Dense is a matrix format which explicitly stores all values of the matrix. More...

#include <ginkgo/core/matrix/dense.hpp>

Inheritance diagram for gko::matrix::Dense< ValueType >:

Collaboration diagram for gko::matrix::Dense< ValueType >:

Public Types
using	value_type = ValueType

using	index_type = int64

using	transposed_type = Dense< ValueType >

using	mat_data = matrix_data< ValueType, int64 >

using	mat_data32 = matrix_data< ValueType, int32 >

using	device_mat_data = device_matrix_data< ValueType, int64 >

using	device_mat_data32 = device_matrix_data< ValueType, int32 >

using	absolute_type = remove_complex< Dense >

using	real_type = absolute_type

using	complex_type = to_complex< Dense >

using	row_major_range = gko::range< gko::accessor::row_major< ValueType, 2 > >

Public Types inherited from gko::EnablePolymorphicAssignment< Dense< ValueType > >
using	result_type = Dense< ValueType >

Public Types inherited from gko::ConvertibleTo< Dense< ValueType > >
using	result_type = Dense< ValueType >

Public Types inherited from gko::ConvertibleTo< Dense< next_precision_with_half< ValueType > > >
using	result_type = Dense< next_precision_with_half< ValueType > >

Public Types inherited from gko::ConvertibleTo< Coo< ValueType, int32 > >
using	result_type = Coo< ValueType, int32 >

Public Types inherited from gko::ConvertibleTo< Coo< ValueType, int64 > >
using	result_type = Coo< ValueType, int64 >

Public Types inherited from gko::ConvertibleTo< Csr< ValueType, int32 > >
using	result_type = Csr< ValueType, int32 >

Public Types inherited from gko::ConvertibleTo< Csr< ValueType, int64 > >
using	result_type = Csr< ValueType, int64 >

Public Types inherited from gko::ConvertibleTo< Ell< ValueType, int32 > >
using	result_type = Ell< ValueType, int32 >

Public Types inherited from gko::ConvertibleTo< Ell< ValueType, int64 > >
using	result_type = Ell< ValueType, int64 >

Public Types inherited from gko::ConvertibleTo< Fbcsr< ValueType, int32 > >
using	result_type = Fbcsr< ValueType, int32 >

Public Types inherited from gko::ConvertibleTo< Fbcsr< ValueType, int64 > >
using	result_type = Fbcsr< ValueType, int64 >

Public Types inherited from gko::ConvertibleTo< Hybrid< ValueType, int32 > >
using	result_type = Hybrid< ValueType, int32 >

Public Types inherited from gko::ConvertibleTo< Hybrid< ValueType, int64 > >
using	result_type = Hybrid< ValueType, int64 >

Public Types inherited from gko::ConvertibleTo< Sellp< ValueType, int32 > >
using	result_type = Sellp< ValueType, int32 >

Public Types inherited from gko::ConvertibleTo< Sellp< ValueType, int64 > >
using	result_type = Sellp< ValueType, int64 >

Public Types inherited from gko::ConvertibleTo< SparsityCsr< ValueType, int32 > >
using	result_type = SparsityCsr< ValueType, int32 >

Public Types inherited from gko::ConvertibleTo< SparsityCsr< ValueType, int64 > >
using	result_type = SparsityCsr< ValueType, int64 >

Public Types inherited from gko::DiagonalExtractable< ValueType >
using	value_type = ValueType

Public Types inherited from gko::ReadableFromMatrixData< ValueType, int32 >
using	value_type = ValueType

using	index_type = int32

Public Types inherited from gko::ReadableFromMatrixData< ValueType, int64 >
using	value_type = ValueType

using	index_type = int64

Public Types inherited from gko::WritableToMatrixData< ValueType, int32 >
using	value_type = ValueType

using	index_type = int32

Public Types inherited from gko::WritableToMatrixData< ValueType, int64 >
using	value_type = ValueType

using	index_type = int64

Public Types inherited from gko::EnableAbsoluteComputation< remove_complex< Dense< ValueType > > >
using	absolute_type = remove_complex< Dense< ValueType > >

Public Member Functions
void	convert_to (Dense< next_precision_with_half< ValueType >> *result) const override

void	move_to (Dense< next_precision_with_half< ValueType >> *result) override

void	convert_to (Coo< ValueType, int32 > *result) const override

void	move_to (Coo< ValueType, int32 > *result) override

void	convert_to (Coo< ValueType, int64 > *result) const override

void	move_to (Coo< ValueType, int64 > *result) override

void	convert_to (Csr< ValueType, int32 > *result) const override

void	move_to (Csr< ValueType, int32 > *result) override

void	convert_to (Csr< ValueType, int64 > *result) const override

void	move_to (Csr< ValueType, int64 > *result) override

void	convert_to (Ell< ValueType, int32 > *result) const override

void	move_to (Ell< ValueType, int32 > *result) override

void	convert_to (Ell< ValueType, int64 > *result) const override

void	move_to (Ell< ValueType, int64 > *result) override

void	convert_to (Fbcsr< ValueType, int32 > *result) const override

void	move_to (Fbcsr< ValueType, int32 > *result) override

void	convert_to (Fbcsr< ValueType, int64 > *result) const override

void	move_to (Fbcsr< ValueType, int64 > *result) override

void	convert_to (Hybrid< ValueType, int32 > *result) const override

void	move_to (Hybrid< ValueType, int32 > *result) override

void	convert_to (Hybrid< ValueType, int64 > *result) const override

void	move_to (Hybrid< ValueType, int64 > *result) override

void	convert_to (Sellp< ValueType, int32 > *result) const override

void	move_to (Sellp< ValueType, int32 > *result) override

void	convert_to (Sellp< ValueType, int64 > *result) const override

void	move_to (Sellp< ValueType, int64 > *result) override

void	convert_to (SparsityCsr< ValueType, int32 > *result) const override

void	move_to (SparsityCsr< ValueType, int32 > *result) override

void	convert_to (SparsityCsr< ValueType, int64 > *result) const override

void	move_to (SparsityCsr< ValueType, int64 > *result) override

void	read (const mat_data &data) override

void	read (const mat_data32 &data) override

void	read (const device_mat_data &data) override

void	read (const device_mat_data32 &data) override

void	read (device_mat_data &&data) override

void	read (device_mat_data32 &&data) override

void	write (mat_data &data) const override

void	write (mat_data32 &data) const override

std::unique_ptr< LinOp >	transpose () const override
	Returns a LinOp representing the transpose of the Transposable object. More...

std::unique_ptr< LinOp >	conj_transpose () const override
	Returns a LinOp representing the conjugate transpose of the Transposable object. More...

void	transpose (ptr_param< Dense > output) const
	Writes the transposed matrix into the given output matrix. More...

void	conj_transpose (ptr_param< Dense > output) const
	Writes the conjugate-transposed matrix into the given output matrix. More...

void	fill (const ValueType value)
	Fill the dense matrix with a given value. More...

std::unique_ptr< Dense >	permute (ptr_param< const Permutation< int32 >> permutation, permute_mode mode=permute_mode::symmetric) const
	Creates a permuted copy of this matrix with the given permutation . More...

std::unique_ptr< Dense >	permute (ptr_param< const Permutation< int64 >> permutation, permute_mode mode=permute_mode::symmetric) const

void	permute (ptr_param< const Permutation< int32 >> permutation, ptr_param< Dense > output, permute_mode mode) const
	Overload of permute(ptr_param<const Permutation<int32>>, permute_mode) that writes the permuted copy into an existing Dense matrix. More...

void	permute (ptr_param< const Permutation< int64 >> permutation, ptr_param< Dense > output, permute_mode mode) const

std::unique_ptr< Dense >	permute (ptr_param< const Permutation< int32 >> row_permutation, ptr_param< const Permutation< int32 >> column_permutation, bool invert=false) const
	Creates a non-symmetrically permuted copy of this matrix with the given row and column permutations and . More...

std::unique_ptr< Dense >	permute (ptr_param< const Permutation< int64 >> row_permutation, ptr_param< const Permutation< int64 >> column_permutation, bool invert=false) const

void	permute (ptr_param< const Permutation< int32 >> row_permutation, ptr_param< const Permutation< int32 >> column_permutation, ptr_param< Dense > output, bool invert=false) const
	Overload of permute(ptr_param<const Permutation<int32>>, ptr_param<const Permutation<int32>>, permute_mode) that writes the permuted copy into an existing Dense matrix. More...

void	permute (ptr_param< const Permutation< int64 >> row_permutation, ptr_param< const Permutation< int64 >> column_permutation, ptr_param< Dense > output, bool invert=false) const

std::unique_ptr< Dense >	scale_permute (ptr_param< const ScaledPermutation< value_type, int32 >> permutation, permute_mode mode=permute_mode::symmetric) const
	Creates a scaled and permuted copy of this matrix. More...

std::unique_ptr< Dense >	scale_permute (ptr_param< const ScaledPermutation< value_type, int64 >> permutation, permute_mode mode=permute_mode::symmetric) const

void	scale_permute (ptr_param< const ScaledPermutation< value_type, int32 >> permutation, ptr_param< Dense > output, permute_mode mode) const
	Overload of scale_permute(ptr_param<const ScaledPermutation<value_type, int32>>, permute_mode) that writes the permuted copy into an existing Dense matrix. More...

void	scale_permute (ptr_param< const ScaledPermutation< value_type, int64 >> permutation, ptr_param< Dense > output, permute_mode mode) const

std::unique_ptr< Dense >	scale_permute (ptr_param< const ScaledPermutation< value_type, int32 >> row_permutation, ptr_param< const ScaledPermutation< value_type, int32 >> column_permutation, bool invert=false) const
	Creates a scaled and permuted copy of this matrix. More...

std::unique_ptr< Dense >	scale_permute (ptr_param< const ScaledPermutation< value_type, int64 >> row_permutation, ptr_param< const ScaledPermutation< value_type, int64 >> column_permutation, bool invert=false) const

void	scale_permute (ptr_param< const ScaledPermutation< value_type, int32 >> row_permutation, ptr_param< const ScaledPermutation< value_type, int32 >> column_permutation, ptr_param< Dense > output, bool invert=false) const
	Overload of scale_permute(ptr_param<const ScaledPermutation<value_type, int32>>, ptr_param<const ScaledPermutation<value_type, int32>>, bool) that writes the permuted copy into an existing Dense matrix. More...

void	scale_permute (ptr_param< const ScaledPermutation< value_type, int64 >> row_permutation, ptr_param< const ScaledPermutation< value_type, int64 >> column_permutation, ptr_param< Dense > output, bool invert=false) const

std::unique_ptr< LinOp >	permute (const array< int32 > *permutation_indices) const override
	Returns a LinOp representing the symmetric row and column permutation of the Permutable object. More...

std::unique_ptr< LinOp >	permute (const array< int64 > *permutation_indices) const override
	Returns a LinOp representing the symmetric row and column permutation of the Permutable object. More...

void	permute (const array< int32 > *permutation_indices, ptr_param< Dense > output) const
	Writes the symmetrically permuted matrix into the given output matrix. More...

void	permute (const array< int64 > *permutation_indices, ptr_param< Dense > output) const

std::unique_ptr< LinOp >	inverse_permute (const array< int32 > *permutation_indices) const override
	Returns a LinOp representing the symmetric inverse row and column permutation of the Permutable object. More...

std::unique_ptr< LinOp >	inverse_permute (const array< int64 > *permutation_indices) const override
	Returns a LinOp representing the symmetric inverse row and column permutation of the Permutable object. More...

void	inverse_permute (const array< int32 > *permutation_indices, ptr_param< Dense > output) const
	Writes the inverse symmetrically permuted matrix into the given output matrix. More...

void	inverse_permute (const array< int64 > *permutation_indices, ptr_param< Dense > output) const

std::unique_ptr< LinOp >	row_permute (const array< int32 > *permutation_indices) const override
	Returns a LinOp representing the row permutation of the Permutable object. More...

std::unique_ptr< LinOp >	row_permute (const array< int64 > *permutation_indices) const override
	Returns a LinOp representing the row permutation of the Permutable object. More...

void	row_permute (const array< int32 > *permutation_indices, ptr_param< Dense > output) const
	Writes the row-permuted matrix into the given output matrix. More...

void	row_permute (const array< int64 > *permutation_indices, ptr_param< Dense > output) const

std::unique_ptr< Dense >	row_gather (const array< int32 > *gather_indices) const
	Create a Dense matrix consisting of the given rows from this matrix. More...

std::unique_ptr< Dense >	row_gather (const array< int64 > *gather_indices) const
	Create a Dense matrix consisting of the given rows from this matrix. More...

void	row_gather (const array< int32 > *gather_indices, ptr_param< LinOp > row_collection) const
	Copies the given rows from this matrix into `row_collection` More...

void	row_gather (const array< int64 > *gather_indices, ptr_param< LinOp > row_collection) const

void	row_gather (ptr_param< const LinOp > alpha, const array< int32 > *gather_indices, ptr_param< const LinOp > beta, ptr_param< LinOp > row_collection) const
	Copies the given rows from this matrix into `row_collection` with scaling. More...

void	row_gather (ptr_param< const LinOp > alpha, const array< int64 > *gather_indices, ptr_param< const LinOp > beta, ptr_param< LinOp > row_collection) const

std::unique_ptr< LinOp >	column_permute (const array< int32 > *permutation_indices) const override
	Returns a LinOp representing the column permutation of the Permutable object. More...

std::unique_ptr< LinOp >	column_permute (const array< int64 > *permutation_indices) const override
	Returns a LinOp representing the column permutation of the Permutable object. More...

void	column_permute (const array< int32 > *permutation_indices, ptr_param< Dense > output) const
	Writes the column-permuted matrix into the given output matrix. More...

void	column_permute (const array< int64 > *permutation_indices, ptr_param< Dense > output) const

std::unique_ptr< LinOp >	inverse_row_permute (const array< int32 > *permutation_indices) const override
	Returns a LinOp representing the row permutation of the inverse permuted object. More...

std::unique_ptr< LinOp >	inverse_row_permute (const array< int64 > *permutation_indices) const override
	Returns a LinOp representing the row permutation of the inverse permuted object. More...

void	inverse_row_permute (const array< int32 > *permutation_indices, ptr_param< Dense > output) const
	Writes the inverse row-permuted matrix into the given output matrix. More...

void	inverse_row_permute (const array< int64 > *permutation_indices, ptr_param< Dense > output) const

std::unique_ptr< LinOp >	inverse_column_permute (const array< int32 > *permutation_indices) const override
	Returns a LinOp representing the row permutation of the inverse permuted object. More...

std::unique_ptr< LinOp >	inverse_column_permute (const array< int64 > *permutation_indices) const override
	Returns a LinOp representing the row permutation of the inverse permuted object. More...

void	inverse_column_permute (const array< int32 > *permutation_indices, ptr_param< Dense > output) const
	Writes the inverse column-permuted matrix into the given output matrix. More...

void	inverse_column_permute (const array< int64 > *permutation_indices, ptr_param< Dense > output) const

std::unique_ptr< Diagonal< ValueType > >	extract_diagonal () const override
	Extracts the diagonal entries of the matrix into a vector. More...

void	extract_diagonal (ptr_param< Diagonal< ValueType >> output) const
	Writes the diagonal of this matrix into an existing diagonal matrix. More...

std::unique_ptr< absolute_type >	compute_absolute () const override
	Gets the AbsoluteLinOp. More...

void	compute_absolute (ptr_param< absolute_type > output) const
	Writes the absolute values of this matrix into an existing matrix. More...

void	compute_absolute_inplace () override
	Compute absolute inplace on each element.

std::unique_ptr< complex_type >	make_complex () const
	Creates a complex copy of the original matrix. More...

void	make_complex (ptr_param< complex_type > result) const
	Writes a complex copy of the original matrix to a given complex matrix. More...

std::unique_ptr< real_type >	get_real () const
	Creates a new real matrix and extracts the real part of the original matrix into that.

void	get_real (ptr_param< real_type > result) const
	Extracts the real part of the original matrix into a given real matrix.

std::unique_ptr< real_type >	get_imag () const
	Creates a new real matrix and extracts the imaginary part of the original matrix into that.

void	get_imag (ptr_param< real_type > result) const
	Extracts the imaginary part of the original matrix into a given real matrix.

value_type *	get_values () noexcept
	Returns a pointer to the array of values of the matrix. More...

const value_type *	get_const_values () const noexcept
	Returns a pointer to the array of values of the matrix. More...

size_type	get_stride () const noexcept
	Returns the stride of the matrix. More...

size_type	get_num_stored_elements () const noexcept
	Returns the number of elements explicitly stored in the matrix. More...

value_type &	at (size_type row, size_type col) noexcept
	Returns a single element of the matrix. More...

value_type	at (size_type row, size_type col) const noexcept
	Returns a single element of the matrix. More...

ValueType &	at (size_type idx) noexcept
	Returns a single element of the matrix. More...

ValueType	at (size_type idx) const noexcept
	Returns a single element of the matrix. More...

void	scale (ptr_param< const LinOp > alpha)
	Scales the matrix with a scalar (aka: BLAS scal). More...

void	inv_scale (ptr_param< const LinOp > alpha)
	Scales the matrix with the inverse of a scalar. More...

void	add_scaled (ptr_param< const LinOp > alpha, ptr_param< const LinOp > b)
	Adds `b` scaled by `alpha` to the matrix (aka: BLAS axpy). More...

void	sub_scaled (ptr_param< const LinOp > alpha, ptr_param< const LinOp > b)
	Subtracts `b` scaled by `alpha` from the matrix (aka: BLAS axpy). More...

void	compute_dot (ptr_param< const LinOp > b, ptr_param< LinOp > result) const
	Computes the column-wise dot product of this matrix and `b`. More...

void	compute_dot (ptr_param< const LinOp > b, ptr_param< LinOp > result, array< char > &tmp) const
	Computes the column-wise dot product of this matrix and `b`. More...

void	compute_conj_dot (ptr_param< const LinOp > b, ptr_param< LinOp > result) const
	Computes the column-wise dot product of `conj(this matrix)` and `b`. More...

void	compute_conj_dot (ptr_param< const LinOp > b, ptr_param< LinOp > result, array< char > &tmp) const
	Computes the column-wise dot product of `conj(this matrix)` and `b`. More...

void	compute_norm2 (ptr_param< LinOp > result) const
	Computes the column-wise Euclidean (L^2) norm of this matrix. More...

void	compute_norm2 (ptr_param< LinOp > result, array< char > &tmp) const
	Computes the column-wise Euclidean (L^2) norm of this matrix. More...

void	compute_norm1 (ptr_param< LinOp > result) const
	Computes the column-wise (L^1) norm of this matrix. More...

void	compute_norm1 (ptr_param< LinOp > result, array< char > &tmp) const
	Computes the column-wise (L^1) norm of this matrix. More...

void	compute_squared_norm2 (ptr_param< LinOp > result) const
	Computes the square of the column-wise Euclidean (L^2) norm of this matrix. More...

void	compute_squared_norm2 (ptr_param< LinOp > result, array< char > &tmp) const
	Computes the square of the column-wise Euclidean (L^2) norm of this matrix. More...

void	compute_mean (ptr_param< LinOp > result) const
	Computes the column-wise arithmetic mean of this matrix. More...

void	compute_mean (ptr_param< LinOp > result, array< char > &tmp) const
	Computes the column-wise arithmetic mean of this matrix. More...

std::unique_ptr< Dense >	create_submatrix (const span &rows, const span &columns, const size_type stride)
	Create a submatrix from the original matrix. More...

std::unique_ptr< Dense >	create_submatrix (const span &rows, const span &columns)
	Create a submatrix from the original matrix. More...

std::unique_ptr< real_type >	create_real_view ()
	Create a real view of the (potentially) complex original matrix. More...

std::unique_ptr< const real_type >	create_real_view () const
	Create a real view of the (potentially) complex original matrix. More...

Dense &	operator= (const Dense &)
	Copy-assigns a Dense matrix. More...

Dense &	operator= (Dense &&)
	Move-assigns a Dense matrix. More...

	Dense (const Dense &)
	Copy-constructs a Dense matrix. More...

	Dense (Dense &&)
	Move-constructs a Dense matrix. More...

Public Member Functions inherited from gko::EnableLinOp< Dense< ValueType > >
const Dense< ValueType > *	apply (ptr_param< const LinOp > b, ptr_param< LinOp > x) const

Dense< ValueType > *	apply (ptr_param< const LinOp > b, ptr_param< LinOp > x)

const Dense< ValueType > *	apply (ptr_param< const LinOp > alpha, ptr_param< const LinOp > b, ptr_param< const LinOp > beta, ptr_param< LinOp > x) const

Dense< ValueType > *	apply (ptr_param< const LinOp > alpha, ptr_param< const LinOp > b, ptr_param< const LinOp > beta, ptr_param< LinOp > x)

Public Member Functions inherited from gko::EnableAbstractPolymorphicObject< Dense< ValueType >, LinOp >
std::unique_ptr< Dense< ValueType > >	create_default (std::shared_ptr< const Executor > exec) const

std::unique_ptr< Dense< ValueType > >	create_default () const

std::unique_ptr< Dense< ValueType > >	clone (std::shared_ptr< const Executor > exec) const

std::unique_ptr< Dense< ValueType > >	clone () const

Dense< ValueType > *	copy_from (const PolymorphicObject *other)

std::enable_if_t< std::is_base_of< PolymorphicObject, std::decay_t< Derived > >::value, Dense< ValueType > > *	copy_from (std::unique_ptr< Derived > &&other)

std::enable_if_t< std::is_base_of< PolymorphicObject, std::decay_t< Derived > >::value, Dense< ValueType > > *	copy_from (const std::unique_ptr< Derived > &other)

Dense< ValueType > *	copy_from (const std::shared_ptr< const PolymorphicObject > &other)

Dense< ValueType > *	move_from (ptr_param< PolymorphicObject > other)

Dense< ValueType > *	clear ()

Public Member Functions inherited from gko::LinOp
LinOp *	apply (ptr_param< const LinOp > b, ptr_param< LinOp > x)
	Applies a linear operator to a vector (or a sequence of vectors). More...

const LinOp *	apply (ptr_param< const LinOp > b, ptr_param< LinOp > x) const

LinOp *	apply (ptr_param< const LinOp > alpha, ptr_param< const LinOp > b, ptr_param< const LinOp > beta, ptr_param< LinOp > x)
	Performs the operation x = alpha * op(b) + beta * x. More...

const LinOp *	apply (ptr_param< const LinOp > alpha, ptr_param< const LinOp > b, ptr_param< const LinOp > beta, ptr_param< LinOp > x) const

const dim< 2 > &	get_size () const noexcept
	Returns the size of the operator. More...

virtual bool	apply_uses_initial_guess () const
	Returns true if the linear operator uses the data given in x as an initial guess. More...

LinOp &	operator= (const LinOp &)=default
	Copy-assigns a LinOp. More...

LinOp &	operator= (LinOp &&other)
	Move-assigns a LinOp. More...

	LinOp (const LinOp &)=default
	Copy-constructs a LinOp. More...

	LinOp (LinOp &&other)
	Move-constructs a LinOp. More...

Public Member Functions inherited from gko::EnableAbstractPolymorphicObject< LinOp >
std::unique_ptr< LinOp >	create_default (std::shared_ptr< const Executor > exec) const

std::unique_ptr< LinOp >	create_default () const

std::unique_ptr< LinOp >	clone (std::shared_ptr< const Executor > exec) const

std::unique_ptr< LinOp >	clone () const

LinOp *	copy_from (const PolymorphicObject *other)

std::enable_if_t< std::is_base_of< PolymorphicObject, std::decay_t< Derived > >::value, LinOp > *	copy_from (std::unique_ptr< Derived > &&other)

std::enable_if_t< std::is_base_of< PolymorphicObject, std::decay_t< Derived > >::value, LinOp > *	copy_from (const std::unique_ptr< Derived > &other)

LinOp *	copy_from (const std::shared_ptr< const PolymorphicObject > &other)

LinOp *	move_from (ptr_param< PolymorphicObject > other)

LinOp *	clear ()

Public Member Functions inherited from gko::PolymorphicObject
PolymorphicObject &	operator= (const PolymorphicObject &)

std::unique_ptr< PolymorphicObject >	create_default (std::shared_ptr< const Executor > exec) const
	Creates a new "default" object of the same dynamic type as this object. More...

std::unique_ptr< PolymorphicObject >	create_default () const
	Creates a new "default" object of the same dynamic type as this object. More...

std::unique_ptr< PolymorphicObject >	clone (std::shared_ptr< const Executor > exec) const
	Creates a clone of the object. More...

std::unique_ptr< PolymorphicObject >	clone () const
	Creates a clone of the object. More...

PolymorphicObject *	copy_from (const PolymorphicObject *other)
	Copies another object into this object. More...

template<typename Derived , typename Deleter >
std::enable_if_t< std::is_base_of< PolymorphicObject, std::decay_t< Derived > >::value, PolymorphicObject > *	copy_from (std::unique_ptr< Derived, Deleter > &&other)
	Moves another object into this object. More...

template<typename Derived , typename Deleter >
std::enable_if_t< std::is_base_of< PolymorphicObject, std::decay_t< Derived > >::value, PolymorphicObject > *	copy_from (const std::unique_ptr< Derived, Deleter > &other)
	Copies another object into this object. More...

PolymorphicObject *	copy_from (const std::shared_ptr< const PolymorphicObject > &other)
	Copies another object into this object. More...

PolymorphicObject *	move_from (ptr_param< PolymorphicObject > other)
	Moves another object into this object. More...

PolymorphicObject *	clear ()
	Transforms the object into its default state. More...

std::shared_ptr< const Executor >	get_executor () const noexcept
	Returns the Executor of the object. More...

Public Member Functions inherited from gko::log::EnableLogging< PolymorphicObject >
void	add_logger (std::shared_ptr< const Logger > logger) override

void	remove_logger (const Logger *logger) override

void	remove_logger (ptr_param< const Logger > logger)

const std::vector< std::shared_ptr< const Logger > > &	get_loggers () const override

void	clear_loggers () override

Public Member Functions inherited from gko::log::Loggable
void	remove_logger (ptr_param< const Logger > logger)

Public Member Functions inherited from gko::EnablePolymorphicAssignment< Dense< ValueType > >
void	convert_to (result_type *result) const override
	Converts the implementer to an object of type result_type. More...

void	move_to (result_type *result) override
	Converts the implementer to an object of type result_type by moving data from this object. More...

Public Member Functions inherited from gko::ConvertibleTo< Dense< ValueType > >
void	convert_to (ptr_param< result_type > result) const

void	move_to (ptr_param< result_type > result)

Public Member Functions inherited from gko::ConvertibleTo< Dense< next_precision_with_half< ValueType > > >
virtual void	convert_to (result_type *result) const=0
	Converts the implementer to an object of type result_type. More...

void	convert_to (ptr_param< result_type > result) const

virtual void	move_to (result_type *result)=0
	Converts the implementer to an object of type result_type by moving data from this object. More...

void	move_to (ptr_param< result_type > result)

Public Member Functions inherited from gko::ConvertibleTo< Coo< ValueType, int32 > >
virtual void	convert_to (result_type *result) const=0
	Converts the implementer to an object of type result_type. More...

void	convert_to (ptr_param< result_type > result) const

virtual void	move_to (result_type *result)=0
	Converts the implementer to an object of type result_type by moving data from this object. More...

void	move_to (ptr_param< result_type > result)

Public Member Functions inherited from gko::ConvertibleTo< Coo< ValueType, int64 > >
virtual void	convert_to (result_type *result) const=0
	Converts the implementer to an object of type result_type. More...

void	convert_to (ptr_param< result_type > result) const

virtual void	move_to (result_type *result)=0
	Converts the implementer to an object of type result_type by moving data from this object. More...

void	move_to (ptr_param< result_type > result)

Public Member Functions inherited from gko::ConvertibleTo< Csr< ValueType, int32 > >
virtual void	convert_to (result_type *result) const=0
	Converts the implementer to an object of type result_type. More...

void	convert_to (ptr_param< result_type > result) const

virtual void	move_to (result_type *result)=0
	Converts the implementer to an object of type result_type by moving data from this object. More...

void	move_to (ptr_param< result_type > result)

Public Member Functions inherited from gko::ConvertibleTo< Csr< ValueType, int64 > >
virtual void	convert_to (result_type *result) const=0
	Converts the implementer to an object of type result_type. More...

void	convert_to (ptr_param< result_type > result) const

virtual void	move_to (result_type *result)=0
	Converts the implementer to an object of type result_type by moving data from this object. More...

void	move_to (ptr_param< result_type > result)

Public Member Functions inherited from gko::ConvertibleTo< Ell< ValueType, int32 > >
virtual void	convert_to (result_type *result) const=0
	Converts the implementer to an object of type result_type. More...

void	convert_to (ptr_param< result_type > result) const

virtual void	move_to (result_type *result)=0
	Converts the implementer to an object of type result_type by moving data from this object. More...

void	move_to (ptr_param< result_type > result)

Public Member Functions inherited from gko::ConvertibleTo< Ell< ValueType, int64 > >
virtual void	convert_to (result_type *result) const=0
	Converts the implementer to an object of type result_type. More...

void	convert_to (ptr_param< result_type > result) const

virtual void	move_to (result_type *result)=0
	Converts the implementer to an object of type result_type by moving data from this object. More...

void	move_to (ptr_param< result_type > result)

Public Member Functions inherited from gko::ConvertibleTo< Fbcsr< ValueType, int32 > >
virtual void	convert_to (result_type *result) const=0
	Converts the implementer to an object of type result_type. More...

void	convert_to (ptr_param< result_type > result) const

virtual void	move_to (result_type *result)=0
	Converts the implementer to an object of type result_type by moving data from this object. More...

void	move_to (ptr_param< result_type > result)

Public Member Functions inherited from gko::ConvertibleTo< Fbcsr< ValueType, int64 > >
virtual void	convert_to (result_type *result) const=0
	Converts the implementer to an object of type result_type. More...

void	convert_to (ptr_param< result_type > result) const

virtual void	move_to (result_type *result)=0
	Converts the implementer to an object of type result_type by moving data from this object. More...

void	move_to (ptr_param< result_type > result)

Public Member Functions inherited from gko::ConvertibleTo< Hybrid< ValueType, int32 > >
virtual void	convert_to (result_type *result) const=0
	Converts the implementer to an object of type result_type. More...

void	convert_to (ptr_param< result_type > result) const

virtual void	move_to (result_type *result)=0
	Converts the implementer to an object of type result_type by moving data from this object. More...

void	move_to (ptr_param< result_type > result)

Public Member Functions inherited from gko::ConvertibleTo< Hybrid< ValueType, int64 > >
virtual void	convert_to (result_type *result) const=0
	Converts the implementer to an object of type result_type. More...

void	convert_to (ptr_param< result_type > result) const

virtual void	move_to (result_type *result)=0
	Converts the implementer to an object of type result_type by moving data from this object. More...

void	move_to (ptr_param< result_type > result)

Public Member Functions inherited from gko::ConvertibleTo< Sellp< ValueType, int32 > >
virtual void	convert_to (result_type *result) const=0
	Converts the implementer to an object of type result_type. More...

void	convert_to (ptr_param< result_type > result) const

virtual void	move_to (result_type *result)=0
	Converts the implementer to an object of type result_type by moving data from this object. More...

void	move_to (ptr_param< result_type > result)

Public Member Functions inherited from gko::ConvertibleTo< Sellp< ValueType, int64 > >
virtual void	convert_to (result_type *result) const=0
	Converts the implementer to an object of type result_type. More...

void	convert_to (ptr_param< result_type > result) const

virtual void	move_to (result_type *result)=0
	Converts the implementer to an object of type result_type by moving data from this object. More...

void	move_to (ptr_param< result_type > result)

Public Member Functions inherited from gko::ConvertibleTo< SparsityCsr< ValueType, int32 > >
virtual void	convert_to (result_type *result) const=0
	Converts the implementer to an object of type result_type. More...

void	convert_to (ptr_param< result_type > result) const

virtual void	move_to (result_type *result)=0
	Converts the implementer to an object of type result_type by moving data from this object. More...

void	move_to (ptr_param< result_type > result)

Public Member Functions inherited from gko::ConvertibleTo< SparsityCsr< ValueType, int64 > >
virtual void	convert_to (result_type *result) const=0
	Converts the implementer to an object of type result_type. More...

void	convert_to (ptr_param< result_type > result) const

virtual void	move_to (result_type *result)=0
	Converts the implementer to an object of type result_type by moving data from this object. More...

void	move_to (ptr_param< result_type > result)

Public Member Functions inherited from gko::DiagonalExtractable< ValueType >
std::unique_ptr< LinOp >	extract_diagonal_linop () const override
	Extracts the diagonal entries of the matrix into a vector. More...

Public Member Functions inherited from gko::ReadableFromMatrixData< ValueType, int32 >
virtual void	read (const matrix_data< ValueType, int32 > &data)=0
	Reads a matrix from a matrix_data structure. More...

void	read (const matrix_assembly_data< ValueType, int32 > &data)
	Reads a matrix from a matrix_assembly_data structure. More...

virtual void	read (const device_matrix_data< ValueType, int32 > &data)
	Reads a matrix from a device_matrix_data structure. More...

virtual void	read (device_matrix_data< ValueType, int32 > &&data)
	Reads a matrix from a device_matrix_data structure. More...

Public Member Functions inherited from gko::ReadableFromMatrixData< ValueType, int64 >
virtual void	read (const matrix_data< ValueType, int64 > &data)=0
	Reads a matrix from a matrix_data structure. More...

void	read (const matrix_assembly_data< ValueType, int64 > &data)
	Reads a matrix from a matrix_assembly_data structure. More...

virtual void	read (const device_matrix_data< ValueType, int64 > &data)
	Reads a matrix from a device_matrix_data structure. More...

virtual void	read (device_matrix_data< ValueType, int64 > &&data)
	Reads a matrix from a device_matrix_data structure. More...

Public Member Functions inherited from gko::WritableToMatrixData< ValueType, int32 >
virtual void	write (matrix_data< ValueType, int32 > &data) const=0
	Writes a matrix to a matrix_data structure. More...

Public Member Functions inherited from gko::WritableToMatrixData< ValueType, int64 >
virtual void	write (matrix_data< ValueType, int64 > &data) const=0
	Writes a matrix to a matrix_data structure. More...

Public Member Functions inherited from gko::EnableAbsoluteComputation< remove_complex< Dense< ValueType > > >
std::unique_ptr< LinOp >	compute_absolute_linop () const override
	Gets the absolute LinOp. More...

Public Member Functions inherited from gko::ScaledIdentityAddable
void	add_scaled_identity (ptr_param< const LinOp > const a, ptr_param< const LinOp > const b)
	Scales this and adds another scalar times the identity to it. More...

Static Public Member Functions
static std::unique_ptr< Dense >	create_with_config_of (ptr_param< const Dense > other)
	Creates a Dense matrix with the same size and stride as another Dense matrix. More...

static std::unique_ptr< Dense >	create_with_type_of (ptr_param< const Dense > other, std::shared_ptr< const Executor > exec, const dim< 2 > &size=dim< 2 >{})
	Creates a Dense matrix with the same type as another Dense matrix but on a different executor and with a different size. More...

static std::unique_ptr< Dense >	create_with_type_of (ptr_param< const Dense > other, std::shared_ptr< const Executor > exec, const dim< 2 > &size, size_type stride)

static std::unique_ptr< Dense >	create_with_type_of (ptr_param< const Dense > other, std::shared_ptr< const Executor > exec, const dim< 2 > &size, const dim< 2 > &local_size, size_type stride)

static std::unique_ptr< Dense >	create_view_of (ptr_param< Dense > other)
	Creates a Dense matrix, where the underlying array is a view of another Dense matrix' array. More...

static std::unique_ptr< const Dense >	create_const_view_of (ptr_param< const Dense > other)
	Creates a immutable Dense matrix, where the underlying array is a view of another Dense matrix' array. More...

static std::unique_ptr< Dense >	create (std::shared_ptr< const Executor > exec, const dim< 2 > &size={}, size_type stride=0)
	Creates an uninitialized Dense matrix of the specified size. More...

static std::unique_ptr< Dense >	create (std::shared_ptr< const Executor > exec, const dim< 2 > &size, array< value_type > values, size_type stride)
	Creates a Dense matrix from an already allocated (and initialized) array. More...

template<typename InputValueType >
static std::unique_ptr< Dense >	create (std::shared_ptr< const Executor > exec, const dim< 2 > &size, std::initializer_list< InputValueType > values, size_type stride)
	create(std::shared_ptr<const Executor>, More...

static std::unique_ptr< const Dense >	create_const (std::shared_ptr< const Executor > exec, const dim< 2 > &size, gko::detail::const_array_view< ValueType > &&values, size_type stride)
	Creates a constant (immutable) Dense matrix from a constant array. More...

Friends
class	EnablePolymorphicObject< Dense, LinOp >

class	Coo< ValueType, int32 >

class	Coo< ValueType, int64 >

class	Csr< ValueType, int32 >

class	Csr< ValueType, int64 >

class	Diagonal< ValueType >

class	Ell< ValueType, int32 >

class	Ell< ValueType, int64 >

class	Fbcsr< ValueType, int32 >

class	Fbcsr< ValueType, int64 >

class	Hybrid< ValueType, int32 >

class	Hybrid< ValueType, int64 >

class	Sellp< ValueType, int32 >

class	Sellp< ValueType, int64 >

class	SparsityCsr< ValueType, int32 >

class	SparsityCsr< ValueType, int64 >

class	Dense< to_complex< ValueType > >

class	experimental::distributed::Vector< ValueType >

class	Dense< previous_precision_with_half< ValueType > >

Detailed Description

template<typename ValueType = default_precision>
class gko::matrix::Dense< ValueType >

Dense is a matrix format which explicitly stores all values of the matrix.

The values are stored in row-major format (values belonging to the same row appear consecutive in the memory). Optionally, rows can be padded for better memory access.

Template Parameters

ValueType precision of matrix elements

Note: While this format is not very useful for storing sparse matrices, it is often suitable to store vectors, and sets of vectors.

Constructor & Destructor Documentation

◆ Dense() [1/2]

template<typename ValueType = default_precision>

gko::matrix::Dense< ValueType >::Dense ( const Dense< ValueType > & )

Copy-constructs a Dense matrix.

Inherits executor and dimensions, but copies data without padding.

◆ Dense() [2/2]

template<typename ValueType = default_precision>

gko::matrix::Dense< ValueType >::Dense ( Dense< ValueType > && )

Move-constructs a Dense matrix.

Inherits executor, dimensions and data with padding. The moved-from object is empty (0x0 with empty Array).

Member Function Documentation

◆ add_scaled()

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::add_scaled	(	ptr_param< const LinOp >	alpha,
		ptr_param< const LinOp >	b
	)

Adds b scaled by alpha to the matrix (aka: BLAS axpy).

Parameters

alpha	If alpha is 1x1 Dense matrix, the entire matrix is scaled by alpha. If it is a Dense row vector of values, then i-th column of the matrix is scaled with the i-th element of alpha (the number of columns of alpha has to match the number of columns of the matrix).
b	a matrix of the same dimension as this

◆ at() [1/4]

template<typename ValueType = default_precision>

ValueType gko::matrix::Dense< ValueType >::at ( size_type idx ) const

inlinenoexcept

Returns a single element of the matrix.

Useful for iterating across all elements of the matrix. However, it is less efficient than the two-parameter variant of this method.

Parameters

idx	a linear index of the requested element (ignoring the stride)

Note: the method has to be called on the same Executor the matrix is stored at (e.g. trying to call this method on a GPU matrix from the OMP results in a runtime error)

◆ at() [2/4]

template<typename ValueType = default_precision>

ValueType& gko::matrix::Dense< ValueType >::at ( size_type idx )

inlinenoexcept

Returns a single element of the matrix.

Useful for iterating across all elements of the matrix. However, it is less efficient than the two-parameter variant of this method.

Parameters

idx	a linear index of the requested element (ignoring the stride)

Note: the method has to be called on the same Executor the matrix is stored at (e.g. trying to call this method on a GPU matrix from the OMP results in a runtime error)

◆ at() [3/4]

template<typename ValueType = default_precision>

value_type gko::matrix::Dense< ValueType >::at	(	size_type	row,
		size_type	col
	)		const

inlinenoexcept

Returns a single element of the matrix.

Parameters

row	the row of the requested element
col	the column of the requested element

Note: the method has to be called on the same Executor the matrix is stored at (e.g. trying to call this method on a GPU matrix from the OMP results in a runtime error)

◆ at() [4/4]

template<typename ValueType = default_precision>

value_type& gko::matrix::Dense< ValueType >::at	(	size_type	row,
		size_type	col
	)

inlinenoexcept

Returns a single element of the matrix.

Parameters

row	the row of the requested element
col	the column of the requested element

Note: the method has to be called on the same Executor the matrix is stored at (e.g. trying to call this method on a GPU matrix from the OMP results in a runtime error)

Referenced by gko::initialize().

◆ column_permute() [1/4]

template<typename ValueType = default_precision>

std::unique_ptr<LinOp> gko::matrix::Dense< ValueType >::column_permute ( const array< int32 > * permutation_indices ) const

overridevirtual

Returns a LinOp representing the column permutation of the Permutable object.

In the resulting LinOp, the column i contains the input column perm[i].

From the linear algebra perspective, with $P_{ij} = \delta_{i \pi(i)}$ , this represents the operation $A P^T$ .

Parameters

permutation_indices the array of indices containing the permutation order perm.

Returns: a pointer to the new column permuted object

Implements gko::Permutable< int32 >.

◆ column_permute() [2/4]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::column_permute	(	const array< int32 > *	permutation_indices,
		ptr_param< Dense< ValueType > >	output
	)		const

Writes the column-permuted matrix into the given output matrix.

Parameters

permutation_indices	The array containing permutation indices. It must have `this->get_size()[1]` elements.
output	The output matrix. It must have the dimensions `this->get_size()`

See also: Dense::column_permute(const array<int32>*)

◆ column_permute() [3/4]

template<typename ValueType = default_precision>

std::unique_ptr<LinOp> gko::matrix::Dense< ValueType >::column_permute ( const array< int64 > * permutation_indices ) const

overridevirtual

Returns a LinOp representing the column permutation of the Permutable object.

In the resulting LinOp, the column i contains the input column perm[i].

From the linear algebra perspective, with $P_{ij} = \delta_{i \pi(i)}$ , this represents the operation $A P^T$ .

Parameters

permutation_indices the array of indices containing the permutation order perm.

Returns: a pointer to the new column permuted object

Implements gko::Permutable< int64 >.

◆ column_permute() [4/4]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::column_permute	(	const array< int64 > *	permutation_indices,
		ptr_param< Dense< ValueType > >	output
	)		const

◆ compute_absolute() [1/2]

template<typename ValueType = default_precision>

std::unique_ptr<absolute_type> gko::matrix::Dense< ValueType >::compute_absolute ( ) const

overridevirtual

Gets the AbsoluteLinOp.

Returns: a pointer to the new absolute object

Implements gko::EnableAbsoluteComputation< remove_complex< Dense< ValueType > > >.

◆ compute_absolute() [2/2]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::compute_absolute ( ptr_param< absolute_type > output ) const

Writes the absolute values of this matrix into an existing matrix.

Parameters

output The output matrix. Its size must match the size of this matrix.

See also: Dense::compute_absolute()

◆ compute_conj_dot() [1/2]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::compute_conj_dot	(	ptr_param< const LinOp >	b,
		ptr_param< LinOp >	result
	)		const

Computes the column-wise dot product of conj(this matrix) and b.

Parameters

b	a Dense matrix of same dimension as this
result	a Dense row vector, used to store the dot product (the number of column in the vector must match the number of columns of this)

◆ compute_conj_dot() [2/2]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::compute_conj_dot	(	ptr_param< const LinOp >	b,
		ptr_param< LinOp >	result,
		array< char > &	tmp
	)		const

Computes the column-wise dot product of conj(this matrix) and b.

Parameters

b	a Dense matrix of same dimension as this
result	a Dense row vector, used to store the dot product (the number of column in the vector must match the number of columns of this)
tmp	the temporary storage to use for partial sums during the reduction computation. It may be resized and/or reset to the correct executor.

◆ compute_dot() [1/2]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::compute_dot	(	ptr_param< const LinOp >	b,
		ptr_param< LinOp >	result
	)		const

Computes the column-wise dot product of this matrix and b.

Parameters

b	a Dense matrix of same dimension as this
result	a Dense row vector, used to store the dot product (the number of column in the vector must match the number of columns of this)

◆ compute_dot() [2/2]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::compute_dot	(	ptr_param< const LinOp >	b,
		ptr_param< LinOp >	result,
		array< char > &	tmp
	)		const

Computes the column-wise dot product of this matrix and b.

Parameters

b	a Dense matrix of same dimension as this
result	a Dense row vector, used to store the dot product (the number of column in the vector must match the number of columns of this)
tmp	the temporary storage to use for partial sums during the reduction computation. It may be resized and/or reset to the correct executor.

◆ compute_mean() [1/2]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::compute_mean ( ptr_param< LinOp > result ) const

Computes the column-wise arithmetic mean of this matrix.

Parameters

result a Dense row vector, used to store the mean (the number of columns in the vector must match the number of columns of this)

◆ compute_mean() [2/2]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::compute_mean	(	ptr_param< LinOp >	result,
		array< char > &	tmp
	)		const

Computes the column-wise arithmetic mean of this matrix.

Parameters

result	a Dense row vector, used to store the mean (the number of columns in the vector must match the number of columns of this)
tmp	the temporary storage to use for partial sums during the reduction computation. It may be resized and/or reset to the correct executor.

◆ compute_norm1() [1/2]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::compute_norm1 ( ptr_param< LinOp > result ) const

Computes the column-wise (L^1) norm of this matrix.

Parameters

result a Dense row vector, used to store the norm (the number of columns in the vector must match the number of columns of this)

◆ compute_norm1() [2/2]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::compute_norm1	(	ptr_param< LinOp >	result,
		array< char > &	tmp
	)		const

Computes the column-wise (L^1) norm of this matrix.

Parameters

result	a Dense row vector, used to store the norm (the number of columns in the vector must match the number of columns of this)
tmp	the temporary storage to use for partial sums during the reduction computation. It may be resized and/or reset to the correct executor.

◆ compute_norm2() [1/2]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::compute_norm2 ( ptr_param< LinOp > result ) const

Computes the column-wise Euclidean (L^2) norm of this matrix.

Parameters

result a Dense row vector, used to store the norm (the number of columns in the vector must match the number of columns of this)

◆ compute_norm2() [2/2]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::compute_norm2	(	ptr_param< LinOp >	result,
		array< char > &	tmp
	)		const

Computes the column-wise Euclidean (L^2) norm of this matrix.

Parameters

result	a Dense row vector, used to store the norm (the number of columns in the vector must match the number of columns of this)
tmp	the temporary storage to use for partial sums during the reduction computation. It may be resized and/or reset to the correct executor.

◆ compute_squared_norm2() [1/2]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::compute_squared_norm2 ( ptr_param< LinOp > result ) const

Computes the square of the column-wise Euclidean (L^2) norm of this matrix.

Parameters

result a Dense row vector, used to store the norm (the number of columns in the vector must match the number of columns of this)

◆ compute_squared_norm2() [2/2]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::compute_squared_norm2	(	ptr_param< LinOp >	result,
		array< char > &	tmp
	)		const

Computes the square of the column-wise Euclidean (L^2) norm of this matrix.

Parameters

result	a Dense row vector, used to store the norm (the number of columns in the vector must match the number of columns of this)
tmp	the temporary storage to use for partial sums during the reduction computation. It may be resized and/or reset to the correct executor.

◆ conj_transpose() [1/2]

template<typename ValueType = default_precision>

std::unique_ptr<LinOp> gko::matrix::Dense< ValueType >::conj_transpose ( ) const

overridevirtual

Returns a LinOp representing the conjugate transpose of the Transposable object.

Returns: a pointer to the new conjugate transposed object

Implements gko::Transposable.

◆ conj_transpose() [2/2]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::conj_transpose ( ptr_param< Dense< ValueType > > output ) const

Writes the conjugate-transposed matrix into the given output matrix.

Parameters

output The output matrix. It must have the dimensions gko::transpose(this->get_size())

◆ create() [1/3]

template<typename ValueType = default_precision>

static std::unique_ptr<Dense> gko::matrix::Dense< ValueType >::create	(	std::shared_ptr< const Executor >	exec,
		const dim< 2 > &	size,
		array< value_type >	values,
		size_type	stride
	)

static

Creates a Dense matrix from an already allocated (and initialized) array.

Parameters

exec	Executor associated to the matrix
size	size of the matrix
values	array of matrix values
stride	stride of the rows (i.e. offset between the first elements of two consecutive rows, expressed as the number of matrix elements)

Note: If values is not an rvalue, not an array of ValueType, or is on the wrong executor, an internal copy will be created, and the original array data will not be used in the matrix.

Returns: A smart pointer to the newly created matrix.

◆ create() [2/3]

template<typename ValueType = default_precision>

template<typename InputValueType >

static std::unique_ptr<Dense> gko::matrix::Dense< ValueType >::create	(	std::shared_ptr< const Executor >	exec,
		const dim< 2 > &	size,
		std::initializer_list< InputValueType >	values,
		size_type	stride
	)

inlinestatic

create(std::shared_ptr<const Executor>,

create(std::shared_ptr<const Executor>, const dim<2>&, array<value_type>, size_type)

◆ create() [3/3]

template<typename ValueType = default_precision>

static std::unique_ptr<Dense> gko::matrix::Dense< ValueType >::create	(	std::shared_ptr< const Executor >	exec,
		const dim< 2 > &	size = `{}`,
		size_type	stride = `0`
	)

static

Creates an uninitialized Dense matrix of the specified size.

Parameters

exec	Executor associated to the matrix
size	size of the matrix
stride	stride of the rows (i.e. offset between the first elements of two consecutive rows, expressed as the number of matrix elements). If it is set to 0, size[1] will be used instead.

Returns: A smart pointer to the newly created matrix.

Referenced by gko::matrix::Dense< value_type >::create().

◆ create_const()

template<typename ValueType = default_precision>

static std::unique_ptr<const Dense> gko::matrix::Dense< ValueType >::create_const	(	std::shared_ptr< const Executor >	exec,
		const dim< 2 > &	size,
		gko::detail::const_array_view< ValueType > &&	values,
		size_type	stride
	)

static

Creates a constant (immutable) Dense matrix from a constant array.

Parameters

exec	the executor to create the matrix on
size	the dimensions of the matrix
values	the value array of the matrix
stride	the row-stride of the matrix

Returns: A smart pointer to the constant matrix wrapping the input array (if it resides on the same executor as the matrix) or a copy of the array on the correct executor.

◆ create_const_view_of()

template<typename ValueType = default_precision>

static std::unique_ptr<const Dense> gko::matrix::Dense< ValueType >::create_const_view_of ( ptr_param< const Dense< ValueType > > other )

inlinestatic

Creates a immutable Dense matrix, where the underlying array is a view of another Dense matrix' array.

Parameters

other The other matrix on which to create the view

Returns: A immutable Dense matrix that is a view of other

Referenced by gko::make_const_dense_view().

◆ create_real_view() [1/2]

template<typename ValueType = default_precision>

std::unique_ptr<real_type> gko::matrix::Dense< ValueType >::create_real_view ( )

Create a real view of the (potentially) complex original matrix.

If the original matrix is real, nothing changes. If the original matrix is complex, the result is created by viewing the complex matrix with as real with a reinterpret_cast with twice the number of columns and double the stride.

◆ create_real_view() [2/2]

template<typename ValueType = default_precision>

std::unique_ptr<const real_type> gko::matrix::Dense< ValueType >::create_real_view ( ) const

Create a real view of the (potentially) complex original matrix.

If the original matrix is real, nothing changes. If the original matrix is complex, the result is created by viewing the complex matrix with as real with a reinterpret_cast with twice the number of columns and double the stride.

◆ create_submatrix() [1/2]

template<typename ValueType = default_precision>

std::unique_ptr<Dense> gko::matrix::Dense< ValueType >::create_submatrix	(	const span &	rows,
		const span &	columns
	)

inline

Create a submatrix from the original matrix.

Parameters

rows	row span
columns	column span

◆ create_submatrix() [2/2]

template<typename ValueType = default_precision>

std::unique_ptr<Dense> gko::matrix::Dense< ValueType >::create_submatrix	(	const span &	rows,
		const span &	columns,
		const size_type	stride
	)

inline

Create a submatrix from the original matrix.

Warning: defining stride for this create_submatrix method might cause wrong memory access. Better use the create_submatrix(rows, columns) method instead.

Parameters

rows	row span
columns	column span
stride	stride of the new submatrix.

Referenced by gko::matrix::Dense< value_type >::create_submatrix().

◆ create_view_of()

template<typename ValueType = default_precision>

static std::unique_ptr<Dense> gko::matrix::Dense< ValueType >::create_view_of ( ptr_param< Dense< ValueType > > other )

inlinestatic

Creates a Dense matrix, where the underlying array is a view of another Dense matrix' array.

Parameters

other The other matrix on which to create the view

Returns: A Dense matrix that is a view of other

Referenced by gko::make_dense_view().

◆ create_with_config_of()

template<typename ValueType = default_precision>

static std::unique_ptr<Dense> gko::matrix::Dense< ValueType >::create_with_config_of ( ptr_param< const Dense< ValueType > > other )

inlinestatic

Creates a Dense matrix with the same size and stride as another Dense matrix.

Parameters

other The other matrix whose configuration needs to copied.

◆ create_with_type_of() [1/3]

template<typename ValueType = default_precision>

static std::unique_ptr<Dense> gko::matrix::Dense< ValueType >::create_with_type_of	(	ptr_param< const Dense< ValueType > >	other,
		std::shared_ptr< const Executor >	exec,
		const dim< 2 > &	size,
		const dim< 2 > &	local_size,
		size_type	stride
	)

inlinestatic

Parameters

local_size	Unused
stride	The stride of the new matrix.

Note: This is an overload to stay consistent with gko::experimental::distributed::Vector

◆ create_with_type_of() [2/3]

template<typename ValueType = default_precision>

static std::unique_ptr<Dense> gko::matrix::Dense< ValueType >::create_with_type_of	(	ptr_param< const Dense< ValueType > >	other,
		std::shared_ptr< const Executor >	exec,
		const dim< 2 > &	size,
		size_type	stride
	)

inlinestatic

Parameters

stride The stride of the new matrix.

Note: This is an overload which allows full parameter specification.

◆ create_with_type_of() [3/3]

template<typename ValueType = default_precision>

static std::unique_ptr<Dense> gko::matrix::Dense< ValueType >::create_with_type_of	(	ptr_param< const Dense< ValueType > >	other,
		std::shared_ptr< const Executor >	exec,
		const dim< 2 > &	size = `dim<2>{}`
	)

inlinestatic

Creates a Dense matrix with the same type as another Dense matrix but on a different executor and with a different size.

Parameters

other	The other matrix whose type we target.
exec	The executor of the new matrix.
size	The size of the new matrix.
stride	The stride of the new matrix.

Returns: a Dense matrix with the type of other.

◆ extract_diagonal() [1/2]

template<typename ValueType = default_precision>

std::unique_ptr<Diagonal<ValueType> > gko::matrix::Dense< ValueType >::extract_diagonal ( ) const

overridevirtual

Extracts the diagonal entries of the matrix into a vector.

Parameters

diag	the vector into which the diagonal will be written

Implements gko::DiagonalExtractable< ValueType >.

◆ extract_diagonal() [2/2]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::extract_diagonal ( ptr_param< Diagonal< ValueType >> output ) const

Writes the diagonal of this matrix into an existing diagonal matrix.

Parameters

output The output matrix. Its size must match the size of this matrix's diagonal.

See also: Dense::extract_diagonal()

◆ fill()

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::fill ( const ValueType value )

Fill the dense matrix with a given value.

Parameters

value the value to be filled

◆ get_const_values()

template<typename ValueType = default_precision>

const value_type* gko::matrix::Dense< ValueType >::get_const_values ( ) const

inlinenoexcept

Returns a pointer to the array of values of the matrix.

Returns: the pointer to the array of values

Note: This is the constant version of the function, which can be significantly more memory efficient than the non-constant version, so always prefer this version.

◆ get_num_stored_elements()

template<typename ValueType = default_precision>

size_type gko::matrix::Dense< ValueType >::get_num_stored_elements ( ) const

inlinenoexcept

Returns the number of elements explicitly stored in the matrix.

Returns: the number of elements explicitly stored in the matrix

◆ get_stride()

template<typename ValueType = default_precision>

size_type gko::matrix::Dense< ValueType >::get_stride ( ) const

inlinenoexcept

Returns the stride of the matrix.

Returns: the stride of the matrix.

Referenced by gko::matrix::Dense< value_type >::create_submatrix().

◆ get_values()

template<typename ValueType = default_precision>

value_type* gko::matrix::Dense< ValueType >::get_values ( )

inlinenoexcept

Returns a pointer to the array of values of the matrix.

Returns: the pointer to the array of values

◆ inv_scale()

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::inv_scale ( ptr_param< const LinOp > alpha )

Scales the matrix with the inverse of a scalar.

Parameters

alpha If alpha is 1x1 Dense matrix, the entire matrix is scaled by 1 / alpha. If it is a Dense row vector of values, then i-th column of the matrix is scaled with the inverse of the i-th element of alpha (the number of columns of alpha has to match the number of columns of the matrix).

◆ inverse_column_permute() [1/4]

template<typename ValueType = default_precision>

std::unique_ptr<LinOp> gko::matrix::Dense< ValueType >::inverse_column_permute ( const array< int32 > * permutation_indices ) const

overridevirtual

Returns a LinOp representing the row permutation of the inverse permuted object.

In the resulting LinOp, the column perm[i] contains the input column i.

From the linear algebra perspective, with $P_{ij} = \delta_{i \pi(i)}$ , this represents the operation $A P^{-T}$ .

Parameters

permutation_indices the array of indices containing the permutation order perm.

Returns: a pointer to the new inverse permuted object

Implements gko::Permutable< int32 >.

◆ inverse_column_permute() [2/4]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::inverse_column_permute	(	const array< int32 > *	permutation_indices,
		ptr_param< Dense< ValueType > >	output
	)		const

Writes the inverse column-permuted matrix into the given output matrix.

Parameters

permutation_indices	The array containing permutation indices. It must have `this->get_size()[1]` elements.
output	The output matrix. It must have the dimensions `this->get_size()`

See also: Dense::inverse_column_permute(const array<int32>*)

◆ inverse_column_permute() [3/4]

template<typename ValueType = default_precision>

std::unique_ptr<LinOp> gko::matrix::Dense< ValueType >::inverse_column_permute ( const array< int64 > * permutation_indices ) const

overridevirtual

Returns a LinOp representing the row permutation of the inverse permuted object.

In the resulting LinOp, the column perm[i] contains the input column i.

From the linear algebra perspective, with $P_{ij} = \delta_{i \pi(i)}$ , this represents the operation $A P^{-T}$ .

Parameters

permutation_indices the array of indices containing the permutation order perm.

Returns: a pointer to the new inverse permuted object

Implements gko::Permutable< int64 >.

◆ inverse_column_permute() [4/4]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::inverse_column_permute	(	const array< int64 > *	permutation_indices,
		ptr_param< Dense< ValueType > >	output
	)		const

◆ inverse_permute() [1/4]

template<typename ValueType = default_precision>

std::unique_ptr<LinOp> gko::matrix::Dense< ValueType >::inverse_permute ( const array< int32 > * permutation_indices ) const

overridevirtual

Returns a LinOp representing the symmetric inverse row and column permutation of the Permutable object.

In the resulting LinOp, the entry at location (perm[i],perm[j]) contains the input value (i,j).

From the linear algebra perspective, with $P_{ij} = \delta_{i \pi(i)}$ , this represents the operation $P^{-1} A P^{-T}$ .

Parameters

permutation_indices the array of indices containing the permutation order.

Returns: a pointer to the new permuted object

Reimplemented from gko::Permutable< int32 >.

◆ inverse_permute() [2/4]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::inverse_permute	(	const array< int32 > *	permutation_indices,
		ptr_param< Dense< ValueType > >	output
	)		const

Writes the inverse symmetrically permuted matrix into the given output matrix.

Parameters

permutation_indices	The array containing permutation indices. It must have `this->get_size()[0]` elements.
output	The output matrix. It must have the dimensions `this->get_size()`

See also: Dense::inverse_permute(const array<int32>*)

◆ inverse_permute() [3/4]

template<typename ValueType = default_precision>

std::unique_ptr<LinOp> gko::matrix::Dense< ValueType >::inverse_permute ( const array< int64 > * permutation_indices ) const

overridevirtual

Returns a LinOp representing the symmetric inverse row and column permutation of the Permutable object.

In the resulting LinOp, the entry at location (perm[i],perm[j]) contains the input value (i,j).

From the linear algebra perspective, with $P_{ij} = \delta_{i \pi(i)}$ , this represents the operation $P^{-1} A P^{-T}$ .

Parameters

permutation_indices the array of indices containing the permutation order.

Returns: a pointer to the new permuted object

Reimplemented from gko::Permutable< int64 >.

◆ inverse_permute() [4/4]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::inverse_permute	(	const array< int64 > *	permutation_indices,
		ptr_param< Dense< ValueType > >	output
	)		const

◆ inverse_row_permute() [1/4]

template<typename ValueType = default_precision>

std::unique_ptr<LinOp> gko::matrix::Dense< ValueType >::inverse_row_permute ( const array< int32 > * permutation_indices ) const

overridevirtual

Returns a LinOp representing the row permutation of the inverse permuted object.

In the resulting LinOp, the row perm[i] contains the input row i.

From the linear algebra perspective, with $P_{ij} = \delta_{i \pi(i)}$ , this represents the operation $P^{-1} A$ .

Parameters

permutation_indices the array of indices containing the permutation order perm.

Returns: a pointer to the new inverse permuted object

Implements gko::Permutable< int32 >.

◆ inverse_row_permute() [2/4]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::inverse_row_permute	(	const array< int32 > *	permutation_indices,
		ptr_param< Dense< ValueType > >	output
	)		const

Writes the inverse row-permuted matrix into the given output matrix.

Parameters

permutation_indices	The array containing permutation indices. It must have `this->get_size()[0]` elements.
output	The output matrix. It must have the dimensions `this->get_size()`

See also: Dense::inverse_row_permute(const array<int32>*)

◆ inverse_row_permute() [3/4]

template<typename ValueType = default_precision>

std::unique_ptr<LinOp> gko::matrix::Dense< ValueType >::inverse_row_permute ( const array< int64 > * permutation_indices ) const

overridevirtual

Returns a LinOp representing the row permutation of the inverse permuted object.

In the resulting LinOp, the row perm[i] contains the input row i.

From the linear algebra perspective, with $P_{ij} = \delta_{i \pi(i)}$ , this represents the operation $P^{-1} A$ .

Parameters

permutation_indices the array of indices containing the permutation order perm.

Returns: a pointer to the new inverse permuted object

Implements gko::Permutable< int64 >.

◆ inverse_row_permute() [4/4]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::inverse_row_permute	(	const array< int64 > *	permutation_indices,
		ptr_param< Dense< ValueType > >	output
	)		const

◆ make_complex() [1/2]

template<typename ValueType = default_precision>

std::unique_ptr<complex_type> gko::matrix::Dense< ValueType >::make_complex ( ) const

Creates a complex copy of the original matrix.

If the original matrix was real, the imaginary part of the result will be zero.

◆ make_complex() [2/2]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::make_complex ( ptr_param< complex_type > result ) const

Writes a complex copy of the original matrix to a given complex matrix.

If the original matrix was real, the imaginary part of the result will be zero.

◆ operator=() [1/2]

template<typename ValueType = default_precision>

Dense& gko::matrix::Dense< ValueType >::operator= ( const Dense< ValueType > & )

Copy-assigns a Dense matrix.

Preserves the executor, reallocates the matrix with minimal stride if the dimensions don't match, then copies the data over, ignoring padding.

◆ operator=() [2/2]

template<typename ValueType = default_precision>

Dense& gko::matrix::Dense< ValueType >::operator= ( Dense< ValueType > && )

Move-assigns a Dense matrix.

Preserves the executor, moves the data over preserving size and stride. Leaves the moved-from object in an empty state (0x0 with empty Array).

◆ permute() [1/12]

template<typename ValueType = default_precision>

std::unique_ptr<LinOp> gko::matrix::Dense< ValueType >::permute ( const array< int32 > * permutation_indices ) const

overridevirtual

Returns a LinOp representing the symmetric row and column permutation of the Permutable object.

In the resulting LinOp, the entry at location (i,j) contains the input value (perm[i],perm[j]).

From the linear algebra perspective, with $P_{ij} = \delta_{i \pi(i)}$ , this represents the operation $P A P^T$ .

Parameters

permutation_indices the array of indices containing the permutation order.

Returns: a pointer to the new permuted object

Reimplemented from gko::Permutable< int32 >.

◆ permute() [2/12]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::permute	(	const array< int32 > *	permutation_indices,
		ptr_param< Dense< ValueType > >	output
	)		const

Writes the symmetrically permuted matrix into the given output matrix.

Parameters

permutation_indices	The array containing permutation indices. It must have `this->get_size()[0]` elements.
output	The output matrix. It must have the dimensions `this->get_size()`

See also: Dense::permute(const array<int32>*)

◆ permute() [3/12]

template<typename ValueType = default_precision>

std::unique_ptr<LinOp> gko::matrix::Dense< ValueType >::permute ( const array< int64 > * permutation_indices ) const

overridevirtual

Returns a LinOp representing the symmetric row and column permutation of the Permutable object.

In the resulting LinOp, the entry at location (i,j) contains the input value (perm[i],perm[j]).

From the linear algebra perspective, with $P_{ij} = \delta_{i \pi(i)}$ , this represents the operation $P A P^T$ .

Parameters

permutation_indices the array of indices containing the permutation order.

Returns: a pointer to the new permuted object

Reimplemented from gko::Permutable< int64 >.

◆ permute() [4/12]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::permute	(	const array< int64 > *	permutation_indices,
		ptr_param< Dense< ValueType > >	output
	)		const

◆ permute() [5/12]

template<typename ValueType = default_precision>

std::unique_ptr<Dense> gko::matrix::Dense< ValueType >::permute	(	ptr_param< const Permutation< int32 >>	permutation,
		permute_mode	mode = `permute_mode::symmetric`
	)		const

Creates a permuted copy $A'$ of this matrix $A$ with the given permutation $P$ .

By default, this computes a symmetric permutation (permute_mode::symmetric). For the effect of the different permutation modes, see permute_mode.

Parameters

permutation	The input permutation.
mode	The permutation mode. If permute_mode::inverse is set, we use the inverse permutation $P^{-1}$ instead of . If permute_mode::rows is set, the rows will be permuted. If permute_mode::columns is set, the columns will be permuted.

Returns: The permuted matrix.

◆ permute() [6/12]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::permute	(	ptr_param< const Permutation< int32 >>	permutation,
		ptr_param< Dense< ValueType > >	output,
		permute_mode	mode
	)		const

Overload of permute(ptr_param<const Permutation<int32>>, permute_mode) that writes the permuted copy into an existing Dense matrix.

Parameters

output the output matrix.

◆ permute() [7/12]

template<typename ValueType = default_precision>

std::unique_ptr<Dense> gko::matrix::Dense< ValueType >::permute	(	ptr_param< const Permutation< int32 >>	row_permutation,
		ptr_param< const Permutation< int32 >>	column_permutation,
		bool	invert = `false`
	)		const

Creates a non-symmetrically permuted copy $A'$ of this matrix $A$ with the given row and column permutations $P$ and $Q$ .

The operation will compute $A'(i, j) = A(p[i], q[j])$ , or $A' = P A Q^T$ if invert is false, and $A'(p[i], q[j]) = A(i,j)$ , or $A' = P^{-1} A Q^{-T}$ if invert is true.

Parameters

row_permutation	The permutation to apply to the rows
column_permutation	The permutation to apply to the columns
invert	If set to `false`, uses the input permutations, otherwise uses their inverses $P^{-1}, Q^{-1}$

Returns: The permuted matrix.

◆ permute() [8/12]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::permute	(	ptr_param< const Permutation< int32 >>	row_permutation,
		ptr_param< const Permutation< int32 >>	column_permutation,
		ptr_param< Dense< ValueType > >	output,
		bool	invert = `false`
	)		const

Overload of permute(ptr_param<const Permutation<int32>>, ptr_param<const Permutation<int32>>, permute_mode) that writes the permuted copy into an existing Dense matrix.

Parameters

output the output matrix.

◆ permute() [9/12]

template<typename ValueType = default_precision>

std::unique_ptr<Dense> gko::matrix::Dense< ValueType >::permute	(	ptr_param< const Permutation< int64 >>	permutation,
		permute_mode	mode = `permute_mode::symmetric`
	)		const

◆ permute() [10/12]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::permute	(	ptr_param< const Permutation< int64 >>	permutation,
		ptr_param< Dense< ValueType > >	output,
		permute_mode	mode
	)		const

◆ permute() [11/12]

template<typename ValueType = default_precision>

std::unique_ptr<Dense> gko::matrix::Dense< ValueType >::permute	(	ptr_param< const Permutation< int64 >>	row_permutation,
		ptr_param< const Permutation< int64 >>	column_permutation,
		bool	invert = `false`
	)		const

◆ permute() [12/12]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::permute	(	ptr_param< const Permutation< int64 >>	row_permutation,
		ptr_param< const Permutation< int64 >>	column_permutation,
		ptr_param< Dense< ValueType > >	output,
		bool	invert = `false`
	)		const

◆ row_gather() [1/6]

template<typename ValueType = default_precision>

std::unique_ptr<Dense> gko::matrix::Dense< ValueType >::row_gather ( const array< int32 > * gather_indices ) const

Create a Dense matrix consisting of the given rows from this matrix.

Parameters

gather_indices pointer to an array containing row indices from this matrix. It may contain duplicates.

Returns: Dense matrix on the same executor with the same number of columns and gather_indices->get_size() rows containing the gathered rows from this matrix: output(i,j) = input(gather_indices(i), j)

◆ row_gather() [2/6]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::row_gather	(	const array< int32 > *	gather_indices,
		ptr_param< LinOp >	row_collection
	)		const

Copies the given rows from this matrix into row_collection

Parameters

gather_indices	pointer to an array containing row indices from this matrix. It may contain duplicates.
row_collection	pointer to a LinOp that will store the gathered rows: `row_collection(i,j) = input(gather_indices(i), j)` It must have the same number of columns as this matrix and `gather_indices->get_size()` rows.

◆ row_gather() [3/6]

template<typename ValueType = default_precision>

std::unique_ptr<Dense> gko::matrix::Dense< ValueType >::row_gather ( const array< int64 > * gather_indices ) const

Create a Dense matrix consisting of the given rows from this matrix.

Parameters

gather_indices pointer to an array containing row indices from this matrix. It may contain duplicates.

Returns: Dense matrix on the same executor with the same number of columns and gather_indices->get_size() rows containing the gathered rows from this matrix: output(i,j) = input(gather_indices(i), j)

◆ row_gather() [4/6]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::row_gather	(	const array< int64 > *	gather_indices,
		ptr_param< LinOp >	row_collection
	)		const

◆ row_gather() [5/6]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::row_gather	(	ptr_param< const LinOp >	alpha,
		const array< int32 > *	gather_indices,
		ptr_param< const LinOp >	beta,
		ptr_param< LinOp >	row_collection
	)		const

Copies the given rows from this matrix into row_collection with scaling.

Parameters

alpha	scaling the result of row gathering
gather_indices	pointer to an array containing row indices from this matrix. It may contain duplicates.
beta	scaling the input row_collection
row_collection	pointer to a LinOp that will store the gathered rows: `row_collection(i,j) = input(gather_indices(i), j)` It must have the same number of columns as this matrix and `gather_indices->get_size()` rows.

◆ row_gather() [6/6]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::row_gather	(	ptr_param< const LinOp >	alpha,
		const array< int64 > *	gather_indices,
		ptr_param< const LinOp >	beta,
		ptr_param< LinOp >	row_collection
	)		const

◆ row_permute() [1/4]

template<typename ValueType = default_precision>

std::unique_ptr<LinOp> gko::matrix::Dense< ValueType >::row_permute ( const array< int32 > * permutation_indices ) const

overridevirtual

Returns a LinOp representing the row permutation of the Permutable object.

In the resulting LinOp, the row i contains the input row perm[i].

From the linear algebra perspective, with $P_{ij} = \delta_{i \pi(i)}$ , this represents the operation $P A$ .

Parameters

permutation_indices the array of indices containing the permutation order.

Returns: a pointer to the new permuted object

Implements gko::Permutable< int32 >.

◆ row_permute() [2/4]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::row_permute	(	const array< int32 > *	permutation_indices,
		ptr_param< Dense< ValueType > >	output
	)		const

Writes the row-permuted matrix into the given output matrix.

Parameters

permutation_indices	The array containing permutation indices. It must have `this->get_size()[0]` elements.
output	The output matrix. It must have the dimensions `this->get_size()`

See also: Dense::row_permute(const array<int32>*)

◆ row_permute() [3/4]

template<typename ValueType = default_precision>

std::unique_ptr<LinOp> gko::matrix::Dense< ValueType >::row_permute ( const array< int64 > * permutation_indices ) const

overridevirtual

Returns a LinOp representing the row permutation of the Permutable object.

In the resulting LinOp, the row i contains the input row perm[i].

From the linear algebra perspective, with $P_{ij} = \delta_{i \pi(i)}$ , this represents the operation $P A$ .

Parameters

permutation_indices the array of indices containing the permutation order.

Returns: a pointer to the new permuted object

Implements gko::Permutable< int64 >.

◆ row_permute() [4/4]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::row_permute	(	const array< int64 > *	permutation_indices,
		ptr_param< Dense< ValueType > >	output
	)		const

◆ scale()

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::scale ( ptr_param< const LinOp > alpha )

Scales the matrix with a scalar (aka: BLAS scal).

Parameters

alpha If alpha is 1x1 Dense matrix, the entire matrix is scaled by alpha. If it is a Dense row vector of values, then i-th column of the matrix is scaled with the i-th element of alpha (the number of columns of alpha has to match the number of columns of the matrix).

◆ scale_permute() [1/8]

template<typename ValueType = default_precision>

std::unique_ptr<Dense> gko::matrix::Dense< ValueType >::scale_permute	(	ptr_param< const ScaledPermutation< value_type, int32 >>	permutation,
		permute_mode	mode = `permute_mode::symmetric`
	)		const

Creates a scaled and permuted copy of this matrix.

For an explanation of the permutation modes, see permute(ptr_param<const Permutation<index_type>>, permute_mode)

Parameters

permutation	The scaled permutation.
mode	The permutation mode.

Returns: The permuted matrix.

◆ scale_permute() [2/8]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::scale_permute	(	ptr_param< const ScaledPermutation< value_type, int32 >>	permutation,
		ptr_param< Dense< ValueType > >	output,
		permute_mode	mode
	)		const

Overload of scale_permute(ptr_param<const ScaledPermutation<value_type, int32>>, permute_mode) that writes the permuted copy into an existing Dense matrix.

Parameters

output the output matrix.

◆ scale_permute() [3/8]

template<typename ValueType = default_precision>

std::unique_ptr<Dense> gko::matrix::Dense< ValueType >::scale_permute	(	ptr_param< const ScaledPermutation< value_type, int32 >>	row_permutation,
		ptr_param< const ScaledPermutation< value_type, int32 >>	column_permutation,
		bool	invert = `false`
	)		const

Creates a scaled and permuted copy of this matrix.

For an explanation of the parameters, see permute(ptr_param<const Permutation<index_type>>, ptr_param<const Permutation<index_type>>, permute_mode)

Parameters

row_permutation	The scaled row permutation.
column_permutation	The scaled column permutation.
invert	If set to `false`, uses the input permutations, otherwise uses their inverses $P^{-1}, Q^{-1}$

Returns: The permuted matrix.

◆ scale_permute() [4/8]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::scale_permute	(	ptr_param< const ScaledPermutation< value_type, int32 >>	row_permutation,
		ptr_param< const ScaledPermutation< value_type, int32 >>	column_permutation,
		ptr_param< Dense< ValueType > >	output,
		bool	invert = `false`
	)		const

Overload of scale_permute(ptr_param<const ScaledPermutation<value_type, int32>>, ptr_param<const ScaledPermutation<value_type, int32>>, bool) that writes the permuted copy into an existing Dense matrix.

Parameters

output the output matrix.

◆ scale_permute() [5/8]

template<typename ValueType = default_precision>

std::unique_ptr<Dense> gko::matrix::Dense< ValueType >::scale_permute	(	ptr_param< const ScaledPermutation< value_type, int64 >>	permutation,
		permute_mode	mode = `permute_mode::symmetric`
	)		const

◆ scale_permute() [6/8]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::scale_permute	(	ptr_param< const ScaledPermutation< value_type, int64 >>	permutation,
		ptr_param< Dense< ValueType > >	output,
		permute_mode	mode
	)		const

◆ scale_permute() [7/8]

template<typename ValueType = default_precision>

std::unique_ptr<Dense> gko::matrix::Dense< ValueType >::scale_permute	(	ptr_param< const ScaledPermutation< value_type, int64 >>	row_permutation,
		ptr_param< const ScaledPermutation< value_type, int64 >>	column_permutation,
		bool	invert = `false`
	)		const

◆ scale_permute() [8/8]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::scale_permute	(	ptr_param< const ScaledPermutation< value_type, int64 >>	row_permutation,
		ptr_param< const ScaledPermutation< value_type, int64 >>	column_permutation,
		ptr_param< Dense< ValueType > >	output,
		bool	invert = `false`
	)		const

◆ sub_scaled()

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::sub_scaled	(	ptr_param< const LinOp >	alpha,
		ptr_param< const LinOp >	b
	)

Subtracts b scaled by alpha from the matrix (aka: BLAS axpy).

Parameters

alpha	If alpha is 1x1 Dense matrix, b is scaled by alpha. If it is a Dense row vector of values, then i-th column of b is scaled with the i-th element of alpha (the number of columns of alpha has to match the number of columns of the matrix).
b	a matrix of the same dimension as this

◆ transpose() [1/2]

template<typename ValueType = default_precision>

std::unique_ptr<LinOp> gko::matrix::Dense< ValueType >::transpose ( ) const

overridevirtual

Returns a LinOp representing the transpose of the Transposable object.

Returns: a pointer to the new transposed object

Implements gko::Transposable.

◆ transpose() [2/2]

template<typename ValueType = default_precision>

void gko::matrix::Dense< ValueType >::transpose ( ptr_param< Dense< ValueType > > output ) const

Writes the transposed matrix into the given output matrix.

Parameters

output The output matrix. It must have the dimensions gko::transpose(this->get_size())

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

ginkgo/core/base/dense_cache.hpp
ginkgo/core/matrix/dense.hpp

Public Types

Public Member Functions

Static Public Member Functions

Friends

Detailed Description

template<typename ValueType = default_precision> class gko::matrix::Dense< ValueType >

Constructor & Destructor Documentation

◆ Dense() [1/2]

◆ Dense() [2/2]

Member Function Documentation

◆ add_scaled()

◆ at() [1/4]

◆ at() [2/4]

◆ at() [3/4]

◆ at() [4/4]

◆ column_permute() [1/4]

◆ column_permute() [2/4]

◆ column_permute() [3/4]

◆ column_permute() [4/4]

◆ compute_absolute() [1/2]

◆ compute_absolute() [2/2]

◆ compute_conj_dot() [1/2]

◆ compute_conj_dot() [2/2]

◆ compute_dot() [1/2]

◆ compute_dot() [2/2]

◆ compute_mean() [1/2]

◆ compute_mean() [2/2]

◆ compute_norm1() [1/2]

◆ compute_norm1() [2/2]

◆ compute_norm2() [1/2]

◆ compute_norm2() [2/2]

◆ compute_squared_norm2() [1/2]

◆ compute_squared_norm2() [2/2]

◆ conj_transpose() [1/2]

◆ conj_transpose() [2/2]

◆ create() [1/3]

◆ create() [2/3]

◆ create() [3/3]

◆ create_const()

◆ create_const_view_of()

◆ create_real_view() [1/2]

◆ create_real_view() [2/2]

◆ create_submatrix() [1/2]

◆ create_submatrix() [2/2]

◆ create_view_of()

◆ create_with_config_of()

◆ create_with_type_of() [1/3]

◆ create_with_type_of() [2/3]

◆ create_with_type_of() [3/3]

◆ extract_diagonal() [1/2]

◆ extract_diagonal() [2/2]

◆ fill()

◆ get_const_values()

◆ get_num_stored_elements()

◆ get_stride()

◆ get_values()

◆ inv_scale()

◆ inverse_column_permute() [1/4]

◆ inverse_column_permute() [2/4]

◆ inverse_column_permute() [3/4]

◆ inverse_column_permute() [4/4]

◆ inverse_permute() [1/4]

◆ inverse_permute() [2/4]

◆ inverse_permute() [3/4]

◆ inverse_permute() [4/4]

◆ inverse_row_permute() [1/4]

◆ inverse_row_permute() [2/4]

◆ inverse_row_permute() [3/4]

◆ inverse_row_permute() [4/4]

◆ make_complex() [1/2]

◆ make_complex() [2/2]

◆ operator=() [1/2]

◆ operator=() [2/2]

◆ permute() [1/12]

◆ permute() [2/12]

◆ permute() [3/12]

◆ permute() [4/12]

◆ permute() [5/12]

◆ permute() [6/12]

◆ permute() [7/12]

template<typename ValueType = default_precision>
class gko::matrix::Dense< ValueType >