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)