vn-verdnaturachat/ios/Pods/boost-for-react-native/boost/random/lognormal_distribution.hpp

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/* 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