| // This file is part of Eigen, a lightweight C++ template library | |
| // for linear algebra. | |
| // | |
| // Copyright (C) 2013 Christoph Hertzberg <chtz@informatik.uni-bremen.de> | |
| // | |
| // This Source Code Form is subject to the terms of the Mozilla | |
| // Public License v. 2.0. If a copy of the MPL was not distributed | |
| // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. | |
| #include "main.h" | |
| #include <unsupported/Eigen/AutoDiff> | |
| /* | |
| * In this file scalar derivations are tested for correctness. | |
| * TODO add more tests! | |
| */ | |
| template<typename Scalar> void check_atan2() | |
| { | |
| typedef Matrix<Scalar, 1, 1> Deriv1; | |
| typedef AutoDiffScalar<Deriv1> AD; | |
| AD x(internal::random<Scalar>(-3.0, 3.0), Deriv1::UnitX()); | |
| using std::exp; | |
| Scalar r = exp(internal::random<Scalar>(-10, 10)); | |
| AD s = sin(x), c = cos(x); | |
| AD res = atan2(r*s, r*c); | |
| VERIFY_IS_APPROX(res.value(), x.value()); | |
| VERIFY_IS_APPROX(res.derivatives(), x.derivatives()); | |
| res = atan2(r*s+0, r*c+0); | |
| VERIFY_IS_APPROX(res.value(), x.value()); | |
| VERIFY_IS_APPROX(res.derivatives(), x.derivatives()); | |
| } | |
| template<typename Scalar> void check_hyperbolic_functions() | |
| { | |
| using std::sinh; | |
| using std::cosh; | |
| using std::tanh; | |
| typedef Matrix<Scalar, 1, 1> Deriv1; | |
| typedef AutoDiffScalar<Deriv1> AD; | |
| Deriv1 p = Deriv1::Random(); | |
| AD val(p.x(),Deriv1::UnitX()); | |
| Scalar cosh_px = std::cosh(p.x()); | |
| AD res1 = tanh(val); | |
| VERIFY_IS_APPROX(res1.value(), std::tanh(p.x())); | |
| VERIFY_IS_APPROX(res1.derivatives().x(), Scalar(1.0) / (cosh_px * cosh_px)); | |
| AD res2 = sinh(val); | |
| VERIFY_IS_APPROX(res2.value(), std::sinh(p.x())); | |
| VERIFY_IS_APPROX(res2.derivatives().x(), cosh_px); | |
| AD res3 = cosh(val); | |
| VERIFY_IS_APPROX(res3.value(), cosh_px); | |
| VERIFY_IS_APPROX(res3.derivatives().x(), std::sinh(p.x())); | |
| // Check constant values. | |
| const Scalar sample_point = Scalar(1) / Scalar(3); | |
| val = AD(sample_point,Deriv1::UnitX()); | |
| res1 = tanh(val); | |
| VERIFY_IS_APPROX(res1.derivatives().x(), Scalar(0.896629559604914)); | |
| res2 = sinh(val); | |
| VERIFY_IS_APPROX(res2.derivatives().x(), Scalar(1.056071867829939)); | |
| res3 = cosh(val); | |
| VERIFY_IS_APPROX(res3.derivatives().x(), Scalar(0.339540557256150)); | |
| } | |
| template <typename Scalar> | |
| void check_limits_specialization() | |
| { | |
| typedef Eigen::Matrix<Scalar, 1, 1> Deriv; | |
| typedef Eigen::AutoDiffScalar<Deriv> AD; | |
| typedef std::numeric_limits<AD> A; | |
| typedef std::numeric_limits<Scalar> B; | |
| // workaround "unused typedef" warning: | |
| VERIFY(!bool(internal::is_same<B, A>::value)); | |
| #if EIGEN_HAS_CXX11 | |
| VERIFY(bool(std::is_base_of<B, A>::value)); | |
| #endif | |
| } | |
| EIGEN_DECLARE_TEST(autodiff_scalar) | |
| { | |
| for(int i = 0; i < g_repeat; i++) { | |
| CALL_SUBTEST_1( check_atan2<float>() ); | |
| CALL_SUBTEST_2( check_atan2<double>() ); | |
| CALL_SUBTEST_3( check_hyperbolic_functions<float>() ); | |
| CALL_SUBTEST_4( check_hyperbolic_functions<double>() ); | |
| CALL_SUBTEST_5( check_limits_specialization<double>()); | |
| } | |
| } |