eigen/Eigen/src/Core/SelfAdjointView.h
Gael Guennebaud 0529ecfe1b Big refactoring/cleaning in the spasre module with
in particular the addition of a selfadjointView, and the
extension of triangularView. The rest is cleaning and does not
change/extend the API.
2009-11-18 14:52:52 +01:00

218 lines
8.3 KiB
C++

// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2009 Gael Guennebaud <g.gael@free.fr>
//
// Eigen is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_SELFADJOINTMATRIX_H
#define EIGEN_SELFADJOINTMATRIX_H
/** \class SelfAdjointView
* \nonstableyet
*
* \brief Expression of a selfadjoint matrix from a triangular part of a dense matrix
*
* \param MatrixType the type of the dense matrix storing the coefficients
* \param TriangularPart can be either \c LowerTriangular or \c UpperTriangular
*
* This class is an expression of a sefladjoint matrix from a triangular part of a matrix
* with given dense storage of the coefficients. It is the return type of MatrixBase::selfadjointView()
* and most of the time this is the only way that it is used.
*
* \sa class TriangularBase, MatrixBase::selfAdjointView()
*/
template<typename MatrixType, unsigned int TriangularPart>
struct ei_traits<SelfAdjointView<MatrixType, TriangularPart> > : ei_traits<MatrixType>
{
typedef typename ei_nested<MatrixType>::type MatrixTypeNested;
typedef typename ei_unref<MatrixTypeNested>::type _MatrixTypeNested;
typedef MatrixType ExpressionType;
enum {
Mode = TriangularPart | SelfAdjointBit,
Flags = _MatrixTypeNested::Flags & (HereditaryBits)
& (~(PacketAccessBit | DirectAccessBit | LinearAccessBit)), // FIXME these flags should be preserved
CoeffReadCost = _MatrixTypeNested::CoeffReadCost
};
};
template <typename Lhs, int LhsMode, bool LhsIsVector,
typename Rhs, int RhsMode, bool RhsIsVector>
struct SelfadjointProductMatrix;
// FIXME could also be called SelfAdjointWrapper to be consistent with DiagonalWrapper ??
template<typename MatrixType, unsigned int UpLo> class SelfAdjointView
: public TriangularBase<SelfAdjointView<MatrixType, UpLo> >
{
public:
typedef TriangularBase<SelfAdjointView> Base;
typedef typename ei_traits<SelfAdjointView>::Scalar Scalar;
enum {
Mode = ei_traits<SelfAdjointView>::Mode
};
typedef typename MatrixType::PlainMatrixType PlainMatrixType;
inline SelfAdjointView(const MatrixType& matrix) : m_matrix(matrix)
{ ei_assert(ei_are_flags_consistent<Mode>::ret); }
inline int rows() const { return m_matrix.rows(); }
inline int cols() const { return m_matrix.cols(); }
inline int stride() const { return m_matrix.stride(); }
/** \sa MatrixBase::coeff()
* \warning the coordinates must fit into the referenced triangular part
*/
inline Scalar coeff(int row, int col) const
{
Base::check_coordinates_internal(row, col);
return m_matrix.coeff(row, col);
}
/** \sa MatrixBase::coeffRef()
* \warning the coordinates must fit into the referenced triangular part
*/
inline Scalar& coeffRef(int row, int col)
{
Base::check_coordinates_internal(row, col);
return m_matrix.const_cast_derived().coeffRef(row, col);
}
/** \internal */
const MatrixType& _expression() const { return m_matrix; }
/** Efficient self-adjoint matrix times vector/matrix product */
template<typename OtherDerived>
SelfadjointProductMatrix<MatrixType,Mode,false,OtherDerived,0,OtherDerived::IsVectorAtCompileTime>
operator*(const MatrixBase<OtherDerived>& rhs) const
{
return SelfadjointProductMatrix
<MatrixType,Mode,false,OtherDerived,0,OtherDerived::IsVectorAtCompileTime>
(m_matrix, rhs.derived());
}
/** Efficient vector/matrix times self-adjoint matrix product */
template<typename OtherDerived> friend
SelfadjointProductMatrix<OtherDerived,0,OtherDerived::IsVectorAtCompileTime,MatrixType,Mode,false>
operator*(const MatrixBase<OtherDerived>& lhs, const SelfAdjointView& rhs)
{
return SelfadjointProductMatrix
<OtherDerived,0,OtherDerived::IsVectorAtCompileTime,MatrixType,Mode,false>
(lhs.derived(),rhs.m_matrix);
}
/** Perform a symmetric rank 2 update of the selfadjoint matrix \c *this:
* \f$ this = this + \alpha ( u v^* + v u^*) \f$
* \returns a reference to \c *this
*
* The vectors \a u and \c v \b must be column vectors, however they can be
* a adjoint expression without any overhead. Only the meaningful triangular
* part of the matrix is updated, the rest is left unchanged.
*
* \sa rankUpdate(const MatrixBase<DerivedU>&, Scalar)
*/
template<typename DerivedU, typename DerivedV>
SelfAdjointView& rankUpdate(const MatrixBase<DerivedU>& u, const MatrixBase<DerivedV>& v, Scalar alpha = Scalar(1));
/** Perform a symmetric rank K update of the selfadjoint matrix \c *this:
* \f$ this = this + \alpha ( u u^* ) \f$ where \a u is a vector or matrix.
*
* \returns a reference to \c *this
*
* Note that to perform \f$ this = this + \alpha ( u^* u ) \f$ you can simply
* call this function with u.adjoint().
*
* \sa rankUpdate(const MatrixBase<DerivedU>&, const MatrixBase<DerivedV>&, Scalar)
*/
template<typename DerivedU>
SelfAdjointView& rankUpdate(const MatrixBase<DerivedU>& u, Scalar alpha = Scalar(1));
/////////// Cholesky module ///////////
const LLT<PlainMatrixType, UpLo> llt() const;
const LDLT<PlainMatrixType> ldlt() const;
protected:
const typename MatrixType::Nested m_matrix;
};
// template<typename OtherDerived, typename MatrixType, unsigned int UpLo>
// ei_selfadjoint_matrix_product_returntype<OtherDerived,SelfAdjointView<MatrixType,UpLo> >
// operator*(const MatrixBase<OtherDerived>& lhs, const SelfAdjointView<MatrixType,UpLo>& rhs)
// {
// return ei_matrix_selfadjoint_product_returntype<OtherDerived,SelfAdjointView<MatrixType,UpLo> >(lhs.derived(),rhs);
// }
template<typename Derived1, typename Derived2, int UnrollCount, bool ClearOpposite>
struct ei_triangular_assignment_selector<Derived1, Derived2, SelfAdjoint, UnrollCount, ClearOpposite>
{
enum {
col = (UnrollCount-1) / Derived1::RowsAtCompileTime,
row = (UnrollCount-1) % Derived1::RowsAtCompileTime
};
inline static void run(Derived1 &dst, const Derived2 &src)
{
ei_triangular_assignment_selector<Derived1, Derived2, SelfAdjoint, UnrollCount-1, ClearOpposite>::run(dst, src);
if(row == col)
dst.coeffRef(row, col) = ei_real(src.coeff(row, col));
else if(row < col)
dst.coeffRef(col, row) = ei_conj(dst.coeffRef(row, col) = src.coeff(row, col));
}
};
// selfadjoint to dense matrix
template<typename Derived1, typename Derived2, bool ClearOpposite>
struct ei_triangular_assignment_selector<Derived1, Derived2, SelfAdjoint, Dynamic, ClearOpposite>
{
inline static void run(Derived1 &dst, const Derived2 &src)
{
for(int j = 0; j < dst.cols(); ++j)
{
for(int i = 0; i < j; ++i)
dst.coeffRef(j, i) = ei_conj(dst.coeffRef(i, j) = src.coeff(i, j));
dst.coeffRef(j, j) = ei_real(src.coeff(j, j));
}
}
};
/***************************************************************************
* Implementation of MatrixBase methods
***************************************************************************/
template<typename Derived>
template<unsigned int UpLo>
const SelfAdjointView<Derived, UpLo> MatrixBase<Derived>::selfadjointView() const
{
return derived();
}
template<typename Derived>
template<unsigned int UpLo>
SelfAdjointView<Derived, UpLo> MatrixBase<Derived>::selfadjointView()
{
return derived();
}
#endif // EIGEN_SELFADJOINTMATRIX_H