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- // 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_4)
- BOOST_AUTO_TEST_CASE_TEMPLATE(lround_llround_lltrunc_truncl, T,
- all_float_types) {
- using boost::math::llround;
- using boost::math::lltrunc;
- using boost::math::lround;
- using boost::multiprecision::llround;
- using boost::multiprecision::lltrunc;
- using boost::multiprecision::lround;
- using detail::llround;
- using detail::lltrunc;
- using detail::lround;
- using detail::truncl;
- using std::truncl;
- constexpr std::size_t m = 3;
- const auto &cx = static_cast<T>(3.25);
- auto x = make_fvar<T, m>(cx);
- auto yl = lround(x);
- BOOST_CHECK_EQUAL(yl, lround(cx));
- auto yll = llround(x);
- BOOST_CHECK_EQUAL(yll, llround(cx));
- BOOST_CHECK_EQUAL(lltrunc(cx), lltrunc(x));
- #ifndef BOOST_NO_CXX17_IF_CONSTEXPR
- if constexpr (!bmp::is_number<T>::value &&
- !bmp::is_number_expression<T>::value) {
- BOOST_CHECK_EQUAL(truncl(x), truncl(cx));
- }
- #endif
- }
- BOOST_AUTO_TEST_CASE_TEMPLATE(equality, T, all_float_types) {
- BOOST_MATH_STD_USING
- using boost::math::epsilon_difference;
- using boost::math::fpclassify;
- using boost::math::ulp;
- using std::fpclassify;
- constexpr std::size_t m = 3;
- // check zeros
- {
- auto x = make_fvar<T, m>(0.0);
- auto y = T(-0.0);
- BOOST_CHECK_EQUAL(x.derivative(0u), y);
- }
- }
- #if defined(BOOST_AUTODIFF_TESTING_INCLUDE_MULTIPRECISION)
- BOOST_AUTO_TEST_CASE_TEMPLATE(multiprecision, T, multiprecision_float_types) {
- using boost::multiprecision::fabs;
- using detail::fabs;
- using std::fabs;
- const T eps = 3000 * std::numeric_limits<T>::epsilon();
- constexpr std::size_t Nw = 3;
- constexpr std::size_t Nx = 2;
- constexpr std::size_t Ny = 4;
- constexpr std::size_t Nz = 3;
- const auto w = make_fvar<T, Nw>(11);
- const auto x = make_fvar<T, 0, Nx>(12);
- const auto y = make_fvar<T, 0, 0, Ny>(13);
- const auto z = make_fvar<T, 0, 0, 0, Nz>(14);
- const auto v =
- mixed_partials_f(w, x, y, z); // auto = autodiff_fvar<T,Nw,Nx,Ny,Nz>
- // Calculated from Mathematica symbolic differentiation.
- const T answer = boost::lexical_cast<T>(
- "1976.3196007477977177798818752904187209081211892187"
- "5499076582535951111845769110560421820940516423255314");
- // BOOST_CHECK_CLOSE(v.derivative(Nw,Nx,Ny,Nz), answer, eps); // Doesn't work
- // for cpp_dec_float
- const T relative_error =
- static_cast<T>(fabs(v.derivative(Nw, Nx, Ny, Nz) / answer - 1));
- BOOST_CHECK_LT(relative_error, eps);
- }
- #endif
- BOOST_AUTO_TEST_CASE_TEMPLATE(acosh_hpp, T, all_float_types) {
- using boost::math::acosh;
- using test_constants = test_constants_t<T>;
- static constexpr auto m = test_constants::order;
- test_detail::RandomSample<T> x_sampler{1, 100};
- for (auto i : boost::irange(test_constants::n_samples)) {
- std::ignore = i;
- auto x = x_sampler.next();
- auto autodiff_v = acosh(make_fvar<T, m>(x));
- auto anchor_v = acosh(x);
- BOOST_CHECK_CLOSE(autodiff_v.derivative(0u), anchor_v,
- 1e3 * test_constants::pct_epsilon());
- }
- }
- BOOST_AUTO_TEST_CASE_TEMPLATE(asinh_hpp, T, all_float_types) {
- using boost::math::asinh;
- using test_constants = test_constants_t<T>;
- static constexpr auto m = test_constants::order;
- test_detail::RandomSample<T> x_sampler{-100, 100};
- for (auto i : boost::irange(test_constants::n_samples)) {
- std::ignore = i;
- auto x = x_sampler.next();
- auto autodiff_v = asinh(make_fvar<T, m>(x));
- auto anchor_v = asinh(x);
- BOOST_CHECK_CLOSE(autodiff_v.derivative(0u), anchor_v,
- 1e3 * test_constants::pct_epsilon());
- }
- }
- BOOST_AUTO_TEST_CASE_TEMPLATE(atanh_hpp, T, all_float_types) {
- using boost::math::nextafter;
- using std::nextafter;
- using boost::math::atanh;
- using test_constants = test_constants_t<T>;
- static constexpr auto m = test_constants::order;
- test_detail::RandomSample<T> x_sampler{-1, 1};
- for (auto i : boost::irange(test_constants::n_samples)) {
- std::ignore = i;
- auto x = nextafter(x_sampler.next(), T(0));
- auto autodiff_v = atanh(make_fvar<T, m>(x));
- auto anchor_v = atanh(x);
- BOOST_CHECK_CLOSE(autodiff_v.derivative(0u), anchor_v,
- 1e3 * test_constants::pct_epsilon());
- }
- }
- BOOST_AUTO_TEST_CASE_TEMPLATE(atan_hpp, T, all_float_types) {
- using boost::math::float_prior;
- using boost::math::fpclassify;
- using boost::math::signbit;
- using boost::math::differentiation::detail::atan;
- using boost::multiprecision::atan;
- using boost::multiprecision::fabs;
- using boost::multiprecision::fpclassify;
- using boost::multiprecision::signbit;
- using detail::fabs;
- using std::atan;
- using std::fabs;
- using test_constants = test_constants_t<T>;
- static constexpr auto m = test_constants::order;
- test_detail::RandomSample<T> x_sampler{-1, 1};
- for (auto i : boost::irange(test_constants::n_samples)) {
- std::ignore = i;
- auto x = T(1);
- while (fpclassify(T(fabs(x) - 1)) == FP_ZERO) {
- x = x_sampler.next();
- }
- auto autodiff_v = atan(make_fvar<T, m>(x));
- auto anchor_v = atan(x);
- BOOST_CHECK_CLOSE(autodiff_v.derivative(0u), anchor_v,
- 1e3 * test_constants::pct_epsilon());
- }
- }
- BOOST_AUTO_TEST_CASE_TEMPLATE(bernoulli_hpp, T, all_float_types) {
- using boost::multiprecision::min;
- using std::min;
- using test_constants = test_constants_t<T>;
- static constexpr auto m = test_constants::order;
- for (auto i : boost::irange(test_constants::n_samples)) {
- {
- auto autodiff_v = boost::math::bernoulli_b2n<autodiff_fvar<T, m>>(i);
- auto anchor_v = boost::math::bernoulli_b2n<T>(i);
- BOOST_CHECK_CLOSE(autodiff_v.derivative(0u), anchor_v,
- 50 * test_constants::pct_epsilon());
- }
- {
- auto i_ = (min)(19, i);
- auto autodiff_v = boost::math::tangent_t2n<autodiff_fvar<T, m>>(i_);
- auto anchor_v = boost::math::tangent_t2n<T>(i_);
- BOOST_CHECK_CLOSE(autodiff_v.derivative(0u), anchor_v,
- 50 * test_constants::pct_epsilon());
- }
- }
- }
- BOOST_AUTO_TEST_SUITE_END()
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