[1166] | 1 | // Random number extensions -*- C++ -*-
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| 2 |
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| 3 | // Copyright (C) 2012-2021 Free Software Foundation, Inc.
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| 4 | //
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| 5 | // This file is part of the GNU ISO C++ Library. This library is free
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| 6 | // software; you can redistribute it and/or modify it under the
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| 7 | // terms of the GNU General Public License as published by the
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| 8 | // Free Software Foundation; either version 3, or (at your option)
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| 9 | // any later version.
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| 10 |
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| 11 | // This library is distributed in the hope that it will be useful,
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| 12 | // but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 13 | // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 14 | // GNU General Public License for more details.
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| 15 |
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| 16 | // Under Section 7 of GPL version 3, you are granted additional
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| 17 | // permissions described in the GCC Runtime Library Exception, version
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| 18 | // 3.1, as published by the Free Software Foundation.
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| 19 |
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| 20 | // You should have received a copy of the GNU General Public License and
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| 21 | // a copy of the GCC Runtime Library Exception along with this program;
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| 22 | // see the files COPYING3 and COPYING.RUNTIME respectively. If not, see
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| 23 | // <http://www.gnu.org/licenses/>.
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| 24 |
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| 25 | /** @file ext/random
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| 26 | * This file is a GNU extension to the Standard C++ Library.
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| 27 | */
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| 28 |
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| 29 | #ifndef _EXT_RANDOM
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| 30 | #define _EXT_RANDOM 1
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| 31 |
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| 32 | #pragma GCC system_header
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| 33 |
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| 34 | #if __cplusplus < 201103L
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| 35 | # include <bits/c++0x_warning.h>
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| 36 | #else
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| 37 |
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| 38 | #include <random>
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| 39 | #include <algorithm>
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| 40 | #include <array>
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| 41 | #include <ext/cmath>
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| 42 | #ifdef __SSE2__
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| 43 | # include <emmintrin.h>
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| 44 | #endif
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| 45 |
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| 46 | #if defined(_GLIBCXX_USE_C99_STDINT_TR1) && defined(UINT32_C)
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| 47 |
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| 48 | namespace __gnu_cxx _GLIBCXX_VISIBILITY(default)
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| 49 | {
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| 50 | _GLIBCXX_BEGIN_NAMESPACE_VERSION
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| 51 |
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| 52 | #if __BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__
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| 53 |
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| 54 | /* Mersenne twister implementation optimized for vector operations.
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| 55 | *
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| 56 | * Reference: http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/SFMT/
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| 57 | */
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| 58 | template<typename _UIntType, size_t __m,
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| 59 | size_t __pos1, size_t __sl1, size_t __sl2,
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| 60 | size_t __sr1, size_t __sr2,
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| 61 | uint32_t __msk1, uint32_t __msk2,
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| 62 | uint32_t __msk3, uint32_t __msk4,
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| 63 | uint32_t __parity1, uint32_t __parity2,
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| 64 | uint32_t __parity3, uint32_t __parity4>
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| 65 | class simd_fast_mersenne_twister_engine
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| 66 | {
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| 67 | static_assert(std::is_unsigned<_UIntType>::value, "template argument "
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| 68 | "substituting _UIntType not an unsigned integral type");
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| 69 | static_assert(__sr1 < 32, "first right shift too large");
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| 70 | static_assert(__sr2 < 16, "second right shift too large");
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| 71 | static_assert(__sl1 < 32, "first left shift too large");
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| 72 | static_assert(__sl2 < 16, "second left shift too large");
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| 73 |
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| 74 | public:
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| 75 | typedef _UIntType result_type;
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| 76 |
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| 77 | private:
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| 78 | static constexpr size_t m_w = sizeof(result_type) * 8;
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| 79 | static constexpr size_t _M_nstate = __m / 128 + 1;
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| 80 | static constexpr size_t _M_nstate32 = _M_nstate * 4;
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| 81 |
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| 82 | static_assert(std::is_unsigned<_UIntType>::value, "template argument "
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| 83 | "substituting _UIntType not an unsigned integral type");
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| 84 | static_assert(__pos1 < _M_nstate, "POS1 not smaller than state size");
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| 85 | static_assert(16 % sizeof(_UIntType) == 0,
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| 86 | "UIntType size must divide 16");
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| 87 |
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| 88 | template<typename _Sseq>
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| 89 | using _If_seed_seq
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| 90 | = typename std::enable_if<std::__detail::__is_seed_seq<
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| 91 | _Sseq, simd_fast_mersenne_twister_engine, result_type>::value
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| 92 | >::type;
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| 93 |
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| 94 | public:
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| 95 | static constexpr size_t state_size = _M_nstate * (16
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| 96 | / sizeof(result_type));
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| 97 | static constexpr result_type default_seed = 5489u;
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| 98 |
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| 99 | // constructors and member functions
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| 100 |
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| 101 | simd_fast_mersenne_twister_engine()
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| 102 | : simd_fast_mersenne_twister_engine(default_seed)
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| 103 | { }
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| 104 |
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| 105 | explicit
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| 106 | simd_fast_mersenne_twister_engine(result_type __sd)
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| 107 | { seed(__sd); }
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| 108 |
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| 109 | template<typename _Sseq, typename = _If_seed_seq<_Sseq>>
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| 110 | explicit
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| 111 | simd_fast_mersenne_twister_engine(_Sseq& __q)
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| 112 | { seed(__q); }
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| 113 |
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| 114 | void
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| 115 | seed(result_type __sd = default_seed);
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| 116 |
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| 117 | template<typename _Sseq>
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| 118 | _If_seed_seq<_Sseq>
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| 119 | seed(_Sseq& __q);
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| 120 |
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| 121 | static constexpr result_type
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| 122 | min()
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| 123 | { return 0; }
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| 124 |
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| 125 | static constexpr result_type
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| 126 | max()
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| 127 | { return std::numeric_limits<result_type>::max(); }
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| 128 |
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| 129 | void
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| 130 | discard(unsigned long long __z);
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| 131 |
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| 132 | result_type
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| 133 | operator()()
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| 134 | {
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| 135 | if (__builtin_expect(_M_pos >= state_size, 0))
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| 136 | _M_gen_rand();
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| 137 |
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| 138 | return _M_stateT[_M_pos++];
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| 139 | }
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| 140 |
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| 141 | template<typename _UIntType_2, size_t __m_2,
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| 142 | size_t __pos1_2, size_t __sl1_2, size_t __sl2_2,
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| 143 | size_t __sr1_2, size_t __sr2_2,
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| 144 | uint32_t __msk1_2, uint32_t __msk2_2,
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| 145 | uint32_t __msk3_2, uint32_t __msk4_2,
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| 146 | uint32_t __parity1_2, uint32_t __parity2_2,
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| 147 | uint32_t __parity3_2, uint32_t __parity4_2>
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| 148 | friend bool
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| 149 | operator==(const simd_fast_mersenne_twister_engine<_UIntType_2,
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| 150 | __m_2, __pos1_2, __sl1_2, __sl2_2, __sr1_2, __sr2_2,
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| 151 | __msk1_2, __msk2_2, __msk3_2, __msk4_2,
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| 152 | __parity1_2, __parity2_2, __parity3_2, __parity4_2>& __lhs,
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| 153 | const simd_fast_mersenne_twister_engine<_UIntType_2,
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| 154 | __m_2, __pos1_2, __sl1_2, __sl2_2, __sr1_2, __sr2_2,
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| 155 | __msk1_2, __msk2_2, __msk3_2, __msk4_2,
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| 156 | __parity1_2, __parity2_2, __parity3_2, __parity4_2>& __rhs);
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| 157 |
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| 158 | template<typename _UIntType_2, size_t __m_2,
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| 159 | size_t __pos1_2, size_t __sl1_2, size_t __sl2_2,
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| 160 | size_t __sr1_2, size_t __sr2_2,
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| 161 | uint32_t __msk1_2, uint32_t __msk2_2,
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| 162 | uint32_t __msk3_2, uint32_t __msk4_2,
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| 163 | uint32_t __parity1_2, uint32_t __parity2_2,
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| 164 | uint32_t __parity3_2, uint32_t __parity4_2,
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| 165 | typename _CharT, typename _Traits>
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| 166 | friend std::basic_ostream<_CharT, _Traits>&
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| 167 | operator<<(std::basic_ostream<_CharT, _Traits>& __os,
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| 168 | const __gnu_cxx::simd_fast_mersenne_twister_engine
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| 169 | <_UIntType_2,
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| 170 | __m_2, __pos1_2, __sl1_2, __sl2_2, __sr1_2, __sr2_2,
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| 171 | __msk1_2, __msk2_2, __msk3_2, __msk4_2,
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| 172 | __parity1_2, __parity2_2, __parity3_2, __parity4_2>& __x);
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| 173 |
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| 174 | template<typename _UIntType_2, size_t __m_2,
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| 175 | size_t __pos1_2, size_t __sl1_2, size_t __sl2_2,
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| 176 | size_t __sr1_2, size_t __sr2_2,
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| 177 | uint32_t __msk1_2, uint32_t __msk2_2,
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| 178 | uint32_t __msk3_2, uint32_t __msk4_2,
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| 179 | uint32_t __parity1_2, uint32_t __parity2_2,
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| 180 | uint32_t __parity3_2, uint32_t __parity4_2,
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| 181 | typename _CharT, typename _Traits>
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| 182 | friend std::basic_istream<_CharT, _Traits>&
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| 183 | operator>>(std::basic_istream<_CharT, _Traits>& __is,
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| 184 | __gnu_cxx::simd_fast_mersenne_twister_engine<_UIntType_2,
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| 185 | __m_2, __pos1_2, __sl1_2, __sl2_2, __sr1_2, __sr2_2,
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| 186 | __msk1_2, __msk2_2, __msk3_2, __msk4_2,
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| 187 | __parity1_2, __parity2_2, __parity3_2, __parity4_2>& __x);
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| 188 |
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| 189 | private:
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| 190 | union
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| 191 | {
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| 192 | #ifdef __SSE2__
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| 193 | __m128i _M_state[_M_nstate];
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| 194 | #endif
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| 195 | #ifdef __ARM_NEON
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| 196 | #ifdef __aarch64__
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| 197 | __Uint32x4_t _M_state[_M_nstate];
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| 198 | #endif
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| 199 | #endif
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| 200 | uint32_t _M_state32[_M_nstate32];
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| 201 | result_type _M_stateT[state_size];
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| 202 | } __attribute__ ((__aligned__ (16)));
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| 203 | size_t _M_pos;
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| 204 |
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| 205 | void _M_gen_rand(void);
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| 206 | void _M_period_certification();
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| 207 | };
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| 208 |
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| 209 |
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| 210 | template<typename _UIntType, size_t __m,
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| 211 | size_t __pos1, size_t __sl1, size_t __sl2,
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| 212 | size_t __sr1, size_t __sr2,
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| 213 | uint32_t __msk1, uint32_t __msk2,
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| 214 | uint32_t __msk3, uint32_t __msk4,
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| 215 | uint32_t __parity1, uint32_t __parity2,
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| 216 | uint32_t __parity3, uint32_t __parity4>
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| 217 | inline bool
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| 218 | operator!=(const __gnu_cxx::simd_fast_mersenne_twister_engine<_UIntType,
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| 219 | __m, __pos1, __sl1, __sl2, __sr1, __sr2, __msk1, __msk2, __msk3,
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| 220 | __msk4, __parity1, __parity2, __parity3, __parity4>& __lhs,
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| 221 | const __gnu_cxx::simd_fast_mersenne_twister_engine<_UIntType,
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| 222 | __m, __pos1, __sl1, __sl2, __sr1, __sr2, __msk1, __msk2, __msk3,
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| 223 | __msk4, __parity1, __parity2, __parity3, __parity4>& __rhs)
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| 224 | { return !(__lhs == __rhs); }
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| 225 |
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| 226 |
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| 227 | /* Definitions for the SIMD-oriented Fast Mersenne Twister as defined
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| 228 | * in the C implementation by Daito and Matsumoto, as both a 32-bit
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| 229 | * and 64-bit version.
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| 230 | */
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| 231 | typedef simd_fast_mersenne_twister_engine<uint32_t, 607, 2,
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| 232 | 15, 3, 13, 3,
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| 233 | 0xfdff37ffU, 0xef7f3f7dU,
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| 234 | 0xff777b7dU, 0x7ff7fb2fU,
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| 235 | 0x00000001U, 0x00000000U,
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| 236 | 0x00000000U, 0x5986f054U>
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| 237 | sfmt607;
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| 238 |
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| 239 | typedef simd_fast_mersenne_twister_engine<uint64_t, 607, 2,
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| 240 | 15, 3, 13, 3,
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| 241 | 0xfdff37ffU, 0xef7f3f7dU,
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| 242 | 0xff777b7dU, 0x7ff7fb2fU,
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| 243 | 0x00000001U, 0x00000000U,
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| 244 | 0x00000000U, 0x5986f054U>
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| 245 | sfmt607_64;
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| 246 |
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| 247 |
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| 248 | typedef simd_fast_mersenne_twister_engine<uint32_t, 1279, 7,
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| 249 | 14, 3, 5, 1,
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| 250 | 0xf7fefffdU, 0x7fefcfffU,
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| 251 | 0xaff3ef3fU, 0xb5ffff7fU,
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| 252 | 0x00000001U, 0x00000000U,
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| 253 | 0x00000000U, 0x20000000U>
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| 254 | sfmt1279;
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| 255 |
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| 256 | typedef simd_fast_mersenne_twister_engine<uint64_t, 1279, 7,
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| 257 | 14, 3, 5, 1,
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| 258 | 0xf7fefffdU, 0x7fefcfffU,
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| 259 | 0xaff3ef3fU, 0xb5ffff7fU,
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| 260 | 0x00000001U, 0x00000000U,
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| 261 | 0x00000000U, 0x20000000U>
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| 262 | sfmt1279_64;
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| 263 |
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| 264 |
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| 265 | typedef simd_fast_mersenne_twister_engine<uint32_t, 2281, 12,
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| 266 | 19, 1, 5, 1,
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| 267 | 0xbff7ffbfU, 0xfdfffffeU,
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| 268 | 0xf7ffef7fU, 0xf2f7cbbfU,
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| 269 | 0x00000001U, 0x00000000U,
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| 270 | 0x00000000U, 0x41dfa600U>
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| 271 | sfmt2281;
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| 272 |
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| 273 | typedef simd_fast_mersenne_twister_engine<uint64_t, 2281, 12,
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| 274 | 19, 1, 5, 1,
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| 275 | 0xbff7ffbfU, 0xfdfffffeU,
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| 276 | 0xf7ffef7fU, 0xf2f7cbbfU,
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| 277 | 0x00000001U, 0x00000000U,
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| 278 | 0x00000000U, 0x41dfa600U>
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| 279 | sfmt2281_64;
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| 280 |
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| 281 |
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| 282 | typedef simd_fast_mersenne_twister_engine<uint32_t, 4253, 17,
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| 283 | 20, 1, 7, 1,
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| 284 | 0x9f7bffffU, 0x9fffff5fU,
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| 285 | 0x3efffffbU, 0xfffff7bbU,
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| 286 | 0xa8000001U, 0xaf5390a3U,
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| 287 | 0xb740b3f8U, 0x6c11486dU>
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| 288 | sfmt4253;
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| 289 |
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| 290 | typedef simd_fast_mersenne_twister_engine<uint64_t, 4253, 17,
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| 291 | 20, 1, 7, 1,
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| 292 | 0x9f7bffffU, 0x9fffff5fU,
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| 293 | 0x3efffffbU, 0xfffff7bbU,
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| 294 | 0xa8000001U, 0xaf5390a3U,
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| 295 | 0xb740b3f8U, 0x6c11486dU>
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| 296 | sfmt4253_64;
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| 297 |
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| 298 |
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| 299 | typedef simd_fast_mersenne_twister_engine<uint32_t, 11213, 68,
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| 300 | 14, 3, 7, 3,
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| 301 | 0xeffff7fbU, 0xffffffefU,
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| 302 | 0xdfdfbfffU, 0x7fffdbfdU,
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| 303 | 0x00000001U, 0x00000000U,
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| 304 | 0xe8148000U, 0xd0c7afa3U>
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| 305 | sfmt11213;
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| 306 |
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| 307 | typedef simd_fast_mersenne_twister_engine<uint64_t, 11213, 68,
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| 308 | 14, 3, 7, 3,
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| 309 | 0xeffff7fbU, 0xffffffefU,
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| 310 | 0xdfdfbfffU, 0x7fffdbfdU,
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| 311 | 0x00000001U, 0x00000000U,
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| 312 | 0xe8148000U, 0xd0c7afa3U>
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| 313 | sfmt11213_64;
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| 314 |
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| 315 |
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| 316 | typedef simd_fast_mersenne_twister_engine<uint32_t, 19937, 122,
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| 317 | 18, 1, 11, 1,
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| 318 | 0xdfffffefU, 0xddfecb7fU,
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| 319 | 0xbffaffffU, 0xbffffff6U,
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| 320 | 0x00000001U, 0x00000000U,
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| 321 | 0x00000000U, 0x13c9e684U>
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| 322 | sfmt19937;
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| 323 |
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| 324 | typedef simd_fast_mersenne_twister_engine<uint64_t, 19937, 122,
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| 325 | 18, 1, 11, 1,
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| 326 | 0xdfffffefU, 0xddfecb7fU,
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| 327 | 0xbffaffffU, 0xbffffff6U,
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| 328 | 0x00000001U, 0x00000000U,
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| 329 | 0x00000000U, 0x13c9e684U>
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| 330 | sfmt19937_64;
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| 331 |
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| 332 |
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| 333 | typedef simd_fast_mersenne_twister_engine<uint32_t, 44497, 330,
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| 334 | 5, 3, 9, 3,
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| 335 | 0xeffffffbU, 0xdfbebfffU,
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| 336 | 0xbfbf7befU, 0x9ffd7bffU,
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| 337 | 0x00000001U, 0x00000000U,
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| 338 | 0xa3ac4000U, 0xecc1327aU>
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| 339 | sfmt44497;
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| 340 |
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| 341 | typedef simd_fast_mersenne_twister_engine<uint64_t, 44497, 330,
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| 342 | 5, 3, 9, 3,
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| 343 | 0xeffffffbU, 0xdfbebfffU,
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| 344 | 0xbfbf7befU, 0x9ffd7bffU,
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| 345 | 0x00000001U, 0x00000000U,
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| 346 | 0xa3ac4000U, 0xecc1327aU>
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| 347 | sfmt44497_64;
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| 348 |
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| 349 |
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| 350 | typedef simd_fast_mersenne_twister_engine<uint32_t, 86243, 366,
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| 351 | 6, 7, 19, 1,
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| 352 | 0xfdbffbffU, 0xbff7ff3fU,
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| 353 | 0xfd77efffU, 0xbf9ff3ffU,
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| 354 | 0x00000001U, 0x00000000U,
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| 355 | 0x00000000U, 0xe9528d85U>
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| 356 | sfmt86243;
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| 357 |
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| 358 | typedef simd_fast_mersenne_twister_engine<uint64_t, 86243, 366,
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| 359 | 6, 7, 19, 1,
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| 360 | 0xfdbffbffU, 0xbff7ff3fU,
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| 361 | 0xfd77efffU, 0xbf9ff3ffU,
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| 362 | 0x00000001U, 0x00000000U,
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| 363 | 0x00000000U, 0xe9528d85U>
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| 364 | sfmt86243_64;
|
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| 365 |
|
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| 366 |
|
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| 367 | typedef simd_fast_mersenne_twister_engine<uint32_t, 132049, 110,
|
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| 368 | 19, 1, 21, 1,
|
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| 369 | 0xffffbb5fU, 0xfb6ebf95U,
|
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| 370 | 0xfffefffaU, 0xcff77fffU,
|
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| 371 | 0x00000001U, 0x00000000U,
|
---|
| 372 | 0xcb520000U, 0xc7e91c7dU>
|
---|
| 373 | sfmt132049;
|
---|
| 374 |
|
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| 375 | typedef simd_fast_mersenne_twister_engine<uint64_t, 132049, 110,
|
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| 376 | 19, 1, 21, 1,
|
---|
| 377 | 0xffffbb5fU, 0xfb6ebf95U,
|
---|
| 378 | 0xfffefffaU, 0xcff77fffU,
|
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| 379 | 0x00000001U, 0x00000000U,
|
---|
| 380 | 0xcb520000U, 0xc7e91c7dU>
|
---|
| 381 | sfmt132049_64;
|
---|
| 382 |
|
---|
| 383 |
|
---|
| 384 | typedef simd_fast_mersenne_twister_engine<uint32_t, 216091, 627,
|
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| 385 | 11, 3, 10, 1,
|
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| 386 | 0xbff7bff7U, 0xbfffffffU,
|
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| 387 | 0xbffffa7fU, 0xffddfbfbU,
|
---|
| 388 | 0xf8000001U, 0x89e80709U,
|
---|
| 389 | 0x3bd2b64bU, 0x0c64b1e4U>
|
---|
| 390 | sfmt216091;
|
---|
| 391 |
|
---|
| 392 | typedef simd_fast_mersenne_twister_engine<uint64_t, 216091, 627,
|
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| 393 | 11, 3, 10, 1,
|
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| 394 | 0xbff7bff7U, 0xbfffffffU,
|
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| 395 | 0xbffffa7fU, 0xffddfbfbU,
|
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| 396 | 0xf8000001U, 0x89e80709U,
|
---|
| 397 | 0x3bd2b64bU, 0x0c64b1e4U>
|
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| 398 | sfmt216091_64;
|
---|
| 399 |
|
---|
| 400 | #endif // __BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__
|
---|
| 401 |
|
---|
| 402 | /**
|
---|
| 403 | * @brief A beta continuous distribution for random numbers.
|
---|
| 404 | *
|
---|
| 405 | * The formula for the beta probability density function is:
|
---|
| 406 | * @f[
|
---|
| 407 | * p(x|\alpha,\beta) = \frac{1}{B(\alpha,\beta)}
|
---|
| 408 | * x^{\alpha - 1} (1 - x)^{\beta - 1}
|
---|
| 409 | * @f]
|
---|
| 410 | */
|
---|
| 411 | template<typename _RealType = double>
|
---|
| 412 | class beta_distribution
|
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| 413 | {
|
---|
| 414 | static_assert(std::is_floating_point<_RealType>::value,
|
---|
| 415 | "template argument not a floating point type");
|
---|
| 416 |
|
---|
| 417 | public:
|
---|
| 418 | /** The type of the range of the distribution. */
|
---|
| 419 | typedef _RealType result_type;
|
---|
| 420 |
|
---|
| 421 | /** Parameter type. */
|
---|
| 422 | struct param_type
|
---|
| 423 | {
|
---|
| 424 | typedef beta_distribution<_RealType> distribution_type;
|
---|
| 425 | friend class beta_distribution<_RealType>;
|
---|
| 426 |
|
---|
| 427 | param_type() : param_type(1) { }
|
---|
| 428 |
|
---|
| 429 | explicit
|
---|
| 430 | param_type(_RealType __alpha_val, _RealType __beta_val = _RealType(1))
|
---|
| 431 | : _M_alpha(__alpha_val), _M_beta(__beta_val)
|
---|
| 432 | {
|
---|
| 433 | __glibcxx_assert(_M_alpha > _RealType(0));
|
---|
| 434 | __glibcxx_assert(_M_beta > _RealType(0));
|
---|
| 435 | }
|
---|
| 436 |
|
---|
| 437 | _RealType
|
---|
| 438 | alpha() const
|
---|
| 439 | { return _M_alpha; }
|
---|
| 440 |
|
---|
| 441 | _RealType
|
---|
| 442 | beta() const
|
---|
| 443 | { return _M_beta; }
|
---|
| 444 |
|
---|
| 445 | friend bool
|
---|
| 446 | operator==(const param_type& __p1, const param_type& __p2)
|
---|
| 447 | { return (__p1._M_alpha == __p2._M_alpha
|
---|
| 448 | && __p1._M_beta == __p2._M_beta); }
|
---|
| 449 |
|
---|
| 450 | friend bool
|
---|
| 451 | operator!=(const param_type& __p1, const param_type& __p2)
|
---|
| 452 | { return !(__p1 == __p2); }
|
---|
| 453 |
|
---|
| 454 | private:
|
---|
| 455 | void
|
---|
| 456 | _M_initialize();
|
---|
| 457 |
|
---|
| 458 | _RealType _M_alpha;
|
---|
| 459 | _RealType _M_beta;
|
---|
| 460 | };
|
---|
| 461 |
|
---|
| 462 | public:
|
---|
| 463 | beta_distribution() : beta_distribution(1.0) { }
|
---|
| 464 |
|
---|
| 465 | /**
|
---|
| 466 | * @brief Constructs a beta distribution with parameters
|
---|
| 467 | * @f$\alpha@f$ and @f$\beta@f$.
|
---|
| 468 | */
|
---|
| 469 | explicit
|
---|
| 470 | beta_distribution(_RealType __alpha_val,
|
---|
| 471 | _RealType __beta_val = _RealType(1))
|
---|
| 472 | : _M_param(__alpha_val, __beta_val)
|
---|
| 473 | { }
|
---|
| 474 |
|
---|
| 475 | explicit
|
---|
| 476 | beta_distribution(const param_type& __p)
|
---|
| 477 | : _M_param(__p)
|
---|
| 478 | { }
|
---|
| 479 |
|
---|
| 480 | /**
|
---|
| 481 | * @brief Resets the distribution state.
|
---|
| 482 | */
|
---|
| 483 | void
|
---|
| 484 | reset()
|
---|
| 485 | { }
|
---|
| 486 |
|
---|
| 487 | /**
|
---|
| 488 | * @brief Returns the @f$\alpha@f$ of the distribution.
|
---|
| 489 | */
|
---|
| 490 | _RealType
|
---|
| 491 | alpha() const
|
---|
| 492 | { return _M_param.alpha(); }
|
---|
| 493 |
|
---|
| 494 | /**
|
---|
| 495 | * @brief Returns the @f$\beta@f$ of the distribution.
|
---|
| 496 | */
|
---|
| 497 | _RealType
|
---|
| 498 | beta() const
|
---|
| 499 | { return _M_param.beta(); }
|
---|
| 500 |
|
---|
| 501 | /**
|
---|
| 502 | * @brief Returns the parameter set of the distribution.
|
---|
| 503 | */
|
---|
| 504 | param_type
|
---|
| 505 | param() const
|
---|
| 506 | { return _M_param; }
|
---|
| 507 |
|
---|
| 508 | /**
|
---|
| 509 | * @brief Sets the parameter set of the distribution.
|
---|
| 510 | * @param __param The new parameter set of the distribution.
|
---|
| 511 | */
|
---|
| 512 | void
|
---|
| 513 | param(const param_type& __param)
|
---|
| 514 | { _M_param = __param; }
|
---|
| 515 |
|
---|
| 516 | /**
|
---|
| 517 | * @brief Returns the greatest lower bound value of the distribution.
|
---|
| 518 | */
|
---|
| 519 | result_type
|
---|
| 520 | min() const
|
---|
| 521 | { return result_type(0); }
|
---|
| 522 |
|
---|
| 523 | /**
|
---|
| 524 | * @brief Returns the least upper bound value of the distribution.
|
---|
| 525 | */
|
---|
| 526 | result_type
|
---|
| 527 | max() const
|
---|
| 528 | { return result_type(1); }
|
---|
| 529 |
|
---|
| 530 | /**
|
---|
| 531 | * @brief Generating functions.
|
---|
| 532 | */
|
---|
| 533 | template<typename _UniformRandomNumberGenerator>
|
---|
| 534 | result_type
|
---|
| 535 | operator()(_UniformRandomNumberGenerator& __urng)
|
---|
| 536 | { return this->operator()(__urng, _M_param); }
|
---|
| 537 |
|
---|
| 538 | template<typename _UniformRandomNumberGenerator>
|
---|
| 539 | result_type
|
---|
| 540 | operator()(_UniformRandomNumberGenerator& __urng,
|
---|
| 541 | const param_type& __p);
|
---|
| 542 |
|
---|
| 543 | template<typename _ForwardIterator,
|
---|
| 544 | typename _UniformRandomNumberGenerator>
|
---|
| 545 | void
|
---|
| 546 | __generate(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 547 | _UniformRandomNumberGenerator& __urng)
|
---|
| 548 | { this->__generate(__f, __t, __urng, _M_param); }
|
---|
| 549 |
|
---|
| 550 | template<typename _ForwardIterator,
|
---|
| 551 | typename _UniformRandomNumberGenerator>
|
---|
| 552 | void
|
---|
| 553 | __generate(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 554 | _UniformRandomNumberGenerator& __urng,
|
---|
| 555 | const param_type& __p)
|
---|
| 556 | { this->__generate_impl(__f, __t, __urng, __p); }
|
---|
| 557 |
|
---|
| 558 | template<typename _UniformRandomNumberGenerator>
|
---|
| 559 | void
|
---|
| 560 | __generate(result_type* __f, result_type* __t,
|
---|
| 561 | _UniformRandomNumberGenerator& __urng,
|
---|
| 562 | const param_type& __p)
|
---|
| 563 | { this->__generate_impl(__f, __t, __urng, __p); }
|
---|
| 564 |
|
---|
| 565 | /**
|
---|
| 566 | * @brief Return true if two beta distributions have the same
|
---|
| 567 | * parameters and the sequences that would be generated
|
---|
| 568 | * are equal.
|
---|
| 569 | */
|
---|
| 570 | friend bool
|
---|
| 571 | operator==(const beta_distribution& __d1,
|
---|
| 572 | const beta_distribution& __d2)
|
---|
| 573 | { return __d1._M_param == __d2._M_param; }
|
---|
| 574 |
|
---|
| 575 | /**
|
---|
| 576 | * @brief Inserts a %beta_distribution random number distribution
|
---|
| 577 | * @p __x into the output stream @p __os.
|
---|
| 578 | *
|
---|
| 579 | * @param __os An output stream.
|
---|
| 580 | * @param __x A %beta_distribution random number distribution.
|
---|
| 581 | *
|
---|
| 582 | * @returns The output stream with the state of @p __x inserted or in
|
---|
| 583 | * an error state.
|
---|
| 584 | */
|
---|
| 585 | template<typename _RealType1, typename _CharT, typename _Traits>
|
---|
| 586 | friend std::basic_ostream<_CharT, _Traits>&
|
---|
| 587 | operator<<(std::basic_ostream<_CharT, _Traits>& __os,
|
---|
| 588 | const __gnu_cxx::beta_distribution<_RealType1>& __x);
|
---|
| 589 |
|
---|
| 590 | /**
|
---|
| 591 | * @brief Extracts a %beta_distribution random number distribution
|
---|
| 592 | * @p __x from the input stream @p __is.
|
---|
| 593 | *
|
---|
| 594 | * @param __is An input stream.
|
---|
| 595 | * @param __x A %beta_distribution random number generator engine.
|
---|
| 596 | *
|
---|
| 597 | * @returns The input stream with @p __x extracted or in an error state.
|
---|
| 598 | */
|
---|
| 599 | template<typename _RealType1, typename _CharT, typename _Traits>
|
---|
| 600 | friend std::basic_istream<_CharT, _Traits>&
|
---|
| 601 | operator>>(std::basic_istream<_CharT, _Traits>& __is,
|
---|
| 602 | __gnu_cxx::beta_distribution<_RealType1>& __x);
|
---|
| 603 |
|
---|
| 604 | private:
|
---|
| 605 | template<typename _ForwardIterator,
|
---|
| 606 | typename _UniformRandomNumberGenerator>
|
---|
| 607 | void
|
---|
| 608 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 609 | _UniformRandomNumberGenerator& __urng,
|
---|
| 610 | const param_type& __p);
|
---|
| 611 |
|
---|
| 612 | param_type _M_param;
|
---|
| 613 | };
|
---|
| 614 |
|
---|
| 615 | /**
|
---|
| 616 | * @brief Return true if two beta distributions are different.
|
---|
| 617 | */
|
---|
| 618 | template<typename _RealType>
|
---|
| 619 | inline bool
|
---|
| 620 | operator!=(const __gnu_cxx::beta_distribution<_RealType>& __d1,
|
---|
| 621 | const __gnu_cxx::beta_distribution<_RealType>& __d2)
|
---|
| 622 | { return !(__d1 == __d2); }
|
---|
| 623 |
|
---|
| 624 |
|
---|
| 625 | /**
|
---|
| 626 | * @brief A multi-variate normal continuous distribution for random numbers.
|
---|
| 627 | *
|
---|
| 628 | * The formula for the normal probability density function is
|
---|
| 629 | * @f[
|
---|
| 630 | * p(\overrightarrow{x}|\overrightarrow{\mu },\Sigma) =
|
---|
| 631 | * \frac{1}{\sqrt{(2\pi )^k\det(\Sigma))}}
|
---|
| 632 | * e^{-\frac{1}{2}(\overrightarrow{x}-\overrightarrow{\mu})^\text{T}
|
---|
| 633 | * \Sigma ^{-1}(\overrightarrow{x}-\overrightarrow{\mu})}
|
---|
| 634 | * @f]
|
---|
| 635 | *
|
---|
| 636 | * where @f$\overrightarrow{x}@f$ and @f$\overrightarrow{\mu}@f$ are
|
---|
| 637 | * vectors of dimension @f$k@f$ and @f$\Sigma@f$ is the covariance
|
---|
| 638 | * matrix (which must be positive-definite).
|
---|
| 639 | */
|
---|
| 640 | template<std::size_t _Dimen, typename _RealType = double>
|
---|
| 641 | class normal_mv_distribution
|
---|
| 642 | {
|
---|
| 643 | static_assert(std::is_floating_point<_RealType>::value,
|
---|
| 644 | "template argument not a floating point type");
|
---|
| 645 | static_assert(_Dimen != 0, "dimension is zero");
|
---|
| 646 |
|
---|
| 647 | public:
|
---|
| 648 | /** The type of the range of the distribution. */
|
---|
| 649 | typedef std::array<_RealType, _Dimen> result_type;
|
---|
| 650 | /** Parameter type. */
|
---|
| 651 | class param_type
|
---|
| 652 | {
|
---|
| 653 | static constexpr size_t _M_t_size = _Dimen * (_Dimen + 1) / 2;
|
---|
| 654 |
|
---|
| 655 | public:
|
---|
| 656 | typedef normal_mv_distribution<_Dimen, _RealType> distribution_type;
|
---|
| 657 | friend class normal_mv_distribution<_Dimen, _RealType>;
|
---|
| 658 |
|
---|
| 659 | param_type()
|
---|
| 660 | {
|
---|
| 661 | std::fill(_M_mean.begin(), _M_mean.end(), _RealType(0));
|
---|
| 662 | auto __it = _M_t.begin();
|
---|
| 663 | for (size_t __i = 0; __i < _Dimen; ++__i)
|
---|
| 664 | {
|
---|
| 665 | std::fill_n(__it, __i, _RealType(0));
|
---|
| 666 | __it += __i;
|
---|
| 667 | *__it++ = _RealType(1);
|
---|
| 668 | }
|
---|
| 669 | }
|
---|
| 670 |
|
---|
| 671 | template<typename _ForwardIterator1, typename _ForwardIterator2>
|
---|
| 672 | param_type(_ForwardIterator1 __meanbegin,
|
---|
| 673 | _ForwardIterator1 __meanend,
|
---|
| 674 | _ForwardIterator2 __varcovbegin,
|
---|
| 675 | _ForwardIterator2 __varcovend)
|
---|
| 676 | {
|
---|
| 677 | __glibcxx_function_requires(_ForwardIteratorConcept<
|
---|
| 678 | _ForwardIterator1>)
|
---|
| 679 | __glibcxx_function_requires(_ForwardIteratorConcept<
|
---|
| 680 | _ForwardIterator2>)
|
---|
| 681 | _GLIBCXX_DEBUG_ASSERT(std::distance(__meanbegin, __meanend)
|
---|
| 682 | <= _Dimen);
|
---|
| 683 | const auto __dist = std::distance(__varcovbegin, __varcovend);
|
---|
| 684 | _GLIBCXX_DEBUG_ASSERT(__dist == _Dimen * _Dimen
|
---|
| 685 | || __dist == _Dimen * (_Dimen + 1) / 2
|
---|
| 686 | || __dist == _Dimen);
|
---|
| 687 |
|
---|
| 688 | if (__dist == _Dimen * _Dimen)
|
---|
| 689 | _M_init_full(__meanbegin, __meanend, __varcovbegin, __varcovend);
|
---|
| 690 | else if (__dist == _Dimen * (_Dimen + 1) / 2)
|
---|
| 691 | _M_init_lower(__meanbegin, __meanend, __varcovbegin, __varcovend);
|
---|
| 692 | else
|
---|
| 693 | {
|
---|
| 694 | __glibcxx_assert(__dist == _Dimen);
|
---|
| 695 | _M_init_diagonal(__meanbegin, __meanend,
|
---|
| 696 | __varcovbegin, __varcovend);
|
---|
| 697 | }
|
---|
| 698 | }
|
---|
| 699 |
|
---|
| 700 | param_type(std::initializer_list<_RealType> __mean,
|
---|
| 701 | std::initializer_list<_RealType> __varcov)
|
---|
| 702 | {
|
---|
| 703 | _GLIBCXX_DEBUG_ASSERT(__mean.size() <= _Dimen);
|
---|
| 704 | _GLIBCXX_DEBUG_ASSERT(__varcov.size() == _Dimen * _Dimen
|
---|
| 705 | || __varcov.size() == _Dimen * (_Dimen + 1) / 2
|
---|
| 706 | || __varcov.size() == _Dimen);
|
---|
| 707 |
|
---|
| 708 | if (__varcov.size() == _Dimen * _Dimen)
|
---|
| 709 | _M_init_full(__mean.begin(), __mean.end(),
|
---|
| 710 | __varcov.begin(), __varcov.end());
|
---|
| 711 | else if (__varcov.size() == _Dimen * (_Dimen + 1) / 2)
|
---|
| 712 | _M_init_lower(__mean.begin(), __mean.end(),
|
---|
| 713 | __varcov.begin(), __varcov.end());
|
---|
| 714 | else
|
---|
| 715 | {
|
---|
| 716 | __glibcxx_assert(__varcov.size() == _Dimen);
|
---|
| 717 | _M_init_diagonal(__mean.begin(), __mean.end(),
|
---|
| 718 | __varcov.begin(), __varcov.end());
|
---|
| 719 | }
|
---|
| 720 | }
|
---|
| 721 |
|
---|
| 722 | std::array<_RealType, _Dimen>
|
---|
| 723 | mean() const
|
---|
| 724 | { return _M_mean; }
|
---|
| 725 |
|
---|
| 726 | std::array<_RealType, _M_t_size>
|
---|
| 727 | varcov() const
|
---|
| 728 | { return _M_t; }
|
---|
| 729 |
|
---|
| 730 | friend bool
|
---|
| 731 | operator==(const param_type& __p1, const param_type& __p2)
|
---|
| 732 | { return __p1._M_mean == __p2._M_mean && __p1._M_t == __p2._M_t; }
|
---|
| 733 |
|
---|
| 734 | friend bool
|
---|
| 735 | operator!=(const param_type& __p1, const param_type& __p2)
|
---|
| 736 | { return !(__p1 == __p2); }
|
---|
| 737 |
|
---|
| 738 | private:
|
---|
| 739 | template <typename _InputIterator1, typename _InputIterator2>
|
---|
| 740 | void _M_init_full(_InputIterator1 __meanbegin,
|
---|
| 741 | _InputIterator1 __meanend,
|
---|
| 742 | _InputIterator2 __varcovbegin,
|
---|
| 743 | _InputIterator2 __varcovend);
|
---|
| 744 | template <typename _InputIterator1, typename _InputIterator2>
|
---|
| 745 | void _M_init_lower(_InputIterator1 __meanbegin,
|
---|
| 746 | _InputIterator1 __meanend,
|
---|
| 747 | _InputIterator2 __varcovbegin,
|
---|
| 748 | _InputIterator2 __varcovend);
|
---|
| 749 | template <typename _InputIterator1, typename _InputIterator2>
|
---|
| 750 | void _M_init_diagonal(_InputIterator1 __meanbegin,
|
---|
| 751 | _InputIterator1 __meanend,
|
---|
| 752 | _InputIterator2 __varbegin,
|
---|
| 753 | _InputIterator2 __varend);
|
---|
| 754 |
|
---|
| 755 | // param_type constructors apply Cholesky decomposition to the
|
---|
| 756 | // varcov matrix in _M_init_full and _M_init_lower, but the
|
---|
| 757 | // varcov matrix output ot a stream is already decomposed, so
|
---|
| 758 | // we need means to restore it as-is when reading it back in.
|
---|
| 759 | template<size_t _Dimen1, typename _RealType1,
|
---|
| 760 | typename _CharT, typename _Traits>
|
---|
| 761 | friend std::basic_istream<_CharT, _Traits>&
|
---|
| 762 | operator>>(std::basic_istream<_CharT, _Traits>& __is,
|
---|
| 763 | __gnu_cxx::normal_mv_distribution<_Dimen1, _RealType1>&
|
---|
| 764 | __x);
|
---|
| 765 | param_type(std::array<_RealType, _Dimen> const &__mean,
|
---|
| 766 | std::array<_RealType, _M_t_size> const &__varcov)
|
---|
| 767 | : _M_mean (__mean), _M_t (__varcov)
|
---|
| 768 | {}
|
---|
| 769 |
|
---|
| 770 | std::array<_RealType, _Dimen> _M_mean;
|
---|
| 771 | std::array<_RealType, _M_t_size> _M_t;
|
---|
| 772 | };
|
---|
| 773 |
|
---|
| 774 | public:
|
---|
| 775 | normal_mv_distribution()
|
---|
| 776 | : _M_param(), _M_nd()
|
---|
| 777 | { }
|
---|
| 778 |
|
---|
| 779 | template<typename _ForwardIterator1, typename _ForwardIterator2>
|
---|
| 780 | normal_mv_distribution(_ForwardIterator1 __meanbegin,
|
---|
| 781 | _ForwardIterator1 __meanend,
|
---|
| 782 | _ForwardIterator2 __varcovbegin,
|
---|
| 783 | _ForwardIterator2 __varcovend)
|
---|
| 784 | : _M_param(__meanbegin, __meanend, __varcovbegin, __varcovend),
|
---|
| 785 | _M_nd()
|
---|
| 786 | { }
|
---|
| 787 |
|
---|
| 788 | normal_mv_distribution(std::initializer_list<_RealType> __mean,
|
---|
| 789 | std::initializer_list<_RealType> __varcov)
|
---|
| 790 | : _M_param(__mean, __varcov), _M_nd()
|
---|
| 791 | { }
|
---|
| 792 |
|
---|
| 793 | explicit
|
---|
| 794 | normal_mv_distribution(const param_type& __p)
|
---|
| 795 | : _M_param(__p), _M_nd()
|
---|
| 796 | { }
|
---|
| 797 |
|
---|
| 798 | /**
|
---|
| 799 | * @brief Resets the distribution state.
|
---|
| 800 | */
|
---|
| 801 | void
|
---|
| 802 | reset()
|
---|
| 803 | { _M_nd.reset(); }
|
---|
| 804 |
|
---|
| 805 | /**
|
---|
| 806 | * @brief Returns the mean of the distribution.
|
---|
| 807 | */
|
---|
| 808 | result_type
|
---|
| 809 | mean() const
|
---|
| 810 | { return _M_param.mean(); }
|
---|
| 811 |
|
---|
| 812 | /**
|
---|
| 813 | * @brief Returns the compact form of the variance/covariance
|
---|
| 814 | * matrix of the distribution.
|
---|
| 815 | */
|
---|
| 816 | std::array<_RealType, _Dimen * (_Dimen + 1) / 2>
|
---|
| 817 | varcov() const
|
---|
| 818 | { return _M_param.varcov(); }
|
---|
| 819 |
|
---|
| 820 | /**
|
---|
| 821 | * @brief Returns the parameter set of the distribution.
|
---|
| 822 | */
|
---|
| 823 | param_type
|
---|
| 824 | param() const
|
---|
| 825 | { return _M_param; }
|
---|
| 826 |
|
---|
| 827 | /**
|
---|
| 828 | * @brief Sets the parameter set of the distribution.
|
---|
| 829 | * @param __param The new parameter set of the distribution.
|
---|
| 830 | */
|
---|
| 831 | void
|
---|
| 832 | param(const param_type& __param)
|
---|
| 833 | { _M_param = __param; }
|
---|
| 834 |
|
---|
| 835 | /**
|
---|
| 836 | * @brief Returns the greatest lower bound value of the distribution.
|
---|
| 837 | */
|
---|
| 838 | result_type
|
---|
| 839 | min() const
|
---|
| 840 | { result_type __res;
|
---|
| 841 | __res.fill(std::numeric_limits<_RealType>::lowest());
|
---|
| 842 | return __res; }
|
---|
| 843 |
|
---|
| 844 | /**
|
---|
| 845 | * @brief Returns the least upper bound value of the distribution.
|
---|
| 846 | */
|
---|
| 847 | result_type
|
---|
| 848 | max() const
|
---|
| 849 | { result_type __res;
|
---|
| 850 | __res.fill(std::numeric_limits<_RealType>::max());
|
---|
| 851 | return __res; }
|
---|
| 852 |
|
---|
| 853 | /**
|
---|
| 854 | * @brief Generating functions.
|
---|
| 855 | */
|
---|
| 856 | template<typename _UniformRandomNumberGenerator>
|
---|
| 857 | result_type
|
---|
| 858 | operator()(_UniformRandomNumberGenerator& __urng)
|
---|
| 859 | { return this->operator()(__urng, _M_param); }
|
---|
| 860 |
|
---|
| 861 | template<typename _UniformRandomNumberGenerator>
|
---|
| 862 | result_type
|
---|
| 863 | operator()(_UniformRandomNumberGenerator& __urng,
|
---|
| 864 | const param_type& __p);
|
---|
| 865 |
|
---|
| 866 | template<typename _ForwardIterator,
|
---|
| 867 | typename _UniformRandomNumberGenerator>
|
---|
| 868 | void
|
---|
| 869 | __generate(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 870 | _UniformRandomNumberGenerator& __urng)
|
---|
| 871 | { return this->__generate_impl(__f, __t, __urng, _M_param); }
|
---|
| 872 |
|
---|
| 873 | template<typename _ForwardIterator,
|
---|
| 874 | typename _UniformRandomNumberGenerator>
|
---|
| 875 | void
|
---|
| 876 | __generate(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 877 | _UniformRandomNumberGenerator& __urng,
|
---|
| 878 | const param_type& __p)
|
---|
| 879 | { return this->__generate_impl(__f, __t, __urng, __p); }
|
---|
| 880 |
|
---|
| 881 | /**
|
---|
| 882 | * @brief Return true if two multi-variant normal distributions have
|
---|
| 883 | * the same parameters and the sequences that would
|
---|
| 884 | * be generated are equal.
|
---|
| 885 | */
|
---|
| 886 | template<size_t _Dimen1, typename _RealType1>
|
---|
| 887 | friend bool
|
---|
| 888 | operator==(const
|
---|
| 889 | __gnu_cxx::normal_mv_distribution<_Dimen1, _RealType1>&
|
---|
| 890 | __d1,
|
---|
| 891 | const
|
---|
| 892 | __gnu_cxx::normal_mv_distribution<_Dimen1, _RealType1>&
|
---|
| 893 | __d2);
|
---|
| 894 |
|
---|
| 895 | /**
|
---|
| 896 | * @brief Inserts a %normal_mv_distribution random number distribution
|
---|
| 897 | * @p __x into the output stream @p __os.
|
---|
| 898 | *
|
---|
| 899 | * @param __os An output stream.
|
---|
| 900 | * @param __x A %normal_mv_distribution random number distribution.
|
---|
| 901 | *
|
---|
| 902 | * @returns The output stream with the state of @p __x inserted or in
|
---|
| 903 | * an error state.
|
---|
| 904 | */
|
---|
| 905 | template<size_t _Dimen1, typename _RealType1,
|
---|
| 906 | typename _CharT, typename _Traits>
|
---|
| 907 | friend std::basic_ostream<_CharT, _Traits>&
|
---|
| 908 | operator<<(std::basic_ostream<_CharT, _Traits>& __os,
|
---|
| 909 | const
|
---|
| 910 | __gnu_cxx::normal_mv_distribution<_Dimen1, _RealType1>&
|
---|
| 911 | __x);
|
---|
| 912 |
|
---|
| 913 | /**
|
---|
| 914 | * @brief Extracts a %normal_mv_distribution random number distribution
|
---|
| 915 | * @p __x from the input stream @p __is.
|
---|
| 916 | *
|
---|
| 917 | * @param __is An input stream.
|
---|
| 918 | * @param __x A %normal_mv_distribution random number generator engine.
|
---|
| 919 | *
|
---|
| 920 | * @returns The input stream with @p __x extracted or in an error
|
---|
| 921 | * state.
|
---|
| 922 | */
|
---|
| 923 | template<size_t _Dimen1, typename _RealType1,
|
---|
| 924 | typename _CharT, typename _Traits>
|
---|
| 925 | friend std::basic_istream<_CharT, _Traits>&
|
---|
| 926 | operator>>(std::basic_istream<_CharT, _Traits>& __is,
|
---|
| 927 | __gnu_cxx::normal_mv_distribution<_Dimen1, _RealType1>&
|
---|
| 928 | __x);
|
---|
| 929 |
|
---|
| 930 | private:
|
---|
| 931 | template<typename _ForwardIterator,
|
---|
| 932 | typename _UniformRandomNumberGenerator>
|
---|
| 933 | void
|
---|
| 934 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 935 | _UniformRandomNumberGenerator& __urng,
|
---|
| 936 | const param_type& __p);
|
---|
| 937 |
|
---|
| 938 | param_type _M_param;
|
---|
| 939 | std::normal_distribution<_RealType> _M_nd;
|
---|
| 940 | };
|
---|
| 941 |
|
---|
| 942 | /**
|
---|
| 943 | * @brief Return true if two multi-variate normal distributions are
|
---|
| 944 | * different.
|
---|
| 945 | */
|
---|
| 946 | template<size_t _Dimen, typename _RealType>
|
---|
| 947 | inline bool
|
---|
| 948 | operator!=(const __gnu_cxx::normal_mv_distribution<_Dimen, _RealType>&
|
---|
| 949 | __d1,
|
---|
| 950 | const __gnu_cxx::normal_mv_distribution<_Dimen, _RealType>&
|
---|
| 951 | __d2)
|
---|
| 952 | { return !(__d1 == __d2); }
|
---|
| 953 |
|
---|
| 954 |
|
---|
| 955 | /**
|
---|
| 956 | * @brief A Rice continuous distribution for random numbers.
|
---|
| 957 | *
|
---|
| 958 | * The formula for the Rice probability density function is
|
---|
| 959 | * @f[
|
---|
| 960 | * p(x|\nu,\sigma) = \frac{x}{\sigma^2}
|
---|
| 961 | * \exp\left(-\frac{x^2+\nu^2}{2\sigma^2}\right)
|
---|
| 962 | * I_0\left(\frac{x \nu}{\sigma^2}\right)
|
---|
| 963 | * @f]
|
---|
| 964 | * where @f$I_0(z)@f$ is the modified Bessel function of the first kind
|
---|
| 965 | * of order 0 and @f$\nu >= 0@f$ and @f$\sigma > 0@f$.
|
---|
| 966 | *
|
---|
| 967 | * <table border=1 cellpadding=10 cellspacing=0>
|
---|
| 968 | * <caption align=top>Distribution Statistics</caption>
|
---|
| 969 | * <tr><td>Mean</td><td>@f$\sqrt{\pi/2}L_{1/2}(-\nu^2/2\sigma^2)@f$</td></tr>
|
---|
| 970 | * <tr><td>Variance</td><td>@f$2\sigma^2 + \nu^2
|
---|
| 971 | * + (\pi\sigma^2/2)L^2_{1/2}(-\nu^2/2\sigma^2)@f$</td></tr>
|
---|
| 972 | * <tr><td>Range</td><td>@f$[0, \infty)@f$</td></tr>
|
---|
| 973 | * </table>
|
---|
| 974 | * where @f$L_{1/2}(x)@f$ is the Laguerre polynomial of order 1/2.
|
---|
| 975 | */
|
---|
| 976 | template<typename _RealType = double>
|
---|
| 977 | class
|
---|
| 978 | rice_distribution
|
---|
| 979 | {
|
---|
| 980 | static_assert(std::is_floating_point<_RealType>::value,
|
---|
| 981 | "template argument not a floating point type");
|
---|
| 982 | public:
|
---|
| 983 | /** The type of the range of the distribution. */
|
---|
| 984 | typedef _RealType result_type;
|
---|
| 985 |
|
---|
| 986 | /** Parameter type. */
|
---|
| 987 | struct param_type
|
---|
| 988 | {
|
---|
| 989 | typedef rice_distribution<result_type> distribution_type;
|
---|
| 990 |
|
---|
| 991 | param_type() : param_type(0) { }
|
---|
| 992 |
|
---|
| 993 | param_type(result_type __nu_val,
|
---|
| 994 | result_type __sigma_val = result_type(1))
|
---|
| 995 | : _M_nu(__nu_val), _M_sigma(__sigma_val)
|
---|
| 996 | {
|
---|
| 997 | __glibcxx_assert(_M_nu >= result_type(0));
|
---|
| 998 | __glibcxx_assert(_M_sigma > result_type(0));
|
---|
| 999 | }
|
---|
| 1000 |
|
---|
| 1001 | result_type
|
---|
| 1002 | nu() const
|
---|
| 1003 | { return _M_nu; }
|
---|
| 1004 |
|
---|
| 1005 | result_type
|
---|
| 1006 | sigma() const
|
---|
| 1007 | { return _M_sigma; }
|
---|
| 1008 |
|
---|
| 1009 | friend bool
|
---|
| 1010 | operator==(const param_type& __p1, const param_type& __p2)
|
---|
| 1011 | { return __p1._M_nu == __p2._M_nu && __p1._M_sigma == __p2._M_sigma; }
|
---|
| 1012 |
|
---|
| 1013 | friend bool
|
---|
| 1014 | operator!=(const param_type& __p1, const param_type& __p2)
|
---|
| 1015 | { return !(__p1 == __p2); }
|
---|
| 1016 |
|
---|
| 1017 | private:
|
---|
| 1018 | void _M_initialize();
|
---|
| 1019 |
|
---|
| 1020 | result_type _M_nu;
|
---|
| 1021 | result_type _M_sigma;
|
---|
| 1022 | };
|
---|
| 1023 |
|
---|
| 1024 | /**
|
---|
| 1025 | * @brief Constructors.
|
---|
| 1026 | * @{
|
---|
| 1027 | */
|
---|
| 1028 |
|
---|
| 1029 | rice_distribution() : rice_distribution(0) { }
|
---|
| 1030 |
|
---|
| 1031 | explicit
|
---|
| 1032 | rice_distribution(result_type __nu_val,
|
---|
| 1033 | result_type __sigma_val = result_type(1))
|
---|
| 1034 | : _M_param(__nu_val, __sigma_val),
|
---|
| 1035 | _M_ndx(__nu_val, __sigma_val),
|
---|
| 1036 | _M_ndy(result_type(0), __sigma_val)
|
---|
| 1037 | { }
|
---|
| 1038 |
|
---|
| 1039 | explicit
|
---|
| 1040 | rice_distribution(const param_type& __p)
|
---|
| 1041 | : _M_param(__p),
|
---|
| 1042 | _M_ndx(__p.nu(), __p.sigma()),
|
---|
| 1043 | _M_ndy(result_type(0), __p.sigma())
|
---|
| 1044 | { }
|
---|
| 1045 |
|
---|
| 1046 | /// @}
|
---|
| 1047 |
|
---|
| 1048 | /**
|
---|
| 1049 | * @brief Resets the distribution state.
|
---|
| 1050 | */
|
---|
| 1051 | void
|
---|
| 1052 | reset()
|
---|
| 1053 | {
|
---|
| 1054 | _M_ndx.reset();
|
---|
| 1055 | _M_ndy.reset();
|
---|
| 1056 | }
|
---|
| 1057 |
|
---|
| 1058 | /**
|
---|
| 1059 | * @brief Return the parameters of the distribution.
|
---|
| 1060 | */
|
---|
| 1061 | result_type
|
---|
| 1062 | nu() const
|
---|
| 1063 | { return _M_param.nu(); }
|
---|
| 1064 |
|
---|
| 1065 | result_type
|
---|
| 1066 | sigma() const
|
---|
| 1067 | { return _M_param.sigma(); }
|
---|
| 1068 |
|
---|
| 1069 | /**
|
---|
| 1070 | * @brief Returns the parameter set of the distribution.
|
---|
| 1071 | */
|
---|
| 1072 | param_type
|
---|
| 1073 | param() const
|
---|
| 1074 | { return _M_param; }
|
---|
| 1075 |
|
---|
| 1076 | /**
|
---|
| 1077 | * @brief Sets the parameter set of the distribution.
|
---|
| 1078 | * @param __param The new parameter set of the distribution.
|
---|
| 1079 | */
|
---|
| 1080 | void
|
---|
| 1081 | param(const param_type& __param)
|
---|
| 1082 | { _M_param = __param; }
|
---|
| 1083 |
|
---|
| 1084 | /**
|
---|
| 1085 | * @brief Returns the greatest lower bound value of the distribution.
|
---|
| 1086 | */
|
---|
| 1087 | result_type
|
---|
| 1088 | min() const
|
---|
| 1089 | { return result_type(0); }
|
---|
| 1090 |
|
---|
| 1091 | /**
|
---|
| 1092 | * @brief Returns the least upper bound value of the distribution.
|
---|
| 1093 | */
|
---|
| 1094 | result_type
|
---|
| 1095 | max() const
|
---|
| 1096 | { return std::numeric_limits<result_type>::max(); }
|
---|
| 1097 |
|
---|
| 1098 | /**
|
---|
| 1099 | * @brief Generating functions.
|
---|
| 1100 | */
|
---|
| 1101 | template<typename _UniformRandomNumberGenerator>
|
---|
| 1102 | result_type
|
---|
| 1103 | operator()(_UniformRandomNumberGenerator& __urng)
|
---|
| 1104 | {
|
---|
| 1105 | result_type __x = this->_M_ndx(__urng);
|
---|
| 1106 | result_type __y = this->_M_ndy(__urng);
|
---|
| 1107 | #if _GLIBCXX_USE_C99_MATH_TR1
|
---|
| 1108 | return std::hypot(__x, __y);
|
---|
| 1109 | #else
|
---|
| 1110 | return std::sqrt(__x * __x + __y * __y);
|
---|
| 1111 | #endif
|
---|
| 1112 | }
|
---|
| 1113 |
|
---|
| 1114 | template<typename _UniformRandomNumberGenerator>
|
---|
| 1115 | result_type
|
---|
| 1116 | operator()(_UniformRandomNumberGenerator& __urng,
|
---|
| 1117 | const param_type& __p)
|
---|
| 1118 | {
|
---|
| 1119 | typename std::normal_distribution<result_type>::param_type
|
---|
| 1120 | __px(__p.nu(), __p.sigma()), __py(result_type(0), __p.sigma());
|
---|
| 1121 | result_type __x = this->_M_ndx(__px, __urng);
|
---|
| 1122 | result_type __y = this->_M_ndy(__py, __urng);
|
---|
| 1123 | #if _GLIBCXX_USE_C99_MATH_TR1
|
---|
| 1124 | return std::hypot(__x, __y);
|
---|
| 1125 | #else
|
---|
| 1126 | return std::sqrt(__x * __x + __y * __y);
|
---|
| 1127 | #endif
|
---|
| 1128 | }
|
---|
| 1129 |
|
---|
| 1130 | template<typename _ForwardIterator,
|
---|
| 1131 | typename _UniformRandomNumberGenerator>
|
---|
| 1132 | void
|
---|
| 1133 | __generate(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 1134 | _UniformRandomNumberGenerator& __urng)
|
---|
| 1135 | { this->__generate(__f, __t, __urng, _M_param); }
|
---|
| 1136 |
|
---|
| 1137 | template<typename _ForwardIterator,
|
---|
| 1138 | typename _UniformRandomNumberGenerator>
|
---|
| 1139 | void
|
---|
| 1140 | __generate(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 1141 | _UniformRandomNumberGenerator& __urng,
|
---|
| 1142 | const param_type& __p)
|
---|
| 1143 | { this->__generate_impl(__f, __t, __urng, __p); }
|
---|
| 1144 |
|
---|
| 1145 | template<typename _UniformRandomNumberGenerator>
|
---|
| 1146 | void
|
---|
| 1147 | __generate(result_type* __f, result_type* __t,
|
---|
| 1148 | _UniformRandomNumberGenerator& __urng,
|
---|
| 1149 | const param_type& __p)
|
---|
| 1150 | { this->__generate_impl(__f, __t, __urng, __p); }
|
---|
| 1151 |
|
---|
| 1152 | /**
|
---|
| 1153 | * @brief Return true if two Rice distributions have
|
---|
| 1154 | * the same parameters and the sequences that would
|
---|
| 1155 | * be generated are equal.
|
---|
| 1156 | */
|
---|
| 1157 | friend bool
|
---|
| 1158 | operator==(const rice_distribution& __d1,
|
---|
| 1159 | const rice_distribution& __d2)
|
---|
| 1160 | { return (__d1._M_param == __d2._M_param
|
---|
| 1161 | && __d1._M_ndx == __d2._M_ndx
|
---|
| 1162 | && __d1._M_ndy == __d2._M_ndy); }
|
---|
| 1163 |
|
---|
| 1164 | /**
|
---|
| 1165 | * @brief Inserts a %rice_distribution random number distribution
|
---|
| 1166 | * @p __x into the output stream @p __os.
|
---|
| 1167 | *
|
---|
| 1168 | * @param __os An output stream.
|
---|
| 1169 | * @param __x A %rice_distribution random number distribution.
|
---|
| 1170 | *
|
---|
| 1171 | * @returns The output stream with the state of @p __x inserted or in
|
---|
| 1172 | * an error state.
|
---|
| 1173 | */
|
---|
| 1174 | template<typename _RealType1, typename _CharT, typename _Traits>
|
---|
| 1175 | friend std::basic_ostream<_CharT, _Traits>&
|
---|
| 1176 | operator<<(std::basic_ostream<_CharT, _Traits>&,
|
---|
| 1177 | const rice_distribution<_RealType1>&);
|
---|
| 1178 |
|
---|
| 1179 | /**
|
---|
| 1180 | * @brief Extracts a %rice_distribution random number distribution
|
---|
| 1181 | * @p __x from the input stream @p __is.
|
---|
| 1182 | *
|
---|
| 1183 | * @param __is An input stream.
|
---|
| 1184 | * @param __x A %rice_distribution random number
|
---|
| 1185 | * generator engine.
|
---|
| 1186 | *
|
---|
| 1187 | * @returns The input stream with @p __x extracted or in an error state.
|
---|
| 1188 | */
|
---|
| 1189 | template<typename _RealType1, typename _CharT, typename _Traits>
|
---|
| 1190 | friend std::basic_istream<_CharT, _Traits>&
|
---|
| 1191 | operator>>(std::basic_istream<_CharT, _Traits>&,
|
---|
| 1192 | rice_distribution<_RealType1>&);
|
---|
| 1193 |
|
---|
| 1194 | private:
|
---|
| 1195 | template<typename _ForwardIterator,
|
---|
| 1196 | typename _UniformRandomNumberGenerator>
|
---|
| 1197 | void
|
---|
| 1198 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 1199 | _UniformRandomNumberGenerator& __urng,
|
---|
| 1200 | const param_type& __p);
|
---|
| 1201 |
|
---|
| 1202 | param_type _M_param;
|
---|
| 1203 |
|
---|
| 1204 | std::normal_distribution<result_type> _M_ndx;
|
---|
| 1205 | std::normal_distribution<result_type> _M_ndy;
|
---|
| 1206 | };
|
---|
| 1207 |
|
---|
| 1208 | /**
|
---|
| 1209 | * @brief Return true if two Rice distributions are not equal.
|
---|
| 1210 | */
|
---|
| 1211 | template<typename _RealType1>
|
---|
| 1212 | inline bool
|
---|
| 1213 | operator!=(const rice_distribution<_RealType1>& __d1,
|
---|
| 1214 | const rice_distribution<_RealType1>& __d2)
|
---|
| 1215 | { return !(__d1 == __d2); }
|
---|
| 1216 |
|
---|
| 1217 |
|
---|
| 1218 | /**
|
---|
| 1219 | * @brief A Nakagami continuous distribution for random numbers.
|
---|
| 1220 | *
|
---|
| 1221 | * The formula for the Nakagami probability density function is
|
---|
| 1222 | * @f[
|
---|
| 1223 | * p(x|\mu,\omega) = \frac{2\mu^\mu}{\Gamma(\mu)\omega^\mu}
|
---|
| 1224 | * x^{2\mu-1}e^{-\mu x / \omega}
|
---|
| 1225 | * @f]
|
---|
| 1226 | * where @f$\Gamma(z)@f$ is the gamma function and @f$\mu >= 0.5@f$
|
---|
| 1227 | * and @f$\omega > 0@f$.
|
---|
| 1228 | */
|
---|
| 1229 | template<typename _RealType = double>
|
---|
| 1230 | class
|
---|
| 1231 | nakagami_distribution
|
---|
| 1232 | {
|
---|
| 1233 | static_assert(std::is_floating_point<_RealType>::value,
|
---|
| 1234 | "template argument not a floating point type");
|
---|
| 1235 |
|
---|
| 1236 | public:
|
---|
| 1237 | /** The type of the range of the distribution. */
|
---|
| 1238 | typedef _RealType result_type;
|
---|
| 1239 |
|
---|
| 1240 | /** Parameter type. */
|
---|
| 1241 | struct param_type
|
---|
| 1242 | {
|
---|
| 1243 | typedef nakagami_distribution<result_type> distribution_type;
|
---|
| 1244 |
|
---|
| 1245 | param_type() : param_type(1) { }
|
---|
| 1246 |
|
---|
| 1247 | param_type(result_type __mu_val,
|
---|
| 1248 | result_type __omega_val = result_type(1))
|
---|
| 1249 | : _M_mu(__mu_val), _M_omega(__omega_val)
|
---|
| 1250 | {
|
---|
| 1251 | __glibcxx_assert(_M_mu >= result_type(0.5L));
|
---|
| 1252 | __glibcxx_assert(_M_omega > result_type(0));
|
---|
| 1253 | }
|
---|
| 1254 |
|
---|
| 1255 | result_type
|
---|
| 1256 | mu() const
|
---|
| 1257 | { return _M_mu; }
|
---|
| 1258 |
|
---|
| 1259 | result_type
|
---|
| 1260 | omega() const
|
---|
| 1261 | { return _M_omega; }
|
---|
| 1262 |
|
---|
| 1263 | friend bool
|
---|
| 1264 | operator==(const param_type& __p1, const param_type& __p2)
|
---|
| 1265 | { return __p1._M_mu == __p2._M_mu && __p1._M_omega == __p2._M_omega; }
|
---|
| 1266 |
|
---|
| 1267 | friend bool
|
---|
| 1268 | operator!=(const param_type& __p1, const param_type& __p2)
|
---|
| 1269 | { return !(__p1 == __p2); }
|
---|
| 1270 |
|
---|
| 1271 | private:
|
---|
| 1272 | void _M_initialize();
|
---|
| 1273 |
|
---|
| 1274 | result_type _M_mu;
|
---|
| 1275 | result_type _M_omega;
|
---|
| 1276 | };
|
---|
| 1277 |
|
---|
| 1278 | /**
|
---|
| 1279 | * @brief Constructors.
|
---|
| 1280 | * @{
|
---|
| 1281 | */
|
---|
| 1282 |
|
---|
| 1283 | nakagami_distribution() : nakagami_distribution(1) { }
|
---|
| 1284 |
|
---|
| 1285 | explicit
|
---|
| 1286 | nakagami_distribution(result_type __mu_val,
|
---|
| 1287 | result_type __omega_val = result_type(1))
|
---|
| 1288 | : _M_param(__mu_val, __omega_val),
|
---|
| 1289 | _M_gd(__mu_val, __omega_val / __mu_val)
|
---|
| 1290 | { }
|
---|
| 1291 |
|
---|
| 1292 | explicit
|
---|
| 1293 | nakagami_distribution(const param_type& __p)
|
---|
| 1294 | : _M_param(__p),
|
---|
| 1295 | _M_gd(__p.mu(), __p.omega() / __p.mu())
|
---|
| 1296 | { }
|
---|
| 1297 |
|
---|
| 1298 | /// @}
|
---|
| 1299 |
|
---|
| 1300 | /**
|
---|
| 1301 | * @brief Resets the distribution state.
|
---|
| 1302 | */
|
---|
| 1303 | void
|
---|
| 1304 | reset()
|
---|
| 1305 | { _M_gd.reset(); }
|
---|
| 1306 |
|
---|
| 1307 | /**
|
---|
| 1308 | * @brief Return the parameters of the distribution.
|
---|
| 1309 | */
|
---|
| 1310 | result_type
|
---|
| 1311 | mu() const
|
---|
| 1312 | { return _M_param.mu(); }
|
---|
| 1313 |
|
---|
| 1314 | result_type
|
---|
| 1315 | omega() const
|
---|
| 1316 | { return _M_param.omega(); }
|
---|
| 1317 |
|
---|
| 1318 | /**
|
---|
| 1319 | * @brief Returns the parameter set of the distribution.
|
---|
| 1320 | */
|
---|
| 1321 | param_type
|
---|
| 1322 | param() const
|
---|
| 1323 | { return _M_param; }
|
---|
| 1324 |
|
---|
| 1325 | /**
|
---|
| 1326 | * @brief Sets the parameter set of the distribution.
|
---|
| 1327 | * @param __param The new parameter set of the distribution.
|
---|
| 1328 | */
|
---|
| 1329 | void
|
---|
| 1330 | param(const param_type& __param)
|
---|
| 1331 | { _M_param = __param; }
|
---|
| 1332 |
|
---|
| 1333 | /**
|
---|
| 1334 | * @brief Returns the greatest lower bound value of the distribution.
|
---|
| 1335 | */
|
---|
| 1336 | result_type
|
---|
| 1337 | min() const
|
---|
| 1338 | { return result_type(0); }
|
---|
| 1339 |
|
---|
| 1340 | /**
|
---|
| 1341 | * @brief Returns the least upper bound value of the distribution.
|
---|
| 1342 | */
|
---|
| 1343 | result_type
|
---|
| 1344 | max() const
|
---|
| 1345 | { return std::numeric_limits<result_type>::max(); }
|
---|
| 1346 |
|
---|
| 1347 | /**
|
---|
| 1348 | * @brief Generating functions.
|
---|
| 1349 | */
|
---|
| 1350 | template<typename _UniformRandomNumberGenerator>
|
---|
| 1351 | result_type
|
---|
| 1352 | operator()(_UniformRandomNumberGenerator& __urng)
|
---|
| 1353 | { return std::sqrt(this->_M_gd(__urng)); }
|
---|
| 1354 |
|
---|
| 1355 | template<typename _UniformRandomNumberGenerator>
|
---|
| 1356 | result_type
|
---|
| 1357 | operator()(_UniformRandomNumberGenerator& __urng,
|
---|
| 1358 | const param_type& __p)
|
---|
| 1359 | {
|
---|
| 1360 | typename std::gamma_distribution<result_type>::param_type
|
---|
| 1361 | __pg(__p.mu(), __p.omega() / __p.mu());
|
---|
| 1362 | return std::sqrt(this->_M_gd(__pg, __urng));
|
---|
| 1363 | }
|
---|
| 1364 |
|
---|
| 1365 | template<typename _ForwardIterator,
|
---|
| 1366 | typename _UniformRandomNumberGenerator>
|
---|
| 1367 | void
|
---|
| 1368 | __generate(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 1369 | _UniformRandomNumberGenerator& __urng)
|
---|
| 1370 | { this->__generate(__f, __t, __urng, _M_param); }
|
---|
| 1371 |
|
---|
| 1372 | template<typename _ForwardIterator,
|
---|
| 1373 | typename _UniformRandomNumberGenerator>
|
---|
| 1374 | void
|
---|
| 1375 | __generate(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 1376 | _UniformRandomNumberGenerator& __urng,
|
---|
| 1377 | const param_type& __p)
|
---|
| 1378 | { this->__generate_impl(__f, __t, __urng, __p); }
|
---|
| 1379 |
|
---|
| 1380 | template<typename _UniformRandomNumberGenerator>
|
---|
| 1381 | void
|
---|
| 1382 | __generate(result_type* __f, result_type* __t,
|
---|
| 1383 | _UniformRandomNumberGenerator& __urng,
|
---|
| 1384 | const param_type& __p)
|
---|
| 1385 | { this->__generate_impl(__f, __t, __urng, __p); }
|
---|
| 1386 |
|
---|
| 1387 | /**
|
---|
| 1388 | * @brief Return true if two Nakagami distributions have
|
---|
| 1389 | * the same parameters and the sequences that would
|
---|
| 1390 | * be generated are equal.
|
---|
| 1391 | */
|
---|
| 1392 | friend bool
|
---|
| 1393 | operator==(const nakagami_distribution& __d1,
|
---|
| 1394 | const nakagami_distribution& __d2)
|
---|
| 1395 | { return (__d1._M_param == __d2._M_param
|
---|
| 1396 | && __d1._M_gd == __d2._M_gd); }
|
---|
| 1397 |
|
---|
| 1398 | /**
|
---|
| 1399 | * @brief Inserts a %nakagami_distribution random number distribution
|
---|
| 1400 | * @p __x into the output stream @p __os.
|
---|
| 1401 | *
|
---|
| 1402 | * @param __os An output stream.
|
---|
| 1403 | * @param __x A %nakagami_distribution random number distribution.
|
---|
| 1404 | *
|
---|
| 1405 | * @returns The output stream with the state of @p __x inserted or in
|
---|
| 1406 | * an error state.
|
---|
| 1407 | */
|
---|
| 1408 | template<typename _RealType1, typename _CharT, typename _Traits>
|
---|
| 1409 | friend std::basic_ostream<_CharT, _Traits>&
|
---|
| 1410 | operator<<(std::basic_ostream<_CharT, _Traits>&,
|
---|
| 1411 | const nakagami_distribution<_RealType1>&);
|
---|
| 1412 |
|
---|
| 1413 | /**
|
---|
| 1414 | * @brief Extracts a %nakagami_distribution random number distribution
|
---|
| 1415 | * @p __x from the input stream @p __is.
|
---|
| 1416 | *
|
---|
| 1417 | * @param __is An input stream.
|
---|
| 1418 | * @param __x A %nakagami_distribution random number
|
---|
| 1419 | * generator engine.
|
---|
| 1420 | *
|
---|
| 1421 | * @returns The input stream with @p __x extracted or in an error state.
|
---|
| 1422 | */
|
---|
| 1423 | template<typename _RealType1, typename _CharT, typename _Traits>
|
---|
| 1424 | friend std::basic_istream<_CharT, _Traits>&
|
---|
| 1425 | operator>>(std::basic_istream<_CharT, _Traits>&,
|
---|
| 1426 | nakagami_distribution<_RealType1>&);
|
---|
| 1427 |
|
---|
| 1428 | private:
|
---|
| 1429 | template<typename _ForwardIterator,
|
---|
| 1430 | typename _UniformRandomNumberGenerator>
|
---|
| 1431 | void
|
---|
| 1432 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 1433 | _UniformRandomNumberGenerator& __urng,
|
---|
| 1434 | const param_type& __p);
|
---|
| 1435 |
|
---|
| 1436 | param_type _M_param;
|
---|
| 1437 |
|
---|
| 1438 | std::gamma_distribution<result_type> _M_gd;
|
---|
| 1439 | };
|
---|
| 1440 |
|
---|
| 1441 | /**
|
---|
| 1442 | * @brief Return true if two Nakagami distributions are not equal.
|
---|
| 1443 | */
|
---|
| 1444 | template<typename _RealType>
|
---|
| 1445 | inline bool
|
---|
| 1446 | operator!=(const nakagami_distribution<_RealType>& __d1,
|
---|
| 1447 | const nakagami_distribution<_RealType>& __d2)
|
---|
| 1448 | { return !(__d1 == __d2); }
|
---|
| 1449 |
|
---|
| 1450 |
|
---|
| 1451 | /**
|
---|
| 1452 | * @brief A Pareto continuous distribution for random numbers.
|
---|
| 1453 | *
|
---|
| 1454 | * The formula for the Pareto cumulative probability function is
|
---|
| 1455 | * @f[
|
---|
| 1456 | * P(x|\alpha,\mu) = 1 - \left(\frac{\mu}{x}\right)^\alpha
|
---|
| 1457 | * @f]
|
---|
| 1458 | * The formula for the Pareto probability density function is
|
---|
| 1459 | * @f[
|
---|
| 1460 | * p(x|\alpha,\mu) = \frac{\alpha + 1}{\mu}
|
---|
| 1461 | * \left(\frac{\mu}{x}\right)^{\alpha + 1}
|
---|
| 1462 | * @f]
|
---|
| 1463 | * where @f$x >= \mu@f$ and @f$\mu > 0@f$, @f$\alpha > 0@f$.
|
---|
| 1464 | *
|
---|
| 1465 | * <table border=1 cellpadding=10 cellspacing=0>
|
---|
| 1466 | * <caption align=top>Distribution Statistics</caption>
|
---|
| 1467 | * <tr><td>Mean</td><td>@f$\alpha \mu / (\alpha - 1)@f$
|
---|
| 1468 | * for @f$\alpha > 1@f$</td></tr>
|
---|
| 1469 | * <tr><td>Variance</td><td>@f$\alpha \mu^2 / [(\alpha - 1)^2(\alpha - 2)]@f$
|
---|
| 1470 | * for @f$\alpha > 2@f$</td></tr>
|
---|
| 1471 | * <tr><td>Range</td><td>@f$[\mu, \infty)@f$</td></tr>
|
---|
| 1472 | * </table>
|
---|
| 1473 | */
|
---|
| 1474 | template<typename _RealType = double>
|
---|
| 1475 | class
|
---|
| 1476 | pareto_distribution
|
---|
| 1477 | {
|
---|
| 1478 | static_assert(std::is_floating_point<_RealType>::value,
|
---|
| 1479 | "template argument not a floating point type");
|
---|
| 1480 |
|
---|
| 1481 | public:
|
---|
| 1482 | /** The type of the range of the distribution. */
|
---|
| 1483 | typedef _RealType result_type;
|
---|
| 1484 |
|
---|
| 1485 | /** Parameter type. */
|
---|
| 1486 | struct param_type
|
---|
| 1487 | {
|
---|
| 1488 | typedef pareto_distribution<result_type> distribution_type;
|
---|
| 1489 |
|
---|
| 1490 | param_type() : param_type(1) { }
|
---|
| 1491 |
|
---|
| 1492 | param_type(result_type __alpha_val,
|
---|
| 1493 | result_type __mu_val = result_type(1))
|
---|
| 1494 | : _M_alpha(__alpha_val), _M_mu(__mu_val)
|
---|
| 1495 | {
|
---|
| 1496 | __glibcxx_assert(_M_alpha > result_type(0));
|
---|
| 1497 | __glibcxx_assert(_M_mu > result_type(0));
|
---|
| 1498 | }
|
---|
| 1499 |
|
---|
| 1500 | result_type
|
---|
| 1501 | alpha() const
|
---|
| 1502 | { return _M_alpha; }
|
---|
| 1503 |
|
---|
| 1504 | result_type
|
---|
| 1505 | mu() const
|
---|
| 1506 | { return _M_mu; }
|
---|
| 1507 |
|
---|
| 1508 | friend bool
|
---|
| 1509 | operator==(const param_type& __p1, const param_type& __p2)
|
---|
| 1510 | { return __p1._M_alpha == __p2._M_alpha && __p1._M_mu == __p2._M_mu; }
|
---|
| 1511 |
|
---|
| 1512 | friend bool
|
---|
| 1513 | operator!=(const param_type& __p1, const param_type& __p2)
|
---|
| 1514 | { return !(__p1 == __p2); }
|
---|
| 1515 |
|
---|
| 1516 | private:
|
---|
| 1517 | void _M_initialize();
|
---|
| 1518 |
|
---|
| 1519 | result_type _M_alpha;
|
---|
| 1520 | result_type _M_mu;
|
---|
| 1521 | };
|
---|
| 1522 |
|
---|
| 1523 | /**
|
---|
| 1524 | * @brief Constructors.
|
---|
| 1525 | * @{
|
---|
| 1526 | */
|
---|
| 1527 |
|
---|
| 1528 | pareto_distribution() : pareto_distribution(1) { }
|
---|
| 1529 |
|
---|
| 1530 | explicit
|
---|
| 1531 | pareto_distribution(result_type __alpha_val,
|
---|
| 1532 | result_type __mu_val = result_type(1))
|
---|
| 1533 | : _M_param(__alpha_val, __mu_val),
|
---|
| 1534 | _M_ud()
|
---|
| 1535 | { }
|
---|
| 1536 |
|
---|
| 1537 | explicit
|
---|
| 1538 | pareto_distribution(const param_type& __p)
|
---|
| 1539 | : _M_param(__p),
|
---|
| 1540 | _M_ud()
|
---|
| 1541 | { }
|
---|
| 1542 |
|
---|
| 1543 | /// @}
|
---|
| 1544 |
|
---|
| 1545 | /**
|
---|
| 1546 | * @brief Resets the distribution state.
|
---|
| 1547 | */
|
---|
| 1548 | void
|
---|
| 1549 | reset()
|
---|
| 1550 | {
|
---|
| 1551 | _M_ud.reset();
|
---|
| 1552 | }
|
---|
| 1553 |
|
---|
| 1554 | /**
|
---|
| 1555 | * @brief Return the parameters of the distribution.
|
---|
| 1556 | */
|
---|
| 1557 | result_type
|
---|
| 1558 | alpha() const
|
---|
| 1559 | { return _M_param.alpha(); }
|
---|
| 1560 |
|
---|
| 1561 | result_type
|
---|
| 1562 | mu() const
|
---|
| 1563 | { return _M_param.mu(); }
|
---|
| 1564 |
|
---|
| 1565 | /**
|
---|
| 1566 | * @brief Returns the parameter set of the distribution.
|
---|
| 1567 | */
|
---|
| 1568 | param_type
|
---|
| 1569 | param() const
|
---|
| 1570 | { return _M_param; }
|
---|
| 1571 |
|
---|
| 1572 | /**
|
---|
| 1573 | * @brief Sets the parameter set of the distribution.
|
---|
| 1574 | * @param __param The new parameter set of the distribution.
|
---|
| 1575 | */
|
---|
| 1576 | void
|
---|
| 1577 | param(const param_type& __param)
|
---|
| 1578 | { _M_param = __param; }
|
---|
| 1579 |
|
---|
| 1580 | /**
|
---|
| 1581 | * @brief Returns the greatest lower bound value of the distribution.
|
---|
| 1582 | */
|
---|
| 1583 | result_type
|
---|
| 1584 | min() const
|
---|
| 1585 | { return this->mu(); }
|
---|
| 1586 |
|
---|
| 1587 | /**
|
---|
| 1588 | * @brief Returns the least upper bound value of the distribution.
|
---|
| 1589 | */
|
---|
| 1590 | result_type
|
---|
| 1591 | max() const
|
---|
| 1592 | { return std::numeric_limits<result_type>::max(); }
|
---|
| 1593 |
|
---|
| 1594 | /**
|
---|
| 1595 | * @brief Generating functions.
|
---|
| 1596 | */
|
---|
| 1597 | template<typename _UniformRandomNumberGenerator>
|
---|
| 1598 | result_type
|
---|
| 1599 | operator()(_UniformRandomNumberGenerator& __urng)
|
---|
| 1600 | {
|
---|
| 1601 | return this->mu() * std::pow(this->_M_ud(__urng),
|
---|
| 1602 | -result_type(1) / this->alpha());
|
---|
| 1603 | }
|
---|
| 1604 |
|
---|
| 1605 | template<typename _UniformRandomNumberGenerator>
|
---|
| 1606 | result_type
|
---|
| 1607 | operator()(_UniformRandomNumberGenerator& __urng,
|
---|
| 1608 | const param_type& __p)
|
---|
| 1609 | {
|
---|
| 1610 | return __p.mu() * std::pow(this->_M_ud(__urng),
|
---|
| 1611 | -result_type(1) / __p.alpha());
|
---|
| 1612 | }
|
---|
| 1613 |
|
---|
| 1614 | template<typename _ForwardIterator,
|
---|
| 1615 | typename _UniformRandomNumberGenerator>
|
---|
| 1616 | void
|
---|
| 1617 | __generate(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 1618 | _UniformRandomNumberGenerator& __urng)
|
---|
| 1619 | { this->__generate(__f, __t, __urng, _M_param); }
|
---|
| 1620 |
|
---|
| 1621 | template<typename _ForwardIterator,
|
---|
| 1622 | typename _UniformRandomNumberGenerator>
|
---|
| 1623 | void
|
---|
| 1624 | __generate(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 1625 | _UniformRandomNumberGenerator& __urng,
|
---|
| 1626 | const param_type& __p)
|
---|
| 1627 | { this->__generate_impl(__f, __t, __urng, __p); }
|
---|
| 1628 |
|
---|
| 1629 | template<typename _UniformRandomNumberGenerator>
|
---|
| 1630 | void
|
---|
| 1631 | __generate(result_type* __f, result_type* __t,
|
---|
| 1632 | _UniformRandomNumberGenerator& __urng,
|
---|
| 1633 | const param_type& __p)
|
---|
| 1634 | { this->__generate_impl(__f, __t, __urng, __p); }
|
---|
| 1635 |
|
---|
| 1636 | /**
|
---|
| 1637 | * @brief Return true if two Pareto distributions have
|
---|
| 1638 | * the same parameters and the sequences that would
|
---|
| 1639 | * be generated are equal.
|
---|
| 1640 | */
|
---|
| 1641 | friend bool
|
---|
| 1642 | operator==(const pareto_distribution& __d1,
|
---|
| 1643 | const pareto_distribution& __d2)
|
---|
| 1644 | { return (__d1._M_param == __d2._M_param
|
---|
| 1645 | && __d1._M_ud == __d2._M_ud); }
|
---|
| 1646 |
|
---|
| 1647 | /**
|
---|
| 1648 | * @brief Inserts a %pareto_distribution random number distribution
|
---|
| 1649 | * @p __x into the output stream @p __os.
|
---|
| 1650 | *
|
---|
| 1651 | * @param __os An output stream.
|
---|
| 1652 | * @param __x A %pareto_distribution random number distribution.
|
---|
| 1653 | *
|
---|
| 1654 | * @returns The output stream with the state of @p __x inserted or in
|
---|
| 1655 | * an error state.
|
---|
| 1656 | */
|
---|
| 1657 | template<typename _RealType1, typename _CharT, typename _Traits>
|
---|
| 1658 | friend std::basic_ostream<_CharT, _Traits>&
|
---|
| 1659 | operator<<(std::basic_ostream<_CharT, _Traits>&,
|
---|
| 1660 | const pareto_distribution<_RealType1>&);
|
---|
| 1661 |
|
---|
| 1662 | /**
|
---|
| 1663 | * @brief Extracts a %pareto_distribution random number distribution
|
---|
| 1664 | * @p __x from the input stream @p __is.
|
---|
| 1665 | *
|
---|
| 1666 | * @param __is An input stream.
|
---|
| 1667 | * @param __x A %pareto_distribution random number
|
---|
| 1668 | * generator engine.
|
---|
| 1669 | *
|
---|
| 1670 | * @returns The input stream with @p __x extracted or in an error state.
|
---|
| 1671 | */
|
---|
| 1672 | template<typename _RealType1, typename _CharT, typename _Traits>
|
---|
| 1673 | friend std::basic_istream<_CharT, _Traits>&
|
---|
| 1674 | operator>>(std::basic_istream<_CharT, _Traits>&,
|
---|
| 1675 | pareto_distribution<_RealType1>&);
|
---|
| 1676 |
|
---|
| 1677 | private:
|
---|
| 1678 | template<typename _ForwardIterator,
|
---|
| 1679 | typename _UniformRandomNumberGenerator>
|
---|
| 1680 | void
|
---|
| 1681 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 1682 | _UniformRandomNumberGenerator& __urng,
|
---|
| 1683 | const param_type& __p);
|
---|
| 1684 |
|
---|
| 1685 | param_type _M_param;
|
---|
| 1686 |
|
---|
| 1687 | std::uniform_real_distribution<result_type> _M_ud;
|
---|
| 1688 | };
|
---|
| 1689 |
|
---|
| 1690 | /**
|
---|
| 1691 | * @brief Return true if two Pareto distributions are not equal.
|
---|
| 1692 | */
|
---|
| 1693 | template<typename _RealType>
|
---|
| 1694 | inline bool
|
---|
| 1695 | operator!=(const pareto_distribution<_RealType>& __d1,
|
---|
| 1696 | const pareto_distribution<_RealType>& __d2)
|
---|
| 1697 | { return !(__d1 == __d2); }
|
---|
| 1698 |
|
---|
| 1699 |
|
---|
| 1700 | /**
|
---|
| 1701 | * @brief A K continuous distribution for random numbers.
|
---|
| 1702 | *
|
---|
| 1703 | * The formula for the K probability density function is
|
---|
| 1704 | * @f[
|
---|
| 1705 | * p(x|\lambda, \mu, \nu) = \frac{2}{x}
|
---|
| 1706 | * \left(\frac{\lambda\nu x}{\mu}\right)^{\frac{\lambda + \nu}{2}}
|
---|
| 1707 | * \frac{1}{\Gamma(\lambda)\Gamma(\nu)}
|
---|
| 1708 | * K_{\nu - \lambda}\left(2\sqrt{\frac{\lambda\nu x}{\mu}}\right)
|
---|
| 1709 | * @f]
|
---|
| 1710 | * where @f$I_0(z)@f$ is the modified Bessel function of the second kind
|
---|
| 1711 | * of order @f$\nu - \lambda@f$ and @f$\lambda > 0@f$, @f$\mu > 0@f$
|
---|
| 1712 | * and @f$\nu > 0@f$.
|
---|
| 1713 | *
|
---|
| 1714 | * <table border=1 cellpadding=10 cellspacing=0>
|
---|
| 1715 | * <caption align=top>Distribution Statistics</caption>
|
---|
| 1716 | * <tr><td>Mean</td><td>@f$\mu@f$</td></tr>
|
---|
| 1717 | * <tr><td>Variance</td><td>@f$\mu^2\frac{\lambda + \nu + 1}{\lambda\nu}@f$</td></tr>
|
---|
| 1718 | * <tr><td>Range</td><td>@f$[0, \infty)@f$</td></tr>
|
---|
| 1719 | * </table>
|
---|
| 1720 | */
|
---|
| 1721 | template<typename _RealType = double>
|
---|
| 1722 | class
|
---|
| 1723 | k_distribution
|
---|
| 1724 | {
|
---|
| 1725 | static_assert(std::is_floating_point<_RealType>::value,
|
---|
| 1726 | "template argument not a floating point type");
|
---|
| 1727 |
|
---|
| 1728 | public:
|
---|
| 1729 | /** The type of the range of the distribution. */
|
---|
| 1730 | typedef _RealType result_type;
|
---|
| 1731 |
|
---|
| 1732 | /** Parameter type. */
|
---|
| 1733 | struct param_type
|
---|
| 1734 | {
|
---|
| 1735 | typedef k_distribution<result_type> distribution_type;
|
---|
| 1736 |
|
---|
| 1737 | param_type() : param_type(1) { }
|
---|
| 1738 |
|
---|
| 1739 | param_type(result_type __lambda_val,
|
---|
| 1740 | result_type __mu_val = result_type(1),
|
---|
| 1741 | result_type __nu_val = result_type(1))
|
---|
| 1742 | : _M_lambda(__lambda_val), _M_mu(__mu_val), _M_nu(__nu_val)
|
---|
| 1743 | {
|
---|
| 1744 | __glibcxx_assert(_M_lambda > result_type(0));
|
---|
| 1745 | __glibcxx_assert(_M_mu > result_type(0));
|
---|
| 1746 | __glibcxx_assert(_M_nu > result_type(0));
|
---|
| 1747 | }
|
---|
| 1748 |
|
---|
| 1749 | result_type
|
---|
| 1750 | lambda() const
|
---|
| 1751 | { return _M_lambda; }
|
---|
| 1752 |
|
---|
| 1753 | result_type
|
---|
| 1754 | mu() const
|
---|
| 1755 | { return _M_mu; }
|
---|
| 1756 |
|
---|
| 1757 | result_type
|
---|
| 1758 | nu() const
|
---|
| 1759 | { return _M_nu; }
|
---|
| 1760 |
|
---|
| 1761 | friend bool
|
---|
| 1762 | operator==(const param_type& __p1, const param_type& __p2)
|
---|
| 1763 | {
|
---|
| 1764 | return __p1._M_lambda == __p2._M_lambda
|
---|
| 1765 | && __p1._M_mu == __p2._M_mu
|
---|
| 1766 | && __p1._M_nu == __p2._M_nu;
|
---|
| 1767 | }
|
---|
| 1768 |
|
---|
| 1769 | friend bool
|
---|
| 1770 | operator!=(const param_type& __p1, const param_type& __p2)
|
---|
| 1771 | { return !(__p1 == __p2); }
|
---|
| 1772 |
|
---|
| 1773 | private:
|
---|
| 1774 | void _M_initialize();
|
---|
| 1775 |
|
---|
| 1776 | result_type _M_lambda;
|
---|
| 1777 | result_type _M_mu;
|
---|
| 1778 | result_type _M_nu;
|
---|
| 1779 | };
|
---|
| 1780 |
|
---|
| 1781 | /**
|
---|
| 1782 | * @brief Constructors.
|
---|
| 1783 | * @{
|
---|
| 1784 | */
|
---|
| 1785 |
|
---|
| 1786 | k_distribution() : k_distribution(1) { }
|
---|
| 1787 |
|
---|
| 1788 | explicit
|
---|
| 1789 | k_distribution(result_type __lambda_val,
|
---|
| 1790 | result_type __mu_val = result_type(1),
|
---|
| 1791 | result_type __nu_val = result_type(1))
|
---|
| 1792 | : _M_param(__lambda_val, __mu_val, __nu_val),
|
---|
| 1793 | _M_gd1(__lambda_val, result_type(1) / __lambda_val),
|
---|
| 1794 | _M_gd2(__nu_val, __mu_val / __nu_val)
|
---|
| 1795 | { }
|
---|
| 1796 |
|
---|
| 1797 | explicit
|
---|
| 1798 | k_distribution(const param_type& __p)
|
---|
| 1799 | : _M_param(__p),
|
---|
| 1800 | _M_gd1(__p.lambda(), result_type(1) / __p.lambda()),
|
---|
| 1801 | _M_gd2(__p.nu(), __p.mu() / __p.nu())
|
---|
| 1802 | { }
|
---|
| 1803 |
|
---|
| 1804 | /// @}
|
---|
| 1805 |
|
---|
| 1806 | /**
|
---|
| 1807 | * @brief Resets the distribution state.
|
---|
| 1808 | */
|
---|
| 1809 | void
|
---|
| 1810 | reset()
|
---|
| 1811 | {
|
---|
| 1812 | _M_gd1.reset();
|
---|
| 1813 | _M_gd2.reset();
|
---|
| 1814 | }
|
---|
| 1815 |
|
---|
| 1816 | /**
|
---|
| 1817 | * @brief Return the parameters of the distribution.
|
---|
| 1818 | */
|
---|
| 1819 | result_type
|
---|
| 1820 | lambda() const
|
---|
| 1821 | { return _M_param.lambda(); }
|
---|
| 1822 |
|
---|
| 1823 | result_type
|
---|
| 1824 | mu() const
|
---|
| 1825 | { return _M_param.mu(); }
|
---|
| 1826 |
|
---|
| 1827 | result_type
|
---|
| 1828 | nu() const
|
---|
| 1829 | { return _M_param.nu(); }
|
---|
| 1830 |
|
---|
| 1831 | /**
|
---|
| 1832 | * @brief Returns the parameter set of the distribution.
|
---|
| 1833 | */
|
---|
| 1834 | param_type
|
---|
| 1835 | param() const
|
---|
| 1836 | { return _M_param; }
|
---|
| 1837 |
|
---|
| 1838 | /**
|
---|
| 1839 | * @brief Sets the parameter set of the distribution.
|
---|
| 1840 | * @param __param The new parameter set of the distribution.
|
---|
| 1841 | */
|
---|
| 1842 | void
|
---|
| 1843 | param(const param_type& __param)
|
---|
| 1844 | { _M_param = __param; }
|
---|
| 1845 |
|
---|
| 1846 | /**
|
---|
| 1847 | * @brief Returns the greatest lower bound value of the distribution.
|
---|
| 1848 | */
|
---|
| 1849 | result_type
|
---|
| 1850 | min() const
|
---|
| 1851 | { return result_type(0); }
|
---|
| 1852 |
|
---|
| 1853 | /**
|
---|
| 1854 | * @brief Returns the least upper bound value of the distribution.
|
---|
| 1855 | */
|
---|
| 1856 | result_type
|
---|
| 1857 | max() const
|
---|
| 1858 | { return std::numeric_limits<result_type>::max(); }
|
---|
| 1859 |
|
---|
| 1860 | /**
|
---|
| 1861 | * @brief Generating functions.
|
---|
| 1862 | */
|
---|
| 1863 | template<typename _UniformRandomNumberGenerator>
|
---|
| 1864 | result_type
|
---|
| 1865 | operator()(_UniformRandomNumberGenerator&);
|
---|
| 1866 |
|
---|
| 1867 | template<typename _UniformRandomNumberGenerator>
|
---|
| 1868 | result_type
|
---|
| 1869 | operator()(_UniformRandomNumberGenerator&, const param_type&);
|
---|
| 1870 |
|
---|
| 1871 | template<typename _ForwardIterator,
|
---|
| 1872 | typename _UniformRandomNumberGenerator>
|
---|
| 1873 | void
|
---|
| 1874 | __generate(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 1875 | _UniformRandomNumberGenerator& __urng)
|
---|
| 1876 | { this->__generate(__f, __t, __urng, _M_param); }
|
---|
| 1877 |
|
---|
| 1878 | template<typename _ForwardIterator,
|
---|
| 1879 | typename _UniformRandomNumberGenerator>
|
---|
| 1880 | void
|
---|
| 1881 | __generate(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 1882 | _UniformRandomNumberGenerator& __urng,
|
---|
| 1883 | const param_type& __p)
|
---|
| 1884 | { this->__generate_impl(__f, __t, __urng, __p); }
|
---|
| 1885 |
|
---|
| 1886 | template<typename _UniformRandomNumberGenerator>
|
---|
| 1887 | void
|
---|
| 1888 | __generate(result_type* __f, result_type* __t,
|
---|
| 1889 | _UniformRandomNumberGenerator& __urng,
|
---|
| 1890 | const param_type& __p)
|
---|
| 1891 | { this->__generate_impl(__f, __t, __urng, __p); }
|
---|
| 1892 |
|
---|
| 1893 | /**
|
---|
| 1894 | * @brief Return true if two K distributions have
|
---|
| 1895 | * the same parameters and the sequences that would
|
---|
| 1896 | * be generated are equal.
|
---|
| 1897 | */
|
---|
| 1898 | friend bool
|
---|
| 1899 | operator==(const k_distribution& __d1,
|
---|
| 1900 | const k_distribution& __d2)
|
---|
| 1901 | { return (__d1._M_param == __d2._M_param
|
---|
| 1902 | && __d1._M_gd1 == __d2._M_gd1
|
---|
| 1903 | && __d1._M_gd2 == __d2._M_gd2); }
|
---|
| 1904 |
|
---|
| 1905 | /**
|
---|
| 1906 | * @brief Inserts a %k_distribution random number distribution
|
---|
| 1907 | * @p __x into the output stream @p __os.
|
---|
| 1908 | *
|
---|
| 1909 | * @param __os An output stream.
|
---|
| 1910 | * @param __x A %k_distribution random number distribution.
|
---|
| 1911 | *
|
---|
| 1912 | * @returns The output stream with the state of @p __x inserted or in
|
---|
| 1913 | * an error state.
|
---|
| 1914 | */
|
---|
| 1915 | template<typename _RealType1, typename _CharT, typename _Traits>
|
---|
| 1916 | friend std::basic_ostream<_CharT, _Traits>&
|
---|
| 1917 | operator<<(std::basic_ostream<_CharT, _Traits>&,
|
---|
| 1918 | const k_distribution<_RealType1>&);
|
---|
| 1919 |
|
---|
| 1920 | /**
|
---|
| 1921 | * @brief Extracts a %k_distribution random number distribution
|
---|
| 1922 | * @p __x from the input stream @p __is.
|
---|
| 1923 | *
|
---|
| 1924 | * @param __is An input stream.
|
---|
| 1925 | * @param __x A %k_distribution random number
|
---|
| 1926 | * generator engine.
|
---|
| 1927 | *
|
---|
| 1928 | * @returns The input stream with @p __x extracted or in an error state.
|
---|
| 1929 | */
|
---|
| 1930 | template<typename _RealType1, typename _CharT, typename _Traits>
|
---|
| 1931 | friend std::basic_istream<_CharT, _Traits>&
|
---|
| 1932 | operator>>(std::basic_istream<_CharT, _Traits>&,
|
---|
| 1933 | k_distribution<_RealType1>&);
|
---|
| 1934 |
|
---|
| 1935 | private:
|
---|
| 1936 | template<typename _ForwardIterator,
|
---|
| 1937 | typename _UniformRandomNumberGenerator>
|
---|
| 1938 | void
|
---|
| 1939 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 1940 | _UniformRandomNumberGenerator& __urng,
|
---|
| 1941 | const param_type& __p);
|
---|
| 1942 |
|
---|
| 1943 | param_type _M_param;
|
---|
| 1944 |
|
---|
| 1945 | std::gamma_distribution<result_type> _M_gd1;
|
---|
| 1946 | std::gamma_distribution<result_type> _M_gd2;
|
---|
| 1947 | };
|
---|
| 1948 |
|
---|
| 1949 | /**
|
---|
| 1950 | * @brief Return true if two K distributions are not equal.
|
---|
| 1951 | */
|
---|
| 1952 | template<typename _RealType>
|
---|
| 1953 | inline bool
|
---|
| 1954 | operator!=(const k_distribution<_RealType>& __d1,
|
---|
| 1955 | const k_distribution<_RealType>& __d2)
|
---|
| 1956 | { return !(__d1 == __d2); }
|
---|
| 1957 |
|
---|
| 1958 |
|
---|
| 1959 | /**
|
---|
| 1960 | * @brief An arcsine continuous distribution for random numbers.
|
---|
| 1961 | *
|
---|
| 1962 | * The formula for the arcsine probability density function is
|
---|
| 1963 | * @f[
|
---|
| 1964 | * p(x|a,b) = \frac{1}{\pi \sqrt{(x - a)(b - x)}}
|
---|
| 1965 | * @f]
|
---|
| 1966 | * where @f$x >= a@f$ and @f$x <= b@f$.
|
---|
| 1967 | *
|
---|
| 1968 | * <table border=1 cellpadding=10 cellspacing=0>
|
---|
| 1969 | * <caption align=top>Distribution Statistics</caption>
|
---|
| 1970 | * <tr><td>Mean</td><td>@f$ (a + b) / 2 @f$</td></tr>
|
---|
| 1971 | * <tr><td>Variance</td><td>@f$ (b - a)^2 / 8 @f$</td></tr>
|
---|
| 1972 | * <tr><td>Range</td><td>@f$[a, b]@f$</td></tr>
|
---|
| 1973 | * </table>
|
---|
| 1974 | */
|
---|
| 1975 | template<typename _RealType = double>
|
---|
| 1976 | class
|
---|
| 1977 | arcsine_distribution
|
---|
| 1978 | {
|
---|
| 1979 | static_assert(std::is_floating_point<_RealType>::value,
|
---|
| 1980 | "template argument not a floating point type");
|
---|
| 1981 |
|
---|
| 1982 | public:
|
---|
| 1983 | /** The type of the range of the distribution. */
|
---|
| 1984 | typedef _RealType result_type;
|
---|
| 1985 |
|
---|
| 1986 | /** Parameter type. */
|
---|
| 1987 | struct param_type
|
---|
| 1988 | {
|
---|
| 1989 | typedef arcsine_distribution<result_type> distribution_type;
|
---|
| 1990 |
|
---|
| 1991 | param_type() : param_type(0) { }
|
---|
| 1992 |
|
---|
| 1993 | param_type(result_type __a, result_type __b = result_type(1))
|
---|
| 1994 | : _M_a(__a), _M_b(__b)
|
---|
| 1995 | {
|
---|
| 1996 | __glibcxx_assert(_M_a <= _M_b);
|
---|
| 1997 | }
|
---|
| 1998 |
|
---|
| 1999 | result_type
|
---|
| 2000 | a() const
|
---|
| 2001 | { return _M_a; }
|
---|
| 2002 |
|
---|
| 2003 | result_type
|
---|
| 2004 | b() const
|
---|
| 2005 | { return _M_b; }
|
---|
| 2006 |
|
---|
| 2007 | friend bool
|
---|
| 2008 | operator==(const param_type& __p1, const param_type& __p2)
|
---|
| 2009 | { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; }
|
---|
| 2010 |
|
---|
| 2011 | friend bool
|
---|
| 2012 | operator!=(const param_type& __p1, const param_type& __p2)
|
---|
| 2013 | { return !(__p1 == __p2); }
|
---|
| 2014 |
|
---|
| 2015 | private:
|
---|
| 2016 | void _M_initialize();
|
---|
| 2017 |
|
---|
| 2018 | result_type _M_a;
|
---|
| 2019 | result_type _M_b;
|
---|
| 2020 | };
|
---|
| 2021 |
|
---|
| 2022 | /**
|
---|
| 2023 | * @brief Constructors.
|
---|
| 2024 | * :{
|
---|
| 2025 | */
|
---|
| 2026 |
|
---|
| 2027 | arcsine_distribution() : arcsine_distribution(0) { }
|
---|
| 2028 |
|
---|
| 2029 | explicit
|
---|
| 2030 | arcsine_distribution(result_type __a, result_type __b = result_type(1))
|
---|
| 2031 | : _M_param(__a, __b),
|
---|
| 2032 | _M_ud(-1.5707963267948966192313216916397514L,
|
---|
| 2033 | +1.5707963267948966192313216916397514L)
|
---|
| 2034 | { }
|
---|
| 2035 |
|
---|
| 2036 | explicit
|
---|
| 2037 | arcsine_distribution(const param_type& __p)
|
---|
| 2038 | : _M_param(__p),
|
---|
| 2039 | _M_ud(-1.5707963267948966192313216916397514L,
|
---|
| 2040 | +1.5707963267948966192313216916397514L)
|
---|
| 2041 | { }
|
---|
| 2042 |
|
---|
| 2043 | /// @}
|
---|
| 2044 |
|
---|
| 2045 | /**
|
---|
| 2046 | * @brief Resets the distribution state.
|
---|
| 2047 | */
|
---|
| 2048 | void
|
---|
| 2049 | reset()
|
---|
| 2050 | { _M_ud.reset(); }
|
---|
| 2051 |
|
---|
| 2052 | /**
|
---|
| 2053 | * @brief Return the parameters of the distribution.
|
---|
| 2054 | */
|
---|
| 2055 | result_type
|
---|
| 2056 | a() const
|
---|
| 2057 | { return _M_param.a(); }
|
---|
| 2058 |
|
---|
| 2059 | result_type
|
---|
| 2060 | b() const
|
---|
| 2061 | { return _M_param.b(); }
|
---|
| 2062 |
|
---|
| 2063 | /**
|
---|
| 2064 | * @brief Returns the parameter set of the distribution.
|
---|
| 2065 | */
|
---|
| 2066 | param_type
|
---|
| 2067 | param() const
|
---|
| 2068 | { return _M_param; }
|
---|
| 2069 |
|
---|
| 2070 | /**
|
---|
| 2071 | * @brief Sets the parameter set of the distribution.
|
---|
| 2072 | * @param __param The new parameter set of the distribution.
|
---|
| 2073 | */
|
---|
| 2074 | void
|
---|
| 2075 | param(const param_type& __param)
|
---|
| 2076 | { _M_param = __param; }
|
---|
| 2077 |
|
---|
| 2078 | /**
|
---|
| 2079 | * @brief Returns the greatest lower bound value of the distribution.
|
---|
| 2080 | */
|
---|
| 2081 | result_type
|
---|
| 2082 | min() const
|
---|
| 2083 | { return this->a(); }
|
---|
| 2084 |
|
---|
| 2085 | /**
|
---|
| 2086 | * @brief Returns the least upper bound value of the distribution.
|
---|
| 2087 | */
|
---|
| 2088 | result_type
|
---|
| 2089 | max() const
|
---|
| 2090 | { return this->b(); }
|
---|
| 2091 |
|
---|
| 2092 | /**
|
---|
| 2093 | * @brief Generating functions.
|
---|
| 2094 | */
|
---|
| 2095 | template<typename _UniformRandomNumberGenerator>
|
---|
| 2096 | result_type
|
---|
| 2097 | operator()(_UniformRandomNumberGenerator& __urng)
|
---|
| 2098 | {
|
---|
| 2099 | result_type __x = std::sin(this->_M_ud(__urng));
|
---|
| 2100 | return (__x * (this->b() - this->a())
|
---|
| 2101 | + this->a() + this->b()) / result_type(2);
|
---|
| 2102 | }
|
---|
| 2103 |
|
---|
| 2104 | template<typename _UniformRandomNumberGenerator>
|
---|
| 2105 | result_type
|
---|
| 2106 | operator()(_UniformRandomNumberGenerator& __urng,
|
---|
| 2107 | const param_type& __p)
|
---|
| 2108 | {
|
---|
| 2109 | result_type __x = std::sin(this->_M_ud(__urng));
|
---|
| 2110 | return (__x * (__p.b() - __p.a())
|
---|
| 2111 | + __p.a() + __p.b()) / result_type(2);
|
---|
| 2112 | }
|
---|
| 2113 |
|
---|
| 2114 | template<typename _ForwardIterator,
|
---|
| 2115 | typename _UniformRandomNumberGenerator>
|
---|
| 2116 | void
|
---|
| 2117 | __generate(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 2118 | _UniformRandomNumberGenerator& __urng)
|
---|
| 2119 | { this->__generate(__f, __t, __urng, _M_param); }
|
---|
| 2120 |
|
---|
| 2121 | template<typename _ForwardIterator,
|
---|
| 2122 | typename _UniformRandomNumberGenerator>
|
---|
| 2123 | void
|
---|
| 2124 | __generate(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 2125 | _UniformRandomNumberGenerator& __urng,
|
---|
| 2126 | const param_type& __p)
|
---|
| 2127 | { this->__generate_impl(__f, __t, __urng, __p); }
|
---|
| 2128 |
|
---|
| 2129 | template<typename _UniformRandomNumberGenerator>
|
---|
| 2130 | void
|
---|
| 2131 | __generate(result_type* __f, result_type* __t,
|
---|
| 2132 | _UniformRandomNumberGenerator& __urng,
|
---|
| 2133 | const param_type& __p)
|
---|
| 2134 | { this->__generate_impl(__f, __t, __urng, __p); }
|
---|
| 2135 |
|
---|
| 2136 | /**
|
---|
| 2137 | * @brief Return true if two arcsine distributions have
|
---|
| 2138 | * the same parameters and the sequences that would
|
---|
| 2139 | * be generated are equal.
|
---|
| 2140 | */
|
---|
| 2141 | friend bool
|
---|
| 2142 | operator==(const arcsine_distribution& __d1,
|
---|
| 2143 | const arcsine_distribution& __d2)
|
---|
| 2144 | { return (__d1._M_param == __d2._M_param
|
---|
| 2145 | && __d1._M_ud == __d2._M_ud); }
|
---|
| 2146 |
|
---|
| 2147 | /**
|
---|
| 2148 | * @brief Inserts a %arcsine_distribution random number distribution
|
---|
| 2149 | * @p __x into the output stream @p __os.
|
---|
| 2150 | *
|
---|
| 2151 | * @param __os An output stream.
|
---|
| 2152 | * @param __x A %arcsine_distribution random number distribution.
|
---|
| 2153 | *
|
---|
| 2154 | * @returns The output stream with the state of @p __x inserted or in
|
---|
| 2155 | * an error state.
|
---|
| 2156 | */
|
---|
| 2157 | template<typename _RealType1, typename _CharT, typename _Traits>
|
---|
| 2158 | friend std::basic_ostream<_CharT, _Traits>&
|
---|
| 2159 | operator<<(std::basic_ostream<_CharT, _Traits>&,
|
---|
| 2160 | const arcsine_distribution<_RealType1>&);
|
---|
| 2161 |
|
---|
| 2162 | /**
|
---|
| 2163 | * @brief Extracts a %arcsine_distribution random number distribution
|
---|
| 2164 | * @p __x from the input stream @p __is.
|
---|
| 2165 | *
|
---|
| 2166 | * @param __is An input stream.
|
---|
| 2167 | * @param __x A %arcsine_distribution random number
|
---|
| 2168 | * generator engine.
|
---|
| 2169 | *
|
---|
| 2170 | * @returns The input stream with @p __x extracted or in an error state.
|
---|
| 2171 | */
|
---|
| 2172 | template<typename _RealType1, typename _CharT, typename _Traits>
|
---|
| 2173 | friend std::basic_istream<_CharT, _Traits>&
|
---|
| 2174 | operator>>(std::basic_istream<_CharT, _Traits>&,
|
---|
| 2175 | arcsine_distribution<_RealType1>&);
|
---|
| 2176 |
|
---|
| 2177 | private:
|
---|
| 2178 | template<typename _ForwardIterator,
|
---|
| 2179 | typename _UniformRandomNumberGenerator>
|
---|
| 2180 | void
|
---|
| 2181 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 2182 | _UniformRandomNumberGenerator& __urng,
|
---|
| 2183 | const param_type& __p);
|
---|
| 2184 |
|
---|
| 2185 | param_type _M_param;
|
---|
| 2186 |
|
---|
| 2187 | std::uniform_real_distribution<result_type> _M_ud;
|
---|
| 2188 | };
|
---|
| 2189 |
|
---|
| 2190 | /**
|
---|
| 2191 | * @brief Return true if two arcsine distributions are not equal.
|
---|
| 2192 | */
|
---|
| 2193 | template<typename _RealType>
|
---|
| 2194 | inline bool
|
---|
| 2195 | operator!=(const arcsine_distribution<_RealType>& __d1,
|
---|
| 2196 | const arcsine_distribution<_RealType>& __d2)
|
---|
| 2197 | { return !(__d1 == __d2); }
|
---|
| 2198 |
|
---|
| 2199 |
|
---|
| 2200 | /**
|
---|
| 2201 | * @brief A Hoyt continuous distribution for random numbers.
|
---|
| 2202 | *
|
---|
| 2203 | * The formula for the Hoyt probability density function is
|
---|
| 2204 | * @f[
|
---|
| 2205 | * p(x|q,\omega) = \frac{(1 + q^2)x}{q\omega}
|
---|
| 2206 | * \exp\left(-\frac{(1 + q^2)^2 x^2}{4 q^2 \omega}\right)
|
---|
| 2207 | * I_0\left(\frac{(1 - q^4) x^2}{4 q^2 \omega}\right)
|
---|
| 2208 | * @f]
|
---|
| 2209 | * where @f$I_0(z)@f$ is the modified Bessel function of the first kind
|
---|
| 2210 | * of order 0 and @f$0 < q < 1@f$.
|
---|
| 2211 | *
|
---|
| 2212 | * <table border=1 cellpadding=10 cellspacing=0>
|
---|
| 2213 | * <caption align=top>Distribution Statistics</caption>
|
---|
| 2214 | * <tr><td>Mean</td><td>@f$ \sqrt{\frac{2}{\pi}} \sqrt{\frac{\omega}{1 + q^2}}
|
---|
| 2215 | * E(1 - q^2) @f$</td></tr>
|
---|
| 2216 | * <tr><td>Variance</td><td>@f$ \omega \left(1 - \frac{2E^2(1 - q^2)}
|
---|
| 2217 | * {\pi (1 + q^2)}\right) @f$</td></tr>
|
---|
| 2218 | * <tr><td>Range</td><td>@f$[0, \infty)@f$</td></tr>
|
---|
| 2219 | * </table>
|
---|
| 2220 | * where @f$E(x)@f$ is the elliptic function of the second kind.
|
---|
| 2221 | */
|
---|
| 2222 | template<typename _RealType = double>
|
---|
| 2223 | class
|
---|
| 2224 | hoyt_distribution
|
---|
| 2225 | {
|
---|
| 2226 | static_assert(std::is_floating_point<_RealType>::value,
|
---|
| 2227 | "template argument not a floating point type");
|
---|
| 2228 |
|
---|
| 2229 | public:
|
---|
| 2230 | /** The type of the range of the distribution. */
|
---|
| 2231 | typedef _RealType result_type;
|
---|
| 2232 |
|
---|
| 2233 | /** Parameter type. */
|
---|
| 2234 | struct param_type
|
---|
| 2235 | {
|
---|
| 2236 | typedef hoyt_distribution<result_type> distribution_type;
|
---|
| 2237 |
|
---|
| 2238 | param_type() : param_type(0.5) { }
|
---|
| 2239 |
|
---|
| 2240 | param_type(result_type __q, result_type __omega = result_type(1))
|
---|
| 2241 | : _M_q(__q), _M_omega(__omega)
|
---|
| 2242 | {
|
---|
| 2243 | __glibcxx_assert(_M_q > result_type(0));
|
---|
| 2244 | __glibcxx_assert(_M_q < result_type(1));
|
---|
| 2245 | }
|
---|
| 2246 |
|
---|
| 2247 | result_type
|
---|
| 2248 | q() const
|
---|
| 2249 | { return _M_q; }
|
---|
| 2250 |
|
---|
| 2251 | result_type
|
---|
| 2252 | omega() const
|
---|
| 2253 | { return _M_omega; }
|
---|
| 2254 |
|
---|
| 2255 | friend bool
|
---|
| 2256 | operator==(const param_type& __p1, const param_type& __p2)
|
---|
| 2257 | { return __p1._M_q == __p2._M_q && __p1._M_omega == __p2._M_omega; }
|
---|
| 2258 |
|
---|
| 2259 | friend bool
|
---|
| 2260 | operator!=(const param_type& __p1, const param_type& __p2)
|
---|
| 2261 | { return !(__p1 == __p2); }
|
---|
| 2262 |
|
---|
| 2263 | private:
|
---|
| 2264 | void _M_initialize();
|
---|
| 2265 |
|
---|
| 2266 | result_type _M_q;
|
---|
| 2267 | result_type _M_omega;
|
---|
| 2268 | };
|
---|
| 2269 |
|
---|
| 2270 | /**
|
---|
| 2271 | * @brief Constructors.
|
---|
| 2272 | * @{
|
---|
| 2273 | */
|
---|
| 2274 |
|
---|
| 2275 | hoyt_distribution() : hoyt_distribution(0.5) { }
|
---|
| 2276 |
|
---|
| 2277 | explicit
|
---|
| 2278 | hoyt_distribution(result_type __q, result_type __omega = result_type(1))
|
---|
| 2279 | : _M_param(__q, __omega),
|
---|
| 2280 | _M_ad(result_type(0.5L) * (result_type(1) + __q * __q),
|
---|
| 2281 | result_type(0.5L) * (result_type(1) + __q * __q)
|
---|
| 2282 | / (__q * __q)),
|
---|
| 2283 | _M_ed(result_type(1))
|
---|
| 2284 | { }
|
---|
| 2285 |
|
---|
| 2286 | explicit
|
---|
| 2287 | hoyt_distribution(const param_type& __p)
|
---|
| 2288 | : _M_param(__p),
|
---|
| 2289 | _M_ad(result_type(0.5L) * (result_type(1) + __p.q() * __p.q()),
|
---|
| 2290 | result_type(0.5L) * (result_type(1) + __p.q() * __p.q())
|
---|
| 2291 | / (__p.q() * __p.q())),
|
---|
| 2292 | _M_ed(result_type(1))
|
---|
| 2293 | { }
|
---|
| 2294 |
|
---|
| 2295 | /**
|
---|
| 2296 | * @brief Resets the distribution state.
|
---|
| 2297 | */
|
---|
| 2298 | void
|
---|
| 2299 | reset()
|
---|
| 2300 | {
|
---|
| 2301 | _M_ad.reset();
|
---|
| 2302 | _M_ed.reset();
|
---|
| 2303 | }
|
---|
| 2304 |
|
---|
| 2305 | /**
|
---|
| 2306 | * @brief Return the parameters of the distribution.
|
---|
| 2307 | */
|
---|
| 2308 | result_type
|
---|
| 2309 | q() const
|
---|
| 2310 | { return _M_param.q(); }
|
---|
| 2311 |
|
---|
| 2312 | result_type
|
---|
| 2313 | omega() const
|
---|
| 2314 | { return _M_param.omega(); }
|
---|
| 2315 |
|
---|
| 2316 | /**
|
---|
| 2317 | * @brief Returns the parameter set of the distribution.
|
---|
| 2318 | */
|
---|
| 2319 | param_type
|
---|
| 2320 | param() const
|
---|
| 2321 | { return _M_param; }
|
---|
| 2322 |
|
---|
| 2323 | /**
|
---|
| 2324 | * @brief Sets the parameter set of the distribution.
|
---|
| 2325 | * @param __param The new parameter set of the distribution.
|
---|
| 2326 | */
|
---|
| 2327 | void
|
---|
| 2328 | param(const param_type& __param)
|
---|
| 2329 | { _M_param = __param; }
|
---|
| 2330 |
|
---|
| 2331 | /**
|
---|
| 2332 | * @brief Returns the greatest lower bound value of the distribution.
|
---|
| 2333 | */
|
---|
| 2334 | result_type
|
---|
| 2335 | min() const
|
---|
| 2336 | { return result_type(0); }
|
---|
| 2337 |
|
---|
| 2338 | /**
|
---|
| 2339 | * @brief Returns the least upper bound value of the distribution.
|
---|
| 2340 | */
|
---|
| 2341 | result_type
|
---|
| 2342 | max() const
|
---|
| 2343 | { return std::numeric_limits<result_type>::max(); }
|
---|
| 2344 |
|
---|
| 2345 | /**
|
---|
| 2346 | * @brief Generating functions.
|
---|
| 2347 | */
|
---|
| 2348 | template<typename _UniformRandomNumberGenerator>
|
---|
| 2349 | result_type
|
---|
| 2350 | operator()(_UniformRandomNumberGenerator& __urng);
|
---|
| 2351 |
|
---|
| 2352 | template<typename _UniformRandomNumberGenerator>
|
---|
| 2353 | result_type
|
---|
| 2354 | operator()(_UniformRandomNumberGenerator& __urng,
|
---|
| 2355 | const param_type& __p);
|
---|
| 2356 |
|
---|
| 2357 | template<typename _ForwardIterator,
|
---|
| 2358 | typename _UniformRandomNumberGenerator>
|
---|
| 2359 | void
|
---|
| 2360 | __generate(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 2361 | _UniformRandomNumberGenerator& __urng)
|
---|
| 2362 | { this->__generate(__f, __t, __urng, _M_param); }
|
---|
| 2363 |
|
---|
| 2364 | template<typename _ForwardIterator,
|
---|
| 2365 | typename _UniformRandomNumberGenerator>
|
---|
| 2366 | void
|
---|
| 2367 | __generate(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 2368 | _UniformRandomNumberGenerator& __urng,
|
---|
| 2369 | const param_type& __p)
|
---|
| 2370 | { this->__generate_impl(__f, __t, __urng, __p); }
|
---|
| 2371 |
|
---|
| 2372 | template<typename _UniformRandomNumberGenerator>
|
---|
| 2373 | void
|
---|
| 2374 | __generate(result_type* __f, result_type* __t,
|
---|
| 2375 | _UniformRandomNumberGenerator& __urng,
|
---|
| 2376 | const param_type& __p)
|
---|
| 2377 | { this->__generate_impl(__f, __t, __urng, __p); }
|
---|
| 2378 |
|
---|
| 2379 | /**
|
---|
| 2380 | * @brief Return true if two Hoyt distributions have
|
---|
| 2381 | * the same parameters and the sequences that would
|
---|
| 2382 | * be generated are equal.
|
---|
| 2383 | */
|
---|
| 2384 | friend bool
|
---|
| 2385 | operator==(const hoyt_distribution& __d1,
|
---|
| 2386 | const hoyt_distribution& __d2)
|
---|
| 2387 | { return (__d1._M_param == __d2._M_param
|
---|
| 2388 | && __d1._M_ad == __d2._M_ad
|
---|
| 2389 | && __d1._M_ed == __d2._M_ed); }
|
---|
| 2390 |
|
---|
| 2391 | /**
|
---|
| 2392 | * @brief Inserts a %hoyt_distribution random number distribution
|
---|
| 2393 | * @p __x into the output stream @p __os.
|
---|
| 2394 | *
|
---|
| 2395 | * @param __os An output stream.
|
---|
| 2396 | * @param __x A %hoyt_distribution random number distribution.
|
---|
| 2397 | *
|
---|
| 2398 | * @returns The output stream with the state of @p __x inserted or in
|
---|
| 2399 | * an error state.
|
---|
| 2400 | */
|
---|
| 2401 | template<typename _RealType1, typename _CharT, typename _Traits>
|
---|
| 2402 | friend std::basic_ostream<_CharT, _Traits>&
|
---|
| 2403 | operator<<(std::basic_ostream<_CharT, _Traits>&,
|
---|
| 2404 | const hoyt_distribution<_RealType1>&);
|
---|
| 2405 |
|
---|
| 2406 | /**
|
---|
| 2407 | * @brief Extracts a %hoyt_distribution random number distribution
|
---|
| 2408 | * @p __x from the input stream @p __is.
|
---|
| 2409 | *
|
---|
| 2410 | * @param __is An input stream.
|
---|
| 2411 | * @param __x A %hoyt_distribution random number
|
---|
| 2412 | * generator engine.
|
---|
| 2413 | *
|
---|
| 2414 | * @returns The input stream with @p __x extracted or in an error state.
|
---|
| 2415 | */
|
---|
| 2416 | template<typename _RealType1, typename _CharT, typename _Traits>
|
---|
| 2417 | friend std::basic_istream<_CharT, _Traits>&
|
---|
| 2418 | operator>>(std::basic_istream<_CharT, _Traits>&,
|
---|
| 2419 | hoyt_distribution<_RealType1>&);
|
---|
| 2420 |
|
---|
| 2421 | private:
|
---|
| 2422 | template<typename _ForwardIterator,
|
---|
| 2423 | typename _UniformRandomNumberGenerator>
|
---|
| 2424 | void
|
---|
| 2425 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 2426 | _UniformRandomNumberGenerator& __urng,
|
---|
| 2427 | const param_type& __p);
|
---|
| 2428 |
|
---|
| 2429 | param_type _M_param;
|
---|
| 2430 |
|
---|
| 2431 | __gnu_cxx::arcsine_distribution<result_type> _M_ad;
|
---|
| 2432 | std::exponential_distribution<result_type> _M_ed;
|
---|
| 2433 | };
|
---|
| 2434 |
|
---|
| 2435 | /**
|
---|
| 2436 | * @brief Return true if two Hoyt distributions are not equal.
|
---|
| 2437 | */
|
---|
| 2438 | template<typename _RealType>
|
---|
| 2439 | inline bool
|
---|
| 2440 | operator!=(const hoyt_distribution<_RealType>& __d1,
|
---|
| 2441 | const hoyt_distribution<_RealType>& __d2)
|
---|
| 2442 | { return !(__d1 == __d2); }
|
---|
| 2443 |
|
---|
| 2444 |
|
---|
| 2445 | /**
|
---|
| 2446 | * @brief A triangular distribution for random numbers.
|
---|
| 2447 | *
|
---|
| 2448 | * The formula for the triangular probability density function is
|
---|
| 2449 | * @f[
|
---|
| 2450 | * / 0 for x < a
|
---|
| 2451 | * p(x|a,b,c) = | \frac{2(x-a)}{(c-a)(b-a)} for a <= x <= b
|
---|
| 2452 | * | \frac{2(c-x)}{(c-a)(c-b)} for b < x <= c
|
---|
| 2453 | * \ 0 for c < x
|
---|
| 2454 | * @f]
|
---|
| 2455 | *
|
---|
| 2456 | * <table border=1 cellpadding=10 cellspacing=0>
|
---|
| 2457 | * <caption align=top>Distribution Statistics</caption>
|
---|
| 2458 | * <tr><td>Mean</td><td>@f$ \frac{a+b+c}{2} @f$</td></tr>
|
---|
| 2459 | * <tr><td>Variance</td><td>@f$ \frac{a^2+b^2+c^2-ab-ac-bc}
|
---|
| 2460 | * {18}@f$</td></tr>
|
---|
| 2461 | * <tr><td>Range</td><td>@f$[a, c]@f$</td></tr>
|
---|
| 2462 | * </table>
|
---|
| 2463 | */
|
---|
| 2464 | template<typename _RealType = double>
|
---|
| 2465 | class triangular_distribution
|
---|
| 2466 | {
|
---|
| 2467 | static_assert(std::is_floating_point<_RealType>::value,
|
---|
| 2468 | "template argument not a floating point type");
|
---|
| 2469 |
|
---|
| 2470 | public:
|
---|
| 2471 | /** The type of the range of the distribution. */
|
---|
| 2472 | typedef _RealType result_type;
|
---|
| 2473 |
|
---|
| 2474 | /** Parameter type. */
|
---|
| 2475 | struct param_type
|
---|
| 2476 | {
|
---|
| 2477 | friend class triangular_distribution<_RealType>;
|
---|
| 2478 |
|
---|
| 2479 | param_type() : param_type(0) { }
|
---|
| 2480 |
|
---|
| 2481 | explicit
|
---|
| 2482 | param_type(_RealType __a,
|
---|
| 2483 | _RealType __b = _RealType(0.5),
|
---|
| 2484 | _RealType __c = _RealType(1))
|
---|
| 2485 | : _M_a(__a), _M_b(__b), _M_c(__c)
|
---|
| 2486 | {
|
---|
| 2487 | __glibcxx_assert(_M_a <= _M_b);
|
---|
| 2488 | __glibcxx_assert(_M_b <= _M_c);
|
---|
| 2489 | __glibcxx_assert(_M_a < _M_c);
|
---|
| 2490 |
|
---|
| 2491 | _M_r_ab = (_M_b - _M_a) / (_M_c - _M_a);
|
---|
| 2492 | _M_f_ab_ac = (_M_b - _M_a) * (_M_c - _M_a);
|
---|
| 2493 | _M_f_bc_ac = (_M_c - _M_b) * (_M_c - _M_a);
|
---|
| 2494 | }
|
---|
| 2495 |
|
---|
| 2496 | _RealType
|
---|
| 2497 | a() const
|
---|
| 2498 | { return _M_a; }
|
---|
| 2499 |
|
---|
| 2500 | _RealType
|
---|
| 2501 | b() const
|
---|
| 2502 | { return _M_b; }
|
---|
| 2503 |
|
---|
| 2504 | _RealType
|
---|
| 2505 | c() const
|
---|
| 2506 | { return _M_c; }
|
---|
| 2507 |
|
---|
| 2508 | friend bool
|
---|
| 2509 | operator==(const param_type& __p1, const param_type& __p2)
|
---|
| 2510 | {
|
---|
| 2511 | return (__p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b
|
---|
| 2512 | && __p1._M_c == __p2._M_c);
|
---|
| 2513 | }
|
---|
| 2514 |
|
---|
| 2515 | friend bool
|
---|
| 2516 | operator!=(const param_type& __p1, const param_type& __p2)
|
---|
| 2517 | { return !(__p1 == __p2); }
|
---|
| 2518 |
|
---|
| 2519 | private:
|
---|
| 2520 |
|
---|
| 2521 | _RealType _M_a;
|
---|
| 2522 | _RealType _M_b;
|
---|
| 2523 | _RealType _M_c;
|
---|
| 2524 | _RealType _M_r_ab;
|
---|
| 2525 | _RealType _M_f_ab_ac;
|
---|
| 2526 | _RealType _M_f_bc_ac;
|
---|
| 2527 | };
|
---|
| 2528 |
|
---|
| 2529 | triangular_distribution() : triangular_distribution(0.0) { }
|
---|
| 2530 |
|
---|
| 2531 | /**
|
---|
| 2532 | * @brief Constructs a triangle distribution with parameters
|
---|
| 2533 | * @f$ a @f$, @f$ b @f$ and @f$ c @f$.
|
---|
| 2534 | */
|
---|
| 2535 | explicit
|
---|
| 2536 | triangular_distribution(result_type __a,
|
---|
| 2537 | result_type __b = result_type(0.5),
|
---|
| 2538 | result_type __c = result_type(1))
|
---|
| 2539 | : _M_param(__a, __b, __c)
|
---|
| 2540 | { }
|
---|
| 2541 |
|
---|
| 2542 | explicit
|
---|
| 2543 | triangular_distribution(const param_type& __p)
|
---|
| 2544 | : _M_param(__p)
|
---|
| 2545 | { }
|
---|
| 2546 |
|
---|
| 2547 | /**
|
---|
| 2548 | * @brief Resets the distribution state.
|
---|
| 2549 | */
|
---|
| 2550 | void
|
---|
| 2551 | reset()
|
---|
| 2552 | { }
|
---|
| 2553 |
|
---|
| 2554 | /**
|
---|
| 2555 | * @brief Returns the @f$ a @f$ of the distribution.
|
---|
| 2556 | */
|
---|
| 2557 | result_type
|
---|
| 2558 | a() const
|
---|
| 2559 | { return _M_param.a(); }
|
---|
| 2560 |
|
---|
| 2561 | /**
|
---|
| 2562 | * @brief Returns the @f$ b @f$ of the distribution.
|
---|
| 2563 | */
|
---|
| 2564 | result_type
|
---|
| 2565 | b() const
|
---|
| 2566 | { return _M_param.b(); }
|
---|
| 2567 |
|
---|
| 2568 | /**
|
---|
| 2569 | * @brief Returns the @f$ c @f$ of the distribution.
|
---|
| 2570 | */
|
---|
| 2571 | result_type
|
---|
| 2572 | c() const
|
---|
| 2573 | { return _M_param.c(); }
|
---|
| 2574 |
|
---|
| 2575 | /**
|
---|
| 2576 | * @brief Returns the parameter set of the distribution.
|
---|
| 2577 | */
|
---|
| 2578 | param_type
|
---|
| 2579 | param() const
|
---|
| 2580 | { return _M_param; }
|
---|
| 2581 |
|
---|
| 2582 | /**
|
---|
| 2583 | * @brief Sets the parameter set of the distribution.
|
---|
| 2584 | * @param __param The new parameter set of the distribution.
|
---|
| 2585 | */
|
---|
| 2586 | void
|
---|
| 2587 | param(const param_type& __param)
|
---|
| 2588 | { _M_param = __param; }
|
---|
| 2589 |
|
---|
| 2590 | /**
|
---|
| 2591 | * @brief Returns the greatest lower bound value of the distribution.
|
---|
| 2592 | */
|
---|
| 2593 | result_type
|
---|
| 2594 | min() const
|
---|
| 2595 | { return _M_param._M_a; }
|
---|
| 2596 |
|
---|
| 2597 | /**
|
---|
| 2598 | * @brief Returns the least upper bound value of the distribution.
|
---|
| 2599 | */
|
---|
| 2600 | result_type
|
---|
| 2601 | max() const
|
---|
| 2602 | { return _M_param._M_c; }
|
---|
| 2603 |
|
---|
| 2604 | /**
|
---|
| 2605 | * @brief Generating functions.
|
---|
| 2606 | */
|
---|
| 2607 | template<typename _UniformRandomNumberGenerator>
|
---|
| 2608 | result_type
|
---|
| 2609 | operator()(_UniformRandomNumberGenerator& __urng)
|
---|
| 2610 | { return this->operator()(__urng, _M_param); }
|
---|
| 2611 |
|
---|
| 2612 | template<typename _UniformRandomNumberGenerator>
|
---|
| 2613 | result_type
|
---|
| 2614 | operator()(_UniformRandomNumberGenerator& __urng,
|
---|
| 2615 | const param_type& __p)
|
---|
| 2616 | {
|
---|
| 2617 | std::__detail::_Adaptor<_UniformRandomNumberGenerator, result_type>
|
---|
| 2618 | __aurng(__urng);
|
---|
| 2619 | result_type __rnd = __aurng();
|
---|
| 2620 | if (__rnd <= __p._M_r_ab)
|
---|
| 2621 | return __p.a() + std::sqrt(__rnd * __p._M_f_ab_ac);
|
---|
| 2622 | else
|
---|
| 2623 | return __p.c() - std::sqrt((result_type(1) - __rnd)
|
---|
| 2624 | * __p._M_f_bc_ac);
|
---|
| 2625 | }
|
---|
| 2626 |
|
---|
| 2627 | template<typename _ForwardIterator,
|
---|
| 2628 | typename _UniformRandomNumberGenerator>
|
---|
| 2629 | void
|
---|
| 2630 | __generate(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 2631 | _UniformRandomNumberGenerator& __urng)
|
---|
| 2632 | { this->__generate(__f, __t, __urng, _M_param); }
|
---|
| 2633 |
|
---|
| 2634 | template<typename _ForwardIterator,
|
---|
| 2635 | typename _UniformRandomNumberGenerator>
|
---|
| 2636 | void
|
---|
| 2637 | __generate(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 2638 | _UniformRandomNumberGenerator& __urng,
|
---|
| 2639 | const param_type& __p)
|
---|
| 2640 | { this->__generate_impl(__f, __t, __urng, __p); }
|
---|
| 2641 |
|
---|
| 2642 | template<typename _UniformRandomNumberGenerator>
|
---|
| 2643 | void
|
---|
| 2644 | __generate(result_type* __f, result_type* __t,
|
---|
| 2645 | _UniformRandomNumberGenerator& __urng,
|
---|
| 2646 | const param_type& __p)
|
---|
| 2647 | { this->__generate_impl(__f, __t, __urng, __p); }
|
---|
| 2648 |
|
---|
| 2649 | /**
|
---|
| 2650 | * @brief Return true if two triangle distributions have the same
|
---|
| 2651 | * parameters and the sequences that would be generated
|
---|
| 2652 | * are equal.
|
---|
| 2653 | */
|
---|
| 2654 | friend bool
|
---|
| 2655 | operator==(const triangular_distribution& __d1,
|
---|
| 2656 | const triangular_distribution& __d2)
|
---|
| 2657 | { return __d1._M_param == __d2._M_param; }
|
---|
| 2658 |
|
---|
| 2659 | /**
|
---|
| 2660 | * @brief Inserts a %triangular_distribution random number distribution
|
---|
| 2661 | * @p __x into the output stream @p __os.
|
---|
| 2662 | *
|
---|
| 2663 | * @param __os An output stream.
|
---|
| 2664 | * @param __x A %triangular_distribution random number distribution.
|
---|
| 2665 | *
|
---|
| 2666 | * @returns The output stream with the state of @p __x inserted or in
|
---|
| 2667 | * an error state.
|
---|
| 2668 | */
|
---|
| 2669 | template<typename _RealType1, typename _CharT, typename _Traits>
|
---|
| 2670 | friend std::basic_ostream<_CharT, _Traits>&
|
---|
| 2671 | operator<<(std::basic_ostream<_CharT, _Traits>& __os,
|
---|
| 2672 | const __gnu_cxx::triangular_distribution<_RealType1>& __x);
|
---|
| 2673 |
|
---|
| 2674 | /**
|
---|
| 2675 | * @brief Extracts a %triangular_distribution random number distribution
|
---|
| 2676 | * @p __x from the input stream @p __is.
|
---|
| 2677 | *
|
---|
| 2678 | * @param __is An input stream.
|
---|
| 2679 | * @param __x A %triangular_distribution random number generator engine.
|
---|
| 2680 | *
|
---|
| 2681 | * @returns The input stream with @p __x extracted or in an error state.
|
---|
| 2682 | */
|
---|
| 2683 | template<typename _RealType1, typename _CharT, typename _Traits>
|
---|
| 2684 | friend std::basic_istream<_CharT, _Traits>&
|
---|
| 2685 | operator>>(std::basic_istream<_CharT, _Traits>& __is,
|
---|
| 2686 | __gnu_cxx::triangular_distribution<_RealType1>& __x);
|
---|
| 2687 |
|
---|
| 2688 | private:
|
---|
| 2689 | template<typename _ForwardIterator,
|
---|
| 2690 | typename _UniformRandomNumberGenerator>
|
---|
| 2691 | void
|
---|
| 2692 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 2693 | _UniformRandomNumberGenerator& __urng,
|
---|
| 2694 | const param_type& __p);
|
---|
| 2695 |
|
---|
| 2696 | param_type _M_param;
|
---|
| 2697 | };
|
---|
| 2698 |
|
---|
| 2699 | /**
|
---|
| 2700 | * @brief Return true if two triangle distributions are different.
|
---|
| 2701 | */
|
---|
| 2702 | template<typename _RealType>
|
---|
| 2703 | inline bool
|
---|
| 2704 | operator!=(const __gnu_cxx::triangular_distribution<_RealType>& __d1,
|
---|
| 2705 | const __gnu_cxx::triangular_distribution<_RealType>& __d2)
|
---|
| 2706 | { return !(__d1 == __d2); }
|
---|
| 2707 |
|
---|
| 2708 |
|
---|
| 2709 | /**
|
---|
| 2710 | * @brief A von Mises distribution for random numbers.
|
---|
| 2711 | *
|
---|
| 2712 | * The formula for the von Mises probability density function is
|
---|
| 2713 | * @f[
|
---|
| 2714 | * p(x|\mu,\kappa) = \frac{e^{\kappa \cos(x-\mu)}}
|
---|
| 2715 | * {2\pi I_0(\kappa)}
|
---|
| 2716 | * @f]
|
---|
| 2717 | *
|
---|
| 2718 | * The generating functions use the method according to:
|
---|
| 2719 | *
|
---|
| 2720 | * D. J. Best and N. I. Fisher, 1979. "Efficient Simulation of the
|
---|
| 2721 | * von Mises Distribution", Journal of the Royal Statistical Society.
|
---|
| 2722 | * Series C (Applied Statistics), Vol. 28, No. 2, pp. 152-157.
|
---|
| 2723 | *
|
---|
| 2724 | * <table border=1 cellpadding=10 cellspacing=0>
|
---|
| 2725 | * <caption align=top>Distribution Statistics</caption>
|
---|
| 2726 | * <tr><td>Mean</td><td>@f$ \mu @f$</td></tr>
|
---|
| 2727 | * <tr><td>Variance</td><td>@f$ 1-I_1(\kappa)/I_0(\kappa) @f$</td></tr>
|
---|
| 2728 | * <tr><td>Range</td><td>@f$[-\pi, \pi]@f$</td></tr>
|
---|
| 2729 | * </table>
|
---|
| 2730 | */
|
---|
| 2731 | template<typename _RealType = double>
|
---|
| 2732 | class von_mises_distribution
|
---|
| 2733 | {
|
---|
| 2734 | static_assert(std::is_floating_point<_RealType>::value,
|
---|
| 2735 | "template argument not a floating point type");
|
---|
| 2736 |
|
---|
| 2737 | public:
|
---|
| 2738 | /** The type of the range of the distribution. */
|
---|
| 2739 | typedef _RealType result_type;
|
---|
| 2740 |
|
---|
| 2741 | /** Parameter type. */
|
---|
| 2742 | struct param_type
|
---|
| 2743 | {
|
---|
| 2744 | friend class von_mises_distribution<_RealType>;
|
---|
| 2745 |
|
---|
| 2746 | param_type() : param_type(0) { }
|
---|
| 2747 |
|
---|
| 2748 | explicit
|
---|
| 2749 | param_type(_RealType __mu, _RealType __kappa = _RealType(1))
|
---|
| 2750 | : _M_mu(__mu), _M_kappa(__kappa)
|
---|
| 2751 | {
|
---|
| 2752 | const _RealType __pi = __gnu_cxx::__math_constants<_RealType>::__pi;
|
---|
| 2753 | __glibcxx_assert(_M_mu >= -__pi && _M_mu <= __pi);
|
---|
| 2754 | __glibcxx_assert(_M_kappa >= _RealType(0));
|
---|
| 2755 |
|
---|
| 2756 | auto __tau = std::sqrt(_RealType(4) * _M_kappa * _M_kappa
|
---|
| 2757 | + _RealType(1)) + _RealType(1);
|
---|
| 2758 | auto __rho = ((__tau - std::sqrt(_RealType(2) * __tau))
|
---|
| 2759 | / (_RealType(2) * _M_kappa));
|
---|
| 2760 | _M_r = (_RealType(1) + __rho * __rho) / (_RealType(2) * __rho);
|
---|
| 2761 | }
|
---|
| 2762 |
|
---|
| 2763 | _RealType
|
---|
| 2764 | mu() const
|
---|
| 2765 | { return _M_mu; }
|
---|
| 2766 |
|
---|
| 2767 | _RealType
|
---|
| 2768 | kappa() const
|
---|
| 2769 | { return _M_kappa; }
|
---|
| 2770 |
|
---|
| 2771 | friend bool
|
---|
| 2772 | operator==(const param_type& __p1, const param_type& __p2)
|
---|
| 2773 | { return __p1._M_mu == __p2._M_mu && __p1._M_kappa == __p2._M_kappa; }
|
---|
| 2774 |
|
---|
| 2775 | friend bool
|
---|
| 2776 | operator!=(const param_type& __p1, const param_type& __p2)
|
---|
| 2777 | { return !(__p1 == __p2); }
|
---|
| 2778 |
|
---|
| 2779 | private:
|
---|
| 2780 | _RealType _M_mu;
|
---|
| 2781 | _RealType _M_kappa;
|
---|
| 2782 | _RealType _M_r;
|
---|
| 2783 | };
|
---|
| 2784 |
|
---|
| 2785 | von_mises_distribution() : von_mises_distribution(0.0) { }
|
---|
| 2786 |
|
---|
| 2787 | /**
|
---|
| 2788 | * @brief Constructs a von Mises distribution with parameters
|
---|
| 2789 | * @f$\mu@f$ and @f$\kappa@f$.
|
---|
| 2790 | */
|
---|
| 2791 | explicit
|
---|
| 2792 | von_mises_distribution(result_type __mu,
|
---|
| 2793 | result_type __kappa = result_type(1))
|
---|
| 2794 | : _M_param(__mu, __kappa)
|
---|
| 2795 | { }
|
---|
| 2796 |
|
---|
| 2797 | explicit
|
---|
| 2798 | von_mises_distribution(const param_type& __p)
|
---|
| 2799 | : _M_param(__p)
|
---|
| 2800 | { }
|
---|
| 2801 |
|
---|
| 2802 | /**
|
---|
| 2803 | * @brief Resets the distribution state.
|
---|
| 2804 | */
|
---|
| 2805 | void
|
---|
| 2806 | reset()
|
---|
| 2807 | { }
|
---|
| 2808 |
|
---|
| 2809 | /**
|
---|
| 2810 | * @brief Returns the @f$ \mu @f$ of the distribution.
|
---|
| 2811 | */
|
---|
| 2812 | result_type
|
---|
| 2813 | mu() const
|
---|
| 2814 | { return _M_param.mu(); }
|
---|
| 2815 |
|
---|
| 2816 | /**
|
---|
| 2817 | * @brief Returns the @f$ \kappa @f$ of the distribution.
|
---|
| 2818 | */
|
---|
| 2819 | result_type
|
---|
| 2820 | kappa() const
|
---|
| 2821 | { return _M_param.kappa(); }
|
---|
| 2822 |
|
---|
| 2823 | /**
|
---|
| 2824 | * @brief Returns the parameter set of the distribution.
|
---|
| 2825 | */
|
---|
| 2826 | param_type
|
---|
| 2827 | param() const
|
---|
| 2828 | { return _M_param; }
|
---|
| 2829 |
|
---|
| 2830 | /**
|
---|
| 2831 | * @brief Sets the parameter set of the distribution.
|
---|
| 2832 | * @param __param The new parameter set of the distribution.
|
---|
| 2833 | */
|
---|
| 2834 | void
|
---|
| 2835 | param(const param_type& __param)
|
---|
| 2836 | { _M_param = __param; }
|
---|
| 2837 |
|
---|
| 2838 | /**
|
---|
| 2839 | * @brief Returns the greatest lower bound value of the distribution.
|
---|
| 2840 | */
|
---|
| 2841 | result_type
|
---|
| 2842 | min() const
|
---|
| 2843 | {
|
---|
| 2844 | return -__gnu_cxx::__math_constants<result_type>::__pi;
|
---|
| 2845 | }
|
---|
| 2846 |
|
---|
| 2847 | /**
|
---|
| 2848 | * @brief Returns the least upper bound value of the distribution.
|
---|
| 2849 | */
|
---|
| 2850 | result_type
|
---|
| 2851 | max() const
|
---|
| 2852 | {
|
---|
| 2853 | return __gnu_cxx::__math_constants<result_type>::__pi;
|
---|
| 2854 | }
|
---|
| 2855 |
|
---|
| 2856 | /**
|
---|
| 2857 | * @brief Generating functions.
|
---|
| 2858 | */
|
---|
| 2859 | template<typename _UniformRandomNumberGenerator>
|
---|
| 2860 | result_type
|
---|
| 2861 | operator()(_UniformRandomNumberGenerator& __urng)
|
---|
| 2862 | { return this->operator()(__urng, _M_param); }
|
---|
| 2863 |
|
---|
| 2864 | template<typename _UniformRandomNumberGenerator>
|
---|
| 2865 | result_type
|
---|
| 2866 | operator()(_UniformRandomNumberGenerator& __urng,
|
---|
| 2867 | const param_type& __p);
|
---|
| 2868 |
|
---|
| 2869 | template<typename _ForwardIterator,
|
---|
| 2870 | typename _UniformRandomNumberGenerator>
|
---|
| 2871 | void
|
---|
| 2872 | __generate(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 2873 | _UniformRandomNumberGenerator& __urng)
|
---|
| 2874 | { this->__generate(__f, __t, __urng, _M_param); }
|
---|
| 2875 |
|
---|
| 2876 | template<typename _ForwardIterator,
|
---|
| 2877 | typename _UniformRandomNumberGenerator>
|
---|
| 2878 | void
|
---|
| 2879 | __generate(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 2880 | _UniformRandomNumberGenerator& __urng,
|
---|
| 2881 | const param_type& __p)
|
---|
| 2882 | { this->__generate_impl(__f, __t, __urng, __p); }
|
---|
| 2883 |
|
---|
| 2884 | template<typename _UniformRandomNumberGenerator>
|
---|
| 2885 | void
|
---|
| 2886 | __generate(result_type* __f, result_type* __t,
|
---|
| 2887 | _UniformRandomNumberGenerator& __urng,
|
---|
| 2888 | const param_type& __p)
|
---|
| 2889 | { this->__generate_impl(__f, __t, __urng, __p); }
|
---|
| 2890 |
|
---|
| 2891 | /**
|
---|
| 2892 | * @brief Return true if two von Mises distributions have the same
|
---|
| 2893 | * parameters and the sequences that would be generated
|
---|
| 2894 | * are equal.
|
---|
| 2895 | */
|
---|
| 2896 | friend bool
|
---|
| 2897 | operator==(const von_mises_distribution& __d1,
|
---|
| 2898 | const von_mises_distribution& __d2)
|
---|
| 2899 | { return __d1._M_param == __d2._M_param; }
|
---|
| 2900 |
|
---|
| 2901 | /**
|
---|
| 2902 | * @brief Inserts a %von_mises_distribution random number distribution
|
---|
| 2903 | * @p __x into the output stream @p __os.
|
---|
| 2904 | *
|
---|
| 2905 | * @param __os An output stream.
|
---|
| 2906 | * @param __x A %von_mises_distribution random number distribution.
|
---|
| 2907 | *
|
---|
| 2908 | * @returns The output stream with the state of @p __x inserted or in
|
---|
| 2909 | * an error state.
|
---|
| 2910 | */
|
---|
| 2911 | template<typename _RealType1, typename _CharT, typename _Traits>
|
---|
| 2912 | friend std::basic_ostream<_CharT, _Traits>&
|
---|
| 2913 | operator<<(std::basic_ostream<_CharT, _Traits>& __os,
|
---|
| 2914 | const __gnu_cxx::von_mises_distribution<_RealType1>& __x);
|
---|
| 2915 |
|
---|
| 2916 | /**
|
---|
| 2917 | * @brief Extracts a %von_mises_distribution random number distribution
|
---|
| 2918 | * @p __x from the input stream @p __is.
|
---|
| 2919 | *
|
---|
| 2920 | * @param __is An input stream.
|
---|
| 2921 | * @param __x A %von_mises_distribution random number generator engine.
|
---|
| 2922 | *
|
---|
| 2923 | * @returns The input stream with @p __x extracted or in an error state.
|
---|
| 2924 | */
|
---|
| 2925 | template<typename _RealType1, typename _CharT, typename _Traits>
|
---|
| 2926 | friend std::basic_istream<_CharT, _Traits>&
|
---|
| 2927 | operator>>(std::basic_istream<_CharT, _Traits>& __is,
|
---|
| 2928 | __gnu_cxx::von_mises_distribution<_RealType1>& __x);
|
---|
| 2929 |
|
---|
| 2930 | private:
|
---|
| 2931 | template<typename _ForwardIterator,
|
---|
| 2932 | typename _UniformRandomNumberGenerator>
|
---|
| 2933 | void
|
---|
| 2934 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 2935 | _UniformRandomNumberGenerator& __urng,
|
---|
| 2936 | const param_type& __p);
|
---|
| 2937 |
|
---|
| 2938 | param_type _M_param;
|
---|
| 2939 | };
|
---|
| 2940 |
|
---|
| 2941 | /**
|
---|
| 2942 | * @brief Return true if two von Mises distributions are different.
|
---|
| 2943 | */
|
---|
| 2944 | template<typename _RealType>
|
---|
| 2945 | inline bool
|
---|
| 2946 | operator!=(const __gnu_cxx::von_mises_distribution<_RealType>& __d1,
|
---|
| 2947 | const __gnu_cxx::von_mises_distribution<_RealType>& __d2)
|
---|
| 2948 | { return !(__d1 == __d2); }
|
---|
| 2949 |
|
---|
| 2950 |
|
---|
| 2951 | /**
|
---|
| 2952 | * @brief A discrete hypergeometric random number distribution.
|
---|
| 2953 | *
|
---|
| 2954 | * The hypergeometric distribution is a discrete probability distribution
|
---|
| 2955 | * that describes the probability of @p k successes in @p n draws @a without
|
---|
| 2956 | * replacement from a finite population of size @p N containing exactly @p K
|
---|
| 2957 | * successes.
|
---|
| 2958 | *
|
---|
| 2959 | * The formula for the hypergeometric probability density function is
|
---|
| 2960 | * @f[
|
---|
| 2961 | * p(k|N,K,n) = \frac{\binom{K}{k} \binom{N-K}{n-k}}{\binom{N}{n}}
|
---|
| 2962 | * @f]
|
---|
| 2963 | * where @f$N@f$ is the total population of the distribution,
|
---|
| 2964 | * @f$K@f$ is the total population of the distribution.
|
---|
| 2965 | *
|
---|
| 2966 | * <table border=1 cellpadding=10 cellspacing=0>
|
---|
| 2967 | * <caption align=top>Distribution Statistics</caption>
|
---|
| 2968 | * <tr><td>Mean</td><td>@f$ n\frac{K}{N} @f$</td></tr>
|
---|
| 2969 | * <tr><td>Variance</td><td>@f$ n\frac{K}{N}\frac{N-K}{N}\frac{N-n}{N-1}
|
---|
| 2970 | * @f$</td></tr>
|
---|
| 2971 | * <tr><td>Range</td><td>@f$[max(0, n+K-N), min(K, n)]@f$</td></tr>
|
---|
| 2972 | * </table>
|
---|
| 2973 | */
|
---|
| 2974 | template<typename _UIntType = unsigned int>
|
---|
| 2975 | class hypergeometric_distribution
|
---|
| 2976 | {
|
---|
| 2977 | static_assert(std::is_unsigned<_UIntType>::value, "template argument "
|
---|
| 2978 | "substituting _UIntType not an unsigned integral type");
|
---|
| 2979 |
|
---|
| 2980 | public:
|
---|
| 2981 | /** The type of the range of the distribution. */
|
---|
| 2982 | typedef _UIntType result_type;
|
---|
| 2983 |
|
---|
| 2984 | /** Parameter type. */
|
---|
| 2985 | struct param_type
|
---|
| 2986 | {
|
---|
| 2987 | typedef hypergeometric_distribution<_UIntType> distribution_type;
|
---|
| 2988 | friend class hypergeometric_distribution<_UIntType>;
|
---|
| 2989 |
|
---|
| 2990 | param_type() : param_type(10) { }
|
---|
| 2991 |
|
---|
| 2992 | explicit
|
---|
| 2993 | param_type(result_type __N, result_type __K = 5,
|
---|
| 2994 | result_type __n = 1)
|
---|
| 2995 | : _M_N{__N}, _M_K{__K}, _M_n{__n}
|
---|
| 2996 | {
|
---|
| 2997 | __glibcxx_assert(_M_N >= _M_K);
|
---|
| 2998 | __glibcxx_assert(_M_N >= _M_n);
|
---|
| 2999 | }
|
---|
| 3000 |
|
---|
| 3001 | result_type
|
---|
| 3002 | total_size() const
|
---|
| 3003 | { return _M_N; }
|
---|
| 3004 |
|
---|
| 3005 | result_type
|
---|
| 3006 | successful_size() const
|
---|
| 3007 | { return _M_K; }
|
---|
| 3008 |
|
---|
| 3009 | result_type
|
---|
| 3010 | unsuccessful_size() const
|
---|
| 3011 | { return _M_N - _M_K; }
|
---|
| 3012 |
|
---|
| 3013 | result_type
|
---|
| 3014 | total_draws() const
|
---|
| 3015 | { return _M_n; }
|
---|
| 3016 |
|
---|
| 3017 | friend bool
|
---|
| 3018 | operator==(const param_type& __p1, const param_type& __p2)
|
---|
| 3019 | { return (__p1._M_N == __p2._M_N)
|
---|
| 3020 | && (__p1._M_K == __p2._M_K)
|
---|
| 3021 | && (__p1._M_n == __p2._M_n); }
|
---|
| 3022 |
|
---|
| 3023 | friend bool
|
---|
| 3024 | operator!=(const param_type& __p1, const param_type& __p2)
|
---|
| 3025 | { return !(__p1 == __p2); }
|
---|
| 3026 |
|
---|
| 3027 | private:
|
---|
| 3028 |
|
---|
| 3029 | result_type _M_N;
|
---|
| 3030 | result_type _M_K;
|
---|
| 3031 | result_type _M_n;
|
---|
| 3032 | };
|
---|
| 3033 |
|
---|
| 3034 | // constructors and member functions
|
---|
| 3035 |
|
---|
| 3036 | hypergeometric_distribution() : hypergeometric_distribution(10) { }
|
---|
| 3037 |
|
---|
| 3038 | explicit
|
---|
| 3039 | hypergeometric_distribution(result_type __N, result_type __K = 5,
|
---|
| 3040 | result_type __n = 1)
|
---|
| 3041 | : _M_param{__N, __K, __n}
|
---|
| 3042 | { }
|
---|
| 3043 |
|
---|
| 3044 | explicit
|
---|
| 3045 | hypergeometric_distribution(const param_type& __p)
|
---|
| 3046 | : _M_param{__p}
|
---|
| 3047 | { }
|
---|
| 3048 |
|
---|
| 3049 | /**
|
---|
| 3050 | * @brief Resets the distribution state.
|
---|
| 3051 | */
|
---|
| 3052 | void
|
---|
| 3053 | reset()
|
---|
| 3054 | { }
|
---|
| 3055 |
|
---|
| 3056 | /**
|
---|
| 3057 | * @brief Returns the distribution parameter @p N,
|
---|
| 3058 | * the total number of items.
|
---|
| 3059 | */
|
---|
| 3060 | result_type
|
---|
| 3061 | total_size() const
|
---|
| 3062 | { return this->_M_param.total_size(); }
|
---|
| 3063 |
|
---|
| 3064 | /**
|
---|
| 3065 | * @brief Returns the distribution parameter @p K,
|
---|
| 3066 | * the total number of successful items.
|
---|
| 3067 | */
|
---|
| 3068 | result_type
|
---|
| 3069 | successful_size() const
|
---|
| 3070 | { return this->_M_param.successful_size(); }
|
---|
| 3071 |
|
---|
| 3072 | /**
|
---|
| 3073 | * @brief Returns the total number of unsuccessful items @f$ N - K @f$.
|
---|
| 3074 | */
|
---|
| 3075 | result_type
|
---|
| 3076 | unsuccessful_size() const
|
---|
| 3077 | { return this->_M_param.unsuccessful_size(); }
|
---|
| 3078 |
|
---|
| 3079 | /**
|
---|
| 3080 | * @brief Returns the distribution parameter @p n,
|
---|
| 3081 | * the total number of draws.
|
---|
| 3082 | */
|
---|
| 3083 | result_type
|
---|
| 3084 | total_draws() const
|
---|
| 3085 | { return this->_M_param.total_draws(); }
|
---|
| 3086 |
|
---|
| 3087 | /**
|
---|
| 3088 | * @brief Returns the parameter set of the distribution.
|
---|
| 3089 | */
|
---|
| 3090 | param_type
|
---|
| 3091 | param() const
|
---|
| 3092 | { return this->_M_param; }
|
---|
| 3093 |
|
---|
| 3094 | /**
|
---|
| 3095 | * @brief Sets the parameter set of the distribution.
|
---|
| 3096 | * @param __param The new parameter set of the distribution.
|
---|
| 3097 | */
|
---|
| 3098 | void
|
---|
| 3099 | param(const param_type& __param)
|
---|
| 3100 | { this->_M_param = __param; }
|
---|
| 3101 |
|
---|
| 3102 | /**
|
---|
| 3103 | * @brief Returns the greatest lower bound value of the distribution.
|
---|
| 3104 | */
|
---|
| 3105 | result_type
|
---|
| 3106 | min() const
|
---|
| 3107 | {
|
---|
| 3108 | using _IntType = typename std::make_signed<result_type>::type;
|
---|
| 3109 | return static_cast<result_type>(std::max(static_cast<_IntType>(0),
|
---|
| 3110 | static_cast<_IntType>(this->total_draws()
|
---|
| 3111 | - this->unsuccessful_size())));
|
---|
| 3112 | }
|
---|
| 3113 |
|
---|
| 3114 | /**
|
---|
| 3115 | * @brief Returns the least upper bound value of the distribution.
|
---|
| 3116 | */
|
---|
| 3117 | result_type
|
---|
| 3118 | max() const
|
---|
| 3119 | { return std::min(this->successful_size(), this->total_draws()); }
|
---|
| 3120 |
|
---|
| 3121 | /**
|
---|
| 3122 | * @brief Generating functions.
|
---|
| 3123 | */
|
---|
| 3124 | template<typename _UniformRandomNumberGenerator>
|
---|
| 3125 | result_type
|
---|
| 3126 | operator()(_UniformRandomNumberGenerator& __urng)
|
---|
| 3127 | { return this->operator()(__urng, this->_M_param); }
|
---|
| 3128 |
|
---|
| 3129 | template<typename _UniformRandomNumberGenerator>
|
---|
| 3130 | result_type
|
---|
| 3131 | operator()(_UniformRandomNumberGenerator& __urng,
|
---|
| 3132 | const param_type& __p);
|
---|
| 3133 |
|
---|
| 3134 | template<typename _ForwardIterator,
|
---|
| 3135 | typename _UniformRandomNumberGenerator>
|
---|
| 3136 | void
|
---|
| 3137 | __generate(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 3138 | _UniformRandomNumberGenerator& __urng)
|
---|
| 3139 | { this->__generate(__f, __t, __urng, this->_M_param); }
|
---|
| 3140 |
|
---|
| 3141 | template<typename _ForwardIterator,
|
---|
| 3142 | typename _UniformRandomNumberGenerator>
|
---|
| 3143 | void
|
---|
| 3144 | __generate(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 3145 | _UniformRandomNumberGenerator& __urng,
|
---|
| 3146 | const param_type& __p)
|
---|
| 3147 | { this->__generate_impl(__f, __t, __urng, __p); }
|
---|
| 3148 |
|
---|
| 3149 | template<typename _UniformRandomNumberGenerator>
|
---|
| 3150 | void
|
---|
| 3151 | __generate(result_type* __f, result_type* __t,
|
---|
| 3152 | _UniformRandomNumberGenerator& __urng,
|
---|
| 3153 | const param_type& __p)
|
---|
| 3154 | { this->__generate_impl(__f, __t, __urng, __p); }
|
---|
| 3155 |
|
---|
| 3156 | /**
|
---|
| 3157 | * @brief Return true if two hypergeometric distributions have the same
|
---|
| 3158 | * parameters and the sequences that would be generated
|
---|
| 3159 | * are equal.
|
---|
| 3160 | */
|
---|
| 3161 | friend bool
|
---|
| 3162 | operator==(const hypergeometric_distribution& __d1,
|
---|
| 3163 | const hypergeometric_distribution& __d2)
|
---|
| 3164 | { return __d1._M_param == __d2._M_param; }
|
---|
| 3165 |
|
---|
| 3166 | /**
|
---|
| 3167 | * @brief Inserts a %hypergeometric_distribution random number
|
---|
| 3168 | * distribution @p __x into the output stream @p __os.
|
---|
| 3169 | *
|
---|
| 3170 | * @param __os An output stream.
|
---|
| 3171 | * @param __x A %hypergeometric_distribution random number
|
---|
| 3172 | * distribution.
|
---|
| 3173 | *
|
---|
| 3174 | * @returns The output stream with the state of @p __x inserted or in
|
---|
| 3175 | * an error state.
|
---|
| 3176 | */
|
---|
| 3177 | template<typename _UIntType1, typename _CharT, typename _Traits>
|
---|
| 3178 | friend std::basic_ostream<_CharT, _Traits>&
|
---|
| 3179 | operator<<(std::basic_ostream<_CharT, _Traits>& __os,
|
---|
| 3180 | const __gnu_cxx::hypergeometric_distribution<_UIntType1>&
|
---|
| 3181 | __x);
|
---|
| 3182 |
|
---|
| 3183 | /**
|
---|
| 3184 | * @brief Extracts a %hypergeometric_distribution random number
|
---|
| 3185 | * distribution @p __x from the input stream @p __is.
|
---|
| 3186 | *
|
---|
| 3187 | * @param __is An input stream.
|
---|
| 3188 | * @param __x A %hypergeometric_distribution random number generator
|
---|
| 3189 | * distribution.
|
---|
| 3190 | *
|
---|
| 3191 | * @returns The input stream with @p __x extracted or in an error
|
---|
| 3192 | * state.
|
---|
| 3193 | */
|
---|
| 3194 | template<typename _UIntType1, typename _CharT, typename _Traits>
|
---|
| 3195 | friend std::basic_istream<_CharT, _Traits>&
|
---|
| 3196 | operator>>(std::basic_istream<_CharT, _Traits>& __is,
|
---|
| 3197 | __gnu_cxx::hypergeometric_distribution<_UIntType1>& __x);
|
---|
| 3198 |
|
---|
| 3199 | private:
|
---|
| 3200 |
|
---|
| 3201 | template<typename _ForwardIterator,
|
---|
| 3202 | typename _UniformRandomNumberGenerator>
|
---|
| 3203 | void
|
---|
| 3204 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 3205 | _UniformRandomNumberGenerator& __urng,
|
---|
| 3206 | const param_type& __p);
|
---|
| 3207 |
|
---|
| 3208 | param_type _M_param;
|
---|
| 3209 | };
|
---|
| 3210 |
|
---|
| 3211 | /**
|
---|
| 3212 | * @brief Return true if two hypergeometric distributions are different.
|
---|
| 3213 | */
|
---|
| 3214 | template<typename _UIntType>
|
---|
| 3215 | inline bool
|
---|
| 3216 | operator!=(const __gnu_cxx::hypergeometric_distribution<_UIntType>& __d1,
|
---|
| 3217 | const __gnu_cxx::hypergeometric_distribution<_UIntType>& __d2)
|
---|
| 3218 | { return !(__d1 == __d2); }
|
---|
| 3219 |
|
---|
| 3220 | /**
|
---|
| 3221 | * @brief A logistic continuous distribution for random numbers.
|
---|
| 3222 | *
|
---|
| 3223 | * The formula for the logistic probability density function is
|
---|
| 3224 | * @f[
|
---|
| 3225 | * p(x|\a,\b) = \frac{e^{(x - a)/b}}{b[1 + e^{(x - a)/b}]^2}
|
---|
| 3226 | * @f]
|
---|
| 3227 | * where @f$b > 0@f$.
|
---|
| 3228 | *
|
---|
| 3229 | * The formula for the logistic probability function is
|
---|
| 3230 | * @f[
|
---|
| 3231 | * cdf(x|\a,\b) = \frac{e^{(x - a)/b}}{1 + e^{(x - a)/b}}
|
---|
| 3232 | * @f]
|
---|
| 3233 | * where @f$b > 0@f$.
|
---|
| 3234 | *
|
---|
| 3235 | * <table border=1 cellpadding=10 cellspacing=0>
|
---|
| 3236 | * <caption align=top>Distribution Statistics</caption>
|
---|
| 3237 | * <tr><td>Mean</td><td>@f$a@f$</td></tr>
|
---|
| 3238 | * <tr><td>Variance</td><td>@f$b^2\pi^2/3@f$</td></tr>
|
---|
| 3239 | * <tr><td>Range</td><td>@f$[0, \infty)@f$</td></tr>
|
---|
| 3240 | * </table>
|
---|
| 3241 | */
|
---|
| 3242 | template<typename _RealType = double>
|
---|
| 3243 | class
|
---|
| 3244 | logistic_distribution
|
---|
| 3245 | {
|
---|
| 3246 | static_assert(std::is_floating_point<_RealType>::value,
|
---|
| 3247 | "template argument not a floating point type");
|
---|
| 3248 |
|
---|
| 3249 | public:
|
---|
| 3250 | /** The type of the range of the distribution. */
|
---|
| 3251 | typedef _RealType result_type;
|
---|
| 3252 |
|
---|
| 3253 | /** Parameter type. */
|
---|
| 3254 | struct param_type
|
---|
| 3255 | {
|
---|
| 3256 | typedef logistic_distribution<result_type> distribution_type;
|
---|
| 3257 |
|
---|
| 3258 | param_type() : param_type(0) { }
|
---|
| 3259 |
|
---|
| 3260 | explicit
|
---|
| 3261 | param_type(result_type __a, result_type __b = result_type(1))
|
---|
| 3262 | : _M_a(__a), _M_b(__b)
|
---|
| 3263 | {
|
---|
| 3264 | __glibcxx_assert(_M_b > result_type(0));
|
---|
| 3265 | }
|
---|
| 3266 |
|
---|
| 3267 | result_type
|
---|
| 3268 | a() const
|
---|
| 3269 | { return _M_a; }
|
---|
| 3270 |
|
---|
| 3271 | result_type
|
---|
| 3272 | b() const
|
---|
| 3273 | { return _M_b; }
|
---|
| 3274 |
|
---|
| 3275 | friend bool
|
---|
| 3276 | operator==(const param_type& __p1, const param_type& __p2)
|
---|
| 3277 | { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; }
|
---|
| 3278 |
|
---|
| 3279 | friend bool
|
---|
| 3280 | operator!=(const param_type& __p1, const param_type& __p2)
|
---|
| 3281 | { return !(__p1 == __p2); }
|
---|
| 3282 |
|
---|
| 3283 | private:
|
---|
| 3284 | void _M_initialize();
|
---|
| 3285 |
|
---|
| 3286 | result_type _M_a;
|
---|
| 3287 | result_type _M_b;
|
---|
| 3288 | };
|
---|
| 3289 |
|
---|
| 3290 | /**
|
---|
| 3291 | * @brief Constructors.
|
---|
| 3292 | * @{
|
---|
| 3293 | */
|
---|
| 3294 | logistic_distribution() : logistic_distribution(0.0) { }
|
---|
| 3295 |
|
---|
| 3296 | explicit
|
---|
| 3297 | logistic_distribution(result_type __a, result_type __b = result_type(1))
|
---|
| 3298 | : _M_param(__a, __b)
|
---|
| 3299 | { }
|
---|
| 3300 |
|
---|
| 3301 | explicit
|
---|
| 3302 | logistic_distribution(const param_type& __p)
|
---|
| 3303 | : _M_param(__p)
|
---|
| 3304 | { }
|
---|
| 3305 |
|
---|
| 3306 | /// @}
|
---|
| 3307 |
|
---|
| 3308 | /**
|
---|
| 3309 | * @brief Resets the distribution state.
|
---|
| 3310 | */
|
---|
| 3311 | void
|
---|
| 3312 | reset()
|
---|
| 3313 | { }
|
---|
| 3314 |
|
---|
| 3315 | /**
|
---|
| 3316 | * @brief Return the parameters of the distribution.
|
---|
| 3317 | */
|
---|
| 3318 | result_type
|
---|
| 3319 | a() const
|
---|
| 3320 | { return _M_param.a(); }
|
---|
| 3321 |
|
---|
| 3322 | result_type
|
---|
| 3323 | b() const
|
---|
| 3324 | { return _M_param.b(); }
|
---|
| 3325 |
|
---|
| 3326 | /**
|
---|
| 3327 | * @brief Returns the parameter set of the distribution.
|
---|
| 3328 | */
|
---|
| 3329 | param_type
|
---|
| 3330 | param() const
|
---|
| 3331 | { return _M_param; }
|
---|
| 3332 |
|
---|
| 3333 | /**
|
---|
| 3334 | * @brief Sets the parameter set of the distribution.
|
---|
| 3335 | * @param __param The new parameter set of the distribution.
|
---|
| 3336 | */
|
---|
| 3337 | void
|
---|
| 3338 | param(const param_type& __param)
|
---|
| 3339 | { _M_param = __param; }
|
---|
| 3340 |
|
---|
| 3341 | /**
|
---|
| 3342 | * @brief Returns the greatest lower bound value of the distribution.
|
---|
| 3343 | */
|
---|
| 3344 | result_type
|
---|
| 3345 | min() const
|
---|
| 3346 | { return -std::numeric_limits<result_type>::max(); }
|
---|
| 3347 |
|
---|
| 3348 | /**
|
---|
| 3349 | * @brief Returns the least upper bound value of the distribution.
|
---|
| 3350 | */
|
---|
| 3351 | result_type
|
---|
| 3352 | max() const
|
---|
| 3353 | { return std::numeric_limits<result_type>::max(); }
|
---|
| 3354 |
|
---|
| 3355 | /**
|
---|
| 3356 | * @brief Generating functions.
|
---|
| 3357 | */
|
---|
| 3358 | template<typename _UniformRandomNumberGenerator>
|
---|
| 3359 | result_type
|
---|
| 3360 | operator()(_UniformRandomNumberGenerator& __urng)
|
---|
| 3361 | { return this->operator()(__urng, this->_M_param); }
|
---|
| 3362 |
|
---|
| 3363 | template<typename _UniformRandomNumberGenerator>
|
---|
| 3364 | result_type
|
---|
| 3365 | operator()(_UniformRandomNumberGenerator&,
|
---|
| 3366 | const param_type&);
|
---|
| 3367 |
|
---|
| 3368 | template<typename _ForwardIterator,
|
---|
| 3369 | typename _UniformRandomNumberGenerator>
|
---|
| 3370 | void
|
---|
| 3371 | __generate(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 3372 | _UniformRandomNumberGenerator& __urng)
|
---|
| 3373 | { this->__generate(__f, __t, __urng, this->param()); }
|
---|
| 3374 |
|
---|
| 3375 | template<typename _ForwardIterator,
|
---|
| 3376 | typename _UniformRandomNumberGenerator>
|
---|
| 3377 | void
|
---|
| 3378 | __generate(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 3379 | _UniformRandomNumberGenerator& __urng,
|
---|
| 3380 | const param_type& __p)
|
---|
| 3381 | { this->__generate_impl(__f, __t, __urng, __p); }
|
---|
| 3382 |
|
---|
| 3383 | template<typename _UniformRandomNumberGenerator>
|
---|
| 3384 | void
|
---|
| 3385 | __generate(result_type* __f, result_type* __t,
|
---|
| 3386 | _UniformRandomNumberGenerator& __urng,
|
---|
| 3387 | const param_type& __p)
|
---|
| 3388 | { this->__generate_impl(__f, __t, __urng, __p); }
|
---|
| 3389 |
|
---|
| 3390 | /**
|
---|
| 3391 | * @brief Return true if two logistic distributions have
|
---|
| 3392 | * the same parameters and the sequences that would
|
---|
| 3393 | * be generated are equal.
|
---|
| 3394 | */
|
---|
| 3395 | template<typename _RealType1>
|
---|
| 3396 | friend bool
|
---|
| 3397 | operator==(const logistic_distribution<_RealType1>& __d1,
|
---|
| 3398 | const logistic_distribution<_RealType1>& __d2)
|
---|
| 3399 | { return __d1.param() == __d2.param(); }
|
---|
| 3400 |
|
---|
| 3401 | /**
|
---|
| 3402 | * @brief Inserts a %logistic_distribution random number distribution
|
---|
| 3403 | * @p __x into the output stream @p __os.
|
---|
| 3404 | *
|
---|
| 3405 | * @param __os An output stream.
|
---|
| 3406 | * @param __x A %logistic_distribution random number distribution.
|
---|
| 3407 | *
|
---|
| 3408 | * @returns The output stream with the state of @p __x inserted or in
|
---|
| 3409 | * an error state.
|
---|
| 3410 | */
|
---|
| 3411 | template<typename _RealType1, typename _CharT, typename _Traits>
|
---|
| 3412 | friend std::basic_ostream<_CharT, _Traits>&
|
---|
| 3413 | operator<<(std::basic_ostream<_CharT, _Traits>&,
|
---|
| 3414 | const logistic_distribution<_RealType1>&);
|
---|
| 3415 |
|
---|
| 3416 | /**
|
---|
| 3417 | * @brief Extracts a %logistic_distribution random number distribution
|
---|
| 3418 | * @p __x from the input stream @p __is.
|
---|
| 3419 | *
|
---|
| 3420 | * @param __is An input stream.
|
---|
| 3421 | * @param __x A %logistic_distribution random number
|
---|
| 3422 | * generator engine.
|
---|
| 3423 | *
|
---|
| 3424 | * @returns The input stream with @p __x extracted or in an error state.
|
---|
| 3425 | */
|
---|
| 3426 | template<typename _RealType1, typename _CharT, typename _Traits>
|
---|
| 3427 | friend std::basic_istream<_CharT, _Traits>&
|
---|
| 3428 | operator>>(std::basic_istream<_CharT, _Traits>&,
|
---|
| 3429 | logistic_distribution<_RealType1>&);
|
---|
| 3430 |
|
---|
| 3431 | private:
|
---|
| 3432 | template<typename _ForwardIterator,
|
---|
| 3433 | typename _UniformRandomNumberGenerator>
|
---|
| 3434 | void
|
---|
| 3435 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 3436 | _UniformRandomNumberGenerator& __urng,
|
---|
| 3437 | const param_type& __p);
|
---|
| 3438 |
|
---|
| 3439 | param_type _M_param;
|
---|
| 3440 | };
|
---|
| 3441 |
|
---|
| 3442 | /**
|
---|
| 3443 | * @brief Return true if two logistic distributions are not equal.
|
---|
| 3444 | */
|
---|
| 3445 | template<typename _RealType1>
|
---|
| 3446 | inline bool
|
---|
| 3447 | operator!=(const logistic_distribution<_RealType1>& __d1,
|
---|
| 3448 | const logistic_distribution<_RealType1>& __d2)
|
---|
| 3449 | { return !(__d1 == __d2); }
|
---|
| 3450 |
|
---|
| 3451 |
|
---|
| 3452 | /**
|
---|
| 3453 | * @brief A distribution for random coordinates on a unit sphere.
|
---|
| 3454 | *
|
---|
| 3455 | * The method used in the generation function is attributed by Donald Knuth
|
---|
| 3456 | * to G. W. Brown, Modern Mathematics for the Engineer (1956).
|
---|
| 3457 | */
|
---|
| 3458 | template<std::size_t _Dimen, typename _RealType = double>
|
---|
| 3459 | class uniform_on_sphere_distribution
|
---|
| 3460 | {
|
---|
| 3461 | static_assert(std::is_floating_point<_RealType>::value,
|
---|
| 3462 | "template argument not a floating point type");
|
---|
| 3463 | static_assert(_Dimen != 0, "dimension is zero");
|
---|
| 3464 |
|
---|
| 3465 | public:
|
---|
| 3466 | /** The type of the range of the distribution. */
|
---|
| 3467 | typedef std::array<_RealType, _Dimen> result_type;
|
---|
| 3468 |
|
---|
| 3469 | /** Parameter type. */
|
---|
| 3470 | struct param_type
|
---|
| 3471 | {
|
---|
| 3472 | param_type() { }
|
---|
| 3473 |
|
---|
| 3474 | friend bool
|
---|
| 3475 | operator==(const param_type&, const param_type&)
|
---|
| 3476 | { return true; }
|
---|
| 3477 |
|
---|
| 3478 | friend bool
|
---|
| 3479 | operator!=(const param_type&, const param_type&)
|
---|
| 3480 | { return false; }
|
---|
| 3481 | };
|
---|
| 3482 |
|
---|
| 3483 | /**
|
---|
| 3484 | * @brief Constructs a uniform on sphere distribution.
|
---|
| 3485 | */
|
---|
| 3486 | uniform_on_sphere_distribution()
|
---|
| 3487 | : _M_param(), _M_nd()
|
---|
| 3488 | { }
|
---|
| 3489 |
|
---|
| 3490 | explicit
|
---|
| 3491 | uniform_on_sphere_distribution(const param_type& __p)
|
---|
| 3492 | : _M_param(__p), _M_nd()
|
---|
| 3493 | { }
|
---|
| 3494 |
|
---|
| 3495 | /**
|
---|
| 3496 | * @brief Resets the distribution state.
|
---|
| 3497 | */
|
---|
| 3498 | void
|
---|
| 3499 | reset()
|
---|
| 3500 | { _M_nd.reset(); }
|
---|
| 3501 |
|
---|
| 3502 | /**
|
---|
| 3503 | * @brief Returns the parameter set of the distribution.
|
---|
| 3504 | */
|
---|
| 3505 | param_type
|
---|
| 3506 | param() const
|
---|
| 3507 | { return _M_param; }
|
---|
| 3508 |
|
---|
| 3509 | /**
|
---|
| 3510 | * @brief Sets the parameter set of the distribution.
|
---|
| 3511 | * @param __param The new parameter set of the distribution.
|
---|
| 3512 | */
|
---|
| 3513 | void
|
---|
| 3514 | param(const param_type& __param)
|
---|
| 3515 | { _M_param = __param; }
|
---|
| 3516 |
|
---|
| 3517 | /**
|
---|
| 3518 | * @brief Returns the greatest lower bound value of the distribution.
|
---|
| 3519 | * This function makes no sense for this distribution.
|
---|
| 3520 | */
|
---|
| 3521 | result_type
|
---|
| 3522 | min() const
|
---|
| 3523 | {
|
---|
| 3524 | result_type __res;
|
---|
| 3525 | __res.fill(0);
|
---|
| 3526 | return __res;
|
---|
| 3527 | }
|
---|
| 3528 |
|
---|
| 3529 | /**
|
---|
| 3530 | * @brief Returns the least upper bound value of the distribution.
|
---|
| 3531 | * This function makes no sense for this distribution.
|
---|
| 3532 | */
|
---|
| 3533 | result_type
|
---|
| 3534 | max() const
|
---|
| 3535 | {
|
---|
| 3536 | result_type __res;
|
---|
| 3537 | __res.fill(0);
|
---|
| 3538 | return __res;
|
---|
| 3539 | }
|
---|
| 3540 |
|
---|
| 3541 | /**
|
---|
| 3542 | * @brief Generating functions.
|
---|
| 3543 | */
|
---|
| 3544 | template<typename _UniformRandomNumberGenerator>
|
---|
| 3545 | result_type
|
---|
| 3546 | operator()(_UniformRandomNumberGenerator& __urng)
|
---|
| 3547 | { return this->operator()(__urng, _M_param); }
|
---|
| 3548 |
|
---|
| 3549 | template<typename _UniformRandomNumberGenerator>
|
---|
| 3550 | result_type
|
---|
| 3551 | operator()(_UniformRandomNumberGenerator& __urng,
|
---|
| 3552 | const param_type& __p);
|
---|
| 3553 |
|
---|
| 3554 | template<typename _ForwardIterator,
|
---|
| 3555 | typename _UniformRandomNumberGenerator>
|
---|
| 3556 | void
|
---|
| 3557 | __generate(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 3558 | _UniformRandomNumberGenerator& __urng)
|
---|
| 3559 | { this->__generate(__f, __t, __urng, this->param()); }
|
---|
| 3560 |
|
---|
| 3561 | template<typename _ForwardIterator,
|
---|
| 3562 | typename _UniformRandomNumberGenerator>
|
---|
| 3563 | void
|
---|
| 3564 | __generate(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 3565 | _UniformRandomNumberGenerator& __urng,
|
---|
| 3566 | const param_type& __p)
|
---|
| 3567 | { this->__generate_impl(__f, __t, __urng, __p); }
|
---|
| 3568 |
|
---|
| 3569 | template<typename _UniformRandomNumberGenerator>
|
---|
| 3570 | void
|
---|
| 3571 | __generate(result_type* __f, result_type* __t,
|
---|
| 3572 | _UniformRandomNumberGenerator& __urng,
|
---|
| 3573 | const param_type& __p)
|
---|
| 3574 | { this->__generate_impl(__f, __t, __urng, __p); }
|
---|
| 3575 |
|
---|
| 3576 | /**
|
---|
| 3577 | * @brief Return true if two uniform on sphere distributions have
|
---|
| 3578 | * the same parameters and the sequences that would be
|
---|
| 3579 | * generated are equal.
|
---|
| 3580 | */
|
---|
| 3581 | friend bool
|
---|
| 3582 | operator==(const uniform_on_sphere_distribution& __d1,
|
---|
| 3583 | const uniform_on_sphere_distribution& __d2)
|
---|
| 3584 | { return __d1._M_nd == __d2._M_nd; }
|
---|
| 3585 |
|
---|
| 3586 | /**
|
---|
| 3587 | * @brief Inserts a %uniform_on_sphere_distribution random number
|
---|
| 3588 | * distribution @p __x into the output stream @p __os.
|
---|
| 3589 | *
|
---|
| 3590 | * @param __os An output stream.
|
---|
| 3591 | * @param __x A %uniform_on_sphere_distribution random number
|
---|
| 3592 | * distribution.
|
---|
| 3593 | *
|
---|
| 3594 | * @returns The output stream with the state of @p __x inserted or in
|
---|
| 3595 | * an error state.
|
---|
| 3596 | */
|
---|
| 3597 | template<size_t _Dimen1, typename _RealType1, typename _CharT,
|
---|
| 3598 | typename _Traits>
|
---|
| 3599 | friend std::basic_ostream<_CharT, _Traits>&
|
---|
| 3600 | operator<<(std::basic_ostream<_CharT, _Traits>& __os,
|
---|
| 3601 | const __gnu_cxx::uniform_on_sphere_distribution<_Dimen1,
|
---|
| 3602 | _RealType1>&
|
---|
| 3603 | __x);
|
---|
| 3604 |
|
---|
| 3605 | /**
|
---|
| 3606 | * @brief Extracts a %uniform_on_sphere_distribution random number
|
---|
| 3607 | * distribution
|
---|
| 3608 | * @p __x from the input stream @p __is.
|
---|
| 3609 | *
|
---|
| 3610 | * @param __is An input stream.
|
---|
| 3611 | * @param __x A %uniform_on_sphere_distribution random number
|
---|
| 3612 | * generator engine.
|
---|
| 3613 | *
|
---|
| 3614 | * @returns The input stream with @p __x extracted or in an error state.
|
---|
| 3615 | */
|
---|
| 3616 | template<std::size_t _Dimen1, typename _RealType1, typename _CharT,
|
---|
| 3617 | typename _Traits>
|
---|
| 3618 | friend std::basic_istream<_CharT, _Traits>&
|
---|
| 3619 | operator>>(std::basic_istream<_CharT, _Traits>& __is,
|
---|
| 3620 | __gnu_cxx::uniform_on_sphere_distribution<_Dimen1,
|
---|
| 3621 | _RealType1>& __x);
|
---|
| 3622 |
|
---|
| 3623 | private:
|
---|
| 3624 | template<typename _ForwardIterator,
|
---|
| 3625 | typename _UniformRandomNumberGenerator>
|
---|
| 3626 | void
|
---|
| 3627 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 3628 | _UniformRandomNumberGenerator& __urng,
|
---|
| 3629 | const param_type& __p);
|
---|
| 3630 |
|
---|
| 3631 | param_type _M_param;
|
---|
| 3632 | std::normal_distribution<_RealType> _M_nd;
|
---|
| 3633 | };
|
---|
| 3634 |
|
---|
| 3635 | /**
|
---|
| 3636 | * @brief Return true if two uniform on sphere distributions are different.
|
---|
| 3637 | */
|
---|
| 3638 | template<std::size_t _Dimen, typename _RealType>
|
---|
| 3639 | inline bool
|
---|
| 3640 | operator!=(const __gnu_cxx::uniform_on_sphere_distribution<_Dimen,
|
---|
| 3641 | _RealType>& __d1,
|
---|
| 3642 | const __gnu_cxx::uniform_on_sphere_distribution<_Dimen,
|
---|
| 3643 | _RealType>& __d2)
|
---|
| 3644 | { return !(__d1 == __d2); }
|
---|
| 3645 |
|
---|
| 3646 |
|
---|
| 3647 | /**
|
---|
| 3648 | * @brief A distribution for random coordinates inside a unit sphere.
|
---|
| 3649 | */
|
---|
| 3650 | template<std::size_t _Dimen, typename _RealType = double>
|
---|
| 3651 | class uniform_inside_sphere_distribution
|
---|
| 3652 | {
|
---|
| 3653 | static_assert(std::is_floating_point<_RealType>::value,
|
---|
| 3654 | "template argument not a floating point type");
|
---|
| 3655 | static_assert(_Dimen != 0, "dimension is zero");
|
---|
| 3656 |
|
---|
| 3657 | public:
|
---|
| 3658 | /** The type of the range of the distribution. */
|
---|
| 3659 | using result_type = std::array<_RealType, _Dimen>;
|
---|
| 3660 |
|
---|
| 3661 | /** Parameter type. */
|
---|
| 3662 | struct param_type
|
---|
| 3663 | {
|
---|
| 3664 | using distribution_type
|
---|
| 3665 | = uniform_inside_sphere_distribution<_Dimen, _RealType>;
|
---|
| 3666 | friend class uniform_inside_sphere_distribution<_Dimen, _RealType>;
|
---|
| 3667 |
|
---|
| 3668 | param_type() : param_type(1.0) { }
|
---|
| 3669 |
|
---|
| 3670 | explicit
|
---|
| 3671 | param_type(_RealType __radius)
|
---|
| 3672 | : _M_radius(__radius)
|
---|
| 3673 | {
|
---|
| 3674 | __glibcxx_assert(_M_radius > _RealType(0));
|
---|
| 3675 | }
|
---|
| 3676 |
|
---|
| 3677 | _RealType
|
---|
| 3678 | radius() const
|
---|
| 3679 | { return _M_radius; }
|
---|
| 3680 |
|
---|
| 3681 | friend bool
|
---|
| 3682 | operator==(const param_type& __p1, const param_type& __p2)
|
---|
| 3683 | { return __p1._M_radius == __p2._M_radius; }
|
---|
| 3684 |
|
---|
| 3685 | friend bool
|
---|
| 3686 | operator!=(const param_type& __p1, const param_type& __p2)
|
---|
| 3687 | { return !(__p1 == __p2); }
|
---|
| 3688 |
|
---|
| 3689 | private:
|
---|
| 3690 | _RealType _M_radius;
|
---|
| 3691 | };
|
---|
| 3692 |
|
---|
| 3693 | /**
|
---|
| 3694 | * @brief Constructors.
|
---|
| 3695 | * @{
|
---|
| 3696 | */
|
---|
| 3697 |
|
---|
| 3698 | uniform_inside_sphere_distribution()
|
---|
| 3699 | : uniform_inside_sphere_distribution(1.0)
|
---|
| 3700 | { }
|
---|
| 3701 |
|
---|
| 3702 | explicit
|
---|
| 3703 | uniform_inside_sphere_distribution(_RealType __radius)
|
---|
| 3704 | : _M_param(__radius), _M_uosd()
|
---|
| 3705 | { }
|
---|
| 3706 |
|
---|
| 3707 | explicit
|
---|
| 3708 | uniform_inside_sphere_distribution(const param_type& __p)
|
---|
| 3709 | : _M_param(__p), _M_uosd()
|
---|
| 3710 | { }
|
---|
| 3711 |
|
---|
| 3712 | /// @}
|
---|
| 3713 |
|
---|
| 3714 | /**
|
---|
| 3715 | * @brief Resets the distribution state.
|
---|
| 3716 | */
|
---|
| 3717 | void
|
---|
| 3718 | reset()
|
---|
| 3719 | { _M_uosd.reset(); }
|
---|
| 3720 |
|
---|
| 3721 | /**
|
---|
| 3722 | * @brief Returns the @f$radius@f$ of the distribution.
|
---|
| 3723 | */
|
---|
| 3724 | _RealType
|
---|
| 3725 | radius() const
|
---|
| 3726 | { return _M_param.radius(); }
|
---|
| 3727 |
|
---|
| 3728 | /**
|
---|
| 3729 | * @brief Returns the parameter set of the distribution.
|
---|
| 3730 | */
|
---|
| 3731 | param_type
|
---|
| 3732 | param() const
|
---|
| 3733 | { return _M_param; }
|
---|
| 3734 |
|
---|
| 3735 | /**
|
---|
| 3736 | * @brief Sets the parameter set of the distribution.
|
---|
| 3737 | * @param __param The new parameter set of the distribution.
|
---|
| 3738 | */
|
---|
| 3739 | void
|
---|
| 3740 | param(const param_type& __param)
|
---|
| 3741 | { _M_param = __param; }
|
---|
| 3742 |
|
---|
| 3743 | /**
|
---|
| 3744 | * @brief Returns the greatest lower bound value of the distribution.
|
---|
| 3745 | * This function makes no sense for this distribution.
|
---|
| 3746 | */
|
---|
| 3747 | result_type
|
---|
| 3748 | min() const
|
---|
| 3749 | {
|
---|
| 3750 | result_type __res;
|
---|
| 3751 | __res.fill(0);
|
---|
| 3752 | return __res;
|
---|
| 3753 | }
|
---|
| 3754 |
|
---|
| 3755 | /**
|
---|
| 3756 | * @brief Returns the least upper bound value of the distribution.
|
---|
| 3757 | * This function makes no sense for this distribution.
|
---|
| 3758 | */
|
---|
| 3759 | result_type
|
---|
| 3760 | max() const
|
---|
| 3761 | {
|
---|
| 3762 | result_type __res;
|
---|
| 3763 | __res.fill(0);
|
---|
| 3764 | return __res;
|
---|
| 3765 | }
|
---|
| 3766 |
|
---|
| 3767 | /**
|
---|
| 3768 | * @brief Generating functions.
|
---|
| 3769 | */
|
---|
| 3770 | template<typename _UniformRandomNumberGenerator>
|
---|
| 3771 | result_type
|
---|
| 3772 | operator()(_UniformRandomNumberGenerator& __urng)
|
---|
| 3773 | { return this->operator()(__urng, _M_param); }
|
---|
| 3774 |
|
---|
| 3775 | template<typename _UniformRandomNumberGenerator>
|
---|
| 3776 | result_type
|
---|
| 3777 | operator()(_UniformRandomNumberGenerator& __urng,
|
---|
| 3778 | const param_type& __p);
|
---|
| 3779 |
|
---|
| 3780 | template<typename _ForwardIterator,
|
---|
| 3781 | typename _UniformRandomNumberGenerator>
|
---|
| 3782 | void
|
---|
| 3783 | __generate(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 3784 | _UniformRandomNumberGenerator& __urng)
|
---|
| 3785 | { this->__generate(__f, __t, __urng, this->param()); }
|
---|
| 3786 |
|
---|
| 3787 | template<typename _ForwardIterator,
|
---|
| 3788 | typename _UniformRandomNumberGenerator>
|
---|
| 3789 | void
|
---|
| 3790 | __generate(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 3791 | _UniformRandomNumberGenerator& __urng,
|
---|
| 3792 | const param_type& __p)
|
---|
| 3793 | { this->__generate_impl(__f, __t, __urng, __p); }
|
---|
| 3794 |
|
---|
| 3795 | template<typename _UniformRandomNumberGenerator>
|
---|
| 3796 | void
|
---|
| 3797 | __generate(result_type* __f, result_type* __t,
|
---|
| 3798 | _UniformRandomNumberGenerator& __urng,
|
---|
| 3799 | const param_type& __p)
|
---|
| 3800 | { this->__generate_impl(__f, __t, __urng, __p); }
|
---|
| 3801 |
|
---|
| 3802 | /**
|
---|
| 3803 | * @brief Return true if two uniform on sphere distributions have
|
---|
| 3804 | * the same parameters and the sequences that would be
|
---|
| 3805 | * generated are equal.
|
---|
| 3806 | */
|
---|
| 3807 | friend bool
|
---|
| 3808 | operator==(const uniform_inside_sphere_distribution& __d1,
|
---|
| 3809 | const uniform_inside_sphere_distribution& __d2)
|
---|
| 3810 | { return __d1._M_param == __d2._M_param && __d1._M_uosd == __d2._M_uosd; }
|
---|
| 3811 |
|
---|
| 3812 | /**
|
---|
| 3813 | * @brief Inserts a %uniform_inside_sphere_distribution random number
|
---|
| 3814 | * distribution @p __x into the output stream @p __os.
|
---|
| 3815 | *
|
---|
| 3816 | * @param __os An output stream.
|
---|
| 3817 | * @param __x A %uniform_inside_sphere_distribution random number
|
---|
| 3818 | * distribution.
|
---|
| 3819 | *
|
---|
| 3820 | * @returns The output stream with the state of @p __x inserted or in
|
---|
| 3821 | * an error state.
|
---|
| 3822 | */
|
---|
| 3823 | template<size_t _Dimen1, typename _RealType1, typename _CharT,
|
---|
| 3824 | typename _Traits>
|
---|
| 3825 | friend std::basic_ostream<_CharT, _Traits>&
|
---|
| 3826 | operator<<(std::basic_ostream<_CharT, _Traits>& __os,
|
---|
| 3827 | const __gnu_cxx::uniform_inside_sphere_distribution<_Dimen1,
|
---|
| 3828 | _RealType1>&
|
---|
| 3829 | );
|
---|
| 3830 |
|
---|
| 3831 | /**
|
---|
| 3832 | * @brief Extracts a %uniform_inside_sphere_distribution random number
|
---|
| 3833 | * distribution
|
---|
| 3834 | * @p __x from the input stream @p __is.
|
---|
| 3835 | *
|
---|
| 3836 | * @param __is An input stream.
|
---|
| 3837 | * @param __x A %uniform_inside_sphere_distribution random number
|
---|
| 3838 | * generator engine.
|
---|
| 3839 | *
|
---|
| 3840 | * @returns The input stream with @p __x extracted or in an error state.
|
---|
| 3841 | */
|
---|
| 3842 | template<std::size_t _Dimen1, typename _RealType1, typename _CharT,
|
---|
| 3843 | typename _Traits>
|
---|
| 3844 | friend std::basic_istream<_CharT, _Traits>&
|
---|
| 3845 | operator>>(std::basic_istream<_CharT, _Traits>& __is,
|
---|
| 3846 | __gnu_cxx::uniform_inside_sphere_distribution<_Dimen1,
|
---|
| 3847 | _RealType1>&);
|
---|
| 3848 |
|
---|
| 3849 | private:
|
---|
| 3850 | template<typename _ForwardIterator,
|
---|
| 3851 | typename _UniformRandomNumberGenerator>
|
---|
| 3852 | void
|
---|
| 3853 | __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
|
---|
| 3854 | _UniformRandomNumberGenerator& __urng,
|
---|
| 3855 | const param_type& __p);
|
---|
| 3856 |
|
---|
| 3857 | param_type _M_param;
|
---|
| 3858 | uniform_on_sphere_distribution<_Dimen, _RealType> _M_uosd;
|
---|
| 3859 | };
|
---|
| 3860 |
|
---|
| 3861 | /**
|
---|
| 3862 | * @brief Return true if two uniform on sphere distributions are different.
|
---|
| 3863 | */
|
---|
| 3864 | template<std::size_t _Dimen, typename _RealType>
|
---|
| 3865 | inline bool
|
---|
| 3866 | operator!=(const __gnu_cxx::uniform_inside_sphere_distribution<_Dimen,
|
---|
| 3867 | _RealType>& __d1,
|
---|
| 3868 | const __gnu_cxx::uniform_inside_sphere_distribution<_Dimen,
|
---|
| 3869 | _RealType>& __d2)
|
---|
| 3870 | { return !(__d1 == __d2); }
|
---|
| 3871 |
|
---|
| 3872 | _GLIBCXX_END_NAMESPACE_VERSION
|
---|
| 3873 | } // namespace __gnu_cxx
|
---|
| 3874 |
|
---|
| 3875 | #include <ext/opt_random.h>
|
---|
| 3876 | #include <ext/random.tcc>
|
---|
| 3877 |
|
---|
| 3878 | #endif // _GLIBCXX_USE_C99_STDINT_TR1 && UINT32_C
|
---|
| 3879 |
|
---|
| 3880 | #endif // C++11
|
---|
| 3881 |
|
---|
| 3882 | #endif // _EXT_RANDOM
|
---|