mirror of
https://github.com/ecency/ecency-mobile.git
synced 2024-12-21 20:31:37 +03:00
293 lines
9.2 KiB
C++
293 lines
9.2 KiB
C++
/* boost random/gamma_distribution.hpp header file
|
|
*
|
|
* Copyright Jens Maurer 2002
|
|
* Copyright Steven Watanabe 2010
|
|
* 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.
|
|
*
|
|
* $Id$
|
|
*
|
|
*/
|
|
|
|
#ifndef BOOST_RANDOM_GAMMA_DISTRIBUTION_HPP
|
|
#define BOOST_RANDOM_GAMMA_DISTRIBUTION_HPP
|
|
|
|
#include <boost/config/no_tr1/cmath.hpp>
|
|
#include <istream>
|
|
#include <iosfwd>
|
|
#include <boost/assert.hpp>
|
|
#include <boost/limits.hpp>
|
|
#include <boost/static_assert.hpp>
|
|
#include <boost/random/detail/config.hpp>
|
|
#include <boost/random/exponential_distribution.hpp>
|
|
|
|
namespace boost {
|
|
namespace random {
|
|
|
|
// The algorithm is taken from Knuth
|
|
|
|
/**
|
|
* The gamma distribution is a continuous distribution with two
|
|
* parameters alpha and beta. It produces values > 0.
|
|
*
|
|
* It has
|
|
* \f$\displaystyle p(x) = x^{\alpha-1}\frac{e^{-x/\beta}}{\beta^\alpha\Gamma(\alpha)}\f$.
|
|
*/
|
|
template<class RealType = double>
|
|
class gamma_distribution
|
|
{
|
|
public:
|
|
typedef RealType input_type;
|
|
typedef RealType result_type;
|
|
|
|
class param_type
|
|
{
|
|
public:
|
|
typedef gamma_distribution distribution_type;
|
|
|
|
/**
|
|
* Constructs a @c param_type object from the "alpha" and "beta"
|
|
* parameters.
|
|
*
|
|
* Requires: alpha > 0 && beta > 0
|
|
*/
|
|
param_type(const RealType& alpha_arg = RealType(1.0),
|
|
const RealType& beta_arg = RealType(1.0))
|
|
: _alpha(alpha_arg), _beta(beta_arg)
|
|
{
|
|
}
|
|
|
|
/** Returns the "alpha" parameter of the distribution. */
|
|
RealType alpha() const { return _alpha; }
|
|
/** Returns the "beta" parameter of the distribution. */
|
|
RealType beta() const { return _beta; }
|
|
|
|
#ifndef BOOST_RANDOM_NO_STREAM_OPERATORS
|
|
/** Writes the parameters to a @c std::ostream. */
|
|
template<class CharT, class Traits>
|
|
friend std::basic_ostream<CharT, Traits>&
|
|
operator<<(std::basic_ostream<CharT, Traits>& os,
|
|
const param_type& parm)
|
|
{
|
|
os << parm._alpha << ' ' << parm._beta;
|
|
return os;
|
|
}
|
|
|
|
/** Reads the parameters from a @c std::istream. */
|
|
template<class CharT, class Traits>
|
|
friend std::basic_istream<CharT, Traits>&
|
|
operator>>(std::basic_istream<CharT, Traits>& is, param_type& parm)
|
|
{
|
|
is >> parm._alpha >> std::ws >> parm._beta;
|
|
return is;
|
|
}
|
|
#endif
|
|
|
|
/** Returns true if the two sets of parameters are the same. */
|
|
friend bool operator==(const param_type& lhs, const param_type& rhs)
|
|
{
|
|
return lhs._alpha == rhs._alpha && lhs._beta == rhs._beta;
|
|
}
|
|
/** Returns true if the two sets fo parameters are different. */
|
|
friend bool operator!=(const param_type& lhs, const param_type& rhs)
|
|
{
|
|
return !(lhs == rhs);
|
|
}
|
|
private:
|
|
RealType _alpha;
|
|
RealType _beta;
|
|
};
|
|
|
|
#ifndef BOOST_NO_LIMITS_COMPILE_TIME_CONSTANTS
|
|
BOOST_STATIC_ASSERT(!std::numeric_limits<RealType>::is_integer);
|
|
#endif
|
|
|
|
/**
|
|
* Creates a new gamma_distribution with parameters "alpha" and "beta".
|
|
*
|
|
* Requires: alpha > 0 && beta > 0
|
|
*/
|
|
explicit gamma_distribution(const result_type& alpha_arg = result_type(1.0),
|
|
const result_type& beta_arg = result_type(1.0))
|
|
: _exp(result_type(1)), _alpha(alpha_arg), _beta(beta_arg)
|
|
{
|
|
BOOST_ASSERT(_alpha > result_type(0));
|
|
BOOST_ASSERT(_beta > result_type(0));
|
|
init();
|
|
}
|
|
|
|
/** Constructs a @c gamma_distribution from its parameters. */
|
|
explicit gamma_distribution(const param_type& parm)
|
|
: _exp(result_type(1)), _alpha(parm.alpha()), _beta(parm.beta())
|
|
{
|
|
init();
|
|
}
|
|
|
|
// compiler-generated copy ctor and assignment operator are fine
|
|
|
|
/** Returns the "alpha" paramter of the distribution. */
|
|
RealType alpha() const { return _alpha; }
|
|
/** Returns the "beta" parameter of the distribution. */
|
|
RealType beta() const { return _beta; }
|
|
/** Returns the smallest value that the distribution can produce. */
|
|
RealType min BOOST_PREVENT_MACRO_SUBSTITUTION () const { return 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(_alpha, _beta); }
|
|
/** Sets the parameters of the distribution. */
|
|
void param(const param_type& parm)
|
|
{
|
|
_alpha = parm.alpha();
|
|
_beta = parm.beta();
|
|
init();
|
|
}
|
|
|
|
/**
|
|
* Effects: Subsequent uses of the distribution do not depend
|
|
* on values produced by any engine prior to invoking reset.
|
|
*/
|
|
void reset() { _exp.reset(); }
|
|
|
|
/**
|
|
* Returns a random variate distributed according to
|
|
* the gamma distribution.
|
|
*/
|
|
template<class Engine>
|
|
result_type operator()(Engine& eng)
|
|
{
|
|
#ifndef BOOST_NO_STDC_NAMESPACE
|
|
// allow for Koenig lookup
|
|
using std::tan; using std::sqrt; using std::exp; using std::log;
|
|
using std::pow;
|
|
#endif
|
|
if(_alpha == result_type(1)) {
|
|
return _exp(eng) * _beta;
|
|
} else if(_alpha > result_type(1)) {
|
|
// Can we have a boost::mathconst please?
|
|
const result_type pi = result_type(3.14159265358979323846);
|
|
for(;;) {
|
|
result_type y = tan(pi * uniform_01<RealType>()(eng));
|
|
result_type x = sqrt(result_type(2)*_alpha-result_type(1))*y
|
|
+ _alpha-result_type(1);
|
|
if(x <= result_type(0))
|
|
continue;
|
|
if(uniform_01<RealType>()(eng) >
|
|
(result_type(1)+y*y) * exp((_alpha-result_type(1))
|
|
*log(x/(_alpha-result_type(1)))
|
|
- sqrt(result_type(2)*_alpha
|
|
-result_type(1))*y))
|
|
continue;
|
|
return x * _beta;
|
|
}
|
|
} else /* alpha < 1.0 */ {
|
|
for(;;) {
|
|
result_type u = uniform_01<RealType>()(eng);
|
|
result_type y = _exp(eng);
|
|
result_type x, q;
|
|
if(u < _p) {
|
|
x = exp(-y/_alpha);
|
|
q = _p*exp(-x);
|
|
} else {
|
|
x = result_type(1)+y;
|
|
q = _p + (result_type(1)-_p) * pow(x,_alpha-result_type(1));
|
|
}
|
|
if(u >= q)
|
|
continue;
|
|
return x * _beta;
|
|
}
|
|
}
|
|
}
|
|
|
|
template<class URNG>
|
|
RealType operator()(URNG& urng, const param_type& parm) const
|
|
{
|
|
return gamma_distribution(parm)(urng);
|
|
}
|
|
|
|
#ifndef BOOST_RANDOM_NO_STREAM_OPERATORS
|
|
/** Writes a @c gamma_distribution to a @c std::ostream. */
|
|
template<class CharT, class Traits>
|
|
friend std::basic_ostream<CharT,Traits>&
|
|
operator<<(std::basic_ostream<CharT,Traits>& os,
|
|
const gamma_distribution& gd)
|
|
{
|
|
os << gd.param();
|
|
return os;
|
|
}
|
|
|
|
/** Reads a @c gamma_distribution from a @c std::istream. */
|
|
template<class CharT, class Traits>
|
|
friend std::basic_istream<CharT,Traits>&
|
|
operator>>(std::basic_istream<CharT,Traits>& is, gamma_distribution& gd)
|
|
{
|
|
gd.read(is);
|
|
return is;
|
|
}
|
|
#endif
|
|
|
|
/**
|
|
* Returns true if the two distributions will produce identical
|
|
* sequences of random variates given equal generators.
|
|
*/
|
|
friend bool operator==(const gamma_distribution& lhs,
|
|
const gamma_distribution& rhs)
|
|
{
|
|
return lhs._alpha == rhs._alpha
|
|
&& lhs._beta == rhs._beta
|
|
&& lhs._exp == rhs._exp;
|
|
}
|
|
|
|
/**
|
|
* Returns true if the two distributions can produce different
|
|
* sequences of random variates, given equal generators.
|
|
*/
|
|
friend bool operator!=(const gamma_distribution& lhs,
|
|
const gamma_distribution& rhs)
|
|
{
|
|
return !(lhs == rhs);
|
|
}
|
|
|
|
private:
|
|
/// \cond hide_private_members
|
|
|
|
template<class CharT, class Traits>
|
|
void read(std::basic_istream<CharT, Traits>& is)
|
|
{
|
|
param_type parm;
|
|
if(is >> parm) {
|
|
param(parm);
|
|
}
|
|
}
|
|
|
|
void init()
|
|
{
|
|
#ifndef BOOST_NO_STDC_NAMESPACE
|
|
// allow for Koenig lookup
|
|
using std::exp;
|
|
#endif
|
|
_p = exp(result_type(1)) / (_alpha + exp(result_type(1)));
|
|
}
|
|
/// \endcond
|
|
|
|
exponential_distribution<RealType> _exp;
|
|
result_type _alpha;
|
|
result_type _beta;
|
|
// some data precomputed from the parameters
|
|
result_type _p;
|
|
};
|
|
|
|
|
|
} // namespace random
|
|
|
|
using random::gamma_distribution;
|
|
|
|
} // namespace boost
|
|
|
|
#endif // BOOST_RANDOM_GAMMA_DISTRIBUTION_HPP
|