def reorganize_preproc_files(outdir,
sid,
proto,
image_basename,
tmp_capsul,
overwrite=False):
"""
Perform the tree reorganization
"""
#describe reorganization
processing_struct = {
"1-BET": ["{}_brain_mask.nii.gz", "{}_brain.nii.gz"],
"5-SliceTiming": ["au{}.nii", "pyscript_slicetiming.m"],
"6-Realign": [
"rp_au{}.txt", "rau{}.nii", "pyscript_realign.m", "meanau{}.nii",
"au{}.mat"
],
"8-Normalize":
["wmeanau{}.nii", "pyscript_normalize.m", "meanau{}_sn.mat"],
"9-Normalize":
["wau{}.nii", ["pyscript_normalize.m", "pyscript_apply_normalize.m"]],
"10-Smooth": ["pyscript_smooth.m", "swau{}.nii"]
}
# clean target entry
gzdestpath = os.path.join(outdir, sid, proto)
if os.path.exists(gzdestpath):
if overwrite:
shutil.rmtree(gzdestpath)
else:
raise Exception("Directory already exists: %s" % gzdestpath)
os.makedirs(gzdestpath)
# loop on items
for step_name, step_fnames in processing_struct.items():
for base in step_fnames:
if type(base) == list:
basename = base[0]
rename = base[1]
else:
basename = base
rename = base
basename = basename.format(image_basename)
rename = rename.format(image_basename)
srcpath = os.path.join(tmp_capsul, step_name, basename)
if srcpath.endswith(".nii"):
gzip_file(srcpath, prefix="", output_directory=gzdestpath)
print "****gzip ", srcpath, gzdestpath
else:
destpath = os.path.join(gzdestpath, rename)
print "****mv ", srcpath, destpath
if os.path.exists(srcpath):
shutil.move(srcpath, destpath)
print "rm ", tmp_capsul
shutil.rmtree(tmp_capsul)
def test_specific_functions(self):
""" Test functions execution follow up.
"""
# element_to_list tests
out_list = element_to_list("element_test")
self.assertIsInstance(out_list, list)
self.assertEqual(out_list, ["element_test"])
# list_to_element tests
with self.assertRaises(ValueError):
list_to_element([1, 2, 3])
with self.assertRaises(ValueError):
list_to_element("no_list")
out_element = list_to_element(["singleton_element"])
self.assertIn(out_element, ["singleton_element"])
self.assertIsInstance(out_element, str)
# ungzip_file tests
out_file = ungzip_file(os.path.join(os.path.dirname(
os.path.realpath(__file__)),
"test_file.gz"),
output_directory=self.outdir,
prefix="u")
self.assertTrue(os.path.isfile(out_file))
self.assertEqual("u", os.path.basename(out_file)[0])
with self.assertRaises(ValueError):
ungzip_file("no_file",
output_directory=self.outdir,
prefix="u")
with self.assertRaises(ValueError):
ungzip_file(os.path.join(os.path.dirname(
os.path.realpath(__file__)),
"test_file.gz"),
output_directory="non_existent",
prefix="u")
# gzip file tests
out_file = gzip_file(os.path.join(os.path.dirname(
os.path.realpath(__file__)),
"test_file.txt"),
output_directory=self.outdir,
prefix="g")
self.assertTrue(os.path.isfile(out_file))
self.assertEqual("g", os.path.basename(out_file)[0])
with self.assertRaises(ValueError):
ungzip_file("no_file",
output_directory=self.outdir,
prefix="g")
with self.assertRaises(ValueError):
ungzip_file(os.path.join(os.path.dirname(
os.path.realpath(__file__)),
"test_file.gz"),
output_directory="non_existent",
prefix="g")
def test_specific_functions(self):
""" Test functions execution follow up.
"""
# element_to_list tests
out_list = element_to_list("element_test")
self.assertIsInstance(out_list, list)
self.assertEqual(out_list, ["element_test"])
# list_to_element tests
with self.assertRaises(ValueError):
list_to_element([1, 2, 3])
with self.assertRaises(ValueError):
list_to_element("no_list")
out_element = list_to_element(["singleton_element"])
self.assertIn(out_element, ["singleton_element"])
self.assertIsInstance(out_element, str)
# ungzip_file tests
out_file = ungzip_file(os.path.join(
os.path.dirname(os.path.realpath(__file__)), "test_file.gz"),
output_directory=self.outdir,
prefix="u")
self.assertTrue(os.path.isfile(out_file))
self.assertEqual("u", os.path.basename(out_file)[0])
with self.assertRaises(ValueError):
ungzip_file("no_file", output_directory=self.outdir, prefix="u")
with self.assertRaises(ValueError):
ungzip_file(os.path.join(
os.path.dirname(os.path.realpath(__file__)), "test_file.gz"),
output_directory="non_existent",
prefix="u")
# gzip file tests
out_file = gzip_file(os.path.join(
os.path.dirname(os.path.realpath(__file__)), "test_file.txt"),
output_directory=self.outdir,
prefix="g")
self.assertTrue(os.path.isfile(out_file))
self.assertEqual("g", os.path.basename(out_file)[0])
with self.assertRaises(ValueError):
ungzip_file("no_file", output_directory=self.outdir, prefix="g")
with self.assertRaises(ValueError):
ungzip_file(os.path.join(
os.path.dirname(os.path.realpath(__file__)), "test_file.gz"),
output_directory="non_existent",
prefix="g")
# .m files
mfiles = glob.glob(os.path.join(capsulwd, "*", "pyscript*.m"))
for mfile in mfiles:
shutil.copy(mfile, soutdir)
# reg file
regfile = os.path.join(capsulwd, "9-covars", "complete_reg_file.txt")
shutil.copy(regfile, os.path.join(soutdir, "rp_nuisance_extended.txt"))
# EstimateModel niftis
estimate_model_dir = os.path.join(capsulwd, "13-EstimateModel")
images = [
os.path.join(estimate_model_dir, fname)
for fname in ("mask.nii", "RPV.nii", "ResMS.nii")
]
for image in images:
gzip_file(image,
prefix="",
output_directory=soutdir,
remove_original_file=False)
# betas
betas = glob.glob(os.path.join(estimate_model_dir, "beta*.nii"))
with tarfile.open(os.path.join(soutdir, "beta_files.tar.gz"), 'w:gz') as f:
for beta in betas:
f.add(beta, arcname=os.path.basename(beta))
# SPM.mat
spmmatfile = os.path.join(capsulwd, "14-EstimateContrast", "SPM.mat")
gzip_file(spmmatfile,
prefix="",
output_directory=soutdir,
remove_original_file=False)
# nii_spmF_images_dir niftis
nii_spmF_images_dir = os.path.join(capsulwd, "15-nii_spmF_images")
nii_spmF_images_files = []
"bet.fsl_bet": ["{}_brain_mask.nii.gz", "{}_brain.nii.gz"],
"spm_slicer": ["au{}.nii", "pyscript_slicetiming.m"],
"realign": ["rp_au{}.txt", "rau{}.nii", "pyscript_realign.m", "meanau{}.nii", "au{}.mat"],
"spm_normalize_template": ["wmeanau{}.nii", "pyscript_normalize.m", "meanau{}_sn.mat"],
"spm_funcnormalize_template": ["wau{}.nii", "pyscript_normalize.m"],
"smoothing": ["pyscript_smooth.m", "swau{}.nii"],
}
else:
raise NotImplementedError("Can't reorganize the data.")
image_basename = os.path.basename(funcfile).split(".")[0]
for step_name, step_fnames in processing_struct.items():
for basename in step_fnames:
basename = basename.format(image_basename)
srcpath = os.path.join(tmp_capsul, step_name, basename)
if srcpath.endswith(".nii"):
gzip_file(srcpath, prefix="", output_directory=outdir)
else:
if (step_name == "spm_funcnormalize_template") and (basename == "pyscript_normalize.m"):
destpath = os.path.join(outdir, "pyscript_apply_normalize.m")
elif step_name == "":
destpath = os.path.join(logdir, "{0}_{1}".format(sid, basename))
else:
destpath = os.path.join(outdir, basename)
shutil.move(srcpath, destpath)
shutil.rmtree(tmp_capsul)
"""
Create a snap to chack the registration result
"""
if args.template_mask is not None:
snap = os.path.join(outdir, image_basename + ".pdf")
use_spm=True,
spm_exec=args.spmbin,
spm_standalone=True,
use_nipype=True,
output_directory=capsulwd)
print " ... done."
# Get the pipeline
pipeline = get_process_instance("clinfmri.utils.spm_new_segment_only.xml")
# Configure the pipeline
pipeline.channel_files = [args.t1file]
#to find the template TPM.nii from the standalone distrib
pipeline.spm_dir = args.spmdir
# Execute the pipeline
study_config.run(pipeline, verbose=1)
# Keep only data of interest
batch = os.path.join(capsulwd, "3-NewSegment", "pyscript_newsegment.m")
images = glob.glob(os.path.join(capsulwd, "1-ungzipfnames", "*.nii"))
images = [item for item in images
if not os.path.basename(item).startswith(("u", "iy_"))]
mat = glob.glob(os.path.join(capsulwd, "1-ungzipfnames", "*.mat"))[0]
for path in images:
gzip_file(path, prefix="", output_directory=soutdir,
remove_original_file=False)
shutil.copy(mat, soutdir)
shutil.rmtree(capsulwd)
