Inheritance diagram for ZeroCrossingCounter:

Public Types
enum	ZeroCrossingFeatureIDs { NUM_ZERO_CROSSINGS_COUNTED =0, ZERO_CROSSING_MAGNITUDE, TOTAL_NUM_ZERO_CROSSING_FEATURES }

enum	FeatureModes { INDEPENDANT_FEATURE_MODE =0, COMBINED_FEATURE_MODE }

Public Types inherited from FeatureExtraction
typedef std::map< std::string, FeatureExtraction ()() >	StringFeatureExtractionMap

Public Types inherited from MLBase
enum	BaseType { BASE_TYPE_NOT_SET =0, CLASSIFIER, REGRESSIFIER, CLUSTERER, PRE_PROCSSING, POST_PROCESSING, FEATURE_EXTRACTION, CONTEXT }

Public Member Functions
	ZeroCrossingCounter (const UINT searchWindowSize=20, const Float deadZoneThreshold=0.01, const UINT numDimensions=1, const UINT featureMode=INDEPENDANT_FEATURE_MODE)

	ZeroCrossingCounter (const ZeroCrossingCounter &rhs)

virtual	~ZeroCrossingCounter ()

ZeroCrossingCounter &	operator= (const ZeroCrossingCounter &rhs)

virtual bool	deepCopyFrom (const FeatureExtraction *featureExtraction)

virtual bool	computeFeatures (const VectorFloat &inputVector)

virtual bool	reset ()

virtual bool	save (std::fstream &file) const

virtual bool	load (std::fstream &file)

bool	init (const UINT searchWindowSize, const Float deadZoneThreshold, const UINT numDimensions, const UINT featureMode)

VectorFloat	update (const Float x)

VectorFloat	update (const VectorFloat &x)

bool	setSearchWindowSize (const UINT searchWindowSize)

bool	setFeatureMode (const UINT featureMode)

bool	setDeadZoneThreshold (const Float deadZoneThreshold)

UINT	getSearchWindowSize () const

UINT	getNumFeatures () const

UINT	getFeatureMode () const

Float	getDeadZoneThreshold () const

CircularBuffer< VectorFloat >	getDataBuffer () const

Public Member Functions inherited from FeatureExtraction
	FeatureExtraction (const std::string id="")

virtual	~FeatureExtraction ()

bool	copyBaseVariables (const FeatureExtraction *featureExtractionModule)

virtual bool	computeFeatures (const MatrixFloat &inputMatrix)

virtual bool	clear () override

bool	getInitialized () const

bool	getFeatureDataReady () const

const VectorFloat &	getFeatureVector () const

const MatrixFloat &	getFeatureMatrix () const

FeatureExtraction *	create () const

	GRT_DEPRECATED_MSG ("createNewInstance is deprecated, use create() instead.", FeatureExtraction *createNewInstance() const )

	GRT_DEPRECATED_MSG ("createInstanceFromString(id) is deprecated, use create(id) instead.", static FeatureExtraction *createInstanceFromString(const std::string &id))

	GRT_DEPRECATED_MSG ("getFeatureExtractionType is deprecated, use getId() instead", std::string getFeatureExtractionType() const )

Public Member Functions inherited from MLBase
	MLBase (const std::string &id="", const BaseType type=BASE_TYPE_NOT_SET)

virtual	~MLBase (void)

bool	copyMLBaseVariables (const MLBase *mlBase)

virtual bool	train (ClassificationData trainingData)

virtual bool	train_ (ClassificationData &trainingData)

virtual bool	train (RegressionData trainingData)

virtual bool	train_ (RegressionData &trainingData)

virtual bool	train (RegressionData trainingData, RegressionData validationData)

virtual bool	train_ (RegressionData &trainingData, RegressionData &validationData)

virtual bool	train (TimeSeriesClassificationData trainingData)

virtual bool	train_ (TimeSeriesClassificationData &trainingData)

virtual bool	train (ClassificationDataStream trainingData)

virtual bool	train_ (ClassificationDataStream &trainingData)

virtual bool	train (UnlabelledData trainingData)

virtual bool	train_ (UnlabelledData &trainingData)

virtual bool	train (MatrixFloat data)

virtual bool	train_ (MatrixFloat &data)

virtual bool	predict (VectorFloat inputVector)

virtual bool	predict_ (VectorFloat &inputVector)

virtual bool	predict (MatrixFloat inputMatrix)

virtual bool	predict_ (MatrixFloat &inputMatrix)

virtual bool	map (VectorFloat inputVector)

virtual bool	map_ (VectorFloat &inputVector)

virtual bool	print () const

virtual bool	save (const std::string &filename) const

virtual bool	load (const std::string &filename)

	GRT_DEPRECATED_MSG ("saveModelToFile(std::string filename) is deprecated, use save(const std::string &filename) instead", virtual bool saveModelToFile(const std::string &filename) const )

	GRT_DEPRECATED_MSG ("saveModelToFile(std::fstream &file) is deprecated, use save(std::fstream &file) instead", virtual bool saveModelToFile(std::fstream &file) const )

	GRT_DEPRECATED_MSG ("loadModelFromFile(std::string filename) is deprecated, use load(const std::string &filename) instead", virtual bool loadModelFromFile(const std::string &filename))

	GRT_DEPRECATED_MSG ("loadModelFromFile(std::fstream &file) is deprecated, use load(std::fstream &file) instead", virtual bool loadModelFromFile(std::fstream &file))

virtual bool	getModel (std::ostream &stream) const

virtual std::string	getModelAsString () const

DataType	getInputType () const

DataType	getOutputType () const

BaseType	getType () const

UINT	getNumInputFeatures () const

UINT	getNumInputDimensions () const

UINT	getNumOutputDimensions () const

UINT	getMinNumEpochs () const

UINT	getMaxNumEpochs () const

UINT	getBatchSize () const

UINT	getNumRestarts () const

UINT	getValidationSetSize () const

UINT	getNumTrainingIterationsToConverge () const

Float	getMinChange () const

Float	getLearningRate () const

Float	getRMSTrainingError () const

	GRT_DEPRECATED_MSG ("getRootMeanSquaredTrainingError() is deprecated, use getRMSTrainingError() instead", Float getRootMeanSquaredTrainingError() const )

Float	getTotalSquaredTrainingError () const

Float	getRMSValidationError () const

Float	getValidationSetAccuracy () const

VectorFloat	getValidationSetPrecision () const

VectorFloat	getValidationSetRecall () const

bool	getUseValidationSet () const

bool	getRandomiseTrainingOrder () const

bool	getTrained () const

	GRT_DEPRECATED_MSG ("getModelTrained() is deprecated, use getTrained() instead", bool getModelTrained() const )

bool	getConverged () const

bool	getScalingEnabled () const

bool	getIsBaseTypeClassifier () const

bool	getIsBaseTypeRegressifier () const

bool	getIsBaseTypeClusterer () const

bool	getTrainingLoggingEnabled () const

bool	getTestingLoggingEnabled () const

bool	enableScaling (const bool useScaling)

bool	setMaxNumEpochs (const UINT maxNumEpochs)

bool	setBatchSize (const UINT batchSize)

bool	setMinNumEpochs (const UINT minNumEpochs)

bool	setNumRestarts (const UINT numRestarts)

bool	setMinChange (const Float minChange)

bool	setLearningRate (const Float learningRate)

bool	setUseValidationSet (const bool useValidationSet)

bool	setValidationSetSize (const UINT validationSetSize)

bool	setRandomiseTrainingOrder (const bool randomiseTrainingOrder)

bool	setTrainingLoggingEnabled (const bool loggingEnabled)

bool	setTestingLoggingEnabled (const bool loggingEnabled)

bool	registerTrainingResultsObserver (Observer< TrainingResult > &observer)

bool	registerTestResultsObserver (Observer< TestInstanceResult > &observer)

bool	removeTrainingResultsObserver (const Observer< TrainingResult > &observer)

bool	removeTestResultsObserver (const Observer< TestInstanceResult > &observer)

bool	removeAllTrainingObservers ()

bool	removeAllTestObservers ()

bool	notifyTrainingResultsObservers (const TrainingResult &data)

bool	notifyTestResultsObservers (const TestInstanceResult &data)

MLBase *	getMLBasePointer ()

const MLBase *	getMLBasePointer () const

Vector< TrainingResult >	getTrainingResults () const

Public Member Functions inherited from GRTBase
	GRTBase (const std::string &id="")

virtual	~GRTBase (void)

bool	copyGRTBaseVariables (const GRTBase *GRTBase)

	GRT_DEPRECATED_MSG ("getClassType is deprecated, use getId() instead!", std::string getClassType() const )

std::string	getId () const

std::string	getLastWarningMessage () const

std::string	getLastErrorMessage () const

std::string	getLastInfoMessage () const

bool	setInfoLoggingEnabled (const bool loggingEnabled)

bool	setWarningLoggingEnabled (const bool loggingEnabled)

bool	setErrorLoggingEnabled (const bool loggingEnabled)

bool	setDebugLoggingEnabled (const bool loggingEnabled)

GRTBase *	getGRTBasePointer ()

const GRTBase *	getGRTBasePointer () const

Float	scale (const Float &x, const Float &minSource, const Float &maxSource, const Float &minTarget, const Float &maxTarget, const bool constrain=false)

Float	SQR (const Float &x) const

Public Member Functions inherited from Observer< TrainingResult >
virtual void	notify (const TrainingResult &data)

Public Member Functions inherited from Observer< TestInstanceResult >
virtual void	notify (const TestInstanceResult &data)

Static Public Member Functions
static std::string	getId ()

Static Public Member Functions inherited from FeatureExtraction
static FeatureExtraction *	create (const std::string &id)

Static Public Member Functions inherited from GRTBase
static std::string	getGRTVersion (bool returnRevision=true)

static std::string	getGRTRevison ()

Protected Attributes
UINT	searchWindowSize
	The size of the search window, i.e. the amount of previous data stored and searched.

UINT	featureMode
	The featureMode controls how the features are added to the feature vector.

Float	deadZoneThreshold
	The threshold value used for the dead zone filter.

Derivative	derivative
	Used to compute the derivative of the input signal.

DeadZone	deadZone
	Used to remove small amounts of noise from the data.

CircularBuffer< VectorFloat >	dataBuffer
	A buffer used to store the previous derivative data.

Protected Attributes inherited from FeatureExtraction
std::string	featureExtractionType

bool	initialized

bool	featureDataReady

VectorFloat	featureVector

MatrixFloat	featureMatrix

Protected Attributes inherited from MLBase
bool	trained

bool	useScaling

bool	converged

DataType	inputType

DataType	outputType

BaseType	baseType

UINT	numInputDimensions

UINT	numOutputDimensions

UINT	numTrainingIterationsToConverge

UINT	minNumEpochs

UINT	maxNumEpochs

UINT	batchSize

UINT	validationSetSize

UINT	numRestarts

Float	learningRate

Float	minChange

Float	rmsTrainingError

Float	rmsValidationError

Float	totalSquaredTrainingError

Float	validationSetAccuracy

bool	useValidationSet

bool	randomiseTrainingOrder

VectorFloat	validationSetPrecision

VectorFloat	validationSetRecall

Random	random

Vector< TrainingResult >	trainingResults

TrainingResultsObserverManager	trainingResultsObserverManager

TestResultsObserverManager	testResultsObserverManager

TrainingLog	trainingLog

TestingLog	testingLog

Protected Attributes inherited from GRTBase
std::string	classId
	Stores the name of the class (e.g., MinDist)

DebugLog	debugLog

ErrorLog	errorLog

InfoLog	infoLog

WarningLog	warningLog

Additional Inherited Members
Protected Member Functions inherited from FeatureExtraction
bool	init ()

bool	saveFeatureExtractionSettingsToFile (std::fstream &file) const

bool	loadFeatureExtractionSettingsFromFile (std::fstream &file)

Protected Member Functions inherited from MLBase
bool	saveBaseSettingsToFile (std::fstream &file) const

bool	loadBaseSettingsFromFile (std::fstream &file)

Static Protected Member Functions inherited from FeatureExtraction
static StringFeatureExtractionMap *	getMap ()

Detailed Description

Definition at line 50 of file ZeroCrossingCounter.h.

Constructor & Destructor Documentation

ZeroCrossingCounter::ZeroCrossingCounter	(	const UINT	searchWindowSize = `20`,
		const Float	deadZoneThreshold = `0.01`,
		const UINT	numDimensions = `1`,
		const UINT	featureMode = `INDEPENDANT_FEATURE_MODE`
	)

Constructor, sets the search window size, deadZoneThreshold, and the dimensionality of the input data. The search window size sets how much data should be held in memory and searched each time the update function is called.

Parameters

searchWindowSize	sets how much data should be held in memory and searched each time the update function is called. Default value = 20
deadZoneThreshold	sets the dead zone threshold. Default value = 0.01
numDimensions	the dimensionality of the input data to filter. Default numDimensions = 1
featureMode	sets how the features are added to the feature vector, shoule be either INDEPENDANT_FEATURE_MODE or COMBINED_FEATURE_MODE. Default is featureMode = INDEPENDANT_FEATURE_MODE

Definition at line 33 of file ZeroCrossingCounter.cpp.

ZeroCrossingCounter::ZeroCrossingCounter ( const ZeroCrossingCounter & rhs )

Copy constructor, copies the ZeroCrossingCounter from the rhs instance to this instance.

Parameters

rhs	another instance of the ZeroCrossingCounter class from which the data will be copied to this instance

Definition at line 38 of file ZeroCrossingCounter.cpp.

ZeroCrossingCounter::~ZeroCrossingCounter ( )

virtual

Default Destructor

Definition at line 44 of file ZeroCrossingCounter.cpp.

Member Function Documentation

bool ZeroCrossingCounter::computeFeatures ( const VectorFloat & inputVector )

virtual

Sets the FeatureExtraction computeFeatures function, overwriting the base FeatureExtraction function. This function is called by the GestureRecognitionPipeline when any new input data needs to be processed (during the prediction phase for example). This function calls the ZeroCrossingCounter's update function.

Parameters

inputVector the inputVector that should be processed. Must have the same dimensionality as the FeatureExtraction module

Returns: returns true if the data was processed, false otherwise

Reimplemented from FeatureExtraction.

Definition at line 77 of file ZeroCrossingCounter.cpp.

bool ZeroCrossingCounter::deepCopyFrom ( const FeatureExtraction * featureExtraction )

virtual

Sets the FeatureExtraction deepCopyFrom function, overwriting the base FeatureExtraction function. This function is used to deep copy the values from the input pointer to this instance of the FeatureExtraction module. This function is called by the GestureRecognitionPipeline when the user adds a new FeatureExtraction module to the pipeleine.

Parameters

featureExtraction a pointer to another instance of a ZeroCrossingCounter, the values of that instance will be cloned to this instance

Returns: returns true if the deep copy was successful, false otherwise

Reimplemented from FeatureExtraction.

Definition at line 62 of file ZeroCrossingCounter.cpp.

CircularBuffer< VectorFloat > ZeroCrossingCounter::getDataBuffer ( ) const

inline

Gets the current values in the data buffer. An empty circular buffer will be returned if the ZeroCrossingCounter has not been initialized.

Returns: returns a curcular buffer containing the data buffer values, an empty circular buffer will be returned if the ZeroCrossingCounter has not been initialized

Definition at line 224 of file ZeroCrossingCounter.h.

Float ZeroCrossingCounter::getDeadZoneThreshold ( ) const

inline

Gets the deadZoneThreshold value.

Returns: returns a Float representing the deadZoneThreshold, returns zero if the feature extraction module has not been initialized

Definition at line 216 of file ZeroCrossingCounter.h.

UINT ZeroCrossingCounter::getFeatureMode ( ) const

inline

Gets the current featureMode, this will be either INDEPENDANT_FEATURE_MODE (0) or COMBINED_FEATURE_MODE (1).

Returns: returns an unsigned int representing the current feature mode

Definition at line 209 of file ZeroCrossingCounter.h.

std::string ZeroCrossingCounter::getId ( )

static

Gets a string that represents the ZeroCrossingCounter class.

Returns: returns a string containing the ID of this class

Definition at line 28 of file ZeroCrossingCounter.cpp.

UINT ZeroCrossingCounter::getNumFeatures ( ) const

inline

Gets the number of feature values computed for each input dimensions. The size of the feature vector will be getNumFeatures() * numInputDimensions.

Returns: returns an unsigned int representing the total number of zero crossing features per input dimension

Definition at line 202 of file ZeroCrossingCounter.h.

UINT ZeroCrossingCounter::getSearchWindowSize ( ) const

inline

Gets the search window size.

Returns: returns an unsigned int representing the search window size, returns zero if the feature extraction module has not been initialized

Definition at line 194 of file ZeroCrossingCounter.h.

bool ZeroCrossingCounter::init	(	const UINT	searchWindowSize,
		const Float	deadZoneThreshold,
		const UINT	numDimensions,
		const UINT	featureMode
	)

Initializes the ZeroCrossingCounter, setting the searchWindowSize, deadZoneThreshold, and dimensionality of the data it will filter. The search window size, deadZoneThreshold, and numDimensions values must be larger than 0. Sets all the data buffer values to zero.

Parameters

searchWindowSize	sets how much data should be held in memory and searched each time the update function is called
deadZoneThreshold	sets the dead zone threshold value
numDimensions	the dimensionality of the input data to filter
featureMode	sets how the features are added to the feature vector, shoule be either INDEPENDANT_FEATURE_MODE or COMBINED_FEATURE_MODE

Returns: true if the filter was initiliazed, false otherwise

Definition at line 172 of file ZeroCrossingCounter.cpp.

bool ZeroCrossingCounter::load ( std::fstream & file )

virtual

This loads the feature extraction settings from a file. This overrides the load function in the FeatureExtraction base class.

Parameters

file	a reference to the file to load the settings from

Returns: returns true if the settings were loaded successfully, false otherwise

Reimplemented from MLBase.

Definition at line 125 of file ZeroCrossingCounter.cpp.

ZeroCrossingCounter & ZeroCrossingCounter::operator= ( const ZeroCrossingCounter & rhs )

Sets the equals operator, copies the data from the rhs instance to this instance.

Parameters

rhs	another instance of the ZeroCrossingCounter class from which the data will be copied to this instance

Returns: a reference to this instance of ZeroCrossingCounter

Definition at line 48 of file ZeroCrossingCounter.cpp.

bool ZeroCrossingCounter::reset ( )

virtual

Sets the FeatureExtraction reset function, overwriting the base FeatureExtraction function. This function is called by the GestureRecognitionPipeline when the pipelines main reset() function is called. This function resets the feature extraction by re-initiliazing the instance.

Returns: true if the filter was reset, false otherwise

Reimplemented from MLBase.

Definition at line 94 of file ZeroCrossingCounter.cpp.

bool ZeroCrossingCounter::save ( std::fstream & file ) const

virtual

This saves the feature extraction settings to a file. This overrides the save function in the FeatureExtraction base class.

Parameters

file	a reference to the file to save the settings to

Returns: returns true if the settings were saved successfully, false otherwise

Reimplemented from MLBase.

Definition at line 101 of file ZeroCrossingCounter.cpp.

bool ZeroCrossingCounter::setDeadZoneThreshold ( const Float deadZoneThreshold )

Sets the deadZoneThreshold. The deadZoneThreshold must be larger than zero. Calling this function will reset the feature extraction.

Parameters

deadZoneThreshold sets the dead zone threshold value

Returns: true if the deadZoneThreshold value was updated, false otherwise

Definition at line 290 of file ZeroCrossingCounter.cpp.

bool ZeroCrossingCounter::setFeatureMode ( const UINT featureMode )

Sets the featureMode, this should be either INDEPENDANT_FEATURE_MODE (0) or COMBINED_FEATURE_MODE (1). Calling this function will reset the feature extraction.

Parameters

featureMode sets the featureMode, options are either INDEPENDANT_FEATURE_MODE (0) or COMBINED_FEATURE_MODE (1)

Returns: true if the featureMode value was updated, false otherwise

Definition at line 280 of file ZeroCrossingCounter.cpp.

bool ZeroCrossingCounter::setSearchWindowSize ( const UINT searchWindowSize )

Sets the search window size. The search window size must be larger than zero. Calling this function will reset the feature extraction.

Parameters

searchWindowSize sets how much data should be held in memory and searched each time the update function is called

Returns: true if the searchWindowSize value was updated, false otherwise

Definition at line 270 of file ZeroCrossingCounter.cpp.

VectorFloat ZeroCrossingCounter::update ( const Float x )

Computes the ZeroCrossingCounter features from the input, this should only be called if the dimensionality of this instance was set to 1.

Parameters

x	the value to compute features from, this should only be called if the dimensionality of the filter was set to 1

Returns: a vector containing the ZeroCrossingCounter features, an empty vector will be returned if the features were not computed

Definition at line 215 of file ZeroCrossingCounter.cpp.

VectorFloat ZeroCrossingCounter::update ( const VectorFloat & x )

Computes the ZeroCrossingCounter features from the input, the dimensionality of x should match that of this instance.

Parameters

x	a vector containing the values to be processed, must be the same size as the numInputDimensions

Returns: a vector containing the ZeroCrossingCounter features, an empty vector will be returned if the features were not computed

Definition at line 219 of file ZeroCrossingCounter.cpp.

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

Public Types

Public Member Functions

Static Public Member Functions

Protected Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation