#include <deal.II/lac/lapack_full_matrix.h>

Inheritance diagram for LAPACKFullMatrix< number >:

Public Types
using	size_type = std::make_unsigned< types::blas_int >::type

Public Types inherited from TransposeTable< number >
using	size_type = typename TableBase< 2, number >::size_type

using	value_type = typename AlignedVector< number >::value_type

using	reference = typename AlignedVector< number >::reference

using	const_reference = typename AlignedVector< number >::const_reference

using	const_iterator = MatrixTableIterators::Iterator< TransposeTable< number >, true, MatrixTableIterators::Storage::column_major >

using	iterator = MatrixTableIterators::Iterator< TransposeTable< number >, false, MatrixTableIterators::Storage::column_major >

Public Types inherited from TableBase< 2, number >
using	value_type = number

using	size_type = typename AlignedVector< number >::size_type

Public Member Functions
	LAPACKFullMatrix (const size_type size=0)

	LAPACKFullMatrix (const size_type rows, const size_type cols)

	LAPACKFullMatrix (const LAPACKFullMatrix &)

LAPACKFullMatrix< number > &	operator= (const LAPACKFullMatrix< number > &)

template<typename number2 >
LAPACKFullMatrix< number > &	operator= (const FullMatrix< number2 > &)

template<typename number2 >
LAPACKFullMatrix< number > &	operator= (const SparseMatrix< number2 > &)

LAPACKFullMatrix< number > &	operator= (const number d)

LAPACKFullMatrix< number > &	operator*= (const number factor)

LAPACKFullMatrix< number > &	operator/= (const number factor)

void	set (const size_type i, const size_type j, const number value)

void	add (const number a, const LAPACKFullMatrix< number > &B)

void	rank1_update (const number a, const Vector< number > &v)

void	apply_givens_rotation (const std::array< number, 3 > &csr, const size_type i, const size_type k, const bool left=true)

template<typename MatrixType >
void	copy_from (const MatrixType &)

void	reinit (const size_type size)

void	grow_or_shrink (const size_type size)

void	remove_row_and_column (const size_type row, const size_type col)

void	reinit (const size_type rows, const size_type cols)

void	set_property (const LAPACKSupport::Property property)

size_type	m () const

size_type	n () const

template<typename MatrixType >
void	fill (const MatrixType &src, const size_type dst_offset_i=0, const size_type dst_offset_j=0, const size_type src_offset_i=0, const size_type src_offset_j=0, const number factor=1., const bool transpose=false)

template<typename number2 >
void	vmult (Vector< number2 > &w, const Vector< number2 > &v, const bool adding=false) const

void	vmult (Vector< number > &w, const Vector< number > &v, const bool adding=false) const

template<typename number2 >
void	vmult_add (Vector< number2 > &w, const Vector< number2 > &v) const

void	vmult_add (Vector< number > &w, const Vector< number > &v) const

template<typename number2 >
void	Tvmult (Vector< number2 > &w, const Vector< number2 > &v, const bool adding=false) const

void	Tvmult (Vector< number > &w, const Vector< number > &v, const bool adding=false) const

template<typename number2 >
void	Tvmult_add (Vector< number2 > &w, const Vector< number2 > &v) const

void	Tvmult_add (Vector< number > &w, const Vector< number > &v) const

void	mmult (LAPACKFullMatrix< number > &C, const LAPACKFullMatrix< number > &B, const bool adding=false) const

void	mmult (FullMatrix< number > &C, const LAPACKFullMatrix< number > &B, const bool adding=false) const

void	Tmmult (LAPACKFullMatrix< number > &C, const LAPACKFullMatrix< number > &B, const bool adding=false) const

void	Tmmult (FullMatrix< number > &C, const LAPACKFullMatrix< number > &B, const bool adding=false) const

void	Tmmult (LAPACKFullMatrix< number > &C, const LAPACKFullMatrix< number > &B, const Vector< number > &V, const bool adding=false) const

void	mTmult (LAPACKFullMatrix< number > &C, const LAPACKFullMatrix< number > &B, const bool adding=false) const

void	mTmult (FullMatrix< number > &C, const LAPACKFullMatrix< number > &B, const bool adding=false) const

void	TmTmult (LAPACKFullMatrix< number > &C, const LAPACKFullMatrix< number > &B, const bool adding=false) const

void	TmTmult (FullMatrix< number > &C, const LAPACKFullMatrix< number > &B, const bool adding=false) const

void	transpose (LAPACKFullMatrix< number > &B) const

void	scale_rows (const Vector< number > &V)

void	compute_lu_factorization ()

void	compute_cholesky_factorization ()

number	reciprocal_condition_number (const number l1_norm) const

number	reciprocal_condition_number () const

number	determinant () const

number	l1_norm () const

number	linfty_norm () const

number	frobenius_norm () const

number	trace () const

void	invert ()

void	solve (Vector< number > &v, const bool transposed=false) const

void	solve (LAPACKFullMatrix< number > &B, const bool transposed=false) const

void	compute_eigenvalues (const bool right_eigenvectors=false, const bool left_eigenvectors=false)

void	compute_eigenvalues_symmetric (const number lower_bound, const number upper_bound, const number abs_accuracy, Vector< number > &eigenvalues, FullMatrix< number > &eigenvectors)

void	compute_generalized_eigenvalues_symmetric (LAPACKFullMatrix< number > &B, const number lower_bound, const number upper_bound, const number abs_accuracy, Vector< number > &eigenvalues, std::vector< Vector< number >> &eigenvectors, const types::blas_int itype=1)

void	compute_generalized_eigenvalues_symmetric (LAPACKFullMatrix< number > &B, std::vector< Vector< number >> &eigenvectors, const types::blas_int itype=1)

void	compute_svd ()

void	compute_inverse_svd (const double threshold=0.)

void	compute_inverse_svd_with_kernel (const unsigned int kernel_size)

std::complex< number >	eigenvalue (const size_type i) const

number	singular_value (const size_type i) const

const LAPACKFullMatrix< number > &	get_svd_u () const

const LAPACKFullMatrix< number > &	get_svd_vt () const

void	print_formatted (std::ostream &out, const unsigned int precision=3, const bool scientific=true, const unsigned int width=0, const char *zero_string=" ", const double denominator=1., const double threshold=0.) const

Public Member Functions inherited from TransposeTable< number >
	TransposeTable ()=default

	TransposeTable (const size_type size1, const size_type size2)

void	reinit (const size_type size1, const size_type size2, const bool omit_default_initialization=false)

const_reference	operator() (const size_type i, const size_type j) const

reference	operator() (const size_type i, const size_type j)

size_type	n_rows () const

size_type	n_cols () const

iterator	begin ()

const_iterator	begin () const

iterator	end ()

const_iterator	end () const

Public Member Functions inherited from TableBase< 2, number >
	TableBase ()=default

	TableBase (const TableIndices< N > &sizes)

	TableBase (const TableIndices< N > &sizes, InputIterator entries, const bool C_style_indexing=true)

	TableBase (const TableBase< N, number > &src)

	TableBase (const TableBase< N, T2 > &src)

	TableBase (TableBase< N, number > &&src) noexcept

	~TableBase () override=default

TableBase< N, number > &	operator= (const TableBase< N, number > &src)

TableBase< N, number > &	operator= (const TableBase< N, T2 > &src)

TableBase< N, number > &	operator= (TableBase< N, number > &&src) noexcept

bool	operator== (const TableBase< N, number > &T2) const

void	reset_values ()

void	reinit (const TableIndices< N > &new_size, const bool omit_default_initialization=false)

size_type	size (const unsigned int i) const

const TableIndices< N > &	size () const

size_type	n_elements () const

bool	empty () const

void	fill (InputIterator entries, const bool C_style_indexing=true)

void	fill (const number &value)

AlignedVector< number >::reference	operator() (const TableIndices< N > &indices)

AlignedVector< number >::const_reference	operator() (const TableIndices< N > &indices) const

void	swap (TableBase< N, number > &v)

std::size_t	memory_consumption () const

void	serialize (Archive &ar, const unsigned int version)

Public Member Functions inherited from Subscriptor
	Subscriptor ()

	Subscriptor (const Subscriptor &)

	Subscriptor (Subscriptor &&) noexcept

virtual	~Subscriptor ()

Subscriptor &	operator= (const Subscriptor &)

Subscriptor &	operator= (Subscriptor &&) noexcept

void	subscribe (std::atomic< bool > *const validity, const std::string &identifier="") const

void	unsubscribe (std::atomic< bool > *const validity, const std::string &identifier="") const

unsigned int	n_subscriptions () const

template<typename StreamType >
void	list_subscribers (StreamType &stream) const

void	list_subscribers () const

template<class Archive >
void	serialize (Archive &ar, const unsigned int version)

Private Member Functions
number	norm (const char type) const

Private Attributes
LAPACKSupport::State	state

LAPACKSupport::Property	property

std::vector< number >	work

std::vector< types::blas_int >	iwork

std::vector< types::blas_int >	ipiv

std::vector< number >	inv_work

std::vector< typename numbers::NumberTraits< number >::real_type >	wr

std::vector< number >	wi

std::vector< number >	vl

std::vector< number >	vr

std::unique_ptr< LAPACKFullMatrix< number > >	svd_u

std::unique_ptr< LAPACKFullMatrix< number > >	svd_vt

std::mutex	mutex

Additional Inherited Members
Static Public Member Functions inherited from Subscriptor
static ::ExceptionBase &	ExcInUse (int arg1, std::string arg2, std::string arg3)

static ::ExceptionBase &	ExcNoSubscriber (std::string arg1, std::string arg2)

Protected Member Functions inherited from TransposeTable< number >
reference	el (const size_type i, const size_type j)

const_reference	el (const size_type i, const size_type j) const

Protected Member Functions inherited from TableBase< 2, number >
size_type	position (const TableIndices< N > &indices) const

AlignedVector< number >::reference	el (const TableIndices< N > &indices)

AlignedVector< number >::const_reference	el (const TableIndices< N > &indices) const

Protected Attributes inherited from TableBase< 2, number >
AlignedVector< number >	values

TableIndices< N >	table_size

Detailed Description

template<typename number>
class LAPACKFullMatrix< number >

A variant of FullMatrix using LAPACK functions wherever possible. In order to do this, the matrix is stored in transposed order. The element access functions hide this fact by reverting the transposition.

Note: In order to perform LAPACK functions, the class contains a lot of auxiliary data in the private section. The names of these data vectors are usually the names chosen for the arguments in the LAPACK documentation.

Author: Guido Kanschat, 2005, Denis Davydov, 2017, 2018

Definition at line 60 of file lapack_full_matrix.h.

Member Typedef Documentation

◆ size_type

template<typename number >

using LAPACKFullMatrix< number >::size_type = std::make_unsigned<types::blas_int>::type

Declare type for container size.

Definition at line 66 of file lapack_full_matrix.h.

Constructor & Destructor Documentation

◆ LAPACKFullMatrix() [1/3]

template<typename number >

LAPACKFullMatrix< number >::LAPACKFullMatrix ( const size_type size = 0 )

explicit

Constructor. Initialize the matrix as a square matrix with dimension size.

In order to avoid the implicit conversion of integers and other types to a matrix, this constructor is declared explicit.

By default, no memory is allocated.

Definition at line 244 of file lapack_full_matrix.cc.

◆ LAPACKFullMatrix() [2/3]

template<typename number >

LAPACKFullMatrix< number >::LAPACKFullMatrix	(	const size_type	rows,
		const size_type	cols
	)

Constructor. Initialize the matrix as a rectangular matrix \(\rm{rows} \times \rm{cols}\).

Definition at line 252 of file lapack_full_matrix.cc.

◆ LAPACKFullMatrix() [3/3]

template<typename number >

LAPACKFullMatrix< number >::LAPACKFullMatrix ( const LAPACKFullMatrix< number > & M )

Copy constructor. This constructor does a deep copy of the matrix. Therefore, it poses a possible efficiency problem, if for example, function arguments are passed by value rather than by reference. Unfortunately, we can't mark this copy constructor explicit, since that prevents the use of this class in containers, such as std::vector. The responsibility to check performance of programs must therefore remain with the user of this class.

Definition at line 260 of file lapack_full_matrix.cc.

Member Function Documentation

◆ operator=() [1/4]

template<typename number >

LAPACKFullMatrix< number > & LAPACKFullMatrix< number >::operator= ( const LAPACKFullMatrix< number > & M )

Assignment operator.

Definition at line 269 of file lapack_full_matrix.cc.

◆ operator=() [2/4]

template<typename number >

template<typename number2 >

LAPACKFullMatrix< number > & LAPACKFullMatrix< number >::operator= ( const FullMatrix< number2 > & M )

Assignment operator from a regular FullMatrix.

Note: Since LAPACK expects matrices in transposed order, this transposition is included here.

Definition at line 376 of file lapack_full_matrix.cc.

◆ operator=() [3/4]

template<typename number >

template<typename number2 >

LAPACKFullMatrix< number > & LAPACKFullMatrix< number >::operator= ( const SparseMatrix< number2 > & M )

Assignment operator from a regular SparseMatrix.

Note: Since LAPACK expects matrices in transposed order, this transposition is included here.

Definition at line 393 of file lapack_full_matrix.cc.

◆ operator=() [4/4]

template<typename number >

LAPACKFullMatrix< number > & LAPACKFullMatrix< number >::operator= ( const number d )

This operator assigns a scalar to a matrix. To avoid confusion with constructors, zero (when cast to the number type) is the only value allowed for d.

Definition at line 409 of file lapack_full_matrix.cc.

◆ operator*=()

template<typename number >

LAPACKFullMatrix< number > & LAPACKFullMatrix< number >::operator*= ( const number factor )

This operator multiplies all entries by a fixed factor.

Definition at line 424 of file lapack_full_matrix.cc.

◆ operator/=()

template<typename number >

LAPACKFullMatrix< number > & LAPACKFullMatrix< number >::operator/= ( const number factor )

This operator divides all entries by a fixed factor.

Definition at line 452 of file lapack_full_matrix.cc.

◆ set()

template<typename number >

void LAPACKFullMatrix< number >::set	(	const size_type	i,
		const size_type	j,
		const number	value
	)

inline

Set a particular entry of the matrix to a value. Thus, calling A.set(1,2,3.141); is entirely equivalent to the operation A(1,2) = 3.141;. This function exists for compatibility with the various sparse matrix objects.

Parameters

i	The row index of the element to be set.
j	The column index of the element to be set.
value	The value to be written into the element.

Definition at line 1013 of file lapack_full_matrix.h.

◆ add()

template<typename number >

void LAPACKFullMatrix< number >::add	(	const number	a,
		const LAPACKFullMatrix< number > &	B
	)

Simple addition of a scaled matrix, i.e. \(\mathbf A \mathrel{+}= a \, \mathbf B\).

Definition at line 483 of file lapack_full_matrix.cc.

◆ rank1_update()

template<typename number >

void LAPACKFullMatrix< number >::rank1_update	(	const number	a,
		const Vector< number > &	v
	)

Perform a rank-1 update of a symmetric matrix \( \mathbf A \leftarrow \mathbf A + a \, \mathbf v \mathbf v^T \).

This function also works for Cholesky factorization. In that case, updating ( \(a>0\)) is performed via Givens rotations, whereas downdating ( \(a<0\)) via hyperbolic rotations. Note that the latter case might lead to a negative definite matrix in which case the error will be thrown (because Cholesky factorizations are only valid for symmetric and positive definite matrices).

Definition at line 610 of file lapack_full_matrix.cc.

◆ apply_givens_rotation()

template<typename number >

void LAPACKFullMatrix< number >::apply_givens_rotation	(	const std::array< number, 3 > &	csr,
		const size_type	i,
		const size_type	k,
		const bool	left = `true`
	)

Apply Givens rotation csr (a triplet of cosine, sine and radius, see Utilities::LinearAlgebra::givens_rotation() for the definition of the rotation matrix \(\mathbf G\)) to this matrix in the plane spanned by the i'th and k'th unit vectors. If left is true, the rotation is applied from left \(\mathbf A \leftarrow \mathbf G \mathbf A\) and only rows i and k are affected. Otherwise, transpose of the rotation matrix is applied from right \(\mathbf A \leftarrow \mathbf A \mathbf G^T\) and only columns i and k are affected.

Definition at line 305 of file lapack_full_matrix.cc.

◆ copy_from()

template<typename number >

template<typename MatrixType >

void LAPACKFullMatrix< number >::copy_from ( const MatrixType & M )

inline

Assignment from different matrix classes, performing the usual conversion to the transposed format expected by LAPACK. This assignment operator uses iterators of the typename MatrixType. Therefore, sparse matrices are possible sources.

Definition at line 1038 of file lapack_full_matrix.h.

◆ reinit() [1/2]

template<typename number >

void LAPACKFullMatrix< number >::reinit ( const size_type size )

Regenerate the current matrix by one that has the same properties as if it were created by the constructor of this class with the same argument list as this present function.

Definition at line 281 of file lapack_full_matrix.cc.

◆ grow_or_shrink()

template<typename number >

void LAPACKFullMatrix< number >::grow_or_shrink ( const size_type size )

Same as above but will preserve the values of matrix upon resizing. The original values of the matrix are kept on increasing the size

\[ \mathbf A \rightarrow \left( \begin{array}{cc} \mathbf A & \mathbf 0 \\ \mathbf 0 & \mathbf 0 \end{array} \right) \]

Whereas if the new size is smaller, the matrix will contain the upper left block of the original one

\[ \left( \begin{array}{cc} \mathbf A_{11} & \mathbf A_{12} \\ \mathbf A_{21} & \mathbf A_{22} \end{array} \right) \rightarrow \mathbf A_{11} \]

Definition at line 291 of file lapack_full_matrix.cc.

◆ remove_row_and_column()

template<typename number >

void LAPACKFullMatrix< number >::remove_row_and_column	(	const size_type	row,
		const size_type	col
	)

Remove row row and column col from the matrix.

\[ \left( \begin{array}{ccc} \mathbf A_{11} & \mathbf a_{12} & \mathbf A_{13} \\ \mathbf a_{21}^T & a_{22} & \mathbf a_{23}^T \\ \mathbf A_{31} & \mathbf a_{32} & \mathbf A_{33} \end{array} \right) \rightarrow \left( \begin{array}{cc} \mathbf A_{11} & \mathbf A_{13} \\ \mathbf A_{31} & \mathbf A_{33} \end{array} \right) \]

Definition at line 339 of file lapack_full_matrix.cc.

◆ reinit() [2/2]

template<typename number >

void LAPACKFullMatrix< number >::reinit	(	const size_type	rows,
		const size_type	cols
	)

Regenerate the current matrix by one that has the same properties as if it were created by the constructor of this class with the same argument list as this present function.

Definition at line 366 of file lapack_full_matrix.cc.

◆ set_property()

template<typename number >

void LAPACKFullMatrix< number >::set_property ( const LAPACKSupport::Property property )

Assign property to this matrix.

Definition at line 1388 of file lapack_full_matrix.cc.

◆ m()

template<typename number >

LAPACKFullMatrix< number >::size_type LAPACKFullMatrix< number >::m

inline

Return the dimension of the codomain (or range) space.

Note: The matrix is of dimension \(m \times n\).

Definition at line 1023 of file lapack_full_matrix.h.

◆ n()

template<typename number >

LAPACKFullMatrix< number >::size_type LAPACKFullMatrix< number >::n

inline

Return the dimension of the domain space.

Note: The matrix is of dimension \(m \times n\).

Definition at line 1030 of file lapack_full_matrix.h.

◆ fill()

template<typename number >

template<typename MatrixType >

void LAPACKFullMatrix< number >::fill	(	const MatrixType &	src,
		const size_type	dst_offset_i = `0`,
		const size_type	dst_offset_j = `0`,
		const size_type	src_offset_i = `0`,
		const size_type	src_offset_j = `0`,
		const number	factor = `1.`,
		const bool	transpose = `false`
	)

inline

Fill rectangular block.

A rectangular block of the matrix src is copied into this. The upper left corner of the block being copied is (src_offset_i,src_offset_j). The upper left corner of the copied block is (dst_offset_i,dst_offset_j). The size of the rectangular block being copied is the maximum size possible, determined either by the size of this or src.

The final two arguments allow to enter a multiple of the source or its transpose.

Definition at line 1062 of file lapack_full_matrix.h.

◆ vmult() [1/2]

template<typename number >

template<typename number2 >

void LAPACKFullMatrix< number >::vmult	(	Vector< number2 > &	w,
		const Vector< number2 > &	v,
		const bool	adding = `false`
	)		const

Matrix-vector-multiplication.

Depending on previous transformations recorded in state, the result of this function is one of

If state is LAPACKSupport::matrix or LAPACKSupport::inverse_matrix, this will be a regular matrix vector product using LAPACK gemv().
If state is LAPACKSupport::svd or LAPACKSupport::inverse_svd, this function first multiplies with the right transformation matrix, then with the diagonal matrix of singular values or their reciprocal values, and finally with the left transformation matrix.

The optional parameter adding determines, whether the result is stored in the vector \(\mathbf w = \mathbf A \cdot \mathbf v\) or added to it \(\mathbf w \mathrel{+}= \mathbf A \cdot \mathbf v\).

Note: Source and destination must not be the same vector.; The template with number2 only exists for compile-time compatibility with FullMatrix. Only the case number2 = number is implemented due to limitations in the underlying LAPACK interface. All other variants throw an error upon invocation.

Definition at line 1096 of file lapack_full_matrix.h.

◆ vmult() [2/2]

template<typename number >

void LAPACKFullMatrix< number >::vmult	(	Vector< number > &	w,
		const Vector< number > &	v,
		const bool	adding = `false`
	)		const

Specialization of above function for compatible Vector::value_type.

Definition at line 650 of file lapack_full_matrix.cc.

◆ vmult_add() [1/2]

template<typename number >

template<typename number2 >

void LAPACKFullMatrix< number >::vmult_add	(	Vector< number2 > &	w,
		const Vector< number2 > &	v
	)		const

Adding Matrix-vector-multiplication \(\mathbf w \mathrel{+}= \mathbf A \cdot \mathbf v\).

See the documentation of vmult() for details on the implementation.

Definition at line 1109 of file lapack_full_matrix.h.

◆ vmult_add() [2/2]

template<typename number >

void LAPACKFullMatrix< number >::vmult_add	(	Vector< number > &	w,
		const Vector< number > &	v
	)		const

Specialization of above function for compatible Vector::value_type.

Definition at line 923 of file lapack_full_matrix.cc.

◆ Tvmult() [1/2]

template<typename number >

template<typename number2 >

void LAPACKFullMatrix< number >::Tvmult	(	Vector< number2 > &	w,
		const Vector< number2 > &	v,
		const bool	adding = `false`
	)		const

Transpose matrix-vector-multiplication.

The optional parameter adding determines, whether the result is stored in the vector \(\mathbf w = \mathbf A^T \cdot \mathbf v\) or added to it \(\mathbf w \mathrel{+}= \mathbf A^T \cdot \mathbf v\).

See the documentation of vmult() for details on the implementation.

Definition at line 1121 of file lapack_full_matrix.h.

◆ Tvmult() [2/2]

template<typename number >

void LAPACKFullMatrix< number >::Tvmult	(	Vector< number > &	w,
		const Vector< number > &	v,
		const bool	adding = `false`
	)		const

Specialization of above function for compatible Vector::value_type.

Definition at line 785 of file lapack_full_matrix.cc.

◆ Tvmult_add() [1/2]

template<typename number >

template<typename number2 >

void LAPACKFullMatrix< number >::Tvmult_add	(	Vector< number2 > &	w,
		const Vector< number2 > &	v
	)		const

Adding transpose matrix-vector-multiplication \(\mathbf w \mathrel{+}= \mathbf A^T \cdot \mathbf v\).

See the documentation of vmult() for details on the implementation.

Definition at line 1134 of file lapack_full_matrix.h.

◆ Tvmult_add() [2/2]

template<typename number >

void LAPACKFullMatrix< number >::Tvmult_add	(	Vector< number > &	w,
		const Vector< number > &	v
	)		const

Specialization of above function for compatible Vector::value_type.

Definition at line 932 of file lapack_full_matrix.cc.

◆ mmult() [1/2]

template<typename number >

void LAPACKFullMatrix< number >::mmult	(	LAPACKFullMatrix< number > &	C,
		const LAPACKFullMatrix< number > &	B,
		const bool	adding = `false`
	)		const

Matrix-matrix-multiplication.

The optional parameter adding determines, whether the result is stored in the matrix \(\mathbf C = \mathbf A \cdot \mathbf B\) or added to it \(\mathbf C \mathrel{+}= \mathbf A \cdot \mathbf B\).

Note: It is assumed that A and B have compatible sizes and that C already has the right size.

This function uses the BLAS function Xgemm.

Definition at line 941 of file lapack_full_matrix.cc.

◆ mmult() [2/2]

template<typename number >

void LAPACKFullMatrix< number >::mmult	(	FullMatrix< number > &	C,
		const LAPACKFullMatrix< number > &	B,
		const bool	adding = `false`
	)		const

Same as before, but stores the result in a FullMatrix, not in a LAPACKFullMatrix.

Definition at line 975 of file lapack_full_matrix.cc.

◆ Tmmult() [1/3]

template<typename number >

void LAPACKFullMatrix< number >::Tmmult	(	LAPACKFullMatrix< number > &	C,
		const LAPACKFullMatrix< number > &	B,
		const bool	adding = `false`
	)		const

Matrix-matrix-multiplication using transpose of this.

The optional parameter adding determines, whether the result is stored in the matrix \(\mathbf C = \mathbf A^T \cdot \mathbf B\) or added to it \(\mathbf C \mathrel{+}= \mathbf A^T \cdot \mathbf B\).

Note: It is assumed that A and B have compatible sizes and that C already has the right size.; This function uses the BLAS function Xgemm.

Definition at line 1110 of file lapack_full_matrix.cc.

◆ Tmmult() [2/3]

template<typename number >

void LAPACKFullMatrix< number >::Tmmult	(	FullMatrix< number > &	C,
		const LAPACKFullMatrix< number > &	B,
		const bool	adding = `false`
	)		const

Same as before, but stores the result in a FullMatrix, not in a LAPACKFullMatrix.

Definition at line 1167 of file lapack_full_matrix.cc.

◆ Tmmult() [3/3]

template<typename number >

void LAPACKFullMatrix< number >::Tmmult	(	LAPACKFullMatrix< number > &	C,
		const LAPACKFullMatrix< number > &	B,
		const Vector< number > &	V,
		const bool	adding = `false`
	)		const

Matrix-matrix-multiplication using transpose of this and a diagonal vector V.

If the adding=false then the result is stored in the matrix \(\mathbf C = \mathbf A^T \cdot \rm{diag}(\mathbf V) \cdot \mathbf B\) otherwise it is added \(\mathbf C \mathrel{+}= \mathbf A^T \cdot \rm{diag}(\mathbf V) \cdot \mathbf B\).

Note: It is assumed that A, B and V have compatible sizes and that C already has the right size.; This function is not provided by LAPACK. The function first forms \(\rm{diag}(\mathbf V) \cdot \mathbf B\) product and then uses Xgemm function.

Definition at line 1011 of file lapack_full_matrix.cc.

◆ mTmult() [1/2]

template<typename number >

void LAPACKFullMatrix< number >::mTmult	(	LAPACKFullMatrix< number > &	C,
		const LAPACKFullMatrix< number > &	B,
		const bool	adding = `false`
	)		const

Matrix-matrix-multiplication using transpose of B.

The optional parameter adding determines, whether the result is stored in the matrix \(\mathbf C = \mathbf A \cdot \mathbf B^T\) or added to it \(\mathbf C \mathrel{+}= \mathbf A \cdot \mathbf B^T\).

Note: It is assumed that A and B have compatible sizes and that C already has the right size.; This function uses the BLAS function Xgemm.

Definition at line 1202 of file lapack_full_matrix.cc.

◆ mTmult() [2/2]

template<typename number >

void LAPACKFullMatrix< number >::mTmult	(	FullMatrix< number > &	C,
		const LAPACKFullMatrix< number > &	B,
		const bool	adding = `false`
	)		const

Same as before, but stores the result in a FullMatrix, not in a LAPACKFullMatrix.

Definition at line 1260 of file lapack_full_matrix.cc.

◆ TmTmult() [1/2]

template<typename number >

void LAPACKFullMatrix< number >::TmTmult	(	LAPACKFullMatrix< number > &	C,
		const LAPACKFullMatrix< number > &	B,
		const bool	adding = `false`
	)		const

Matrix-matrix-multiplication using transpose of this and B.

The optional parameter adding determines, whether the result is stored in the matrix \(\mathbf C = \mathbf A^T \cdot \mathbf B^T\) or added to it \(\mathbf C \mathrel{+}= \mathbf A^T \cdot \mathbf B^T\).

Note: It is assumed that A and B have compatible sizes and that C already has the right size.; This function uses the BLAS function Xgemm.

Definition at line 1295 of file lapack_full_matrix.cc.

◆ TmTmult() [2/2]

template<typename number >

void LAPACKFullMatrix< number >::TmTmult	(	FullMatrix< number > &	C,
		const LAPACKFullMatrix< number > &	B,
		const bool	adding = `false`
	)		const

Same as before, but stores the result in a FullMatrix, not in a LAPACKFullMatrix.

Definition at line 1329 of file lapack_full_matrix.cc.

◆ transpose()

template<typename number >

void LAPACKFullMatrix< number >::transpose ( LAPACKFullMatrix< number > & B ) const

Performs out-place transposition. Matrix B should be appropriately sized.

Note: for complex number types, conjugate transpose will be performed.; If deal.II is configured with Intel-MKL, mkl_?omatcopy will be used, otherwise transposition is done element by element.

Definition at line 1073 of file lapack_full_matrix.cc.

◆ scale_rows()

template<typename number >

void LAPACKFullMatrix< number >::scale_rows ( const Vector< number > & V )

Scale rows of this matrix by V . This is equivalent to premultiplication with a diagonal matrix \(\mathbf A\leftarrow {\rm diag}(\mathbf V)\mathbf A\).

Definition at line 1093 of file lapack_full_matrix.cc.

◆ compute_lu_factorization()

template<typename number >

void LAPACKFullMatrix< number >::compute_lu_factorization

Compute the LU factorization of the matrix using LAPACK function Xgetrf.

Definition at line 1364 of file lapack_full_matrix.cc.

◆ compute_cholesky_factorization()

template<typename number >

void LAPACKFullMatrix< number >::compute_cholesky_factorization

Compute the Cholesky factorization of the matrix using LAPACK function Xpotrf.

Note: The factorization is stored in the lower-triangular part of the matrix.

Definition at line 1478 of file lapack_full_matrix.cc.

◆ reciprocal_condition_number() [1/2]

template<typename number >

number LAPACKFullMatrix< number >::reciprocal_condition_number ( const number l1_norm ) const

Estimate the reciprocal of the condition number \(1/k(\mathbf A)\) in \(L_1\) norm ( \(1/(||\mathbf A||_1 \, ||\mathbf A^{-1}||_1)\)) of a symmetric positive definite matrix using Cholesky factorization. This function can only be called if the matrix is already factorized.

Note: The condition number \(k(\mathbf A)\) can be used to estimate the numerical error related to the matrix inversion or the solution of the system of linear algebraic equations as error = std::numeric_limits<Number>::epsilon * k. Alternatively one can get the number of accurate digits std::floor(std::log10(k)).; The function computes reciprocal of the condition number to avoid possible overflow if the matrix is nearly singular.

void LAPACKFullMatrix< number >::solve	(	Vector< number > &	v,
		const bool	transposed = `false`
	)		const

Solve the linear system with right hand side v and put the solution back to v. The matrix should be either triangular or LU/Cholesky factorization should be previously computed.

The flag transposed indicates whether the solution of the transposed system is to be performed.

Definition at line 1739 of file lapack_full_matrix.cc.

◆ solve() [2/2]

template<typename number >

void LAPACKFullMatrix< number >::solve	(	LAPACKFullMatrix< number > &	B,
		const bool	transposed = `false`
	)		const

Same as above but for multiple right hand sides (as many as there are columns in the matrix B).

Definition at line 1782 of file lapack_full_matrix.cc.

◆ compute_eigenvalues()

template<typename number >

void LAPACKFullMatrix< number >::compute_eigenvalues	(	const bool	right_eigenvectors = `false`,
		const bool	left_eigenvectors = `false`
	)

Compute eigenvalues of the matrix. After this routine has been called, eigenvalues can be retrieved using the eigenvalue() function. The matrix itself will be LAPACKSupport::unusable after this operation.

The optional arguments allow to compute left and right eigenvectors as well.

Note that the function does not return the computed eigenvalues right away since that involves copying data around between the output arrays of the LAPACK functions and any return array. This is often unnecessary since one may not be interested in all eigenvalues at once, but for example only the extreme ones. In that case, it is cheaper to just have this function compute the eigenvalues and have a separate function that returns whatever eigenvalue is requested.

Note: Calls the LAPACK function Xgeev.

Definition at line 1881 of file lapack_full_matrix.cc.

◆ compute_eigenvalues_symmetric()

template<typename number >

void LAPACKFullMatrix< number >::compute_eigenvalues_symmetric	(	const number	lower_bound,
		const number	upper_bound,
		const number	abs_accuracy,
		Vector< number > &	eigenvalues,
		FullMatrix< number > &	eigenvectors
	)

Compute eigenvalues and eigenvectors of a real symmetric matrix. Only eigenvalues in the interval \((\rm{lower\_bound}, \rm{upper\_bound}]\) are computed with the absolute tolerance \(\rm abs\_accuracy\). An approximate eigenvalue is accepted as converged when it is determined to lie in an interval \([a,b]\) of width less than or equal to \(\rm{abs\_accuracy} + eps * \rm{max}(|a|,|b|)\), where \(eps\) is the machine precision. If \(\rm{abs\_accuracy}\) is less than or equal to zero, then \(eps\,|\mathbf{T}|_1\) will be used in its place, where \(|\mathbf{T}|_1\) is the 1-norm of the tridiagonal matrix obtained by reducing \(\mathbf A\) to tridiagonal form. Eigenvalues will be computed most accurately when \(\rm{abs\_accuracy}\) is set to twice the underflow threshold, not zero. After this routine has been called, all eigenvalues in \((\rm{lower\_bound}, \rm{upper\_bound}]\) will be stored in eigenvalues and the corresponding eigenvectors will be stored in the columns of eigenvectors, whose dimension is set accordingly.

Note: Calls the LAPACK function Xsyevx.

Definition at line 1961 of file lapack_full_matrix.cc.

◆ compute_generalized_eigenvalues_symmetric() [1/2]

template<typename number >

void LAPACKFullMatrix< number >::compute_generalized_eigenvalues_symmetric	(	LAPACKFullMatrix< number > &	B,
		const number	lower_bound,
		const number	upper_bound,
		const number	abs_accuracy,
		Vector< number > &	eigenvalues,
		std::vector< Vector< number >> &	eigenvectors,
		const types::blas_int	itype = `1`
	)

Compute generalized eigenvalues and eigenvectors of a real generalized symmetric eigenproblem of the form

itype = 1: \(\mathbf A \cdot \mathbf x=\lambda \mathbf B \cdot \mathbf x\)
itype = 2: \(\mathbf A \cdot \mathbf B \cdot \mathbf x=\lambda \mathbf x\)
itype = 3: \(\mathbf B \cdot \mathbf A \cdot \mathbf x=\lambda \mathbf x\)

where \(\mathbf A\) is this matrix. \(\mathbf A\) and \(\mathbf B\) are assumed to be symmetric, and \(\mathbf B\) has to be positive definite. Only eigenvalues in the interval \((\rm{lower\_bound}, \rm{upper\_bound}]\) are computed with the absolute tolerance \(\rm{abs\_accuracy}\). An approximate eigenvalue is accepted as converged when it is determined to lie in an interval \([a,b]\) of width less than or equal to \(\rm{abs\_accuracy} + eps * \rm{max}( |a|,|b| )\), where \(eps\) is the machine precision. If \(\rm{abs\_accuracy}\) is less than or equal to zero, then \(eps \, |\mathbf{T}|_1\) will be used in its place, where \(|\mathbf{T}|_1\) is the 1-norm of the tridiagonal matrix obtained by reducing \(\mathbf A\) to tridiagonal form. Eigenvalues will be computed most accurately when \(\rm{abs\_accuracy}\) is set to twice the underflow threshold, not zero. After this routine has been called, all eigenvalues in \((\rm{lower\_bound}, \rm{upper\_bound}]\) will be stored in eigenvalues and the corresponding eigenvectors will be stored in eigenvectors, whose dimension is set accordingly.

Note: Calls the LAPACK function Xsygvx.

Definition at line 2072 of file lapack_full_matrix.cc.

◆ compute_generalized_eigenvalues_symmetric() [2/2]

template<typename number >

void LAPACKFullMatrix< number >::compute_generalized_eigenvalues_symmetric	(	LAPACKFullMatrix< number > &	B,
		std::vector< Vector< number >> &	eigenvectors,
		const types::blas_int	itype = `1`
	)

Same as the other compute_generalized_eigenvalues_symmetric function except that all eigenvalues are computed and the tolerance is set automatically. Note that this function does not return the computed eigenvalues right away since that involves copying data around between the output arrays of the LAPACK functions and any return array. This is often unnecessary since one may not be interested in all eigenvalues at once, but for example only the extreme ones. In that case, it is cheaper to just have this function compute the eigenvalues and have a separate function that returns whatever eigenvalue is requested. Eigenvalues can be retrieved using the eigenvalue() function. The number of computed eigenvectors is equal to eigenvectors.size()

Note: Calls the LAPACK function Xsygv.

Definition at line 2197 of file lapack_full_matrix.cc.

◆ compute_svd()

template<typename number >

void LAPACKFullMatrix< number >::compute_svd

Compute the singular value decomposition of the matrix using LAPACK function Xgesdd.

Requires that the state is LAPACKSupport::matrix, fills the data members wr, svd_u, and svd_vt, and leaves the object in the state LAPACKSupport::svd.

The singular value decomposition factorizes the provided matrix (A) into three parts: U, sigma, and the transpose of V (V^T), such that A = U sigma V^T. Sigma is a MxN matrix which contains the singular values of A on the diagonal while all the other elements are zero. U is a MxM orthogonal matrix containing the left singular vectors corresponding to the singular values of A. V is a NxN orthonal matrix containing the right singular vectors corresponding the singular values of A.

Note that the variable svd_vt contains the tranpose of V and can be accessed by get_svd_vt(), while U is accessed with get_svd_u().

Definition at line 1576 of file lapack_full_matrix.cc.

◆ compute_inverse_svd()

template<typename number >

void LAPACKFullMatrix< number >::compute_inverse_svd ( const double threshold = 0. )

Compute the inverse of the matrix by singular value decomposition.

Requires that state is either LAPACKSupport::matrix or LAPACKSupport::svd. In the first case, this function calls compute_svd(). After this function, the object will have the state LAPACKSupport::inverse_svd.

For a singular value decomposition, the inverse is simply computed by replacing all singular values by their reciprocal values. If the matrix does not have maximal rank, singular values 0 are not touched, thus computing the minimal norm right inverse of the matrix.

The parameter threshold determines, when a singular value should be considered zero. It is the ratio of the smallest to the largest nonzero singular value \(s_{max}\). Thus, the inverses of all singular values less than \(s_{max}/\rm{threshold}\) will be set to zero.

Definition at line 1652 of file lapack_full_matrix.cc.

template<typename number >

void LAPACKFullMatrix< number >::print_formatted	(	std::ostream &	out,
		const unsigned int	precision = `3`,
		const bool	scientific = `true`,
		const unsigned int	width = `0`,
		const char *	zero_string = `" "`,
		const double	denominator = `1.`,
		const double	threshold = `0.`
	)		const

Print the matrix and allow formatting of entries.

The parameters allow for a flexible setting of the output format:

Parameters

out	This specifies the stream to write to.
precision	denotes the number of trailing digits.
scientific	is used to determine the number format, where `scientific = false` means fixed point notation.
width	denotes the with of each column. A zero entry for `width` makes the function compute a width, but it may be changed to a positive value, if output is crude.
zero_string	specifies a string printed for zero entries.
denominator	Multiply the whole matrix by this common denominator to get nicer numbers.
threshold	all entries with absolute value smaller than this are considered zero.

Note: The entries stored resemble a matrix only if the state is either LAPACKSupport::matrix or LAPACK::inverse_matrix. Otherwise, calling this function is not allowed.

Definition at line 2289 of file lapack_full_matrix.cc.

◆ norm()

template<typename number >

number LAPACKFullMatrix< number >::norm ( const char type ) const

private

Internal function to compute various norms.

Definition at line 1427 of file lapack_full_matrix.cc.

Member Data Documentation

◆ state

template<typename number >

LAPACKSupport::State LAPACKFullMatrix< number >::state

private

Since LAPACK operations notoriously change the meaning of the matrix entries, we record the current state after the last operation here.

Definition at line 908 of file lapack_full_matrix.h.

◆ property

template<typename number >

LAPACKSupport::Property LAPACKFullMatrix< number >::property

private

Additional property of the matrix which may help to select more efficient LAPACK functions.

Definition at line 914 of file lapack_full_matrix.h.

◆ work

template<typename number >

std::vector<number> LAPACKFullMatrix< number >::work

mutableprivate

The working array used for some LAPACK functions.

Definition at line 919 of file lapack_full_matrix.h.

◆ iwork

template<typename number >

std::vector<types::blas_int> LAPACKFullMatrix< number >::iwork

mutableprivate

Integer working array used for some LAPACK functions.

Definition at line 924 of file lapack_full_matrix.h.

◆ ipiv

template<typename number >

template<typename number >

std::mutex LAPACKFullMatrix< number >::mutex

mutableprivate

Thread mutex.

Definition at line 976 of file lapack_full_matrix.h.

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

include/deal.II/lac/lapack_full_matrix.h
source/lac/lapack_full_matrix.cc

Public Types

Public Member Functions

Private Member Functions

Private Attributes

Additional Inherited Members

Detailed Description

template<typename number> class LAPACKFullMatrix< number >

Member Typedef Documentation

◆ size_type

Constructor & Destructor Documentation

◆ LAPACKFullMatrix() [1/3]

◆ LAPACKFullMatrix() [2/3]

◆ LAPACKFullMatrix() [3/3]

Member Function Documentation

◆ operator=() [1/4]

◆ operator=() [2/4]

◆ operator=() [3/4]

◆ operator=() [4/4]

◆ operator*=()

◆ operator/=()

◆ set()

◆ add()

◆ rank1_update()

◆ apply_givens_rotation()

◆ copy_from()

◆ reinit() [1/2]

◆ grow_or_shrink()

◆ remove_row_and_column()

◆ reinit() [2/2]

◆ set_property()

◆ m()

◆ n()

◆ fill()

◆ vmult() [1/2]

◆ vmult() [2/2]

◆ vmult_add() [1/2]

◆ vmult_add() [2/2]

◆ Tvmult() [1/2]

◆ Tvmult() [2/2]

◆ Tvmult_add() [1/2]

◆ Tvmult_add() [2/2]

◆ mmult() [1/2]

◆ mmult() [2/2]

◆ Tmmult() [1/3]

◆ Tmmult() [2/3]

◆ Tmmult() [3/3]

◆ mTmult() [1/2]

◆ mTmult() [2/2]

◆ TmTmult() [1/2]

◆ TmTmult() [2/2]

◆ transpose()

◆ scale_rows()

◆ compute_lu_factorization()

◆ compute_cholesky_factorization()

◆ reciprocal_condition_number() [1/2]

◆ reciprocal_condition_number() [2/2]

◆ determinant()

◆ l1_norm()

◆ linfty_norm()

◆ frobenius_norm()

◆ trace()

◆ invert()

◆ solve() [1/2]

◆ solve() [2/2]

◆ compute_eigenvalues()

◆ compute_eigenvalues_symmetric()

◆ compute_generalized_eigenvalues_symmetric() [1/2]

◆ compute_generalized_eigenvalues_symmetric() [2/2]

◆ compute_svd()

◆ compute_inverse_svd()

◆ compute_inverse_svd_with_kernel()

◆ eigenvalue()

◆ singular_value()

◆ get_svd_u()

◆ get_svd_vt()

◆ print_formatted()

◆ norm()

Member Data Documentation

◆ state

◆ property

template<typename number>
class LAPACKFullMatrix< number >