GestureRecognitionToolkit  Version: 0.2.5
The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, c++ machine learning library for real-time gesture recognition.
Public Member Functions | Static Public Member Functions | Protected Attributes | List of all members
MovingAverageFilter Class Reference

The MovingAverageFilter implements a low pass moving average filter. More...

#include <MovingAverageFilter.h>

Inheritance diagram for MovingAverageFilter:
PreProcessing MLBase GRTBase Observer< TrainingResult > Observer< TestInstanceResult >

Public Member Functions

 MovingAverageFilter (const UINT filterSize=5, const UINT numDimensions=1)
 
 MovingAverageFilter (const MovingAverageFilter &rhs)
 
virtual ~MovingAverageFilter ()
 
MovingAverageFilter & operator= (const MovingAverageFilter &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 (const UINT filterSize, const UINT numDimensions)
 
Float filter (const Float x)
 
VectorFloat filter (const VectorFloat &x)
 
UINT getFilterSize () const
 
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.
 
UINT inputSampleCounter
 A counter to keep track of the number of input samples.
 
CircularBuffer< VectorFloat > dataBuffer
 A buffer to store the previous N values, N = filterSize.
 
- 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 MovingAverageFilter implements a low pass 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/MovingAverageFilterExample/MovingAverageFilterExample.cpp.

Definition at line 38 of file MovingAverageFilter.h.

Constructor & Destructor Documentation

MovingAverageFilter::MovingAverageFilter ( const UINT  filterSize = 5,
const UINT  numDimensions = 1 
)

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

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

Definition at line 33 of file MovingAverageFilter.cpp.

MovingAverageFilter::MovingAverageFilter ( const MovingAverageFilter &  rhs)

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

Parameters
rhsanother instance of the MovingAverageFilter class from which the data will be copied to this instance

Definition at line 38 of file MovingAverageFilter.cpp.

MovingAverageFilter::~MovingAverageFilter ( )
virtual

Default Destructor

Definition at line 48 of file MovingAverageFilter.cpp.

Member Function Documentation

bool MovingAverageFilter::deepCopyFrom ( const PreProcessing *  preProcessing)
virtual

Sets the PreProcessing deepCopyFrom function, overwriting the base PreProcessing function. This function is used to deep copy 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
preProcessinga pointer to another instance of a MovingAverageFilter, the values of that instance will be cloned to this instance
Returns
true if the deep copy was successful, false otherwise

Reimplemented from PreProcessing.

Definition at line 71 of file MovingAverageFilter.cpp.

Float MovingAverageFilter::filter ( const Float  x)

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

Parameters
xthe 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/MovingAverageFilterExample/MovingAverageFilterExample.cpp.

Definition at line 205 of file MovingAverageFilter.cpp.

VectorFloat MovingAverageFilter::filter ( const VectorFloat &  x)

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

Parameters
xthe 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 219 of file MovingAverageFilter.cpp.

VectorFloat MovingAverageFilter::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 250 of file MovingAverageFilter.cpp.

UINT MovingAverageFilter::getFilterSize ( ) const

Gets the current filter size.

Returns
returns the filter size

Definition at line 248 of file MovingAverageFilter.cpp.

std::string MovingAverageFilter::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 28 of file MovingAverageFilter.cpp.

bool MovingAverageFilter::init ( const UINT  filterSize,
const 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
filterSizethe size of the moving average filter, should be a value greater than zero
Returns
true if the filter was initiliazed, false otherwise

Definition at line 174 of file MovingAverageFilter.cpp.

bool MovingAverageFilter::load ( std::fstream &  file)
virtual

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

Parameters
filea 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/MovingAverageFilterExample/MovingAverageFilterExample.cpp.

Definition at line 129 of file MovingAverageFilter.cpp.

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

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

Parameters
rhsanother instance of the MovingAverageFilter class from which the data will be copied to this instance
Returns
a reference to this instance of MovingAverageFilter

Definition at line 52 of file MovingAverageFilter.cpp.

bool MovingAverageFilter::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 MovingAverageFilter's filter function.

Parameters
inputVectorthe 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 89 of file MovingAverageFilter.cpp.

bool MovingAverageFilter::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.

Returns
true if the filter was reset, false otherwise

Reimplemented from PreProcessing.

Definition at line 108 of file MovingAverageFilter.cpp.

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

This saves the current settings of the MovingAverageFilter to a file. This overrides the save function in the PreProcessing base class.

Parameters
filea reference to the file the settings will be saved to
Returns
returns true if the settings were saved successfully, false otherwise

Reimplemented from MLBase.

Examples:
PreprocessingModulesExamples/MovingAverageFilterExample/MovingAverageFilterExample.cpp.

Definition at line 113 of file MovingAverageFilter.cpp.

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