1c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This file is part of Eigen, a lightweight C++ template library 2c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// for linear algebra. 3c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// 4c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com> 5c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// 6c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This Source Code Form is subject to the terms of the Mozilla 7c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Public License v. 2.0. If a copy of the MPL was not distributed 8c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. 9c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 10c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN_NO_STATIC_ASSERT 11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include "main.h" 12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename T> 14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct other_matrix_type 15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef int type; 17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}; 18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols> 20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct other_matrix_type<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> > 21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef Matrix<_Scalar, _Rows, _Cols, _Options^RowMajor, _MaxRows, _MaxCols> type; 23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}; 24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename MatrixType> void swap(const MatrixType& m) 26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef typename other_matrix_type<MatrixType>::type OtherMatrixType; 28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef typename MatrixType::Scalar Scalar; 29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath ei_assert((!ei_is_same_type<MatrixType,OtherMatrixType>::ret)); 31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath int rows = m.rows(); 32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath int cols = m.cols(); 33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // construct 3 matrix guaranteed to be distinct 35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath MatrixType m1 = MatrixType::Random(rows,cols); 36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath MatrixType m2 = MatrixType::Random(rows,cols) + Scalar(100) * MatrixType::Identity(rows,cols); 37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath OtherMatrixType m3 = OtherMatrixType::Random(rows,cols) + Scalar(200) * OtherMatrixType::Identity(rows,cols); 38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath MatrixType m1_copy = m1; 40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath MatrixType m2_copy = m2; 41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath OtherMatrixType m3_copy = m3; 42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // test swapping 2 matrices of same type 44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m1.swap(m2); 45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m1,m2_copy); 46c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m2,m1_copy); 47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m1 = m1_copy; 48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m2 = m2_copy; 49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // test swapping 2 matrices of different types 51c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m1.swap(m3); 52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m1,m3_copy); 53c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m3,m1_copy); 54c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m1 = m1_copy; 55c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m3 = m3_copy; 56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // test swapping matrix with expression 58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m1.swap(m2.block(0,0,rows,cols)); 59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m1,m2_copy); 60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m2,m1_copy); 61c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m1 = m1_copy; 62c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m2 = m2_copy; 63c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 64c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // test swapping two expressions of different types 65c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m1.transpose().swap(m3.transpose()); 66c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m1,m3_copy); 67c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m3,m1_copy); 68c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m1 = m1_copy; 69c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m3 = m3_copy; 70c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 71c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // test assertion on mismatching size -- matrix case 72c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_RAISES_ASSERT(m1.swap(m1.row(0))); 73c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // test assertion on mismatching size -- xpr case 74c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_RAISES_ASSERT(m1.row(0).swap(m1)); 75c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} 76c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 77c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid test_eigen2_swap() 78c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 79c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_1( swap(Matrix3f()) ); // fixed size, no vectorization 80c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_1( swap(Matrix4d()) ); // fixed size, possible vectorization 81c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_1( swap(MatrixXd(3,3)) ); // dyn size, no vectorization 82c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_1( swap(MatrixXf(30,30)) ); // dyn size, possible vectorization 83c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} 84