def transform_vol(invol, xfm, space_defining):
invol = bg.unzip_file(invol) # in case zipped
xfm = bg.unzip_file(xfm) # in case zipped
space_defining = bg.unzip_file(space_defining) # in case zipped
pp.apply_transform_onefile(xfm, invol)
pp.reslice(space_defining, invol)
rinvol = pp.prefix_filename(invol, prefix='r')
bg.remove_files([invol])
bg.zip_files([space_defining])
return rinvol
def transform_vol(invol, xfm, space_defining):
invol = bg.unzip_file(invol)# in case zipped
xfm = bg.unzip_file(xfm)# in case zipped
space_defining = bg.unzip_file(space_defining)# in case zipped
pp.apply_transform_onefile(xfm, invol)
pp.reslice(space_defining, invol)
rinvol = pp.prefix_filename(invol, prefix='r')
bg.remove_files([invol])
bg.zip_files([space_defining])
return rinvol
# 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
pons_searchstr = "%s/ref_region/pons_tu.nii*" % tracerdir
pons = pp.find_single_file(pons_searchstr)
if "gz" in pons:
## find sum
globstr = os.path.join(s, "pib", "realign_QA", "mean20min*.nii")
sum = pp.find_single_file(globstr)
if brainmask is None or sum is None:
logging.error("pet2mri sum: %s brainmask: %s" % (sum, brainmask))
continue
# move dvr and sum to coregdir, unzip if necessary
cdvr = bg.copy_file(dvr, coregdir)
csum = bg.copy_file(sum, coregdir)
cdvr = bg.unzip_file(cdvr)
csum = bg.unzip_file(csum)
## coreg pet 2 brainmask
corg_out = pp.simple_coregister(str(brainmask), str(csum), other=str(cdvr))
if not corg_out.runtime.returncode == 0:
logging.error(corg_out.runtime.traceback)
continue
rdvr = corg_out.outputs.coregistered_files
# copy dvr to freesurfer subjects petdir
cdvr = bg.copy_file(rdvr, petdir)
globstr = os.path.join(fsdir, "mri", "T1.mgz")
t1 = pp.find_single_file(globstr)
if t1 is None:
logging.error("%s not found" % globstr)
continue
xfm = fst.fs_generate_dat(cdvr, t1, subid)
outfiles = fst.pet_2_surf(cdvr, xfm, mridir)
# zip files in coregdir
allf = glob("%s/*" % coregdir)
bg.zip_files(allf)
# 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
pons_searchstr = '%s/ref_region/pons_tu.nii*' % tracerdir
pons = pp.find_single_file(pons_searchstr)
if 'gz' in pons:
sum = pp.find_single_file(globstr)
if brainmask is None or sum is None:
logging.error('pet2mri sum: %s brainmask: %s' % (sum, brainmask))
continue
# move dvr and sum to coregdir, unzip if necessary
cdvr = bg.copy_file(dvr, coregdir)
csum = bg.copy_file(sum, coregdir)
cdvr = bg.unzip_file(cdvr)
csum = bg.unzip_file(csum)
## coreg pet 2 brainmask
corg_out = pp.simple_coregister(str(brainmask),
str(csum),
other=str(cdvr))
if not corg_out.runtime.returncode == 0:
logging.error(corg_out.runtime.traceback)
continue
rdvr = corg_out.outputs.coregistered_files
# copy dvr to freesurfer subjects petdir
cdvr = bg.copy_file(rdvr, petdir)
globstr = os.path.join(fsdir, 'mri', 'T1.mgz')
t1 = pp.find_single_file(globstr)
if t1 is None:
logging.error('%s not found' % globstr)
continue
xfm = fst.fs_generate_dat(cdvr, t1, subid)
outfiles = fst.pet_2_surf(cdvr, xfm, mridir)
# zip files in coregdir
allf = glob('%s/*' % coregdir)
bg.zip_files(allf)
