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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2014 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_SPARSEASSIGN_H
#define EIGEN_SPARSEASSIGN_H
namespace Eigen {
template<typename Derived>
template<typename OtherDerived>
Derived& SparseMatrixBase<Derived>::operator=(const EigenBase<OtherDerived> &other)
{
internal::call_assignment_no_alias(derived(), other.derived());
return derived();
}
template<typename Derived>
template<typename OtherDerived>
Derived& SparseMatrixBase<Derived>::operator=(const ReturnByValue<OtherDerived>& other)
{
// TODO use the evaluator mechanism
other.evalTo(derived());
return derived();
}
template<typename Derived>
template<typename OtherDerived>
inline Derived& SparseMatrixBase<Derived>::operator=(const SparseMatrixBase<OtherDerived>& other)
{
// by default sparse evaluation do not alias, so we can safely bypass the generic call_assignment routine
internal::Assignment<Derived,OtherDerived,internal::assign_op<Scalar,typename OtherDerived::Scalar> >
::run(derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
return derived();
}
template<typename Derived>
inline Derived& SparseMatrixBase<Derived>::operator=(const Derived& other)
{
internal::call_assignment_no_alias(derived(), other.derived());
return derived();
}
namespace internal {
template<>
struct storage_kind_to_evaluator_kind<Sparse> {
typedef IteratorBased Kind;
};
template<>
struct storage_kind_to_shape<Sparse> {
typedef SparseShape Shape;
};
struct Sparse2Sparse {};
struct Sparse2Dense {};
template<> struct AssignmentKind<SparseShape, SparseShape> { typedef Sparse2Sparse Kind; };
template<> struct AssignmentKind<SparseShape, SparseTriangularShape> { typedef Sparse2Sparse Kind; };
template<> struct AssignmentKind<DenseShape, SparseShape> { typedef Sparse2Dense Kind; };
template<> struct AssignmentKind<DenseShape, SparseTriangularShape> { typedef Sparse2Dense Kind; };
template<typename DstXprType, typename SrcXprType>
void assign_sparse_to_sparse(DstXprType &dst, const SrcXprType &src)
{
typedef typename DstXprType::Scalar Scalar;
typedef internal::evaluator<DstXprType> DstEvaluatorType;
typedef internal::evaluator<SrcXprType> SrcEvaluatorType;
SrcEvaluatorType srcEvaluator(src);
const bool transpose = (DstEvaluatorType::Flags & RowMajorBit) != (SrcEvaluatorType::Flags & RowMajorBit);
const Index outerEvaluationSize = (SrcEvaluatorType::Flags&RowMajorBit) ? src.rows() : src.cols();
if ((!transpose) && src.isRValue())
{
// eval without temporary
dst.resize(src.rows(), src.cols());
dst.setZero();
dst.reserve((std::max)(src.rows(),src.cols())*2);
for (Index j=0; j<outerEvaluationSize; ++j)
{
dst.startVec(j);
for (typename SrcEvaluatorType::InnerIterator it(srcEvaluator, j); it; ++it)
{
Scalar v = it.value();
dst.insertBackByOuterInner(j,it.index()) = v;
}
}
dst.finalize();
}
else
{
// eval through a temporary
eigen_assert(( ((internal::traits<DstXprType>::SupportedAccessPatterns & OuterRandomAccessPattern)==OuterRandomAccessPattern) ||
(!((DstEvaluatorType::Flags & RowMajorBit) != (SrcEvaluatorType::Flags & RowMajorBit)))) &&
"the transpose operation is supposed to be handled in SparseMatrix::operator=");
enum { Flip = (DstEvaluatorType::Flags & RowMajorBit) != (SrcEvaluatorType::Flags & RowMajorBit) };
DstXprType temp(src.rows(), src.cols());
temp.reserve((std::max)(src.rows(),src.cols())*2);
for (Index j=0; j<outerEvaluationSize; ++j)
{
temp.startVec(j);
for (typename SrcEvaluatorType::InnerIterator it(srcEvaluator, j); it; ++it)
{
Scalar v = it.value();
temp.insertBackByOuterInner(Flip?it.index():j,Flip?j:it.index()) = v;
}
}
temp.finalize();
dst = temp.markAsRValue();
}
}
// Generic Sparse to Sparse assignment
template< typename DstXprType, typename SrcXprType, typename Functor>
struct Assignment<DstXprType, SrcXprType, Functor, Sparse2Sparse>
{
static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
{
assign_sparse_to_sparse(dst.derived(), src.derived());
}
};
// Generic Sparse to Dense assignment
template< typename DstXprType, typename SrcXprType, typename Functor>
struct Assignment<DstXprType, SrcXprType, Functor, Sparse2Dense>
{
static void run(DstXprType &dst, const SrcXprType &src, const Functor &func)
{
if(internal::is_same<Functor,internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> >::value)
dst.setZero();
internal::evaluator<SrcXprType> srcEval(src);
resize_if_allowed(dst, src, func);
internal::evaluator<DstXprType> dstEval(dst);
const Index outerEvaluationSize = (internal::evaluator<SrcXprType>::Flags&RowMajorBit) ? src.rows() : src.cols();
for (Index j=0; j<outerEvaluationSize; ++j)
for (typename internal::evaluator<SrcXprType>::InnerIterator i(srcEval,j); i; ++i)
func.assignCoeff(dstEval.coeffRef(i.row(),i.col()), i.value());
}
};
// Specialization for "dst = dec.solve(rhs)"
// NOTE we need to specialize it for Sparse2Sparse to avoid ambiguous specialization error
template<typename DstXprType, typename DecType, typename RhsType, typename Scalar>
struct Assignment<DstXprType, Solve<DecType,RhsType>, internal::assign_op<Scalar,Scalar>, Sparse2Sparse>
{
typedef Solve<DecType,RhsType> SrcXprType;
static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<Scalar,Scalar> &)
{
Index dstRows = src.rows();
Index dstCols = src.cols();
if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
dst.resize(dstRows, dstCols);
src.dec()._solve_impl(src.rhs(), dst);
}
};
struct Diagonal2Sparse {};
template<> struct AssignmentKind<SparseShape,DiagonalShape> { typedef Diagonal2Sparse Kind; };
template< typename DstXprType, typename SrcXprType, typename Functor>
struct Assignment<DstXprType, SrcXprType, Functor, Diagonal2Sparse>
{
typedef typename DstXprType::StorageIndex StorageIndex;
typedef typename DstXprType::Scalar Scalar;
typedef Array<StorageIndex,Dynamic,1> ArrayXI;
typedef Array<Scalar,Dynamic,1> ArrayXS;
template<int Options>
static void run(SparseMatrix<Scalar,Options,StorageIndex> &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
{
Index dstRows = src.rows();
Index dstCols = src.cols();
if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
dst.resize(dstRows, dstCols);
Index size = src.diagonal().size();
dst.makeCompressed();
dst.resizeNonZeros(size);
Map<ArrayXI>(dst.innerIndexPtr(), size).setLinSpaced(0,StorageIndex(size)-1);
Map<ArrayXI>(dst.outerIndexPtr(), size+1).setLinSpaced(0,StorageIndex(size));
Map<ArrayXS>(dst.valuePtr(), size) = src.diagonal();
}
template<typename DstDerived>
static void run(SparseMatrixBase<DstDerived> &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
{
dst.diagonal() = src.diagonal();
}
static void run(DstXprType &dst, const SrcXprType &src, const internal::add_assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
{ dst.diagonal() += src.diagonal(); }
static void run(DstXprType &dst, const SrcXprType &src, const internal::sub_assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
{ dst.diagonal() -= src.diagonal(); }
};
} // end namespace internal
} // end namespace Eigen
#endif // EIGEN_SPARSEASSIGN_H
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