def test_first_level_models_from_bids():
with InTemporaryDirectory():
bids_path = _create_fake_bids_dataset(n_sub=10, n_ses=2,
tasks=['localizer', 'main'],
n_runs=[1, 3])
# test arguments are provided correctly
assert_raises(TypeError, first_level_models_from_bids, 2, 'main', 'MNI')
assert_raises(ValueError, first_level_models_from_bids, 'lolo', 'main', 'MNI')
assert_raises(TypeError, first_level_models_from_bids, bids_path, 2, 'MNI')
assert_raises(TypeError, first_level_models_from_bids,
bids_path, 'main', 'MNI', model_init=[])
# test output is as expected
models, m_imgs, m_events, m_confounds = first_level_models_from_bids(
bids_path, 'main', 'MNI', [('variant', 'some')])
assert_true(len(models) == len(m_imgs))
assert_true(len(models) == len(m_events))
assert_true(len(models) == len(m_confounds))
# test repeated run tag error when run tag is in filenames
# can arise when variant or space is present and not specified
assert_raises(ValueError, first_level_models_from_bids,
bids_path, 'main', 'T1w') # variant not specified
# test more than one ses file error when run tag is not in filenames
# can arise when variant or space is present and not specified
assert_raises(ValueError, first_level_models_from_bids,
bids_path, 'localizer', 'T1w') # variant not specified
# test issues with confound files. There should be only one confound
# file per img. An one per image or None. Case when one is missing
confound_files = get_bids_files(os.path.join(bids_path, 'derivatives'),
file_tag='confounds')
os.remove(confound_files[-1])
assert_raises(ValueError, first_level_models_from_bids,
bids_path, 'main', 'MNI')
# test issues with event files
events_files = get_bids_files(bids_path, file_tag='events')
os.remove(events_files[0])
# one file missing
assert_raises(ValueError, first_level_models_from_bids,
bids_path, 'main', 'MNI')
for f in events_files[1:]:
os.remove(f)
# all files missing
assert_raises(ValueError, first_level_models_from_bids,
bids_path, 'main', 'MNI')
# In case different variant and spaces exist and are not selected we
# fail and ask for more specific information
shutil.rmtree(os.path.join(bids_path, 'derivatives'))
# issue if no derivatives folder is present
assert_raises(ValueError, first_level_models_from_bids,
bids_path, 'main', 'MNI')
# check runs are not repeated when ses field is not used
shutil.rmtree(bids_path)
bids_path = _create_fake_bids_dataset(n_sub=10, n_ses=1,
tasks=['localizer', 'main'],
n_runs=[1, 3], no_session=True)
# test repeated run tag error when run tag is in filenames and not ses
# can arise when variant or space is present and not specified
assert_raises(ValueError, first_level_models_from_bids,
bids_path, 'main', 'T1w') # variant not specified
def test_first_level_models_from_bids():
with InTemporaryDirectory():
bids_path = create_fake_bids_dataset(n_sub=10, n_ses=2,
tasks=['localizer', 'main'],
n_runs=[1, 3])
# test arguments are provided correctly
assert_raises(TypeError, first_level_models_from_bids, 2, 'main', 'MNI')
assert_raises(ValueError, first_level_models_from_bids, 'lolo', 'main', 'MNI')
assert_raises(TypeError, first_level_models_from_bids, bids_path, 2, 'MNI')
assert_raises(TypeError, first_level_models_from_bids,
bids_path, 'main', 'MNI', model_init=[])
# test output is as expected
models, m_imgs, m_events, m_confounds = first_level_models_from_bids(
bids_path, 'main', 'MNI', [('variant', 'some')])
assert_true(len(models) == len(m_imgs))
assert_true(len(models) == len(m_events))
assert_true(len(models) == len(m_confounds))
# test repeated run tag error when run tag is in filenames
# can arise when variant or space is present and not specified
assert_raises(ValueError, first_level_models_from_bids,
bids_path, 'main', 'T1w') # variant not specified
# test more than one ses file error when run tag is not in filenames
# can arise when variant or space is present and not specified
assert_raises(ValueError, first_level_models_from_bids,
bids_path, 'localizer', 'T1w') # variant not specified
# test issues with confound files. There should be only one confound
# file per img. An one per image or None. Case when one is missing
confound_files = get_bids_files(os.path.join(bids_path, 'derivatives'),
file_tag='confounds')
os.remove(confound_files[-1])
assert_raises(ValueError, first_level_models_from_bids,
bids_path, 'main', 'MNI')
# test issues with event files
events_files = get_bids_files(bids_path, file_tag='events')
os.remove(events_files[0])
# one file missing
assert_raises(ValueError, first_level_models_from_bids,
bids_path, 'main', 'MNI')
for f in events_files[1:]:
os.remove(f)
# all files missing
assert_raises(ValueError, first_level_models_from_bids,
bids_path, 'main', 'MNI')
# In case different variant and spaces exist and are not selected we
# fail and ask for more specific information
shutil.rmtree(os.path.join(bids_path, 'derivatives'))
# issue if no derivatives folder is present
assert_raises(ValueError, first_level_models_from_bids,
bids_path, 'main', 'MNI')
# check runs are not repeated when ses field is not used
shutil.rmtree(bids_path)
bids_path = create_fake_bids_dataset(n_sub=10, n_ses=1,
tasks=['localizer', 'main'],
n_runs=[1, 3], no_session=True)
# test repeated run tag error when run tag is in filenames and not ses
# can arise when variant or space is present and not specified
assert_raises(ValueError, first_level_models_from_bids,
bids_path, 'main', 'T1w') # variant not specified
def test_get_bids_files():
with InTemporaryDirectory():
bids_path = _create_fake_bids_dataset(n_sub=10,
n_ses=2,
tasks=['localizer', 'main'],
n_runs=[1, 3])
# For each possible possible option of file selection we check
# that we recover the appropriate amount of files, as included
# in the fake bids dataset.
# 250 files in total related to subject images. Top level files like
# README not included
selection = get_bids_files(bids_path)
assert_true(len(selection) == 250)
# 160 bold files expected. .nii and .json files
selection = get_bids_files(bids_path, file_tag='bold')
assert_true(len(selection) == 160)
# Only 90 files are nii.gz. Bold and T1w files.
selection = get_bids_files(bids_path, file_type='nii.gz')
assert_true(len(selection) == 90)
# Only 25 files correspond to subject 01
selection = get_bids_files(bids_path, sub_label='01')
assert_true(len(selection) == 25)
# There are only 10 files in anat folders. One T1w per subject.
selection = get_bids_files(bids_path, modality_folder='anat')
assert_true(len(selection) == 10)
# 20 files corresponding to run 1 of session 2 of main task.
# 10 bold.nii.gz and 10 bold.json files. (10 subjects)
filters = [('task', 'main'), ('run', '01'), ('ses', '02')]
selection = get_bids_files(bids_path, file_tag='bold', filters=filters)
assert_true(len(selection) == 20)
# Get Top level folder files. Only 1 in this case, the README file.
selection = get_bids_files(bids_path, sub_folder=False)
assert_true(len(selection) == 1)