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src/a/z/AZOrange-HEAD/orange/OrangeWidgets/Data/OWDataDomain.py   AZOrange(Download)
            newdata = dataUtilities.DataTable(domain, self.data)
            newdata.name = self.data.name
            if not self.userWarned and len(newdata.domain.getmetas()) != 0:            
                QMessageBox.warning( None, "Select - Meta Attributes", "There are meta-attributes present in the dataset.\nThe presence of meta-Attributes in datasets used with Learners/Classifiers\nrequires the use of considerably more ram memory!" , QMessageBox.Ok) 
                self.userWarned = True

src/a/z/AZOrange-HEAD/tests/source/data/createTestDataSets.py   AZOrange(Download)
varsS = ["Measure","[Br]([C])","[N]([N])","[O]([C])","[C]([C][F])","Level","DiscAttr1","DiscAttr2","Attr3","YetOther","Activity"]
domain = orange.Domain([data.domain[attr] for attr in varsS])
domain.addmetas(data.domain.getmetas())
data = dataUtilities.DataTable(domain,data)
#LargeDataset
#============ Regression ====================
domainR = orange.Domain([attr for attr in data.domain if attr.name != "Measure" and attr.name != "Activity"],data.domain["Measure"])
domainR.addmetas(data.domain.getmetas())
dataR = dataUtilities.DataTable(domainR,data)
random.seed(1)