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📄 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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