]>
Commit | Line | Data |
---|---|---|
7c673cae FG |
1 | /* boost random/lognormal_distribution.hpp header file |
2 | * | |
3 | * Copyright Jens Maurer 2000-2001 | |
4 | * Copyright Steven Watanabe 2011 | |
5 | * Distributed under the Boost Software License, Version 1.0. (See | |
6 | * accompanying file LICENSE_1_0.txt or copy at | |
7 | * http://www.boost.org/LICENSE_1_0.txt) | |
8 | * | |
9 | * See http://www.boost.org for most recent version including documentation. | |
10 | * | |
11 | * $Id$ | |
12 | * | |
13 | * Revision history | |
14 | * 2001-02-18 moved to individual header files | |
15 | */ | |
16 | ||
17 | #ifndef BOOST_RANDOM_LOGNORMAL_DISTRIBUTION_HPP | |
18 | #define BOOST_RANDOM_LOGNORMAL_DISTRIBUTION_HPP | |
19 | ||
20 | #include <boost/config/no_tr1/cmath.hpp> // std::exp, std::sqrt | |
21 | #include <cassert> | |
22 | #include <iosfwd> | |
23 | #include <istream> | |
24 | #include <boost/limits.hpp> | |
25 | #include <boost/random/detail/config.hpp> | |
26 | #include <boost/random/detail/operators.hpp> | |
27 | #include <boost/random/normal_distribution.hpp> | |
28 | ||
29 | namespace boost { | |
30 | namespace random { | |
31 | ||
32 | /** | |
33 | * Instantiations of class template lognormal_distribution model a | |
34 | * \random_distribution. Such a distribution produces random numbers | |
35 | * with \f$\displaystyle p(x) = \frac{1}{x s \sqrt{2\pi}} e^{\frac{-\left(\log(x)-m\right)^2}{2s^2}}\f$ | |
36 | * for x > 0. | |
37 | * | |
38 | * @xmlwarning | |
39 | * This distribution has been updated to match the C++ standard. | |
40 | * Its behavior has changed from the original | |
41 | * boost::lognormal_distribution. A backwards compatible | |
42 | * version is provided in namespace boost. | |
43 | * @endxmlwarning | |
44 | */ | |
45 | template<class RealType = double> | |
46 | class lognormal_distribution | |
47 | { | |
48 | public: | |
49 | typedef typename normal_distribution<RealType>::input_type input_type; | |
50 | typedef RealType result_type; | |
51 | ||
52 | class param_type | |
53 | { | |
54 | public: | |
55 | ||
56 | typedef lognormal_distribution distribution_type; | |
57 | ||
58 | /** Constructs the parameters of a lognormal_distribution. */ | |
59 | explicit param_type(RealType m_arg = RealType(0.0), | |
60 | RealType s_arg = RealType(1.0)) | |
61 | : _m(m_arg), _s(s_arg) {} | |
62 | ||
63 | /** Returns the "m" parameter of the distribution. */ | |
64 | RealType m() const { return _m; } | |
65 | ||
66 | /** Returns the "s" parameter of the distribution. */ | |
67 | RealType s() const { return _s; } | |
68 | ||
69 | /** Writes the parameters to a std::ostream. */ | |
70 | BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, param_type, parm) | |
71 | { | |
72 | os << parm._m << " " << parm._s; | |
73 | return os; | |
74 | } | |
75 | ||
76 | /** Reads the parameters from a std::istream. */ | |
77 | BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, param_type, parm) | |
78 | { | |
79 | is >> parm._m >> std::ws >> parm._s; | |
80 | return is; | |
81 | } | |
82 | ||
83 | /** Returns true if the two sets of parameters are equal. */ | |
84 | BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(param_type, lhs, rhs) | |
85 | { return lhs._m == rhs._m && lhs._s == rhs._s; } | |
86 | ||
87 | /** Returns true if the two sets of parameters are different. */ | |
88 | BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(param_type) | |
89 | ||
90 | private: | |
91 | RealType _m; | |
92 | RealType _s; | |
93 | }; | |
94 | ||
95 | /** | |
96 | * Constructs a lognormal_distribution. @c m and @c s are the | |
97 | * parameters of the distribution. | |
98 | */ | |
99 | explicit lognormal_distribution(RealType m_arg = RealType(0.0), | |
100 | RealType s_arg = RealType(1.0)) | |
101 | : _normal(m_arg, s_arg) {} | |
102 | ||
103 | /** | |
104 | * Constructs a lognormal_distribution from its parameters. | |
105 | */ | |
106 | explicit lognormal_distribution(const param_type& parm) | |
107 | : _normal(parm.m(), parm.s()) {} | |
108 | ||
109 | // compiler-generated copy ctor and assignment operator are fine | |
110 | ||
111 | /** Returns the m parameter of the distribution. */ | |
112 | RealType m() const { return _normal.mean(); } | |
113 | /** Returns the s parameter of the distribution. */ | |
114 | RealType s() const { return _normal.sigma(); } | |
115 | ||
116 | /** Returns the smallest value that the distribution can produce. */ | |
117 | RealType min BOOST_PREVENT_MACRO_SUBSTITUTION () const | |
118 | { return RealType(0); } | |
119 | /** Returns the largest value that the distribution can produce. */ | |
120 | RealType max BOOST_PREVENT_MACRO_SUBSTITUTION () const | |
121 | { return (std::numeric_limits<RealType>::infinity)(); } | |
122 | ||
123 | /** Returns the parameters of the distribution. */ | |
124 | param_type param() const { return param_type(m(), s()); } | |
125 | /** Sets the parameters of the distribution. */ | |
126 | void param(const param_type& parm) | |
127 | { | |
128 | typedef normal_distribution<RealType> normal_type; | |
129 | typename normal_type::param_type normal_param(parm.m(), parm.s()); | |
130 | _normal.param(normal_param); | |
131 | } | |
132 | ||
133 | /** | |
134 | * Effects: Subsequent uses of the distribution do not depend | |
135 | * on values produced by any engine prior to invoking reset. | |
136 | */ | |
137 | void reset() { _normal.reset(); } | |
138 | ||
139 | /** | |
140 | * Returns a random variate distributed according to the | |
141 | * lognormal distribution. | |
142 | */ | |
143 | template<class Engine> | |
144 | result_type operator()(Engine& eng) | |
145 | { | |
146 | using std::exp; | |
147 | return exp(_normal(eng)); | |
148 | } | |
149 | ||
150 | /** | |
151 | * Returns a random variate distributed according to the | |
152 | * lognormal distribution with parameters specified by param. | |
153 | */ | |
154 | template<class Engine> | |
155 | result_type operator()(Engine& eng, const param_type& parm) | |
156 | { return lognormal_distribution(parm)(eng); } | |
157 | ||
158 | /** Writes the distribution to a @c std::ostream. */ | |
159 | BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, lognormal_distribution, ld) | |
160 | { | |
161 | os << ld._normal; | |
162 | return os; | |
163 | } | |
164 | ||
165 | /** Reads the distribution from a @c std::istream. */ | |
166 | BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, lognormal_distribution, ld) | |
167 | { | |
168 | is >> ld._normal; | |
169 | return is; | |
170 | } | |
171 | ||
172 | /** | |
173 | * Returns true if the two distributions will produce identical | |
174 | * sequences of values given equal generators. | |
175 | */ | |
176 | BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(lognormal_distribution, lhs, rhs) | |
177 | { return lhs._normal == rhs._normal; } | |
178 | ||
179 | /** | |
180 | * Returns true if the two distributions may produce different | |
181 | * sequences of values given equal generators. | |
182 | */ | |
183 | BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(lognormal_distribution) | |
184 | ||
185 | private: | |
186 | normal_distribution<result_type> _normal; | |
187 | }; | |
188 | ||
189 | } // namespace random | |
190 | ||
191 | /// \cond show_deprecated | |
192 | ||
193 | /** | |
194 | * Provided for backwards compatibility. This class is | |
195 | * deprecated. It provides the old behavior of lognormal_distribution with | |
196 | * \f$\displaystyle p(x) = \frac{1}{x \sigma_N \sqrt{2\pi}} e^{\frac{-\left(\log(x)-\mu_N\right)^2}{2\sigma_N^2}}\f$ | |
197 | * for x > 0, where \f$\displaystyle \mu_N = \log\left(\frac{\mu^2}{\sqrt{\sigma^2 + \mu^2}}\right)\f$ and | |
198 | * \f$\displaystyle \sigma_N = \sqrt{\log\left(1 + \frac{\sigma^2}{\mu^2}\right)}\f$. | |
199 | */ | |
200 | template<class RealType = double> | |
201 | class lognormal_distribution | |
202 | { | |
203 | public: | |
204 | typedef typename normal_distribution<RealType>::input_type input_type; | |
205 | typedef RealType result_type; | |
206 | ||
207 | lognormal_distribution(RealType mean_arg = RealType(1.0), | |
208 | RealType sigma_arg = RealType(1.0)) | |
209 | : _mean(mean_arg), _sigma(sigma_arg) | |
210 | { | |
211 | init(); | |
212 | } | |
213 | RealType mean() const { return _mean; } | |
214 | RealType sigma() const { return _sigma; } | |
215 | void reset() { _normal.reset(); } | |
216 | template<class Engine> | |
217 | RealType operator()(Engine& eng) | |
218 | { | |
219 | using std::exp; | |
220 | return exp(_normal(eng) * _nsigma + _nmean); | |
221 | } | |
222 | BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, lognormal_distribution, ld) | |
223 | { | |
224 | os << ld._normal << " " << ld._mean << " " << ld._sigma; | |
225 | return os; | |
226 | } | |
227 | BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, lognormal_distribution, ld) | |
228 | { | |
229 | is >> ld._normal >> std::ws >> ld._mean >> std::ws >> ld._sigma; | |
230 | ld.init(); | |
231 | return is; | |
232 | } | |
233 | private: | |
234 | /// \cond show_private | |
235 | void init() | |
236 | { | |
237 | using std::log; | |
238 | using std::sqrt; | |
239 | _nmean = log(_mean*_mean/sqrt(_sigma*_sigma + _mean*_mean)); | |
240 | _nsigma = sqrt(log(_sigma*_sigma/_mean/_mean+result_type(1))); | |
241 | } | |
242 | RealType _mean; | |
243 | RealType _sigma; | |
244 | RealType _nmean; | |
245 | RealType _nsigma; | |
246 | normal_distribution<RealType> _normal; | |
247 | /// \endcond | |
248 | }; | |
249 | ||
250 | /// \endcond | |
251 | ||
252 | } // namespace boost | |
253 | ||
254 | #endif // BOOST_RANDOM_LOGNORMAL_DISTRIBUTION_HPP |