X-Git-Url: https://git.donarmstrong.com/?p=rsem.git;a=blobdiff_plain;f=boost%2Frandom%2Fgamma_distribution.hpp;fp=boost%2Frandom%2Fgamma_distribution.hpp;h=20f5c3b4ff906cb8cb5ab594835cc60ea40be61b;hp=384954baca2994c4afcb7a183dbce988489d06a8;hb=2d71eb92104693ca9baa5a2e1c23eeca776d8fd3;hpb=da57529b92adbb7ae74a89861cb39fb35ac7c62d

diff --git a/boost/random/gamma_distribution.hpp b/boost/random/gamma_distribution.hpp
index 384954b..20f5c3b 100644
--- a/boost/random/gamma_distribution.hpp
+++ b/boost/random/gamma_distribution.hpp
@@ -1,13 +1,14 @@
 /* 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: gamma_distribution.hpp 60755 2010-03-22 00:45:06Z steven_watanabe $
+ * $Id: gamma_distribution.hpp 71018 2011-04-05 21:27:52Z steven_watanabe $
  *
  */
 
@@ -15,129 +16,277 @@
 #define BOOST_RANDOM_GAMMA_DISTRIBUTION_HPP
 
 #include <boost/config/no_tr1/cmath.hpp>
-#include <cassert>
+#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 a single
- * parameter alpha.
+ * The gamma distribution is a continuous distribution with two
+ * parameters alpha and beta.  It produces values > 0.
  *
- * It has \f$p(x) = x^{\alpha-1}\frac{e^{-x}}{\Gamma(\alpha)}\f$.
+ * 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;
+    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);
+    BOOST_STATIC_ASSERT(!std::numeric_limits<RealType>::is_integer);
 #endif
 
-  explicit gamma_distribution(const result_type& alpha_arg = result_type(1))
-    : _exp(result_type(1)), _alpha(alpha_arg)
-  {
-    assert(_alpha > result_type(0));
-    init();
-  }
+    /**
+     * 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
+    // compiler-generated copy ctor and assignment operator are fine
 
-  RealType alpha() const { return _alpha; }
+    /** 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)(); }
 
-  void reset() { _exp.reset(); }
+    /** 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(); }
 
-  template<class Engine>
-  result_type operator()(Engine& eng)
-  {
+    /**
+     * 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;
+        // 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);
-    } 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 * eng());
-        result_type x = sqrt(result_type(2)*_alpha-result_type(1))*y
-          + _alpha-result_type(1);
-        if(x <= result_type(0))
-          continue;
-        if(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;
-      }
-    } else /* alpha < 1.0 */ {
-      for(;;) {
-        result_type u = 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(_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;
+            }
         }
-        if(u >= q)
-          continue;
-        return x;
-      }
     }
-  }
+
+    template<class URNG>
+    RealType operator()(URNG& urng, const param_type& parm) const
+    {
+        return gamma_distribution(parm)(urng);
+    }
 
 #ifndef BOOST_RANDOM_NO_STREAM_OPERATORS
-  template<class CharT, class Traits>
-  friend std::basic_ostream<CharT,Traits>&
-  operator<<(std::basic_ostream<CharT,Traits>& os, const gamma_distribution& gd)
-  {
-    os << gd._alpha;
-    return os;
-  }
-
-  template<class CharT, class Traits>
-  friend std::basic_istream<CharT,Traits>&
-  operator>>(std::basic_istream<CharT,Traits>& is, gamma_distribution& gd)
-  {
-    is >> std::ws >> gd._alpha;
-    gd.init();
-    return is;
-  }
+    /** 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
-  void init()
-  {
+    /// \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;
+        // 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;
-  // some data precomputed from the parameters
-  result_type _p;
+        _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