comparison DEPENDENCIES/generic/include/boost/math/concepts/distributions.hpp @ 16:2665513ce2d3

Add boost headers

+//  Copyright John Maddock 2006.
+//  Use, modification and distribution are subject to 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)
+
+// distributions.hpp provides definitions of the concept of a distribution
+// and non-member accessor functions that must be implemented by all distributions.
+// This is used to verify that
+// all the features of a distributions have been fully implemented.
+
+#ifndef BOOST_MATH_DISTRIBUTION_CONCEPT_HPP
+#define BOOST_MATH_DISTRIBUTION_CONCEPT_HPP
+
+#include <boost/math/distributions/complement.hpp>
+#include <boost/math/distributions/fwd.hpp>
+#ifdef BOOST_MSVC
+#pragma warning(push)
+#pragma warning(disable: 4100)
+#pragma warning(disable: 4510)
+#pragma warning(disable: 4610)
+#pragma warning(disable: 4189) // local variable is initialized but not referenced.
+#endif
+#include <boost/concept_check.hpp>
+#ifdef BOOST_MSVC
+#pragma warning(pop)
+#endif
+#include <utility>
+
+namespace boost{
+namespace math{
+
+namespace concepts
+{
+// Begin by defining a concept archetype
+// for a distribution class:
+//
+template <class RealType>
+class distribution_archetype
+{
+public:
+   typedef RealType value_type;
+
+   distribution_archetype(const distribution_archetype&); // Copy constructible.
+   distribution_archetype& operator=(const distribution_archetype&); // Assignable.
+
+   // There is no default constructor,
+   // but we need a way to instantiate the archetype:
+   static distribution_archetype& get_object()
+   {
+      // will never get caled:
+      return *reinterpret_cast<distribution_archetype*>(0);
+   }
+}; // template <class RealType>class distribution_archetype
+
+// Non-member accessor functions:
+// (This list defines the functions that must be implemented by all distributions).
+
+template <class RealType>
+RealType pdf(const distribution_archetype<RealType>& dist, const RealType& x);
+
+template <class RealType>
+RealType cdf(const distribution_archetype<RealType>& dist, const RealType& x);
+
+template <class RealType>
+RealType quantile(const distribution_archetype<RealType>& dist, const RealType& p);
+
+template <class RealType>
+RealType cdf(const complemented2_type<distribution_archetype<RealType>, RealType>& c);
+
+template <class RealType>
+RealType quantile(const complemented2_type<distribution_archetype<RealType>, RealType>& c);
+
+template <class RealType>
+RealType mean(const distribution_archetype<RealType>& dist);
+
+template <class RealType>
+RealType standard_deviation(const distribution_archetype<RealType>& dist);
+
+template <class RealType>
+RealType variance(const distribution_archetype<RealType>& dist);
+
+template <class RealType>
+RealType hazard(const distribution_archetype<RealType>& dist);
+
+template <class RealType>
+RealType chf(const distribution_archetype<RealType>& dist);
+// http://en.wikipedia.org/wiki/Characteristic_function_%28probability_theory%29
+
+template <class RealType>
+RealType coefficient_of_variation(const distribution_archetype<RealType>& dist);
+
+template <class RealType>
+RealType mode(const distribution_archetype<RealType>& dist);
+
+template <class RealType>
+RealType skewness(const distribution_archetype<RealType>& dist);
+
+template <class RealType>
+RealType kurtosis_excess(const distribution_archetype<RealType>& dist);
+
+template <class RealType>
+RealType kurtosis(const distribution_archetype<RealType>& dist);
+
+template <class RealType>
+RealType median(const distribution_archetype<RealType>& dist);
+
+template <class RealType>
+std::pair<RealType, RealType> range(const distribution_archetype<RealType>& dist);
+
+template <class RealType>
+std::pair<RealType, RealType> support(const distribution_archetype<RealType>& dist);
+
+//
+// Next comes the concept checks for verifying that a class
+// fullfils the requirements of a Distribution:
+//
+template <class Distribution>
+struct DistributionConcept
+{
+   typedef typename Distribution::value_type value_type;
+
+   void constraints()
+   {
+      function_requires<CopyConstructibleConcept<Distribution> >();
+      function_requires<AssignableConcept<Distribution> >();
+
+      const Distribution& dist = DistributionConcept<Distribution>::get_object();
+
+      value_type x = 0;
+       // The result values are ignored in all these checks.
+       value_type v = cdf(dist, x);
+      v = cdf(complement(dist, x));
+      suppress_unused_variable_warning(v);
+      v = pdf(dist, x);
+      suppress_unused_variable_warning(v);
+      v = quantile(dist, x);
+      suppress_unused_variable_warning(v);
+      v = quantile(complement(dist, x));
+      suppress_unused_variable_warning(v);
+      v = mean(dist);
+      suppress_unused_variable_warning(v);
+      v = mode(dist);
+      suppress_unused_variable_warning(v);
+      v = standard_deviation(dist);
+      suppress_unused_variable_warning(v);
+      v = variance(dist);
+      suppress_unused_variable_warning(v);
+      v = hazard(dist, x);
+      suppress_unused_variable_warning(v);
+      v = chf(dist, x);
+      suppress_unused_variable_warning(v);
+      v = coefficient_of_variation(dist);
+      suppress_unused_variable_warning(v);
+      v = skewness(dist);
+      suppress_unused_variable_warning(v);
+      v = kurtosis(dist);
+      suppress_unused_variable_warning(v);
+      v = kurtosis_excess(dist);
+      suppress_unused_variable_warning(v);
+      v = median(dist);
+      suppress_unused_variable_warning(v);
+      std::pair<value_type, value_type> pv;
+      pv = range(dist);
+      suppress_unused_variable_warning(pv);
+      pv = support(dist);
+      suppress_unused_variable_warning(pv);
+
+      float f = 1;
+      v = cdf(dist, f);
+      suppress_unused_variable_warning(v);
+      v = cdf(complement(dist, f));
+      suppress_unused_variable_warning(v);
+      v = pdf(dist, f);
+      suppress_unused_variable_warning(v);
+      v = quantile(dist, f);
+      suppress_unused_variable_warning(v);
+      v = quantile(complement(dist, f));
+      suppress_unused_variable_warning(v);
+      v = hazard(dist, f);
+      suppress_unused_variable_warning(v);
+      v = chf(dist, f);
+      suppress_unused_variable_warning(v);
+      double d = 1;
+      v = cdf(dist, d);
+      suppress_unused_variable_warning(v);
+      v = cdf(complement(dist, d));
+      suppress_unused_variable_warning(v);
+      v = pdf(dist, d);
+      suppress_unused_variable_warning(v);
+      v = quantile(dist, d);
+      suppress_unused_variable_warning(v);
+      v = quantile(complement(dist, d));
+      suppress_unused_variable_warning(v);
+      v = hazard(dist, d);
+      suppress_unused_variable_warning(v);
+      v = chf(dist, d);
+      suppress_unused_variable_warning(v);
+#ifndef TEST_MPFR
+      long double ld = 1;
+      v = cdf(dist, ld);
+      suppress_unused_variable_warning(v);
+      v = cdf(complement(dist, ld));
+      suppress_unused_variable_warning(v);
+      v = pdf(dist, ld);
+      suppress_unused_variable_warning(v);
+      v = quantile(dist, ld);
+      suppress_unused_variable_warning(v);
+      v = quantile(complement(dist, ld));
+      suppress_unused_variable_warning(v);
+      v = hazard(dist, ld);
+      suppress_unused_variable_warning(v);
+      v = chf(dist, ld);
+      suppress_unused_variable_warning(v);
+#endif
+      int i = 1;
+      v = cdf(dist, i);
+      suppress_unused_variable_warning(v);
+      v = cdf(complement(dist, i));
+      suppress_unused_variable_warning(v);
+      v = pdf(dist, i);
+      suppress_unused_variable_warning(v);
+      v = quantile(dist, i);
+      suppress_unused_variable_warning(v);
+      v = quantile(complement(dist, i));
+      suppress_unused_variable_warning(v);
+      v = hazard(dist, i);
+      suppress_unused_variable_warning(v);
+      v = chf(dist, i);
+      suppress_unused_variable_warning(v);
+      unsigned long li = 1;
+      v = cdf(dist, li);
+      suppress_unused_variable_warning(v);
+      v = cdf(complement(dist, li));
+      suppress_unused_variable_warning(v);
+      v = pdf(dist, li);
+      suppress_unused_variable_warning(v);
+      v = quantile(dist, li);
+      suppress_unused_variable_warning(v);
+      v = quantile(complement(dist, li));
+      suppress_unused_variable_warning(v);
+      v = hazard(dist, li);
+      suppress_unused_variable_warning(v);
+      v = chf(dist, li);
+      suppress_unused_variable_warning(v);
+      test_extra_members(dist);
+   }
+   template <class D>
+   static void test_extra_members(const D&)
+   {}
+   template <class R, class P>
+   static void test_extra_members(const boost::math::bernoulli_distribution<R, P>& d)
+   {
+      value_type r = d.success_fraction();
+      (void)r; // warning suppression
+   }
+   template <class R, class P>
+   static void test_extra_members(const boost::math::beta_distribution<R, P>& d)
+   {
+      value_type r1 = d.alpha();
+      value_type r2 = d.beta();
+      r1 = boost::math::beta_distribution<R, P>::find_alpha(r1, r2);
+      suppress_unused_variable_warning(r1);
+      r1 = boost::math::beta_distribution<R, P>::find_beta(r1, r2);
+      suppress_unused_variable_warning(r1);
+      r1 = boost::math::beta_distribution<R, P>::find_alpha(r1, r2, r1);
+      suppress_unused_variable_warning(r1);
+      r1 = boost::math::beta_distribution<R, P>::find_beta(r1, r2, r1);
+      suppress_unused_variable_warning(r1);
+   }
+   template <class R, class P>
+   static void test_extra_members(const boost::math::binomial_distribution<R, P>& d)
+   {
+      value_type r = d.success_fraction();
+      r = d.trials();
+      r = Distribution::find_lower_bound_on_p(r, r, r);
+      r = Distribution::find_lower_bound_on_p(r, r, r, Distribution::clopper_pearson_exact_interval);
+      r = Distribution::find_lower_bound_on_p(r, r, r, Distribution::jeffreys_prior_interval);
+      r = Distribution::find_upper_bound_on_p(r, r, r);
+      r = Distribution::find_upper_bound_on_p(r, r, r, Distribution::clopper_pearson_exact_interval);
+      r = Distribution::find_upper_bound_on_p(r, r, r, Distribution::jeffreys_prior_interval);
+      r = Distribution::find_minimum_number_of_trials(r, r, r);
+      r = Distribution::find_maximum_number_of_trials(r, r, r);
+      suppress_unused_variable_warning(r);
+   }
+   template <class R, class P>
+   static void test_extra_members(const boost::math::cauchy_distribution<R, P>& d)
+   {
+      value_type r = d.location();
+      r = d.scale();
+      suppress_unused_variable_warning(r);
+   }
+   template <class R, class P>
+   static void test_extra_members(const boost::math::chi_squared_distribution<R, P>& d)
+   {
+      value_type r = d.degrees_of_freedom();
+      r = Distribution::find_degrees_of_freedom(r, r, r, r);
+      r = Distribution::find_degrees_of_freedom(r, r, r, r, r);
+      suppress_unused_variable_warning(r);
+   }
+   template <class R, class P>
+   static void test_extra_members(const boost::math::exponential_distribution<R, P>& d)
+   {
+      value_type r = d.lambda();
+      suppress_unused_variable_warning(r);
+   }
+   template <class R, class P>
+   static void test_extra_members(const boost::math::extreme_value_distribution<R, P>& d)
+   {
+      value_type r = d.scale();
+      r = d.location();
+      suppress_unused_variable_warning(r);
+   }
+   template <class R, class P>
+   static void test_extra_members(const boost::math::fisher_f_distribution<R, P>& d)
+   {
+      value_type r = d.degrees_of_freedom1();
+      r = d.degrees_of_freedom2();
+      suppress_unused_variable_warning(r);
+   }
+   template <class R, class P>
+   static void test_extra_members(const boost::math::gamma_distribution<R, P>& d)
+   {
+      value_type r = d.scale();
+      r = d.shape();
+      suppress_unused_variable_warning(r);
+   }
+   template <class R, class P>
+   static void test_extra_members(const boost::math::inverse_chi_squared_distribution<R, P>& d)
+   {
+      value_type r = d.scale();
+      r = d.degrees_of_freedom();
+      suppress_unused_variable_warning(r);
+   }
+   template <class R, class P>
+   static void test_extra_members(const boost::math::inverse_gamma_distribution<R, P>& d)
+   {
+      value_type r = d.scale();
+      r = d.shape();
+      suppress_unused_variable_warning(r);
+   }
+   template <class R, class P>
+   static void test_extra_members(const boost::math::hypergeometric_distribution<R, P>& d)
+   {
+      unsigned u = d.defective();
+      u = d.sample_count();
+      u = d.total();
+      suppress_unused_variable_warning(u);
+   }
+   template <class R, class P>
+   static void test_extra_members(const boost::math::laplace_distribution<R, P>& d)
+   {
+      value_type r = d.scale();
+      r = d.location();
+      suppress_unused_variable_warning(r);
+   }
+   template <class R, class P>
+   static void test_extra_members(const boost::math::logistic_distribution<R, P>& d)
+   {
+      value_type r = d.scale();
+      r = d.location();
+      suppress_unused_variable_warning(r);
+   }
+   template <class R, class P>
+   static void test_extra_members(const boost::math::lognormal_distribution<R, P>& d)
+   {
+      value_type r = d.scale();
+      r = d.location();
+      suppress_unused_variable_warning(r);
+   }
+   template <class R, class P>
+   static void test_extra_members(const boost::math::negative_binomial_distribution<R, P>& d)
+   {
+      value_type r = d.success_fraction();
+      r = d.successes();
+      r = Distribution::find_lower_bound_on_p(r, r, r);
+      r = Distribution::find_upper_bound_on_p(r, r, r);
+      r = Distribution::find_minimum_number_of_trials(r, r, r);
+      r = Distribution::find_maximum_number_of_trials(r, r, r);
+      suppress_unused_variable_warning(r);
+   }
+   template <class R, class P>
+   static void test_extra_members(const boost::math::non_central_beta_distribution<R, P>& d)
+   {
+      value_type r1 = d.alpha();
+      value_type r2 = d.beta();
+      r1 = d.non_centrality();
+      (void)r1; // warning suppression
+      (void)r2; // warning suppression
+   }
+   template <class R, class P>
+   static void test_extra_members(const boost::math::non_central_chi_squared_distribution<R, P>& d)
+   {
+      value_type r = d.degrees_of_freedom();
+      r = d.non_centrality();
+      r = Distribution::find_degrees_of_freedom(r, r, r);
+      r = Distribution::find_degrees_of_freedom(boost::math::complement(r, r, r));
+      r = Distribution::find_non_centrality(r, r, r);
+      r = Distribution::find_non_centrality(boost::math::complement(r, r, r));
+      (void)r; // warning suppression
+   }
+   template <class R, class P>
+   static void test_extra_members(const boost::math::non_central_f_distribution<R, P>& d)
+   {
+      value_type r = d.degrees_of_freedom1();
+      r = d.degrees_of_freedom2();
+      r = d.non_centrality();
+      (void)r; // warning suppression
+   }
+   template <class R, class P>
+   static void test_extra_members(const boost::math::non_central_t_distribution<R, P>& d)
+   {
+      value_type r = d.degrees_of_freedom();
+      r = d.non_centrality();
+      (void)r; // warning suppression
+   }
+   template <class R, class P>
+   static void test_extra_members(const boost::math::normal_distribution<R, P>& d)
+   {
+      value_type r = d.scale();
+      r = d.location();
+      r = d.mean();
+      r = d.standard_deviation();
+      (void)r; // warning suppression
+   }
+   template <class R, class P>
+   static void test_extra_members(const boost::math::pareto_distribution<R, P>& d)
+   {
+      value_type r = d.scale();
+      r = d.shape();
+      (void)r; // warning suppression
+   }
+   template <class R, class P>
+   static void test_extra_members(const boost::math::poisson_distribution<R, P>& d)
+   {
+      value_type r = d.mean();
+      (void)r; // warning suppression
+   }
+   template <class R, class P>
+   static void test_extra_members(const boost::math::rayleigh_distribution<R, P>& d)
+   {
+      value_type r = d.sigma();
+      (void)r; // warning suppression
+   }
+   template <class R, class P>
+   static void test_extra_members(const boost::math::students_t_distribution<R, P>& d)
+   {
+      value_type r = d.degrees_of_freedom();
+      r = d.find_degrees_of_freedom(r, r, r, r);
+      r = d.find_degrees_of_freedom(r, r, r, r, r);
+      (void)r; // warning suppression
+   }
+   template <class R, class P>
+   static void test_extra_members(const boost::math::triangular_distribution<R, P>& d)
+   {
+      value_type r = d.lower();
+      r = d.mode();
+      r = d.upper();
+      (void)r; // warning suppression
+   }
+   template <class R, class P>
+   static void test_extra_members(const boost::math::weibull_distribution<R, P>& d)
+   {
+      value_type r = d.scale();
+      r = d.shape();
+      (void)r; // warning suppression
+   }
+   template <class R, class P>
+   static void test_extra_members(const boost::math::uniform_distribution<R, P>& d)
+   {
+      value_type r = d.lower();
+      r = d.upper();
+      (void)r; // warning suppression
+   }
+private:
+   static Distribution* pd;
+   static Distribution& get_object()
+   {
+      // In reality this will never get called:
+      return *pd;
+   }
+}; // struct DistributionConcept
+
+template <class Distribution>
+Distribution* DistributionConcept<Distribution>::pd = 0;
+
+} // namespace concepts
+} // namespace math
+} // namespace boost
+
+#endif // BOOST_MATH_DISTRIBUTION_CONCEPT_HPP
+