Gaussian model data manipulation. More...

#include <GaussianModel.h>

Public Types
typedef unsigned int	ClassIDT
	CLass ID type definiton. More...

typedef std::vector< ClassSampleT >	ClassSamplesContainerT
	Class samples container type definition. More...

typedef std::vector< double >	ClassSampleT
	Class sample type definition. More...

typedef std::map< ClassIDT, ClassSamplesContainerT >	MClassesSamplesCT
	Multi-classes samples container type definition. More...

typedef boost::shared_ptr< MClassesSamplesCT >	MClassesSamplesCTPtr
	A shared pointer to a multi classes samples container type definition. More...

Public Member Functions
bool	CalculatingMuAndSigmaRegion (void)

bool	CalculatingMuClass (void)

bool	CalculatingSigmaClass ()

boost::numeric::ublas::matrix< double >	checkCovarianceMatrix (boost::numeric::ublas::matrix< double >)

bool	execute (void)

	GaussianModel ()
	Constructor. More...

bool	GettingStatisticalTests (void)

bool	GettingStochasticDistances (void)

bool	LoadingSamples (void)

	~GaussianModel ()
	Destructor. More...

Public Attributes
std::vector< boost::numeric::ublas::matrix< double > >	m_classesCovarianceMatrixes
	Sigma classes parameter. More...

std::vector< unsigned int >	m_classesIDT
	Training class ID. More...

std::vector< ClassIDT >	m_classesIndex2IDMu
	A class index ordered vector of classes IDs for Mu parameter. More...

te::rst::Raster *	m_inputRasterPtr
	Input raster. More...

std::vector< unsigned int >	m_inputRastersBands
	Bands to process. More...

unsigned int	m_lagX
	The horizontal correlation value. More...

unsigned int	m_lagY
	The vertical correlation value. More...

std::vector< std::vector< double > >	m_muClassesParameters
	Mu classes parameter. More...

std::vector< std::vector< double > >	m_muRegionsParameter
	Mu Regions parameter. More...

std::vector< int >	m_numberOfSamples

std::vector< te::gm::Polygon >	m_polygonSamplesT
	Training samples polygons. More...

std::vector< std::vector< double > >	m_polygonSamplesTNew
	Training samples polygons. More...

std::vector< te::gm::Polygon * >	m_polygonsSegImage
	Polygons of segmented image. More...

std::vector< std::vector< double > >	m_pValue
	P-values container. More...

std::vector< boost::numeric::ublas::matrix< double > >	m_regionsCovarianceMatrixes
	Sigma regions parameter. More...

std::vector< double >	m_regionsSize
	Size of regions. More...

std::vector< double >	m_samplesSize
	Size of sample containers. More...

double	m_significanceLevel
	The significance level. More...

unsigned int	m_sourcesNumber
	Number of sources. More...

std::vector< std::vector< double > >	m_statisticalTest
	Statistical test container. More...

std::vector< std::vector< double > >	m_stochasticDistance
	Stochastic distance container. More...

std::string	m_stochasticDistanceType
	The stochastic distance type definition. More...

MClassesSamplesCTPtr	m_trainSamplesPtr
	A shared pointer to a always-valid structure where training samples are stored. More...

Detailed Description

Gaussian model data manipulation.

Definition at line 51 of file GaussianModel.h.

Member Typedef Documentation

◆ ClassIDT

typedef unsigned int te::rp::radar::GaussianModel::ClassIDT

CLass ID type definiton.

Definition at line 69 of file GaussianModel.h.

◆ ClassSamplesContainerT

typedef std::vector< ClassSampleT > te::rp::radar::GaussianModel::ClassSamplesContainerT

Class samples container type definition.

Definition at line 79 of file GaussianModel.h.

◆ ClassSampleT

typedef std::vector< double > te::rp::radar::GaussianModel::ClassSampleT

Class sample type definition.

Definition at line 77 of file GaussianModel.h.

◆ MClassesSamplesCT

typedef std::map< ClassIDT, ClassSamplesContainerT > te::rp::radar::GaussianModel::MClassesSamplesCT

Multi-classes samples container type definition.

Definition at line 81 of file GaussianModel.h.

◆ MClassesSamplesCTPtr

typedef boost::shared_ptr<MClassesSamplesCT> te::rp::radar::GaussianModel::MClassesSamplesCTPtr

A shared pointer to a multi classes samples container type definition.

Definition at line 83 of file GaussianModel.h.

Constructor & Destructor Documentation

◆ GaussianModel()

te::rp::radar::GaussianModel::GaussianModel ( )

Constructor.

◆ ~GaussianModel()

te::rp::radar::GaussianModel::~GaussianModel ( )

Destructor.

Member Function Documentation

◆ CalculatingMuAndSigmaRegion()

bool te::rp::radar::GaussianModel::CalculatingMuAndSigmaRegion ( void )

◆ CalculatingMuClass()

bool te::rp::radar::GaussianModel::CalculatingMuClass ( void )

◆ CalculatingSigmaClass()

bool te::rp::radar::GaussianModel::CalculatingSigmaClass ( )

◆ checkCovarianceMatrix()

boost::numeric::ublas::matrix< double > te::rp::radar::GaussianModel::checkCovarianceMatrix ( boost::numeric::ublas::matrix< double > )

◆ execute()

bool te::rp::radar::GaussianModel::execute ( void )

◆ GettingStatisticalTests()

bool te::rp::radar::GaussianModel::GettingStatisticalTests ( void )

◆ GettingStochasticDistances()

bool te::rp::radar::GaussianModel::GettingStochasticDistances ( void )

◆ LoadingSamples()

bool te::rp::radar::GaussianModel::LoadingSamples ( void )

Member Data Documentation

◆ m_classesCovarianceMatrixes

std::vector< boost::numeric::ublas::matrix< double > > te::rp::radar::GaussianModel::m_classesCovarianceMatrixes

Sigma classes parameter.

Definition at line 91 of file GaussianModel.h.

◆ m_classesIDT

std::vector< unsigned int > te::rp::radar::GaussianModel::m_classesIDT

Training class ID.

Definition at line 71 of file GaussianModel.h.

◆ m_classesIndex2IDMu

std::vector< ClassIDT > te::rp::radar::GaussianModel::m_classesIndex2IDMu

A class index ordered vector of classes IDs for Mu parameter.

Definition at line 87 of file GaussianModel.h.

◆ m_inputRasterPtr

te::rst::Raster* te::rp::radar::GaussianModel::m_inputRasterPtr

Input raster.

Definition at line 59 of file GaussianModel.h.

◆ m_inputRastersBands

std::vector< unsigned int > te::rp::radar::GaussianModel::m_inputRastersBands

Bands to process.

Definition at line 61 of file GaussianModel.h.

◆ m_lagX

unsigned int te::rp::radar::GaussianModel::m_lagX

The horizontal correlation value.

Definition at line 65 of file GaussianModel.h.

◆ m_lagY

unsigned int te::rp::radar::GaussianModel::m_lagY

The vertical correlation value.

Definition at line 67 of file GaussianModel.h.

◆ m_muClassesParameters

std::vector< std::vector< double > > te::rp::radar::GaussianModel::m_muClassesParameters

Mu classes parameter.

Definition at line 89 of file GaussianModel.h.

◆ m_muRegionsParameter

std::vector< std::vector< double > > te::rp::radar::GaussianModel::m_muRegionsParameter

Mu Regions parameter.

Definition at line 93 of file GaussianModel.h.

◆ m_numberOfSamples

std::vector< int > te::rp::radar::GaussianModel::m_numberOfSamples

Definition at line 75 of file GaussianModel.h.

◆ m_polygonSamplesT

std::vector< te::gm::Polygon > te::rp::radar::GaussianModel::m_polygonSamplesT

Training samples polygons.

Definition at line 73 of file GaussianModel.h.

◆ m_polygonSamplesTNew

std::vector< std::vector< double > > te::rp::radar::GaussianModel::m_polygonSamplesTNew

Training samples polygons.

Definition at line 74 of file GaussianModel.h.

◆ m_polygonsSegImage

std::vector< te::gm::Polygon* > te::rp::radar::GaussianModel::m_polygonsSegImage

Polygons of segmented image.

Definition at line 63 of file GaussianModel.h.

◆ m_pValue

std::vector< std::vector< double > > te::rp::radar::GaussianModel::m_pValue

P-values container.

Definition at line 103 of file GaussianModel.h.

◆ m_regionsCovarianceMatrixes

std::vector< boost::numeric::ublas::matrix< double > > te::rp::radar::GaussianModel::m_regionsCovarianceMatrixes

Sigma regions parameter.

Definition at line 95 of file GaussianModel.h.

◆ m_regionsSize

std::vector< double > te::rp::radar::GaussianModel::m_regionsSize

Size of regions.

Definition at line 107 of file GaussianModel.h.

◆ m_samplesSize

std::vector< double > te::rp::radar::GaussianModel::m_samplesSize

Size of sample containers.

Definition at line 109 of file GaussianModel.h.

◆ m_significanceLevel

double te::rp::radar::GaussianModel::m_significanceLevel

The significance level.

Definition at line 105 of file GaussianModel.h.

◆ m_sourcesNumber

unsigned int te::rp::radar::GaussianModel::m_sourcesNumber

Number of sources.

Definition at line 57 of file GaussianModel.h.

◆ m_statisticalTest

std::vector< std::vector< double > > te::rp::radar::GaussianModel::m_statisticalTest

Statistical test container.

Definition at line 101 of file GaussianModel.h.

◆ m_stochasticDistance

std::vector< std::vector< double > > te::rp::radar::GaussianModel::m_stochasticDistance

Stochastic distance container.

Definition at line 99 of file GaussianModel.h.

◆ m_stochasticDistanceType

std::string te::rp::radar::GaussianModel::m_stochasticDistanceType

The stochastic distance type definition.

Definition at line 97 of file GaussianModel.h.

◆ m_trainSamplesPtr

MClassesSamplesCTPtr te::rp::radar::GaussianModel::m_trainSamplesPtr

A shared pointer to a always-valid structure where training samples are stored.

Definition at line 85 of file GaussianModel.h.

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

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

Public Types

Public Member Functions

Public Attributes