1c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This file is triangularView of Eigen, a lightweight C++ template library
2c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// for linear algebra.
3c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
4c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.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
12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename MatrixType> void bandmatrix(const MatrixType& _m)
13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename MatrixType::Index Index;
15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename MatrixType::Scalar Scalar;
16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename NumTraits<Scalar>::Real RealScalar;
17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrixType;
18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Index rows = _m.rows();
20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Index cols = _m.cols();
21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Index supers = _m.supers();
22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Index subs = _m.subs();
23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  MatrixType m(rows,cols,supers,subs);
25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  DenseMatrixType dm1(rows,cols);
27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  dm1.setZero();
28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  m.diagonal().setConstant(123);
30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  dm1.diagonal().setConstant(123);
31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int i=1; i<=m.supers();++i)
32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    m.diagonal(i).setConstant(static_cast<RealScalar>(i));
34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    dm1.diagonal(i).setConstant(static_cast<RealScalar>(i));
35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int i=1; i<=m.subs();++i)
37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    m.diagonal(-i).setConstant(-static_cast<RealScalar>(i));
39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    dm1.diagonal(-i).setConstant(-static_cast<RealScalar>(i));
40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  //std::cerr << m.m_data << "\n\n" << m.toDense() << "\n\n" << dm1 << "\n\n\n\n";
42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX(dm1,m.toDenseMatrix());
43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int i=0; i<cols; ++i)
45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
46c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    m.col(i).setConstant(static_cast<RealScalar>(i+1));
47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    dm1.col(i).setConstant(static_cast<RealScalar>(i+1));
48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Index d = (std::min)(rows,cols);
50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Index a = std::max<Index>(0,cols-d-supers);
51c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Index b = std::max<Index>(0,rows-d-subs);
52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  if(a>0) dm1.block(0,d+supers,rows,a).setZero();
53c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  dm1.block(0,supers+1,cols-supers-1-a,cols-supers-1-a).template triangularView<Upper>().setZero();
54c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  dm1.block(subs+1,0,rows-subs-1-b,rows-subs-1-b).template triangularView<Lower>().setZero();
55c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  if(b>0) dm1.block(d+subs,0,b,cols).setZero();
56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  //std::cerr << m.m_data << "\n\n" << m.toDense() << "\n\n" << dm1 << "\n\n";
57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX(dm1,m.toDenseMatrix());
58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
61c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathusing Eigen::internal::BandMatrix;
62c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
63c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid test_bandmatrix()
64c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
65c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef BandMatrix<float>::Index Index;
66c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
67c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for(int i = 0; i < 10*g_repeat ; i++) {
68c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Index rows = internal::random<Index>(1,10);
69c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Index cols = internal::random<Index>(1,10);
70c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Index sups = internal::random<Index>(0,cols-1);
71c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Index subs = internal::random<Index>(0,rows-1);
72c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CALL_SUBTEST(bandmatrix(BandMatrix<float>(rows,cols,sups,subs)) );
73c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
74c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
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