X-Git-Url: http://wagnertech.de/git?a=blobdiff_plain;f=i686-linux-gnu-4.7%2Fusr%2Finclude%2Fc%2B%2B%2F4.7%2Fbits%2Frandom.h;fp=i686-linux-gnu-4.7%2Fusr%2Finclude%2Fc%2B%2B%2F4.7%2Fbits%2Frandom.h;h=1e8caa023b37c3ed686bd6a4d28453c564007198;hb=94df942c2c7bd3457276fe5b7367623cbb8c1302;hp=0000000000000000000000000000000000000000;hpb=4dd7d9155a920895ff7b1cb6b9c9c676aa62000a;p=cross.git diff --git a/i686-linux-gnu-4.7/usr/include/c++/4.7/bits/random.h b/i686-linux-gnu-4.7/usr/include/c++/4.7/bits/random.h new file mode 100644 index 0000000..1e8caa0 --- /dev/null +++ b/i686-linux-gnu-4.7/usr/include/c++/4.7/bits/random.h @@ -0,0 +1,5390 @@ +// random number generation -*- C++ -*- + +// Copyright (C) 2009-2012 Free Software Foundation, Inc. +// +// This file is part of the GNU ISO C++ Library. This library is free +// software; you can redistribute it and/or modify it under the +// 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 +// . + +/** + * @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 + +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 + _RealType + generate_canonical(_UniformRandomNumberGenerator& __g); + +_GLIBCXX_END_NAMESPACE_VERSION + + /* + * Implementation-space details. + */ + namespace __detail + { + _GLIBCXX_BEGIN_NAMESPACE_VERSION + + template + (std::numeric_limits<_UIntType>::digits)> + struct _Shift + { static const _UIntType __value = 0; }; + + template + struct _Shift<_UIntType, __w, true> + { static const _UIntType __value = _UIntType(1) << __w; }; + + template + struct _Mod; + + // Dispatch based on modulus value to prevent divide-by-zero compile-time + // errors when m == 0. + template + inline _Tp + __mod(_Tp __x) + { return _Mod<_Tp, __m, __a, __c, __m == 0>::__calc(__x); } + + /* + * An adaptor class for converting the output of any Generator into + * the input for a specific Distribution. + */ + template + 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. + * + *
Random Number Generator Requirements
To be documented.
+ * + * @{ + */ + + /** + * @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 + 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"); + + // XXX FIXME: + // _Mod::__calc should handle correctly __m % __a >= __m / __a too. + static_assert(__m % __a < __m / __a, + "sorry, not implemented yet: try a smaller 'a' constant"); + + 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::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 std::enable_if::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 + 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 + 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 + 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 + 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::value> + ::type> + explicit + mersenne_twister_engine(_Sseq& __q) + { seed(__q); } + + void + seed(result_type __sd = default_seed); + + template + typename std::enable_if::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) + { + for (; __z != 0ULL; --__z) + (*this)(); + } + + 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 + 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 + 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: + _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 + 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 + 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::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 std::enable_if::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 + 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 + 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 + 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 + 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::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 + 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 + 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 + 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 + 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 + 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::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 + 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 + 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 + 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 + 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 + 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::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 + 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 + 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 + 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 + 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 + minstd_rand0; + + /** + * An alternative LCR (Lehmer Generator function). + */ + typedef linear_congruential_engine + 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 + ranlux24_base; + + typedef subtract_with_carry_engine + ranlux48_base; + + typedef discard_block_engine ranlux24; + + typedef discard_block_engine ranlux48; + + typedef shuffle_order_engine 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 = "/dev/urandom") + { + if ((__token != "/dev/urandom" && __token != "/dev/random") + || !(_M_file = std::fopen(__token.c_str(), "rb"))) + std::__throw_runtime_error(__N("random_device::" + "random_device(const std::string&)")); + } + + ~random_device() + { std::fclose(_M_file); } + +#else + + explicit + random_device(const std::string& __token = "mt19937") + : _M_mt(_M_strtoul(__token)) { } + + private: + static unsigned long + _M_strtoul(const std::string& __str) + { + unsigned long __ret = 5489UL; + if (__str != "mt19937") + { + const char* __nptr = __str.c_str(); + char* __endptr; + __ret = std::strtoul(__nptr, &__endptr, 0); + if (*__nptr == '\0' || *__endptr != '\0') + std::__throw_runtime_error(__N("random_device::_M_strtoul" + "(const std::string&)")); + } + return __ret; + } + + public: + +#endif + + static constexpr result_type + min() + { return std::numeric_limits::min(); } + + static constexpr result_type + max() + { return std::numeric_limits::max(); } + + double + entropy() const noexcept + { return 0.0; } + + result_type + operator()() + { +#ifdef _GLIBCXX_USE_RANDOM_TR1 + result_type __ret; + std::fread(reinterpret_cast(&__ret), sizeof(result_type), + 1, _M_file); + return __ret; +#else + return _M_mt(); +#endif + } + + // No copy functions. + random_device(const random_device&) = delete; + void operator=(const random_device&) = delete; + + private: + +#ifdef _GLIBCXX_USE_RANDOM_TR1 + FILE* _M_file; +#else + mt19937 _M_mt; +#endif + }; + + /* @} */ // 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 + 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 + result_type + operator()(_UniformRandomNumberGenerator& __urng) + { return this->operator()(__urng, _M_param); } + + template + result_type + operator()(_UniformRandomNumberGenerator& __urng, + const param_type& __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: + param_type _M_param; + }; + + /** + * @brief Return true if two uniform integer distributions have + * different parameters. + */ + template + 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 + 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 + 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 + 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 + result_type + operator()(_UniformRandomNumberGenerator& __urng) + { return this->operator()(__urng, _M_param); } + + template + result_type + operator()(_UniformRandomNumberGenerator& __urng, + const param_type& __p) + { + __detail::_Adaptor<_UniformRandomNumberGenerator, result_type> + __aurng(__urng); + return (__aurng() * (__p.b() - __p.a())) + __p.a(); + } + + /** + * @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: + param_type _M_param; + }; + + /** + * @brief Return true if two uniform real distributions have + * different parameters. + */ + template + 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 + 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 + 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 + 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::min(); } + + /** + * @brief Returns the least upper bound value of the distribution. + */ + result_type + max() const + { return std::numeric_limits::max(); } + + /** + * @brief Generating functions. + */ + template + result_type + operator()(_UniformRandomNumberGenerator& __urng) + { return this->operator()(__urng, _M_param); } + + template + result_type + operator()(_UniformRandomNumberGenerator& __urng, + const param_type& __p); + + /** + * @brief Return true if two normal distributions have + * the same parameters and the sequences that would + * be generated are equal. + */ + template + 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 + 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 + friend std::basic_istream<_CharT, _Traits>& + operator>>(std::basic_istream<_CharT, _Traits>& __is, + std::normal_distribution<_RealType1>& __x); + + private: + param_type _M_param; + result_type _M_saved; + bool _M_saved_available; + }; + + /** + * @brief Return true if two normal distributions are different. + */ + template + 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 + 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::max(); } + + /** + * @brief Generating functions. + */ + template + result_type + operator()(_UniformRandomNumberGenerator& __urng) + { return this->operator()(__urng, _M_param); } + + template + result_type + operator()(_UniformRandomNumberGenerator& __urng, + const param_type& __p) + { return std::exp(__p.s() * _M_nd(__urng) + __p.m()); } + + /** + * @brief Return true if two lognormal distributions have + * the same parameters and the sequences that would + * be generated are equal. + */ + 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 + 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 + friend std::basic_istream<_CharT, _Traits>& + operator>>(std::basic_istream<_CharT, _Traits>& __is, + std::lognormal_distribution<_RealType1>& __x); + + private: + param_type _M_param; + + std::normal_distribution _M_nd; + }; + + /** + * @brief Return true if two lognormal distributions are different. + */ + template + 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 + 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::max(); } + + /** + * @brief Generating functions. + */ + template + result_type + operator()(_UniformRandomNumberGenerator& __urng) + { return this->operator()(__urng, _M_param); } + + template + result_type + operator()(_UniformRandomNumberGenerator& __urng, + const param_type& __p); + + /** + * @brief Return true if two gamma distributions have the same + * parameters and the sequences that would be generated + * are equal. + */ + 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 + 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 + friend std::basic_istream<_CharT, _Traits>& + operator>>(std::basic_istream<_CharT, _Traits>& __is, + std::gamma_distribution<_RealType1>& __x); + + private: + param_type _M_param; + + std::normal_distribution _M_nd; + }; + + /** + * @brief Return true if two gamma distributions are different. + */ + template + 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 + 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::max(); } + + /** + * @brief Generating functions. + */ + template + result_type + operator()(_UniformRandomNumberGenerator& __urng) + { return 2 * _M_gd(__urng); } + + template + result_type + operator()(_UniformRandomNumberGenerator& __urng, + const param_type& __p) + { + typedef typename std::gamma_distribution::param_type + param_type; + return 2 * _M_gd(__urng, param_type(__p.n() / 2)); + } + + /** + * @brief Return true if two Chi-squared distributions have + * the same parameters and the sequences that would be + * generated are equal. + */ + 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 + 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 + friend std::basic_istream<_CharT, _Traits>& + operator>>(std::basic_istream<_CharT, _Traits>& __is, + std::chi_squared_distribution<_RealType1>& __x); + + private: + param_type _M_param; + + std::gamma_distribution _M_gd; + }; + + /** + * @brief Return true if two Chi-squared distributions are different. + */ + template + 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 + 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::min(); } + + /** + * @brief Returns the least upper bound value of the distribution. + */ + result_type + max() const + { return std::numeric_limits::max(); } + + /** + * @brief Generating functions. + */ + template + result_type + operator()(_UniformRandomNumberGenerator& __urng) + { return this->operator()(__urng, _M_param); } + + template + result_type + operator()(_UniformRandomNumberGenerator& __urng, + const param_type& __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: + param_type _M_param; + }; + + /** + * @brief Return true if two Cauchy distributions have + * different parameters. + */ + template + 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 + 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 + 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 + 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::max(); } + + /** + * @brief Generating functions. + */ + template + result_type + operator()(_UniformRandomNumberGenerator& __urng) + { return (_M_gd_x(__urng) * n()) / (_M_gd_y(__urng) * m()); } + + template + result_type + operator()(_UniformRandomNumberGenerator& __urng, + const param_type& __p) + { + typedef typename std::gamma_distribution::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())); + } + + /** + * @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 + 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 + friend std::basic_istream<_CharT, _Traits>& + operator>>(std::basic_istream<_CharT, _Traits>& __is, + std::fisher_f_distribution<_RealType1>& __x); + + private: + param_type _M_param; + + std::gamma_distribution _M_gd_x, _M_gd_y; + }; + + /** + * @brief Return true if two Fisher f distributions are diferent. + */ + template + 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 + 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::min(); } + + /** + * @brief Returns the least upper bound value of the distribution. + */ + result_type + max() const + { return std::numeric_limits::max(); } + + /** + * @brief Generating functions. + */ + template + result_type + operator()(_UniformRandomNumberGenerator& __urng) + { return _M_nd(__urng) * std::sqrt(n() / _M_gd(__urng)); } + + template + result_type + operator()(_UniformRandomNumberGenerator& __urng, + const param_type& __p) + { + typedef typename std::gamma_distribution::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); + } + + /** + * @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 + 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 + friend std::basic_istream<_CharT, _Traits>& + operator>>(std::basic_istream<_CharT, _Traits>& __is, + std::student_t_distribution<_RealType1>& __x); + + private: + param_type _M_param; + + std::normal_distribution _M_nd; + std::gamma_distribution _M_gd; + }; + + /** + * @brief Return true if two Student t distributions are different. + */ + template + 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::min(); } + + /** + * @brief Returns the least upper bound value of the distribution. + */ + result_type + max() const + { return std::numeric_limits::max(); } + + /** + * @brief Generating functions. + */ + template + result_type + operator()(_UniformRandomNumberGenerator& __urng) + { return this->operator()(__urng, _M_param); } + + template + 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; + } + + /** + * @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: + 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 + 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 + 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$p(i|t,p) = \binom{n}{i} p^i (1 - p)^{t - i}@f$ where @f$t@f$ + * and @f$p@f$ are the parameters of the distribution. + */ + template + 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 + result_type + operator()(_UniformRandomNumberGenerator& __urng) + { return this->operator()(__urng, _M_param); } + + template + result_type + operator()(_UniformRandomNumberGenerator& __urng, + const param_type& __p); + + /** + * @brief Return true if two binomial distributions have + * the same parameters and the sequences that would + * be generated are equal. + */ + 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 + 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 + friend std::basic_istream<_CharT, _Traits>& + operator>>(std::basic_istream<_CharT, _Traits>& __is, + std::binomial_distribution<_IntType1>& __x); + + private: + template + 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 _M_nd; + }; + + /** + * @brief Return true if two binomial distributions are different. + */ + template + 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 + 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::max(); } + + /** + * @brief Generating functions. + */ + template + result_type + operator()(_UniformRandomNumberGenerator& __urng) + { return this->operator()(__urng, _M_param); } + + template + result_type + operator()(_UniformRandomNumberGenerator& __urng, + const param_type& __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: + param_type _M_param; + }; + + /** + * @brief Return true if two geometric distributions have + * different parameters. + */ + template + 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 + 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 + 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 + 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::max(); } + + /** + * @brief Generating functions. + */ + template + result_type + operator()(_UniformRandomNumberGenerator& __urng); + + template + result_type + operator()(_UniformRandomNumberGenerator& __urng, + const param_type& __p); + + /** + * @brief Return true if two negative binomial distributions have + * the same parameters and the sequences that would be + * generated are equal. + */ + 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 + 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 + friend std::basic_istream<_CharT, _Traits>& + operator>>(std::basic_istream<_CharT, _Traits>& __is, + std::negative_binomial_distribution<_IntType1>& __x); + + private: + param_type _M_param; + + std::gamma_distribution _M_gd; + }; + + /** + * @brief Return true if two negative binomial distributions are different. + */ + template + 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 + 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::max(); } + + /** + * @brief Generating functions. + */ + template + result_type + operator()(_UniformRandomNumberGenerator& __urng) + { return this->operator()(__urng, _M_param); } + + template + result_type + operator()(_UniformRandomNumberGenerator& __urng, + const param_type& __p); + + /** + * @brief Return true if two Poisson distributions have the same + * parameters and the sequences that would be generated + * are equal. + */ + 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 + 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 + friend std::basic_istream<_CharT, _Traits>& + operator>>(std::basic_istream<_CharT, _Traits>& __is, + std::poisson_distribution<_IntType1>& __x); + + private: + param_type _M_param; + + // NB: Unused when _GLIBCXX_USE_C99_MATH_TR1 is undefined. + std::normal_distribution _M_nd; + }; + + /** + * @brief Return true if two Poisson distributions are different. + */ + template + 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$p(x|\lambda) = \lambda e^{-\lambda x}@f$. + * + * + * + * + * + * + * + * + *
Distribution Statistics
Mean@f$\frac{1}{\lambda}@f$
Median@f$\frac{\ln 2}{\lambda}@f$
Mode@f$zero@f$
Range@f$[0, \infty]@f$
Standard Deviation@f$\frac{1}{\lambda}@f$
+ */ + template + 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::max(); } + + /** + * @brief Generating functions. + */ + template + result_type + operator()(_UniformRandomNumberGenerator& __urng) + { return this->operator()(__urng, _M_param); } + + template + 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(); + } + + /** + * @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: + param_type _M_param; + }; + + /** + * @brief Return true if two exponential distributions have different + * parameters. + */ + template + 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 + 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 + 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 + 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::max(); } + + /** + * @brief Generating functions. + */ + template + result_type + operator()(_UniformRandomNumberGenerator& __urng) + { return this->operator()(__urng, _M_param); } + + template + result_type + operator()(_UniformRandomNumberGenerator& __urng, + const param_type& __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: + param_type _M_param; + }; + + /** + * @brief Return true if two Weibull distributions have different + * parameters. + */ + template + 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 + 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 + 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 + 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::min(); } + + /** + * @brief Returns the least upper bound value of the distribution. + */ + result_type + max() const + { return std::numeric_limits::max(); } + + /** + * @brief Generating functions. + */ + template + result_type + operator()(_UniformRandomNumberGenerator& __urng) + { return this->operator()(__urng, _M_param); } + + template + result_type + operator()(_UniformRandomNumberGenerator& __urng, + const param_type& __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: + param_type _M_param; + }; + + /** + * @brief Return true if two extreme value distributions have different + * parameters. + */ + template + 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 + 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 + 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 + 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 + param_type(_InputIterator __wbegin, + _InputIterator __wend) + : _M_prob(__wbegin, __wend), _M_cp() + { _M_initialize(); } + + param_type(initializer_list __wil) + : _M_prob(__wil.begin(), __wil.end()), _M_cp() + { _M_initialize(); } + + template + 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 + probabilities() const + { return _M_prob.empty() ? std::vector(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 _M_prob; + std::vector _M_cp; + }; + + discrete_distribution() + : _M_param() + { } + + template + discrete_distribution(_InputIterator __wbegin, + _InputIterator __wend) + : _M_param(__wbegin, __wend) + { } + + discrete_distribution(initializer_list __wl) + : _M_param(__wl) + { } + + template + 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 + probabilities() const + { + return _M_param._M_prob.empty() + ? std::vector(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 + result_type + operator()(_UniformRandomNumberGenerator& __urng) + { return this->operator()(__urng, _M_param); } + + template + result_type + operator()(_UniformRandomNumberGenerator& __urng, + const param_type& __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 + 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 + friend std::basic_istream<_CharT, _Traits>& + operator>>(std::basic_istream<_CharT, _Traits>& __is, + std::discrete_distribution<_IntType1>& __x); + + private: + param_type _M_param; + }; + + /** + * @brief Return true if two discrete distributions have different + * parameters. + */ + template + 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 + 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 + param_type(_InputIteratorB __bfirst, + _InputIteratorB __bend, + _InputIteratorW __wbegin); + + template + param_type(initializer_list<_RealType> __bi, _Func __fw); + + template + 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 + densities() const + { return _M_den.empty() ? std::vector(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 _M_den; + std::vector _M_cp; + }; + + explicit + piecewise_constant_distribution() + : _M_param() + { } + + template + piecewise_constant_distribution(_InputIteratorB __bfirst, + _InputIteratorB __bend, + _InputIteratorW __wbegin) + : _M_param(__bfirst, __bend, __wbegin) + { } + + template + piecewise_constant_distribution(initializer_list<_RealType> __bl, + _Func __fw) + : _M_param(__bl, __fw) + { } + + template + 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 + densities() const + { + return _M_param._M_den.empty() + ? std::vector(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 + result_type + operator()(_UniformRandomNumberGenerator& __urng) + { return this->operator()(__urng, _M_param); } + + template + result_type + operator()(_UniformRandomNumberGenerator& __urng, + const param_type& __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 + 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 + friend std::basic_istream<_CharT, _Traits>& + operator>>(std::basic_istream<_CharT, _Traits>& __is, + std::piecewise_constant_distribution<_RealType1>& __x); + + private: + param_type _M_param; + }; + + /** + * @brief Return true if two piecewise constant distributions have + * different parameters. + */ + template + 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 + 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 + param_type(_InputIteratorB __bfirst, + _InputIteratorB __bend, + _InputIteratorW __wbegin); + + template + param_type(initializer_list<_RealType> __bl, _Func __fw); + + template + 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 + densities() const + { return _M_den.empty() ? std::vector(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 _M_den; + std::vector _M_cp; + std::vector _M_m; + }; + + explicit + piecewise_linear_distribution() + : _M_param() + { } + + template + piecewise_linear_distribution(_InputIteratorB __bfirst, + _InputIteratorB __bend, + _InputIteratorW __wbegin) + : _M_param(__bfirst, __bend, __wbegin) + { } + + template + piecewise_linear_distribution(initializer_list<_RealType> __bl, + _Func __fw) + : _M_param(__bl, __fw) + { } + + template + 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 + densities() const + { + return _M_param._M_den.empty() + ? std::vector(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 + result_type + operator()(_UniformRandomNumberGenerator& __urng) + { return this->operator()(__urng, _M_param); } + + template + result_type + operator()(_UniformRandomNumberGenerator& __urng, + const param_type& __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 + 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 + friend std::basic_istream<_CharT, _Traits>& + operator>>(std::basic_istream<_CharT, _Traits>& __is, + std::piecewise_linear_distribution<_RealType1>& __x); + + private: + param_type _M_param; + }; + + /** + * @brief Return true if two piecewise linear distributions have + * different parameters. + */ + template + 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 + seed_seq(std::initializer_list<_IntType> il); + + template + seed_seq(_InputIterator __begin, _InputIterator __end); + + // generating functions + template + void + generate(_RandomAccessIterator __begin, _RandomAccessIterator __end); + + // property functions + size_t size() const + { return _M_v.size(); } + + template + void + param(OutputIterator __dest) const + { std::copy(_M_v.begin(), _M_v.end(), __dest); } + + private: + /// + std::vector _M_v; + }; + + /* @} */ // group random_utilities + + /* @} */ // group random + +_GLIBCXX_END_NAMESPACE_VERSION +} // namespace std + +#endif