te::rp::radar::MultiSourceClassifierInputParameters Class Reference

MultiSourceClassifier input parameters. More...

#include <MultiSourceClassifierInputParameters.h>

Inheritance diagram for te::rp::radar::MultiSourceClassifierInputParameters:

Public Types
typedef unsigned int	ClassIDT
	CLass ID type definiton.

Public Member Functions
AbstractParameters *	clone () const
	Create a clone copy of this instance.
	MultiSourceClassifierInputParameters ()
	MultiSourceClassifierInputParameters (const MultiSourceClassifierInputParameters &)
const MultiSourceClassifierInputParameters &	operator= (const MultiSourceClassifierInputParameters &params)
void	reset ()
	Clear all internal allocated resources and reset the parameters instance to its initial state.
bool	serialize (te::rp::AlgorithmParametersSerializer &serializer) const
	Returns a parameter serialization object.
	~MultiSourceClassifierInputParameters ()

Public Attributes
std::vector< double >	m_betaValue
	Beta values for Renyi distance container.
std::vector< unsigned int >	m_classesIDT
	Training class ID.
std::vector< unsigned int >	m_classesIDT2
	Class ID.
std::vector< unsigned int >	m_classesIDTest
	Test class ID.
std::string	m_combinationType
	How the build the multi-source classification procedure (sum, multiplication,minimum,Hellinger,fuzzy).
std::map< std::string, std::string >	m_dirTestSamples
	Test samples data directory.
std::map< std::string, std::string >	m_dirTrainingSamples
	Training samples data directory.
std::vector< double >	m_ENL
	Equivalent Number of Looks container.
te::rst::Grid *	m_extent
	The geographic extension of the raster data.
std::vector< std::string >	m_imageType
	The used data model (one for each input image) (Gaussian,Gamma,IntensityPair,Wishart).
std::vector< te::rst::Raster * >	m_inputRasterPtr
	Input rasters.
std::vector< std::vector< unsigned int > >	m_inputRastersBands
	Bands to process.
unsigned int	m_lagX
	The horizontal correlation value.
unsigned int	m_lagY
	The vertical correlation value.
std::vector< std::string >	m_nameOfSamples
std::vector< std::string >	m_nameOfSamplesTest
unsigned int	m_numberOfClassesOnTest
	Number of classes on test.
unsigned int	m_numberOfClassesOnTraining
	Number of classes on training.
unsigned int	m_numberOfColumns
	Number of columns that all input rasters must have.
unsigned int	m_numberOfRows
	Number of rows that all input rasters must have.
std::vector< int >	m_numberOfSamples
std::vector< int >	m_numberOfSamplesTest
std::vector< te::gm::Polygon >	m_polygonSamplesT
	Training samples polygons.
std::vector< te::gm::Polygon >	m_polygonSamplesTest
	Test samples polygons.
std::vector< std::vector< double > >	m_polygonSamplesTestNew
std::vector< std::vector< double > >	m_polygonSamplesTNew
	Training samples polygons.
std::vector< te::gm::Polygon * >	m_polygonsSegImage
	Polygons of segmented image.
std::vector< std::string >	m_radarDataRepresentationType
	The radar data representation container.
te::rst::Raster const *	m_rasterSegPtr
	Input segmented raster.
bool	m_saveDistances
	The flag to indicate if stochastic distance values will be saved on disk.
bool	m_savePerClassDistancesFile
	The flag to indicate if stochastic distance values per class will be saved on disk.
bool	m_savePerClassPValueFile
	The flag to indicate if p-values per class will be saved on disk.
bool	m_savePerClassStatiticsFile
	The flag to indicate if statistic test values per class will be saved on disk.
bool	m_savePValues
	The flag to indicate if p-values will be saved on disk.
bool	m_saveReportFile
	The flag to indicate if the report will be saved on disk.
bool	m_saveStatitics
	The flag to indicate if statistic test values will be saved on disk.
double	m_significanceLevel
	The significance level.
unsigned int	m_sourcesNumber
	The number of different image sources.
int	m_SRID
	The SRID of raster data;.
std::vector< std::string >	m_stochasticDistanceType
	The stochastic distance type (Bhattacharyya,Triangular).
std::vector< unsigned int >	m_vectorOrMatrixOrder
	The lexicographic vector and covariance matrix order container.

Detailed Description

MultiSourceClassifier input parameters.

Definition at line 46 of file MultiSourceClassifierInputParameters.h.

Member Typedef Documentation

ClassIDT

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

CLass ID type definiton.

Definition at line 50 of file MultiSourceClassifierInputParameters.h.

Constructor & Destructor Documentation

MultiSourceClassifierInputParameters() [1/2]

te::rp::radar::MultiSourceClassifierInputParameters::MultiSourceClassifierInputParameters

(

)

MultiSourceClassifierInputParameters() [2/2]

te::rp::radar::MultiSourceClassifierInputParameters::MultiSourceClassifierInputParameters

(

const MultiSourceClassifierInputParameters &

)

~MultiSourceClassifierInputParameters()

te::rp::radar::MultiSourceClassifierInputParameters::~MultiSourceClassifierInputParameters

(

)

Member Function Documentation

clone()

AbstractParameters * te::rp::radar::MultiSourceClassifierInputParameters::clone ( ) const

virtual

Create a clone copy of this instance.

Returns

A clone copy of this instance.

Note

The caller will take the ownership of the returned pointer.

Implements te::common::AbstractParameters.

operator=()

const MultiSourceClassifierInputParameters & te::rp::radar::MultiSourceClassifierInputParameters::operator=

(

const MultiSourceClassifierInputParameters &

params

)

reset()

void te::rp::radar::MultiSourceClassifierInputParameters::reset ( )

virtual

Clear all internal allocated resources and reset the parameters instance to its initial state.

Implements te::common::AbstractParameters.

serialize()

bool te::rp::radar::MultiSourceClassifierInputParameters::serialize ( te::rp::AlgorithmParametersSerializer &  serializer ) const

virtual

Returns a parameter serialization object.

Parameters

serializer

The output serialization object.

Returns

Returns true if ok, false on erros.

Reimplemented from te::rp::AlgorithmInputParameters.

Member Data Documentation

m_betaValue

std::vector< double > te::rp::radar::MultiSourceClassifierInputParameters::m_betaValue

Beta values for Renyi distance container.

Definition at line 105 of file MultiSourceClassifierInputParameters.h.

m_classesIDT

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

Training class ID.

Definition at line 120 of file MultiSourceClassifierInputParameters.h.

m_classesIDT2

std::vector< unsigned int > te::rp::radar::MultiSourceClassifierInputParameters::m_classesIDT2

Class ID.

Definition at line 126 of file MultiSourceClassifierInputParameters.h.

m_classesIDTest

std::vector< unsigned int > te::rp::radar::MultiSourceClassifierInputParameters::m_classesIDTest

Test class ID.

Definition at line 124 of file MultiSourceClassifierInputParameters.h.

m_combinationType

std::string te::rp::radar::MultiSourceClassifierInputParameters::m_combinationType

How the build the multi-source classification procedure (sum, multiplication,minimum,Hellinger,fuzzy).

Definition at line 90 of file MultiSourceClassifierInputParameters.h.

m_dirTestSamples

std::map< std::string, std::string > te::rp::radar::MultiSourceClassifierInputParameters::m_dirTestSamples

Test samples data directory.

Definition at line 110 of file MultiSourceClassifierInputParameters.h.

m_dirTrainingSamples

std::map< std::string, std::string > te::rp::radar::MultiSourceClassifierInputParameters::m_dirTrainingSamples

Training samples data directory.

Definition at line 108 of file MultiSourceClassifierInputParameters.h.

m_ENL

std::vector< double > te::rp::radar::MultiSourceClassifierInputParameters::m_ENL

Equivalent Number of Looks container.

Definition at line 103 of file MultiSourceClassifierInputParameters.h.

m_extent

te::rst::Grid* te::rp::radar::MultiSourceClassifierInputParameters::m_extent

The geographic extension of the raster data.

Definition at line 64 of file MultiSourceClassifierInputParameters.h.

m_imageType

std::vector< std::string > te::rp::radar::MultiSourceClassifierInputParameters::m_imageType

The used data model (one for each input image) (Gaussian,Gamma,IntensityPair,Wishart).

Definition at line 72 of file MultiSourceClassifierInputParameters.h.

m_inputRasterPtr

std::vector< te::rst::Raster* > te::rp::radar::MultiSourceClassifierInputParameters::m_inputRasterPtr

Input rasters.

Definition at line 53 of file MultiSourceClassifierInputParameters.h.

m_inputRastersBands

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

Bands to process.

Definition at line 55 of file MultiSourceClassifierInputParameters.h.

m_lagX

unsigned int te::rp::radar::MultiSourceClassifierInputParameters::m_lagX

The horizontal correlation value.

Definition at line 92 of file MultiSourceClassifierInputParameters.h.

m_lagY

unsigned int te::rp::radar::MultiSourceClassifierInputParameters::m_lagY

The vertical correlation value.

Definition at line 94 of file MultiSourceClassifierInputParameters.h.

m_nameOfSamples

std::vector< std::string > te::rp::radar::MultiSourceClassifierInputParameters::m_nameOfSamples

Definition at line 117 of file MultiSourceClassifierInputParameters.h.

m_nameOfSamplesTest

std::vector< std::string > te::rp::radar::MultiSourceClassifierInputParameters::m_nameOfSamplesTest

Definition at line 118 of file MultiSourceClassifierInputParameters.h.

m_numberOfClassesOnTest

unsigned int te::rp::radar::MultiSourceClassifierInputParameters::m_numberOfClassesOnTest

Number of classes on test.

Definition at line 130 of file MultiSourceClassifierInputParameters.h.

m_numberOfClassesOnTraining

unsigned int te::rp::radar::MultiSourceClassifierInputParameters::m_numberOfClassesOnTraining

Number of classes on training.

Definition at line 128 of file MultiSourceClassifierInputParameters.h.

m_numberOfColumns

unsigned int te::rp::radar::MultiSourceClassifierInputParameters::m_numberOfColumns

Number of columns that all input rasters must have.

Definition at line 58 of file MultiSourceClassifierInputParameters.h.

m_numberOfRows

unsigned int te::rp::radar::MultiSourceClassifierInputParameters::m_numberOfRows

Number of rows that all input rasters must have.

Definition at line 60 of file MultiSourceClassifierInputParameters.h.

m_numberOfSamples

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

Definition at line 115 of file MultiSourceClassifierInputParameters.h.

m_numberOfSamplesTest

std::vector< int > te::rp::radar::MultiSourceClassifierInputParameters::m_numberOfSamplesTest

Definition at line 116 of file MultiSourceClassifierInputParameters.h.

m_polygonSamplesT

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

Training samples polygons.

Definition at line 112 of file MultiSourceClassifierInputParameters.h.

m_polygonSamplesTest

std::vector< te::gm::Polygon > te::rp::radar::MultiSourceClassifierInputParameters::m_polygonSamplesTest

Test samples polygons.

Definition at line 122 of file MultiSourceClassifierInputParameters.h.

m_polygonSamplesTestNew

std::vector< std::vector< double > > te::rp::radar::MultiSourceClassifierInputParameters::m_polygonSamplesTestNew

Definition at line 114 of file MultiSourceClassifierInputParameters.h.

m_polygonSamplesTNew

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

Training samples polygons.

Definition at line 113 of file MultiSourceClassifierInputParameters.h.

m_polygonsSegImage

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

Polygons of segmented image.

Definition at line 66 of file MultiSourceClassifierInputParameters.h.

m_radarDataRepresentationType

std::vector< std::string > te::rp::radar::MultiSourceClassifierInputParameters::m_radarDataRepresentationType

The radar data representation container.

Definition at line 99 of file MultiSourceClassifierInputParameters.h.

m_rasterSegPtr

te::rst::Raster const* te::rp::radar::MultiSourceClassifierInputParameters::m_rasterSegPtr

Input segmented raster.

Definition at line 68 of file MultiSourceClassifierInputParameters.h.

m_saveDistances

bool te::rp::radar::MultiSourceClassifierInputParameters::m_saveDistances

The flag to indicate if stochastic distance values will be saved on disk.

Definition at line 82 of file MultiSourceClassifierInputParameters.h.

m_savePerClassDistancesFile

bool te::rp::radar::MultiSourceClassifierInputParameters::m_savePerClassDistancesFile

The flag to indicate if stochastic distance values per class will be saved on disk.

Definition at line 76 of file MultiSourceClassifierInputParameters.h.

m_savePerClassPValueFile

bool te::rp::radar::MultiSourceClassifierInputParameters::m_savePerClassPValueFile

The flag to indicate if p-values per class will be saved on disk.

Definition at line 80 of file MultiSourceClassifierInputParameters.h.

m_savePerClassStatiticsFile

bool te::rp::radar::MultiSourceClassifierInputParameters::m_savePerClassStatiticsFile

The flag to indicate if statistic test values per class will be saved on disk.

Definition at line 78 of file MultiSourceClassifierInputParameters.h.

m_savePValues

bool te::rp::radar::MultiSourceClassifierInputParameters::m_savePValues

The flag to indicate if p-values will be saved on disk.

Definition at line 86 of file MultiSourceClassifierInputParameters.h.

m_saveReportFile

bool te::rp::radar::MultiSourceClassifierInputParameters::m_saveReportFile

The flag to indicate if the report will be saved on disk.

Definition at line 88 of file MultiSourceClassifierInputParameters.h.

m_saveStatitics

bool te::rp::radar::MultiSourceClassifierInputParameters::m_saveStatitics

The flag to indicate if statistic test values will be saved on disk.

Definition at line 84 of file MultiSourceClassifierInputParameters.h.

m_significanceLevel

double te::rp::radar::MultiSourceClassifierInputParameters::m_significanceLevel

The significance level.

Definition at line 96 of file MultiSourceClassifierInputParameters.h.

m_sourcesNumber

unsigned int te::rp::radar::MultiSourceClassifierInputParameters::m_sourcesNumber

The number of different image sources.

Definition at line 70 of file MultiSourceClassifierInputParameters.h.

m_SRID

int te::rp::radar::MultiSourceClassifierInputParameters::m_SRID

The SRID of raster data;.

Definition at line 62 of file MultiSourceClassifierInputParameters.h.

m_stochasticDistanceType

std::vector< std::string > te::rp::radar::MultiSourceClassifierInputParameters::m_stochasticDistanceType

The stochastic distance type (Bhattacharyya,Triangular).

Definition at line 74 of file MultiSourceClassifierInputParameters.h.

m_vectorOrMatrixOrder

std::vector< unsigned int > te::rp::radar::MultiSourceClassifierInputParameters::m_vectorOrMatrixOrder

The lexicographic vector and covariance matrix order container.

Definition at line 101 of file MultiSourceClassifierInputParameters.h.

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

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