1c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This file is part of Eigen, a lightweight C++ template library
2c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// for linear algebra.
3c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
4c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
5c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk>
6c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
7c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This Source Code Form is subject to the terms of the Mozilla
8c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Public License v. 2.0. If a copy of the MPL was not distributed
9c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
10c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include "main.h"
12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include <Eigen/Eigenvalues>
13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar,int Size> void hessenberg(int size = Size)
15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef Matrix<Scalar,Size,Size> MatrixType;
17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // Test basic functionality: A = U H U* and H is Hessenberg
19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for(int counter = 0; counter < g_repeat; ++counter) {
20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    MatrixType m = MatrixType::Random(size,size);
21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    HessenbergDecomposition<MatrixType> hess(m);
22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    MatrixType Q = hess.matrixQ();
23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    MatrixType H = hess.matrixH();
24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    VERIFY_IS_APPROX(m, Q * H * Q.adjoint());
25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for(int row = 2; row < size; ++row) {
26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      for(int col = 0; col < row-1; ++col) {
27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath	VERIFY(H(row,col) == (typename MatrixType::Scalar)0);
28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      }
29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // Test whether compute() and constructor returns same result
33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  MatrixType A = MatrixType::Random(size, size);
34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  HessenbergDecomposition<MatrixType> cs1;
35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  cs1.compute(A);
36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  HessenbergDecomposition<MatrixType> cs2(A);
37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_EQUAL(cs1.matrixH().eval(), cs2.matrixH().eval());
38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  MatrixType cs1Q = cs1.matrixQ();
39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  MatrixType cs2Q = cs2.matrixQ();
40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_EQUAL(cs1Q, cs2Q);
41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // Test assertions for when used uninitialized
43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  HessenbergDecomposition<MatrixType> hessUninitialized;
44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_RAISES_ASSERT( hessUninitialized.matrixH() );
45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_RAISES_ASSERT( hessUninitialized.matrixQ() );
46c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_RAISES_ASSERT( hessUninitialized.householderCoefficients() );
47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_RAISES_ASSERT( hessUninitialized.packedMatrix() );
48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // TODO: Add tests for packedMatrix() and householderCoefficients()
50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
51c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid test_hessenberg()
53c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
54c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  CALL_SUBTEST_1(( hessenberg<std::complex<double>,1>() ));
55c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  CALL_SUBTEST_2(( hessenberg<std::complex<double>,2>() ));
56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  CALL_SUBTEST_3(( hessenberg<std::complex<float>,4>() ));
57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  CALL_SUBTEST_4(( hessenberg<float,Dynamic>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE)) ));
58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  CALL_SUBTEST_5(( hessenberg<std::complex<double>,Dynamic>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE)) ));
59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // Test problem size constructors
61c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  CALL_SUBTEST_6(HessenbergDecomposition<MatrixXf>(10));
62c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
63