1c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This file is part of Eigen, a lightweight C++ template library 2c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// for linear algebra. Eigen itself is part of the KDE project. 3c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// 4c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr> 5c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// 6c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This Source Code Form is subject to the terms of the Mozilla 7c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Public License v. 2.0. If a copy of the MPL was not distributed 8c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. 9c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 10c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include "main.h" 11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include <Eigen/QR> 12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename MatrixType> void qr(const MatrixType& m) 14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath /* this test covers the following files: 16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath QR.h 17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath */ 18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath int rows = m.rows(); 19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath int cols = m.cols(); 20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef typename MatrixType::Scalar Scalar; 22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, MatrixType::ColsAtCompileTime> SquareMatrixType; 23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> VectorType; 24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath MatrixType a = MatrixType::Random(rows,cols); 26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath QR<MatrixType> qrOfA(a); 27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(a, qrOfA.matrixQ() * qrOfA.matrixR()); 28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_NOT_APPROX(a+MatrixType::Identity(rows, cols), qrOfA.matrixQ() * qrOfA.matrixR()); 29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath #if 0 // eigenvalues module not yet ready 31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath SquareMatrixType b = a.adjoint() * a; 32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // check tridiagonalization 34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Tridiagonalization<SquareMatrixType> tridiag(b); 35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(b, tridiag.matrixQ() * tridiag.matrixT() * tridiag.matrixQ().adjoint()); 36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // check hessenberg decomposition 38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath HessenbergDecomposition<SquareMatrixType> hess(b); 39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(b, hess.matrixQ() * hess.matrixH() * hess.matrixQ().adjoint()); 40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(tridiag.matrixT(), hess.matrixH()); 41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath b = SquareMatrixType::Random(cols,cols); 42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath hess.compute(b); 43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(b, hess.matrixQ() * hess.matrixH() * hess.matrixQ().adjoint()); 44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath #endif 45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} 46c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid test_eigen2_qr() 48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath for(int i = 0; i < 1; i++) { 50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_1( qr(Matrix2f()) ); 51c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_2( qr(Matrix4d()) ); 52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_3( qr(MatrixXf(12,8)) ); 53c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_4( qr(MatrixXcd(5,5)) ); 54c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_4( qr(MatrixXcd(7,3)) ); 55c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#ifdef EIGEN_TEST_PART_5 58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // small isFullRank test 59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Matrix3d mat; 61c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath mat << 1, 45, 1, 2, 2, 2, 1, 2, 3; 62c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY(mat.qr().isFullRank()); 63c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath mat << 1, 1, 1, 2, 2, 2, 1, 2, 3; 64c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath //always returns true in eigen2support 65c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath //VERIFY(!mat.qr().isFullRank()); 66c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 67c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 68c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif 69c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} 70