// 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 #ifndef BOOST_MATH_STANDALONE #include #include #ifdef _MSC_VER #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 #ifdef _MSC_VER #pragma warning(pop) #endif #include namespace boost{ namespace math{ namespace concepts { // Begin by defining a concept archetype // for a distribution class: // template 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(0); } }; // template class distribution_archetype // Non-member accessor functions: // (This list defines the functions that must be implemented by all distributions). template RealType pdf(const distribution_archetype& dist, const RealType& x); template RealType cdf(const distribution_archetype& dist, const RealType& x); template RealType quantile(const distribution_archetype& dist, const RealType& p); template RealType cdf(const complemented2_type, RealType>& c); template RealType quantile(const complemented2_type, RealType>& c); template RealType mean(const distribution_archetype& dist); template RealType standard_deviation(const distribution_archetype& dist); template RealType variance(const distribution_archetype& dist); template RealType hazard(const distribution_archetype& dist); template RealType chf(const distribution_archetype& dist); // http://en.wikipedia.org/wiki/Characteristic_function_%28probability_theory%29 template RealType coefficient_of_variation(const distribution_archetype& dist); template RealType mode(const distribution_archetype& dist); template RealType skewness(const distribution_archetype& dist); template RealType kurtosis_excess(const distribution_archetype& dist); template RealType kurtosis(const distribution_archetype& dist); template RealType median(const distribution_archetype& dist); template std::pair range(const distribution_archetype& dist); template std::pair support(const distribution_archetype& dist); // // Next comes the concept checks for verifying that a class // fulfils the requirements of a Distribution: // template struct DistributionConcept { typedef typename Distribution::value_type value_type; void constraints() { function_requires >(); function_requires >(); const Distribution& dist = DistributionConcept::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 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 static void test_extra_members(const D&) {} template static void test_extra_members(const boost::math::bernoulli_distribution& d) { value_type r = d.success_fraction(); (void)r; // warning suppression } template static void test_extra_members(const boost::math::beta_distribution& d) { value_type r1 = d.alpha(); value_type r2 = d.beta(); r1 = boost::math::beta_distribution::find_alpha(r1, r2); suppress_unused_variable_warning(r1); r1 = boost::math::beta_distribution::find_beta(r1, r2); suppress_unused_variable_warning(r1); r1 = boost::math::beta_distribution::find_alpha(r1, r2, r1); suppress_unused_variable_warning(r1); r1 = boost::math::beta_distribution::find_beta(r1, r2, r1); suppress_unused_variable_warning(r1); } template static void test_extra_members(const boost::math::binomial_distribution& 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 static void test_extra_members(const boost::math::cauchy_distribution& d) { value_type r = d.location(); r = d.scale(); suppress_unused_variable_warning(r); } template static void test_extra_members(const boost::math::chi_squared_distribution& 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 static void test_extra_members(const boost::math::exponential_distribution& d) { value_type r = d.lambda(); suppress_unused_variable_warning(r); } template static void test_extra_members(const boost::math::extreme_value_distribution& d) { value_type r = d.scale(); r = d.location(); suppress_unused_variable_warning(r); } template static void test_extra_members(const boost::math::fisher_f_distribution& d) { value_type r = d.degrees_of_freedom1(); r = d.degrees_of_freedom2(); suppress_unused_variable_warning(r); } template static void test_extra_members(const boost::math::gamma_distribution& d) { value_type r = d.scale(); r = d.shape(); suppress_unused_variable_warning(r); } template static void test_extra_members(const boost::math::inverse_chi_squared_distribution& d) { value_type r = d.scale(); r = d.degrees_of_freedom(); suppress_unused_variable_warning(r); } template static void test_extra_members(const boost::math::inverse_gamma_distribution& d) { value_type r = d.scale(); r = d.shape(); suppress_unused_variable_warning(r); } template static void test_extra_members(const boost::math::hypergeometric_distribution& d) { unsigned u = d.defective(); u = d.sample_count(); u = d.total(); suppress_unused_variable_warning(u); } template static void test_extra_members(const boost::math::laplace_distribution& d) { value_type r = d.scale(); r = d.location(); suppress_unused_variable_warning(r); } template static void test_extra_members(const boost::math::logistic_distribution& d) { value_type r = d.scale(); r = d.location(); suppress_unused_variable_warning(r); } template static void test_extra_members(const boost::math::lognormal_distribution& d) { value_type r = d.scale(); r = d.location(); suppress_unused_variable_warning(r); } template static void test_extra_members(const boost::math::negative_binomial_distribution& 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 static void test_extra_members(const boost::math::non_central_beta_distribution& d) { value_type r1 = d.alpha(); value_type r2 = d.beta(); r1 = d.non_centrality(); (void)r1; // warning suppression (void)r2; // warning suppression } template static void test_extra_members(const boost::math::non_central_chi_squared_distribution& 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 static void test_extra_members(const boost::math::non_central_f_distribution& d) { value_type r = d.degrees_of_freedom1(); r = d.degrees_of_freedom2(); r = d.non_centrality(); (void)r; // warning suppression } template static void test_extra_members(const boost::math::non_central_t_distribution& d) { value_type r = d.degrees_of_freedom(); r = d.non_centrality(); (void)r; // warning suppression } template static void test_extra_members(const boost::math::normal_distribution& d) { value_type r = d.scale(); r = d.location(); r = d.mean(); r = d.standard_deviation(); (void)r; // warning suppression } template static void test_extra_members(const boost::math::pareto_distribution& d) { value_type r = d.scale(); r = d.shape(); (void)r; // warning suppression } template static void test_extra_members(const boost::math::poisson_distribution& d) { value_type r = d.mean(); (void)r; // warning suppression } template static void test_extra_members(const boost::math::rayleigh_distribution& d) { value_type r = d.sigma(); (void)r; // warning suppression } template static void test_extra_members(const boost::math::students_t_distribution& 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 static void test_extra_members(const boost::math::triangular_distribution& d) { value_type r = d.lower(); r = d.mode(); r = d.upper(); (void)r; // warning suppression } template static void test_extra_members(const boost::math::weibull_distribution& d) { value_type r = d.scale(); r = d.shape(); (void)r; // warning suppression } template static void test_extra_members(const boost::math::uniform_distribution& 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 Distribution* DistributionConcept::pd = 0; } // namespace concepts } // namespace math } // namespace boost #else #error This header can not be used in standalone mode. #endif // BOOST_MATH_STANDALONE #endif // BOOST_MATH_DISTRIBUTION_CONCEPT_HPP