// random number generation (out of line) -*- C++ -*-
-// Copyright (C) 2009, 2010, 2011 Free Software Foundation, Inc.
+// Copyright (C) 2009, 2010, 2011, 2012 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
//
// Preconditions: a > 0, m > 0.
//
+ // XXX FIXME: as-is, only works correctly for __m % __a < __m / __a.
+ //
template<typename _Tp, _Tp __m, _Tp __a, _Tp __c, bool>
struct _Mod
{
__os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left);
__os.fill(__space);
- for (size_t __i = 0; __i < __n - 1; ++__i)
+ for (size_t __i = 0; __i < __n; ++__i)
__os << __x._M_x[__i] << __space;
- __os << __x._M_x[__n - 1];
+ __os << __x._M_p;
__os.flags(__flags);
__os.fill(__fill);
for (size_t __i = 0; __i < __n; ++__i)
__is >> __x._M_x[__i];
+ __is >> __x._M_p;
__is.flags(__flags);
return __is;
for (size_t __i = 0; __i < __r; ++__i)
__os << __x._M_x[__i] << __space;
- __os << __x._M_carry;
+ __os << __x._M_carry << __space << __x._M_p;
__os.flags(__flags);
__os.fill(__fill);
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;
independent_bits_engine<_RandomNumberEngine, __w, _UIntType>::
operator()()
{
- const long double __r = static_cast<long double>(_M_b.max())
- - static_cast<long double>(_M_b.min()) + 1.0L;
- const result_type __m = std::log(__r) / std::log(2.0L);
- result_type __n, __n0, __y0, __y1, __s0, __s1;
+ 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 result_type __w0 = __w / __n;
- const result_type __w1 = __w0 + 1;
- __s0 = result_type(1) << __w0;
- __s1 = result_type(1) << __w1;
- __y0 = __s0 * (__r / __s0);
- __y1 = __s1 * (__r / __s1);
- if (__r - __y0 <= __y0 / __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)
{
- result_type __u;
+ __ctype __u;
do
__u = _M_b() - _M_b.min();
- while (__u >= __y0);
- __sum = __s0 * __sum + __u % __s0;
+ while (__y0 && __u >= __y0);
+ __sum = __s0 * __sum + (__s0 ? __u % __s0 : __u);
}
for (size_t __k = __n0; __k < __n; ++__k)
{
- result_type __u;
+ __ctype __u;
do
__u = _M_b() - _M_b.min();
- while (__u >= __y1);
- __sum = __s1 * __sum + __u % __s1;
+ while (__y1 && __u >= __y1);
+ __sum = __s1 * __sum + (__s1 ? __u % __s1 : __u);
}
return __sum;
}
operator()(_UniformRandomNumberGenerator& __urng,
const param_type& __param)
{
- typedef typename std::make_unsigned<typename
- _UniformRandomNumberGenerator::result_type>::type __urngtype;
+ typedef typename _UniformRandomNumberGenerator::result_type
+ _Gresult_type;
typedef typename std::make_unsigned<result_type>::type __utype;
- typedef typename std::conditional<(sizeof(__urngtype)
- > sizeof(__utype)),
- __urngtype, __utype>::type __uctype;
+ typedef typename std::common_type<_Gresult_type, __utype>::type
+ __uctype;
const __uctype __urngmin = __urng.min();
const __uctype __urngmax = __urng.max();
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
param_type;
const double __y =
- _M_gd(__urng, param_type(__p.k(), __p.p() / (1.0 - __p.p())));
+ _M_gd(__urng, param_type(__p.k(), (1.0 - __p.p()) / __p.p()));
std::poisson_distribution<result_type> __poisson(__y);
return __poisson(__urng);
: (__n - 1) / 2;
const size_t __p = (__n - __t) / 2;
const size_t __q = __p + __t;
- const size_t __m = std::max(__s + 1, __n);
+ 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, 0u>(__r1);
+ _Type __r1 = __arg ^ (__arg >> 27);
+ __r1 = __detail::__mod<_Type,
+ __detail::_Shift<_Type, 32>::__value>(1664525u * __r1);
_Type __r2 = __r1;
if (__k == 0)
__r2 += __s;
_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, 0u>(__r3);
+ _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] ^= __r4;
- __begin[(__k + __q) % __n] ^= __r3;
+ __begin[(__k + __p) % __n] ^= __r3;
+ __begin[(__k + __q) % __n] ^= __r4;
__begin[__k % __n] = __r4;
}
}
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