// random number generation -*- C++ -*-
-// Copyright (C) 2009, 2010 Free Software Foundation, Inc.
+// Copyright (C) 2009-2014 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
/**
* @file bits/random.h
* 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}
*/
#ifndef _RANDOM_H
#include <vector>
-namespace std
+namespace std _GLIBCXX_VISIBILITY(default)
{
+_GLIBCXX_BEGIN_NAMESPACE_VERSION
+
// [26.4] Random number generation
/**
_RealType
generate_canonical(_UniformRandomNumberGenerator& __g);
+_GLIBCXX_END_NAMESPACE_VERSION
+
/*
* Implementation-space details.
*/
namespace __detail
{
+ _GLIBCXX_BEGIN_NAMESPACE_VERSION
+
template<typename _UIntType, size_t __w,
bool = __w < static_cast<size_t>
(std::numeric_limits<_UIntType>::digits)>
struct _Shift<_UIntType, __w, true>
{ static const _UIntType __value = _UIntType(1) << __w; };
- template<typename _Tp, _Tp __m, _Tp __a, _Tp __c, bool>
- struct _Mod;
+ template<int __s,
+ int __which = ((__s <= __CHAR_BIT__ * sizeof (int))
+ + (__s <= __CHAR_BIT__ * sizeof (long))
+ + (__s <= __CHAR_BIT__ * sizeof (long long))
+ /* assume long long no bigger than __int128 */
+ + (__s <= 128))>
+ struct _Select_uint_least_t
+ {
+ static_assert(__which < 0, /* needs to be dependent */
+ "sorry, would be too much trouble for a slow result");
+ };
+
+ template<int __s>
+ struct _Select_uint_least_t<__s, 4>
+ { typedef unsigned int type; };
+
+ template<int __s>
+ struct _Select_uint_least_t<__s, 3>
+ { typedef unsigned long type; };
+
+ template<int __s>
+ struct _Select_uint_least_t<__s, 2>
+ { typedef unsigned long long type; };
+
+#ifdef _GLIBCXX_USE_INT128
+ template<int __s>
+ struct _Select_uint_least_t<__s, 1>
+ { typedef unsigned __int128 type; };
+#endif
+
+ // Assume a != 0, a < m, c < m, x < m.
+ template<typename _Tp, _Tp __m, _Tp __a, _Tp __c,
+ bool __big_enough = (!(__m & (__m - 1))
+ || (_Tp(-1) - __c) / __a >= __m - 1),
+ bool __schrage_ok = __m % __a < __m / __a>
+ struct _Mod
+ {
+ typedef typename _Select_uint_least_t<std::__lg(__a)
+ + std::__lg(__m) + 2>::type _Tp2;
+ static _Tp
+ __calc(_Tp __x)
+ { return static_cast<_Tp>((_Tp2(__a) * __x + __c) % __m); }
+ };
+
+ // Schrage.
+ template<typename _Tp, _Tp __m, _Tp __a, _Tp __c>
+ struct _Mod<_Tp, __m, __a, __c, false, true>
+ {
+ static _Tp
+ __calc(_Tp __x);
+ };
+
+ // Special cases:
+ // - for m == 2^n or m == 0, unsigned integer overflow is safe.
+ // - a * (m - 1) + c fits in _Tp, there is no overflow.
+ template<typename _Tp, _Tp __m, _Tp __a, _Tp __c, bool __s>
+ struct _Mod<_Tp, __m, __a, __c, true, __s>
+ {
+ static _Tp
+ __calc(_Tp __x)
+ {
+ _Tp __res = __a * __x + __c;
+ if (__m)
+ __res %= __m;
+ return __res;
+ }
+ };
- // Dispatch based on modulus value to prevent divide-by-zero compile-time
- // errors when m == 0.
template<typename _Tp, _Tp __m, _Tp __a = 1, _Tp __c = 0>
inline _Tp
__mod(_Tp __x)
- { return _Mod<_Tp, __m, __a, __c, __m == 0>::__calc(__x); }
+ { return _Mod<_Tp, __m, __a, __c>::__calc(__x); }
+
+ /* Determine whether number is a power of 2. */
+ template<typename _Tp>
+ inline bool
+ _Power_of_2(_Tp __x)
+ {
+ return ((__x - 1) & __x) == 0;
+ };
/*
* An adaptor class for converting the output of any Generator into
private:
_Engine& _M_g;
};
+
+ _GLIBCXX_END_NAMESPACE_VERSION
} // namespace __detail
+_GLIBCXX_BEGIN_NAMESPACE_VERSION
+
/**
* @addtogroup random_generators Random Number Generators
* @ingroup random
typedef _UIntType result_type;
/** The multiplier. */
- static const result_type multiplier = __a;
+ static constexpr result_type multiplier = __a;
/** An increment. */
- static const result_type increment = __c;
+ static constexpr result_type increment = __c;
/** The modulus. */
- static const result_type modulus = __m;
- static const result_type default_seed = 1u;
+ static constexpr result_type modulus = __m;
+ static constexpr result_type default_seed = 1u;
/**
* @brief Constructs a %linear_congruential_engine random number
*
* The minimum depends on the @p __c parameter: if it is zero, the
* minimum generated must be > 0, otherwise 0 is allowed.
- *
- * @todo This should be constexpr.
*/
- result_type
- min() const
+ static constexpr result_type
+ min()
{ return __c == 0u ? 1u : 0u; }
/**
* @brief Gets the largest possible value in the output range.
- *
- * @todo This should be constexpr.
*/
- result_type
- max() const
+ static constexpr result_type
+ max()
{ return __m - 1u; }
/**
* @brief Discard a sequence of random numbers.
- *
- * @todo Look for a faster way to do discard.
*/
void
discard(unsigned long long __z)
template<typename _UIntType1, _UIntType1 __a1, _UIntType1 __c1,
_UIntType1 __m1, typename _CharT, typename _Traits>
friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
const std::linear_congruential_engine<_UIntType1,
- __a1, __c1, __m1>&);
+ __a1, __c1, __m1>& __lcr);
/**
* @brief Sets the state of the engine by reading its textual
template<typename _UIntType1, _UIntType1 __a1, _UIntType1 __c1,
_UIntType1 __m1, typename _CharT, typename _Traits>
friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>&,
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
std::linear_congruential_engine<_UIntType1, __a1,
- __c1, __m1>&);
+ __c1, __m1>& __lcr);
private:
_UIntType _M_x;
* This algorithm was originally invented by Makoto Matsumoto and
* Takuji Nishimura.
*
- * @var word_size The number of bits in each element of the state vector.
- * @var state_size The degree of recursion.
- * @var shift_size The period parameter.
- * @var mask_bits The separation point bit index.
- * @var parameter_a The last row of the twist matrix.
- * @var output_u The first right-shift tempering matrix parameter.
- * @var output_s The first left-shift tempering matrix parameter.
- * @var output_b The first left-shift tempering matrix mask.
- * @var output_t The second left-shift tempering matrix parameter.
- * @var output_c The second left-shift tempering matrix mask.
- * @var output_l The second right-shift tempering matrix parameter.
+ * @tparam __w Word size, the number of bits in each element of
+ * the state vector.
+ * @tparam __n The degree of recursion.
+ * @tparam __m The period parameter.
+ * @tparam __r The separation point bit index.
+ * @tparam __a The last row of the twist matrix.
+ * @tparam __u The first right-shift tempering matrix parameter.
+ * @tparam __d The first right-shift tempering matrix mask.
+ * @tparam __s The first left-shift tempering matrix parameter.
+ * @tparam __b The first left-shift tempering matrix mask.
+ * @tparam __t The second left-shift tempering matrix parameter.
+ * @tparam __c The second left-shift tempering matrix mask.
+ * @tparam __l The second right-shift tempering matrix parameter.
+ * @tparam __f Initialization multiplier.
*/
template<typename _UIntType, size_t __w,
size_t __n, size_t __m, size_t __r,
typedef _UIntType result_type;
// parameter values
- static const size_t word_size = __w;
- static const size_t state_size = __n;
- static const size_t shift_size = __m;
- static const size_t mask_bits = __r;
- static const result_type xor_mask = __a;
- static const size_t tempering_u = __u;
- static const result_type tempering_d = __d;
- static const size_t tempering_s = __s;
- static const result_type tempering_b = __b;
- static const size_t tempering_t = __t;
- static const result_type tempering_c = __c;
- static const size_t tempering_l = __l;
- static const result_type initialization_multiplier = __f;
- static const result_type default_seed = 5489u;
+ static constexpr size_t word_size = __w;
+ static constexpr size_t state_size = __n;
+ static constexpr size_t shift_size = __m;
+ static constexpr size_t mask_bits = __r;
+ static constexpr result_type xor_mask = __a;
+ static constexpr size_t tempering_u = __u;
+ static constexpr result_type tempering_d = __d;
+ static constexpr size_t tempering_s = __s;
+ static constexpr result_type tempering_b = __b;
+ static constexpr size_t tempering_t = __t;
+ static constexpr result_type tempering_c = __c;
+ static constexpr size_t tempering_l = __l;
+ static constexpr result_type initialization_multiplier = __f;
+ static constexpr result_type default_seed = 5489u;
// constructors and member function
explicit
/**
* @brief Gets the smallest possible value in the output range.
- *
- * @todo This should be constexpr.
*/
- result_type
- min() const
+ static constexpr result_type
+ min()
{ return 0; };
/**
* @brief Gets the largest possible value in the output range.
- *
- * @todo This should be constexpr.
*/
- result_type
- max() const
+ static constexpr result_type
+ max()
{ return __detail::_Shift<_UIntType, __w>::__value - 1; }
/**
* @brief Discard a sequence of random numbers.
- *
- * @todo Look for a faster way to do discard.
*/
void
- discard(unsigned long long __z)
- {
- for (; __z != 0ULL; --__z)
- (*this)();
- }
+ discard(unsigned long long __z);
result_type
operator()();
friend bool
operator==(const mersenne_twister_engine& __lhs,
const mersenne_twister_engine& __rhs)
- { return std::equal(__lhs._M_x, __lhs._M_x + state_size, __rhs._M_x); }
+ { return (std::equal(__lhs._M_x, __lhs._M_x + state_size, __rhs._M_x)
+ && __lhs._M_p == __rhs._M_p); }
/**
* @brief Inserts the current state of a % mersenne_twister_engine
_UIntType1 __c1, size_t __l1, _UIntType1 __f1,
typename _CharT, typename _Traits>
friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
const std::mersenne_twister_engine<_UIntType1, __w1, __n1,
__m1, __r1, __a1, __u1, __d1, __s1, __b1, __t1, __c1,
- __l1, __f1>&);
+ __l1, __f1>& __x);
/**
* @brief Extracts the current state of a % mersenne_twister_engine
_UIntType1 __c1, size_t __l1, _UIntType1 __f1,
typename _CharT, typename _Traits>
friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>&,
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
std::mersenne_twister_engine<_UIntType1, __w1, __n1, __m1,
__r1, __a1, __u1, __d1, __s1, __b1, __t1, __c1,
- __l1, __f1>&);
+ __l1, __f1>& __x);
private:
+ void _M_gen_rand();
+
_UIntType _M_x[state_size];
size_t _M_p;
};
typedef _UIntType result_type;
// parameter values
- static const size_t word_size = __w;
- static const size_t short_lag = __s;
- static const size_t long_lag = __r;
- static const result_type default_seed = 19780503u;
+ static constexpr size_t word_size = __w;
+ static constexpr size_t short_lag = __s;
+ static constexpr size_t long_lag = __r;
+ static constexpr result_type default_seed = 19780503u;
/**
* @brief Constructs an explicitly seeded % subtract_with_carry_engine
/**
* @brief Gets the inclusive minimum value of the range of random
* integers returned by this generator.
- *
- * @todo This should be constexpr.
*/
- result_type
- min() const
+ static constexpr result_type
+ min()
{ return 0; }
/**
* @brief Gets the inclusive maximum value of the range of random
* integers returned by this generator.
- *
- * @todo This should be constexpr.
*/
- result_type
- max() const
+ static constexpr result_type
+ max()
{ return __detail::_Shift<_UIntType, __w>::__value - 1; }
/**
* @brief Discard a sequence of random numbers.
- *
- * @todo Look for a faster way to do discard.
*/
void
discard(unsigned long long __z)
friend bool
operator==(const subtract_with_carry_engine& __lhs,
const subtract_with_carry_engine& __rhs)
- { return std::equal(__lhs._M_x, __lhs._M_x + long_lag, __rhs._M_x); }
+ { return (std::equal(__lhs._M_x, __lhs._M_x + long_lag, __rhs._M_x)
+ && __lhs._M_carry == __rhs._M_carry
+ && __lhs._M_p == __rhs._M_p); }
/**
* @brief Inserts the current state of a % subtract_with_carry_engine
typedef typename _RandomNumberEngine::result_type result_type;
// parameter values
- static const size_t block_size = __p;
- static const size_t used_block = __r;
+ static constexpr size_t block_size = __p;
+ static constexpr size_t used_block = __r;
/**
* @brief Constructs a default %discard_block_engine engine.
* @brief Copy constructs a %discard_block_engine engine.
*
* Copies an existing base class random number generator.
- * @param rng An existing (base class) engine object.
+ * @param __rng An existing (base class) engine object.
*/
explicit
- discard_block_engine(const _RandomNumberEngine& __rne)
- : _M_b(__rne), _M_n(0) { }
+ discard_block_engine(const _RandomNumberEngine& __rng)
+ : _M_b(__rng), _M_n(0) { }
/**
* @brief Move constructs a %discard_block_engine engine.
*
* Copies an existing base class random number generator.
- * @param rng An existing (base class) engine object.
+ * @param __rng An existing (base class) engine object.
*/
explicit
- discard_block_engine(_RandomNumberEngine&& __rne)
- : _M_b(std::move(__rne)), _M_n(0) { }
+ discard_block_engine(_RandomNumberEngine&& __rng)
+ : _M_b(std::move(__rng)), _M_n(0) { }
/**
* @brief Seed constructs a %discard_block_engine engine.
* object.
*/
const _RandomNumberEngine&
- base() const
+ base() const noexcept
{ return _M_b; }
/**
* @brief Gets the minimum value in the generated random number range.
- *
- * @todo This should be constexpr.
*/
- result_type
- min() const
- { return _M_b.min(); }
+ static constexpr result_type
+ min()
+ { return _RandomNumberEngine::min(); }
/**
* @brief Gets the maximum value in the generated random number range.
- *
- * @todo This should be constexpr.
*/
- result_type
- max() const
- { return _M_b.max(); }
+ static constexpr result_type
+ max()
+ { return _RandomNumberEngine::max(); }
/**
* @brief Discard a sequence of random numbers.
- *
- * @todo Look for a faster way to do discard.
*/
void
discard(unsigned long long __z)
template<typename _RandomNumberEngine1, size_t __p1, size_t __r1,
typename _CharT, typename _Traits>
friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
const std::discard_block_engine<_RandomNumberEngine1,
- __p1, __r1>&);
+ __p1, __r1>& __x);
/**
* @brief Extracts the current state of a % subtract_with_carry_engine
template<typename _RandomNumberEngine1, size_t __p1, size_t __r1,
typename _CharT, typename _Traits>
friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>&,
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
std::discard_block_engine<_RandomNumberEngine1,
- __p1, __r1>&);
+ __p1, __r1>& __x);
private:
_RandomNumberEngine _M_b;
* @brief Copy constructs a %independent_bits_engine engine.
*
* Copies an existing base class random number generator.
- * @param rng An existing (base class) engine object.
+ * @param __rng An existing (base class) engine object.
*/
explicit
- independent_bits_engine(const _RandomNumberEngine& __rne)
- : _M_b(__rne) { }
+ independent_bits_engine(const _RandomNumberEngine& __rng)
+ : _M_b(__rng) { }
/**
* @brief Move constructs a %independent_bits_engine engine.
*
* Copies an existing base class random number generator.
- * @param rng An existing (base class) engine object.
+ * @param __rng An existing (base class) engine object.
*/
explicit
- independent_bits_engine(_RandomNumberEngine&& __rne)
- : _M_b(std::move(__rne)) { }
+ independent_bits_engine(_RandomNumberEngine&& __rng)
+ : _M_b(std::move(__rng)) { }
/**
* @brief Seed constructs a %independent_bits_engine engine.
* object.
*/
const _RandomNumberEngine&
- base() const
+ base() const noexcept
{ return _M_b; }
/**
* @brief Gets the minimum value in the generated random number range.
- *
- * @todo This should be constexpr.
*/
- result_type
- min() const
+ static constexpr result_type
+ min()
{ return 0U; }
/**
* @brief Gets the maximum value in the generated random number range.
- *
- * @todo This should be constexpr.
*/
- result_type
- max() const
+ static constexpr result_type
+ max()
{ return __detail::_Shift<_UIntType, __w>::__value - 1; }
/**
* @brief Discard a sequence of random numbers.
- *
- * @todo Look for a faster way to do discard.
*/
void
discard(unsigned long long __z)
/** The type of the generated random value. */
typedef typename _RandomNumberEngine::result_type result_type;
- static const size_t table_size = __k;
+ static constexpr size_t table_size = __k;
/**
* @brief Constructs a default %shuffle_order_engine engine.
* @brief Copy constructs a %shuffle_order_engine engine.
*
* Copies an existing base class random number generator.
- * @param rng An existing (base class) engine object.
+ * @param __rng An existing (base class) engine object.
*/
explicit
- shuffle_order_engine(const _RandomNumberEngine& __rne)
- : _M_b(__rne)
+ shuffle_order_engine(const _RandomNumberEngine& __rng)
+ : _M_b(__rng)
{ _M_initialize(); }
/**
* @brief Move constructs a %shuffle_order_engine engine.
*
* Copies an existing base class random number generator.
- * @param rng An existing (base class) engine object.
+ * @param __rng An existing (base class) engine object.
*/
explicit
- shuffle_order_engine(_RandomNumberEngine&& __rne)
- : _M_b(std::move(__rne))
+ shuffle_order_engine(_RandomNumberEngine&& __rng)
+ : _M_b(std::move(__rng))
{ _M_initialize(); }
/**
* Gets a const reference to the underlying generator engine object.
*/
const _RandomNumberEngine&
- base() const
+ base() const noexcept
{ return _M_b; }
/**
* Gets the minimum value in the generated random number range.
- *
- * @todo This should be constexpr.
*/
- result_type
- min() const
- { return _M_b.min(); }
+ static constexpr result_type
+ min()
+ { return _RandomNumberEngine::min(); }
/**
* Gets the maximum value in the generated random number range.
- *
- * @todo This should be constexpr.
*/
- result_type
- max() const
- { return _M_b.max(); }
+ static constexpr result_type
+ max()
+ { return _RandomNumberEngine::max(); }
/**
* Discard a sequence of random numbers.
- *
- * @todo Look for a faster way to do discard.
*/
void
discard(unsigned long long __z)
friend bool
operator==(const shuffle_order_engine& __lhs,
const shuffle_order_engine& __rhs)
- { return __lhs._M_b == __rhs._M_b; }
+ { return (__lhs._M_b == __rhs._M_b
+ && std::equal(__lhs._M_v, __lhs._M_v + __k, __rhs._M_v)
+ && __lhs._M_y == __rhs._M_y); }
/**
* @brief Inserts the current state of a %shuffle_order_engine random
template<typename _RandomNumberEngine1, size_t __k1,
typename _CharT, typename _Traits>
friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
const std::shuffle_order_engine<_RandomNumberEngine1,
- __k1>&);
+ __k1>& __x);
/**
* @brief Extracts the current state of a % subtract_with_carry_engine
template<typename _RandomNumberEngine1, size_t __k1,
typename _CharT, typename _Traits>
friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>&,
- std::shuffle_order_engine<_RandomNumberEngine1, __k1>&);
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::shuffle_order_engine<_RandomNumberEngine1, __k1>& __x);
private:
void _M_initialize()
#ifdef _GLIBCXX_USE_RANDOM_TR1
explicit
- random_device(const std::string& __token = "/dev/urandom")
+ random_device(const std::string& __token = "default")
{
- if ((__token != "/dev/urandom" && __token != "/dev/random")
- || !(_M_file = std::fopen(__token.c_str(), "rb")))
- std::__throw_runtime_error(__N("random_device::"
- "random_device(const std::string&)"));
+ _M_init(__token);
}
~random_device()
- { std::fclose(_M_file); }
+ { _M_fini(); }
#else
explicit
random_device(const std::string& __token = "mt19937")
- : _M_mt(_M_strtoul(__token)) { }
-
- private:
- static unsigned long
- _M_strtoul(const std::string& __str)
- {
- unsigned long __ret = 5489UL;
- if (__str != "mt19937")
- {
- const char* __nptr = __str.c_str();
- char* __endptr;
- __ret = std::strtoul(__nptr, &__endptr, 0);
- if (*__nptr == '\0' || *__endptr != '\0')
- std::__throw_runtime_error(__N("random_device::_M_strtoul"
- "(const std::string&)"));
- }
- return __ret;
- }
+ { _M_init_pretr1(__token); }
public:
#endif
- result_type
- min() const
+ static constexpr result_type
+ min()
{ return std::numeric_limits<result_type>::min(); }
- result_type
- max() const
+ static constexpr result_type
+ max()
{ return std::numeric_limits<result_type>::max(); }
double
- entropy() const
+ entropy() const noexcept
{ return 0.0; }
result_type
operator()()
{
#ifdef _GLIBCXX_USE_RANDOM_TR1
- result_type __ret;
- std::fread(reinterpret_cast<void*>(&__ret), sizeof(result_type),
- 1, _M_file);
- return __ret;
+ return this->_M_getval();
#else
- return _M_mt();
+ return this->_M_getval_pretr1();
#endif
}
private:
-#ifdef _GLIBCXX_USE_RANDOM_TR1
- FILE* _M_file;
-#else
- mt19937 _M_mt;
-#endif
+ void _M_init(const std::string& __token);
+ void _M_init_pretr1(const std::string& __token);
+ void _M_fini();
+
+ result_type _M_getval();
+ result_type _M_getval_pretr1();
+
+ union
+ {
+ void* _M_file;
+ mt19937 _M_mt;
+ };
};
/* @} */ // group random_generators
*/
/**
- * @addtogroup random_distributions_uniform Uniform
+ * @addtogroup random_distributions_uniform Uniform Distributions
* @ingroup random_distributions
* @{
*/
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, this->param()); }
+ { return this->operator()(__urng, _M_param); }
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng,
const param_type& __p);
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng)
+ { this->__generate(__f, __t, __urng, _M_param); }
+
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ template<typename _UniformRandomNumberGenerator>
+ void
+ __generate(result_type* __f, result_type* __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ /**
+ * @brief Return true if two uniform integer distributions have
+ * the same parameters.
+ */
+ friend bool
+ operator==(const uniform_int_distribution& __d1,
+ const uniform_int_distribution& __d2)
+ { return __d1._M_param == __d2._M_param; }
+
+ private:
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
param_type _M_param;
};
- /**
- * @brief Return true if two uniform integer distributions have
- * the same parameters.
- */
- template<typename _IntType>
- inline bool
- operator==(const std::uniform_int_distribution<_IntType>& __d1,
- const std::uniform_int_distribution<_IntType>& __d2)
- { return __d1.param() == __d2.param(); }
-
/**
* @brief Return true if two uniform integer distributions have
* different parameters.
/**
* @brief Constructs a uniform_real_distribution object.
*
- * @param __min [IN] The lower bound of the distribution.
- * @param __max [IN] The upper bound of the distribution.
+ * @param __a [IN] The lower bound of the distribution.
+ * @param __b [IN] The upper bound of the distribution.
*/
explicit
uniform_real_distribution(_RealType __a = _RealType(0),
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, this->param()); }
+ { return this->operator()(__urng, _M_param); }
template<typename _UniformRandomNumberGenerator>
result_type
return (__aurng() * (__p.b() - __p.a())) + __p.a();
}
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng)
+ { this->__generate(__f, __t, __urng, _M_param); }
+
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ template<typename _UniformRandomNumberGenerator>
+ void
+ __generate(result_type* __f, result_type* __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ /**
+ * @brief Return true if two uniform real distributions have
+ * the same parameters.
+ */
+ friend bool
+ operator==(const uniform_real_distribution& __d1,
+ const uniform_real_distribution& __d2)
+ { return __d1._M_param == __d2._M_param; }
+
private:
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
param_type _M_param;
};
- /**
- * @brief Return true if two uniform real distributions have
- * the same parameters.
- */
- template<typename _IntType>
- inline bool
- operator==(const std::uniform_real_distribution<_IntType>& __d1,
- const std::uniform_real_distribution<_IntType>& __d2)
- { return __d1.param() == __d2.param(); }
-
/**
* @brief Return true if two uniform real distributions have
* different parameters.
/* @} */ // group random_distributions_uniform
/**
- * @addtogroup random_distributions_normal Normal
+ * @addtogroup random_distributions_normal Normal Distributions
* @ingroup random_distributions
* @{
*/
*/
result_type
min() const
- { return std::numeric_limits<result_type>::min(); }
+ { return std::numeric_limits<result_type>::lowest(); }
/**
* @brief Returns the least upper bound value of the distribution.
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, this->param()); }
+ { return this->operator()(__urng, _M_param); }
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng,
const param_type& __p);
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng)
+ { this->__generate(__f, __t, __urng, _M_param); }
+
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ template<typename _UniformRandomNumberGenerator>
+ void
+ __generate(result_type* __f, result_type* __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
/**
* @brief Return true if two normal distributions have
* the same parameters and the sequences that would
*/
template<typename _RealType1, typename _CharT, typename _Traits>
friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
- const std::normal_distribution<_RealType1>&);
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::normal_distribution<_RealType1>& __x);
/**
* @brief Extracts a %normal_distribution random number distribution
*/
template<typename _RealType1, typename _CharT, typename _Traits>
friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>&,
- std::normal_distribution<_RealType1>&);
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::normal_distribution<_RealType1>& __x);
private:
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
param_type _M_param;
result_type _M_saved;
bool _M_saved_available;
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, this->param()); }
+ { return this->operator()(__urng, _M_param); }
template<typename _UniformRandomNumberGenerator>
result_type
const param_type& __p)
{ return std::exp(__p.s() * _M_nd(__urng) + __p.m()); }
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng)
+ { this->__generate(__f, __t, __urng, _M_param); }
+
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ template<typename _UniformRandomNumberGenerator>
+ void
+ __generate(result_type* __f, result_type* __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
/**
* @brief Return true if two lognormal distributions have
* the same parameters and the sequences that would
* be generated are equal.
*/
- template<typename _RealType1>
- friend bool
- operator==(const std::lognormal_distribution<_RealType1>& __d1,
- const std::lognormal_distribution<_RealType1>& __d2)
- { return (__d1.param() == __d2.param()
- && __d1._M_nd == __d2._M_nd); }
+ friend bool
+ operator==(const lognormal_distribution& __d1,
+ const lognormal_distribution& __d2)
+ { return (__d1._M_param == __d2._M_param
+ && __d1._M_nd == __d2._M_nd); }
/**
* @brief Inserts a %lognormal_distribution random number distribution
*/
template<typename _RealType1, typename _CharT, typename _Traits>
friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
- const std::lognormal_distribution<_RealType1>&);
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::lognormal_distribution<_RealType1>& __x);
/**
* @brief Extracts a %lognormal_distribution random number distribution
*/
template<typename _RealType1, typename _CharT, typename _Traits>
friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>&,
- std::lognormal_distribution<_RealType1>&);
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::lognormal_distribution<_RealType1>& __x);
private:
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
param_type _M_param;
std::normal_distribution<result_type> _M_nd;
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, this->param()); }
+ { return this->operator()(__urng, _M_param); }
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng,
const param_type& __p);
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng)
+ { this->__generate(__f, __t, __urng, _M_param); }
+
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ template<typename _UniformRandomNumberGenerator>
+ void
+ __generate(result_type* __f, result_type* __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
/**
* @brief Return true if two gamma distributions have the same
* parameters and the sequences that would be generated
* are equal.
*/
- template<typename _RealType1>
- friend bool
- operator==(const std::gamma_distribution<_RealType1>& __d1,
- const std::gamma_distribution<_RealType1>& __d2)
- { return (__d1.param() == __d2.param()
- && __d1._M_nd == __d2._M_nd); }
+ friend bool
+ operator==(const gamma_distribution& __d1,
+ const gamma_distribution& __d2)
+ { return (__d1._M_param == __d2._M_param
+ && __d1._M_nd == __d2._M_nd); }
/**
* @brief Inserts a %gamma_distribution random number distribution
*/
template<typename _RealType1, typename _CharT, typename _Traits>
friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
- const std::gamma_distribution<_RealType1>&);
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::gamma_distribution<_RealType1>& __x);
/**
* @brief Extracts a %gamma_distribution random number distribution
*/
template<typename _RealType1, typename _CharT, typename _Traits>
friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>&,
- std::gamma_distribution<_RealType1>&);
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::gamma_distribution<_RealType1>& __x);
private:
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
param_type _M_param;
std::normal_distribution<result_type> _M_nd;
* @brief Return true if two gamma distributions are different.
*/
template<typename _RealType>
- inline bool
+ inline bool
operator!=(const std::gamma_distribution<_RealType>& __d1,
const std::gamma_distribution<_RealType>& __d2)
{ return !(__d1 == __d2); }
return 2 * _M_gd(__urng, param_type(__p.n() / 2));
}
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng)
+ { this->__generate_impl(__f, __t, __urng); }
+
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { typename std::gamma_distribution<result_type>::param_type
+ __p2(__p.n() / 2);
+ this->__generate_impl(__f, __t, __urng, __p2); }
+
+ template<typename _UniformRandomNumberGenerator>
+ void
+ __generate(result_type* __f, result_type* __t,
+ _UniformRandomNumberGenerator& __urng)
+ { this->__generate_impl(__f, __t, __urng); }
+
+ template<typename _UniformRandomNumberGenerator>
+ void
+ __generate(result_type* __f, result_type* __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { typename std::gamma_distribution<result_type>::param_type
+ __p2(__p.n() / 2);
+ this->__generate_impl(__f, __t, __urng, __p2); }
+
/**
* @brief Return true if two Chi-squared distributions have
* the same parameters and the sequences that would be
* generated are equal.
*/
- template<typename _RealType1>
- friend bool
- operator==(const std::chi_squared_distribution<_RealType1>& __d1,
- const std::chi_squared_distribution<_RealType1>& __d2)
- { return __d1.param() == __d2.param() && __d1._M_gd == __d2._M_gd; }
+ friend bool
+ operator==(const chi_squared_distribution& __d1,
+ const chi_squared_distribution& __d2)
+ { return __d1._M_param == __d2._M_param && __d1._M_gd == __d2._M_gd; }
/**
* @brief Inserts a %chi_squared_distribution random number distribution
*/
template<typename _RealType1, typename _CharT, typename _Traits>
friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
- const std::chi_squared_distribution<_RealType1>&);
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::chi_squared_distribution<_RealType1>& __x);
/**
* @brief Extracts a %chi_squared_distribution random number distribution
*/
template<typename _RealType1, typename _CharT, typename _Traits>
friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>&,
- std::chi_squared_distribution<_RealType1>&);
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::chi_squared_distribution<_RealType1>& __x);
private:
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng);
+
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const typename
+ std::gamma_distribution<result_type>::param_type& __p);
+
param_type _M_param;
std::gamma_distribution<result_type> _M_gd;
*/
result_type
min() const
- { return std::numeric_limits<result_type>::min(); }
+ { return std::numeric_limits<result_type>::lowest(); }
/**
* @brief Returns the least upper bound value of the distribution.
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, this->param()); }
+ { return this->operator()(__urng, _M_param); }
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng,
const param_type& __p);
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng)
+ { this->__generate(__f, __t, __urng, _M_param); }
+
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ template<typename _UniformRandomNumberGenerator>
+ void
+ __generate(result_type* __f, result_type* __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ /**
+ * @brief Return true if two Cauchy distributions have
+ * the same parameters.
+ */
+ friend bool
+ operator==(const cauchy_distribution& __d1,
+ const cauchy_distribution& __d2)
+ { return __d1._M_param == __d2._M_param; }
+
private:
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
param_type _M_param;
};
- /**
- * @brief Return true if two Cauchy distributions have
- * the same parameters.
- */
- template<typename _RealType>
- inline bool
- operator==(const std::cauchy_distribution<_RealType>& __d1,
- const std::cauchy_distribution<_RealType>& __d2)
- { return __d1.param() == __d2.param(); }
-
/**
* @brief Return true if two Cauchy distributions have
* different parameters.
*/
template<typename _RealType, typename _CharT, typename _Traits>
std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
- const std::cauchy_distribution<_RealType>&);
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::cauchy_distribution<_RealType>& __x);
/**
* @brief Extracts a %cauchy_distribution random number distribution
*/
template<typename _RealType, typename _CharT, typename _Traits>
std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>&,
- std::cauchy_distribution<_RealType>&);
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::cauchy_distribution<_RealType>& __x);
/**
/ (_M_gd_y(__urng, param_type(__p.n() / 2)) * m()));
}
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng)
+ { this->__generate_impl(__f, __t, __urng); }
+
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ template<typename _UniformRandomNumberGenerator>
+ void
+ __generate(result_type* __f, result_type* __t,
+ _UniformRandomNumberGenerator& __urng)
+ { this->__generate_impl(__f, __t, __urng); }
+
+ template<typename _UniformRandomNumberGenerator>
+ void
+ __generate(result_type* __f, result_type* __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
/**
* @brief Return true if two Fisher f distributions have
* the same parameters and the sequences that would
* be generated are equal.
*/
- template<typename _RealType1>
- friend bool
- operator==(const std::fisher_f_distribution<_RealType1>& __d1,
- const std::fisher_f_distribution<_RealType1>& __d2)
- { return (__d1.param() == __d2.param()
- && __d1._M_gd_x == __d2._M_gd_x
- && __d1._M_gd_y == __d2._M_gd_y); }
+ friend bool
+ operator==(const fisher_f_distribution& __d1,
+ const fisher_f_distribution& __d2)
+ { return (__d1._M_param == __d2._M_param
+ && __d1._M_gd_x == __d2._M_gd_x
+ && __d1._M_gd_y == __d2._M_gd_y); }
/**
* @brief Inserts a %fisher_f_distribution random number distribution
*/
template<typename _RealType1, typename _CharT, typename _Traits>
friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
- const std::fisher_f_distribution<_RealType1>&);
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::fisher_f_distribution<_RealType1>& __x);
/**
* @brief Extracts a %fisher_f_distribution random number distribution
*/
template<typename _RealType1, typename _CharT, typename _Traits>
friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>&,
- std::fisher_f_distribution<_RealType1>&);
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::fisher_f_distribution<_RealType1>& __x);
private:
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng);
+
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
param_type _M_param;
std::gamma_distribution<result_type> _M_gd_x, _M_gd_y;
};
/**
- * @brief Return true if two Fisher f distributions are diferent.
+ * @brief Return true if two Fisher f distributions are different.
*/
template<typename _RealType>
inline bool
*/
result_type
min() const
- { return std::numeric_limits<result_type>::min(); }
+ { return std::numeric_limits<result_type>::lowest(); }
/**
* @brief Returns the least upper bound value of the distribution.
return _M_nd(__urng) * std::sqrt(__p.n() / __g);
}
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng)
+ { this->__generate_impl(__f, __t, __urng); }
+
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ template<typename _UniformRandomNumberGenerator>
+ void
+ __generate(result_type* __f, result_type* __t,
+ _UniformRandomNumberGenerator& __urng)
+ { this->__generate_impl(__f, __t, __urng); }
+
+ template<typename _UniformRandomNumberGenerator>
+ void
+ __generate(result_type* __f, result_type* __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
/**
* @brief Return true if two Student t distributions have
* the same parameters and the sequences that would
* be generated are equal.
*/
- template<typename _RealType1>
- friend bool
- operator==(const std::student_t_distribution<_RealType1>& __d1,
- const std::student_t_distribution<_RealType1>& __d2)
- { return (__d1.param() == __d2.param()
- && __d1._M_nd == __d2._M_nd && __d1._M_gd == __d2._M_gd); }
+ friend bool
+ operator==(const student_t_distribution& __d1,
+ const student_t_distribution& __d2)
+ { return (__d1._M_param == __d2._M_param
+ && __d1._M_nd == __d2._M_nd && __d1._M_gd == __d2._M_gd); }
/**
* @brief Inserts a %student_t_distribution random number distribution
*/
template<typename _RealType1, typename _CharT, typename _Traits>
friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
- const std::student_t_distribution<_RealType1>&);
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::student_t_distribution<_RealType1>& __x);
/**
* @brief Extracts a %student_t_distribution random number distribution
*/
template<typename _RealType1, typename _CharT, typename _Traits>
friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>&,
- std::student_t_distribution<_RealType1>&);
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::student_t_distribution<_RealType1>& __x);
private:
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng);
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
param_type _M_param;
std::normal_distribution<result_type> _M_nd;
/* @} */ // group random_distributions_normal
/**
- * @addtogroup random_distributions_bernoulli Bernoulli
+ * @addtogroup random_distributions_bernoulli Bernoulli Distributions
* @ingroup random_distributions
* @{
*/
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, this->param()); }
+ { return this->operator()(__urng, _M_param); }
template<typename _UniformRandomNumberGenerator>
result_type
return false;
}
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng)
+ { this->__generate(__f, __t, __urng, _M_param); }
+
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng, const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ template<typename _UniformRandomNumberGenerator>
+ void
+ __generate(result_type* __f, result_type* __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ /**
+ * @brief Return true if two Bernoulli distributions have
+ * the same parameters.
+ */
+ friend bool
+ operator==(const bernoulli_distribution& __d1,
+ const bernoulli_distribution& __d2)
+ { return __d1._M_param == __d2._M_param; }
+
private:
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
param_type _M_param;
};
- /**
- * @brief Return true if two Bernoulli distributions have
- * the same parameters.
- */
- inline bool
- operator==(const std::bernoulli_distribution& __d1,
- const std::bernoulli_distribution& __d2)
- { return __d1.param() == __d2.param(); }
-
/**
* @brief Return true if two Bernoulli distributions have
* different parameters.
*/
template<typename _CharT, typename _Traits>
std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
- const std::bernoulli_distribution&);
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::bernoulli_distribution& __x);
/**
* @brief Extracts a %bernoulli_distribution random number distribution
* @brief A discrete binomial random number distribution.
*
* The formula for the binomial probability density function is
- * @f$p(i|t,p) = \binom{n}{i} p^i (1 - p)^{t - i}@f$ where @f$t@f$
+ * @f$p(i|t,p) = \binom{t}{i} p^i (1 - p)^{t - i}@f$ where @f$t@f$
* and @f$p@f$ are the parameters of the distribution.
*/
template<typename _IntType = int>
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, this->param()); }
+ { return this->operator()(__urng, _M_param); }
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng,
const param_type& __p);
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng)
+ { this->__generate(__f, __t, __urng, _M_param); }
+
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ template<typename _UniformRandomNumberGenerator>
+ void
+ __generate(result_type* __f, result_type* __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
/**
* @brief Return true if two binomial distributions have
* the same parameters and the sequences that would
* be generated are equal.
*/
- template<typename _IntType1>
friend bool
- operator==(const std::binomial_distribution<_IntType1>& __d1,
- const std::binomial_distribution<_IntType1>& __d2)
+ operator==(const binomial_distribution& __d1,
+ const binomial_distribution& __d2)
#ifdef _GLIBCXX_USE_C99_MATH_TR1
- { return __d1.param() == __d2.param() && __d1._M_nd == __d2._M_nd; }
+ { return __d1._M_param == __d2._M_param && __d1._M_nd == __d2._M_nd; }
#else
- { return __d1.param() == __d2.param(); }
+ { return __d1._M_param == __d2._M_param; }
#endif
/**
template<typename _IntType1,
typename _CharT, typename _Traits>
friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
- const std::binomial_distribution<_IntType1>&);
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::binomial_distribution<_IntType1>& __x);
/**
* @brief Extracts a %binomial_distribution random number distribution
template<typename _IntType1,
typename _CharT, typename _Traits>
friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>&,
- std::binomial_distribution<_IntType1>&);
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::binomial_distribution<_IntType1>& __x);
private:
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
template<typename _UniformRandomNumberGenerator>
result_type
- _M_waiting(_UniformRandomNumberGenerator& __urng, _IntType __t);
+ _M_waiting(_UniformRandomNumberGenerator& __urng,
+ _IntType __t, double __q);
param_type _M_param;
* @brief A discrete geometric random number distribution.
*
* The formula for the geometric probability density function is
- * @f$p(i|p) = (1 - p)p^{i-1}@f$ where @f$p@f$ is the parameter of the
+ * @f$p(i|p) = p(1 - p)^{i}@f$ where @f$p@f$ is the parameter of the
* distribution.
*/
template<typename _IntType = int>
param_type(double __p = 0.5)
: _M_p(__p)
{
- _GLIBCXX_DEBUG_ASSERT((_M_p >= 0.0)
- && (_M_p <= 1.0));
+ _GLIBCXX_DEBUG_ASSERT((_M_p > 0.0) && (_M_p < 1.0));
_M_initialize();
}
private:
void
_M_initialize()
- { _M_log_p = std::log(_M_p); }
+ { _M_log_1_p = std::log(1.0 - _M_p); }
double _M_p;
- double _M_log_p;
+ double _M_log_1_p;
};
// constructors and member function
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, this->param()); }
+ { return this->operator()(__urng, _M_param); }
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng,
const param_type& __p);
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng)
+ { this->__generate(__f, __t, __urng, _M_param); }
+
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ template<typename _UniformRandomNumberGenerator>
+ void
+ __generate(result_type* __f, result_type* __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ /**
+ * @brief Return true if two geometric distributions have
+ * the same parameters.
+ */
+ friend bool
+ operator==(const geometric_distribution& __d1,
+ const geometric_distribution& __d2)
+ { return __d1._M_param == __d2._M_param; }
+
private:
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
param_type _M_param;
};
- /**
- * @brief Return true if two geometric distributions have
- * the same parameters.
- */
- template<typename _IntType>
- inline bool
- operator==(const std::geometric_distribution<_IntType>& __d1,
- const std::geometric_distribution<_IntType>& __d2)
- { return __d1.param() == __d2.param(); }
-
/**
* @brief Return true if two geometric distributions have
* different parameters.
template<typename _IntType,
typename _CharT, typename _Traits>
std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
- const std::geometric_distribution<_IntType>&);
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::geometric_distribution<_IntType>& __x);
/**
* @brief Extracts a %geometric_distribution random number distribution
template<typename _IntType,
typename _CharT, typename _Traits>
std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>&,
- std::geometric_distribution<_IntType>&);
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::geometric_distribution<_IntType>& __x);
/**
explicit
param_type(_IntType __k = 1, double __p = 0.5)
: _M_k(__k), _M_p(__p)
- { }
+ {
+ _GLIBCXX_DEBUG_ASSERT((_M_k > 0) && (_M_p > 0.0) && (_M_p <= 1.0));
+ }
_IntType
k() const
explicit
negative_binomial_distribution(_IntType __k = 1, double __p = 0.5)
- : _M_param(__k, __p), _M_gd(__k, __p / (1.0 - __p))
+ : _M_param(__k, __p), _M_gd(__k, (1.0 - __p) / __p)
{ }
explicit
negative_binomial_distribution(const param_type& __p)
- : _M_param(__p), _M_gd(__p.k(), __p.p() / (1.0 - __p.p()))
+ : _M_param(__p), _M_gd(__p.k(), (1.0 - __p.p()) / __p.p())
{ }
/**
operator()(_UniformRandomNumberGenerator& __urng,
const param_type& __p);
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng)
+ { this->__generate_impl(__f, __t, __urng); }
+
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ template<typename _UniformRandomNumberGenerator>
+ void
+ __generate(result_type* __f, result_type* __t,
+ _UniformRandomNumberGenerator& __urng)
+ { this->__generate_impl(__f, __t, __urng); }
+
+ template<typename _UniformRandomNumberGenerator>
+ void
+ __generate(result_type* __f, result_type* __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
/**
* @brief Return true if two negative binomial distributions have
* the same parameters and the sequences that would be
* generated are equal.
*/
- template<typename _IntType1>
- friend bool
- operator==(const std::negative_binomial_distribution<_IntType1>& __d1,
- const std::negative_binomial_distribution<_IntType1>& __d2)
- { return __d1.param() == __d2.param() && __d1._M_gd == __d2._M_gd; }
+ friend bool
+ operator==(const negative_binomial_distribution& __d1,
+ const negative_binomial_distribution& __d2)
+ { return __d1._M_param == __d2._M_param && __d1._M_gd == __d2._M_gd; }
/**
* @brief Inserts a %negative_binomial_distribution random
*/
template<typename _IntType1, typename _CharT, typename _Traits>
friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
- const std::negative_binomial_distribution<_IntType1>&);
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::negative_binomial_distribution<_IntType1>& __x);
/**
* @brief Extracts a %negative_binomial_distribution random number
*/
template<typename _IntType1, typename _CharT, typename _Traits>
friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>&,
- std::negative_binomial_distribution<_IntType1>&);
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::negative_binomial_distribution<_IntType1>& __x);
private:
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng);
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
param_type _M_param;
std::gamma_distribution<double> _M_gd;
/* @} */ // group random_distributions_bernoulli
/**
- * @addtogroup random_distributions_poisson Poisson
+ * @addtogroup random_distributions_poisson Poisson Distributions
* @ingroup random_distributions
* @{
*/
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, this->param()); }
+ { return this->operator()(__urng, _M_param); }
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng,
const param_type& __p);
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng)
+ { this->__generate(__f, __t, __urng, _M_param); }
+
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ template<typename _UniformRandomNumberGenerator>
+ void
+ __generate(result_type* __f, result_type* __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
/**
* @brief Return true if two Poisson distributions have the same
* parameters and the sequences that would be generated
* are equal.
*/
- template<typename _IntType1>
- friend bool
- operator==(const std::poisson_distribution<_IntType1>& __d1,
- const std::poisson_distribution<_IntType1>& __d2)
+ friend bool
+ operator==(const poisson_distribution& __d1,
+ const poisson_distribution& __d2)
#ifdef _GLIBCXX_USE_C99_MATH_TR1
- { return __d1.param() == __d2.param() && __d1._M_nd == __d2._M_nd; }
+ { return __d1._M_param == __d2._M_param && __d1._M_nd == __d2._M_nd; }
#else
- { return __d1.param() == __d2.param(); }
+ { return __d1._M_param == __d2._M_param; }
#endif
/**
*/
template<typename _IntType1, typename _CharT, typename _Traits>
friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
- const std::poisson_distribution<_IntType1>&);
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::poisson_distribution<_IntType1>& __x);
/**
* @brief Extracts a %poisson_distribution random number distribution
*/
template<typename _IntType1, typename _CharT, typename _Traits>
friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>&,
- std::poisson_distribution<_IntType1>&);
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::poisson_distribution<_IntType1>& __x);
private:
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
param_type _M_param;
// NB: Unused when _GLIBCXX_USE_C99_MATH_TR1 is undefined.
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, this->param()); }
+ { return this->operator()(__urng, _M_param); }
template<typename _UniformRandomNumberGenerator>
result_type
{
__detail::_Adaptor<_UniformRandomNumberGenerator, result_type>
__aurng(__urng);
- return -std::log(__aurng()) / __p.lambda();
+ return -std::log(result_type(1) - __aurng()) / __p.lambda();
}
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng)
+ { this->__generate(__f, __t, __urng, _M_param); }
+
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ template<typename _UniformRandomNumberGenerator>
+ void
+ __generate(result_type* __f, result_type* __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ /**
+ * @brief Return true if two exponential distributions have the same
+ * parameters.
+ */
+ friend bool
+ operator==(const exponential_distribution& __d1,
+ const exponential_distribution& __d2)
+ { return __d1._M_param == __d2._M_param; }
+
private:
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
param_type _M_param;
};
- /**
- * @brief Return true if two exponential distributions have the same
- * parameters.
- */
- template<typename _RealType>
- inline bool
- operator==(const std::exponential_distribution<_RealType>& __d1,
- const std::exponential_distribution<_RealType>& __d2)
- { return __d1.param() == __d2.param(); }
-
/**
* @brief Return true if two exponential distributions have different
* parameters.
*/
template<typename _RealType, typename _CharT, typename _Traits>
std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
- const std::exponential_distribution<_RealType>&);
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::exponential_distribution<_RealType>& __x);
/**
* @brief Extracts a %exponential_distribution random number distribution
*/
template<typename _RealType, typename _CharT, typename _Traits>
std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>&,
- std::exponential_distribution<_RealType>&);
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::exponential_distribution<_RealType>& __x);
/**
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, this->param()); }
+ { return this->operator()(__urng, _M_param); }
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng,
const param_type& __p);
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng)
+ { this->__generate(__f, __t, __urng, _M_param); }
+
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ template<typename _UniformRandomNumberGenerator>
+ void
+ __generate(result_type* __f, result_type* __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ /**
+ * @brief Return true if two Weibull distributions have the same
+ * parameters.
+ */
+ friend bool
+ operator==(const weibull_distribution& __d1,
+ const weibull_distribution& __d2)
+ { return __d1._M_param == __d2._M_param; }
+
private:
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
param_type _M_param;
};
- /**
- * @brief Return true if two Weibull distributions have the same
- * parameters.
- */
- template<typename _RealType>
- inline bool
- operator==(const std::weibull_distribution<_RealType>& __d1,
- const std::weibull_distribution<_RealType>& __d2)
- { return __d1.param() == __d2.param(); }
-
/**
* @brief Return true if two Weibull distributions have different
* parameters.
*/
template<typename _RealType, typename _CharT, typename _Traits>
std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
- const std::weibull_distribution<_RealType>&);
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::weibull_distribution<_RealType>& __x);
/**
* @brief Extracts a %weibull_distribution random number distribution
*/
template<typename _RealType, typename _CharT, typename _Traits>
std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>&,
- std::weibull_distribution<_RealType>&);
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::weibull_distribution<_RealType>& __x);
/**
*/
result_type
min() const
- { return std::numeric_limits<result_type>::min(); }
+ { return std::numeric_limits<result_type>::lowest(); }
/**
* @brief Returns the least upper bound value of the distribution.
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, this->param()); }
+ { return this->operator()(__urng, _M_param); }
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng,
const param_type& __p);
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng)
+ { this->__generate(__f, __t, __urng, _M_param); }
+
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ template<typename _UniformRandomNumberGenerator>
+ void
+ __generate(result_type* __f, result_type* __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ /**
+ * @brief Return true if two extreme value distributions have the same
+ * parameters.
+ */
+ friend bool
+ operator==(const extreme_value_distribution& __d1,
+ const extreme_value_distribution& __d2)
+ { return __d1._M_param == __d2._M_param; }
+
private:
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
param_type _M_param;
};
- /**
- * @brief Return true if two extreme value distributions have the same
- * parameters.
- */
- template<typename _RealType>
- inline bool
- operator==(const std::extreme_value_distribution<_RealType>& __d1,
- const std::extreme_value_distribution<_RealType>& __d2)
- { return __d1.param() == __d2.param(); }
-
/**
* @brief Return true if two extreme value distributions have different
* parameters.
*/
template<typename _RealType, typename _CharT, typename _Traits>
std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
- const std::extreme_value_distribution<_RealType>&);
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::extreme_value_distribution<_RealType>& __x);
/**
* @brief Extracts a %extreme_value_distribution random number
*/
template<typename _RealType, typename _CharT, typename _Traits>
std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>&,
- std::extreme_value_distribution<_RealType>&);
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::extreme_value_distribution<_RealType>& __x);
/**
friend class discrete_distribution<_IntType>;
param_type()
- : _M_prob(1, 1.0), _M_cp()
+ : _M_prob(), _M_cp()
{ }
template<typename _InputIterator>
std::vector<double>
probabilities() const
- { return _M_prob; }
+ { return _M_prob.empty() ? std::vector<double>(1, 1.0) : _M_prob; }
friend bool
operator==(const param_type& __p1, const param_type& __p2)
*/
std::vector<double>
probabilities() const
- { return _M_param.probabilities(); }
+ {
+ return _M_param._M_prob.empty()
+ ? std::vector<double>(1, 1.0) : _M_param._M_prob;
+ }
/**
* @brief Returns the parameter set of the distribution.
*/
result_type
max() const
- { return this->_M_param._M_prob.size() - 1; }
+ {
+ return _M_param._M_prob.empty()
+ ? result_type(0) : result_type(_M_param._M_prob.size() - 1);
+ }
/**
* @brief Generating functions.
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, this->param()); }
+ { return this->operator()(__urng, _M_param); }
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng,
const param_type& __p);
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng)
+ { this->__generate(__f, __t, __urng, _M_param); }
+
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ template<typename _UniformRandomNumberGenerator>
+ void
+ __generate(result_type* __f, result_type* __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ /**
+ * @brief Return true if two discrete distributions have the same
+ * parameters.
+ */
+ friend bool
+ operator==(const discrete_distribution& __d1,
+ const discrete_distribution& __d2)
+ { return __d1._M_param == __d2._M_param; }
+
/**
* @brief Inserts a %discrete_distribution random number distribution
* @p __x into the output stream @p __os.
*/
template<typename _IntType1, typename _CharT, typename _Traits>
friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
- const std::discrete_distribution<_IntType1>&);
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::discrete_distribution<_IntType1>& __x);
/**
* @brief Extracts a %discrete_distribution random number distribution
*/
template<typename _IntType1, typename _CharT, typename _Traits>
friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>&,
- std::discrete_distribution<_IntType1>&);
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::discrete_distribution<_IntType1>& __x);
private:
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
param_type _M_param;
};
- /**
- * @brief Return true if two discrete distributions have the same
- * parameters.
- */
- template<typename _IntType>
- inline bool
- operator==(const std::discrete_distribution<_IntType>& __d1,
- const std::discrete_distribution<_IntType>& __d2)
- { return __d1.param() == __d2.param(); }
-
/**
* @brief Return true if two discrete distributions have different
* parameters.
friend class piecewise_constant_distribution<_RealType>;
param_type()
- : _M_int(2), _M_den(1, 1.0), _M_cp()
- { _M_int[1] = _RealType(1); }
+ : _M_int(), _M_den(), _M_cp()
+ { }
template<typename _InputIteratorB, typename _InputIteratorW>
param_type(_InputIteratorB __bfirst,
std::vector<_RealType>
intervals() const
- { return _M_int; }
+ {
+ if (_M_int.empty())
+ {
+ std::vector<_RealType> __tmp(2);
+ __tmp[1] = _RealType(1);
+ return __tmp;
+ }
+ else
+ return _M_int;
+ }
std::vector<double>
densities() const
- { return _M_den; }
+ { return _M_den.empty() ? std::vector<double>(1, 1.0) : _M_den; }
friend bool
operator==(const param_type& __p1, const param_type& __p2)
*/
std::vector<_RealType>
intervals() const
- { return _M_param.intervals(); }
+ {
+ if (_M_param._M_int.empty())
+ {
+ std::vector<_RealType> __tmp(2);
+ __tmp[1] = _RealType(1);
+ return __tmp;
+ }
+ else
+ return _M_param._M_int;
+ }
/**
* @brief Returns a vector of the probability densities.
*/
std::vector<double>
densities() const
- { return _M_param.densities(); }
+ {
+ return _M_param._M_den.empty()
+ ? std::vector<double>(1, 1.0) : _M_param._M_den;
+ }
/**
* @brief Returns the parameter set of the distribution.
*/
result_type
min() const
- { return this->_M_param._M_int.front(); }
+ {
+ return _M_param._M_int.empty()
+ ? result_type(0) : _M_param._M_int.front();
+ }
/**
* @brief Returns the least upper bound value of the distribution.
*/
result_type
max() const
- { return this->_M_param._M_int.back(); }
+ {
+ return _M_param._M_int.empty()
+ ? result_type(1) : _M_param._M_int.back();
+ }
/**
* @brief Generating functions.
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, this->param()); }
+ { return this->operator()(__urng, _M_param); }
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng,
const param_type& __p);
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng)
+ { this->__generate(__f, __t, __urng, _M_param); }
+
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ template<typename _UniformRandomNumberGenerator>
+ void
+ __generate(result_type* __f, result_type* __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ /**
+ * @brief Return true if two piecewise constant distributions have the
+ * same parameters.
+ */
+ friend bool
+ operator==(const piecewise_constant_distribution& __d1,
+ const piecewise_constant_distribution& __d2)
+ { return __d1._M_param == __d2._M_param; }
+
/**
- * @brief Inserts a %piecewise_constan_distribution random
+ * @brief Inserts a %piecewise_constant_distribution random
* number distribution @p __x into the output stream @p __os.
*
* @param __os An output stream.
- * @param __x A %piecewise_constan_distribution random number
+ * @param __x A %piecewise_constant_distribution random number
* distribution.
*
* @returns The output stream with the state of @p __x inserted or in
*/
template<typename _RealType1, typename _CharT, typename _Traits>
friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
- const std::piecewise_constant_distribution<_RealType1>&);
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::piecewise_constant_distribution<_RealType1>& __x);
/**
- * @brief Extracts a %piecewise_constan_distribution random
+ * @brief Extracts a %piecewise_constant_distribution random
* number distribution @p __x from the input stream @p __is.
*
* @param __is An input stream.
- * @param __x A %piecewise_constan_distribution random number
+ * @param __x A %piecewise_constant_distribution random number
* generator engine.
*
* @returns The input stream with @p __x extracted or in an error
*/
template<typename _RealType1, typename _CharT, typename _Traits>
friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>&,
- std::piecewise_constant_distribution<_RealType1>&);
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::piecewise_constant_distribution<_RealType1>& __x);
private:
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
param_type _M_param;
};
- /**
- * @brief Return true if two piecewise constant distributions have the
- * same parameters.
- */
- template<typename _RealType>
- inline bool
- operator==(const std::piecewise_constant_distribution<_RealType>& __d1,
- const std::piecewise_constant_distribution<_RealType>& __d2)
- { return __d1.param() == __d2.param(); }
-
/**
* @brief Return true if two piecewise constant distributions have
* different parameters.
friend class piecewise_linear_distribution<_RealType>;
param_type()
- : _M_int(2), _M_den(2, 1.0), _M_cp(), _M_m()
- { _M_int[1] = _RealType(1); }
+ : _M_int(), _M_den(), _M_cp(), _M_m()
+ { }
template<typename _InputIteratorB, typename _InputIteratorW>
param_type(_InputIteratorB __bfirst,
std::vector<_RealType>
intervals() const
- { return _M_int; }
+ {
+ if (_M_int.empty())
+ {
+ std::vector<_RealType> __tmp(2);
+ __tmp[1] = _RealType(1);
+ return __tmp;
+ }
+ else
+ return _M_int;
+ }
std::vector<double>
densities() const
- { return _M_den; }
+ { return _M_den.empty() ? std::vector<double>(2, 1.0) : _M_den; }
friend bool
operator==(const param_type& __p1, const param_type& __p2)
*/
std::vector<_RealType>
intervals() const
- { return _M_param.intervals(); }
+ {
+ if (_M_param._M_int.empty())
+ {
+ std::vector<_RealType> __tmp(2);
+ __tmp[1] = _RealType(1);
+ return __tmp;
+ }
+ else
+ return _M_param._M_int;
+ }
/**
* @brief Return a vector of the probability densities of the
*/
std::vector<double>
densities() const
- { return _M_param.densities(); }
+ {
+ return _M_param._M_den.empty()
+ ? std::vector<double>(2, 1.0) : _M_param._M_den;
+ }
/**
* @brief Returns the parameter set of the distribution.
*/
result_type
min() const
- { return this->_M_param._M_int.front(); }
+ {
+ return _M_param._M_int.empty()
+ ? result_type(0) : _M_param._M_int.front();
+ }
/**
* @brief Returns the least upper bound value of the distribution.
*/
result_type
max() const
- { return this->_M_param._M_int.back(); }
+ {
+ return _M_param._M_int.empty()
+ ? result_type(1) : _M_param._M_int.back();
+ }
/**
* @brief Generating functions.
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, this->param()); }
+ { return this->operator()(__urng, _M_param); }
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng,
const param_type& __p);
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng)
+ { this->__generate(__f, __t, __urng, _M_param); }
+
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ template<typename _UniformRandomNumberGenerator>
+ void
+ __generate(result_type* __f, result_type* __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { this->__generate_impl(__f, __t, __urng, __p); }
+
+ /**
+ * @brief Return true if two piecewise linear distributions have the
+ * same parameters.
+ */
+ friend bool
+ operator==(const piecewise_linear_distribution& __d1,
+ const piecewise_linear_distribution& __d2)
+ { return __d1._M_param == __d2._M_param; }
+
/**
* @brief Inserts a %piecewise_linear_distribution random number
* distribution @p __x into the output stream @p __os.
*/
template<typename _RealType1, typename _CharT, typename _Traits>
friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
- const std::piecewise_linear_distribution<_RealType1>&);
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::piecewise_linear_distribution<_RealType1>& __x);
/**
* @brief Extracts a %piecewise_linear_distribution random number
*/
template<typename _RealType1, typename _CharT, typename _Traits>
friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>&,
- std::piecewise_linear_distribution<_RealType1>&);
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::piecewise_linear_distribution<_RealType1>& __x);
private:
+ template<typename _ForwardIterator,
+ typename _UniformRandomNumberGenerator>
+ void
+ __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
+ _UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
param_type _M_param;
};
- /**
- * @brief Return true if two piecewise linear distributions have the
- * same parameters.
- */
- template<typename _RealType>
- inline bool
- operator==(const std::piecewise_linear_distribution<_RealType>& __d1,
- const std::piecewise_linear_distribution<_RealType>& __d2)
- { return __d1.param() == __d2.param(); }
-
/**
* @brief Return true if two piecewise linear distributions have
* different parameters.
/* @} */ // group random_utilities
/* @} */ // group random
-}
+
+_GLIBCXX_END_NAMESPACE_VERSION
+} // namespace std
#endif
projects / thirdparty / gcc.git / blobdiff