algo/IBDT.py
def runJob(self, data:DataFrame,  maxSaccadeDurationMs:float, minSampleConfidence:float, classification:int) -> list:
        """Sets classifier parameters, runs classification and returns list of specified event type.

        :param data: pandas dataframe with 4 columns - time(ms), validity(higher is more valid), x(px or mm), y(px or mm).
        :param maxSaccadeDurationMs: saccades longer than this will not be classified as saccades.
        :param minSampleConfidence: validity lower than this will be considered undefined sample.
        :param classification: int code whether to classify pursuits or fixations and saccades only.
        :return: list of IBDT_Data with events classified.
        """
        self.maxSaccadeDurationMs = maxSaccadeDurationMs
        self.minSampleConfidence = minSampleConfidence
        self.classification = classification


        #----
        ibdtData = []
        for index, row in data.iterrows():
            ibdtData.append(IBDT_Data( base=GazeDataEntry(ts=row[0], confidence=row[1], x=row[2], y=row[3]) ))

        #----
        self.train(ibdtData)
        for pt in ibdtData:
            self.addPoint(pt)
        self.result = ibdtData


        return self.result
Sets classifier parameters, runs classification and returns list of specified event type.

        :param data: pandas dataframe with 4 columns - time(ms), validity(higher is more valid), x(px or mm), y(px or mm).
        :param maxSaccadeDurationMs: saccades longer than this will not be classified as saccades.
        :param minSampleConfidence: validity lower than this will be considered undefined sample.
        :param classification: int code whether to classify pursuits or fixations and saccades only.
        :return: list of IBDT_Data with events classified.
        
Sets classifier parameters, runs classification and returns list of specified event type.
Sets classifier parameters runs classification and returns list of specified event type .
def runJob(self, data:DataFrame,  maxSaccadeDurationMs:float, minSampleConfidence:float, classification:int) -> list:
        self.maxSaccadeDurationMs = maxSaccadeDurationMs
        self.minSampleConfidence = minSampleConfidence
        self.classification = classification
        ibdtData = []
        for index, row in data.iterrows():
            ibdtData.append(IBDT_Data( base=GazeDataEntry(ts=row[0], confidence=row[1], x=row[2], y=row[3]) ))
        self.train(ibdtData)
        for pt in ibdtData:
            self.addPoint(pt)
        self.result = ibdtData
        return self.result
def runJob ( self , data : DataFrame , maxSaccadeDurationMs : float , minSampleConfidence : float , classification : int ) -> list : self . maxSaccadeDurationMs = maxSaccadeDurationMs self . minSampleConfidence = minSampleConfidence self . classification = classification ibdtData = [ ] for index , row in data . iterrows ( ) : ibdtData . append ( IBDT_Data ( base = GazeDataEntry ( ts = row [ 0 ] , confidence = row [ 1 ] , x = row [ 2 ] , y = row [ 3 ] ) ) ) self . train ( ibdtData ) for pt in ibdtData : self . addPoint ( pt ) self . result = ibdtData return self . result
Sets classifier parameters, runs classification and returns list of specified event type.
Sets classifier parameters runs classification and returns list of specified event type .
"""Sets classifier parameters, runs classification and returns list of specified event type.

        :param data: pandas dataframe with 4 columns - time(ms), validity(higher is more valid), x(px or mm), y(px or mm).
        :param maxSaccadeDurationMs: saccades longer than this will not be classified as saccades.
        :param minSampleConfidence: validity lower than this will be considered undefined sample.
        :param classification: int code whether to classify pursuits or fixations and saccades only.
        :return: list of IBDT_Data with events classified.
        """ #---- #----
list of IBDT_Data with events classified.
list of IBDT_Data with events classified .
self
data
DataFrame
pandas dataframe with 4 columns - time(ms), validity(higher is more valid), x(px or mm), y(px or mm).
pandas dataframe with 4 columns - time ( ms ) validity ( higher is more valid ) x ( px or mm ) y ( px or mm ) .
maxSaccadeDurationMs
float
saccades longer than this will not be classified as saccades.
saccades longer than this will not be classified as saccades .
minSampleConfidence
float
validity lower than this will be considered undefined sample.
validity lower than this will be considered undefined sample .
classification
int
int code whether to classify pursuits or fixations and saccades only.
int code whether to classify pursuits or fixations and saccades only .