BlockMatrixBase< MatrixType > Class Template Reference
[Basic matrices]

Inheritance diagram for BlockMatrixBase< MatrixType >:
Inheritance graph
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List of all members.

Classes

class  ExcIncompatibleColNumbers
class  ExcIncompatibleRowNumbers

Public Types

typedef MatrixType BlockType
typedef BlockType::value_type value_type
typedef value_typepointer
typedef const value_typeconst_pointer
typedef value_typereference
typedef const value_typeconst_reference
typedef size_t size_type
typedef MatrixIterator
< BlockMatrixIterators::Accessor
< BlockMatrixBase, false > > 
iterator
typedef MatrixIterator
< BlockMatrixIterators::Accessor
< BlockMatrixBase, true > > 
const_iterator

Public Member Functions

 BlockMatrixBase ()
template<class BlockMatrixType >
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
unsigned int m () const
unsigned int n () const
unsigned int n_block_rows () const
unsigned int n_block_cols () const
void set (const unsigned int i, const unsigned int j, const value_type value)
template<typename number >
void set (const std::vector< unsigned int > &indices, const FullMatrix< number > &full_matrix, const bool elide_zero_values=false)
template<typename number >
void set (const std::vector< unsigned int > &row_indices, const std::vector< unsigned int > &col_indices, const FullMatrix< number > &full_matrix, const bool elide_zero_values=false)
template<typename number >
void set (const unsigned int row, const std::vector< unsigned int > &col_indices, const std::vector< number > &values, const bool elide_zero_values=false)
template<typename number >
void set (const unsigned int row, const unsigned int n_cols, const unsigned int *col_indices, const number *values, const bool elide_zero_values=false)
void add (const unsigned int i, const unsigned int j, const value_type value)
template<typename number >
void add (const std::vector< unsigned int > &indices, const FullMatrix< number > &full_matrix, const bool elide_zero_values=true)
template<typename number >
void add (const std::vector< unsigned int > &row_indices, const std::vector< unsigned int > &col_indices, const FullMatrix< number > &full_matrix, const bool elide_zero_values=true)
template<typename number >
void add (const unsigned int row, const std::vector< unsigned int > &col_indices, const std::vector< number > &values, const bool elide_zero_values=true)
template<typename number >
void add (const unsigned int row, const unsigned int n_cols, const unsigned int *col_indices, const number *values, const bool elide_zero_values=true, const bool col_indices_are_sorted=false)
value_type operator() (const unsigned int i, const unsigned int j) const
value_type el (const unsigned int i, const unsigned int j) const
value_type diag_element (const unsigned int i) const
void compress ()
BlockMatrixBaseoperator*= (const value_type factor)
BlockMatrixBaseoperator/= (const value_type factor)
template<class BlockMatrixType >
void add (const value_type factor, const BlockMatrixType &matrix)
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
iterator begin ()
iterator end ()
iterator begin (const unsigned int r)
iterator end (const unsigned int r)
const_iterator begin () const
const_iterator end () const
const_iterator begin (const unsigned int r) const
const_iterator end (const unsigned int r) const
const BlockIndicesget_row_indices () const
const BlockIndicesget_column_indices () const

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

Protected Attributes

BlockIndices row_block_indices
BlockIndices column_block_indices
Table< 2, SmartPointer
< BlockType > > 
sub_objects

Private Attributes

std::vector< unsigned intcounter_within_block
std::vector< std::vector
< unsigned int > > 
column_indices
std::vector< std::vector
< double > > 
column_values

Friends

class BlockMatrixIterators::Accessor
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).
Author:
Wolfgang Bangerth, 2000, 2004

Member Typedef Documentation

template<typename MatrixType>
typedef MatrixType BlockMatrixBase< MatrixType >::BlockType
template<typename MatrixType>
typedef BlockType::value_type BlockMatrixBase< MatrixType >::value_type

Type of matrix entries. In analogy to the STL container classes.

Reimplemented in BlockSparseMatrix< number >, PETScWrappers::BlockSparseMatrix, PETScWrappers::MPI::BlockSparseMatrix, and TrilinosWrappers::BlockSparseMatrix.

template<typename MatrixType>
typedef value_type* BlockMatrixBase< MatrixType >::pointer
template<typename MatrixType>
typedef const value_type* BlockMatrixBase< MatrixType >::const_pointer
template<typename MatrixType>
typedef value_type& BlockMatrixBase< MatrixType >::reference
template<typename MatrixType>
typedef const value_type& BlockMatrixBase< MatrixType >::const_reference
template<typename MatrixType>
typedef size_t BlockMatrixBase< MatrixType >::size_type
template<typename MatrixType>
typedef MatrixIterator<BlockMatrixIterators::Accessor<BlockMatrixBase, false> > BlockMatrixBase< MatrixType >::iterator
template<typename MatrixType>
typedef MatrixIterator<BlockMatrixIterators::Accessor<BlockMatrixBase, true> > BlockMatrixBase< MatrixType >::const_iterator

Constructor & Destructor Documentation

template<typename MatrixType>
BlockMatrixBase< MatrixType >::BlockMatrixBase (  ) 

Default constructor.


Member Function Documentation

template<typename MatrixType>
template<class BlockMatrixType >
BlockMatrixBase& BlockMatrixBase< MatrixType >::copy_from ( const BlockMatrixType &  source  )  [inline]

Copy the given matrix to this one. The operation throws an error if the sparsity patterns of the two involved matrices do not point to the same object, since in this case the copy operation is cheaper. Since this operation is notheless not for free, we do not make it available through operator=(), since this may lead to unwanted usage, e.g. in copy arguments to functions, which should really be arguments by reference.

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.

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

Access the block with the given coordinates.

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.

template<typename MatrixType>
unsigned int BlockMatrixBase< MatrixType >::m (  )  const

Return the dimension of the image space. To remember: the matrix is of dimension $m \times n$.

template<typename MatrixType>
unsigned int BlockMatrixBase< MatrixType >::n (  )  const

Return the dimension of the range space. To remember: the matrix is of dimension $m \times n$.

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.

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.

template<typename MatrixType>
void BlockMatrixBase< MatrixType >::set ( const unsigned int  i,
const unsigned int  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.

template<typename MatrixType>
template<typename number >
void BlockMatrixBase< MatrixType >::set ( const std::vector< unsigned int > &  indices,
const FullMatrix< number > &  full_matrix,
const bool  elide_zero_values = false 
) [inline]

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.

template<typename MatrixType>
template<typename number >
void BlockMatrixBase< MatrixType >::set ( const std::vector< unsigned int > &  row_indices,
const std::vector< unsigned int > &  col_indices,
const FullMatrix< number > &  full_matrix,
const bool  elide_zero_values = false 
) [inline]

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.

template<typename MatrixType>
template<typename number >
void BlockMatrixBase< MatrixType >::set ( const unsigned int  row,
const std::vector< unsigned int > &  col_indices,
const std::vector< number > &  values,
const bool  elide_zero_values = false 
) [inline]

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.

template<typename MatrixType>
template<typename number >
void BlockMatrixBase< MatrixType >::set ( const unsigned int  row,
const unsigned int  n_cols,
const unsigned int col_indices,
const number *  values,
const bool  elide_zero_values = false 
) [inline]

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.

template<typename MatrixType>
void BlockMatrixBase< MatrixType >::add ( const unsigned int  i,
const unsigned int  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.

template<typename MatrixType>
template<typename number >
void BlockMatrixBase< MatrixType >::add ( const std::vector< unsigned int > &  indices,
const FullMatrix< number > &  full_matrix,
const bool  elide_zero_values = true 
) [inline]

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.

template<typename MatrixType>
template<typename number >
void BlockMatrixBase< MatrixType >::add ( const std::vector< unsigned int > &  row_indices,
const std::vector< unsigned int > &  col_indices,
const FullMatrix< number > &  full_matrix,
const bool  elide_zero_values = true 
) [inline]

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.

template<typename MatrixType>
template<typename number >
void BlockMatrixBase< MatrixType >::add ( const unsigned int  row,
const std::vector< unsigned int > &  col_indices,
const std::vector< number > &  values,
const bool  elide_zero_values = true 
) [inline]

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.

template<typename MatrixType>
template<typename number >
void BlockMatrixBase< MatrixType >::add ( const unsigned int  row,
const unsigned int  n_cols,
const unsigned int col_indices,
const number *  values,
const bool  elide_zero_values = true,
const bool  col_indices_are_sorted = false 
) [inline]

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.

template<typename MatrixType>
value_type BlockMatrixBase< MatrixType >::operator() ( const unsigned int  i,
const unsigned int  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.

template<typename MatrixType>
value_type BlockMatrixBase< MatrixType >::el ( const unsigned int  i,
const unsigned int  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.

template<typename MatrixType>
value_type BlockMatrixBase< MatrixType >::diag_element ( const unsigned int  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.

template<typename MatrixType>
void BlockMatrixBase< MatrixType >::compress (  ) 

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

Reimplemented in TrilinosWrappers::BlockSparseMatrix.

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

Multiply the entire matrix by a fixed factor.

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

Divide the entire matrix by a fixed factor.

template<typename MatrixType>
template<class BlockMatrixType >
void BlockMatrixBase< MatrixType >::add ( const value_type  factor,
const BlockMatrixType &  matrix 
) [inline]

Add matrix scaled by factor to this matrix, i.e. the matrix factor*matrix is added to this. This function throws an error if the sparsity patterns of the two involved matrices do not point to the same object, since in this case the operation is cheaper.

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

template<typename MatrixType>
template<class BlockVectorType >
void BlockMatrixBase< MatrixType >::vmult_add ( BlockVectorType &  dst,
const BlockVectorType &  src 
) const [inline]

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

template<typename MatrixType>
template<class BlockVectorType >
void BlockMatrixBase< MatrixType >::Tvmult_add ( BlockVectorType &  dst,
const BlockVectorType &  src 
) const [inline]

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

template<typename MatrixType>
template<class BlockVectorType >
value_type BlockMatrixBase< MatrixType >::matrix_norm_square ( const BlockVectorType &  v  )  const [inline]

Return the norm of the vector v with respect to the norm induced by this matrix, i.e. vTMv). This is useful, e.g. in the finite element context, where the LT-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.

template<typename MatrixType>
template<class BlockVectorType >
value_type BlockMatrixBase< MatrixType >::matrix_scalar_product ( const BlockVectorType &  u,
const BlockVectorType &  v 
) const [inline]

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

template<typename MatrixType>
template<class BlockVectorType >
value_type BlockMatrixBase< MatrixType >::residual ( BlockVectorType &  dst,
const BlockVectorType &  x,
const BlockVectorType &  b 
) const [inline]

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

template<typename MatrixType>
iterator BlockMatrixBase< MatrixType >::begin (  ) 

STL-like iterator with the first entry.

template<typename MatrixType>
iterator BlockMatrixBase< MatrixType >::end (  ) 

Final iterator.

template<typename MatrixType>
iterator BlockMatrixBase< MatrixType >::begin ( const unsigned int  r  ) 

STL-like iterator with the first entry of row r.

template<typename MatrixType>
iterator BlockMatrixBase< MatrixType >::end ( const unsigned int  r  ) 

Final iterator of row r.

template<typename MatrixType>
const_iterator BlockMatrixBase< MatrixType >::begin (  )  const

STL-like iterator with the first entry.

template<typename MatrixType>
const_iterator BlockMatrixBase< MatrixType >::end (  )  const

Final iterator.

template<typename MatrixType>
const_iterator BlockMatrixBase< MatrixType >::begin ( const unsigned int  r  )  const

STL-like iterator with the first entry of row r.

template<typename MatrixType>
const_iterator BlockMatrixBase< MatrixType >::end ( const unsigned int  r  )  const

Final iterator of row r.

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

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

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

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

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.

Reimplemented in BlockSparseMatrix< number >.

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.

Reimplemented in PETScWrappers::BlockSparseMatrix, PETScWrappers::MPI::BlockSparseMatrix, and TrilinosWrappers::BlockSparseMatrix.

template<typename MatrixType>
template<class BlockVectorType >
void BlockMatrixBase< MatrixType >::vmult_block_block ( BlockVectorType &  dst,
const BlockVectorType &  src 
) const [inline, 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.

template<typename MatrixType>
template<class BlockVectorType , class VectorType >
void BlockMatrixBase< MatrixType >::vmult_block_nonblock ( BlockVectorType &  dst,
const VectorType &  src 
) const [inline, 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.

template<typename MatrixType>
template<class BlockVectorType , class VectorType >
void BlockMatrixBase< MatrixType >::vmult_nonblock_block ( VectorType &  dst,
const BlockVectorType &  src 
) const [inline, 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.

template<typename MatrixType>
template<class VectorType >
void BlockMatrixBase< MatrixType >::vmult_nonblock_nonblock ( VectorType &  dst,
const VectorType &  src 
) const [inline, 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.

template<typename MatrixType>
template<class BlockVectorType >
void BlockMatrixBase< MatrixType >::Tvmult_block_block ( BlockVectorType &  dst,
const BlockVectorType &  src 
) const [inline, 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.

template<typename MatrixType>
template<class BlockVectorType , class VectorType >
void BlockMatrixBase< MatrixType >::Tvmult_block_nonblock ( BlockVectorType &  dst,
const VectorType &  src 
) const [inline, 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.

template<typename MatrixType>
template<class BlockVectorType , class VectorType >
void BlockMatrixBase< MatrixType >::Tvmult_nonblock_block ( VectorType &  dst,
const BlockVectorType &  src 
) const [inline, 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.

template<typename MatrixType>
template<class VectorType >
void BlockMatrixBase< MatrixType >::Tvmult_nonblock_nonblock ( VectorType &  dst,
const VectorType &  src 
) const [inline, 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.


Friends And Related Function Documentation

template<typename MatrixType>
friend class BlockMatrixIterators::Accessor [friend]

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

template<typename MatrixType>
friend class MatrixIterator [friend]

Member Data Documentation

template<typename MatrixType>
BlockIndices BlockMatrixBase< MatrixType >::row_block_indices [protected]

Index arrays for rows and columns.

template<typename MatrixType>
BlockIndices BlockMatrixBase< MatrixType >::column_block_indices [protected]
template<typename MatrixType>
Table<2,SmartPointer<BlockType> > BlockMatrixBase< MatrixType >::sub_objects [protected]

Array of sub-matrices.

template<typename MatrixType>
std::vector<unsigned int> BlockMatrixBase< MatrixType >::counter_within_block [private]

Temporary vector for counting the elements written into the individual blocks when doing a collective add or set.

template<typename MatrixType>
std::vector<std::vector<unsigned int> > BlockMatrixBase< MatrixType >::column_indices [private]

Temporary vector for column indices on each block when writing local to global data on each sparse matrix.

template<typename MatrixType>
std::vector<std::vector<double> > BlockMatrixBase< MatrixType >::column_values [private]

Temporary vector for storing the local values (they need to be reordered when writing local to global).


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

deal.II documentation generated on Mon Nov 23 22:57:29 2009 by doxygen 1.6.1