Computes several unary operations on general matrices. More...

#include <EvaluateLinearAlgebraUnaryAlgo.h>

Inheritance diagram for EvaluateLinearAlgebraUnaryAlgorithm:

Public Types
enum	Operator { NEGATE, TRANSPOSE, SCALAR_MULTIPLY }

typedef SCIRun::Core::Datatypes::DenseMatrixConstHandle	Inputs

typedef boost::tuple< Operator, boost::optional< double > >	Parameters

typedef SCIRun::Core::Datatypes::DenseMatrixHandle	Outputs

Public Types inherited from HasId< IdType, IdGenerator >
typedef IdType	id_type

Public Types inherited from AlgorithmStatusReporter
typedef boost::function< void(double)>	UpdaterFunc

Public Member Functions
	EvaluateLinearAlgebraUnaryAlgorithm ()

Outputs	run (const Inputs &matrix, const Parameters &params) const

AlgorithmOutput	run_generic (const AlgorithmInput &input) const

Public Member Functions inherited from AlgorithmBase
virtual	~AlgorithmBase ()

Public Member Functions inherited from AlgorithmParameterList
	AlgorithmParameterList ()

bool	set (const AlgorithmParameterName &key, const AlgorithmParameter::Value &value)

const AlgorithmParameter &	get (const AlgorithmParameterName &key) const

bool	set_option (const AlgorithmParameterName &key, const std::string &value)

bool	get_option (const AlgorithmParameterName &key, std::string &value) const

std::string	get_option (const AlgorithmParameterName &key) const

bool	check_option (const AlgorithmParameterName &key, const std::string &value) const

virtual bool	keyNotFoundPolicy (const AlgorithmParameterName &key)

Public Member Functions inherited from AlgorithmInterface
virtual	~AlgorithmInterface ()

Public Member Functions inherited from HasId< IdType, IdGenerator >
	HasId ()

IdType	id () const

Public Member Functions inherited from AlgorithmLogger
	AlgorithmLogger ()

	~AlgorithmLogger ()

void	setLogger (Core::Logging::LoggerHandle logger)

virtual void	error (const std::string &error) const
	functions for the algorithm, so it can forward errors if needed More...

virtual void	warning (const std::string &warning) const

virtual void	remark (const std::string &remark) const

virtual void	status (const std::string &status) const

Public Member Functions inherited from LegacyLoggerInterface
virtual	~LegacyLoggerInterface ()

Public Member Functions inherited from AlgorithmStatusReporter
	AlgorithmStatusReporter ()

	~AlgorithmStatusReporter ()

virtual void	report_start (const std::string &tag) const

virtual void	report_end () const

virtual void	update_progress (double percent) const

void	setUpdaterFunc (UpdaterFunc func)

UpdaterFunc	getUpdaterFunc () const

Public Member Functions inherited from ProgressReporter
virtual	~ProgressReporter ()

template<typename T1 , typename T2 >
void	update_progress_max (T1 current, T2 max) const

Additional Inherited Members
Protected Member Functions inherited from AlgorithmParameterList
void	dumpAlgoState () const

void	addParameter (const AlgorithmParameterName &key, const AlgorithmParameter::Value &defaultValue)

void	add_option (const AlgorithmParameterName &key, const std::string &defval, const std::string &options)

Detailed Description

Computes several unary operations on general matrices.

Template Parameters

_MatrixType the type of the matrix of which we are computing the eigendecomposition; this is expected to be an instantiation of the Matrix class template. Currently, only real matrices are supported.

The eigenvalues and eigenvectors of a matrix $ A $ are scalars $\lambda$ and vectors $ v $ such that $Av = \lambda v$ . If $ D $ is a diagonal matrix with the eigenvalues on the diagonal, and $ V $ is a matrix with the eigenvectors as its columns, then $ A V = V D $ . The matrix $ V $ is almost always invertible, in which case we have $A = V D V^{-1}$ . This is called the eigendecomposition.

Call the function compute() to compute the eigenvalues and eigenvectors of a given matrix. Alternatively, you can use the EigenSolver(const MatrixType&, bool) constructor which computes the eigenvalues and eigenvectors at construction time. Once the eigenvalue and eigenvectors are computed, they can be retrieved with the eigenvalues() and eigenvectors() functions. The pseudoEigenvalueMatrix() and pseudoEigenvectors() methods allow the construction of the pseudo-eigendecomposition.

The documentation for EigenSolver(const MatrixType&, bool) contains an example of the typical use of this class.

Note: The implementation is adapted from JAMA (public domain). Their code is based on EISPACK.

See Also: MatrixBase::eigenvalues(), class ComplexEigenSolver, class SelfAdjointEigenSolver

Member Typedef Documentation

typedef SCIRun::Core::Datatypes::DenseMatrixConstHandle Inputs

typedef SCIRun::Core::Datatypes::DenseMatrixHandle Outputs

typedef boost::tuple<Operator, boost::optional<double> > Parameters

Member Enumeration Documentation

enum Operator

Enumerator
NEGATE
TRANSPOSE
SCALAR_MULTIPLY

Constructor & Destructor Documentation

EvaluateLinearAlgebraUnaryAlgorithm ( )

Member Function Documentation

EvaluateLinearAlgebraUnaryAlgorithm::Outputs run	(	const Inputs &	matrix,
		const Parameters &	params
	)		const

Todo:: : absolutely need matrix move semantics here!!!!!!!

AlgorithmOutput run_generic ( const AlgorithmInput & input ) const

virtual

Implements AlgorithmInterface.

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

Core/Algorithms/Math/EvaluateLinearAlgebraUnaryAlgo.h
Core/Algorithms/Math/EvaluateLinearAlgebraUnaryAlgo.cc

Public Types

Public Member Functions

Additional Inherited Members

Detailed Description

Member Typedef Documentation

Member Enumeration Documentation

Constructor & Destructor Documentation

Member Function Documentation