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