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Reference documentation for deal.II version 9.3.3
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Reference documentation for deal.II version 9.3.3
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Modules | |
| Exceptions and assertions | |
Namespaces | |
| namespace | BlockMatrixIterators |
| namespace | ChunkSparseMatrixIterators |
| namespace | SparseMatrixIterators |
Friends | |
| template<typename > | |
| class | BlockMatrixIterators::AccessorBase< BlockMatrixType >::MatrixIterator |
| template<typename > | |
| class | BlockMatrixIterators::Accessor< BlockMatrixType, false >::MatrixIterator |
| class | BlockMatrixIterators::Accessor< BlockMatrixType, false >::Accessor< BlockMatrixType, true > |
| template<typename > | |
| class | BlockMatrixIterators::Accessor< BlockMatrixType, true >::::MatrixIterator |
| template<typename , bool > | |
| class | ChunkSparseMatrixIterators::Accessor< number, true >::Iterator |
| template<typename , bool > | |
| class | ChunkSparseMatrixIterators::Accessor< number, false >::Iterator |
Constructors and initialization | |
| BlockSparseMatrix< number >::BlockSparseMatrix ()=default | |
| BlockSparseMatrix< number >::BlockSparseMatrix (const BlockSparsityPattern &sparsity) | |
| virtual | BlockSparseMatrix< number >::~BlockSparseMatrix () override |
| BlockSparseMatrix & | BlockSparseMatrix< number >::operator= (const BlockSparseMatrix &) |
| BlockSparseMatrix & | BlockSparseMatrix< number >::operator= (const double d) |
| void | BlockSparseMatrix< number >::clear () |
| virtual void | BlockSparseMatrix< number >::reinit (const BlockSparsityPattern &sparsity) |
Information on the matrix | |
| bool | BlockSparseMatrix< number >::empty () const |
| size_type | BlockSparseMatrix< number >::get_row_length (const size_type row) const |
| size_type | BlockSparseMatrix< number >::n_nonzero_elements () const |
| size_type | BlockSparseMatrix< number >::n_actually_nonzero_elements (const double threshold=0.0) const |
| const BlockSparsityPattern & | BlockSparseMatrix< number >::get_sparsity_pattern () const |
| std::size_t | BlockSparseMatrix< number >::memory_consumption () const |
Multiplications | |
| template<typename block_number > | |
| void | BlockSparseMatrix< number >::vmult (BlockVector< block_number > &dst, const BlockVector< block_number > &src) const |
| template<typename block_number , typename nonblock_number > | |
| void | BlockSparseMatrix< number >::vmult (BlockVector< block_number > &dst, const Vector< nonblock_number > &src) const |
| template<typename block_number , typename nonblock_number > | |
| void | BlockSparseMatrix< number >::vmult (Vector< nonblock_number > &dst, const BlockVector< block_number > &src) const |
| template<typename nonblock_number > | |
| void | BlockSparseMatrix< number >::vmult (Vector< nonblock_number > &dst, const Vector< nonblock_number > &src) const |
| template<typename block_number > | |
| void | BlockSparseMatrix< number >::Tvmult (BlockVector< block_number > &dst, const BlockVector< block_number > &src) const |
| template<typename block_number , typename nonblock_number > | |
| void | BlockSparseMatrix< number >::Tvmult (BlockVector< block_number > &dst, const Vector< nonblock_number > &src) const |
| template<typename block_number , typename nonblock_number > | |
| void | BlockSparseMatrix< number >::Tvmult (Vector< nonblock_number > &dst, const BlockVector< block_number > &src) const |
| template<typename nonblock_number > | |
| void | BlockSparseMatrix< number >::Tvmult (Vector< nonblock_number > &dst, const Vector< nonblock_number > &src) const |
Preconditioning methods | |
| template<class BlockVectorType > | |
| void | BlockSparseMatrix< number >::precondition_Jacobi (BlockVectorType &dst, const BlockVectorType &src, const number omega=1.) const |
| template<typename number2 > | |
| void | BlockSparseMatrix< number >::precondition_Jacobi (Vector< number2 > &dst, const Vector< number2 > &src, const number omega=1.) const |
Input/Output | |
| void | BlockSparseMatrix< number >::print_formatted (std::ostream &out, const unsigned int precision=3, const bool scientific=true, const unsigned int width=0, const char *zero_string=" ", const double denominator=1.) const |
Constructors and initialization. | |
| ChunkSparseMatrix< number >::ChunkSparseMatrix () | |
| ChunkSparseMatrix< number >::ChunkSparseMatrix (const ChunkSparseMatrix &) | |
| ChunkSparseMatrix< number >::ChunkSparseMatrix (const ChunkSparsityPattern &sparsity) | |
| ChunkSparseMatrix< number >::ChunkSparseMatrix (const ChunkSparsityPattern &sparsity, const IdentityMatrix &id) | |
| virtual | ChunkSparseMatrix< number >::~ChunkSparseMatrix () override |
| ChunkSparseMatrix< number > & | ChunkSparseMatrix< number >::operator= (const ChunkSparseMatrix< number > &) |
| ChunkSparseMatrix< number > & | ChunkSparseMatrix< number >::operator= (const IdentityMatrix &id) |
| ChunkSparseMatrix & | ChunkSparseMatrix< number >::operator= (const double d) |
| virtual void | ChunkSparseMatrix< number >::reinit (const ChunkSparsityPattern &sparsity) |
| virtual void | ChunkSparseMatrix< number >::clear () |
Information on the matrix | |
| bool | ChunkSparseMatrix< number >::empty () const |
| size_type | ChunkSparseMatrix< number >::m () const |
| size_type | ChunkSparseMatrix< number >::n () const |
| size_type | ChunkSparseMatrix< number >::n_nonzero_elements () const |
| size_type | ChunkSparseMatrix< number >::n_actually_nonzero_elements () const |
| const ChunkSparsityPattern & | ChunkSparseMatrix< number >::get_sparsity_pattern () const |
| std::size_t | ChunkSparseMatrix< number >::memory_consumption () const |
Modifying entries | |
| void | ChunkSparseMatrix< number >::set (const size_type i, const size_type j, const number value) |
| void | ChunkSparseMatrix< number >::add (const size_type i, const size_type j, const number value) |
| template<typename number2 > | |
| void | ChunkSparseMatrix< number >::add (const size_type row, const size_type n_cols, const size_type *col_indices, const number2 *values, const bool elide_zero_values=true, const bool col_indices_are_sorted=false) |
| ChunkSparseMatrix & | ChunkSparseMatrix< number >::operator*= (const number factor) |
| ChunkSparseMatrix & | ChunkSparseMatrix< number >::operator/= (const number factor) |
| void | ChunkSparseMatrix< number >::symmetrize () |
| template<typename somenumber > | |
| ChunkSparseMatrix< number > & | ChunkSparseMatrix< number >::copy_from (const ChunkSparseMatrix< somenumber > &source) |
| template<typename ForwardIterator > | |
| void | ChunkSparseMatrix< number >::copy_from (const ForwardIterator begin, const ForwardIterator end) |
| template<typename somenumber > | |
| void | ChunkSparseMatrix< number >::copy_from (const FullMatrix< somenumber > &matrix) |
| template<typename somenumber > | |
| void | ChunkSparseMatrix< number >::add (const number factor, const ChunkSparseMatrix< somenumber > &matrix) |
Entry Access | |
| number | ChunkSparseMatrix< number >::operator() (const size_type i, const size_type j) const |
| number | ChunkSparseMatrix< number >::el (const size_type i, const size_type j) const |
| number | ChunkSparseMatrix< number >::diag_element (const size_type i) const |
| void | ChunkSparseMatrix< number >::extract_row_copy (const size_type row, const size_type array_length, size_type &row_length, size_type *column_indices, number *values) const |
Matrix vector multiplications | |
| template<class OutVector , class InVector > | |
| void | ChunkSparseMatrix< number >::vmult (OutVector &dst, const InVector &src) const |
| template<class OutVector , class InVector > | |
| void | ChunkSparseMatrix< number >::Tvmult (OutVector &dst, const InVector &src) const |
| template<class OutVector , class InVector > | |
| void | ChunkSparseMatrix< number >::vmult_add (OutVector &dst, const InVector &src) const |
| template<class OutVector , class InVector > | |
| void | ChunkSparseMatrix< number >::Tvmult_add (OutVector &dst, const InVector &src) const |
| template<typename somenumber > | |
| somenumber | ChunkSparseMatrix< number >::matrix_norm_square (const Vector< somenumber > &v) const |
| template<typename somenumber > | |
| somenumber | ChunkSparseMatrix< number >::matrix_scalar_product (const Vector< somenumber > &u, const Vector< somenumber > &v) const |
| template<typename somenumber > | |
| somenumber | ChunkSparseMatrix< number >::residual (Vector< somenumber > &dst, const Vector< somenumber > &x, const Vector< somenumber > &b) const |
Matrix norms | |
| real_type | ChunkSparseMatrix< number >::l1_norm () const |
| real_type | ChunkSparseMatrix< number >::linfty_norm () const |
| real_type | ChunkSparseMatrix< number >::frobenius_norm () const |
Preconditioning methods | |
| template<typename somenumber > | |
| void | ChunkSparseMatrix< number >::precondition_Jacobi (Vector< somenumber > &dst, const Vector< somenumber > &src, const number omega=1.) const |
| template<typename somenumber > | |
| void | ChunkSparseMatrix< number >::precondition_SSOR (Vector< somenumber > &dst, const Vector< somenumber > &src, const number om=1.) const |
| template<typename somenumber > | |
| void | ChunkSparseMatrix< number >::precondition_SOR (Vector< somenumber > &dst, const Vector< somenumber > &src, const number om=1.) const |
| template<typename somenumber > | |
| void | ChunkSparseMatrix< number >::precondition_TSOR (Vector< somenumber > &dst, const Vector< somenumber > &src, const number om=1.) const |
| template<typename somenumber > | |
| void | ChunkSparseMatrix< number >::SSOR (Vector< somenumber > &v, const number omega=1.) const |
| template<typename somenumber > | |
| void | ChunkSparseMatrix< number >::SOR (Vector< somenumber > &v, const number om=1.) const |
| template<typename somenumber > | |
| void | ChunkSparseMatrix< number >::TSOR (Vector< somenumber > &v, const number om=1.) const |
| template<typename somenumber > | |
| void | ChunkSparseMatrix< number >::PSOR (Vector< somenumber > &v, const std::vector< size_type > &permutation, const std::vector< size_type > &inverse_permutation, const number om=1.) const |
| template<typename somenumber > | |
| void | ChunkSparseMatrix< number >::TPSOR (Vector< somenumber > &v, const std::vector< size_type > &permutation, const std::vector< size_type > &inverse_permutation, const number om=1.) const |
| template<typename somenumber > | |
| void | ChunkSparseMatrix< number >::SOR_step (Vector< somenumber > &v, const Vector< somenumber > &b, const number om=1.) const |
| template<typename somenumber > | |
| void | ChunkSparseMatrix< number >::TSOR_step (Vector< somenumber > &v, const Vector< somenumber > &b, const number om=1.) const |
| template<typename somenumber > | |
| void | ChunkSparseMatrix< number >::SSOR_step (Vector< somenumber > &v, const Vector< somenumber > &b, const number om=1.) const |
Iterators | |
| const_iterator | ChunkSparseMatrix< number >::begin () const |
| const_iterator | ChunkSparseMatrix< number >::end () const |
| iterator | ChunkSparseMatrix< number >::begin () |
| iterator | ChunkSparseMatrix< number >::end () |
| const_iterator | ChunkSparseMatrix< number >::begin (const unsigned int r) const |
| const_iterator | ChunkSparseMatrix< number >::end (const unsigned int r) const |
| iterator | ChunkSparseMatrix< number >::begin (const unsigned int r) |
| iterator | ChunkSparseMatrix< number >::end (const unsigned int r) |
Input/Output | |
| void | ChunkSparseMatrix< number >::print (std::ostream &out) const |
| void | ChunkSparseMatrix< number >::print_formatted (std::ostream &out, const unsigned int precision=3, const bool scientific=true, const unsigned int width=0, const char *zero_string=" ", const double denominator=1.) const |
| void | ChunkSparseMatrix< number >::print_pattern (std::ostream &out, const double threshold=0.) const |
| void | ChunkSparseMatrix< number >::block_write (std::ostream &out) const |
| void | ChunkSparseMatrix< number >::block_read (std::istream &in) |
These are the actual matrix classes provided by deal.II. It is possible to store values in them and retrieve them. Furthermore, they provide the full interface required by linear solvers (see Solvers).
Among the matrices in this group are full matrices, different sparse matrices, and block matrices. In addition, some of the classes in the interfaces to other linear algebra libraries (for example the PETScWrappers) are matrices.
Most of the deal.II sparse matrix classes are separated from their sparsity patterns, to make storing several matrices with the same sparsity pattern more efficient. See Sparsity for more information.
| using BlockMatrixIterators::AccessorBase< BlockMatrixType >::size_type = types::global_dof_index |
Declare type for container size.
Definition at line 67 of file block_matrix_base.h.
| using BlockMatrixIterators::AccessorBase< BlockMatrixType >::value_type = typename BlockMatrixType::value_type |
Typedef the value type of the matrix we point into.
Definition at line 72 of file block_matrix_base.h.
| using BlockMatrixIterators::Accessor< BlockMatrixType, false >::size_type = types::global_dof_index |
Declare type for container size.
Definition at line 126 of file block_matrix_base.h.
| using BlockMatrixIterators::Accessor< BlockMatrixType, false >::MatrixType = BlockMatrixType |
Type of the matrix used in this accessor.
Definition at line 131 of file block_matrix_base.h.
| using BlockMatrixIterators::Accessor< BlockMatrixType, false >::value_type = typename BlockMatrixType::value_type |
Typedef the value type of the matrix we point into.
Definition at line 136 of file block_matrix_base.h.
| using BlockMatrixIterators::Accessor< BlockMatrixType, true >::size_type = types::global_dof_index |
Declare type for container size.
Definition at line 211 of file block_matrix_base.h.
| using BlockMatrixIterators::Accessor< BlockMatrixType, true >::MatrixType = const BlockMatrixType |
Type of the matrix used in this accessor.
Definition at line 216 of file block_matrix_base.h.
| using BlockMatrixIterators::Accessor< BlockMatrixType, true >::value_type = typename BlockMatrixType::value_type |
Typedef the value type of the matrix we point into.
Definition at line 221 of file block_matrix_base.h.
| using BlockMatrixBase< MatrixType >::BlockType = MatrixType |
Typedef the type of the underlying matrix.
Definition at line 355 of file block_matrix_base.h.
| using BlockMatrixBase< MatrixType >::value_type = typename BlockType::value_type |
Type of matrix entries. These are analogous to alias in the standard library containers.
Definition at line 361 of file block_matrix_base.h.
| using BlockMatrixBase< MatrixType >::real_type = typename numbers::NumberTraits<value_type>::real_type |
Definition at line 362 of file block_matrix_base.h.
| using BlockMatrixBase< MatrixType >::pointer = value_type * |
Definition at line 363 of file block_matrix_base.h.
| using BlockMatrixBase< MatrixType >::const_pointer = const value_type * |
Definition at line 364 of file block_matrix_base.h.
| using BlockMatrixBase< MatrixType >::reference = value_type & |
Definition at line 365 of file block_matrix_base.h.
| using BlockMatrixBase< MatrixType >::const_reference = const value_type & |
Definition at line 366 of file block_matrix_base.h.
| using BlockMatrixBase< MatrixType >::size_type = types::global_dof_index |
Definition at line 367 of file block_matrix_base.h.
| using BlockMatrixBase< MatrixType >::iterator = MatrixIterator<BlockMatrixIterators::Accessor<BlockMatrixBase, false> > |
Definition at line 369 of file block_matrix_base.h.
| using BlockMatrixBase< MatrixType >::const_iterator = MatrixIterator<BlockMatrixIterators::Accessor<BlockMatrixBase, true> > |
Definition at line 372 of file block_matrix_base.h.
| using BlockSparseMatrix< number >::BaseClass = BlockMatrixBase<SparseMatrix<number> > |
Typedef the base class for simpler access to its own alias.
Definition at line 55 of file block_sparse_matrix.h.
| using BlockSparseMatrix< number >::BlockType = typename BaseClass::BlockType |
Typedef the type of the underlying matrix.
Definition at line 60 of file block_sparse_matrix.h.
| using BlockSparseMatrix< number >::value_type = typename BaseClass::value_type |
Import the alias from the base class.
Definition at line 65 of file block_sparse_matrix.h.
| using BlockSparseMatrix< number >::pointer = typename BaseClass::pointer |
Definition at line 66 of file block_sparse_matrix.h.
| using BlockSparseMatrix< number >::const_pointer = typename BaseClass::const_pointer |
Definition at line 67 of file block_sparse_matrix.h.
| using BlockSparseMatrix< number >::reference = typename BaseClass::reference |
Definition at line 68 of file block_sparse_matrix.h.
| using BlockSparseMatrix< number >::const_reference = typename BaseClass::const_reference |
Definition at line 69 of file block_sparse_matrix.h.
| using BlockSparseMatrix< number >::size_type = typename BaseClass::size_type |
Definition at line 70 of file block_sparse_matrix.h.
| using BlockSparseMatrix< number >::iterator = typename BaseClass::iterator |
Definition at line 71 of file block_sparse_matrix.h.
| using BlockSparseMatrix< number >::const_iterator = typename BaseClass::const_iterator |
Definition at line 72 of file block_sparse_matrix.h.
| using BlockSparseMatrixEZ< Number >::size_type = types::global_dof_index |
Declare type for container size.
Definition at line 66 of file block_sparse_matrix_ez.h.
| using ChunkSparseMatrixIterators::Accessor< number, true >::MatrixType = const ChunkSparseMatrix<number> |
Typedef for the type (including constness) of the matrix to be used here.
Definition at line 106 of file chunk_sparse_matrix.h.
| using ChunkSparseMatrixIterators::Accessor< number, false >::MatrixType = ChunkSparseMatrix<number> |
Typedef for the type (including constness) of the matrix to be used here.
Definition at line 242 of file chunk_sparse_matrix.h.
| using ChunkSparseMatrixIterators::Iterator< number, Constness >::MatrixType = typename Accessor<number, Constness>::MatrixType |
Typedef for the matrix type (including constness) we are to operate on.
Definition at line 302 of file chunk_sparse_matrix.h.
| using ChunkSparseMatrixIterators::Iterator< number, Constness >::value_type = const Accessor<number, Constness> & |
An alias for the type you get when you dereference an iterator of the current kind.
Definition at line 308 of file chunk_sparse_matrix.h.
| using ChunkSparseMatrix< number >::size_type = types::global_dof_index |
Declare the type for container size.
Definition at line 427 of file chunk_sparse_matrix.h.
| using ChunkSparseMatrix< number >::value_type = number |
Type of matrix entries. This alias is analogous to value_type in the standard library containers.
Definition at line 433 of file chunk_sparse_matrix.h.
| using ChunkSparseMatrix< number >::real_type = typename numbers::NumberTraits<number>::real_type |
Declare a type that has holds real-valued numbers with the same precision as the template argument to this class. If the template argument of this class is a real data type, then real_type equals the template argument. If the template argument is a std::complex type then real_type equals the type underlying the complex numbers.
This alias is used to represent the return type of norms.
Definition at line 444 of file chunk_sparse_matrix.h.
| using ChunkSparseMatrix< number >::const_iterator = ChunkSparseMatrixIterators::Iterator<number, true> |
Typedef of an iterator class walking over all the nonzero entries of this matrix. This iterator cannot change the values of the matrix.
Definition at line 450 of file chunk_sparse_matrix.h.
| using ChunkSparseMatrix< number >::iterator = ChunkSparseMatrixIterators::Iterator<number, false> |
Typedef of an iterator class walking over all the nonzero entries of this matrix. This iterator can change the values of the matrix, but of course can't change the sparsity pattern as this is fixed once a sparse matrix is attached to it.
Definition at line 458 of file chunk_sparse_matrix.h.
| BlockMatrixIterators::AccessorBase< BlockMatrixType >::AccessorBase | ( | ) |
Initialize data fields to default values.
| unsigned int BlockMatrixIterators::AccessorBase< BlockMatrixType >::block_row | ( | ) | const |
Block row of the element represented by this object.
| unsigned int BlockMatrixIterators::AccessorBase< BlockMatrixType >::block_column | ( | ) | const |
Block column of the element represented by this object.
| BlockMatrixIterators::Accessor< BlockMatrixType, false >::Accessor | ( | BlockMatrixType * | m, |
| const size_type | row, | ||
| const size_type | col | ||
| ) |
Constructor. Since we use accessors only for read access, a const matrix pointer is sufficient.
Place the iterator at the beginning of the given row of the matrix, or create the end pointer if row equals the total number of rows in the matrix.
| size_type BlockMatrixIterators::Accessor< BlockMatrixType, false >::row | ( | ) | const |
Row number of the element represented by this object.
| size_type BlockMatrixIterators::Accessor< BlockMatrixType, false >::column | ( | ) | const |
Column number of the element represented by this object.
| value_type BlockMatrixIterators::Accessor< BlockMatrixType, false >::value | ( | ) | const |
Value of the entry at the current position.
| void BlockMatrixIterators::Accessor< BlockMatrixType, false >::set_value | ( | value_type | newval | ) | const |
Set new value.
|
protected |
Move ahead one element.
|
protected |
Compare this accessor with another one for equality.
| BlockMatrixIterators::Accessor< BlockMatrixType, true >::Accessor | ( | const BlockMatrixType * | m, |
| const size_type | row, | ||
| const size_type | col | ||
| ) |
Constructor. Since we use accessors only for read access, a const matrix pointer is sufficient.
Place the iterator at the beginning of the given row of the matrix, or create the end pointer if row equals the total number of rows in the matrix.
| BlockMatrixIterators::Accessor< BlockMatrixType, true >::Accessor | ( | const Accessor< BlockMatrixType, false > & | ) |
Initialize const accessor from non const accessor.
| size_type BlockMatrixIterators::Accessor< BlockMatrixType, true >::row | ( | ) | const |
Row number of the element represented by this object.
| size_type BlockMatrixIterators::Accessor< BlockMatrixType, true >::column | ( | ) | const |
Column number of the element represented by this object.
| value_type BlockMatrixIterators::Accessor< BlockMatrixType, true >::value | ( | ) | const |
Value of the entry at the current position.
|
protected |
Move ahead one element.
|
protected |
Compare this accessor with another one for equality.
|
default |
Default constructor.
|
override |
Destructor.
| BlockMatrixBase & BlockMatrixBase< MatrixType >::copy_from | ( | const BlockMatrixType & | source | ) |
Copy the matrix given as argument into the current object.
Copying matrices is an expensive operation that we do not want to happen by accident through compiler generated code for operator=. (This would happen, for example, if one accidentally declared a function argument of the current type by value rather than by reference.) The functionality of copying matrices is implemented in this member function instead. All copy operations of objects of this type therefore require an explicit function call.
The source matrix may be a matrix of arbitrary type, as long as its data type is convertible to the data type of this matrix.
The function returns a reference to this.
| BlockType & BlockMatrixBase< MatrixType >::block | ( | const unsigned int | row, |
| const unsigned int | column | ||
| ) |
Access the block with the given coordinates.
| 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.
| size_type BlockMatrixBase< MatrixType >::m | ( | ) | const |
Return the dimension of the codomain (or range) space. Note that the matrix is of dimension \(m \times n\).
| size_type BlockMatrixBase< MatrixType >::n | ( | ) | const |
Return the dimension of the domain space. Note that the matrix is of dimension \(m \times n\).
| 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.
| 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.
| void BlockMatrixBase< MatrixType >::set | ( | const size_type | i, |
| const size_type | j, | ||
| const value_type | value | ||
| ) |
Set the element (i,j) to value. Throws an error if the entry does not exist or if value is not a finite number. Still, it is allowed to store zero values in non-existent fields.
| void BlockMatrixBase< MatrixType >::set | ( | const std::vector< size_type > & | indices, |
| const FullMatrix< number > & | full_matrix, | ||
| const bool | elide_zero_values = false |
||
| ) |
Set all elements given in a FullMatrix into the sparse matrix locations given by indices. In other words, this function writes the elements in full_matrix into the calling matrix, using the local-to-global indexing specified by indices for both the rows and the columns of the matrix. This function assumes a quadratic sparse matrix and a quadratic full_matrix, the usual situation in FE calculations.
The optional parameter elide_zero_values can be used to specify whether zero values should be set anyway or they should be filtered away (and not change the previous content in the respective element if it exists). The default value is false, i.e., even zero values are treated.
| void BlockMatrixBase< MatrixType >::set | ( | const std::vector< size_type > & | row_indices, |
| const std::vector< size_type > & | col_indices, | ||
| const FullMatrix< number > & | full_matrix, | ||
| const bool | elide_zero_values = false |
||
| ) |
Same function as before, but now including the possibility to use rectangular full_matrices and different local-to-global indexing on rows and columns, respectively.
| void BlockMatrixBase< MatrixType >::set | ( | const size_type | row, |
| const std::vector< size_type > & | col_indices, | ||
| const std::vector< number > & | values, | ||
| const bool | elide_zero_values = false |
||
| ) |
Set several elements in the specified row of the matrix with column indices as given by col_indices to the respective value.
The optional parameter elide_zero_values can be used to specify whether zero values should be set anyway or they should be filtered away (and not change the previous content in the respective element if it exists). The default value is false, i.e., even zero values are treated.
| void BlockMatrixBase< MatrixType >::set | ( | const size_type | row, |
| const size_type | n_cols, | ||
| const size_type * | col_indices, | ||
| const number * | values, | ||
| const bool | elide_zero_values = false |
||
| ) |
Set several elements to values given by values in a given row in columns given by col_indices into the sparse matrix.
The optional parameter elide_zero_values can be used to specify whether zero values should be inserted anyway or they should be filtered away. The default value is false, i.e., even zero values are inserted/replaced.
| void BlockMatrixBase< MatrixType >::add | ( | const size_type | i, |
| const size_type | j, | ||
| const value_type | value | ||
| ) |
Add value to the element (i,j). Throws an error if the entry does not exist or if value is not a finite number. Still, it is allowed to store zero values in non-existent fields.
| void BlockMatrixBase< MatrixType >::add | ( | const std::vector< size_type > & | indices, |
| const FullMatrix< number > & | full_matrix, | ||
| const bool | elide_zero_values = true |
||
| ) |
Add all elements given in a FullMatrix<double> into sparse matrix locations given by indices. In other words, this function adds the elements in full_matrix to the respective entries in calling matrix, using the local-to-global indexing specified by indices for both the rows and the columns of the matrix. This function assumes a quadratic sparse matrix and a quadratic full_matrix, the usual situation in FE calculations.
The optional parameter elide_zero_values can be used to specify whether zero values should be added anyway or these should be filtered away and only non-zero data is added. The default value is true, i.e., zero values won't be added into the matrix.
| void BlockMatrixBase< MatrixType >::add | ( | const std::vector< size_type > & | row_indices, |
| const std::vector< size_type > & | col_indices, | ||
| const FullMatrix< number > & | full_matrix, | ||
| const bool | elide_zero_values = true |
||
| ) |
Same function as before, but now including the possibility to use rectangular full_matrices and different local-to-global indexing on rows and columns, respectively.
| void BlockMatrixBase< MatrixType >::add | ( | const size_type | row, |
| const std::vector< size_type > & | col_indices, | ||
| const std::vector< number > & | values, | ||
| const bool | elide_zero_values = true |
||
| ) |
Set several elements in the specified row of the matrix with column indices as given by col_indices to the respective value.
The optional parameter elide_zero_values can be used to specify whether zero values should be added anyway or these should be filtered away and only non-zero data is added. The default value is true, i.e., zero values won't be added into the matrix.
| void BlockMatrixBase< MatrixType >::add | ( | const size_type | row, |
| const size_type | n_cols, | ||
| const size_type * | col_indices, | ||
| const number * | values, | ||
| const bool | elide_zero_values = true, |
||
| const bool | col_indices_are_sorted = false |
||
| ) |
Add an array of values given by values in the given global matrix row at columns specified by col_indices in the sparse matrix.
The optional parameter elide_zero_values can be used to specify whether zero values should be added anyway or these should be filtered away and only non-zero data is added. The default value is true, i.e., zero values won't be added into the matrix.
| void BlockMatrixBase< MatrixType >::add | ( | const value_type | factor, |
| const BlockMatrixBase< MatrixType > & | matrix | ||
| ) |
Add matrix scaled by factor to this matrix, i.e. the matrix factor*matrix is added to this. If the sparsity pattern of the calling matrix does not contain all the elements in the sparsity pattern of the input matrix, this function will throw an exception.
Depending on MatrixType, however, additional restrictions might arise. Some sparse matrix formats require matrix to be based on the same sparsity pattern as the calling matrix.
| value_type BlockMatrixBase< MatrixType >::operator() | ( | const size_type | i, |
| const size_type | j | ||
| ) | const |
Return the value of the entry (i,j). This may be an expensive operation and you should always take care where to call this function. In order to avoid abuse, this function throws an exception if the wanted element does not exist in the matrix.
| value_type BlockMatrixBase< MatrixType >::el | ( | const size_type | i, |
| const size_type | j | ||
| ) | const |
This function is mostly like operator()() in that it returns the value of the matrix entry (i,j). The only difference is that if this entry does not exist in the sparsity pattern, then instead of raising an exception, zero is returned. While this may be convenient in some cases, note that it is simple to write algorithms that are slow compared to an optimal solution, since the sparsity of the matrix is not used.
| value_type BlockMatrixBase< MatrixType >::diag_element | ( | const size_type | i | ) | const |
Return the main diagonal element in the ith row. This function throws an error if the matrix is not quadratic and also if the diagonal blocks of the matrix are not quadratic.
This function is considerably faster than the operator()(), since for quadratic matrices, the diagonal entry may be the first to be stored in each row and access therefore does not involve searching for the right column number.
| void BlockMatrixBase< MatrixType >::compress | ( | ::VectorOperation::values | operation | ) |
Call the compress() function on all the subblocks of the matrix.
See Compressing distributed objects for more information.
| BlockMatrixBase & BlockMatrixBase< MatrixType >::operator*= | ( | const value_type | factor | ) |
Multiply the entire matrix by a fixed factor.
| BlockMatrixBase & BlockMatrixBase< MatrixType >::operator/= | ( | const value_type | factor | ) |
Divide the entire matrix by a fixed factor.
| void BlockMatrixBase< MatrixType >::vmult_add | ( | BlockVectorType & | dst, |
| const BlockVectorType & | src | ||
| ) | const |
Adding Matrix-vector multiplication. Add \(M*src\) on \(dst\) with \(M\) being this matrix.
| void BlockMatrixBase< MatrixType >::Tvmult_add | ( | BlockVectorType & | dst, |
| const BlockVectorType & | src | ||
| ) | const |
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.
| value_type BlockMatrixBase< MatrixType >::matrix_norm_square | ( | const BlockVectorType & | v | ) | const |
Return the norm of the vector v with respect to the norm induced by this matrix, i.e. 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.
| real_type BlockMatrixBase< MatrixType >::frobenius_norm | ( | ) | const |
Return the frobenius norm of the matrix, i.e. the square root of the sum of squares of all entries in the matrix.
| value_type BlockMatrixBase< MatrixType >::matrix_scalar_product | ( | const BlockVectorType & | u, |
| const BlockVectorType & | v | ||
| ) | const |
Compute the matrix scalar product \(\left(u,Mv\right)\).
| value_type BlockMatrixBase< MatrixType >::residual | ( | BlockVectorType & | dst, |
| const BlockVectorType & | x, | ||
| const BlockVectorType & | b | ||
| ) | const |
Compute the residual r=b-Ax. Write the residual into dst.
| void BlockMatrixBase< MatrixType >::print | ( | std::ostream & | out, |
| const bool | alternative_output = false |
||
| ) | const |
Print the matrix to the given stream, using the format (line,col) value, i.e. one nonzero entry of the matrix per line. The optional flag outputs the sparsity pattern in a different style according to the underlying sparse matrix type.
| iterator BlockMatrixBase< MatrixType >::begin | ( | ) |
Iterator starting at the first entry.
| iterator BlockMatrixBase< MatrixType >::end | ( | ) |
Final iterator.
| iterator BlockMatrixBase< MatrixType >::begin | ( | const size_type | r | ) |
Iterator starting at the first entry of row r.
| iterator BlockMatrixBase< MatrixType >::end | ( | const size_type | r | ) |
Final iterator of row r.
| const_iterator BlockMatrixBase< MatrixType >::begin | ( | ) | const |
Iterator starting at the first entry.
| const_iterator BlockMatrixBase< MatrixType >::end | ( | ) | const |
Final iterator.
| const_iterator BlockMatrixBase< MatrixType >::begin | ( | const size_type | r | ) | const |
Iterator starting at the first entry of row r.
| const_iterator BlockMatrixBase< MatrixType >::end | ( | const size_type | r | ) | const |
Final iterator of row r.
| const BlockIndices & BlockMatrixBase< MatrixType >::get_row_indices | ( | ) | const |
Return a reference to the underlying BlockIndices data of the rows.
| const BlockIndices & BlockMatrixBase< MatrixType >::get_column_indices | ( | ) | const |
Return a reference to the underlying BlockIndices data of the columns.
| std::size_t BlockMatrixBase< MatrixType >::memory_consumption | ( | ) | const |
Determine an estimate for the memory consumption (in bytes) of this object. Note that only the memory reserved on the current processor is returned in case this is called in an MPI-based program.
|
default |
Constructor; initializes the matrix to be empty, without any structure, i.e. the matrix is not usable at all. This constructor is therefore only useful for matrices which are members of a class. All other matrices should be created at a point in the data flow where all necessary information is available.
You have to initialize the matrix before usage with reinit(BlockSparsityPattern). The number of blocks per row and column are then determined by that function.
| BlockSparseMatrix< number >::BlockSparseMatrix | ( | const BlockSparsityPattern & | sparsity | ) |
Constructor. Takes the given matrix sparsity structure to represent the sparsity pattern of this matrix. You can change the sparsity pattern later on by calling the reinit() function.
This constructor initializes all sub-matrices with the sub-sparsity pattern within the argument.
You have to make sure that the lifetime of the sparsity structure is at least as long as that of this matrix or as long as reinit() is not called with a new sparsity structure.
|
overridevirtual |
Destructor.
| BlockSparseMatrix & BlockSparseMatrix< number >::operator= | ( | const BlockSparseMatrix< number > & | ) |
Pseudo copy operator only copying empty objects. The sizes of the block matrices need to be the same.
|
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 379 of file block_sparse_matrix.h.
| void BlockSparseMatrix< number >::clear | ( | ) |
Release all memory and return to a state just like after having called the default constructor. It also forgets the sparsity pattern it was previously tied to.
This calls SparseMatrix::clear on all sub-matrices and then resets this object to have no blocks at all.
|
virtual |
Reinitialize the sparse matrix with the given sparsity pattern. The latter tells the matrix how many nonzero elements there need to be reserved.
Basically, this function only calls SparseMatrix::reinit() of the sub- matrices with the block sparsity patterns of the parameter.
You have to make sure that the lifetime of the sparsity structure is at least as long as that of this matrix or as long as reinit(const SparsityPattern &) is not called with a new sparsity structure.
The elements of the matrix are set to zero by this function.
| bool BlockSparseMatrix< number >::empty | ( | ) | const |
Return whether the object is empty. It is empty if either both dimensions are zero or no BlockSparsityPattern is associated.
| size_type BlockSparseMatrix< number >::get_row_length | ( | const size_type | row | ) | const |
Return the number of entries in a specific row.
| size_type BlockSparseMatrix< number >::n_nonzero_elements | ( | ) | const |
Return the number of nonzero elements of this matrix. Actually, it returns the number of entries in the sparsity pattern; if any of the entries should happen to be zero, it is counted anyway.
| size_type BlockSparseMatrix< number >::n_actually_nonzero_elements | ( | const double | threshold = 0.0 | ) | const |
Return the number of actually nonzero elements. Just counts the number of actually nonzero elements (with absolute value larger than threshold) of all the blocks.
| const BlockSparsityPattern & BlockSparseMatrix< number >::get_sparsity_pattern | ( | ) | const |
Return a (constant) reference to the underlying sparsity pattern of this matrix.
Though the return value is declared const, you should be aware that it may change if you call any nonconstant function of objects which operate on it.
| std::size_t BlockSparseMatrix< number >::memory_consumption | ( | ) | const |
Determine an estimate for the memory consumption (in bytes) of this object.
|
inline |
Matrix-vector multiplication: let \(dst = M*src\) with \(M\) being this matrix.
Definition at line 395 of file block_sparse_matrix.h.
|
inline |
Matrix-vector multiplication. Just like the previous function, but only applicable if the matrix has only one block column.
Definition at line 406 of file block_sparse_matrix.h.
|
inline |
Matrix-vector multiplication. Just like the previous function, but only applicable if the matrix has only one block row.
Definition at line 417 of file block_sparse_matrix.h.
|
inline |
Matrix-vector multiplication. Just like the previous function, but only applicable if the matrix has only one block.
Definition at line 428 of file block_sparse_matrix.h.
|
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 439 of file block_sparse_matrix.h.
|
inline |
Matrix-vector multiplication. Just like the previous function, but only applicable if the matrix has only one block row.
Definition at line 450 of file block_sparse_matrix.h.
|
inline |
Matrix-vector multiplication. Just like the previous function, but only applicable if the matrix has only one block column.
Definition at line 461 of file block_sparse_matrix.h.
|
inline |
Matrix-vector multiplication. Just like the previous function, but only applicable if the matrix has only one block.
Definition at line 472 of file block_sparse_matrix.h.
|
inline |
Apply the Jacobi preconditioner, which multiplies every element of the src vector by the inverse of the respective diagonal element and multiplies the result with the relaxation parameter omega.
All diagonal blocks must be square matrices for this operation.
Definition at line 483 of file block_sparse_matrix.h.
|
inline |
Apply the Jacobi preconditioner to a simple vector.
The matrix must be a single square block for this.
Definition at line 504 of file block_sparse_matrix.h.
| void BlockSparseMatrix< number >::print_formatted | ( | std::ostream & | out, |
| const unsigned int | precision = 3, |
||
| const bool | scientific = true, |
||
| const unsigned int | width = 0, |
||
| const char * | zero_string = " ", |
||
| const double | denominator = 1. |
||
| ) | const |
Print the matrix in the usual format, i.e. as a matrix and not as a list of nonzero elements. For better readability, elements not in the matrix are displayed as empty space, while matrix elements which are explicitly set to zero are displayed as such.
The parameters allow for a flexible setting of the output format: precision and scientific are used to determine the number format, where scientific = false means fixed point notation. A zero entry for width makes the function compute a width, but it may be changed to a positive value, if output is crude.
Additionally, a character for an empty value may be specified.
Finally, the whole matrix can be multiplied with a common denominator to produce more readable output, even integers.
|
default |
Default constructor. The result is an empty object with zero dimensions.
| BlockSparseMatrixEZ< Number >::BlockSparseMatrixEZ | ( | const unsigned int | block_rows, |
| const unsigned int | block_cols | ||
| ) |
Constructor setting up an object with given number of block rows and columns. The blocks themselves still have zero dimension.
| BlockSparseMatrixEZ< Number >::BlockSparseMatrixEZ | ( | const BlockSparseMatrixEZ< Number > & | ) |
Copy constructor. This is needed for some container classes. It creates an object of the same number of block rows and columns. Since it calls the copy constructor of SparseMatrixEZ, the block s must be empty.
| BlockSparseMatrixEZ & BlockSparseMatrixEZ< Number >::operator= | ( | const BlockSparseMatrixEZ< Number > & | ) |
Copy operator. Like the copy constructor, this may be called for objects with empty blocks only.
| BlockSparseMatrixEZ & BlockSparseMatrixEZ< Number >::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 BlockSparseMatrixEZ< Number >::clear | ( | ) |
Set matrix to zero dimensions and release memory.
| void BlockSparseMatrixEZ< Number >::reinit | ( | const unsigned int | n_block_rows, |
| const unsigned int | n_block_cols | ||
| ) |
Initialize to given block numbers. After this operation, the matrix will have the block dimensions provided. Each block will have zero dimensions and must be initialized subsequently. After setting the sizes of the blocks, collect_sizes() must be called to update internal data structures.
| void BlockSparseMatrixEZ< 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.
|
inline |
Access the block with the given coordinates.
Definition at line 290 of file block_sparse_matrix_ez.h.
|
inline |
Access the block with the given coordinates. Version for constant objects.
Definition at line 303 of file block_sparse_matrix_ez.h.
|
inline |
Return the number of blocks in a column.
Definition at line 272 of file block_sparse_matrix_ez.h.
|
inline |
Return the number of blocks in a row.
Definition at line 281 of file block_sparse_matrix_ez.h.
| bool BlockSparseMatrixEZ< Number >::empty | ( | ) | const |
Return whether the object is empty. It is empty if no memory is allocated, which is the same as that both dimensions are zero. This function is just the concatenation of the respective call to all sub- matrices.
|
inline |
Return number of rows of this matrix, which equals the dimension of the codomain (or range) space. It is the sum of the number of rows over the sub-matrix blocks of this matrix. Recall that the matrix is of size m() times n().
Definition at line 316 of file block_sparse_matrix_ez.h.
|
inline |
Return number of columns of this matrix, which equals the dimension of the domain space. It is the sum of the number of columns over the sub- matrix blocks of this matrix. Recall that the matrix is of size m() times n().
Definition at line 325 of file block_sparse_matrix_ez.h.
|
inline |
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.
Definition at line 334 of file block_sparse_matrix_ez.h.
|
inline |
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.
Definition at line 352 of file block_sparse_matrix_ez.h.
| void BlockSparseMatrixEZ< Number >::vmult | ( | BlockVector< somenumber > & | dst, |
| const BlockVector< somenumber > & | src | ||
| ) | const |
Matrix-vector multiplication: let \(dst = M*src\) with \(M\) being this matrix.
Definition at line 370 of file block_sparse_matrix_ez.h.
| void BlockSparseMatrixEZ< Number >::Tvmult | ( | BlockVector< somenumber > & | dst, |
| const BlockVector< somenumber > & | src | ||
| ) | const |
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 408 of file block_sparse_matrix_ez.h.
| void BlockSparseMatrixEZ< Number >::vmult_add | ( | BlockVector< somenumber > & | dst, |
| const BlockVector< somenumber > & | src | ||
| ) | const |
Adding Matrix-vector multiplication. Add \(M*src\) on \(dst\) with \(M\) being this matrix.
Definition at line 390 of file block_sparse_matrix_ez.h.
| void BlockSparseMatrixEZ< Number >::Tvmult_add | ( | BlockVector< somenumber > & | dst, |
| const BlockVector< somenumber > & | src | ||
| ) | const |
Adding Matrix-vector multiplication. Add \(M^T*src\) to \(dst\) with \(M\) being this matrix. This function does the same as vmult_add() but takes the transposed matrix.
Definition at line 428 of file block_sparse_matrix_ez.h.
|
inline |
Print statistics. If full is true, prints a histogram of all existing row lengths and allocated row lengths. Otherwise, just the relation of allocated and used entries is shown.
Definition at line 446 of file block_sparse_matrix_ez.h.
| number ChunkSparseMatrixIterators::Accessor< number, Constness >::value | ( | ) | const |
Value of this matrix entry.
| number & ChunkSparseMatrixIterators::Accessor< number, Constness >::value | ( | ) |
Value of this matrix entry.
| const ChunkSparseMatrix< number > & ChunkSparseMatrixIterators::Accessor< number, Constness >::get_matrix | ( | ) | const |
Return a reference to the matrix into which this accessor points. Note that in the present case, this is a constant reference.
| ChunkSparseMatrixIterators::Accessor< number, true >::Accessor | ( | MatrixType * | matrix, |
| const unsigned int | row | ||
| ) |
Constructor.
| ChunkSparseMatrixIterators::Accessor< number, true >::Accessor | ( | MatrixType * | matrix | ) |
Constructor. Construct the end accessor for the given matrix.
| ChunkSparseMatrixIterators::Accessor< number, true >::Accessor | ( | const ChunkSparseMatrixIterators::Accessor< number, false > & | a | ) |
Copy constructor to get from a non-const accessor to a const accessor.
| number ChunkSparseMatrixIterators::Accessor< number, true >::value | ( | ) | const |
Value of this matrix entry.
| const MatrixType & ChunkSparseMatrixIterators::Accessor< number, true >::get_matrix | ( | ) | const |
Return a reference to the matrix into which this accessor points. Note that in the present case, this is a constant reference.
| ChunkSparseMatrixIterators::Accessor< number, false >::Reference::Reference | ( | const Accessor< number, false > * | accessor, |
| const bool | dummy | ||
| ) |
Constructor. For the second argument, see the general class documentation.
| ChunkSparseMatrixIterators::Accessor< number, false >::Reference::operator number | ( | ) | const |
Conversion operator to the data type of the matrix.
| const Reference & ChunkSparseMatrixIterators::Accessor< number, false >::Reference::operator= | ( | const number | n | ) | const |
Set the element of the matrix we presently point to to n.
| const Reference & ChunkSparseMatrixIterators::Accessor< number, false >::Reference::operator+= | ( | const number | n | ) | const |
Add n to the element of the matrix we presently point to.
| const Reference & ChunkSparseMatrixIterators::Accessor< number, false >::Reference::operator-= | ( | const number | n | ) | const |
Subtract n from the element of the matrix we presently point to.
| const Reference & ChunkSparseMatrixIterators::Accessor< number, false >::Reference::operator*= | ( | const number | n | ) | const |
Multiply the element of the matrix we presently point to by n.
| const Reference & ChunkSparseMatrixIterators::Accessor< number, false >::Reference::operator/= | ( | const number | n | ) | const |
Divide the element of the matrix we presently point to by n.
| ChunkSparseMatrixIterators::Accessor< number, false >::Accessor | ( | MatrixType * | matrix, |
| const unsigned int | row | ||
| ) |
Constructor.
| ChunkSparseMatrixIterators::Accessor< number, false >::Accessor | ( | MatrixType * | matrix | ) |
Constructor. Construct the end accessor for the given matrix.
| Reference ChunkSparseMatrixIterators::Accessor< number, false >::value | ( | ) | const |
Value of this matrix entry, returned as a read- and writable reference.
| MatrixType & ChunkSparseMatrixIterators::Accessor< number, false >::get_matrix | ( | ) | const |
Return a reference to the matrix into which this accessor points. Note that in the present case, this is a non-constant reference.
| ChunkSparseMatrixIterators::Iterator< number, Constness >::Iterator | ( | MatrixType * | matrix, |
| const unsigned int | row | ||
| ) |
Constructor. Create an iterator into the matrix matrix for the given row and the index within it.
| ChunkSparseMatrixIterators::Iterator< number, Constness >::Iterator | ( | MatrixType * | matrix | ) |
Constructor. Create the end iterator for the given matrix.
| ChunkSparseMatrixIterators::Iterator< number, Constness >::Iterator | ( | const ChunkSparseMatrixIterators::Iterator< number, false > & | i | ) |
Conversion constructor to get from a non-const iterator to a const iterator.
| Iterator & ChunkSparseMatrixIterators::Iterator< number, Constness >::operator++ | ( | ) |
Prefix increment.
| Iterator ChunkSparseMatrixIterators::Iterator< number, Constness >::operator++ | ( | int | ) |
Postfix increment.
| const Accessor< number, Constness > & ChunkSparseMatrixIterators::Iterator< number, Constness >::operator* | ( | ) | const |
Dereferencing operator.
| const Accessor< number, Constness > * ChunkSparseMatrixIterators::Iterator< number, Constness >::operator-> | ( | ) | const |
Dereferencing operator.
| bool ChunkSparseMatrixIterators::Iterator< number, Constness >::operator== | ( | const Iterator< number, Constness > & | ) | const |
Comparison. True, if both iterators point to the same matrix position.
| bool ChunkSparseMatrixIterators::Iterator< number, Constness >::operator!= | ( | const Iterator< number, Constness > & | ) | const |
Inverse of ==.
| bool ChunkSparseMatrixIterators::Iterator< number, Constness >::operator< | ( | const Iterator< number, Constness > & | ) | const |
Comparison operator. Result is true if either the first row number is smaller or if the row numbers are equal and the first index is smaller.
This function is only valid if both iterators point into the same matrix.
| bool ChunkSparseMatrixIterators::Iterator< number, Constness >::operator> | ( | const Iterator< number, Constness > & | ) | const |
Comparison operator. Works in the same way as above operator, just the other way round.
| int ChunkSparseMatrixIterators::Iterator< number, Constness >::operator- | ( | const Iterator< number, Constness > & | p | ) | const |
Return the distance between the current iterator and the argument. The distance is given by how many times one has to apply operator++ to the current iterator to get the argument (for a positive return value), or operator-- (for a negative return value).
| Iterator ChunkSparseMatrixIterators::Iterator< number, Constness >::operator+ | ( | const unsigned int | n | ) | const |
Return an iterator that is n ahead of the current one.
| ChunkSparseMatrix< number >::ChunkSparseMatrix | ( | ) |
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(const ChunkSparsityPattern&).
| ChunkSparseMatrix< number >::ChunkSparseMatrix | ( | const ChunkSparseMatrix< number > & | ) |
Copy constructor. This constructor is only allowed to be called if the matrix to be copied is empty. This is for the same reason as for the ChunkSparsityPattern, see there for the details.
If you really want to copy a whole matrix, you can do so by using the copy_from() function.
|
explicit |
Constructor. Takes the given matrix sparsity structure to represent the sparsity pattern of this matrix. You can change the sparsity pattern later on by calling the reinit(const ChunkSparsityPattern&) function.
You have to make sure that the lifetime of the sparsity structure is at least as long as that of this matrix or as long as reinit(const ChunkSparsityPattern&) is not called with a new sparsity pattern.
The constructor is marked explicit so as to disallow that someone passes a sparsity pattern in place of a sparse matrix to some function, where an empty matrix would be generated then.
| ChunkSparseMatrix< number >::ChunkSparseMatrix | ( | const ChunkSparsityPattern & | sparsity, |
| const IdentityMatrix & | id | ||
| ) |
Copy constructor: initialize the matrix with the identity matrix. This constructor will throw an exception if the sizes of the sparsity pattern and the identity matrix do not coincide, or if the sparsity pattern does not provide for nonzero entries on the entire diagonal.
|
overridevirtual |
Destructor. Free all memory, but do not release the memory of the sparsity structure.
| ChunkSparseMatrix< number > & ChunkSparseMatrix< number >::operator= | ( | const ChunkSparseMatrix< number > & | ) |
Copy operator. Since copying entire sparse matrices is a very expensive operation, we disallow doing so except for the special case of empty matrices of size zero. This doesn't seem particularly useful, but is exactly what one needs if one wanted to have a std::vector<ChunkSparseMatrix<double> >: in that case, one can create a vector (which needs the ability to copy objects) of empty matrices that are then later filled with something useful.
| ChunkSparseMatrix< number > & ChunkSparseMatrix< number >::operator= | ( | const IdentityMatrix & | id | ) |
Copy operator: initialize the matrix with the identity matrix. This operator will throw an exception if the sizes of the sparsity pattern and the identity matrix do not coincide, or if the sparsity pattern does not provide for nonzero entries on the entire diagonal.
| ChunkSparseMatrix & ChunkSparseMatrix< number >::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.
|
virtual |
Reinitialize the sparse matrix with the given sparsity pattern. The latter tells the matrix how many nonzero elements there need to be reserved.
Regarding memory allocation, the same applies as said above.
You have to make sure that the lifetime of the sparsity structure is at least as long as that of this matrix or as long as reinit(const ChunkSparsityPattern &) is not called with a new sparsity structure.
The elements of the matrix are set to zero by this function.
|
virtual |
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.
| bool ChunkSparseMatrix< number >::empty | ( | ) | const |
Return whether the object is empty. It is empty if either both dimensions are zero or no ChunkSparsityPattern is associated.
| size_type ChunkSparseMatrix< number >::m | ( | ) | const |
Return the dimension of the codomain (or range) space. Note that the matrix is of dimension \(m \times n\).
| size_type ChunkSparseMatrix< number >::n | ( | ) | const |
Return the dimension of the domain space. Note that the matrix is of dimension \(m \times n\).
| size_type ChunkSparseMatrix< number >::n_nonzero_elements | ( | ) | const |
Return the number of nonzero elements of this matrix. Actually, it returns the number of entries in the sparsity pattern; if any of the entries should happen to be zero, it is counted anyway.
| size_type ChunkSparseMatrix< number >::n_actually_nonzero_elements | ( | ) | const |
Return the number of actually nonzero elements of this matrix.
Note, that this function does (in contrary to n_nonzero_elements()) not count all entries of the sparsity pattern but only the ones that are nonzero.
| const ChunkSparsityPattern & ChunkSparseMatrix< number >::get_sparsity_pattern | ( | ) | const |
Return a (constant) reference to the underlying sparsity pattern of this matrix.
Though the return value is declared const, you should be aware that it may change if you call any nonconstant function of objects which operate on it.
| std::size_t ChunkSparseMatrix< number >::memory_consumption | ( | ) | const |
Determine an estimate for the memory consumption (in bytes) of this object. See MemoryConsumption.
| void ChunkSparseMatrix< number >::set | ( | const size_type | i, |
| const size_type | j, | ||
| const number | 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.
| void ChunkSparseMatrix< number >::add | ( | const size_type | i, |
| const size_type | j, | ||
| const number | 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.
| void ChunkSparseMatrix< number >::add | ( | const size_type | row, |
| const size_type | n_cols, | ||
| const size_type * | col_indices, | ||
| const number2 * | values, | ||
| const bool | elide_zero_values = true, |
||
| const bool | col_indices_are_sorted = false |
||
| ) |
Add an array of values given by values in the given global matrix row at columns specified by col_indices in the sparse matrix.
The optional parameter elide_zero_values can be used to specify whether zero values should be added anyway or these should be filtered away and only non-zero data is added. The default value is true, i.e., zero values won't be added into the matrix.
| ChunkSparseMatrix & ChunkSparseMatrix< number >::operator*= | ( | const number | factor | ) |
Multiply the entire matrix by a fixed factor.
| ChunkSparseMatrix & ChunkSparseMatrix< number >::operator/= | ( | const number | factor | ) |
Divide the entire matrix by a fixed factor.
| void ChunkSparseMatrix< number >::symmetrize | ( | ) |
Symmetrize the matrix by forming the mean value between the existing matrix and its transpose, \(A = \frac 12(A+A^T)\).
This operation assumes that the underlying sparsity pattern represents a symmetric object. If this is not the case, then the result of this operation will not be a symmetric matrix, since it only explicitly symmetrizes by looping over the lower left triangular part for efficiency reasons; if there are entries in the upper right triangle, then these elements are missed in the symmetrization. Symmetrization of the sparsity pattern can be obtain by ChunkSparsityPattern::symmetrize().
| ChunkSparseMatrix< number > & ChunkSparseMatrix< number >::copy_from | ( | const ChunkSparseMatrix< somenumber > & | source | ) |
Copy the matrix given as argument into the current object.
Copying matrices is an expensive operation that we do not want to happen by accident through compiler generated code for operator=. (This would happen, for example, if one accidentally declared a function argument of the current type by value rather than by reference.) The functionality of copying matrices is implemented in this member function instead. All copy operations of objects of this type therefore require an explicit function call.
The source matrix may be a matrix of arbitrary type, as long as its data type is convertible to the data type of this matrix.
The function returns a reference to *this.
| void ChunkSparseMatrix< number >::copy_from | ( | const ForwardIterator | begin, |
| const ForwardIterator | end | ||
| ) |
This function is complete analogous to the ChunkSparsityPattern::copy_from() function in that it allows to initialize a whole matrix in one step. See there for more information on argument types and their meaning. You can also find a small example on how to use this function there.
The only difference to the cited function is that the objects which the inner iterator points to need to be of type std::pair<unsigned int, value, where value needs to be convertible to the element type of this class, as specified by the number template argument.
Previous content of the matrix is overwritten. Note that the entries specified by the input parameters need not necessarily cover all elements of the matrix. Elements not covered remain untouched.
| void ChunkSparseMatrix< number >::copy_from | ( | const FullMatrix< somenumber > & | matrix | ) |
Copy the nonzero entries of a full matrix into this object. Previous content is deleted. Note that the underlying sparsity pattern must be appropriate to hold the nonzero entries of the full matrix.
| void ChunkSparseMatrix< number >::add | ( | const number | factor, |
| const ChunkSparseMatrix< somenumber > & | matrix | ||
| ) |
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.
| number ChunkSparseMatrix< number >::operator() | ( | const size_type | i, |
| const size_type | j | ||
| ) | const |
Return the value of the entry (i,j). This may be an expensive operation and you should always take care where to call this function. In order to avoid abuse, this function throws an exception if the required element does not exist in the matrix.
In case you want a function that returns zero instead (for entries that are not in the sparsity pattern of the matrix), use the el() function.
If you are looping over all elements, consider using one of the iterator classes instead, since they are tailored better to a sparse matrix structure.
| number ChunkSparseMatrix< number >::el | ( | const size_type | i, |
| const size_type | j | ||
| ) | const |
This function is mostly like operator()() in that it returns the value of the matrix entry (i,j). The only difference is that if this entry does not exist in the sparsity pattern, then instead of raising an exception, zero is returned. While this may be convenient in some cases, note that it is simple to write algorithms that are slow compared to an optimal solution, since the sparsity of the matrix is not used.
If you are looping over all elements, consider using one of the iterator classes instead, since they are tailored better to a sparse matrix structure.
| number ChunkSparseMatrix< number >::diag_element | ( | const size_type | i | ) | const |
Return the main diagonal element in the ith row. This function throws an error if the matrix is not quadratic.
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.
| void ChunkSparseMatrix< number >::extract_row_copy | ( | const size_type | row, |
| const size_type | array_length, | ||
| size_type & | row_length, | ||
| size_type * | column_indices, | ||
| number * | values | ||
| ) | const |
Extracts a copy of the values and indices in the given matrix row.
The user is expected to pass the length of the arrays column_indices and values, which gives a means for checking that we do not write to unallocated memory. This method is motivated by a similar method in Trilinos row matrices and gives faster access to entries in the matrix as compared to iterators which are quite slow for this matrix type.
| void ChunkSparseMatrix< number >::vmult | ( | OutVector & | dst, |
| const InVector & | src | ||
| ) | const |
Matrix-vector multiplication: let dst = M*src with M being this matrix.
Note that while this function can operate on all vectors that offer iterator classes, it is only really effective for objects of type Vector. For all classes for which iterating over elements, or random member access is expensive, this function is not efficient. In particular, if you want to multiply with BlockVector objects, you should consider using a BlockChunkSparseMatrix as well.
Source and destination must not be the same vector.
| void ChunkSparseMatrix< number >::Tvmult | ( | OutVector & | dst, |
| const InVector & | src | ||
| ) | const |
Matrix-vector multiplication: let dst = MT*src with M being this matrix. This function does the same as vmult() but takes the transposed matrix.
Note that while this function can operate on all vectors that offer iterator classes, it is only really effective for objects of type Vector. For all classes for which iterating over elements, or random member access is expensive, this function is not efficient. In particular, if you want to multiply with BlockVector objects, you should consider using a BlockChunkSparseMatrix as well.
Source and destination must not be the same vector.
| void ChunkSparseMatrix< number >::vmult_add | ( | OutVector & | dst, |
| const InVector & | src | ||
| ) | const |
Adding Matrix-vector multiplication. Add M*src on dst with M being this matrix.
Note that while this function can operate on all vectors that offer iterator classes, it is only really effective for objects of type Vector. For all classes for which iterating over elements, or random member access is expensive, this function is not efficient. In particular, if you want to multiply with BlockVector objects, you should consider using a BlockChunkSparseMatrix as well.
Source and destination must not be the same vector.
| void ChunkSparseMatrix< number >::Tvmult_add | ( | OutVector & | dst, |
| const InVector & | src | ||
| ) | const |
Adding Matrix-vector multiplication. Add MT*src to dst with M being this matrix. This function does the same as vmult_add() but takes the transposed matrix.
Note that while this function can operate on all vectors that offer iterator classes, it is only really effective for objects of type Vector. For all classes for which iterating over elements, or random member access is expensive, this function is not efficient. In particular, if you want to multiply with BlockVector objects, you should consider using a BlockChunkSparseMatrix as well.
Source and destination must not be the same vector.
| somenumber ChunkSparseMatrix< number >::matrix_norm_square | ( | const Vector< somenumber > & | v | ) | const |
Return the square of the norm of the vector \(v\) with respect to the norm induced by this matrix, i.e. \(\left(v,Mv\right)\). This is useful, e.g. in the finite element context, where the \(L_2\) 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.
Obviously, the matrix needs to be quadratic for this operation, and for the result to actually be a norm it also needs to be either real symmetric or complex hermitian.
The underlying template types of both this matrix and the given vector should either both be real or complex-valued, but not mixed, for this function to make sense.
| somenumber ChunkSparseMatrix< number >::matrix_scalar_product | ( | const Vector< somenumber > & | u, |
| const Vector< somenumber > & | v | ||
| ) | const |
Compute the matrix scalar product \(\left(u,Mv\right)\).
| somenumber ChunkSparseMatrix< number >::residual | ( | Vector< somenumber > & | dst, |
| const Vector< somenumber > & | x, | ||
| const Vector< somenumber > & | 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.
| real_type ChunkSparseMatrix< number >::l1_norm | ( | ) | const |
Return the l1-norm of the matrix, that is \(|M|_1=max_{all columns j}\sum_{all rows i} |M_ij|\), (max. sum of columns). This is the natural matrix norm that is compatible to the l1-norm for vectors, i.e. \(|Mv|_1\leq |M|_1 |v|_1\). (cf. Haemmerlin-Hoffmann : Numerische Mathematik)
| real_type ChunkSparseMatrix< number >::linfty_norm | ( | ) | const |
Return the linfty-norm of the matrix, that is \(|M|_infty=max_{all rows i}\sum_{all columns j} |M_ij|\), (max. sum of rows). This is the natural matrix norm that is compatible to the linfty-norm of vectors, i.e. \(|Mv|_infty \leq |M|_infty |v|_infty\). (cf. Haemmerlin-Hoffmann : Numerische Mathematik)
| real_type ChunkSparseMatrix< number >::frobenius_norm | ( | ) | const |
Return the frobenius norm of the matrix, i.e. the square root of the sum of squares of all entries in the matrix.
| void ChunkSparseMatrix< number >::precondition_Jacobi | ( | Vector< somenumber > & | dst, |
| const Vector< somenumber > & | src, | ||
| const number | omega = 1. |
||
| ) | const |
Apply the Jacobi preconditioner, which multiplies every element of the src vector by the inverse of the respective diagonal element and multiplies the result with the relaxation factor omega.
| void ChunkSparseMatrix< number >::precondition_SSOR | ( | Vector< somenumber > & | dst, |
| const Vector< somenumber > & | src, | ||
| const number | om = 1. |
||
| ) | const |
Apply SSOR preconditioning to src.
| void ChunkSparseMatrix< number >::precondition_SOR | ( | Vector< somenumber > & | dst, |
| const Vector< somenumber > & | src, | ||
| const number | om = 1. |
||
| ) | const |
Apply SOR preconditioning matrix to src.
| void ChunkSparseMatrix< number >::precondition_TSOR | ( | Vector< somenumber > & | dst, |
| const Vector< somenumber > & | src, | ||
| const number | om = 1. |
||
| ) | const |
Apply transpose SOR preconditioning matrix to src.
| void ChunkSparseMatrix< number >::SSOR | ( | Vector< somenumber > & | v, |
| const number | omega = 1. |
||
| ) | const |
Perform SSOR preconditioning in-place. Apply the preconditioner matrix without copying to a second vector. omega is the relaxation parameter.
| void ChunkSparseMatrix< number >::SOR | ( | Vector< somenumber > & | v, |
| const number | om = 1. |
||
| ) | const |
Perform an SOR preconditioning in-place. omega is the relaxation parameter.
| void ChunkSparseMatrix< number >::TSOR | ( | Vector< somenumber > & | v, |
| const number | om = 1. |
||
| ) | const |
Perform a transpose SOR preconditioning in-place. omega is the relaxation parameter.
| void ChunkSparseMatrix< number >::PSOR | ( | Vector< somenumber > & | v, |
| const std::vector< size_type > & | permutation, | ||
| const std::vector< size_type > & | inverse_permutation, | ||
| const number | om = 1. |
||
| ) | const |
Perform a permuted SOR preconditioning in-place.
The standard SOR method is applied in the order prescribed by permutation, that is, first the row permutation[0], then permutation[1] and so on. For efficiency reasons, the permutation as well as its inverse are required.
omega is the relaxation parameter.
| void ChunkSparseMatrix< number >::TPSOR | ( | Vector< somenumber > & | v, |
| const std::vector< size_type > & | permutation, | ||
| const std::vector< size_type > & | inverse_permutation, | ||
| const number | om = 1. |
||
| ) | const |
Perform a transposed permuted SOR preconditioning in-place.
The transposed SOR method is applied in the order prescribed by permutation, that is, first the row permutation[m()-1], then permutation[m()-2] and so on. For efficiency reasons, the permutation as well as its inverse are required.
omega is the relaxation parameter.
| void ChunkSparseMatrix< number >::SOR_step | ( | Vector< somenumber > & | v, |
| const Vector< somenumber > & | b, | ||
| const number | om = 1. |
||
| ) | const |
Do one SOR step on v. Performs a direct SOR step with right hand side b.
| void ChunkSparseMatrix< number >::TSOR_step | ( | Vector< somenumber > & | v, |
| const Vector< somenumber > & | b, | ||
| const number | om = 1. |
||
| ) | const |
Do one adjoint SOR step on v. Performs a direct TSOR step with right hand side b.
| void ChunkSparseMatrix< number >::SSOR_step | ( | Vector< somenumber > & | v, |
| const Vector< somenumber > & | b, | ||
| const number | om = 1. |
||
| ) | const |
Do one SSOR step on v. Performs a direct SSOR step with right hand side b by performing TSOR after SOR.
| const_iterator ChunkSparseMatrix< number >::begin | ( | ) | const |
Iterator starting at first entry of the matrix. This is the version for constant matrices.
Note that due to the layout in ChunkSparseMatrix, iterating over matrix entries is considerably slower than for a sparse matrix, as the iterator is travels row-by-row, whereas data is stored in chunks of several rows and columns.
| const_iterator ChunkSparseMatrix< number >::end | ( | ) | const |
Final iterator. This is the version for constant matrices.
Note that due to the layout in ChunkSparseMatrix, iterating over matrix entries is considerably slower than for a sparse matrix, as the iterator is travels row-by-row, whereas data is stored in chunks of several rows and columns.
| iterator ChunkSparseMatrix< number >::begin | ( | ) |
Iterator starting at the first entry of the matrix. This is the version for non-constant matrices.
Note that due to the layout in ChunkSparseMatrix, iterating over matrix entries is considerably slower than for a sparse matrix, as the iterator is travels row-by-row, whereas data is stored in chunks of several rows and columns.
| iterator ChunkSparseMatrix< number >::end | ( | ) |
Final iterator. This is the version for non-constant matrices.
Note that due to the layout in ChunkSparseMatrix, iterating over matrix entries is considerably slower than for a sparse matrix, as the iterator is travels row-by-row, whereas data is stored in chunks of several rows and columns.
| const_iterator ChunkSparseMatrix< number >::begin | ( | const unsigned int | r | ) | const |
Iterator starting at the first entry of row r. This is the version for constant matrices.
Note that if the given row is empty, i.e. does not contain any nonzero entries, then the iterator returned by this function equals end(r). Note also that the iterator may not be dereferenceable in that case.
Note that due to the layout in ChunkSparseMatrix, iterating over matrix entries is considerably slower than for a sparse matrix, as the iterator is travels row-by-row, whereas data is stored in chunks of several rows and columns.
| const_iterator ChunkSparseMatrix< number >::end | ( | const unsigned int | r | ) | const |
Final iterator of row r. It points to the first element past the end of line r, or past the end of the entire sparsity pattern. This is the version for constant matrices.
Note that the end iterator is not necessarily dereferenceable. This is in particular the case if it is the end iterator for the last row of a matrix.
Note that due to the layout in ChunkSparseMatrix, iterating over matrix entries is considerably slower than for a sparse matrix, as the iterator is travels row-by-row, whereas data is stored in chunks of several rows and columns.
| iterator ChunkSparseMatrix< number >::begin | ( | const unsigned int | r | ) |
Iterator starting at the first entry of row r. This is the version for non-constant matrices.
Note that if the given row is empty, i.e. does not contain any nonzero entries, then the iterator returned by this function equals end(r). Note also that the iterator may not be dereferenceable in that case.
Note that due to the layout in ChunkSparseMatrix, iterating over matrix entries is considerably slower than for a sparse matrix, as the iterator is travels row-by-row, whereas data is stored in chunks of several rows and columns.
| iterator ChunkSparseMatrix< number >::end | ( | const unsigned int | r | ) |
Final iterator of row r. It points to the first element past the end of line r, or past the end of the entire sparsity pattern. This is the version for non-constant matrices.
Note that the end iterator is not necessarily dereferenceable. This is in particular the case if it is the end iterator for the last row of a matrix.
Note that due to the layout in ChunkSparseMatrix, iterating over matrix entries is considerably slower than for a sparse matrix, as the iterator is travels row-by-row, whereas data is stored in chunks of several rows and columns.
| void ChunkSparseMatrix< number >::print | ( | std::ostream & | out | ) | const |
Print the matrix to the given stream, using the format (line,col) value, i.e. one nonzero entry of the matrix per line.
| void ChunkSparseMatrix< number >::print_formatted | ( | std::ostream & | out, |
| const unsigned int | precision = 3, |
||
| const bool | scientific = true, |
||
| const unsigned int | width = 0, |
||
| const char * | zero_string = " ", |
||
| const double | denominator = 1. |
||
| ) | const |
Print the matrix in the usual format, i.e. as a matrix and not as a list of nonzero elements. For better readability, elements not in the matrix are displayed as empty space, while matrix elements which are explicitly set to zero are displayed as such.
The parameters allow for a flexible setting of the output format: precision and scientific are used to determine the number format, where scientific = false means fixed point notation. A zero entry for width makes the function compute a width, but it may be changed to a positive value, if output is crude.
Additionally, a character for an empty value may be specified.
Finally, the whole matrix can be multiplied with a common denominator to produce more readable output, even integers.
| void ChunkSparseMatrix< number >::print_pattern | ( | std::ostream & | out, |
| const double | threshold = 0. |
||
| ) | const |
Print the actual pattern of the matrix. For each entry with an absolute value larger than threshold, a '*' is printed, a ':' for every value smaller and a '.' for every entry not allocated.
| void ChunkSparseMatrix< number >::block_write | ( | std::ostream & | out | ) | const |
Write the data of this object en bloc to a file. This is done in a binary mode, so the output is neither readable by humans nor (probably) by other computers using a different operating system or number format.
The purpose of this function is that you can swap out matrices and sparsity pattern if you are short of memory, want to communicate between different programs, or allow objects to be persistent across different runs of the program.
| void ChunkSparseMatrix< number >::block_read | ( | std::istream & | in | ) |
Read data that has previously been written by block_write() from a file. This is done using the inverse operations to the above function, so it is reasonably fast because the bitstream is not interpreted except for a few numbers up front.
The object is resized on this operation, and all previous contents are lost. Note, however, that no checks are performed whether new data and the underlying ChunkSparsityPattern object fit together. It is your responsibility to make sure that the sparsity pattern and the data to be read match.
A primitive form of error checking is performed which will recognize the bluntest attempts to interpret some data as a matrix stored bitwise to a file that wasn't actually created that way, but not more.
|
protected |
Block row into which we presently point.
Definition at line 95 of file block_matrix_base.h.
|
protected |
Block column into which we presently point.
Definition at line 100 of file block_matrix_base.h.
|
protected |
The matrix accessed.
Definition at line 176 of file block_matrix_base.h.
|
protected |
Iterator of the underlying matrix class.
Definition at line 181 of file block_matrix_base.h.
|
protected |
The matrix accessed.
Definition at line 262 of file block_matrix_base.h.
|
protected |
Iterator of the underlying matrix class.
Definition at line 267 of file block_matrix_base.h.
|
private |
Object storing and managing the transformation of row indices to indices of the sub-objects.
Definition at line 252 of file block_sparse_matrix_ez.h.
|
private |
Object storing and managing the transformation of column indices to indices of the sub-objects.
Definition at line 258 of file block_sparse_matrix_ez.h.
|
private |
The actual matrices
Definition at line 263 of file block_sparse_matrix_ez.h.
|
private |
Pointer to the matrix we use.
Definition at line 140 of file chunk_sparse_matrix.h.
|
private |
Pointer to the accessor that denotes which element we presently point to.
Definition at line 234 of file chunk_sparse_matrix.h.
|
private |
Pointer to the matrix we use.
Definition at line 271 of file chunk_sparse_matrix.h.
|
private |
Store an object of the accessor class.
Definition at line 397 of file chunk_sparse_matrix.h.
Definition at line 104 of file block_matrix_base.h.
Definition at line 196 of file block_matrix_base.h.
|
friend |
Definition at line 196 of file block_matrix_base.h.
Definition at line 283 of file block_matrix_base.h.
Definition at line 149 of file chunk_sparse_matrix.h.
Definition at line 280 of file chunk_sparse_matrix.h.
1.9.4