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82 lines
2.2 KiB
C++
82 lines
2.2 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#include "main.h"
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#include <Eigen/CXX11/Tensor>
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using Eigen::Tensor;
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using Eigen::TensorMap;
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static void test_additions()
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{
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Tensor<std::complex<float>, 1> data1(3);
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Tensor<std::complex<float>, 1> data2(3);
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for (int i = 0; i < 3; ++i) {
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data1(i) = std::complex<float>(i, -i);
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data2(i) = std::complex<float>(i, 7 * i);
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}
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Tensor<std::complex<float>, 1> sum = data1 + data2;
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for (int i = 0; i < 3; ++i) {
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VERIFY_IS_EQUAL(sum(i), std::complex<float>(2*i, 6*i));
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}
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}
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static void test_abs()
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{
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Tensor<std::complex<float>, 1> data1(3);
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Tensor<std::complex<double>, 1> data2(3);
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data1.setRandom();
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data2.setRandom();
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Tensor<float, 1> abs1 = data1.abs();
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Tensor<double, 1> abs2 = data2.abs();
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for (int i = 0; i < 3; ++i) {
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VERIFY_IS_APPROX(abs1(i), std::abs(data1(i)));
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VERIFY_IS_APPROX(abs2(i), std::abs(data2(i)));
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}
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}
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static void test_contractions()
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{
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Tensor<std::complex<float>, 4> t_left(30, 50, 8, 31);
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Tensor<std::complex<float>, 5> t_right(8, 31, 7, 20, 10);
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Tensor<std::complex<float>, 5> t_result(30, 50, 7, 20, 10);
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t_left.setRandom();
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t_right.setRandom();
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typedef Map<Matrix<std::complex<float>, Dynamic, Dynamic>> MapXcf;
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MapXcf m_left(t_left.data(), 1500, 248);
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MapXcf m_right(t_right.data(), 248, 1400);
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Matrix<std::complex<float>, Dynamic, Dynamic> m_result(1500, 1400);
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// This contraction should be equivalent to a regular matrix multiplication
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typedef Tensor<float, 1>::DimensionPair DimPair;
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Eigen::array<DimPair, 2> dims({{DimPair(2, 0), DimPair(3, 1)}});
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t_result = t_left.contract(t_right, dims);
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m_result = m_left * m_right;
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for (size_t i = 0; i < t_result.dimensions().TotalSize(); i++) {
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VERIFY_IS_APPROX(t_result.data()[i], m_result.data()[i]);
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}
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}
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void test_cxx11_tensor_of_complex()
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{
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CALL_SUBTEST(test_additions());
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CALL_SUBTEST(test_abs());
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CALL_SUBTEST(test_contractions());
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}
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