def test_io_set_raw(fname):
"""Test importing EEGLAB .set files."""
montage = _read_eeglab_montage(montage_path)
montage.ch_names = [
'EEG {0:03d}'.format(ii) for ii in range(len(montage.ch_names))
]
kws = dict(reader=read_raw_eeglab, input_fname=fname)
if fname.endswith('test_raw_chanloc.set'):
with pytest.warns(RuntimeWarning,
match="The data contains 'boundary' events"):
raw0 = _test_raw_reader(**kws)
elif '_h5' in fname: # should be safe enough, and much faster
raw0 = read_raw_eeglab(fname, preload=True)
else:
raw0 = _test_raw_reader(**kws)
# test that preloading works
if fname.endswith('test_raw_chanloc.set'):
raw0.set_montage(montage, on_missing='ignore')
# crop to check if the data has been properly preloaded; we cannot
# filter as the snippet of raw data is very short
raw0.crop(0, 1)
else:
raw0.set_montage(montage)
raw0.filter(1,
None,
l_trans_bandwidth='auto',
filter_length='auto',
phase='zero')
# test that using uint16_codec does not break stuff
read_raw_kws = dict(input_fname=fname, preload=False, uint16_codec='ascii')
if fname.endswith('test_raw_chanloc.set'):
with pytest.warns(RuntimeWarning,
match="The data contains 'boundary' events"):
raw0 = read_raw_eeglab(**read_raw_kws)
raw0.set_montage(montage, on_missing='ignore')
else:
raw0 = read_raw_eeglab(**read_raw_kws)
raw0.set_montage(montage)
# Annotations
if fname != raw_fname_chanloc:
assert len(raw0.annotations) == 154
assert set(raw0.annotations.description) == {'rt', 'square'}
assert_array_equal(raw0.annotations.duration, 0.)
def test_io_set_raw(fname):
"""Test importing EEGLAB .set files."""
montage = _read_eeglab_montage(montage_path)
montage.ch_names = [
'EEG {0:03d}'.format(ii) for ii in range(len(montage.ch_names))
]
_test_raw_reader(read_raw_eeglab, input_fname=fname)
# test that preloading works
raw0 = read_raw_eeglab(input_fname=fname, preload=True)
raw0.set_montage(montage)
raw0.filter(1, None, l_trans_bandwidth='auto', filter_length='auto',
phase='zero')
# test that using uint16_codec does not break stuff
raw0 = read_raw_eeglab(input_fname=fname,
preload=False, uint16_codec='ascii')
raw0.set_montage(montage)
def test_io_set_raw(fname):
"""Test importing EEGLAB .set files."""
montage = _read_eeglab_montage(montage_path)
montage.ch_names = [
'EEG {0:03d}'.format(ii) for ii in range(len(montage.ch_names))
]
kws = dict(reader=read_raw_eeglab, input_fname=fname)
if fname.endswith('test_raw_chanloc.set'):
with pytest.warns(RuntimeWarning,
match="The data contains 'boundary' events"):
_test_raw_reader(**kws)
else:
_test_raw_reader(**kws)
# test that preloading works
read_raw_kws = dict(input_fname=fname, preload=True)
if fname.endswith('test_raw_chanloc.set'):
with pytest.warns(RuntimeWarning,
match="The data contains 'boundary' events"):
raw0 = read_raw_eeglab(**read_raw_kws)
raw0.set_montage(montage, on_missing='ignore')
# crop to check if the data has been properly preloaded; we cannot
# filter as the snippet of raw data is very short
raw0.crop(0, 1)
else:
raw0 = read_raw_eeglab(**read_raw_kws)
raw0.set_montage(montage)
raw0.filter(1,
None,
l_trans_bandwidth='auto',
filter_length='auto',
phase='zero')
# test that using uint16_codec does not break stuff
read_raw_kws = dict(input_fname=fname, preload=False, uint16_codec='ascii')
if fname.endswith('test_raw_chanloc.set'):
with pytest.warns(RuntimeWarning,
match="The data contains 'boundary' events"):
raw0 = read_raw_eeglab(**read_raw_kws)
raw0.set_montage(montage, on_missing='ignore')
else:
raw0 = read_raw_eeglab(**read_raw_kws)
raw0.set_montage(montage)
def test_position_information(one_chanpos_fname):
"""Test reading file with 3 channels - one without position information."""
nan = np.nan
EXPECTED_LOCATIONS_FROM_FILE = np.array([
[-4., 1., 7., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[-5., 2., 8., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan],
])
EXPECTED_LOCATIONS_FROM_MONTAGE = np.array([
[-0.56705965, 0.67706631, 0.46906776, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan],
[0, 0.99977915, -0.02101571, 0, 0, 0, 0, 0, 0, 0, 0, 0],
])
montage = _read_eeglab_montage(montage_path)
raw = read_raw_eeglab(input_fname=one_chanpos_fname, preload=True)
assert_array_equal(np.array([ch['loc'] for ch in raw.info['chs']]),
EXPECTED_LOCATIONS_FROM_FILE)
# To acomodate the new behavior so that:
# read_raw_eeglab(.. montage=montage) and raw.set_montage(montage)
# behaves the same we need to flush the montage. otherwise we get
# a mix of what is in montage and in the file
raw = read_raw_eeglab(
input_fname=one_chanpos_fname,
preload=True,
).set_montage(None) # Flush the montage builtin within input_fname
with pytest.raises(ValueError):
raw.set_montage(montage, update_ch_names=False)
_msg = (
'DigMontage is a only a subset of info. '
'Did not set 1 channel positions:\nunknown'
)
with pytest.warns(RuntimeWarning, match=_msg):
raw.set_montage(montage, update_ch_names=False, raise_if_subset=False)
_assert_array_allclose_nan(np.array([ch['loc'] for ch in raw.info['chs']]),
EXPECTED_LOCATIONS_FROM_MONTAGE)
def test_position_information(one_chanpos_fname):
"""Test reading file with 3 channels - one without position information."""
nan = np.nan
EXPECTED_LOCATIONS_FROM_FILE = np.array([
[-4., 1., 7., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[-5., 2., 8., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan],
])
EXPECTED_LOCATIONS_FROM_MONTAGE = np.array([
[nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan],
[nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan],
[nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan],
])
montage = _read_eeglab_montage(montage_path)
raw = read_raw_eeglab(input_fname=one_chanpos_fname, preload=True)
assert_array_equal(np.array([ch['loc'] for ch in raw.info['chs']]),
EXPECTED_LOCATIONS_FROM_FILE)
# To acomodate the new behavior so that:
# read_raw_eeglab(.. montage=montage) and raw.set_montage(montage)
# behaves the same we need to flush the montage. otherwise we get
# a mix of what is in montage and in the file
raw = read_raw_eeglab(
input_fname=one_chanpos_fname,
preload=True,
).set_montage(None) # Flush the montage builtin within input_fname
_assert_array_allclose_nan(np.array([ch['loc'] for ch in raw.info['chs']]),
EXPECTED_LOCATIONS_FROM_MONTAGE)
with pytest.raises(ValueError):
raw.set_montage(montage, update_ch_names=False)
_assert_array_allclose_nan(np.array([ch['loc'] for ch in raw.info['chs']]),
EXPECTED_LOCATIONS_FROM_MONTAGE)
