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author | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-27 18:24:20 +0000 |
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committer | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-27 18:24:20 +0000 |
commit | 483eb2f56657e8e7f419ab1a4fab8dce9ade8609 (patch) | |
tree | e5d88d25d870d5dedacb6bbdbe2a966086a0a5cf /src/boost/libs/math/test/test_autodiff_5.cpp | |
parent | Initial commit. (diff) | |
download | ceph-upstream.tar.xz ceph-upstream.zip |
Adding upstream version 14.2.21.upstream/14.2.21upstream
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
Diffstat (limited to 'src/boost/libs/math/test/test_autodiff_5.cpp')
-rw-r--r-- | src/boost/libs/math/test/test_autodiff_5.cpp | 120 |
1 files changed, 120 insertions, 0 deletions
diff --git a/src/boost/libs/math/test/test_autodiff_5.cpp b/src/boost/libs/math/test/test_autodiff_5.cpp new file mode 100644 index 00000000..614630ca --- /dev/null +++ b/src/boost/libs/math/test/test_autodiff_5.cpp @@ -0,0 +1,120 @@ +// Copyright Matthew Pulver 2018 - 2019. +// Distributed under the Boost Software License, Version 1.0. +// (See accompanying file LICENSE_1_0.txt or copy at +// https://www.boost.org/LICENSE_1_0.txt) + +#include "test_autodiff.hpp" + +BOOST_AUTO_TEST_SUITE(test_autodiff_5) + +BOOST_AUTO_TEST_CASE_TEMPLATE(binomial_hpp, T, all_float_types) { + using boost::multiprecision::min; + using std::fabs; + using std::min; + + using test_constants = test_constants_t<T>; + static constexpr auto m = test_constants::order; + test_detail::RandomSample<unsigned> n_sampler{0u, 30u}; + test_detail::RandomSample<unsigned> r_sampler{0u, 30u}; + + for (auto i : boost::irange(test_constants::n_samples)) { + std::ignore = i; + auto n = n_sampler.next(); + auto r = n == 0 ? 0 : (min)(r_sampler.next(), n - 1); + + // This is a hard function to test for type float due to a specialization of + // boost::math::binomial_coefficient + auto autodiff_v = + std::is_same<T, float>::value + ? make_fvar<T, m>(boost::math::binomial_coefficient<T>(n, r)) + : boost::math::binomial_coefficient<T>(n, r); + auto anchor_v = boost::math::binomial_coefficient<T>(n, r); + BOOST_CHECK_EQUAL(autodiff_v.derivative(0u), anchor_v); + } +} + +BOOST_AUTO_TEST_CASE_TEMPLATE(cbrt_hpp, T, all_float_types) { + using test_constants = test_constants_t<T>; + static constexpr auto m = test_constants::order; + test_detail::RandomSample<T> x_sampler{-2000, 2000}; + for (auto i : boost::irange(test_constants::n_samples)) { + std::ignore = i; + auto x = x_sampler.next(); + BOOST_CHECK_CLOSE(boost::math::cbrt(make_fvar<T, m>(x)).derivative(0u), + boost::math::cbrt(x), 50 * test_constants::pct_epsilon()); + } +} + +BOOST_AUTO_TEST_CASE_TEMPLATE(chebyshev_hpp, T, all_float_types) { + using test_constants = test_constants_t<T>; + static constexpr auto m = test_constants::order; + { + test_detail::RandomSample<unsigned> n_sampler{0u, 10u}; + test_detail::RandomSample<T> x_sampler{-2, 2}; + for (auto i : boost::irange(test_constants::n_samples)) { + std::ignore = i; + auto n = n_sampler.next(); + auto x = x_sampler.next(); + BOOST_CHECK_CLOSE( + boost::math::chebyshev_t(n, make_fvar<T, m>(x)).derivative(0u), + boost::math::chebyshev_t(n, x), 40 * test_constants::pct_epsilon()); + + BOOST_CHECK_CLOSE( + boost::math::chebyshev_u(n, make_fvar<T, m>(x)).derivative(0u), + boost::math::chebyshev_u(n, x), 40 * test_constants::pct_epsilon()); + + BOOST_CHECK_CLOSE( + boost::math::chebyshev_t_prime(n, make_fvar<T, m>(x)).derivative(0u), + boost::math::chebyshev_t_prime(n, x), + 40 * test_constants::pct_epsilon()); + + /*/usr/include/boost/math/special_functions/chebyshev.hpp:164:40: error: + cannot convert + boost::math::differentiation::autodiff_v1::detail::fvar<double, 3> to + double in return + BOOST_CHECK_EQUAL(boost::math::chebyshev_clenshaw_recurrence(c.data(),c.size(),make_fvar<T,m>(0.20)) + , + boost::math::chebyshev_clenshaw_recurrence(c.data(),c.size(),static_cast<T>(0.20)));*/ + /*try { + std::array<T, 4> c0{{14.2, -13.7, 82.3, 96}}; + BOOST_CHECK_CLOSE(boost::math::chebyshev_clenshaw_recurrence(c0.data(), + c0.size(), make_fvar<T,m>(x)), + boost::math::chebyshev_clenshaw_recurrence(c0.data(), + c0.size(), x), 10*test_constants::pct_epsilon()); } catch (...) { + std::rethrow_exception(std::exception_ptr(std::current_exception())); + }*/ + } + } +} + +BOOST_AUTO_TEST_CASE_TEMPLATE(cospi_hpp, T, all_float_types) { + using test_constants = test_constants_t<T>; + static constexpr auto m = test_constants::order; + test_detail::RandomSample<T> x_sampler{-2000, 2000}; + for (auto i : boost::irange(test_constants::n_samples)) { + std::ignore = i; + auto x = x_sampler.next(); + BOOST_CHECK_CLOSE(boost::math::cos_pi(make_fvar<T, m>(x)).derivative(0u), + boost::math::cos_pi(x), test_constants::pct_epsilon()); + } +} + +BOOST_AUTO_TEST_CASE_TEMPLATE(digamma_hpp, T, all_float_types) { + + using boost::math::nextafter; + using std::nextafter; + + using test_constants = test_constants_t<T>; + static constexpr auto m = test_constants::order; + test_detail::RandomSample<T> x_sampler{-1, 2000}; + for (auto i : boost::irange(test_constants::n_samples)) { + std::ignore = i; + auto x = nextafter(x_sampler.next(), ((std::numeric_limits<T>::max))()); + auto autodiff_v = boost::math::digamma(make_fvar<T, m>(x)); + auto anchor_v = boost::math::digamma(x); + BOOST_CHECK_CLOSE(autodiff_v.derivative(0u), anchor_v, + 1e4 * test_constants::pct_epsilon()); + } +} + +BOOST_AUTO_TEST_SUITE_END() |