1// This file is part of Eigen, a lightweight C++ template library
2// for linear algebra.
3//
4// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
5//
6// This Source Code Form is subject to the terms of the Mozilla
7// Public License v. 2.0. If a copy of the MPL was not distributed
8// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
9
10#include "main.h"
11
12template<typename MatrixType> void product_selfadjoint(const MatrixType& m)
13{
14  typedef typename MatrixType::Index Index;
15  typedef typename MatrixType::Scalar Scalar;
16  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
17  typedef Matrix<Scalar, 1, MatrixType::RowsAtCompileTime> RowVectorType;
18
19  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, Dynamic, RowMajor> RhsMatrixType;
20
21  Index rows = m.rows();
22  Index cols = m.cols();
23
24  MatrixType m1 = MatrixType::Random(rows, cols),
25             m2 = MatrixType::Random(rows, cols),
26             m3;
27  VectorType v1 = VectorType::Random(rows),
28             v2 = VectorType::Random(rows),
29             v3(rows);
30  RowVectorType r1 = RowVectorType::Random(rows),
31                r2 = RowVectorType::Random(rows);
32  RhsMatrixType m4 = RhsMatrixType::Random(rows,10);
33
34  Scalar s1 = internal::random<Scalar>(),
35         s2 = internal::random<Scalar>(),
36         s3 = internal::random<Scalar>();
37
38  m1 = (m1.adjoint() + m1).eval();
39
40  // rank2 update
41  m2 = m1.template triangularView<Lower>();
42  m2.template selfadjointView<Lower>().rankUpdate(v1,v2);
43  VERIFY_IS_APPROX(m2, (m1 + v1 * v2.adjoint()+ v2 * v1.adjoint()).template triangularView<Lower>().toDenseMatrix());
44
45  m2 = m1.template triangularView<Upper>();
46  m2.template selfadjointView<Upper>().rankUpdate(-v1,s2*v2,s3);
47  VERIFY_IS_APPROX(m2, (m1 + (s3*(-v1)*(s2*v2).adjoint()+numext::conj(s3)*(s2*v2)*(-v1).adjoint())).template triangularView<Upper>().toDenseMatrix());
48
49  m2 = m1.template triangularView<Upper>();
50  m2.template selfadjointView<Upper>().rankUpdate(-s2*r1.adjoint(),r2.adjoint()*s3,s1);
51  VERIFY_IS_APPROX(m2, (m1 + s1*(-s2*r1.adjoint())*(r2.adjoint()*s3).adjoint() + numext::conj(s1)*(r2.adjoint()*s3) * (-s2*r1.adjoint()).adjoint()).template triangularView<Upper>().toDenseMatrix());
52
53  if (rows>1)
54  {
55    m2 = m1.template triangularView<Lower>();
56    m2.block(1,1,rows-1,cols-1).template selfadjointView<Lower>().rankUpdate(v1.tail(rows-1),v2.head(cols-1));
57    m3 = m1;
58    m3.block(1,1,rows-1,cols-1) += v1.tail(rows-1) * v2.head(cols-1).adjoint()+ v2.head(cols-1) * v1.tail(rows-1).adjoint();
59    VERIFY_IS_APPROX(m2, m3.template triangularView<Lower>().toDenseMatrix());
60  }
61}
62
63void test_product_selfadjoint()
64{
65  int s = 0;
66  for(int i = 0; i < g_repeat ; i++) {
67    CALL_SUBTEST_1( product_selfadjoint(Matrix<float, 1, 1>()) );
68    CALL_SUBTEST_2( product_selfadjoint(Matrix<float, 2, 2>()) );
69    CALL_SUBTEST_3( product_selfadjoint(Matrix3d()) );
70
71    s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2);
72    CALL_SUBTEST_4( product_selfadjoint(MatrixXcf(s, s)) );
73    TEST_SET_BUT_UNUSED_VARIABLE(s)
74
75    s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2);
76    CALL_SUBTEST_5( product_selfadjoint(MatrixXcd(s,s)) );
77    TEST_SET_BUT_UNUSED_VARIABLE(s)
78
79    s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE);
80    CALL_SUBTEST_6( product_selfadjoint(MatrixXd(s,s)) );
81    TEST_SET_BUT_UNUSED_VARIABLE(s)
82
83    s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE);
84    CALL_SUBTEST_7( product_selfadjoint(Matrix<float,Dynamic,Dynamic,RowMajor>(s,s)) );
85    TEST_SET_BUT_UNUSED_VARIABLE(s)
86  }
87}
88