diff options
Diffstat (limited to 'gcc-4.8.1/libstdc++-v3/include/ext/random')
| -rw-r--r-- | gcc-4.8.1/libstdc++-v3/include/ext/random | 2858 |
1 files changed, 0 insertions, 2858 deletions
diff --git a/gcc-4.8.1/libstdc++-v3/include/ext/random b/gcc-4.8.1/libstdc++-v3/include/ext/random deleted file mode 100644 index 7af313008..000000000 --- a/gcc-4.8.1/libstdc++-v3/include/ext/random +++ /dev/null @@ -1,2858 +0,0 @@ -// Random number extensions -*- C++ -*- - -// Copyright (C) 2012-2013 Free Software Foundation, Inc. -// -// This file is part of the GNU ISO C++ Library. This library is free -// software; you can redistribute it and/or modify it under the -// terms of the GNU General Public License as published by the -// Free Software Foundation; either version 3, or (at your option) -// any later version. - -// This library is distributed in the hope that it will be useful, -// but WITHOUT ANY WARRANTY; without even the implied warranty of -// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the -// GNU General Public License for more details. - -// Under Section 7 of GPL version 3, you are granted additional -// permissions described in the GCC Runtime Library Exception, version -// 3.1, as published by the Free Software Foundation. - -// You should have received a copy of the GNU General Public License and -// a copy of the GCC Runtime Library Exception along with this program; -// see the files COPYING3 and COPYING.RUNTIME respectively. If not, see -// <http://www.gnu.org/licenses/>. - -/** @file ext/random - * This file is a GNU extension to the Standard C++ Library. - */ - -#ifndef _EXT_RANDOM -#define _EXT_RANDOM 1 - -#pragma GCC system_header - -#if __cplusplus < 201103L -# include <bits/c++0x_warning.h> -#else - -#include <random> -#include <array> -#include <ext/cmath> -#ifdef __SSE2__ -# include <x86intrin.h> -#endif - -#ifdef _GLIBCXX_USE_C99_STDINT_TR1 - -namespace __gnu_cxx _GLIBCXX_VISIBILITY(default) -{ -_GLIBCXX_BEGIN_NAMESPACE_VERSION - -#if __BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__ - - /* Mersenne twister implementation optimized for vector operations. - * - * Reference: http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/SFMT/ - */ - template<typename _UIntType, size_t __m, - size_t __pos1, size_t __sl1, size_t __sl2, - size_t __sr1, size_t __sr2, - uint32_t __msk1, uint32_t __msk2, - uint32_t __msk3, uint32_t __msk4, - uint32_t __parity1, uint32_t __parity2, - uint32_t __parity3, uint32_t __parity4> - class simd_fast_mersenne_twister_engine - { - static_assert(std::is_unsigned<_UIntType>::value, "template argument " - "substituting _UIntType not an unsigned integral type"); - static_assert(__sr1 < 32, "first right shift too large"); - static_assert(__sr2 < 16, "second right shift too large"); - static_assert(__sl1 < 32, "first left shift too large"); - static_assert(__sl2 < 16, "second left shift too large"); - - public: - typedef _UIntType result_type; - - private: - static constexpr size_t m_w = sizeof(result_type) * 8; - static constexpr size_t _M_nstate = __m / 128 + 1; - static constexpr size_t _M_nstate32 = _M_nstate * 4; - - static_assert(std::is_unsigned<_UIntType>::value, "template argument " - "substituting _UIntType not an unsigned integral type"); - static_assert(__pos1 < _M_nstate, "POS1 not smaller than state size"); - static_assert(16 % sizeof(_UIntType) == 0, - "UIntType size must divide 16"); - - public: - static constexpr size_t state_size = _M_nstate * (16 - / sizeof(result_type)); - static constexpr result_type default_seed = 5489u; - - // constructors and member function - explicit - simd_fast_mersenne_twister_engine(result_type __sd = default_seed) - { seed(__sd); } - - template<typename _Sseq, typename = typename - std::enable_if<!std::is_same<_Sseq, - simd_fast_mersenne_twister_engine>::value> - ::type> - explicit - simd_fast_mersenne_twister_engine(_Sseq& __q) - { seed(__q); } - - void - seed(result_type __sd = default_seed); - - template<typename _Sseq> - typename std::enable_if<std::is_class<_Sseq>::value>::type - seed(_Sseq& __q); - - static constexpr result_type - min() - { return 0; }; - - static constexpr result_type - max() - { return std::numeric_limits<result_type>::max(); } - - void - discard(unsigned long long __z); - - result_type - operator()() - { - if (__builtin_expect(_M_pos >= state_size, 0)) - _M_gen_rand(); - - return _M_stateT[_M_pos++]; - } - - template<typename _UIntType_2, size_t __m_2, - size_t __pos1_2, size_t __sl1_2, size_t __sl2_2, - size_t __sr1_2, size_t __sr2_2, - uint32_t __msk1_2, uint32_t __msk2_2, - uint32_t __msk3_2, uint32_t __msk4_2, - uint32_t __parity1_2, uint32_t __parity2_2, - uint32_t __parity3_2, uint32_t __parity4_2> - friend bool - operator==(const simd_fast_mersenne_twister_engine<_UIntType_2, - __m_2, __pos1_2, __sl1_2, __sl2_2, __sr1_2, __sr2_2, - __msk1_2, __msk2_2, __msk3_2, __msk4_2, - __parity1_2, __parity2_2, __parity3_2, __parity4_2>& __lhs, - const simd_fast_mersenne_twister_engine<_UIntType_2, - __m_2, __pos1_2, __sl1_2, __sl2_2, __sr1_2, __sr2_2, - __msk1_2, __msk2_2, __msk3_2, __msk4_2, - __parity1_2, __parity2_2, __parity3_2, __parity4_2>& __rhs); - - template<typename _UIntType_2, size_t __m_2, - size_t __pos1_2, size_t __sl1_2, size_t __sl2_2, - size_t __sr1_2, size_t __sr2_2, - uint32_t __msk1_2, uint32_t __msk2_2, - uint32_t __msk3_2, uint32_t __msk4_2, - uint32_t __parity1_2, uint32_t __parity2_2, - uint32_t __parity3_2, uint32_t __parity4_2, - typename _CharT, typename _Traits> - friend std::basic_ostream<_CharT, _Traits>& - operator<<(std::basic_ostream<_CharT, _Traits>& __os, - const __gnu_cxx::simd_fast_mersenne_twister_engine - <_UIntType_2, - __m_2, __pos1_2, __sl1_2, __sl2_2, __sr1_2, __sr2_2, - __msk1_2, __msk2_2, __msk3_2, __msk4_2, - __parity1_2, __parity2_2, __parity3_2, __parity4_2>& __x); - - template<typename _UIntType_2, size_t __m_2, - size_t __pos1_2, size_t __sl1_2, size_t __sl2_2, - size_t __sr1_2, size_t __sr2_2, - uint32_t __msk1_2, uint32_t __msk2_2, - uint32_t __msk3_2, uint32_t __msk4_2, - uint32_t __parity1_2, uint32_t __parity2_2, - uint32_t __parity3_2, uint32_t __parity4_2, - typename _CharT, typename _Traits> - friend std::basic_istream<_CharT, _Traits>& - operator>>(std::basic_istream<_CharT, _Traits>& __is, - __gnu_cxx::simd_fast_mersenne_twister_engine<_UIntType_2, - __m_2, __pos1_2, __sl1_2, __sl2_2, __sr1_2, __sr2_2, - __msk1_2, __msk2_2, __msk3_2, __msk4_2, - __parity1_2, __parity2_2, __parity3_2, __parity4_2>& __x); - - private: - union - { -#ifdef __SSE2__ - __m128i _M_state[_M_nstate]; -#endif - uint32_t _M_state32[_M_nstate32]; - result_type _M_stateT[state_size]; - } __attribute__ ((__aligned__ (16))); - size_t _M_pos; - - void _M_gen_rand(void); - void _M_period_certification(); - }; - - - template<typename _UIntType, size_t __m, - size_t __pos1, size_t __sl1, size_t __sl2, - size_t __sr1, size_t __sr2, - uint32_t __msk1, uint32_t __msk2, - uint32_t __msk3, uint32_t __msk4, - uint32_t __parity1, uint32_t __parity2, - uint32_t __parity3, uint32_t __parity4> - inline bool - operator!=(const __gnu_cxx::simd_fast_mersenne_twister_engine<_UIntType, - __m, __pos1, __sl1, __sl2, __sr1, __sr2, __msk1, __msk2, __msk3, - __msk4, __parity1, __parity2, __parity3, __parity4>& __lhs, - const __gnu_cxx::simd_fast_mersenne_twister_engine<_UIntType, - __m, __pos1, __sl1, __sl2, __sr1, __sr2, __msk1, __msk2, __msk3, - __msk4, __parity1, __parity2, __parity3, __parity4>& __rhs) - { return !(__lhs == __rhs); } - - - /* Definitions for the SIMD-oriented Fast Mersenne Twister as defined - * in the C implementation by Daito and Matsumoto, as both a 32-bit - * and 64-bit version. - */ - typedef simd_fast_mersenne_twister_engine<uint32_t, 607, 2, - 15, 3, 13, 3, - 0xfdff37ffU, 0xef7f3f7dU, - 0xff777b7dU, 0x7ff7fb2fU, - 0x00000001U, 0x00000000U, - 0x00000000U, 0x5986f054U> - sfmt607; - - typedef simd_fast_mersenne_twister_engine<uint64_t, 607, 2, - 15, 3, 13, 3, - 0xfdff37ffU, 0xef7f3f7dU, - 0xff777b7dU, 0x7ff7fb2fU, - 0x00000001U, 0x00000000U, - 0x00000000U, 0x5986f054U> - sfmt607_64; - - - typedef simd_fast_mersenne_twister_engine<uint32_t, 1279, 7, - 14, 3, 5, 1, - 0xf7fefffdU, 0x7fefcfffU, - 0xaff3ef3fU, 0xb5ffff7fU, - 0x00000001U, 0x00000000U, - 0x00000000U, 0x20000000U> - sfmt1279; - - typedef simd_fast_mersenne_twister_engine<uint64_t, 1279, 7, - 14, 3, 5, 1, - 0xf7fefffdU, 0x7fefcfffU, - 0xaff3ef3fU, 0xb5ffff7fU, - 0x00000001U, 0x00000000U, - 0x00000000U, 0x20000000U> - sfmt1279_64; - - - typedef simd_fast_mersenne_twister_engine<uint32_t, 2281, 12, - 19, 1, 5, 1, - 0xbff7ffbfU, 0xfdfffffeU, - 0xf7ffef7fU, 0xf2f7cbbfU, - 0x00000001U, 0x00000000U, - 0x00000000U, 0x41dfa600U> - sfmt2281; - - typedef simd_fast_mersenne_twister_engine<uint64_t, 2281, 12, - 19, 1, 5, 1, - 0xbff7ffbfU, 0xfdfffffeU, - 0xf7ffef7fU, 0xf2f7cbbfU, - 0x00000001U, 0x00000000U, - 0x00000000U, 0x41dfa600U> - sfmt2281_64; - - - typedef simd_fast_mersenne_twister_engine<uint32_t, 4253, 17, - 20, 1, 7, 1, - 0x9f7bffffU, 0x9fffff5fU, - 0x3efffffbU, 0xfffff7bbU, - 0xa8000001U, 0xaf5390a3U, - 0xb740b3f8U, 0x6c11486dU> - sfmt4253; - - typedef simd_fast_mersenne_twister_engine<uint64_t, 4253, 17, - 20, 1, 7, 1, - 0x9f7bffffU, 0x9fffff5fU, - 0x3efffffbU, 0xfffff7bbU, - 0xa8000001U, 0xaf5390a3U, - 0xb740b3f8U, 0x6c11486dU> - sfmt4253_64; - - - typedef simd_fast_mersenne_twister_engine<uint32_t, 11213, 68, - 14, 3, 7, 3, - 0xeffff7fbU, 0xffffffefU, - 0xdfdfbfffU, 0x7fffdbfdU, - 0x00000001U, 0x00000000U, - 0xe8148000U, 0xd0c7afa3U> - sfmt11213; - - typedef simd_fast_mersenne_twister_engine<uint64_t, 11213, 68, - 14, 3, 7, 3, - 0xeffff7fbU, 0xffffffefU, - 0xdfdfbfffU, 0x7fffdbfdU, - 0x00000001U, 0x00000000U, - 0xe8148000U, 0xd0c7afa3U> - sfmt11213_64; - - - typedef simd_fast_mersenne_twister_engine<uint32_t, 19937, 122, - 18, 1, 11, 1, - 0xdfffffefU, 0xddfecb7fU, - 0xbffaffffU, 0xbffffff6U, - 0x00000001U, 0x00000000U, - 0x00000000U, 0x13c9e684U> - sfmt19937; - - typedef simd_fast_mersenne_twister_engine<uint64_t, 19937, 122, - 18, 1, 11, 1, - 0xdfffffefU, 0xddfecb7fU, - 0xbffaffffU, 0xbffffff6U, - 0x00000001U, 0x00000000U, - 0x00000000U, 0x13c9e684U> - sfmt19937_64; - - - typedef simd_fast_mersenne_twister_engine<uint32_t, 44497, 330, - 5, 3, 9, 3, - 0xeffffffbU, 0xdfbebfffU, - 0xbfbf7befU, 0x9ffd7bffU, - 0x00000001U, 0x00000000U, - 0xa3ac4000U, 0xecc1327aU> - sfmt44497; - - typedef simd_fast_mersenne_twister_engine<uint64_t, 44497, 330, - 5, 3, 9, 3, - 0xeffffffbU, 0xdfbebfffU, - 0xbfbf7befU, 0x9ffd7bffU, - 0x00000001U, 0x00000000U, - 0xa3ac4000U, 0xecc1327aU> - sfmt44497_64; - - - typedef simd_fast_mersenne_twister_engine<uint32_t, 86243, 366, - 6, 7, 19, 1, - 0xfdbffbffU, 0xbff7ff3fU, - 0xfd77efffU, 0xbf9ff3ffU, - 0x00000001U, 0x00000000U, - 0x00000000U, 0xe9528d85U> - sfmt86243; - - typedef simd_fast_mersenne_twister_engine<uint64_t, 86243, 366, - 6, 7, 19, 1, - 0xfdbffbffU, 0xbff7ff3fU, - 0xfd77efffU, 0xbf9ff3ffU, - 0x00000001U, 0x00000000U, - 0x00000000U, 0xe9528d85U> - sfmt86243_64; - - - typedef simd_fast_mersenne_twister_engine<uint32_t, 132049, 110, - 19, 1, 21, 1, - 0xffffbb5fU, 0xfb6ebf95U, - 0xfffefffaU, 0xcff77fffU, - 0x00000001U, 0x00000000U, - 0xcb520000U, 0xc7e91c7dU> - sfmt132049; - - typedef simd_fast_mersenne_twister_engine<uint64_t, 132049, 110, - 19, 1, 21, 1, - 0xffffbb5fU, 0xfb6ebf95U, - 0xfffefffaU, 0xcff77fffU, - 0x00000001U, 0x00000000U, - 0xcb520000U, 0xc7e91c7dU> - sfmt132049_64; - - - typedef simd_fast_mersenne_twister_engine<uint32_t, 216091, 627, - 11, 3, 10, 1, - 0xbff7bff7U, 0xbfffffffU, - 0xbffffa7fU, 0xffddfbfbU, - 0xf8000001U, 0x89e80709U, - 0x3bd2b64bU, 0x0c64b1e4U> - sfmt216091; - - typedef simd_fast_mersenne_twister_engine<uint64_t, 216091, 627, - 11, 3, 10, 1, - 0xbff7bff7U, 0xbfffffffU, - 0xbffffa7fU, 0xffddfbfbU, - 0xf8000001U, 0x89e80709U, - 0x3bd2b64bU, 0x0c64b1e4U> - sfmt216091_64; - -#endif // __BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__ - - /** - * @brief A beta continuous distribution for random numbers. - * - * The formula for the beta probability density function is: - * @f[ - * p(x|\alpha,\beta) = \frac{1}{B(\alpha,\beta)} - * x^{\alpha - 1} (1 - x)^{\beta - 1} - * @f] - */ - template<typename _RealType = double> - class beta_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 beta_distribution<_RealType> distribution_type; - friend class beta_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)); - _GLIBCXX_DEBUG_ASSERT(_M_beta > _RealType(0)); - } - - _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; - }; - - public: - /** - * @brief Constructs a beta distribution with parameters - * @f$\alpha@f$ and @f$\beta@f$. - */ - explicit - beta_distribution(_RealType __alpha_val = _RealType(1), - _RealType __beta_val = _RealType(1)) - : _M_param(__alpha_val, __beta_val) - { } - - explicit - beta_distribution(const param_type& __p) - : _M_param(__p) - { } - - /** - * @brief Resets the distribution state. - */ - void - 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 result_type(1); } - - /** - * @brief Generating functions. - */ - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng) - { return this->operator()(__urng, _M_param); } - - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng, - const param_type& __p); - - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng) - { this->__generate(__f, __t, __urng, _M_param); } - - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng, - const param_type& __p) - { this->__generate_impl(__f, __t, __urng, __p); } - - template<typename _UniformRandomNumberGenerator> - void - __generate(result_type* __f, result_type* __t, - _UniformRandomNumberGenerator& __urng, - const param_type& __p) - { this->__generate_impl(__f, __t, __urng, __p); } - - /** - * @brief Return true if two beta distributions have the same - * parameters and the sequences that would be generated - * are equal. - */ - friend bool - operator==(const beta_distribution& __d1, - const beta_distribution& __d2) - { return __d1._M_param == __d2._M_param; } - - /** - * @brief Inserts a %beta_distribution random number distribution - * @p __x into the output stream @p __os. - * - * @param __os An output stream. - * @param __x A %beta_distribution random number distribution. - * - * @returns The output stream with the state of @p __x inserted or in - * an error state. - */ - template<typename _RealType1, typename _CharT, typename _Traits> - friend std::basic_ostream<_CharT, _Traits>& - operator<<(std::basic_ostream<_CharT, _Traits>& __os, - const __gnu_cxx::beta_distribution<_RealType1>& __x); - - /** - * @brief Extracts a %beta_distribution random number distribution - * @p __x from the input stream @p __is. - * - * @param __is An input stream. - * @param __x A %beta_distribution random number generator engine. - * - * @returns The input stream with @p __x extracted or in an error state. - */ - template<typename _RealType1, typename _CharT, typename _Traits> - friend std::basic_istream<_CharT, _Traits>& - operator>>(std::basic_istream<_CharT, _Traits>& __is, - __gnu_cxx::beta_distribution<_RealType1>& __x); - - private: - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate_impl(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng, - const param_type& __p); - - param_type _M_param; - }; - - /** - * @brief Return true if two beta distributions are different. - */ - template<typename _RealType> - inline bool - operator!=(const __gnu_cxx::beta_distribution<_RealType>& __d1, - const __gnu_cxx::beta_distribution<_RealType>& __d2) - { return !(__d1 == __d2); } - - - /** - * @brief A multi-variate normal continuous distribution for random numbers. - * - * The formula for the normal probability density function is - * @f[ - * p(\overrightarrow{x}|\overrightarrow{\mu },\Sigma) = - * \frac{1}{\sqrt{(2\pi )^k\det(\Sigma))}} - * e^{-\frac{1}{2}(\overrightarrow{x}-\overrightarrow{\mu})^\text{T} - * \Sigma ^{-1}(\overrightarrow{x}-\overrightarrow{\mu})} - * @f] - * - * where @f$\overrightarrow{x}@f$ and @f$\overrightarrow{\mu}@f$ are - * vectors of dimension @f$k@f$ and @f$\Sigma@f$ is the covariance - * matrix (which must be positive-definite). - */ - template<std::size_t _Dimen, typename _RealType = double> - class normal_mv_distribution - { - static_assert(std::is_floating_point<_RealType>::value, - "template argument not a floating point type"); - static_assert(_Dimen != 0, "dimension is zero"); - - public: - /** The type of the range of the distribution. */ - typedef std::array<_RealType, _Dimen> result_type; - /** Parameter type. */ - class param_type - { - static constexpr size_t _M_t_size = _Dimen * (_Dimen + 1) / 2; - - public: - typedef normal_mv_distribution<_Dimen, _RealType> distribution_type; - friend class normal_mv_distribution<_Dimen, _RealType>; - - param_type() - { - std::fill(_M_mean.begin(), _M_mean.end(), _RealType(0)); - auto __it = _M_t.begin(); - for (size_t __i = 0; __i < _Dimen; ++__i) - { - std::fill_n(__it, __i, _RealType(0)); - __it += __i; - *__it++ = _RealType(1); - } - } - - template<typename _ForwardIterator1, typename _ForwardIterator2> - param_type(_ForwardIterator1 __meanbegin, - _ForwardIterator1 __meanend, - _ForwardIterator2 __varcovbegin, - _ForwardIterator2 __varcovend) - { - __glibcxx_function_requires(_ForwardIteratorConcept< - _ForwardIterator1>) - __glibcxx_function_requires(_ForwardIteratorConcept< - _ForwardIterator2>) - _GLIBCXX_DEBUG_ASSERT(std::distance(__meanbegin, __meanend) - <= _Dimen); - const auto __dist = std::distance(__varcovbegin, __varcovend); - _GLIBCXX_DEBUG_ASSERT(__dist == _Dimen * _Dimen - || __dist == _Dimen * (_Dimen + 1) / 2 - || __dist == _Dimen); - - if (__dist == _Dimen * _Dimen) - _M_init_full(__meanbegin, __meanend, __varcovbegin, __varcovend); - else if (__dist == _Dimen * (_Dimen + 1) / 2) - _M_init_lower(__meanbegin, __meanend, __varcovbegin, __varcovend); - else - _M_init_diagonal(__meanbegin, __meanend, - __varcovbegin, __varcovend); - } - - param_type(std::initializer_list<_RealType> __mean, - std::initializer_list<_RealType> __varcov) - { - _GLIBCXX_DEBUG_ASSERT(__mean.size() <= _Dimen); - _GLIBCXX_DEBUG_ASSERT(__varcov.size() == _Dimen * _Dimen - || __varcov.size() == _Dimen * (_Dimen + 1) / 2 - || __varcov.size() == _Dimen); - - if (__varcov.size() == _Dimen * _Dimen) - _M_init_full(__mean.begin(), __mean.end(), - __varcov.begin(), __varcov.end()); - else if (__varcov.size() == _Dimen * (_Dimen + 1) / 2) - _M_init_lower(__mean.begin(), __mean.end(), - __varcov.begin(), __varcov.end()); - else - _M_init_diagonal(__mean.begin(), __mean.end(), - __varcov.begin(), __varcov.end()); - } - - std::array<_RealType, _Dimen> - mean() const - { return _M_mean; } - - std::array<_RealType, _M_t_size> - varcov() const - { return _M_t; } - - friend bool - operator==(const param_type& __p1, const param_type& __p2) - { return __p1._M_mean == __p2._M_mean && __p1._M_t == __p2._M_t; } - - private: - template <typename _InputIterator1, typename _InputIterator2> - void _M_init_full(_InputIterator1 __meanbegin, - _InputIterator1 __meanend, - _InputIterator2 __varcovbegin, - _InputIterator2 __varcovend); - template <typename _InputIterator1, typename _InputIterator2> - void _M_init_lower(_InputIterator1 __meanbegin, - _InputIterator1 __meanend, - _InputIterator2 __varcovbegin, - _InputIterator2 __varcovend); - template <typename _InputIterator1, typename _InputIterator2> - void _M_init_diagonal(_InputIterator1 __meanbegin, - _InputIterator1 __meanend, - _InputIterator2 __varbegin, - _InputIterator2 __varend); - - std::array<_RealType, _Dimen> _M_mean; - std::array<_RealType, _M_t_size> _M_t; - }; - - public: - normal_mv_distribution() - : _M_param(), _M_nd() - { } - - template<typename _ForwardIterator1, typename _ForwardIterator2> - normal_mv_distribution(_ForwardIterator1 __meanbegin, - _ForwardIterator1 __meanend, - _ForwardIterator2 __varcovbegin, - _ForwardIterator2 __varcovend) - : _M_param(__meanbegin, __meanend, __varcovbegin, __varcovend), - _M_nd() - { } - - normal_mv_distribution(std::initializer_list<_RealType> __mean, - std::initializer_list<_RealType> __varcov) - : _M_param(__mean, __varcov), _M_nd() - { } - - explicit - normal_mv_distribution(const param_type& __p) - : _M_param(__p), _M_nd() - { } - - /** - * @brief Resets the distribution state. - */ - void - reset() - { _M_nd.reset(); } - - /** - * @brief Returns the mean of the distribution. - */ - result_type - mean() const - { return _M_param.mean(); } - - /** - * @brief Returns the compact form of the variance/covariance - * matrix of the distribution. - */ - std::array<_RealType, _Dimen * (_Dimen + 1) / 2> - varcov() const - { return _M_param.varcov(); } - - /** - * @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 - { result_type __res; - __res.fill(std::numeric_limits<_RealType>::min()); - return __res; } - - /** - * @brief Returns the least upper bound value of the distribution. - */ - result_type - max() const - { result_type __res; - __res.fill(std::numeric_limits<_RealType>::max()); - return __res; } - - /** - * @brief Generating functions. - */ - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng) - { return this->operator()(__urng, _M_param); } - - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng, - const param_type& __p); - - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng) - { return this->__generate_impl(__f, __t, __urng, _M_param); } - - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng, - const param_type& __p) - { return this->__generate_impl(__f, __t, __urng, __p); } - - /** - * @brief Return true if two multi-variant normal distributions have - * the same parameters and the sequences that would - * be generated are equal. - */ - template<size_t _Dimen1, typename _RealType1> - friend bool - operator==(const - __gnu_cxx::normal_mv_distribution<_Dimen1, _RealType1>& - __d1, - const - __gnu_cxx::normal_mv_distribution<_Dimen1, _RealType1>& - __d2); - - /** - * @brief Inserts a %normal_mv_distribution random number distribution - * @p __x into the output stream @p __os. - * - * @param __os An output stream. - * @param __x A %normal_mv_distribution random number distribution. - * - * @returns The output stream with the state of @p __x inserted or in - * an error state. - */ - template<size_t _Dimen1, typename _RealType1, - typename _CharT, typename _Traits> - friend std::basic_ostream<_CharT, _Traits>& - operator<<(std::basic_ostream<_CharT, _Traits>& __os, - const - __gnu_cxx::normal_mv_distribution<_Dimen1, _RealType1>& - __x); - - /** - * @brief Extracts a %normal_mv_distribution random number distribution - * @p __x from the input stream @p __is. - * - * @param __is An input stream. - * @param __x A %normal_mv_distribution random number generator engine. - * - * @returns The input stream with @p __x extracted or in an error - * state. - */ - template<size_t _Dimen1, typename _RealType1, - typename _CharT, typename _Traits> - friend std::basic_istream<_CharT, _Traits>& - operator>>(std::basic_istream<_CharT, _Traits>& __is, - __gnu_cxx::normal_mv_distribution<_Dimen1, _RealType1>& - __x); - - private: - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate_impl(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng, - const param_type& __p); - - param_type _M_param; - std::normal_distribution<_RealType> _M_nd; - }; - - /** - * @brief Return true if two multi-variate normal distributions are - * different. - */ - template<size_t _Dimen, typename _RealType> - inline bool - operator!=(const __gnu_cxx::normal_mv_distribution<_Dimen, _RealType>& - __d1, - const __gnu_cxx::normal_mv_distribution<_Dimen, _RealType>& - __d2) - { return !(__d1 == __d2); } - - - /** - * @brief A Rice continuous distribution for random numbers. - * - * The formula for the Rice probability density function is - * @f[ - * p(x|\nu,\sigma) = \frac{x}{\sigma^2} - * \exp\left(-\frac{x^2+\nu^2}{2\sigma^2}\right) - * I_0\left(\frac{x \nu}{\sigma^2}\right) - * @f] - * where @f$I_0(z)@f$ is the modified Bessel function of the first kind - * of order 0 and @f$\nu >= 0@f$ and @f$\sigma > 0@f$. - * - * <table border=1 cellpadding=10 cellspacing=0> - * <caption align=top>Distribution Statistics</caption> - * <tr><td>Mean</td><td>@f$\sqrt{\pi/2}L_{1/2}(-\nu^2/2\sigma^2)@f$</td></tr> - * <tr><td>Variance</td><td>@f$2\sigma^2 + \nu^2 - * + (\pi\sigma^2/2)L^2_{1/2}(-\nu^2/2\sigma^2)@f$</td></tr> - * <tr><td>Range</td><td>@f$[0, \infty)@f$</td></tr> - * </table> - * where @f$L_{1/2}(x)@f$ is the Laguerre polynomial of order 1/2. - */ - template<typename _RealType = double> - class - rice_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 rice_distribution<result_type> distribution_type; - - param_type(result_type __nu_val = result_type(0), - result_type __sigma_val = result_type(1)) - : _M_nu(__nu_val), _M_sigma(__sigma_val) - { - _GLIBCXX_DEBUG_ASSERT(_M_nu >= result_type(0)); - _GLIBCXX_DEBUG_ASSERT(_M_sigma > result_type(0)); - } - - result_type - nu() const - { return _M_nu; } - - result_type - sigma() const - { return _M_sigma; } - - friend bool - operator==(const param_type& __p1, const param_type& __p2) - { return __p1._M_nu == __p2._M_nu - && __p1._M_sigma == __p2._M_sigma; } - - private: - void _M_initialize(); - - result_type _M_nu; - result_type _M_sigma; - }; - - /** - * @brief Constructors. - */ - explicit - rice_distribution(result_type __nu_val = result_type(0), - result_type __sigma_val = result_type(1)) - : _M_param(__nu_val, __sigma_val), - _M_ndx(__nu_val, __sigma_val), - _M_ndy(result_type(0), __sigma_val) - { } - - explicit - rice_distribution(const param_type& __p) - : _M_param(__p), - _M_ndx(__p.nu(), __p.sigma()), - _M_ndy(result_type(0), __p.sigma()) - { } - - /** - * @brief Resets the distribution state. - */ - void - reset() - { - _M_ndx.reset(); - _M_ndy.reset(); - } - - /** - * @brief Return the parameters of the distribution. - */ - result_type - nu() const - { return _M_param.nu(); } - - result_type - sigma() const - { return _M_param.sigma(); } - - /** - * @brief Returns the parameter set of the distribution. - */ - param_type - param() const - { return _M_param; } - - /** - * @brief Sets the parameter set of the distribution. - * @param __param The new parameter set of the distribution. - */ - void - param(const param_type& __param) - { _M_param = __param; } - - /** - * @brief Returns the greatest lower bound value of the distribution. - */ - result_type - min() const - { return result_type(0); } - - /** - * @brief Returns the least upper bound value of the distribution. - */ - result_type - max() const - { return std::numeric_limits<result_type>::max(); } - - /** - * @brief Generating functions. - */ - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng) - { - result_type __x = this->_M_ndx(__urng); - result_type __y = this->_M_ndy(__urng); -#if _GLIBCXX_USE_C99_MATH_TR1 - return std::hypot(__x, __y); -#else - return std::sqrt(__x * __x + __y * __y); -#endif - } - - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng, - const param_type& __p) - { - typename std::normal_distribution<result_type>::param_type - __px(__p.nu(), __p.sigma()), __py(result_type(0), __p.sigma()); - result_type __x = this->_M_ndx(__px, __urng); - result_type __y = this->_M_ndy(__py, __urng); -#if _GLIBCXX_USE_C99_MATH_TR1 - return std::hypot(__x, __y); -#else - return std::sqrt(__x * __x + __y * __y); -#endif - } - - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng) - { this->__generate(__f, __t, __urng, _M_param); } - - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng, - const param_type& __p) - { this->__generate_impl(__f, __t, __urng, __p); } - - template<typename _UniformRandomNumberGenerator> - void - __generate(result_type* __f, result_type* __t, - _UniformRandomNumberGenerator& __urng, - const param_type& __p) - { this->__generate_impl(__f, __t, __urng, __p); } - - /** - * @brief Return true if two Rice distributions have - * the same parameters and the sequences that would - * be generated are equal. - */ - friend bool - operator==(const rice_distribution& __d1, - const rice_distribution& __d2) - { return (__d1._M_param == __d2._M_param - && __d1._M_ndx == __d2._M_ndx - && __d1._M_ndy == __d2._M_ndy); } - - /** - * @brief Inserts a %rice_distribution random number distribution - * @p __x into the output stream @p __os. - * - * @param __os An output stream. - * @param __x A %rice_distribution random number distribution. - * - * @returns The output stream with the state of @p __x inserted or in - * an error state. - */ - template<typename _RealType1, typename _CharT, typename _Traits> - friend std::basic_ostream<_CharT, _Traits>& - operator<<(std::basic_ostream<_CharT, _Traits>&, - const rice_distribution<_RealType1>&); - - /** - * @brief Extracts a %rice_distribution random number distribution - * @p __x from the input stream @p __is. - * - * @param __is An input stream. - * @param __x A %rice_distribution random number - * generator engine. - * - * @returns The input stream with @p __x extracted or in an error state. - */ - template<typename _RealType1, typename _CharT, typename _Traits> - friend std::basic_istream<_CharT, _Traits>& - operator>>(std::basic_istream<_CharT, _Traits>&, - rice_distribution<_RealType1>&); - - private: - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate_impl(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng, - const param_type& __p); - - param_type _M_param; - - std::normal_distribution<result_type> _M_ndx; - std::normal_distribution<result_type> _M_ndy; - }; - - /** - * @brief Return true if two Rice distributions are not equal. - */ - template<typename _RealType1> - inline bool - operator!=(const rice_distribution<_RealType1>& __d1, - const rice_distribution<_RealType1>& __d2) - { return !(__d1 == __d2); } - - - /** - * @brief A Nakagami continuous distribution for random numbers. - * - * The formula for the Nakagami probability density function is - * @f[ - * p(x|\mu,\omega) = \frac{2\mu^\mu}{\Gamma(\mu)\omega^\mu} - * x^{2\mu-1}e^{-\mu x / \omega} - * @f] - * where @f$\Gamma(z)@f$ is the gamma function and @f$\mu >= 0.5@f$ - * and @f$\omega > 0@f$. - */ - template<typename _RealType = double> - class - nakagami_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 nakagami_distribution<result_type> distribution_type; - - param_type(result_type __mu_val = result_type(1), - result_type __omega_val = result_type(1)) - : _M_mu(__mu_val), _M_omega(__omega_val) - { - _GLIBCXX_DEBUG_ASSERT(_M_mu >= result_type(0.5L)); - _GLIBCXX_DEBUG_ASSERT(_M_omega > result_type(0)); - } - - result_type - mu() const - { return _M_mu; } - - result_type - omega() const - { return _M_omega; } - - friend bool - operator==(const param_type& __p1, const param_type& __p2) - { return __p1._M_mu == __p2._M_mu - && __p1._M_omega == __p2._M_omega; } - - private: - void _M_initialize(); - - result_type _M_mu; - result_type _M_omega; - }; - - /** - * @brief Constructors. - */ - explicit - nakagami_distribution(result_type __mu_val = result_type(1), - result_type __omega_val = result_type(1)) - : _M_param(__mu_val, __omega_val), - _M_gd(__mu_val, __omega_val / __mu_val) - { } - - explicit - nakagami_distribution(const param_type& __p) - : _M_param(__p), - _M_gd(__p.mu(), __p.omega() / __p.mu()) - { } - - /** - * @brief Resets the distribution state. - */ - void - reset() - { _M_gd.reset(); } - - /** - * @brief Return the parameters of the distribution. - */ - result_type - mu() const - { return _M_param.mu(); } - - result_type - omega() const - { return _M_param.omega(); } - - /** - * @brief Returns the parameter set of the distribution. - */ - param_type - param() const - { return _M_param; } - - /** - * @brief Sets the parameter set of the distribution. - * @param __param The new parameter set of the distribution. - */ - void - param(const param_type& __param) - { _M_param = __param; } - - /** - * @brief Returns the greatest lower bound value of the distribution. - */ - result_type - min() const - { return result_type(0); } - - /** - * @brief Returns the least upper bound value of the distribution. - */ - result_type - max() const - { return std::numeric_limits<result_type>::max(); } - - /** - * @brief Generating functions. - */ - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng) - { return std::sqrt(this->_M_gd(__urng)); } - - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng, - const param_type& __p) - { - typename std::gamma_distribution<result_type>::param_type - __pg(__p.mu(), __p.omega() / __p.mu()); - return std::sqrt(this->_M_gd(__pg, __urng)); - } - - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng) - { this->__generate(__f, __t, __urng, _M_param); } - - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng, - const param_type& __p) - { this->__generate_impl(__f, __t, __urng, __p); } - - template<typename _UniformRandomNumberGenerator> - void - __generate(result_type* __f, result_type* __t, - _UniformRandomNumberGenerator& __urng, - const param_type& __p) - { this->__generate_impl(__f, __t, __urng, __p); } - - /** - * @brief Return true if two Nakagami distributions have - * the same parameters and the sequences that would - * be generated are equal. - */ - friend bool - operator==(const nakagami_distribution& __d1, - const nakagami_distribution& __d2) - { return (__d1._M_param == __d2._M_param - && __d1._M_gd == __d2._M_gd); } - - /** - * @brief Inserts a %nakagami_distribution random number distribution - * @p __x into the output stream @p __os. - * - * @param __os An output stream. - * @param __x A %nakagami_distribution random number distribution. - * - * @returns The output stream with the state of @p __x inserted or in - * an error state. - */ - template<typename _RealType1, typename _CharT, typename _Traits> - friend std::basic_ostream<_CharT, _Traits>& - operator<<(std::basic_ostream<_CharT, _Traits>&, - const nakagami_distribution<_RealType1>&); - - /** - * @brief Extracts a %nakagami_distribution random number distribution - * @p __x from the input stream @p __is. - * - * @param __is An input stream. - * @param __x A %nakagami_distribution random number - * generator engine. - * - * @returns The input stream with @p __x extracted or in an error state. - */ - template<typename _RealType1, typename _CharT, typename _Traits> - friend std::basic_istream<_CharT, _Traits>& - operator>>(std::basic_istream<_CharT, _Traits>&, - nakagami_distribution<_RealType1>&); - - private: - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate_impl(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng, - const param_type& __p); - - param_type _M_param; - - std::gamma_distribution<result_type> _M_gd; - }; - - /** - * @brief Return true if two Nakagami distributions are not equal. - */ - template<typename _RealType> - inline bool - operator!=(const nakagami_distribution<_RealType>& __d1, - const nakagami_distribution<_RealType>& __d2) - { return !(__d1 == __d2); } - - - /** - * @brief A Pareto continuous distribution for random numbers. - * - * The formula for the Pareto cumulative probability function is - * @f[ - * P(x|\alpha,\mu) = 1 - \left(\frac{\mu}{x}\right)^\alpha - * @f] - * The formula for the Pareto probability density function is - * @f[ - * p(x|\alpha,\mu) = \frac{\alpha + 1}{\mu} - * \left(\frac{\mu}{x}\right)^{\alpha + 1} - * @f] - * where @f$x >= \mu@f$ and @f$\mu > 0@f$, @f$\alpha > 0@f$. - * - * <table border=1 cellpadding=10 cellspacing=0> - * <caption align=top>Distribution Statistics</caption> - * <tr><td>Mean</td><td>@f$\alpha \mu / (\alpha - 1)@f$ - * for @f$\alpha > 1@f$</td></tr> - * <tr><td>Variance</td><td>@f$\alpha \mu^2 / [(\alpha - 1)^2(\alpha - 2)]@f$ - * for @f$\alpha > 2@f$</td></tr> - * <tr><td>Range</td><td>@f$[\mu, \infty)@f$</td></tr> - * </table> - */ - template<typename _RealType = double> - class - pareto_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 pareto_distribution<result_type> distribution_type; - - param_type(result_type __alpha_val = result_type(1), - result_type __mu_val = result_type(1)) - : _M_alpha(__alpha_val), _M_mu(__mu_val) - { - _GLIBCXX_DEBUG_ASSERT(_M_alpha > result_type(0)); - _GLIBCXX_DEBUG_ASSERT(_M_mu > result_type(0)); - } - - result_type - alpha() const - { return _M_alpha; } - - result_type - mu() const - { return _M_mu; } - - friend bool - operator==(const param_type& __p1, const param_type& __p2) - { return __p1._M_alpha == __p2._M_alpha && __p1._M_mu == __p2._M_mu; } - - private: - void _M_initialize(); - - result_type _M_alpha; - result_type _M_mu; - }; - - /** - * @brief Constructors. - */ - explicit - pareto_distribution(result_type __alpha_val = result_type(1), - result_type __mu_val = result_type(1)) - : _M_param(__alpha_val, __mu_val), - _M_ud() - { } - - explicit - pareto_distribution(const param_type& __p) - : _M_param(__p), - _M_ud() - { } - - /** - * @brief Resets the distribution state. - */ - void - reset() - { - _M_ud.reset(); - } - - /** - * @brief Return the parameters of the distribution. - */ - result_type - alpha() const - { return _M_param.alpha(); } - - result_type - mu() const - { return _M_param.mu(); } - - /** - * @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 this->mu(); } - - /** - * @brief Returns the least upper bound value of the distribution. - */ - result_type - max() const - { return std::numeric_limits<result_type>::max(); } - - /** - * @brief Generating functions. - */ - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng) - { - return this->mu() * std::pow(this->_M_ud(__urng), - -result_type(1) / this->alpha()); - } - - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng, - const param_type& __p) - { - return __p.mu() * std::pow(this->_M_ud(__urng), - -result_type(1) / __p.alpha()); - } - - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng) - { this->__generate(__f, __t, __urng, _M_param); } - - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng, - const param_type& __p) - { this->__generate_impl(__f, __t, __urng, __p); } - - template<typename _UniformRandomNumberGenerator> - void - __generate(result_type* __f, result_type* __t, - _UniformRandomNumberGenerator& __urng, - const param_type& __p) - { this->__generate_impl(__f, __t, __urng, __p); } - - /** - * @brief Return true if two Pareto distributions have - * the same parameters and the sequences that would - * be generated are equal. - */ - friend bool - operator==(const pareto_distribution& __d1, - const pareto_distribution& __d2) - { return (__d1._M_param == __d2._M_param - && __d1._M_ud == __d2._M_ud); } - - /** - * @brief Inserts a %pareto_distribution random number distribution - * @p __x into the output stream @p __os. - * - * @param __os An output stream. - * @param __x A %pareto_distribution random number distribution. - * - * @returns The output stream with the state of @p __x inserted or in - * an error state. - */ - template<typename _RealType1, typename _CharT, typename _Traits> - friend std::basic_ostream<_CharT, _Traits>& - operator<<(std::basic_ostream<_CharT, _Traits>&, - const pareto_distribution<_RealType1>&); - - /** - * @brief Extracts a %pareto_distribution random number distribution - * @p __x from the input stream @p __is. - * - * @param __is An input stream. - * @param __x A %pareto_distribution random number - * generator engine. - * - * @returns The input stream with @p __x extracted or in an error state. - */ - template<typename _RealType1, typename _CharT, typename _Traits> - friend std::basic_istream<_CharT, _Traits>& - operator>>(std::basic_istream<_CharT, _Traits>&, - pareto_distribution<_RealType1>&); - - private: - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate_impl(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng, - const param_type& __p); - - param_type _M_param; - - std::uniform_real_distribution<result_type> _M_ud; - }; - - /** - * @brief Return true if two Pareto distributions are not equal. - */ - template<typename _RealType> - inline bool - operator!=(const pareto_distribution<_RealType>& __d1, - const pareto_distribution<_RealType>& __d2) - { return !(__d1 == __d2); } - - - /** - * @brief A K continuous distribution for random numbers. - * - * The formula for the K probability density function is - * @f[ - * p(x|\lambda, \mu, \nu) = \frac{2}{x} - * \left(\frac{\lambda\nu x}{\mu}\right)^{\frac{\lambda + \nu}{2}} - * \frac{1}{\Gamma(\lambda)\Gamma(\nu)} - * K_{\nu - \lambda}\left(2\sqrt{\frac{\lambda\nu x}{\mu}}\right) - * @f] - * where @f$I_0(z)@f$ is the modified Bessel function of the second kind - * of order @f$\nu - \lambda@f$ and @f$\lambda > 0@f$, @f$\mu > 0@f$ - * and @f$\nu > 0@f$. - * - * <table border=1 cellpadding=10 cellspacing=0> - * <caption align=top>Distribution Statistics</caption> - * <tr><td>Mean</td><td>@f$\mu@f$</td></tr> - * <tr><td>Variance</td><td>@f$\mu^2\frac{\lambda + \nu + 1}{\lambda\nu}@f$</td></tr> - * <tr><td>Range</td><td>@f$[0, \infty)@f$</td></tr> - * </table> - */ - template<typename _RealType = double> - class - k_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 k_distribution<result_type> distribution_type; - - param_type(result_type __lambda_val = result_type(1), - result_type __mu_val = result_type(1), - result_type __nu_val = result_type(1)) - : _M_lambda(__lambda_val), _M_mu(__mu_val), _M_nu(__nu_val) - { - _GLIBCXX_DEBUG_ASSERT(_M_lambda > result_type(0)); - _GLIBCXX_DEBUG_ASSERT(_M_mu > result_type(0)); - _GLIBCXX_DEBUG_ASSERT(_M_nu > result_type(0)); - } - - result_type - lambda() const - { return _M_lambda; } - - result_type - mu() const - { return _M_mu; } - - result_type - nu() const - { return _M_nu; } - - friend bool - operator==(const param_type& __p1, const param_type& __p2) - { return __p1._M_lambda == __p2._M_lambda - && __p1._M_mu == __p2._M_mu - && __p1._M_nu == __p2._M_nu; } - - private: - void _M_initialize(); - - result_type _M_lambda; - result_type _M_mu; - result_type _M_nu; - }; - - /** - * @brief Constructors. - */ - explicit - k_distribution(result_type __lambda_val = result_type(1), - result_type __mu_val = result_type(1), - result_type __nu_val = result_type(1)) - : _M_param(__lambda_val, __mu_val, __nu_val), - _M_gd1(__lambda_val, result_type(1) / __lambda_val), - _M_gd2(__nu_val, __mu_val / __nu_val) - { } - - explicit - k_distribution(const param_type& __p) - : _M_param(__p), - _M_gd1(__p.lambda(), result_type(1) / __p.lambda()), - _M_gd2(__p.nu(), __p.mu() / __p.nu()) - { } - - /** - * @brief Resets the distribution state. - */ - void - reset() - { - _M_gd1.reset(); - _M_gd2.reset(); - } - - /** - * @brief Return the parameters of the distribution. - */ - result_type - lambda() const - { return _M_param.lambda(); } - - result_type - mu() const - { return _M_param.mu(); } - - result_type - nu() const - { return _M_param.nu(); } - - /** - * @brief Returns the parameter set of the distribution. - */ - param_type - param() const - { return _M_param; } - - /** - * @brief Sets the parameter set of the distribution. - * @param __param The new parameter set of the distribution. - */ - void - param(const param_type& __param) - { _M_param = __param; } - - /** - * @brief Returns the greatest lower bound value of the distribution. - */ - result_type - min() const - { return result_type(0); } - - /** - * @brief Returns the least upper bound value of the distribution. - */ - result_type - max() const - { return std::numeric_limits<result_type>::max(); } - - /** - * @brief Generating functions. - */ - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator&); - - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator&, const param_type&); - - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng) - { this->__generate(__f, __t, __urng, _M_param); } - - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng, - const param_type& __p) - { this->__generate_impl(__f, __t, __urng, __p); } - - template<typename _UniformRandomNumberGenerator> - void - __generate(result_type* __f, result_type* __t, - _UniformRandomNumberGenerator& __urng, - const param_type& __p) - { this->__generate_impl(__f, __t, __urng, __p); } - - /** - * @brief Return true if two K distributions have - * the same parameters and the sequences that would - * be generated are equal. - */ - friend bool - operator==(const k_distribution& __d1, - const k_distribution& __d2) - { return (__d1._M_param == __d2._M_param - && __d1._M_gd1 == __d2._M_gd1 - && __d1._M_gd2 == __d2._M_gd2); } - - /** - * @brief Inserts a %k_distribution random number distribution - * @p __x into the output stream @p __os. - * - * @param __os An output stream. - * @param __x A %k_distribution random number distribution. - * - * @returns The output stream with the state of @p __x inserted or in - * an error state. - */ - template<typename _RealType1, typename _CharT, typename _Traits> - friend std::basic_ostream<_CharT, _Traits>& - operator<<(std::basic_ostream<_CharT, _Traits>&, - const k_distribution<_RealType1>&); - - /** - * @brief Extracts a %k_distribution random number distribution - * @p __x from the input stream @p __is. - * - * @param __is An input stream. - * @param __x A %k_distribution random number - * generator engine. - * - * @returns The input stream with @p __x extracted or in an error state. - */ - template<typename _RealType1, typename _CharT, typename _Traits> - friend std::basic_istream<_CharT, _Traits>& - operator>>(std::basic_istream<_CharT, _Traits>&, - k_distribution<_RealType1>&); - - private: - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate_impl(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng, - const param_type& __p); - - param_type _M_param; - - std::gamma_distribution<result_type> _M_gd1; - std::gamma_distribution<result_type> _M_gd2; - }; - - /** - * @brief Return true if two K distributions are not equal. - */ - template<typename _RealType> - inline bool - operator!=(const k_distribution<_RealType>& __d1, - const k_distribution<_RealType>& __d2) - { return !(__d1 == __d2); } - - - /** - * @brief An arcsine continuous distribution for random numbers. - * - * The formula for the arcsine probability density function is - * @f[ - * p(x|a,b) = \frac{1}{\pi \sqrt{(x - a)(b - x)}} - * @f] - * where @f$x >= a@f$ and @f$x <= b@f$. - * - * <table border=1 cellpadding=10 cellspacing=0> - * <caption align=top>Distribution Statistics</caption> - * <tr><td>Mean</td><td>@f$ (a + b) / 2 @f$</td></tr> - * <tr><td>Variance</td><td>@f$ (b - a)^2 / 8 @f$</td></tr> - * <tr><td>Range</td><td>@f$[a, b]@f$</td></tr> - * </table> - */ - template<typename _RealType = double> - class - arcsine_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 arcsine_distribution<result_type> distribution_type; - - param_type(result_type __a = result_type(0), - result_type __b = result_type(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: - void _M_initialize(); - - result_type _M_a; - result_type _M_b; - }; - - /** - * @brief Constructors. - */ - explicit - arcsine_distribution(result_type __a = result_type(0), - result_type __b = result_type(1)) - : _M_param(__a, __b), - _M_ud(-1.5707963267948966192313216916397514L, - +1.5707963267948966192313216916397514L) - { } - - explicit - arcsine_distribution(const param_type& __p) - : _M_param(__p), - _M_ud(-1.5707963267948966192313216916397514L, - +1.5707963267948966192313216916397514L) - { } - - /** - * @brief Resets the distribution state. - */ - void - reset() - { _M_ud.reset(); } - - /** - * @brief Return the parameters of the distribution. - */ - 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 greatest lower bound value of the distribution. - */ - result_type - min() const - { return this->a(); } - - /** - * @brief Returns the least upper bound value of the distribution. - */ - result_type - max() const - { return this->b(); } - - /** - * @brief Generating functions. - */ - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng) - { - result_type __x = std::sin(this->_M_ud(__urng)); - return (__x * (this->b() - this->a()) - + this->a() + this->b()) / result_type(2); - } - - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng, - const param_type& __p) - { - result_type __x = std::sin(this->_M_ud(__urng)); - return (__x * (__p.b() - __p.a()) - + __p.a() + __p.b()) / result_type(2); - } - - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng) - { this->__generate(__f, __t, __urng, _M_param); } - - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng, - const param_type& __p) - { this->__generate_impl(__f, __t, __urng, __p); } - - template<typename _UniformRandomNumberGenerator> - void - __generate(result_type* __f, result_type* __t, - _UniformRandomNumberGenerator& __urng, - const param_type& __p) - { this->__generate_impl(__f, __t, __urng, __p); } - - /** - * @brief Return true if two arcsine distributions have - * the same parameters and the sequences that would - * be generated are equal. - */ - friend bool - operator==(const arcsine_distribution& __d1, - const arcsine_distribution& __d2) - { return (__d1._M_param == __d2._M_param - && __d1._M_ud == __d2._M_ud); } - - /** - * @brief Inserts a %arcsine_distribution random number distribution - * @p __x into the output stream @p __os. - * - * @param __os An output stream. - * @param __x A %arcsine_distribution random number distribution. - * - * @returns The output stream with the state of @p __x inserted or in - * an error state. - */ - template<typename _RealType1, typename _CharT, typename _Traits> - friend std::basic_ostream<_CharT, _Traits>& - operator<<(std::basic_ostream<_CharT, _Traits>&, - const arcsine_distribution<_RealType1>&); - - /** - * @brief Extracts a %arcsine_distribution random number distribution - * @p __x from the input stream @p __is. - * - * @param __is An input stream. - * @param __x A %arcsine_distribution random number - * generator engine. - * - * @returns The input stream with @p __x extracted or in an error state. - */ - template<typename _RealType1, typename _CharT, typename _Traits> - friend std::basic_istream<_CharT, _Traits>& - operator>>(std::basic_istream<_CharT, _Traits>&, - arcsine_distribution<_RealType1>&); - - private: - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate_impl(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng, - const param_type& __p); - - param_type _M_param; - - std::uniform_real_distribution<result_type> _M_ud; - }; - - /** - * @brief Return true if two arcsine distributions are not equal. - */ - template<typename _RealType> - inline bool - operator!=(const arcsine_distribution<_RealType>& __d1, - const arcsine_distribution<_RealType>& __d2) - { return !(__d1 == __d2); } - - - /** - * @brief A Hoyt continuous distribution for random numbers. - * - * The formula for the Hoyt probability density function is - * @f[ - * p(x|q,\omega) = \frac{(1 + q^2)x}{q\omega} - * \exp\left(-\frac{(1 + q^2)^2 x^2}{4 q^2 \omega}\right) - * I_0\left(\frac{(1 - q^4) x^2}{4 q^2 \omega}\right) - * @f] - * where @f$I_0(z)@f$ is the modified Bessel function of the first kind - * of order 0 and @f$0 < q < 1@f$. - * - * <table border=1 cellpadding=10 cellspacing=0> - * <caption align=top>Distribution Statistics</caption> - * <tr><td>Mean</td><td>@f$ \sqrt{\frac{2}{\pi}} \sqrt{\frac{\omega}{1 + q^2}} - * E(1 - q^2) @f$</td></tr> - * <tr><td>Variance</td><td>@f$ \omega \left(1 - \frac{2E^2(1 - q^2)} - * {\pi (1 + q^2)}\right) @f$</td></tr> - * <tr><td>Range</td><td>@f$[0, \infty)@f$</td></tr> - * </table> - * where @f$E(x)@f$ is the elliptic function of the second kind. - */ - template<typename _RealType = double> - class - hoyt_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 hoyt_distribution<result_type> distribution_type; - - param_type(result_type __q = result_type(0.5L), - result_type __omega = result_type(1)) - : _M_q(__q), _M_omega(__omega) - { - _GLIBCXX_DEBUG_ASSERT(_M_q > result_type(0)); - _GLIBCXX_DEBUG_ASSERT(_M_q < result_type(1)); - } - - result_type - q() const - { return _M_q; } - - result_type - omega() const - { return _M_omega; } - - friend bool - operator==(const param_type& __p1, const param_type& __p2) - { return __p1._M_q == __p2._M_q - && __p1._M_omega == __p2._M_omega; } - - private: - void _M_initialize(); - - result_type _M_q; - result_type _M_omega; - }; - - /** - * @brief Constructors. - */ - explicit - hoyt_distribution(result_type __q = result_type(0.5L), - result_type __omega = result_type(1)) - : _M_param(__q, __omega), - _M_ad(result_type(0.5L) * (result_type(1) + __q * __q), - result_type(0.5L) * (result_type(1) + __q * __q) - / (__q * __q)), - _M_ed(result_type(1)) - { } - - explicit - hoyt_distribution(const param_type& __p) - : _M_param(__p), - _M_ad(result_type(0.5L) * (result_type(1) + __p.q() * __p.q()), - result_type(0.5L) * (result_type(1) + __p.q() * __p.q()) - / (__p.q() * __p.q())), - _M_ed(result_type(1)) - { } - - /** - * @brief Resets the distribution state. - */ - void - reset() - { - _M_ad.reset(); - _M_ed.reset(); - } - - /** - * @brief Return the parameters of the distribution. - */ - result_type - q() const - { return _M_param.q(); } - - result_type - omega() const - { return _M_param.omega(); } - - /** - * @brief Returns the parameter set of the distribution. - */ - param_type - param() const - { return _M_param; } - - /** - * @brief Sets the parameter set of the distribution. - * @param __param The new parameter set of the distribution. - */ - void - param(const param_type& __param) - { _M_param = __param; } - - /** - * @brief Returns the greatest lower bound value of the distribution. - */ - result_type - min() const - { return result_type(0); } - - /** - * @brief Returns the least upper bound value of the distribution. - */ - result_type - max() const - { return std::numeric_limits<result_type>::max(); } - - /** - * @brief Generating functions. - */ - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng); - - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng, - const param_type& __p); - - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng) - { this->__generate(__f, __t, __urng, _M_param); } - - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng, - const param_type& __p) - { this->__generate_impl(__f, __t, __urng, __p); } - - template<typename _UniformRandomNumberGenerator> - void - __generate(result_type* __f, result_type* __t, - _UniformRandomNumberGenerator& __urng, - const param_type& __p) - { this->__generate_impl(__f, __t, __urng, __p); } - - /** - * @brief Return true if two Hoyt distributions have - * the same parameters and the sequences that would - * be generated are equal. - */ - friend bool - operator==(const hoyt_distribution& __d1, - const hoyt_distribution& __d2) - { return (__d1._M_param == __d2._M_param - && __d1._M_ad == __d2._M_ad - && __d1._M_ed == __d2._M_ed); } - - /** - * @brief Inserts a %hoyt_distribution random number distribution - * @p __x into the output stream @p __os. - * - * @param __os An output stream. - * @param __x A %hoyt_distribution random number distribution. - * - * @returns The output stream with the state of @p __x inserted or in - * an error state. - */ - template<typename _RealType1, typename _CharT, typename _Traits> - friend std::basic_ostream<_CharT, _Traits>& - operator<<(std::basic_ostream<_CharT, _Traits>&, - const hoyt_distribution<_RealType1>&); - - /** - * @brief Extracts a %hoyt_distribution random number distribution - * @p __x from the input stream @p __is. - * - * @param __is An input stream. - * @param __x A %hoyt_distribution random number - * generator engine. - * - * @returns The input stream with @p __x extracted or in an error state. - */ - template<typename _RealType1, typename _CharT, typename _Traits> - friend std::basic_istream<_CharT, _Traits>& - operator>>(std::basic_istream<_CharT, _Traits>&, - hoyt_distribution<_RealType1>&); - - private: - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate_impl(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng, - const param_type& __p); - - param_type _M_param; - - __gnu_cxx::arcsine_distribution<result_type> _M_ad; - std::exponential_distribution<result_type> _M_ed; - }; - - /** - * @brief Return true if two Hoyt distributions are not equal. - */ - template<typename _RealType> - inline bool - operator!=(const hoyt_distribution<_RealType>& __d1, - const hoyt_distribution<_RealType>& __d2) - { return !(__d1 == __d2); } - - - /** - * @brief A triangular distribution for random numbers. - * - * The formula for the triangular probability density function is - * @f[ - * / 0 for x < a - * p(x|a,b,c) = | \frac{2(x-a)}{(c-a)(b-a)} for a <= x <= b - * | \frac{2(c-x)}{(c-a)(c-b)} for b < x <= c - * \ 0 for c < x - * @f] - * - * <table border=1 cellpadding=10 cellspacing=0> - * <caption align=top>Distribution Statistics</caption> - * <tr><td>Mean</td><td>@f$ \frac{a+b+c}{2} @f$</td></tr> - * <tr><td>Variance</td><td>@f$ \frac{a^2+b^2+c^2-ab-ac-bc} - * {18}@f$</td></tr> - * <tr><td>Range</td><td>@f$[a, c]@f$</td></tr> - * </table> - */ - template<typename _RealType = double> - class triangular_distribution - { - static_assert(std::is_floating_point<_RealType>::value, - "template argument not a floating point type"); - - public: - /** The type of the range of the distribution. */ - typedef _RealType result_type; - /** Parameter type. */ - struct param_type - { - friend class triangular_distribution<_RealType>; - - explicit - param_type(_RealType __a = _RealType(0), - _RealType __b = _RealType(0.5), - _RealType __c = _RealType(1)) - : _M_a(__a), _M_b(__b), _M_c(__c) - { - _GLIBCXX_DEBUG_ASSERT(_M_a <= _M_b); - _GLIBCXX_DEBUG_ASSERT(_M_b <= _M_c); - _GLIBCXX_DEBUG_ASSERT(_M_a < _M_c); - - _M_r_ab = (_M_b - _M_a) / (_M_c - _M_a); - _M_f_ab_ac = (_M_b - _M_a) * (_M_c - _M_a); - _M_f_bc_ac = (_M_c - _M_b) * (_M_c - _M_a); - } - - _RealType - a() const - { return _M_a; } - - _RealType - b() const - { return _M_b; } - - _RealType - c() const - { return _M_c; } - - friend bool - operator==(const param_type& __p1, const param_type& __p2) - { return (__p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b - && __p1._M_c == __p2._M_c); } - - private: - - _RealType _M_a; - _RealType _M_b; - _RealType _M_c; - _RealType _M_r_ab; - _RealType _M_f_ab_ac; - _RealType _M_f_bc_ac; - }; - - /** - * @brief Constructs a triangle distribution with parameters - * @f$ a @f$, @f$ b @f$ and @f$ c @f$. - */ - explicit - triangular_distribution(result_type __a = result_type(0), - result_type __b = result_type(0.5), - result_type __c = result_type(1)) - : _M_param(__a, __b, __c) - { } - - explicit - triangular_distribution(const param_type& __p) - : _M_param(__p) - { } - - /** - * @brief Resets the distribution state. - */ - void - reset() - { } - - /** - * @brief Returns the @f$ a @f$ of the distribution. - */ - result_type - a() const - { return _M_param.a(); } - - /** - * @brief Returns the @f$ b @f$ of the distribution. - */ - result_type - b() const - { return _M_param.b(); } - - /** - * @brief Returns the @f$ c @f$ of the distribution. - */ - result_type - c() const - { return _M_param.c(); } - - /** - * @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_a; } - - /** - * @brief Returns the least upper bound value of the distribution. - */ - result_type - max() const - { return _M_param._M_c; } - - /** - * @brief Generating functions. - */ - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng) - { return this->operator()(__urng, _M_param); } - - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng, - const param_type& __p) - { - std::__detail::_Adaptor<_UniformRandomNumberGenerator, result_type> - __aurng(__urng); - result_type __rnd = __aurng(); - if (__rnd <= __p._M_r_ab) - return __p.a() + std::sqrt(__rnd * __p._M_f_ab_ac); - else - return __p.c() - std::sqrt((result_type(1) - __rnd) - * __p._M_f_bc_ac); - } - - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng) - { this->__generate(__f, __t, __urng, _M_param); } - - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng, - const param_type& __p) - { this->__generate_impl(__f, __t, __urng, __p); } - - template<typename _UniformRandomNumberGenerator> - void - __generate(result_type* __f, result_type* __t, - _UniformRandomNumberGenerator& __urng, - const param_type& __p) - { this->__generate_impl(__f, __t, __urng, __p); } - - /** - * @brief Return true if two triangle distributions have the same - * parameters and the sequences that would be generated - * are equal. - */ - friend bool - operator==(const triangular_distribution& __d1, - const triangular_distribution& __d2) - { return __d1._M_param == __d2._M_param; } - - /** - * @brief Inserts a %triangular_distribution random number distribution - * @p __x into the output stream @p __os. - * - * @param __os An output stream. - * @param __x A %triangular_distribution random number distribution. - * - * @returns The output stream with the state of @p __x inserted or in - * an error state. - */ - template<typename _RealType1, typename _CharT, typename _Traits> - friend std::basic_ostream<_CharT, _Traits>& - operator<<(std::basic_ostream<_CharT, _Traits>& __os, - const __gnu_cxx::triangular_distribution<_RealType1>& __x); - - /** - * @brief Extracts a %triangular_distribution random number distribution - * @p __x from the input stream @p __is. - * - * @param __is An input stream. - * @param __x A %triangular_distribution random number generator engine. - * - * @returns The input stream with @p __x extracted or in an error state. - */ - template<typename _RealType1, typename _CharT, typename _Traits> - friend std::basic_istream<_CharT, _Traits>& - operator>>(std::basic_istream<_CharT, _Traits>& __is, - __gnu_cxx::triangular_distribution<_RealType1>& __x); - - private: - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate_impl(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng, - const param_type& __p); - - param_type _M_param; - }; - - /** - * @brief Return true if two triangle distributions are different. - */ - template<typename _RealType> - inline bool - operator!=(const __gnu_cxx::triangular_distribution<_RealType>& __d1, - const __gnu_cxx::triangular_distribution<_RealType>& __d2) - { return !(__d1 == __d2); } - - - /** - * @brief A von Mises distribution for random numbers. - * - * The formula for the von Mises probability density function is - * @f[ - * p(x|\mu,\kappa) = \frac{e^{\kappa \cos(x-\mu)}} - * {2\pi I_0(\kappa)} - * @f] - * - * The generating functions use the method according to: - * - * D. J. Best and N. I. Fisher, 1979. "Efficient Simulation of the - * von Mises Distribution", Journal of the Royal Statistical Society. - * Series C (Applied Statistics), Vol. 28, No. 2, pp. 152-157. - * - * <table border=1 cellpadding=10 cellspacing=0> - * <caption align=top>Distribution Statistics</caption> - * <tr><td>Mean</td><td>@f$ \mu @f$</td></tr> - * <tr><td>Variance</td><td>@f$ 1-I_1(\kappa)/I_0(\kappa) @f$</td></tr> - * <tr><td>Range</td><td>@f$[-\pi, \pi]@f$</td></tr> - * </table> - */ - template<typename _RealType = double> - class von_mises_distribution - { - static_assert(std::is_floating_point<_RealType>::value, - "template argument not a floating point type"); - - public: - /** The type of the range of the distribution. */ - typedef _RealType result_type; - /** Parameter type. */ - struct param_type - { - friend class von_mises_distribution<_RealType>; - - explicit - param_type(_RealType __mu = _RealType(0), - _RealType __kappa = _RealType(1)) - : _M_mu(__mu), _M_kappa(__kappa) - { - const _RealType __pi = __gnu_cxx::__math_constants<_RealType>::__pi; - _GLIBCXX_DEBUG_ASSERT(_M_mu >= -__pi && _M_mu <= __pi); - _GLIBCXX_DEBUG_ASSERT(_M_kappa >= _RealType(0)); - - auto __tau = std::sqrt(_RealType(4) * _M_kappa * _M_kappa - + _RealType(1)) + _RealType(1); - auto __rho = ((__tau - std::sqrt(_RealType(2) * __tau)) - / (_RealType(2) * _M_kappa)); - _M_r = (_RealType(1) + __rho * __rho) / (_RealType(2) * __rho); - } - - _RealType - mu() const - { return _M_mu; } - - _RealType - kappa() const - { return _M_kappa; } - - friend bool - operator==(const param_type& __p1, const param_type& __p2) - { return (__p1._M_mu == __p2._M_mu - && __p1._M_kappa == __p2._M_kappa); } - - private: - _RealType _M_mu; - _RealType _M_kappa; - _RealType _M_r; - }; - - /** - * @brief Constructs a von Mises distribution with parameters - * @f$\mu@f$ and @f$\kappa@f$. - */ - explicit - von_mises_distribution(result_type __mu = result_type(0), - result_type __kappa = result_type(1)) - : _M_param(__mu, __kappa) - { } - - explicit - von_mises_distribution(const param_type& __p) - : _M_param(__p) - { } - - /** - * @brief Resets the distribution state. - */ - void - reset() - { } - - /** - * @brief Returns the @f$ \mu @f$ of the distribution. - */ - result_type - mu() const - { return _M_param.mu(); } - - /** - * @brief Returns the @f$ \kappa @f$ of the distribution. - */ - result_type - kappa() const - { return _M_param.kappa(); } - - /** - * @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 -__gnu_cxx::__math_constants<result_type>::__pi; - } - - /** - * @brief Returns the least upper bound value of the distribution. - */ - result_type - max() const - { - return __gnu_cxx::__math_constants<result_type>::__pi; - } - - /** - * @brief Generating functions. - */ - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng) - { return this->operator()(__urng, _M_param); } - - template<typename _UniformRandomNumberGenerator> - result_type - operator()(_UniformRandomNumberGenerator& __urng, - const param_type& __p) - { - const result_type __pi - = __gnu_cxx::__math_constants<result_type>::__pi; - std::__detail::_Adaptor<_UniformRandomNumberGenerator, result_type> - __aurng(__urng); - - result_type __f; - while (1) - { - result_type __rnd = std::cos(__pi * __aurng()); - __f = (result_type(1) + __p._M_r * __rnd) / (__p._M_r + __rnd); - result_type __c = __p._M_kappa * (__p._M_r - __f); - - result_type __rnd2 = __aurng(); - if (__c * (result_type(2) - __c) > __rnd2) - break; - if (std::log(__c / __rnd2) >= __c - result_type(1)) - break; - } - - result_type __res = std::acos(__f); -#if _GLIBCXX_USE_C99_MATH_TR1 - __res = std::copysign(__res, __aurng() - result_type(0.5)); -#else - if (__aurng() < result_type(0.5)) - __res = -__res; -#endif - __res += __p._M_mu; - if (__res > __pi) - __res -= result_type(2) * __pi; - else if (__res < -__pi) - __res += result_type(2) * __pi; - return __res; - } - - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng) - { this->__generate(__f, __t, __urng, _M_param); } - - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng, - const param_type& __p) - { this->__generate_impl(__f, __t, __urng, __p); } - - template<typename _UniformRandomNumberGenerator> - void - __generate(result_type* __f, result_type* __t, - _UniformRandomNumberGenerator& __urng, - const param_type& __p) - { this->__generate_impl(__f, __t, __urng, __p); } - - /** - * @brief Return true if two von Mises distributions have the same - * parameters and the sequences that would be generated - * are equal. - */ - friend bool - operator==(const von_mises_distribution& __d1, - const von_mises_distribution& __d2) - { return __d1._M_param == __d2._M_param; } - - /** - * @brief Inserts a %von_mises_distribution random number distribution - * @p __x into the output stream @p __os. - * - * @param __os An output stream. - * @param __x A %von_mises_distribution random number distribution. - * - * @returns The output stream with the state of @p __x inserted or in - * an error state. - */ - template<typename _RealType1, typename _CharT, typename _Traits> - friend std::basic_ostream<_CharT, _Traits>& - operator<<(std::basic_ostream<_CharT, _Traits>& __os, - const __gnu_cxx::von_mises_distribution<_RealType1>& __x); - - /** - * @brief Extracts a %von_mises_distribution random number distribution - * @p __x from the input stream @p __is. - * - * @param __is An input stream. - * @param __x A %von_mises_distribution random number generator engine. - * - * @returns The input stream with @p __x extracted or in an error state. - */ - template<typename _RealType1, typename _CharT, typename _Traits> - friend std::basic_istream<_CharT, _Traits>& - operator>>(std::basic_istream<_CharT, _Traits>& __is, - __gnu_cxx::von_mises_distribution<_RealType1>& __x); - - private: - template<typename _ForwardIterator, - typename _UniformRandomNumberGenerator> - void - __generate_impl(_ForwardIterator __f, _ForwardIterator __t, - _UniformRandomNumberGenerator& __urng, - const param_type& __p); - - param_type _M_param; - }; - - /** - * @brief Return true if two von Mises distributions are different. - */ - template<typename _RealType> - inline bool - operator!=(const __gnu_cxx::von_mises_distribution<_RealType>& __d1, - const __gnu_cxx::von_mises_distribution<_RealType>& __d2) - { return !(__d1 == __d2); } - -_GLIBCXX_END_NAMESPACE_VERSION -} // namespace __gnu_cxx - -#include "opt_random.h" -#include "random.tcc" - -#endif // _GLIBCXX_USE_C99_STDINT_TR1 - -#endif // C++11 - -#endif // _EXT_RANDOM |