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

Inheritance diagram for BlockMatrixBase< MatrixType >:

Classes
struct	TemporaryData

Public Types
using	BlockType = MatrixType

using	value_type = typename BlockType::value_type

Public Member Functions
	BlockMatrixBase ()=default

	~BlockMatrixBase () override

template<class BlockMatrixType >
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)

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

template<typename number >
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)

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

template<typename number >
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)

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

template<typename number >
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)

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

template<typename number >
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< MatrixType > &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)

template<class BlockVectorType >
void	vmult_add (BlockVectorType &dst, const BlockVectorType &src) const

template<class BlockVectorType >
void	Tvmult_add (BlockVectorType &dst, const BlockVectorType &src) const

template<class BlockVectorType >
value_type	matrix_norm_square (const BlockVectorType &v) const

template<class BlockVectorType >
value_type	matrix_scalar_product (const BlockVectorType &u, const BlockVectorType &v) const

template<class BlockVectorType >
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	end ()

iterator	begin (const size_type r)

iterator	end (const size_type r)

const_iterator	begin () const

const_iterator	end () const

const_iterator	begin (const size_type r) 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

Public Member Functions inherited from Subscriptor
	Subscriptor ()

	Subscriptor (const Subscriptor &)

	Subscriptor (Subscriptor &&) noexcept

virtual	~Subscriptor ()

Subscriptor &	operator= (const Subscriptor &)

Subscriptor &	operator= (Subscriptor &&) noexcept

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 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)

Static Public Member Functions inherited from Subscriptor
static ::ExceptionBase &	ExcInUse (int arg1, std::string arg2, std::string arg3)

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

Protected Member Functions
void	clear ()

void	collect_sizes ()

template<class BlockVectorType >
void	vmult_block_block (BlockVectorType &dst, const BlockVectorType &src) const

template<class BlockVectorType , class VectorType >
void	vmult_block_nonblock (BlockVectorType &dst, const VectorType &src) const

template<class BlockVectorType , class VectorType >
void	vmult_nonblock_block (VectorType &dst, const BlockVectorType &src) const

template<class VectorType >
void	vmult_nonblock_nonblock (VectorType &dst, const VectorType &src) const

template<class BlockVectorType >
void	Tvmult_block_block (BlockVectorType &dst, const BlockVectorType &src) const

template<class BlockVectorType , class VectorType >
void	Tvmult_block_nonblock (BlockVectorType &dst, const VectorType &src) const

template<class BlockVectorType , class VectorType >
void	Tvmult_nonblock_block (VectorType &dst, const BlockVectorType &src) const

template<class VectorType >
void	Tvmult_nonblock_nonblock (VectorType &dst, const VectorType &src) const

void	prepare_add_operation ()

void	prepare_set_operation ()

Protected Attributes
BlockIndices	row_block_indices

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

Private Attributes
TemporaryData	temporary_data

Friends
template<typename , bool >
class	BlockMatrixIterators::Accessor

template<typename >
class	MatrixIterator

Detailed Description

template<typename MatrixType>
class BlockMatrixBase< MatrixType >

Blocked matrix class. The behaviour of objects of this type is almost as for the usual matrix objects, with most of the functions being implemented in both classes. The main difference is that the matrix represented by this object is composed of an array of matrices (e.g. of type SparseMatrix<number>) and all accesses to the elements of this object are relayed to accesses of the base matrices. The actual type of the individual blocks of this matrix is the type of the template argument, and can, for example be the usual SparseMatrix or PETScWrappers::SparseMatrix.

In addition to the usual matrix access and linear algebra functions, there are functions block() which allow access to the different blocks of the matrix. This may, for example, be of help when you want to implement Schur complement methods, or block preconditioners, where each block belongs to a specific component of the equation you are presently discretizing.

Note that the numbers of blocks and rows are implicitly determined by the sparsity pattern objects used.

Objects of this type are frequently used when a system of differential equations has solutions with variables that fall into different classes. For example, solutions of the Stokes or Navier-Stokes equations have dim velocity components and one pressure component. In this case, it may make sense to consider the linear system of equations as a system of 2x2 blocks, and one can construct preconditioners or solvers based on this 2x2 block structure. This class can help you in these cases, as it allows to view the matrix alternatively as one big matrix, or as a number of individual blocks.

Inheriting from this class

Since this class simply forwards its calls to the subobjects (if necessary after adjusting indices denoting which subobject is meant), this class is completely independent of the actual type of the subobject. The functions that set up block matrices and destroy them, however, have to be implemented in derived classes. These functions also have to fill the data members provided by this base class, as they are only used passively in this class.

Most of the functions take a vector or block vector argument. These functions can, in general, only successfully be compiled if the individual blocks of this matrix implement the respective functions operating on the vector type in question. For example, if you have a block sparse matrix over deal.II SparseMatrix objects, then you will likely not be able to form the matrix-vector multiplication with a block vector over PETScWrappers::SparseMatrix objects. If you attempt anyway, you will likely get a number of compiler errors.

Note: Instantiations for this template are provided for <float> and <double>; others can be generated in application programs (see the section on Template instantiations in the manual).

See also: Block (linear algebra)

Author: Wolfgang Bangerth, 2000, 2004

Definition at line 1865 of file affine_constraints.h.

Member Typedef Documentation

◆ BlockType

template<typename MatrixType>

using BlockMatrixBase< MatrixType >::BlockType = MatrixType

Typedef the type of the underlying matrix.

Definition at line 360 of file block_matrix_base.h.

◆ value_type

template<typename MatrixType>

using BlockMatrixBase< MatrixType >::value_type = typename BlockType::value_type

Type of matrix entries. These are analogous to alias in the standard library containers.

Definition at line 366 of file block_matrix_base.h.

Constructor & Destructor Documentation

◆ BlockMatrixBase()

template<typename MatrixType>

BlockMatrixBase< MatrixType >::BlockMatrixBase ( )

default

Default constructor.

◆ ~BlockMatrixBase()

template<typename MatrixType>

BlockMatrixBase< MatrixType >::~BlockMatrixBase ( )

override

Destructor.

Member Function Documentation

◆ copy_from()

template<typename MatrixType>

template<class BlockMatrixType >

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

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]

template<typename MatrixType>

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

Access the block with the given coordinates.

◆ block() [2/2]

template<typename MatrixType>

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

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

◆ m()

template<typename MatrixType>

size_type BlockMatrixBase< MatrixType >::m ( ) const

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

◆ n()

template<typename MatrixType>

size_type BlockMatrixBase< MatrixType >::n ( ) const

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

◆ n_block_rows()

template<typename MatrixType>

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

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

◆ n_block_cols()

template<typename MatrixType>

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

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

◆ set() [1/5]

template<typename MatrixType>

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

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]

template<typename MatrixType>

template<typename number >

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

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]

template<typename MatrixType>

template<typename number >

void BlockMatrixBase< MatrixType >::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`
	)

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]

template<typename MatrixType>

template<typename number >

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

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]

template<typename MatrixType>

template<typename number >

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

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]

template<typename MatrixType>

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

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]

template<typename MatrixType>

template<typename number >

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

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]

template<typename MatrixType>

template<typename number >

void BlockMatrixBase< MatrixType >::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`
	)

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]

template<typename MatrixType>

template<typename number >

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

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]

template<typename MatrixType>

template<typename number >

void BlockMatrixBase< MatrixType >::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`
	)

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]

template<typename MatrixType>

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

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()()

template<typename MatrixType>

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

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()

template<typename MatrixType>

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

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()

template<typename MatrixType>

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

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()

template<typename MatrixType>

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

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

See Compressing distributed objects for more information.

◆ operator*=()

template<typename MatrixType>

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

Multiply the entire matrix by a fixed factor.

◆ operator/=()

template<typename MatrixType>

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

Divide the entire matrix by a fixed factor.

◆ vmult_add()

template<typename MatrixType>

template<class BlockVectorType >

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

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

◆ Tvmult_add()

template<typename MatrixType>

template<class BlockVectorType >

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

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()

template<typename MatrixType>

template<class BlockVectorType >

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

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.

◆ matrix_scalar_product()

template<typename MatrixType>

template<class BlockVectorType >

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

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

◆ residual()

template<typename MatrixType>

template<class BlockVectorType >

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

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

◆ print()

template<typename MatrixType>

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

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]

template<typename MatrixType>

iterator BlockMatrixBase< MatrixType >::begin ( )

Iterator starting at the first entry.

◆ end() [1/4]

template<typename MatrixType>

iterator BlockMatrixBase< MatrixType >::end ( )

Final iterator.

◆ begin() [2/4]

template<typename MatrixType>

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

Iterator starting at the first entry of row r.

◆ end() [2/4]

template<typename MatrixType>

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

Final iterator of row r.

◆ begin() [3/4]

template<typename MatrixType>

const_iterator BlockMatrixBase< MatrixType >::begin ( ) const

Iterator starting at the first entry.

◆ end() [3/4]

template<typename MatrixType>

const_iterator BlockMatrixBase< MatrixType >::end ( ) const

Final iterator.

◆ begin() [4/4]

template<typename MatrixType>

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

Iterator starting at the first entry of row r.

◆ end() [4/4]

template<typename MatrixType>

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

Final iterator of row r.

◆ get_row_indices()

template<typename MatrixType>

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

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

◆ get_column_indices()

template<typename MatrixType>

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

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

◆ memory_consumption()

template<typename MatrixType>

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

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()

template<typename MatrixType>

void BlockMatrixBase< MatrixType >::clear ( )

protected

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.

◆ collect_sizes()

template<typename MatrixType>

void BlockMatrixBase< MatrixType >::collect_sizes ( )

protected

This function collects the sizes of the sub-objects and stores them in internal arrays, in order to be able to relay global indices into the matrix to indices into the subobjects. You must call this function each time after you have changed the size of the sub-objects.

Derived classes should call this function whenever the size of the sub- objects has changed and the X_block_indices arrays need to be updated.

Note that this function is not public since not all derived classes need to export its interface. For example, for the usual deal.II SparseMatrix class, the sizes are implicitly determined whenever reinit() is called, and individual blocks cannot be resized. For that class, this function therefore does not have to be public. On the other hand, for the PETSc classes, there is no associated sparsity pattern object that determines the block sizes, and for these the function needs to be publicly available. These classes therefore export this function.

◆ vmult_block_block()

template<typename MatrixType>

template<class BlockVectorType >

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

protected

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()

template<typename MatrixType>

template<class BlockVectorType , class VectorType >

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

protected

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()

template<typename MatrixType>

template<class BlockVectorType , class VectorType >

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

protected

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()

template<typename MatrixType>

template<class VectorType >

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

protected

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()

template<typename MatrixType>

template<class BlockVectorType >

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

protected

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()

template<typename MatrixType>

template<class BlockVectorType , class VectorType >

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

protected

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()

template<typename MatrixType>

template<class BlockVectorType , class VectorType >

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

protected

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()

template<typename MatrixType>

template<class VectorType >

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

protected

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()

template<typename MatrixType>

void BlockMatrixBase< MatrixType >::prepare_add_operation ( )

protected

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()

template<typename MatrixType>

void BlockMatrixBase< MatrixType >::prepare_set_operation ( )

protected

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

Friends And Related Function Documentation

◆ BlockMatrixIterators::Accessor

template<typename MatrixType>

template<typename , bool >

friend class BlockMatrixIterators::Accessor

friend

Make the iterator class a friend. We have to work around a compiler bug here again.

Definition at line 1068 of file block_matrix_base.h.

Member Data Documentation

◆ row_block_indices

template<typename MatrixType>

BlockIndices BlockMatrixBase< MatrixType >::row_block_indices

protected

Index arrays for rows and columns.

Definition at line 843 of file block_matrix_base.h.

◆ sub_objects

template<typename MatrixType>

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

protected

Array of sub-matrices.

Definition at line 849 of file block_matrix_base.h.

◆ temporary_data

template<typename MatrixType>

TemporaryData BlockMatrixBase< MatrixType >::temporary_data

private

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 1061 of file block_matrix_base.h.

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

deal.II/lac/affine_constraints.h
deal.II/lac/block_matrix_base.h

Classes

Public Types

Public Member Functions

Static Public Member Functions

Protected Member Functions

Protected Attributes

Private Attributes

Friends

Detailed Description

template<typename MatrixType> class BlockMatrixBase< MatrixType >

Inheriting from this class

Member Typedef Documentation

◆ BlockType

◆ value_type

Constructor & Destructor Documentation

◆ BlockMatrixBase()

◆ ~BlockMatrixBase()

Member Function Documentation

◆ 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()

◆ matrix_scalar_product()

◆ residual()

◆ print()

◆ begin() [1/4]

◆ end() [1/4]

◆ begin() [2/4]

◆ end() [2/4]

◆ begin() [3/4]

◆ end() [3/4]

◆ begin() [4/4]

◆ end() [4/4]

◆ get_row_indices()

◆ get_column_indices()

◆ memory_consumption()

◆ clear()

◆ collect_sizes()

◆ 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()

Friends And Related Function Documentation

◆ BlockMatrixIterators::Accessor

Member Data Documentation

◆ row_block_indices

◆ sub_objects

◆ temporary_data

template<typename MatrixType>
class BlockMatrixBase< MatrixType >