logging.info("realigned %s" % subid)

        # make final mean image
        meanimg = pp.make_summed_image(tmprealigned)

        # move data back to main directory
        nifti_dir, _ = os.path.split(nifti[0])
        movedmean = bg.copy_file(meanimg, nifti_dir)

        # QA
        if not hasqa:
            logging.info("qa %s" % subid)
            qa.plot_movement(tmpparameterfile, subid)
            # get rid of NAN in files
            no_nanfiles = pp.clean_nan(tmprealigned)
            # make 4d volume to visualize movement
            img4d = qa.make_4d_nibabel(no_nanfiles)
            bg.zip_files(tmprealigned)
            # save qa image
            # qa.save_qa_img(img4d)
            qa.plot_movement(tmpparameterfile, subid)
            qa.calc_robust_median_diff(img4d)
            qa.screen_pet(img4d)
            # remove tmpfiles

            bg.remove_files(no_nanfiles)
            bg.remove_files(newnifti)

        # coreg pons to pet
        # find PONS
                           indir='%s/'%root)

    subs.sort()
    for sub in subs:
        _, subid = os.path.split(sub)
        logging.info('%s'%subid)
        # check is ponsnormed exists
        searchstring = '%s/fdg/nonan-ponsnormed_*.nii*'%sub
        pn = pp.find_single_file(searchstring)
        if pn is not None:
            logging.info('%s exists, skipping'%(pn))
            continue
        # find sum
        searchstring = '%s/fdg/sum_rB*.nii*' % sub
        sum = pp.find_single_file(searchstring)
        if sum is None:
            logging.error('%s not found'%(searchstring))
            continue
        searchstr = '%s/fdg/ref_region/rpons_tu.nii*' % sub
        pons = pp.find_single_file(searchstr)
        if pons is None:
            logging.error('%s not found'%(searchstring))
            continue
        outfname = os.path.join(sub, 'fdg', 
                                'ponsnormed_%s_%s.nii'%(subid,
                                                        tracer.lower()))
        pp.make_pons_normed(pet, newpons, outfname)
        no_nanfiles = pp.clean_nan([outfname])
        logging.info('saved %s'%(outfname))

            logging.info('realigned %s' % subid)

        # make final mean image
        meanimg = pp.make_summed_image(tmprealigned)

        # move data back to main directory
        nifti_dir, _ = os.path.split(nifti[0])
        movedmean = bg.copy_file(meanimg, nifti_dir)

        #QA
        if not hasqa:
            logging.info('qa %s' % subid)
            qa.plot_movement(tmpparameterfile, subid)
            # get rid of NAN in files
            no_nanfiles = pp.clean_nan(tmprealigned)
            #make 4d volume to visualize movement
            img4d = qa.make_4d_nibabel(no_nanfiles)
            bg.zip_files(tmprealigned)
            #save qa image
            #qa.save_qa_img(img4d)
            qa.plot_movement(tmpparameterfile, subid)
            qa.calc_robust_median_diff(img4d)
            qa.screen_pet(img4d)
            #remove tmpfiles

            bg.remove_files(no_nanfiles)
            bg.remove_files(newnifti)

        # coreg pons to pet
        # find PONS