def main():
parser = argparse.ArgumentParser(
'Gets the task list BEFORE the events files are copied into the dataset'
)
parser.add_argument("--bidsdir",
help="Path to a curated BIDS directory",
required=True)
args = parser.parse_args()
bidsdir = args.bidsdir
layout = BIDSLayout(bidsdir)
task_list = layout.get_tasks()
# move scenemem to end of list
if 'scenemem' in task_list:
task_list.append(task_list.pop(task_list.index('scenemem')))
# remove unhandled tasks
if 'rest' in task_list:
task_list.remove('rest')
if 'binder' in task_list:
task_list.remove('binder')
if 'verbgen' in task_list:
task_list.remove('verbgen')
sys.stdout.write(' '.join(task_list))
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 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 _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 _run_interface(self, runtime):
import json
from bids import BIDSLayout
def validate_derivatives(bids_dir, derivatives):
""" Validate derivatives argument provided by the user.
Args:
bids_dir: list
Path to bids root directory.
derivatives: str or list(str)
Derivatives to use for denoising.
Returns:
derivatives_: list
Validated derivatives list.
scope: list
Right scope keyword used in pybids query.
"""
if isinstance(derivatives, str):
derivatives_ = [derivatives]
else:
derivatives_ = derivatives
# Create full paths to derivatives folders
derivatives_ = [
os.path.join(bids_dir, 'derivatives', d) for d in derivatives_
]
# Establish right scope keyword for arbitrary packages
scope = []
for derivative_path in derivatives_:
dataset_desc_path = os.path.join(derivative_path,
'dataset_description.json')
try:
with open(dataset_desc_path, 'r') as f:
dataset_desc = json.load(f)
scope.append(dataset_desc['PipelineDescription']['Name'])
except FileNotFoundError as e:
raise Exception(f"{derivative_path} should contain" +
" dataset_description.json file") from e
except KeyError as e:
raise Exception(
f"Key 'PipelineDescription.Name' is " +
"required in {dataset_desc_path} file") from e
return derivatives_, scope
def validate_option(layout, option, kind='task'):
""" Validate BIDS query filters provided by the user.
Args:
layout: bids.layout.layout.BIDSLayout
Lightweight class representing BIDS project file tree.
option: list
Filter arguments provided by the user.
kind: string
Type of query. Available options are 'task', 'session' and
'subject'.
Returns:
option_: list
Validated filter values.
"""
# Grab all possible filter values
if kind == 'task':
option_all = layout.get_tasks()
elif kind == 'session':
option_all = layout.get_sessions()
elif kind == 'subject':
option_all = layout.get_subjects()
option_ = option
for option_item in option_:
if option_item not in option_all:
raise ValueError(f'{kind} {option_item} is not found')
return option_
# Validate derivatives argument
derivatives, scope = validate_derivatives(
bids_dir=self.inputs.bids_dir, derivatives=self.inputs.derivatives)
layout = BIDSLayout(root=self.inputs.bids_dir,
validate=True,
derivatives=derivatives)
# Validate optional arguments
filter_base = {}
if isdefined(self.inputs.task):
task = validate_option(layout, self.inputs.task, kind='task')
filter_base['task'] = task
else:
task = layout.get_tasks()
if isdefined(self.inputs.session):
session = validate_option(layout,
self.inputs.session,
kind='session')
filter_base['session'] = session
if isdefined(self.inputs.subject):
subject = validate_option(layout,
self.inputs.subject,
kind='subject')
filter_base['subject'] = subject
# Define query filters
keys_entities = ['task', 'session', 'subject', 'datatype']
filter_fmri = {
'extension': ['nii', 'nii.gz'],
'suffix': 'bold',
'desc': 'preproc'
}
filter_fmri_aroma = {
'extension': ['nii', 'nii.gz'],
'suffix': 'bold',
'desc': 'smoothAROMAnonaggr',
}
filter_conf = {
'extension': 'tsv',
'suffix': 'regressors',
'desc': 'confounds',
} # for later
filter_conf_json = {
'extension': 'json',
'suffix': 'regressors',
'desc': 'confounds',
}
filter_fmri.update(filter_base)
########################################################################
### SOLUTION FOR LATER #################################################
########################################################################
# filter_fmri_aroma.update(filter_base)
# filter_conf.update(filter_base)
# filter_conf_json.update(filter_base)
# # Grab all requested files
# fmri_prep = layout.get(scope=scope, **filter_fmri)
# if self.inputs.ica_aroma:
# fmri_prep_aroma = layout.get(scope=scope, **filter_fmri_aroma)
# conf_raw = layout.get(scope=scope, **filter_conf)
# conf_json = layout.get(scope=scope, **filter_conf_json)
########################################################################
########################################################################
########################################################################
fmri_prep, fmri_prep_aroma, conf_raw, conf_json, entities = (
[] for _ in range(5))
for fmri_file in layout.get(scope=scope, **filter_fmri):
entity_bold = fmri_file.get_entities()
# Look for corresponding confounds file
filter_entities = {
key: value
for key, value in entity_bold.items() if key in keys_entities
}
# Constraining search
filter_conf.update(filter_entities)
filter_conf_json.update(filter_entities)
conf_file = layout.get(scope=scope, **filter_conf)
conf_json_file = layout.get(scope=scope, **filter_conf_json)
if not conf_file:
raise FileNotFoundError(
f"Regressor file not found for file {fmri_file.path}")
else:
# Add entity only if both files are available
if len(conf_file) > 1:
print(
f"Warning: Multiple regressors found for file {fmri_file.path}.\n"
f"Selecting {conf_file[0].path}"
) # TODO: find proper warning (logging?)
conf_file = conf_file[0]
if not conf_json_file:
raise FileNotFoundError(
f"Regressor file not found for file {fmri_file.path}")
else:
# Add entity only if both files are available
if len(conf_json_file) > 1:
print(
f"Warning: Multiple .json regressors found for file {fmri_file.path}.\n"
f"Selecting {conf_json_file[0].path}")
conf_json_file = conf_json_file[0]
if self.inputs.ica_aroma:
filter_fmri_aroma.update(
filter_entities) # Add specific fields to constrain search
fmri_aroma_file = layout.get(scope=scope, **filter_fmri_aroma)
if not fmri_aroma_file:
raise FileNotFoundError(
f"ICA-Aroma file not found for file {fmri_file.path}")
else:
# Add entity only if both files are available
if len(fmri_aroma_file) > 1:
print(
f"Warning: Multiple ICA-Aroma files found for file {fmri_file.path}.\n"
f"Selecting {fmri_aroma_file[0].path}")
# TODO: find proper warning (logging?)
fmri_aroma_file = fmri_aroma_file[0]
fmri_prep_aroma.append(fmri_aroma_file.path)
fmri_prep.append(fmri_file.path)
conf_raw.append(conf_file.path)
conf_json.append(conf_json_file.path)
entities.append(filter_entities)
# Extract TRs
tr_dict = {}
for t in task:
filter_fmri_tr = filter_fmri.copy()
filter_fmri_tr['task'] = t
example_file = layout.get(**filter_fmri_tr)[0]
tr = layout.get_metadata(example_file.path)['RepetitionTime']
tr_dict[t] = tr
self._results['fmri_prep'] = fmri_prep
self._results['fmri_prep_aroma'] = fmri_prep_aroma
self._results['conf_raw'] = conf_raw
self._results['conf_json'] = conf_json
self._results['entities'] = entities
self._results['tr_dict'] = tr_dict
return runtime
from bids import BIDSLayout bids_dataset = '/home/emdupre/Desktop/ds000007' # Change to your dataset location ! # first, we want to make sure we have a valid BIDS dataset ! # let's navigate to : # https://bids-standard.github.io/bids-validator/ layout = BIDSLayout(bids_dataset) # Let's learn a little about the data we have layout.description layout.get_modalities() layout.get_tasks()
def _run_interface(self, runtime):
# Validate derivatives argument
derivatives, scope = validate_derivatives(
bids_dir=self.inputs.bids_dir, derivatives=self.inputs.derivatives)
layout = BIDSLayout(root=self.inputs.bids_dir,
derivatives=derivatives,
validate=True,
index_metadata=False)
# Validate optional arguments
filter_base = {}
if isdefined(self.inputs.task):
task = validate_option(layout, self.inputs.task, kind='task')
filter_base['task'] = task
else:
task = layout.get_tasks()
if isdefined(self.inputs.session):
session = validate_option(layout,
self.inputs.session,
kind='session')
filter_base['session'] = session
if isdefined(self.inputs.subject):
subject = validate_option(layout,
self.inputs.subject,
kind='subject')
filter_base['subject'] = subject
# Define query filters
filter_fmri = {
'extension': ['nii', 'nii.gz'],
'suffix': 'bold',
'desc': 'preproc',
'space': 'MNI152NLin2009cAsym'
}
filter_fmri_aroma = {
'extension': ['nii', 'nii.gz'],
'suffix': 'bold',
'desc': 'smoothAROMAnonaggr',
'space': 'MNI152NLin2009cAsym'
}
filter_conf = {
'extension': 'tsv',
'suffix': 'regressors',
'desc': 'confounds',
}
filter_conf_json = {
'extension': 'json',
'suffix': 'regressors',
'desc': 'confounds',
}
filter_fmri.update(filter_base)
filter_fmri_aroma.update(filter_base)
filter_conf.update(filter_base)
filter_conf_json.update(filter_base)
# Grab all requested files
fmri_prep = layout.get(scope=scope, **filter_fmri)
if self.inputs.ica_aroma:
fmri_prep_aroma = layout.get(scope=scope, **filter_fmri_aroma)
if not fmri_prep_aroma:
raise MissingFile(
"ICA-AROMA files not found in BIDS directory")
conf_raw = layout.get(scope=scope, **filter_conf)
conf_json = layout.get(scope=scope, **filter_conf_json)
# Validate correspondence between queried files
entities = []
for i, fmri_file in enumerate(fmri_prep):
# reference common entities for preprocessed files
if self.inputs.ica_aroma and fmri_prep_aroma:
compare_common_entities(fmri_file, fmri_prep_aroma[i])
compare_common_entities(fmri_file, conf_raw[i])
compare_common_entities(fmri_file, conf_json[i])
entities.append({
key: value
for key, value in fmri_file.get_entities().items()
if key in ['task', 'session', 'subject', 'datatype']
})
# Extract TRs
tr_dict = {}
#TODO: this is just a funny workaround, look for better solution later
layout_for_tr = BIDSLayout(root=self.inputs.bids_dir,
derivatives=derivatives,
validate=True,
index_metadata=True)
for t in task:
filter_fmri_tr = filter_fmri.copy()
filter_fmri_tr['task'] = t
try:
example_file = layout_for_tr.get(**filter_fmri_tr)[0]
except IndexError:
raise MissingFile(f"no imaging file found for task {t}")
tr_dict[t] = layout_for_tr.get_metadata(
example_file.path)['RepetitionTime']
self._results['fmri_prep'] = [file.path for file in fmri_prep]
if self.inputs.ica_aroma:
self._results['fmri_prep_aroma'] = [
file.path for file in fmri_prep_aroma
]
self._results['conf_raw'] = [file.path for file in conf_raw]
self._results['conf_json'] = [file.path for file in conf_json]
self._results['entities'] = entities
self._results['tr_dict'] = tr_dict
return runtime
"suffix": "T1w",
"extensions": ["nii", ".nii.gz"]
}
layout = BIDSLayout(args['directory'])
data_grabber_node_iterables = []
if args['task'] is not None:
struct_params['task'] = args['task']
time_series_params['task'] = args['task']
elif args['fmri_task'] is not None:
time_series_params['task'] = args['fmri_task']
elif args['t1_task'] is not None:
struct_params['task'] = args['t1_task']
else:
data_grabber_node_iterables.append(('task', layout.get_tasks()))
if args['acquisition'] is not None:
struct_params['acquisition'] = args['acquisition']
time_series_params['acquisition'] = args['acquisition']
elif args['t1_acquisition'] is not None:
struct_params['acquisition'] = args['t1_acquisition']
elif args['fmri_acquisition'] is not None:
time_series_params['acquisition'] = args['fmri_acquisition']
else:
data_grabber_node_iterables.append(
('acquisition', layout.get_acquisitions()))
if args['session'] is not None:
struct_params['session'] = args['session']
time_series_params['session'] = args['session']
def get_files(subject_id,
session,
task,
raw_data_dir,
preprocessed_data_dir,
space=None,
run=[],
strict=True,
**kwargs):
"""
Given some information, retrieve all the files and metadata from a
BIDS-formatted dataset that will be passed to the analysis pipeline.
"""
from bids import BIDSLayout
# only the raw files have the correct metadata, eg TR, and the event files are here
raw_layout = BIDSLayout(raw_data_dir, validate=False, derivatives=False)
preproc_layout = BIDSLayout(preprocessed_data_dir, validate=False)
subjects = preproc_layout.get_subjects()
assert subject_id in subjects and subject_id in raw_layout.get_subjects(
), "Subject not found!"
sessions = preproc_layout.get_sessions()
assert session in sessions, "Session not found!"
tasks = preproc_layout.get_tasks()
assert task in tasks, "Task not found!"
if space == "None":
space = None
if space is None:
print("Space is None")
bolds = sorted([
f for f in preproc_layout.get(subject=subject_id,
session=session,
task=task,
run=run,
suffix='bold',
extension=['nii.gz'],
return_type='file')
])
else:
bolds = sorted([
f for f in preproc_layout.get(subject=subject_id,
session=session,
task=task,
run=run,
suffix='bold',
extension=['nii.gz'],
return_type='file')
if f"space-{space}" in f
])
print(f"BOLDS: {len(bolds)}\n{bolds}")
if space is None:
masks = sorted([
f for f in preproc_layout.get(subject=subject_id,
suffix='mask',
session=session,
task=task,
extension=['nii.gz'],
return_type='file')
])
if not masks:
masks = sorted([
f for f in preproc_layout.get(subject=subject_id,
suffix='mask',
session=session,
extension=['nii.gz'],
return_type='file')
])
else:
masks = sorted([
f for f in preproc_layout.get(subject=subject_id,
suffix='mask',
session=session,
task=task,
extension=['nii.gz'],
return_type='file')
if f"space-{space}" in f
])
if not masks:
masks = sorted([
f for f in preproc_layout.get(subject=subject_id,
suffix='mask',
session=session,
extension=['nii.gz'],
return_type='file')
if f"space-{space}" in f
])
if len(masks
) == 1: # there is only one mask and it is to be used for all runs
masks = masks * len(bolds)
print(f"Masks: {len(masks)}\n{masks}")
eventfiles = sorted(
raw_layout.get(subject=subject_id,
suffix='events',
task=task,
session=session,
run=run,
extension=['tsv'],
return_type='file'))
print(f"Eventfiles: {len(eventfiles)}\n{eventfiles}")
raw_bolds = sorted(
raw_layout.get(subject=subject_id,
suffix='bold',
task=task,
session=session,
run=run,
extension=['nii.gz'],
return_type='file'))
TRs = [raw_layout.get_metadata(f)['RepetitionTime'] for f in raw_bolds]
print(TRs, len(TRs))
confounds = sorted(
preproc_layout.get(subject=subject_id,
suffix="regressors",
task=task,
session=session,
run=run,
extension=['tsv'],
return_type='file'))
print(f"Confounds: {len(confounds)}\n{confounds}")
if not confounds:
confounds = [''] * len(bolds)
#print(list(zip(bolds, masks, eventfiles, TRs)))
# edit 11/9/18 - remove assert on event files, since some early hemifield scans don't have it
# but warn!
if (len(eventfiles) != len(bolds)):
print("Some functional runs do not have corresponding event files!")
assert TRs.count(TRs[0]) == len(
TRs
), "Not all TRs are the same!" # all runs for a particular task must have same TR
if strict:
assert len(bolds) == len(
masks
) > 0, "Input lists are not the same length!" # used to also check for ==len(confounds)
TR = TRs[0]
return bolds, masks, eventfiles, TR, confounds
