def _run_test_for_invalid_separator(filepath, delimiter_name):
if delimiter_name not in ('tab', 'comma'):
with assert_raises(ValueError):
_verify_events_file_uses_tab_separators(events_files=filepath)
else:
result = _verify_events_file_uses_tab_separators(events_files=filepath)
assert_true(result is None)
def test_binary_opening_an_image():
img_data = bytearray(
b'GIF87a\x01\x00\x01\x00\xe7*\x00\x00\x00\x00\x01\x01\x01\x02\x02'
b'\x07\x08\x08\x08\t\t\t\n\n\n\x0b\x0b\x0b\x0c\x0c\x0c\r;')
with NamedTemporaryFile(mode='wb', suffix='.gif',
dir=os.getcwd()) as temp_img_obj:
temp_img_obj.write(img_data)
with assert_raises(ValueError):
_verify_events_file_uses_tab_separators(
events_files=temp_img_obj.name)
def test_with_1D_dataframe():
data_for_pandas_dataframe, _ = make_data_for_test_runs()
for dataframe_ in data_for_pandas_dataframe:
events_pandas_dataframe = pd.DataFrame(dataframe_)
result = _verify_events_file_uses_tab_separators(
events_files=events_pandas_dataframe)
assert_true(result is None)
def test_binary_bytearray_of_ints_data():
temp_data_bytearray_from_ints = bytearray([0, 1, 0, 11, 10])
with NamedTemporaryFile(mode='wb', dir=os.getcwd(),
suffix='.bin') as temp_bin_obj:
temp_bin_obj.write(temp_data_bytearray_from_ints)
with assert_raises(ValueError):
result = _verify_events_file_uses_tab_separators(
events_files=temp_bin_obj.name)
def fetch_localizer_first_level(data_dir=None, verbose=1):
""" Download a first-level localizer fMRI dataset
Parameters
----------
data_dir: string
directory where data should be downloaded and unpacked.
Returns
-------
data: sklearn.datasets.base.Bunch
dictionary-like object, with the keys:
epi_img: the input 4D image
events: a csv file describing the paardigm
"""
url = 'ftp://ftp.cea.fr/pub/dsv/madic/download/nipy'
dataset_name = "localizer_first_level"
files = dict(epi_img="s12069_swaloc1_corr.nii.gz",
events="localizer_paradigm.csv")
# The options needed for _fetch_files
options = [(filename, os.path.join(url, filename), {})
for _, filename in sorted(files.items())]
data_dir = _get_dataset_dir(dataset_name,
data_dir=data_dir,
verbose=verbose)
sub_files = _fetch_files(data_dir, options, resume=True, verbose=verbose)
params = dict(zip(sorted(files.keys()), sub_files))
try:
_verify_events_file_uses_tab_separators(params['events'])
except ValueError:
_make_events_file_localizer_first_level(events_file=params['events'])
return Bunch(**params)
def test_for_pandas_dataframe():
events_pandas_dataframe = pd.DataFrame([['a', 'b', 'c'], [0, 1, 2]])
result = _verify_events_file_uses_tab_separators(
events_files=events_pandas_dataframe)
assert_true(result is None)
def test_for_invalid_filepath():
filepath = 'junk_file_path.csv'
result = _verify_events_file_uses_tab_separators(events_files=filepath)
assert_true(result is None)
