typedef piecewise_linear_distribution<_RealType> distribution_type; |
| 6087 | friend class piecewise_linear_distribution<_RealType>; |
| 6088 | |
| 6089 | param_type() |
| 6090 | : _M_int(), _M_den(), _M_cp(), _M_m() |
| 6091 | { } |
| 6092 | |
| 6093 | template<typename _InputIteratorB, typename _InputIteratorW> |
| 6094 | param_type(_InputIteratorB __bfirst, |
| 6095 | _InputIteratorB __bend, |
| 6096 | _InputIteratorW __wbegin); |
| 6097 | |
| 6098 | template<typename _Func> |
| 6099 | param_type(initializer_list<_RealType> __bl, _Func __fw); |
| 6100 | |
| 6101 | template<typename _Func> |
| 6102 | param_type(size_t __nw, _RealType __xmin, _RealType __xmax, |
| 6103 | _Func __fw); |
| 6104 | |
| 6105 | // See: http://cpp-next.com/archive/2010/10/implicit-move-must-go/ |
| 6106 | param_type(const param_type&) = default; |
| 6107 | param_type& operator=(const param_type&) = default; |
| 6108 | |
| 6109 | std::vector<_RealType> |
| 6110 | intervals() const |
| 6111 | { |
| 6112 | if (_M_int.empty()) |
| 6113 | { |
| 6114 | std::vector<_RealType> __tmp(2); |
| 6115 | __tmp[1] = _RealType(1); |
| 6116 | return __tmp; |
| 6117 | } |
| 6118 | else |
| 6119 | return _M_int; |
| 6120 | } |
| 6121 | |
| 6122 | std::vector<double> |
| 6123 | densities() const |
| 6124 | { return _M_den.empty() ? std::vector<double>(2, 1.0) : _M_den; } |
| 6125 | |
| 6126 | friend bool |
| 6127 | operator==(const param_type& __p1, const param_type& __p2) |
| 6128 | { return __p1._M_int == __p2._M_int && __p1._M_den == __p2._M_den; } |
| 6129 | |
| 6130 | #if __cpp_impl_three_way_comparison < 201907L |
| 6131 | friend bool |
| 6132 | operator!=(const param_type& __p1, const param_type& __p2) |
| 6133 | { return !(__p1 == __p2); } |
| 6134 | #endif |
| 6135 | |
| 6136 | private: |
| 6137 | void |
| 6138 | _M_initialize(); |
| 6139 | |
| 6140 | std::vector<_RealType> _M_int; |
| 6141 | std::vector<double> _M_den; |
| 6142 | std::vector<double> _M_cp; |
| 6143 | std::vector<double> _M_m; |
| 6144 | }; |
| 6145 | |
| 6146 | piecewise_linear_distribution() |
| 6147 | : _M_param() |
| 6148 | { } |
| 6149 | |
| 6150 | template<typename _InputIteratorB, typename _InputIteratorW> |
| 6151 | piecewise_linear_distribution(_InputIteratorB __bfirst, |
| 6152 | _InputIteratorB __bend, |
| 6153 | _InputIteratorW __wbegin) |
| 6154 | : _M_param(__bfirst, __bend, __wbegin) |
| 6155 | { } |
| 6156 | |
| 6157 | template<typename _Func> |
| 6158 | piecewise_linear_distribution(initializer_list<_RealType> __bl, |
| 6159 | _Func __fw) |
| 6160 | : _M_param(__bl, __fw) |
| 6161 | { } |
| 6162 | |
| 6163 | template<typename _Func> |
| 6164 | piecewise_linear_distribution(size_t __nw, |
| 6165 | _RealType __xmin, _RealType __xmax, |
| 6166 | _Func __fw) |
| 6167 | : _M_param(__nw, __xmin, __xmax, __fw) |
| 6168 | { } |
| 6169 | |
| 6170 | explicit |
| 6171 | piecewise_linear_distribution(const param_type& __p) |
| 6172 | : _M_param(__p) |
| 6173 | { } |
| 6174 | |
| 6175 | /** |
| 6176 | * Resets the distribution state. |
| 6177 | */ |
| 6178 | void |
| 6179 | reset() |
| 6180 | { } |
| 6181 | |
| 6182 | /** |
| 6183 | * @brief Return the intervals of the distribution. |
| 6184 | */ |
| 6185 | std::vector<_RealType> |
| 6186 | intervals() const |
| 6187 | { |
| 6188 | if (_M_param._M_int.empty()) |
| 6189 | { |
| 6190 | std::vector<_RealType> __tmp(2); |
| 6191 | __tmp[1] = _RealType(1); |
| 6192 | return __tmp; |
| 6193 | } |
| 6194 | else |
| 6195 | return _M_param._M_int; |
| 6196 | } |
| 6197 | |
| 6198 | /** |
| 6199 | * @brief Return a vector of the probability densities of the |
| 6200 | * distribution. |
| 6201 | */ |
| 6202 | std::vector<double> |
| 6203 | densities() const |
| 6204 | { |
| 6205 | return _M_param._M_den.empty() |
| 6206 | ? std::vector<double>(2, 1.0) : _M_param._M_den; |
| 6207 | } |
| 6208 | |
| 6209 | /** |
| 6210 | * @brief Returns the parameter set of the distribution. |
| 6211 | */ |
| 6212 | param_type |
| 6213 | param() const |
| 6214 | { return _M_param; } |
| 6215 | |
| 6216 | /** |
| 6217 | * @brief Sets the parameter set of the distribution. |
| 6218 | * @param __param The new parameter set of the distribution. |
| 6219 | */ |
| 6220 | void |
| 6221 | param(const param_type& __param) |
| 6222 | { _M_param = __param; } |
| 6223 | |
| 6224 | /** |
| 6225 | * @brief Returns the greatest lower bound value of the distribution. |
| 6226 | */ |
| 6227 | result_type |
| 6228 | min() const |
| 6229 | { |
| 6230 | return _M_param._M_int.empty() |
| 6231 | ? result_type(0) : _M_param._M_int.front(); |
| 6232 | } |
| 6233 | |
| 6234 | /** |
| 6235 | * @brief Returns the least upper bound value of the distribution. |
| 6236 | */ |
| 6237 | result_type |
| 6238 | max() const |
| 6239 | { |
| 6240 | return _M_param._M_int.empty() |
| 6241 | ? result_type(1) : _M_param._M_int.back(); |
| 6242 | } |
| 6243 | |
| 6244 | /** |
| 6245 | * @brief Generating functions. |
| 6246 | */ |
| 6247 | template<typename _UniformRandomNumberGenerator> |
| 6248 | result_type |
| 6249 | operator()(_UniformRandomNumberGenerator& __urng) |
| 6250 | { return this->operator()(__urng, _M_param); } |
| 6251 | |
| 6252 | template<typename _UniformRandomNumberGenerator> |
| 6253 | result_type |
| 6254 | operator()(_UniformRandomNumberGenerator& __urng, |
| 6255 | const param_type& __p); |
| 6256 | |
| 6257 | template<typename _ForwardIterator, |
| 6258 | typename _UniformRandomNumberGenerator> |
| 6259 | void |
| 6260 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 6261 | _UniformRandomNumberGenerator& __urng) |
| 6262 | { this->__generate(__f, __t, __urng, _M_param); } |
| 6263 | |
| 6264 | template<typename _ForwardIterator, |
| 6265 | typename _UniformRandomNumberGenerator> |
| 6266 | void |
| 6267 | __generate(_ForwardIterator __f, _ForwardIterator __t, |
| 6268 | _UniformRandomNumberGenerator& __urng, |
| 6269 | const param_type& __p) |
| 6270 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 6271 | |
| 6272 | template<typename _UniformRandomNumberGenerator> |
| 6273 | void |
| 6274 | __generate(result_type* __f, result_type* __t, |
| 6275 | _UniformRandomNumberGenerator& __urng, |
| 6276 | const param_type& __p) |
| 6277 | { this->__generate_impl(__f, __t, __urng, __p); } |
| 6278 | |
| 6279 | /** |
| 6280 | * @brief Return true if two piecewise linear distributions have the |
| 6281 | * same parameters. |
| 6282 | */ |
| 6283 | friend bool |
| 6284 | operator==(const piecewise_linear_distribution& __d1, |
| 6285 | const piecewise_linear_distribution& __d2) |
| 6286 | { return __d1._M_param == __d2._M_param; } |
| 6287 | |
| 6288 | /** |
| 6289 | * @brief Inserts a %piecewise_linear_distribution random number |
| 6290 | * distribution @p __x into the output stream @p __os. |
| 6291 | * |
| 6292 | * @param __os An output stream. |
| 6293 | * @param __x A %piecewise_linear_distribution random number |
| 6294 | * distribution. |
| 6295 | * |
| 6296 | * @returns The output stream with the state of @p __x inserted or in |
| 6297 | * an error state. |
| 6298 | */ |
| 6299 | template<typename _RealType1, typename _CharT, typename _Traits> |
| 6300 | friend std::basic_ostream<_CharT, _Traits>& |
| 6301 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 6302 | const std::piecewise_linear_distribution<_RealType1>& __x); |
| 6303 | |
| 6304 | /** |
| 6305 | * @brief Extracts a %piecewise_linear_distribution random number |
| 6306 | * distribution @p __x from the input stream @p __is. |
| 6307 | * |
| 6308 | * @param __is An input stream. |
| 6309 | * @param __x A %piecewise_linear_distribution random number |
| 6310 | * generator engine. |
| 6311 | * |
| 6312 | * @returns The input stream with @p __x extracted or in an error |
| 6313 | * state. |
| 6314 | */ |
| 6315 | template<typename _RealType1, typename _CharT, typename _Traits> |
| 6316 | friend std::basic_istream<_CharT, _Traits>& |
| 6317 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 6318 | std::piecewise_linear_distribution<_RealType1>& __x); |
| 6319 | |
| 6320 | private: |
| 6321 | template<typename _ForwardIterator, |
| 6322 | typename _UniformRandomNumberGenerator> |
| 6323 | void |
| 6324 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
| 6325 | _UniformRandomNumberGenerator& __urng, |
| 6326 | const param_type& __p); |
| 6327 | |
| 6328 | param_type _M_param; |
| 6329 | }; |
| 6330 | |
| 6331 | #if __cpp_impl_three_way_comparison < 201907L |
| 6332 | /** |
| 6333 | * @brief Return true if two piecewise linear distributions have |
| 6334 | * different parameters. |
| 6335 | */ |
| 6336 | template<typename _RealType> |
| 6337 | inline bool |
| 6338 | operator!=(const std::piecewise_linear_distribution<_RealType>& __d1, |
| 6339 | const std::piecewise_linear_distribution<_RealType>& __d2) |
| 6340 | { return !(__d1 == __d2); } |
| 6341 | #endif |
| 6342 | |
| 6343 | /// @} group random_distributions_sampling |
| 6344 | |
| 6345 | /// @} *group random_distributions |
| 6346 | |
| 6347 | /** |
| 6348 | * @addtogroup random_utilities Random Number Utilities |
| 6349 | * @ingroup random |
| 6350 | * @{ |
| 6351 | */ |
| 6352 | |
| 6353 | /** |
| 6354 | * @brief The seed_seq class generates sequences of seeds for random |
| 6355 | * number generators. |
| 6356 | * |
| 6357 | * @headerfile random |
| 6358 | * @since C++11 |
| 6359 | */ |
| 6360 | class seed_seq |
| 6361 | { |
| 6362 | public: |
| 6363 | /** The type of the seed vales. */ |
| 6364 | typedef uint_least32_t result_type; |
| 6365 | |
| 6366 | /** Default constructor. */ |
| 6367 | seed_seq() noexcept |
| 6368 | : _M_v() |
| 6369 | { } |
| 6370 | |
| 6371 | template<typename _IntType, typename = _Require<is_integral<_IntType>>> |
| 6372 | seed_seq(std::initializer_list<_IntType> __il); |
| 6373 | |
| 6374 | template<typename _InputIterator> |
| 6375 | seed_seq(_InputIterator __begin, _InputIterator __end); |
| 6376 | |
| 6377 | // generating functions |
| 6378 | template<typename _RandomAccessIterator> |
| 6379 | void |
| 6380 | generate(_RandomAccessIterator __begin, _RandomAccessIterator __end); |
| 6381 | |
| 6382 | // property functions |
| 6383 | size_t size() const noexcept |
| 6384 | { return _M_v.size(); } |
| 6385 | |
| 6386 | template<typename _OutputIterator> |
| 6387 | void |
| 6388 | param(_OutputIterator __dest) const |
| 6389 | { std::copy(_M_v.begin(), _M_v.end(), __dest); } |
| 6390 | |
| 6391 | // no copy functions |
| 6392 | seed_seq(const seed_seq&) = delete; |
| 6393 | seed_seq& operator=(const seed_seq&) = delete; |
| 6394 | |
| 6395 | private: |
| 6396 | std::vector<result_type> _M_v; |
| 6397 | }; |
| 6398 | |
| 6399 | /// @} group random_utilities |
| 6400 | |
| 6401 | /// @} group random |
| 6402 | |
| 6403 | _GLIBCXX_END_NAMESPACE_VERSION |
| 6404 | } // namespace std |
| 6405 | |
| 6406 | #endif |
| 6407 |
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