def resampleNUCtoLSQ6Space(self):
        if(not(rf.isFileHandler(self.inputs[0]))):
            print("Error: resampleNUCtoLSQ6Space can only be called on file handlers. Goodbye.\n")
            sys.exit()        

        if(self.initial_model == None and self.targetForLSQ6 == None):
            print("Error: resampleNUCtoLSQ6Space does not know what to do without an initial model and without a target file for the LSQ6 stage. Sorry. Goodbye.\n")
            sys.exit()
            
        # create a new group for these files
        self.addLSQ6NUCGroupToInputs()
            
        nuCorrectedLSQ6 = []
        nuCorrectedLSQ6Masks = []
        lsq6SpaceTarget = None
        if self.initial_model:
            lsq6SpaceTarget = self.initial_model[0]
        else:
            lsq6SpaceTarget = self.targetForLSQ6
        for inputFH in self.inputs:
                # find the lsq6 group again
                indexLsq6 = None 
                for index, value in inputFH.groupNames.iteritems():
                    if(value == "lsq6"):
                        indexLsq6 = index
                if(indexLsq6 != None):
                    # find the last transform that is associated with the standard space model
                    if(inputFH.groupedFiles[indexLsq6].transforms.has_key(lsq6SpaceTarget)):
                        transformToLSQ6 = inputFH.getLastXfm(lsq6SpaceTarget, groupIndex=indexLsq6)
                        outFileBase = fh.removeBaseAndExtension(inputFH.getLastBasevol()) + "_lsq6.mnc"
                        outFileDir  = inputFH.resampledDir
                        outFile     = fh.createBaseName(outFileDir, outFileBase)
                        nuCorrectedLSQ6.append(outFile)
                        resamplings = ma.mincresampleFileAndMask(inputFH,
                                                                 lsq6SpaceTarget,
                                                                 nameForStage="mincresample NUC to LSQ6",
                                                                 likeFile=lsq6SpaceTarget,  
                                                                 transform=transformToLSQ6,
                                                                 output=outFile,
                                                                 argArray=["-sinc"])
                        nuCorrectedLSQ6Masks.append(resamplings.outputFilesMask[0])
                        self.p.addPipeline(resamplings.p)
                    else:
                        # not good either...
                        print("\nError: can not find the 6 parameter transformation between: %s and %s (in the function: resampleNUCtoLSQ6Space). Exiting now...\n" % (inputFH.inputFileName, lsq6SpaceTarget.inputFileName))
                        sys.exit()
                else:
                    #oops...
                    print("\nError: we were not able to find the \"lsq6\" class of files during the non uniformity correction stage. Were trying to determine the transformation that resamples the non uniformity corrected file in native space to LSQ6 space. Exiting now...\n\n")
                    sys.exit()
        self.NUCorrectedLSQ6 = nuCorrectedLSQ6
        self.NUCorrectedLSQ6Masks = nuCorrectedLSQ6Masks
This function is called when useOriginalInput is True.  That means that the 
dataset/ETHPy150Open Mouse-Imaging-Centre/pydpiper/atoms_and_modules/LSQ6.py/NonUniformityCorrection.resampleNUCtoLSQ6Space