#include <SwipeDetector.h>

Inheritance diagram for SwipeDetector:

Public Types
enum	SwipeDirections { POSITIVE_SWIPE =0, NEGATIVE_SWIPE }

Public Types inherited from Classifier
typedef std::map< std::string, Classifier ()() >	StringClassifierMap

Public Types inherited from MLBase
enum	BaseTypes { BASE_TYPE_NOT_SET =0, CLASSIFIER, REGRESSIFIER, CLUSTERER }

Public Member Functions
	SwipeDetector (const unsigned int swipeIndex=0, const unsigned int swipeThreshold=100, const unsigned int hysteresisThreshold=0, const unsigned int swipeDirection=POSITIVE_SWIPE, bool useScaling=false)

	SwipeDetector (const SwipeDetector &rhs)

virtual	~SwipeDetector (void)

SwipeDetector &	operator= (const SwipeDetector &rhs)

virtual bool	deepCopyFrom (const Classifier *classifier)

bool	init (const unsigned int numInputDimensions)

virtual bool	train_ (ClassificationData &trainingData)

virtual bool	predict_ (VectorDouble &inputVector)

virtual bool	clear ()

virtual bool	reset ()

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

virtual bool	loadModelFromFile (std::fstream &file)

bool	getSwipeDetected () const

Float	getSwipeValue () const

Float	getSwipeThreshold () const

Float	getHysteresisThreshold () const

Float	getMovementVelocity () const

Float	getMovementThreshold () const

Float	getContextValue () const

Float	getSwipeIntegrationCoeff () const

bool	setContext (const bool context)

bool	setSwipeIndex (const unsigned int swipeIndex)

bool	setSwipeDirection (const unsigned int swipeDirection)

bool	setSwipeThreshold (const Float swipeThreshold)

bool	setHysteresisThreshold (const Float hysteresisThreshold)

bool	setMovementThreshold (const Float movementThreshold)

bool	setSwipeIntegrationCoeff (const Float swipeIntegrationCoeff)

Public Member Functions inherited from Classifier
	Classifier (void)

virtual	~Classifier (void)

bool	copyBaseVariables (const Classifier *classifier)

std::string	getClassifierType () const

bool	getSupportsNullRejection () const

bool	getNullRejectionEnabled () const

Float	getNullRejectionCoeff () const

Float	getMaximumLikelihood () const

Float	getBestDistance () const

Float	getPhase () const

virtual UINT	getNumClasses () const

UINT	getClassLabelIndexValue (UINT classLabel) const

UINT	getPredictedClassLabel () const

VectorFloat	getClassLikelihoods () const

VectorFloat	getClassDistances () const

VectorFloat	getNullRejectionThresholds () const

Vector< UINT >	getClassLabels () const

Vector< MinMax >	getRanges () const

bool	enableNullRejection (bool useNullRejection)

virtual bool	setNullRejectionCoeff (Float nullRejectionCoeff)

virtual bool	setNullRejectionThresholds (VectorFloat newRejectionThresholds)

virtual bool	recomputeNullRejectionThresholds ()

bool	getTimeseriesCompatible () const

Classifier *	createNewInstance () const

Classifier *	deepCopy () const

const Classifier *	getClassifierPointer () const

const Classifier &	getBaseClassifier () const

Public Member Functions inherited from MLBase
	MLBase (void)

virtual	~MLBase (void)

bool	copyMLBaseVariables (const MLBase *mlBase)

virtual bool	train (ClassificationData trainingData)

virtual bool	train (RegressionData trainingData)

virtual bool	train_ (RegressionData &trainingData)

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 (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)

virtual bool	saveModelToFile (std::string filename) const

virtual bool	loadModelFromFile (std::string filename)

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

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

virtual std::string	getModelAsString () const

DataType	getInputType () const

DataType	getOutputType () const

UINT	getBaseType () const

UINT	getNumInputFeatures () const

UINT	getNumInputDimensions () const

UINT	getNumOutputDimensions () const

UINT	getMinNumEpochs () const

UINT	getMaxNumEpochs () const

UINT	getValidationSetSize () const

UINT	getNumTrainingIterationsToConverge () const

Float	getMinChange () const

Float	getLearningRate () const

Float	getRootMeanSquaredTrainingError () const

Float	getTotalSquaredTrainingError () const

Float	getValidationSetAccuracy () const

VectorFloat	getValidationSetPrecision () const

VectorFloat	getValidationSetRecall () const

bool	getUseValidationSet () const

bool	getRandomiseTrainingOrder () const

bool	getTrained () const

bool	getModelTrained () const

bool	getScalingEnabled () const

bool	getIsBaseTypeClassifier () const

bool	getIsBaseTypeRegressifier () const

bool	getIsBaseTypeClusterer () const

bool	enableScaling (const bool useScaling)

bool	setMaxNumEpochs (const UINT maxNumEpochs)

bool	setMinNumEpochs (const UINT minNumEpochs)

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	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 (void)

virtual	~GRTBase (void)

bool	copyGRTBaseVariables (const GRTBase *GRTBase)

std::string	getClassType () 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)

GRTBase *	getGRTBasePointer ()

const GRTBase *	getGRTBasePointer () 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)

Protected Attributes
bool	firstSample

bool	swipeDetected

bool	contextInput

unsigned int	swipeIndex

unsigned int	swipeDirection

unsigned int	contextFilterSize

Float	swipeIntegrationCoeff

Float	movementIntegrationCoeff

Float	swipeThreshold

Float	hysteresisThreshold

Float	swipeVelocity

Float	movementVelocity

Float	movementThreshold

Float	contextFilteredValue

VectorFloat	lastX

GRT::ThresholdCrossingDetector	thresholdDetector

GRT::MedianFilter	contextFilter

Protected Attributes inherited from Classifier
std::string	classifierType

bool	supportsNullRejection

bool	useNullRejection

UINT	numClasses

UINT	predictedClassLabel

UINT	classifierMode

Float	nullRejectionCoeff

Float	maxLikelihood

Float	bestDistance

Float	phase

VectorFloat	classLikelihoods

VectorFloat	classDistances

VectorFloat	nullRejectionThresholds

Vector< UINT >	classLabels

Vector< MinMax >	ranges

Protected Attributes inherited from MLBase
bool	trained

bool	useScaling

DataType	inputType

DataType	outputType

UINT	baseType

UINT	numInputDimensions

UINT	numOutputDimensions

UINT	numTrainingIterationsToConverge

UINT	minNumEpochs

UINT	maxNumEpochs

UINT	validationSetSize

Float	learningRate

Float	minChange

Float	rootMeanSquaredTrainingError

Float	totalSquaredTrainingError

Float	validationSetAccuracy

bool	useValidationSet

bool	randomiseTrainingOrder

VectorFloat	validationSetPrecision

VectorFloat	validationSetRecall

Random	random

std::vector< TrainingResult >	trainingResults

TrainingResultsObserverManager	trainingResultsObserverManager

TestResultsObserverManager	testResultsObserverManager

Protected Attributes inherited from GRTBase
std::string	classType

DebugLog	debugLog

ErrorLog	errorLog

InfoLog	infoLog

TrainingLog	trainingLog

TestingLog	testingLog

WarningLog	warningLog

Static Protected Attributes
static RegisterClassifierModule< SwipeDetector >	registerModule

Additional Inherited Members
Static Public Member Functions inherited from Classifier
static Classifier *	createInstanceFromString (std::string const &classifierType)

static Vector< std::string >	getRegisteredClassifiers ()

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

static std::string	getGRTRevison ()

Protected Types inherited from Classifier
enum	ClassifierModes { STANDARD_CLASSIFIER_MODE =0, TIMESERIES_CLASSIFIER_MODE }

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

bool	loadBaseSettingsFromFile (std::fstream &file)

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

bool	loadBaseSettingsFromFile (std::fstream &file)

Protected Member Functions inherited from GRTBase
Float	SQR (const Float &x) const

Static Protected Member Functions inherited from Classifier
static StringClassifierMap *	getMap ()

Detailed Description

GRT MIT License Copyright (c) <2012> <Nicholas Gillian, Media Lab, MIT>

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Definition at line 40 of file SwipeDetector.h.

Constructor & Destructor Documentation

SwipeDetector::SwipeDetector	(	const unsigned int	swipeIndex = `0`,
		const unsigned int	swipeThreshold = `100`,
		const unsigned int	hysteresisThreshold = `0`,
		const unsigned int	swipeDirection = `POSITIVE_SWIPE`,
		bool	useScaling = `false`
	)

Default Constructor

Parameters

useScaling sets if the training and prediction data should be scaled to a specific range. Default value is useScaling = false

Definition at line 28 of file SwipeDetector.cpp.

SwipeDetector::SwipeDetector ( const SwipeDetector & rhs )

Defines the copy constructor.

Parameters

rhs	the instance from which all the data will be copied into this instance

Definition at line 55 of file SwipeDetector.cpp.

SwipeDetector::~SwipeDetector ( void )

virtual

Default Destructor

Definition at line 73 of file SwipeDetector.cpp.

Member Function Documentation

bool SwipeDetector::clear ( )

virtual

This overrides the clear function in the Classifier base class. It will completely clear the ML module, removing any trained model and setting all the base variables to their default values.

Returns: returns true if the module was cleared succesfully, false otherwise

Reimplemented from Classifier.

Definition at line 247 of file SwipeDetector.cpp.

bool SwipeDetector::deepCopyFrom ( const Classifier * classifier )

virtual

This is required for the Gesture Recognition Pipeline for when the pipeline.setClassifier(...) method is called. It clones the data from the Base Class Classifier pointer (which should be pointing to an SwipeDetector instance) into this instance

Parameters

classifier a pointer to the Classifier Base Class, this should be pointing to another SwipeDetector instance

Returns: returns true if the clone was successfull, false otherwise

Reimplemented from Classifier.

Definition at line 104 of file SwipeDetector.cpp.

Float SwipeDetector::getContextValue ( ) const

Returns: returns the context value, this is the latest output of the context filter

Definition at line 445 of file SwipeDetector.cpp.

Float SwipeDetector::getHysteresisThreshold ( ) const

Returns: returns the hysteresis threshold, this is the value that the swipe analysis value must cross (after a valid swipe detection), before the next swipe will be detected

Definition at line 433 of file SwipeDetector.cpp.

Float SwipeDetector::getMovementThreshold ( ) const

Returns: returns the movement threshold, the movement velocity must be below this value for a valid swipe to be detected

Definition at line 441 of file SwipeDetector.cpp.

Float SwipeDetector::getMovementVelocity ( ) const

This function returns the movement velocity. This is the integrated difference between each of the additional inputs (that are not the swipe index) that is used to detected a valid swipe. The movement velocity must be below the movement threshold for a valid swipe to be detected.

Returns: returns the movement velocity

Definition at line 437 of file SwipeDetector.cpp.

bool SwipeDetector::getSwipeDetected ( ) const

Returns: returns true if a swipe was detected, false otherwise

Definition at line 421 of file SwipeDetector.cpp.

Float SwipeDetector::getSwipeIntegrationCoeff ( ) const

Returns: returns the swipe integration coeff

Definition at line 449 of file SwipeDetector.cpp.

Float SwipeDetector::getSwipeThreshold ( ) const

Returns: returns the swipe threshold, this is the value that the swipe analysis value must cross for a swipe to be trigger

Definition at line 429 of file SwipeDetector.cpp.

Float SwipeDetector::getSwipeValue ( ) const

Returns: returns the swipe analysis value, this is the value that the swipe threshold is matched against

Definition at line 425 of file SwipeDetector.cpp.

bool SwipeDetector::loadModelFromFile ( std::fstream & file )

virtual

This loads a trained SwipeDetector model from a file. This overrides the loadModelFromFile function in the Classifier base class.

Parameters

file	a reference to the file the SwipeDetector model will be loaded from

Returns: returns true if the model was loaded successfully, false otherwise

Reimplemented from MLBase.

Definition at line 321 of file SwipeDetector.cpp.

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

Defines how the data from the rhs SwipeDetector should be copied to this SwipeDetector

Parameters

rhs	another instance of a SwipeDetector

Returns: returns a pointer to this instance of the SwipeDetector

Definition at line 77 of file SwipeDetector.cpp.

bool SwipeDetector::predict_ ( VectorDouble & inputVector )

virtual

This predicts the class of the inputVector. This overrides the predict function in the Classifier base class.

Parameters

inputVector the input vector to classify

Returns: returns true if the prediction was performed, false otherwise

Reimplemented from MLBase.

Definition at line 189 of file SwipeDetector.cpp.

bool SwipeDetector::reset ( )

virtual

This overrides the reset function in the Classifier base class.

Returns: returns true if the module was reset succesfully, false otherwise

Reimplemented from Classifier.

Definition at line 257 of file SwipeDetector.cpp.

bool SwipeDetector::saveModelToFile ( std::fstream & file ) const

virtual

This saves the trained SwipeDetector model to a file. This overrides the saveModelToFile function in the Classifier base class.

Parameters

file	a reference to the file the SwipeDetector model will be saved to

Returns: returns true if the model was saved successfully, false otherwise

Reimplemented from MLBase.

Definition at line 284 of file SwipeDetector.cpp.

bool SwipeDetector::setContext ( const bool context )

This function lets you set the current context input. This should be called before you call the predict function.

Returns: returns true if the context value was updated, false otherwise

Definition at line 453 of file SwipeDetector.cpp.

bool SwipeDetector::setHysteresisThreshold ( const Float hysteresisThreshold )

This function lets you set the swipe hysteresisThreshold, this is the threshold that the swipe analysis value must pass after a valid swipe before a new swipe can be detected.

Parameters

hysteresisThreshold the new hysteresis threshold

Returns: returns true if the parameter was updated, false otherwise

Definition at line 483 of file SwipeDetector.cpp.

bool SwipeDetector::setMovementThreshold ( const Float movementThreshold )

This function lets you set the swipe movementThreshold. The movement index must be below the movementThreshold for a valid swipe to be detected.

Parameters

movementThreshold the new movement threshold

Returns: returns true if the parameter was updated, false otherwise

Definition at line 489 of file SwipeDetector.cpp.

bool SwipeDetector::setSwipeDirection ( const unsigned int swipeDirection )

This function lets you set the swipe direction, this should be one of the SwipeDirections enums.

Parameters

swipeDirection the direction you want to search for a swipe in

Returns: returns true if the parameter was updated, false otherwise

Definition at line 464 of file SwipeDetector.cpp.

bool SwipeDetector::setSwipeIndex ( const unsigned int swipeIndex )

This function lets you set the swipe index, this is the index in the input vector that contains the main axis you want to use for the swipe detection. The other elements in the input vector will be combined to compute the movement index. The swipeIndex should be a valid index in your input vector.

Parameters

swipeIndex the index in the input vector you want to use for the swipe detection

Returns: returns true if the parameter was updated, false otherwise

Definition at line 458 of file SwipeDetector.cpp.

bool SwipeDetector::setSwipeIntegrationCoeff ( const Float swipeIntegrationCoeff )

This function lets you set the swipe integration coeff. This controls how much 'memory' is used to when integrating the input data.

Parameters

swipeIntegrationCoeff the new integration coefficient

Returns: returns true if the parameter was updated, false otherwise

Definition at line 495 of file SwipeDetector.cpp.

bool SwipeDetector::setSwipeThreshold ( const Float swipeThreshold )

This function lets you set the swipe threshold, this is the threshold that the swipe analysis value must pass for a swipe to be detected.

Parameters

swipeThreshold the new swipe threshold

Returns: returns true if the parameter was updated, false otherwise

Definition at line 477 of file SwipeDetector.cpp.

bool SwipeDetector::train_ ( ClassificationData & trainingData )

virtual

This trains the SwipeDetector model, using the labelled classification data. This overrides the train function in the Classifier base class.

Parameters

trainingData a reference to the training data

Returns: returns true if the SwipeDetector model was trained, false otherwise

Reimplemented from MLBase.

Definition at line 155 of file SwipeDetector.cpp.

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

Public Types

Public Member Functions

Protected Attributes

Static Protected Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation