TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator > Class Template Reference

Implementation of dense matrix, i.e. matrix storing explicitly all of its elements including zeros. More...

#include <TNL/Matrices/DenseMatrix.h>

Inheritance diagram for TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >:

Collaboration diagram for TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >:

Public Types
using	ConstViewType = typename DenseMatrixView< Real, Device, Index, Organization >::ConstViewType
	Matrix view type for constant instances.
using	RealAllocatorType = RealAllocator
	The allocator for matrix elements.
template<typename _Real = Real, typename _Device = Device, typename _Index = Index, ElementsOrganization _Organization = Algorithms::Segments::DefaultElementsOrganization< _Device >::getOrganization(), typename _RealAllocator = typename Allocators::Default< _Device >::template Allocator< _Real >>
using	Self = DenseMatrix< _Real, _Device, _Index, _Organization, _RealAllocator >
	Helper type for getting self type or its modifications.
using	ValuesVectorType = Containers::Vector< Real, Device, Index, RealAllocator >
	Type of vector holding values of matrix elements.
using	ViewType = DenseMatrixView< Real, Device, Index, Organization >
	Type of related matrix view.
Public Types inherited from TNL::Matrices::DenseMatrixBase< double, Devices::Host, int, Algorithms::Segments::DefaultElementsOrganization< Devices::Host >::getOrganization() >
using	ConstRowView
	Type for accessing immutable matrix row.
using	DeviceType
	The device where the matrix is allocated.
using	IndexType
	The type used for matrix elements indexing.
using	RealType
	The type of matrix elements.
using	RowView
	Type for accessing matrix row.
Public Types inherited from TNL::Matrices::MatrixBase< double, Devices::Host, int, GeneralMatrix, Organization >
using	ConstValuesViewType
	Type of constant vector view holding values of matrix elements.
using	DeviceType
	The device where the matrix is allocated.
using	IndexType
	The type used for matrix elements indexing.
using	RealType
	The type of matrix elements.
using	RowCapacitiesType
using	ValuesViewType
	Type of vector view holding values of matrix elements.

Public Member Functions
	DenseMatrix (const DenseMatrix &matrix)
	Copy constructor.
	DenseMatrix (const RealAllocatorType &allocator=RealAllocatorType())
	Constructor only with values allocator.
	DenseMatrix (DenseMatrix &&matrix) noexcept=default
	Move constructor.
	DenseMatrix (Index rows, Index columns, const RealAllocatorType &allocator=RealAllocatorType())
	Constructor with matrix dimensions.
template<typename Value >
	DenseMatrix (std::initializer_list< std::initializer_list< Value > > data, const RealAllocatorType &allocator=RealAllocatorType())
	Constructor with 2D initializer list.
ConstViewType	getConstView () const
	Returns a non-modifiable view of the dense matrix.
template<int tileDim = 16>
void	getInPlaceTransposition (Real matrixMultiplicator=1.0)
	Performs an in-place transposition of this matrix.
template<typename Matrix1 , typename Matrix2 , int tileDim = 16>
void	getMatrixProduct (const Matrix1 &matrix1, const Matrix2 &matrix2, Real matrixMultiplicator=1.0, TransposeState transposeA=TransposeState::None, TransposeState transposeB=TransposeState::None)
	Computes the product of two matrices and stores the result in this matrix.
template<typename Matrix , int tileDim = 16>
void	getTransposition (const Matrix &matrix, Real matrixMultiplicator=1.0)
	Computes the transposition of a given matrix and stores the result in this matrix.
ViewType	getView ()
	Returns a modifiable view of the dense matrix.
void	load (const String &fileName)
	Method for loading the matrix from the file with given filename.
void	load (File &file) override
	Method for loading the matrix from a file.
DenseMatrix &	operator= (const DenseMatrix &matrix)
	Copy-assignment of exactly the same matrix type.
template<typename Real , typename Device , typename Index , ElementsOrganization Organization, typename RealAllocator >
DenseMatrix< Real, Device, Index, Organization, RealAllocator > &	operator= (const DenseMatrix< Real, Device, Index, Organization, RealAllocator > &matrix)
template<typename RHSReal , typename RHSDevice , typename RHSIndex , typename RHSRealAllocator >
DenseMatrix &	operator= (const DenseMatrix< RHSReal, RHSDevice, RHSIndex, Organization, RHSRealAllocator > &matrix)
	Assignment operator with the same organization.
template<typename RHSReal , typename RHSDevice , typename RHSIndex , typename RHSRealAllocator >
DenseMatrix< Real, Device, Index, Organization, RealAllocator > &	operator= (const DenseMatrix< RHSReal, RHSDevice, RHSIndex, Organization, RHSRealAllocator > &matrix)
template<typename RHSReal , typename RHSDevice , typename RHSIndex , ElementsOrganization RHSOrganization, typename RHSRealAllocator >
DenseMatrix &	operator= (const DenseMatrix< RHSReal, RHSDevice, RHSIndex, RHSOrganization, RHSRealAllocator > &matrix)
	Assignment operator with other dense matrices.
template<typename RHSReal , typename RHSDevice , typename RHSIndex , ElementsOrganization RHSOrganization, typename RHSRealAllocator >
DenseMatrix< Real, Device, Index, Organization, RealAllocator > &	operator= (const DenseMatrix< RHSReal, RHSDevice, RHSIndex, RHSOrganization, RHSRealAllocator > &matrix)
template<typename RHSReal , typename RHSDevice , typename RHSIndex >
DenseMatrix &	operator= (const DenseMatrixView< RHSReal, RHSDevice, RHSIndex, Organization > &matrix)
	Assignment operator with matrix view having the same elements organization.
template<typename RHSReal , typename RHSDevice , typename RHSIndex >
DenseMatrix< Real, Device, Index, Organization, RealAllocator > &	operator= (const DenseMatrixView< RHSReal, RHSDevice, RHSIndex, Organization > &matrix)
template<typename RHSReal , typename RHSDevice , typename RHSIndex , ElementsOrganization RHSOrganization>
DenseMatrix &	operator= (const DenseMatrixView< RHSReal, RHSDevice, RHSIndex, RHSOrganization > &matrix)
	Assignment operator with other dense matrices.
template<typename RHSReal , typename RHSDevice , typename RHSIndex , ElementsOrganization RHSOrganization>
DenseMatrix< Real, Device, Index, Organization, RealAllocator > &	operator= (const DenseMatrixView< RHSReal, RHSDevice, RHSIndex, RHSOrganization > &matrix)
template<typename RHSMatrix >
DenseMatrix &	operator= (const RHSMatrix &matrix)
	Assignment operator with other (sparse) types of matrices.
template<typename RHSMatrix >
DenseMatrix< Real, Device, Index, Organization, RealAllocator > &	operator= (const RHSMatrix &matrix)
DenseMatrix &	operator= (DenseMatrix &&matrix) noexcept(false)
	Move-assignment of exactly the same matrix type.
template<typename Real , typename Device , typename Index , ElementsOrganization Organization, typename RealAllocator >
DenseMatrix< Real, Device, Index, Organization, RealAllocator > &	operator= (DenseMatrix< Real, Device, Index, Organization, RealAllocator > &&matrix) noexcept(false)
void	reset ()
	Resets the matrix to zero dimensions.
void	save (const String &fileName) const
	Method for saving the matrix to the file with given filename.
void	save (File &file) const override
	Method for saving the matrix to a file.
void	setDimensions (Index rows, Index columns)
	Set number of rows and columns of this matrix.
template<typename MapIndex , typename MapValue >
void	setElements (const std::map< std::pair< MapIndex, MapIndex >, MapValue > &map)
	This method sets the dense matrix elements from std::map.
template<typename Value >
void	setElements (std::initializer_list< std::initializer_list< Value > > data)
	This method recreates the dense matrix from 2D initializer list.
template<typename Matrix >
void	setLike (const Matrix &matrix)
	Set the number of matrix rows and columns by the given matrix.
template<typename Matrix_ >
void	setLike (const Matrix_ &matrix)
template<typename RowCapacitiesVector >
void	setRowCapacities (const RowCapacitiesVector &rowCapacities)
	This method is only for the compatibility with the sparse matrices.
Public Member Functions inherited from TNL::Object
virtual	~Object ()=default
	Destructor.
virtual std::string	getSerializationTypeVirtual () const
void	load (const String &fileName)
	Method for restoring the object from a file.
void	save (const String &fileName) const
	Method for saving the object to a file as a binary data.
Public Member Functions inherited from TNL::Matrices::DenseMatrixBase< double, Devices::Host, int, Algorithms::Segments::DefaultElementsOrganization< Devices::Host >::getOrganization() >
__cuda_callable__	DenseMatrixBase ()=default
	Constructor without parameters.
__cuda_callable__	DenseMatrixBase (const DenseMatrixBase &matrix)=default
	Copy constructor.
__cuda_callable__	DenseMatrixBase (DenseMatrixBase &&matrix) noexcept=default
	Move constructor.
__cuda_callable__	DenseMatrixBase (IndexType rows, IndexType columns, typename Base::ValuesViewType values)
	Constructor with matrix dimensions and values.
__cuda_callable__ void	addElement (IndexType row, IndexType column, const RealType &value, const RealType &thisElementMultiplicator=1.0)
	Add element at given row and column to given value.
void	addMatrix (const Matrix &matrix, const RealType &matrixMultiplicator=1.0, const RealType &thisMatrixMultiplicator=1.0, TransposeState transpose=TransposeState::None)
	Computes matrix addition.
void	forAllElements (Function &&function)
	This method calls forElements for all matrix rows.
void	forAllElements (Function &&function) const
	This method calls forElements for all matrix rows.
void	forAllRows (Function &&function)
	Method for parallel iteration over all matrix rows.
void	forAllRows (Function &&function) const
	Method for parallel iteration over all matrix rows for constant instances.
void	forElements (IndexType begin, IndexType end, Function &&function)
	Method for iteration over all matrix rows for non-constant instances.
void	forElements (IndexType begin, IndexType end, Function &&function) const
	Method for iteration over all matrix rows for constant instances.
void	forRows (IndexType begin, IndexType end, Function &&function)
	Method for parallel iteration over matrix rows from interval [begin, end).
void	forRows (IndexType begin, IndexType end, Function &&function) const
	Method for parallel iteration over matrix rows from interval [begin, end) for constant instances.
void	getCompressedRowLengths (Vector &rowLengths) const
	Computes number of non-zeros in each row.
__cuda_callable__ double	getElement (IndexType row, IndexType column) const
	Returns value of matrix element at position given by its row and column index.
__cuda_callable__ RowView	getRow (IndexType rowIdx)
	Non-constant getter of simple structure for accessing given matrix row.
__cuda_callable__ ConstRowView	getRow (IndexType rowIdx) const
	Constant getter of simple structure for accessing given matrix row.
void	getRowCapacities (Vector &rowCapacities) const
	Compute capacities of all rows.
__cuda_callable__ IndexType	getRowCapacity (IndexType row) const
	Returns capacity of given matrix row.
bool	operator!= (const DenseMatrixBase< Real_, Device_, Index_, Organization > &matrix) const
	Comparison operator with another dense matrix view.
__cuda_callable__ double &	operator() (IndexType row, IndexType column)
	Returns non-constant reference to element at row row and column column.
__cuda_callable__ const double &	operator() (IndexType row, IndexType column) const
	Returns constant reference to element at row row and column column.
DenseMatrixBase &	operator= (const DenseMatrixBase &)=delete
	Copy-assignment operator.
DenseMatrixBase &	operator= (DenseMatrixBase &&)=delete
	Move-assignment operator.
bool	operator== (const DenseMatrixBase< Real_, Device_, Index_, Organization > &matrix) const
	Comparison operator with another dense matrix view.
void	print (std::ostream &str) const
	Method for printing the matrix to output stream.
void	reduceAllRows (Fetch &&fetch, const Reduce &reduce, Keep &&keep, const FetchReal &identity) const
	Method for performing general reduction on ALL matrix rows for constant instances.
void	reduceRows (IndexType begin, IndexType end, Fetch &&fetch, const Reduce &reduce, Keep &&keep, const FetchReal &identity) const
	Method for performing general reduction on matrix rows for constant instances.
void	reduceRows (IndexType begin, IndexType end, Fetch &&fetch, const Reduce &reduce, Keep &&keep, const FetchValue &identity) const
void	sequentialForAllRows (Function &&function)
	This method calls sequentialForRows for all matrix rows.
void	sequentialForAllRows (Function &&function) const
	This method calls sequentialForRows for all matrix rows (for constant instances).
void	sequentialForRows (IndexType begin, IndexType end, Function &&function)
	Method for sequential iteration over all matrix rows for non-constant instances.
void	sequentialForRows (IndexType begin, IndexType end, Function &&function) const
	Method for sequential iteration over all matrix rows for constant instances.
__cuda_callable__ void	setElement (IndexType row, IndexType column, const RealType &value)
	Sets element at given row and column to given value.
void	setValue (const RealType &v)
	Sets all matrix elements to value v.
void	vectorProduct (const InVector &inVector, OutVector &outVector, const RealType &matrixMultiplicator=1.0, const RealType &outVectorMultiplicator=0.0, IndexType begin=0, IndexType end=0) const
	Computes product of matrix and vector.
Public Member Functions inherited from TNL::Matrices::MatrixBase< double, Devices::Host, int, GeneralMatrix, Organization >
__cuda_callable__	MatrixBase ()=default
	Basic constructor with no parameters.
__cuda_callable__	MatrixBase (const MatrixBase &view)=default
	Shallow copy constructor.
__cuda_callable__	MatrixBase (IndexType rows, IndexType columns, ValuesViewType values)
	Constructor with matrix dimensions and matrix elements values.
__cuda_callable__	MatrixBase (MatrixBase &&view) noexcept=default
	Move constructor.
IndexType	getAllocatedElementsCount () const
	Tells the number of allocated matrix elements.
__cuda_callable__ IndexType	getColumns () const
	Returns number of matrix columns.
virtual IndexType	getNonzeroElementsCount () const
	Computes a current number of nonzero matrix elements.
__cuda_callable__ IndexType	getRows () const
	Returns number of matrix rows.
__cuda_callable__ ValuesViewType &	getValues ()
	Returns a reference to a vector with the matrix elements values.
__cuda_callable__ const ValuesViewType &	getValues () const
	Returns a constant reference to a vector with the matrix elements values.
bool	operator!= (const Matrix &matrix) const
	Comparison operator with another arbitrary matrix view type.
bool	operator!= (const MatrixT &matrix) const
__cuda_callable__ MatrixBase &	operator= (const MatrixBase &)=delete
	Copy-assignment operator.
__cuda_callable__ MatrixBase &	operator= (MatrixBase &&)=delete
	Move-assignment operator.
bool	operator== (const Matrix &matrix) const
	Comparison operator with another arbitrary matrix view type.
bool	operator== (const MatrixT &matrix) const

Static Public Member Functions
static std::string	getSerializationType ()
	Returns string with serialization type.
Static Public Member Functions inherited from TNL::Object
static std::string	getSerializationType ()
	Static serialization type getter.
Static Public Member Functions inherited from TNL::Matrices::DenseMatrixBase< double, Devices::Host, int, Algorithms::Segments::DefaultElementsOrganization< Devices::Host >::getOrganization() >
static std::string	getSerializationType ()
	Returns string with serialization type.
Static Public Member Functions inherited from TNL::Matrices::MatrixBase< double, Devices::Host, int, GeneralMatrix, Organization >
static constexpr ElementsOrganization	getOrganization ()
	Matrix elements organization getter.
static constexpr bool	isBinary ()
	Test of binary matrix type.
static constexpr bool	isSymmetric ()
	Test of symmetric matrix type.

Protected Attributes
Base::SegmentsType	segments
	Instance of the segments used for indexing in the dense matrix.
ValuesVectorType	values
	Vector containing the allocated matrix elements.
Protected Attributes inherited from TNL::Matrices::DenseMatrixBase< double, Devices::Host, int, Algorithms::Segments::DefaultElementsOrganization< Devices::Host >::getOrganization() >
SegmentsViewType	segments
Protected Attributes inherited from TNL::Matrices::MatrixBase< double, Devices::Host, int, GeneralMatrix, Organization >
IndexType	columns
IndexType	rows
ValuesViewType	values

Additional Inherited Members
Protected Types inherited from TNL::Matrices::DenseMatrixBase< double, Devices::Host, int, Algorithms::Segments::DefaultElementsOrganization< Devices::Host >::getOrganization() >
using	Base
using	SegmentsReductionKernel
using	SegmentsType
using	SegmentsViewType
using	SegmentViewType
Protected Member Functions inherited from TNL::Matrices::DenseMatrixBase< double, Devices::Host, int, Algorithms::Segments::DefaultElementsOrganization< Devices::Host >::getOrganization() >
__cuda_callable__ void	bind (IndexType rows, IndexType columns, typename Base::ValuesViewType values, SegmentsViewType segments)
	Re-initializes the internal attributes of the base class.
__cuda_callable__ IndexType	getElementIndex (IndexType row, IndexType column) const
Protected Member Functions inherited from TNL::Matrices::MatrixBase< double, Devices::Host, int, GeneralMatrix, Organization >
__cuda_callable__ void	bind (IndexType rows, IndexType columns, ValuesViewType values)
	Re-initializes the internal attributes of the base class.

Detailed Description

template<typename Real = double, typename Device = Devices::Host, typename Index = int, ElementsOrganization Organization = Algorithms::Segments::DefaultElementsOrganization< Device >::getOrganization(), typename RealAllocator = typename Allocators::Default< Device >::template Allocator< Real >>
class TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >

Implementation of dense matrix, i.e. matrix storing explicitly all of its elements including zeros.

Template Parameters

Real	is a type of matrix elements.
Device	is a device where the matrix is allocated.
Index	is a type for indexing of the matrix elements.
Organization	tells the ordering of matrix elements. It is either RowMajorOrder or ColumnMajorOrder.
RealAllocator	is allocator for the matrix elements.

Member Typedef Documentation

ConstViewType

template<typename Real = double, typename Device = Devices::Host, typename Index = int, ElementsOrganization Organization = Algorithms::Segments::DefaultElementsOrganization< Device >::getOrganization(), typename RealAllocator = typename Allocators::Default< Device >::template Allocator< Real >>

using TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >::ConstViewType = typename DenseMatrixView< Real, Device, Index, Organization >::ConstViewType

Matrix view type for constant instances.

See DenseMatrixView.

ViewType

template<typename Real = double, typename Device = Devices::Host, typename Index = int, ElementsOrganization Organization = Algorithms::Segments::DefaultElementsOrganization< Device >::getOrganization(), typename RealAllocator = typename Allocators::Default< Device >::template Allocator< Real >>

using TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >::ViewType = DenseMatrixView< Real, Device, Index, Organization >

Type of related matrix view.

See DenseMatrixView.

Constructor & Destructor Documentation

DenseMatrix() [1/5]

template<typename Real , typename Device , typename Index , ElementsOrganization Organization, typename RealAllocator >

TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >::DenseMatrix

(

const RealAllocatorType &

allocator = RealAllocatorType()

)

Constructor only with values allocator.

Parameters

allocator

is used for allocation of matrix elements values.

DenseMatrix() [2/5]

template<typename Real , typename Device , typename Index , ElementsOrganization Organization, typename RealAllocator >

TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >::DenseMatrix

(

const DenseMatrix< Real, Device, Index, Organization, RealAllocator > &

matrix

)

Copy constructor.

Parameters

matrix

is the source matrix

DenseMatrix() [3/5]

template<typename Real = double, typename Device = Devices::Host, typename Index = int, ElementsOrganization Organization = Algorithms::Segments::DefaultElementsOrganization< Device >::getOrganization(), typename RealAllocator = typename Allocators::Default< Device >::template Allocator< Real >>

TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >::DenseMatrix ( DenseMatrix< Real, Device, Index, Organization, RealAllocator > && matrix )

defaultnoexcept

Move constructor.

Parameters

matrix

is the source matrix

DenseMatrix() [4/5]

template<typename Real , typename Device , typename Index , ElementsOrganization Organization, typename RealAllocator >

TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >::DenseMatrix	(	Index	rows,
		Index	columns,
		const RealAllocatorType &	allocator = RealAllocatorType() )

Constructor with matrix dimensions.

Parameters

rows	is number of matrix rows.
columns	is number of matrix columns.
allocator	is used for allocation of matrix elements values.

DenseMatrix() [5/5]

template<typename Real , typename Device , typename Index , ElementsOrganization Organization, typename RealAllocator >

template<typename Value >

TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >::DenseMatrix	(	std::initializer_list< std::initializer_list< Value > >	data,
		const RealAllocatorType &	allocator = RealAllocatorType() )

Constructor with 2D initializer list.

The number of matrix rows is set to the outer list size and the number of matrix columns is set to maximum size of inner lists. Missing elements are filled in with zeros.

Parameters

data	is a initializer list of initializer lists representing list of matrix rows.
allocator	is used for allocation of matrix elements values.

Example

#include <iostream>
#include <TNL/Matrices/DenseMatrix.h>
#include <TNL/Devices/Host.h>
 
template< typename Device >
void
initializerListExample()
{
   TNL::Matrices::DenseMatrix< double, Device > matrix{
      // clang-format off
      {  1,  2,  3,  4,  5,  6 },
      {  7,  8,  9, 10, 11, 12 },
      { 13, 14, 15, 16, 17, 18 }
      // clang-format on
   };
 
   std::cout << "General dense matrix: " << std::endl << matrix << std::endl;
 
   TNL::Matrices::DenseMatrix< double, Device > triangularMatrix{
      // clang-format off
      {  1 },
      {  2,  3 },
      {  4,  5,  6 },
      {  7,  8,  9, 10 },
      { 11, 12, 13, 14, 15 }
      // clang-format on
   };
 
   std::cout << "Triangular dense matrix: " << std::endl << triangularMatrix << std::endl;
}
 
int
main( int argc, char* argv[] )
{
   std::cout << "Creating matrices on CPU ... " << std::endl;
   initializerListExample< TNL::Devices::Host >();
 
#ifdef __CUDACC__
   std::cout << "Creating matrices on CUDA GPU ... " << std::endl;
   initializerListExample< TNL::Devices::Cuda >();
#endif
}

Output

Creating matrices on CPU ... 
General dense matrix: 
Row: 0 ->     0:1       1:2       2:3       3:4       4:5       5:6   
Row: 1 ->     0:7       1:8       2:9       3:10      4:11      5:12  
Row: 2 ->     0:13      1:14      2:15      3:16      4:17      5:18  
Triangular dense matrix: 
Row: 0 ->     0:1       1:0       2:0       3:0       4:0   
Row: 1 ->     0:2       1:3       2:0       3:0       4:0   
Row: 2 ->     0:4       1:5       2:6       3:0       4:0   
Row: 3 ->     0:7       1:8       2:9       3:10      4:0   
Row: 4 ->     0:11      1:12      2:13      3:14      4:15  
Creating matrices on CUDA GPU ... 
General dense matrix: 
Row: 0 ->     0:1       1:2       2:3       3:4       4:5       5:6   
Row: 1 ->     0:7       1:8       2:9       3:10      4:11      5:12  
Row: 2 ->     0:13      1:14      2:15      3:16      4:17      5:18  
Triangular dense matrix: 
Row: 0 ->     0:1       1:0       2:0       3:0       4:0   
Row: 1 ->     0:2       1:3       2:0       3:0       4:0   
Row: 2 ->     0:4       1:5       2:6       3:0       4:0   
Row: 3 ->     0:7       1:8       2:9       3:10      4:0   
Row: 4 ->     0:11      1:12      2:13      3:14      4:15  

Member Function Documentation

getConstView()

template<typename Real , typename Device , typename Index , ElementsOrganization Organization, typename RealAllocator >

auto TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >::getConstView ( ) const

nodiscard

Returns a non-modifiable view of the dense matrix.

See DenseMatrixView.

Returns

dense matrix view.

getInPlaceTransposition()

template<typename Real , typename Device , typename Index , ElementsOrganization Organization, typename RealAllocator >

template<int tileDim>

void TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >::getInPlaceTransposition

(

Real

matrixMultiplicator = 1.0

)

Performs an in-place transposition of this matrix.

This method transposes this matrix in place, modifying the original matrix. The operation can optionally scale the matrix by a specified factor.

Template Parameters

tileDim

Tile dimension for GPU computation optimization. Default is 16.

Parameters

matrixMultiplicator

A scalar value by which the matrix is scaled during the transposition. Default is 1.0.

Example

#include <iostream>
#include <TNL/Matrices/DenseMatrix.h>
#include <TNL/Devices/Host.h>
 
template< typename Device >
void
getInPlaceTranspositionExample()
{
   // clang-format off
   TNL::Matrices::DenseMatrix< double, Device > matrix{
      { 1, 2, 3, 4 },
      { 6, 7, 8, 9 },
      { 10, 11, 12, 13 },
      { 14, 15, 16, 17 }
   };
   // clang-format on
 
   std::cout << "Dense matrix: " << std::endl << matrix << std::endl;
 
   matrix.getInPlaceTransposition();
 
   std::cout << "Transposed dense matrix: " << std::endl << matrix << std::endl;
}
 
int
main( int argc, char* argv[] )
{
   std::cout << "Creating matrix on CPU ... " << std::endl;
   getInPlaceTranspositionExample< TNL::Devices::Host >();
 
#ifdef __CUDACC__
   std::cout << "Creating matrix on CUDA GPU ... " << std::endl;
   getInPlaceTranspositionExample< TNL::Devices::Cuda >();
#endif
}

Output

Creating matrix on CPU ... 
Dense matrix: 
Row: 0 ->     0:1       1:2       2:3       3:4   
Row: 1 ->     0:6       1:7       2:8       3:9   
Row: 2 ->     0:10      1:11      2:12      3:13  
Row: 3 ->     0:14      1:15      2:16      3:17  
Transposed dense matrix: 
Row: 0 ->     0:1       1:6       2:10      3:14  
Row: 1 ->     0:2       1:7       2:11      3:15  
Row: 2 ->     0:3       1:8       2:12      3:16  
Row: 3 ->     0:4       1:9       2:13      3:17  
Creating matrix on CUDA GPU ... 
Dense matrix: 
Row: 0 ->     0:1       1:2       2:3       3:4   
Row: 1 ->     0:6       1:7       2:8       3:9   
Row: 2 ->     0:10      1:11      2:12      3:13  
Row: 3 ->     0:14      1:15      2:16      3:17  
Transposed dense matrix: 
Row: 0 ->     0:1       1:6       2:10      3:14  
Row: 1 ->     0:2       1:7       2:11      3:15  
Row: 2 ->     0:3       1:8       2:12      3:16  
Row: 3 ->     0:4       1:9       2:13      3:17  

getMatrixProduct()

template<typename Real , typename Device , typename Index , ElementsOrganization Organization, typename RealAllocator >

template<typename Matrix1 , typename Matrix2 , int tileDim>

void TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >::getMatrixProduct	(	const Matrix1 &	matrix1,
		const Matrix2 &	matrix2,
		Real	matrixMultiplicator = 1.0,
		TransposeState	transposeA = TransposeState::None,
		TransposeState	transposeB = TransposeState::None )

Computes the product of two matrices and stores the result in this matrix.

This method calculates the product of two given matrices (matrix1 and matrix2) and stores the result in this matrix. It optionally supports transposing the input matrices before performing the multiplication and scaling the result by a specified factor.

Template Parameters

Matrix1	Type of the first input matrix.
Matrix2	Type of the second input matrix.
tileDim	Tile dimension for GPU computation optimization. Default is 16.

Parameters

matrix1	The first input matrix.
matrix2	The second input matrix.
matrixMultiplicator	A scalar value by which the matrix product is scaled. Default is 1.0.
transposeA	Specifies whether to transpose matrix1 before multiplication. Default is TransposeState::None.
transposeB	Specifies whether to transpose matrix2 before multiplication. Default is TransposeState::None.

Example

#include "TNL/Algorithms/Segments/ElementsOrganization.h"
#include <iostream>
#include <TNL/Matrices/DenseMatrix.h>
#include <TNL/Devices/Host.h>
#include <TNL/Devices/Cuda.h>
 
template< typename Device, TNL::Matrices::ElementsOrganization Organization >
void
matrixProductExample( TNL::Matrices::TransposeState transposeA, TNL::Matrices::TransposeState transposeB )
{
   std::cout << "Matrix product (";
   std::cout << ( transposeA == TNL::Matrices::TransposeState::Transpose ? "Transposed x " : "Normal x " );
   std::cout << ( transposeB == TNL::Matrices::TransposeState::Transpose ? "Transposed)" : "Normal)" ) << std::endl;
 
   TNL::Matrices::DenseMatrix< double, Device, int, Organization > matrix1;
   TNL::Matrices::DenseMatrix< double, Device, int, Organization > matrix2;
 
   if( transposeA == TNL::Matrices::TransposeState::Transpose ) {
      // clang-format off
      matrix1 = {
      { 5, 6, 6 },
      { 6, 5, 7 },
      { 7, 2, 1 },
      { 3, 3, 9 } };
      // clang-format on
   }
   else {
      // clang-format off
      matrix1 = {
      { 5, 6, 7, 3 },
      { 6, 5, 2, 3 },
      { 6, 7, 1, 9 } };
      // clang-format on
   }
 
   std::cout << "Dense matrix 1: " << std::endl << matrix1 << std::endl;
 
   if( transposeB == TNL::Matrices::TransposeState::Transpose ) {
      // clang-format off
      matrix2 = {
      { 4, 3, 2, 6 },
      { 3, 4, 2, 8 },
      { 1, 4, 7, 9 },
      { 2, 3, 8, 0 },
      { 7, 6, 5, 4 } };
      // clang-format on
   }
   else {
      // clang-format off
      matrix2 = {
      { 4, 3, 2, 6, 7 },
      { 3, 4, 2, 8, 6 },
      { 1, 4, 7, 9, 5 },
      { 2, 3, 8, 0, 4 } };
      // clang-format on
   }
 
   std::cout << "Dense matrix 2: " << std::endl << matrix2 << std::endl;
 
   TNL::Matrices::DenseMatrix< double, Device, int, Organization > resultMatrix;
   resultMatrix.getMatrixProduct( matrix1, matrix2, 1.0, transposeA, transposeB );
 
   std::cout << "Product: " << std::endl << resultMatrix << std::endl;
}
 
int
main( int argc, char* argv[] )
{
   std::cout << "Creating matrices on CPU ... " << std::endl;
   std::cout << "Stored in Row Major Order ... " << std::endl;
   matrixProductExample< TNL::Devices::Host, TNL::Algorithms::Segments::ElementsOrganization::RowMajorOrder >(
      TNL::Matrices::TransposeState::None, TNL::Matrices::TransposeState::None );
   std::cout << "Stored in Column Major Order" << std::endl;
   matrixProductExample< TNL::Devices::Host, TNL::Algorithms::Segments::ElementsOrganization::ColumnMajorOrder >(
      TNL::Matrices::TransposeState::None, TNL::Matrices::TransposeState::None );
 
#ifdef __CUDACC__
   std::cout << "Creating matrices on CUDA GPU ... " << std::endl;
   std::cout << "Stored in Row Major Order ... " << std::endl;
   matrixProductExample< TNL::Devices::Cuda, TNL::Algorithms::Segments::ElementsOrganization::RowMajorOrder >(
      TNL::Matrices::TransposeState::None, TNL::Matrices::TransposeState::None );
   std::cout << "Stored in Column Major Order ... " << std::endl;
   matrixProductExample< TNL::Devices::Cuda, TNL::Algorithms::Segments::ElementsOrganization::ColumnMajorOrder >(
      TNL::Matrices::TransposeState::None, TNL::Matrices::TransposeState::None );
 
   std::cout << "Stored in Row Major Order ... " << std::endl;
   matrixProductExample< TNL::Devices::Cuda, TNL::Algorithms::Segments::ElementsOrganization::RowMajorOrder >(
      TNL::Matrices::TransposeState::Transpose, TNL::Matrices::TransposeState::None );
   std::cout << "Stored in Column Major Order ... " << std::endl;
   matrixProductExample< TNL::Devices::Cuda, TNL::Algorithms::Segments::ElementsOrganization::ColumnMajorOrder >(
      TNL::Matrices::TransposeState::Transpose, TNL::Matrices::TransposeState::None );
 
   std::cout << "Stored in Row Major Order ... " << std::endl;
   matrixProductExample< TNL::Devices::Cuda, TNL::Algorithms::Segments::ElementsOrganization::RowMajorOrder >(
      TNL::Matrices::TransposeState::None, TNL::Matrices::TransposeState::Transpose );
   std::cout << "Stored in Column Major Order ... " << std::endl;
   matrixProductExample< TNL::Devices::Cuda, TNL::Algorithms::Segments::ElementsOrganization::ColumnMajorOrder >(
      TNL::Matrices::TransposeState::None, TNL::Matrices::TransposeState::Transpose );
 
   std::cout << "Stored in Row Major Order ... " << std::endl;
   matrixProductExample< TNL::Devices::Cuda, TNL::Algorithms::Segments::ElementsOrganization::RowMajorOrder >(
      TNL::Matrices::TransposeState::Transpose, TNL::Matrices::TransposeState::Transpose );
   std::cout << "Stored in Column Major Order ... " << std::endl;
   matrixProductExample< TNL::Devices::Cuda, TNL::Algorithms::Segments::ElementsOrganization::ColumnMajorOrder >(
      TNL::Matrices::TransposeState::Transpose, TNL::Matrices::TransposeState::Transpose );
#endif
}

Output

Creating matrices on CPU ... 
Stored in Row Major Order ... 
Matrix product (Normal x Normal)
Dense matrix 1: 
Row: 0 ->     0:5       1:6       2:7       3:3   
Row: 1 ->     0:6       1:5       2:2       3:3   
Row: 2 ->     0:6       1:7       2:1       3:9   
Dense matrix 2: 
Row: 0 ->     0:4       1:3       2:2       3:6       4:7   
Row: 1 ->     0:3       1:4       2:2       3:8       4:6   
Row: 2 ->     0:1       1:4       2:7       3:9       4:5   
Row: 3 ->     0:2       1:3       2:8       3:0       4:4   
Product: 
Row: 0 ->     0:51      1:76      2:95      3:141     4:118 
Row: 1 ->     0:47      1:55      2:60      3:94      4:94  
Row: 2 ->     0:64      1:77      2:105     3:101     4:125 
Stored in Column Major Order
Matrix product (Normal x Normal)
Dense matrix 1: 
Row: 0 ->     0:5       1:6       2:7       3:3   
Row: 1 ->     0:6       1:5       2:2       3:3   
Row: 2 ->     0:6       1:7       2:1       3:9   
Dense matrix 2: 
Row: 0 ->     0:4       1:3       2:2       3:6       4:7   
Row: 1 ->     0:3       1:4       2:2       3:8       4:6   
Row: 2 ->     0:1       1:4       2:7       3:9       4:5   
Row: 3 ->     0:2       1:3       2:8       3:0       4:4   
Product: 
Row: 0 ->     0:51      1:76      2:95      3:141     4:118 
Row: 1 ->     0:47      1:55      2:60      3:94      4:94  
Row: 2 ->     0:64      1:77      2:105     3:101     4:125 
Creating matrices on CUDA GPU ... 
Stored in Row Major Order ... 
Matrix product (Normal x Normal)
Dense matrix 1: 
Row: 0 ->     0:5       1:6       2:7       3:3   
Row: 1 ->     0:6       1:5       2:2       3:3   
Row: 2 ->     0:6       1:7       2:1       3:9   
Dense matrix 2: 
Row: 0 ->     0:4       1:3       2:2       3:6       4:7   
Row: 1 ->     0:3       1:4       2:2       3:8       4:6   
Row: 2 ->     0:1       1:4       2:7       3:9       4:5   
Row: 3 ->     0:2       1:3       2:8       3:0       4:4   
Product: 
Row: 0 ->     0:51      1:76      2:95      3:141     4:118 
Row: 1 ->     0:47      1:55      2:60      3:94      4:94  
Row: 2 ->     0:64      1:77      2:105     3:101     4:125 
Stored in Column Major Order ... 
Matrix product (Normal x Normal)
Dense matrix 1: 
Row: 0 ->     0:5       1:6       2:7       3:3   
Row: 1 ->     0:6       1:5       2:2       3:3   
Row: 2 ->     0:6       1:7       2:1       3:9   
Dense matrix 2: 
Row: 0 ->     0:4       1:3       2:2       3:6       4:7   
Row: 1 ->     0:3       1:4       2:2       3:8       4:6   
Row: 2 ->     0:1       1:4       2:7       3:9       4:5   
Row: 3 ->     0:2       1:3       2:8       3:0       4:4   
Product: 
Row: 0 ->     0:51      1:76      2:95      3:141     4:118 
Row: 1 ->     0:47      1:55      2:60      3:94      4:94  
Row: 2 ->     0:64      1:77      2:105     3:101     4:125 
Stored in Row Major Order ... 
Matrix product (Transposed x Normal)
Dense matrix 1: 
Row: 0 ->     0:5       1:6       2:6   
Row: 1 ->     0:6       1:5       2:7   
Row: 2 ->     0:7       1:2       2:1   
Row: 3 ->     0:3       1:3       2:9   
Dense matrix 2: 
Row: 0 ->     0:4       1:3       2:2       3:6       4:7   
Row: 1 ->     0:3       1:4       2:2       3:8       4:6   
Row: 2 ->     0:1       1:4       2:7       3:9       4:5   
Row: 3 ->     0:2       1:3       2:8       3:0       4:4   
Product: 
Row: 0 ->     0:51      1:76      2:95      3:141     4:118 
Row: 1 ->     0:47      1:55      2:60      3:94      4:94  
Row: 2 ->     0:64      1:77      2:105     3:101     4:125 
Stored in Column Major Order ... 
Matrix product (Transposed x Normal)
Dense matrix 1: 
Row: 0 ->     0:5       1:6       2:6   
Row: 1 ->     0:6       1:5       2:7   
Row: 2 ->     0:7       1:2       2:1   
Row: 3 ->     0:3       1:3       2:9   
Dense matrix 2: 
Row: 0 ->     0:4       1:3       2:2       3:6       4:7   
Row: 1 ->     0:3       1:4       2:2       3:8       4:6   
Row: 2 ->     0:1       1:4       2:7       3:9       4:5   
Row: 3 ->     0:2       1:3       2:8       3:0       4:4   
Product: 
Row: 0 ->     0:51      1:76      2:95      3:141     4:118 
Row: 1 ->     0:47      1:55      2:60      3:94      4:94  
Row: 2 ->     0:64      1:77      2:105     3:101     4:125 
Stored in Row Major Order ... 
Matrix product (Normal x Transposed)
Dense matrix 1: 
Row: 0 ->     0:5       1:6       2:7       3:3   
Row: 1 ->     0:6       1:5       2:2       3:3   
Row: 2 ->     0:6       1:7       2:1       3:9   
Dense matrix 2: 
Row: 0 ->     0:4       1:3       2:2       3:6   
Row: 1 ->     0:3       1:4       2:2       3:8   
Row: 2 ->     0:1       1:4       2:7       3:9   
Row: 3 ->     0:2       1:3       2:8       3:0   
Row: 4 ->     0:7       1:6       2:5       3:4   
Product: 
Row: 0 ->     0:70      1:77      2:105     3:84      4:118 
Row: 1 ->     0:61      1:66      2:67      3:43      4:94  
Row: 2 ->     0:101     1:120     2:122     3:41      4:125 
Stored in Column Major Order ... 
Matrix product (Normal x Transposed)
Dense matrix 1: 
Row: 0 ->     0:5       1:6       2:7       3:3   
Row: 1 ->     0:6       1:5       2:2       3:3   
Row: 2 ->     0:6       1:7       2:1       3:9   
Dense matrix 2: 
Row: 0 ->     0:4       1:3       2:2       3:6   
Row: 1 ->     0:3       1:4       2:2       3:8   
Row: 2 ->     0:1       1:4       2:7       3:9   
Row: 3 ->     0:2       1:3       2:8       3:0   
Row: 4 ->     0:7       1:6       2:5       3:4   
Product: 
Row: 0 ->     0:70      1:77      2:105     3:84      4:118 
Row: 1 ->     0:61      1:66      2:67      3:43      4:94  
Row: 2 ->     0:101     1:120     2:122     3:41      4:125 
Stored in Row Major Order ... 
Matrix product (Transposed x Transposed)
Dense matrix 1: 
Row: 0 ->     0:5       1:6       2:6   
Row: 1 ->     0:6       1:5       2:7   
Row: 2 ->     0:7       1:2       2:1   
Row: 3 ->     0:3       1:3       2:9   
Dense matrix 2: 
Row: 0 ->     0:4       1:3       2:2       3:6   
Row: 1 ->     0:3       1:4       2:2       3:8   
Row: 2 ->     0:1       1:4       2:7       3:9   
Row: 3 ->     0:2       1:3       2:8       3:0   
Row: 4 ->     0:7       1:6       2:5       3:4   
Product: 
Row: 0 ->     0:70      1:77      2:105     3:84      4:118 
Row: 1 ->     0:61      1:66      2:67      3:43      4:94  
Row: 2 ->     0:101     1:120     2:122     3:41      4:125 
Stored in Column Major Order ... 
Matrix product (Transposed x Transposed)
Dense matrix 1: 
Row: 0 ->     0:5       1:6       2:6   
Row: 1 ->     0:6       1:5       2:7   
Row: 2 ->     0:7       1:2       2:1   
Row: 3 ->     0:3       1:3       2:9   
Dense matrix 2: 
Row: 0 ->     0:4       1:3       2:2       3:6   
Row: 1 ->     0:3       1:4       2:2       3:8   
Row: 2 ->     0:1       1:4       2:7       3:9   
Row: 3 ->     0:2       1:3       2:8       3:0   
Row: 4 ->     0:7       1:6       2:5       3:4   
Product: 
Row: 0 ->     0:70      1:77      2:105     3:84      4:118 
Row: 1 ->     0:61      1:66      2:67      3:43      4:94  
Row: 2 ->     0:101     1:120     2:122     3:41      4:125 

getSerializationType()

template<typename Real = double, typename Device = Devices::Host, typename Index = int, ElementsOrganization Organization = Algorithms::Segments::DefaultElementsOrganization< Device >::getOrganization(), typename RealAllocator = typename Allocators::Default< Device >::template Allocator< Real >>

std::string TNL::Matrices::DenseMatrixBase< Real, Device, Index, Organization >::getSerializationType ( )

staticnodiscard

Returns string with serialization type.

The string has a form `MatricesDenseMatrix< RealType, [any_device], IndexType, [any_allocator], true/false >`.

Returns

String with the serialization type.

getTransposition()

template<typename Real , typename Device , typename Index , ElementsOrganization Organization, typename RealAllocator >

template<typename Matrix , int tileDim>

void TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >::getTransposition	(	const Matrix &	matrix,
		Real	matrixMultiplicator = 1.0 )

Computes the transposition of a given matrix and stores the result in this matrix.

This method calculates the transpose of a given matrix and stores the result in this matrix. The result can also be scaled by a specified factor.

Template Parameters

Matrix	Type of the input matrix.
tileDim	Tile dimension for GPU computation optimization. Default is 16.

Parameters

matrix	The input matrix to be transposed.
matrixMultiplicator	A scalar value by which the transposed matrix is scaled. Default is 1.0.

Example

#include <iostream>
#include <TNL/Matrices/DenseMatrix.h>
#include <TNL/Devices/Host.h>
#include <TNL/Devices/Cuda.h>
 
template< typename Device >
void
getTranspositionExample()
{
   // clang-format off
   TNL::Matrices::DenseMatrix< double, Device > matrix{
   { 1, 2, 3 },
   { 4, 5, 6 },
   { 7, 8, 9 },
   { 10, 11, 12 },
   { 13, 14, 15 } };
   // clang-format on
 
   std::cout << "Dense matrix: " << std::endl << matrix << std::endl;
 
   TNL::Matrices::DenseMatrix< double, Device > outputMatrix;
 
   outputMatrix.getTransposition( matrix );
 
   std::cout << "Transposed dense matrix: " << std::endl << outputMatrix << std::endl;
}
 
int
main( int argc, char* argv[] )
{
   std::cout << "Creating matrix on CPU ... " << std::endl;
   getTranspositionExample< TNL::Devices::Host >();
 
#ifdef __CUDACC__
   std::cout << "Creating matrix on CUDA GPU ... " << std::endl;
   getTranspositionExample< TNL::Devices::Cuda >();
#endif
}

Output

Creating matrix on CPU ... 
Dense matrix: 
Row: 0 ->     0:1       1:2       2:3   
Row: 1 ->     0:4       1:5       2:6   
Row: 2 ->     0:7       1:8       2:9   
Row: 3 ->     0:10      1:11      2:12  
Row: 4 ->     0:13      1:14      2:15  
Transposed dense matrix: 
Row: 0 ->     0:1       1:4       2:7       3:10      4:13  
Row: 1 ->     0:2       1:5       2:8       3:11      4:14  
Row: 2 ->     0:3       1:6       2:9       3:12      4:15  
Creating matrix on CUDA GPU ... 
Dense matrix: 
Row: 0 ->     0:1       1:2       2:3   
Row: 1 ->     0:4       1:5       2:6   
Row: 2 ->     0:7       1:8       2:9   
Row: 3 ->     0:10      1:11      2:12  
Row: 4 ->     0:13      1:14      2:15  
Transposed dense matrix: 
Row: 0 ->     0:1       1:4       2:7       3:10      4:13  
Row: 1 ->     0:2       1:5       2:8       3:11      4:14  
Row: 2 ->     0:3       1:6       2:9       3:12      4:15  

getView()

template<typename Real , typename Device , typename Index , ElementsOrganization Organization, typename RealAllocator >

auto TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >::getView ( )

nodiscard

Returns a modifiable view of the dense matrix.

See DenseMatrixView.

Returns

dense matrix view.

load() [1/2]

template<typename Real , typename Device , typename Index , ElementsOrganization Organization, typename RealAllocator >

void TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >::load

(

const String &

fileName

)

Method for loading the matrix from the file with given filename.

Parameters

fileName

is name of the file.

load() [2/2]

template<typename Real , typename Device , typename Index , ElementsOrganization Organization, typename RealAllocator >

void TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >::load ( File & file )

overridevirtual

Method for loading the matrix from a file.

Parameters

file	is the file from which the matrix will be loaded.

Reimplemented from TNL::Object.

operator=() [1/7]

template<typename Real = double, typename Device = Devices::Host, typename Index = int, ElementsOrganization Organization = Algorithms::Segments::DefaultElementsOrganization< Device >::getOrganization(), typename RealAllocator = typename Allocators::Default< Device >::template Allocator< Real >>

DenseMatrix & TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >::operator=

(

const DenseMatrix< Real, Device, Index, Organization, RealAllocator > &

matrix

)

Copy-assignment of exactly the same matrix type.

Parameters

matrix

is input matrix for the assignment.

Returns

reference to this matrix.

operator=() [2/7]

template<typename Real = double, typename Device = Devices::Host, typename Index = int, ElementsOrganization Organization = Algorithms::Segments::DefaultElementsOrganization< Device >::getOrganization(), typename RealAllocator = typename Allocators::Default< Device >::template Allocator< Real >>

template<typename RHSReal , typename RHSDevice , typename RHSIndex , typename RHSRealAllocator >

DenseMatrix & TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >::operator=

(

const DenseMatrix< RHSReal, RHSDevice, RHSIndex, Organization, RHSRealAllocator > &

matrix

)

Assignment operator with the same organization.

Parameters

matrix

is the right-hand side matrix.

Returns

reference to this matrix.

operator=() [3/7]

template<typename Real = double, typename Device = Devices::Host, typename Index = int, ElementsOrganization Organization = Algorithms::Segments::DefaultElementsOrganization< Device >::getOrganization(), typename RealAllocator = typename Allocators::Default< Device >::template Allocator< Real >>

template<typename RHSReal , typename RHSDevice , typename RHSIndex , ElementsOrganization RHSOrganization, typename RHSRealAllocator >

DenseMatrix & TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >::operator=

(

const DenseMatrix< RHSReal, RHSDevice, RHSIndex, RHSOrganization, RHSRealAllocator > &

matrix

)

Assignment operator with other dense matrices.

Parameters

matrix

is the right-hand side matrix.

Returns

reference to this matrix.

operator=() [4/7]

template<typename Real = double, typename Device = Devices::Host, typename Index = int, ElementsOrganization Organization = Algorithms::Segments::DefaultElementsOrganization< Device >::getOrganization(), typename RealAllocator = typename Allocators::Default< Device >::template Allocator< Real >>

template<typename RHSReal , typename RHSDevice , typename RHSIndex >

DenseMatrix & TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >::operator=

(

const DenseMatrixView< RHSReal, RHSDevice, RHSIndex, Organization > &

matrix

)

Assignment operator with matrix view having the same elements organization.

Parameters

matrix

is the right-hand side matrix.

Returns

reference to this matrix.

operator=() [5/7]

template<typename Real = double, typename Device = Devices::Host, typename Index = int, ElementsOrganization Organization = Algorithms::Segments::DefaultElementsOrganization< Device >::getOrganization(), typename RealAllocator = typename Allocators::Default< Device >::template Allocator< Real >>

template<typename RHSReal , typename RHSDevice , typename RHSIndex , ElementsOrganization RHSOrganization>

DenseMatrix & TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >::operator=

(

const DenseMatrixView< RHSReal, RHSDevice, RHSIndex, RHSOrganization > &

matrix

)

Assignment operator with other dense matrices.

Parameters

matrix

is the right-hand side matrix.

Returns

reference to this matrix.

operator=() [6/7]

template<typename Real = double, typename Device = Devices::Host, typename Index = int, ElementsOrganization Organization = Algorithms::Segments::DefaultElementsOrganization< Device >::getOrganization(), typename RealAllocator = typename Allocators::Default< Device >::template Allocator< Real >>

template<typename RHSMatrix >

DenseMatrix & TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >::operator=

(

const RHSMatrix &

matrix

)

Assignment operator with other (sparse) types of matrices.

Parameters

matrix

is the right-hand side matrix.

Returns

reference to this matrix.

operator=() [7/7]

template<typename Real = double, typename Device = Devices::Host, typename Index = int, ElementsOrganization Organization = Algorithms::Segments::DefaultElementsOrganization< Device >::getOrganization(), typename RealAllocator = typename Allocators::Default< Device >::template Allocator< Real >>

DenseMatrix & TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >::operator=

(

DenseMatrix< Real, Device, Index, Organization, RealAllocator > &&

matrix

)

Move-assignment of exactly the same matrix type.

Parameters

matrix

is input matrix for the assignment.

Returns

reference to this matrix.

save() [1/2]

template<typename Real , typename Device , typename Index , ElementsOrganization Organization, typename RealAllocator >

void TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >::save

(

const String &

fileName

)

const

Method for saving the matrix to the file with given filename.

Parameters

fileName

is name of the file.

save() [2/2]

template<typename Real , typename Device , typename Index , ElementsOrganization Organization, typename RealAllocator >

void TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >::save ( File & file ) const

overridevirtual

Method for saving the matrix to a file.

Parameters

file	is the file where the matrix will be saved.

Reimplemented from TNL::Object.

setDimensions()

template<typename Real , typename Device , typename Index , ElementsOrganization Organization, typename RealAllocator >

void TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >::setDimensions	(	Index	rows,
		Index	columns )

Set number of rows and columns of this matrix.

Parameters

rows	is the number of matrix rows.
columns	is the number of matrix columns.

setElements() [1/2]

template<typename Real , typename Device , typename Index , ElementsOrganization Organization, typename RealAllocator >

template<typename MapIndex , typename MapValue >

void TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >::setElements

(

const std::map< std::pair< MapIndex, MapIndex >, MapValue > &

map

)

This method sets the dense matrix elements from std::map.

This is intended for compatibility with SparseMatrix, the method is used e.g. in MatrixReader.

The matrix elements values are given as a map data where keys are std::pair of matrix coordinates ( {row, column} ) and value is the matrix element value.

Template Parameters

MapIndex	is a type for indexing rows and columns.
MapValue	is a type for matrix elements values in the map.

Parameters

map	is std::map containing matrix elements.

setElements() [2/2]

template<typename Real , typename Device , typename Index , ElementsOrganization Organization, typename RealAllocator >

template<typename Value >

void TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >::setElements

(

std::initializer_list< std::initializer_list< Value > >

data

)

This method recreates the dense matrix from 2D initializer list.

The number of matrix rows is set to the outer list size and the number of matrix columns is set to maximum size of inner lists. Missing elements are filled in with zeros.

Parameters

data	is a initializer list of initializer lists representing list of matrix rows.

Example

#include <iostream>
#include <TNL/Matrices/DenseMatrix.h>
#include <TNL/Devices/Host.h>
#include <TNL/Devices/Cuda.h>
 
template< typename Device >
void
setElementsExample()
{
   TNL::Matrices::DenseMatrix< double, Device > matrix;
   matrix.setElements( {
      // clang-format off
      {  1,  2,  3,  4,  5,  6 },
      {  7,  8,  9, 10, 11, 12 },
      { 13, 14, 15, 16, 17, 18 }
      // clang-format on
   } );
 
   std::cout << matrix << std::endl;
 
   TNL::Matrices::DenseMatrix< double, Device > triangularMatrix;
   triangularMatrix.setElements( {
      // clang-format off
      {  1 },
      {  2,  3 },
      {  4,  5,  6 },
      {  7,  8,  9, 10 },
      { 11, 12, 13, 14, 15 }
      // clang-format on
   } );
 
   std::cout << triangularMatrix << std::endl;
}
 
int
main( int argc, char* argv[] )
{
   std::cout << "Setting matrix elements on host: " << std::endl;
   setElementsExample< TNL::Devices::Host >();
 
#ifdef __CUDACC__
   std::cout << "Setting matrix elements on CUDA device: " << std::endl;
   setElementsExample< TNL::Devices::Cuda >();
#endif
}

Output

Setting matrix elements on host: 
Row: 0 ->     0:1       1:2       2:3       3:4       4:5       5:6   
Row: 1 ->     0:7       1:8       2:9       3:10      4:11      5:12  
Row: 2 ->     0:13      1:14      2:15      3:16      4:17      5:18  
Row: 0 ->     0:1       1:0       2:0       3:0       4:0   
Row: 1 ->     0:2       1:3       2:0       3:0       4:0   
Row: 2 ->     0:4       1:5       2:6       3:0       4:0   
Row: 3 ->     0:7       1:8       2:9       3:10      4:0   
Row: 4 ->     0:11      1:12      2:13      3:14      4:15  
Setting matrix elements on CUDA device: 
Row: 0 ->     0:1       1:2       2:3       3:4       4:5       5:6   
Row: 1 ->     0:7       1:8       2:9       3:10      4:11      5:12  
Row: 2 ->     0:13      1:14      2:15      3:16      4:17      5:18  
Row: 0 ->     0:1       1:0       2:0       3:0       4:0   
Row: 1 ->     0:2       1:3       2:0       3:0       4:0   
Row: 2 ->     0:4       1:5       2:6       3:0       4:0   
Row: 3 ->     0:7       1:8       2:9       3:10      4:0   
Row: 4 ->     0:11      1:12      2:13      3:14      4:15  

setLike()

template<typename Real = double, typename Device = Devices::Host, typename Index = int, ElementsOrganization Organization = Algorithms::Segments::DefaultElementsOrganization< Device >::getOrganization(), typename RealAllocator = typename Allocators::Default< Device >::template Allocator< Real >>

template<typename Matrix >

void TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >::setLike

(

const Matrix &

matrix

)

Set the number of matrix rows and columns by the given matrix.

Template Parameters

Matrix

is matrix type. This can be any matrix having methods getRows and getColumns.

Parameters

matrix

in the input matrix dimensions of which are to be adopted.

setRowCapacities()

template<typename Real , typename Device , typename Index , ElementsOrganization Organization, typename RealAllocator >

template<typename RowCapacitiesVector >

void TNL::Matrices::DenseMatrix< Real, Device, Index, Organization, RealAllocator >::setRowCapacities

(

const RowCapacitiesVector &

rowCapacities

)

This method is only for the compatibility with the sparse matrices.

This method does nothing. In debug mode it contains assertions checking that given rowCapacities are compatible with the current matrix dimensions.

---

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

• src/TNL/Matrices/DenseMatrix.h
• src/TNL/Matrices/DenseMatrix.hpp