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255 lines
8.1 KiB
C++
255 lines
8.1 KiB
C++
/* boost random/lognormal_distribution.hpp header file
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*
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* Copyright Jens Maurer 2000-2001
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* Copyright Steven Watanabe 2011
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* Distributed under the Boost Software License, Version 1.0. (See
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* accompanying file LICENSE_1_0.txt or copy at
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* http://www.boost.org/LICENSE_1_0.txt)
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*
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* See http://www.boost.org for most recent version including documentation.
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*
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* $Id$
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*
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* Revision history
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* 2001-02-18 moved to individual header files
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*/
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#ifndef BOOST_RANDOM_LOGNORMAL_DISTRIBUTION_HPP
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#define BOOST_RANDOM_LOGNORMAL_DISTRIBUTION_HPP
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#include <boost/config/no_tr1/cmath.hpp> // std::exp, std::sqrt
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#include <cassert>
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#include <iosfwd>
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#include <istream>
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#include <boost/limits.hpp>
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#include <boost/random/detail/config.hpp>
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#include <boost/random/detail/operators.hpp>
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#include <boost/random/normal_distribution.hpp>
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namespace boost {
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namespace random {
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/**
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* Instantiations of class template lognormal_distribution model a
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* \random_distribution. Such a distribution produces random numbers
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* with \f$\displaystyle p(x) = \frac{1}{x s \sqrt{2\pi}} e^{\frac{-\left(\log(x)-m\right)^2}{2s^2}}\f$
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* for x > 0.
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*
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* @xmlwarning
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* This distribution has been updated to match the C++ standard.
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* Its behavior has changed from the original
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* boost::lognormal_distribution. A backwards compatible
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* version is provided in namespace boost.
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* @endxmlwarning
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*/
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template<class RealType = double>
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class lognormal_distribution
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{
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public:
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typedef typename normal_distribution<RealType>::input_type input_type;
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typedef RealType result_type;
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class param_type
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{
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public:
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typedef lognormal_distribution distribution_type;
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/** Constructs the parameters of a lognormal_distribution. */
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explicit param_type(RealType m_arg = RealType(0.0),
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RealType s_arg = RealType(1.0))
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: _m(m_arg), _s(s_arg) {}
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/** Returns the "m" parameter of the distribution. */
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RealType m() const { return _m; }
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/** Returns the "s" parameter of the distribution. */
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RealType s() const { return _s; }
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/** Writes the parameters to a std::ostream. */
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BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, param_type, parm)
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{
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os << parm._m << " " << parm._s;
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return os;
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}
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/** Reads the parameters from a std::istream. */
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BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, param_type, parm)
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{
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is >> parm._m >> std::ws >> parm._s;
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return is;
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}
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/** Returns true if the two sets of parameters are equal. */
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BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(param_type, lhs, rhs)
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{ return lhs._m == rhs._m && lhs._s == rhs._s; }
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/** Returns true if the two sets of parameters are different. */
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BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(param_type)
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private:
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RealType _m;
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RealType _s;
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};
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/**
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* Constructs a lognormal_distribution. @c m and @c s are the
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* parameters of the distribution.
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*/
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explicit lognormal_distribution(RealType m_arg = RealType(0.0),
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RealType s_arg = RealType(1.0))
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: _normal(m_arg, s_arg) {}
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/**
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* Constructs a lognormal_distribution from its parameters.
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*/
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explicit lognormal_distribution(const param_type& parm)
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: _normal(parm.m(), parm.s()) {}
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// compiler-generated copy ctor and assignment operator are fine
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/** Returns the m parameter of the distribution. */
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RealType m() const { return _normal.mean(); }
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/** Returns the s parameter of the distribution. */
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RealType s() const { return _normal.sigma(); }
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/** Returns the smallest value that the distribution can produce. */
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RealType min BOOST_PREVENT_MACRO_SUBSTITUTION () const
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{ return RealType(0); }
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/** Returns the largest value that the distribution can produce. */
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RealType max BOOST_PREVENT_MACRO_SUBSTITUTION () const
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{ return (std::numeric_limits<RealType>::infinity)(); }
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/** Returns the parameters of the distribution. */
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param_type param() const { return param_type(m(), s()); }
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/** Sets the parameters of the distribution. */
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void param(const param_type& parm)
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{
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typedef normal_distribution<RealType> normal_type;
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typename normal_type::param_type normal_param(parm.m(), parm.s());
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_normal.param(normal_param);
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}
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/**
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* Effects: Subsequent uses of the distribution do not depend
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* on values produced by any engine prior to invoking reset.
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*/
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void reset() { _normal.reset(); }
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/**
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* Returns a random variate distributed according to the
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* lognormal distribution.
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*/
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template<class Engine>
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result_type operator()(Engine& eng)
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{
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using std::exp;
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return exp(_normal(eng));
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}
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/**
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* Returns a random variate distributed according to the
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* lognormal distribution with parameters specified by param.
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*/
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template<class Engine>
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result_type operator()(Engine& eng, const param_type& parm)
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{ return lognormal_distribution(parm)(eng); }
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/** Writes the distribution to a @c std::ostream. */
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BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, lognormal_distribution, ld)
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{
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os << ld._normal;
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return os;
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}
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/** Reads the distribution from a @c std::istream. */
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BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, lognormal_distribution, ld)
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{
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is >> ld._normal;
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return is;
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}
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/**
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* Returns true if the two distributions will produce identical
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* sequences of values given equal generators.
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*/
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BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(lognormal_distribution, lhs, rhs)
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{ return lhs._normal == rhs._normal; }
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/**
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* Returns true if the two distributions may produce different
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* sequences of values given equal generators.
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*/
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BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(lognormal_distribution)
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private:
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normal_distribution<result_type> _normal;
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};
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} // namespace random
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/// \cond show_deprecated
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/**
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* Provided for backwards compatibility. This class is
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* deprecated. It provides the old behavior of lognormal_distribution with
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* \f$\displaystyle p(x) = \frac{1}{x \sigma_N \sqrt{2\pi}} e^{\frac{-\left(\log(x)-\mu_N\right)^2}{2\sigma_N^2}}\f$
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* for x > 0, where \f$\displaystyle \mu_N = \log\left(\frac{\mu^2}{\sqrt{\sigma^2 + \mu^2}}\right)\f$ and
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* \f$\displaystyle \sigma_N = \sqrt{\log\left(1 + \frac{\sigma^2}{\mu^2}\right)}\f$.
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*/
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template<class RealType = double>
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class lognormal_distribution
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{
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public:
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typedef typename normal_distribution<RealType>::input_type input_type;
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typedef RealType result_type;
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lognormal_distribution(RealType mean_arg = RealType(1.0),
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RealType sigma_arg = RealType(1.0))
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: _mean(mean_arg), _sigma(sigma_arg)
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{
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init();
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}
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RealType mean() const { return _mean; }
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RealType sigma() const { return _sigma; }
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void reset() { _normal.reset(); }
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template<class Engine>
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RealType operator()(Engine& eng)
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{
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using std::exp;
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return exp(_normal(eng) * _nsigma + _nmean);
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}
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BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, lognormal_distribution, ld)
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{
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os << ld._normal << " " << ld._mean << " " << ld._sigma;
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return os;
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}
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BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, lognormal_distribution, ld)
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{
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is >> ld._normal >> std::ws >> ld._mean >> std::ws >> ld._sigma;
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ld.init();
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return is;
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}
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private:
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/// \cond show_private
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void init()
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{
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using std::log;
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using std::sqrt;
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_nmean = log(_mean*_mean/sqrt(_sigma*_sigma + _mean*_mean));
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_nsigma = sqrt(log(_sigma*_sigma/_mean/_mean+result_type(1)));
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}
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RealType _mean;
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RealType _sigma;
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RealType _nmean;
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RealType _nsigma;
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normal_distribution<RealType> _normal;
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/// \endcond
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};
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/// \endcond
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} // namespace boost
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#endif // BOOST_RANDOM_LOGNORMAL_DISTRIBUTION_HPP
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