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authorGravatar Gael Guennebaud <g.gael@free.fr>2015-09-03 11:18:27 +0200
committerGravatar Gael Guennebaud <g.gael@free.fr>2015-09-03 11:18:27 +0200
commit2795ffd6a0c6f4cd868ddda39104f99e7c6639dd (patch)
tree0a0cea4b1037a2319727da6c7e223d522571a628 /Eigen/src/OrderingMethods
parentef2b54f422a68ca40e9aedb07969228141ce1ede (diff)
Fix Index vs StorageIndex naming convention
Diffstat (limited to 'Eigen/src/OrderingMethods')
-rw-r--r--Eigen/src/OrderingMethods/Ordering.h14
1 files changed, 8 insertions, 6 deletions
diff --git a/Eigen/src/OrderingMethods/Ordering.h b/Eigen/src/OrderingMethods/Ordering.h
index cb838d04a..25792a828 100644
--- a/Eigen/src/OrderingMethods/Ordering.h
+++ b/Eigen/src/OrderingMethods/Ordering.h
@@ -44,14 +44,14 @@ void ordering_helper_at_plus_a(const MatrixType& mat, MatrixType& symmat)
*
* Functor computing the \em approximate \em minimum \em degree ordering
* If the matrix is not structurally symmetric, an ordering of A^T+A is computed
- * \tparam Index The type of indices of the matrix
+ * \tparam StorageIndex The type of indices of the matrix
* \sa COLAMDOrdering
*/
-template <typename Index>
+template <typename StorageIndex>
class AMDOrdering
{
public:
- typedef PermutationMatrix<Dynamic, Dynamic, Index> PermutationType;
+ typedef PermutationMatrix<Dynamic, Dynamic, StorageIndex> PermutationType;
/** Compute the permutation vector from a sparse matrix
* This routine is much faster if the input matrix is column-major
@@ -60,7 +60,7 @@ class AMDOrdering
void operator()(const MatrixType& mat, PermutationType& perm)
{
// Compute the symmetric pattern
- SparseMatrix<typename MatrixType::Scalar, ColMajor, Index> symm;
+ SparseMatrix<typename MatrixType::Scalar, ColMajor, StorageIndex> symm;
internal::ordering_helper_at_plus_a(mat,symm);
// Call the AMD routine
@@ -72,7 +72,7 @@ class AMDOrdering
template <typename SrcType, unsigned int SrcUpLo>
void operator()(const SparseSelfAdjointView<SrcType, SrcUpLo>& mat, PermutationType& perm)
{
- SparseMatrix<typename SrcType::Scalar, ColMajor, Index> C; C = mat;
+ SparseMatrix<typename SrcType::Scalar, ColMajor, StorageIndex> C; C = mat;
// Call the AMD routine
// m_mat.prune(keep_diag()); //Remove the diagonal elements
@@ -88,7 +88,7 @@ class AMDOrdering
* Functor computing the natural ordering (identity)
*
* \note Returns an empty permutation matrix
- * \tparam Index The type of indices of the matrix
+ * \tparam StorageIndex The type of indices of the matrix
*/
template <typename StorageIndex>
class NaturalOrdering
@@ -108,6 +108,8 @@ class NaturalOrdering
/** \ingroup OrderingMethods_Module
* \class COLAMDOrdering
*
+ * \tparam StorageIndex The type of indices of the matrix
+ *
* Functor computing the \em column \em approximate \em minimum \em degree ordering
* The matrix should be in column-major and \b compressed format (see SparseMatrix::makeCompressed()).
*/