te::rp::PostClassification Class Reference

Raster post classification. More...

#include <PostClassification.h>

Inheritance diagram for te::rp::PostClassification:
te::rp::Algorithm

Classes

class  InputParameters
 Filter input parameters. More...
 
class  OutputParameters
 PostClassification output parameters. More...
 

Public Member Functions

bool execute (AlgorithmOutputParameters &outputParams) _NOEXCEPT_OP(false)
 Executes the algorithm using the supplied parameters. More...
 
const std::string & getErrorMessage () const
 Return the current error message if there is any. More...
 
bool initialize (const AlgorithmInputParameters &inputParams) _NOEXCEPT_OP(false)
 Initialize the algorithm instance making it ready for execution. More...
 
bool isInitialized () const
 Returns true if the algorithm instance is initialized and ready for execution. More...
 
 PostClassification ()
 
void reset () _NOEXCEPT_OP(false)
 Clear all internal allocated objects and reset the algorithm to its initial state. More...
 
 ~PostClassification ()
 

Protected Member Functions

bool runPostClassification (const te::rst::Raster &srcRaster, te::rst::Raster &dstRaster, unsigned int weight, unsigned int threshold)
 Apply the post classification. More...
 
void setErrorMessage (const std::string &newErrorMessage)
 Set the current error message. More...
 

Protected Attributes

PostClassification::InputParameters m_inputParameters
 Input parameters. More...
 
bool m_isInitialized
 Is this instance already initialized? More...
 

Detailed Description

Raster post classification.

Definition at line 40 of file PostClassification.h.

Constructor & Destructor Documentation

te::rp::PostClassification::PostClassification ( )
te::rp::PostClassification::~PostClassification ( )
default

Referenced by PostClassification().

Member Function Documentation

bool te::rp::PostClassification::initialize ( const AlgorithmInputParameters inputParams)
virtual
bool te::rp::PostClassification::isInitialized ( ) const
virtual

Returns true if the algorithm instance is initialized and ready for execution.

Returns
true if the algorithm instance is initialized and ready for execution.

Implements te::rp::Algorithm.

Definition at line 278 of file PostClassification.cpp.

References m_isInitialized.

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

Clear all internal allocated objects and reset the algorithm to its initial state.

Reimplemented from te::rp::Algorithm.

Definition at line 243 of file PostClassification.cpp.

References m_inputParameters, m_isInitialized, te::rp::PostClassification::InputParameters::reset(), and te::rp::Algorithm::reset().

bool te::rp::PostClassification::runPostClassification ( const te::rst::Raster srcRaster,
te::rst::Raster dstRaster,
unsigned int  weight,
unsigned int  threshold 
)
protected

Apply the post classification.

Parameters
srcRasterSource raster.
srcBandIdxSource raster band index.
dstRasterDestination raster.
dstBandIdxDestination raster band index.
weightWeight value.
thresholdThreshold value.
useProgressif true, the progress interface must be used.

Definition at line 283 of file PostClassification.cpp.

References col, te::rst::Copy(), te::rst::Raster::getBand(), te::rst::Raster::getNumberOfColumns(), te::rst::Raster::getNumberOfRows(), te::rst::Band::getValue(), and te::rst::Raster::setIValue().

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

Set the current error message.

Parameters
newErrorMessageNew error message;

Definition at line 49 of file rp/Algorithm.cpp.

References te::rp::Algorithm::m_errorMessage.

Member Data Documentation

PostClassification::InputParameters te::rp::PostClassification::m_inputParameters
protected

Input parameters.

Definition at line 124 of file PostClassification.h.

Referenced by execute(), initialize(), and reset().

bool te::rp::PostClassification::m_isInitialized
protected

Is this instance already initialized?

Definition at line 122 of file PostClassification.h.

Referenced by execute(), initialize(), isInitialized(), and reset().


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