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// 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
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 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;
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
*
* 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,int StorageOrder> void evalTo(SparseMatrix<DestScalar,StorageOrder,Index>& _dest) const
{
internal::permute_symm_to_fullsymm<UpLo>(m_matrix, _dest);
}
template<typename DestScalar> void evalTo(DynamicSparseMatrix<DestScalar,ColMajor,Index>& _dest) const
{
// TODO directly evaluate into _dest;
SparseMatrix<DestScalar,ColMajor,Index> tmp(_dest.rows(),_dest.cols());
internal::permute_symm_to_fullsymm<UpLo>(m_matrix, tmp);
_dest = tmp;
}
/** \returns an expression of P H P^-1 */
SparseSymmetricPermutationProduct<_MatrixTypeNested,UpLo> twistedBy(const PermutationMatrix<Dynamic,Dynamic,Index>& 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;
}
SparseSelfAdjointView& operator=(const SparseSelfAdjointView& src)
{
PermutationMatrix<Dynamic> pnull;
return *this = src.twistedBy(pnull);
}
template<typename SrcMatrixType,unsigned int SrcUpLo>
SparseSelfAdjointView& operator=(const SparseSelfAdjointView<SrcMatrixType,SrcUpLo>& src)
{
PermutationMatrix<Dynamic> pnull;
return *this = src.twistedBy(pnull);
}
// const SparseLLT<PlainObject, UpLo> llt() const;
// const SparseLDLT<PlainObject, UpLo> ldlt() const;
protected:
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)
{
while (i && i.index()<j) ++i;
if(i && i.index()==j)
{
dest.row(j) += i.value() * m_rhs.row(j);
++i;
}
}
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)
};
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 r = it.row();
Index c = it.col();
Index ip = perm ? perm[i] : i;
if(UpLo==(Upper|Lower))
count[StorageOrderMatch ? jp : ip]++;
else if(r==c)
count[ip]++;
else if(( UpLo==Lower && r>c) || ( UpLo==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(Index j = 0; j<size; ++j)
{
for(typename MatrixType::InnerIterator it(mat,j); it; ++it)
{
Index i = it.index();
Index r = it.row();
Index c = it.col();
Index jp = perm ? perm[j] : j;
Index ip = perm ? perm[i] : i;
if(UpLo==(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(( (UpLo&Lower)==Lower && r>c) || ( (UpLo&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] = internal::conj(it.value());
}
}
}
}
template<int _SrcUpLo,int _DstUpLo,typename MatrixType,int DstOrder>
void permute_symm_to_symm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DstOrder,typename MatrixType::Index>& _dest, const typename MatrixType::Index* perm)
{
typedef typename MatrixType::Index Index;
typedef typename MatrixType::Scalar Scalar;
SparseMatrix<Scalar,DstOrder,Index>& dest(_dest.derived());
typedef Matrix<Index,Dynamic,1> VectorI;
enum {
SrcOrder = MatrixType::IsRowMajor ? RowMajor : ColMajor,
StorageOrderMatch = int(SrcOrder) == int(DstOrder),
DstUpLo = DstOrder==RowMajor ? (_DstUpLo==Upper ? Lower : Upper) : _DstUpLo,
SrcUpLo = SrcOrder==RowMajor ? (_SrcUpLo==Upper ? Lower : Upper) : _SrcUpLo
};
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((int(SrcUpLo)==int(Lower) && i<j) || (int(SrcUpLo)==int(Upper) && i>j))
continue;
Index ip = perm ? perm[i] : i;
count[int(DstUpLo)==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(Index j = 0; j<size; ++j)
{
for(typename MatrixType::InnerIterator it(mat,j); it; ++it)
{
Index i = it.index();
if((int(SrcUpLo)==int(Lower) && i<j) || (int(SrcUpLo)==int(Upper) && i>j))
continue;
Index jp = perm ? perm[j] : j;
Index ip = perm? perm[i] : i;
Index k = count[int(DstUpLo)==int(Lower) ? (std::min)(ip,jp) : (std::max)(ip,jp)]++;
dest.innerIndexPtr()[k] = int(DstUpLo)==int(Lower) ? (std::max)(ip,jp) : (std::min)(ip,jp);
if(!StorageOrderMatch) std::swap(ip,jp);
if( ((int(DstUpLo)==int(Lower) && ip<jp) || (int(DstUpLo)==int(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> >
{
public:
typedef typename MatrixType::Scalar Scalar;
typedef typename MatrixType::Index Index;
protected:
typedef PermutationMatrix<Dynamic,Dynamic,Index> Perm;
public:
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, int Options, typename DstIndex>
void evalTo(SparseMatrix<DestScalar,Options,DstIndex>& _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:
MatrixTypeNested m_matrix;
const Perm& m_perm;
};
} // end namespace Eigen
#endif // EIGEN_SPARSE_SELFADJOINTVIEW_H
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