def test_how_to_deal_with_warnings(): """Test filter some messages out of warning records.""" with pytest.warns(UserWarning, match='bb') as w: warnings.warn("aa warning", UserWarning) warnings.warn("bb warning", UserWarning) warnings.warn("bb warning", RuntimeWarning) warnings.warn("aa warning", UserWarning) filter_out_warnings(w, category=UserWarning, match='aa') filter_out_warnings(w, category=RuntimeWarning) assert len(w) == 1
def test_how_to_deal_with_warnings(): """Test filter some messages out of warning records.""" with pytest.warns(UserWarning, match='bb') as w: warnings.warn("aa warning", UserWarning) warnings.warn("bb warning", UserWarning) warnings.warn("bb warning", RuntimeWarning) warnings.warn("aa warning", UserWarning) filter_out_warnings(w, category=UserWarning, match='aa') filter_out_warnings(w, category=RuntimeWarning) assert len(w) == 1
def test_io_set_raw(fnames, tmpdir): """Test importing EEGLAB .set files.""" tmpdir = str(tmpdir) raw_fname, raw_fname_onefile = fnames with pytest.warns(RuntimeWarning) as w: _test_raw_reader(read_raw_eeglab, input_fname=raw_fname, montage=montage) _test_raw_reader(read_raw_eeglab, input_fname=raw_fname_onefile, montage=montage) for want in ('Events like', 'could not be mapped', 'string preload is not supported'): assert (any(want in str(ww.message) for ww in w)) with pytest.warns(RuntimeWarning) as w: # test finding events in continuous data event_id = {'rt': 1, 'square': 2} raw0 = read_raw_eeglab(input_fname=raw_fname, montage=montage, event_id=event_id, preload=True) raw1 = read_raw_eeglab(input_fname=raw_fname, montage=montage, event_id=event_id, preload=False) raw2 = read_raw_eeglab(input_fname=raw_fname_onefile, montage=montage, event_id=event_id) raw3 = read_raw_eeglab(input_fname=raw_fname, montage=montage, event_id=event_id) raw4 = read_raw_eeglab(input_fname=raw_fname, montage=montage) assert raw0.filenames[0].endswith('.fdt') # .set with additional .fdt assert raw2.filenames[0].endswith('.set') # standalone .set raw0_events = find_events(raw0) assert raw0_events.size Epochs(raw0, raw0_events, event_id) epochs = Epochs(raw1, find_events(raw1), event_id) assert len(find_events(raw4)) == 0 # no events without event_id assert epochs["square"].average().nave == 80 # 80 with assert_array_equal(raw0[:][0], raw1[:][0], raw2[:][0], raw3[:][0]) assert_array_equal(raw0[:][-1], raw1[:][-1], raw2[:][-1], raw3[:][-1]) # 1 for preload=False / str with fname_onefile, 3 for dropped events raw0.filter(1, None, l_trans_bandwidth='auto', filter_length='auto', phase='zero') # test that preloading works filter_out_warnings(w, category=FutureWarning) filter_out_warnings(w, category=ImportWarning) assert len(w) == 3 # check `preload=False` raises RuntimeWarning # test that using uint16_codec does not break stuff raw0 = read_raw_eeglab(input_fname=raw_fname, montage=montage, event_id=event_id, preload=False, uint16_codec='ascii') # test old EEGLAB version event import (read old version) eeg = io.loadmat(raw_fname_mat, struct_as_record=False, squeeze_me=True)['EEG'] for event in eeg.event: # old version allows integer events event.type = 1 with pytest.warns(DeprecationWarning, match="read_events_eeglab"): assert read_events_eeglab(eeg)[-1, -1] == 1 eeg.event = eeg.event[0] # single event eeg.event.latency = float(eeg.event.latency) - .1 # test rounding with pytest.warns(DeprecationWarning, match="read_events_eeglab"): assert read_events_eeglab(eeg)[-1, -1] == 1 # test reading file with one event (read old version) eeg = io.loadmat(raw_fname_mat, struct_as_record=False, squeeze_me=True)['EEG'] one_event_fname = op.join(tmpdir, 'test_one_event.set') io.savemat(one_event_fname, { 'EEG': { 'trials': eeg.trials, 'srate': eeg.srate, 'nbchan': eeg.nbchan, 'data': 'test_one_event.fdt', 'epoch': eeg.epoch, 'event': eeg.event[0], 'chanlocs': eeg.chanlocs, 'pnts': eeg.pnts } }, appendmat=False, oned_as='row') shutil.copyfile(op.join(base_dir, 'test_raw.fdt'), one_event_fname.replace('.set', '.fdt')) event_id = {eeg.event[0].type: 1} test_raw = read_raw_eeglab(input_fname=one_event_fname, montage=montage, event_id=event_id, preload=True) # test that sample indices are read python-wise (zero-based) assert find_events(test_raw)[0, 0] == round(eeg.event[0].latency) - 1 # test negative event latencies negative_latency_fname = op.join(tmpdir, 'test_negative_latency.set') evnts = deepcopy(eeg.event[0]) evnts.latency = 0 io.savemat(negative_latency_fname, { 'EEG': { 'trials': eeg.trials, 'srate': eeg.srate, 'nbchan': eeg.nbchan, 'data': 'test_negative_latency.fdt', 'epoch': eeg.epoch, 'event': evnts, 'chanlocs': eeg.chanlocs, 'pnts': eeg.pnts } }, appendmat=False, oned_as='row') shutil.copyfile(op.join(base_dir, 'test_raw.fdt'), negative_latency_fname.replace('.set', '.fdt')) event_id = {eeg.event[0].type: 1} with pytest.warns(RuntimeWarning, match="has a sample index of -1."): read_raw_eeglab(input_fname=negative_latency_fname, preload=True, event_id=event_id, montage=montage) evnts.latency = -1 io.savemat(negative_latency_fname, { 'EEG': { 'trials': eeg.trials, 'srate': eeg.srate, 'nbchan': eeg.nbchan, 'data': 'test_negative_latency.fdt', 'epoch': eeg.epoch, 'event': evnts, 'chanlocs': eeg.chanlocs, 'pnts': eeg.pnts } }, appendmat=False, oned_as='row') with pytest.raises(ValueError, match='event sample index is negative'): with pytest.warns(RuntimeWarning, match="has a sample index of -1."): read_raw_eeglab(input_fname=negative_latency_fname, preload=True, event_id=event_id, montage=montage) # test overlapping events overlap_fname = op.join(tmpdir, 'test_overlap_event.set') io.savemat(overlap_fname, { 'EEG': { 'trials': eeg.trials, 'srate': eeg.srate, 'nbchan': eeg.nbchan, 'data': 'test_overlap_event.fdt', 'epoch': eeg.epoch, 'event': [eeg.event[0], eeg.event[0]], 'chanlocs': eeg.chanlocs, 'pnts': eeg.pnts } }, appendmat=False, oned_as='row') shutil.copyfile(op.join(base_dir, 'test_raw.fdt'), overlap_fname.replace('.set', '.fdt')) event_id = {'rt': 1, 'square': 2} with pytest.warns(RuntimeWarning, match='will be dropped'): raw = read_raw_eeglab(input_fname=overlap_fname, montage=montage, event_id=event_id, preload=True) events_stimchan = find_events(raw) with pytest.warns(DeprecationWarning, match="read_events_eeglab"): events_read_events_eeglab = read_events_eeglab(overlap_fname, event_id) assert (len(events_stimchan) == 1) assert (len(events_read_events_eeglab) == 2) # test reading file with one channel one_chan_fname = op.join(tmpdir, 'test_one_channel.set') io.savemat(one_chan_fname, { 'EEG': { 'trials': eeg.trials, 'srate': eeg.srate, 'nbchan': 1, 'data': np.random.random((1, 3)), 'epoch': eeg.epoch, 'event': eeg.epoch, 'chanlocs': { 'labels': 'E1', 'Y': -6.6069, 'X': 6.3023, 'Z': -2.9423 }, 'times': eeg.times[:3], 'pnts': 3 } }, appendmat=False, oned_as='row') with pytest.warns(None) as w: read_raw_eeglab(input_fname=one_chan_fname, preload=True) # no warning for 'no events found' assert len(w) == 0 # test reading file with 3 channels - one without position information # first, create chanlocs structured array ch_names = ['F3', 'unknown', 'FPz'] x, y, z = [1., 2., np.nan], [4., 5., np.nan], [7., 8., np.nan] dt = [('labels', 'S10'), ('X', 'f8'), ('Y', 'f8'), ('Z', 'f8')] chanlocs = np.zeros((3, ), dtype=dt) for ind, vals in enumerate(zip(ch_names, x, y, z)): for fld in range(4): chanlocs[ind][dt[fld][0]] = vals[fld] if LooseVersion(np.__version__) == '1.14.0': # There is a bug in 1.14.0 (or maybe with SciPy 1.0.0?) that causes # this write to fail! raise SkipTest('Need to fix bug in NumPy 1.14.0!') # save set file one_chanpos_fname = op.join(tmpdir, 'test_chanpos.set') io.savemat(one_chanpos_fname, { 'EEG': { 'trials': eeg.trials, 'srate': eeg.srate, 'nbchan': 3, 'data': np.random.random((3, 3)), 'epoch': eeg.epoch, 'event': eeg.epoch, 'chanlocs': chanlocs, 'times': eeg.times[:3], 'pnts': 3 } }, appendmat=False, oned_as='row') # load it with pytest.warns(RuntimeWarning, match='did not have a position'): raw = read_raw_eeglab(input_fname=one_chanpos_fname, preload=True) # position should be present for first two channels for i in range(2): assert_array_equal( raw.info['chs'][i]['loc'][:3], np.array([-chanlocs[i]['Y'], chanlocs[i]['X'], chanlocs[i]['Z']])) # position of the last channel should be zero assert_array_equal(raw.info['chs'][-1]['loc'][:3], [np.nan] * 3) # test reading channel names from set and positions from montage with pytest.warns(RuntimeWarning, match='did not have a position'): raw = read_raw_eeglab(input_fname=one_chanpos_fname, preload=True, montage=montage) # when montage was passed - channel positions should be taken from there correct_pos = [[-0.56705965, 0.67706631, 0.46906776], [np.nan] * 3, [0., 0.99977915, -0.02101571]] for ch_ind in range(3): assert_array_almost_equal(raw.info['chs'][ch_ind]['loc'][:3], np.array(correct_pos[ch_ind])) # test reading channel names but not positions when there is no X (only Z) # field in the EEG.chanlocs structure nopos_chanlocs = chanlocs[['labels', 'Z']] nopos_fname = op.join(tmpdir, 'test_no_chanpos.set') io.savemat(nopos_fname, { 'EEG': { 'trials': eeg.trials, 'srate': eeg.srate, 'nbchan': 3, 'data': np.random.random((3, 2)), 'epoch': eeg.epoch, 'event': eeg.epoch, 'chanlocs': nopos_chanlocs, 'times': eeg.times[:2], 'pnts': 2 } }, appendmat=False, oned_as='row') # load the file raw = read_raw_eeglab(input_fname=nopos_fname, preload=True) # test that channel names have been loaded but not channel positions for i in range(3): assert_equal(raw.info['chs'][i]['ch_name'], ch_names[i]) assert_array_equal(raw.info['chs'][i]['loc'][:3], np.array([np.nan, np.nan, np.nan]))