1c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This file is part of Eigen, a lightweight C++ template library
2c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// for linear algebra.
3c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
4c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2010 Vincent Lejeune
5c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2010 Gael Guennebaud <gael.guennebaud@inria.fr>
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#ifndef EIGEN_BLOCK_HOUSEHOLDER_H
12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN_BLOCK_HOUSEHOLDER_H
13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This file contains some helper function to deal with block householder reflectors
15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace Eigen {
17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace internal {
19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal */
21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename TriangularFactorType,typename VectorsType,typename CoeffsType>
22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid make_block_householder_triangular_factor(TriangularFactorType& triFactor, const VectorsType& vectors, const CoeffsType& hCoeffs)
23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename TriangularFactorType::Index Index;
25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename VectorsType::Scalar Scalar;
26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  const Index nbVecs = vectors.cols();
27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  eigen_assert(triFactor.rows() == nbVecs && triFactor.cols() == nbVecs && vectors.rows()>=nbVecs);
28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for(Index i = 0; i < nbVecs; i++)
30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Index rs = vectors.rows() - i;
32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Scalar Vii = vectors(i,i);
33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    vectors.const_cast_derived().coeffRef(i,i) = Scalar(1);
34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    triFactor.col(i).head(i).noalias() = -hCoeffs(i) * vectors.block(i, 0, rs, i).adjoint()
35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath                                       * vectors.col(i).tail(rs);
36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    vectors.const_cast_derived().coeffRef(i, i) = Vii;
37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    // FIXME add .noalias() once the triangular product can work inplace
38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    triFactor.col(i).head(i) = triFactor.block(0,0,i,i).template triangularView<Upper>()
39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath                             * triFactor.col(i).head(i);
40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    triFactor(i,i) = hCoeffs(i);
41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal */
45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename MatrixType,typename VectorsType,typename CoeffsType>
46c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid apply_block_householder_on_the_left(MatrixType& mat, const VectorsType& vectors, const CoeffsType& hCoeffs)
47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename MatrixType::Index Index;
49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum { TFactorSize = MatrixType::ColsAtCompileTime };
50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Index nbVecs = vectors.cols();
517faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  Matrix<typename MatrixType::Scalar, TFactorSize, TFactorSize, ColMajor> T(nbVecs,nbVecs);
52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  make_block_householder_triangular_factor(T, vectors, hCoeffs);
53c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
54c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  const TriangularView<const VectorsType, UnitLower>& V(vectors);
55c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // A -= V T V^* A
57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Matrix<typename MatrixType::Scalar,VectorsType::ColsAtCompileTime,MatrixType::ColsAtCompileTime,0,
58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath         VectorsType::MaxColsAtCompileTime,MatrixType::MaxColsAtCompileTime> tmp = V.adjoint() * mat;
59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // FIXME add .noalias() once the triangular product can work inplace
60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  tmp = T.template triangularView<Upper>().adjoint() * tmp;
61c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  mat.noalias() -= V * tmp;
62c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
63c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
64c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace internal
65c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
66c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace Eigen
67c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
68c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif // EIGEN_BLOCK_HOUSEHOLDER_H
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