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,
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372 | 0xcb520000U, 0xc7e91c7dU>
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373 | sfmt132049;
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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,
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377 | 0xffffbb5fU, 0xfb6ebf95U,
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378 | 0xfffefffaU, 0xcff77fffU,
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379 | 0x00000001U, 0x00000000U,
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380 | 0xcb520000U, 0xc7e91c7dU>
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381 | sfmt132049_64;
|
---|
382 |
|
---|
383 |
|
---|
384 | typedef simd_fast_mersenne_twister_engine<uint32_t, 216091, 627,
|
---|
385 | 11, 3, 10, 1,
|
---|
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,
|
---|
393 | 11, 3, 10, 1,
|
---|
394 | 0xbff7bff7U, 0xbfffffffU,
|
---|
395 | 0xbffffa7fU, 0xffddfbfbU,
|
---|
396 | 0xf8000001U, 0x89e80709U,
|
---|
397 | 0x3bd2b64bU, 0x0c64b1e4U>
|
---|
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
|
---|
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
|
---|