99 lines
3.2 KiB
C++
99 lines
3.2 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) 2009 Benoit Jacob <jacob.benoit.1@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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template <typename T>
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struct other_matrix_type {
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typedef int type;
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};
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template <typename Scalar_, int Rows_, int Cols_, int Options_, int MaxRows_, int MaxCols_>
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struct other_matrix_type<Matrix<Scalar_, Rows_, Cols_, Options_, MaxRows_, MaxCols_> > {
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typedef Matrix<Scalar_, Rows_, Cols_, Options_ ^ RowMajor, MaxRows_, MaxCols_> type;
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};
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template <typename MatrixType>
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std::enable_if_t<(MatrixType::RowsAtCompileTime == 1 || MatrixType::RowsAtCompileTime == Dynamic), void> check_row_swap(
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MatrixType& m1) {
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if (m1.rows() != 1) {
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// test assertion on mismatching size -- matrix case
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VERIFY_RAISES_ASSERT(m1.swap(m1.row(0)));
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// test assertion on mismatching size -- xpr case
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VERIFY_RAISES_ASSERT(m1.row(0).swap(m1));
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}
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}
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template <typename MatrixType>
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std::enable_if_t<!(MatrixType::RowsAtCompileTime == 1 || MatrixType::RowsAtCompileTime == Dynamic), void>
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check_row_swap(MatrixType& /* unused */) {}
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template <typename MatrixType>
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void swap(const MatrixType& m) {
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typedef typename other_matrix_type<MatrixType>::type OtherMatrixType;
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typedef typename MatrixType::Scalar Scalar;
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eigen_assert((!internal::is_same<MatrixType, OtherMatrixType>::value));
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Index rows = m.rows();
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Index cols = m.cols();
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// construct 3 matrix guaranteed to be distinct
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MatrixType m1 = MatrixType::Random(rows, cols);
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MatrixType m2 = MatrixType::Random(rows, cols) + Scalar(100) * MatrixType::Identity(rows, cols);
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OtherMatrixType m3 = OtherMatrixType::Random(rows, cols) + Scalar(200) * OtherMatrixType::Identity(rows, cols);
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MatrixType m1_copy = m1;
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MatrixType m2_copy = m2;
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OtherMatrixType m3_copy = m3;
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// test swapping 2 matrices of same type
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Scalar *d1 = m1.data(), *d2 = m2.data();
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m1.swap(m2);
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VERIFY_IS_APPROX(m1, m2_copy);
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VERIFY_IS_APPROX(m2, m1_copy);
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if (MatrixType::SizeAtCompileTime == Dynamic) {
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VERIFY(m1.data() == d2);
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VERIFY(m2.data() == d1);
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}
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m1 = m1_copy;
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m2 = m2_copy;
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// test swapping 2 matrices of different types
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m1.swap(m3);
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VERIFY_IS_APPROX(m1, m3_copy);
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VERIFY_IS_APPROX(m3, m1_copy);
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m1 = m1_copy;
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m3 = m3_copy;
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// test swapping matrix with expression
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m1.swap(m2.block(0, 0, rows, cols));
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VERIFY_IS_APPROX(m1, m2_copy);
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VERIFY_IS_APPROX(m2, m1_copy);
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m1 = m1_copy;
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m2 = m2_copy;
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// test swapping two expressions of different types
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m1.transpose().swap(m3.transpose());
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VERIFY_IS_APPROX(m1, m3_copy);
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VERIFY_IS_APPROX(m3, m1_copy);
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m1 = m1_copy;
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m3 = m3_copy;
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check_row_swap(m1);
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}
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EIGEN_DECLARE_TEST(swap) {
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int s = internal::random<int>(1, EIGEN_TEST_MAX_SIZE);
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CALL_SUBTEST_1(swap(Matrix3f())); // fixed size, no vectorization
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CALL_SUBTEST_2(swap(Matrix4d())); // fixed size, possible vectorization
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CALL_SUBTEST_3(swap(MatrixXd(s, s))); // dyn size, no vectorization
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CALL_SUBTEST_4(swap(MatrixXf(s, s))); // dyn size, possible vectorization
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TEST_SET_BUT_UNUSED_VARIABLE(s)
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}
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