| // This file is part of Eigen, a lightweight C++ template library |
| // for linear algebra. |
| // |
| // Copyright (C) 2009-2014 Gael Guennebaud <gael.guennebaud@inria.fr> |
| // |
| // This Source Code Form is subject to the terms of the Mozilla |
| // Public License v. 2.0. If a copy of the MPL was not distributed |
| // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. |
| |
| #ifndef EIGEN_SPARSE_SELFADJOINTVIEW_H |
| #define EIGEN_SPARSE_SELFADJOINTVIEW_H |
| |
| namespace Eigen { |
| |
| /** \ingroup SparseCore_Module |
| * \class SparseSelfAdjointView |
| * |
| * \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 Mode 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() |
| */ |
| namespace internal { |
| |
| template<typename MatrixType, unsigned int Mode> |
| struct traits<SparseSelfAdjointView<MatrixType,Mode> > : traits<MatrixType> { |
| }; |
| |
| template<int SrcMode,int DstMode,typename MatrixType,int DestOrder> |
| void permute_symm_to_symm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DestOrder,typename MatrixType::StorageIndex>& _dest, const typename MatrixType::StorageIndex* perm = 0); |
| |
| template<int Mode,typename MatrixType,int DestOrder> |
| void permute_symm_to_fullsymm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DestOrder,typename MatrixType::StorageIndex>& _dest, const typename MatrixType::StorageIndex* perm = 0); |
| |
| } |
| |
| template<typename MatrixType, unsigned int _Mode> class SparseSelfAdjointView |
| : public EigenBase<SparseSelfAdjointView<MatrixType,_Mode> > |
| { |
| public: |
| |
| enum { |
| Mode = _Mode, |
| TransposeMode = ((Mode & Upper) ? Lower : 0) | ((Mode & Lower) ? Upper : 0), |
| RowsAtCompileTime = internal::traits<SparseSelfAdjointView>::RowsAtCompileTime, |
| ColsAtCompileTime = internal::traits<SparseSelfAdjointView>::ColsAtCompileTime |
| }; |
| |
| typedef EigenBase<SparseSelfAdjointView> Base; |
| typedef typename MatrixType::Scalar Scalar; |
| typedef typename MatrixType::StorageIndex StorageIndex; |
| typedef Matrix<StorageIndex,Dynamic,1> VectorI; |
| typedef typename internal::ref_selector<MatrixType>::non_const_type MatrixTypeNested; |
| typedef typename internal::remove_all<MatrixTypeNested>::type _MatrixTypeNested; |
| |
| explicit inline SparseSelfAdjointView(MatrixType& matrix) : m_matrix(matrix) |
| { |
| eigen_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 _MatrixTypeNested& matrix() const { return m_matrix; } |
| typename internal::remove_reference<MatrixTypeNested>::type& matrix() { return m_matrix; } |
| |
| /** \returns an expression of the matrix product between a sparse self-adjoint matrix \c *this and a sparse matrix \a rhs. |
| * |
| * Note that there is no algorithmic advantage of performing such a product compared to a general sparse-sparse matrix product. |
| * Indeed, the SparseSelfadjointView operand is first copied into a temporary SparseMatrix before computing the product. |
| */ |
| template<typename OtherDerived> |
| Product<SparseSelfAdjointView, OtherDerived> |
| operator*(const SparseMatrixBase<OtherDerived>& rhs) const |
| { |
| return Product<SparseSelfAdjointView, OtherDerived>(*this, rhs.derived()); |
| } |
| |
| /** \returns an expression of the matrix product between a sparse matrix \a lhs and a sparse self-adjoint matrix \a rhs. |
| * |
| * Note that there is no algorithmic advantage of performing such a product compared to a general sparse-sparse matrix product. |
| * Indeed, the SparseSelfadjointView operand is first copied into a temporary SparseMatrix before computing the product. |
| */ |
| template<typename OtherDerived> friend |
| Product<OtherDerived, SparseSelfAdjointView> |
| operator*(const SparseMatrixBase<OtherDerived>& lhs, const SparseSelfAdjointView& rhs) |
| { |
| return Product<OtherDerived, SparseSelfAdjointView>(lhs.derived(), rhs); |
| } |
| |
| /** Efficient sparse self-adjoint matrix times dense vector/matrix product */ |
| template<typename OtherDerived> |
| Product<SparseSelfAdjointView,OtherDerived> |
| operator*(const MatrixBase<OtherDerived>& rhs) const |
| { |
| return Product<SparseSelfAdjointView,OtherDerived>(*this, rhs.derived()); |
| } |
| |
| /** Efficient dense vector/matrix times sparse self-adjoint matrix product */ |
| template<typename OtherDerived> friend |
| Product<OtherDerived,SparseSelfAdjointView> |
| operator*(const MatrixBase<OtherDerived>& lhs, const SparseSelfAdjointView& rhs) |
| { |
| return Product<OtherDerived,SparseSelfAdjointView>(lhs.derived(), rhs); |
| } |
| |
| /** 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 |
| * |
| * To perform \f$ this = this + \alpha ( u^* u ) \f$ you can simply |
| * call this function with u.adjoint(). |
| */ |
| template<typename DerivedU> |
| SparseSelfAdjointView& rankUpdate(const SparseMatrixBase<DerivedU>& u, const Scalar& alpha = Scalar(1)); |
| |
| /** \returns an expression of P H P^-1 */ |
| // TODO implement twists in a more evaluator friendly fashion |
| SparseSymmetricPermutationProduct<_MatrixTypeNested,Mode> twistedBy(const PermutationMatrix<Dynamic,Dynamic,StorageIndex>& perm) const |
| { |
| return SparseSymmetricPermutationProduct<_MatrixTypeNested,Mode>(m_matrix, perm); |
| } |
| |
| template<typename SrcMatrixType,int SrcMode> |
| SparseSelfAdjointView& operator=(const SparseSymmetricPermutationProduct<SrcMatrixType,SrcMode>& permutedMatrix) |
| { |
| internal::call_assignment_no_alias_no_transpose(*this, permutedMatrix); |
| return *this; |
| } |
| |
| SparseSelfAdjointView& operator=(const SparseSelfAdjointView& src) |
| { |
| PermutationMatrix<Dynamic,Dynamic,StorageIndex> pnull; |
| return *this = src.twistedBy(pnull); |
| } |
| |
| // Since we override the copy-assignment operator, we need to explicitly re-declare the copy-constructor |
| EIGEN_DEFAULT_COPY_CONSTRUCTOR(SparseSelfAdjointView) |
| |
| template<typename SrcMatrixType,unsigned int SrcMode> |
| SparseSelfAdjointView& operator=(const SparseSelfAdjointView<SrcMatrixType,SrcMode>& src) |
| { |
| PermutationMatrix<Dynamic,Dynamic,StorageIndex> pnull; |
| return *this = src.twistedBy(pnull); |
| } |
| |
| void resize(Index rows, Index cols) |
| { |
| EIGEN_ONLY_USED_FOR_DEBUG(rows); |
| EIGEN_ONLY_USED_FOR_DEBUG(cols); |
| eigen_assert(rows == this->rows() && cols == this->cols() |
| && "SparseSelfadjointView::resize() does not actually allow to resize."); |
| } |
| |
| protected: |
| |
| MatrixTypeNested m_matrix; |
| //mutable VectorI m_countPerRow; |
| //mutable VectorI m_countPerCol; |
| private: |
| template<typename Dest> void evalTo(Dest &) const; |
| }; |
| |
| /*************************************************************************** |
| * Implementation of SparseMatrixBase methods |
| ***************************************************************************/ |
| |
| template<typename Derived> |
| template<unsigned int UpLo> |
| typename SparseMatrixBase<Derived>::template ConstSelfAdjointViewReturnType<UpLo>::Type SparseMatrixBase<Derived>::selfadjointView() const |
| { |
| return SparseSelfAdjointView<const Derived, UpLo>(derived()); |
| } |
| |
| template<typename Derived> |
| template<unsigned int UpLo> |
| typename SparseMatrixBase<Derived>::template SelfAdjointViewReturnType<UpLo>::Type SparseMatrixBase<Derived>::selfadjointView() |
| { |
| return SparseSelfAdjointView<Derived, UpLo>(derived()); |
| } |
| |
| /*************************************************************************** |
| * Implementation of SparseSelfAdjointView methods |
| ***************************************************************************/ |
| |
| template<typename MatrixType, unsigned int Mode> |
| template<typename DerivedU> |
| SparseSelfAdjointView<MatrixType,Mode>& |
| SparseSelfAdjointView<MatrixType,Mode>::rankUpdate(const SparseMatrixBase<DerivedU>& u, const Scalar& alpha) |
| { |
| SparseMatrix<Scalar,(MatrixType::Flags&RowMajorBit)?RowMajor:ColMajor> tmp = u * u.adjoint(); |
| if(alpha==Scalar(0)) |
| m_matrix = tmp.template triangularView<Mode>(); |
| else |
| m_matrix += alpha * tmp.template triangularView<Mode>(); |
| |
| return *this; |
| } |
| |
| namespace internal { |
| |
| // TODO currently a selfadjoint expression has the form SelfAdjointView<.,.> |
| // in the future selfadjoint-ness should be defined by the expression traits |
| // such that Transpose<SelfAdjointView<.,.> > is valid. (currently TriangularBase::transpose() is overloaded to make it work) |
| template<typename MatrixType, unsigned int Mode> |
| struct evaluator_traits<SparseSelfAdjointView<MatrixType,Mode> > |
| { |
| typedef typename storage_kind_to_evaluator_kind<typename MatrixType::StorageKind>::Kind Kind; |
| typedef SparseSelfAdjointShape Shape; |
| }; |
| |
| struct SparseSelfAdjoint2Sparse {}; |
| |
| template<> struct AssignmentKind<SparseShape,SparseSelfAdjointShape> { typedef SparseSelfAdjoint2Sparse Kind; }; |
| template<> struct AssignmentKind<SparseSelfAdjointShape,SparseShape> { typedef Sparse2Sparse Kind; }; |
| |
| template< typename DstXprType, typename SrcXprType, typename Functor> |
| struct Assignment<DstXprType, SrcXprType, Functor, SparseSelfAdjoint2Sparse> |
| { |
| typedef typename DstXprType::StorageIndex StorageIndex; |
| typedef internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> AssignOpType; |
| |
| template<typename DestScalar,int StorageOrder> |
| static void run(SparseMatrix<DestScalar,StorageOrder,StorageIndex> &dst, const SrcXprType &src, const AssignOpType&/*func*/) |
| { |
| internal::permute_symm_to_fullsymm<SrcXprType::Mode>(src.matrix(), dst); |
| } |
| |
| // FIXME: the handling of += and -= in sparse matrices should be cleanup so that next two overloads could be reduced to: |
| template<typename DestScalar,int StorageOrder,typename AssignFunc> |
| static void run(SparseMatrix<DestScalar,StorageOrder,StorageIndex> &dst, const SrcXprType &src, const AssignFunc& func) |
| { |
| SparseMatrix<DestScalar,StorageOrder,StorageIndex> tmp(src.rows(),src.cols()); |
| run(tmp, src, AssignOpType()); |
| call_assignment_no_alias_no_transpose(dst, tmp, func); |
| } |
| |
| template<typename DestScalar,int StorageOrder> |
| static void run(SparseMatrix<DestScalar,StorageOrder,StorageIndex> &dst, const SrcXprType &src, |
| const internal::add_assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar>& /* func */) |
| { |
| SparseMatrix<DestScalar,StorageOrder,StorageIndex> tmp(src.rows(),src.cols()); |
| run(tmp, src, AssignOpType()); |
| dst += tmp; |
| } |
| |
| template<typename DestScalar,int StorageOrder> |
| static void run(SparseMatrix<DestScalar,StorageOrder,StorageIndex> &dst, const SrcXprType &src, |
| const internal::sub_assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar>& /* func */) |
| { |
| SparseMatrix<DestScalar,StorageOrder,StorageIndex> tmp(src.rows(),src.cols()); |
| run(tmp, src, AssignOpType()); |
| dst -= tmp; |
| } |
| |
| template<typename DestScalar> |
| static void run(DynamicSparseMatrix<DestScalar,ColMajor,StorageIndex>& dst, const SrcXprType &src, const AssignOpType&/*func*/) |
| { |
| // TODO directly evaluate into dst; |
| SparseMatrix<DestScalar,ColMajor,StorageIndex> tmp(dst.rows(),dst.cols()); |
| internal::permute_symm_to_fullsymm<SrcXprType::Mode>(src.matrix(), tmp); |
| dst = tmp; |
| } |
| }; |
| |
| } // end namespace internal |
| |
| /*************************************************************************** |
| * Implementation of sparse self-adjoint time dense matrix |
| ***************************************************************************/ |
| |
| namespace internal { |
| |
| template<int Mode, typename SparseLhsType, typename DenseRhsType, typename DenseResType, typename AlphaType> |
| inline void sparse_selfadjoint_time_dense_product(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, const AlphaType& alpha) |
| { |
| EIGEN_ONLY_USED_FOR_DEBUG(alpha); |
| |
| typedef typename internal::nested_eval<SparseLhsType,DenseRhsType::MaxColsAtCompileTime>::type SparseLhsTypeNested; |
| typedef typename internal::remove_all<SparseLhsTypeNested>::type SparseLhsTypeNestedCleaned; |
| typedef evaluator<SparseLhsTypeNestedCleaned> LhsEval; |
| typedef typename LhsEval::InnerIterator LhsIterator; |
| typedef typename SparseLhsType::Scalar LhsScalar; |
| |
| enum { |
| LhsIsRowMajor = (LhsEval::Flags&RowMajorBit)==RowMajorBit, |
| ProcessFirstHalf = |
| ((Mode&(Upper|Lower))==(Upper|Lower)) |
| || ( (Mode&Upper) && !LhsIsRowMajor) |
| || ( (Mode&Lower) && LhsIsRowMajor), |
| ProcessSecondHalf = !ProcessFirstHalf |
| }; |
| |
| SparseLhsTypeNested lhs_nested(lhs); |
| LhsEval lhsEval(lhs_nested); |
| |
| // work on one column at once |
| for (Index k=0; k<rhs.cols(); ++k) |
| { |
| for (Index j=0; j<lhs.outerSize(); ++j) |
| { |
| LhsIterator i(lhsEval,j); |
| // handle diagonal coeff |
| if (ProcessSecondHalf) |
| { |
| while (i && i.index()<j) ++i; |
| if(i && i.index()==j) |
| { |
| res.coeffRef(j,k) += alpha * i.value() * rhs.coeff(j,k); |
| ++i; |
| } |
| } |
| |
| // premultiplied rhs for scatters |
| typename ScalarBinaryOpTraits<AlphaType, typename DenseRhsType::Scalar>::ReturnType rhs_j(alpha*rhs(j,k)); |
| // accumulator for partial scalar product |
| typename DenseResType::Scalar res_j(0); |
| for(; (ProcessFirstHalf ? i && i.index() < j : i) ; ++i) |
| { |
| LhsScalar lhs_ij = i.value(); |
| if(!LhsIsRowMajor) lhs_ij = numext::conj(lhs_ij); |
| res_j += lhs_ij * rhs.coeff(i.index(),k); |
| res(i.index(),k) += numext::conj(lhs_ij) * rhs_j; |
| } |
| res.coeffRef(j,k) += alpha * res_j; |
| |
| // handle diagonal coeff |
| if (ProcessFirstHalf && i && (i.index()==j)) |
| res.coeffRef(j,k) += alpha * i.value() * rhs.coeff(j,k); |
| } |
| } |
| } |
| |
| |
| template<typename LhsView, typename Rhs, int ProductType> |
| struct generic_product_impl<LhsView, Rhs, SparseSelfAdjointShape, DenseShape, ProductType> |
| : generic_product_impl_base<LhsView, Rhs, generic_product_impl<LhsView, Rhs, SparseSelfAdjointShape, DenseShape, ProductType> > |
| { |
| template<typename Dest> |
| static void scaleAndAddTo(Dest& dst, const LhsView& lhsView, const Rhs& rhs, const typename Dest::Scalar& alpha) |
| { |
| typedef typename LhsView::_MatrixTypeNested Lhs; |
| typedef typename nested_eval<Lhs,Dynamic>::type LhsNested; |
| typedef typename nested_eval<Rhs,Dynamic>::type RhsNested; |
| LhsNested lhsNested(lhsView.matrix()); |
| RhsNested rhsNested(rhs); |
| |
| internal::sparse_selfadjoint_time_dense_product<LhsView::Mode>(lhsNested, rhsNested, dst, alpha); |
| } |
| }; |
| |
| template<typename Lhs, typename RhsView, int ProductType> |
| struct generic_product_impl<Lhs, RhsView, DenseShape, SparseSelfAdjointShape, ProductType> |
| : generic_product_impl_base<Lhs, RhsView, generic_product_impl<Lhs, RhsView, DenseShape, SparseSelfAdjointShape, ProductType> > |
| { |
| template<typename Dest> |
| static void scaleAndAddTo(Dest& dst, const Lhs& lhs, const RhsView& rhsView, const typename Dest::Scalar& alpha) |
| { |
| typedef typename RhsView::_MatrixTypeNested Rhs; |
| typedef typename nested_eval<Lhs,Dynamic>::type LhsNested; |
| typedef typename nested_eval<Rhs,Dynamic>::type RhsNested; |
| LhsNested lhsNested(lhs); |
| RhsNested rhsNested(rhsView.matrix()); |
| |
| // transpose everything |
| Transpose<Dest> dstT(dst); |
| internal::sparse_selfadjoint_time_dense_product<RhsView::TransposeMode>(rhsNested.transpose(), lhsNested.transpose(), dstT, alpha); |
| } |
| }; |
| |
| // NOTE: these two overloads are needed to evaluate the sparse selfadjoint view into a full sparse matrix |
| // TODO: maybe the copy could be handled by generic_product_impl so that these overloads would not be needed anymore |
| |
| template<typename LhsView, typename Rhs, int ProductTag> |
| struct product_evaluator<Product<LhsView, Rhs, DefaultProduct>, ProductTag, SparseSelfAdjointShape, SparseShape> |
| : public evaluator<typename Product<typename Rhs::PlainObject, Rhs, DefaultProduct>::PlainObject> |
| { |
| typedef Product<LhsView, Rhs, DefaultProduct> XprType; |
| typedef typename XprType::PlainObject PlainObject; |
| typedef evaluator<PlainObject> Base; |
| |
| product_evaluator(const XprType& xpr) |
| : m_lhs(xpr.lhs()), m_result(xpr.rows(), xpr.cols()) |
| { |
| ::new (static_cast<Base*>(this)) Base(m_result); |
| generic_product_impl<typename Rhs::PlainObject, Rhs, SparseShape, SparseShape, ProductTag>::evalTo(m_result, m_lhs, xpr.rhs()); |
| } |
| |
| protected: |
| typename Rhs::PlainObject m_lhs; |
| PlainObject m_result; |
| }; |
| |
| template<typename Lhs, typename RhsView, int ProductTag> |
| struct product_evaluator<Product<Lhs, RhsView, DefaultProduct>, ProductTag, SparseShape, SparseSelfAdjointShape> |
| : public evaluator<typename Product<Lhs, typename Lhs::PlainObject, DefaultProduct>::PlainObject> |
| { |
| typedef Product<Lhs, RhsView, DefaultProduct> XprType; |
| typedef typename XprType::PlainObject PlainObject; |
| typedef evaluator<PlainObject> Base; |
| |
| product_evaluator(const XprType& xpr) |
| : m_rhs(xpr.rhs()), m_result(xpr.rows(), xpr.cols()) |
| { |
| ::new (static_cast<Base*>(this)) Base(m_result); |
| generic_product_impl<Lhs, typename Lhs::PlainObject, SparseShape, SparseShape, ProductTag>::evalTo(m_result, xpr.lhs(), m_rhs); |
| } |
| |
| protected: |
| typename Lhs::PlainObject m_rhs; |
| PlainObject m_result; |
| }; |
| |
| } // namespace internal |
| |
| /*************************************************************************** |
| * Implementation of symmetric copies and permutations |
| ***************************************************************************/ |
| namespace internal { |
| |
| template<int Mode,typename MatrixType,int DestOrder> |
| void permute_symm_to_fullsymm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DestOrder,typename MatrixType::StorageIndex>& _dest, const typename MatrixType::StorageIndex* perm) |
| { |
| typedef typename MatrixType::StorageIndex StorageIndex; |
| typedef typename MatrixType::Scalar Scalar; |
| typedef SparseMatrix<Scalar,DestOrder,StorageIndex> Dest; |
| typedef Matrix<StorageIndex,Dynamic,1> VectorI; |
| typedef evaluator<MatrixType> MatEval; |
| typedef typename evaluator<MatrixType>::InnerIterator MatIterator; |
| |
| MatEval matEval(mat); |
| Dest& dest(_dest.derived()); |
| enum { |
| StorageOrderMatch = int(Dest::IsRowMajor) == int(MatrixType::IsRowMajor) |
| }; |
| |
| Index size = mat.rows(); |
| VectorI count; |
| count.resize(size); |
| count.setZero(); |
| dest.resize(size,size); |
| for(Index j = 0; j<size; ++j) |
| { |
| Index jp = perm ? perm[j] : j; |
| for(MatIterator it(matEval,j); it; ++it) |
| { |
| Index i = it.index(); |
| Index r = it.row(); |
| Index c = it.col(); |
| Index ip = perm ? perm[i] : i; |
| if(Mode==int(Upper|Lower)) |
| count[StorageOrderMatch ? jp : ip]++; |
| else if(r==c) |
| count[ip]++; |
| else if(( Mode==Lower && r>c) || ( Mode==Upper && r<c)) |
| { |
| count[ip]++; |
| count[jp]++; |
| } |
| } |
| } |
| Index nnz = count.sum(); |
| |
| // reserve space |
| dest.resizeNonZeros(nnz); |
| dest.outerIndexPtr()[0] = 0; |
| for(Index j=0; j<size; ++j) |
| dest.outerIndexPtr()[j+1] = dest.outerIndexPtr()[j] + count[j]; |
| for(Index j=0; j<size; ++j) |
| count[j] = dest.outerIndexPtr()[j]; |
| |
| // copy data |
| for(StorageIndex j = 0; j<size; ++j) |
| { |
| for(MatIterator it(matEval,j); it; ++it) |
| { |
| StorageIndex i = internal::convert_index<StorageIndex>(it.index()); |
| Index r = it.row(); |
| Index c = it.col(); |
| |
| StorageIndex jp = perm ? perm[j] : j; |
| StorageIndex ip = perm ? perm[i] : i; |
| |
| if(Mode==int(Upper|Lower)) |
| { |
| Index k = count[StorageOrderMatch ? jp : ip]++; |
| dest.innerIndexPtr()[k] = StorageOrderMatch ? ip : jp; |
| dest.valuePtr()[k] = it.value(); |
| } |
| else if(r==c) |
| { |
| Index k = count[ip]++; |
| dest.innerIndexPtr()[k] = ip; |
| dest.valuePtr()[k] = it.value(); |
| } |
| else if(( (Mode&Lower)==Lower && r>c) || ( (Mode&Upper)==Upper && r<c)) |
| { |
| if(!StorageOrderMatch) |
| std::swap(ip,jp); |
| Index k = count[jp]++; |
| dest.innerIndexPtr()[k] = ip; |
| dest.valuePtr()[k] = it.value(); |
| k = count[ip]++; |
| dest.innerIndexPtr()[k] = jp; |
| dest.valuePtr()[k] = numext::conj(it.value()); |
| } |
| } |
| } |
| } |
| |
| template<int _SrcMode,int _DstMode,typename MatrixType,int DstOrder> |
| void permute_symm_to_symm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DstOrder,typename MatrixType::StorageIndex>& _dest, const typename MatrixType::StorageIndex* perm) |
| { |
| typedef typename MatrixType::StorageIndex StorageIndex; |
| typedef typename MatrixType::Scalar Scalar; |
| SparseMatrix<Scalar,DstOrder,StorageIndex>& dest(_dest.derived()); |
| typedef Matrix<StorageIndex,Dynamic,1> VectorI; |
| typedef evaluator<MatrixType> MatEval; |
| typedef typename evaluator<MatrixType>::InnerIterator MatIterator; |
| |
| enum { |
| SrcOrder = MatrixType::IsRowMajor ? RowMajor : ColMajor, |
| StorageOrderMatch = int(SrcOrder) == int(DstOrder), |
| DstMode = DstOrder==RowMajor ? (_DstMode==Upper ? Lower : Upper) : _DstMode, |
| SrcMode = SrcOrder==RowMajor ? (_SrcMode==Upper ? Lower : Upper) : _SrcMode |
| }; |
| |
| MatEval matEval(mat); |
| |
| Index size = mat.rows(); |
| VectorI count(size); |
| count.setZero(); |
| dest.resize(size,size); |
| for(StorageIndex j = 0; j<size; ++j) |
| { |
| StorageIndex jp = perm ? perm[j] : j; |
| for(MatIterator it(matEval,j); it; ++it) |
| { |
| StorageIndex i = it.index(); |
| if((int(SrcMode)==int(Lower) && i<j) || (int(SrcMode)==int(Upper) && i>j)) |
| continue; |
| |
| StorageIndex ip = perm ? perm[i] : i; |
| count[int(DstMode)==int(Lower) ? (std::min)(ip,jp) : (std::max)(ip,jp)]++; |
| } |
| } |
| dest.outerIndexPtr()[0] = 0; |
| for(Index j=0; j<size; ++j) |
| dest.outerIndexPtr()[j+1] = dest.outerIndexPtr()[j] + count[j]; |
| dest.resizeNonZeros(dest.outerIndexPtr()[size]); |
| for(Index j=0; j<size; ++j) |
| count[j] = dest.outerIndexPtr()[j]; |
| |
| for(StorageIndex j = 0; j<size; ++j) |
| { |
| |
| for(MatIterator it(matEval,j); it; ++it) |
| { |
| StorageIndex i = it.index(); |
| if((int(SrcMode)==int(Lower) && i<j) || (int(SrcMode)==int(Upper) && i>j)) |
| continue; |
| |
| StorageIndex jp = perm ? perm[j] : j; |
| StorageIndex ip = perm? perm[i] : i; |
| |
| Index k = count[int(DstMode)==int(Lower) ? (std::min)(ip,jp) : (std::max)(ip,jp)]++; |
| dest.innerIndexPtr()[k] = int(DstMode)==int(Lower) ? (std::max)(ip,jp) : (std::min)(ip,jp); |
| |
| if(!StorageOrderMatch) std::swap(ip,jp); |
| if( ((int(DstMode)==int(Lower) && ip<jp) || (int(DstMode)==int(Upper) && ip>jp))) |
| dest.valuePtr()[k] = numext::conj(it.value()); |
| else |
| dest.valuePtr()[k] = it.value(); |
| } |
| } |
| } |
| |
| } |
| |
| // TODO implement twists in a more evaluator friendly fashion |
| |
| namespace internal { |
| |
| template<typename MatrixType, int Mode> |
| struct traits<SparseSymmetricPermutationProduct<MatrixType,Mode> > : traits<MatrixType> { |
| }; |
| |
| } |
| |
| template<typename MatrixType,int Mode> |
| class SparseSymmetricPermutationProduct |
| : public EigenBase<SparseSymmetricPermutationProduct<MatrixType,Mode> > |
| { |
| public: |
| typedef typename MatrixType::Scalar Scalar; |
| typedef typename MatrixType::StorageIndex StorageIndex; |
| enum { |
| RowsAtCompileTime = internal::traits<SparseSymmetricPermutationProduct>::RowsAtCompileTime, |
| ColsAtCompileTime = internal::traits<SparseSymmetricPermutationProduct>::ColsAtCompileTime |
| }; |
| protected: |
| typedef PermutationMatrix<Dynamic,Dynamic,StorageIndex> Perm; |
| public: |
| typedef Matrix<StorageIndex,Dynamic,1> VectorI; |
| typedef typename MatrixType::Nested MatrixTypeNested; |
| typedef typename internal::remove_all<MatrixTypeNested>::type NestedExpression; |
| |
| SparseSymmetricPermutationProduct(const MatrixType& mat, const Perm& perm) |
| : m_matrix(mat), m_perm(perm) |
| {} |
| |
| inline Index rows() const { return m_matrix.rows(); } |
| inline Index cols() const { return m_matrix.cols(); } |
| |
| const NestedExpression& matrix() const { return m_matrix; } |
| const Perm& perm() const { return m_perm; } |
| |
| protected: |
| MatrixTypeNested m_matrix; |
| const Perm& m_perm; |
| |
| }; |
| |
| namespace internal { |
| |
| template<typename DstXprType, typename MatrixType, int Mode, typename Scalar> |
| struct Assignment<DstXprType, SparseSymmetricPermutationProduct<MatrixType,Mode>, internal::assign_op<Scalar,typename MatrixType::Scalar>, Sparse2Sparse> |
| { |
| typedef SparseSymmetricPermutationProduct<MatrixType,Mode> SrcXprType; |
| typedef typename DstXprType::StorageIndex DstIndex; |
| template<int Options> |
| static void run(SparseMatrix<Scalar,Options,DstIndex> &dst, const SrcXprType &src, const internal::assign_op<Scalar,typename MatrixType::Scalar> &) |
| { |
| // internal::permute_symm_to_fullsymm<Mode>(m_matrix,_dest,m_perm.indices().data()); |
| SparseMatrix<Scalar,(Options&RowMajor)==RowMajor ? ColMajor : RowMajor, DstIndex> tmp; |
| internal::permute_symm_to_fullsymm<Mode>(src.matrix(),tmp,src.perm().indices().data()); |
| dst = tmp; |
| } |
| |
| template<typename DestType,unsigned int DestMode> |
| static void run(SparseSelfAdjointView<DestType,DestMode>& dst, const SrcXprType &src, const internal::assign_op<Scalar,typename MatrixType::Scalar> &) |
| { |
| internal::permute_symm_to_symm<Mode,DestMode>(src.matrix(),dst.matrix(),src.perm().indices().data()); |
| } |
| }; |
| |
| } // end namespace internal |
| |
| } // end namespace Eigen |
| |
| #endif // EIGEN_SPARSE_SELFADJOINTVIEW_H |
