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.
Derivative Class Reference

The Derivative class computes either the first or second order derivative of the input signal. More...

#include <Derivative.h>

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

Public Types

enum  DerivativeOrders { FIRST_DERIVATIVE =1, SECOND_DERIVATIVE }
 
- 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
}
 

Public Member Functions

 Derivative (const UINT derivativeOrder=FIRST_DERIVATIVE, const Float delta=1, const UINT numDimensions=1, const bool filterData=true, const UINT filterSize=3)
 
 Derivative (const Derivative &rhs)
 
virtual ~Derivative ()
 
Derivativeoperator= (const Derivative &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 derivativeOrder, const Float delta, const UINT numDimensions, const bool filterData, const UINT filterSize)
 
Float computeDerivative (const Float x)
 
VectorFloat computeDerivative (const VectorFloat &x)
 
bool setDerivativeOrder (const UINT derivativeOrder)
 
bool setFilterSize (const UINT filterSize)
 
bool setDelta (const Float delta)
 
bool enableFiltering (const bool filterData)
 
UINT getFilterSize () const
 
Float getDerivative (const UINT derivativeOrder=FIRST_DERIVATIVE) const
 
VectorFloat getDerivatives (const UINT derivativeOrder=FIRST_DERIVATIVE) 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
 
PreProcessingcreate () 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)
 
MLBasegetMLBasePointer ()
 
const MLBasegetMLBasePointer () const
 
Vector< TrainingResultgetTrainingResults () 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)
 
GRTBasegetGRTBasePointer ()
 
const GRTBasegetGRTBasePointer () 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 PreProcessingcreate (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 derivativeOrder
 The order of the derivative that will be computed (either FIRST_DERIVATIVE or SECOND_DERIVATIVE)
 
UINT filterSize
 The size of the filter used to filter the input data before the derivative is computed.
 
Float delta
 The estimated time between sensor samples.
 
bool filterData
 Flags if the input data should be filtered before the derivative is computed.
 
MovingAverageFilter filter
 The filter used to low pass filter the input data.
 
VectorFloat yy
 A buffer holding the previous input value(s)
 
VectorFloat yyy
 A buffer holding the previous first derivative values.
 
- 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< TrainingResulttrainingResults
 
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 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 StringPreProcessingMapgetMap ()
 

Detailed Description

The Derivative class computes either the first or second order derivative of the input signal.

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/DerivativeExample/DerivativeExample.cpp.

Definition at line 39 of file Derivative.h.

Constructor & Destructor Documentation

Derivative::Derivative ( const UINT  derivativeOrder = FIRST_DERIVATIVE,
const Float  delta = 1,
const UINT  numDimensions = 1,
const bool  filterData = true,
const UINT  filterSize = 3 
)

Constructor, sets the derivativeOrder (which should be either FIRST_DERIVATIVE or SECOND_DERIVATIVE), the delta value (which should be set to 1000.0/sampleRate, the dimensionality of the input data, if the data should be filtered before computing the derivative, and the size of the filter if the data is to be filtered.

Parameters
derivativeOrderthe derivative order, should be either FIRST_DERIVATIVE or SECOND_DERIVATIVE. Default derivativeOrder = FIRST_DERIVATIVE
deltasets the time between samples, this should be set to sampleRate/1000.0, where sampleRate is the sample rate of your sensor data. Default delta = 1.0
numDimensionsthe dimensionality of the input data. Default numDimensions = 1
filterDataa flag that sets if the data should be filtered before computing the derivative. Default filterData = true
filterSizethe size of the filter if the data is to be filtered

Definition at line 33 of file Derivative.cpp.

Derivative::Derivative ( const Derivative rhs)

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

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

Definition at line 38 of file Derivative.cpp.

Derivative::~Derivative ( )
virtual

Default Destructor

Definition at line 52 of file Derivative.cpp.

Member Function Documentation

Float Derivative::computeDerivative ( const Float  x)

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

Parameters
xthe value to compute the derivative of, this should only be called if the dimensionality of the filter was set to 1
Returns
the derivative of the input. Zero will be returned if the value was not computed
Examples:
PreprocessingModulesExamples/DerivativeExample/DerivativeExample.cpp.

Definition at line 248 of file Derivative.cpp.

VectorFloat Derivative::computeDerivative ( const VectorFloat x)

Computes the derivative of the input, the dimensionality of the input should match the number of inputs for the derivative

Parameters
xthe values to compute the derivative of, the dimensionality of the input should match the number of inputs for the derivative
Returns
the derivatives of the input. An empty vector will be returned if the values were not filtered

Definition at line 262 of file Derivative.cpp.

bool Derivative::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
preProcessinga pointer to another instance of a Derivative, 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 70 of file Derivative.cpp.

bool Derivative::enableFiltering ( const bool  filterData)

Sets if the input data will be filtered using a moving average filter before the derivative is computed. Updating this parameter will re-initialize this instance.

Parameters
filterDatasets if the data should be filtered before computing the derivative
Returns
returns true if the filterData parameter was set, false otherwise

Definition at line 316 of file Derivative.cpp.

Float Derivative::getDerivative ( const UINT  derivativeOrder = FIRST_DERIVATIVE) const

Gets the last computed derivative value. Will return either the first or second derivative (you can only get the second derivative if the derivativeOrder is set to 2nd derivative).

Parameters
derivativeOrderflags which derivative order you want, the default value is 0 which will return whatever the current derivativeOrder is
Returns
returns the last computed derivative value, will return 0 if no values have been computed

Definition at line 327 of file Derivative.cpp.

VectorFloat Derivative::getDerivatives ( const UINT  derivativeOrder = FIRST_DERIVATIVE) const

Gets the last computed derivative values. Will return either the first or second derivative (you can only get the second derivative if the derivativeOrder is set to 2nd derivative).

Parameters
derivativeOrderflags which derivative order you want, the default value is 0 which will return whatever the current derivativeOrder is
Returns
returns the last computed derivative values, will return 0 if no values have been computed

Definition at line 347 of file Derivative.cpp.

UINT Derivative::getFilterSize ( ) const

Gets the size of the moving average filter. If the instance has not been initialized then zero will be returned.

Returns
returns the size of the moving average filter, will return 0 if no values have been computed

Definition at line 322 of file Derivative.cpp.

std::string Derivative::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 Derivative.cpp.

bool Derivative::init ( const UINT  derivativeOrder,
const Float  delta,
const UINT  numDimensions,
const bool  filterData,
const UINT  filterSize 
)

Initializes the instance, sets the derivativeOrder (which should be either FIRST_DERIVATIVE or SECOND_DERIVATIVE), the delta value (which should be set to 1000.0/sampleRate, the dimensionality of the input data, if the data should be filtered before computing the derivative, and the size of the filter if the data is to be filtered.

Parameters
derivativeOrderthe derivative order, should be either FIRST_DERIVATIVE or SECOND_DERIVATIVE. Default derivativeOrder = FIRST_DERIVATIVE
deltasets the time between samples, this should be set to sampleRate/1000.0, where sampleRate is the sample rate of your sensor data. Default delta = 1.0
numDimensionsthe dimensionality of the input data. Default numDimensions = 1
filterDataa flag that sets if the data should be filtered before computing the derivative. Default filterData = true
filterSizethe size of the filter if the data is to be filtered
Returns
true if the instance was initiliazed, false otherwise

Definition at line 207 of file Derivative.cpp.

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

This loads the Derivative 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/DerivativeExample/DerivativeExample.cpp.

Definition at line 138 of file Derivative.cpp.

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

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

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

Definition at line 56 of file Derivative.cpp.

bool Derivative::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 Derivative's computeDerivative 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 96 of file Derivative.cpp.

bool Derivative::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 Derivative values by re-initiliazing the filter.

Returns
true if the Derivative was reset, false otherwise

Reimplemented from PreProcessing.

Definition at line 114 of file Derivative.cpp.

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

This saves the current settings of the Derivative 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/DerivativeExample/DerivativeExample.cpp.

Definition at line 119 of file Derivative.cpp.

bool Derivative::setDelta ( const Float  delta)

Sets the delta value. This is the time between samples and should be set to sampleRate/1000.0, where sampleRate is the sample rate of your sensor data. For example, if your sensor runs at 30FPS then delta would be 30.0/1000.0 = 0.03. Delta must be greater than zero. Setting delta will re-initialize this instance.

Parameters
deltathe estimated sampling time between sensor samples, must be greater than zero
Returns
returns true if delta was set, false otherwise
bool Derivative::setDerivativeOrder ( const UINT  derivativeOrder)

Sets the derivative order. This should either be FIRST_DERIVATIVE (1) or SECOND_DERIVATIVE (2). Setting the derivative order will re-initialize this instance.

Parameters
derivativeOrderthe derivative order you wish to set, this should either be FIRST_DERIVATIVE (1) or SECOND_DERIVATIVE (2)
Returns
returns true if the derivative order was set, false otherwise

Definition at line 296 of file Derivative.cpp.

bool Derivative::setFilterSize ( const UINT  filterSize)

Sets the size of the moving average filter used to smooth the input data (if the filterData parameter is set to true). The filterSize value must be greater than zero. Setting the filterSize will re-initialize this instance.

Parameters
filterSizethe size of the moving average filter used to smooth the input data, must be greater than zero
Returns
returns true if the filterSize was set, false otherwise

Definition at line 306 of file Derivative.cpp.


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