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// random number generation (out of line) -*- C++ -*-// Copyright (C) 2009, 2010 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 tr1/random.tcc* This is an internal header file, included by other library headers.* Do not attempt to use it directly. @headername{tr1/random}*/#ifndef _GLIBCXX_TR1_RANDOM_TCC#define _GLIBCXX_TR1_RANDOM_TCC 1namespace std _GLIBCXX_VISIBILITY(default){namespace tr1{/** (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.//// Because a and c are compile-time integral constants the compiler kindly// elides any unreachable paths.//// Preconditions: a > 0, m > 0.//template<typename _Tp, _Tp __a, _Tp __c, _Tp __m, bool>struct _Mod{static _Tp__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;}};// Special case for m == 0 -- use unsigned integer overflow as modulo// operator.template<typename _Tp, _Tp __a, _Tp __c, _Tp __m>struct _Mod<_Tp, __a, __c, __m, true>{static _Tp__calc(_Tp __x){ return __a * __x + __c; }};_GLIBCXX_END_NAMESPACE_VERSION} // namespace __detail_GLIBCXX_BEGIN_NAMESPACE_VERSIONtemplate<class _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>const _UIntTypelinear_congruential<_UIntType, __a, __c, __m>::multiplier;template<class _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>const _UIntTypelinear_congruential<_UIntType, __a, __c, __m>::increment;template<class _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>const _UIntTypelinear_congruential<_UIntType, __a, __c, __m>::modulus;/*** Seeds the LCR with integral value @p __x0, adjusted so that the* ring identity is never a member of the convergence set.*/template<class _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>voidlinear_congruential<_UIntType, __a, __c, __m>::seed(unsigned long __x0){if ((__detail::__mod<_UIntType, 1, 0, __m>(__c) == 0)&& (__detail::__mod<_UIntType, 1, 0, __m>(__x0) == 0))_M_x = __detail::__mod<_UIntType, 1, 0, __m>(1);else_M_x = __detail::__mod<_UIntType, 1, 0, __m>(__x0);}/*** Seeds the LCR engine with a value generated by @p __g.*/template<class _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>template<class _Gen>voidlinear_congruential<_UIntType, __a, __c, __m>::seed(_Gen& __g, false_type){_UIntType __x0 = __g();if ((__detail::__mod<_UIntType, 1, 0, __m>(__c) == 0)&& (__detail::__mod<_UIntType, 1, 0, __m>(__x0) == 0))_M_x = __detail::__mod<_UIntType, 1, 0, __m>(1);else_M_x = __detail::__mod<_UIntType, 1, 0, __m>(__x0);}/*** Gets the next generated value in sequence.*/template<class _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>typename linear_congruential<_UIntType, __a, __c, __m>::result_typelinear_congruential<_UIntType, __a, __c, __m>::operator()(){_M_x = __detail::__mod<_UIntType, __a, __c, __m>(_M_x);return _M_x;}template<class _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<_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<class _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<_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<class _UIntType, int __w, int __n, int __m, int __r,_UIntType __a, int __u, int __s,_UIntType __b, int __t, _UIntType __c, int __l>const intmersenne_twister<_UIntType, __w, __n, __m, __r, __a, __u, __s,__b, __t, __c, __l>::word_size;template<class _UIntType, int __w, int __n, int __m, int __r,_UIntType __a, int __u, int __s,_UIntType __b, int __t, _UIntType __c, int __l>const intmersenne_twister<_UIntType, __w, __n, __m, __r, __a, __u, __s,__b, __t, __c, __l>::state_size;template<class _UIntType, int __w, int __n, int __m, int __r,_UIntType __a, int __u, int __s,_UIntType __b, int __t, _UIntType __c, int __l>const intmersenne_twister<_UIntType, __w, __n, __m, __r, __a, __u, __s,__b, __t, __c, __l>::shift_size;template<class _UIntType, int __w, int __n, int __m, int __r,_UIntType __a, int __u, int __s,_UIntType __b, int __t, _UIntType __c, int __l>const intmersenne_twister<_UIntType, __w, __n, __m, __r, __a, __u, __s,__b, __t, __c, __l>::mask_bits;template<class _UIntType, int __w, int __n, int __m, int __r,_UIntType __a, int __u, int __s,_UIntType __b, int __t, _UIntType __c, int __l>const _UIntTypemersenne_twister<_UIntType, __w, __n, __m, __r, __a, __u, __s,__b, __t, __c, __l>::parameter_a;template<class _UIntType, int __w, int __n, int __m, int __r,_UIntType __a, int __u, int __s,_UIntType __b, int __t, _UIntType __c, int __l>const intmersenne_twister<_UIntType, __w, __n, __m, __r, __a, __u, __s,__b, __t, __c, __l>::output_u;template<class _UIntType, int __w, int __n, int __m, int __r,_UIntType __a, int __u, int __s,_UIntType __b, int __t, _UIntType __c, int __l>const intmersenne_twister<_UIntType, __w, __n, __m, __r, __a, __u, __s,__b, __t, __c, __l>::output_s;template<class _UIntType, int __w, int __n, int __m, int __r,_UIntType __a, int __u, int __s,_UIntType __b, int __t, _UIntType __c, int __l>const _UIntTypemersenne_twister<_UIntType, __w, __n, __m, __r, __a, __u, __s,__b, __t, __c, __l>::output_b;template<class _UIntType, int __w, int __n, int __m, int __r,_UIntType __a, int __u, int __s,_UIntType __b, int __t, _UIntType __c, int __l>const intmersenne_twister<_UIntType, __w, __n, __m, __r, __a, __u, __s,__b, __t, __c, __l>::output_t;template<class _UIntType, int __w, int __n, int __m, int __r,_UIntType __a, int __u, int __s,_UIntType __b, int __t, _UIntType __c, int __l>const _UIntTypemersenne_twister<_UIntType, __w, __n, __m, __r, __a, __u, __s,__b, __t, __c, __l>::output_c;template<class _UIntType, int __w, int __n, int __m, int __r,_UIntType __a, int __u, int __s,_UIntType __b, int __t, _UIntType __c, int __l>const intmersenne_twister<_UIntType, __w, __n, __m, __r, __a, __u, __s,__b, __t, __c, __l>::output_l;template<class _UIntType, int __w, int __n, int __m, int __r,_UIntType __a, int __u, int __s,_UIntType __b, int __t, _UIntType __c, int __l>voidmersenne_twister<_UIntType, __w, __n, __m, __r, __a, __u, __s,__b, __t, __c, __l>::seed(unsigned long __value){_M_x[0] = __detail::__mod<_UIntType, 1, 0,__detail::_Shift<_UIntType, __w>::__value>(__value);for (int __i = 1; __i < state_size; ++__i){_UIntType __x = _M_x[__i - 1];__x ^= __x >> (__w - 2);__x *= 1812433253ul;__x += __i;_M_x[__i] = __detail::__mod<_UIntType, 1, 0,__detail::_Shift<_UIntType, __w>::__value>(__x);}_M_p = state_size;}template<class _UIntType, int __w, int __n, int __m, int __r,_UIntType __a, int __u, int __s,_UIntType __b, int __t, _UIntType __c, int __l>template<class _Gen>voidmersenne_twister<_UIntType, __w, __n, __m, __r, __a, __u, __s,__b, __t, __c, __l>::seed(_Gen& __gen, false_type){for (int __i = 0; __i < state_size; ++__i)_M_x[__i] = __detail::__mod<_UIntType, 1, 0,__detail::_Shift<_UIntType, __w>::__value>(__gen());_M_p = state_size;}template<class _UIntType, int __w, int __n, int __m, int __r,_UIntType __a, int __u, int __s,_UIntType __b, int __t, _UIntType __c, int __l>typenamemersenne_twister<_UIntType, __w, __n, __m, __r, __a, __u, __s,__b, __t, __c, __l>::result_typemersenne_twister<_UIntType, __w, __n, __m, __r, __a, __u, __s,__b, __t, __c, __l>::operator()(){// Reload the vector - cost is O(n) amortized over n calls.if (_M_p >= state_size){const _UIntType __upper_mask = (~_UIntType()) << __r;const _UIntType __lower_mask = ~__upper_mask;for (int __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 (int __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;}// Calculate o(x(i)).result_type __z = _M_x[_M_p++];__z ^= (__z >> __u);__z ^= (__z << __s) & __b;__z ^= (__z << __t) & __c;__z ^= (__z >> __l);return __z;}template<class _UIntType, int __w, int __n, int __m, int __r,_UIntType __a, int __u, int __s, _UIntType __b, int __t,_UIntType __c, int __l,typename _CharT, typename _Traits>std::basic_ostream<_CharT, _Traits>&operator<<(std::basic_ostream<_CharT, _Traits>& __os,const mersenne_twister<_UIntType, __w, __n, __m,__r, __a, __u, __s, __b, __t, __c, __l>& __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 (int __i = 0; __i < __n - 1; ++__i)__os << __x._M_x[__i] << __space;__os << __x._M_x[__n - 1];__os.flags(__flags);__os.fill(__fill);return __os;}template<class _UIntType, int __w, int __n, int __m, int __r,_UIntType __a, int __u, int __s, _UIntType __b, int __t,_UIntType __c, int __l,typename _CharT, typename _Traits>std::basic_istream<_CharT, _Traits>&operator>>(std::basic_istream<_CharT, _Traits>& __is,mersenne_twister<_UIntType, __w, __n, __m,__r, __a, __u, __s, __b, __t, __c, __l>& __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 (int __i = 0; __i < __n; ++__i)__is >> __x._M_x[__i];__is.flags(__flags);return __is;}template<typename _IntType, _IntType __m, int __s, int __r>const _IntTypesubtract_with_carry<_IntType, __m, __s, __r>::modulus;template<typename _IntType, _IntType __m, int __s, int __r>const intsubtract_with_carry<_IntType, __m, __s, __r>::long_lag;template<typename _IntType, _IntType __m, int __s, int __r>const intsubtract_with_carry<_IntType, __m, __s, __r>::short_lag;template<typename _IntType, _IntType __m, int __s, int __r>voidsubtract_with_carry<_IntType, __m, __s, __r>::seed(unsigned long __value){if (__value == 0)__value = 19780503;std::tr1::linear_congruential<unsigned long, 40014, 0, 2147483563>__lcg(__value);for (int __i = 0; __i < long_lag; ++__i)_M_x[__i] = __detail::__mod<_UIntType, 1, 0, modulus>(__lcg());_M_carry = (_M_x[long_lag - 1] == 0) ? 1 : 0;_M_p = 0;}template<typename _IntType, _IntType __m, int __s, int __r>template<class _Gen>voidsubtract_with_carry<_IntType, __m, __s, __r>::seed(_Gen& __gen, false_type){const int __n = (std::numeric_limits<_UIntType>::digits + 31) / 32;for (int __i = 0; __i < long_lag; ++__i){_UIntType __tmp = 0;_UIntType __factor = 1;for (int __j = 0; __j < __n; ++__j){__tmp += __detail::__mod<__detail::_UInt32Type, 1, 0, 0>(__gen()) * __factor;__factor *= __detail::_Shift<_UIntType, 32>::__value;}_M_x[__i] = __detail::__mod<_UIntType, 1, 0, modulus>(__tmp);}_M_carry = (_M_x[long_lag - 1] == 0) ? 1 : 0;_M_p = 0;}template<typename _IntType, _IntType __m, int __s, int __r>typename subtract_with_carry<_IntType, __m, __s, __r>::result_typesubtract_with_carry<_IntType, __m, __s, __r>::operator()(){// Derive short lag index from current index.int __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 _IntType, _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 = modulus - _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 _IntType, _IntType __m, int __s, int __r,typename _CharT, typename _Traits>std::basic_ostream<_CharT, _Traits>&operator<<(std::basic_ostream<_CharT, _Traits>& __os,const subtract_with_carry<_IntType, __m, __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 (int __i = 0; __i < __r; ++__i)__os << __x._M_x[__i] << __space;__os << __x._M_carry;__os.flags(__flags);__os.fill(__fill);return __os;}template<typename _IntType, _IntType __m, int __s, int __r,typename _CharT, typename _Traits>std::basic_istream<_CharT, _Traits>&operator>>(std::basic_istream<_CharT, _Traits>& __is,subtract_with_carry<_IntType, __m, __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 (int __i = 0; __i < __r; ++__i)__is >> __x._M_x[__i];__is >> __x._M_carry;__is.flags(__flags);return __is;}template<typename _RealType, int __w, int __s, int __r>const intsubtract_with_carry_01<_RealType, __w, __s, __r>::word_size;template<typename _RealType, int __w, int __s, int __r>const intsubtract_with_carry_01<_RealType, __w, __s, __r>::long_lag;template<typename _RealType, int __w, int __s, int __r>const intsubtract_with_carry_01<_RealType, __w, __s, __r>::short_lag;template<typename _RealType, int __w, int __s, int __r>voidsubtract_with_carry_01<_RealType, __w, __s, __r>::_M_initialize_npows(){for (int __j = 0; __j < __n; ++__j)#if _GLIBCXX_USE_C99_MATH_TR1_M_npows[__j] = std::tr1::ldexp(_RealType(1), -__w + __j * 32);#else_M_npows[__j] = std::pow(_RealType(2), -__w + __j * 32);#endif}template<typename _RealType, int __w, int __s, int __r>voidsubtract_with_carry_01<_RealType, __w, __s, __r>::seed(unsigned long __value){if (__value == 0)__value = 19780503;// _GLIBCXX_RESOLVE_LIB_DEFECTS// 512. Seeding subtract_with_carry_01 from a single unsigned long.std::tr1::linear_congruential<unsigned long, 40014, 0, 2147483563>__lcg(__value);this->seed(__lcg);}template<typename _RealType, int __w, int __s, int __r>template<class _Gen>voidsubtract_with_carry_01<_RealType, __w, __s, __r>::seed(_Gen& __gen, false_type){for (int __i = 0; __i < long_lag; ++__i){for (int __j = 0; __j < __n - 1; ++__j)_M_x[__i][__j] = __detail::__mod<_UInt32Type, 1, 0, 0>(__gen());_M_x[__i][__n - 1] = __detail::__mod<_UInt32Type, 1, 0,__detail::_Shift<_UInt32Type, __w % 32>::__value>(__gen());}_M_carry = 1;for (int __j = 0; __j < __n; ++__j)if (_M_x[long_lag - 1][__j] != 0){_M_carry = 0;break;}_M_p = 0;}template<typename _RealType, int __w, int __s, int __r>typename subtract_with_carry_01<_RealType, __w, __s, __r>::result_typesubtract_with_carry_01<_RealType, __w, __s, __r>::operator()(){// Derive short lag index from current index.int __ps = _M_p - short_lag;if (__ps < 0)__ps += long_lag;_UInt32Type __new_carry;for (int __j = 0; __j < __n - 1; ++__j){if (_M_x[__ps][__j] > _M_x[_M_p][__j]|| (_M_x[__ps][__j] == _M_x[_M_p][__j] && _M_carry == 0))__new_carry = 0;else__new_carry = 1;_M_x[_M_p][__j] = _M_x[__ps][__j] - _M_x[_M_p][__j] - _M_carry;_M_carry = __new_carry;}if (_M_x[__ps][__n - 1] > _M_x[_M_p][__n - 1]|| (_M_x[__ps][__n - 1] == _M_x[_M_p][__n - 1] && _M_carry == 0))__new_carry = 0;else__new_carry = 1;_M_x[_M_p][__n - 1] = __detail::__mod<_UInt32Type, 1, 0,__detail::_Shift<_UInt32Type, __w % 32>::__value>(_M_x[__ps][__n - 1] - _M_x[_M_p][__n - 1] - _M_carry);_M_carry = __new_carry;result_type __ret = 0.0;for (int __j = 0; __j < __n; ++__j)__ret += _M_x[_M_p][__j] * _M_npows[__j];// Adjust current index to loop around in ring buffer.if (++_M_p >= long_lag)_M_p = 0;return __ret;}template<typename _RealType, int __w, int __s, int __r,typename _CharT, typename _Traits>std::basic_ostream<_CharT, _Traits>&operator<<(std::basic_ostream<_CharT, _Traits>& __os,const subtract_with_carry_01<_RealType, __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 (int __i = 0; __i < __r; ++__i)for (int __j = 0; __j < __x.__n; ++__j)__os << __x._M_x[__i][__j] << __space;__os << __x._M_carry;__os.flags(__flags);__os.fill(__fill);return __os;}template<typename _RealType, int __w, int __s, int __r,typename _CharT, typename _Traits>std::basic_istream<_CharT, _Traits>&operator>>(std::basic_istream<_CharT, _Traits>& __is,subtract_with_carry_01<_RealType, __w, __s, __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);for (int __i = 0; __i < __r; ++__i)for (int __j = 0; __j < __x.__n; ++__j)__is >> __x._M_x[__i][__j];__is >> __x._M_carry;__is.flags(__flags);return __is;}template<class _UniformRandomNumberGenerator, int __p, int __r>const intdiscard_block<_UniformRandomNumberGenerator, __p, __r>::block_size;template<class _UniformRandomNumberGenerator, int __p, int __r>const intdiscard_block<_UniformRandomNumberGenerator, __p, __r>::used_block;template<class _UniformRandomNumberGenerator, int __p, int __r>typename discard_block<_UniformRandomNumberGenerator,__p, __r>::result_typediscard_block<_UniformRandomNumberGenerator, __p, __r>::operator()(){if (_M_n >= used_block){while (_M_n < block_size){_M_b();++_M_n;}_M_n = 0;}++_M_n;return _M_b();}template<class _UniformRandomNumberGenerator, int __p, int __r,typename _CharT, typename _Traits>std::basic_ostream<_CharT, _Traits>&operator<<(std::basic_ostream<_CharT, _Traits>& __os,const discard_block<_UniformRandomNumberGenerator,__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._M_b << __space << __x._M_n;__os.flags(__flags);__os.fill(__fill);return __os;}template<class _UniformRandomNumberGenerator, int __p, int __r,typename _CharT, typename _Traits>std::basic_istream<_CharT, _Traits>&operator>>(std::basic_istream<_CharT, _Traits>& __is,discard_block<_UniformRandomNumberGenerator, __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<class _UniformRandomNumberGenerator1, int __s1,class _UniformRandomNumberGenerator2, int __s2>const intxor_combine<_UniformRandomNumberGenerator1, __s1,_UniformRandomNumberGenerator2, __s2>::shift1;template<class _UniformRandomNumberGenerator1, int __s1,class _UniformRandomNumberGenerator2, int __s2>const intxor_combine<_UniformRandomNumberGenerator1, __s1,_UniformRandomNumberGenerator2, __s2>::shift2;template<class _UniformRandomNumberGenerator1, int __s1,class _UniformRandomNumberGenerator2, int __s2>voidxor_combine<_UniformRandomNumberGenerator1, __s1,_UniformRandomNumberGenerator2, __s2>::_M_initialize_max(){const int __w = std::numeric_limits<result_type>::digits;const result_type __m1 =std::min(result_type(_M_b1.max() - _M_b1.min()),__detail::_Shift<result_type, __w - __s1>::__value - 1);const result_type __m2 =std::min(result_type(_M_b2.max() - _M_b2.min()),__detail::_Shift<result_type, __w - __s2>::__value - 1);// NB: In TR1 s1 is not required to be >= s2.if (__s1 < __s2)_M_max = _M_initialize_max_aux(__m2, __m1, __s2 - __s1) << __s1;else_M_max = _M_initialize_max_aux(__m1, __m2, __s1 - __s2) << __s2;}template<class _UniformRandomNumberGenerator1, int __s1,class _UniformRandomNumberGenerator2, int __s2>typename xor_combine<_UniformRandomNumberGenerator1, __s1,_UniformRandomNumberGenerator2, __s2>::result_typexor_combine<_UniformRandomNumberGenerator1, __s1,_UniformRandomNumberGenerator2, __s2>::_M_initialize_max_aux(result_type __a, result_type __b, int __d){const result_type __two2d = result_type(1) << __d;const result_type __c = __a * __two2d;if (__a == 0 || __b < __two2d)return __c + __b;const result_type __t = std::max(__c, __b);const result_type __u = std::min(__c, __b);result_type __ub = __u;result_type __p;for (__p = 0; __ub != 1; __ub >>= 1)++__p;const result_type __two2p = result_type(1) << __p;const result_type __k = __t / __two2p;if (__k & 1)return (__k + 1) * __two2p - 1;if (__c >= __b)return (__k + 1) * __two2p + _M_initialize_max_aux((__t % __two2p)/ __two2d,__u % __two2p, __d);elsereturn (__k + 1) * __two2p + _M_initialize_max_aux((__u % __two2p)/ __two2d,__t % __two2p, __d);}template<class _UniformRandomNumberGenerator1, int __s1,class _UniformRandomNumberGenerator2, int __s2,typename _CharT, typename _Traits>std::basic_ostream<_CharT, _Traits>&operator<<(std::basic_ostream<_CharT, _Traits>& __os,const xor_combine<_UniformRandomNumberGenerator1, __s1,_UniformRandomNumberGenerator2, __s2>& __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.base1() << __space << __x.base2();__os.flags(__flags);__os.fill(__fill);return __os;}template<class _UniformRandomNumberGenerator1, int __s1,class _UniformRandomNumberGenerator2, int __s2,typename _CharT, typename _Traits>std::basic_istream<_CharT, _Traits>&operator>>(std::basic_istream<_CharT, _Traits>& __is,xor_combine<_UniformRandomNumberGenerator1, __s1,_UniformRandomNumberGenerator2, __s2>& __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);__is >> __x._M_b1 >> __x._M_b2;__is.flags(__flags);return __is;}template<typename _IntType>template<typename _UniformRandomNumberGenerator>typename uniform_int<_IntType>::result_typeuniform_int<_IntType>::_M_call(_UniformRandomNumberGenerator& __urng,result_type __min, result_type __max, true_type){// XXX Must be fixed to work well for *arbitrary* __urng.max(),// __urng.min(), __max, __min. Currently works fine only in the// most common case __urng.max() - __urng.min() >= __max - __min,// with __urng.max() > __urng.min() >= 0.typedef typename __gnu_cxx::__add_unsigned<typename_UniformRandomNumberGenerator::result_type>::__type __urntype;typedef typename __gnu_cxx::__add_unsigned<result_type>::__type__utype;typedef typename __gnu_cxx::__conditional_type<(sizeof(__urntype)> sizeof(__utype)),__urntype, __utype>::__type __uctype;result_type __ret;const __urntype __urnmin = __urng.min();const __urntype __urnmax = __urng.max();const __urntype __urnrange = __urnmax - __urnmin;const __uctype __urange = __max - __min;const __uctype __udenom = (__urnrange <= __urange? 1 : __urnrange / (__urange + 1));do__ret = (__urntype(__urng()) - __urnmin) / __udenom;while (__ret > __max - __min);return __ret + __min;}template<typename _IntType, typename _CharT, typename _Traits>std::basic_ostream<_CharT, _Traits>&operator<<(std::basic_ostream<_CharT, _Traits>& __os,const uniform_int<_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.min() << __space << __x.max();__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<_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);__is >> __x._M_min >> __x._M_max;__is.flags(__flags);return __is;}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(__gnu_cxx::__numeric_traits<double>::__max_digits10);__os << __x.p();__os.flags(__flags);__os.fill(__fill);__os.precision(__precision);return __os;}template<typename _IntType, typename _RealType>template<class _UniformRandomNumberGenerator>typename geometric_distribution<_IntType, _RealType>::result_typegeometric_distribution<_IntType, _RealType>::operator()(_UniformRandomNumberGenerator& __urng){// About the epsilon thing see this thread:// http://gcc.gnu.org/ml/gcc-patches/2006-10/msg00971.htmlconst _RealType __naf =(1 - std::numeric_limits<_RealType>::epsilon()) / 2;// The largest _RealType convertible to _IntType.const _RealType __thr =std::numeric_limits<_IntType>::max() + __naf;_RealType __cand;do__cand = std::ceil(std::log(__urng()) / _M_log_p);while (__cand >= __thr);return result_type(__cand + __naf);}template<typename _IntType, typename _RealType,typename _CharT, typename _Traits>std::basic_ostream<_CharT, _Traits>&operator<<(std::basic_ostream<_CharT, _Traits>& __os,const geometric_distribution<_IntType, _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(__gnu_cxx::__numeric_traits<_RealType>::__max_digits10);__os << __x.p();__os.flags(__flags);__os.fill(__fill);__os.precision(__precision);return __os;}template<typename _IntType, typename _RealType>voidpoisson_distribution<_IntType, _RealType>::_M_initialize(){#if _GLIBCXX_USE_C99_MATH_TR1if (_M_mean >= 12){const _RealType __m = std::floor(_M_mean);_M_lm_thr = std::log(_M_mean);_M_lfm = std::tr1::lgamma(__m + 1);_M_sm = std::sqrt(__m);const _RealType __pi_4 = 0.7853981633974483096156608458198757L;const _RealType __dx = std::sqrt(2 * __m * std::log(32 * __m/ __pi_4));_M_d = std::tr1::round(std::max(_RealType(6),std::min(__m, __dx)));const _RealType __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, typename _RealType>template<class _UniformRandomNumberGenerator>typename poisson_distribution<_IntType, _RealType>::result_typepoisson_distribution<_IntType, _RealType>::operator()(_UniformRandomNumberGenerator& __urng){#if _GLIBCXX_USE_C99_MATH_TR1if (_M_mean >= 12){_RealType __x;// See comments above...const _RealType __naf =(1 - std::numeric_limits<_RealType>::epsilon()) / 2;const _RealType __thr =std::numeric_limits<_IntType>::max() + __naf;const _RealType __m = std::floor(_M_mean);// sqrt(pi / 2)const _RealType __spi_2 = 1.2533141373155002512078826424055226L;const _RealType __c1 = _M_sm * __spi_2;const _RealType __c2 = _M_c2b + __c1;const _RealType __c3 = __c2 + 1;const _RealType __c4 = __c3 + 1;// e^(1 / 78)const _RealType __e178 = 1.0129030479320018583185514777512983L;const _RealType __c5 = __c4 + __e178;const _RealType __c = _M_cb + __c5;const _RealType __2cx = 2 * (2 * __m + _M_d);bool __reject = true;do{const _RealType __u = __c * __urng();const _RealType __e = -std::log(__urng());_RealType __w = 0.0;if (__u <= __c1){const _RealType __n = _M_nd(__urng);const _RealType __y = -std::abs(__n) * _M_sm - 1;__x = std::floor(__y);__w = -__n * __n / 2;if (__x < -__m)continue;}else if (__u <= __c2){const _RealType __n = _M_nd(__urng);const _RealType __y = 1 + std::abs(__n) * _M_scx;__x = std::ceil(__y);__w = __y * (2 - __y) * _M_1cx;if (__x > _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 _RealType __v = -std::log(__urng());const _RealType __y = _M_d + __v * __2cx / _M_d;__x = std::ceil(__y);__w = -_M_d * _M_1cx * (1 + __y / 2);}__reject = (__w - __e - __x * _M_lm_thr> _M_lfm - std::tr1::lgamma(__x + __m + 1));__reject |= __x + __m >= __thr;} while (__reject);return result_type(__x + __m + __naf);}else#endif{_IntType __x = 0;_RealType __prod = 1.0;do{__prod *= __urng();__x += 1;}while (__prod > _M_lm_thr);return __x - 1;}}template<typename _IntType, typename _RealType,typename _CharT, typename _Traits>std::basic_ostream<_CharT, _Traits>&operator<<(std::basic_ostream<_CharT, _Traits>& __os,const poisson_distribution<_IntType, _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(__gnu_cxx::__numeric_traits<_RealType>::__max_digits10);__os << __x.mean() << __space << __x._M_nd;__os.flags(__flags);__os.fill(__fill);__os.precision(__precision);return __os;}template<typename _IntType, typename _RealType,typename _CharT, typename _Traits>std::basic_istream<_CharT, _Traits>&operator>>(std::basic_istream<_CharT, _Traits>& __is,poisson_distribution<_IntType, _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);__is >> __x._M_mean >> __x._M_nd;__x._M_initialize();__is.flags(__flags);return __is;}template<typename _IntType, typename _RealType>voidbinomial_distribution<_IntType, _RealType>::_M_initialize(){const _RealType __p12 = _M_p <= 0.5 ? _M_p : 1.0 - _M_p;_M_easy = true;#if _GLIBCXX_USE_C99_MATH_TR1if (_M_t * __p12 >= 8){_M_easy = false;const _RealType __np = std::floor(_M_t * __p12);const _RealType __pa = __np / _M_t;const _RealType __1p = 1 - __pa;const _RealType __pi_4 = 0.7853981633974483096156608458198757L;const _RealType __d1x =std::sqrt(__np * __1p * std::log(32 * __np/ (81 * __pi_4 * __1p)));_M_d1 = std::tr1::round(std::max(_RealType(1), __d1x));const _RealType __d2x =std::sqrt(__np * __1p * std::log(32 * _M_t * __1p/ (__pi_4 * __pa)));_M_d2 = std::tr1::round(std::max(_RealType(1), __d2x));// sqrt(pi / 2)const _RealType __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 _RealType __a12 = _M_a1 + _M_s2 * __spi_2;const _RealType __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 _RealType __s2s = _M_s2 * _M_s2;_M_s = (_M_a123 + 2 * __s2s / _M_d2* std::exp(-_M_d2 * _M_d2 / (2 * __s2s)));_M_lf = (std::tr1::lgamma(__np + 1)+ std::tr1::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, typename _RealType>template<class _UniformRandomNumberGenerator>typename binomial_distribution<_IntType, _RealType>::result_typebinomial_distribution<_IntType, _RealType>::_M_waiting(_UniformRandomNumberGenerator& __urng, _IntType __t){_IntType __x = 0;_RealType __sum = 0;do{const _RealType __e = -std::log(__urng());__sum += __e / (__t - __x);__x += 1;}while (__sum <= _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, typename _RealType>template<class _UniformRandomNumberGenerator>typename binomial_distribution<_IntType, _RealType>::result_typebinomial_distribution<_IntType, _RealType>::operator()(_UniformRandomNumberGenerator& __urng){result_type __ret;const _RealType __p12 = _M_p <= 0.5 ? _M_p : 1.0 - _M_p;#if _GLIBCXX_USE_C99_MATH_TR1if (!_M_easy){_RealType __x;// See comments above...const _RealType __naf =(1 - std::numeric_limits<_RealType>::epsilon()) / 2;const _RealType __thr =std::numeric_limits<_IntType>::max() + __naf;const _RealType __np = std::floor(_M_t * __p12);const _RealType __pa = __np / _M_t;// sqrt(pi / 2)const _RealType __spi_2 = 1.2533141373155002512078826424055226L;const _RealType __a1 = _M_a1;const _RealType __a12 = __a1 + _M_s2 * __spi_2;const _RealType __a123 = _M_a123;const _RealType __s1s = _M_s1 * _M_s1;const _RealType __s2s = _M_s2 * _M_s2;bool __reject;do{const _RealType __u = _M_s * __urng();_RealType __v;if (__u <= __a1){const _RealType __n = _M_nd(__urng);const _RealType __y = _M_s1 * std::abs(__n);__reject = __y >= _M_d1;if (!__reject){const _RealType __e = -std::log(__urng());__x = std::floor(__y);__v = -__e - __n * __n / 2 + _M_c;}}else if (__u <= __a12){const _RealType __n = _M_nd(__urng);const _RealType __y = _M_s2 * std::abs(__n);__reject = __y >= _M_d2;if (!__reject){const _RealType __e = -std::log(__urng());__x = std::floor(-__y);__v = -__e - __n * __n / 2;}}else if (__u <= __a123){const _RealType __e1 = -std::log(__urng());const _RealType __e2 = -std::log(__urng());const _RealType __y = _M_d1 + 2 * __s1s * __e1 / _M_d1;__x = std::floor(__y);__v = (-__e2 + _M_d1 * (1 / (_M_t - __np)-__y / (2 * __s1s)));__reject = false;}else{const _RealType __e1 = -std::log(__urng());const _RealType __e2 = -std::log(__urng());const _RealType __y = _M_d2 + 2 * __s2s * __e1 / _M_d2;__x = std::floor(-__y);__v = -__e2 - _M_d2 * __y / (2 * __s2s);__reject = false;}__reject = __reject || __x < -__np || __x > _M_t - __np;if (!__reject){const _RealType __lfx =std::tr1::lgamma(__np + __x + 1)+ std::tr1::lgamma(_M_t - (__np + __x) + 1);__reject = __v > _M_lf - __lfx + __x * _M_lp1p;}__reject |= __x + __np >= __thr;}while (__reject);__x += __np + __naf;const _IntType __z = _M_waiting(__urng, _M_t - _IntType(__x));__ret = _IntType(__x) + __z;}else#endif__ret = _M_waiting(__urng, _M_t);if (__p12 != _M_p)__ret = _M_t - __ret;return __ret;}template<typename _IntType, typename _RealType,typename _CharT, typename _Traits>std::basic_ostream<_CharT, _Traits>&operator<<(std::basic_ostream<_CharT, _Traits>& __os,const binomial_distribution<_IntType, _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(__gnu_cxx::__numeric_traits<_RealType>::__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 _RealType,typename _CharT, typename _Traits>std::basic_istream<_CharT, _Traits>&operator>>(std::basic_istream<_CharT, _Traits>& __is,binomial_distribution<_IntType, _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);__is >> __x._M_t >> __x._M_p >> __x._M_nd;__x._M_initialize();__is.flags(__flags);return __is;}template<typename _RealType, typename _CharT, typename _Traits>std::basic_ostream<_CharT, _Traits>&operator<<(std::basic_ostream<_CharT, _Traits>& __os,const uniform_real<_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(__gnu_cxx::__numeric_traits<_RealType>::__max_digits10);__os << __x.min() << __space << __x.max();__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<_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);__is >> __x._M_min >> __x._M_max;__is.flags(__flags);return __is;}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(__gnu_cxx::__numeric_traits<_RealType>::__max_digits10);__os << __x.lambda();__os.flags(__flags);__os.fill(__fill);__os.precision(__precision);return __os;}/*** 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<class _UniformRandomNumberGenerator>typename normal_distribution<_RealType>::result_typenormal_distribution<_RealType>::operator()(_UniformRandomNumberGenerator& __urng){result_type __ret;if (_M_saved_available){_M_saved_available = false;__ret = _M_saved;}else{result_type __x, __y, __r2;do{__x = result_type(2.0) * __urng() - 1.0;__y = result_type(2.0) * __urng() - 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 * _M_sigma + _M_mean;return __ret;}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(__gnu_cxx::__numeric_traits<_RealType>::__max_digits10);__os << __x._M_saved_available << __space<< __x.mean() << __space<< __x.sigma();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);__is >> __x._M_saved_available >> __x._M_mean>> __x._M_sigma;if (__x._M_saved_available)__is >> __x._M_saved;__is.flags(__flags);return __is;}template<typename _RealType>voidgamma_distribution<_RealType>::_M_initialize(){if (_M_alpha >= 1)_M_l_d = std::sqrt(2 * _M_alpha - 1);else_M_l_d = (std::pow(_M_alpha, _M_alpha / (1 - _M_alpha))* (1 - _M_alpha));}/*** Cheng's rejection algorithm GB for alpha >= 1 and a modification* of Vaduva's rejection from Weibull algorithm due to Devroye for* alpha < 1.** References:* Cheng, R. C. The Generation of Gamma Random Variables with Non-integral* Shape Parameter. Applied Statistics, 26, 71-75, 1977.** Vaduva, I. Computer Generation of Gamma Gandom Variables by Rejection* and Composition Procedures. Math. Operationsforschung and Statistik,* Series in Statistics, 8, 545-576, 1977.** Devroye, L. Non-Uniform Random Variates Generation. Springer-Verlag,* New York, 1986, Ch. IX, Sect. 3.4 (+ Errata!).*/template<typename _RealType>template<class _UniformRandomNumberGenerator>typename gamma_distribution<_RealType>::result_typegamma_distribution<_RealType>::operator()(_UniformRandomNumberGenerator& __urng){result_type __x;bool __reject;if (_M_alpha >= 1){// alpha - log(4)const result_type __b = _M_alpha- result_type(1.3862943611198906188344642429163531L);const result_type __c = _M_alpha + _M_l_d;const result_type __1l = 1 / _M_l_d;// 1 + log(9 / 2)const result_type __k = 2.5040773967762740733732583523868748L;do{const result_type __u = __urng();const result_type __v = __urng();const result_type __y = __1l * std::log(__v / (1 - __v));__x = _M_alpha * std::exp(__y);const result_type __z = __u * __v * __v;const result_type __r = __b + __c * __y - __x;__reject = __r < result_type(4.5) * __z - __k;if (__reject)__reject = __r < std::log(__z);}while (__reject);}else{const result_type __c = 1 / _M_alpha;do{const result_type __z = -std::log(__urng());const result_type __e = -std::log(__urng());__x = std::pow(__z, __c);__reject = __z + __e < _M_l_d + __x;}while (__reject);}return __x;}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();__os.flags(__ios_base::scientific | __ios_base::left);__os.fill(__os.widen(' '));__os.precision(__gnu_cxx::__numeric_traits<_RealType>::__max_digits10);__os << __x.alpha();__os.flags(__flags);__os.fill(__fill);__os.precision(__precision);return __os;}_GLIBCXX_END_NAMESPACE_VERSION}}#endif
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