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// (C) Copyright John Maddock 2007.
// 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)
#ifndef BOOST_MATH_OVERFLOW_ERROR_POLICY
#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
#endif
#include <boost/math/concepts/real_concept.hpp>
#define BOOST_TEST_MAIN
#include <boost/test/unit_test.hpp>
#include <boost/test/tools/floating_point_comparison.hpp>
#include <boost/math/distributions/non_central_beta.hpp>
#include <boost/math/distributions/poisson.hpp>
#include <boost/type_traits/is_floating_point.hpp>
#include <boost/array.hpp>
#include "functor.hpp"
#include "handle_test_result.hpp"
#include "table_type.hpp"
#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;\
}\
}
template <class T>
T nc_beta_cdf(T a, T b, T nc, T x)
{
#ifdef NC_BETA_CDF_FUNCTION_TO_TEST
return NC_BETA_CDF_FUNCTION_TO_TEST(a, b, nc, x);
#else
return cdf(boost::math::non_central_beta_distribution<T>(a, b, nc), x);
#endif
}
template <class T>
T nc_beta_ccdf(T a, T b, T nc, T x)
{
#ifdef NC_BETA_CCDF_FUNCTION_TO_TEST
return NC_BETA_CCDF_FUNCTION_TO_TEST(a, b, nc, x);
#else
return cdf(complement(boost::math::non_central_beta_distribution<T>(a, b, nc), x));
#endif
}
template <typename Real, typename T>
void do_test_nc_chi_squared(T& data, const char* type_name, const char* test)
{
typedef Real 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;
#if !(defined(ERROR_REPORTING_MODE) && !defined(NC_BETA_CDF_FUNCTION_TO_TEST))
result = boost::math::tools::test_hetero<Real>(
data,
bind_func<Real>(fp1, 0, 1, 2, 3),
extract_result<Real>(4));
handle_test_result(result, data[result.worst()], result.worst(),
type_name, "non central beta CDF", test);
#endif
#if !(defined(ERROR_REPORTING_MODE) && !defined(NC_BETA_CCDF_FUNCTION_TO_TEST))
fp1 = nc_beta_ccdf;
result = boost::math::tools::test_hetero<Real>(
data,
bind_func<Real>(fp1, 0, 1, 2, 3),
extract_result<Real>(5));
handle_test_result(result, data[result.worst()], result.worst(),
type_name, "non central beta CDF complement", test);
#endif
std::cout << std::endl;
}
template <typename Real, typename T>
void quantile_sanity_check(T& data, const char* type_name, const char* test)
{
#ifndef ERROR_REPORTING_MODE
typedef Real 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);
}
}
}
#endif
}
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<T>(ncbeta, type_name, "Non Central Beta, medium parameters");
quantile_sanity_check<T>(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<T>(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
}
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