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Reference documentation for deal.II version 9.6.0
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Reference documentation for deal.II version 9.6.0
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#include <deal.II/lac/trilinos_block_sparse_matrix.h>
Public Types | |
| using | BaseClass = BlockMatrixBase<SparseMatrix> |
| using | BlockType = BaseClass::BlockType |
| using | value_type = BaseClass::value_type |
| using | pointer = BaseClass::pointer |
| using | const_pointer = BaseClass::const_pointer |
| using | reference = BaseClass::reference |
| using | const_reference = BaseClass::const_reference |
| using | size_type = BaseClass::size_type |
| using | iterator = BaseClass::iterator |
| using | const_iterator = BaseClass::const_iterator |
| using | real_type |
Public Member Functions | |
| BlockSparseMatrix ()=default | |
| ~BlockSparseMatrix () override | |
| BlockSparseMatrix & | operator= (const BlockSparseMatrix &)=default |
| BlockSparseMatrix & | operator= (const double d) |
| void | reinit (const size_type n_block_rows, const size_type n_block_columns) |
| template<typename BlockSparsityPatternType > | |
| void | reinit (const std::vector< IndexSet > &input_maps, const BlockSparsityPatternType &block_sparsity_pattern, const MPI_Comm communicator=MPI_COMM_WORLD, const bool exchange_data=false) |
| template<typename BlockSparsityPatternType > | |
| void | reinit (const BlockSparsityPatternType &block_sparsity_pattern) |
| void | reinit (const std::vector< IndexSet > ¶llel_partitioning, const ::BlockSparseMatrix< double > &dealii_block_sparse_matrix, const MPI_Comm communicator=MPI_COMM_WORLD, const double drop_tolerance=1e-13) |
| void | reinit (const ::BlockSparseMatrix< double > &deal_ii_sparse_matrix, const double drop_tolerance=1e-13) |
| bool | is_compressed () const |
| void | collect_sizes () |
| std::uint64_t | n_nonzero_elements () const |
| MPI_Comm | get_mpi_communicator () const |
| std::vector< IndexSet > | locally_owned_domain_indices () const |
| std::vector< IndexSet > | locally_owned_range_indices () const |
| template<typename VectorType1 , typename VectorType2 > | |
| void | vmult (VectorType1 &dst, const VectorType2 &src) const |
| template<typename VectorType1 , typename VectorType2 > | |
| void | Tvmult (VectorType1 &dst, const VectorType2 &src) const |
| TrilinosScalar | residual (MPI::BlockVector &dst, const MPI::BlockVector &x, const MPI::BlockVector &b) const |
| TrilinosScalar | residual (MPI::BlockVector &dst, const MPI::Vector &x, const MPI::BlockVector &b) const |
| TrilinosScalar | residual (MPI::Vector &dst, const MPI::BlockVector &x, const MPI::Vector &b) const |
| TrilinosScalar | residual (MPI::Vector &dst, const MPI::Vector &x, const MPI::Vector &b) const |
| template<> | |
| void | reinit (const BlockSparsityPattern &block_sparsity_pattern) |
| BlockMatrixBase & | copy_from (const BlockMatrixType &source) |
| BlockType & | block (const unsigned int row, const unsigned int column) |
| const BlockType & | block (const unsigned int row, const unsigned int column) const |
| size_type | m () const |
| size_type | n () const |
| unsigned int | n_block_rows () const |
| unsigned int | n_block_cols () const |
| void | set (const size_type i, const size_type j, const value_type value) |
| void | set (const std::vector< size_type > &indices, const FullMatrix< number > &full_matrix, const bool elide_zero_values=false) |
| void | set (const std::vector< size_type > &row_indices, const std::vector< size_type > &col_indices, const FullMatrix< number > &full_matrix, const bool elide_zero_values=false) |
| void | set (const size_type row, const std::vector< size_type > &col_indices, const std::vector< number > &values, const bool elide_zero_values=false) |
| void | set (const size_type row, const size_type n_cols, const size_type *col_indices, const number *values, const bool elide_zero_values=false) |
| void | add (const size_type i, const size_type j, const value_type value) |
| void | add (const std::vector< size_type > &indices, const FullMatrix< number > &full_matrix, const bool elide_zero_values=true) |
| void | add (const std::vector< size_type > &row_indices, const std::vector< size_type > &col_indices, const FullMatrix< number > &full_matrix, const bool elide_zero_values=true) |
| void | add (const size_type row, const std::vector< size_type > &col_indices, const std::vector< number > &values, const bool elide_zero_values=true) |
| void | add (const size_type row, const size_type n_cols, const size_type *col_indices, const number *values, const bool elide_zero_values=true, const bool col_indices_are_sorted=false) |
| void | add (const value_type factor, const BlockMatrixBase< SparseMatrix > &matrix) |
| value_type | operator() (const size_type i, const size_type j) const |
| value_type | el (const size_type i, const size_type j) const |
| value_type | diag_element (const size_type i) const |
| void | compress (VectorOperation::values operation) |
| BlockMatrixBase & | operator*= (const value_type factor) |
| BlockMatrixBase & | operator/= (const value_type factor) |
| void | vmult_add (BlockVectorType &dst, const BlockVectorType &src) const |
| void | Tvmult_add (BlockVectorType &dst, const BlockVectorType &src) const |
| value_type | matrix_norm_square (const BlockVectorType &v) const |
| real_type | frobenius_norm () const |
| value_type | matrix_scalar_product (const BlockVectorType &u, const BlockVectorType &v) const |
| value_type | residual (BlockVectorType &dst, const BlockVectorType &x, const BlockVectorType &b) const |
| void | print (std::ostream &out, const bool alternative_output=false) const |
| iterator | begin () |
| iterator | begin (const size_type r) |
| const_iterator | begin () const |
| const_iterator | begin (const size_type r) const |
| iterator | end () |
| iterator | end (const size_type r) |
| const_iterator | end () const |
| const_iterator | end (const size_type r) const |
| const BlockIndices & | get_row_indices () const |
| const BlockIndices & | get_column_indices () const |
| std::size_t | memory_consumption () const |
| template<class Archive > | |
| void | serialize (Archive &ar, const unsigned int version) |
Subscriptor functionality | |
Classes derived from Subscriptor provide a facility to subscribe to this object. This is mostly used by the SmartPointer class. | |
| void | subscribe (std::atomic< bool > *const validity, const std::string &identifier="") const |
| void | unsubscribe (std::atomic< bool > *const validity, const std::string &identifier="") const |
| unsigned int | n_subscriptions () const |
| template<typename StreamType > | |
| void | list_subscribers (StreamType &stream) const |
| void | list_subscribers () const |
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 ::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 | vmult_block_block (BlockVectorType &dst, const BlockVectorType &src) const |
| void | vmult_block_nonblock (BlockVectorType &dst, const VectorType &src) const |
| void | vmult_nonblock_block (VectorType &dst, const BlockVectorType &src) const |
| void | vmult_nonblock_nonblock (VectorType &dst, const VectorType &src) const |
| void | Tvmult_block_block (BlockVectorType &dst, const BlockVectorType &src) const |
| void | Tvmult_block_nonblock (BlockVectorType &dst, const VectorType &src) const |
| void | Tvmult_nonblock_block (VectorType &dst, const BlockVectorType &src) const |
| void | Tvmult_nonblock_nonblock (VectorType &dst, const VectorType &src) const |
| void | prepare_add_operation () |
| void | prepare_set_operation () |
Protected Attributes | |
| BlockIndices | row_block_indices |
| BlockIndices | column_block_indices |
| Table< 2, SmartPointer< BlockType, BlockMatrixBase< SparseMatrix > > > | sub_objects |
Private Types | |
| using | map_value_type = decltype(counter_map)::value_type |
| using | map_iterator = decltype(counter_map)::iterator |
Private Member Functions | |
| template<typename VectorType1 , typename VectorType2 > | |
| void | vmult (VectorType1 &dst, const VectorType2 &src, const bool transpose, const std::bool_constant< true >, const std::bool_constant< true >) const |
| template<typename VectorType1 , typename VectorType2 > | |
| void | vmult (VectorType1 &dst, const VectorType2 &src, const bool transpose, const std::bool_constant< false >, const std::bool_constant< true >) const |
| template<typename VectorType1 , typename VectorType2 > | |
| void | vmult (VectorType1 &dst, const VectorType2 &src, const bool transpose, const std::bool_constant< true >, const std::bool_constant< false >) const |
| template<typename VectorType1 , typename VectorType2 > | |
| void | vmult (VectorType1 &dst, const VectorType2 &src, const bool transpose, const std::bool_constant< false >, const std::bool_constant< false >) const |
| void | check_no_subscribers () const noexcept |
Private Attributes | |
| TemporaryData | temporary_data |
| std::atomic< unsigned int > | counter |
| std::map< std::string, unsigned int > | counter_map |
| std::vector< std::atomic< bool > * > | validity_pointers |
| const std::type_info * | object_info |
Static Private Attributes | |
| static std::mutex | mutex |
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.
Definition at line 71 of file trilinos_block_sparse_matrix.h.
Typedef the base class for simpler access to its own alias.
Definition at line 77 of file trilinos_block_sparse_matrix.h.
Typedef the type of the underlying matrix.
Definition at line 82 of file trilinos_block_sparse_matrix.h.
Import the alias from the base class.
Definition at line 87 of file trilinos_block_sparse_matrix.h.
Definition at line 88 of file trilinos_block_sparse_matrix.h.
Definition at line 89 of file trilinos_block_sparse_matrix.h.
Definition at line 90 of file trilinos_block_sparse_matrix.h.
Definition at line 91 of file trilinos_block_sparse_matrix.h.
Definition at line 92 of file trilinos_block_sparse_matrix.h.
Definition at line 93 of file trilinos_block_sparse_matrix.h.
Definition at line 94 of file trilinos_block_sparse_matrix.h.
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inherited |
Definition at line 362 of file block_matrix_base.h.
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privateinherited |
The data type used in counter_map.
Definition at line 229 of file subscriptor.h.
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privateinherited |
The iterator type used in counter_map.
Definition at line 234 of file subscriptor.h.
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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.
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override |
Destructor.
Definition at line 26 of file trilinos_block_sparse_matrix.cc.
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default |
Pseudo copy operator only copying empty objects. The sizes of the block matrices need to be the same.
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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 411 of file trilinos_block_sparse_matrix.h.
| void TrilinosWrappers::BlockSparseMatrix::reinit | ( | const size_type | n_block_rows, |
| const size_type | n_block_columns ) |
Resize the matrix, by setting the number of block rows and columns. This deletes all blocks and replaces them with uninitialized 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 they desire.
| void BlockSparseMatrix< BlockSparsityPatternType >::reinit | ( | const std::vector< IndexSet > & | input_maps, |
| const BlockSparsityPatternType & | block_sparsity_pattern, | ||
| const MPI_Comm | communicator = MPI_COMM_WORLD, | ||
| const bool | exchange_data = false ) |
Resize the matrix, by using an array of index sets to determine the parallel distribution of the individual matrices. This function assumes that a quadratic block matrix is generated.
Definition at line 72 of file trilinos_block_sparse_matrix.cc.
| void BlockSparseMatrix< BlockSparsityPatternType >::reinit | ( | const BlockSparsityPatternType & | block_sparsity_pattern | ) |
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.
Definition at line 126 of file trilinos_block_sparse_matrix.cc.
| void BlockSparseMatrix< number >::reinit | ( | const std::vector< IndexSet > & | parallel_partitioning, |
| const ::BlockSparseMatrix< double > & | dealii_block_sparse_matrix, | ||
| const MPI_Comm | communicator = MPI_COMM_WORLD, | ||
| const double | drop_tolerance = 1e-13 ) |
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).
Definition at line 163 of file trilinos_block_sparse_matrix.cc.
| void BlockSparseMatrix< number >::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.
Definition at line 200 of file trilinos_block_sparse_matrix.cc.
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inline |
Return 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().
Definition at line 425 of file trilinos_block_sparse_matrix.h.
| void BlockSparseMatrix< number >::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().
Definition at line 226 of file trilinos_block_sparse_matrix.cc.
| std::uint64_t BlockSparseMatrix< number >::n_nonzero_elements | ( | ) | const |
Return the total number of nonzero elements of this matrix (summed over all MPI processes).
Definition at line 235 of file trilinos_block_sparse_matrix.cc.
| MPI_Comm BlockSparseMatrix< number >::get_mpi_communicator | ( | ) | const |
Return the underlying MPI communicator.
Definition at line 308 of file trilinos_block_sparse_matrix.cc.
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inline |
Return the partitioning of the domain space for the individual blocks of this matrix, i.e., the partitioning of the block vectors this matrix has to be multiplied with.
Definition at line 532 of file trilinos_block_sparse_matrix.h.
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inline |
Return the partitioning of the range space for the individual blocks of this matrix, i.e., the partitioning of the block vectors that result from matrix-vector products.
Definition at line 548 of file trilinos_block_sparse_matrix.h.
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inline |
Matrix-vector multiplication: let \(dst = M*src\) with \(M\) being this matrix. The vector types can be block vectors or non-block vectors (only if the matrix has only one row or column, respectively), and need to define TrilinosWrappers::SparseMatrix::vmult.
Definition at line 443 of file trilinos_block_sparse_matrix.h.
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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 456 of file trilinos_block_sparse_matrix.h.
| TrilinosScalar BlockSparseMatrix< number >::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.
This function only applicable if the matrix only has one block row.
Definition at line 248 of file trilinos_block_sparse_matrix.cc.
| TrilinosScalar BlockSparseMatrix< number >::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.
This function is only applicable if the matrix only has one block row.
Definition at line 266 of file trilinos_block_sparse_matrix.cc.
| TrilinosScalar BlockSparseMatrix< number >::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.
This function is only applicable if the matrix only has one block column.
Definition at line 280 of file trilinos_block_sparse_matrix.cc.
| TrilinosScalar BlockSparseMatrix< number >::residual | ( | MPI::Vector & | dst, |
| const MPI::Vector & | 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.
This function is only applicable if the matrix only has one block.
Definition at line 294 of file trilinos_block_sparse_matrix.cc.
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inlineprivate |
Internal version of (T)vmult with two block vectors
Definition at line 469 of file trilinos_block_sparse_matrix.h.
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inlineprivate |
Internal version of (T)vmult where the source vector is a block vector but the destination vector is a non-block vector
Definition at line 485 of file trilinos_block_sparse_matrix.h.
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inlineprivate |
Internal version of (T)vmult where the source vector is a non-block vector but the destination vector is a block vector
Definition at line 501 of file trilinos_block_sparse_matrix.h.
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inlineprivate |
Internal version of (T)vmult where both source vector and the destination vector are non-block vectors (only defined if the matrix consists of only one block)
Definition at line 517 of file trilinos_block_sparse_matrix.h.
| void TrilinosWrappers::BlockSparseMatrix::reinit | ( | const BlockSparsityPattern & | block_sparsity_pattern | ) |
Definition at line 141 of file trilinos_block_sparse_matrix.cc.
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inherited |
Copy the matrix given as argument into the current object.
Copying matrices is an expensive operation that we do not want to happen by accident through compiler generated code for operator=. (This would happen, for example, if one accidentally declared a function argument of the current type by value rather than by reference.) The functionality of copying matrices is implemented in this member function instead. All copy operations of objects of this type therefore require an explicit function call.
The source matrix may be a matrix of arbitrary type, as long as its data type is convertible to the data type of this matrix.
The function returns a reference to this.
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inherited |
Access the block with the given coordinates.
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inherited |
Access the block with the given coordinates. Version for constant objects.
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inherited |
Return the dimension of the codomain (or range) space. Note that the matrix is of dimension \(m \times n\).
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inherited |
Return the dimension of the domain space. Note that the matrix is of dimension \(m \times n\).
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inherited |
Return the number of blocks in a column. Returns zero if no sparsity pattern is presently associated to this matrix.
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inherited |
Return the number of blocks in a row. Returns zero if no sparsity pattern is presently associated to this matrix.
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inherited |
Set the element (i,j) to value. Throws an error if the entry does not exist or if value is not a finite number. Still, it is allowed to store zero values in non-existent fields.
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inherited |
Set all elements given in a FullMatrix into the sparse matrix locations given by indices. In other words, this function writes the elements in full_matrix into the calling matrix, using the local-to-global indexing specified by indices for both the rows and the columns of the matrix. This function assumes a quadratic sparse matrix and a quadratic full_matrix, the usual situation in FE calculations.
The optional parameter elide_zero_values can be used to specify whether zero values should be set anyway or they should be filtered away (and not change the previous content in the respective element if it exists). The default value is false, i.e., even zero values are treated.
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inherited |
Same function as before, but now including the possibility to use rectangular full_matrices and different local-to-global indexing on rows and columns, respectively.
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inherited |
Set several elements in the specified row of the matrix with column indices as given by col_indices to the respective value.
The optional parameter elide_zero_values can be used to specify whether zero values should be set anyway or they should be filtered away (and not change the previous content in the respective element if it exists). The default value is false, i.e., even zero values are treated.
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inherited |
Set several elements to values given by values in a given row in columns given by col_indices into the sparse matrix.
The optional parameter elide_zero_values can be used to specify whether zero values should be inserted anyway or they should be filtered away. The default value is false, i.e., even zero values are inserted/replaced.
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inherited |
Add value to the element (i,j). Throws an error if the entry does not exist or if value is not a finite number. Still, it is allowed to store zero values in non-existent fields.
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inherited |
Add all elements given in a FullMatrix<double> into sparse matrix locations given by indices. In other words, this function adds the elements in full_matrix to the respective entries in calling matrix, using the local-to-global indexing specified by indices for both the rows and the columns of the matrix. This function assumes a quadratic sparse matrix and a quadratic full_matrix, the usual situation in FE calculations.
The optional parameter elide_zero_values can be used to specify whether zero values should be added anyway or these should be filtered away and only non-zero data is added. The default value is true, i.e., zero values won't be added into the matrix.
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inherited |
Same function as before, but now including the possibility to use rectangular full_matrices and different local-to-global indexing on rows and columns, respectively.
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inherited |
Set several elements in the specified row of the matrix with column indices as given by col_indices to the respective value.
The optional parameter elide_zero_values can be used to specify whether zero values should be added anyway or these should be filtered away and only non-zero data is added. The default value is true, i.e., zero values won't be added into the matrix.
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inherited |
Add an array of values given by values in the given global matrix row at columns specified by col_indices in the sparse matrix.
The optional parameter elide_zero_values can be used to specify whether zero values should be added anyway or these should be filtered away and only non-zero data is added. The default value is true, i.e., zero values won't be added into the matrix.
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inherited |
Add matrix scaled by factor to this matrix, i.e. the matrix factor*matrix is added to this. If the sparsity pattern of the calling matrix does not contain all the elements in the sparsity pattern of the input matrix, this function will throw an exception.
Depending on MatrixType, however, additional restrictions might arise. Some sparse matrix formats require matrix to be based on the same sparsity pattern as the calling matrix.
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inherited |
Return the value of the entry (i,j). This may be an expensive operation and you should always take care where to call this function. In order to avoid abuse, this function throws an exception if the wanted element does not exist in the matrix.
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inherited |
This function is mostly like operator()() in that it returns the value of the matrix entry (i,j). The only difference is that if this entry does not exist in the sparsity pattern, then instead of raising an exception, zero is returned. While this may be convenient in some cases, note that it is simple to write algorithms that are slow compared to an optimal solution, since the sparsity of the matrix is not used.
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inherited |
Return the main diagonal element in the ith row. This function throws an error if the matrix is not quadratic and also if the diagonal blocks of the matrix are not quadratic.
This function is considerably faster than the operator()(), since for quadratic matrices, the diagonal entry may be the first to be stored in each row and access therefore does not involve searching for the right column number.
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inherited |
Call the compress() function on all the subblocks of the matrix.
See Compressing distributed objects for more information.
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inherited |
Multiply the entire matrix by a fixed factor.
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inherited |
Divide the entire matrix by a fixed factor.
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inherited |
Adding Matrix-vector multiplication. Add \(M*src\) on \(dst\) with \(M\) being this matrix.
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inherited |
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.
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inherited |
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.
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inherited |
Return the frobenius norm of the matrix, i.e. the square root of the sum of squares of all entries in the matrix.
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inherited |
Compute the matrix scalar product \(\left(u,Mv\right)\).
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inherited |
Compute the residual r=b-Ax. Write the residual into dst.
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inherited |
Print the matrix to the given stream, using the format (line,col) value, i.e. one nonzero entry of the matrix per line. The optional flag outputs the sparsity pattern in a different style according to the underlying sparse matrix type.
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inherited |
Iterator starting at the first entry.
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inherited |
Iterator starting at the first entry of row r.
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inherited |
Iterator starting at the first entry.
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inherited |
Iterator starting at the first entry of row r.
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inherited |
Final iterator.
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inherited |
Final iterator of row r.
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inherited |
Final iterator.
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inherited |
Final iterator of row r.
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inherited |
Return a reference to the underlying BlockIndices data of the rows.
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inherited |
Return a reference to the underlying BlockIndices data of the columns.
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inherited |
Determine an estimate for the memory consumption (in bytes) of this object. Note that only the memory reserved on the current processor is returned in case this is called in an MPI-based program.
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protectedinherited |
Release all memory and return to a state just like after having called the default constructor. It also forgets the sparsity pattern it was previously tied to.
This calls clear for all sub-matrices and then resets this object to have no blocks at all.
This function is protected since it may be necessary to release additional structures. A derived class can make it public again, if it is sufficient.
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protectedinherited |
Matrix-vector multiplication: let \(dst = M*src\) with \(M\) being this matrix.
Due to problems with deriving template arguments between the block and non-block versions of the vmult/Tvmult functions, the actual functions are implemented in derived classes, with implementations forwarding the calls to the implementations provided here under a unique name for which template arguments can be derived by the compiler.
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protectedinherited |
Matrix-vector multiplication. Just like the previous function, but only applicable if the matrix has only one block column.
Due to problems with deriving template arguments between the block and non-block versions of the vmult/Tvmult functions, the actual functions are implemented in derived classes, with implementations forwarding the calls to the implementations provided here under a unique name for which template arguments can be derived by the compiler.
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protectedinherited |
Matrix-vector multiplication. Just like the previous function, but only applicable if the matrix has only one block row.
Due to problems with deriving template arguments between the block and non-block versions of the vmult/Tvmult functions, the actual functions are implemented in derived classes, with implementations forwarding the calls to the implementations provided here under a unique name for which template arguments can be derived by the compiler.
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protectedinherited |
Matrix-vector multiplication. Just like the previous function, but only applicable if the matrix has only one block.
Due to problems with deriving template arguments between the block and non-block versions of the vmult/Tvmult functions, the actual functions are implemented in derived classes, with implementations forwarding the calls to the implementations provided here under a unique name for which template arguments can be derived by the compiler.
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protectedinherited |
Matrix-vector multiplication: let \(dst = M^T*src\) with \(M\) being this matrix. This function does the same as vmult() but takes the transposed matrix.
Due to problems with deriving template arguments between the block and non-block versions of the vmult/Tvmult functions, the actual functions are implemented in derived classes, with implementations forwarding the calls to the implementations provided here under a unique name for which template arguments can be derived by the compiler.
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protectedinherited |
Matrix-vector multiplication. Just like the previous function, but only applicable if the matrix has only one block row.
Due to problems with deriving template arguments between the block and non-block versions of the vmult/Tvmult functions, the actual functions are implemented in derived classes, with implementations forwarding the calls to the implementations provided here under a unique name for which template arguments can be derived by the compiler.
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protectedinherited |
Matrix-vector multiplication. Just like the previous function, but only applicable if the matrix has only one block column.
Due to problems with deriving template arguments between the block and non-block versions of the vmult/Tvmult functions, the actual functions are implemented in derived classes, with implementations forwarding the calls to the implementations provided here under a unique name for which template arguments can be derived by the compiler.
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protectedinherited |
Matrix-vector multiplication. Just like the previous function, but only applicable if the matrix has only one block.
Due to problems with deriving template arguments between the block and non-block versions of the vmult/Tvmult functions, the actual functions are implemented in derived classes, with implementations forwarding the calls to the implementations provided here under a unique name for which template arguments can be derived by the compiler.
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protectedinherited |
Some matrix types, in particular PETSc, need to synchronize set and add operations. This has to be done for all matrices in the BlockMatrix. This routine prepares adding of elements by notifying all blocks. Called by all internal routines before adding elements.
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protectedinherited |
Notifies all blocks to let them prepare for setting elements, see prepare_add_operation().
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inherited |
Subscribes a user of the object by storing the pointer validity. The subscriber may be identified by text supplied as identifier.
Definition at line 135 of file subscriptor.cc.
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inherited |
Unsubscribes a user from the object.
identifier and the validity pointer must be the same as the one supplied to subscribe(). Definition at line 155 of file subscriptor.cc.
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inlineinherited |
Return the present number of subscriptions to this object. This allows to use this class for reference counted lifetime determination where the last one to unsubscribe also deletes the object.
Definition at line 300 of file subscriptor.h.
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inlineinherited |
List the subscribers to the input stream.
Definition at line 317 of file subscriptor.h.
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inherited |
List the subscribers to deallog.
Definition at line 203 of file subscriptor.cc.
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inlineinherited |
Read or write the data of this object to or from a stream for the purpose of serialization using the BOOST serialization library.
This function does not actually serialize any of the member variables of this class. The reason is that what this class stores is only who subscribes to this object, but who does so at the time of storing the contents of this object does not necessarily have anything to do with who subscribes to the object when it is restored. Consequently, we do not want to overwrite the subscribers at the time of restoring, and then there is no reason to write the subscribers out in the first place.
Definition at line 309 of file subscriptor.h.
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privatenoexceptinherited |
Check that there are no objects subscribing to this object. If this check passes then it is safe to destroy the current object. It this check fails then this function will either abort or print an error message to deallog (by using the AssertNothrow mechanism), but will not throw an exception.
Definition at line 52 of file subscriptor.cc.
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protectedinherited |
Index arrays for rows and columns.
Definition at line 846 of file block_matrix_base.h.
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protectedinherited |
Definition at line 847 of file block_matrix_base.h.
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protectedinherited |
Array of sub-matrices.
Definition at line 852 of file block_matrix_base.h.
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privateinherited |
A set of scratch arrays that can be used by the add() and set() functions that take pointers to data to pre-sort indices before use. Access from multiple threads is synchronized via the mutex variable that is part of the structure.
Definition at line 1064 of file block_matrix_base.h.
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mutableprivateinherited |
Store the number of objects which subscribed to this object. Initially, this number is zero, and upon destruction it shall be zero again (i.e. all objects which subscribed should have unsubscribed again).
The creator (and owner) of an object is counted in the map below if HE manages to supply identification.
We use the mutable keyword in order to allow subscription to constant objects also.
This counter may be read from and written to concurrently in multithreaded code: hence we use the std::atomic class template.
Definition at line 218 of file subscriptor.h.
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mutableprivateinherited |
In this map, we count subscriptions for each different identification string supplied to subscribe().
Definition at line 224 of file subscriptor.h.
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mutableprivateinherited |
In this vector, we store pointers to the validity bool in the SmartPointer objects that subscribe to this class.
Definition at line 240 of file subscriptor.h.
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mutableprivateinherited |
Pointer to the typeinfo object of this object, from which we can later deduce the class name. Since this information on the derived class is neither available in the destructor, nor in the constructor, we obtain it in between and store it here.
Definition at line 248 of file subscriptor.h.
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staticprivateinherited |
A mutex used to ensure data consistency when accessing the mutable members of this class. This lock is used in the subscribe() and unsubscribe() functions, as well as in list_subscribers().
Definition at line 271 of file subscriptor.h.
1.11.0