#include <deal.II/lac/trilinos_block_sparse_matrix.h>

Inheritance diagram for TrilinosWrappers::BlockSparseMatrix:

Public Types
using	BaseClass = BlockMatrixBase< SparseMatrix >

using	BlockType = BaseClass::BlockType

using	value_type = BaseClass::value_type

using	pointer = BaseClass::pointer

using	const_pointer = BaseClass::const_pointer

using	reference = BaseClass::reference

using	const_reference = BaseClass::const_reference

using	size_type = BaseClass::size_type

using	iterator = BaseClass::iterator

using	const_iterator = BaseClass::const_iterator

using	real_type = typename numbers::NumberTraits< value_type >::real_type

Public Member Functions
	BlockSparseMatrix ()=default

	~BlockSparseMatrix () override

BlockSparseMatrix &	operator= (const BlockSparseMatrix &)=default

BlockSparseMatrix &	operator= (const double d)

void	reinit (const size_type n_block_rows, const size_type n_block_columns)

template<typename BlockSparsityPatternType >
void	reinit (const std::vector< IndexSet > &input_maps, const BlockSparsityPatternType &block_sparsity_pattern, const MPI_Comm &communicator=MPI_COMM_WORLD, const bool exchange_data=false)

template<typename BlockSparsityPatternType >
void	reinit (const BlockSparsityPatternType &block_sparsity_pattern)

void	reinit (const std::vector< IndexSet > &parallel_partitioning, const ::BlockSparseMatrix< double > &dealii_block_sparse_matrix, const MPI_Comm &communicator=MPI_COMM_WORLD, const double drop_tolerance=1e-13)

void	reinit (const ::BlockSparseMatrix< double > &deal_ii_sparse_matrix, const double drop_tolerance=1e-13)

bool	is_compressed () const

void	collect_sizes ()

std::uint64_t	n_nonzero_elements () const

MPI_Comm	get_mpi_communicator () const

std::vector< IndexSet >	locally_owned_domain_indices () const

std::vector< IndexSet >	locally_owned_range_indices () const

template<typename VectorType1 , typename VectorType2 >
void	vmult (VectorType1 &dst, const VectorType2 &src) const

template<typename VectorType1 , typename VectorType2 >
void	Tvmult (VectorType1 &dst, const VectorType2 &src) const

TrilinosScalar	residual (MPI::BlockVector &dst, const MPI::BlockVector &x, const MPI::BlockVector &b) const

TrilinosScalar	residual (MPI::BlockVector &dst, const MPI::Vector &x, const MPI::BlockVector &b) const

TrilinosScalar	residual (MPI::Vector &dst, const MPI::BlockVector &x, const MPI::Vector &b) const

TrilinosScalar	residual (MPI::Vector &dst, const MPI::Vector &x, const MPI::Vector &b) const

template<>
void	reinit (const BlockSparsityPattern &block_sparsity_pattern)

BlockMatrixBase &	copy_from (const BlockMatrixType &source)

BlockType &	block (const unsigned int row, const unsigned int column)

const BlockType &	block (const unsigned int row, const unsigned int column) const

size_type	m () const

size_type	n () const

unsigned int	n_block_rows () const

unsigned int	n_block_cols () const

void	set (const size_type i, const size_type j, const value_type value)

void	set (const std::vector< size_type > &indices, const FullMatrix< number > &full_matrix, const bool elide_zero_values=false)

void	set (const std::vector< size_type > &row_indices, const std::vector< size_type > &col_indices, const FullMatrix< number > &full_matrix, const bool elide_zero_values=false)

void	set (const size_type row, const std::vector< size_type > &col_indices, const std::vector< number > &values, const bool elide_zero_values=false)

void	set (const size_type row, const size_type n_cols, const size_type col_indices, const number values, const bool elide_zero_values=false)

void	add (const size_type i, const size_type j, const value_type value)

void	add (const std::vector< size_type > &indices, const FullMatrix< number > &full_matrix, const bool elide_zero_values=true)

void	add (const std::vector< size_type > &row_indices, const std::vector< size_type > &col_indices, const FullMatrix< number > &full_matrix, const bool elide_zero_values=true)

void	add (const size_type row, const std::vector< size_type > &col_indices, const std::vector< number > &values, const bool elide_zero_values=true)

void	add (const size_type row, const size_type n_cols, const size_type col_indices, const number values, const bool elide_zero_values=true, const bool col_indices_are_sorted=false)

void	add (const value_type factor, const BlockMatrixBase< SparseMatrix > &matrix)

value_type	operator() (const size_type i, const size_type j) const

value_type	el (const size_type i, const size_type j) const

value_type	diag_element (const size_type i) const

void	compress (::VectorOperation::values operation)

BlockMatrixBase &	operator*= (const value_type factor)

BlockMatrixBase &	operator/= (const value_type factor)

void	vmult_add (BlockVectorType &dst, const BlockVectorType &src) const

void	Tvmult_add (BlockVectorType &dst, const BlockVectorType &src) const

value_type	matrix_norm_square (const BlockVectorType &v) const

real_type	frobenius_norm () const

value_type	matrix_scalar_product (const BlockVectorType &u, const BlockVectorType &v) const

value_type	residual (BlockVectorType &dst, const BlockVectorType &x, const BlockVectorType &b) const

void	print (std::ostream &out, const bool alternative_output=false) const

iterator	begin ()

iterator	begin (const size_type r)

const_iterator	begin () const

const_iterator	begin (const size_type r) const

iterator	end ()

iterator	end (const size_type r)

const_iterator	end () const

const_iterator	end (const size_type r) const

const BlockIndices &	get_row_indices () const

const BlockIndices &	get_column_indices () const

std::size_t	memory_consumption () const

Static Public Member Functions
static ::ExceptionBase &	ExcIncompatibleRowNumbers (int arg1, int arg2, int arg3, int arg4)

static ::ExceptionBase &	ExcIncompatibleColNumbers (int arg1, int arg2, int arg3, int arg4)

Protected Member Functions
void	clear ()

void	vmult_block_block (BlockVectorType &dst, const BlockVectorType &src) const

void	vmult_block_nonblock (BlockVectorType &dst, const VectorType &src) const

void	vmult_nonblock_block (VectorType &dst, const BlockVectorType &src) const

void	vmult_nonblock_nonblock (VectorType &dst, const VectorType &src) const

void	Tvmult_block_block (BlockVectorType &dst, const BlockVectorType &src) const

void	Tvmult_block_nonblock (BlockVectorType &dst, const VectorType &src) const

void	Tvmult_nonblock_block (VectorType &dst, const BlockVectorType &src) const

void	Tvmult_nonblock_nonblock (VectorType &dst, const VectorType &src) const

void	prepare_add_operation ()

void	prepare_set_operation ()

Protected Attributes
BlockIndices	row_block_indices

BlockIndices	column_block_indices

Table< 2, SmartPointer< BlockType, BlockMatrixBase< SparseMatrix > > >	sub_objects

Private Member Functions
template<typename VectorType1 , typename VectorType2 >
void	vmult (VectorType1 &dst, const VectorType2 &src, const bool transpose, const std::integral_constant< bool, true >, const std::integral_constant< bool, true >) const

template<typename VectorType1 , typename VectorType2 >
void	vmult (VectorType1 &dst, const VectorType2 &src, const bool transpose, const std::integral_constant< bool, false >, const std::integral_constant< bool, true >) const

template<typename VectorType1 , typename VectorType2 >
void	vmult (VectorType1 &dst, const VectorType2 &src, const bool transpose, const std::integral_constant< bool, true >, const std::integral_constant< bool, false >) const

template<typename VectorType1 , typename VectorType2 >
void	vmult (VectorType1 &dst, const VectorType2 &src, const bool transpose, const std::integral_constant< bool, false >, const std::integral_constant< bool, false >) const

Private Attributes
TemporaryData	temporary_data

Subscriptor functionality
Classes derived from Subscriptor provide a facility to subscribe to this object. This is mostly used by the SmartPointer class.
void	subscribe (std::atomic< bool > *const validity, const std::string &identifier="") const

void	unsubscribe (std::atomic< bool > *const validity, const std::string &identifier="") const

unsigned int	n_subscriptions () const

template<typename StreamType >
void	list_subscribers (StreamType &stream) const

void	list_subscribers () const

template<class Archive >
void	serialize (Archive &ar, const unsigned int version)

static ::ExceptionBase &	ExcInUse (int arg1, std::string arg2, std::string arg3)

static ::ExceptionBase &	ExcNoSubscriber (std::string arg1, std::string arg2)

void	check_no_subscribers () const noexcept

std::atomic< unsigned int >	counter

std::map< std::string, unsigned int >	counter_map

std::vector< std::atomic< bool > * >	validity_pointers

const std::type_info *	object_info

using	map_value_type = decltype(counter_map)::value_type

using	map_iterator = decltype(counter_map)::iterator

static std::mutex	mutex

Detailed Description

Blocked sparse matrix based on the TrilinosWrappers::SparseMatrix class. This class implements the functions that are specific to the Trilinos SparseMatrix base objects for a blocked sparse matrix, and leaves the actual work relaying most of the calls to the individual blocks to the functions implemented in the base class. See there also for a description of when this class is useful.

In contrast to the deal.II-type SparseMatrix class, the Trilinos matrices do not have external objects for the sparsity patterns. Thus, one does not determine the size of the individual blocks of a block matrix of this type by attaching a block sparsity pattern, but by calling reinit() to set the number of blocks and then by setting the size of each block separately. In order to fix the data structures of the block matrix, it is then necessary to let it know that we have changed the sizes of the underlying matrices. For this, one has to call the collect_sizes() function, for much the same reason as is documented with the BlockSparsityPattern class.

@ Block (linear algebra)

Definition at line 71 of file trilinos_block_sparse_matrix.h.

Member Typedef Documentation

◆ real_type

using BlockMatrixBase< SparseMatrix >::real_type = typename numbers::NumberTraits<value_type>::real_type

inherited

Definition at line 362 of file block_matrix_base.h.

Member Function Documentation

◆ reinit()

template<>

void TrilinosWrappers::BlockSparseMatrix::reinit ( const BlockSparsityPattern & block_sparsity_pattern )

Definition at line 142 of file trilinos_block_sparse_matrix.cc.

◆ copy_from()

BlockMatrixBase & BlockMatrixBase< SparseMatrix >::copy_from ( const BlockMatrixType & source )

inherited

Copy the matrix given as argument into the current object.

Copying matrices is an expensive operation that we do not want to happen by accident through compiler generated code for operator=. (This would happen, for example, if one accidentally declared a function argument of the current type by value rather than by reference.) The functionality of copying matrices is implemented in this member function instead. All copy operations of objects of this type therefore require an explicit function call.

The source matrix may be a matrix of arbitrary type, as long as its data type is convertible to the data type of this matrix.

The function returns a reference to this.

◆ block() [1/2]

BlockType & BlockMatrixBase< SparseMatrix >::block	(	const unsigned int	row,
		const unsigned int	column
	)

inherited

Access the block with the given coordinates.

◆ block() [2/2]

const BlockType & BlockMatrixBase< SparseMatrix >::block	(	const unsigned int	row,
		const unsigned int	column
	)		const

inherited

Access the block with the given coordinates. Version for constant objects.

◆ m()

size_type BlockMatrixBase< SparseMatrix >::m ( ) const

inherited

Return the dimension of the codomain (or range) space. Note that the matrix is of dimension \(m \times n\).

◆ n()

size_type BlockMatrixBase< SparseMatrix >::n ( ) const

inherited

Return the dimension of the domain space. Note that the matrix is of dimension \(m \times n\).

◆ n_block_rows()

unsigned int BlockMatrixBase< SparseMatrix >::n_block_rows ( ) const

inherited

Return the number of blocks in a column. Returns zero if no sparsity pattern is presently associated to this matrix.

◆ n_block_cols()

unsigned int BlockMatrixBase< SparseMatrix >::n_block_cols ( ) const

inherited

Return the number of blocks in a row. Returns zero if no sparsity pattern is presently associated to this matrix.

◆ set() [1/5]

void BlockMatrixBase< SparseMatrix >::set	(	const size_type	i,
		const size_type	j,
		const value_type	value
	)

inherited

Set the element (i,j) to value. Throws an error if the entry does not exist or if value is not a finite number. Still, it is allowed to store zero values in non-existent fields.

◆ set() [2/5]

void BlockMatrixBase< SparseMatrix >::set	(	const std::vector< size_type > &	indices,
		const FullMatrix< number > &	full_matrix,
		const bool	elide_zero_values = `false`
	)

inherited

Set all elements given in a FullMatrix into the sparse matrix locations given by indices. In other words, this function writes the elements in full_matrix into the calling matrix, using the local-to-global indexing specified by indices for both the rows and the columns of the matrix. This function assumes a quadratic sparse matrix and a quadratic full_matrix, the usual situation in FE calculations.

The optional parameter elide_zero_values can be used to specify whether zero values should be set anyway or they should be filtered away (and not change the previous content in the respective element if it exists). The default value is false, i.e., even zero values are treated.

◆ set() [3/5]

void BlockMatrixBase< SparseMatrix >::set	(	const std::vector< size_type > &	row_indices,
		const std::vector< size_type > &	col_indices,
		const FullMatrix< number > &	full_matrix,
		const bool	elide_zero_values = `false`
	)

inherited

Same function as before, but now including the possibility to use rectangular full_matrices and different local-to-global indexing on rows and columns, respectively.

◆ set() [4/5]

void BlockMatrixBase< SparseMatrix >::set	(	const size_type	row,
		const std::vector< size_type > &	col_indices,
		const std::vector< number > &	values,
		const bool	elide_zero_values = `false`
	)

inherited

Set several elements in the specified row of the matrix with column indices as given by col_indices to the respective value.

The optional parameter elide_zero_values can be used to specify whether zero values should be set anyway or they should be filtered away (and not change the previous content in the respective element if it exists). The default value is false, i.e., even zero values are treated.

◆ set() [5/5]

void BlockMatrixBase< SparseMatrix >::set	(	const size_type	row,
		const size_type	n_cols,
		const size_type *	col_indices,
		const number *	values,
		const bool	elide_zero_values = `false`
	)

inherited

Set several elements to values given by values in a given row in columns given by col_indices into the sparse matrix.

The optional parameter elide_zero_values can be used to specify whether zero values should be inserted anyway or they should be filtered away. The default value is false, i.e., even zero values are inserted/replaced.

◆ add() [1/6]

void BlockMatrixBase< SparseMatrix >::add	(	const size_type	i,
		const size_type	j,
		const value_type	value
	)

inherited

Add value to the element (i,j). Throws an error if the entry does not exist or if value is not a finite number. Still, it is allowed to store zero values in non-existent fields.

◆ add() [2/6]

void BlockMatrixBase< SparseMatrix >::add	(	const std::vector< size_type > &	indices,
		const FullMatrix< number > &	full_matrix,
		const bool	elide_zero_values = `true`
	)

inherited

Add all elements given in a FullMatrix<double> into sparse matrix locations given by indices. In other words, this function adds the elements in full_matrix to the respective entries in calling matrix, using the local-to-global indexing specified by indices for both the rows and the columns of the matrix. This function assumes a quadratic sparse matrix and a quadratic full_matrix, the usual situation in FE calculations.

The optional parameter elide_zero_values can be used to specify whether zero values should be added anyway or these should be filtered away and only non-zero data is added. The default value is true, i.e., zero values won't be added into the matrix.

◆ add() [3/6]

void BlockMatrixBase< SparseMatrix >::add	(	const std::vector< size_type > &	row_indices,
		const std::vector< size_type > &	col_indices,
		const FullMatrix< number > &	full_matrix,
		const bool	elide_zero_values = `true`
	)

inherited

Same function as before, but now including the possibility to use rectangular full_matrices and different local-to-global indexing on rows and columns, respectively.

◆ add() [4/6]

void BlockMatrixBase< SparseMatrix >::add	(	const size_type	row,
		const std::vector< size_type > &	col_indices,
		const std::vector< number > &	values,
		const bool	elide_zero_values = `true`
	)

inherited

Set several elements in the specified row of the matrix with column indices as given by col_indices to the respective value.

The optional parameter elide_zero_values can be used to specify whether zero values should be added anyway or these should be filtered away and only non-zero data is added. The default value is true, i.e., zero values won't be added into the matrix.

◆ add() [5/6]

void BlockMatrixBase< SparseMatrix >::add	(	const size_type	row,
		const size_type	n_cols,
		const size_type *	col_indices,
		const number *	values,
		const bool	elide_zero_values = `true`,
		const bool	col_indices_are_sorted = `false`
	)

inherited

Add an array of values given by values in the given global matrix row at columns specified by col_indices in the sparse matrix.

The optional parameter elide_zero_values can be used to specify whether zero values should be added anyway or these should be filtered away and only non-zero data is added. The default value is true, i.e., zero values won't be added into the matrix.

◆ add() [6/6]

void BlockMatrixBase< SparseMatrix >::add	(	const value_type	factor,
		const BlockMatrixBase< SparseMatrix > &	matrix
	)

inherited

Add matrix scaled by factor to this matrix, i.e. the matrix factor*matrix is added to this. If the sparsity pattern of the calling matrix does not contain all the elements in the sparsity pattern of the input matrix, this function will throw an exception.

Depending on MatrixType, however, additional restrictions might arise. Some sparse matrix formats require matrix to be based on the same sparsity pattern as the calling matrix.

◆ operator()()

value_type BlockMatrixBase< SparseMatrix >::operator()	(	const size_type	i,
		const size_type	j
	)		const

inherited

Return the value of the entry (i,j). This may be an expensive operation and you should always take care where to call this function. In order to avoid abuse, this function throws an exception if the wanted element does not exist in the matrix.

◆ el()

value_type BlockMatrixBase< SparseMatrix >::el	(	const size_type	i,
		const size_type	j
	)		const

inherited

This function is mostly like operator()() in that it returns the value of the matrix entry (i,j). The only difference is that if this entry does not exist in the sparsity pattern, then instead of raising an exception, zero is returned. While this may be convenient in some cases, note that it is simple to write algorithms that are slow compared to an optimal solution, since the sparsity of the matrix is not used.

◆ diag_element()

value_type BlockMatrixBase< SparseMatrix >::diag_element ( const size_type i ) const

inherited

Return the main diagonal element in the ith row. This function throws an error if the matrix is not quadratic and also if the diagonal blocks of the matrix are not quadratic.

This function is considerably faster than the operator()(), since for quadratic matrices, the diagonal entry may be the first to be stored in each row and access therefore does not involve searching for the right column number.

◆ compress()

void BlockMatrixBase< SparseMatrix >::compress ( ::VectorOperation::values operation )

inherited

Call the compress() function on all the subblocks of the matrix.

See Compressing distributed objects for more information.

◆ operator*=()

BlockMatrixBase & BlockMatrixBase< SparseMatrix >::operator*= ( const value_type factor )

inherited

Multiply the entire matrix by a fixed factor.

◆ operator/=()

BlockMatrixBase & BlockMatrixBase< SparseMatrix >::operator/= ( const value_type factor )

inherited

Divide the entire matrix by a fixed factor.

◆ vmult_add()

void BlockMatrixBase< SparseMatrix >::vmult_add	(	BlockVectorType &	dst,
		const BlockVectorType &	src
	)		const

inherited

Adding Matrix-vector multiplication. Add \(M*src\) on \(dst\) with \(M\) being this matrix.

◆ Tvmult_add()

void BlockMatrixBase< SparseMatrix >::Tvmult_add	(	BlockVectorType &	dst,
		const BlockVectorType &	src
	)		const

inherited

Adding Matrix-vector multiplication. Add M^Tsrc to dst with M being this matrix. This function does the same as vmult_add() but takes the transposed matrix.

◆ matrix_norm_square()

value_type BlockMatrixBase< SparseMatrix >::matrix_norm_square ( const BlockVectorType & v ) const

inherited

Return the norm of the vector v with respect to the norm induced by this matrix, i.e. v^TMv). This is useful, e.g. in the finite element context, where the L^T-norm of a function equals the matrix norm with respect to the mass matrix of the vector representing the nodal values of the finite element function. Note that even though the function's name might suggest something different, for historic reasons not the norm but its square is returned, as defined above by the scalar product.

Obviously, the matrix needs to be square for this operation.

◆ frobenius_norm()

real_type BlockMatrixBase< SparseMatrix >::frobenius_norm ( ) const

inherited

Return the frobenius norm of the matrix, i.e. the square root of the sum of squares of all entries in the matrix.

◆ matrix_scalar_product()

value_type BlockMatrixBase< SparseMatrix >::matrix_scalar_product	(	const BlockVectorType &	u,
		const BlockVectorType &	v
	)		const

inherited

Compute the matrix scalar product \(\left(u,Mv\right)\).

◆ residual()

value_type BlockMatrixBase< SparseMatrix >::residual	(	BlockVectorType &	dst,
		const BlockVectorType &	x,
		const BlockVectorType &	b
	)		const

inherited

Compute the residual r=b-Ax. Write the residual into dst.

◆ print()

void BlockMatrixBase< SparseMatrix >::print	(	std::ostream &	out,
		const bool	alternative_output = `false`
	)		const

inherited

Print the matrix to the given stream, using the format (line,col) value, i.e. one nonzero entry of the matrix per line. The optional flag outputs the sparsity pattern in a different style according to the underlying sparse matrix type.

◆ begin() [1/4]

iterator BlockMatrixBase< SparseMatrix >::begin ( )

inherited

Iterator starting at the first entry.

◆ begin() [2/4]

iterator BlockMatrixBase< SparseMatrix >::begin ( const size_type r )

inherited

Iterator starting at the first entry of row r.

◆ begin() [3/4]

const_iterator BlockMatrixBase< SparseMatrix >::begin ( ) const

inherited

Iterator starting at the first entry.

◆ begin() [4/4]

const_iterator BlockMatrixBase< SparseMatrix >::begin ( const size_type r ) const

inherited

Iterator starting at the first entry of row r.

◆ end() [1/4]

iterator BlockMatrixBase< SparseMatrix >::end ( )

inherited

Final iterator.

◆ end() [2/4]

iterator BlockMatrixBase< SparseMatrix >::end ( const size_type r )

inherited

Final iterator of row r.

◆ end() [3/4]

const_iterator BlockMatrixBase< SparseMatrix >::end ( ) const

inherited

Final iterator.

◆ end() [4/4]

const_iterator BlockMatrixBase< SparseMatrix >::end ( const size_type r ) const

inherited

Final iterator of row r.

◆ get_row_indices()

const BlockIndices & BlockMatrixBase< SparseMatrix >::get_row_indices ( ) const

inherited

Return a reference to the underlying BlockIndices data of the rows.

◆ get_column_indices()

const BlockIndices & BlockMatrixBase< SparseMatrix >::get_column_indices ( ) const

inherited

Return a reference to the underlying BlockIndices data of the columns.

◆ memory_consumption()

std::size_t BlockMatrixBase< SparseMatrix >::memory_consumption ( ) const

inherited

Determine an estimate for the memory consumption (in bytes) of this object. Note that only the memory reserved on the current processor is returned in case this is called in an MPI-based program.

◆ clear()

void BlockMatrixBase< SparseMatrix >::clear ( )

protectedinherited

Release all memory and return to a state just like after having called the default constructor. It also forgets the sparsity pattern it was previously tied to.

This calls clear for all sub-matrices and then resets this object to have no blocks at all.

This function is protected since it may be necessary to release additional structures. A derived class can make it public again, if it is sufficient.

◆ vmult_block_block()

void BlockMatrixBase< SparseMatrix >::vmult_block_block	(	BlockVectorType &	dst,
		const BlockVectorType &	src
	)		const

protectedinherited

Matrix-vector multiplication: let \(dst = M*src\) with \(M\) being this matrix.

Due to problems with deriving template arguments between the block and non-block versions of the vmult/Tvmult functions, the actual functions are implemented in derived classes, with implementations forwarding the calls to the implementations provided here under a unique name for which template arguments can be derived by the compiler.

◆ vmult_block_nonblock()

void BlockMatrixBase< SparseMatrix >::vmult_block_nonblock	(	BlockVectorType &	dst,
		const VectorType &	src
	)		const

protectedinherited

Matrix-vector multiplication. Just like the previous function, but only applicable if the matrix has only one block column.

Due to problems with deriving template arguments between the block and non-block versions of the vmult/Tvmult functions, the actual functions are implemented in derived classes, with implementations forwarding the calls to the implementations provided here under a unique name for which template arguments can be derived by the compiler.

◆ vmult_nonblock_block()

void BlockMatrixBase< SparseMatrix >::vmult_nonblock_block	(	VectorType &	dst,
		const BlockVectorType &	src
	)		const

protectedinherited

Matrix-vector multiplication. Just like the previous function, but only applicable if the matrix has only one block row.

Due to problems with deriving template arguments between the block and non-block versions of the vmult/Tvmult functions, the actual functions are implemented in derived classes, with implementations forwarding the calls to the implementations provided here under a unique name for which template arguments can be derived by the compiler.

◆ vmult_nonblock_nonblock()

void BlockMatrixBase< SparseMatrix >::vmult_nonblock_nonblock	(	VectorType &	dst,
		const VectorType &	src
	)		const

protectedinherited

Matrix-vector multiplication. Just like the previous function, but only applicable if the matrix has only one block.

Due to problems with deriving template arguments between the block and non-block versions of the vmult/Tvmult functions, the actual functions are implemented in derived classes, with implementations forwarding the calls to the implementations provided here under a unique name for which template arguments can be derived by the compiler.

◆ Tvmult_block_block()

void BlockMatrixBase< SparseMatrix >::Tvmult_block_block	(	BlockVectorType &	dst,
		const BlockVectorType &	src
	)		const

protectedinherited

Matrix-vector multiplication: let \(dst = M^T*src\) with \(M\) being this matrix. This function does the same as vmult() but takes the transposed matrix.

Due to problems with deriving template arguments between the block and non-block versions of the vmult/Tvmult functions, the actual functions are implemented in derived classes, with implementations forwarding the calls to the implementations provided here under a unique name for which template arguments can be derived by the compiler.

◆ Tvmult_block_nonblock()

void BlockMatrixBase< SparseMatrix >::Tvmult_block_nonblock	(	BlockVectorType &	dst,
		const VectorType &	src
	)		const

protectedinherited

Matrix-vector multiplication. Just like the previous function, but only applicable if the matrix has only one block row.

Due to problems with deriving template arguments between the block and non-block versions of the vmult/Tvmult functions, the actual functions are implemented in derived classes, with implementations forwarding the calls to the implementations provided here under a unique name for which template arguments can be derived by the compiler.

◆ Tvmult_nonblock_block()

void BlockMatrixBase< SparseMatrix >::Tvmult_nonblock_block	(	VectorType &	dst,
		const BlockVectorType &	src
	)		const

protectedinherited

Matrix-vector multiplication. Just like the previous function, but only applicable if the matrix has only one block column.

Due to problems with deriving template arguments between the block and non-block versions of the vmult/Tvmult functions, the actual functions are implemented in derived classes, with implementations forwarding the calls to the implementations provided here under a unique name for which template arguments can be derived by the compiler.

◆ Tvmult_nonblock_nonblock()

void BlockMatrixBase< SparseMatrix >::Tvmult_nonblock_nonblock	(	VectorType &	dst,
		const VectorType &	src
	)		const

protectedinherited

Matrix-vector multiplication. Just like the previous function, but only applicable if the matrix has only one block.

Due to problems with deriving template arguments between the block and non-block versions of the vmult/Tvmult functions, the actual functions are implemented in derived classes, with implementations forwarding the calls to the implementations provided here under a unique name for which template arguments can be derived by the compiler.

◆ prepare_add_operation()

void BlockMatrixBase< SparseMatrix >::prepare_add_operation ( )

protectedinherited

Some matrix types, in particular PETSc, need to synchronize set and add operations. This has to be done for all matrices in the BlockMatrix. This routine prepares adding of elements by notifying all blocks. Called by all internal routines before adding elements.

◆ prepare_set_operation()

void BlockMatrixBase< SparseMatrix >::prepare_set_operation ( )

protectedinherited

Notifies all blocks to let them prepare for setting elements, see prepare_add_operation().

Member Data Documentation

◆ row_block_indices

BlockIndices BlockMatrixBase< SparseMatrix >::row_block_indices

protectedinherited

Index arrays for rows and columns.

Definition at line 846 of file block_matrix_base.h.

◆ column_block_indices

BlockIndices BlockMatrixBase< SparseMatrix >::column_block_indices

protectedinherited

Definition at line 847 of file block_matrix_base.h.

◆ sub_objects

Table<2, SmartPointer<BlockType, BlockMatrixBase<SparseMatrix > > > BlockMatrixBase< SparseMatrix >::sub_objects

protectedinherited

Array of sub-matrices.

Definition at line 852 of file block_matrix_base.h.

◆ temporary_data

TemporaryData BlockMatrixBase< SparseMatrix >::temporary_data

privateinherited

A set of scratch arrays that can be used by the add() and set() functions that take pointers to data to pre-sort indices before use. Access from multiple threads is synchronized via the mutex variable that is part of the structure.

Definition at line 1064 of file block_matrix_base.h.

The documentation for this class was generated from the following files:

include/deal.II/lac/trilinos_block_sparse_matrix.h
source/lac/trilinos_block_sparse_matrix.cc

Public Types

Public Member Functions

Static Public Member Functions

Protected Member Functions

Protected Attributes

Private Member Functions

Private Attributes

Subscriptor functionality

Detailed Description

Member Typedef Documentation

◆ real_type

Member Function Documentation

◆ reinit()

◆ copy_from()

◆ block() [1/2]

◆ block() [2/2]

◆ m()

◆ n()

◆ n_block_rows()

◆ n_block_cols()

◆ set() [1/5]

◆ set() [2/5]

◆ set() [3/5]

◆ set() [4/5]

◆ set() [5/5]

◆ add() [1/6]

◆ add() [2/6]

◆ add() [3/6]

◆ add() [4/6]

◆ add() [5/6]

◆ add() [6/6]

◆ operator()()

◆ el()

◆ diag_element()

◆ compress()

◆ operator*=()

◆ operator/=()

◆ vmult_add()

◆ Tvmult_add()

◆ matrix_norm_square()

◆ frobenius_norm()

◆ matrix_scalar_product()

◆ residual()

◆ print()

◆ begin() [1/4]

◆ begin() [2/4]

◆ begin() [3/4]

◆ begin() [4/4]

◆ end() [1/4]

◆ end() [2/4]

◆ end() [3/4]

◆ end() [4/4]

◆ get_row_indices()

◆ get_column_indices()

◆ memory_consumption()

◆ clear()

◆ vmult_block_block()

◆ vmult_block_nonblock()

◆ vmult_nonblock_block()

◆ vmult_nonblock_nonblock()

◆ Tvmult_block_block()

◆ Tvmult_block_nonblock()

◆ Tvmult_nonblock_block()

◆ Tvmult_nonblock_nonblock()

◆ prepare_add_operation()

◆ prepare_set_operation()

Member Data Documentation

◆ row_block_indices

◆ column_block_indices

◆ sub_objects

◆ temporary_data