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SparseAssign.h
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Sat, Feb 22, 17:47

SparseAssign.h
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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::min)(src.rows()*src.cols(), (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::min)(src.rows()*src.cols(), (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, typename Weak>
struct Assignment<DstXprType, SrcXprType, Functor, Sparse2Dense, Weak>
{
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 dense ?= dense +/- sparse and dense ?= sparse +/- dense
template<typename DstXprType, typename Func1, typename Func2>
struct assignment_from_dense_op_sparse
{
template<typename SrcXprType, typename InitialFunc>
static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
void run(DstXprType &dst, const SrcXprType &src, const InitialFunc& /*func*/)
{
#ifdef EIGEN_SPARSE_ASSIGNMENT_FROM_DENSE_OP_SPARSE_PLUGIN
EIGEN_SPARSE_ASSIGNMENT_FROM_DENSE_OP_SPARSE_PLUGIN
#endif
call_assignment_no_alias(dst, src.lhs(), Func1());
call_assignment_no_alias(dst, src.rhs(), Func2());
}
// Specialization for dense1 = sparse + dense2; -> dense1 = dense2; dense1 += sparse;
template<typename Lhs, typename Rhs, typename Scalar>
static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
typename internal::enable_if<internal::is_same<typename internal::evaluator_traits<Rhs>::Shape,DenseShape>::value>::type
run(DstXprType &dst, const CwiseBinaryOp<internal::scalar_sum_op<Scalar,Scalar>, const Lhs, const Rhs> &src,
const internal::assign_op<typename DstXprType::Scalar,Scalar>& /*func*/)
{
#ifdef EIGEN_SPARSE_ASSIGNMENT_FROM_SPARSE_ADD_DENSE_PLUGIN
EIGEN_SPARSE_ASSIGNMENT_FROM_SPARSE_ADD_DENSE_PLUGIN
#endif
// Apply the dense matrix first, then the sparse one.
call_assignment_no_alias(dst, src.rhs(), Func1());
call_assignment_no_alias(dst, src.lhs(), Func2());
}
// Specialization for dense1 = sparse - dense2; -> dense1 = -dense2; dense1 += sparse;
template<typename Lhs, typename Rhs, typename Scalar>
static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
typename internal::enable_if<internal::is_same<typename internal::evaluator_traits<Rhs>::Shape,DenseShape>::value>::type
run(DstXprType &dst, const CwiseBinaryOp<internal::scalar_difference_op<Scalar,Scalar>, const Lhs, const Rhs> &src,
const internal::assign_op<typename DstXprType::Scalar,Scalar>& /*func*/)
{
#ifdef EIGEN_SPARSE_ASSIGNMENT_FROM_SPARSE_SUB_DENSE_PLUGIN
EIGEN_SPARSE_ASSIGNMENT_FROM_SPARSE_SUB_DENSE_PLUGIN
#endif
// Apply the dense matrix first, then the sparse one.
call_assignment_no_alias(dst, -src.rhs(), Func1());
call_assignment_no_alias(dst, src.lhs(), add_assign_op<typename DstXprType::Scalar,typename Lhs::Scalar>());
}
};
#define EIGEN_CATCH_ASSIGN_DENSE_OP_SPARSE(ASSIGN_OP,BINOP,ASSIGN_OP2) \
template< typename DstXprType, typename Lhs, typename Rhs, typename Scalar> \
struct Assignment<DstXprType, CwiseBinaryOp<internal::BINOP<Scalar,Scalar>, const Lhs, const Rhs>, internal::ASSIGN_OP<typename DstXprType::Scalar,Scalar>, \
Sparse2Dense, \
typename internal::enable_if< internal::is_same<typename internal::evaluator_traits<Lhs>::Shape,DenseShape>::value \
|| internal::is_same<typename internal::evaluator_traits<Rhs>::Shape,DenseShape>::value>::type> \
: assignment_from_dense_op_sparse<DstXprType, internal::ASSIGN_OP<typename DstXprType::Scalar,typename Lhs::Scalar>, internal::ASSIGN_OP2<typename DstXprType::Scalar,typename Rhs::Scalar> > \
{}
EIGEN_CATCH_ASSIGN_DENSE_OP_SPARSE(assign_op, scalar_sum_op,add_assign_op);
EIGEN_CATCH_ASSIGN_DENSE_OP_SPARSE(add_assign_op,scalar_sum_op,add_assign_op);
EIGEN_CATCH_ASSIGN_DENSE_OP_SPARSE(sub_assign_op,scalar_sum_op,sub_assign_op);
EIGEN_CATCH_ASSIGN_DENSE_OP_SPARSE(assign_op, scalar_difference_op,sub_assign_op);
EIGEN_CATCH_ASSIGN_DENSE_OP_SPARSE(add_assign_op,scalar_difference_op,sub_assign_op);
EIGEN_CATCH_ASSIGN_DENSE_OP_SPARSE(sub_assign_op,scalar_difference_op,add_assign_op);
// 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;
template<int Options, typename AssignFunc>
static void run(SparseMatrix<Scalar,Options,StorageIndex> &dst, const SrcXprType &src, const AssignFunc &func)
{ dst.assignDiagonal(src.diagonal(), func); }
template<typename DstDerived>
static void run(SparseMatrixBase<DstDerived> &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
{ dst.derived().diagonal() = src.diagonal(); }
template<typename DstDerived>
static void run(SparseMatrixBase<DstDerived> &dst, const SrcXprType &src, const internal::add_assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
{ dst.derived().diagonal() += src.diagonal(); }
template<typename DstDerived>
static void run(SparseMatrixBase<DstDerived> &dst, const SrcXprType &src, const internal::sub_assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
{ dst.derived().diagonal() -= src.diagonal(); }
};
} // end namespace internal
} // end namespace Eigen
#endif // EIGEN_SPARSEASSIGN_H

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