def test_dcm2bids():
tmpBase = os.path.join(TEST_DATA_DIR, "tmp")
#bidsDir = TemporaryDirectory(dir=tmpBase)
bidsDir = TemporaryDirectory()
tmpSubDir = os.path.join(bidsDir.name, DEFAULT.tmpDirName, "sub-01")
shutil.copytree(
os.path.join(TEST_DATA_DIR, "sidecars"),
tmpSubDir)
app = Dcm2bids(
[TEST_DATA_DIR], "01",
os.path.join(TEST_DATA_DIR, "config_test.json"),
bidsDir.name
)
app.run()
layout = BIDSLayout(bidsDir.name, validate=False)
assert layout.get_subjects() == ["01"]
assert layout.get_sessions() == []
assert layout.get_tasks() == ["rest"]
assert layout.get_runs() == [1,2,3]
app = Dcm2bids(
[TEST_DATA_DIR], "01",
os.path.join(TEST_DATA_DIR, "config_test.json"),
bidsDir.name
)
app.run()
fmapFile = os.path.join(
bidsDir.name, "sub-01", "fmap", "sub-01_echo-492_fmap.json")
data = load_json(fmapFile)
fmapMtime = os.stat(fmapFile).st_mtime
assert data["IntendedFor"] == "dwi/sub-01_dwi.nii.gz"
data = load_json(os.path.join(
bidsDir.name, "sub-01", "localizer", "sub-01_run-01_localizer.json"))
assert data["ProcedureStepDescription"] == "Modify by dcm2bids"
#rerun
shutil.rmtree(tmpSubDir)
shutil.copytree(
os.path.join(TEST_DATA_DIR, "sidecars"),
tmpSubDir)
app = Dcm2bids(
[TEST_DATA_DIR], "01",
os.path.join(TEST_DATA_DIR, "config_test.json"),
bidsDir.name
)
app.run()
fmapMtimeRerun = os.stat(fmapFile).st_mtime
assert fmapMtime == fmapMtimeRerun
bidsDir.cleanup()
def test_dcm2bids():
# tmpBase = os.path.join(TEST_DATA_DIR, "tmp")
# bidsDir = TemporaryDirectory(dir=tmpBase)
bidsDir = TemporaryDirectory()
tmpSubDir = os.path.join(bidsDir.name, DEFAULT.tmpDirName, "sub-01")
shutil.copytree(os.path.join(TEST_DATA_DIR, "sidecars"), tmpSubDir)
app = Dcm2bids(
[TEST_DATA_DIR],
"01",
os.path.join(TEST_DATA_DIR, "config_test.json"),
bidsDir.name,
)
app.run()
layout = BIDSLayout(bidsDir.name, validate=False)
assert layout.get_subjects() == ["01"]
assert layout.get_sessions() == []
assert layout.get_tasks() == ["rest"]
assert layout.get_runs() == [1, 2, 3]
app = Dcm2bids(
[TEST_DATA_DIR],
"01",
os.path.join(TEST_DATA_DIR, "config_test.json"),
bidsDir.name,
)
app.run()
fmapFile = os.path.join(bidsDir.name, "sub-01", "fmap",
"sub-01_echo-492_fmap.json")
data = load_json(fmapFile)
fmapMtime = os.stat(fmapFile).st_mtime
assert data["IntendedFor"] == "dwi/sub-01_dwi.nii.gz"
data = load_json(
os.path.join(bidsDir.name, "sub-01", "localizer",
"sub-01_run-01_localizer.json"))
assert data["ProcedureStepDescription"] == "Modify by dcm2bids"
# rerun
shutil.rmtree(tmpSubDir)
shutil.copytree(os.path.join(TEST_DATA_DIR, "sidecars"), tmpSubDir)
app = Dcm2bids(
[TEST_DATA_DIR],
"01",
os.path.join(TEST_DATA_DIR, "config_test.json"),
bidsDir.name,
)
app.run()
fmapMtimeRerun = os.stat(fmapFile).st_mtime
assert fmapMtime == fmapMtimeRerun
if os.name != 'nt':
bidsDir.cleanup()
def _fill_empty_lists(layout: BIDSLayout, subjects: list, tasks: list, sessions: list, runs: t.List[str]):
"""
If filters are not provided by the user, load them from layout.
"""
subjects = subjects if subjects else layout.get_subjects()
tasks = tasks if tasks else layout.get_tasks()
sessions = sessions if sessions else layout.get_sessions()
runs = runs if runs else layout.get_runs()
return subjects, tasks, sessions, runs
def main(**args):
path = "/mnt/DATA_4Tera/Dati_Sherlock/bids/"
derivatives = os.path.join(path, "derivatives", "afniproc")
print("mkdir -p {}".format(derivatives))
os.system("mkdir -p {}".format(derivatives))
subj_deriv = os.path.join(derivatives, 'sub-{subject}', "ses-{session}")
layout = BIDSLayout(path)
subjects = layout.get_subjects()
sessions = layout.get_sessions()
for session in sessions:
for subj in subjects:
deriv_dir = subj_deriv.format(session=session, subject=subj)
print("mkdir -p {}".format(deriv_dir))
os.system("mkdir -p {}".format(deriv_dir))
# Create anat and func
anat_dir = os.path.join(subj_deriv,
"{datatype}").format(session=session,
subject=subj,
datatype='anat')
func_dir = os.path.join(subj_deriv,
"{datatype}").format(session=session,
subject=subj,
datatype='func')
print("mkdir -p {}".format(anat_dir))
os.system("mkdir -p {}".format(anat_dir))
print("mkdir -p {}".format(func_dir))
os.system("mkdir -p {}".format(func_dir))
# Check and convert T1 to send Freesurfer segmentation
t1 = layout.get(subject=subj, session=session, suffix='T1w')[0]
entities = t1.get_entities()
pattern = os.path.join(
subj_deriv, "{datatype}",
"sub-{subject}[_ses-{session}][_desc-{desc}]_{suffix}.{extension}"
)
entities['desc'] = 'fsprep'
t1_fs = layout.build_path(entities, pattern, validate=False)
entities['extension'] = 'txt'
t1_log = layout.build_path(entities, pattern, validate=False)
command = "check_dset_for_fs.py -input %s -fix_all -fix_out_prefix %s -fix_out_vox_dim 1 -verb > %s"
command = command % (t1.path, t1_fs, t1_log)
print(command)
os.system(command)
check_fs(layout, subj, session, subj_deriv)
### T1 to MNI space coreg
entities = t1.get_entities()
entities['desc'] = 'fsprep'
entities['space'] = 'MNI152'
pattern = os.path.join(
subj_deriv, "{datatype}",
"sub-{subject}[_ses-{session}][_space-{space}][_desc-{desc}]_{suffix}.{extension}"
)
t1_mni = layout.build_path(entities, pattern, validate=False)
command = "@auto_tlrc -base MNI152_2009_template.nii.gz -pad_base 35 -prefix {prefix} -input {input}"
command = command.format(prefix=t1_mni, input=t1_fs)
print(command)
os.system(command)
runs = layout.get_runs()
ordered_bold = []
for run in runs:
fname = layout.get(session=session,
subject=subj,
run=run,
suffix='bold')
if len(fname) != 0:
ordered_bold.append(fname[0])
# Slice time correction - motion correction - align EPI to Anat to MNI
bold = layout.get(subject=subj,
session=session,
suffix='bold',
extension='nii.gz')
# 1D File
slice_timing = np.array(bold[0].get_metadata()['SliceTiming'])
slice_fname = os.path.join(path, "slice_timing.txt")
np.savetxt(slice_fname,
slice_timing,
delimiter=' ',
newline=' ',
fmt='%.5f')
epi = layout.get(subject=subj,
session=session,
suffix='bold',
extension='nii.gz',
run=1)[0].path
child_epi = " ".join([b.path for b in ordered_bold])
command = "align_epi_anat.py -anat {anat} -epi {epi} -child_epi {child_epi}"+\
" -epi_base 0 -tshift_opts -tpattern {tpattern} -epi2anat -giant_move"+\
" -tlrc_apar {tlrc_apar}"
command = command.format(anat=t1_fs,
epi=epi,
child_epi=child_epi,
tpattern=slice_fname,
tlrc_apar=t1_mni)
print(command)
os.system(command)
# Create mask
automask = " ".join(
[b.filename[:-7] + '_tlrc_al+tlrc.HEAD' for b in bold])
mean_mask_prefix = 'mean_mni.nii.gz'
command = '3dTstat -prefix {prefix} {input}'.format(
prefix=mean_mask_prefix, input=automask)
print(command)
os.system(command)
entities = bold[0].get_entities()
entities['suffix'] = 'mask'
entities['space'] = 'MNI152'
pattern = os.path.join(
subj_deriv, "{datatype}",
"sub-{subject}[_ses-{session}][_space-{space}][_desc-{desc}]_{suffix}.{extension}"
)
mask_prefix = layout.build_path(entities, pattern, validate=False)
command = '3dAutomask -prefix {prefix} {input}'.format(
input=mean_mask_prefix, prefix=mask_prefix)
print(command)
os.system(command)
# Clean files
removed = " ".join([b.filename[:-7] + '_al+orig.*' for b in bold])
command = "rm " + removed
print(command)
os.system(command)
command = "rm __tt_*.*"
print(command)
os.system(command)
command = "rm malldump.*"
print(command)
os.system(command)
# Put files in BIDS
header = [
'trans_x', 'trans_y', 'trans_z', 'rot_x', 'rot_y', 'rot_z'
]
motion_ordered = list()
for bold in ordered_bold:
motion_fname = bold.filename[:-7] + "_vr_motion.1D"
motion = np.genfromtxt(motion_fname)
motion_ordered.append(motion_fname)
entities = bold.get_entities()
entities['suffix'] = 'motion'
entities['desc'] = 'volreg'
entities['extension'] = 'tsv'
pattern = os.path.join(
subj_deriv, "{datatype}",
"sub-{subject}_ses-{session}_task-{task}_run-{run:02d}_desc-{desc}_{suffix}.{extension}"
)
motion_bids = pattern.format(**entities)
motion = motion[:, [3, 4, 5, 0, 1, 2]]
np.savetxt(motion_bids,
motion,
fmt="%f",
delimiter="\t",
header="\t".join(header))
print("rm " + motion_fname)
os.system("rm " + motion_fname)
for desc in ['mat', "reg_mat", "tlrc_mat"]:
affine_fname = bold.filename[:-7] + "_al_" + desc + ".aff12.1D"
entities = bold.get_entities()
entities['suffix'] = 'affine'
entities['desc'] = desc.replace("_", "")
entities['extension'] = 'tsv'
pattern = os.path.join(
subj_deriv, "{datatype}",
"sub-{subject}_ses-{session}_task-{task}_run-{run:02d}_desc-{desc}_{suffix}.{extension}"
)
affine_bids = pattern.format(**entities)
command = "mv {0} {1}".format(affine_fname, affine_bids)
print(command)
os.system(command)
afni_bold = bold.filename[:-7] + "_tlrc_al+tlrc"
entities = bold.get_entities()
entities['desc'] = "afniproc"
entities['extension'] = 'nii.gz'
entities['space'] = 'MNI152'
pattern = os.path.join(
subj_deriv, "{datatype}",
"sub-{subject}_ses-{session}_task-{task}_run-{run:02d}_space-{space}_desc-{desc}_{suffix}.{extension}"
)
afni_bids = pattern.format(**entities)
command = "3dcopy {0} {1}".format(afni_bold, afni_bids)
print(command)
os.system(command)
print("rm {}*".format(afni_bold))
os.system("rm {}*".format(afni_bold))
# Create confound regressors
# Motion
motion_files = list()
for run in runs:
f = layout.get(subject=subj,
session=session,
task=session,
run=run,
suffix='motion')
if len(f) != 0:
motion_files.append(f[0])
motion_df = [
pd.read_csv(m.path, delimiter="\t") for m in motion_files
]
motion_demean = [m - m.mean(0) for m in motion_df]
motion_demean = pd.concat(motion_demean)
entities = motion_files[0].get_entities()
entities['desc'] = 'demean'
pattern = os.path.join(
subj_deriv, "{datatype}",
"sub-{subject}_ses-{session}_desc-{desc}_{suffix}.{extension}")
demean_fname = pattern.format(**entities)
motion_demean.to_csv(demean_fname,
header=False,
index=False,
sep="\t")
motion_deriv = [m.diff() for m in motion_df]
motion_deriv = [m.fillna(0) for m in motion_deriv]
motion_deriv = [m - m.mean(0) for m in motion_deriv]
motion_deriv = pd.concat(motion_deriv)
entities['desc'] = 'deriv'
deriv_fname = pattern.format(**entities)
motion_deriv.to_csv(deriv_fname,
header=False,
index=False,
sep="\t")
tr_counts = [m.shape[0] for m in motion_df]
for j, t in enumerate(tr_counts):
command = "1dBport -nodata {ntr} 1 -band 0.01 999 -invert -nozero > bpass.1D".format(
ntr=t)
print(command)
os.system(command)
command = "1d_tool.py -infile bpass.1D -pad_into_many_runs {run:1d} {n_runs}"+\
" -set_run_lengths {tr_counts} -write bpass.{run:02d}.1D"
command = command.format(run=j + 1,
n_runs=str(len(tr_counts)),
tr_counts=" ".join(
[str(t) for t in tr_counts]))
print(command)
os.system(command)
entities['desc'] = 'bpass'
entities['suffix'] = 'timeseries'
entities['extension'] = '1D'
bpass_fname = pattern.format(**entities)
command = "1dcat bpass.*.1D > {}".format(bpass_fname)
print(command)
os.system(command)
command = "rm bpass*"
print(command)
os.system(command)
