#include <FFTFeatures.h>

Inheritance diagram for FFTFeatures:

Public Member Functions
	FFTFeatures (UINT fftWindowSize=512, UINT numChannelsInFFTSignal=1, bool computeMaxFreqFeature=true, bool computeMaxFreqSpectrumRatio=true, bool computeCentroidFeature=true, bool computeTopNFreqFeatures=true, UINT N=10)

	FFTFeatures (const FFTFeatures &rhs)

virtual	~FFTFeatures (void)

FFTFeatures &	operator= (const FFTFeatures &rhs)

virtual bool	deepCopyFrom (const FeatureExtraction *featureExtraction)

virtual bool	computeFeatures (const VectorFloat &inputVector)

virtual bool	reset ()

virtual bool	saveModelToFile (std::string filename) const

virtual bool	loadModelFromFile (std::string filename)

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

virtual bool	loadModelFromFile (std::fstream &file)

bool	init (UINT fftWindowSize, UINT numChannelsInFFTSignal, bool computeMaxFreqFeature, bool computeMaxFreqSpectrumRatio, bool computeCentroidFeature, bool computeTopNFreqFeatures, UINT N)

Public Member Functions inherited from FeatureExtraction
	FeatureExtraction ()

virtual	~FeatureExtraction ()

bool	copyBaseVariables (const FeatureExtraction *featureExtractionModule)

virtual bool	computeFeatures (const MatrixFloat &inputMatrix)

virtual bool	clear ()

std::string	getFeatureExtractionType () const

UINT	getNumInputDimensions () const

UINT	getNumOutputDimensions () const

bool	getInitialized () const

bool	getFeatureDataReady () const

const VectorFloat &	getFeatureVector () const

const MatrixFloat &	getFeatureMatrix () const

FeatureExtraction *	createNewInstance () 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_ (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_ (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	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
UINT	fftWindowSize

UINT	numChannelsInFFTSignal

bool	computeMaxFreqFeature

bool	computeMaxFreqSpectrumRatio

bool	computeCentroidFeature

bool	computeTopNFreqFeatures

UINT	N

Float	maxFreqFeature

Float	maxFreqSpectrumRatio

Float	centroidFeature

VectorFloat	topNFreqFeatures

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

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 RegisterFeatureExtractionModule< FFTFeatures >	registerModule

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

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

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

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

static std::string	getGRTRevison ()

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)

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

Static Protected Member Functions inherited from FeatureExtraction
static StringFeatureExtractionMap *	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 37 of file FFTFeatures.h.

Constructor & Destructor Documentation

FFTFeatures::FFTFeatures	(	UINT	fftWindowSize = `512`,
		UINT	numChannelsInFFTSignal = `1`,
		bool	computeMaxFreqFeature = `true`,
		bool	computeMaxFreqSpectrumRatio = `true`,
		bool	computeCentroidFeature = `true`,
		bool	computeTopNFreqFeatures = `true`,
		UINT	N = `10`
	)

Default Constructor, sets the default settings for the FFTFeatures module. The fftWindowSize and numChannelsInFFTSignal parameters should match the settings of the FFT module that will be used as input to this module.

Parameters

fftWindowSize	the window size of the FFT that will be used as input to this module. Default value = 512
numChannelsInFFTSignal	this is the number of channels (i.e. input dimensions) to the FFT module. Default value = 1
computeMaxFreqFeature	sets if the maximum frequency feature will be included in the feature vector. Default value = true
computeMaxFreqSpectrumRatio	sets if the maximum-frequency spectrum-frequency ratio feature will be included in the feature vector. Default value = true
computeCentroidFeature	sets if the centroid frequency feature will be included in the feature vector. Default value = true
computeTopNFreqFeatures	sets if the top N frequency feature will be included in the feature vector. Default value = true
N	sets if size of N for the top N frequency features. Default value = 10

Definition at line 30 of file FFTFeatures.cpp.

FFTFeatures::FFTFeatures ( const FFTFeatures & rhs )

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

Parameters

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

Definition at line 44 of file FFTFeatures.cpp.

FFTFeatures::~FFTFeatures ( void )

virtual

Default Destructor

Definition at line 57 of file FFTFeatures.cpp.

Member Function Documentation

bool FFTFeatures::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).

Parameters

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

Returns: true if the data was processed, false otherwise

Reimplemented from FeatureExtraction.

Definition at line 269 of file FFTFeatures.cpp.

bool FFTFeatures::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 pipeline.

Parameters

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

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

Reimplemented from FeatureExtraction.

Definition at line 80 of file FFTFeatures.cpp.

bool FFTFeatures::init	(	UINT	fftWindowSize,
		UINT	numChannelsInFFTSignal,
		bool	computeMaxFreqFeature,
		bool	computeMaxFreqSpectrumRatio,
		bool	computeCentroidFeature,
		bool	computeTopNFreqFeatures,
		UINT	N
	)

Initializes the FFTFeatures. Should be called before calling the computeFFT(...) or computeFeatures(...) methods. This function is automatically called by the constructor.

Parameters

fftWindowSize	the window size of the FFT that will be used as input to this module. Default value = FFT::FFT_WINDOW_SIZE_512
numChannelsInFFTSignal	the size of the FFT feature vector that will be used as input to this module. Default value = 1
computeMaxFreqFeature	sets if the maximum frequency feature will be included in the feature vector. Default value = true
computeMaxFreqSpectrumRatio	sets if the maximum-frequency spectrum-frequency ratio feature will be included in the feature vector. Default value = true
computeCentroidFeature	sets if the centroid frequency feature will be included in the feature vector. Default value = true
computeTopNFreqFeatures	sets if the top N frequency feature will be included in the feature vector. Default value = true
N	sets if size of N for the top N frequency features. Default value = 10

Returns: true if the FTT was initialized, false otherwise

Definition at line 231 of file FFTFeatures.cpp.

bool FFTFeatures::loadModelFromFile ( std::string filename )

virtual

This saves the feature extraction settings to a file.

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 111 of file FFTFeatures.cpp.

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

virtual

This loads the feature extraction settings from a file. This overrides the loadSettingsFromFile 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 FeatureExtraction.

Definition at line 154 of file FFTFeatures.cpp.

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

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

Parameters

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

Returns: a reference to this instance of FFT

Definition at line 61 of file FFTFeatures.cpp.

bool FFTFeatures::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 FFTFeatures by re-initiliazing the instance.

Returns: true if the FFTFeatures was reset, false otherwise

Reimplemented from FeatureExtraction.

Definition at line 346 of file FFTFeatures.cpp.

bool FFTFeatures::saveModelToFile ( std::string filename ) const

virtual

This saves the feature extraction settings to a file.

Parameters

filename the filename to save the settings to

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

Reimplemented from MLBase.

Definition at line 97 of file FFTFeatures.cpp.

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

virtual

This saves the feature extraction settings to a file. This overrides the saveSettingsToFile 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 FeatureExtraction.

Definition at line 126 of file FFTFeatures.cpp.

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

Public Member Functions

Protected Attributes

Static Protected Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation