| dcfbfb22 |
1 | // Random number extensions -*- C++ -*- |
| 2 | |
| fbd26352 |
3 | // Copyright (C) 2012-2019 Free Software Foundation, Inc. |
| dcfbfb22 |
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 | /** @file ext/random.tcc |
| 26 | * This is an internal header file, included by other library headers. |
| 27 | * Do not attempt to use it directly. @headername{ext/random} |
| 28 | */ |
| 29 | |
| 30 | #ifndef _EXT_RANDOM_TCC |
| 31 | #define _EXT_RANDOM_TCC 1 |
| 32 | |
| 33 | #pragma GCC system_header |
| 34 | |
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35 | namespace __gnu_cxx _GLIBCXX_VISIBILITY(default) |
| 36 | { |
| 37 | _GLIBCXX_BEGIN_NAMESPACE_VERSION |
| 38 | |
| 011ea24c |
39 | #if __BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__ |
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40 | |
| 41 | template<typename _UIntType, size_t __m, |
| 42 | size_t __pos1, size_t __sl1, size_t __sl2, |
| 43 | size_t __sr1, size_t __sr2, |
| 44 | uint32_t __msk1, uint32_t __msk2, |
| 45 | uint32_t __msk3, uint32_t __msk4, |
| 46 | uint32_t __parity1, uint32_t __parity2, |
| 47 | uint32_t __parity3, uint32_t __parity4> |
| 48 | void simd_fast_mersenne_twister_engine<_UIntType, __m, |
| 49 | __pos1, __sl1, __sl2, __sr1, __sr2, |
| 50 | __msk1, __msk2, __msk3, __msk4, |
| 51 | __parity1, __parity2, __parity3, |
| 52 | __parity4>:: |
| 53 | seed(_UIntType __seed) |
| 54 | { |
| 55 | _M_state32[0] = static_cast<uint32_t>(__seed); |
| 56 | for (size_t __i = 1; __i < _M_nstate32; ++__i) |
| 57 | _M_state32[__i] = (1812433253UL |
| 58 | * (_M_state32[__i - 1] ^ (_M_state32[__i - 1] >> 30)) |
| 59 | + __i); |
| 60 | _M_pos = state_size; |
| 61 | _M_period_certification(); |
| 62 | } |
| 63 | |
| 64 | |
| 65 | namespace { |
| 66 | |
| 67 | inline uint32_t _Func1(uint32_t __x) |
| 68 | { |
| 69 | return (__x ^ (__x >> 27)) * UINT32_C(1664525); |
| 70 | } |
| 71 | |
| 72 | inline uint32_t _Func2(uint32_t __x) |
| 73 | { |
| 74 | return (__x ^ (__x >> 27)) * UINT32_C(1566083941); |
| 75 | } |
| 76 | |
| 77 | } |
| 78 | |
| 79 | |
| 80 | template<typename _UIntType, size_t __m, |
| 81 | size_t __pos1, size_t __sl1, size_t __sl2, |
| 82 | size_t __sr1, size_t __sr2, |
| 83 | uint32_t __msk1, uint32_t __msk2, |
| 84 | uint32_t __msk3, uint32_t __msk4, |
| 85 | uint32_t __parity1, uint32_t __parity2, |
| 86 | uint32_t __parity3, uint32_t __parity4> |
| 87 | template<typename _Sseq> |
| cae1d5ed |
88 | auto |
| dcfbfb22 |
89 | simd_fast_mersenne_twister_engine<_UIntType, __m, |
| 90 | __pos1, __sl1, __sl2, __sr1, __sr2, |
| 91 | __msk1, __msk2, __msk3, __msk4, |
| 92 | __parity1, __parity2, __parity3, |
| 93 | __parity4>:: |
| 94 | seed(_Sseq& __q) |
| cae1d5ed |
95 | -> _If_seed_seq<_Sseq> |
| dcfbfb22 |
96 | { |
| 97 | size_t __lag; |
| 98 | |
| 99 | if (_M_nstate32 >= 623) |
| 100 | __lag = 11; |
| 101 | else if (_M_nstate32 >= 68) |
| 102 | __lag = 7; |
| 103 | else if (_M_nstate32 >= 39) |
| 104 | __lag = 5; |
| 105 | else |
| 106 | __lag = 3; |
| 107 | const size_t __mid = (_M_nstate32 - __lag) / 2; |
| 108 | |
| 109 | std::fill(_M_state32, _M_state32 + _M_nstate32, UINT32_C(0x8b8b8b8b)); |
| 110 | uint32_t __arr[_M_nstate32]; |
| 111 | __q.generate(__arr + 0, __arr + _M_nstate32); |
| 112 | |
| 113 | uint32_t __r = _Func1(_M_state32[0] ^ _M_state32[__mid] |
| 114 | ^ _M_state32[_M_nstate32 - 1]); |
| 115 | _M_state32[__mid] += __r; |
| 116 | __r += _M_nstate32; |
| 117 | _M_state32[__mid + __lag] += __r; |
| 118 | _M_state32[0] = __r; |
| 119 | |
| 120 | for (size_t __i = 1, __j = 0; __j < _M_nstate32; ++__j) |
| 121 | { |
| 122 | __r = _Func1(_M_state32[__i] |
| 123 | ^ _M_state32[(__i + __mid) % _M_nstate32] |
| 124 | ^ _M_state32[(__i + _M_nstate32 - 1) % _M_nstate32]); |
| 125 | _M_state32[(__i + __mid) % _M_nstate32] += __r; |
| 126 | __r += __arr[__j] + __i; |
| 127 | _M_state32[(__i + __mid + __lag) % _M_nstate32] += __r; |
| 128 | _M_state32[__i] = __r; |
| 129 | __i = (__i + 1) % _M_nstate32; |
| 130 | } |
| 131 | for (size_t __j = 0; __j < _M_nstate32; ++__j) |
| 132 | { |
| 133 | const size_t __i = (__j + 1) % _M_nstate32; |
| 134 | __r = _Func2(_M_state32[__i] |
| 135 | + _M_state32[(__i + __mid) % _M_nstate32] |
| 136 | + _M_state32[(__i + _M_nstate32 - 1) % _M_nstate32]); |
| 137 | _M_state32[(__i + __mid) % _M_nstate32] ^= __r; |
| 138 | __r -= __i; |
| 139 | _M_state32[(__i + __mid + __lag) % _M_nstate32] ^= __r; |
| 140 | _M_state32[__i] = __r; |
| 141 | } |
| 142 | |
| 143 | _M_pos = state_size; |
| 144 | _M_period_certification(); |
| 145 | } |
| 146 | |
| 147 | |
| 148 | template<typename _UIntType, size_t __m, |
| 149 | size_t __pos1, size_t __sl1, size_t __sl2, |
| 150 | size_t __sr1, size_t __sr2, |
| 151 | uint32_t __msk1, uint32_t __msk2, |
| 152 | uint32_t __msk3, uint32_t __msk4, |
| 153 | uint32_t __parity1, uint32_t __parity2, |
| 154 | uint32_t __parity3, uint32_t __parity4> |
| 155 | void simd_fast_mersenne_twister_engine<_UIntType, __m, |
| 156 | __pos1, __sl1, __sl2, __sr1, __sr2, |
| 157 | __msk1, __msk2, __msk3, __msk4, |
| 158 | __parity1, __parity2, __parity3, |
| 159 | __parity4>:: |
| 160 | _M_period_certification(void) |
| 161 | { |
| 162 | static const uint32_t __parity[4] = { __parity1, __parity2, |
| 163 | __parity3, __parity4 }; |
| 164 | uint32_t __inner = 0; |
| 165 | for (size_t __i = 0; __i < 4; ++__i) |
| 166 | if (__parity[__i] != 0) |
| 167 | __inner ^= _M_state32[__i] & __parity[__i]; |
| 168 | |
| 169 | if (__builtin_parity(__inner) & 1) |
| 170 | return; |
| 171 | for (size_t __i = 0; __i < 4; ++__i) |
| 172 | if (__parity[__i] != 0) |
| 173 | { |
| 174 | _M_state32[__i] ^= 1 << (__builtin_ffs(__parity[__i]) - 1); |
| 175 | return; |
| 176 | } |
| 177 | __builtin_unreachable(); |
| 178 | } |
| 179 | |
| 180 | |
| 181 | template<typename _UIntType, size_t __m, |
| 182 | size_t __pos1, size_t __sl1, size_t __sl2, |
| 183 | size_t __sr1, size_t __sr2, |
| 184 | uint32_t __msk1, uint32_t __msk2, |
| 185 | uint32_t __msk3, uint32_t __msk4, |
| 186 | uint32_t __parity1, uint32_t __parity2, |
| 187 | uint32_t __parity3, uint32_t __parity4> |
| 188 | void simd_fast_mersenne_twister_engine<_UIntType, __m, |
| 189 | __pos1, __sl1, __sl2, __sr1, __sr2, |
| 190 | __msk1, __msk2, __msk3, __msk4, |
| 191 | __parity1, __parity2, __parity3, |
| 192 | __parity4>:: |
| 193 | discard(unsigned long long __z) |
| 194 | { |
| 195 | while (__z > state_size - _M_pos) |
| 196 | { |
| 197 | __z -= state_size - _M_pos; |
| 198 | |
| 199 | _M_gen_rand(); |
| 200 | } |
| 201 | |
| 202 | _M_pos += __z; |
| 203 | } |
| 204 | |
| 205 | |
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206 | #ifndef _GLIBCXX_OPT_HAVE_RANDOM_SFMT_GEN_READ |
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207 | |
| 208 | namespace { |
| 209 | |
| 210 | template<size_t __shift> |
| 211 | inline void __rshift(uint32_t *__out, const uint32_t *__in) |
| 212 | { |
| 213 | uint64_t __th = ((static_cast<uint64_t>(__in[3]) << 32) |
| 214 | | static_cast<uint64_t>(__in[2])); |
| 215 | uint64_t __tl = ((static_cast<uint64_t>(__in[1]) << 32) |
| 216 | | static_cast<uint64_t>(__in[0])); |
| 217 | |
| 218 | uint64_t __oh = __th >> (__shift * 8); |
| 219 | uint64_t __ol = __tl >> (__shift * 8); |
| 220 | __ol |= __th << (64 - __shift * 8); |
| 221 | __out[1] = static_cast<uint32_t>(__ol >> 32); |
| 222 | __out[0] = static_cast<uint32_t>(__ol); |
| 223 | __out[3] = static_cast<uint32_t>(__oh >> 32); |
| 224 | __out[2] = static_cast<uint32_t>(__oh); |
| 225 | } |
| 226 | |
| 227 | |
| 228 | template<size_t __shift> |
| 229 | inline void __lshift(uint32_t *__out, const uint32_t *__in) |
| 230 | { |
| 231 | uint64_t __th = ((static_cast<uint64_t>(__in[3]) << 32) |
| 232 | | static_cast<uint64_t>(__in[2])); |
| 233 | uint64_t __tl = ((static_cast<uint64_t>(__in[1]) << 32) |
| 234 | | static_cast<uint64_t>(__in[0])); |
| 235 | |
| 236 | uint64_t __oh = __th << (__shift * 8); |
| 237 | uint64_t __ol = __tl << (__shift * 8); |
| 238 | __oh |= __tl >> (64 - __shift * 8); |
| 239 | __out[1] = static_cast<uint32_t>(__ol >> 32); |
| 240 | __out[0] = static_cast<uint32_t>(__ol); |
| 241 | __out[3] = static_cast<uint32_t>(__oh >> 32); |
| 242 | __out[2] = static_cast<uint32_t>(__oh); |
| 243 | } |
| 244 | |
| 245 | |
| 246 | template<size_t __sl1, size_t __sl2, size_t __sr1, size_t __sr2, |
| 247 | uint32_t __msk1, uint32_t __msk2, uint32_t __msk3, uint32_t __msk4> |
| 248 | inline void __recursion(uint32_t *__r, |
| 249 | const uint32_t *__a, const uint32_t *__b, |
| 250 | const uint32_t *__c, const uint32_t *__d) |
| 251 | { |
| 252 | uint32_t __x[4]; |
| 253 | uint32_t __y[4]; |
| 254 | |
| 255 | __lshift<__sl2>(__x, __a); |
| 256 | __rshift<__sr2>(__y, __c); |
| 257 | __r[0] = (__a[0] ^ __x[0] ^ ((__b[0] >> __sr1) & __msk1) |
| 258 | ^ __y[0] ^ (__d[0] << __sl1)); |
| 259 | __r[1] = (__a[1] ^ __x[1] ^ ((__b[1] >> __sr1) & __msk2) |
| 260 | ^ __y[1] ^ (__d[1] << __sl1)); |
| 261 | __r[2] = (__a[2] ^ __x[2] ^ ((__b[2] >> __sr1) & __msk3) |
| 262 | ^ __y[2] ^ (__d[2] << __sl1)); |
| 263 | __r[3] = (__a[3] ^ __x[3] ^ ((__b[3] >> __sr1) & __msk4) |
| 264 | ^ __y[3] ^ (__d[3] << __sl1)); |
| 265 | } |
| 266 | |
| 267 | } |
| 268 | |
| 269 | |
| 270 | template<typename _UIntType, size_t __m, |
| 271 | size_t __pos1, size_t __sl1, size_t __sl2, |
| 272 | size_t __sr1, size_t __sr2, |
| 273 | uint32_t __msk1, uint32_t __msk2, |
| 274 | uint32_t __msk3, uint32_t __msk4, |
| 275 | uint32_t __parity1, uint32_t __parity2, |
| 276 | uint32_t __parity3, uint32_t __parity4> |
| 277 | void simd_fast_mersenne_twister_engine<_UIntType, __m, |
| 278 | __pos1, __sl1, __sl2, __sr1, __sr2, |
| 279 | __msk1, __msk2, __msk3, __msk4, |
| 280 | __parity1, __parity2, __parity3, |
| 281 | __parity4>:: |
| 282 | _M_gen_rand(void) |
| 283 | { |
| 284 | const uint32_t *__r1 = &_M_state32[_M_nstate32 - 8]; |
| 285 | const uint32_t *__r2 = &_M_state32[_M_nstate32 - 4]; |
| 286 | static constexpr size_t __pos1_32 = __pos1 * 4; |
| 287 | |
| 288 | size_t __i; |
| 289 | for (__i = 0; __i < _M_nstate32 - __pos1_32; __i += 4) |
| 290 | { |
| 291 | __recursion<__sl1, __sl2, __sr1, __sr2, |
| 292 | __msk1, __msk2, __msk3, __msk4> |
| 293 | (&_M_state32[__i], &_M_state32[__i], |
| 294 | &_M_state32[__i + __pos1_32], __r1, __r2); |
| 295 | __r1 = __r2; |
| 296 | __r2 = &_M_state32[__i]; |
| 297 | } |
| 298 | |
| 299 | for (; __i < _M_nstate32; __i += 4) |
| 300 | { |
| 301 | __recursion<__sl1, __sl2, __sr1, __sr2, |
| 302 | __msk1, __msk2, __msk3, __msk4> |
| 303 | (&_M_state32[__i], &_M_state32[__i], |
| 304 | &_M_state32[__i + __pos1_32 - _M_nstate32], __r1, __r2); |
| 305 | __r1 = __r2; |
| 306 | __r2 = &_M_state32[__i]; |
| 307 | } |
| 308 | |
| 309 | _M_pos = 0; |
| 310 | } |
| 311 | |
| 312 | #endif |
| 313 | |
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314 | #ifndef _GLIBCXX_OPT_HAVE_RANDOM_SFMT_OPERATOREQUAL |
| 315 | template<typename _UIntType, size_t __m, |
| 316 | size_t __pos1, size_t __sl1, size_t __sl2, |
| 317 | size_t __sr1, size_t __sr2, |
| 318 | uint32_t __msk1, uint32_t __msk2, |
| 319 | uint32_t __msk3, uint32_t __msk4, |
| 320 | uint32_t __parity1, uint32_t __parity2, |
| 321 | uint32_t __parity3, uint32_t __parity4> |
| 322 | bool |
| 323 | operator==(const __gnu_cxx::simd_fast_mersenne_twister_engine<_UIntType, |
| 324 | __m, __pos1, __sl1, __sl2, __sr1, __sr2, |
| 325 | __msk1, __msk2, __msk3, __msk4, |
| 326 | __parity1, __parity2, __parity3, __parity4>& __lhs, |
| 327 | const __gnu_cxx::simd_fast_mersenne_twister_engine<_UIntType, |
| 328 | __m, __pos1, __sl1, __sl2, __sr1, __sr2, |
| 329 | __msk1, __msk2, __msk3, __msk4, |
| 330 | __parity1, __parity2, __parity3, __parity4>& __rhs) |
| 331 | { |
| ea08aea4 |
332 | typedef __gnu_cxx::simd_fast_mersenne_twister_engine<_UIntType, |
| 333 | __m, __pos1, __sl1, __sl2, __sr1, __sr2, |
| 334 | __msk1, __msk2, __msk3, __msk4, |
| 335 | __parity1, __parity2, __parity3, __parity4> __engine; |
| 336 | return (std::equal(__lhs._M_stateT, |
| 337 | __lhs._M_stateT + __engine::state_size, |
| a6e71142 |
338 | __rhs._M_stateT) |
| 339 | && __lhs._M_pos == __rhs._M_pos); |
| 340 | } |
| 341 | #endif |
| dcfbfb22 |
342 | |
| 343 | template<typename _UIntType, size_t __m, |
| 344 | size_t __pos1, size_t __sl1, size_t __sl2, |
| 345 | size_t __sr1, size_t __sr2, |
| 346 | uint32_t __msk1, uint32_t __msk2, |
| 347 | uint32_t __msk3, uint32_t __msk4, |
| 348 | uint32_t __parity1, uint32_t __parity2, |
| 349 | uint32_t __parity3, uint32_t __parity4, |
| 350 | typename _CharT, typename _Traits> |
| 351 | std::basic_ostream<_CharT, _Traits>& |
| 352 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 353 | const __gnu_cxx::simd_fast_mersenne_twister_engine<_UIntType, |
| 354 | __m, __pos1, __sl1, __sl2, __sr1, __sr2, |
| 355 | __msk1, __msk2, __msk3, __msk4, |
| 356 | __parity1, __parity2, __parity3, __parity4>& __x) |
| 357 | { |
| 358 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; |
| 359 | typedef typename __ostream_type::ios_base __ios_base; |
| 360 | |
| 361 | const typename __ios_base::fmtflags __flags = __os.flags(); |
| 362 | const _CharT __fill = __os.fill(); |
| 363 | const _CharT __space = __os.widen(' '); |
| 364 | __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left); |
| 365 | __os.fill(__space); |
| 366 | |
| 367 | for (size_t __i = 0; __i < __x._M_nstate32; ++__i) |
| 368 | __os << __x._M_state32[__i] << __space; |
| 369 | __os << __x._M_pos; |
| 370 | |
| 371 | __os.flags(__flags); |
| 372 | __os.fill(__fill); |
| 373 | return __os; |
| 374 | } |
| 375 | |
| 376 | |
| 377 | template<typename _UIntType, size_t __m, |
| 378 | size_t __pos1, size_t __sl1, size_t __sl2, |
| 379 | size_t __sr1, size_t __sr2, |
| 380 | uint32_t __msk1, uint32_t __msk2, |
| 381 | uint32_t __msk3, uint32_t __msk4, |
| 382 | uint32_t __parity1, uint32_t __parity2, |
| 383 | uint32_t __parity3, uint32_t __parity4, |
| 384 | typename _CharT, typename _Traits> |
| 385 | std::basic_istream<_CharT, _Traits>& |
| 386 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 387 | __gnu_cxx::simd_fast_mersenne_twister_engine<_UIntType, |
| 388 | __m, __pos1, __sl1, __sl2, __sr1, __sr2, |
| 389 | __msk1, __msk2, __msk3, __msk4, |
| 390 | __parity1, __parity2, __parity3, __parity4>& __x) |
| 391 | { |
| 392 | typedef std::basic_istream<_CharT, _Traits> __istream_type; |
| 393 | typedef typename __istream_type::ios_base __ios_base; |
| 394 | |
| 395 | const typename __ios_base::fmtflags __flags = __is.flags(); |
| 396 | __is.flags(__ios_base::dec | __ios_base::skipws); |
| 397 | |
| 398 | for (size_t __i = 0; __i < __x._M_nstate32; ++__i) |
| 399 | __is >> __x._M_state32[__i]; |
| 400 | __is >> __x._M_pos; |
| 401 | |
| 402 | __is.flags(__flags); |
| 403 | return __is; |
| 404 | } |
| 405 | |
| 011ea24c |
406 | #endif // __BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__ |
| 13d7b546 |
407 | |
| 408 | /** |
| 409 | * Iteration method due to M.D. J<o:>hnk. |
| 410 | * |
| 411 | * M.D. J<o:>hnk, Erzeugung von betaverteilten und gammaverteilten |
| 412 | * Zufallszahlen, Metrika, Volume 8, 1964 |
| 413 | */ |
| 414 | template<typename _RealType> |
| 415 | template<typename _UniformRandomNumberGenerator> |
| 416 | typename beta_distribution<_RealType>::result_type |
| 417 | beta_distribution<_RealType>:: |
| 418 | operator()(_UniformRandomNumberGenerator& __urng, |
| 419 | const param_type& __param) |
| 420 | { |
| 421 | std::__detail::_Adaptor<_UniformRandomNumberGenerator, result_type> |
| 422 | __aurng(__urng); |
| 423 | |
| 424 | result_type __x, __y; |
| 425 | do |
| 426 | { |
| 427 | __x = std::exp(std::log(__aurng()) / __param.alpha()); |
| 428 | __y = std::exp(std::log(__aurng()) / __param.beta()); |
| 429 | } |
| 430 | while (__x + __y > result_type(1)); |
| 431 | |
| 432 | return __x / (__x + __y); |
| 433 | } |
| 434 | |
| 435 | template<typename _RealType> |
| 436 | template<typename _OutputIterator, |
| 437 | typename _UniformRandomNumberGenerator> |
| 438 | void |
| 439 | beta_distribution<_RealType>:: |
| 440 | __generate_impl(_OutputIterator __f, _OutputIterator __t, |
| 441 | _UniformRandomNumberGenerator& __urng, |
| 442 | const param_type& __param) |
| 443 | { |
| 4a611aa2 |
444 | __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator, |
| 445 | result_type>) |
| 13d7b546 |
446 | |
| 447 | std::__detail::_Adaptor<_UniformRandomNumberGenerator, result_type> |
| 448 | __aurng(__urng); |
| 449 | |
| 450 | while (__f != __t) |
| 451 | { |
| 452 | result_type __x, __y; |
| 453 | do |
| 454 | { |
| 455 | __x = std::exp(std::log(__aurng()) / __param.alpha()); |
| 456 | __y = std::exp(std::log(__aurng()) / __param.beta()); |
| 457 | } |
| 458 | while (__x + __y > result_type(1)); |
| 459 | |
| 460 | *__f++ = __x / (__x + __y); |
| 461 | } |
| 462 | } |
| 463 | |
| 464 | template<typename _RealType, typename _CharT, typename _Traits> |
| 465 | std::basic_ostream<_CharT, _Traits>& |
| 466 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 467 | const __gnu_cxx::beta_distribution<_RealType>& __x) |
| 468 | { |
| 469 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; |
| 470 | typedef typename __ostream_type::ios_base __ios_base; |
| 471 | |
| 472 | const typename __ios_base::fmtflags __flags = __os.flags(); |
| 473 | const _CharT __fill = __os.fill(); |
| 474 | const std::streamsize __precision = __os.precision(); |
| 475 | const _CharT __space = __os.widen(' '); |
| 476 | __os.flags(__ios_base::scientific | __ios_base::left); |
| 477 | __os.fill(__space); |
| 478 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
| 479 | |
| 480 | __os << __x.alpha() << __space << __x.beta(); |
| 481 | |
| 482 | __os.flags(__flags); |
| 483 | __os.fill(__fill); |
| 484 | __os.precision(__precision); |
| 485 | return __os; |
| 486 | } |
| 487 | |
| 488 | template<typename _RealType, typename _CharT, typename _Traits> |
| 489 | std::basic_istream<_CharT, _Traits>& |
| 490 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 491 | __gnu_cxx::beta_distribution<_RealType>& __x) |
| 492 | { |
| 493 | typedef std::basic_istream<_CharT, _Traits> __istream_type; |
| 494 | typedef typename __istream_type::ios_base __ios_base; |
| 495 | |
| 496 | const typename __ios_base::fmtflags __flags = __is.flags(); |
| 497 | __is.flags(__ios_base::dec | __ios_base::skipws); |
| 498 | |
| 499 | _RealType __alpha_val, __beta_val; |
| 500 | __is >> __alpha_val >> __beta_val; |
| 501 | __x.param(typename __gnu_cxx::beta_distribution<_RealType>:: |
| 502 | param_type(__alpha_val, __beta_val)); |
| 503 | |
| 504 | __is.flags(__flags); |
| 505 | return __is; |
| 506 | } |
| 507 | |
| 6b46354d |
508 | |
| 509 | template<std::size_t _Dimen, typename _RealType> |
| 510 | template<typename _InputIterator1, typename _InputIterator2> |
| 511 | void |
| 512 | normal_mv_distribution<_Dimen, _RealType>::param_type:: |
| 513 | _M_init_full(_InputIterator1 __meanbegin, _InputIterator1 __meanend, |
| 514 | _InputIterator2 __varcovbegin, _InputIterator2 __varcovend) |
| 515 | { |
| 516 | __glibcxx_function_requires(_InputIteratorConcept<_InputIterator1>) |
| 517 | __glibcxx_function_requires(_InputIteratorConcept<_InputIterator2>) |
| 518 | std::fill(std::copy(__meanbegin, __meanend, _M_mean.begin()), |
| 519 | _M_mean.end(), _RealType(0)); |
| 520 | |
| 521 | // Perform the Cholesky decomposition |
| 522 | auto __w = _M_t.begin(); |
| 523 | for (size_t __j = 0; __j < _Dimen; ++__j) |
| 524 | { |
| 525 | _RealType __sum = _RealType(0); |
| 526 | |
| 527 | auto __slitbegin = __w; |
| 528 | auto __cit = _M_t.begin(); |
| 529 | for (size_t __i = 0; __i < __j; ++__i) |
| 530 | { |
| 531 | auto __slit = __slitbegin; |
| 532 | _RealType __s = *__varcovbegin++; |
| 533 | for (size_t __k = 0; __k < __i; ++__k) |
| 534 | __s -= *__slit++ * *__cit++; |
| 535 | |
| 536 | *__w++ = __s /= *__cit++; |
| 537 | __sum += __s * __s; |
| 538 | } |
| 539 | |
| 540 | __sum = *__varcovbegin - __sum; |
| 541 | if (__builtin_expect(__sum <= _RealType(0), 0)) |
| 542 | std::__throw_runtime_error(__N("normal_mv_distribution::" |
| 543 | "param_type::_M_init_full")); |
| 544 | *__w++ = std::sqrt(__sum); |
| 545 | |
| 546 | std::advance(__varcovbegin, _Dimen - __j); |
| 547 | } |
| 548 | } |
| 549 | |
| 550 | template<std::size_t _Dimen, typename _RealType> |
| 551 | template<typename _InputIterator1, typename _InputIterator2> |
| 552 | void |
| 553 | normal_mv_distribution<_Dimen, _RealType>::param_type:: |
| 554 | _M_init_lower(_InputIterator1 __meanbegin, _InputIterator1 __meanend, |
| 555 | _InputIterator2 __varcovbegin, _InputIterator2 __varcovend) |
| 556 | { |
| 557 | __glibcxx_function_requires(_InputIteratorConcept<_InputIterator1>) |
| 558 | __glibcxx_function_requires(_InputIteratorConcept<_InputIterator2>) |
| 559 | std::fill(std::copy(__meanbegin, __meanend, _M_mean.begin()), |
| 560 | _M_mean.end(), _RealType(0)); |
| 561 | |
| 562 | // Perform the Cholesky decomposition |
| 563 | auto __w = _M_t.begin(); |
| 564 | for (size_t __j = 0; __j < _Dimen; ++__j) |
| 565 | { |
| 566 | _RealType __sum = _RealType(0); |
| 567 | |
| 568 | auto __slitbegin = __w; |
| 569 | auto __cit = _M_t.begin(); |
| 570 | for (size_t __i = 0; __i < __j; ++__i) |
| 571 | { |
| 572 | auto __slit = __slitbegin; |
| 573 | _RealType __s = *__varcovbegin++; |
| 574 | for (size_t __k = 0; __k < __i; ++__k) |
| 575 | __s -= *__slit++ * *__cit++; |
| 576 | |
| 577 | *__w++ = __s /= *__cit++; |
| 578 | __sum += __s * __s; |
| 579 | } |
| 580 | |
| 581 | __sum = *__varcovbegin++ - __sum; |
| 582 | if (__builtin_expect(__sum <= _RealType(0), 0)) |
| 583 | std::__throw_runtime_error(__N("normal_mv_distribution::" |
| 584 | "param_type::_M_init_full")); |
| 585 | *__w++ = std::sqrt(__sum); |
| 586 | } |
| 587 | } |
| 588 | |
| 589 | template<std::size_t _Dimen, typename _RealType> |
| 590 | template<typename _InputIterator1, typename _InputIterator2> |
| 591 | void |
| 592 | normal_mv_distribution<_Dimen, _RealType>::param_type:: |
| 593 | _M_init_diagonal(_InputIterator1 __meanbegin, _InputIterator1 __meanend, |
| 594 | _InputIterator2 __varbegin, _InputIterator2 __varend) |
| 595 | { |
| 596 | __glibcxx_function_requires(_InputIteratorConcept<_InputIterator1>) |
| 597 | __glibcxx_function_requires(_InputIteratorConcept<_InputIterator2>) |
| 598 | std::fill(std::copy(__meanbegin, __meanend, _M_mean.begin()), |
| 599 | _M_mean.end(), _RealType(0)); |
| 600 | |
| 601 | auto __w = _M_t.begin(); |
| 602 | size_t __step = 0; |
| 603 | while (__varbegin != __varend) |
| 604 | { |
| 605 | std::fill_n(__w, __step, _RealType(0)); |
| 606 | __w += __step++; |
| 607 | if (__builtin_expect(*__varbegin < _RealType(0), 0)) |
| 608 | std::__throw_runtime_error(__N("normal_mv_distribution::" |
| 609 | "param_type::_M_init_diagonal")); |
| 610 | *__w++ = std::sqrt(*__varbegin++); |
| 611 | } |
| 612 | } |
| 613 | |
| 614 | template<std::size_t _Dimen, typename _RealType> |
| 615 | template<typename _UniformRandomNumberGenerator> |
| 616 | typename normal_mv_distribution<_Dimen, _RealType>::result_type |
| 617 | normal_mv_distribution<_Dimen, _RealType>:: |
| 618 | operator()(_UniformRandomNumberGenerator& __urng, |
| 619 | const param_type& __param) |
| 620 | { |
| 621 | result_type __ret; |
| 622 | |
| 8237461c |
623 | _M_nd.__generate(__ret.begin(), __ret.end(), __urng); |
| 6b46354d |
624 | |
| 625 | auto __t_it = __param._M_t.crbegin(); |
| 626 | for (size_t __i = _Dimen; __i > 0; --__i) |
| 627 | { |
| 628 | _RealType __sum = _RealType(0); |
| 629 | for (size_t __j = __i; __j > 0; --__j) |
| 630 | __sum += __ret[__j - 1] * *__t_it++; |
| 631 | __ret[__i - 1] = __sum; |
| 632 | } |
| 633 | |
| 634 | return __ret; |
| 635 | } |
| 636 | |
| 637 | template<std::size_t _Dimen, typename _RealType> |
| 638 | template<typename _ForwardIterator, typename _UniformRandomNumberGenerator> |
| 639 | void |
| 640 | normal_mv_distribution<_Dimen, _RealType>:: |
| 641 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, |
| 642 | _UniformRandomNumberGenerator& __urng, |
| 643 | const param_type& __param) |
| 644 | { |
| 645 | __glibcxx_function_requires(_Mutable_ForwardIteratorConcept< |
| 646 | _ForwardIterator>) |
| 647 | while (__f != __t) |
| 648 | *__f++ = this->operator()(__urng, __param); |
| 649 | } |
| 650 | |
| 651 | template<size_t _Dimen, typename _RealType> |
| 652 | bool |
| 653 | operator==(const __gnu_cxx::normal_mv_distribution<_Dimen, _RealType>& |
| 654 | __d1, |
| 655 | const __gnu_cxx::normal_mv_distribution<_Dimen, _RealType>& |
| 656 | __d2) |
| 657 | { |
| 658 | return __d1._M_param == __d2._M_param && __d1._M_nd == __d2._M_nd; |
| 659 | } |
| 660 | |
| 661 | template<size_t _Dimen, typename _RealType, typename _CharT, typename _Traits> |
| 662 | std::basic_ostream<_CharT, _Traits>& |
| 663 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 664 | const __gnu_cxx::normal_mv_distribution<_Dimen, _RealType>& __x) |
| 665 | { |
| 666 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; |
| 667 | typedef typename __ostream_type::ios_base __ios_base; |
| 668 | |
| 669 | const typename __ios_base::fmtflags __flags = __os.flags(); |
| 670 | const _CharT __fill = __os.fill(); |
| 671 | const std::streamsize __precision = __os.precision(); |
| 672 | const _CharT __space = __os.widen(' '); |
| 673 | __os.flags(__ios_base::scientific | __ios_base::left); |
| 674 | __os.fill(__space); |
| 675 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
| 676 | |
| 677 | auto __mean = __x._M_param.mean(); |
| 678 | for (auto __it : __mean) |
| 679 | __os << __it << __space; |
| 680 | auto __t = __x._M_param.varcov(); |
| 681 | for (auto __it : __t) |
| 682 | __os << __it << __space; |
| 683 | |
| 684 | __os << __x._M_nd; |
| 685 | |
| 686 | __os.flags(__flags); |
| 687 | __os.fill(__fill); |
| 688 | __os.precision(__precision); |
| 689 | return __os; |
| 690 | } |
| 691 | |
| 692 | template<size_t _Dimen, typename _RealType, typename _CharT, typename _Traits> |
| 693 | std::basic_istream<_CharT, _Traits>& |
| 694 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 695 | __gnu_cxx::normal_mv_distribution<_Dimen, _RealType>& __x) |
| 696 | { |
| 697 | typedef std::basic_istream<_CharT, _Traits> __istream_type; |
| 698 | typedef typename __istream_type::ios_base __ios_base; |
| 699 | |
| 700 | const typename __ios_base::fmtflags __flags = __is.flags(); |
| 701 | __is.flags(__ios_base::dec | __ios_base::skipws); |
| 702 | |
| 703 | std::array<_RealType, _Dimen> __mean; |
| 704 | for (auto& __it : __mean) |
| 705 | __is >> __it; |
| 706 | std::array<_RealType, _Dimen * (_Dimen + 1) / 2> __varcov; |
| 707 | for (auto& __it : __varcov) |
| 708 | __is >> __it; |
| 709 | |
| 710 | __is >> __x._M_nd; |
| 711 | |
| 712 | __x.param(typename normal_mv_distribution<_Dimen, _RealType>:: |
| 713 | param_type(__mean.begin(), __mean.end(), |
| 714 | __varcov.begin(), __varcov.end())); |
| 715 | |
| 716 | __is.flags(__flags); |
| 717 | return __is; |
| 718 | } |
| 719 | |
| 720 | |
| 00206029 |
721 | template<typename _RealType> |
| 722 | template<typename _OutputIterator, |
| 723 | typename _UniformRandomNumberGenerator> |
| 724 | void |
| 725 | rice_distribution<_RealType>:: |
| 726 | __generate_impl(_OutputIterator __f, _OutputIterator __t, |
| 727 | _UniformRandomNumberGenerator& __urng, |
| 728 | const param_type& __p) |
| 729 | { |
| 4a611aa2 |
730 | __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator, |
| 731 | result_type>) |
| 00206029 |
732 | |
| 00206029 |
733 | while (__f != __t) |
| 734 | { |
| 735 | typename std::normal_distribution<result_type>::param_type |
| 736 | __px(__p.nu(), __p.sigma()), __py(result_type(0), __p.sigma()); |
| 737 | result_type __x = this->_M_ndx(__px, __urng); |
| 738 | result_type __y = this->_M_ndy(__py, __urng); |
| 485dedbc |
739 | #if _GLIBCXX_USE_C99_MATH_TR1 |
| 00206029 |
740 | *__f++ = std::hypot(__x, __y); |
| 485dedbc |
741 | #else |
| 742 | *__f++ = std::sqrt(__x * __x + __y * __y); |
| 743 | #endif |
| 00206029 |
744 | } |
| 745 | } |
| 746 | |
| 747 | template<typename _RealType, typename _CharT, typename _Traits> |
| 748 | std::basic_ostream<_CharT, _Traits>& |
| 749 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 750 | const rice_distribution<_RealType>& __x) |
| 751 | { |
| 752 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; |
| 753 | typedef typename __ostream_type::ios_base __ios_base; |
| 754 | |
| 755 | const typename __ios_base::fmtflags __flags = __os.flags(); |
| 756 | const _CharT __fill = __os.fill(); |
| 757 | const std::streamsize __precision = __os.precision(); |
| 758 | const _CharT __space = __os.widen(' '); |
| 759 | __os.flags(__ios_base::scientific | __ios_base::left); |
| 760 | __os.fill(__space); |
| 761 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
| 762 | |
| 763 | __os << __x.nu() << __space << __x.sigma(); |
| 764 | __os << __space << __x._M_ndx; |
| 765 | __os << __space << __x._M_ndy; |
| 766 | |
| 767 | __os.flags(__flags); |
| 768 | __os.fill(__fill); |
| 769 | __os.precision(__precision); |
| 770 | return __os; |
| 771 | } |
| 772 | |
| 773 | template<typename _RealType, typename _CharT, typename _Traits> |
| 774 | std::basic_istream<_CharT, _Traits>& |
| 775 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 776 | rice_distribution<_RealType>& __x) |
| 777 | { |
| 778 | typedef std::basic_istream<_CharT, _Traits> __istream_type; |
| 779 | typedef typename __istream_type::ios_base __ios_base; |
| 780 | |
| 781 | const typename __ios_base::fmtflags __flags = __is.flags(); |
| 782 | __is.flags(__ios_base::dec | __ios_base::skipws); |
| 783 | |
| f2296c4b |
784 | _RealType __nu_val, __sigma_val; |
| 785 | __is >> __nu_val >> __sigma_val; |
| 00206029 |
786 | __is >> __x._M_ndx; |
| 787 | __is >> __x._M_ndy; |
| 788 | __x.param(typename rice_distribution<_RealType>:: |
| f2296c4b |
789 | param_type(__nu_val, __sigma_val)); |
| 00206029 |
790 | |
| 791 | __is.flags(__flags); |
| 792 | return __is; |
| 793 | } |
| 794 | |
| c96c2073 |
795 | |
| 796 | template<typename _RealType> |
| 797 | template<typename _OutputIterator, |
| 798 | typename _UniformRandomNumberGenerator> |
| 799 | void |
| 800 | nakagami_distribution<_RealType>:: |
| 801 | __generate_impl(_OutputIterator __f, _OutputIterator __t, |
| 802 | _UniformRandomNumberGenerator& __urng, |
| 803 | const param_type& __p) |
| 804 | { |
| 4a611aa2 |
805 | __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator, |
| 806 | result_type>) |
| c96c2073 |
807 | |
| 808 | typename std::gamma_distribution<result_type>::param_type |
| 809 | __pg(__p.mu(), __p.omega() / __p.mu()); |
| 810 | while (__f != __t) |
| 811 | *__f++ = std::sqrt(this->_M_gd(__pg, __urng)); |
| 812 | } |
| 813 | |
| 814 | template<typename _RealType, typename _CharT, typename _Traits> |
| 815 | std::basic_ostream<_CharT, _Traits>& |
| 816 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 817 | const nakagami_distribution<_RealType>& __x) |
| 818 | { |
| 819 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; |
| 820 | typedef typename __ostream_type::ios_base __ios_base; |
| 821 | |
| 822 | const typename __ios_base::fmtflags __flags = __os.flags(); |
| 823 | const _CharT __fill = __os.fill(); |
| 824 | const std::streamsize __precision = __os.precision(); |
| 825 | const _CharT __space = __os.widen(' '); |
| 826 | __os.flags(__ios_base::scientific | __ios_base::left); |
| 827 | __os.fill(__space); |
| 828 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
| 829 | |
| 830 | __os << __x.mu() << __space << __x.omega(); |
| 831 | __os << __space << __x._M_gd; |
| 832 | |
| 833 | __os.flags(__flags); |
| 834 | __os.fill(__fill); |
| 835 | __os.precision(__precision); |
| 836 | return __os; |
| 837 | } |
| 838 | |
| 839 | template<typename _RealType, typename _CharT, typename _Traits> |
| 840 | std::basic_istream<_CharT, _Traits>& |
| 841 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 842 | nakagami_distribution<_RealType>& __x) |
| 843 | { |
| 844 | typedef std::basic_istream<_CharT, _Traits> __istream_type; |
| 845 | typedef typename __istream_type::ios_base __ios_base; |
| 846 | |
| 847 | const typename __ios_base::fmtflags __flags = __is.flags(); |
| 848 | __is.flags(__ios_base::dec | __ios_base::skipws); |
| 849 | |
| f2296c4b |
850 | _RealType __mu_val, __omega_val; |
| 851 | __is >> __mu_val >> __omega_val; |
| c96c2073 |
852 | __is >> __x._M_gd; |
| 853 | __x.param(typename nakagami_distribution<_RealType>:: |
| f2296c4b |
854 | param_type(__mu_val, __omega_val)); |
| c96c2073 |
855 | |
| 856 | __is.flags(__flags); |
| 857 | return __is; |
| 858 | } |
| 859 | |
| cfbdd143 |
860 | |
| 861 | template<typename _RealType> |
| 862 | template<typename _OutputIterator, |
| 863 | typename _UniformRandomNumberGenerator> |
| 864 | void |
| 865 | pareto_distribution<_RealType>:: |
| 866 | __generate_impl(_OutputIterator __f, _OutputIterator __t, |
| 867 | _UniformRandomNumberGenerator& __urng, |
| 868 | const param_type& __p) |
| 869 | { |
| 4a611aa2 |
870 | __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator, |
| 871 | result_type>) |
| cfbdd143 |
872 | |
| f2296c4b |
873 | result_type __mu_val = __p.mu(); |
| cfbdd143 |
874 | result_type __malphinv = -result_type(1) / __p.alpha(); |
| 875 | while (__f != __t) |
| f2296c4b |
876 | *__f++ = __mu_val * std::pow(this->_M_ud(__urng), __malphinv); |
| cfbdd143 |
877 | } |
| 878 | |
| 879 | template<typename _RealType, typename _CharT, typename _Traits> |
| 880 | std::basic_ostream<_CharT, _Traits>& |
| 881 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 882 | const pareto_distribution<_RealType>& __x) |
| 883 | { |
| 884 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; |
| 885 | typedef typename __ostream_type::ios_base __ios_base; |
| 886 | |
| 887 | const typename __ios_base::fmtflags __flags = __os.flags(); |
| 888 | const _CharT __fill = __os.fill(); |
| 889 | const std::streamsize __precision = __os.precision(); |
| 890 | const _CharT __space = __os.widen(' '); |
| 891 | __os.flags(__ios_base::scientific | __ios_base::left); |
| 892 | __os.fill(__space); |
| 893 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
| 894 | |
| 895 | __os << __x.alpha() << __space << __x.mu(); |
| 896 | __os << __space << __x._M_ud; |
| 897 | |
| 898 | __os.flags(__flags); |
| 899 | __os.fill(__fill); |
| 900 | __os.precision(__precision); |
| 901 | return __os; |
| 902 | } |
| 903 | |
| 904 | template<typename _RealType, typename _CharT, typename _Traits> |
| 905 | std::basic_istream<_CharT, _Traits>& |
| 906 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 907 | pareto_distribution<_RealType>& __x) |
| 908 | { |
| 909 | typedef std::basic_istream<_CharT, _Traits> __istream_type; |
| 910 | typedef typename __istream_type::ios_base __ios_base; |
| 911 | |
| 912 | const typename __ios_base::fmtflags __flags = __is.flags(); |
| 913 | __is.flags(__ios_base::dec | __ios_base::skipws); |
| 914 | |
| f2296c4b |
915 | _RealType __alpha_val, __mu_val; |
| 916 | __is >> __alpha_val >> __mu_val; |
| cfbdd143 |
917 | __is >> __x._M_ud; |
| 918 | __x.param(typename pareto_distribution<_RealType>:: |
| f2296c4b |
919 | param_type(__alpha_val, __mu_val)); |
| cfbdd143 |
920 | |
| 921 | __is.flags(__flags); |
| 922 | return __is; |
| 923 | } |
| 924 | |
| 2695aab2 |
925 | |
| 926 | template<typename _RealType> |
| 927 | template<typename _UniformRandomNumberGenerator> |
| 928 | typename k_distribution<_RealType>::result_type |
| 929 | k_distribution<_RealType>:: |
| 930 | operator()(_UniformRandomNumberGenerator& __urng) |
| 931 | { |
| 932 | result_type __x = this->_M_gd1(__urng); |
| 933 | result_type __y = this->_M_gd2(__urng); |
| 934 | return std::sqrt(__x * __y); |
| 935 | } |
| 936 | |
| 937 | template<typename _RealType> |
| 938 | template<typename _UniformRandomNumberGenerator> |
| 939 | typename k_distribution<_RealType>::result_type |
| 940 | k_distribution<_RealType>:: |
| 941 | operator()(_UniformRandomNumberGenerator& __urng, |
| 942 | const param_type& __p) |
| 943 | { |
| 944 | typename std::gamma_distribution<result_type>::param_type |
| 945 | __p1(__p.lambda(), result_type(1) / __p.lambda()), |
| 946 | __p2(__p.nu(), __p.mu() / __p.nu()); |
| 947 | result_type __x = this->_M_gd1(__p1, __urng); |
| 948 | result_type __y = this->_M_gd2(__p2, __urng); |
| 949 | return std::sqrt(__x * __y); |
| 950 | } |
| 951 | |
| 952 | template<typename _RealType> |
| 953 | template<typename _OutputIterator, |
| 954 | typename _UniformRandomNumberGenerator> |
| 955 | void |
| 956 | k_distribution<_RealType>:: |
| 957 | __generate_impl(_OutputIterator __f, _OutputIterator __t, |
| 958 | _UniformRandomNumberGenerator& __urng, |
| 959 | const param_type& __p) |
| 960 | { |
| 4a611aa2 |
961 | __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator, |
| 962 | result_type>) |
| 2695aab2 |
963 | |
| 964 | typename std::gamma_distribution<result_type>::param_type |
| 965 | __p1(__p.lambda(), result_type(1) / __p.lambda()), |
| 966 | __p2(__p.nu(), __p.mu() / __p.nu()); |
| 967 | while (__f != __t) |
| 968 | { |
| 969 | result_type __x = this->_M_gd1(__p1, __urng); |
| 970 | result_type __y = this->_M_gd2(__p2, __urng); |
| 971 | *__f++ = std::sqrt(__x * __y); |
| 972 | } |
| 973 | } |
| 974 | |
| 975 | template<typename _RealType, typename _CharT, typename _Traits> |
| 976 | std::basic_ostream<_CharT, _Traits>& |
| 977 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 978 | const k_distribution<_RealType>& __x) |
| 979 | { |
| 980 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; |
| 981 | typedef typename __ostream_type::ios_base __ios_base; |
| 982 | |
| 983 | const typename __ios_base::fmtflags __flags = __os.flags(); |
| 984 | const _CharT __fill = __os.fill(); |
| 985 | const std::streamsize __precision = __os.precision(); |
| 986 | const _CharT __space = __os.widen(' '); |
| 987 | __os.flags(__ios_base::scientific | __ios_base::left); |
| 988 | __os.fill(__space); |
| 989 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
| 990 | |
| 991 | __os << __x.lambda() << __space << __x.mu() << __space << __x.nu(); |
| 992 | __os << __space << __x._M_gd1; |
| 993 | __os << __space << __x._M_gd2; |
| 994 | |
| 995 | __os.flags(__flags); |
| 996 | __os.fill(__fill); |
| 997 | __os.precision(__precision); |
| 998 | return __os; |
| 999 | } |
| 1000 | |
| 1001 | template<typename _RealType, typename _CharT, typename _Traits> |
| 1002 | std::basic_istream<_CharT, _Traits>& |
| 1003 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 1004 | k_distribution<_RealType>& __x) |
| 1005 | { |
| 1006 | typedef std::basic_istream<_CharT, _Traits> __istream_type; |
| 1007 | typedef typename __istream_type::ios_base __ios_base; |
| 1008 | |
| 1009 | const typename __ios_base::fmtflags __flags = __is.flags(); |
| 1010 | __is.flags(__ios_base::dec | __ios_base::skipws); |
| 1011 | |
| 1012 | _RealType __lambda_val, __mu_val, __nu_val; |
| 1013 | __is >> __lambda_val >> __mu_val >> __nu_val; |
| 1014 | __is >> __x._M_gd1; |
| 1015 | __is >> __x._M_gd2; |
| 1016 | __x.param(typename k_distribution<_RealType>:: |
| 1017 | param_type(__lambda_val, __mu_val, __nu_val)); |
| 1018 | |
| 1019 | __is.flags(__flags); |
| 1020 | return __is; |
| 1021 | } |
| 1022 | |
| ad7e9ce5 |
1023 | |
| 1024 | template<typename _RealType> |
| 1025 | template<typename _OutputIterator, |
| 1026 | typename _UniformRandomNumberGenerator> |
| 1027 | void |
| 1028 | arcsine_distribution<_RealType>:: |
| 1029 | __generate_impl(_OutputIterator __f, _OutputIterator __t, |
| 1030 | _UniformRandomNumberGenerator& __urng, |
| 1031 | const param_type& __p) |
| 1032 | { |
| 4a611aa2 |
1033 | __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator, |
| 1034 | result_type>) |
| ad7e9ce5 |
1035 | |
| 1036 | result_type __dif = __p.b() - __p.a(); |
| 1037 | result_type __sum = __p.a() + __p.b(); |
| 1038 | while (__f != __t) |
| 1039 | { |
| 1040 | result_type __x = std::sin(this->_M_ud(__urng)); |
| 1041 | *__f++ = (__x * __dif + __sum) / result_type(2); |
| 1042 | } |
| 1043 | } |
| 1044 | |
| 1045 | template<typename _RealType, typename _CharT, typename _Traits> |
| 1046 | std::basic_ostream<_CharT, _Traits>& |
| 1047 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 1048 | const arcsine_distribution<_RealType>& __x) |
| 1049 | { |
| 1050 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; |
| 1051 | typedef typename __ostream_type::ios_base __ios_base; |
| 1052 | |
| 1053 | const typename __ios_base::fmtflags __flags = __os.flags(); |
| 1054 | const _CharT __fill = __os.fill(); |
| 1055 | const std::streamsize __precision = __os.precision(); |
| 1056 | const _CharT __space = __os.widen(' '); |
| 1057 | __os.flags(__ios_base::scientific | __ios_base::left); |
| 1058 | __os.fill(__space); |
| 1059 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
| 1060 | |
| 1061 | __os << __x.a() << __space << __x.b(); |
| 1062 | __os << __space << __x._M_ud; |
| 1063 | |
| 1064 | __os.flags(__flags); |
| 1065 | __os.fill(__fill); |
| 1066 | __os.precision(__precision); |
| 1067 | return __os; |
| 1068 | } |
| 1069 | |
| 1070 | template<typename _RealType, typename _CharT, typename _Traits> |
| 1071 | std::basic_istream<_CharT, _Traits>& |
| 1072 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 1073 | arcsine_distribution<_RealType>& __x) |
| 1074 | { |
| 1075 | typedef std::basic_istream<_CharT, _Traits> __istream_type; |
| 1076 | typedef typename __istream_type::ios_base __ios_base; |
| 1077 | |
| 1078 | const typename __ios_base::fmtflags __flags = __is.flags(); |
| 1079 | __is.flags(__ios_base::dec | __ios_base::skipws); |
| 1080 | |
| 1081 | _RealType __a, __b; |
| 1082 | __is >> __a >> __b; |
| 1083 | __is >> __x._M_ud; |
| 1084 | __x.param(typename arcsine_distribution<_RealType>:: |
| 1085 | param_type(__a, __b)); |
| 1086 | |
| 1087 | __is.flags(__flags); |
| 1088 | return __is; |
| 1089 | } |
| 1090 | |
| 1091 | |
| 1092 | template<typename _RealType> |
| 1093 | template<typename _UniformRandomNumberGenerator> |
| 1094 | typename hoyt_distribution<_RealType>::result_type |
| 1095 | hoyt_distribution<_RealType>:: |
| 1096 | operator()(_UniformRandomNumberGenerator& __urng) |
| 1097 | { |
| 1098 | result_type __x = this->_M_ad(__urng); |
| 1099 | result_type __y = this->_M_ed(__urng); |
| 1100 | return (result_type(2) * this->q() |
| 1101 | / (result_type(1) + this->q() * this->q())) |
| 1102 | * std::sqrt(this->omega() * __x * __y); |
| 1103 | } |
| 1104 | |
| 1105 | template<typename _RealType> |
| 1106 | template<typename _UniformRandomNumberGenerator> |
| 1107 | typename hoyt_distribution<_RealType>::result_type |
| 1108 | hoyt_distribution<_RealType>:: |
| 1109 | operator()(_UniformRandomNumberGenerator& __urng, |
| 1110 | const param_type& __p) |
| 1111 | { |
| 1112 | result_type __q2 = __p.q() * __p.q(); |
| 1113 | result_type __num = result_type(0.5L) * (result_type(1) + __q2); |
| 1114 | typename __gnu_cxx::arcsine_distribution<result_type>::param_type |
| 1115 | __pa(__num, __num / __q2); |
| 1116 | result_type __x = this->_M_ad(__pa, __urng); |
| 1117 | result_type __y = this->_M_ed(__urng); |
| 1118 | return (result_type(2) * __p.q() / (result_type(1) + __q2)) |
| 1119 | * std::sqrt(__p.omega() * __x * __y); |
| 1120 | } |
| 1121 | |
| 1122 | template<typename _RealType> |
| 1123 | template<typename _OutputIterator, |
| 1124 | typename _UniformRandomNumberGenerator> |
| 1125 | void |
| 1126 | hoyt_distribution<_RealType>:: |
| 1127 | __generate_impl(_OutputIterator __f, _OutputIterator __t, |
| 1128 | _UniformRandomNumberGenerator& __urng, |
| 1129 | const param_type& __p) |
| 1130 | { |
| 4a611aa2 |
1131 | __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator, |
| 1132 | result_type>) |
| ad7e9ce5 |
1133 | |
| 1134 | result_type __2q = result_type(2) * __p.q(); |
| 1135 | result_type __q2 = __p.q() * __p.q(); |
| 1136 | result_type __q2p1 = result_type(1) + __q2; |
| 1137 | result_type __num = result_type(0.5L) * __q2p1; |
| 1138 | result_type __omega = __p.omega(); |
| 1139 | typename __gnu_cxx::arcsine_distribution<result_type>::param_type |
| 1140 | __pa(__num, __num / __q2); |
| 1141 | while (__f != __t) |
| 1142 | { |
| 1143 | result_type __x = this->_M_ad(__pa, __urng); |
| 1144 | result_type __y = this->_M_ed(__urng); |
| 1145 | *__f++ = (__2q / __q2p1) * std::sqrt(__omega * __x * __y); |
| 1146 | } |
| 1147 | } |
| 1148 | |
| 1149 | template<typename _RealType, typename _CharT, typename _Traits> |
| 1150 | std::basic_ostream<_CharT, _Traits>& |
| 1151 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 1152 | const hoyt_distribution<_RealType>& __x) |
| 1153 | { |
| 1154 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; |
| 1155 | typedef typename __ostream_type::ios_base __ios_base; |
| 1156 | |
| 1157 | const typename __ios_base::fmtflags __flags = __os.flags(); |
| 1158 | const _CharT __fill = __os.fill(); |
| 1159 | const std::streamsize __precision = __os.precision(); |
| 1160 | const _CharT __space = __os.widen(' '); |
| 1161 | __os.flags(__ios_base::scientific | __ios_base::left); |
| 1162 | __os.fill(__space); |
| 1163 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
| 1164 | |
| 1165 | __os << __x.q() << __space << __x.omega(); |
| 1166 | __os << __space << __x._M_ad; |
| 1167 | __os << __space << __x._M_ed; |
| 1168 | |
| 1169 | __os.flags(__flags); |
| 1170 | __os.fill(__fill); |
| 1171 | __os.precision(__precision); |
| 1172 | return __os; |
| 1173 | } |
| 1174 | |
| 1175 | template<typename _RealType, typename _CharT, typename _Traits> |
| 1176 | std::basic_istream<_CharT, _Traits>& |
| 1177 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 1178 | hoyt_distribution<_RealType>& __x) |
| 1179 | { |
| 1180 | typedef std::basic_istream<_CharT, _Traits> __istream_type; |
| 1181 | typedef typename __istream_type::ios_base __ios_base; |
| 1182 | |
| 1183 | const typename __ios_base::fmtflags __flags = __is.flags(); |
| 1184 | __is.flags(__ios_base::dec | __ios_base::skipws); |
| 1185 | |
| 1186 | _RealType __q, __omega; |
| 1187 | __is >> __q >> __omega; |
| 1188 | __is >> __x._M_ad; |
| 1189 | __is >> __x._M_ed; |
| 1190 | __x.param(typename hoyt_distribution<_RealType>:: |
| 1191 | param_type(__q, __omega)); |
| 1192 | |
| 1193 | __is.flags(__flags); |
| 1194 | return __is; |
| 1195 | } |
| 1196 | |
| 0f808dc1 |
1197 | |
| 1198 | template<typename _RealType> |
| 1199 | template<typename _OutputIterator, |
| 1200 | typename _UniformRandomNumberGenerator> |
| 1201 | void |
| 1202 | triangular_distribution<_RealType>:: |
| 1203 | __generate_impl(_OutputIterator __f, _OutputIterator __t, |
| 1204 | _UniformRandomNumberGenerator& __urng, |
| 1205 | const param_type& __param) |
| 1206 | { |
| 4a611aa2 |
1207 | __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator, |
| 1208 | result_type>) |
| 0f808dc1 |
1209 | |
| 1210 | while (__f != __t) |
| 1211 | *__f++ = this->operator()(__urng, __param); |
| 1212 | } |
| 1213 | |
| 1214 | template<typename _RealType, typename _CharT, typename _Traits> |
| 1215 | std::basic_ostream<_CharT, _Traits>& |
| 1216 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 1217 | const __gnu_cxx::triangular_distribution<_RealType>& __x) |
| 1218 | { |
| 1219 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; |
| 1220 | typedef typename __ostream_type::ios_base __ios_base; |
| 1221 | |
| 1222 | const typename __ios_base::fmtflags __flags = __os.flags(); |
| 1223 | const _CharT __fill = __os.fill(); |
| 1224 | const std::streamsize __precision = __os.precision(); |
| 1225 | const _CharT __space = __os.widen(' '); |
| 1226 | __os.flags(__ios_base::scientific | __ios_base::left); |
| 1227 | __os.fill(__space); |
| 1228 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
| 1229 | |
| 1230 | __os << __x.a() << __space << __x.b() << __space << __x.c(); |
| 1231 | |
| 1232 | __os.flags(__flags); |
| 1233 | __os.fill(__fill); |
| 1234 | __os.precision(__precision); |
| 1235 | return __os; |
| 1236 | } |
| 1237 | |
| 1238 | template<typename _RealType, typename _CharT, typename _Traits> |
| 1239 | std::basic_istream<_CharT, _Traits>& |
| 1240 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 1241 | __gnu_cxx::triangular_distribution<_RealType>& __x) |
| 1242 | { |
| 1243 | typedef std::basic_istream<_CharT, _Traits> __istream_type; |
| 1244 | typedef typename __istream_type::ios_base __ios_base; |
| 1245 | |
| 1246 | const typename __ios_base::fmtflags __flags = __is.flags(); |
| 1247 | __is.flags(__ios_base::dec | __ios_base::skipws); |
| 1248 | |
| 1249 | _RealType __a, __b, __c; |
| 1250 | __is >> __a >> __b >> __c; |
| 1251 | __x.param(typename __gnu_cxx::triangular_distribution<_RealType>:: |
| 1252 | param_type(__a, __b, __c)); |
| 1253 | |
| 1254 | __is.flags(__flags); |
| 1255 | return __is; |
| 1256 | } |
| 1257 | |
| 1258 | |
| e582be1d |
1259 | template<typename _RealType> |
| 1260 | template<typename _UniformRandomNumberGenerator> |
| 1261 | typename von_mises_distribution<_RealType>::result_type |
| 1262 | von_mises_distribution<_RealType>:: |
| 1263 | operator()(_UniformRandomNumberGenerator& __urng, |
| 1264 | const param_type& __p) |
| 1265 | { |
| 1266 | const result_type __pi |
| 1267 | = __gnu_cxx::__math_constants<result_type>::__pi; |
| 1268 | std::__detail::_Adaptor<_UniformRandomNumberGenerator, result_type> |
| 1269 | __aurng(__urng); |
| 1270 | |
| 1271 | result_type __f; |
| 1272 | while (1) |
| 1273 | { |
| 1274 | result_type __rnd = std::cos(__pi * __aurng()); |
| 1275 | __f = (result_type(1) + __p._M_r * __rnd) / (__p._M_r + __rnd); |
| 1276 | result_type __c = __p._M_kappa * (__p._M_r - __f); |
| 1277 | |
| 1278 | result_type __rnd2 = __aurng(); |
| 1279 | if (__c * (result_type(2) - __c) > __rnd2) |
| 1280 | break; |
| 1281 | if (std::log(__c / __rnd2) >= __c - result_type(1)) |
| 1282 | break; |
| 1283 | } |
| 1284 | |
| 1285 | result_type __res = std::acos(__f); |
| 1286 | #if _GLIBCXX_USE_C99_MATH_TR1 |
| 1287 | __res = std::copysign(__res, __aurng() - result_type(0.5)); |
| 1288 | #else |
| 1289 | if (__aurng() < result_type(0.5)) |
| 1290 | __res = -__res; |
| 1291 | #endif |
| 1292 | __res += __p._M_mu; |
| 1293 | if (__res > __pi) |
| 1294 | __res -= result_type(2) * __pi; |
| 1295 | else if (__res < -__pi) |
| 1296 | __res += result_type(2) * __pi; |
| 1297 | return __res; |
| 1298 | } |
| 1299 | |
| 0f808dc1 |
1300 | template<typename _RealType> |
| 1301 | template<typename _OutputIterator, |
| 1302 | typename _UniformRandomNumberGenerator> |
| 1303 | void |
| 1304 | von_mises_distribution<_RealType>:: |
| 1305 | __generate_impl(_OutputIterator __f, _OutputIterator __t, |
| 1306 | _UniformRandomNumberGenerator& __urng, |
| 1307 | const param_type& __param) |
| 1308 | { |
| 4a611aa2 |
1309 | __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator, |
| 1310 | result_type>) |
| 0f808dc1 |
1311 | |
| 1312 | while (__f != __t) |
| 1313 | *__f++ = this->operator()(__urng, __param); |
| 1314 | } |
| 1315 | |
| 1316 | template<typename _RealType, typename _CharT, typename _Traits> |
| 1317 | std::basic_ostream<_CharT, _Traits>& |
| 1318 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 1319 | const __gnu_cxx::von_mises_distribution<_RealType>& __x) |
| 1320 | { |
| 1321 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; |
| 1322 | typedef typename __ostream_type::ios_base __ios_base; |
| 1323 | |
| 1324 | const typename __ios_base::fmtflags __flags = __os.flags(); |
| 1325 | const _CharT __fill = __os.fill(); |
| 1326 | const std::streamsize __precision = __os.precision(); |
| 1327 | const _CharT __space = __os.widen(' '); |
| 1328 | __os.flags(__ios_base::scientific | __ios_base::left); |
| 1329 | __os.fill(__space); |
| 1330 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
| 1331 | |
| 1332 | __os << __x.mu() << __space << __x.kappa(); |
| 1333 | |
| 1334 | __os.flags(__flags); |
| 1335 | __os.fill(__fill); |
| 1336 | __os.precision(__precision); |
| 1337 | return __os; |
| 1338 | } |
| 1339 | |
| 1340 | template<typename _RealType, typename _CharT, typename _Traits> |
| 1341 | std::basic_istream<_CharT, _Traits>& |
| 1342 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 1343 | __gnu_cxx::von_mises_distribution<_RealType>& __x) |
| 1344 | { |
| 1345 | typedef std::basic_istream<_CharT, _Traits> __istream_type; |
| 1346 | typedef typename __istream_type::ios_base __ios_base; |
| 1347 | |
| 1348 | const typename __ios_base::fmtflags __flags = __is.flags(); |
| 1349 | __is.flags(__ios_base::dec | __ios_base::skipws); |
| 1350 | |
| 1351 | _RealType __mu, __kappa; |
| 1352 | __is >> __mu >> __kappa; |
| 1353 | __x.param(typename __gnu_cxx::von_mises_distribution<_RealType>:: |
| 1354 | param_type(__mu, __kappa)); |
| 1355 | |
| 1356 | __is.flags(__flags); |
| 1357 | return __is; |
| 1358 | } |
| 1359 | |
| 94612be7 |
1360 | |
| 1361 | template<typename _UIntType> |
| 1362 | template<typename _UniformRandomNumberGenerator> |
| 1363 | typename hypergeometric_distribution<_UIntType>::result_type |
| 1364 | hypergeometric_distribution<_UIntType>:: |
| 1365 | operator()(_UniformRandomNumberGenerator& __urng, |
| 1366 | const param_type& __param) |
| 1367 | { |
| 85448703 |
1368 | std::__detail::_Adaptor<_UniformRandomNumberGenerator, double> |
| 94612be7 |
1369 | __aurng(__urng); |
| 1370 | |
| 1371 | result_type __a = __param.successful_size(); |
| 1372 | result_type __b = __param.total_size(); |
| 1373 | result_type __k = 0; |
| 1374 | |
| 01cd60c5 |
1375 | if (__param.total_draws() < __param.total_size() / 2) |
| 94612be7 |
1376 | { |
| 1377 | for (result_type __i = 0; __i < __param.total_draws(); ++__i) |
| 1378 | { |
| 1379 | if (__b * __aurng() < __a) |
| 1380 | { |
| 1381 | ++__k; |
| 1382 | if (__k == __param.successful_size()) |
| 1383 | return __k; |
| 1384 | --__a; |
| 1385 | } |
| 1386 | --__b; |
| 1387 | } |
| 1388 | return __k; |
| 1389 | } |
| 1390 | else |
| 1391 | { |
| 1392 | for (result_type __i = 0; __i < __param.unsuccessful_size(); ++__i) |
| 1393 | { |
| 1394 | if (__b * __aurng() < __a) |
| 1395 | { |
| 1396 | ++__k; |
| 1397 | if (__k == __param.successful_size()) |
| 1398 | return __param.successful_size() - __k; |
| 1399 | --__a; |
| 1400 | } |
| 1401 | --__b; |
| 1402 | } |
| 1403 | return __param.successful_size() - __k; |
| 1404 | } |
| 1405 | } |
| 1406 | |
| 1407 | template<typename _UIntType> |
| 1408 | template<typename _OutputIterator, |
| 1409 | typename _UniformRandomNumberGenerator> |
| 1410 | void |
| 1411 | hypergeometric_distribution<_UIntType>:: |
| 1412 | __generate_impl(_OutputIterator __f, _OutputIterator __t, |
| 1413 | _UniformRandomNumberGenerator& __urng, |
| 1414 | const param_type& __param) |
| 1415 | { |
| 4a611aa2 |
1416 | __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator, |
| 1417 | result_type>) |
| 94612be7 |
1418 | |
| 1419 | while (__f != __t) |
| 1420 | *__f++ = this->operator()(__urng); |
| 1421 | } |
| 1422 | |
| 1423 | template<typename _UIntType, typename _CharT, typename _Traits> |
| 1424 | std::basic_ostream<_CharT, _Traits>& |
| 1425 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 1426 | const __gnu_cxx::hypergeometric_distribution<_UIntType>& __x) |
| 1427 | { |
| 1428 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; |
| 1429 | typedef typename __ostream_type::ios_base __ios_base; |
| 1430 | |
| 1431 | const typename __ios_base::fmtflags __flags = __os.flags(); |
| 1432 | const _CharT __fill = __os.fill(); |
| 1433 | const std::streamsize __precision = __os.precision(); |
| 1434 | const _CharT __space = __os.widen(' '); |
| 1435 | __os.flags(__ios_base::scientific | __ios_base::left); |
| 1436 | __os.fill(__space); |
| 1437 | __os.precision(std::numeric_limits<_UIntType>::max_digits10); |
| 1438 | |
| 1439 | __os << __x.total_size() << __space << __x.successful_size() << __space |
| 1440 | << __x.total_draws(); |
| 1441 | |
| 1442 | __os.flags(__flags); |
| 1443 | __os.fill(__fill); |
| 1444 | __os.precision(__precision); |
| 1445 | return __os; |
| 1446 | } |
| 1447 | |
| 1448 | template<typename _UIntType, typename _CharT, typename _Traits> |
| 1449 | std::basic_istream<_CharT, _Traits>& |
| 1450 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 1451 | __gnu_cxx::hypergeometric_distribution<_UIntType>& __x) |
| 1452 | { |
| 1453 | typedef std::basic_istream<_CharT, _Traits> __istream_type; |
| 1454 | typedef typename __istream_type::ios_base __ios_base; |
| 1455 | |
| 1456 | const typename __ios_base::fmtflags __flags = __is.flags(); |
| 1457 | __is.flags(__ios_base::dec | __ios_base::skipws); |
| 1458 | |
| 1459 | _UIntType __total_size, __successful_size, __total_draws; |
| 1460 | __is >> __total_size >> __successful_size >> __total_draws; |
| 1461 | __x.param(typename __gnu_cxx::hypergeometric_distribution<_UIntType>:: |
| 1462 | param_type(__total_size, __successful_size, __total_draws)); |
| 1463 | |
| 1464 | __is.flags(__flags); |
| 1465 | return __is; |
| 1466 | } |
| 1467 | |
| e582be1d |
1468 | |
| 1469 | template<typename _RealType> |
| 1470 | template<typename _UniformRandomNumberGenerator> |
| 1471 | typename logistic_distribution<_RealType>::result_type |
| 1472 | logistic_distribution<_RealType>:: |
| 1473 | operator()(_UniformRandomNumberGenerator& __urng, |
| 1474 | const param_type& __p) |
| 1475 | { |
| 1476 | std::__detail::_Adaptor<_UniformRandomNumberGenerator, result_type> |
| 1477 | __aurng(__urng); |
| 1478 | |
| 1479 | result_type __arg = result_type(1); |
| 1480 | while (__arg == result_type(1) || __arg == result_type(0)) |
| 1481 | __arg = __aurng(); |
| 1482 | return __p.a() |
| 1483 | + __p.b() * std::log(__arg / (result_type(1) - __arg)); |
| 1484 | } |
| 1485 | |
| 1486 | template<typename _RealType> |
| 1487 | template<typename _OutputIterator, |
| 1488 | typename _UniformRandomNumberGenerator> |
| 1489 | void |
| 1490 | logistic_distribution<_RealType>:: |
| 1491 | __generate_impl(_OutputIterator __f, _OutputIterator __t, |
| 1492 | _UniformRandomNumberGenerator& __urng, |
| 1493 | const param_type& __p) |
| 1494 | { |
| 4a611aa2 |
1495 | __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator, |
| 1496 | result_type>) |
| 1497 | |
| e582be1d |
1498 | std::__detail::_Adaptor<_UniformRandomNumberGenerator, result_type> |
| 1499 | __aurng(__urng); |
| 1500 | |
| 1501 | while (__f != __t) |
| 1502 | { |
| 1503 | result_type __arg = result_type(1); |
| 1504 | while (__arg == result_type(1) || __arg == result_type(0)) |
| 1505 | __arg = __aurng(); |
| 1506 | *__f++ = __p.a() |
| 1507 | + __p.b() * std::log(__arg / (result_type(1) - __arg)); |
| 1508 | } |
| 1509 | } |
| 1510 | |
| 1511 | template<typename _RealType, typename _CharT, typename _Traits> |
| 1512 | std::basic_ostream<_CharT, _Traits>& |
| 1513 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 1514 | const logistic_distribution<_RealType>& __x) |
| 1515 | { |
| 1516 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; |
| 1517 | typedef typename __ostream_type::ios_base __ios_base; |
| 1518 | |
| 1519 | const typename __ios_base::fmtflags __flags = __os.flags(); |
| 1520 | const _CharT __fill = __os.fill(); |
| 1521 | const std::streamsize __precision = __os.precision(); |
| 1522 | const _CharT __space = __os.widen(' '); |
| 1523 | __os.flags(__ios_base::scientific | __ios_base::left); |
| 1524 | __os.fill(__space); |
| 1525 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
| 1526 | |
| 1527 | __os << __x.a() << __space << __x.b(); |
| 1528 | |
| 1529 | __os.flags(__flags); |
| 1530 | __os.fill(__fill); |
| 1531 | __os.precision(__precision); |
| 1532 | return __os; |
| 1533 | } |
| 1534 | |
| 1535 | template<typename _RealType, typename _CharT, typename _Traits> |
| 1536 | std::basic_istream<_CharT, _Traits>& |
| 1537 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 1538 | logistic_distribution<_RealType>& __x) |
| 1539 | { |
| 1540 | typedef std::basic_istream<_CharT, _Traits> __istream_type; |
| 1541 | typedef typename __istream_type::ios_base __ios_base; |
| 1542 | |
| 1543 | const typename __ios_base::fmtflags __flags = __is.flags(); |
| 1544 | __is.flags(__ios_base::dec | __ios_base::skipws); |
| 1545 | |
| 1546 | _RealType __a, __b; |
| 1547 | __is >> __a >> __b; |
| 1548 | __x.param(typename logistic_distribution<_RealType>:: |
| 1549 | param_type(__a, __b)); |
| 1550 | |
| 1551 | __is.flags(__flags); |
| 1552 | return __is; |
| 1553 | } |
| 1554 | |
| 01cd60c5 |
1555 | |
| 434a8652 |
1556 | namespace { |
| 1557 | |
| 1558 | // Helper class for the uniform_on_sphere_distribution generation |
| 1559 | // function. |
| 1560 | template<std::size_t _Dimen, typename _RealType> |
| 1561 | class uniform_on_sphere_helper |
| 1562 | { |
| bd07ab1e |
1563 | typedef typename uniform_on_sphere_distribution<_Dimen, _RealType>:: |
| 1564 | result_type result_type; |
| 434a8652 |
1565 | |
| 1566 | public: |
| bd07ab1e |
1567 | template<typename _NormalDistribution, |
| 1568 | typename _UniformRandomNumberGenerator> |
| 434a8652 |
1569 | result_type operator()(_NormalDistribution& __nd, |
| 1570 | _UniformRandomNumberGenerator& __urng) |
| 1571 | { |
| 1572 | result_type __ret; |
| 1573 | typename result_type::value_type __norm; |
| 1574 | |
| 1575 | do |
| 1576 | { |
| 1577 | auto __sum = _RealType(0); |
| 1578 | |
| 1579 | std::generate(__ret.begin(), __ret.end(), |
| 1580 | [&__nd, &__urng, &__sum](){ |
| 1581 | _RealType __t = __nd(__urng); |
| 1582 | __sum += __t * __t; |
| 1583 | return __t; }); |
| 1584 | __norm = std::sqrt(__sum); |
| 1585 | } |
| 017dc518 |
1586 | while (__norm == _RealType(0) || ! __builtin_isfinite(__norm)); |
| 434a8652 |
1587 | |
| 1588 | std::transform(__ret.begin(), __ret.end(), __ret.begin(), |
| 1589 | [__norm](_RealType __val){ return __val / __norm; }); |
| 1590 | |
| 1591 | return __ret; |
| 1592 | } |
| 1593 | }; |
| 1594 | |
| 1595 | |
| 1596 | template<typename _RealType> |
| 1597 | class uniform_on_sphere_helper<2, _RealType> |
| 1598 | { |
| 1599 | typedef typename uniform_on_sphere_distribution<2, _RealType>:: |
| 1600 | result_type result_type; |
| 1601 | |
| 1602 | public: |
| 1603 | template<typename _NormalDistribution, |
| 1604 | typename _UniformRandomNumberGenerator> |
| 1605 | result_type operator()(_NormalDistribution&, |
| 1606 | _UniformRandomNumberGenerator& __urng) |
| 1607 | { |
| 1608 | result_type __ret; |
| 1609 | _RealType __sq; |
| 1610 | std::__detail::_Adaptor<_UniformRandomNumberGenerator, |
| 1611 | _RealType> __aurng(__urng); |
| 1612 | |
| 1613 | do |
| 1614 | { |
| 1615 | __ret[0] = _RealType(2) * __aurng() - _RealType(1); |
| 1616 | __ret[1] = _RealType(2) * __aurng() - _RealType(1); |
| 1617 | |
| 1618 | __sq = __ret[0] * __ret[0] + __ret[1] * __ret[1]; |
| 1619 | } |
| 1620 | while (__sq == _RealType(0) || __sq > _RealType(1)); |
| 1621 | |
| bd07ab1e |
1622 | #if _GLIBCXX_USE_C99_MATH_TR1 |
| 434a8652 |
1623 | // Yes, we do not just use sqrt(__sq) because hypot() is more |
| 1624 | // accurate. |
| 1625 | auto __norm = std::hypot(__ret[0], __ret[1]); |
| bd07ab1e |
1626 | #else |
| 766b5160 |
1627 | auto __norm = std::sqrt(__sq); |
| bd07ab1e |
1628 | #endif |
| 434a8652 |
1629 | __ret[0] /= __norm; |
| 1630 | __ret[1] /= __norm; |
| 1631 | |
| 1632 | return __ret; |
| 1633 | } |
| 1634 | }; |
| 1635 | |
| 1636 | } |
| 1637 | |
| 1638 | |
| 01cd60c5 |
1639 | template<std::size_t _Dimen, typename _RealType> |
| 1640 | template<typename _UniformRandomNumberGenerator> |
| 1641 | typename uniform_on_sphere_distribution<_Dimen, _RealType>::result_type |
| 1642 | uniform_on_sphere_distribution<_Dimen, _RealType>:: |
| 1643 | operator()(_UniformRandomNumberGenerator& __urng, |
| 1644 | const param_type& __p) |
| 1645 | { |
| 434a8652 |
1646 | uniform_on_sphere_helper<_Dimen, _RealType> __helper; |
| 1647 | return __helper(_M_nd, __urng); |
| 01cd60c5 |
1648 | } |
| 1649 | |
| 1650 | template<std::size_t _Dimen, typename _RealType> |
| 1651 | template<typename _OutputIterator, |
| 1652 | typename _UniformRandomNumberGenerator> |
| 1653 | void |
| 1654 | uniform_on_sphere_distribution<_Dimen, _RealType>:: |
| 1655 | __generate_impl(_OutputIterator __f, _OutputIterator __t, |
| 1656 | _UniformRandomNumberGenerator& __urng, |
| 1657 | const param_type& __param) |
| 1658 | { |
| 4a611aa2 |
1659 | __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator, |
| 1660 | result_type>) |
| 01cd60c5 |
1661 | |
| 1662 | while (__f != __t) |
| 1663 | *__f++ = this->operator()(__urng, __param); |
| 1664 | } |
| 1665 | |
| 1666 | template<std::size_t _Dimen, typename _RealType, typename _CharT, |
| 1667 | typename _Traits> |
| 1668 | std::basic_ostream<_CharT, _Traits>& |
| 1669 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 1670 | const __gnu_cxx::uniform_on_sphere_distribution<_Dimen, |
| 1671 | _RealType>& __x) |
| 1672 | { |
| 1c7c9ed3 |
1673 | return __os << __x._M_nd; |
| 01cd60c5 |
1674 | } |
| 1675 | |
| 1676 | template<std::size_t _Dimen, typename _RealType, typename _CharT, |
| 1677 | typename _Traits> |
| 1678 | std::basic_istream<_CharT, _Traits>& |
| 1679 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 1680 | __gnu_cxx::uniform_on_sphere_distribution<_Dimen, |
| 1681 | _RealType>& __x) |
| 1682 | { |
| 1c7c9ed3 |
1683 | return __is >> __x._M_nd; |
| 01cd60c5 |
1684 | } |
| 1685 | |
| 48367519 |
1686 | |
| 1687 | namespace { |
| 1688 | |
| 1689 | // Helper class for the uniform_inside_sphere_distribution generation |
| 1690 | // function. |
| 1691 | template<std::size_t _Dimen, bool _SmallDimen, typename _RealType> |
| 1692 | class uniform_inside_sphere_helper; |
| 1693 | |
| 1694 | template<std::size_t _Dimen, typename _RealType> |
| 1695 | class uniform_inside_sphere_helper<_Dimen, false, _RealType> |
| 1696 | { |
| 1697 | using result_type |
| 1698 | = typename uniform_inside_sphere_distribution<_Dimen, _RealType>:: |
| 1699 | result_type; |
| 1700 | |
| 1701 | public: |
| 1702 | template<typename _UniformOnSphereDistribution, |
| 1703 | typename _UniformRandomNumberGenerator> |
| 1704 | result_type |
| 1705 | operator()(_UniformOnSphereDistribution& __uosd, |
| 1706 | _UniformRandomNumberGenerator& __urng, |
| 1707 | _RealType __radius) |
| 1708 | { |
| 1709 | std::__detail::_Adaptor<_UniformRandomNumberGenerator, |
| 1710 | _RealType> __aurng(__urng); |
| 1711 | |
| 1712 | _RealType __pow = 1 / _RealType(_Dimen); |
| 1713 | _RealType __urt = __radius * std::pow(__aurng(), __pow); |
| 1714 | result_type __ret = __uosd(__aurng); |
| 1715 | |
| 1716 | std::transform(__ret.begin(), __ret.end(), __ret.begin(), |
| 1717 | [__urt](_RealType __val) |
| 1718 | { return __val * __urt; }); |
| 1719 | |
| 1720 | return __ret; |
| 1721 | } |
| 1722 | }; |
| 1723 | |
| 1724 | // Helper class for the uniform_inside_sphere_distribution generation |
| 1725 | // function specialized for small dimensions. |
| 1726 | template<std::size_t _Dimen, typename _RealType> |
| 1727 | class uniform_inside_sphere_helper<_Dimen, true, _RealType> |
| 1728 | { |
| 1729 | using result_type |
| 1730 | = typename uniform_inside_sphere_distribution<_Dimen, _RealType>:: |
| 1731 | result_type; |
| 1732 | |
| 1733 | public: |
| 1734 | template<typename _UniformOnSphereDistribution, |
| 1735 | typename _UniformRandomNumberGenerator> |
| 1736 | result_type |
| 1737 | operator()(_UniformOnSphereDistribution&, |
| 1738 | _UniformRandomNumberGenerator& __urng, |
| 1739 | _RealType __radius) |
| 1740 | { |
| 1741 | result_type __ret; |
| 1742 | _RealType __sq; |
| 1743 | _RealType __radsq = __radius * __radius; |
| 1744 | std::__detail::_Adaptor<_UniformRandomNumberGenerator, |
| 1745 | _RealType> __aurng(__urng); |
| 1746 | |
| 1747 | do |
| 1748 | { |
| 1749 | __sq = _RealType(0); |
| 1750 | for (int i = 0; i < _Dimen; ++i) |
| 1751 | { |
| 1752 | __ret[i] = _RealType(2) * __aurng() - _RealType(1); |
| 1753 | __sq += __ret[i] * __ret[i]; |
| 1754 | } |
| 1755 | } |
| 1756 | while (__sq > _RealType(1)); |
| 1757 | |
| 1758 | for (int i = 0; i < _Dimen; ++i) |
| 1759 | __ret[i] *= __radius; |
| 1760 | |
| 1761 | return __ret; |
| 1762 | } |
| 1763 | }; |
| 1764 | } // namespace |
| 1765 | |
| 1766 | // |
| 1767 | // Experiments have shown that rejection is more efficient than transform |
| 1768 | // for dimensions less than 8. |
| 1769 | // |
| 1770 | template<std::size_t _Dimen, typename _RealType> |
| 1771 | template<typename _UniformRandomNumberGenerator> |
| 1772 | typename uniform_inside_sphere_distribution<_Dimen, _RealType>::result_type |
| 1773 | uniform_inside_sphere_distribution<_Dimen, _RealType>:: |
| 1774 | operator()(_UniformRandomNumberGenerator& __urng, |
| 1775 | const param_type& __p) |
| 1776 | { |
| 1777 | uniform_inside_sphere_helper<_Dimen, _Dimen < 8, _RealType> __helper; |
| 1778 | return __helper(_M_uosd, __urng, __p.radius()); |
| 1779 | } |
| 1780 | |
| 1781 | template<std::size_t _Dimen, typename _RealType> |
| 1782 | template<typename _OutputIterator, |
| 1783 | typename _UniformRandomNumberGenerator> |
| 1784 | void |
| 1785 | uniform_inside_sphere_distribution<_Dimen, _RealType>:: |
| 1786 | __generate_impl(_OutputIterator __f, _OutputIterator __t, |
| 1787 | _UniformRandomNumberGenerator& __urng, |
| 1788 | const param_type& __param) |
| 1789 | { |
| 4a611aa2 |
1790 | __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator, |
| 1791 | result_type>) |
| 48367519 |
1792 | |
| 1793 | while (__f != __t) |
| 1794 | *__f++ = this->operator()(__urng, __param); |
| 1795 | } |
| 1796 | |
| 1797 | template<std::size_t _Dimen, typename _RealType, typename _CharT, |
| 1798 | typename _Traits> |
| 1799 | std::basic_ostream<_CharT, _Traits>& |
| 1800 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, |
| 1801 | const __gnu_cxx::uniform_inside_sphere_distribution<_Dimen, |
| 1802 | _RealType>& __x) |
| 1803 | { |
| 1804 | typedef std::basic_ostream<_CharT, _Traits> __ostream_type; |
| 1805 | typedef typename __ostream_type::ios_base __ios_base; |
| 1806 | |
| 1807 | const typename __ios_base::fmtflags __flags = __os.flags(); |
| 1808 | const _CharT __fill = __os.fill(); |
| 1809 | const std::streamsize __precision = __os.precision(); |
| 1810 | const _CharT __space = __os.widen(' '); |
| 1811 | __os.flags(__ios_base::scientific | __ios_base::left); |
| 1812 | __os.fill(__space); |
| 1813 | __os.precision(std::numeric_limits<_RealType>::max_digits10); |
| 1814 | |
| 1815 | __os << __x.radius() << __space << __x._M_uosd; |
| 1816 | |
| 1817 | __os.flags(__flags); |
| 1818 | __os.fill(__fill); |
| 1819 | __os.precision(__precision); |
| 1820 | |
| 1821 | return __os; |
| 1822 | } |
| 1823 | |
| 1824 | template<std::size_t _Dimen, typename _RealType, typename _CharT, |
| 1825 | typename _Traits> |
| 1826 | std::basic_istream<_CharT, _Traits>& |
| 1827 | operator>>(std::basic_istream<_CharT, _Traits>& __is, |
| 1828 | __gnu_cxx::uniform_inside_sphere_distribution<_Dimen, |
| 1829 | _RealType>& __x) |
| 1830 | { |
| 1831 | typedef std::basic_istream<_CharT, _Traits> __istream_type; |
| 1832 | typedef typename __istream_type::ios_base __ios_base; |
| 1833 | |
| 1834 | const typename __ios_base::fmtflags __flags = __is.flags(); |
| 1835 | __is.flags(__ios_base::dec | __ios_base::skipws); |
| 1836 | |
| 1837 | _RealType __radius_val; |
| 1838 | __is >> __radius_val >> __x._M_uosd; |
| 1839 | __x.param(typename uniform_inside_sphere_distribution<_Dimen, _RealType>:: |
| 1840 | param_type(__radius_val)); |
| 1841 | |
| 1842 | __is.flags(__flags); |
| 1843 | |
| 1844 | return __is; |
| 1845 | } |
| 1846 | |
| dcfbfb22 |
1847 | _GLIBCXX_END_NAMESPACE_VERSION |
| 48367519 |
1848 | } // namespace __gnu_cxx |
| dcfbfb22 |
1849 | |
| 1850 | |
| 1851 | #endif // _EXT_RANDOM_TCC |
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