Class for a sparse matrix stored in compressed row storage format.

#include <TSparseMatrix.hh>

Inheritance diagram for TSparseMatrix< T_value >:

Public Member Functions
	TSparseMatrix (const size_t anrows, const size_t ancols)
	construct sparse matrix of size anrows × ancols

	TSparseMatrix (const TIndexSet arow_is, const TIndexSet acol_is)
	construct sparse matrix of size anrows × ancols

	TSparseMatrix (const TBlockCluster *bct=nullptr)
	construct sparse matrix with size defined by block cluster bct

virtual void	set_cluster (const TBlockCluster *bct)
	set block cluster of matrix

virtual void	set_size (const size_t nrows, const size_t ncols)
	directly set dimension of matrix

void	init (const size_t nnz)
	initialise CRS data for nnz non-zero entries

size_t	rows () const
	return number of rows in matrix

size_t	cols () const
	return number of columns in matrix

size_t	n_non_zero () const
	return number of non-zero elements

const idx_t *	rowptr () const
	return row pointer array

const idx_t *	colind () const
	return column index array

virtual value_t	entry (const idx_t i, const idx_t j) const
	return matrix coefficient a_ij

virtual void	set_entry (const idx_t i, const idx_t j, const value_t c)
	set matrix coefficient a_ij if existent

virtual void	add_entry (const idx_t i, const idx_t j, const value_t c)
	add c to matrix coefficient a_ij if existent

virtual bool	has_entry (const idx_t i, const idx_t j) const
	return true if entry (i, j) exists

void	sort_entries ()
	sort matrix coefficients per row with respect to column

idx_t	rowptr (const idx_t i) const
	return i'th row pointer (constant)

idx_t &	rowptr (const idx_t i)
	return i'th row pointer

idx_t	colind (const idx_t i) const
	return i'th column index (constant)

idx_t &	colind (const idx_t i)
	return i'th column index

value_t	coeff (const idx_t i) const
	return i'th coefficient (constant)

value_t &	coeff (const idx_t i)
	return i'th coefficient

void	permute (const TPermutation &rowperm, const TPermutation &colperm)

bool	test_symmetry ()
	return true if matrix is symmetric (really check data)

size_t	avg_entries_per_row () const
	compute average number of entries per row

size_t	max_entries_per_row () const
	compute maximal number of entries per row

bool	has_diag_zero (const real_t eps=0.0)
	return true if matrix contains zero or elements < ε on diagonal

bool	is_diag_dom (const bool weak=false)
	return true if S is (weakly) diagonally dominant

real_t	diag_dom_factor ()
	return factor α, such that S + α·I is diagonally dominant (this = S)

void	check_matrix () const
	perform some tests on the matrix (for debugging)

template<typename T_idx >
void	import_crs (const size_t nrows, const size_t ncols, const size_t nnonzero, const T_idx rowptr, const T_idx colind, const value_t *coeffs)
	import CRS data into local matrix

template<typename T_idx >
void	import_ccs (const size_t nrows, const size_t ncols, const size_t nnonzero, const T_idx colptr, const T_idx rowind, const value_t *coeffs)
	import CCS data into local matrix

template<typename T_idx >
void	export_ccs (std::vector< T_idx > &colptr, std::vector< T_idx > &rowind, std::vector< value_t > &coeffs, const bool use_sym) const

virtual void	scale (const value_t alpha)
	compute this ≔ α·this

virtual void	mul_vec (const value_t alpha, const TVector< value_t > x, const value_t beta, TVector< value_t > y, const matop_t op=apply_normal) const
	compute y ≔ β·y + α·op(M)·x, with M = this

virtual void	add (const value_t alpha, const TMatrix< value_t > *matrix)
	compute this ≔ this + α · matrix

virtual void	transpose ()
	transpose matrix

virtual void	conjugate ()
	conjugate matrix coefficients

virtual void	truncate (const TTruncAcc &)
	truncate matrix to given accuracy (NOT YET IMPLEMENTED)

std::unique_ptr< TSparseMatrix< value_t > >	restrict (const TIndexSet &rowis, const TIndexSet &colis) const
	restrict sparse matrix to block index set rowis × colis

std::unique_ptr< TSparseMatrix< value_t > >	restrict (const TIndexSet &rowis, const TPermutation rowperm, const TIndexSet &colis, const TPermutation colperm) const

size_t	restrict_nonzeroes (const TIndexSet &rowis, const TIndexSet &colis) const
	return number of coefficients in sub block index set rowis × colis

size_t	restrict_nonzeroes (const TIndexSet &rowis, const TPermutation rowperm, const TIndexSet &colis, const TPermutation colperm) const
	return number of coefficients in sub block index set rowis × colis

virtual void	print (const uint ofs=0) const
	print matrix to stdout

virtual void	read (TByteStream &s)
	read data from stream s and copy to matrix

virtual void	build (TByteStream &s)
	use data from stream s to build matrix

virtual void	write (TByteStream &s) const
	write data to stream s

virtual size_t	bs_size () const
	returns size of object in bytestream

virtual auto	create () const -> std::unique_ptr< TMatrix< value_t > >
	return matrix of same class (but no content)

virtual auto	copy () const -> std::unique_ptr< TMatrix< value_t > >
	return copy of matrix

virtual auto	copy_struct () const -> std::unique_ptr< TMatrix< value_t > >
	return structural copy of matrix

virtual void	copy_to (TMatrix< value_t > *A) const
	copy matrix into matrix A

virtual size_t	byte_size () const
	return size in bytes used by this object

virtual void	check_data () const
	test data for invalid values, e.g. INF and NAN

virtual void	print_pattern_hist (std::ostream &os) const
	print histogram for entries per row in GNUPLOT format

Public Member Functions inherited from TMatrix< T_value >
	TMatrix ()
	construct zero sized matrix

	TMatrix (const TBlockCluster *bcl)
	construct matrix of size defined by block cluster bcl

	TMatrix (const TBlockIndexSet &bis)
	construct matrix of size defined by block index set bis

	TMatrix (const TMatrix< value_t > &A)
	copy constructor

virtual	~TMatrix ()
	dtor

int	id () const
	return ID

void	set_id (const int aid)
	set ID

virtual size_t	nrows (const matop_t op) const
	return number of rows of op(M)

virtual size_t	ncols (const matop_t op) const
	return number of columns of op(M)

TIndexSet	row_is () const
	return row index set

TIndexSet	col_is () const
	return column index set

TBlockIndexSet	block_is () const
	return block index set

TIndexSet	row_is (const matop_t op) const
	return row index set w.r.t. given matrix operation

TIndexSet	col_is (const matop_t op) const
	return row index set w.r.t. given matrix operation

TBlockIndexSet	block_is (const matop_t op) const
	return row index set w.r.t. given matrix operation

virtual idx_t	row_ofs () const
	return first index (number) in row

virtual idx_t	col_ofs () const
	return first index (number) in column

virtual void	set_ofs (const idx_t r, const idx_t c)
	set index set offsets

virtual void	set_block_is (const TBlockIndexSet &is)
	set block index set of matrix

bool	is_nonsym () const
	return true if matrix is unsymmetric

bool	is_symmetric () const
	return true if matrix is symmetric

bool	is_hermitian () const
	return true if matrix is hermitian

matform_t	form () const
	return matrix format

void	set_nonsym ()
	set matrix to be unsymmetric

void	set_symmetric ()
	set matrix to be symmetric

void	set_hermitian ()
	set matrix to be hermitian

virtual void	set_form (const matform_t f)
	set matrix format

virtual bool	is_zero () const
	return true, if matrix is zero

virtual bool	is_blocked () const
	return true, if matrix is blocked

virtual bool	is_dense () const
	return true, if matrix is dense

virtual bool	is_self_adjoint () const
	return true, if operator is self adjoint

const TProcSet &	procs () const
	return matrix processor set

uint	nprocs () const
	return number of processors in local set

virtual void	set_procs (const TProcSet &ps, const recursion_type_t rec_type=nonrecursive)
	set processor set of matrix

bool	is_distributed () const
	return true if matrix is distributed

virtual void	copy_struct_from (const TMatrix *M)

TUpdateAccumulator< value_t > &	accumulator ()
	access accumulator object

void	add_update (const TMatrix< value_t > *M, const TTruncAcc &acc)
	add update matrix

void	add_pending_direct (TDirectMatrixUpdate< value_t > *U)
	add update U to set of recursive pending updates

void	add_pending_recursive (TRecursiveMatrixUpdate< value_t > *U)
	add update U to set of recursive pending updates

virtual void	apply_updates (const TTruncAcc &acc, const recursion_type_t rec_type)

virtual bool	has_updates (const recursion_type_t recursion) const
	return true, if matrix has updates not yet applied

virtual bool	has_parent_updates (const recursion_type_t recursion) const
	return true, if parent matrix has updates not yet applied

const TBlockCluster *	cluster () const
	return corresponding block cluster of matrix

virtual void	set_cluster_force (const TBlockCluster *c)
	set block cluster of matrix (with forced setting of cluster variable)

virtual void	apply (const TVector< value_t > x, TVector< value_t > y, const matop_t op=apply_normal) const

virtual void	apply_add (const value_t alpha, const TVector< value_t > x, TVector< value_t > y, const matop_t op=apply_normal) const

virtual void	apply_add (const value_t alpha, const BLAS::Vector< value_t > &x, BLAS::Vector< value_t > &y, const matop_t op=apply_normal) const

virtual size_t	domain_dim () const
	return dimension of domain

virtual size_t	range_dim () const
	return dimension of range

virtual auto	domain_vector () const -> std::unique_ptr< TVector< value_t > >
	return vector in domain space

virtual auto	range_vector () const -> std::unique_ptr< TVector< value_t > >
	return vector in range space

virtual TMatrix< value_t > *	mul_right (const value_t alpha, const TMatrix< value_t > *B, const matop_t op_A, const matop_t op_B) const
	compute α·op(A)·op(B), with A = this

virtual TMatrix< value_t > *	mul_left (const value_t alpha, const TMatrix< value_t > *A, const matop_t op_A, const matop_t op_B) const
	compute α·op(A)·op(B), with B = this

virtual size_t	global_byte_size () const

virtual auto	copy (const TTruncAcc &acc, const bool coarsen=false) const -> std::unique_ptr< TMatrix< value_t > >
	return copy of matrix with accuracy acc and optional coarsening

virtual void	copy_from (const TMatrix< value_t > *A)
	copy data from matrix A

virtual void	copy_to (TMatrix< value_t > *A, const TTruncAcc &acc, const bool coarsen=false) const
	copy matrix into matrix A with accuracy acc and optional coarsening

virtual auto	row_vector () const -> std::unique_ptr< TVector< value_t > >
	return appropriate row vector object for matrix

virtual auto	col_vector () const -> std::unique_ptr< TVector< value_t > >
	return appropriate column vector object for matrix

virtual void	sum (const TProcSet &p, const uint pid, const uint nparts, TByteStream *bs, const TTruncAcc &acc)

Public Member Functions inherited from TLinearOperator< T_value >
virtual bool	is_complex () const
	return true, if field type is complex valued

virtual bool	is_real () const
	return true, if field type is real valued

Public Member Functions inherited from TTypeInfo
virtual typeid_t	type () const =0
	return type ID of object

virtual bool	is_type (const typeid_t t) const
	return true if local object is of given type ID t

virtual std::string	typestr () const
	return string representation of type

Public Member Functions inherited from TLockable
TMutex &	mutex ()
	give access to internal mutex

void	lock ()
	lock local mutex

void	unlock ()
	unlock local mutex

size_t	byte_size () const
	return size in bytes used by this object

Member Function Documentation

◆ export_ccs()

void export_ccs	(	std::vector< T_idx > &	colptr,
		std::vector< T_idx > &	rowind,
		std::vector< value_t > &	coeffs,
		const bool	use_sym
	)		const

export internal data to CCS format (real valued); if use_sym is true, only the lower triangular part is exported

◆ permute()

void permute	(	const TPermutation &	rowperm,
		const TPermutation &	colperm
	)

permute entries in sparse matrix according to rowperm (for rows) and colperm (for columns)

◆ restrict()

std::unique_ptr< TSparseMatrix< value_t > > restrict	(	const TIndexSet &	rowis,
		const TPermutation *	rowperm,
		const TIndexSet &	colis,
		const TPermutation *	colperm
	)		const

restrict sparse matrix to block index set rowis × colis which is given in a different ordering

rowperm permutes the row indices to the local ordering of the sparse matrix, while colperm permutes the local column indices to the ordering of colis
the returned matrix has the same ordering as rowis and colis

Public Member Functions

Member Function Documentation

◆ export_ccs()

◆ permute()

◆ restrict()