// 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> // // 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/QR> template<typename MatrixType> void qr(const MatrixType& m) { /* this test covers the following files: QR.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 a = MatrixType::Random(rows,cols); QR<MatrixType> qrOfA(a); VERIFY_IS_APPROX(a, qrOfA.matrixQ() * qrOfA.matrixR()); VERIFY_IS_NOT_APPROX(a+MatrixType::Identity(rows, cols), qrOfA.matrixQ() * qrOfA.matrixR()); #if 0 // eigenvalues module not yet ready SquareMatrixType b = a.adjoint() * a; // check tridiagonalization Tridiagonalization<SquareMatrixType> tridiag(b); VERIFY_IS_APPROX(b, tridiag.matrixQ() * tridiag.matrixT() * tridiag.matrixQ().adjoint()); // check hessenberg decomposition HessenbergDecomposition<SquareMatrixType> hess(b); VERIFY_IS_APPROX(b, hess.matrixQ() * hess.matrixH() * hess.matrixQ().adjoint()); VERIFY_IS_APPROX(tridiag.matrixT(), hess.matrixH()); b = SquareMatrixType::Random(cols,cols); hess.compute(b); VERIFY_IS_APPROX(b, hess.matrixQ() * hess.matrixH() * hess.matrixQ().adjoint()); #endif } void test_eigen2_qr() { for(int i = 0; i < 1; i++) { CALL_SUBTEST_1( qr(Matrix2f()) ); CALL_SUBTEST_2( qr(Matrix4d()) ); CALL_SUBTEST_3( qr(MatrixXf(12,8)) ); CALL_SUBTEST_4( qr(MatrixXcd(5,5)) ); CALL_SUBTEST_4( qr(MatrixXcd(7,3)) ); } #ifdef EIGEN_TEST_PART_5 // small isFullRank test { Matrix3d mat; mat << 1, 45, 1, 2, 2, 2, 1, 2, 3; VERIFY(mat.qr().isFullRank()); mat << 1, 1, 1, 2, 2, 2, 1, 2, 3; //always returns true in eigen2support //VERIFY(!mat.qr().isFullRank()); } #endif }