#### /Src/Dependencies/Boost/boost/random/chi_squared_distribution.hpp

C++ Header | 209 lines | 119 code | 26 blank | 64 comment | 5 complexity | 79eebf135d637d16aa5948f38a9da97f MD5 | raw file
  1/* boost random/chi_squared_distribution.hpp header file
2 *
3 * Copyright Steven Watanabe 2011
5 * accompanying file LICENSE_1_0.txt or copy at
7 *
9 *
10 * $Id: chi_squared_distribution.hpp 71018 2011-04-05 21:27:52Z steven_watanabe$
11 */
12
13#ifndef BOOST_RANDOM_CHI_SQUARED_DISTRIBUTION_HPP_INCLUDED
14#define BOOST_RANDOM_CHI_SQUARED_DISTRIBUTION_HPP_INCLUDED
15
16#include <iosfwd>
17#include <boost/limits.hpp>
18
19#include <boost/random/detail/config.hpp>
20#include <boost/random/gamma_distribution.hpp>
21
22namespace boost {
23namespace random {
24
25/**
26 * The chi squared distribution is a real valued distribution with
27 * one parameter, @c n.  The distribution produces values > 0.
28 *
29 * The distribution function is
30 * \f$\displaystyle P(x) = \frac{x^{(n/2)-1}e^{-x/2}}{\Gamma(n/2)2^{n/2}}\f$.
31 */
32template<class RealType = double>
33class chi_squared_distribution {
34public:
35    typedef RealType result_type;
36    typedef RealType input_type;
37
38    class param_type {
39    public:
40        typedef chi_squared_distribution distribution_type;
41        /**
42         * Construct a param_type object.  @c n
43         * is the parameter of the distribution.
44         *
45         * Requires: t >=0 && 0 <= p <= 1
46         */
47        explicit param_type(RealType n_arg = RealType(1))
48          : _n(n_arg)
49        {}
50        /** Returns the @c n parameter of the distribution. */
51        RealType n() const { return _n; }
52#ifndef BOOST_RANDOM_NO_STREAM_OPERATORS
53        /** Writes the parameters of the distribution to a @c std::ostream. */
54        template<class CharT, class Traits>
55        friend std::basic_ostream<CharT,Traits>&
56        operator<<(std::basic_ostream<CharT,Traits>& os,
57                   const param_type& parm)
58        {
59            os << parm._n;
60            return os;
61        }
62
63        /** Reads the parameters of the distribution from a @c std::istream. */
64        template<class CharT, class Traits>
65        friend std::basic_istream<CharT,Traits>&
66        operator>>(std::basic_istream<CharT,Traits>& is, param_type& parm)
67        {
68            is >> parm._n;
69            return is;
70        }
71#endif
72        /** Returns true if the parameters have the same values. */
73        friend bool operator==(const param_type& lhs, const param_type& rhs)
74        {
75            return lhs._n == rhs._n;
76        }
77        /** Returns true if the parameters have different values. */
78        friend bool operator!=(const param_type& lhs, const param_type& rhs)
79        {
80            return !(lhs == rhs);
81        }
82    private:
83        RealType _n;
84    };
85
86    /**
87     * Construct a @c chi_squared_distribution object. @c n
88     * is the parameter of the distribution.
89     *
90     * Requires: t >=0 && 0 <= p <= 1
91     */
92    explicit chi_squared_distribution(RealType n_arg = RealType(1))
93      : _impl(n_arg / 2)
94    {
95    }
96
97    /**
98     * Construct an @c chi_squared_distribution object from the
99     * parameters.
100     */
101    explicit chi_squared_distribution(const param_type& parm)
102      : _impl(parm.n() / 2)
103    {
104    }
105
106    /**
107     * Returns a random variate distributed according to the
108     * chi squared distribution.
109     */
110    template<class URNG>
111    RealType operator()(URNG& urng)
112    {
113        return 2 * _impl(urng);
114    }
115
116    /**
117     * Returns a random variate distributed according to the
118     * chi squared distribution with parameters specified by @c param.
119     */
120    template<class URNG>
121    RealType operator()(URNG& urng, const param_type& parm) const
122    {
123        return chi_squared_distribution(parm)(urng);
124    }
125
126    /** Returns the @c n parameter of the distribution. */
127    RealType n() const { return 2 * _impl.alpha(); }
128
129    /** Returns the smallest value that the distribution can produce. */
130    RealType min BOOST_PREVENT_MACRO_SUBSTITUTION() const { return 0; }
131    /** Returns the largest value that the distribution can produce. */
132    RealType max BOOST_PREVENT_MACRO_SUBSTITUTION() const
133    { return (std::numeric_limits<RealType>::infinity)(); }
134
135    /** Returns the parameters of the distribution. */
136    param_type param() const { return param_type(n()); }
137    /** Sets parameters of the distribution. */
138    void param(const param_type& parm)
139    {
140        typedef gamma_distribution<RealType> impl_type;
141        typename impl_type::param_type impl_parm(parm.n() / 2);
142        _impl.param(impl_parm);
143    }
144
145    /**
146     * Effects: Subsequent uses of the distribution do not depend
147     * on values produced by any engine prior to invoking reset.
148     */
149    void reset() { _impl.reset(); }
150
151#ifndef BOOST_RANDOM_NO_STREAM_OPERATORS
152    /** Writes the parameters of the distribution to a @c std::ostream. */
153    template<class CharT, class Traits>
154    friend std::basic_ostream<CharT,Traits>&
155    operator<<(std::basic_ostream<CharT,Traits>& os,
156               const chi_squared_distribution& c2d)
157    {
158        os << c2d.param();
159        return os;
160    }
161
162    /** Reads the parameters of the distribution from a @c std::istream. */
163    template<class CharT, class Traits>
164    friend std::basic_istream<CharT,Traits>&
165    operator>>(std::basic_istream<CharT,Traits>& is,
166               chi_squared_distribution& c2d)
167    {
169        return is;
170    }
171#endif
172
173    /** Returns true if the two distributions will produce the same
174        sequence of values, given equal generators. */
175    friend bool operator==(const chi_squared_distribution& lhs,
176                           const chi_squared_distribution& rhs)
177    {
178        return lhs._impl == rhs._impl;
179    }
180    /** Returns true if the two distributions could produce different
181        sequences of values, given equal generators. */
182    friend bool operator!=(const chi_squared_distribution& lhs,
183                           const chi_squared_distribution& rhs)
184    {
185        return !(lhs == rhs);
186    }
187
188private:
189
190    /// @cond show_private
191
192    template<class CharT, class Traits>
193    void read(std::basic_istream<CharT, Traits>& is) {
194        param_type parm;
195        if(is >> parm) {
196            param(parm);
197        }
198    }
199
200    gamma_distribution<RealType> _impl;
201
202    /// @endcond
203};
204
205}
206
207}
208
209#endif