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// 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
}
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