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import eigen2 test suite. enable by defining EIGEN_TEST_EIGEN2
only test_prec_inverse4x4 is fixed at the moment. now need to go over all those tests.
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85
test/eigen2/qr.cpp
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85
test/eigen2/qr.cpp
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// 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/QR>
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template<typename MatrixType> void qr(const MatrixType& m)
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{
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/* this test covers the following files:
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QR.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 a = MatrixType::Random(rows,cols);
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QR<MatrixType> qrOfA(a);
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VERIFY_IS_APPROX(a, qrOfA.matrixQ() * qrOfA.matrixR());
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VERIFY_IS_NOT_APPROX(a+MatrixType::Identity(rows, cols), qrOfA.matrixQ() * qrOfA.matrixR());
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SquareMatrixType b = a.adjoint() * a;
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// check tridiagonalization
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Tridiagonalization<SquareMatrixType> tridiag(b);
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VERIFY_IS_APPROX(b, tridiag.matrixQ() * tridiag.matrixT() * tridiag.matrixQ().adjoint());
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// check hessenberg decomposition
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HessenbergDecomposition<SquareMatrixType> hess(b);
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VERIFY_IS_APPROX(b, hess.matrixQ() * hess.matrixH() * hess.matrixQ().adjoint());
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VERIFY_IS_APPROX(tridiag.matrixT(), hess.matrixH());
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b = SquareMatrixType::Random(cols,cols);
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hess.compute(b);
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VERIFY_IS_APPROX(b, hess.matrixQ() * hess.matrixH() * hess.matrixQ().adjoint());
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}
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void test_qr()
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{
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for(int i = 0; i < 1; i++) {
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CALL_SUBTEST( qr(Matrix2f()) );
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CALL_SUBTEST( qr(Matrix4d()) );
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CALL_SUBTEST( qr(MatrixXf(12,8)) );
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CALL_SUBTEST( qr(MatrixXcd(5,5)) );
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CALL_SUBTEST( qr(MatrixXcd(7,3)) );
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}
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// small isFullRank test
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{
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Matrix3d mat;
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mat << 1, 45, 1, 2, 2, 2, 1, 2, 3;
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VERIFY(mat.qr().isFullRank());
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mat << 1, 1, 1, 2, 2, 2, 1, 2, 3;
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VERIFY(!mat.qr().isFullRank());
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}
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{
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MatrixXf m = MatrixXf::Zero(10,10);
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VectorXf b = VectorXf::Zero(10);
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VectorXf x = VectorXf::Random(10);
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VERIFY(m.qr().solve(b,&x));
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VERIFY(x.isZero());
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}
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}
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