/
usr
/
include
/
boost
/
random
/
/usr/include/boost/random
mkdir
upload
Name
Size
Mode
Actions
detail/
-
0755
rm
additive_combine.hpp
8826
0644
edit
dl
rm
bernoulli_distribution.hpp
5608
0644
edit
dl
rm
beta_distribution.hpp
5900
0644
edit
dl
rm
binomial_distribution.hpp
12985
0644
edit
dl
rm
cauchy_distribution.hpp
6528
0644
edit
dl
rm
chi_squared_distribution.hpp
6322
0644
edit
dl
rm
discard_block.hpp
7991
0644
edit
dl
rm
discrete_distribution.hpp
21137
0644
edit
dl
rm
exponential_distribution.hpp
20895
0644
edit
dl
rm
extreme_value_distribution.hpp
5611
0644
edit
dl
rm
faure.hpp
11474
0644
edit
dl
rm
fisher_f_distribution.hpp
5924
0644
edit
dl
rm
gamma_distribution.hpp
9166
0644
edit
dl
rm
generate_canonical.hpp
2954
0644
edit
dl
rm
geometric_distribution.hpp
7339
0644
edit
dl
rm
hyperexponential_distribution.hpp
36980
0644
edit
dl
rm
independent_bits.hpp
9117
0644
edit
dl
rm
inversive_congruential.hpp
9550
0644
edit
dl
rm
lagged_fibonacci.hpp
18256
0644
edit
dl
rm
laplace_distribution.hpp
5743
0644
edit
dl
rm
linear_congruential.hpp
16214
0644
edit
dl
rm
linear_feedback_shift.hpp
7162
0644
edit
dl
rm
lognormal_distribution.hpp
8051
0644
edit
dl
rm
mersenne_twister.hpp
24094
0644
edit
dl
rm
negative_binomial_distribution.hpp
6911
0644
edit
dl
rm
niederreiter_base2.hpp
11736
0644
edit
dl
rm
non_central_chi_squared_distribution.hpp
7724
0644
edit
dl
rm
normal_distribution.hpp
17441
0644
edit
dl
rm
piecewise_constant_distribution.hpp
17186
0644
edit
dl
rm
piecewise_linear_distribution.hpp
18802
0644
edit
dl
rm
poisson_distribution.hpp
10145
0644
edit
dl
rm
random_device.hpp
5032
0644
edit
dl
rm
random_number_generator.hpp
1958
0644
edit
dl
rm
ranlux.hpp
3292
0644
edit
dl
rm
seed_seq.hpp
3792
0644
edit
dl
rm
shuffle_order.hpp
9181
0644
edit
dl
rm
shuffle_output.hpp
1352
0644
edit
dl
rm
sobol.hpp
7704
0644
edit
dl
rm
student_t_distribution.hpp
5633
0644
edit
dl
rm
subtract_with_carry.hpp
21590
0644
edit
dl
rm
taus88.hpp
1164
0644
edit
dl
rm
traits.hpp
4165
0644
edit
dl
rm
triangle_distribution.hpp
7033
0644
edit
dl
rm
uniform_01.hpp
7538
0644
edit
dl
rm
uniform_int.hpp
2909
0644
edit
dl
rm
uniform_int_distribution.hpp
16199
0644
edit
dl
rm
uniform_on_sphere.hpp
8812
0644
edit
dl
rm
uniform_real.hpp
2449
0644
edit
dl
rm
uniform_real_distribution.hpp
7726
0644
edit
dl
rm
uniform_smallint.hpp
12230
0644
edit
dl
rm
variate_generator.hpp
3708
0644
edit
dl
rm
weibull_distribution.hpp
5524
0644
edit
dl
rm
xor_combine.hpp
7049
0644
edit
dl
rm
Edit:
/usr/include/boost/random/lognormal_distribution.hpp
(8051B)
/* boost random/lognormal_distribution.hpp header file * * Copyright Jens Maurer 2000-2001 * Copyright Steven Watanabe 2011 * Distributed under the Boost Software License, Version 1.0. (See * accompanying file LICENSE_1_0.txt or copy at * http://www.boost.org/LICENSE_1_0.txt) * * See http://www.boost.org for most recent version including documentation. * * $Id$ * * Revision history * 2001-02-18 moved to individual header files */ #ifndef BOOST_RANDOM_LOGNORMAL_DISTRIBUTION_HPP #define BOOST_RANDOM_LOGNORMAL_DISTRIBUTION_HPP #include <boost/config/no_tr1/cmath.hpp> // std::exp, std::sqrt #include <cassert> #include <iosfwd> #include <istream> #include <boost/limits.hpp> #include <boost/random/detail/config.hpp> #include <boost/random/detail/operators.hpp> #include <boost/random/normal_distribution.hpp> namespace boost { namespace random { /** * Instantiations of class template lognormal_distribution model a * \random_distribution. Such a distribution produces random numbers * with \f$\displaystyle p(x) = \frac{1}{x s \sqrt{2\pi}} e^{\frac{-\left(\log(x)-m\right)^2}{2s^2}}\f$ * for x > 0. * * @xmlwarning * This distribution has been updated to match the C++ standard. * Its behavior has changed from the original * boost::lognormal_distribution. A backwards compatible * version is provided in namespace boost. * @endxmlwarning */ template<class RealType = double> class lognormal_distribution { public: typedef typename normal_distribution<RealType>::input_type input_type; typedef RealType result_type; class param_type { public: typedef lognormal_distribution distribution_type; /** Constructs the parameters of a lognormal_distribution. */ explicit param_type(RealType m_arg = RealType(0.0), RealType s_arg = RealType(1.0)) : _m(m_arg), _s(s_arg) {} /** Returns the "m" parameter of the distribution. */ RealType m() const { return _m; } /** Returns the "s" parameter of the distribution. */ RealType s() const { return _s; } /** Writes the parameters to a std::ostream. */ BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, param_type, parm) { os << parm._m << " " << parm._s; return os; } /** Reads the parameters from a std::istream. */ BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, param_type, parm) { is >> parm._m >> std::ws >> parm._s; return is; } /** Returns true if the two sets of parameters are equal. */ BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(param_type, lhs, rhs) { return lhs._m == rhs._m && lhs._s == rhs._s; } /** Returns true if the two sets of parameters are different. */ BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(param_type) private: RealType _m; RealType _s; }; /** * Constructs a lognormal_distribution. @c m and @c s are the * parameters of the distribution. */ explicit lognormal_distribution(RealType m_arg = RealType(0.0), RealType s_arg = RealType(1.0)) : _normal(m_arg, s_arg) {} /** * Constructs a lognormal_distribution from its parameters. */ explicit lognormal_distribution(const param_type& parm) : _normal(parm.m(), parm.s()) {} // compiler-generated copy ctor and assignment operator are fine /** Returns the m parameter of the distribution. */ RealType m() const { return _normal.mean(); } /** Returns the s parameter of the distribution. */ RealType s() const { return _normal.sigma(); } /** Returns the smallest value that the distribution can produce. */ RealType min BOOST_PREVENT_MACRO_SUBSTITUTION () const { return RealType(0); } /** Returns the largest value that the distribution can produce. */ RealType max BOOST_PREVENT_MACRO_SUBSTITUTION () const { return (std::numeric_limits<RealType>::infinity)(); } /** Returns the parameters of the distribution. */ param_type param() const { return param_type(m(), s()); } /** Sets the parameters of the distribution. */ void param(const param_type& parm) { typedef normal_distribution<RealType> normal_type; typename normal_type::param_type normal_param(parm.m(), parm.s()); _normal.param(normal_param); } /** * Effects: Subsequent uses of the distribution do not depend * on values produced by any engine prior to invoking reset. */ void reset() { _normal.reset(); } /** * Returns a random variate distributed according to the * lognormal distribution. */ template<class Engine> result_type operator()(Engine& eng) { using std::exp; return exp(_normal(eng)); } /** * Returns a random variate distributed according to the * lognormal distribution with parameters specified by param. */ template<class Engine> result_type operator()(Engine& eng, const param_type& parm) { return lognormal_distribution(parm)(eng); } /** Writes the distribution to a @c std::ostream. */ BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, lognormal_distribution, ld) { os << ld._normal; return os; } /** Reads the distribution from a @c std::istream. */ BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, lognormal_distribution, ld) { is >> ld._normal; return is; } /** * Returns true if the two distributions will produce identical * sequences of values given equal generators. */ BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(lognormal_distribution, lhs, rhs) { return lhs._normal == rhs._normal; } /** * Returns true if the two distributions may produce different * sequences of values given equal generators. */ BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(lognormal_distribution) private: normal_distribution<result_type> _normal; }; } // namespace random /// \cond show_deprecated /** * Provided for backwards compatibility. This class is * deprecated. It provides the old behavior of lognormal_distribution with * \f$\displaystyle p(x) = \frac{1}{x \sigma_N \sqrt{2\pi}} e^{\frac{-\left(\log(x)-\mu_N\right)^2}{2\sigma_N^2}}\f$ * for x > 0, where \f$\displaystyle \mu_N = \log\left(\frac{\mu^2}{\sqrt{\sigma^2 + \mu^2}}\right)\f$ and * \f$\displaystyle \sigma_N = \sqrt{\log\left(1 + \frac{\sigma^2}{\mu^2}\right)}\f$. */ template<class RealType = double> class lognormal_distribution { public: typedef typename normal_distribution<RealType>::input_type input_type; typedef RealType result_type; lognormal_distribution(RealType mean_arg = RealType(1.0), RealType sigma_arg = RealType(1.0)) : _mean(mean_arg), _sigma(sigma_arg) { init(); } RealType mean() const { return _mean; } RealType sigma() const { return _sigma; } void reset() { _normal.reset(); } template<class Engine> RealType operator()(Engine& eng) { using std::exp; return exp(_normal(eng) * _nsigma + _nmean); } BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, lognormal_distribution, ld) { os << ld._normal << " " << ld._mean << " " << ld._sigma; return os; } BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, lognormal_distribution, ld) { is >> ld._normal >> std::ws >> ld._mean >> std::ws >> ld._sigma; ld.init(); return is; } private: /// \cond show_private void init() { using std::log; using std::sqrt; _nmean = log(_mean*_mean/sqrt(_sigma*_sigma + _mean*_mean)); _nsigma = sqrt(log(_sigma*_sigma/_mean/_mean+result_type(1))); } RealType _mean; RealType _sigma; RealType _nmean; RealType _nsigma; normal_distribution<RealType> _normal; /// \endcond }; /// \endcond } // namespace boost #endif // BOOST_RANDOM_LOGNORMAL_DISTRIBUTION_HPP
Save
cmd:
run