diff options
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.tcc | 3484 |
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 |