[136] | 1 | // This file is part of Eigen, a lightweight C++ template library
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| 2 | // for linear algebra.
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| 3 | //
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| 4 | // Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
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| 5 | //
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| 6 | // This Source Code Form is subject to the terms of the Mozilla
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| 7 | // Public License v. 2.0. If a copy of the MPL was not distributed
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| 8 | // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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| 9 |
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| 10 | #ifndef EIGEN_SPARSE_SELFADJOINTVIEW_H
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| 11 | #define EIGEN_SPARSE_SELFADJOINTVIEW_H
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| 12 |
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| 13 | namespace Eigen {
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| 14 |
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| 15 | /** \ingroup SparseCore_Module
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| 16 | * \class SparseSelfAdjointView
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| 17 | *
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| 18 | * \brief Pseudo expression to manipulate a triangular sparse matrix as a selfadjoint matrix.
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| 19 | *
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| 20 | * \param MatrixType the type of the dense matrix storing the coefficients
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| 21 | * \param UpLo can be either \c #Lower or \c #Upper
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| 22 | *
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| 23 | * This class is an expression of a sefladjoint matrix from a triangular part of a matrix
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| 24 | * with given dense storage of the coefficients. It is the return type of MatrixBase::selfadjointView()
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| 25 | * and most of the time this is the only way that it is used.
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| 26 | *
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| 27 | * \sa SparseMatrixBase::selfadjointView()
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| 28 | */
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| 29 | template<typename Lhs, typename Rhs, int UpLo>
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| 30 | class SparseSelfAdjointTimeDenseProduct;
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| 31 |
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| 32 | template<typename Lhs, typename Rhs, int UpLo>
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| 33 | class DenseTimeSparseSelfAdjointProduct;
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| 34 |
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| 35 | namespace internal {
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| 36 |
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| 37 | template<typename MatrixType, unsigned int UpLo>
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| 38 | struct traits<SparseSelfAdjointView<MatrixType,UpLo> > : traits<MatrixType> {
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| 39 | };
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| 40 |
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| 41 | template<int SrcUpLo,int DstUpLo,typename MatrixType,int DestOrder>
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| 42 | void permute_symm_to_symm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DestOrder,typename MatrixType::Index>& _dest, const typename MatrixType::Index* perm = 0);
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| 43 |
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| 44 | template<int UpLo,typename MatrixType,int DestOrder>
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| 45 | void permute_symm_to_fullsymm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DestOrder,typename MatrixType::Index>& _dest, const typename MatrixType::Index* perm = 0);
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| 46 |
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| 47 | }
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| 48 |
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| 49 | template<typename MatrixType, unsigned int UpLo> class SparseSelfAdjointView
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| 50 | : public EigenBase<SparseSelfAdjointView<MatrixType,UpLo> >
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| 51 | {
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| 52 | public:
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| 53 |
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| 54 | typedef typename MatrixType::Scalar Scalar;
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| 55 | typedef typename MatrixType::Index Index;
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| 56 | typedef Matrix<Index,Dynamic,1> VectorI;
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| 57 | typedef typename MatrixType::Nested MatrixTypeNested;
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| 58 | typedef typename internal::remove_all<MatrixTypeNested>::type _MatrixTypeNested;
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| 59 |
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| 60 | inline SparseSelfAdjointView(const MatrixType& matrix) : m_matrix(matrix)
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| 61 | {
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| 62 | eigen_assert(rows()==cols() && "SelfAdjointView is only for squared matrices");
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| 63 | }
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| 64 |
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| 65 | inline Index rows() const { return m_matrix.rows(); }
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| 66 | inline Index cols() const { return m_matrix.cols(); }
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| 67 |
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| 68 | /** \internal \returns a reference to the nested matrix */
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| 69 | const _MatrixTypeNested& matrix() const { return m_matrix; }
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| 70 | _MatrixTypeNested& matrix() { return m_matrix.const_cast_derived(); }
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| 71 |
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| 72 | /** \returns an expression of the matrix product between a sparse self-adjoint matrix \c *this and a sparse matrix \a rhs.
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| 73 | *
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| 74 | * Note that there is no algorithmic advantage of performing such a product compared to a general sparse-sparse matrix product.
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| 75 | * Indeed, the SparseSelfadjointView operand is first copied into a temporary SparseMatrix before computing the product.
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| 76 | */
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| 77 | template<typename OtherDerived>
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| 78 | SparseSparseProduct<typename OtherDerived::PlainObject, OtherDerived>
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| 79 | operator*(const SparseMatrixBase<OtherDerived>& rhs) const
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| 80 | {
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| 81 | return SparseSparseProduct<typename OtherDerived::PlainObject, OtherDerived>(*this, rhs.derived());
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| 82 | }
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| 83 |
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| 84 | /** \returns an expression of the matrix product between a sparse matrix \a lhs and a sparse self-adjoint matrix \a rhs.
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| 85 | *
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| 86 | * Note that there is no algorithmic advantage of performing such a product compared to a general sparse-sparse matrix product.
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| 87 | * Indeed, the SparseSelfadjointView operand is first copied into a temporary SparseMatrix before computing the product.
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| 88 | */
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| 89 | template<typename OtherDerived> friend
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| 90 | SparseSparseProduct<OtherDerived, typename OtherDerived::PlainObject >
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| 91 | operator*(const SparseMatrixBase<OtherDerived>& lhs, const SparseSelfAdjointView& rhs)
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| 92 | {
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| 93 | return SparseSparseProduct<OtherDerived, typename OtherDerived::PlainObject>(lhs.derived(), rhs);
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| 94 | }
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| 95 |
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| 96 | /** Efficient sparse self-adjoint matrix times dense vector/matrix product */
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| 97 | template<typename OtherDerived>
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| 98 | SparseSelfAdjointTimeDenseProduct<MatrixType,OtherDerived,UpLo>
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| 99 | operator*(const MatrixBase<OtherDerived>& rhs) const
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| 100 | {
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| 101 | return SparseSelfAdjointTimeDenseProduct<MatrixType,OtherDerived,UpLo>(m_matrix, rhs.derived());
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| 102 | }
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| 103 |
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| 104 | /** Efficient dense vector/matrix times sparse self-adjoint matrix product */
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| 105 | template<typename OtherDerived> friend
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| 106 | DenseTimeSparseSelfAdjointProduct<OtherDerived,MatrixType,UpLo>
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| 107 | operator*(const MatrixBase<OtherDerived>& lhs, const SparseSelfAdjointView& rhs)
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| 108 | {
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| 109 | return DenseTimeSparseSelfAdjointProduct<OtherDerived,_MatrixTypeNested,UpLo>(lhs.derived(), rhs.m_matrix);
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| 110 | }
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| 111 |
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| 112 | /** Perform a symmetric rank K update of the selfadjoint matrix \c *this:
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| 113 | * \f$ this = this + \alpha ( u u^* ) \f$ where \a u is a vector or matrix.
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| 114 | *
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| 115 | * \returns a reference to \c *this
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| 116 | *
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| 117 | * To perform \f$ this = this + \alpha ( u^* u ) \f$ you can simply
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| 118 | * call this function with u.adjoint().
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| 119 | */
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| 120 | template<typename DerivedU>
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| 121 | SparseSelfAdjointView& rankUpdate(const SparseMatrixBase<DerivedU>& u, const Scalar& alpha = Scalar(1));
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| 122 |
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| 123 | /** \internal triggered by sparse_matrix = SparseSelfadjointView; */
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| 124 | template<typename DestScalar,int StorageOrder> void evalTo(SparseMatrix<DestScalar,StorageOrder,Index>& _dest) const
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| 125 | {
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| 126 | internal::permute_symm_to_fullsymm<UpLo>(m_matrix, _dest);
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| 127 | }
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| 128 |
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| 129 | template<typename DestScalar> void evalTo(DynamicSparseMatrix<DestScalar,ColMajor,Index>& _dest) const
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| 130 | {
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| 131 | // TODO directly evaluate into _dest;
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| 132 | SparseMatrix<DestScalar,ColMajor,Index> tmp(_dest.rows(),_dest.cols());
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| 133 | internal::permute_symm_to_fullsymm<UpLo>(m_matrix, tmp);
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| 134 | _dest = tmp;
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| 135 | }
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| 136 |
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| 137 | /** \returns an expression of P H P^-1 */
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| 138 | SparseSymmetricPermutationProduct<_MatrixTypeNested,UpLo> twistedBy(const PermutationMatrix<Dynamic,Dynamic,Index>& perm) const
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| 139 | {
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| 140 | return SparseSymmetricPermutationProduct<_MatrixTypeNested,UpLo>(m_matrix, perm);
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| 141 | }
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| 142 |
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| 143 | template<typename SrcMatrixType,int SrcUpLo>
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| 144 | SparseSelfAdjointView& operator=(const SparseSymmetricPermutationProduct<SrcMatrixType,SrcUpLo>& permutedMatrix)
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| 145 | {
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| 146 | permutedMatrix.evalTo(*this);
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| 147 | return *this;
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| 148 | }
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| 149 |
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| 150 |
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| 151 | SparseSelfAdjointView& operator=(const SparseSelfAdjointView& src)
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| 152 | {
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| 153 | PermutationMatrix<Dynamic> pnull;
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| 154 | return *this = src.twistedBy(pnull);
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| 155 | }
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| 156 |
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| 157 | template<typename SrcMatrixType,unsigned int SrcUpLo>
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| 158 | SparseSelfAdjointView& operator=(const SparseSelfAdjointView<SrcMatrixType,SrcUpLo>& src)
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| 159 | {
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| 160 | PermutationMatrix<Dynamic> pnull;
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| 161 | return *this = src.twistedBy(pnull);
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| 162 | }
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| 163 |
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| 164 |
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| 165 | // const SparseLLT<PlainObject, UpLo> llt() const;
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| 166 | // const SparseLDLT<PlainObject, UpLo> ldlt() const;
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| 167 |
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| 168 | protected:
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| 169 |
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| 170 | typename MatrixType::Nested m_matrix;
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| 171 | mutable VectorI m_countPerRow;
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| 172 | mutable VectorI m_countPerCol;
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| 173 | };
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| 174 |
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| 175 | /***************************************************************************
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| 176 | * Implementation of SparseMatrixBase methods
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| 177 | ***************************************************************************/
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| 178 |
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| 179 | template<typename Derived>
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| 180 | template<unsigned int UpLo>
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| 181 | const SparseSelfAdjointView<Derived, UpLo> SparseMatrixBase<Derived>::selfadjointView() const
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| 182 | {
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| 183 | return derived();
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| 184 | }
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| 185 |
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| 186 | template<typename Derived>
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| 187 | template<unsigned int UpLo>
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| 188 | SparseSelfAdjointView<Derived, UpLo> SparseMatrixBase<Derived>::selfadjointView()
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| 189 | {
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| 190 | return derived();
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| 191 | }
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| 192 |
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| 193 | /***************************************************************************
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| 194 | * Implementation of SparseSelfAdjointView methods
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| 195 | ***************************************************************************/
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| 196 |
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| 197 | template<typename MatrixType, unsigned int UpLo>
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| 198 | template<typename DerivedU>
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| 199 | SparseSelfAdjointView<MatrixType,UpLo>&
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| 200 | SparseSelfAdjointView<MatrixType,UpLo>::rankUpdate(const SparseMatrixBase<DerivedU>& u, const Scalar& alpha)
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| 201 | {
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| 202 | SparseMatrix<Scalar,MatrixType::Flags&RowMajorBit?RowMajor:ColMajor> tmp = u * u.adjoint();
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| 203 | if(alpha==Scalar(0))
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| 204 | m_matrix.const_cast_derived() = tmp.template triangularView<UpLo>();
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| 205 | else
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| 206 | m_matrix.const_cast_derived() += alpha * tmp.template triangularView<UpLo>();
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| 207 |
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| 208 | return *this;
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| 209 | }
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| 210 |
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| 211 | /***************************************************************************
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| 212 | * Implementation of sparse self-adjoint time dense matrix
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| 213 | ***************************************************************************/
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| 214 |
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| 215 | namespace internal {
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| 216 | template<typename Lhs, typename Rhs, int UpLo>
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| 217 | struct traits<SparseSelfAdjointTimeDenseProduct<Lhs,Rhs,UpLo> >
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| 218 | : traits<ProductBase<SparseSelfAdjointTimeDenseProduct<Lhs,Rhs,UpLo>, Lhs, Rhs> >
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| 219 | {
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| 220 | typedef Dense StorageKind;
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| 221 | };
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| 222 | }
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| 223 |
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| 224 | template<typename Lhs, typename Rhs, int UpLo>
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| 225 | class SparseSelfAdjointTimeDenseProduct
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| 226 | : public ProductBase<SparseSelfAdjointTimeDenseProduct<Lhs,Rhs,UpLo>, Lhs, Rhs>
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| 227 | {
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| 228 | public:
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| 229 | EIGEN_PRODUCT_PUBLIC_INTERFACE(SparseSelfAdjointTimeDenseProduct)
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| 230 |
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| 231 | SparseSelfAdjointTimeDenseProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
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| 232 | {}
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| 233 |
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| 234 | template<typename Dest> void scaleAndAddTo(Dest& dest, const Scalar& alpha) const
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| 235 | {
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| 236 | EIGEN_ONLY_USED_FOR_DEBUG(alpha);
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| 237 | // TODO use alpha
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| 238 | eigen_assert(alpha==Scalar(1) && "alpha != 1 is not implemented yet, sorry");
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| 239 | typedef typename internal::remove_all<Lhs>::type _Lhs;
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| 240 | typedef typename _Lhs::InnerIterator LhsInnerIterator;
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| 241 | enum {
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| 242 | LhsIsRowMajor = (_Lhs::Flags&RowMajorBit)==RowMajorBit,
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| 243 | ProcessFirstHalf =
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| 244 | ((UpLo&(Upper|Lower))==(Upper|Lower))
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| 245 | || ( (UpLo&Upper) && !LhsIsRowMajor)
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| 246 | || ( (UpLo&Lower) && LhsIsRowMajor),
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| 247 | ProcessSecondHalf = !ProcessFirstHalf
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| 248 | };
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| 249 | for (Index j=0; j<m_lhs.outerSize(); ++j)
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| 250 | {
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| 251 | LhsInnerIterator i(m_lhs,j);
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| 252 | if (ProcessSecondHalf)
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| 253 | {
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| 254 | while (i && i.index()<j) ++i;
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| 255 | if(i && i.index()==j)
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| 256 | {
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| 257 | dest.row(j) += i.value() * m_rhs.row(j);
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| 258 | ++i;
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| 259 | }
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| 260 | }
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| 261 | for(; (ProcessFirstHalf ? i && i.index() < j : i) ; ++i)
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| 262 | {
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| 263 | Index a = LhsIsRowMajor ? j : i.index();
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| 264 | Index b = LhsIsRowMajor ? i.index() : j;
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| 265 | typename Lhs::Scalar v = i.value();
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| 266 | dest.row(a) += (v) * m_rhs.row(b);
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| 267 | dest.row(b) += numext::conj(v) * m_rhs.row(a);
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| 268 | }
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| 269 | if (ProcessFirstHalf && i && (i.index()==j))
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| 270 | dest.row(j) += i.value() * m_rhs.row(j);
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| 271 | }
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| 272 | }
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| 273 |
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| 274 | private:
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| 275 | SparseSelfAdjointTimeDenseProduct& operator=(const SparseSelfAdjointTimeDenseProduct&);
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| 276 | };
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| 277 |
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| 278 | namespace internal {
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| 279 | template<typename Lhs, typename Rhs, int UpLo>
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| 280 | struct traits<DenseTimeSparseSelfAdjointProduct<Lhs,Rhs,UpLo> >
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| 281 | : traits<ProductBase<DenseTimeSparseSelfAdjointProduct<Lhs,Rhs,UpLo>, Lhs, Rhs> >
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| 282 | {};
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| 283 | }
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| 284 |
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| 285 | template<typename Lhs, typename Rhs, int UpLo>
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| 286 | class DenseTimeSparseSelfAdjointProduct
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| 287 | : public ProductBase<DenseTimeSparseSelfAdjointProduct<Lhs,Rhs,UpLo>, Lhs, Rhs>
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| 288 | {
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| 289 | public:
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| 290 | EIGEN_PRODUCT_PUBLIC_INTERFACE(DenseTimeSparseSelfAdjointProduct)
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| 291 |
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| 292 | DenseTimeSparseSelfAdjointProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
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| 293 | {}
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| 294 |
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| 295 | template<typename Dest> void scaleAndAddTo(Dest& /*dest*/, const Scalar& /*alpha*/) const
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| 296 | {
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| 297 | // TODO
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| 298 | }
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| 299 |
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| 300 | private:
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| 301 | DenseTimeSparseSelfAdjointProduct& operator=(const DenseTimeSparseSelfAdjointProduct&);
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| 302 | };
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| 303 |
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| 304 | /***************************************************************************
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| 305 | * Implementation of symmetric copies and permutations
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| 306 | ***************************************************************************/
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| 307 | namespace internal {
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| 308 |
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| 309 | template<typename MatrixType, int UpLo>
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| 310 | struct traits<SparseSymmetricPermutationProduct<MatrixType,UpLo> > : traits<MatrixType> {
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| 311 | };
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| 312 |
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| 313 | template<int UpLo,typename MatrixType,int DestOrder>
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| 314 | void permute_symm_to_fullsymm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DestOrder,typename MatrixType::Index>& _dest, const typename MatrixType::Index* perm)
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| 315 | {
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| 316 | typedef typename MatrixType::Index Index;
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| 317 | typedef typename MatrixType::Scalar Scalar;
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| 318 | typedef SparseMatrix<Scalar,DestOrder,Index> Dest;
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| 319 | typedef Matrix<Index,Dynamic,1> VectorI;
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| 320 |
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| 321 | Dest& dest(_dest.derived());
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| 322 | enum {
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| 323 | StorageOrderMatch = int(Dest::IsRowMajor) == int(MatrixType::IsRowMajor)
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| 324 | };
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| 325 |
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| 326 | Index size = mat.rows();
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| 327 | VectorI count;
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| 328 | count.resize(size);
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| 329 | count.setZero();
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| 330 | dest.resize(size,size);
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| 331 | for(Index j = 0; j<size; ++j)
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| 332 | {
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| 333 | Index jp = perm ? perm[j] : j;
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| 334 | for(typename MatrixType::InnerIterator it(mat,j); it; ++it)
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| 335 | {
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| 336 | Index i = it.index();
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| 337 | Index r = it.row();
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| 338 | Index c = it.col();
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| 339 | Index ip = perm ? perm[i] : i;
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| 340 | if(UpLo==(Upper|Lower))
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| 341 | count[StorageOrderMatch ? jp : ip]++;
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| 342 | else if(r==c)
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| 343 | count[ip]++;
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| 344 | else if(( UpLo==Lower && r>c) || ( UpLo==Upper && r<c))
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| 345 | {
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| 346 | count[ip]++;
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| 347 | count[jp]++;
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| 348 | }
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| 349 | }
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| 350 | }
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| 351 | Index nnz = count.sum();
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| 352 |
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| 353 | // reserve space
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| 354 | dest.resizeNonZeros(nnz);
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| 355 | dest.outerIndexPtr()[0] = 0;
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| 356 | for(Index j=0; j<size; ++j)
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| 357 | dest.outerIndexPtr()[j+1] = dest.outerIndexPtr()[j] + count[j];
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| 358 | for(Index j=0; j<size; ++j)
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| 359 | count[j] = dest.outerIndexPtr()[j];
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| 360 |
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| 361 | // copy data
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| 362 | for(Index j = 0; j<size; ++j)
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| 363 | {
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| 364 | for(typename MatrixType::InnerIterator it(mat,j); it; ++it)
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| 365 | {
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| 366 | Index i = it.index();
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| 367 | Index r = it.row();
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| 368 | Index c = it.col();
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| 369 |
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| 370 | Index jp = perm ? perm[j] : j;
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| 371 | Index ip = perm ? perm[i] : i;
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| 372 |
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| 373 | if(UpLo==(Upper|Lower))
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| 374 | {
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| 375 | Index k = count[StorageOrderMatch ? jp : ip]++;
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| 376 | dest.innerIndexPtr()[k] = StorageOrderMatch ? ip : jp;
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| 377 | dest.valuePtr()[k] = it.value();
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| 378 | }
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| 379 | else if(r==c)
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| 380 | {
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| 381 | Index k = count[ip]++;
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| 382 | dest.innerIndexPtr()[k] = ip;
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| 383 | dest.valuePtr()[k] = it.value();
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| 384 | }
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| 385 | else if(( (UpLo&Lower)==Lower && r>c) || ( (UpLo&Upper)==Upper && r<c))
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| 386 | {
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| 387 | if(!StorageOrderMatch)
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| 388 | std::swap(ip,jp);
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| 389 | Index k = count[jp]++;
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| 390 | dest.innerIndexPtr()[k] = ip;
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| 391 | dest.valuePtr()[k] = it.value();
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| 392 | k = count[ip]++;
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| 393 | dest.innerIndexPtr()[k] = jp;
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| 394 | dest.valuePtr()[k] = numext::conj(it.value());
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| 395 | }
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| 396 | }
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| 397 | }
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| 398 | }
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| 399 |
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| 400 | template<int _SrcUpLo,int _DstUpLo,typename MatrixType,int DstOrder>
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| 401 | void permute_symm_to_symm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DstOrder,typename MatrixType::Index>& _dest, const typename MatrixType::Index* perm)
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| 402 | {
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| 403 | typedef typename MatrixType::Index Index;
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| 404 | typedef typename MatrixType::Scalar Scalar;
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| 405 | SparseMatrix<Scalar,DstOrder,Index>& dest(_dest.derived());
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| 406 | typedef Matrix<Index,Dynamic,1> VectorI;
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| 407 | enum {
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| 408 | SrcOrder = MatrixType::IsRowMajor ? RowMajor : ColMajor,
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| 409 | StorageOrderMatch = int(SrcOrder) == int(DstOrder),
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| 410 | DstUpLo = DstOrder==RowMajor ? (_DstUpLo==Upper ? Lower : Upper) : _DstUpLo,
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| 411 | SrcUpLo = SrcOrder==RowMajor ? (_SrcUpLo==Upper ? Lower : Upper) : _SrcUpLo
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| 412 | };
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| 413 |
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| 414 | Index size = mat.rows();
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| 415 | VectorI count(size);
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| 416 | count.setZero();
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| 417 | dest.resize(size,size);
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| 418 | for(Index j = 0; j<size; ++j)
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| 419 | {
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| 420 | Index jp = perm ? perm[j] : j;
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| 421 | for(typename MatrixType::InnerIterator it(mat,j); it; ++it)
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| 422 | {
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| 423 | Index i = it.index();
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| 424 | if((int(SrcUpLo)==int(Lower) && i<j) || (int(SrcUpLo)==int(Upper) && i>j))
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| 425 | continue;
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| 426 |
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| 427 | Index ip = perm ? perm[i] : i;
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| 428 | count[int(DstUpLo)==int(Lower) ? (std::min)(ip,jp) : (std::max)(ip,jp)]++;
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| 429 | }
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| 430 | }
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| 431 | dest.outerIndexPtr()[0] = 0;
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| 432 | for(Index j=0; j<size; ++j)
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| 433 | dest.outerIndexPtr()[j+1] = dest.outerIndexPtr()[j] + count[j];
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| 434 | dest.resizeNonZeros(dest.outerIndexPtr()[size]);
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| 435 | for(Index j=0; j<size; ++j)
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| 436 | count[j] = dest.outerIndexPtr()[j];
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| 437 |
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| 438 | for(Index j = 0; j<size; ++j)
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| 439 | {
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| 440 |
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| 441 | for(typename MatrixType::InnerIterator it(mat,j); it; ++it)
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| 442 | {
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| 443 | Index i = it.index();
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| 444 | if((int(SrcUpLo)==int(Lower) && i<j) || (int(SrcUpLo)==int(Upper) && i>j))
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| 445 | continue;
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| 446 |
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| 447 | Index jp = perm ? perm[j] : j;
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| 448 | Index ip = perm? perm[i] : i;
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| 449 |
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| 450 | Index k = count[int(DstUpLo)==int(Lower) ? (std::min)(ip,jp) : (std::max)(ip,jp)]++;
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| 451 | dest.innerIndexPtr()[k] = int(DstUpLo)==int(Lower) ? (std::max)(ip,jp) : (std::min)(ip,jp);
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| 452 |
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| 453 | if(!StorageOrderMatch) std::swap(ip,jp);
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| 454 | if( ((int(DstUpLo)==int(Lower) && ip<jp) || (int(DstUpLo)==int(Upper) && ip>jp)))
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| 455 | dest.valuePtr()[k] = numext::conj(it.value());
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| 456 | else
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| 457 | dest.valuePtr()[k] = it.value();
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| 458 | }
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| 459 | }
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| 460 | }
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| 461 |
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| 462 | }
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| 463 |
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| 464 | template<typename MatrixType,int UpLo>
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| 465 | class SparseSymmetricPermutationProduct
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| 466 | : public EigenBase<SparseSymmetricPermutationProduct<MatrixType,UpLo> >
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| 467 | {
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| 468 | public:
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| 469 | typedef typename MatrixType::Scalar Scalar;
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| 470 | typedef typename MatrixType::Index Index;
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| 471 | protected:
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| 472 | typedef PermutationMatrix<Dynamic,Dynamic,Index> Perm;
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| 473 | public:
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| 474 | typedef Matrix<Index,Dynamic,1> VectorI;
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| 475 | typedef typename MatrixType::Nested MatrixTypeNested;
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| 476 | typedef typename internal::remove_all<MatrixTypeNested>::type _MatrixTypeNested;
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| 477 |
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| 478 | SparseSymmetricPermutationProduct(const MatrixType& mat, const Perm& perm)
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| 479 | : m_matrix(mat), m_perm(perm)
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| 480 | {}
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| 481 |
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| 482 | inline Index rows() const { return m_matrix.rows(); }
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| 483 | inline Index cols() const { return m_matrix.cols(); }
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| 484 |
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| 485 | template<typename DestScalar, int Options, typename DstIndex>
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| 486 | void evalTo(SparseMatrix<DestScalar,Options,DstIndex>& _dest) const
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| 487 | {
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| 488 | // internal::permute_symm_to_fullsymm<UpLo>(m_matrix,_dest,m_perm.indices().data());
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| 489 | SparseMatrix<DestScalar,(Options&RowMajor)==RowMajor ? ColMajor : RowMajor, DstIndex> tmp;
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| 490 | internal::permute_symm_to_fullsymm<UpLo>(m_matrix,tmp,m_perm.indices().data());
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| 491 | _dest = tmp;
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| 492 | }
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| 493 |
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| 494 | template<typename DestType,unsigned int DestUpLo> void evalTo(SparseSelfAdjointView<DestType,DestUpLo>& dest) const
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| 495 | {
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| 496 | internal::permute_symm_to_symm<UpLo,DestUpLo>(m_matrix,dest.matrix(),m_perm.indices().data());
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| 497 | }
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| 498 |
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| 499 | protected:
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| 500 | MatrixTypeNested m_matrix;
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| 501 | const Perm& m_perm;
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| 502 |
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| 503 | };
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| 504 |
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| 505 | } // end namespace Eigen
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| 506 |
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| 507 | #endif // EIGEN_SPARSE_SELFADJOINTVIEW_H
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