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1860430a UD |
1 | // Random number extensions -*- C++ -*- |
2 | ||
7adcbafe | 3 | // Copyright (C) 2012-2022 Free Software Foundation, Inc. |
1860430a UD |
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 | |
26 | * This file is a GNU extension to the Standard C++ Library. | |
27 | */ | |
28 | ||
29 | #ifndef _EXT_RANDOM | |
30 | #define _EXT_RANDOM 1 | |
31 | ||
32 | #pragma GCC system_header | |
33 | ||
734f5023 | 34 | #if __cplusplus < 201103L |
8054b82e PC |
35 | # include <bits/c++0x_warning.h> |
36 | #else | |
37 | ||
1860430a | 38 | #include <random> |
863a2c7e | 39 | #include <algorithm> |
bf30f229 | 40 | #include <array> |
d233c237 | 41 | #include <ext/cmath> |
1860430a | 42 | #ifdef __SSE2__ |
141aa58b | 43 | # include <emmintrin.h> |
1860430a UD |
44 | #endif |
45 | ||
7215aaed | 46 | #if defined(_GLIBCXX_USE_C99_STDINT_TR1) && defined(UINT32_C) |
1860430a UD |
47 | |
48 | namespace __gnu_cxx _GLIBCXX_VISIBILITY(default) | |
49 | { | |
50 | _GLIBCXX_BEGIN_NAMESPACE_VERSION | |
51 | ||
eeeef8f4 PC |
52 | #if __BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__ |
53 | ||
1860430a UD |
54 | /* Mersenne twister implementation optimized for vector operations. |
55 | * | |
56 | * Reference: http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/SFMT/ | |
57 | */ | |
58 | template<typename _UIntType, size_t __m, | |
59 | size_t __pos1, size_t __sl1, size_t __sl2, | |
60 | size_t __sr1, size_t __sr2, | |
61 | uint32_t __msk1, uint32_t __msk2, | |
62 | uint32_t __msk3, uint32_t __msk4, | |
63 | uint32_t __parity1, uint32_t __parity2, | |
64 | uint32_t __parity3, uint32_t __parity4> | |
65 | class simd_fast_mersenne_twister_engine | |
66 | { | |
67 | static_assert(std::is_unsigned<_UIntType>::value, "template argument " | |
68 | "substituting _UIntType not an unsigned integral type"); | |
69 | static_assert(__sr1 < 32, "first right shift too large"); | |
70 | static_assert(__sr2 < 16, "second right shift too large"); | |
71 | static_assert(__sl1 < 32, "first left shift too large"); | |
72 | static_assert(__sl2 < 16, "second left shift too large"); | |
73 | ||
74 | public: | |
75 | typedef _UIntType result_type; | |
76 | ||
77 | private: | |
78 | static constexpr size_t m_w = sizeof(result_type) * 8; | |
79 | static constexpr size_t _M_nstate = __m / 128 + 1; | |
80 | static constexpr size_t _M_nstate32 = _M_nstate * 4; | |
81 | ||
82 | static_assert(std::is_unsigned<_UIntType>::value, "template argument " | |
83 | "substituting _UIntType not an unsigned integral type"); | |
84 | static_assert(__pos1 < _M_nstate, "POS1 not smaller than state size"); | |
85 | static_assert(16 % sizeof(_UIntType) == 0, | |
86 | "UIntType size must divide 16"); | |
87 | ||
5a7960da JW |
88 | template<typename _Sseq> |
89 | using _If_seed_seq | |
90 | = typename std::enable_if<std::__detail::__is_seed_seq< | |
91 | _Sseq, simd_fast_mersenne_twister_engine, result_type>::value | |
92 | >::type; | |
93 | ||
1860430a UD |
94 | public: |
95 | static constexpr size_t state_size = _M_nstate * (16 | |
96 | / sizeof(result_type)); | |
97 | static constexpr result_type default_seed = 5489u; | |
98 | ||
dd9db6f8 JW |
99 | // constructors and member functions |
100 | ||
101 | simd_fast_mersenne_twister_engine() | |
102 | : simd_fast_mersenne_twister_engine(default_seed) | |
103 | { } | |
104 | ||
1860430a | 105 | explicit |
dd9db6f8 | 106 | simd_fast_mersenne_twister_engine(result_type __sd) |
1860430a UD |
107 | { seed(__sd); } |
108 | ||
5a7960da | 109 | template<typename _Sseq, typename = _If_seed_seq<_Sseq>> |
1860430a UD |
110 | explicit |
111 | simd_fast_mersenne_twister_engine(_Sseq& __q) | |
112 | { seed(__q); } | |
113 | ||
114 | void | |
115 | seed(result_type __sd = default_seed); | |
116 | ||
117 | template<typename _Sseq> | |
5a7960da | 118 | _If_seed_seq<_Sseq> |
1860430a UD |
119 | seed(_Sseq& __q); |
120 | ||
121 | static constexpr result_type | |
122 | min() | |
57c51668 | 123 | { return 0; } |
1860430a UD |
124 | |
125 | static constexpr result_type | |
126 | max() | |
127 | { return std::numeric_limits<result_type>::max(); } | |
128 | ||
129 | void | |
130 | discard(unsigned long long __z); | |
131 | ||
132 | result_type | |
133 | operator()() | |
134 | { | |
135 | if (__builtin_expect(_M_pos >= state_size, 0)) | |
136 | _M_gen_rand(); | |
137 | ||
138 | return _M_stateT[_M_pos++]; | |
139 | } | |
140 | ||
9bf714c2 UD |
141 | template<typename _UIntType_2, size_t __m_2, |
142 | size_t __pos1_2, size_t __sl1_2, size_t __sl2_2, | |
143 | size_t __sr1_2, size_t __sr2_2, | |
144 | uint32_t __msk1_2, uint32_t __msk2_2, | |
145 | uint32_t __msk3_2, uint32_t __msk4_2, | |
146 | uint32_t __parity1_2, uint32_t __parity2_2, | |
147 | uint32_t __parity3_2, uint32_t __parity4_2> | |
148 | friend bool | |
149 | operator==(const simd_fast_mersenne_twister_engine<_UIntType_2, | |
150 | __m_2, __pos1_2, __sl1_2, __sl2_2, __sr1_2, __sr2_2, | |
151 | __msk1_2, __msk2_2, __msk3_2, __msk4_2, | |
152 | __parity1_2, __parity2_2, __parity3_2, __parity4_2>& __lhs, | |
153 | const simd_fast_mersenne_twister_engine<_UIntType_2, | |
154 | __m_2, __pos1_2, __sl1_2, __sl2_2, __sr1_2, __sr2_2, | |
155 | __msk1_2, __msk2_2, __msk3_2, __msk4_2, | |
156 | __parity1_2, __parity2_2, __parity3_2, __parity4_2>& __rhs); | |
1860430a UD |
157 | |
158 | template<typename _UIntType_2, size_t __m_2, | |
159 | size_t __pos1_2, size_t __sl1_2, size_t __sl2_2, | |
160 | size_t __sr1_2, size_t __sr2_2, | |
161 | uint32_t __msk1_2, uint32_t __msk2_2, | |
162 | uint32_t __msk3_2, uint32_t __msk4_2, | |
163 | uint32_t __parity1_2, uint32_t __parity2_2, | |
164 | uint32_t __parity3_2, uint32_t __parity4_2, | |
165 | typename _CharT, typename _Traits> | |
166 | friend std::basic_ostream<_CharT, _Traits>& | |
167 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
d9d69f64 PC |
168 | const __gnu_cxx::simd_fast_mersenne_twister_engine |
169 | <_UIntType_2, | |
1860430a UD |
170 | __m_2, __pos1_2, __sl1_2, __sl2_2, __sr1_2, __sr2_2, |
171 | __msk1_2, __msk2_2, __msk3_2, __msk4_2, | |
172 | __parity1_2, __parity2_2, __parity3_2, __parity4_2>& __x); | |
173 | ||
174 | template<typename _UIntType_2, size_t __m_2, | |
175 | size_t __pos1_2, size_t __sl1_2, size_t __sl2_2, | |
176 | size_t __sr1_2, size_t __sr2_2, | |
177 | uint32_t __msk1_2, uint32_t __msk2_2, | |
178 | uint32_t __msk3_2, uint32_t __msk4_2, | |
179 | uint32_t __parity1_2, uint32_t __parity2_2, | |
180 | uint32_t __parity3_2, uint32_t __parity4_2, | |
181 | typename _CharT, typename _Traits> | |
182 | friend std::basic_istream<_CharT, _Traits>& | |
183 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
184 | __gnu_cxx::simd_fast_mersenne_twister_engine<_UIntType_2, | |
185 | __m_2, __pos1_2, __sl1_2, __sl2_2, __sr1_2, __sr2_2, | |
186 | __msk1_2, __msk2_2, __msk3_2, __msk4_2, | |
187 | __parity1_2, __parity2_2, __parity3_2, __parity4_2>& __x); | |
188 | ||
189 | private: | |
190 | union | |
191 | { | |
192 | #ifdef __SSE2__ | |
193 | __m128i _M_state[_M_nstate]; | |
5bbf7664 MC |
194 | #endif |
195 | #ifdef __ARM_NEON | |
196 | #ifdef __aarch64__ | |
197 | __Uint32x4_t _M_state[_M_nstate]; | |
198 | #endif | |
1860430a UD |
199 | #endif |
200 | uint32_t _M_state32[_M_nstate32]; | |
201 | result_type _M_stateT[state_size]; | |
202 | } __attribute__ ((__aligned__ (16))); | |
203 | size_t _M_pos; | |
204 | ||
205 | void _M_gen_rand(void); | |
206 | void _M_period_certification(); | |
207 | }; | |
208 | ||
209 | ||
210 | template<typename _UIntType, size_t __m, | |
211 | size_t __pos1, size_t __sl1, size_t __sl2, | |
212 | size_t __sr1, size_t __sr2, | |
213 | uint32_t __msk1, uint32_t __msk2, | |
214 | uint32_t __msk3, uint32_t __msk4, | |
215 | uint32_t __parity1, uint32_t __parity2, | |
216 | uint32_t __parity3, uint32_t __parity4> | |
217 | inline bool | |
218 | operator!=(const __gnu_cxx::simd_fast_mersenne_twister_engine<_UIntType, | |
219 | __m, __pos1, __sl1, __sl2, __sr1, __sr2, __msk1, __msk2, __msk3, | |
220 | __msk4, __parity1, __parity2, __parity3, __parity4>& __lhs, | |
221 | const __gnu_cxx::simd_fast_mersenne_twister_engine<_UIntType, | |
222 | __m, __pos1, __sl1, __sl2, __sr1, __sr2, __msk1, __msk2, __msk3, | |
223 | __msk4, __parity1, __parity2, __parity3, __parity4>& __rhs) | |
224 | { return !(__lhs == __rhs); } | |
225 | ||
226 | ||
227 | /* Definitions for the SIMD-oriented Fast Mersenne Twister as defined | |
228 | * in the C implementation by Daito and Matsumoto, as both a 32-bit | |
229 | * and 64-bit version. | |
230 | */ | |
231 | typedef simd_fast_mersenne_twister_engine<uint32_t, 607, 2, | |
232 | 15, 3, 13, 3, | |
233 | 0xfdff37ffU, 0xef7f3f7dU, | |
234 | 0xff777b7dU, 0x7ff7fb2fU, | |
235 | 0x00000001U, 0x00000000U, | |
236 | 0x00000000U, 0x5986f054U> | |
237 | sfmt607; | |
238 | ||
239 | typedef simd_fast_mersenne_twister_engine<uint64_t, 607, 2, | |
240 | 15, 3, 13, 3, | |
241 | 0xfdff37ffU, 0xef7f3f7dU, | |
242 | 0xff777b7dU, 0x7ff7fb2fU, | |
243 | 0x00000001U, 0x00000000U, | |
244 | 0x00000000U, 0x5986f054U> | |
245 | sfmt607_64; | |
246 | ||
247 | ||
248 | typedef simd_fast_mersenne_twister_engine<uint32_t, 1279, 7, | |
249 | 14, 3, 5, 1, | |
250 | 0xf7fefffdU, 0x7fefcfffU, | |
251 | 0xaff3ef3fU, 0xb5ffff7fU, | |
252 | 0x00000001U, 0x00000000U, | |
253 | 0x00000000U, 0x20000000U> | |
254 | sfmt1279; | |
255 | ||
256 | typedef simd_fast_mersenne_twister_engine<uint64_t, 1279, 7, | |
257 | 14, 3, 5, 1, | |
258 | 0xf7fefffdU, 0x7fefcfffU, | |
259 | 0xaff3ef3fU, 0xb5ffff7fU, | |
260 | 0x00000001U, 0x00000000U, | |
261 | 0x00000000U, 0x20000000U> | |
262 | sfmt1279_64; | |
263 | ||
264 | ||
265 | typedef simd_fast_mersenne_twister_engine<uint32_t, 2281, 12, | |
266 | 19, 1, 5, 1, | |
267 | 0xbff7ffbfU, 0xfdfffffeU, | |
268 | 0xf7ffef7fU, 0xf2f7cbbfU, | |
269 | 0x00000001U, 0x00000000U, | |
270 | 0x00000000U, 0x41dfa600U> | |
271 | sfmt2281; | |
272 | ||
273 | typedef simd_fast_mersenne_twister_engine<uint64_t, 2281, 12, | |
274 | 19, 1, 5, 1, | |
275 | 0xbff7ffbfU, 0xfdfffffeU, | |
276 | 0xf7ffef7fU, 0xf2f7cbbfU, | |
277 | 0x00000001U, 0x00000000U, | |
278 | 0x00000000U, 0x41dfa600U> | |
279 | sfmt2281_64; | |
280 | ||
281 | ||
282 | typedef simd_fast_mersenne_twister_engine<uint32_t, 4253, 17, | |
283 | 20, 1, 7, 1, | |
284 | 0x9f7bffffU, 0x9fffff5fU, | |
285 | 0x3efffffbU, 0xfffff7bbU, | |
286 | 0xa8000001U, 0xaf5390a3U, | |
287 | 0xb740b3f8U, 0x6c11486dU> | |
288 | sfmt4253; | |
289 | ||
290 | typedef simd_fast_mersenne_twister_engine<uint64_t, 4253, 17, | |
291 | 20, 1, 7, 1, | |
292 | 0x9f7bffffU, 0x9fffff5fU, | |
293 | 0x3efffffbU, 0xfffff7bbU, | |
294 | 0xa8000001U, 0xaf5390a3U, | |
295 | 0xb740b3f8U, 0x6c11486dU> | |
296 | sfmt4253_64; | |
297 | ||
298 | ||
299 | typedef simd_fast_mersenne_twister_engine<uint32_t, 11213, 68, | |
300 | 14, 3, 7, 3, | |
301 | 0xeffff7fbU, 0xffffffefU, | |
302 | 0xdfdfbfffU, 0x7fffdbfdU, | |
303 | 0x00000001U, 0x00000000U, | |
304 | 0xe8148000U, 0xd0c7afa3U> | |
305 | sfmt11213; | |
306 | ||
307 | typedef simd_fast_mersenne_twister_engine<uint64_t, 11213, 68, | |
308 | 14, 3, 7, 3, | |
309 | 0xeffff7fbU, 0xffffffefU, | |
310 | 0xdfdfbfffU, 0x7fffdbfdU, | |
311 | 0x00000001U, 0x00000000U, | |
312 | 0xe8148000U, 0xd0c7afa3U> | |
313 | sfmt11213_64; | |
314 | ||
315 | ||
316 | typedef simd_fast_mersenne_twister_engine<uint32_t, 19937, 122, | |
317 | 18, 1, 11, 1, | |
318 | 0xdfffffefU, 0xddfecb7fU, | |
319 | 0xbffaffffU, 0xbffffff6U, | |
320 | 0x00000001U, 0x00000000U, | |
321 | 0x00000000U, 0x13c9e684U> | |
322 | sfmt19937; | |
323 | ||
324 | typedef simd_fast_mersenne_twister_engine<uint64_t, 19937, 122, | |
325 | 18, 1, 11, 1, | |
326 | 0xdfffffefU, 0xddfecb7fU, | |
327 | 0xbffaffffU, 0xbffffff6U, | |
328 | 0x00000001U, 0x00000000U, | |
329 | 0x00000000U, 0x13c9e684U> | |
330 | sfmt19937_64; | |
331 | ||
332 | ||
333 | typedef simd_fast_mersenne_twister_engine<uint32_t, 44497, 330, | |
334 | 5, 3, 9, 3, | |
335 | 0xeffffffbU, 0xdfbebfffU, | |
336 | 0xbfbf7befU, 0x9ffd7bffU, | |
337 | 0x00000001U, 0x00000000U, | |
338 | 0xa3ac4000U, 0xecc1327aU> | |
339 | sfmt44497; | |
340 | ||
341 | typedef simd_fast_mersenne_twister_engine<uint64_t, 44497, 330, | |
342 | 5, 3, 9, 3, | |
343 | 0xeffffffbU, 0xdfbebfffU, | |
344 | 0xbfbf7befU, 0x9ffd7bffU, | |
345 | 0x00000001U, 0x00000000U, | |
346 | 0xa3ac4000U, 0xecc1327aU> | |
347 | sfmt44497_64; | |
348 | ||
349 | ||
350 | typedef simd_fast_mersenne_twister_engine<uint32_t, 86243, 366, | |
351 | 6, 7, 19, 1, | |
352 | 0xfdbffbffU, 0xbff7ff3fU, | |
353 | 0xfd77efffU, 0xbf9ff3ffU, | |
354 | 0x00000001U, 0x00000000U, | |
355 | 0x00000000U, 0xe9528d85U> | |
356 | sfmt86243; | |
357 | ||
358 | typedef simd_fast_mersenne_twister_engine<uint64_t, 86243, 366, | |
359 | 6, 7, 19, 1, | |
360 | 0xfdbffbffU, 0xbff7ff3fU, | |
361 | 0xfd77efffU, 0xbf9ff3ffU, | |
362 | 0x00000001U, 0x00000000U, | |
363 | 0x00000000U, 0xe9528d85U> | |
364 | sfmt86243_64; | |
365 | ||
366 | ||
367 | typedef simd_fast_mersenne_twister_engine<uint32_t, 132049, 110, | |
368 | 19, 1, 21, 1, | |
369 | 0xffffbb5fU, 0xfb6ebf95U, | |
370 | 0xfffefffaU, 0xcff77fffU, | |
371 | 0x00000001U, 0x00000000U, | |
372 | 0xcb520000U, 0xc7e91c7dU> | |
373 | sfmt132049; | |
374 | ||
375 | typedef simd_fast_mersenne_twister_engine<uint64_t, 132049, 110, | |
376 | 19, 1, 21, 1, | |
377 | 0xffffbb5fU, 0xfb6ebf95U, | |
378 | 0xfffefffaU, 0xcff77fffU, | |
379 | 0x00000001U, 0x00000000U, | |
380 | 0xcb520000U, 0xc7e91c7dU> | |
381 | sfmt132049_64; | |
382 | ||
383 | ||
384 | typedef simd_fast_mersenne_twister_engine<uint32_t, 216091, 627, | |
385 | 11, 3, 10, 1, | |
386 | 0xbff7bff7U, 0xbfffffffU, | |
387 | 0xbffffa7fU, 0xffddfbfbU, | |
388 | 0xf8000001U, 0x89e80709U, | |
389 | 0x3bd2b64bU, 0x0c64b1e4U> | |
390 | sfmt216091; | |
391 | ||
392 | typedef simd_fast_mersenne_twister_engine<uint64_t, 216091, 627, | |
393 | 11, 3, 10, 1, | |
394 | 0xbff7bff7U, 0xbfffffffU, | |
395 | 0xbffffa7fU, 0xffddfbfbU, | |
396 | 0xf8000001U, 0x89e80709U, | |
397 | 0x3bd2b64bU, 0x0c64b1e4U> | |
398 | sfmt216091_64; | |
399 | ||
eeeef8f4 | 400 | #endif // __BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__ |
d4d348a9 UD |
401 | |
402 | /** | |
403 | * @brief A beta continuous distribution for random numbers. | |
404 | * | |
405 | * The formula for the beta probability density function is: | |
406 | * @f[ | |
407 | * p(x|\alpha,\beta) = \frac{1}{B(\alpha,\beta)} | |
408 | * x^{\alpha - 1} (1 - x)^{\beta - 1} | |
409 | * @f] | |
410 | */ | |
411 | template<typename _RealType = double> | |
412 | class beta_distribution | |
413 | { | |
414 | static_assert(std::is_floating_point<_RealType>::value, | |
415 | "template argument not a floating point type"); | |
416 | ||
417 | public: | |
418 | /** The type of the range of the distribution. */ | |
419 | typedef _RealType result_type; | |
12905f10 | 420 | |
d4d348a9 UD |
421 | /** Parameter type. */ |
422 | struct param_type | |
423 | { | |
424 | typedef beta_distribution<_RealType> distribution_type; | |
425 | friend class beta_distribution<_RealType>; | |
426 | ||
977ac63e JW |
427 | param_type() : param_type(1) { } |
428 | ||
d4d348a9 | 429 | explicit |
977ac63e | 430 | param_type(_RealType __alpha_val, _RealType __beta_val = _RealType(1)) |
d4d348a9 UD |
431 | : _M_alpha(__alpha_val), _M_beta(__beta_val) |
432 | { | |
2f1e8e7c JW |
433 | __glibcxx_assert(_M_alpha > _RealType(0)); |
434 | __glibcxx_assert(_M_beta > _RealType(0)); | |
d4d348a9 UD |
435 | } |
436 | ||
437 | _RealType | |
438 | alpha() const | |
439 | { return _M_alpha; } | |
440 | ||
441 | _RealType | |
442 | beta() const | |
443 | { return _M_beta; } | |
444 | ||
445 | friend bool | |
446 | operator==(const param_type& __p1, const param_type& __p2) | |
447 | { return (__p1._M_alpha == __p2._M_alpha | |
448 | && __p1._M_beta == __p2._M_beta); } | |
449 | ||
12905f10 JW |
450 | friend bool |
451 | operator!=(const param_type& __p1, const param_type& __p2) | |
452 | { return !(__p1 == __p2); } | |
453 | ||
d4d348a9 UD |
454 | private: |
455 | void | |
456 | _M_initialize(); | |
457 | ||
458 | _RealType _M_alpha; | |
459 | _RealType _M_beta; | |
460 | }; | |
461 | ||
462 | public: | |
dd9db6f8 JW |
463 | beta_distribution() : beta_distribution(1.0) { } |
464 | ||
d4d348a9 UD |
465 | /** |
466 | * @brief Constructs a beta distribution with parameters | |
467 | * @f$\alpha@f$ and @f$\beta@f$. | |
468 | */ | |
469 | explicit | |
dd9db6f8 | 470 | beta_distribution(_RealType __alpha_val, |
d4d348a9 UD |
471 | _RealType __beta_val = _RealType(1)) |
472 | : _M_param(__alpha_val, __beta_val) | |
473 | { } | |
474 | ||
475 | explicit | |
476 | beta_distribution(const param_type& __p) | |
477 | : _M_param(__p) | |
478 | { } | |
479 | ||
480 | /** | |
481 | * @brief Resets the distribution state. | |
482 | */ | |
483 | void | |
484 | reset() | |
485 | { } | |
486 | ||
487 | /** | |
488 | * @brief Returns the @f$\alpha@f$ of the distribution. | |
489 | */ | |
490 | _RealType | |
491 | alpha() const | |
492 | { return _M_param.alpha(); } | |
493 | ||
494 | /** | |
495 | * @brief Returns the @f$\beta@f$ of the distribution. | |
496 | */ | |
497 | _RealType | |
498 | beta() const | |
499 | { return _M_param.beta(); } | |
500 | ||
501 | /** | |
502 | * @brief Returns the parameter set of the distribution. | |
503 | */ | |
504 | param_type | |
505 | param() const | |
506 | { return _M_param; } | |
507 | ||
508 | /** | |
509 | * @brief Sets the parameter set of the distribution. | |
510 | * @param __param The new parameter set of the distribution. | |
511 | */ | |
512 | void | |
513 | param(const param_type& __param) | |
514 | { _M_param = __param; } | |
515 | ||
516 | /** | |
517 | * @brief Returns the greatest lower bound value of the distribution. | |
518 | */ | |
519 | result_type | |
520 | min() const | |
521 | { return result_type(0); } | |
522 | ||
523 | /** | |
524 | * @brief Returns the least upper bound value of the distribution. | |
525 | */ | |
526 | result_type | |
527 | max() const | |
528 | { return result_type(1); } | |
529 | ||
530 | /** | |
531 | * @brief Generating functions. | |
532 | */ | |
533 | template<typename _UniformRandomNumberGenerator> | |
534 | result_type | |
535 | operator()(_UniformRandomNumberGenerator& __urng) | |
5bcb3b4d | 536 | { return this->operator()(__urng, _M_param); } |
d4d348a9 UD |
537 | |
538 | template<typename _UniformRandomNumberGenerator> | |
539 | result_type | |
540 | operator()(_UniformRandomNumberGenerator& __urng, | |
541 | const param_type& __p); | |
542 | ||
543 | template<typename _ForwardIterator, | |
544 | typename _UniformRandomNumberGenerator> | |
545 | void | |
546 | __generate(_ForwardIterator __f, _ForwardIterator __t, | |
547 | _UniformRandomNumberGenerator& __urng) | |
5bcb3b4d | 548 | { this->__generate(__f, __t, __urng, _M_param); } |
d4d348a9 UD |
549 | |
550 | template<typename _ForwardIterator, | |
551 | typename _UniformRandomNumberGenerator> | |
552 | void | |
553 | __generate(_ForwardIterator __f, _ForwardIterator __t, | |
554 | _UniformRandomNumberGenerator& __urng, | |
555 | const param_type& __p) | |
556 | { this->__generate_impl(__f, __t, __urng, __p); } | |
557 | ||
558 | template<typename _UniformRandomNumberGenerator> | |
559 | void | |
560 | __generate(result_type* __f, result_type* __t, | |
561 | _UniformRandomNumberGenerator& __urng, | |
562 | const param_type& __p) | |
563 | { this->__generate_impl(__f, __t, __urng, __p); } | |
564 | ||
5bcb3b4d PC |
565 | /** |
566 | * @brief Return true if two beta distributions have the same | |
567 | * parameters and the sequences that would be generated | |
568 | * are equal. | |
569 | */ | |
570 | friend bool | |
571 | operator==(const beta_distribution& __d1, | |
572 | const beta_distribution& __d2) | |
573 | { return __d1._M_param == __d2._M_param; } | |
574 | ||
d4d348a9 UD |
575 | /** |
576 | * @brief Inserts a %beta_distribution random number distribution | |
577 | * @p __x into the output stream @p __os. | |
578 | * | |
579 | * @param __os An output stream. | |
580 | * @param __x A %beta_distribution random number distribution. | |
581 | * | |
582 | * @returns The output stream with the state of @p __x inserted or in | |
583 | * an error state. | |
584 | */ | |
585 | template<typename _RealType1, typename _CharT, typename _Traits> | |
586 | friend std::basic_ostream<_CharT, _Traits>& | |
587 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
588 | const __gnu_cxx::beta_distribution<_RealType1>& __x); | |
589 | ||
590 | /** | |
591 | * @brief Extracts a %beta_distribution random number distribution | |
592 | * @p __x from the input stream @p __is. | |
593 | * | |
594 | * @param __is An input stream. | |
595 | * @param __x A %beta_distribution random number generator engine. | |
596 | * | |
597 | * @returns The input stream with @p __x extracted or in an error state. | |
598 | */ | |
599 | template<typename _RealType1, typename _CharT, typename _Traits> | |
600 | friend std::basic_istream<_CharT, _Traits>& | |
601 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
602 | __gnu_cxx::beta_distribution<_RealType1>& __x); | |
603 | ||
604 | private: | |
605 | template<typename _ForwardIterator, | |
606 | typename _UniformRandomNumberGenerator> | |
607 | void | |
608 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
609 | _UniformRandomNumberGenerator& __urng, | |
610 | const param_type& __p); | |
611 | ||
612 | param_type _M_param; | |
613 | }; | |
614 | ||
615 | /** | |
616 | * @brief Return true if two beta distributions are different. | |
617 | */ | |
28312618 ESR |
618 | template<typename _RealType> |
619 | inline bool | |
620 | operator!=(const __gnu_cxx::beta_distribution<_RealType>& __d1, | |
621 | const __gnu_cxx::beta_distribution<_RealType>& __d2) | |
026ae646 | 622 | { return !(__d1 == __d2); } |
d4d348a9 UD |
623 | |
624 | ||
bf30f229 UD |
625 | /** |
626 | * @brief A multi-variate normal continuous distribution for random numbers. | |
627 | * | |
628 | * The formula for the normal probability density function is | |
629 | * @f[ | |
630 | * p(\overrightarrow{x}|\overrightarrow{\mu },\Sigma) = | |
631 | * \frac{1}{\sqrt{(2\pi )^k\det(\Sigma))}} | |
632 | * e^{-\frac{1}{2}(\overrightarrow{x}-\overrightarrow{\mu})^\text{T} | |
633 | * \Sigma ^{-1}(\overrightarrow{x}-\overrightarrow{\mu})} | |
634 | * @f] | |
635 | * | |
636 | * where @f$\overrightarrow{x}@f$ and @f$\overrightarrow{\mu}@f$ are | |
637 | * vectors of dimension @f$k@f$ and @f$\Sigma@f$ is the covariance | |
638 | * matrix (which must be positive-definite). | |
639 | */ | |
640 | template<std::size_t _Dimen, typename _RealType = double> | |
641 | class normal_mv_distribution | |
642 | { | |
643 | static_assert(std::is_floating_point<_RealType>::value, | |
644 | "template argument not a floating point type"); | |
645 | static_assert(_Dimen != 0, "dimension is zero"); | |
646 | ||
647 | public: | |
648 | /** The type of the range of the distribution. */ | |
649 | typedef std::array<_RealType, _Dimen> result_type; | |
650 | /** Parameter type. */ | |
651 | class param_type | |
652 | { | |
653 | static constexpr size_t _M_t_size = _Dimen * (_Dimen + 1) / 2; | |
654 | ||
655 | public: | |
656 | typedef normal_mv_distribution<_Dimen, _RealType> distribution_type; | |
657 | friend class normal_mv_distribution<_Dimen, _RealType>; | |
658 | ||
659 | param_type() | |
660 | { | |
661 | std::fill(_M_mean.begin(), _M_mean.end(), _RealType(0)); | |
662 | auto __it = _M_t.begin(); | |
663 | for (size_t __i = 0; __i < _Dimen; ++__i) | |
664 | { | |
665 | std::fill_n(__it, __i, _RealType(0)); | |
666 | __it += __i; | |
667 | *__it++ = _RealType(1); | |
668 | } | |
669 | } | |
670 | ||
671 | template<typename _ForwardIterator1, typename _ForwardIterator2> | |
672 | param_type(_ForwardIterator1 __meanbegin, | |
673 | _ForwardIterator1 __meanend, | |
674 | _ForwardIterator2 __varcovbegin, | |
675 | _ForwardIterator2 __varcovend) | |
676 | { | |
677 | __glibcxx_function_requires(_ForwardIteratorConcept< | |
678 | _ForwardIterator1>) | |
679 | __glibcxx_function_requires(_ForwardIteratorConcept< | |
680 | _ForwardIterator2>) | |
681 | _GLIBCXX_DEBUG_ASSERT(std::distance(__meanbegin, __meanend) | |
682 | <= _Dimen); | |
683 | const auto __dist = std::distance(__varcovbegin, __varcovend); | |
684 | _GLIBCXX_DEBUG_ASSERT(__dist == _Dimen * _Dimen | |
685 | || __dist == _Dimen * (_Dimen + 1) / 2 | |
686 | || __dist == _Dimen); | |
687 | ||
688 | if (__dist == _Dimen * _Dimen) | |
689 | _M_init_full(__meanbegin, __meanend, __varcovbegin, __varcovend); | |
690 | else if (__dist == _Dimen * (_Dimen + 1) / 2) | |
691 | _M_init_lower(__meanbegin, __meanend, __varcovbegin, __varcovend); | |
692 | else | |
2f1e8e7c JW |
693 | { |
694 | __glibcxx_assert(__dist == _Dimen); | |
695 | _M_init_diagonal(__meanbegin, __meanend, | |
696 | __varcovbegin, __varcovend); | |
697 | } | |
bf30f229 UD |
698 | } |
699 | ||
700 | param_type(std::initializer_list<_RealType> __mean, | |
701 | std::initializer_list<_RealType> __varcov) | |
702 | { | |
703 | _GLIBCXX_DEBUG_ASSERT(__mean.size() <= _Dimen); | |
704 | _GLIBCXX_DEBUG_ASSERT(__varcov.size() == _Dimen * _Dimen | |
705 | || __varcov.size() == _Dimen * (_Dimen + 1) / 2 | |
706 | || __varcov.size() == _Dimen); | |
707 | ||
708 | if (__varcov.size() == _Dimen * _Dimen) | |
709 | _M_init_full(__mean.begin(), __mean.end(), | |
710 | __varcov.begin(), __varcov.end()); | |
711 | else if (__varcov.size() == _Dimen * (_Dimen + 1) / 2) | |
712 | _M_init_lower(__mean.begin(), __mean.end(), | |
713 | __varcov.begin(), __varcov.end()); | |
714 | else | |
2f1e8e7c JW |
715 | { |
716 | __glibcxx_assert(__varcov.size() == _Dimen); | |
717 | _M_init_diagonal(__mean.begin(), __mean.end(), | |
718 | __varcov.begin(), __varcov.end()); | |
719 | } | |
bf30f229 UD |
720 | } |
721 | ||
722 | std::array<_RealType, _Dimen> | |
723 | mean() const | |
724 | { return _M_mean; } | |
725 | ||
726 | std::array<_RealType, _M_t_size> | |
727 | varcov() const | |
728 | { return _M_t; } | |
729 | ||
730 | friend bool | |
731 | operator==(const param_type& __p1, const param_type& __p2) | |
732 | { return __p1._M_mean == __p2._M_mean && __p1._M_t == __p2._M_t; } | |
733 | ||
12905f10 JW |
734 | friend bool |
735 | operator!=(const param_type& __p1, const param_type& __p2) | |
736 | { return !(__p1 == __p2); } | |
737 | ||
bf30f229 UD |
738 | private: |
739 | template <typename _InputIterator1, typename _InputIterator2> | |
740 | void _M_init_full(_InputIterator1 __meanbegin, | |
741 | _InputIterator1 __meanend, | |
742 | _InputIterator2 __varcovbegin, | |
743 | _InputIterator2 __varcovend); | |
744 | template <typename _InputIterator1, typename _InputIterator2> | |
745 | void _M_init_lower(_InputIterator1 __meanbegin, | |
746 | _InputIterator1 __meanend, | |
747 | _InputIterator2 __varcovbegin, | |
748 | _InputIterator2 __varcovend); | |
749 | template <typename _InputIterator1, typename _InputIterator2> | |
750 | void _M_init_diagonal(_InputIterator1 __meanbegin, | |
751 | _InputIterator1 __meanend, | |
752 | _InputIterator2 __varbegin, | |
753 | _InputIterator2 __varend); | |
754 | ||
c787deb0 AO |
755 | // param_type constructors apply Cholesky decomposition to the |
756 | // varcov matrix in _M_init_full and _M_init_lower, but the | |
757 | // varcov matrix output ot a stream is already decomposed, so | |
758 | // we need means to restore it as-is when reading it back in. | |
759 | template<size_t _Dimen1, typename _RealType1, | |
760 | typename _CharT, typename _Traits> | |
761 | friend std::basic_istream<_CharT, _Traits>& | |
762 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
763 | __gnu_cxx::normal_mv_distribution<_Dimen1, _RealType1>& | |
764 | __x); | |
765 | param_type(std::array<_RealType, _Dimen> const &__mean, | |
766 | std::array<_RealType, _M_t_size> const &__varcov) | |
767 | : _M_mean (__mean), _M_t (__varcov) | |
768 | {} | |
769 | ||
bf30f229 UD |
770 | std::array<_RealType, _Dimen> _M_mean; |
771 | std::array<_RealType, _M_t_size> _M_t; | |
772 | }; | |
773 | ||
774 | public: | |
775 | normal_mv_distribution() | |
776 | : _M_param(), _M_nd() | |
777 | { } | |
778 | ||
779 | template<typename _ForwardIterator1, typename _ForwardIterator2> | |
780 | normal_mv_distribution(_ForwardIterator1 __meanbegin, | |
781 | _ForwardIterator1 __meanend, | |
782 | _ForwardIterator2 __varcovbegin, | |
783 | _ForwardIterator2 __varcovend) | |
784 | : _M_param(__meanbegin, __meanend, __varcovbegin, __varcovend), | |
785 | _M_nd() | |
786 | { } | |
787 | ||
788 | normal_mv_distribution(std::initializer_list<_RealType> __mean, | |
789 | std::initializer_list<_RealType> __varcov) | |
790 | : _M_param(__mean, __varcov), _M_nd() | |
791 | { } | |
792 | ||
793 | explicit | |
794 | normal_mv_distribution(const param_type& __p) | |
795 | : _M_param(__p), _M_nd() | |
796 | { } | |
797 | ||
798 | /** | |
799 | * @brief Resets the distribution state. | |
800 | */ | |
801 | void | |
802 | reset() | |
803 | { _M_nd.reset(); } | |
804 | ||
805 | /** | |
806 | * @brief Returns the mean of the distribution. | |
807 | */ | |
808 | result_type | |
809 | mean() const | |
810 | { return _M_param.mean(); } | |
811 | ||
812 | /** | |
813 | * @brief Returns the compact form of the variance/covariance | |
814 | * matrix of the distribution. | |
815 | */ | |
816 | std::array<_RealType, _Dimen * (_Dimen + 1) / 2> | |
817 | varcov() const | |
818 | { return _M_param.varcov(); } | |
819 | ||
820 | /** | |
821 | * @brief Returns the parameter set of the distribution. | |
822 | */ | |
823 | param_type | |
824 | param() const | |
825 | { return _M_param; } | |
826 | ||
827 | /** | |
828 | * @brief Sets the parameter set of the distribution. | |
829 | * @param __param The new parameter set of the distribution. | |
830 | */ | |
831 | void | |
832 | param(const param_type& __param) | |
833 | { _M_param = __param; } | |
834 | ||
835 | /** | |
836 | * @brief Returns the greatest lower bound value of the distribution. | |
837 | */ | |
838 | result_type | |
839 | min() const | |
840 | { result_type __res; | |
a803975d | 841 | __res.fill(std::numeric_limits<_RealType>::lowest()); |
bf30f229 UD |
842 | return __res; } |
843 | ||
844 | /** | |
845 | * @brief Returns the least upper bound value of the distribution. | |
846 | */ | |
847 | result_type | |
848 | max() const | |
849 | { result_type __res; | |
850 | __res.fill(std::numeric_limits<_RealType>::max()); | |
851 | return __res; } | |
852 | ||
853 | /** | |
854 | * @brief Generating functions. | |
855 | */ | |
856 | template<typename _UniformRandomNumberGenerator> | |
857 | result_type | |
858 | operator()(_UniformRandomNumberGenerator& __urng) | |
5bcb3b4d | 859 | { return this->operator()(__urng, _M_param); } |
bf30f229 UD |
860 | |
861 | template<typename _UniformRandomNumberGenerator> | |
862 | result_type | |
863 | operator()(_UniformRandomNumberGenerator& __urng, | |
864 | const param_type& __p); | |
865 | ||
866 | template<typename _ForwardIterator, | |
867 | typename _UniformRandomNumberGenerator> | |
868 | void | |
869 | __generate(_ForwardIterator __f, _ForwardIterator __t, | |
870 | _UniformRandomNumberGenerator& __urng) | |
5bcb3b4d | 871 | { return this->__generate_impl(__f, __t, __urng, _M_param); } |
bf30f229 UD |
872 | |
873 | template<typename _ForwardIterator, | |
874 | typename _UniformRandomNumberGenerator> | |
875 | void | |
876 | __generate(_ForwardIterator __f, _ForwardIterator __t, | |
877 | _UniformRandomNumberGenerator& __urng, | |
878 | const param_type& __p) | |
879 | { return this->__generate_impl(__f, __t, __urng, __p); } | |
880 | ||
881 | /** | |
882 | * @brief Return true if two multi-variant normal distributions have | |
883 | * the same parameters and the sequences that would | |
884 | * be generated are equal. | |
885 | */ | |
886 | template<size_t _Dimen1, typename _RealType1> | |
887 | friend bool | |
888 | operator==(const | |
889 | __gnu_cxx::normal_mv_distribution<_Dimen1, _RealType1>& | |
890 | __d1, | |
891 | const | |
892 | __gnu_cxx::normal_mv_distribution<_Dimen1, _RealType1>& | |
893 | __d2); | |
894 | ||
895 | /** | |
896 | * @brief Inserts a %normal_mv_distribution random number distribution | |
897 | * @p __x into the output stream @p __os. | |
898 | * | |
899 | * @param __os An output stream. | |
900 | * @param __x A %normal_mv_distribution random number distribution. | |
901 | * | |
902 | * @returns The output stream with the state of @p __x inserted or in | |
903 | * an error state. | |
904 | */ | |
905 | template<size_t _Dimen1, typename _RealType1, | |
906 | typename _CharT, typename _Traits> | |
907 | friend std::basic_ostream<_CharT, _Traits>& | |
908 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
909 | const | |
910 | __gnu_cxx::normal_mv_distribution<_Dimen1, _RealType1>& | |
911 | __x); | |
912 | ||
913 | /** | |
914 | * @brief Extracts a %normal_mv_distribution random number distribution | |
915 | * @p __x from the input stream @p __is. | |
916 | * | |
917 | * @param __is An input stream. | |
918 | * @param __x A %normal_mv_distribution random number generator engine. | |
919 | * | |
920 | * @returns The input stream with @p __x extracted or in an error | |
921 | * state. | |
922 | */ | |
923 | template<size_t _Dimen1, typename _RealType1, | |
924 | typename _CharT, typename _Traits> | |
925 | friend std::basic_istream<_CharT, _Traits>& | |
926 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
927 | __gnu_cxx::normal_mv_distribution<_Dimen1, _RealType1>& | |
928 | __x); | |
929 | ||
930 | private: | |
931 | template<typename _ForwardIterator, | |
932 | typename _UniformRandomNumberGenerator> | |
933 | void | |
934 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
935 | _UniformRandomNumberGenerator& __urng, | |
936 | const param_type& __p); | |
937 | ||
938 | param_type _M_param; | |
939 | std::normal_distribution<_RealType> _M_nd; | |
940 | }; | |
941 | ||
942 | /** | |
943 | * @brief Return true if two multi-variate normal distributions are | |
944 | * different. | |
945 | */ | |
946 | template<size_t _Dimen, typename _RealType> | |
947 | inline bool | |
948 | operator!=(const __gnu_cxx::normal_mv_distribution<_Dimen, _RealType>& | |
949 | __d1, | |
950 | const __gnu_cxx::normal_mv_distribution<_Dimen, _RealType>& | |
951 | __d2) | |
952 | { return !(__d1 == __d2); } | |
953 | ||
d4d348a9 | 954 | |
28312618 ESR |
955 | /** |
956 | * @brief A Rice continuous distribution for random numbers. | |
957 | * | |
958 | * The formula for the Rice probability density function is | |
959 | * @f[ | |
960 | * p(x|\nu,\sigma) = \frac{x}{\sigma^2} | |
961 | * \exp\left(-\frac{x^2+\nu^2}{2\sigma^2}\right) | |
962 | * I_0\left(\frac{x \nu}{\sigma^2}\right) | |
963 | * @f] | |
964 | * where @f$I_0(z)@f$ is the modified Bessel function of the first kind | |
965 | * of order 0 and @f$\nu >= 0@f$ and @f$\sigma > 0@f$. | |
966 | * | |
967 | * <table border=1 cellpadding=10 cellspacing=0> | |
968 | * <caption align=top>Distribution Statistics</caption> | |
969 | * <tr><td>Mean</td><td>@f$\sqrt{\pi/2}L_{1/2}(-\nu^2/2\sigma^2)@f$</td></tr> | |
970 | * <tr><td>Variance</td><td>@f$2\sigma^2 + \nu^2 | |
971 | * + (\pi\sigma^2/2)L^2_{1/2}(-\nu^2/2\sigma^2)@f$</td></tr> | |
972 | * <tr><td>Range</td><td>@f$[0, \infty)@f$</td></tr> | |
973 | * </table> | |
974 | * where @f$L_{1/2}(x)@f$ is the Laguerre polynomial of order 1/2. | |
975 | */ | |
976 | template<typename _RealType = double> | |
977 | class | |
978 | rice_distribution | |
979 | { | |
980 | static_assert(std::is_floating_point<_RealType>::value, | |
981 | "template argument not a floating point type"); | |
982 | public: | |
983 | /** The type of the range of the distribution. */ | |
984 | typedef _RealType result_type; | |
12905f10 | 985 | |
28312618 ESR |
986 | /** Parameter type. */ |
987 | struct param_type | |
988 | { | |
989 | typedef rice_distribution<result_type> distribution_type; | |
990 | ||
977ac63e JW |
991 | param_type() : param_type(0) { } |
992 | ||
993 | param_type(result_type __nu_val, | |
37f1d5c9 UB |
994 | result_type __sigma_val = result_type(1)) |
995 | : _M_nu(__nu_val), _M_sigma(__sigma_val) | |
28312618 | 996 | { |
2f1e8e7c JW |
997 | __glibcxx_assert(_M_nu >= result_type(0)); |
998 | __glibcxx_assert(_M_sigma > result_type(0)); | |
28312618 ESR |
999 | } |
1000 | ||
1001 | result_type | |
1002 | nu() const | |
1003 | { return _M_nu; } | |
1004 | ||
1005 | result_type | |
1006 | sigma() const | |
1007 | { return _M_sigma; } | |
1008 | ||
1009 | friend bool | |
1010 | operator==(const param_type& __p1, const param_type& __p2) | |
12905f10 JW |
1011 | { return __p1._M_nu == __p2._M_nu && __p1._M_sigma == __p2._M_sigma; } |
1012 | ||
1013 | friend bool | |
1014 | operator!=(const param_type& __p1, const param_type& __p2) | |
1015 | { return !(__p1 == __p2); } | |
28312618 ESR |
1016 | |
1017 | private: | |
1018 | void _M_initialize(); | |
1019 | ||
1020 | result_type _M_nu; | |
1021 | result_type _M_sigma; | |
1022 | }; | |
1023 | ||
1024 | /** | |
1025 | * @brief Constructors. | |
dd9db6f8 | 1026 | * @{ |
28312618 | 1027 | */ |
dd9db6f8 JW |
1028 | |
1029 | rice_distribution() : rice_distribution(0) { } | |
1030 | ||
28312618 | 1031 | explicit |
dd9db6f8 | 1032 | rice_distribution(result_type __nu_val, |
37f1d5c9 UB |
1033 | result_type __sigma_val = result_type(1)) |
1034 | : _M_param(__nu_val, __sigma_val), | |
1035 | _M_ndx(__nu_val, __sigma_val), | |
1036 | _M_ndy(result_type(0), __sigma_val) | |
28312618 ESR |
1037 | { } |
1038 | ||
1039 | explicit | |
1040 | rice_distribution(const param_type& __p) | |
1041 | : _M_param(__p), | |
1042 | _M_ndx(__p.nu(), __p.sigma()), | |
1043 | _M_ndy(result_type(0), __p.sigma()) | |
1044 | { } | |
1045 | ||
f0b88346 | 1046 | /// @} |
dd9db6f8 | 1047 | |
28312618 ESR |
1048 | /** |
1049 | * @brief Resets the distribution state. | |
1050 | */ | |
1051 | void | |
1052 | reset() | |
1053 | { | |
1054 | _M_ndx.reset(); | |
1055 | _M_ndy.reset(); | |
1056 | } | |
1057 | ||
1058 | /** | |
1059 | * @brief Return the parameters of the distribution. | |
1060 | */ | |
1061 | result_type | |
1062 | nu() const | |
1063 | { return _M_param.nu(); } | |
1064 | ||
1065 | result_type | |
1066 | sigma() const | |
1067 | { return _M_param.sigma(); } | |
1068 | ||
1069 | /** | |
1070 | * @brief Returns the parameter set of the distribution. | |
1071 | */ | |
1072 | param_type | |
1073 | param() const | |
1074 | { return _M_param; } | |
1075 | ||
1076 | /** | |
1077 | * @brief Sets the parameter set of the distribution. | |
1078 | * @param __param The new parameter set of the distribution. | |
1079 | */ | |
1080 | void | |
1081 | param(const param_type& __param) | |
1082 | { _M_param = __param; } | |
1083 | ||
1084 | /** | |
1085 | * @brief Returns the greatest lower bound value of the distribution. | |
1086 | */ | |
1087 | result_type | |
1088 | min() const | |
1089 | { return result_type(0); } | |
1090 | ||
1091 | /** | |
1092 | * @brief Returns the least upper bound value of the distribution. | |
1093 | */ | |
1094 | result_type | |
1095 | max() const | |
1096 | { return std::numeric_limits<result_type>::max(); } | |
1097 | ||
1098 | /** | |
1099 | * @brief Generating functions. | |
1100 | */ | |
1101 | template<typename _UniformRandomNumberGenerator> | |
1102 | result_type | |
1103 | operator()(_UniformRandomNumberGenerator& __urng) | |
1104 | { | |
1105 | result_type __x = this->_M_ndx(__urng); | |
1106 | result_type __y = this->_M_ndy(__urng); | |
decf0e27 | 1107 | #if _GLIBCXX_USE_C99_MATH_TR1 |
28312618 | 1108 | return std::hypot(__x, __y); |
decf0e27 PC |
1109 | #else |
1110 | return std::sqrt(__x * __x + __y * __y); | |
1111 | #endif | |
28312618 ESR |
1112 | } |
1113 | ||
1114 | template<typename _UniformRandomNumberGenerator> | |
1115 | result_type | |
1116 | operator()(_UniformRandomNumberGenerator& __urng, | |
1117 | const param_type& __p) | |
d233c237 | 1118 | { |
28312618 ESR |
1119 | typename std::normal_distribution<result_type>::param_type |
1120 | __px(__p.nu(), __p.sigma()), __py(result_type(0), __p.sigma()); | |
1121 | result_type __x = this->_M_ndx(__px, __urng); | |
1122 | result_type __y = this->_M_ndy(__py, __urng); | |
decf0e27 | 1123 | #if _GLIBCXX_USE_C99_MATH_TR1 |
28312618 | 1124 | return std::hypot(__x, __y); |
decf0e27 PC |
1125 | #else |
1126 | return std::sqrt(__x * __x + __y * __y); | |
1127 | #endif | |
28312618 ESR |
1128 | } |
1129 | ||
1130 | template<typename _ForwardIterator, | |
1131 | typename _UniformRandomNumberGenerator> | |
1132 | void | |
1133 | __generate(_ForwardIterator __f, _ForwardIterator __t, | |
1134 | _UniformRandomNumberGenerator& __urng) | |
5bcb3b4d | 1135 | { this->__generate(__f, __t, __urng, _M_param); } |
28312618 ESR |
1136 | |
1137 | template<typename _ForwardIterator, | |
1138 | typename _UniformRandomNumberGenerator> | |
1139 | void | |
1140 | __generate(_ForwardIterator __f, _ForwardIterator __t, | |
1141 | _UniformRandomNumberGenerator& __urng, | |
1142 | const param_type& __p) | |
1143 | { this->__generate_impl(__f, __t, __urng, __p); } | |
1144 | ||
1145 | template<typename _UniformRandomNumberGenerator> | |
1146 | void | |
1147 | __generate(result_type* __f, result_type* __t, | |
1148 | _UniformRandomNumberGenerator& __urng, | |
1149 | const param_type& __p) | |
1150 | { this->__generate_impl(__f, __t, __urng, __p); } | |
1151 | ||
1152 | /** | |
1153 | * @brief Return true if two Rice distributions have | |
1154 | * the same parameters and the sequences that would | |
1155 | * be generated are equal. | |
1156 | */ | |
d9d69f64 PC |
1157 | friend bool |
1158 | operator==(const rice_distribution& __d1, | |
1159 | const rice_distribution& __d2) | |
5bcb3b4d | 1160 | { return (__d1._M_param == __d2._M_param |
d9d69f64 PC |
1161 | && __d1._M_ndx == __d2._M_ndx |
1162 | && __d1._M_ndy == __d2._M_ndy); } | |
28312618 ESR |
1163 | |
1164 | /** | |
1165 | * @brief Inserts a %rice_distribution random number distribution | |
1166 | * @p __x into the output stream @p __os. | |
1167 | * | |
1168 | * @param __os An output stream. | |
1169 | * @param __x A %rice_distribution random number distribution. | |
1170 | * | |
1171 | * @returns The output stream with the state of @p __x inserted or in | |
1172 | * an error state. | |
1173 | */ | |
1174 | template<typename _RealType1, typename _CharT, typename _Traits> | |
1175 | friend std::basic_ostream<_CharT, _Traits>& | |
1176 | operator<<(std::basic_ostream<_CharT, _Traits>&, | |
1177 | const rice_distribution<_RealType1>&); | |
1178 | ||
1179 | /** | |
1180 | * @brief Extracts a %rice_distribution random number distribution | |
1181 | * @p __x from the input stream @p __is. | |
1182 | * | |
1183 | * @param __is An input stream. | |
1184 | * @param __x A %rice_distribution random number | |
1185 | * generator engine. | |
1186 | * | |
1187 | * @returns The input stream with @p __x extracted or in an error state. | |
1188 | */ | |
1189 | template<typename _RealType1, typename _CharT, typename _Traits> | |
1190 | friend std::basic_istream<_CharT, _Traits>& | |
1191 | operator>>(std::basic_istream<_CharT, _Traits>&, | |
1192 | rice_distribution<_RealType1>&); | |
1193 | ||
1194 | private: | |
1195 | template<typename _ForwardIterator, | |
1196 | typename _UniformRandomNumberGenerator> | |
1197 | void | |
1198 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1199 | _UniformRandomNumberGenerator& __urng, | |
1200 | const param_type& __p); | |
1201 | ||
1202 | param_type _M_param; | |
1203 | ||
1204 | std::normal_distribution<result_type> _M_ndx; | |
1205 | std::normal_distribution<result_type> _M_ndy; | |
1206 | }; | |
1207 | ||
1208 | /** | |
1209 | * @brief Return true if two Rice distributions are not equal. | |
1210 | */ | |
1211 | template<typename _RealType1> | |
1212 | inline bool | |
1213 | operator!=(const rice_distribution<_RealType1>& __d1, | |
1214 | const rice_distribution<_RealType1>& __d2) | |
1215 | { return !(__d1 == __d2); } | |
1216 | ||
19ece7ec ESR |
1217 | |
1218 | /** | |
1219 | * @brief A Nakagami continuous distribution for random numbers. | |
1220 | * | |
1221 | * The formula for the Nakagami probability density function is | |
1222 | * @f[ | |
1223 | * p(x|\mu,\omega) = \frac{2\mu^\mu}{\Gamma(\mu)\omega^\mu} | |
1224 | * x^{2\mu-1}e^{-\mu x / \omega} | |
1225 | * @f] | |
1226 | * where @f$\Gamma(z)@f$ is the gamma function and @f$\mu >= 0.5@f$ | |
1227 | * and @f$\omega > 0@f$. | |
1228 | */ | |
1229 | template<typename _RealType = double> | |
1230 | class | |
1231 | nakagami_distribution | |
1232 | { | |
1233 | static_assert(std::is_floating_point<_RealType>::value, | |
1234 | "template argument not a floating point type"); | |
1235 | ||
1236 | public: | |
1237 | /** The type of the range of the distribution. */ | |
1238 | typedef _RealType result_type; | |
12905f10 | 1239 | |
19ece7ec ESR |
1240 | /** Parameter type. */ |
1241 | struct param_type | |
1242 | { | |
1243 | typedef nakagami_distribution<result_type> distribution_type; | |
1244 | ||
977ac63e JW |
1245 | param_type() : param_type(1) { } |
1246 | ||
1247 | param_type(result_type __mu_val, | |
37f1d5c9 UB |
1248 | result_type __omega_val = result_type(1)) |
1249 | : _M_mu(__mu_val), _M_omega(__omega_val) | |
19ece7ec | 1250 | { |
2f1e8e7c JW |
1251 | __glibcxx_assert(_M_mu >= result_type(0.5L)); |
1252 | __glibcxx_assert(_M_omega > result_type(0)); | |
19ece7ec ESR |
1253 | } |
1254 | ||
1255 | result_type | |
1256 | mu() const | |
1257 | { return _M_mu; } | |
1258 | ||
1259 | result_type | |
1260 | omega() const | |
1261 | { return _M_omega; } | |
1262 | ||
1263 | friend bool | |
1264 | operator==(const param_type& __p1, const param_type& __p2) | |
12905f10 JW |
1265 | { return __p1._M_mu == __p2._M_mu && __p1._M_omega == __p2._M_omega; } |
1266 | ||
1267 | friend bool | |
1268 | operator!=(const param_type& __p1, const param_type& __p2) | |
1269 | { return !(__p1 == __p2); } | |
19ece7ec ESR |
1270 | |
1271 | private: | |
1272 | void _M_initialize(); | |
1273 | ||
1274 | result_type _M_mu; | |
1275 | result_type _M_omega; | |
1276 | }; | |
1277 | ||
1278 | /** | |
1279 | * @brief Constructors. | |
dd9db6f8 | 1280 | * @{ |
19ece7ec | 1281 | */ |
dd9db6f8 JW |
1282 | |
1283 | nakagami_distribution() : nakagami_distribution(1) { } | |
1284 | ||
19ece7ec | 1285 | explicit |
dd9db6f8 | 1286 | nakagami_distribution(result_type __mu_val, |
37f1d5c9 UB |
1287 | result_type __omega_val = result_type(1)) |
1288 | : _M_param(__mu_val, __omega_val), | |
1289 | _M_gd(__mu_val, __omega_val / __mu_val) | |
19ece7ec ESR |
1290 | { } |
1291 | ||
1292 | explicit | |
1293 | nakagami_distribution(const param_type& __p) | |
1294 | : _M_param(__p), | |
1295 | _M_gd(__p.mu(), __p.omega() / __p.mu()) | |
1296 | { } | |
1297 | ||
f0b88346 | 1298 | /// @} |
dd9db6f8 | 1299 | |
19ece7ec ESR |
1300 | /** |
1301 | * @brief Resets the distribution state. | |
1302 | */ | |
1303 | void | |
1304 | reset() | |
1305 | { _M_gd.reset(); } | |
1306 | ||
1307 | /** | |
1308 | * @brief Return the parameters of the distribution. | |
1309 | */ | |
1310 | result_type | |
1311 | mu() const | |
1312 | { return _M_param.mu(); } | |
1313 | ||
1314 | result_type | |
1315 | omega() const | |
1316 | { return _M_param.omega(); } | |
1317 | ||
1318 | /** | |
1319 | * @brief Returns the parameter set of the distribution. | |
1320 | */ | |
1321 | param_type | |
1322 | param() const | |
1323 | { return _M_param; } | |
1324 | ||
1325 | /** | |
1326 | * @brief Sets the parameter set of the distribution. | |
1327 | * @param __param The new parameter set of the distribution. | |
1328 | */ | |
1329 | void | |
1330 | param(const param_type& __param) | |
1331 | { _M_param = __param; } | |
1332 | ||
1333 | /** | |
1334 | * @brief Returns the greatest lower bound value of the distribution. | |
1335 | */ | |
1336 | result_type | |
1337 | min() const | |
1338 | { return result_type(0); } | |
1339 | ||
1340 | /** | |
1341 | * @brief Returns the least upper bound value of the distribution. | |
1342 | */ | |
1343 | result_type | |
1344 | max() const | |
1345 | { return std::numeric_limits<result_type>::max(); } | |
1346 | ||
1347 | /** | |
1348 | * @brief Generating functions. | |
1349 | */ | |
1350 | template<typename _UniformRandomNumberGenerator> | |
1351 | result_type | |
1352 | operator()(_UniformRandomNumberGenerator& __urng) | |
1353 | { return std::sqrt(this->_M_gd(__urng)); } | |
1354 | ||
1355 | template<typename _UniformRandomNumberGenerator> | |
1356 | result_type | |
1357 | operator()(_UniformRandomNumberGenerator& __urng, | |
1358 | const param_type& __p) | |
d233c237 | 1359 | { |
19ece7ec ESR |
1360 | typename std::gamma_distribution<result_type>::param_type |
1361 | __pg(__p.mu(), __p.omega() / __p.mu()); | |
1362 | return std::sqrt(this->_M_gd(__pg, __urng)); | |
1363 | } | |
1364 | ||
1365 | template<typename _ForwardIterator, | |
1366 | typename _UniformRandomNumberGenerator> | |
1367 | void | |
1368 | __generate(_ForwardIterator __f, _ForwardIterator __t, | |
1369 | _UniformRandomNumberGenerator& __urng) | |
5bcb3b4d | 1370 | { this->__generate(__f, __t, __urng, _M_param); } |
19ece7ec ESR |
1371 | |
1372 | template<typename _ForwardIterator, | |
1373 | typename _UniformRandomNumberGenerator> | |
1374 | void | |
1375 | __generate(_ForwardIterator __f, _ForwardIterator __t, | |
1376 | _UniformRandomNumberGenerator& __urng, | |
1377 | const param_type& __p) | |
1378 | { this->__generate_impl(__f, __t, __urng, __p); } | |
1379 | ||
1380 | template<typename _UniformRandomNumberGenerator> | |
1381 | void | |
1382 | __generate(result_type* __f, result_type* __t, | |
1383 | _UniformRandomNumberGenerator& __urng, | |
1384 | const param_type& __p) | |
1385 | { this->__generate_impl(__f, __t, __urng, __p); } | |
1386 | ||
1387 | /** | |
1388 | * @brief Return true if two Nakagami distributions have | |
1389 | * the same parameters and the sequences that would | |
1390 | * be generated are equal. | |
1391 | */ | |
1392 | friend bool | |
1393 | operator==(const nakagami_distribution& __d1, | |
1394 | const nakagami_distribution& __d2) | |
5bcb3b4d | 1395 | { return (__d1._M_param == __d2._M_param |
19ece7ec ESR |
1396 | && __d1._M_gd == __d2._M_gd); } |
1397 | ||
1398 | /** | |
1399 | * @brief Inserts a %nakagami_distribution random number distribution | |
1400 | * @p __x into the output stream @p __os. | |
1401 | * | |
1402 | * @param __os An output stream. | |
1403 | * @param __x A %nakagami_distribution random number distribution. | |
1404 | * | |
1405 | * @returns The output stream with the state of @p __x inserted or in | |
1406 | * an error state. | |
1407 | */ | |
1408 | template<typename _RealType1, typename _CharT, typename _Traits> | |
1409 | friend std::basic_ostream<_CharT, _Traits>& | |
1410 | operator<<(std::basic_ostream<_CharT, _Traits>&, | |
1411 | const nakagami_distribution<_RealType1>&); | |
1412 | ||
1413 | /** | |
1414 | * @brief Extracts a %nakagami_distribution random number distribution | |
1415 | * @p __x from the input stream @p __is. | |
1416 | * | |
1417 | * @param __is An input stream. | |
1418 | * @param __x A %nakagami_distribution random number | |
1419 | * generator engine. | |
1420 | * | |
1421 | * @returns The input stream with @p __x extracted or in an error state. | |
1422 | */ | |
1423 | template<typename _RealType1, typename _CharT, typename _Traits> | |
1424 | friend std::basic_istream<_CharT, _Traits>& | |
1425 | operator>>(std::basic_istream<_CharT, _Traits>&, | |
1426 | nakagami_distribution<_RealType1>&); | |
1427 | ||
1428 | private: | |
1429 | template<typename _ForwardIterator, | |
1430 | typename _UniformRandomNumberGenerator> | |
1431 | void | |
1432 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1433 | _UniformRandomNumberGenerator& __urng, | |
1434 | const param_type& __p); | |
1435 | ||
1436 | param_type _M_param; | |
1437 | ||
1438 | std::gamma_distribution<result_type> _M_gd; | |
1439 | }; | |
1440 | ||
1441 | /** | |
1442 | * @brief Return true if two Nakagami distributions are not equal. | |
1443 | */ | |
1444 | template<typename _RealType> | |
1445 | inline bool | |
1446 | operator!=(const nakagami_distribution<_RealType>& __d1, | |
1447 | const nakagami_distribution<_RealType>& __d2) | |
1448 | { return !(__d1 == __d2); } | |
1449 | ||
0c105b72 ESR |
1450 | |
1451 | /** | |
1452 | * @brief A Pareto continuous distribution for random numbers. | |
1453 | * | |
1454 | * The formula for the Pareto cumulative probability function is | |
1455 | * @f[ | |
1456 | * P(x|\alpha,\mu) = 1 - \left(\frac{\mu}{x}\right)^\alpha | |
1457 | * @f] | |
1458 | * The formula for the Pareto probability density function is | |
1459 | * @f[ | |
1460 | * p(x|\alpha,\mu) = \frac{\alpha + 1}{\mu} | |
1461 | * \left(\frac{\mu}{x}\right)^{\alpha + 1} | |
1462 | * @f] | |
1463 | * where @f$x >= \mu@f$ and @f$\mu > 0@f$, @f$\alpha > 0@f$. | |
1464 | * | |
1465 | * <table border=1 cellpadding=10 cellspacing=0> | |
1466 | * <caption align=top>Distribution Statistics</caption> | |
1467 | * <tr><td>Mean</td><td>@f$\alpha \mu / (\alpha - 1)@f$ | |
1468 | * for @f$\alpha > 1@f$</td></tr> | |
1469 | * <tr><td>Variance</td><td>@f$\alpha \mu^2 / [(\alpha - 1)^2(\alpha - 2)]@f$ | |
1470 | * for @f$\alpha > 2@f$</td></tr> | |
1471 | * <tr><td>Range</td><td>@f$[\mu, \infty)@f$</td></tr> | |
1472 | * </table> | |
1473 | */ | |
1474 | template<typename _RealType = double> | |
1475 | class | |
1476 | pareto_distribution | |
1477 | { | |
1478 | static_assert(std::is_floating_point<_RealType>::value, | |
1479 | "template argument not a floating point type"); | |
1480 | ||
1481 | public: | |
1482 | /** The type of the range of the distribution. */ | |
1483 | typedef _RealType result_type; | |
12905f10 | 1484 | |
0c105b72 ESR |
1485 | /** Parameter type. */ |
1486 | struct param_type | |
1487 | { | |
1488 | typedef pareto_distribution<result_type> distribution_type; | |
1489 | ||
977ac63e JW |
1490 | param_type() : param_type(1) { } |
1491 | ||
1492 | param_type(result_type __alpha_val, | |
37f1d5c9 UB |
1493 | result_type __mu_val = result_type(1)) |
1494 | : _M_alpha(__alpha_val), _M_mu(__mu_val) | |
0c105b72 | 1495 | { |
2f1e8e7c JW |
1496 | __glibcxx_assert(_M_alpha > result_type(0)); |
1497 | __glibcxx_assert(_M_mu > result_type(0)); | |
0c105b72 ESR |
1498 | } |
1499 | ||
1500 | result_type | |
1501 | alpha() const | |
1502 | { return _M_alpha; } | |
1503 | ||
1504 | result_type | |
1505 | mu() const | |
1506 | { return _M_mu; } | |
1507 | ||
1508 | friend bool | |
1509 | operator==(const param_type& __p1, const param_type& __p2) | |
1510 | { return __p1._M_alpha == __p2._M_alpha && __p1._M_mu == __p2._M_mu; } | |
1511 | ||
12905f10 JW |
1512 | friend bool |
1513 | operator!=(const param_type& __p1, const param_type& __p2) | |
1514 | { return !(__p1 == __p2); } | |
1515 | ||
0c105b72 ESR |
1516 | private: |
1517 | void _M_initialize(); | |
1518 | ||
1519 | result_type _M_alpha; | |
1520 | result_type _M_mu; | |
1521 | }; | |
1522 | ||
1523 | /** | |
1524 | * @brief Constructors. | |
dd9db6f8 | 1525 | * @{ |
0c105b72 | 1526 | */ |
dd9db6f8 JW |
1527 | |
1528 | pareto_distribution() : pareto_distribution(1) { } | |
1529 | ||
0c105b72 | 1530 | explicit |
dd9db6f8 | 1531 | pareto_distribution(result_type __alpha_val, |
37f1d5c9 UB |
1532 | result_type __mu_val = result_type(1)) |
1533 | : _M_param(__alpha_val, __mu_val), | |
0c105b72 ESR |
1534 | _M_ud() |
1535 | { } | |
1536 | ||
1537 | explicit | |
1538 | pareto_distribution(const param_type& __p) | |
1539 | : _M_param(__p), | |
1540 | _M_ud() | |
1541 | { } | |
1542 | ||
f0b88346 | 1543 | /// @} |
dd9db6f8 | 1544 | |
0c105b72 ESR |
1545 | /** |
1546 | * @brief Resets the distribution state. | |
1547 | */ | |
1548 | void | |
1549 | reset() | |
1550 | { | |
1551 | _M_ud.reset(); | |
1552 | } | |
1553 | ||
1554 | /** | |
1555 | * @brief Return the parameters of the distribution. | |
1556 | */ | |
1557 | result_type | |
1558 | alpha() const | |
1559 | { return _M_param.alpha(); } | |
1560 | ||
1561 | result_type | |
1562 | mu() const | |
1563 | { return _M_param.mu(); } | |
1564 | ||
1565 | /** | |
1566 | * @brief Returns the parameter set of the distribution. | |
1567 | */ | |
1568 | param_type | |
1569 | param() const | |
1570 | { return _M_param; } | |
1571 | ||
1572 | /** | |
1573 | * @brief Sets the parameter set of the distribution. | |
1574 | * @param __param The new parameter set of the distribution. | |
1575 | */ | |
1576 | void | |
1577 | param(const param_type& __param) | |
1578 | { _M_param = __param; } | |
1579 | ||
1580 | /** | |
1581 | * @brief Returns the greatest lower bound value of the distribution. | |
1582 | */ | |
1583 | result_type | |
1584 | min() const | |
1585 | { return this->mu(); } | |
1586 | ||
1587 | /** | |
1588 | * @brief Returns the least upper bound value of the distribution. | |
1589 | */ | |
1590 | result_type | |
1591 | max() const | |
1592 | { return std::numeric_limits<result_type>::max(); } | |
1593 | ||
1594 | /** | |
1595 | * @brief Generating functions. | |
1596 | */ | |
1597 | template<typename _UniformRandomNumberGenerator> | |
1598 | result_type | |
1599 | operator()(_UniformRandomNumberGenerator& __urng) | |
1600 | { | |
1601 | return this->mu() * std::pow(this->_M_ud(__urng), | |
1602 | -result_type(1) / this->alpha()); | |
1603 | } | |
1604 | ||
1605 | template<typename _UniformRandomNumberGenerator> | |
1606 | result_type | |
1607 | operator()(_UniformRandomNumberGenerator& __urng, | |
1608 | const param_type& __p) | |
d233c237 | 1609 | { |
0c105b72 ESR |
1610 | return __p.mu() * std::pow(this->_M_ud(__urng), |
1611 | -result_type(1) / __p.alpha()); | |
1612 | } | |
1613 | ||
1614 | template<typename _ForwardIterator, | |
1615 | typename _UniformRandomNumberGenerator> | |
1616 | void | |
1617 | __generate(_ForwardIterator __f, _ForwardIterator __t, | |
1618 | _UniformRandomNumberGenerator& __urng) | |
5bcb3b4d | 1619 | { this->__generate(__f, __t, __urng, _M_param); } |
0c105b72 ESR |
1620 | |
1621 | template<typename _ForwardIterator, | |
1622 | typename _UniformRandomNumberGenerator> | |
1623 | void | |
1624 | __generate(_ForwardIterator __f, _ForwardIterator __t, | |
1625 | _UniformRandomNumberGenerator& __urng, | |
1626 | const param_type& __p) | |
1627 | { this->__generate_impl(__f, __t, __urng, __p); } | |
1628 | ||
1629 | template<typename _UniformRandomNumberGenerator> | |
1630 | void | |
1631 | __generate(result_type* __f, result_type* __t, | |
1632 | _UniformRandomNumberGenerator& __urng, | |
1633 | const param_type& __p) | |
1634 | { this->__generate_impl(__f, __t, __urng, __p); } | |
1635 | ||
1636 | /** | |
1637 | * @brief Return true if two Pareto distributions have | |
1638 | * the same parameters and the sequences that would | |
1639 | * be generated are equal. | |
1640 | */ | |
1641 | friend bool | |
1642 | operator==(const pareto_distribution& __d1, | |
1643 | const pareto_distribution& __d2) | |
5bcb3b4d | 1644 | { return (__d1._M_param == __d2._M_param |
0c105b72 ESR |
1645 | && __d1._M_ud == __d2._M_ud); } |
1646 | ||
1647 | /** | |
1648 | * @brief Inserts a %pareto_distribution random number distribution | |
1649 | * @p __x into the output stream @p __os. | |
1650 | * | |
1651 | * @param __os An output stream. | |
1652 | * @param __x A %pareto_distribution random number distribution. | |
1653 | * | |
1654 | * @returns The output stream with the state of @p __x inserted or in | |
1655 | * an error state. | |
1656 | */ | |
1657 | template<typename _RealType1, typename _CharT, typename _Traits> | |
1658 | friend std::basic_ostream<_CharT, _Traits>& | |
1659 | operator<<(std::basic_ostream<_CharT, _Traits>&, | |
1660 | const pareto_distribution<_RealType1>&); | |
1661 | ||
1662 | /** | |
1663 | * @brief Extracts a %pareto_distribution random number distribution | |
1664 | * @p __x from the input stream @p __is. | |
1665 | * | |
1666 | * @param __is An input stream. | |
1667 | * @param __x A %pareto_distribution random number | |
1668 | * generator engine. | |
1669 | * | |
1670 | * @returns The input stream with @p __x extracted or in an error state. | |
1671 | */ | |
1672 | template<typename _RealType1, typename _CharT, typename _Traits> | |
1673 | friend std::basic_istream<_CharT, _Traits>& | |
1674 | operator>>(std::basic_istream<_CharT, _Traits>&, | |
1675 | pareto_distribution<_RealType1>&); | |
1676 | ||
1677 | private: | |
1678 | template<typename _ForwardIterator, | |
1679 | typename _UniformRandomNumberGenerator> | |
1680 | void | |
1681 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1682 | _UniformRandomNumberGenerator& __urng, | |
1683 | const param_type& __p); | |
1684 | ||
1685 | param_type _M_param; | |
1686 | ||
1687 | std::uniform_real_distribution<result_type> _M_ud; | |
1688 | }; | |
1689 | ||
1690 | /** | |
1691 | * @brief Return true if two Pareto distributions are not equal. | |
1692 | */ | |
1693 | template<typename _RealType> | |
1694 | inline bool | |
1695 | operator!=(const pareto_distribution<_RealType>& __d1, | |
1696 | const pareto_distribution<_RealType>& __d2) | |
1697 | { return !(__d1 == __d2); } | |
1698 | ||
21a8ccc0 ESR |
1699 | |
1700 | /** | |
1701 | * @brief A K continuous distribution for random numbers. | |
1702 | * | |
1703 | * The formula for the K probability density function is | |
1704 | * @f[ | |
1705 | * p(x|\lambda, \mu, \nu) = \frac{2}{x} | |
1706 | * \left(\frac{\lambda\nu x}{\mu}\right)^{\frac{\lambda + \nu}{2}} | |
1707 | * \frac{1}{\Gamma(\lambda)\Gamma(\nu)} | |
1708 | * K_{\nu - \lambda}\left(2\sqrt{\frac{\lambda\nu x}{\mu}}\right) | |
1709 | * @f] | |
1710 | * where @f$I_0(z)@f$ is the modified Bessel function of the second kind | |
1711 | * of order @f$\nu - \lambda@f$ and @f$\lambda > 0@f$, @f$\mu > 0@f$ | |
1712 | * and @f$\nu > 0@f$. | |
1713 | * | |
1714 | * <table border=1 cellpadding=10 cellspacing=0> | |
1715 | * <caption align=top>Distribution Statistics</caption> | |
1716 | * <tr><td>Mean</td><td>@f$\mu@f$</td></tr> | |
1717 | * <tr><td>Variance</td><td>@f$\mu^2\frac{\lambda + \nu + 1}{\lambda\nu}@f$</td></tr> | |
1718 | * <tr><td>Range</td><td>@f$[0, \infty)@f$</td></tr> | |
1719 | * </table> | |
1720 | */ | |
1721 | template<typename _RealType = double> | |
1722 | class | |
1723 | k_distribution | |
1724 | { | |
1725 | static_assert(std::is_floating_point<_RealType>::value, | |
1726 | "template argument not a floating point type"); | |
1727 | ||
1728 | public: | |
1729 | /** The type of the range of the distribution. */ | |
1730 | typedef _RealType result_type; | |
12905f10 | 1731 | |
21a8ccc0 ESR |
1732 | /** Parameter type. */ |
1733 | struct param_type | |
1734 | { | |
1735 | typedef k_distribution<result_type> distribution_type; | |
1736 | ||
977ac63e JW |
1737 | param_type() : param_type(1) { } |
1738 | ||
1739 | param_type(result_type __lambda_val, | |
21a8ccc0 ESR |
1740 | result_type __mu_val = result_type(1), |
1741 | result_type __nu_val = result_type(1)) | |
1742 | : _M_lambda(__lambda_val), _M_mu(__mu_val), _M_nu(__nu_val) | |
1743 | { | |
2f1e8e7c JW |
1744 | __glibcxx_assert(_M_lambda > result_type(0)); |
1745 | __glibcxx_assert(_M_mu > result_type(0)); | |
1746 | __glibcxx_assert(_M_nu > result_type(0)); | |
21a8ccc0 ESR |
1747 | } |
1748 | ||
1749 | result_type | |
1750 | lambda() const | |
1751 | { return _M_lambda; } | |
1752 | ||
1753 | result_type | |
1754 | mu() const | |
1755 | { return _M_mu; } | |
1756 | ||
1757 | result_type | |
1758 | nu() const | |
1759 | { return _M_nu; } | |
1760 | ||
1761 | friend bool | |
1762 | operator==(const param_type& __p1, const param_type& __p2) | |
12905f10 JW |
1763 | { |
1764 | return __p1._M_lambda == __p2._M_lambda | |
d233c237 | 1765 | && __p1._M_mu == __p2._M_mu |
12905f10 JW |
1766 | && __p1._M_nu == __p2._M_nu; |
1767 | } | |
1768 | ||
1769 | friend bool | |
1770 | operator!=(const param_type& __p1, const param_type& __p2) | |
1771 | { return !(__p1 == __p2); } | |
21a8ccc0 ESR |
1772 | |
1773 | private: | |
1774 | void _M_initialize(); | |
1775 | ||
1776 | result_type _M_lambda; | |
1777 | result_type _M_mu; | |
1778 | result_type _M_nu; | |
1779 | }; | |
1780 | ||
1781 | /** | |
1782 | * @brief Constructors. | |
dd9db6f8 | 1783 | * @{ |
21a8ccc0 | 1784 | */ |
dd9db6f8 JW |
1785 | |
1786 | k_distribution() : k_distribution(1) { } | |
1787 | ||
21a8ccc0 | 1788 | explicit |
dd9db6f8 | 1789 | k_distribution(result_type __lambda_val, |
21a8ccc0 ESR |
1790 | result_type __mu_val = result_type(1), |
1791 | result_type __nu_val = result_type(1)) | |
1792 | : _M_param(__lambda_val, __mu_val, __nu_val), | |
1793 | _M_gd1(__lambda_val, result_type(1) / __lambda_val), | |
1794 | _M_gd2(__nu_val, __mu_val / __nu_val) | |
1795 | { } | |
1796 | ||
1797 | explicit | |
1798 | k_distribution(const param_type& __p) | |
1799 | : _M_param(__p), | |
1800 | _M_gd1(__p.lambda(), result_type(1) / __p.lambda()), | |
1801 | _M_gd2(__p.nu(), __p.mu() / __p.nu()) | |
1802 | { } | |
1803 | ||
f0b88346 | 1804 | /// @} |
dd9db6f8 | 1805 | |
21a8ccc0 ESR |
1806 | /** |
1807 | * @brief Resets the distribution state. | |
1808 | */ | |
1809 | void | |
1810 | reset() | |
1811 | { | |
1812 | _M_gd1.reset(); | |
1813 | _M_gd2.reset(); | |
1814 | } | |
1815 | ||
1816 | /** | |
1817 | * @brief Return the parameters of the distribution. | |
1818 | */ | |
1819 | result_type | |
1820 | lambda() const | |
1821 | { return _M_param.lambda(); } | |
1822 | ||
1823 | result_type | |
1824 | mu() const | |
1825 | { return _M_param.mu(); } | |
1826 | ||
1827 | result_type | |
1828 | nu() const | |
1829 | { return _M_param.nu(); } | |
1830 | ||
1831 | /** | |
1832 | * @brief Returns the parameter set of the distribution. | |
1833 | */ | |
1834 | param_type | |
1835 | param() const | |
1836 | { return _M_param; } | |
1837 | ||
1838 | /** | |
1839 | * @brief Sets the parameter set of the distribution. | |
1840 | * @param __param The new parameter set of the distribution. | |
1841 | */ | |
1842 | void | |
1843 | param(const param_type& __param) | |
1844 | { _M_param = __param; } | |
1845 | ||
1846 | /** | |
1847 | * @brief Returns the greatest lower bound value of the distribution. | |
1848 | */ | |
1849 | result_type | |
1850 | min() const | |
1851 | { return result_type(0); } | |
1852 | ||
1853 | /** | |
1854 | * @brief Returns the least upper bound value of the distribution. | |
1855 | */ | |
1856 | result_type | |
1857 | max() const | |
1858 | { return std::numeric_limits<result_type>::max(); } | |
1859 | ||
1860 | /** | |
1861 | * @brief Generating functions. | |
1862 | */ | |
1863 | template<typename _UniformRandomNumberGenerator> | |
1864 | result_type | |
1865 | operator()(_UniformRandomNumberGenerator&); | |
1866 | ||
1867 | template<typename _UniformRandomNumberGenerator> | |
1868 | result_type | |
1869 | operator()(_UniformRandomNumberGenerator&, const param_type&); | |
1870 | ||
1871 | template<typename _ForwardIterator, | |
1872 | typename _UniformRandomNumberGenerator> | |
1873 | void | |
1874 | __generate(_ForwardIterator __f, _ForwardIterator __t, | |
1875 | _UniformRandomNumberGenerator& __urng) | |
5bcb3b4d | 1876 | { this->__generate(__f, __t, __urng, _M_param); } |
21a8ccc0 ESR |
1877 | |
1878 | template<typename _ForwardIterator, | |
1879 | typename _UniformRandomNumberGenerator> | |
1880 | void | |
1881 | __generate(_ForwardIterator __f, _ForwardIterator __t, | |
1882 | _UniformRandomNumberGenerator& __urng, | |
1883 | const param_type& __p) | |
1884 | { this->__generate_impl(__f, __t, __urng, __p); } | |
1885 | ||
1886 | template<typename _UniformRandomNumberGenerator> | |
1887 | void | |
1888 | __generate(result_type* __f, result_type* __t, | |
1889 | _UniformRandomNumberGenerator& __urng, | |
1890 | const param_type& __p) | |
1891 | { this->__generate_impl(__f, __t, __urng, __p); } | |
1892 | ||
1893 | /** | |
1894 | * @brief Return true if two K distributions have | |
1895 | * the same parameters and the sequences that would | |
1896 | * be generated are equal. | |
1897 | */ | |
1898 | friend bool | |
1899 | operator==(const k_distribution& __d1, | |
1900 | const k_distribution& __d2) | |
5bcb3b4d | 1901 | { return (__d1._M_param == __d2._M_param |
21a8ccc0 ESR |
1902 | && __d1._M_gd1 == __d2._M_gd1 |
1903 | && __d1._M_gd2 == __d2._M_gd2); } | |
1904 | ||
1905 | /** | |
1906 | * @brief Inserts a %k_distribution random number distribution | |
1907 | * @p __x into the output stream @p __os. | |
1908 | * | |
1909 | * @param __os An output stream. | |
1910 | * @param __x A %k_distribution random number distribution. | |
1911 | * | |
1912 | * @returns The output stream with the state of @p __x inserted or in | |
1913 | * an error state. | |
1914 | */ | |
1915 | template<typename _RealType1, typename _CharT, typename _Traits> | |
1916 | friend std::basic_ostream<_CharT, _Traits>& | |
1917 | operator<<(std::basic_ostream<_CharT, _Traits>&, | |
1918 | const k_distribution<_RealType1>&); | |
1919 | ||
1920 | /** | |
1921 | * @brief Extracts a %k_distribution random number distribution | |
1922 | * @p __x from the input stream @p __is. | |
1923 | * | |
1924 | * @param __is An input stream. | |
1925 | * @param __x A %k_distribution random number | |
1926 | * generator engine. | |
1927 | * | |
1928 | * @returns The input stream with @p __x extracted or in an error state. | |
1929 | */ | |
1930 | template<typename _RealType1, typename _CharT, typename _Traits> | |
1931 | friend std::basic_istream<_CharT, _Traits>& | |
1932 | operator>>(std::basic_istream<_CharT, _Traits>&, | |
1933 | k_distribution<_RealType1>&); | |
1934 | ||
1935 | private: | |
1936 | template<typename _ForwardIterator, | |
1937 | typename _UniformRandomNumberGenerator> | |
1938 | void | |
1939 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
1940 | _UniformRandomNumberGenerator& __urng, | |
1941 | const param_type& __p); | |
1942 | ||
1943 | param_type _M_param; | |
1944 | ||
1945 | std::gamma_distribution<result_type> _M_gd1; | |
1946 | std::gamma_distribution<result_type> _M_gd2; | |
1947 | }; | |
1948 | ||
1949 | /** | |
1950 | * @brief Return true if two K distributions are not equal. | |
1951 | */ | |
1952 | template<typename _RealType> | |
1953 | inline bool | |
1954 | operator!=(const k_distribution<_RealType>& __d1, | |
1955 | const k_distribution<_RealType>& __d2) | |
1956 | { return !(__d1 == __d2); } | |
1957 | ||
50060222 ESR |
1958 | |
1959 | /** | |
1960 | * @brief An arcsine continuous distribution for random numbers. | |
1961 | * | |
1962 | * The formula for the arcsine probability density function is | |
1963 | * @f[ | |
1964 | * p(x|a,b) = \frac{1}{\pi \sqrt{(x - a)(b - x)}} | |
1965 | * @f] | |
1966 | * where @f$x >= a@f$ and @f$x <= b@f$. | |
1967 | * | |
1968 | * <table border=1 cellpadding=10 cellspacing=0> | |
1969 | * <caption align=top>Distribution Statistics</caption> | |
1970 | * <tr><td>Mean</td><td>@f$ (a + b) / 2 @f$</td></tr> | |
1971 | * <tr><td>Variance</td><td>@f$ (b - a)^2 / 8 @f$</td></tr> | |
1972 | * <tr><td>Range</td><td>@f$[a, b]@f$</td></tr> | |
1973 | * </table> | |
1974 | */ | |
1975 | template<typename _RealType = double> | |
1976 | class | |
1977 | arcsine_distribution | |
1978 | { | |
1979 | static_assert(std::is_floating_point<_RealType>::value, | |
1980 | "template argument not a floating point type"); | |
1981 | ||
1982 | public: | |
1983 | /** The type of the range of the distribution. */ | |
1984 | typedef _RealType result_type; | |
12905f10 | 1985 | |
50060222 ESR |
1986 | /** Parameter type. */ |
1987 | struct param_type | |
1988 | { | |
1989 | typedef arcsine_distribution<result_type> distribution_type; | |
1990 | ||
977ac63e JW |
1991 | param_type() : param_type(0) { } |
1992 | ||
1993 | param_type(result_type __a, result_type __b = result_type(1)) | |
50060222 ESR |
1994 | : _M_a(__a), _M_b(__b) |
1995 | { | |
2f1e8e7c | 1996 | __glibcxx_assert(_M_a <= _M_b); |
50060222 ESR |
1997 | } |
1998 | ||
1999 | result_type | |
2000 | a() const | |
2001 | { return _M_a; } | |
2002 | ||
2003 | result_type | |
2004 | b() const | |
2005 | { return _M_b; } | |
2006 | ||
2007 | friend bool | |
2008 | operator==(const param_type& __p1, const param_type& __p2) | |
2009 | { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; } | |
2010 | ||
12905f10 JW |
2011 | friend bool |
2012 | operator!=(const param_type& __p1, const param_type& __p2) | |
2013 | { return !(__p1 == __p2); } | |
2014 | ||
50060222 ESR |
2015 | private: |
2016 | void _M_initialize(); | |
2017 | ||
2018 | result_type _M_a; | |
2019 | result_type _M_b; | |
2020 | }; | |
2021 | ||
2022 | /** | |
2023 | * @brief Constructors. | |
dd9db6f8 | 2024 | * :{ |
50060222 | 2025 | */ |
dd9db6f8 JW |
2026 | |
2027 | arcsine_distribution() : arcsine_distribution(0) { } | |
2028 | ||
50060222 | 2029 | explicit |
dd9db6f8 | 2030 | arcsine_distribution(result_type __a, result_type __b = result_type(1)) |
50060222 ESR |
2031 | : _M_param(__a, __b), |
2032 | _M_ud(-1.5707963267948966192313216916397514L, | |
d233c237 | 2033 | +1.5707963267948966192313216916397514L) |
50060222 ESR |
2034 | { } |
2035 | ||
2036 | explicit | |
2037 | arcsine_distribution(const param_type& __p) | |
2038 | : _M_param(__p), | |
2039 | _M_ud(-1.5707963267948966192313216916397514L, | |
d233c237 | 2040 | +1.5707963267948966192313216916397514L) |
50060222 ESR |
2041 | { } |
2042 | ||
f0b88346 | 2043 | /// @} |
dd9db6f8 | 2044 | |
50060222 ESR |
2045 | /** |
2046 | * @brief Resets the distribution state. | |
2047 | */ | |
2048 | void | |
2049 | reset() | |
2050 | { _M_ud.reset(); } | |
2051 | ||
2052 | /** | |
2053 | * @brief Return the parameters of the distribution. | |
2054 | */ | |
2055 | result_type | |
2056 | a() const | |
2057 | { return _M_param.a(); } | |
2058 | ||
2059 | result_type | |
2060 | b() const | |
2061 | { return _M_param.b(); } | |
2062 | ||
2063 | /** | |
2064 | * @brief Returns the parameter set of the distribution. | |
2065 | */ | |
2066 | param_type | |
2067 | param() const | |
2068 | { return _M_param; } | |
2069 | ||
2070 | /** | |
2071 | * @brief Sets the parameter set of the distribution. | |
2072 | * @param __param The new parameter set of the distribution. | |
2073 | */ | |
2074 | void | |
2075 | param(const param_type& __param) | |
2076 | { _M_param = __param; } | |
2077 | ||
2078 | /** | |
2079 | * @brief Returns the greatest lower bound value of the distribution. | |
2080 | */ | |
2081 | result_type | |
2082 | min() const | |
2083 | { return this->a(); } | |
2084 | ||
2085 | /** | |
2086 | * @brief Returns the least upper bound value of the distribution. | |
2087 | */ | |
2088 | result_type | |
2089 | max() const | |
2090 | { return this->b(); } | |
2091 | ||
2092 | /** | |
2093 | * @brief Generating functions. | |
2094 | */ | |
2095 | template<typename _UniformRandomNumberGenerator> | |
2096 | result_type | |
2097 | operator()(_UniformRandomNumberGenerator& __urng) | |
2098 | { | |
2099 | result_type __x = std::sin(this->_M_ud(__urng)); | |
2100 | return (__x * (this->b() - this->a()) | |
2101 | + this->a() + this->b()) / result_type(2); | |
2102 | } | |
2103 | ||
2104 | template<typename _UniformRandomNumberGenerator> | |
2105 | result_type | |
2106 | operator()(_UniformRandomNumberGenerator& __urng, | |
2107 | const param_type& __p) | |
d233c237 | 2108 | { |
50060222 ESR |
2109 | result_type __x = std::sin(this->_M_ud(__urng)); |
2110 | return (__x * (__p.b() - __p.a()) | |
2111 | + __p.a() + __p.b()) / result_type(2); | |
2112 | } | |
2113 | ||
2114 | template<typename _ForwardIterator, | |
2115 | typename _UniformRandomNumberGenerator> | |
2116 | void | |
2117 | __generate(_ForwardIterator __f, _ForwardIterator __t, | |
2118 | _UniformRandomNumberGenerator& __urng) | |
5bcb3b4d | 2119 | { this->__generate(__f, __t, __urng, _M_param); } |
50060222 ESR |
2120 | |
2121 | template<typename _ForwardIterator, | |
2122 | typename _UniformRandomNumberGenerator> | |
2123 | void | |
2124 | __generate(_ForwardIterator __f, _ForwardIterator __t, | |
2125 | _UniformRandomNumberGenerator& __urng, | |
2126 | const param_type& __p) | |
2127 | { this->__generate_impl(__f, __t, __urng, __p); } | |
2128 | ||
2129 | template<typename _UniformRandomNumberGenerator> | |
2130 | void | |
2131 | __generate(result_type* __f, result_type* __t, | |
2132 | _UniformRandomNumberGenerator& __urng, | |
2133 | const param_type& __p) | |
2134 | { this->__generate_impl(__f, __t, __urng, __p); } | |
2135 | ||
2136 | /** | |
2137 | * @brief Return true if two arcsine distributions have | |
2138 | * the same parameters and the sequences that would | |
2139 | * be generated are equal. | |
2140 | */ | |
2141 | friend bool | |
2142 | operator==(const arcsine_distribution& __d1, | |
2143 | const arcsine_distribution& __d2) | |
5bcb3b4d | 2144 | { return (__d1._M_param == __d2._M_param |
50060222 ESR |
2145 | && __d1._M_ud == __d2._M_ud); } |
2146 | ||
2147 | /** | |
2148 | * @brief Inserts a %arcsine_distribution random number distribution | |
2149 | * @p __x into the output stream @p __os. | |
2150 | * | |
2151 | * @param __os An output stream. | |
2152 | * @param __x A %arcsine_distribution random number distribution. | |
2153 | * | |
2154 | * @returns The output stream with the state of @p __x inserted or in | |
2155 | * an error state. | |
2156 | */ | |
2157 | template<typename _RealType1, typename _CharT, typename _Traits> | |
2158 | friend std::basic_ostream<_CharT, _Traits>& | |
2159 | operator<<(std::basic_ostream<_CharT, _Traits>&, | |
2160 | const arcsine_distribution<_RealType1>&); | |
2161 | ||
2162 | /** | |
2163 | * @brief Extracts a %arcsine_distribution random number distribution | |
2164 | * @p __x from the input stream @p __is. | |
2165 | * | |
2166 | * @param __is An input stream. | |
2167 | * @param __x A %arcsine_distribution random number | |
2168 | * generator engine. | |
2169 | * | |
2170 | * @returns The input stream with @p __x extracted or in an error state. | |
2171 | */ | |
2172 | template<typename _RealType1, typename _CharT, typename _Traits> | |
2173 | friend std::basic_istream<_CharT, _Traits>& | |
2174 | operator>>(std::basic_istream<_CharT, _Traits>&, | |
2175 | arcsine_distribution<_RealType1>&); | |
2176 | ||
2177 | private: | |
2178 | template<typename _ForwardIterator, | |
2179 | typename _UniformRandomNumberGenerator> | |
2180 | void | |
2181 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2182 | _UniformRandomNumberGenerator& __urng, | |
2183 | const param_type& __p); | |
2184 | ||
2185 | param_type _M_param; | |
2186 | ||
2187 | std::uniform_real_distribution<result_type> _M_ud; | |
2188 | }; | |
2189 | ||
2190 | /** | |
2191 | * @brief Return true if two arcsine distributions are not equal. | |
2192 | */ | |
2193 | template<typename _RealType> | |
2194 | inline bool | |
2195 | operator!=(const arcsine_distribution<_RealType>& __d1, | |
2196 | const arcsine_distribution<_RealType>& __d2) | |
2197 | { return !(__d1 == __d2); } | |
2198 | ||
2199 | ||
2200 | /** | |
2201 | * @brief A Hoyt continuous distribution for random numbers. | |
2202 | * | |
2203 | * The formula for the Hoyt probability density function is | |
2204 | * @f[ | |
2205 | * p(x|q,\omega) = \frac{(1 + q^2)x}{q\omega} | |
2206 | * \exp\left(-\frac{(1 + q^2)^2 x^2}{4 q^2 \omega}\right) | |
2207 | * I_0\left(\frac{(1 - q^4) x^2}{4 q^2 \omega}\right) | |
2208 | * @f] | |
2209 | * where @f$I_0(z)@f$ is the modified Bessel function of the first kind | |
2210 | * of order 0 and @f$0 < q < 1@f$. | |
2211 | * | |
2212 | * <table border=1 cellpadding=10 cellspacing=0> | |
2213 | * <caption align=top>Distribution Statistics</caption> | |
2214 | * <tr><td>Mean</td><td>@f$ \sqrt{\frac{2}{\pi}} \sqrt{\frac{\omega}{1 + q^2}} | |
2215 | * E(1 - q^2) @f$</td></tr> | |
2216 | * <tr><td>Variance</td><td>@f$ \omega \left(1 - \frac{2E^2(1 - q^2)} | |
2217 | * {\pi (1 + q^2)}\right) @f$</td></tr> | |
2218 | * <tr><td>Range</td><td>@f$[0, \infty)@f$</td></tr> | |
2219 | * </table> | |
2220 | * where @f$E(x)@f$ is the elliptic function of the second kind. | |
2221 | */ | |
2222 | template<typename _RealType = double> | |
2223 | class | |
2224 | hoyt_distribution | |
2225 | { | |
2226 | static_assert(std::is_floating_point<_RealType>::value, | |
2227 | "template argument not a floating point type"); | |
2228 | ||
2229 | public: | |
2230 | /** The type of the range of the distribution. */ | |
2231 | typedef _RealType result_type; | |
12905f10 | 2232 | |
50060222 ESR |
2233 | /** Parameter type. */ |
2234 | struct param_type | |
2235 | { | |
2236 | typedef hoyt_distribution<result_type> distribution_type; | |
2237 | ||
977ac63e JW |
2238 | param_type() : param_type(0.5) { } |
2239 | ||
2240 | param_type(result_type __q, result_type __omega = result_type(1)) | |
50060222 ESR |
2241 | : _M_q(__q), _M_omega(__omega) |
2242 | { | |
2f1e8e7c JW |
2243 | __glibcxx_assert(_M_q > result_type(0)); |
2244 | __glibcxx_assert(_M_q < result_type(1)); | |
50060222 ESR |
2245 | } |
2246 | ||
2247 | result_type | |
2248 | q() const | |
2249 | { return _M_q; } | |
2250 | ||
2251 | result_type | |
2252 | omega() const | |
2253 | { return _M_omega; } | |
2254 | ||
2255 | friend bool | |
2256 | operator==(const param_type& __p1, const param_type& __p2) | |
12905f10 JW |
2257 | { return __p1._M_q == __p2._M_q && __p1._M_omega == __p2._M_omega; } |
2258 | ||
2259 | friend bool | |
2260 | operator!=(const param_type& __p1, const param_type& __p2) | |
2261 | { return !(__p1 == __p2); } | |
50060222 ESR |
2262 | |
2263 | private: | |
2264 | void _M_initialize(); | |
2265 | ||
2266 | result_type _M_q; | |
2267 | result_type _M_omega; | |
2268 | }; | |
2269 | ||
2270 | /** | |
2271 | * @brief Constructors. | |
dd9db6f8 | 2272 | * @{ |
50060222 | 2273 | */ |
dd9db6f8 JW |
2274 | |
2275 | hoyt_distribution() : hoyt_distribution(0.5) { } | |
2276 | ||
50060222 | 2277 | explicit |
dd9db6f8 | 2278 | hoyt_distribution(result_type __q, result_type __omega = result_type(1)) |
50060222 ESR |
2279 | : _M_param(__q, __omega), |
2280 | _M_ad(result_type(0.5L) * (result_type(1) + __q * __q), | |
2281 | result_type(0.5L) * (result_type(1) + __q * __q) | |
2282 | / (__q * __q)), | |
2283 | _M_ed(result_type(1)) | |
2284 | { } | |
2285 | ||
2286 | explicit | |
2287 | hoyt_distribution(const param_type& __p) | |
2288 | : _M_param(__p), | |
2289 | _M_ad(result_type(0.5L) * (result_type(1) + __p.q() * __p.q()), | |
2290 | result_type(0.5L) * (result_type(1) + __p.q() * __p.q()) | |
2291 | / (__p.q() * __p.q())), | |
2292 | _M_ed(result_type(1)) | |
2293 | { } | |
2294 | ||
2295 | /** | |
2296 | * @brief Resets the distribution state. | |
2297 | */ | |
2298 | void | |
2299 | reset() | |
2300 | { | |
2301 | _M_ad.reset(); | |
2302 | _M_ed.reset(); | |
2303 | } | |
2304 | ||
2305 | /** | |
2306 | * @brief Return the parameters of the distribution. | |
2307 | */ | |
2308 | result_type | |
2309 | q() const | |
2310 | { return _M_param.q(); } | |
2311 | ||
2312 | result_type | |
2313 | omega() const | |
2314 | { return _M_param.omega(); } | |
2315 | ||
2316 | /** | |
2317 | * @brief Returns the parameter set of the distribution. | |
2318 | */ | |
2319 | param_type | |
2320 | param() const | |
2321 | { return _M_param; } | |
2322 | ||
2323 | /** | |
2324 | * @brief Sets the parameter set of the distribution. | |
2325 | * @param __param The new parameter set of the distribution. | |
2326 | */ | |
2327 | void | |
2328 | param(const param_type& __param) | |
2329 | { _M_param = __param; } | |
2330 | ||
2331 | /** | |
2332 | * @brief Returns the greatest lower bound value of the distribution. | |
2333 | */ | |
2334 | result_type | |
2335 | min() const | |
2336 | { return result_type(0); } | |
2337 | ||
2338 | /** | |
2339 | * @brief Returns the least upper bound value of the distribution. | |
2340 | */ | |
2341 | result_type | |
2342 | max() const | |
2343 | { return std::numeric_limits<result_type>::max(); } | |
2344 | ||
2345 | /** | |
2346 | * @brief Generating functions. | |
2347 | */ | |
2348 | template<typename _UniformRandomNumberGenerator> | |
2349 | result_type | |
2350 | operator()(_UniformRandomNumberGenerator& __urng); | |
2351 | ||
2352 | template<typename _UniformRandomNumberGenerator> | |
2353 | result_type | |
2354 | operator()(_UniformRandomNumberGenerator& __urng, | |
2355 | const param_type& __p); | |
2356 | ||
2357 | template<typename _ForwardIterator, | |
2358 | typename _UniformRandomNumberGenerator> | |
2359 | void | |
2360 | __generate(_ForwardIterator __f, _ForwardIterator __t, | |
2361 | _UniformRandomNumberGenerator& __urng) | |
5bcb3b4d | 2362 | { this->__generate(__f, __t, __urng, _M_param); } |
50060222 ESR |
2363 | |
2364 | template<typename _ForwardIterator, | |
2365 | typename _UniformRandomNumberGenerator> | |
2366 | void | |
2367 | __generate(_ForwardIterator __f, _ForwardIterator __t, | |
2368 | _UniformRandomNumberGenerator& __urng, | |
2369 | const param_type& __p) | |
2370 | { this->__generate_impl(__f, __t, __urng, __p); } | |
2371 | ||
2372 | template<typename _UniformRandomNumberGenerator> | |
2373 | void | |
2374 | __generate(result_type* __f, result_type* __t, | |
2375 | _UniformRandomNumberGenerator& __urng, | |
2376 | const param_type& __p) | |
2377 | { this->__generate_impl(__f, __t, __urng, __p); } | |
2378 | ||
2379 | /** | |
2380 | * @brief Return true if two Hoyt distributions have | |
2381 | * the same parameters and the sequences that would | |
2382 | * be generated are equal. | |
2383 | */ | |
2384 | friend bool | |
2385 | operator==(const hoyt_distribution& __d1, | |
2386 | const hoyt_distribution& __d2) | |
5bcb3b4d | 2387 | { return (__d1._M_param == __d2._M_param |
50060222 ESR |
2388 | && __d1._M_ad == __d2._M_ad |
2389 | && __d1._M_ed == __d2._M_ed); } | |
2390 | ||
2391 | /** | |
2392 | * @brief Inserts a %hoyt_distribution random number distribution | |
2393 | * @p __x into the output stream @p __os. | |
2394 | * | |
2395 | * @param __os An output stream. | |
2396 | * @param __x A %hoyt_distribution random number distribution. | |
2397 | * | |
2398 | * @returns The output stream with the state of @p __x inserted or in | |
2399 | * an error state. | |
2400 | */ | |
2401 | template<typename _RealType1, typename _CharT, typename _Traits> | |
2402 | friend std::basic_ostream<_CharT, _Traits>& | |
2403 | operator<<(std::basic_ostream<_CharT, _Traits>&, | |
2404 | const hoyt_distribution<_RealType1>&); | |
2405 | ||
2406 | /** | |
2407 | * @brief Extracts a %hoyt_distribution random number distribution | |
2408 | * @p __x from the input stream @p __is. | |
2409 | * | |
2410 | * @param __is An input stream. | |
2411 | * @param __x A %hoyt_distribution random number | |
2412 | * generator engine. | |
2413 | * | |
2414 | * @returns The input stream with @p __x extracted or in an error state. | |
2415 | */ | |
2416 | template<typename _RealType1, typename _CharT, typename _Traits> | |
2417 | friend std::basic_istream<_CharT, _Traits>& | |
2418 | operator>>(std::basic_istream<_CharT, _Traits>&, | |
2419 | hoyt_distribution<_RealType1>&); | |
2420 | ||
2421 | private: | |
2422 | template<typename _ForwardIterator, | |
2423 | typename _UniformRandomNumberGenerator> | |
2424 | void | |
2425 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2426 | _UniformRandomNumberGenerator& __urng, | |
2427 | const param_type& __p); | |
2428 | ||
2429 | param_type _M_param; | |
2430 | ||
2431 | __gnu_cxx::arcsine_distribution<result_type> _M_ad; | |
2432 | std::exponential_distribution<result_type> _M_ed; | |
2433 | }; | |
2434 | ||
2435 | /** | |
2436 | * @brief Return true if two Hoyt distributions are not equal. | |
2437 | */ | |
2438 | template<typename _RealType> | |
2439 | inline bool | |
2440 | operator!=(const hoyt_distribution<_RealType>& __d1, | |
2441 | const hoyt_distribution<_RealType>& __d2) | |
2442 | { return !(__d1 == __d2); } | |
2443 | ||
d233c237 UD |
2444 | |
2445 | /** | |
2446 | * @brief A triangular distribution for random numbers. | |
2447 | * | |
2448 | * The formula for the triangular probability density function is | |
2449 | * @f[ | |
2450 | * / 0 for x < a | |
2451 | * p(x|a,b,c) = | \frac{2(x-a)}{(c-a)(b-a)} for a <= x <= b | |
2452 | * | \frac{2(c-x)}{(c-a)(c-b)} for b < x <= c | |
2453 | * \ 0 for c < x | |
2454 | * @f] | |
2455 | * | |
2456 | * <table border=1 cellpadding=10 cellspacing=0> | |
2457 | * <caption align=top>Distribution Statistics</caption> | |
2458 | * <tr><td>Mean</td><td>@f$ \frac{a+b+c}{2} @f$</td></tr> | |
2459 | * <tr><td>Variance</td><td>@f$ \frac{a^2+b^2+c^2-ab-ac-bc} | |
2460 | * {18}@f$</td></tr> | |
2461 | * <tr><td>Range</td><td>@f$[a, c]@f$</td></tr> | |
2462 | * </table> | |
2463 | */ | |
2464 | template<typename _RealType = double> | |
2465 | class triangular_distribution | |
2466 | { | |
2467 | static_assert(std::is_floating_point<_RealType>::value, | |
2468 | "template argument not a floating point type"); | |
2469 | ||
2470 | public: | |
2471 | /** The type of the range of the distribution. */ | |
2472 | typedef _RealType result_type; | |
12905f10 | 2473 | |
d233c237 UD |
2474 | /** Parameter type. */ |
2475 | struct param_type | |
2476 | { | |
2477 | friend class triangular_distribution<_RealType>; | |
2478 | ||
977ac63e JW |
2479 | param_type() : param_type(0) { } |
2480 | ||
d233c237 | 2481 | explicit |
977ac63e | 2482 | param_type(_RealType __a, |
d233c237 UD |
2483 | _RealType __b = _RealType(0.5), |
2484 | _RealType __c = _RealType(1)) | |
2485 | : _M_a(__a), _M_b(__b), _M_c(__c) | |
2486 | { | |
2f1e8e7c JW |
2487 | __glibcxx_assert(_M_a <= _M_b); |
2488 | __glibcxx_assert(_M_b <= _M_c); | |
2489 | __glibcxx_assert(_M_a < _M_c); | |
d233c237 UD |
2490 | |
2491 | _M_r_ab = (_M_b - _M_a) / (_M_c - _M_a); | |
2492 | _M_f_ab_ac = (_M_b - _M_a) * (_M_c - _M_a); | |
2493 | _M_f_bc_ac = (_M_c - _M_b) * (_M_c - _M_a); | |
2494 | } | |
2495 | ||
2496 | _RealType | |
2497 | a() const | |
2498 | { return _M_a; } | |
2499 | ||
2500 | _RealType | |
2501 | b() const | |
2502 | { return _M_b; } | |
2503 | ||
2504 | _RealType | |
2505 | c() const | |
2506 | { return _M_c; } | |
2507 | ||
2508 | friend bool | |
2509 | operator==(const param_type& __p1, const param_type& __p2) | |
12905f10 JW |
2510 | { |
2511 | return (__p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b | |
2512 | && __p1._M_c == __p2._M_c); | |
2513 | } | |
2514 | ||
2515 | friend bool | |
2516 | operator!=(const param_type& __p1, const param_type& __p2) | |
2517 | { return !(__p1 == __p2); } | |
d233c237 UD |
2518 | |
2519 | private: | |
2520 | ||
2521 | _RealType _M_a; | |
2522 | _RealType _M_b; | |
2523 | _RealType _M_c; | |
2524 | _RealType _M_r_ab; | |
2525 | _RealType _M_f_ab_ac; | |
2526 | _RealType _M_f_bc_ac; | |
2527 | }; | |
2528 | ||
dd9db6f8 JW |
2529 | triangular_distribution() : triangular_distribution(0.0) { } |
2530 | ||
d233c237 UD |
2531 | /** |
2532 | * @brief Constructs a triangle distribution with parameters | |
2533 | * @f$ a @f$, @f$ b @f$ and @f$ c @f$. | |
2534 | */ | |
2535 | explicit | |
dd9db6f8 | 2536 | triangular_distribution(result_type __a, |
d233c237 UD |
2537 | result_type __b = result_type(0.5), |
2538 | result_type __c = result_type(1)) | |
2539 | : _M_param(__a, __b, __c) | |
2540 | { } | |
2541 | ||
2542 | explicit | |
2543 | triangular_distribution(const param_type& __p) | |
2544 | : _M_param(__p) | |
2545 | { } | |
2546 | ||
2547 | /** | |
2548 | * @brief Resets the distribution state. | |
2549 | */ | |
2550 | void | |
2551 | reset() | |
2552 | { } | |
2553 | ||
2554 | /** | |
2555 | * @brief Returns the @f$ a @f$ of the distribution. | |
2556 | */ | |
2557 | result_type | |
2558 | a() const | |
2559 | { return _M_param.a(); } | |
2560 | ||
2561 | /** | |
2562 | * @brief Returns the @f$ b @f$ of the distribution. | |
2563 | */ | |
2564 | result_type | |
2565 | b() const | |
2566 | { return _M_param.b(); } | |
2567 | ||
2568 | /** | |
2569 | * @brief Returns the @f$ c @f$ of the distribution. | |
2570 | */ | |
2571 | result_type | |
2572 | c() const | |
2573 | { return _M_param.c(); } | |
2574 | ||
2575 | /** | |
2576 | * @brief Returns the parameter set of the distribution. | |
2577 | */ | |
2578 | param_type | |
2579 | param() const | |
2580 | { return _M_param; } | |
2581 | ||
2582 | /** | |
2583 | * @brief Sets the parameter set of the distribution. | |
2584 | * @param __param The new parameter set of the distribution. | |
2585 | */ | |
2586 | void | |
2587 | param(const param_type& __param) | |
2588 | { _M_param = __param; } | |
2589 | ||
2590 | /** | |
2591 | * @brief Returns the greatest lower bound value of the distribution. | |
2592 | */ | |
2593 | result_type | |
2594 | min() const | |
2595 | { return _M_param._M_a; } | |
2596 | ||
2597 | /** | |
2598 | * @brief Returns the least upper bound value of the distribution. | |
2599 | */ | |
2600 | result_type | |
2601 | max() const | |
2602 | { return _M_param._M_c; } | |
2603 | ||
2604 | /** | |
2605 | * @brief Generating functions. | |
2606 | */ | |
2607 | template<typename _UniformRandomNumberGenerator> | |
2608 | result_type | |
2609 | operator()(_UniformRandomNumberGenerator& __urng) | |
2610 | { return this->operator()(__urng, _M_param); } | |
2611 | ||
2612 | template<typename _UniformRandomNumberGenerator> | |
2613 | result_type | |
2614 | operator()(_UniformRandomNumberGenerator& __urng, | |
2615 | const param_type& __p) | |
2616 | { | |
2617 | std::__detail::_Adaptor<_UniformRandomNumberGenerator, result_type> | |
2618 | __aurng(__urng); | |
2619 | result_type __rnd = __aurng(); | |
2620 | if (__rnd <= __p._M_r_ab) | |
2621 | return __p.a() + std::sqrt(__rnd * __p._M_f_ab_ac); | |
2622 | else | |
2623 | return __p.c() - std::sqrt((result_type(1) - __rnd) | |
2624 | * __p._M_f_bc_ac); | |
2625 | } | |
2626 | ||
2627 | template<typename _ForwardIterator, | |
2628 | typename _UniformRandomNumberGenerator> | |
2629 | void | |
2630 | __generate(_ForwardIterator __f, _ForwardIterator __t, | |
2631 | _UniformRandomNumberGenerator& __urng) | |
2632 | { this->__generate(__f, __t, __urng, _M_param); } | |
2633 | ||
2634 | template<typename _ForwardIterator, | |
2635 | typename _UniformRandomNumberGenerator> | |
2636 | void | |
2637 | __generate(_ForwardIterator __f, _ForwardIterator __t, | |
2638 | _UniformRandomNumberGenerator& __urng, | |
2639 | const param_type& __p) | |
2640 | { this->__generate_impl(__f, __t, __urng, __p); } | |
2641 | ||
2642 | template<typename _UniformRandomNumberGenerator> | |
2643 | void | |
2644 | __generate(result_type* __f, result_type* __t, | |
2645 | _UniformRandomNumberGenerator& __urng, | |
2646 | const param_type& __p) | |
2647 | { this->__generate_impl(__f, __t, __urng, __p); } | |
2648 | ||
2649 | /** | |
2650 | * @brief Return true if two triangle distributions have the same | |
2651 | * parameters and the sequences that would be generated | |
2652 | * are equal. | |
2653 | */ | |
2654 | friend bool | |
2655 | operator==(const triangular_distribution& __d1, | |
2656 | const triangular_distribution& __d2) | |
2657 | { return __d1._M_param == __d2._M_param; } | |
2658 | ||
2659 | /** | |
2660 | * @brief Inserts a %triangular_distribution random number distribution | |
2661 | * @p __x into the output stream @p __os. | |
2662 | * | |
2663 | * @param __os An output stream. | |
2664 | * @param __x A %triangular_distribution random number distribution. | |
2665 | * | |
2666 | * @returns The output stream with the state of @p __x inserted or in | |
2667 | * an error state. | |
2668 | */ | |
2669 | template<typename _RealType1, typename _CharT, typename _Traits> | |
2670 | friend std::basic_ostream<_CharT, _Traits>& | |
2671 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2672 | const __gnu_cxx::triangular_distribution<_RealType1>& __x); | |
2673 | ||
2674 | /** | |
2675 | * @brief Extracts a %triangular_distribution random number distribution | |
2676 | * @p __x from the input stream @p __is. | |
2677 | * | |
2678 | * @param __is An input stream. | |
2679 | * @param __x A %triangular_distribution random number generator engine. | |
2680 | * | |
2681 | * @returns The input stream with @p __x extracted or in an error state. | |
2682 | */ | |
2683 | template<typename _RealType1, typename _CharT, typename _Traits> | |
2684 | friend std::basic_istream<_CharT, _Traits>& | |
2685 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2686 | __gnu_cxx::triangular_distribution<_RealType1>& __x); | |
2687 | ||
2688 | private: | |
2689 | template<typename _ForwardIterator, | |
2690 | typename _UniformRandomNumberGenerator> | |
2691 | void | |
2692 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2693 | _UniformRandomNumberGenerator& __urng, | |
2694 | const param_type& __p); | |
2695 | ||
2696 | param_type _M_param; | |
2697 | }; | |
2698 | ||
2699 | /** | |
2700 | * @brief Return true if two triangle distributions are different. | |
2701 | */ | |
2702 | template<typename _RealType> | |
2703 | inline bool | |
2704 | operator!=(const __gnu_cxx::triangular_distribution<_RealType>& __d1, | |
2705 | const __gnu_cxx::triangular_distribution<_RealType>& __d2) | |
026ae646 | 2706 | { return !(__d1 == __d2); } |
d233c237 UD |
2707 | |
2708 | ||
2709 | /** | |
2710 | * @brief A von Mises distribution for random numbers. | |
2711 | * | |
2712 | * The formula for the von Mises probability density function is | |
2713 | * @f[ | |
2714 | * p(x|\mu,\kappa) = \frac{e^{\kappa \cos(x-\mu)}} | |
2715 | * {2\pi I_0(\kappa)} | |
2716 | * @f] | |
2717 | * | |
2718 | * The generating functions use the method according to: | |
2719 | * | |
2720 | * D. J. Best and N. I. Fisher, 1979. "Efficient Simulation of the | |
2721 | * von Mises Distribution", Journal of the Royal Statistical Society. | |
2722 | * Series C (Applied Statistics), Vol. 28, No. 2, pp. 152-157. | |
2723 | * | |
2724 | * <table border=1 cellpadding=10 cellspacing=0> | |
2725 | * <caption align=top>Distribution Statistics</caption> | |
2726 | * <tr><td>Mean</td><td>@f$ \mu @f$</td></tr> | |
2727 | * <tr><td>Variance</td><td>@f$ 1-I_1(\kappa)/I_0(\kappa) @f$</td></tr> | |
2728 | * <tr><td>Range</td><td>@f$[-\pi, \pi]@f$</td></tr> | |
2729 | * </table> | |
2730 | */ | |
2731 | template<typename _RealType = double> | |
2732 | class von_mises_distribution | |
2733 | { | |
2734 | static_assert(std::is_floating_point<_RealType>::value, | |
2735 | "template argument not a floating point type"); | |
2736 | ||
2737 | public: | |
2738 | /** The type of the range of the distribution. */ | |
2739 | typedef _RealType result_type; | |
dd9db6f8 | 2740 | |
d233c237 UD |
2741 | /** Parameter type. */ |
2742 | struct param_type | |
2743 | { | |
2744 | friend class von_mises_distribution<_RealType>; | |
2745 | ||
977ac63e JW |
2746 | param_type() : param_type(0) { } |
2747 | ||
d233c237 | 2748 | explicit |
977ac63e | 2749 | param_type(_RealType __mu, _RealType __kappa = _RealType(1)) |
d233c237 UD |
2750 | : _M_mu(__mu), _M_kappa(__kappa) |
2751 | { | |
2752 | const _RealType __pi = __gnu_cxx::__math_constants<_RealType>::__pi; | |
2f1e8e7c JW |
2753 | __glibcxx_assert(_M_mu >= -__pi && _M_mu <= __pi); |
2754 | __glibcxx_assert(_M_kappa >= _RealType(0)); | |
0388c913 UD |
2755 | |
2756 | auto __tau = std::sqrt(_RealType(4) * _M_kappa * _M_kappa | |
2757 | + _RealType(1)) + _RealType(1); | |
2758 | auto __rho = ((__tau - std::sqrt(_RealType(2) * __tau)) | |
2759 | / (_RealType(2) * _M_kappa)); | |
2760 | _M_r = (_RealType(1) + __rho * __rho) / (_RealType(2) * __rho); | |
d233c237 UD |
2761 | } |
2762 | ||
2763 | _RealType | |
2764 | mu() const | |
2765 | { return _M_mu; } | |
2766 | ||
2767 | _RealType | |
2768 | kappa() const | |
2769 | { return _M_kappa; } | |
2770 | ||
2771 | friend bool | |
2772 | operator==(const param_type& __p1, const param_type& __p2) | |
12905f10 JW |
2773 | { return __p1._M_mu == __p2._M_mu && __p1._M_kappa == __p2._M_kappa; } |
2774 | ||
2775 | friend bool | |
2776 | operator!=(const param_type& __p1, const param_type& __p2) | |
2777 | { return !(__p1 == __p2); } | |
d233c237 UD |
2778 | |
2779 | private: | |
d233c237 UD |
2780 | _RealType _M_mu; |
2781 | _RealType _M_kappa; | |
0388c913 | 2782 | _RealType _M_r; |
d233c237 UD |
2783 | }; |
2784 | ||
dd9db6f8 JW |
2785 | von_mises_distribution() : von_mises_distribution(0.0) { } |
2786 | ||
d233c237 | 2787 | /** |
0388c913 | 2788 | * @brief Constructs a von Mises distribution with parameters |
d233c237 UD |
2789 | * @f$\mu@f$ and @f$\kappa@f$. |
2790 | */ | |
2791 | explicit | |
dd9db6f8 | 2792 | von_mises_distribution(result_type __mu, |
d233c237 | 2793 | result_type __kappa = result_type(1)) |
dd9db6f8 | 2794 | : _M_param(__mu, __kappa) |
d233c237 UD |
2795 | { } |
2796 | ||
2797 | explicit | |
2798 | von_mises_distribution(const param_type& __p) | |
2799 | : _M_param(__p) | |
2800 | { } | |
2801 | ||
2802 | /** | |
2803 | * @brief Resets the distribution state. | |
2804 | */ | |
2805 | void | |
2806 | reset() | |
2807 | { } | |
2808 | ||
2809 | /** | |
2810 | * @brief Returns the @f$ \mu @f$ of the distribution. | |
2811 | */ | |
2812 | result_type | |
2813 | mu() const | |
2814 | { return _M_param.mu(); } | |
2815 | ||
2816 | /** | |
2817 | * @brief Returns the @f$ \kappa @f$ of the distribution. | |
2818 | */ | |
2819 | result_type | |
2820 | kappa() const | |
2821 | { return _M_param.kappa(); } | |
2822 | ||
2823 | /** | |
2824 | * @brief Returns the parameter set of the distribution. | |
2825 | */ | |
2826 | param_type | |
2827 | param() const | |
2828 | { return _M_param; } | |
2829 | ||
2830 | /** | |
2831 | * @brief Sets the parameter set of the distribution. | |
2832 | * @param __param The new parameter set of the distribution. | |
2833 | */ | |
2834 | void | |
2835 | param(const param_type& __param) | |
2836 | { _M_param = __param; } | |
2837 | ||
2838 | /** | |
2839 | * @brief Returns the greatest lower bound value of the distribution. | |
2840 | */ | |
2841 | result_type | |
2842 | min() const | |
2843 | { | |
2844 | return -__gnu_cxx::__math_constants<result_type>::__pi; | |
2845 | } | |
2846 | ||
2847 | /** | |
2848 | * @brief Returns the least upper bound value of the distribution. | |
2849 | */ | |
2850 | result_type | |
2851 | max() const | |
2852 | { | |
2853 | return __gnu_cxx::__math_constants<result_type>::__pi; | |
2854 | } | |
2855 | ||
2856 | /** | |
2857 | * @brief Generating functions. | |
2858 | */ | |
2859 | template<typename _UniformRandomNumberGenerator> | |
2860 | result_type | |
2861 | operator()(_UniformRandomNumberGenerator& __urng) | |
2862 | { return this->operator()(__urng, _M_param); } | |
2863 | ||
2864 | template<typename _UniformRandomNumberGenerator> | |
2865 | result_type | |
2866 | operator()(_UniformRandomNumberGenerator& __urng, | |
8daac774 | 2867 | const param_type& __p); |
d233c237 UD |
2868 | |
2869 | template<typename _ForwardIterator, | |
2870 | typename _UniformRandomNumberGenerator> | |
2871 | void | |
2872 | __generate(_ForwardIterator __f, _ForwardIterator __t, | |
2873 | _UniformRandomNumberGenerator& __urng) | |
2874 | { this->__generate(__f, __t, __urng, _M_param); } | |
2875 | ||
2876 | template<typename _ForwardIterator, | |
2877 | typename _UniformRandomNumberGenerator> | |
2878 | void | |
2879 | __generate(_ForwardIterator __f, _ForwardIterator __t, | |
2880 | _UniformRandomNumberGenerator& __urng, | |
2881 | const param_type& __p) | |
2882 | { this->__generate_impl(__f, __t, __urng, __p); } | |
2883 | ||
2884 | template<typename _UniformRandomNumberGenerator> | |
2885 | void | |
2886 | __generate(result_type* __f, result_type* __t, | |
2887 | _UniformRandomNumberGenerator& __urng, | |
2888 | const param_type& __p) | |
2889 | { this->__generate_impl(__f, __t, __urng, __p); } | |
2890 | ||
2891 | /** | |
2892 | * @brief Return true if two von Mises distributions have the same | |
2893 | * parameters and the sequences that would be generated | |
2894 | * are equal. | |
2895 | */ | |
2896 | friend bool | |
2897 | operator==(const von_mises_distribution& __d1, | |
2898 | const von_mises_distribution& __d2) | |
2899 | { return __d1._M_param == __d2._M_param; } | |
2900 | ||
2901 | /** | |
2902 | * @brief Inserts a %von_mises_distribution random number distribution | |
2903 | * @p __x into the output stream @p __os. | |
2904 | * | |
2905 | * @param __os An output stream. | |
2906 | * @param __x A %von_mises_distribution random number distribution. | |
2907 | * | |
2908 | * @returns The output stream with the state of @p __x inserted or in | |
2909 | * an error state. | |
2910 | */ | |
2911 | template<typename _RealType1, typename _CharT, typename _Traits> | |
2912 | friend std::basic_ostream<_CharT, _Traits>& | |
2913 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
2914 | const __gnu_cxx::von_mises_distribution<_RealType1>& __x); | |
2915 | ||
2916 | /** | |
2917 | * @brief Extracts a %von_mises_distribution random number distribution | |
2918 | * @p __x from the input stream @p __is. | |
2919 | * | |
2920 | * @param __is An input stream. | |
2921 | * @param __x A %von_mises_distribution random number generator engine. | |
2922 | * | |
2923 | * @returns The input stream with @p __x extracted or in an error state. | |
2924 | */ | |
2925 | template<typename _RealType1, typename _CharT, typename _Traits> | |
2926 | friend std::basic_istream<_CharT, _Traits>& | |
2927 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
2928 | __gnu_cxx::von_mises_distribution<_RealType1>& __x); | |
2929 | ||
2930 | private: | |
2931 | template<typename _ForwardIterator, | |
2932 | typename _UniformRandomNumberGenerator> | |
2933 | void | |
2934 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
2935 | _UniformRandomNumberGenerator& __urng, | |
2936 | const param_type& __p); | |
2937 | ||
2938 | param_type _M_param; | |
2939 | }; | |
2940 | ||
2941 | /** | |
2942 | * @brief Return true if two von Mises distributions are different. | |
2943 | */ | |
2944 | template<typename _RealType> | |
2945 | inline bool | |
2946 | operator!=(const __gnu_cxx::von_mises_distribution<_RealType>& __d1, | |
2947 | const __gnu_cxx::von_mises_distribution<_RealType>& __d2) | |
026ae646 | 2948 | { return !(__d1 == __d2); } |
d233c237 | 2949 | |
d2ae7b11 ESR |
2950 | |
2951 | /** | |
2952 | * @brief A discrete hypergeometric random number distribution. | |
2953 | * | |
2954 | * The hypergeometric distribution is a discrete probability distribution | |
2955 | * that describes the probability of @p k successes in @p n draws @a without | |
2956 | * replacement from a finite population of size @p N containing exactly @p K | |
2957 | * successes. | |
2958 | * | |
2959 | * The formula for the hypergeometric probability density function is | |
2960 | * @f[ | |
2961 | * p(k|N,K,n) = \frac{\binom{K}{k} \binom{N-K}{n-k}}{\binom{N}{n}} | |
2962 | * @f] | |
2963 | * where @f$N@f$ is the total population of the distribution, | |
2964 | * @f$K@f$ is the total population of the distribution. | |
2965 | * | |
2966 | * <table border=1 cellpadding=10 cellspacing=0> | |
2967 | * <caption align=top>Distribution Statistics</caption> | |
2968 | * <tr><td>Mean</td><td>@f$ n\frac{K}{N} @f$</td></tr> | |
2969 | * <tr><td>Variance</td><td>@f$ n\frac{K}{N}\frac{N-K}{N}\frac{N-n}{N-1} | |
2970 | * @f$</td></tr> | |
2971 | * <tr><td>Range</td><td>@f$[max(0, n+K-N), min(K, n)]@f$</td></tr> | |
2972 | * </table> | |
2973 | */ | |
2974 | template<typename _UIntType = unsigned int> | |
2975 | class hypergeometric_distribution | |
2976 | { | |
2977 | static_assert(std::is_unsigned<_UIntType>::value, "template argument " | |
2978 | "substituting _UIntType not an unsigned integral type"); | |
2979 | ||
2980 | public: | |
2981 | /** The type of the range of the distribution. */ | |
2982 | typedef _UIntType result_type; | |
2983 | ||
2984 | /** Parameter type. */ | |
2985 | struct param_type | |
2986 | { | |
2987 | typedef hypergeometric_distribution<_UIntType> distribution_type; | |
2988 | friend class hypergeometric_distribution<_UIntType>; | |
2989 | ||
977ac63e JW |
2990 | param_type() : param_type(10) { } |
2991 | ||
d2ae7b11 | 2992 | explicit |
977ac63e | 2993 | param_type(result_type __N, result_type __K = 5, |
d2ae7b11 ESR |
2994 | result_type __n = 1) |
2995 | : _M_N{__N}, _M_K{__K}, _M_n{__n} | |
2996 | { | |
2f1e8e7c JW |
2997 | __glibcxx_assert(_M_N >= _M_K); |
2998 | __glibcxx_assert(_M_N >= _M_n); | |
d2ae7b11 ESR |
2999 | } |
3000 | ||
3001 | result_type | |
3002 | total_size() const | |
3003 | { return _M_N; } | |
3004 | ||
3005 | result_type | |
3006 | successful_size() const | |
3007 | { return _M_K; } | |
3008 | ||
3009 | result_type | |
3010 | unsuccessful_size() const | |
3011 | { return _M_N - _M_K; } | |
3012 | ||
3013 | result_type | |
3014 | total_draws() const | |
3015 | { return _M_n; } | |
3016 | ||
3017 | friend bool | |
3018 | operator==(const param_type& __p1, const param_type& __p2) | |
3019 | { return (__p1._M_N == __p2._M_N) | |
3020 | && (__p1._M_K == __p2._M_K) | |
3021 | && (__p1._M_n == __p2._M_n); } | |
3022 | ||
12905f10 JW |
3023 | friend bool |
3024 | operator!=(const param_type& __p1, const param_type& __p2) | |
3025 | { return !(__p1 == __p2); } | |
3026 | ||
d2ae7b11 ESR |
3027 | private: |
3028 | ||
3029 | result_type _M_N; | |
3030 | result_type _M_K; | |
3031 | result_type _M_n; | |
3032 | }; | |
3033 | ||
dd9db6f8 JW |
3034 | // constructors and member functions |
3035 | ||
3036 | hypergeometric_distribution() : hypergeometric_distribution(10) { } | |
3037 | ||
d2ae7b11 | 3038 | explicit |
dd9db6f8 | 3039 | hypergeometric_distribution(result_type __N, result_type __K = 5, |
d2ae7b11 ESR |
3040 | result_type __n = 1) |
3041 | : _M_param{__N, __K, __n} | |
3042 | { } | |
3043 | ||
3044 | explicit | |
3045 | hypergeometric_distribution(const param_type& __p) | |
3046 | : _M_param{__p} | |
3047 | { } | |
3048 | ||
3049 | /** | |
3050 | * @brief Resets the distribution state. | |
3051 | */ | |
3052 | void | |
3053 | reset() | |
3054 | { } | |
3055 | ||
3056 | /** | |
3057 | * @brief Returns the distribution parameter @p N, | |
3058 | * the total number of items. | |
3059 | */ | |
3060 | result_type | |
3061 | total_size() const | |
3062 | { return this->_M_param.total_size(); } | |
3063 | ||
3064 | /** | |
3065 | * @brief Returns the distribution parameter @p K, | |
3066 | * the total number of successful items. | |
3067 | */ | |
3068 | result_type | |
3069 | successful_size() const | |
3070 | { return this->_M_param.successful_size(); } | |
3071 | ||
3072 | /** | |
3073 | * @brief Returns the total number of unsuccessful items @f$ N - K @f$. | |
3074 | */ | |
3075 | result_type | |
3076 | unsuccessful_size() const | |
3077 | { return this->_M_param.unsuccessful_size(); } | |
3078 | ||
3079 | /** | |
3080 | * @brief Returns the distribution parameter @p n, | |
3081 | * the total number of draws. | |
3082 | */ | |
3083 | result_type | |
3084 | total_draws() const | |
3085 | { return this->_M_param.total_draws(); } | |
3086 | ||
3087 | /** | |
3088 | * @brief Returns the parameter set of the distribution. | |
3089 | */ | |
3090 | param_type | |
3091 | param() const | |
3092 | { return this->_M_param; } | |
3093 | ||
3094 | /** | |
3095 | * @brief Sets the parameter set of the distribution. | |
3096 | * @param __param The new parameter set of the distribution. | |
3097 | */ | |
3098 | void | |
3099 | param(const param_type& __param) | |
3100 | { this->_M_param = __param; } | |
3101 | ||
3102 | /** | |
3103 | * @brief Returns the greatest lower bound value of the distribution. | |
3104 | */ | |
3105 | result_type | |
3106 | min() const | |
3107 | { | |
3108 | using _IntType = typename std::make_signed<result_type>::type; | |
3109 | return static_cast<result_type>(std::max(static_cast<_IntType>(0), | |
863a2c7e | 3110 | static_cast<_IntType>(this->total_draws() |
d2ae7b11 ESR |
3111 | - this->unsuccessful_size()))); |
3112 | } | |
3113 | ||
3114 | /** | |
3115 | * @brief Returns the least upper bound value of the distribution. | |
3116 | */ | |
3117 | result_type | |
3118 | max() const | |
3119 | { return std::min(this->successful_size(), this->total_draws()); } | |
3120 | ||
3121 | /** | |
3122 | * @brief Generating functions. | |
3123 | */ | |
3124 | template<typename _UniformRandomNumberGenerator> | |
3125 | result_type | |
3126 | operator()(_UniformRandomNumberGenerator& __urng) | |
3127 | { return this->operator()(__urng, this->_M_param); } | |
3128 | ||
3129 | template<typename _UniformRandomNumberGenerator> | |
3130 | result_type | |
3131 | operator()(_UniformRandomNumberGenerator& __urng, | |
3132 | const param_type& __p); | |
3133 | ||
3134 | template<typename _ForwardIterator, | |
3135 | typename _UniformRandomNumberGenerator> | |
3136 | void | |
3137 | __generate(_ForwardIterator __f, _ForwardIterator __t, | |
3138 | _UniformRandomNumberGenerator& __urng) | |
3139 | { this->__generate(__f, __t, __urng, this->_M_param); } | |
3140 | ||
3141 | template<typename _ForwardIterator, | |
3142 | typename _UniformRandomNumberGenerator> | |
3143 | void | |
3144 | __generate(_ForwardIterator __f, _ForwardIterator __t, | |
3145 | _UniformRandomNumberGenerator& __urng, | |
3146 | const param_type& __p) | |
3147 | { this->__generate_impl(__f, __t, __urng, __p); } | |
3148 | ||
3149 | template<typename _UniformRandomNumberGenerator> | |
3150 | void | |
3151 | __generate(result_type* __f, result_type* __t, | |
3152 | _UniformRandomNumberGenerator& __urng, | |
3153 | const param_type& __p) | |
3154 | { this->__generate_impl(__f, __t, __urng, __p); } | |
3155 | ||
3156 | /** | |
3157 | * @brief Return true if two hypergeometric distributions have the same | |
3158 | * parameters and the sequences that would be generated | |
3159 | * are equal. | |
3160 | */ | |
3161 | friend bool | |
3162 | operator==(const hypergeometric_distribution& __d1, | |
3163 | const hypergeometric_distribution& __d2) | |
3164 | { return __d1._M_param == __d2._M_param; } | |
3165 | ||
3166 | /** | |
3167 | * @brief Inserts a %hypergeometric_distribution random number | |
3168 | * distribution @p __x into the output stream @p __os. | |
3169 | * | |
3170 | * @param __os An output stream. | |
3171 | * @param __x A %hypergeometric_distribution random number | |
3172 | * distribution. | |
3173 | * | |
3174 | * @returns The output stream with the state of @p __x inserted or in | |
3175 | * an error state. | |
3176 | */ | |
3177 | template<typename _UIntType1, typename _CharT, typename _Traits> | |
3178 | friend std::basic_ostream<_CharT, _Traits>& | |
3179 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
3180 | const __gnu_cxx::hypergeometric_distribution<_UIntType1>& | |
863a2c7e | 3181 | __x); |
d2ae7b11 ESR |
3182 | |
3183 | /** | |
3184 | * @brief Extracts a %hypergeometric_distribution random number | |
3185 | * distribution @p __x from the input stream @p __is. | |
3186 | * | |
3187 | * @param __is An input stream. | |
3188 | * @param __x A %hypergeometric_distribution random number generator | |
3189 | * distribution. | |
3190 | * | |
3191 | * @returns The input stream with @p __x extracted or in an error | |
3192 | * state. | |
3193 | */ | |
3194 | template<typename _UIntType1, typename _CharT, typename _Traits> | |
3195 | friend std::basic_istream<_CharT, _Traits>& | |
3196 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
3197 | __gnu_cxx::hypergeometric_distribution<_UIntType1>& __x); | |
3198 | ||
3199 | private: | |
3200 | ||
3201 | template<typename _ForwardIterator, | |
3202 | typename _UniformRandomNumberGenerator> | |
3203 | void | |
3204 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
3205 | _UniformRandomNumberGenerator& __urng, | |
3206 | const param_type& __p); | |
3207 | ||
3208 | param_type _M_param; | |
3209 | }; | |
3210 | ||
3211 | /** | |
3212 | * @brief Return true if two hypergeometric distributions are different. | |
3213 | */ | |
3214 | template<typename _UIntType> | |
3215 | inline bool | |
3216 | operator!=(const __gnu_cxx::hypergeometric_distribution<_UIntType>& __d1, | |
3217 | const __gnu_cxx::hypergeometric_distribution<_UIntType>& __d2) | |
3218 | { return !(__d1 == __d2); } | |
3219 | ||
8daac774 ESR |
3220 | /** |
3221 | * @brief A logistic continuous distribution for random numbers. | |
3222 | * | |
3223 | * The formula for the logistic probability density function is | |
3224 | * @f[ | |
3225 | * p(x|\a,\b) = \frac{e^{(x - a)/b}}{b[1 + e^{(x - a)/b}]^2} | |
3226 | * @f] | |
3227 | * where @f$b > 0@f$. | |
3228 | * | |
3229 | * The formula for the logistic probability function is | |
3230 | * @f[ | |
3231 | * cdf(x|\a,\b) = \frac{e^{(x - a)/b}}{1 + e^{(x - a)/b}} | |
3232 | * @f] | |
3233 | * where @f$b > 0@f$. | |
3234 | * | |
3235 | * <table border=1 cellpadding=10 cellspacing=0> | |
3236 | * <caption align=top>Distribution Statistics</caption> | |
3237 | * <tr><td>Mean</td><td>@f$a@f$</td></tr> | |
3238 | * <tr><td>Variance</td><td>@f$b^2\pi^2/3@f$</td></tr> | |
3239 | * <tr><td>Range</td><td>@f$[0, \infty)@f$</td></tr> | |
3240 | * </table> | |
3241 | */ | |
3242 | template<typename _RealType = double> | |
3243 | class | |
3244 | logistic_distribution | |
3245 | { | |
3246 | static_assert(std::is_floating_point<_RealType>::value, | |
3247 | "template argument not a floating point type"); | |
3248 | ||
3249 | public: | |
3250 | /** The type of the range of the distribution. */ | |
3251 | typedef _RealType result_type; | |
12905f10 | 3252 | |
8daac774 ESR |
3253 | /** Parameter type. */ |
3254 | struct param_type | |
3255 | { | |
3256 | typedef logistic_distribution<result_type> distribution_type; | |
3257 | ||
977ac63e JW |
3258 | param_type() : param_type(0) { } |
3259 | ||
3260 | explicit | |
3261 | param_type(result_type __a, result_type __b = result_type(1)) | |
8daac774 ESR |
3262 | : _M_a(__a), _M_b(__b) |
3263 | { | |
2f1e8e7c | 3264 | __glibcxx_assert(_M_b > result_type(0)); |
8daac774 ESR |
3265 | } |
3266 | ||
3267 | result_type | |
3268 | a() const | |
3269 | { return _M_a; } | |
3270 | ||
3271 | result_type | |
3272 | b() const | |
3273 | { return _M_b; } | |
3274 | ||
3275 | friend bool | |
3276 | operator==(const param_type& __p1, const param_type& __p2) | |
12905f10 JW |
3277 | { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; } |
3278 | ||
3279 | friend bool | |
3280 | operator!=(const param_type& __p1, const param_type& __p2) | |
3281 | { return !(__p1 == __p2); } | |
8daac774 ESR |
3282 | |
3283 | private: | |
3284 | void _M_initialize(); | |
3285 | ||
3286 | result_type _M_a; | |
3287 | result_type _M_b; | |
3288 | }; | |
3289 | ||
3290 | /** | |
3291 | * @brief Constructors. | |
dd9db6f8 | 3292 | * @{ |
8daac774 | 3293 | */ |
dd9db6f8 JW |
3294 | logistic_distribution() : logistic_distribution(0.0) { } |
3295 | ||
8daac774 | 3296 | explicit |
dd9db6f8 | 3297 | logistic_distribution(result_type __a, result_type __b = result_type(1)) |
8daac774 ESR |
3298 | : _M_param(__a, __b) |
3299 | { } | |
3300 | ||
3301 | explicit | |
3302 | logistic_distribution(const param_type& __p) | |
3303 | : _M_param(__p) | |
3304 | { } | |
3305 | ||
f0b88346 | 3306 | /// @} |
dd9db6f8 | 3307 | |
8daac774 ESR |
3308 | /** |
3309 | * @brief Resets the distribution state. | |
3310 | */ | |
3311 | void | |
3312 | reset() | |
3313 | { } | |
3314 | ||
3315 | /** | |
3316 | * @brief Return the parameters of the distribution. | |
3317 | */ | |
3318 | result_type | |
3319 | a() const | |
3320 | { return _M_param.a(); } | |
3321 | ||
3322 | result_type | |
3323 | b() const | |
3324 | { return _M_param.b(); } | |
3325 | ||
3326 | /** | |
3327 | * @brief Returns the parameter set of the distribution. | |
3328 | */ | |
3329 | param_type | |
3330 | param() const | |
3331 | { return _M_param; } | |
3332 | ||
3333 | /** | |
3334 | * @brief Sets the parameter set of the distribution. | |
3335 | * @param __param The new parameter set of the distribution. | |
3336 | */ | |
3337 | void | |
3338 | param(const param_type& __param) | |
3339 | { _M_param = __param; } | |
3340 | ||
3341 | /** | |
3342 | * @brief Returns the greatest lower bound value of the distribution. | |
3343 | */ | |
3344 | result_type | |
3345 | min() const | |
3346 | { return -std::numeric_limits<result_type>::max(); } | |
3347 | ||
3348 | /** | |
3349 | * @brief Returns the least upper bound value of the distribution. | |
3350 | */ | |
3351 | result_type | |
3352 | max() const | |
3353 | { return std::numeric_limits<result_type>::max(); } | |
3354 | ||
3355 | /** | |
3356 | * @brief Generating functions. | |
3357 | */ | |
3358 | template<typename _UniformRandomNumberGenerator> | |
3359 | result_type | |
3360 | operator()(_UniformRandomNumberGenerator& __urng) | |
3361 | { return this->operator()(__urng, this->_M_param); } | |
3362 | ||
3363 | template<typename _UniformRandomNumberGenerator> | |
3364 | result_type | |
3365 | operator()(_UniformRandomNumberGenerator&, | |
3366 | const param_type&); | |
3367 | ||
3368 | template<typename _ForwardIterator, | |
3369 | typename _UniformRandomNumberGenerator> | |
3370 | void | |
3371 | __generate(_ForwardIterator __f, _ForwardIterator __t, | |
3372 | _UniformRandomNumberGenerator& __urng) | |
3373 | { this->__generate(__f, __t, __urng, this->param()); } | |
3374 | ||
3375 | template<typename _ForwardIterator, | |
3376 | typename _UniformRandomNumberGenerator> | |
3377 | void | |
3378 | __generate(_ForwardIterator __f, _ForwardIterator __t, | |
3379 | _UniformRandomNumberGenerator& __urng, | |
3380 | const param_type& __p) | |
3381 | { this->__generate_impl(__f, __t, __urng, __p); } | |
3382 | ||
3383 | template<typename _UniformRandomNumberGenerator> | |
3384 | void | |
3385 | __generate(result_type* __f, result_type* __t, | |
3386 | _UniformRandomNumberGenerator& __urng, | |
3387 | const param_type& __p) | |
3388 | { this->__generate_impl(__f, __t, __urng, __p); } | |
3389 | ||
3390 | /** | |
3391 | * @brief Return true if two logistic distributions have | |
3392 | * the same parameters and the sequences that would | |
3393 | * be generated are equal. | |
3394 | */ | |
3395 | template<typename _RealType1> | |
863a2c7e UD |
3396 | friend bool |
3397 | operator==(const logistic_distribution<_RealType1>& __d1, | |
8daac774 | 3398 | const logistic_distribution<_RealType1>& __d2) |
863a2c7e | 3399 | { return __d1.param() == __d2.param(); } |
8daac774 ESR |
3400 | |
3401 | /** | |
3402 | * @brief Inserts a %logistic_distribution random number distribution | |
3403 | * @p __x into the output stream @p __os. | |
3404 | * | |
3405 | * @param __os An output stream. | |
3406 | * @param __x A %logistic_distribution random number distribution. | |
3407 | * | |
3408 | * @returns The output stream with the state of @p __x inserted or in | |
3409 | * an error state. | |
3410 | */ | |
3411 | template<typename _RealType1, typename _CharT, typename _Traits> | |
3412 | friend std::basic_ostream<_CharT, _Traits>& | |
3413 | operator<<(std::basic_ostream<_CharT, _Traits>&, | |
3414 | const logistic_distribution<_RealType1>&); | |
3415 | ||
3416 | /** | |
3417 | * @brief Extracts a %logistic_distribution random number distribution | |
3418 | * @p __x from the input stream @p __is. | |
3419 | * | |
3420 | * @param __is An input stream. | |
3421 | * @param __x A %logistic_distribution random number | |
3422 | * generator engine. | |
3423 | * | |
3424 | * @returns The input stream with @p __x extracted or in an error state. | |
3425 | */ | |
3426 | template<typename _RealType1, typename _CharT, typename _Traits> | |
3427 | friend std::basic_istream<_CharT, _Traits>& | |
3428 | operator>>(std::basic_istream<_CharT, _Traits>&, | |
3429 | logistic_distribution<_RealType1>&); | |
3430 | ||
3431 | private: | |
3432 | template<typename _ForwardIterator, | |
3433 | typename _UniformRandomNumberGenerator> | |
3434 | void | |
3435 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
3436 | _UniformRandomNumberGenerator& __urng, | |
3437 | const param_type& __p); | |
3438 | ||
3439 | param_type _M_param; | |
3440 | }; | |
3441 | ||
3442 | /** | |
3443 | * @brief Return true if two logistic distributions are not equal. | |
3444 | */ | |
3445 | template<typename _RealType1> | |
3446 | inline bool | |
3447 | operator!=(const logistic_distribution<_RealType1>& __d1, | |
3448 | const logistic_distribution<_RealType1>& __d2) | |
3449 | { return !(__d1 == __d2); } | |
3450 | ||
863a2c7e UD |
3451 | |
3452 | /** | |
3453 | * @brief A distribution for random coordinates on a unit sphere. | |
3454 | * | |
3455 | * The method used in the generation function is attributed by Donald Knuth | |
3456 | * to G. W. Brown, Modern Mathematics for the Engineer (1956). | |
3457 | */ | |
3458 | template<std::size_t _Dimen, typename _RealType = double> | |
3459 | class uniform_on_sphere_distribution | |
3460 | { | |
3461 | static_assert(std::is_floating_point<_RealType>::value, | |
3462 | "template argument not a floating point type"); | |
3463 | static_assert(_Dimen != 0, "dimension is zero"); | |
3464 | ||
3465 | public: | |
3466 | /** The type of the range of the distribution. */ | |
3467 | typedef std::array<_RealType, _Dimen> result_type; | |
12905f10 | 3468 | |
863a2c7e UD |
3469 | /** Parameter type. */ |
3470 | struct param_type | |
3471 | { | |
977ac63e | 3472 | param_type() { } |
863a2c7e UD |
3473 | |
3474 | friend bool | |
12905f10 | 3475 | operator==(const param_type&, const param_type&) |
863a2c7e | 3476 | { return true; } |
12905f10 JW |
3477 | |
3478 | friend bool | |
3479 | operator!=(const param_type&, const param_type&) | |
3480 | { return false; } | |
863a2c7e UD |
3481 | }; |
3482 | ||
3483 | /** | |
3484 | * @brief Constructs a uniform on sphere distribution. | |
3485 | */ | |
863a2c7e | 3486 | uniform_on_sphere_distribution() |
026ae646 | 3487 | : _M_param(), _M_nd() |
863a2c7e UD |
3488 | { } |
3489 | ||
3490 | explicit | |
3491 | uniform_on_sphere_distribution(const param_type& __p) | |
026ae646 | 3492 | : _M_param(__p), _M_nd() |
863a2c7e UD |
3493 | { } |
3494 | ||
3495 | /** | |
3496 | * @brief Resets the distribution state. | |
3497 | */ | |
3498 | void | |
3499 | reset() | |
026ae646 | 3500 | { _M_nd.reset(); } |
863a2c7e UD |
3501 | |
3502 | /** | |
3503 | * @brief Returns the parameter set of the distribution. | |
3504 | */ | |
3505 | param_type | |
3506 | param() const | |
3507 | { return _M_param; } | |
3508 | ||
3509 | /** | |
3510 | * @brief Sets the parameter set of the distribution. | |
3511 | * @param __param The new parameter set of the distribution. | |
3512 | */ | |
3513 | void | |
3514 | param(const param_type& __param) | |
3515 | { _M_param = __param; } | |
3516 | ||
3517 | /** | |
3518 | * @brief Returns the greatest lower bound value of the distribution. | |
3519 | * This function makes no sense for this distribution. | |
3520 | */ | |
3521 | result_type | |
3522 | min() const | |
3523 | { | |
3524 | result_type __res; | |
3525 | __res.fill(0); | |
3526 | return __res; | |
3527 | } | |
3528 | ||
3529 | /** | |
3530 | * @brief Returns the least upper bound value of the distribution. | |
3531 | * This function makes no sense for this distribution. | |
3532 | */ | |
3533 | result_type | |
3534 | max() const | |
3535 | { | |
3536 | result_type __res; | |
3537 | __res.fill(0); | |
3538 | return __res; | |
3539 | } | |
3540 | ||
3541 | /** | |
3542 | * @brief Generating functions. | |
3543 | */ | |
3544 | template<typename _UniformRandomNumberGenerator> | |
3545 | result_type | |
3546 | operator()(_UniformRandomNumberGenerator& __urng) | |
3547 | { return this->operator()(__urng, _M_param); } | |
3548 | ||
3549 | template<typename _UniformRandomNumberGenerator> | |
3550 | result_type | |
3551 | operator()(_UniformRandomNumberGenerator& __urng, | |
3552 | const param_type& __p); | |
3553 | ||
3554 | template<typename _ForwardIterator, | |
3555 | typename _UniformRandomNumberGenerator> | |
3556 | void | |
3557 | __generate(_ForwardIterator __f, _ForwardIterator __t, | |
3558 | _UniformRandomNumberGenerator& __urng) | |
3559 | { this->__generate(__f, __t, __urng, this->param()); } | |
3560 | ||
3561 | template<typename _ForwardIterator, | |
3562 | typename _UniformRandomNumberGenerator> | |
3563 | void | |
3564 | __generate(_ForwardIterator __f, _ForwardIterator __t, | |
3565 | _UniformRandomNumberGenerator& __urng, | |
3566 | const param_type& __p) | |
3567 | { this->__generate_impl(__f, __t, __urng, __p); } | |
3568 | ||
3569 | template<typename _UniformRandomNumberGenerator> | |
3570 | void | |
3571 | __generate(result_type* __f, result_type* __t, | |
3572 | _UniformRandomNumberGenerator& __urng, | |
3573 | const param_type& __p) | |
3574 | { this->__generate_impl(__f, __t, __urng, __p); } | |
3575 | ||
3576 | /** | |
3577 | * @brief Return true if two uniform on sphere distributions have | |
3578 | * the same parameters and the sequences that would be | |
3579 | * generated are equal. | |
3580 | */ | |
3581 | friend bool | |
3582 | operator==(const uniform_on_sphere_distribution& __d1, | |
3583 | const uniform_on_sphere_distribution& __d2) | |
026ae646 | 3584 | { return __d1._M_nd == __d2._M_nd; } |
863a2c7e UD |
3585 | |
3586 | /** | |
026ae646 PC |
3587 | * @brief Inserts a %uniform_on_sphere_distribution random number |
3588 | * distribution @p __x into the output stream @p __os. | |
863a2c7e UD |
3589 | * |
3590 | * @param __os An output stream. | |
026ae646 PC |
3591 | * @param __x A %uniform_on_sphere_distribution random number |
3592 | * distribution. | |
863a2c7e UD |
3593 | * |
3594 | * @returns The output stream with the state of @p __x inserted or in | |
3595 | * an error state. | |
3596 | */ | |
3597 | template<size_t _Dimen1, typename _RealType1, typename _CharT, | |
3598 | typename _Traits> | |
3599 | friend std::basic_ostream<_CharT, _Traits>& | |
3600 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
3601 | const __gnu_cxx::uniform_on_sphere_distribution<_Dimen1, | |
3602 | _RealType1>& | |
3603 | __x); | |
3604 | ||
3605 | /** | |
026ae646 PC |
3606 | * @brief Extracts a %uniform_on_sphere_distribution random number |
3607 | * distribution | |
863a2c7e UD |
3608 | * @p __x from the input stream @p __is. |
3609 | * | |
3610 | * @param __is An input stream. | |
026ae646 PC |
3611 | * @param __x A %uniform_on_sphere_distribution random number |
3612 | * generator engine. | |
863a2c7e UD |
3613 | * |
3614 | * @returns The input stream with @p __x extracted or in an error state. | |
3615 | */ | |
3616 | template<std::size_t _Dimen1, typename _RealType1, typename _CharT, | |
3617 | typename _Traits> | |
3618 | friend std::basic_istream<_CharT, _Traits>& | |
3619 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
3620 | __gnu_cxx::uniform_on_sphere_distribution<_Dimen1, | |
3621 | _RealType1>& __x); | |
3622 | ||
3623 | private: | |
3624 | template<typename _ForwardIterator, | |
3625 | typename _UniformRandomNumberGenerator> | |
3626 | void | |
3627 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
3628 | _UniformRandomNumberGenerator& __urng, | |
3629 | const param_type& __p); | |
3630 | ||
3631 | param_type _M_param; | |
026ae646 | 3632 | std::normal_distribution<_RealType> _M_nd; |
863a2c7e UD |
3633 | }; |
3634 | ||
3635 | /** | |
3636 | * @brief Return true if two uniform on sphere distributions are different. | |
3637 | */ | |
3638 | template<std::size_t _Dimen, typename _RealType> | |
3639 | inline bool | |
3640 | operator!=(const __gnu_cxx::uniform_on_sphere_distribution<_Dimen, | |
3641 | _RealType>& __d1, | |
3642 | const __gnu_cxx::uniform_on_sphere_distribution<_Dimen, | |
3643 | _RealType>& __d2) | |
026ae646 | 3644 | { return !(__d1 == __d2); } |
863a2c7e | 3645 | |
10da5b7c ESR |
3646 | |
3647 | /** | |
3648 | * @brief A distribution for random coordinates inside a unit sphere. | |
3649 | */ | |
3650 | template<std::size_t _Dimen, typename _RealType = double> | |
3651 | class uniform_inside_sphere_distribution | |
3652 | { | |
3653 | static_assert(std::is_floating_point<_RealType>::value, | |
3654 | "template argument not a floating point type"); | |
3655 | static_assert(_Dimen != 0, "dimension is zero"); | |
3656 | ||
3657 | public: | |
3658 | /** The type of the range of the distribution. */ | |
3659 | using result_type = std::array<_RealType, _Dimen>; | |
3660 | ||
3661 | /** Parameter type. */ | |
3662 | struct param_type | |
3663 | { | |
3664 | using distribution_type | |
3665 | = uniform_inside_sphere_distribution<_Dimen, _RealType>; | |
3666 | friend class uniform_inside_sphere_distribution<_Dimen, _RealType>; | |
3667 | ||
977ac63e JW |
3668 | param_type() : param_type(1.0) { } |
3669 | ||
10da5b7c | 3670 | explicit |
977ac63e | 3671 | param_type(_RealType __radius) |
10da5b7c ESR |
3672 | : _M_radius(__radius) |
3673 | { | |
3674 | __glibcxx_assert(_M_radius > _RealType(0)); | |
3675 | } | |
3676 | ||
3677 | _RealType | |
3678 | radius() const | |
3679 | { return _M_radius; } | |
3680 | ||
3681 | friend bool | |
3682 | operator==(const param_type& __p1, const param_type& __p2) | |
3683 | { return __p1._M_radius == __p2._M_radius; } | |
3684 | ||
12905f10 JW |
3685 | friend bool |
3686 | operator!=(const param_type& __p1, const param_type& __p2) | |
3687 | { return !(__p1 == __p2); } | |
3688 | ||
10da5b7c ESR |
3689 | private: |
3690 | _RealType _M_radius; | |
3691 | }; | |
3692 | ||
3693 | /** | |
3694 | * @brief Constructors. | |
dd9db6f8 | 3695 | * @{ |
10da5b7c | 3696 | */ |
dd9db6f8 JW |
3697 | |
3698 | uniform_inside_sphere_distribution() | |
3699 | : uniform_inside_sphere_distribution(1.0) | |
3700 | { } | |
3701 | ||
10da5b7c | 3702 | explicit |
dd9db6f8 | 3703 | uniform_inside_sphere_distribution(_RealType __radius) |
10da5b7c ESR |
3704 | : _M_param(__radius), _M_uosd() |
3705 | { } | |
3706 | ||
3707 | explicit | |
3708 | uniform_inside_sphere_distribution(const param_type& __p) | |
3709 | : _M_param(__p), _M_uosd() | |
3710 | { } | |
3711 | ||
f0b88346 | 3712 | /// @} |
dd9db6f8 | 3713 | |
10da5b7c ESR |
3714 | /** |
3715 | * @brief Resets the distribution state. | |
3716 | */ | |
3717 | void | |
3718 | reset() | |
3719 | { _M_uosd.reset(); } | |
3720 | ||
3721 | /** | |
3722 | * @brief Returns the @f$radius@f$ of the distribution. | |
3723 | */ | |
3724 | _RealType | |
3725 | radius() const | |
3726 | { return _M_param.radius(); } | |
3727 | ||
3728 | /** | |
3729 | * @brief Returns the parameter set of the distribution. | |
3730 | */ | |
3731 | param_type | |
3732 | param() const | |
3733 | { return _M_param; } | |
3734 | ||
3735 | /** | |
3736 | * @brief Sets the parameter set of the distribution. | |
3737 | * @param __param The new parameter set of the distribution. | |
3738 | */ | |
3739 | void | |
3740 | param(const param_type& __param) | |
3741 | { _M_param = __param; } | |
3742 | ||
3743 | /** | |
3744 | * @brief Returns the greatest lower bound value of the distribution. | |
3745 | * This function makes no sense for this distribution. | |
3746 | */ | |
3747 | result_type | |
3748 | min() const | |
3749 | { | |
3750 | result_type __res; | |
3751 | __res.fill(0); | |
3752 | return __res; | |
3753 | } | |
3754 | ||
3755 | /** | |
3756 | * @brief Returns the least upper bound value of the distribution. | |
3757 | * This function makes no sense for this distribution. | |
3758 | */ | |
3759 | result_type | |
3760 | max() const | |
3761 | { | |
3762 | result_type __res; | |
3763 | __res.fill(0); | |
3764 | return __res; | |
3765 | } | |
3766 | ||
3767 | /** | |
3768 | * @brief Generating functions. | |
3769 | */ | |
3770 | template<typename _UniformRandomNumberGenerator> | |
3771 | result_type | |
3772 | operator()(_UniformRandomNumberGenerator& __urng) | |
3773 | { return this->operator()(__urng, _M_param); } | |
3774 | ||
3775 | template<typename _UniformRandomNumberGenerator> | |
3776 | result_type | |
3777 | operator()(_UniformRandomNumberGenerator& __urng, | |
3778 | const param_type& __p); | |
3779 | ||
3780 | template<typename _ForwardIterator, | |
3781 | typename _UniformRandomNumberGenerator> | |
3782 | void | |
3783 | __generate(_ForwardIterator __f, _ForwardIterator __t, | |
3784 | _UniformRandomNumberGenerator& __urng) | |
3785 | { this->__generate(__f, __t, __urng, this->param()); } | |
3786 | ||
3787 | template<typename _ForwardIterator, | |
3788 | typename _UniformRandomNumberGenerator> | |
3789 | void | |
3790 | __generate(_ForwardIterator __f, _ForwardIterator __t, | |
3791 | _UniformRandomNumberGenerator& __urng, | |
3792 | const param_type& __p) | |
3793 | { this->__generate_impl(__f, __t, __urng, __p); } | |
3794 | ||
3795 | template<typename _UniformRandomNumberGenerator> | |
3796 | void | |
3797 | __generate(result_type* __f, result_type* __t, | |
3798 | _UniformRandomNumberGenerator& __urng, | |
3799 | const param_type& __p) | |
3800 | { this->__generate_impl(__f, __t, __urng, __p); } | |
3801 | ||
3802 | /** | |
3803 | * @brief Return true if two uniform on sphere distributions have | |
3804 | * the same parameters and the sequences that would be | |
3805 | * generated are equal. | |
3806 | */ | |
3807 | friend bool | |
3808 | operator==(const uniform_inside_sphere_distribution& __d1, | |
3809 | const uniform_inside_sphere_distribution& __d2) | |
3810 | { return __d1._M_param == __d2._M_param && __d1._M_uosd == __d2._M_uosd; } | |
3811 | ||
3812 | /** | |
3813 | * @brief Inserts a %uniform_inside_sphere_distribution random number | |
3814 | * distribution @p __x into the output stream @p __os. | |
3815 | * | |
3816 | * @param __os An output stream. | |
3817 | * @param __x A %uniform_inside_sphere_distribution random number | |
3818 | * distribution. | |
3819 | * | |
3820 | * @returns The output stream with the state of @p __x inserted or in | |
3821 | * an error state. | |
3822 | */ | |
3823 | template<size_t _Dimen1, typename _RealType1, typename _CharT, | |
3824 | typename _Traits> | |
3825 | friend std::basic_ostream<_CharT, _Traits>& | |
3826 | operator<<(std::basic_ostream<_CharT, _Traits>& __os, | |
3827 | const __gnu_cxx::uniform_inside_sphere_distribution<_Dimen1, | |
3828 | _RealType1>& | |
3829 | ); | |
3830 | ||
3831 | /** | |
3832 | * @brief Extracts a %uniform_inside_sphere_distribution random number | |
3833 | * distribution | |
3834 | * @p __x from the input stream @p __is. | |
3835 | * | |
3836 | * @param __is An input stream. | |
3837 | * @param __x A %uniform_inside_sphere_distribution random number | |
3838 | * generator engine. | |
3839 | * | |
3840 | * @returns The input stream with @p __x extracted or in an error state. | |
3841 | */ | |
3842 | template<std::size_t _Dimen1, typename _RealType1, typename _CharT, | |
3843 | typename _Traits> | |
3844 | friend std::basic_istream<_CharT, _Traits>& | |
3845 | operator>>(std::basic_istream<_CharT, _Traits>& __is, | |
3846 | __gnu_cxx::uniform_inside_sphere_distribution<_Dimen1, | |
3847 | _RealType1>&); | |
3848 | ||
3849 | private: | |
3850 | template<typename _ForwardIterator, | |
3851 | typename _UniformRandomNumberGenerator> | |
3852 | void | |
3853 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t, | |
3854 | _UniformRandomNumberGenerator& __urng, | |
3855 | const param_type& __p); | |
3856 | ||
3857 | param_type _M_param; | |
3858 | uniform_on_sphere_distribution<_Dimen, _RealType> _M_uosd; | |
3859 | }; | |
3860 | ||
3861 | /** | |
3862 | * @brief Return true if two uniform on sphere distributions are different. | |
3863 | */ | |
3864 | template<std::size_t _Dimen, typename _RealType> | |
3865 | inline bool | |
3866 | operator!=(const __gnu_cxx::uniform_inside_sphere_distribution<_Dimen, | |
3867 | _RealType>& __d1, | |
3868 | const __gnu_cxx::uniform_inside_sphere_distribution<_Dimen, | |
3869 | _RealType>& __d2) | |
3870 | { return !(__d1 == __d2); } | |
3871 | ||
1860430a | 3872 | _GLIBCXX_END_NAMESPACE_VERSION |
9bf714c2 | 3873 | } // namespace __gnu_cxx |
1860430a | 3874 | |
9f5391ee JW |
3875 | #include <ext/opt_random.h> |
3876 | #include <ext/random.tcc> | |
1860430a | 3877 | |
7215aaed | 3878 | #endif // _GLIBCXX_USE_C99_STDINT_TR1 && UINT32_C |
8054b82e | 3879 | |
734f5023 | 3880 | #endif // C++11 |
8054b82e PC |
3881 | |
3882 | #endif // _EXT_RANDOM |