| /* 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 |