def test_find_edf_events_deprecation():
"""Test find_edf_events deprecation."""
raw = read_raw_edf(edf_path)
with pytest.deprecated_call(match="find_edf_events"):
raw.find_edf_events()
with pytest.deprecated_call(match="find_edf_events"):
find_edf_events(raw)
def test_find_edf_events_deprecation():
"""Test find_edf_events deprecation."""
raw = read_raw_edf(edf_path)
with pytest.deprecated_call(match="find_edf_events"):
raw.find_edf_events()
with pytest.deprecated_call(match="find_edf_events"):
find_edf_events(raw)
def test_stim_channel():
"""Test reading raw edf files with stim channel."""
raw_py = read_raw_edf(edf_path,
misc=range(-4, 0),
stim_channel=139,
preload=True)
picks = pick_types(raw_py.info,
meg=False,
eeg=True,
exclude=['EDF Annotations'])
data_py, _ = raw_py[picks]
print(raw_py) # to test repr
print(raw_py.info) # to test Info repr
# this .mat was generated using the EEG Lab Biosemi Reader
raw_eeglab = io.loadmat(edf_eeglab_path)
raw_eeglab = raw_eeglab['data'] * 1e-6 # data are stored in microvolts
data_eeglab = raw_eeglab[picks]
assert_array_almost_equal(data_py, data_eeglab, 10)
events = find_edf_events(raw_py)
assert (len(events) - 1 == len(find_events(raw_py))) # start not found
# Test uneven sampling
raw_py = read_raw_edf(edf_uneven_path, stim_channel=None)
data_py, _ = raw_py[0]
# this .mat was generated using the EEG Lab Biosemi Reader
raw_eeglab = io.loadmat(edf_uneven_eeglab_path)
raw_eeglab = raw_eeglab['data']
data_eeglab = raw_eeglab[0]
# match upsampling
upsample = len(data_eeglab) / len(raw_py)
data_py = np.repeat(data_py, repeats=upsample)
assert_array_equal(data_py, data_eeglab)
pytest.raises(RuntimeError,
read_raw_edf,
edf_path,
preload=False,
stim_channel=-1)
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
raw = read_raw_edf(edf_stim_resamp_path, verbose=True, stim_channel=-1)
assert_equal(len(w), 2)
assert (any('Events may jitter' in str(ww.message) for ww in w))
assert (any('truncated' in str(ww.message) for ww in w))
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
raw[:]
assert_equal(len(w), 0)
events = raw_py.find_edf_events()
assert (len(events) == 0)
def test_stim_channel():
"""Test reading raw edf files with stim channel."""
raw_py = read_raw_edf(edf_path,
misc=range(-4, 0),
stim_channel=139,
preload=True)
picks = pick_types(raw_py.info,
meg=False,
eeg=True,
exclude=['EDF Annotations'])
data_py, _ = raw_py[picks]
print(raw_py) # to test repr
print(raw_py.info) # to test Info repr
# this .mat was generated using the EEG Lab Biosemi Reader
raw_eeglab = loadmat(edf_eeglab_path)
raw_eeglab = raw_eeglab['data'] * 1e-6 # data are stored in microvolts
data_eeglab = raw_eeglab[picks]
assert_array_almost_equal(data_py, data_eeglab, 10)
events = find_edf_events(raw_py)
assert len(events) - 1 == len(find_events(raw_py)) # start not found
# Test uneven sampling
raw_py = read_raw_edf(edf_uneven_path, stim_channel=None)
data_py, _ = raw_py[0]
# this .mat was generated using the EEG Lab Biosemi Reader
raw_eeglab = loadmat(edf_uneven_eeglab_path)
raw_eeglab = raw_eeglab['data']
data_eeglab = raw_eeglab[0]
# match upsampling
upsample = len(data_eeglab) / len(raw_py)
data_py = np.repeat(data_py, repeats=upsample)
assert_array_equal(data_py, data_eeglab)
pytest.raises(RuntimeError,
read_raw_edf,
edf_path,
preload=False,
stim_channel=-1)
with pytest.warns(RuntimeWarning,
match='Interpolating stim .* Events may jitter'):
raw = read_raw_edf(edf_stim_resamp_path, verbose=True, stim_channel=-1)
with pytest.warns(None) as w:
raw[:]
assert len(w) == 0
events = raw_py.find_edf_events()
assert len(events) == 0
def test_stim_channel():
"""Test reading raw edf files with stim channel."""
raw_py = read_raw_edf(edf_path, misc=range(-4, 0), stim_channel=139,
preload=True)
picks = pick_types(raw_py.info, meg=False, eeg=True,
exclude=['EDF Annotations'])
data_py, _ = raw_py[picks]
print(raw_py) # to test repr
print(raw_py.info) # to test Info repr
# this .mat was generated using the EEG Lab Biosemi Reader
raw_eeglab = io.loadmat(edf_eeglab_path)
raw_eeglab = raw_eeglab['data'] * 1e-6 # data are stored in microvolts
data_eeglab = raw_eeglab[picks]
assert_array_almost_equal(data_py, data_eeglab, 10)
events = find_edf_events(raw_py)
assert_true(len(events) - 1 == len(find_events(raw_py))) # start not found
# Test uneven sampling
raw_py = read_raw_edf(edf_uneven_path, stim_channel=None)
data_py, _ = raw_py[0]
# this .mat was generated using the EEG Lab Biosemi Reader
raw_eeglab = io.loadmat(edf_uneven_eeglab_path)
raw_eeglab = raw_eeglab['data']
data_eeglab = raw_eeglab[0]
# match upsampling
upsample = len(data_eeglab) / len(raw_py)
data_py = np.repeat(data_py, repeats=upsample)
assert_array_equal(data_py, data_eeglab)
assert_raises(RuntimeError, read_raw_edf, edf_path, preload=False,
stim_channel=-1)
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
raw = read_raw_edf(edf_stim_resamp_path, verbose=True, stim_channel=-1)
assert_equal(len(w), 2)
assert_true(any('Events may jitter' in str(ww.message) for ww in w))
assert_true(any('truncated' in str(ww.message) for ww in w))
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
raw[:]
assert_equal(len(w), 0)
events = raw_py.find_edf_events()
assert_true(len(events) == 0)
def test_stim_channel():
"""Test reading raw edf files with stim channel."""
raw_py = read_raw_edf(edf_path, misc=range(-4, 0), stim_channel=139,
preload=True)
picks = pick_types(raw_py.info, meg=False, eeg=True,
exclude=['EDF Annotations'])
data_py, _ = raw_py[picks]
print(raw_py) # to test repr
print(raw_py.info) # to test Info repr
# this .mat was generated using the EEG Lab Biosemi Reader
raw_eeglab = io.loadmat(edf_eeglab_path)
raw_eeglab = raw_eeglab['data'] * 1e-6 # data are stored in microvolts
data_eeglab = raw_eeglab[picks]
assert_array_almost_equal(data_py, data_eeglab, 10)
events = find_edf_events(raw_py)
assert (len(events) - 1 == len(find_events(raw_py))) # start not found
# Test uneven sampling
raw_py = read_raw_edf(edf_uneven_path, stim_channel=None)
data_py, _ = raw_py[0]
# this .mat was generated using the EEG Lab Biosemi Reader
raw_eeglab = io.loadmat(edf_uneven_eeglab_path)
raw_eeglab = raw_eeglab['data']
data_eeglab = raw_eeglab[0]
# match upsampling
upsample = len(data_eeglab) / len(raw_py)
data_py = np.repeat(data_py, repeats=upsample)
assert_array_equal(data_py, data_eeglab)
pytest.raises(RuntimeError, read_raw_edf, edf_path, preload=False,
stim_channel=-1)
with pytest.warns(RuntimeWarning,
match='Interpolating stim .* Events may jitter'):
raw = read_raw_edf(edf_stim_resamp_path, verbose=True, stim_channel=-1)
with pytest.warns(None) as w:
raw[:]
assert len(w) == 0
events = raw_py.find_edf_events()
assert (len(events) == 0)