| // This file is part of Eigen, a lightweight C++ template library |
| // for linear algebra. |
| // |
| // Copyright (C) 2009 Hauke Heibel <hauke.heibel@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/Core> |
| |
| using namespace Eigen; |
| |
| template <typename Scalar, int Storage> |
| void run_matrix_tests() |
| { |
| typedef Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic, Storage> MatrixType; |
| typedef typename MatrixType::Index Index; |
| |
| MatrixType m, n; |
| |
| // boundary cases ... |
| m = n = MatrixType::Random(50,50); |
| m.conservativeResize(1,50); |
| VERIFY_IS_APPROX(m, n.block(0,0,1,50)); |
| |
| m = n = MatrixType::Random(50,50); |
| m.conservativeResize(50,1); |
| VERIFY_IS_APPROX(m, n.block(0,0,50,1)); |
| |
| m = n = MatrixType::Random(50,50); |
| m.conservativeResize(50,50); |
| VERIFY_IS_APPROX(m, n.block(0,0,50,50)); |
| |
| // random shrinking ... |
| for (int i=0; i<25; ++i) |
| { |
| const Index rows = internal::random<Index>(1,50); |
| const Index cols = internal::random<Index>(1,50); |
| m = n = MatrixType::Random(50,50); |
| m.conservativeResize(rows,cols); |
| VERIFY_IS_APPROX(m, n.block(0,0,rows,cols)); |
| } |
| |
| // random growing with zeroing ... |
| for (int i=0; i<25; ++i) |
| { |
| const Index rows = internal::random<Index>(50,75); |
| const Index cols = internal::random<Index>(50,75); |
| m = n = MatrixType::Random(50,50); |
| m.conservativeResizeLike(MatrixType::Zero(rows,cols)); |
| VERIFY_IS_APPROX(m.block(0,0,n.rows(),n.cols()), n); |
| VERIFY( rows<=50 || m.block(50,0,rows-50,cols).sum() == Scalar(0) ); |
| VERIFY( cols<=50 || m.block(0,50,rows,cols-50).sum() == Scalar(0) ); |
| } |
| } |
| |
| template <typename Scalar> |
| void run_vector_tests() |
| { |
| typedef Matrix<Scalar, 1, Eigen::Dynamic> MatrixType; |
| |
| MatrixType m, n; |
| |
| // boundary cases ... |
| m = n = MatrixType::Random(50); |
| m.conservativeResize(1); |
| VERIFY_IS_APPROX(m, n.segment(0,1)); |
| |
| m = n = MatrixType::Random(50); |
| m.conservativeResize(50); |
| VERIFY_IS_APPROX(m, n.segment(0,50)); |
| |
| // random shrinking ... |
| for (int i=0; i<50; ++i) |
| { |
| const int size = internal::random<int>(1,50); |
| m = n = MatrixType::Random(50); |
| m.conservativeResize(size); |
| VERIFY_IS_APPROX(m, n.segment(0,size)); |
| } |
| |
| // random growing with zeroing ... |
| for (int i=0; i<50; ++i) |
| { |
| const int size = internal::random<int>(50,100); |
| m = n = MatrixType::Random(50); |
| m.conservativeResizeLike(MatrixType::Zero(size)); |
| VERIFY_IS_APPROX(m.segment(0,50), n); |
| VERIFY( size<=50 || m.segment(50,size-50).sum() == Scalar(0) ); |
| } |
| } |
| |
| void test_conservative_resize() |
| { |
| CALL_SUBTEST_1((run_matrix_tests<int, Eigen::RowMajor>())); |
| CALL_SUBTEST_1((run_matrix_tests<int, Eigen::ColMajor>())); |
| CALL_SUBTEST_2((run_matrix_tests<float, Eigen::RowMajor>())); |
| CALL_SUBTEST_2((run_matrix_tests<float, Eigen::ColMajor>())); |
| CALL_SUBTEST_3((run_matrix_tests<double, Eigen::RowMajor>())); |
| CALL_SUBTEST_3((run_matrix_tests<double, Eigen::ColMajor>())); |
| CALL_SUBTEST_4((run_matrix_tests<std::complex<float>, Eigen::RowMajor>())); |
| CALL_SUBTEST_4((run_matrix_tests<std::complex<float>, Eigen::ColMajor>())); |
| CALL_SUBTEST_5((run_matrix_tests<std::complex<double>, Eigen::RowMajor>())); |
| CALL_SUBTEST_6((run_matrix_tests<std::complex<double>, Eigen::ColMajor>())); |
| |
| CALL_SUBTEST_1((run_vector_tests<int>())); |
| CALL_SUBTEST_2((run_vector_tests<float>())); |
| CALL_SUBTEST_3((run_vector_tests<double>())); |
| CALL_SUBTEST_4((run_vector_tests<std::complex<float> >())); |
| CALL_SUBTEST_5((run_vector_tests<std::complex<double> >())); |
| } |