# Authors: Alexandre Gramfort # Denis Engemann # Martin Luessi # Eric Larson # Jaakko Leppakangas # # License: Simplified BSD import os.path as op import numpy as np import pytest from mne import read_events, Epochs, pick_types, read_cov from mne.channels import read_layout from mne.io import read_raw_fif from mne.utils import run_tests_if_main, requires_version from mne.viz import plot_drop_log from mne.viz.utils import _fake_click # Set our plotters to test mode import matplotlib matplotlib.use('Agg') # for testing don't use X server base_dir = op.join(op.dirname(__file__), '..', '..', 'io', 'tests', 'data') evoked_fname = op.join(base_dir, 'test-ave.fif') raw_fname = op.join(base_dir, 'test_raw.fif') cov_fname = op.join(base_dir, 'test-cov.fif') event_name = op.join(base_dir, 'test-eve.fif') event_id, tmin, tmax = 1, -0.1, 1.0 n_chan = 20 layout = read_layout('Vectorview-all') def _get_epochs(): """Get epochs.""" raw = read_raw_fif(raw_fname) events = read_events(event_name) picks = pick_types(raw.info, meg=True, eeg=False, stim=False, ecg=False, eog=False, exclude='bads') # Use a subset of channels for plotting speed picks = np.round(np.linspace(0, len(picks) + 1, n_chan)).astype(int) with pytest.warns(RuntimeWarning, match='projection'): epochs = Epochs(raw, events[:5], event_id, tmin, tmax, picks=picks, proj=False) epochs.info.normalize_proj() # avoid warnings return epochs def test_plot_epochs(): """Test epoch plotting.""" import matplotlib.pyplot as plt epochs = _get_epochs() epochs.info['lowpass'] = 10. # allow heavy decim during plotting epochs.plot(scalings=None, title='Epochs') plt.close('all') # covariance / whitening cov = read_cov(cov_fname) assert len(cov['names']) == 366 # all channels assert cov['bads'] == [] assert epochs.info['bads'] == [] # all good with pytest.warns(RuntimeWarning, match='projection'): epochs.plot(noise_cov=cov) plt.close('all') # add a channel to the epochs.info['bads'] epochs.info['bads'] = [epochs.ch_names[0]] with pytest.warns(RuntimeWarning, match='projection'): epochs.plot(noise_cov=cov) plt.close('all') # add a channel to cov['bads'] cov['bads'] = [epochs.ch_names[1]] with pytest.warns(RuntimeWarning, match='projection'): epochs.plot(noise_cov=cov) plt.close('all') # have a data channels missing from the covariance cov['names'] = cov['names'][:306] cov['data'] = cov['data'][:306][:306] with pytest.warns(RuntimeWarning, match='projection'): epochs.plot(noise_cov=cov) plt.close('all') # other options fig = epochs[0].plot(picks=[0, 2, 3], scalings=None) fig.canvas.key_press_event('escape') plt.close('all') fig = epochs.plot() fig.canvas.key_press_event('left') fig.canvas.key_press_event('right') fig.canvas.scroll_event(0.5, 0.5, -0.5) # scroll down fig.canvas.scroll_event(0.5, 0.5, 0.5) # scroll up fig.canvas.key_press_event('up') fig.canvas.key_press_event('down') fig.canvas.key_press_event('pageup') fig.canvas.key_press_event('pagedown') fig.canvas.key_press_event('-') fig.canvas.key_press_event('+') fig.canvas.key_press_event('=') fig.canvas.key_press_event('b') fig.canvas.key_press_event('f11') fig.canvas.key_press_event('home') fig.canvas.key_press_event('?') fig.canvas.key_press_event('h') fig.canvas.key_press_event('o') fig.canvas.key_press_event('end') fig.canvas.resize_event() fig.canvas.close_event() # closing and epoch dropping plt.close('all') pytest.raises(RuntimeError, epochs.plot, picks=[]) plt.close('all') fig = epochs.plot(events=epochs.events) # test mouse clicks x = fig.get_axes()[0].get_xlim()[1] / 2 y = fig.get_axes()[0].get_ylim()[0] / 2 data_ax = fig.get_axes()[0] n_epochs = len(epochs) _fake_click(fig, data_ax, [x, y], xform='data') # mark a bad epoch _fake_click(fig, data_ax, [x, y], xform='data') # unmark a bad epoch _fake_click(fig, data_ax, [0.5, 0.999]) # click elsewhere in 1st axes _fake_click(fig, data_ax, [-0.1, 0.9]) # click on y-label _fake_click(fig, data_ax, [-0.1, 0.9], button=3) _fake_click(fig, fig.get_axes()[2], [0.5, 0.5]) # change epochs _fake_click(fig, fig.get_axes()[3], [0.5, 0.5]) # change channels fig.canvas.close_event() # closing and epoch dropping assert(n_epochs - 1 == len(epochs)) plt.close('all') epochs.plot_sensors() # Test plot_sensors plt.close('all') def test_plot_epochs_image(): """Test plotting of epochs image.""" import matplotlib.pyplot as plt epochs = _get_epochs() epochs.plot_image(picks=[1, 2]) overlay_times = [0.1] epochs.plot_image(picks=[1], order=[0], overlay_times=overlay_times, vmin=0.01, title="test" ) epochs.plot_image(picks=[1], overlay_times=overlay_times, vmin=-0.001, vmax=0.001) pytest.raises(ValueError, epochs.plot_image, picks=[1], overlay_times=[0.1, 0.2]) pytest.raises(ValueError, epochs.plot_image, picks=[1], order=[0, 1]) pytest.raises(ValueError, epochs.plot_image, axes=dict(), group_by=list(), combine='mean') pytest.raises(ValueError, epochs.plot_image, axes=list(), group_by=dict(), combine='mean') pytest.raises(ValueError, epochs.plot_image, group_by='error', picks=[1, 2]) pytest.raises(ValueError, epochs.plot_image, units={"hi": 1}, scalings={"ho": 1}) epochs.load_data().pick_types(meg='mag') epochs.info.normalize_proj() epochs.plot_image(group_by='type', combine='mean') epochs.plot_image(group_by={"1": [1, 2], "2": [1, 2]}, combine='mean') epochs.plot_image(vmin=lambda x: x.min()) pytest.raises(ValueError, epochs.plot_image, axes=1, fig=2) ts_args = dict(show_sensors=False) with pytest.warns(RuntimeWarning, match='fall outside'): epochs.plot_image(overlay_times=[1.1], combine="gfp", ts_args=ts_args) pytest.raises(ValueError, epochs.plot_image, combine='error', ts_args=ts_args) with pytest.raises(NotImplementedError, match='currently'): epochs.plot_image(ts_args=dict(invert_y=True)) plt.close('all') def test_plot_drop_log(): """Test plotting a drop log.""" import matplotlib.pyplot as plt epochs = _get_epochs() pytest.raises(ValueError, epochs.plot_drop_log) epochs.drop_bad() epochs.plot_drop_log() plot_drop_log([['One'], [], []]) plot_drop_log([['One'], ['Two'], []]) plot_drop_log([['One'], ['One', 'Two'], []]) plt.close('all') @requires_version('scipy', '0.12') def test_plot_psd_epochs(): """Test plotting epochs psd (+topomap).""" import matplotlib.pyplot as plt epochs = _get_epochs() epochs.plot_psd() pytest.raises(RuntimeError, epochs.plot_psd_topomap, bands=[(0, 0.01, 'foo')]) # no freqs in range epochs.plot_psd_topomap() plt.close('all') run_tests_if_main()