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Diffstat (limited to 'extern/Eigen3/Eigen/src/Sparse/SparseSelfAdjointView.h')
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diff --git a/extern/Eigen3/Eigen/src/Sparse/SparseSelfAdjointView.h b/extern/Eigen3/Eigen/src/Sparse/SparseSelfAdjointView.h new file mode 100644 index 00000000000..d82044c789c --- /dev/null +++ b/extern/Eigen3/Eigen/src/Sparse/SparseSelfAdjointView.h @@ -0,0 +1,454 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr> +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see <http://www.gnu.org/licenses/>. + +#ifndef EIGEN_SPARSE_SELFADJOINTVIEW_H +#define EIGEN_SPARSE_SELFADJOINTVIEW_H + +/** \class SparseSelfAdjointView + * + * + * \brief Pseudo expression to manipulate a triangular sparse matrix as a selfadjoint matrix. + * + * \param MatrixType the type of the dense matrix storing the coefficients + * \param UpLo can be either \c #Lower or \c #Upper + * + * This class is an expression of a sefladjoint matrix from a triangular part of a matrix + * with given dense storage of the coefficients. It is the return type of MatrixBase::selfadjointView() + * and most of the time this is the only way that it is used. + * + * \sa SparseMatrixBase::selfadjointView() + */ +template<typename Lhs, typename Rhs, int UpLo> +class SparseSelfAdjointTimeDenseProduct; + +template<typename Lhs, typename Rhs, int UpLo> +class DenseTimeSparseSelfAdjointProduct; + +template<typename MatrixType,int UpLo> +class SparseSymmetricPermutationProduct; + +namespace internal { + +template<typename MatrixType, unsigned int UpLo> +struct traits<SparseSelfAdjointView<MatrixType,UpLo> > : traits<MatrixType> { +}; + +template<int SrcUpLo,int DstUpLo,typename MatrixType,int DestOrder> +void permute_symm_to_symm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DestOrder,typename MatrixType::Index>& _dest, const typename MatrixType::Index* perm = 0); + +template<int UpLo,typename MatrixType,int DestOrder> +void permute_symm_to_fullsymm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DestOrder,typename MatrixType::Index>& _dest, const typename MatrixType::Index* perm = 0); + +} + +template<typename MatrixType, unsigned int UpLo> class SparseSelfAdjointView + : public EigenBase<SparseSelfAdjointView<MatrixType,UpLo> > +{ + public: + + typedef typename MatrixType::Scalar Scalar; + typedef typename MatrixType::Index Index; + typedef Matrix<Index,Dynamic,1> VectorI; + typedef typename MatrixType::Nested MatrixTypeNested; + typedef typename internal::remove_all<MatrixTypeNested>::type _MatrixTypeNested; + + inline SparseSelfAdjointView(const 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; } + _MatrixTypeNested& matrix() { return m_matrix.const_cast_derived(); } + + /** Efficient sparse self-adjoint matrix times dense vector/matrix product */ + template<typename OtherDerived> + SparseSelfAdjointTimeDenseProduct<MatrixType,OtherDerived,UpLo> + operator*(const MatrixBase<OtherDerived>& rhs) const + { + return SparseSelfAdjointTimeDenseProduct<MatrixType,OtherDerived,UpLo>(m_matrix, rhs.derived()); + } + + /** Efficient dense vector/matrix times sparse self-adjoint matrix product */ + template<typename OtherDerived> friend + DenseTimeSparseSelfAdjointProduct<OtherDerived,MatrixType,UpLo> + operator*(const MatrixBase<OtherDerived>& lhs, const SparseSelfAdjointView& rhs) + { + return DenseTimeSparseSelfAdjointProduct<OtherDerived,_MatrixTypeNested,UpLo>(lhs.derived(), rhs.m_matrix); + } + + /** Perform a symmetric rank K update of the selfadjoint matrix \c *this: + * \f$ this = this + \alpha ( u u^* ) \f$ where \a u is a vector or matrix. + * + * \returns a reference to \c *this + * + * Note that it is faster to set alpha=0 than initializing the matrix to zero + * and then keep the default value alpha=1. + * + * To perform \f$ this = this + \alpha ( u^* u ) \f$ you can simply + * call this function with u.adjoint(). + */ + template<typename DerivedU> + SparseSelfAdjointView& rankUpdate(const SparseMatrixBase<DerivedU>& u, Scalar alpha = Scalar(1)); + + /** \internal triggered by sparse_matrix = SparseSelfadjointView; */ + template<typename DestScalar> void evalTo(SparseMatrix<DestScalar>& _dest) const + { + internal::permute_symm_to_fullsymm<UpLo>(m_matrix, _dest); + } + + template<typename DestScalar> void evalTo(DynamicSparseMatrix<DestScalar>& _dest) const + { + // TODO directly evaluate into _dest; + SparseMatrix<DestScalar> tmp(_dest.rows(),_dest.cols()); + internal::permute_symm_to_fullsymm<UpLo>(m_matrix, tmp); + _dest = tmp; + } + + /** \returns an expression of P^-1 H P */ + SparseSymmetricPermutationProduct<_MatrixTypeNested,UpLo> twistedBy(const PermutationMatrix<Dynamic>& perm) const + { + return SparseSymmetricPermutationProduct<_MatrixTypeNested,UpLo>(m_matrix, perm); + } + + template<typename SrcMatrixType,int SrcUpLo> + SparseSelfAdjointView& operator=(const SparseSymmetricPermutationProduct<SrcMatrixType,SrcUpLo>& permutedMatrix) + { + permutedMatrix.evalTo(*this); + return *this; + } + + + // const SparseLLT<PlainObject, UpLo> llt() const; + // const SparseLDLT<PlainObject, UpLo> ldlt() const; + + protected: + + const typename MatrixType::Nested m_matrix; + mutable VectorI m_countPerRow; + mutable VectorI m_countPerCol; +}; + +/*************************************************************************** +* Implementation of SparseMatrixBase methods +***************************************************************************/ + +template<typename Derived> +template<unsigned int UpLo> +const SparseSelfAdjointView<Derived, UpLo> SparseMatrixBase<Derived>::selfadjointView() const +{ + return derived(); +} + +template<typename Derived> +template<unsigned int UpLo> +SparseSelfAdjointView<Derived, UpLo> SparseMatrixBase<Derived>::selfadjointView() +{ + return derived(); +} + +/*************************************************************************** +* Implementation of SparseSelfAdjointView methods +***************************************************************************/ + +template<typename MatrixType, unsigned int UpLo> +template<typename DerivedU> +SparseSelfAdjointView<MatrixType,UpLo>& +SparseSelfAdjointView<MatrixType,UpLo>::rankUpdate(const SparseMatrixBase<DerivedU>& u, Scalar alpha) +{ + SparseMatrix<Scalar,MatrixType::Flags&RowMajorBit?RowMajor:ColMajor> tmp = u * u.adjoint(); + if(alpha==Scalar(0)) + m_matrix.const_cast_derived() = tmp.template triangularView<UpLo>(); + else + m_matrix.const_cast_derived() += alpha * tmp.template triangularView<UpLo>(); + + return *this; +} + +/*************************************************************************** +* Implementation of sparse self-adjoint time dense matrix +***************************************************************************/ + +namespace internal { +template<typename Lhs, typename Rhs, int UpLo> +struct traits<SparseSelfAdjointTimeDenseProduct<Lhs,Rhs,UpLo> > + : traits<ProductBase<SparseSelfAdjointTimeDenseProduct<Lhs,Rhs,UpLo>, Lhs, Rhs> > +{ + typedef Dense StorageKind; +}; +} + +template<typename Lhs, typename Rhs, int UpLo> +class SparseSelfAdjointTimeDenseProduct + : public ProductBase<SparseSelfAdjointTimeDenseProduct<Lhs,Rhs,UpLo>, Lhs, Rhs> +{ + public: + EIGEN_PRODUCT_PUBLIC_INTERFACE(SparseSelfAdjointTimeDenseProduct) + + SparseSelfAdjointTimeDenseProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs) + {} + + template<typename Dest> void scaleAndAddTo(Dest& dest, Scalar alpha) const + { + // TODO use alpha + eigen_assert(alpha==Scalar(1) && "alpha != 1 is not implemented yet, sorry"); + typedef typename internal::remove_all<Lhs>::type _Lhs; + typedef typename internal::remove_all<Rhs>::type _Rhs; + typedef typename _Lhs::InnerIterator LhsInnerIterator; + enum { + LhsIsRowMajor = (_Lhs::Flags&RowMajorBit)==RowMajorBit, + ProcessFirstHalf = + ((UpLo&(Upper|Lower))==(Upper|Lower)) + || ( (UpLo&Upper) && !LhsIsRowMajor) + || ( (UpLo&Lower) && LhsIsRowMajor), + ProcessSecondHalf = !ProcessFirstHalf + }; + for (Index j=0; j<m_lhs.outerSize(); ++j) + { + LhsInnerIterator i(m_lhs,j); + if (ProcessSecondHalf && i && (i.index()==j)) + { + dest.row(j) += i.value() * m_rhs.row(j); + ++i; + } + Block<Dest,1,Dest::ColsAtCompileTime> dest_j(dest.row(LhsIsRowMajor ? j : 0)); + for(; (ProcessFirstHalf ? i && i.index() < j : i) ; ++i) + { + Index a = LhsIsRowMajor ? j : i.index(); + Index b = LhsIsRowMajor ? i.index() : j; + typename Lhs::Scalar v = i.value(); + dest.row(a) += (v) * m_rhs.row(b); + dest.row(b) += internal::conj(v) * m_rhs.row(a); + } + if (ProcessFirstHalf && i && (i.index()==j)) + dest.row(j) += i.value() * m_rhs.row(j); + } + } + + private: + SparseSelfAdjointTimeDenseProduct& operator=(const SparseSelfAdjointTimeDenseProduct&); +}; + +namespace internal { +template<typename Lhs, typename Rhs, int UpLo> +struct traits<DenseTimeSparseSelfAdjointProduct<Lhs,Rhs,UpLo> > + : traits<ProductBase<DenseTimeSparseSelfAdjointProduct<Lhs,Rhs,UpLo>, Lhs, Rhs> > +{}; +} + +template<typename Lhs, typename Rhs, int UpLo> +class DenseTimeSparseSelfAdjointProduct + : public ProductBase<DenseTimeSparseSelfAdjointProduct<Lhs,Rhs,UpLo>, Lhs, Rhs> +{ + public: + EIGEN_PRODUCT_PUBLIC_INTERFACE(DenseTimeSparseSelfAdjointProduct) + + DenseTimeSparseSelfAdjointProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs) + {} + + template<typename Dest> void scaleAndAddTo(Dest& /*dest*/, Scalar /*alpha*/) const + { + // TODO + } + + private: + DenseTimeSparseSelfAdjointProduct& operator=(const DenseTimeSparseSelfAdjointProduct&); +}; + +/*************************************************************************** +* Implementation of symmetric copies and permutations +***************************************************************************/ +namespace internal { + +template<typename MatrixType, int UpLo> +struct traits<SparseSymmetricPermutationProduct<MatrixType,UpLo> > : traits<MatrixType> { +}; + +template<int UpLo,typename MatrixType,int DestOrder> +void permute_symm_to_fullsymm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DestOrder,typename MatrixType::Index>& _dest, const typename MatrixType::Index* perm) +{ + typedef typename MatrixType::Index Index; + typedef typename MatrixType::Scalar Scalar; + typedef SparseMatrix<Scalar,DestOrder,Index> Dest; + typedef Matrix<Index,Dynamic,1> VectorI; + + Dest& dest(_dest.derived()); + enum { + StorageOrderMatch = int(Dest::IsRowMajor) == int(MatrixType::IsRowMajor) + }; + eigen_assert(perm==0); + 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(typename MatrixType::InnerIterator it(mat,j); it; ++it) + { + Index i = it.index(); + Index ip = perm ? perm[i] : i; + if(i==j) + count[ip]++; + else if((UpLo==Lower && i>j) || (UpLo==Upper && i<j)) + { + count[ip]++; + count[jp]++; + } + } + } + Index nnz = count.sum(); + + // reserve space + dest.reserve(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(Index j = 0; j<size; ++j) + { + Index jp = perm ? perm[j] : j; + for(typename MatrixType::InnerIterator it(mat,j); it; ++it) + { + Index i = it.index(); + Index ip = perm ? perm[i] : i; + if(i==j) + { + int k = count[ip]++; + dest._innerIndexPtr()[k] = ip; + dest._valuePtr()[k] = it.value(); + } + else if((UpLo==Lower && i>j) || (UpLo==Upper && i<j)) + { + int k = count[jp]++; + dest._innerIndexPtr()[k] = ip; + dest._valuePtr()[k] = it.value(); + k = count[ip]++; + dest._innerIndexPtr()[k] = jp; + dest._valuePtr()[k] = internal::conj(it.value()); + } + } + } +} + +template<int SrcUpLo,int DstUpLo,typename MatrixType,int DestOrder> +void permute_symm_to_symm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DestOrder,typename MatrixType::Index>& _dest, const typename MatrixType::Index* perm) +{ + typedef typename MatrixType::Index Index; + typedef typename MatrixType::Scalar Scalar; + typedef SparseMatrix<Scalar,DestOrder,Index> Dest; + Dest& dest(_dest.derived()); + typedef Matrix<Index,Dynamic,1> VectorI; + //internal::conj_if<SrcUpLo!=DstUpLo> cj; + + Index size = mat.rows(); + VectorI count(size); + count.setZero(); + dest.resize(size,size); + for(Index j = 0; j<size; ++j) + { + Index jp = perm ? perm[j] : j; + for(typename MatrixType::InnerIterator it(mat,j); it; ++it) + { + Index i = it.index(); + if((SrcUpLo==Lower && i<j) || (SrcUpLo==Upper && i>j)) + continue; + + Index ip = perm ? perm[i] : i; + count[DstUpLo==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(Index j = 0; j<size; ++j) + { + Index jp = perm ? perm[j] : j; + for(typename MatrixType::InnerIterator it(mat,j); it; ++it) + { + Index i = it.index(); + if((SrcUpLo==Lower && i<j) || (SrcUpLo==Upper && i>j)) + continue; + + Index ip = perm? perm[i] : i; + Index k = count[DstUpLo==Lower ? (std::min)(ip,jp) : (std::max)(ip,jp)]++; + dest._innerIndexPtr()[k] = DstUpLo==Lower ? (std::max)(ip,jp) : (std::min)(ip,jp); + + if((DstUpLo==Lower && ip<jp) || (DstUpLo==Upper && ip>jp)) + dest._valuePtr()[k] = conj(it.value()); + else + dest._valuePtr()[k] = it.value(); + } + } +} + +} + +template<typename MatrixType,int UpLo> +class SparseSymmetricPermutationProduct + : public EigenBase<SparseSymmetricPermutationProduct<MatrixType,UpLo> > +{ + typedef PermutationMatrix<Dynamic> Perm; + public: + typedef typename MatrixType::Scalar Scalar; + typedef typename MatrixType::Index Index; + typedef Matrix<Index,Dynamic,1> VectorI; + typedef typename MatrixType::Nested MatrixTypeNested; + typedef typename internal::remove_all<MatrixTypeNested>::type _MatrixTypeNested; + + 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(); } + + template<typename DestScalar> void evalTo(SparseMatrix<DestScalar>& _dest) const + { + internal::permute_symm_to_fullsymm<UpLo>(m_matrix,_dest,m_perm.indices().data()); + } + + template<typename DestType,unsigned int DestUpLo> void evalTo(SparseSelfAdjointView<DestType,DestUpLo>& dest) const + { + internal::permute_symm_to_symm<UpLo,DestUpLo>(m_matrix,dest.matrix(),m_perm.indices().data()); + } + + protected: + const MatrixTypeNested m_matrix; + const Perm& m_perm; + +}; + +#endif // EIGEN_SPARSE_SELFADJOINTVIEW_H |