// random number generation -*- C++ -*-
-// Copyright (C) 2009 Free Software Foundation, Inc.
+// Copyright (C) 2009, 2010 Free Software Foundation, Inc.
//
// This file is part of the GNU ISO C++ Library. This library is free
// software; you can redistribute it and/or modify it under the
namespace std
{
-
// [26.4] Random number generation
/**
- * @addtogroup std_random Random Number Generation
+ * @defgroup random Random Number Generation
+ * @ingroup numerics
+ *
* A facility for generating random numbers on selected distributions.
* @{
*/
_RealType
generate_canonical(_UniformRandomNumberGenerator& __g);
- class seed_seq;
-
/*
* Implementation-space details.
*/
struct _Shift<_UIntType, __w, true>
{ static const _UIntType __value = _UIntType(1) << __w; };
- template<typename _Tp, _Tp __a, _Tp __c, _Tp __m, bool>
+ template<typename _Tp, _Tp __m, _Tp __a, _Tp __c, bool>
struct _Mod;
// Dispatch based on modulus value to prevent divide-by-zero compile-time
// errors when m == 0.
- template<typename _Tp, _Tp __a, _Tp __c, _Tp __m>
+ template<typename _Tp, _Tp __m, _Tp __a = 1, _Tp __c = 0>
inline _Tp
__mod(_Tp __x)
- { return _Mod<_Tp, __a, __c, __m, __m == 0>::__calc(__x); }
-
- typedef __gnu_cxx::__conditional_type<(sizeof(unsigned) == 4),
- unsigned, unsigned long>::__type _UInt32Type;
+ { return _Mod<_Tp, __m, __a, __c, __m == 0>::__calc(__x); }
/*
* An adaptor class for converting the output of any Generator into
} // namespace __detail
/**
- * @addtogroup std_random_generators Random Number Generators
- * @ingroup std_random
+ * @addtogroup random_generators Random Number Generators
+ * @ingroup random
*
* These classes define objects which provide random or pseudorandom
* numbers, either from a discrete or a continuous interval. The
/**
* @brief A model of a linear congruential random number generator.
*
- * A random number generator that produces pseudorandom numbers using the
- * linear function @f$x_{i+1}\leftarrow(ax_{i} + c) \bmod m @f$.
+ * A random number generator that produces pseudorandom numbers via
+ * linear function:
+ * @f[
+ * x_{i+1}\leftarrow(ax_{i} + c) \bmod m
+ * @f]
*
* The template parameter @p _UIntType must be an unsigned integral type
* large enough to store values up to (__m-1). If the template parameter
* std::numeric_limits<_UIntType>::max() plus 1. Otherwise, the template
* parameters @p __a and @p __c must be less than @p __m.
*
- * The size of the state is @f$ 1 @f$.
+ * The size of the state is @f$1@f$.
*/
template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>
class linear_congruential_engine
{
- __glibcxx_class_requires(_UIntType, _UnsignedIntegerConcept)
- static_assert(__m == 0 || (__a < __m && __c < __m),
- "template arguments out of bounds"
- " in linear_congruential_engine");
+ static_assert(std::is_unsigned<_UIntType>::value, "template argument "
+ "substituting _UIntType not an unsigned integral type");
+ static_assert(__m == 0u || (__a < __m && __c < __m),
+ "template argument substituting __m out of bounds");
public:
/** The type of the generated random value. */
*/
explicit
linear_congruential_engine(result_type __s = default_seed)
- { this->seed(__s); }
+ { seed(__s); }
/**
* @brief Constructs a %linear_congruential_engine random number
*
* @param __q the seed sequence.
*/
- explicit
- linear_congruential_engine(seed_seq& __q)
- { this->seed(__q); }
+ template<typename _Sseq, typename = typename
+ std::enable_if<!std::is_same<_Sseq, linear_congruential_engine>::value>
+ ::type>
+ explicit
+ linear_congruential_engine(_Sseq& __q)
+ { seed(__q); }
/**
* @brief Reseeds the %linear_congruential_engine random number generator
*
* @param __q the seed sequence.
*/
- void
- seed(seed_seq& __q);
+ template<typename _Sseq>
+ typename std::enable_if<std::is_class<_Sseq>::value>::type
+ seed(_Sseq& __q);
/**
* @brief Gets the smallest possible value in the output range.
result_type
operator()()
{
- _M_x = __detail::__mod<_UIntType, __a, __c, __m>(_M_x);
+ _M_x = __detail::__mod<_UIntType, __m, __a, __c>(_M_x);
return _M_x;
}
* @param __rhs Another linear congruential random number generator
* object.
*
- * @returns true if the two objects are equal, false otherwise.
+ * @returns true if the infinite sequences of generated values
+ * would be equal, false otherwise.
*/
friend bool
operator==(const linear_congruential_engine& __lhs,
* @returns __os.
*/
template<typename _UIntType1, _UIntType1 __a1, _UIntType1 __c1,
- _UIntType1 __m1,
- typename _CharT, typename _Traits>
+ _UIntType1 __m1, typename _CharT, typename _Traits>
friend std::basic_ostream<_CharT, _Traits>&
operator<<(std::basic_ostream<_CharT, _Traits>&,
const std::linear_congruential_engine<_UIntType1,
* @returns __is.
*/
template<typename _UIntType1, _UIntType1 __a1, _UIntType1 __c1,
- _UIntType1 __m1,
- typename _CharT, typename _Traits>
+ _UIntType1 __m1, typename _CharT, typename _Traits>
friend std::basic_istream<_CharT, _Traits>&
operator>>(std::basic_istream<_CharT, _Traits>&,
std::linear_congruential_engine<_UIntType1, __a1,
_UIntType _M_x;
};
+ /**
+ * @brief Compares two linear congruential random number generator
+ * objects of the same type for inequality.
+ *
+ * @param __lhs A linear congruential random number generator object.
+ * @param __rhs Another linear congruential random number generator
+ * object.
+ *
+ * @returns true if the infinite sequences of generated values
+ * would be different, false otherwise.
+ */
+ template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>
+ inline bool
+ operator!=(const std::linear_congruential_engine<_UIntType, __a,
+ __c, __m>& __lhs,
+ const std::linear_congruential_engine<_UIntType, __a,
+ __c, __m>& __rhs)
+ { return !(__lhs == __rhs); }
+
/**
* A generalized feedback shift register discrete random number generator.
_UIntType __c, size_t __l, _UIntType __f>
class mersenne_twister_engine
{
- __glibcxx_class_requires(_UIntType, _UnsignedIntegerConcept)
-
- static_assert(__m >= 1U,
- "mersenne_twister_engine template arguments out of bounds");
- static_assert(__n >= __m,
- "mersenne_twister_engine template arguments out of bounds");
- static_assert(__w >= __r,
- "mersenne_twister_engine template arguments out of bounds");
- static_assert(__w >= __u,
- "mersenne_twister_engine template arguments out of bounds");
- static_assert(__w >= __s,
- "mersenne_twister_engine template arguments out of bounds");
- static_assert(__w >= __t,
- "mersenne_twister_engine template arguments out of bounds");
- static_assert(__w >= __l,
- "mersenne_twister_engine template arguments out of bounds");
- static_assert(__w <=
- static_cast<size_t>(std::numeric_limits<_UIntType>::digits),
- "mersenne_twister_engine template arguments out of bounds");
+ static_assert(std::is_unsigned<_UIntType>::value, "template argument "
+ "substituting _UIntType not an unsigned integral type");
+ static_assert(1u <= __m && __m <= __n,
+ "template argument substituting __m out of bounds");
+ static_assert(__r <= __w, "template argument substituting "
+ "__r out of bound");
+ static_assert(__u <= __w, "template argument substituting "
+ "__u out of bound");
+ static_assert(__s <= __w, "template argument substituting "
+ "__s out of bound");
+ static_assert(__t <= __w, "template argument substituting "
+ "__t out of bound");
+ static_assert(__l <= __w, "template argument substituting "
+ "__l out of bound");
+ static_assert(__w <= std::numeric_limits<_UIntType>::digits,
+ "template argument substituting __w out of bound");
static_assert(__a <= (__detail::_Shift<_UIntType, __w>::__value - 1),
- "mersenne_twister_engine template arguments out of bounds");
+ "template argument substituting __a out of bound");
static_assert(__b <= (__detail::_Shift<_UIntType, __w>::__value - 1),
- "mersenne_twister_engine template arguments out of bounds");
+ "template argument substituting __b out of bound");
static_assert(__c <= (__detail::_Shift<_UIntType, __w>::__value - 1),
- "mersenne_twister_engine template arguments out of bounds");
+ "template argument substituting __c out of bound");
+ static_assert(__d <= (__detail::_Shift<_UIntType, __w>::__value - 1),
+ "template argument substituting __d out of bound");
+ static_assert(__f <= (__detail::_Shift<_UIntType, __w>::__value - 1),
+ "template argument substituting __f out of bound");
public:
/** The type of the generated random value. */
static const size_t tempering_t = __t;
static const result_type tempering_c = __c;
static const size_t tempering_l = __l;
- static const size_t initialization_multiplier = __f;
+ static const result_type initialization_multiplier = __f;
static const result_type default_seed = 5489u;
// constructors and member function
*
* @param __q the seed sequence.
*/
- explicit
- mersenne_twister_engine(seed_seq& __q)
- { seed(__q); }
+ template<typename _Sseq, typename = typename
+ std::enable_if<!std::is_same<_Sseq, mersenne_twister_engine>::value>
+ ::type>
+ explicit
+ mersenne_twister_engine(_Sseq& __q)
+ { seed(__q); }
void
seed(result_type __sd = default_seed);
- void
- seed(seed_seq& __q);
+ template<typename _Sseq>
+ typename std::enable_if<std::is_class<_Sseq>::value>::type
+ seed(_Sseq& __q);
/**
* @brief Gets the smallest possible value in the output range.
* @param __rhs Another % mersenne_twister_engine random number
* generator object.
*
- * @returns true if the two objects are equal, false otherwise.
+ * @returns true if the infinite sequences of generated values
+ * would be equal, false otherwise.
*/
friend bool
operator==(const mersenne_twister_engine& __lhs,
};
/**
+ * @brief Compares two % mersenne_twister_engine random number generator
+ * objects of the same type for inequality.
+ *
+ * @param __lhs A % mersenne_twister_engine random number generator
+ * object.
+ * @param __rhs Another % mersenne_twister_engine random number
+ * generator object.
+ *
+ * @returns true if the infinite sequences of generated values
+ * would be different, false otherwise.
+ */
+ 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>
+ inline bool
+ operator!=(const std::mersenne_twister_engine<_UIntType, __w, __n, __m,
+ __r, __a, __u, __d, __s, __b, __t, __c, __l, __f>& __lhs,
+ const std::mersenne_twister_engine<_UIntType, __w, __n, __m,
+ __r, __a, __u, __d, __s, __b, __t, __c, __l, __f>& __rhs)
+ { return !(__lhs == __rhs); }
+
+
+ /**
* @brief The Marsaglia-Zaman generator.
*
* This is a model of a Generalized Fibonacci discrete random number
* generator, sometimes referred to as the SWC generator.
*
* A discrete random number generator that produces pseudorandom
- * numbers using @f$x_{i}\leftarrow(x_{i - s} - x_{i - r} -
- * carry_{i-1}) \bmod m @f$.
+ * numbers using:
+ * @f[
+ * x_{i}\leftarrow(x_{i - s} - x_{i - r} - carry_{i-1}) \bmod m
+ * @f]
*
- * The size of the state is @f$ r @f$
- * and the maximum period of the generator is @f$ m^r - m^s - 1 @f$.
+ * The size of the state is @f$r@f$
+ * and the maximum period of the generator is @f$(m^r - m^s - 1)@f$.
*
* @var _M_x The state of the generator. This is a ring buffer.
* @var _M_carry The carry.
template<typename _UIntType, size_t __w, size_t __s, size_t __r>
class subtract_with_carry_engine
{
- __glibcxx_class_requires(_UIntType, _UnsignedIntegerConcept)
- static_assert(__s > 0U && __r > __s
- && __w > 0U
- && __w <= static_cast<size_t>
- (std::numeric_limits<_UIntType>::digits),
- "template arguments out of bounds"
- " in subtract_with_carry_engine");
+ static_assert(std::is_unsigned<_UIntType>::value, "template argument "
+ "substituting _UIntType not an unsigned integral type");
+ static_assert(0u < __s && __s < __r,
+ "template argument substituting __s out of bounds");
+ static_assert(0u < __w && __w <= std::numeric_limits<_UIntType>::digits,
+ "template argument substituting __w out of bounds");
public:
/** The type of the generated random value. */
*/
explicit
subtract_with_carry_engine(result_type __sd = default_seed)
- { this->seed(__sd); }
+ { seed(__sd); }
/**
* @brief Constructs a %subtract_with_carry_engine random number engine
*
* @param __q the seed sequence.
*/
- explicit
- subtract_with_carry_engine(seed_seq& __q)
- { this->seed(__q); }
+ template<typename _Sseq, typename = typename
+ std::enable_if<!std::is_same<_Sseq, subtract_with_carry_engine>::value>
+ ::type>
+ explicit
+ subtract_with_carry_engine(_Sseq& __q)
+ { seed(__q); }
/**
- * @brief Seeds the initial state @f$ x_0 @f$ of the random number
+ * @brief Seeds the initial state @f$x_0@f$ of the random number
* generator.
*
* N1688[4.19] modifies this as follows. If @p __value == 0,
seed(result_type __sd = default_seed);
/**
- * @brief Seeds the initial state @f$ x_0 @f$ of the
+ * @brief Seeds the initial state @f$x_0@f$ of the
* % subtract_with_carry_engine random number generator.
*/
- void
- seed(seed_seq& __q);
+ template<typename _Sseq>
+ typename std::enable_if<std::is_class<_Sseq>::value>::type
+ seed(_Sseq& __q);
/**
* @brief Gets the inclusive minimum value of the range of random
* @param __rhs Another % subtract_with_carry_engine random number
* generator object.
*
- * @returns true if the two objects are equal, false otherwise.
- */
+ * @returns true if the infinite sequences of generated values
+ * would be equal, false otherwise.
+ */
friend bool
operator==(const subtract_with_carry_engine& __lhs,
const subtract_with_carry_engine& __rhs)
* @p __is.
*
* @param __is An input stream.
- * @param __x A % subtract_with_carry_engine random number generator engine.
+ * @param __x A % subtract_with_carry_engine random number generator
+ * engine.
*
* @returns The input stream with the state of @p __x extracted or in
* an error state.
};
/**
+ * @brief Compares two % subtract_with_carry_engine random number
+ * generator objects of the same type for inequality.
+ *
+ * @param __lhs A % subtract_with_carry_engine random number generator
+ * object.
+ * @param __rhs Another % subtract_with_carry_engine random number
+ * generator object.
+ *
+ * @returns true if the infinite sequences of generated values
+ * would be different, false otherwise.
+ */
+ template<typename _UIntType, size_t __w, size_t __s, size_t __r>
+ inline bool
+ operator!=(const std::subtract_with_carry_engine<_UIntType, __w,
+ __s, __r>& __lhs,
+ const std::subtract_with_carry_engine<_UIntType, __w,
+ __s, __r>& __rhs)
+ { return !(__lhs == __rhs); }
+
+
+ /**
* Produces random numbers from some base engine by discarding blocks of
* data.
*
template<typename _RandomNumberEngine, size_t __p, size_t __r>
class discard_block_engine
{
- static_assert(__r >= 1U && __p >= __r,
- "template arguments out of bounds"
- " in discard_block_engine");
+ static_assert(1 <= __r && __r <= __p,
+ "template argument substituting __r out of bounds");
public:
/** The type of the generated random value. */
*
* @param __q A seed sequence.
*/
- explicit
- discard_block_engine(seed_seq& __q)
- : _M_b(__q), _M_n(0)
- { }
+ template<typename _Sseq, typename = typename
+ std::enable_if<!std::is_same<_Sseq, discard_block_engine>::value
+ && !std::is_same<_Sseq, _RandomNumberEngine>::value>
+ ::type>
+ explicit
+ discard_block_engine(_Sseq& __q)
+ : _M_b(__q), _M_n(0)
+ { }
/**
* @brief Reseeds the %discard_block_engine object with the default
* sequence.
* @param __q A seed generator function.
*/
- void
- seed(seed_seq& __q)
- {
- _M_b.seed(__q);
- _M_n = 0;
- }
+ template<typename _Sseq>
+ void
+ seed(_Sseq& __q)
+ {
+ _M_b.seed(__q);
+ _M_n = 0;
+ }
/**
* @brief Gets a const reference to the underlying generator engine
* @param __rhs Another %discard_block_engine random number generator
* object.
*
- * @returns true if the two objects are equal, false otherwise.
+ * @returns true if the infinite sequences of generated values
+ * would be equal, false otherwise.
*/
friend bool
operator==(const discard_block_engine& __lhs,
const discard_block_engine& __rhs)
- { return (__lhs._M_b == __rhs._M_b) && (__lhs._M_n == __rhs._M_n); }
+ { return __lhs._M_b == __rhs._M_b && __lhs._M_n == __rhs._M_n; }
/**
* @brief Inserts the current state of a %discard_block_engine random
};
/**
+ * @brief Compares two %discard_block_engine random number generator
+ * objects of the same type for inequality.
+ *
+ * @param __lhs A %discard_block_engine random number generator object.
+ * @param __rhs Another %discard_block_engine random number generator
+ * object.
+ *
+ * @returns true if the infinite sequences of generated values
+ * would be different, false otherwise.
+ */
+ template<typename _RandomNumberEngine, size_t __p, size_t __r>
+ inline bool
+ operator!=(const std::discard_block_engine<_RandomNumberEngine, __p,
+ __r>& __lhs,
+ const std::discard_block_engine<_RandomNumberEngine, __p,
+ __r>& __rhs)
+ { return !(__lhs == __rhs); }
+
+
+ /**
* Produces random numbers by combining random numbers from some base
* engine to produce random numbers with a specifies number of bits @p __w.
*/
template<typename _RandomNumberEngine, size_t __w, typename _UIntType>
class independent_bits_engine
{
- static_assert(__w > 0U
- && __w <=
- static_cast<size_t>
- (std::numeric_limits<_UIntType>::digits),
- "template arguments out of bounds "
- "in independent_bits_engine");
+ static_assert(std::is_unsigned<_UIntType>::value, "template argument "
+ "substituting _UIntType not an unsigned integral type");
+ static_assert(0u < __w && __w <= std::numeric_limits<_UIntType>::digits,
+ "template argument substituting __w out of bounds");
public:
/** The type of the generated random value. */
*
* @param __q A seed sequence.
*/
- explicit
- independent_bits_engine(seed_seq& __q)
- : _M_b(__q)
- { }
+ template<typename _Sseq, typename = typename
+ std::enable_if<!std::is_same<_Sseq, independent_bits_engine>::value
+ && !std::is_same<_Sseq, _RandomNumberEngine>::value>
+ ::type>
+ explicit
+ independent_bits_engine(_Sseq& __q)
+ : _M_b(__q)
+ { }
/**
* @brief Reseeds the %independent_bits_engine object with the default
* seed sequence.
* @param __q A seed generator function.
*/
- void
- seed(seed_seq& __q)
- { _M_b.seed(__q); }
+ template<typename _Sseq>
+ void
+ seed(_Sseq& __q)
+ { _M_b.seed(__q); }
/**
* @brief Gets a const reference to the underlying generator engine
* @param __rhs Another %independent_bits_engine random number generator
* object.
*
- * @returns true if the two objects are equal, false otherwise.
+ * @returns true if the infinite sequences of generated values
+ * would be equal, false otherwise.
*/
friend bool
operator==(const independent_bits_engine& __lhs,
};
/**
+ * @brief Compares two %independent_bits_engine random number generator
+ * objects of the same type for inequality.
+ *
+ * @param __lhs A %independent_bits_engine random number generator
+ * object.
+ * @param __rhs Another %independent_bits_engine random number generator
+ * object.
+ *
+ * @returns true if the infinite sequences of generated values
+ * would be different, false otherwise.
+ */
+ template<typename _RandomNumberEngine, size_t __w, typename _UIntType>
+ inline bool
+ operator!=(const std::independent_bits_engine<_RandomNumberEngine, __w,
+ _UIntType>& __lhs,
+ const std::independent_bits_engine<_RandomNumberEngine, __w,
+ _UIntType>& __rhs)
+ { return !(__lhs == __rhs); }
+
+ /**
* @brief Inserts the current state of a %independent_bits_engine random
* number generator engine @p __x into the output stream @p __os.
*
return __os;
}
+
/**
* @brief Produces random numbers by combining random numbers from some
* base engine to produce random numbers with a specifies number of bits
template<typename _RandomNumberEngine, size_t __k>
class shuffle_order_engine
{
- static_assert(__k >= 1U,
- "template arguments out of bounds"
- " in shuffle_order_engine");
+ static_assert(1u <= __k, "template argument substituting "
+ "__k out of bound");
public:
/** The type of the generated random value. */
*
* @param __q A seed sequence.
*/
- explicit
- shuffle_order_engine(seed_seq& __q)
- : _M_b(__q)
- { _M_initialize(); }
+ template<typename _Sseq, typename = typename
+ std::enable_if<!std::is_same<_Sseq, shuffle_order_engine>::value
+ && !std::is_same<_Sseq, _RandomNumberEngine>::value>
+ ::type>
+ explicit
+ shuffle_order_engine(_Sseq& __q)
+ : _M_b(__q)
+ { _M_initialize(); }
/**
* @brief Reseeds the %shuffle_order_engine object with the default seed
* sequence.
* @param __q A seed generator function.
*/
- void
- seed(seed_seq& __q)
- {
- _M_b.seed(__q);
- _M_initialize();
- }
+ template<typename _Sseq>
+ void
+ seed(_Sseq& __q)
+ {
+ _M_b.seed(__q);
+ _M_initialize();
+ }
/**
* Gets a const reference to the underlying generator engine object.
* @param __rhs Another %shuffle_order_engine random number generator
* object.
*
- * @returns true if the two objects are equal, false otherwise.
- */
+ * @returns true if the infinite sequences of generated values
+ * would be equal, false otherwise.
+ */
friend bool
operator==(const shuffle_order_engine& __lhs,
const shuffle_order_engine& __rhs)
};
/**
+ * Compares two %shuffle_order_engine random number generator objects
+ * of the same type for inequality.
+ *
+ * @param __lhs A %shuffle_order_engine random number generator object.
+ * @param __rhs Another %shuffle_order_engine random number generator
+ * object.
+ *
+ * @returns true if the infinite sequences of generated values
+ * would be different, false otherwise.
+ */
+ template<typename _RandomNumberEngine, size_t __k>
+ inline bool
+ operator!=(const std::shuffle_order_engine<_RandomNumberEngine,
+ __k>& __lhs,
+ const std::shuffle_order_engine<_RandomNumberEngine,
+ __k>& __rhs)
+ { return !(__lhs == __rhs); }
+
+
+ /**
* The classic Minimum Standard rand0 of Lewis, Goodman, and Miller.
*/
typedef linear_congruential_engine<uint_fast32_t, 16807UL, 0UL, 2147483647UL>
minstd_rand0;
/**
- * An alternative LCR (Lehmer Generator function) .
+ * An alternative LCR (Lehmer Generator function).
*/
typedef linear_congruential_engine<uint_fast32_t, 48271UL, 0UL, 2147483647UL>
minstd_rand;
* The classic Mersenne Twister.
*
* Reference:
- * M. Matsumoto and T. Nishimura, "Mersenne Twister: A 623-Dimensionally
- * Equidistributed Uniform Pseudo-Random Number Generator", ACM Transactions
+ * M. Matsumoto and T. Nishimura, Mersenne Twister: A 623-Dimensionally
+ * Equidistributed Uniform Pseudo-Random Number Generator, ACM Transactions
* on Modeling and Computer Simulation, Vol. 8, No. 1, January 1998, pp 3-30.
*/
typedef mersenne_twister_engine<
0xfff7eee000000000ULL, 43,
6364136223846793005ULL> mt19937_64;
- /**
- * .
- */
typedef subtract_with_carry_engine<uint_fast32_t, 24, 10, 24>
ranlux24_base;
- typedef discard_block_engine<ranlux24_base, 223, 23> ranlux24;
-
typedef subtract_with_carry_engine<uint_fast64_t, 48, 5, 12>
ranlux48_base;
+ typedef discard_block_engine<ranlux24_base, 223, 23> ranlux24;
+
typedef discard_block_engine<ranlux48_base, 389, 11> ranlux48;
- /**
- * .
- */
typedef shuffle_order_engine<minstd_rand0, 256> knuth_b;
- /**
- * .
- */
typedef minstd_rand0 default_random_engine;
/**
#endif
};
- /* @} */ // group std_random_generators
+ /* @} */ // group random_generators
/**
- * @addtogroup std_random_distributions Random Number Distributions
- * @ingroup std_random
+ * @addtogroup random_distributions Random Number Distributions
+ * @ingroup random
* @{
*/
/**
- * @addtogroup std_random_distributions_uniform Uniform Distributions
- * @ingroup std_random_distributions
+ * @addtogroup random_distributions_uniform Uniform
+ * @ingroup random_distributions
* @{
*/
template<typename _IntType = int>
class uniform_int_distribution
{
- __glibcxx_class_requires(_IntType, _IntegerConcept)
+ static_assert(std::is_integral<_IntType>::value,
+ "template argument not an integral type");
public:
/** The type of the range of the distribution. */
b() const
{ return _M_b; }
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; }
+
private:
_IntType _M_a;
_IntType _M_b;
{ return _M_param.b(); }
/**
- * @brief Returns the inclusive lower bound of the distribution range.
- */
- result_type
- min() const
- { return this->a(); }
-
- /**
- * @brief Returns the inclusive upper bound of the distribution range.
- */
- result_type
- max() const
- { return this->b(); }
-
- /**
* @brief Returns the parameter set of the distribution.
*/
param_type
{ _M_param = __param; }
/**
- * Gets a uniformly distributed random number in the range
- * @f$(min, max)@f$.
+ * @brief Returns the inclusive lower bound of the distribution range.
+ */
+ result_type
+ min() const
+ { return this->a(); }
+
+ /**
+ * @brief Returns the inclusive upper bound of the distribution range.
+ */
+ result_type
+ max() const
+ { return this->b(); }
+
+ /**
+ * @brief Generating functions.
*/
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
{ return this->operator()(__urng, this->param()); }
- /**
- * Gets a uniform random number in the range @f$[0, n)@f$.
- *
- * This function is aimed at use with std::random_shuffle.
- */
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng,
};
/**
+ * @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.
+ */
+ template<typename _IntType>
+ inline bool
+ operator!=(const std::uniform_int_distribution<_IntType>& __d1,
+ const std::uniform_int_distribution<_IntType>& __d2)
+ { return !(__d1 == __d2); }
+
+ /**
* @brief Inserts a %uniform_int_distribution random number
* distribution @p __x into the output stream @p os.
*
template<typename _RealType = double>
class uniform_real_distribution
{
+ static_assert(std::is_floating_point<_RealType>::value,
+ "template argument not a floating point type");
+
public:
/** The type of the range of the distribution. */
typedef _RealType result_type;
b() const
{ return _M_b; }
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; }
+
private:
_RealType _M_a;
_RealType _M_b;
{ return _M_param.b(); }
/**
+ * @brief Returns the parameter set of the distribution.
+ */
+ param_type
+ param() const
+ { return _M_param; }
+
+ /**
+ * @brief Sets the parameter set of the distribution.
+ * @param __param The new parameter set of the distribution.
+ */
+ void
+ param(const param_type& __param)
+ { _M_param = __param; }
+
+ /**
* @brief Returns the inclusive lower bound of the distribution range.
*/
result_type
{ return this->b(); }
/**
- * @brief Returns the parameter set of the distribution.
- */
- param_type
- param() const
- { return _M_param; }
-
- /**
- * @brief Sets the parameter set of the distribution.
- * @param __param The new parameter set of the distribution.
+ * @brief Generating functions.
*/
- void
- param(const param_type& __param)
- { _M_param = __param; }
-
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
};
/**
+ * @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.
+ */
+ template<typename _IntType>
+ inline bool
+ operator!=(const std::uniform_real_distribution<_IntType>& __d1,
+ const std::uniform_real_distribution<_IntType>& __d2)
+ { return !(__d1 == __d2); }
+
+ /**
* @brief Inserts a %uniform_real_distribution random number
* distribution @p __x into the output stream @p __os.
*
operator>>(std::basic_istream<_CharT, _Traits>&,
std::uniform_real_distribution<_RealType>&);
- /* @} */ // group std_random_distributions_uniform
+ /* @} */ // group random_distributions_uniform
/**
- * @addtogroup std_random_distributions_normal Normal Distributions
- * @ingroup std_random_distributions
+ * @addtogroup random_distributions_normal Normal
+ * @ingroup random_distributions
* @{
*/
* @brief A normal continuous distribution for random numbers.
*
* The formula for the normal probability density function is
- * @f$ p(x|\mu,\sigma) = \frac{1}{\sigma \sqrt{2 \pi}}
- * e^{- \frac{{x - \mu}^ {2}}{2 \sigma ^ {2}} } @f$.
+ * @f[
+ * p(x|\mu,\sigma) = \frac{1}{\sigma \sqrt{2 \pi}}
+ * e^{- \frac{{x - \mu}^ {2}}{2 \sigma ^ {2}} }
+ * @f]
*/
template<typename _RealType = double>
class normal_distribution
{
+ static_assert(std::is_floating_point<_RealType>::value,
+ "template argument not a floating point type");
+
public:
/** The type of the range of the distribution. */
typedef _RealType result_type;
stddev() const
{ return _M_stddev; }
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return (__p1._M_mean == __p2._M_mean
+ && __p1._M_stddev == __p2._M_stddev); }
+
private:
_RealType _M_mean;
_RealType _M_stddev;
public:
/**
- * Constructs a normal distribution with parameters @f$ mean @f$ and
+ * Constructs a normal distribution with parameters @f$mean@f$ and
* standard deviation.
*/
explicit
max() const
{ return std::numeric_limits<result_type>::max(); }
+ /**
+ * @brief Generating functions.
+ */
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
const param_type& __p);
/**
+ * @brief Return true if two normal distributions have
+ * the same parameters and the sequences that would
+ * be generated are equal.
+ */
+ template<typename _RealType1>
+ friend bool
+ operator==(const std::normal_distribution<_RealType1>& __d1,
+ const std::normal_distribution<_RealType1>& __d2);
+
+ /**
* @brief Inserts a %normal_distribution random number distribution
* @p __x into the output stream @p __os.
*
bool _M_saved_available;
};
+ /**
+ * @brief Return true if two normal distributions are different.
+ */
+ template<typename _RealType>
+ inline bool
+ operator!=(const std::normal_distribution<_RealType>& __d1,
+ const std::normal_distribution<_RealType>& __d2)
+ { return !(__d1 == __d2); }
+
/**
* @brief A lognormal_distribution random number distribution.
*
* The formula for the normal probability mass function is
- * @f$ p(x|m,s) = \frac{1}{sx\sqrt{2\pi}}
- * \exp{-\frac{(\ln{x} - m)^2}{2s^2}} @f$
+ * @f[
+ * p(x|m,s) = \frac{1}{sx\sqrt{2\pi}}
+ * \exp{-\frac{(\ln{x} - m)^2}{2s^2}}
+ * @f]
*/
template<typename _RealType = double>
class lognormal_distribution
{
+ static_assert(std::is_floating_point<_RealType>::value,
+ "template argument not a floating point type");
+
public:
/** The type of the range of the distribution. */
typedef _RealType result_type;
s() const
{ return _M_s; }
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_m == __p2._M_m && __p1._M_s == __p2._M_s; }
+
private:
_RealType _M_m;
_RealType _M_s;
max() const
{ return std::numeric_limits<result_type>::max(); }
+ /**
+ * @brief Generating functions.
+ */
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
const param_type& __p)
{ return std::exp(__p.s() * _M_nd(__urng) + __p.m()); }
+ /**
+ * @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); }
+
+ /**
+ * @brief Inserts a %lognormal_distribution random number distribution
+ * @p __x into the output stream @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A %lognormal_distribution random number distribution.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ template<typename _RealType1, typename _CharT, typename _Traits>
+ friend std::basic_ostream<_CharT, _Traits>&
+ operator<<(std::basic_ostream<_CharT, _Traits>&,
+ const std::lognormal_distribution<_RealType1>&);
+
+ /**
+ * @brief Extracts a %lognormal_distribution random number distribution
+ * @p __x from the input stream @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A %lognormal_distribution random number
+ * generator engine.
+ *
+ * @returns The input stream with @p __x extracted or in an error state.
+ */
+ template<typename _RealType1, typename _CharT, typename _Traits>
+ friend std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>&,
+ std::lognormal_distribution<_RealType1>&);
+
private:
param_type _M_param;
};
/**
- * @brief Inserts a %lognormal_distribution random number distribution
- * @p __x into the output stream @p __os.
- *
- * @param __os An output stream.
- * @param __x A %lognormal_distribution random number distribution.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
+ * @brief Return true if two lognormal distributions are different.
*/
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
- const std::lognormal_distribution<_RealType>&);
+ template<typename _RealType>
+ inline bool
+ operator!=(const std::lognormal_distribution<_RealType>& __d1,
+ const std::lognormal_distribution<_RealType>& __d2)
+ { return !(__d1 == __d2); }
- /**
- * @brief Extracts a %lognormal_distribution random number distribution
- * @p __x from the input stream @p __is.
- *
- * @param __is An input stream.
- * @param __x A %lognormal_distribution random number
- * generator engine.
- *
- * @returns The input stream with @p __x extracted or in an error state.
- */
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>&,
- std::lognormal_distribution<_RealType>&);
-
/**
* @brief A gamma continuous distribution for random numbers.
*
- * The formula for the gamma probability density function is
- * @f$ p(x|\alpha,\beta) = \frac{1}{\beta\Gamma(\alpha)}
- * (x/\beta)^{\alpha - 1} e^{-x/\beta} @f$.
+ * The formula for the gamma probability density function is:
+ * @f[
+ * p(x|\alpha,\beta) = \frac{1}{\beta\Gamma(\alpha)}
+ * (x/\beta)^{\alpha - 1} e^{-x/\beta}
+ * @f]
*/
template<typename _RealType = double>
class gamma_distribution
{
+ static_assert(std::is_floating_point<_RealType>::value,
+ "template argument not a floating point type");
+
public:
/** The type of the range of the distribution. */
typedef _RealType result_type;
beta() const
{ return _M_beta; }
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return (__p1._M_alpha == __p2._M_alpha
+ && __p1._M_beta == __p2._M_beta); }
+
private:
void
_M_initialize();
public:
/**
* @brief Constructs a gamma distribution with parameters
- * @f$ \alpha @f$ and @f$ \beta @f$.
+ * @f$\alpha@f$ and @f$\beta@f$.
*/
explicit
gamma_distribution(_RealType __alpha_val = _RealType(1),
{ _M_nd.reset(); }
/**
- * @brief Returns the @f$ \alpha @f$ of the distribution.
+ * @brief Returns the @f$\alpha@f$ of the distribution.
*/
_RealType
alpha() const
{ return _M_param.alpha(); }
/**
- * @brief Returns the @f$ \beta @f$ of the distribution.
+ * @brief Returns the @f$\beta@f$ of the distribution.
*/
_RealType
beta() const
max() const
{ return std::numeric_limits<result_type>::max(); }
+ /**
+ * @brief Generating functions.
+ */
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
operator()(_UniformRandomNumberGenerator& __urng,
const param_type& __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); }
+
+ /**
+ * @brief Inserts a %gamma_distribution random number distribution
+ * @p __x into the output stream @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A %gamma_distribution random number distribution.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ template<typename _RealType1, typename _CharT, typename _Traits>
+ friend std::basic_ostream<_CharT, _Traits>&
+ operator<<(std::basic_ostream<_CharT, _Traits>&,
+ const std::gamma_distribution<_RealType1>&);
+
+ /**
+ * @brief Extracts a %gamma_distribution random number distribution
+ * @p __x from the input stream @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A %gamma_distribution random number generator engine.
+ *
+ * @returns The input stream with @p __x extracted or in an error state.
+ */
+ template<typename _RealType1, typename _CharT, typename _Traits>
+ friend std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>&,
+ std::gamma_distribution<_RealType1>&);
+
private:
param_type _M_param;
};
/**
- * @brief Inserts a %gamma_distribution random number distribution
- * @p __x into the output stream @p __os.
- *
- * @param __os An output stream.
- * @param __x A %gamma_distribution random number distribution.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
- */
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
- const std::gamma_distribution<_RealType>&);
-
- /**
- * @brief Extracts a %gamma_distribution random number distribution
- * @p __x from the input stream @p __is.
- *
- * @param __is An input stream.
- * @param __x A %gamma_distribution random number generator engine.
- *
- * @returns The input stream with @p __x extracted or in an error state.
+ * @brief Return true if two gamma distributions are different.
*/
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>&,
- std::gamma_distribution<_RealType>&);
+ template<typename _RealType>
+ inline bool
+ operator!=(const std::gamma_distribution<_RealType>& __d1,
+ const std::gamma_distribution<_RealType>& __d2)
+ { return !(__d1 == __d2); }
/**
* @brief A chi_squared_distribution random number distribution.
*
* The formula for the normal probability mass function is
- * @f$ p(x|n) = \frac{x^{(n/2) - 1}e^{-x/2}}{\Gamma(n/2) 2^{n/2}} @f$
+ * @f$p(x|n) = \frac{x^{(n/2) - 1}e^{-x/2}}{\Gamma(n/2) 2^{n/2}}@f$
*/
template<typename _RealType = double>
class chi_squared_distribution
{
+ static_assert(std::is_floating_point<_RealType>::value,
+ "template argument not a floating point type");
+
public:
/** The type of the range of the distribution. */
typedef _RealType result_type;
n() const
{ return _M_n; }
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_n == __p2._M_n; }
+
private:
_RealType _M_n;
};
max() const
{ return std::numeric_limits<result_type>::max(); }
+ /**
+ * @brief Generating functions.
+ */
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
return 2 * _M_gd(__urng, param_type(__p.n() / 2));
}
+ /**
+ * @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; }
+
+ /**
+ * @brief Inserts a %chi_squared_distribution random number distribution
+ * @p __x into the output stream @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A %chi_squared_distribution random number distribution.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ 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>&);
+
+ /**
+ * @brief Extracts a %chi_squared_distribution random number distribution
+ * @p __x from the input stream @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A %chi_squared_distribution random number
+ * generator engine.
+ *
+ * @returns The input stream with @p __x extracted or in an error state.
+ */
+ template<typename _RealType1, typename _CharT, typename _Traits>
+ friend std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>&,
+ std::chi_squared_distribution<_RealType1>&);
+
private:
param_type _M_param;
};
/**
- * @brief Inserts a %chi_squared_distribution random number distribution
- * @p __x into the output stream @p __os.
- *
- * @param __os An output stream.
- * @param __x A %chi_squared_distribution random number distribution.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
- */
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
- const std::chi_squared_distribution<_RealType>&);
-
- /**
- * @brief Extracts a %chi_squared_distribution random number distribution
- * @p __x from the input stream @p __is.
- *
- * @param __is An input stream.
- * @param __x A %chi_squared_distribution random number
- * generator engine.
- *
- * @returns The input stream with @p __x extracted or in an error state.
+ * @brief Return true if two Chi-squared distributions are different.
*/
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>&,
- std::chi_squared_distribution<_RealType>&);
+ template<typename _RealType>
+ inline bool
+ operator!=(const std::chi_squared_distribution<_RealType>& __d1,
+ const std::chi_squared_distribution<_RealType>& __d2)
+ { return !(__d1 == __d2); }
/**
* @brief A cauchy_distribution random number distribution.
*
* The formula for the normal probability mass function is
- * @f$ p(x|a,b) = (\pi b (1 + (\frac{x-a}{b})^2))^{-1} @f$
+ * @f$p(x|a,b) = (\pi b (1 + (\frac{x-a}{b})^2))^{-1}@f$
*/
template<typename _RealType = double>
class cauchy_distribution
{
+ static_assert(std::is_floating_point<_RealType>::value,
+ "template argument not a floating point type");
+
public:
/** The type of the range of the distribution. */
typedef _RealType result_type;
b() const
{ return _M_b; }
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; }
+
private:
_RealType _M_a;
_RealType _M_b;
max() const
{ return std::numeric_limits<result_type>::max(); }
+ /**
+ * @brief Generating functions.
+ */
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
};
/**
+ * @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>
+ inline bool
+ operator!=(const std::cauchy_distribution<_RealType>& __d1,
+ const std::cauchy_distribution<_RealType>& __d2)
+ { return !(__d1 == __d2); }
+
+ /**
* @brief Inserts a %cauchy_distribution random number distribution
* @p __x into the output stream @p __os.
*
* @brief A fisher_f_distribution random number distribution.
*
* The formula for the normal probability mass function is
- * @f$ p(x|m,n) = \frac{\Gamma((m+n)/2)}{\Gamma(m/2)\Gamma(n/2)}
+ * @f[
+ * p(x|m,n) = \frac{\Gamma((m+n)/2)}{\Gamma(m/2)\Gamma(n/2)}
* (\frac{m}{n})^{m/2} x^{(m/2)-1}
- * (1 + \frac{mx}{n})^{-(m+n)/2} @f$
+ * (1 + \frac{mx}{n})^{-(m+n)/2}
+ * @f]
*/
template<typename _RealType = double>
class fisher_f_distribution
{
+ static_assert(std::is_floating_point<_RealType>::value,
+ "template argument not a floating point type");
+
public:
/** The type of the range of the distribution. */
typedef _RealType result_type;
n() const
{ return _M_n; }
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_m == __p2._M_m && __p1._M_n == __p2._M_n; }
+
private:
_RealType _M_m;
_RealType _M_n;
max() const
{ return std::numeric_limits<result_type>::max(); }
+ /**
+ * @brief Generating functions.
+ */
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
/ (_M_gd_y(__urng, param_type(__p.n() / 2)) * m()));
}
+ /**
+ * @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); }
+
+ /**
+ * @brief Inserts a %fisher_f_distribution random number distribution
+ * @p __x into the output stream @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A %fisher_f_distribution random number distribution.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ 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>&);
+
+ /**
+ * @brief Extracts a %fisher_f_distribution random number distribution
+ * @p __x from the input stream @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A %fisher_f_distribution random number
+ * generator engine.
+ *
+ * @returns The input stream with @p __x extracted or in an error state.
+ */
+ template<typename _RealType1, typename _CharT, typename _Traits>
+ friend std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>&,
+ std::fisher_f_distribution<_RealType1>&);
+
private:
param_type _M_param;
};
/**
- * @brief Inserts a %fisher_f_distribution random number distribution
- * @p __x into the output stream @p __os.
- *
- * @param __os An output stream.
- * @param __x A %fisher_f_distribution random number distribution.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
- */
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
- const std::fisher_f_distribution<_RealType>&);
-
- /**
- * @brief Extracts a %fisher_f_distribution random number distribution
- * @p __x from the input stream @p __is.
- *
- * @param __is An input stream.
- * @param __x A %fisher_f_distribution random number
- * generator engine.
- *
- * @returns The input stream with @p __x extracted or in an error state.
+ * @brief Return true if two Fisher f distributions are diferent.
*/
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>&,
- std::fisher_f_distribution<_RealType>&);
-
+ template<typename _RealType>
+ inline bool
+ operator!=(const std::fisher_f_distribution<_RealType>& __d1,
+ const std::fisher_f_distribution<_RealType>& __d2)
+ { return !(__d1 == __d2); }
/**
* @brief A student_t_distribution random number distribution.
*
- * The formula for the normal probability mass function is
- * @f$ p(x|n) = \frac{1}{\sqrt(n\pi)} \frac{\Gamma((n+1)/2)}{\Gamma(n/2)}
- * (1 + \frac{x^2}{n}) ^{-(n+1)/2} @f$
+ * The formula for the normal probability mass function is:
+ * @f[
+ * p(x|n) = \frac{1}{\sqrt(n\pi)} \frac{\Gamma((n+1)/2)}{\Gamma(n/2)}
+ * (1 + \frac{x^2}{n}) ^{-(n+1)/2}
+ * @f]
*/
template<typename _RealType = double>
class student_t_distribution
{
+ static_assert(std::is_floating_point<_RealType>::value,
+ "template argument not a floating point type");
+
public:
/** The type of the range of the distribution. */
typedef _RealType result_type;
n() const
{ return _M_n; }
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_n == __p2._M_n; }
+
private:
_RealType _M_n;
};
max() const
{ return std::numeric_limits<result_type>::max(); }
+ /**
+ * @brief Generating functions.
+ */
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
return _M_nd(__urng) * std::sqrt(__p.n() / __g);
}
+ /**
+ * @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); }
+
+ /**
+ * @brief Inserts a %student_t_distribution random number distribution
+ * @p __x into the output stream @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A %student_t_distribution random number distribution.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ 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>&);
+
+ /**
+ * @brief Extracts a %student_t_distribution random number distribution
+ * @p __x from the input stream @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A %student_t_distribution random number
+ * generator engine.
+ *
+ * @returns The input stream with @p __x extracted or in an error state.
+ */
+ template<typename _RealType1, typename _CharT, typename _Traits>
+ friend std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>&,
+ std::student_t_distribution<_RealType1>&);
+
private:
param_type _M_param;
};
/**
- * @brief Inserts a %student_t_distribution random number distribution
- * @p __x into the output stream @p __os.
- *
- * @param __os An output stream.
- * @param __x A %student_t_distribution random number distribution.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
+ * @brief Return true if two Student t distributions are different.
*/
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
- const std::student_t_distribution<_RealType>&);
+ template<typename _RealType>
+ inline bool
+ operator!=(const std::student_t_distribution<_RealType>& __d1,
+ const std::student_t_distribution<_RealType>& __d2)
+ { return !(__d1 == __d2); }
- /**
- * @brief Extracts a %student_t_distribution random number distribution
- * @p __x from the input stream @p __is.
- *
- * @param __is An input stream.
- * @param __x A %student_t_distribution random number
- * generator engine.
- *
- * @returns The input stream with @p __x extracted or in an error state.
- */
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>&,
- std::student_t_distribution<_RealType>&);
- /* @} */ // group std_random_distributions_normal
+ /* @} */ // group random_distributions_normal
/**
- * @addtogroup std_random_distributions_bernoulli Bernoulli Distributions
- * @ingroup std_random_distributions
+ * @addtogroup random_distributions_bernoulli Bernoulli
+ * @ingroup random_distributions
* @{
*/
/**
* @brief A Bernoulli random number distribution.
*
- * Generates a sequence of true and false values with likelihood @f$ p @f$
- * that true will come up and @f$ (1 - p) @f$ that false will appear.
+ * Generates a sequence of true and false values with likelihood @f$p@f$
+ * that true will come up and @f$(1 - p)@f$ that false will appear.
*/
class bernoulli_distribution
{
p() const
{ return _M_p; }
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_p == __p2._M_p; }
+
private:
double _M_p;
};
* @brief Constructs a Bernoulli distribution with likelihood @p p.
*
* @param __p [IN] The likelihood of a true result being returned.
- * Must be in the interval @f$ [0, 1] @f$.
+ * Must be in the interval @f$[0, 1]@f$.
*/
explicit
bernoulli_distribution(double __p = 0.5)
{ return std::numeric_limits<result_type>::max(); }
/**
- * @brief Returns the next value in the Bernoullian sequence.
+ * @brief Generating functions.
*/
template<typename _UniformRandomNumberGenerator>
result_type
};
/**
+ * @brief Return true if two Bernoulli distributions have
+ * the same parameters.
+ */
+ inline bool
+ operator==(const std::bernoulli_distribution& __d1,
+ const std::bernoulli_distribution& __d2)
+ { return __d1.param() == __d2.param(); }
+
+ /**
+ * @brief Return true if two Bernoulli distributions have
+ * different parameters.
+ */
+ inline bool
+ operator!=(const std::bernoulli_distribution& __d1,
+ const std::bernoulli_distribution& __d2)
+ { return !(__d1 == __d2); }
+
+ /**
* @brief Inserts a %bernoulli_distribution random number distribution
* @p __x into the output stream @p __os.
*
* @brief A discrete binomial random number distribution.
*
* The formula for the binomial probability density function is
- * @f$ p(i|t,p) = \binom{n}{i} p^i (1 - p)^{t - i} @f$ where @f$ t @f$
- * and @f$ p @f$ are the parameters of the distribution.
+ * @f$p(i|t,p) = \binom{n}{i} p^i (1 - p)^{t - i}@f$ where @f$t@f$
+ * and @f$p@f$ are the parameters of the distribution.
*/
template<typename _IntType = int>
class binomial_distribution
{
- __glibcxx_class_requires(_IntType, _IntegerConcept)
+ static_assert(std::is_integral<_IntType>::value,
+ "template argument not an integral type");
public:
/** The type of the range of the distribution. */
p() const
{ return _M_p; }
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_t == __p2._M_t && __p1._M_p == __p2._M_p; }
+
private:
void
_M_initialize();
max() const
{ return _M_param.t(); }
+ /**
+ * @brief Generating functions.
+ */
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
const param_type& __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)
+#ifdef _GLIBCXX_USE_C99_MATH_TR1
+ { return __d1.param() == __d2.param() && __d1._M_nd == __d2._M_nd; }
+#else
+ { return __d1.param() == __d2.param(); }
+#endif
+
+ /**
* @brief Inserts a %binomial_distribution random number distribution
* @p __x into the output stream @p __os.
*
std::normal_distribution<double> _M_nd;
};
+ /**
+ * @brief Return true if two binomial distributions are different.
+ */
+ template<typename _IntType>
+ inline bool
+ operator!=(const std::binomial_distribution<_IntType>& __d1,
+ const std::binomial_distribution<_IntType>& __d2)
+ { return !(__d1 == __d2); }
+
/**
* @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$p(i|p) = (1 - p)p^{i-1}@f$ where @f$p@f$ is the parameter of the
* distribution.
*/
template<typename _IntType = int>
class geometric_distribution
{
- __glibcxx_class_requires(_IntType, _IntegerConcept)
+ static_assert(std::is_integral<_IntType>::value,
+ "template argument not an integral type");
public:
/** The type of the range of the distribution. */
p() const
{ return _M_p; }
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_p == __p2._M_p; }
+
private:
void
_M_initialize()
max() const
{ return std::numeric_limits<result_type>::max(); }
+ /**
+ * @brief Generating functions.
+ */
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
};
/**
+ * @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>
+ inline bool
+ operator!=(const std::geometric_distribution<_IntType>& __d1,
+ const std::geometric_distribution<_IntType>& __d2)
+ { return !(__d1 == __d2); }
+
+ /**
* @brief Inserts a %geometric_distribution random number distribution
* @p __x into the output stream @p __os.
*
* @brief A negative_binomial_distribution random number distribution.
*
* The formula for the negative binomial probability mass function is
- * @f$ p(i) = \binom{n}{i} p^i (1 - p)^{t - i} @f$ where @f$ t @f$
- * and @f$ p @f$ are the parameters of the distribution.
+ * @f$p(i) = \binom{n}{i} p^i (1 - p)^{t - i}@f$ where @f$t@f$
+ * and @f$p@f$ are the parameters of the distribution.
*/
template<typename _IntType = int>
class negative_binomial_distribution
{
- __glibcxx_class_requires(_IntType, _IntegerConcept)
+ static_assert(std::is_integral<_IntType>::value,
+ "template argument not an integral type");
public:
/** The type of the range of the distribution. */
p() const
{ return _M_p; }
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_k == __p2._M_k && __p1._M_p == __p2._M_p; }
+
private:
_IntType _M_k;
double _M_p;
{ _M_gd.reset(); }
/**
- * @brief Return the @f$ k @f$ parameter of the distribution.
+ * @brief Return the @f$k@f$ parameter of the distribution.
*/
_IntType
k() const
{ return _M_param.k(); }
/**
- * @brief Return the @f$ p @f$ parameter of the distribution.
+ * @brief Return the @f$p@f$ parameter of the distribution.
*/
double
p() const
max() const
{ return std::numeric_limits<result_type>::max(); }
+ /**
+ * @brief Generating functions.
+ */
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng);
operator()(_UniformRandomNumberGenerator& __urng,
const param_type& __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; }
+
+ /**
+ * @brief Inserts a %negative_binomial_distribution random
+ * number distribution @p __x into the output stream @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A %negative_binomial_distribution random number
+ * distribution.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ 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>&);
+
+ /**
+ * @brief Extracts a %negative_binomial_distribution random number
+ * distribution @p __x from the input stream @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A %negative_binomial_distribution random number
+ * generator engine.
+ *
+ * @returns The input stream with @p __x extracted or in an error state.
+ */
+ template<typename _IntType1, typename _CharT, typename _Traits>
+ friend std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>&,
+ std::negative_binomial_distribution<_IntType1>&);
+
private:
param_type _M_param;
};
/**
- * @brief Inserts a %negative_binomial_distribution random
- * number distribution @p __x into the output stream @p __os.
- *
- * @param __os An output stream.
- * @param __x A %negative_binomial_distribution random number
- * distribution.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
+ * @brief Return true if two negative binomial distributions are different.
*/
- template<typename _IntType, typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
- const std::negative_binomial_distribution<_IntType>&);
+ template<typename _IntType>
+ inline bool
+ operator!=(const std::negative_binomial_distribution<_IntType>& __d1,
+ const std::negative_binomial_distribution<_IntType>& __d2)
+ { return !(__d1 == __d2); }
- /**
- * @brief Extracts a %negative_binomial_distribution random number
- * distribution @p __x from the input stream @p __is.
- *
- * @param __is An input stream.
- * @param __x A %negative_binomial_distribution random number
- * generator engine.
- *
- * @returns The input stream with @p __x extracted or in an error state.
- */
- template<typename _IntType, typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>&,
- std::negative_binomial_distribution<_IntType>&);
- /* @} */ // group std_random_distributions_bernoulli
+ /* @} */ // group random_distributions_bernoulli
/**
- * @addtogroup std_random_distributions_poisson Poisson Distributions
- * @ingroup std_random_distributions
+ * @addtogroup random_distributions_poisson Poisson
+ * @ingroup random_distributions
* @{
*/
* @brief A discrete Poisson random number distribution.
*
* The formula for the Poisson probability density function is
- * @f$ p(i|\mu) = \frac{\mu^i}{i!} e^{-\mu} @f$ where @f$ \mu @f$ is the
+ * @f$p(i|\mu) = \frac{\mu^i}{i!} e^{-\mu}@f$ where @f$\mu@f$ is the
* parameter of the distribution.
*/
template<typename _IntType = int>
class poisson_distribution
{
- __glibcxx_class_requires(_IntType, _IntegerConcept)
+ static_assert(std::is_integral<_IntType>::value,
+ "template argument not an integral type");
public:
/** The type of the range of the distribution. */
mean() const
{ return _M_mean; }
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_mean == __p2._M_mean; }
+
private:
// Hosts either log(mean) or the threshold of the simple method.
void
max() const
{ return std::numeric_limits<result_type>::max(); }
+ /**
+ * @brief Generating functions.
+ */
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
operator()(_UniformRandomNumberGenerator& __urng,
const param_type& __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)
+#ifdef _GLIBCXX_USE_C99_MATH_TR1
+ { return __d1.param() == __d2.param() && __d1._M_nd == __d2._M_nd; }
+#else
+ { return __d1.param() == __d2.param(); }
+#endif
+
/**
* @brief Inserts a %poisson_distribution random number distribution
* @p __x into the output stream @p __os.
};
/**
+ * @brief Return true if two Poisson distributions are different.
+ */
+ template<typename _IntType>
+ inline bool
+ operator!=(const std::poisson_distribution<_IntType>& __d1,
+ const std::poisson_distribution<_IntType>& __d2)
+ { return !(__d1 == __d2); }
+
+
+ /**
* @brief An exponential continuous distribution for random numbers.
*
* The formula for the exponential probability density function is
- * @f$ p(x|\lambda) = \lambda e^{-\lambda x} @f$.
+ * @f$p(x|\lambda) = \lambda e^{-\lambda x}@f$.
*
* <table border=1 cellpadding=10 cellspacing=0>
* <caption align=top>Distribution Statistics</caption>
- * <tr><td>Mean</td><td>@f$ \frac{1}{\lambda} @f$</td></tr>
- * <tr><td>Median</td><td>@f$ \frac{\ln 2}{\lambda} @f$</td></tr>
- * <tr><td>Mode</td><td>@f$ zero @f$</td></tr>
+ * <tr><td>Mean</td><td>@f$\frac{1}{\lambda}@f$</td></tr>
+ * <tr><td>Median</td><td>@f$\frac{\ln 2}{\lambda}@f$</td></tr>
+ * <tr><td>Mode</td><td>@f$zero@f$</td></tr>
* <tr><td>Range</td><td>@f$[0, \infty]@f$</td></tr>
- * <tr><td>Standard Deviation</td><td>@f$ \frac{1}{\lambda} @f$</td></tr>
+ * <tr><td>Standard Deviation</td><td>@f$\frac{1}{\lambda}@f$</td></tr>
* </table>
*/
template<typename _RealType = double>
class exponential_distribution
{
+ static_assert(std::is_floating_point<_RealType>::value,
+ "template argument not a floating point type");
+
public:
/** The type of the range of the distribution. */
typedef _RealType result_type;
lambda() const
{ return _M_lambda; }
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_lambda == __p2._M_lambda; }
+
private:
_RealType _M_lambda;
};
public:
/**
* @brief Constructs an exponential distribution with inverse scale
- * parameter @f$ \lambda @f$.
+ * parameter @f$\lambda@f$.
*/
explicit
exponential_distribution(const result_type& __lambda = result_type(1))
max() const
{ return std::numeric_limits<result_type>::max(); }
+ /**
+ * @brief Generating functions.
+ */
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
};
/**
+ * @brief Return true if two exponential distributions have the same
+ * parameters.
+ */
+ template<typename _RealType>
+ inline bool
+ operator==(const std::exponential_distribution<_RealType>& __d1,
+ const std::exponential_distribution<_RealType>& __d2)
+ { return __d1.param() == __d2.param(); }
+
+ /**
+ * @brief Return true if two exponential distributions have different
+ * parameters.
+ */
+ template<typename _RealType>
+ inline bool
+ operator!=(const std::exponential_distribution<_RealType>& __d1,
+ const std::exponential_distribution<_RealType>& __d2)
+ { return !(__d1 == __d2); }
+
+ /**
* @brief Inserts a %exponential_distribution random number distribution
* @p __x into the output stream @p __os.
*
/**
* @brief A weibull_distribution random number distribution.
*
- * The formula for the normal probability density function is
- * @f$ p(x|\alpha,\beta) = \frac{a}{b} (frac{x}{b})^{a-1}
- * \exp{(-(frac{x}{b})^a)} @f$.
+ * The formula for the normal probability density function is:
+ * @f[
+ * p(x|\alpha,\beta) = \frac{\alpha}{\beta} (\frac{x}{\beta})^{\alpha-1}
+ * \exp{(-(\frac{x}{\beta})^\alpha)}
+ * @f]
*/
template<typename _RealType = double>
class weibull_distribution
{
+ static_assert(std::is_floating_point<_RealType>::value,
+ "template argument not a floating point type");
+
public:
/** The type of the range of the distribution. */
typedef _RealType result_type;
b() const
{ return _M_b; }
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; }
+
private:
_RealType _M_a;
_RealType _M_b;
{ }
/**
- * @brief Return the @f$ a @f$ parameter of the distribution.
+ * @brief Return the @f$a@f$ parameter of the distribution.
*/
_RealType
a() const
{ return _M_param.a(); }
/**
- * @brief Return the @f$ b @f$ parameter of the distribution.
+ * @brief Return the @f$b@f$ parameter of the distribution.
*/
_RealType
b() const
max() const
{ return std::numeric_limits<result_type>::max(); }
+ /**
+ * @brief Generating functions.
+ */
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
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>
+ inline bool
+ operator!=(const std::weibull_distribution<_RealType>& __d1,
+ const std::weibull_distribution<_RealType>& __d2)
+ { return !(__d1 == __d2); }
+
/**
* @brief Inserts a %weibull_distribution random number distribution
* @p __x into the output stream @p __os.
* @brief A extreme_value_distribution random number distribution.
*
* The formula for the normal probability mass function is
- * @f$ p(x|a,b) = \frac{1}{b}
- * \exp( \frac{a-x}{b} - \exp(\frac{a-x}{b})) @f$
+ * @f[
+ * p(x|a,b) = \frac{1}{b}
+ * \exp( \frac{a-x}{b} - \exp(\frac{a-x}{b}))
+ * @f]
*/
template<typename _RealType = double>
class extreme_value_distribution
{
+ static_assert(std::is_floating_point<_RealType>::value,
+ "template argument not a floating point type");
+
public:
/** The type of the range of the distribution. */
typedef _RealType result_type;
b() const
{ return _M_b; }
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; }
+
private:
_RealType _M_a;
_RealType _M_b;
{ }
/**
- * @brief Return the @f$ a @f$ parameter of the distribution.
+ * @brief Return the @f$a@f$ parameter of the distribution.
*/
_RealType
a() const
{ return _M_param.a(); }
/**
- * @brief Return the @f$ b @f$ parameter of the distribution.
+ * @brief Return the @f$b@f$ parameter of the distribution.
*/
_RealType
b() const
max() const
{ return std::numeric_limits<result_type>::max(); }
+ /**
+ * @brief Generating functions.
+ */
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
};
/**
+ * @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>
+ inline bool
+ operator!=(const std::extreme_value_distribution<_RealType>& __d1,
+ const std::extreme_value_distribution<_RealType>& __d2)
+ { return !(__d1 == __d2); }
+
+ /**
* @brief Inserts a %extreme_value_distribution random number distribution
* @p __x into the output stream @p __os.
*
template<typename _IntType = int>
class discrete_distribution
{
- __glibcxx_class_requires(_IntType, _IntegerConcept)
+ static_assert(std::is_integral<_IntType>::value,
+ "template argument not an integral type");
public:
/** The type of the range of the distribution. */
probabilities() const
{ return _M_prob; }
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_prob == __p2._M_prob; }
+
private:
void
_M_initialize();
max() const
{ return this->_M_param._M_prob.size() - 1; }
+ /**
+ * @brief Generating functions.
+ */
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
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.
+ */
+ template<typename _IntType>
+ inline bool
+ operator!=(const std::discrete_distribution<_IntType>& __d1,
+ const std::discrete_distribution<_IntType>& __d2)
+ { return !(__d1 == __d2); }
+
/**
* @brief A piecewise_constant_distribution random number distribution.
template<typename _RealType = double>
class piecewise_constant_distribution
{
+ static_assert(std::is_floating_point<_RealType>::value,
+ "template argument not a floating point type");
+
public:
/** The type of the range of the distribution. */
typedef _RealType result_type;
densities() const
{ return _M_den; }
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_int == __p2._M_int && __p1._M_den == __p2._M_den; }
+
private:
void
_M_initialize();
max() const
{ return this->_M_param._M_int.back(); }
+ /**
+ * @brief Generating functions.
+ */
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
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.
+ */
+ template<typename _RealType>
+ inline bool
+ operator!=(const std::piecewise_constant_distribution<_RealType>& __d1,
+ const std::piecewise_constant_distribution<_RealType>& __d2)
+ { return !(__d1 == __d2); }
+
/**
* @brief A piecewise_linear_distribution random number distribution.
template<typename _RealType = double>
class piecewise_linear_distribution
{
+ static_assert(std::is_floating_point<_RealType>::value,
+ "template argument not a floating point type");
+
public:
/** The type of the range of the distribution. */
typedef _RealType result_type;
densities() const
{ return _M_den; }
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return (__p1._M_int == __p2._M_int
+ && __p1._M_den == __p2._M_den); }
+
private:
void
_M_initialize();
max() const
{ return this->_M_param._M_int.back(); }
+ /**
+ * @brief Generating functions.
+ */
template<typename _UniformRandomNumberGenerator>
result_type
operator()(_UniformRandomNumberGenerator& __urng)
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.
+ */
+ template<typename _RealType>
+ inline bool
+ operator!=(const std::piecewise_linear_distribution<_RealType>& __d1,
+ const std::piecewise_linear_distribution<_RealType>& __d2)
+ { return !(__d1 == __d2); }
+
- /* @} */ // group std_random_distributions_poisson
+ /* @} */ // group random_distributions_poisson
- /* @} */ // group std_random_distributions
+ /* @} */ // group random_distributions
/**
- * @addtogroup std_random_utilities Random Number Utilities
- * @ingroup std_random
+ * @addtogroup random_utilities Random Number Utilities
+ * @ingroup random
* @{
*/
std::vector<result_type> _M_v;
};
- /* @} */ // group std_random_utilities
+ /* @} */ // group random_utilities
- /* @} */ // group std_random
+ /* @} */ // group random
}
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