| // 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)); |
| |
| VERIFY(bool(std::is_base_of<B, A>::value)); |
| } |
| |
| 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>()); |
| } |
| } |