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Diffstat (limited to 'gcc-4.8.1/libstdc++-v3/include/bits/random.h')
| -rw-r--r-- | gcc-4.8.1/libstdc++-v3/include/bits/random.h | 6068 |
1 files changed, 0 insertions, 6068 deletions
diff --git a/gcc-4.8.1/libstdc++-v3/include/bits/random.h b/gcc-4.8.1/libstdc++-v3/include/bits/random.h deleted file mode 100644 index b471726be..000000000 --- a/gcc-4.8.1/libstdc++-v3/include/bits/random.h +++ /dev/null @@ -1,6068 +0,0 @@ -// random number generation -*- C++ -*- - -// Copyright (C) 2009-2013 Free Software Foundation, Inc. -// -// This file is part of the GNU ISO C++ Library. This library is free -// software; you can redistribute it and/or modify it under the -// terms of the GNU General Public License as published by the -// Free Software Foundation; either version 3, or (at your option) -// any later version. - -// This library is distributed in the hope that it will be useful, -// but WITHOUT ANY WARRANTY; without even the implied warranty of -// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the -// GNU General Public License for more details. - -// Under Section 7 of GPL version 3, you are granted additional -// permissions described in the GCC Runtime Library Exception, version -// 3.1, as published by the Free Software Foundation. - -// You should have received a copy of the GNU General Public License and -// a copy of the GCC Runtime Library Exception along with this program; -// see the files COPYING3 and COPYING.RUNTIME respectively. If not, see -// <http://www.gnu.org/licenses/>. - -/** - * @file bits/random.h - * This is an internal header file, included by other library headers. - * Do not attempt to use it directly. @headername{random} - */ - -#ifndef _RANDOM_H -#define _RANDOM_H 1 - -#include <vector> - -namespace std _GLIBCXX_VISIBILITY(default) -{ -_GLIBCXX_BEGIN_NAMESPACE_VERSION - - // [26.4] Random number generation - - /** - * @defgroup random Random Number Generation - * @ingroup numerics - * - * A facility for generating random numbers on selected distributions. - * @{ - */ - - /** - * @brief A function template for converting the output of a (integral) - * uniform random number generator to a floatng point result in the range - * [0-1). - */ - template<typename _RealType, size_t __bits, - typename _UniformRandomNumberGenerator> - _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 - { static const _UIntType __value = 0; }; - - template<typename _UIntType, size_t __w> - struct _Shift<_UIntType, __w, true> - { static const _UIntType __value = _UIntType(1) << __w; }; - - 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; - } - }; - - template<typename _Tp, _Tp __m, _Tp __a = 1, _Tp __c = 0> - inline _Tp - __mod(_Tp __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 - * the input for a specific Distribution. - */ - template<typename _Engine, typename _DInputType> - struct _Adaptor - { - - public: - _Adaptor(_Engine& __g) - : _M_g(__g) { } - - _DInputType - min() const - { return _DInputType(0); } - - _DInputType - max() const - { return _DInputType(1); } - - /* - * Converts a value generated by the adapted random number generator - * into a value in the input domain for the dependent random number - * distribution. - */ - _DInputType - operator()() - { - return std::generate_canonical<_DInputType, - std::numeric_limits<_DInputType>::digits, - _Engine>(_M_g); - } - - private: - _Engine& _M_g; - }; - - _GLIBCXX_END_NAMESPACE_VERSION - } // namespace __detail - -_GLIBCXX_BEGIN_NAMESPACE_VERSION - - /** - * @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 - * random number generator supplied as a part of this library are - * all uniform random number generators which provide a sequence of - * random number uniformly distributed over their range. - * - * A number generator is a function object with an operator() that - * takes zero arguments and returns a number. - * - * A compliant random number generator must satisfy the following - * requirements. <table border=1 cellpadding=10 cellspacing=0> - * <caption align=top>Random Number Generator Requirements</caption> - * <tr><td>To be documented.</td></tr> </table> - * - * @{ - */ - - /** - * @brief A model of a linear congruential random number generator. - * - * 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 - * @p __m is 0, the modulus @p __m used is - * 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$1@f$. - */ - template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m> - class 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. */ - typedef _UIntType result_type; - - /** The multiplier. */ - static constexpr result_type multiplier = __a; - /** An increment. */ - static constexpr result_type increment = __c; - /** The modulus. */ - static constexpr result_type modulus = __m; - static constexpr result_type default_seed = 1u; - - /** - * @brief Constructs a %linear_congruential_engine random number - * generator engine with seed @p __s. The default seed value - * is 1. - * - * @param __s The initial seed value. - */ - explicit - linear_congruential_engine(result_type __s = default_seed) - { seed(__s); } - - /** - * @brief Constructs a %linear_congruential_engine random number - * generator engine seeded from the seed sequence @p __q. - * - * @param __q the seed sequence. - */ - 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 - * engine sequence to the seed @p __s. - * - * @param __s The new seed. - */ - void - seed(result_type __s = default_seed); - - /** - * @brief Reseeds the %linear_congruential_engine random number generator - * engine - * sequence using values from the seed sequence @p __q. - * - * @param __q the seed sequence. - */ - 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. - * - * The minimum depends on the @p __c parameter: if it is zero, the - * minimum generated must be > 0, otherwise 0 is allowed. - */ - static constexpr result_type - min() - { return __c == 0u ? 1u : 0u; } - - /** - * @brief Gets the largest possible value in the output range. - */ - static constexpr result_type - max() - { return __m - 1u; } - - /** - * @brief Discard a sequence of random numbers. - */ - void - discard(unsigned long long __z) - { - for (; __z != 0ULL; --__z) - (*this)(); - } - - /** - * @brief Gets the next random number in the sequence. - */ - result_type - operator()() - { - _M_x = __detail::__mod<_UIntType, __m, __a, __c>(_M_x); - return _M_x; - } - - /** - * @brief Compares two linear congruential random number generator - * objects of the same type for equality. - * - * @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 equal, false otherwise. - */ - friend bool - operator==(const linear_congruential_engine& __lhs, - const linear_congruential_engine& __rhs) - { return __lhs._M_x == __rhs._M_x; } - - /** - * @brief Writes the textual representation of the state x(i) of x to - * @p __os. - * - * @param __os The output stream. - * @param __lcr A % linear_congruential_engine random number generator. - * @returns __os. - */ - 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>& __os, - const std::linear_congruential_engine<_UIntType1, - __a1, __c1, __m1>& __lcr); - - /** - * @brief Sets the state of the engine by reading its textual - * representation from @p __is. - * - * The textual representation must have been previously written using - * an output stream whose imbued locale and whose type's template - * specialization arguments _CharT and _Traits were the same as those - * of @p __is. - * - * @param __is The input stream. - * @param __lcr A % linear_congruential_engine random number generator. - * @returns __is. - */ - 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>& __is, - std::linear_congruential_engine<_UIntType1, __a1, - __c1, __m1>& __lcr); - - private: - _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. - * - * This algorithm avoids multiplication and division and is designed to be - * friendly to a pipelined architecture. If the parameters are chosen - * correctly, this generator will produce numbers with a very long period and - * fairly good apparent entropy, although still not cryptographically strong. - * - * The best way to use this generator is with the predefined mt19937 class. - * - * This algorithm was originally invented by Makoto Matsumoto and - * Takuji Nishimura. - * - * @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, - _UIntType __a, size_t __u, _UIntType __d, size_t __s, - _UIntType __b, size_t __t, - _UIntType __c, size_t __l, _UIntType __f> - class mersenne_twister_engine - { - 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), - "template argument substituting __a out of bound"); - static_assert(__b <= (__detail::_Shift<_UIntType, __w>::__value - 1), - "template argument substituting __b out of bound"); - static_assert(__c <= (__detail::_Shift<_UIntType, __w>::__value - 1), - "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. */ - typedef _UIntType result_type; - - // parameter values - 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 - mersenne_twister_engine(result_type __sd = default_seed) - { seed(__sd); } - - /** - * @brief Constructs a %mersenne_twister_engine random number generator - * engine seeded from the seed sequence @p __q. - * - * @param __q the seed sequence. - */ - 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); - - 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. - */ - static constexpr result_type - min() - { return 0; }; - - /** - * @brief Gets the largest possible value in the output range. - */ - static constexpr result_type - max() - { return __detail::_Shift<_UIntType, __w>::__value - 1; } - - /** - * @brief Discard a sequence of random numbers. - */ - void - discard(unsigned long long __z); - - result_type - operator()(); - - /** - * @brief Compares two % mersenne_twister_engine random number generator - * objects of the same type for equality. - * - * @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 equal, false otherwise. - */ - 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) - && __lhs._M_p == __rhs._M_p); } - - /** - * @brief Inserts the current state of a % mersenne_twister_engine - * random number generator engine @p __x into the output stream - * @p __os. - * - * @param __os An output stream. - * @param __x A % mersenne_twister_engine random number generator - * engine. - * - * @returns The output stream with the state of @p __x inserted or in - * an error state. - */ - template<typename _UIntType1, - size_t __w1, size_t __n1, - size_t __m1, size_t __r1, - _UIntType1 __a1, size_t __u1, - _UIntType1 __d1, size_t __s1, - _UIntType1 __b1, size_t __t1, - _UIntType1 __c1, size_t __l1, _UIntType1 __f1, - typename _CharT, typename _Traits> - friend 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>& __x); - - /** - * @brief Extracts the current state of a % mersenne_twister_engine - * random number generator engine @p __x from the input stream - * @p __is. - * - * @param __is An input stream. - * @param __x A % mersenne_twister_engine random number generator - * engine. - * - * @returns The input stream with the state of @p __x extracted or in - * an error state. - */ - template<typename _UIntType1, - size_t __w1, size_t __n1, - size_t __m1, size_t __r1, - _UIntType1 __a1, size_t __u1, - _UIntType1 __d1, size_t __s1, - _UIntType1 __b1, size_t __t1, - _UIntType1 __c1, size_t __l1, _UIntType1 __f1, - typename _CharT, typename _Traits> - friend 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>& __x); - - private: - void _M_gen_rand(); - - _UIntType _M_x[state_size]; - size_t _M_p; - }; - - /** - * @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] - * - * 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. - * @var _M_p Current index of x(i - r). - */ - template<typename _UIntType, size_t __w, size_t __s, size_t __r> - class 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. */ - typedef _UIntType result_type; - - // parameter values - 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 - * random number generator. - */ - explicit - subtract_with_carry_engine(result_type __sd = default_seed) - { seed(__sd); } - - /** - * @brief Constructs a %subtract_with_carry_engine random number engine - * seeded from the seed sequence @p __q. - * - * @param __q the seed sequence. - */ - 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 - * generator. - * - * N1688[4.19] modifies this as follows. If @p __value == 0, - * sets value to 19780503. In any case, with a linear - * congruential generator lcg(i) having parameters @f$ m_{lcg} = - * 2147483563, a_{lcg} = 40014, c_{lcg} = 0, and lcg(0) = value - * @f$, sets @f$ x_{-r} \dots x_{-1} @f$ to @f$ lcg(1) \bmod m - * \dots lcg(r) \bmod m @f$ respectively. If @f$ x_{-1} = 0 @f$ - * set carry to 1, otherwise sets carry to 0. - */ - void - seed(result_type __sd = default_seed); - - /** - * @brief Seeds the initial state @f$x_0@f$ of the - * % subtract_with_carry_engine random number generator. - */ - 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 - * integers returned by this generator. - */ - static constexpr result_type - min() - { return 0; } - - /** - * @brief Gets the inclusive maximum value of the range of random - * integers returned by this generator. - */ - static constexpr result_type - max() - { return __detail::_Shift<_UIntType, __w>::__value - 1; } - - /** - * @brief Discard a sequence of random numbers. - */ - void - discard(unsigned long long __z) - { - for (; __z != 0ULL; --__z) - (*this)(); - } - - /** - * @brief Gets the next random number in the sequence. - */ - result_type - operator()(); - - /** - * @brief Compares two % subtract_with_carry_engine random number - * generator objects of the same type for equality. - * - * @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 equal, false otherwise. - */ - 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) - && __lhs._M_carry == __rhs._M_carry - && __lhs._M_p == __rhs._M_p); } - - /** - * @brief Inserts the current state of a % subtract_with_carry_engine - * random number generator engine @p __x into the output stream - * @p __os. - * - * @param __os An output stream. - * @param __x A % subtract_with_carry_engine random number generator - * engine. - * - * @returns The output stream with the state of @p __x inserted or in - * an error state. - */ - template<typename _UIntType1, size_t __w1, size_t __s1, size_t __r1, - typename _CharT, typename _Traits> - friend std::basic_ostream<_CharT, _Traits>& - operator<<(std::basic_ostream<_CharT, _Traits>&, - const std::subtract_with_carry_engine<_UIntType1, __w1, - __s1, __r1>&); - - /** - * @brief Extracts the current state of a % subtract_with_carry_engine - * random number generator engine @p __x from the input stream - * @p __is. - * - * @param __is An input stream. - * @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. - */ - template<typename _UIntType1, size_t __w1, size_t __s1, size_t __r1, - typename _CharT, typename _Traits> - friend std::basic_istream<_CharT, _Traits>& - operator>>(std::basic_istream<_CharT, _Traits>&, - std::subtract_with_carry_engine<_UIntType1, __w1, - __s1, __r1>&); - - private: - _UIntType _M_x[long_lag]; - _UIntType _M_carry; - size_t _M_p; - }; - - /** - * @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. - * - * 0 <= @p __r <= @p __p - */ - template<typename _RandomNumberEngine, size_t __p, size_t __r> - class discard_block_engine - { - static_assert(1 <= __r && __r <= __p, - "template argument substituting __r out of bounds"); - - public: - /** The type of the generated random value. */ - typedef typename _RandomNumberEngine::result_type result_type; - - // parameter values - static constexpr size_t block_size = __p; - static constexpr size_t used_block = __r; - - /** - * @brief Constructs a default %discard_block_engine engine. - * - * The underlying engine is default constructed as well. - */ - discard_block_engine() - : _M_b(), _M_n(0) { } - - /** - * @brief Copy constructs a %discard_block_engine engine. - * - * Copies an existing base class random number generator. - * @param __rng An existing (base class) engine object. - */ - explicit - 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. - */ - explicit - discard_block_engine(_RandomNumberEngine&& __rng) - : _M_b(std::move(__rng)), _M_n(0) { } - - /** - * @brief Seed constructs a %discard_block_engine engine. - * - * Constructs the underlying generator engine seeded with @p __s. - * @param __s A seed value for the base class engine. - */ - explicit - discard_block_engine(result_type __s) - : _M_b(__s), _M_n(0) { } - - /** - * @brief Generator construct a %discard_block_engine engine. - * - * @param __q A seed sequence. - */ - 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 - * seed for the underlying base class generator engine. - */ - void - seed() - { - _M_b.seed(); - _M_n = 0; - } - - /** - * @brief Reseeds the %discard_block_engine object with the default - * seed for the underlying base class generator engine. - */ - void - seed(result_type __s) - { - _M_b.seed(__s); - _M_n = 0; - } - - /** - * @brief Reseeds the %discard_block_engine object with the given seed - * sequence. - * @param __q A seed generator function. - */ - template<typename _Sseq> - void - seed(_Sseq& __q) - { - _M_b.seed(__q); - _M_n = 0; - } - - /** - * @brief Gets a const reference to the underlying generator engine - * object. - */ - const _RandomNumberEngine& - base() const noexcept - { return _M_b; } - - /** - * @brief Gets the minimum value in the generated random number range. - */ - static constexpr result_type - min() - { return _RandomNumberEngine::min(); } - - /** - * @brief Gets the maximum value in the generated random number range. - */ - static constexpr result_type - max() - { return _RandomNumberEngine::max(); } - - /** - * @brief Discard a sequence of random numbers. - */ - void - discard(unsigned long long __z) - { - for (; __z != 0ULL; --__z) - (*this)(); - } - - /** - * @brief Gets the next value in the generated random number sequence. - */ - result_type - operator()(); - - /** - * @brief Compares two %discard_block_engine random number generator - * objects of the same type for equality. - * - * @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 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; } - - /** - * @brief Inserts the current state of a %discard_block_engine random - * number generator engine @p __x into the output stream - * @p __os. - * - * @param __os An output stream. - * @param __x A %discard_block_engine random number generator engine. - * - * @returns The output stream with the state of @p __x inserted or in - * an error state. - */ - 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>& __os, - const std::discard_block_engine<_RandomNumberEngine1, - __p1, __r1>& __x); - - /** - * @brief Extracts the current state of a % subtract_with_carry_engine - * random number generator engine @p __x from the input stream - * @p __is. - * - * @param __is An input stream. - * @param __x A %discard_block_engine random number generator engine. - * - * @returns The input stream with the state of @p __x extracted or in - * an error state. - */ - 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>& __is, - std::discard_block_engine<_RandomNumberEngine1, - __p1, __r1>& __x); - - private: - _RandomNumberEngine _M_b; - size_t _M_n; - }; - - /** - * @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(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. */ - typedef _UIntType result_type; - - /** - * @brief Constructs a default %independent_bits_engine engine. - * - * The underlying engine is default constructed as well. - */ - independent_bits_engine() - : _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. - */ - explicit - 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. - */ - explicit - independent_bits_engine(_RandomNumberEngine&& __rng) - : _M_b(std::move(__rng)) { } - - /** - * @brief Seed constructs a %independent_bits_engine engine. - * - * Constructs the underlying generator engine seeded with @p __s. - * @param __s A seed value for the base class engine. - */ - explicit - independent_bits_engine(result_type __s) - : _M_b(__s) { } - - /** - * @brief Generator construct a %independent_bits_engine engine. - * - * @param __q A seed sequence. - */ - 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 for the underlying base class generator engine. - */ - void - seed() - { _M_b.seed(); } - - /** - * @brief Reseeds the %independent_bits_engine object with the default - * seed for the underlying base class generator engine. - */ - void - seed(result_type __s) - { _M_b.seed(__s); } - - /** - * @brief Reseeds the %independent_bits_engine object with the given - * seed sequence. - * @param __q A seed generator function. - */ - template<typename _Sseq> - void - seed(_Sseq& __q) - { _M_b.seed(__q); } - - /** - * @brief Gets a const reference to the underlying generator engine - * object. - */ - const _RandomNumberEngine& - base() const noexcept - { return _M_b; } - - /** - * @brief Gets the minimum value in the generated random number range. - */ - static constexpr result_type - min() - { return 0U; } - - /** - * @brief Gets the maximum value in the generated random number range. - */ - static constexpr result_type - max() - { return __detail::_Shift<_UIntType, __w>::__value - 1; } - - /** - * @brief Discard a sequence of random numbers. - */ - void - discard(unsigned long long __z) - { - for (; __z != 0ULL; --__z) - (*this)(); - } - - /** - * @brief Gets the next value in the generated random number sequence. - */ - result_type - operator()(); - - /** - * @brief Compares two %independent_bits_engine random number generator - * objects of the same type for equality. - * - * @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 equal, false otherwise. - */ - friend bool - operator==(const independent_bits_engine& __lhs, - const independent_bits_engine& __rhs) - { return __lhs._M_b == __rhs._M_b; } - - /** - * @brief Extracts the current state of a % subtract_with_carry_engine - * random number generator engine @p __x from the input stream - * @p __is. - * - * @param __is An input stream. - * @param __x A %independent_bits_engine random number generator - * engine. - * - * @returns The input stream with the state of @p __x extracted or in - * an error state. - */ - template<typename _CharT, typename _Traits> - friend std::basic_istream<_CharT, _Traits>& - operator>>(std::basic_istream<_CharT, _Traits>& __is, - std::independent_bits_engine<_RandomNumberEngine, - __w, _UIntType>& __x) - { - __is >> __x._M_b; - return __is; - } - - private: - _RandomNumberEngine _M_b; - }; - - /** - * @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. - * - * @param __os An output stream. - * @param __x A %independent_bits_engine random number generator engine. - * - * @returns The output stream with the state of @p __x inserted or in - * an error state. - */ - template<typename _RandomNumberEngine, size_t __w, typename _UIntType, - typename _CharT, typename _Traits> - std::basic_ostream<_CharT, _Traits>& - operator<<(std::basic_ostream<_CharT, _Traits>& __os, - const std::independent_bits_engine<_RandomNumberEngine, - __w, _UIntType>& __x) - { - __os << __x.base(); - return __os; - } - - - /** - * @brief 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 __k> - class shuffle_order_engine - { - static_assert(1u <= __k, "template argument substituting " - "__k out of bound"); - - public: - /** The type of the generated random value. */ - typedef typename _RandomNumberEngine::result_type result_type; - - static constexpr size_t table_size = __k; - - /** - * @brief Constructs a default %shuffle_order_engine engine. - * - * The underlying engine is default constructed as well. - */ - shuffle_order_engine() - : _M_b() - { _M_initialize(); } - - /** - * @brief Copy constructs a %shuffle_order_engine engine. - * - * Copies an existing base class random number generator. - * @param __rng An existing (base class) engine object. - */ - explicit - 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. - */ - explicit - shuffle_order_engine(_RandomNumberEngine&& __rng) - : _M_b(std::move(__rng)) - { _M_initialize(); } - - /** - * @brief Seed constructs a %shuffle_order_engine engine. - * - * Constructs the underlying generator engine seeded with @p __s. - * @param __s A seed value for the base class engine. - */ - explicit - shuffle_order_engine(result_type __s) - : _M_b(__s) - { _M_initialize(); } - - /** - * @brief Generator construct a %shuffle_order_engine engine. - * - * @param __q A seed sequence. - */ - 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 - for the underlying base class generator engine. - */ - void - seed() - { - _M_b.seed(); - _M_initialize(); - } - - /** - * @brief Reseeds the %shuffle_order_engine object with the default seed - * for the underlying base class generator engine. - */ - void - seed(result_type __s) - { - _M_b.seed(__s); - _M_initialize(); - } - - /** - * @brief Reseeds the %shuffle_order_engine object with the given seed - * sequence. - * @param __q A seed generator function. - */ - template<typename _Sseq> - void - seed(_Sseq& __q) - { - _M_b.seed(__q); - _M_initialize(); - } - - /** - * Gets a const reference to the underlying generator engine object. - */ - const _RandomNumberEngine& - base() const noexcept - { return _M_b; } - - /** - * Gets the minimum value in the generated random number range. - */ - static constexpr result_type - min() - { return _RandomNumberEngine::min(); } - - /** - * Gets the maximum value in the generated random number range. - */ - static constexpr result_type - max() - { return _RandomNumberEngine::max(); } - - /** - * Discard a sequence of random numbers. - */ - void - discard(unsigned long long __z) - { - for (; __z != 0ULL; --__z) - (*this)(); - } - - /** - * Gets the next value in the generated random number sequence. - */ - result_type - operator()(); - - /** - * Compares two %shuffle_order_engine random number generator objects - * of the same type for equality. - * - * @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 equal, false otherwise. - */ - friend bool - operator==(const shuffle_order_engine& __lhs, - const shuffle_order_engine& __rhs) - { 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 - * number generator engine @p __x into the output stream - @p __os. - * - * @param __os An output stream. - * @param __x A %shuffle_order_engine random number generator engine. - * - * @returns The output stream with the state of @p __x inserted or in - * an error state. - */ - template<typename _RandomNumberEngine1, size_t __k1, - typename _CharT, typename _Traits> - friend std::basic_ostream<_CharT, _Traits>& - operator<<(std::basic_ostream<_CharT, _Traits>& __os, - const std::shuffle_order_engine<_RandomNumberEngine1, - __k1>& __x); - - /** - * @brief Extracts the current state of a % subtract_with_carry_engine - * random number generator engine @p __x from the input stream - * @p __is. - * - * @param __is An input stream. - * @param __x A %shuffle_order_engine random number generator engine. - * - * @returns The input stream with the state of @p __x extracted or in - * an error state. - */ - template<typename _RandomNumberEngine1, size_t __k1, - typename _CharT, typename _Traits> - friend std::basic_istream<_CharT, _Traits>& - operator>>(std::basic_istream<_CharT, _Traits>& __is, - std::shuffle_order_engine<_RandomNumberEngine1, __k1>& __x); - - private: - void _M_initialize() - { - for (size_t __i = 0; __i < __k; ++__i) - _M_v[__i] = _M_b(); - _M_y = _M_b(); - } - - _RandomNumberEngine _M_b; - result_type _M_v[__k]; - result_type _M_y; - }; - - /** - * 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). - */ - 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 - * on Modeling and Computer Simulation, Vol. 8, No. 1, January 1998, pp 3-30. - */ - typedef mersenne_twister_engine< - uint_fast32_t, - 32, 624, 397, 31, - 0x9908b0dfUL, 11, - 0xffffffffUL, 7, - 0x9d2c5680UL, 15, - 0xefc60000UL, 18, 1812433253UL> mt19937; - - /** - * An alternative Mersenne Twister. - */ - typedef mersenne_twister_engine< - uint_fast64_t, - 64, 312, 156, 31, - 0xb5026f5aa96619e9ULL, 29, - 0x5555555555555555ULL, 17, - 0x71d67fffeda60000ULL, 37, - 0xfff7eee000000000ULL, 43, - 6364136223846793005ULL> mt19937_64; - - typedef subtract_with_carry_engine<uint_fast32_t, 24, 10, 24> - ranlux24_base; - - 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; - - /** - * A standard interface to a platform-specific non-deterministic - * random number generator (if any are available). - */ - class random_device - { - public: - /** The type of the generated random value. */ - typedef unsigned int result_type; - - // constructors, destructors and member functions - -#ifdef _GLIBCXX_USE_RANDOM_TR1 - - explicit - random_device(const std::string& __token = "default") - { - _M_init(__token); - } - - ~random_device() - { _M_fini(); } - -#else - - explicit - random_device(const std::string& __token = "mt19937") - { _M_init_pretr1(__token); } - - public: - -#endif - - static constexpr result_type - min() - { return std::numeric_limits<result_type>::min(); } - - static constexpr result_type - max() - { return std::numeric_limits<result_type>::max(); } - - double - entropy() const noexcept - { return 0.0; } - - result_type - operator()() - { -#ifdef _GLIBCXX_USE_RANDOM_TR1 - return this->_M_getval(); -#else - return this->_M_getval_pretr1(); -#endif - } - - // No copy functions. - random_device(const random_device&) = delete; - void operator=(const random_device&) = delete; - - private: - - 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 - { - FILE* _M_file; - mt19937 _M_mt; - }; - }; - - /* @} */ // group random_generators - - /** - * @addtogroup random_distributions Random Number Distributions - * @ingroup random - * @{ - */ - - /** - * @addtogroup random_distributions_uniform Uniform Distributions - * @ingroup random_distributions - * @{ - */ - - /** - * @brief Uniform discrete distribution for random numbers. - * A discrete random distribution on the range @f$[min, max]@f$ with equal - * probability throughout the range. - */ - template<typename _IntType = int> - class uniform_int_distribution - { - static_assert(std::is_integral<_IntType>::value, - "template argument not an integral type"); - - public: - /** The type of the range of the distribution. */ - typedef _IntType result_type; - /** Parameter type. */ - struct param_type - { - typedef uniform_int_distribution<_IntType> distribution_type; - - explicit - param_type(_IntType __a = 0, - _IntType __b = std::numeric_limits<_IntType>::max()) - : _M_a(__a), _M_b(__b) - { - _GLIBCXX_DEBUG_ASSERT(_M_a <= _M_b); - } - - result_type - a() const - { return _M_a; } - - 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: - _IntType _M_a; - _IntType _M_b; - }; - - public: - /** - * @brief Constructs a uniform distribution object. - */ - explicit - uniform_int_distribution(_IntType __a = 0, - _IntType __b = std::numeric_limits<_IntType>::max()) - : _M_param(__a, __b) - { } - - explicit - uniform_int_distribution(const param_type& __p) - : _M_param(__p) - { } - - /** - * @brief Resets the distribution state. - * - * Does nothing for the uniform integer distribution. - */ - void - reset() { } - - result_type - a() const - { return _M_param.a(); } - - result_type - b() const - { 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 - 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, _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 - * 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. - * - * @param __os An output stream. - * @param __x A %uniform_int_distribution random number distribution. - * - * @returns The output stream with the state of @p __x inserted or in - * an error state. - */ - template<typename _IntType, typename _CharT, typename _Traits> - std::basic_ostream<_CharT, _Traits>& - operator<<(std::basic_ostream<_CharT, _Traits>&, - const std::uniform_int_distribution<_IntType>&); - - /** - * @brief Extracts a %uniform_int_distribution random number distribution - * @p __x from the input stream @p __is. - * - * @param __is An input stream. - * @param __x A %uniform_int_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::uniform_int_distribution<_IntType>&); - - - /** - * @brief Uniform continuous distribution for random numbers. - * - * A continuous random distribution on the range [min, max) with equal - * probability throughout the range. The URNG should be real-valued and - * deliver number in the range [0, 1). - */ - 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; - /** Parameter type. */ - struct param_type - { - typedef uniform_real_distribution<_RealType> distribution_type; - - explicit - param_type(_RealType __a = _RealType(0), - _RealType __b = _RealType(1)) - : _M_a(__a), _M_b(__b) - { - _GLIBCXX_DEBUG_ASSERT(_M_a <= _M_b); - } - - result_type - a() const - { return _M_a; } - - 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; - }; - - public: - /** - * @brief Constructs a uniform_real_distribution object. - * - * @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), - _RealType __b = _RealType(1)) - : _M_param(__a, __b) - { } - - explicit - uniform_real_distribution(const param_type& __p) - : _M_param(__p) - { } - - /** - * @brief Resets the distribution state. - * - * Does nothing for the uniform real distribution. - */ - void - reset() { } - - result_type - a() const - { return _M_param.a(); } - - result_type - b() const - { 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 - 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, _M_param); } - - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng, - const param_type& __p) - { - __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> - __aurng(__urng); - 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 - * 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. - * - * @param __os An output stream. - * @param __x A %uniform_real_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::uniform_real_distribution<_RealType>&); - - /** - * @brief Extracts a %uniform_real_distribution random number distribution - * @p __x from the input stream @p __is. - * - * @param __is An input stream. - * @param __x A %uniform_real_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::uniform_real_distribution<_RealType>&); - - /* @} */ // group random_distributions_uniform - - /** - * @addtogroup random_distributions_normal Normal Distributions - * @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] - */ - 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; - /** Parameter type. */ - struct param_type - { - typedef normal_distribution<_RealType> distribution_type; - - explicit - param_type(_RealType __mean = _RealType(0), - _RealType __stddev = _RealType(1)) - : _M_mean(__mean), _M_stddev(__stddev) - { - _GLIBCXX_DEBUG_ASSERT(_M_stddev > _RealType(0)); - } - - _RealType - mean() const - { return _M_mean; } - - _RealType - 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 - * standard deviation. - */ - explicit - normal_distribution(result_type __mean = result_type(0), - result_type __stddev = result_type(1)) - : _M_param(__mean, __stddev), _M_saved_available(false) - { } - - explicit - normal_distribution(const param_type& __p) - : _M_param(__p), _M_saved_available(false) - { } - - /** - * @brief Resets the distribution state. - */ - void - reset() - { _M_saved_available = false; } - - /** - * @brief Returns the mean of the distribution. - */ - _RealType - mean() const - { return _M_param.mean(); } - - /** - * @brief Returns the standard deviation of the distribution. - */ - _RealType - stddev() const - { return _M_param.stddev(); } - - /** - * @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 greatest lower bound value of the distribution. - */ - result_type - min() const - { return std::numeric_limits<result_type>::min(); } - - /** - * @brief Returns the least upper bound value of the distribution. - */ - result_type - max() const - { return std::numeric_limits<result_type>::max(); } - - /** - * @brief Generating functions. - */ - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng) - { 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 - * 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. - * - * @param __os An output stream. - * @param __x A %normal_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>& __os, - const std::normal_distribution<_RealType1>& __x); - - /** - * @brief Extracts a %normal_distribution random number distribution - * @p __x from the input stream @p __is. - * - * @param __is An input stream. - * @param __x A %normal_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>& __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; - }; - - /** - * @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] - */ - 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; - /** Parameter type. */ - struct param_type - { - typedef lognormal_distribution<_RealType> distribution_type; - - explicit - param_type(_RealType __m = _RealType(0), - _RealType __s = _RealType(1)) - : _M_m(__m), _M_s(__s) - { } - - _RealType - m() const - { return _M_m; } - - _RealType - 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; - }; - - explicit - lognormal_distribution(_RealType __m = _RealType(0), - _RealType __s = _RealType(1)) - : _M_param(__m, __s), _M_nd() - { } - - explicit - lognormal_distribution(const param_type& __p) - : _M_param(__p), _M_nd() - { } - - /** - * Resets the distribution state. - */ - void - reset() - { _M_nd.reset(); } - - /** - * - */ - _RealType - m() const - { return _M_param.m(); } - - _RealType - s() const - { return _M_param.s(); } - - /** - * @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 greatest lower bound value of the distribution. - */ - result_type - min() const - { return result_type(0); } - - /** - * @brief Returns the least upper bound value of the distribution. - */ - result_type - max() const - { return std::numeric_limits<result_type>::max(); } - - /** - * @brief Generating functions. - */ - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng) - { return this->operator()(__urng, _M_param); } - - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng, - 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. - */ - 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 - * @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>& __os, - const std::lognormal_distribution<_RealType1>& __x); - - /** - * @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>& __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; - }; - - /** - * @brief Return true if two lognormal distributions are different. - */ - template<typename _RealType> - inline bool - operator!=(const std::lognormal_distribution<_RealType>& __d1, - const std::lognormal_distribution<_RealType>& __d2) - { return !(__d1 == __d2); } - - - /** - * @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] - */ - 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; - /** Parameter type. */ - struct param_type - { - typedef gamma_distribution<_RealType> distribution_type; - friend class gamma_distribution<_RealType>; - - explicit - param_type(_RealType __alpha_val = _RealType(1), - _RealType __beta_val = _RealType(1)) - : _M_alpha(__alpha_val), _M_beta(__beta_val) - { - _GLIBCXX_DEBUG_ASSERT(_M_alpha > _RealType(0)); - _M_initialize(); - } - - _RealType - alpha() const - { return _M_alpha; } - - _RealType - 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(); - - _RealType _M_alpha; - _RealType _M_beta; - - _RealType _M_malpha, _M_a2; - }; - - public: - /** - * @brief Constructs a gamma distribution with parameters - * @f$\alpha@f$ and @f$\beta@f$. - */ - explicit - gamma_distribution(_RealType __alpha_val = _RealType(1), - _RealType __beta_val = _RealType(1)) - : _M_param(__alpha_val, __beta_val), _M_nd() - { } - - explicit - gamma_distribution(const param_type& __p) - : _M_param(__p), _M_nd() - { } - - /** - * @brief Resets the distribution state. - */ - void - reset() - { _M_nd.reset(); } - - /** - * @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. - */ - _RealType - beta() const - { return _M_param.beta(); } - - /** - * @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 greatest lower bound value of the distribution. - */ - result_type - min() const - { return result_type(0); } - - /** - * @brief Returns the least upper bound value of the distribution. - */ - result_type - max() const - { return std::numeric_limits<result_type>::max(); } - - /** - * @brief Generating functions. - */ - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng) - { 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. - */ - 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 - * @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>& __os, - const std::gamma_distribution<_RealType1>& __x); - - /** - * @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>& __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 - 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$p(x|n) = \frac{x^{(n/2) - 1}e^{-x/2}}{\Gamma(n/2) 2^{n/2}}@f$ - */ - 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; - /** Parameter type. */ - struct param_type - { - typedef chi_squared_distribution<_RealType> distribution_type; - - explicit - param_type(_RealType __n = _RealType(1)) - : _M_n(__n) - { } - - _RealType - 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; - }; - - explicit - chi_squared_distribution(_RealType __n = _RealType(1)) - : _M_param(__n), _M_gd(__n / 2) - { } - - explicit - chi_squared_distribution(const param_type& __p) - : _M_param(__p), _M_gd(__p.n() / 2) - { } - - /** - * @brief Resets the distribution state. - */ - void - reset() - { _M_gd.reset(); } - - /** - * - */ - _RealType - n() const - { return _M_param.n(); } - - /** - * @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 greatest lower bound value of the distribution. - */ - result_type - min() const - { return result_type(0); } - - /** - * @brief Returns the least upper bound value of the distribution. - */ - result_type - 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); } - - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng, - const param_type& __p) - { - typedef typename std::gamma_distribution<result_type>::param_type - param_type; - 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. - */ - 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 - * @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>& __os, - const std::chi_squared_distribution<_RealType1>& __x); - - /** - * @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>& __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; - }; - - /** - * @brief Return true if two Chi-squared distributions are different. - */ - 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$p(x|a,b) = (\pi b (1 + (\frac{x-a}{b})^2))^{-1}@f$ - */ - 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; - /** Parameter type. */ - struct param_type - { - typedef cauchy_distribution<_RealType> distribution_type; - - explicit - param_type(_RealType __a = _RealType(0), - _RealType __b = _RealType(1)) - : _M_a(__a), _M_b(__b) - { } - - _RealType - a() const - { return _M_a; } - - _RealType - 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; - }; - - explicit - cauchy_distribution(_RealType __a = _RealType(0), - _RealType __b = _RealType(1)) - : _M_param(__a, __b) - { } - - explicit - cauchy_distribution(const param_type& __p) - : _M_param(__p) - { } - - /** - * @brief Resets the distribution state. - */ - void - reset() - { } - - /** - * - */ - _RealType - a() const - { return _M_param.a(); } - - _RealType - b() const - { 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 greatest lower bound value of the distribution. - */ - result_type - min() const - { return std::numeric_limits<result_type>::min(); } - - /** - * @brief Returns the least upper bound value of the distribution. - */ - result_type - max() const - { return std::numeric_limits<result_type>::max(); } - - /** - * @brief Generating functions. - */ - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng) - { 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 - * 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. - * - * @param __os An output stream. - * @param __x A %cauchy_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>& __os, - const std::cauchy_distribution<_RealType>& __x); - - /** - * @brief Extracts a %cauchy_distribution random number distribution - * @p __x from the input stream @p __is. - * - * @param __is An input stream. - * @param __x A %cauchy_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>& __is, - std::cauchy_distribution<_RealType>& __x); - - - /** - * @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)} - * (\frac{m}{n})^{m/2} x^{(m/2)-1} - * (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; - /** Parameter type. */ - struct param_type - { - typedef fisher_f_distribution<_RealType> distribution_type; - - explicit - param_type(_RealType __m = _RealType(1), - _RealType __n = _RealType(1)) - : _M_m(__m), _M_n(__n) - { } - - _RealType - m() const - { return _M_m; } - - _RealType - 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; - }; - - explicit - fisher_f_distribution(_RealType __m = _RealType(1), - _RealType __n = _RealType(1)) - : _M_param(__m, __n), _M_gd_x(__m / 2), _M_gd_y(__n / 2) - { } - - explicit - fisher_f_distribution(const param_type& __p) - : _M_param(__p), _M_gd_x(__p.m() / 2), _M_gd_y(__p.n() / 2) - { } - - /** - * @brief Resets the distribution state. - */ - void - reset() - { - _M_gd_x.reset(); - _M_gd_y.reset(); - } - - /** - * - */ - _RealType - m() const - { return _M_param.m(); } - - _RealType - n() const - { return _M_param.n(); } - - /** - * @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 greatest lower bound value of the distribution. - */ - result_type - min() const - { return result_type(0); } - - /** - * @brief Returns the least upper bound value of the distribution. - */ - result_type - max() const - { return std::numeric_limits<result_type>::max(); } - - /** - * @brief Generating functions. - */ - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng) - { return (_M_gd_x(__urng) * n()) / (_M_gd_y(__urng) * m()); } - - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng, - const param_type& __p) - { - typedef typename std::gamma_distribution<result_type>::param_type - param_type; - return ((_M_gd_x(__urng, param_type(__p.m() / 2)) * n()) - / (_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. - */ - 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 - * @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>& __os, - const std::fisher_f_distribution<_RealType1>& __x); - - /** - * @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>& __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. - */ - 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] - */ - 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; - /** Parameter type. */ - struct param_type - { - typedef student_t_distribution<_RealType> distribution_type; - - explicit - param_type(_RealType __n = _RealType(1)) - : _M_n(__n) - { } - - _RealType - 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; - }; - - explicit - student_t_distribution(_RealType __n = _RealType(1)) - : _M_param(__n), _M_nd(), _M_gd(__n / 2, 2) - { } - - explicit - student_t_distribution(const param_type& __p) - : _M_param(__p), _M_nd(), _M_gd(__p.n() / 2, 2) - { } - - /** - * @brief Resets the distribution state. - */ - void - reset() - { - _M_nd.reset(); - _M_gd.reset(); - } - - /** - * - */ - _RealType - n() const - { return _M_param.n(); } - - /** - * @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 greatest lower bound value of the distribution. - */ - result_type - min() const - { return std::numeric_limits<result_type>::min(); } - - /** - * @brief Returns the least upper bound value of the distribution. - */ - result_type - 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(n() / _M_gd(__urng)); } - - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng, - const param_type& __p) - { - typedef typename std::gamma_distribution<result_type>::param_type - param_type; - - const result_type __g = _M_gd(__urng, param_type(__p.n() / 2, 2)); - 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. - */ - 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 - * @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>& __os, - const std::student_t_distribution<_RealType1>& __x); - - /** - * @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>& __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; - std::gamma_distribution<result_type> _M_gd; - }; - - /** - * @brief Return true if two Student t distributions are different. - */ - template<typename _RealType> - inline bool - operator!=(const std::student_t_distribution<_RealType>& __d1, - const std::student_t_distribution<_RealType>& __d2) - { return !(__d1 == __d2); } - - - /* @} */ // group random_distributions_normal - - /** - * @addtogroup random_distributions_bernoulli Bernoulli Distributions - * @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. - */ - class bernoulli_distribution - { - public: - /** The type of the range of the distribution. */ - typedef bool result_type; - /** Parameter type. */ - struct param_type - { - typedef bernoulli_distribution distribution_type; - - explicit - param_type(double __p = 0.5) - : _M_p(__p) - { - _GLIBCXX_DEBUG_ASSERT((_M_p >= 0.0) && (_M_p <= 1.0)); - } - - double - 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; - }; - - public: - /** - * @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$[0, 1]@f$. - */ - explicit - bernoulli_distribution(double __p = 0.5) - : _M_param(__p) - { } - - explicit - bernoulli_distribution(const param_type& __p) - : _M_param(__p) - { } - - /** - * @brief Resets the distribution state. - * - * Does nothing for a Bernoulli distribution. - */ - void - reset() { } - - /** - * @brief Returns the @p p parameter of the distribution. - */ - double - p() const - { return _M_param.p(); } - - /** - * @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 greatest lower bound value of the distribution. - */ - result_type - min() const - { return std::numeric_limits<result_type>::min(); } - - /** - * @brief Returns the least upper bound value of the distribution. - */ - result_type - max() const - { return std::numeric_limits<result_type>::max(); } - - /** - * @brief Generating functions. - */ - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng) - { return this->operator()(__urng, _M_param); } - - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng, - const param_type& __p) - { - __detail::_Adaptor<_UniformRandomNumberGenerator, double> - __aurng(__urng); - if ((__aurng() - __aurng.min()) - < __p.p() * (__aurng.max() - __aurng.min())) - return true; - 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 - * 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. - * - * @param __os An output stream. - * @param __x A %bernoulli_distribution random number distribution. - * - * @returns The output stream with the state of @p __x inserted or in - * an error state. - */ - template<typename _CharT, typename _Traits> - std::basic_ostream<_CharT, _Traits>& - operator<<(std::basic_ostream<_CharT, _Traits>& __os, - const std::bernoulli_distribution& __x); - - /** - * @brief Extracts a %bernoulli_distribution random number distribution - * @p __x from the input stream @p __is. - * - * @param __is An input stream. - * @param __x A %bernoulli_distribution random number generator engine. - * - * @returns The input stream with @p __x extracted or in an error state. - */ - template<typename _CharT, typename _Traits> - std::basic_istream<_CharT, _Traits>& - operator>>(std::basic_istream<_CharT, _Traits>& __is, - std::bernoulli_distribution& __x) - { - double __p; - __is >> __p; - __x.param(bernoulli_distribution::param_type(__p)); - return __is; - } - - - /** - * @brief A discrete binomial random number distribution. - * - * The formula for the binomial probability density function is - * @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> - class binomial_distribution - { - static_assert(std::is_integral<_IntType>::value, - "template argument not an integral type"); - - public: - /** The type of the range of the distribution. */ - typedef _IntType result_type; - /** Parameter type. */ - struct param_type - { - typedef binomial_distribution<_IntType> distribution_type; - friend class binomial_distribution<_IntType>; - - explicit - param_type(_IntType __t = _IntType(1), double __p = 0.5) - : _M_t(__t), _M_p(__p) - { - _GLIBCXX_DEBUG_ASSERT((_M_t >= _IntType(0)) - && (_M_p >= 0.0) - && (_M_p <= 1.0)); - _M_initialize(); - } - - _IntType - t() const - { return _M_t; } - - double - 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(); - - _IntType _M_t; - double _M_p; - - double _M_q; -#if _GLIBCXX_USE_C99_MATH_TR1 - double _M_d1, _M_d2, _M_s1, _M_s2, _M_c, - _M_a1, _M_a123, _M_s, _M_lf, _M_lp1p; -#endif - bool _M_easy; - }; - - // constructors and member function - explicit - binomial_distribution(_IntType __t = _IntType(1), - double __p = 0.5) - : _M_param(__t, __p), _M_nd() - { } - - explicit - binomial_distribution(const param_type& __p) - : _M_param(__p), _M_nd() - { } - - /** - * @brief Resets the distribution state. - */ - void - reset() - { _M_nd.reset(); } - - /** - * @brief Returns the distribution @p t parameter. - */ - _IntType - t() const - { return _M_param.t(); } - - /** - * @brief Returns the distribution @p p parameter. - */ - double - p() const - { return _M_param.p(); } - - /** - * @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 greatest lower bound value of the distribution. - */ - result_type - min() const - { return 0; } - - /** - * @brief Returns the least upper bound value of the distribution. - */ - result_type - max() const - { return _M_param.t(); } - - /** - * @brief Generating functions. - */ - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng) - { 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. - */ - friend bool - operator==(const binomial_distribution& __d1, - const binomial_distribution& __d2) -#ifdef _GLIBCXX_USE_C99_MATH_TR1 - { return __d1._M_param == __d2._M_param && __d1._M_nd == __d2._M_nd; } -#else - { return __d1._M_param == __d2._M_param; } -#endif - - /** - * @brief Inserts a %binomial_distribution random number distribution - * @p __x into the output stream @p __os. - * - * @param __os An output stream. - * @param __x A %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>& __os, - const std::binomial_distribution<_IntType1>& __x); - - /** - * @brief Extracts a %binomial_distribution random number distribution - * @p __x from the input stream @p __is. - * - * @param __is An input stream. - * @param __x A %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>& __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); - - param_type _M_param; - - // NB: Unused when _GLIBCXX_USE_C99_MATH_TR1 is undefined. - 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$p(i|p) = p(1 - p)^{i}@f$ where @f$p@f$ is the parameter of the - * distribution. - */ - template<typename _IntType = int> - class geometric_distribution - { - static_assert(std::is_integral<_IntType>::value, - "template argument not an integral type"); - - public: - /** The type of the range of the distribution. */ - typedef _IntType result_type; - /** Parameter type. */ - struct param_type - { - typedef geometric_distribution<_IntType> distribution_type; - friend class geometric_distribution<_IntType>; - - explicit - param_type(double __p = 0.5) - : _M_p(__p) - { - _GLIBCXX_DEBUG_ASSERT((_M_p > 0.0) && (_M_p < 1.0)); - _M_initialize(); - } - - double - 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() - { _M_log_1_p = std::log(1.0 - _M_p); } - - double _M_p; - - double _M_log_1_p; - }; - - // constructors and member function - explicit - geometric_distribution(double __p = 0.5) - : _M_param(__p) - { } - - explicit - geometric_distribution(const param_type& __p) - : _M_param(__p) - { } - - /** - * @brief Resets the distribution state. - * - * Does nothing for the geometric distribution. - */ - void - reset() { } - - /** - * @brief Returns the distribution parameter @p p. - */ - double - p() const - { return _M_param.p(); } - - /** - * @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 greatest lower bound value of the distribution. - */ - result_type - min() const - { return 0; } - - /** - * @brief Returns the least upper bound value of the distribution. - */ - result_type - max() const - { return std::numeric_limits<result_type>::max(); } - - /** - * @brief Generating functions. - */ - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng) - { 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 - * 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. - * - * @param __os An output stream. - * @param __x A %geometric_distribution random number distribution. - * - * @returns The output stream with the state of @p __x inserted or in - * an error state. - */ - template<typename _IntType, - typename _CharT, typename _Traits> - std::basic_ostream<_CharT, _Traits>& - operator<<(std::basic_ostream<_CharT, _Traits>& __os, - const std::geometric_distribution<_IntType>& __x); - - /** - * @brief Extracts a %geometric_distribution random number distribution - * @p __x from the input stream @p __is. - * - * @param __is An input stream. - * @param __x A %geometric_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>& __is, - std::geometric_distribution<_IntType>& __x); - - - /** - * @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. - */ - template<typename _IntType = int> - class negative_binomial_distribution - { - static_assert(std::is_integral<_IntType>::value, - "template argument not an integral type"); - - public: - /** The type of the range of the distribution. */ - typedef _IntType result_type; - /** Parameter type. */ - struct param_type - { - typedef negative_binomial_distribution<_IntType> distribution_type; - - 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 - { return _M_k; } - - double - 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; - }; - - explicit - negative_binomial_distribution(_IntType __k = 1, double __p = 0.5) - : _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(), (1.0 - __p.p()) / __p.p()) - { } - - /** - * @brief Resets the distribution state. - */ - void - reset() - { _M_gd.reset(); } - - /** - * @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. - */ - double - p() const - { return _M_param.p(); } - - /** - * @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 greatest lower bound value of the distribution. - */ - result_type - min() const - { return result_type(0); } - - /** - * @brief Returns the least upper bound value of the distribution. - */ - result_type - max() const - { return std::numeric_limits<result_type>::max(); } - - /** - * @brief Generating functions. - */ - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng); - - 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_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. - */ - 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 - * 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>& __os, - const std::negative_binomial_distribution<_IntType1>& __x); - - /** - * @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>& __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; - }; - - /** - * @brief Return true if two negative binomial distributions are different. - */ - template<typename _IntType> - inline bool - operator!=(const std::negative_binomial_distribution<_IntType>& __d1, - const std::negative_binomial_distribution<_IntType>& __d2) - { return !(__d1 == __d2); } - - - /* @} */ // group random_distributions_bernoulli - - /** - * @addtogroup random_distributions_poisson Poisson Distributions - * @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 - * parameter of the distribution. - */ - template<typename _IntType = int> - class poisson_distribution - { - static_assert(std::is_integral<_IntType>::value, - "template argument not an integral type"); - - public: - /** The type of the range of the distribution. */ - typedef _IntType result_type; - /** Parameter type. */ - struct param_type - { - typedef poisson_distribution<_IntType> distribution_type; - friend class poisson_distribution<_IntType>; - - explicit - param_type(double __mean = 1.0) - : _M_mean(__mean) - { - _GLIBCXX_DEBUG_ASSERT(_M_mean > 0.0); - _M_initialize(); - } - - double - 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 - _M_initialize(); - - double _M_mean; - - double _M_lm_thr; -#if _GLIBCXX_USE_C99_MATH_TR1 - double _M_lfm, _M_sm, _M_d, _M_scx, _M_1cx, _M_c2b, _M_cb; -#endif - }; - - // constructors and member function - explicit - poisson_distribution(double __mean = 1.0) - : _M_param(__mean), _M_nd() - { } - - explicit - poisson_distribution(const param_type& __p) - : _M_param(__p), _M_nd() - { } - - /** - * @brief Resets the distribution state. - */ - void - reset() - { _M_nd.reset(); } - - /** - * @brief Returns the distribution parameter @p mean. - */ - double - mean() const - { return _M_param.mean(); } - - /** - * @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 greatest lower bound value of the distribution. - */ - result_type - min() const - { return 0; } - - /** - * @brief Returns the least upper bound value of the distribution. - */ - result_type - max() const - { return std::numeric_limits<result_type>::max(); } - - /** - * @brief Generating functions. - */ - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng) - { 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. - */ - friend bool - operator==(const poisson_distribution& __d1, - const poisson_distribution& __d2) -#ifdef _GLIBCXX_USE_C99_MATH_TR1 - { return __d1._M_param == __d2._M_param && __d1._M_nd == __d2._M_nd; } -#else - { return __d1._M_param == __d2._M_param; } -#endif - - /** - * @brief Inserts a %poisson_distribution random number distribution - * @p __x into the output stream @p __os. - * - * @param __os An output stream. - * @param __x A %poisson_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>& __os, - const std::poisson_distribution<_IntType1>& __x); - - /** - * @brief Extracts a %poisson_distribution random number distribution - * @p __x from the input stream @p __is. - * - * @param __is An input stream. - * @param __x A %poisson_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>& __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. - std::normal_distribution<double> _M_nd; - }; - - /** - * @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$p(x|\lambda) = \lambda e^{-\lambda x}@f$. - * - * <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>Range</td><td>@f$[0, \infty]@f$</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; - /** Parameter type. */ - struct param_type - { - typedef exponential_distribution<_RealType> distribution_type; - - explicit - param_type(_RealType __lambda = _RealType(1)) - : _M_lambda(__lambda) - { - _GLIBCXX_DEBUG_ASSERT(_M_lambda > _RealType(0)); - } - - _RealType - 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$\lambda@f$. - */ - explicit - exponential_distribution(const result_type& __lambda = result_type(1)) - : _M_param(__lambda) - { } - - explicit - exponential_distribution(const param_type& __p) - : _M_param(__p) - { } - - /** - * @brief Resets the distribution state. - * - * Has no effect on exponential distributions. - */ - void - reset() { } - - /** - * @brief Returns the inverse scale parameter of the distribution. - */ - _RealType - lambda() const - { return _M_param.lambda(); } - - /** - * @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 greatest lower bound value of the distribution. - */ - result_type - min() const - { return result_type(0); } - - /** - * @brief Returns the least upper bound value of the distribution. - */ - result_type - max() const - { return std::numeric_limits<result_type>::max(); } - - /** - * @brief Generating functions. - */ - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng) - { return this->operator()(__urng, _M_param); } - - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng, - const param_type& __p) - { - __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> - __aurng(__urng); - 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 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. - * - * @param __os An output stream. - * @param __x A %exponential_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>& __os, - const std::exponential_distribution<_RealType>& __x); - - /** - * @brief Extracts a %exponential_distribution random number distribution - * @p __x from the input stream @p __is. - * - * @param __is An input stream. - * @param __x A %exponential_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>& __is, - std::exponential_distribution<_RealType>& __x); - - - /** - * @brief A weibull_distribution random number distribution. - * - * 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; - /** Parameter type. */ - struct param_type - { - typedef weibull_distribution<_RealType> distribution_type; - - explicit - param_type(_RealType __a = _RealType(1), - _RealType __b = _RealType(1)) - : _M_a(__a), _M_b(__b) - { } - - _RealType - a() const - { return _M_a; } - - _RealType - 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; - }; - - explicit - weibull_distribution(_RealType __a = _RealType(1), - _RealType __b = _RealType(1)) - : _M_param(__a, __b) - { } - - explicit - weibull_distribution(const param_type& __p) - : _M_param(__p) - { } - - /** - * @brief Resets the distribution state. - */ - void - reset() - { } - - /** - * @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. - */ - _RealType - b() const - { 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 greatest lower bound value of the distribution. - */ - result_type - min() const - { return result_type(0); } - - /** - * @brief Returns the least upper bound value of the distribution. - */ - result_type - max() const - { return std::numeric_limits<result_type>::max(); } - - /** - * @brief Generating functions. - */ - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng) - { 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 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. - * - * @param __os An output stream. - * @param __x A %weibull_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>& __os, - const std::weibull_distribution<_RealType>& __x); - - /** - * @brief Extracts a %weibull_distribution random number distribution - * @p __x from the input stream @p __is. - * - * @param __is An input stream. - * @param __x A %weibull_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>& __is, - std::weibull_distribution<_RealType>& __x); - - - /** - * @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] - */ - 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; - /** Parameter type. */ - struct param_type - { - typedef extreme_value_distribution<_RealType> distribution_type; - - explicit - param_type(_RealType __a = _RealType(0), - _RealType __b = _RealType(1)) - : _M_a(__a), _M_b(__b) - { } - - _RealType - a() const - { return _M_a; } - - _RealType - 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; - }; - - explicit - extreme_value_distribution(_RealType __a = _RealType(0), - _RealType __b = _RealType(1)) - : _M_param(__a, __b) - { } - - explicit - extreme_value_distribution(const param_type& __p) - : _M_param(__p) - { } - - /** - * @brief Resets the distribution state. - */ - void - reset() - { } - - /** - * @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. - */ - _RealType - b() const - { 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 greatest lower bound value of the distribution. - */ - result_type - min() const - { return std::numeric_limits<result_type>::min(); } - - /** - * @brief Returns the least upper bound value of the distribution. - */ - result_type - max() const - { return std::numeric_limits<result_type>::max(); } - - /** - * @brief Generating functions. - */ - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng) - { 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 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. - * - * @param __os An output stream. - * @param __x A %extreme_value_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>& __os, - const std::extreme_value_distribution<_RealType>& __x); - - /** - * @brief Extracts a %extreme_value_distribution random number - * distribution @p __x from the input stream @p __is. - * - * @param __is An input stream. - * @param __x A %extreme_value_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>& __is, - std::extreme_value_distribution<_RealType>& __x); - - - /** - * @brief A discrete_distribution random number distribution. - * - * The formula for the discrete probability mass function is - * - */ - template<typename _IntType = int> - class discrete_distribution - { - static_assert(std::is_integral<_IntType>::value, - "template argument not an integral type"); - - public: - /** The type of the range of the distribution. */ - typedef _IntType result_type; - /** Parameter type. */ - struct param_type - { - typedef discrete_distribution<_IntType> distribution_type; - friend class discrete_distribution<_IntType>; - - param_type() - : _M_prob(), _M_cp() - { } - - template<typename _InputIterator> - param_type(_InputIterator __wbegin, - _InputIterator __wend) - : _M_prob(__wbegin, __wend), _M_cp() - { _M_initialize(); } - - param_type(initializer_list<double> __wil) - : _M_prob(__wil.begin(), __wil.end()), _M_cp() - { _M_initialize(); } - - template<typename _Func> - param_type(size_t __nw, double __xmin, double __xmax, - _Func __fw); - - // See: http://cpp-next.com/archive/2010/10/implicit-move-must-go/ - param_type(const param_type&) = default; - param_type& operator=(const param_type&) = default; - - std::vector<double> - probabilities() const - { return _M_prob.empty() ? std::vector<double>(1, 1.0) : _M_prob; } - - friend bool - operator==(const param_type& __p1, const param_type& __p2) - { return __p1._M_prob == __p2._M_prob; } - - private: - void - _M_initialize(); - - std::vector<double> _M_prob; - std::vector<double> _M_cp; - }; - - discrete_distribution() - : _M_param() - { } - - template<typename _InputIterator> - discrete_distribution(_InputIterator __wbegin, - _InputIterator __wend) - : _M_param(__wbegin, __wend) - { } - - discrete_distribution(initializer_list<double> __wl) - : _M_param(__wl) - { } - - template<typename _Func> - discrete_distribution(size_t __nw, double __xmin, double __xmax, - _Func __fw) - : _M_param(__nw, __xmin, __xmax, __fw) - { } - - explicit - discrete_distribution(const param_type& __p) - : _M_param(__p) - { } - - /** - * @brief Resets the distribution state. - */ - void - reset() - { } - - /** - * @brief Returns the probabilities of the distribution. - */ - std::vector<double> - probabilities() const - { - return _M_param._M_prob.empty() - ? std::vector<double>(1, 1.0) : _M_param._M_prob; - } - - /** - * @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 greatest lower bound value of the distribution. - */ - result_type - min() const - { return result_type(0); } - - /** - * @brief Returns the least upper bound value of the distribution. - */ - result_type - max() const - { - 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, _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. - * - * @param __os An output stream. - * @param __x A %discrete_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>& __os, - const std::discrete_distribution<_IntType1>& __x); - - /** - * @brief Extracts a %discrete_distribution random number distribution - * @p __x from the input stream @p __is. - * - * @param __is An input stream. - * @param __x A %discrete_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>& __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 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. - * - * The formula for the piecewise constant probability mass function is - * - */ - 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; - /** Parameter type. */ - struct param_type - { - typedef piecewise_constant_distribution<_RealType> distribution_type; - friend class piecewise_constant_distribution<_RealType>; - - param_type() - : _M_int(), _M_den(), _M_cp() - { } - - template<typename _InputIteratorB, typename _InputIteratorW> - param_type(_InputIteratorB __bfirst, - _InputIteratorB __bend, - _InputIteratorW __wbegin); - - template<typename _Func> - param_type(initializer_list<_RealType> __bi, _Func __fw); - - template<typename _Func> - param_type(size_t __nw, _RealType __xmin, _RealType __xmax, - _Func __fw); - - // See: http://cpp-next.com/archive/2010/10/implicit-move-must-go/ - param_type(const param_type&) = default; - param_type& operator=(const param_type&) = default; - - std::vector<_RealType> - intervals() const - { - 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.empty() ? std::vector<double>(1, 1.0) : _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(); - - std::vector<_RealType> _M_int; - std::vector<double> _M_den; - std::vector<double> _M_cp; - }; - - explicit - piecewise_constant_distribution() - : _M_param() - { } - - template<typename _InputIteratorB, typename _InputIteratorW> - piecewise_constant_distribution(_InputIteratorB __bfirst, - _InputIteratorB __bend, - _InputIteratorW __wbegin) - : _M_param(__bfirst, __bend, __wbegin) - { } - - template<typename _Func> - piecewise_constant_distribution(initializer_list<_RealType> __bl, - _Func __fw) - : _M_param(__bl, __fw) - { } - - template<typename _Func> - piecewise_constant_distribution(size_t __nw, - _RealType __xmin, _RealType __xmax, - _Func __fw) - : _M_param(__nw, __xmin, __xmax, __fw) - { } - - explicit - piecewise_constant_distribution(const param_type& __p) - : _M_param(__p) - { } - - /** - * @brief Resets the distribution state. - */ - void - reset() - { } - - /** - * @brief Returns a vector of the intervals. - */ - std::vector<_RealType> - intervals() const - { - 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._M_den.empty() - ? std::vector<double>(1, 1.0) : _M_param._M_den; - } - - /** - * @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 greatest lower bound value of the distribution. - */ - result_type - min() const - { - 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 _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, _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 - * number distribution @p __x into the output stream @p __os. - * - * @param __os An output stream. - * @param __x A %piecewise_constan_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>& __os, - const std::piecewise_constant_distribution<_RealType1>& __x); - - /** - * @brief Extracts a %piecewise_constan_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 - * 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>& __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 - * 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. - * - * The formula for the piecewise linear probability mass function is - * - */ - 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; - /** Parameter type. */ - struct param_type - { - typedef piecewise_linear_distribution<_RealType> distribution_type; - friend class piecewise_linear_distribution<_RealType>; - - param_type() - : _M_int(), _M_den(), _M_cp(), _M_m() - { } - - template<typename _InputIteratorB, typename _InputIteratorW> - param_type(_InputIteratorB __bfirst, - _InputIteratorB __bend, - _InputIteratorW __wbegin); - - template<typename _Func> - param_type(initializer_list<_RealType> __bl, _Func __fw); - - template<typename _Func> - param_type(size_t __nw, _RealType __xmin, _RealType __xmax, - _Func __fw); - - // See: http://cpp-next.com/archive/2010/10/implicit-move-must-go/ - param_type(const param_type&) = default; - param_type& operator=(const param_type&) = default; - - std::vector<_RealType> - intervals() const - { - 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.empty() ? std::vector<double>(2, 1.0) : _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(); - - std::vector<_RealType> _M_int; - std::vector<double> _M_den; - std::vector<double> _M_cp; - std::vector<double> _M_m; - }; - - explicit - piecewise_linear_distribution() - : _M_param() - { } - - template<typename _InputIteratorB, typename _InputIteratorW> - piecewise_linear_distribution(_InputIteratorB __bfirst, - _InputIteratorB __bend, - _InputIteratorW __wbegin) - : _M_param(__bfirst, __bend, __wbegin) - { } - - template<typename _Func> - piecewise_linear_distribution(initializer_list<_RealType> __bl, - _Func __fw) - : _M_param(__bl, __fw) - { } - - template<typename _Func> - piecewise_linear_distribution(size_t __nw, - _RealType __xmin, _RealType __xmax, - _Func __fw) - : _M_param(__nw, __xmin, __xmax, __fw) - { } - - explicit - piecewise_linear_distribution(const param_type& __p) - : _M_param(__p) - { } - - /** - * Resets the distribution state. - */ - void - reset() - { } - - /** - * @brief Return the intervals of the distribution. - */ - std::vector<_RealType> - intervals() const - { - 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 - * distribution. - */ - std::vector<double> - densities() const - { - return _M_param._M_den.empty() - ? std::vector<double>(2, 1.0) : _M_param._M_den; - } - - /** - * @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 greatest lower bound value of the distribution. - */ - result_type - min() const - { - 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 _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, _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. - * - * @param __os An output stream. - * @param __x A %piecewise_linear_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>& __os, - const std::piecewise_linear_distribution<_RealType1>& __x); - - /** - * @brief Extracts a %piecewise_linear_distribution random number - * distribution @p __x from the input stream @p __is. - * - * @param __is An input stream. - * @param __x A %piecewise_linear_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>& __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 - * 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 random_distributions_poisson - - /* @} */ // group random_distributions - - /** - * @addtogroup random_utilities Random Number Utilities - * @ingroup random - * @{ - */ - - /** - * @brief The seed_seq class generates sequences of seeds for random - * number generators. - */ - class seed_seq - { - - public: - /** The type of the seed vales. */ - typedef uint_least32_t result_type; - - /** Default constructor. */ - seed_seq() - : _M_v() - { } - - template<typename _IntType> - seed_seq(std::initializer_list<_IntType> il); - - template<typename _InputIterator> - seed_seq(_InputIterator __begin, _InputIterator __end); - - // generating functions - template<typename _RandomAccessIterator> - void - generate(_RandomAccessIterator __begin, _RandomAccessIterator __end); - - // property functions - size_t size() const - { return _M_v.size(); } - - template<typename OutputIterator> - void - param(OutputIterator __dest) const - { std::copy(_M_v.begin(), _M_v.end(), __dest); } - - private: - /// - std::vector<result_type> _M_v; - }; - - /* @} */ // group random_utilities - - /* @} */ // group random - -_GLIBCXX_END_NAMESPACE_VERSION -} // namespace std - -#endif |