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
29namespace boost {
30namespace 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 */
45template<class RealType = double>
46class lognormal_distribution
47{
48public:
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
185private:
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 */
200template<class RealType = double>
201class lognormal_distribution
202{
203public:
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 }
233private:
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
255