// random number generation (out of line) -*- C++ -*-
-// Copyright (C) 2009 Free Software Foundation, Inc.
+// Copyright (C) 2009, 2010, 2011 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
/** @file bits/random.tcc
* This is an internal header file, included by other library headers.
- * You should not attempt to use it directly.
+ * Do not attempt to use it directly. @headername{random}
*/
-#include <numeric>
-#include <algorithm>
+#ifndef _RANDOM_TCC
+#define _RANDOM_TCC 1
-namespace std
+#include <numeric> // std::accumulate and std::partial_sum
+
+namespace std _GLIBCXX_VISIBILITY(default)
{
/*
* (Further) implementation-space details.
*/
namespace __detail
{
+ _GLIBCXX_BEGIN_NAMESPACE_VERSION
+
// General case for x = (ax + c) mod m -- use Schrage's algorithm to
// avoid integer overflow.
//
__calc(_Tp __x)
{ return __a * __x + __c; }
};
+
+ template<typename _InputIterator, typename _OutputIterator,
+ typename _UnaryOperation>
+ _OutputIterator
+ __transform(_InputIterator __first, _InputIterator __last,
+ _OutputIterator __result, _UnaryOperation __unary_op)
+ {
+ for (; __first != __last; ++__first, ++__result)
+ *__result = __unary_op(*__first);
+ return __result;
+ }
+
+ _GLIBCXX_END_NAMESPACE_VERSION
} // namespace __detail
+_GLIBCXX_BEGIN_NAMESPACE_VERSION
+
+ template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>
+ constexpr _UIntType
+ linear_congruential_engine<_UIntType, __a, __c, __m>::multiplier;
+
+ template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>
+ constexpr _UIntType
+ linear_congruential_engine<_UIntType, __a, __c, __m>::increment;
+
+ template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>
+ constexpr _UIntType
+ linear_congruential_engine<_UIntType, __a, __c, __m>::modulus;
+
+ template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>
+ constexpr _UIntType
+ linear_congruential_engine<_UIntType, __a, __c, __m>::default_seed;
+
/**
* Seeds the LCR with integral value @p __s, adjusted so that the
* ring identity is never a member of the convergence set.
* Seeds the LCR engine with a value generated by @p __q.
*/
template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>
- void
- linear_congruential_engine<_UIntType, __a, __c, __m>::
- seed(seed_seq& __q)
- {
- const _UIntType __k0 = __m == 0 ? std::numeric_limits<_UIntType>::digits
- : std::__lg(__m);
- const _UIntType __k = (__k0 + 31) / 32;
- _UIntType __arr[__k + 3];
- __q.generate(__arr + 0, __arr + __k + 3);
- _UIntType __factor = 1u;
- _UIntType __sum = 0u;
- for (size_t __j = 0; __j < __k; ++__j)
- {
- __sum += __arr[__j + 3] * __factor;
- __factor *= __detail::_Shift<_UIntType, 32>::__value;
- }
- seed(__sum);
- }
+ template<typename _Sseq>
+ typename std::enable_if<std::is_class<_Sseq>::value>::type
+ linear_congruential_engine<_UIntType, __a, __c, __m>::
+ seed(_Sseq& __q)
+ {
+ const _UIntType __k0 = __m == 0 ? std::numeric_limits<_UIntType>::digits
+ : std::__lg(__m);
+ const _UIntType __k = (__k0 + 31) / 32;
+ uint_least32_t __arr[__k + 3];
+ __q.generate(__arr + 0, __arr + __k + 3);
+ _UIntType __factor = 1u;
+ _UIntType __sum = 0u;
+ for (size_t __j = 0; __j < __k; ++__j)
+ {
+ __sum += __arr[__j + 3] * __factor;
+ __factor *= __detail::_Shift<_UIntType, 32>::__value;
+ }
+ seed(__sum);
+ }
template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m,
typename _CharT, typename _Traits>
}
+ template<typename _UIntType,
+ size_t __w, size_t __n, size_t __m, size_t __r,
+ _UIntType __a, size_t __u, _UIntType __d, size_t __s,
+ _UIntType __b, size_t __t, _UIntType __c, size_t __l,
+ _UIntType __f>
+ constexpr size_t
+ mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
+ __s, __b, __t, __c, __l, __f>::word_size;
+
+ template<typename _UIntType,
+ size_t __w, size_t __n, size_t __m, size_t __r,
+ _UIntType __a, size_t __u, _UIntType __d, size_t __s,
+ _UIntType __b, size_t __t, _UIntType __c, size_t __l,
+ _UIntType __f>
+ constexpr size_t
+ mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
+ __s, __b, __t, __c, __l, __f>::state_size;
+
+ template<typename _UIntType,
+ size_t __w, size_t __n, size_t __m, size_t __r,
+ _UIntType __a, size_t __u, _UIntType __d, size_t __s,
+ _UIntType __b, size_t __t, _UIntType __c, size_t __l,
+ _UIntType __f>
+ constexpr size_t
+ mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
+ __s, __b, __t, __c, __l, __f>::shift_size;
+
+ template<typename _UIntType,
+ size_t __w, size_t __n, size_t __m, size_t __r,
+ _UIntType __a, size_t __u, _UIntType __d, size_t __s,
+ _UIntType __b, size_t __t, _UIntType __c, size_t __l,
+ _UIntType __f>
+ constexpr size_t
+ mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
+ __s, __b, __t, __c, __l, __f>::mask_bits;
+
+ template<typename _UIntType,
+ size_t __w, size_t __n, size_t __m, size_t __r,
+ _UIntType __a, size_t __u, _UIntType __d, size_t __s,
+ _UIntType __b, size_t __t, _UIntType __c, size_t __l,
+ _UIntType __f>
+ constexpr _UIntType
+ mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
+ __s, __b, __t, __c, __l, __f>::xor_mask;
+
+ template<typename _UIntType,
+ size_t __w, size_t __n, size_t __m, size_t __r,
+ _UIntType __a, size_t __u, _UIntType __d, size_t __s,
+ _UIntType __b, size_t __t, _UIntType __c, size_t __l,
+ _UIntType __f>
+ constexpr size_t
+ mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
+ __s, __b, __t, __c, __l, __f>::tempering_u;
+
+ template<typename _UIntType,
+ size_t __w, size_t __n, size_t __m, size_t __r,
+ _UIntType __a, size_t __u, _UIntType __d, size_t __s,
+ _UIntType __b, size_t __t, _UIntType __c, size_t __l,
+ _UIntType __f>
+ constexpr _UIntType
+ mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
+ __s, __b, __t, __c, __l, __f>::tempering_d;
+
+ template<typename _UIntType,
+ size_t __w, size_t __n, size_t __m, size_t __r,
+ _UIntType __a, size_t __u, _UIntType __d, size_t __s,
+ _UIntType __b, size_t __t, _UIntType __c, size_t __l,
+ _UIntType __f>
+ constexpr size_t
+ mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
+ __s, __b, __t, __c, __l, __f>::tempering_s;
+
+ template<typename _UIntType,
+ size_t __w, size_t __n, size_t __m, size_t __r,
+ _UIntType __a, size_t __u, _UIntType __d, size_t __s,
+ _UIntType __b, size_t __t, _UIntType __c, size_t __l,
+ _UIntType __f>
+ constexpr _UIntType
+ mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
+ __s, __b, __t, __c, __l, __f>::tempering_b;
+
+ template<typename _UIntType,
+ size_t __w, size_t __n, size_t __m, size_t __r,
+ _UIntType __a, size_t __u, _UIntType __d, size_t __s,
+ _UIntType __b, size_t __t, _UIntType __c, size_t __l,
+ _UIntType __f>
+ constexpr size_t
+ mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
+ __s, __b, __t, __c, __l, __f>::tempering_t;
+
+ template<typename _UIntType,
+ size_t __w, size_t __n, size_t __m, size_t __r,
+ _UIntType __a, size_t __u, _UIntType __d, size_t __s,
+ _UIntType __b, size_t __t, _UIntType __c, size_t __l,
+ _UIntType __f>
+ constexpr _UIntType
+ mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
+ __s, __b, __t, __c, __l, __f>::tempering_c;
+
+ template<typename _UIntType,
+ size_t __w, size_t __n, size_t __m, size_t __r,
+ _UIntType __a, size_t __u, _UIntType __d, size_t __s,
+ _UIntType __b, size_t __t, _UIntType __c, size_t __l,
+ _UIntType __f>
+ constexpr size_t
+ mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
+ __s, __b, __t, __c, __l, __f>::tempering_l;
+
+ template<typename _UIntType,
+ size_t __w, size_t __n, size_t __m, size_t __r,
+ _UIntType __a, size_t __u, _UIntType __d, size_t __s,
+ _UIntType __b, size_t __t, _UIntType __c, size_t __l,
+ _UIntType __f>
+ constexpr _UIntType
+ mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
+ __s, __b, __t, __c, __l, __f>::
+ initialization_multiplier;
+
+ template<typename _UIntType,
+ size_t __w, size_t __n, size_t __m, size_t __r,
+ _UIntType __a, size_t __u, _UIntType __d, size_t __s,
+ _UIntType __b, size_t __t, _UIntType __c, size_t __l,
+ _UIntType __f>
+ constexpr _UIntType
+ mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
+ __s, __b, __t, __c, __l, __f>::default_seed;
+
template<typename _UIntType,
size_t __w, size_t __n, size_t __m, size_t __r,
_UIntType __a, size_t __u, _UIntType __d, size_t __s,
_UIntType __a, size_t __u, _UIntType __d, size_t __s,
_UIntType __b, size_t __t, _UIntType __c, size_t __l,
_UIntType __f>
- void
- mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
+ template<typename _Sseq>
+ typename std::enable_if<std::is_class<_Sseq>::value>::type
+ mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d,
__s, __b, __t, __c, __l, __f>::
- seed(seed_seq& __q)
- {
- const _UIntType __upper_mask = (~_UIntType()) << __r;
- const size_t __k = (__w + 31) / 32;
- uint_least32_t __arr[__n * __k];
- __q.generate(__arr + 0, __arr + __n * __k);
-
- bool __zero = true;
- for (size_t __i = 0; __i < state_size; ++__i)
- {
- _UIntType __factor = 1u;
- _UIntType __sum = 0u;
- for (size_t __j = 0; __j < __k; ++__j)
- {
- __sum += __arr[__k * __i + __j] * __factor;
- __factor *= __detail::_Shift<_UIntType, 32>::__value;
- }
- _M_x[__i] = __detail::__mod<_UIntType,
- __detail::_Shift<_UIntType, __w>::__value>(__sum);
+ seed(_Sseq& __q)
+ {
+ const _UIntType __upper_mask = (~_UIntType()) << __r;
+ const size_t __k = (__w + 31) / 32;
+ uint_least32_t __arr[__n * __k];
+ __q.generate(__arr + 0, __arr + __n * __k);
- if (__zero)
- {
- if (__i == 0)
- {
- if ((_M_x[0] & __upper_mask) != 0u)
- __zero = false;
- }
- else if (_M_x[__i] != 0u)
- __zero = false;
- }
- }
+ bool __zero = true;
+ for (size_t __i = 0; __i < state_size; ++__i)
+ {
+ _UIntType __factor = 1u;
+ _UIntType __sum = 0u;
+ for (size_t __j = 0; __j < __k; ++__j)
+ {
+ __sum += __arr[__k * __i + __j] * __factor;
+ __factor *= __detail::_Shift<_UIntType, 32>::__value;
+ }
+ _M_x[__i] = __detail::__mod<_UIntType,
+ __detail::_Shift<_UIntType, __w>::__value>(__sum);
+
+ if (__zero)
+ {
+ if (__i == 0)
+ {
+ if ((_M_x[0] & __upper_mask) != 0u)
+ __zero = false;
+ }
+ else if (_M_x[__i] != 0u)
+ __zero = false;
+ }
+ }
if (__zero)
_M_x[0] = __detail::_Shift<_UIntType, __w - 1>::__value;
- }
+ }
template<typename _UIntType, size_t __w,
size_t __n, size_t __m, size_t __r,
}
+ template<typename _UIntType, size_t __w, size_t __s, size_t __r>
+ constexpr size_t
+ subtract_with_carry_engine<_UIntType, __w, __s, __r>::word_size;
+
+ template<typename _UIntType, size_t __w, size_t __s, size_t __r>
+ constexpr size_t
+ subtract_with_carry_engine<_UIntType, __w, __s, __r>::short_lag;
+
+ template<typename _UIntType, size_t __w, size_t __s, size_t __r>
+ constexpr size_t
+ subtract_with_carry_engine<_UIntType, __w, __s, __r>::long_lag;
+
+ template<typename _UIntType, size_t __w, size_t __s, size_t __r>
+ constexpr _UIntType
+ subtract_with_carry_engine<_UIntType, __w, __s, __r>::default_seed;
+
template<typename _UIntType, size_t __w, size_t __s, size_t __r>
void
subtract_with_carry_engine<_UIntType, __w, __s, __r>::
}
template<typename _UIntType, size_t __w, size_t __s, size_t __r>
- void
- subtract_with_carry_engine<_UIntType, __w, __s, __r>::
- seed(seed_seq& __q)
- {
- const size_t __k = (__w + 31) / 32;
- uint_least32_t __arr[__r * __k];
- __q.generate(__arr + 0, __arr + __r * __k);
+ template<typename _Sseq>
+ typename std::enable_if<std::is_class<_Sseq>::value>::type
+ subtract_with_carry_engine<_UIntType, __w, __s, __r>::
+ seed(_Sseq& __q)
+ {
+ const size_t __k = (__w + 31) / 32;
+ uint_least32_t __arr[__r * __k];
+ __q.generate(__arr + 0, __arr + __r * __k);
- for (size_t __i = 0; __i < long_lag; ++__i)
- {
- _UIntType __sum = 0u;
- _UIntType __factor = 1u;
- for (size_t __j = 0; __j < __k; ++__j)
- {
- __sum += __arr[__k * __i + __j] * __factor;
- __factor *= __detail::_Shift<_UIntType, 32>::__value;
- }
- _M_x[__i] = __detail::__mod<_UIntType,
- __detail::_Shift<_UIntType, __w>::__value>(__sum);
- }
- _M_carry = (_M_x[long_lag - 1] == 0) ? 1 : 0;
- _M_p = 0;
- }
+ for (size_t __i = 0; __i < long_lag; ++__i)
+ {
+ _UIntType __sum = 0u;
+ _UIntType __factor = 1u;
+ for (size_t __j = 0; __j < __k; ++__j)
+ {
+ __sum += __arr[__k * __i + __j] * __factor;
+ __factor *= __detail::_Shift<_UIntType, 32>::__value;
+ }
+ _M_x[__i] = __detail::__mod<_UIntType,
+ __detail::_Shift<_UIntType, __w>::__value>(__sum);
+ }
+ _M_carry = (_M_x[long_lag - 1] == 0) ? 1 : 0;
+ _M_p = 0;
+ }
template<typename _UIntType, size_t __w, size_t __s, size_t __r>
typename subtract_with_carry_engine<_UIntType, __w, __s, __r>::
}
+ template<typename _RandomNumberEngine, size_t __p, size_t __r>
+ constexpr size_t
+ discard_block_engine<_RandomNumberEngine, __p, __r>::block_size;
+
+ template<typename _RandomNumberEngine, size_t __p, size_t __r>
+ constexpr size_t
+ discard_block_engine<_RandomNumberEngine, __p, __r>::used_block;
+
template<typename _RandomNumberEngine, size_t __p, size_t __r>
typename discard_block_engine<_RandomNumberEngine,
__p, __r>::result_type
}
+ template<typename _RandomNumberEngine, size_t __k>
+ constexpr size_t
+ shuffle_order_engine<_RandomNumberEngine, __k>::table_size;
+
template<typename _RandomNumberEngine, size_t __k>
typename shuffle_order_engine<_RandomNumberEngine, __k>::result_type
shuffle_order_engine<_RandomNumberEngine, __k>::
operator()(_UniformRandomNumberGenerator& __urng,
const param_type& __param)
{
- // XXX Must be fixed to work well for *arbitrary* __urng.max(),
- // __urng.min(), __param.b(), __param.a(). Currently works fine only
- // in the most common case __urng.max() - __urng.min() >=
- // __param.b() - __param.a(), 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;
+ typedef typename std::make_unsigned<typename
+ _UniformRandomNumberGenerator::result_type>::type __urngtype;
+ typedef typename std::make_unsigned<result_type>::type __utype;
+ typedef typename std::conditional<(sizeof(__urngtype)
+ > sizeof(__utype)),
+ __urngtype, __utype>::type __uctype;
+
+ const __uctype __urngmin = __urng.min();
+ const __uctype __urngmax = __urng.max();
+ const __uctype __urngrange = __urngmax - __urngmin;
+ const __uctype __urange
+ = __uctype(__param.b()) - __uctype(__param.a());
+
+ __uctype __ret;
+
+ if (__urngrange > __urange)
+ {
+ // downscaling
+ const __uctype __uerange = __urange + 1; // __urange can be zero
+ const __uctype __scaling = __urngrange / __uerange;
+ const __uctype __past = __uerange * __scaling;
+ do
+ __ret = __uctype(__urng()) - __urngmin;
+ while (__ret >= __past);
+ __ret /= __scaling;
+ }
+ else if (__urngrange < __urange)
+ {
+ // upscaling
+ /*
+ Note that every value in [0, urange]
+ can be written uniquely as
- result_type __ret;
+ (urngrange + 1) * high + low
- const __urntype __urnmin = __urng.min();
- const __urntype __urnmax = __urng.max();
- const __urntype __urnrange = __urnmax - __urnmin;
- const __uctype __urange = __param.b() - __param.a();
- const __uctype __udenom = (__urnrange <= __urange
- ? 1 : __urnrange / (__urange + 1));
- do
- __ret = (__urntype(__urng()) - __urnmin) / __udenom;
- while (__ret > __param.b() - __param.a());
+ where
+
+ high in [0, urange / (urngrange + 1)]
+
+ and
+
+ low in [0, urngrange].
+ */
+ __uctype __tmp; // wraparound control
+ do
+ {
+ const __uctype __uerngrange = __urngrange + 1;
+ __tmp = (__uerngrange * operator()
+ (__urng, param_type(0, __urange / __uerngrange)));
+ __ret = __tmp + (__uctype(__urng()) - __urngmin);
+ }
+ while (__ret > __urange || __ret < __tmp);
+ }
+ else
+ __ret = __uctype(__urng()) - __urngmin;
return __ret + __param.a();
}
const _CharT __space = __os.widen(' ');
__os.flags(__ios_base::scientific | __ios_base::left);
__os.fill(__space);
- __os.precision(std::numeric_limits<_RealType>::digits10 + 1);
+ __os.precision(std::numeric_limits<_RealType>::max_digits10);
__os << __x.a() << __space << __x.b();
const std::streamsize __precision = __os.precision();
__os.flags(__ios_base::scientific | __ios_base::left);
__os.fill(__os.widen(' '));
- __os.precision(std::numeric_limits<double>::digits10 + 1);
+ __os.precision(std::numeric_limits<double>::max_digits10);
__os << __x.p();
double __cand;
do
- __cand = std::ceil(std::log(__aurng()) / __param._M_log_p);
+ __cand = std::floor(std::log(__aurng()) / __param._M_log_1_p);
while (__cand >= __thr);
return result_type(__cand + __naf);
const std::streamsize __precision = __os.precision();
__os.flags(__ios_base::scientific | __ios_base::left);
__os.fill(__os.widen(' '));
- __os.precision(std::numeric_limits<double>::digits10 + 1);
+ __os.precision(std::numeric_limits<double>::max_digits10);
__os << __x.p();
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);
const _CharT __space = __os.widen(' ');
__os.flags(__ios_base::scientific | __ios_base::left);
__os.fill(__os.widen(' '));
- __os.precision(std::numeric_limits<double>::digits10 + 1);
+ __os.precision(std::numeric_limits<double>::max_digits10);
__os << __x.k() << __space << __x.p()
<< __space << __x._M_gd;
* is defined.
*
* Reference:
- * Devroye, L. "Non-Uniform Random Variates Generation." Springer-Verlag,
+ * Devroye, L. Non-Uniform Random Variates Generation. Springer-Verlag,
* New York, 1986, Ch. X, Sects. 3.3 & 3.4 (+ Errata!).
*/
template<typename _IntType>
const _CharT __space = __os.widen(' ');
__os.flags(__ios_base::scientific | __ios_base::left);
__os.fill(__space);
- __os.precision(std::numeric_limits<double>::digits10 + 1);
+ __os.precision(std::numeric_limits<double>::max_digits10);
__os << __x.mean() << __space << __x._M_nd;
* is defined.
*
* Reference:
- * Devroye, L. "Non-Uniform Random Variates Generation." Springer-Verlag,
+ * Devroye, L. Non-Uniform Random Variates Generation. Springer-Verlag,
* New York, 1986, Ch. X, Sect. 4 (+ Errata!).
*/
template<typename _IntType>
{
result_type __ret;
const _IntType __t = __param.t();
- const _IntType __p = __param.p();
+ const double __p = __param.p();
const double __p12 = __p <= 0.5 ? __p : 1.0 - __p;
__detail::_Adaptor<_UniformRandomNumberGenerator, double>
__aurng(__urng);
const _CharT __space = __os.widen(' ');
__os.flags(__ios_base::scientific | __ios_base::left);
__os.fill(__space);
- __os.precision(std::numeric_limits<double>::digits10 + 1);
+ __os.precision(std::numeric_limits<double>::max_digits10);
__os << __x.t() << __space << __x.p()
<< __space << __x._M_nd;
const std::streamsize __precision = __os.precision();
__os.flags(__ios_base::scientific | __ios_base::left);
__os.fill(__os.widen(' '));
- __os.precision(std::numeric_limits<_RealType>::digits10 + 1);
+ __os.precision(std::numeric_limits<_RealType>::max_digits10);
__os << __x.lambda();
/**
* Polar method due to Marsaglia.
*
- * Devroye, L. "Non-Uniform Random Variates Generation." Springer-Verlag,
+ * Devroye, L. Non-Uniform Random Variates Generation. Springer-Verlag,
* New York, 1986, Ch. V, Sect. 4.4.
*/
template<typename _RealType>
return __ret;
}
+ template<typename _RealType>
+ bool
+ operator==(const std::normal_distribution<_RealType>& __d1,
+ const std::normal_distribution<_RealType>& __d2)
+ {
+ if (__d1._M_param == __d2._M_param
+ && __d1._M_saved_available == __d2._M_saved_available)
+ {
+ if (__d1._M_saved_available
+ && __d1._M_saved == __d2._M_saved)
+ return true;
+ else if(!__d1._M_saved_available)
+ return true;
+ else
+ return false;
+ }
+ else
+ return false;
+ }
+
template<typename _RealType, typename _CharT, typename _Traits>
std::basic_ostream<_CharT, _Traits>&
operator<<(std::basic_ostream<_CharT, _Traits>& __os,
const _CharT __space = __os.widen(' ');
__os.flags(__ios_base::scientific | __ios_base::left);
__os.fill(__space);
- __os.precision(std::numeric_limits<_RealType>::digits10 + 1);
+ __os.precision(std::numeric_limits<_RealType>::max_digits10);
__os << __x.mean() << __space << __x.stddev()
<< __space << __x._M_saved_available;
const _CharT __space = __os.widen(' ');
__os.flags(__ios_base::scientific | __ios_base::left);
__os.fill(__space);
- __os.precision(std::numeric_limits<_RealType>::digits10 + 1);
+ __os.precision(std::numeric_limits<_RealType>::max_digits10);
__os << __x.m() << __space << __x.s()
<< __space << __x._M_nd;
const _CharT __space = __os.widen(' ');
__os.flags(__ios_base::scientific | __ios_base::left);
__os.fill(__space);
- __os.precision(std::numeric_limits<_RealType>::digits10 + 1);
+ __os.precision(std::numeric_limits<_RealType>::max_digits10);
__os << __x.n() << __space << __x._M_gd;
const _CharT __space = __os.widen(' ');
__os.flags(__ios_base::scientific | __ios_base::left);
__os.fill(__space);
- __os.precision(std::numeric_limits<_RealType>::digits10 + 1);
+ __os.precision(std::numeric_limits<_RealType>::max_digits10);
__os << __x.a() << __space << __x.b();
const _CharT __space = __os.widen(' ');
__os.flags(__ios_base::scientific | __ios_base::left);
__os.fill(__space);
- __os.precision(std::numeric_limits<_RealType>::digits10 + 1);
+ __os.precision(std::numeric_limits<_RealType>::max_digits10);
__os << __x.m() << __space << __x.n()
<< __space << __x._M_gd_x << __space << __x._M_gd_y;
const _CharT __space = __os.widen(' ');
__os.flags(__ios_base::scientific | __ios_base::left);
__os.fill(__space);
- __os.precision(std::numeric_limits<_RealType>::digits10 + 1);
+ __os.precision(std::numeric_limits<_RealType>::max_digits10);
__os << __x.n() << __space << __x._M_nd << __space << __x._M_gd;
const _CharT __space = __os.widen(' ');
__os.flags(__ios_base::scientific | __ios_base::left);
__os.fill(__space);
- __os.precision(std::numeric_limits<_RealType>::digits10 + 1);
+ __os.precision(std::numeric_limits<_RealType>::max_digits10);
__os << __x.alpha() << __space << __x.beta()
<< __space << __x._M_nd;
const _CharT __space = __os.widen(' ');
__os.flags(__ios_base::scientific | __ios_base::left);
__os.fill(__space);
- __os.precision(std::numeric_limits<_RealType>::digits10 + 1);
+ __os.precision(std::numeric_limits<_RealType>::max_digits10);
__os << __x.a() << __space << __x.b();
const _CharT __space = __os.widen(' ');
__os.flags(__ios_base::scientific | __ios_base::left);
__os.fill(__space);
- __os.precision(std::numeric_limits<_RealType>::digits10 + 1);
+ __os.precision(std::numeric_limits<_RealType>::max_digits10);
__os << __x.a() << __space << __x.b();
if (_M_prob.size() < 2)
{
_M_prob.clear();
- _M_prob.push_back(1.0);
return;
}
const double __sum = std::accumulate(_M_prob.begin(),
_M_prob.end(), 0.0);
// Now normalize the probabilites.
- std::transform(_M_prob.begin(), _M_prob.end(), _M_prob.begin(),
- std::bind2nd(std::divides<double>(), __sum));
+ __detail::__transform(_M_prob.begin(), _M_prob.end(), _M_prob.begin(),
+ std::bind2nd(std::divides<double>(), __sum));
// Accumulate partial sums.
_M_cp.reserve(_M_prob.size());
std::partial_sum(_M_prob.begin(), _M_prob.end(),
operator()(_UniformRandomNumberGenerator& __urng,
const param_type& __param)
{
+ if (__param._M_cp.empty())
+ return result_type(0);
+
__detail::_Adaptor<_UniformRandomNumberGenerator, double>
__aurng(__urng);
const _CharT __space = __os.widen(' ');
__os.flags(__ios_base::scientific | __ios_base::left);
__os.fill(__space);
- __os.precision(std::numeric_limits<double>::digits10 + 1);
+ __os.precision(std::numeric_limits<double>::max_digits10);
std::vector<double> __prob = __x.probabilities();
__os << __prob.size();
piecewise_constant_distribution<_RealType>::param_type::
_M_initialize()
{
- if (_M_int.size() < 2)
+ if (_M_int.size() < 2
+ || (_M_int.size() == 2
+ && _M_int[0] == _RealType(0)
+ && _M_int[1] == _RealType(1)))
{
_M_int.clear();
- _M_int.reserve(2);
- _M_int.push_back(_RealType(0));
- _M_int.push_back(_RealType(1));
-
_M_den.clear();
- _M_den.push_back(1.0);
-
return;
}
const double __sum = std::accumulate(_M_den.begin(),
_M_den.end(), 0.0);
- std::transform(_M_den.begin(), _M_den.end(), _M_den.begin(),
- std::bind2nd(std::divides<double>(), __sum));
+ __detail::__transform(_M_den.begin(), _M_den.end(), _M_den.begin(),
+ std::bind2nd(std::divides<double>(), __sum));
_M_cp.reserve(_M_den.size());
std::partial_sum(_M_den.begin(), _M_den.end(),
__aurng(__urng);
const double __p = __aurng();
+ if (__param._M_cp.empty())
+ return __p;
+
auto __pos = std::lower_bound(__param._M_cp.begin(),
__param._M_cp.end(), __p);
const size_t __i = __pos - __param._M_cp.begin();
const _CharT __space = __os.widen(' ');
__os.flags(__ios_base::scientific | __ios_base::left);
__os.fill(__space);
- __os.precision(std::numeric_limits<_RealType>::digits10 + 1);
+ __os.precision(std::numeric_limits<_RealType>::max_digits10);
std::vector<_RealType> __int = __x.intervals();
__os << __int.size() - 1;
piecewise_linear_distribution<_RealType>::param_type::
_M_initialize()
{
- if (_M_int.size() < 2)
+ if (_M_int.size() < 2
+ || (_M_int.size() == 2
+ && _M_int[0] == _RealType(0)
+ && _M_int[1] == _RealType(1)
+ && _M_den[0] == _M_den[1]))
{
_M_int.clear();
- _M_int.reserve(2);
- _M_int.push_back(_RealType(0));
- _M_int.push_back(_RealType(1));
-
_M_den.clear();
- _M_den.reserve(2);
- _M_den.push_back(1.0);
- _M_den.push_back(1.0);
-
return;
}
}
// Now normalize the densities...
- std::transform(_M_den.begin(), _M_den.end(), _M_den.begin(),
- std::bind2nd(std::divides<double>(), __sum));
+ __detail::__transform(_M_den.begin(), _M_den.end(), _M_den.begin(),
+ std::bind2nd(std::divides<double>(), __sum));
// ... and partial sums...
- std::transform(_M_cp.begin(), _M_cp.end(), _M_cp.begin(),
- std::bind2nd(std::divides<double>(), __sum));
+ __detail::__transform(_M_cp.begin(), _M_cp.end(), _M_cp.begin(),
+ std::bind2nd(std::divides<double>(), __sum));
// ... and slopes.
- std::transform(_M_m.begin(), _M_m.end(), _M_m.begin(),
- std::bind2nd(std::divides<double>(), __sum));
+ __detail::__transform(_M_m.begin(), _M_m.end(), _M_m.begin(),
+ std::bind2nd(std::divides<double>(), __sum));
// Make sure the last cumulative probablility is one.
_M_cp[_M_cp.size() - 1] = 1.0;
}
__aurng(__urng);
const double __p = __aurng();
+ if (__param._M_cp.empty())
+ return __p;
+
auto __pos = std::lower_bound(__param._M_cp.begin(),
__param._M_cp.end(), __p);
const size_t __i = __pos - __param._M_cp.begin();
const _CharT __space = __os.widen(' ');
__os.flags(__ios_base::scientific | __ios_base::left);
__os.fill(__space);
- __os.precision(std::numeric_limits<_RealType>::digits10 + 1);
+ __os.precision(std::numeric_limits<_RealType>::max_digits10);
std::vector<_RealType> __int = __x.intervals();
__os << __int.size() - 1;
}
return __sum / __tmp;
}
-}
+
+_GLIBCXX_END_NAMESPACE_VERSION
+} // namespace
+
+#endif
projects / gcc.git / blobdiff