This structure is used as an intermediate data type to store a sparse matrix. More...

#include <ginkgo/core/base/matrix_data.hpp>

Collaboration diagram for gko::matrix_data< ValueType, IndexType >:

Public Types
using	value_type = ValueType

using	index_type = IndexType

using	nonzero_type = matrix_data_entry< value_type, index_type >

Public Member Functions
	matrix_data (dim< 2 > size_=dim< 2 >{}, ValueType value=zero< ValueType >())
	Initializes a matrix filled with the specified value. More...

template<typename RandomDistribution , typename RandomEngine >
	matrix_data (dim< 2 > size_, RandomDistribution &&dist, RandomEngine &&engine)
	Initializes a matrix with random values from the specified distribution. More...

	matrix_data (std::initializer_list< std::initializer_list< ValueType >> values)
	List-initializes the structure from a matrix of values. More...

	matrix_data (dim< 2 > size_, std::initializer_list< detail::input_triple< ValueType, IndexType >> nonzeros_)
	Initializes the structure from a list of nonzeros. More...

	matrix_data (dim< 2 > size_, const matrix_data &block)
	Initializes a matrix out of a matrix block via duplication. More...

template<typename Accessor >
	matrix_data (const range< Accessor > &data)
	Initializes a matrix from a range. More...

void	sort_row_major ()
	Sorts the nonzero vector so the values follow row-major order.

void	ensure_row_major_order ()
	Sorts the nonzero vector so the values follow row-major order.

void	remove_zeros ()
	Remove entries with value zero from the matrix data.

void	sum_duplicates ()
	Sum up all values that refer to the same matrix entry. More...

Static Public Member Functions
static matrix_data	diag (dim< 2 > size_, ValueType value)
	Initializes a diagonal matrix. More...

static matrix_data	diag (dim< 2 > size_, std::initializer_list< ValueType > nonzeros_)
	Initializes a diagonal matrix using a list of diagonal elements. More...

static matrix_data	diag (dim< 2 > size_, const matrix_data &block)
	Initializes a block-diagonal matrix. More...

template<typename ForwardIterator >
static matrix_data	diag (ForwardIterator begin, ForwardIterator end)
	Initializes a block-diagonal matrix from a list of diagonal blocks. More...

static matrix_data	diag (std::initializer_list< matrix_data > blocks)
	Initializes a block-diagonal matrix from a list of diagonal blocks. More...

template<typename RandomDistribution , typename RandomEngine >
static matrix_data	cond (size_type size, remove_complex< ValueType > condition_number, RandomDistribution &&dist, RandomEngine &&engine, size_type num_reflectors)
	Initializes a random dense matrix with a specific condition number. More...

template<typename RandomDistribution , typename RandomEngine >
static matrix_data	cond (size_type size, remove_complex< ValueType > condition_number, RandomDistribution &&dist, RandomEngine &&engine)
	Initializes a random dense matrix with a specific condition number. More...

Public Attributes
dim< 2 >	size
	Size of the matrix.

std::vector< nonzero_type >	nonzeros
	A vector of tuples storing the non-zeros of the matrix. More...

Detailed Description

template<typename ValueType = default_precision, typename IndexType = int32>
struct gko::matrix_data< ValueType, IndexType >

This structure is used as an intermediate data type to store a sparse matrix.

The matrix is stored as a sequence of nonzero elements, where each element is a triple of the form (row_index, column_index, value).

Note: All Ginkgo functions returning such a structure will return the nonzeros sorted in row-major order.; All Ginkgo functions that take this structure as input expect that the nonzeros are sorted in row-major order and that the index pair (row_index, column_index) of each nonzero is unique.; This structure is not optimized for usual access patterns and it can only exist on the CPU. Thus, it should only be used for utility functions which do not have to be optimized for performance.

Template Parameters

ValueType	type of matrix values stored in the structure
IndexType	type of matrix indexes stored in the structure

Constructor & Destructor Documentation

◆ matrix_data() [1/6]

template<typename ValueType = default_precision, typename IndexType = int32>

gko::matrix_data< ValueType, IndexType >::matrix_data	(	dim< 2 >	size_ = `dim<2>{}`,
		ValueType	value = `zero<ValueType>()`
	)

inline

Initializes a matrix filled with the specified value.

Parameters

size_	dimensions of the matrix
value	value used to fill the elements of the matrix

◆ matrix_data() [2/6]

template<typename ValueType = default_precision, typename IndexType = int32>

template<typename RandomDistribution , typename RandomEngine >

gko::matrix_data< ValueType, IndexType >::matrix_data	(	dim< 2 >	size_,
		RandomDistribution &&	dist,
		RandomEngine &&	engine
	)

inline

Initializes a matrix with random values from the specified distribution.

Template Parameters

RandomDistribution	random distribution type
RandomEngine	random engine type

Parameters

size_	dimensions of the matrix
dist	random distribution of the elements of the matrix
engine	random engine used to generate random values

◆ matrix_data() [3/6]

template<typename ValueType = default_precision, typename IndexType = int32>

gko::matrix_data< ValueType, IndexType >::matrix_data ( std::initializer_list< std::initializer_list< ValueType >> values )

inline

List-initializes the structure from a matrix of values.

Parameters

values a 2D braced-init-list of matrix values.

◆ matrix_data() [4/6]

template<typename ValueType = default_precision, typename IndexType = int32>

gko::matrix_data< ValueType, IndexType >::matrix_data	(	dim< 2 >	size_,
		std::initializer_list< detail::input_triple< ValueType, IndexType >>	nonzeros_
	)

inline

Initializes the structure from a list of nonzeros.

Parameters

size_	dimensions of the matrix
nonzeros_	list of nonzero elements

◆ matrix_data() [5/6]

template<typename ValueType = default_precision, typename IndexType = int32>

gko::matrix_data< ValueType, IndexType >::matrix_data	(	dim< 2 >	size_,
		const matrix_data< ValueType, IndexType > &	block
	)

inline

Initializes a matrix out of a matrix block via duplication.

Parameters

size	size of the block-matrix (in blocks)
diag_block	matrix block used to fill the complete matrix

References gko::matrix_data< ValueType, IndexType >::size.

◆ matrix_data() [6/6]

template<typename ValueType = default_precision, typename IndexType = int32>

template<typename Accessor >

gko::matrix_data< ValueType, IndexType >::matrix_data ( const range< Accessor > & data )

inline

Initializes a matrix from a range.

Template Parameters

Accessor accessor type of the input range

Parameters

data	range used to initialize the matrix

References gko::range< Accessor >::length().

Member Function Documentation

◆ cond() [1/2]

template<typename ValueType = default_precision, typename IndexType = int32>

template<typename RandomDistribution , typename RandomEngine >

static matrix_data gko::matrix_data< ValueType, IndexType >::cond	(	size_type	size,
		remove_complex< ValueType >	condition_number,
		RandomDistribution &&	dist,
		RandomEngine &&	engine
	)

inlinestatic

Initializes a random dense matrix with a specific condition number.

The matrix is generated by applying a series of random Hausholder reflectors to a diagonal matrix with diagonal entries uniformly distributed between sqrt(condition_number) and 1/sqrt(condition_number).

This version of the function applies size - 1 reflectors to each side of the diagonal matrix.

Template Parameters

RandomDistribution	the type of the random distribution
RandomEngine	the type of the random engine

Parameters

size	number of rows and columns of the matrix
condition_number	condition number of the matrix
dist	random distribution used to generate reflectors
engine	random engine used to generate reflectors

Returns: the dense matrix with the specified condition number

References gko::matrix_data< ValueType, IndexType >::cond(), and gko::matrix_data< ValueType, IndexType >::size.

◆ cond() [2/2]

template<typename ValueType = default_precision, typename IndexType = int32>

template<typename RandomDistribution , typename RandomEngine >

static matrix_data gko::matrix_data< ValueType, IndexType >::cond	(	size_type	size,
		remove_complex< ValueType >	condition_number,
		RandomDistribution &&	dist,
		RandomEngine &&	engine,
		size_type	num_reflectors
	)

inlinestatic

Initializes a random dense matrix with a specific condition number.

The matrix is generated by applying a series of random Hausholder reflectors to a diagonal matrix with diagonal entries uniformly distributed between sqrt(condition_number) and 1/sqrt(condition_number).

Template Parameters

RandomDistribution	the type of the random distribution
RandomEngine	the type of the random engine

Parameters

size	number of rows and columns of the matrix
condition_number	condition number of the matrix
dist	random distribution used to generate reflectors
engine	random engine used to generate reflectors
num_reflectors	number of reflectors to apply from each side

Returns: the dense matrix with the specified condition number

References gko::matrix_data< ValueType, IndexType >::size.

Referenced by gko::matrix_data< ValueType, IndexType >::cond().

◆ diag() [1/5]

template<typename ValueType = default_precision, typename IndexType = int32>

static matrix_data gko::matrix_data< ValueType, IndexType >::diag	(	dim< 2 >	size_,
		const matrix_data< ValueType, IndexType > &	block
	)

inlinestatic

Initializes a block-diagonal matrix.

Parameters

size_	the size of the matrix
diag_block	matrix used to fill diagonal blocks

Returns: the block-diagonal matrix

References gko::matrix_data< ValueType, IndexType >::nonzeros, and gko::matrix_data< ValueType, IndexType >::size.

◆ diag() [2/5]

template<typename ValueType = default_precision, typename IndexType = int32>

static matrix_data gko::matrix_data< ValueType, IndexType >::diag	(	dim< 2 >	size_,
		std::initializer_list< ValueType >	nonzeros_
	)

inlinestatic

Initializes a diagonal matrix using a list of diagonal elements.

Parameters

size_	dimensions of the matrix
nonzeros_	list of diagonal elements

Returns: the diagonal matrix

References gko::matrix_data< ValueType, IndexType >::nonzeros.

◆ diag() [3/5]

template<typename ValueType = default_precision, typename IndexType = int32>

static matrix_data gko::matrix_data< ValueType, IndexType >::diag	(	dim< 2 >	size_,
		ValueType	value
	)

inlinestatic

Initializes a diagonal matrix.

Parameters

size_	dimensions of the matrix
value	value used to fill the elements of the matrix

Returns: the diagonal matrix

References gko::is_nonzero(), and gko::matrix_data< ValueType, IndexType >::nonzeros.

Referenced by gko::matrix_data< ValueType, IndexType >::diag().

◆ diag() [4/5]

template<typename ValueType = default_precision, typename IndexType = int32>

template<typename ForwardIterator >

static matrix_data gko::matrix_data< ValueType, IndexType >::diag	(	ForwardIterator	begin,
		ForwardIterator	end
	)

inlinestatic

Initializes a block-diagonal matrix from a list of diagonal blocks.

Template Parameters

ForwardIterator type of list iterator

Parameters

begin	the first iterator of the list
end	the last iterator of the list

Returns: the block-diagonal matrix with diagonal blocks set to the blocks between begin (inclusive) and end (exclusive)

References gko::matrix_data< ValueType, IndexType >::nonzeros.

◆ diag() [5/5]

template<typename ValueType = default_precision, typename IndexType = int32>

static matrix_data gko::matrix_data< ValueType, IndexType >::diag ( std::initializer_list< matrix_data< ValueType, IndexType > > blocks )

inlinestatic

Initializes a block-diagonal matrix from a list of diagonal blocks.

Parameters

blocks a list of blocks to initialize from

Returns: the block-diagonal matrix with diagonal blocks set to the blocks passed in blocks

References gko::matrix_data< ValueType, IndexType >::diag().

◆ sum_duplicates()

template<typename ValueType = default_precision, typename IndexType = int32>

void gko::matrix_data< ValueType, IndexType >::sum_duplicates ( )

inline

Sum up all values that refer to the same matrix entry.

The result is sorted in row-major order.

References gko::matrix_data< ValueType, IndexType >::nonzeros, and gko::matrix_data< ValueType, IndexType >::sort_row_major().

Member Data Documentation

◆ nonzeros

template<typename ValueType = default_precision, typename IndexType = int32>

std::vector<nonzero_type> gko::matrix_data< ValueType, IndexType >::nonzeros

A vector of tuples storing the non-zeros of the matrix.

The first two elements of the tuple are the row index and the column index of a matrix element, and its third element is the value at that position.

Referenced by gko::matrix_data< ValueType, IndexType >::diag(), gko::matrix_data< ValueType, IndexType >::remove_zeros(), gko::matrix_data< ValueType, IndexType >::sort_row_major(), and gko::matrix_data< ValueType, IndexType >::sum_duplicates().

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

ginkgo/core/base/matrix_data.hpp

Public Types

Public Member Functions

Static Public Member Functions

Public Attributes

Detailed Description

template<typename ValueType = default_precision, typename IndexType = int32> struct gko::matrix_data< ValueType, IndexType >

Constructor & Destructor Documentation

◆ matrix_data() [1/6]

◆ matrix_data() [2/6]

◆ matrix_data() [3/6]

◆ matrix_data() [4/6]

◆ matrix_data() [5/6]

◆ matrix_data() [6/6]

Member Function Documentation

◆ cond() [1/2]

◆ cond() [2/2]

◆ diag() [1/5]

◆ diag() [2/5]

◆ diag() [3/5]

◆ diag() [4/5]

◆ diag() [5/5]

◆ sum_duplicates()

Member Data Documentation

◆ nonzeros

template<typename ValueType = default_precision, typename IndexType = int32>
struct gko::matrix_data< ValueType, IndexType >