TrilinosWrappers::BlockSparseMatrix Class Reference
[TrilinosWrappersBasic matrices]

Inheritance diagram for TrilinosWrappers::BlockSparseMatrix:
Inheritance graph
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List of all members.

Classes

class  ExcIncompatibleColNumbers
class  ExcIncompatibleRowNumbers

Public Types

typedef BlockMatrixBase
< SparseMatrix
BaseClass
typedef BaseClass::BlockType BlockType
typedef BaseClass::value_type value_type
typedef BaseClass::pointer pointer
typedef BaseClass::const_pointer const_pointer
typedef BaseClass::reference reference
typedef BaseClass::const_reference const_reference
typedef BaseClass::size_type size_type
typedef BaseClass::iterator iterator
typedef BaseClass::const_iterator const_iterator

Public Member Functions

 BlockSparseMatrix ()
 ~BlockSparseMatrix ()
BlockSparseMatrixoperator= (const BlockSparseMatrix &)
BlockSparseMatrixoperator= (const double d)
void reinit (const unsigned int n_block_rows, const unsigned int n_block_columns)
template<typename BlockSparsityType >
void reinit (const std::vector< Epetra_Map > &input_maps, const BlockSparsityType &block_sparsity_pattern)
template<typename BlockSparsityType >
void reinit (const BlockSparsityType &block_sparsity_pattern)
void reinit (const std::vector< Epetra_Map > &input_maps, const ::::BlockSparseMatrix< double > &deal_ii_sparse_matrix, const double drop_tolerance=1e-13)
void reinit (const ::::BlockSparseMatrix< double > &deal_ii_sparse_matrix, const double drop_tolerance=1e-13)
void compress ()
bool is_compressed () const
void collect_sizes ()
unsigned int n_nonzero_elements () const
void vmult (MPI::BlockVector &dst, const MPI::BlockVector &src) const
void vmult (BlockVector &dst, const BlockVector &src) const
void vmult (MPI::BlockVector &dst, const MPI::Vector &src) const
void vmult (BlockVector &dst, const Vector &src) const
void vmult (MPI::Vector &dst, const MPI::BlockVector &src) const
void vmult (Vector &dst, const BlockVector &src) const
void vmult (VectorBase &dst, const VectorBase &src) const
void Tvmult (MPI::BlockVector &dst, const MPI::BlockVector &src) const
void Tvmult (BlockVector &dst, const BlockVector &src) const
void Tvmult (MPI::BlockVector &dst, const MPI::Vector &src) const
void Tvmult (BlockVector &dst, const Vector &src) const
void Tvmult (MPI::Vector &dst, const MPI::BlockVector &src) const
void Tvmult (Vector &dst, const BlockVector &src) const
void Tvmult (VectorBase &dst, const VectorBase &src) const
TrilinosScalar residual (MPI::BlockVector &dst, const MPI::BlockVector &x, const MPI::BlockVector &b) const
TrilinosScalar residual (BlockVector &dst, const BlockVector &x, const BlockVector &b) const
TrilinosScalar residual (MPI::BlockVector &dst, const MPI::Vector &x, const MPI::BlockVector &b) const
TrilinosScalar residual (BlockVector &dst, const Vector &x, const BlockVector &b) const
TrilinosScalar residual (MPI::Vector &dst, const MPI::BlockVector &x, const MPI::Vector &b) const
TrilinosScalar residual (Vector &dst, const BlockVector &x, const Vector &b) const
TrilinosScalar residual (VectorBase &dst, const VectorBase &x, const VectorBase &b) const

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.

Author:
Martin Kronbichler, Wolfgang Bangerth, 2008

Member Typedef Documentation

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

Typedef the type of the underlying matrix.

Reimplemented from BlockMatrixBase< SparseMatrix >.

Import the typedefs from the base class.

Reimplemented from BlockMatrixBase< SparseMatrix >.

Reimplemented from BlockMatrixBase< SparseMatrix >.

Reimplemented from BlockMatrixBase< SparseMatrix >.

Reimplemented from BlockMatrixBase< SparseMatrix >.

Reimplemented from BlockMatrixBase< SparseMatrix >.

Reimplemented from BlockMatrixBase< SparseMatrix >.

Reimplemented from BlockMatrixBase< SparseMatrix >.

Reimplemented from BlockMatrixBase< SparseMatrix >.


Constructor & Destructor Documentation

TrilinosWrappers::BlockSparseMatrix::BlockSparseMatrix (  ) 

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.

TrilinosWrappers::BlockSparseMatrix::~BlockSparseMatrix (  ) 

Destructor.


Member Function Documentation

BlockSparseMatrix& TrilinosWrappers::BlockSparseMatrix::operator= ( const BlockSparseMatrix  ) 

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

Reimplemented from Subscriptor.

BlockSparseMatrix& TrilinosWrappers::BlockSparseMatrix::operator= ( const double  d  ) 

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.

void TrilinosWrappers::BlockSparseMatrix::reinit ( const unsigned int  n_block_rows,
const unsigned int  n_block_columns 
)

Resize the matrix, by setting the number of block rows and columns. This deletes all blocks and replaces them by unitialized ones, i.e. ones for which also the sizes are not yet set. You have to do that by calling the reinit functions of the blocks themselves. Do not forget to call collect_sizes() after that on this object.

The reason that you have to set sizes of the blocks yourself is that the sizes may be varying, the maximum number of elements per row may be varying, etc. It is simpler not to reproduce the interface of the SparsityPattern class here but rather let the user call whatever function she desires.

template<typename BlockSparsityType >
void TrilinosWrappers::BlockSparseMatrix::reinit ( const std::vector< Epetra_Map > &  input_maps,
const BlockSparsityType &  block_sparsity_pattern 
) [inline]

Resize the matrix, by using an array of Epetra maps to determine the distribution of the individual matrices. This function assumes that a quadratic block matrix is generated.

template<typename BlockSparsityType >
void TrilinosWrappers::BlockSparseMatrix::reinit ( const BlockSparsityType &  block_sparsity_pattern  )  [inline]

Resize the matrix and initialize it by the given sparsity pattern. Since no distribution map is given, the result is a block matrix for which all elements are stored locally.

void TrilinosWrappers::BlockSparseMatrix::reinit ( const std::vector< Epetra_Map > &  input_maps,
const ::::BlockSparseMatrix< double > &  deal_ii_sparse_matrix,
const double  drop_tolerance = 1e-13 
)

This function initializes the Trilinos matrix using the deal.II sparse matrix and the entries stored therein. It uses a threshold to copy only elements whose modulus is larger than the threshold (so zeros in the deal.II matrix can be filtered away).

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

This function initializes the Trilinos matrix using the deal.II sparse matrix and the entries stored therein. It uses a threshold to copy only elements whose modulus is larger than the threshold (so zeros in the deal.II matrix can be filtered away). Since no Epetra_Map is given, all the elements will be locally stored.

void TrilinosWrappers::BlockSparseMatrix::compress (  ) 

This function calls the compress() command of all matrices after the assembly is completed. Note that all MPI processes need to call this command (whereas the individual assembly routines will most probably only be called on each processor individually) before any can complete it.

Reimplemented from BlockMatrixBase< SparseMatrix >.

bool BlockSparseMatrix< number >::is_compressed (  )  const [inline]

Returns the state of the matrix, i.e., whether compress() needs to be called after an operation requiring data exchange. Does only return non-true values when used in debug mode, since it is quite expensive to keep track of all operations that lead to the need for compress().

References BlockMatrixBase< SparseMatrix >::block(), BlockMatrixBase< SparseMatrix >::n_block_cols(), and BlockMatrixBase< SparseMatrix >::n_block_rows().

void TrilinosWrappers::BlockSparseMatrix::collect_sizes (  ) 

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. Note that this is a collective operation, i.e., it needs to be called on all MPI processes. This command internally calls the method compress(), so you don't need to call that function in case you use collect_sizes().

Reimplemented from BlockMatrixBase< SparseMatrix >.

unsigned int TrilinosWrappers::BlockSparseMatrix::n_nonzero_elements (  )  const

Return the number of nonzero elements of this matrix.

void BlockSparseMatrix< number >::vmult ( MPI::BlockVector dst,
const MPI::BlockVector src 
) const [inline]

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

References BlockMatrixBase< SparseMatrix >::vmult_block_block().

void BlockSparseMatrix< number >::vmult ( BlockVector dst,
const BlockVector src 
) const [inline]

Matrix-vector multiplication: let $dst = M*src$ with $M$ being this matrix, now applied to localized block vectors (works only when run on one processor).

References BlockMatrixBase< SparseMatrix >::vmult_block_block().

void BlockSparseMatrix< number >::vmult ( MPI::BlockVector dst,
const MPI::Vector src 
) const [inline]

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

References BlockMatrixBase< SparseMatrix >::vmult_block_nonblock().

void BlockSparseMatrix< number >::vmult ( BlockVector dst,
const Vector src 
) const [inline]

Matrix-vector multiplication. Just like the previous function, but only applicable if the matrix has only one block column, now applied to localized vectors (works only when run on one processor).

References BlockMatrixBase< SparseMatrix >::vmult_block_nonblock().

void BlockSparseMatrix< number >::vmult ( MPI::Vector dst,
const MPI::BlockVector src 
) const [inline]

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

References BlockMatrixBase< SparseMatrix >::vmult_nonblock_block().

void BlockSparseMatrix< number >::vmult ( Vector dst,
const BlockVector src 
) const [inline]

Matrix-vector multiplication. Just like the previous function, but only applicable if the matrix has only one block row, now applied to localized vectors (works only when run on one processor).

References BlockMatrixBase< SparseMatrix >::vmult_nonblock_block().

void BlockSparseMatrix< number >::vmult ( VectorBase dst,
const VectorBase src 
) const [inline]

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

References BlockMatrixBase< SparseMatrix >::vmult_nonblock_nonblock().

void BlockSparseMatrix< number >::Tvmult ( MPI::BlockVector dst,
const MPI::BlockVector 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.

References BlockMatrixBase< SparseMatrix >::Tvmult_block_block().

void BlockSparseMatrix< number >::Tvmult ( BlockVector dst,
const BlockVector 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, now applied to localized Trilinos vectors (works only when run on one processor).

References BlockMatrixBase< SparseMatrix >::Tvmult_block_block().

void BlockSparseMatrix< number >::Tvmult ( MPI::BlockVector dst,
const MPI::Vector src 
) const [inline]

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

References BlockMatrixBase< SparseMatrix >::Tvmult_block_nonblock().

void BlockSparseMatrix< number >::Tvmult ( BlockVector dst,
const Vector src 
) const [inline]

Matrix-vector multiplication. Just like the previous function, but only applicable if the matrix has only one block row, now applied to localized Trilinos vectors (works only when run on one processor).

References BlockMatrixBase< SparseMatrix >::Tvmult_block_nonblock().

void BlockSparseMatrix< number >::Tvmult ( MPI::Vector dst,
const MPI::BlockVector src 
) const [inline]

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

References BlockMatrixBase< SparseMatrix >::Tvmult_nonblock_block().

void BlockSparseMatrix< number >::Tvmult ( Vector dst,
const BlockVector src 
) const [inline]

Matrix-vector multiplication. Just like the previous function, but only applicable if the matrix has only one block column, now applied to localized Trilinos vectors (works only when run on one processor).

References BlockMatrixBase< SparseMatrix >::Tvmult_nonblock_block().

void BlockSparseMatrix< number >::Tvmult ( VectorBase dst,
const VectorBase src 
) const [inline]

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

References BlockMatrixBase< SparseMatrix >::Tvmult_nonblock_nonblock().

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

Compute the residual of an equation Mx=b, where the residual is defined to be r=b-Mx. Write the residual into dst. The l2 norm of the residual vector is returned.

Source x and destination dst must not be the same vector.

Note that both vectors have to be distributed vectors generated using the same Map as was used for the matrix in case you work on a distributed memory architecture, using the interface in the TrilinosWrappers::MPI::BlockVector class.

TrilinosScalar TrilinosWrappers::BlockSparseMatrix::residual ( BlockVector dst,
const BlockVector x,
const BlockVector b 
) const

Compute the residual of an equation Mx=b, where the residual is defined to be r=b-Mx. Write the residual into dst. The l2 norm of the residual vector is returned.

Source x and destination dst must not be the same vector.

Note that both vectors have to be distributed vectors generated using the same Map as was used for the matrix in case you work on a distributed memory architecture, using the interface in the TrilinosWrappers::BlockVector class. Since the block matrix is in general distributed among processes, this function only works when running the program on one processor.

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

Compute the residual of an equation Mx=b, where the residual is defined to be r=b-Mx. Write the residual into dst. The l2 norm of the residual vector is returned. Just like the previous function, but only applicable if the matrix only has one block row.

TrilinosScalar TrilinosWrappers::BlockSparseMatrix::residual ( BlockVector dst,
const Vector x,
const BlockVector b 
) const

Compute the residual of an equation Mx=b, where the residual is defined to be r=b-Mx. Write the residual into dst. The l2 norm of the residual vector is returned. Just like the previous function, but only applicable if the matrix only has one block row.

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

Compute the residual of an equation Mx=b, where the residual is defined to be r=b-Mx. Write the residual into dst. The l2 norm of the residual vector is returned. Just like the previous function, but only applicable if the matrix only has one block column.

TrilinosScalar TrilinosWrappers::BlockSparseMatrix::residual ( Vector dst,
const BlockVector x,
const Vector b 
) const

Compute the residual of an equation Mx=b, where the residual is defined to be r=b-Mx. Write the residual into dst. The l2 norm of the residual vector is returned. Just like the previous function, but only applicable if the matrix only has one block column.

TrilinosScalar TrilinosWrappers::BlockSparseMatrix::residual ( VectorBase dst,
const VectorBase x,
const VectorBase b 
) const

Compute the residual of an equation Mx=b, where the residual is defined to be r=b-Mx. Write the residual into dst. The l2 norm of the residual vector is returned. Just like the previous function, but only applicable if the matrix only has one block.


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

deal.II documentation generated on Mon Nov 23 22:58:36 2009 by doxygen 1.6.1