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// 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_SPARSE_SELFADJOINTVIEW_H
#define EIGEN_SPARSE_SELFADJOINTVIEW_H
/** \class SparseSelfAdjointView
* \nonstableyet
*
* \brief Pseudo expression to manipulate a triangular sparse matrix as a selfadjoint matrix.
*
* \param MatrixType the type of the dense matrix storing the coefficients
* \param UpLo can be either \c Lower or \c Upper
*
* 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 SparseMatrixBase::selfAdjointView()
*/
template<typename Lhs, typename Rhs, int UpLo>
class SparseSelfAdjointTimeDenseProduct;
template<typename Lhs, typename Rhs, int UpLo>
class DenseTimeSparseSelfAdjointProduct;
template<typename MatrixType, unsigned int UpLo> class SparseSelfAdjointView
{
public:
typedef typename MatrixType::Scalar Scalar;
typedef typename MatrixType::Index Index;
inline SparseSelfAdjointView(const MatrixType& matrix) : m_matrix(matrix)
{
ei_assert(ei_are_flags_consistent<UpLo>::ret);
ei_assert(rows()==cols() && "SelfAdjointView is only for squared matrices");
}
inline Index rows() const { return m_matrix.rows(); }
inline Index cols() const { return m_matrix.cols(); }
/** \internal \returns a reference to the nested matrix */
const MatrixType& matrix() const { return m_matrix; }
/** Efficient sparse self-adjoint matrix times dense vector/matrix product */
template<typename OtherDerived>
SparseSelfAdjointTimeDenseProduct<MatrixType,OtherDerived,UpLo>
operator*(const MatrixBase<OtherDerived>& rhs) const
{
return SparseSelfAdjointTimeDenseProduct<MatrixType,OtherDerived,UpLo>(m_matrix, rhs.derived());
}
/** Efficient dense vector/matrix times sparse self-adjoint matrix product */
template<typename OtherDerived> friend
DenseTimeSparseSelfAdjointProduct<OtherDerived,MatrixType,UpLo>
operator*(const MatrixBase<OtherDerived>& lhs, const SparseSelfAdjointView& rhs)
{
return DenseTimeSparseSelfAdjointProduct<OtherDerived,MatrixType,UpLo>(lhs.derived(), rhs.m_matrix);
}
/** 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 it is faster to set alpha=0 than initializing the matrix to zero
* and then keep the default value alpha=1.
*
* To perform \f$ this = this + \alpha ( u^* u ) \f$ you can simply
* call this function with u.adjoint().
*/
template<typename DerivedU>
SparseSelfAdjointView& rankUpdate(const MatrixBase<DerivedU>& u, Scalar alpha = Scalar(1));
// const SparseLLT<PlainObject, UpLo> llt() const;
// const SparseLDLT<PlainObject, UpLo> ldlt() const;
protected:
const typename MatrixType::Nested m_matrix;
};
/***************************************************************************
* Implementation of SparseMatrixBase methods
***************************************************************************/
template<typename Derived>
template<unsigned int UpLo>
const SparseSelfAdjointView<Derived, UpLo> SparseMatrixBase<Derived>::selfadjointView() const
{
return derived();
}
template<typename Derived>
template<unsigned int UpLo>
SparseSelfAdjointView<Derived, UpLo> SparseMatrixBase<Derived>::selfadjointView()
{
return derived();
}
/***************************************************************************
* Implementation of SparseSelfAdjointView methods
***************************************************************************/
template<typename MatrixType, unsigned int UpLo>
template<typename DerivedU>
SparseSelfAdjointView<MatrixType,UpLo>&
SparseSelfAdjointView<MatrixType,UpLo>::rankUpdate(const MatrixBase<DerivedU>& u, Scalar alpha)
{
SparseMatrix<Scalar,MatrixType::Flags&RowMajorBit?RowMajor:ColMajor> tmp = u * u.adjoint();
if(alpha==Scalar(0))
m_matrix = tmp.template triangularView<UpLo>();
else
m_matrix += alpha * tmp.template triangularView<UpLo>();
return this;
}
/***************************************************************************
* Implementation of sparse self-adjoint time dense matrix
***************************************************************************/
template<typename Lhs, typename Rhs, int UpLo>
struct ei_traits<SparseSelfAdjointTimeDenseProduct<Lhs,Rhs,UpLo> >
: ei_traits<ProductBase<SparseSelfAdjointTimeDenseProduct<Lhs,Rhs,UpLo>, Lhs, Rhs> >
{
typedef Dense StorageKind;
};
template<typename Lhs, typename Rhs, int UpLo>
class SparseSelfAdjointTimeDenseProduct
: public ProductBase<SparseSelfAdjointTimeDenseProduct<Lhs,Rhs,UpLo>, Lhs, Rhs>
{
public:
EIGEN_PRODUCT_PUBLIC_INTERFACE(SparseSelfAdjointTimeDenseProduct)
SparseSelfAdjointTimeDenseProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
{}
template<typename Dest> void scaleAndAddTo(Dest& dest, Scalar alpha) const
{
// TODO use alpha
ei_assert(alpha==Scalar(1) && "alpha != 1 is not implemented yet, sorry");
typedef typename ei_cleantype<Lhs>::type _Lhs;
typedef typename ei_cleantype<Rhs>::type _Rhs;
typedef typename _Lhs::InnerIterator LhsInnerIterator;
enum {
LhsIsRowMajor = (_Lhs::Flags&RowMajorBit)==RowMajorBit,
ProcessFirstHalf =
((UpLo&(Upper|Lower))==(Upper|Lower))
|| ( (UpLo&Upper) && !LhsIsRowMajor)
|| ( (UpLo&Lower) && LhsIsRowMajor),
ProcessSecondHalf = !ProcessFirstHalf
};
for (Index j=0; j<m_lhs.outerSize(); ++j)
{
LhsInnerIterator i(m_lhs,j);
if (ProcessSecondHalf && i && (i.index()==j))
{
dest.row(j) += i.value() * m_rhs.row(j);
++i;
}
Block<Dest,1,Dest::ColsAtCompileTime> dest_j(dest.row(LhsIsRowMajor ? j : 0));
for(; (ProcessFirstHalf ? i && i.index() < j : i) ; ++i)
{
Index a = LhsIsRowMajor ? j : i.index();
Index b = LhsIsRowMajor ? i.index() : j;
typename Lhs::Scalar v = i.value();
dest.row(a) += (v) * m_rhs.row(b);
dest.row(b) += ei_conj(v) * m_rhs.row(a);
}
if (ProcessFirstHalf && i && (i.index()==j))
dest.row(j) += i.value() * m_rhs.row(j);
}
}
private:
SparseSelfAdjointTimeDenseProduct& operator=(const SparseSelfAdjointTimeDenseProduct&);
};
template<typename Lhs, typename Rhs, int UpLo>
struct ei_traits<DenseTimeSparseSelfAdjointProduct<Lhs,Rhs,UpLo> >
: ei_traits<ProductBase<DenseTimeSparseSelfAdjointProduct<Lhs,Rhs,UpLo>, Lhs, Rhs> >
{};
template<typename Lhs, typename Rhs, int UpLo>
class DenseTimeSparseSelfAdjointProduct
: public ProductBase<DenseTimeSparseSelfAdjointProduct<Lhs,Rhs,UpLo>, Lhs, Rhs>
{
public:
EIGEN_PRODUCT_PUBLIC_INTERFACE(DenseTimeSparseSelfAdjointProduct)
DenseTimeSparseSelfAdjointProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
{}
template<typename Dest> void scaleAndAddTo(Dest& /*dest*/, Scalar /*alpha*/) const
{
// TODO
}
private:
DenseTimeSparseSelfAdjointProduct& operator=(const DenseTimeSparseSelfAdjointProduct&);
};
#endif // EIGEN_SPARSE_SELFADJOINTVIEW_H