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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2012 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_PERMUTATION_H
#define EIGEN_SPARSE_PERMUTATION_H
// This file implements sparse * permutation products
namespace Eigen {
namespace internal {
template<typename MatrixType, int Side, bool Transposed>
struct permutation_matrix_product<MatrixType, Side, Transposed, SparseShape>
{
typedef typename remove_all<typename MatrixType::Nested>::type MatrixTypeNestedCleaned;
typedef typename MatrixTypeNestedCleaned::Scalar Scalar;
typedef typename MatrixTypeNestedCleaned::StorageIndex StorageIndex;
enum {
SrcStorageOrder = MatrixTypeNestedCleaned::Flags&RowMajorBit ? RowMajor : ColMajor,
MoveOuter = SrcStorageOrder==RowMajor ? Side==OnTheLeft : Side==OnTheRight
};
typedef typename internal::conditional<MoveOuter,
SparseMatrix<Scalar,SrcStorageOrder,StorageIndex>,
SparseMatrix<Scalar,int(SrcStorageOrder)==RowMajor?ColMajor:RowMajor,StorageIndex> >::type ReturnType;
template<typename Dest,typename PermutationType>
static inline void run(Dest& dst, const PermutationType& perm, const MatrixType& mat)
{
if(MoveOuter)
{
SparseMatrix<Scalar,SrcStorageOrder,StorageIndex> tmp(mat.rows(), mat.cols());
Matrix<StorageIndex,Dynamic,1> sizes(mat.outerSize());
for(Index j=0; j<mat.outerSize(); ++j)
{
Index jp = perm.indices().coeff(j);
sizes[((Side==OnTheLeft) ^ Transposed) ? jp : j] = StorageIndex(mat.innerVector(((Side==OnTheRight) ^ Transposed) ? jp : j).nonZeros());
}
tmp.reserve(sizes);
for(Index j=0; j<mat.outerSize(); ++j)
{
Index jp = perm.indices().coeff(j);
Index jsrc = ((Side==OnTheRight) ^ Transposed) ? jp : j;
Index jdst = ((Side==OnTheLeft) ^ Transposed) ? jp : j;
for(typename MatrixTypeNestedCleaned::InnerIterator it(mat,jsrc); it; ++it)
tmp.insertByOuterInner(jdst,it.index()) = it.value();
}
dst = tmp;
}
else
{
SparseMatrix<Scalar,int(SrcStorageOrder)==RowMajor?ColMajor:RowMajor,StorageIndex> tmp(mat.rows(), mat.cols());
Matrix<StorageIndex,Dynamic,1> sizes(tmp.outerSize());
sizes.setZero();
PermutationMatrix<Dynamic,Dynamic,StorageIndex> perm_cpy;
if((Side==OnTheLeft) ^ Transposed)
perm_cpy = perm;
else
perm_cpy = perm.transpose();
for(Index j=0; j<mat.outerSize(); ++j)
for(typename MatrixTypeNestedCleaned::InnerIterator it(mat,j); it; ++it)
sizes[perm_cpy.indices().coeff(it.index())]++;
tmp.reserve(sizes);
for(Index j=0; j<mat.outerSize(); ++j)
for(typename MatrixTypeNestedCleaned::InnerIterator it(mat,j); it; ++it)
tmp.insertByOuterInner(perm_cpy.indices().coeff(it.index()),j) = it.value();
dst = tmp;
}
}
};
}
namespace internal {
template <int ProductTag> struct product_promote_storage_type<Sparse, PermutationStorage, ProductTag> { typedef Sparse ret; };
template <int ProductTag> struct product_promote_storage_type<PermutationStorage, Sparse, ProductTag> { typedef Sparse ret; };
// TODO, the following two overloads are only needed to define the right temporary type through
// typename traits<permutation_sparse_matrix_product<Rhs,Lhs,OnTheRight,false> >::ReturnType
// whereas it should be correctly handled by traits<Product<> >::PlainObject
template<typename Lhs, typename Rhs, int ProductTag>
struct product_evaluator<Product<Lhs, Rhs, AliasFreeProduct>, ProductTag, PermutationShape, SparseShape, typename traits<Lhs>::Scalar, typename traits<Rhs>::Scalar>
: public evaluator<typename permutation_matrix_product<Rhs,OnTheRight,false,SparseShape>::ReturnType>
{
typedef Product<Lhs, Rhs, AliasFreeProduct> XprType;
typedef typename permutation_matrix_product<Rhs,OnTheRight,false,SparseShape>::ReturnType PlainObject;
typedef evaluator<PlainObject> Base;
explicit product_evaluator(const XprType& xpr)
: m_result(xpr.rows(), xpr.cols())
{
::new (static_cast<Base*>(this)) Base(m_result);
generic_product_impl<Lhs, Rhs, PermutationShape, SparseShape, ProductTag>::evalTo(m_result, xpr.lhs(), xpr.rhs());
}
protected:
PlainObject m_result;
};
template<typename Lhs, typename Rhs, int ProductTag>
struct product_evaluator<Product<Lhs, Rhs, AliasFreeProduct>, ProductTag, SparseShape, PermutationShape, typename traits<Lhs>::Scalar, typename traits<Rhs>::Scalar>
: public evaluator<typename permutation_matrix_product<Lhs,OnTheRight,false,SparseShape>::ReturnType>
{
typedef Product<Lhs, Rhs, AliasFreeProduct> XprType;
typedef typename permutation_matrix_product<Lhs,OnTheRight,false,SparseShape>::ReturnType PlainObject;
typedef evaluator<PlainObject> Base;
explicit product_evaluator(const XprType& xpr)
: m_result(xpr.rows(), xpr.cols())
{
::new (static_cast<Base*>(this)) Base(m_result);
generic_product_impl<Lhs, Rhs, SparseShape, PermutationShape, ProductTag>::evalTo(m_result, xpr.lhs(), xpr.rhs());
}
protected:
PlainObject m_result;
};
} // end namespace internal
/** \returns the matrix with the permutation applied to the columns
*/
template<typename SparseDerived, typename PermDerived>
inline const Product<SparseDerived, PermDerived>
operator*(const SparseMatrixBase<SparseDerived>& matrix, const PermutationBase<PermDerived>& perm)
{ return Product<SparseDerived, PermDerived>(matrix.derived(), perm.derived()); }
/** \returns the matrix with the permutation applied to the rows
*/
template<typename SparseDerived, typename PermDerived>
inline const Product<PermDerived, SparseDerived>
operator*( const PermutationBase<PermDerived>& perm, const SparseMatrixBase<SparseDerived>& matrix)
{ return Product<PermDerived, SparseDerived>(perm.derived(), matrix.derived()); }
// TODO, the following specializations should not be needed as Transpose<Permutation*> should be a PermutationBase.
/** \returns the matrix with the inverse permutation applied to the columns.
*/
template<typename SparseDerived, typename PermDerived>
inline const Product<SparseDerived, Transpose<PermutationBase<PermDerived> > >
operator*(const SparseMatrixBase<SparseDerived>& matrix, const Transpose<PermutationBase<PermDerived> >& tperm)
{
return Product<SparseDerived, Transpose<PermutationBase<PermDerived> > >(matrix.derived(), tperm);
}
/** \returns the matrix with the inverse permutation applied to the rows.
*/
template<typename SparseDerived, typename PermDerived>
inline const Product<Transpose<PermutationBase<PermDerived> >, SparseDerived>
operator*(const Transpose<PermutationBase<PermDerived> >& tperm, const SparseMatrixBase<SparseDerived>& matrix)
{
return Product<Transpose<PermutationBase<PermDerived> >, SparseDerived>(tperm, matrix.derived());
}
} // end namespace Eigen
#endif // EIGEN_SPARSE_SELFADJOINTVIEW_H
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