def test_unlock_raises(path, path2, path3):
# make sure, we are not within a dataset:
_cwd = getpwd()
chpwd(path)
# no dataset and no path:
assert_raises(InsufficientArgumentsError, unlock, dataset=None, path=None)
# no dataset and path not within a dataset:
with swallow_logs(new_level=logging.WARNING) as cml:
unlock(dataset=None, path=path2)
assert_in(
"ignored paths that do not belong to any dataset: ['{0}'".format(
path2), cml.out)
create(path=path, no_annex=True)
ds = Dataset(path)
# no complaints
ds.unlock()
# make it annex, but call unlock with invalid path:
AnnexRepo(path, create=True)
with swallow_logs(new_level=logging.WARNING) as cml:
ds.unlock(path="notexistent.txt")
assert_in("ignored non-existing paths", cml.out)
chpwd(_cwd)
def test_unlock_raises(path, path2, path3):
# make sure, we are not within a dataset:
_cwd = getpwd()
chpwd(path)
# no dataset and no path:
assert_raises(InsufficientArgumentsError,
unlock, dataset=None, path=None)
# no dataset and path not within a dataset:
with swallow_logs(new_level=logging.WARNING) as cml:
unlock(dataset=None, path=path2)
assert_in("ignored paths that do not belong to any dataset: ['{0}'".format(path2),
cml.out)
create(path=path, no_annex=True)
ds = Dataset(path)
# no complaints
ds.unlock()
# make it annex, but call unlock with invalid path:
AnnexRepo(path, create=True)
with swallow_logs(new_level=logging.WARNING) as cml:
ds.unlock(path="notexistent.txt")
assert_in("ignored non-existing paths", cml.out)
chpwd(_cwd)
def test_unlock_raises(path, path2, path3):
# make sure, we are not within a dataset:
_cwd = getpwd()
chpwd(path)
# no dataset and no path:
assert_raises(InsufficientArgumentsError, unlock, dataset=None, path=None)
# no dataset and path not within a dataset:
res = unlock(dataset=None,
path=path2,
result_xfm=None,
on_failure='ignore',
return_type='item-or-list')
eq_(res['message'], "path not associated with any dataset")
eq_(res['path'], path2)
create(path=path, no_annex=True)
ds = Dataset(path)
# no complaints
ds.unlock()
# make it annex, but call unlock with invalid path:
AnnexRepo(path, create=True)
res = ds.unlock(path="notexistent.txt",
result_xfm=None,
on_failure='ignore',
return_type='item-or-list')
eq_(res['message'], "path does not exist")
chpwd(_cwd)
def test_unlock_raises(path, path2, path3):
# make sure, we are not within a dataset:
_cwd = getpwd()
chpwd(path)
# no dataset and no path:
assert_raises(InsufficientArgumentsError,
unlock, dataset=None, path=None)
# no dataset and path not within a dataset:
res = unlock(dataset=None, path=path2, result_xfm=None,
on_failure='ignore', return_type='item-or-list')
eq_(res['message'], "path not associated with any dataset")
eq_(res['path'], path2)
create(path=path, no_annex=True)
ds = Dataset(path)
# no complaints
ds.unlock()
# make it annex, but call unlock with invalid path:
AnnexRepo(path, create=True)
res = ds.unlock(path="notexistent.txt", result_xfm=None,
on_failure='ignore', return_type='item-or-list')
eq_(res['message'], "path does not exist")
chpwd(_cwd)
def read_bids_data(bids_root,
subject,
datatype="meg",
task="memento",
suffix="meg"):
"""
Read in a BIDS directory.
:param subject: str, subject identifier, takes the form '001'
:param bids_root: str, path to the root of a BIDS directory to read from
:param datatype: str, descriptor of the data type, e.g., 'meg'
:param task: str, descriptor of the task name ('memento')
:param suffix: str, BIDS suffix for the data, e.g., 'meg'
"""
bids_path = BIDSPath(root=bids_root,
datatype=datatype,
subject=subject,
task=task,
suffix=suffix)
try:
# Only now (Apr. 2021) MNE python gained the ability to read in split
# annexed data. Until this is released and established, we're making
# sure files are read fully, and if not, we attempt to unlock them first
raw = read_raw_bids(
bids_path=bids_path,
extra_params=dict(on_split_missing="raise"),
)
except ValueError:
logging.warn(
"Ooops! I can't load all splits of the data. This may be because "
"you run a version of MNE-python that does not read in annexed "
"data automatically. I will try to datalad-unlock them for you.")
import datalad.api as dl
dl.unlock(bids_path.directory)
raw = read_raw_bids(
bids_path=bids_path,
extra_params=dict(on_split_missing="raise"),
)
# return the raw data, and also the bids path as it has
return raw, bids_path