Reference documentation for deal.II version 9.1.1
\(\newcommand{\dealcoloneq}{\mathrel{\vcenter{:}}=}\)
Public Types | Static Public Member Functions | Private Attributes | List of all members
BlockSparseMatrix< number > Class Template Reference

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

Inheritance diagram for BlockSparseMatrix< number >:
[legend]

Public Types

using BaseClass = BlockMatrixBase< SparseMatrix< number > >
 
using BlockType = typename BaseClass::BlockType
 
using value_type = typename BaseClass::value_type
 
- Public Types inherited from BlockMatrixBase< SparseMatrix< number > >
using BlockType = SparseMatrix< number >
 
using value_type = typename BlockType::value_type
 

Public Member Functions

Constructors and initialization
 BlockSparseMatrix ()=default
 
 BlockSparseMatrix (const BlockSparsityPattern &sparsity)
 
virtual ~BlockSparseMatrix () override
 
BlockSparseMatrixoperator= (const BlockSparseMatrix &)
 
BlockSparseMatrixoperator= (const double d)
 
void clear ()
 
virtual void reinit (const BlockSparsityPattern &sparsity)
 
Information on the matrix
bool empty () const
 
size_type get_row_length (const size_type row) const
 
size_type n_nonzero_elements () const
 
size_type n_actually_nonzero_elements (const double threshold=0.0) const
 
const BlockSparsityPatternget_sparsity_pattern () const
 
std::size_t memory_consumption () const
 
Multiplications
template<typename block_number >
void vmult (BlockVector< block_number > &dst, const BlockVector< block_number > &src) const
 
template<typename block_number , typename nonblock_number >
void vmult (BlockVector< block_number > &dst, const Vector< nonblock_number > &src) const
 
template<typename block_number , typename nonblock_number >
void vmult (Vector< nonblock_number > &dst, const BlockVector< block_number > &src) const
 
template<typename nonblock_number >
void vmult (Vector< nonblock_number > &dst, const Vector< nonblock_number > &src) const
 
template<typename block_number >
void Tvmult (BlockVector< block_number > &dst, const BlockVector< block_number > &src) const
 
template<typename block_number , typename nonblock_number >
void Tvmult (BlockVector< block_number > &dst, const Vector< nonblock_number > &src) const
 
template<typename block_number , typename nonblock_number >
void Tvmult (Vector< nonblock_number > &dst, const BlockVector< block_number > &src) const
 
template<typename nonblock_number >
void Tvmult (Vector< nonblock_number > &dst, const Vector< nonblock_number > &src) const
 
Preconditioning methods
template<class BlockVectorType >
void precondition_Jacobi (BlockVectorType &dst, const BlockVectorType &src, const number omega=1.) const
 
template<typename number2 >
void precondition_Jacobi (Vector< number2 > &dst, const Vector< number2 > &src, const number omega=1.) const
 
Input/Output
void print_formatted (std::ostream &out, const unsigned int precision=3, const bool scientific=true, const unsigned int width=0, const char *zero_string=" ", const double denominator=1.) const
 
- Public Member Functions inherited from BlockMatrixBase< SparseMatrix< number > >
 BlockMatrixBase ()=default
 
 ~BlockMatrixBase () override
 
BlockMatrixBasecopy_from (const BlockMatrixType &source)
 
BlockTypeblock (const unsigned int row, const unsigned int column)
 
const BlockTypeblock (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< number > > &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)
 
BlockMatrixBaseoperator*= (const value_type factor)
 
BlockMatrixBaseoperator/= (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
 
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 BlockIndicesget_row_indices () const
 
const BlockIndicesget_column_indices () const
 
std::size_t memory_consumption () const
 
- Public Member Functions inherited from Subscriptor
 Subscriptor ()
 
 Subscriptor (const Subscriptor &)
 
 Subscriptor (Subscriptor &&) noexcept
 
virtual ~Subscriptor ()
 
Subscriptoroperator= (const Subscriptor &)
 
Subscriptoroperator= (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 ::ExceptionBaseExcBlockDimensionMismatch ()
 
- Static Public Member Functions inherited from BlockMatrixBase< SparseMatrix< number > >
static ::ExceptionBaseExcIncompatibleRowNumbers (int arg1, int arg2, int arg3, int arg4)
 
static ::ExceptionBaseExcIncompatibleColNumbers (int arg1, int arg2, int arg3, int arg4)
 
- Static Public Member Functions inherited from Subscriptor
static ::ExceptionBaseExcInUse (int arg1, std::string arg2, std::string arg3)
 
static ::ExceptionBaseExcNoSubscriber (std::string arg1, std::string arg2)
 

Private Attributes

SmartPointer< const BlockSparsityPattern, BlockSparseMatrix< number > > sparsity_pattern
 

Additional Inherited Members

- Protected Member Functions inherited from BlockMatrixBase< SparseMatrix< number > >
void clear ()
 
void collect_sizes ()
 
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 inherited from BlockMatrixBase< SparseMatrix< number > >
BlockIndices row_block_indices
 
Table< 2, SmartPointer< BlockType, BlockMatrixBase< SparseMatrix< number > > > > sub_objects
 

Detailed Description

template<typename number>
class BlockSparseMatrix< number >

Blocked sparse matrix based on the SparseMatrix class. This class implements the functions that are specific to the 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.

See also
Block (linear algebra)
Author
Wolfgang Bangerth, 2000, 2004

Definition at line 47 of file affine_constraints.h.

Member Typedef Documentation

◆ BaseClass

template<typename number>
using BlockSparseMatrix< number >::BaseClass = BlockMatrixBase<SparseMatrix<number> >

Typedef the base class for simpler access to its own alias.

Definition at line 56 of file block_sparse_matrix.h.

◆ BlockType

template<typename number>
using BlockSparseMatrix< number >::BlockType = typename BaseClass::BlockType

Typedef the type of the underlying matrix.

Definition at line 61 of file block_sparse_matrix.h.

◆ value_type

template<typename number>
using BlockSparseMatrix< number >::value_type = typename BaseClass::value_type

Import the alias from the base class.

Definition at line 66 of file block_sparse_matrix.h.

Constructor & Destructor Documentation

◆ BlockSparseMatrix() [1/2]

template<typename number>
BlockSparseMatrix< number >::BlockSparseMatrix ( )
default

Constructor; initializes the matrix to be empty, without any structure, i.e. the matrix is not usable at all. This constructor is therefore only useful for matrices which are members of a class. All other matrices should be created at a point in the data flow where all necessary information is available.

You have to initialize the matrix before usage with reinit(BlockSparsityPattern). The number of blocks per row and column are then determined by that function.

◆ BlockSparseMatrix() [2/2]

template<typename number>
BlockSparseMatrix< number >::BlockSparseMatrix ( const BlockSparsityPattern sparsity)

Constructor. Takes the given matrix sparsity structure to represent the sparsity pattern of this matrix. You can change the sparsity pattern later on by calling the reinit() function.

This constructor initializes all sub-matrices with the sub-sparsity pattern within the argument.

You have to make sure that the lifetime of the sparsity structure is at least as long as that of this matrix or as long as reinit() is not called with a new sparsity structure.

◆ ~BlockSparseMatrix()

template<typename number>
virtual BlockSparseMatrix< number >::~BlockSparseMatrix ( )
overridevirtual

Destructor.

Member Function Documentation

◆ operator=() [1/2]

template<typename number>
BlockSparseMatrix& BlockSparseMatrix< number >::operator= ( const BlockSparseMatrix< number > &  )

Pseudo copy operator only copying empty objects. The sizes of the block matrices need to be the same.

◆ operator=() [2/2]

template<typename number >
BlockSparseMatrix< number > & BlockSparseMatrix< number >::operator= ( const double  d)
inline

This operator assigns a scalar to a matrix. Since this does usually not make much sense (should we set all matrix entries to this value? Only the nonzero entries of the sparsity pattern?), this operation is only allowed if the actual value to be assigned is zero. This operator only exists to allow for the obvious notation matrix=0, which sets all elements of the matrix to zero, but keep the sparsity pattern previously used.

Definition at line 380 of file block_sparse_matrix.h.

◆ clear()

template<typename number>
void BlockSparseMatrix< number >::clear ( )

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 SparseMatrix::clear on all sub-matrices and then resets this object to have no blocks at all.

◆ reinit()

template<typename number>
virtual void BlockSparseMatrix< number >::reinit ( const BlockSparsityPattern sparsity)
virtual

Reinitialize the sparse matrix with the given sparsity pattern. The latter tells the matrix how many nonzero elements there need to be reserved.

Basically, this function only calls SparseMatrix::reinit() of the sub- matrices with the block sparsity patterns of the parameter.

You have to make sure that the lifetime of the sparsity structure is at least as long as that of this matrix or as long as reinit(const SparsityPattern &) is not called with a new sparsity structure.

The elements of the matrix are set to zero by this function.

◆ empty()

template<typename number>
bool BlockSparseMatrix< number >::empty ( ) const

Return whether the object is empty. It is empty if either both dimensions are zero or no BlockSparsityPattern is associated.

◆ get_row_length()

template<typename number>
size_type BlockSparseMatrix< number >::get_row_length ( const size_type  row) const

Return the number of entries in a specific row.

◆ n_nonzero_elements()

template<typename number>
size_type BlockSparseMatrix< number >::n_nonzero_elements ( ) const

Return the number of nonzero elements of this matrix. Actually, it returns the number of entries in the sparsity pattern; if any of the entries should happen to be zero, it is counted anyway.

◆ n_actually_nonzero_elements()

template<typename number>
size_type BlockSparseMatrix< number >::n_actually_nonzero_elements ( const double  threshold = 0.0) const

Return the number of actually nonzero elements. Just counts the number of actually nonzero elements (with absolute value larger than threshold) of all the blocks.

◆ get_sparsity_pattern()

template<typename number>
const BlockSparsityPattern& BlockSparseMatrix< number >::get_sparsity_pattern ( ) const

Return a (constant) reference to the underlying sparsity pattern of this matrix.

Though the return value is declared const, you should be aware that it may change if you call any nonconstant function of objects which operate on it.

◆ memory_consumption()

template<typename number>
std::size_t BlockSparseMatrix< number >::memory_consumption ( ) const

Determine an estimate for the memory consumption (in bytes) of this object.

◆ vmult() [1/4]

template<typename number >
template<typename block_number >
void BlockSparseMatrix< number >::vmult ( BlockVector< block_number > &  dst,
const BlockVector< block_number > &  src 
) const
inline

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

Definition at line 396 of file block_sparse_matrix.h.

◆ vmult() [2/4]

template<typename number >
template<typename block_number , typename nonblock_number >
void BlockSparseMatrix< number >::vmult ( BlockVector< block_number > &  dst,
const Vector< nonblock_number > &  src 
) const
inline

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

Definition at line 407 of file block_sparse_matrix.h.

◆ vmult() [3/4]

template<typename number >
template<typename block_number , typename nonblock_number >
void BlockSparseMatrix< number >::vmult ( Vector< nonblock_number > &  dst,
const BlockVector< block_number > &  src 
) const
inline

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

Definition at line 418 of file block_sparse_matrix.h.

◆ vmult() [4/4]

template<typename number >
template<typename nonblock_number >
void BlockSparseMatrix< number >::vmult ( Vector< nonblock_number > &  dst,
const Vector< nonblock_number > &  src 
) const
inline

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

Definition at line 429 of file block_sparse_matrix.h.

◆ Tvmult() [1/4]

template<typename number >
template<typename block_number >
void BlockSparseMatrix< number >::Tvmult ( BlockVector< block_number > &  dst,
const BlockVector< block_number > &  src 
) const
inline

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.

Definition at line 440 of file block_sparse_matrix.h.

◆ Tvmult() [2/4]

template<typename number >
template<typename block_number , typename nonblock_number >
void BlockSparseMatrix< number >::Tvmult ( BlockVector< block_number > &  dst,
const Vector< nonblock_number > &  src 
) const
inline

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

Definition at line 451 of file block_sparse_matrix.h.

◆ Tvmult() [3/4]

template<typename number >
template<typename block_number , typename nonblock_number >
void BlockSparseMatrix< number >::Tvmult ( Vector< nonblock_number > &  dst,
const BlockVector< block_number > &  src 
) const
inline

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

Definition at line 462 of file block_sparse_matrix.h.

◆ Tvmult() [4/4]

template<typename number >
template<typename nonblock_number >
void BlockSparseMatrix< number >::Tvmult ( Vector< nonblock_number > &  dst,
const Vector< nonblock_number > &  src 
) const
inline

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

Definition at line 473 of file block_sparse_matrix.h.

◆ precondition_Jacobi() [1/2]

template<typename number >
template<class BlockVectorType >
void BlockSparseMatrix< number >::precondition_Jacobi ( BlockVectorType &  dst,
const BlockVectorType &  src,
const number  omega = 1. 
) const
inline

Apply the Jacobi preconditioner, which multiplies every element of the src vector by the inverse of the respective diagonal element and multiplies the result with the relaxation parameter omega.

All diagonal blocks must be square matrices for this operation.

Definition at line 484 of file block_sparse_matrix.h.

◆ precondition_Jacobi() [2/2]

template<typename number >
template<typename number2 >
void BlockSparseMatrix< number >::precondition_Jacobi ( Vector< number2 > &  dst,
const Vector< number2 > &  src,
const number  omega = 1. 
) const
inline

Apply the Jacobi preconditioner to a simple vector.

The matrix must be a single square block for this.

Definition at line 505 of file block_sparse_matrix.h.

◆ print_formatted()

template<typename number>
void BlockSparseMatrix< number >::print_formatted ( std::ostream &  out,
const unsigned int  precision = 3,
const bool  scientific = true,
const unsigned int  width = 0,
const char *  zero_string = " ",
const double  denominator = 1. 
) const

Print the matrix in the usual format, i.e. as a matrix and not as a list of nonzero elements. For better readability, elements not in the matrix are displayed as empty space, while matrix elements which are explicitly set to zero are displayed as such.

The parameters allow for a flexible setting of the output format: precision and scientific are used to determine the number format, where scientific = false means fixed point notation. A zero entry for width makes the function compute a width, but it may be changed to a positive value, if output is crude.

Additionally, a character for an empty value may be specified.

Finally, the whole matrix can be multiplied with a common denominator to produce more readable output, even integers.

Attention
This function may produce large amounts of output if applied to a large matrix!

Member Data Documentation

◆ sparsity_pattern

template<typename number>
SmartPointer<const BlockSparsityPattern, BlockSparseMatrix<number> > BlockSparseMatrix< number >::sparsity_pattern
private

Pointer to the block sparsity pattern used for this matrix. In order to guarantee that it is not deleted while still in use, we subscribe to it using the SmartPointer class.

Definition at line 368 of file block_sparse_matrix.h.


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