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// 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* [])
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