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
product_selfadjoint(const MatrixType & m)12 template<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
test_product_selfadjoint()63 void 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