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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 PermutationType, typename MatrixType, int Side, bool Transposed>
struct traits<permut_sparsematrix_product_retval<PermutationType, MatrixType, Side, Transposed> >
{
typedef typename remove_all<typename MatrixType::Nested>::type MatrixTypeNestedCleaned;
typedef typename MatrixTypeNestedCleaned::Scalar Scalar;
typedef typename MatrixTypeNestedCleaned::Index Index;
enum {
SrcStorageOrder = MatrixTypeNestedCleaned::Flags&RowMajorBit ? RowMajor : ColMajor,
MoveOuter = SrcStorageOrder==RowMajor ? Side==OnTheLeft : Side==OnTheRight
};
typedef typename internal::conditional<MoveOuter,
SparseMatrix<Scalar,SrcStorageOrder,Index>,
SparseMatrix<Scalar,int(SrcStorageOrder)==RowMajor?ColMajor:RowMajor,Index> >::type ReturnType;
};
template<typename PermutationType, typename MatrixType, int Side, bool Transposed>
struct permut_sparsematrix_product_retval
: public ReturnByValue<permut_sparsematrix_product_retval<PermutationType, MatrixType, Side, Transposed> >
{
typedef typename remove_all<typename MatrixType::Nested>::type MatrixTypeNestedCleaned;
typedef typename MatrixTypeNestedCleaned::Scalar Scalar;
typedef typename MatrixTypeNestedCleaned::Index Index;
enum {
SrcStorageOrder = MatrixTypeNestedCleaned::Flags&RowMajorBit ? RowMajor : ColMajor,
MoveOuter = SrcStorageOrder==RowMajor ? Side==OnTheLeft : Side==OnTheRight
};
permut_sparsematrix_product_retval(const PermutationType& perm, const MatrixType& matrix)
: m_permutation(perm), m_matrix(matrix)
{}
inline int rows() const { return m_matrix.rows(); }
inline int cols() const { return m_matrix.cols(); }
template<typename Dest> inline void evalTo(Dest& dst) const
{
if(MoveOuter)
{
SparseMatrix<Scalar,SrcStorageOrder,Index> tmp(m_matrix.rows(), m_matrix.cols());
VectorXi sizes(m_matrix.outerSize());
for(Index j=0; j<m_matrix.outerSize(); ++j)
{
Index jp = m_permutation.indices().coeff(j);
sizes[((Side==OnTheLeft) ^ Transposed) ? jp : j] = m_matrix.innerVector(((Side==OnTheRight) ^ Transposed) ? jp : j).size();
}
tmp.reserve(sizes);
for(Index j=0; j<m_matrix.outerSize(); ++j)
{
Index jp = m_permutation.indices().coeff(j);
Index jsrc = ((Side==OnTheRight) ^ Transposed) ? jp : j;
Index jdst = ((Side==OnTheLeft) ^ Transposed) ? jp : j;
for(typename MatrixTypeNestedCleaned::InnerIterator it(m_matrix,jsrc); it; ++it)
tmp.insertByOuterInner(jdst,it.index()) = it.value();
}
dst = tmp;
}
else
{
SparseMatrix<Scalar,int(SrcStorageOrder)==RowMajor?ColMajor:RowMajor,Index> tmp(m_matrix.rows(), m_matrix.cols());
VectorXi sizes(tmp.outerSize());
sizes.setZero();
PermutationMatrix<Dynamic,Dynamic,Index> perm;
if((Side==OnTheLeft) ^ Transposed)
perm = m_permutation;
else
perm = m_permutation.transpose();
for(Index j=0; j<m_matrix.outerSize(); ++j)
for(typename MatrixTypeNestedCleaned::InnerIterator it(m_matrix,j); it; ++it)
sizes[perm.indices().coeff(it.index())]++;
tmp.reserve(sizes);
for(Index j=0; j<m_matrix.outerSize(); ++j)
for(typename MatrixTypeNestedCleaned::InnerIterator it(m_matrix,j); it; ++it)
tmp.insertByOuterInner(perm.indices().coeff(it.index()),j) = it.value();
dst = tmp;
}
}
protected:
const PermutationType& m_permutation;
typename MatrixType::Nested m_matrix;
};
}
/** \returns the matrix with the permutation applied to the columns
*/
template<typename SparseDerived, typename PermDerived>
inline const internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheRight, false>
operator*(const SparseMatrixBase<SparseDerived>& matrix, const PermutationBase<PermDerived>& perm)
{
return internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheRight, false>(perm, matrix.derived());
}
/** \returns the matrix with the permutation applied to the rows
*/
template<typename SparseDerived, typename PermDerived>
inline const internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheLeft, false>
operator*( const PermutationBase<PermDerived>& perm, const SparseMatrixBase<SparseDerived>& matrix)
{
return internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheLeft, false>(perm, matrix.derived());
}
/** \returns the matrix with the inverse permutation applied to the columns.
*/
template<typename SparseDerived, typename PermDerived>
inline const internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheRight, true>
operator*(const SparseMatrixBase<SparseDerived>& matrix, const Transpose<PermutationBase<PermDerived> >& tperm)
{
return internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheRight, true>(tperm.nestedPermutation(), matrix.derived());
}
/** \returns the matrix with the inverse permutation applied to the rows.
*/
template<typename SparseDerived, typename PermDerived>
inline const internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheLeft, true>
operator*(const Transpose<PermutationBase<PermDerived> >& tperm, const SparseMatrixBase<SparseDerived>& matrix)
{
return internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheLeft, true>(tperm.nestedPermutation(), matrix.derived());
}
} // end namespace Eigen
#endif // EIGEN_SPARSE_SELFADJOINTVIEW_H
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