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Use size_type as return type of SparseMatrix::m(). #16670

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merged 1 commit into from
Feb 20, 2024
Merged

Use size_type as return type of SparseMatrix::m(). #16670

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8 changes: 4 additions & 4 deletions include/deal.II/lac/trilinos_tpetra_sparse_matrix.h
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Original file line number Diff line number Diff line change
Expand Up @@ -406,13 +406,13 @@ namespace LinearAlgebra
/**
* Return the number of rows in this matrix.
*/
dealii::types::signed_global_dof_index
size_type
m() const;

/**
* Return the number of columns in this matrix.
*/
dealii::types::signed_global_dof_index
size_type
n() const;


Expand Down Expand Up @@ -1110,7 +1110,7 @@ namespace LinearAlgebra


template <typename Number, typename MemorySpace>
inline dealii::types::signed_global_dof_index
inline typename SparseMatrix<Number, MemorySpace>::size_type
SparseMatrix<Number, MemorySpace>::m() const
{
return matrix->getRowMap()->getGlobalNumElements();
Expand All @@ -1119,7 +1119,7 @@ namespace LinearAlgebra


template <typename Number, typename MemorySpace>
inline dealii::types::signed_global_dof_index
inline typename SparseMatrix<Number, MemorySpace>::size_type
SparseMatrix<Number, MemorySpace>::n() const
{
// If the matrix structure has not been fixed (i.e., we did not have a
Expand Down
4 changes: 2 additions & 2 deletions include/deal.II/lac/trilinos_tpetra_sparse_matrix.templates.h
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Expand Up @@ -594,7 +594,7 @@ namespace LinearAlgebra
const bool copy_values,
const dealii::SparsityPattern *use_this_sparsity)
{
dealii::types::signed_global_dof_index n_rows = dealii_sparse_matrix.m();
const size_type n_rows = dealii_sparse_matrix.m();
AssertDimension(row_parallel_partitioning.size(), n_rows);
AssertDimension(col_parallel_partitioning.size(),
dealii_sparse_matrix.n());
Expand Down Expand Up @@ -631,7 +631,7 @@ namespace LinearAlgebra
std::vector<size_type> row_indices(maximum_row_length);
std::vector<Number> values(maximum_row_length);

for (dealii::types::signed_global_dof_index row = 0; row < n_rows; ++row)
for (size_type row = 0; row < n_rows; ++row)
// see if the row is locally stored on this processor
if (row_parallel_partitioning.is_element(row) == true)
{
Expand Down