📄 test_nc_beta.cpp
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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){#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");#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");}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* [])
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