The class implements a Float moving average filter. More...

#include <DoubleMovingAverageFilter.h>

Inheritance diagram for DoubleMovingAverageFilter:

Public Member Functions
	DoubleMovingAverageFilter (const UINT filterSize=5, const UINT numDimensions=1)

	DoubleMovingAverageFilter (const DoubleMovingAverageFilter &rhs)

virtual	~DoubleMovingAverageFilter ()

DoubleMovingAverageFilter &	operator= (const DoubleMovingAverageFilter &rhs)

virtual bool	deepCopyFrom (const PreProcessing *preProcessing)

virtual bool	process (const VectorFloat &inputVector)

virtual bool	reset ()

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

virtual bool	load (std::fstream &file)

bool	init (UINT filterSize, UINT numDimensions)

Float	filter (const Float x)

VectorFloat	filter (const VectorFloat &x)

VectorFloat	getFilteredData () const

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

virtual	~PreProcessing (void)

bool	copyBaseVariables (const PreProcessing *preProcessingModule)

virtual bool	clear () override

bool	getInitialized () const

VectorFloat	getProcessedData () const

PreProcessing *	create () const

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

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

	GRT_DEPRECATED_MSG ("getPreProcessingType is deprecated, use getId() instead", std::string getPreProcessingType() 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 PreProcessing
static PreProcessing *	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	filterSize
	The size of the filter.

MovingAverageFilter	filter1
	The first moving average filter.

MovingAverageFilter	filter2
	The second moving average filter.

Protected Attributes inherited from PreProcessing
std::string	preProcessingType

bool	initialized

VectorFloat	processedData

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
Public Types inherited from PreProcessing
typedef std::map< std::string, PreProcessing ()() >	StringPreProcessingMap

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

Protected Member Functions inherited from PreProcessing
bool	init ()

bool	savePreProcessingSettingsToFile (std::fstream &file) const

bool	loadPreProcessingSettingsFromFile (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 PreProcessing
static StringPreProcessingMap *	getMap ()

Detailed Description

The class implements a Float moving average filter.

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.

Examples:: PreprocessingModulesExamples/DoubleMovingAverageFilterExample/DoubleMovingAverageFilterExample.cpp.

Definition at line 39 of file DoubleMovingAverageFilter.h.

Constructor & Destructor Documentation

DoubleMovingAverageFilter::DoubleMovingAverageFilter	(	const UINT	filterSize = `5`,
		const UINT	numDimensions = `1`
	)

Constructor, sets the size of the Float moving average filter and the dimensionality of the data it will filter.

Parameters

filterSize	the size of the moving average filter, should be a value greater than zero. Default filterSize = 5
numDimensions	the dimensionality of the data to filter. Default numDimensions = 1

Definition at line 42 of file DoubleMovingAverageFilter.cpp.

DoubleMovingAverageFilter::DoubleMovingAverageFilter ( const DoubleMovingAverageFilter & rhs )

Copy Constructor, copies the DoubleMovingAverageFilter from the rhs instance to this instance

Parameters

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

Definition at line 47 of file DoubleMovingAverageFilter.cpp.

DoubleMovingAverageFilter::~DoubleMovingAverageFilter ( )

virtual

Default Destructor

Definition at line 52 of file DoubleMovingAverageFilter.cpp.

Member Function Documentation

bool DoubleMovingAverageFilter::deepCopyFrom ( const PreProcessing * preProcessing )

virtual

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

Parameters

preProcessing a pointer to another instance of a DoubleMovingAverageFilter, the values of that instance will be cloned to this instance

Returns: true if the deep coy was successful, false otherwise

Reimplemented from PreProcessing.

Definition at line 68 of file DoubleMovingAverageFilter.cpp.

Float DoubleMovingAverageFilter::filter ( const Float x )

Filters the input, this should only be called if the dimensionality of the filter was set to 1.

Parameters

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

Returns: the filtered value. Zero will be returned if the value was not filtered

Examples:: PreprocessingModulesExamples/DoubleMovingAverageFilterExample/DoubleMovingAverageFilterExample.cpp.

Definition at line 213 of file DoubleMovingAverageFilter.cpp.

VectorFloat DoubleMovingAverageFilter::filter ( const VectorFloat & x )

Filters the input, the dimensionality of the input vector should match that of the filter.

Parameters

x	the values to filter, the dimensionality of the input vector should match that of the filter

Returns: the filtered values. An empty vector will be returned if the values were not filtered

Definition at line 227 of file DoubleMovingAverageFilter.cpp.

VectorFloat DoubleMovingAverageFilter::getFilteredData ( ) const

Returns the last value(s) that were filtered.

Returns: the filtered values. An empty vector will be returned if the values were not filtered

Definition at line 260 of file DoubleMovingAverageFilter.cpp.

std::string DoubleMovingAverageFilter::getId ( )

static

Gets a string that represents the ID of this class.

Returns: returns a string containing the ID of this class

Definition at line 37 of file DoubleMovingAverageFilter.cpp.

bool DoubleMovingAverageFilter::init	(	UINT	filterSize,
		UINT	numDimensions
	)

Initializes the filter, setting the filter size and dimensionality of the data it will filter. Sets all the filter values to zero.

Parameters

filterSize	the size of the Float moving average filter, should be a value greater than zero
numDimensions	the dimensionality of the data to filter

Returns: true if the filter was initiliazed, false otherwise

Definition at line 175 of file DoubleMovingAverageFilter.cpp.

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

virtual

This loads the DoubleMovingAverageFilter settings from a file. This overrides the load function in the PreProcessing base class.

Parameters

file	a reference to the file to load the settings from

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

Reimplemented from MLBase.

Examples:: PreprocessingModulesExamples/DoubleMovingAverageFilterExample/DoubleMovingAverageFilterExample.cpp.

Definition at line 130 of file DoubleMovingAverageFilter.cpp.

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

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

Parameters

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

Returns: a reference to this instance of DoubleMovingAverageFilter

Definition at line 56 of file DoubleMovingAverageFilter.cpp.

bool DoubleMovingAverageFilter::process ( const VectorFloat & inputVector )

virtual

Sets the PreProcessing process function, overwriting the base PreProcessing 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 DoubleMovingAverageFilter's filter function.

Parameters

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

Returns: true if the data was processed, false otherwise

Reimplemented from PreProcessing.

Definition at line 91 of file DoubleMovingAverageFilter.cpp.

bool DoubleMovingAverageFilter::reset ( )

virtual

Sets the PreProcessing reset function, overwriting the base PreProcessing function. This function is called by the GestureRecognitionPipeline when the pipelines main reset() function is called. This function resets the filter values by re-initiliazing the filter.