Implement the K-distribution as an extension.

From-SVN: r191688

1 files changed, 244 insertions, 0 deletions

diff --git a/libstdc++-v3/include/ext/random b/libstdc++-v3/include/ext/random
index 97bd014..c7321a9 100644
--- a/libstdc++-v3/include/ext/random
+++ b/libstdc++-v3/include/ext/random
@@ -1596,6 +1596,250 @@ _GLIBCXX_BEGIN_NAMESPACE_VERSION
 	       const pareto_distribution<_RealType>& __d2)
     { return !(__d1 == __d2); }
 
+
+  /**
+   * @brief A K continuous distribution for random numbers.
+   *
+   * The formula for the K probability density function is
+   * @f[
+   *     p(x|\lambda, \mu, \nu) = \frac{2}{x}
+   *             \left(\frac{\lambda\nu x}{\mu}\right)^{\frac{\lambda + \nu}{2}}
+   *             \frac{1}{\Gamma(\lambda)\Gamma(\nu)}
+   *             K_{\nu - \lambda}\left(2\sqrt{\frac{\lambda\nu x}{\mu}}\right)
+   * @f]
+   * where @f$I_0(z)@f$ is the modified Bessel function of the second kind
+   * of order @f$\nu - \lambda@f$ and @f$\lambda > 0@f$, @f$\mu > 0@f$
+   * and @f$\nu > 0@f$.
+   *
+   * <table border=1 cellpadding=10 cellspacing=0>
+   * <caption align=top>Distribution Statistics</caption>
+   * <tr><td>Mean</td><td>@f$\mu@f$</td></tr>
+   * <tr><td>Variance</td><td>@f$\mu^2\frac{\lambda + \nu + 1}{\lambda\nu}@f$</td></tr>
+   * <tr><td>Range</td><td>@f$[0, \infty)@f$</td></tr>
+   * </table>
+   */
+  template<typename _RealType = double>
+    class
+    k_distribution
+    {
+      static_assert(std::is_floating_point<_RealType>::value,
+		    "template argument not a floating point type");
+
+    public:
+      /** The type of the range of the distribution. */
+      typedef _RealType result_type;
+      /** Parameter type. */
+      struct param_type
+      {
+	typedef k_distribution<result_type> distribution_type;
+
+	param_type(result_type __lambda_val = result_type(1),
+		   result_type __mu_val = result_type(1),
+		   result_type __nu_val = result_type(1))
+	: _M_lambda(__lambda_val), _M_mu(__mu_val), _M_nu(__nu_val)
+	{
+	  _GLIBCXX_DEBUG_ASSERT(_M_lambda > result_type(0));
+	  _GLIBCXX_DEBUG_ASSERT(_M_mu > result_type(0));
+	  _GLIBCXX_DEBUG_ASSERT(_M_nu > result_type(0));
+	}
+
+	result_type
+	lambda() const
+	{ return _M_lambda; }
+
+	result_type
+	mu() const
+	{ return _M_mu; }
+
+	result_type
+	nu() const
+	{ return _M_nu; }
+
+	friend bool
+	operator==(const param_type& __p1, const param_type& __p2)
+	{ return __p1._M_lambda == __p2._M_lambda
+              && __p1._M_mu == __p2._M_mu
+	      && __p1._M_nu == __p2._M_nu; }
+
+      private:
+	void _M_initialize();
+
+	result_type _M_lambda;
+	result_type _M_mu;
+	result_type _M_nu;
+      };
+
+      /**
+       * @brief Constructors.
+       */
+      explicit
+      k_distribution(result_type __lambda_val = result_type(1),
+		     result_type __mu_val = result_type(1),
+		     result_type __nu_val = result_type(1))
+      : _M_param(__lambda_val, __mu_val, __nu_val),
+	_M_gd1(__lambda_val, result_type(1) / __lambda_val),
+	_M_gd2(__nu_val, __mu_val / __nu_val)
+      { }
+
+      explicit
+      k_distribution(const param_type& __p)
+      : _M_param(__p),
+	_M_gd1(__p.lambda(), result_type(1) / __p.lambda()),
+	_M_gd2(__p.nu(), __p.mu() / __p.nu())
+      { }
+
+      /**
+       * @brief Resets the distribution state.
+       */
+      void
+      reset()
+      {
+	_M_gd1.reset();
+	_M_gd2.reset();
+      }
+
+      /**
+       * @brief Return the parameters of the distribution.
+       */
+      result_type
+      lambda() const
+      { return _M_param.lambda(); }
+
+      result_type
+      mu() const
+      { return _M_param.mu(); }
+
+      result_type
+      nu() const
+      { return _M_param.nu(); }
+
+      /**
+       * @brief Returns the parameter set of the distribution.
+       */
+      param_type
+      param() const
+      { return _M_param; }
+
+      /**
+       * @brief Sets the parameter set of the distribution.
+       * @param __param The new parameter set of the distribution.
+       */
+      void
+      param(const param_type& __param)
+      { _M_param = __param; }
+
+      /**
+       * @brief Returns the greatest lower bound value of the distribution.
+       */
+      result_type
+      min() const
+      { return result_type(0); }
+
+      /**
+       * @brief Returns the least upper bound value of the distribution.
+       */
+      result_type
+      max() const
+      { return std::numeric_limits<result_type>::max(); }
+
+      /**
+       * @brief Generating functions.
+       */
+      template<typename _UniformRandomNumberGenerator>
+	result_type
+	operator()(_UniformRandomNumberGenerator&);
+
+      template<typename _UniformRandomNumberGenerator>
+	result_type
+	operator()(_UniformRandomNumberGenerator&, const param_type&);
+
+      template<typename _ForwardIterator,
+	       typename _UniformRandomNumberGenerator>
+	void
+	__generate(_ForwardIterator __f, _ForwardIterator __t,
+		   _UniformRandomNumberGenerator& __urng)
+	{ this->__generate(__f, __t, __urng, this->param()); }
+
+      template<typename _ForwardIterator,
+	       typename _UniformRandomNumberGenerator>
+	void
+	__generate(_ForwardIterator __f, _ForwardIterator __t,
+		   _UniformRandomNumberGenerator& __urng,
+		   const param_type& __p)
+	{ this->__generate_impl(__f, __t, __urng, __p); }
+
+      template<typename _UniformRandomNumberGenerator>
+	void
+	__generate(result_type* __f, result_type* __t,
+		   _UniformRandomNumberGenerator& __urng,
+		   const param_type& __p)
+	{ this->__generate_impl(__f, __t, __urng, __p); }
+
+      /**
+       * @brief Return true if two K distributions have
+       *        the same parameters and the sequences that would
+       *        be generated are equal.
+       */
+      friend bool
+      operator==(const k_distribution& __d1,
+		 const k_distribution& __d2)
+      { return (__d1.param() == __d2.param()
+		&& __d1._M_gd1 == __d2._M_gd1
+		&& __d1._M_gd2 == __d2._M_gd2); }
+
+      /**
+       * @brief Inserts a %k_distribution random number distribution
+       * @p __x into the output stream @p __os.
+       *
+       * @param __os An output stream.
+       * @param __x  A %k_distribution random number distribution.
+       *
+       * @returns The output stream with the state of @p __x inserted or in
+       * an error state.
+       */
+      template<typename _RealType1, typename _CharT, typename _Traits>
+	friend std::basic_ostream<_CharT, _Traits>&
+	operator<<(std::basic_ostream<_CharT, _Traits>&,
+		   const k_distribution<_RealType1>&);
+
+      /**
+       * @brief Extracts a %k_distribution random number distribution
+       * @p __x from the input stream @p __is.
+       *
+       * @param __is An input stream.
+       * @param __x A %k_distribution random number
+       *            generator engine.
+       *
+       * @returns The input stream with @p __x extracted or in an error state.
+       */
+      template<typename _RealType1, typename _CharT, typename _Traits>
+	friend std::basic_istream<_CharT, _Traits>&
+	operator>>(std::basic_istream<_CharT, _Traits>&,
+		   k_distribution<_RealType1>&);
+
+    private:
+      template<typename _ForwardIterator,
+	       typename _UniformRandomNumberGenerator>
+	void
+	__generate_impl(_ForwardIterator __f, _ForwardIterator __t,
+			_UniformRandomNumberGenerator& __urng,
+			const param_type& __p);
+
+      param_type _M_param;
+
+      std::gamma_distribution<result_type> _M_gd1;
+      std::gamma_distribution<result_type> _M_gd2;
+    };
+
+  /**
+   * @brief Return true if two K distributions are not equal.
+   */
+  template<typename _RealType>
+    inline bool
+    operator!=(const k_distribution<_RealType>& __d1,
+	       const k_distribution<_RealType>& __d2)
+    { return !(__d1 == __d2); }
+
 _GLIBCXX_END_NAMESPACE_VERSION
 } // namespace __gnu_cxx