Orange.widgets.widget.OWWidget.openContext

All Samples(6) | Call(6) | Derive(0) | Import(0)

src/o/r/orange3-HEAD/Orange/widgets/visualize/owmosaic.py orange3(Download)

 
        self.initCombos(self.data)
        self.openContext(self.data)
 
        if data and self.unprocessedSubsetData:  # if we first received subset data we now have to call setSubsetData to process it

src/o/r/orange3-HEAD/Orange/widgets/data/owselectattributes.py orange3(Download)

        self.data = data
        if data is not None:
            self.openContext(data)
            all_vars = data.domain.variables + data.domain.metas

src/o/r/orange3-HEAD/Orange/widgets/data/owselectdata.py orange3(Download)

        if not data:
            return
        self.openContext(data)
        if not self.conditions and len(domain.variables):
            self.add_row()

src/o/r/orange3-HEAD/Orange/widgets/visualize/owboxplot.py orange3(Download)

        self.attrCombo.clear()
        if dataset:
            self.openContext(self.ddataset)
            self.attributes = [(a.name, a.var_type) for a in dataset.domain]
            self.grouping = ["None"] + [(a.name, a.var_type)

src/o/r/orange3-HEAD/Orange/widgets/visualize/owscatterplot.py orange3(Download)

        self.classificationResults = None
        self.outlierValues = None
        self.openContext(self.data)
 
    # set an example table with a data subset subset of the data. if called by a visual classifier, the update parameter will be 0

src/o/r/orange3-HEAD/Orange/widgets/data/owfeatureconstructor.py orange3(Download)

 
        if self.data is not None:
            self.openContext(data)
            self.featuremodel.wrap(self.descriptors)
            self.setCurrentIndex(self.currentIndex)