35 namespace std _GLIBCXX_VISIBILITY(default)
42 _GLIBCXX_BEGIN_NAMESPACE_VERSION
54 template<
typename _Tp, _Tp __m, _Tp __a, _Tp __c,
bool>
64 static const _Tp __q = __m / __a;
65 static const _Tp __r = __m % __a;
67 _Tp __t1 = __a * (__x % __q);
68 _Tp __t2 = __r * (__x / __q);
72 __x = __m - __t2 + __t1;
77 const _Tp __d = __m - __x;
89 template<
typename _Tp, _Tp __m, _Tp __a, _Tp __c>
90 struct _Mod<_Tp, __m, __a, __c, true>
94 {
return __a * __x + __c; }
97 template<
typename _InputIterator,
typename _OutputIterator,
98 typename _UnaryOperation>
100 __transform(_InputIterator __first, _InputIterator __last,
101 _OutputIterator __result, _UnaryOperation __unary_op)
103 for (; __first != __last; ++__first, ++__result)
104 *__result = __unary_op(*__first);
108 _GLIBCXX_END_NAMESPACE_VERSION
111 _GLIBCXX_BEGIN_NAMESPACE_VERSION
113 template<
typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>
115 linear_congruential_engine<_UIntType, __a, __c, __m>::multiplier;
117 template<
typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>
119 linear_congruential_engine<_UIntType, __a, __c, __m>::increment;
121 template<
typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>
123 linear_congruential_engine<_UIntType, __a, __c, __m>::modulus;
125 template<
typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>
127 linear_congruential_engine<_UIntType, __a, __c, __m>::default_seed;
133 template<
typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>
138 if ((__detail::__mod<_UIntType, __m>(__c) == 0)
139 && (__detail::__mod<_UIntType, __m>(__s) == 0))
142 _M_x = __detail::__mod<_UIntType, __m>(__s);
148 template<
typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>
149 template<
typename _Sseq>
156 const _UIntType __k = (__k0 + 31) / 32;
157 uint_least32_t __arr[__k + 3];
158 __q.generate(__arr + 0, __arr + __k + 3);
159 _UIntType __factor = 1u;
160 _UIntType __sum = 0u;
161 for (
size_t __j = 0; __j < __k; ++__j)
163 __sum += __arr[__j + 3] * __factor;
164 __factor *= __detail::_Shift<_UIntType, 32>::__value;
169 template<
typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m,
170 typename _CharT,
typename _Traits>
172 operator<<(std::basic_ostream<_CharT, _Traits>& __os,
174 __a, __c, __m>& __lcr)
177 typedef typename __ostream_type::ios_base __ios_base;
179 const typename __ios_base::fmtflags __flags = __os.
flags();
180 const _CharT __fill = __os.fill();
182 __os.fill(__os.widen(
' '));
191 template<
typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m,
192 typename _CharT,
typename _Traits>
195 linear_congruential_engine<_UIntType, __a, __c, __m>& __lcr)
198 typedef typename __istream_type::ios_base __ios_base;
200 const typename __ios_base::fmtflags __flags = __is.
flags();
210 template<
typename _UIntType,
211 size_t __w,
size_t __n,
size_t __m,
size_t __r,
212 _UIntType __a,
size_t __u, _UIntType __d,
size_t __s,
213 _UIntType __b,
size_t __t, _UIntType __c,
size_t __l,
216 mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
217 __s, __b, __t, __c, __l, __f>::word_size;
219 template<
typename _UIntType,
220 size_t __w,
size_t __n,
size_t __m,
size_t __r,
221 _UIntType __a,
size_t __u, _UIntType __d,
size_t __s,
222 _UIntType __b,
size_t __t, _UIntType __c,
size_t __l,
225 mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
226 __s, __b, __t, __c, __l, __f>::state_size;
228 template<
typename _UIntType,
229 size_t __w,
size_t __n,
size_t __m,
size_t __r,
230 _UIntType __a,
size_t __u, _UIntType __d,
size_t __s,
231 _UIntType __b,
size_t __t, _UIntType __c,
size_t __l,
234 mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
235 __s, __b, __t, __c, __l, __f>::shift_size;
237 template<
typename _UIntType,
238 size_t __w,
size_t __n,
size_t __m,
size_t __r,
239 _UIntType __a,
size_t __u, _UIntType __d,
size_t __s,
240 _UIntType __b,
size_t __t, _UIntType __c,
size_t __l,
243 mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
244 __s, __b, __t, __c, __l, __f>::mask_bits;
246 template<
typename _UIntType,
247 size_t __w,
size_t __n,
size_t __m,
size_t __r,
248 _UIntType __a,
size_t __u, _UIntType __d,
size_t __s,
249 _UIntType __b,
size_t __t, _UIntType __c,
size_t __l,
252 mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
253 __s, __b, __t, __c, __l, __f>::xor_mask;
255 template<
typename _UIntType,
256 size_t __w,
size_t __n,
size_t __m,
size_t __r,
257 _UIntType __a,
size_t __u, _UIntType __d,
size_t __s,
258 _UIntType __b,
size_t __t, _UIntType __c,
size_t __l,
261 mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
262 __s, __b, __t, __c, __l, __f>::tempering_u;
264 template<
typename _UIntType,
265 size_t __w,
size_t __n,
size_t __m,
size_t __r,
266 _UIntType __a,
size_t __u, _UIntType __d,
size_t __s,
267 _UIntType __b,
size_t __t, _UIntType __c,
size_t __l,
270 mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
271 __s, __b, __t, __c, __l, __f>::tempering_d;
273 template<
typename _UIntType,
274 size_t __w,
size_t __n,
size_t __m,
size_t __r,
275 _UIntType __a,
size_t __u, _UIntType __d,
size_t __s,
276 _UIntType __b,
size_t __t, _UIntType __c,
size_t __l,
279 mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
280 __s, __b, __t, __c, __l, __f>::tempering_s;
282 template<
typename _UIntType,
283 size_t __w,
size_t __n,
size_t __m,
size_t __r,
284 _UIntType __a,
size_t __u, _UIntType __d,
size_t __s,
285 _UIntType __b,
size_t __t, _UIntType __c,
size_t __l,
288 mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
289 __s, __b, __t, __c, __l, __f>::tempering_b;
291 template<
typename _UIntType,
292 size_t __w,
size_t __n,
size_t __m,
size_t __r,
293 _UIntType __a,
size_t __u, _UIntType __d,
size_t __s,
294 _UIntType __b,
size_t __t, _UIntType __c,
size_t __l,
297 mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
298 __s, __b, __t, __c, __l, __f>::tempering_t;
300 template<
typename _UIntType,
301 size_t __w,
size_t __n,
size_t __m,
size_t __r,
302 _UIntType __a,
size_t __u, _UIntType __d,
size_t __s,
303 _UIntType __b,
size_t __t, _UIntType __c,
size_t __l,
306 mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
307 __s, __b, __t, __c, __l, __f>::tempering_c;
309 template<
typename _UIntType,
310 size_t __w,
size_t __n,
size_t __m,
size_t __r,
311 _UIntType __a,
size_t __u, _UIntType __d,
size_t __s,
312 _UIntType __b,
size_t __t, _UIntType __c,
size_t __l,
315 mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
316 __s, __b, __t, __c, __l, __f>::tempering_l;
318 template<
typename _UIntType,
319 size_t __w,
size_t __n,
size_t __m,
size_t __r,
320 _UIntType __a,
size_t __u, _UIntType __d,
size_t __s,
321 _UIntType __b,
size_t __t, _UIntType __c,
size_t __l,
324 mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
325 __s, __b, __t, __c, __l, __f>::
326 initialization_multiplier;
328 template<
typename _UIntType,
329 size_t __w,
size_t __n,
size_t __m,
size_t __r,
330 _UIntType __a,
size_t __u, _UIntType __d,
size_t __s,
331 _UIntType __b,
size_t __t, _UIntType __c,
size_t __l,
334 mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
335 __s, __b, __t, __c, __l, __f>::default_seed;
337 template<
typename _UIntType,
338 size_t __w,
size_t __n,
size_t __m,
size_t __r,
339 _UIntType __a,
size_t __u, _UIntType __d,
size_t __s,
340 _UIntType __b,
size_t __t, _UIntType __c,
size_t __l,
343 mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
344 __s, __b, __t, __c, __l, __f>::
345 seed(result_type __sd)
347 _M_x[0] = __detail::__mod<_UIntType,
348 __detail::_Shift<_UIntType, __w>::__value>(__sd);
350 for (
size_t __i = 1; __i < state_size; ++__i)
352 _UIntType __x = _M_x[__i - 1];
353 __x ^= __x >> (__w - 2);
355 __x += __detail::__mod<_UIntType, __n>(__i);
356 _M_x[__i] = __detail::__mod<_UIntType,
357 __detail::_Shift<_UIntType, __w>::__value>(__x);
362 template<
typename _UIntType,
363 size_t __w,
size_t __n,
size_t __m,
size_t __r,
364 _UIntType __a,
size_t __u, _UIntType __d,
size_t __s,
365 _UIntType __b,
size_t __t, _UIntType __c,
size_t __l,
367 template<
typename _Sseq>
369 mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
370 __s, __b, __t, __c, __l, __f>::
373 const _UIntType __upper_mask = (~_UIntType()) << __r;
374 const size_t __k = (__w + 31) / 32;
375 uint_least32_t __arr[__n * __k];
376 __q.generate(__arr + 0, __arr + __n * __k);
379 for (
size_t __i = 0; __i < state_size; ++__i)
381 _UIntType __factor = 1u;
382 _UIntType __sum = 0u;
383 for (
size_t __j = 0; __j < __k; ++__j)
385 __sum += __arr[__k * __i + __j] * __factor;
386 __factor *= __detail::_Shift<_UIntType, 32>::__value;
388 _M_x[__i] = __detail::__mod<_UIntType,
389 __detail::_Shift<_UIntType, __w>::__value>(__sum);
395 if ((_M_x[0] & __upper_mask) != 0u)
398 else if (_M_x[__i] != 0u)
403 _M_x[0] = __detail::_Shift<_UIntType, __w - 1>::__value;
406 template<
typename _UIntType,
size_t __w,
407 size_t __n,
size_t __m,
size_t __r,
408 _UIntType __a,
size_t __u, _UIntType __d,
size_t __s,
409 _UIntType __b,
size_t __t, _UIntType __c,
size_t __l,
412 mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
413 __s, __b, __t, __c, __l, __f>::result_type
414 mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
415 __s, __b, __t, __c, __l, __f>::
419 if (_M_p >= state_size)
421 const _UIntType __upper_mask = (~_UIntType()) << __r;
422 const _UIntType __lower_mask = ~__upper_mask;
424 for (
size_t __k = 0; __k < (__n - __m); ++__k)
426 _UIntType __y = ((_M_x[__k] & __upper_mask)
427 | (_M_x[__k + 1] & __lower_mask));
428 _M_x[__k] = (_M_x[__k + __m] ^ (__y >> 1)
429 ^ ((__y & 0x01) ? __a : 0));
432 for (
size_t __k = (__n - __m); __k < (__n - 1); ++__k)
434 _UIntType __y = ((_M_x[__k] & __upper_mask)
435 | (_M_x[__k + 1] & __lower_mask));
436 _M_x[__k] = (_M_x[__k + (__m - __n)] ^ (__y >> 1)
437 ^ ((__y & 0x01) ? __a : 0));
440 _UIntType __y = ((_M_x[__n - 1] & __upper_mask)
441 | (_M_x[0] & __lower_mask));
442 _M_x[__n - 1] = (_M_x[__m - 1] ^ (__y >> 1)
443 ^ ((__y & 0x01) ? __a : 0));
448 result_type __z = _M_x[_M_p++];
449 __z ^= (__z >> __u) & __d;
450 __z ^= (__z << __s) & __b;
451 __z ^= (__z << __t) & __c;
457 template<
typename _UIntType,
size_t __w,
458 size_t __n,
size_t __m,
size_t __r,
459 _UIntType __a,
size_t __u, _UIntType __d,
size_t __s,
460 _UIntType __b,
size_t __t, _UIntType __c,
size_t __l,
461 _UIntType __f,
typename _CharT,
typename _Traits>
463 operator<<(std::basic_ostream<_CharT, _Traits>& __os,
464 const mersenne_twister_engine<_UIntType, __w, __n, __m,
465 __r, __a, __u, __d, __s, __b, __t, __c, __l, __f>& __x)
468 typedef typename __ostream_type::ios_base __ios_base;
470 const typename __ios_base::fmtflags __flags = __os.
flags();
471 const _CharT __fill = __os.fill();
472 const _CharT __space = __os.widen(
' ');
476 for (
size_t __i = 0; __i < __n; ++__i)
477 __os << __x._M_x[__i] << __space;
485 template<
typename _UIntType,
size_t __w,
486 size_t __n,
size_t __m,
size_t __r,
487 _UIntType __a,
size_t __u, _UIntType __d,
size_t __s,
488 _UIntType __b,
size_t __t, _UIntType __c,
size_t __l,
489 _UIntType __f,
typename _CharT,
typename _Traits>
492 mersenne_twister_engine<_UIntType, __w, __n, __m,
493 __r, __a, __u, __d, __s, __b, __t, __c, __l, __f>& __x)
496 typedef typename __istream_type::ios_base __ios_base;
498 const typename __ios_base::fmtflags __flags = __is.
flags();
501 for (
size_t __i = 0; __i < __n; ++__i)
502 __is >> __x._M_x[__i];
510 template<
typename _UIntType,
size_t __w,
size_t __s,
size_t __r>
512 subtract_with_carry_engine<_UIntType, __w, __s, __r>::word_size;
514 template<
typename _UIntType,
size_t __w,
size_t __s,
size_t __r>
516 subtract_with_carry_engine<_UIntType, __w, __s, __r>::short_lag;
518 template<
typename _UIntType,
size_t __w,
size_t __s,
size_t __r>
520 subtract_with_carry_engine<_UIntType, __w, __s, __r>::long_lag;
522 template<
typename _UIntType,
size_t __w,
size_t __s,
size_t __r>
524 subtract_with_carry_engine<_UIntType, __w, __s, __r>::default_seed;
526 template<
typename _UIntType,
size_t __w,
size_t __s,
size_t __r>
528 subtract_with_carry_engine<_UIntType, __w, __s, __r>::
529 seed(result_type __value)
532 __lcg(__value == 0u ? default_seed : __value);
534 const size_t __n = (__w + 31) / 32;
536 for (
size_t __i = 0; __i < long_lag; ++__i)
538 _UIntType __sum = 0u;
539 _UIntType __factor = 1u;
540 for (
size_t __j = 0; __j < __n; ++__j)
542 __sum += __detail::__mod<uint_least32_t,
543 __detail::_Shift<uint_least32_t, 32>::__value>
544 (__lcg()) * __factor;
545 __factor *= __detail::_Shift<_UIntType, 32>::__value;
547 _M_x[__i] = __detail::__mod<_UIntType,
548 __detail::_Shift<_UIntType, __w>::__value>(__sum);
550 _M_carry = (_M_x[long_lag - 1] == 0) ? 1 : 0;
554 template<
typename _UIntType,
size_t __w,
size_t __s,
size_t __r>
555 template<
typename _Sseq>
557 subtract_with_carry_engine<_UIntType, __w, __s, __r>::
560 const size_t __k = (__w + 31) / 32;
561 uint_least32_t __arr[__r * __k];
562 __q.generate(__arr + 0, __arr + __r * __k);
564 for (
size_t __i = 0; __i < long_lag; ++__i)
566 _UIntType __sum = 0u;
567 _UIntType __factor = 1u;
568 for (
size_t __j = 0; __j < __k; ++__j)
570 __sum += __arr[__k * __i + __j] * __factor;
571 __factor *= __detail::_Shift<_UIntType, 32>::__value;
573 _M_x[__i] = __detail::__mod<_UIntType,
574 __detail::_Shift<_UIntType, __w>::__value>(__sum);
576 _M_carry = (_M_x[long_lag - 1] == 0) ? 1 : 0;
580 template<
typename _UIntType,
size_t __w,
size_t __s,
size_t __r>
581 typename subtract_with_carry_engine<_UIntType, __w, __s, __r>::
583 subtract_with_carry_engine<_UIntType, __w, __s, __r>::
587 long __ps = _M_p - short_lag;
595 if (_M_x[__ps] >= _M_x[_M_p] + _M_carry)
597 __xi = _M_x[__ps] - _M_x[_M_p] - _M_carry;
602 __xi = (__detail::_Shift<_UIntType, __w>::__value
603 - _M_x[_M_p] - _M_carry + _M_x[__ps]);
609 if (++_M_p >= long_lag)
615 template<
typename _UIntType,
size_t __w,
size_t __s,
size_t __r,
616 typename _CharT,
typename _Traits>
618 operator<<(std::basic_ostream<_CharT, _Traits>& __os,
619 const subtract_with_carry_engine<_UIntType,
623 typedef typename __ostream_type::ios_base __ios_base;
625 const typename __ios_base::fmtflags __flags = __os.
flags();
626 const _CharT __fill = __os.fill();
627 const _CharT __space = __os.widen(
' ');
631 for (
size_t __i = 0; __i < __r; ++__i)
632 __os << __x._M_x[__i] << __space;
633 __os << __x._M_carry << __space << __x._M_p;
640 template<
typename _UIntType,
size_t __w,
size_t __s,
size_t __r,
641 typename _CharT,
typename _Traits>
644 subtract_with_carry_engine<_UIntType, __w, __s, __r>& __x)
647 typedef typename __istream_type::ios_base __ios_base;
649 const typename __ios_base::fmtflags __flags = __is.
flags();
652 for (
size_t __i = 0; __i < __r; ++__i)
653 __is >> __x._M_x[__i];
654 __is >> __x._M_carry;
662 template<
typename _RandomNumberEngine,
size_t __p,
size_t __r>
664 discard_block_engine<_RandomNumberEngine, __p, __r>::block_size;
666 template<
typename _RandomNumberEngine,
size_t __p,
size_t __r>
668 discard_block_engine<_RandomNumberEngine, __p, __r>::used_block;
670 template<
typename _RandomNumberEngine,
size_t __p,
size_t __r>
671 typename discard_block_engine<_RandomNumberEngine,
672 __p, __r>::result_type
676 if (_M_n >= used_block)
678 _M_b.discard(block_size - _M_n);
685 template<
typename _RandomNumberEngine,
size_t __p,
size_t __r,
686 typename _CharT,
typename _Traits>
688 operator<<(std::basic_ostream<_CharT, _Traits>& __os,
693 typedef typename __ostream_type::ios_base __ios_base;
695 const typename __ios_base::fmtflags __flags = __os.
flags();
696 const _CharT __fill = __os.fill();
697 const _CharT __space = __os.widen(
' ');
701 __os << __x.base() << __space << __x._M_n;
708 template<
typename _RandomNumberEngine,
size_t __p,
size_t __r,
709 typename _CharT,
typename _Traits>
712 discard_block_engine<_RandomNumberEngine, __p, __r>& __x)
715 typedef typename __istream_type::ios_base __ios_base;
717 const typename __ios_base::fmtflags __flags = __is.
flags();
720 __is >> __x._M_b >> __x._M_n;
727 template<
typename _RandomNumberEngine,
size_t __w,
typename _UIntType>
728 typename independent_bits_engine<_RandomNumberEngine, __w, _UIntType>::
733 typedef typename _RandomNumberEngine::result_type _Eresult_type;
734 const _Eresult_type __r
736 ? _M_b.max() - _M_b.min() + 1 : 0);
738 const unsigned __m = __r ?
std::__lg(__r) : __edig;
745 __ctype __s0, __s1, __y0, __y1;
747 for (
size_t __i = 0; __i < 2; ++__i)
749 __n = (__w + __m - 1) / __m + __i;
750 __n0 = __n - __w % __n;
751 const unsigned __w0 = __w / __n;
757 __s0 = __ctype(1) << __w0;
765 __y0 = __s0 * (__r / __s0);
767 __y1 = __s1 * (__r / __s1);
769 if (__r - __y0 <= __y0 / __n)
777 for (
size_t __k = 0; __k < __n0; ++__k)
781 __u = _M_b() - _M_b.
min();
782 while (__y0 && __u >= __y0);
783 __sum = __s0 * __sum + (__s0 ? __u % __s0 : __u);
785 for (
size_t __k = __n0; __k < __n; ++__k)
789 __u = _M_b() - _M_b.min();
790 while (__y1 && __u >= __y1);
791 __sum = __s1 * __sum + (__s1 ? __u % __s1 : __u);
797 template<
typename _RandomNumberEngine,
size_t __k>
801 template<
typename _RandomNumberEngine,
size_t __k>
806 size_t __j = __k * ((_M_y - _M_b.min())
807 / (_M_b.max() - _M_b.min() + 1.0L));
814 template<
typename _RandomNumberEngine,
size_t __k,
815 typename _CharT,
typename _Traits>
817 operator<<(std::basic_ostream<_CharT, _Traits>& __os,
821 typedef typename __ostream_type::ios_base __ios_base;
823 const typename __ios_base::fmtflags __flags = __os.
flags();
824 const _CharT __fill = __os.fill();
825 const _CharT __space = __os.widen(
' ');
830 for (
size_t __i = 0; __i < __k; ++__i)
831 __os << __space << __x._M_v[__i];
832 __os << __space << __x._M_y;
839 template<
typename _RandomNumberEngine,
size_t __k,
840 typename _CharT,
typename _Traits>
843 shuffle_order_engine<_RandomNumberEngine, __k>& __x)
846 typedef typename __istream_type::ios_base __ios_base;
848 const typename __ios_base::fmtflags __flags = __is.
flags();
852 for (
size_t __i = 0; __i < __k; ++__i)
853 __is >> __x._M_v[__i];
861 template<
typename _IntType>
862 template<
typename _UniformRandomNumberGenerator>
863 typename uniform_int_distribution<_IntType>::result_type
865 operator()(_UniformRandomNumberGenerator& __urng,
866 const param_type& __param)
868 typedef typename _UniformRandomNumberGenerator::result_type
870 typedef typename std::make_unsigned<result_type>::type __utype;
874 const __uctype __urngmin = __urng.min();
875 const __uctype __urngmax = __urng.max();
876 const __uctype __urngrange = __urngmax - __urngmin;
877 const __uctype __urange
878 = __uctype(__param.b()) - __uctype(__param.a());
882 if (__urngrange > __urange)
885 const __uctype __uerange = __urange + 1;
886 const __uctype __scaling = __urngrange / __uerange;
887 const __uctype __past = __uerange * __scaling;
889 __ret = __uctype(__urng()) - __urngmin;
890 while (__ret >= __past);
893 else if (__urngrange < __urange)
913 const __uctype __uerngrange = __urngrange + 1;
914 __tmp = (__uerngrange * operator()
915 (__urng, param_type(0, __urange / __uerngrange)));
916 __ret = __tmp + (__uctype(__urng()) - __urngmin);
918 while (__ret > __urange || __ret < __tmp);
921 __ret = __uctype(__urng()) - __urngmin;
923 return __ret + __param.a();
926 template<
typename _IntType,
typename _CharT,
typename _Traits>
928 operator<<(std::basic_ostream<_CharT, _Traits>& __os,
932 typedef typename __ostream_type::ios_base __ios_base;
934 const typename __ios_base::fmtflags __flags = __os.
flags();
935 const _CharT __fill = __os.fill();
936 const _CharT __space = __os.widen(
' ');
940 __os << __x.a() << __space << __x.b();
947 template<
typename _IntType,
typename _CharT,
typename _Traits>
953 typedef typename __istream_type::ios_base __ios_base;
955 const typename __ios_base::fmtflags __flags = __is.
flags();
961 param_type(__a, __b));
968 template<
typename _RealType,
typename _CharT,
typename _Traits>
970 operator<<(std::basic_ostream<_CharT, _Traits>& __os,
974 typedef typename __ostream_type::ios_base __ios_base;
976 const typename __ios_base::fmtflags __flags = __os.
flags();
977 const _CharT __fill = __os.fill();
979 const _CharT __space = __os.widen(
' ');
984 __os << __x.a() << __space << __x.b();
988 __os.precision(__precision);
992 template<
typename _RealType,
typename _CharT,
typename _Traits>
998 typedef typename __istream_type::ios_base __ios_base;
1000 const typename __ios_base::fmtflags __flags = __is.
flags();
1006 param_type(__a, __b));
1008 __is.
flags(__flags);
1013 template<
typename _CharT,
typename _Traits>
1015 operator<<(std::basic_ostream<_CharT, _Traits>& __os,
1019 typedef typename __ostream_type::ios_base __ios_base;
1021 const typename __ios_base::fmtflags __flags = __os.
flags();
1022 const _CharT __fill = __os.fill();
1025 __os.fill(__os.widen(
' '));
1030 __os.flags(__flags);
1032 __os.precision(__precision);
1037 template<
typename _IntType>
1038 template<
typename _UniformRandomNumberGenerator>
1039 typename geometric_distribution<_IntType>::result_type
1041 operator()(_UniformRandomNumberGenerator& __urng,
1042 const param_type& __param)
1046 const double __naf =
1049 const double __thr =
1051 __detail::_Adaptor<_UniformRandomNumberGenerator, double>
1056 __cand = std::floor(
std::log(__aurng()) / __param._M_log_1_p);
1057 while (__cand >= __thr);
1059 return result_type(__cand + __naf);
1062 template<
typename _IntType,
1063 typename _CharT,
typename _Traits>
1065 operator<<(std::basic_ostream<_CharT, _Traits>& __os,
1069 typedef typename __ostream_type::ios_base __ios_base;
1071 const typename __ios_base::fmtflags __flags = __os.
flags();
1072 const _CharT __fill = __os.fill();
1075 __os.fill(__os.widen(
' '));
1080 __os.flags(__flags);
1082 __os.precision(__precision);
1086 template<
typename _IntType,
1087 typename _CharT,
typename _Traits>
1093 typedef typename __istream_type::ios_base __ios_base;
1095 const typename __ios_base::fmtflags __flags = __is.
flags();
1102 __is.
flags(__flags);
1107 template<
typename _IntType>
1108 template<
typename _UniformRandomNumberGenerator>
1109 typename negative_binomial_distribution<_IntType>::result_type
1111 operator()(_UniformRandomNumberGenerator& __urng)
1113 const double __y = _M_gd(__urng);
1117 return __poisson(__urng);
1120 template<
typename _IntType>
1121 template<
typename _UniformRandomNumberGenerator>
1122 typename negative_binomial_distribution<_IntType>::result_type
1124 operator()(_UniformRandomNumberGenerator& __urng,
1125 const param_type& __p)
1131 _M_gd(__urng, param_type(__p.k(), (1.0 - __p.p()) / __p.p()));
1134 return __poisson(__urng);
1137 template<
typename _IntType,
typename _CharT,
typename _Traits>
1139 operator<<(std::basic_ostream<_CharT, _Traits>& __os,
1140 const negative_binomial_distribution<_IntType>& __x)
1143 typedef typename __ostream_type::ios_base __ios_base;
1145 const typename __ios_base::fmtflags __flags = __os.
flags();
1146 const _CharT __fill = __os.fill();
1148 const _CharT __space = __os.widen(
' ');
1150 __os.fill(__os.widen(
' '));
1153 __os << __x.k() << __space << __x.p()
1154 << __space << __x._M_gd;
1156 __os.flags(__flags);
1158 __os.precision(__precision);
1162 template<
typename _IntType,
typename _CharT,
typename _Traits>
1165 negative_binomial_distribution<_IntType>& __x)
1168 typedef typename __istream_type::ios_base __ios_base;
1170 const typename __ios_base::fmtflags __flags = __is.
flags();
1175 __is >> __k >> __p >> __x._M_gd;
1176 __x.param(
typename negative_binomial_distribution<_IntType>::
1177 param_type(__k, __p));
1179 __is.
flags(__flags);
1184 template<
typename _IntType>
1186 poisson_distribution<_IntType>::param_type::
1189 #if _GLIBCXX_USE_C99_MATH_TR1
1192 const double __m = std::floor(_M_mean);
1194 _M_lfm = std::lgamma(__m + 1);
1197 const double __pi_4 = 0.7853981633974483096156608458198757L;
1201 const double __cx = 2 * __m + _M_d;
1206 _M_cb = 2 * __cx *
std::exp(-_M_d * _M_1cx * (1 + _M_d / 2))
1224 template<
typename _IntType>
1225 template<
typename _UniformRandomNumberGenerator>
1226 typename poisson_distribution<_IntType>::result_type
1229 const param_type& __param)
1231 __detail::_Adaptor<_UniformRandomNumberGenerator, double>
1233 #if _GLIBCXX_USE_C99_MATH_TR1
1234 if (__param.mean() >= 12)
1239 const double __naf =
1241 const double __thr =
1244 const double __m = std::floor(__param.mean());
1246 const double __spi_2 = 1.2533141373155002512078826424055226L;
1247 const double __c1 = __param._M_sm * __spi_2;
1248 const double __c2 = __param._M_c2b + __c1;
1249 const double __c3 = __c2 + 1;
1250 const double __c4 = __c3 + 1;
1252 const double __e178 = 1.0129030479320018583185514777512983L;
1253 const double __c5 = __c4 + __e178;
1254 const double __c = __param._M_cb + __c5;
1255 const double __2cx = 2 * (2 * __m + __param._M_d);
1257 bool __reject =
true;
1260 const double __u = __c * __aurng();
1261 const double __e = -
std::log(__aurng());
1267 const double __n = _M_nd(__urng);
1268 const double __y = -
std::abs(__n) * __param._M_sm - 1;
1269 __x = std::floor(__y);
1270 __w = -__n * __n / 2;
1274 else if (__u <= __c2)
1276 const double __n = _M_nd(__urng);
1277 const double __y = 1 +
std::abs(__n) * __param._M_scx;
1278 __x = std::ceil(__y);
1279 __w = __y * (2 - __y) * __param._M_1cx;
1280 if (__x > __param._M_d)
1283 else if (__u <= __c3)
1287 else if (__u <= __c4)
1289 else if (__u <= __c5)
1293 const double __v = -
std::log(__aurng());
1294 const double __y = __param._M_d
1295 + __v * __2cx / __param._M_d;
1296 __x = std::ceil(__y);
1297 __w = -__param._M_d * __param._M_1cx * (1 + __y / 2);
1300 __reject = (__w - __e - __x * __param._M_lm_thr
1301 > __param._M_lfm - std::lgamma(__x + __m + 1));
1303 __reject |= __x + __m >= __thr;
1313 double __prod = 1.0;
1317 __prod *= __aurng();
1320 while (__prod > __param._M_lm_thr);
1326 template<
typename _IntType,
1327 typename _CharT,
typename _Traits>
1329 operator<<(std::basic_ostream<_CharT, _Traits>& __os,
1333 typedef typename __ostream_type::ios_base __ios_base;
1335 const typename __ios_base::fmtflags __flags = __os.
flags();
1336 const _CharT __fill = __os.fill();
1338 const _CharT __space = __os.widen(
' ');
1343 __os << __x.mean() << __space << __x._M_nd;
1345 __os.flags(__flags);
1347 __os.precision(__precision);
1351 template<
typename _IntType,
1352 typename _CharT,
typename _Traits>
1355 poisson_distribution<_IntType>& __x)
1358 typedef typename __istream_type::ios_base __ios_base;
1360 const typename __ios_base::fmtflags __flags = __is.
flags();
1364 __is >> __mean >> __x._M_nd;
1365 __x.param(
typename poisson_distribution<_IntType>::param_type(__mean));
1367 __is.
flags(__flags);
1372 template<
typename _IntType>
1374 binomial_distribution<_IntType>::param_type::
1377 const double __p12 = _M_p <= 0.5 ? _M_p : 1.0 - _M_p;
1381 #if _GLIBCXX_USE_C99_MATH_TR1
1382 if (_M_t * __p12 >= 8)
1385 const double __np = std::floor(_M_t * __p12);
1386 const double __pa = __np / _M_t;
1387 const double __1p = 1 - __pa;
1389 const double __pi_4 = 0.7853981633974483096156608458198757L;
1390 const double __d1x =
1392 / (81 * __pi_4 * __1p)));
1393 _M_d1 = std::round(
std::max(1.0, __d1x));
1394 const double __d2x =
1396 / (__pi_4 * __pa)));
1397 _M_d2 = std::round(
std::max(1.0, __d2x));
1400 const double __spi_2 = 1.2533141373155002512078826424055226L;
1401 _M_s1 =
std::sqrt(__np * __1p) * (1 + _M_d1 / (4 * __np));
1402 _M_s2 =
std::sqrt(__np * __1p) * (1 + _M_d2 / (4 * _M_t * __1p));
1403 _M_c = 2 * _M_d1 / __np;
1404 _M_a1 =
std::exp(_M_c) * _M_s1 * __spi_2;
1405 const double __a12 = _M_a1 + _M_s2 * __spi_2;
1406 const double __s1s = _M_s1 * _M_s1;
1407 _M_a123 = __a12 + (
std::exp(_M_d1 / (_M_t * __1p))
1409 *
std::exp(-_M_d1 * _M_d1 / (2 * __s1s)));
1410 const double __s2s = _M_s2 * _M_s2;
1411 _M_s = (_M_a123 + 2 * __s2s / _M_d2
1412 *
std::exp(-_M_d2 * _M_d2 / (2 * __s2s)));
1413 _M_lf = (std::lgamma(__np + 1)
1414 + std::lgamma(_M_t - __np + 1));
1417 _M_q = -
std::log(1 - (__p12 - __pa) / __1p);
1424 template<
typename _IntType>
1425 template<
typename _UniformRandomNumberGenerator>
1426 typename binomial_distribution<_IntType>::result_type
1427 binomial_distribution<_IntType>::
1428 _M_waiting(_UniformRandomNumberGenerator& __urng, _IntType __t)
1432 __detail::_Adaptor<_UniformRandomNumberGenerator, double>
1437 const double __e = -
std::log(__aurng());
1438 __sum += __e / (__t - __x);
1441 while (__sum <= _M_param._M_q);
1456 template<
typename _IntType>
1457 template<
typename _UniformRandomNumberGenerator>
1458 typename binomial_distribution<_IntType>::result_type
1461 const param_type& __param)
1464 const _IntType __t = __param.t();
1465 const double __p = __param.p();
1466 const double __p12 = __p <= 0.5 ? __p : 1.0 - __p;
1467 __detail::_Adaptor<_UniformRandomNumberGenerator, double>
1470 #if _GLIBCXX_USE_C99_MATH_TR1
1471 if (!__param._M_easy)
1476 const double __naf =
1478 const double __thr =
1481 const double __np = std::floor(__t * __p12);
1484 const double __spi_2 = 1.2533141373155002512078826424055226L;
1485 const double __a1 = __param._M_a1;
1486 const double __a12 = __a1 + __param._M_s2 * __spi_2;
1487 const double __a123 = __param._M_a123;
1488 const double __s1s = __param._M_s1 * __param._M_s1;
1489 const double __s2s = __param._M_s2 * __param._M_s2;
1494 const double __u = __param._M_s * __aurng();
1500 const double __n = _M_nd(__urng);
1501 const double __y = __param._M_s1 *
std::abs(__n);
1502 __reject = __y >= __param._M_d1;
1505 const double __e = -
std::log(__aurng());
1506 __x = std::floor(__y);
1507 __v = -__e - __n * __n / 2 + __param._M_c;
1510 else if (__u <= __a12)
1512 const double __n = _M_nd(__urng);
1513 const double __y = __param._M_s2 *
std::abs(__n);
1514 __reject = __y >= __param._M_d2;
1517 const double __e = -
std::log(__aurng());
1518 __x = std::floor(-__y);
1519 __v = -__e - __n * __n / 2;
1522 else if (__u <= __a123)
1524 const double __e1 = -
std::log(__aurng());
1525 const double __e2 = -
std::log(__aurng());
1527 const double __y = __param._M_d1
1528 + 2 * __s1s * __e1 / __param._M_d1;
1529 __x = std::floor(__y);
1530 __v = (-__e2 + __param._M_d1 * (1 / (__t - __np)
1531 -__y / (2 * __s1s)));
1536 const double __e1 = -
std::log(__aurng());
1537 const double __e2 = -
std::log(__aurng());
1539 const double __y = __param._M_d2
1540 + 2 * __s2s * __e1 / __param._M_d2;
1541 __x = std::floor(-__y);
1542 __v = -__e2 - __param._M_d2 * __y / (2 * __s2s);
1546 __reject = __reject || __x < -__np || __x > __t - __np;
1549 const double __lfx =
1550 std::lgamma(__np + __x + 1)
1551 + std::lgamma(__t - (__np + __x) + 1);
1552 __reject = __v > __param._M_lf - __lfx
1553 + __x * __param._M_lp1p;
1556 __reject |= __x + __np >= __thr;
1560 __x += __np + __naf;
1562 const _IntType __z = _M_waiting(__urng, __t - _IntType(__x));
1563 __ret = _IntType(__x) + __z;
1567 __ret = _M_waiting(__urng, __t);
1570 __ret = __t - __ret;
1574 template<
typename _IntType,
1575 typename _CharT,
typename _Traits>
1577 operator<<(std::basic_ostream<_CharT, _Traits>& __os,
1581 typedef typename __ostream_type::ios_base __ios_base;
1583 const typename __ios_base::fmtflags __flags = __os.
flags();
1584 const _CharT __fill = __os.fill();
1586 const _CharT __space = __os.widen(
' ');
1591 __os << __x.t() << __space << __x.p()
1592 << __space << __x._M_nd;
1594 __os.flags(__flags);
1596 __os.precision(__precision);
1600 template<
typename _IntType,
1601 typename _CharT,
typename _Traits>
1604 binomial_distribution<_IntType>& __x)
1607 typedef typename __istream_type::ios_base __ios_base;
1609 const typename __ios_base::fmtflags __flags = __is.
flags();
1614 __is >> __t >> __p >> __x._M_nd;
1615 __x.param(
typename binomial_distribution<_IntType>::
1616 param_type(__t, __p));
1618 __is.
flags(__flags);
1623 template<
typename _RealType,
typename _CharT,
typename _Traits>
1625 operator<<(std::basic_ostream<_CharT, _Traits>& __os,
1629 typedef typename __ostream_type::ios_base __ios_base;
1631 const typename __ios_base::fmtflags __flags = __os.
flags();
1632 const _CharT __fill = __os.fill();
1635 __os.fill(__os.widen(
' '));
1638 __os << __x.lambda();
1640 __os.flags(__flags);
1642 __os.precision(__precision);
1646 template<
typename _RealType,
typename _CharT,
typename _Traits>
1652 typedef typename __istream_type::ios_base __ios_base;
1654 const typename __ios_base::fmtflags __flags = __is.
flags();
1660 param_type(__lambda));
1662 __is.
flags(__flags);
1673 template<
typename _RealType>
1674 template<
typename _UniformRandomNumberGenerator>
1675 typename normal_distribution<_RealType>::result_type
1678 const param_type& __param)
1681 __detail::_Adaptor<_UniformRandomNumberGenerator, result_type>
1684 if (_M_saved_available)
1686 _M_saved_available =
false;
1696 __r2 = __x * __x + __y * __y;
1698 while (__r2 > 1.0 || __r2 == 0.0);
1701 _M_saved = __x * __mult;
1702 _M_saved_available =
true;
1703 __ret = __y * __mult;
1706 __ret = __ret * __param.stddev() + __param.mean();
1710 template<
typename _RealType>
1715 if (__d1._M_param == __d2._M_param
1716 && __d1._M_saved_available == __d2._M_saved_available)
1718 if (__d1._M_saved_available
1719 && __d1._M_saved == __d2._M_saved)
1721 else if(!__d1._M_saved_available)
1730 template<
typename _RealType,
typename _CharT,
typename _Traits>
1732 operator<<(std::basic_ostream<_CharT, _Traits>& __os,
1733 const normal_distribution<_RealType>& __x)
1736 typedef typename __ostream_type::ios_base __ios_base;
1738 const typename __ios_base::fmtflags __flags = __os.
flags();
1739 const _CharT __fill = __os.fill();
1741 const _CharT __space = __os.widen(
' ');
1746 __os << __x.mean() << __space << __x.stddev()
1747 << __space << __x._M_saved_available;
1748 if (__x._M_saved_available)
1749 __os << __space << __x._M_saved;
1751 __os.flags(__flags);
1753 __os.precision(__precision);
1757 template<
typename _RealType,
typename _CharT,
typename _Traits>
1760 normal_distribution<_RealType>& __x)
1763 typedef typename __istream_type::ios_base __ios_base;
1765 const typename __ios_base::fmtflags __flags = __is.
flags();
1768 double __mean, __stddev;
1769 __is >> __mean >> __stddev
1770 >> __x._M_saved_available;
1771 if (__x._M_saved_available)
1772 __is >> __x._M_saved;
1773 __x.param(
typename normal_distribution<_RealType>::
1774 param_type(__mean, __stddev));
1776 __is.
flags(__flags);
1781 template<
typename _RealType,
typename _CharT,
typename _Traits>
1783 operator<<(std::basic_ostream<_CharT, _Traits>& __os,
1784 const lognormal_distribution<_RealType>& __x)
1787 typedef typename __ostream_type::ios_base __ios_base;
1789 const typename __ios_base::fmtflags __flags = __os.
flags();
1790 const _CharT __fill = __os.fill();
1792 const _CharT __space = __os.widen(
' ');
1797 __os << __x.m() << __space << __x.s()
1798 << __space << __x._M_nd;
1800 __os.flags(__flags);
1802 __os.precision(__precision);
1806 template<
typename _RealType,
typename _CharT,
typename _Traits>
1809 lognormal_distribution<_RealType>& __x)
1812 typedef typename __istream_type::ios_base __ios_base;
1814 const typename __ios_base::fmtflags __flags = __is.
flags();
1818 __is >> __m >> __s >> __x._M_nd;
1819 __x.param(
typename lognormal_distribution<_RealType>::
1820 param_type(__m, __s));
1822 __is.
flags(__flags);
1827 template<
typename _RealType,
typename _CharT,
typename _Traits>
1829 operator<<(std::basic_ostream<_CharT, _Traits>& __os,
1830 const chi_squared_distribution<_RealType>& __x)
1833 typedef typename __ostream_type::ios_base __ios_base;
1835 const typename __ios_base::fmtflags __flags = __os.
flags();
1836 const _CharT __fill = __os.fill();
1838 const _CharT __space = __os.widen(
' ');
1843 __os << __x.n() << __space << __x._M_gd;
1845 __os.flags(__flags);
1847 __os.precision(__precision);
1851 template<
typename _RealType,
typename _CharT,
typename _Traits>
1854 chi_squared_distribution<_RealType>& __x)
1857 typedef typename __istream_type::ios_base __ios_base;
1859 const typename __ios_base::fmtflags __flags = __is.
flags();
1863 __is >> __n >> __x._M_gd;
1864 __x.param(
typename chi_squared_distribution<_RealType>::
1867 __is.
flags(__flags);
1872 template<
typename _RealType>
1873 template<
typename _UniformRandomNumberGenerator>
1874 typename cauchy_distribution<_RealType>::result_type
1876 operator()(_UniformRandomNumberGenerator& __urng,
1877 const param_type& __p)
1879 __detail::_Adaptor<_UniformRandomNumberGenerator, result_type>
1886 const _RealType __pi = 3.1415926535897932384626433832795029L;
1887 return __p.a() + __p.b() *
std::tan(__pi * __u);
1890 template<
typename _RealType,
typename _CharT,
typename _Traits>
1892 operator<<(std::basic_ostream<_CharT, _Traits>& __os,
1896 typedef typename __ostream_type::ios_base __ios_base;
1898 const typename __ios_base::fmtflags __flags = __os.
flags();
1899 const _CharT __fill = __os.fill();
1901 const _CharT __space = __os.widen(
' ');
1906 __os << __x.a() << __space << __x.b();
1908 __os.flags(__flags);
1910 __os.precision(__precision);
1914 template<
typename _RealType,
typename _CharT,
typename _Traits>
1920 typedef typename __istream_type::ios_base __ios_base;
1922 const typename __ios_base::fmtflags __flags = __is.
flags();
1928 param_type(__a, __b));
1930 __is.
flags(__flags);
1935 template<
typename _RealType,
typename _CharT,
typename _Traits>
1937 operator<<(std::basic_ostream<_CharT, _Traits>& __os,
1938 const fisher_f_distribution<_RealType>& __x)
1941 typedef typename __ostream_type::ios_base __ios_base;
1943 const typename __ios_base::fmtflags __flags = __os.
flags();
1944 const _CharT __fill = __os.fill();
1946 const _CharT __space = __os.widen(
' ');
1951 __os << __x.m() << __space << __x.n()
1952 << __space << __x._M_gd_x << __space << __x._M_gd_y;
1954 __os.flags(__flags);
1956 __os.precision(__precision);
1960 template<
typename _RealType,
typename _CharT,
typename _Traits>
1963 fisher_f_distribution<_RealType>& __x)
1966 typedef typename __istream_type::ios_base __ios_base;
1968 const typename __ios_base::fmtflags __flags = __is.
flags();
1972 __is >> __m >> __n >> __x._M_gd_x >> __x._M_gd_y;
1973 __x.param(
typename fisher_f_distribution<_RealType>::
1974 param_type(__m, __n));
1976 __is.
flags(__flags);
1981 template<
typename _RealType,
typename _CharT,
typename _Traits>
1983 operator<<(std::basic_ostream<_CharT, _Traits>& __os,
1984 const student_t_distribution<_RealType>& __x)
1987 typedef typename __ostream_type::ios_base __ios_base;
1989 const typename __ios_base::fmtflags __flags = __os.
flags();
1990 const _CharT __fill = __os.fill();
1992 const _CharT __space = __os.widen(
' ');
1997 __os << __x.n() << __space << __x._M_nd << __space << __x._M_gd;
1999 __os.flags(__flags);
2001 __os.precision(__precision);
2005 template<
typename _RealType,
typename _CharT,
typename _Traits>
2008 student_t_distribution<_RealType>& __x)
2011 typedef typename __istream_type::ios_base __ios_base;
2013 const typename __ios_base::fmtflags __flags = __is.
flags();
2017 __is >> __n >> __x._M_nd >> __x._M_gd;
2018 __x.param(
typename student_t_distribution<_RealType>::param_type(__n));
2020 __is.
flags(__flags);
2025 template<
typename _RealType>
2027 gamma_distribution<_RealType>::param_type::
2030 _M_malpha = _M_alpha < 1.0 ? _M_alpha + _RealType(1.0) : _M_alpha;
2032 const _RealType __a1 = _M_malpha - _RealType(1.0) / _RealType(3.0);
2033 _M_a2 = _RealType(1.0) /
std::sqrt(_RealType(9.0) * __a1);
2041 template<
typename _RealType>
2042 template<
typename _UniformRandomNumberGenerator>
2043 typename gamma_distribution<_RealType>::result_type
2046 const param_type& __param)
2048 __detail::_Adaptor<_UniformRandomNumberGenerator, result_type>
2053 - _RealType(1.0) / _RealType(3.0));
2059 __n = _M_nd(__urng);
2064 __v = __v * __v * __v;
2067 while (__u >
result_type(1.0) - 0.331 * __n * __n * __n * __n
2068 && (
std::log(__u) > (0.5 * __n * __n + __a1
2071 if (__param.alpha() == __param._M_malpha)
2072 return __a1 * __v * __param.beta();
2080 * __a1 * __v * __param.beta());
2084 template<
typename _RealType,
typename _CharT,
typename _Traits>
2086 operator<<(std::basic_ostream<_CharT, _Traits>& __os,
2090 typedef typename __ostream_type::ios_base __ios_base;
2092 const typename __ios_base::fmtflags __flags = __os.
flags();
2093 const _CharT __fill = __os.fill();
2095 const _CharT __space = __os.widen(
' ');
2100 __os << __x.alpha() << __space << __x.beta()
2101 << __space << __x._M_nd;
2103 __os.flags(__flags);
2105 __os.precision(__precision);
2109 template<
typename _RealType,
typename _CharT,
typename _Traits>
2112 gamma_distribution<_RealType>& __x)
2115 typedef typename __istream_type::ios_base __ios_base;
2117 const typename __ios_base::fmtflags __flags = __is.
flags();
2120 _RealType __alpha_val, __beta_val;
2121 __is >> __alpha_val >> __beta_val >> __x._M_nd;
2122 __x.param(
typename gamma_distribution<_RealType>::
2123 param_type(__alpha_val, __beta_val));
2125 __is.
flags(__flags);
2130 template<
typename _RealType>
2131 template<
typename _UniformRandomNumberGenerator>
2132 typename weibull_distribution<_RealType>::result_type
2134 operator()(_UniformRandomNumberGenerator& __urng,
2135 const param_type& __p)
2137 __detail::_Adaptor<_UniformRandomNumberGenerator, result_type>
2143 template<
typename _RealType,
typename _CharT,
typename _Traits>
2145 operator<<(std::basic_ostream<_CharT, _Traits>& __os,
2149 typedef typename __ostream_type::ios_base __ios_base;
2151 const typename __ios_base::fmtflags __flags = __os.
flags();
2152 const _CharT __fill = __os.fill();
2154 const _CharT __space = __os.widen(
' ');
2159 __os << __x.a() << __space << __x.b();
2161 __os.flags(__flags);
2163 __os.precision(__precision);
2167 template<
typename _RealType,
typename _CharT,
typename _Traits>
2173 typedef typename __istream_type::ios_base __ios_base;
2175 const typename __ios_base::fmtflags __flags = __is.
flags();
2181 param_type(__a, __b));
2183 __is.
flags(__flags);
2188 template<
typename _RealType>
2189 template<
typename _UniformRandomNumberGenerator>
2190 typename extreme_value_distribution<_RealType>::result_type
2192 operator()(_UniformRandomNumberGenerator& __urng,
2193 const param_type& __p)
2195 __detail::_Adaptor<_UniformRandomNumberGenerator, result_type>
2200 template<
typename _RealType,
typename _CharT,
typename _Traits>
2202 operator<<(std::basic_ostream<_CharT, _Traits>& __os,
2206 typedef typename __ostream_type::ios_base __ios_base;
2208 const typename __ios_base::fmtflags __flags = __os.
flags();
2209 const _CharT __fill = __os.fill();
2211 const _CharT __space = __os.widen(
' ');
2216 __os << __x.a() << __space << __x.b();
2218 __os.flags(__flags);
2220 __os.precision(__precision);
2224 template<
typename _RealType,
typename _CharT,
typename _Traits>
2230 typedef typename __istream_type::ios_base __ios_base;
2232 const typename __ios_base::fmtflags __flags = __is.
flags();
2238 param_type(__a, __b));
2240 __is.
flags(__flags);
2245 template<
typename _IntType>
2247 discrete_distribution<_IntType>::param_type::
2250 if (_M_prob.size() < 2)
2257 _M_prob.end(), 0.0);
2259 __detail::__transform(_M_prob.begin(), _M_prob.end(), _M_prob.begin(),
2262 _M_cp.reserve(_M_prob.size());
2266 _M_cp[_M_cp.size() - 1] = 1.0;
2269 template<
typename _IntType>
2270 template<
typename _Func>
2271 discrete_distribution<_IntType>::param_type::
2272 param_type(
size_t __nw,
double __xmin,
double __xmax, _Func __fw)
2273 : _M_prob(), _M_cp()
2275 const size_t __n = __nw == 0 ? 1 : __nw;
2276 const double __delta = (__xmax - __xmin) / __n;
2278 _M_prob.reserve(__n);
2279 for (
size_t __k = 0; __k < __nw; ++__k)
2280 _M_prob.push_back(__fw(__xmin + __k * __delta + 0.5 * __delta));
2285 template<
typename _IntType>
2286 template<
typename _UniformRandomNumberGenerator>
2287 typename discrete_distribution<_IntType>::result_type
2288 discrete_distribution<_IntType>::
2289 operator()(_UniformRandomNumberGenerator& __urng,
2290 const param_type& __param)
2292 if (__param._M_cp.empty())
2293 return result_type(0);
2295 __detail::_Adaptor<_UniformRandomNumberGenerator, double>
2298 const double __p = __aurng();
2300 __param._M_cp.end(), __p);
2302 return __pos - __param._M_cp.begin();
2305 template<
typename _IntType,
typename _CharT,
typename _Traits>
2307 operator<<(std::basic_ostream<_CharT, _Traits>& __os,
2308 const discrete_distribution<_IntType>& __x)
2311 typedef typename __ostream_type::ios_base __ios_base;
2313 const typename __ios_base::fmtflags __flags = __os.
flags();
2314 const _CharT __fill = __os.fill();
2316 const _CharT __space = __os.widen(
' ');
2322 __os << __prob.
size();
2323 for (
auto __dit = __prob.
begin(); __dit != __prob.
end(); ++__dit)
2324 __os << __space << *__dit;
2326 __os.flags(__flags);
2328 __os.precision(__precision);
2332 template<
typename _IntType,
typename _CharT,
typename _Traits>
2335 discrete_distribution<_IntType>& __x)
2338 typedef typename __istream_type::ios_base __ios_base;
2340 const typename __ios_base::fmtflags __flags = __is.
flags();
2348 for (; __n != 0; --__n)
2355 __x.param(
typename discrete_distribution<_IntType>::
2356 param_type(__prob_vec.
begin(), __prob_vec.
end()));
2358 __is.
flags(__flags);
2363 template<
typename _RealType>
2365 piecewise_constant_distribution<_RealType>::param_type::
2368 if (_M_int.size() < 2
2369 || (_M_int.size() == 2
2370 && _M_int[0] == _RealType(0)
2371 && _M_int[1] == _RealType(1)))
2381 __detail::__transform(_M_den.begin(), _M_den.end(), _M_den.begin(),
2384 _M_cp.reserve(_M_den.size());
2389 _M_cp[_M_cp.size() - 1] = 1.0;
2391 for (
size_t __k = 0; __k < _M_den.size(); ++__k)
2392 _M_den[__k] /= _M_int[__k + 1] - _M_int[__k];
2395 template<
typename _RealType>
2396 template<
typename _InputIteratorB,
typename _InputIteratorW>
2397 piecewise_constant_distribution<_RealType>::param_type::
2398 param_type(_InputIteratorB __bbegin,
2399 _InputIteratorB __bend,
2400 _InputIteratorW __wbegin)
2401 : _M_int(), _M_den(), _M_cp()
2403 if (__bbegin != __bend)
2407 _M_int.push_back(*__bbegin);
2409 if (__bbegin == __bend)
2412 _M_den.push_back(*__wbegin);
2420 template<
typename _RealType>
2421 template<
typename _Func>
2422 piecewise_constant_distribution<_RealType>::param_type::
2423 param_type(initializer_list<_RealType> __bl, _Func __fw)
2424 : _M_int(), _M_den(), _M_cp()
2426 _M_int.reserve(__bl.size());
2427 for (
auto __biter = __bl.begin(); __biter != __bl.end(); ++__biter)
2428 _M_int.push_back(*__biter);
2430 _M_den.reserve(_M_int.size() - 1);
2431 for (
size_t __k = 0; __k < _M_int.size() - 1; ++__k)
2432 _M_den.push_back(__fw(0.5 * (_M_int[__k + 1] + _M_int[__k])));
2437 template<
typename _RealType>
2438 template<
typename _Func>
2439 piecewise_constant_distribution<_RealType>::param_type::
2440 param_type(
size_t __nw, _RealType __xmin, _RealType __xmax, _Func __fw)
2441 : _M_int(), _M_den(), _M_cp()
2443 const size_t __n = __nw == 0 ? 1 : __nw;
2444 const _RealType __delta = (__xmax - __xmin) / __n;
2446 _M_int.reserve(__n + 1);
2447 for (
size_t __k = 0; __k <= __nw; ++__k)
2448 _M_int.push_back(__xmin + __k * __delta);
2450 _M_den.reserve(__n);
2451 for (
size_t __k = 0; __k < __nw; ++__k)
2452 _M_den.push_back(__fw(_M_int[__k] + 0.5 * __delta));
2457 template<
typename _RealType>
2458 template<
typename _UniformRandomNumberGenerator>
2459 typename piecewise_constant_distribution<_RealType>::result_type
2460 piecewise_constant_distribution<_RealType>::
2461 operator()(_UniformRandomNumberGenerator& __urng,
2462 const param_type& __param)
2464 __detail::_Adaptor<_UniformRandomNumberGenerator, double>
2467 const double __p = __aurng();
2468 if (__param._M_cp.empty())
2472 __param._M_cp.end(), __p);
2473 const size_t __i = __pos - __param._M_cp.begin();
2475 const double __pref = __i > 0 ? __param._M_cp[__i - 1] : 0.0;
2477 return __param._M_int[__i] + (__p - __pref) / __param._M_den[__i];
2480 template<
typename _RealType,
typename _CharT,
typename _Traits>
2482 operator<<(std::basic_ostream<_CharT, _Traits>& __os,
2483 const piecewise_constant_distribution<_RealType>& __x)
2486 typedef typename __ostream_type::ios_base __ios_base;
2488 const typename __ios_base::fmtflags __flags = __os.
flags();
2489 const _CharT __fill = __os.fill();
2491 const _CharT __space = __os.widen(
' ');
2497 __os << __int.
size() - 1;
2499 for (
auto __xit = __int.
begin(); __xit != __int.
end(); ++__xit)
2500 __os << __space << *__xit;
2503 for (
auto __dit = __den.
begin(); __dit != __den.
end(); ++__dit)
2504 __os << __space << *__dit;
2506 __os.flags(__flags);
2508 __os.precision(__precision);
2512 template<
typename _RealType,
typename _CharT,
typename _Traits>
2515 piecewise_constant_distribution<_RealType>& __x)
2518 typedef typename __istream_type::ios_base __ios_base;
2520 const typename __ios_base::fmtflags __flags = __is.
flags();
2528 for (
size_t __i = 0; __i <= __n; ++__i)
2537 for (
size_t __i = 0; __i < __n; ++__i)
2544 __x.param(
typename piecewise_constant_distribution<_RealType>::
2545 param_type(__int_vec.
begin(), __int_vec.
end(), __den_vec.
begin()));
2547 __is.
flags(__flags);
2552 template<
typename _RealType>
2554 piecewise_linear_distribution<_RealType>::param_type::
2557 if (_M_int.size() < 2
2558 || (_M_int.size() == 2
2559 && _M_int[0] == _RealType(0)
2560 && _M_int[1] == _RealType(1)
2561 && _M_den[0] == _M_den[1]))
2569 _M_cp.reserve(_M_int.size() - 1);
2570 _M_m.reserve(_M_int.size() - 1);
2571 for (
size_t __k = 0; __k < _M_int.size() - 1; ++__k)
2573 const _RealType __delta = _M_int[__k + 1] - _M_int[__k];
2574 __sum += 0.5 * (_M_den[__k + 1] + _M_den[__k]) * __delta;
2575 _M_cp.push_back(__sum);
2576 _M_m.push_back((_M_den[__k + 1] - _M_den[__k]) / __delta);
2580 __detail::__transform(_M_den.begin(), _M_den.end(), _M_den.begin(),
2583 __detail::__transform(_M_cp.begin(), _M_cp.end(), _M_cp.begin(),
2586 __detail::__transform(_M_m.begin(), _M_m.end(), _M_m.begin(),
2589 _M_cp[_M_cp.size() - 1] = 1.0;
2592 template<
typename _RealType>
2593 template<
typename _InputIteratorB,
typename _InputIteratorW>
2594 piecewise_linear_distribution<_RealType>::param_type::
2595 param_type(_InputIteratorB __bbegin,
2596 _InputIteratorB __bend,
2597 _InputIteratorW __wbegin)
2598 : _M_int(), _M_den(), _M_cp(), _M_m()
2600 for (; __bbegin != __bend; ++__bbegin, ++__wbegin)
2602 _M_int.push_back(*__bbegin);
2603 _M_den.push_back(*__wbegin);
2609 template<
typename _RealType>
2610 template<
typename _Func>
2611 piecewise_linear_distribution<_RealType>::param_type::
2612 param_type(initializer_list<_RealType> __bl, _Func __fw)
2613 : _M_int(), _M_den(), _M_cp(), _M_m()
2615 _M_int.reserve(__bl.size());
2616 _M_den.reserve(__bl.size());
2617 for (
auto __biter = __bl.begin(); __biter != __bl.end(); ++__biter)
2619 _M_int.push_back(*__biter);
2620 _M_den.push_back(__fw(*__biter));
2626 template<
typename _RealType>
2627 template<
typename _Func>
2628 piecewise_linear_distribution<_RealType>::param_type::
2629 param_type(
size_t __nw, _RealType __xmin, _RealType __xmax, _Func __fw)
2630 : _M_int(), _M_den(), _M_cp(), _M_m()
2632 const size_t __n = __nw == 0 ? 1 : __nw;
2633 const _RealType __delta = (__xmax - __xmin) / __n;
2635 _M_int.reserve(__n + 1);
2636 _M_den.reserve(__n + 1);
2637 for (
size_t __k = 0; __k <= __nw; ++__k)
2639 _M_int.push_back(__xmin + __k * __delta);
2640 _M_den.push_back(__fw(_M_int[__k] + __delta));
2646 template<
typename _RealType>
2647 template<
typename _UniformRandomNumberGenerator>
2648 typename piecewise_linear_distribution<_RealType>::result_type
2649 piecewise_linear_distribution<_RealType>::
2650 operator()(_UniformRandomNumberGenerator& __urng,
2651 const param_type& __param)
2653 __detail::_Adaptor<_UniformRandomNumberGenerator, double>
2656 const double __p = __aurng();
2657 if (__param._M_cp.empty())
2661 __param._M_cp.end(), __p);
2662 const size_t __i = __pos - __param._M_cp.begin();
2664 const double __pref = __i > 0 ? __param._M_cp[__i - 1] : 0.0;
2666 const double __a = 0.5 * __param._M_m[__i];
2667 const double __b = __param._M_den[__i];
2668 const double __cm = __p - __pref;
2670 _RealType __x = __param._M_int[__i];
2675 const double __d = __b * __b + 4.0 * __a * __cm;
2676 __x += 0.5 * (
std::sqrt(__d) - __b) / __a;
2682 template<
typename _RealType,
typename _CharT,
typename _Traits>
2684 operator<<(std::basic_ostream<_CharT, _Traits>& __os,
2685 const piecewise_linear_distribution<_RealType>& __x)
2688 typedef typename __ostream_type::ios_base __ios_base;
2690 const typename __ios_base::fmtflags __flags = __os.
flags();
2691 const _CharT __fill = __os.fill();
2693 const _CharT __space = __os.widen(
' ');
2699 __os << __int.
size() - 1;
2701 for (
auto __xit = __int.
begin(); __xit != __int.
end(); ++__xit)
2702 __os << __space << *__xit;
2705 for (
auto __dit = __den.
begin(); __dit != __den.
end(); ++__dit)
2706 __os << __space << *__dit;
2708 __os.flags(__flags);
2710 __os.precision(__precision);
2714 template<
typename _RealType,
typename _CharT,
typename _Traits>
2717 piecewise_linear_distribution<_RealType>& __x)
2720 typedef typename __istream_type::ios_base __ios_base;
2722 const typename __ios_base::fmtflags __flags = __is.
flags();
2730 for (
size_t __i = 0; __i <= __n; ++__i)
2739 for (
size_t __i = 0; __i <= __n; ++__i)
2746 __x.param(
typename piecewise_linear_distribution<_RealType>::
2747 param_type(__int_vec.
begin(), __int_vec.
end(), __den_vec.
begin()));
2749 __is.
flags(__flags);
2754 template<
typename _IntType>
2757 for (
auto __iter = __il.begin(); __iter != __il.end(); ++__iter)
2758 _M_v.push_back(__detail::__mod<result_type,
2759 __detail::_Shift<result_type, 32>::__value>(*__iter));
2762 template<
typename _InputIterator>
2763 seed_seq::seed_seq(_InputIterator __begin, _InputIterator __end)
2765 for (_InputIterator __iter = __begin; __iter != __end; ++__iter)
2766 _M_v.push_back(__detail::__mod<result_type,
2767 __detail::_Shift<result_type, 32>::__value>(*__iter));
2770 template<
typename _RandomAccessIterator>
2772 seed_seq::generate(_RandomAccessIterator __begin,
2773 _RandomAccessIterator __end)
2775 typedef typename iterator_traits<_RandomAccessIterator>::value_type
2778 if (__begin == __end)
2781 std::fill(__begin, __end, _Type(0x8b8b8b8bu));
2783 const size_t __n = __end - __begin;
2784 const size_t __s = _M_v.size();
2785 const size_t __t = (__n >= 623) ? 11
2790 const size_t __p = (__n - __t) / 2;
2791 const size_t __q = __p + __t;
2792 const size_t __m =
std::max(
size_t(__s + 1), __n);
2794 for (
size_t __k = 0; __k < __m; ++__k)
2796 _Type __arg = (__begin[__k % __n]
2797 ^ __begin[(__k + __p) % __n]
2798 ^ __begin[(__k - 1) % __n]);
2799 _Type __r1 = __arg ^ (__arg >> 27);
2800 __r1 = __detail::__mod<_Type,
2801 __detail::_Shift<_Type, 32>::__value>(1664525u * __r1);
2805 else if (__k <= __s)
2806 __r2 += __k % __n + _M_v[__k - 1];
2809 __r2 = __detail::__mod<_Type,
2810 __detail::_Shift<_Type, 32>::__value>(__r2);
2811 __begin[(__k + __p) % __n] += __r1;
2812 __begin[(__k + __q) % __n] += __r2;
2813 __begin[__k % __n] = __r2;
2816 for (
size_t __k = __m; __k < __m + __n; ++__k)
2818 _Type __arg = (__begin[__k % __n]
2819 + __begin[(__k + __p) % __n]
2820 + __begin[(__k - 1) % __n]);
2821 _Type __r3 = __arg ^ (__arg >> 27);
2822 __r3 = __detail::__mod<_Type,
2823 __detail::_Shift<_Type, 32>::__value>(1566083941u * __r3);
2824 _Type __r4 = __r3 - __k % __n;
2825 __r4 = __detail::__mod<_Type,
2826 __detail::_Shift<_Type, 32>::__value>(__r4);
2827 __begin[(__k + __p) % __n] ^= __r3;
2828 __begin[(__k + __q) % __n] ^= __r4;
2829 __begin[__k % __n] = __r4;
2833 template<
typename _RealType,
size_t __bits,
2834 typename _UniformRandomNumberGenerator>
2841 const long double __r =
static_cast<long double>(__urng.max())
2842 - static_cast<long double>(__urng.min()) + 1.0L;
2844 size_t __k = std::max<size_t>(1UL, (__b + __log2r - 1UL) / __log2r);
2845 _RealType __sum = _RealType(0);
2846 _RealType __tmp = _RealType(1);
2847 for (; __k != 0; --__k)
2849 __sum += _RealType(__urng() - __urng.min()) * __tmp;
2852 return __sum / __tmp;
2855 _GLIBCXX_END_NAMESPACE_VERSION