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https://gitlab.com/libeigen/eigen.git
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522e24f2d7
replaced the QTestLib framework my custom macros and a (optional) custom script to run the tests from ctest.
79 lines
3.0 KiB
C++
79 lines
3.0 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra. Eigen itself is part of the KDE project.
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//
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// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
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//
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// Eigen is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 3 of the License, or (at your option) any later version.
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//
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// Alternatively, you can redistribute it and/or
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// modify it under the terms of the GNU General Public License as
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// published by the Free Software Foundation; either version 2 of
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// the License, or (at your option) any later version.
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//
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// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
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// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License and a copy of the GNU General Public License along with
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// Eigen. If not, see <http://www.gnu.org/licenses/>.
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#include "main.h"
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#include <Eigen/LU>
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template<typename MatrixType> void nullDeterminant(const MatrixType& m)
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{
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/* this test covers the following files:
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Determinant.h
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*/
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int rows = m.rows();
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int cols = m.cols();
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typedef typename MatrixType::Scalar Scalar;
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typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, MatrixType::ColsAtCompileTime> SquareMatrixType;
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typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> VectorType;
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MatrixType dinv(rows, cols), dnotinv(rows, cols);
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dinv.col(0).setOnes();
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dinv.block(0,1, rows, cols-2).setRandom();
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dnotinv.col(0).setOnes();
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dnotinv.block(0,1, rows, cols-2).setRandom();
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dnotinv.col(cols-1).setOnes();
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for (int i=0 ; i<rows ; ++i)
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{
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dnotinv.row(i).block(0,1,1,cols-2) = ei_random<Scalar>(99.999999,100.00000001)*dnotinv.row(i).block(0,1,1,cols-2).normalized();
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dnotinv(i,cols-1) = dnotinv.row(i).block(0,1,1,cols-2).norm2();
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dinv(i,cols-1) = dinv.row(i).block(0,1,1,cols-2).norm2();
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}
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SquareMatrixType invertibleCovarianceMatrix = dinv.transpose() * dinv;
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SquareMatrixType notInvertibleCovarianceMatrix = dnotinv.transpose() * dnotinv;
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std::cout << notInvertibleCovarianceMatrix << "\n" << notInvertibleCovarianceMatrix.determinant() << "\n";
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VERIFY_IS_MUCH_SMALLER_THAN(notInvertibleCovarianceMatrix.determinant(),
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notInvertibleCovarianceMatrix.cwiseAbs().maxCoeff());
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VERIFY(invertibleCovarianceMatrix.inverse().exists());
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VERIFY(!notInvertibleCovarianceMatrix.inverse().exists());
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}
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void test_determinant()
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{
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for(int i = 0; i < g_repeat; i++) {
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CALL_SUBTEST( nullDeterminant(Matrix<float, 30, 3>()) );
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CALL_SUBTEST( nullDeterminant(Matrix<double, 30, 3>()) );
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CALL_SUBTEST( nullDeterminant(Matrix<float, 20, 4>()) );
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CALL_SUBTEST( nullDeterminant(Matrix<double, 20, 4>()) );
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// CALL_SUBTEST( nullDeterminant(MatrixXd(20,4));
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}
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}
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