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Doxygen LaTeX fixes #13830

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merged 8 commits into from
Feb 25, 2025
Merged

Doxygen LaTeX fixes #13830

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16cf92b
Anasazi: Fix docstring
cgcgcg Feb 20, 2025
1835ddc
Tpetra: Fix docstring
cgcgcg Feb 21, 2025
f0b5280
Ifpack2: Fix docstring
cgcgcg Feb 21, 2025
96a0303
Stokhos: Fix docstring
cgcgcg Feb 21, 2025
beb227a
Intrepid2: Fix docstring
cgcgcg Feb 22, 2025
48b4c0b
Thyra: Fix docstrings
cgcgcg Feb 22, 2025
86cde8d
MueLu: Fix docstring
cgcgcg Feb 22, 2025
70e8a11
ROL: Fix docstrings
cgcgcg Feb 22, 2025
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4 changes: 2 additions & 2 deletions packages/anasazi/src/AnasaziDenseMatTraits.hpp
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Expand Up @@ -124,8 +124,8 @@ namespace Anasazi {
\return The return value is a pointer to the data, stored sequentially.
\c *cor denotes whether the data is stored column-oriented (\f$*cor ==
true$) or row-oriented (\f$cor == false$). \c *stride denotes the stride
between columns/rows.
true\f$) or row-oriented (\f$cor == false\f$). \c *stride denotes the stride
between columns/rows.
*/
static ScalarType * values( DM& dm, int *stride, bool *cor) {
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5 changes: 2 additions & 3 deletions packages/ifpack2/src/Ifpack2_Details_AdditiveSchwarzFilter_decl.hpp
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Expand Up @@ -108,7 +108,7 @@ namespace Details
void updateMatrixValues();

Teuchos::RCP<const crs_matrix_type> getFilteredMatrix() const;

//! Destructor.
virtual ~AdditiveSchwarzFilter ();

Expand Down Expand Up @@ -294,7 +294,7 @@ namespace Details

//! Returns the Frobenius norm of the matrix.
/** Computes and returns the Frobenius norm of the matrix, defined as:
\f$ \|A\|_F = \sqrt{\sum_{i,j} \|\a_{ij}\|^2} \f$
\f$ \|A\|_F = \sqrt{\sum_{i,j} \|a_{ij}\|^2} \f$
*/
virtual mag_type getFrobeniusNorm() const;

Expand Down Expand Up @@ -403,4 +403,3 @@ namespace Details
}} //namespace Ifpack2::Details

#endif

4 changes: 2 additions & 2 deletions packages/ifpack2/src/Ifpack2_Details_DenseSolver_decl.hpp
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Expand Up @@ -133,7 +133,7 @@ class DenseSolver<MatrixType, false> :
/// \brief Apply the preconditioner to X, putting the result in Y.
///
/// If the result of applying this preconditioner to a vector X is
/// \f$M^{-1} \cdot X$, then this method computes \f$\beta Y + \alpha M^{-1} \cdot X\f$.
/// \f$M^{-1} \cdot X\f$, then this method computes \f$\beta Y + \alpha M^{-1} \cdot X\f$.
/// The typical case is \f$\beta = 0\f$ and \f$\alpha = 1\f$.
void
apply (const Tpetra::MultiVector<scalar_type,local_ordinal_type,global_ordinal_type,node_type>& X,
Expand Down Expand Up @@ -388,7 +388,7 @@ class DenseSolver<MatrixType, true> :
/// \brief Apply the preconditioner to X, putting the result in Y.
///
/// If the result of applying this preconditioner to a vector X is
/// \f$M^{-1} \cdot X$, then this method computes \f$\beta Y + \alpha M^{-1} \cdot X\f$.
/// \f$M^{-1} \cdot X\f$, then this method computes \f$\beta Y + \alpha M^{-1} \cdot X\f$.
/// The typical case is \f$\beta = 0\f$ and \f$\alpha = 1\f$.
void
apply (const Tpetra::MultiVector<scalar_type,local_ordinal_type,global_ordinal_type,node_type>& X,
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4 changes: 2 additions & 2 deletions packages/ifpack2/src/Ifpack2_Details_TriDiSolver_decl.hpp
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Expand Up @@ -131,7 +131,7 @@ class TriDiSolver<MatrixType, false> :
/// \brief Apply the preconditioner to X, putting the result in Y.
///
/// If the result of applying this preconditioner to a vector X is
/// \f$M^{-1} \cdot X$, then this method computes \f$\beta Y + \alpha M^{-1} \cdot X\f$.
/// \f$M^{-1} \cdot X\f$, then this method computes \f$\beta Y + \alpha M^{-1} \cdot X\f$.
/// The typical case is \f$\beta = 0\f$ and \f$\alpha = 1\f$.
void
apply (const Tpetra::MultiVector<scalar_type,local_ordinal_type,global_ordinal_type,node_type>& X,
Expand Down Expand Up @@ -387,7 +387,7 @@ class TriDiSolver<MatrixType, true> :
/// \brief Apply the preconditioner to X, putting the result in Y.
///
/// If the result of applying this preconditioner to a vector X is
/// \f$M^{-1} \cdot X$, then this method computes \f$\beta Y + \alpha M^{-1} \cdot X\f$.
/// \f$M^{-1} \cdot X\f$, then this method computes \f$\beta Y + \alpha M^{-1} \cdot X\f$.
/// The typical case is \f$\beta = 0\f$ and \f$\alpha = 1\f$.
void
apply (const Tpetra::MultiVector<scalar_type,local_ordinal_type,global_ordinal_type,node_type>& X,
Expand Down
4 changes: 2 additions & 2 deletions packages/ifpack2/src/Ifpack2_DiagonalFilter_decl.hpp
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Expand Up @@ -129,7 +129,7 @@ class DiagonalFilter :

//! \brief Returns the maximum number of entries across all rows/columns on this node.
virtual size_t getLocalMaxNumRowEntries() const;

//! The number of degrees of freedom per mesh point.
virtual LocalOrdinal getBlockSize () const;

Expand Down Expand Up @@ -251,7 +251,7 @@ class DiagonalFilter :

//! Returns the Frobenius norm of the matrix.
/** Computes and returns the Frobenius norm of the matrix, defined as:
\f$ \|A\|_F = \sqrt{\sum_{i,j} \|\a_{ij}\|^2} \f$
\f$ \|A\|_F = \sqrt{\sum_{i,j} \|a_{ij}\|^2} \f$
*/
virtual mag_type getFrobeniusNorm() const;

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2 changes: 1 addition & 1 deletion packages/ifpack2/src/Ifpack2_Diagonal_decl.hpp
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Expand Up @@ -163,7 +163,7 @@ class Diagonal :
/// \brief Apply the preconditioner to X, putting the result in Y.
///
/// If the result of applying this preconditioner to a vector X is
/// \f$F \cdot X$, then this method computes \f$\beta Y + \alpha F \cdot X\f$.
/// \f$F \cdot X\f$, then this method computes \f$\beta Y + \alpha F \cdot X\f$.
/// The typical case is \f$\beta = 0\f$ and \f$\alpha = 1\f$.
void
apply (const Tpetra::MultiVector<scalar_type,local_ordinal_type,global_ordinal_type,node_type>& X,
Expand Down
4 changes: 2 additions & 2 deletions packages/ifpack2/src/Ifpack2_DropFilter_decl.hpp
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Expand Up @@ -131,7 +131,7 @@ class DropFilter :

//! \brief Returns the maximum number of entries across all rows/columns on this node.
virtual size_t getLocalMaxNumRowEntries() const;

//! The number of degrees of freedom per mesh point.
virtual LocalOrdinal getBlockSize () const;

Expand Down Expand Up @@ -253,7 +253,7 @@ class DropFilter :

//! Returns the Frobenius norm of the matrix.
/** Computes and returns the Frobenius norm of the matrix, defined as:
\f$ \|A\|_F = \sqrt{\sum_{i,j} \|\a_{ij}\|^2} \f$
\f$ \|A\|_F = \sqrt{\sum_{i,j} \|a_{ij}\|^2} \f$
*/
virtual mag_type getFrobeniusNorm() const;

Expand Down
4 changes: 2 additions & 2 deletions packages/ifpack2/src/Ifpack2_OverlappingRowMatrix_decl.hpp
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Expand Up @@ -160,7 +160,7 @@ class OverlappingRowMatrix :

//! The maximum number of entries in any row on the calling process.
virtual size_t getLocalMaxNumRowEntries() const;

//! The number of degrees of freedom per mesh point.
virtual local_ordinal_type getBlockSize () const;

Expand Down Expand Up @@ -283,7 +283,7 @@ class OverlappingRowMatrix :

//! Returns the Frobenius norm of the matrix.
/** Computes and returns the Frobenius norm of the matrix, defined as:
\f$ \|A\|_F = \sqrt{\sum_{i,j} \|\a_{ij}\|^2} \f$
\f$ \|A\|_F = \sqrt{\sum_{i,j} \|a_{ij}\|^2} \f$
*/
virtual mag_type
getFrobeniusNorm () const;
Expand Down
2 changes: 1 addition & 1 deletion packages/ifpack2/src/Ifpack2_Preconditioner.hpp
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Expand Up @@ -100,7 +100,7 @@ class Preconditioner :
/// @brief Apply the preconditioner to X, putting the result in Y.
///
/// If the result of applying this preconditioner to a vector X is
/// \f$F \cdot X$\f$, then this method computes \f$\beta Y + \alpha F \cdot X\f$.
/// \f$F \cdot X\f$, then this method computes \f$\beta Y + \alpha F \cdot X\f$.
/// The typical case is \f$\beta = 0\f$ and \f$\alpha = 1\f$.
virtual void
apply (const Tpetra::MultiVector<Scalar,LocalOrdinal,GlobalOrdinal,Node> &X,
Expand Down
2 changes: 1 addition & 1 deletion packages/ifpack2/src/Ifpack2_Relaxation_decl.hpp
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Expand Up @@ -147,7 +147,7 @@ iteration $k+1$ of whatever relaxation method we are using. Here,
The Richardson method computes
\f[
x^{(k+1)}_i = x_^{(k)}_i + alpha ( b_i - \sum_{j} A_{ij} x^{(k)}_j ).
x^{(k+1)}_i = x^{(k)}_i + alpha ( b_i - \sum_{j} A_{ij} x^{(k)}_j ).
\f]
The Jacobi method computes
Expand Down
2 changes: 1 addition & 1 deletion packages/ifpack2/src/Ifpack2_ReorderFilter_decl.hpp
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Expand Up @@ -273,7 +273,7 @@ class ReorderFilter :

//! Returns the Frobenius norm of the matrix.
/** Computes and returns the Frobenius norm of the matrix, defined as:
\f$ \|A\|_F = \sqrt{\sum_{i,j} \|\a_{ij}\|^2} \f$
\f$ \|A\|_F = \sqrt{\sum_{i,j} \|a_{ij}\|^2} \f$
*/
virtual mag_type getFrobeniusNorm() const;

Expand Down
2 changes: 1 addition & 1 deletion packages/ifpack2/src/Ifpack2_SingletonFilter_decl.hpp
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Expand Up @@ -238,7 +238,7 @@ class SingletonFilter :

//! Returns the Frobenius norm of the matrix.
/** Computes and returns the Frobenius norm of the matrix, defined as:
\f$ \|A\|_F = \sqrt{\sum_{i,j} \|\a_{ij}\|^2} \f$
\f$ \|A\|_F = \sqrt{\sum_{i,j} \|a_{ij}\|^2} \f$
*/
virtual mag_type getFrobeniusNorm() const;

Expand Down
2 changes: 1 addition & 1 deletion packages/ifpack2/src/Ifpack2_SparsityFilter_decl.hpp
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Expand Up @@ -258,7 +258,7 @@ class SparsityFilter :

//! Returns the Frobenius norm of the matrix.
/** Computes and returns the Frobenius norm of the matrix, defined as:
\f$ \|A\|_F = \sqrt{\sum_{i,j} \|\a_{ij}\|^2} \f$
\f$ \|A\|_F = \sqrt{\sum_{i,j} \|a_{ij}\|^2} \f$
*/
virtual mag_type getFrobeniusNorm() const;

Expand Down
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