aboutsummaryrefslogtreecommitdiffstats
path: root/gcc-4.8.1/libstdc++-v3/include/bits/random.tcc
diff options
context:
space:
mode:
Diffstat (limited to 'gcc-4.8.1/libstdc++-v3/include/bits/random.tcc')
-rw-r--r--gcc-4.8.1/libstdc++-v3/include/bits/random.tcc3484
1 files changed, 0 insertions, 3484 deletions
diff --git a/gcc-4.8.1/libstdc++-v3/include/bits/random.tcc b/gcc-4.8.1/libstdc++-v3/include/bits/random.tcc
deleted file mode 100644
index 5b562b9f2..000000000
--- a/gcc-4.8.1/libstdc++-v3/include/bits/random.tcc
+++ /dev/null
@@ -1,3484 +0,0 @@
-// random number generation (out of line) -*- C++ -*-
-
-// Copyright (C) 2009-2013 Free Software Foundation, Inc.
-//
-// This file is part of the GNU ISO C++ Library. This library is free
-// software; you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the
-// Free Software Foundation; either version 3, or (at your option)
-// any later version.
-
-// This library is distributed in the hope that it will be useful,
-// but WITHOUT ANY WARRANTY; without even the implied warranty of
-// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-// GNU General Public License for more details.
-
-// Under Section 7 of GPL version 3, you are granted additional
-// permissions described in the GCC Runtime Library Exception, version
-// 3.1, as published by the Free Software Foundation.
-
-// You should have received a copy of the GNU General Public License and
-// a copy of the GCC Runtime Library Exception along with this program;
-// see the files COPYING3 and COPYING.RUNTIME respectively. If not, see
-// <http://www.gnu.org/licenses/>.
-
-/** @file bits/random.tcc
- * This is an internal header file, included by other library headers.
- * Do not attempt to use it directly. @headername{random}
- */
-
-#ifndef _RANDOM_TCC
-#define _RANDOM_TCC 1
-
-#include <numeric> // std::accumulate and std::partial_sum
-
-namespace std _GLIBCXX_VISIBILITY(default)
-{
- /*
- * (Further) implementation-space details.
- */
- namespace __detail
- {
- _GLIBCXX_BEGIN_NAMESPACE_VERSION
-
- // General case for x = (ax + c) mod m -- use Schrage's algorithm
- // to avoid integer overflow.
- //
- // Preconditions: a > 0, m > 0.
- //
- // Note: only works correctly for __m % __a < __m / __a.
- template<typename _Tp, _Tp __m, _Tp __a, _Tp __c>
- _Tp
- _Mod<_Tp, __m, __a, __c, false, true>::
- __calc(_Tp __x)
- {
- if (__a == 1)
- __x %= __m;
- else
- {
- static const _Tp __q = __m / __a;
- static const _Tp __r = __m % __a;
-
- _Tp __t1 = __a * (__x % __q);
- _Tp __t2 = __r * (__x / __q);
- if (__t1 >= __t2)
- __x = __t1 - __t2;
- else
- __x = __m - __t2 + __t1;
- }
-
- if (__c != 0)
- {
- const _Tp __d = __m - __x;
- if (__d > __c)
- __x += __c;
- else
- __x = __c - __d;
- }
- return __x;
- }
-
- template<typename _InputIterator, typename _OutputIterator,
- typename _Tp>
- _OutputIterator
- __normalize(_InputIterator __first, _InputIterator __last,
- _OutputIterator __result, const _Tp& __factor)
- {
- for (; __first != __last; ++__first, ++__result)
- *__result = *__first / __factor;
- return __result;
- }
-
- _GLIBCXX_END_NAMESPACE_VERSION
- } // namespace __detail
-
-_GLIBCXX_BEGIN_NAMESPACE_VERSION
-
- template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>
- constexpr _UIntType
- linear_congruential_engine<_UIntType, __a, __c, __m>::multiplier;
-
- template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>
- constexpr _UIntType
- linear_congruential_engine<_UIntType, __a, __c, __m>::increment;
-
- template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>
- constexpr _UIntType
- linear_congruential_engine<_UIntType, __a, __c, __m>::modulus;
-
- template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>
- constexpr _UIntType
- linear_congruential_engine<_UIntType, __a, __c, __m>::default_seed;
-
- /**
- * Seeds the LCR with integral value @p __s, adjusted so that the
- * ring identity is never a member of the convergence set.
- */
- template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>
- void
- linear_congruential_engine<_UIntType, __a, __c, __m>::
- seed(result_type __s)
- {
- if ((__detail::__mod<_UIntType, __m>(__c) == 0)
- && (__detail::__mod<_UIntType, __m>(__s) == 0))
- _M_x = 1;
- else
- _M_x = __detail::__mod<_UIntType, __m>(__s);
- }
-
- /**
- * Seeds the LCR engine with a value generated by @p __q.
- */
- template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>
- template<typename _Sseq>
- typename std::enable_if<std::is_class<_Sseq>::value>::type
- linear_congruential_engine<_UIntType, __a, __c, __m>::
- seed(_Sseq& __q)
- {
- const _UIntType __k0 = __m == 0 ? std::numeric_limits<_UIntType>::digits
- : std::__lg(__m);
- const _UIntType __k = (__k0 + 31) / 32;
- uint_least32_t __arr[__k + 3];
- __q.generate(__arr + 0, __arr + __k + 3);
- _UIntType __factor = 1u;
- _UIntType __sum = 0u;
- for (size_t __j = 0; __j < __k; ++__j)
- {
- __sum += __arr[__j + 3] * __factor;
- __factor *= __detail::_Shift<_UIntType, 32>::__value;
- }
- seed(__sum);
- }
-
- template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m,
- typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const linear_congruential_engine<_UIntType,
- __a, __c, __m>& __lcr)
- {
- typedef std::basic_ostream<_CharT, _Traits> __ostream_type;
- typedef typename __ostream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __os.flags();
- const _CharT __fill = __os.fill();
- __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left);
- __os.fill(__os.widen(' '));
-
- __os << __lcr._M_x;
-
- __os.flags(__flags);
- __os.fill(__fill);
- return __os;
- }
-
- template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m,
- typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- linear_congruential_engine<_UIntType, __a, __c, __m>& __lcr)
- {
- typedef std::basic_istream<_CharT, _Traits> __istream_type;
- typedef typename __istream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __is.flags();
- __is.flags(__ios_base::dec);
-
- __is >> __lcr._M_x;
-
- __is.flags(__flags);
- return __is;
- }
-
-
- template<typename _UIntType,
- size_t __w, size_t __n, size_t __m, size_t __r,
- _UIntType __a, size_t __u, _UIntType __d, size_t __s,
- _UIntType __b, size_t __t, _UIntType __c, size_t __l,
- _UIntType __f>
- constexpr size_t
- mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
- __s, __b, __t, __c, __l, __f>::word_size;
-
- template<typename _UIntType,
- size_t __w, size_t __n, size_t __m, size_t __r,
- _UIntType __a, size_t __u, _UIntType __d, size_t __s,
- _UIntType __b, size_t __t, _UIntType __c, size_t __l,
- _UIntType __f>
- constexpr size_t
- mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
- __s, __b, __t, __c, __l, __f>::state_size;
-
- template<typename _UIntType,
- size_t __w, size_t __n, size_t __m, size_t __r,
- _UIntType __a, size_t __u, _UIntType __d, size_t __s,
- _UIntType __b, size_t __t, _UIntType __c, size_t __l,
- _UIntType __f>
- constexpr size_t
- mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
- __s, __b, __t, __c, __l, __f>::shift_size;
-
- template<typename _UIntType,
- size_t __w, size_t __n, size_t __m, size_t __r,
- _UIntType __a, size_t __u, _UIntType __d, size_t __s,
- _UIntType __b, size_t __t, _UIntType __c, size_t __l,
- _UIntType __f>
- constexpr size_t
- mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
- __s, __b, __t, __c, __l, __f>::mask_bits;
-
- template<typename _UIntType,
- size_t __w, size_t __n, size_t __m, size_t __r,
- _UIntType __a, size_t __u, _UIntType __d, size_t __s,
- _UIntType __b, size_t __t, _UIntType __c, size_t __l,
- _UIntType __f>
- constexpr _UIntType
- mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
- __s, __b, __t, __c, __l, __f>::xor_mask;
-
- template<typename _UIntType,
- size_t __w, size_t __n, size_t __m, size_t __r,
- _UIntType __a, size_t __u, _UIntType __d, size_t __s,
- _UIntType __b, size_t __t, _UIntType __c, size_t __l,
- _UIntType __f>
- constexpr size_t
- mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
- __s, __b, __t, __c, __l, __f>::tempering_u;
-
- template<typename _UIntType,
- size_t __w, size_t __n, size_t __m, size_t __r,
- _UIntType __a, size_t __u, _UIntType __d, size_t __s,
- _UIntType __b, size_t __t, _UIntType __c, size_t __l,
- _UIntType __f>
- constexpr _UIntType
- mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
- __s, __b, __t, __c, __l, __f>::tempering_d;
-
- template<typename _UIntType,
- size_t __w, size_t __n, size_t __m, size_t __r,
- _UIntType __a, size_t __u, _UIntType __d, size_t __s,
- _UIntType __b, size_t __t, _UIntType __c, size_t __l,
- _UIntType __f>
- constexpr size_t
- mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
- __s, __b, __t, __c, __l, __f>::tempering_s;
-
- template<typename _UIntType,
- size_t __w, size_t __n, size_t __m, size_t __r,
- _UIntType __a, size_t __u, _UIntType __d, size_t __s,
- _UIntType __b, size_t __t, _UIntType __c, size_t __l,
- _UIntType __f>
- constexpr _UIntType
- mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
- __s, __b, __t, __c, __l, __f>::tempering_b;
-
- template<typename _UIntType,
- size_t __w, size_t __n, size_t __m, size_t __r,
- _UIntType __a, size_t __u, _UIntType __d, size_t __s,
- _UIntType __b, size_t __t, _UIntType __c, size_t __l,
- _UIntType __f>
- constexpr size_t
- mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
- __s, __b, __t, __c, __l, __f>::tempering_t;
-
- template<typename _UIntType,
- size_t __w, size_t __n, size_t __m, size_t __r,
- _UIntType __a, size_t __u, _UIntType __d, size_t __s,
- _UIntType __b, size_t __t, _UIntType __c, size_t __l,
- _UIntType __f>
- constexpr _UIntType
- mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
- __s, __b, __t, __c, __l, __f>::tempering_c;
-
- template<typename _UIntType,
- size_t __w, size_t __n, size_t __m, size_t __r,
- _UIntType __a, size_t __u, _UIntType __d, size_t __s,
- _UIntType __b, size_t __t, _UIntType __c, size_t __l,
- _UIntType __f>
- constexpr size_t
- mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
- __s, __b, __t, __c, __l, __f>::tempering_l;
-
- template<typename _UIntType,
- size_t __w, size_t __n, size_t __m, size_t __r,
- _UIntType __a, size_t __u, _UIntType __d, size_t __s,
- _UIntType __b, size_t __t, _UIntType __c, size_t __l,
- _UIntType __f>
- constexpr _UIntType
- mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
- __s, __b, __t, __c, __l, __f>::
- initialization_multiplier;
-
- template<typename _UIntType,
- size_t __w, size_t __n, size_t __m, size_t __r,
- _UIntType __a, size_t __u, _UIntType __d, size_t __s,
- _UIntType __b, size_t __t, _UIntType __c, size_t __l,
- _UIntType __f>
- constexpr _UIntType
- mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
- __s, __b, __t, __c, __l, __f>::default_seed;
-
- template<typename _UIntType,
- size_t __w, size_t __n, size_t __m, size_t __r,
- _UIntType __a, size_t __u, _UIntType __d, size_t __s,
- _UIntType __b, size_t __t, _UIntType __c, size_t __l,
- _UIntType __f>
- void
- mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
- __s, __b, __t, __c, __l, __f>::
- seed(result_type __sd)
- {
- _M_x[0] = __detail::__mod<_UIntType,
- __detail::_Shift<_UIntType, __w>::__value>(__sd);
-
- for (size_t __i = 1; __i < state_size; ++__i)
- {
- _UIntType __x = _M_x[__i - 1];
- __x ^= __x >> (__w - 2);
- __x *= __f;
- __x += __detail::__mod<_UIntType, __n>(__i);
- _M_x[__i] = __detail::__mod<_UIntType,
- __detail::_Shift<_UIntType, __w>::__value>(__x);
- }
- _M_p = state_size;
- }
-
- template<typename _UIntType,
- size_t __w, size_t __n, size_t __m, size_t __r,
- _UIntType __a, size_t __u, _UIntType __d, size_t __s,
- _UIntType __b, size_t __t, _UIntType __c, size_t __l,
- _UIntType __f>
- template<typename _Sseq>
- typename std::enable_if<std::is_class<_Sseq>::value>::type
- mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
- __s, __b, __t, __c, __l, __f>::
- seed(_Sseq& __q)
- {
- const _UIntType __upper_mask = (~_UIntType()) << __r;
- const size_t __k = (__w + 31) / 32;
- uint_least32_t __arr[__n * __k];
- __q.generate(__arr + 0, __arr + __n * __k);
-
- bool __zero = true;
- for (size_t __i = 0; __i < state_size; ++__i)
- {
- _UIntType __factor = 1u;
- _UIntType __sum = 0u;
- for (size_t __j = 0; __j < __k; ++__j)
- {
- __sum += __arr[__k * __i + __j] * __factor;
- __factor *= __detail::_Shift<_UIntType, 32>::__value;
- }
- _M_x[__i] = __detail::__mod<_UIntType,
- __detail::_Shift<_UIntType, __w>::__value>(__sum);
-
- if (__zero)
- {
- if (__i == 0)
- {
- if ((_M_x[0] & __upper_mask) != 0u)
- __zero = false;
- }
- else if (_M_x[__i] != 0u)
- __zero = false;
- }
- }
- if (__zero)
- _M_x[0] = __detail::_Shift<_UIntType, __w - 1>::__value;
- _M_p = state_size;
- }
-
- template<typename _UIntType, size_t __w,
- size_t __n, size_t __m, size_t __r,
- _UIntType __a, size_t __u, _UIntType __d, size_t __s,
- _UIntType __b, size_t __t, _UIntType __c, size_t __l,
- _UIntType __f>
- void
- mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
- __s, __b, __t, __c, __l, __f>::
- _M_gen_rand(void)
- {
- const _UIntType __upper_mask = (~_UIntType()) << __r;
- const _UIntType __lower_mask = ~__upper_mask;
-
- for (size_t __k = 0; __k < (__n - __m); ++__k)
- {
- _UIntType __y = ((_M_x[__k] & __upper_mask)
- | (_M_x[__k + 1] & __lower_mask));
- _M_x[__k] = (_M_x[__k + __m] ^ (__y >> 1)
- ^ ((__y & 0x01) ? __a : 0));
- }
-
- for (size_t __k = (__n - __m); __k < (__n - 1); ++__k)
- {
- _UIntType __y = ((_M_x[__k] & __upper_mask)
- | (_M_x[__k + 1] & __lower_mask));
- _M_x[__k] = (_M_x[__k + (__m - __n)] ^ (__y >> 1)
- ^ ((__y & 0x01) ? __a : 0));
- }
-
- _UIntType __y = ((_M_x[__n - 1] & __upper_mask)
- | (_M_x[0] & __lower_mask));
- _M_x[__n - 1] = (_M_x[__m - 1] ^ (__y >> 1)
- ^ ((__y & 0x01) ? __a : 0));
- _M_p = 0;
- }
-
- template<typename _UIntType, size_t __w,
- size_t __n, size_t __m, size_t __r,
- _UIntType __a, size_t __u, _UIntType __d, size_t __s,
- _UIntType __b, size_t __t, _UIntType __c, size_t __l,
- _UIntType __f>
- void
- mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
- __s, __b, __t, __c, __l, __f>::
- discard(unsigned long long __z)
- {
- while (__z > state_size - _M_p)
- {
- __z -= state_size - _M_p;
- _M_gen_rand();
- }
- _M_p += __z;
- }
-
- template<typename _UIntType, size_t __w,
- size_t __n, size_t __m, size_t __r,
- _UIntType __a, size_t __u, _UIntType __d, size_t __s,
- _UIntType __b, size_t __t, _UIntType __c, size_t __l,
- _UIntType __f>
- typename
- mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
- __s, __b, __t, __c, __l, __f>::result_type
- mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
- __s, __b, __t, __c, __l, __f>::
- operator()()
- {
- // Reload the vector - cost is O(n) amortized over n calls.
- if (_M_p >= state_size)
- _M_gen_rand();
-
- // Calculate o(x(i)).
- result_type __z = _M_x[_M_p++];
- __z ^= (__z >> __u) & __d;
- __z ^= (__z << __s) & __b;
- __z ^= (__z << __t) & __c;
- __z ^= (__z >> __l);
-
- return __z;
- }
-
- template<typename _UIntType, size_t __w,
- size_t __n, size_t __m, size_t __r,
- _UIntType __a, size_t __u, _UIntType __d, size_t __s,
- _UIntType __b, size_t __t, _UIntType __c, size_t __l,
- _UIntType __f, typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const mersenne_twister_engine<_UIntType, __w, __n, __m,
- __r, __a, __u, __d, __s, __b, __t, __c, __l, __f>& __x)
- {
- typedef std::basic_ostream<_CharT, _Traits> __ostream_type;
- typedef typename __ostream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __os.flags();
- const _CharT __fill = __os.fill();
- const _CharT __space = __os.widen(' ');
- __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left);
- __os.fill(__space);
-
- for (size_t __i = 0; __i < __n; ++__i)
- __os << __x._M_x[__i] << __space;
- __os << __x._M_p;
-
- __os.flags(__flags);
- __os.fill(__fill);
- return __os;
- }
-
- template<typename _UIntType, size_t __w,
- size_t __n, size_t __m, size_t __r,
- _UIntType __a, size_t __u, _UIntType __d, size_t __s,
- _UIntType __b, size_t __t, _UIntType __c, size_t __l,
- _UIntType __f, typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- mersenne_twister_engine<_UIntType, __w, __n, __m,
- __r, __a, __u, __d, __s, __b, __t, __c, __l, __f>& __x)
- {
- typedef std::basic_istream<_CharT, _Traits> __istream_type;
- typedef typename __istream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __is.flags();
- __is.flags(__ios_base::dec | __ios_base::skipws);
-
- for (size_t __i = 0; __i < __n; ++__i)
- __is >> __x._M_x[__i];
- __is >> __x._M_p;
-
- __is.flags(__flags);
- return __is;
- }
-
-
- template<typename _UIntType, size_t __w, size_t __s, size_t __r>
- constexpr size_t
- subtract_with_carry_engine<_UIntType, __w, __s, __r>::word_size;
-
- template<typename _UIntType, size_t __w, size_t __s, size_t __r>
- constexpr size_t
- subtract_with_carry_engine<_UIntType, __w, __s, __r>::short_lag;
-
- template<typename _UIntType, size_t __w, size_t __s, size_t __r>
- constexpr size_t
- subtract_with_carry_engine<_UIntType, __w, __s, __r>::long_lag;
-
- template<typename _UIntType, size_t __w, size_t __s, size_t __r>
- constexpr _UIntType
- subtract_with_carry_engine<_UIntType, __w, __s, __r>::default_seed;
-
- template<typename _UIntType, size_t __w, size_t __s, size_t __r>
- void
- subtract_with_carry_engine<_UIntType, __w, __s, __r>::
- seed(result_type __value)
- {
- std::linear_congruential_engine<result_type, 40014u, 0u, 2147483563u>
- __lcg(__value == 0u ? default_seed : __value);
-
- const size_t __n = (__w + 31) / 32;
-
- for (size_t __i = 0; __i < long_lag; ++__i)
- {
- _UIntType __sum = 0u;
- _UIntType __factor = 1u;
- for (size_t __j = 0; __j < __n; ++__j)
- {
- __sum += __detail::__mod<uint_least32_t,
- __detail::_Shift<uint_least32_t, 32>::__value>
- (__lcg()) * __factor;
- __factor *= __detail::_Shift<_UIntType, 32>::__value;
- }
- _M_x[__i] = __detail::__mod<_UIntType,
- __detail::_Shift<_UIntType, __w>::__value>(__sum);
- }
- _M_carry = (_M_x[long_lag - 1] == 0) ? 1 : 0;
- _M_p = 0;
- }
-
- template<typename _UIntType, size_t __w, size_t __s, size_t __r>
- template<typename _Sseq>
- typename std::enable_if<std::is_class<_Sseq>::value>::type
- subtract_with_carry_engine<_UIntType, __w, __s, __r>::
- seed(_Sseq& __q)
- {
- const size_t __k = (__w + 31) / 32;
- uint_least32_t __arr[__r * __k];
- __q.generate(__arr + 0, __arr + __r * __k);
-
- for (size_t __i = 0; __i < long_lag; ++__i)
- {
- _UIntType __sum = 0u;
- _UIntType __factor = 1u;
- for (size_t __j = 0; __j < __k; ++__j)
- {
- __sum += __arr[__k * __i + __j] * __factor;
- __factor *= __detail::_Shift<_UIntType, 32>::__value;
- }
- _M_x[__i] = __detail::__mod<_UIntType,
- __detail::_Shift<_UIntType, __w>::__value>(__sum);
- }
- _M_carry = (_M_x[long_lag - 1] == 0) ? 1 : 0;
- _M_p = 0;
- }
-
- template<typename _UIntType, size_t __w, size_t __s, size_t __r>
- typename subtract_with_carry_engine<_UIntType, __w, __s, __r>::
- result_type
- subtract_with_carry_engine<_UIntType, __w, __s, __r>::
- operator()()
- {
- // Derive short lag index from current index.
- long __ps = _M_p - short_lag;
- if (__ps < 0)
- __ps += long_lag;
-
- // Calculate new x(i) without overflow or division.
- // NB: Thanks to the requirements for _UIntType, _M_x[_M_p] + _M_carry
- // cannot overflow.
- _UIntType __xi;
- if (_M_x[__ps] >= _M_x[_M_p] + _M_carry)
- {
- __xi = _M_x[__ps] - _M_x[_M_p] - _M_carry;
- _M_carry = 0;
- }
- else
- {
- __xi = (__detail::_Shift<_UIntType, __w>::__value
- - _M_x[_M_p] - _M_carry + _M_x[__ps]);
- _M_carry = 1;
- }
- _M_x[_M_p] = __xi;
-
- // Adjust current index to loop around in ring buffer.
- if (++_M_p >= long_lag)
- _M_p = 0;
-
- return __xi;
- }
-
- template<typename _UIntType, size_t __w, size_t __s, size_t __r,
- typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const subtract_with_carry_engine<_UIntType,
- __w, __s, __r>& __x)
- {
- typedef std::basic_ostream<_CharT, _Traits> __ostream_type;
- typedef typename __ostream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __os.flags();
- const _CharT __fill = __os.fill();
- const _CharT __space = __os.widen(' ');
- __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left);
- __os.fill(__space);
-
- for (size_t __i = 0; __i < __r; ++__i)
- __os << __x._M_x[__i] << __space;
- __os << __x._M_carry << __space << __x._M_p;
-
- __os.flags(__flags);
- __os.fill(__fill);
- return __os;
- }
-
- template<typename _UIntType, size_t __w, size_t __s, size_t __r,
- typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- subtract_with_carry_engine<_UIntType, __w, __s, __r>& __x)
- {
- typedef std::basic_ostream<_CharT, _Traits> __istream_type;
- typedef typename __istream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __is.flags();
- __is.flags(__ios_base::dec | __ios_base::skipws);
-
- for (size_t __i = 0; __i < __r; ++__i)
- __is >> __x._M_x[__i];
- __is >> __x._M_carry;
- __is >> __x._M_p;
-
- __is.flags(__flags);
- return __is;
- }
-
-
- template<typename _RandomNumberEngine, size_t __p, size_t __r>
- constexpr size_t
- discard_block_engine<_RandomNumberEngine, __p, __r>::block_size;
-
- template<typename _RandomNumberEngine, size_t __p, size_t __r>
- constexpr size_t
- discard_block_engine<_RandomNumberEngine, __p, __r>::used_block;
-
- template<typename _RandomNumberEngine, size_t __p, size_t __r>
- typename discard_block_engine<_RandomNumberEngine,
- __p, __r>::result_type
- discard_block_engine<_RandomNumberEngine, __p, __r>::
- operator()()
- {
- if (_M_n >= used_block)
- {
- _M_b.discard(block_size - _M_n);
- _M_n = 0;
- }
- ++_M_n;
- return _M_b();
- }
-
- template<typename _RandomNumberEngine, size_t __p, size_t __r,
- typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const discard_block_engine<_RandomNumberEngine,
- __p, __r>& __x)
- {
- typedef std::basic_ostream<_CharT, _Traits> __ostream_type;
- typedef typename __ostream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __os.flags();
- const _CharT __fill = __os.fill();
- const _CharT __space = __os.widen(' ');
- __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left);
- __os.fill(__space);
-
- __os << __x.base() << __space << __x._M_n;
-
- __os.flags(__flags);
- __os.fill(__fill);
- return __os;
- }
-
- template<typename _RandomNumberEngine, size_t __p, size_t __r,
- typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- discard_block_engine<_RandomNumberEngine, __p, __r>& __x)
- {
- typedef std::basic_istream<_CharT, _Traits> __istream_type;
- typedef typename __istream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __is.flags();
- __is.flags(__ios_base::dec | __ios_base::skipws);
-
- __is >> __x._M_b >> __x._M_n;
-
- __is.flags(__flags);
- return __is;
- }
-
-
- template<typename _RandomNumberEngine, size_t __w, typename _UIntType>
- typename independent_bits_engine<_RandomNumberEngine, __w, _UIntType>::
- result_type
- independent_bits_engine<_RandomNumberEngine, __w, _UIntType>::
- operator()()
- {
- typedef typename _RandomNumberEngine::result_type _Eresult_type;
- const _Eresult_type __r
- = (_M_b.max() - _M_b.min() < std::numeric_limits<_Eresult_type>::max()
- ? _M_b.max() - _M_b.min() + 1 : 0);
- const unsigned __edig = std::numeric_limits<_Eresult_type>::digits;
- const unsigned __m = __r ? std::__lg(__r) : __edig;
-
- typedef typename std::common_type<_Eresult_type, result_type>::type
- __ctype;
- const unsigned __cdig = std::numeric_limits<__ctype>::digits;
-
- unsigned __n, __n0;
- __ctype __s0, __s1, __y0, __y1;
-
- for (size_t __i = 0; __i < 2; ++__i)
- {
- __n = (__w + __m - 1) / __m + __i;
- __n0 = __n - __w % __n;
- const unsigned __w0 = __w / __n; // __w0 <= __m
-
- __s0 = 0;
- __s1 = 0;
- if (__w0 < __cdig)
- {
- __s0 = __ctype(1) << __w0;
- __s1 = __s0 << 1;
- }
-
- __y0 = 0;
- __y1 = 0;
- if (__r)
- {
- __y0 = __s0 * (__r / __s0);
- if (__s1)
- __y1 = __s1 * (__r / __s1);
-
- if (__r - __y0 <= __y0 / __n)
- break;
- }
- else
- break;
- }
-
- result_type __sum = 0;
- for (size_t __k = 0; __k < __n0; ++__k)
- {
- __ctype __u;
- do
- __u = _M_b() - _M_b.min();
- while (__y0 && __u >= __y0);
- __sum = __s0 * __sum + (__s0 ? __u % __s0 : __u);
- }
- for (size_t __k = __n0; __k < __n; ++__k)
- {
- __ctype __u;
- do
- __u = _M_b() - _M_b.min();
- while (__y1 && __u >= __y1);
- __sum = __s1 * __sum + (__s1 ? __u % __s1 : __u);
- }
- return __sum;
- }
-
-
- template<typename _RandomNumberEngine, size_t __k>
- constexpr size_t
- shuffle_order_engine<_RandomNumberEngine, __k>::table_size;
-
- template<typename _RandomNumberEngine, size_t __k>
- typename shuffle_order_engine<_RandomNumberEngine, __k>::result_type
- shuffle_order_engine<_RandomNumberEngine, __k>::
- operator()()
- {
- size_t __j = __k * ((_M_y - _M_b.min())
- / (_M_b.max() - _M_b.min() + 1.0L));
- _M_y = _M_v[__j];
- _M_v[__j] = _M_b();
-
- return _M_y;
- }
-
- template<typename _RandomNumberEngine, size_t __k,
- typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const shuffle_order_engine<_RandomNumberEngine, __k>& __x)
- {
- typedef std::basic_ostream<_CharT, _Traits> __ostream_type;
- typedef typename __ostream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __os.flags();
- const _CharT __fill = __os.fill();
- const _CharT __space = __os.widen(' ');
- __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left);
- __os.fill(__space);
-
- __os << __x.base();
- for (size_t __i = 0; __i < __k; ++__i)
- __os << __space << __x._M_v[__i];
- __os << __space << __x._M_y;
-
- __os.flags(__flags);
- __os.fill(__fill);
- return __os;
- }
-
- template<typename _RandomNumberEngine, size_t __k,
- typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- shuffle_order_engine<_RandomNumberEngine, __k>& __x)
- {
- typedef std::basic_istream<_CharT, _Traits> __istream_type;
- typedef typename __istream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __is.flags();
- __is.flags(__ios_base::dec | __ios_base::skipws);
-
- __is >> __x._M_b;
- for (size_t __i = 0; __i < __k; ++__i)
- __is >> __x._M_v[__i];
- __is >> __x._M_y;
-
- __is.flags(__flags);
- return __is;
- }
-
-
- template<typename _IntType>
- template<typename _UniformRandomNumberGenerator>
- typename uniform_int_distribution<_IntType>::result_type
- uniform_int_distribution<_IntType>::
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __param)
- {
- typedef typename _UniformRandomNumberGenerator::result_type
- _Gresult_type;
- typedef typename std::make_unsigned<result_type>::type __utype;
- typedef typename std::common_type<_Gresult_type, __utype>::type
- __uctype;
-
- const __uctype __urngmin = __urng.min();
- const __uctype __urngmax = __urng.max();
- const __uctype __urngrange = __urngmax - __urngmin;
- const __uctype __urange
- = __uctype(__param.b()) - __uctype(__param.a());
-
- __uctype __ret;
-
- if (__urngrange > __urange)
- {
- // downscaling
- const __uctype __uerange = __urange + 1; // __urange can be zero
- const __uctype __scaling = __urngrange / __uerange;
- const __uctype __past = __uerange * __scaling;
- do
- __ret = __uctype(__urng()) - __urngmin;
- while (__ret >= __past);
- __ret /= __scaling;
- }
- else if (__urngrange < __urange)
- {
- // upscaling
- /*
- Note that every value in [0, urange]
- can be written uniquely as
-
- (urngrange + 1) * high + low
-
- where
-
- high in [0, urange / (urngrange + 1)]
-
- and
-
- low in [0, urngrange].
- */
- __uctype __tmp; // wraparound control
- do
- {
- const __uctype __uerngrange = __urngrange + 1;
- __tmp = (__uerngrange * operator()
- (__urng, param_type(0, __urange / __uerngrange)));
- __ret = __tmp + (__uctype(__urng()) - __urngmin);
- }
- while (__ret > __urange || __ret < __tmp);
- }
- else
- __ret = __uctype(__urng()) - __urngmin;
-
- return __ret + __param.a();
- }
-
-
- template<typename _IntType>
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- uniform_int_distribution<_IntType>::
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __param)
- {
- __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>)
- typedef typename _UniformRandomNumberGenerator::result_type
- _Gresult_type;
- typedef typename std::make_unsigned<result_type>::type __utype;
- typedef typename std::common_type<_Gresult_type, __utype>::type
- __uctype;
-
- const __uctype __urngmin = __urng.min();
- const __uctype __urngmax = __urng.max();
- const __uctype __urngrange = __urngmax - __urngmin;
- const __uctype __urange
- = __uctype(__param.b()) - __uctype(__param.a());
-
- __uctype __ret;
-
- if (__urngrange > __urange)
- {
- if (__detail::_Power_of_2(__urngrange + 1)
- && __detail::_Power_of_2(__urange + 1))
- {
- while (__f != __t)
- {
- __ret = __uctype(__urng()) - __urngmin;
- *__f++ = (__ret & __urange) + __param.a();
- }
- }
- else
- {
- // downscaling
- const __uctype __uerange = __urange + 1; // __urange can be zero
- const __uctype __scaling = __urngrange / __uerange;
- const __uctype __past = __uerange * __scaling;
- while (__f != __t)
- {
- do
- __ret = __uctype(__urng()) - __urngmin;
- while (__ret >= __past);
- *__f++ = __ret / __scaling + __param.a();
- }
- }
- }
- else if (__urngrange < __urange)
- {
- // upscaling
- /*
- Note that every value in [0, urange]
- can be written uniquely as
-
- (urngrange + 1) * high + low
-
- where
-
- high in [0, urange / (urngrange + 1)]
-
- and
-
- low in [0, urngrange].
- */
- __uctype __tmp; // wraparound control
- while (__f != __t)
- {
- do
- {
- const __uctype __uerngrange = __urngrange + 1;
- __tmp = (__uerngrange * operator()
- (__urng, param_type(0, __urange / __uerngrange)));
- __ret = __tmp + (__uctype(__urng()) - __urngmin);
- }
- while (__ret > __urange || __ret < __tmp);
- *__f++ = __ret;
- }
- }
- else
- while (__f != __t)
- *__f++ = __uctype(__urng()) - __urngmin + __param.a();
- }
-
- template<typename _IntType, typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const uniform_int_distribution<_IntType>& __x)
- {
- typedef std::basic_ostream<_CharT, _Traits> __ostream_type;
- typedef typename __ostream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __os.flags();
- const _CharT __fill = __os.fill();
- const _CharT __space = __os.widen(' ');
- __os.flags(__ios_base::scientific | __ios_base::left);
- __os.fill(__space);
-
- __os << __x.a() << __space << __x.b();
-
- __os.flags(__flags);
- __os.fill(__fill);
- return __os;
- }
-
- template<typename _IntType, typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- uniform_int_distribution<_IntType>& __x)
- {
- typedef std::basic_istream<_CharT, _Traits> __istream_type;
- typedef typename __istream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __is.flags();
- __is.flags(__ios_base::dec | __ios_base::skipws);
-
- _IntType __a, __b;
- __is >> __a >> __b;
- __x.param(typename uniform_int_distribution<_IntType>::
- param_type(__a, __b));
-
- __is.flags(__flags);
- return __is;
- }
-
-
- template<typename _RealType>
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- uniform_real_distribution<_RealType>::
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- {
- __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>)
- __detail::_Adaptor<_UniformRandomNumberGenerator, result_type>
- __aurng(__urng);
- auto __range = __p.b() - __p.a();
- while (__f != __t)
- *__f++ = __aurng() * __range + __p.a();
- }
-
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const uniform_real_distribution<_RealType>& __x)
- {
- typedef std::basic_ostream<_CharT, _Traits> __ostream_type;
- typedef typename __ostream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __os.flags();
- const _CharT __fill = __os.fill();
- const std::streamsize __precision = __os.precision();
- const _CharT __space = __os.widen(' ');
- __os.flags(__ios_base::scientific | __ios_base::left);
- __os.fill(__space);
- __os.precision(std::numeric_limits<_RealType>::max_digits10);
-
- __os << __x.a() << __space << __x.b();
-
- __os.flags(__flags);
- __os.fill(__fill);
- __os.precision(__precision);
- return __os;
- }
-
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- uniform_real_distribution<_RealType>& __x)
- {
- typedef std::basic_istream<_CharT, _Traits> __istream_type;
- typedef typename __istream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __is.flags();
- __is.flags(__ios_base::skipws);
-
- _RealType __a, __b;
- __is >> __a >> __b;
- __x.param(typename uniform_real_distribution<_RealType>::
- param_type(__a, __b));
-
- __is.flags(__flags);
- return __is;
- }
-
-
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- std::bernoulli_distribution::
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- {
- __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>)
- __detail::_Adaptor<_UniformRandomNumberGenerator, double>
- __aurng(__urng);
- auto __limit = __p.p() * (__aurng.max() - __aurng.min());
-
- while (__f != __t)
- *__f++ = (__aurng() - __aurng.min()) < __limit;
- }
-
- template<typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const bernoulli_distribution& __x)
- {
- typedef std::basic_ostream<_CharT, _Traits> __ostream_type;
- typedef typename __ostream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __os.flags();
- const _CharT __fill = __os.fill();
- const std::streamsize __precision = __os.precision();
- __os.flags(__ios_base::scientific | __ios_base::left);
- __os.fill(__os.widen(' '));
- __os.precision(std::numeric_limits<double>::max_digits10);
-
- __os << __x.p();
-
- __os.flags(__flags);
- __os.fill(__fill);
- __os.precision(__precision);
- return __os;
- }
-
-
- template<typename _IntType>
- template<typename _UniformRandomNumberGenerator>
- typename geometric_distribution<_IntType>::result_type
- geometric_distribution<_IntType>::
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __param)
- {
- // About the epsilon thing see this thread:
- // http://gcc.gnu.org/ml/gcc-patches/2006-10/msg00971.html
- const double __naf =
- (1 - std::numeric_limits<double>::epsilon()) / 2;
- // The largest _RealType convertible to _IntType.
- const double __thr =
- std::numeric_limits<_IntType>::max() + __naf;
- __detail::_Adaptor<_UniformRandomNumberGenerator, double>
- __aurng(__urng);
-
- double __cand;
- do
- __cand = std::floor(std::log(1.0 - __aurng()) / __param._M_log_1_p);
- while (__cand >= __thr);
-
- return result_type(__cand + __naf);
- }
-
- template<typename _IntType>
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- geometric_distribution<_IntType>::
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __param)
- {
- __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>)
- // About the epsilon thing see this thread:
- // http://gcc.gnu.org/ml/gcc-patches/2006-10/msg00971.html
- const double __naf =
- (1 - std::numeric_limits<double>::epsilon()) / 2;
- // The largest _RealType convertible to _IntType.
- const double __thr =
- std::numeric_limits<_IntType>::max() + __naf;
- __detail::_Adaptor<_UniformRandomNumberGenerator, double>
- __aurng(__urng);
-
- while (__f != __t)
- {
- double __cand;
- do
- __cand = std::floor(std::log(1.0 - __aurng())
- / __param._M_log_1_p);
- while (__cand >= __thr);
-
- *__f++ = __cand + __naf;
- }
- }
-
- template<typename _IntType,
- typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const geometric_distribution<_IntType>& __x)
- {
- typedef std::basic_ostream<_CharT, _Traits> __ostream_type;
- typedef typename __ostream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __os.flags();
- const _CharT __fill = __os.fill();
- const std::streamsize __precision = __os.precision();
- __os.flags(__ios_base::scientific | __ios_base::left);
- __os.fill(__os.widen(' '));
- __os.precision(std::numeric_limits<double>::max_digits10);
-
- __os << __x.p();
-
- __os.flags(__flags);
- __os.fill(__fill);
- __os.precision(__precision);
- return __os;
- }
-
- template<typename _IntType,
- typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- geometric_distribution<_IntType>& __x)
- {
- typedef std::basic_istream<_CharT, _Traits> __istream_type;
- typedef typename __istream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __is.flags();
- __is.flags(__ios_base::skipws);
-
- double __p;
- __is >> __p;
- __x.param(typename geometric_distribution<_IntType>::param_type(__p));
-
- __is.flags(__flags);
- return __is;
- }
-
- // This is Leger's algorithm, also in Devroye, Ch. X, Example 1.5.
- template<typename _IntType>
- template<typename _UniformRandomNumberGenerator>
- typename negative_binomial_distribution<_IntType>::result_type
- negative_binomial_distribution<_IntType>::
- operator()(_UniformRandomNumberGenerator& __urng)
- {
- const double __y = _M_gd(__urng);
-
- // XXX Is the constructor too slow?
- std::poisson_distribution<result_type> __poisson(__y);
- return __poisson(__urng);
- }
-
- template<typename _IntType>
- template<typename _UniformRandomNumberGenerator>
- typename negative_binomial_distribution<_IntType>::result_type
- negative_binomial_distribution<_IntType>::
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- {
- typedef typename std::gamma_distribution<result_type>::param_type
- param_type;
-
- const double __y =
- _M_gd(__urng, param_type(__p.k(), (1.0 - __p.p()) / __p.p()));
-
- std::poisson_distribution<result_type> __poisson(__y);
- return __poisson(__urng);
- }
-
- template<typename _IntType>
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- negative_binomial_distribution<_IntType>::
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng)
- {
- __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>)
- while (__f != __t)
- {
- const double __y = _M_gd(__urng);
-
- // XXX Is the constructor too slow?
- std::poisson_distribution<result_type> __poisson(__y);
- *__f++ = __poisson(__urng);
- }
- }
-
- template<typename _IntType>
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- negative_binomial_distribution<_IntType>::
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- {
- __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>)
- typename std::gamma_distribution<result_type>::param_type
- __p2(__p.k(), (1.0 - __p.p()) / __p.p());
-
- while (__f != __t)
- {
- const double __y = _M_gd(__urng, __p2);
-
- std::poisson_distribution<result_type> __poisson(__y);
- *__f++ = __poisson(__urng);
- }
- }
-
- template<typename _IntType, typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const negative_binomial_distribution<_IntType>& __x)
- {
- typedef std::basic_ostream<_CharT, _Traits> __ostream_type;
- typedef typename __ostream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __os.flags();
- const _CharT __fill = __os.fill();
- const std::streamsize __precision = __os.precision();
- const _CharT __space = __os.widen(' ');
- __os.flags(__ios_base::scientific | __ios_base::left);
- __os.fill(__os.widen(' '));
- __os.precision(std::numeric_limits<double>::max_digits10);
-
- __os << __x.k() << __space << __x.p()
- << __space << __x._M_gd;
-
- __os.flags(__flags);
- __os.fill(__fill);
- __os.precision(__precision);
- return __os;
- }
-
- template<typename _IntType, typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- negative_binomial_distribution<_IntType>& __x)
- {
- typedef std::basic_istream<_CharT, _Traits> __istream_type;
- typedef typename __istream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __is.flags();
- __is.flags(__ios_base::skipws);
-
- _IntType __k;
- double __p;
- __is >> __k >> __p >> __x._M_gd;
- __x.param(typename negative_binomial_distribution<_IntType>::
- param_type(__k, __p));
-
- __is.flags(__flags);
- return __is;
- }
-
-
- template<typename _IntType>
- void
- poisson_distribution<_IntType>::param_type::
- _M_initialize()
- {
-#if _GLIBCXX_USE_C99_MATH_TR1
- if (_M_mean >= 12)
- {
- const double __m = std::floor(_M_mean);
- _M_lm_thr = std::log(_M_mean);
- _M_lfm = std::lgamma(__m + 1);
- _M_sm = std::sqrt(__m);
-
- const double __pi_4 = 0.7853981633974483096156608458198757L;
- const double __dx = std::sqrt(2 * __m * std::log(32 * __m
- / __pi_4));
- _M_d = std::round(std::max(6.0, std::min(__m, __dx)));
- const double __cx = 2 * __m + _M_d;
- _M_scx = std::sqrt(__cx / 2);
- _M_1cx = 1 / __cx;
-
- _M_c2b = std::sqrt(__pi_4 * __cx) * std::exp(_M_1cx);
- _M_cb = 2 * __cx * std::exp(-_M_d * _M_1cx * (1 + _M_d / 2))
- / _M_d;
- }
- else
-#endif
- _M_lm_thr = std::exp(-_M_mean);
- }
-
- /**
- * A rejection algorithm when mean >= 12 and a simple method based
- * upon the multiplication of uniform random variates otherwise.
- * NB: The former is available only if _GLIBCXX_USE_C99_MATH_TR1
- * is defined.
- *
- * Reference:
- * Devroye, L. Non-Uniform Random Variates Generation. Springer-Verlag,
- * New York, 1986, Ch. X, Sects. 3.3 & 3.4 (+ Errata!).
- */
- template<typename _IntType>
- template<typename _UniformRandomNumberGenerator>
- typename poisson_distribution<_IntType>::result_type
- poisson_distribution<_IntType>::
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __param)
- {
- __detail::_Adaptor<_UniformRandomNumberGenerator, double>
- __aurng(__urng);
-#if _GLIBCXX_USE_C99_MATH_TR1
- if (__param.mean() >= 12)
- {
- double __x;
-
- // See comments above...
- const double __naf =
- (1 - std::numeric_limits<double>::epsilon()) / 2;
- const double __thr =
- std::numeric_limits<_IntType>::max() + __naf;
-
- const double __m = std::floor(__param.mean());
- // sqrt(pi / 2)
- const double __spi_2 = 1.2533141373155002512078826424055226L;
- const double __c1 = __param._M_sm * __spi_2;
- const double __c2 = __param._M_c2b + __c1;
- const double __c3 = __c2 + 1;
- const double __c4 = __c3 + 1;
- // e^(1 / 78)
- const double __e178 = 1.0129030479320018583185514777512983L;
- const double __c5 = __c4 + __e178;
- const double __c = __param._M_cb + __c5;
- const double __2cx = 2 * (2 * __m + __param._M_d);
-
- bool __reject = true;
- do
- {
- const double __u = __c * __aurng();
- const double __e = -std::log(1.0 - __aurng());
-
- double __w = 0.0;
-
- if (__u <= __c1)
- {
- const double __n = _M_nd(__urng);
- const double __y = -std::abs(__n) * __param._M_sm - 1;
- __x = std::floor(__y);
- __w = -__n * __n / 2;
- if (__x < -__m)
- continue;
- }
- else if (__u <= __c2)
- {
- const double __n = _M_nd(__urng);
- const double __y = 1 + std::abs(__n) * __param._M_scx;
- __x = std::ceil(__y);
- __w = __y * (2 - __y) * __param._M_1cx;
- if (__x > __param._M_d)
- continue;
- }
- else if (__u <= __c3)
- // NB: This case not in the book, nor in the Errata,
- // but should be ok...
- __x = -1;
- else if (__u <= __c4)
- __x = 0;
- else if (__u <= __c5)
- __x = 1;
- else
- {
- const double __v = -std::log(1.0 - __aurng());
- const double __y = __param._M_d
- + __v * __2cx / __param._M_d;
- __x = std::ceil(__y);
- __w = -__param._M_d * __param._M_1cx * (1 + __y / 2);
- }
-
- __reject = (__w - __e - __x * __param._M_lm_thr
- > __param._M_lfm - std::lgamma(__x + __m + 1));
-
- __reject |= __x + __m >= __thr;
-
- } while (__reject);
-
- return result_type(__x + __m + __naf);
- }
- else
-#endif
- {
- _IntType __x = 0;
- double __prod = 1.0;
-
- do
- {
- __prod *= __aurng();
- __x += 1;
- }
- while (__prod > __param._M_lm_thr);
-
- return __x - 1;
- }
- }
-
- template<typename _IntType>
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- poisson_distribution<_IntType>::
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __param)
- {
- __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>)
- // We could duplicate everything from operator()...
- while (__f != __t)
- *__f++ = this->operator()(__urng, __param);
- }
-
- template<typename _IntType,
- typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const poisson_distribution<_IntType>& __x)
- {
- typedef std::basic_ostream<_CharT, _Traits> __ostream_type;
- typedef typename __ostream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __os.flags();
- const _CharT __fill = __os.fill();
- const std::streamsize __precision = __os.precision();
- const _CharT __space = __os.widen(' ');
- __os.flags(__ios_base::scientific | __ios_base::left);
- __os.fill(__space);
- __os.precision(std::numeric_limits<double>::max_digits10);
-
- __os << __x.mean() << __space << __x._M_nd;
-
- __os.flags(__flags);
- __os.fill(__fill);
- __os.precision(__precision);
- return __os;
- }
-
- template<typename _IntType,
- typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- poisson_distribution<_IntType>& __x)
- {
- typedef std::basic_istream<_CharT, _Traits> __istream_type;
- typedef typename __istream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __is.flags();
- __is.flags(__ios_base::skipws);
-
- double __mean;
- __is >> __mean >> __x._M_nd;
- __x.param(typename poisson_distribution<_IntType>::param_type(__mean));
-
- __is.flags(__flags);
- return __is;
- }
-
-
- template<typename _IntType>
- void
- binomial_distribution<_IntType>::param_type::
- _M_initialize()
- {
- const double __p12 = _M_p <= 0.5 ? _M_p : 1.0 - _M_p;
-
- _M_easy = true;
-
-#if _GLIBCXX_USE_C99_MATH_TR1
- if (_M_t * __p12 >= 8)
- {
- _M_easy = false;
- const double __np = std::floor(_M_t * __p12);
- const double __pa = __np / _M_t;
- const double __1p = 1 - __pa;
-
- const double __pi_4 = 0.7853981633974483096156608458198757L;
- const double __d1x =
- std::sqrt(__np * __1p * std::log(32 * __np
- / (81 * __pi_4 * __1p)));
- _M_d1 = std::round(std::max(1.0, __d1x));
- const double __d2x =
- std::sqrt(__np * __1p * std::log(32 * _M_t * __1p
- / (__pi_4 * __pa)));
- _M_d2 = std::round(std::max(1.0, __d2x));
-
- // sqrt(pi / 2)
- const double __spi_2 = 1.2533141373155002512078826424055226L;
- _M_s1 = std::sqrt(__np * __1p) * (1 + _M_d1 / (4 * __np));
- _M_s2 = std::sqrt(__np * __1p) * (1 + _M_d2 / (4 * _M_t * __1p));
- _M_c = 2 * _M_d1 / __np;
- _M_a1 = std::exp(_M_c) * _M_s1 * __spi_2;
- const double __a12 = _M_a1 + _M_s2 * __spi_2;
- const double __s1s = _M_s1 * _M_s1;
- _M_a123 = __a12 + (std::exp(_M_d1 / (_M_t * __1p))
- * 2 * __s1s / _M_d1
- * std::exp(-_M_d1 * _M_d1 / (2 * __s1s)));
- const double __s2s = _M_s2 * _M_s2;
- _M_s = (_M_a123 + 2 * __s2s / _M_d2
- * std::exp(-_M_d2 * _M_d2 / (2 * __s2s)));
- _M_lf = (std::lgamma(__np + 1)
- + std::lgamma(_M_t - __np + 1));
- _M_lp1p = std::log(__pa / __1p);
-
- _M_q = -std::log(1 - (__p12 - __pa) / __1p);
- }
- else
-#endif
- _M_q = -std::log(1 - __p12);
- }
-
- template<typename _IntType>
- template<typename _UniformRandomNumberGenerator>
- typename binomial_distribution<_IntType>::result_type
- binomial_distribution<_IntType>::
- _M_waiting(_UniformRandomNumberGenerator& __urng, _IntType __t)
- {
- _IntType __x = 0;
- double __sum = 0.0;
- __detail::_Adaptor<_UniformRandomNumberGenerator, double>
- __aurng(__urng);
-
- do
- {
- if (__t == __x)
- return __x;
- const double __e = -std::log(1.0 - __aurng());
- __sum += __e / (__t - __x);
- __x += 1;
- }
- while (__sum <= _M_param._M_q);
-
- return __x - 1;
- }
-
- /**
- * A rejection algorithm when t * p >= 8 and a simple waiting time
- * method - the second in the referenced book - otherwise.
- * NB: The former is available only if _GLIBCXX_USE_C99_MATH_TR1
- * is defined.
- *
- * Reference:
- * Devroye, L. Non-Uniform Random Variates Generation. Springer-Verlag,
- * New York, 1986, Ch. X, Sect. 4 (+ Errata!).
- */
- template<typename _IntType>
- template<typename _UniformRandomNumberGenerator>
- typename binomial_distribution<_IntType>::result_type
- binomial_distribution<_IntType>::
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __param)
- {
- result_type __ret;
- const _IntType __t = __param.t();
- const double __p = __param.p();
- const double __p12 = __p <= 0.5 ? __p : 1.0 - __p;
- __detail::_Adaptor<_UniformRandomNumberGenerator, double>
- __aurng(__urng);
-
-#if _GLIBCXX_USE_C99_MATH_TR1
- if (!__param._M_easy)
- {
- double __x;
-
- // See comments above...
- const double __naf =
- (1 - std::numeric_limits<double>::epsilon()) / 2;
- const double __thr =
- std::numeric_limits<_IntType>::max() + __naf;
-
- const double __np = std::floor(__t * __p12);
-
- // sqrt(pi / 2)
- const double __spi_2 = 1.2533141373155002512078826424055226L;
- const double __a1 = __param._M_a1;
- const double __a12 = __a1 + __param._M_s2 * __spi_2;
- const double __a123 = __param._M_a123;
- const double __s1s = __param._M_s1 * __param._M_s1;
- const double __s2s = __param._M_s2 * __param._M_s2;
-
- bool __reject;
- do
- {
- const double __u = __param._M_s * __aurng();
-
- double __v;
-
- if (__u <= __a1)
- {
- const double __n = _M_nd(__urng);
- const double __y = __param._M_s1 * std::abs(__n);
- __reject = __y >= __param._M_d1;
- if (!__reject)
- {
- const double __e = -std::log(1.0 - __aurng());
- __x = std::floor(__y);
- __v = -__e - __n * __n / 2 + __param._M_c;
- }
- }
- else if (__u <= __a12)
- {
- const double __n = _M_nd(__urng);
- const double __y = __param._M_s2 * std::abs(__n);
- __reject = __y >= __param._M_d2;
- if (!__reject)
- {
- const double __e = -std::log(1.0 - __aurng());
- __x = std::floor(-__y);
- __v = -__e - __n * __n / 2;
- }
- }
- else if (__u <= __a123)
- {
- const double __e1 = -std::log(1.0 - __aurng());
- const double __e2 = -std::log(1.0 - __aurng());
-
- const double __y = __param._M_d1
- + 2 * __s1s * __e1 / __param._M_d1;
- __x = std::floor(__y);
- __v = (-__e2 + __param._M_d1 * (1 / (__t - __np)
- -__y / (2 * __s1s)));
- __reject = false;
- }
- else
- {
- const double __e1 = -std::log(1.0 - __aurng());
- const double __e2 = -std::log(1.0 - __aurng());
-
- const double __y = __param._M_d2
- + 2 * __s2s * __e1 / __param._M_d2;
- __x = std::floor(-__y);
- __v = -__e2 - __param._M_d2 * __y / (2 * __s2s);
- __reject = false;
- }
-
- __reject = __reject || __x < -__np || __x > __t - __np;
- if (!__reject)
- {
- const double __lfx =
- std::lgamma(__np + __x + 1)
- + std::lgamma(__t - (__np + __x) + 1);
- __reject = __v > __param._M_lf - __lfx
- + __x * __param._M_lp1p;
- }
-
- __reject |= __x + __np >= __thr;
- }
- while (__reject);
-
- __x += __np + __naf;
-
- const _IntType __z = _M_waiting(__urng, __t - _IntType(__x));
- __ret = _IntType(__x) + __z;
- }
- else
-#endif
- __ret = _M_waiting(__urng, __t);
-
- if (__p12 != __p)
- __ret = __t - __ret;
- return __ret;
- }
-
- template<typename _IntType>
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- binomial_distribution<_IntType>::
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __param)
- {
- __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>)
- // We could duplicate everything from operator()...
- while (__f != __t)
- *__f++ = this->operator()(__urng, __param);
- }
-
- template<typename _IntType,
- typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const binomial_distribution<_IntType>& __x)
- {
- typedef std::basic_ostream<_CharT, _Traits> __ostream_type;
- typedef typename __ostream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __os.flags();
- const _CharT __fill = __os.fill();
- const std::streamsize __precision = __os.precision();
- const _CharT __space = __os.widen(' ');
- __os.flags(__ios_base::scientific | __ios_base::left);
- __os.fill(__space);
- __os.precision(std::numeric_limits<double>::max_digits10);
-
- __os << __x.t() << __space << __x.p()
- << __space << __x._M_nd;
-
- __os.flags(__flags);
- __os.fill(__fill);
- __os.precision(__precision);
- return __os;
- }
-
- template<typename _IntType,
- typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- binomial_distribution<_IntType>& __x)
- {
- typedef std::basic_istream<_CharT, _Traits> __istream_type;
- typedef typename __istream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __is.flags();
- __is.flags(__ios_base::dec | __ios_base::skipws);
-
- _IntType __t;
- double __p;
- __is >> __t >> __p >> __x._M_nd;
- __x.param(typename binomial_distribution<_IntType>::
- param_type(__t, __p));
-
- __is.flags(__flags);
- return __is;
- }
-
-
- template<typename _RealType>
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- std::exponential_distribution<_RealType>::
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- {
- __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>)
- __detail::_Adaptor<_UniformRandomNumberGenerator, result_type>
- __aurng(__urng);
- while (__f != __t)
- *__f++ = -std::log(result_type(1) - __aurng()) / __p.lambda();
- }
-
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const exponential_distribution<_RealType>& __x)
- {
- typedef std::basic_ostream<_CharT, _Traits> __ostream_type;
- typedef typename __ostream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __os.flags();
- const _CharT __fill = __os.fill();
- const std::streamsize __precision = __os.precision();
- __os.flags(__ios_base::scientific | __ios_base::left);
- __os.fill(__os.widen(' '));
- __os.precision(std::numeric_limits<_RealType>::max_digits10);
-
- __os << __x.lambda();
-
- __os.flags(__flags);
- __os.fill(__fill);
- __os.precision(__precision);
- return __os;
- }
-
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- exponential_distribution<_RealType>& __x)
- {
- typedef std::basic_istream<_CharT, _Traits> __istream_type;
- typedef typename __istream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __is.flags();
- __is.flags(__ios_base::dec | __ios_base::skipws);
-
- _RealType __lambda;
- __is >> __lambda;
- __x.param(typename exponential_distribution<_RealType>::
- param_type(__lambda));
-
- __is.flags(__flags);
- return __is;
- }
-
-
- /**
- * Polar method due to Marsaglia.
- *
- * Devroye, L. Non-Uniform Random Variates Generation. Springer-Verlag,
- * New York, 1986, Ch. V, Sect. 4.4.
- */
- template<typename _RealType>
- template<typename _UniformRandomNumberGenerator>
- typename normal_distribution<_RealType>::result_type
- normal_distribution<_RealType>::
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __param)
- {
- result_type __ret;
- __detail::_Adaptor<_UniformRandomNumberGenerator, result_type>
- __aurng(__urng);
-
- if (_M_saved_available)
- {
- _M_saved_available = false;
- __ret = _M_saved;
- }
- else
- {
- result_type __x, __y, __r2;
- do
- {
- __x = result_type(2.0) * __aurng() - 1.0;
- __y = result_type(2.0) * __aurng() - 1.0;
- __r2 = __x * __x + __y * __y;
- }
- while (__r2 > 1.0 || __r2 == 0.0);
-
- const result_type __mult = std::sqrt(-2 * std::log(__r2) / __r2);
- _M_saved = __x * __mult;
- _M_saved_available = true;
- __ret = __y * __mult;
- }
-
- __ret = __ret * __param.stddev() + __param.mean();
- return __ret;
- }
-
- template<typename _RealType>
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- normal_distribution<_RealType>::
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __param)
- {
- __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>)
-
- if (__f == __t)
- return;
-
- if (_M_saved_available)
- {
- _M_saved_available = false;
- *__f++ = _M_saved * __param.stddev() + __param.mean();
-
- if (__f == __t)
- return;
- }
-
- __detail::_Adaptor<_UniformRandomNumberGenerator, result_type>
- __aurng(__urng);
-
- while (__f + 1 < __t)
- {
- result_type __x, __y, __r2;
- do
- {
- __x = result_type(2.0) * __aurng() - 1.0;
- __y = result_type(2.0) * __aurng() - 1.0;
- __r2 = __x * __x + __y * __y;
- }
- while (__r2 > 1.0 || __r2 == 0.0);
-
- const result_type __mult = std::sqrt(-2 * std::log(__r2) / __r2);
- *__f++ = __y * __mult * __param.stddev() + __param.mean();
- *__f++ = __x * __mult * __param.stddev() + __param.mean();
- }
-
- if (__f != __t)
- {
- result_type __x, __y, __r2;
- do
- {
- __x = result_type(2.0) * __aurng() - 1.0;
- __y = result_type(2.0) * __aurng() - 1.0;
- __r2 = __x * __x + __y * __y;
- }
- while (__r2 > 1.0 || __r2 == 0.0);
-
- const result_type __mult = std::sqrt(-2 * std::log(__r2) / __r2);
- _M_saved = __x * __mult;
- _M_saved_available = true;
- *__f = __y * __mult * __param.stddev() + __param.mean();
- }
- }
-
- template<typename _RealType>
- bool
- operator==(const std::normal_distribution<_RealType>& __d1,
- const std::normal_distribution<_RealType>& __d2)
- {
- if (__d1._M_param == __d2._M_param
- && __d1._M_saved_available == __d2._M_saved_available)
- {
- if (__d1._M_saved_available
- && __d1._M_saved == __d2._M_saved)
- return true;
- else if(!__d1._M_saved_available)
- return true;
- else
- return false;
- }
- else
- return false;
- }
-
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const normal_distribution<_RealType>& __x)
- {
- typedef std::basic_ostream<_CharT, _Traits> __ostream_type;
- typedef typename __ostream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __os.flags();
- const _CharT __fill = __os.fill();
- const std::streamsize __precision = __os.precision();
- const _CharT __space = __os.widen(' ');
- __os.flags(__ios_base::scientific | __ios_base::left);
- __os.fill(__space);
- __os.precision(std::numeric_limits<_RealType>::max_digits10);
-
- __os << __x.mean() << __space << __x.stddev()
- << __space << __x._M_saved_available;
- if (__x._M_saved_available)
- __os << __space << __x._M_saved;
-
- __os.flags(__flags);
- __os.fill(__fill);
- __os.precision(__precision);
- return __os;
- }
-
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- normal_distribution<_RealType>& __x)
- {
- typedef std::basic_istream<_CharT, _Traits> __istream_type;
- typedef typename __istream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __is.flags();
- __is.flags(__ios_base::dec | __ios_base::skipws);
-
- double __mean, __stddev;
- __is >> __mean >> __stddev
- >> __x._M_saved_available;
- if (__x._M_saved_available)
- __is >> __x._M_saved;
- __x.param(typename normal_distribution<_RealType>::
- param_type(__mean, __stddev));
-
- __is.flags(__flags);
- return __is;
- }
-
-
- template<typename _RealType>
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- lognormal_distribution<_RealType>::
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- {
- __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>)
- while (__f != __t)
- *__f++ = std::exp(__p.s() * _M_nd(__urng) + __p.m());
- }
-
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const lognormal_distribution<_RealType>& __x)
- {
- typedef std::basic_ostream<_CharT, _Traits> __ostream_type;
- typedef typename __ostream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __os.flags();
- const _CharT __fill = __os.fill();
- const std::streamsize __precision = __os.precision();
- const _CharT __space = __os.widen(' ');
- __os.flags(__ios_base::scientific | __ios_base::left);
- __os.fill(__space);
- __os.precision(std::numeric_limits<_RealType>::max_digits10);
-
- __os << __x.m() << __space << __x.s()
- << __space << __x._M_nd;
-
- __os.flags(__flags);
- __os.fill(__fill);
- __os.precision(__precision);
- return __os;
- }
-
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- lognormal_distribution<_RealType>& __x)
- {
- typedef std::basic_istream<_CharT, _Traits> __istream_type;
- typedef typename __istream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __is.flags();
- __is.flags(__ios_base::dec | __ios_base::skipws);
-
- _RealType __m, __s;
- __is >> __m >> __s >> __x._M_nd;
- __x.param(typename lognormal_distribution<_RealType>::
- param_type(__m, __s));
-
- __is.flags(__flags);
- return __is;
- }
-
- template<typename _RealType>
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- std::chi_squared_distribution<_RealType>::
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng)
- {
- __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>)
- while (__f != __t)
- *__f++ = 2 * _M_gd(__urng);
- }
-
- template<typename _RealType>
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- std::chi_squared_distribution<_RealType>::
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const typename
- std::gamma_distribution<result_type>::param_type& __p)
- {
- __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>)
- while (__f != __t)
- *__f++ = 2 * _M_gd(__urng, __p);
- }
-
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const chi_squared_distribution<_RealType>& __x)
- {
- typedef std::basic_ostream<_CharT, _Traits> __ostream_type;
- typedef typename __ostream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __os.flags();
- const _CharT __fill = __os.fill();
- const std::streamsize __precision = __os.precision();
- const _CharT __space = __os.widen(' ');
- __os.flags(__ios_base::scientific | __ios_base::left);
- __os.fill(__space);
- __os.precision(std::numeric_limits<_RealType>::max_digits10);
-
- __os << __x.n() << __space << __x._M_gd;
-
- __os.flags(__flags);
- __os.fill(__fill);
- __os.precision(__precision);
- return __os;
- }
-
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- chi_squared_distribution<_RealType>& __x)
- {
- typedef std::basic_istream<_CharT, _Traits> __istream_type;
- typedef typename __istream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __is.flags();
- __is.flags(__ios_base::dec | __ios_base::skipws);
-
- _RealType __n;
- __is >> __n >> __x._M_gd;
- __x.param(typename chi_squared_distribution<_RealType>::
- param_type(__n));
-
- __is.flags(__flags);
- return __is;
- }
-
-
- template<typename _RealType>
- template<typename _UniformRandomNumberGenerator>
- typename cauchy_distribution<_RealType>::result_type
- cauchy_distribution<_RealType>::
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- {
- __detail::_Adaptor<_UniformRandomNumberGenerator, result_type>
- __aurng(__urng);
- _RealType __u;
- do
- __u = __aurng();
- while (__u == 0.5);
-
- const _RealType __pi = 3.1415926535897932384626433832795029L;
- return __p.a() + __p.b() * std::tan(__pi * __u);
- }
-
- template<typename _RealType>
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- cauchy_distribution<_RealType>::
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- {
- __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>)
- const _RealType __pi = 3.1415926535897932384626433832795029L;
- __detail::_Adaptor<_UniformRandomNumberGenerator, result_type>
- __aurng(__urng);
- while (__f != __t)
- {
- _RealType __u;
- do
- __u = __aurng();
- while (__u == 0.5);
-
- *__f++ = __p.a() + __p.b() * std::tan(__pi * __u);
- }
- }
-
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const cauchy_distribution<_RealType>& __x)
- {
- typedef std::basic_ostream<_CharT, _Traits> __ostream_type;
- typedef typename __ostream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __os.flags();
- const _CharT __fill = __os.fill();
- const std::streamsize __precision = __os.precision();
- const _CharT __space = __os.widen(' ');
- __os.flags(__ios_base::scientific | __ios_base::left);
- __os.fill(__space);
- __os.precision(std::numeric_limits<_RealType>::max_digits10);
-
- __os << __x.a() << __space << __x.b();
-
- __os.flags(__flags);
- __os.fill(__fill);
- __os.precision(__precision);
- return __os;
- }
-
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- cauchy_distribution<_RealType>& __x)
- {
- typedef std::basic_istream<_CharT, _Traits> __istream_type;
- typedef typename __istream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __is.flags();
- __is.flags(__ios_base::dec | __ios_base::skipws);
-
- _RealType __a, __b;
- __is >> __a >> __b;
- __x.param(typename cauchy_distribution<_RealType>::
- param_type(__a, __b));
-
- __is.flags(__flags);
- return __is;
- }
-
-
- template<typename _RealType>
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- std::fisher_f_distribution<_RealType>::
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng)
- {
- __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>)
- while (__f != __t)
- *__f++ = ((_M_gd_x(__urng) * n()) / (_M_gd_y(__urng) * m()));
- }
-
- template<typename _RealType>
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- std::fisher_f_distribution<_RealType>::
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- {
- __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>)
- typedef typename std::gamma_distribution<result_type>::param_type
- param_type;
- param_type __p1(__p.m() / 2);
- param_type __p2(__p.n() / 2);
- while (__f != __t)
- *__f++ = ((_M_gd_x(__urng, __p1) * n())
- / (_M_gd_y(__urng, __p2) * m()));
- }
-
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const fisher_f_distribution<_RealType>& __x)
- {
- typedef std::basic_ostream<_CharT, _Traits> __ostream_type;
- typedef typename __ostream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __os.flags();
- const _CharT __fill = __os.fill();
- const std::streamsize __precision = __os.precision();
- const _CharT __space = __os.widen(' ');
- __os.flags(__ios_base::scientific | __ios_base::left);
- __os.fill(__space);
- __os.precision(std::numeric_limits<_RealType>::max_digits10);
-
- __os << __x.m() << __space << __x.n()
- << __space << __x._M_gd_x << __space << __x._M_gd_y;
-
- __os.flags(__flags);
- __os.fill(__fill);
- __os.precision(__precision);
- return __os;
- }
-
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- fisher_f_distribution<_RealType>& __x)
- {
- typedef std::basic_istream<_CharT, _Traits> __istream_type;
- typedef typename __istream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __is.flags();
- __is.flags(__ios_base::dec | __ios_base::skipws);
-
- _RealType __m, __n;
- __is >> __m >> __n >> __x._M_gd_x >> __x._M_gd_y;
- __x.param(typename fisher_f_distribution<_RealType>::
- param_type(__m, __n));
-
- __is.flags(__flags);
- return __is;
- }
-
-
- template<typename _RealType>
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- std::student_t_distribution<_RealType>::
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng)
- {
- __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>)
- while (__f != __t)
- *__f++ = _M_nd(__urng) * std::sqrt(n() / _M_gd(__urng));
- }
-
- template<typename _RealType>
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- std::student_t_distribution<_RealType>::
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- {
- __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>)
- typename std::gamma_distribution<result_type>::param_type
- __p2(__p.n() / 2, 2);
- while (__f != __t)
- *__f++ = _M_nd(__urng) * std::sqrt(__p.n() / _M_gd(__urng, __p2));
- }
-
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const student_t_distribution<_RealType>& __x)
- {
- typedef std::basic_ostream<_CharT, _Traits> __ostream_type;
- typedef typename __ostream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __os.flags();
- const _CharT __fill = __os.fill();
- const std::streamsize __precision = __os.precision();
- const _CharT __space = __os.widen(' ');
- __os.flags(__ios_base::scientific | __ios_base::left);
- __os.fill(__space);
- __os.precision(std::numeric_limits<_RealType>::max_digits10);
-
- __os << __x.n() << __space << __x._M_nd << __space << __x._M_gd;
-
- __os.flags(__flags);
- __os.fill(__fill);
- __os.precision(__precision);
- return __os;
- }
-
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- student_t_distribution<_RealType>& __x)
- {
- typedef std::basic_istream<_CharT, _Traits> __istream_type;
- typedef typename __istream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __is.flags();
- __is.flags(__ios_base::dec | __ios_base::skipws);
-
- _RealType __n;
- __is >> __n >> __x._M_nd >> __x._M_gd;
- __x.param(typename student_t_distribution<_RealType>::param_type(__n));
-
- __is.flags(__flags);
- return __is;
- }
-
-
- template<typename _RealType>
- void
- gamma_distribution<_RealType>::param_type::
- _M_initialize()
- {
- _M_malpha = _M_alpha < 1.0 ? _M_alpha + _RealType(1.0) : _M_alpha;
-
- const _RealType __a1 = _M_malpha - _RealType(1.0) / _RealType(3.0);
- _M_a2 = _RealType(1.0) / std::sqrt(_RealType(9.0) * __a1);
- }
-
- /**
- * Marsaglia, G. and Tsang, W. W.
- * "A Simple Method for Generating Gamma Variables"
- * ACM Transactions on Mathematical Software, 26, 3, 363-372, 2000.
- */
- template<typename _RealType>
- template<typename _UniformRandomNumberGenerator>
- typename gamma_distribution<_RealType>::result_type
- gamma_distribution<_RealType>::
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __param)
- {
- __detail::_Adaptor<_UniformRandomNumberGenerator, result_type>
- __aurng(__urng);
-
- result_type __u, __v, __n;
- const result_type __a1 = (__param._M_malpha
- - _RealType(1.0) / _RealType(3.0));
-
- do
- {
- do
- {
- __n = _M_nd(__urng);
- __v = result_type(1.0) + __param._M_a2 * __n;
- }
- while (__v <= 0.0);
-
- __v = __v * __v * __v;
- __u = __aurng();
- }
- while (__u > result_type(1.0) - 0.331 * __n * __n * __n * __n
- && (std::log(__u) > (0.5 * __n * __n + __a1
- * (1.0 - __v + std::log(__v)))));
-
- if (__param.alpha() == __param._M_malpha)
- return __a1 * __v * __param.beta();
- else
- {
- do
- __u = __aurng();
- while (__u == 0.0);
-
- return (std::pow(__u, result_type(1.0) / __param.alpha())
- * __a1 * __v * __param.beta());
- }
- }
-
- template<typename _RealType>
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- gamma_distribution<_RealType>::
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __param)
- {
- __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>)
- __detail::_Adaptor<_UniformRandomNumberGenerator, result_type>
- __aurng(__urng);
-
- result_type __u, __v, __n;
- const result_type __a1 = (__param._M_malpha
- - _RealType(1.0) / _RealType(3.0));
-
- if (__param.alpha() == __param._M_malpha)
- while (__f != __t)
- {
- do
- {
- do
- {
- __n = _M_nd(__urng);
- __v = result_type(1.0) + __param._M_a2 * __n;
- }
- while (__v <= 0.0);
-
- __v = __v * __v * __v;
- __u = __aurng();
- }
- while (__u > result_type(1.0) - 0.331 * __n * __n * __n * __n
- && (std::log(__u) > (0.5 * __n * __n + __a1
- * (1.0 - __v + std::log(__v)))));
-
- *__f++ = __a1 * __v * __param.beta();
- }
- else
- while (__f != __t)
- {
- do
- {
- do
- {
- __n = _M_nd(__urng);
- __v = result_type(1.0) + __param._M_a2 * __n;
- }
- while (__v <= 0.0);
-
- __v = __v * __v * __v;
- __u = __aurng();
- }
- while (__u > result_type(1.0) - 0.331 * __n * __n * __n * __n
- && (std::log(__u) > (0.5 * __n * __n + __a1
- * (1.0 - __v + std::log(__v)))));
-
- do
- __u = __aurng();
- while (__u == 0.0);
-
- *__f++ = (std::pow(__u, result_type(1.0) / __param.alpha())
- * __a1 * __v * __param.beta());
- }
- }
-
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const gamma_distribution<_RealType>& __x)
- {
- typedef std::basic_ostream<_CharT, _Traits> __ostream_type;
- typedef typename __ostream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __os.flags();
- const _CharT __fill = __os.fill();
- const std::streamsize __precision = __os.precision();
- const _CharT __space = __os.widen(' ');
- __os.flags(__ios_base::scientific | __ios_base::left);
- __os.fill(__space);
- __os.precision(std::numeric_limits<_RealType>::max_digits10);
-
- __os << __x.alpha() << __space << __x.beta()
- << __space << __x._M_nd;
-
- __os.flags(__flags);
- __os.fill(__fill);
- __os.precision(__precision);
- return __os;
- }
-
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- gamma_distribution<_RealType>& __x)
- {
- typedef std::basic_istream<_CharT, _Traits> __istream_type;
- typedef typename __istream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __is.flags();
- __is.flags(__ios_base::dec | __ios_base::skipws);
-
- _RealType __alpha_val, __beta_val;
- __is >> __alpha_val >> __beta_val >> __x._M_nd;
- __x.param(typename gamma_distribution<_RealType>::
- param_type(__alpha_val, __beta_val));
-
- __is.flags(__flags);
- return __is;
- }
-
-
- template<typename _RealType>
- template<typename _UniformRandomNumberGenerator>
- typename weibull_distribution<_RealType>::result_type
- weibull_distribution<_RealType>::
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- {
- __detail::_Adaptor<_UniformRandomNumberGenerator, result_type>
- __aurng(__urng);
- return __p.b() * std::pow(-std::log(result_type(1) - __aurng()),
- result_type(1) / __p.a());
- }
-
- template<typename _RealType>
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- weibull_distribution<_RealType>::
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- {
- __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>)
- __detail::_Adaptor<_UniformRandomNumberGenerator, result_type>
- __aurng(__urng);
- auto __inv_a = result_type(1) / __p.a();
-
- while (__f != __t)
- *__f++ = __p.b() * std::pow(-std::log(result_type(1) - __aurng()),
- __inv_a);
- }
-
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const weibull_distribution<_RealType>& __x)
- {
- typedef std::basic_ostream<_CharT, _Traits> __ostream_type;
- typedef typename __ostream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __os.flags();
- const _CharT __fill = __os.fill();
- const std::streamsize __precision = __os.precision();
- const _CharT __space = __os.widen(' ');
- __os.flags(__ios_base::scientific | __ios_base::left);
- __os.fill(__space);
- __os.precision(std::numeric_limits<_RealType>::max_digits10);
-
- __os << __x.a() << __space << __x.b();
-
- __os.flags(__flags);
- __os.fill(__fill);
- __os.precision(__precision);
- return __os;
- }
-
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- weibull_distribution<_RealType>& __x)
- {
- typedef std::basic_istream<_CharT, _Traits> __istream_type;
- typedef typename __istream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __is.flags();
- __is.flags(__ios_base::dec | __ios_base::skipws);
-
- _RealType __a, __b;
- __is >> __a >> __b;
- __x.param(typename weibull_distribution<_RealType>::
- param_type(__a, __b));
-
- __is.flags(__flags);
- return __is;
- }
-
-
- template<typename _RealType>
- template<typename _UniformRandomNumberGenerator>
- typename extreme_value_distribution<_RealType>::result_type
- extreme_value_distribution<_RealType>::
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- {
- __detail::_Adaptor<_UniformRandomNumberGenerator, result_type>
- __aurng(__urng);
- return __p.a() - __p.b() * std::log(-std::log(result_type(1)
- - __aurng()));
- }
-
- template<typename _RealType>
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- extreme_value_distribution<_RealType>::
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- {
- __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>)
- __detail::_Adaptor<_UniformRandomNumberGenerator, result_type>
- __aurng(__urng);
-
- while (__f != __t)
- *__f++ = __p.a() - __p.b() * std::log(-std::log(result_type(1)
- - __aurng()));
- }
-
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const extreme_value_distribution<_RealType>& __x)
- {
- typedef std::basic_ostream<_CharT, _Traits> __ostream_type;
- typedef typename __ostream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __os.flags();
- const _CharT __fill = __os.fill();
- const std::streamsize __precision = __os.precision();
- const _CharT __space = __os.widen(' ');
- __os.flags(__ios_base::scientific | __ios_base::left);
- __os.fill(__space);
- __os.precision(std::numeric_limits<_RealType>::max_digits10);
-
- __os << __x.a() << __space << __x.b();
-
- __os.flags(__flags);
- __os.fill(__fill);
- __os.precision(__precision);
- return __os;
- }
-
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- extreme_value_distribution<_RealType>& __x)
- {
- typedef std::basic_istream<_CharT, _Traits> __istream_type;
- typedef typename __istream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __is.flags();
- __is.flags(__ios_base::dec | __ios_base::skipws);
-
- _RealType __a, __b;
- __is >> __a >> __b;
- __x.param(typename extreme_value_distribution<_RealType>::
- param_type(__a, __b));
-
- __is.flags(__flags);
- return __is;
- }
-
-
- template<typename _IntType>
- void
- discrete_distribution<_IntType>::param_type::
- _M_initialize()
- {
- if (_M_prob.size() < 2)
- {
- _M_prob.clear();
- return;
- }
-
- const double __sum = std::accumulate(_M_prob.begin(),
- _M_prob.end(), 0.0);
- // Now normalize the probabilites.
- __detail::__normalize(_M_prob.begin(), _M_prob.end(), _M_prob.begin(),
- __sum);
- // Accumulate partial sums.
- _M_cp.reserve(_M_prob.size());
- std::partial_sum(_M_prob.begin(), _M_prob.end(),
- std::back_inserter(_M_cp));
- // Make sure the last cumulative probability is one.
- _M_cp[_M_cp.size() - 1] = 1.0;
- }
-
- template<typename _IntType>
- template<typename _Func>
- discrete_distribution<_IntType>::param_type::
- param_type(size_t __nw, double __xmin, double __xmax, _Func __fw)
- : _M_prob(), _M_cp()
- {
- const size_t __n = __nw == 0 ? 1 : __nw;
- const double __delta = (__xmax - __xmin) / __n;
-
- _M_prob.reserve(__n);
- for (size_t __k = 0; __k < __nw; ++__k)
- _M_prob.push_back(__fw(__xmin + __k * __delta + 0.5 * __delta));
-
- _M_initialize();
- }
-
- template<typename _IntType>
- template<typename _UniformRandomNumberGenerator>
- typename discrete_distribution<_IntType>::result_type
- discrete_distribution<_IntType>::
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __param)
- {
- if (__param._M_cp.empty())
- return result_type(0);
-
- __detail::_Adaptor<_UniformRandomNumberGenerator, double>
- __aurng(__urng);
-
- const double __p = __aurng();
- auto __pos = std::lower_bound(__param._M_cp.begin(),
- __param._M_cp.end(), __p);
-
- return __pos - __param._M_cp.begin();
- }
-
- template<typename _IntType>
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- discrete_distribution<_IntType>::
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __param)
- {
- __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>)
-
- if (__param._M_cp.empty())
- {
- while (__f != __t)
- *__f++ = result_type(0);
- return;
- }
-
- __detail::_Adaptor<_UniformRandomNumberGenerator, double>
- __aurng(__urng);
-
- while (__f != __t)
- {
- const double __p = __aurng();
- auto __pos = std::lower_bound(__param._M_cp.begin(),
- __param._M_cp.end(), __p);
-
- *__f++ = __pos - __param._M_cp.begin();
- }
- }
-
- template<typename _IntType, typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const discrete_distribution<_IntType>& __x)
- {
- typedef std::basic_ostream<_CharT, _Traits> __ostream_type;
- typedef typename __ostream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __os.flags();
- const _CharT __fill = __os.fill();
- const std::streamsize __precision = __os.precision();
- const _CharT __space = __os.widen(' ');
- __os.flags(__ios_base::scientific | __ios_base::left);
- __os.fill(__space);
- __os.precision(std::numeric_limits<double>::max_digits10);
-
- std::vector<double> __prob = __x.probabilities();
- __os << __prob.size();
- for (auto __dit = __prob.begin(); __dit != __prob.end(); ++__dit)
- __os << __space << *__dit;
-
- __os.flags(__flags);
- __os.fill(__fill);
- __os.precision(__precision);
- return __os;
- }
-
- template<typename _IntType, typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- discrete_distribution<_IntType>& __x)
- {
- typedef std::basic_istream<_CharT, _Traits> __istream_type;
- typedef typename __istream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __is.flags();
- __is.flags(__ios_base::dec | __ios_base::skipws);
-
- size_t __n;
- __is >> __n;
-
- std::vector<double> __prob_vec;
- __prob_vec.reserve(__n);
- for (; __n != 0; --__n)
- {
- double __prob;
- __is >> __prob;
- __prob_vec.push_back(__prob);
- }
-
- __x.param(typename discrete_distribution<_IntType>::
- param_type(__prob_vec.begin(), __prob_vec.end()));
-
- __is.flags(__flags);
- return __is;
- }
-
-
- template<typename _RealType>
- void
- piecewise_constant_distribution<_RealType>::param_type::
- _M_initialize()
- {
- if (_M_int.size() < 2
- || (_M_int.size() == 2
- && _M_int[0] == _RealType(0)
- && _M_int[1] == _RealType(1)))
- {
- _M_int.clear();
- _M_den.clear();
- return;
- }
-
- const double __sum = std::accumulate(_M_den.begin(),
- _M_den.end(), 0.0);
-
- __detail::__normalize(_M_den.begin(), _M_den.end(), _M_den.begin(),
- __sum);
-
- _M_cp.reserve(_M_den.size());
- std::partial_sum(_M_den.begin(), _M_den.end(),
- std::back_inserter(_M_cp));
-
- // Make sure the last cumulative probability is one.
- _M_cp[_M_cp.size() - 1] = 1.0;
-
- for (size_t __k = 0; __k < _M_den.size(); ++__k)
- _M_den[__k] /= _M_int[__k + 1] - _M_int[__k];
- }
-
- template<typename _RealType>
- template<typename _InputIteratorB, typename _InputIteratorW>
- piecewise_constant_distribution<_RealType>::param_type::
- param_type(_InputIteratorB __bbegin,
- _InputIteratorB __bend,
- _InputIteratorW __wbegin)
- : _M_int(), _M_den(), _M_cp()
- {
- if (__bbegin != __bend)
- {
- for (;;)
- {
- _M_int.push_back(*__bbegin);
- ++__bbegin;
- if (__bbegin == __bend)
- break;
-
- _M_den.push_back(*__wbegin);
- ++__wbegin;
- }
- }
-
- _M_initialize();
- }
-
- template<typename _RealType>
- template<typename _Func>
- piecewise_constant_distribution<_RealType>::param_type::
- param_type(initializer_list<_RealType> __bl, _Func __fw)
- : _M_int(), _M_den(), _M_cp()
- {
- _M_int.reserve(__bl.size());
- for (auto __biter = __bl.begin(); __biter != __bl.end(); ++__biter)
- _M_int.push_back(*__biter);
-
- _M_den.reserve(_M_int.size() - 1);
- for (size_t __k = 0; __k < _M_int.size() - 1; ++__k)
- _M_den.push_back(__fw(0.5 * (_M_int[__k + 1] + _M_int[__k])));
-
- _M_initialize();
- }
-
- template<typename _RealType>
- template<typename _Func>
- piecewise_constant_distribution<_RealType>::param_type::
- param_type(size_t __nw, _RealType __xmin, _RealType __xmax, _Func __fw)
- : _M_int(), _M_den(), _M_cp()
- {
- const size_t __n = __nw == 0 ? 1 : __nw;
- const _RealType __delta = (__xmax - __xmin) / __n;
-
- _M_int.reserve(__n + 1);
- for (size_t __k = 0; __k <= __nw; ++__k)
- _M_int.push_back(__xmin + __k * __delta);
-
- _M_den.reserve(__n);
- for (size_t __k = 0; __k < __nw; ++__k)
- _M_den.push_back(__fw(_M_int[__k] + 0.5 * __delta));
-
- _M_initialize();
- }
-
- template<typename _RealType>
- template<typename _UniformRandomNumberGenerator>
- typename piecewise_constant_distribution<_RealType>::result_type
- piecewise_constant_distribution<_RealType>::
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __param)
- {
- __detail::_Adaptor<_UniformRandomNumberGenerator, double>
- __aurng(__urng);
-
- const double __p = __aurng();
- if (__param._M_cp.empty())
- return __p;
-
- auto __pos = std::lower_bound(__param._M_cp.begin(),
- __param._M_cp.end(), __p);
- const size_t __i = __pos - __param._M_cp.begin();
-
- const double __pref = __i > 0 ? __param._M_cp[__i - 1] : 0.0;
-
- return __param._M_int[__i] + (__p - __pref) / __param._M_den[__i];
- }
-
- template<typename _RealType>
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- piecewise_constant_distribution<_RealType>::
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __param)
- {
- __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>)
- __detail::_Adaptor<_UniformRandomNumberGenerator, double>
- __aurng(__urng);
-
- if (__param._M_cp.empty())
- {
- while (__f != __t)
- *__f++ = __aurng();
- return;
- }
-
- while (__f != __t)
- {
- const double __p = __aurng();
-
- auto __pos = std::lower_bound(__param._M_cp.begin(),
- __param._M_cp.end(), __p);
- const size_t __i = __pos - __param._M_cp.begin();
-
- const double __pref = __i > 0 ? __param._M_cp[__i - 1] : 0.0;
-
- *__f++ = (__param._M_int[__i]
- + (__p - __pref) / __param._M_den[__i]);
- }
- }
-
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const piecewise_constant_distribution<_RealType>& __x)
- {
- typedef std::basic_ostream<_CharT, _Traits> __ostream_type;
- typedef typename __ostream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __os.flags();
- const _CharT __fill = __os.fill();
- const std::streamsize __precision = __os.precision();
- const _CharT __space = __os.widen(' ');
- __os.flags(__ios_base::scientific | __ios_base::left);
- __os.fill(__space);
- __os.precision(std::numeric_limits<_RealType>::max_digits10);
-
- std::vector<_RealType> __int = __x.intervals();
- __os << __int.size() - 1;
-
- for (auto __xit = __int.begin(); __xit != __int.end(); ++__xit)
- __os << __space << *__xit;
-
- std::vector<double> __den = __x.densities();
- for (auto __dit = __den.begin(); __dit != __den.end(); ++__dit)
- __os << __space << *__dit;
-
- __os.flags(__flags);
- __os.fill(__fill);
- __os.precision(__precision);
- return __os;
- }
-
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- piecewise_constant_distribution<_RealType>& __x)
- {
- typedef std::basic_istream<_CharT, _Traits> __istream_type;
- typedef typename __istream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __is.flags();
- __is.flags(__ios_base::dec | __ios_base::skipws);
-
- size_t __n;
- __is >> __n;
-
- std::vector<_RealType> __int_vec;
- __int_vec.reserve(__n + 1);
- for (size_t __i = 0; __i <= __n; ++__i)
- {
- _RealType __int;
- __is >> __int;
- __int_vec.push_back(__int);
- }
-
- std::vector<double> __den_vec;
- __den_vec.reserve(__n);
- for (size_t __i = 0; __i < __n; ++__i)
- {
- double __den;
- __is >> __den;
- __den_vec.push_back(__den);
- }
-
- __x.param(typename piecewise_constant_distribution<_RealType>::
- param_type(__int_vec.begin(), __int_vec.end(), __den_vec.begin()));
-
- __is.flags(__flags);
- return __is;
- }
-
-
- template<typename _RealType>
- void
- piecewise_linear_distribution<_RealType>::param_type::
- _M_initialize()
- {
- if (_M_int.size() < 2
- || (_M_int.size() == 2
- && _M_int[0] == _RealType(0)
- && _M_int[1] == _RealType(1)
- && _M_den[0] == _M_den[1]))
- {
- _M_int.clear();
- _M_den.clear();
- return;
- }
-
- double __sum = 0.0;
- _M_cp.reserve(_M_int.size() - 1);
- _M_m.reserve(_M_int.size() - 1);
- for (size_t __k = 0; __k < _M_int.size() - 1; ++__k)
- {
- const _RealType __delta = _M_int[__k + 1] - _M_int[__k];
- __sum += 0.5 * (_M_den[__k + 1] + _M_den[__k]) * __delta;
- _M_cp.push_back(__sum);
- _M_m.push_back((_M_den[__k + 1] - _M_den[__k]) / __delta);
- }
-
- // Now normalize the densities...
- __detail::__normalize(_M_den.begin(), _M_den.end(), _M_den.begin(),
- __sum);
- // ... and partial sums...
- __detail::__normalize(_M_cp.begin(), _M_cp.end(), _M_cp.begin(), __sum);
- // ... and slopes.
- __detail::__normalize(_M_m.begin(), _M_m.end(), _M_m.begin(), __sum);
-
- // Make sure the last cumulative probablility is one.
- _M_cp[_M_cp.size() - 1] = 1.0;
- }
-
- template<typename _RealType>
- template<typename _InputIteratorB, typename _InputIteratorW>
- piecewise_linear_distribution<_RealType>::param_type::
- param_type(_InputIteratorB __bbegin,
- _InputIteratorB __bend,
- _InputIteratorW __wbegin)
- : _M_int(), _M_den(), _M_cp(), _M_m()
- {
- for (; __bbegin != __bend; ++__bbegin, ++__wbegin)
- {
- _M_int.push_back(*__bbegin);
- _M_den.push_back(*__wbegin);
- }
-
- _M_initialize();
- }
-
- template<typename _RealType>
- template<typename _Func>
- piecewise_linear_distribution<_RealType>::param_type::
- param_type(initializer_list<_RealType> __bl, _Func __fw)
- : _M_int(), _M_den(), _M_cp(), _M_m()
- {
- _M_int.reserve(__bl.size());
- _M_den.reserve(__bl.size());
- for (auto __biter = __bl.begin(); __biter != __bl.end(); ++__biter)
- {
- _M_int.push_back(*__biter);
- _M_den.push_back(__fw(*__biter));
- }
-
- _M_initialize();
- }
-
- template<typename _RealType>
- template<typename _Func>
- piecewise_linear_distribution<_RealType>::param_type::
- param_type(size_t __nw, _RealType __xmin, _RealType __xmax, _Func __fw)
- : _M_int(), _M_den(), _M_cp(), _M_m()
- {
- const size_t __n = __nw == 0 ? 1 : __nw;
- const _RealType __delta = (__xmax - __xmin) / __n;
-
- _M_int.reserve(__n + 1);
- _M_den.reserve(__n + 1);
- for (size_t __k = 0; __k <= __nw; ++__k)
- {
- _M_int.push_back(__xmin + __k * __delta);
- _M_den.push_back(__fw(_M_int[__k] + __delta));
- }
-
- _M_initialize();
- }
-
- template<typename _RealType>
- template<typename _UniformRandomNumberGenerator>
- typename piecewise_linear_distribution<_RealType>::result_type
- piecewise_linear_distribution<_RealType>::
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __param)
- {
- __detail::_Adaptor<_UniformRandomNumberGenerator, double>
- __aurng(__urng);
-
- const double __p = __aurng();
- if (__param._M_cp.empty())
- return __p;
-
- auto __pos = std::lower_bound(__param._M_cp.begin(),
- __param._M_cp.end(), __p);
- const size_t __i = __pos - __param._M_cp.begin();
-
- const double __pref = __i > 0 ? __param._M_cp[__i - 1] : 0.0;
-
- const double __a = 0.5 * __param._M_m[__i];
- const double __b = __param._M_den[__i];
- const double __cm = __p - __pref;
-
- _RealType __x = __param._M_int[__i];
- if (__a == 0)
- __x += __cm / __b;
- else
- {
- const double __d = __b * __b + 4.0 * __a * __cm;
- __x += 0.5 * (std::sqrt(__d) - __b) / __a;
- }
-
- return __x;
- }
-
- template<typename _RealType>
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- piecewise_linear_distribution<_RealType>::
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __param)
- {
- __glibcxx_function_requires(_ForwardIteratorConcept<_ForwardIterator>)
- // We could duplicate everything from operator()...
- while (__f != __t)
- *__f++ = this->operator()(__urng, __param);
- }
-
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const piecewise_linear_distribution<_RealType>& __x)
- {
- typedef std::basic_ostream<_CharT, _Traits> __ostream_type;
- typedef typename __ostream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __os.flags();
- const _CharT __fill = __os.fill();
- const std::streamsize __precision = __os.precision();
- const _CharT __space = __os.widen(' ');
- __os.flags(__ios_base::scientific | __ios_base::left);
- __os.fill(__space);
- __os.precision(std::numeric_limits<_RealType>::max_digits10);
-
- std::vector<_RealType> __int = __x.intervals();
- __os << __int.size() - 1;
-
- for (auto __xit = __int.begin(); __xit != __int.end(); ++__xit)
- __os << __space << *__xit;
-
- std::vector<double> __den = __x.densities();
- for (auto __dit = __den.begin(); __dit != __den.end(); ++__dit)
- __os << __space << *__dit;
-
- __os.flags(__flags);
- __os.fill(__fill);
- __os.precision(__precision);
- return __os;
- }
-
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- piecewise_linear_distribution<_RealType>& __x)
- {
- typedef std::basic_istream<_CharT, _Traits> __istream_type;
- typedef typename __istream_type::ios_base __ios_base;
-
- const typename __ios_base::fmtflags __flags = __is.flags();
- __is.flags(__ios_base::dec | __ios_base::skipws);
-
- size_t __n;
- __is >> __n;
-
- std::vector<_RealType> __int_vec;
- __int_vec.reserve(__n + 1);
- for (size_t __i = 0; __i <= __n; ++__i)
- {
- _RealType __int;
- __is >> __int;
- __int_vec.push_back(__int);
- }
-
- std::vector<double> __den_vec;
- __den_vec.reserve(__n + 1);
- for (size_t __i = 0; __i <= __n; ++__i)
- {
- double __den;
- __is >> __den;
- __den_vec.push_back(__den);
- }
-
- __x.param(typename piecewise_linear_distribution<_RealType>::
- param_type(__int_vec.begin(), __int_vec.end(), __den_vec.begin()));
-
- __is.flags(__flags);
- return __is;
- }
-
-
- template<typename _IntType>
- seed_seq::seed_seq(std::initializer_list<_IntType> __il)
- {
- for (auto __iter = __il.begin(); __iter != __il.end(); ++__iter)
- _M_v.push_back(__detail::__mod<result_type,
- __detail::_Shift<result_type, 32>::__value>(*__iter));
- }
-
- template<typename _InputIterator>
- seed_seq::seed_seq(_InputIterator __begin, _InputIterator __end)
- {
- for (_InputIterator __iter = __begin; __iter != __end; ++__iter)
- _M_v.push_back(__detail::__mod<result_type,
- __detail::_Shift<result_type, 32>::__value>(*__iter));
- }
-
- template<typename _RandomAccessIterator>
- void
- seed_seq::generate(_RandomAccessIterator __begin,
- _RandomAccessIterator __end)
- {
- typedef typename iterator_traits<_RandomAccessIterator>::value_type
- _Type;
-
- if (__begin == __end)
- return;
-
- std::fill(__begin, __end, _Type(0x8b8b8b8bu));
-
- const size_t __n = __end - __begin;
- const size_t __s = _M_v.size();
- const size_t __t = (__n >= 623) ? 11
- : (__n >= 68) ? 7
- : (__n >= 39) ? 5
- : (__n >= 7) ? 3
- : (__n - 1) / 2;
- const size_t __p = (__n - __t) / 2;
- const size_t __q = __p + __t;
- const size_t __m = std::max(size_t(__s + 1), __n);
-
- for (size_t __k = 0; __k < __m; ++__k)
- {
- _Type __arg = (__begin[__k % __n]
- ^ __begin[(__k + __p) % __n]
- ^ __begin[(__k - 1) % __n]);
- _Type __r1 = __arg ^ (__arg >> 27);
- __r1 = __detail::__mod<_Type,
- __detail::_Shift<_Type, 32>::__value>(1664525u * __r1);
- _Type __r2 = __r1;
- if (__k == 0)
- __r2 += __s;
- else if (__k <= __s)
- __r2 += __k % __n + _M_v[__k - 1];
- else
- __r2 += __k % __n;
- __r2 = __detail::__mod<_Type,
- __detail::_Shift<_Type, 32>::__value>(__r2);
- __begin[(__k + __p) % __n] += __r1;
- __begin[(__k + __q) % __n] += __r2;
- __begin[__k % __n] = __r2;
- }
-
- for (size_t __k = __m; __k < __m + __n; ++__k)
- {
- _Type __arg = (__begin[__k % __n]
- + __begin[(__k + __p) % __n]
- + __begin[(__k - 1) % __n]);
- _Type __r3 = __arg ^ (__arg >> 27);
- __r3 = __detail::__mod<_Type,
- __detail::_Shift<_Type, 32>::__value>(1566083941u * __r3);
- _Type __r4 = __r3 - __k % __n;
- __r4 = __detail::__mod<_Type,
- __detail::_Shift<_Type, 32>::__value>(__r4);
- __begin[(__k + __p) % __n] ^= __r3;
- __begin[(__k + __q) % __n] ^= __r4;
- __begin[__k % __n] = __r4;
- }
- }
-
- template<typename _RealType, size_t __bits,
- typename _UniformRandomNumberGenerator>
- _RealType
- generate_canonical(_UniformRandomNumberGenerator& __urng)
- {
- const size_t __b
- = std::min(static_cast<size_t>(std::numeric_limits<_RealType>::digits),
- __bits);
- const long double __r = static_cast<long double>(__urng.max())
- - static_cast<long double>(__urng.min()) + 1.0L;
- const size_t __log2r = std::log(__r) / std::log(2.0L);
- size_t __k = std::max<size_t>(1UL, (__b + __log2r - 1UL) / __log2r);
- _RealType __sum = _RealType(0);
- _RealType __tmp = _RealType(1);
- for (; __k != 0; --__k)
- {
- __sum += _RealType(__urng() - __urng.min()) * __tmp;
- __tmp *= __r;
- }
- return __sum / __tmp;
- }
-
-_GLIBCXX_END_NAMESPACE_VERSION
-} // namespace
-
-#endif