A maximum likelihood estimation strategy for classification (a.k.a. MaxVer in portuguese). More...

#include <ClassifierMaxLikelihoodStrategy.h>

Inheritance diagram for te::rp::ClassifierMaxLikelihoodStrategy:

Classes
class	Parameters
	Classifier Parameters. More...

Public Member Functions
	ClassifierMaxLikelihoodStrategy ()

void	enableMultiThread (const bool &enable)
	Enable / disable the use of multiple threads. More...

void	enableOutputPalette (const bool enabled)
	Enable (true) or disable (false) the creation of a paletted output raster. More...

void	enableProgressInterface (const bool &enable)
	Enable / disable the progress interface. More...

void	enableRasterCache (const bool &enable)
	Enable / disable the use of raster data cache. More...

bool	execute ()
	Executes the classification strategy. More...

const std::string &	getErrorMessage () const
	Return the current error message if there is any. More...

void	getMetaData (std::map< std::string, std::string > &metadata) const
	Returns strategy-dependent metadata. More...

unsigned int	getOutputNumberBands (void)

virtual ClassifierStrategyOutParameters const *	getOutputParameters () const
	Returns a pointer to the strategy output execution parameters or a null pointer if there are none. More...

bool	initialize (ClassifierStrategyParameters const *const strategyParams)
	Initialize the classification strategy. More...

std::unique_ptr< te::rst::Raster >	releaseOutputRaster ()
	Returns a pointer to the output raster or a void pointer if there is none. More...

void	setInputPolygons (const std::vector< te::gm::Polygon * > &polygonsPtrs)
	Set the input polygons. More...

void	setInputRaster (const te::rst::Raster &raster)
	Set the input raster. More...

void	setInputRasterBands (const std::vector< unsigned int > &rasterBands)
	Set the input raste bandsr. More...

void	setUserOutputPalette (std::vector< te::rst::BandProperty::ColorEntry > &userPalette)
	Set the output user palette. More...

	~ClassifierMaxLikelihoodStrategy ()

Protected Member Functions
bool	applyICM (const te::rst::Raster &inputRaster, std::unique_ptr< te::rp::Matrix< unsigned int > > &matrixPtr, const unsigned int classifiedMatrixNoDataValue, std::string &errorMessage) const
	Apply an ICM filter. More...

bool	createOutputRaster (const std::vector< int > &bandsDataTypes, const std::vector< double > &noDataValues)
	Create the output raster using the EXPANSIBLE driver. More...

bool	getICMBeta (const te::rp::Matrix< unsigned int > &matrix, const unsigned int matrixNoDataValue, double &betaValue, std::string &errorMessage) const
	Iteration Beta value Calule. More...

virtual void	reset ()
	Reset to an initial state. More...

double	rtbis (double(func)(double x, double param), double *param) const
	Metodo da biseccao para achar os zeros de uma funcao de dupla precisao com parametros. Numerical Recipes in C cap 9. Versao del 22 de agosto de 1990. INPE. O vetor (double)param contem os seguintes valores: param[0] = o minimo do intervalo de procura param[1] = o maximo do intervalo de procura param[2] = a tolerancia param[3] ... param[n] = parametros da funcao. More...

void	setErrorMessage (const std::string &newErrorMessage)
	Set the current error message. More...

bool	setOutputRasterPalette (const unsigned int size)
	Create and set the output raster palette folowing the current internal settings. More...

Static Protected Member Functions
static int	compara_uchar_vesre (const void x, const void y)

static void	Estimacao_geral (double *term, const te::rp::Matrix< unsigned int > &matrix)
	Compute the common part in pseudo-likelihood equation. More...

static double	plikehood_2 (double, double *)

static double	plikehood_3 (double, double *)

static double	plikehood_4 (double, double *)

static double	sigmo (double a)

Protected Attributes
bool	m_createRasterPalette
	Enable (true) or disable (false) the creation of a paletted output raster. More...

bool	m_enableMultiThread
	Enable or disable the use multipe threads. More...

bool	m_enableRasterCache
	Enable or disable the use a raster data cache. More...

te::cl::MaxLikelihood	m_genClassInstance
	A generir classifier instance. More...

Parameters::ClassIDT	m_highestTrainClassID
	The highest train sample lable. More...

ClassifierMaxLikelihoodStrategy::Parameters	m_initParams
	Initialization parameters. More...

std::vector< te::gm::Polygon * > const *	m_inputPolygonsPtr
	Input polygons. More...

std::vector< unsigned int >	m_inputRasterBands
	Input raster bands. More...

te::rst::Raster const *	m_inputRasterPtr
	A pointer to the input raster. More...

bool	m_isInitialized
	Is this instance initialized? More...

std::map< std::string, std::string >	m_metaData
	Strategy-dependent metadata. More...

std::unique_ptr< te::rst::Raster >	m_outputRasterPtr
	A pointer to the output raster. More...

bool	m_progressInterfaceEnabled
	Progress interface status. More...

std::vector< te::rst::BandProperty::ColorEntry >	m_userOutputPalette
	User output raster palette (it must be large enough to accomodate all classifyier generated classes or an empty vector to automatically generate an random palette. More...

Private Attributes
std::string	m_errorMessage
	Current error message. More...

Detailed Description

A maximum likelihood estimation strategy for classification (a.k.a. MaxVer in portuguese).

See also: te::cl::MaxLikelihood class docs

Definition at line 55 of file ClassifierMaxLikelihoodStrategy.h.

Constructor & Destructor Documentation

◆ ClassifierMaxLikelihoodStrategy()

te::rp::ClassifierMaxLikelihoodStrategy::ClassifierMaxLikelihoodStrategy ( )

◆ ~ClassifierMaxLikelihoodStrategy()

te::rp::ClassifierMaxLikelihoodStrategy::~ClassifierMaxLikelihoodStrategy ( )

Member Function Documentation

◆ applyICM()

bool te::rp::ClassifierMaxLikelihoodStrategy::applyICM	(	const te::rst::Raster &	inputRaster,
		std::unique_ptr< te::rp::Matrix< unsigned int > > &	matrixPtr,
		const unsigned int	classifiedMatrixNoDataValue,
		std::string &	errorMessage
	)		const

protected

Apply an ICM filter.

Parameters

inputRaster	Input raster.
matrixPtr	A pointer to a input/output classified matrix (the pointer may be reassigned if required).
classifiedMatrixNoDataValue	Matrix no-data value.
errorMessage	Error message.

Returns: true if OK, false on errors;

◆ compara_uchar_vesre()

static int te::rp::ClassifierMaxLikelihoodStrategy::compara_uchar_vesre	(	const void *	x,
		const void *	y
	)

staticprotected

◆ createOutputRaster()

bool te::rp::ClassifierStrategy::createOutputRaster	(	const std::vector< int > &	bandsDataTypes,
		const std::vector< double > &	noDataValues
	)

protectedinherited

Create the output raster using the EXPANSIBLE driver.

Parameters

bandsDataTypes	Bands data types.
noDataValues	A vector of no-data values for each band.

Returns: true if ok,false on errors.

Note: A pointer to the created raster will be handled by m_outputRasterPtr.

◆ enableMultiThread()

void te::rp::ClassifierStrategy::enableMultiThread ( const bool & enable )

inherited

Enable / disable the use of multiple threads.

Parameters

enable Enable (true) or disable (false) the use of multiple threads.

◆ enableOutputPalette()

void te::rp::ClassifierStrategy::enableOutputPalette ( const bool enabled )

inherited

Enable (true) or disable (false) the creation of a paletted output raster.

Parameters

enabled Enable (true) or disable (false) the creation of a paletted output raster.

◆ enableProgressInterface()

void te::rp::ClassifierStrategy::enableProgressInterface ( const bool & enable )

inherited

Enable / disable the progress interface.

Parameters

enable Enable (true) or disable (false) the progress interface.

◆ enableRasterCache()

void te::rp::ClassifierStrategy::enableRasterCache ( const bool & enable )

inherited

Enable / disable the use of raster data cache.

Parameters

enable Enable (true) or disable (false) the use of raster cache.

◆ Estimacao_geral()

static void te::rp::ClassifierMaxLikelihoodStrategy::Estimacao_geral	(	double *	term,
		const te::rp::Matrix< unsigned int > &	matrix
	)

staticprotected

Compute the common part in pseudo-likelihood equation.

Parameters

img_box	: image to process.
term	: comom part

◆ execute()

bool te::rp::ClassifierMaxLikelihoodStrategy::execute ( )

virtual

Executes the classification strategy.

Returns: true if OK, false on errors.

Implements te::rp::ClassifierStrategy.

◆ getErrorMessage()

const std::string& te::rp::ClassifierStrategy::getErrorMessage ( ) const

inherited

Return the current error message if there is any.

Returns: Return the current error message if there is any.

◆ getICMBeta()

bool te::rp::ClassifierMaxLikelihoodStrategy::getICMBeta	(	const te::rp::Matrix< unsigned int > &	matrix,
		const unsigned int	matrixNoDataValue,
		double &	betaValue,
		std::string &	errorMessage
	)		const

protected

Iteration Beta value Calule.

Parameters

matrix	Current classified matrix.
matrixNoDataValue	Matrix no-data value.
errorMessage	Error message.

Returns: true if OK, false on errors;

◆ getMetaData()

void te::rp::ClassifierStrategy::getMetaData ( std::map< std::string, std::string > & metadata ) const

inherited

Returns strategy-dependent metadata.

Parameters

metadata Strategy-dependent metadata.

◆ getOutputNumberBands()

unsigned int te::rp::ClassifierMaxLikelihoodStrategy::getOutputNumberBands ( void )

◆ getOutputParameters()

virtual ClassifierStrategyOutParameters const* te::rp::ClassifierStrategy::getOutputParameters ( ) const

virtualinherited

Returns a pointer to the strategy output execution parameters or a null pointer if there are none.

Returns: Returns a pointer to the strategy output execution parameters or a null pointer if there are none.

Reimplemented in te::rp::ClassifierMAPStrategy.

◆ initialize()

bool te::rp::ClassifierMaxLikelihoodStrategy::initialize ( ClassifierStrategyParameters const *const strategyParams )

virtual

Initialize the classification strategy.

Parameters

strategyParams A pointer to the user given specific classification strategy parameters ou NULL if no parameters are present.

Returns: true if OK, false on errors.

Implements te::rp::ClassifierStrategy.

◆ plikehood_2()

static double te::rp::ClassifierMaxLikelihoodStrategy::plikehood_2	(	double	,
		double *
	)

staticprotected

◆ plikehood_3()

static double te::rp::ClassifierMaxLikelihoodStrategy::plikehood_3	(	double	,
		double *
	)

staticprotected

◆ plikehood_4()

static double te::rp::ClassifierMaxLikelihoodStrategy::plikehood_4	(	double	,
		double *
	)

staticprotected

◆ releaseOutputRaster()

std::unique_ptr< te::rst::Raster > te::rp::ClassifierStrategy::releaseOutputRaster ( )

inherited

Returns a pointer to the output raster or a void pointer if there is none.

Returns: Returns a pointer to the output raster or a void pointer if there is none.

Note: The caller of this method must take the ownership of the returned object.

◆ reset()

virtual void te::rp::ClassifierStrategy::reset ( )

protectedvirtualinherited

Reset to an initial state.

◆ rtbis()

double te::rp::ClassifierMaxLikelihoodStrategy::rtbis	(	double()(double x, double param)	func,
		double *	param
	)		const

protected

Metodo da biseccao para achar os zeros de uma funcao de dupla precisao com parametros. Numerical Recipes in C cap 9. Versao del 22 de agosto de 1990. INPE. O vetor (double)param contem os seguintes valores: param[0] = o minimo do intervalo de procura param[1] = o maximo do intervalo de procura param[2] = a tolerancia param[3] ... param[n] = parametros da funcao.

Note: Imported from SPRING

◆ setErrorMessage()

void te::rp::ClassifierStrategy::setErrorMessage ( const std::string & newErrorMessage )

protectedinherited

Set the current error message.

Parameters

newErrorMessage New error message;

◆ setInputPolygons()

void te::rp::ClassifierStrategy::setInputPolygons ( const std::vector< te::gm::Polygon * > & polygonsPtrs )

inherited

Set the input polygons.

Parameters

polygonsPtrs Input polygons pointers.

Note: The caller of this method must keep the ownership of the objects.

◆ setInputRaster()

void te::rp::ClassifierStrategy::setInputRaster ( const te::rst::Raster & raster )

inherited

Set the input raster.

Parameters

raster Input raster.

◆ setInputRasterBands()

void te::rp::ClassifierStrategy::setInputRasterBands ( const std::vector< unsigned int > & rasterBands )

inherited

Set the input raste bandsr.

Parameters

rasterBands Input raster bands.

◆ setOutputRasterPalette()

bool te::rp::ClassifierStrategy::setOutputRasterPalette ( const unsigned int size )

protectedinherited

Create and set the output raster palette folowing the current internal settings.

Parameters

size	Palette size.

Returns: true if ok,false on errors.

◆ setUserOutputPalette()

void te::rp::ClassifierStrategy::setUserOutputPalette ( std::vector< te::rst::BandProperty::ColorEntry > & userPalette )

inherited

Set the output user palette.

Parameters

userPalette User output raster palette (it must be large enough to accomodate all classifyier generated classes or an empty vector to automatically generate an random palette.

◆ sigmo()

static double te::rp::ClassifierMaxLikelihoodStrategy::sigmo ( double a )

staticprotected

Member Data Documentation

◆ m_createRasterPalette

bool te::rp::ClassifierStrategy::m_createRasterPalette

protectedinherited

Enable (true) or disable (false) the creation of a paletted output raster.

Definition at line 172 of file ClassifierStrategy.h.

◆ m_enableMultiThread

bool te::rp::ClassifierStrategy::m_enableMultiThread

protectedinherited

Enable or disable the use multipe threads.

Definition at line 167 of file ClassifierStrategy.h.

◆ m_enableRasterCache

bool te::rp::ClassifierStrategy::m_enableRasterCache

protectedinherited

Enable or disable the use a raster data cache.

Definition at line 162 of file ClassifierStrategy.h.

◆ m_errorMessage

std::string te::rp::ClassifierStrategy::m_errorMessage

privateinherited

Current error message.

Definition at line 236 of file ClassifierStrategy.h.

◆ m_genClassInstance

te::cl::MaxLikelihood te::rp::ClassifierMaxLikelihoodStrategy::m_genClassInstance

protected

A generir classifier instance.

Definition at line 123 of file ClassifierMaxLikelihoodStrategy.h.

◆ m_highestTrainClassID

Parameters::ClassIDT te::rp::ClassifierMaxLikelihoodStrategy::m_highestTrainClassID

protected

The highest train sample lable.

Definition at line 119 of file ClassifierMaxLikelihoodStrategy.h.

◆ m_initParams

ClassifierMaxLikelihoodStrategy::Parameters te::rp::ClassifierMaxLikelihoodStrategy::m_initParams

protected

Initialization parameters.

Definition at line 121 of file ClassifierMaxLikelihoodStrategy.h.

◆ m_inputPolygonsPtr

std::vector<te::gm::Polygon*> const* te::rp::ClassifierStrategy::m_inputPolygonsPtr

protectedinherited

Input polygons.

Definition at line 187 of file ClassifierStrategy.h.

◆ m_inputRasterBands

std::vector<unsigned int> te::rp::ClassifierStrategy::m_inputRasterBands

protectedinherited

Input raster bands.

Definition at line 182 of file ClassifierStrategy.h.

◆ m_inputRasterPtr

te::rst::Raster const* te::rp::ClassifierStrategy::m_inputRasterPtr

protectedinherited

A pointer to the input raster.

Definition at line 152 of file ClassifierStrategy.h.

◆ m_isInitialized

bool te::rp::ClassifierMaxLikelihoodStrategy::m_isInitialized

protected

Is this instance initialized?

Definition at line 117 of file ClassifierMaxLikelihoodStrategy.h.

◆ m_metaData

std::map< std::string, std::string > te::rp::ClassifierStrategy::m_metaData

protectedinherited

Strategy-dependent metadata.

Definition at line 192 of file ClassifierStrategy.h.

◆ m_outputRasterPtr

std::unique_ptr< te::rst::Raster > te::rp::ClassifierStrategy::m_outputRasterPtr

protectedinherited

A pointer to the output raster.

Definition at line 177 of file ClassifierStrategy.h.

◆ m_progressInterfaceEnabled

bool te::rp::ClassifierStrategy::m_progressInterfaceEnabled

protectedinherited

Progress interface status.

Definition at line 157 of file ClassifierStrategy.h.

◆ m_userOutputPalette

std::vector< te::rst::BandProperty::ColorEntry > te::rp::ClassifierStrategy::m_userOutputPalette

protectedinherited

User output raster palette (it must be large enough to accomodate all classifyier generated classes or an empty vector to automatically generate an random palette.

Definition at line 197 of file ClassifierStrategy.h.

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

/home/castejon/castejon_files/develop/terralib5/git_release/src/terralib/rp/ClassifierMaxLikelihoodStrategy.h

Classes

Public Member Functions

Protected Member Functions

Static Protected Member Functions

Protected Attributes

Private Attributes

Detailed Description

Constructor & Destructor Documentation

◆ ClassifierMaxLikelihoodStrategy()

◆ ~ClassifierMaxLikelihoodStrategy()

Member Function Documentation

◆ applyICM()

◆ compara_uchar_vesre()

◆ createOutputRaster()

◆ enableMultiThread()

◆ enableOutputPalette()

◆ enableProgressInterface()

◆ enableRasterCache()

◆ Estimacao_geral()

◆ execute()

◆ getErrorMessage()

◆ getICMBeta()

◆ getMetaData()

◆ getOutputNumberBands()

◆ getOutputParameters()

◆ initialize()

◆ plikehood_2()

◆ plikehood_3()

◆ plikehood_4()

◆ releaseOutputRaster()

◆ reset()

◆ rtbis()

◆ setErrorMessage()

◆ setInputPolygons()

◆ setInputRaster()

◆ setInputRasterBands()

◆ setOutputRasterPalette()

◆ setUserOutputPalette()

◆ sigmo()

Member Data Documentation

◆ m_createRasterPalette

◆ m_enableMultiThread

◆ m_enableRasterCache

◆ m_errorMessage

◆ m_genClassInstance

◆ m_highestTrainClassID

◆ m_initParams

◆ m_inputPolygonsPtr

◆ m_inputRasterBands

◆ m_inputRasterPtr

◆ m_isInitialized

◆ m_metaData

◆ m_outputRasterPtr

◆ m_progressInterfaceEnabled

◆ m_userOutputPalette