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- all what's not in unsupported/ is considered stable API (except internal stuff e.g. expression templates).
227 lines
8.3 KiB
C++
227 lines
8.3 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
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//
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// Eigen is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 3 of the License, or (at your option) any later version.
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//
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// Alternatively, you can redistribute it and/or
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// modify it under the terms of the GNU General Public License as
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// published by the Free Software Foundation; either version 2 of
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// the License, or (at your option) any later version.
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//
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// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
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// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License and a copy of the GNU General Public License along with
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// Eigen. If not, see <http://www.gnu.org/licenses/>.
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#ifndef EIGEN_SPARSE_SELFADJOINTVIEW_H
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#define EIGEN_SPARSE_SELFADJOINTVIEW_H
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/** \class SparseSelfAdjointView
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*
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*
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* \brief Pseudo expression to manipulate a triangular sparse matrix as a selfadjoint matrix.
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*
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* \param MatrixType the type of the dense matrix storing the coefficients
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* \param UpLo can be either \c Lower or \c Upper
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*
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* This class is an expression of a sefladjoint matrix from a triangular part of a matrix
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* with given dense storage of the coefficients. It is the return type of MatrixBase::selfadjointView()
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* and most of the time this is the only way that it is used.
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*
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* \sa SparseMatrixBase::selfAdjointView()
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*/
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template<typename Lhs, typename Rhs, int UpLo>
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class SparseSelfAdjointTimeDenseProduct;
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template<typename Lhs, typename Rhs, int UpLo>
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class DenseTimeSparseSelfAdjointProduct;
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template<typename MatrixType, unsigned int UpLo> class SparseSelfAdjointView
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{
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public:
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typedef typename MatrixType::Scalar Scalar;
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typedef typename MatrixType::Index Index;
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inline SparseSelfAdjointView(const MatrixType& matrix) : m_matrix(matrix)
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{
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ei_assert(ei_are_flags_consistent<UpLo>::ret);
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ei_assert(rows()==cols() && "SelfAdjointView is only for squared matrices");
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}
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inline Index rows() const { return m_matrix.rows(); }
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inline Index cols() const { return m_matrix.cols(); }
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/** \internal \returns a reference to the nested matrix */
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const MatrixType& matrix() const { return m_matrix; }
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/** Efficient sparse self-adjoint matrix times dense vector/matrix product */
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template<typename OtherDerived>
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SparseSelfAdjointTimeDenseProduct<MatrixType,OtherDerived,UpLo>
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operator*(const MatrixBase<OtherDerived>& rhs) const
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{
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return SparseSelfAdjointTimeDenseProduct<MatrixType,OtherDerived,UpLo>(m_matrix, rhs.derived());
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}
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/** Efficient dense vector/matrix times sparse self-adjoint matrix product */
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template<typename OtherDerived> friend
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DenseTimeSparseSelfAdjointProduct<OtherDerived,MatrixType,UpLo>
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operator*(const MatrixBase<OtherDerived>& lhs, const SparseSelfAdjointView& rhs)
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{
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return DenseTimeSparseSelfAdjointProduct<OtherDerived,MatrixType,UpLo>(lhs.derived(), rhs.m_matrix);
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}
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/** Perform a symmetric rank K update of the selfadjoint matrix \c *this:
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* \f$ this = this + \alpha ( u u^* ) \f$ where \a u is a vector or matrix.
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*
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* \returns a reference to \c *this
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*
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* Note that it is faster to set alpha=0 than initializing the matrix to zero
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* and then keep the default value alpha=1.
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*
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* To perform \f$ this = this + \alpha ( u^* u ) \f$ you can simply
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* call this function with u.adjoint().
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*/
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template<typename DerivedU>
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SparseSelfAdjointView& rankUpdate(const MatrixBase<DerivedU>& u, Scalar alpha = Scalar(1));
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// const SparseLLT<PlainObject, UpLo> llt() const;
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// const SparseLDLT<PlainObject, UpLo> ldlt() const;
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protected:
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const typename MatrixType::Nested m_matrix;
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};
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/***************************************************************************
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* Implementation of SparseMatrixBase methods
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***************************************************************************/
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template<typename Derived>
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template<unsigned int UpLo>
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const SparseSelfAdjointView<Derived, UpLo> SparseMatrixBase<Derived>::selfadjointView() const
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{
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return derived();
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}
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template<typename Derived>
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template<unsigned int UpLo>
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SparseSelfAdjointView<Derived, UpLo> SparseMatrixBase<Derived>::selfadjointView()
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{
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return derived();
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}
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/***************************************************************************
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* Implementation of SparseSelfAdjointView methods
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***************************************************************************/
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template<typename MatrixType, unsigned int UpLo>
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template<typename DerivedU>
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SparseSelfAdjointView<MatrixType,UpLo>&
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SparseSelfAdjointView<MatrixType,UpLo>::rankUpdate(const MatrixBase<DerivedU>& u, Scalar alpha)
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{
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SparseMatrix<Scalar,MatrixType::Flags&RowMajorBit?RowMajor:ColMajor> tmp = u * u.adjoint();
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if(alpha==Scalar(0))
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m_matrix = tmp.template triangularView<UpLo>();
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else
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m_matrix += alpha * tmp.template triangularView<UpLo>();
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return this;
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}
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/***************************************************************************
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* Implementation of sparse self-adjoint time dense matrix
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***************************************************************************/
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template<typename Lhs, typename Rhs, int UpLo>
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struct ei_traits<SparseSelfAdjointTimeDenseProduct<Lhs,Rhs,UpLo> >
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: ei_traits<ProductBase<SparseSelfAdjointTimeDenseProduct<Lhs,Rhs,UpLo>, Lhs, Rhs> >
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{
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typedef Dense StorageKind;
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};
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template<typename Lhs, typename Rhs, int UpLo>
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class SparseSelfAdjointTimeDenseProduct
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: public ProductBase<SparseSelfAdjointTimeDenseProduct<Lhs,Rhs,UpLo>, Lhs, Rhs>
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{
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public:
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EIGEN_PRODUCT_PUBLIC_INTERFACE(SparseSelfAdjointTimeDenseProduct)
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SparseSelfAdjointTimeDenseProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
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{}
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template<typename Dest> void scaleAndAddTo(Dest& dest, Scalar alpha) const
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{
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// TODO use alpha
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ei_assert(alpha==Scalar(1) && "alpha != 1 is not implemented yet, sorry");
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typedef typename ei_cleantype<Lhs>::type _Lhs;
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typedef typename ei_cleantype<Rhs>::type _Rhs;
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typedef typename _Lhs::InnerIterator LhsInnerIterator;
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enum {
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LhsIsRowMajor = (_Lhs::Flags&RowMajorBit)==RowMajorBit,
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ProcessFirstHalf =
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((UpLo&(Upper|Lower))==(Upper|Lower))
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|| ( (UpLo&Upper) && !LhsIsRowMajor)
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|| ( (UpLo&Lower) && LhsIsRowMajor),
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ProcessSecondHalf = !ProcessFirstHalf
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};
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for (Index j=0; j<m_lhs.outerSize(); ++j)
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{
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LhsInnerIterator i(m_lhs,j);
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if (ProcessSecondHalf && i && (i.index()==j))
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{
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dest.row(j) += i.value() * m_rhs.row(j);
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++i;
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}
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Block<Dest,1,Dest::ColsAtCompileTime> dest_j(dest.row(LhsIsRowMajor ? j : 0));
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for(; (ProcessFirstHalf ? i && i.index() < j : i) ; ++i)
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{
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Index a = LhsIsRowMajor ? j : i.index();
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Index b = LhsIsRowMajor ? i.index() : j;
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typename Lhs::Scalar v = i.value();
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dest.row(a) += (v) * m_rhs.row(b);
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dest.row(b) += ei_conj(v) * m_rhs.row(a);
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}
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if (ProcessFirstHalf && i && (i.index()==j))
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dest.row(j) += i.value() * m_rhs.row(j);
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}
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}
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private:
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SparseSelfAdjointTimeDenseProduct& operator=(const SparseSelfAdjointTimeDenseProduct&);
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};
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template<typename Lhs, typename Rhs, int UpLo>
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struct ei_traits<DenseTimeSparseSelfAdjointProduct<Lhs,Rhs,UpLo> >
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: ei_traits<ProductBase<DenseTimeSparseSelfAdjointProduct<Lhs,Rhs,UpLo>, Lhs, Rhs> >
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{};
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template<typename Lhs, typename Rhs, int UpLo>
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class DenseTimeSparseSelfAdjointProduct
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: public ProductBase<DenseTimeSparseSelfAdjointProduct<Lhs,Rhs,UpLo>, Lhs, Rhs>
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{
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public:
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EIGEN_PRODUCT_PUBLIC_INTERFACE(DenseTimeSparseSelfAdjointProduct)
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DenseTimeSparseSelfAdjointProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
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{}
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template<typename Dest> void scaleAndAddTo(Dest& /*dest*/, Scalar /*alpha*/) const
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{
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// TODO
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}
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private:
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DenseTimeSparseSelfAdjointProduct& operator=(const DenseTimeSparseSelfAdjointProduct&);
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};
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#endif // EIGEN_SPARSE_SELFADJOINTVIEW_H
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