| // test_nc_beta.cpp |
| |
| // Copyright John Maddock 2008. |
| |
| // 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) |
| |
| #include <pch.hpp> |
| |
| #ifdef _MSC_VER |
| #pragma warning (disable:4127 4512) |
| #endif |
| |
| #if !defined(TEST_FLOAT) && !defined(TEST_DOUBLE) && !defined(TEST_LDOUBLE) && !defined(TEST_REAL_CONCEPT) |
| # define TEST_FLOAT |
| # define TEST_DOUBLE |
| # define TEST_LDOUBLE |
| # define TEST_REAL_CONCEPT |
| #endif |
| |
| #include <boost/math/concepts/real_concept.hpp> // for real_concept |
| #include <boost/math/distributions/non_central_beta.hpp> // for chi_squared_distribution |
| #include <boost/math/distributions/poisson.hpp> // for chi_squared_distribution |
| #include <boost/test/test_exec_monitor.hpp> // for test_main |
| #include <boost/test/results_collector.hpp> |
| #include <boost/test/unit_test.hpp> |
| #include <boost/test/floating_point_comparison.hpp> // for BOOST_CHECK_CLOSE |
| |
| #include "functor.hpp" |
| #include "handle_test_result.hpp" |
| #include "test_ncbeta_hooks.hpp" |
| |
| #include <iostream> |
| using std::cout; |
| using std::endl; |
| #include <limits> |
| using std::numeric_limits; |
| |
| #define BOOST_CHECK_CLOSE_EX(a, b, prec, i) \ |
| {\ |
| unsigned int failures = boost::unit_test::results_collector.results( boost::unit_test::framework::current_test_case().p_id ).p_assertions_failed;\ |
| BOOST_CHECK_CLOSE(a, b, prec); \ |
| if(failures != boost::unit_test::results_collector.results( boost::unit_test::framework::current_test_case().p_id ).p_assertions_failed)\ |
| {\ |
| std::cerr << "Failure was at row " << i << std::endl;\ |
| std::cerr << std::setprecision(35); \ |
| std::cerr << "{ " << data[i][0] << " , " << data[i][1] << " , " << data[i][2];\ |
| std::cerr << " , " << data[i][3] << " , " << data[i][4] << " } " << std::endl;\ |
| }\ |
| } |
| |
| #define BOOST_CHECK_EX(a, i) \ |
| {\ |
| unsigned int failures = boost::unit_test::results_collector.results( boost::unit_test::framework::current_test_case().p_id ).p_assertions_failed;\ |
| BOOST_CHECK(a); \ |
| if(failures != boost::unit_test::results_collector.results( boost::unit_test::framework::current_test_case().p_id ).p_assertions_failed)\ |
| {\ |
| std::cerr << "Failure was at row " << i << std::endl;\ |
| std::cerr << std::setprecision(35); \ |
| std::cerr << "{ " << data[i][0] << " , " << data[i][1] << " , " << data[i][2];\ |
| std::cerr << " , " << data[i][3] << " , " << data[i][4] << " } " << std::endl;\ |
| }\ |
| } |
| |
| void expected_results() |
| { |
| // |
| // Define the max and mean errors expected for |
| // various compilers and platforms. |
| // |
| const char* largest_type; |
| #ifndef BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS |
| if(boost::math::policies::digits<double, boost::math::policies::policy<> >() == boost::math::policies::digits<long double, boost::math::policies::policy<> >()) |
| { |
| largest_type = "(long\\s+)?double|real_concept"; |
| } |
| else |
| { |
| largest_type = "long double|real_concept"; |
| } |
| #else |
| largest_type = "(long\\s+)?double|real_concept"; |
| #endif |
| |
| #ifndef BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS |
| if(boost::math::tools::digits<long double>() == 64) |
| { |
| // |
| // Allow a small amount of error leakage from long double to double: |
| // |
| add_expected_result( |
| "[^|]*", // compiler |
| "[^|]*", // stdlib |
| "[^|]*", // platform |
| "double", // test type(s) |
| "[^|]*large[^|]*", // test data group |
| "[^|]*", 5, 5); // test function |
| } |
| |
| if(boost::math::tools::digits<long double>() == 64) |
| { |
| add_expected_result( |
| "[^|]*", // compiler |
| "[^|]*", // stdlib |
| "[^|]*", // platform |
| largest_type, // test type(s) |
| "[^|]*medium[^|]*", // test data group |
| "[^|]*", 1200, 500); // test function |
| add_expected_result( |
| "[^|]*", // compiler |
| "[^|]*", // stdlib |
| "[^|]*", // platform |
| largest_type, // test type(s) |
| "[^|]*large[^|]*", // test data group |
| "[^|]*", 40000, 6000); // test function |
| } |
| #endif |
| // |
| // Catch all cases come last: |
| // |
| add_expected_result( |
| "[^|]*", // compiler |
| "[^|]*", // stdlib |
| "[^|]*", // platform |
| largest_type, // test type(s) |
| "[^|]*medium[^|]*", // test data group |
| "[^|]*", 700, 500); // test function |
| add_expected_result( |
| "[^|]*", // compiler |
| "[^|]*", // stdlib |
| "[^|]*", // platform |
| "real_concept", // test type(s) |
| "[^|]*large[^|]*", // test data group |
| "[^|]*", 30000, 4000); // test function |
| add_expected_result( |
| "[^|]*", // compiler |
| "[^|]*", // stdlib |
| "[^|]*", // platform |
| largest_type, // test type(s) |
| "[^|]*large[^|]*", // test data group |
| "[^|]*", 20000, 2000); // test function |
| // |
| // Finish off by printing out the compiler/stdlib/platform names, |
| // we do this to make it easier to mark up expected error rates. |
| // |
| std::cout << "Tests run with " << BOOST_COMPILER << ", " |
| << BOOST_STDLIB << ", " << BOOST_PLATFORM << std::endl; |
| } |
| |
| template <class RealType> |
| RealType naive_pdf(RealType a, RealType b, RealType lam, RealType x) |
| { |
| using namespace boost::math; |
| |
| RealType term = pdf(poisson_distribution<RealType>(lam/2), 0) |
| * ibeta_derivative(a, b, x); |
| RealType sum = term; |
| |
| int i = 1; |
| while(term / sum > tools::epsilon<RealType>()) |
| { |
| term = pdf(poisson_distribution<RealType>(lam/2), i) |
| * ibeta_derivative(a + i, b, x); |
| ++i; |
| sum += term; |
| } |
| return sum; |
| } |
| |
| template <class RealType> |
| void test_spot( |
| RealType a, // alpha |
| RealType b, // beta |
| RealType ncp, // non-centrality param |
| RealType cs, // Chi Square statistic |
| RealType P, // CDF |
| RealType Q, // Complement of CDF |
| RealType D, // PDF |
| RealType tol) // Test tolerance |
| { |
| boost::math::non_central_beta_distribution<RealType> dist(a, b, ncp); |
| BOOST_CHECK_CLOSE( |
| cdf(dist, cs), P, tol); |
| // |
| // Sanity checking using the naive PDF calculation above fails at |
| // float precision: |
| // |
| if(!boost::is_same<float, RealType>::value) |
| { |
| BOOST_CHECK_CLOSE( |
| pdf(dist, cs), naive_pdf(dist.alpha(), dist.beta(), ncp, cs), tol); |
| } |
| BOOST_CHECK_CLOSE( |
| pdf(dist, cs), D, tol); |
| |
| if((P < 0.99) && (Q < 0.99)) |
| { |
| // |
| // We can only check this if P is not too close to 1, |
| // so that we can guarentee Q is reasonably free of error: |
| // |
| BOOST_CHECK_CLOSE( |
| cdf(complement(dist, cs)), Q, tol); |
| BOOST_CHECK_CLOSE( |
| quantile(dist, P), cs, tol * 10); |
| BOOST_CHECK_CLOSE( |
| quantile(complement(dist, Q)), cs, tol * 10); |
| } |
| } |
| |
| template <class RealType> // Any floating-point type RealType. |
| void test_spots(RealType) |
| { |
| RealType tolerance = (std::max)( |
| boost::math::tools::epsilon<RealType>() * 100, |
| (RealType)1e-6) * 100; |
| |
| cout << "Tolerance = " << tolerance << "%." << endl; |
| |
| // |
| // Spot tests use values computed by the R statistical |
| // package and the pbeta and dbeta functions: |
| // |
| test_spot( |
| RealType(2), // alpha |
| RealType(5), // beta |
| RealType(1), // non-centrality param |
| RealType(0.25), // Chi Square statistic |
| RealType(0.3658349), // CDF |
| RealType(1-0.3658349), // Complement of CDF |
| RealType(2.184465), // PDF |
| RealType(tolerance)); |
| test_spot( |
| RealType(20), // alpha |
| RealType(15), // beta |
| RealType(35), // non-centrality param |
| RealType(0.75), // Chi Square statistic |
| RealType(0.6994175), // CDF |
| RealType(1-0.6994175), // Complement of CDF |
| RealType(5.576146), // PDF |
| RealType(tolerance)); |
| test_spot( |
| RealType(100), // alpha |
| RealType(3), // beta |
| RealType(63), // non-centrality param |
| RealType(0.95), // Chi Square statistic |
| RealType(0.03529306), // CDF |
| RealType(1-0.03529306), // Complement of CDF |
| RealType(3.637894), // PDF |
| RealType(tolerance)); |
| test_spot( |
| RealType(0.25), // alpha |
| RealType(0.75), // beta |
| RealType(150), // non-centrality param |
| RealType(0.975), // Chi Square statistic |
| RealType(0.09752216), // CDF |
| RealType(1-0.09752216), // Complement of CDF |
| RealType(8.020935), // PDF |
| RealType(tolerance)); |
| |
| } // template <class RealType>void test_spots(RealType) |
| |
| template <class T> |
| T nc_beta_cdf(T a, T b, T nc, T x) |
| { |
| return cdf(boost::math::non_central_beta_distribution<T>(a, b, nc), x); |
| } |
| |
| template <class T> |
| T nc_beta_ccdf(T a, T b, T nc, T x) |
| { |
| return cdf(complement(boost::math::non_central_beta_distribution<T>(a, b, nc), x)); |
| } |
| |
| template <typename T> |
| void do_test_nc_chi_squared(T& data, const char* type_name, const char* test) |
| { |
| typedef typename T::value_type row_type; |
| typedef typename row_type::value_type value_type; |
| |
| std::cout << "Testing: " << test << std::endl; |
| |
| value_type (*fp1)(value_type, value_type, value_type, value_type) = nc_beta_cdf; |
| boost::math::tools::test_result<value_type> result; |
| |
| result = boost::math::tools::test( |
| data, |
| bind_func(fp1, 0, 1, 2, 3), |
| extract_result(4)); |
| handle_test_result(result, data[result.worst()], result.worst(), |
| type_name, "CDF", test); |
| |
| fp1 = nc_beta_ccdf; |
| result = boost::math::tools::test( |
| data, |
| bind_func(fp1, 0, 1, 2, 3), |
| extract_result(5)); |
| handle_test_result(result, data[result.worst()], result.worst(), |
| type_name, "CCDF", test); |
| |
| #ifdef TEST_OTHER |
| fp1 = other::ncbeta_cdf; |
| result = boost::math::tools::test( |
| data, |
| bind_func(fp1, 0, 1, 2, 3), |
| extract_result(4)); |
| handle_test_result(result, data[result.worst()], result.worst(), |
| type_name, "Other::CDF", test); |
| #endif |
| std::cout << std::endl; |
| |
| } |
| |
| template <typename T> |
| void quantile_sanity_check(T& data, const char* type_name, const char* test) |
| { |
| typedef typename T::value_type row_type; |
| typedef typename row_type::value_type value_type; |
| |
| // |
| // Tests with type real_concept take rather too long to run, so |
| // for now we'll disable them: |
| // |
| if(!boost::is_floating_point<value_type>::value) |
| return; |
| |
| std::cout << "Testing: " << type_name << " quantile sanity check, with tests " << test << std::endl; |
| |
| // |
| // These sanity checks test for a round trip accuracy of one half |
| // of the bits in T, unless T is type float, in which case we check |
| // for just one decimal digit. The problem here is the sensitivity |
| // of the functions, not their accuracy. This test data was generated |
| // for the forward functions, which means that when it is used as |
| // the input to the inverses then it is necessarily inexact. This rounding |
| // of the input is what makes the data unsuitable for use as an accuracy check, |
| // and also demonstrates that you can't in general round-trip these functions. |
| // It is however a useful sanity check. |
| // |
| value_type precision = static_cast<value_type>(ldexp(1.0, 1-boost::math::policies::digits<value_type, boost::math::policies::policy<> >()/2)) * 100; |
| if(boost::math::policies::digits<value_type, boost::math::policies::policy<> >() < 50) |
| precision = 1; // 1% or two decimal digits, all we can hope for when the input is truncated to float |
| |
| for(unsigned i = 0; i < data.size(); ++i) |
| { |
| // |
| // Test case 493 fails at float precision: not enough bits to get |
| // us back where we started: |
| // |
| if((i == 493) && boost::is_same<float, value_type>::value) |
| continue; |
| |
| if(data[i][4] == 0) |
| { |
| BOOST_CHECK(0 == quantile(boost::math::non_central_beta_distribution<value_type>(data[i][0], data[i][1], data[i][2]), data[i][4])); |
| } |
| else if(data[i][4] < 0.9999f) |
| { |
| value_type p = quantile(boost::math::non_central_beta_distribution<value_type>(data[i][0], data[i][1], data[i][2]), data[i][4]); |
| value_type pt = data[i][3]; |
| BOOST_CHECK_CLOSE_EX(pt, p, precision, i); |
| } |
| if(data[i][5] == 0) |
| { |
| BOOST_CHECK(1 == quantile(complement(boost::math::non_central_beta_distribution<value_type>(data[i][0], data[i][1], data[i][2]), data[i][5]))); |
| } |
| else if(data[i][5] < 0.9999f) |
| { |
| value_type p = quantile(complement(boost::math::non_central_beta_distribution<value_type>(data[i][0], data[i][1], data[i][2]), data[i][5])); |
| value_type pt = data[i][3]; |
| BOOST_CHECK_CLOSE_EX(pt, p, precision, i); |
| } |
| if(boost::math::tools::digits<value_type>() > 50) |
| { |
| // |
| // Sanity check mode, accuracy of |
| // the mode is at *best* the square root of the accuracy of the PDF: |
| // |
| value_type m = mode(boost::math::non_central_beta_distribution<value_type>(data[i][0], data[i][1], data[i][2])); |
| if((m == 1) || (m == 0)) |
| break; |
| value_type p = pdf(boost::math::non_central_beta_distribution<value_type>(data[i][0], data[i][1], data[i][2]), m); |
| if(m * (1 + sqrt(precision) * 10) < 1) |
| { |
| BOOST_CHECK_EX(pdf(boost::math::non_central_beta_distribution<value_type>(data[i][0], data[i][1], data[i][2]), m * (1 + sqrt(precision) * 10)) <= p, i); |
| } |
| if(m * (1 - sqrt(precision)) * 10 > boost::math::tools::min_value<value_type>()) |
| { |
| BOOST_CHECK_EX(pdf(boost::math::non_central_beta_distribution<value_type>(data[i][0], data[i][1], data[i][2]), m * (1 - sqrt(precision)) * 10) <= p, i); |
| } |
| } |
| } |
| } |
| |
| template <typename T> |
| void test_accuracy(T, const char* type_name) |
| { |
| #if !defined(TEST_DATA) || (TEST_DATA == 1) |
| #include "ncbeta.ipp" |
| do_test_nc_chi_squared(ncbeta, type_name, "Non Central Beta, medium parameters"); |
| quantile_sanity_check(ncbeta, type_name, "Non Central Beta, medium parameters"); |
| #endif |
| #if !defined(TEST_DATA) || (TEST_DATA == 2) |
| #include "ncbeta_big.ipp" |
| do_test_nc_chi_squared(ncbeta_big, type_name, "Non Central Beta, large parameters"); |
| // Takes too long to run: |
| // quantile_sanity_check(ncbeta_big, type_name, "Non Central Beta, large parameters"); |
| #endif |
| } |
| |
| int test_main(int, char* []) |
| { |
| BOOST_MATH_CONTROL_FP; |
| // Basic sanity-check spot values. |
| expected_results(); |
| // (Parameter value, arbitrarily zero, only communicates the floating point type). |
| #ifdef TEST_FLOAT |
| test_spots(0.0F); // Test float. |
| #endif |
| #ifdef TEST_DOUBLE |
| test_spots(0.0); // Test double. |
| #endif |
| #ifndef BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS |
| #ifdef TEST_LDOUBLE |
| test_spots(0.0L); // Test long double. |
| #endif |
| #if !BOOST_WORKAROUND(__BORLANDC__, BOOST_TESTED_AT(0x582)) |
| #ifdef TEST_REAL_CONCEPT |
| test_spots(boost::math::concepts::real_concept(0.)); // Test real concept. |
| #endif |
| #endif |
| #endif |
| |
| #ifdef TEST_FLOAT |
| test_accuracy(0.0F, "float"); // Test float. |
| #endif |
| #ifdef TEST_DOUBLE |
| test_accuracy(0.0, "double"); // Test double. |
| #endif |
| #ifndef BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS |
| #ifdef TEST_LDOUBLE |
| test_accuracy(0.0L, "long double"); // Test long double. |
| #endif |
| #if !BOOST_WORKAROUND(__BORLANDC__, BOOST_TESTED_AT(0x582)) |
| #ifdef TEST_REAL_CONCEPT |
| test_accuracy(boost::math::concepts::real_concept(0.), "real_concept"); // Test real concept. |
| #endif |
| #endif |
| #endif |
| return 0; |
| } // int test_main(int, char* []) |
| |
