1 | #ifndef _theplu_yat_random_ |
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2 | #define _theplu_yat_random_ |
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3 | |
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4 | // $Id: random.h 3591 2017-01-20 02:19:49Z peter $ |
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5 | |
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6 | /* |
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7 | Copyright (C) 2005, 2006, 2007, 2008 Jari Häkkinen, Peter Johansson |
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8 | Copyright (C) 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017 Peter Johansson |
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9 | |
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10 | This file is part of the yat library, http://dev.thep.lu.se/yat |
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11 | |
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12 | The yat library is free software; you can redistribute it and/or |
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13 | modify it under the terms of the GNU General Public License as |
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14 | published by the Free Software Foundation; either version 3 of the |
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15 | License, or (at your option) any later version. |
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16 | |
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17 | The yat library is distributed in the hope that it will be useful, |
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18 | but WITHOUT ANY WARRANTY; without even the implied warranty of |
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19 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU |
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20 | General Public License for more details. |
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21 | |
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22 | You should have received a copy of the GNU General Public License |
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23 | along with yat. If not, see <http://www.gnu.org/licenses/>. |
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24 | */ |
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25 | |
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26 | #include "yat/utility/config_public.h" |
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27 | |
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28 | #include "yat/statistics/Histogram.h" |
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29 | #include "yat/utility/deprecate.h" |
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30 | |
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31 | // always include this before <boost/excpetion_ptr.hpp> indirectly below |
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32 | #include "yat/utility/boost_exception_ptr.h" |
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33 | |
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34 | #include <boost/concept_check.hpp> |
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35 | #include <boost/iterator/iterator_concepts.hpp> |
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36 | #include <boost/thread.hpp> |
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37 | #include <boost/thread/tss.hpp> |
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38 | |
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39 | #include <gsl/gsl_rng.h> |
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40 | #include <gsl/gsl_randist.h> |
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41 | |
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42 | #include <algorithm> |
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43 | #ifdef YAT_HAVE_ATOMIC |
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44 | #include <atomic> |
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45 | #endif |
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46 | #include <string> |
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47 | #include <vector> |
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48 | |
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49 | namespace theplu { |
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50 | namespace yat { |
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51 | namespace random { |
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52 | |
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53 | //forward declaration |
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54 | class RNG_state; |
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55 | |
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56 | /// |
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57 | /// @brief Random Number Generator |
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58 | /// |
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59 | /// The RNG class is wrapper to the GSL random number generator |
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60 | /// (rng). In yat 0.8 (or older) this class provided a single global |
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61 | /// instance of the rng, and made sure there was only one point of |
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62 | /// access to the generator. Since version 0.9 this class provides |
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63 | /// one rng per thread in order to avoid collisions in multi-thread |
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64 | /// applications. |
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65 | /// |
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66 | /// There are many different rng's available in GSL. RNG uses the |
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67 | /// default generator, unless the global variable \c gsl_rng_default |
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68 | /// has been modified (see <a |
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69 | /// href=\gsl_url/Random-number-environment-variables.html>GSL |
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70 | /// Manual</a>). Note, \c gsl_rng_default should be changed before |
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71 | /// RNG creates its generator and safest way to achieve this is to |
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72 | /// modify \c gsl_rng_default prior calling instance() the first |
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73 | /// time. |
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74 | /// |
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75 | /// There is information about how to change seeding and generators |
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76 | /// at run time without recompilation using environment variables in |
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77 | /// the <a |
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78 | /// href=\gsl_url/Random-number-environment-variables.html>GSL |
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79 | /// Manual</a>. RNG supports seeding at compile time if you don't |
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80 | /// want to bother about environment variables and GSL. |
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81 | /// |
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82 | /// The class provides one generator per thread. The first generator |
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83 | /// created is seeded with \c gsl_rng_default_seed and subsequent |
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84 | /// generators are seeded with \c gsl_rng_default_seed + 1, \c |
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85 | /// gsl_rng_default_seed + 2 etc, unless the seed has been modified |
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86 | /// with seed() or seed_from_devurandom(). |
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87 | /// |
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88 | /// @see Design Patterns (the singleton and adapter pattern). <a |
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89 | /// href=\gsl_url/Random-Number-Generation.html>GSL documentation</a>. |
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90 | /// |
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91 | class RNG |
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92 | { |
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93 | public: |
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94 | |
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95 | /// |
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96 | /// @brief Get an instance of the Random Number Generator. |
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97 | /// |
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98 | /// Get an instance of RNG. If a random number generator is not |
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99 | /// already created for current thread, the call will create a new |
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100 | /// generator of type \c gsl_rng_default. If it is the first |
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101 | /// generator created it will be seeded with \c |
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102 | /// gsl_rng_default_seed; otherwise created generator will be |
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103 | /// seeded with \c seed + \c n, where \c seed is the latest seed |
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104 | /// set (with seed() or seed_from_devurandom()) The seed may be |
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105 | /// changed with the seed or seed_from_devurandom member |
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106 | /// functions. |
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107 | /// |
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108 | /// @return A pointer to the random number generator. |
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109 | /// |
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110 | /// @see seed and seed_from_devurandom |
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111 | /// |
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112 | static RNG* instance(void); |
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113 | |
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114 | /// |
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115 | /// @brief Returns the largest number that the random number |
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116 | /// generator can return. |
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117 | /// |
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118 | unsigned long max(void) const; |
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119 | |
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120 | /// |
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121 | /// @brief Returns the smallest number that the random number |
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122 | /// generator can return. |
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123 | /// |
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124 | unsigned long min(void) const; |
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125 | |
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126 | /// |
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127 | /// @brief Returns the name of the random number generator |
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128 | /// |
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129 | std::string name(void) const; |
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130 | |
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131 | /// |
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132 | /// Access underlying GSL random number generator speicific to |
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133 | /// current thread. Behaviour of returned generator is undefined |
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134 | /// outside current thread. |
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135 | /// |
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136 | /// @return const pointer to underlying GSL random generator. |
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137 | /// |
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138 | const gsl_rng* rng(void) const; |
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139 | |
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140 | /// |
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141 | /// @brief Set the seed \a s for the rng. |
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142 | /// |
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143 | /// Set the seed \a s for the rng. If \a s is zero, a default |
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144 | /// value from the rng's original implementation is used (cf. GSL |
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145 | /// documentation). |
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146 | /// |
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147 | /// This function will also effect generators created subsequently |
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148 | /// in other threads. The seed \a s is saved and subsequent |
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149 | /// generators will be created with seed \c s + 1, \c s + 2, etc. |
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150 | /// |
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151 | /// @see seed_from_devurandom |
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152 | /// |
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153 | void seed(unsigned long s) const; |
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154 | |
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155 | /// |
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156 | /// @brief Seed the rng using the /dev/urandom device. |
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157 | /// |
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158 | /// This function will also effect generators in other threads |
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159 | /// created subsequntly (see seed()). |
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160 | /// |
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161 | /// @return The seed acquired from /dev/urandom. |
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162 | /// |
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163 | unsigned long seed_from_devurandom(void); |
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164 | |
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165 | /** |
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166 | \brief Set the state to \a state. |
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167 | |
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168 | \return 0 always. |
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169 | |
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170 | \note this function only effects the RNG in current thread |
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171 | |
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172 | \throw utility::GSL_error on error |
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173 | |
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174 | \see gsl_rng_memcpy |
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175 | */ |
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176 | // return int for backward compatibility with yat 0.8 |
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177 | int set_state(const RNG_state&); |
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178 | |
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179 | private: |
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180 | RNG(void); |
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181 | |
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182 | /** |
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183 | \brief Not implemented. |
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184 | |
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185 | This copy contructor is not implemented. The constructor is |
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186 | declared in order to avoid compiler generated default copy |
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187 | constructor. |
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188 | */ |
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189 | RNG(const RNG&); |
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190 | |
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191 | /** |
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192 | There can be only one RNG so assignment is always |
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193 | self-assignment and we do not allow it |
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194 | */ |
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195 | RNG& operator=(const RNG&); |
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196 | |
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197 | virtual ~RNG(void); |
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198 | void rng_alloc(void) const; |
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199 | |
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200 | #ifdef YAT_HAVE_ATOMIC |
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201 | static std::atomic<RNG*> instance_; |
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202 | #else |
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203 | static RNG* instance_; |
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204 | #endif |
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205 | // holds one gsl_rng per thread. Access through rng(void) so a |
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206 | // gsl_rng is allocated if necessary. |
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207 | mutable boost::thread_specific_ptr<gsl_rng> rng_; |
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208 | mutable unsigned long seed_; |
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209 | // guard needs to be mutable because major mission for it is to protect seed_ against multi-access, and seed_ is mutable... |
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210 | mutable boost::mutex mutex_; |
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211 | static boost::mutex init_mutex_; |
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212 | }; |
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213 | |
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214 | |
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215 | /// |
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216 | /// @brief Class holding state of a random generator |
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217 | /// |
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218 | class RNG_state |
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219 | { |
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220 | public: |
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221 | /// |
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222 | /// @brief Constructor |
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223 | /// |
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224 | explicit RNG_state(const RNG*); |
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225 | |
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226 | /** |
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227 | Copy Constructor |
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228 | |
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229 | \since Explicitely declared since yat 0.5 |
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230 | */ |
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231 | RNG_state(const RNG_state&); |
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232 | |
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233 | /// |
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234 | /// @brief Destructor |
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235 | /// |
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236 | ~RNG_state(void); |
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237 | |
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238 | /// |
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239 | /// @return const pointer to underlying GSL random generator. |
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240 | /// |
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241 | const gsl_rng* rng(void) const; |
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242 | |
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243 | /** |
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244 | Assignment operator |
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245 | |
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246 | \since Explicitely declared since yat 0.5 |
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247 | */ |
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248 | RNG_state& operator=(const RNG_state&); |
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249 | |
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250 | private: |
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251 | gsl_rng* rng_; |
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252 | |
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253 | void clone(const gsl_rng&); |
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254 | }; |
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255 | |
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256 | |
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257 | // --------------------- Discrete distribtuions --------------------- |
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258 | |
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259 | /// |
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260 | /// @brief Discrete random number distributions. |
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261 | /// |
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262 | /// Abstract base class for discrete random number |
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263 | /// distributions. Given K discrete events with different |
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264 | /// probabilities \f$ P[k] \f$, produce a random value k consistent |
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265 | /// with its probability. |
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266 | /// |
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267 | class Discrete |
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268 | { |
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269 | public: |
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270 | /** |
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271 | type returned by operator() |
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272 | |
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273 | \since New in yat 0.10 |
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274 | */ |
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275 | typedef unsigned long int result_type; |
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276 | |
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277 | /// |
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278 | /// @brief Constructor |
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279 | /// |
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280 | Discrete(void); |
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281 | |
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282 | /// |
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283 | /// @brief The destructor |
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284 | /// |
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285 | virtual ~Discrete(void); |
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286 | |
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287 | /// |
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288 | /// @brief Set the seed to \a s. |
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289 | /// |
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290 | /// Set the seed to \a s in the underlying rng. If \a s is zero, a |
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291 | /// default value from the rng's original implementation is used |
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292 | /// (cf. GSL documentation). |
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293 | /// |
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294 | /// \deprecated Provided for backward compatibility with the 0.7 |
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295 | /// API. Use RNG::instance()->seed(s) instead. |
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296 | /// |
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297 | void seed(unsigned long s) const YAT_DEPRECATE; |
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298 | |
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299 | /// |
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300 | /// @brief Set the seed using the /dev/urandom device. |
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301 | /// |
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302 | /// @return The seed acquired from /dev/urandom. |
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303 | /// |
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304 | /// \deprecated Provided for backward compatibility with the 0.7 |
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305 | /// API. Use RNG::instance()->seed_from_devurandom() instead. |
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306 | /// |
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307 | unsigned long seed_from_devurandom(void) YAT_DEPRECATE; |
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308 | |
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309 | /// |
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310 | /// @return A random number. |
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311 | /// |
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312 | virtual result_type operator()(void) const = 0; |
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313 | |
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314 | protected: |
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315 | /// GSL random gererator |
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316 | RNG* rng_; |
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317 | }; |
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318 | |
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319 | /** |
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320 | \brief Binomial distribution |
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321 | |
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322 | \see gsl_ran_binomial |
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323 | |
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324 | \since New in yat 0.10 |
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325 | */ |
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326 | class Binomial : public Discrete |
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327 | { |
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328 | public: |
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329 | /** |
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330 | \brief Constructor |
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331 | |
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332 | Create an object that generates random numbers from binomial |
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333 | distribution, the number of successes in \n trials each with |
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334 | success probability \a p. |
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335 | */ |
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336 | Binomial(double p, unsigned int n); |
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337 | |
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338 | /** |
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339 | \return number from binomial distrubtion as parametrized in constructor. |
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340 | */ |
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341 | unsigned long operator()(void) const; |
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342 | private: |
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343 | double p_; |
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344 | unsigned int n_; |
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345 | }; |
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346 | |
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347 | /// |
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348 | /// @brief General |
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349 | /// |
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350 | class DiscreteGeneral : public Discrete |
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351 | { |
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352 | public: |
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353 | /// |
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354 | /// @brief Constructor |
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355 | /// |
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356 | /// @param hist is a Histogram defining the probability distribution |
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357 | /// |
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358 | explicit DiscreteGeneral(const statistics::Histogram& hist); |
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359 | |
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360 | /** |
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361 | \brief Copy constructor |
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362 | |
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363 | \since Explicitely implemented in yat 0.5 |
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364 | */ |
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365 | DiscreteGeneral(const DiscreteGeneral&); |
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366 | |
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367 | /// |
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368 | /// @brief Destructor |
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369 | /// |
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370 | ~DiscreteGeneral(void); |
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371 | |
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372 | /// |
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373 | /// The generated number is an integer and proportional to the |
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374 | /// frequency in the corresponding histogram bin. In other words, |
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375 | /// the probability that 0 is returned is proportinal to the size |
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376 | /// of the first bin. |
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377 | /// |
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378 | /// @return A random number. |
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379 | /// |
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380 | unsigned long operator()(void) const; |
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381 | |
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382 | /** |
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383 | \brief Assignment operator |
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384 | |
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385 | \since Explicitely implemented in yat 0.5 |
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386 | */ |
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387 | DiscreteGeneral& operator=(const DiscreteGeneral&); |
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388 | |
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389 | private: |
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390 | void free(void); |
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391 | void preproc(void); |
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392 | |
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393 | gsl_ran_discrete_t* gen_; |
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394 | std::vector<double> p_; |
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395 | }; |
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396 | |
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397 | /** |
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398 | @brief Discrete uniform distribution |
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399 | |
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400 | Discrete uniform distribution also known as the "equally likely |
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401 | outcomes" distribution. Each outcome, in this case an integer |
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402 | from [0,n-1] , have equal probability to occur. |
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403 | |
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404 | Distribution function \f$ p(k) = \frac{1}{n+1} \f$ for \f$ 0 \le |
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405 | k < n \f$ \n |
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406 | Expectation value: \f$ \frac{n-1}{2} \f$ \n |
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407 | Variance: \f$ \frac{1}{12}(n-1)(n+1) \f$ |
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408 | */ |
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409 | class DiscreteUniform |
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410 | : public Discrete, |
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411 | public std::unary_function<unsigned long, unsigned long> |
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412 | { |
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413 | public: |
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414 | /** |
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415 | \brief Constructor. |
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416 | |
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417 | The generator will generate integers within the range \f$ |
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418 | [0,n-1] \f$. If \a n is zero, then the whole range of the |
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419 | underlying RNG will be used \f$ [min,max] \f$. Setting \a n to |
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420 | zero is the preferred way to sample the whole range of the |
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421 | underlying RNG, i.e. not setting \n to RNG.max. |
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422 | |
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423 | \throw If \a n is larger than the maximum number the underlying |
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424 | random number generator can return, then a GSL_error exception |
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425 | is thrown. |
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426 | */ |
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427 | explicit DiscreteUniform(unsigned long n=0); |
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428 | |
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429 | /** |
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430 | \brief Get a random number |
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431 | |
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432 | The returned integer is either in the range [RNG.min,RNG.max] |
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433 | or [0,n-1] depending on how the random number generator was |
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434 | created. |
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435 | |
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436 | \see DiscreteUniform(const unsigned long n=0) |
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437 | */ |
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438 | unsigned long operator()(void) const; |
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439 | |
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440 | /** |
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441 | \brief Get a random integer in the range \f$ [0,n-1] \f$. |
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442 | |
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443 | All integers in the range [0,n-1] are equally likely. This |
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444 | function should be avoided for sampling the whole range of the |
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445 | underlying RNG. |
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446 | |
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447 | \throw GSL_error if \a n is larger than the range of the |
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448 | underlying generator. |
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449 | */ |
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450 | unsigned long operator()(unsigned long n) const; |
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451 | |
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452 | private: |
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453 | unsigned long range_; |
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454 | }; |
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455 | |
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456 | |
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457 | /** |
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458 | @brief Geomtric Distribution |
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459 | |
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460 | The number of independent trials with probability \em p until the |
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461 | first success. |
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462 | |
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463 | Probability function \f$ p(k) = p (1-p)^(k-1) \f$ |
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464 | |
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465 | \since New in yat 0.14 |
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466 | */ |
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467 | class Geometric : public Discrete |
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468 | { |
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469 | public: |
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470 | /** |
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471 | \brief Constructor |
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472 | |
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473 | \param p is probability for success in one trial |
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474 | */ |
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475 | Geometric(double p); |
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476 | |
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477 | /* |
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478 | \return a number from Geomtric distribution |
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479 | */ |
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480 | unsigned long operator()(void) const; |
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481 | |
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482 | /** |
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483 | \return a number from Geomtric distribution with success rate \a p |
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484 | |
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485 | \note this operator ignores parameters set in Constructor |
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486 | */ |
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487 | unsigned long operator()(double p) const; |
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488 | |
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489 | private: |
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490 | double p_; |
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491 | }; |
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492 | |
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493 | |
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494 | /** |
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495 | If we have \a n1 samples of type 1 and \a n2 samples of type 2 |
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496 | and draw \a t samples with replacement, number of drawn samples |
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497 | of type 1 will follow the hyper geometric distribution. |
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498 | |
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499 | \since New in yat 0.14 |
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500 | */ |
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501 | class HyperGeometric : public Discrete |
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502 | { |
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503 | public: |
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504 | /** |
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505 | \brief Defaul constructor |
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506 | */ |
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507 | HyperGeometric(void); |
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508 | |
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509 | /** |
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510 | \brief Constructor |
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511 | \param n1 number of samples of type 1 |
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512 | \param n2 number of samples of type 2 |
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513 | \param t number of samples to draw |
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514 | */ |
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515 | HyperGeometric(unsigned int n1, unsigned int n2, unsigned int t); |
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516 | |
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517 | /** |
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518 | \return random number from hypergeometric distribution using |
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519 | parameters set in constructor. |
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520 | */ |
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521 | unsigned long int operator()(void) const; |
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522 | |
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523 | /** |
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524 | \return random number from hypergeometric distribution using |
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525 | parameters passed. |
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526 | */ |
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527 | unsigned long int operator()(unsigned int n1, unsigned int n2, |
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528 | unsigned int t) const; |
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529 | private: |
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530 | unsigned int n1_; |
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531 | unsigned int n2_; |
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532 | unsigned int t_; |
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533 | }; |
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534 | |
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535 | /** |
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536 | We have \a n1 samples of type 1 and \a n2 samples of type 2. |
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537 | Samples are drawn with replacement until \a t samles of type 2 |
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538 | are drawn. Then \a k, number of drawn samples of type 1, follows |
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539 | negative hypergeometric distribution. |
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540 | |
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541 | \since New in yat 0.14 |
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542 | |
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543 | \see HyperGeometric |
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544 | */ |
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545 | class NegativeHyperGeometric : public Discrete |
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546 | { |
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547 | public: |
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548 | /** |
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549 | \brief Default constructor |
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550 | */ |
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551 | NegativeHyperGeometric(void); |
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552 | |
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553 | /** |
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554 | \brief Constructor |
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555 | \param n1 number of samples of type 1 |
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556 | \param n2 number of samples of type 2 |
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557 | \param t number of samples of type 2 to draw |
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558 | */ |
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559 | NegativeHyperGeometric(unsigned int n1, unsigned int n2, unsigned int t); |
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560 | |
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561 | /** |
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562 | \return random number from negative hypergeometric distribution |
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563 | using parameters set in constructor. |
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564 | */ |
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565 | unsigned long int operator()(void) const; |
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566 | |
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567 | /** |
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568 | \return random number from negative hypergeometric distribution |
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569 | using parameters passed. |
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570 | */ |
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571 | unsigned long int operator()(unsigned int n1, unsigned int n2, |
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572 | unsigned int t) const; |
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573 | private: |
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574 | unsigned int n1_; |
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575 | unsigned int n2_; |
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576 | unsigned int t_; |
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577 | }; |
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578 | |
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579 | |
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580 | /** |
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581 | @brief Poisson Distribution |
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582 | |
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583 | Having a Poisson process (i.e. no memory), number of occurences |
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584 | within a given time window is Poisson distributed. This |
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585 | distribution is the limit of a Binomial distribution when number |
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586 | of attempts is large, and the probability for one attempt to be |
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587 | succesful is small (in such a way that the expected number of |
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588 | succesful attempts is \f$ m \f$. |
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589 | |
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590 | Probability function \f$ p(k) = e^{-m}\frac{m^k}{k!} \f$ for \f$ 0 \le |
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591 | k \f$ \n |
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592 | Expectation value: \f$ m \f$ \n |
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593 | Variance: \f$ m \f$ |
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594 | */ |
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595 | class Poisson : public Discrete |
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596 | { |
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597 | public: |
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598 | /// |
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599 | /// @brief Constructor |
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600 | /// |
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601 | /// @param m is expectation value |
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602 | /// |
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603 | explicit Poisson(const double m=1); |
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604 | |
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605 | /// |
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606 | /// @return A Poisson distributed number. |
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607 | /// |
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608 | unsigned long operator()(void) const; |
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609 | |
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610 | /// |
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611 | /// @return A Poisson distributed number with expectation value |
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612 | /// \a m |
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613 | /// |
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614 | /// @note this operator ignores parameters set in Constructor |
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615 | /// |
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616 | unsigned long operator()(const double m) const; |
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617 | |
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618 | private: |
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619 | double m_; |
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620 | }; |
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621 | |
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622 | // --------------------- Continuous distribtuions --------------------- |
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623 | |
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624 | /// |
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625 | /// @brief Continuous random number distributions. |
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626 | /// |
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627 | /// Abstract base class for continuous random number distributions. |
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628 | /// |
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629 | class Continuous |
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630 | { |
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631 | public: |
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632 | /** |
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633 | type returned by operator() |
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634 | |
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635 | \since New in yat 0.10 |
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636 | */ |
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637 | typedef double result_type; |
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638 | |
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639 | /// |
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640 | /// @brief Constructor |
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641 | /// |
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642 | Continuous(void); |
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643 | |
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644 | /// |
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645 | /// @brief The destructor |
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646 | /// |
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647 | virtual ~Continuous(void); |
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648 | |
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649 | /// |
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650 | /// @brief Set the seed to \a s. |
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651 | /// |
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652 | /// Set the seed to \a s in the underlying rng. If \a s is zero, a |
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653 | /// default value from the rng's original implementation is used |
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654 | /// (cf. GSL documentation). |
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655 | /// |
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656 | /// \deprecated Provided for backward compatibility with the 0.7 |
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657 | /// API. Use RNG::instance()->seed(s) instead. |
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658 | /// |
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659 | void seed(unsigned long s) const YAT_DEPRECATE; |
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660 | |
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661 | /// |
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662 | /// @brief Set the seed using the /dev/urandom device. |
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663 | /// |
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664 | /// @return The seed acquired from /dev/urandom. |
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665 | /// |
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666 | /// \deprecated Provided for backward compatibility with the 0.7 |
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667 | /// API. Use RNG::instance()->seed_from_devurandom() instead. |
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668 | /// |
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669 | unsigned long seed_from_devurandom(void) YAT_DEPRECATE; |
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670 | |
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671 | /// |
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672 | /// @return A random number |
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673 | /// |
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674 | virtual result_type operator()(void) const = 0; |
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675 | |
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676 | protected: |
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677 | /// pointer to GSL random generator |
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678 | RNG* rng_; |
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679 | }; |
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680 | |
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681 | // ContinuousUniform is declared before ContinuousGeneral to avoid |
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682 | // forward declaration |
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683 | /// |
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684 | /// @brief Uniform distribution |
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685 | /// |
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686 | /// Class for generating a random number from a uniform distribution |
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687 | /// in the range [0,1), i.e. zero is included but not 1. |
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688 | /// |
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689 | /// Distribution function \f$ f(x) = 1 \f$ for \f$ 0 \le x < 1 \f$ \n |
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690 | /// Expectation value: 0.5 \n |
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691 | /// Variance: \f$ \frac{1}{12} \f$ |
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692 | /// |
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693 | class ContinuousUniform : public Continuous |
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694 | { |
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695 | public: |
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696 | double operator()(void) const; |
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697 | }; |
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698 | |
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699 | /// |
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700 | /// @brief Generates numbers from a histogram in a continuous manner. |
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701 | /// |
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702 | class ContinuousGeneral : public Continuous |
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703 | { |
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704 | public: |
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705 | /// |
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706 | /// @brief Constructor |
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707 | /// |
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708 | /// @param hist is a Histogram defining the probability distribution |
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709 | /// |
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710 | explicit ContinuousGeneral(const statistics::Histogram& hist); |
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711 | |
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712 | /// |
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713 | /// The number is generated in a two step process. First the bin |
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714 | /// in the histogram is randomly selected (see |
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715 | /// DiscreteGeneral). Then a number is generated uniformly from |
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716 | /// the interval defined by the bin. |
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717 | /// |
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718 | /// @return A random number. |
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719 | /// |
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720 | double operator()(void) const; |
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721 | |
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722 | private: |
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723 | const DiscreteGeneral discrete_; |
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724 | const statistics::Histogram hist_; |
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725 | ContinuousUniform u_; |
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726 | }; |
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727 | |
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728 | /** |
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729 | \brief Generator of random numbers from an exponential |
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730 | distribution. |
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731 | |
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732 | The distribution function is \f$ f(x) = \frac{1}{m}\exp(-x/a) |
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733 | \f$ for \f$ x \f$ with the expectation value \f$ m \f$ and |
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734 | variance \f$ m^2 \f$ |
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735 | */ |
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736 | class Exponential : public Continuous |
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737 | { |
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738 | public: |
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739 | /// |
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740 | /// @brief Constructor |
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741 | /// |
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742 | /// @param m is the expectation value of the distribution. |
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743 | /// |
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744 | explicit Exponential(const double m=1); |
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745 | |
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746 | /// |
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747 | /// @return A random number from exponential distribution. |
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748 | /// |
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749 | double operator()(void) const; |
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750 | |
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751 | /// |
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752 | /// @return A random number from exponential distribution, with |
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753 | /// expectation value \a m |
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754 | /// |
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755 | /// @note This operator ignores parameters given in constructor. |
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756 | /// |
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757 | double operator()(const double m) const; |
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758 | |
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759 | private: |
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760 | double m_; |
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761 | }; |
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762 | |
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763 | /** |
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764 | @brief Gaussian distribution |
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765 | |
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766 | Class for generating a random number from a Gaussian distribution |
---|
767 | between zero and unity. Utilizes the Box-Muller algorithm, which |
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768 | needs two calls to random generator. |
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769 | |
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770 | Distribution function \f$ f(x) = |
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771 | \frac{1}{\sqrt{2\pi\sigma^2}}\exp(-\frac{(x-\mu)^2}{2\sigma^2}) |
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772 | \f$ \n |
---|
773 | Expectation value: \f$ \mu \f$ \n |
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774 | Variance: \f$ \sigma^2 \f$ |
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775 | */ |
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776 | class Gaussian : public Continuous |
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777 | { |
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778 | public: |
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779 | /// |
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780 | /// @brief Constructor |
---|
781 | /// |
---|
782 | /// @param s is the standard deviation \f$ \sigma \f$ of distribution |
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783 | /// @param m is the expectation value \f$ \mu \f$ of the distribution |
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784 | /// |
---|
785 | explicit Gaussian(const double s=1, const double m=0); |
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786 | |
---|
787 | /// |
---|
788 | /// @return A random Gaussian number |
---|
789 | /// |
---|
790 | double operator()(void) const; |
---|
791 | |
---|
792 | /// |
---|
793 | /// @return A random Gaussian number with standard deviation \a s |
---|
794 | /// and expectation value 0. |
---|
795 | /// |
---|
796 | /// @note this operator ignores parameters given in Constructor |
---|
797 | /// |
---|
798 | double operator()(const double s) const; |
---|
799 | |
---|
800 | /// |
---|
801 | /// @return A random Gaussian number with standard deviation \a s |
---|
802 | /// and expectation value \a m. |
---|
803 | /// |
---|
804 | /// @note this operator ignores parameters given in Constructor |
---|
805 | /// |
---|
806 | double operator()(const double s, const double m) const; |
---|
807 | |
---|
808 | private: |
---|
809 | double m_; |
---|
810 | double s_; |
---|
811 | }; |
---|
812 | |
---|
813 | /** |
---|
814 | \brief Convenience function to shuffle a range with singleton RNG. |
---|
815 | |
---|
816 | Wrapper around std::random_shuffle using DiscreteUniform as |
---|
817 | random generator and thereby using the underlying RNG class, |
---|
818 | which is singleton. |
---|
819 | |
---|
820 | Type Requirements: |
---|
821 | - RandomAccessIterator is \random_access_iterator |
---|
822 | */ |
---|
823 | template<typename RandomAccessIterator> |
---|
824 | void random_shuffle(RandomAccessIterator first, RandomAccessIterator last) |
---|
825 | { |
---|
826 | DiscreteUniform rnd; |
---|
827 | std::random_shuffle(first, last, rnd); |
---|
828 | } |
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829 | |
---|
830 | }}} // of namespace random, yat, and theplu |
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831 | |
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832 | #endif |
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