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 Benoit Jacob <jacob.benoit.1@gmail.com>
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#ifndef EIGEN_MISC_KERNEL_H
11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN_MISC_KERNEL_H
12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace Eigen {
14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace internal {
16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \class kernel_retval_base
18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename DecompositionType>
21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct traits<kernel_retval_base<DecompositionType> >
22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename DecompositionType::MatrixType MatrixType;
24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef Matrix<
25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typename MatrixType::Scalar,
26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    MatrixType::ColsAtCompileTime, // the number of rows in the "kernel matrix"
27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath                                   // is the number of cols of the original matrix
28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath                                   // so that the product "matrix * kernel = zero" makes sense
29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Dynamic,                       // we don't know at compile-time the dimension of the kernel
30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    MatrixType::Options,
31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    MatrixType::MaxColsAtCompileTime, // see explanation for 2nd template parameter
32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    MatrixType::MaxColsAtCompileTime // the kernel is a subspace of the domain space,
33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath                                     // whose dimension is the number of columns of the original matrix
34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  > ReturnType;
35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename _DecompositionType> struct kernel_retval_base
38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath : public ReturnByValue<kernel_retval_base<_DecompositionType> >
39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef _DecompositionType DecompositionType;
41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef ReturnByValue<kernel_retval_base> Base;
42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename Base::Index Index;
43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  kernel_retval_base(const DecompositionType& dec)
45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    : m_dec(dec),
46c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      m_rank(dec.rank()),
47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      m_cols(m_rank==dec.cols() ? 1 : dec.cols() - m_rank)
48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {}
49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline Index rows() const { return m_dec.cols(); }
51c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline Index cols() const { return m_cols; }
52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline Index rank() const { return m_rank; }
53c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline const DecompositionType& dec() const { return m_dec; }
54c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
55c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Dest> inline void evalTo(Dest& dst) const
56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    static_cast<const kernel_retval<DecompositionType>*>(this)->evalTo(dst);
58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  protected:
61c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const DecompositionType& m_dec;
62c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Index m_rank, m_cols;
63c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
64c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
65c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace internal
66c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
67c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN_MAKE_KERNEL_HELPERS(DecompositionType) \
68c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename DecompositionType::MatrixType MatrixType; \
69c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename MatrixType::Scalar Scalar; \
70c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename MatrixType::RealScalar RealScalar; \
71c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename MatrixType::Index Index; \
72c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef Eigen::internal::kernel_retval_base<DecompositionType> Base; \
73c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  using Base::dec; \
74c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  using Base::rank; \
75c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  using Base::rows; \
76c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  using Base::cols; \
77c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  kernel_retval(const DecompositionType& dec) : Base(dec) {}
78c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
79c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace Eigen
80c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
81c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif // EIGEN_MISC_KERNEL_H
82