def get_config(
subject: Optional[str] = None,
session: Optional[str] = None
) -> BunchConst:
cfg = BunchConst(
process_er=config.process_er,
runs=config.get_runs(subject=subject),
use_maxwell_filter=config.use_maxwell_filter,
proc=config.proc,
task=config.get_task(),
datatype=config.get_datatype(),
session=session,
acq=config.acq,
rec=config.rec,
space=config.space,
bids_root=config.get_bids_root(),
deriv_root=config.get_deriv_root(),
interactive=config.interactive,
epochs_tmin=config.epochs_tmin,
epochs_tmax=config.epochs_tmax,
epochs_metadata_tmin=config.epochs_metadata_tmin,
epochs_metadata_tmax=config.epochs_metadata_tmax,
epochs_metadata_keep_first=config.epochs_metadata_keep_first,
epochs_metadata_keep_last=config.epochs_metadata_keep_last,
event_repeated=config.event_repeated,
decim=config.decim,
ch_types=config.ch_types,
eeg_reference=config.get_eeg_reference()
)
return cfg
def get_config(subject: Optional[str] = None,
session: Optional[str] = None) -> SimpleNamespace:
# Deal with configurations where `deriv_root` was specified, but not
# `fs_subjects_dir`. We normally raise an exception in this case in
# `get_fs_subjects_dir()`. However, in situations where users only run the
# sensor-space scripts, we never call this function, so everything works
# totally fine at first (which is expected). Yet, when creating the
# reports, the pipeline would fail with an exception – which is
# unjustified, as it would not make sense to force users to provide an
# `fs_subjects_dir` if they don't care about source analysis anyway! So
# simply assign a dummy value in such cases.
# `get_fs_subject()` calls `get_fs_subjects_dir()`, so take care of this
# too.
try:
fs_subjects_dir = config.get_fs_subjects_dir()
except ValueError:
fs_subjects_dir = None
fs_subject = None
else:
fs_subject = config.get_fs_subject(subject=subject)
cfg = SimpleNamespace(
task=config.get_task(),
runs=config.get_runs(subject=subject),
datatype=config.get_datatype(),
acq=config.acq,
rec=config.rec,
space=config.space,
proc=config.proc,
analyze_channels=config.analyze_channels,
process_er=config.process_er,
find_noisy_channels_meg=config.find_noisy_channels_meg,
h_freq=config.h_freq,
spatial_filter=config.spatial_filter,
ica_reject=config.ica_reject,
conditions=config.conditions,
contrasts=config.contrasts,
time_frequency_conditions=config.time_frequency_conditions,
decode=config.decode,
decoding_metric=config.decoding_metric,
n_boot=config.n_boot,
inverse_method=config.inverse_method,
fs_subject=fs_subject,
fs_subjects_dir=fs_subjects_dir,
deriv_root=config.get_deriv_root(),
bids_root=config.get_bids_root(),
use_template_mri=config.use_template_mri,
interactive=config.interactive,
plot_psd_for_runs=config.plot_psd_for_runs,
)
return cfg
def main() -> None:
"""Run freesurfer recon-all command on BIDS dataset.
The script allows to run the freesurfer recon-all
command on all subjects of your BIDS dataset. It can
run in parallel with the --n_jobs parameter.
It is built on top of the FreeSurfer BIDS app:
https://github.com/BIDS-Apps/freesurfer
and the MNE BIDS Pipeline
https://mne.tools/mne-bids-pipeline
You must have freesurfer available on your system.
Run via the MNE BIDS Pipeline's `run.py`:
python run.py --steps=freesurfer --config=your_pipeline_config.py
""" # noqa
logger.info('Running FreeSurfer')
subjects = config.get_subjects()
root_dir = config.get_bids_root()
subjects_dir = Path(config.get_fs_subjects_dir())
subjects_dir.mkdir(parents=True, exist_ok=True)
with config.get_parallel_backend():
n_jobs = config.get_n_jobs()
parallel, run_func, _ = parallel_func(run_recon, n_jobs=n_jobs)
parallel(run_func(root_dir, subject, fs_bids_app)
for subject in subjects)
# Handle fsaverage
fsaverage_dir = subjects_dir / 'fsaverage'
if fsaverage_dir.exists():
if fsaverage_dir.is_symlink():
fsaverage_dir.unlink()
else:
shutil.rmtree(fsaverage_dir)
env = os.environ
shutil.copytree(f"{env['FREESURFER_HOME']}/subjects/fsaverage",
subjects_dir / 'fsaverage')
def get_config(subject: Optional[str] = None,
session: Optional[str] = None) -> SimpleNamespace:
cfg = SimpleNamespace(
task=config.get_task(),
runs=config.get_runs(subject=subject),
datatype=config.get_datatype(),
acq=config.acq,
rec=config.rec,
space=config.space,
mindist=config.mindist,
spacing=config.spacing,
use_template_mri=config.use_template_mri,
source_info_path_update=config.source_info_path_update,
ch_types=config.ch_types,
fs_subject=config.get_fs_subject(subject=subject),
fs_subjects_dir=config.get_fs_subjects_dir(),
deriv_root=config.get_deriv_root(),
bids_root=config.get_bids_root(),
n_jobs=config.get_n_jobs())
return cfg
def get_config(subject: Optional[str] = None,
session: Optional[str] = None) -> BunchConst:
cfg = BunchConst(
process_er=config.process_er,
runs=config.get_runs(subject=subject),
use_maxwell_filter=config.use_maxwell_filter,
proc=config.proc,
task=config.get_task(),
datatype=config.get_datatype(),
acq=config.acq,
rec=config.rec,
space=config.space,
bids_root=config.get_bids_root(),
deriv_root=config.get_deriv_root(),
l_freq=config.l_freq,
h_freq=config.h_freq,
l_trans_bandwidth=config.l_trans_bandwidth,
h_trans_bandwidth=config.h_trans_bandwidth,
resample_sfreq=config.resample_sfreq,
crop_runs=config.crop_runs,
interactive=config.interactive,
rename_events=config.rename_events,
eeg_bipolar_channels=config.eeg_bipolar_channels,
eeg_template_montage=config.eeg_template_montage,
fix_stim_artifact=config.fix_stim_artifact,
stim_artifact_tmin=config.stim_artifact_tmin,
stim_artifact_tmax=config.stim_artifact_tmax,
find_flat_channels_meg=config.find_flat_channels_meg,
find_noisy_channels_meg=config.find_noisy_channels_meg,
reference_run=config.get_mf_reference_run(),
drop_channels=config.drop_channels,
find_breaks=config.find_breaks,
min_break_duration=config.min_break_duration,
t_break_annot_start_after_previous_event=config.
t_break_annot_start_after_previous_event, # noqa:E501
t_break_annot_stop_before_next_event=config.
t_break_annot_stop_before_next_event, # noqa:E501
)
return cfg
def get_config(
subject: Optional[str] = None,
session: Optional[str] = None
) -> BunchConst:
cfg = BunchConst(
task=config.get_task(),
runs=config.get_runs(subject=subject),
datatype=config.get_datatype(),
acq=config.acq,
rec=config.rec,
space=config.space,
mindist=config.mindist,
spacing=config.spacing,
use_template_mri=config.use_template_mri,
ch_types=config.ch_types,
fs_subject=config.get_fs_subject(subject=subject),
fs_subjects_dir=config.get_fs_subjects_dir(),
deriv_root=config.get_deriv_root(),
bids_root=config.get_bids_root(),
n_jobs=config.get_n_jobs()
)
return cfg
def get_config(
subject: Optional[str] = None,
session: Optional[str] = None
) -> BunchConst:
cfg = BunchConst(
mf_cal_fname=config.get_mf_cal_fname(subject, session),
mf_ctc_fname=config.get_mf_ctc_fname(subject, session),
mf_st_duration=config.mf_st_duration,
mf_head_origin=config.mf_head_origin,
process_er=config.process_er,
runs=config.get_runs(subject=subject), # XXX needs to accept session!
use_maxwell_filter=config.use_maxwell_filter,
proc=config.proc,
task=config.get_task(),
datatype=config.get_datatype(),
acq=config.acq,
rec=config.rec,
space=config.space,
bids_root=config.get_bids_root(),
deriv_root=config.get_deriv_root(),
crop_runs=config.crop_runs,
interactive=config.interactive,
rename_events=config.rename_events,
eeg_template_montage=config.eeg_template_montage,
fix_stim_artifact=config.fix_stim_artifact,
stim_artifact_tmin=config.stim_artifact_tmin,
stim_artifact_tmax=config.stim_artifact_tmax,
find_flat_channels_meg=config.find_flat_channels_meg,
find_noisy_channels_meg=config.find_noisy_channels_meg,
mf_reference_run=config.get_mf_reference_run(),
drop_channels=config.drop_channels,
find_breaks=config.find_breaks,
min_break_duration=config.min_break_duration,
t_break_annot_start_after_previous_event=config.t_break_annot_start_after_previous_event, # noqa:E501
t_break_annot_stop_before_next_event=config.t_break_annot_stop_before_next_event, # noqa:E501
)
return cfg