diff options
Diffstat (limited to 'gcc-4.9/libstdc++-v3/include/ext/random.tcc')
| -rw-r--r-- | gcc-4.9/libstdc++-v3/include/ext/random.tcc | 1420 |
1 files changed, 1420 insertions, 0 deletions
diff --git a/gcc-4.9/libstdc++-v3/include/ext/random.tcc b/gcc-4.9/libstdc++-v3/include/ext/random.tcc new file mode 100644 index 0000000..dd7a14a --- /dev/null +++ b/gcc-4.9/libstdc++-v3/include/ext/random.tcc @@ -0,0 +1,1420 @@ +// Random number extensions -*- C++ -*- + +// Copyright (C) 2012-2014 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 ext/random.tcc + * This is an internal header file, included by other library headers. + * Do not attempt to use it directly. @headername{ext/random} + */ + +#ifndef _EXT_RANDOM_TCC +#define _EXT_RANDOM_TCC 1 + +#pragma GCC system_header + +namespace __gnu_cxx _GLIBCXX_VISIBILITY(default) +{ +_GLIBCXX_BEGIN_NAMESPACE_VERSION + +#if __BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__ + + template<typename _UIntType, size_t __m, + size_t __pos1, size_t __sl1, size_t __sl2, + size_t __sr1, size_t __sr2, + uint32_t __msk1, uint32_t __msk2, + uint32_t __msk3, uint32_t __msk4, + uint32_t __parity1, uint32_t __parity2, + uint32_t __parity3, uint32_t __parity4> + void simd_fast_mersenne_twister_engine<_UIntType, __m, + __pos1, __sl1, __sl2, __sr1, __sr2, + __msk1, __msk2, __msk3, __msk4, + __parity1, __parity2, __parity3, + __parity4>:: + seed(_UIntType __seed) + { + _M_state32[0] = static_cast<uint32_t>(__seed); + for (size_t __i = 1; __i < _M_nstate32; ++__i) + _M_state32[__i] = (1812433253UL + * (_M_state32[__i - 1] ^ (_M_state32[__i - 1] >> 30)) + + __i); + _M_pos = state_size; + _M_period_certification(); + } + + + namespace { + + inline uint32_t _Func1(uint32_t __x) + { + return (__x ^ (__x >> 27)) * UINT32_C(1664525); + } + + inline uint32_t _Func2(uint32_t __x) + { + return (__x ^ (__x >> 27)) * UINT32_C(1566083941); + } + + } + + + template<typename _UIntType, size_t __m, + size_t __pos1, size_t __sl1, size_t __sl2, + size_t __sr1, size_t __sr2, + uint32_t __msk1, uint32_t __msk2, + uint32_t __msk3, uint32_t __msk4, + uint32_t __parity1, uint32_t __parity2, + uint32_t __parity3, uint32_t __parity4> + template<typename _Sseq> + typename std::enable_if<std::is_class<_Sseq>::value>::type + simd_fast_mersenne_twister_engine<_UIntType, __m, + __pos1, __sl1, __sl2, __sr1, __sr2, + __msk1, __msk2, __msk3, __msk4, + __parity1, __parity2, __parity3, + __parity4>:: + seed(_Sseq& __q) + { + size_t __lag; + + if (_M_nstate32 >= 623) + __lag = 11; + else if (_M_nstate32 >= 68) + __lag = 7; + else if (_M_nstate32 >= 39) + __lag = 5; + else + __lag = 3; + const size_t __mid = (_M_nstate32 - __lag) / 2; + + std::fill(_M_state32, _M_state32 + _M_nstate32, UINT32_C(0x8b8b8b8b)); + uint32_t __arr[_M_nstate32]; + __q.generate(__arr + 0, __arr + _M_nstate32); + + uint32_t __r = _Func1(_M_state32[0] ^ _M_state32[__mid] + ^ _M_state32[_M_nstate32 - 1]); + _M_state32[__mid] += __r; + __r += _M_nstate32; + _M_state32[__mid + __lag] += __r; + _M_state32[0] = __r; + + for (size_t __i = 1, __j = 0; __j < _M_nstate32; ++__j) + { + __r = _Func1(_M_state32[__i] + ^ _M_state32[(__i + __mid) % _M_nstate32] + ^ _M_state32[(__i + _M_nstate32 - 1) % _M_nstate32]); + _M_state32[(__i + __mid) % _M_nstate32] += __r; + __r += __arr[__j] + __i; + _M_state32[(__i + __mid + __lag) % _M_nstate32] += __r; + _M_state32[__i] = __r; + __i = (__i + 1) % _M_nstate32; + } + for (size_t __j = 0; __j < _M_nstate32; ++__j) + { + const size_t __i = (__j + 1) % _M_nstate32; + __r = _Func2(_M_state32[__i] + + _M_state32[(__i + __mid) % _M_nstate32] + + _M_state32[(__i + _M_nstate32 - 1) % _M_nstate32]); + _M_state32[(__i + __mid) % _M_nstate32] ^= __r; + __r -= __i; + _M_state32[(__i + __mid + __lag) % _M_nstate32] ^= __r; + _M_state32[__i] = __r; + } + + _M_pos = state_size; + _M_period_certification(); + } + + + template<typename _UIntType, size_t __m, + size_t __pos1, size_t __sl1, size_t __sl2, + size_t __sr1, size_t __sr2, + uint32_t __msk1, uint32_t __msk2, + uint32_t __msk3, uint32_t __msk4, + uint32_t __parity1, uint32_t __parity2, + uint32_t __parity3, uint32_t __parity4> + void simd_fast_mersenne_twister_engine<_UIntType, __m, + __pos1, __sl1, __sl2, __sr1, __sr2, + __msk1, __msk2, __msk3, __msk4, + __parity1, __parity2, __parity3, + __parity4>:: + _M_period_certification(void) + { + static const uint32_t __parity[4] = { __parity1, __parity2, + __parity3, __parity4 }; + uint32_t __inner = 0; + for (size_t __i = 0; __i < 4; ++__i) + if (__parity[__i] != 0) + __inner ^= _M_state32[__i] & __parity[__i]; + + if (__builtin_parity(__inner) & 1) + return; + for (size_t __i = 0; __i < 4; ++__i) + if (__parity[__i] != 0) + { + _M_state32[__i] ^= 1 << (__builtin_ffs(__parity[__i]) - 1); + return; + } + __builtin_unreachable(); + } + + + template<typename _UIntType, size_t __m, + size_t __pos1, size_t __sl1, size_t __sl2, + size_t __sr1, size_t __sr2, + uint32_t __msk1, uint32_t __msk2, + uint32_t __msk3, uint32_t __msk4, + uint32_t __parity1, uint32_t __parity2, + uint32_t __parity3, uint32_t __parity4> + void simd_fast_mersenne_twister_engine<_UIntType, __m, + __pos1, __sl1, __sl2, __sr1, __sr2, + __msk1, __msk2, __msk3, __msk4, + __parity1, __parity2, __parity3, + __parity4>:: + discard(unsigned long long __z) + { + while (__z > state_size - _M_pos) + { + __z -= state_size - _M_pos; + + _M_gen_rand(); + } + + _M_pos += __z; + } + + +#ifndef _GLIBCXX_OPT_HAVE_RANDOM_SFMT_GEN_READ + + namespace { + + template<size_t __shift> + inline void __rshift(uint32_t *__out, const uint32_t *__in) + { + uint64_t __th = ((static_cast<uint64_t>(__in[3]) << 32) + | static_cast<uint64_t>(__in[2])); + uint64_t __tl = ((static_cast<uint64_t>(__in[1]) << 32) + | static_cast<uint64_t>(__in[0])); + + uint64_t __oh = __th >> (__shift * 8); + uint64_t __ol = __tl >> (__shift * 8); + __ol |= __th << (64 - __shift * 8); + __out[1] = static_cast<uint32_t>(__ol >> 32); + __out[0] = static_cast<uint32_t>(__ol); + __out[3] = static_cast<uint32_t>(__oh >> 32); + __out[2] = static_cast<uint32_t>(__oh); + } + + + template<size_t __shift> + inline void __lshift(uint32_t *__out, const uint32_t *__in) + { + uint64_t __th = ((static_cast<uint64_t>(__in[3]) << 32) + | static_cast<uint64_t>(__in[2])); + uint64_t __tl = ((static_cast<uint64_t>(__in[1]) << 32) + | static_cast<uint64_t>(__in[0])); + + uint64_t __oh = __th << (__shift * 8); + uint64_t __ol = __tl << (__shift * 8); + __oh |= __tl >> (64 - __shift * 8); + __out[1] = static_cast<uint32_t>(__ol >> 32); + __out[0] = static_cast<uint32_t>(__ol); + __out[3] = static_cast<uint32_t>(__oh >> 32); + __out[2] = static_cast<uint32_t>(__oh); + } + + + template<size_t __sl1, size_t __sl2, size_t __sr1, size_t __sr2, + uint32_t __msk1, uint32_t __msk2, uint32_t __msk3, uint32_t __msk4> + inline void __recursion(uint32_t *__r, + const uint32_t *__a, const uint32_t *__b, + const uint32_t *__c, const uint32_t *__d) + { + uint32_t __x[4]; + uint32_t __y[4]; + + __lshift<__sl2>(__x, __a); + __rshift<__sr2>(__y, __c); + __r[0] = (__a[0] ^ __x[0] ^ ((__b[0] >> __sr1) & __msk1) + ^ __y[0] ^ (__d[0] << __sl1)); + __r[1] = (__a[1] ^ __x[1] ^ ((__b[1] >> __sr1) & __msk2) + ^ __y[1] ^ (__d[1] << __sl1)); + __r[2] = (__a[2] ^ __x[2] ^ ((__b[2] >> __sr1) & __msk3) + ^ __y[2] ^ (__d[2] << __sl1)); + __r[3] = (__a[3] ^ __x[3] ^ ((__b[3] >> __sr1) & __msk4) + ^ __y[3] ^ (__d[3] << __sl1)); + } + + } + + + template<typename _UIntType, size_t __m, + size_t __pos1, size_t __sl1, size_t __sl2, + size_t __sr1, size_t __sr2, + uint32_t __msk1, uint32_t __msk2, + uint32_t __msk3, uint32_t __msk4, + uint32_t __parity1, uint32_t __parity2, + uint32_t __parity3, uint32_t __parity4> + void simd_fast_mersenne_twister_engine<_UIntType, __m, + __pos1, __sl1, __sl2, __sr1, __sr2, + __msk1, __msk2, __msk3, __msk4, + __parity1, __parity2, __parity3, + __parity4>:: + _M_gen_rand(void) + { + const uint32_t *__r1 = &_M_state32[_M_nstate32 - 8]; + const uint32_t *__r2 = &_M_state32[_M_nstate32 - 4]; + static constexpr size_t __pos1_32 = __pos1 * 4; + + size_t __i; + for (__i = 0; __i < _M_nstate32 - __pos1_32; __i += 4) + { + __recursion<__sl1, __sl2, __sr1, __sr2, + __msk1, __msk2, __msk3, __msk4> + (&_M_state32[__i], &_M_state32[__i], + &_M_state32[__i + __pos1_32], __r1, __r2); + __r1 = __r2; + __r2 = &_M_state32[__i]; + } + + for (; __i < _M_nstate32; __i += 4) + { + __recursion<__sl1, __sl2, __sr1, __sr2, + __msk1, __msk2, __msk3, __msk4> + (&_M_state32[__i], &_M_state32[__i], + &_M_state32[__i + __pos1_32 - _M_nstate32], __r1, __r2); + __r1 = __r2; + __r2 = &_M_state32[__i]; + } + + _M_pos = 0; + } + +#endif + +#ifndef _GLIBCXX_OPT_HAVE_RANDOM_SFMT_OPERATOREQUAL + template<typename _UIntType, size_t __m, + size_t __pos1, size_t __sl1, size_t __sl2, + size_t __sr1, size_t __sr2, + uint32_t __msk1, uint32_t __msk2, + uint32_t __msk3, uint32_t __msk4, + uint32_t __parity1, uint32_t __parity2, + uint32_t __parity3, uint32_t __parity4> + bool + operator==(const __gnu_cxx::simd_fast_mersenne_twister_engine<_UIntType, + __m, __pos1, __sl1, __sl2, __sr1, __sr2, + __msk1, __msk2, __msk3, __msk4, + __parity1, __parity2, __parity3, __parity4>& __lhs, + const __gnu_cxx::simd_fast_mersenne_twister_engine<_UIntType, + __m, __pos1, __sl1, __sl2, __sr1, __sr2, + __msk1, __msk2, __msk3, __msk4, + __parity1, __parity2, __parity3, __parity4>& __rhs) + { + typedef __gnu_cxx::simd_fast_mersenne_twister_engine<_UIntType, + __m, __pos1, __sl1, __sl2, __sr1, __sr2, + __msk1, __msk2, __msk3, __msk4, + __parity1, __parity2, __parity3, __parity4> __engine; + return (std::equal(__lhs._M_stateT, + __lhs._M_stateT + __engine::state_size, + __rhs._M_stateT) + && __lhs._M_pos == __rhs._M_pos); + } +#endif + + template<typename _UIntType, size_t __m, + size_t __pos1, size_t __sl1, size_t __sl2, + size_t __sr1, size_t __sr2, + uint32_t __msk1, uint32_t __msk2, + uint32_t __msk3, uint32_t __msk4, + uint32_t __parity1, uint32_t __parity2, + uint32_t __parity3, uint32_t __parity4, + typename _CharT, typename _Traits> + std::basic_ostream<_CharT, _Traits>& + operator<<(std::basic_ostream<_CharT, _Traits>& __os, + const __gnu_cxx::simd_fast_mersenne_twister_engine<_UIntType, + __m, __pos1, __sl1, __sl2, __sr1, __sr2, + __msk1, __msk2, __msk3, __msk4, + __parity1, __parity2, __parity3, __parity4>& __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 < __x._M_nstate32; ++__i) + __os << __x._M_state32[__i] << __space; + __os << __x._M_pos; + + __os.flags(__flags); + __os.fill(__fill); + return __os; + } + + + template<typename _UIntType, size_t __m, + size_t __pos1, size_t __sl1, size_t __sl2, + size_t __sr1, size_t __sr2, + uint32_t __msk1, uint32_t __msk2, + uint32_t __msk3, uint32_t __msk4, + uint32_t __parity1, uint32_t __parity2, + uint32_t __parity3, uint32_t __parity4, + typename _CharT, typename _Traits> + std::basic_istream<_CharT, _Traits>& + operator>>(std::basic_istream<_CharT, _Traits>& __is, + __gnu_cxx::simd_fast_mersenne_twister_engine<_UIntType, + __m, __pos1, __sl1, __sl2, __sr1, __sr2, + __msk1, __msk2, __msk3, __msk4, + __parity1, __parity2, __parity3, __parity4>& __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 < __x._M_nstate32; ++__i) + __is >> __x._M_state32[__i]; + __is >> __x._M_pos; + + __is.flags(__flags); + return __is; + } + +#endif // __BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__ + + /** + * Iteration method due to M.D. J<o:>hnk. + * + * M.D. J<o:>hnk, Erzeugung von betaverteilten und gammaverteilten + * Zufallszahlen, Metrika, Volume 8, 1964 + */ + template<typename _RealType> + template<typename _UniformRandomNumberGenerator> + typename beta_distribution<_RealType>::result_type + beta_distribution<_RealType>:: + operator()(_UniformRandomNumberGenerator& __urng, + const param_type& __param) + { + std::__detail::_Adaptor<_UniformRandomNumberGenerator, result_type> + __aurng(__urng); + + result_type __x, __y; + do + { + __x = std::exp(std::log(__aurng()) / __param.alpha()); + __y = std::exp(std::log(__aurng()) / __param.beta()); + } + while (__x + __y > result_type(1)); + + return __x / (__x + __y); + } + + template<typename _RealType> + template<typename _OutputIterator, + typename _UniformRandomNumberGenerator> + void + beta_distribution<_RealType>:: + __generate_impl(_OutputIterator __f, _OutputIterator __t, + _UniformRandomNumberGenerator& __urng, + const param_type& __param) + { + __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator>) + + std::__detail::_Adaptor<_UniformRandomNumberGenerator, result_type> + __aurng(__urng); + + while (__f != __t) + { + result_type __x, __y; + do + { + __x = std::exp(std::log(__aurng()) / __param.alpha()); + __y = std::exp(std::log(__aurng()) / __param.beta()); + } + while (__x + __y > result_type(1)); + + *__f++ = __x / (__x + __y); + } + } + + template<typename _RealType, typename _CharT, typename _Traits> + std::basic_ostream<_CharT, _Traits>& + operator<<(std::basic_ostream<_CharT, _Traits>& __os, + const __gnu_cxx::beta_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(); + + __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, + __gnu_cxx::beta_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.param(typename __gnu_cxx::beta_distribution<_RealType>:: + param_type(__alpha_val, __beta_val)); + + __is.flags(__flags); + return __is; + } + + + template<std::size_t _Dimen, typename _RealType> + template<typename _InputIterator1, typename _InputIterator2> + void + normal_mv_distribution<_Dimen, _RealType>::param_type:: + _M_init_full(_InputIterator1 __meanbegin, _InputIterator1 __meanend, + _InputIterator2 __varcovbegin, _InputIterator2 __varcovend) + { + __glibcxx_function_requires(_InputIteratorConcept<_InputIterator1>) + __glibcxx_function_requires(_InputIteratorConcept<_InputIterator2>) + std::fill(std::copy(__meanbegin, __meanend, _M_mean.begin()), + _M_mean.end(), _RealType(0)); + + // Perform the Cholesky decomposition + auto __w = _M_t.begin(); + for (size_t __j = 0; __j < _Dimen; ++__j) + { + _RealType __sum = _RealType(0); + + auto __slitbegin = __w; + auto __cit = _M_t.begin(); + for (size_t __i = 0; __i < __j; ++__i) + { + auto __slit = __slitbegin; + _RealType __s = *__varcovbegin++; + for (size_t __k = 0; __k < __i; ++__k) + __s -= *__slit++ * *__cit++; + + *__w++ = __s /= *__cit++; + __sum += __s * __s; + } + + __sum = *__varcovbegin - __sum; + if (__builtin_expect(__sum <= _RealType(0), 0)) + std::__throw_runtime_error(__N("normal_mv_distribution::" + "param_type::_M_init_full")); + *__w++ = std::sqrt(__sum); + + std::advance(__varcovbegin, _Dimen - __j); + } + } + + template<std::size_t _Dimen, typename _RealType> + template<typename _InputIterator1, typename _InputIterator2> + void + normal_mv_distribution<_Dimen, _RealType>::param_type:: + _M_init_lower(_InputIterator1 __meanbegin, _InputIterator1 __meanend, + _InputIterator2 __varcovbegin, _InputIterator2 __varcovend) + { + __glibcxx_function_requires(_InputIteratorConcept<_InputIterator1>) + __glibcxx_function_requires(_InputIteratorConcept<_InputIterator2>) + std::fill(std::copy(__meanbegin, __meanend, _M_mean.begin()), + _M_mean.end(), _RealType(0)); + + // Perform the Cholesky decomposition + auto __w = _M_t.begin(); + for (size_t __j = 0; __j < _Dimen; ++__j) + { + _RealType __sum = _RealType(0); + + auto __slitbegin = __w; + auto __cit = _M_t.begin(); + for (size_t __i = 0; __i < __j; ++__i) + { + auto __slit = __slitbegin; + _RealType __s = *__varcovbegin++; + for (size_t __k = 0; __k < __i; ++__k) + __s -= *__slit++ * *__cit++; + + *__w++ = __s /= *__cit++; + __sum += __s * __s; + } + + __sum = *__varcovbegin++ - __sum; + if (__builtin_expect(__sum <= _RealType(0), 0)) + std::__throw_runtime_error(__N("normal_mv_distribution::" + "param_type::_M_init_full")); + *__w++ = std::sqrt(__sum); + } + } + + template<std::size_t _Dimen, typename _RealType> + template<typename _InputIterator1, typename _InputIterator2> + void + normal_mv_distribution<_Dimen, _RealType>::param_type:: + _M_init_diagonal(_InputIterator1 __meanbegin, _InputIterator1 __meanend, + _InputIterator2 __varbegin, _InputIterator2 __varend) + { + __glibcxx_function_requires(_InputIteratorConcept<_InputIterator1>) + __glibcxx_function_requires(_InputIteratorConcept<_InputIterator2>) + std::fill(std::copy(__meanbegin, __meanend, _M_mean.begin()), + _M_mean.end(), _RealType(0)); + + auto __w = _M_t.begin(); + size_t __step = 0; + while (__varbegin != __varend) + { + std::fill_n(__w, __step, _RealType(0)); + __w += __step++; + if (__builtin_expect(*__varbegin < _RealType(0), 0)) + std::__throw_runtime_error(__N("normal_mv_distribution::" + "param_type::_M_init_diagonal")); + *__w++ = std::sqrt(*__varbegin++); + } + } + + template<std::size_t _Dimen, typename _RealType> + template<typename _UniformRandomNumberGenerator> + typename normal_mv_distribution<_Dimen, _RealType>::result_type + normal_mv_distribution<_Dimen, _RealType>:: + operator()(_UniformRandomNumberGenerator& __urng, + const param_type& __param) + { + result_type __ret; + + _M_nd.__generate(__ret.begin(), __ret.end(), __urng); + + auto __t_it = __param._M_t.crbegin(); + for (size_t __i = _Dimen; __i > 0; --__i) + { + _RealType __sum = _RealType(0); + for (size_t __j = __i; __j > 0; --__j) + __sum += __ret[__j - 1] * *__t_it++; + __ret[__i - 1] = __sum; + } + + return __ret; + } + + template<std::size_t _Dimen, typename _RealType> + template<typename _ForwardIterator, typename _UniformRandomNumberGenerator> + void + normal_mv_distribution<_Dimen, _RealType>:: + __generate_impl(_ForwardIterator __f, _ForwardIterator __t, + _UniformRandomNumberGenerator& __urng, + const param_type& __param) + { + __glibcxx_function_requires(_Mutable_ForwardIteratorConcept< + _ForwardIterator>) + while (__f != __t) + *__f++ = this->operator()(__urng, __param); + } + + template<size_t _Dimen, typename _RealType> + bool + operator==(const __gnu_cxx::normal_mv_distribution<_Dimen, _RealType>& + __d1, + const __gnu_cxx::normal_mv_distribution<_Dimen, _RealType>& + __d2) + { + return __d1._M_param == __d2._M_param && __d1._M_nd == __d2._M_nd; + } + + template<size_t _Dimen, typename _RealType, typename _CharT, typename _Traits> + std::basic_ostream<_CharT, _Traits>& + operator<<(std::basic_ostream<_CharT, _Traits>& __os, + const __gnu_cxx::normal_mv_distribution<_Dimen, _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); + + auto __mean = __x._M_param.mean(); + for (auto __it : __mean) + __os << __it << __space; + auto __t = __x._M_param.varcov(); + for (auto __it : __t) + __os << __it << __space; + + __os << __x._M_nd; + + __os.flags(__flags); + __os.fill(__fill); + __os.precision(__precision); + return __os; + } + + template<size_t _Dimen, typename _RealType, typename _CharT, typename _Traits> + std::basic_istream<_CharT, _Traits>& + operator>>(std::basic_istream<_CharT, _Traits>& __is, + __gnu_cxx::normal_mv_distribution<_Dimen, _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); + + std::array<_RealType, _Dimen> __mean; + for (auto& __it : __mean) + __is >> __it; + std::array<_RealType, _Dimen * (_Dimen + 1) / 2> __varcov; + for (auto& __it : __varcov) + __is >> __it; + + __is >> __x._M_nd; + + __x.param(typename normal_mv_distribution<_Dimen, _RealType>:: + param_type(__mean.begin(), __mean.end(), + __varcov.begin(), __varcov.end())); + + __is.flags(__flags); + return __is; + } + + + template<typename _RealType> + template<typename _OutputIterator, + typename _UniformRandomNumberGenerator> + void + rice_distribution<_RealType>:: + __generate_impl(_OutputIterator __f, _OutputIterator __t, + _UniformRandomNumberGenerator& __urng, + const param_type& __p) + { + __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator>) + + while (__f != __t) + { + typename std::normal_distribution<result_type>::param_type + __px(__p.nu(), __p.sigma()), __py(result_type(0), __p.sigma()); + result_type __x = this->_M_ndx(__px, __urng); + result_type __y = this->_M_ndy(__py, __urng); +#if _GLIBCXX_USE_C99_MATH_TR1 + *__f++ = std::hypot(__x, __y); +#else + *__f++ = std::sqrt(__x * __x + __y * __y); +#endif + } + } + + template<typename _RealType, typename _CharT, typename _Traits> + std::basic_ostream<_CharT, _Traits>& + operator<<(std::basic_ostream<_CharT, _Traits>& __os, + const rice_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.nu() << __space << __x.sigma(); + __os << __space << __x._M_ndx; + __os << __space << __x._M_ndy; + + __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, + rice_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 __nu_val, __sigma_val; + __is >> __nu_val >> __sigma_val; + __is >> __x._M_ndx; + __is >> __x._M_ndy; + __x.param(typename rice_distribution<_RealType>:: + param_type(__nu_val, __sigma_val)); + + __is.flags(__flags); + return __is; + } + + + template<typename _RealType> + template<typename _OutputIterator, + typename _UniformRandomNumberGenerator> + void + nakagami_distribution<_RealType>:: + __generate_impl(_OutputIterator __f, _OutputIterator __t, + _UniformRandomNumberGenerator& __urng, + const param_type& __p) + { + __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator>) + + typename std::gamma_distribution<result_type>::param_type + __pg(__p.mu(), __p.omega() / __p.mu()); + while (__f != __t) + *__f++ = std::sqrt(this->_M_gd(__pg, __urng)); + } + + template<typename _RealType, typename _CharT, typename _Traits> + std::basic_ostream<_CharT, _Traits>& + operator<<(std::basic_ostream<_CharT, _Traits>& __os, + const nakagami_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.mu() << __space << __x.omega(); + __os << __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, + nakagami_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 __mu_val, __omega_val; + __is >> __mu_val >> __omega_val; + __is >> __x._M_gd; + __x.param(typename nakagami_distribution<_RealType>:: + param_type(__mu_val, __omega_val)); + + __is.flags(__flags); + return __is; + } + + + template<typename _RealType> + template<typename _OutputIterator, + typename _UniformRandomNumberGenerator> + void + pareto_distribution<_RealType>:: + __generate_impl(_OutputIterator __f, _OutputIterator __t, + _UniformRandomNumberGenerator& __urng, + const param_type& __p) + { + __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator>) + + result_type __mu_val = __p.mu(); + result_type __malphinv = -result_type(1) / __p.alpha(); + while (__f != __t) + *__f++ = __mu_val * std::pow(this->_M_ud(__urng), __malphinv); + } + + template<typename _RealType, typename _CharT, typename _Traits> + std::basic_ostream<_CharT, _Traits>& + operator<<(std::basic_ostream<_CharT, _Traits>& __os, + const pareto_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.mu(); + __os << __space << __x._M_ud; + + __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, + pareto_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, __mu_val; + __is >> __alpha_val >> __mu_val; + __is >> __x._M_ud; + __x.param(typename pareto_distribution<_RealType>:: + param_type(__alpha_val, __mu_val)); + + __is.flags(__flags); + return __is; + } + + + template<typename _RealType> + template<typename _UniformRandomNumberGenerator> + typename k_distribution<_RealType>::result_type + k_distribution<_RealType>:: + operator()(_UniformRandomNumberGenerator& __urng) + { + result_type __x = this->_M_gd1(__urng); + result_type __y = this->_M_gd2(__urng); + return std::sqrt(__x * __y); + } + + template<typename _RealType> + template<typename _UniformRandomNumberGenerator> + typename k_distribution<_RealType>::result_type + k_distribution<_RealType>:: + operator()(_UniformRandomNumberGenerator& __urng, + const param_type& __p) + { + typename std::gamma_distribution<result_type>::param_type + __p1(__p.lambda(), result_type(1) / __p.lambda()), + __p2(__p.nu(), __p.mu() / __p.nu()); + result_type __x = this->_M_gd1(__p1, __urng); + result_type __y = this->_M_gd2(__p2, __urng); + return std::sqrt(__x * __y); + } + + template<typename _RealType> + template<typename _OutputIterator, + typename _UniformRandomNumberGenerator> + void + k_distribution<_RealType>:: + __generate_impl(_OutputIterator __f, _OutputIterator __t, + _UniformRandomNumberGenerator& __urng, + const param_type& __p) + { + __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator>) + + typename std::gamma_distribution<result_type>::param_type + __p1(__p.lambda(), result_type(1) / __p.lambda()), + __p2(__p.nu(), __p.mu() / __p.nu()); + while (__f != __t) + { + result_type __x = this->_M_gd1(__p1, __urng); + result_type __y = this->_M_gd2(__p2, __urng); + *__f++ = std::sqrt(__x * __y); + } + } + + template<typename _RealType, typename _CharT, typename _Traits> + std::basic_ostream<_CharT, _Traits>& + operator<<(std::basic_ostream<_CharT, _Traits>& __os, + const k_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.lambda() << __space << __x.mu() << __space << __x.nu(); + __os << __space << __x._M_gd1; + __os << __space << __x._M_gd2; + + __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, + k_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_val, __mu_val, __nu_val; + __is >> __lambda_val >> __mu_val >> __nu_val; + __is >> __x._M_gd1; + __is >> __x._M_gd2; + __x.param(typename k_distribution<_RealType>:: + param_type(__lambda_val, __mu_val, __nu_val)); + + __is.flags(__flags); + return __is; + } + + + template<typename _RealType> + template<typename _OutputIterator, + typename _UniformRandomNumberGenerator> + void + arcsine_distribution<_RealType>:: + __generate_impl(_OutputIterator __f, _OutputIterator __t, + _UniformRandomNumberGenerator& __urng, + const param_type& __p) + { + __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator>) + + result_type __dif = __p.b() - __p.a(); + result_type __sum = __p.a() + __p.b(); + while (__f != __t) + { + result_type __x = std::sin(this->_M_ud(__urng)); + *__f++ = (__x * __dif + __sum) / result_type(2); + } + } + + template<typename _RealType, typename _CharT, typename _Traits> + std::basic_ostream<_CharT, _Traits>& + operator<<(std::basic_ostream<_CharT, _Traits>& __os, + const arcsine_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 << __space << __x._M_ud; + + __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, + arcsine_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; + __is >> __x._M_ud; + __x.param(typename arcsine_distribution<_RealType>:: + param_type(__a, __b)); + + __is.flags(__flags); + return __is; + } + + + template<typename _RealType> + template<typename _UniformRandomNumberGenerator> + typename hoyt_distribution<_RealType>::result_type + hoyt_distribution<_RealType>:: + operator()(_UniformRandomNumberGenerator& __urng) + { + result_type __x = this->_M_ad(__urng); + result_type __y = this->_M_ed(__urng); + return (result_type(2) * this->q() + / (result_type(1) + this->q() * this->q())) + * std::sqrt(this->omega() * __x * __y); + } + + template<typename _RealType> + template<typename _UniformRandomNumberGenerator> + typename hoyt_distribution<_RealType>::result_type + hoyt_distribution<_RealType>:: + operator()(_UniformRandomNumberGenerator& __urng, + const param_type& __p) + { + result_type __q2 = __p.q() * __p.q(); + result_type __num = result_type(0.5L) * (result_type(1) + __q2); + typename __gnu_cxx::arcsine_distribution<result_type>::param_type + __pa(__num, __num / __q2); + result_type __x = this->_M_ad(__pa, __urng); + result_type __y = this->_M_ed(__urng); + return (result_type(2) * __p.q() / (result_type(1) + __q2)) + * std::sqrt(__p.omega() * __x * __y); + } + + template<typename _RealType> + template<typename _OutputIterator, + typename _UniformRandomNumberGenerator> + void + hoyt_distribution<_RealType>:: + __generate_impl(_OutputIterator __f, _OutputIterator __t, + _UniformRandomNumberGenerator& __urng, + const param_type& __p) + { + __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator>) + + result_type __2q = result_type(2) * __p.q(); + result_type __q2 = __p.q() * __p.q(); + result_type __q2p1 = result_type(1) + __q2; + result_type __num = result_type(0.5L) * __q2p1; + result_type __omega = __p.omega(); + typename __gnu_cxx::arcsine_distribution<result_type>::param_type + __pa(__num, __num / __q2); + while (__f != __t) + { + result_type __x = this->_M_ad(__pa, __urng); + result_type __y = this->_M_ed(__urng); + *__f++ = (__2q / __q2p1) * std::sqrt(__omega * __x * __y); + } + } + + template<typename _RealType, typename _CharT, typename _Traits> + std::basic_ostream<_CharT, _Traits>& + operator<<(std::basic_ostream<_CharT, _Traits>& __os, + const hoyt_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.q() << __space << __x.omega(); + __os << __space << __x._M_ad; + __os << __space << __x._M_ed; + + __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, + hoyt_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 __q, __omega; + __is >> __q >> __omega; + __is >> __x._M_ad; + __is >> __x._M_ed; + __x.param(typename hoyt_distribution<_RealType>:: + param_type(__q, __omega)); + + __is.flags(__flags); + return __is; + } + + + template<typename _RealType> + template<typename _OutputIterator, + typename _UniformRandomNumberGenerator> + void + triangular_distribution<_RealType>:: + __generate_impl(_OutputIterator __f, _OutputIterator __t, + _UniformRandomNumberGenerator& __urng, + const param_type& __param) + { + __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator>) + + 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 __gnu_cxx::triangular_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() << __space << __x.c(); + + __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, + __gnu_cxx::triangular_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, __c; + __is >> __a >> __b >> __c; + __x.param(typename __gnu_cxx::triangular_distribution<_RealType>:: + param_type(__a, __b, __c)); + + __is.flags(__flags); + return __is; + } + + + template<typename _RealType> + template<typename _OutputIterator, + typename _UniformRandomNumberGenerator> + void + von_mises_distribution<_RealType>:: + __generate_impl(_OutputIterator __f, _OutputIterator __t, + _UniformRandomNumberGenerator& __urng, + const param_type& __param) + { + __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator>) + + 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 __gnu_cxx::von_mises_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.mu() << __space << __x.kappa(); + + __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, + __gnu_cxx::von_mises_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 __mu, __kappa; + __is >> __mu >> __kappa; + __x.param(typename __gnu_cxx::von_mises_distribution<_RealType>:: + param_type(__mu, __kappa)); + + __is.flags(__flags); + return __is; + } + + + template<typename _UIntType> + template<typename _UniformRandomNumberGenerator> + typename hypergeometric_distribution<_UIntType>::result_type + hypergeometric_distribution<_UIntType>:: + operator()(_UniformRandomNumberGenerator& __urng, + const param_type& __param) + { + std::__detail::_Adaptor<_UniformRandomNumberGenerator, result_type> + __aurng(__urng); + + result_type __a = __param.successful_size(); + result_type __b = __param.total_size(); + result_type __k = 0; + + if (__param.total_draws() < __param.total_size() / 2) + { + for (result_type __i = 0; __i < __param.total_draws(); ++__i) + { + if (__b * __aurng() < __a) + { + ++__k; + if (__k == __param.successful_size()) + return __k; + --__a; + } + --__b; + } + return __k; + } + else + { + for (result_type __i = 0; __i < __param.unsuccessful_size(); ++__i) + { + if (__b * __aurng() < __a) + { + ++__k; + if (__k == __param.successful_size()) + return __param.successful_size() - __k; + --__a; + } + --__b; + } + return __param.successful_size() - __k; + } + } + + template<typename _UIntType> + template<typename _OutputIterator, + typename _UniformRandomNumberGenerator> + void + hypergeometric_distribution<_UIntType>:: + __generate_impl(_OutputIterator __f, _OutputIterator __t, + _UniformRandomNumberGenerator& __urng, + const param_type& __param) + { + __glibcxx_function_requires(_OutputIteratorConcept<_OutputIterator>) + + while (__f != __t) + *__f++ = this->operator()(__urng); + } + + template<typename _UIntType, typename _CharT, typename _Traits> + std::basic_ostream<_CharT, _Traits>& + operator<<(std::basic_ostream<_CharT, _Traits>& __os, + const __gnu_cxx::hypergeometric_distribution<_UIntType>& __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<_UIntType>::max_digits10); + + __os << __x.total_size() << __space << __x.successful_size() << __space + << __x.total_draws(); + + __os.flags(__flags); + __os.fill(__fill); + __os.precision(__precision); + return __os; + } + + template<typename _UIntType, typename _CharT, typename _Traits> + std::basic_istream<_CharT, _Traits>& + operator>>(std::basic_istream<_CharT, _Traits>& __is, + __gnu_cxx::hypergeometric_distribution<_UIntType>& __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); + + _UIntType __total_size, __successful_size, __total_draws; + __is >> __total_size >> __successful_size >> __total_draws; + __x.param(typename __gnu_cxx::hypergeometric_distribution<_UIntType>:: + param_type(__total_size, __successful_size, __total_draws)); + + __is.flags(__flags); + return __is; + } + +_GLIBCXX_END_NAMESPACE_VERSION +} // namespace + + +#endif // _EXT_RANDOM_TCC |