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}
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