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