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// 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
// IWYU pragma: private
#include "./InternalHeaderCheck.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, bool NonHermitian, 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, bool NonHermitian, 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);
} // namespace internal
template <typename MatrixType, unsigned int Mode_>
class SparseSelfAdjointView : public EigenBase<SparseSelfAdjointView<MatrixType, Mode_> > {
public:
enum {
Mode = Mode_,
TransposeMode = ((int(Mode) & int(Upper)) ? Lower : 0) | ((int(Mode) & int(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 internal::remove_all_t<MatrixTypeNested> 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; }
std::remove_reference_t<MatrixTypeNested>& 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, false>(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;
}
};
} // 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 internal::remove_all_t<SparseLhsTypeNested> 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()) {
internal::construct_at<Base>(this, 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, bool NonHermitian, 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] = (NonHermitian ? it.value() : numext::conj(it.value()));
}
}
}
}
template <int SrcMode_, int DstMode_, bool NonHermitian, 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] = (NonHermitian ? it.value() : numext::conj(it.value()));
else
dest.valuePtr()[k] = it.value();
}
}
}
} // namespace internal
// TODO implement twists in a more evaluator friendly fashion
namespace internal {
template <typename MatrixType, int Mode>
struct traits<SparseSymmetricPermutationProduct<MatrixType, Mode> > : traits<MatrixType> {};
} // namespace internal
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 internal::remove_all_t<MatrixTypeNested> 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, false>(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, false>(src.matrix(), dst.matrix(), src.perm().indices().data());
}
};
} // end namespace internal
} // end namespace Eigen
#endif // EIGEN_SPARSE_SELFADJOINTVIEW_H