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src/a/z/AZOrange-HEAD/doc/openExampleScripts/getAccParamOpt.py   AZOrange(Download)
    attrList = [attr.name for attr in trainData.domain.attributes if attr.varType == orange.Variable.String]
 
    trainData = dataUtilities.attributeDeselectionData(trainData, attrList)
 
    # Save the trainData set

src/a/z/AZOrange-HEAD/azorange/AZutilities/getUnbiasedAccuracy.py   AZOrange(Download)
                self.__log("ERROR: Attribute Filter Ctrl was selected, but attribute is not in expected format: " + str(self.testAttrFilter))
                return False
            self.data = dataUtilities.attributeDeselectionData(self.data, [self.testAttrFilter]) 
        else:
            self.usePreDefFolds = False
                       self.__log("Selected attrs: "+str([attr.name for attr in trainData.domain]))
                    else:
                       trainData = dataUtilities.attributeDeselectionData(trainData, [smilesAttr]) 
                       testData = dataUtilities.attributeDeselectionData(testData, [smilesAttr]) 
                       self.__log("Selected attrs: "+str([attr.name for attr in trainData.domain[0:3]] + ["..."] + [attr.name for attr in trainData.domain[len(trainData.domain)-3:]]))
                    if smilesAttr:
                        self.__log("Found SMILES attribute:"+smilesAttr)
                        testData = dataUtilities.attributeDeselectionData(testData, [smilesAttr])
                        self.__log("Selected attrs: "+str([attr.name for attr in trainData.domain[0:3]] + ["..."] + [attr.name for attr in trainData.domain[len(trainData.domain)-3:]]))
 

src/a/z/AZOrange-HEAD/azorange/AZutilities/competitiveWorkflow.py   AZOrange(Download)
               log(logFile,"Selected attrs: "+str([attr.name for attr in trainData.domain]))
            else:
               trainData = dataUtilities.attributeDeselectionData(trainData, [smilesAttr])
               log(logFile,"Selected attrs: "+str([attr.name for attr in trainData.domain[0:3]] + ["..."] +\
                                              [attr.name for attr in trainData.domain[len(trainData.domain)-3:]]))
        smilesAttr = dataUtilities.getSMILESAttr(trainData)
        if smilesAttr:
            trainData = dataUtilities.attributeDeselectionData(trainData, [smilesAttr])
 
        # optimize all MLMethods

src/a/z/AZOrange-HEAD/azorange/AZutilities/similarityMetrics.py   AZOrange(Download)
            print "The predictor does not have a trainDataPath specifyed. We need it for calculating Mahalanobis results!"
            return None, None
        testData = dataUtilities.attributeDeselectionData(predictor.exToPred,["SMILEStoPred"])
        if not dataTableFile:
            trainData = dataUtilities.DataTable(predictor.trainDataPath)
    # This data contains SMILES and ID, which data and ex are assumed not to. 
    attrList = ["SMILES", "ID"]
    data = dataUtilities.attributeDeselectionData(data, attrList)
    testData = dataUtilities.attributeDeselectionData(testData, attrList)
 

src/a/z/AZOrange-HEAD/azorange/AZutilities/getBBRCDesc.py   AZOrange(Download)
    print "BBRC descriptors returned: "+str(len(newAttrs)-len(desAttrs))
    if desAttrs:
        outData = dataUtilities.attributeDeselectionData(outData, desAttrs)
    unknownAttrs = [attr for attr in descList if attr not in outData.domain]
    print "Attributes not found among the structural descriptors: ",len(unknownAttrs)," (set to 0.0)"

src/a/z/AZOrange-HEAD/azorange/AZutilities/ConfPredClass.py   AZOrange(Download)
    """
    attrList = ["SMILES_1"]
    extTrain = dataUtilities.attributeDeselectionData(extTrain, attrList)
 
    # Deselect example idx in extTrain
 
    attrList = ["SMILES_1"]
    extTrain = dataUtilities.attributeDeselectionData(extTrain, attrList)
 
    distListSame = [] 
    """
    attrList = ["SMILES_1"]
    extTrain = dataUtilities.attributeDeselectionData(extTrain, attrList)
 
    distListSame = [] 
    """
    attrList = ["SMILES_1"]
    extTrain = dataUtilities.attributeDeselectionData(extTrain, attrList)
 
    distList = [] 
    """
    attrList = ["SMILES_1"]
    extTrain = dataUtilities.attributeDeselectionData(extTrain, attrList)
 
    distList = [] 

src/a/z/AZOrange-HEAD/azorange/AZutilities/evalUtilities.py   AZOrange(Download)
                print "      Examples selected for validation: "+str(len(examples))
                print "      Examples to be appended to the train set: "+str(len(self.trainBias))
                examples = dataUtilities.attributeDeselectionData(examples, [testAttrFilter])
        elif testAttrFilter is not None and testFilterVal is None and testAttrFilter in data.domain:
            #Enable pre-selected-indices
            print "      Examples selected for validation: "+str(len(examples))
            print "      Examples to be appended to the train set: "+str(len(self.trainBias))
            examples = dataUtilities.attributeDeselectionData(examples, [testAttrFilter])
 
        else:

src/a/z/AZOrange-HEAD/azorange/AZutilities/SimBoostedQSAR.py   AZOrange(Download)
        if cleanedData:      
            #Remove the fixed SMILES and revert to the Original SMILES           
            newdata = dataUtilities.attributeDeselectionData(newdata,[SMILESattr])
            newdata.domain["OrigSMI_ID"].name = SMILESattr
        return newdata