| // This file is part of Eigen, a lightweight C++ template library |
| // for linear algebra. |
| // |
| // Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com> |
| // |
| // 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 <Eigen/CXX11/Tensor> |
| |
| using Eigen::Tensor; |
| using Eigen::TensorMap; |
| |
| static void test_additions() { |
| Tensor<std::complex<float>, 1> data1(3); |
| Tensor<std::complex<float>, 1> data2(3); |
| for (int i = 0; i < 3; ++i) { |
| data1(i) = std::complex<float>(i, -i); |
| data2(i) = std::complex<float>(i, 7 * i); |
| } |
| |
| Tensor<std::complex<float>, 1> sum = data1 + data2; |
| for (int i = 0; i < 3; ++i) { |
| VERIFY_IS_EQUAL(sum(i), std::complex<float>(2 * i, 6 * i)); |
| } |
| } |
| |
| static void test_abs() { |
| Tensor<std::complex<float>, 1> data1(3); |
| Tensor<std::complex<double>, 1> data2(3); |
| data1.setRandom(); |
| data2.setRandom(); |
| |
| Tensor<float, 1> abs1 = data1.abs(); |
| Tensor<double, 1> abs2 = data2.abs(); |
| for (int i = 0; i < 3; ++i) { |
| VERIFY_IS_APPROX(abs1(i), std::abs(data1(i))); |
| VERIFY_IS_APPROX(abs2(i), std::abs(data2(i))); |
| } |
| } |
| |
| static void test_arg() { |
| Tensor<std::complex<float>, 1> data1(3); |
| Tensor<std::complex<double>, 1> data2(3); |
| data1.setRandom(); |
| data2.setRandom(); |
| |
| Tensor<float, 1> arg1 = data1.arg(); |
| Tensor<double, 1> arg2 = data2.arg(); |
| for (int i = 0; i < 3; ++i) { |
| VERIFY_IS_APPROX(arg1(i), std::arg(data1(i))); |
| VERIFY_IS_APPROX(arg2(i), std::arg(data2(i))); |
| } |
| } |
| |
| static void test_conjugate() { |
| Tensor<std::complex<float>, 1> data1(3); |
| Tensor<std::complex<double>, 1> data2(3); |
| Tensor<int, 1> data3(3); |
| data1.setRandom(); |
| data2.setRandom(); |
| data3.setRandom(); |
| |
| Tensor<std::complex<float>, 1> conj1 = data1.conjugate(); |
| Tensor<std::complex<double>, 1> conj2 = data2.conjugate(); |
| Tensor<int, 1> conj3 = data3.conjugate(); |
| for (int i = 0; i < 3; ++i) { |
| VERIFY_IS_APPROX(conj1(i), std::conj(data1(i))); |
| VERIFY_IS_APPROX(conj2(i), std::conj(data2(i))); |
| VERIFY_IS_APPROX(conj3(i), data3(i)); |
| } |
| } |
| |
| static void test_contractions() { |
| Tensor<std::complex<float>, 4> t_left(30, 50, 8, 31); |
| Tensor<std::complex<float>, 5> t_right(8, 31, 7, 20, 10); |
| Tensor<std::complex<float>, 5> t_result(30, 50, 7, 20, 10); |
| |
| t_left.setRandom(); |
| t_right.setRandom(); |
| |
| typedef Map<Matrix<std::complex<float>, Dynamic, Dynamic>> MapXcf; |
| MapXcf m_left(t_left.data(), 1500, 248); |
| MapXcf m_right(t_right.data(), 248, 1400); |
| Matrix<std::complex<float>, Dynamic, Dynamic> m_result(1500, 1400); |
| |
| // This contraction should be equivalent to a regular matrix multiplication |
| typedef Tensor<float, 1>::DimensionPair DimPair; |
| Eigen::array<DimPair, 2> dims; |
| dims[0] = DimPair(2, 0); |
| dims[1] = DimPair(3, 1); |
| t_result = t_left.contract(t_right, dims); |
| m_result = m_left * m_right; |
| for (int i = 0; i < t_result.dimensions().TotalSize(); i++) { |
| VERIFY_IS_APPROX(t_result.data()[i], m_result.data()[i]); |
| } |
| } |
| |
| EIGEN_DECLARE_TEST(cxx11_tensor_of_complex) { |
| CALL_SUBTEST(test_additions()); |
| CALL_SUBTEST(test_abs()); |
| CALL_SUBTEST(test_arg()); |
| CALL_SUBTEST(test_conjugate()); |
| CALL_SUBTEST(test_contractions()); |
| } |